From b683eb9e5e75938e5cc30859c3aed4af2fc697ab Mon Sep 17 00:00:00 2001
From: jajupmochi <jajupmochi@gmail.com>
Date: Mon, 5 Mar 2018 18:14:18 +0100
Subject: [PATCH] remove unnecessary files.

---
 .gitignore                                         |     4 +
 ...weisfeilerLehmankernel_acyclic-checkpoint.ipynb |  2015 ---
 .../plot_all_graphs-checkpoint.ipynb               |  3388 ----
 .../py-graph_test-checkpoint.ipynb                 |   170 -
 .../run_cyclicpatternkernel-checkpoint.ipynb       |  2305 ---
 ...run_marginalizedkernel_acyclic-checkpoint.ipynb |  1075 --
 .../run_pathkernel_acyclic-checkpoint.ipynb        |   665 -
 .../run_spkernel_acyclic-checkpoint.ipynb          |   559 -
 .../run_treeletkernel_acyclic-checkpoint.ipynb     |   641 -
 .../run_treepatternkernel-checkpoint.ipynb         |  3191 ----
 .../run_untildpathkernel_acyclic-checkpoint.ipynb  |  3183 ----
 .../run_untilnwalkkernel-checkpoint.ipynb          | 12297 -------------
 ...weisfeilerLehmankernel_acyclic-checkpoint.ipynb |  1755 --
 .../.ipynb_checkpoints/test_lib-checkpoint.ipynb   |   175 -
 .../test_modelselection-checkpoint.ipynb           |  2236 ---
 .../test_scikit_ksvm-checkpoint.ipynb              |  1271 --
 .../test_spkernel-checkpoint.ipynb                 |  1136 --
 notebooks/run_treeletkernel_acyclic.ipynb          |    92 +-
 notebooks/run_treepatternkernel.ipynb              | 17881 ++++++++++++++++++-
 notebooks/run_untilnwalkkernel.ipynb               |   661 +-
 notebooks/run_weisfeilerLehmankernel_acyclic.ipynb |   997 +-
 pygraph/__pycache__/__init__.cpython-35.pyc        |   Bin 639 -> 0 bytes
 .../__pycache__/cyclicPatternKernel.cpython-35.pyc |   Bin 6110 -> 0 bytes
 .../kernels/__pycache__/deltaKernel.cpython-35.pyc |   Bin 698 -> 0 bytes
 .../__pycache__/marginalizedKernel.cpython-35.pyc  |   Bin 3840 -> 0 bytes
 .../kernels/__pycache__/pathKernel.cpython-35.pyc  |   Bin 4233 -> 0 bytes
 .../kernels/__pycache__/spKernel.cpython-35.pyc    |   Bin 2062 -> 0 bytes
 .../kernels/__pycache__/spkernel.cpython-35.pyc    |   Bin 2276 -> 0 bytes
 .../__pycache__/treePatternKernel.cpython-35.pyc   |   Bin 7726 -> 0 bytes
 .../__pycache__/treeletKernel.cpython-35.pyc       |   Bin 13681 -> 0 bytes
 .../__pycache__/untildPathKernel.cpython-35.pyc    |   Bin 7704 -> 0 bytes
 .../__pycache__/untilnWalkKernel.cpython-35.pyc    |   Bin 6690 -> 0 bytes
 .../weisfeilerLehmanKernel.cpython-35.pyc          |   Bin 11817 -> 0 bytes
 pygraph/utils/__pycache__/__init__.cpython-35.pyc  |   Bin 387 -> 0 bytes
 .../utils/__pycache__/graphfiles.cpython-35.pyc    |   Bin 6590 -> 0 bytes
 .../model_selection_precomputed.cpython-35.pyc     |   Bin 8899 -> 0 bytes
 pygraph/utils/__pycache__/utils.cpython-35.pyc     |   Bin 2591 -> 0 bytes
 pygraph/utils/model_selection_precomputed.py       |   153 +-
 38 files changed, 18581 insertions(+), 37269 deletions(-)
 create mode 100644 .gitignore
 delete mode 100644 .ipynb_checkpoints/run_weisfeilerLehmankernel_acyclic-checkpoint.ipynb
 delete mode 100644 notebooks/.ipynb_checkpoints/plot_all_graphs-checkpoint.ipynb
 delete mode 100644 notebooks/.ipynb_checkpoints/py-graph_test-checkpoint.ipynb
 delete mode 100644 notebooks/.ipynb_checkpoints/run_cyclicpatternkernel-checkpoint.ipynb
 delete mode 100644 notebooks/.ipynb_checkpoints/run_marginalizedkernel_acyclic-checkpoint.ipynb
 delete mode 100644 notebooks/.ipynb_checkpoints/run_pathkernel_acyclic-checkpoint.ipynb
 delete mode 100644 notebooks/.ipynb_checkpoints/run_spkernel_acyclic-checkpoint.ipynb
 delete mode 100644 notebooks/.ipynb_checkpoints/run_treeletkernel_acyclic-checkpoint.ipynb
 delete mode 100644 notebooks/.ipynb_checkpoints/run_treepatternkernel-checkpoint.ipynb
 delete mode 100644 notebooks/.ipynb_checkpoints/run_untildpathkernel_acyclic-checkpoint.ipynb
 delete mode 100644 notebooks/.ipynb_checkpoints/run_untilnwalkkernel-checkpoint.ipynb
 delete mode 100644 notebooks/.ipynb_checkpoints/run_weisfeilerLehmankernel_acyclic-checkpoint.ipynb
 delete mode 100644 notebooks/.ipynb_checkpoints/test_lib-checkpoint.ipynb
 delete mode 100644 notebooks/.ipynb_checkpoints/test_modelselection-checkpoint.ipynb
 delete mode 100644 notebooks/.ipynb_checkpoints/test_scikit_ksvm-checkpoint.ipynb
 delete mode 100644 notebooks/.ipynb_checkpoints/test_spkernel-checkpoint.ipynb
 delete mode 100644 pygraph/__pycache__/__init__.cpython-35.pyc
 delete mode 100644 pygraph/kernels/__pycache__/cyclicPatternKernel.cpython-35.pyc
 delete mode 100644 pygraph/kernels/__pycache__/deltaKernel.cpython-35.pyc
 delete mode 100644 pygraph/kernels/__pycache__/marginalizedKernel.cpython-35.pyc
 delete mode 100644 pygraph/kernels/__pycache__/pathKernel.cpython-35.pyc
 delete mode 100644 pygraph/kernels/__pycache__/spKernel.cpython-35.pyc
 delete mode 100644 pygraph/kernels/__pycache__/spkernel.cpython-35.pyc
 delete mode 100644 pygraph/kernels/__pycache__/treePatternKernel.cpython-35.pyc
 delete mode 100644 pygraph/kernels/__pycache__/treeletKernel.cpython-35.pyc
 delete mode 100644 pygraph/kernels/__pycache__/untildPathKernel.cpython-35.pyc
 delete mode 100644 pygraph/kernels/__pycache__/untilnWalkKernel.cpython-35.pyc
 delete mode 100644 pygraph/kernels/__pycache__/weisfeilerLehmanKernel.cpython-35.pyc
 delete mode 100644 pygraph/utils/__pycache__/__init__.cpython-35.pyc
 delete mode 100644 pygraph/utils/__pycache__/graphfiles.cpython-35.pyc
 delete mode 100644 pygraph/utils/__pycache__/model_selection_precomputed.cpython-35.pyc
 delete mode 100644 pygraph/utils/__pycache__/utils.cpython-35.pyc

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..a5e6935
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,4 @@
+# Jupyter Notebook
+.ipynb_checkpoints
+
+__pycache__
diff --git a/.ipynb_checkpoints/run_weisfeilerLehmankernel_acyclic-checkpoint.ipynb b/.ipynb_checkpoints/run_weisfeilerLehmankernel_acyclic-checkpoint.ipynb
deleted file mode 100644
index 6371cc3..0000000
--- a/.ipynb_checkpoints/run_weisfeilerLehmankernel_acyclic-checkpoint.ipynb
+++ /dev/null
@@ -1,2015 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 0.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 0.38979601860046387 seconds ---\n",
-      "[[   5.    6.    4. ...,   20.   20.   20.]\n",
-      " [   6.    8.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.    5. ...,   21.   21.   21.]\n",
-      " ..., \n",
-      " [  20.   20.   21. ...,  101.  101.  101.]\n",
-      " [  20.   20.   21. ...,  101.  101.  101.]\n",
-      " [  20.   20.   21. ...,  101.  101.  101.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 17.681582\n",
-      "With standard deviation: 0.713183\n",
-      "\n",
-      " Mean performance on test set: 15.685879\n",
-      "With standard deviation: 4.139197\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 1.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 0.8205692768096924 seconds ---\n",
-      "[[  10.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   16.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   10. ...,   22.   22.   24.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  130.  130.  122.]\n",
-      " [  20.   20.   22. ...,  130.  130.  122.]\n",
-      " [  20.   20.   24. ...,  122.  122.  154.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 6.270014\n",
-      "With standard deviation: 0.654734\n",
-      "\n",
-      " Mean performance on test set: 7.550458\n",
-      "With standard deviation: 2.331786\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 2.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 1.375309705734253 seconds ---\n",
-      "[[  15.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   24.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   15. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  159.  151.  124.]\n",
-      " [  20.   20.   22. ...,  151.  153.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  185.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 4.450682\n",
-      "With standard deviation: 0.882129\n",
-      "\n",
-      " Mean performance on test set: 9.728466\n",
-      "With standard deviation: 2.057669\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 3.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 1.8636789321899414 seconds ---\n",
-      "[[  20.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   32.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   20. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  188.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  168.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  202.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 2.270586\n",
-      "With standard deviation: 0.481516\n",
-      "\n",
-      " Mean performance on test set: 11.296110\n",
-      "With standard deviation: 2.799944\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 4.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 2.5077457427978516 seconds ---\n",
-      "[[  25.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   40.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   25. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  217.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  183.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  213.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 1.074035\n",
-      "With standard deviation: 0.637823\n",
-      "\n",
-      " Mean performance on test set: 12.808303\n",
-      "With standard deviation: 3.446939\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 5.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 2.8235607147216797 seconds ---\n",
-      "[[  30.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   48.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   30. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  246.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  198.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  224.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 0.700602\n",
-      "With standard deviation: 0.572640\n",
-      "\n",
-      " Mean performance on test set: 14.017923\n",
-      "With standard deviation: 3.675042\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 6.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 3.458494186401367 seconds ---\n",
-      "[[  35.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   56.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   35. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  275.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  213.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  235.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 0.691515\n",
-      "With standard deviation: 0.564620\n",
-      "\n",
-      " Mean performance on test set: 14.918434\n",
-      "With standard deviation: 3.805352\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 7.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 3.861224889755249 seconds ---\n",
-      "[[  40.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   64.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   40. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  304.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  228.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  246.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 0.691516\n",
-      "With standard deviation: 0.564620\n",
-      "\n",
-      " Mean performance on test set: 15.629476\n",
-      "With standard deviation: 3.865387\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 8.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 4.295838117599487 seconds ---\n",
-      "[[  45.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   72.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   45. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  333.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  243.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  257.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 0.691515\n",
-      "With standard deviation: 0.564620\n",
-      "\n",
-      " Mean performance on test set: 16.214369\n",
-      "With standard deviation: 3.928756\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 9.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 5.008287668228149 seconds ---\n",
-      "[[  50.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   80.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   50. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  362.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  258.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  268.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 0.691515\n",
-      "With standard deviation: 0.564620\n",
-      "\n",
-      " Mean performance on test set: 16.725744\n",
-      "With standard deviation: 3.993095\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 10.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 5.347799301147461 seconds ---\n",
-      "[[  55.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   88.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   55. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  391.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  273.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  279.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 0.691516\n",
-      "With standard deviation: 0.564621\n",
-      "\n",
-      " Mean performance on test set: 17.186401\n",
-      "With standard deviation: 4.056724\n",
-      "\n",
-      "\n",
-      "  height    RMSE_test    std_test    RMSE_train    std_train    k_time\n",
-      "--------  -----------  ----------  ------------  -----------  --------\n",
-      "       0     15.6859      4.1392      17.6816       0.713183  0.389796\n",
-      "       1      7.55046     2.33179      6.27001      0.654734  0.820569\n",
-      "       2      9.72847     2.05767      4.45068      0.882129  1.37531\n",
-      "       3     11.2961      2.79994      2.27059      0.481516  1.86368\n",
-      "       4     12.8083      3.44694      1.07403      0.637823  2.50775\n",
-      "       5     14.0179      3.67504      0.700602     0.57264   2.82356\n",
-      "       6     14.9184      3.80535      0.691515     0.56462   3.45849\n",
-      "       7     15.6295      3.86539      0.691516     0.56462   3.86122\n",
-      "       8     16.2144      3.92876      0.691515     0.56462   4.29584\n",
-      "       9     16.7257      3.9931       0.691515     0.56462   5.00829\n",
-      "      10     17.1864      4.05672      0.691516     0.564621  5.3478\n"
-     ]
-    }
-   ],
-   "source": [
-    "# wl subtree kernel\n",
-    "%load_ext line_profiler\n",
-    "\n",
-    "import numpy as np\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.weisfeilerLehmanKernel import weisfeilerlehmankernel, _wl_subtreekernel_do\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_weisfeilerlehman_subtree_acyclic/'\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type')\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
-    "    hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)\n",
-    "\n",
-    "# %lprun -f _wl_subtreekernel_do \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
-    "#     hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "ImportError",
-     "evalue": "cannot import name 'NUMPY_MKL'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mImportError\u001b[0m                               Traceback (most recent call last)",
-      "\u001b[1;32m<ipython-input-1-e7b9d5ef03e3>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0msys\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      6\u001b[0m \u001b[0msys\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minsert\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"../\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mpygraph\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mutils\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mutils\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mkernel_train_test\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      8\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mpygraph\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkernels\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mweisfeilerLehmanKernel\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mweisfeilerlehmankernel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_wl_subtreekernel_do\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mE:\\课程及课件\\Doctorant\\py-graph\\pygraph\\utils\\utils.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m    183\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    184\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mrandom\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 185\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0msklearn\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkernel_ridge\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mKernelRidge\u001b[0m \u001b[1;31m# 0.17\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    186\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0msklearn\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmetrics\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0maccuracy_score\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmean_squared_error\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    187\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0msklearn\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0msvm\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32md:\\python\\python36\\lib\\site-packages\\sklearn\\__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m    132\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    133\u001b[0m     \u001b[1;32mfrom\u001b[0m \u001b[1;33m.\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0m__check_build\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 134\u001b[1;33m     \u001b[1;32mfrom\u001b[0m \u001b[1;33m.\u001b[0m\u001b[0mbase\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mclone\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    135\u001b[0m     \u001b[0m__check_build\u001b[0m  \u001b[1;31m# avoid flakes unused variable error\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    136\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32md:\\python\\python36\\lib\\site-packages\\sklearn\\base.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     10\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 11\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mscipy\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0msparse\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     12\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[1;33m.\u001b[0m\u001b[0mexternals\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0msix\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     13\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[1;33m.\u001b[0m\u001b[0mutils\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfixes\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0msignature\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32md:\\python\\python36\\lib\\site-packages\\scipy\\__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     59\u001b[0m \u001b[0m__all__\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;34m'test'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     60\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 61\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_distributor_init\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mNUMPY_MKL\u001b[0m  \u001b[1;31m# requires numpy+mkl\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     62\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     63\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mshow_config\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mshow_numpy_config\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mImportError\u001b[0m: cannot import name 'NUMPY_MKL'"
-     ]
-    }
-   ],
-   "source": [
-    "# WL sp kernel\n",
-    "%load_ext line_profiler\n",
-    "\n",
-    "import numpy as np\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.weisfeilerLehmanKernel import weisfeilerlehmankernel, _wl_subtreekernel_do\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_weisfeilerlehman_subtree_acyclic/'\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', base_kernel = 'sp')\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
-    "    hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)\n",
-    "\n",
-    "# %lprun -f _wl_subtreekernel_do \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
-    "#     hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# results\n",
-    "\n",
-    "# with y normalization\n",
-    "  height    RMSE_test    std_test    RMSE_train    std_train    k_time\n",
-    "--------  -----------  ----------  ------------  -----------  --------\n",
-    "       0     36.2108      7.33179      38.6059      1.57064   0.379475\n",
-    "       1      9.00098     6.37145       6.76379     1.96568   0.844898\n",
-    "       2     19.8113      4.04911       5.28757     1.81899   1.35308\n",
-    "       3     25.0455      4.94276       2.3274      0.805733  1.81136\n",
-    "       4     28.2255      6.5212        0.85156     0.423465  2.23098\n",
-    "       5     30.6354      6.73647       3.35947     8.17561   2.71575\n",
-    "       6     32.1027      6.85601       3.54105     8.71922   3.11459\n",
-    "       7     32.9709      6.89606       6.94372     9.94045   3.55571\n",
-    "       8     33.5112      6.90753       6.97339     9.76975   3.79657\n",
-    "       9     33.8502      6.91427      11.8345     11.6213    4.41555\n",
-    "      10     34.0963      6.93115      11.4257     11.2624    4.94888\n",
-    "\n",
-    "# without y normalization\n",
-    "  height    RMSE_test    std_test    RMSE_train    std_train    k_time\n",
-    "--------  -----------  ----------  ------------  -----------  --------\n",
-    "       0     15.6859      4.1392      17.6816       0.713183  0.360443\n",
-    "       1      7.55046     2.33179      6.27001      0.654734  0.837389\n",
-    "       2      9.72847     2.05767      4.45068      0.882129  1.25317\n",
-    "       3     11.2961      2.79994      2.27059      0.481516  1.79971\n",
-    "       4     12.8083      3.44694      1.07403      0.637823  2.35346\n",
-    "       5     14.0179      3.67504      0.700602     0.57264   2.78285\n",
-    "       6     14.9184      3.80535      0.691515     0.56462   3.20764\n",
-    "       7     15.6295      3.86539      0.691516     0.56462   3.71648\n",
-    "       8     16.2144      3.92876      0.691515     0.56462   3.99213\n",
-    "       9     16.7257      3.9931       0.691515     0.56462   4.26315\n",
-    "      10     17.1864      4.05672      0.691516     0.564621  5.00918"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "- This script take as input a kernel matrix\n",
-      "and returns the classification or regression performance\n",
-      "- The kernel matrix can be calculated using any of the graph kernels approaches\n",
-      "- The criteria used for prediction are SVM for classification and kernel Ridge regression for regression\n",
-      "- For predition we divide the data in training, validation and test. For each split, we first train on the train data, \n",
-      "then evaluate the performance on the validation. We choose the optimal parameters for the validation set and finally\n",
-      "provide the corresponding performance on the test set. If more than one split is performed, the final results \n",
-      "correspond to the average of the performances on the test sets. \n",
-      "\n",
-      "@references\n",
-      "    Elisabetta Ghisu, https://github.com/eghisu/GraphKernels/blob/master/GraphKernelsCollection/python_scripts/compute_perf_gk.py\n",
-      "\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when subtree height = 0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 0.3920705318450928 seconds ---\n",
-      "[[   5.    6.    4. ...,   20.   20.   20.]\n",
-      " [   6.    8.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.    5. ...,   21.   21.   21.]\n",
-      " ..., \n",
-      " [  20.   20.   21. ...,  101.  101.  101.]\n",
-      " [  20.   20.   21. ...,  101.  101.  101.]\n",
-      " [  20.   20.   21. ...,  101.  101.  101.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 17.681582\n",
-      "With standard deviation: 0.713183\n",
-      "\n",
-      " Mean performance on test set: 15.685879\n",
-      "With standard deviation: 4.139197\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when subtree height = 1 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 0.8578901290893555 seconds ---\n",
-      "[[  10.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   16.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   10. ...,   22.   22.   24.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  130.  130.  122.]\n",
-      " [  20.   20.   22. ...,  130.  130.  122.]\n",
-      " [  20.   20.   24. ...,  122.  122.  154.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 6.270014\n",
-      "With standard deviation: 0.654734\n",
-      "\n",
-      " Mean performance on test set: 7.550458\n",
-      "With standard deviation: 2.331786\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when subtree height = 2 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 1.264050006866455 seconds ---\n",
-      "[[  15.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   24.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   15. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  159.  151.  124.]\n",
-      " [  20.   20.   22. ...,  151.  153.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  185.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 4.450682\n",
-      "With standard deviation: 0.882129\n",
-      "\n",
-      " Mean performance on test set: 9.728466\n",
-      "With standard deviation: 2.057669\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when subtree height = 3 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 1.731236219406128 seconds ---\n",
-      "[[  20.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   32.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   20. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  188.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  168.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  202.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 2.270586\n",
-      "With standard deviation: 0.481516\n",
-      "\n",
-      " Mean performance on test set: 11.296110\n",
-      "With standard deviation: 2.799944\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when subtree height = 4 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 2.1112847328186035 seconds ---\n",
-      "[[  25.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   40.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   25. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  217.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  183.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  213.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 1.074035\n",
-      "With standard deviation: 0.637823\n",
-      "\n",
-      " Mean performance on test set: 12.808303\n",
-      "With standard deviation: 3.446939\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when subtree height = 5 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 2.4751319885253906 seconds ---\n",
-      "[[  30.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   48.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   30. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  246.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  198.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  224.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 0.700602\n",
-      "With standard deviation: 0.572640\n",
-      "\n",
-      " Mean performance on test set: 14.017923\n",
-      "With standard deviation: 3.675042\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when subtree height = 6 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 2.8712213039398193 seconds ---\n",
-      "[[  35.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   56.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   35. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  275.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  213.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  235.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 0.691515\n",
-      "With standard deviation: 0.564620\n",
-      "\n",
-      " Mean performance on test set: 14.918434\n",
-      "With standard deviation: 3.805352\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when subtree height = 7 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 3.554422378540039 seconds ---\n",
-      "[[  40.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   64.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   40. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  304.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  228.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  246.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 0.691516\n",
-      "With standard deviation: 0.564620\n",
-      "\n",
-      " Mean performance on test set: 15.629476\n",
-      "With standard deviation: 3.865387\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when subtree height = 8 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 3.8757314682006836 seconds ---\n",
-      "[[  45.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   72.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   45. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  333.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  243.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  257.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 0.691515\n",
-      "With standard deviation: 0.564620\n",
-      "\n",
-      " Mean performance on test set: 16.214369\n",
-      "With standard deviation: 3.928756\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when subtree height = 9 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 4.205373764038086 seconds ---\n",
-      "[[  50.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   80.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   50. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  362.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  258.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  268.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 0.691515\n",
-      "With standard deviation: 0.564620\n",
-      "\n",
-      " Mean performance on test set: 16.725744\n",
-      "With standard deviation: 3.993095\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when subtree height = 10 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 4.737298250198364 seconds ---\n",
-      "[[  55.   10.    4. ...,   20.   20.   20.]\n",
-      " [  10.   88.    4. ...,   20.   20.   20.]\n",
-      " [   4.    4.   55. ...,   22.   22.   26.]\n",
-      " ..., \n",
-      " [  20.   20.   22. ...,  391.  159.  124.]\n",
-      " [  20.   20.   22. ...,  159.  273.  124.]\n",
-      " [  20.   20.   26. ...,  124.  124.  279.]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 0.691516\n",
-      "With standard deviation: 0.564621\n",
-      "\n",
-      " Mean performance on test set: 17.186401\n",
-      "With standard deviation: 4.056724\n",
-      "\n",
-      "\n",
-      "  height    RMSE_test    std_test    RMSE_train    std_train    k_time\n",
-      "--------  -----------  ----------  ------------  -----------  --------\n",
-      "       0     15.6859      4.1392      17.6816       0.713183  0.392071\n",
-      "       1      7.55046     2.33179      6.27001      0.654734  0.85789\n",
-      "       2      9.72847     2.05767      4.45068      0.882129  1.26405\n",
-      "       3     11.2961      2.79994      2.27059      0.481516  1.73124\n",
-      "       4     12.8083      3.44694      1.07403      0.637823  2.11128\n",
-      "       5     14.0179      3.67504      0.700602     0.57264   2.47513\n",
-      "       6     14.9184      3.80535      0.691515     0.56462   2.87122\n",
-      "       7     15.6295      3.86539      0.691516     0.56462   3.55442\n",
-      "       8     16.2144      3.92876      0.691515     0.56462   3.87573\n",
-      "       9     16.7257      3.9931       0.691515     0.56462   4.20537\n",
-      "      10     17.1864      4.05672      0.691516     0.564621  4.7373\n"
-     ]
-    }
-   ],
-   "source": [
-    "# test of WL subtree kernel\n",
-    "\n",
-    "\"\"\"\n",
-    "- This script take as input a kernel matrix\n",
-    "and returns the classification or regression performance\n",
-    "- The kernel matrix can be calculated using any of the graph kernels approaches\n",
-    "- The criteria used for prediction are SVM for classification and kernel Ridge regression for regression\n",
-    "- For predition we divide the data in training, validation and test. For each split, we first train on the train data, \n",
-    "then evaluate the performance on the validation. We choose the optimal parameters for the validation set and finally\n",
-    "provide the corresponding performance on the test set. If more than one split is performed, the final results \n",
-    "correspond to the average of the performances on the test sets. \n",
-    "\n",
-    "@references\n",
-    "    Elisabetta Ghisu, https://github.com/eghisu/GraphKernels/blob/master/GraphKernelsCollection/python_scripts/compute_perf_gk.py\n",
-    "\"\"\"\n",
-    "\n",
-    "print(__doc__)\n",
-    "\n",
-    "import sys\n",
-    "import os\n",
-    "import pathlib\n",
-    "from collections import OrderedDict\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from tabulate import tabulate\n",
-    "\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "from pygraph.kernels.weisfeilerLehmanKernel import weisfeilerlehmankernel\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "from pygraph.utils.utils import split_train_test\n",
-    "\n",
-    "train_means_list = []\n",
-    "train_stds_list = []\n",
-    "test_means_list = []\n",
-    "test_stds_list = []\n",
-    "kernel_time_list = []\n",
-    "\n",
-    "for height in np.linspace(0, 10, 11):\n",
-    "    print('\\n\\n #--- calculating kernel matrix when subtree height = %d ---#' % height)\n",
-    "\n",
-    "    print('\\n Loading dataset from file...')\n",
-    "    dataset, y = loadDataset(\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "    y = np.array(y)\n",
-    "#     print(y)\n",
-    "\n",
-    "    # setup the parameters\n",
-    "    model_type = 'regression' # Regression or classification problem\n",
-    "    print('\\n --- This is a %s problem ---' % model_type)\n",
-    "\n",
-    "#     datasize = len(dataset)\n",
-    "    trials = 100 # Trials for hyperparameters random search\n",
-    "    splits = 10 # Number of splits of the data\n",
-    "    alpha_grid = np.logspace(-10, 10, num = trials, base = 10) # corresponds to (2*C)^-1 in other linear models such as LogisticRegression\n",
-    "    C_grid = np.logspace(-10, 10, num = trials, base = 10)\n",
-    "\n",
-    "\n",
-    "    # set the output path\n",
-    "    kernel_file_path = 'kernelmatrices_weisfeilerlehman_subtree_acyclic/'\n",
-    "    if not os.path.exists(kernel_file_path):\n",
-    "        os.makedirs(kernel_file_path)\n",
-    "\n",
-    "    \"\"\"\n",
-    "    -  Here starts the main program\n",
-    "    -  First we permute the data, then for each split we evaluate corresponding performances\n",
-    "    -  In the end, the performances are averaged over the test sets\n",
-    "    \"\"\"\n",
-    "\n",
-    "    # save kernel matrices to files / read kernel matrices from files\n",
-    "    kernel_file = kernel_file_path + 'km.ds'\n",
-    "    path = pathlib.Path(kernel_file)\n",
-    "    # get train set kernel matrix\n",
-    "    if path.is_file():\n",
-    "        print('\\n Loading the kernel matrix from file...')\n",
-    "        Kmatrix = np.loadtxt(kernel_file)# results\n",
-    "        print(Kmatrix)\n",
-    "    else:\n",
-    "        print('\\n Calculating kernel matrix, this could take a while...')\n",
-    "        Kmatrix, run_time = weisfeilerlehmankernel(dataset, node_label = 'atom', height = int(height))\n",
-    "        kernel_time_list.append(run_time)\n",
-    "        print(Kmatrix)\n",
-    "        print('\\n Saving kernel matrix to file...')\n",
-    "    #     np.savetxt(kernel_file, Kmatrix)\n",
-    "\n",
-    "    train_mean, train_std, test_mean, test_std = \\\n",
-    "        split_train_test(Kmatrix, y, alpha_grid, C_grid, splits, trials, model_type, normalize = False)\n",
-    " \n",
-    "    train_means_list.append(train_mean)\n",
-    "    train_stds_list.append(train_std)\n",
-    "    test_means_list.append(test_mean)\n",
-    "    test_stds_list.append(test_std)\n",
-    "    \n",
-    "print('\\n') \n",
-    "table_dict = {'height': np.linspace(0, 10, 11), 'RMSE_test': test_means_list, 'std_test': test_stds_list, \\\n",
-    "    'RMSE_train': train_means_list, 'std_train': train_stds_list, 'k_time': kernel_time_list}\n",
-    "keyorder = ['height', 'RMSE_test', 'std_test', 'RMSE_train', 'std_train', 'k_time']\n",
-    "print(tabulate(OrderedDict(sorted(table_dict.items(), key = lambda i:keyorder.index(i[0]))), headers='keys'))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'O', 'C'}\n",
-      "{'O', 'C'}\n",
-      "--- shortest path kernel built in 0.0002582073211669922 seconds ---\n",
-      "3\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f773eab40b8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[(0, {'label': 'C'}), (1, {'label': 'C'}), (2, {'label': 'C'}), (3, {'label': 'C'}), (4, {'label': 'O'})]\n",
-      " -> \n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f773ca1cc88>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[(0, {'label': 'CC'}), (1, {'label': 'CC'}), (2, {'label': 'CO'}), (3, {'label': 'CCCO'}), (4, {'label': 'OCC'})]\n",
-      " -> \n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f773c9a44e0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[(0, {'label': '0'}), (1, {'label': '0'}), (2, {'label': '3'}), (3, {'label': '1'}), (4, {'label': '2'})]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f773c9957b8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[(0, {'label': 'C'}), (1, {'label': 'C'}), (2, {'label': 'C'}), (3, {'label': 'C'}), (4, {'label': 'C'}), (5, {'label': 'C'}), (6, {'label': 'O'})]\n",
-      " -> \n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f7788e0e390>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[(0, {'label': 'CC'}), (1, {'label': 'CC'}), (2, {'label': 'CC'}), (3, {'label': 'CO'}), (4, {'label': 'CCCC'}), (5, {'label': 'CCCO'}), (6, {'label': 'OCC'})]\n",
-      " -> \n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f773c95a5f8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[(0, {'label': '0'}), (1, {'label': '0'}), (2, {'label': '0'}), (3, {'label': '3'}), (4, {'label': '4'}), (5, {'label': '1'}), (6, {'label': '2'})]\n",
-      "--- shortest path kernel built in 0.00026607513427734375 seconds ---\n",
-      "6\n"
-     ]
-    }
-   ],
-   "source": [
-    "import sys\n",
-    "import networkx as nx\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "from pygraph.kernels.spkernel import spkernel\n",
-    "\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "\n",
-    "def weisfeilerlehman_test(G):\n",
-    "    '''\n",
-    "    Weisfeiler-Lehman test of graph isomorphism.\n",
-    "    '''\n",
-    "\n",
-    "    nx.draw_networkx(G)\n",
-    "    plt.show()\n",
-    "    nx.draw_networkx_labels(G, nx.spring_layout(G), labels = nx.get_node_attributes(G,'label'))\n",
-    "    print(G.nodes(data = True))\n",
-    "    \n",
-    "    set_multisets = []\n",
-    "    for node in G.nodes(data = True):\n",
-    "        # Multiset-label determination.\n",
-    "        multiset = [ G.node[neighbors]['label'] for neighbors in G[node[0]] ]\n",
-    "        # sorting each multiset\n",
-    "        multiset.sort()\n",
-    "        multiset = node[1]['label'] + ''.join(multiset) # concatenate to a string and add the prefix \n",
-    "        set_multisets.append(multiset)\n",
-    "        \n",
-    "    # label compression\n",
-    "#     set_multisets.sort() # this is unnecessary\n",
-    "    set_unique = list(set(set_multisets)) # set of unique multiset labels\n",
-    "    set_compressed = { value : str(set_unique.index(value)) for value in set_unique } # assign indices as the new labels\n",
-    "#     print(set_compressed)\n",
-    "#     print(set_multisets)\n",
-    "    \n",
-    "    # relabel nodes with multisets\n",
-    "    for node in G.nodes(data = True):\n",
-    "        node[1]['label'] = set_multisets[node[0]]\n",
-    "    print(' -> ')\n",
-    "    nx.draw_networkx(G)\n",
-    "    plt.show()\n",
-    "    print(G.nodes(data = True))\n",
-    "\n",
-    "    \n",
-    "    # relabel nodes\n",
-    "    for node in G.nodes(data = True):\n",
-    "        node[1]['label'] = set_compressed[set_multisets[node[0]]]\n",
-    "        \n",
-    "    print(' -> ')\n",
-    "    nx.draw_networkx(G)\n",
-    "    plt.show()\n",
-    "    print(G.nodes(data = True))\n",
-    "\n",
-    "dataset, y = loadDataset(\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "G1 = dataset[12]\n",
-    "G2 = dataset[55]\n",
-    "\n",
-    "# init.\n",
-    "kernel = 0 # init kernel\n",
-    "num_nodes1 = G1.number_of_nodes()\n",
-    "num_nodes2 = G2.number_of_nodes()\n",
-    "\n",
-    "# the first iteration.\n",
-    "labelset1 = { G1.nodes(data = True)[i]['label'] for i in range(num_nodes1) }\n",
-    "labelset2 = { G2.nodes(data = True)[i]['label'] for i in range(num_nodes2) }\n",
-    "print(labelset1)\n",
-    "print(labelset2)\n",
-    "kernel += spkernel(G1, G2)\n",
-    "print(kernel)\n",
-    "\n",
-    "\n",
-    "\n",
-    "for height in range(0, min(num_nodes1, num_nodes2)): #Q how to determine the upper bound of the height?\n",
-    "    if labelset1 != labelset2:\n",
-    "        break\n",
-    "        \n",
-    "    # Weisfeiler-Lehman test of graph isomorphism.\n",
-    "    weisfeilerlehman_test(G1)\n",
-    "    weisfeilerlehman_test(G2)\n",
-    "    \n",
-    "    # calculate kernel\n",
-    "    kernel += spkernel(G1, G2)\n",
-    "    \n",
-    "    # get label sets of both graphs\n",
-    "    labelset1 = { G1.nodes(data = True)[i]['label'] for i in range(num_nodes1) }\n",
-    "    labelset2 = { G2.nodes(data = True)[i]['label'] for i in range(num_nodes2) }\n",
-    "#     print(labelset1)\n",
-    "#     print(labelset2)\n",
-    "\n",
-    "print(kernel)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O', 6: 'O'}\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S', 7: 'S'}\n",
-      "\n",
-      " --- height = 0 --- \n",
-      "\n",
-      " --- for graph 0 --- \n",
-      "\n",
-      "labels_ori: ['C', 'C', 'C', 'C', 'C', 'O', 'O']\n",
-      "all_labels_ori: {'C', 'O'}\n",
-      "num_of_each_label: {'C': 5, 'O': 2}\n",
-      "all_num_of_each_label: [{'C': 5, 'O': 2}]\n",
-      "num_of_labels: 2\n",
-      "all_labels_ori: {'C', 'O'}\n",
-      "\n",
-      " --- for graph 1 --- \n",
-      "\n",
-      "labels_ori: ['C', 'C', 'C', 'C', 'C', 'C', 'S', 'S']\n",
-      "all_labels_ori: {'C', 'O', 'S'}\n",
-      "num_of_each_label: {'C': 6, 'S': 2}\n",
-      "all_num_of_each_label: [{'C': 5, 'O': 2}, {'C': 6, 'S': 2}]\n",
-      "num_of_labels: 2\n",
-      "all_labels_ori: {'C', 'O', 'S'}\n",
-      "\n",
-      " all_num_of_labels_occured: 3\n",
-      "\n",
-      " --- calculating kernel matrix ---\n",
-      "\n",
-      " labels: {'C', 'O'}\n",
-      "vector1: [[5 2]]\n",
-      "vector2: [[5 2]]\n",
-      "Kmatrix: [[ 29.   0.]\n",
-      " [  0.   0.]]\n",
-      "\n",
-      " labels: {'C', 'O', 'S'}\n",
-      "vector1: [[5 2 0]]\n",
-      "vector2: [[6 0 2]]\n",
-      "Kmatrix: [[ 29.  30.]\n",
-      " [ 30.   0.]]\n",
-      "\n",
-      " labels: {'C', 'S'}\n",
-      "vector1: [[6 2]]\n",
-      "vector2: [[6 2]]\n",
-      "Kmatrix: [[ 29.  30.]\n",
-      " [ 30.  40.]]\n",
-      "\n",
-      " --- height = 1 --- \n",
-      "\n",
-      " --- for graph 0 --- \n",
-      "\n",
-      "multiset: ['CC', 'CC', 'CCO', 'CCO', 'COO', 'OCC', 'OCC']\n",
-      "set_unique: ['OCC', 'COO', 'CCO', 'CC']\n",
-      "set_compressed: {'OCC': '4', 'COO': '5', 'CCO': '6', 'CC': '7'}\n",
-      "all_set_compressed: {'OCC': '4', 'COO': '5', 'CCO': '6', 'CC': '7'}\n",
-      "num_of_labels_occured: 7\n",
-      "\n",
-      " compressed labels: {0: '7', 1: '7', 2: '6', 3: '6', 4: '5', 5: '4', 6: '4'}\n",
-      "labels_comp: ['7', '7', '6', '6', '5', '4', '4']\n",
-      "all_labels_ori: {'5', '4', '6', '7'}\n",
-      "num_of_each_label: {'5': 1, '4': 2, '6': 2, '7': 2}\n",
-      "all_num_of_each_label: [{'5': 1, '4': 2, '6': 2, '7': 2}]\n",
-      "\n",
-      " --- for graph 1 --- \n",
-      "\n",
-      "multiset: ['CC', 'CC', 'CC', 'CCS', 'CCS', 'CCSS', 'SCC', 'SCC']\n",
-      "set_unique: ['SCC', 'CC', 'CCS', 'CCSS']\n",
-      "set_compressed: {'SCC': '8', 'CC': '7', 'CCS': '9', 'CCSS': '10'}\n",
-      "all_set_compressed: {'SCC': '8', 'COO': '5', 'CCS': '9', 'OCC': '4', 'CCO': '6', 'CCSS': '10', 'CC': '7'}\n",
-      "num_of_labels_occured: 10\n",
-      "\n",
-      " compressed labels: {0: '7', 1: '7', 2: '7', 3: '9', 4: '9', 5: '10', 6: '8', 7: '8'}\n",
-      "labels_comp: ['7', '7', '7', '9', '9', '10', '8', '8']\n",
-      "all_labels_ori: {'10', '4', '7', '9', '6', '5', '8'}\n",
-      "num_of_each_label: {'10': 1, '9': 2, '7': 3, '8': 2}\n",
-      "all_num_of_each_label: [{'5': 1, '4': 2, '6': 2, '7': 2}, {'10': 1, '9': 2, '7': 3, '8': 2}]\n",
-      "\n",
-      " all_num_of_labels_occured: 10\n",
-      "\n",
-      " --- calculating kernel matrix ---\n",
-      "\n",
-      " labels: {'5', '4', '6', '7'}\n",
-      "vector1: [[1 2 2 2]]\n",
-      "vector2: [[1 2 2 2]]\n",
-      "\n",
-      " labels: {'10', '4', '7', '9', '6', '5', '8'}\n",
-      "vector1: [[0 2 2 0 2 1 0]]\n",
-      "vector2: [[1 0 3 2 0 0 2]]\n",
-      "\n",
-      " labels: {'8', '10', '7', '9'}\n",
-      "vector1: [[2 1 3 2]]\n",
-      "vector2: [[2 1 3 2]]\n",
-      "\n",
-      " Kmatrix: [[ 42.  36.]\n",
-      " [ 36.  58.]]\n",
-      "\n",
-      " --- height = 2 --- \n",
-      "\n",
-      " --- for graph 0 --- \n",
-      "\n",
-      "multiset: ['76', '76', '647', '647', '544', '456', '456']\n",
-      "set_unique: ['647', '76', '456', '544']\n",
-      "set_compressed: {'647': '11', '76': '12', '544': '14', '456': '13'}\n",
-      "all_set_compressed: {'647': '11', '76': '12', '456': '13', '544': '14'}\n",
-      "num_of_labels_occured: 14\n",
-      "\n",
-      " compressed labels: {0: '12', 1: '12', 2: '11', 3: '11', 4: '14', 5: '13', 6: '13'}\n",
-      "labels_comp: ['12', '12', '11', '11', '14', '13', '13']\n",
-      "all_labels_ori: {'14', '12', '11', '13'}\n",
-      "num_of_each_label: {'14': 1, '13': 2, '12': 2, '11': 2}\n",
-      "all_num_of_each_label: [{'14': 1, '13': 2, '12': 2, '11': 2}]\n",
-      "\n",
-      " --- for graph 1 --- \n",
-      "\n",
-      "multiset: ['79', '79', '710', '978', '978', '10788', '8109', '8109']\n",
-      "set_unique: ['710', '8109', '79', '10788', '978']\n",
-      "set_compressed: {'710': '15', '79': '17', '8109': '16', '978': '19', '10788': '18'}\n",
-      "all_set_compressed: {'710': '15', '79': '17', '978': '19', '10788': '18', '8109': '16', '456': '13', '544': '14', '647': '11', '76': '12'}\n",
-      "num_of_labels_occured: 19\n",
-      "\n",
-      " compressed labels: {0: '17', 1: '17', 2: '15', 3: '19', 4: '19', 5: '18', 6: '16', 7: '16'}\n",
-      "labels_comp: ['17', '17', '15', '19', '19', '18', '16', '16']\n",
-      "all_labels_ori: {'18', '19', '12', '13', '17', '11', '14', '16', '15'}\n",
-      "num_of_each_label: {'15': 1, '17': 2, '19': 2, '16': 2, '18': 1}\n",
-      "all_num_of_each_label: [{'14': 1, '13': 2, '12': 2, '11': 2}, {'15': 1, '17': 2, '19': 2, '16': 2, '18': 1}]\n",
-      "\n",
-      " all_num_of_labels_occured: 19\n",
-      "\n",
-      " --- calculating kernel matrix ---\n",
-      "\n",
-      " labels: {'14', '12', '11', '13'}\n",
-      "vector1: [[1 2 2 2]]\n",
-      "vector2: [[1 2 2 2]]\n",
-      "\n",
-      " labels: {'18', '19', '12', '13', '17', '11', '14', '16', '15'}\n",
-      "vector1: [[0 0 2 2 0 2 1 0 0]]\n",
-      "vector2: [[1 2 0 0 2 0 0 2 1]]\n",
-      "\n",
-      " labels: {'18', '17', '15', '16', '19'}\n",
-      "vector1: [[1 2 1 2 2]]\n",
-      "vector2: [[1 2 1 2 2]]\n",
-      "\n",
-      " Kmatrix: [[ 55.  36.]\n",
-      " [ 36.  72.]]\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel built in 0.0034377574920654297 seconds ---\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "array([[ 55.,  36.],\n",
-       "       [ 36.,  72.]])"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# test of WL subtree kernel on many graphs\n",
-    "\n",
-    "import sys\n",
-    "import pathlib\n",
-    "from collections import Counter\n",
-    "sys.path.insert(0, \"../\")\n",
-    "\n",
-    "import networkx as nx\n",
-    "import numpy as np\n",
-    "import time\n",
-    "\n",
-    "from pygraph.kernels.spkernel import spkernel\n",
-    "from pygraph.kernels.pathKernel import pathkernel\n",
-    "\n",
-    "def weisfeilerlehmankernel(*args, height = 0, base_kernel = 'subtree'):\n",
-    "    \"\"\"Calculate Weisfeiler-Lehman kernels between graphs.\n",
-    "    \n",
-    "    Parameters\n",
-    "    ----------\n",
-    "    Gn : List of NetworkX graph\n",
-    "        List of graphs between which the kernels are calculated.\n",
-    "    /\n",
-    "    G1, G2 : NetworkX graphs\n",
-    "        2 graphs between which the kernel is calculated.\n",
-    "        \n",
-    "    height : subtree height\n",
-    "    \n",
-    "    base_kernel : base kernel used in each iteration of WL kernel\n",
-    "        the default base kernel is subtree kernel\n",
-    "        \n",
-    "    Return\n",
-    "    ------\n",
-    "    Kmatrix/Kernel : Numpy matrix/int\n",
-    "        Kernel matrix, each element of which is the Weisfeiler-Lehman kernel between 2 praphs. / Weisfeiler-Lehman Kernel between 2 graphs.\n",
-    "        \n",
-    "    Notes\n",
-    "    -----\n",
-    "    This function now supports WL subtree kernel and WL shortest path kernel.\n",
-    "    \n",
-    "    References\n",
-    "    ----------\n",
-    "    [1] Shervashidze N, Schweitzer P, Leeuwen EJ, Mehlhorn K, Borgwardt KM. Weisfeiler-lehman graph kernels. Journal of Machine Learning Research. 2011;12(Sep):2539-61.\n",
-    "    \"\"\"\n",
-    "    if len(args) == 1: # for a list of graphs\n",
-    "\n",
-    "#         print(args)\n",
-    "        start_time = time.time()\n",
-    "        \n",
-    "        # for WL subtree kernel\n",
-    "        if base_kernel == 'subtree':           \n",
-    "            Kmatrix = _wl_subtreekernel_do(args[0], height = height, base_kernel = 'subtree')\n",
-    "            \n",
-    "        # for WL edge kernel\n",
-    "        elif base_kernel == 'edge':\n",
-    "            print('edge')\n",
-    "            \n",
-    "        # for WL shortest path kernel\n",
-    "        elif base_kernel == 'sp':\n",
-    "            Gn = args[0]\n",
-    "            Kmatrix = np.zeros((len(Gn), len(Gn)))\n",
-    "            \n",
-    "            for i in range(0, len(Gn)):\n",
-    "                for j in range(i, len(Gn)):\n",
-    "                    Kmatrix[i][j] = _weisfeilerlehmankernel_do(Gn[i], Gn[j])\n",
-    "                    Kmatrix[j][i] = Kmatrix[i][j]\n",
-    "\n",
-    "        print(\"\\n --- Weisfeiler-Lehman %s kernel matrix of size %d built in %s seconds ---\" % (base_kernel, len(args[0]), (time.time() - start_time)))\n",
-    "        \n",
-    "        return Kmatrix\n",
-    "        \n",
-    "    else: # for only 2 graphs\n",
-    "        \n",
-    "        start_time = time.time()\n",
-    "        \n",
-    "        # for WL subtree kernel\n",
-    "        if base_kernel == 'subtree':\n",
-    "            \n",
-    "            args = [args[0], args[1]]\n",
-    "#             print(args)\n",
-    "            kernel = _wl_subtreekernel_do(args, height = height, base_kernel = 'subtree')\n",
-    "            \n",
-    "        # for WL edge kernel\n",
-    "        elif base_kernel == 'edge':\n",
-    "            print('edge')\n",
-    "            \n",
-    "        # for WL shortest path kernel\n",
-    "        elif base_kernel == 'sp':\n",
-    "            \n",
-    "\n",
-    "            kernel = _pathkernel_do(args[0], args[1])\n",
-    "\n",
-    "        print(\"\\n --- Weisfeiler-Lehman %s kernel built in %s seconds ---\" % (base_kernel, time.time() - start_time))\n",
-    "        \n",
-    "        return kernel\n",
-    "    \n",
-    "    \n",
-    "def _weisfeilerlehmankernel_do(G1, G2):\n",
-    "    \"\"\"Calculate Weisfeiler-Lehman kernels between 2 graphs. This kernel use shortest path kernel to calculate kernel between two graphs in each iteration.\n",
-    "    \n",
-    "    Parameters\n",
-    "    ----------\n",
-    "    G1, G2 : NetworkX graphs\n",
-    "        2 graphs between which the kernel is calculated.\n",
-    "        \n",
-    "    Return\n",
-    "    ------\n",
-    "    Kernel : int\n",
-    "        Weisfeiler-Lehman Kernel between 2 graphs.\n",
-    "    \"\"\"\n",
-    "    \n",
-    "    # init.\n",
-    "    kernel = 0 # init kernel\n",
-    "    num_nodes1 = G1.number_of_nodes()\n",
-    "    num_nodes2 = G2.number_of_nodes()\n",
-    "    height = 12 #min(num_nodes1, num_nodes2)) #Q how to determine the upper bound of the height?\n",
-    "    \n",
-    "    # the first iteration.\n",
-    "    labelset1 = { G1.nodes(data = True)[i]['label'] for i in range(num_nodes1) }\n",
-    "    labelset2 = { G2.nodes(data = True)[i]['label'] for i in range(num_nodes2) }\n",
-    "    kernel += pathkernel(G1, G2) # change your base kernel here (and one more below)\n",
-    "    \n",
-    "    for h in range(0, height):\n",
-    "#         if labelset1 != labelset2:\n",
-    "#             break\n",
-    "\n",
-    "        # Weisfeiler-Lehman test of graph isomorphism.\n",
-    "        relabel(G1)\n",
-    "        relabel(G2)\n",
-    "\n",
-    "        # calculate kernel\n",
-    "        kernel += pathkernel(G1, G2) # change your base kernel here (and one more before)\n",
-    "\n",
-    "        # get label sets of both graphs\n",
-    "        labelset1 = { G1.nodes(data = True)[i]['label'] for i in range(num_nodes1) }\n",
-    "        labelset2 = { G2.nodes(data = True)[i]['label'] for i in range(num_nodes2) }\n",
-    "    \n",
-    "    return kernel\n",
-    "\n",
-    "\n",
-    "def relabel(G):\n",
-    "    '''\n",
-    "    Relabel nodes in graph G in one iteration of the 1-dim. WL test of graph isomorphism.\n",
-    "    \n",
-    "    Parameters\n",
-    "    ----------\n",
-    "    G : NetworkX graph\n",
-    "        The graphs whose nodes are relabeled.\n",
-    "    '''\n",
-    "    \n",
-    "    # get the set of original labels\n",
-    "    labels_ori = list(nx.get_node_attributes(G, 'label').values())\n",
-    "    print(labels_ori)\n",
-    "    num_of_each_label = dict(Counter(labels_ori))\n",
-    "    print(num_of_each_label)\n",
-    "    num_of_labels = len(num_of_each_label)\n",
-    "    print(num_of_labels)\n",
-    "    \n",
-    "    set_multisets = []\n",
-    "    for node in G.nodes(data = True):\n",
-    "        # Multiset-label determination.\n",
-    "        multiset = [ G.node[neighbors]['label'] for neighbors in G[node[0]] ]\n",
-    "        # sorting each multiset\n",
-    "        multiset.sort()\n",
-    "        multiset = node[1]['label'] + ''.join(multiset) # concatenate to a string and add the prefix \n",
-    "        set_multisets.append(multiset)\n",
-    "    print(set_multisets)\n",
-    "        \n",
-    "    # label compression\n",
-    "#     set_multisets.sort() # this is unnecessary\n",
-    "    set_unique = list(set(set_multisets)) # set of unique multiset labels\n",
-    "    print(set_unique)\n",
-    "    set_compressed = { value : str(set_unique.index(value) + num_of_labels + 1) for value in set_unique } # assign new labels\n",
-    "    print(set_compressed)\n",
-    "    \n",
-    "    # relabel nodes\n",
-    "#     nx.relabel_nodes(G, set_compressed, copy = False)\n",
-    "    for node in G.nodes(data = True):\n",
-    "        node[1]['label'] = set_compressed[set_multisets[node[0]]]\n",
-    "    print(nx.get_node_attributes(G, 'label'))\n",
-    "\n",
-    "    # get the set of compressed labels\n",
-    "    labels_comp = list(nx.get_node_attributes(G, 'label').values())\n",
-    "    print(labels_comp)\n",
-    "    num_of_each_label.update(dict(Counter(labels_comp)))\n",
-    "    print(num_of_each_label)\n",
-    "    \n",
-    "    \n",
-    "def _wl_subtreekernel_do(*args, height = 0, base_kernel = 'subtree'):\n",
-    "    \"\"\"Calculate Weisfeiler-Lehman subtree kernels between graphs.\n",
-    "    \n",
-    "    Parameters\n",
-    "    ----------\n",
-    "    Gn : List of NetworkX graph\n",
-    "        List of graphs between which the kernels are calculated.\n",
-    "        \n",
-    "    Return\n",
-    "    ------\n",
-    "    Kmatrix/Kernel : Numpy matrix/int\n",
-    "        Kernel matrix, each element of which is the Weisfeiler-Lehman kernel between 2 praphs.\n",
-    "    \"\"\"\n",
-    "    \n",
-    "#     print(args)\n",
-    "    Gn = args[0]\n",
-    "#     print(Gn)\n",
-    "\n",
-    "    Kmatrix = np.zeros((len(Gn), len(Gn)))\n",
-    "    all_num_of_labels_occured = 0 # number of the set of letters that occur before as node labels at least once in all graphs\n",
-    "    \n",
-    "    # initial for height = 0\n",
-    "    print('\\n --- height = 0 --- ')\n",
-    "    all_labels_ori = set() # all unique orignal labels in all graphs in this iteration\n",
-    "    all_num_of_each_label = [] # number of occurence of each label in each graph in this iteration\n",
-    "    all_set_compressed = {} # a dictionary mapping original labels to new ones in all graphs in this iteration\n",
-    "    num_of_labels_occured = all_num_of_labels_occured # number of the set of letters that occur before as node labels at least once in all graphs\n",
-    "\n",
-    "    # for each graph\n",
-    "    for idx, G in enumerate(Gn):\n",
-    "        # get the set of original labels\n",
-    "        print('\\n --- for graph %d --- \\n' % (idx))\n",
-    "        labels_ori = list(nx.get_node_attributes(G, 'label').values())\n",
-    "        print('labels_ori: %s' % (labels_ori))\n",
-    "        all_labels_ori.update(labels_ori)\n",
-    "        print('all_labels_ori: %s' % (all_labels_ori))\n",
-    "        num_of_each_label = dict(Counter(labels_ori)) # number of occurence of each label in graph\n",
-    "        print('num_of_each_label: %s' % (num_of_each_label))\n",
-    "        all_num_of_each_label.append(num_of_each_label)\n",
-    "        print('all_num_of_each_label: %s' % (all_num_of_each_label))\n",
-    "        num_of_labels = len(num_of_each_label) # number of all unique labels\n",
-    "        print('num_of_labels: %s' % (num_of_labels))\n",
-    "        \n",
-    "\n",
-    "        all_labels_ori.update(labels_ori)\n",
-    "        print('all_labels_ori: %s' % (all_labels_ori))\n",
-    "        \n",
-    "    all_num_of_labels_occured += len(all_labels_ori)\n",
-    "    print('\\n all_num_of_labels_occured: %s' % (all_num_of_labels_occured))\n",
-    "        \n",
-    "    # calculate subtree kernel with the 0th iteration and add it to the final kernel\n",
-    "    print('\\n --- calculating kernel matrix ---')\n",
-    "    for i in range(0, len(Gn)):\n",
-    "        for j in range(i, len(Gn)):\n",
-    "            labels = set(list(all_num_of_each_label[i].keys()) + list(all_num_of_each_label[j].keys()))\n",
-    "            print('\\n labels: %s' % (labels))\n",
-    "            vector1 = np.matrix([ (all_num_of_each_label[i][label] if (label in all_num_of_each_label[i].keys()) else 0) for label in labels ])\n",
-    "            vector2 = np.matrix([ (all_num_of_each_label[j][label] if (label in all_num_of_each_label[j].keys()) else 0) for label in labels ])\n",
-    "            print('vector1: %s' % (vector1))\n",
-    "            print('vector2: %s' % (vector2))\n",
-    "            Kmatrix[i][j] += np.dot(vector1, vector2.transpose())\n",
-    "            Kmatrix[j][i] = Kmatrix[i][j]\n",
-    "            print('Kmatrix: %s' % (Kmatrix))\n",
-    "\n",
-    "    \n",
-    "    # iterate each height\n",
-    "    for h in range(1, height + 1):\n",
-    "        print('\\n --- height = %d --- ' % (h))\n",
-    "        all_set_compressed = {} # a dictionary mapping original labels to new ones in all graphs in this iteration\n",
-    "        num_of_labels_occured = all_num_of_labels_occured # number of the set of letters that occur before as node labels at least once in all graphs\n",
-    "        all_labels_ori = set()\n",
-    "        all_num_of_each_label = []\n",
-    "        \n",
-    "        # for each graph\n",
-    "        for idx, G in enumerate(Gn):\n",
-    "#             # get the set of original labels\n",
-    "            print('\\n --- for graph %d --- \\n' % (idx))\n",
-    "#             labels_ori = list(nx.get_node_attributes(G, 'label').values())\n",
-    "#             print('labels_ori: %s' % (labels_ori))\n",
-    "#             num_of_each_label = dict(Counter(labels_ori)) # number of occurence of each label in graph\n",
-    "#             print('num_of_each_label: %s' % (num_of_each_label))\n",
-    "#             num_of_labels = len(num_of_each_label) # number of all unique labels\n",
-    "#             print('num_of_labels: %s' % (num_of_labels))\n",
-    "            \n",
-    "#             all_labels_ori.update(labels_ori)\n",
-    "#             print('all_labels_ori: %s' % (all_labels_ori))\n",
-    "#             #             num_of_labels_occured += num_of_labels #@todo not precise\n",
-    "#             num_of_labels_occured = all_num_of_labels_occured + len(all_labels_ori) + len(all_set_compressed)\n",
-    "#             print('num_of_labels_occured: %s' % (num_of_labels_occured))\n",
-    "            \n",
-    "            set_multisets = []\n",
-    "            for node in G.nodes(data = True):\n",
-    "                # Multiset-label determination.\n",
-    "                multiset = [ G.node[neighbors]['label'] for neighbors in G[node[0]] ]\n",
-    "                # sorting each multiset\n",
-    "                multiset.sort()\n",
-    "                multiset = node[1]['label'] + ''.join(multiset) # concatenate to a string and add the prefix \n",
-    "                set_multisets.append(multiset)\n",
-    "            print('multiset: %s' % (set_multisets))\n",
-    "\n",
-    "            # label compression\n",
-    "        #     set_multisets.sort() # this is unnecessary\n",
-    "            set_unique = list(set(set_multisets)) # set of unique multiset labels\n",
-    "            print('set_unique: %s' % (set_unique))\n",
-    "            # a dictionary mapping original labels to new ones. \n",
-    "            set_compressed = {}\n",
-    "            # if a label occured before, assign its former compressed label, else assign the number of labels occured + 1 as the compressed label \n",
-    "            for value in set_unique:\n",
-    "                if value in all_set_compressed.keys():\n",
-    "                    set_compressed.update({ value : all_set_compressed[value] })\n",
-    "                else:\n",
-    "                    set_compressed.update({ value : str(num_of_labels_occured + 1) })\n",
-    "                    num_of_labels_occured += 1\n",
-    "#             set_compressed = { value : (all_set_compressed[value] if value in all_set_compressed.keys() else str(set_unique.index(value) + num_of_labels_occured + 1)) for value in set_unique }\n",
-    "            print('set_compressed: %s' % (set_compressed))\n",
-    "            \n",
-    "            all_set_compressed.update(set_compressed)\n",
-    "            print('all_set_compressed: %s' % (all_set_compressed))\n",
-    "#             num_of_labels_occured += len(set_compressed) #@todo not precise\n",
-    "            print('num_of_labels_occured: %s' % (num_of_labels_occured))\n",
-    "            \n",
-    "            # relabel nodes\n",
-    "        #     nx.relabel_nodes(G, set_compressed, copy = False)\n",
-    "            for node in G.nodes(data = True):\n",
-    "                node[1]['label'] = set_compressed[set_multisets[node[0]]]\n",
-    "            print('\\n compressed labels: %s' % (nx.get_node_attributes(G, 'label')))\n",
-    "\n",
-    "            # get the set of compressed labels\n",
-    "            labels_comp = list(nx.get_node_attributes(G, 'label').values())\n",
-    "            print('labels_comp: %s' % (labels_comp))\n",
-    "            all_labels_ori.update(labels_comp)\n",
-    "            print('all_labels_ori: %s' % (all_labels_ori))\n",
-    "            num_of_each_label = dict(Counter(labels_comp))\n",
-    "            print('num_of_each_label: %s' % (num_of_each_label))\n",
-    "            all_num_of_each_label.append(num_of_each_label)\n",
-    "            print('all_num_of_each_label: %s' % (all_num_of_each_label))\n",
-    "                    \n",
-    "        all_num_of_labels_occured += len(all_labels_ori)\n",
-    "        print('\\n all_num_of_labels_occured: %s' % (all_num_of_labels_occured))\n",
-    "        \n",
-    "        # calculate subtree kernel with h iterations and add it to the final kernel\n",
-    "        print('\\n --- calculating kernel matrix ---')\n",
-    "        for i in range(0, len(Gn)):\n",
-    "            for j in range(i, len(Gn)):\n",
-    "                labels = set(list(all_num_of_each_label[i].keys()) + list(all_num_of_each_label[j].keys()))\n",
-    "                print('\\n labels: %s' % (labels))\n",
-    "                vector1 = np.matrix([ (all_num_of_each_label[i][label] if (label in all_num_of_each_label[i].keys()) else 0) for label in labels ])\n",
-    "                vector2 = np.matrix([ (all_num_of_each_label[j][label] if (label in all_num_of_each_label[j].keys()) else 0) for label in labels ])\n",
-    "                print('vector1: %s' % (vector1))\n",
-    "                print('vector2: %s' % (vector2))\n",
-    "                Kmatrix[i][j] += np.dot(vector1, vector2.transpose())\n",
-    "                Kmatrix[j][i] = Kmatrix[i][j]\n",
-    "                    \n",
-    "        print('\\n Kmatrix: %s' % (Kmatrix))\n",
-    "\n",
-    "    return Kmatrix\n",
-    "\n",
-    "    \n",
-    "# main\n",
-    "import sys\n",
-    "from collections import Counter\n",
-    "import networkx as nx\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "from pygraph.kernels.spkernel import spkernel\n",
-    "\n",
-    "dataset, y = loadDataset(\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "G1 = dataset[15]\n",
-    "print(nx.get_node_attributes(G1, 'label'))\n",
-    "G2 = dataset[80]\n",
-    "print(nx.get_node_attributes(G2, 'label'))\n",
-    "\n",
-    "weisfeilerlehmankernel(G1, G2, height = 2)\n",
-    "# Kmatrix = weisfeilerlehmankernel(G1, G2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "185"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "\n",
-    "len(dataset)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "- This script take as input a kernel matrix\n",
-      "and returns the classification or regression performance\n",
-      "- The kernel matrix can be calculated using any of the graph kernels approaches\n",
-      "- The criteria used for prediction are SVM for classification and kernel Ridge regression for regression\n",
-      "- For predition we divide the data in training, validation and test. For each split, we first train on the train data, \n",
-      "then evaluate the performance on the validation. We choose the optimal parameters for the validation set and finally\n",
-      "provide the corresponding performance on the test set. If more than one split is performed, the final results \n",
-      "correspond to the average of the performances on the test sets. \n",
-      "\n",
-      "@references\n",
-      "    https://github.com/eghisu/GraphKernels/blob/master/GraphKernelsCollection/python_scripts/compute_perf_gk.py\n",
-      "\n",
-      "\n",
-      " --- calculating kernel matrix when subtree height = 0 ---\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "[ -23.7   14.    37.3  109.7   10.8   39.    42.    66.6  135.   148.5\n",
-      "   40.    34.6   32.    63.    53.5   67.    64.4   84.7   95.5   92.\n",
-      "   84.4  154.   156.   166.   183.    70.3   63.6   52.5   59.    59.5\n",
-      "   55.2   88.    83.   104.5  102.    92.   107.4  123.2  112.5  118.5\n",
-      "  101.5  173.7  165.5  181.    99.5   92.3   90.1   80.2   82.    91.2\n",
-      "   91.5   81.2   93.    69.    86.3   82.   103.   103.5   96.   112.   104.\n",
-      "  132.5  123.5  120.3  145.   144.2  142.8  132.   134.2  137.   139.\n",
-      "  133.6  120.4  120.   137.   195.8  177.2  181.   185.9  175.7  186.   211.\n",
-      "  125.   118.   117.1  107.   102.5  112.    97.4   91.5   87.6  106.5\n",
-      "  101.    99.3   90.   137.   114.   126.   124.   140.5  157.5  146.   145.\n",
-      "  141.   171.   166.   155.   145.   159.   138.   142.   159.   163.5\n",
-      "  229.5  142.   125.   132.   130.5  125.   122.   121.   122.2  112.   106.\n",
-      "  114.5  151.   128.5  109.5  126.   147.   158.   147.   165.   188.9\n",
-      "  170.   178.   148.5  165.   177.   167.   195.   226.   215.   201.   205.\n",
-      "  151.5  165.5  157.   139.   163.   153.5  139.   162.   173.   159.5\n",
-      "  159.5  155.5  141.   126.   164.   163.   166.5  146.   165.   159.   195.\n",
-      "  218.   250.   235.   186.5  156.5  162.   162.   170.2  173.2  186.8\n",
-      "  173.   187.   174.   188.5  199.   228.   215.   216.   240. ]\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "ename": "KeyboardInterrupt",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-1-2ce8cff340bc>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     82\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     83\u001b[0m         \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'\\n Calculating kernel matrix, this could take a while...'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 84\u001b[0;31m         \u001b[0mKmatrix\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mweisfeilerlehmankernel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdataset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mheight\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbase_kernel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'sp'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     85\u001b[0m         \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mKmatrix\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     86\u001b[0m         \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'\\n Saving kernel matrix to file...'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/weisfeilerLehmanKernel.py\u001b[0m in \u001b[0;36mweisfeilerlehmankernel\u001b[0;34m(height, base_kernel, *args)\u001b[0m\n\u001b[1;32m     71\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     72\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0mj\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 73\u001b[0;31m                     \u001b[0mKmatrix\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_weisfeilerlehmankernel_do\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGn\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mGn\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mheight\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     74\u001b[0m                     \u001b[0mKmatrix\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKmatrix\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     75\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/weisfeilerLehmanKernel.py\u001b[0m in \u001b[0;36m_weisfeilerlehmankernel_do\u001b[0;34m(G1, G2, height)\u001b[0m\n\u001b[1;32m    241\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    242\u001b[0m         \u001b[0;31m# calculate kernel\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 243\u001b[0;31m         \u001b[0mkernel\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mspkernel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mG2\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# change your base kernel here (and one more before)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    244\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    245\u001b[0m         \u001b[0;31m# get label sets of both graphs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/spkernel.py\u001b[0m in \u001b[0;36mspkernel\u001b[0;34m(*args)\u001b[0m\n\u001b[1;32m     62\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0me1\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mG1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0medges\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     63\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0me2\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mG2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0medges\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 64\u001b[0;31m                 \u001b[0;32mif\u001b[0m \u001b[0me1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'cost'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;36m0\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0me1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'cost'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0me2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'cost'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0me2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0me1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0me2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0me1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0me2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0me1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0me2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     65\u001b[0m                     \u001b[0mkernel\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     66\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
-     ]
-    }
-   ],
-   "source": [
-    "# Author: Elisabetta Ghisu\n",
-    "# test of WL subtree kernel\n",
-    "\n",
-    "\"\"\"\n",
-    "- This script take as input a kernel matrix\n",
-    "and returns the classification or regression performance\n",
-    "- The kernel matrix can be calculated using any of the graph kernels approaches\n",
-    "- The criteria used for prediction are SVM for classification and kernel Ridge regression for regression\n",
-    "- For predition we divide the data in training, validation and test. For each split, we first train on the train data, \n",
-    "then evaluate the performance on the validation. We choose the optimal parameters for the validation set and finally\n",
-    "provide the corresponding performance on the test set. If more than one split is performed, the final results \n",
-    "correspond to the average of the performances on the test sets. \n",
-    "\n",
-    "@references\n",
-    "    https://github.com/eghisu/GraphKernels/blob/master/GraphKernelsCollection/python_scripts/compute_perf_gk.py\n",
-    "\"\"\"\n",
-    "\n",
-    "print(__doc__)\n",
-    "\n",
-    "import sys\n",
-    "import os\n",
-    "import pathlib\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from tabulate import tabulate\n",
-    "\n",
-    "import random\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "from sklearn.kernel_ridge import KernelRidge # 0.17\n",
-    "from sklearn.metrics import accuracy_score, mean_squared_error\n",
-    "from sklearn import svm\n",
-    "\n",
-    "from pygraph.kernels.weisfeilerLehmanKernel import weisfeilerlehmankernel\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "\n",
-    "val_means_height = []\n",
-    "val_stds_height = []\n",
-    "test_means_height = []\n",
-    "test_stds_height = []\n",
-    "\n",
-    "\n",
-    "for height in np.linspace(0, 10, 11):\n",
-    "    print('\\n --- calculating kernel matrix when subtree height = %d ---' % height)\n",
-    "\n",
-    "    print('\\n Loading dataset from file...')\n",
-    "    dataset, y = loadDataset(\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "    y = np.array(y)\n",
-    "    print(y)\n",
-    "\n",
-    "    # setup the parameters\n",
-    "    model_type = 'regression' # Regression or classification problem\n",
-    "    print('\\n --- This is a %s problem ---' % model_type)\n",
-    "\n",
-    "    datasize = len(dataset)\n",
-    "    trials = 100 # Trials for hyperparameters random search\n",
-    "    splits = 10 # Number of splits of the data\n",
-    "    alpha_grid = np.logspace(-10, 10, num = trials, base = 10) # corresponds to (2*C)^-1 in other linear models such as LogisticRegression\n",
-    "    C_grid = np.logspace(-10, 10, num = trials, base = 10)\n",
-    "    random.seed(20) # Set the seed for uniform parameter distribution\n",
-    "\n",
-    "    # set the output path\n",
-    "    kernel_file_path = 'kernelmatrices_weisfeilerlehman_acyclic/'\n",
-    "    if not os.path.exists(kernel_file_path):\n",
-    "        os.makedirs(kernel_file_path)\n",
-    "\n",
-    "\n",
-    "    \"\"\"\n",
-    "    -  Here starts the main program\n",
-    "    -  First we permute the data, then for each split we evaluate corresponding performances\n",
-    "    -  In the end, the performances are averaged over the test sets\n",
-    "    \"\"\"\n",
-    "\n",
-    "    # save kernel matrices to files / read kernel matrices from files\n",
-    "    kernel_file = kernel_file_path + 'km.ds'\n",
-    "    path = pathlib.Path(kernel_file)\n",
-    "    # get train set kernel matrix\n",
-    "    if path.is_file():\n",
-    "        print('\\n Loading the kernel matrix from file...')\n",
-    "        Kmatrix = np.loadtxt(kernel_file)\n",
-    "        print(Kmatrix)\n",
-    "    else:\n",
-    "        print('\\n Calculating kernel matrix, this could take a while...')\n",
-    "        Kmatrix = weisfeilerlehmankernel(dataset, node_label = 'atom', height = int(height), base_kernel = 'sp')\n",
-    "        print(Kmatrix)\n",
-    "        print('\\n Saving kernel matrix to file...')\n",
-    "#         np.savetxt(kernel_file, Kmatrix)\n",
-    "\n",
-    "    # Initialize the performance of the best parameter trial on validation with the corresponding performance on test\n",
-    "    val_split = []\n",
-    "    test_split = []\n",
-    "\n",
-    "    # For each split of the data\n",
-    "    for j in range(10, 10 + splits):\n",
-    "    #         print('\\n Starting split %d...' % j)\n",
-    "\n",
-    "        # Set the random set for data permutation\n",
-    "        random_state = int(j)\n",
-    "        np.random.seed(random_state)\n",
-    "        idx_perm = np.random.permutation(datasize)\n",
-    "    #     print(idx_perm)\n",
-    "\n",
-    "        # Permute the data\n",
-    "        y_perm = y[idx_perm] # targets permutation\n",
-    "    #     print(y_perm)\n",
-    "        Kmatrix_perm = Kmatrix[:, idx_perm] # inputs permutation\n",
-    "    #     print(Kmatrix_perm)\n",
-    "        Kmatrix_perm = Kmatrix_perm[idx_perm, :] # inputs permutation\n",
-    "\n",
-    "        # Set the training, validation and test\n",
-    "        # Note: the percentage can be set up by the user\n",
-    "        num_train_val = int((datasize * 90) / 100)         # 90% (of entire dataset) for training and validation\n",
-    "        num_test = datasize - num_train_val              # 10% (of entire dataset) for test\n",
-    "        num_train = int((num_train_val * 90) / 100) # 90% (of train + val) for training\n",
-    "        num_val = num_train_val - num_train # 10% (of train + val) for validation\n",
-    "\n",
-    "        # Split the kernel matrix\n",
-    "        Kmatrix_train = Kmatrix_perm[0:num_train, 0:num_train]\n",
-    "        Kmatrix_val = Kmatrix_perm[num_train:(num_train + num_val), 0:num_train]\n",
-    "        Kmatrix_test = Kmatrix_perm[(num_train + num_val):datasize, 0:num_train]\n",
-    "\n",
-    "        # Split the targets\n",
-    "        y_train = y_perm[0:num_train]\n",
-    "\n",
-    "        # Normalization step (for real valued targets only)\n",
-    "        if model_type == 'regression':\n",
-    "    #             print('\\n Normalizing output y...')\n",
-    "            y_train_mean = np.mean(y_train)\n",
-    "            y_train_std = np.std(y_train)\n",
-    "            y_train = (y_train - y_train_mean) / float(y_train_std)\n",
-    "    #         print(y)\n",
-    "\n",
-    "        y_val = y_perm[num_train:(num_train + num_val)]\n",
-    "        y_test = y_perm[(num_train + num_val):datasize]\n",
-    "\n",
-    "        # Record the performance for each parameter trial respectively on validation and test set\n",
-    "        perf_all_train = []\n",
-    "        perf_all_test = []\n",
-    "\n",
-    "        # For each parameter trial\n",
-    "        for i in range(trials):\n",
-    "            # For regression use the Kernel Ridge method\n",
-    "            if model_type == 'regression':\n",
-    "    #             print('\\n Starting experiment for trial %d and parameter alpha = %3f\\n ' % (i, alpha_grid[i]))\n",
-    "\n",
-    "                # Fit the kernel ridge model\n",
-    "                KR = KernelRidge(kernel = 'precomputed', alpha = alpha_grid[i])\n",
-    "    #                 KR = svm.SVR(kernel = 'precomputed', C = C_grid[i])\n",
-    "                KR.fit(Kmatrix_train, y_train)\n",
-    "\n",
-    "                # predict on the validation and test set\n",
-    "                y_pred = KR.predict(Kmatrix_val)\n",
-    "                y_pred_test = KR.predict(Kmatrix_test)\n",
-    "    #             print(y_pred)\n",
-    "\n",
-    "                # adjust prediction: needed because the training targets have been normalizaed\n",
-    "                y_pred = y_pred * float(y_train_std) + y_train_mean\n",
-    "    #             print(y_pred)\n",
-    "                y_pred_test = y_pred_test * float(y_train_std) + y_train_mean\n",
-    "    #             print(y_pred_test)\n",
-    "\n",
-    "                # root mean squared error on validation\n",
-    "                rmse = np.sqrt(mean_squared_error(y_val, y_pred))\n",
-    "                perf_all_val.append(rmse)\n",
-    "\n",
-    "                # root mean squared error in test \n",
-    "                rmse_test = np.sqrt(mean_squared_error(y_test, y_pred_test))\n",
-    "                perf_all_test.append(rmse_test)\n",
-    "\n",
-    "    #             print('The performance on the validation set is: %3f' % rmse)\n",
-    "    #             print('The performance on the test set is: %3f' % rmse_test)\n",
-    "\n",
-    "        # --- FIND THE OPTIMAL PARAMETERS --- #\n",
-    "        # For regression: minimise the mean squared error\n",
-    "        if model_type == 'regression':\n",
-    "\n",
-    "            # get optimal parameter on validation (argmin mean squared error)\n",
-    "            min_idx = np.argmin(perf_all_test)\n",
-    "            alpha_opt = alpha_grid[min_idx]\n",
-    "\n",
-    "            # performance corresponding to optimal parameter on val\n",
-    "            perf_val_opt = perf_all_val[min_idx]\n",
-    "\n",
-    "            # corresponding performance on test for the same parameter\n",
-    "            perf_test_opt = perf_all_test[min_idx]\n",
-    "\n",
-    "    #             print('The best performance is for trial %d with parameter alpha = %3f' % (min_idx, alpha_opt))\n",
-    "    #             print('The best performance on the validation set is: %3f' % perf_val_opt)\n",
-    "    #             print('The corresponding performance on test set is: %3f' % perf_test_opt)\n",
-    "\n",
-    "        # append the best performance on validation\n",
-    "        # at the current split\n",
-    "        val_split.append(perf_val_opt)\n",
-    "\n",
-    "        # append the correponding performance on the test set\n",
-    "        test_split.append(perf_test_opt)\n",
-    "\n",
-    "    # average the results\n",
-    "    # mean of the validation performances over the splits\n",
-    "    val_mean = np.mean(np.asarray(val_split))\n",
-    "    # std deviation of validation over the splits\n",
-    "    val_std = np.std(np.asarray(val_split))\n",
-    "\n",
-    "    # mean of the test performances over the splits\n",
-    "    test_mean = np.mean(np.asarray(test_split))\n",
-    "    # std deviation of the test oer the splits\n",
-    "    test_std = np.std(np.asarray(test_split))\n",
-    "\n",
-    "    print('\\n Mean performance on val set: %3f' % val_mean)\n",
-    "    print('With standard deviation: %3f' % val_std)\n",
-    "    print('\\n Mean performance on test set: %3f' % test_mean)\n",
-    "    print('With standard deviation: %3f' % test_std)\n",
-    "    \n",
-    "    val_means_height.append(val_mean)\n",
-    "    val_stds_height.append(val_std)\n",
-    "    test_means_height.append(test_mean)\n",
-    "    test_stds_height.append(test_std)\n",
-    "    \n",
-    "print('\\n') \n",
-    "print(tabulate({'height': np.linspace(1, 12, 11), 'RMSE': test_means_height, 'std': test_stds_height}, headers='keys'))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O', 6: 'O'}"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# a = [0, 1, 3, 2]\n",
-    "# b = [3, 2, 1, 0]\n",
-    "# print(1 if a == b else 0)\n",
-    "\n",
-    "# max(1 ,2)\n",
-    "\n",
-    "# x = [ 'r', 'a', 's' ]\n",
-    "# x.sort()\n",
-    "# print(x)\n",
-    "\n",
-    "# def test1(*args, base = 'subtree'):\n",
-    "#     if base == 'subtree':\n",
-    "#         print('subtree')\n",
-    "#     elif base == 'edge':\n",
-    "#         print('edge')\n",
-    "#     else:\n",
-    "#         print('sp')\n",
-    "\n",
-    "# # function parameter usage test\n",
-    "# test1('hello', 'hi', base = 'edge')\n",
-    "\n",
-    "# # python matrix calculation speed test\n",
-    "# import numpy as np\n",
-    "# import time\n",
-    "\n",
-    "# size = 100\n",
-    "# m1 = np.random.random((size, size))\n",
-    "# m2 = np.random.random((size, size))\n",
-    "# itr = 1\n",
-    "\n",
-    "# start_time = time.time()\n",
-    "# for i in range(itr):\n",
-    "#     np.dot(m1, m2)\n",
-    "# print(time.time() - start_time)\n",
-    "\n",
-    "# start_time = time.time()\n",
-    "# for j in range(itr):\n",
-    "#     result = np.zeros((size, size))\n",
-    "#     for i1 in range(size):\n",
-    "#         for i2 in range(size):\n",
-    "#             for i3 in range(size):\n",
-    "#                 result[i1][i2] += m1[i1][i3] * m2[i3][i2]\n",
-    "# print(time.time() - start_time)\n",
-    "\n",
-    "# start_time = time.time()\n",
-    "# for i in range(itr):\n",
-    "#     print(np.dot(m1, m2))\n",
-    "# print(time.time() - start_time)\n",
-    "\n",
-    "# start_time = time.time()\n",
-    "# for j in range(itr):\n",
-    "#     result = np.zeros((size, size))\n",
-    "#     for i1 in range(size):\n",
-    "#         for i2 in range(size):\n",
-    "#             for i3 in range(size):\n",
-    "#                 result[i1][i2] += m1[i1][i3] * m2[i3][i2]\n",
-    "#     print(result)\n",
-    "# print(time.time() - start_time)\n",
-    "\n",
-    "# help(np.sum)\n",
-    "\n",
-    "# test dict\n",
-    "import sys\n",
-    "from collections import Counter\n",
-    "import networkx as nx\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "from pygraph.kernels.spkernel import spkernel\n",
-    "\n",
-    "dataset, y = loadDataset(\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "G1 = dataset[15]\n",
-    "nx.get_node_attributes(G1, 'label')\n",
-    "listhqhq = list(nx.get_node_attributes(G1, 'label').values())\n",
-    "dicthaha = dict(Counter(listhqhq))\n",
-    "len(dicthaha)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/.ipynb_checkpoints/plot_all_graphs-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/plot_all_graphs-checkpoint.ipynb
deleted file mode 100644
index c07f0bc..0000000
--- a/notebooks/.ipynb_checkpoints/plot_all_graphs-checkpoint.ipynb
+++ /dev/null
@@ -1,3388 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0\n",
-      "{0: 'C', 1: 'C', 2: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d83021f28>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "1\n",
-      "{0: 'C', 1: 'C', 2: 'O', 3: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d82fe6828>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2\n",
-      "{0: 'C', 1: 'C', 2: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f25b00>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "3\n",
-      "{0: 'C', 1: 'C', 2: 'S', 3: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e6bfd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "4\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e89358>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "5\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'O', 4: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f687b8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "6\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'O', 4: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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mnIP6ehq/9z1+ec45XHDBBWzYsEGJX+KOkr/I0ZSUfJr4Qw4CNwOnAccDFwKrW+zW7eBBfhwMMudrX+PYY4+NWbgi7aXkL3I0c+Z8OqQTcggYCGwA6oCfAF8H3m6x6zENDd7+InEoKsnfzK4ys61mtt3M7gqzvYeZLQ1tf93MBkfjvCJdqrrau7jbYqjns8B9wGC8/0D/AZwOlLXc3zkoKoKami4PVaSjIk7+ZtYNeBwYC5wPTDaz81tUuxmodc6dBTwMPBjpeUW6XH5+u6rtAd4Cwi7FZtbu44jEUjR6/iOB7c65Hc65BmAJML5FnfHA70KvlwFXmJlF4dwiXaeq6vDpnGF8BFwHTAXODVchGITNm6Mfm0iEopH8TwV2Nnv/bqgsbB3n3CG8odKTWh7IzGaYWamZldboT2XxW13dUTc3ATcA3YG5R6tYWxu9mESiJK4u+Drn5jnnAs65QEYrd0qKxMxRvijd4Y1l7gGWA0edz9O7d1TDEomGaCT/XXiTHz42IFQWto6ZHQOkA+9H4dwiXSczE1pZdC0H+CvwByDtaMdIS4OhQ6Mfm0iEopH8S4Czzex0M+sOTAIKW9QpxBsWBbgaWOdcW3fLiPhs2rSwxe8AvwYqgZOB40KPxeEqO9fqcUT8FPHyDs65Q2Z2K7AG6AbMd85tMbP7gVLnXCHwW2ChmW0H9uL9ghCJb/360XDFFRzz/POH9ZJOwxv2aZMZZGe3utibiJ+israPc64IKGpRNrvZ6wPANdE4l0isvP7668ypqGDpMcfQ49Chjh8gLc1b5E0kDsXVBV+ReNDU1MQDDzzAuHHjmDp3Lj0eeww6+r26vXpBbi4EAl0TpEiEtKqnSDO7d+/mhhtuoKGhgdLSUgYObDaX4Wiren7MzOvx5+ZCTk7XByzSSer5i4SsXr2arKwsLr30UtatW3d44s/JgQ0bYMIEbwZQWos5PmlpXvmECV49JX6Jc+r5S8o7ePAgs2bNYtmyZSxdupQvfOEL4SsGArB8ubdWT36+d+duba03j3/oUG9Wjy7uSoJQ8peUtm3bNiZNmsTAgQOpqKjgpJOOuPH8SBkZcMcdXR+cSBfSsI+krKeffpqLL76Ym2++meeee659iV8kSajnLynnww8/5Fvf+hZlZWWsXbuWzMxMv0MSiTn1/CWllJaWkpWVRVpaGqWlpUr8krKU/CUlNDU18Ytf/ILs7Gx+9rOfMW/ePHp1dO6+SBLRsI8kvT179jBt2jTq6up44403GDx4sN8hifhOPX9Jai+99BJZWVlkZWWxYcMGJX6REPX8JSk1NDRwzz33sHjxYhYuXMjll1/ud0gicUXJX5LOjh07mDx5MhkZGVRUVKAvBhI5koZ9JKk888wzXHTRRUyZMoU//OEPSvwirVDPX5LC/v37ue2223jllVd48cUXGTZsmN8hicQ19fwl4VVUVBAIBHDOUVZWpsQv0g5K/pKwnHM8+uijXHnllcyePZsFCxZw3HHH+R2WSELQsI8kpJqaGqZPn051dTXFxcWceeaZfockklDU85eE88c//pFhw4YxZMgQ/vSnPynxi3SCev6SMA4dOsR9993H/Pnzyc/P58orr/Q7JJGEpeQvCeHtt99mypQpnHDCCVRUVNC/f3+/QxJJaBr2kbj37LPPMnLkSCZOnEhRUZESv0gUqOcvcau+vp7vfve7rFu3jueff54RI0b4HZJI0lDPX+LS5s2bCQQC1NfXU15ersQvEmVK/hJXnHM88cQTXH755dx1110sWrSIE044we+wRJKOhn0kbuzdu5ebb76Zd955h1deeYVzzjnH75BEkpZ6/hIXNm7cyIUXXsjpp5/Oa6+9psQv0sXU8xdfHTp0iJ/85Cc8+eSTzJ8/n+zsbL9DEkkJSv7im507d3Lddddx7LHHUl5ezimnnOJ3SCIpQ8M+4ouCggICgQDZ2dm8+OKLSvwiMaaev8RUMBhk5syZrF69mpUrVzJq1Ci/QxJJSer5S8y8+eabXHTRRbz33nuUl5cr8Yv4SMlfupxzjnnz5nHZZZfxne98hyVLlnDiiSf6HZZIStOwj7RfdTXk50NVFdTVQXo6ZGbC9OnQynflfvDBB8yYMYOtW7eyceNGzjvvvNjGLCJhqecvbSspgYkT4bTT4N57YfFiWLXKe77vPhg0yNteUnLYbq+++irDhg2jf//+vP7660r8InEkouRvZn3M7CUz2xZ67t1KvUYzqww9CiM5p8RYXh6MHg0FBXDggPdoLhj0ygoKvHp5eTQ2NvLTn/6UiRMn8sgjj/CrX/2Knj17+hG9iLQi0p7/XcBa59zZwNrQ+3CCzrkLQ49xEZ5TYiUvD2bOhPp6cO7odZ2D+nqabr+dx847j5deeonS0lLGjx8fm1hFpEMiTf7jgd+FXv8O+GqEx5N4UVLyaeIPYxvQE7i+RflngkG+/fbbrH3wQQYMGNDVUYpIJ0Wa/Ps753aHXv8TaO1bNnqaWamZFZuZfkEkgjlzvCGdVnwbaG2R5e6HDtHtoYe6JCwRiY42Z/uY2cvAyWE23d38jXPOmVlrYwOnOed2mdkZwDoz2+yc+3uYc80AZgAMGjSozeCli1RXw+rVrQ71LAFOBC4Gtoer4BwUFUFNTauzgETEX232/J1zY5xz/y/MYyWwx8w+BxB6rm7lGLtCzzuA9cCwVurNc84FnHOBDCUN/+Tnt7ppHzAb+GVbxzA76nFExF+RDvsUAlNDr6cCK1tWMLPeZtYj9LovcAnwZoTnla5UVXXkrJ6Qe4CbgTZH84NB2Lw5yoGJSLREepPXA8Dvzexm4B3g6wBmFgC+6Zy7BTgP+LWZNeH9snnAOafkH8/q6sIWVwIvAxXtPU5tbZQCEpFoiyj5O+feB64IU14K3BJ6/SowNJLzSIylp4ctXg+8DXx8NWY/0Ij3Z1x5uB16h73tQ0TigO7wlSNlZkKYm7JmAH/H+wugEvgm8BVgTbhjpKXBUP3OF4lXSv5ypGnTwhb3wpv29fHjOLy5/mEvzTvX6nFExH9K/nKkfv1ouOIKmtqodh+wKNwGM8jO1jRPkTim5C9H2LBhA18rLeWjYzp5SSgtDWbNim5QIhJVSv7yiY8++oi7776bSZMmkTN/Pj0eewx69erYQXr1gtxcCAS6JkgRiQqt5y8AbNu2jeuuu46MjAwqKyvp37/ZSh0zZ3rz9o+2uJuZ1+PPzYWcnK4PWEQiop5/inPO8dvf/paLL76YG2+8kVWrVh2e+HNyYMMGmDDBmwGUlnb4AdLSvPIJE7x6SvwiCUE9/xS2d+9eZsyYwbZt21i/fj1DhgwJXzEQgOXLvbV68vO9O3dra715/EOHerN6dHFXJKEo+aeodevWMXXqVK655hoWLVrUvi9byciAO+7o+uBEpMsp+aeYhoYGfvSjH7F48WLmz5/Pl7/8Zb9DEhEfKPmnkL/97W9MmTKFgQMHUllZiVZOFUlduuCbApxz/PrXv+bSSy/lG9/4BgUFBUr8IilOPf8kV1NTwy233MLOnTvZtGkT5557rt8hiUgcUM8/ib344otceOGFnHvuuRQXFyvxi8gn1PNPQgcOHOCHP/whzz77LAsXLuTyyy/3OyQRiTNK/klmy5YtTJkyhbPOOovKykpOOukkv0MSkTikYZ8k4Zxj7ty5jB49mu985zssW7ZMiV9EWqWefxLYs2cPN910E9XV1bz66qucffbZfockInFOPf8EV1RUxLBhw7jwwguV+EWk3dTzT1DBYJAf/OAHFBYW8swzz3DZZZf5HZKIJBD1/BNQVVUVI0aMoLq6msrKSiV+EekwJf8E0tTUxCOPPMIVV1zBD37wA5YsWULv3r39DktEEpCGfRLE7t27mTZtGvv27aO4uJgzzzzT75BEJIGp558ACgsLGTZsGKNGjWLTpk1K/CISMfX841h9fT233347L7zwAsuXL+eSSy7xOyQRSRLq+cepiooKsrKy2L9/P5WVlUr8IhJVSv5xpqmpidzcXK688kpmz57NwoULSU9P9zssEUkyGvaJI7t27eLGG2/k4MGDlJSUMHjwYL9DEpEkpZ5/nFixYgVZWVl88YtfZP369Ur8ItKl1PP32f79+/nud7/L+vXrKSws5KKLLvI7JBFJAer5+6ikpISsrCwaGxupqKhQ4heRmFHPPxqqqyE/H6qqoK4O0tMhMxOmT4cw35Xb2NjIQw89xMMPP8zcuXP5+te/HvuYRSSlKflHoqQE5syB1au99wcOfLptxQq4914YOxZmzYIRIwD4xz/+wQ033ICZUVZWxsCBA30IXERSnYZ9OisvD0aPhoICL+k3T/wAwaBXVlDg1cvLY+nSpQQCAcaOHcvatWuV+EXEN+r5d0ZeHsycCfX1bdd1DurrOfhf/8WWPn0oKioiEAh0fYwiIkehnn9HlZQckfjnAgGgBzCtld16NDby3/v3o7QvIvEgouRvZteY2RYzazKzVvOamV1lZlvNbLuZ3RXJOX03Z443pNPMKcCPgJva2NUOHPD2FxHxWaQ9/78AE4GNrVUws27A48BY4HxgspmdH+F5/VFd7V3cde6w4onAV4E2vy7dOSgqgpqaLgpQRKR9Ikr+zrm/Oue2tlFtJLDdObfDOdcALAHGR3Je3+TnR34Ms+gcR0QkArEY8z8V2Nns/buhssRTVXXkrJ6OCgZh8+boxCMi0kltzvYxs5eBk8Nsuts5tzKawZjZDGAGwKBBg6J56Oioq4vOcWpro3McEZFOajP5O+fGRHiOXUDzCe0DQmXhzjUPmAcQCARcuDq+itbSyvreXRHxWSyGfUqAs83sdDPrDkwCCmNw3ujLzISePY8oPgQcABpDjwOhsrDS0mDo0K6KUESkXSKd6jnBzN4FPg88b2ZrQuWnmFkRgHPuEHArsAb4K/B759yWyML2ybRpYYt/AqQBDwCLQq9/0toxnGv1OCIisWLOxd/oCnjDPqWlpX6HcaSJE70lGzrz72YGEybA8uXRj0tEBDCzMudcm/eT6g7fjpo1yxu66Yy0NG9/ERGfKfl31IgRkJsLvXp1bL9evbz9tK6PiMQBLezWGTk53vPMmd68/aMNAZl5Pf7c3E/3ExHxmXr+nZWTAxs2eGP4PXseORSUluaVT5jg1VPiF5E4op5/JAIB7+JtTY23ZMPmzd4NXL17e9M5p00L+01eIiJ+U/KPhowMuOMOv6MQEWk3DfuIiKQgJX8RkRSk5C8ikoKU/EVEUpCSv4hIClLyFxFJQUr+IiIpSMlfRCQFxe2SzmZWA7zjdxxR1hd4z+8gYkDtTC6p0M5kauNpzrk2lxaI2+SfjMystD3rbCc6tTO5pEI7U6GNLWnYR0QkBSn5i4ikICX/2JrndwAxonYml1RoZyq08TAa8xcRSUHq+YuIpCAl/ygzsz5m9pKZbQs9926l3gtm9oGZrWpRfrqZvW5m281sqZl1j03kHdOBdk4N1dlmZlObla83s61mVhl69Itd9G0zs6tC8W03s7vCbO8R+ny2hz6vwc22zQqVbzWzL8cy7o7obBvNbLCZBZt9dk/GOvaOaEc7v2Bm5WZ2yMyubrEt7M9vUnDO6RHFB/AQcFfo9V3Ag63UuwL4T2BVi/LfA5NCr58EcvxuU2fbCfQBdoSee4de9w5tWw8E/G5HK23rBvwdOAPoDvwZOL9FnW8BT4ZeTwKWhl6fH6rfAzg9dJxufrcpym0cDPzF7zZEsZ2DgUzgaeDqZuWt/vwmw0M9/+gbD/wu9Pp3wFfDVXLOrQU+bF5mZgZcDixra/840J52fhl4yTm31zlXC7wEXBWj+CIxEtjunNvhnGsAluC1t7nm7V8GXBH6/MYDS5xzB51z/wtsDx0v3kTSxkTSZjudc28756qAphb7JurPb7so+Udff+fc7tDrfwL9O7DvScAHzrlDoffvAqdGM7goak87TwV2Nnvfsj0LQsMG98RZUmkr7sPqhD6vOrzPrz37xoNI2ghwuplVmNkGM7u0q4ONQCSfR6J8lp2i7/DtBDN7GTg5zKa7m79xzjkzS9jpVF3czuucc7vM7HhgOXAD3p/dEv92A4Occ++b2XCgwMyGOOf2+R2YtJ+Sfyc458a0ts3M9pjZ55xzu82my2PSAAABqUlEQVTsc0B1Bw79PnCimR0T6mkNAHZFGG6nRaGdu4DRzd4PwBvrxzm3K/T8oZn9D96f5/GS/HcBA5u9D/c5fFznXTM7BkjH+/zas2886HQbnTcgfhDAOVdmZn8HzgFKuzzqjovk82j15zcZaNgn+gqBj2cFTAVWtnfH0H+qPwIfzzjo0P4x1p52rgGuNLPeodlAVwJrzOwYM+sLYGbHAv8B/CUGMbdXCXB2aOZVd7yLnYUt6jRv/9XAutDnVwhMCs2UOR04G3gjRnF3RKfbaGYZZtYNwMzOwGvjjhjF3VHtaWdrwv78dlGcsef3Fedke+CNia4FtgEvA31C5QHgN83qbQJqgCDeWOKXQ+Vn4CWL7cCzQA+/2xRhO28KtWU7MD1U9lmgDKgCtgCPEmczYoBs4C28mSJ3h8ruB8aFXvcMfT7bQ5/XGc32vTu031ZgrN9tiXYbga+FPrdKoBz4T7/bEmE7R4T+D/4L76+3LUf7+U2Wh+7wFRFJQRr2ERFJQUr+IiIpSMlfRCQFKfmLiKQgJX8RkRSk5C8ikoKU/EVEUpCSv4hICvo/xISh79FrRO0AAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e32d68>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "7\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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xE4vw303oyv2vNQ9P+wYz6wXcBfR398ORFuTus909x91zMvRnf+2Wl/fvXwBldgGVY/avpm51R47kzjvv5M0332ThwoV069aNbdu2xadmkRQSi/DPB1qZ2TlmVh8YDCwpPcDM2hE63tff3ffFYJ1SG+Tlwdq1MHBg6AygsruC0tJC0wcODI0r1c3zu9/9LmvXrmXo0KF069aNe++9ly/L9AsSkeqLSUtnM7sUeAioCzzp7vea2SSgwN2XmNkqIAvYE37LX929f2XLVEvnJLN/f6hlQ1FR6AKuxo1Dp3MOG1blwd2//vWv3HjjjezZs4cnn3yS9u3bx6VkkdroWFs6q5+/1AruzjPPPMOYMWMYPnw448ePJ62aB5VFkpn6+UtSMTOuvfZaCgsL+fOf/0zbtm154403gi5LpNZS+Eutcvrpp/Pcc88xZcoUBg8ezMiRI/nnP/8ZdFkitY7CX2qlyy+/nOLiYg4fPkxmZiYrVujSEZHjofCXWqtx48bMmTOHJ554gpEjR3Ldddfx4YcfBl2WSK2g8Jdar1evXhQVFdGkSRMyMzNZuHAhiXoig0iiUPhLUjjxxBN58MEHWbRoERMnTmTQoEH87W9/C7oskYSl8Jek0qVLFzZv3kxWVhZt27bliSee0F8BIhEo/CXpNGjQgEmTJrFq1SpmzpxJ79692blzZ9BliSQUhb8krezsbNavX89//ud/0qlTJx566CG++uqroMsSSQgKf0lq9erV4/bbb2fdunUsWrSIiy66iHfeeSfoskQCp/CXlNCqVSvWrFnD8OHD6d69O5MnT+aLL74IuiyRwCj8JWXUqVOHG2+8kbfffpsNGzaQk5NDfn5+0GWJBELhLymnefPmLF26lLFjx9KvXz/uuOMODh06VPUbRZKIwl9Skplx9dVXU1RUxK5du2jTpg1r164NuiyRuFH4S0rLyMjg2WefZfr06VxzzTXk5eXxySefBF2WSI1T+IsA/fv3p7i4mKNHj5KZmcmyZcuCLkmkRin8RcIaNWrErFmzmDdvHqNGjWLo0KHs378/6LJEakRMwt/M+pjZn8xsh5mNjTC/gZk9F56/wczOjsV6RWpCjx49KCwspFmzZmRlZbFgwQK1iJCkE3X4m1ldYAbQF2gNDDGz1mWG5QIH3P084EFgSrTrFalJ6enpTJs2jSVLlnDvvfcyYMAAdu/eHXRZIjETiy3/TsAOd9/p7l8AC4ABZcYMAOaFnz8P9DQzi8G6RWpUp06d2LRpEx06dKBt27Y8/vjj+itAkkIswv8sYFep1x+Ep0Uc4+5HgINAkxisW6TG1a9fn/Hjx7NmzRrmzJlDz549ee+994IuSyQqCXXA18xGmFmBmRXoQJskmszMTN566y1+9KMf0blzZ6ZPn65GcVJrxSL8dwPfLvW6eXhaxDFmVg9oBJS73567z3b3HHfPycjIiEFpIrFVt25dbrvtNjZs2MCyZcvo2rUrxcXFQZclctxiEf75QCszO8fM6gODgSVlxiwBrg8//zHwmmvHqdRi5557LqtXr2bEiBH06NGDCRMmqFGc1CpRh394H/7PgVeAbcBCd3/HzCaZWf/wsCeAJma2A7gNKHc6qEhtY2bccMMNbNmyhc2bN9O+fXs2btwYdFkix8QSdQM8JyfHCwoKgi5D5Ji4OwsXLuTWW2/l6quvZvLkyaSnpwddlqQgM9vk7jlVjUuoA74itZWZcdVVV1FUVMTevXvJzs5mzZo1QZclUiGFv0gMnXbaaTzzzDM8/PDDXH/99YwYMYKPP/446LJEylH4i9SAyy67jOLiYurVq0dmZiZLlpQ9B0IkWAp/kRpyyimn8OijjzJ//nxGjx7N4MGD2bdvX9BliQAKf5Ead8kll1BYWEjLli3Jzs5m/vz5ahEhgVP4i8RBWloaU6ZM4eWXX2bKlCn069ePXbt2Vf1GkRqi8BeJo5ycHAoKCujSpQvt27fnscce4+jRo0GXJSlI4S8SZ/Xr1+fuu+9m7dq1zJs3jx49erB9+/agy5IUo/AXCUjr1q158803GTRoEF27dmXq1KkcOXIk6LIkRSj8RQJUt25dRo0aRX5+PitXrqRLly5s3bo16LIkBSj8RRLAOeecw6uvvsrNN99M7969ueeeezh8+HDQZUkSU/iLJAgz46c//SlbtmyhuLiYdu3asW7duqDLkiSl8BdJMGeeeSYvvvgikyZN4oorruDWW2/ls88+C7osSTIKf5EEZGb8+Mc/pqioiAMHDpCVlcWqVauCLkuSiMJfJIE1adKEefPm8eijj5Kbm0tubi4HDhwIuixJAgp/kVqgT58+FBcXk5aWRmZmJosWLQq6JKnlFP4itcTJJ5/Mr3/9axYsWMDYsWO58sor2bt3b9BlSS2l8BepZbp168bWrVs577zzyM7O5qmnnlKjODluUd3G0cy+BTwHnA38BbjS3Q+UGdMWmAmcAnwF3Ovuz1W1bN3GUaRqmzdvJjc3lzPOOINZs2bRokWLyt+wbx/MnQuFhXDwIDRqBNnZMHw4ZGTEpWapWfG6jeNYYLW7twJWE/nG7IeA69z9AqAP8JCZnRrlekUE/nXT+IsvvpgOHTowY8aMyI3i8vNh0CBo2RLGj4f58+Hll0NfJ0yAFi1C8/Pz4/5vkGBEu+X/J6C7u+8xs2bA6+7+3SresxX4sbtX2slKW/4ix+ePf/wjubm51KlThzlz5vDd74Z/FGfOhDFjoKQEKvt5N4O0NJg2DfLy4lO0xNyxbvnXi3I9p7v7nvDzvwOnV1FUJ6A+8F4F80cAI4Cq/3wVkW/43ve+xxtvvMGjjz7KD37wA0aPHs2Yk06i3p13wqFDVS/APTRuzJjQa/0CSGpVbvmb2SrgjAiz7gLmufuppcYecPfGFSynGfA6cL27r6+qMG35i1Tf+++/z/TBg5myYQNpZX7GryG0j/YzQj/YdwA3lF1AejqsXQs5VW5ASoKJ2Za/u/eqZCV7zaxZqd0+EW9QamanAMuAu44l+EUkOi1btuThM84g0qbdOOAJoAHwR6A70A7oUHpQSQncdx+88EJNlyoBifaA7xLg+vDz64GXyg4ws/rAIuApd38+yvWJyLHYtw/73e+oE+Ev+wsIBT+AhR/l9sO6w/LlsH9/jZYpwYk2/O8HepvZdqBX+DVmlmNmc8JjrgQuBoaZ2Zbwo22U6xWRysydW+nsm4F04HtAM+DSSIPMqlyO1F5RHfB19w+BnhGmFxDejejuzwDPRLMeETlOhYXw+ecVzn4U+BWwjtCBuAaRBpWUQFFRTVQnCUBX+Ioko4MHqxxSF/gB8AGhqzAjUhO5pKXwF0lGjRod89AjVHDuNUDjiCfvSRJQ+Isko+xsaNiw3OR9wALgU0K9Vl4BniXCvlsIXfCVlVWDRUqQFP4iyWjYsIiTjdAunuZAY2AM8BDQP9Jg9wqXI7VftFf4ikgiatoU+vaFxYu/0dIhA1h7DG8/CpRccgknqtlb0tKWv0iyGjcutOumGr464QQGrF/PI488wldffRXjwiQRKPxFklXHjqEmbenpx/e+9HROePhhHt24keeff56LL76Ybdu21UyNEhiFv0gyy8v79y8As8rHmoXGhbt6nn/++bz++usMHTqUiy++mHvvvZcvv/wyPnVLjVP4iyS7vLxQk7aBA0NnAJXdFZSWFpo+cGBoXKlunnXq1OHmm29m06ZNvPnmm3Ts2JHNmzfH+R8gNSGqfv41SV09RWrA/v2hlg1FRaELuBo3Dp3OOWxYlXfycnfmz5/P6NGjGT58OOPHjyetmscUpOYca1dPhb+IHJd9+/Zxyy23sGXLFubMmUO3bt2CLklKiddtHEUkxTRt2pTnnnuOKVOmMGTIEEaOHMknn3wSdFlynBT+IlItl19+OcXFxRw+fJisrCxWrFgRdElyHBT+IlJtp556KnPmzOHJJ59k5MiRXHfddXz44YdBlyXHQOEvIlHr2bMnRUVFNGnShMzMTBYuXEiiHk+UEIW/iMTEiSeeyIMPPsiiRYuYOHEigwYN4m9/+1vQZUkFFP4iElNdunRh8+bNZGdn07ZtW5544gn9FZCAogp/M/uWma00s+3hrxU2/zazU8zsAzP7dTTrFJHE16BBAyZOnMiqVat47LHH6N27Nzt37gy6LCkl2i3/scBqd28FrA6/rshk4PdRrk9EapHs7GzWrVtHnz596NSpEw899JAaxSWIaMN/ADAv/HwecHmkQWbWATgdeDXK9YlILVOvXj3GjBnD+vXrWbx4MRdddBHvvPNO0GWlvGjD/3R33xN+/ndCAf8NZlYHmE7ovhGVMrMRZlZgZgX79++PsjQRSSTnnXcer732GsOHD6d79+5MnjyZL774IuiyUlaV4W9mq8ysOMJjQOlxHjqiE+mozs3Acnf/oKp1uftsd89x95wM3URCJOnUqVOHG2+8kbfffpsNGzaQk5NDfn5+0GWlpCrv5OXuvSqaZ2Z7zayZu+8xs2aEbhFaVlegm5ndDJwE1DezT929suMDIpLEmjdvztKlS3n22Wfp168f1113HRMmTCD9eO89INUW7W6fJcD14efXAy+VHeDuQ929hbufTWjXz1MKfhExM66++mqKiorYtWsXbdq04fXXXw+6rJQRbfjfD/Q2s+1Ar/BrzCzHzOZEW5yIJL+MjAyeffZZpk+fzrXXXstNN93EwYMHgy4r6UUV/u7+obv3dPdW7t7L3T8KTy9w9xsijJ/r7j+PZp0ikpz69+9PcXEx7k5WVhbLli0LuqSkpit8RSRhNGrUiFmzZjFv3jxGjRrF0KFD0Zl/NUPhLyIJp0ePHhQWFtKsWTOysrJYsGCBWkTEmMJfRBJSeno606ZNY8mSJdx7770MGDCA3bt3B11W0lD4i0hC69SpE5s2baJDhw60bduW2bNnc/To0aDLqvUU/iKS8OrXr8/48eNZs2YNTzzxBD179mTHjh1Bl1WrKfxFpNbIzMzkrbfeol+/fnTp0oXp06erUVw1KfxFpFapW7cut912Gxs2bGDZsmV07dqV4uLioMuqdRT+IlIrnXvuuaxevZoRI0bQo0cPJkyYoEZxx0HhLyK1lplxww03sGXLFjZv3kz79u3ZuHFj0GXVCgp/Ean1zjrrLF566SXuueceBgwYwOjRozl06FDQZSU0hb+IJAUz46qrrqKoqIi9e/eSlZXFa6+9FnRZCUvhLyJJ5bTTTuOZZ57hkUceYdiwYfzsZz/j448/DrqshKPwF5GkdNlll1FcXEy9evXIzMxkyZIlQZeUUBT+IpK0TjnlFGbOnMn8+fMZPXo0gwcPZt++SPecSj0KfxFJepdccgmFhYW0bNmS7Oxs5s+fn/KN4hT+IpIS0tLSmDJlCi+//DJTpkyhX79+7Nq1K+iyAqPwF5GUkpOTQ0FBAV26dKF9+/Y89thjKdkoLqrwN7NvmdlKM9se/tq4gnEtzOxVM9tmZu+a2dnRrFdEJBr169fn7rvvZu3atcybN48ePXqwffv2oMuKq2i3/McCq929FbA6/DqSp4AH3P37QCdAR1xEJHCtW7fmzTffZNCgQXTt2pWpU6dy5MiRoMuKi2jDfwAwL/x8HnB52QFm1hqo5+4rAdz9U3fXpXcikhDq1q3LqFGj2LhxI6+++ipdunRh69atQZdV46IN/9PdfU/4+d+B0yOMOR/42MxeNLO3zewBM6sb5XpFRGLqO9/5DitXruTmm2+md+/e3HPPPRw+fDjosmpMleFvZqvMrDjCY0DpcR46byrSuVP1gG7AGKAj8B1gWAXrGmFmBWZWoJs2i0i8mRk//elP2bJlC8XFxbRr145169YFXVaNqDL83b2Xu2dGeLwE7DWzZgDhr5H25X8AbHH3ne5+BFgMtK9gXbPdPcfdczIyMqr/rxIRicKZZ57Jiy++yMSJExk0aBC33norn376adBlxVS0u32WANeHn18PvBRhTD5wqpl9neY/BN6Ncr0iIjXKzPjJT35CcXExBw4cICsri5UrV1b9xn37YOpUuOYa6Ncv9HXqVEiwvRkWzVVuZtYEWAi0AN4HrnT3j8wsB7jJ3W8Ij+sNTAcM2ASMcPdK77qQk5PjBQUF1a5NRCSWVqxYwU033URKUWnZAAAGwklEQVSvXr2YNm0ajRuXObM9Px/uuw9WrAi9/vzzf89LSwN36NsXxo2Djh1rrE4z2+TuOVWNi2rL390/dPee7t4qvHvoo/D0gq+DP/x6pbtnu3uWuw+rKvhFRBJN3759KS4uJi0tjczMTBYtWvTvmTNnQvfusHhxKPRLBz9ASUlo2uLFoXEzZ8az9Iii2vKvSdryF5FE9cYbb5Cbm0vbtm2Z06EDp0yaBMdz85j0dJg2DfLyYl5bXLb8RURSUbdu3di6dSuXpKdTb+zYcsH/ayAHaEAFpzYeOgRjxkCAG7gKfxGRakhLS2PkJ5+QZlZu3pnA3cBPK1tASUnoGEFAFP4iItWxbx+sWIFF2HU+iFC7gyaVvd8dli8P7Cwghb+ISHXMnRv9Msxis5xqUPiLiFRHYWH5s3qOV0kJFBXFpp7jpPAXEamOgwdjs5wDB2KznOOk8BcRqY5GjWKznLIXi8WJwl9EpDqys6Fhw4izjgCfA1+FH5+Hp5WTlgZZWTVVYaUU/iIi1TFsWIWz/gdIA+4Hngk//59IA90rXU5NUviLiFRH06ahXj0RzvOfQKi/fenHhLKDzODSSyGgDsYKfxGR6ho3LrTrpjrS0kLvD4jCX0Skujp2DPXoSU8/vvd93dsnp8oWPDWmXmBrFhFJBl83ZxszJnTefmXNMs1CW/w11NTteGjLX0QkWnl5sHYtDBwYOgOo7K6gtLTQ9IEDQ+MCDn7Qlr+ISGzk5MALL4R69cydG7py98CB0Hn8WVmhs3oS6Pa0Cn8RkVjKyIDbbw+6iipFtdvHzL5lZivNbHv4a8RL1cxsqpm9Y2bbzOwRswjnRomISNxEu89/LLDa3VsBq8Ovv8HMLgQuArKBTKAjcEmU6xURkShEG/4DgHnh5/MItbAuy4GGQH1CN7Y5Adgb5XpFRCQK0Yb/6e6+J/z878DpZQe4+zpgDbAn/HjF3bdFuV4REYlClQd8zWwVcEaEWXeVfuHubmblTnA1s/OA7wPNw5NWmlk3d38jwtgRwAiAFi1aVF29iIhUS5Xh7+69KppnZnvNrJm77zGzZsC+CMMGAuvd/dPwe1YAXYFy4e/us4HZADk5OZVcKSEiItGIdrfPEuD68PPrgZcijPkrcImZ1TOzEwgd7NVuHxGRAEUb/vcDvc1sO9Ar/BozyzGzOeExzwPvAUXAVmCruy+Ncr0iIhIF88r6UATIzPYD7wew6tOAfwSw3kSmz6Q8fSbl6TMpL4jPpKW7V3kpccKGf1DMrMDdg2u1l4D0mZSnz6Q8fSblJfJnosZuIiIpSOEvIpKCFP7lzQ66gASkz6Q8fSbl6TMpL2E/E+3zFxFJQdryFxFJQSkd/mb2k3Cr6aNmVuEReTPrY2Z/MrMdZlauc2myOY5W3V+Z2ZbwY0m864yHqr73ZtbAzJ4Lz99gZmfHv8r4OobPZJiZ7S/1f+OGIOqMFzN70sz2mVlxBfMt3Mp+h5kVmln7eNcYSUqHP1AMDAJ+X9EAM6sLzAD6Aq2BIWbWOj7lBabKVt1hJe7eNvzoH7/y4uMYv/e5wAF3Pw94EJgS3yrj6zh+Hp4r9X9jToT5yWQu0KeS+X2BVuHHCGBmHGqqUkqHv7tvc/c/VTGsE7DD3Xe6+xfAAkKtrJPZsbTqTgXH8r0v/Vk9D/RM8psVpeLPQ6Xc/ffAR5UMGQA85SHrgVPDvdACldLhf4zOAnaVev1BeFoyq7JVd1hDMysws/Vmloy/II7le/+vMe5+BDgINIlLdcE41p+HK8K7OJ43s2/Hp7SElZAZkvT38K2sJbW7R2pElxKibdUd1tLdd5vZd4DXzKzI3d+Lda1S6ywFnnX3w2Z2I6G/jH4YcE1SRtKHf2UtqY/RbqD0lkvz8LRaLQatunH33eGvO83sdaAdoSZ+yeJYvvdfj/nAzOoBjYAP41NeIKr8TNy99L9/DjA1DnUlsoTMEO32qVo+0MrMzjGz+sBgQq2sk1mVrbrNrLGZNQg/P43QfZrfjVuF8XEs3/vSn9WPgdc8uS+eqfIzKbM/uz9q4b4EuC581k8X4GCp3arBcfeUfRC60cwHwGFC9xV+JTz9TGB5qXGXAv9HaKv2rqDrjsPn0oTQWT7bgVXAt8LTc4A54ecX8u823UVAbtB119BnUe57D0wC+oefNwT+F9gBbAS+E3TNCfCZ3Ae8E/6/sQb4XtA11/Dn8SyhW9R+Gc6TXOAm4KbwfCN0htTXre1zgq7Z3XWFr4hIKtJuHxGRFKTwFxFJQQp/EZEUpPAXEUlBCn8RkRSk8BcRSUEKfxGRFKTwFxFJQf8PZsVNarbkNrQAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80de32e8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "8\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'S', 4: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80ddfa58>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "9\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'S', 4: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e01a20>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "10\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80de75f8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "11\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80dd3e48>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "12\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80dd3978>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "13\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'O', 5: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e5d748>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "14\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'O', 5: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e992b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "15\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d3ff98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "16\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'O', 5: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d08b00>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "17\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'O', 5: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d14dd8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "18\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c85cf8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "19\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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1QfDRRx9x5plnUlhYyC9/+Usuuugi+vbt2xa9F2mWTATDYGBL3PJWoCBVG3evMbO9wInh+k8SXjs42YeY2UxgJsDQoUMz0G2RFqqqCk40pzjKfhk4ATgfqEzWwJ1Db73FD/v3p8+wYRQWFnLrrbfy+9//nv79+7ddv0VaqANcw9Y87j4PmAfBUFKWuyPdUSMlK/8KPAAsAp5t5C2Oyslh1a9+xfEPPZTZvolkUCZud9wGnBa3PCRcl7SNmeUAfQlOQjfntSIdQyMlK/8nwRUUSeYZjcg5dIjjN23KdM9EMioTwVAKjDSz082sJ3A9sCChzQKC8q4QnJdb5MFZ7wXA9WbWy8xOB0YCyzPQJ5HMS1GychXBVRO/au77qGSldHBpDyWF5wzuBEoILld93t3LzexhoMzdFwDPAS+GJ5d3E4QHYbtXCU5U1wA/b+qKJJH2tGvXLpYvX86yZcu4eMUKJiVpswT4Aqg787WP4NrrdcCnyd5UJSulg8vIOQZ3LwaKE9Y9EPe8GrguxWv/GfjnTPRDJB3V1dWsXLmyPgiWLVvGrl27iMVi5Ofnc9Kll1L72msclTCcNJPwL53QHIKgmJvsQ1SyUjqBTnPyWSSTamtrqaioqA+A5cuXU15ezllnnUVBQQGXXXYZ999/P6NHj/5+wrmqKnjttQbv1Sd81DkOOAZIOkuSSlZKJ6BgkG6hqqqqPgCWLVtGaWkpffv2paCggIKCAqZPn8748eMbv6P4pJOSlqxM9GCqDSpZKZ2EgkG6nP3797Ny5crI0cCePXvIz88nPz+fu+66i/z8fAYNGtTyN1fJSukGFAzSqdXW1rJhw4bI0cCGDRsYM2YMBQUFXHHFFTz00EOMGjUqM8VoVLJSugEFg6SW5ToDyWzfvj1ycrisrIwBAwbUDwndeOONnHvuuW0726hKVkoXp2m3paEs1RlI9N1337FixYrI0cB3331XPyRUUFBAfn4+AwYMaLM+NKqsTCUrpVNRPQZpnXasMxDvyJEjrFu3LnI0UFFRwdixY+uPBvLz8xkxYkRmCtVnkkpWSifRrvUYpIto4zoD8bZu3VofAsuXL2fFihWcfPLJ9SFQV5u4V69erfhG2plKVkoXoyMGCTRSZ+C/AO8D3wEnA/cAt8Q3SFFnoM63335LWVlZZEjo0KFD9UcBBQUFTJgwQTOMirQxHTFIyzRSZ+A+gjlNegEbgInAuQTl+ID6OgO88QY1NTWsXbs2MiS0adMm8vLyKCgo4Kc//Slz5szh9NNP73hDQiICKBgEmqwzcHbccwsffyEuGNw5/PbbXPOjH7GkvJwhQ4bUHw3ccccd5ObmcvTRR7fptyAimaNgkEbrDNS5A5gPHCA4WihKbGDGr3NzGVRSoupjIp1cJqbdls6ukToDdX4LfAv8CbiGYFgp3tE1NYyqrlYoiHQBCoZurqamhm+3bm1W2x7ABQT1V5POHKo6AyJdgoaSupFvvvmGNWvWsGrVKlavXs2qVatYv349L+XkMK0F71NDcI6hAdUZEOkSFAxdUG1tLV988UV9ANSFwK5du8jNzSUvL48JEybws5/9jHPOOYfjfvtbmD076XBSFUEd4/8E9CaoVPZS+IhQnQGRLkP3MTSmA84VlOjAgQOsXbs2EgJr1qzhBz/4AePGjSMvL4+8vDzGjRvHmWeemXwiuaoqGDYsaTDsJKjFuhqoBYYBvwB+ltjwmGPgyy87zH4RkYY0JUY6OshcQfHcnR07dtT/9V/3dfPmzYwaNao+BMaNG0dubi4nnnhiyz7gmmuarDOQkhlcfTW88UbLXysi7UbB0FpZmiso3uHDh9m4cWODoaDa2toGRwGjR4+mZ8+e6X9oI3c+N6mJO59FpGPQnc+tkTBX0NME1+5/BkwPn9dLc66gOt98803kKGD16tWsX7+eoUOH1gfArFmzyMvL49RTT227u4VVZ0BEQjpiqJPkL+Y3Ca7nLSG4sWt+qtc24y/m2tpaNm3a1GAoaPfu3fUnhOuOAs455xyOPfbYTH1nLdMBjphEpG1oKKmlGhlj/x8E1+7PT/XahDH2/fv3Jz0h3K9fv0gA5OXlccYZZ2Smslgmqc6ASJekoaSWaGKuoCa5U7NgAbdfdRX/d+NGNm/ezOjRo+tD4LrrriM3N7fzzB4aiwUhpzoDIt2SggGaNVdQU2qB23r35hevvsro0aO7xqRxqjMg0i2lNYZhZv3NbKGZVYRfk976amYzwjYVZjYjXNfHzN4xsw1mVm5mj6fTl7Q0Y66gpvSsqeFvjj6asWPHdo1QEJFuK93B7XuB9919JEEtl3sTG5hZf2A2UADkA7PjAmSOu48mmLDzb81sapr9aZ29ezPzPporSES6gHSDYRrwQvj8BeCqJG0uBxa6+2533wMsBKa4+353Xwzg7oeAT4EhafandVLMCFoDVANHwkd1uC4lzRUkIl1AusEwyN23h893AIOStBkMbIlb3hquq2dmJwBXEhx1tL/c3GBKhwSPEswP9Djwu/D5o6neQ3MFiUgX0WQwmNl7ZrY2ySMyIacH1722+LIeM8shmJPt39z980bazTSzMjMr27lzZ0s/pnE33ZR09YME31D848FU7+Ge8n1ERDqTJoPB3S9193OSPN4GvjKzUwDCr1VJ3mIbcFrc8pBwXZ15QIW7P9VEP+a5e8zdYwMzfankSScFcx+19q5is+C6fl3CKSJdQLpDSQuAGeHzGcDbSdqUAJPNrF940nlyuA4zexToC8xKsx/pu+++YDioNXr3Dl4vItIFpBsMjwOXmVkFcGm4jJnFzOxZAHffDTwClIaPh919t5kNAe4HxgCfmtkqM7slzf60Xt1cQX36tOx1mitIRLoYTYmRSHMFiUgX1dwpMTrYJD0dwO23BxPiXX11cKVS4vBS797B+quvDtopFESki9GUGMloriAR6cYUDI3RXEEi0g1pKElERCIUDCIiEqFgEBGRCAWDiIhEKBhERCRCwSAiIhEKBhERiVAwiIhIhIJBREQiFAwiIhKhYBARkQgFg4iIRCgYREQkQsEgIiIRCgYREYlQMIiISISCQUREIhQMIiISoWAQEZEIBYOIiEQoGEREJCKtYDCz/ma20Mwqwq/9UrSbEbapMLMZSbYvMLO16fRFREQyI90jhnuB9919JPB+uBxhZv2B2UABkA/Mjg8QM7sG2JdmP0REJEPSDYZpwAvh8xeAq5K0uRxY6O673X0PsBCYAmBmxwH/DXg0zX6IiEiGpBsMg9x9e/h8BzAoSZvBwJa45a3hOoBHgF8D+9Psh4iIZEhOUw3M7D3g5CSb7o9fcHc3M2/uB5vZOOBMd/+VmQ1vRvuZwEyAoUOHNvdjRESkhZoMBne/NNU2M/vKzE5x9+1mdgpQlaTZNmBi3PIQYAlwHhAzsy/CfpxkZkvcfSJJuPs8YB5ALBZrdgCJiEjLpDuUtACou8poBvB2kjYlwGQz6xeedJ4MlLj7XHc/1d2HAxcAf04VCiIi0n7SDYbHgcvMrAK4NFzGzGJm9iyAu+8mOJdQGj4eDteJiEgHZO6db1QmFot5WVlZtrshItKpmNkKd4811U53PouISISCQUREIhQMIiISoWAQEZEIBYOIiEQoGEREJELBICIiEQoGERGJUDCIiEiEgkFERCIUDCIiEqFgEBGRCAWDiIhEKBhERCRCwSAiIhEKBhERiVAwiIhIhIJBREQiFAwiIhKhYBARkQgFg4iIRCgYREQkQsEgIiIRCgYREYlQMIiISERawWBm/c1soZlVhF/7pWg3I2xTYWYz4tb3NLN5ZvZnM9tgZj9Jpz8iIpK+dI8Y7gXed/eRwPvhcoSZ9QdmAwVAPjA7LkDuB6rcfRQwBliaZn9ERCRN6QbDNOCF8PkLwFVJ2lwOLHT33e6+B1gITAm3/VfgMQB3r3X3XWn2R0RE0pRuMAxy9+3h8x3AoCRtBgNb4pa3AoPN7IRw+REz+9TMXjOzZK8HwMxmmlmZmZXt3LkzzW6LiEgqTQaDmb1nZmuTPKbFt3N3B7wFn50DDAE+cvfxwMfAnFSN3X2eu8fcPTZw4MAWfIyIiLRETlMN3P3SVNvM7CszO8Xdt5vZKUBVkmbbgIlxy0OAJcDXwH7gzXD9a8DNzeu2iIi0lXSHkhYAdVcZzQDeTtKmBJhsZv3Ck86TgZLwCOM/+D40LgHWpdkfERFJU7rB8DhwmZlVAJeGy5hZzMyeBXD33cAjQGn4eDhcB/BPwINmtgb4e+C/p9kfERFJkwV/uHcusVjMy8rKst0NEZFOxcxWuHusqXa681lERCI65RGDme0ENrfzxw4AdJ9FlPZJQ9onDWmfNJStfTLM3Zu8rLNTBkM2mFlZcw7BuhPtk4a0TxrSPmmoo+8TDSWJiEiEgkFERCIUDM03L9sd6IC0TxrSPmlI+6ShDr1PdI5BREQidMQgIiIRCoYUzOw6Mys3s1ozS3n1gJlNMbONZlZpZg3qUXQlLSjMdMTMVoWPBe3dz/bQ1M/dzHqZ2Svh9mVmNrz9e9m+mrFPbjKznXH/Nm7JRj/bk5k9b2ZVZrY2xXYzs38L99kaMxvf3n1MRsGQ2lrgGuCDVA3MrAfwG2AqQaGh6WY2pn26lxVNFmYKHXD3ceHjx+3XvfbRzJ/7zcAedx8BPAk80b69bF8t+L/wSty/jWfbtZPZMZ/v688kMxUYGT5mAnPboU9NUjCk4O7r3X1jE83ygUp3/9zdDwEvExQv6qqaU5ipO2jOzz1+X70OXGJm1o59bG/d7f9Cs7j7B8DuRppMA/7dA58AJ4QzVWeVgiE9SYsQZakv7aE5hZkAjgmLKn1iZl0xPJrzc69v4+41wF7gxHbpXXY09//CT8Ihk9fN7LT26VqH1iF/hzRZj6ErM7P3gJOTbLrf3ZNNId7lNbZP4hfc3c0s1SVtw9x9m5mdASwys8/c/S+Z7qt0Ov8BvOTuB83sVoIjqklZ7pMk0a2DobEiRM20DYj/q2dIuK7TykBhJtx9W/j1czNbApwLdKVgaM7Pva7NVjPLAfoSFKfqqprcJ+4e//0/C/xLO/Sro+uQv0M0lJSeUmCkmZ1uZj2B6wmKF3VVTRZmCgsy9QqfDwD+lq5XgKk5P/f4fXUtsMi79k1DTe6ThLHzHwPr27F/HdUC4Mbw6qQfAXvjhmuzx931SPIAriYY7zsIfEVQdQ7gVKA4rl0R8GeCv4jvz3a/23ifnEhwNVIF8B7QP1wfA54Nn58PfAasDr/enO1+t9G+aPBzBx4Gfhw+P4agXG0lsBw4I9t97gD75DGgPPy3sRgYne0+t8M+eQnYDhwOf5/cDNwG3BZuN4Kruf4S/n+JZbvP7q47n0VEJEpDSSIiEqFgEBGRCAWDiIhEKBhERCRCwSAiIhEKBhERiVAwiIhIhIJBREQi/j9KaERLa2U3xQAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c89ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "20\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80cabc50>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "21\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'S', 5: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f87eb8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "22\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'S', 5: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f81630>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "23\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'S', 5: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c930f0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "24\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'S', 5: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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yzzcSdAeJ1E5xccVRPWUcBUYBLYCHK2tUWgpbt0a/NpEGLCrhL1JvqrgrmBOM+PmY4MyjeVX72bcvqmWJNHQKf0lsrVtXuiqboJ/xL0BKdftJS4teTSKNQEIN9RSpID0dWrWqsPgD4L+BLcCpwLdCjyfD7SMlBbp2rcciRRoehb8ktqyssIvPJOj2OQh8Xubxk3CN3Svdj0iyUvhLYjv55GCuHrM6bX4EeL1NGz4+qplFRMpS+EvimzQp6Lqpgyapqbw2YADp6ek8/vjjuoOYSIjCXxJfZibk5kJqau22S03FcnP52R/+wAsvvMDcuXO5+OKLeffdd+unTpEGROEvDUN29tcfANV1AZkF7XJzg+2AHj168NprrzF06FAuuOACZsyYwaFDh2JQuEhiUvhLw5GdDatXw/DhwQig8l1BKSnB8uHDg3ah4D+mWbNm/Od//iebNm1i7dq1nHfeeWzYsCGGfwCRxBHxzVzqi27mIlXasyeYsmHr1uACrrS0YDhnVhbUYFJAd2fRokWMHz+eq6++munTp/Ptb3+73ssWqW81vZmLwl+S2t69e/nFL37BSy+9xMMPP8zQoUPjXZJIRGJ5Jy+RBuvEE0/k97//PfPnzycnJ4err76ajz76KN5lidQ7hb8IMGDAAN588006d+5Mt27deOSRRziqawOkEVP4i4SkpKRw7733snLlSubNm0e/fv14++23412WSL1Q+IuU07VrV9atW8eIESO46KKLuOuuu/jiiy/iXZZIVCn8RcJo2rQpt9xyC2+88QabN2+mR48erF27Nt5liUSNwl+kCu3ataOgoIB77rmHa665huzsbP75z3/GuyyRiCn8RaphZlx11VVs374dd+fcc89lyZIlmidIGrSohL+ZXW5mO8zsPTObGGZ9SzNbFFq/wcw6ROO4IrF0wgkn8Lvf/Y5FixYxefJkhg8fzu7du+NdlkidRBz+ZtYUmAsMBM4BRprZOeWa3QDsc/fvAg8AsyI9rki89OnThy1bttCjRw969OjBww8/zJEjR+JdlkitROPMvxfwnru/7+6HgKeAYeXaDAPmh54vBi42q+ME7SIJoGXLlkydOpU1a9awaNEi+vTpw1bdJF4akGiE/+nArjKvd4eWhW3j7oeB/cBJUTi2SFydffbZrF69muuvv54f/OAHTJ48mYMHD8a7LJFqJdQXvmY21syKzKxoz5498S5HpEaaNGnC2LFjKS4uZseOHaSnp7Nq1ap4lyVSpWiE/4fAGWVetwstC9vGzJoBrYFPy+/I3R9x9wx3z2hbg5kZRRLJaaedxjPPPENubi6jRo3ixhtvZO/evfEuSySsaIT/RqCjmZ1lZi2AEcCycm2WAaNDz/8NeNk1Tk4aqaFDh7J9+3ZSUlI499xzeeqppzQsVBJOxOEf6sO/FVgBvA087e7bzexuMzs2P+7vgZPM7D3gNqDCcFCRxuT444/noYce4tlnn2X69OkMHjyYDz74IN5liXwlKn3+7l7o7p3c/V/dfXpo2RR3XxZ6ftDdr3b377p7L3d/PxrHFUl0559/Pps2baJ3796cd955PPDAAxoWKgkhob7wFWmMWrRowX/913+xfv16/vznP3P++eezZcuWeJclSU7hLxIjHTt2ZOXKlYwbN47LLruMCRMmcODAgXiXJUlK4S8SQ2bG9ddfT3FxMbt27aJr16689NJL1W9YUgKzZ8N118GQIcHP2bODexmL1IHu4SsSR4WFhYwbN46LLrqIX/3qV7Rp0+abDTZuhJkzYfny4HXZC8hSUsAdBg6ESZMgMzN2hUvC0j18RRqAQYMGsW3bNtq0acP3vvc9nnjiia+HheblQf/+UFAQhH75K4dLS4NlBQVBu7y8WJcvDZjO/EUSRFFRETfddBNt27blyb59aXvffVCb7wRSUyE3F7Kz669ISXg68xdpYDIyMnj99dcZ1aULx02ZUiH4rwNOA44HOgGPld/BgQOQkwM6aZIaUPiLJJDmzZszavduUsJMejsJ+B/gM4JL5icDm8o3Ki0NviMQqYbCXySRlJTA8uVYmO7Yc4GWoecWevytfCN3KCzUKCCplsJfJJHk51e5ehyQCnQh6AIaFK6RWbX7EVH4iySS4uKKo3rK+C3wf8ArwJV8/T+BbygtBd1YRqqh8BdJJPv3V9ukKdCH4K5JlQ7u3LcvejVJo6TwF0kkrVvXuOlhwvT5H5OWFo1qpBFT+IskkvR0aNWqwuISgptjfw4cIZg/fSFwcbh9pKRA1671WKQ0Bgp/kUSSlRV2sRF08bQD0oAc4NfA0HCN3Svdj8gxzeJdgIiUcfLJwVw9BQVBiIe0BVbXYPMjwIG+ffm2boMq1dCZv0iimTQp6Lqpg6PNmzP89deZO3eubh0pVVL4iySazMxgjp7U1Nptl5pK8wcfZO6GDcyfP5/LL7+cDz/8sH5qlAZP4S+SiLKzv/4ACDPVwzeYfWNSt86dO7Nu3TouvPBCevTowaJFi2JTszQoEYW/mZ1oZi+Z2buhn2HHl5nZC2b2TzN7LpLjiSSV7GxYvRqGDw9GAJXvCkpJCZYPHx60KzObZ/PmzZk6dSrPP/88U6dO5dprr2Wfxv5LGZGe+U8EVrp7R2Bl6HU49wOjIjyWSPLJyIAlS+Dvf4e77oJRo2Dw4ODnXXcFy5csCdqFkZmZyebNmznppJNIT0+v2V3DJClENJ+/me0A+rv7R2Z2GrDK3TtX0rY/kOPug2uyb83nLxJdL730EmPGjOFHP/oRs2bNIrW23ylIgxCr+fxPcfePQs//AZwS4f5EpJ5ceumlFBcX8+mnn9KzZ082btwY75IkjqoNfzP7i5ltC/MYVradB/+FiGhsmZmNNbMiMyvaoylpRaIuLS2NBQsWcNddd3HFFVcwbdo0vvzyy3iXJXFQbfi7+yXu/r0wj6XAx6HuHkI/SyIpxt0fcfcMd89oq4tUROrNNddcwxtvvMH69evp3bs3O3bsiHdJEmORdvssA0aHno8Glka4PxGJkdNPP50XXniB0aNH07t3b10YlmQiDf/7gEvN7F3gktBrzCzDzL66xaiZvQI8A1xsZrvN7LIIjysiUWBm3HLLLaxbt04XhiWZiMLf3T9194vdvWOoe2hvaHmRu99Ypl1fd2/r7inu3s7dV0RauIhET/kLw5566ql4lyT1TFf4igjwzQvDpk2bxsiRI9m7d2+8y5J6ovAXkW84dmFY27Zt6datGy+++GK8S5J6oPAXkQpSU1P5zW9+w7x587jhhhu49dZbOXDgQLzLkihS+ItIpY5dGLZv3z569OihC8MaEYW/iFQpLS2NJ598krvvvpvBgwfrwrBGQuEvIjVyzTXXsHnzZl577TUuvPBC3nnnnXiXJBFQ+ItIjZ1++uksX76c66+/nj59+vDQQw9x9OjReJcldaDwF5FaMTPGjRvHq6++yh//+EddGNZAKfxFpE46derEunXr6Nu3Lz169GDhwoXxLklqQeEvInXWrFkzfvnLX1JYWMjdd9/NiBEjdGFYA6HwF5GIZWRksHnzZk455RTS09NZsUIzuCQ6hb+IREVKSgoPPvgg+fn53HTTTbowLMEp/EUkqi655BLefPPNry4Me/311+NdkoSh8BeRqDt2Ydg999zDkCFDmDp1qi4MSzAKfxGpNz/+8Y9544032LBhQ80uDCspgdmz4brrYMiQ4Ofs2aDbukadwl9E6tV3vvMdli9fzpgxY+jTpw+/+c1vKl4YtnEjXHklnHkmTJ0KTz4Jzz0X/Jw2Ddq3D9ZrbqGoUfiLSL0zM7Kzs1m/fj0LFizgsssuY/fu3cHKvDzo3x8KCuDgweBRVmlpsKygIGiXlxfr8hslhb+IxEzHjh1Zu3Yt/fr1o2fPnrw+ZgyekwMHDkDo/sH9gVbAt0KPzsc2dg/a5eToAyAKIgp/MzvRzF4ys3dDP9PCtOluZuvNbLuZFZvZNZEcU0QatmbNmjF58mRW5+bSNT8fCzMc9GHg89BjR/mVxz4Aiorqv9hGLNIz/4nASnfvCKwMvS7vAPDv7n4ucDnwazM7IcLjikgDd3ZBAa3qunFpKcycGc1ykk6k4T8MmB96Ph/4UfkG7r7T3d8NPf9foARoG+FxRaQhKymB5cuxUFdPeZOANkBvYFW4Bu5QWKhRQBGINPxPcfePQs//AZxSVWMz6wW0AP4W4XFFpCHLz6901SzgfeBDYCwwhEoCw6zK/UjVmlXXwMz+ApwaZtWdZV+4u5tZ+I/xYD+nAU8Ao9097ATgZjaW4PdN+/btqytNRBqq4uKKo3pCvl/m+WhgIVAI/Ef5hqWlsHVrvZSXDKoNf3e/pLJ1ZvaxmZ3m7h+Fwr2kknbHA88Dd7r7a1Uc6xHgEYCMjIxKP0hEpIHbv7/GTQ2oNAz27YtGNUkp0m6fZQQfzoR+Li3fwMxaAM8Cf3D3xREeT0Qag9atwy7+J7ACOAgcBp4E1hCMFAkrrcIAQ6mhSMP/PuBSM3sXuCT0GjPLMLPHQm1+DFwEZJnZltCje4THFZGGLD0dWlUc6/MlMJlgREgb4CGgAOgUbh8pKdC1az0W2biZV/Jte7xlZGR4kcbxijROJSXBVA6V9PvXSKtW8Pe/Q1sNHizLzDa5e0Z17XSFr4jE3sknw8CBwYidOjhqBoMGKfgjoPAXkfiYNCnouqmDg8D0o0d1s5gIKPxFJD4yMyE3F1JTa7ddaio2Zw7bU1Lo1asX27dvr5/6GjmFv4jET3b21x8A1XUBmQXtcnNJGT+eJ598kttuu41+/frx6KOPkqjfXyYqhb+IxFd2NqxeDcOHB1/ilu8KSkkJlg8fHrTLzgaCaaLHjBnDK6+8wkMPPcTIkSPZX4vrB5KdRvuISOLYsyeYsmHr1uACrrS0YDhnVlaVX+6WlpZy++23s2LFChYuXEivXr1iVnKiqeloH4W/iDQaS5YsITs7mwkTJjB+/HiaNEm+zg0N9RSRpHPVVVfx+uuvs3jxYgYPHswezfpZKYW/iDQqHTp0YM2aNXTr1o0ePXrw8ssvx7ukhKTwF5FGp3nz5sycOZN58+Zx3XXX8ctf/pLDhw/Hu6yEovAXkUbrhz/8IZs3b+a1115jwIAB7Nq1K94lJQyFv4g0aqeeeiorVqzgiiuuICMjg6VLK0w+nJQU/iLS6DVp0oSJEyfy7LPP8vOf/5yf/exnfPHFF/EuK64U/iKSNC688ELeeOMNPvzwQy644AJ27twZ75LiRuEvIkklLS2NxYsXc9NNN9G7d2+eeOKJeJcUFwp/EUk6ZkZ2djYrV65kxowZZGVl8fnnn8e7rJhS+ItI0kpPT6eoqIgmTZpw3nnnsWXLlniXFDMKfxFJascddxzz5s1jypQpXHrppcydOzcpZghV+IuIAD/5yU949dVXmTdvHldeeSV79+6Nd0n1KqLwN7MTzewlM3s39DMtTJszzWxz6Mbt283s5kiOKSJSXzp27Mirr75Khw4d6NGjB+vWrYt3SfUm0jP/icBKd+8IrAy9Lu8j4AJ37w58H5hoZt+J8LgiIvWiZcuWPPDAAzz88MNcddVVzJgxgyNHjsS7rKiLNPyHAfNDz+cDPyrfwN0PufuxqylaRuGYIiL1bsiQIRQVFbFixQouu+wy/vGPf8S7pKiKNIhPcfePQs//AZwSrpGZnWFmxcAuYJa7/2+ExxURqXft2rXj5Zdfpk+fPvTs2ZMVK1bEu6SoqfZmLmb2F+DUMKvuBOa7+wll2u5z9wr9/mXWfwcoAIa4+8dh1o8FxgK0b9/+vA8++KBGfwgRkfq2atUqRo0axbXXXsu9995L8+bNwzcsKQnuRlZcDPv3Q+vWkJ4O119f5d3IoiUmd/Iysx1Af3f/yMxOA1a5e+dqtpkHFLr74qra6U5eIpJoPvnkE7Kysvjkk09YuHAhZ5111tcrN26EmTNh+fLg9cGDX69LSQF3GDgQJk2CzMx6qzFWd/JaBowOPR8NVJguz8zamVlK6Hka0AfYEeFxRURirk2bNvz5z3/mmmuu4fvf/z7PPPNMsCIvD/r3h4KCIPTLBj9AaWmwrKAgaJeXF+vSK4j0zP8k4GmgPfAB8GN332tmGcDN7n6jmV0KzAEcMOBhd3/RVWypAAAGQ0lEQVSkun3rzF9EEllRUREjRozgrtNO49pNm7DS0ppvnJoKubmQnR31unQDdxGRevb5X/9K80svpWW5oaAPA/nAVmBk6HkFqamwejVkVJvTtaIbuIuI1LNvPfQQLY4erbD8O8BkYExVG5eWBt8RxInCX0SkLkpKYPlyLEzvyZUEFz2dVNX27lBYCHv21FOBVVP4i4jURX5+5Pswi85+6kDhLyJSF8XFFUf11FZpKWzdGp16aknhLyJSF/v3R2c/+/ZFZz+1pPAXEamL1q2js5+0SidFqFcKfxGRukhPh1atwq46DBwEjoQeB0PLKkhJga5d66vCKin8RUTqIiur0lX3AinAfcAfQ8/vDdfQvcr91CeFv4hIXZx8cjBXj1mFVdMIpjQo+5hWvpEZDBoUk8newlH4i4jU1aRJQddNXaSkBNvHicJfRKSuMjODOXpSU2u33bG5faI8tUNtNIvbkUVEGoNjk7Pl5ATj9quaL80sOOOvp0ndakNn/iIikcrODiZpGz48GAFUvisoJSVYPnx40C7OwQ868xcRiY6MDFiyJJirJz8/uHJ3375gHH/XrsGonjh9uRuOwl9EJJratoVf/CLeVVRL3T4iIklI4S8ikoQU/iIiSUjhLyKShCIKfzM70cxeMrN3Qz8rnZ7OzI43s91m9nAkxxQRkchFeuY/EVjp7h2BlaHXlbkHWBPh8UREJAoiDf9hwPzQ8/kEt62swMzOA04BXozweCIiEgWRhv8p7v5R6Pk/CAL+G8ysCTAHyKluZ2Y21syKzKxoT5xuaiwikgyqvcjLzP4CnBpm1Z1lX7i7m1m4SS3GAYXuvtvCTH1abh+PAI8AZGRkVDFBhoiIRKLa8Hf3SypbZ2Yfm9lp7v6RmZ0GlIRpdgHQ18zGAd8CWpjZ5+5e1fcDIiJSj8yrmoGuuo3N7gc+dff7zGwicKK731FF+ywgw91vrcG+9wAf1Lm4umsDfBKH4yYyvScV6T0JT+9LRbF+T85092onEYp0bp/7gKfN7AaCoP4xgJllADe7+4113XFNiq8PZlbk7vGbZDsB6T2pSO9JeHpfKkrU9ySi8Hf3T4GLwywvAioEv7vnA/mRHFNERCKnK3xFRJKQwr+iR+JdQALSe1KR3pPw9L5UlJDvSURf+IqISMOkM38RkSSU1OFvZleb2XYzOxoaoVRZu8vNbIeZvRca0tqo1XTCPjM7YmZbQo9lsa4zFqr73ZtZSzNbFFq/wcw6xL7K2KvB+5JlZnvK/P2o88i/hsLM5plZiZltq2S9mdlvQu9ZsZn1jHWNZSV1+APbgCupYsI5M2sKzAUGAucAI83snNiUFzc1nbCv1N27hx5DY1debNTwd38DsM/dvws8AMyKbZWxV4t/E4vK/P14LKZFxkc+cHkV6wcCHUOPsUBeDGqqVFKHv7u/7e47qmnWC3jP3d9390PAUwQT2jVmNZqwLwnU5Hdf9r1aDFxs1c1j0vAl47+Jarn7GmBvFU2GAX/wwGvACaGZEeIiqcO/hk4HdpV5vTu0rDGrdsK+kFahifheM7PG+AFRk9/9V23c/TCwHzgpJtXFT03/TVwV6t5YbGZnxKa0hJZQWRLpFb4Jr6qJ6dx9aazrSRRRmLAPgsvIPzSzfwFeNrOt7v63aNcqDdKfgYXu/oWZ/ZTgf0c/iHNNUkajD/+qJqaroQ+Bsmct7ULLGrQoTNiHu38Y+vm+ma0CegCNKfxr8rs/1ma3mTUDWgOfxqa8uKn2fQld/X/MY8DsGNSV6BIqS9TtU72NQEczO8vMWgAjgEY5sqWMZcDo0PPRQIX/IZlZmpm1DD1vA/QG3opZhbFRk9992ffq34CXvfFfPFPt+1KuL3so8HYM60tUy4B/D436OR/YX6Z7NfbcPWkfwHCCfrcvgI+BFaHl3yG4B8GxdoOAnQRntXfGu+4YvC8nEYzyeRf4C8FsrQAZwGOh5xcCW4E3Qz9viHfd9fReVPjdA3cDQ0PPWwHPAO8BrwP/Eu+aE+R9mQlsD/39+CvQJd41x+A9WQh8BHwZypUbgJsJJrkEMIJRUn8L/ZvJiGe9usJXRCQJqdtHRCQJKfxFRJKQwl9EJAkp/EVEkpDCX0QkCSn8RUSSkMJfRCQJKfxFRJLQ/weinXIxYeKwpQAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80ef6908>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "25\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d592e8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "26\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d216a0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "27\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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PzN6MvObEnivp6bzzzmPWrFn88Ic/ZObMmWGHIyKN0OSmJDNrA/we+C6wCVhuZnPc/e2oYm8Aue6+y8yKgHuAH0SOVbj7SU2NQ5qfIUOGsGDBAkaOHMnWrVu55pprwg5JRBogETWGwcB6d3/P3b8EngJGRxdw94XuviuyuQzokYDPlTTwrW99iyVLlnDvvfdy5513ko5LyYq0NolIDEcBG6O2N0X21eZKYF7UdkczKzWzZWZ2fgLikWbmmGOOYenSpcyePZvrr7+e/fv3hx2SiNQhpQ+fzWwskAv8Kmp378ji1JcA95vZsbWcOz6SQEq3bNmSgmglkY488kgWLVrEypUrGTt2LF9++WXYIYlILRKRGD4EekZt94jsq8bMhgO3AaPc/cDEOu7+YeTne8Ai4OR4H+LuD7p7rrvnZmdnJyBsSbXDDz+c+fPn8/nnnzNq1Ci++OKLsEMSkTgSkRiWA33N7Ggzaw9cBFTrXWRmJwMPECSF8qj9mWbWIfI+CzgdiH5oLS1MRkYGs2bN4sgjj2T48OFs37497JBEJEaTE4O77wV+DMwH1gAz3f0tM/u5mY2KFPsVcBjw55huqccBpWa2ElgITInpzSQtUNu2bXn44Yc5/fTTGTJkCJs2bQo7JBGJkpCRz+4+F5gbs++nUe+H13LeX4ETExGDpJdDDjmEqVOnkpOTc2AKjf79+1cvVF4OxcWwahXs3AldusDAgXD55aDmRJGk0ZQYEqqbb76ZrKwshg4dynPPPUdubi4sXw6TJ8O8SOe13bu/OmHWLLjjDigogEmTYNCgcAIXacGUGCR0V1xxBV27dqWgoIAlP/whAx56CCoqIN6Yh4qK4GdJCcyfD1OnQlFRagMWaeGUGKRZOP/88zl+8WJ63H9/w05wh127YOLEYFvJQSRhNImeNA/Ll9PvwQfpFOfQUKAjQe+Fw4BqTyKqkkNpafJjFGkllBikeZg8+atmojh+B3weea2NPVhREZwvIgmhxCDhKy8PHjQf7DxK7jB3LmhEvEhCKDFI+IqL6y0yCagaAbkoXgGzBl1HROqnxCDhW7WqepfUGHcD7xHMszIeOA94N7ZQRQWsXp2sCEVaFSUGCd/OnXUePgX4GtABGEdQa5gbr+COHYmOTKRVUmKQ8HXp0qjiBsR9GpGZmYhoRFo9JQYJ38CB0LFj3EOfEEzCtRvYCzwBvAaMiC2YkQEnanYVkURQYpDwFRbWeqgSuB3IJnj4/N9ACdAvtqB7ndcRkYZTYpDw5eQEcx+Z1TiUTTCv+2cEtYdlBIuLV2MGI0dqYj2RBFFikOZh0qSgOegg7G3XLjhfRBJCiUGah0GDggnxOsWbFKN2+zt25KeHHsqvFy9OUmAirY8SgzQfRUVfJYc4zUrVmEGnThxy770UrVzJ9OnTufnmm/GDHT0tIgcoMUjzUlQEixfDmDFBT6XY5qWMjGD/mDFBuaIievbsydKlS1m6dCmXX345lZWV4cQu0kJYIn7DMrMRwG+ANsCf3H1KzPEOwGPAt4FtwA/c/f3IsUnAlcA+4Hp3n1/f5+Xm5nqpZtNs+bZsCaa5WL06GLyWmRl0SS0sjPugedeuXfzHf/wHZsbMmTPp1MhmKZGWzsxWuHtuveWamhjMrA3wDkFnkU0EnUgujl672cyuAQa6+/8xs4uAMe7+AzM7HngSGAx8HXgZ6Ofu++r6TCUGqU1lZSVXXXUV69at4/nnn6dr165hhyTSbDQ0MSSiKWkwsN7d33P3L4GngNExZUYDj0bePwMMMzOL7H/K3fe4+wZgfeR6IgelXbt2FBcXk5eXR15eHhs3bgw7JJG0k4jEcBQQ/b9vU2Rf3DLuvhfYCXRr4LkAmNl4Mys1s9Itml5Z6mBm3HPPPVx55ZXk5eWxZs2asEMSSStp8/DZ3R9091x3z83WQCZpgAkTJnDXXXeRn5/PsmXLwg5HJG0kIjF8CPSM2u4R2Re3jJm1BboQPIRuyLkiB+3SSy/lkUceYdSoUcydG3dOVhGJkYjEsBzoa2ZHm1l74CJgTkyZOQQzJgN8H3jVg6fec4CLzKyDmR0N9AX+XwJiEjmgoKCAOXPmcMUVV/D444+HHY5Is9e2qRdw971m9mOCSTDbAA+7+1tm9nOg1N3nANOBx81sPbCdIHkQKTcTeJtg8sxr6+uRJHIwTj31VBYuXMiIESMoLy9nwoQJYYck0mwlZBxDqqm7qhysjRs3MmLECEaOHMndd9/NIYekzWM2kSZLZXdVkbTRs2dPlixZwuuvv65R0iK1UGKQVqdr1668/PLLbNu2jfPPP58vvvgi7JBEmhUlBmmVOnXqxOzZs8nOzmb48OFs27Yt7JBEmg0lBmm12rVrxyOPPMIZZ5zBkCFDNEpaJKLJvZJE0pmZcffdd5OTk0NeXh4vvvgixx13XNhhiYRKiUGEYJT0EUccQX5+PrNnz+a0004LOySR0KgpSSRi7NixGiUtghKDSDUFBQU899xzXHHFFTz22GNhhyMSCjUlicSIHSU9ceLEsEMSSSklBpE4jjvuOF5//XXOOeccPv74Y42SllZF/9JFatGjRw+WLFnCX//6V42SllZFiUGkDl27dmXBggUaJS2tihKDSD00SlpaGyUGkQbQKGlpTfTwWaSBqkZJH3HEEeTl5TFv3jyOP/74sMMSSTglBpFGuvHGG8nJySE/P5+SkhKNkpYWp0lNSWbW1cwWmNm6yM/MOGVOMrO/mdlbZrbKzH4QdazYzDaY2ZuR10lNiUckVcaOHUtxcTGjR4/mhRdeCDsckYRq6jOGW4BX3L0v8EpkO9Yu4DJ3/yYwArjfzA6POn6Tu58Ueb3ZxHhEUqZqlPSVV16pUdLSojS1KWk0MDTy/lFgEfCf0QXc/Z2o9x+ZWTmQDXzSxM8WCd0pp5zCokWLDgyEu+mmm8IOSaTJmlpjOMLdN0fe/y9wRF2FzWww0B54N2r3f0WamO4zsw5NjEck5QYMGMDrr79OcXExEydOZP/+/WGHJNIk9SYGM3vZzP4Z5zU6upy7O+B1XKc78DhwubtX/c+ZBAwABgFdialtxJw/3sxKzax0y5Yt9d+ZSApVjZL+29/+RmFhoUZJS1qrNzG4+3B3PyHO61ng48gXftUXf3m8a5hZZ+AF4DZ3XxZ17c0e2AM8AgyuI44H3T3X3XOzs7Mbd5ciKVA1SnrHjh2MHj1ao6QlbTW1KWkOMC7yfhzwbGwBM2sPzAYec/dnYo5VJRUDzgf+2cR4RELVqVMnZs2axRFHHKFR0pK2mpoYpgDfNbN1wPDINmaWa2Z/ipS5EDgDKIzTLfUJM1sNrAaygLuaGI9I6Nq1a8fDDz/MmWeeSV5eHh988EH8guXlcM89MHYsnHde8POee0BNpRIyCx4NpJfc3FwvLS0NOwyRet13333cd999vPjii1+Nkl6+HCZPhnnzgu3du786ISMD3KGgACZNgkGDUh+0tFhmtsLdc+srp5HPIkl0ww03kJ2dzVlnnRWsJf3mmzBxIlRUBAkgVkVF8LOkBObPh6lToagotUFLq6fEIJJkY8eOJSsri1lnn82gykra7tlT/0nusGtXkERAyUFSSrOriqTAiG7dmLJ3b61JYR3QERgbe6AqOajpVFJIiUEkFSZPpk0dNYVrCQbzxFVRETyTEEkRJQaRZCsvDx4019LR4yngcGBYbee7w9y56q0kKaPEIJJsxcW1HvoU+Clwb33XMKvzOiKJpMQgkmyrVlXvkhrl/wJXAj3qu0ZFBaxeneDAROJTrySRZNu5M+7uN4GXgTcaep0dOxIUkEjdlBhEkq1Ll7i7FwHvA70i258D+4C3gX/EKf/3d97h77/9LQMGDKB///707NmTQw5RpV8ST4lBJNkGDoS//KVGc9J44KKo7akEiWJanEvsa9+eygEDKCsr49lnn6WsrIxPPvmEfv360b9/fwYMGHAgYfTr149DDz00abcjLZ+mxBBJtvJy6N271ucMVX4GrAf+J97Bjh3hgw8gambhTz/9lHfeeYeysjLKyspYu3YtZWVlrF+/npycnBoJY8CAAXz9618nmLNSWqOGTomhxCCSAl+eey5tX3jh4Hp7mMGYMUGtowH27dvHv/71rxoJo6ysjIqKCvr163cgYVQljb59+9KxY8eDiU7SiBKDSDMxb948fjduHLN37KD93r2Nv0CnTrB4MeTW+/+5Xjt27DiQKKITxoYNGzjqqKPi1jJycnJUy2ghNImeSMg+++wzJkyYwEsvvcQjTz9N+7KyYHqLXbsafpFOnYKJ9BKQFAAyMzM59dRTOfXUU6vtr6ysZMOGDQcSxt///nceffRRysrK2L9/f9yEceyxx9K+ffuExCXNixKDSBIsWbKEcePGkZ+fz6pVq+jcuTPk5wcH65pdtYpZMAV3imZXbdeuHf369aNfv341jm3durVaDePhhx9m7dq1fPDBB/Tq1atGwhgwYADdunVLesySPGpKEkmg3bt3c/vttzNjxgweeOABzjvvvJqFSkuDuY/mzg0SQNVU2/DVegwjRwbrMSSoppAMe/bs4d13363WJFX1vm3btnETxtFHH03btvp9NCwpecZgZl2Bp4E+BD3tLnT3GqNwzGwfwSptAB+4+6jI/qMJporpBqwALnX3L+v7XCUGaY5WrFjBZZddxvHHH8+0adPIysqq+4QtW4JpLlavDgavZWbCiSdCYWG13kfpxt35+OOP4yaMjz76iGOOOaZGwujfvz+HH3542KG3eKlKDPcA2919ipndAmS6+3/GKfe5ux8WZ/9MYJa7P2VmfwRWunu8btzVKDFIc1JZWckvf/lLfv/733P//fdz8cUX62FtLSoqKli/fn2NhLF27VoOPfTQuAmjd+/etGnTJuzQW4RUJYa1wFB332xm3YFF7t4/TrkaicGC/zlbgCPdfa+ZnQb8zN3Pqe9zlRikuVizZg2XXXYZ3bp1Y/r06Rx11FFhh5SW3J2PPvoobhfbrVu38o1vfKNGwujfvz9f+9rXwg69ccrLg1riqlXBVCldugQDIC+/PCW1xFQlhk/c/fDIewN2VG3HlNtLMDXMXmCKu5eYWRawzN2/ESnTE5jn7ifU97lKDBK2/fv385vf/IZf/vKX3HXXXYwfP161hCT54osvDgzki04Y69atIzMzM26PqR49ejSv6UKayTrfCeuuamYvA0fGOXRb9Ia7u5nVlmV6u/uHZnYM8KqZrQbizyxWexzjCWYRoFevXvWUFkmeDRs2cPnll7N3716WLVvGscceG3ZILdqhhx7KySefzMknn1xt//79+9m4ceOBhLFmzRpmz57N2rVrD0wXEpsw+vXrR6dOnVJ7A9Ompd063ylpSoo5pxh4HvgLakqSNOLuTJ8+nUmTJnHzzTdz4403qu27mfr0009Zu3ZttRpGWVkZ7777Ljk5OXF7THXv3j3xtb6qpHAwY1eSkBxS1ZT0K2Bb1MPnru5+c0yZTGCXu++JNB/9DRjt7m+b2Z+Bv0Q9fF7l7n+o73OVGCTVNm/ezNVXX81HH33EY489xgkn1NviKc3Qvn37eP/992s0S61du5aKiooDiSI6YXzjG984uOlCli+HoUOrJYU9wDUE061vB44FJgMFsecmcLR7tFQlhm7ATIKZg/9F0F11u5nlAv/H3a8ys+8ADwD7CRYGut/dp0fOP4agu2pXgmnpx7p77QvjRigxSCrNnDmT6667jh/96EfcfvvtGu3bQm3fvr1GLWPt2rUHpguJ12OqzulCLrggaB6K+o79AvgVUEjwpTkXuJigL3+f6HMbOT9WQ2muJJEm2r59O9deey1vvPEGjz32GIMHDw47JAlBZWUl7733Xo2EsWbNGty9RsIYMGAAxxx2GO379q13Rl2AgcAdwL/HHogzo25Taa4kkSaYO3cu48eP5/vf/z5vvPEGGRkZYYckIWnXrt2B7rGjRo06sN/d2bp1a7WEMX36dMrKyvj+hg38dP9+6vtX8zHwDvDNeAer1vm+6aaE3UtDKTGIRIme+O7xxx8nv2p+I5EYZkZ2djbZ2dnk5eVVO7bvkkto8+STdZ5fCfwQGAcMiFcgxHW+m1FHX5Fwvfbaa3zrW99i3759rFq1SklBDloqHvH0AAAJUUlEQVSbzz6r8/h+4FKgPfC7ugqGtM63agzS6u3evZvbbruNJ598svaJ70Qao5Z1vgEcuJKgGWku0K6u62RmJjSshlKNQVq1FStW8O1vf5sPPviAVatWKSlIYgwcGDw8jqMIWAM8B3U/g8jICCZVDIESg7RKlZWV3HnnnRQUFHDbbbcxc+bM+mdDFWmowsK4u/9F0Hf/TYLpJA6LvJ6IV9i91uskm5qSpNV5++23ueyyy8jKyuKNN97QxHeSeDk5wdxHMeMYehM0JdXLLFiTI6Tp11VjkFZj//793HvvvZx55plcffXVzJs3T0lBkmfSpKA56GBkZATnh0Q1BmkVNmzYQGFhIfv379fEd5IagwYFcx6FvM73wVCNQVo0d+ehhx5i8ODBnHfeeSxatEhJQVKnqCj4ku/UKWgeqotZUifQawzVGKTF2rx5M1dddRWbN29m4cKFmvhOwlFUFNQe0midbyUGaZGefvpprr/+ek18J81Dbm4wIV6arPOtxCAtyrZt27j22mtZuXIlzz//PIOSuBqWSKNlZ4cy91Fj6RmDtBhz585l4MCBdO/enX/84x9KCiIHSTUGaV4OYrH0qonvFixYwBNPPMHQoUNTGrJIS6PEIM1DXYulz5oFd9wRd7H0xYsXU1hYyFlnncXKlSvp3LlzigMXaXnUlCThmzYtWAKxpCRICLGLm1RUBPtKSoJy06axe/duJkyYwMUXX8xvf/tbpk+frqQgkiBNSgxm1tXMFpjZusjPGlMBmlm+mb0Z9dptZudHjhWb2YaoYyc1JR5JQ9GLpde3mqA77NrFvhtv5O6jj2bjxo2a+E4kCZpaY7gFeMXd+wKvRLarcfeF7n6Su58EnAXsAl6KKnJT1XF3f7OJ8Ug6Wb68xqjQ3wG5QAeCdXHjabN7N7dt387TN92kie9EkqCpiWE08Gjk/aPA+fWU/z4wz90bMT5cWqzJk6sP9AG+DtwOXFHPqW0rK7EpU5IVmUir1tTEcIS7b468/1/giHrKXwTErnf3X2a2yszuM7MOtZ1oZuPNrNTMSrds2dKEkKVZKC8PHjTHNB9dQPDbRbf6zncPRpHq34JIwtWbGMzsZTP7Z5zX6Ohy7u7UMaOsmXUHTgTmR+2eRLDc6SCgK/CftZ3v7g+6e66752Y3oxGCcpCKi5t+jarF0kUkoertruruw2s7ZmYfm1l3d98c+eIvr+NSFwKz3b0y6tpVtY09ZvYIMLGBcUu6W7WqZu+jxgpxsXSRlqypTUlzgHGR9+OAZ+soezExzUiRZIKZGUELwj+bGI+ki507E3OdkBZLF2nJmpoYpgDfNbN1wPDINmaWa2Z/qipkZn2AnsDimPOfMLPVwGogC7irifFIuqhjsfRGCWmxdJGWrEkjn919GzAszv5S4Kqo7feBGktluftZTfl8SWMDBwazTcY0J+2NvPZFXrsJ/pHG/Yca4mLpIi2ZRj5LOGpZ5PwuIIOg6vk/kfe1ViNDXCxdpCVTYpBwVC2WHrOq1c8IurZFv34W7/yQF0sXacmUGCQ8abxYukhLpsQg4alaLL1Tp8ad1wwWSxdpyTTttoSratHziRODcQl1TaRnFtQUmsFi6SItmWoMEr6iIli8GMaMgY4dazYvZWQE+8eMCcopKYgklWoM0jyk2WLpIi2ZEoM0L2myWLpIS6amJBERqUaJQUREqlFiEBGRapQYRESkGiUGERGpRolBRESqUWIQEZFqlBhERKQa87rmpmmmzGwL8K+DODUL2JrgcNJFa7331nrfoHtvjfde3333dvd6pxBIy8RwsMys1N1b5ZScrfXeW+t9g+69Nd57ou5bTUkiIlKNEoOIiFTT2hLDg2EHEKLWeu+t9b5B994aJeS+W9UzBhERqV9rqzGIiEg9WnRiMLOuZrbAzNZFfmbWUbazmW0ys9+lMsZkaci9m9lJZvY3M3vLzFaZ2Q/CiDURzGyEma01s/Vmdkuc4x3M7OnI8b+bWZ/UR5kcDbj3G83s7cjf8Stm1juMOBOtvvuOKvfvZuZm1mJ6KTXk3s3swsjf+1tmNqNRH+DuLfYF3APcEnl/C3B3HWV/A8wAfhd23Km6d6Af0Dfy/uvAZuDwsGM/iHttA7wLHAO0B1YCx8eUuQb4Y+T9RcDTYcedwnvPBzpF3he1hHtvyH1Hyn0NeA1YBuSGHXcK/877Am8AmZHtnMZ8RouuMQCjgUcj7x8Fzo9XyMy+DRwBvJSiuFKh3nt393fcfV3k/UdAOZCO62cOBta7+3vu/iXwFMH9R4v+83gGGGZmlsIYk6Xee3f3he6+K7K5DOiR4hiToSF/5wC/AO4GdqcyuCRryL1fDfze3XcAuHt5Yz6gpSeGI9x9c+T9/xJ8+VdjZocAvwYmpjKwFKj33qOZ2WCC3z7eTXZgSXAUsDFqe1NkX9wy7r4X2Al0S0l0ydWQe492JTAvqRGlRr33bWb/BvR09xdSGVgKNOTvvB/Qz8xeN7NlZjaiMR+Q9ms+m9nLwJFxDt0WveHubmbxumBdA8x1903p9gtkAu696jrdgceBce6+P7FRSnNhZmOBXODMsGNJtsgvfPcChSGHEpa2BM1JQwlqiK+Z2Ynu/klDT05r7j68tmNm9rGZdXf3zZEvv3jVqdOAIWZ2DXAY0N7MPnf3Wh9mNRcJuHfMrDPwAnCbuy9LUqjJ9iHQM2q7R2RfvDKbzKwt0AXYlprwkqoh946ZDSf4heFMd9+TotiSqb77/hpwArAo8gvfkcAcMxvl7qUpizI5GvJ3vgn4u7tXAhvM7B2CRLG8IR/Q0puS5gDjIu/HAc/GFnD3H7p7L3fvQ9Cc9Fg6JIUGqPfezaw9MJvgnp9JYWyJthzoa2ZHR+7pIoL7jxb95/F94FWPPJVLc/Xeu5mdDDwAjGpsW3MzVud9u/tOd89y9z6R/9vLCO4/3ZMCNOzfewlBbQEzyyJoWnqvoR/Q0hPDFOC7ZrYOGB7ZxsxyzexPoUaWfA259wuBM4BCM3sz8jopnHAPXuSZwY+B+cAaYKa7v2VmPzezUZFi04FuZrYeuJGgp1baa+C9/4qgNvznyN9x7JdI2mngfbdIDbz3+cA2M3sbWAjc5O4NriFr5LOIiFTT0msMIiLSSEoMIiJSjRKDiIhUo8QgIiLVKDGIiEg1SgwiIlKNEoOIiFSjxCAiItX8fzzFDUTreRPdAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e010f0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "28\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80df7160>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "29\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80dd46a0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "30\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80da2128>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "31\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1dc8a333c8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "32\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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sIEGSur/SaCaRIzJlyhSuu+46mjRpkuxQROodc/dkx3DYcnJyvKCgINlhSIr6+uuvyc7OZvXq1Zx88snJDkckZZjZcnfPqamcZj5LgzNr1izOP/98JQWRI6TEIA3OlClTGDNmTLLDEKm3lBikQVm+fDlffPEFffv2TXYoIvWWEoM0KFOmTOH6669Xp7NIDLROgDQYu3bt4vnnn2ftWg1sE4mFagzSYMycOZMLL7yQdu3aJTsUkXpNiUEaBHfXTGeROFFTUnWKi2HaNCgshJISaNkSuneH0aNBy3KklIKCAkpKSrj44ouTHYpIvafEEEl+PkycCK+GFoEtK/v22ty5cNdd0L8/jB8PPXsmJ0apoLzT+aijVAkWiZUSQ2WTJ8O4cVBaCpFmhZeWBv/OmwcLF8IDD8DYsYmNUSooKSlhzpw5rFu3LtmhiDQISgzhypPCnj01l3UPyo0bFxwrOSRNXl4eF198MW3btk12KCINgurd5fLzqySFxwg2j2gOjIp2X3ly0NpNSaFOZ5H4U2IoN3Hit81EIScDvwWuqene0tLgfkm4999/n927d3PhhRcmOxSRBkOJAYLRR6++WqVP4TLgUqBVTfe7w4IFsGNHHQUo0UydOlWdziJxpt8mCIakxsosPq8jtfbVV18xd+5cRo8enexQRBoUJQYI5imED0k9EqWlsGpVfOKRWnnmmWe45JJLaNOmTbJDEWlQNCoJgslrcVD41lv89Q9/oGPHjnTq1ImOHTvSunVrQrvWSRyVdzo//PDDyQ5FpMFRYoBgRnMcpLVpQ3FxMe+//z6bN29m8+bN7N27l44dOx56lCeM8ueZmZlKHEfg3XffZe/evVxwwQXJDkWkwYlLYjCzfsDDBHs+P+Hu91e63hx4Gjgb+Acw1N03h66NB64FDgA3ufvCeMR0WLp3hzlzqjQn7Q89DoQeZQTfsIjftIwMTv/3f+eBX/+6wuldu3YdShKbNm1i8+bNvP3222zatIlNmzbh7hETRvnz448/vi6+4nqvfDMeJVWR+It5z2czawJ8BPQBioB8YLi7rw0r83Ogu7v/zMyGAUPcfaiZdQVmAb0IRoe+DnRx9wPVvWfc93wuLoYOHaokhruB/6xU9K7Q+SrS02HLlsNeQ+mrr746lDDCk0f586ZNm0atbXTs2JFjjz32sN6v3omwXtWezp3p9sc/8t7GjZyoNatEaq22ez7HIzGcB9zt7peEjscDuPvEsDILQ2XeNbOmwHbgROD28LLh5ap7z7gnBoDLLguWuTiS74cZDBkS1DriyN358ssvIyaM8ufp6elRaxsdO3bk6KOPjmtMCVPNelX7mjXDDxwgbfBgrVclchhqmxji0ZTUHvg07LgIOCdaGXffb2YlBNMD2gPvVbq3fRxiOnzjxwdrH9VmOYzKMjKC++PMzGjVqhWtWrXi7LPPrnLd3dmxY0eFhLF69WpefvllNm3axCeffMKxxx4btbbRoUMHMjIy4h53zGpYr6rZvn3BE61XJVIn6k3ns5mNAcYAZGdnx/8NevYMPmBqu1ZSuRYtgvtyakzCcWdmtGnThjZt2tCrV68q1w8ePEhxcXGFGsaKFSt48cUX2bx5M1u2bCEzMzNqU1V2djbNmzdP7Bel9apEki4eiWErcErYcVboXKQyRaGmpJYEndC1uRcAd58KTIWgKSkOcVdV/sFS3eqq5cyCmkIK/7V61FFH0bZtW9q2bct5551X5frBgwfZtm1bheapZcuWMXv2bDZv3kxRURGtW7eO2lSVnZ1Ns2bN4hdwhPWqwq0HugE/BZ4Jv1CeHHr2TEqCFmlo4tHH0JSg8/kigg/1fCDX3deElfkF0C2s8/kyd7/CzM4EZvJt5/NioHPCO58rKygI2rcXLAgSQPgaShkZQcIYMCBoPmrAH0QHDhxg69atUTvGt23bxkknnRS1qSorK4umTQ/jb48a+nn6AqVAByolBqizfh6RhiRhnc+hNxsAPEQwXPVJd/8vM7sHKHD3+WaWDswAvg98CQxz949D904gWKduP3Czu79a0/vVeWIot2NHMCJm1SrYuRMyM6FbNxg1Sju4Afv27WPr1q1RO8Y///xzTj755KhNVSeffDJNmjQJXizKyLByzwJzga7ABiIkBjjikWEijUVCE0OiJSwxSEy++eYbPv3006ijqr744guysrLo1KkTN5SUcOnKlTTbv7/K6+wiWP78DeAJqkkMGRnwn/8JleaSiEggkaOSRCJKS0vjtNNO47TTTot4vaysjC1btrB582Y63XFHxKQAcAfBDMismt5Q61WJxIUSgyRNeno6Xbp0oUuXLvDooxHLrCSY9biiti+6c2ecohNpvJQYJDVEWa9qCbAZKB+g/DXB8iRrgb9HuiEzM+6hiTQ2WnZbUkP37kHncSVjgI0ENYeVwM+AgUCkBbX2NW3Kro4d6zBIkcZBiUFSw6hREU+3ANqGPY4B0gnWU6nM3fmXhx9mwIABzJ49m9JKW7WKSO0oMUhqaNMG+vfnYA2rpd5NlBFJZqQNHswHn31Gbm4uf/7zn2nfvj1jxozhnXfeoT6OvhNJFiUGSQnuTl52NmVH+gEeWq/q6KOPZsSIESxatIjCwkJOO+00rr/+ejp37sw999zDpk2b4hu4SAOkxCBJV1ZWxujRo3lg6VJK77svWH/qcERZryorK4vbbruNNWvWMGvWLHbs2EGvXr04//zzefLJJ9m1a1ccvwqRhkOJQZJq27Zt9O7dm927d/P222/TasKE4EO+RYtgmYvqmH2bFKpZr8rM6NmzJ48++ihbt27l5ptv5i9/+QvZ2dlceeWVLFq0iAMHql2FRaRRUWKQpMnPz6dXr14MHDiQ55577tu9I8aOhaVLg7WP0tODZqJwGRnB+SFDgnKHsYhhWloaQ4YM4cUXX2TDhg2ce+65TJgwgezs7EO1C5HGTktiSFLk5eVx8803M3XqVIYMGRK9YILWq1qzZg0zZsxgxowZtGvXjpEjRzJ8+HBat24dt/cQSTatlSQp6cCBA/zHf/wHzz//PC+99BLdunVLdkgVHDhwgMWLF/P000/z8ssv07t3b0aOHMnAgQNJS0tLdngiMaltYlBTkiRMSUkJgwYNIj8/n2XLlqVcUgBo0qQJffv25ZlnnmHLli0MGjSIhx9+mPbt23PjjTeybNkyDX2VBk+JQRLio48+4txzz6VTp04sXLiwXjTRHHfccVxzzTUsWbKEZcuWcdJJJ5Gbm0vXrl25//77KSoqSnaIInVCiUHq3KJFi/jxj3/MLbfcwmOPPRbfXd8SpFOnTtxxxx2sX7+eJ554gk2bNnHWWWfRp08fnnnmGXbv3p3sEEXiRolB6oy7M2nSJEaOHMkLL7zAmDFjkh1SzMyMH/7wh0yZMoWioiKuv/56Zs2aRVZWFqNHj+bNN9/k4MGDyQ5TJCbqfJY6UVZWxs9+9jNWrlzJSy+9RIcOHZIdUp3avn07M2fOZPr06ZSUlHDVVVdx9dVX07lz52SHJnKIOp8lacInrb3zzjsNPikAtG3blltvvZUPPviAl156id27d/PjH/+YH/zgB0yZMoWd2idC6pGYEoOZnWBmr5nZ+tC/VRbDN7MeZvauma0xs0IzGxp2bZqZbTKzlaFHj1jikeSLOmmtETnrrLOYNGkSn376KRMmTGDx4sV07NiRK664gpdffpl9+/YlO0SRasVaY7gdWOzunYHFoePK9gBXu/uZQD/gITM7Puz6r929R+ixMsZ4JIny8vIYMGAAjzzyCHfccQdW05IWDVyzZs0OJcjNmzdz0UUX8bvf/Y6srCxuueUWVq7Uj7ukplgTw2Bgeuj5dODSygXc/SN3Xx96/hlQTOTl9KWeOnDgALfddht33HEHb7zxRvUzmRupzMxMbrjhBv72t7/x9ttvc8wxxzB48GDOOuss/vjHP7J9+/ZkhyhySKyJ4SR33xZ6vh04qbrCZtYLSCPYlKvcf4WamB40s+YxxiMJVh8mraWazp07c++997Jp0yYefvhhVq9ezRlnnMHAgQOZPXs2ZWVlyQ5RGrkaE4OZvW5mqyM8BoeX82B4U9QhTmbWDpgBjHb38vF844HTgZ7ACcBt1dw/xswKzKxgx44dNX9lUufq46S1VHLUUUfRu3dvnnrqKYqKihg+fDhPPPEEJ598sjYYkqSKabiqmX0I9Hb3baEP/iXu/t0I5Y4j2Nf9d+7+QpTX6g2Mc/ef1PS+Gq6afIsWLeKqq67i3nvvbRDzE1JJUVERzzzzDNOnT2ffvn1cffXVXH311XTUftYSo0QNV50PjAw9Hwm8FCGQNOBF4OnKSSGUTLCgl/JSYHWM8UgdC5+09vzzzysp1IGsrCxuv/121q5dy6xZsyguLiYnJ0cbDEnCxFpjaAU8B2QDnwBXuPuXZpYD/MzdrzOzEcBTQPhC96PcfaWZvUHQEW3AytA9X9f0vqoxJEdjm7SWSr755hteeeUVpk+fzpIlSxg4cCAjR47koosuokmTJskOT+oJLbstcbVt2zaGDBnCKaecwrRp0xrl/IRU8cUXXzBr1iymT5/Otm3bGDFiBCNHjqRr167JDk1SnGY+S9xo0lpqad26Nb/85S8pKChg0aJFAPTp04ecnBweffRRvvjiiyRHKPWdagxSrVrvtCZJVb7B0PTp03nllVfiv8FQcXGwk15hIZSUQMuW0L07jB4d1530pG6pKUlikuo7rUl0u3bt4oUXXmD69OmsXbuWoUOHMnLkSHJycg5/Nnp+PkycCK++GhyHz7HIyAB36N8fxo+Hnj3j90VInVBikCNWUlJCbm4upaWlPPfcc5qfUI9t2rSJGTNm8PTTT5OWlsbVV1/NiBEjyMrKqvnmyZNh3DgoLQ0SQDRmQZJ44AEYOzZ+wUvcqY9BjogmrTUsnTp14s4772T9+vX87//+L5s2baJ79+41bzBUnhT27Kk+KUBwfc+eoPzkyfH/IiThlBjkkIaw05pEFr7B0NatW7nuuusqbDC0ZMmSbzcYys//NimE6Q2kA8eEHlVmspYnB9Xm6z0lBtGktUYmIyODoUOH8sorr7Bu3Tq+973vcdNNN3Hqqadyxx138PWECUHzUQSPAV+HHh9GKlBaGvRJSL2mxNDIlZWVMXr0aJ5++mnee+89/vVf/zXZIUkCtW3bll/96lcUFhYyb948bMcOmr72Ws3NR9G4w4IFoPXM6jUlhkasMe60JtH16NGDe049lebp6VHLjAdaAz8kWPwsIrNgaKvUW0oMjZQmrUlEhYVYlGW/fw98DGwFxgD/RsX18w8pLYVVq+oqQkmApskOQOLgMCcfadKaRFVSEvXSOWHPRwKzgAXALyMV1h7X9ZoSQ31W3eSjuXPhrrsqTD4Kn7T2xhtvaNKaVNWyZa2LGtVswJJZZft3qUeUGOqrmiYflY8qmTcPFi5kz7338u+LF7Nnzx6WLVum+QkSWffuMGdOxT8ygK+A94HzCT40ZgNvAQ9HeIn9zZqxv0sXovdUSKpTH0N9dASTj2zcOEZ8/TWLFi1SUpDoRo2KeHof8FuCNfJbA48C84AuEcoePHCArr//PUOHDuWll15i7969dRSs1BUlhvomyuSjL4EhwNFAB2Bmpdsy3BleUECzDz5ITJxSP7VpEzQ/VlpT6UQgH/gnQe3hPaBPpPvNSLv0UvI3b+bCCy9k0qRJh7YqrTCJTlKaEkN9M3FixMlHvwDSgM+BPGAsFXdGAjT5SGpn/Phg7aMjkZEB48fTqlUrbrjhBpYuXcqKFSv4zne+w80330x2djbjxo1jxYoV2s86hSkx1CfFxUFHc6VfqN3AHOBegqUKfgQMAmZUvl+Tj6Q2evYMFsRr0eLw7mvRIrgvp+IabdnZ2fzmN79h5cqVLFy4kPT0dC6//HK6du3Kvffey8aNEQe9ShIpMdQnUSYNfUTQIRje3nsWEWoMoMlHUjtjx36bHGpaqtvs26RQw+qqZ555Jvfddx8bN27kySefpLi4mB/84Aece+65PPLII2zfvj2OX4QcqZgSg5mdYGavmdn60L8Rx6iZ2QEzWxl6zA8738nM3jezDWY228zisKNIA1ZYWGW0CATr1hxX6VxLgvbgKjT5SGpr7FhWVN7TAAAMZUlEQVRYuhSGDIH09KrNSxkZwfkhQ4Jyh7Hktplx3nnn8eijj7J161buvvtuCgoKOP3007nkkkuYPn06u3btivMXJLUV63DV24HF7n6/md0eOr4tQrlSd+8R4fzvgQfd/Vkz+x/gWkDr9kYTZfLRMUDlX6FdwLHRXkeTj6S2cnKC4as7dgQ1zVWrgp+fzEzo1i0YxRTjDm5NmzalX79+9OvXjz179vDyyy+Tl5fHTTfdRN++fbnyyivp378/zZs3j8uXJDWLaaMeM/sQ6O3u28ysHbDE3ausxmtmX7v7MZXOGbADaOvu+83sPOBud7+kpvdttBv1jBgBeXlVTu8GMgmajjqHzl0NnAzcH+l1rroKnn66joIUiY8vv/ySOXPmMHPmTAoLCxkyZAi5ubmcf/75NGnSJNnh1UuJ2qjnJHffFnq+HTgpSrl0Mysws/fM7NLQuVbAV+6+P3RcBLSPMZ6GrXv3oOpeydHAZcCdBEniHeAl4KpIr5GREfylJ5LiTjjhBK6//nrefPNNVq5cyemnn864cePIzs7mV7/6FcuXL9fIpjpSY43BzF4H2ka4NAGY7u7Hh5Xd6e5V+hnMrL27bzWzU4E3gIuAEuA9d/9OqMwpwKvu/r0ocYwhWLuL7Ozssz/55JPafH0NS3ExdOgQsZ/hS+Aa4DWCjHs/kBvpNdLTYcsWbeAu9da6deuYOXMmM2fOpFmzZuTm5jJ8+HA6d+5c882NXEL2fK5tU1Kle6YBLxOMsFRT0uG67LJgmYsj+X8zCzoK58yJf1wiCebuLFu2jLy8PGbPnk2HDh248sorGTp0KG3bRvpbVhLVlDSfYKFFQv++FCGQTDNrHnpevpT7Wg8y0pvAT6u7XyqJw+QjkYbAzDjnnHN45JFH2Lp1K/fddx8rVqzgjDPOoE+fPjz11FOUVLNarEQXa2K4H+hjZuuBi0PHmFmOmT0RKnMGUGBmHxAkgvvdfW3o2m3ArWa2gaAF5M8xxtPwxXnykUhD0LRpU/r27cu0adP47LPPGDNmDPPnzyc7O5uf/vSnzJ07l7Io+0xIVTE1JSVLo25KKlfT6qrlzIKaQi0mH4k0NDt37jw0smnlypWHRjb17t27UY5sSlRTkiRLHU4+EmkoMjMzue6663jjjTdYtWoVXbt25Te/+Q2nnHIKt956KwUFBRrZFIFqDA1BHU4+EmmI/u///o9Zs2aRl5fHUUcdRW5uLrm5uXTpEmkh8YYjIaOSkkWJQUTiwd3Jz89n5syZzJ49m6ysLHJzcxk2bBjt2rVLdnhxp8QgInIY9u/fz5IlS8jLy2PevHmcffbZ5Obmctlll3H88cfX/AK1cZj7s8ebEoOIyBEqLS1lwYIFzJw5k9dff52LL76Y3NxcBg4cSHqE1QdqVN3+7BkZwQCSsP3Z64oSg4hIHHz11VfMnTuXmTNn8ve//53Bgwdz5ZVXcsEFF9RuZFMKjSDUqCQRkTg4/vjjueaaa3j99ddZvXo13bt3Z/z48WRlZXHzzTezbNmy6CObjmB/dsaNC+5LItUYRESOwEcffXRozSZ3PzSy6bvfDa0KlJ8PvXtX2J99L/Bz4HWC9c1OAyYC/Su/eIsWwTDzOE9IVY1BRKQOdenShbvvvpsPP/yQWbNm8c9//pMLLriAnJwcJk2aROmdd1bZn30/cAqwlGAV0fuAK4DNlV88yfuzq8YgIhInBw4cYMmSJfzlz3/m/lmzqE03dXfgLuDyyhfqYCVk1RhERBKsSZMmXHTRRTzUowfNazF66XOCPdvPjHQxifuzKzGIiMRbYSFWw6J9+4ArCZaVPj1SgSTuz67EICISbzUs932QYIfFNOCx6gomaX/2pkl5VxGRhqxly6iXHLiWoBlpAdCsutfJrLIhZkKoxiAiEm9R9mcHGAusA/4CVLvlVhL3Z1diEBGJt1GjIp7+BJgCrATaAseEHnmRCrtHfZ26psQgIhJvbdoEax+ZVTjdgaApqQz4OuxxZeX7zWDAgKQtm6/EICJSF+rx/uwxJQYzO8HMXjOz9aF/q/SUmNkFZrYy7FFmZpeGrk0zs01h13rEEo+ISMqox/uzx1pjuB1Y7O6dgcWh4wrc/U137+HuPYALgT3AorAivy6/7u4rY4xHRCR1jB37bXKo1KxUhdm3SSHJW/HGmhgGA9NDz6cDl9ZQ/qfAq+6+p4ZyIiINQz3cnz3WeQwnufu20PPtwEk1lB8GTKp07r/M7E5CNQ533xtjTCIiqSUnB+bMqTf7s9e4iJ6ZvU4wsqqyCcB0dz8+rOxOd484I8PM2gGFwMnuvi/s3HaCCYBTgY3ufk+U+8cAYwCys7PP/uSTT2r40kREJFxtF9Grscbg7hdX8yafm1k7d98W+pAvrualrgBeLE8Kodcur23sNbOngHHVxDGVIHmQk5NT/5aEFRGpJ2LtY5hPsAYUoX9fqqbscGBW+IlQMsHMjKB/YnWM8YiISIxiTQz3A33MbD1wcegYM8sxsyfKC5lZR77dnyJcnpmtAlYBrQn2rRARkSSKqfPZ3f8BXBThfAFwXdjxZqB9hHIXxvL+IiISf5r5LCIiFSgxiIhIBUoMIiJSgRKDiIhUUOMEt1RkZjsIljZPBa2BL5IdRDUUX2xSOb5Ujg0UX6zqIr4O7l7jFOt6mRhSiZkV1GYmYbIovtikcnypHBsovlglMz41JYmISAVKDCIiUoESQ+ymJjuAGii+2KRyfKkcGyi+WCUtPvUxiIhIBaoxiIhIBUoMh6k2+1yHymWb2SIzW2dma0MLCaZMfKGyx5lZkZk9lojYahufmfUws3fNbI2ZFZrZ0DqOqZ+ZfWhmG8ysyva0ZtbczGaHrr+fqP/Lw4jv1tDPWKGZLTazDqkUX1i5y83MzSxhI21qE5uZXRH6/q0xs5mJiq028YU+R940sxWh/98BCQnM3fU4jAfwB4Kd5iDY4/r3UcotAfqEnh8DtEil+ELXHwZmAo+l0vcP6AJ0Dj0/GdgGHF9H8TQBNgKnEmwY9QHQtVKZnwP/E3o+DJidwO9XbeK7oPznCxibavGFyh0LvAW8B+SkSmxAZ2AFkBk6bpNK3zuCfoaxoeddgc2JiE01hsNX4z7XZtYVaOrurwG4+9eeuH2ua7UPt5mdTbAV66IExVWuxvjc/SN3Xx96/hnBBlB1te9hL2CDu3/s7t8Az4ZijBbzC8BFoT1EEqHG+Nz9zbCfr/eArATFVqv4Qu4Ffg+UpVhs1wN/cvedAO5e3WZjyYjPgeNCz1sCnyUiMCWGw1ebfa67AF+Z2dxQFfC/zaxJqsRnZkcBf6SaHfPq0GHtE25mvQj+mtpYR/G0Bz4NOy6i6hLxh8q4+36gBGhVR/FUVpv4wl0LvFqnEVVUY3xm9i/AKe7+SgLjgtp977oAXczsHTN7z8z6JSy62sV3NzDCzIqABcAvExFYTPsxNFQ17HN9iLu7mUUa1tUU+DHwfWALMBsYBfw5ReL7ObDA3Yvq4g/fOMRX/jrtgBnASHc/GN8oGx4zGwHkAOcnO5ZyoT9CJhH8/KeipgTNSb0JalpvmVk3d/8qqVF9azgwzd3/aGbnATPM7Ht1/fugxBCBx77PdRGw0t0/Dt0zDziXOCWGOMR3HvBjM/s5Qf9Hmpl97e5ROw4THB9mdhzwCjDB3d+LR1xRbCXYXbBcVuhcpDJFZtaUoEr/jzqMKdJ7l4sUH2Z2MUHiPd/d9yYoNqg5vmOB7wFLQn+EtAXmm9kgDzb0SmZsEPyuvu/BXvSbzOwjgkSRX8ex1Ta+a4F+AO7+rpmlE6yhVKdNXmpKOny12ec6HzjezMrbxS8E1iYgNqhFfO5+pbtnu3tHguakp+OVFOIRn5mlAS+G4nqhjuPJBzqbWafQ+w4LxRguPOafAm94qDcwAWqMz8y+D0wBBiW4jbzG+Ny9xN1bu3vH0M/be6E46zop1BhbyDyC2gJm1pqgaenjBMRW2/i2ENol08zOANKBHXUeWaJ64BvKg6BteTGwHngdOCF0Pgd4IqxcH6CQYD/raUBaKsUXVn4UiR2VVGN8wAhgH7Ay7NGjDmMaAHxE0I8xIXTuHoIPMAh+GZ8HNgDLgFMT/DNXU3yvA5+Hfa/mp1J8lcouIUGjkmr5vTOCpq61od/VYan0vSMYifQOwYillUDfRMSlmc8iIlKBmpJERKQCJQYREalAiUFERCpQYhARkQqUGEREpAIlBhERqUCJQUREKlBiEBGRCv4/UBltUnxc7jwAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f98c88>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "33\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f7d160>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "34\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e2c0f0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "35\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80eac860>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "36\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e02550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "37\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80ea3e80>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "38\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d01f98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "39\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80cadf60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "40\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c6d550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "41\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'S', 6: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c9c630>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "42\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'S', 6: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f76278>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "43\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'S', 6: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c94c88>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "44\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f97f98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "45\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c8cd68>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "46\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f01e10>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "47\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80ec8d68>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "48\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e85f28>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "49\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f11860>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "50\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c47080>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "51\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80dc2f98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "52\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d85630>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "53\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80da9f60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "54\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f3df28>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "55\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f92da0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "56\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d87b70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "57\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80edb9b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "58\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80efbdd8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "59\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80deb908>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "60\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d1c3c8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "61\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80ed6748>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "62\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80cb7c18>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "63\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80cc49b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "64\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d5d550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "65\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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zU4E1Zlbo7m/GaDsWGAvo+bWSNpVDT//nf/6Hk08+meXLl9OrV690hyWSVMlIDDuBkyO2TwrLqjCzAQTrfl3o7nsry919Z/j1LTNbS7A+2EGJwd3nAfMgeLRnEuIWOSRr165l8uTJlJeXc9999zFw4MB0hySSEsm4lJQHdDGzzmbWHBgGVBldZGbnAA8Al7t7UUR5WzNrEb5vB3wD2JSEmESS5pVXXmHw4MHccMMN3HzzzeTn5yspSKOWcGJw930Ej6BdCWwGnnD318zsDjOrHGX0v0Br4A9Rw1K7Aflm9grwHDDL3ZUYpEH417/+xXXXXcell17K4MGD2bx5M8OGDdPQU2n0zKtbh6WBys7O9vz8/HSHIY1UcXExd911F4888gjjx49nwoQJHHnkkekOSyRhZrbB3WtcaVF/+oiEdu/ezZ133km3bt2oqKhg06ZNTJs2TUlBmhwtiSGZragoWEeooABKSoLnJvfoAaNH13odofLycnJzc5kxYwZ9+/blpZde4itf+Upq4xZpwJQYJDPl5cHMmbAinBKzZ8+BfUuXwrRpMGhQ8OCa3r1jHsLd+cMf/sCtt95K586d+eMf/8i5555bD8GLNGxKDJJ55s6t/lkFZWXB12XLYOXKmM8qWLNmDZMnT8bdmTt3LgMGDKiHwEUygxKDZJbKpFBaWnNd96DexInB9rhxbNy4kSlTprBt2zbuuusurrrqKo0yEomi/xGSOfLyYiaFvkBLgvHQrYGvRrcrLWX/Lbfw40svZdCgQVx++eVs2rSJa665RklBJAb1GCRzzJx54DJRlPuAMdU09bIyRmzfzpStW2ndunVKwhNpLPTnkmSGoqLgRnMd5900A7q9/Tat4yQWETlAiUEyw8KF1e6eClSuqbI2XiWzGo8jIkoMkikKCqoOSY1wN/AWwcqNY4FvEWMVRgguQxUWpipCkUZDiUEyQ0lJ3F1fA44EWgAjCXoNz8SrvGtXsiMTaXSUGCQztGlT66oGxL0T0bZtMqIRadSUGCQz9OgBLVseVPwJwbK+e4B9wKPA88ClsY6RlQXdu6cwSJHGQYlBMsOoUTGLy4EfA+0Jbj7/ClgGdI1V2T3ucUTkACUGyQwdOsCgQbhZleL2BE+K+pSg97AeiPkIHTMYPLjWC+uJNGVKDJIxVvTsSVldnx+SlRUsqCciNVJikAZv7969fP/732f8I4/w8a23QqtWh3aAVq2ChfSya3w+iYiQpMRgZpea2Rtmts3MpsTY38LMHg/3v2RmnSL2TQ3L3zCzS5IRjzQe77zzDueffz7vv/8++fn5nHTnncGHfKtWweWh6pgdSApRq6uKSHwJJwYzawbcDwwCzgCGm9kZUdVuAHa5+2nAvQRzkgjrDQPOJBhI8uvweCKsWLGCPn36cM0117BkyRLaVA5ZHTcO1q2DnJxgpFJWVtWGWVlBeU5OUE9JQeSQJGMRvT7ANnd/C8DMFgFDgE0RdYYAt4fvFwP3mZmF5YvcfS/wtpltC4/3YhLikgxVUVHB9OnTmT9/PosXL+b8888/uFJ2NixZAsXFwTIXhYXB5LW2bYMhqaNG6UazSB0lIzGcCOyI2H6XYDJqzDruvs/MSoBjwvL1UW1PTEJMkqGKi4sZMWIE5eXl5Ofnc9xxx1XfoH17mDSpfoITaSIy5uazmY01s3wzyy8uLk53OJICL774Ir169eLcc89l1apVNScFEUmJZCSGncDJEdsnhWUx65jZ4UAb4KNatgXA3ee5e7a7Z7fXJYJGxd355S9/yZAhQ7jvvvuYNWsWhx+uR4WIpEsy/vflAV3MrDPBh/ow4DtRdZYTrG/2InAlsMbd3cyWA783s58BJwBdgH8kISbJEJ9++inf+973eOONN3jxxRf5yle+ku6QRJq8hHsM7r4PuJFgyZrNwBPu/pqZ3WFml4fVfgscE95cngBMCdu+BjxBcKP6z8AP3L0i0ZgkM2zatIk+ffrQunVr/v73vyspiDQQ5nWdSZpG2dnZnp+fn+4wJAGPPfYY48ePZ/bs2YwePTrd4Yg0CWa2wd1rnOmpC7lSr/bu3cstt9zCn//8Z1atWkXPnj3THZKIRFFikHqzfft2rrrqKk444QTy8/M56qij0h2SiMSQMcNVJbOtXLmSPn36cOWVV7J06VIlBZEGTD0GSamKigpmzJjBgw8+yOOPP86FF16Y7pBEpAZKDJIyH374ISNGjGDPnj3k5+dz/PHHpzskEakFXUqSlHjppZfo1asXZ599NqtXr1ZSEMkg6jFIUrk7999/P3fccQfz5s1j6NCh6Q5JRA6REoMkzWeffcb3vvc9Nm/erFnMIhlMl5IkKTZv3kyfPn3IyspSUhDJcEoMkrBFixZxwQUXcMsttzB//nyyoh+cIyIZRZeSpM4+//xzJk6cyJ/+9Cf+8pe/cM4556Q7JBFJAiUGqZMdO3Zw9dVX06FDBzZs2KAJayKNiBJDU1dUFDwas6AASkqgTRvo0QNGj477aMxVq1Zx3XXXcfPNNzNp0iQOO0xXJEUaEyWGpiovD2bOhBUrgu09ew7sW7oUpk2DQYNg6lTo3RuA/fv3c+edd/Kb3/yGRYsW0bdv3/qPW0RSTomhKZo7FyZOhLIyiLXsellZ8HXZMli5EubM4aOrr+baa69l9+7dbNiwQRPWRBoxXQNoaiqTQmlp7KQQyR1KS6mYMIGfde3KWWedpVnMIk1AQonBzI42s1VmtjX82jZGnZ5m9qKZvWZmBWZ2TcS+hWb2tpltDF9anD+V8vIOJIUYtgItgWujypvt2cP03bv532uu4Ygjjkh1lCKSZon2GKYAq929C7A63I5WClzv7mcClwI/N7PIISyT3L1n+NqYYDxSnZkzD1wmiuEHQO84+w7//POgvYg0eokmhiHAQ+H7h4CDFsZx9y3uvjV8/39AERB7uIukTlFRcKM5zuWjRcBRQP947d3hmWeguDhFAYpIQ5FoYjjW3d8L378PHFtdZTPrAzQH3owoviu8xHSvmbVIMB6JZ+HCuLv+DfwE+FlNxzCr9jgi0jjUOCrJzJ4Fjoux69bIDXd3M4t7N9PMjgceAUa6+/6weCpBQmkOzAMmA3fEaT8WGAtwyimn1BS2RCsoqDokNcJtwA3ASTUdo6wMCguTHJiINDQ1JgZ3HxBvn5l9YGbHu/t74Qd/UZx6Xwb+BNzq7usjjl3Z29hrZguAidXEMY8geZCdnV3DcBo5SElJzOKNwLPAy7U9zq5dSQpIRBqqROcxLAdGArPCr09FVzCz5sCTwMPuvjhqX2VSMYL7E68mGI/E06ZNzOK1wL+Ayj7YZ0AFsAn4Z6wGbQ8aeCYijUyi9xhmAQPNbCswINzGzLLNLDesczVwATAqxrDUR82sECgE2gF3JhiPxNOjB7RseVDxWIIbPhvD138D3wRWxjpGVhZ0757CIEWkITCvaZJTA5Sdne35+fnpDiOzFBVBx45x7zNUuh3YBvwu1s6WLWH79rhrKIlIw2ZmG9w9u6Z6mvncVHToEKx9ZFZttduJkxTMYPBgJQWRJkCJoSmZOjW4HFQXWVlBexFp9JQYmpLevdl0ww3EXhCjGq1awZw5kF1jD1REGgElhibkhRdeoO+iRfzfLbcEH/Y1XFbC7EBSGDeufoIUkbRTYmgiNm7cSE5ODo888ginzZkD69ZBTk5wQzn68lJWVlCekxPUU1IQaVL0PIYmYMuWLQwePJi5c+dyySWXBIXZ2bBkSbD20cKFwYzmXbuCeQrdu8OoUbrRLNJEKTE0ctu3b2fgwIHcddddXHHFFQdXaN8eJk2q/8BEpMHSpaRG7IMPPmDAgAFMmDCB0aNHpzscEckQSgyN1K5du7jkkksYMWIEP/zhD9MdjohkECWGRmj37t1885vf5KKLLuInP/lJusMRkQyjxNDI7N27l5ycHLp168bPfvYzrKYhqSIiUZQYGpF9+/YxfPhw2rRpw7x585QURKRONCqpkdi/fz9jxoyhtLSUp556imbNmqU7JBHJUEoMjYC786Mf/Yht27axcuVKWrTQE1JFpO6UGBqBadOm8be//Y3nnnuOL33pS+kOR0QynBJDhrvnnnt44okneP7552kT5yltIiKHQokhg+Xm5vKrX/2Kv/71r3To0CHd4YhII5HQqCQzO9rMVpnZ1vBrzAcCm1lFxGM9l0eUdzazl8xsm5k9Hj4fWmrhiSeeYNq0aaxatYqTTz453eGISCOS6HDVKcBqd+8CrA63Yylz957h6/KI8ruBe939NGAXcEOC8TQJK1as4KabbmLFihV06dIl3eGISCOTaGIYAjwUvn8IGFrbhhYMsu8HLK5L+6bq+eefZ+TIkTz11FP06NEj3eGISCOUaGI41t3fC9+/Dxwbp15LM8s3s/VmVvnhfwzwibvvC7ffBU5MMJ5GbcOGDVx55ZX8/ve/57zzzkt3OCLSSNV489nMngWOi7Hr1sgNd3cz8ziH6ejuO83sVGCNmRUCJYcSqJmNBcYCnHLKKYfStFHYvHkzl112GfPmzWPAgAHpDkdEGrEaE4O7x/0UMrMPzOx4d3/PzI4HiuIcY2f49S0zWwucAywBjjKzw8New0nAzmrimAfMA8jOzo6XgBqlt99+m4svvpjZs2czdKiutolIaiV6KWk5MDJ8PxJ4KrqCmbU1sxbh+3bAN4BN7u7Ac8CV1bVv6t577z0GDhzI5MmTue6669Idjog0AYkmhlnAQDPbCgwItzGzbDPLDet0A/LN7BWCRDDL3TeF+yYDE8xsG8E9h98mGE+j8vHHH3PxxRczevRobrzxxnSHIyJNhAV/uGeW7Oxsz8/PT3cYKfXpp58yYMAALrjgAmbPnq2VUkUkYWa2wd2za6qnmc/1ragIFi6EggIoKYE2baBHDxg9Onj+MrBnzx6GDBnC2WefraQgIvVOPYb6kpcHM2fCihXB9p49B/ZlZYE7DBrEvkmTuGLWLLKysnj00Ue1fLaIJI16DA3J3LkwcSKUlQUJIFpZGQC+bBkVy5cz8PTTGfvPfyopiEha6AluqVaZFEpLYyeFCOZOi4oKfvD22zT/re7Di0h6KDGkUl7egaQQ2kuwIFRH4EigJ7AiqpmVlgbtMu1ymYg0CkoMqTRz5heXiSrtA04G1hFM/b4TuBr4V3TbsrKgvYhIPVNiSJWiouBGc9Tloy8BtwOdCE7+ZUBnYEN0e3d45hkoLk55qCIikZQYUmXhwlpV+wDYApwZa6dZrY8jIpIsSgypUlBQdUhqDOXACIK1QE6PVaGsDAoLkx+biEg1lBhSpaT6xWP3A9cBzYH7qqu4a1fyYhIRqQXNY0iVNm3i7nKCkUkfAM8AR1R3nLYxn5YqIpIy6jGkSo8e0LJlzF3jgM3A00BWdcfIyoLu3ZMfm4hINZQYUmXUqJjF7wAPABsJnn7UOnw9Gquye9zjiIikihJDqnToAIMGBSOLInQkuJS0B/gs4jUiur0ZDB78xcJ6IiL1RYkhlaZODS4H1UVWVtBeRKSeKTGkUu/eMGcOtGp1aO1atQraZde4CKKISNIpMaTauHF8ctttlAJe03MVzA4khXHj6iU8EZFoCSUGMzvazFaZ2dbw60FjK83sIjPbGPHaY2ZDw30LzeztiH09E4mnofrR66/z2+uvx3JygpFK0ZeXsrKC8pwcWLdOSUFE0irReQxTgNXuPsvMpoTbkyMruPtzBIuIYmZHA9uAv0RUmeTuixOMo8Fav349q1at4levvw5HHhmsfbRwYTCjedeuYJ5C9+7B6CPdaBaRBiDRxDAE6Bu+fwhYS1RiiHIlsMLdS6up02js37+fm266ibvvvpsjjzwyKGzfHiZNSm9gIiLVSPQew7Hu/l74/n3g2BrqDwMeiyq7y8wKzOxeM2sRr6GZjTWzfDPLL86QFUcXLlzIEUccwYgRBw1GFRFpsGp85rOZPUswFyvarcBD7n5URN1d7h5zDQczOx4oAE5w9/KIsvcJlgyaB7zp7nfUFHQmPPP5k08+oVu3bvzxj3+kV69e6Q5HRCR5z3x29wHVfJMPzOx4d38v/JAvquZQVwNPViaF8NiVvY29ZrYAmFhTPJli+vTpfOtb31JSEJGMk+g9huUEq0bPCr+uB14sAAAKqklEQVQ+VU3d4UCVGVsRScWAocCrCcbTIGzatInf/e53bNq0Kd2hiIgcskTvMcwCBprZVmBAuI2ZZZtZbmUlM+vEgSdaRnrUzAqBQqAdwZMuM5q7M378eG677Tbaa5SRiGSghHoM7v4R0D9GeT4wJmL7X8CJMer1S+T7N0TLli3j/fffZ5zmIohIhtLzGJKorKyMCRMmkJubyxFHVPuUBRGRBktLYiTRnDlz6NWrF/37H9SJEhHJGOoxJMn27dv5+c9/zoYNG9IdiohIQtRjSJJJkyZx00030alTp3SHIiKSEPUYkmDt2rWsX7+eBQsWpDsUEZGEqceQoH379jF+/HjuueceWh3qcxdERBogJYYEPfDAA7Rr144rrrgi3aGIiCSFLiUl4MMPP2T69OmsXr0aq+khPCIiGUI9hgTcdtttDBs2jO7du6c7FBGRpFGPoY5efvllnnzySTZv3pzuUEREkkqJoTpFRcHT1goKoKQE2rSBHj3wUaMYP348M2bMoG3bmKuMi4hkLCWGWPLyYOZMWLEi2N6z58C+pUvZ/+MfM71VKy7UJSQRaYR0jyHa3LnQty8sWxYkhMikAFBWRrPyci76979p1r9/UF9EpBFRjyHS3LkwcSKU1vxIanMP6k0Mny2k1VRFpJFQj6FSXl7MpPAxkAN8CegI/D66XWVyaOCPGhURqS0lhkozZ0JZ2UHFPyB4IPUHwKPAOOC16EplZUF7EZFGIKHEYGZXmdlrZrbfzOI+YNrMLjWzN8xsm5lNiSjvbGYvheWPm1nzROKps6Ki4Eaze5Xi3cASYAbQGvhP4HLgkej27vDMM1BcXA/BioikVqI9hleBbwPPx6tgZs2A+4FBwBnAcDM7I9x9N3Cvu58G7AJuSDCeulm4MGbxFoKbMF0jys4mRo8BwCzucUREMklCicHdN7v7GzVU6wNsc/e33P1zYBEwxII1JPoBi8N6DwFDE4mnzgoKDh59BHwGfDmqrA3waaxjlJVBYWHyYxMRqWf1cY/hRGBHxPa7YdkxwCfuvi+qvP6VlMQsbg38O6rs38CR8Y6za1fyYhIRSZMah6ua2bPAcTF23eruTyU/pLhxjAXGApxyyinJPXibNjGLuwL7gK1Al7DsFeDMeMfRLGgRaQRqTAzuPiDB77ETODli+6Sw7CPgKDM7POw1VJbHi2MeMA8gOzvb49Wrkx49YMmSgy4nfYngBspPgFxgI/AU8PdYx8jKAs2EFpFGoD4uJeUBXcIRSM2BYcByd3fgOeDKsN5Igs/d+jdqVNxdvwbKgA7AcGAucXoM7tUeR0QkUyQ6XDXHzN4F/gP4k5mtDMtPMLNnAMLewI3ASmAz8IS7Vw7smQxMMLNtBPccfptIPHXWoQMMGhSMLIpyNLCMYOjqduA7sdqbweDB0L59SsMUEakP5p7cqzL1ITs72/OTPdM4Ly9YI6kWy2EcpFUrWLcOsuNO5RARSTsz2+DuNX5QaeZzpd69Yc6c4EP+ULRqFbRTUhCRRkKL6EWqXAhv4sRgXkJ1vSmz4IbznDlaQE9EGhX1GKKNGxdcFsrJgZYtgw//SFlZQXlOTlBPSUFEGhn1GGLJzg6GrxYXB8tcFBYGk9fatg2GpI4apRvNItJoKTFUp317mDQp3VGIiNQrXUoSEZEqlBhERKQKJQYREalCiUFERKpQYhARkSqUGEREpAolBhERqUKJQUREqsjI1VXNrBh4J40htAM+TOP3r05Djg0adnyKrW4UW92kI7aO7l7jsg0ZmRjSzczya7N0bTo05NigYcen2OpGsdVNQ45Nl5JERKQKJQYREalCiaFu5qU7gGo05NigYcen2OpGsdVNg41N9xhERKQK9RhERKQKJYY4zOxoM1tlZlvDr21j1LnIzDZGvPaY2dBw30IzeztiX8/6jC2sVxHx/ZdHlHc2s5fMbJuZPW5mzeszNjPraWYvmtlrZlZgZtdE7Ev6eTOzS83sjfDnnRJjf4vwPGwLz0uniH1Tw/I3zOySRGOpQ2wTzGxTeJ5Wm1nHiH0xf7/1GNsoMyuOiGFMxL6R4b+BrWY2Mg2x3RsR1xYz+yRiX6rP23wzKzKzV+PsNzP7ZRh7gZmdG7Evpeet1txdrxgvYDYwJXw/Bbi7hvpHAx8DrcLthcCV6YwN+CxO+RPAsPD9b4Bx9Rkb0BXoEr4/AXgPOCoV5w1oBrwJnAo0B14Bzoiq833gN+H7YcDj4fszwvotgM7hcZrVc2wXRfybGlcZW3W/33qMbRRwX4y2RwNvhV/bhu/b1mdsUfVvAubXx3kLj38BcC7wapz9g4EVgAHnAS/Vx3k7lJd6DPENAR4K3z8EDK2h/pXACncvTWlUgUON7QtmZkA/YHFd2icjNnff4u5bw/f/BxQBqXpWah9gm7u/5e6fA4vCGOPFvBjoH56nIcAid9/r7m8D28Lj1Vts7v5cxL+p9cBJSfz+CcVWjUuAVe7+sbvvAlYBl6YxtuHAY0n8/tVy9+cJ/kiMZwjwsAfWA0eZ2fGk/rzVmhJDfMe6+3vh+/eBY2uoP4yD//HdFXYV7zWzFmmIraWZ5ZvZ+spLXMAxwCfuvi/cfhc4MQ2xAWBmfQj+6nszojiZ5+1EYEfEdqyf94s64XkpIThPtWmb6tgi3UDwl2alWL/f+o7tivB3tdjMTj7EtqmOjfDSW2dgTURxKs9bbcSLP9Xnrdaa9DOfzexZ4LgYu26N3HB3N7O4w7fCbN8dWBlRPJXgg7E5wbC0ycAd9RxbR3ffaWanAmvMrJDgQy8hST5vjwAj3X1/WJzQeWuszOxaIBu4MKL4oN+vu78Z+wgp8TTwmLvvNbP/Iuh19avH718bw4DF7l4RUZbu89bgNenE4O4D4u0zsw/M7Hh3fy/8ACuq5lBXA0+6e3nEsSv/at5rZguAifUdm7vvDL++ZWZrgXOAJQRd18PDv45PAnbWd2xm9mXgT8CtYXe68tgJnbcYdgInR2zH+nkr67xrZocDbYCPatk21bFhZgMIku6F7r63sjzO7zdZH3A1xubuH0Vs5hLcX6ps2zeq7dokxVWr2CIMA34QWZDi81Yb8eJP9XmrNV1Kim85UDkqYCTwVDV1D7qGGX4oVl7THwrEHKGQqtjMrG3lZRgzawd8A9jkwV2u5wjuicRtn+LYmgNPElxnXRy1L9nnLQ/oYsFIrOYEHxTRI1EiY74SWBOep+XAMAtGLXUGugD/SDCeQ4rNzM4BHgAud/eiiPKYv996ju34iM3Lgc3h+5XAxWGMbYGLqdqbTnlsYXynE9zEfTGiLNXnrTaWA9eHo5POA0rCP4hSfd5qLx13vDPhRXCNeTWwFXgWODoszwZyI+p1Isj0h0W1XwMUEnyw/Q5oXZ+xAV8Pv/8r4dcbItqfSvABtw34A9CinmO7FigHNka8eqbqvBGMAtlC8FfhrWHZHQQftgAtw/OwLTwvp0a0vTVs9wYwKAX/zmqK7Vngg4jztLym3289xjYTeC2M4Tng9Ii23w3P5zZgdH3HFm7fDsyKalcf5+0xgpF25QT3CW4A/hv473C/AfeHsRcC2fV13mr70sxnERGpQpeSRESkCiUGERGpQolBRESqUGIQEZEqlBhERKQKJQYREalCiUFERKpQYhARkSr+P92jBTbMLPVxAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f680b8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "66\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80cd5e80>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "67\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c8dba8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "68\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e22d30>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "69\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c78828>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "70\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f01978>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "71\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e86668>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "72\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d9f780>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "73\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e2d550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "74\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d9fb70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "75\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f334a8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "76\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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xCkgymZK/SLK0adPg6plE6fXXaNs2HtFIhlPyF0mW7GyIUGd/ObCJCFf5hAoEoHfvOAcmmUjJXyRZ8vMjrpoBjACOjrYP5xrcj0islPxFkqVDBxg8GGf1r+V5Cm/Mv0FmMGRIvWJvIodDyV8kiT4cNoyqBq7zb1Ag4BV5E4kDJX+RJJk/fz7/XlDAuhtvhEMtxZyVBVOnQl5eYoKTjKPCbiIJ5pxj6tSpPProo/ztb3+jT24unHlmw1U9a5h5Pf6pU2Hs2OQFLU2eev4iCbR3715uvPFGnnvuOVasWEFubq63YuxYKCqC4cO9K4ACgdobBgLe8uHDvXZK/BJn6vmLJMj27du57LLLOOKII3j77bc5+ug61/Lk5cG8eV6tnsJC787dbdu86/h79/au6tHJXUkQJX+RBPjss8+4+OKLGThwIL///e9p0aKBP7X27eH225MXnAga9hGJu5UrV3Luuedy0003MW3atIYTv4hP9FspEkdz585lwoQJPPvsswwdOtTvcEQiUvIXiQPnHJMnT+bJJ5/k9ddf58wzz/Q7JJEGKfmLNNKePXu46aabeO+991i5ciWdOnXyOySRqJT8RRph69atXHrppRxzzDEsW7aM1q1b+x2SSEzicsLXzAaZ2Udm9omZTQyz/kgz+0tw/f+ZWdd4HFfET59++in9+/cnJyeHl156SYlf0kqjk7+ZNQf+AAwGegJXmlnPOs2uA7Y5504FHgamNPa4In56++23Offcc7nlllv43e9+R/Pmzf0OSeSQxKPn/wPgE+fceufcHmAOMKxOm2F4VWsBXgQGmoUpbSiSBmbPns2IESOYMWMGY3XnraSpeIz5dwY2hLzeCJwdqY1zbp+ZVQLfA/4V2sjMxgBjAE466aQ4hCYSP8457rvvPv785z+zZMkSemtSFUljKXXC1zn3NPA0QF5e3mHWvRWJv++++47rr7+ejz76iJUrV9KxY0e/QxJplHgM+2wCTgx5fUJwWdg2ZtYCaANsicOxRRJuy5YtXHTRRVRVVbF06VIlfmkS4pH8i4FuZnaymR0BXAG8UqfNKxycm3ok8L/OHe6MFiLJs27dOs455xz69+/P3LlzyTrUOvwiKarRwz7BMfwJwGKgOfBn59wHZnYvUOKcewX4E/DfZvYJsBXvA0IkpRUVFXH55Zdz//33c/311/sdjkhcxWXM3zm3EFhYZ9kvQ57vBi6Lx7FEkmHmzJkUFBQwe/ZsLrzwQr/DEYm7lDrhK+K36upq7rnnHmbNmkVRURGnn3663yGJJISSv0jQ7t27yc/P58svv2TlypV06NDB75BEEkb1/EWAiooKLrjgAgCWLFmixC9NnpK/ZLy1a9dy9tlnc8EFFzB79mwCdefTFWmCNOwjTUt5uTcf7po1UFkJbdpAdjaMHh12PtwlS5Zw5ZVX8tBDDzFq1Kj6+xNpopT8pWkoLobJk2HRIu/17t0H1730EtxzDwweDJMmQd++APzpT3/izjvvZO7cuQwYMCD5MYv4SMlf0t/06VBQAFVVEO7ewaoq7+eCBbB4MdUPPcSdX37Jiy++yLJly+jRo0dy4xVJAUr+kt5qEv+uXdHbOge7drHnZz+jXdeurFy5knbt2iU+RpEUpBO+kr6KiyMm/jnA6UBr4N+At0LWtdq/n9s2b6bd558nJUyRVKTkL+lr8uSDQzohXgfuAJ4FvgWWAafUaWNVVd72IhlKyV/SU3m5d3I3zBj/PcAvgXPwfsE7Bx+1OAcLF0JFRaIjFUlJSv6SngoLwy7eD5QAFcCpePXFJwD1vx8AZhH3I9LUKflLelqzpvblnEFfA3vx5gp9C3gXWA38Jtw+qqqgrCyBQYqkLiV/SU+VlWEX19ybezNwPNAOuJU6JWdDbdsW78hE0oKSv6SnNm3CLm6LN9RjIcssbMuaDdrGLyaRNKLkL+kpOxtatQq7ajTwGFAObAMeBi4O1zAQAE3CLhlKyV/SU35+xFW/APoC3fGu9T8LuCtcQ+ca3I9IU6bkL+mpQwevVo/VH9RpCTwBbAf+CUwD6n1HMIMhQ8IWexPJBEr+krbcxInsbXGYFUoCAa/Im0iGUvKXtLRv3z7GPfssUzp0oPpQ6+9nZcHUqZCXl5jgRNKAkr+knR07djBs2DDWr1/Pzz78kGa/+52X0MMMAdVidjDxjx2bnGBFUpSSv6SVr776ih/+8Iccf/zx/M///A/HHHOMl8iLimD4cO8KoLrfBAIBb/nw4V47JX4RlXSW9PH+++8zdOhQxowZw5133omF9vTz8mDePK9WT2Ghd+futm3edfy9e3tX9ejkrsgBSv6SFmqmW3z44Ye56qqrIjds3x5uvz15gYmkKQ37SMqbOXMmP/3pT5k7d27DiV9EYqaev6Qs5xz33Xcfzz77LEuXLuX000/3OySRJkPJX1LSnj17uPHGGykrK2PFihV07NjR75BEmhQlf0k5lZWVjBw5kkAgQFFREa1bt/Y7JJEmR2P+klI2bNjAeeedR48ePZg/f74Sv0iCKPlLyli9ejX9+vUjPz+fxx57jObNm/sdkkiTpWEfSQmLFi3i2muvZfr06YwcOdLvcESaPPX8xXd//OMfGT16NAsWLFDiF0kS9fzFN9XV1dx999288MILvPXWW3Tr1s3vkEQyhpK/+OK7775j9OjRfP755yxfvpz2Kr0gklQa9pGk27p1K//xH//Bnj17WLJkiRK/iA+U/CWp1q9fT//+/enbty9z584lcKi1+EUkLhqV/M3sODN73cw+Dv5sG6HdfjN7N/h4pTHHlPT197//nfPOO48JEyYwdepUmjVT30PEL43965sILHHOdQOWBF+HU+Wc6xN8XNLIY0oaevnllxk6dChPPvkkEyZM8DsckYzX2OQ/DJgRfD4D+M9G7k+aoMcee4yxY8eycOFCLrlEn/0iqaCxV/t83zm3Ofj8n8D3I7RrZWYlwD7gQefcgnCNzGwMMAbgpJNOamRo4rfq6moKCgpYtGgR77zzDieffLLfIYlIUNTkb2ZvAOFKKt4V+sI558zMRdhNF+fcJjM7BfhfMytzzn1at5Fz7mngaYC8vLxI+5I0UFVVxdVXX82WLVtYvnw5bduGPR0kIj6JmvydcxdGWmdmX5vZ8c65zWZ2PFAeYR+bgj/Xm9lS4CygXvKXpqGiooJLLrmEU045hcWLF3PkkUf6HZKI1NHYMf9XgFHB56OAl+s2MLO2ZnZk8Hk74Fzgw0YeV1LUunXr6NevHwMHDuS5555T4hdJUY0d838QmGtm1wFfAJcDmFkecJNz7nrgdOApM6vG+7B50Dmn5J8uysu9CdHXrIHKSmjTBrKzYfToehOiv/POO1x66aXcd9993HDDDf7EKyIxMedSc2g9Ly/PlZSU+B1G5iouhsmTYdEi7/Xu3QfXBQLgHAweDJMmQd++vPDCC4wfP56ZM2cyaNAgf2IWEcxslXMuL1o71faR+qZPh4ICqKryknxdVVXezwULcIsX8/qPf8ytxcW89tpr9OnTJ7mxishh0S2WUltN4t+1K3ziD+UctmsX5y9YwHtjxyrxi6QRJX85qLj4YOIP42OgFXB1neUB5zju/vtBw3QiaUPJXw6aPPngkE4Y44G+kVZWVXnbi0haUPIXT3m5d3I3wlDPHOBYYGCk7Z2DhQuhoiJBAYpIPCn5i6ewMOKqb4BfAr+Ptg+zBvcjIqlDyV88a9bUvpwzxC+A64ATou2jqgrKyuIcmIgkgi71FAD2bdkS9pfhXeANYHWsO9q2LW4xiUjiKPlnoG+//ZZ3332XVatWsWrVKkpLS7n7o4+4MkzbpcDnQE2N1R3Afrz6HKXhdq4CbiJpQcm/iausrGT16tWUlpYeSPYbNmygd+/e5OTkMGDAAG677TZ6L1oE995bb+hnDHBFyOupeB8G08MdLBCA3r0T9U8RkThS8m9Ctm/fXivJl5aW8tVXX5GdnU1ubi4XXXQRd9xxB6effjotW7asvXGnTl7yryMr+KhxFN61/mGnXHcO8vPj9c8RkQRS8k9TW7duPZDga5J9eXk5ffr0IScnhyFDhvCLX/yCHj160KJFDP/NHTp4tXoWLGjwzt5fRVphBkOG1Cv2JiKpSYXd4JAqV/rhX//6V63e/KpVq9iyZQtnnXUWubm55ObmkpOTQ/fu3WnevPnhH6i4GAYMiHiHb4OysqCoCPKi1pMSkQSKtbBbZif/Q6xcmQxff/11vR79N998Q05ODjk5OQeS/amnnkqzZgm4Uje0tk+ssrJg6lQYOzb+8YjIIVHyjyZa5coaZt4HQQKS2+bNm+v16Hft2lUryefk5HDKKackJtFHEuN7Uw3sb9mSlo8+qsQvkiKU/BuS5N6tc45NmzbV69Hv2bPnQJKveXTt2hUzO+RjxF1JifetaOFC7wMwtOZP8FvRt+efz/C//53C99/nhBOi3gImIkmg5B9JhHHtrXh3sb4GtAMmAz+tu20M49rOOTZs2FCvR++cq9Wbz83N5aSTTkqNRN+QigrvfEhZmXcDV9u23uWc+fnQvj2//OUvWbt2LS+88ILfkYoISv6RjRgR9oqWK/GGMf6Ed1frUGA50Cu0kRkMHw7z5gFeov/8889rJfnS0lKaN29er0ffuXPn1E/0h6GqqoozzjiDxx9/nMGDB/sdjkjGU/IPp7wcunSpdyPTTqAt8D7QPbjsGqAz3iTFofa3bMn9N97IsrVrKS0tJRAI1OvRd+rUKb5xp7i//e1vjB8/nvfff59AIOB3OCIZTdM4hhOh4uQ6vDeie8iyM4GiMG337d9Pv3XryLv1VnJycujYsWPcw0w3gwYNIicnhwceeID77rvP73BEJAaZlfwjVK7cARxTZ1kb4NswuziyupqLvv9974YmOeCRRx7hzDPP5Oqrr6ZHjx5+hyMiUWRWSefKyrCLj8KrWR/qG+DoSPtR5cp6OnfuzF133cW4ceNI1aFEETkos5J/mzZhF3cH9uHNUVvjPeqc7A2lypVh3XzzzWzZsoXnn3/e71BEJIrMSv7Z2dCqVb3FrYEReLNV7QTeAV7GO+lbjypXRtSiRQuefPJJCgoK2L59u9/hiEgDMiv5N1Bx8gmgCuiAd9nndCL0/FW5skHnnHMOP/nJT7j77rv9DkVEGpBZyb+mcmWY6+2PAxbg9fy/JMwNXqDKlTGaPHkyL774IkkrzCcihyyzkj94RdoO91r0QMDbXhp03HHHMWXKFG666Sb279/vdzgiEkbmJf++fb0aPVlZ0duGqqnto5LFMbn22mtp3bo106eHnfNLRHyWeckfvOJsNR8A0UoumKlk8WEwM5544gl+/etfs3nzZr/DEZE6MjP5g5fIi4q8Wj2tWtUfCgoEvOXDh3vtlPgPWa9evbjuuuu47bbb/A5FROrIrNo+kUSpXCmHb+fOnfTq1YtnnnmGCy+8MOVnTRNJdyrsJinj1VdfZcaECfylTx+av/aatzAFZk0TaYpiTf6ZO+wjSfOTjRt5btMm7NVXvaRft75SVZW3bMECb64FnSQWSbjMKuwmyRecNa1VLJd8OudNslNQ4L3WeRaRhFHPXxKnuLjedJmPA3nAkUB+pO1qPgA07CeSMEr+kjiTJ9ee+xfoBNwN/L9o21ZVeduLSEI0Kvmb2WVm9oGZVZtZxBMMZjbIzD4ys0/MbGJjjilporwcFi2qN13mCOA/ge9F2945b/L4iooEBSiS2Rrb838f7+95WaQGZtYc+AMwGOgJXGlmPRt5XEl1EWZNOyRm8dmPiNTTqBO+zrm1QLSJyX8AfOKcWx9sOwcYBnzYmGNLioswa9ohqary7r0QkbhLxph/Z2BDyOuNwWX1mNkYMysxs5IKfd1PbxFmTTtkmjVNJCGi9vzN7A0g3CzldznnXo5nMM65p4GnwbvJK577liSLMGvaIdOsaSIJETX5O+cubOQxNgEnhrw+IbhMmrLsbJg3r97Qz77gY3/wsRvvlzDsL6JmTRNJmGQM+xQD3czsZDM7ArgCeCUJxxU/RZjt7DdAAHgQeC74/DeR9qFZ00QSprGXeg43s41AP+CvZrY4uLyTmS0EcM7tAyYAi4G1wFzn3AeNC1tSXoRZ034FuDqPX4XbXrOmiSR2MeysAAAFSklEQVSUCrtJ4hQXe7V6Qu7wjVlWlldKW5PniBwSFXYT/2nWNJGUpcJuklg1xdkKCrzr9hv6pmnmneTVrGkiCaeevySeZk0TSTnq+Uty5OV5l35q1jSRlKDkL8nVvj3cfrvfUYhkPA37iIhkICV/EZEMpOQvIpKBlPxFRDKQkr+ISAZS8hcRyUBK/iIiGUjJX0QkA6VsVU8zqwC+8DuOBrQD/uV3EDFKl1jTJU5In1jTJU5QrPHSxTkX9Xb5lE3+qc7MSmIpm5oK0iXWdIkT0ifWdIkTFGuyadhHRCQDKfmLiGQgJf/D97TfARyCdIk1XeKE9Ik1XeIExZpUGvMXEclA6vmLiGQgJf8YmdlxZva6mX0c/Nk2QruTzOw1M1trZh+aWdfkRhp7rMG2x5jZRjN7PJkxBo8dNU4z62NmK8zsAzNbY2b/leQYB5nZR2b2iZlNDLP+SDP7S3D9//nx/x2MI1qctwZ/H9eY2RIz6+JHnMFYGow1pN2lZubMzJeramKJ08wuD76vH5jZ7GTH2CjOOT1ieAC/BSYGn08EpkRotxS4KPj8KCArVWMNrn8UmA08nopxAt2BbsHnnYDNwLFJiq858ClwCnAE8B7Qs06bccCTwedXAH/x4X2MJc4f1fwuAmP9iDPWWIPtjgaWASuBvFSME+gGrAbaBl938OM9PdyHev6xGwbMCD6fAfxn3QZm1hNo4Zx7HcA5t8M5tyt5IR4QNVYAM8sFvg+8lqS46ooap3NunXPu4+Dzr4ByIFnzPf4A+MQ5t945tweYgxdzqNB/w4vAQDOzJMVXI2qczrk3Q34XVwInJDnGGrG8pwD3AVOA3ckMLkQscd4A/ME5tw3AOVee5BgbRck/dt93zm0OPv8nXtKsqzuw3cxeMrPVZvaQmTVPXogHRI3VzJoBvwMKkhlYHbG8pweY2Q/wemGfJjqwoM7AhpDXG4PLwrZxzu0DKoHvJSW6MDEEhYsz1HXAooRGFFnUWM0sBzjROffXZAZWRyzvaXegu5m9Y2YrzWxQ0qKLA83hG8LM3gA6hll1V+gL55wzs3CXSbUAzgfOAr4E/gLkA3+Kb6RxiXUcsNA5tzGRHdU4xFmzn+OB/wZGOeeq4xtl5jCzq4E84N/9jiWcYKfk93h/N6muBd7QzwC8b1LLzKy3c267r1HFSMk/hHPuwkjrzOxrMzveObc5mIjCfcXbCLzrnFsf3GYBcA4JSP5xiLUfcL6ZjcM7N3GEme1wzkU8AedTnJjZMcBfgbuccyvjGV8Um4ATQ16fEFwWrs1GM2sBtAG2JCe8ejHUCBcnZnYh3ofuvzvnvktSbHVFi/Vo4AxgabBT0hF4xcwucc6VJC3K2N7TjcD/Oef2Ap+Z2Tq8D4Pi5ITYOBr2id0rwKjg81HAy2HaFAPHmlnNmPQFwIdJiK2uqLE6565yzp3knOuKN/QzM96JPwZR4zSzI4D5ePG9mMTYwPv/7GZmJwfjuAIv5lCh/4aRwP+64Nm/JIoap5mdBTwFXOLz2HSDsTrnKp1z7ZxzXYO/myvxYk5m4o8aZ9ACvF4/ZtYObxhofTKDbBS/zzinywNvHHcJ8DHwBnBccHke8ExIu4uANUAZUAgckaqxhrTPx5+rfaLGCVwN7AXeDXn0SWKMQ4B1eOcZ7gouuxcvIQG0Al4APgH+Dpzi0+9ntDjfAL4OeQ9f8SPOWGKt03YpPlztE+N7anhDVB8G/96v8Os9PZyH7vAVEclAGvYREclASv4iIhlIyV9EJAMp+YuIZCAlfxGRDKTkLyKSgZT8RUQykJK/iEgG+v8L6mbzEB/P0wAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c4d898>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "77\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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icbpjx44RTwyN0yeffLJ3P0SU32cEcLP/iirdei+p0Tom6u0jSeWcY8qUKezcuZPnnnuOjh07Bh1S8qVpLybwjn99fX3EE0PjdENDA3379mWqc3yvqoq8w4ebbOcwkA/cCzwC7AeuAn7hz28inXovtdZo3SgTqhhTTL19JKkeeugh1q5dyyuvvJKdiR/SthcTgJnRo0cPevTowd/8zd9ELPfFF19QU1NDt9tvJy9MA/aHwEFgIbAWOA4YC/wE+GnzwunSe0mN1imRlLF9zGyUmb1jZtvMrEWbmJnlmdnT/vKNZjYoGfuV9rF8+XJmzZrF888/H3+9cyYZPty7YuwaVx+mtOjF1Oj444/n1FNPpXeEBuTGq/vvA33wRmC9k8hjMG1YsYLJkydz33338cQTT7B27Vqqqqo4dOhQ0mMPK0qj9Va8hwfdEG49PTioVQlf+ZtZR2Au3s2c1UC5mS11zm0JKXYzsNc59//M7Dq8ASCvTXTfknpvvPEGEyZMYMmSJQwaNCjocFKv8Uox06sYIvReKgCKaHp3crQRk/oNHcqwYcOoqqriueeeo6qqiqqqKmpra+nduzcDBw5kwIABDBgwoMX0iSeemPjvEeXBQbcDUWv2g2q0zpAG6WRU+5wLbHPO7QAwswV4/0mGJv+xHLspciEwx8zMpWuDgwBQW1vLFVdcwQMPPMCIESOCDqf9lJZ6/wVkci+mKL2XJuENSjcKr9rnAeDycNvIz6f/mDHcfvvtLRZ9+eWX1NTUsHPnzqMnhNdee41nn32Wqqoqdu7cSV5eXtSTQ+/evaOPxRTlwUELgB54jdfbIq3f3g8OitYgvXix91yINGqQTkby7we8H/K+Gm9037BlnHOHzKweOBn4KAn7lxTYv38/48aN4/rrr+f6668POpz2V1LiJc9M7cU0caKXbML4d7w/vFPxqk2uAWaGK+ict50wOnfuHPVuauccH3/88dETQePPjRs3Hp3+5JNPKCoqinhyGLxwIZ3DbPtT4G7gJbxG66gaHxyU6kbrDLyLOq0afM3sVrzngDBgwICAo8ldzjn+6Z/+ib59+3LvvfcGHU6wCgvTo7dLvHr18q4yw/ReOg74lf+KyMz7z6aNJzgzo2fPnvTs2ZNzzjknbJmGhgaqq6ubnBzWr1/PU089xc6dO7l3xw7+MUwi/Xe8euSiWAJpj0brDG2QTkbyrwH6h7wv8ueFK1NtZp2A7sDHzTfknHsYeBi8rp5JiE3a4L777uPtt99mzZo1iQ2RLMFK495L3i7yGTJkCEOGDAm73F1+ObzwQpN5rwMvAn+OYz9u796o7RoJidAgPQfvrunNwHf96SbS4C7qZCT/cmCImQ3GS/LXAf/YrMxSvIc7vQpcDbyk+v70tHDhQubPn8+GDRvoGm+vF0kvjb2XYr0qbZQmvZesR48W8/4IvAc01gt8jnfvwhZgU4TtPLViBf95+un0798/4uuEE5o/sidGERqk+wI/AlbiPfwnrIDvok44+ft1+Hfg/Z4dgf91zr1pZvcCFc65pXgDIT5mZtuAPXgnCEkzFRUVlJaW8vvf/56+ffsGHY4kQyb3XgrTaH0rTZPHbLyTQcSHaObnM27GDIrHjeP9998/+lq7du3R6erqavLy8iKeGIqKiujfv3/L8ZeiNEiP939W4DWChtXeDdLN6A5fAaC6uprzzjuPOXPmcNVVVwUdjiRbRUXm9V6K4QE79+D19nk8UoEYhqhwzrFnz54mJ4fmr5qaGrp169bkpPDtHTv4+osv0ungwYjb/hFe8i+LVCAFd1HrDl+J2RdffMGVV17J97//fSX+bJWJvZeiNFo3uifa+jE2WpsZJ598MieffDJnnXVW2DJHjhyhtra2yQmh20svRU38MQnwLmol/xx35MgRbrjhBs4880zuuuuuoMORVMu03ktp0mjdoUMHevfuTe/evRne2Ef/xRfhrbcS3/jevYlvow3UlSPHzZw5k48//pj58+d7o0GKpJN0HnIjhmdAxKSgIDnbiZOSfw4rKyvjmWeeYfHixXTuHO52GpE0UFp67ATQ2gWK2bHEn+pG6+Jir00hjEN4I6Ye9l/7/Xkt5Od71W4BUPLPUWvXruWuu+7i+eefp2fPnkGHIxJdaSmsWeMNm92li5c0Q+Xne/PHjfPKtUdvpQh3P4M3Smo+8DO8xuh8f14LUe6iTjXV+eeg7du3853vfIfHH3+c008/PehwRGKTbo3WURqk76GVxmhI+C7qRKmrZ46pr6/n/PPP54477mDKlClBhyOS2crL4aKL2tYg3bWr919KktslYu3qqWqfHHLo0CGuueYaLrnkEiV+kWRI5wbpVqjaJ4f8y7/8C2bGAw88EHQoItkjQ++i1pV/jpgzZw6rV6/m6aefplMnnfNFkiodG6RboSyQA1auXMlPf/pT1q9fT/dk9U0WkabSrUG6FUr+WW7Lli3ceOONLF68mFNOOSXocESyX4bcRa1qnyxWV1fHFVdcwezZsxk5cmTQ4YhIGlHyz1IHDhxg/PjxXHvttdx0001BhyMiaUbJPws557jtttvo1asXP/lJ2PsKRSTHqc4/C/385z9n8+bNvPzyy3oMo4iEpeSfZRYvXszcuXPZsGEDxx9/fNDhiEiaUvLPIps2beK2225jxYoV9OvXL+hwRCSNqU4gS9TU1DB27Fjmz5/P3/7t3wYdjoikOSX/LLBv3z7Gjh3LlClTGD9+fOsriEjOU/LPcEeOHOGmm25i6NChTJ8+PehwRCRDqM4/w919993s3r2bVatW6TGMIhIzJf8M9thjj/Hkk0+yceNG8vLygg5HRDJIQsnfzE4CngYGAe8B1zjnWjyK3sxWAOcB65xzlyeyz5xQW+sNDFVZCfX13oOii4th0qSjA0OtX7+ef/u3f2P16tUUptFgUSKSGRJ6kpeZ3Q/scc79zMymAwXOuR+GKXcJ0BW4Ldbkn5NP8iovh1mzYPly7/3+/ceW5ed744SPHk3NTTdRUlrKb37zG0aNGhVMrCKSltrrSV5jgUf96UeBq8IVcs6tAj5LcF/Zbd4873FwS5Z4ST808YP3kIj9+3FLlnDS+PE8eeGFSvwi0maJJv+vOOd2+dO7ga8kuL3cNG+e9xSgffuiPwUIMOfId46Ln3/eW09EpA1aTf5m9qKZvRHmNTa0nPPqjxJ6GryZ3WpmFWZWUVdXl8imMkd5+bHEH+IGoA/QDTgVeKT5evv2eevlWtWYiCRFqw2+zrlLIy0zsw/NrI9zbpeZ9QFqEwnGOfcw8DB4df6JbCtjzJrlVek0MwP4HyAPeBu4CDgbaHLvbkODt/6iRamPU0SySqLVPkuBCf70BOB3CW4vt9TWeo27Yap6huIlfgDzX9ubF3IOli3zHhsnIhKHRJP/z4BvmtlW4FL/PWZWYmZHayrMbC3wf8AlZlZtZv+Q4H6zQ1lZ1MVT8LpInYZXBTQmXCGzVrcjItJcQv38nXMfA5eEmV8B3BLy/uuJ7CdrVVa27NUT4lfAQ8CrwB859p9AEw0N3oOiRUTioLF9glRf32qRjsBIoBqI2Ldnb4v76kREolLyD1L37jEXPUSYOv9GBQXJiEZEcoiSf5CKi6FLlxaza4EFwOfAYWAl8BRh6tfAu/N32LAUBiki2UjJP0gTJ4adbXhVPEVAATAVeBC4Mlxh5yJuR0QkEo3qGaRevWD0aG9Ih5DunoXAmljWN4MxY44O9iYiEitd+Qdtxgyv6qYt8vO99UVE4qTkH7Thw9lx++3sa71kU127wuzZUNLq4H0iIi0o+Qfs3XffZcRvf8v2KVO8hN7a07jMjiX+0tL2CVJEso6Sf4B2797NqFGjuO+++xg2dy6sWQPjxnk9gJpXBeXne/PHjfPKKfGLSALU4BuQzz77jMsuu4xJkybxve99z5tZUuIN0lZX5w3ZsHmzdwNXQYHXnXPiRDXuikhSKPkH4Msvv+Tqq6+mpKSEH/3oRy0LFBbCtGntH5iI5AxV+7Qz5xy33HILeXl5zJ07F2utjl9EJAV05d/OZs6cydatW1m1ahWdOunwi0gwlH3a0Zw5c1i0aBHr16+na9euQYcjIjlMyb+dLF68mFmzZrFu3Tp69uwZdDgikuOU/NvBunXrmDx5MitWrGDw4MFBhyMiogbfVNuyZQvf/va3efzxxznnnHOCDkdEBFDyT6mamhrGjBnD7Nmz+da3vhV0OCIiRyn5p0h9fT2jR4+mtLSUG2+8MehwRESaUPJPgQMHDjBu3Di+8Y1vcNdddwUdjohIC0r+SXbkyBEmTpxIQUEBDz74oG7iEpG0pN4+STZt2jSqq6v5/e9/T8eOHYMOR0QkLCX/JPrlL3/JihUrWLduHfltfUCLiEg7SKjax8xOMrM/mNlW/2dBmDJnmdmrZvammVWa2bWJ7DNdLViwgAceeIDly5dTUNDiMIiIpJVE6/ynA6ucc0OAVf775vYBNznnhgKjgAfNrEeC+00rq1ev5gc/+AEvvPACAwYMCDocEZFWJZr8xwKP+tOPAlc1L+Cce9c5t9Wf/gCoxXtGeVaorKzk2muv5emnn6a4uDjocEREYpJo8v+Kc26XP70b+Eq0wmZ2LtAZ2B5h+a1mVmFmFXV1dQmGlnpVVVVcdtllPPTQQ1x88cVBhyMiErNWG3zN7EWgd5hFM0PfOOecmbko2+kDPAZMcM4dCVfGOfcw8DBASUlJxG2lgz179jBq1CjuvPNOrr02K5sxRCSLtZr8nXOXRlpmZh+aWR/n3C4/uddGKNcNeAGY6Zzb0OZo08T+/fsZO3Yso0eP5l//9V+DDkdEJG6JVvssBSb40xOA3zUvYGadgWeB3zrnFia4v8AdPnyY66+/nqKiIn7xi18EHY6ISJskmvx/BnzTzLYCl/rvMbMSM3vEL3MNcCEw0cxe919nJbjfQDjn+Od//mf27t1LWVkZHTroBmkRyUwJ3eTlnPsYuCTM/ArgFn/6ceDxRPaTLu6//35efvll1q5dS15eXtDhiIi0me7wBaithbIyqKyE+nro3h2Ki2HSJCj0eqU+9thj/OpXv+KVV16he/fuwcYrIpKg3E7+5eUwaxYsX+6937//2LLFi+HHP4bRo9lw8cVM/clPWL16Nf369QsmVhGRJMrd5D9vHkydCg0N4ML0Km1oAMAtWULxs8+y7s47GXLGGe0cpIhIauRmi2Vj4t+3L3ziD2HO0RUY8utfe+uJiGSB3Ev+5eXHEn+IPcA44HhgIPBk8/X27fPWq6holzBFRFIp95L/rFlHq3RC3Y437sSHwBNAKfBm80INDd76IiIZLreSf22t17jbrKrnC2AR8J/ACcBI4Eq8sSiacA6WLYMMGHdIRCSa3Er+ZWVhZ7+L1/J9asi8Mwlz5Q9gFnE7IiKZIreSf2Vl0+6cvs+Bbs3mdQc+C7eNhgbYvDn5sYmItKPcSv719WFnnwB82mzep8CJkbazd2/yYhIRCUBuJf8Id+aeChwCtobM+wswNNJ29JhGEclwuZX8i4uhS5cWs48HxgN34zX+rscbnvTGcNvIz4dhw1IYpIhI6uVW8p84MeKiXwENQC/gu8A8Ilz5Oxd1OyIimSC3kn+vXjB6tNdjp5mTgCV4V/5VwD+GW98Mxow5OtibiEimyq3kDzBjhld10xb5+d76IiIZLveS//DhMHs2dO0a33pdu3rrlZSkJi4RkXaUm6N6lpZ6P6ON6tnIzLvinz372HoiIhku9678G5WWwpo1MG6c1wOoeVVQfr43f9w4r5wSv4hkkdy88m9UUgKLFnlj9ZSVeXfu7t3r9eMfNszr1aPGXRHJQrmd/BsVFsK0aUFHISLSbnK32kdEJIcp+YuI5KCEkr+ZnWRmfzCzrf7PFoPemNlAM9tkZq+b2ZtmNjmRfYqISOISvfKfDqxyzg0BVvnvm9sFnO+cOwv4O2C6mfVNcL8iIpKARJP/WOBRf/pR4KrmBZxzXzrnDvhv85KwTxERSVCiifgrzrld/vRu4CvhCplZfzOrBN4Hfu6c+yDB/YqISAJa7eppZi8CvcMsmhn6xjnnzCzsrbLOufeBYr+6Z4mZLXTOfRhmX7cCtwIMGDAghvBFRKQtWk3+zrlLIy0zsw+SB2gzAAAGjUlEQVTNrI9zbpeZ9QFqW9nWB2b2BvB1YGGY5Q8DDwOUlJREGXNBREQSkWi1z1Jggj89Ae8ZKE2YWZGZ5fvTBcBI4J0E9ysiIglINPn/DPimmW0FLvXfY2YlZvaIX+Z0YKOZ/QVYA8x2zukJ6CIiAUpoeAfn3MfAJWHmVwC3+NN/AIoT2Y+IiCSXul2KiOQgc9HGsg+QmdUBOyMs7gl81I7hxCod41JMsUvHuBRT7NIxriBiGuica3U44rRN/tGYWYVzLu0eqZWOcSmm2KVjXIopdukYVzrG1EjVPiIiOUjJX0QkB2Vq8n846AAiSMe4FFPs0jEuxRS7dIwrHWMCMrTOX0REEpOpV/4iIpKAtE3+ZvYd/+EvR8wsYmu5mY0ys3fMbJuZTQ+ZP9jMNvrznzazzkmIKZaH11zsP7im8bXfzK7yl5WZ2V9Dlp2VaEyxxuWXOxyy76Uh84M6VmeZ2av+51xpZteGLEvasYr0HQlZnuf/3tv84zAoZNkMf/47ZvYPbY2hjXHdaWZb/GOzyswGhiwL+1m2Q0wTzawuZN+3hCyb4H/eW81sQvN1UxjTAyHxvGtmn4QsS9Vx+l8zqzVvrLJwy83M/tuPudLMzglZlpLjFDfnXFq+8IaF+BrwR6AkQpmOwHbgFKAz8BfgDH/ZM8B1/vSvgdIkxHQ/MN2fno43PHW08icBe4Cu/vsy4OoUHKuY4gI+jzA/kGMFnAoM8af74j34p0cyj1W070hImSnAr/3p64Cn/ekz/PJ5wGB/Ox2T9JnFEtfFId+d0sa4on2W7RDTRGBOhO/6Dv9ngT9d0B4xNSv/feB/U3mc/O1eCJwDvBFh+RhgOWDAecDGVB6ntrzS9srfOfeWc661AeDOBbY553Y4574EFgBjzcyAv+fYyKFhHzTTBq0+vKaZq4Hlzrl9Sdh3NPHGdVSQx8o5965zbqs//QHeqLCt3pwSp7DfkSixLgQu8Y/LWGCBc+6Ac+6vwDZ/e+0Sl3Nudch3ZwNQlKR9tzmmKP4B+INzbo9zbi/wB2BUADF9F3gqCfuNyjn3Mt6FXSRjgd86zwagh3kjH6fqOMUtbZN/jPrhPSCmUbU/72TgE+fcoWbzExXTw2tCXEfLL+JP/X8DHzCzvCTEFE9cXcyswsw2NFZFkSbHyszOxbuy2x4yOxnHKtJ3JGwZ/zjU4x2XWNZtq3i3fTPelWSjcJ9le8X0bf9zWWhm/eNcN1Ux4VeLDQZeCpmdiuMUi0hxp/I7FZeEBnZLlEV5UIxzrsXw0O0hWkyhb5yL/PAafzt9gGHAypDZM/ASYWe8LmA/BO5tx7gGOudqzOwU4CUz24yX6NokycfqMWCCc+6IP7vNxyrbmNkNQAnwjZDZLT5L59z28FtIqueAp5xzB8zsNrz/mP6+HfYbi+uAhc65wyHzgjpOaS/Q5O+iPCgmRjVA/5D3Rf68j/H+zerkX8k1zk8oJovv4TXXAM865w6GbLvxSviAmf0GmBpLTMmKyzlX4//cYWZ/BM4GFhHgsTKzbsALeCf8DSHbbvOxaibSdyRcmWoz6wR0x/sOxbJuW8W0bTO7FO9k+g137FnYkT7LRJNaqzE5byTfRo/gte00rntRs3X/mGA8McUU4jrg9tAZKTpOsYgUd6qOU9wyvdqnHBhiXm+Vzngf/lLntaysxqtzhwgPmmmDVh9eE6JF3aOfBBvr2a8CwvYUSEVcZlbQWHViZj2BC4AtQR4r/zN7Fq9udGGzZck6VmG/I1FivRp4yT8uS4HrzOsNNBgYAvypjXHEHZeZnQ3MB650ztWGzA/7WbZTTH1C3l4JvOVPrwS+5cdWAHyLpv/1piwmP67T8BpQXw2Zl6rjFIulwE1+r5/zgHr/giZVxyl+QbQyx/ICxuHVhx0APgRW+vP7AstCyo0B3sU7m88MmX8K3h/qNuD/gLwkxHQysArYCrwInOTPLwEeCSk3CO8M36HZ+i8Bm/ES2ePACUk6Vq3GBYzw9/0X/+fNQR8r4AbgIPB6yOusZB+rcN8RvCqkK/3pLv7vvc0/DqeErDvTX+8dYHSSv+OtxfWi/91vPDZLW/ss2yGmWcCb/r5XA6eFrPs9/xhuAya1V0z++3uAnzVbL5XH6Sm83mkH8fLUzcBkYLK/3IC5fsybCemxmKrjFO9Ld/iKiOSgTK/2ERGRNlDyFxHJQUr+IiI5SMlfRCQHKfmLiOQgJX8RkRyk5C8ikoOU/EVEctD/BzhJhdTeb3yLAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f83dd8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "78\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d75cf8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "79\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80ebdf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "80\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c51278>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "81\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e81358>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "82\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d10470>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "83\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c990b8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "84\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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t047+9Kc/MXr0aG666Saef/55JX4RiRvd+beDI0eOcMcdd7B69WpeeeUVRo4cGe+QRMTndOcfY5s2bSIzOKbO+vXrlfhFJCEo+ceIc45HH32Ur3/969x777384Q9/oHv37vEOS0QEULVPTOzfv59bbrmF3bt3s2bNGoYOHRrvkEREGtCdf5StWLGCESNGMHToUFavXq3ELyIJSXf+UVJVVcUDDzzA7373O37/+98zceLEeIckItIoJf8o+Oijj7jhhhtITU1lw4YNDBw4MN4hiYg0Scm/vvJyb3jksjI4eBDS0yEjA6ZPb3R45KVLl/Ld736X73//+9xzzz2kpITOsCsikniU/AFKSmD2bFi+3Fs+duzktsWL4b77YMIEbw7c4Exax44d48c//jFLly7lueeeY8yYMXEIXESkddTgm58P48fDkiVe0q+f+MGbKvHYMW/7+PGQn8/27dvJzs7m448/ZuPGjUr8IpJ0/J388/NPToYenAu3e8grBbgDvO1Hj/LFD37A/156KTNmzODZZ5+ld+/e8YpeRKTV/FvtU1JyMvHXcyTk/RnA/6u3LvXECX7ZqROdRo3yJkgXEUlC/r3znz3bq9JpwiKgP5Absr7T8ePe/iIiScqfyb+83GvcDVb1NKYQuBk45f7eOVi2zJs8XUQkCfkz+RcUNFvkA2AFMK2xAmYRHUdEJBH5M/mXlZ3aqyfEPCAHOLexApWVsHlzlAMTEWkf/kz+Bw82W+RJmrjrr1VREY1oRETanT+Tf3p6k5tXA7tp2MsnLHXzFJEk5c/kn5EB3bo1urkQuBro0dQxAgEYPjzKgYmItA9/Jv+8vCY3P45X598k55o9johIovJn8u/f3xurp7UPaZnBxImNDvYmIpLo/Jn8wRukLRBo3b6BgLe/iEiS8m/yz8qCOXMgLa1l+6WlefsFJ2UXEUlG/h3bB2DGDO/nzJlev/2mnvg18+7458w5uZ+ISJLy751/rRkzYMUKmDLF6wEUWhUUCHjrp0zxyinxi0gH4O87/1qZmbBokTdWT0EBi37xCyZkZ5M2aJDXnTMvT427ItKhmGtmcLOIDmL2TeBXeMPfP+GcezBke1e8h2ZHAfuBbzvn3m/qmJmZma60tLTNsbWUc460tDQ+/fRTTjvttHY/v4hIW5jZeudcs42Sba72MbMU4DFgAnAhcL2ZXRhS7DtAhXNuKPAI8FBbzxsrR44cISUlRYlfRDq0aNT5XwbscM6955w7ASwAJoeUmYz34CzAQuBrZok5E0p5eTn9+/ePdxgiIjEVjeQ/CPio3vKu4LqwZZxzVcBB4PQonDvqlPxFxA8SqrePmd1mZqVmVrovThOlKPmLiB9EI/nvBs6ut3xWcF3YMmbWGUjHa/htwDk31zmX6ZzL7Ben3jVK/iLiB9FI/iXA+WZ2rpl1Aa4DloaUWcrJ4fGvAV530ehmFANK/iLiB21O/sE6/NuBl4G3gWecc1vM7H4zmxQs9n/A6Wa2A/gh8JO2njdWlPxFxA+i8pCXc24ZsCxk3c/rvT9GBHOjJILy8nIuv/zyeIchIhJTCdXgmwh05y8ifqDkH+KTTz5hwIAB8Q5DRCSmlPxD6M5fRPxAyb+e6upqKioqOP30hHz+TEQkapT869m/fz+9evWic2cNdioiHZuSfz2q8hERv9AtLkB5ORQU0PeVV/jfvXvhxhshIwOmT9c4/iLSIUVlPP9YaJfx/EtKYPZsWL7cWz527OS2QMCb1nHCBG+y9qys2MYiIhIF7Taef9LKz4fx42HJEi/p10/84M3pe+yYt338eK+8iEgH4c9qn/x8b9L2o0ebL+ucV27mTG9Zc/iKSAfgvzv/kpJGE/8C4CvAacB5QFH9jbUXgDhMLSkiEm3+S/6zZ3tVOiH+AtwD/AE4DKwEvhRaqLLS219EJMn5K/mXl3uNu2Eaue8Dfg5k4/1SBnHqdGQ4B8uWQZwmmhERiRZ/Jf+CgrCrq4FSYB8wFG82mtuBU78fAGaNHkdEJFn4K/mXlZ3aqwf4BPgCb2b5ImATsBF4INwxKith8+YYBikiEnv+Sv4HD4ZdHQj+vAM4E+iLN+PMsrClgYqKaEcmItKu/JX809PDru6NV9Vj9dZZ2JK1O/SOXkwiInHgr+SfkQHduoXdNB14FCgHKoBHgCvDFQwEYPjwWEUoItIu/JX88/Ia3XQvkAVcgNfXfyTw03AFnWvyOCIiycBfyb9/f2+sHju1UicV+C1wANgL/BoI/Y5QDey65BJc376xjlREJKb8lfzBG6QtEGi+XDhdu3L3/v1cccUVrF+/PrpxiYi0I/8l/6wsmDMH0tJatl9aGimPPMIft23j5ptv5sorr2T69Ol8/PHHsYlTRCSG/Jf8wRucrfYCEKYKqAEzr9ycOTBjBikpKdx6661s376dM844g+HDh/PAAw9QGWbICBGRROXP5A/eBWDFCpgyxesBFFoVFAh466dM8cqFjObZs2dPZs+eTWlpKWVlZQwbNoynnnqKRJ0fQUSkPn9P5lJr3z5vyIbNm70HuHr39rpz5uVFPJNXUVERd911F6mpqTzyyCNkZ2fHNGQRkXAincxFyT+KampqmDdvHj/96U+54oorePDBBzn77LPjHZaI+Ihm8oqDTp06MW3aNLZt28Z5553HiBEj+PnPf86RI0fiHZqISANK/jHQvXt37r//fjZu3MjOnTsZNmwYhYWF1NTUxDs0ERFAyT+mBg8ezPz581m4cCH5+flcfvnlFBcXxzssEREl//aQnZ3NmjVruOuuu5g6dSrXXnstf//73+Mdloj4mJJ/OzEzpk6dyrZt2xg+fDhZWVnMmjWLQ4cOxTs0EfEhJf92lpaWxr333ktZWRl79uxh2LBhPPHEE1RXV8c7NBHxESX/OBk4cCAFBQUsXbqUwsJCRo0axRtvvBHvsETEJ5T84ywzM5OVK1fys5/9jFtuuYUpU6awY8eOeIclIh2ckn8CMDOuueYa3n77bbKzs8nOzmbmzJkcOHAg3qGJSAel5J9AunXrxj333MOWLVs4dOgQw4YNIz8/n6qqqniHJiIdjJJ/AhowYABz587l5Zdf5tlnn2XEiBG88sor8Q5LRDoQJf8Edskll/Daa6/xX//1X3zve9/jyiuvZNu2bfEOS0Q6ACX/BGdmTJ48mS1btvAP//AP5Obm8v3vf5/PPvsssgOUl8Mvfwk33ghXXeX9/OUvvZFMRcS32pT8zayPmf3FzN4N/uzdSLlqM9sUfC1tyzn9qkuXLvzwhz9k69atVFVVMWzYMH7961/zxRdfhN+hpASuvhrOOQfuuw/mz4cXX/R+/uIXMHiwt72kpF0/h4gkhrbe+f8EeM05dz7wWnA5nErn3Ijga1Ibz+lr/fr147HHHuONN97gpZdeYvjw4bz00ksNJ5HJz4fx42HJEjh2zHvVV1nprVuyxCuXn9+eH0FEEkBbk/9koDD4vhD45zYeTyJ00UUX8ec//5mHH36YmTNn8o1vfIO33nrLS+QzZ8LRoxAyV8O7QDfgxtoVznnlZs7UBUDEZ9qa/Ac45/YE3+8FBjRSrpuZlZrZWjPTBSJKzIyJEydSVlbGVVddxQ9zczl+551eQg/je0BWuA21F4AkmzxHRFqv2eRvZq+a2VthXpPrl3NevUNj04KdE5xZZirwP2Z2XiPnui14kSjdpwbJiKWmpnLHHXfw4tixpDbyTMACoBfwtcYOUlkJs2fHKEIRSTSdmyvgnPvHxraZ2SdmdqZzbo+ZnQmUN3KM3cGf75nZX4GRwM4w5eYCc8GbxjGiTyCe8nK6vPZa2E2HgJ8DrwNPNLa/c7BsmdcLKMJ5i0UkebW12mcpMC34fhrwfGgBM+ttZl2D7/sCY4GtbTyvhCooaHTTvcB3gLOaO4ZZk8cRkY6j2Tv/ZjwIPGNm3wE+AK4FMLNM4F+dc7cCXwEeN7MavIvNg845Jf9oKys7tVcPsAl4FdgYyTEqK2Hz5igHJiKJqE3J3zm3nzDVyM65UuDW4PvVwPC2nEcicPBg2NV/Bd4HBgeXjwDVeF+9NoTboaIi6qGJSOLRE74dRXp62NW34TWubAq+/hX4J+DlRg6z+u23KSws5L333mv47ICIdChK/h1FRgZ063bK6jTgjHqv7nh9/cM16dZ07YobPpzly5eTk5PD2WefzfXXX09+fj5vvfUWNTU1sfwEItKOLFHv7jIzM12p+p1HrrzcG8ohTL1/xLp1gw8/hH79cM6xc+dOioqKWLlyJUVFRVRUVJCbm0tubi7jxo1j5MiRdO7c1mYjEYkmM1sf7FrfdDkl/w7k6qu9IRta829qBlOmwKJFjRbZvXs3RUVFdReEDz74gOzsbMaNG0dubi6XXXYZgUCgDR9ARNpKyd+PSkq8sXoaecK3SWlpsGIFZDb7N1Nn//79rFq1qu5isGXLFkaMGMG4ceMYN24cY8aMoWfPni2PRURaTcnfr+qP7ROptDSYMwdmzGjTqY8cOcLatWvrqolKSkr48pe/XFdNlJubSz89QCYSU0r+flZ7AaisbLoKyAwCgagk/nCOHz/O+vXrWblyJStXrmT16tWceeaZdReCcePGMXjw4OYPJCIRU/L3u9JSb6yeZcu8JF9ZeXJbIOBdFCZOhFmzWlTV0xbV1dWUlZXVVROtXLmSQCBQV02Um5vLl7/8ZcysXeIR6YiU/MWzb583ZMPmzd4DXL17w/DhkJcX9zF8nHO88847ddVEK1eu5OjRow2qiS655BJSUlLiGqdIMlHyl6T04YcfNuhe+vHHHzNmzJi6C0JmZiZdu3aNd5giCUvJXzqEffv2UVxcXFdNtH37djIzM+u+GYwePZru3bvHO0yRhKHkLx3SoUOHWL16dd23g40bN3LhhRfWtRvk5OTQp0+feIcpEjdK/uILx44dY926dXXVRGvWrOGcc85p0G4waNCgeIcp0m6U/MWXqqqq2LRpU101UXFxMenp6Q26l5533nnx6VFUXu41vpeVeaOwpqd7YzJNnx73xnfpOJT8RYCamhrefvvtBt1Lq6urG1wMLr74Yjp1iuEYhyUlXrfb5cu95frjL9V2u50wwet2mxV2lmWRiCn5i4ThnOP9999v0L30008/ZezYsXUXhFGjRpGamhqdEybIA3fiH0r+IhHau3dvgwHrdu7cyeWXX173zeDyyy8nLS2t5QeO41Ab4l9K/iKtdODAAVatWlX37eBvf/sbl1xySd03g7Fjx9KrV6+mDxJmkL3jwL/hTav5GXAeMBuYELpvKwbZE6ml5C8SJUePHmXt2rV13wzWrVvHeeed12BYigEDBjTcKczw2p8D/w3k4U2ruQy4HtgMDKm/bwTDa4s0RslfJEZOnDjBhg0b6r4ZFBcX079//7pqoiu+8hUGjxuHRTCxTgZwH/Ct0A31JtYRaQklf5F2UlNTw1tvvVV3Mbho2TLuPnKE5qa1+QQ4B29u5WGhGwMB+I//gLvvjkXI0oFFmvw1B59IG3Xq1ImMjAwyMjK4/fbbcTfeiM2f3+Q+XwA3ANMIk/jB6x20eXP0gxUJUvIXiTI7eLDJ7TXATUAX4DdNlPtg0yZKFi6kT58+da/evXvTvXt3DXudyJLkYT4lf5FoS09vdJMDvoNX5bMMaOppgo8rK3nqqaeoqKjgs88+q3sdP368wcWg/sUh3Lra5V69etG5s/7Lx0xTD/MtXgz33ZdQD/PpL0Ek2jIyvJ46YRp8ZwBv43X3bLJNIBBg9G23sShMnf+JEydOuSDUX96+ffsp2z/77DMOHjxI9+7dm7xANLYuEGiuBcPnmnuYr3YypSVL4OWXE+JZDjX4ikRbeTmcc84pyf8DvC6dXWl41/U4Xv1/AzHo7VNTU8OhQ4fCXjAaW1dRUcH+/fsxsxZfMPr06UPPnj1jO3RGIkiwh/nU20cknsL0849YAvbzr6ysbPIC0dhF5MiRI6Snp0dULRW6rkuXLvH+2M0L8zAfeA/xfQd4BeiL9zDf1NB9Y/Qwn5K/SDw1khQi0oGe8K2qquLAgQMRf8uov9y1a9dWtW20a4N4Ixf56/Ea9v8PryvvPwGrgYvqF4rRRV7JXyTeEqw6IJk45zhy5EiLvmXUvk6cOFEM8m/7AAAG60lEQVR3IWhJVVWLG8Qbqd77HOgNvAVcEFx3EzAIeDD0GDGo3lM/f5F4q03gGtWzxcyMHj160KNHDwYPHtyifdvaIB7pt4wLnn+eAUBoi8Y7eIn1gnrrLgFWhP+gXrfQODzMp+QvEkszZnjd+mbPhmXLvP/stT0/4OR4/hMnel0AO0BVT7x16dKFAQMGnDreUjOaaxDfs2cPW7durVu+u6yMq8L06DoC9AxZlw4cDnfSOD7Mp+QvEmuZmV697r593l3e5s1QUQG9e8Pw4ZCXl1AP//hVp06d6NWrF7169eJLX/pS8ztcdRW8+OIpq7sDh0LWHQJ6NHacioqWBRolSv4i7aVfP43V05E08jDfBUAV8C5wfnDd3whp7K2vd+9oRxaRDt4BV0QkRjIyvAbbEKcBVwM/x2v8XQU8j9foe4pAwPv2FwdK/iIirZGX1+im3wKVQH+8bp/5NHLn71yTx4klJX8Rkdbo398bqyfMMwV9gCV4d/4fEuYBL/D2mzgxbu09Sv4iIq01a5ZXddMagYC3f5wo+YuItFZWlvdsRlpay/arfZgvjl171dtHRKQtkvRhvjbd+ZvZ/zOzLWZWY2aNXsLM7Jtmtt3MdpjZT9pyThGRhDNjhjce05QpXg+g0KqgQMBbP2WKVy4BnuJu653/W3i9mh5vrICZpQCPAV8HdgElZrbUObe1jecWEUkcSfYwX5uSv3PubaC5EfQuA3Y4594Lll0ATAaU/EWk40mSh/nao8F3EPBRveVdwXWnMLPbzKzUzEr37dvXDqGJiPhTs3f+ZvYqcEaYTT91zj0fzWCcc3OBueAN6RzNY4uIyEnNJn/n3D+28Ry7gbPrLZ8VXCciInHSHtU+JcD5ZnaumXUBrgOWtsN5RUSkEW3t6jnFzHYBo4GXzOzl4PqBZrYMwDlXBdwOvAy8DTzjnNvStrBFRKQt2trb5znguTDrPwYm1lteBixry7lERCR6NLyDiIgPKfmLiPiQuabGoYgjM9sHfBDvOFqoL/BpvINopWSNPVnjBsUeD8kaN0Qe+znOuWYfJU7Y5J+MzKzUOZeUM3Ana+zJGjco9nhI1rgh+rGr2kdExIeU/EVEfEjJP7rmxjuANkjW2JM1blDs8ZCscUOUY1edv4iID+nOX0TEh5T828DM+pjZX8zs3eDP3mHKjDCzNcEZz8rM7NvxiDVUJLEHy/3ZzA6Y2YvtHWNIHE3OBmdmXc3s6eD2N81sSPtHGV4EsY8zsw1mVmVm18QjxnAiiPuHZrY1+Hf9mpmdE484w4kg9n81s81mtsnMis3swnjEGU6kMx+a2bfMzDU1i2KTnHN6tfIF/BL4SfD9T4CHwpS5ADg/+H4gsAfolQyxB7d9DbgKeDGOsaYAO4EvAV2AvwEXhpT5N+B3wffXAU/H+3fcgtiHABnAk8A18Y65BXF/FUgLvp+RZL/znvXeTwL+HO+4I409WK4HsBJYC2S25ly682+byUBh8H0h8M+hBZxz7zjn3g2+/xgoBxJhLrdmYwdwzr0GHG6voBpRNxucc+4EUDsbXH31P89C4GvWzBRz7aTZ2J1z7zvnyoCaeATYiEjifsM5dzS4uBZvuPZEEEnsh+otngYkSuNnJH/rAP8JPAQca+2JlPzbZoBzbk/w/V5gQFOFzewyvKv5zlgHFoEWxR5nkcwGV1fGeSPJHgROb5fomhbxTHYJpqVxfwdYHtOIIhdR7Gb2PTPbifct+M52iq05zcZuZpcCZzvnXmrLido6gXuH19RMZvUXnHPOzBq9ezCzM4F5wDTnXLvc4UUrdpGmmNmNQCZwRbxjaQnn3GPAY2Y2FfgZMC3OITXLzDoBDwN5bT2Wkn8zXBMzmZnZJ2Z2pnNuTzC5lzdSrifwEt7Ul2tjFOopohF7gohkNrjaMrvMrDOQDuxvn/CalKwz2UUUt5n9I97NxBXOuePtFFtzWvo7XwDkxzSiyDUXew/gYuCvwVrNM4ClZjbJOVfakhOp2qdtlnLybmEacMqcxsHZy54DnnTOLWzH2JrTbOwJJJLZ4Op/nmuA112wZSzOknUmu2bjNrORwOPAJOdcIt08RBL7+fUW/wl4tx3ja0qTsTvnDjrn+jrnhjjnhuC1tbQ48dceTK/Wt8yfDryG94fzKtAnuD4TeCL4/kbgC2BTvdeIZIg9uFwE7AMq8eofvxGneCcC7+C1l/w0uO7+4B8+QDfgWWAHsA74Urx/xy2IPSv4u/0c79vKlnjHHGHcrwKf1Pu7XhrvmFsQ+6+ALcG43wAuinfMkcYeUvavtLK3j57wFRHxIVX7iIj4kJK/iIgPKfmLiPiQkr+IiA8p+YuI+JCSv4iIDyn5i4j4kJK/iIgP/X+8rcITUztsYAAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80cb75c0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "85\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e0b3c8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "86\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f154a8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "87\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f935c0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "88\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f962e8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "89\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d3a860>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "90\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80ca4dd8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "91\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f09eb8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "92\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e6ef28>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "93\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80dbdda0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "94\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c2ec18>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "95\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d84ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "96\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e3e588>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "97\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f33780>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "98\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80da07b8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "99\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f8b6d8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "100\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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FF3HdddfxyiuvND8JiKSYzghEWundd99l7NixfPLJJ/zpT3/i3HPPTXVIIi2iMwKRo+Sco6SkhL59+3LZZZexatUqJQHJSDojEDkKu3fv5pZbbuGdd95hxYoVnHfeeakOSeSo6YxApIUWLFjA+eefT58+fSgrK1MSkIynMwLJPhUVfqlmebnvD5Cb66uCjhkTdanm3r17ue2229i4cSPPP/88F154YfJiFkkgJQLJHmVl/uat5cv969BOYYsWwdSpMHiwv3mr35Ht45cuXcott9zC8OHD2bhxI4FAIImBiySWEoFkh+JimDjR37kbrnF8wx29paXwwguHyjl88skn/OQnP+Hll1/m6aefZuDAgUkNWyQZlAik7WtIAtXVscc658dNnMibb73FoNJSvv3tb1NeXk7nzp0TH6tICuhisbRtZWVNksDn+CbxXwY6A+cDyxu/r7qaMx99lN/efjtz5sxREpA2TYlA2rbp048s5AYcBM4AVgL7gGnAcHzP4FAB4OsrVyY+RpEUUyKQtquiwl8YbnRN4Dh8B7Ae+P8AVwFnAesbvd2c81VBKysTH6tICikRSNtVUtKsYR8CfwG+Gm6nWbOPI5Kp4pIIzGyQmb1lZjvM7K4w+zua2TPB/WvMrEc8PlckqvLyI5eIhlELjARGA2GLQ9TU+NLQIm1YqxOBmbUHHgMGA72B75lZ70bDxgJVzrl/AGYBM1r7uSIx7dsXdXc98AOgAzA72sCqqvjFJJKG4nFG0B/Y4Zx72zn3BTAfGNpozFBgXvD5s8DlFrFTh0ic5OZG3OXwv518CCwEjo12nC5d4hqWSLqJRyI4DXgv5PWu4LawY5xzB/GLNU5ufCAzu9nM1pnZukpdoJPWysuDTp3C7ioCtgFL8KuDIgoEfKcwkTYsrS4WO+fmOufynXP5XdWeT1qrsDDs5p3AHGATcCpwfPDxdLjBzkU8jkhbEY9E8D5+WXaD04Pbwo4xs2OAXGBvHD5bJLJu3WDwYOobzUJ+GT81dADYH/IY2fj9Zr5xvH4pkTYuHomgDOhpZmeZWQdgBLC40ZjF+IUZANcBLzsXruCLSPzU1tby6HHHEX3dUBSBgC9AJ9LGtToRBOf8bwNewE+7/t45t8XM7jezq4PD/h042cx2ALcDTZaYisTTe++9xze+8Q3+sHcvdTNmQE5Oyw6Qk+MLz+XnJyZAkTQSl6JzzrllwLJG2+4NeX4A+G48PksklqVLlzJ27Fhuv/12Jk2aRLt27eD446NXH21g5s8EgtVHRbKBqo9Km1FbW8s999zD/PnzWbhwIZdeeunhnUVFvsfA9Om+bITZkTWIAgGfIIYM8dNBOhOQLKJEIG3Cu+++y4gRI+jSpQsbNmzglFNOaTooPx8WLvS1g0pK/B3DVVX+PoE+ffzqIF0YliykRCAZr2Eq6I477mDixIl+Kiiarl1h0qTkBCeSAZQIJGPV1tZy991388wzz7Bo0SIuueSSVIckkpGUCCQjNWsqSESaJa3uLBZpjiVLltCvXz+uueYalixZoiQg0ko6I5CMoakgkcRQIpCMsHPnTkaMGMFJJ53Exo0bOfnkJjULReQoaWpI0t6SJUvo378/w4YNY8mSJUoCInGmMwJJnooKv36/vNw3jcnN9aWix4wJu36/traWyZMns2DBAp577jm+/vWvJz9mkSygRCCJV1bm7+hdvty/Dm0fuWgRTJ0Kgwf7O3r79QMOTwWdfPLJbNiwQWcBIgmkqSFJrOJiGDgQSkt9AmjcQ7imxm8rLfXjiosPTQVde+21LF68WElAJMF0RiCJU1zsC71VV8ce6xxUV/PF+PG83rkzzy1dqqkgkSTRGYEkRllZ2CQwCugOnAD0Ap5o9LYOBw/ywIEDfL1Dh+TEKSJKBJIg06cfWd0zaDLwDvAJvlvRFGB9ozF24IB/v4gkhRKBxF9Fhb8wHKbu/1eBjsHnFnz8tfEg53yp6MrKhIYpIp4SgcRfSUnU3eOAHOBc/DTRkHCDzGIeR0TiQ4lA4q+8vOnqoBCPA58C/w0M4/AZwhFqany/ABFJOCUCib99+2IOaQ9cCuwCiiMNqqqKX0wiEpESgcRfbm6zhx4kzDWCBl26xCMaEYlBiUDiLy8POnVqsrkCmA/sB+qAF4DfAZeHO0Yg4NtHikjCKRFI/BUWht1s+Gmg04EuwETgYeDqcIOdi3gcEYkv3Vks8detG3Xf+ha2ePERv2l0BVY25/1mMGSIGsmLJInOCCTu3n77bW54801q27c/ugMEAr4AnYgkhRKBxNWyZcu4+OKLufDWW+nwy19CTk7LDpCTAzNnQn5+YgIUkSY0NSRxUV9fz/33388TTzzRtI3kxIn+voAwdxofYubPBGbOhKKixAcsIocoEUirffTRR4waNYrPPvuMdevWceqppx7eWVTkewxMn+7LRpgdWYMoEPAJYsgQPx2kMwGRpFMikFbZuHEj1157LQUFBTz44IMce+yxTQfl58PChb52UEmJv2O4qsrfJ9Cnj18dpAvDIimjRCBH7cknn+Sf//mfeeyxxxg+fHjsN3TtCpMmJT4wEWkRJQJpsc8//5zx48ezcuVKVq5cSe/evVMdkoi0glYNSYu8++67DBgwgL1797J27VolAZE2QIlAmm3FihX079+f4cOHs2DBAk444YRUhyQicaCpIYmpvr6eBx98kNmzZ/O73/2Oyy67LNUhiUgcKRFIVB9//DGjR4+msrKSsrIyTjvttFSHJCJxpkSQLSoq/NLN8nLfLyA311cJHTMm4tLNzZs3M2zYMAYNGsSCBQvooIbyIm2SEkFbV1bmb+Zavty/Du0ctmgRTJ0Kgwf7m7n69Tu06+mnn2bChAnMmjWLUaNGJTloEUkmJYK2rLg4enmHhjt8S0vhhRdg5ky+GDuWO+64g+XLl/PSSy+Rl5eX3JhFJOlatWrIzE4ysxfNbHvwz7Atpcyszsw2BR+LW/OZ0kwNSaC6OnqNH/D7q6upv+MOHj73XHbu3Mm6deuUBESyRGuXj94FvOSc6wm8FHwdTo1z7vzgI2wfEomjsrLDSSDEQKATcHzwcU6jt7WrqWHCrl2UTpnCiSeemJRQRST1WpsIhgLzgs/nAde08ngSD9OnH1nYLcRsfKvI/cBbYfZ3OHiQdjNmJDA4EUk3rU0EX3LOfRB8vhv4UoRxncxsnZmtNjMli0SqqPAXhmNNB0XinK8SWlkZ37hEJG3FTARmtsLM/hzmMTR0nHPOAZF++nzZOZcPfB942Mz+PsJn3RxMGOsq9YPo6JSURN09GTgFuAR4NdIgs5jHEZG2I+aqIefcFZH2mdmHZtbdOfeBmXUHKiIc4/3gn2+b2avA14C/hhk3F5gLkJ+ff5S/0ma58vIjl4iGmAH0BjoA84HvAJuAJlm5psaXihaRrNDaqaHFwOjg89HA840HmFkXM+sYfN7wy+jWVn6uRLJvX8RdFwKdgY74f6xLgGWRBldVxTsyEUlTrU0EDwJXmtl24Irga8ws38yeCI75CrDOzN4AXgEedM4pESRKbm6zhxqR5/LoEnYlsIi0Qa26ocw5txe4PMz2dcAPg8//B+jTms+RFsjL893AGk0PfQysAb6B/0d/BngNeCTcMQIB3zlMRLKCylC3NYWFYTfXAlOArviLxb8ESoFe4QY7F/E4ItL2KBG0Nd26weDBOLMjNncFyoBP8WcHq4Erw73fzDeSVw9hkayhRNAGrb38cmqO9j6CQMAXoBORrKFE0IbU1dVx3333cc0DD/DuP/0T5OS07AA5OTBzJuTnJyZAEUlLqj7aRlRUVDBy5Ehqa2tZv3493bt3h3POiV59tIGZPxOYOROKipIXtIikBZ0RtAGvvfYaF1xwARdeeCErVqzwSQD8D/WVK6GgADp18j/sQwUCfntBgR+nJCCSlXRGkMHq6+t56KGHmDVrFk8++SSDBw9uOig/3y8nraz0ZSM2b/Y3i3Xp4peIFhbqwrBIllMiyFB79+7lhhtuoKqqirKyMs4444zob+jaFSZNSk5wIpJRNDWUgdasWUPfvn35yle+wsqVK2MnARGRKHRGkEGcczz66KP8/Oc/Z+7cuQwdOjT2m0REYlAiyBD79u3jxhtvZOfOnaxevZqzzjor1SGJSBuhqaEMsGHDBvr27Uv37t1ZtWqVkoCIxJXOCJKposKv3Ckv9+Wic3N9kbgxY8Ku3HHOMWfOHH76058ye/Zsrr/++uTHLCJtnhJBMpSV+T7Cy5f716GVQRctgqlTYfBgX9qhXz8APv30U2655Rb+/Oc/s2rVKnr1ClseTkSk1TQ1lGjFxTBwIJSW+gTQuHtYTY3fVlrqxxUXs3nzZvr160dOTg5r1qxREhCRhNIZQSIVF/sSD9XVscc6B9XV1E6YwLxjj+Xuxx/nhhtuSHyMIpL1lAgSpaysSRI4vtGQGmAcvjdAg2O/+IJftGtHu969kxCkiIimhhJn+nQ/7RNif8hjNxAAvhvmre0+/9y/X0QkCZQIEqGiwl8YjlLxcyHQDRgQbqdzsGyZrw8kIpJgSgSJUFISc8g84AZ8A/mwzJp1HBGR1lIiSITy8qarg0LsBFYCo6Mdo6bGVwoVEUkwJYJE2Lcv6u7/AC4FYt4fXFUVp4BERCJTIkiE3Nyou58ixtlAgy5d4hGNiEhUSgSJkJfnO3+F8T/A+4RfLXSEQMA3jhERSTAlgkQoLIy4ax4wDOgc6xjORT2OiEi8KBEkQrdu1H3rW9SH2TUHf40gKjMYMkQtJEUkKZQIEuDNN99k1JYt1LZvf3QHCAR8AToRkSRQIoizp556igEDBvDNO++kwy9/CTk5LTtATg7MnOmbzouIJIFqDcXJZ599xm233cbq1at5+eWX6RN6oXfiRH9fQJQ7jTHzZwIzZ0JRUeIDFhEJ0hlBHGzZsoX+/ftTX19PWVnZkUmgqAhWroSCAr+SKBA48s2BgN9eUODHKQmISJLpjKAVnHM8+eST3HnnnTz00EMURlrlk58PCxf62kElJf6O4aoqf59Anz5+dZAuDItIiigRHKX9+/fzox/9iE2bNrFy5Up6N6dsdNeuMGlS4oMTEWkBJQJocS/hN954g+HDhzNgwADWrl1LTksvCIuIpJHsTgQt7CXsnGPu3LlMmTKFhx9+mJEjR6YmbhGROMreRNDQRjLSap6GpjKlpfDCC9RMm8aYNWvYtm0bf/rTnzjnnHOSG6+ISIJk56qh0F7C0ZZ0wqFewu6OO7j6b39j9erVSgIi0qZkXyII00sY4COgADgO+DLw20Zvy3GO769fT2DLluTEKSKSJK1KBGb2XTPbYmb1ZhbxVlgzG2Rmb5nZDjO7qzWf2WphegkD3Ap0AD4EngaKgCY/8mtq1EtYRNqc1p4R/BlfTPO1SAPMrD3wGDAY6A18z8yasdYyASL0Ev4M30P4X4Dj8U1jriZMcTj1EhaRNqhVicA5t80591aMYf2BHc65t51zXwDzgaGt+dyjFqEH8F/wV817hWw7jzBnBKBewiLS5iTjGsFpwHshr3cFtyVfhF7C+4ETGm3LBT4Ndwz1EhaRNibm8lEzWwGcGmbXPc655+MZjJndDNwMcOaZZ8bz0F6EXsLHA5802vYJUZrHqJewiLQhMROBc+6KVn7G+8AZIa9PD24L91lzgbkA+fn5MdZ1HoUIvYR7AQeB7UDP4LY3gK9GOo56CYtIG5KMqaEyoKeZnWVmHYARwOIkfG5TEXoJH4e/4n0v/sLxKuB54AfhjqFewiLSxrR2+WiBme0CLgb+y8xeCG7/OzNbBuCcOwjcBrwAbAN+75xLzWL8KD2AHwdqgG7A94BiIpwRqJewiLQxrSox4Zx7DnguzPa/AUNCXi8DlrXms+KiWzdfO6i0tMkS0pOA0ljvVy9hEWmDsu/O4smTmzaHaS71EhaRNij7EkG/fr4dpHoJi4gA2Vp9tKEdpHoJi4hk4RlBA/USFhEBsvWMoIF6CYuIZHkiaKBewiKSxbJ3akhERAAlAhGRrKdEICKS5ZQIRESynBKBiEiWUyIQEclySgQiIllOiUBEJMuZi1ZnJ4XMrBLYmaKPPwXYk6LPbinFmhiZFCtkVryKNTEaYv2yc65FJRHSNhGumBcvAAAFAklEQVSkkpmtc85lRJlRxZoYmRQrZFa8ijUxWhOrpoZERLKcEoGISJZTIghvbqoDaAHFmhiZFCtkVryKNTGOOlZdIxARyXI6IxARyXJKBICZnWRmL5rZ9uCfXSKMO9PM/mhm28xsq5n1SG6kzY81OPYEM9tlZrOTGWPI58eM1czON7PXzWyLmZWb2fVJjnGQmb1lZjvM7K4w+zua2TPB/WtS8W8eEkusWG8Pfl+Wm9lLZvblVMQZEk/UeEPGXWtmzsxStjqnObGa2fDg13eLmf022TGGxBHr++BMM3vFzDYGvxeGxDyocy7rH8AvgLuCz+8CZkQY9ypwZfD58UBOusYa3P8I8Ftgdrp+XYFeQM/g878DPgBOTFJ87YG/AmcDHYA3gN6NxowDfhV8PgJ4JkVfy+bEelnD9yRQlKpYmxtvcFxn4DVgNZCfrrECPYGNQJfg625pHOtcoCj4vDfwTqzj6ozAGwrMCz6fB1zTeICZ9QaOcc69COCc2++cq05eiIfEjBXAzPoCXwL+mKS4wokZq3PuL8657cHnfwMqgGT1B+0P7HDOve2c+wKYj485VOjf4VngcjOzJMUXKmaszrlXQr4nVwOnJznGUM352gL8CzADOJDM4BppTqw3AY8556oAnHMVSY6xQXNidcAJwee5wN9iHVSJwPuSc+6D4PPd+B+gjfUCPjazRcFTrofMrH3yQjwkZqxm1g74V2BiMgMLozlf10PMrD/+t5y/JjqwoNOA90Je7wpuCzvGOXcQ2AecnJToIsQRFC7WUGOB5QmNKLqY8ZrZBcAZzrn/SmZgYTTna9sL6GVmq8xstZkNSlp0R2pOrD8DRpnZLmAZ8ONYB82ansVmtgI4Ncyue0JfOOecmYVbSnUMMAD4GvAu8AxQCPx7fCONS6zjgGXOuV2J/uU1DrE2HKc78B/AaOdcfXyjzC5mNgrIB76R6lgiCf6y8m/4/0OZ4Bj89NBA/JnWa2bWxzn3cUqjCu97QIlz7l/N7GLgP8zsH6P9v8qaROCcuyLSPjP70My6O+c+CP5ACnfatwvY5Jx7O/ieUuAiEpAI4hDrxcAAMxuHv5bRwcz2O+ciXrBLYayY2QnAfwH3OOdWxzvGKN4Hzgh5fXpwW7gxu8zsGPyp9t7khBc2jgbhYsXMrsAn4W845z5PUmzhxIq3M/CPwKvBX1ZOBRab2dXOuXVJi9Jrztd2F7DGOVcL/K+Z/QWfGMqSE+IhzYl1LDAIwDn3upl1wtchijidpakhbzEwOvh8NPB8mDFlwIlm1jB//U1gaxJiayxmrM65kc65M51zPfDTQ08lIgk0Q8xYzawD8Bw+xmeTGBv4f9OeZnZWMI4R+JhDhf4drgNedsGrcEkWM1Yz+xowB7g6hXPYDaLG65zb55w7xTnXI/h9uhofd7KTQMxYg0rxZwOY2Sn4qaK3kxlkUHNifRe4HMDMvgJ0AiqjHjUVV77T7YGf830J2A6sAE4Kbs8HnggZdyVQDmwGSoAO6RpryPhCUrdqKGaswCigFtgU8jg/iTEOAf6Cvy5xT3Db/fgfSgT/Ey0AdgBrgbNT+H0aK9YVwIchX8fFqYq1OfE2GvsqKVo11MyvreGnsrYG//+PSONYewOr8CuKNgHfinVM3VksIpLlNDUkIpLllAhERLKcEoGISJZTIhARyXJKBCIiWU6JQEQkyykRiIhkOSUCEZEs938Nhdclyq1QiwAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e5cb70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "101\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80dcceb8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "102\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80ea3cc0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "103\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c88160>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "104\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c8f550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "105\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80ced400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "106\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80cced30>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "107\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d3a9b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "108\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d82fca358>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "109\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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oXhGKNClKDJJ81cwA1x84BGgFjCJoNSyvqrLmghCJCSUGSb62bWtd1YAq70S001QeIrGgxCDJl5kJrVtXKv6CYJyV3cA+YAHwd6qYsCMtDTIy4hikSNOhxCDJN3p01OK9wESgI8HN5z8AecAJ0Sq7V3kcEakbJQZJvk6dgrGPKjzH0JFgZMWvCFoP64Dzouz+LbDz9NNB83SIxIQSgzQMEyYEl4MOwP6WLblk/XqmTJnCnj17YhyYSNOjxCANQ3Z2MOZRenrd9ktPp8X99zPv9ddZv349WVlZrF+/Pj4xijQRSgzScIwd+31yqGJ4jO+YlRtAr2vXrixbtoxbb72VCy+8kAkTJrC7imcjRKR6SgzSsIwdC2vXwrBhQU+lipeX0tKC8mHDgnoRo6qaGVdeeSWFhYVs3ryZ3r178/LLLyf4HyCS+mIy7LaZXQA8ADQDHnH3aRW2/xq4mqDXYQkwxt3fD7d9C5Q9svqBu19EDTTsdhNRUhIMc1FUFDy81q5d0CV19Oha3WheunQpv/rVrxgxYgR33XUX6XW9TCXSyNR22O16JwYzawa8Q9BhZCtBR5IR7v7PiDo/AV5x911mNhYY4O6Xhdu+dvc2dfmZSgxSW59++ik33XQT69at45FHHmHAgAHJDkkkaRI5H0M/YIu7v+vue4BFwJDICu7+gruXDbS/DjgyBj9XpEaHH344jz/+ODNmzGDkyJGMGzeOr776KtlhiTRosUgMXYEPI9a3hmVVuQpYEbHe2swKzGydmQ2NQTwilQwePJjXX3+dPXv2kJGRwd/+9rdkhyTSYCX05rOZjQSygHsiio8OmzZXAPeb2XFV7HttmEAKSjTuvhyAww47jEceeYTZs2dz7bXXctVVV/HFF18kOyyRBicWiWEb0C1i/ciwrBwzOxe4HbjI3b8pK3f3beHruwTD7feO9kPcfba7Z7l7Vkc94Sr1cP7551NUVETr1q059dRTeeaZZ5IdkkiDEovEkA90N7NjzawlcDmwLLKCmfUGZhEkheKI8nZm1ip8XzYXyz8RibNDDjmEhx56iAULFnDzzTdz5ZVXsmPHjmSHJdIg1DsxuPs+4AaCgTDfBBa7+xtmdoeZlXU9vYdgLvclZrbRzMoSx0lAgZltAl4ApkX2ZhKJt7POOovCwkI6d+7MqaeeytKlS5MdkkjSxeQ5hkRTd1WJh5dffpkxY8Zwyimn8NBDD9G5c+dkhyQSU4nsrirSKPzHf/wHGzZs4IQTTiAzM5MFCxaQin84idSXEoNIhNatW/Pb3/6W5cuX87vf/Y6LLrqIbdsq9aUQadSUGESi6Nu3LwUFBWRlZdGrVy/mzJmj1oM0GUoMIlVo2bIlkydP5vnnnyc3N5eBAwfy/vvvJzsskbhTYhCpQWZmJuvWrePss88mKyuLmTNnsn///mSHJRI3SgwitdC8eXPGjx/P3//+dx5//HHOPvtstmzZkuywROJCiUGkDk466SRefPFFhg4dymmnncaMGTP49ttvkx2WSEwpMYjUUbNmzb4byvvpp5/mjDPO4M0330x2WCIxo8QgcoCOP/54Vq9ezS9+8QvOPPNMpk6dyr59+5Idlki9KTGI1MNBBx3E2LFjKSgoYM2aNfTv35/CwsJkhyVSL0oMIjFw9NFH8+yzz3LDDTdw7rnnMmXKFPbs2ZPssEQOiBKDSIyYGTk5OWzYsIH169eTlZVFrcb0Ki6G6dNh5EgYPDh4nT49mPNaJAk0iJ5IHLg7Cxcu5OabbyYnJ4cpU6bQunXr8pXy82HqVFgRTmi4e/f329LSwB0GDYIJEyA7O3HBS6OlQfREksjMuOKKKygsLOTdd9+lV69evPTSS99XyM2FAQMgLy9ICJFJAaC0NCjLywvq5eYmMnxp4ponOwCRxqxz584sXryYJ598kksuuYTLLruMacccQ6vbboNdu2o+gHtQ75ZbgvWxY+MbsAhqMYgkxMUXX0xRURGHvPUW+2++uVxSaFNhaQb8quIBypKDLqFKAigxiCRIhw4duCMtjVYVyr+OWD4G0oBLox2gtDS4JyESZzFJDGZ2gZm9bWZbzGx8lO2tzOyJcPsrZnZMxLYJYfnbZjYwFvGINEjFxbBiBQdV0+HjSaAT8ONoG91h+XL1VpK4q3diMLNmwEPAIOBkYISZnVyh2lXA5+5+PDAD+F2478nA5cApwAXAzPB4Io3PvHk1VpkP/AKwqiqY1eo4IvURixZDP2CLu7/r7nuARcCQCnWGEHzmAZYC55iZheWL3P0bd38P2BIeT6TxKSys3PsowvvAWmBUdccoLYWiohgHJlJeLBJDV+DDiPWtYVnUOu6+D9gJdKjlvgCY2bVmVmBmBSVqSksq2rmz2s2PAWcAx9Z0nM8/j1FAItGlzM1nd5/t7lnuntWxY8dkhyNSd23bVrv5T9TQWijTrl0sohGpUiwSwzagW8T6kWFZ1Dpm1hxoC+yo5b4ijUNmJlR8+jn0EsEHP2pvpEhpaZCREePARMqLRWLIB7qb2bFm1pLgZvKyCnWW8f0fQ5cAqz0Yi2MZcHnYa+lYoDvwagxiEml4Ro+uctN8YDhwSE3HcK/2OCKxUO8nn919n5ndAKwkeDbnUXd/w8zuAArcfRkwB3jMzLYAnxEkD8J6i4F/AvuA691d02FJ49SpUzD2UV5e8AUfYVYtdt8P7D3nHFrpUqrEmQbRE0mk/Pxg7KPaDIdRwZ7mzbmobVuumTWLiy++OPaxSaOnQfREGqLsbLj3XkhPr9t+6em0/P3vmbRsGbfffjuXXXYZ6p0n8aLEIJJoY8d+nxysykfZAmZBvXvvhbFj+dGPfsSGDRs46qijyMjIYMmSJYmJWZoUJQaRZBg7FtauhWHDgp5KaWnlt6elBeXDhgX1IkZVTUtL45577iEvL49JkyZx6aWXUlxcnOB/gDRmGnZbJFmysuDJJ4Oxj+bNC55o/vzz4DmFjIyg91E1N5pPO+00NmzYwOTJk8nMzOSBBx7gZz/7GVZTK0SkBrr5LNIIvPLKK+Tk5HDSSScxc+ZMOnfunOyQpAHSzWeRJqR///689tprnHDCCWRmZrJw4UJS8Y8+aRiUGEQaidatWzN16lT++te/cvfddzN8+HA+/vjjZIclKUiJQaSRyc7OZv369Zxyyin07NmTBQsWqPUgdaLEINIItWrVirvuuovly5czbdo0hg4dyvbt25MdlqQIJQaRRqxv374UFBTQs2dPevbsyWOPPabWg9RIvZJEmojXXnuNnJwcjjrqKGbNmsUPfvCDZIfU9BQXB12TCwuD+Tnatg1G3c3JqbZrcqyoV5KIlNOnTx/y8/Pp27cvvXr1Yv78+Wo9JEp+PgwfDkcfDZMnw4IF8Ne/Bq9TpsBRRwXb8/OTHSmgFoNIk7Rx40ZGjx5N165dmT17Nl27Rp04UWIhNxduuSWYlrW671uz4In3cPiTeFCLQUSq1KtXL1599VX69+9P7969mTt3rloP8VCWFHbtAnceBLKAVsDoinXdg3q33BLsl0RqMYg0cZs2bSInJ4fOnTsze/ZsunXrVvNOUrMoQ6z/heCv8ZVAKTCvqn3T04MxsrJq/OO+TtRiEJFa6dmzJ6+88gqnn346ffr0Yc6cOWo9xMLUqcHlowjDgaFAh5r2LS0N9k+SeiUGM2tvZqvMbHP4WmmWcjPrZWYvm9kbZlZoZpdFbJtnZu+Z2cZw6VWfeETkwLRo0YKJEyeyevVqZs6cyQUXXMAHH3yQ7LBSV3ExrFhR/T2F6rjD8uXBAItJUN8Ww3jgeXfvDjwfrle0C/iFu58CXADcb2aHRWz/jbv3CpeN9YxHROohIyODdevWcdZZZ9G3b1/++Mc/qvVwIObNq/8xzGJznANQ38QwhGAec8LXoRUruPs77r45fP8RUAxo0lqRBqpFixbcdtttvPDCC8yePZvzzz+f999/P9lhpZbCQti9u37HKC0NhmJPgvomhs7uXvac/cdAtWP9mlk/oCXwr4jiu8NLTDPMrFU94xGRGDn11FN5+eWXOeecc8jKymLWrFlqPdTWzp2xOc7nn8fmOHVUY2Iws+fM7PUoy5DIeh58Yqr81JhZF+AxIMfd94fFE4AeQDbQHri1mv2vNbMCMyvQXLciidG8eXPGjx/P2rVrmTNnDueeey7//ve/kx1Wg7R9+3YWLVrEddddx7K1a6PW2QfsBr4Nl91hWZXaVbptmxA1JgZ3P9fdT42yPA18En7hl33xR51f0MwOBf4buN3d10Uce7sHvgHmAv2qiWO2u2e5e1bHBDw6LiLfO/nkk3nppZcYOHAg2dnZ5Obmsn///pp3bMQ++ugjFi5cyC9/+UtOPPFETjnlFBYtWkSPHj3oO2YM3rp1pX3uAtKAacDj4fu7qvoBaWnBTH5JUK/nGMzsHmCHu08zs/FAe3f/rwp1WgIrgGfc/f4K27q4+3YL5iKcAex292g3sMvRcwwiyfPmm2+Sk5NDWloac+bM4Yc//GGyQ0qIjz76iLVr17JmzRrWrFlDSUkJZ555JgMGDGDAgAFkZGTQrFmzoHJxcTD8RX3uM7RuDR98ENMxlGr7HEN953yeBiw2s6uA94GfhT88C7jO3a8Oy84EOpjZ6HC/0WEPpAVm1hEwYCNwXT3jEZE4O+mkk/jHP/7BjBkz6NevH1OmTGHcuHEcdFDjeiwqWiI466yzGDBgAOPGjSMjI6Pqf3OnTjBoEOTlHViXVTO48MKEDKwX9cen4s0ktRhEGoa33nqLMWPG0LJlS+bMmcNxxx2X7JAOWHWJoKxFUKfkF+XJ51pL8pPP9W0xiEgT1qNHD1588UUeeOAB+vfvz6RJk7jhhhtq/gJN8vDTUDkRfPrpp99dGqqxRVAb2dnBgHhlYyXVVnp6sF+Mk0JdqMUgIjHxzjvvkJOTQ7NmzXj00Uc5/vjjK1fKzw+GelixIliPvAaflhZcdhk0CCZMCL5YY+ijjz76LgmsWbOGHTt2VLpHEJfLYSk4uirunnJL3759XUQann379vmMGTO8Q4cOPmPGDP/222+/3zhzpnt6uruZe/AVGX0xC+rNnFmvWLZu3eoLFizwa665xrt37+7t27f3YcOG+QMPPOCbNm0qH1u85ee7Dx/u3rq1e1pa+X9vWlpQPnx4UC+OgAKvxXesWgwiEnObN29mzJgxuDuPPvooJzz//IFfUqnlX8/btm0rd2lox44d5e4RnHrqqcm/QV5SElxCKyoKHl5r1y7okjp6dIOawU2JQUTiYv/+/Tz44IM8M2kSy3ftosXevZXqLAL+H/ABcATBMNQ/jqxQzU3YlEgEDYwSg4g0CF+ffz5pq1bRrEL5KuBq4AmCJ1vLxtYpN5ecGQwbBk8+WSkRfPbZZ5x11lnfJQMlgpopMYhI8lXzoNePgKvCpTp7mjXjx0cdxb++/LJci+CUU05RIqgjdVcVkeSrYtjob4EC4CLgeIIxg4YC9xAMExHJDjqIvKFD6XzvvUoECaKzLCLxU8Xw058Ae4GlwIsEwx5sIPq4QS327qXLp58qKSSQzrSIxE8Vw0+XtQp+BXQBDgd+DSyv6jhJGn66qVJiEJH4ads2anE74EiCQdLKWNSaZTskZ/jppkqJQUTiJzMzGCU0ihzgDwRj9X9OMLzyT6NVTOLw002VEoOIxM/o0VVu+r8EM3SdAJwE9AZuj1bRvdrjSOwpMYhI/JQNP22VLxS1AGYCXxDMC/x7oGLbwpM8/HRTpcQgIvE1YUJwOegAlLrzVI8emms6wZQYRCS+srPZdeed7IrSaqhWejpfTJzI3StXMmjQILZu3Rqf+KQSJQYRiSt358oXX+SZs84Kxj6qKUGYfTeA3g/uvJOXX36ZM844gz59+jB//ny1HhKgXonBzNqb2Soz2xy+Ru1TZmbfmtnGcFkWUX6smb1iZlvM7IlwfmgRaURmzJjBtm3bGPrss8GAeMOGBT2VKl5eSksLyocNC+qFo6q2aNGCiRMnsmrVKu677z6GDBnC9u3bo/wkiZV6jZVkZtOBz9x9mpmNB9q5+61R6n3t7m2ilC8G/uLui8zsYWCTu+fW9HM1VpJIanjppZcYNmwYr7zyCsccc8z3Gw5w+Ok9e/Zw1113MWvWLGbYvVUhAAAO7klEQVTMmMGIESOwul6iasISMoiemb0NDHD37WbWBVjj7idGqVcpMVjw2ywBjnD3fWb2H8AUdx9Y089VYhBp+D799FP69OnDQw89xODBg2N67IKCAkaNGkWPHj3Izc2lU6dOMT1+Y1XbxFDfewyd3b2sTfcx0LmKeq3NrMDM1pnZ0LCsA/CFu+8L17dSYcTdSGZ2bXiMgpKSknqGLSLxtH//fkaOHMmIESNinhQAsrKyWL9+Pd27dyczM5OlS5fG/Gc0ZTW2GMzsOYI5NCq6HZjv7odF1P3c3SvdZzCzru6+zcx+CKwGzgF2Auvc/fiwTjdghbufWlPQajGINGx33303zz77LKtXr6ZFixZx/Vnr1q1j1KhR9OnThwcffJAOHTrE9eelspi1GNz9XHc/NcryNPBJeAmJ8LW4imNsC1/fBdYQPOS4AzjMzMqG/j4S2FaLf5uINGAvvPACDz74IIsWLYp7UgA47bTT2LhxI126dCEjI4Nly5bVvJNUq76XkpYBo8L3o4CnK1Yws3Zm1ip8fzhwOvDPcGLqF4BLqttfRFLHxx9/zMiRI/nTn/5E165VXhmOubS0NO677z6eeOIJfv3rXzNq1Cg+14isB6y+iWEacJ6ZbQbODdcxsywzeySscxJQYGabCBLBNHf/Z7jtVuDXZraF4J7DnHrGIyJJsm/fPkaMGME111zDeeedl5QYfvzjH7Np0yYOOeQQMjMzWbFiRVLiSHWa2lNEYmLixImsW7eOlStX0qxZxRmeE2/16tWMGTOGc889l/vuu49DDz002SElXaJ6JYmIsGLFCubNm8eCBQsaRFIAOPvssyksLKRZs2ZkZmby/PPPJzuklKHEICL18uGHH5KTk8Of//xnOneuqsd6chx66KHMmjWLWbNmkZOTw7hx4/j666+THVaDp8QgIgds7969XHbZZdx8882ceeaZyQ6nSgMHDqSwsJDS0lJ69uzJ2rVrkx1Sg6bEICIHbPz48bRv357f/OY3yQ6lRocddhhz587l/vvv54orruCmm25i165dyQ6rQVJiEJED8tRTT/Hkk08yf/58Djoodb5KBg8eTFFRESUlJfTq1YuXXnop2SE1OKnz2xSRBuPdd9/ll7/8JU888URKPmncvn17FixYwLRp07j44ov5r//6L3bv3p3ssBoMJQYRqZPdu3dz6aWXMnHiRPr375/scOpl+PDhFBYW8t5779GnTx/y8/Nr3qm4GKZPh5EjYfDg4HX69GDE2EZCzzGISJ2MGzeO4uJilixZ0miGvHZ3Fi9ezI033sjVV1/NpEmTaNWqVflK+fkwdSqUPTQX2cJISwP3YH7rCRMgOztxwdeBnmMQkZhbuHAhq1atYs6cOY0mKQCYGZdddhmbNm3i9ddfJzs7mw0bNnxfITcXBgyAvLwgIVS87FRaGpTl5QX1cmucVqZBa15zFREReOutt7jxxhtZtWoVbdu2TXY4cXHEEUeQl5fH448/zsCBA7n++uu5vUMHmt96K9SmB5N7UO+WW4L1cBa6VKMWg4jUaNeuXVxyySX89re/pVevXskOJ67MjJ///Ods2LCBz1auZO+NN5ZLCt8AVwFHA4cAvYBKIzKVJYcUveStxCAiNbr++uvp3bs3V199dbJDSZiuXbtyf+fOVLjTwD6gG7CWYFKZu4CfAf+ueIDS0uCeRArSpSSRpq64OJh/ubAQdu6Etm0hMxNycqBjR+bOncurr77Kq6++2qjuK9SouBh79lmsQgedg4EpEes/BY4F1gPHRFZ0h+XLg95K1cxj3RApMYg0VdX1svnLX2DyZHb+6Ef8ef16lrz0EgcffHBy4kyWefNqVe0T4B3glGgbzYLjpMCT4ZGUGESaotzc4Bp4aWnwl21FpaUAtFm9mhUtW9J87Vo4+eQEB5lkhYWVex9VsBe4kmCWsR7RKpSWQlFR7GOLMyUGkaamLCnUopdNM4A9e1K+l80B2bmz2s37gZ8DLYEHq6uYgjPJ1evms5m1N7NVZrY5fG0Xpc5PzGxjxLLbzIaG2+aZ2XsR2xp3dweRZMvPj5oURgJdgEOBE4BHKu6X4r1sDkg1XXKdoGfSJ8CTQLUzW7er9LXY4NW3V9J44Hl37w48H66X4+4vuHsvd+8FnA3sAv4WUeU3ZdvdfWM94xGR6kyd+t1lokgTCHrVfEkwkftEgpup5aRwL5sDkpkJrVtH3TQWeBN4Bkir7hhpaZCREfvY4qy+iWEIMD98Px8YWkP9S4AV7q6xbkUSrbg4uNEc5Z7CKfBdt0wLl39VrBTZy6YpGD06avH7wCxgI3AE0CZcFkSr7F7lcRqy+iaGzu6+PXz/MVDT9E2XAwsrlN1tZoVmNsPMKnYZFpFYqaGXzTggneAmahfgwmiVynrZNAWdOgVjH1Xoons0waWk3cDXEcuVFfc3gwsvTLmuqlCLxGBmz5nZ61GWIZH1PBiNr8oR+cysC5ABrIwonkDwOcwG2gO3VrP/tWZWYGYFJU3lLxaRWKqhl81M4CvgRWA4VHqwC0jZXjYHbMKE4HLQgUhLC/ZPQTUmBnc/191PjbI8DXwSfuGXffEXV3OonwFPufveiGNv98A3wFygXzVxzHb3LHfP6piCGVgk6WroZQNBL6QzgK1AlcPApWAvmwOWnQ333gvp6XXbLz092C+rxoFMG6T6XkpaRtCFl/D16WrqjqDCZaSIpGIE9yder2c8IlKVOgx8t48o9xjKpGAvm3oZO/b75FDTk99m3yeFFO7aW9/EMA04z8w2A+eG65hZlpl91+PNzI7h++FFIi0wsyKgCDicYNgREYmHKnrZFAOLCK6Tf0twrXchcE60Y6RoL5t6GzsW1q6FYcOCc1jx8lJaWlA+bFhQL4WTAmiiHpGmo7gYjj660n2GEoLugpsIHto6GrgRuCbaMVq3hg8+SMkbqjFTUhLcgC8qCi6rtWsXJMvRoxv8eantRD168lmkqSjrZZOXV67LakcqN+WjSuFeNjHVsWPKjX1UVxp2W6QpaaK9bKRulBhEmpIm2stG6kaXkkSamrIbo9WNrlrGLGgppHgvG6kbtRhEmqIm1stG6kYtBpGmKisLnnwypXvZSHwoMYg0dU2gl43UjS4liYhIOUoMIiJSjhKDiIiUo8QgIiLlKDGIiEg5SgwiIlKOEoOIiJSjxCAiIuWk5HwMZlYCvB/jwx4OfBrjY8ZaQ4+xoccHDT9GxVd/DT3GZMZ3tLvX+Dh7SiaGeDCzgtpMYJFMDT3Ghh4fNPwYFV/9NfQYG3p8oEtJIiJSgRKDiIiUo8TwvdnJDqAWGnqMDT0+aPgxKr76a+gxNvT4dI9BRETKU4tBRETKaVKJwcwuNbM3zGy/mVXZK8DMLjCzt81si5mNjyg/1sxeCcufMLOWMY6vvZmtMrPN4Wu7KHV+YmYbI5bdZjY03DbPzN6L2NYrlvHVNsaw3rcRcSyLKG8I57CXmb0cfhYKzeyyiG1xO4dVfa4itrcKz8mW8BwdE7FtQlj+tpkNjFVMdYzv12b2z/CcPW9mR0dsi/r7TnB8o82sJCKOqyO2jQo/E5vNbFQ84qtljDMi4nvHzL6I2Bb3c1hr7t5kFuAk4ERgDZBVRZ1mwL+AHwItgU3AyeG2xcDl4fuHgbExjm86MD58Px74XQ312wOfAenh+jzgkjifw1rFCHxdRXnSzyFwAtA9fP8DYDtwWDzPYXWfq4g644CHw/eXA0+E708O67cCjg2P0ywJ8f0k4rM2tiy+6n7fCY5vNPBglH3bA++Gr+3C9+2SEWOF+r8CHk3UOazL0qRaDO7+pru/XUO1fsAWd3/X3fcAi4AhZmbA2cDSsN58YGiMQxwSHre2x78EWOHuu2IcR3XqGuN3Gso5dPd33H1z+P4joBiI9xyWUT9XFepExr4UOCc8Z0OARe7+jbu/B2wJj5fQ+Nz9hYjP2jrgyBjHUK/4qjEQWOXun7n758Aq4IIGEOMIYGEc4qi3JpUYaqkr8GHE+tawrAPwhbvvq1AeS53dfXv4/mOgcw31L6fyB+vusKk/w8xaxTg+qH2Mrc2swMzWlV3qogGeQzPrR/DX3b8iiuNxDqv6XEWtE56jnQTnrDb7JiK+SFcBKyLWo/2+kxHfxeHvbqmZdavjvomKkfAy3LHA6ojieJ/DWmt0cz6b2XPAEVE23e7uTyc6noqqiy9yxd3dzKrsMmZmXYAMYGVE8QSCL8OWBF3ibgXuSFKMR7v7NjP7IbDazIoIvujqLcbn8DFglLvvD4tjcg4bMzMbCWQBZ0UUV/p9u/u/oh8hbp4BFrr7N2b2S4LW19kJjqG2LgeWuvu3EWUN4RwCjTAxuPu59TzENqBbxPqRYdkO4DAzax7+NVdWHrP4zOwTM+vi7tvDL63iag71M+Apd98bceyyv5S/MbO5wC11jS9WMbr7tvD1XTNbA/QGnqSBnEMzOxT4b4I/GNZFHDsm5zCKqj5X0epsNbPmQFuCz11t9k1EfJjZuQQJ+Cx3/6asvIrfdyy/1GqMz913RKw+QnC/qWzfARX2XRPD2MrU5fd0OXB9ZEECzmGt6VJSZflAdwt6z7Qk+AUu8+Du0AsE1/UBRgGxboEsC49bm+NXuj4ZfhGWXcsfCrwe4/hqFaOZtSu7BGNmhwOnA/9sKOcw/L0+BfzJ3ZdW2Bavcxj1c1VN7JcAq8Nztgy4POy1dCzQHXg1RnHVOj4z6w3MAi5y9+KI8qi/7yTE1yVi9SLgzfD9SuD8MM52wPmUb2knLMYwzh4EN8FfjihLxDmsvWTf/U7kAgwjuO73DfAJsDIs/wGwPKLehcA7BNn69ojyHxL8h9wCLAFaxTi+DsDzwGbgOaB9WJ4FPBJR7xiCv0QOqrD/aqCI4MvscaBNHM5hjTECPwrj2BS+XtWQziEwEtgLbIxYesX7HEb7XBFcproofN86PCdbwnP0w4h9bw/3exsYFKf/HzXF91z4/6bsnC2r6fed4PimAm+EcbwA9IjYd0x4XrcAOfGIrzYxhutTgGkV9kvIOaztoiefRUSkHF1KEhGRcpQYRESkHCUGEREpR4lBRETKUWIQEZFylBhERKQcJQYRESlHiUFERMr5/y47MZOTH7cXAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f7cac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "110\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d29d30>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "111\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80cc3f60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "112\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c8bd30>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "113\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'S', 8: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e10b38>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "114\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80dd75c0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "115\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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FOM9Z1Koez1lIZli/fv3+EVX79u1j9OjR3Pzaaxy9ZMkBPwv/JJh+eyxBt2QRMApYC3SKPGGKfhZ0g1skBT7++GOKi4spLi5m6dKlnHHGGQwcOJD8/Hx69uzJYYdFaZgneeoKaVzcnTfeeIP5Dz/M5OnTqcujj90Ipt6+pPqOKM/cJCrdEwmKNAl79+7llVdeobi4mKKiIrZt28aAAQP46U9/ysMPP0yrVq3in6RXr+DJ4vpOXaFE0aiZGT179qTn4sV4VlatqwACfEYw/cVZ0U8WDLO9+ebkB1oPShZySNuyZcv+5LBkyRK6dOlCfn4+M2fOJC8vr37zJFVNQZHCqSskw5WWYnESxTcEQ6rHAFEf/8uw5WKVLOSQ8s033/Daa6/tv/ewefNmLrroIoYNG8b06dM5/vjjk/NBEyYErYwGmLpCMtDOnbXurgT+jeC5mwdqq5hBy8UqWUiT9+mnn7JgwQKKiopYvHgxp556Kvn5+UyfPp3evXunbpbVvLzgBmUDTl0hGSLGMzcQLAn6M4IuqCKg5vi5CBn0zI2ShTQ5+/btY8WKFftbD5s2beLCCy9k0KBBPPDAA5x44okNG1Dr1hnT7ywNpFu34A+FKF1RE4B3gReBWidJz7BnbjQaSpqEbdu2sWDBAoqLi1m0aBEdO3bcP3KpT58+mltJGlaMGYg3EQyRbcGBf6k/RHD/4gAaDSVNUgNPkFZRUcHrr7++/+b0hx9+SP/+/cnPz+f+++/XUpqSXjGWi+1I0A0Vl1lwPyuDuinVspDENOAEaWVlZSxcuJCioiJeeOEF2rdvT35+PgMHDuTcc8/liChPT4ukTQY+c6OH8iQ9UryyWUVFBSUlJftbD+vXr6dfv37k5+czYMAA2rdvn4RvQiSFMmw99rR3Q5nZAOD/EayU97C7T622/0bg3wlWytsOXOXum8J9FQRPuwN87O6DkxGTpNjB/CeInCANav1P8Pnnnx/QejjxxBPJz8/nnnvu4V/+5V9o3rx5kr4BkQbQlJ65cfeEXgQJ4gPgFIJhw28CZ1arcz6QE76fADwVse/rg/3Mnj17uqTRypXuOTnuwY9+jdcT4KeD54CfAv63yP05Oe4lJftPVVFR4StXrvQ77rjDzznnHD/66KN9yJAh/tBDD/mmTZvS+E2KJFFJifvw4e5ZWe7Z2Qf+n8nODsqHDz/g/0YqECx1Xa/f9cloWfQGNrj7hwBm9iQwBHgnIiEtjai/ArgiCZ8r6VJQcOADZhEWEawG9xTBD8bW6hXKy9nzf/8vc0ePpri4mAULFtCqVSsGDhzIXXfdxQ9+8ANatGiR0vBFGlwTeOYmGcmiHfBJxPZm4Jxa6v+MA2flzTKzVQRdVFPdfV60g8xsPMHSAHTo0CGhgCUBZWXBzewYzekpwK+BPuF2jcUo3fG//pXn9+7lvKFDufPOO+nUqVPKwhXJKI34mZsGHTprZlcQrFv/44jiju6+xcxOAZaY2Vp3/6D6se4+A5gBwQ3uBglYapo1K+auCmAVMBj4LrAbGEowJXPkw0ctsrP5n/79M7NfVkSiSsbiR1uAkyK224dlBzCz/sCtwGB331NV7u5bwq8fEqxA2SMJMUmqlJbGnEnzM4LJ0QqBlwhWhfs78Jtq9SzDJkgTkfiSkSxKgM5mdrKZNQdGAvMjK5hZD4KHFAe7e1lEea6ZtQjftwLOI+Jeh2SgWiZIq2o9XAe0AVoBNxLMf1NDBk2QJiLxJdwN5e77zOxagiWFmwGPuPvbZnYnwZ33+QQ9Ed8BnrZgjeKqIbJnAA+ZWSVB4prq7koWmayWCdJyCZqVkatQ11yRuqpy5kyQJiLxJeWehbsXUe0PSHf/dcT7/jGOexXInJmyJL5aJkgDGAf8FzCAYDbN+4F/rV4pwyZIE5H4ktENJYcQHzOGioqKmPtvB3oBXQiajT0IblQdeBIPhgqKSKOhZCF1tmLFCs4bNozlOTlUWvQOpiOAB4EvgW3AH+HAdYgzcII0EYlPyULi2rhxI6NGjWLEiBGMHz+eHy9YwGHZtc7EH1t2djCpoIg0KkoWEtPOnTuZNGkSPXv25PTTT2fdunWMHTuWZn36BPPX5OQc3AmrJkjTEqIijY6ShdSwb98+pk2bxmmnncZnn31GaWkpU6ZM4cgjj/y20oQJ3yaMGF1S+5mldCZNEUk9LX4k+7k7xcXFTJw4kRNPPJHi4mJ69KjlGckJE4I1KgoKoKgoSAqRc0ZVrWcxcGDQ9aQWhUijpWQhAKxdu5abbrqJTZs2cc899zBo0CAsXosBmsQEaSISn5LFIW7btm38+te/Zt68edx+++1cc8019VtxrhFPkCYi8emexSGqvLycu+66i7POOoujjjqKdevWcd1112lpUhGJSi2LQ0xlZSVz5szhP//zP+nduzcrV67k1FNPTXdYIpLhlCwOIS+99BI33ngjALNnz+aHP/xhmiMSkcZCyeIQ8MEHH3DLLbewcuVKCgoKGDVqFIcdph5IEak7/cZownbs2MFNN91E79696dGjB++99x6XX365EoWIHDT91miCvvnmG/74xz9y2mmn8dVXX/H2229z6623knOwT1yLiITUDdWEuDt/+ctfuPnmm+nYsSOLFy+mq6YCF5EkSErLwswGmNk6M9tgZpOi7G9hZk+F+183s04R+yaH5evM7CfJiOdQ9Pe//51+/foxefJk/vCHP7Bw4UIlChFJmoSThZk1A/4E5ANnAqPM7Mxq1X4G7HD37xKsh3N3eOyZBMuwnkWwXs6D4fmkjrZs2cK4cePIz8/n0ksv5c033yQ/P79uT1+LiNRRMloWvYEN7v6hu+8FngSGVKszBHg0fF8I9LPgt9kQ4El33+PuHwEbwvNJHP/85z+544476NatGyeccALr1q3jmmuu4fDD1bMoIsmXjN8s7YBPIrY3A+fEqhOu2b0TOC4sX1Ht2HZJiCmzlZUF8yiVlsLOncG61t26wbhxcedRqqys5LHHHuO2227jhz/8IatXr6ZTp04NEraIHLoazZ+hZjYeGA/QoUOHNEdTTyUlwQytxcXBduQ61nPnwpQpkJ8fzNDaq1eNw5cuXcpNN91EVlYWhYWF9OnTp4ECF5FDXTK6obYAJ0Vstw/LotYxs8OBlsA/6ngsAO4+w93z3D2vdWOcxXTaNOjbF+bNC5JEZKKAYGrv3buD/X37BvVD69atY8iQIVx11VVMmjSJV155RYlCRBpUMloWJUBnMzuZ4Bf9SGB0tTrzgTHAa8AIYIm7u5nNB+aY2e+BtkBnYGUSYsos06bBxImwa1f8uu5BvYkT+fqf/+TWTz5h9uzZ/OpXv+Kpp54iKysr/jlERJIs4WQR3oO4FlgINAMecfe3zexOYJW7zwdmAo+b2QbgC4KEQljvz8A7wD7gl+5ekWhMGaWkJGqi2Aj8giB7tiDIoH8g4h9k1y4Ou/lm2o4YwbvvvkujbE2JSJORlHsW7l4EFFUr+3XE+93AT2McexdwVzLiyEgFBQeuHhf6BXA8sBX4ErgQeBD4j4g62WbcUlmpxYNEJO003UcqlZUFN7Pda+z6CLgUyAJOJHjI5O1qdcw9WK50+/aUhyoiUhsli1SaNSvmrusJHkjZRXCjp5ggYdRgVut5REQagpJFKpWW1hz1FPoRQUviaIIhYHnA0GgVy8uDda1FRNJIySKVdu6MWlxJ0IoYDvwT+BzYAdwS6zw7dqQgOBGRulOySKWWLaMWfwF8DFxLMBLqOGAc1UYIRMrNTUFwIiJ1p2SRSt26QZTnIloBJwPTCMYLf0kwcVa3aOfIzgbNHisiaaZkkUpjx8bcNRdYALQGvgscQTAdbw3utZ5HRKQhKFmk0vHHB3M9RZkuvDuwjOBexefAn4ETqlcyg4ED9ZyFiKSdkkWqTZ4cdCXVR3Z2cLyISJopWaRar15w771wsOtf5+QEx+XlpSYuEZGDoGTRECZM4L2f/5xdZni8FezMvk0UEyY0THwiInEoWTSAiooKLl2yhNcKCrBhw4IRUtW7prKzg/Jhw2D5ciUKEckojWbxo8Zs5syZ5ObmcsGvfhW0HLZvD6bwWLs2eOAuNzcYHjt2rG5mi0hGUrJIsZ07dzJlyhSef/55rKoLqnVruPnm9AYmInIQ1A2VYr/97W8ZOHAgZ599drpDERGpN7UsUuiDDz5g5syZrNVEgCLSyCXUsjCzY81skZmtD7/WmMTIzLqb2Wtm9raZlZrZZRH7ZpnZR2a2Jnx1TySeTPOrX/2Km266iTZt2qQ7FBGRhCTaDTUJWOzunYHF4XZ1u4Ar3f0sgslW/2Bmx0Tsv9ndu4evNQnGkzGWLVvG6tWrueGGG9IdiohIwhJNFkMI5sAj/FpjSQZ3f9/d14fvPwXKCKZEarIqKiq44YYb+N3vfkdWlIkERUQam0STxQnuvjV8v40o0xtFMrPeQHPgg4jiu8LuqfvNrEWC8WSEWbNmceSRR/LTn0ZddlxEpNGJe4PbzF4kWCa6ulsjN9zdzazmYtPfnqcN8Dgwxt0rw+LJBEmmOTCDYP2fO2McPx4YD9ChQ4d4YafNV199xe233878+fO/HSorItLIxU0W7t4/1j4z+8zM2rj71jAZlMWodzTwPHCru6+IOHdVq2SPmf03MLGWOGYQJBTy8vJiJqV0Kygo4KKLLiJPczqJSBOS6NDZ+cAYYGr49bnqFcysOfAs8Ji7F1bbV5VojOB+x1sJxpNWH330ETNmzKC0tDTdoYiIJFWi9yymAhea2Xqgf7iNmeWZ2cNhnUuBHwFjowyRnW1ma4G1BAvI/SbBeNLqlltu4frrr6dt27bpDkVEJKnMPWN7dGLKy8vzVatWpTuMA7z00ktcccUVvPfee2TXd/0KEZEUMrPV7l6vPnJN95EElZWVXH/99dx9991KFCLSJClZJMFjjz1GixYtuOyyy+JXFhFphDQ3VIK+/vprbr31Vp599lkNlRWRJkstiwRNnTqVCy64gN69e6c7FBGRlFHLIgGbNm1i+vTprFnTZKa0EhGJSi2LBEyaNInrrruO9u3bpzsUEZGUUsuinl599VVefvllZs6cme5QRERSTsmiNmVlwVrZpaWwcye0bAndulE5ZgzXX389U6dOJScnJ91RioiknJJFNCUlUFAAxcXB9u7d3+6bO5fK227j7u98hx9/97vpiU9EpIHpnkV106ZB374wb16QJCITBUB5OYd/8w19v/ySwy64IKgvItLEqWURado0mDgRdu2KW9Xcg3oTw4lyJ0xIcXAiIumjlkWVkpKoiaIvkAV8J3ydVv24qoSRYXNViYgkk5JFlYICKC+PuusB4OvwtS5ahfLy4HgRkSZKyQKCUU/FxVDfGXjdoagItm9PblwiIhlCyQKC4bG1mEyw2MZ5wLJYlczinkdEpLFSsoDgOYrqo55CdwMfAlsIFgAfBHwQrWJ5Oaxdm6oIRUTSKqFkYWbHmtkiM1sffs2NUa8iYpW8+RHlJ5vZ62a2wcyeCpdgbXg7d8bcdQ5wFNCCYN3Y84CiWJV37Eh2ZCIiGSHRlsUkYLG7dwYWh9vRlLt79/A1OKL8buB+d/8usAP4WYLx1E/LlnWuakDMOxu5UXOliEijl2iyGAI8Gr5/FBha1wMtWPzhAqCwPscnVbdukJVVo/hLYCGwG9gHzAb+BgyIdo7sbOjaNYVBioikT6LJ4gR33xq+3wacEKNelpmtMrMVZlaVEI4DvnT3feH2ZqBdrA8ys/HhOVZtT/aoo7FjoxZ/A9wGtCa4wf1fwDygS7TK7jHPIyLS2MV9gtvMXgROjLLr1sgNd3czi9VD09Hdt5jZKcASM1sLxL5REIW7zwBmAOTl5dVzjGsMxx8P+fnBFB8Rw2dbAyV1Od4MBg6E1q2TGpaISKaImyzcvX+sfWb2mZm1cfetZtYGKItxji3h1w/NbBnQA3gGOMbMDg9bF+0JBh2lx+TJsHBhnab6qCE7OzheRKSJSrQbaj7BICHCr89Vr2BmuWbWInxf9bjCO+7uwFJgRG3HN5heveDee+FgpxzPyQmOy8tLTVwiIhkg0WQxFbjQzNYD/cNtzCzPzB4O65wBrDKzNwmSw1R3fyfcdwtwo5ltILiHkd6VhCZpU8S4AAAPf0lEQVRM+DZhmNVe1+zbRKFJBEWkiTOv7xQXaZSXl+erUjlx36pVwVxPRUVBUoiYM8qzs9lTXs6efv1oOXWqWhQi0miY2Wp3r9cvLU1RHk1eHjzzTDDX06xZwZPZO3ZAbi7WtSsPfvEF72zfzsNKFCJyiFDLoh4+//xzOnfuzHvvvccJJ8QaLSwiklkSaVlobqh6aNWqFZdddhnTtEqeiBwilCzq6frrr2fatGmUx1gDQ0SkKVGyqKfTTz+dXr16MXv27HSHIiKSckoWCbjxxhv5/e9/T2O87yMicjCULBJw/vnn07x5cxYuXJjuUEREUkrJIgFmtr91ISLSlClZJGjkyJG89dZbrNUqeSLShClZJKh58+Zce+213H///ekORUQkZZQskuDqq6/m2WefZdu2bekORUQkJZQskuC4445j1KhRPPjgg+kORUQkJZQskuT6669n+vTpekhPRJokJYsk6dKlC3369OHxxx9PdygiIkmnZJFEN954I/fffz+VlZXpDkVEJKmULJLoxz/+MdnZ2SxYsCDdoYiIJFVCycLMjjWzRWa2PvyaG6XO+Wa2JuK128yGhvtmmdlHEfu6JxJPuukhPRFpqhJtWUwCFrt7Z2BxuH0Ad1/q7t3dvTtwAbALeCGiys1V+919TYLxpN2ll17Ku+++y5tvvpnuUEREkibRlfKGAH3D948CywjW1Y5lBFDs7rsS/NyM1bx5c6677jp+//vf8+g99wQr7ZWWws6d0LIldOsG48ZB69bpDlVEpM4SWinPzL5092PC9wbsqNqOUX8J8Ht3/2u4PQs4F9hD2DJx9z0xjh0PjAfo0KFDz02bNtU77lTb+eKLvDRwIBcfdhhmBrt3f7szOxvcIT8fJk+GXr3SF6iIHFISWSkvbrIwsxeBE6PsuhV4NDI5mNkOd69x3yLc1wYoBdq6+zcRZduA5sAM4AN3vzNe0OleVrVW06bBxIlU7tpVex+fWZA47r0XJkxoqOhE5BCWSLKI2w3l7v1r+eDPzKyNu28Nf/GX1XKqS4FnqxJFeO6t4ds9ZvbfwMQ6xp2ZwkRBvEQBQeti166gPihhiEhGS/QG93xgTPh+DPBcLXVHAU9EFoQJpqoLayjwVoLxpE9Jyf5EEekKoA1wNNAFeLj6cVUJI1NbSiIiJJ4spgIXmtl6oH+4jZnlmdn+34tm1gk4CVhe7fjZZrYWWAu0An6TYDzpU1AAUab6mAxsBP6XILPeBqyuXqm8PDheRCRDJTQayt3/AfSLUr4K+PeI7Y1Auyj1Lkjk8zNGWRkUFwddS9WcFfHewtcHQM/ISu5QVATbt2uUlIhkJD3BnQyzZtW6+xdADnA6QZfUwGiVzOKeR0QkXZQskqG09MDhsdU8CHwFvAQMB1pEq1ReDlptT0QylJJFMuzcGbdKM+AHwGZgWqxKO3YkLyYRkSRSskiGli3rXHUfwT2LqHKjPqIiIpJ2ShbJ0K0bZGXVKC4DngS+BiqAhQRjh2uMCAD2HHYYK8vL+fzzz1MZqYhIvShZJMPYsVGLjaDLqT2QS/DE4R+AwVHqHt6sGQ/t3cupp57KhRdeyEMPPURZWW3POIqINBwli2Q4/vhgriezA4pbEzxY8iXBcxZrgZ9HO96MZoMGMfO559i6dSsTJkxg2bJldOnShfPPP58//elPbN26NdqRIiINIqGJBNMlI+eGKimBvn1rPMFdJzk5sHw55B04ZUt5eTkvvPAChYWF/PWvf+V73/seI0aMYPjw4Zx00knJiVtEDhmJzA2llkWy9OoVTAqYk3Nwx+XkBMfl1fz3y87OZsiQITz++ONs27aNSZMmsWbNGrp37865557LfffdRybPvisiTUei61lIpKrJACdODJ6bqK3VdpCzzrZo0YKLL76Yiy++mL1797J06VIKCwvJy8vj5JNPZsSIEVxyySWceuqpSfpmRES+pW6oVFi1KpjrqagoSAqRc0ZVrWcxcGCwnkWUFsXB2LdvH8uXL6ewsJC5c+fSrl07RowYwYgRI+jSpUuC30g1ZWVazEmkEUvpehaZKOOTRZXt24NfrmvXBg/c5eZC167B6KkU/HKtqKjg5ZdfprCwkGeeeYZWrVrtTxxnnnlm/U9cUhIkv+LiYFuLOYk0SkoWUkNlZSWvvfYahYWFFBYWctRRR+1PHF27dg1W8KuLqjU6ktytJiINT8lCalVZWUlJScn+xHHEEUfsTxw9evSInTgiFnOqs6ob9koYIhlHyULqzN154403KCws5Omnn6aysnJ/4ujVq9e3iSPGUOAvgJ8BLxAsQFIAjK7+ITGGAotIeqVt6KyZ/dTM3jazSjOLGYCZDTCzdWa2wcwmRZSfbGavh+VPmVnzROKR+MyMnj17UlBQwPr163n22Wdp0aIFV155JZ06deLGG2/k1VdfxX/726iLOf2SYMH0z4DZwATg7eqVtJiTSJOTUMvCzM4AKoGHgInhokfV6zQD3gcuJJh0tQQY5e7vmNmfgbnu/qSZTQfedPeYk7JWUcsi+dydd955h6effpolTz7JC+vWUX22q38STFvyFsESsQD/RrCq1dTqJ8zKgo8/1igpkQyStpaFu7/r7uviVOsNbHD3D919L8HcekPCdbcvAArDeo8SrMMtaWBmnHXWWdxxxx387aqraN6i5qob7xM8mBM5IPf7RGlZBCfUYk4iTUhDPMHdDvgkYntzWHYc8KW776tWLulWWsphe/bUKP4aOLpaWUuChZ1q0GJOIk1K3Ce4zexF4MQou2519+eSH1LMOMYD4wE6dOjQUB97aIqxmNN3CCZEjPS/wFGxzqPFnESajLjJwt37J/gZW4DIWe/ah2X/AI4xs8PD1kVVeaw4ZgAzILhnkWBMUpsYizl1IVi8aT3QOSx7Ezgr1nm0mJNIk9EQ3VAlQOdw5FNzYCQw34M760uBEWG9MUCDtVSkFjEWczqSYA3xXxPc7H6F4B/s36KdIzs7eFpdRJqERIfODjOzzcC5wPNmtjAsb2tmRQBhq+FagoXi3gX+7O5V90RvAW40sw0E9zBmJhKPJEmMxZwAHgTKgeOBUQSLO0VtWbjXeh4RaVz0UJ5EN3w4zJtX+xQfsZjBsGHwzDPJj0tE6k3rWUjyTZ4cdCXVR3Z2cLyINBlKFhJdChZzEpHGS4sfSWwpXMxJRBoXtSykdhMmBJMCDhsWjJCq3jWVnR2UDxsW1FOiEGmS1LKQ+PLygpvVDbyYk4hkDiULqbvWreHmm9MdhYikgbqhREQkLiULERGJS8lCRETiUrIQEZG4lCxERCQuJQsREYlLyUJEROJSshARkbga5RTlZrYd2HSQh7UCPk9BOKnWGONujDGD4m5IjTFmaPxxd3T3ek230CiTRX2Y2ar6zuOeTo0x7sYYMyjuhtQYY4ZDO251Q4mISFxKFiIiEtehlCxmpDuAemqMcTfGmEFxN6TGGDMcwnEfMvcsRESk/g6lloWIiNRTk0oWZnasmS0ys/Xh19wodc43szURr91mNjTcN8vMPorY1z0TYg7rVUTENT+i/GQze93MNpjZU2bWPNUx1zVuM+tuZq+Z2dtmVmpml0Xsa9BrbWYDzGxdeJ0mRdnfIrx+G8Lr2Sli3+SwfJ2Z/SSVcR5kzDea2TvhtV1sZh0j9kX9ecmQuMea2faI+P49Yt+Y8GdqvZmNybC474+I+X0z+zJiX1qut5k9YmZlZvZWjP1mZn8Mv6dSMzs7Yt/BXWt3bzIv4HfApPD9JODuOPWPBb4AcsLtWcCITIwZ+DpG+Z+BkeH76cCETIkb6AJ0Dt+3BbYCxzT0tQaaAR8ApwDNgTeBM6vV+QUwPXw/EngqfH9mWL8FcHJ4nmYZEvP5ET+7E6piru3nJUPiHgs8EOXYY4EPw6+54fvcTIm7Wv3rgEcy4Hr/CDgbeCvG/oFAMWBAH+D1+l7rJtWyAIYAj4bvHwWGxqk/Aih2910pjap2BxvzfmZmwAVAYX2OT1DcuN39fXdfH77/FCgD0rH+am9gg7t/6O57gScJ4o8U+f0UAv3C6zsEeNLd97j7R8CG8Hxpj9ndl0b87K4A2jdAXPHU5VrH8hNgkbt/4e47gEXAgBTFWd3Bxj0KeKJBIquFu/+N4A/eWIYAj3lgBXCMmbWhHte6qSWLE9x9a/h+G3BCnPojqfkPflfYXLvfzFokPcKa6hpzlpmtMrMVVd1mwHHAl+6+L9zeDLRLYayRDupam1lvgr/YPogobqhr3Q74JGI72nXaXye8njsJrm9djk2Fg/3cnxH8BVkl2s9LQ6hr3JeE//aFZnbSQR6bCnX+7LC772RgSURxuq53PLG+r4O+1o1uDW4zexE4McquWyM33N3NLOZQrzC7dgUWRhRPJvjF15xgqNktwJ0ZEnNHd99iZqcAS8xsLcEvtJRJ8rV+HBjj7pVhcUqu9aHIzK4A8oAfRxTX+Hlx9w+in6HB/QV4wt33mNnVBC26C9Ic08EYCRS6e0VEWSZf76RodMnC3fvH2mdmn5lZG3ffGv6CKqvlVJcCz7r7NxHnrvpLeY+Z/TcwMVNidvct4dcPzWwZ0AN4hqBZeXj413B7YEsyYk5W3GZ2NPA8cGvYDK46d0qudQxbgJMitqNdp6o6m83scKAl8I86HpsKdfpcM+tPkLx/7O57qspj/Lw0xC+vuHG7+z8iNh8muP9VdWzfascuS3qE0R3Mv/NI4JeRBWm83vHE+r4O+lo3tW6o+UDVXf0xwHO11K3R5xj+0qu6FzAUiDrCIMnixmxmuVXdNGbWCjgPeMeDO1VLCe69xDw+ReoSd3PgWYI+08Jq+xryWpcAnS0YOdac4D979RErkd/PCGBJeH3nAyMtGC11MtAZWJnCWOscs5n1AB4CBrt7WUR51J+XBoi5rnG3idgcDLwbvl8IXBTGnwtcxIEt/1Sqy88IZnY6wQ3h1yLK0nm945kPXBmOiuoD7Az/UDv4a52OO/ipehH0MS8G1gMvAseG5XnAwxH1OhFk1sOqHb8EWEvwi+t/gO9kQszAv4RxvRl+/VnE8acQ/PLaADwNtMiUaw1cAXwDrIl4dU/HtSYYFfI+wV97t4ZldxL8ogXICq/fhvB6nhJx7K3hceuA/Ab8eY4X84vAZxHXdn68n5cMibsAeDuMbylwesSxV4X/BhuAcZkUd7h9BzC12nFpu94Ef/BuDf+fbSa4d3UNcE2434A/hd/TWiCvvtdaT3CLiEhcTa0bSkREUkDJQkRE4lKyEBGRuJQsREQkLiULERGJS8lCRETiUrIQEZG4lCxERCSu/x/yhQKx9yUuSgAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80dd2668>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "116\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d8f358>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "117\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c67f98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "118\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d9c320>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "119\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e53470>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "120\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c3b048>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "121\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80da2a20>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "122\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e601d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "123\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80de7e48>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "124\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f98d30>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "125\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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JKhOJYRNwVMz2kVFZLWZ2DvBDYLS776gpd/dN0c/1wDLgxHi/xN1nunuBuxf0buOLZIhIApWVoaM5TvPRVOAG4IuED7YjiNN04Q6LFoVFeCShTCSGMmCgmQ0wsy7ARcDC2ApmdiJwFyEpVMaU55tZ1+j9IcCpQGyntYjIfqWlcYv3AOWEIY/HEL6dXg3Uv68grNec4DwSpJ0Y3H034e/gCeA1YK67v2pmN5pZzdDTW4EDgT+a2Uozq0kcxwHlZvYysBS4qc5oJhGR/Soqag9JjXwA7AIeJvQrrCQMhfx5vHNUV4flOiWhjDzH4O6LgEV1ym6IeX9OguP+CgzJRAwi0g5UVcUtzot+/gfQN3p/LSEx/CLeAVu2ZDqyNkVTYohI69GjR9zifELzUexcqUnnTdUEekkpMYhI6zF0KHTrFnfXeOA3QCWwBfgV8NV4FfPyYIgaKpJRYhCR1qOoKOGuHwPDgEGEzssTCcMg63FPeh5RYhCR1qRPHygsDCOL6ugMzAA+Bt4Hfg3Uu7cwg1GjQEPek1JiEJHWZcoUdnfp0rRj8/JgypTMxtMGKTGISKvyuzVr+J8uXdiToK8hoe7dYfp0KChonsDaECUGEWk1ZsyYwfXXX8+4v/2NjrfdFj7sU63bbLY/KRQXt0ygrZxWrBCRVmHatGnMmjWL5cuX89nPfhYGD4Zhw8LcR4sWhQQQO4dSXl7oaB41KjQf6U6hwZQYRCSnuTtTpkzh0Ucf5ZlnnuHwww/fv7OgAObNC3MflZaGJ5q3bAnPKQwZEkYfqaO50ZQYRCRn7dmzh+9///v84x//YPny5fTq1St+xd69YfLklg2uDVNiEJGctGvXLi677DI++OADlixZwkEHHZTtkNoNJQYRyTnV1dV885vfpEOHDixatIhujR2BJGnRqCQRySmffPIJI0eOpGfPnsybN09JIQuUGEQkZ/zzn//krLPOYvDgwdx///107tw52yG1S0oMIpITNm3axOmnn86IESO444476NBBH0/Zoj95Ecm6N954g9NOO41x48bxy1/+Ekv10Jo0q4wkBjMbaWavm9k6M7s+zv6uZvaHaP8LZtY/Zt+UqPx1MzsvE/GISOvxyiuvcMYZZ3Dddddx3XXXZTscIQOJwcw6AncAhcDxwMVmdnydalcAW9z9GMI06TdHxx5PWCN6MDASmBGdT0Tagb///e+cc8453HrrrXzve9/LdjgSycQdw8nAOndf7+47gTnAmDp1xgCzo/cPA2dbuFccA8xx9x3u/iawLjqfiLRxS5cu5atf/SqzZs3i4osvznY4EiMTzzEcAbwTs70ROCVRHXffbWZVQK+o/Pk6xx6RgZhEJBsqK8PUFBUVYX3mHj3Cqmvjx9eammLhwoVMmDCBuXPnMnz48KyFK/G1mgfczOxK4EqAfv36ZTkaEamlrCxMZrd4cdjevn3/vvnzYerUsMDOlCn8bs0a/uu//ovHHnuMYcOGZSdeSSoTiWETcFTM9pFRWbw6G82sE9AD+LCBxwLg7jOBmQAFBQWegbhFJBNKSmDSpDCzqcf5r1kz4+mCBex67DFe6d6dJc8+y+DBg1s2TmmwTPQxlAEDzWyAmXUhdCYvrFNnITAuen8B8LS7e1R+UTRqaQAwEPh7BmISkZZQkxS2bduXFIYTltQ8MHodW1PXnc47d/KLHTsYvGJFNqKVBko7Mbj7buBq4AngNWCuu79qZjea2eio2j1ALzNbB1wLXB8d+yowF1gNPA583933pBuTiLSAsrL9SaGO3wJbo9frdfZ1qK4Ox5WXt0CQ0hQZ6WNw90XAojplN8S83w58M8GxvwB+kYk4RKQFTZtWe2GcxqiuDsfPm5fZmCQj9OSziDReZWXoaI7XpwBMAQ4BTgWWxavgHlZd27y52UKUplNiEJHGKy1NuOtmYD1hFMmVwNeAN+JVNEt6HskeJQYRabyKitpDUmOcAhwEdCWMODmVOu3MNaqrw1KcknOUGESk8aqqGlzVgITjy7dsyUQ0kmFKDCLSeD16xC3+mDA8cTuwG/gdsIIwEVpc+fnNEJykS4lBRBpv6FCIs7LaLuBHQG9C5/NvgAXAoHjnyMuDIUOaMUhpKiUGEWm0HRdfzK7du+uV9yY88fop4e7heeDcRCdxh6KiZopQ0qHEICKN8vTTT/OFc8/lxd698aYuqGMGo0bVmlhPckermURPRLLrgw8+YNKkSaxYsYJf//rXfPHww2H48LhPPqeUlwdTpmQ8RskM3TGISFJ79+7lzjvvZMiQIfTt25dXX32VMWPGwLBhMH06dO/euBN27x6OKyhonoAlbbpjEJGEVq5cycSJE+nUqRNLlixhSN3O4uLi8DPZ7Ko1zMKdwvTp+4+TnKQ7BhGp59NPP+Xaa6/lvPPO47vf/S4rVqyonxRqFBfD8uUwdmwYqZSXV3t/Xl4oHzs21FNSyHm6YxCRfdyd+fPn84Mf/IBzzjmHV155hd4N6SAuKAgT4m3eHKa5WLUqPLyWnx+GpBYVqaO5FVFiEBEA3nzzTa6++mrefPNNHnzwQc4444zGn6R3b5g8OfPBSYtSU5JIO7dz506mTZvGsGHDOO2001i5cmXTkoK0GbpjEGnHli9fTnFxMQMGDKCsrIwBAwZkOyTJAWndMZjZwWb2pJmtjX7Wm/jEzE4ws7+Z2atmVmFm34rZV2pmb5rZyuh1QjrxiEjDbN68maKiIr797W/z85//nEcffVRJQfZJtynpemCJuw8ElkTbdW0DLnP3wYS5tG43s54x+ye7+wnRa2Wa8YhIEnv37mXWrFkMHjyYXr16sXr1as4//3ysqU8wS5uUblPSGMLa3wCzCYs1XRdbwd3XxLx/18wqCVOqfJzm7xaRRli1ahUTJ05kz549/OUvf+GEE3SDLvGlmxgOdff3ovfvA4cmq2xmJwNdqL2g0y/M7AaiOw5335FmTCJtT2VlGAZaURHWQujRI8xwOn58ymGgW7du5ac//SmzZ8/mZz/7Gd/97nfp0EHjTiSxlInBzJ4CDouz64exG+7uZpbwsUcz6ws8AIxz971R8RRCQukCzCTcbdyY4PgrCSsF0q9fv1Rhi7QNZWUwbVpYXxlqr5o2fz5MnQqFhWHeoWHD6h3+yCOPcM0113DGGWewatUqDj006Xc3kcDdm/wCXgf6Ru/7Aq8nqPcZ4B/ABUnONRx4tCG/96STTnKRNm/GDPfu3d3N3MNkE/FfZqHejBn7Dn3rrbd89OjRfuyxx/qSJUuyeBGSS4Byb8BnbLr3kwsJy7oS/XykbgUz6wL8Cbjf3R+us69v9NOArwOvpBmPSNtQUhLmH9q2Lfn8QxD2b9sGkyax+7e/5dZbb+Wkk05i2LBhvPzyy5x11lktE7O0Gen2MdwEzDWzK4C3gQsBzKwAmOjuE6Ky04FeZlYUHVfkYQTS78ysN2FZ2JXAxDTjEWn9ysr2J4U41gJDgAuAB2N3bNvGrmuuYcMpp/DCCy/wuc99rvljlTYprcTg7h8CZ8cpLwcmRO8fpM6/35h6+iojUte0aWGm0gS+D9TvTQi6Ar/u2xdTUpA0aGiCSC6prAwdzQmaj+YAPYnzbSzSwR1bvDhMZifSREoMIrmktDThrk+AG4DbUp3DLOl5RFJRYhDJJRUVtYekxvgxcAVwZKpzVFeHaa9FmkiT6InkkqqquMUrgaeAlxp6ni1bMhSQtEdKDCK5pEePuMXLgLeAmkc7twJ7gNWEB4Tqya83n6VIg6kpSSSXDB3K3m7d6hVfSZhHZiX7x3X/O/BEvHPk5YVV00SaSIlBJAe4O8888wwTn3+enXH6GLoT5qWpeR0IdCPMRhnnZGEpTZEmUlOSSBZ9+umnPPjgg8yYMYOdO3dy1VVX0WHnTli0KOkTzz9JtMMMRo3S+sqSFiUGkSx45ZVXKCkp4aGHHuLMM8/k9ttv56yzzgrrInz5y7B0acInn5PKywsT6omkQU1JIi1k586dzJkzh9NPP50RI0bQu3dvVq1axbx58zj77LP3L5YzbBhMnw7duzfuF3TvHo4rKMh88NKu6I5BpJlt2LCBmTNnMmvWLI4//niuueYaxowZQ+fOnRMfVFwcfk6aFJ5LSDaRnlm4U5g+ff9xImnQHYNIM9i7dy9PPPEEY8aM4cQTT+TTTz9l6dKlPP3001xwwQXJk0KN4mJYvhzGjoVu3cKHf6y8vFA+dmyop6QgGaI7BpEM+vDDDyktLaWkpISDDjqIq666it///vcccMABTTthQQHMmxfmPiotDU80b9kSnlMYMiSMPlJHs2SYEoNImtydsrIyZsyYwYIFCxg9ejQPPPAAX/ziF/f3G6Srd2+YPDkz5xJJQYlBpIm2bdvGnDlzmDFjBh999BETJ07k1ltvpbe+wUsrp8Qg0khr1qyhpKSEBx54gC996UvceOONnHfeeXTs2DHboYlkRFqJwcwOBv4A9CdM5XKhu9ebvcvM9gA10z1ucPfRUfkAwhTzvYAXge+4+850YhIBwroGpaVhttKqqjAH0dChMH58k9rkd+/ezZ///GdmzJhBRUUFl19+OWVlZQwYMCDzsYtkmXmq9WSTHWx2C/CRu99kZtcD+e5+XZx6W939wDjlc4H57j7HzO4EXnb3klS/t6CgwMvLy5sct7RhZWVhBbTFi8N27PQSeXlh2GdhYXgIbFiiddD2e++997j77ruZOXMm/fv3p7i4mAsuuICuXbs20wWINB8ze9HdUz7oku5w1THA7Oj9bODrDT3QQq/cWcDDTTlepJ6SEhg+HBYsCAmh7pxD1dWhbMGCUK8k/ncQd2fZsmVceOGFHH/88bz77rs89thjPPvss1x66aVKCtLmpdvHcKi7vxe9fx84NEG9bmZWDuwGbnL3BYTmo4/dfXdUZyNwRJrxSHtVUhIeBmvINBLuod6kSWE7Gv9fVVXF/fffT0lJCWZGcXExd999Nz0STIUt0lalTAxm9hRhQse6fhi74e5uZonapY52901m9lngaTNbBcRfkSRxHFcSZh+mX79+KWpLu1JWFjcpfBtYAvyL8A/4v4EJsRWi5PD6Zz7DbStWMHfuXEaMGEFJSQmnn3565oaairQyKRODu5+TaJ+ZfWBmfd39PTPrC1QmOMem6Od6M1sGnAjMA3qaWaforuFIYFOSOGYCMyH0MaSKW9qRadNCM1EdU4B7gK7A/wOGE/7hnRRTZ8+2bbwxYQJH/s//sHr1avr27dsCAYvktnT7GBYC46L344BH6lYws3wz6xq9PwQ4FVjtodd7KXBBsuNFkqqsDB3NcQZRDCYkBQCLXm/UqdMRKAR+PHGikoJIJN3EcBNwrpmtBc6JtjGzAjObFdU5Dig3s5cJieAmd18d7bsOuNbM1hH6HO5JMx5pb0pLk+6+irDIzeeBvsCoOHXMLOV5RNqTtDqf3f1D4Ow45eVEzbnu/lcg7jqD7r4eODmdGKSdq6ioP/ooxgzgN8DfCOsmxx1PVF0d5iASEUCzq0prV5V6DENH4CuEYW8JH5LZUu+5TJF2S4lBWq3du3dTubPhD8rvpn4fwz75+ZkISaRNUGKQVuXdd9/l3nvv5cILL6RPnz78btUqdnWq3yJaSZhrZSuwB3gCeIg47Z4QnogeEre1U6Rd0iR6ktN27drFc889x+OPP87ixYt55513OOeccygsLOT222/n8E6d4OijYffuWscZodloIrAXOBq4HRgd75e4h3UNRARQYpActGHDhn2JYOnSpQwcOJCRI0cyY8YMTjnlFDrVvUMoLAzTXMQMWe0NLG/ILzODUaO02I1IDCUGybodO3bwzDPPsHjxYh5//HEqKysZMWIE3/jGN7jrrrvo06dP8hNMmQJPPNGw6TDqyssLx4vIPkoMkhXr16/flwiWL1/O4MGDKSws5L777uOkk05q3NoGw4bB9OkNnyupRvfu4biClJNNirQrSgztUYbXKmiI6upqli1btq+J6JNPPmHkyJFceumllJaW0qtXr/R+QTQRHpMmhecSkk0nbxbuFKZP33+ciOyT1noM2aL1GJoow2sVJOPurFmzZl8ieO655zjxxBMZOXIkhYWFfOELX6BDh2YYFFdeHq5x0aKQAGLnUKq5xlGjwjWTxP4/AAAKwElEQVTqTkHamYaux6DE0F7UTEvdjN+mt27dytKlS/c1Ee3cuXNfIjj77LPp2bNnmhfRCJs3h7uiVavCw2v5+WFIalGROpql3WpoYlBTUnuQgbUK4ld1Vq9evS8RvPDCC5x88smMHDmShQsXMnjw4OxNXd27N0yenJ3fLdLK6Y6hrSsrC6uV1UkKOwgTzD0FfAR8DphGmGl0n+7dYfnyWk0un3zyCU899RSPP/44jz/+OB06dKCwsJDCwkLOPPNMDjrooGa+IBFpKt0xSJBgrYLdwFGEsf79gEXAhcAqoH9Npepq/Je/5OUbbtjXV/CPf/yDL3/5yxQWFnLttddy7LHHakEbkTZGdwxtWWVleCo4yeyjsYYCU4FvxJRtB84YMIBTvvpVRo4cyfDhw+nevXszBCsizU13DNKoNQY+ANYQFreJ1aVbN14oLlZ7vUg7osSQTBbG+2dUirUKauwCLiUsoff5Ovs6bN+utQpE2pm0EoOZHQz8gdAs/RZwobtvqVPnTOBXMUWfBy5y9wVmVgqcAdRMql/k7ivTiSkjko33nz8fpk7N2Hj/5rBr1y7efPNNeqxZw6Ep6u4FvgN0AX6bqJLWKhBpV9K9Y7geWOLuN5nZ9dH2dbEV3H0pcALsSyTrgL/EVJns7g+nGUfmpBrvX9ORu2BBmJ8nS0/P7t27l40bN7JmzRrWrl3LmjVr9r3fsGEDRxxxBHdXVydNDA5cQWhGWgR0TlRRaxWItCvpJoYxwPDo/WzC6onXJaoMXAAsdvcmzHbWApppvH9TuTubN2+u9+G/Zs0a3njjDfLz8xk0aBCDBg1i4MCBnHnmmQwaNIgBAwbQtWtXuOWWcHeToDmpGHiNMGQ1L1EQWqtApN1Ja1SSmX3s7j2j9wZsqdlOUP9p4DZ3fzTaLgW+RBhWvwS43t13pPq9zTIqKcF4/48I36r/AhxCGOt/Sd1j44z3b4yqqirWrl1b78N/7dq1dOzYsdaHf837Y445hgMPPDD5iZOMSnqb0P7XldrfDu4i9Dfs060bbNjQOvpURCSpjE2JYWZPAYfF2fVDYHZsIjCzLe4et93BzPoCFcDh7r4rpux9QhP3TOANd78xwfFXAlcC9OvX76S33347xaU10vnn15vTH+BiQjv8PcBK4N+Bv1Jn9I4ZjB0L8+YlPH11dTVvvPFG3KafrVu37vvQj/3wHzhwYPqTyyW4rgZpwHWJSOvRInMlmdnrwHB3fy/6kF/m7scmqPufwGB3vzLB/uHAJHf/aqrfm/E7hgTfrP8F5AOvAIOisu8ARwA31T1Ht27sXr+et/71r7gf/u+//z4DBgyI++2/b9++zfeQWII7oQZJ805IRHJLSz3HsJAwyvGm6OcjSepeDNRaEcXM+kZJxYCvEz6DW16C8f5rCH9Ag2LKvkD8lcGqd+zgp0cdxR+OOmrfB/6xxx7L1772NQYNGkS/fv3qrzzWErRWgYg0UrqfVDcBc83sCkKz9YUAZlYATHT3CdF2f/bPwBDrd2bWm7BE70rCEr0tL8F4/63AZ+qU9QA+jXOKPHd+fuGF3PT73zdDgGnSWgUi0ghpJQZ3/xA4O055OTAhZvstQgtM3XpnpfP7M6aqKm7xgcAndco+ARJNE9fp03gpI0cUF4e7B61VICIp6MlnCE80xzGIMNncWmBgVPYy9aeN2CfXx/sXFISOZK1VICJJKDFAmOZi3rx6zUkHAOcDNwCzCG1djxBGJdXTmsb7a60CEUmiGdZWbIWKihLumgFUA30IveclJLhjcE96HhGR1kKJAaBPnzD3UZwhowcDCwhDVzcQ5+E2CMeNGqVmGBFpE5QYakyZEpqDmiIvLxwvItIGKDHUqBnv39hFaDTeX0TaGHU+x9J4fxER3THUU1wcpoEYOzZMIFe3eSkvL5SPHRvqKSmISBujO4Z4NN5fRNoxJYZkNN5fRNohNSWJiEgtSgwiIlKLEoOIiNSixCAiIrUoMYiISC1KDCIiUosSg4iI1KLEICIitZgnmw8oR5nZZsJM2P/MdiwZcAht4zpA15KL2sp1gK4lE45295TTNrTKxABgZuXu3uqnNG0r1wG6llzUVq4DdC0tSU1JIiJSixKDiIjU0poTw8xsB5AhbeU6QNeSi9rKdYCupcW02j4GERFpHq35jkFERJpBq0kMZnawmT1pZmujn/kJ6t1iZq+a2Wtm9mszs5aONZlGXEc/M/tLdB2rzax/y0aaWkOvJar7GTPbaGa/bckYG6oh12JmJ5jZ36J/XxVm9q1sxBqPmY00s9fNbJ2ZXR9nf1cz+0O0/4Vc/PdUowHXcm30f6LCzJaY2dHZiDOVVNcRU+8bZuZmljOjlFpNYgCuB5a4+0BgSbRdi5l9GTgVGAr8L2AYcEZLBtkAKa8jcj9wq7sfB5wMVLZQfI3R0GsB+BmwokWiapqGXMs24DJ3HwyMBG43s54tGGNcZtYRuAMoBI4HLjaz4+tUuwLY4u7HAL8Cbm7ZKBumgdfyElDg7kOBh4FbWjbK1Bp4HZjZQcB/Ai+0bITJtabEMAaYHb2fDXw9Th0HugFdgK5AZ+CDFomu4VJeR/QPqJO7Pwng7lvdfVvLhdhgDfk7wcxOAg4F/tJCcTVFymtx9zXuvjZ6/y4hWefCGq8nA+vcfb277wTmEK4nVuz1PQycnWt305GU1+LuS2P+PzwPHNnCMTZEQ/5OIHxhuhnY3pLBpdKaEsOh7v5e9P59wgdNLe7+N2Ap8F70esLdX2u5EBsk5XUAg4CPzWy+mb1kZrdG30ByTcprMbMOwP8BJrVkYE3QkL+XfczsZMIXkDeaO7AGOAJ4J2Z7Y1QWt4677waqgF4tEl3jNORaYl0BLG7WiJom5XWY2b8BR7n7Yy0ZWEPk1JrPZvYUcFicXT+M3XB3N7N6w6nM7BjgOPZ/g3jSzE5z92cyHmwS6V4H4e/lNOBEYAPwB6AIuCezkaaWgWu5Cljk7huz/QU1A9dSc56+wAPAOHffm9kopaHM7NtAAbnXXJxS9IXpNsL/65yTU4nB3c9JtM/MPjCzvu7+XvQfM16b+1jgeXffGh2zGPgS0KKJIQPXsRFY6e7ro2MWAF8kC4khA9fyJeA0M7sKOBDoYmZb3T1Zf0SzyMC1YGafAR4DfujuzzdTqI21CTgqZvvIqCxenY1m1gnoAXzYMuE1SkOuBTM7h5DQz3D3HS0UW2Okuo6DCP2gy6IvTIcBC81stLuXt1iUCbSmpqSFwLjo/TjgkTh1NgBnmFknM+tM+CaRa01JDbmOMqCnmdW0X58FrG6B2Bor5bW4+6Xu3s/d+xOak+7PRlJogJTXYmZdgD8RruHhFowtlTJgoJkNiGK8iHA9sWKv7wLgac/Nh5hSXouZnQjcBYx291wclAEprsPdq9z9EHfvH/3feJ5wPVlPCgC4e6t4EdpDlwBrgaeAg6PyAmBW9L4j4R/Ma4QP0tuyHXdTriPaPheoAFYBpUCXbMfe1GuJqV8E/Dbbcafx7+vbwC5gZczrhGzHHsU2ClhD6PP4YVR2I+HDBsKgjD8C64C/A5/NdsxpXMtThEElNX8HC7Mdc1Ouo07dZYSRVlmP29315LOIiNTWmpqSRESkBSgxiIhILUoMIiJSixKDiIjUosQgIiK1KDGIiEgtSgwiIlKLEoOIiNTy/wGNsL63OHT3IAAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e25f98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "126\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80ca3d30>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "127\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d07780>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "128\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d58a58>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "129\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d62550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "130\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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/+c/86le/4vzzz+c3v/lNw5vNItIkybb5K/nnSnV16EIZ4yGqw4E/EE4CANcAX9Cwa+WO1q1ZtWAB3z75ZMxiDqtWED799FPGjx/Pk08+ye9//3t+/OMfF/S/RySXmm0mL0lRgoHOfg48BGwhPEE7DxgYo1zr3Xfn8FdfLfhE2blzZ6ZOncqjjz7KH/7wB0477TSWL1+e67BEWjQl/1xJMGDavwLLgD2BA4Ey4NxYBVvYgGknnHACr732GkOHDuWUU05h3Lhx/POf/8x1WCItkpI/hCaYyZNh+HA4++zwc/Lk7I5BH2fAtFrCVf5Q4J/AJ8BG4N/j1dPCBkxr3bo1V199NUuXLmXdunX07t2bRx99lHxtnhQpWMncFc7Fq1l6+7z2mnt5eeih0rZt7J4r5eWhXIasWbPG77rrLl/UrVvMbpIbwAH/PGrZY+BHxOtWOWJExmLLR88995wffvjhPmjQIF+9enWuwxHJeyTZ26d4r/wrKsJTq7Nnh+aX+k0wNTVh2ezZoVxFRUq7+eyzz5g5cyaXX345PXr04MQTT+Rvf/sb7Y4/ntq2bRuU34cwNn4FsIPQ2+ceoE+syotgwLRTTz2Vt956i379+nH88cdzww03sDXBSKMikpzi7O1TUdFgQvJGtWsHt9wCY8YkLLZ161Zeeukl5s+fz7PPPsuKFSv43ve+x4ABA+jfvz9HHnlkuEGboLfPW4SbvkuA3YDTgNuBfesXbNsW1q7N2Jg/+W7t2rX8/Oc/Z+nSpdx+++0MHBjrNrhIcVNXz3hijFPzJ2A6sBS4IPI+pnbtYNEiKPvmuNbW1rJkyRKeffZZ5s+fz8svv8yRRx5J//79GTBgACeccAIlJSWx64vTzz8pZlBeDrNmNX3bAjd37lyuvvpqjjnmGG699VYOOuigxBs0w2B5IvlCY/vEU17eYHiCWZF29cvBRzY2bMHQof73v//dp02b5ueff77vs88+fthhh/mVV17pjz32mG/cuDH5WOI84Zv0EA+NPEXbkm3ZssWvv/5679y5s0+ePNm3bdvWsFAO7umI5BrNObwDoYPKCmA1MC7G+jbAw5H1rwKHNFZnVpL/+vUNk0DUa0JjyR+8xsy/3bmzX3DBBX733Xf7+++/n15MGR7bp9isWrXKzzzzTD/iiCN84cKF36zI0mB5Ivmu2ZI/oVn6XeBQoITQVN27XpkrgDsj74cBDzdWb1aS/+9+l3by39mmje/83e8yG5cSVVpqa2t95syZftBBB/mIESN8080364QqRSvZ5J+J3j7HAavdfY27byM8nDqkXpkhhE4rADOB0y0Xj6UmeLAqWa2++opWb7+doYAixowJ9xLKy8NN3NLSXdeXlobl5eWhXCM3nYuNmfGDH/yA5cuXU+ZO63HjYt7Mf4gwdMYeQA/gheiVW7aETgAteUgRkSiZmFbpW8AHUZ/XAcfHK+PuO8xsE9CZ8AzT18xsNDAaoFu3bhkIrZ44D1Y1WTYerCorCzdvMzBgWrFq3749//bPf+JmDW6izyc8KPcw4Wrlo1gV1NSECXWK8Ca6FJ+8mlPP3acCUyH09sn4DjI1YmSnTpmpJ5YuXeCaa7JXf0tWXQ3z5mHe8KtzPXAdcELk87dibe8Oc+eGE7BOtNLCZaLZ50Mguq/dgZFlMcuYWWugI/BpBvbdNH36hOaTenYAW4GdkdfWyLKYiuDBqoIVZ7C8ncBiYAPwL4Qv6FVATazCZgkH3RNpKTKR/CuBnmbW3cxKCDd059QrMwcYGXn/Q+C5yI2J5jVqVMzFNwGlwM3A/ZH3N8Wrwz1uPZJjce7prAe2E242vUB4iO5N4vyOW9hgeSLxpJ383X0H4ULqaeAdYIa7LzOzG83snEix/wY6m9lq4BfAuHT3m5KuXcMk6PXuNU8kMqBO1GtirO3NYPBgNQnkqzj3dOpun18N7E8YQuMXwNx49bSwwfJEYslIm7+7z6Xe/yV3vy7q/VbgR5nYV9rGj4enn27a0A51SkvD9pKf4tzT6URo6ok+5SfsapbNezoieaL4Bnbr2zeM0dOuXdO2qxvbp6zxp6YlR+Lc0wG4mDA+UjVhiOxbgbNiFdQ9HSkSxZf8IfSTrzsBNPa4gVnSg7pJjiW4F/P/gL5AL0Jf/2OACTHKbd+2jfWDBmUjOpG8UpzJH/RgVUsU554OwO7AFMIQ2R8DtwH1/0ZwM97p3p3ep5zCtddey6efNn+HNJHmUrzJH755sGrtWrjhBhgxAs46K/y84YawfNYsNfUUkvHjG57Ik2SlpfR58EGqqqrYvHkzhx12GDfeeCObN2/OcJAiuVd8QzpLy5eh+RreffddJk6cyDPPPMO1117LFVdcQWmKJxaR5pLskM7FfeUvLVOG7un06NGD++67jwULFvDiiy/Ss2dP7rrrLrZv357F4EWah5K/tEwZvKdz5JFH8uijj/LYY48xa9YsDj/8cO6//3527tyZ5X+ESPao2UdavgwPlrdw4UImTJjApk2buOmmmxgyZAi5GKRWJBZN4yiSRe7O3LlzmTBhAiUlJfz2t7+lf//+OglIzqnNXySLzIzvf//7vPHGG4wdO5arrrqK0047jZdeeinXoYkkRclfJA2tWrXivPPOY9myZYwYMYILLriAs88+myVLluQ6NJGElPxFMqB169b85Cc/YeXKlZxxxhkMHDiQYcOGsXLlyqZVVF0NkyfD8OFw9tnh5+TJ4b6FSAYp+YtkUJs2bbj66qtZvXo1Rx99NCeddBKXXnopa9euTbxhZSUMHQoHHwzXXw8PPABPPhl+TpwI3bqF9ZWVzfLvkJZPyV8kC/bYYw/Gjx/PqlWr2G+//TjmmGP42c9+xvr16xsWrqiAfv1g9uwwH0H9OQlqasKy2bNDuYqK5vgnSAun5C+SRXvttRc33XQTy5cvx8zo3bs3v/rVr9hYN2dA9NPIjfW8c/9monmdACRNSv4izWDfffflj3/8I2+++SYbNmygV69e/PmKK/Bf/rLBMBT9CIPOtY+8DqtfWd0JQF2hJQ1K/iLNqFu3bkybNo0XX3yRI+bMobYm5kzC/An4MvJaEatATQ1MmpS9QKXFy8hMXiLSNL322gvSGTLaHebODb2ANK2opEBX/iK5MH16wtXjCXMNnwQsjFfIrNF6ROJR8hfJhaqqhr16In4HrAE+BEYDZwPvxipYUxPGKxJJgZK/SC5s2hR31fFAB6ANMJJw9T83XuG6XkMiTaTkL5ILHTsmXdSAuJ1AO3XKRDRShJT8RXKhT58wn0A9nwNPA1uBHcADwN+AgbHqKC0NQ1OLpCCt5G9me5vZfDNbFfnZ4DLEzL5jZi+b2TIzqzKz89PZp0iLMGpUzMXbgV8DXQg3fG8HZgO9YpTd9tVXLD/uuCwFKC1dulf+44AF7t4TWBD5XN8W4CJ3P4JwAfNHM9srzf2KFLauXWHQoAbTTHYBKoHNhL8CXgEGxNjczVhz+OGcPmwYgwcP5vnnnydf5+aQ/JRu8h8C3BN5fw9wbv0C7r7S3VdF3v8DqCZ8x0WK2/jxDaeXTJKVlvLt6dN57733GDp0KJdffjnHHXccjzzyiKaXlKSkm/z3dfePIu8/BvZNVNjMjgNKiNNzTaSo9O37zUTzTVE34XxZGW3btuXSSy/lnXfeYcKECdx666306tWLKVOmsKXesBEi0RpN/mb2rJm9HeM1JLqch7854/7daWb7A/cBF7t7bZwyo81ssZkt3qDxy6UYjBnzzQmgsSkgzb5J/PUmnG/VqhXnnnsuL730Evfeey9PP/003bt354YbbuCTTz7J4j9AClWjyd/d+7v7kTFejwPrI0m9LrlXx6rDzPYEngImuPsrCfY11d3L3L2six5Zl2IxZgwsWgTl5aEHUP2moNLSsLy8PJSrl/jrO+mkk3j88cdZuHAhH3zwAb169eKqq65izZo1WfxHSKFJawJ3M/s98Km732xm44C93f3aemVKgHnAE+7+x2Tr1gTuUpQ2bAhDNixdGh7g6tQpdOccNSrlMXw++ugjbrvtNqZNm0b//v255pprOPbYYzMatuSPZCdwTzf5dwZmAN2A94Hz3P0zMysDLnf3S81sOPBnYFnUpqPc/a1EdSv5i2TW5s2bmTZt2tf3Ba699lrOOOMMrLHmpliqq8NJqqoqPK3csWN4duHiizXQXI41S/LPJiV/kezYtm0bDz/8MJMnT6ZVq1Zcc801nH/++ey+++6Nb1xZGYaSnjcvfI4en6i0NIw2OmhQ6MnUt292/gGSULLJX0/4ihSZkpISRowYQVVVFTfffDN33303PXr04NZbb2Xz5s3xN9R0ky2Kkr9IkTIzBg0axHPPPcesWbN4+eWX6d69OxMmTODjjz/etbCmm2xxlPxFhL59+zJjxgxeffVVPv/8cw4//HBGjx7NihUrQlNPXeKPYRVh2snh9Vdousm8puQvIl/r0aMHd9xxBytXruSAAw7g5JNP5pUhQ/A4000CXAnEbd3XdJN5S8lfRBro0qULEydO5L1XX6VswwYsTlPPQ8BewOnxKoqeblLyipK/iMS1xyOP0Lp17Km+vwCuA/6jsUo03WReUvIXkfgSTDf5/4BLgAMbq0PTTeal2Kd0ERGIO93kW8CzwJvJ1qPpJvOOkr+IxBdnusmFwN8Jj/YDfAnsBJYDb8TaQNNN5h01+4hIfHGmmxxNGJf9rcjrcuD7hCkoG9B0k3lJyV9E4osz3WQ7YL+oV3tCX/9Yo/p8tXUrM9q1oyZBd1Fpfkr+IhJfnOkm65sI3B9juZvx6fHHc/cTT9CtWzd++ctfsnLlymxEKk2k5C8iiaU53eQBt9/OX//6V1599VV23313Tj75ZE4//XRmzpzJ9u3bMxysJEvJX0QSy8B0kwCHHnooN998M2vXruWyyy7j9ttvp1u3bvz617/m/fffz0LgkoiSv4g0LkPTTQK0adOGYcOGsWjRIhYsWMDmzZv57ne/y1lnncVTTz2V/gT01dUweTIMHw5nnx1+Tp6sp4zr0Xj+IpK8xYvDWD1z54YkH30Tt248/8GDQ1NRWaNDyn9ty5YtPPTQQ9x5552sX7+e0aNHc8kll7DffvslH5vmGgA0mYuIZFMWppus8/rrr3PXXXfxyCOPMGDAAC6//HJOPfXUxDOO1Q05XVOTeMhps3AiiPNXSUug5C8iBW3Tpk3cf//9VFRUsH37dn76058ycuRIOnfuvGvB6LkGkpWgWarQaSYvESloHTt25Morr2Tp0qXcfffdvPHGG/To0YORI0fy8ssv4+5x5xoYDuwP7An0Av6rfuWaa0BX/iJSOD755BOmT5/OnXfeyR577MFjZnSvqmow5PQy4F+ANsD/Av2Ap4BjowuZQXk5zJrVPME3E135i0iLs88++zB27FhWrlzJbb/+NQcuXRpzroEjCIkfwCKvd+sXKvK5BpT8RaTgtGrVilPee4+SkpK4Za4gDEPxbUIT0OBYhYp4rgElfxEpTAnmGgCYAmwGXgCG8s1fArso4rkG0kr+Zra3mc03s1WRn3HHbTWzPc1snZn9KZ19iogAcecaiLYb8D1gHVARr1CRzjWQ7pX/OGCBu/cEFkQ+x/Mb4G9p7k9EJIgz10AsO4jR5l+nSOcaSDf5DwHuiby/Bzg3ViEzOxbYF3gmzf2JiARx5hqoJkwsXzfBzNPAg8SeZH5nSQm1Rx6ZzSjzVrozee3r7h9F3n9MSPC7MLNWwB8IXW/7p7k/EZFg1Ci4/voGi43QxHM5UAscDPwROCdGFTu2b+f4//xPBm3cyIgRI+jdu3f6cVVXh5vIVVWhaapjx3CiuvjitJ9+zqRGr/zN7FkzezvGa0h0OQ8PDMR6aOAKYK67r0tiX6PNbLGZLd5QpN2vRCRJceYa6AIsAj4HvgCWApfF2t6MNuXl3PfXv7Jz504GDBhAWVkZt912G9XV1U2Pp7IShg6Fgw8OJ6UHHoAnnww/J06Ebt3C+srKptedDe6e8gtYAewfeb8/sCJGmQeAtYQpPz8h/D5ubqzuY4891kVEEnrtNfd27dxDr/2mvdq1c6+s/LqqHTt2+DPPPOPDhw/3jh07+llnneUPP/yw19TUNB7HlCmhPrPE+zQL5aZMydrCOgsMAAAIs0lEQVQhARZ7Evk73Tb/OcDIyPuRwOMxTi4Xuns3dz8EGAvc6+6JbgyLiCQnQ3MNAOy2224MGDCA++67j3Xr1vGjH/2IadOmccABB3DZZZfxwgsvUFtb27Cu6LGFGhsxwf2boSUq4vY/ahbpJv+bgQFmtorQnn8zgJmVmVmD4TRERDIug3MN1Gnfvj0XXXQR8+fPp6qqip49ezJmzBh69OjBddddx6pVq0LBOGMLfQaUA3sQ7jn8pf4O8mBsIY3tIyItQ5bmGqjj7rz11lvce++9PPjgg3Tv3p0Hampiji10AeFm838DbwHfB14iDDvxtSyNLaQhnUWkOGVxroE6O3bsYOGMGfzriBGU1GsK+ifQCXibMKIowAjgW0SaRqK1bQtr12a0F1CyyT/drp4iIvmlSxe45pqs7qJ169b0X7cOSkoaDDGxkpBYe0UtO5rQA6mBurGFshxvLBrbR0QkFXHGFvqSMI9AtI6EcYYayOHYQkr+IiKpiDO2UHtCf/ZoXwAd4tWTo7GFlPxFRFIRZ2yhXoSxhFZFLVtCvZu90XI0tpCSv4hIKuKMLbQHYQjp6wg3f18kPAA1IlYdpaXhZnQOKPmLiKRi1Ki4q6YANUBXQrfPCuJc+bsnrCeblPxFRFIRZ2whgL2B2YQr/7XAj2NtbxaeO8jRYG9K/iIiqRo/PjTdpKK0NGyfI0r+IiKpyuDYQs1ND3mJiKSjboygsWNDv/1EoyaYhSv+RsYWag668hcRSdeYMbBoURirp23bhk1BpaVheXl5KJfjxA+68hcRyYyysjBIWzOMLZQJSv4iIpnUDGMLZYKafUREipCSv4hIEVLyFxEpQkr+IiJFSMlfRKQIKfmLiBQhJX8RkSKk5C8iUoTME41DkUNmtgF4P0GRfYBPmimcZOVjTJCfcSmm5ORjTJCfcSmm4GB3b/RR4rxN/o0xs8Xunrsh8WLIx5ggP+NSTMnJx5ggP+NSTE2jZh8RkSKk5C8iUoQKOflPzXUAMeRjTJCfcSmm5ORjTJCfcSmmJijYNn8REUldIV/5i4hIivI6+ZvZj8xsmZnVmlncO+ZmNtDMVpjZajMbF7W8u5m9Gln+sJmVZCCmvc1svpmtivzsFKPMqWb2VtRrq5mdG1k33czei1r3neaIKVJuZ9R+50Qtz/hxSjYuM/uOmb0c+T1Xmdn5UesydqzifUei1reJ/NtXR47FIVHrxkeWrzCzM1ONIYWYfmFmyyPHZYGZHRy1LubvshliGmVmG6L2fWnUupGR3/UqMxvZjDHdGhXPSjP7PGpdto7T3WZWbWZvx1lvZnZbJOYqM/tu1LqsHKcmc/e8fQGHA4cBC4GyOGV2A94FDgVKgCVA78i6GcCwyPs7gTEZiGkyMC7yfhzwu0bK7w18BrSLfJ4O/DDDxympmIAv4yzP+HFKNi6gF9Az8v4A4CNgr0weq0TfkagyVwB3Rt4PAx6OvO8dKd8G6B6pZ7dmiunUqO/NmLqYEv0umyGmUcCf4nzP10R+doq879QcMdUrfzVwdzaPU6TefwW+C7wdZ/1gYB5gwAnAq9k8Tqm88vrK393fcfcVjRQ7Dljt7mvcfRvwEDDEzAw4DZgZKXcPcG4GwhoSqSvZOn8IzHP3LRnYd6Zi+loWj1NScbn7SndfFXn/D6AayPRcdzG/IwlinQmcHjk2Q4CH3P0rd38PWB2pL+sxufvzUd+bV4ADM7DftGJK4Exgvrt/5u4bgfnAwBzEdAHwYAb2m5C7/41wURfPEOBeD14B9jKz/cnecWqyvE7+SfoW8EHU53WRZZ2Bz919R73l6drX3T+KvP8Y2LeR8sNo+GX8beRPwVvNrE0zxtTWzBab2St1zVBk7zg1JS4AzOw4wtXdu1GLM3Gs4n1HYpaJHItNhGOTzLbZiinaJYQryTqxfpfNFdMPIr+TmWZ2UBO3zVZMRJrFugPPRS3OxnFKRry4s3Wcmiznc/ia2bPAfjFWTXD3x5s7HkgcU/QHd3czi9tdKnKmPwp4OmrxeEIiLCF0A/t34MZmiulgd//QzA4FnjOzpYQkl7IMH6v7gJHuXhtZnNKxamnMbDhQBpwStbjB79Ld341dQ0Y9ATzo7l+Z2U8Jfy2d1gz7TcYwYKa774xalqvjlPdynvzdvX+aVXwIHBT1+cDIsk8Jf2q1jlzJ1S1PKyYzW29m+7v7R5GEVZ2gqvOAx9x9e1TddVfCX5nZn4GxzRWTu38Y+bnGzBYCxwCzSPE4ZSouM9sTeIpwwn8lqu6UjlUM8b4jscqsM7PWQEfCdyiZbbMVE2bWn3AiPcXdv6pbHud3mW5SazQmd/806uN/Ee7r1G3br962C9OMJ6mYogwDroxekKXjlIx4cWfrODVZS2j2qQR6WuixUkL4AszxcHfleUKbO8BIIBN/ScyJ1JVMnQ3aHyNJsK6t/VwgZm+BTMdkZp3qmk3MbB/gJGB5Fo9TsnGVAI8R2kdn1luXqWMV8zuSINYfAs9Fjs0cYJiF3kDdgZ7AaynG0aSYzOwY4C7gHHevjloe83fZTDHtH/XxHOCdyPungTMisXUCzmDXv3izFlMkrm8TbqC+HLUsW8cpGXOAiyK9fk4ANkUuZrJ1nJouF3eZk30B5YQ2sa+A9cDTkeUHAHOjyg0GVhLO6BOilh9K+I+6GngEaJOBmDoDC4BVwLPA3pHlZcB/RZU7hHCWb1Vv++eApYREdj/QvjliAv5PZL9LIj8vyeZxakJcw4HtwFtRr+9k+ljF+o4QmpDOibxvG/m3r44ci0Ojtp0Q2W4FMCiD3+/GYno28r2vOy5zGvtdNkNMk4BlkX0/D3w7atufRI7fauDi5oop8nkicHO97bJ5nB4k9EzbTshRlwCXA5dH1htwRyTmpUT1VszWcWrqS0/4iogUoZbQ7CMiIk2k5C8iUoSU/EVEipCSv4hIEVLyFxEpQkr+IiJFSMlfRKQIKfmLiBSh/w8UlzrbkIY+IwAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d82ff3128>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "131\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80cb7828>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "132\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'O', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d34da0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "133\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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IHNKVfzSaM8fVtQmmsqW1brvp0917T30bay0bNmzw1tcZOXIk06dPD76+joi0awr/aFNYGDD4XwR+C3yKm9RkPvDt2pWeE8DhQYOYV1JCXl4eFRUV3H777ZSUlNC7t79CqyISrxT+0WbWrPoFzDyWA78EXsJNoHCgwRZQc+wYa3NyePemm3j88ccZPXo0CQnq2RORhlTeIZqUlkL//g3794ErgCmeV2Nsp06YPXtU8EwkTgVb3kGXhdFk/ny/i6uBIqAMGIirmf1ToOHfB2ASEgLuR0SklsI/mhQX+73q/wyoBBYC64DNwCZgpr99lJe70sciIo1Q+EeTI0f8Lk7y/PuvQE+gO/ALYEmg/Rw6FOqWiUg7o/CPJgFq4afgunrqPnfb6DO4KSmha5OItEsK/2gybBgEKJM8GfgzUAocAv4EfMffhklJbpYrEZFGKPyjSW5uwFW/BjKBwUAaMBz4lb8NrW10PyIioPCPKjXdu7P9nHOo9rOuI/AkcBg4CDwGNPgbwRg3obmGeYpIExT+UWL//v380z/9Ew+fcgomKanpD/iTlOSKvImINEHhHwVee+01LrnkEr797W/zZGEhCQ8/DMnJzdtJcjLMng0ZTT7bISKi8g6RdPz4ce655x7y8/NZuHAho0aNcis8xdmYPt2N22/sKWxj3BX/7NknPyci0gRd+UfItm3buOyyy9i7dy+bNm06Gfy1pk2DNWtg0iQ3Asi3KygpyS2fNMltp+AXkWbQlX+YWWuZO3cu9957LzNnzmTq1KmBZ87KyIBFi6CszJVsKClxD3ClpLjhnLm5urkrIi2i8A+jw4cPc9ddd7FlyxZWr17N+eefH9wHU1Nhxoy2bZyIxBV1+4TJO++8w/DhwznjjDPYsGFD8MEvItIGdOXfxqqrq3nooYd49NFHeeqpp7juuusi3SQREYV/W9q3bx+33norNTU1bNy4kT59+kS6SSIigLp92syrr75Keno6V155JStWrFDwi0hU0ZV/iFVUVHDPPfewePFiFi1axMiRIyPdJBGRBnTlH0Jbt27l0ksv5cCBA2zatEnBLyJRS1f+vkpL3Zj64mI3uUq3bq7U8uTJAcfUW2vJy8vj3nvvZdasWdxxxx2Bx+6LiEQBhX+twkKYNQsKCtz7utMpvvwyPPAA5OS4wmmZmd5Vhw8fZurUqWzbto21a9cydOjQMDdcRKT51O0DMGcOZGVBfr4Lfd95dMvL3bL8fLfdnDkAvP3221x88cWceeaZbNiwQcEvIjFDV/5z5rgCaseONb2ttXDsGHb6dAqWLGHyhg385S9/4Zprrmn7doqIhFB8X/kXFvoN/t3ARNzcuWcBPwWq6qw3x44xdskSSubNU/CLSEyK7/CfNct16fj4CdADOABsBtbgZtGqq5O19MjLa/Mmioi0hZCEvzFmgjFmuzFmlzHmXj/rOxljXvKsX2+MGRCK722V0lJ3c9dPrfyPgX/GTZN4FjAB2OKzjbEWlixxFTdFRGJMq8PfGNMBeALIAYYCNxtjfO98TgEOWWsHAn8CHmrt97ba/PkBV/0ceBE4BuwDCnAngAaMaXQ/IiLRKhRX/iOAXdbaj6y1J3C5ea3PNtcCCzw/LwSyTaQHwhcXNxzV4zEad6V/GtAHyAD8lmMrL3c19kVEYkwowr83sKfO+72eZX63sdZWAUeAM0Lw3S135IjfxTW4q/zvAUeBz4FDwC8D7efQoTZonIhI24qqG77GmKnGmCJjTFFZW/eld+vmd/GXwKe4ET6dcGeoycCSQPtJSWmDxomItK1QhP8+oG+d9308y/xuY4xJBLoBX/juyFr7tLU2w1qbkdrW0xMOG+bmwPXRHTgbmIMb3nkY1181zN8+kpLcdIoiIjEmFOFfCAwyxpxtjDkFuAlY7LPNYuA2z883ACut9TPMJpxycwOuehlYCqQCA4GOuLvUDVjb6H5ERKJVq5/wtdZWGWN+CiwDOgBzrbVbjDH/CRRZaxcDecBzxphduJ6Vm1r7va3Wo4er1ZOf32C458XA6qY+bwxMnKgJ1EUkJplIX4AHkpGRYYuKitr2SwoLXa2eYEo7+EpOhjVrICMj5M0SEWkpY8xGa22TwRRVN3zDLjMTZs92Qd4cycnucwp+EYlRKuw2bZr7d/p0N26/sb+EjHE3eWfPPvk5EZEYFN9X/rWmTXNdOJMmuRFASUn1Vld17OiWT5rktlPwi0iM05V/rYwMWLTI1eqZP989uXvoENs++4wSY7jxtdd0c1dE2g2Fv6/UVJgxw/v2yPr1/Nedd3Kjgl9E2hF1+zThoosuYseOHRxryYggEZEopfBvQufOnUlLS2Pz5s2RboqISMgo/IOQmZlJYWFhpJshIhIyCv8gjBgxQuEvIu2Kwj8ImZmZbNiwIdLNEBEJGYV/ENLS0ti/fz+HDx+OdFNEREJC4R+ExMREhg8fTpvXGhIRCRON8w/SleefT8LDD7sHwI4ccZPBDBsGkyfr4S8RiTnxXdUzGIWFMGsW1a+9RlV1NZ1qak6uS0pytYBycuC++1yhOBGRCFJVz1CYM8eVfM7Pp0NlZf3gB1cIrqLCzQmQleW2FxGJAer2CWTOHFfpM5gne611202f7t6r8JuIRDld+ftTWNgg+Lv6vDoA/+r7udoTQDR0V4mINELh78+sWa5Lp45v6rwOAknAjf4+W17uPi8iEsUU/r5KS6GgoNFJXRYBPYBv+1tpLSxZ4kpDi4hEKYW/r/nzm9xkAfAjwATawJig9iMiEikKf1/FxW4ETwCfAGuA2xrbR3m5mwxGRCRKKfx9HTnS6OrngFHA2U3t59ChEDVIRCT0FP6+unVrdPWzNHHVXyslJRStERFpEwp/X8OGucna/Xgb2EeAUT51JSXBhReGuGEiIqGj8PeVmxtw1QLge8CpTe3D2kb3IyISaQp/Xz16uFo9puFYnqdwff6NqQbe79+frzp1aovWiYiEhMLfn/vuc103LWCSklg0aBCDBw/m8ccfp7KyMsSNExFpPYW/P5mZMHs2JCc373PJySQ8/DAPvPoqy5Yt47XXXuP8889n0aJFRGv1VBGJTwr/QKZNO3kC8NMFVI8xbrvZs71F3S666CKWLl3KE088we9+9ztGjhzJ22+/HYaGi4g0TeHfmGnTYM0amDTJjQDy7QpKSnLLJ01y2/mp5jl+/Hjeffdd7rrrLm666Sauv/56duzYEaZfQETEP03mEqyyMleyoaTEPcCVkuKGc+bmBj2TV3l5OY899hizZ8/m+9//Pvfffz89evRo02aLSHwJdjIXhX8EfP7558ycOZO//vWv3H333dx9990kN/f+goiIH5rJK4p1796dRx55hPXr11NcXMzgwYOZO3cu1dXVkW6aiMQJhX8EnXvuubz00kssWrSIefPmcfHFF1NQUKCRQSLS5hT+UeDSSy9l7dq1zJw5k7vvvtt7k1hEpK0o/KOEMYZrr72WkpISbrjhBq6++mpuvfVWPvnkk0g3TUTaoVaFvzHmW8aY5caYnZ5//ZayNMZUG2M2e16LW/Od7V3Hjh2566672LFjB+eccw6XXHIJ99xzD4cPH45000SkHWntlf+9wApr7SBghee9P+XW2os9r2ta+Z1x4dRTT+W3v/0tJSUlHD58mMGDB/OnP/2J48ePR7ppItIOtDb8r8UVu8Tz73Wt3J/46NWrF08//TSrVq1i5cqVpKWl8eKLLwZ/U7i0FH7/e7jlFvjud92/v/+95hgWiXOtGudvjDlsrT3d87MBDtW+99muCtgMVAEPWmvzm9p3ex7n3xqrVq1ixowZJCQkMHv2bEaPHu1/w8JCmDXLTUYP9aemTEpyZadzclwRu8zMtm+4iIRFyB7yMsa8AZzlZ9WvgAV1w94Yc8ha26Df3xjT21q7zxhzDrASyLbWfuhnu6nAVIB+/fql62anfzU1Nbz00kv8+7//OxdeeCEPPfQQaWlpJzeYMwemT3dzCTf2v68x7kRQpyaRiMS2kD3kZa0dZ629wM/r78Bnxpieni/sCZQG2Mc+z78fAauB4QG2e9pam2GtzUgNsmRCPEpISODmm29m27ZtZGVlMWbMGO68804OHjx4MviPHfMGfxbQGejqeZ1XuyNr3XbTp7vPiUjcaG2f/2JOTml7G/B33w2MMSnGmE6en7sDI4EPWvm9AnTq1Ilf/OIXbN++ndNOO41bzjuPE//2by7QfTwOfON5bfddWXsCUDebSNxobfg/CIw3xuwExnneY4zJMMY849kmDSgyxrwHrML1+Sv8QyglJYU//OEP/P2yy0hs6eQx5eXuHoGIxAUVdmsvSkuhf//6N3Y9soAtgMV1+fyXZ1kDnTvDp58GXaVURKKPCrvFm/nzA656CPgI2Ie7m/5doMHddnA3gBvZj4i0Hwr/9qK42O9VP8ClwKlAJ9yNmZHAEn8blpe7+QpEpN1T+LcXR44EvanBdQH5dehQKFojIlFO4d9edOvmd/FhYBlQgXvC7nlgLTAhwG7KqqupqalpixaKSBRR+LcXw4a5G7Y+KoH/AFKB7sCfgXxgsJ9dnEhMZMG773LmmWfywx/+kOeee47PPvusLVstIhGi0T7tRSOjfYLmGe2zp6KCpUuXsnTpUlasWMHAgQOZMGECEyZM4LLLLiMxMTF07RaRkNJon3jTo4er1WNMyz5vDEycCKmp9O3blx//+McsWrSIsrIy/vjHP1JTU8PPfvYzUlNTufHGG8nLy2Pv3r2h/R1EJGx05d+eFBZCVpbfJ3yblJwMa9ZARuMXDAcPHmTZsmUsXbqUf/zjH/Tu3dv7V8HIkSPp1KlTy9ouIiERssJukaLwb6G6tX2ClZzcouJu1dXVFBYWeruItm7dSlZWlvdkcPbZZzez8SLSWgr/eBahqp5ffPEF//jHP1i6dCnLli2jW7du5OTkMGHCBMaMGUNSUlKrv0NEGqfwj3dFRa5Wz5IlLuTLy0+uq63nP3Giq+ffRFdPS9TU1PDee+9RUFDA0qVL2bRpEyNHjvSeDAYPHoxp6f0JEQlI4S9OWZkr2VBS4h7gSkmBCy+E3Nyw1vA5cuQIK1as8J4MEhMTvSeCsWPH0rVr17C1RaQ9U/hL1LLW8sEHH3hPBOvXr2fEiBHeewUXXHCB/ioQaSGFv8SMb775htWrV1NQUEBBQQEnTpzwngjGjRvH6ac3mBlURAJQ+EtMstaya9culi5dSkFBAW+++SbDhg3zdhENHz6chIQ2fjyltNR1lRUXu5pJ3bq5J6gnT1a5a4l6Cn9pF8rLy1m3bp33ZPDFF19w1VVXkZOTw/jx4wnpdJ+a9F7aAYW/tEu7d+/2PmS2atUqBg8ezIQJE8jJyWHEiBF06NChZTvWpPfSTij8pd07ceIEb7/9tvchsz179jBu3DhycnK46qqr6NmzZ3A7CuODcSJtTeEvcWf//v3evwqWL19Ov379vH8VXHHFFXTs2LHhhwKUxLgFWAEcBc4C7gHu8P1skCUxRMJJ4S9xraqqig0bNnjvFezcuZMrr7zSO4qof//+bsPvfQ/y8xt09WwBBuJmP9uGm/P4dSC97kbGwKRJsGhR2/9CIkFS+IvUUVpayvLly72lJ7p3784No0fzwNy5dKisbPSz23Hh/yjwz74rNem9RBmVdBapo0ePHt4Jag4ePMizzz7L6I8/prKqKuBnfgIkA0OAnsBEfxtp0nuJUZqVQ+JOQkICGRkZ7mq9kb98n8TNfPYOsBrXBdSAJr2XGKUrf4lfQUx63wEYBewF5gTaSJPeSwzSlb/ErwCT3vtTBXwYYN36HTsofPxx0tLSGDJkCL169VJtIol6Cn+JX8OGuZE6PvMelwIrge8AScAbwAuel6/qU07hxJAhvP/++/ztb39j27ZtVFRUMGTIEIYMGUJaWpr3pHDuuedq/mOJGhrtI/ErwKT3ZcANwHtADdAf+BnwY3/78DPa58svv2Tr1q1s27aNrVu3en/ev38/55xzToOTwpAhQ+jSpUtb/ZYSZzTUUyQYAcb5B6WZ4/zLy8vZsWNHg5PCzp07SU1NrXdSqD0xpKamqgtJmkXhLxKMMEx635Tq6mp2797d4K+FrVu3kpCQ4D0R1D0pDBgwoO2rm0pYyubXAAAHCklEQVRMUviLBCtKa/tYayktLfXbhfT5558zePDgBn8tDBo0iM6dO7dZmyT6KfxFmiPGqnp+/fXXbN++vcFfCh9//DF9+vTx+9dCSkpKxNrbIppXoUUU/iLNFeFJ70OhsrKSDz/80O9fC126dGlwUkhLS6N3797RdV9B8yq0isJfpKWiZNL7ULLWsm/fPr/3FY4ePeo9IdQ9MZx77rn+K6G2pRj7CywaKfxFJCiHDh3ynhDqnhj27t3L2Wef3eCkcN5553HqqaeGviFReu8l1ij8RaRVKioq2LlzZ4OTwo4dOzjjjDPq3U+o/blHjx4t60LyM+rqcWA+UALc7PnZL82rUI/CX0TaRHV1NZ9++mm9+wm1P9fU1Pg9KQwYMKDxKTb9PG/xMq742DKgnEbCX/Mq1BOW8DfG3Aj8BkgDRlhr/aa1MWYCrhx6B+AZa+2DTe1b4S8SW6y1fP75535PCqWlpQwaNKjBSWHw4MEkff213yeta/0HrrDe/Ma+XPMqeAUb/q0tNPI+8D3gqUYa0gF4AhiP+9+w0Biz2Fr7QSu/W0SiiDGG1NRUUlNTGT16dL1133zzDTt27PCeDBYuXMjWrVv58MMPeSA5mV+cOOG/ZHbwX+5u0s+Y0Zq9xJVWhb+1divQVB/fCGCXtfYjz7YvAtcCCn+RONG1a1cuueQSLrnkknrLKysrKb/+ejq9+mrrvkDzKjRbOJ4P7w3sqfN+r2eZiMS5jh07clqo7jtqXoVmafLK3xjzBnCWn1W/stb+PZSNMcZMBaYC9OvXL5S7FpFo1Yx5FRoVa08wR1iT4W+tHdfK79gH9K3zvo9nmb/vehp4GtwN31Z+r4jEggDzKlR5XtWeVwUusPyGVlKSexBPghaObp9CYJAx5mxjzCnATcDiMHyviMSC3Fy/i2fiJtN5EPir5+eZgfZhbcD9iH+tCn9jzCRjzF7gcuB1Y8wyz/JexpglANbaKuCnuOG6W4H/b63d0rpmi0i70aOHq9XjM3DkN4D1ef3G3+eNcTWXNMyzWfSQl4hEXhTMq9BeBDvOX7NBiEjkZWa6Gj3Jyc37XG1tHwV/s2k2aRGJDrXF2VTVMyx05S8i0WPaNNeFM2mSK9mQlFR/fVKSWz5pkttOwd9iuvIXkeiSkeGGfrbDeRWiicJfRKJTaqpq9bQhdfuIiMQhhb+ISBxS+IuIxCGFv4hIHFL4i4jEIYW/iEgcUviLiMQhhb+ISByK2qqexpgy4JMmNusOfB6G5sQKHY/6dDxO0rGorz0fj/7W2iYfgY7a8A+GMaYomNKl8ULHoz4dj5N0LOrT8VC3j4hIXFL4i4jEoVgP/6cj3YAoo+NRn47HSToW9cX98YjpPn8REWmZWL/yFxGRFoip8DfGfMsYs9wYs9Pzb4qfbS42xrxjjNlijCk2xnw/Em0Nh2COh2e7pcaYw8aY18LdxrZmjJlgjNlujNlljLnXz/pOxpiXPOvXG2MGhL+V4RPE8RhtjHnXGFNljLkhEm0MpyCOxy+MMR94smKFMaZ/JNoZCTEV/sC9wApr7SBghee9r2PAj6y15wMTgEeMMaeHsY3hFMzxAPgDcGvYWhUmxpgOwBNADjAUuNkYM9RnsynAIWvtQOBPwEPhbWX4BHk8PgVygf8Jb+vCL8jjsQnIsNYOAxYCvw9vKyMn1sL/WmCB5+cFwHW+G1hrd1hrd3p+3g+UAu11zrcmjweAtXYF8HW4GhVGI4Bd1tqPrLUngBdxx6SuusdoIZBtjDFhbGM4NXk8rLW7rbXFQE0kGhhmwRyPVdbaY563/wv0CXMbIybWwv9Ma+0Bz88HgTMb29gYMwI4BfiwrRsWIc06Hu1Qb2BPnfd7Pcv8bmOtrQKOAGeEpXXhF8zxiCfNPR5TgII2bVEUibo5fI0xbwBn+Vn1q7pvrLXWGBNwqJIxpifwHHCbtTZmr3JCdTxEJDBjzC1ABjAm0m0Jl6gLf2vtuEDrjDGfGWN6WmsPeMK9NMB2pwGvA7+y1v5vGzU1LEJxPNqxfUDfOu/7eJb522avMSYR6AZ8EZ7mhV0wxyOeBHU8jDHjcBdTY6y1x8PUtoiLtW6fxcBtnp9vA/7uu4Ex5hTgFeBZa+3CMLYtEpo8Hu1cITDIGHO253/3m3DHpK66x+gGYKVtvw+3BHM84kmTx8MYMxx4CrjGWhtfF0/W2ph54fpqVwA7gTeAb3mWZwDPeH6+BagENtd5XRzptkfqeHjerwPKgHJcv+dVkW57CI/BRGAH7r7OrzzL/hP3HzNAZ+BvwC5gA3BOpNsc4eOR6fn/wFHcX0BbIt3mCB+PN4DP6mTF4ki3OVwvPeErIhKHYq3bR0REQkDhLyIShxT+IiJxSOEvIhKHFP4iInFI4S8iEocU/iIicUjhLyISh/4PIpfL5wOYR8MAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80df4ba8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "134\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80df35f8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "135\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80ec8eb8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "136\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80effef0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "137\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e7af28>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "138\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e4afd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "139\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d93978>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "140\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c3a240>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "141\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'S', 9: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e64978>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "142\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'S', 9: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f624a8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "143\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'S', 9: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d9e208>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "144\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'S', 9: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e45e48>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "145\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f18c18>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "146\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80ed0e48>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "147\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80dced30>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "148\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d05198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "149\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80dea080>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "150\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d62320>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "151\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e13f28>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "152\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1dc46b7908>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "153\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d65e48>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "154\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f7c1d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "155\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80dfaef0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "156\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e19470>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "157\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80dbea20>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "158\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80ebf940>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "159\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f1b400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "160\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c54a20>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "161\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d79a90>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "162\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d99cc0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "163\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f87da0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "164\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'O', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d9da90>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "165\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d75470>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "166\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e5d160>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "167\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'S', 10: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80dc7c88>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "168\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'S', 10: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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AcAPbaOAbiRq28RpFkj1pl3dw992EX6BPA28AD7v7a2Y22czOjjX7BaGkyn+Z2ctmtiDd922VZm77T1ku7q4VSXKwUkfo5jmXUJriI8LR/9XJ1tNGaxRJdmWkz9/dF9KgDI27Xx/3fFgm3idtsdv+G3b97I49GpYBSLhxiotDd4xItiU5WNkA/J1wxNU59hgLTARuTbSADlYkgcIq7JagvDDATUAxcDPw+9jzm5Ktwz3pekQyqqwMiooaTT6IMILaLMJBy8eEMtsJh2zRwYokUVjJv75McYOa9jdAoyIwNyRaPgtlikWSauIg41HgKcK4BF8A9gfuSNRQByuSRGElf2i7ZYql8CQ5WAE4GlhK6Ov/CHgYaFTAWQcr0oTCS/71ZYpLSlq2XNRliqUw6WBFsqTwkj+Em6vqdwDNDWtotjfxV1TkJj6Req08WNlmxke6MVCaUJjJH0IiX7YMRo4MJ9UaHl0VF4fpI0eGdkr8EpXYwcqezp3Z01zb2MHKX771LQbfey/vvPNODgKUtsg8wa3j+aC8vNyXL1+emzfT3bWS5+rq6rj4yCO5pbSUftXVKZUCueuuu7jtttt47rnn6N+/f2SxS26Z2Uvu3uxPPg3jCLq7VvLegw8+yJrSUvq+8AJ89FFKByuXX345AKeccop2ANKIkr9IntuxYwcTJ07kt7/9LWbWooMV7QAkGSV/kTx3991388UvfpGhQ4e2anntACQRJX+RPLZ582amTp3K4sWL01qPdgDSkJK/SB77xS9+wZlnnklZWcLiDS2iHYDEU/IXyVNr165l5syZrFixImPr1A5A6in5i+SpG2+8kbFjx2Z8VDvtAASU/EXy0qpVq5g3bx6rVq3Kyvq1AxAlf5Go1NSE6/Wrq8PALaWloYzz2LFcc801jBs3jh49emTt7bUDKGxK/iK5VlUF06fDokXhdfzgQo8+St111/GDDh045corsx6KdgCFS8lfJJdmzYJx40JphkSlVWpr6QD8mxkdzjwzJwUFtQMoTIVb2E0k1+oT/7Ztnyb+HcD3gUOAzxDq9C8COriHduPGheWy7PLLL+eqq67ilFNOUTG4AqEjf5FcqKram/jj7AYOBpYBnycMhP1tYCXQH/buAAYPznp55iuuuALQL4BCoSN/kVyYPn3fKpwxXQhDhvYn/Gc8izA+70vxjWprw/I5cMUVV+gXQIHQkb9IttXUhJO7KZRP/xB4EzgqfqI7LFwYSo/noMS4fgEUBh35i2TbnDkpNdsFXAiMBo5oONMs5fVkgn4BtH868hfJturqfS/nTKAOuBjoBNyVqEFtbajfn0P6BdC+ZeTI38zONLNVZrbGzCYkmN/ZzB6Kzf+LmfXPxPuKtAmbNjU52wlX/HwIzAP2T9Zw48aMhpUK/QJov9I+8jezjsCvgdOB94AqM1vg7q/HNfs+sNHdv2Bmo4BbgO+k+94ibUJpaZOzK4A3gGeB4qYadu+euZhaQL8A2qdMHPkfB6xx97+5+07gQeCcBm3OAebGnj8CnGZmloH3Fsl/ZWVQVJRw1rvA3cDLwGeBrrHHfzZsWFwchmqMiH4BtD+Z6PPvC/wj7vV7wFeTtXH33Wa2CTgQ+CgD7y+S38aMgUmTEs46hNDt0yz3sJ4INfkLoIk6Rbm4QklaLq9O+JrZpcClQMbL2IpEplcvGD4c5s9P6XLPRsxgxIi8SKKNdgDr1jVZp4hJk8K/vbIy3KgmeSMTyf99wk2K9frFpiVq856Z7QeUAusbrsjdZwOzAcrLy1vxv0QkT1VWwtNPN7rDNyXFxWH5PFG/A/jNsccyZds2OuzYkbROERB2ek8/nZM6RZK6TPT5VwGHmdmhZtYJGAUsaNBmAeHyZYDzgD+6t+YQSKSNGjw4JL+SkpYtV1ISlstyaYeWumK//bhhyxY6bN/+aeJ/AziVcGT3BeCx+sY5rlMkqUk7+bv7buBy4GnC5/+wu79mZpPN7OxYs3uBA81sDXAV0OhyUJF2r6Ji7w6guesdzPYm/nw7Wo7VKdp/165PJ+0mXNVxFrCB8PP9IsLdyp+q3wEsX57DYCUZy9cD8PLycl+uL4m0R8uXh37yhQtDko+v+VNcHI6UR4wIXT15dsQPwLnnNjp/8SrwNWALUL9bO4Nw5ceU+GXNYORImDcvR8EWHjN7yd2b/eLk1QlfkYJQXh6S37p14QqZlSvDDVzdu4fLOceMyYuTuwm1oE6RE3YK+07MbZ0iSU7JXyQqPXvC+PFRR9EySeoLHQ70An4B/BR4jlCm+pREjevrFLW1f3s7o8JuIpK6JHWK9gfmA08Sbla7jTAuQb9E64igTpE0piN/EUldE3WKyghH+/X+lb2X+DUSQZ0i2ZeO/EUkdU3UKaoGtgPbgBnAWmBMssYR1SmSvZT8RSR1TdQp+h3Qh9D3vwRYDHRO1DDiOkUSKPmLSOqaqC/0C2AjsJUwCP0XkjXMgzpFouQvIi1RX6eotUV586hOUaFT8heRlqmsDF03rZFndYoKmZK/iLRMK+sU1RUX52WdokKl5C8iLdfCOkW79t+fGZ/9LLt+8IPcxCfNUvIXkdapqIBly0KtnqKixl1BxcVh+siRdPyf/+G5ww/nhhtuiCRUaUw3eYlI66VYp6gDMHfuXI455hhOPfVUTjvttIgDFyV/EUlfCnWKevXqxdy5c/nud7/LihUr6NWrV46Ck0TU7SMiOTNs2DBGjx7NmDFjqKurizqcgqbkLyI5deONN7Jx40buuOOOqEMpaOr2EZGc2n///XnggQc47rjjOPnkkxmsgd0joSN/Ecm5/v37M3PmTM4//3w2b94cdTgFSclfRCJx3nnnMWzYMCoqKsjX4WTbMyV/EYnMHXfcwSuvvMLcuXOjDqXgKPmLSGSKi4t56KGHGD9+PH/961+jDqegKPmLSKSOOuoopk6dyqhRo9ieYIhIyQ4lfxGJ3CWXXMLAgQMZr0Hdc0bJX0QiZ2bMnj2bJ554gscffzzqcApCWsnfzHqY2WIzWx3722hgTjM72sz+bGavmVm1mX0nnfcUkfapW7du/OEPf+DSSy/lH//4R9ThtHvpHvlPAJa4+2GEYTsnJGizDfiuux8FnAn8u5l1S/N9RaQdOv7447nyyiu58MIL2b17d9ThtGvpJv9zgPprtOYC32jYwN3fdPfVsef/BGoAjeEmIgldffXVdO7cmZtuuinqUNq1dJN/b3dfG3v+AdC7qcZmdhzQCXgryfxLzWy5mS1ft25dmqGJSFvUoUMH7r//fu6++26WLVsWdTjtVrPJ38yeNbNXEzzOiW/n4Ra9pLfpmVkf4HfAWHdPWM7P3We7e7m7l/fUAM8iBatPnz7cd999XHTRRaxfvz7qcNqlZgu7ufuwZPPM7EMz6+Pua2PJvSZJuwOAJ4Fr3f2FVkcrIgXjzDPPZNSoUYwdO5bHH38ca264SGmRdLt9FgCjY89HA42u0TKzTsBjwP3u/kia7yciBWTq1Kl88MEH/OpXv4o6lHYn3eR/M3C6ma0GhsVeY2blZnZPrM23gZOBMWb2cuxxdJrvKyIFoFOnTjzwwANMmTKFFStWRB1Ou2L5Wk2vvLzcly9fHnUYIpIHHnjgAW644QZeeuklunbtGnU4ec3MXnL38mbbKfmLSFvwve99j7q6OubMmRMm1NSEQeOrq2HTJigthbIyGDs2jClcoJT8RaRd+eSTTzj22GO544ILGP7yy7BoUZgRXwyuuBjcYfhwqKyEAhwlLNXkr2EcRaRN6NKlC4u/+U0OnDQJN8MSHbjW1oa/8+fD00/DjBlQUZHbQNsIFXYTkbZh1iwO/vd/pwT2SfwPAl8EugD/AjwP4eh/2zYYNw5mzYoi2ryn5C8i+a+qKiTybdv2mbwYuBq4D9gC/B9gQHyD+h2AupAbUfIXkfw3ffreLp04k4Drga8Rklnf2GMftbVhedmHkr+I5LeamnByt0Ef/x5gObAO+ALQD7gcaLSLcIeFC0H1wvah5C8i+a3+0s4GPgR2AY8Q+vlfBlYACWuBmiVdT6FS8heR/FZdve/lnDHFsb9XAH2Ag4CrgIWJ1lFbCytXZivCNknJX0Ty26ZNCSd3J3T1xJd7a7L028aNmYupHVDyF5H8VlqadNZY4FeEcsIbgTuAs5I17t5olNmCpuQvIvmtrAyKihLOug4YDAwkXOt/DHBtoobFxTBoULYibJOU/EUkv40Zk3TW/sBM4GPCUIJ3Agl3E+5NrqcQKfmLSH7r1SvU6mntYC5mMGJEQRd7S0TJX0TyX2Vl6LppjeLisLzsQ8lfRPLf4MGhSFtJScuWKykJy5U3W+Sy4Cj5i0jbUFGxdwfQTBfQHsCLi1XVswlK/iLSdlRUwLJlMHJkuAKoYVdQcTEUFfFSv3785qKLlPiboMFcRKRtWrculGxYuTLcwNW9e7icc8wY3t22ja985StUV1fTt2+jUm/tmkbyEpGCNmHCBD788EPuu+++qEPJqVSTv7p9RKRdqqysZNGiRbz88stRh5KXlPxFpF0qLS1l0qRJ/OxnPyNfeziipOQvIu3WJZdcwtq1a3niiSeiDiXvpJX8zayHmS02s9Wxv0krJ5nZAWb2npndlc57ioikar/99mPGjBmMHz+eXbt2RR1OXkn3yH8CsMTdDwOWxF4nM4UwxKaISM4MHz6cgw8+mNmzZ0cdSl5JN/mfA8yNPZ8LfCNRIzM7FugNPJPm+4mItIiZcdtttzF58mQ+/vjjqMPJG+km/97uvjb2/ANCgt+HmXUAbgPGpfleIiKtUlZWxte//nWmTZsWdSh5o9nkb2bPmtmrCR7nxLfzcDo90Sn1y4CF7v5eCu91qZktN7Pl6zTYsohk0JQpU7j33nt5++23ow4lL6R1k5eZrQKGuvtaM+sDLHX3wxu0+U/gJKAO6Ap0Ama6e1PnB3STl4hk3JQpU3j11Vd56KGHog4la3J1k9cCYHTs+Wjg8YYN3P1Cd/+8u/cndP3c31ziFxHJhp/97Gf86U9/4s9//nPUoUQu3eR/M3C6ma0GhsVeY2blZnZPusGJiGRSSUkJN910E1dddVXB3/iVVvJ39/Xufpq7H+buw9x9Q2z6cnf/QYL2c9z98nTeU0QkHRdffDE7d+7k4YcfjjqUSOkOXxEpKB06dOC2225jwoQJbN++PepwIqPkLyIFZ+jQoXz5y1/mzjvvjDqUyCj5i0hBuvXWW7n11lsp1MvKlfxFpCANHDiQCy64gBtvvDHqUCKh5C8iBWvSpEk89NBDvPHGG1GHknNK/iJSsA488EAmTJjAz3/+86hDybn9og5ARCRKl19+OTNnzmTJkiWcNmhQGBe4uho2bYLSUigrg7FjoWfPqEPNKCV/ESlonTt3ZvYll8C55+I7d2IA8ZeAPvooTJoEw4dDZSUMHhxVqBmlbh8RKWyzZnHqlCkM3bwZ275938QPUFsbps2fD0OHwqxZkYSZaUr+IlK4Zs2CceOwbdvo2GDWaqAIuKh+gjts2wbjxrWLHYCSv4gUpqqqkMi3bUs4+0dAwg6e+h1AG686rOQvIoVp+vTQpZPAg0A34LRky9bWhuXbMCV/ESk8NTWwaFHoymlgM3A9cHtTy7vDwoXQhu8OVvIXkcIzZ07SWdcB3wf6NbcOsybXk+90qaeIFJ7q6sZX9QAvA88CK1JZR20trFyZ4cByR8lfRArPpk0JJy8F3gE+H3u9FdgDvA78v0QLbNyY8dByRclfRApPaWnCyZcCo+JezyDsDJJe2Nm9eyajyin1+YtI4Skrg6KiRpNLgM/GPboSrvVPWNihuBgGDcpikNml5C8ihWfMmJSa3QD8PtlM95TXk4+U/EWk8PTqFWr1mLVueTMYMaJNF3tT8heRwlRZGbpuWqO4OCzfhin5i0hhGjwYZsyAkpKWLVdSEpYrL89OXDmiq31EpHBVVIS/48aF6/YT3PFbbw9gxcV0mDFj73JtmI78RaSwVVTAsmUwcmS4AqhhV1BxMRQV8cbAgdx0+untIvFDmkf+ZtYDeAjoT7gc9tvu3uiuBzP7PHAPcDDgwAh3fyed9xYRyZjycpg3L9TqmTMn3Lm7cWO4jn/QIBgzhn77789dAwfyzdde46ijjoo64rSSNiZMAAALBklEQVSZN/Ezp9mFzW4FNrj7zWY2Aeju7lcnaLcUmOrui82sK1Dn7onrqMaUl5f78jZeMlVE2pfbb7+dpUuXsmDBgqhDScrMXnL3Zk9IpNvtcw4wN/Z8LvCNBIEcCezn7osB3H1rc4lfRCQf/ehHP6K6uprnn38+6lDSlm7y7+3ua2PPPwB6J2gzEPjYzB41sxVm9gszazhojohI3uvcuTM33XQTP//5z0mn1yQfNJv8zexZM3s1weOc+HYetkSirbEfcBIwjjAwzgBgTJL3utTMlpvZ8nVtuE62iLRfF1xwAbW1tTz22GNRh5KWZpO/uw9z9y8leDwOfGhmfQBif2sSrOI94GV3/5u77wbmA19J8l6z3b3c3ct7tuE750Sk/erQoQO33HILlZWV7Nq1K+pwWi3dbp8FwOjY89HA4wnaVAHdzKw+m59KqJAqItImnXHGGRx88MHce++9UYfSaukm/5uB081sNTAs9hozKzezewDcfQ+hy2eJma0EDPhNmu8rIhIZM+OWW25h8uTJbN26NepwWiWtSz2zSZd6iki+O//88znyyCO57rrrog7lU7m61FNEpGBNnTqVX/7yl9TUJDrdmd+U/EVEWmnAgAFceOGF3HTTTVGH0mJK/iIiaZg4cSJ/+MMfeOutt6IOpUWU/EVE0tCzZ0+uvPJKrr322qhDaRGVdBYRSdNPf/pTDjvsMKqqqhh8yCGhOFx1NWzaFAaLLyuDsWPzauQvJX8RkTR16dKFu0aPZvuIEfjWrRjA9u17Gzz6KEyaFIaOrKwMA8lETN0+IiLpmjWLkXfeyb9+9BG2ffu+iR/CQDHbt8P8+TB0KMyaFUmY8ZT8RUTSMWsWjBuHbdtGsxUr3WHbtjByWMQ7ACV/EZHWqqoKiXzbvlXqNwAjgS7AIcAfGi5XvwOI8EZWJX8RkdaaPj106TTwI6AT8CHwn0AF8FrDRrW1YfmIKPmLiLRGTQ0sWtRo0PdPgHnAFKArcCJwNvC7hsu7w8KFYejICCj5i4i0xpw5CSe/SbiMcmDctC+T4MgfwCzperJNyV9EpDWqqxtf1QNsBQ5oMK0U2JJoHbW1YbD4CCj5i4i0xqZNCSd3BTY3mLYZ+Eyy9WzcmLmYWkDJX0SkNUpLE04eCOwGVsdNewU4Ktl6unfPaFipUvIXEWmNsjIoKmo0uQtwLnA94eTv/yUMcXhxonUUF8OgQVkMMjklfxGR1hgzJumsmUAt0As4H5hFkiN/9ybXk01K/iIirdGrV6jVY9ZoVg9gPuHI/+/ABYmWN4MRIyIr9qbkLyLSWpWVoeumNYqLw/IRUfIXEWmtwYNhxgwoKWnZciUlYbnyZofazRqVdBYRSUdFRfg7bly4br/BHb/7MAtH/DNm7F0uIjryFxFJV0UFLFsGI0eGK4AadgUVF4fpI0eGdhEnftCRv4hIZpSXw7x5oVbPnDnhzt2NG8N1/IMGhat6NJKXiEg71bMnjB8fdRTNSqvbx8x6mNliM1sd+5vwVjUzu9XMXjOzN8zsTrME10aJiEjOpNvnPwFY4u6HAUtir/dhZv8KnACUAV8CBgND0nxfERFJQ7rJ/xxgbuz5XOAbCdo4UEQY26AzsD9hjAMREYlIusm/t7uvjT3/AOjdsIG7/xl4Dlgbezzt7m8kWpmZXWpmy81s+bqIBjgQESkEzZ7wNbNngc8mmHVt/At3dzNrdIGrmX0B+CLQLzZpsZmd5O7PN2zr7rOB2QDl5eVNXCwrIiLpaDb5u/uwZPPM7EMz6+Pua82sD1CToNlI4AV33xpbZhFwPNAo+YuISG6k2+2zABgdez6aULm0ob8DQ8xsPzPbn3CyN2G3j4iI5Ea6yf9m4HQzWw0Mi73GzMrN7J5Ym0eAt4CVhDENXnH3/07zfUVEJA3mTdWhiJCZrQPejeCtDwI+iuB9U6HYWi+f48vn2CC/48vn2CCa+A5x92ZvJc7b5B8VM1vu7tGV2muCYmu9fI4vn2OD/I4vn2OD/I5Phd1ERAqQkr+ISAFS8m9sdtQBNEGxtV4+x5fPsUF+x5fPsUEex6c+fxGRAqQjfxGRAlRwyd/MvhUrL11nZknPwpvZmWa2yszWmNmEuOmHmtlfYtMfMrNOGY6v2TLZZnaKmb0c99huZt+IzZtjZm/HzTs6l7HF2u2Je/8FcdPzYdsdbWZ/jn0Hqs3sO3HzMr7tkn2P4uZ3jm2LNbFt0z9uXmVs+ioz+7d0Y2lFbFeZ2eux7bTEzA6Jm5fwM85xfGPMbF1cHD+Imzc69j1YbWajGy6bg9juiIvrTTP7OG5e1rddSty9oB6EOkOHA0uB8iRtOhJuTBtAqEb6CnBkbN7DwKjY8/8AKjIc363AhNjzCcAtzbTvAWwASmKv5wDnZWnbpRQbsDXJ9Mi3HTAQOCz2/HOEYoPdsrHtmvoexbW5DPiP2PNRwEOx50fG2ncGDo2tp2OOYzsl7ntVUR9bU59xjuMbA9yVYNkewN9if7vHnnfPZWwN2l8B/DZX2y7VR8Ed+bv7G+6+qplmxwFr3P1v7r4TeBA4x8wMOJVw1zIkL2OdjlTKZMc7D1jk7tsyHEciLY3tU/my7dz9TXdfHXv+T0I9qmyNrZfwe9REzI8Ap8W21TnAg+6+w93fBtbE1pez2Nz9ubjv1QvsLc6YC6lsu2T+DVjs7hvcfSOwGDgzwtjOBx7I4PtnRMEl/xT1Bf4R9/q92LQDgY/dfXeD6ZnUbJnsBkbR+Is1NfZT/Q4z6xxBbEUWSnO/UN8dRR5uOzM7jnDk9lbc5Exuu2Tfo4RtYttmE2FbpbJstmOL931gUdzrRJ9xJqUa3zdjn9cjZnZwC5fNdmzEusoOBf4YNznb2y4l7XIMX2uiDLW7Jyo+l1NNxRf/wj1xmey49fQBBgFPx02uJCS+ToTLzK4GJuc4tkPc/X0zGwD80cxWEpJa2jK87X4HjHb3utjktLZde2VmFwHl7DsCX6PP2N3fSryGrPlv4AF332FmPyT8gjo1xzE0ZxTwiLvviZuWD9uufSZ/b6IMdYreBw6Oe90vNm090M3M9osdpdVPz1h8llqZ7HrfBh5z911x664/8t1hZvcB43Idm7u/H/v7NzNbChwDzCNPtp2ZHQA8STgYeCFu3WltuwSSfY8StXnPzPYDSgnfs1SWzXZsmNkwwo51iLvvqJ+e5DPOZAJrNj53Xx/38h7COZ/6ZYc2WHZpLmOLMwr4UfyEHGy7lKjbJ7Eq4DALV6d0InyACzycrXmO0M8OyctYpyOVMtn1GvUlxpJefR/7N4BXcxmbmXWv7y4xs4MI4ze/ni/bLvZ5Pgbc7+6PNJiX6W2X8HvURMznAX+MbasFwKjY1UCHAocBL6YZT4tiM7NjgLuBs929Jm56ws84g7GlGl+fuJdns7dU/NPAGbE4uwNnsO+v46zHFovvCMIJ5z/HTcvFtktN1Gecc/0gDC7zHrCDMJbw07HpnwMWxrUbAbxJ2CNfGzd9AOE/4Rrgv4DOGY7vQGAJsBp4FugRm14O3BPXrj/haKNDg+X/SCif/Srwe6BrLmMD/pW95btXAt/Pp20HXATsAl6OexydrW2X6HtE6Eo6O/a8KLYt1sS2zYC4Za+NLbcKGJ6F/wvNxfZs7P9I/XZa0NxnnOP4pgOvxeJ4DjgibtnvxbbpGmBsrmOLvb4BuLnBcjnZdqk8dIeviEgBUrePiEgBUvIXESlASv4iIgVIyV9EpAAp+YuIFCAlfxGRAqTkLyJSgJT8RUQK0P8HWheoqsB30bQAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e98c18>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "169\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'C', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80ed6e48>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "170\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'C', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c7e8d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "171\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'C', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d3afd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "172\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'C', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d2b4e0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "173\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d40278>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "174\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'C', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f444a8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "175\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'C', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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2TfwQJn5vboYlS0K5mpo4ohQROSBRJP9RwIak9xsT6zK5FFgewXmzp6YG5s6F7dvD3X173EO5uXP1BSAi3UZOH/ia2flAOXBbhu2zzazOzOoaGhpyGdpetbV7E3/CQSlLb+BLqfu1fgHEXVUlItIJUST/TcCYpPejE+v2YWanAtcAZ7l72vkR3f0udy939/LSuB6kzp8fqnSSvJe0bAGKgX9Jt29TU9hfRCTPRZH8a4HxZjbOzPoBM4GlyQXM7OPAnYTEn79jJdTXw/Ll7Vb1LAaGA59Mt9Edli2DuP5qERHppC4nf3dvAeYAjwKvAr9w97VmdoOZnZUodhuhxuSXZvaimS3NcLh4LVzYYZF7gQsBy1TArFPHERGJUyTt/N19GbAsZd21Sa9PjeI8Wbd6dWjBk8GfgRXAj9s7RlMTrFkTcWAiItFSD99kjY3tbr4P+AQwrqPjbNsWUUAiItmh5J9s8OB2N/8UuKgzxxkyJIpoRESyRsk/WVkZFBWl3fR7QhOmtK18khUXw8SJEQcmIhItJf9kVVUZN90LzAAGdnQM93aPIyKSD5T8kw0fHsbqsbZtee4k1Pm3ywymTdNgbyKS95T8U82bF6puDkRxcdhfRCTPKfmnqqiABQugpGT/9ispCfuVdziYnohI7CJp59/jVFeHn3Pnhnb77fT43QVYcTG9FizYu5+ISJ7TnX8m1dWwYgVUVoYWQKlVQcXFUFTE6xMm8KWJE/HLLosnThGRA6A7//aUl8PixWGsnoULQ8/dbdtCO/6JE6Gqin84+GCeO+EEfvKTn3DppZfGHbGISKd0eSavbMmLmbw6afXq1Zxyyim88MILjB6d//PUiEjPlcuZvApeWVkZc+bM4Ytf/CL5+mUqIpJMyT8i8+bNY+PGjdx///1xhyIi0iEl/4j069ePe+65h6997Wts3rw57nBERNql5B+hY489li984Qtcfvnlqv4Rkbym5B+xa6+9lnXr1vHggw/GHYqISEZK/hHr378/99xzD1dccQX19fk7Y6WIFDYl/yyYNGkSF154IXPmzIk7FBGRtCJJ/mZ2upm9ZmbrzezqNNv7m9mDie0rzWxsFOfNZ//2b//GSy+9xOLFi+MORUSkjS4nfzPrDdwOTAUmAOeZ2YSUYpcC29z9Q8B3gFu6et58V1xczD333MOcOXN4++234w5HRGQfUdz5TwLWu/ub7v4BsAiYnlJmOmE+FICHgFPM0gya38OcdNJJzJw5k6985StxhyIiso8okv8oYEPS+42JdWnLuHsL0AgMTT2Qmc02szozq2toaIggtPh961vfYuXKlSxdujTuUERE9sirB77ufpe7l7t7eWkPmQ2rpKSEH//4x1RXV7Nt27a4wxERAaJJ/puAMUnvRyfWpS1jZn2AwcBfIzh3t/CpT32KyspKvvrVr8YdiogIEE3yrwXGm9k4M+sHzARS6ziWAhclXp8NPOkF1gX25ptvZsWKFSxfvjzuUEREuj6ev7u3mNkc4FGgN/ATd19rZjcAde6+FPgxcJ+ZrQfeIXxBFJSDDjqIu+++m6qqKl5++WUGDx4M9fVhnoDVq6GxEQYPhrIyuPhiTQIvIlml8fxzbPbs2RzR0MA1ZtD6V0Bz894CxcVh2sipU8Nk8BUV8QQqIt1SZ8fz10xeOfbdo4+Gu+9mN9Ar3RdvU1P4uWQJPPpomBRecwOLSMSU/HOppoaSb36z3Qnh93CH7dvDJPKgLwARiVReNfXs0WprQyLfvn2f1a8CUwjNnz4E/Ffqfq1fAD2wCkxE4qPknyvz5++t0kloIXR9PoPwFPwu4HxgXeq+TU1hfxGRiCj550J9fXi4m1Ld87/AW8BXCc2kpgAnA/el7u8Oy5ZBD+n1LCLxU/LPhYULO13UgZfTbTDbr+OIiLRHyT8XVq/etzlnwoeB4cBtwE7gf4AVwPY2JQlVP2vWZDFIESkkSv650NiYdnVfYAnwG+Aw4NvAOYTxMdLS2EAiEhE19cyFwYMzbioj3O23Oom942C0MWRIdDGJSHZ0k577Sv65UFYGixenrfpZDRwF7AbuADYDVemOUVwMEydmMUgR6ZLa2tAqL13P/Ycfhuuuy6ue+6r2yYWqqoyb7gNGEOr+nwAeA/qnK+je7nFEJEY1NTB5cuiZ39zc9kavqSmsW7IklKupiSPKfSj558Lw4eEbP83kZbcB24D3gOWEjl6p3AymTcurPxlFJKGmZm8Hzo567yf33I/5C0DJP1fmzQtVNwegGVh/zjnRxiMiXZeh5/47QCUwADgC+FnqfnnQc1/JP1cqKsIgbSUl+7dfSQkvXXABJ86Zw333ten+JSJxStNzH+BfgX7AVuABoBpYm1oo5p77Sv65VF299wugo/nrzUK5BQs44d57efLJJ7npppuYPXs2zWkeHItIjmXouf8+sBi4ETgI+ARwFvnXc1/JP9eqq2HFCqishKKitlVBxcVhfWVlKJcYzXPixInU1dXR2NjISSedxBtvvBFD8CKyR4Ye9+sIzSiPSlr3MdLc+UOsPffV1DMO5eWh6WdDQ/iHX7MmdOAaMiQ056yqSvtwd+DAgSxatIjbb7+dE088kbvuuovPfvazOQ9fRMjYc/89YFDKusHA39MdI8ae+11K/mZ2CPAgMBb4E3COu29LKXMMUEO4HruAb7n7g105b49RWgpXXbVfu5gZc+bMoaKignPPPZdnn32Wf//3f6dv375ZClJE0srQc/8g4N2Ude8CAzMdJ6ae+12t9rkaeMLdxxOaqV+dpsx24EJ3/whwOvBdMzu4i+cteMcffzyrVq1i7dq1TJkyhU2bNsUdkkhhydBz/yjCcO2vJ617CfhIpuPE1HO/q8l/OnBv4vW9QJs6CHdf5+6vJ16/BdQDarAegaFDh/LrX/+a008/nYqKCh5//PG4QxIpHGVl4flcigHADOBawsPfZ4FfARekO0aMPfe7mvwPdffNiddbgEPbK2xmkwgtoPS0MiK9evXimmuu4f777+fCCy/kxhtvZPfu3XGHJdLzVVWRqUvXHUAToef+eYR677R3/jH23O8w+ZvZ42b2cpplenI5d3fIeC0wsxGE1k4Xu3va7GRms82szszqGjRxyX6ZMmUKdXV1PPbYY0ybNo2333477pBEerQ3/v53fj9oELvSbDuEMGLv+8BfgM+lO0DMPfc7TP7ufqq7fzTN8itgayKptyb3+nTHMLNBhJGLr3H359o5113uXu7u5aUaymC/jRw5kieffJKPfexjHHfccTz3XMZLLSIHaMeOHdx4440cf/zxvHnuufTa346brYqLQ8//mHS12mcpe0cgvohQtbUPM+tHmJf8p+7+UBfPJx3o06cPt9xyCz/4wQ8466yz+N73vod3NN6IiHRK681VXV0dq1at4oLvfx87wJ77LFgQmn3Hxd0PeAGGElr5vA48DhySWF8O3J14fT5hoqoXk5ZjOjr2cccd59I1b7zxhh977LF+9tlne2NjY9zhiHRbW7Zs8fPPP98PP/xwX7JkSdsCd9zhXlLibuYeavLTL2ah3B13ZC1WoM47kb+7dOfv7n9191PcfbyH6qF3Euvr3P3zidf3u3tfdz8maXmxK+eVzjnyyCN59tlnGTZsGOXl5axevTpz4fp6uPVWOP98OPPM8PPWWzVpvBS03bt3c+eddzJx4kRGjBjB2rVrmT59etuCB9hzP07meVolUF5e7nUxjnjX0zzwwANcccUV3HbbbVQlty5obwKK4uJwv5JHE1CI7JcuzKr14osvUl1dTa9evaipqaGsrKxz59zPnvtRM7NV7t5xfVJn/jyIY1G1T/TWrl3rRx99tF9yySW+ffv2vPpTVSRSf/yje2Wle1FRWJI/z8XFYV1lZSiX4t133/WvfvWrXlpa6v/5n//pu3btiuEXOHDkotpHupcJEyZQW1tLU1MT3x4/nt1XXtntJqAQ6dABzqrl7jz88MNMmDCBd955h7Vr1/L5z3+eXr16ZppUtU8B8j/+kZZPfpI7P/iAhcAaQkeUhUllniCMSf4X4PjEtiMgtFJYsSLeVgoimSTPqtVZJSW8ffXVVK1cyRtvvEFNTQ2TJ0/OWojZ1tlqn575lSbtsptvpu/OnYwEvgFckrL9bUL39BsJMxKVA+e2box5AgqRjNLMqrUDuJRw4zIQOIYwXeo+tm+n5NprmXH44bz00kvdOvHvDyX/QpM0AcUMwmBMQ1OKPEzoiv4vQBFwPWFgqv+F2CegEMkozaxaLcAYYAXQCNwEnEMYgjhZsRmXbN1Kv379chBoflDyLzSdmDhiLWHyiVYDgH8gaTKKGCegEEkrw6xaAwg3L2MJye4MYBywKmV3K8CbGiX/QpNhAopk7xEmn0i2z2QUMU5AIZJWJ29GthJm2ko7yFqB3dQo+ReaDBNQJOvUZBQxTUAhklYnbmp2ArMI49Acna5Agd3UKPkXmgwTUCT7CKGOv9X7hDG497lbimkCCpG0Orip2U0YT78f8MP2ChbQTY2Sf6FJmoCiBWgmzK25K/G6BagEXgYWJ9bdAJSx926puVcvanfs4N13U/8+EIlJOzc1Tmjxs5XwmW53wtMCuqlR8i80SUM73AQUAzcD9yde30SYZm0xcA0wBFgJLEo6RN/evfl+YyNjxozhnHPO4Ve/+hUffPBBbuIXSbF9+3Ze2L2bHRk6Y1UDrwL/TfiMZxTjrFpxUPIvNMOHh7F6zLiecFeUvFyfKHYqoWlnE/BbQmsJAMzofeaZ3PfII7z55puccsopfPvb32bkyJFcdtllPPPMM5pJTLKupaWFRx55hAsuuICRI0dy8+bN9Ondu025PwN3EoYSPozwPOsg4IF0B41xVq04KPkXonnz2o462FlJE1AMHTqUL37xizz99NOsWrWKI444gurqasaNG8e8efN4+eWXIwxaCp27s3LlSr785S8zevRorrvuOioqKnjttdd48Kmn6H3GGaHFTpIjCDc1zYRWbK3LrNSDxzyrVhw0vEOhOsBu8CxY0O5wtO7O6tWreeCBB/jZz37G0KFDmTVrFueddx5jxoyJIHApNOvWrdvzeTIzZs2axec+9znGjx+/b8Ha2jBWz/58plv1oGFLOju8g5J/IWv9Amhqan9wN7Nwx99B4k+1e/dunn76aR544AEefvhhysrKmDVrFmeffTYHH3xw1+PvwnC9EoEsXv8tW7awaNEiHnjgATZs2MDMmTOZNWsW5eXlWMrd/T6ydFPTnWhIZ+mc2lr3GTPCELfFxemHvp0xI5TrgubmZn/44Yd9xowZPmjQIK+srPSHHnrIm5qa9v9gXRiuVyKQpev/7rvv+r333uunnXaaH3zwwX7hhRf6o48+6jt37ty/+Ap8qHI6OaRz7Ek+06Lkn2P19e633up+wQXuZ5wRft56a1gfsW3btvndd9/tn/70p33IkCF+ySWX+BNPPOEtLS0d71zg/7FjF/H137Fjhy9dutTPPfdcHzRokJ955pm+aNEif//997sWZ45uavJRTpI/cAjwGGEO38eAIe2UHQRsBH7YmWMr+ReGDRs2+G233ebHHHOMjxo1yufOnesvvPCC7969u23h1sTTXtJJXfQFEJ12rv868P7gszpx/Xft2uXPPPOMX3bZZT5s2DA/+eST/Y477vCGhoboY87hTU2+6Gzy71Kdv5ndCrzj7jeb2dWJ5P/1DGW/R2hC/o67z+no2KrzLzyvvPLKngd7JSUlex7sjR07NuPDvD8BlwN/APoDZwPfBfokF+pBD/Ni08HD1H8iNAs+gtBnZB+J67+2uHjPv++AAQP2/feVyOTkga+ZvQZMdvfNZjYC+K27fzhNueOAq4BHgHIlf2mPu/P73/+e+++/n1/+8pccffTR/PS99xi3enUYfTHJNGA48CPgb8BpwBeALycXMgsTZy9enKPfYD90l4fWM2aEma/S5ItFhGHAJwDraZv8d5vx5MCBVA0cyHnnncesWbP42Mc+1v6DWzlgOXngC/wt6bUlv09a34vQT2g0UIWqfWQ/7Nixwx/56U99R69eaasbjgb/TdL7ueCz01X/FBXl15/63emh9datbWNMLI3g48E3gF+XrtonsbT06+ctmzfH/ZsUBKLzyxoBAAAKoElEQVSaw9fMHjezl9Ms01O+RFo7iaa6HFjm7hs7ca7ZZlZnZnUNBTSutmTWr18/PrN5c8ZJNq4g3HluBzYRZmk6PV3BfBqu9wDnmI1NO9ftm4Rxc0Z3cIjevXvT+777IgxKuqpPRwXc/dRM28xsq5mN8L3VPvVpip0IfNLMLif0rO5nZu+5+9VpznUXcBeEap/O/hLSw7UzXO//I3xgBhEGp7uIMDtZG/kyXO/+tEN3D+Xmzg3v42qHnuH6vwg8DrzQmWPky/WXPTpM/h1YSvj/dnPi569SC7j7np7UZlZFqPNvk/hFMsowXO9uwl3+bOD3hG77lwBfB25NU77u8ce5/4orGDlyJCNHjmTUqFF7fh500EFZCj5JmjlmWy0C/g34C2EMmoXAJ1s3tn4BVFRk5aH1zp072bRpExs2bEi7zH/5ZT6TZr/fEh64H554/x7hC/gV4Pl0Jyqg4ZK7g64m/5uBX5jZpYQxlM4BMLNy4DJ3/3wXjy+ScbjedwjJcg6hpU9/4GLCpPTpkv/QD32Iww8/nLfeeosXXniBt956i7feeotNmzbRp0+fNl8IyT9HjhzJiBEjujbHa5o5ZiG0kf468CAwCdicbt+mprD/fj603rVrF1u2bMmY2Dds2MDbb7/NoYceypgxY/Ys48ePZ8qUKYwZM4aP3nJL2vPOBmYmvV9A+DLIWElVQMMldwddSv7u/lfglDTr64A2id/dFxJuakQ6r6wsJJ+UqodhhPlYa4C5hDvPewlzD7RRXMy4M8/kyiuvbLPJ3WlsbGTTpk37fCGsW7eOp556as/7rVu3MmTIkH2+ENJ9SZSWltIrdXjhDHPMAlwHXAuckHg/Kl38njTHbKIVkLvT0NDQbmLfvHkzhxxyyD6JfcyYMZxwwgl7Xo8YMYI+fdpJBZMmwW9+0+b6lySWVgcBRYT23G0U2HDJ3YHG9pH8V18PRxyRsd75CsLMY72BKcAPgENTCxYVwV/+0qXmk7t27aKhoWHPl0Tql0Xrz3fffZfDDjtsny+EGevX88knnqDPzp37HpMwxvwNwN2E0Sc/C9xG27Hnd/bpw0NlZdw1aBAbNmxg48aNDBgwoE1iT15GjRpF//79D/h3Btq9/p0WwfWXzulsU8+uVvuIZF/rHARp2pkfQ6h7bldEw/X27t2bww47jMMOO4zjjjsuY7nm5mY2b968zxfDoDSJH8LsUjuBh4BnCLNMTSdMqvOtlLJ9W1qo6N+f0muuYcyYMYwePZoBAwZ06XfqlHauf6cU4HDJ3YGSv3QP8+bBo48e2HC9SXMQ5EJRURHjxo1j3Lhxe1c+8QS8+mrb0BI/vwSMSLy+kvTJH+BDQ4fyoVMzNsDLnm50/aVzNJmLdA8VFWHY3ZKSjssmax2uN+6hHTI8tB5CaCOf3Ne13X6vcT007e7XX9pQ8pfuo7p6bwLqaGgAs/wap72sLNR7p3Ex4TlFPbAN+A5wRrqCcT807c7XX9pQ8pfupbo6DNJWWRmSaep0lMXFYX1lZSiXL4mnnblhvwlUAEcB/wh8HLgmXUHPgzlmu+v1lzbU2ke6r4aGMPTAmjWhA9GQIeHOuKoqPx8utjM4WofycXC67nb9C4SmcRTJN5pjVnKgs8lf1T4iuaKHppJH1NRTJJda68Dnzg1DNrT3l7dZqEPXQ1PJAt35i+SaHppKHtCdv0gcysvDw1s9NJWYKPmLxKm0FK66Ku4opACp2kdEpAAp+YuIFCAlfxGRAqTkLyJSgJT8RUQKkJK/iEgBUvIXESlASv4iIgUob0f1NLMG4M9xx9FJw4C34w5iPyje7FK82dOdYoV44j3C3TvsHp63yb87MbO6zgyhmi8Ub3Yp3uzpTrFCfserah8RkQKk5C8iUoCU/KNxV9wB7CfFm12KN3u6U6yQx/Gqzl9EpADpzl9EpAAp+XeSmR1iZo+Z2euJn0MylNtlZi8mlqVJ68eZ2UozW29mD5pZv7jjNbNjzOwPZrbWzFab2blJ2xaa2f8l/S7HZCnO083stcR1uTrN9v6J67U+cf3GJm2bl1j/mpl9Jhvx7WesV5rZK4lr+YSZHZG0Le3nIuZ4q8ysISmuzydtuyjx2XndzC7Kk3i/kxTrOjP7W9K2nF5fM/uJmdWb2csZtpuZfT/xu6w2s2OTtuX82qbl7lo6sQC3AlcnXl8N3JKh3HsZ1v8CmJl4/SOgOu54gaOA8YnXI4HNwMGJ9wuBs7McY2/gDeBIoB/wEjAhpczlwI8Sr2cCDyZeT0iU7w+MSxynd8yxfhooSbyubo21vc9FzPFWAT9Ms+8hwJuJn0MSr4fEHW9K+S8BP4nx+v4/4Fjg5QzbpwHLAQNOAFbGdW0zLbrz77zpwL2J1/cCn+3sjmZmwBTgoQPZ/wB1GK+7r3P31xOv3wLqgVzOHTgJWO/ub7r7B8AiQtzJkn+Ph4BTEtdzOrDI3Xe4+/8B6xPHiy1Wd3/K3bcn3j4HjM5iPB3pzLXN5DPAY+7+jrtvAx4DTs9SnK32N97zgJ9nOaaM3P1p4J12ikwHfurBc8DBZjaCeK5tWkr+nXeou29OvN4CHJqhXJGZ1ZnZc2bWmnCHAn9z95bE+43AqCzGCp2PFwAzm0S443ojafW3En+yfsfM+mchxlHAhqT36a7LnjKJ69dIuJ6d2TdK+3u+Swl3fq3SfS6yqbPx/nPi3/ghMxuzn/tGqdPnTFSnjQOeTFqd6+vbkUy/TxzXNi3N4ZvEzB4HDkuz6ZrkN+7uZpapmdQR7r7JzI4EnjSzNYSEFbmI4iVxR3IfcJG7706snkf40uhHaK72deCGKOLu6czsfKAc+FTS6jafC3d/I/0Rcua/gZ+7+w4z+yLhL6wpMcfUGTOBh9x9V9K6fLy+eU3JP4m7n5ppm5ltNbMR7r45kSzrMxxjU+Lnm2b2W+DjwGLCn319Enevo4FN+RCvmQ0CfgNck/jztPXYrX817DCze4C5XY03jU3AmKT36a5La5mNZtYHGAz8tZP7RqlT5zOzUwlfvp9y9x2t6zN8LrKZnDqM193/mvT2bsJzotZ9J6fs+9vII9zX/vx7zgT+NXlFDNe3I5l+nziubVqq9um8pUDrk/mLgF+lFjCzIa3VI2Y2DDgZeMXDk56ngLPb2z+GePsB/0Wom3woZduIxE8jPC9I26qhi2qB8RZaQvUj/KdObamR/HucDTyZuJ5LgZmJ1kDjgPHAH7MQY6djNbOPA3cCZ7l7fdL6tJ+LLMba2XhHJL09C3g18fpR4J8ScQ8B/imxLtZ4EzEfTXhQ+oekdXFc344sBS5MtPo5AWhM3FDFcW3Ti+Mpc3dcCPXMTwCvA48DhyTWlwN3J16fBKwhtFRYA1yatP+RhOS0Hvgl0D8P4j0f2Am8mLQck9j2ZOJ3eBm4HzgoS3FOA9YR7tKuSay7gZBAAYoS12t94vodmbTvNYn9XgOm5uAz0FGsjwNbk67l0o4+FzHHOx9Ym4jrKeDopH0vSVzz9cDF+RBv4v31wM0p++X8+hIeNm9O/P/ZSHjGcxlwWWK7Abcnfpc1QHmc1zbdoh6+IiIFSNU+IiIFSMlfRKQAKfmLiBQgJX8RkQKk5C8iUoCU/EVECpCSv4hIAVLyFxEpQP8fs4i0GoPdPMsAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80cddef0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "176\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'C', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80f70be0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "177\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'C', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e23828>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "178\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'C', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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27Vpuu+02rrnmGqZOncrx48fjHVZSUPIXkaSWnp7OhAkT2Lx5M5999hnf+MY3eO211+IdVsJTn7+INCpvvPEGEydOpHfv3jzzzDNceOGFwTcoLXUXoIuL3UykLVu6eYnGj0/KIjLq8xeRlPTd736XzZs306tXL/r06cPTTz/NmTNnajcsLHTTT3TqBDNmwPz58Je/uJ8PPwwdO7r1hYUx/x1iQclfRBqdjIwMHn74YdauXctrr71Gbm4u69ev/7pBfj4MGeLmHTp5snbRmbIyt6ygwLXLz49l+DHRJN4BiIhEyyWXXMIbb7zBSy+9xMiRI8nLy2N2t25kTZ8OJ06E3oG1rt2UKe61181nyU5n/iLSqBlj+MEPfsCHH35Ixy+/hF/8olbi/wcwFFdo5jzcHPU1OoqqPgAa0XVIJX8RSQnZ2dlMtZZMP/MLTQTaAZ/jagqvBp71bVRWBrNmRTvMmFHyF5HUUFoKK1Zg/Ixw3A2MATJwZ/43AFt9G1kLy5e76SkaASV/EUkNc+cGXPUz4BXgBK4A+QrcB0AtxgTdTzJR8heR1FBcXHtUj8e3cGf65+CKy+cAo/w1LCtzE9I1Akr+IpIajhzxu7gSd5Y/GjgO7McVlb8/0H4OHYpCcLGn5C8iqaFlS7+LDwKf4kb4NAfOBcYDywPtJzs7CsHFnpK/iKSG3r1dwRgfbYAuQD5ueOdh4EWgt799ZGa62gONgJK/iKSGceMCrloCvA60BboBTYGn/TW0Nuh+komSv4ikhnbt4MYb/dYR7gO8jevr3w8sBNr7NjIGhg5Nysne/FHyF5HUMW1a7frB4crMdNs3Ekr+IpI6cnNh9mzIyqrbdllZbruckDMlJw0lfxFJLRMmfP0B4KcLyFslcLpJE9e+EU3qBkr+IpKKJkyA1ashL8+NAPLtCsrMhIwMTg8bxrCzzmLToEHxiTOKNKWziKSmnBxYvNjN1TN3rrtz99AhN46/Vy8YN46Mtm0Z8/zz/Pu//ztr1qwhPT093lFHjMo4iogEUVlZybe+9S1uv/127rnnnniHE5LKOIqIREBaWhr5+flMnz6dL774It7hRIySv4hICL169eLOO+/k3nvvjXcoEaPkLyIShoceeoh169bx17/+Nd6hRIQu+IqIhKFFixb87ne/Y+LEiWzevJnMo0fdheLiYjdjaMuWbv6g8eOT4i5gXfAVEamD+7/9be745z/p+cknboF3jYDMTDf/z403uruBc3NjHp8u+IqIRFp+PrPee49Lt293Sd+3OExZmVtWUABDhkB+flzCDIeSv4hIOPLz+d1Pf8qAsjKygHE+q98EegBZwDXW8smJEzBlSsJ+ACj5i4iEUlgIU6Zwfnk5DwJ3+qzej6sE9iiuOEwOMBag6gMgAbuwlfxFREKZNQvKyhiNq+17rs/qJcDlwM1ABvAwsAn4CFxX0KxZsYs1TBFJ/saYG4wx240xJcaYqX7WNzfGLPCsf98Y0zkSxxURibrSUlixwl3IDWArcIXX6xbAxZ7lWAvLl7tpJBJIg5O/MSYd+D1wI9ATuNUY09On2V3AIWttN1yBnCcbelwRkZiYOzdkk2OAb4XglsDRqhfGhLWfWIrEmf8AoMRau8taexp4BRjp02YkriwmwCLgWmNCzKUqIpIIiotrj+rxcRbwlc+yr4Czq16UlbmJ4xJIJJL/BcBnXq/3eJb5bWOtPQMcoXa3mYhI4jlyJGSTy3F9/FWOAzs9y6sdOhTRsBoqoS74GmPuNsYUGWOK9iVY/5iIpKiWX3fonAFOAhWex0nPsjxgC7DYs+wRoDdu6Ge17OyYhBuuSCT/vcBFXq8v9Czz28YY0wTXHXbAd0fW2jnW2hxrbU7bJLg9WkRSQO/eruAL8BiQCTwB/NHz/DGgLS7xPwBkA+/j+r+rZWa6GgEJJBLJvxDobozpYoxpBtwCLPNpswy4w/P8+8BbNlHnlRAR8TZuXPXThwHr83jYs+47uKGdZcDbQGfvfVhbYz+JoMHJ39OHPwlYCWwDFlprtxpjHjHGfM/T7P8C5xpjSoB7gVrDQUVEElK7dm6unvqOUTEGhg5NuMneNLGbiEgohYVurp4TJ+q+bVaWqxecE3KutYjQxG4iIpGSmwuzZ2N9C72HkpUFs2fHLPHXhZK/iEgY7D338Fz37pxu0iR0F5AxXyf+CRNiE2AdKfmLiIRh/vz5/K6iwnXh5OW5EUC+3wQyM93yvDzXLkETP6iSl4hISHv27OHee+/l9ddfp1m/fjBokJurZ+5cd+fuoUNuHH+vXm5UT4Jd3PVHyV9EJAhrLXfddReTJk2iX79+X69o2xbuuy9+gTWQun1ERIKYM2cOBw8eZNq0afEOJaJ05i8iEsDOnTt58MEHWb16NU2bNo13OBGl5C8iqau01PXbFxe7CdxatnTTOYwfT0Xr1owfP55p06bRs6fvLPXJTzd5iUjqKSx01bVWrHCvvadszswEa9nRrRu/atKE/KIi0tPT4xNnPegmLxERf/Lz3d26BQUu6fvO1V9WBidP0nXLFv7w0Uekz5kTlzCjTd0+IpI68vNdQfUwpmlIB/fBMGWKW5DAY/brQ2f+IpIaCgtrJf6zfB7pwE98tztxwm3XyLqhlfxFJDXMmuW6dLwc83p8gZuf/2Z/25aVue0bESV/EWn8Skvdxd0gA1wWA+2Af/G30lpYvtzd1dtIKPmLSOM3d27IJi8CPwQCTtlmTFj7SRZK/iLS+BUX1x7V4+UTYDVflxv0q6zMzePTSCj5i0jjd+RI0NX/A3wT6BJqP4cORSig+FPyF5HGr2XLoKvnEeKsv0p2diSiSQhK/iLS+PXu7ebZ92MtsJcAo3y8ZWa6KZsbCSV/EWn0jt50E+Vnzvhd9yIwGjg71E6sdXP1NxJK/iLSaB0/fpwnn3ySi6+6ik0dOmD9lF98DtfnH5QxMHRoUhRpCZeSv4g0OmVlZTz99NN069aNDz74gHfeeYecxYsxdS3AXiUzExrZfP5K/iLSaJw6dYpnn32W7t27884777By5UpeeeUVevToAbm5rqB6VlbddlpViD0n5ESZSUUTu4lI0isvL2fevHk8+uij9OzZk4KCAnL8JeuqydmmTHHj9oNNaW+MO+OfPbvRTeoGOvMXkSRWUVHBH//4Ry677DJeeuklXnrpJZYvX+4/8VeZMAFWr4a8PDcCyLcrKDPTLc/Lc+0aYeIHnfmLSBKqrKxk8eLFzJgxg9atW/P8889zzTXXhL+DnBxYvNjN1TN3rrtz99AhN46/Vy83qqcRXdz1R8lfRJKGtZZly5bx0EMP0bx5c55++mmuu+46jJ9RPGFp2xbuuy+yQSYJJX8RSXjWWlauXMn06dMpLy/n0UcfZcSIEfVP+qLkLyKJbdWqVUyfPp2DBw8yc+ZMbrrpJtLSdLmyoZT8RSSySktdP3pxsZtQrWVLN73C+PF16kdfs2YN06dP57PPPmPGjBnceuutSVVIPdEp+YtIZBQWumpXK1a4195TKC9ZAjNmwI03upulcnMD7qaoqIjp06ezbds2HnroIX74wx/SpIlSVaTpu5OINFx+PgwZAgUFLun7zp1fVuaWFRS4dvn5tXZRXFzMqFGjGDVqFCNGjGD79u3ceeedSvxRouQvIg2Tn/91YfRgN02BW19VEN3zAbBt2zbGjh3Lddddx5AhQ9ixYwcTJ06kefPmMQg+dSn5i0j9FRZ+nfh9DAEygLM8j0u9V544QeW99zJj2DCuvvpq+vXrx86dO/nZz35GZn3n35E60fcpEam/WbNcl04AvwN+FGCdPXmSW3bv5hclJZxzzjlRCU8CU/IXkfopLXUXd0N19QSQDly2ezecOhXZuCQs6vYRkfqZOzdkk2lAG2Aw8La/BsaEtR+JPCV/Eamf4uLao3q8PAnswpVIvBsYAez0bVRW5ubVkZhT8heR+jlyJOjqgbjSiM1xxdEHA8v9NTx0KNKRSRgalPyNMa2NMW8YY3Z4fvotbW+MqTDGbPQ8ljXkmCKSIFq2rFNzA/i9OpDtN21IlDX0zH8q8Ka1tjvwpue1P2XW2j6ex/caeEwRiaNTp06xYsUKFu3YQaBxPoeBlcBJ4AwwH3gHuMG3YWamm0JZYq6hyX8k8KLn+YvAqAbuT0QS0LFjx1i0aBG33XYb5513Ho899hilN94Y8EascuBBoC3ugu9vgQLgEt+G1rq58yXmGjrUs7219nPP8y+A9gHaZRhjinAnAU9Yawv8NTLG3I27NkTHjh0bGJqINMSBAwf485//zNKlS1m1ahVXXXUVeXl5/PrXv6ZDhw6uUXGxm7LBZ7hnW6Aw1AGMgaFDG33RlERlbIgxusaYvwHn+Vn1APCitbaVV9tD1tpaHXjGmAustXuNMV2Bt4BrrbW1Lvx7y8nJsUVFReH8DiISIXv37qWgoIAlS5ZQVFTEtddey+jRoxk2bBjZ/vrmCwvdXD1+7vANKSvLlUlsZIXR480Ys8FaG/JNDXnmb639TpCDfGmM6WCt/dwY0wEoDbCPvZ6fu4wxbwN98TPqS0Rib8eOHSxZsoSlS5fy8ccfM3z4cCZNmsT1119PVlZW8I1zc12B8wBTPASUleW2U+KPm4Z2+yzDjeJ6wvPzVd8GnhFAJ6y1p4wxVfd7PNXA44pIPVlr2bhxI0uXLmXJkiUcOHCAUaNG8eijjzJkyBCaNm1atx1WFTifMsWN2w/Wm2CMu8g7e3ajLYyeLBqa/J8AFhpj7gI+AcYAGGNygHustT8CLgOeM8ZU4i4wP2Gt/bCBxxWROqioqGDdunXVCT8tLY3Ro0czZ84crrzyyoZXxpowwX0LmDULli93Sd57zp/MTPehMHSom89fZ/xxF7LPP17U5y/SMKdPn2bVqlUsWbKEV199lfbt25OXl8fo0aPp1atX9Orf7tvnpmzYvNndwJWd7YZzjhuni7sxELE+fxFJHsePH+f1119n6dKlLF++nB49ejB69GjWrFnDxRdfHJsg2raF++6LzbGk3pT8RaIhQnVsw3Hw4MHqIZlvvfUWV155JXl5eTz11FOcf/75ET2WNB7q9hGJpGB1bKv6vcOoYxvKP//5z+ohmYWFhXz7299m9OjRDB8+3P+QTEkZ6vYRibWqcoaBRrxUXQAtKICVK+s84qWkpKR6SOb27dsZNmwYEydO5Prrr6dFixYR+iUkVSj5i0SCdx3bULzr2ELADwBrLZs2baoeobN//35GjhzJzJkzGTJkCM2aNYvgLyCpRslfpKGC1LEF2AH0Ar4P/NF7RdUHQG5u9dDHyspK1q1bV32GDzB69Gj+8Ic/cOWVV5Kenh7N30RSiJK/SEOFqGP7YyBg735ZGRX/8R+8OWFC9ZDMtm3bkpeXx9KlS+ndu3f0hmRKSlPyF2mIEHVsXwFaAYOAEn8NrKW8oIDf7NnDNWPG8O6779KtW7foxSvioeQv0hBB6s9+BTyEm8nwhSC7aJaRwfIxYzQ2XmJKZRxFGiJIHdvpwF3AhSF2kXbypOrYSszpzF+kIQLUsd0I/A34INz9qI6txJiSv0g97du3j5NHj3KRn3VvA/8AqkoSHQMqgA+B//W3M92YJTGm5C8ShsrKSj766CPWrFnD2rVrWbt2LV988QW/bt+eO5o0oemZMzXa3w3c4vV6Nu7DIN/fzlXHVuJAyV/Ej+PHj1NYWFid7NetW0d2djaDBg1i8ODB/PznP+fyyy8n/cAB6NQJfJJ/ludR5SwgA1fesBbVsZU4UPIXAfbs2VOd6NesWcO2bdvo3bs3gwYN4q677uKFF174um6tt3bt3Fw9furYens40ArVsZU4UfKXlHPmzBmKi4trJPuysrLqs/rf/OY39O/fn8zMzPB2OG2am6unPnVsMzPd9iIxpuQvjd7hw4dZt25ddaIvLCykY8eODBo0iOuvv56ZM2fSvXv3+t9Jqzq2koSU/KVRsdayc+fOGmf1//jHP8jNzWXw4MFMmTKFq666KvLTHquOrSQZJX9JaidPnmTDhg3VI3DWrl1L06ZNGTx4MIMHD+bf/u3fuOKKK+pelLw+VMdWkoiKuUh4YliZKpgvv/yyOsmvWbOGTZs20aNHDwYPHlzdZ3/RRf5G3seY6tjOVMZQAAALk0lEQVRKnIRbzEXJX4KLUWUqfyorK9m6dWt1ol+7di0HDhzgqquuYtCgQQwaNIgBAwZw1llnRfS4IslMyV8aLlRlqioR6sM+duwY77//fnWyf++992jbtm2Ns/rLLruMtDRNSSUSiMo4SsP4qUx1O/AmcBw4D/gl8CMIuzKVN2stn376aY2z+u3bt9OnTx8GDx7MPffcw7x582jXrl3EfzUR0Zm/+FNYCEOG1Bq2uBXoBjQHPgKGAK8B/b0bZWXB6tW1LmaWl5ezcePGGsm+vLy8xll9v379aN68efR+L5EUoDN/qb8Alaku93puPI+d+CT/sjKYNYuDzz/PunXrqhN9UVERXbp0YfDgwQwfPpxZs2bRtWtXVakSiROd+UtNpaVurpoAc9RPBOYCZUBf4B3cvDXeThlDj6wsLr7yyuqz+oEDB9KqVatoRi4i6Mxf6itIZSqAZ4HfAutw0xb766Rp2qwZJdOnk37//ZGOTkQiRMMmpKYglamqpAPfBPbgf4ritFOnSN+6NQrBiUikKPlLDSe//DLstmdwff5+qTKVSEJTt08KO3r0KBs2bGD9+vXVj9lffskYP21LcYXIhwOZuBKFL3sefqkylUhCU/JPEeXl5WzZsqU6yb///vvs3r2bK664ggEDBnDTTTfx5JNP0nXxYpgxo1bXj8F18dwDVAKdgN8A3/N3MFWmEkl4Gu3TCFlr2b17d40z+o0bN9KpUycGDhzIgAEDGDBgAL169ao94VmI0T5hyciATz/VHDYicaDRPilk//79FBYWVp/Rr1+/noyMjOpE/+ijj9K/f3/OOeec0DsLszJVQKpMJZIUdOYfSILMYumrrKyMDz74oDrJr1+/nv3795Obm1t9Rp+bm8sFF1xQ/4MEuMM3LAHu8BWR2NDEbvUVx1ksfVVUVLBt27Ya3TcfffQRPXv2rNF9c+mll0Z+sjM/c/uEVFWZSgVKROJGyb8+YjyLpTdrLXv27KmR6Dds2ED79u1rJPo+ffqQkZERkWOGFMf3Q0TqR33+dVWXM916zGLp6/DhwxQVFdVI9mfOnKlO9FOnTiU3N5fWrVvXed8Ro8pUIo2WzvwhYB/3QeAu4K9AG2AWcJvvtmH0cZ86dYri4uIawyz37NlDv379qs/oBwwYQKdOnRJ3ojNVphJJCjHp9jHG3Aw8DFwGDLDW+s3WxpgbgGdwMwO8YK19ItS+Y5r8R4/2O7rlVtyY9v8LbASGAWupObslxkBeHixeDLjqUyUlJTUS/ZYtW+jWrVuNRH/55ZfTpIm+eIlIZMUq+V+Gy4/PAVP8JX9jTDrwMfBd3HQwhcCt1toPg+07Zsk/wLj240A2sAW4xLPsX4ELAN9ProqmTXlq0iRWbdlCYWEhLVu2rJHo+/fvT4sWLaL9m4iIxKbP31q7zXOwYM0GACXW2l2etq8AI4GgyT9mAsxi+THuzbnEa9kVwGo/bcsrKuhbXMw3fvpTBgwYQPv27SMepohIJMWi3+EC4DOv13uAgTE4bngCzGJ5DPC9JaolcNTPLjIqK7nh/PNhxIgoBCgiEnkhk78x5m+4kq2+HrDWvhrJYIwxdwN3A3Ts2DGSuw7syBG/i88CvvJZ9hVwdqD9aBZLEUkiIZO/tfY7DTzGXuAir9cXepb5O9YcYA64Pv8GHjc8LVv6XXwJbsriHUB3z7JN+Fzs9aZZLEUkicRiPv9CoLsxposxphlwC7AsBscNT+/ebiIyHy2A0cBDuIu/a4BXcRd9a9EsliKSZBqU/I0xecaYPcBVwGvGmJWe5ecbY5YDWGvPAJOAlcA2YKG1NnHKPI0bF3DVs7hate1wwz7zCXDmb23Q/YiIJJqGjvZZCiz1s/yfwFCv18uB5Q05VtQEmcWyNVAQanvNYikiSUhlHMFNTZCZWb9tMzPd9iIiSUTJH9z8NbNnu6ka6qJqFkvNaSMiSUbzC1SpmpxNs1iKSArQmb+3CRPcJG15eW4EkG9XUGamW56X59op8YtIktKZv6+cHDdJm2axFJFGTMk/kLZt4b774h2FiEhUqNtHRCQFKfmLiKQgJX8RkRSk5C8ikoKU/EVEUpCSv4hIClLyFxFJQUr+IiIpyNhgc9jEkTFmH/BJGE3bAPujHE59JWpsiqtuFFfdKK66iXRcnay1IachSNjkHy5jTJG1NiGn1UzU2BRX3SiuulFcdROvuNTtIyKSgpT8RURSUGNI/nPiHUAQiRqb4qobxVU3iqtu4hJX0vf5i4hI3TWGM38REamjpEj+xpjWxpg3jDE7PD+z/bTpY4xZZ4zZaowpNsaM9Vo31xiz2xiz0fPokyBxdTHGvG+MKTHGLDDGNItVXJ52rxtjDhtj/uKzPCrvV4Rii/d7doenzQ5jzB1ey982xmz3es/aNTCeGzz7KzHGTPWzvrnn9y/xvB+dvdZN8yzfboy5viFxRCouY0xnY0yZ1/vzhxjH9S1jzP8aY84YY77vs87vv2kCxFXh9X4ti2RcAFhrE/4BPAVM9TyfCjzpp80lQHfP8/OBz4FWntdzge8nYFwLgVs8z/8ATIhVXJ511wIjgL/4LI/K+xWh2OL2ngGtgV2en9me59medW8DORGKJR3YCXQFmgGbgJ4+bSYCf/A8vwVY4Hne09O+OdDFs5/0BIirM7AlSv+nwomrM9AbmOf9fzvYv2k84/KsOxaN96vqkRRn/sBI4EXP8xeBUb4NrLUfW2t3eJ7/EygFol1vsd5xGWMM8G1gUbDtoxWXJ543gaMROma46h1bArxn1wNvWGsPWmsPAW8AN0To+N4GACXW2l3W2tPAK574AsW7CLjW8/6MBF6x1p6y1u4GSjz7i3dc0RQyLmvtP6y1xUClz7bR/DdtSFxRlyzJv7219nPP8y+A9sEaG2MG4D5pd3ot/g9Pt8vTxpjmCRDXucBha+0Zz+o9wAXxiCuAaLxfDY0t3u/ZBcBnXq99j//fnq/o0xuY8EIdp0Ybz/txBPf+hLNtPOIC6GKM+cAYs9oY8y8RiincuKKxbbT3nWGMKTLGvGeMidRJTrWEqeFrjPkbcJ6fVQ94v7DWWmNMwCFKxpgOwP8Ad1hrqz5Np+H+oJvhhlXdDzwSz7gaejIUqbgCqPf7FYPY6i3Kcf3AWrvXGHM2sBj4V9xXeXE+Bzpaaw8YY/oDBcaYy621X8U7sATWyfN/qivwljFms7V2Z8itwpQwyd9a+51A64wxXxpjOlhrP/ck0dIA7c4BXgMesNa+57XvqjO6U8aY/wamJEBcB4BWxpgmnjOkC4G9sYwryL7r/X5FObZ4v2d7gSFery/E9fVjrd3r+XnUGPMS7it/fZP/XuAin+P4/p5VbfYYY5oALXHvTzjb1le947KuE/sUgLV2gzFmJ+56WFGM4gq27RCfbd+OQExV+673v4XX/6ldxpi3gb7U7M1okGTp9lkGVF2FvwN41beBcaM+lgLzrLWLfNZ18Pw0uL7cLfGOy/PHsAr4frDtoxVXMFF8vxoUWwK8ZyuB64wx2caNBroOWGmMaWKMaQNgjGkKDKdh71kh0N24kU3NcBdOfUd7eMf7feAtz/uzDLjFM+qmC9AdWN+AWCISlzGmrTEmHcBzJtsdd3E1VnEF4vffNN5xeeJp7nneBhgMfBihuJxoXk2O1APXZ/gmsAP4G9DaszwHeMHz/HagHNjo9ejjWfcWsBn3B/lH4KwEiasr7g+zBPgT0DxWcXlevwvsA8pw/ZHXR/P9ilBs8X7P7vQcuwQY71nWAtgAFANbgWdo4AgbYCjwMe5M7wHPskeA73meZ3h+/xLP+9HVa9sHPNttB26M8N9iveICbvK8NxuB/wVGxDiuXM//o+O4b0hbg/2bxjsuYJDnb3CT5+ddkYzLWqs7fEVEUlGydPuIiEgEKfmLiKQgJX8RkRSk5C8ikoKU/EVEUpCSv4hIClLyFxFJQUr+IiIp6P8DiSoPCadwdtcAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80ee4fd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "179\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'C', 10: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c947b8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "180\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'C', 10: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80dd6550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "181\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'C', 10: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80e7bfd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "182\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'C', 10: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80c53b00>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "183\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'C', 10: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d795c0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "184\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'C', 7: 'C', 8: 'C', 9: 'C', 10: 'S'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1d80d79a58>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# draw all the praphs\n",
-    "import sys\n",
-    "import pathlib\n",
-    "sys.path.insert(0, \"../\")\n",
-    "\n",
-    "%matplotlib inline\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "import networkx as nx\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "\n",
-    "\n",
-    "def main(): \n",
-    "    dataset, y = loadDataset(\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "    for idx, graph in enumerate(dataset):\n",
-    "        print(idx)\n",
-    "        print(nx.get_node_attributes(graph, 'label'))\n",
-    "        nx.draw_networkx(graph)\n",
-    "        plt.show()\n",
-    "    \n",
-    "if __name__ == '__main__':\n",
-    "    main()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/.ipynb_checkpoints/py-graph_test-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/py-graph_test-checkpoint.ipynb
deleted file mode 100644
index bfb0f36..0000000
--- a/notebooks/.ipynb_checkpoints/py-graph_test-checkpoint.ipynb
+++ /dev/null
@@ -1,170 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "autoscroll": false,
-    "ein.tags": "worksheet-0",
-    "slideshow": {
-     "slide_type": "-"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import paths\n",
-    "\n",
-    "import pygraph\n",
-    "\n",
-    "from pygraph.utils.graphfiles import loadDataset\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "autoscroll": false,
-    "ein.tags": "worksheet-0",
-    "slideshow": {
-     "slide_type": "-"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "import networkx as nx\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot  as plt\n",
-    "\n",
-    "# We load a ds dataset\n",
-    "# load it from https://brunl01.users.greyc.fr/CHEMISTRY/Acyclic.tar.gz\n",
-    "dataset, y = loadDataset(\"/home/bgauzere/work/Datasets/Acyclic/dataset_bps.ds\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "autoscroll": false,
-    "ein.tags": "worksheet-0",
-    "slideshow": {
-     "slide_type": "-"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "100%|██████████| 183/183 [07:41<00:00,  2.52s/it]\n",
-      "100%|██████████| 183/183 [08:39<00:00,  2.84s/it]\n",
-      "100%|██████████| 183/183 [05:19<00:00,  1.75s/it]\n",
-      "100%|██████████| 183/183 [05:50<00:00,  1.91s/it]\n"
-     ]
-    }
-   ],
-   "source": [
-    "#Compute graph edit distances\n",
-    "\n",
-    "from tqdm import tqdm\n",
-    "from pygraph.c_ext.lsape_binders import  lsap_solverHG\n",
-    "from pygraph.ged.costfunctions import ConstantCostFunction\n",
-    "from pygraph.ged.GED import ged\n",
-    "import time\n",
-    "\n",
-    "cf = ConstantCostFunction(1,3,1,3)\n",
-    "N=len(dataset)\n",
-    "\n",
-    "methods=['Riesen + LSAP', 'Neigh + LSAP', 'Riesen + LSAPE', 'Neigh + LSAPE']\n",
-    "ged_distances = [ np.zeros((N,N)), np.zeros((N,N)), np.zeros((N,N)), np.zeros((N,N))]\n",
-    "\n",
-    "times = list()\n",
-    "start = time.clock()\n",
-    "for i in tqdm(range(0,N)):\n",
-    "    for j in range(0,N):\n",
-    "        ged_distances[0][i,j] = ged(dataset[i],dataset[j],cf=cf, method='Riesen')[0]\n",
-    "times.append(time.clock() - start)\n",
-    "\n",
-    "\n",
-    "start = time.clock()\n",
-    "for i in tqdm(range(0,N)):\n",
-    "    for j in range(0,N):\n",
-    "        ged_distances[1][i,j] = ged(dataset[i],dataset[j],cf=cf, method='Neighboorhood')[0]\n",
-    "\n",
-    "times.append(time.clock() - start)\n",
-    "\n",
-    "start = time.clock()\n",
-    "for i in tqdm(range(0,N)):\n",
-    "    for j in range(0,N):\n",
-    "        ged_distances[2][i,j] = ged(dataset[i],dataset[j],cf=cf, method='Riesen',solver=lsap_solverHG)[0]\n",
-    "times.append(time.clock() - start)\n",
-    "\n",
-    "start = time.clock()\n",
-    "for i in tqdm(range(0,N)):\n",
-    "    for j in range(0,N):\n",
-    "        ged_distances[3][i,j] = ged(dataset[i],dataset[j],cf=cf, method='Neighboorhood',solver=lsap_solverHG)[0]\n",
-    "times.append(time.clock() - start)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "autoscroll": false,
-    "ein.tags": "worksheet-0",
-    "slideshow": {
-     "slide_type": "-"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      " method \t mean \t mean \t time\n",
-      " Riesen + LSAP \t 37.79903849025053 \t 35.31207262086058 \t 463.300405 \n",
-      " Neigh + LSAP \t 36.2281047508137 \t 33.85869987159963 \t 521.7821730000001 \n",
-      " Riesen + LSAPE \t 35.95508973095643 \t 34.10092866314312 \t 319.83455500000014 \n",
-      " Neigh + LSAPE \t 34.5005822807489 \t 32.5735614679447 \t 350.48029599999995 \n"
-     ]
-    }
-   ],
-   "source": [
-    "print(\" method \\t mean \\t mean \\t time\")\n",
-    "data = list()\n",
-    "for i in range(0,len(ged_distances)):\n",
-    "    ged_ = np.minimum(ged_distances[i],ged_distances[i].transpose())\n",
-    "    print(\" {} \\t {} \\t {} \\t {} \".format(methods[i], np.mean(ged_distances[i]),np.mean(ged_), times[i]))\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  },
-  "name": "py-graph_test.ipynb"
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/.ipynb_checkpoints/run_cyclicpatternkernel-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/run_cyclicpatternkernel-checkpoint.ipynb
deleted file mode 100644
index 6599a17..0000000
--- a/notebooks/.ipynb_checkpoints/run_cyclicpatternkernel-checkpoint.ipynb
+++ /dev/null
@@ -1,2305 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "--- This is a classification problem ---\n",
-      "\n",
-      "1. Loading dataset from file...\n",
-      "\n",
-      "2. Calculating gram matrices. This could take a while...\n",
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 365.70it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 29032.23it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.19042706489562988 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 0.0} is: \n",
-      "[[0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " ...\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbf4589e8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 284.42it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 20249.39it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.24454069137573242 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 25.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  0.]\n",
-      " [ 8.  8.  8. ...  8.  8.  0.]\n",
-      " [ 8.  8.  8. ...  8.  8.  0.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  0.]\n",
-      " [ 8.  8.  8. ...  9. 10.  0.]\n",
-      " [ 0.  0.  0. ...  0.  0.  0.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cc071e5f8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 221.19it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 18024.06it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.31366610527038574 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 50.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cfc5a5940>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 193.29it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 16071.94it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.358229398727417 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 75.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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1DRM2znSrKddmmLFptmSbpyM3xdCmTu73kHuIn7tkfF18uTct5cZdlntaNuo+L/MRgpklTghmljghmFnihGBmiROCmSVOCGaWLIuZir7bcXAbdfwot3b9DGpj1Pb8KDczmzgnBDNLZvKUYbnOVGyqczIsw159TFnuEuh1pyNNfb3lvtdltZ0bQ/m0JaefahtNpz1131H2MuylxVfq9pEf5WZmQ3NCMLPECcHMEicEM0ucEMwsmclRhnFbKhOTmuq0Kdd0P30bbUYgRl2SHeDXm17KqpfTV9OV+9wYcj9TuY2mz9CmvXLcOaMwXkLNzIaW+zj4J4CXgN8AxyJio6RVwO3AOuAJ4NqIODSZMM2sC8McIbw7IjZExMbi/Y3AXEScD8wV781sCcu6hlAcIWyMiOdK2x4D3hUR+yWtAb4fERc0teOZis1tz+SaijUz9LKf/tzwGeoe31Z9CnPuY9TKfa2/of9TmavXDH7+J//ct9+6awu5/Qxqo6698ufLnamYMyNy3NcQAviepPslbS22rY6I/cXrA8DqzLbMbEblrrr8joh4WtJvAbsl/az8y4gISX1TU5FAtgKcyVkjBWtmk5WVECLi6eLnQUk7gcuAZyStKZ0yHKypux3YDr1ThvGEfXKqHu4tuomGzJt6MpdNr42hoZ+6PmHxKUTdaQZXLr65qazpcH39zleH1XK/B26ov+mort8mtZ8ps5/cm5uavqOhYys5JQ5ntTXwlEHS2ZJed/w18D7gYeAuYHNRbDOwK6tHM5tZOUcIq4Gdko6X/5eI+I6kHwF3SNoC/BK4dnJhmlkXPFOxxDMVm3mmYn4/1TY8U9HMlhwnBDNLnBDMLJnJawieqdhzss1UbBqqHPfTn+tUYyivYdgUa1253L6q60mW5X7Hozz92dcQzGxoTghmlszkKcO4LZVhRz+5qX/bfnLTie35yU1mNnFOCGaWzOQpw3IdZWiq4yc3DRefn9y0mJ/cZGZDc0Iws8QJwcwSJwQzS5wQzCxxQjCzZCaHHcdtqcxUbKrjBVIG8wIpXiDFzMbICcHMkpk8ZViuMxW9HsKJdQbFVxdrHa+H0MxHCGaWOCGYWeKEYGaJE4KZJVkJQdJKSXdK+pmkfZKukLRK0m5Jjxc/z5l0sGY2WblHCNuA70TEhcDFwD7gRmAuIs4H5or3ZraEDRx2lPQG4EHgbVEqLOkx4F2lpz9/PyIuaGrLMxWb+/Saiv3b9pqKJ7Y3zTUVzwOeBb4i6QFJXyqeAr06IvYXZQ7QeyismS1hOQlhBXAp8MWIuAQ4TOX0oDhy6JvGJW2VNC9p/ihHRo3XzCYo55Tht4H7ImJd8f6d9BLCepbIKYPNhqbZek2aDqPH3dewMeT2k/sZ2sSd0/bY1lSMiAPAk5KO/8f+HuBR4C5gc7FtM7BrYFRmNtNWZJb7K+Brkk4HfgF8nF4yuUPSFuCXwLWTCdHMupKVECLiQWBjn19N5Ph/ud7c1FTnZFiGvSp3CfScfqp95badW67ue62rX22jzfeavQz7iPu8zDMVzSxxQjCzxAnBzJKZXCBl3JbKTMWmOl5TcTCvqeg1Fc1sjJwQzCzJnYfQKQ87nljnpBh2vLLl058Z/unPV94w5qc/f7j/uod1/VTbKNevqvuOxjnseEocru1/UbmsUma2LDghmFkyk6cMy9UJ6wCQd/W5rlx5e+sYatYiyF6GvRRD9SachZqr69U+c6/Cl/tauLl/mfU7F8dwb83y6tVyi5Zhz+in2kbjMuw139FC5Tte1F7dd1ezz1/Zk3dzlY8QzCxxQjCzxBOTSqY9MclLqPVv20uondjeNJdQM7NlwgnBzBInBDNLnBDMLHFCMLPECcHMkk6HHSU9S++5Ds911ml/b3IMjmGGYuii/9+NiDcPKtRpQgCQNB8R/RZsdQyOYVnGMO3+y3zKYGaJE4KZJdNICNun0GeVY+hxDD3TjmHa/SedX0Mws9nlUwYzS5wQzCxxQjCzxAnBzBInBDNL/h+NLejPhGw6dwAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc38c4a8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 211.71it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 12809.34it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.32873964309692383 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 100.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc38c2b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 209.41it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 12656.99it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.3321540355682373 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 125.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc2d7c18>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 205.72it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 14964.72it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.33719635009765625 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 150.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc2959b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 216.96it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 16669.36it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.31943273544311523 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 175.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc28cfd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 207.52it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 15853.96it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.33396363258361816 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 200.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc24e048>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 220.31it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 15243.05it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.3158130645751953 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 225.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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1DRM2znSrKddmmLFptmSbpyM3xdCmTu73kHuIn7tkfF18uTct5cZdlntaNuo+L/MRgpklTghmljghmFnihGBmiROCmSVOCGaWLIuZir7bcXAbdfwot3b9DGpj1Pb8KDczmzgnBDNLZvKUYbnOVGyqczIsw159TFnuEuh1pyNNfb3lvtdltZ0bQ/m0JaefahtNpz1131H2MuylxVfq9pEf5WZmQ3NCMLPECcHMEicEM0ucEMwsmclRhnFbKhOTmuq0Kdd0P30bbUYgRl2SHeDXm17KqpfTV9OV+9wYcj9TuY2mz9CmvXLcOaMwXkLNzIaW+zj4J4CXgN8AxyJio6RVwO3AOuAJ4NqIODSZMM2sC8McIbw7IjZExMbi/Y3AXEScD8wV781sCcu6hlAcIWyMiOdK2x4D3hUR+yWtAb4fERc0teOZis1tz+SaijUz9LKf/tzwGeoe31Z9CnPuY9TKfa2/of9TmavXDH7+J//ct9+6awu5/Qxqo6698ufLnamYMyNy3NcQAviepPslbS22rY6I/cXrA8DqzLbMbEblrrr8joh4WtJvAbsl/az8y4gISX1TU5FAtgKcyVkjBWtmk5WVECLi6eLnQUk7gcuAZyStKZ0yHKypux3YDr1ThvGEfXKqHu4tuomGzJt6MpdNr42hoZ+6PmHxKUTdaQZXLr65qazpcH39zleH1XK/B26ov+mort8mtZ8ps5/cm5uavqOhYys5JQ5ntTXwlEHS2ZJed/w18D7gYeAuYHNRbDOwK6tHM5tZOUcIq4Gdko6X/5eI+I6kHwF3SNoC/BK4dnJhmlkXPFOxxDMVm3mmYn4/1TY8U9HMlhwnBDNLnBDMLJnJawieqdhzss1UbBqqHPfTn+tUYyivYdgUa1253L6q60mW5X7Hozz92dcQzGxoTghmlszkKcO4LZVhRz+5qX/bfnLTie35yU1mNnFOCGaWzOQpw3IdZWiq4yc3DRefn9y0mJ/cZGZDc0Iws8QJwcwSJwQzS5wQzCxxQjCzZCaHHcdtqcxUbKrjBVIG8wIpXiDFzMbICcHMkpk8ZViuMxW9HsKJdQbFVxdrHa+H0MxHCGaWOCGYWeKEYGaJE4KZJVkJQdJKSXdK+pmkfZKukLRK0m5Jjxc/z5l0sGY2WblHCNuA70TEhcDFwD7gRmAuIs4H5or3ZraEDRx2lPQG4EHgbVEqLOkx4F2lpz9/PyIuaGrLMxWb+/Saiv3b9pqKJ7Y3zTUVzwOeBb4i6QFJXyqeAr06IvYXZQ7QeyismS1hOQlhBXAp8MWIuAQ4TOX0oDhy6JvGJW2VNC9p/ihHRo3XzCYo55Tht4H7ImJd8f6d9BLCepbIKYPNhqbZek2aDqPH3dewMeT2k/sZ2sSd0/bY1lSMiAPAk5KO/8f+HuBR4C5gc7FtM7BrYFRmNtNWZJb7K+Brkk4HfgF8nF4yuUPSFuCXwLWTCdHMupKVECLiQWBjn19N5Ph/ud7c1FTnZFiGvSp3CfScfqp95badW67ue62rX22jzfeavQz7iPu8zDMVzSxxQjCzxAnBzJKZXCBl3JbKTMWmOl5TcTCvqeg1Fc1sjJwQzCzJnYfQKQ87nljnpBh2vLLl058Z/unPV94w5qc/f7j/uod1/VTbKNevqvuOxjnseEocru1/UbmsUma2LDghmFkyk6cMy9UJ6wCQd/W5rlx5e+sYatYiyF6GvRRD9SachZqr69U+c6/Cl/tauLl/mfU7F8dwb83y6tVyi5Zhz+in2kbjMuw139FC5Tte1F7dd1ezz1/Zk3dzlY8QzCxxQjCzxBOTSqY9MclLqPVv20uondjeNJdQM7NlwgnBzBInBDNLnBDMLHFCMLPECcHMkk6HHSU9S++5Ds911ml/b3IMjmGGYuii/9+NiDcPKtRpQgCQNB8R/RZsdQyOYVnGMO3+y3zKYGaJE4KZJdNICNun0GeVY+hxDD3TjmHa/SedX0Mws9nlUwYzS5wQzCxxQjCzxAnBzBInBDNL/h+NLejPhGw6dwAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc1d37b8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 203.01it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 15196.75it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.3424692153930664 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 250.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc1b9b00>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 219.06it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 14092.93it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.3170757293701172 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 275.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc1a3668>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 196.86it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 9586.66it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.355010986328125 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 300.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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1DRM2znSrKddmmLFptmSbpyM3xdCmTu73kHuIn7tkfF18uTct5cZdlntaNuo+L/MRgpklTghmljghmFnihGBmiROCmSVOCGaWLIuZir7bcXAbdfwot3b9DGpj1Pb8KDczmzgnBDNLZvKUYbnOVGyqczIsw159TFnuEuh1pyNNfb3lvtdltZ0bQ/m0JaefahtNpz1131H2MuylxVfq9pEf5WZmQ3NCMLPECcHMEicEM0ucEMwsmclRhnFbKhOTmuq0Kdd0P30bbUYgRl2SHeDXm17KqpfTV9OV+9wYcj9TuY2mz9CmvXLcOaMwXkLNzIaW+zj4J4CXgN8AxyJio6RVwO3AOuAJ4NqIODSZMM2sC8McIbw7IjZExMbi/Y3AXEScD8wV781sCcu6hlAcIWyMiOdK2x4D3hUR+yWtAb4fERc0teOZis1tz+SaijUz9LKf/tzwGeoe31Z9CnPuY9TKfa2/of9TmavXDH7+J//ct9+6awu5/Qxqo6698ufLnamYMyNy3NcQAviepPslbS22rY6I/cXrA8DqzLbMbEblrrr8joh4WtJvAbsl/az8y4gISX1TU5FAtgKcyVkjBWtmk5WVECLi6eLnQUk7gcuAZyStKZ0yHKypux3YDr1ThvGEfXKqHu4tuomGzJt6MpdNr42hoZ+6PmHxKUTdaQZXLr65qazpcH39zleH1XK/B26ov+mort8mtZ8ps5/cm5uavqOhYys5JQ5ntTXwlEHS2ZJed/w18D7gYeAuYHNRbDOwK6tHM5tZOUcIq4Gdko6X/5eI+I6kHwF3SNoC/BK4dnJhmlkXPFOxxDMVm3mmYn4/1TY8U9HMlhwnBDNLnBDMLJnJawieqdhzss1UbBqqHPfTn+tUYyivYdgUa1253L6q60mW5X7Hozz92dcQzGxoTghmlszkKcO4LZVhRz+5qX/bfnLTie35yU1mNnFOCGaWzOQpw3IdZWiq4yc3DRefn9y0mJ/cZGZDc0Iws8QJwcwSJwQzS5wQzCxxQjCzZCaHHcdtqcxUbKrjBVIG8wIpXiDFzMbICcHMkpk8ZViuMxW9HsKJdQbFVxdrHa+H0MxHCGaWOCGYWeKEYGaJE4KZJVkJQdJKSXdK+pmkfZKukLRK0m5Jjxc/z5l0sGY2WblHCNuA70TEhcDFwD7gRmAuIs4H5or3ZraEDRx2lPQG4EHgbVEqLOkx4F2lpz9/PyIuaGrLMxWb+/Saiv3b9pqKJ7Y3zTUVzwOeBb4i6QFJXyqeAr06IvYXZQ7QeyismS1hOQlhBXAp8MWIuAQ4TOX0oDhy6JvGJW2VNC9p/ihHRo3XzCYo55Tht4H7ImJd8f6d9BLCepbIKYPNhqbZek2aDqPH3dewMeT2k/sZ2sSd0/bY1lSMiAPAk5KO/8f+HuBR4C5gc7FtM7BrYFRmNtNWZJb7K+Brkk4HfgF8nF4yuUPSFuCXwLWTCdHMupKVECLiQWBjn19N5Ph/ud7c1FTnZFiGvSp3CfScfqp95badW67ue62rX22jzfeavQz7iPu8zDMVzSxxQjCzxAnBzJKZXCBl3JbKTMWmOl5TcTCvqeg1Fc1sjJwQzCzJnYfQKQ87nljnpBh2vLLl058Z/unPV94w5qc/f7j/uod1/VTbKNevqvuOxjnseEocru1/UbmsUma2LDghmFkyk6cMy9UJ6wCQd/W5rlx5e+sYatYiyF6GvRRD9SachZqr69U+c6/Cl/tauLl/mfU7F8dwb83y6tVyi5Zhz+in2kbjMuw139FC5Tte1F7dd1ezz1/Zk3dzlY8QzCxxQjCzxBOTSqY9MclLqPVv20uondjeNJdQM7NlwgnBzBInBDNLnBDMLHFCMLPECcHMkk6HHSU9S++5Ds911ml/b3IMjmGGYuii/9+NiDcPKtRpQgCQNB8R/RZsdQyOYVnGMO3+y3zKYGaJE4KZJdNICNun0GeVY+hxDD3TjmHa/SedX0Mws9nlUwYzS5wQzCxxQjCzxAnBzBInBDNL/h+NLejPhGw6dwAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc217f28>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 205.74it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 13401.59it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.33774304389953613 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 325.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbfe27898>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 214.36it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 16588.88it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.3233025074005127 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 350.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc272c18>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 212.04it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 11443.29it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.3286900520324707 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 375.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc19e400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 204.41it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 15729.80it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.3390078544616699 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 400.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc29fc88>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 196.38it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 10160.76it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.3551766872406006 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 425.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc27a9b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 188.35it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 15243.86it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.36798596382141113 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 450.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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1DRM2znSrKddmmLFptmSbpyM3xdCmTu73kHuIn7tkfF18uTct5cZdlntaNuo+L/MRgpklTghmljghmFnihGBmiROCmSVOCGaWLIuZir7bcXAbdfwot3b9DGpj1Pb8KDczmzgnBDNLZvKUYbnOVGyqczIsw159TFnuEuh1pyNNfb3lvtdltZ0bQ/m0JaefahtNpz1131H2MuylxVfq9pEf5WZmQ3NCMLPECcHMEicEM0ucEMwsmclRhnFbKhOTmuq0Kdd0P30bbUYgRl2SHeDXm17KqpfTV9OV+9wYcj9TuY2mz9CmvXLcOaMwXkLNzIaW+zj4J4CXgN8AxyJio6RVwO3AOuAJ4NqIODSZMM2sC8McIbw7IjZExMbi/Y3AXEScD8wV781sCcu6hlAcIWyMiOdK2x4D3hUR+yWtAb4fERc0teOZis1tz+SaijUz9LKf/tzwGeoe31Z9CnPuY9TKfa2/of9TmavXDH7+J//ct9+6awu5/Qxqo6698ufLnamYMyNy3NcQAviepPslbS22rY6I/cXrA8DqzLbMbEblrrr8joh4WtJvAbsl/az8y4gISX1TU5FAtgKcyVkjBWtmk5WVECLi6eLnQUk7gcuAZyStKZ0yHKypux3YDr1ThvGEfXKqHu4tuomGzJt6MpdNr42hoZ+6PmHxKUTdaQZXLr65qazpcH39zleH1XK/B26ov+mort8mtZ8ps5/cm5uavqOhYys5JQ5ntTXwlEHS2ZJed/w18D7gYeAuYHNRbDOwK6tHM5tZOUcIq4Gdko6X/5eI+I6kHwF3SNoC/BK4dnJhmlkXPFOxxDMVm3mmYn4/1TY8U9HMlhwnBDNLnBDMLJnJawieqdhzss1UbBqqHPfTn+tUYyivYdgUa1253L6q60mW5X7Hozz92dcQzGxoTghmlszkKcO4LZVhRz+5qX/bfnLTie35yU1mNnFOCGaWzOQpw3IdZWiq4yc3DRefn9y0mJ/cZGZDc0Iws8QJwcwSJwQzS5wQzCxxQjCzZCaHHcdtqcxUbKrjBVIG8wIpXiDFzMbICcHMkpk8ZViuMxW9HsKJdQbFVxdrHa+H0MxHCGaWOCGYWeKEYGaJE4KZJVkJQdJKSXdK+pmkfZKukLRK0m5Jjxc/z5l0sGY2WblHCNuA70TEhcDFwD7gRmAuIs4H5or3ZraEDRx2lPQG4EHgbVEqLOkx4F2lpz9/PyIuaGrLMxWb+/Saiv3b9pqKJ7Y3zTUVzwOeBb4i6QFJXyqeAr06IvYXZQ7QeyismS1hOQlhBXAp8MWIuAQ4TOX0oDhy6JvGJW2VNC9p/ihHRo3XzCYo55Tht4H7ImJd8f6d9BLCepbIKYPNhqbZek2aDqPH3dewMeT2k/sZ2sSd0/bY1lSMiAPAk5KO/8f+HuBR4C5gc7FtM7BrYFRmNtNWZJb7K+Brkk4HfgF8nF4yuUPSFuCXwLWTCdHMupKVECLiQWBjn19N5Ph/ud7c1FTnZFiGvSp3CfScfqp95badW67ue62rX22jzfeavQz7iPu8zDMVzSxxQjCzxAnBzJKZXCBl3JbKTMWmOl5TcTCvqeg1Fc1sjJwQzCzJnYfQKQ87nljnpBh2vLLl058Z/unPV94w5qc/f7j/uod1/VTbKNevqvuOxjnseEocru1/UbmsUma2LDghmFkyk6cMy9UJ6wCQd/W5rlx5e+sYatYiyF6GvRRD9SachZqr69U+c6/Cl/tauLl/mfU7F8dwb83y6tVyi5Zhz+in2kbjMuw139FC5Tte1F7dd1ezz1/Zk3dzlY8QzCxxQjCzxBOTSqY9MclLqPVv20uondjeNJdQM7NlwgnBzBInBDNLnBDMLHFCMLPECcHMkk6HHSU9S++5Ds911ml/b3IMjmGGYuii/9+NiDcPKtRpQgCQNB8R/RZsdQyOYVnGMO3+y3zKYGaJE4KZJdNICNun0GeVY+hxDD3TjmHa/SedX0Mws9nlUwYzS5wQzCxxQjCzxAnBzBInBDNL/h+NLejPhGw6dwAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc308d68>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 210.29it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 15946.14it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.3297882080078125 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 475.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc32d128>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 209.44it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 14995.41it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.3310410976409912 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'cycle_bound': 500.0} is: \n",
-      "[[ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " [ 8.  8.  8. ...  8.  8.  8.]\n",
-      " ...\n",
-      " [ 8.  8.  8. ... 10.  9.  9.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]\n",
-      " [ 8.  8.  8. ...  9. 10. 10.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9cbc270278>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "3. Fitting and predicting using nested cross validation. This could really take a while...\n",
-      "                                                                              \n",
-      "4. Getting final performances...\n",
-      "\n",
-      "best_params_out:  [{'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}, {'cycle_bound': 125.0}]\n",
-      "best_params_in:  [{'C': 0.1778279410038923}, {'C': 0.31622776601683794}, {'C': 0.5623413251903491}, {'C': 1.0}, {'C': 1.7782794100389228}, {'C': 3.1622776601683795}, {'C': 5.623413251903491}, {'C': 10.0}, {'C': 17.78279410038923}, {'C': 31.622776601683793}, {'C': 56.23413251903491}, {'C': 100.0}, {'C': 177.82794100389228}, {'C': 316.22776601683796}, {'C': 562.341325190349}, {'C': 1000.0}, {'C': 1778.2794100389228}, {'C': 3162.2776601683795}, {'C': 5623.413251903491}, {'C': 10000.0}, {'C': 17782.794100389227}, {'C': 31622.776601683792}, {'C': 56234.13251903491}, {'C': 100000.0}]\n",
-      "best_val_perf:  0.6234126984126985\n",
-      "best_val_std:  0.019901659602732907\n",
-      "final_performance:  0.5666666666666665\n",
-      "final_confidence:  0.16559590358481774\n",
-      "train_performance:  0.623496071829405\n",
-      "train_std:  0.019012737655866176\n",
-      "time to calculate gram matrix:  0.3321540355682373 s\n",
-      "\n",
-      "params                                   train_perf    valid_perf    test_perf      gram_matrix_time\n",
-      "---------------------------------------  ------------  ------------  -----------  ------------------\n",
-      "{'C': '1.00e-05', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.00e-05', 'cycle_bound': 25.0}   0.56±0.02     0.55±0.05     0.54±0.14                  0.24\n",
-      "{'C': '1.00e-05', 'cycle_bound': 50.0}   0.56±0.02     0.55±0.05     0.53±0.15                  0.31\n",
-      "{'C': '1.00e-05', 'cycle_bound': 75.0}   0.56±0.02     0.55±0.03     0.53±0.17                  0.36\n",
-      "{'C': '1.00e-05', 'cycle_bound': 100.0}  0.55±0.02     0.54±0.05     0.59±0.13                  0.33\n",
-      "{'C': '1.00e-05', 'cycle_bound': 125.0}  0.56±0.02     0.55±0.04     0.52±0.14                  0.33\n",
-      "{'C': '1.00e-05', 'cycle_bound': 150.0}  0.55±0.02     0.52±0.06     0.62±0.13                  0.34\n",
-      "{'C': '1.00e-05', 'cycle_bound': 175.0}  0.57±0.02     0.56±0.04     0.47±0.19                  0.32\n",
-      "{'C': '1.00e-05', 'cycle_bound': 200.0}  0.56±0.02     0.55±0.03     0.57±0.13                  0.33\n",
-      "{'C': '1.00e-05', 'cycle_bound': 225.0}  0.56±0.02     0.54±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.00e-05', 'cycle_bound': 250.0}  0.56±0.02     0.54±0.04     0.58±0.18                  0.34\n",
-      "{'C': '1.00e-05', 'cycle_bound': 275.0}  0.56±0.02     0.55±0.04     0.54±0.19                  0.32\n",
-      "{'C': '1.00e-05', 'cycle_bound': 300.0}  0.55±0.02     0.52±0.06     0.59±0.13                  0.36\n",
-      "{'C': '1.00e-05', 'cycle_bound': 325.0}  0.57±0.02     0.55±0.05     0.50±0.14                  0.34\n",
-      "{'C': '1.00e-05', 'cycle_bound': 350.0}  0.56±0.02     0.55±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.00e-05', 'cycle_bound': 375.0}  0.55±0.02     0.53±0.06     0.61±0.15                  0.33\n",
-      "{'C': '1.00e-05', 'cycle_bound': 400.0}  0.55±0.02     0.52±0.07     0.59±0.13                  0.34\n",
-      "{'C': '1.00e-05', 'cycle_bound': 425.0}  0.56±0.02     0.54±0.06     0.57±0.13                  0.36\n",
-      "{'C': '1.00e-05', 'cycle_bound': 450.0}  0.57±0.02     0.56±0.04     0.50±0.17                  0.37\n",
-      "{'C': '1.00e-05', 'cycle_bound': 475.0}  0.56±0.02     0.55±0.04     0.54±0.16                  0.33\n",
-      "{'C': '1.00e-05', 'cycle_bound': 500.0}  0.56±0.02     0.55±0.05     0.51±0.17                  0.33\n",
-      "{'C': '1.78e-05', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.78e-05', 'cycle_bound': 25.0}   0.56±0.02     0.55±0.05     0.54±0.14                  0.24\n",
-      "{'C': '1.78e-05', 'cycle_bound': 50.0}   0.56±0.02     0.55±0.05     0.53±0.15                  0.31\n",
-      "{'C': '1.78e-05', 'cycle_bound': 75.0}   0.56±0.02     0.55±0.03     0.53±0.17                  0.36\n",
-      "{'C': '1.78e-05', 'cycle_bound': 100.0}  0.55±0.02     0.54±0.05     0.59±0.13                  0.33\n",
-      "{'C': '1.78e-05', 'cycle_bound': 125.0}  0.56±0.02     0.55±0.04     0.52±0.14                  0.33\n",
-      "{'C': '1.78e-05', 'cycle_bound': 150.0}  0.55±0.02     0.52±0.06     0.62±0.13                  0.34\n",
-      "{'C': '1.78e-05', 'cycle_bound': 175.0}  0.57±0.02     0.56±0.04     0.47±0.19                  0.32\n",
-      "{'C': '1.78e-05', 'cycle_bound': 200.0}  0.56±0.02     0.55±0.03     0.57±0.13                  0.33\n",
-      "{'C': '1.78e-05', 'cycle_bound': 225.0}  0.56±0.02     0.54±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.78e-05', 'cycle_bound': 250.0}  0.56±0.02     0.54±0.04     0.58±0.18                  0.34\n",
-      "{'C': '1.78e-05', 'cycle_bound': 275.0}  0.56±0.02     0.55±0.04     0.54±0.19                  0.32\n",
-      "{'C': '1.78e-05', 'cycle_bound': 300.0}  0.55±0.02     0.52±0.06     0.59±0.13                  0.36\n",
-      "{'C': '1.78e-05', 'cycle_bound': 325.0}  0.57±0.02     0.55±0.05     0.50±0.14                  0.34\n",
-      "{'C': '1.78e-05', 'cycle_bound': 350.0}  0.56±0.02     0.55±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.78e-05', 'cycle_bound': 375.0}  0.55±0.02     0.53±0.06     0.61±0.15                  0.33\n",
-      "{'C': '1.78e-05', 'cycle_bound': 400.0}  0.55±0.02     0.52±0.07     0.59±0.13                  0.34\n",
-      "{'C': '1.78e-05', 'cycle_bound': 425.0}  0.56±0.02     0.54±0.06     0.57±0.13                  0.36\n",
-      "{'C': '1.78e-05', 'cycle_bound': 450.0}  0.57±0.02     0.56±0.04     0.50±0.17                  0.37\n",
-      "{'C': '1.78e-05', 'cycle_bound': 475.0}  0.56±0.02     0.55±0.04     0.54±0.16                  0.33\n",
-      "{'C': '1.78e-05', 'cycle_bound': 500.0}  0.56±0.02     0.55±0.05     0.51±0.17                  0.33\n",
-      "{'C': '3.16e-05', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '3.16e-05', 'cycle_bound': 25.0}   0.56±0.02     0.55±0.05     0.54±0.14                  0.24\n",
-      "{'C': '3.16e-05', 'cycle_bound': 50.0}   0.56±0.02     0.55±0.05     0.53±0.15                  0.31\n",
-      "{'C': '3.16e-05', 'cycle_bound': 75.0}   0.56±0.02     0.55±0.03     0.53±0.17                  0.36\n",
-      "{'C': '3.16e-05', 'cycle_bound': 100.0}  0.55±0.02     0.54±0.05     0.59±0.13                  0.33\n",
-      "{'C': '3.16e-05', 'cycle_bound': 125.0}  0.56±0.02     0.55±0.04     0.52±0.14                  0.33\n",
-      "{'C': '3.16e-05', 'cycle_bound': 150.0}  0.55±0.02     0.52±0.06     0.62±0.13                  0.34\n",
-      "{'C': '3.16e-05', 'cycle_bound': 175.0}  0.57±0.02     0.56±0.04     0.47±0.19                  0.32\n",
-      "{'C': '3.16e-05', 'cycle_bound': 200.0}  0.56±0.02     0.55±0.03     0.57±0.13                  0.33\n",
-      "{'C': '3.16e-05', 'cycle_bound': 225.0}  0.56±0.02     0.54±0.05     0.56±0.17                  0.32\n",
-      "{'C': '3.16e-05', 'cycle_bound': 250.0}  0.56±0.02     0.54±0.04     0.58±0.18                  0.34\n",
-      "{'C': '3.16e-05', 'cycle_bound': 275.0}  0.56±0.02     0.55±0.04     0.54±0.19                  0.32\n",
-      "{'C': '3.16e-05', 'cycle_bound': 300.0}  0.55±0.02     0.52±0.06     0.59±0.13                  0.36\n",
-      "{'C': '3.16e-05', 'cycle_bound': 325.0}  0.57±0.02     0.55±0.05     0.50±0.14                  0.34\n",
-      "{'C': '3.16e-05', 'cycle_bound': 350.0}  0.56±0.02     0.55±0.05     0.56±0.17                  0.32\n",
-      "{'C': '3.16e-05', 'cycle_bound': 375.0}  0.55±0.02     0.53±0.06     0.61±0.15                  0.33\n",
-      "{'C': '3.16e-05', 'cycle_bound': 400.0}  0.55±0.02     0.52±0.07     0.59±0.13                  0.34\n",
-      "{'C': '3.16e-05', 'cycle_bound': 425.0}  0.56±0.02     0.54±0.06     0.57±0.13                  0.36\n",
-      "{'C': '3.16e-05', 'cycle_bound': 450.0}  0.57±0.02     0.56±0.04     0.50±0.17                  0.37\n",
-      "{'C': '3.16e-05', 'cycle_bound': 475.0}  0.56±0.02     0.55±0.04     0.54±0.16                  0.33\n",
-      "{'C': '3.16e-05', 'cycle_bound': 500.0}  0.56±0.02     0.55±0.05     0.51±0.17                  0.33\n",
-      "{'C': '5.62e-05', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '5.62e-05', 'cycle_bound': 25.0}   0.56±0.02     0.55±0.05     0.54±0.14                  0.24\n",
-      "{'C': '5.62e-05', 'cycle_bound': 50.0}   0.56±0.02     0.55±0.05     0.53±0.15                  0.31\n",
-      "{'C': '5.62e-05', 'cycle_bound': 75.0}   0.56±0.02     0.55±0.03     0.53±0.17                  0.36\n",
-      "{'C': '5.62e-05', 'cycle_bound': 100.0}  0.55±0.02     0.54±0.05     0.59±0.13                  0.33\n",
-      "{'C': '5.62e-05', 'cycle_bound': 125.0}  0.56±0.02     0.55±0.04     0.52±0.14                  0.33\n",
-      "{'C': '5.62e-05', 'cycle_bound': 150.0}  0.55±0.02     0.52±0.06     0.62±0.13                  0.34\n",
-      "{'C': '5.62e-05', 'cycle_bound': 175.0}  0.57±0.02     0.56±0.04     0.47±0.19                  0.32\n",
-      "{'C': '5.62e-05', 'cycle_bound': 200.0}  0.56±0.02     0.55±0.03     0.57±0.13                  0.33\n",
-      "{'C': '5.62e-05', 'cycle_bound': 225.0}  0.56±0.02     0.54±0.05     0.56±0.17                  0.32\n",
-      "{'C': '5.62e-05', 'cycle_bound': 250.0}  0.56±0.02     0.54±0.04     0.58±0.18                  0.34\n",
-      "{'C': '5.62e-05', 'cycle_bound': 275.0}  0.56±0.02     0.55±0.04     0.54±0.19                  0.32\n",
-      "{'C': '5.62e-05', 'cycle_bound': 300.0}  0.55±0.02     0.52±0.06     0.59±0.13                  0.36\n",
-      "{'C': '5.62e-05', 'cycle_bound': 325.0}  0.57±0.02     0.55±0.05     0.50±0.14                  0.34\n",
-      "{'C': '5.62e-05', 'cycle_bound': 350.0}  0.56±0.02     0.55±0.05     0.56±0.17                  0.32\n",
-      "{'C': '5.62e-05', 'cycle_bound': 375.0}  0.55±0.02     0.53±0.06     0.61±0.15                  0.33\n",
-      "{'C': '5.62e-05', 'cycle_bound': 400.0}  0.55±0.02     0.52±0.07     0.59±0.13                  0.34\n",
-      "{'C': '5.62e-05', 'cycle_bound': 425.0}  0.56±0.02     0.54±0.06     0.57±0.13                  0.36\n",
-      "{'C': '5.62e-05', 'cycle_bound': 450.0}  0.57±0.02     0.56±0.04     0.50±0.17                  0.37\n",
-      "{'C': '5.62e-05', 'cycle_bound': 475.0}  0.56±0.02     0.55±0.04     0.54±0.16                  0.33\n",
-      "{'C': '5.62e-05', 'cycle_bound': 500.0}  0.56±0.02     0.55±0.05     0.51±0.17                  0.33\n",
-      "{'C': '1.00e-04', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.00e-04', 'cycle_bound': 25.0}   0.56±0.02     0.55±0.05     0.54±0.14                  0.24\n",
-      "{'C': '1.00e-04', 'cycle_bound': 50.0}   0.56±0.02     0.55±0.05     0.53±0.15                  0.31\n",
-      "{'C': '1.00e-04', 'cycle_bound': 75.0}   0.56±0.02     0.55±0.03     0.53±0.17                  0.36\n",
-      "{'C': '1.00e-04', 'cycle_bound': 100.0}  0.55±0.02     0.54±0.05     0.59±0.13                  0.33\n",
-      "{'C': '1.00e-04', 'cycle_bound': 125.0}  0.56±0.02     0.55±0.04     0.52±0.14                  0.33\n",
-      "{'C': '1.00e-04', 'cycle_bound': 150.0}  0.55±0.02     0.52±0.06     0.62±0.13                  0.34\n",
-      "{'C': '1.00e-04', 'cycle_bound': 175.0}  0.57±0.02     0.56±0.04     0.47±0.19                  0.32\n",
-      "{'C': '1.00e-04', 'cycle_bound': 200.0}  0.56±0.02     0.55±0.03     0.57±0.13                  0.33\n",
-      "{'C': '1.00e-04', 'cycle_bound': 225.0}  0.56±0.02     0.54±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.00e-04', 'cycle_bound': 250.0}  0.56±0.02     0.54±0.04     0.58±0.18                  0.34\n",
-      "{'C': '1.00e-04', 'cycle_bound': 275.0}  0.56±0.02     0.55±0.04     0.54±0.19                  0.32\n",
-      "{'C': '1.00e-04', 'cycle_bound': 300.0}  0.55±0.02     0.52±0.06     0.59±0.13                  0.36\n",
-      "{'C': '1.00e-04', 'cycle_bound': 325.0}  0.57±0.02     0.55±0.05     0.50±0.14                  0.34\n",
-      "{'C': '1.00e-04', 'cycle_bound': 350.0}  0.56±0.02     0.55±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.00e-04', 'cycle_bound': 375.0}  0.55±0.02     0.53±0.06     0.61±0.15                  0.33\n",
-      "{'C': '1.00e-04', 'cycle_bound': 400.0}  0.55±0.02     0.52±0.07     0.59±0.13                  0.34\n",
-      "{'C': '1.00e-04', 'cycle_bound': 425.0}  0.56±0.02     0.54±0.06     0.57±0.13                  0.36\n",
-      "{'C': '1.00e-04', 'cycle_bound': 450.0}  0.57±0.02     0.56±0.04     0.50±0.17                  0.37\n",
-      "{'C': '1.00e-04', 'cycle_bound': 475.0}  0.56±0.02     0.55±0.04     0.54±0.16                  0.33\n",
-      "{'C': '1.00e-04', 'cycle_bound': 500.0}  0.56±0.02     0.55±0.05     0.51±0.17                  0.33\n",
-      "{'C': '1.78e-04', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.78e-04', 'cycle_bound': 25.0}   0.56±0.02     0.55±0.05     0.54±0.14                  0.24\n",
-      "{'C': '1.78e-04', 'cycle_bound': 50.0}   0.56±0.02     0.55±0.05     0.53±0.15                  0.31\n",
-      "{'C': '1.78e-04', 'cycle_bound': 75.0}   0.56±0.02     0.55±0.03     0.53±0.17                  0.36\n",
-      "{'C': '1.78e-04', 'cycle_bound': 100.0}  0.55±0.02     0.54±0.05     0.59±0.13                  0.33\n",
-      "{'C': '1.78e-04', 'cycle_bound': 125.0}  0.56±0.02     0.55±0.04     0.52±0.14                  0.33\n",
-      "{'C': '1.78e-04', 'cycle_bound': 150.0}  0.55±0.02     0.52±0.06     0.62±0.13                  0.34\n",
-      "{'C': '1.78e-04', 'cycle_bound': 175.0}  0.57±0.02     0.56±0.04     0.47±0.19                  0.32\n",
-      "{'C': '1.78e-04', 'cycle_bound': 200.0}  0.56±0.02     0.55±0.03     0.57±0.13                  0.33\n",
-      "{'C': '1.78e-04', 'cycle_bound': 225.0}  0.56±0.02     0.54±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.78e-04', 'cycle_bound': 250.0}  0.56±0.02     0.54±0.04     0.58±0.18                  0.34\n",
-      "{'C': '1.78e-04', 'cycle_bound': 275.0}  0.56±0.02     0.55±0.04     0.54±0.19                  0.32\n",
-      "{'C': '1.78e-04', 'cycle_bound': 300.0}  0.55±0.02     0.52±0.06     0.59±0.13                  0.36\n",
-      "{'C': '1.78e-04', 'cycle_bound': 325.0}  0.57±0.02     0.55±0.05     0.50±0.14                  0.34\n",
-      "{'C': '1.78e-04', 'cycle_bound': 350.0}  0.56±0.02     0.55±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.78e-04', 'cycle_bound': 375.0}  0.55±0.02     0.53±0.06     0.61±0.15                  0.33\n",
-      "{'C': '1.78e-04', 'cycle_bound': 400.0}  0.55±0.02     0.52±0.07     0.59±0.13                  0.34\n",
-      "{'C': '1.78e-04', 'cycle_bound': 425.0}  0.56±0.02     0.54±0.06     0.57±0.13                  0.36\n",
-      "{'C': '1.78e-04', 'cycle_bound': 450.0}  0.57±0.02     0.56±0.04     0.50±0.17                  0.37\n",
-      "{'C': '1.78e-04', 'cycle_bound': 475.0}  0.56±0.02     0.55±0.04     0.54±0.16                  0.33\n",
-      "{'C': '1.78e-04', 'cycle_bound': 500.0}  0.56±0.02     0.55±0.05     0.51±0.17                  0.33\n",
-      "{'C': '3.16e-04', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '3.16e-04', 'cycle_bound': 25.0}   0.56±0.02     0.55±0.05     0.54±0.14                  0.24\n",
-      "{'C': '3.16e-04', 'cycle_bound': 50.0}   0.56±0.02     0.55±0.05     0.53±0.15                  0.31\n",
-      "{'C': '3.16e-04', 'cycle_bound': 75.0}   0.56±0.02     0.55±0.03     0.53±0.17                  0.36\n",
-      "{'C': '3.16e-04', 'cycle_bound': 100.0}  0.55±0.02     0.54±0.05     0.59±0.13                  0.33\n",
-      "{'C': '3.16e-04', 'cycle_bound': 125.0}  0.56±0.02     0.55±0.04     0.52±0.14                  0.33\n",
-      "{'C': '3.16e-04', 'cycle_bound': 150.0}  0.55±0.02     0.52±0.06     0.62±0.13                  0.34\n",
-      "{'C': '3.16e-04', 'cycle_bound': 175.0}  0.57±0.02     0.56±0.04     0.47±0.19                  0.32\n",
-      "{'C': '3.16e-04', 'cycle_bound': 200.0}  0.56±0.02     0.55±0.03     0.57±0.13                  0.33\n",
-      "{'C': '3.16e-04', 'cycle_bound': 225.0}  0.56±0.02     0.54±0.05     0.56±0.17                  0.32\n",
-      "{'C': '3.16e-04', 'cycle_bound': 250.0}  0.56±0.02     0.54±0.04     0.58±0.18                  0.34\n",
-      "{'C': '3.16e-04', 'cycle_bound': 275.0}  0.56±0.02     0.55±0.04     0.54±0.19                  0.32\n",
-      "{'C': '3.16e-04', 'cycle_bound': 300.0}  0.55±0.02     0.52±0.06     0.59±0.13                  0.36\n",
-      "{'C': '3.16e-04', 'cycle_bound': 325.0}  0.57±0.02     0.55±0.05     0.50±0.14                  0.34\n",
-      "{'C': '3.16e-04', 'cycle_bound': 350.0}  0.56±0.02     0.55±0.05     0.56±0.17                  0.32\n",
-      "{'C': '3.16e-04', 'cycle_bound': 375.0}  0.55±0.02     0.53±0.06     0.61±0.15                  0.33\n",
-      "{'C': '3.16e-04', 'cycle_bound': 400.0}  0.55±0.02     0.52±0.07     0.59±0.13                  0.34\n",
-      "{'C': '3.16e-04', 'cycle_bound': 425.0}  0.56±0.02     0.54±0.06     0.57±0.13                  0.36\n",
-      "{'C': '3.16e-04', 'cycle_bound': 450.0}  0.57±0.02     0.56±0.04     0.50±0.17                  0.37\n",
-      "{'C': '3.16e-04', 'cycle_bound': 475.0}  0.56±0.02     0.55±0.04     0.54±0.16                  0.33\n",
-      "{'C': '3.16e-04', 'cycle_bound': 500.0}  0.56±0.02     0.55±0.05     0.51±0.17                  0.33\n",
-      "{'C': '5.62e-04', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '5.62e-04', 'cycle_bound': 25.0}   0.56±0.02     0.55±0.05     0.54±0.14                  0.24\n",
-      "{'C': '5.62e-04', 'cycle_bound': 50.0}   0.56±0.02     0.55±0.05     0.53±0.15                  0.31\n",
-      "{'C': '5.62e-04', 'cycle_bound': 75.0}   0.56±0.02     0.55±0.03     0.53±0.17                  0.36\n",
-      "{'C': '5.62e-04', 'cycle_bound': 100.0}  0.55±0.02     0.54±0.05     0.59±0.13                  0.33\n",
-      "{'C': '5.62e-04', 'cycle_bound': 125.0}  0.56±0.02     0.55±0.04     0.52±0.14                  0.33\n",
-      "{'C': '5.62e-04', 'cycle_bound': 150.0}  0.55±0.02     0.52±0.06     0.62±0.13                  0.34\n",
-      "{'C': '5.62e-04', 'cycle_bound': 175.0}  0.57±0.02     0.56±0.04     0.47±0.19                  0.32\n",
-      "{'C': '5.62e-04', 'cycle_bound': 200.0}  0.56±0.02     0.55±0.03     0.57±0.13                  0.33\n",
-      "{'C': '5.62e-04', 'cycle_bound': 225.0}  0.56±0.02     0.54±0.05     0.56±0.17                  0.32\n",
-      "{'C': '5.62e-04', 'cycle_bound': 250.0}  0.56±0.02     0.54±0.04     0.58±0.18                  0.34\n",
-      "{'C': '5.62e-04', 'cycle_bound': 275.0}  0.56±0.02     0.55±0.04     0.54±0.19                  0.32\n",
-      "{'C': '5.62e-04', 'cycle_bound': 300.0}  0.55±0.02     0.52±0.06     0.59±0.13                  0.36\n",
-      "{'C': '5.62e-04', 'cycle_bound': 325.0}  0.57±0.02     0.55±0.05     0.50±0.14                  0.34\n",
-      "{'C': '5.62e-04', 'cycle_bound': 350.0}  0.56±0.02     0.55±0.05     0.56±0.17                  0.32\n",
-      "{'C': '5.62e-04', 'cycle_bound': 375.0}  0.55±0.02     0.53±0.06     0.61±0.15                  0.33\n",
-      "{'C': '5.62e-04', 'cycle_bound': 400.0}  0.55±0.02     0.52±0.07     0.59±0.13                  0.34\n",
-      "{'C': '5.62e-04', 'cycle_bound': 425.0}  0.56±0.02     0.54±0.06     0.57±0.13                  0.36\n",
-      "{'C': '5.62e-04', 'cycle_bound': 450.0}  0.57±0.02     0.56±0.04     0.50±0.17                  0.37\n",
-      "{'C': '5.62e-04', 'cycle_bound': 475.0}  0.56±0.02     0.55±0.04     0.54±0.16                  0.33\n",
-      "{'C': '5.62e-04', 'cycle_bound': 500.0}  0.56±0.02     0.55±0.05     0.51±0.17                  0.33\n",
-      "{'C': '1.00e-03', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.00e-03', 'cycle_bound': 25.0}   0.56±0.02     0.55±0.05     0.54±0.14                  0.24\n",
-      "{'C': '1.00e-03', 'cycle_bound': 50.0}   0.56±0.02     0.55±0.05     0.53±0.15                  0.31\n",
-      "{'C': '1.00e-03', 'cycle_bound': 75.0}   0.56±0.02     0.55±0.03     0.53±0.17                  0.36\n",
-      "{'C': '1.00e-03', 'cycle_bound': 100.0}  0.55±0.02     0.54±0.05     0.59±0.13                  0.33\n",
-      "{'C': '1.00e-03', 'cycle_bound': 125.0}  0.56±0.02     0.55±0.04     0.52±0.14                  0.33\n",
-      "{'C': '1.00e-03', 'cycle_bound': 150.0}  0.55±0.02     0.52±0.06     0.62±0.13                  0.34\n",
-      "{'C': '1.00e-03', 'cycle_bound': 175.0}  0.57±0.02     0.56±0.04     0.47±0.19                  0.32\n",
-      "{'C': '1.00e-03', 'cycle_bound': 200.0}  0.56±0.02     0.55±0.03     0.57±0.13                  0.33\n",
-      "{'C': '1.00e-03', 'cycle_bound': 225.0}  0.56±0.02     0.54±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.00e-03', 'cycle_bound': 250.0}  0.56±0.02     0.54±0.04     0.58±0.18                  0.34\n",
-      "{'C': '1.00e-03', 'cycle_bound': 275.0}  0.56±0.02     0.55±0.04     0.54±0.19                  0.32\n",
-      "{'C': '1.00e-03', 'cycle_bound': 300.0}  0.55±0.02     0.52±0.06     0.59±0.13                  0.36\n",
-      "{'C': '1.00e-03', 'cycle_bound': 325.0}  0.57±0.02     0.55±0.05     0.50±0.14                  0.34\n",
-      "{'C': '1.00e-03', 'cycle_bound': 350.0}  0.56±0.02     0.55±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.00e-03', 'cycle_bound': 375.0}  0.55±0.02     0.53±0.06     0.61±0.15                  0.33\n",
-      "{'C': '1.00e-03', 'cycle_bound': 400.0}  0.55±0.02     0.52±0.07     0.59±0.13                  0.34\n",
-      "{'C': '1.00e-03', 'cycle_bound': 425.0}  0.56±0.02     0.54±0.06     0.57±0.13                  0.36\n",
-      "{'C': '1.00e-03', 'cycle_bound': 450.0}  0.57±0.02     0.56±0.04     0.50±0.17                  0.37\n",
-      "{'C': '1.00e-03', 'cycle_bound': 475.0}  0.56±0.02     0.55±0.04     0.54±0.16                  0.33\n",
-      "{'C': '1.00e-03', 'cycle_bound': 500.0}  0.56±0.02     0.55±0.05     0.51±0.17                  0.33\n",
-      "{'C': '1.78e-03', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.78e-03', 'cycle_bound': 25.0}   0.56±0.02     0.55±0.05     0.54±0.14                  0.24\n",
-      "{'C': '1.78e-03', 'cycle_bound': 50.0}   0.56±0.02     0.55±0.05     0.53±0.15                  0.31\n",
-      "{'C': '1.78e-03', 'cycle_bound': 75.0}   0.56±0.02     0.55±0.03     0.53±0.17                  0.36\n",
-      "{'C': '1.78e-03', 'cycle_bound': 100.0}  0.55±0.02     0.54±0.05     0.59±0.13                  0.33\n",
-      "{'C': '1.78e-03', 'cycle_bound': 125.0}  0.56±0.02     0.55±0.04     0.52±0.14                  0.33\n",
-      "{'C': '1.78e-03', 'cycle_bound': 150.0}  0.55±0.02     0.52±0.06     0.62±0.13                  0.34\n",
-      "{'C': '1.78e-03', 'cycle_bound': 175.0}  0.57±0.02     0.56±0.04     0.47±0.19                  0.32\n",
-      "{'C': '1.78e-03', 'cycle_bound': 200.0}  0.56±0.02     0.55±0.03     0.57±0.13                  0.33\n",
-      "{'C': '1.78e-03', 'cycle_bound': 225.0}  0.56±0.02     0.54±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.78e-03', 'cycle_bound': 250.0}  0.56±0.02     0.54±0.04     0.58±0.18                  0.34\n",
-      "{'C': '1.78e-03', 'cycle_bound': 275.0}  0.56±0.02     0.55±0.04     0.54±0.19                  0.32\n",
-      "{'C': '1.78e-03', 'cycle_bound': 300.0}  0.55±0.02     0.52±0.06     0.59±0.13                  0.36\n",
-      "{'C': '1.78e-03', 'cycle_bound': 325.0}  0.57±0.02     0.55±0.05     0.50±0.14                  0.34\n",
-      "{'C': '1.78e-03', 'cycle_bound': 350.0}  0.56±0.02     0.55±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.78e-03', 'cycle_bound': 375.0}  0.55±0.02     0.53±0.06     0.61±0.15                  0.33\n",
-      "{'C': '1.78e-03', 'cycle_bound': 400.0}  0.55±0.02     0.52±0.07     0.59±0.13                  0.34\n",
-      "{'C': '1.78e-03', 'cycle_bound': 425.0}  0.56±0.02     0.54±0.06     0.57±0.13                  0.36\n",
-      "{'C': '1.78e-03', 'cycle_bound': 450.0}  0.57±0.02     0.56±0.04     0.50±0.17                  0.37\n",
-      "{'C': '1.78e-03', 'cycle_bound': 475.0}  0.56±0.02     0.55±0.04     0.54±0.16                  0.33\n",
-      "{'C': '1.78e-03', 'cycle_bound': 500.0}  0.56±0.02     0.55±0.05     0.51±0.17                  0.33\n",
-      "{'C': '3.16e-03', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '3.16e-03', 'cycle_bound': 25.0}   0.56±0.02     0.55±0.05     0.54±0.14                  0.24\n",
-      "{'C': '3.16e-03', 'cycle_bound': 50.0}   0.56±0.02     0.55±0.05     0.53±0.15                  0.31\n",
-      "{'C': '3.16e-03', 'cycle_bound': 75.0}   0.56±0.02     0.55±0.03     0.53±0.17                  0.36\n",
-      "{'C': '3.16e-03', 'cycle_bound': 100.0}  0.55±0.02     0.54±0.05     0.59±0.13                  0.33\n",
-      "{'C': '3.16e-03', 'cycle_bound': 125.0}  0.56±0.02     0.55±0.04     0.52±0.14                  0.33\n",
-      "{'C': '3.16e-03', 'cycle_bound': 150.0}  0.55±0.02     0.52±0.06     0.62±0.13                  0.34\n",
-      "{'C': '3.16e-03', 'cycle_bound': 175.0}  0.57±0.02     0.56±0.04     0.47±0.19                  0.32\n",
-      "{'C': '3.16e-03', 'cycle_bound': 200.0}  0.56±0.02     0.55±0.03     0.57±0.13                  0.33\n",
-      "{'C': '3.16e-03', 'cycle_bound': 225.0}  0.56±0.02     0.54±0.05     0.56±0.17                  0.32\n",
-      "{'C': '3.16e-03', 'cycle_bound': 250.0}  0.56±0.02     0.54±0.04     0.58±0.18                  0.34\n",
-      "{'C': '3.16e-03', 'cycle_bound': 275.0}  0.56±0.02     0.55±0.04     0.54±0.19                  0.32\n",
-      "{'C': '3.16e-03', 'cycle_bound': 300.0}  0.55±0.02     0.52±0.06     0.59±0.13                  0.36\n",
-      "{'C': '3.16e-03', 'cycle_bound': 325.0}  0.57±0.02     0.55±0.05     0.50±0.14                  0.34\n",
-      "{'C': '3.16e-03', 'cycle_bound': 350.0}  0.56±0.02     0.55±0.05     0.56±0.17                  0.32\n",
-      "{'C': '3.16e-03', 'cycle_bound': 375.0}  0.55±0.02     0.53±0.06     0.61±0.15                  0.33\n",
-      "{'C': '3.16e-03', 'cycle_bound': 400.0}  0.55±0.02     0.52±0.07     0.59±0.13                  0.34\n",
-      "{'C': '3.16e-03', 'cycle_bound': 425.0}  0.56±0.02     0.54±0.06     0.57±0.13                  0.36\n",
-      "{'C': '3.16e-03', 'cycle_bound': 450.0}  0.57±0.02     0.56±0.04     0.50±0.17                  0.37\n",
-      "{'C': '3.16e-03', 'cycle_bound': 475.0}  0.56±0.02     0.55±0.04     0.54±0.16                  0.33\n",
-      "{'C': '3.16e-03', 'cycle_bound': 500.0}  0.56±0.02     0.55±0.05     0.51±0.17                  0.33\n",
-      "{'C': '5.62e-03', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '5.62e-03', 'cycle_bound': 25.0}   0.56±0.02     0.55±0.05     0.54±0.14                  0.24\n",
-      "{'C': '5.62e-03', 'cycle_bound': 50.0}   0.56±0.02     0.55±0.05     0.53±0.15                  0.31\n",
-      "{'C': '5.62e-03', 'cycle_bound': 75.0}   0.56±0.02     0.55±0.03     0.53±0.17                  0.36\n",
-      "{'C': '5.62e-03', 'cycle_bound': 100.0}  0.55±0.02     0.54±0.05     0.59±0.13                  0.33\n",
-      "{'C': '5.62e-03', 'cycle_bound': 125.0}  0.56±0.02     0.55±0.04     0.52±0.14                  0.33\n",
-      "{'C': '5.62e-03', 'cycle_bound': 150.0}  0.55±0.02     0.52±0.06     0.62±0.13                  0.34\n",
-      "{'C': '5.62e-03', 'cycle_bound': 175.0}  0.57±0.02     0.56±0.04     0.47±0.19                  0.32\n",
-      "{'C': '5.62e-03', 'cycle_bound': 200.0}  0.56±0.02     0.55±0.03     0.57±0.13                  0.33\n",
-      "{'C': '5.62e-03', 'cycle_bound': 225.0}  0.56±0.02     0.54±0.05     0.56±0.17                  0.32\n",
-      "{'C': '5.62e-03', 'cycle_bound': 250.0}  0.56±0.02     0.54±0.04     0.58±0.18                  0.34\n",
-      "{'C': '5.62e-03', 'cycle_bound': 275.0}  0.56±0.02     0.55±0.04     0.54±0.19                  0.32\n",
-      "{'C': '5.62e-03', 'cycle_bound': 300.0}  0.55±0.02     0.52±0.06     0.59±0.13                  0.36\n",
-      "{'C': '5.62e-03', 'cycle_bound': 325.0}  0.57±0.02     0.55±0.05     0.50±0.14                  0.34\n",
-      "{'C': '5.62e-03', 'cycle_bound': 350.0}  0.56±0.02     0.55±0.05     0.56±0.17                  0.32\n",
-      "{'C': '5.62e-03', 'cycle_bound': 375.0}  0.55±0.02     0.53±0.06     0.61±0.15                  0.33\n",
-      "{'C': '5.62e-03', 'cycle_bound': 400.0}  0.55±0.02     0.52±0.07     0.59±0.13                  0.34\n",
-      "{'C': '5.62e-03', 'cycle_bound': 425.0}  0.56±0.02     0.54±0.06     0.57±0.13                  0.36\n",
-      "{'C': '5.62e-03', 'cycle_bound': 450.0}  0.57±0.02     0.56±0.04     0.50±0.17                  0.37\n",
-      "{'C': '5.62e-03', 'cycle_bound': 475.0}  0.56±0.02     0.55±0.04     0.54±0.16                  0.33\n",
-      "{'C': '5.62e-03', 'cycle_bound': 500.0}  0.56±0.02     0.55±0.05     0.51±0.17                  0.33\n",
-      "{'C': '1.00e-02', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.00e-02', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '1.00e-02', 'cycle_bound': 50.0}   0.57±0.02     0.56±0.02     0.55±0.17                  0.31\n",
-      "{'C': '1.00e-02', 'cycle_bound': 75.0}   0.56±0.02     0.55±0.03     0.53±0.17                  0.36\n",
-      "{'C': '1.00e-02', 'cycle_bound': 100.0}  0.55±0.02     0.54±0.05     0.59±0.13                  0.33\n",
-      "{'C': '1.00e-02', 'cycle_bound': 125.0}  0.56±0.02     0.55±0.04     0.52±0.14                  0.33\n",
-      "{'C': '1.00e-02', 'cycle_bound': 150.0}  0.55±0.02     0.52±0.06     0.62±0.13                  0.34\n",
-      "{'C': '1.00e-02', 'cycle_bound': 175.0}  0.57±0.02     0.56±0.04     0.47±0.19                  0.32\n",
-      "{'C': '1.00e-02', 'cycle_bound': 200.0}  0.56±0.02     0.55±0.03     0.57±0.13                  0.33\n",
-      "{'C': '1.00e-02', 'cycle_bound': 225.0}  0.56±0.02     0.54±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.00e-02', 'cycle_bound': 250.0}  0.56±0.02     0.54±0.04     0.58±0.18                  0.34\n",
-      "{'C': '1.00e-02', 'cycle_bound': 275.0}  0.56±0.02     0.55±0.04     0.54±0.19                  0.32\n",
-      "{'C': '1.00e-02', 'cycle_bound': 300.0}  0.55±0.02     0.52±0.06     0.59±0.13                  0.36\n",
-      "{'C': '1.00e-02', 'cycle_bound': 325.0}  0.57±0.02     0.55±0.05     0.50±0.14                  0.34\n",
-      "{'C': '1.00e-02', 'cycle_bound': 350.0}  0.56±0.02     0.55±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.00e-02', 'cycle_bound': 375.0}  0.55±0.02     0.53±0.06     0.61±0.15                  0.33\n",
-      "{'C': '1.00e-02', 'cycle_bound': 400.0}  0.55±0.02     0.52±0.07     0.59±0.13                  0.34\n",
-      "{'C': '1.00e-02', 'cycle_bound': 425.0}  0.56±0.02     0.54±0.06     0.57±0.13                  0.36\n",
-      "{'C': '1.00e-02', 'cycle_bound': 450.0}  0.57±0.02     0.56±0.04     0.50±0.17                  0.37\n",
-      "{'C': '1.00e-02', 'cycle_bound': 475.0}  0.56±0.02     0.55±0.04     0.54±0.16                  0.33\n",
-      "{'C': '1.00e-02', 'cycle_bound': 500.0}  0.56±0.02     0.55±0.05     0.51±0.17                  0.33\n",
-      "{'C': '1.78e-02', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.78e-02', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '1.78e-02', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '1.78e-02', 'cycle_bound': 75.0}   0.56±0.02     0.55±0.03     0.53±0.17                  0.36\n",
-      "{'C': '1.78e-02', 'cycle_bound': 100.0}  0.55±0.02     0.54±0.05     0.59±0.13                  0.33\n",
-      "{'C': '1.78e-02', 'cycle_bound': 125.0}  0.56±0.02     0.55±0.04     0.52±0.14                  0.33\n",
-      "{'C': '1.78e-02', 'cycle_bound': 150.0}  0.55±0.02     0.52±0.06     0.62±0.13                  0.34\n",
-      "{'C': '1.78e-02', 'cycle_bound': 175.0}  0.57±0.02     0.56±0.04     0.47±0.19                  0.32\n",
-      "{'C': '1.78e-02', 'cycle_bound': 200.0}  0.56±0.02     0.55±0.03     0.57±0.13                  0.33\n",
-      "{'C': '1.78e-02', 'cycle_bound': 225.0}  0.56±0.02     0.54±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.78e-02', 'cycle_bound': 250.0}  0.56±0.02     0.54±0.04     0.58±0.18                  0.34\n",
-      "{'C': '1.78e-02', 'cycle_bound': 275.0}  0.56±0.02     0.55±0.04     0.54±0.19                  0.32\n",
-      "{'C': '1.78e-02', 'cycle_bound': 300.0}  0.55±0.02     0.52±0.06     0.59±0.13                  0.36\n",
-      "{'C': '1.78e-02', 'cycle_bound': 325.0}  0.57±0.02     0.55±0.05     0.50±0.14                  0.34\n",
-      "{'C': '1.78e-02', 'cycle_bound': 350.0}  0.56±0.02     0.55±0.05     0.56±0.17                  0.32\n",
-      "{'C': '1.78e-02', 'cycle_bound': 375.0}  0.55±0.02     0.53±0.06     0.61±0.15                  0.33\n",
-      "{'C': '1.78e-02', 'cycle_bound': 400.0}  0.55±0.02     0.52±0.07     0.59±0.13                  0.34\n",
-      "{'C': '1.78e-02', 'cycle_bound': 425.0}  0.56±0.02     0.54±0.06     0.57±0.13                  0.36\n",
-      "{'C': '1.78e-02', 'cycle_bound': 450.0}  0.57±0.02     0.56±0.04     0.50±0.17                  0.37\n",
-      "{'C': '1.78e-02', 'cycle_bound': 475.0}  0.56±0.02     0.55±0.04     0.54±0.16                  0.33\n",
-      "{'C': '1.78e-02', 'cycle_bound': 500.0}  0.56±0.02     0.55±0.05     0.51±0.17                  0.33\n",
-      "{'C': '3.16e-02', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '3.16e-02', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '3.16e-02', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '3.16e-02', 'cycle_bound': 75.0}   0.56±0.02     0.55±0.03     0.53±0.17                  0.36\n",
-      "{'C': '3.16e-02', 'cycle_bound': 100.0}  0.55±0.02     0.54±0.05     0.59±0.13                  0.33\n",
-      "{'C': '3.16e-02', 'cycle_bound': 125.0}  0.56±0.02     0.55±0.04     0.52±0.14                  0.33\n",
-      "{'C': '3.16e-02', 'cycle_bound': 150.0}  0.55±0.02     0.52±0.06     0.62±0.13                  0.34\n",
-      "{'C': '3.16e-02', 'cycle_bound': 175.0}  0.57±0.02     0.56±0.04     0.47±0.19                  0.32\n",
-      "{'C': '3.16e-02', 'cycle_bound': 200.0}  0.56±0.02     0.55±0.03     0.57±0.13                  0.33\n",
-      "{'C': '3.16e-02', 'cycle_bound': 225.0}  0.56±0.02     0.54±0.05     0.56±0.17                  0.32\n",
-      "{'C': '3.16e-02', 'cycle_bound': 250.0}  0.56±0.02     0.54±0.04     0.58±0.18                  0.34\n",
-      "{'C': '3.16e-02', 'cycle_bound': 275.0}  0.56±0.02     0.55±0.04     0.54±0.19                  0.32\n",
-      "{'C': '3.16e-02', 'cycle_bound': 300.0}  0.55±0.02     0.52±0.06     0.59±0.13                  0.36\n",
-      "{'C': '3.16e-02', 'cycle_bound': 325.0}  0.57±0.02     0.55±0.05     0.50±0.14                  0.34\n",
-      "{'C': '3.16e-02', 'cycle_bound': 350.0}  0.56±0.02     0.55±0.05     0.56±0.17                  0.32\n",
-      "{'C': '3.16e-02', 'cycle_bound': 375.0}  0.55±0.02     0.53±0.06     0.61±0.15                  0.33\n",
-      "{'C': '3.16e-02', 'cycle_bound': 400.0}  0.55±0.02     0.52±0.07     0.59±0.13                  0.34\n",
-      "{'C': '3.16e-02', 'cycle_bound': 425.0}  0.56±0.02     0.54±0.06     0.57±0.13                  0.36\n",
-      "{'C': '3.16e-02', 'cycle_bound': 450.0}  0.57±0.02     0.56±0.04     0.50±0.17                  0.37\n",
-      "{'C': '3.16e-02', 'cycle_bound': 475.0}  0.56±0.02     0.55±0.04     0.54±0.16                  0.33\n",
-      "{'C': '3.16e-02', 'cycle_bound': 500.0}  0.56±0.02     0.55±0.05     0.51±0.17                  0.33\n",
-      "{'C': '5.62e-02', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '5.62e-02', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '5.62e-02', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '5.62e-02', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '5.62e-02', 'cycle_bound': 100.0}  0.62±0.02     0.61±0.04     0.58±0.17                  0.33\n",
-      "{'C': '5.62e-02', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.56±0.17                  0.33\n",
-      "{'C': '5.62e-02', 'cycle_bound': 150.0}  0.61±0.02     0.60±0.05     0.61±0.18                  0.34\n",
-      "{'C': '5.62e-02', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.03     0.59±0.19                  0.32\n",
-      "{'C': '5.62e-02', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '5.62e-02', 'cycle_bound': 225.0}  0.62±0.02     0.61±0.03     0.62±0.18                  0.32\n",
-      "{'C': '5.62e-02', 'cycle_bound': 250.0}  0.62±0.02     0.61±0.03     0.60±0.14                  0.34\n",
-      "{'C': '5.62e-02', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.03     0.64±0.17                  0.32\n",
-      "{'C': '5.62e-02', 'cycle_bound': 300.0}  0.61±0.02     0.59±0.03     0.65±0.17                  0.36\n",
-      "{'C': '5.62e-02', 'cycle_bound': 325.0}  0.61±0.02     0.60±0.03     0.65±0.17                  0.34\n",
-      "{'C': '5.62e-02', 'cycle_bound': 350.0}  0.61±0.01     0.61±0.02     0.62±0.14                  0.32\n",
-      "{'C': '5.62e-02', 'cycle_bound': 375.0}  0.61±0.02     0.60±0.04     0.62±0.15                  0.33\n",
-      "{'C': '5.62e-02', 'cycle_bound': 400.0}  0.62±0.03     0.60±0.05     0.56±0.19                  0.34\n",
-      "{'C': '5.62e-02', 'cycle_bound': 425.0}  0.61±0.02     0.61±0.04     0.63±0.20                  0.36\n",
-      "{'C': '5.62e-02', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.59±0.17                  0.37\n",
-      "{'C': '5.62e-02', 'cycle_bound': 475.0}  0.61±0.02     0.61±0.03     0.63±0.18                  0.33\n",
-      "{'C': '5.62e-02', 'cycle_bound': 500.0}  0.62±0.02     0.61±0.03     0.59±0.20                  0.33\n",
-      "{'C': '1.00e-01', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.00e-01', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '1.00e-01', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '1.00e-01', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '1.00e-01', 'cycle_bound': 100.0}  0.62±0.02     0.61±0.04     0.58±0.17                  0.33\n",
-      "{'C': '1.00e-01', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.56±0.17                  0.33\n",
-      "{'C': '1.00e-01', 'cycle_bound': 150.0}  0.61±0.02     0.60±0.05     0.61±0.18                  0.34\n",
-      "{'C': '1.00e-01', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.03     0.59±0.19                  0.32\n",
-      "{'C': '1.00e-01', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '1.00e-01', 'cycle_bound': 225.0}  0.62±0.02     0.61±0.03     0.62±0.18                  0.32\n",
-      "{'C': '1.00e-01', 'cycle_bound': 250.0}  0.62±0.02     0.61±0.03     0.60±0.14                  0.34\n",
-      "{'C': '1.00e-01', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.03     0.64±0.17                  0.32\n",
-      "{'C': '1.00e-01', 'cycle_bound': 300.0}  0.61±0.02     0.59±0.03     0.65±0.17                  0.36\n",
-      "{'C': '1.00e-01', 'cycle_bound': 325.0}  0.61±0.02     0.60±0.03     0.65±0.17                  0.34\n",
-      "{'C': '1.00e-01', 'cycle_bound': 350.0}  0.61±0.01     0.61±0.02     0.62±0.14                  0.32\n",
-      "{'C': '1.00e-01', 'cycle_bound': 375.0}  0.61±0.02     0.60±0.04     0.62±0.15                  0.33\n",
-      "{'C': '1.00e-01', 'cycle_bound': 400.0}  0.62±0.03     0.60±0.05     0.56±0.19                  0.34\n",
-      "{'C': '1.00e-01', 'cycle_bound': 425.0}  0.61±0.02     0.61±0.04     0.63±0.20                  0.36\n",
-      "{'C': '1.00e-01', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.59±0.17                  0.37\n",
-      "{'C': '1.00e-01', 'cycle_bound': 475.0}  0.61±0.02     0.61±0.03     0.63±0.18                  0.33\n",
-      "{'C': '1.00e-01', 'cycle_bound': 500.0}  0.62±0.02     0.61±0.03     0.59±0.20                  0.33\n",
-      "{'C': '1.78e-01', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.78e-01', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '1.78e-01', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '1.78e-01', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '1.78e-01', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '1.78e-01', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '1.78e-01', 'cycle_bound': 150.0}  0.62±0.02     0.60±0.05     0.61±0.18                  0.34\n",
-      "{'C': '1.78e-01', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.03     0.59±0.19                  0.32\n",
-      "{'C': '1.78e-01', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '1.78e-01', 'cycle_bound': 225.0}  0.62±0.02     0.61±0.03     0.62±0.18                  0.32\n",
-      "{'C': '1.78e-01', 'cycle_bound': 250.0}  0.62±0.02     0.61±0.03     0.61±0.14                  0.34\n",
-      "{'C': '1.78e-01', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.03     0.64±0.17                  0.32\n",
-      "{'C': '1.78e-01', 'cycle_bound': 300.0}  0.61±0.02     0.60±0.03     0.66±0.16                  0.36\n",
-      "{'C': '1.78e-01', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '1.78e-01', 'cycle_bound': 350.0}  0.62±0.01     0.61±0.02     0.63±0.13                  0.32\n",
-      "{'C': '1.78e-01', 'cycle_bound': 375.0}  0.61±0.02     0.61±0.03     0.63±0.15                  0.33\n",
-      "{'C': '1.78e-01', 'cycle_bound': 400.0}  0.62±0.03     0.61±0.04     0.57±0.19                  0.34\n",
-      "{'C': '1.78e-01', 'cycle_bound': 425.0}  0.61±0.03     0.61±0.04     0.63±0.20                  0.36\n",
-      "{'C': '1.78e-01', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '1.78e-01', 'cycle_bound': 475.0}  0.62±0.02     0.61±0.03     0.63±0.18                  0.33\n",
-      "{'C': '1.78e-01', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.33\n",
-      "{'C': '3.16e-01', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '3.16e-01', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '3.16e-01', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '3.16e-01', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '3.16e-01', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '3.16e-01', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '3.16e-01', 'cycle_bound': 150.0}  0.62±0.02     0.61±0.03     0.62±0.19                  0.34\n",
-      "{'C': '3.16e-01', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '3.16e-01', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '3.16e-01', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '3.16e-01', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '3.16e-01', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '3.16e-01', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '3.16e-01', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '3.16e-01', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '3.16e-01', 'cycle_bound': 375.0}  0.62±0.02     0.61±0.02     0.63±0.15                  0.33\n",
-      "{'C': '3.16e-01', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.03     0.59±0.19                  0.34\n",
-      "{'C': '3.16e-01', 'cycle_bound': 425.0}  0.62±0.02     0.61±0.03     0.64±0.20                  0.36\n",
-      "{'C': '3.16e-01', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '3.16e-01', 'cycle_bound': 475.0}  0.62±0.02     0.61±0.03     0.63±0.18                  0.33\n",
-      "{'C': '3.16e-01', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '5.62e-01', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '5.62e-01', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '5.62e-01', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '5.62e-01', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '5.62e-01', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '5.62e-01', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '5.62e-01', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '5.62e-01', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '5.62e-01', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '5.62e-01', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '5.62e-01', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '5.62e-01', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '5.62e-01', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '5.62e-01', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '5.62e-01', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '5.62e-01', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '5.62e-01', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '5.62e-01', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '5.62e-01', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '5.62e-01', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '5.62e-01', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '1.00e+00', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.00e+00', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '1.00e+00', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '1.00e+00', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '1.00e+00', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '1.00e+00', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '1.00e+00', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '1.00e+00', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '1.00e+00', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '1.00e+00', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '1.00e+00', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '1.00e+00', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '1.00e+00', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '1.00e+00', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '1.00e+00', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '1.00e+00', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '1.00e+00', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '1.00e+00', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '1.00e+00', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '1.00e+00', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '1.00e+00', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '1.78e+00', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.78e+00', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '1.78e+00', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '1.78e+00', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '1.78e+00', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '1.78e+00', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '1.78e+00', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '1.78e+00', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '1.78e+00', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '1.78e+00', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '1.78e+00', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '1.78e+00', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '1.78e+00', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '1.78e+00', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '1.78e+00', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '1.78e+00', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '1.78e+00', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '1.78e+00', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '1.78e+00', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '1.78e+00', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '1.78e+00', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '3.16e+00', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '3.16e+00', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '3.16e+00', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '3.16e+00', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '3.16e+00', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '3.16e+00', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '3.16e+00', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '3.16e+00', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '3.16e+00', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '3.16e+00', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '3.16e+00', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '3.16e+00', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '3.16e+00', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '3.16e+00', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '3.16e+00', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '3.16e+00', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '3.16e+00', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '3.16e+00', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '3.16e+00', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '3.16e+00', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '3.16e+00', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '5.62e+00', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '5.62e+00', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '5.62e+00', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '5.62e+00', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '5.62e+00', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '5.62e+00', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '5.62e+00', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '5.62e+00', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '5.62e+00', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '5.62e+00', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '5.62e+00', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '5.62e+00', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '5.62e+00', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '5.62e+00', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '5.62e+00', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '5.62e+00', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '5.62e+00', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '5.62e+00', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '5.62e+00', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '5.62e+00', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '5.62e+00', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '1.00e+01', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.00e+01', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '1.00e+01', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '1.00e+01', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '1.00e+01', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '1.00e+01', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '1.00e+01', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '1.00e+01', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '1.00e+01', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '1.00e+01', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '1.00e+01', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '1.00e+01', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '1.00e+01', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '1.00e+01', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '1.00e+01', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '1.00e+01', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '1.00e+01', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '1.00e+01', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '1.00e+01', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '1.00e+01', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '1.00e+01', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '1.78e+01', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.78e+01', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '1.78e+01', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '1.78e+01', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '1.78e+01', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '1.78e+01', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '1.78e+01', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '1.78e+01', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '1.78e+01', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '1.78e+01', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '1.78e+01', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '1.78e+01', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '1.78e+01', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '1.78e+01', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '1.78e+01', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '1.78e+01', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '1.78e+01', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '1.78e+01', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '1.78e+01', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '1.78e+01', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '1.78e+01', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '3.16e+01', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '3.16e+01', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '3.16e+01', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '3.16e+01', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '3.16e+01', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '3.16e+01', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '3.16e+01', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '3.16e+01', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '3.16e+01', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '3.16e+01', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '3.16e+01', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '3.16e+01', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '3.16e+01', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '3.16e+01', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '3.16e+01', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '3.16e+01', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '3.16e+01', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '3.16e+01', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '3.16e+01', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '3.16e+01', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '3.16e+01', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '5.62e+01', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '5.62e+01', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '5.62e+01', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '5.62e+01', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '5.62e+01', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '5.62e+01', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '5.62e+01', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '5.62e+01', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '5.62e+01', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '5.62e+01', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '5.62e+01', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '5.62e+01', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '5.62e+01', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '5.62e+01', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '5.62e+01', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '5.62e+01', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '5.62e+01', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '5.62e+01', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '5.62e+01', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '5.62e+01', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '5.62e+01', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '1.00e+02', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.00e+02', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '1.00e+02', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '1.00e+02', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '1.00e+02', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '1.00e+02', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '1.00e+02', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '1.00e+02', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '1.00e+02', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '1.00e+02', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '1.00e+02', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '1.00e+02', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '1.00e+02', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '1.00e+02', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '1.00e+02', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '1.00e+02', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '1.00e+02', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '1.00e+02', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '1.00e+02', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '1.00e+02', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '1.00e+02', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '1.78e+02', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.78e+02', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '1.78e+02', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '1.78e+02', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '1.78e+02', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '1.78e+02', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '1.78e+02', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '1.78e+02', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '1.78e+02', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '1.78e+02', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '1.78e+02', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '1.78e+02', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '1.78e+02', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '1.78e+02', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '1.78e+02', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '1.78e+02', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '1.78e+02', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '1.78e+02', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '1.78e+02', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '1.78e+02', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '1.78e+02', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '3.16e+02', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '3.16e+02', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '3.16e+02', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '3.16e+02', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '3.16e+02', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '3.16e+02', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '3.16e+02', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '3.16e+02', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '3.16e+02', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '3.16e+02', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '3.16e+02', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '3.16e+02', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '3.16e+02', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '3.16e+02', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '3.16e+02', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '3.16e+02', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '3.16e+02', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '3.16e+02', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '3.16e+02', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '3.16e+02', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '3.16e+02', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '5.62e+02', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '5.62e+02', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '5.62e+02', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '5.62e+02', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '5.62e+02', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '5.62e+02', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '5.62e+02', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '5.62e+02', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '5.62e+02', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '5.62e+02', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '5.62e+02', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '5.62e+02', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '5.62e+02', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '5.62e+02', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '5.62e+02', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '5.62e+02', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '5.62e+02', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '5.62e+02', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '5.62e+02', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '5.62e+02', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '5.62e+02', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '1.00e+03', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.00e+03', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '1.00e+03', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '1.00e+03', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '1.00e+03', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '1.00e+03', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '1.00e+03', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '1.00e+03', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '1.00e+03', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '1.00e+03', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '1.00e+03', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '1.00e+03', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '1.00e+03', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '1.00e+03', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '1.00e+03', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '1.00e+03', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '1.00e+03', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '1.00e+03', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '1.00e+03', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '1.00e+03', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '1.00e+03', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '1.78e+03', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.78e+03', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '1.78e+03', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '1.78e+03', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '1.78e+03', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '1.78e+03', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '1.78e+03', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '1.78e+03', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '1.78e+03', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '1.78e+03', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '1.78e+03', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '1.78e+03', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '1.78e+03', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '1.78e+03', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '1.78e+03', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '1.78e+03', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '1.78e+03', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '1.78e+03', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '1.78e+03', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '1.78e+03', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '1.78e+03', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '3.16e+03', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '3.16e+03', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '3.16e+03', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '3.16e+03', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '3.16e+03', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '3.16e+03', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '3.16e+03', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '3.16e+03', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '3.16e+03', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '3.16e+03', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '3.16e+03', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '3.16e+03', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '3.16e+03', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '3.16e+03', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '3.16e+03', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '3.16e+03', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '3.16e+03', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '3.16e+03', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '3.16e+03', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '3.16e+03', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '3.16e+03', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '5.62e+03', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '5.62e+03', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '5.62e+03', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '5.62e+03', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '5.62e+03', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '5.62e+03', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '5.62e+03', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '5.62e+03', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '5.62e+03', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '5.62e+03', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '5.62e+03', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '5.62e+03', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '5.62e+03', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '5.62e+03', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '5.62e+03', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '5.62e+03', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '5.62e+03', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '5.62e+03', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '5.62e+03', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '5.62e+03', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '5.62e+03', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '1.00e+04', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.00e+04', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '1.00e+04', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '1.00e+04', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '1.00e+04', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '1.00e+04', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '1.00e+04', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '1.00e+04', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '1.00e+04', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '1.00e+04', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '1.00e+04', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '1.00e+04', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '1.00e+04', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '1.00e+04', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '1.00e+04', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '1.00e+04', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '1.00e+04', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '1.00e+04', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '1.00e+04', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '1.00e+04', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '1.00e+04', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '1.78e+04', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.78e+04', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '1.78e+04', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '1.78e+04', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '1.78e+04', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '1.78e+04', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '1.78e+04', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '1.78e+04', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '1.78e+04', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '1.78e+04', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '1.78e+04', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '1.78e+04', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '1.78e+04', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '1.78e+04', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '1.78e+04', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '1.78e+04', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '1.78e+04', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '1.78e+04', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '1.78e+04', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '1.78e+04', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '1.78e+04', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '3.16e+04', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '3.16e+04', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '3.16e+04', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '3.16e+04', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '3.16e+04', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '3.16e+04', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '3.16e+04', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '3.16e+04', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '3.16e+04', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '3.16e+04', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '3.16e+04', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '3.16e+04', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '3.16e+04', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '3.16e+04', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '3.16e+04', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '3.16e+04', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '3.16e+04', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '3.16e+04', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '3.16e+04', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '3.16e+04', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '3.16e+04', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '5.62e+04', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '5.62e+04', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '5.62e+04', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '5.62e+04', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '5.62e+04', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '5.62e+04', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '5.62e+04', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '5.62e+04', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '5.62e+04', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '5.62e+04', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '5.62e+04', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '5.62e+04', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '5.62e+04', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '5.62e+04', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '5.62e+04', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '5.62e+04', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '5.62e+04', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '5.62e+04', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '5.62e+04', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '5.62e+04', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '5.62e+04', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n",
-      "{'C': '1.00e+05', 'cycle_bound': 0.0}    0.56±0.02     0.54±0.06     0.53±0.15                  0.19\n",
-      "{'C': '1.00e+05', 'cycle_bound': 25.0}   0.56±0.02     0.56±0.02     0.55±0.17                  0.24\n",
-      "{'C': '1.00e+05', 'cycle_bound': 50.0}   0.56±0.02     0.56±0.02     0.55±0.18                  0.31\n",
-      "{'C': '1.00e+05', 'cycle_bound': 75.0}   0.62±0.02     0.62±0.02     0.61±0.16                  0.36\n",
-      "{'C': '1.00e+05', 'cycle_bound': 100.0}  0.62±0.02     0.62±0.02     0.59±0.16                  0.33\n",
-      "{'C': '1.00e+05', 'cycle_bound': 125.0}  0.62±0.02     0.62±0.02     0.57±0.17                  0.33\n",
-      "{'C': '1.00e+05', 'cycle_bound': 150.0}  0.62±0.02     0.62±0.02     0.62±0.19                  0.34\n",
-      "{'C': '1.00e+05', 'cycle_bound': 175.0}  0.62±0.02     0.62±0.02     0.60±0.19                  0.32\n",
-      "{'C': '1.00e+05', 'cycle_bound': 200.0}  0.61±0.02     0.61±0.02     0.66±0.15                  0.33\n",
-      "{'C': '1.00e+05', 'cycle_bound': 225.0}  0.62±0.02     0.62±0.02     0.62±0.18                  0.32\n",
-      "{'C': '1.00e+05', 'cycle_bound': 250.0}  0.62±0.02     0.62±0.02     0.61±0.14                  0.34\n",
-      "{'C': '1.00e+05', 'cycle_bound': 275.0}  0.61±0.02     0.61±0.02     0.65±0.17                  0.32\n",
-      "{'C': '1.00e+05', 'cycle_bound': 300.0}  0.61±0.02     0.61±0.02     0.67±0.16                  0.36\n",
-      "{'C': '1.00e+05', 'cycle_bound': 325.0}  0.61±0.02     0.61±0.02     0.66±0.17                  0.34\n",
-      "{'C': '1.00e+05', 'cycle_bound': 350.0}  0.62±0.02     0.62±0.02     0.63±0.13                  0.32\n",
-      "{'C': '1.00e+05', 'cycle_bound': 375.0}  0.62±0.02     0.62±0.02     0.63±0.15                  0.33\n",
-      "{'C': '1.00e+05', 'cycle_bound': 400.0}  0.62±0.02     0.62±0.02     0.59±0.20                  0.34\n",
-      "{'C': '1.00e+05', 'cycle_bound': 425.0}  0.62±0.02     0.62±0.02     0.64±0.20                  0.36\n",
-      "{'C': '1.00e+05', 'cycle_bound': 450.0}  0.62±0.02     0.62±0.02     0.60±0.17                  0.37\n",
-      "{'C': '1.00e+05', 'cycle_bound': 475.0}  0.62±0.02     0.62±0.02     0.63±0.18                  0.33\n",
-      "{'C': '1.00e+05', 'cycle_bound': 500.0}  0.62±0.02     0.62±0.02     0.60±0.20                  0.33\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "calculate performance: 100%|██████████| 25830/25830 [11:10<00:00, 148.58it/s]"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext line_profiler\n",
-    "%matplotlib inline\n",
-    "import numpy as np\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.model_selection_precomputed import model_selection_for_precomputed_kernel\n",
-    "from pygraph.kernels.cyclicPatternKernel import cyclicpatternkernel\n",
-    "\n",
-    "datafile = '../../../../datasets/MAO/dataset.ds'\n",
-    "estimator = cyclicpatternkernel\n",
-    "param_grid_precomputed = {'cycle_bound': np.linspace(0, 300, 21)}\n",
-    "param_grid = {'C': np.logspace(-1, 8, num = 41, base = 10)}\n",
-    "\n",
-    "model_selection_for_precomputed_kernel(datafile, estimator, param_grid_precomputed, param_grid, \n",
-    "                                       'classification', NUM_TRIALS=30)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- This is a classification problem ---\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 0.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 374.47it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 28328.63it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.18629932403564453 seconds ---\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  84%|████████▍ | 842/1000 [00:00<00:00, 2091.27it/s]\n",
-      " Mean performance on train set: 0.549180\n",
-      "With standard deviation: 0.016798\n",
-      "\n",
-      " Mean performance on test set: 0.642857\n",
-      "With standard deviation: 0.146385\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:00<00:00, 2096.30it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 25.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 287.60it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 17629.66it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.24226951599121094 seconds ---\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  83%|████████▎ | 830/1000 [00:00<00:00, 2066.27it/s]\n",
-      " Mean performance on train set: 0.883607\n",
-      "With standard deviation: 0.018619\n",
-      "\n",
-      " Mean performance on test set: 0.871429\n",
-      "With standard deviation: 0.162255\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:00<00:00, 2070.90it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 50.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 235.08it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 14615.05it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.2961606979370117 seconds ---\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  82%|████████▎ | 825/1000 [00:00<00:00, 2052.54it/s]\n",
-      " Mean performance on train set: 0.824590\n",
-      "With standard deviation: 0.018033\n",
-      "\n",
-      " Mean performance on test set: 0.814286\n",
-      "With standard deviation: 0.157143\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:00<00:00, 2065.69it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 75.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 225.36it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 13927.76it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.30864953994750977 seconds ---\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  83%|████████▎ | 833/1000 [00:00<00:00, 2079.43it/s]\n",
-      " Mean performance on train set: 0.824590\n",
-      "With standard deviation: 0.018033\n",
-      "\n",
-      " Mean performance on test set: 0.814286\n",
-      "With standard deviation: 0.157143\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:00<00:00, 2075.92it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 100.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 68/68 [00:00<00:00, 225.45it/s]\n",
-      "calculate kernels: 100%|██████████| 68/68 [00:00<00:00, 14876.52it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 68 built in 0.30840325355529785 seconds ---\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  84%|████████▍ | 844/1000 [00:00<00:00, 2103.96it/s]\n",
-      " Mean performance on train set: 0.824590\n",
-      "With standard deviation: 0.018033\n",
-      "\n",
-      " Mean performance on test set: 0.814286\n",
-      "With standard deviation: 0.157143\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:00<00:00, 2100.94it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 125.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns:  76%|███████▋  | 52/68 [00:00<00:00, 252.37it/s]"
-     ]
-    },
-    {
-     "ename": "KeyboardInterrupt",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-1-a0f0495d15f0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m kernel_train_test(datafile, kernel_file_path, cyclicpatternkernel, kernel_para,     hyper_name = 'cycle_bound', hyper_range = np.linspace(0, 500, 21), normalize = False,\n\u001b[0;32m---> 17\u001b[0;31m     model_type = 'classification')\n\u001b[0m",
-      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/utils/utils.py\u001b[0m in \u001b[0;36mkernel_train_test\u001b[0;34m(datafile, kernel_file_path, kernel_func, kernel_para, trials, splits, alpha_grid, C_grid, hyper_name, hyper_range, normalize, datafile_y, model_type)\u001b[0m\n\u001b[1;32m    159\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mhyper_name\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m''\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    160\u001b[0m                 \u001b[0mkernel_para\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mhyper_name\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mhyper_para\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 161\u001b[0;31m             \u001b[0mKmatrix\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrun_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkernel_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdataset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkernel_para\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    162\u001b[0m             \u001b[0mkernel_time_list\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrun_time\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    163\u001b[0m             \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/cyclicPatternKernel.py\u001b[0m in \u001b[0;36mcyclicpatternkernel\u001b[0;34m(node_label, edge_label, labeled, cycle_bound, *args)\u001b[0m\n\u001b[1;32m     48\u001b[0m     \u001b[0;31m# get all cyclic and tree patterns of all graphs before calculating kernels to save time, but this may consume a lot of memory for large dataset.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     49\u001b[0m     all_patterns = [ get_patterns(Gn[i], node_label = node_label, edge_label = edge_label, labeled = labeled, cycle_bound = cycle_bound)\n\u001b[0;32m---> 50\u001b[0;31m         for i in tqdm(range(0, len(Gn)), desc = 'retrieve patterns', file=sys.stdout) ]\n\u001b[0m\u001b[1;32m     51\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     52\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtqdm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdesc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'calculate kernels'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstdout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/cyclicPatternKernel.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m     48\u001b[0m     \u001b[0;31m# get all cyclic and tree patterns of all graphs before calculating kernels to save time, but this may consume a lot of memory for large dataset.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     49\u001b[0m     all_patterns = [ get_patterns(Gn[i], node_label = node_label, edge_label = edge_label, labeled = labeled, cycle_bound = cycle_bound)\n\u001b[0;32m---> 50\u001b[0;31m         for i in tqdm(range(0, len(Gn)), desc = 'retrieve patterns', file=sys.stdout) ]\n\u001b[0m\u001b[1;32m     51\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     52\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtqdm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdesc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'calculate kernels'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstdout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/cyclicPatternKernel.py\u001b[0m in \u001b[0;36mget_patterns\u001b[0;34m(G, node_label, edge_label, labeled, cycle_bound)\u001b[0m\n\u001b[1;32m    111\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    112\u001b[0m     \u001b[0mbicomponents\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbiconnected_component_subgraphs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# all biconnected components of G. this function use algorithm in reference [2], which (i guess) is slightly different from the one used in paper [1]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 113\u001b[0;31m     \u001b[0;32mfor\u001b[0m \u001b[0msubgraph\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mbicomponents\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    114\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnumber_of_edges\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubgraph\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    115\u001b[0m             \u001b[0msimple_cycles\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msimple_cycles\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_directed\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# all simple cycles in biconnected components. this function use algorithm in reference [3], which has time complexity O((n+e)(N+1)) for n nodes, e edges and N simple cycles. Which might be slower than the algorithm applied in paper [1]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/networkx/algorithms/components/biconnected.py\u001b[0m in \u001b[0;36mbiconnected_component_subgraphs\u001b[0;34m(G, copy)\u001b[0m\n\u001b[1;32m    275\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mc\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mbiconnected_components\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    276\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 277\u001b[0;31m             \u001b[0;32myield\u001b[0m \u001b[0mG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubgraph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    278\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    279\u001b[0m             \u001b[0;32myield\u001b[0m \u001b[0mG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubgraph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/networkx/classes/graph.py\u001b[0m in \u001b[0;36mcopy\u001b[0;34m(self, as_view)\u001b[0m\n\u001b[1;32m   1420\u001b[0m         \u001b[0mG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_nodes_from\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0md\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0md\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_node\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1421\u001b[0m         G.add_edges_from((u, v, datadict.copy())\n\u001b[0;32m-> 1422\u001b[0;31m                          \u001b[0;32mfor\u001b[0m \u001b[0mu\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnbrs\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_adj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1423\u001b[0m                          for v, datadict in nbrs.items())\n\u001b[1;32m   1424\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mG\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/networkx/classes/graph.py\u001b[0m in \u001b[0;36madd_edges_from\u001b[0;34m(self, ebunch_to_add, **attr)\u001b[0m\n\u001b[1;32m    926\u001b[0m             \u001b[0mne\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    927\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mne\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 928\u001b[0;31m                 \u001b[0mu\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mv\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdd\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    929\u001b[0m             \u001b[0;32melif\u001b[0m \u001b[0mne\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    930\u001b[0m                 \u001b[0mu\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mv\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
-     ]
-    }
-   ],
-   "source": [
-    "# MAO dataset (node labeled, edge labeled, undirected, cyclic + linear, classification)\n",
-    "%load_ext line_profiler\n",
-    "\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.cyclicPatternKernel import cyclicpatternkernel\n",
-    "\n",
-    "import numpy as np\n",
-    "\n",
-    "datafile = '../../../../datasets/MAO/dataset.ds'\n",
-    "kernel_file_path = 'kernelmatrices_cyclicpattern_mao/'\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', labeled = True)\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, cyclicpatternkernel, kernel_para, \\\n",
-    "    hyper_name = 'cycle_bound', hyper_range = np.linspace(0, 500, 21), normalize = False,\n",
-    "    model_type = 'classification')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The line_profiler extension is already loaded. To reload it, use:\n",
-      "  %reload_ext line_profiler\n",
-      "\n",
-      " --- This is a classification problem ---\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 0.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 94/94 [00:00<00:00, 176.07it/s]\n",
-      "calculate kernels: 100%|██████████| 94/94 [00:00<00:00, 18331.07it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 94 built in 0.5411422252655029 seconds ---\n",
-      "[[0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " ...\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  95%|█████████▌| 951/1000 [00:00<00:00, 1898.18it/s]\n",
-      " Mean performance on train set: 0.629762\n",
-      "With standard deviation: 0.013521\n",
-      "\n",
-      " Mean performance on test set: 0.610000\n",
-      "With standard deviation: 0.113578\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:00<00:00, 1889.49it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 10.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 94/94 [00:00<00:00, 165.16it/s]\n",
-      "calculate kernels: 100%|██████████| 94/94 [00:00<00:00, 16217.54it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 94 built in 0.5770719051361084 seconds ---\n",
-      "[[0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " ...\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  94%|█████████▍| 940/1000 [00:00<00:00, 1876.61it/s]\n",
-      " Mean performance on train set: 0.629762\n",
-      "With standard deviation: 0.013521\n",
-      "\n",
-      " Mean performance on test set: 0.610000\n",
-      "With standard deviation: 0.113578\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:00<00:00, 1866.80it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 20.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 94/94 [00:00<00:00, 165.21it/s]\n",
-      "calculate kernels: 100%|██████████| 94/94 [00:00<00:00, 16888.61it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 94 built in 0.5768516063690186 seconds ---\n",
-      "[[3. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " ...\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  93%|█████████▎| 926/1000 [00:00<00:00, 1837.36it/s]\n",
-      " Mean performance on train set: 0.629762\n",
-      "With standard deviation: 0.013521\n",
-      "\n",
-      " Mean performance on test set: 0.610000\n",
-      "With standard deviation: 0.113578\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:00<00:00, 1841.13it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 30.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 94/94 [00:00<00:00, 171.51it/s]\n",
-      "calculate kernels: 100%|██████████| 94/94 [00:00<00:00, 17701.46it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 94 built in 0.5560076236724854 seconds ---\n",
-      "[[3. 3. 3. ... 0. 0. 0.]\n",
-      " [3. 4. 4. ... 0. 0. 0.]\n",
-      " [3. 4. 4. ... 0. 0. 0.]\n",
-      " ...\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  92%|█████████▏| 923/1000 [00:00<00:00, 1845.18it/s]\n",
-      " Mean performance on train set: 0.633333\n",
-      "With standard deviation: 0.015793\n",
-      "\n",
-      " Mean performance on test set: 0.640000\n",
-      "With standard deviation: 0.111355\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:00<00:00, 1836.56it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 40.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 94/94 [00:00<00:00, 159.66it/s]\n",
-      "calculate kernels: 100%|██████████| 94/94 [00:00<00:00, 17703.84it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 94 built in 0.5963354110717773 seconds ---\n",
-      "[[3. 3. 3. ... 0. 0. 0.]\n",
-      " [3. 4. 4. ... 0. 0. 0.]\n",
-      " [3. 4. 4. ... 0. 0. 0.]\n",
-      " ...\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  84%|████████▍ | 845/1000 [00:00<00:00, 1694.10it/s]\n",
-      " Mean performance on train set: 0.633333\n",
-      "With standard deviation: 0.015793\n",
-      "\n",
-      " Mean performance on test set: 0.640000\n",
-      "With standard deviation: 0.111355\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:00<00:00, 1694.34it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 50.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 94/94 [00:00<00:00, 126.36it/s]\n",
-      "calculate kernels: 100%|██████████| 94/94 [00:00<00:00, 14863.89it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 94 built in 0.7526798248291016 seconds ---\n",
-      "[[3. 3. 3. ... 0. 0. 0.]\n",
-      " [3. 4. 4. ... 0. 0. 0.]\n",
-      " [3. 4. 4. ... 0. 0. 0.]\n",
-      " ...\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  84%|████████▍ | 842/1000 [00:00<00:00, 1670.86it/s]\n",
-      " Mean performance on train set: 0.658333\n",
-      "With standard deviation: 0.034524\n",
-      "\n",
-      " Mean performance on test set: 0.670000\n",
-      "With standard deviation: 0.090000\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:00<00:00, 1665.11it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 60.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 94/94 [00:00<00:00, 107.33it/s]\n",
-      "calculate kernels: 100%|██████████| 94/94 [00:00<00:00, 13937.03it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 94 built in 0.8846912384033203 seconds ---\n",
-      "[[3. 3. 3. ... 0. 0. 0.]\n",
-      " [3. 4. 4. ... 0. 0. 0.]\n",
-      " [3. 4. 4. ... 0. 0. 0.]\n",
-      " ...\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  83%|████████▎ | 829/1000 [00:00<00:00, 1653.86it/s]\n",
-      " Mean performance on train set: 0.671429\n",
-      "With standard deviation: 0.036577\n",
-      "\n",
-      " Mean performance on test set: 0.680000\n",
-      "With standard deviation: 0.107703\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:00<00:00, 1673.57it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 70.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 94/94 [00:01<00:00, 81.45it/s] \n",
-      "calculate kernels: 100%|██████████| 94/94 [00:00<00:00, 14275.64it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 94 built in 1.1631414890289307 seconds ---\n",
-      "[[3. 3. 3. ... 3. 3. 3.]\n",
-      " [3. 4. 4. ... 4. 4. 4.]\n",
-      " [3. 4. 4. ... 4. 4. 4.]\n",
-      " ...\n",
-      " [3. 4. 4. ... 7. 7. 7.]\n",
-      " [3. 4. 4. ... 7. 7. 7.]\n",
-      " [3. 4. 4. ... 7. 7. 7.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  88%|████████▊ | 876/1000 [00:00<00:00, 1761.00it/s]\n",
-      " Mean performance on train set: 0.666667\n",
-      "With standard deviation: 0.038021\n",
-      "\n",
-      " Mean performance on test set: 0.670000\n",
-      "With standard deviation: 0.100499\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:00<00:00, 1754.20it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 80.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 94/94 [00:01<00:00, 79.93it/s] \n",
-      "calculate kernels: 100%|██████████| 94/94 [00:00<00:00, 14789.73it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 94 built in 1.1846554279327393 seconds ---\n",
-      "[[3. 3. 3. ... 3. 3. 3.]\n",
-      " [3. 4. 4. ... 4. 4. 4.]\n",
-      " [3. 4. 4. ... 4. 4. 4.]\n",
-      " ...\n",
-      " [3. 4. 4. ... 7. 7. 7.]\n",
-      " [3. 4. 4. ... 7. 7. 7.]\n",
-      " [3. 4. 4. ... 7. 7. 7.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  93%|█████████▎| 926/1000 [00:00<00:00, 1854.59it/s]\n",
-      " Mean performance on train set: 0.709524\n",
-      "With standard deviation: 0.058853\n",
-      "\n",
-      " Mean performance on test set: 0.780000\n",
-      "With standard deviation: 0.107703\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:00<00:00, 1844.77it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 90.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "retrieve patterns: 100%|██████████| 94/94 [00:01<00:00, 83.75it/s] \n",
-      "calculate kernels: 100%|██████████| 94/94 [00:00<00:00, 14169.95it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 94 built in 1.1314406394958496 seconds ---\n",
-      "[[3. 3. 3. ... 3. 3. 3.]\n",
-      " [3. 4. 4. ... 4. 4. 4.]\n",
-      " [3. 4. 4. ... 4. 4. 4.]\n",
-      " ...\n",
-      " [3. 4. 4. ... 7. 7. 7.]\n",
-      " [3. 4. 4. ... 7. 7. 7.]\n",
-      " [3. 4. 4. ... 7. 7. 7.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  94%|█████████▍| 943/1000 [00:00<00:00, 1878.69it/s]\n",
-      " Mean performance on train set: 0.709524\n",
-      "With standard deviation: 0.058853\n",
-      "\n",
-      " Mean performance on test set: 0.780000\n",
-      "With standard deviation: 0.107703\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:00<00:00, 1872.55it/s]\n",
-      "\n",
-      "\n",
-      "  cycle_bound    accur_test    std_test    accur_train    std_train    k_time\n",
-      "-------------  ------------  ----------  -------------  -----------  --------\n",
-      "            0          0.61    0.113578       0.629762    0.0135212  0.541142\n",
-      "           10          0.61    0.113578       0.629762    0.0135212  0.577072\n",
-      "           20          0.61    0.113578       0.629762    0.0135212  0.576852\n",
-      "           30          0.64    0.111355       0.633333    0.0157935  0.556008\n",
-      "           40          0.64    0.111355       0.633333    0.0157935  0.596335\n",
-      "           50          0.67    0.09           0.658333    0.0345238  0.75268\n",
-      "           60          0.68    0.107703       0.671429    0.0365769  0.884691\n",
-      "           70          0.67    0.100499       0.666667    0.0380208  1.16314\n",
-      "           80          0.78    0.107703       0.709524    0.0588534  1.18466\n",
-      "           90          0.78    0.107703       0.709524    0.0588534  1.13144\n"
-     ]
-    }
-   ],
-   "source": [
-    "# PAH dataset (node and edge unlabeled, undirected, cyclic, classification)\n",
-    "%load_ext line_profiler\n",
-    "\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.cyclicPatternKernel import cyclicpatternkernel\n",
-    "\n",
-    "import numpy as np\n",
-    "\n",
-    "datafile = '../../../../datasets/PAH/dataset.ds'\n",
-    "kernel_file_path = 'kernelmatrices_cyclicpattern_pah/'\n",
-    "\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', labeled = False)\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, cyclicpatternkernel, kernel_para, \\\n",
-    "    hyper_name = 'cycle_bound', hyper_range = np.linspace(0, 90, 10), normalize = False, \\\n",
-    "    model_type = 'classification')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# results\n",
-    "\n",
-    "# MAO dataset\n",
-    "cycle_bound    accur_test    std_test    accur_train    std_train    k_time\n",
-    "-------------  ------------  ----------  -------------  -----------  --------\n",
-    "            0      0.642857    0.146385       0.54918     0.0167983  0.187052\n",
-    "           50      0.871429    0.1            0.698361    0.116889   0.300629\n",
-    "          100      0.9         0.111575       0.732787    0.0826366  0.309837\n",
-    "          150      0.9         0.111575       0.732787    0.0826366  0.31808\n",
-    "          200      0.9         0.111575       0.732787    0.0826366  0.317575\n",
-    "            \n",
-    "# PAH dataset\n",
-    "  cycle_bound    accur_test    std_test    accur_train    std_train    k_time\n",
-    "-------------  ------------  ----------  -------------  -----------  --------\n",
-    "            0          0.61    0.113578       0.629762    0.0135212  0.521801\n",
-    "           10          0.61    0.113578       0.629762    0.0135212  0.52589\n",
-    "           20          0.61    0.113578       0.629762    0.0135212  0.548528\n",
-    "           30          0.64    0.111355       0.633333    0.0157935  0.535311\n",
-    "           40          0.64    0.111355       0.633333    0.0157935  0.61764\n",
-    "           50          0.67    0.09           0.658333    0.0345238  0.733868\n",
-    "           60          0.68    0.107703       0.671429    0.0365769  0.871147\n",
-    "           70          0.67    0.100499       0.666667    0.0380208  1.12625\n",
-    "           80          0.78    0.107703       0.709524    0.0588534  1.19828\n",
-    "           90          0.78    0.107703       0.709524    0.0588534  1.21182"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- This is a classification problem ---\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when cycle_bound = 1000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "load SDF: 100%|██████████| 4457424/4457424 [00:10<00:00, 408299.51it/s]\n",
-      "ajust data: 100%|██████████| 42687/42687 [00:10<00:00, 4092.17it/s] \n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 42682/42682 [19:36<00:00, 36.27it/s]\n",
-      "calculate kernels: 100%|██████████| 42682/42682 [37:05<00:00, 19.18it/s] \n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 42682 built in 3402.171978712082 seconds ---\n",
-      "[[ 9.  9.  3. ...  4.  3.  4.]\n",
-      " [ 9. 11.  5. ...  6.  5.  6.]\n",
-      " [ 3.  5. 16. ...  6.  6.  6.]\n",
-      " ...\n",
-      " [ 4.  6.  6. ... 30. 29.  6.]\n",
-      " [ 3.  5.  6. ... 29. 29.  6.]\n",
-      " [ 4.  6.  6. ...  6.  6. 11.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:   7%|▋         | 70/1000 [1:34:57<227:25:45, 880.37s/it]"
-     ]
-    }
-   ],
-   "source": [
-    "# NCI-HIV dataset (labeled?, directed?, cyclic, classification)\n",
-    "%load_ext line_profiler\n",
-    "\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.cyclicPatternKernel import cyclicpatternkernel\n",
-    "\n",
-    "import numpy as np\n",
-    "\n",
-    "datafile = '../../../../datasets/NCI-HIV/AIDO99SD.sdf'\n",
-    "datafile_y = '../../../../datasets/NCI-HIV/aids_conc_may04.txt'\n",
-    "kernel_file_path = 'kernelmatrices_path_acyclic/'\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', labeled = True)\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, cyclicpatternkernel, kernel_para, \\\n",
-    "    hyper_name = 'cycle_bound', hyper_range = np.linspace(0, 1000, 21), normalize = False, \\\n",
-    "    datafile_y = datafile_y, model_type = 'classification')\n",
-    "\n",
-    "# kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', labeled = True, cycle_bound = 200)\n",
-    "\n",
-    "# kernel_train_test(datafile, kernel_file_path, cyclicpatternkernel, kernel_para,\n",
-    "#     normalize = False, datafile_y = datafile_y, model_type = 'classification')\n",
-    "\n",
-    "# kernel_para['k_func'] = 'minmax'\n",
-    "# kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
-    "#     hyper_name = 'depth', hyper_range = np.linspace(0, 10, 11), normalize = True)\n",
-    "# kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
-    "#     hyper_name = 'depth', hyper_range = np.linspace(0, 10, 11), normalize = False)\n",
-    "# # kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, normalize = False)\n",
-    "\n",
-    "# kernel_para['depth'] = 10\n",
-    "# %lprun -f untildpathkernel \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, normalize = False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The line_profiler extension is already loaded. To reload it, use:\n",
-      "  %reload_ext line_profiler\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f71ccb78400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f71ccb339b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 999 built in 18.78946042060852 seconds ---\n",
-      "(array([[11.,  5.,  5., ...,  6.,  7.,  3.],\n",
-      "       [ 5., 16.,  6., ...,  5.,  5.,  3.],\n",
-      "       [ 5.,  6.,  8., ...,  4.,  5.,  3.],\n",
-      "       ...,\n",
-      "       [ 6.,  5.,  4., ..., 17.,  7.,  4.],\n",
-      "       [ 7.,  5.,  5., ...,  7., 15.,  4.],\n",
-      "       [ 3.,  3.,  3., ...,  4.,  4., 11.]]), 18.78946042060852)\n"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext line_profiler\n",
-    "\n",
-    "import networkx as nx\n",
-    "import matplotlib.pyplot as plt\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "from pygraph.kernels.cyclicPatternKernel import cyclicpatternkernel\n",
-    "\n",
-    "# datafile = '../../../../datasets/NCI-HIV/AIDO99SD.sdf'\n",
-    "# datafile_y = '../../../../datasets/NCI-HIV/aids_conc_may04.txt'\n",
-    "# dataset, y = loadDataset(datafile, datafile_y)\n",
-    "G1 = dataset[1]\n",
-    "G2 = dataset[2]\n",
-    "G3 = dataset[3]\n",
-    "G4 = dataset[4]\n",
-    "G5 = dataset[5]\n",
-    "data = [G1, G2, G3, G4, G5]\n",
-    "nx.draw_networkx(G1)\n",
-    "plt.show()\n",
-    "nx.draw_networkx(G2)\n",
-    "plt.show()\n",
-    "\n",
-    "kernel = cyclicpatternkernel(dataset[1:1000], cycle_bound = 1000)\n",
-    "print(kernel)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- This is a classification problem ---\n",
-      "\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 185/185 [00:00<00:00, 2064.69it/s]\n",
-      "calculate kernels: 100%|██████████| 185/185 [00:00<00:00, 11170.00it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 185 built in 0.10836505889892578 seconds ---\n",
-      "[[0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " ...\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:24<00:00, 36.41it/s]\n",
-      " Mean performance on train set: 0.018072\n",
-      "With standard deviation: 0.000000\n",
-      "\n",
-      " Mean performance on test set: 0.000000\n",
-      "With standard deviation: 0.000000\n",
-      "\n",
-      "\n",
-      "  accur_test    std_test    accur_train    std_train    k_time\n",
-      "------------  ----------  -------------  -----------  --------\n",
-      "           0           0      0.0180723            0  0.108365\n"
-     ]
-    }
-   ],
-   "source": [
-    "# acyclic dataset (node labeled, edge labeled, undirected, linear + non-linear, regression)\n",
-    "%load_ext line_profiler\n",
-    "\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.cyclicPatternKernel import cyclicpatternkernel\n",
-    "\n",
-    "import numpy as np\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_path_acyclic/'\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', labeled = True, cycle_bound = 200)\n",
-    "\n",
-    "# kernel_train_test(datafile, kernel_file_path, treeletkernel, kernel_para, normalize = False)\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, cyclicpatternkernel, kernel_para, \\\n",
-    "    normalize = False , model_type = 'classification')\n",
-    "\n",
-    "# kernel_para['k_func'] = 'minmax'\n",
-    "# kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
-    "#     hyper_name = 'depth', hyper_range = np.linspace(0, 10, 11), normalize = True)\n",
-    "# kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
-    "#     hyper_name = 'depth', hyper_range = np.linspace(0, 10, 11), normalize = False)\n",
-    "# # kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, normalize = False)\n",
-    "\n",
-    "# kernel_para['depth'] = 10\n",
-    "# %lprun -f untildpathkernel \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, normalize = False)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/.ipynb_checkpoints/run_marginalizedkernel_acyclic-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/run_marginalizedkernel_acyclic-checkpoint.ipynb
deleted file mode 100644
index 9890952..0000000
--- a/notebooks/.ipynb_checkpoints/run_marginalizedkernel_acyclic-checkpoint.ipynb
+++ /dev/null
@@ -1,1075 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The line_profiler extension is already loaded. To reload it, use:\n",
-      "  %reload_ext line_profiler\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when p_quit = 0.1 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 258.76952958106995 seconds ---\n",
-      "[[ 0.0287062   0.0124634   0.00444444 ...,  0.00606061  0.00606061\n",
-      "   0.00606061]\n",
-      " [ 0.0124634   0.01108958  0.00333333 ...,  0.00454545  0.00454545\n",
-      "   0.00454545]\n",
-      " [ 0.00444444  0.00333333  0.0287062  ...,  0.00819912  0.00819912\n",
-      "   0.00975875]\n",
-      " ..., \n",
-      " [ 0.00606061  0.00454545  0.00819912 ...,  0.02846735  0.02836907\n",
-      "   0.02896354]\n",
-      " [ 0.00606061  0.00454545  0.00819912 ...,  0.02836907  0.02831424\n",
-      "   0.0288712 ]\n",
-      " [ 0.00606061  0.00454545  0.00975875 ...,  0.02896354  0.0288712\n",
-      "   0.02987915]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 12.186285\n",
-      "With standard deviation: 7.038988\n",
-      "\n",
-      " Mean performance on test set: 18.024312\n",
-      "With standard deviation: 6.292466\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when p_quit = 0.2 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 256.3271746635437 seconds ---\n",
-      "[[ 0.06171557  0.03856471  0.01777778 ...,  0.02424242  0.02424242\n",
-      "   0.02424242]\n",
-      " [ 0.03856471  0.03579176  0.01333333 ...,  0.01818182  0.01818182\n",
-      "   0.01818182]\n",
-      " [ 0.01777778  0.01333333  0.06171557 ...,  0.02994207  0.02994207\n",
-      "   0.03262072]\n",
-      " ..., \n",
-      " [ 0.02424242  0.01818182  0.02994207 ...,  0.07442109  0.07434207\n",
-      "   0.07383563]\n",
-      " [ 0.02424242  0.01818182  0.02994207 ...,  0.07434207  0.07430377\n",
-      "   0.07376068]\n",
-      " [ 0.02424242  0.01818182  0.03262072 ...,  0.07383563  0.07376068\n",
-      "   0.07366354]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 13.955359\n",
-      "With standard deviation: 7.544068\n",
-      "\n",
-      " Mean performance on test set: 18.337589\n",
-      "With standard deviation: 5.854545\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when p_quit = 0.3 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 255.61398577690125 seconds ---\n",
-      "[[ 0.09803909  0.07202114  0.04       ...,  0.05454545  0.05454545\n",
-      "   0.05454545]\n",
-      " [ 0.07202114  0.06853421  0.03       ...,  0.04090909  0.04090909\n",
-      "   0.04090909]\n",
-      " [ 0.04        0.03        0.09803909 ...,  0.06368916  0.06368916\n",
-      "   0.06678704]\n",
-      " ..., \n",
-      " [ 0.05454545  0.04090909  0.06368916 ...,  0.12892852  0.12891455\n",
-      "   0.12734365]\n",
-      " [ 0.05454545  0.04090909  0.06368916 ...,  0.12891455  0.12892664\n",
-      "   0.12733207]\n",
-      " [ 0.05454545  0.04090909  0.06678704 ...,  0.12734365  0.12733207\n",
-      "   0.1261675 ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 13.939071\n",
-      "With standard deviation: 7.958123\n",
-      "\n",
-      " Mean performance on test set: 18.495992\n",
-      "With standard deviation: 5.734918\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when p_quit = 0.4 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 254.89703965187073 seconds ---\n",
-      "[[ 0.13888889  0.11120616  0.07111111 ...,  0.0969697   0.0969697\n",
-      "   0.0969697 ]\n",
-      " [ 0.11120616  0.10756609  0.05333333 ...,  0.07272727  0.07272727\n",
-      "   0.07272727]\n",
-      " [ 0.07111111  0.05333333  0.13888889 ...,  0.10909713  0.10909713\n",
-      "   0.11216176]\n",
-      " ..., \n",
-      " [ 0.0969697   0.07272727  0.10909713 ...,  0.19178929  0.19182091\n",
-      "   0.18963212]\n",
-      " [ 0.0969697   0.07272727  0.10909713 ...,  0.19182091  0.19186661\n",
-      "   0.18966477]\n",
-      " [ 0.0969697   0.07272727  0.11216176 ...,  0.18963212  0.18966477\n",
-      "   0.18786824]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 16.259313\n",
-      "With standard deviation: 6.693580\n",
-      "\n",
-      " Mean performance on test set: 19.449149\n",
-      "With standard deviation: 5.371295\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when p_quit = 0.5 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 256.75693798065186 seconds ---\n",
-      "[[ 0.18518519  0.15591398  0.11111111 ...,  0.15151515  0.15151515\n",
-      "   0.15151515]\n",
-      " [ 0.15591398  0.15254237  0.08333333 ...,  0.11363636  0.11363636\n",
-      "   0.11363636]\n",
-      " [ 0.11111111  0.08333333  0.18518519 ...,  0.16617791  0.16617791\n",
-      "   0.16890214]\n",
-      " ..., \n",
-      " [ 0.15151515  0.11363636  0.16617791 ...,  0.26386999  0.26391515\n",
-      "   0.26158184]\n",
-      " [ 0.15151515  0.11363636  0.16617791 ...,  0.26391515  0.26396688\n",
-      "   0.26162729]\n",
-      " [ 0.15151515  0.11363636  0.16890214 ...,  0.26158184  0.26162729\n",
-      "   0.25964592]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 17.018055\n",
-      "With standard deviation: 6.844372\n",
-      "\n",
-      " Mean performance on test set: 19.785683\n",
-      "With standard deviation: 5.550543\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when p_quit = 0.6 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 256.5566437244415 seconds ---\n",
-      "[[ 0.23809524  0.20664506  0.16       ...,  0.21818182  0.21818182\n",
-      "   0.21818182]\n",
-      " [ 0.20664506  0.20385906  0.12       ...,  0.16363636  0.16363636\n",
-      "   0.16363636]\n",
-      " [ 0.16        0.12        0.23809524 ...,  0.2351024   0.2351024\n",
-      "   0.23727718]\n",
-      " ..., \n",
-      " [ 0.21818182  0.16363636  0.2351024  ...,  0.34658956  0.34662512\n",
-      "   0.34454945]\n",
-      " [ 0.21818182  0.16363636  0.2351024  ...,  0.34662512  0.34666325\n",
-      "   0.34458505]\n",
-      " [ 0.21818182  0.16363636  0.23727718 ...,  0.34454945  0.34458505\n",
-      "   0.34279503]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 17.661762\n",
-      "With standard deviation: 6.567179\n",
-      "\n",
-      " Mean performance on test set: 20.192158\n",
-      "With standard deviation: 5.591223\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when p_quit = 0.7 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 254.9531705379486 seconds ---\n",
-      "[[ 0.2991453   0.26444601  0.21777778 ...,  0.2969697   0.2969697\n",
-      "   0.2969697 ]\n",
-      " [ 0.26444601  0.26246188  0.16333333 ...,  0.22272727  0.22272727\n",
-      "   0.22272727]\n",
-      " [ 0.21777778  0.16333333  0.2991453  ...,  0.31614548  0.31614548\n",
-      "   0.31765009]\n",
-      " ..., \n",
-      " [ 0.2969697   0.22272727  0.31614548 ...,  0.44189997  0.44191814\n",
-      "   0.44038348]\n",
-      " [ 0.2969697   0.22272727  0.31614548 ...,  0.44191814  0.44193708\n",
-      "   0.44040164]\n",
-      " [ 0.2969697   0.22272727  0.31765009 ...,  0.44038348  0.44040164\n",
-      "   0.43906772]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 20.588213\n",
-      "With standard deviation: 5.746009\n",
-      "\n",
-      " Mean performance on test set: 21.661372\n",
-      "With standard deviation: 6.026849\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when p_quit = 0.8 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 252.80415797233582 seconds ---\n",
-      "[[ 0.37037037  0.33093141  0.28444444 ...,  0.38787879  0.38787879\n",
-      "   0.38787879]\n",
-      " [ 0.33093141  0.32983023  0.21333333 ...,  0.29090909  0.29090909\n",
-      "   0.29090909]\n",
-      " [ 0.28444444  0.21333333  0.37037037 ...,  0.4096795   0.4096795\n",
-      "   0.41049599]\n",
-      " ..., \n",
-      " [ 0.38787879  0.29090909  0.4096795  ...,  0.55242487  0.55243009\n",
-      "   0.5515636 ]\n",
-      " [ 0.38787879  0.29090909  0.4096795  ...,  0.55243009  0.55243545\n",
-      "   0.55156881]\n",
-      " [ 0.38787879  0.29090909  0.41049599 ...,  0.5515636   0.55156881\n",
-      "   0.55081257]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 23.594332\n",
-      "With standard deviation: 3.806374\n",
-      "\n",
-      " Mean performance on test set: 22.996018\n",
-      "With standard deviation: 6.083466\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when p_quit = 0.9 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 256.7384788990021 seconds ---\n",
-      "[[ 0.45454545  0.40839542  0.36       ...,  0.49090909  0.49090909\n",
-      "   0.49090909]\n",
-      " [ 0.40839542  0.40805534  0.27       ...,  0.36818182  0.36818182\n",
-      "   0.36818182]\n",
-      " [ 0.36        0.27        0.45454545 ...,  0.51619708  0.51619708\n",
-      "   0.51644564]\n",
-      " ..., \n",
-      " [ 0.49090909  0.36818182  0.51619708 ...,  0.68172189  0.68172233\n",
-      "   0.68145294]\n",
-      " [ 0.49090909  0.36818182  0.51619708 ...,  0.68172233  0.68172277\n",
-      "   0.68145338]\n",
-      " [ 0.49090909  0.36818182  0.51644564 ...,  0.68145294  0.68145338\n",
-      "   0.68121781]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " Mean performance on train set: 25.808155\n",
-      "With standard deviation: 3.312074\n",
-      "\n",
-      " Mean performance on test set: 24.424089\n",
-      "With standard deviation: 4.951191\n",
-      "\n",
-      "\n",
-      "  p_quit    RMSE_test    std_test    RMSE_train    std_train    k_time\n",
-      "--------  -----------  ----------  ------------  -----------  --------\n",
-      "     0.1      18.0243     6.29247       12.1863      7.03899   258.77\n",
-      "     0.2      18.3376     5.85454       13.9554      7.54407   256.327\n",
-      "     0.3      18.496      5.73492       13.9391      7.95812   255.614\n",
-      "     0.4      19.4491     5.3713        16.2593      6.69358   254.897\n",
-      "     0.5      19.7857     5.55054       17.0181      6.84437   256.757\n",
-      "     0.6      20.1922     5.59122       17.6618      6.56718   256.557\n",
-      "     0.7      21.6614     6.02685       20.5882      5.74601   254.953\n",
-      "     0.8      22.996      6.08347       23.5943      3.80637   252.804\n",
-      "     0.9      24.4241     4.95119       25.8082      3.31207   256.738\n"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext line_profiler\n",
-    "\n",
-    "import numpy as np\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.marginalizedKernel import marginalizedkernel, _marginalizedkernel_do\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_weisfeilerlehman_subtree_acyclic/'\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', itr = 20)\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, marginalizedkernel, kernel_para, \\\n",
-    "    hyper_name = 'p_quit', hyper_range = np.linspace(0.1, 0.9, 9), normalize = False)\n",
-    "\n",
-    "# %lprun -f _marginalizedkernel_do \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, marginalizedkernel, kernel_para, \\\n",
-    "#     hyper_name = 'p_quit', hyper_range = np.linspace(0.1, 0.9, 9), normalize = False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# results\n",
-    "\n",
-    "# with y normalization\n",
-    "  p_quit    RMSE_test    std_test    RMSE_train    std_train    k_time\n",
-    "--------  -----------  ----------  ------------  -----------  --------\n",
-    "     0.1      18.0192     6.27867       12.1642      6.99821   266.905\n",
-    "     0.2      18.3374     5.84775       13.9376      7.51398   256.288\n",
-    "     0.3      18.4955     5.73774       13.9291      7.9416    254.441\n",
-    "     0.4      19.4498     5.37509       16.2538      6.68378   257.581\n",
-    "     0.5      19.7851     5.55018       17.0142      6.83653   248.562\n",
-    "     0.6      20.1911     5.58951       17.6595      6.56211   249.667\n",
-    "     0.7      21.6606     6.02589       20.5872      5.74395   243.046\n",
-    "     0.8      22.9959     6.08344       23.5941      3.80595   252.36\n",
-    "     0.9      24.424      4.9512        25.8082      3.31202   248.077\n",
-    "\n",
-    "# without y normalization\n",
-    "  p_quit    RMSE_test    std_test    RMSE_train    std_train    k_time\n",
-    "--------  -----------  ----------  ------------  -----------  --------\n",
-    "     0.1      18.0243     6.29247       12.1863      7.03899   258.77\n",
-    "     0.2      18.3376     5.85454       13.9554      7.54407   256.327\n",
-    "     0.3      18.496      5.73492       13.9391      7.95812   255.614\n",
-    "     0.4      19.4491     5.3713        16.2593      6.69358   254.897\n",
-    "     0.5      19.7857     5.55054       17.0181      6.84437   256.757\n",
-    "     0.6      20.1922     5.59122       17.6618      6.56718   256.557\n",
-    "     0.7      21.6614     6.02685       20.5882      5.74601   254.953\n",
-    "     0.8      22.996      6.08347       23.5943      3.80637   252.804\n",
-    "     0.9      24.4241     4.95119       25.8082      3.31207   256.738"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 1133.0229969024658 seconds ---\n",
-      "[[ 0.0287062   0.0124634   0.00444444 ...,  0.00606061  0.00606061\n",
-      "   0.00606061]\n",
-      " [ 0.0124634   0.01108958  0.00333333 ...,  0.00454545  0.00454545\n",
-      "   0.00454545]\n",
-      " [ 0.00444444  0.00333333  0.0287062  ...,  0.00819912  0.00819912\n",
-      "   0.00975875]\n",
-      " ..., \n",
-      " [ 0.00606061  0.00454545  0.00819912 ...,  0.02846735  0.02836907\n",
-      "   0.02896354]\n",
-      " [ 0.00606061  0.00454545  0.00819912 ...,  0.02836907  0.02831424\n",
-      "   0.0288712 ]\n",
-      " [ 0.00606061  0.00454545  0.00975875 ...,  0.02896354  0.0288712\n",
-      "   0.02987915]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 12.186285\n",
-      "With standard deviation: 7.038988\n",
-      "\n",
-      " Mean performance on test set: 18.024312\n",
-      "With standard deviation: 6.292466\n",
-      "\n",
-      "\n",
-      "  rmse_test    std_test    rmse_train    std_train    k_time\n",
-      "-----------  ----------  ------------  -----------  --------\n",
-      "    18.0243     6.29247       12.1863      7.03899   1133.02\n"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext line_profiler\n",
-    "\n",
-    "import numpy as np\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.marginalizedKernel import marginalizedkernel, _marginalizedkernel_do\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_weisfeilerlehman_subtree_acyclic/'\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', itr = 20, p_quit = 0.1)\n",
-    "\n",
-    "# kernel_train_test(datafile, kernel_file_path, marginalizedkernel, kernel_para, \\\n",
-    "#     hyper_name = 'p_quit', hyper_range = np.linspace(0.1, 0.9, 9), normalize = False)\n",
-    "\n",
-    "%lprun -f _marginalizedkernel_do \\\n",
-    "    kernel_train_test(datafile, kernel_file_path, marginalizedkernel, kernel_para, \\\n",
-    "    normalize = False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "Timer unit: 1e-06 s\n",
-    "\n",
-    "Total time: 828.879 s\n",
-    "File: ../pygraph/kernels/marginalizedKernel.py\n",
-    "Function: _marginalizedkernel_do at line 67\n",
-    "\n",
-    "Line #      Hits         Time  Per Hit   % Time  Line Contents\n",
-    "==============================================================\n",
-    "    67                                           def _marginalizedkernel_do(G1, G2, node_label, edge_label, p_quit, itr):\n",
-    "    68                                               \"\"\"Calculate marginalized graph kernel between 2 graphs.\n",
-    "    69                                               \n",
-    "    70                                               Parameters\n",
-    "    71                                               ----------\n",
-    "    72                                               G1, G2 : NetworkX graphs\n",
-    "    73                                                   2 graphs between which the kernel is calculated.\n",
-    "    74                                               node_label : string\n",
-    "    75                                                   node attribute used as label.\n",
-    "    76                                               edge_label : string\n",
-    "    77                                                   edge attribute used as label.\n",
-    "    78                                               p_quit : integer\n",
-    "    79                                                   the termination probability in the random walks generating step.\n",
-    "    80                                               itr : integer\n",
-    "    81                                                   time of iterations to calculate R_inf.\n",
-    "    82                                                   \n",
-    "    83                                               Return\n",
-    "    84                                               ------\n",
-    "    85                                               kernel : float\n",
-    "    86                                                   Marginalized Kernel between 2 graphs.\n",
-    "    87                                               \"\"\"\n",
-    "    88                                               # init parameters\n",
-    "    89     17205      12886.0      0.7      0.0      kernel = 0\n",
-    "    90     17205      52542.0      3.1      0.0      num_nodes_G1 = nx.number_of_nodes(G1)\n",
-    "    91     17205      28240.0      1.6      0.0      num_nodes_G2 = nx.number_of_nodes(G2)\n",
-    "    92     17205      15595.0      0.9      0.0      p_init_G1 = 1 / num_nodes_G1 # the initial probability distribution in the random walks generating step (uniform distribution over |G|)\n",
-    "    93     17205      11587.0      0.7      0.0      p_init_G2 = 1 / num_nodes_G2\n",
-    "    94                                           \n",
-    "    95     17205      11663.0      0.7      0.0      q = p_quit * p_quit\n",
-    "    96     17205      10728.0      0.6      0.0      r1 = q\n",
-    "    97                                           \n",
-    "    98                                               # initial R_inf\n",
-    "    99     17205      38412.0      2.2      0.0      R_inf = np.zeros([num_nodes_G1, num_nodes_G2]) # matrix to save all the R_inf for all pairs of nodes\n",
-    "   100                                           \n",
-    "   101                                               # calculate R_inf with a simple interative method\n",
-    "   102    344100     329235.0      1.0      0.0      for i in range(1, itr):\n",
-    "   103    326895     900354.0      2.8      0.1          R_inf_new = np.zeros([num_nodes_G1, num_nodes_G2])\n",
-    "   104    326895    2287346.0      7.0      0.3          R_inf_new.fill(r1)\n",
-    "   105                                           \n",
-    "   106                                                   # calculate R_inf for each pair of nodes\n",
-    "   107   2653464    3667117.0      1.4      0.4          for node1 in G1.nodes(data = True):\n",
-    "   108   2326569    7522840.0      3.2      0.9              neighbor_n1 = G1[node1[0]]\n",
-    "   109   2326569    3492118.0      1.5      0.4              p_trans_n1 = (1 - p_quit) / len(neighbor_n1) # the transition probability distribution in the random walks generating step (uniform distribution over the vertices adjacent to the current vertex)\n",
-    "   110  24024379   27775021.0      1.2      3.4              for node2 in G2.nodes(data = True):\n",
-    "   111  21697810   69471941.0      3.2      8.4                  neighbor_n2 = G2[node2[0]]\n",
-    "   112  21697810   32446626.0      1.5      3.9                  p_trans_n2 = (1 - p_quit) / len(neighbor_n2)    \n",
-    "   113                                           \n",
-    "   114  59095092   52545370.0      0.9      6.3                  for neighbor1 in neighbor_n1:\n",
-    "   115 104193150   92513935.0      0.9     11.2                      for neighbor2 in neighbor_n2:\n",
-    "   116                                           \n",
-    "   117                                                                   t = p_trans_n1 * p_trans_n2 * \\\n",
-    "   118  66795868  285324518.0      4.3     34.4                              deltakernel(G1.node[neighbor1][node_label] == G2.node[neighbor2][node_label]) * \\\n",
-    "   119  66795868  137934393.0      2.1     16.6                              deltakernel(neighbor_n1[neighbor1][edge_label] == neighbor_n2[neighbor2][edge_label])\n",
-    "   120  66795868  106834143.0      1.6     12.9                          R_inf_new[node1[0]][node2[0]] += t * R_inf[neighbor1][neighbor2] # ref [1] equation (8)\n",
-    "   121                                           \n",
-    "   122    326895    1123677.0      3.4      0.1          R_inf[:] = R_inf_new\n",
-    "   123                                           \n",
-    "   124                                               # add elements of R_inf up and calculate kernel\n",
-    "   125    139656     330283.0      2.4      0.0      for node1 in G1.nodes(data = True):\n",
-    "   126   1264441    1435263.0      1.1      0.2          for node2 in G2.nodes(data = True):                \n",
-    "   127   1141990    1377134.0      1.2      0.2              s = p_init_G1 * p_init_G2 * deltakernel(node1[1][node_label] == node2[1][node_label])\n",
-    "   128   1141990    1375456.0      1.2      0.2              kernel += s * R_inf[node1[0]][node2[0]] # ref [1] equation (6)\n",
-    "   129                                           \n",
-    "   130     17205      10801.0      0.6      0.0      return kernel"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "- This script take as input a kernel matrix\n",
-      "and returns the classification or regression performance\n",
-      "- The kernel matrix can be calculated using any of the graph kernels approaches\n",
-      "- The criteria used for prediction are SVM for classification and kernel Ridge regression for regression\n",
-      "- For predition we divide the data in training, validation and test. For each split, we first train on the train data, \n",
-      "then evaluate the performance on the validation. We choose the optimal parameters for the validation set and finally\n",
-      "provide the corresponding performance on the test set. If more than one split is performed, the final results \n",
-      "correspond to the average of the performances on the test sets. \n",
-      "\n",
-      "@references\n",
-      "    https://github.com/eghisu/GraphKernels/blob/master/GraphKernelsCollection/python_scripts/compute_perf_gk.py\n",
-      "\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "[ -23.7   14.    37.3  109.7   10.8   39.    42.    66.6  135.   148.5\n",
-      "   40.    34.6   32.    63.    53.5   67.    64.4   84.7   95.5   92.\n",
-      "   84.4  154.   156.   166.   183.    70.3   63.6   52.5   59.    59.5\n",
-      "   55.2   88.    83.   104.5  102.    92.   107.4  123.2  112.5  118.5\n",
-      "  101.5  173.7  165.5  181.    99.5   92.3   90.1   80.2   82.    91.2\n",
-      "   91.5   81.2   93.    69.    86.3   82.   103.   103.5   96.   112.   104.\n",
-      "  132.5  123.5  120.3  145.   144.2  142.8  132.   134.2  137.   139.\n",
-      "  133.6  120.4  120.   137.   195.8  177.2  181.   185.9  175.7  186.   211.\n",
-      "  125.   118.   117.1  107.   102.5  112.    97.4   91.5   87.6  106.5\n",
-      "  101.    99.3   90.   137.   114.   126.   124.   140.5  157.5  146.   145.\n",
-      "  141.   171.   166.   155.   145.   159.   138.   142.   159.   163.5\n",
-      "  229.5  142.   125.   132.   130.5  125.   122.   121.   122.2  112.   106.\n",
-      "  114.5  151.   128.5  109.5  126.   147.   158.   147.   165.   188.9\n",
-      "  170.   178.   148.5  165.   177.   167.   195.   226.   215.   201.   205.\n",
-      "  151.5  165.5  157.   139.   163.   153.5  139.   162.   173.   159.5\n",
-      "  159.5  155.5  141.   126.   164.   163.   166.5  146.   165.   159.   195.\n",
-      "  218.   250.   235.   186.5  156.5  162.   162.   170.2  173.2  186.8\n",
-      "  173.   187.   174.   188.5  199.   228.   215.   216.   240. ]\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      " --- calculating kernel matrix when termimation probability = 0.1 ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 246.21349620819092 seconds ---\n",
-      "[[ 0.0287062   0.0124634   0.00444444 ...,  0.00606061  0.00606061\n",
-      "   0.00606061]\n",
-      " [ 0.0124634   0.01108958  0.00333333 ...,  0.00454545  0.00454545\n",
-      "   0.00454545]\n",
-      " [ 0.00444444  0.00333333  0.0287062  ...,  0.00819912  0.00819912\n",
-      "   0.00975875]\n",
-      " ..., \n",
-      " [ 0.00606061  0.00454545  0.00819912 ...,  0.02846735  0.02836907\n",
-      "   0.02896354]\n",
-      " [ 0.00606061  0.00454545  0.00819912 ...,  0.02836907  0.02831424\n",
-      "   0.0288712 ]\n",
-      " [ 0.00606061  0.00454545  0.00975875 ...,  0.02896354  0.0288712\n",
-      "   0.02987915]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on val set: 51.192412\n",
-      "With standard deviation: 58.804642\n",
-      "\n",
-      " Mean performance on test set: 18.518782\n",
-      "With standard deviation: 7.749004\n",
-      "\n",
-      " --- calculating kernel matrix when termimation probability = 0.2 ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 240.73209404945374 seconds ---\n",
-      "[[ 0.06171557  0.03856471  0.01777778 ...,  0.02424242  0.02424242\n",
-      "   0.02424242]\n",
-      " [ 0.03856471  0.03579176  0.01333333 ...,  0.01818182  0.01818182\n",
-      "   0.01818182]\n",
-      " [ 0.01777778  0.01333333  0.06171557 ...,  0.02994207  0.02994207\n",
-      "   0.03262072]\n",
-      " ..., \n",
-      " [ 0.02424242  0.01818182  0.02994207 ...,  0.07442109  0.07434207\n",
-      "   0.07383563]\n",
-      " [ 0.02424242  0.01818182  0.02994207 ...,  0.07434207  0.07430377\n",
-      "   0.07376068]\n",
-      " [ 0.02424242  0.01818182  0.03262072 ...,  0.07383563  0.07376068\n",
-      "   0.07366354]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on val set: 56.692288\n",
-      "With standard deviation: 58.162153\n",
-      "\n",
-      " Mean performance on test set: 17.899091\n",
-      "With standard deviation: 6.591042\n",
-      "\n",
-      " --- calculating kernel matrix when termimation probability = 0.3 ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 244.91414594650269 seconds ---\n",
-      "[[ 0.09803909  0.07202114  0.04       ...,  0.05454545  0.05454545\n",
-      "   0.05454545]\n",
-      " [ 0.07202114  0.06853421  0.03       ...,  0.04090909  0.04090909\n",
-      "   0.04090909]\n",
-      " [ 0.04        0.03        0.09803909 ...,  0.06368916  0.06368916\n",
-      "   0.06678704]\n",
-      " ..., \n",
-      " [ 0.05454545  0.04090909  0.06368916 ...,  0.12892852  0.12891455\n",
-      "   0.12734365]\n",
-      " [ 0.05454545  0.04090909  0.06368916 ...,  0.12891455  0.12892664\n",
-      "   0.12733207]\n",
-      " [ 0.05454545  0.04090909  0.06678704 ...,  0.12734365  0.12733207\n",
-      "   0.1261675 ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on val set: 54.360795\n",
-      "With standard deviation: 61.733054\n",
-      "\n",
-      " Mean performance on test set: 18.392352\n",
-      "With standard deviation: 7.101611\n",
-      "\n",
-      " --- calculating kernel matrix when termimation probability = 0.4 ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 246.01012706756592 seconds ---\n",
-      "[[ 0.13888889  0.11120616  0.07111111 ...,  0.0969697   0.0969697\n",
-      "   0.0969697 ]\n",
-      " [ 0.11120616  0.10756609  0.05333333 ...,  0.07272727  0.07272727\n",
-      "   0.07272727]\n",
-      " [ 0.07111111  0.05333333  0.13888889 ...,  0.10909713  0.10909713\n",
-      "   0.11216176]\n",
-      " ..., \n",
-      " [ 0.0969697   0.07272727  0.10909713 ...,  0.19178929  0.19182091\n",
-      "   0.18963212]\n",
-      " [ 0.0969697   0.07272727  0.10909713 ...,  0.19182091  0.19186661\n",
-      "   0.18966477]\n",
-      " [ 0.0969697   0.07272727  0.11216176 ...,  0.18963212  0.18966477\n",
-      "   0.18786824]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on val set: 44.518253\n",
-      "With standard deviation: 44.478206\n",
-      "\n",
-      " Mean performance on test set: 19.623259\n",
-      "With standard deviation: 6.248069\n",
-      "\n",
-      " --- calculating kernel matrix when termimation probability = 0.5 ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 241.62482810020447 seconds ---\n",
-      "[[ 0.18518519  0.15591398  0.11111111 ...,  0.15151515  0.15151515\n",
-      "   0.15151515]\n",
-      " [ 0.15591398  0.15254237  0.08333333 ...,  0.11363636  0.11363636\n",
-      "   0.11363636]\n",
-      " [ 0.11111111  0.08333333  0.18518519 ...,  0.16617791  0.16617791\n",
-      "   0.16890214]\n",
-      " ..., \n",
-      " [ 0.15151515  0.11363636  0.16617791 ...,  0.26386999  0.26391515\n",
-      "   0.26158184]\n",
-      " [ 0.15151515  0.11363636  0.16617791 ...,  0.26391515  0.26396688\n",
-      "   0.26162729]\n",
-      " [ 0.15151515  0.11363636  0.16890214 ...,  0.26158184  0.26162729\n",
-      "   0.25964592]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on val set: 42.848719\n",
-      "With standard deviation: 39.189276\n",
-      "\n",
-      " Mean performance on test set: 19.993624\n",
-      "With standard deviation: 6.299511\n",
-      "\n",
-      " --- calculating kernel matrix when termimation probability = 0.6 ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 240.8926112651825 seconds ---\n",
-      "[[ 0.23809524  0.20664506  0.16       ...,  0.21818182  0.21818182\n",
-      "   0.21818182]\n",
-      " [ 0.20664506  0.20385906  0.12       ...,  0.16363636  0.16363636\n",
-      "   0.16363636]\n",
-      " [ 0.16        0.12        0.23809524 ...,  0.2351024   0.2351024\n",
-      "   0.23727718]\n",
-      " ..., \n",
-      " [ 0.21818182  0.16363636  0.2351024  ...,  0.34658956  0.34662512\n",
-      "   0.34454945]\n",
-      " [ 0.21818182  0.16363636  0.2351024  ...,  0.34662512  0.34666325\n",
-      "   0.34458505]\n",
-      " [ 0.21818182  0.16363636  0.23727718 ...,  0.34454945  0.34458505\n",
-      "   0.34279503]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on val set: 39.983104\n",
-      "With standard deviation: 32.270969\n",
-      "\n",
-      " Mean performance on test set: 20.546624\n",
-      "With standard deviation: 6.261735\n",
-      "\n",
-      " --- calculating kernel matrix when termimation probability = 0.7 ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 240.47843861579895 seconds ---\n",
-      "[[ 0.2991453   0.26444601  0.21777778 ...,  0.2969697   0.2969697\n",
-      "   0.2969697 ]\n",
-      " [ 0.26444601  0.26246188  0.16333333 ...,  0.22272727  0.22272727\n",
-      "   0.22272727]\n",
-      " [ 0.21777778  0.16333333  0.2991453  ...,  0.31614548  0.31614548\n",
-      "   0.31765009]\n",
-      " ..., \n",
-      " [ 0.2969697   0.22272727  0.31614548 ...,  0.44189997  0.44191814\n",
-      "   0.44038348]\n",
-      " [ 0.2969697   0.22272727  0.31614548 ...,  0.44191814  0.44193708\n",
-      "   0.44040164]\n",
-      " [ 0.2969697   0.22272727  0.31765009 ...,  0.44038348  0.44040164\n",
-      "   0.43906772]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " Mean performance on val set: 37.530308\n",
-      "With standard deviation: 29.730795\n",
-      "\n",
-      " Mean performance on test set: 21.701779\n",
-      "With standard deviation: 6.335305\n",
-      "\n",
-      " --- calculating kernel matrix when termimation probability = 0.8 ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 242.16377139091492 seconds ---\n",
-      "[[ 0.37037037  0.33093141  0.28444444 ...,  0.38787879  0.38787879\n",
-      "   0.38787879]\n",
-      " [ 0.33093141  0.32983023  0.21333333 ...,  0.29090909  0.29090909\n",
-      "   0.29090909]\n",
-      " [ 0.28444444  0.21333333  0.37037037 ...,  0.4096795   0.4096795\n",
-      "   0.41049599]\n",
-      " ..., \n",
-      " [ 0.38787879  0.29090909  0.4096795  ...,  0.55242487  0.55243009\n",
-      "   0.5515636 ]\n",
-      " [ 0.38787879  0.29090909  0.4096795  ...,  0.55243009  0.55243545\n",
-      "   0.55156881]\n",
-      " [ 0.38787879  0.29090909  0.41049599 ...,  0.5515636   0.55156881\n",
-      "   0.55081257]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on val set: 37.110483\n",
-      "With standard deviation: 21.287120\n",
-      "\n",
-      " Mean performance on test set: 23.148949\n",
-      "With standard deviation: 6.102457\n",
-      "\n",
-      " --- calculating kernel matrix when termimation probability = 0.9 ---\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- marginalized kernel matrix of size 185 built in 238.44418454170227 seconds ---\n",
-      "[[ 0.45454545  0.40839542  0.36       ...,  0.49090909  0.49090909\n",
-      "   0.49090909]\n",
-      " [ 0.40839542  0.40805534  0.27       ...,  0.36818182  0.36818182\n",
-      "   0.36818182]\n",
-      " [ 0.36        0.27        0.45454545 ...,  0.51619708  0.51619708\n",
-      "   0.51644564]\n",
-      " ..., \n",
-      " [ 0.49090909  0.36818182  0.51619708 ...,  0.68172189  0.68172233\n",
-      "   0.68145294]\n",
-      " [ 0.49090909  0.36818182  0.51619708 ...,  0.68172233  0.68172277\n",
-      "   0.68145338]\n",
-      " [ 0.49090909  0.36818182  0.51644564 ...,  0.68145294  0.68145338\n",
-      "   0.68121781]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on val set: 30.572040\n",
-      "With standard deviation: 11.057046\n",
-      "\n",
-      " Mean performance on test set: 24.715650\n",
-      "With standard deviation: 4.891587\n",
-      "\n",
-      "\n",
-      "  p_quit      std     RMSE\n",
-      "--------  -------  -------\n",
-      "     0.1  7.749    18.5188\n",
-      "     0.2  6.59104  17.8991\n",
-      "     0.3  7.10161  18.3924\n",
-      "     0.4  6.24807  19.6233\n",
-      "     0.5  6.29951  19.9936\n",
-      "     0.6  6.26173  20.5466\n",
-      "     0.7  6.33531  21.7018\n",
-      "     0.8  6.10246  23.1489\n",
-      "     0.9  4.89159  24.7157\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Author: Elisabetta Ghisu\n",
-    "\n",
-    "\"\"\"\n",
-    "- This script take as input a kernel matrix\n",
-    "and returns the classification or regression performance\n",
-    "- The kernel matrix can be calculated using any of the graph kernels approaches\n",
-    "- The criteria used for prediction are SVM for classification and kernel Ridge regression for regression\n",
-    "- For predition we divide the data in training, validation and test. For each split, we first train on the train data, \n",
-    "then evaluate the performance on the validation. We choose the optimal parameters for the validation set and finally\n",
-    "provide the corresponding performance on the test set. If more than one split is performed, the final results \n",
-    "correspond to the average of the performances on the test sets. \n",
-    "\n",
-    "@references\n",
-    "    https://github.com/eghisu/GraphKernels/blob/master/GraphKernelsCollection/python_scripts/compute_perf_gk.py\n",
-    "\"\"\"\n",
-    "\n",
-    "print(__doc__)\n",
-    "\n",
-    "import sys\n",
-    "import os\n",
-    "import pathlib\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from tabulate import tabulate\n",
-    "\n",
-    "import random\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "from sklearn.kernel_ridge import KernelRidge # 0.17\n",
-    "from sklearn.metrics import accuracy_score, mean_squared_error\n",
-    "from sklearn import svm\n",
-    "\n",
-    "from pygraph.kernels.marginalizedKernel import marginalizedkernel\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "\n",
-    "print('\\n Loading dataset from file...')\n",
-    "dataset, y = loadDataset(\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "y = np.array(y)\n",
-    "print(y)\n",
-    "\n",
-    "# setup the parameters\n",
-    "model_type = 'regression' # Regression or classification problem\n",
-    "print('\\n --- This is a %s problem ---' % model_type)\n",
-    "\n",
-    "datasize = len(dataset)\n",
-    "trials = 100 # Trials for hyperparameters random search\n",
-    "splits = 10 # Number of splits of the data\n",
-    "alpha_grid = np.logspace(-10, 10, num = trials, base = 10) # corresponds to (2*C)^-1 in other linear models such as LogisticRegression\n",
-    "C_grid = np.logspace(-10, 10, num = trials, base = 10)\n",
-    "random.seed(20) # Set the seed for uniform parameter distribution\n",
-    "\n",
-    "# set the output path\n",
-    "kernel_file_path = 'kernelmatrices_marginalized_acyclic/'\n",
-    "if not os.path.exists(kernel_file_path):\n",
-    "    os.makedirs(kernel_file_path)\n",
-    "\n",
-    "\n",
-    "\"\"\"\n",
-    "-  Here starts the main program\n",
-    "-  First we permute the data, then for each split we evaluate corresponding performances\n",
-    "-  In the end, the performances are averaged over the test sets\n",
-    "\"\"\"\n",
-    "val_means_pquit = []\n",
-    "val_stds_pquit = []\n",
-    "test_means_pquit = []\n",
-    "test_stds_pquit = []\n",
-    "\n",
-    "\n",
-    "for p_quit in np.linspace(0.1, 0.9, 9):\n",
-    "    print('\\n --- calculating kernel matrix when termimation probability = %.1f ---' % p_quit)\n",
-    "\n",
-    "    # save kernel matrices to files / read kernel matrices from files\n",
-    "    kernel_file = kernel_file_path + 'p_quit-' + str(p_quit)\n",
-    "    path = pathlib.Path(kernel_file)\n",
-    "    # get train set kernel matrix\n",
-    "    if path.is_file():\n",
-    "        print('\\n Loading the kernel matrix from file...')\n",
-    "        Kmatrix = np.loadtxt(kernel_file)\n",
-    "        print(Kmatrix)\n",
-    "    else:\n",
-    "        print('\\n Calculating kernel matrix, this could take a while...')\n",
-    "        Kmatrix, run_time = marginalizedkernel(dataset, p_quit = p_quit, itr = 20, node_label = 'atom', edge_label = 'bond_type')\n",
-    "        print(Kmatrix)\n",
-    "        print('\\n Saving kernel matrix to file...')\n",
-    "        np.savetxt(kernel_file, Kmatrix)\n",
-    "\n",
-    "    # Initialize the performance of the best parameter trial on validation with the corresponding performance on test\n",
-    "    val_split = []\n",
-    "    test_split = []\n",
-    "\n",
-    "    # For each split of the data\n",
-    "    for j in range(10, 10 + splits):\n",
-    "#         print('\\n Starting split %d...' % j)\n",
-    "\n",
-    "        # Set the random set for data permutation\n",
-    "        random_state = int(j)\n",
-    "        np.random.seed(random_state)\n",
-    "        idx_perm = np.random.permutation(datasize)\n",
-    "    #     print(idx_perm)\n",
-    "\n",
-    "        # Permute the data\n",
-    "        y_perm = y[idx_perm] # targets permutation\n",
-    "    #     print(y_perm)\n",
-    "        Kmatrix_perm = Kmatrix[:, idx_perm] # inputs permutation\n",
-    "    #     print(Kmatrix_perm)\n",
-    "        Kmatrix_perm = Kmatrix_perm[idx_perm, :] # inputs permutation\n",
-    "\n",
-    "        # Set the training, validation and test\n",
-    "        # Note: the percentage can be set up by the user\n",
-    "        num_train_val = int((datasize * 90) / 100)         # 90% (of entire dataset) for training and validation\n",
-    "        num_test = datasize - num_train_val              # 10% (of entire dataset) for test\n",
-    "        num_train = int((num_train_val * 90) / 100) # 90% (of train + val) for training\n",
-    "        num_val = num_train_val - num_train # 10% (of train + val) for validation\n",
-    "\n",
-    "        # Split the kernel matrix\n",
-    "        Kmatrix_train = Kmatrix_perm[0:num_train, 0:num_train]\n",
-    "        Kmatrix_val = Kmatrix_perm[num_train:(num_train + num_val), 0:num_train]\n",
-    "        Kmatrix_test = Kmatrix_perm[(num_train + num_val):datasize, 0:num_train]\n",
-    "\n",
-    "        # Split the targets\n",
-    "        y_train = y_perm[0:num_train]\n",
-    "\n",
-    "        # Normalization step (for real valued targets only)\n",
-    "        if model_type == 'regression':\n",
-    "#             print('\\n Normalizing output y...')\n",
-    "            y_train_mean = np.mean(y_train)\n",
-    "            y_train_std = np.std(y_train)\n",
-    "            y_train = (y_train - y_train_mean) / float(y_train_std)\n",
-    "    #         print(y)\n",
-    "\n",
-    "        y_val = y_perm[num_train:(num_train + num_val)]\n",
-    "        y_test = y_perm[(num_train + num_val):datasize]\n",
-    "\n",
-    "        # Record the performance for each parameter trial respectively on validation and test set\n",
-    "        perf_all_val = []\n",
-    "        perf_all_test = []\n",
-    "\n",
-    "        # For each parameter trial\n",
-    "        for i in range(trials):\n",
-    "            # For regression use the Kernel Ridge method\n",
-    "            if model_type == 'regression':\n",
-    "    #             print('\\n Starting experiment for trial %d and parameter alpha = %3f\\n ' % (i, alpha_grid[i]))\n",
-    "\n",
-    "                # Fit the kernel ridge model\n",
-    "                KR = KernelRidge(kernel = 'precomputed', alpha = alpha_grid[i])\n",
-    "#                 KR = svm.SVR(kernel = 'precomputed', C = C_grid[i])\n",
-    "                KR.fit(Kmatrix_train, y_train)\n",
-    "\n",
-    "                # predict on the validation and test set\n",
-    "                y_pred = KR.predict(Kmatrix_val)\n",
-    "                y_pred_test = KR.predict(Kmatrix_test)\n",
-    "    #             print(y_pred)\n",
-    "\n",
-    "                # adjust prediction: needed because the training targets have been normalizaed\n",
-    "                y_pred = y_pred * float(y_train_std) + y_train_mean\n",
-    "    #             print(y_pred)\n",
-    "                y_pred_test = y_pred_test * float(y_train_std) + y_train_mean\n",
-    "    #             print(y_pred_test)\n",
-    "\n",
-    "                # root mean squared error on validation\n",
-    "                rmse = np.sqrt(mean_squared_error(y_val, y_pred))\n",
-    "                perf_all_val.append(rmse)\n",
-    "\n",
-    "                # root mean squared error in test \n",
-    "                rmse_test = np.sqrt(mean_squared_error(y_test, y_pred_test))\n",
-    "                perf_all_test.append(rmse_test)\n",
-    "\n",
-    "    #             print('The performance on the validation set is: %3f' % rmse)\n",
-    "    #             print('The performance on the test set is: %3f' % rmse_test)\n",
-    "\n",
-    "        # --- FIND THE OPTIMAL PARAMETERS --- #\n",
-    "        # For regression: minimise the mean squared error\n",
-    "        if model_type == 'regression':\n",
-    "\n",
-    "            # get optimal parameter on validation (argmin mean squared error)\n",
-    "            min_idx = np.argmin(perf_all_test)\n",
-    "            alpha_opt = alpha_grid[min_idx]\n",
-    "\n",
-    "            # performance corresponding to optimal parameter on val\n",
-    "            perf_val_opt = perf_all_val[min_idx]\n",
-    "\n",
-    "            # corresponding performance on test for the same parameter\n",
-    "            perf_test_opt = perf_all_test[min_idx]\n",
-    "\n",
-    "#             print('The best performance is for trial %d with parameter alpha = %3f' % (min_idx, alpha_opt))\n",
-    "#             print('The best performance on the validation set is: %3f' % perf_val_opt)\n",
-    "#             print('The corresponding performance on test set is: %3f' % perf_test_opt)\n",
-    "        \n",
-    "        # append the best performance on validation\n",
-    "        # at the current split\n",
-    "        val_split.append(perf_val_opt)\n",
-    "\n",
-    "        # append the correponding performance on the test set\n",
-    "        test_split.append(perf_test_opt)\n",
-    "        \n",
-    "    # average the results\n",
-    "    # mean of the validation performances over the splits\n",
-    "    val_mean = np.mean(np.asarray(val_split))\n",
-    "    # std deviation of validation over the splits\n",
-    "    val_std = np.std(np.asarray(val_split))\n",
-    "\n",
-    "    # mean of the test performances over the splits\n",
-    "    test_mean = np.mean(np.asarray(test_split))\n",
-    "    # std deviation of the test oer the splits\n",
-    "    test_std = np.std(np.asarray(test_split))\n",
-    "    \n",
-    "    print('\\n Mean performance on val set: %3f' % val_mean)\n",
-    "    print('With standard deviation: %3f' % val_std)\n",
-    "    print('\\n Mean performance on test set: %3f' % test_mean)\n",
-    "    print('With standard deviation: %3f' % test_std)\n",
-    "    \n",
-    "    val_means_pquit.append(val_mean)\n",
-    "    val_stds_pquit.append(val_std)\n",
-    "    test_means_pquit.append(test_mean)\n",
-    "    test_stds_pquit.append(test_std)\n",
-    "\n",
-    "print('\\n') \n",
-    "print(tabulate({'p_quit': np.linspace(0.1, 0.9, 9), 'RMSE': test_means_pquit, 'std': test_stds_pquit}, headers='keys'))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/.ipynb_checkpoints/run_pathkernel_acyclic-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/run_pathkernel_acyclic-checkpoint.ipynb
deleted file mode 100644
index 12df241..0000000
--- a/notebooks/.ipynb_checkpoints/run_pathkernel_acyclic-checkpoint.ipynb
+++ /dev/null
@@ -1,665 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The line_profiler extension is already loaded. To reload it, use:\n",
-      "  %reload_ext line_profiler\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- mean average path kernel matrix of size 185 built in 29.430902242660522 seconds ---\n",
-      "[[ 0.55555556  0.22222222  0.         ...,  0.          0.          0.        ]\n",
-      " [ 0.22222222  0.27777778  0.         ...,  0.          0.          0.        ]\n",
-      " [ 0.          0.          0.55555556 ...,  0.03030303  0.03030303\n",
-      "   0.03030303]\n",
-      " ..., \n",
-      " [ 0.          0.          0.03030303 ...,  0.08297521  0.05553719\n",
-      "   0.05256198]\n",
-      " [ 0.          0.          0.03030303 ...,  0.05553719  0.07239669\n",
-      "   0.0538843 ]\n",
-      " [ 0.          0.          0.03030303 ...,  0.05256198  0.0538843\n",
-      "   0.07438017]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 3.619948\n",
-      "With standard deviation: 0.512351\n",
-      "\n",
-      " Mean performance on test set: 18.418852\n",
-      "With standard deviation: 10.781119\n",
-      "\n",
-      "\n",
-      "  rmse_test    std_test    rmse_train    std_train    k_time\n",
-      "-----------  ----------  ------------  -----------  --------\n",
-      "    18.4189     10.7811       3.61995     0.512351   29.4309\n"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext line_profiler\n",
-    "\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.pathKernel import pathkernel, _pathkernel_do\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_path_acyclic/'\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type')\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, pathkernel, kernel_para, normalize = False)\n",
-    "\n",
-    "# %lprun -f _pathkernel_do \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, pathkernel, kernel_para, normalize = False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# results\n",
-    "\n",
-    "# with y normalization\n",
-    "  RMSE_test    std_test    RMSE_train    std_train    k_time\n",
-    "-----------  ----------  ------------  -----------  --------\n",
-    "    14.0015     6.93602       3.76191     0.702594   37.5759\n",
-    "\n",
-    "# without y normalization\n",
-    "  RMSE_test    std_test    RMSE_train    std_train    k_time\n",
-    "-----------  ----------  ------------  -----------  --------\n",
-    "    18.4189     10.7811       3.61995     0.512351   29.4309"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "- This script take as input a kernel matrix\n",
-      "and returns the classification or regression performance\n",
-      "- The kernel matrix can be calculated using any of the graph kernels approaches\n",
-      "- The criteria used for prediction are SVM for classification and kernel Ridge regression for regression\n",
-      "- For predition we divide the data in training, validation and test. For each split, we first train on the train data, \n",
-      "then evaluate the performance on the validation. We choose the optimal parameters for the validation set and finally\n",
-      "provide the corresponding performance on the test set. If more than one split is performed, the final results \n",
-      "correspond to the average of the performances on the test sets. \n",
-      "\n",
-      "@references\n",
-      "    https://github.com/eghisu/GraphKernels/blob/master/GraphKernelsCollection/python_scripts/compute_perf_gk.py\n",
-      "\n"
-     ]
-    },
-    {
-     "ename": "IndentationError",
-     "evalue": "unindent does not match any outer indentation level (utils.py, line 106)",
-     "output_type": "error",
-     "traceback": [
-      "Traceback \u001b[0;36m(most recent call last)\u001b[0m:\n",
-      "  File \u001b[1;32m\"/usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m2910\u001b[0m, in \u001b[1;35mrun_code\u001b[0m\n    exec(code_obj, self.user_global_ns, self.user_ns)\n",
-      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-1-0b5b9ebb5cc4>\"\u001b[0;36m, line \u001b[0;32m31\u001b[0;36m, in \u001b[0;35m<module>\u001b[0;36m\u001b[0m\n\u001b[0;31m    from pygraph.utils.utils import split_train_test\u001b[0m\n",
-      "\u001b[0;36m  File \u001b[0;32m\"../pygraph/utils/utils.py\"\u001b[0;36m, line \u001b[0;32m106\u001b[0m\n\u001b[0;31m    train_means_list = []\u001b[0m\n\u001b[0m                         ^\u001b[0m\n\u001b[0;31mIndentationError\u001b[0m\u001b[0;31m:\u001b[0m unindent does not match any outer indentation level\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Author: Elisabetta Ghisu\n",
-    "\n",
-    "\"\"\"\n",
-    "- This script take as input a kernel matrix\n",
-    "and returns the classification or regression performance\n",
-    "- The kernel matrix can be calculated using any of the graph kernels approaches\n",
-    "- The criteria used for prediction are SVM for classification and kernel Ridge regression for regression\n",
-    "- For predition we divide the data in training, validation and test. For each split, we first train on the train data, \n",
-    "then evaluate the performance on the validation. We choose the optimal parameters for the validation set and finally\n",
-    "provide the corresponding performance on the test set. If more than one split is performed, the final results \n",
-    "correspond to the average of the performances on the test sets. \n",
-    "\n",
-    "@references\n",
-    "    https://github.com/eghisu/GraphKernels/blob/master/GraphKernelsCollection/python_scripts/compute_perf_gk.py\n",
-    "\"\"\"\n",
-    "\n",
-    "print(__doc__)\n",
-    "\n",
-    "import sys\n",
-    "import os\n",
-    "import pathlib\n",
-    "from collections import OrderedDict\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from tabulate import tabulate\n",
-    "\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "from pygraph.kernels.pathKernel import pathkernel\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "from pygraph.utils.utils import split_train_test\n",
-    "\n",
-    "train_means_list = []\n",
-    "train_stds_list = []\n",
-    "test_means_list = []\n",
-    "test_stds_list = []\n",
-    "kernel_time_list = []\n",
-    "\n",
-    "print('\\n Loading dataset from file...')\n",
-    "dataset, y = loadDataset(\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "y = np.array(y)\n",
-    "print(y)\n",
-    "\n",
-    "# setup the parameters\n",
-    "model_type = 'regression' # Regression or classification problem\n",
-    "print('\\n --- This is a %s problem ---' % model_type)\n",
-    "\n",
-    "trials = 100 # Trials for hyperparameters random search\n",
-    "splits = 10 # Number of splits of the data\n",
-    "alpha_grid = np.logspace(-10, 10, num = trials, base = 10) # corresponds to (2*C)^-1 in other linear models such as LogisticRegression\n",
-    "C_grid = np.logspace(-10, 10, num = trials, base = 10)\n",
-    "\n",
-    "# set the output path\n",
-    "kernel_file_path = 'kernelmatrices_path_acyclic/'\n",
-    "if not os.path.exists(kernel_file_path):\n",
-    "    os.makedirs(kernel_file_path)\n",
-    "\n",
-    "\"\"\"\n",
-    "-  Here starts the main program\n",
-    "-  First we permute the data, then for each split we evaluate corresponding performances\n",
-    "-  In the end, the performances are averaged over the test sets\n",
-    "\"\"\"\n",
-    "\n",
-    "# save kernel matrices to files / read kernel matrices from files\n",
-    "kernel_file = kernel_file_path + 'km.ds'\n",
-    "path = pathlib.Path(kernel_file)\n",
-    "# get train set kernel matrix\n",
-    "if path.is_file():\n",
-    "    print('\\n Loading the kernel matrix from file...')\n",
-    "    Kmatrix = np.loadtxt(kernel_file)\n",
-    "    print(Kmatrix)\n",
-    "else:\n",
-    "    print('\\n Calculating kernel matrix, this could take a while...')\n",
-    "    Kmatrix, run_time = pathkernel(dataset, node_label = 'atom', edge_label = 'bond_type')\n",
-    "    kernel_time_list.append(run_time)\n",
-    "    print(Kmatrix)\n",
-    "    print('\\n Saving kernel matrix to file...')\n",
-    "#     np.savetxt(kernel_file, Kmatrix)\n",
-    "    \n",
-    "train_mean, train_std, test_mean, test_std = \\\n",
-    "    split_train_test(Kmatrix, y, alpha_grid, C_grid, splits, trials, model_type, normalize = True)\n",
-    "    \n",
-    "train_means_list.append(train_mean)\n",
-    "train_stds_list.append(train_std)\n",
-    "test_means_list.append(test_mean)\n",
-    "test_stds_list.append(test_std)\n",
-    "        \n",
-    "print('\\n') \n",
-    "table_dict = {'RMSE_test': test_means_list, 'std_test': test_stds_list, \\\n",
-    "    'RMSE_train': train_means_list, 'std_train': train_stds_list, 'k_time': kernel_time_list}\n",
-    "keyorder = ['RMSE_test', 'std_test', 'RMSE_train', 'std_train', 'k_time']\n",
-    "print(tabulate(OrderedDict(sorted(table_dict.items(), key = lambda i:keyorder.index(i[0]))), headers='keys'))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "ImportError",
-     "evalue": "cannot import name 'deltaKernel'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mImportError\u001b[0m                               Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-1-51fa7de99690>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minsert\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"../\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mpygraph\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mutils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgraphfiles\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mloadDataset\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mpygraph\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkernels\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdeltaKernel\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mdeltaKernel\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0mdataset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mloadDataset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mImportError\u001b[0m: cannot import name 'deltaKernel'"
-     ]
-    }
-   ],
-   "source": [
-    "import sys\n",
-    "import networkx as nx\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "from pygraph.kernels.deltaKernel import deltaKernel\n",
-    "\n",
-    "dataset, y = loadDataset(\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "G1 = dataset[12]\n",
-    "G2 = dataset[55]\n",
-    "sp1 = []\n",
-    "num_nodes = G1.number_of_nodes()\n",
-    "for node1 in range(num_nodes):\n",
-    "    for node2 in range(node1 + 1, num_nodes):\n",
-    "            sp1.append(nx.shortest_path(G1, node1, node2, weight = 'cost'))\n",
-    "print(sp1)\n",
-    "print(len(sp1))\n",
-    "sp2 = []\n",
-    "num_nodes = G2.number_of_nodes()\n",
-    "for node1 in range(num_nodes):\n",
-    "    for node2 in range(node1 + 1, num_nodes):\n",
-    "            sp2.append(nx.shortest_path(G2, node1, node2, weight = 'cost'))\n",
-    "print(sp2)\n",
-    "print(len(sp2))\n",
-    "\n",
-    "kernel = 0\n",
-    "for path1 in sp1:\n",
-    "    for path2 in sp2:\n",
-    "        if len(path1) == len(path2):\n",
-    "            kernel_path = deltaKernel(G1.node[path1[0]]['label'] == G2.node[path2[0]]['label'])\n",
-    "            print(kernel_path)\n",
-    "            if kernel_path:\n",
-    "                print('yes')\n",
-    "                for i in range(1, len(path1)):\n",
-    "                    kernel_path *= deltaKernel(G1[path1[i - 1]][path1[i]]['label'] == G2[path2[i - 1]][path2[i]]['label']) * deltaKernel(G1.node[path1[i]]['label'] == G2.node[path2[i]]['label'])\n",
-    "                kernel += kernel_path\n",
-    "        \n",
-    "kernel = kernel / (len(sp1) * len(sp2))\n",
-    "\n",
-    "print(kernel)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "- This script take as input a kernel matrix\n",
-      "and returns the classification or regression performance\n",
-      "- The kernel matrix can be calculated using any of the graph kernels approaches\n",
-      "- The criteria used for prediction are SVM for classification and kernel Ridge regression for regression\n",
-      "- For predition we divide the data in training, validation and test. For each split, we first train on the train data, \n",
-      "then evaluate the performance on the validation. We choose the optimal parameters for the validation set and finally\n",
-      "provide the corresponding performance on the test set. If more than one split is performed, the final results \n",
-      "correspond to the average of the performances on the test sets. \n",
-      "\n",
-      "@references\n",
-      "    https://github.com/eghisu/GraphKernels/blob/master/GraphKernelsCollection/python_scripts/compute_perf_gk.py\n",
-      "\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      " Normalizing output y...\n",
-      "\n",
-      " Loading the train set kernel matrix from file...\n",
-      "[[ 0.15254237  0.08333333  0.0625     ...,  0.11363636  0.11363636\n",
-      "   0.11363636]\n",
-      " [ 0.08333333  0.18518519  0.15591398 ...,  0.16617791  0.16617791\n",
-      "   0.16890214]\n",
-      " [ 0.0625      0.15591398  0.15254237 ...,  0.12987013  0.12987013\n",
-      "   0.13163636]\n",
-      " ..., \n",
-      " [ 0.11363636  0.16617791  0.12987013 ...,  0.26383753  0.2639004\n",
-      "   0.26156557]\n",
-      " [ 0.11363636  0.16617791  0.12987013 ...,  0.2639004   0.26396688\n",
-      "   0.26162729]\n",
-      " [ 0.11363636  0.16890214  0.13163636 ...,  0.26156557  0.26162729\n",
-      "   0.25964592]]\n",
-      "\n",
-      " Loading the test set kernel matrix from file...\n",
-      "[[ 0.18518519  0.1715847   0.11111111  0.16588603  0.11904762  0.16450216\n",
-      "   0.17281421  0.14285714  0.125       0.16477273  0.16880154  0.14583333\n",
-      "   0.1660693   0.16906445  0.13333333  0.16612903  0.16420966  0.16441006\n",
-      "   0.15151515]\n",
-      " [ 0.1715847   0.19988118  0.15173333  0.18435596  0.16465263  0.21184723\n",
-      "   0.18985964  0.19960191  0.16819723  0.21540115  0.19575264  0.2041482\n",
-      "   0.21842419  0.20001664  0.18754969  0.2205599   0.20506165  0.22256445\n",
-      "   0.2141792 ]\n",
-      " [ 0.11111111  0.15173333  0.16303156  0.13416478  0.16903494  0.16960573\n",
-      "   0.13862936  0.18511129  0.16989276  0.17395417  0.14762351  0.18709221\n",
-      "   0.17706477  0.15293506  0.17970939  0.17975775  0.16082785  0.18295252\n",
-      "   0.19186573]\n",
-      " [ 0.16588603  0.18435596  0.13416478  0.17413923  0.14529511  0.19230449\n",
-      "   0.17775828  0.17598858  0.14892223  0.19462663  0.18166555  0.17986029\n",
-      "   0.1964604   0.18450695  0.16510376  0.19788853  0.1876399   0.19921541\n",
-      "   0.18843419]\n",
-      " [ 0.11904762  0.16465263  0.16903494  0.14529511  0.17703225  0.18464872\n",
-      "   0.15002895  0.19785455  0.17779663  0.18950917  0.16010081  0.2005743\n",
-      "   0.19306131  0.16599977  0.19113529  0.1960531   0.175064    0.19963794\n",
-      "   0.20696464]\n",
-      " [ 0.16450216  0.21184723  0.16960573  0.19230449  0.18464872  0.23269314\n",
-      "   0.19681552  0.22450276  0.1871932   0.23765844  0.20733248  0.22967925\n",
-      "   0.241199    0.21337314  0.21125341  0.24426963  0.22285333  0.24802555\n",
-      "   0.24156669]\n",
-      " [ 0.17281421  0.18985964  0.13862936  0.17775828  0.15002895  0.19681552\n",
-      "   0.18309269  0.18152273  0.15411585  0.19935309  0.18641218  0.18556038\n",
-      "   0.20169527  0.18946029  0.17030032  0.20320694  0.19192382  0.2042596\n",
-      "   0.19428999]\n",
-      " [ 0.14285714  0.19960191  0.18511129  0.17598858  0.19785455  0.22450276\n",
-      "   0.18152273  0.23269314  0.20168735  0.23049584  0.19407926  0.23694176\n",
-      "   0.23486084  0.20134404  0.22042984  0.23854906  0.21275711  0.24302959\n",
-      "   0.24678197]\n",
-      " [ 0.125       0.16819723  0.16989276  0.14892223  0.17779663  0.1871932\n",
-      "   0.15411585  0.20168735  0.18391356  0.19188588  0.16365606  0.20428161\n",
-      "   0.1952436   0.16940489  0.1919249   0.19815511  0.17760881  0.20152837\n",
-      "   0.20988805]\n",
-      " [ 0.16477273  0.21540115  0.17395417  0.19462663  0.18950917  0.23765844\n",
-      "   0.19935309  0.23049584  0.19188588  0.24296859  0.21058278  0.23586086\n",
-      "   0.24679036  0.21702635  0.21699483  0.25006701  0.22724646  0.25407837\n",
-      "   0.24818625]\n",
-      " [ 0.16880154  0.19575264  0.14762351  0.18166555  0.16010081  0.20733248\n",
-      "   0.18641218  0.19407926  0.16365606  0.21058278  0.19214629  0.19842989\n",
-      "   0.21317298  0.19609213  0.18225175  0.2151567   0.20088139  0.2171273\n",
-      "   0.20810339]\n",
-      " [ 0.14583333  0.2041482   0.18709221  0.17986029  0.2005743   0.22967925\n",
-      "   0.18556038  0.23694176  0.20428161  0.23586086  0.19842989  0.24154885\n",
-      "   0.24042054  0.20590264  0.22439219  0.24421452  0.21769149  0.24880304\n",
-      "   0.25200246]\n",
-      " [ 0.1660693   0.21842419  0.17706477  0.1964604   0.19306131  0.241199\n",
-      "   0.20169527  0.23486084  0.1952436   0.24679036  0.21317298  0.24042054\n",
-      "   0.25107069  0.21988195  0.22126548  0.25446921  0.23058896  0.25855949\n",
-      "   0.25312182]\n",
-      " [ 0.16906445  0.20001664  0.15293506  0.18450695  0.16599977  0.21337314\n",
-      "   0.18946029  0.20134404  0.16940489  0.21702635  0.19609213  0.20590264\n",
-      "   0.21988195  0.20052959  0.18917551  0.22212027  0.2061696   0.22441239\n",
-      "   0.21607563]\n",
-      " [ 0.13333333  0.18754969  0.17970939  0.16510376  0.19113529  0.21125341\n",
-      "   0.17030032  0.22042984  0.1919249   0.21699483  0.18225175  0.22439219\n",
-      "   0.22126548  0.18917551  0.2112185   0.224781    0.20021961  0.22904467\n",
-      "   0.23356012]\n",
-      " [ 0.16612903  0.2205599   0.17975775  0.19788853  0.1960531   0.24426963\n",
-      "   0.20320694  0.23854906  0.19815511  0.25006701  0.2151567   0.24421452\n",
-      "   0.25446921  0.22212027  0.224781    0.25800115  0.23326559  0.26226067\n",
-      "   0.25717144]\n",
-      " [ 0.16420966  0.20506165  0.16082785  0.1876399   0.175064    0.22285333\n",
-      "   0.19192382  0.21275711  0.17760881  0.22724646  0.20088139  0.21769149\n",
-      "   0.23058896  0.2061696   0.20021961  0.23326559  0.21442192  0.2364528\n",
-      "   0.22891788]\n",
-      " [ 0.16441006  0.22256445  0.18295252  0.19921541  0.19963794  0.24802555\n",
-      "   0.2042596   0.24302959  0.20152837  0.25407837  0.2171273   0.24880304\n",
-      "   0.25855949  0.22441239  0.22904467  0.26226067  0.2364528   0.26687384\n",
-      "   0.26210305]\n",
-      " [ 0.15151515  0.2141792   0.19186573  0.18843419  0.20696464  0.24156669\n",
-      "   0.19428999  0.24678197  0.20988805  0.24818625  0.20810339  0.25200246\n",
-      "   0.25312182  0.21607563  0.23356012  0.25717144  0.22891788  0.26210305\n",
-      "   0.26386999]]\n"
-     ]
-    },
-    {
-     "ename": "ValueError",
-     "evalue": "Precomputed metric requires shape (n_queries, n_indexed). Got (19, 19) for 164 indexed.",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-30-d4c5f46d5abf>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m    133\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    134\u001b[0m             \u001b[0;31m# predict on the test set\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 135\u001b[0;31m             \u001b[0my_pred_test\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKR\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mKmatrix_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    136\u001b[0m     \u001b[0;31m#             print(y_pred)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    137\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/sklearn/kernel_ridge.py\u001b[0m in \u001b[0;36mpredict\u001b[0;34m(self, X)\u001b[0m\n\u001b[1;32m    182\u001b[0m         \"\"\"\n\u001b[1;32m    183\u001b[0m         \u001b[0mcheck_is_fitted\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m\"X_fit_\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"dual_coef_\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 184\u001b[0;31m         \u001b[0mK\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_kernel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mX_fit_\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    185\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mK\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdual_coef_\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/sklearn/kernel_ridge.py\u001b[0m in \u001b[0;36m_get_kernel\u001b[0;34m(self, X, Y)\u001b[0m\n\u001b[1;32m    119\u001b[0m                       \"coef0\": self.coef0}\n\u001b[1;32m    120\u001b[0m         return pairwise_kernels(X, Y, metric=self.kernel,\n\u001b[0;32m--> 121\u001b[0;31m                                 filter_params=True, **params)\n\u001b[0m\u001b[1;32m    122\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    123\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/sklearn/metrics/pairwise.py\u001b[0m in \u001b[0;36mpairwise_kernels\u001b[0;34m(X, Y, metric, filter_params, n_jobs, **kwds)\u001b[0m\n\u001b[1;32m   1389\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1390\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mmetric\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"precomputed\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1391\u001b[0;31m         \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_pairwise_arrays\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprecomputed\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1392\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1393\u001b[0m     \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmetric\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mGPKernel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/sklearn/metrics/pairwise.py\u001b[0m in \u001b[0;36mcheck_pairwise_arrays\u001b[0;34m(X, Y, precomputed, dtype)\u001b[0m\n\u001b[1;32m    117\u001b[0m                              \u001b[0;34m\"(n_queries, n_indexed). Got (%d, %d) \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    118\u001b[0m                              \u001b[0;34m\"for %d indexed.\"\u001b[0m \u001b[0;34m%\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 119\u001b[0;31m                              (X.shape[0], X.shape[1], Y.shape[0]))\n\u001b[0m\u001b[1;32m    120\u001b[0m     \u001b[0;32melif\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    121\u001b[0m         raise ValueError(\"Incompatible dimension for X and Y matrices: \"\n",
-      "\u001b[0;31mValueError\u001b[0m: Precomputed metric requires shape (n_queries, n_indexed). Got (19, 19) for 164 indexed."
-     ]
-    }
-   ],
-   "source": [
-    "# Author: Elisabetta Ghisu\n",
-    "\n",
-    "\"\"\"\n",
-    "- This script take as input a kernel matrix\n",
-    "and returns the classification or regression performance\n",
-    "- The kernel matrix can be calculated using any of the graph kernels approaches\n",
-    "- The criteria used for prediction are SVM for classification and kernel Ridge regression for regression\n",
-    "- For predition we divide the data in training, validation and test. For each split, we first train on the train data, \n",
-    "then evaluate the performance on the validation. We choose the optimal parameters for the validation set and finally\n",
-    "provide the corresponding performance on the test set. If more than one split is performed, the final results \n",
-    "correspond to the average of the performances on the test sets. \n",
-    "\n",
-    "@references\n",
-    "    https://github.com/eghisu/GraphKernels/blob/master/GraphKernelsCollection/python_scripts/compute_perf_gk.py\n",
-    "\"\"\"\n",
-    "\n",
-    "print(__doc__)\n",
-    "\n",
-    "import sys\n",
-    "import pathlib\n",
-    "import os\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from tabulate import tabulate\n",
-    "\n",
-    "import random\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "from sklearn.kernel_ridge import KernelRidge # 0.17\n",
-    "from sklearn.metrics import accuracy_score, mean_squared_error\n",
-    "from sklearn import svm\n",
-    "\n",
-    "from pygraph.kernels.pathKernel import pathKernel\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "\n",
-    "# print('\\n Loading dataset from file...')\n",
-    "# dataset, y = loadDataset(\"/home/ljia/Documents/research-repo/datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "# y = np.array(y)\n",
-    "# print(y)\n",
-    "\n",
-    "# kernel_file_path = 'marginalizedkernelmatrix.ds'\n",
-    "# path = pathlib.Path(kernel_file_path)\n",
-    "# if path.is_file():\n",
-    "#     print('\\n Loading the matrix from file...')\n",
-    "#     Kmatrix = np.loadtxt(kernel_file_path)\n",
-    "#     print(Kmatrix)\n",
-    "# else:\n",
-    "#     print('\\n Calculating kernel matrix, this could take a while...')\n",
-    "#     Kmatrix = marginalizeKernel(dataset)\n",
-    "#     print(Kmatrix)\n",
-    "#     print('Saving kernel matrix to file...')\n",
-    "#     np.savetxt(kernel_file_path, Kmatrix)\n",
-    "\n",
-    "# setup the parameters\n",
-    "model_type = 'regression' # Regression or classification problem\n",
-    "print('\\n --- This is a %s problem ---' % model_type)\n",
-    "\n",
-    "# datasize = len(dataset)\n",
-    "trials = 100 # Trials for hyperparameters random search\n",
-    "splits = 100 # Number of splits of the data\n",
-    "alpha_grid = np.linspace(0.01, 100, num = trials) # corresponds to (2*C)^-1 in other linear models such as LogisticRegression\n",
-    "# C_grid = np.linspace(0.0001, 10, num = trials)\n",
-    "random.seed(20) # Set the seed for uniform parameter distribution\n",
-    "data_dir = '/home/ljia/Documents/research-repo/datasets/acyclic/Acyclic/'\n",
-    "\n",
-    "# set the output path\n",
-    "kernel_file_path = 'kernelmatrices_marginalized_acyclic/'\n",
-    "if not os.path.exists(kernel_file_path):\n",
-    "    os.makedirs(kernel_file_path)\n",
-    "\n",
-    "\n",
-    "\"\"\"\n",
-    "-  Here starts the main program\n",
-    "-  First we permute the data, then for each split we evaluate corresponding performances\n",
-    "-  In the end, the performances are averaged over the test sets\n",
-    "\"\"\"\n",
-    "\n",
-    "# Initialize the performance of the best parameter trial on validation with the corresponding performance on test\n",
-    "val_split = []\n",
-    "test_split = []\n",
-    "\n",
-    "p_quit = 0.5\n",
-    "\n",
-    "# for each split of the data\n",
-    "for j in range(10):\n",
-    "    dataset_train, y_train = loadDataset(data_dir + 'trainset_' + str(j) + '.ds')\n",
-    "    dataset_test, y_test = loadDataset(data_dir + 'testset_' + str(j) + '.ds')\n",
-    "    \n",
-    "    # Normalization step (for real valued targets only)\n",
-    "    if model_type == 'regression':\n",
-    "        print('\\n Normalizing output y...')\n",
-    "        y_train_mean = np.mean(y_train)\n",
-    "        y_train_std = np.std(y_train)\n",
-    "        y_train = (y_train - y_train_mean) / float(y_train_std)\n",
-    "#         print(y)\n",
-    "    \n",
-    "    # save kernel matrices to files / read kernel matrices from files\n",
-    "    kernel_file_train = kernel_file_path + 'train' + str(j) + '_pquit_' + str(p_quit)\n",
-    "    kernel_file_test = kernel_file_path + 'test' + str(j) + '_pquit_' + str(p_quit)\n",
-    "    path_train = pathlib.Path(kernel_file_train)\n",
-    "    path_test = pathlib.Path(kernel_file_test)\n",
-    "    # get train set kernel matrix\n",
-    "    if path_train.is_file():\n",
-    "        print('\\n Loading the train set kernel matrix from file...')\n",
-    "        Kmatrix_train = np.loadtxt(kernel_file_train)\n",
-    "        print(Kmatrix_train)\n",
-    "    else:\n",
-    "        print('\\n Calculating train set kernel matrix, this could take a while...')\n",
-    "        Kmatrix_train = marginalizedkernel(dataset_train, p_quit, 20)\n",
-    "        print(Kmatrix_train)\n",
-    "        print('\\n Saving train set kernel matrix to file...')\n",
-    "        np.savetxt(kernel_file_train, Kmatrix_train)\n",
-    "    # get test set kernel matrix\n",
-    "    if path_test.is_file():\n",
-    "        print('\\n Loading the test set kernel matrix from file...')\n",
-    "        Kmatrix_test = np.loadtxt(kernel_file_test)\n",
-    "        print(Kmatrix_test)\n",
-    "    else:\n",
-    "        print('\\n Calculating test set kernel matrix, this could take a while...')\n",
-    "        Kmatrix_test = marginalizedkernel(dataset_test, p_quit, 20)\n",
-    "        print(Kmatrix_test)\n",
-    "        print('\\n Saving test set kernel matrix to file...')\n",
-    "        np.savetxt(kernel_file_test, Kmatrix_test)\n",
-    "\n",
-    "    # For each parameter trial\n",
-    "    for i in range(trials):\n",
-    "        # For regression use the Kernel Ridge method\n",
-    "        if model_type == 'regression':\n",
-    "    #             print('\\n Starting experiment for trial %d and parameter alpha = %3f\\n ' % (i, alpha_grid[i]))\n",
-    "\n",
-    "            # Fit the kernel ridge model\n",
-    "            KR = KernelRidge(kernel = 'precomputed', alpha = alpha_grid[i])\n",
-    "            KR.fit(Kmatrix_train, y_train)\n",
-    "\n",
-    "            # predict on the test set\n",
-    "            y_pred_test = KR.predict(Kmatrix_test)\n",
-    "    #             print(y_pred)\n",
-    "\n",
-    "            # adjust prediction: needed because the training targets have been normalized\n",
-    "            y_pred_test = y_pred_test * float(y_train_std) + y_train_mean\n",
-    "    #             print(y_pred_test)\n",
-    "\n",
-    "            # root mean squared error in test \n",
-    "            rmse_test = np.sqrt(mean_squared_error(y_test, y_pred_test))\n",
-    "            perf_all_test.append(rmse_test)\n",
-    "\n",
-    "    #             print('The performance on the validation set is: %3f' % rmse)\n",
-    "    #             print('The performance on the test set is: %3f' % rmse_test)\n",
-    "\n",
-    "    # --- FIND THE OPTIMAL PARAMETERS --- #\n",
-    "    # For regression: minimise the mean squared error\n",
-    "    if model_type == 'regression':\n",
-    "\n",
-    "        # get optimal parameter on test (argmin mean squared error)\n",
-    "        min_idx = np.argmin(perf_all_test)\n",
-    "        alpha_opt = alpha_grid[min_idx]\n",
-    "\n",
-    "        # corresponding performance on test for the same parameter\n",
-    "        perf_test_opt = perf_all_test[min_idx]\n",
-    "\n",
-    "        print('The best performance is for trial %d with parameter alpha = %3f' % (min_idx, alpha_opt))\n",
-    "        print('The corresponding performance on test set is: %3f' % perf_test_opt)\n",
-    "        \n",
-    "        \n",
-    "        \n",
-    "\n",
-    "# For each split of the data\n",
-    "for j in range(10, 10 + splits):\n",
-    "    print('Starting split %d...' % j)\n",
-    "\n",
-    "    # Set the random set for data permutation\n",
-    "    random_state = int(j)\n",
-    "    np.random.seed(random_state)\n",
-    "    idx_perm = np.random.permutation(datasize)\n",
-    "#     print(idx_perm)\n",
-    "    \n",
-    "    # Permute the data\n",
-    "    y_perm = y[idx_perm] # targets permutation\n",
-    "#     print(y_perm)\n",
-    "    Kmatrix_perm = Kmatrix[:, idx_perm] # inputs permutation\n",
-    "#     print(Kmatrix_perm)\n",
-    "    Kmatrix_perm = Kmatrix_perm[idx_perm, :] # inputs permutation\n",
-    "    \n",
-    "    # Set the training, validation and test\n",
-    "    # Note: the percentage can be set up by the user\n",
-    "    num_train_val = int((datasize * 90) / 100)         # 90% (of entire dataset) for training and validation\n",
-    "    num_test = datasize - num_train_val              # 10% (of entire dataset) for test\n",
-    "    num_train = int((num_train_val * 90) / 100) # 90% (of train + val) for training\n",
-    "    num_val = num_train_val - num_train # 10% (of train + val) for validation\n",
-    "    \n",
-    "    # Split the kernel matrix\n",
-    "    Kmatrix_train = Kmatrix_perm[0:num_train, 0:num_train]\n",
-    "    Kmatrix_val = Kmatrix_perm[num_train:(num_train + num_val), 0:num_train]\n",
-    "    Kmatrix_test = Kmatrix_perm[(num_train + num_val):datasize, 0:num_train]\n",
-    "\n",
-    "    # Split the targets\n",
-    "    y_train = y_perm[0:num_train]\n",
-    "\n",
-    "    # Normalization step (for real valued targets only)\n",
-    "    print('\\n Normalizing output y...')\n",
-    "    if model_type == 'regression':\n",
-    "        y_train_mean = np.mean(y_train)\n",
-    "        y_train_std = np.std(y_train)\n",
-    "        y_train = (y_train - y_train_mean) / float(y_train_std)\n",
-    "#         print(y)\n",
-    "        \n",
-    "    y_val = y_perm[num_train:(num_train + num_val)]\n",
-    "    y_test = y_perm[(num_train + num_val):datasize]\n",
-    "    \n",
-    "    # Record the performance for each parameter trial respectively on validation and test set\n",
-    "    perf_all_val = []\n",
-    "    perf_all_test = []\n",
-    "    \n",
-    "    "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/.ipynb_checkpoints/run_spkernel_acyclic-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/run_spkernel_acyclic-checkpoint.ipynb
deleted file mode 100644
index da4acc3..0000000
--- a/notebooks/.ipynb_checkpoints/run_spkernel_acyclic-checkpoint.ipynb
+++ /dev/null
@@ -1,559 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "--- This is a regression problem ---\n",
-      "\n",
-      "1. Loading dataset from file...\n",
-      "\n",
-      "2. Calculating gram matrices. This could take a while...\n",
-      "--- shortest path kernel matrix of size 183 built in 12.671883821487427 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {} is: \n",
-      "[[ 3.  1.  3. ...  1.  1.  1.]\n",
-      " [ 1.  6.  1. ...  0.  0.  3.]\n",
-      " [ 3.  1.  3. ...  1.  1.  1.]\n",
-      " ...\n",
-      " [ 1.  0.  1. ... 55. 21.  7.]\n",
-      " [ 1.  0.  1. ... 21. 55.  7.]\n",
-      " [ 1.  3.  1. ...  7.  7. 55.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fbc003bc7f0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "3. Fitting and predicting using nested cross validation. This could really take a while...\n",
-      "calculate performance:   0%|          | 1/630 [00:00<01:12,  8.66it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/sklearn/linear_model/ridge.py:154: UserWarning: Singular matrix in solving dual problem. Using least-squares solution instead.\n",
-      "  warnings.warn(\"Singular matrix in solving dual problem. Using \"\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "                                                                        \n",
-      "4. Getting final performances...\n",
-      "\n",
-      "best_params_out:  [{}]\n",
-      "best_params_in:  [{'alpha': 35.481338923357534}]\n",
-      "best_val_perf:  36.08752278925261\n",
-      "best_val_std:  0.9660235949265693\n",
-      "final_performance:  36.45033825376652\n",
-      "final_confidence:  6.625276016213645\n",
-      "train_performance:  28.645168242623424\n",
-      "train_std:  0.59327479451686\n",
-      "time to calculate gram matrix:  12.671883821487427 s\n",
-      "\n",
-      "params                 train_perf      valid_perf       test_perf          gram_matrix_time\n",
-      "---------------------  --------------  ---------------  ---------------  ------------------\n",
-      "{'alpha': '1.00e-01'}  463.68±735.85   1255.03±1875.15  1552.81±4500.30               12.67\n",
-      "{'alpha': '1.41e-01'}  371.29±454.77   910.40±924.50    893.80±1213.60                12.67\n",
-      "{'alpha': '2.00e-01'}  522.21±1406.90  1587.46±4629.03  1301.10±3657.93               12.67\n",
-      "{'alpha': '2.82e-01'}  248.98±245.92   721.57±817.51    569.68±566.78                 12.67\n",
-      "{'alpha': '3.98e-01'}  350.52±614.63   848.29±1379.89   830.27±1370.70                12.67\n",
-      "{'alpha': '5.62e-01'}  167.98±215.81   434.68±466.73    566.30±1462.66                12.67\n",
-      "{'alpha': '7.94e-01'}  157.92±268.28   432.36±664.00    452.75±857.58                 12.67\n",
-      "{'alpha': '1.12e+00'}  134.98±151.51   438.74±741.59    386.57±589.84                 12.67\n",
-      "{'alpha': '1.58e+00'}  97.98±149.69    234.55±335.91    237.38±304.30                 12.67\n",
-      "{'alpha': '2.24e+00'}  55.08±52.90     152.16±218.04    142.67±180.16                 12.67\n",
-      "{'alpha': '3.16e+00'}  57.00±44.47     170.95±206.48    143.07±176.76                 12.67\n",
-      "{'alpha': '4.47e+00'}  41.42±43.03     98.89±127.39     95.73±185.90                  12.67\n",
-      "{'alpha': '6.31e+00'}  29.24±1.43      48.94±3.64       48.05±9.90                    12.67\n",
-      "{'alpha': '8.91e+00'}  28.33±0.95      43.38±1.83       42.94±6.50                    12.67\n",
-      "{'alpha': '1.26e+01'}  27.92±0.76      40.24±1.40       40.08±5.78                    12.67\n",
-      "{'alpha': '1.78e+01'}  27.82±0.66      38.14±1.18       38.19±5.84                    12.67\n",
-      "{'alpha': '2.51e+01'}  28.04±0.61      36.78±1.05       37.00±6.19                    12.67\n",
-      "{'alpha': '3.55e+01'}  28.65±0.59      36.09±0.97       36.45±6.63                    12.67\n",
-      "{'alpha': '5.01e+01'}  32.00±10.86     37.44±6.49       38.66±11.46                   12.67\n",
-      "{'alpha': '7.08e+01'}  49.88±23.28     50.68±16.29      52.34±21.79                   12.67\n",
-      "{'alpha': '1.00e+02'}  35.36±1.02      39.45±1.20       40.39±8.79                    12.67\n",
-      "calculate performance: 100%|██████████| 630/630 [01:00<00:00, 16.40it/s]"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext line_profiler\n",
-    "%matplotlib inline\n",
-    "import numpy as np\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.model_selection_precomputed import model_selection_for_precomputed_kernel\n",
-    "from pygraph.kernels.spKernel import spkernel\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "estimator = spkernel\n",
-    "param_grid_precomputed = {}\n",
-    "param_grid = {'alpha': np.logspace(-1, 2, num = 21, base = 10)}\n",
-    "\n",
-    "model_selection_for_precomputed_kernel(datafile, estimator, param_grid_precomputed, param_grid, \n",
-    "                                       'regression', NUM_TRIALS=30)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "--- shortest path kernel matrix of size 185 built in 13.3865065574646 seconds ---\n",
-      "[[ 3.  1.  3. ...  1.  1.  1.]\n",
-      " [ 1.  6.  1. ...  0.  0.  3.]\n",
-      " [ 3.  1.  3. ...  1.  1.  1.]\n",
-      " ...\n",
-      " [ 1.  0.  1. ... 55. 21.  7.]\n",
-      " [ 1.  0.  1. ... 21. 55.  7.]\n",
-      " [ 1.  3.  1. ...  7.  7. 55.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  94%|█████████▎| 936/1000 [00:01<00:00, 757.54it/s]\n",
-      " Mean performance on train set: 28.360361\n",
-      "With standard deviation: 1.357183\n",
-      "\n",
-      " Mean performance on test set: 35.191954\n",
-      "With standard deviation: 4.495767\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 771.22it/s]\n",
-      "\n",
-      "\n",
-      "  rmse_test    std_test    rmse_train    std_train    k_time\n",
-      "-----------  ----------  ------------  -----------  --------\n",
-      "     35.192     4.49577       28.3604      1.35718   13.3865\n"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext line_profiler\n",
-    "\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.spKernel import spkernel\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_path_acyclic/'\n",
-    "\n",
-    "kernel_para = dict(edge_weight = 'atom')\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, spkernel, kernel_para, normalize = False)\n",
-    "\n",
-    "# %lprun -f spkernel \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, spkernel, kernel_para, normalize = False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# results\n",
-    "\n",
-    "# with y normalization\n",
-    "  RMSE_test    std_test    RMSE_train    std_train    k_time\n",
-    "-----------  ----------  ------------  -----------  --------\n",
-    "    35.6337     5.23183       32.3805      3.92531   14.9301\n",
-    "\n",
-    "# without y normalization\n",
-    "  RMSE_test    std_test    RMSE_train    std_train    k_time\n",
-    "-----------  ----------  ------------  -----------  --------\n",
-    "     35.192     4.49577       28.3604      1.35718   14.5768"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "- This script take as input a kernel matrix\n",
-      "and returns the classification or regression performance\n",
-      "- The kernel matrix can be calculated using any of the graph kernels approaches\n",
-      "- The criteria used for prediction are SVM for classification and kernel Ridge regression for regression\n",
-      "- For predition we divide the data in training, validation and test. For each split, we first train on the train data, \n",
-      "then evaluate the performance on the validation. We choose the optimal parameters for the validation set and finally\n",
-      "provide the corresponding performance on the test set. If more than one split is performed, the final results \n",
-      "correspond to the average of the performances on the test sets. \n",
-      "\n",
-      "@references\n",
-      "    https://github.com/eghisu/GraphKernels/blob/master/GraphKernelsCollection/python_scripts/compute_perf_gk.py\n",
-      "\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "[ -23.7   14.    37.3  109.7   10.8   39.    42.    66.6  135.   148.5\n",
-      "   40.    34.6   32.    63.    53.5   67.    64.4   84.7   95.5   92.\n",
-      "   84.4  154.   156.   166.   183.    70.3   63.6   52.5   59.    59.5\n",
-      "   55.2   88.    83.   104.5  102.    92.   107.4  123.2  112.5  118.5\n",
-      "  101.5  173.7  165.5  181.    99.5   92.3   90.1   80.2   82.    91.2\n",
-      "   91.5   81.2   93.    69.    86.3   82.   103.   103.5   96.   112.   104.\n",
-      "  132.5  123.5  120.3  145.   144.2  142.8  132.   134.2  137.   139.\n",
-      "  133.6  120.4  120.   137.   195.8  177.2  181.   185.9  175.7  186.   211.\n",
-      "  125.   118.   117.1  107.   102.5  112.    97.4   91.5   87.6  106.5\n",
-      "  101.    99.3   90.   137.   114.   126.   124.   140.5  157.5  146.   145.\n",
-      "  141.   171.   166.   155.   145.   159.   138.   142.   159.   163.5\n",
-      "  229.5  142.   125.   132.   130.5  125.   122.   121.   122.2  112.   106.\n",
-      "  114.5  151.   128.5  109.5  126.   147.   158.   147.   165.   188.9\n",
-      "  170.   178.   148.5  165.   177.   167.   195.   226.   215.   201.   205.\n",
-      "  151.5  165.5  157.   139.   163.   153.5  139.   162.   173.   159.5\n",
-      "  159.5  155.5  141.   126.   164.   163.   166.5  146.   165.   159.   195.\n",
-      "  218.   250.   235.   186.5  156.5  162.   162.   170.2  173.2  186.8\n",
-      "  173.   187.   174.   188.5  199.   228.   215.   216.   240. ]\n",
-      "\n",
-      " Loading the matrix from file...\n",
-      "[[  3.   1.   3. ...,   1.   1.   1.]\n",
-      " [  1.   6.   1. ...,   0.   0.   3.]\n",
-      " [  3.   1.   3. ...,   1.   1.   1.]\n",
-      " ..., \n",
-      " [  1.   0.   1. ...,  55.  21.   7.]\n",
-      " [  1.   0.   1. ...,  21.  55.   7.]\n",
-      " [  1.   3.   1. ...,   7.   7.  55.]]\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      " Starting split 10...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 12 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 40.422382\n",
-      "The corresponding performance on test set is: 47.424532\n",
-      "\n",
-      " Starting split 11...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 12 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 33.084913\n",
-      "The corresponding performance on test set is: 35.493699\n",
-      "\n",
-      " Starting split 12...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 12 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 31.306710\n",
-      "The corresponding performance on test set is: 33.173366\n",
-      "\n",
-      " Starting split 13...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 12 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 43.500424\n",
-      "The corresponding performance on test set is: 32.633129\n",
-      "\n",
-      " Starting split 14...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 10 with parameter alpha = 1.000000\n",
-      "The best performance on the validation set is: 53.561752\n",
-      "The corresponding performance on test set is: 42.883548\n",
-      "\n",
-      " Starting split 15...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 12 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 40.444773\n",
-      "The corresponding performance on test set is: 32.713040\n",
-      "\n",
-      " Starting split 16...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 11 with parameter alpha = 10.000000\n",
-      "The best performance on the validation set is: 37.046818\n",
-      "The corresponding performance on test set is: 37.337851\n",
-      "\n",
-      " Starting split 17...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 12 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 39.907628\n",
-      "The corresponding performance on test set is: 38.889064\n",
-      "\n",
-      " Starting split 18...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 12 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 29.879950\n",
-      "The corresponding performance on test set is: 27.652558\n",
-      "\n",
-      " Starting split 19...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 11 with parameter alpha = 10.000000\n",
-      "The best performance on the validation set is: 44.911892\n",
-      "The corresponding performance on test set is: 35.804454\n",
-      "\n",
-      " Mean performance on val set: 39.406724\n",
-      "With standard deviation: 6.720820\n",
-      "\n",
-      " Mean performance on test set: 36.400524\n",
-      "With standard deviation: 5.352940\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Author: Elisabetta Ghisu\n",
-    "\n",
-    "\"\"\"\n",
-    "- This script take as input a kernel matrix\n",
-    "and returns the classification or regression performance\n",
-    "- The kernel matrix can be calculated using any of the graph kernels approaches\n",
-    "- The criteria used for prediction are SVM for classification and kernel Ridge regression for regression\n",
-    "- For predition we divide the data in training, validation and test. For each split, we first train on the train data, \n",
-    "then evaluate the performance on the validation. We choose the optimal parameters for the validation set and finally\n",
-    "provide the corresponding performance on the test set. If more than one split is performed, the final results \n",
-    "correspond to the average of the performances on the test sets. \n",
-    "\n",
-    "@references\n",
-    "    https://github.com/eghisu/GraphKernels/blob/master/GraphKernelsCollection/python_scripts/compute_perf_gk.py\n",
-    "\"\"\"\n",
-    "\n",
-    "print(__doc__)\n",
-    "\n",
-    "import sys\n",
-    "import pathlib\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from tabulate import tabulate\n",
-    "\n",
-    "import random\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "from sklearn.kernel_ridge import KernelRidge # 0.17\n",
-    "from sklearn.metrics import accuracy_score, mean_squared_error\n",
-    "from sklearn import svm\n",
-    "\n",
-    "from pygraph.kernels.spkernel import spkernel\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "\n",
-    "print('\\n Loading dataset from file...')\n",
-    "dataset, y = loadDataset(\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "y = np.array(y)\n",
-    "print(y)\n",
-    "\n",
-    "kernel_file_path = 'kernelmatrix.ds'\n",
-    "path = pathlib.Path(kernel_file_path)\n",
-    "if path.is_file():\n",
-    "    print('\\n Loading the matrix from file...')\n",
-    "    Kmatrix = np.loadtxt(kernel_file_path)\n",
-    "    print(Kmatrix)\n",
-    "else:\n",
-    "    print('\\n Calculating kernel matrix, this could take a while...')\n",
-    "    #@Q: is it appropriate to use bond type between atoms as the edge weight to calculate shortest path????????\n",
-    "    Kmatrix, run_time = spkernel(dataset, edge_weight = 'bond_type')\n",
-    "    print(Kmatrix)\n",
-    "    print('Saving kernel matrix to file...')\n",
-    "    np.savetxt(kernel_file_path, Kmatrix)\n",
-    "\n",
-    "# setup the parameters\n",
-    "model_type = 'regression' # Regression or classification problem\n",
-    "print('\\n --- This is a %s problem ---' % model_type)\n",
-    "\n",
-    "datasize = len(dataset)\n",
-    "trials = 21 # Trials for hyperparameters random search\n",
-    "splits = 10 # Number of splits of the data\n",
-    "alpha_grid = np.logspace(-10, 10, num = trials, base = 10) # corresponds to (2*C)^-1 in other linear models such as LogisticRegression\n",
-    "C_grid = np.logspace(-10, 10, num = trials, base = 10)\n",
-    "random.seed(20) # Set the seed for uniform parameter distribution\n",
-    "\n",
-    "\n",
-    "\"\"\"\n",
-    "-  Here starts the main program\n",
-    "-  First we permute the data, then for each split we evaluate corresponding performances\n",
-    "-  In the end, the performances are averaged over the test sets\n",
-    "\"\"\"\n",
-    "\n",
-    "# Initialize the performance of the best parameter trial on validation with the corresponding performance on test\n",
-    "val_split = []\n",
-    "test_split = []\n",
-    "\n",
-    "# For each split of the data\n",
-    "for j in range(10, 10 + splits):\n",
-    "    print('\\n Starting split %d...' % j)\n",
-    "\n",
-    "    # Set the random set for data permutation\n",
-    "    random_state = int(j)\n",
-    "    np.random.seed(random_state)\n",
-    "    idx_perm = np.random.permutation(datasize)\n",
-    "#     print(idx_perm)\n",
-    "    \n",
-    "    # Permute the data\n",
-    "    y_perm = y[idx_perm] # targets permutation\n",
-    "#     print(y_perm)\n",
-    "    Kmatrix_perm = Kmatrix[:, idx_perm] # inputs permutation\n",
-    "#     print(Kmatrix_perm)\n",
-    "    Kmatrix_perm = Kmatrix_perm[idx_perm, :] # inputs permutation\n",
-    "    \n",
-    "    # Set the training, validation and test\n",
-    "    # Note: the percentage can be set up by the user\n",
-    "    num_train_val = int((datasize * 90) / 100)         # 90% (of entire dataset) for training and validation\n",
-    "    num_test = datasize - num_train_val              # 10% (of entire dataset) for test\n",
-    "    num_train = int((num_train_val * 90) / 100) # 90% (of train + val) for training\n",
-    "    num_val = num_train_val - num_train # 10% (of train + val) for validation\n",
-    "    \n",
-    "    # Split the kernel matrix\n",
-    "    Kmatrix_train = Kmatrix_perm[0:num_train, 0:num_train]\n",
-    "    Kmatrix_val = Kmatrix_perm[num_train:(num_train + num_val), 0:num_train]\n",
-    "    Kmatrix_test = Kmatrix_perm[(num_train + num_val):datasize, 0:num_train]\n",
-    "\n",
-    "    # Split the targets\n",
-    "    y_train = y_perm[0:num_train]\n",
-    "\n",
-    "    # Normalization step (for real valued targets only)\n",
-    "    print('\\n Normalizing output y...')\n",
-    "    if model_type == 'regression':\n",
-    "        y_train_mean = np.mean(y_train)\n",
-    "        y_train_std = np.std(y_train)\n",
-    "        y_train = (y_train - y_train_mean) / float(y_train_std)\n",
-    "#         print(y)\n",
-    "        \n",
-    "    y_val = y_perm[num_train:(num_train + num_val)]\n",
-    "    y_test = y_perm[(num_train + num_val):datasize]\n",
-    "    \n",
-    "    # Record the performance for each parameter trial respectively on validation and test set\n",
-    "    perf_all_val = []\n",
-    "    perf_all_test = []\n",
-    "    \n",
-    "    # For each parameter trial\n",
-    "    for i in range(trials):\n",
-    "        # For regression use the Kernel Ridge method\n",
-    "        if model_type == 'regression':\n",
-    "#             print('\\n Starting experiment for trial %d and parameter alpha = %3f\\n ' % (i, alpha_grid[i]))\n",
-    "\n",
-    "            # Fit the kernel ridge model\n",
-    "            KR = KernelRidge(kernel = 'precomputed', alpha = alpha_grid[i])\n",
-    "#             KR = svm.SVR(kernel = 'precomputed', C = C_grid[i])\n",
-    "            KR.fit(Kmatrix_train, y_train)\n",
-    "\n",
-    "            # predict on the validation and test set\n",
-    "            y_pred = KR.predict(Kmatrix_val)\n",
-    "            y_pred_test = KR.predict(Kmatrix_test)\n",
-    "#             print(y_pred)\n",
-    "\n",
-    "            # adjust prediction: needed because the training targets have been normalizaed\n",
-    "            y_pred = y_pred * float(y_train_std) + y_train_mean\n",
-    "#             print(y_pred)\n",
-    "            y_pred_test = y_pred_test * float(y_train_std) + y_train_mean\n",
-    "#             print(y_pred_test)\n",
-    "\n",
-    "            # root mean squared error on validation\n",
-    "            rmse = np.sqrt(mean_squared_error(y_val, y_pred))\n",
-    "            perf_all_val.append(rmse)\n",
-    "\n",
-    "            # root mean squared error in test \n",
-    "            rmse_test = np.sqrt(mean_squared_error(y_test, y_pred_test))\n",
-    "            perf_all_test.append(rmse_test)\n",
-    "\n",
-    "#             print('The performance on the validation set is: %3f' % rmse)\n",
-    "#             print('The performance on the test set is: %3f' % rmse_test)\n",
-    "            \n",
-    "    # --- FIND THE OPTIMAL PARAMETERS --- #\n",
-    "    # For regression: minimise the mean squared error\n",
-    "    if model_type == 'regression':\n",
-    "\n",
-    "        # get optimal parameter on validation (argmin mean squared error)\n",
-    "        min_idx = np.argmin(perf_all_test)\n",
-    "        alpha_opt = alpha_grid[min_idx]\n",
-    "\n",
-    "        # performance corresponding to optimal parameter on val\n",
-    "        perf_val_opt = perf_all_val[min_idx]\n",
-    "\n",
-    "        # corresponding performance on test for the same parameter\n",
-    "        perf_test_opt = perf_all_test[min_idx]\n",
-    "\n",
-    "        print('The best performance is for trial %d with parameter alpha = %3f' % (min_idx, alpha_opt))\n",
-    "        print('The best performance on the validation set is: %3f' % perf_val_opt)\n",
-    "        print('The corresponding performance on test set is: %3f' % perf_test_opt)\n",
-    "\n",
-    "    # append the best performance on validation\n",
-    "    # at the current split\n",
-    "    val_split.append(perf_val_opt)\n",
-    "\n",
-    "    # append the correponding performance on the test set\n",
-    "    test_split.append(perf_test_opt)\n",
-    "\n",
-    "# average the results\n",
-    "# mean of the validation performances over the splits\n",
-    "val_mean = np.mean(np.asarray(val_split))\n",
-    "# std deviation of validation over the splits\n",
-    "val_std = np.std(np.asarray(val_split))\n",
-    "\n",
-    "# mean of the test performances over the splits\n",
-    "test_mean = np.mean(np.asarray(test_split))\n",
-    "# std deviation of the test oer the splits\n",
-    "test_std = np.std(np.asarray(test_split))\n",
-    "\n",
-    "print('\\n Mean performance on val set: %3f' % val_mean)\n",
-    "print('With standard deviation: %3f' % val_std)\n",
-    "print('\\n Mean performance on test set: %3f' % test_mean)\n",
-    "print('With standard deviation: %3f' % test_std)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/.ipynb_checkpoints/run_treeletkernel_acyclic-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/run_treeletkernel_acyclic-checkpoint.ipynb
deleted file mode 100644
index 59daf4d..0000000
--- a/notebooks/.ipynb_checkpoints/run_treeletkernel_acyclic-checkpoint.ipynb
+++ /dev/null
@@ -1,641 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- treelet kernel matrix of size 185 built in 0.47543811798095703 seconds ---\n",
-      "[[4.00000000e+00 2.60653066e+00 1.00000000e+00 ... 1.26641655e-14\n",
-      "  1.26641655e-14 1.26641655e-14]\n",
-      " [2.60653066e+00 6.00000000e+00 1.00000000e+00 ... 1.26641655e-14\n",
-      "  1.26641655e-14 1.26641655e-14]\n",
-      " [1.00000000e+00 1.00000000e+00 4.00000000e+00 ... 3.00000000e+00\n",
-      "  3.00000000e+00 3.00000000e+00]\n",
-      " ...\n",
-      " [1.26641655e-14 1.26641655e-14 3.00000000e+00 ... 1.80000000e+01\n",
-      "  1.30548713e+01 8.19020657e+00]\n",
-      " [1.26641655e-14 1.26641655e-14 3.00000000e+00 ... 1.30548713e+01\n",
-      "  2.20000000e+01 9.71901120e+00]\n",
-      " [1.26641655e-14 1.26641655e-14 3.00000000e+00 ... 8.19020657e+00\n",
-      "  9.71901120e+00 1.60000000e+01]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 983/1000 [00:01<00:00, 796.45it/s]\n",
-      " Mean performance on train set: 2.688029\n",
-      "With standard deviation: 1.541623\n",
-      "\n",
-      " Mean performance on test set: 10.099738\n",
-      "With standard deviation: 5.035844\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 745.11it/s]\n",
-      "\n",
-      "\n",
-      "  rmse_test    std_test    rmse_train    std_train    k_time\n",
-      "-----------  ----------  ------------  -----------  --------\n",
-      "    10.0997     5.03584       2.68803      1.54162  0.475438\n"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext line_profiler\n",
-    "\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.treeletKernel import treeletkernel\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_path_acyclic/'\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', labeled = True)\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, treeletkernel, kernel_para, normalize = False)\n",
-    "\n",
-    "# %lprun -f treeletkernel \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, treeletkernel, kernel_para, normalize = False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# results\n",
-    "\n",
-    "# with y normalization\n",
-    "  RMSE_test    std_test    RMSE_train    std_train    k_time\n",
-    "-----------  ----------  ------------  -----------  --------\n",
-    "     8.3079     3.37838       2.90887       1.2679   0.500302\n",
-    "\n",
-    "# without y normalization\n",
-    "  RMSE_test    std_test    RMSE_train    std_train    k_time\n",
-    "-----------  ----------  ------------  -----------  --------\n",
-    "    10.0997     5.03584       2.68803      1.54162   0.484171\n",
-    "\n",
-    "    \n",
-    "\n",
-    "# G0 -> WL subtree h = 0\n",
-    "  rmse_test    std_test    rmse_train    std_train    k_time\n",
-    "-----------  ----------  ------------  -----------  --------\n",
-    "    13.9223     2.88611        13.373     0.653301  0.186731\n",
-    "\n",
-    "# G0 U G1 U G6 U G8 U G13 -> WL subtree h = 1\n",
-    "  rmse_test    std_test    rmse_train    std_train    k_time\n",
-    "-----------  ----------  ------------  -----------  --------\n",
-    "    8.97706     2.90771        6.7343      1.17505  0.223171\n",
-    "    \n",
-    "# all patterns \\ { G3 U G4 U G5 U G10 }  -> WL subtree h = 2    \n",
-    "  rmse_test    std_test    rmse_train    std_train    k_time\n",
-    "-----------  ----------  ------------  -----------  --------\n",
-    "    7.31274     1.96289       3.73909     0.406267  0.294902\n",
-    "\n",
-    "# all patterns \\ { G4 U G5 }  -> WL subtree h = 3\n",
-    "  rmse_test    std_test    rmse_train    std_train    k_time\n",
-    "-----------  ----------  ------------  -----------  --------\n",
-    "    8.39977     2.78309        3.8606      1.58686  0.348912\n",
-    "\n",
-    "# all patterns \\ { G5 }    \n",
-    "  rmse_test    std_test    rmse_train    std_train    k_time\n",
-    "-----------  ----------  ------------  -----------  --------\n",
-    "    9.47647     4.22113       3.18029       1.5669  0.423638\n",
-    "    \n",
-    "    \n",
-    "    \n",
-    "# G0, -> WL subtree h = 0\n",
-    "  rmse_test    std_test    rmse_train    std_train    k_time\n",
-    "-----------  ----------  ------------  -----------  --------\n",
-    "    13.9223     2.88611        13.373     0.653301  0.186731  \n",
-    "    \n",
-    "# G0 U G1 U G2 U G6 U G8 U G13 -> WL subtree h = 1\n",
-    "  rmse_test    std_test    rmse_train    std_train    k_time\n",
-    "-----------  ----------  ------------  -----------  --------\n",
-    "    8.62431     2.54327       5.63422     0.255002  0.290797\n",
-    "    \n",
-    "# all patterns \\ { G5 U G10 }  -> WL subtree h = 2\n",
-    "  rmse_test    std_test    rmse_train    std_train    k_time\n",
-    "-----------  ----------  ------------  -----------  --------\n",
-    "    10.1294     3.50275       3.69664      1.55116  0.418498"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O', 6: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f23a4d68ef0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'O', 7: 'O'}\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f23a02cfac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " pattern 0:  [0, 1, 2, 3, 4, 5, 6, 7]\n",
-      " treelet 0:  ['C', 'C', 'C', 'C', 'C', 'C', 'O', 'O']\n",
-      "\n",
-      " pattern 1 :  [[4, 0], [4, 1], [5, 4], [6, 2], [6, 5], [7, 3], [7, 5]]\n",
-      " treelet 1 :  ['1C1C', '1C1C', '1C1C', '1C1O', '1C1O', '1C1O', '1C1O']\n",
-      "\n",
-      " pattern 2 :  [[1, 4, 0], [5, 4, 0], [5, 4, 1], [5, 6, 2], [5, 7, 3], [6, 5, 4], [7, 5, 4], [7, 5, 6]]\n",
-      " treelet 2 :  ['2C1C1C', '2C1C1C', '2C1C1C', '2C1O1C', '2C1O1C', '2C1C1O', '2C1C1O', '2O1C1O']\n",
-      "\n",
-      " pattern 3 :  [[4, 5, 6, 2], [4, 5, 7, 3], [6, 5, 4, 0], [6, 5, 4, 1], [6, 5, 7, 3], [7, 5, 4, 0], [7, 5, 4, 1], [7, 5, 6, 2]]\n",
-      " treelet 3 :  ['3C1C1O1C', '3C1C1O1C', '3C1C1C1O', '3C1C1C1O', '3C1O1C1O', '3C1C1C1O', '3C1C1C1O', '3C1O1C1O']\n",
-      "\n",
-      " pattern 4 :  [[2, 6, 5, 4, 0], [2, 6, 5, 4, 1], [3, 7, 5, 4, 0], [3, 7, 5, 4, 1], [3, 7, 5, 6, 2]]\n",
-      " treelet 4 :  ['4C1C1C1O1C', '4C1C1C1O1C', '4C1C1C1O1C', '4C1C1C1O1C', '4C1O1C1O1C']\n",
-      "\n",
-      " pattern 5 :  []\n",
-      " treelet 5 :  []\n",
-      "\n",
-      " pattern 3 star:  [[4, 0, 1, 5], [5, 4, 6, 7]]\n",
-      " treelet 3 star:  ['6CC1C1C1', '6CC1O1O1']\n",
-      "\n",
-      " pattern 4 star:  []\n",
-      " treelet 4 star:  []\n",
-      "\n",
-      " pattern 5 star:  []\n",
-      " treelet 5 star:  []\n",
-      "\n",
-      " pattern 7:  [[4, 0, 1, 5, 6], [4, 0, 1, 5, 7], [5, 7, 6, 4, 0], [5, 7, 6, 4, 1], [5, 4, 7, 6, 2], [5, 4, 6, 7, 3]]\n",
-      " treelet 7:  ['7CC1C1C1O1', '7CC1C1C1O1', '7CO1O1C1C1', '7CO1O1C1C1', '7CC1O1O1C1', '7CC1O1O1C1']\n",
-      "\n",
-      " pattern 11:  []\n",
-      " treelet 11:  []\n",
-      "\n",
-      " pattern 10:  [[4, 0, 1, 5, 6, 2], [4, 0, 1, 5, 7, 3]]\n",
-      " treelet 10:  ['aCO1C1C1C1C1', 'aCO1C1C1C1C1']\n",
-      "\n",
-      " pattern 12:  [[4, 0, 1, 5, 7, 6]]\n",
-      " treelet 12:  ['cCC1C1C1O1O1']\n",
-      "\n",
-      " pattern 9:  [[5, 7, 6, 4, 2, 0], [5, 7, 6, 4, 2, 1], [5, 6, 7, 4, 3, 0], [5, 6, 7, 4, 3, 1], [5, 4, 7, 6, 3, 2]]\n",
-      " treelet 9:  ['9CO1C1O1C1C1', '9CO1C1O1C1C1', '9CO1C1O1C1C1', '9CO1C1O1C1C1', '9CC1O1O1C1C1']\n",
-      "\n",
-      " numbers of canonical keys:  {'2O1C1O': 1, '7CC1C1C1O1': 2, '7CC1O1O1C1': 2, 'aCO1C1C1C1C1': 2, '2C1C1C': 3, '6CC1C1C1': 1, '9CO1C1O1C1C1': 4, '1C1C': 3, '3C1C1C1O': 4, '4C1C1C1O1C': 4, '7CO1O1C1C1': 2, '2C1C1O': 2, '1C1O': 4, '9CC1O1O1C1C1': 1, '3C1C1O1C': 2, '6CC1O1O1': 1, '2C1O1C': 2, '0O': 2, '4C1O1C1O1C': 1, 'cCC1C1C1O1O1': 1, '0C': 6, '3C1O1C1O': 2}\n",
-      "\n",
-      " pattern 0:  [0, 1, 2, 3, 4, 5, 6]\n",
-      " treelet 0:  ['C', 'C', 'C', 'C', 'C', 'O', 'O']\n",
-      "\n",
-      " pattern 1 :  [[2, 0], [3, 1], [5, 2], [5, 4], [6, 3], [6, 4]]\n",
-      " treelet 1 :  ['1C1C', '1C1C', '1C1O', '1C1O', '1C1O', '1C1O']\n",
-      "\n",
-      " pattern 2 :  [[4, 5, 2], [4, 6, 3], [5, 2, 0], [6, 3, 1], [6, 4, 5]]\n",
-      " treelet 2 :  ['2C1O1C', '2C1O1C', '2C1C1O', '2C1C1O', '2O1C1O']\n",
-      "\n",
-      " pattern 3 :  [[4, 5, 2, 0], [4, 6, 3, 1], [5, 4, 6, 3], [6, 4, 5, 2]]\n",
-      " treelet 3 :  ['3C1C1O1C', '3C1C1O1C', '3C1O1C1O', '3C1O1C1O']\n",
-      "\n",
-      " pattern 4 :  [[3, 6, 4, 5, 2], [5, 4, 6, 3, 1], [6, 4, 5, 2, 0]]\n",
-      " treelet 4 :  ['4C1O1C1O1C', '4C1C1O1C1O', '4C1C1O1C1O']\n",
-      "\n",
-      " pattern 5 :  [[2, 5, 4, 6, 3, 1], [3, 6, 4, 5, 2, 0]]\n",
-      " treelet 5 :  ['5C1C1O1C1O1C', '5C1C1O1C1O1C']\n",
-      "\n",
-      " pattern 3 star:  []\n",
-      " treelet 3 star:  []\n",
-      "\n",
-      " pattern 4 star:  []\n",
-      " treelet 4 star:  []\n",
-      "\n",
-      " pattern 5 star:  []\n",
-      " treelet 5 star:  []\n",
-      "\n",
-      " pattern 7:  []\n",
-      " treelet 7:  []\n",
-      "\n",
-      " pattern 11:  []\n",
-      " treelet 11:  []\n",
-      "\n",
-      " pattern 10:  []\n",
-      " treelet 10:  []\n",
-      "\n",
-      " pattern 12:  []\n",
-      " treelet 12:  []\n",
-      "\n",
-      " pattern 9:  []\n",
-      " treelet 9:  []\n",
-      "\n",
-      " numbers of canonical keys:  {'3C1C1O1C': 2, '2O1C1O': 1, '1C1O': 4, '2C1O1C': 2, '0O': 2, '5C1C1O1C1O1C': 2, '1C1C': 2, '4C1O1C1O1C': 1, '0C': 5, '3C1O1C1O': 2, '4C1C1O1C1O': 2, '2C1C1O': 2}\n"
-     ]
-    }
-   ],
-   "source": [
-    "import sys\n",
-    "import pathlib\n",
-    "from collections import Counter\n",
-    "from itertools import chain\n",
-    "sys.path.insert(0, \"../\")\n",
-    "\n",
-    "import networkx as nx\n",
-    "import numpy as np\n",
-    "import time\n",
-    "\n",
-    "from sklearn.metrics.pairwise import rbf_kernel, paired_distances\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "# main\n",
-    "import sys\n",
-    "from collections import Counter\n",
-    "import networkx as nx\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "\n",
-    "\n",
-    "def main(): \n",
-    "    dataset, y = loadDataset(\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "    G1 = dataset[15]\n",
-    "    print(nx.get_node_attributes(G1, 'label'))\n",
-    "    nx.draw_networkx(G1)\n",
-    "    plt.show()\n",
-    "    G2 = dataset[57] # 180 double 4, 57, 3, double 3\n",
-    "    print(nx.get_node_attributes(G2, 'label'))\n",
-    "    nx.draw_networkx(G2)\n",
-    "    plt.show()\n",
-    "\n",
-    "    treeletkernel(G1, G2, labeled = True)\n",
-    "    # Kmatrix = weisfeilerlehmankernel(G1, G2)\n",
-    "    \n",
-    "def find_paths(G, source_node, length):\n",
-    "    if length == 0:\n",
-    "        return [[source_node]]\n",
-    "    path = [ [source_node] + path for neighbor in G[source_node] \\\n",
-    "        for path in find_paths(G, neighbor, length - 1) if source_node not in path ]\n",
-    "    return path\n",
-    "\n",
-    "def find_all_paths(G, length):\n",
-    "    all_paths = []\n",
-    "    for node in G:\n",
-    "        all_paths.extend(find_paths(G, node, length))\n",
-    "    all_paths_r = [ path[::-1] for path in all_paths ]\n",
-    "    \n",
-    "    # remove double direction\n",
-    "    for idx, path in enumerate(all_paths[:-1]):\n",
-    "        for path2 in all_paths_r[idx+1::]:\n",
-    "            if path == path2:\n",
-    "                all_paths[idx] = []\n",
-    "                break\n",
-    "            \n",
-    "    return list(filter(lambda a: a != [], all_paths))\n",
-    "\n",
-    "def get_canonkey(G, node_label = 'atom', edge_label = 'bond_type', labeled = True):\n",
-    "    \n",
-    "        patterns = {}\n",
-    "        canonkey = {} # canonical key\n",
-    "    \n",
-    "        ### structural analysis ###\n",
-    "        # linear patterns\n",
-    "        patterns['0'] = G.nodes()\n",
-    "        canonkey['0'] = nx.number_of_nodes(G)\n",
-    "        for i in range(1, 6):\n",
-    "            patterns[str(i)] = find_all_paths(G, i)\n",
-    "            canonkey[str(i)] = len(patterns[str(i)])\n",
-    "                \n",
-    "        # n-star patterns\n",
-    "        patterns['3star'] = [ [node] + [neighbor for neighbor in G[node]] for node in G.nodes() if G.degree(node) == 3 ]\n",
-    "        patterns['4star'] = [ [node] + [neighbor for neighbor in G[node]] for node in G.nodes() if G.degree(node) == 4 ]\n",
-    "        patterns['5star'] = [ [node] + [neighbor for neighbor in G[node]] for node in G.nodes() if G.degree(node) == 5 ]        \n",
-    "        # n-star patterns\n",
-    "        canonkey['6'] = len(patterns['3star'])\n",
-    "        canonkey['8'] = len(patterns['4star'])\n",
-    "        canonkey['d'] = len(patterns['5star'])\n",
-    "        \n",
-    "        # pattern 7\n",
-    "        patterns['7'] = []\n",
-    "        for pattern in patterns['3star']:\n",
-    "            for i in range(1, len(pattern)):\n",
-    "                if G.degree(pattern[i]) >= 2:\n",
-    "                    pattern_t = pattern[:]\n",
-    "                    pattern_t[i], pattern_t[3] = pattern_t[3], pattern_t[i]\n",
-    "                    for neighborx in G[pattern[i]]:\n",
-    "                        if neighborx != pattern[0]:\n",
-    "                            new_pattern = pattern_t + [ neighborx ]\n",
-    "#                     new_patterns = [ pattern + [neighbor] for neighbor in G[pattern[i]] if neighbor != pattern[0] ]\n",
-    "                            patterns['7'].append(new_pattern)\n",
-    "        canonkey['7'] = len(patterns['7'])\n",
-    "        \n",
-    "        # pattern 11\n",
-    "        patterns['11'] = []\n",
-    "        for pattern in patterns['4star']:\n",
-    "            for i in range(1, len(pattern)):\n",
-    "                if G.degree(pattern[i]) >= 2:\n",
-    "                    pattern_t = pattern[:]\n",
-    "                    pattern_t[i], pattern_t[4] = pattern_t[4], pattern_t[i]\n",
-    "                    for neighborx in G[pattern[i]]:\n",
-    "                        if neighborx != pattern[0]:\n",
-    "                            new_pattern = pattern_t + [ neighborx ]\n",
-    "#                     new_patterns = [ pattern + [neighborx] for neighborx in G[pattern[i]] if neighborx != pattern[0] ]\n",
-    "                            patterns['11'].append(new_pattern)\n",
-    "        canonkey['b'] = len(patterns['11'])\n",
-    "        \n",
-    "        # pattern 12\n",
-    "        patterns['12'] = []\n",
-    "        rootlist = []\n",
-    "        for pattern in patterns['3star']:\n",
-    "#             print(pattern)\n",
-    "            if pattern[0] not in rootlist:\n",
-    "                rootlist.append(pattern[0])\n",
-    "                for i in range(1, len(pattern)):\n",
-    "                    if G.degree(pattern[i]) >= 3:\n",
-    "                        rootlist.append(pattern[i])\n",
-    "                        pattern_t = pattern[:]\n",
-    "                        pattern_t[i], pattern_t[3] = pattern_t[3], pattern_t[i]\n",
-    "                        for neighborx1 in G[pattern[i]]:\n",
-    "                            if neighborx1 != pattern[0]:\n",
-    "                                for neighborx2 in G[pattern[i]]:\n",
-    "                                    if neighborx1 > neighborx2 and neighborx2 != pattern[0]:\n",
-    "                                        new_pattern = pattern_t + [neighborx1] + [neighborx2]\n",
-    "#                         new_patterns = [ pattern + [neighborx1] + [neighborx2] for neighborx1 in G[pattern[i]] if neighborx1 != pattern[0] for neighborx2 in G[pattern[i]] if (neighborx1 > neighborx2 and neighborx2 != pattern[0]) ]\n",
-    "                                        patterns['12'].append(new_pattern)\n",
-    "        canonkey['c'] = int(len(patterns['12']) / 2)\n",
-    "        \n",
-    "        # pattern 9\n",
-    "        patterns['9'] = []\n",
-    "        for pattern in patterns['3star']:\n",
-    "#             print('pattern: ', pattern)\n",
-    "            for pairs in [ [neighbor1, neighbor2] for neighbor1 in G[pattern[0]] if G.degree(neighbor1) >= 2 \\\n",
-    "                for neighbor2 in G[pattern[0]] if G.degree(neighbor2) >= 2 if neighbor1 > neighbor2 ]:\n",
-    "#                 print('pairs: ', pairs)\n",
-    "                pattern_t = pattern[:]\n",
-    "#                 print('pattern_t: ', pattern_t)\n",
-    "                pattern_t[pattern_t.index(pairs[0])], pattern_t[2] = pattern_t[2], pattern_t[pattern_t.index(pairs[0])]\n",
-    "#                 print('pattern_t: ', pattern_t)\n",
-    "                pattern_t[pattern_t.index(pairs[1])], pattern_t[3] = pattern_t[3], pattern_t[pattern_t.index(pairs[1])]\n",
-    "#                 print('pattern_t: ', pattern_t)\n",
-    "                for neighborx1 in G[pairs[0]]:\n",
-    "                    if neighborx1 != pattern[0]:\n",
-    "                        for neighborx2 in G[pairs[1]]:\n",
-    "                            if neighborx2 != pattern[0]:\n",
-    "                                new_pattern = pattern_t + [neighborx1] + [neighborx2]\n",
-    "#                 new_patterns = [ pattern + [neighborx1] + [neighborx2] for neighborx1 in G[pairs[0]] if neighborx1 != pattern[0] for neighborx2 in G[pairs[1]] if neighborx2 != pattern[0] ]\n",
-    "                                patterns['9'].append(new_pattern)\n",
-    "        canonkey['9'] = len(patterns['9'])\n",
-    "        \n",
-    "        # pattern 10\n",
-    "        patterns['10'] = []\n",
-    "        for pattern in patterns['3star']:        \n",
-    "            for i in range(1, len(pattern)):\n",
-    "                if G.degree(pattern[i]) >= 2:\n",
-    "                    for neighborx in G[pattern[i]]:\n",
-    "                        if neighborx != pattern[0] and G.degree(neighborx) >= 2:\n",
-    "                            pattern_t = pattern[:]\n",
-    "                            pattern_t[i], pattern_t[3] = pattern_t[3], pattern_t[i]\n",
-    "                            new_patterns = [ pattern_t + [neighborx] + [neighborxx] for neighborxx in G[neighborx] if neighborxx != pattern[i] ]\n",
-    "                            patterns['10'].extend(new_patterns)\n",
-    "        canonkey['a'] = len(patterns['10'])\n",
-    "        \n",
-    "        ### labeling information ###\n",
-    "        if labeled == True:\n",
-    "            canonkey_l = {}\n",
-    "            \n",
-    "            # linear patterns\n",
-    "            canonkey_t = Counter(list(nx.get_node_attributes(G, node_label).values()))\n",
-    "            for key in canonkey_t:\n",
-    "                canonkey_l['0' + key] = canonkey_t[key]\n",
-    "            print('\\n pattern 0: ', patterns['0'])\n",
-    "            print(' treelet 0: ', list(nx.get_node_attributes(G, node_label).values()))\n",
-    "            \n",
-    "            for i in range(1, 6):\n",
-    "                treelet = []\n",
-    "                for pattern in patterns[str(i)]:\n",
-    "                    canonlist = list(chain.from_iterable((G.node[node][node_label], \\\n",
-    "                        G[node][pattern[idx+1]][edge_label]) for idx, node in enumerate(pattern[:-1])))\n",
-    "                    canonlist.append(G.node[pattern[-1]][node_label])\n",
-    "                    canonkey_t = ''.join(canonlist)\n",
-    "                    canonkey_t = canonkey_t if canonkey_t < canonkey_t[::-1] else canonkey_t[::-1]\n",
-    "                    treelet.append(str(i) + canonkey_t)\n",
-    "                canonkey_l.update(Counter(treelet))\n",
-    "                print('\\n pattern', i, ': ', patterns[str(i)])\n",
-    "                print(' treelet', i, ': ', treelet)\n",
-    "                \n",
-    "#             print(canonkey_l)\n",
-    "            \n",
-    "            # n-star patterns\n",
-    "            for i in range(3, 6):\n",
-    "                treelet = []\n",
-    "                for pattern in patterns[str(i) + 'star']:\n",
-    "                    canonlist = [ G.node[leaf][node_label] + G[leaf][pattern[0]][edge_label] for leaf in pattern[1:] ]\n",
-    "                    canonlist.sort()\n",
-    "                    canonkey_t = ('d' if i == 5 else str(i * 2)) + G.node[pattern[0]][node_label] + ''.join(canonlist)\n",
-    "                    treelet.append(canonkey_t)\n",
-    "                canonkey_l.update(Counter(treelet))\n",
-    "                print('\\n pattern', i, 'star: ', patterns[str(i) + 'star'])\n",
-    "                print(' treelet', i, 'star: ', treelet)\n",
-    "            \n",
-    "            # pattern 7\n",
-    "            treelet = []\n",
-    "            for pattern in patterns['7']:\n",
-    "                canonlist = [ G.node[leaf][node_label] + G[leaf][pattern[0]][edge_label] for leaf in pattern[1:3] ]\n",
-    "                canonlist.sort()\n",
-    "                canonkey_t = '7' + G.node[pattern[0]][node_label] + ''.join(canonlist) \\\n",
-    "                    + G.node[pattern[3]][node_label] + G[pattern[3]][pattern[0]][edge_label] \\\n",
-    "                     + G.node[pattern[4]][node_label] + G[pattern[4]][pattern[3]][edge_label]\n",
-    "                treelet.append(canonkey_t)\n",
-    "            canonkey_l.update(Counter(treelet))\n",
-    "            print('\\n pattern 7: ', patterns['7'])\n",
-    "            print(' treelet 7: ', treelet)\n",
-    "            \n",
-    "            # pattern 11\n",
-    "            treelet = []\n",
-    "            for pattern in patterns['11']:\n",
-    "                canonlist = [ G.node[leaf][node_label] + G[leaf][pattern[0]][edge_label] for leaf in pattern[1:4] ]\n",
-    "                canonlist.sort()\n",
-    "                canonkey_t = 'b' + G.node[pattern[0]][node_label] + ''.join(canonlist) \\\n",
-    "                    + G.node[pattern[4]][node_label] + G[pattern[4]][pattern[0]][edge_label] \\\n",
-    "                     + G.node[pattern[5]][node_label] + G[pattern[5]][pattern[4]][edge_label]\n",
-    "                treelet.append(canonkey_t)\n",
-    "            canonkey_l.update(Counter(treelet))\n",
-    "            print('\\n pattern 11: ', patterns['11'])\n",
-    "            print(' treelet 11: ', treelet)\n",
-    "\n",
-    "            # pattern 10\n",
-    "            treelet = []\n",
-    "            for pattern in patterns['10']:\n",
-    "                canonkey4 = G.node[pattern[5]][node_label] + G[pattern[5]][pattern[4]][edge_label]\n",
-    "                canonlist = [ G.node[leaf][node_label] + G[leaf][pattern[0]][edge_label] for leaf in pattern[1:3] ]\n",
-    "                canonlist.sort()\n",
-    "                canonkey0 = ''.join(canonlist)\n",
-    "                canonkey_t = 'a' + G.node[pattern[3]][node_label] \\\n",
-    "                    + G.node[pattern[4]][node_label] + G[pattern[4]][pattern[3]][edge_label] \\\n",
-    "                    + G.node[pattern[0]][node_label] + G[pattern[0]][pattern[3]][edge_label] \\\n",
-    "                    + canonkey4 + canonkey0\n",
-    "#                 canonkey_t = 'a' + G.node[pattern[0]][node_label] + ''.join(canonlist) \\\n",
-    "#                     + G.node[pattern[3]][node_label] + G[pattern[3]][pattern[0]][edge_label] \\\n",
-    "#                      + G.node[pattern[4]][node_label] + G[pattern[4]][pattern[3]][edge_label]\n",
-    "                treelet.append(canonkey_t)\n",
-    "            canonkey_l.update(Counter(treelet))\n",
-    "            print('\\n pattern 10: ', patterns['10'])\n",
-    "            print(' treelet 10: ', treelet)\n",
-    "            \n",
-    "            # pattern 12\n",
-    "            treelet = []\n",
-    "            for pattern in patterns['12']:\n",
-    "                canonlist0 = [ G.node[leaf][node_label] + G[leaf][pattern[0]][edge_label] for leaf in pattern[1:3] ]\n",
-    "                canonlist0.sort()\n",
-    "                canonlist3 = [ G.node[leaf][node_label] + G[leaf][pattern[3]][edge_label] for leaf in pattern[4:6] ]\n",
-    "                canonlist3.sort()\n",
-    "                canonkey_t1 = 'c' + G.node[pattern[0]][node_label] \\\n",
-    "                    + ''.join(canonlist0) \\\n",
-    "                    + G.node[pattern[3]][node_label] + G[pattern[3]][pattern[0]][edge_label] \\\n",
-    "                    + ''.join(canonlist3)\n",
-    "                    \n",
-    "                canonkey_t2 = 'c' + G.node[pattern[3]][node_label] \\\n",
-    "                    + ''.join(canonlist3) \\\n",
-    "                    + G.node[pattern[0]][node_label] + G[pattern[0]][pattern[3]][edge_label] \\\n",
-    "                    + ''.join(canonlist0)\n",
-    "                    \n",
-    "                treelet.append(canonkey_t1 if canonkey_t1 < canonkey_t2 else canonkey_t2)\n",
-    "            canonkey_l.update(Counter(treelet))\n",
-    "            print('\\n pattern 12: ', patterns['12'])\n",
-    "            print(' treelet 12: ', treelet)\n",
-    "            \n",
-    "            # pattern 9\n",
-    "            treelet = []\n",
-    "            for pattern in patterns['9']:\n",
-    "                canonkey2 = G.node[pattern[4]][node_label] + G[pattern[4]][pattern[2]][edge_label]\n",
-    "                canonkey3 = G.node[pattern[5]][node_label] + G[pattern[5]][pattern[3]][edge_label]\n",
-    "                prekey2 = G.node[pattern[2]][node_label] + G[pattern[2]][pattern[0]][edge_label]\n",
-    "                prekey3 = G.node[pattern[3]][node_label] + G[pattern[3]][pattern[0]][edge_label]\n",
-    "                if prekey2 + canonkey2 < prekey3 + canonkey3:\n",
-    "                    canonkey_t = G.node[pattern[1]][node_label] + G[pattern[1]][pattern[0]][edge_label] \\\n",
-    "                        + prekey2 + prekey3 + canonkey2 + canonkey3\n",
-    "                else:\n",
-    "                    canonkey_t = G.node[pattern[1]][node_label] + G[pattern[1]][pattern[0]][edge_label] \\\n",
-    "                        + prekey3 + prekey2 + canonkey3 + canonkey2\n",
-    "                treelet.append('9' + G.node[pattern[0]][node_label] + canonkey_t)\n",
-    "            canonkey_l.update(Counter(treelet))\n",
-    "            print('\\n pattern 9: ', patterns['9'])\n",
-    "            print(' treelet 9: ', treelet)\n",
-    "            \n",
-    "\n",
-    "            \n",
-    "            \n",
-    "            print('\\n numbers of canonical keys: ', canonkey_l)\n",
-    "                \n",
-    "            \n",
-    "            return canonkey_l\n",
-    "                    \n",
-    "        return canonkey\n",
-    "        \n",
-    "\n",
-    "def treeletkernel(*args, node_label = 'atom', edge_label = 'bond_type', labeled = True):\n",
-    "    if len(args) == 1: # for a list of graphs\n",
-    "        Gn = args[0]\n",
-    "        Kmatrix = np.zeros((len(Gn), len(Gn)))\n",
-    "\n",
-    "        start_time = time.time()\n",
-    "        \n",
-    "        for i in range(0, len(Gn)):\n",
-    "            print(i)\n",
-    "            for j in range(i, len(Gn)):\n",
-    "                Kmatrix[i][j] = treeletkernel(Gn[i], Gn[j], labeled = labeled, node_label = node_label, edge_label = edge_label)\n",
-    "                Kmatrix[j][i] = Kmatrix[i][j]\n",
-    "\n",
-    "        run_time = time.time() - start_time\n",
-    "        print(\"\\n --- treelet kernel matrix of size %d built in %s seconds ---\" % (len(Gn), run_time))\n",
-    "        \n",
-    "        return Kmatrix, run_time\n",
-    "    \n",
-    "    else: # for only 2 graphs\n",
-    "        \n",
-    "        G1 = args[0]\n",
-    "        G = args[1]\n",
-    "        kernel = 0\n",
-    "        \n",
-    "#         start_time = time.time()\n",
-    "        \n",
-    "                \n",
-    "        canonkey2 = get_canonkey(G, node_label = node_label, edge_label = edge_label, labeled = labeled)\n",
-    "        canonkey1 = get_canonkey(G1, node_label = node_label, edge_label = edge_label, labeled = labeled)\n",
-    "        \n",
-    "        keys = set(canonkey1.keys()) & set(canonkey2.keys()) # find same canonical keys in both graphs\n",
-    "        vector1 = np.matrix([ (canonkey1[key] if (key in canonkey1.keys()) else 0) for key in keys ])\n",
-    "#         print(vector1)\n",
-    "        vector2 = np.matrix([ (canonkey2[key] if (key in canonkey2.keys()) else 0) for key in keys ])        \n",
-    "        kernel = np.sum(np.exp(- np.square(vector1 - vector2) / 2))\n",
-    "#         print(vector2)\n",
-    "    \n",
-    "        # labeling information\n",
-    "        \n",
-    "        # equal keys and graph isomorphism\n",
-    "        \n",
-    "\n",
-    "#         run_time = time.time() - start_time\n",
-    "#         print(\"\\n --- treelet kernel built in %s seconds ---\" % (run_time))\n",
-    "        \n",
-    "#         print(kernel)\n",
-    "        return kernel#, run_time\n",
-    "    \n",
-    "if __name__ == '__main__':\n",
-    "    main()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/.ipynb_checkpoints/run_treepatternkernel-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/run_treepatternkernel-checkpoint.ipynb
deleted file mode 100644
index a5d9ae6..0000000
--- a/notebooks/.ipynb_checkpoints/run_treepatternkernel-checkpoint.ipynb
+++ /dev/null
@@ -1,3191 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1e-10 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.36956548690796 seconds ---\n",
-      "[[ 13.          14.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [ 14.          20.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [  4.           4.          13.         ...  29.          29.\n",
-      "   29.        ]\n",
-      " ...\n",
-      " [ 20.          20.          29.         ... 365.00000001 365.00000001\n",
-      "  365.00000001]\n",
-      " [ 20.          20.          29.         ... 365.00000001 365.00000001\n",
-      "  365.00000001]\n",
-      " [ 20.          20.          29.         ... 365.00000001 365.00000001\n",
-      "  365.00000002]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  91%|█████████▏| 914/1000 [00:01<00:00, 751.28it/s]\n",
-      " Mean performance on train set: 5.993535\n",
-      "With standard deviation: 0.356922\n",
-      "\n",
-      " Mean performance on test set: 7.464904\n",
-      "With standard deviation: 1.718585\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 795.88it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1e-09 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.47467517852783 seconds ---\n",
-      "[[ 13.          14.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [ 14.          20.00000001   4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [  4.           4.          13.         ...  29.          29.\n",
-      "   29.        ]\n",
-      " ...\n",
-      " [ 20.          20.          29.         ... 365.00000015 365.00000015\n",
-      "  365.00000015]\n",
-      " [ 20.          20.          29.         ... 365.00000015 365.00000015\n",
-      "  365.00000015]\n",
-      " [ 20.          20.          29.         ... 365.00000015 365.00000015\n",
-      "  365.0000002 ]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 975/1000 [00:01<00:00, 654.33it/s]\n",
-      " Mean performance on train set: 5.963041\n",
-      "With standard deviation: 0.374107\n",
-      "\n",
-      " Mean performance on test set: 7.375105\n",
-      "With standard deviation: 1.769252\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 711.24it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1e-08 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.32968211174011 seconds ---\n",
-      "[[ 13.00000004  14.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [ 14.          20.00000008   4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [  4.           4.          13.00000004 ...  29.00000004  29.00000004\n",
-      "   29.00000004]\n",
-      " ...\n",
-      " [ 20.          20.          29.00000004 ... 365.00000148 365.00000148\n",
-      "  365.00000148]\n",
-      " [ 20.          20.          29.00000004 ... 365.00000148 365.00000148\n",
-      "  365.00000148]\n",
-      " [ 20.          20.          29.00000004 ... 365.00000148 365.00000148\n",
-      "  365.00000202]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  97%|█████████▋| 967/1000 [00:01<00:00, 809.48it/s]\n",
-      " Mean performance on train set: 5.965110\n",
-      "With standard deviation: 0.378249\n",
-      "\n",
-      " Mean performance on test set: 7.350689\n",
-      "With standard deviation: 1.780556\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 786.78it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1e-07 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.74151062965393 seconds ---\n",
-      "[[ 13.0000004  14.          4.        ...  20.         20.\n",
-      "   20.       ]\n",
-      " [ 14.         20.0000008   4.        ...  20.         20.\n",
-      "   20.       ]\n",
-      " [  4.          4.         13.0000004 ...  29.0000004  29.0000004\n",
-      "   29.0000004]\n",
-      " ...\n",
-      " [ 20.         20.         29.0000004 ... 365.0000148 365.0000148\n",
-      "  365.0000148]\n",
-      " [ 20.         20.         29.0000004 ... 365.0000148 365.0000148\n",
-      "  365.0000148]\n",
-      " [ 20.         20.         29.0000004 ... 365.0000148 365.0000148\n",
-      "  365.0000202]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  95%|█████████▌| 954/1000 [00:01<00:00, 735.76it/s]\n",
-      " Mean performance on train set: 5.966982\n",
-      "With standard deviation: 0.382093\n",
-      "\n",
-      " Mean performance on test set: 7.350999\n",
-      "With standard deviation: 1.781470\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 804.24it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1e-06 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.52131748199463 seconds ---\n",
-      "[[ 13.000004  14.         4.       ...  20.        20.        20.      ]\n",
-      " [ 14.        20.000008   4.       ...  20.        20.        20.      ]\n",
-      " [  4.         4.        13.000004 ...  29.000004  29.000004  29.000004]\n",
-      " ...\n",
-      " [ 20.        20.        29.000004 ... 365.000148 365.000148 365.000148]\n",
-      " [ 20.        20.        29.000004 ... 365.000148 365.000148 365.000148]\n",
-      " [ 20.        20.        29.000004 ... 365.000148 365.000148 365.000202]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  97%|█████████▋| 970/1000 [00:01<00:00, 759.32it/s]\n",
-      " Mean performance on train set: 5.969758\n",
-      "With standard deviation: 0.386318\n",
-      "\n",
-      " Mean performance on test set: 7.351225\n",
-      "With standard deviation: 1.780522\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 783.42it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1e-05 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.67099857330322 seconds ---\n",
-      "[[ 13.00004     14.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [ 14.          20.00008      4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [  4.           4.          13.00004    ...  29.00004     29.00004\n",
-      "   29.00004   ]\n",
-      " ...\n",
-      " [ 20.          20.          29.00004    ... 365.00148001 365.00148001\n",
-      "  365.00148   ]\n",
-      " [ 20.          20.          29.00004    ... 365.00148001 365.00148001\n",
-      "  365.00148   ]\n",
-      " [ 20.          20.          29.00004    ... 365.00148    365.00148\n",
-      "  365.00202   ]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 801.70it/s]\n",
-      " Mean performance on train set: 5.970557\n",
-      "With standard deviation: 0.390719\n",
-      "\n",
-      " Mean performance on test set: 7.348129\n",
-      "With standard deviation: 1.780293\n",
-      "\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 0.0001 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 36.80127692222595 seconds ---\n",
-      "[[ 13.0004      14.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [ 14.          20.0008       4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [  4.           4.          13.0004     ...  29.0004      29.0004\n",
-      "   29.0004    ]\n",
-      " ...\n",
-      " [ 20.          20.          29.0004     ... 365.01480072 365.01480072\n",
-      "  365.0148    ]\n",
-      " [ 20.          20.          29.0004     ... 365.01480072 365.01480072\n",
-      "  365.0148    ]\n",
-      " [ 20.          20.          29.0004     ... 365.0148     365.0148\n",
-      "  365.0202    ]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 980/1000 [00:01<00:00, 889.41it/s]\n",
-      " Mean performance on train set: 5.942495\n",
-      "With standard deviation: 0.331983\n",
-      "\n",
-      " Mean performance on test set: 7.349836\n",
-      "With standard deviation: 1.781100\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 883.76it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 0.001 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 35.8681423664093 seconds ---\n",
-      "[[ 13.004     14.         4.       ...  20.        20.        20.      ]\n",
-      " [ 14.        20.008      4.       ...  20.        20.        20.      ]\n",
-      " [  4.         4.        13.004    ...  29.004     29.004     29.004   ]\n",
-      " ...\n",
-      " [ 20.        20.        29.004    ... 365.148072 365.148072 365.148   ]\n",
-      " [ 20.        20.        29.004    ... 365.148072 365.148072 365.148   ]\n",
-      " [ 20.        20.        29.004    ... 365.148    365.148    365.202   ]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  99%|█████████▉| 988/1000 [00:01<00:00, 886.54it/s]\n",
-      " Mean performance on train set: 5.933395\n",
-      "With standard deviation: 0.324965\n",
-      "\n",
-      " Mean performance on test set: 7.357745\n",
-      "With standard deviation: 1.780977\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 888.00it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 0.01 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 36.001843214035034 seconds ---\n",
-      "[[ 13.04    14.       4.     ...  20.      20.      20.    ]\n",
-      " [ 14.      20.08     4.     ...  20.      20.      20.    ]\n",
-      " [  4.       4.      13.04   ...  29.04    29.04    29.04  ]\n",
-      " ...\n",
-      " [ 20.      20.      29.04   ... 366.4872 366.4872 366.48  ]\n",
-      " [ 20.      20.      29.04   ... 366.4872 366.4872 366.48  ]\n",
-      " [ 20.      20.      29.04   ... 366.48   366.48   367.02  ]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 978/1000 [00:01<00:00, 863.94it/s]\n",
-      " Mean performance on train set: 5.940695\n",
-      "With standard deviation: 0.347431\n",
-      "\n",
-      " Mean performance on test set: 7.374269\n",
-      "With standard deviation: 1.791145\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 878.96it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 0.1 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 36.37146854400635 seconds ---\n",
-      "[[ 13.4   14.     4.   ...  20.    20.    20.  ]\n",
-      " [ 14.    20.8    4.   ...  20.    20.    20.  ]\n",
-      " [  4.     4.    13.4  ...  29.4   29.4   29.4 ]\n",
-      " ...\n",
-      " [ 20.    20.    29.4  ... 380.52 380.52 379.8 ]\n",
-      " [ 20.    20.    29.4  ... 380.52 380.52 379.8 ]\n",
-      " [ 20.    20.    29.4  ... 379.8  379.8  385.2 ]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  99%|█████████▉| 993/1000 [00:01<00:00, 860.40it/s]\n",
-      " Mean performance on train set: 6.427114\n",
-      "With standard deviation: 1.293674\n",
-      "\n",
-      " Mean performance on test set: 7.329299\n",
-      "With standard deviation: 1.913634\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 883.01it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.83972358703613 seconds ---\n",
-      "[[ 17.  14.   4. ...  20.  20.  20.]\n",
-      " [ 14.  28.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.  17. ...  33.  33.  33.]\n",
-      " ...\n",
-      " [ 20.  20.  33. ... 585. 585. 513.]\n",
-      " [ 20.  20.  33. ... 585. 585. 513.]\n",
-      " [ 20.  20.  33. ... 513. 513. 567.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 979/1000 [00:01<00:00, 616.77it/s]\n",
-      " Mean performance on train set: 6.624254\n",
-      "With standard deviation: 1.224196\n",
-      "\n",
-      " Mean performance on test set: 7.271336\n",
-      "With standard deviation: 2.207735\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 630.82it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 10.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.50818395614624 seconds ---\n",
-      "[[5.300e+01 1.400e+01 4.000e+00 ... 2.000e+01 2.000e+01 2.000e+01]\n",
-      " [1.400e+01 1.000e+02 4.000e+00 ... 2.000e+01 2.000e+01 2.000e+01]\n",
-      " [4.000e+00 4.000e+00 5.300e+01 ... 6.900e+01 6.900e+01 6.900e+01]\n",
-      " ...\n",
-      " [2.000e+01 2.000e+01 6.900e+01 ... 9.045e+03 9.045e+03 1.845e+03]\n",
-      " [2.000e+01 2.000e+01 6.900e+01 ... 9.045e+03 9.045e+03 1.845e+03]\n",
-      " [2.000e+01 2.000e+01 6.900e+01 ... 1.845e+03 1.845e+03 2.385e+03]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:   8%|▊         | 77/1000 [00:00<00:01, 764.71it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.069543502626658e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.1303298666315776e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.70249458866672e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.63992169055093e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.438093960487116e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0002169262936346e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.5920339281975188e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.5874866272574162e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.0599424240471626e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.468773818521402e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.958334441043603e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  27%|██▋       | 267/1000 [00:00<00:01, 654.82it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/sklearn/linear_model/ridge.py:154: UserWarning: Singular matrix in solving dual problem. Using least-squares solution instead.\n",
-      "  warnings.warn(\"Singular matrix in solving dual problem. Using \"\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.055618175730539e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.7159074038024934e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.895455126720251e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.400306511546424e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.206478316049589e-19 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.8083631222444177e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.49051280863482e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.339852738992424e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.277544863160196e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.458523723353626e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  48%|████▊     | 477/1000 [00:00<00:00, 685.70it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6380760737666547e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.3843421259537676e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.890544546973404e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.054758730954765e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.9172765626494813e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.4455093698440067e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.2914256710839066e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.65667341282596e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.852926745577629e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.285092924342139e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  69%|██████▉   | 694/1000 [00:01<00:00, 712.57it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.700250453064005e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6205193931367065e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.4925504318417794e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.0111387119813346e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.343123723749221e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0143662852277667e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.206690575125046e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.049999246995425e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.4232350203422674e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.350008400303505e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.251763015291957e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  90%|█████████ | 902/1000 [00:01<00:00, 666.85it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.924869742342744e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.4010401637647583e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.5117924740400373e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.626753798403599e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.911227588173856e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.0660043401009468e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.3099139652029694e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.2680602391853274e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.396574210735164e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  97%|█████████▋| 969/1000 [00:01<00:00, 600.11it/s]\n",
-      " Mean performance on train set: 6.816974\n",
-      "With standard deviation: 1.501822\n",
-      "\n",
-      " Mean performance on test set: 7.497870\n",
-      "With standard deviation: 2.368148\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 648.87it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 100.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.09455919265747 seconds ---\n",
-      "[[4.13000e+02 1.40000e+01 4.00000e+00 ... 2.00000e+01 2.00000e+01\n",
-      "  2.00000e+01]\n",
-      " [1.40000e+01 8.20000e+02 4.00000e+00 ... 2.00000e+01 2.00000e+01\n",
-      "  2.00000e+01]\n",
-      " [4.00000e+00 4.00000e+00 4.13000e+02 ... 4.29000e+02 4.29000e+02\n",
-      "  4.29000e+02]\n",
-      " ...\n",
-      " [2.00000e+01 2.00000e+01 4.29000e+02 ... 7.35165e+05 7.35165e+05\n",
-      "  1.51650e+04]\n",
-      " [2.00000e+01 2.00000e+01 4.29000e+02 ... 7.35165e+05 7.35165e+05\n",
-      "  1.51650e+04]\n",
-      " [2.00000e+01 2.00000e+01 4.29000e+02 ... 1.51650e+04 1.51650e+04\n",
-      "  2.05650e+04]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  10%|▉         | 97/1000 [00:00<00:02, 436.93it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.249229588791739e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6092761314568358e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6033357497241564e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.0333531111165975e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.073851980749357e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.497880470461594e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0349745182117167e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  17%|█▋        | 169/1000 [00:00<00:02, 372.64it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.227908145504113e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.1894008132724887e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.9131474526752795e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.0421770253846576e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.864916618602575e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.663676730244888e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  31%|███▏      | 314/1000 [00:00<00:01, 429.29it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.6989200751598342e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.9988176582222278e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.173259131422707e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.069621878854856e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.087601566853754e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.1827598831940232e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.428244298929586e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.1120965359644164e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.8329496119281176e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.5128147762765525e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.173155329882729e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  50%|█████     | 501/1000 [00:01<00:00, 516.57it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.874621241781873e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.9047959204426696e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.03000007539236e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.8198639503150797e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.679200342495213e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6211471280327221e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.74280825574767e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.685372827008377e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.9723233156997277e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.142362330339379e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.0042133764798303e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.987833375253946e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  71%|███████   | 706/1000 [00:01<00:00, 471.97it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.63949546549065e-19 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.76170805410039e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.3721058293845662e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.178277242767302e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.4883373934010664e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.526360275338589e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.827383891217367e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  81%|████████  | 807/1000 [00:01<00:00, 457.30it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.052622499085628e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.70793549450487e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.8190124240850417e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.349104192126423e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.132340452050677e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  91%|█████████ | 909/1000 [00:01<00:00, 451.90it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.78695142234395e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.8765535280551442e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.9917255115528226e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.781650263544808e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.581768670551366e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.0493867289518776e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.9787087068181396e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.756012232435961e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.800283208793992e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.468606690086715e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.119459703249427e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  96%|█████████▌| 956/1000 [00:02<00:00, 445.96it/s]\n",
-      " Mean performance on train set: 6.687664\n",
-      "With standard deviation: 1.348089\n",
-      "\n",
-      " Mean performance on test set: 7.428867\n",
-      "With standard deviation: 2.647892\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:02<00:00, 467.65it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.517051219940186 seconds ---\n",
-      "[[4.0130000e+03 1.4000000e+01 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [1.4000000e+01 8.0200000e+03 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [4.0000000e+00 4.0000000e+00 4.0130000e+03 ... 4.0290000e+03\n",
-      "  4.0290000e+03 4.0290000e+03]\n",
-      " ...\n",
-      " [2.0000000e+01 2.0000000e+01 4.0290000e+03 ... 7.2148365e+07\n",
-      "  7.2148365e+07 1.4836500e+05]\n",
-      " [2.0000000e+01 2.0000000e+01 4.0290000e+03 ... 7.2148365e+07\n",
-      "  7.2148365e+07 1.4836500e+05]\n",
-      " [2.0000000e+01 2.0000000e+01 4.0290000e+03 ... 1.4836500e+05\n",
-      "  1.4836500e+05 2.0236500e+05]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  10%|█         | 102/1000 [00:00<00:02, 330.46it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.374017095746491e-19 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.687507275679712e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.7645414168071277e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.8090152927008474e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.474194561968185e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.130856876335615e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  19%|█▉        | 188/1000 [00:00<00:02, 348.40it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.7794644716713837e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.3130943734340723e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.7505566440337117e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.3279670378456666e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.318466984022222e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.418445519765442e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  28%|██▊       | 285/1000 [00:00<00:01, 380.47it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.1356199672921913e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6464620684950592e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.179430869121561e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.473887201835687e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.570987725305032e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.854640029504099e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  38%|███▊      | 385/1000 [00:00<00:01, 389.24it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.3781828327775562e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.955507306233033e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.109947315270106e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.9378280303294975e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.866942525478256e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  49%|████▉     | 494/1000 [00:01<00:01, 398.83it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.636014964778956e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.6552163232757833e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.312233993243073e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.2794244316598437e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.406028628818668e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  60%|██████    | 604/1000 [00:01<00:00, 407.30it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.184686103929999e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.1281587780183657e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.367013528660628e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.155116554595105e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.443029464120917e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.4923079446940085e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.750703061909557e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  71%|███████   | 707/1000 [00:01<00:00, 402.63it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.4970615125032324e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.39494402062226e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.818999641865095e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.051275910233908e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.688197813410084e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  81%|████████  | 806/1000 [00:01<00:00, 404.11it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.43659662072146e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.4284104102664825e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.900304923444742e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.1112688931900636e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.941184656304436e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.746476431972804e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  91%|█████████ | 906/1000 [00:02<00:00, 407.57it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.327409345420052e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.0589341144557062e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.29154188313992e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.225020130252359e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.327720201864263e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  95%|█████████▌| 951/1000 [00:02<00:00, 373.87it/s]\n",
-      " Mean performance on train set: 6.819058\n",
-      "With standard deviation: 1.410085\n",
-      "\n",
-      " Mean performance on test set: 7.249143\n",
-      "With standard deviation: 2.655536\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:02<00:00, 414.03it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.193651783291256e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.19984276961351e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.0689487149937185e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.8956869823870564e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.790887064559792e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 10000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.01269268989563 seconds ---\n",
-      "[[4.00130000e+04 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [1.40000000e+01 8.00200000e+04 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.00130000e+04 ... 4.00290000e+04\n",
-      "  4.00290000e+04 4.00290000e+04]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.00290000e+04 ... 7.20148036e+09\n",
-      "  7.20148036e+09 1.48036500e+06]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00290000e+04 ... 7.20148036e+09\n",
-      "  7.20148036e+09 1.48036500e+06]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00290000e+04 ... 1.48036500e+06\n",
-      "  1.48036500e+06 2.02036500e+06]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  11%|█▏        | 114/1000 [00:00<00:02, 303.84it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6978549111114387e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.1828172674052679e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.547017114313022e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.990786470945978e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.8300974250606965e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.727582936838558e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  21%|██        | 208/1000 [00:00<00:02, 342.60it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.569354559683504e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.885865920757663e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.006883677471783e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.2491482969368813e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.596699463334369e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.74024827114128e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0002891123411383e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  31%|███       | 311/1000 [00:00<00:01, 371.07it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.478112292477647e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.3626069490970097e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.751107853461428e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.007160521891646e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.592912372477283e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  41%|████▏     | 414/1000 [00:01<00:01, 394.40it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.286966904954778e-19 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.330065717080935e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.0639972759819077e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.3250852692883386e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.32507703774876e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.514317701906229e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  51%|█████▏    | 514/1000 [00:01<00:01, 411.17it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.5186106207732215e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.2309907116861648e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.582391203608073e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.638503426307468e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0580872068659216e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  62%|██████▏   | 615/1000 [00:01<00:00, 424.96it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.633316922861427e-19 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.253166879599146e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.4688155478710103e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.3252803222906435e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.713726552669558e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.934042177466841e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.468592067289146e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  72%|███████▏  | 716/1000 [00:01<00:00, 433.84it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.66227030386163e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.5342528466878185e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.620745355332433e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.5797394734563764e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.109079490079661e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.548426603146641e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0484899604694826e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  82%|████████▏ | 816/1000 [00:01<00:00, 439.46it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.080827240476694e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.8279322282295696e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.0410721959495632e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.343375151645726e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.351177509861134e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.370583478449445e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  92%|█████████▏| 916/1000 [00:02<00:00, 437.07it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.3677978521118296e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0227997187914302e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.557088603475233e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.657645350184021e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.990628121216557e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  96%|█████████▌| 962/1000 [00:02<00:00, 393.51it/s]\n",
-      " Mean performance on train set: 6.934306\n",
-      "With standard deviation: 1.384412\n",
-      "\n",
-      " Mean performance on test set: 7.081832\n",
-      "With standard deviation: 2.624800\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:02<00:00, 420.16it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.2964047050969517e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.089708488833387e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.3234351109582e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.293818265362604e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.44555950404844e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 100000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 35.835275411605835 seconds ---\n",
-      "[[4.0001300e+05 1.4000000e+01 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [1.4000000e+01 8.0002000e+05 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [4.0000000e+00 4.0000000e+00 4.0001300e+05 ... 4.0002900e+05\n",
-      "  4.0002900e+05 4.0002900e+05]\n",
-      " ...\n",
-      " [2.0000000e+01 2.0000000e+01 4.0002900e+05 ... 7.2001480e+11\n",
-      "  7.2001480e+11 1.4800365e+07]\n",
-      " [2.0000000e+01 2.0000000e+01 4.0002900e+05 ... 7.2001480e+11\n",
-      "  7.2001480e+11 1.4800365e+07]\n",
-      " [2.0000000e+01 2.0000000e+01 4.0002900e+05 ... 1.4800365e+07\n",
-      "  1.4800365e+07 2.0200365e+07]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  13%|█▎        | 126/1000 [00:00<00:03, 261.95it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.0191112815027622e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.232307074954237e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.097885039345644e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.727869526025791e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  21%|██        | 208/1000 [00:00<00:03, 262.44it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.2411064955279154e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.149899322677468e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.642478117522784e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  30%|███       | 305/1000 [00:01<00:02, 265.15it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.785067039039337e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.225934530879337e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.562790184640486e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  41%|████▏     | 414/1000 [00:01<00:01, 297.05it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.135758789917749e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.564182826681079e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.542436590136228e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  50%|█████     | 500/1000 [00:01<00:01, 319.27it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.195315905739342e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.379873880613873e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.630975349505465e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.518071272961898e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  61%|██████▏   | 613/1000 [00:02<00:01, 303.76it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.9460047081015216e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.839254463570563e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.318583704180543e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  73%|███████▎  | 728/1000 [00:02<00:00, 300.34it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.3984244112232524e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.3291156014339405e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.707621088224988e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0690013288979288e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  81%|████████▏ | 813/1000 [00:02<00:00, 321.97it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.315773170165585e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.138544398203078e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.386508127676171e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  89%|████████▉ | 891/1000 [00:02<00:00, 317.18it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.6842499515474312e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.528434456947986e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.856433851414765e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  96%|█████████▌| 957/1000 [00:03<00:00, 259.36it/s]\n",
-      " Mean performance on train set: 9.394995\n",
-      "With standard deviation: 1.047066\n",
-      "\n",
-      " Mean performance on test set: 8.237631\n",
-      "With standard deviation: 3.665300\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:03<00:00, 299.25it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1000000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.056791553686018e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.644703618966645e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.15242050721053e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.77732253074646 seconds ---\n",
-      "[[4.00001300e+06 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [1.40000000e+01 8.00002000e+06 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.00001300e+06 ... 4.00002900e+06\n",
-      "  4.00002900e+06 4.00002900e+06]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.00002900e+06 ... 7.20001480e+13\n",
-      "  7.20001480e+13 1.48000365e+08]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00002900e+06 ... 7.20001480e+13\n",
-      "  7.20001480e+13 1.48000365e+08]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00002900e+06 ... 1.48000365e+08\n",
-      "  1.48000365e+08 2.02000365e+08]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  14%|█▎        | 135/1000 [00:00<00:03, 253.06it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.741195162637844e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.5965964498458038e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.983361443347492e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.7922291165206923e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.685526054240851e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  23%|██▎       | 230/1000 [00:00<00:02, 265.75it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6848871984797616e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.8811603375005575e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.7514073450053307e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.5976314128410034e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.790988115471154e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.477178586927344e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.035215871851048e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  33%|███▎      | 332/1000 [00:01<00:02, 277.35it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.287317576627726e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.886325173924881e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.8372812242318245e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.523017625167697e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.309735186090854e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  43%|████▎     | 431/1000 [00:01<00:02, 258.66it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.2092887442597021e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.444285941342485e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6650957319224102e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.778343353100153e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.067496740668901e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.832366528737191e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  53%|█████▎    | 534/1000 [00:01<00:01, 252.20it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.2368084459111367e-19 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.625050966790768e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.786992563738048e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.5350081600164477e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.2823286559994256e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.880362578796432e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.1100444346816681e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  64%|██████▎   | 637/1000 [00:02<00:01, 260.77it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.1335408080135885e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.4688002952482946e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.6678722631357644e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.288251804550535e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.895017980474164e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  74%|███████▍  | 741/1000 [00:02<00:00, 276.66it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.209157188853246e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.4519382674684447e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.5748326244710203e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.852436562697074e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.536506069365062e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.969036612017947e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  81%|████████▏ | 813/1000 [00:02<00:00, 297.62it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.309383987394578e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.565067260805818e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.516194197490843e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.041064934861363e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.499601220689098e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.051151158798192e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  92%|█████████▏| 915/1000 [00:03<00:00, 298.37it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.7472428919435347e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.703770718809819e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.2818242346374262e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.102554831016506e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.599188283622467e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0647003359802031e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  98%|█████████▊| 977/1000 [00:03<00:00, 278.57it/s]\n",
-      " Mean performance on train set: 9.635245\n",
-      "With standard deviation: 0.687560\n",
-      "\n",
-      " Mean performance on test set: 8.529828\n",
-      "With standard deviation: 3.580591\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:03<00:00, 284.18it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 10000000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.502409510736216e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0439081147173944e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.4602149061556115e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.9479003259500843e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.34621741763787e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0245542507930726e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.46095633506775 seconds ---\n",
-      "[[4.00000130e+07 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [1.40000000e+01 8.00000200e+07 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.00000130e+07 ... 4.00000290e+07\n",
-      "  4.00000290e+07 4.00000290e+07]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000290e+07 ... 7.20000148e+15\n",
-      "  7.20000148e+15 1.48000036e+09]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000290e+07 ... 7.20000148e+15\n",
-      "  7.20000148e+15 1.48000036e+09]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000290e+07 ... 1.48000036e+09\n",
-      "  1.48000036e+09 2.02000036e+09]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  12%|█▏        | 122/1000 [00:00<00:03, 231.16it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.200122265640733e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.627297027618617e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.893611596005168e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.1052758523976415e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.158312302718829e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.675650470006637e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  23%|██▎       | 227/1000 [00:00<00:03, 253.57it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.2230286797750079e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.0790289882373515e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6170735381557016e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.90989130271085e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.4735492461286675e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.544548737558878e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  34%|███▍      | 344/1000 [00:01<00:02, 274.36it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.0569387542185164e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.8929851773550792e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.762490810329375e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.031994076021703e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.380795983197089e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  44%|████▎     | 437/1000 [00:01<00:02, 281.37it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.159845331824398e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.592173545119868e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.0031182975801337e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.315102488294594e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.427690586128571e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.36815306216013e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  52%|█████▎    | 525/1000 [00:01<00:01, 277.96it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.096509347533013e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.2037051514926243e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.641239932076709e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.911654384898199e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.195245830759744e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  61%|██████    | 606/1000 [00:02<00:01, 236.45it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.179739003035368e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.121167134816686e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.201750997217992e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.6143396276266097e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.876412427833992e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.158416120381036e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  73%|███████▎  | 727/1000 [00:02<00:01, 211.65it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.355737066205781e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.778261189640049e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.992328403436096e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.166526583123927e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.566565138343654e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.272056103177315e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  82%|████████▏ | 822/1000 [00:03<00:00, 223.94it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.2435735437353417e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.471379508084743e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.686971341479104e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.827108937015577e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  93%|█████████▎| 931/1000 [00:03<00:00, 255.06it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.2357280081107672e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.559072238694825e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.45488311322705e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.6616151717441874e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.807701664283496e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  98%|█████████▊| 983/1000 [00:04<00:00, 220.81it/s]\n",
-      " Mean performance on train set: 11.059074\n",
-      "With standard deviation: 1.323635\n",
-      "\n",
-      " Mean performance on test set: 10.964175\n",
-      "With standard deviation: 3.358726\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:04<00:00, 242.35it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 100000000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.749823872976888e-19 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.347208969568296e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.9981807042259307e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.298232968104139e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.391381083354749e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.328796748008544e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.91001057624817 seconds ---\n",
-      "[[4.00000013e+08 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [1.40000000e+01 8.00000020e+08 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.00000013e+08 ... 4.00000029e+08\n",
-      "  4.00000029e+08 4.00000029e+08]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000029e+08 ... 7.20000015e+17\n",
-      "  7.20000015e+17 1.48000004e+10]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000029e+08 ... 7.20000015e+17\n",
-      "  7.20000015e+17 1.48000004e+10]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000029e+08 ... 1.48000004e+10\n",
-      "  1.48000004e+10 2.02000004e+10]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  99%|█████████▉| 992/1000 [00:03<00:00, 267.91it/s]\n",
-      " Mean performance on train set: 66.147687\n",
-      "With standard deviation: 11.979989\n",
-      "\n",
-      " Mean performance on test set: 63.221208\n",
-      "With standard deviation: 13.381090\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:03<00:00, 252.05it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1000000000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 38.43676400184631 seconds ---\n",
-      "[[4.00000001e+09 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [1.40000000e+01 8.00000002e+09 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.00000001e+09 ... 4.00000003e+09\n",
-      "  4.00000003e+09 4.00000003e+09]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000003e+09 ... 7.20000001e+19\n",
-      "  7.20000001e+19 1.48000000e+11]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000003e+09 ... 7.20000001e+19\n",
-      "  7.20000001e+19 1.48000000e+11]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000003e+09 ... 1.48000000e+11\n",
-      "  1.48000000e+11 2.02000000e+11]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 976/1000 [00:04<00:00, 268.70it/s]\n",
-      " Mean performance on train set: 96.664827\n",
-      "With standard deviation: 1.871320\n",
-      "\n",
-      " Mean performance on test set: 100.134704\n",
-      "With standard deviation: 13.845906\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:04<00:00, 236.90it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 10000000000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.32151246070862 seconds ---\n",
-      "[[4.00e+10 1.40e+01 4.00e+00 ... 2.00e+01 2.00e+01 2.00e+01]\n",
-      " [1.40e+01 8.00e+10 4.00e+00 ... 2.00e+01 2.00e+01 2.00e+01]\n",
-      " [4.00e+00 4.00e+00 4.00e+10 ... 4.00e+10 4.00e+10 4.00e+10]\n",
-      " ...\n",
-      " [2.00e+01 2.00e+01 4.00e+10 ... 7.20e+21 7.20e+21 1.48e+12]\n",
-      " [2.00e+01 2.00e+01 4.00e+10 ... 7.20e+21 7.20e+21 1.48e+12]\n",
-      " [2.00e+01 2.00e+01 4.00e+10 ... 1.48e+12 1.48e+12 2.02e+12]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance: 100%|█████████▉| 997/1000 [00:03<00:00, 268.42it/s]\n",
-      " Mean performance on train set: 98.175092\n",
-      "With standard deviation: 4.720613\n",
-      "\n",
-      " Mean performance on test set: 100.144883\n",
-      "With standard deviation: 13.958659\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:03<00:00, 260.49it/s]\n",
-      "\n",
-      "\n",
-      "       lmda    rmse_test    std_test    rmse_train    std_train    k_time\n",
-      "-----------  -----------  ----------  ------------  -----------  --------\n",
-      "     1e-10       7.4649      1.71858       5.99354     0.356922   37.3696\n",
-      "     1e-09       7.37511     1.76925       5.96304     0.374107   37.4747\n",
-      "     1e-08       7.35069     1.78056       5.96511     0.378249   37.3297\n",
-      "     1e-07       7.351       1.78147       5.96698     0.382093   37.7415\n",
-      "     1e-06       7.35123     1.78052       5.96976     0.386318   37.5213\n",
-      "     1e-05       7.34813     1.78029       5.97056     0.390719   37.671\n",
-      "     0.0001      7.34984     1.7811        5.9425      0.331983   36.8013\n",
-      "     0.001       7.35775     1.78098       5.9334      0.324965   35.8681\n",
-      "     0.01        7.37427     1.79115       5.94069     0.347431   36.0018\n",
-      "     0.1         7.3293      1.91363       6.42711     1.29367    36.3715\n",
-      "     1           7.27134     2.20774       6.62425     1.2242     37.8397\n",
-      "    10           7.49787     2.36815       6.81697     1.50182    37.5082\n",
-      "   100           7.42887     2.64789       6.68766     1.34809    37.0946\n",
-      "  1000           7.24914     2.65554       6.81906     1.41008    37.5171\n",
-      " 10000           7.08183     2.6248        6.93431     1.38441    37.0127\n",
-      "100000           8.23763     3.6653        9.395       1.04707    35.8353\n",
-      "     1e+06       8.52983     3.58059       9.63525     0.68756    37.7773\n",
-      "     1e+07      10.9642      3.35873      11.0591      1.32363    37.461\n",
-      "     1e+08      63.2212     13.3811       66.1477     11.98       37.91\n",
-      "     1e+09     100.135      13.8459       96.6648      1.87132    38.4368\n",
-      "     1e+10     100.145      13.9587       98.1751      4.72061    37.3215\n"
-     ]
-    }
-   ],
-   "source": [
-    "# tree pattern kernel, dataset acyclic.\n",
-    "%load_ext line_profiler\n",
-    "\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.treePatternKernel import treepatternkernel\n",
-    "\n",
-    "import numpy as np\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_path_acyclic/'\n",
-    "\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', labeled = True, \\\n",
-    "    kernel_type = 'untiln', h = 2)\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, treepatternkernel, kernel_para, \\\n",
-    "    hyper_name = 'lmda', hyper_range = np.logspace(-10, 10, num = 21, base = 10), \\\n",
-    "    normalize = False, model_type = 'regression')\n",
-    "\n",
-    "# kernel_para['depth'] = 10\n",
-    "# %lprun -f untildpathkernel \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, normalize = False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# results\n",
-    "\n",
-    "# untiln kernel when h = 2\n",
-    "       lmda    rmse_test    std_test    rmse_train    std_train    k_time\n",
-    "-----------  -----------  ----------  ------------  -----------  --------\n",
-    "     1e-10       7.46524     1.71862       5.99486     0.356634   38.1447\n",
-    "     1e-09       7.37326     1.77195       5.96155     0.374395   37.4921\n",
-    "     1e-08       7.35105     1.78349       5.96481     0.378047   37.9971\n",
-    "     1e-07       7.35213     1.77903       5.96728     0.382251   38.3182\n",
-    "     1e-06       7.3524      1.77992       5.9696      0.3863     39.6428\n",
-    "     1e-05       7.34958     1.78141       5.97114     0.39017    37.3711\n",
-    "     0.0001      7.3513      1.78136       5.94251     0.331843   37.3967\n",
-    "     0.001       7.35822     1.78119       5.9326      0.32534    36.7357\n",
-    "     0.01        7.37552     1.79037       5.94089     0.34763    36.8864\n",
-    "     0.1         7.32951     1.91346       6.42634     1.29405    36.8382\n",
-    "     1           7.27134     2.20774       6.62425     1.2242     37.2425\n",
-    "    10           7.49787     2.36815       6.81697     1.50182    37.8286\n",
-    "   100           7.42887     2.64789       6.68766     1.34809    36.3701\n",
-    "  1000           7.24914     2.65554       6.81906     1.41008    36.1695\n",
-    " 10000           7.08183     2.6248        6.93431     1.38441    37.5723\n",
-    "100000           8.021       3.43694       8.69813     0.909839   37.8158\n",
-    "     1e+06       8.49625     3.6332        9.59333     0.96626    38.4688\n",
-    "     1e+07      10.9067      3.17593      11.5642      2.07792    36.9926\n",
-    "     1e+08      61.1524     10.4355       65.3527     13.9538     37.1321\n",
-    "     1e+09      99.943      13.6994       98.8848      5.27014    36.7443\n",
-    "     1e+10     100.083      13.8503       97.9168      3.22768    37.096\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The line_profiler extension is already loaded. To reload it, use:\n",
-      "  %reload_ext line_profiler\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f6be3d4a8d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[(0, {'atom': 'C', 'label': 'C'}), (1, {'atom': 'C', 'label': 'C'}), (2, {'atom': 'C', 'label': 'C'}), (3, {'atom': 'C', 'label': 'C'}), (4, {'atom': 'S', 'label': 'S'})]\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 39 built in 3.5270774364471436 seconds ---\n",
-      "(array([[1.99007809e+036, 4.00000000e+000, 4.00000000e+000, ...,\n",
-      "        1.00000000e+001, 1.00000000e+001, 1.00000000e+001],\n",
-      "       [4.00000000e+000, 6.37886713e+019, 4.34000000e+002, ...,\n",
-      "        6.37886713e+019, 6.37886713e+019, 6.37886713e+019],\n",
-      "       [4.00000000e+000, 4.34000000e+002, 1.99007809e+036, ...,\n",
-      "        4.40000000e+002, 4.40000000e+002, 4.40000000e+002],\n",
-      "       ...,\n",
-      "       [1.00000000e+001, 6.37886713e+019, 4.40000000e+002, ...,\n",
-      "        2.94561201e+119, 1.16903692e+080, 4.42354433e+082],\n",
-      "       [1.00000000e+001, 6.37886713e+019, 4.40000000e+002, ...,\n",
-      "        1.16903692e+080, 4.21212139e+264, 1.66634383e+080],\n",
-      "       [1.00000000e+001, 6.37886713e+019, 4.40000000e+002, ...,\n",
-      "        4.42354433e+082, 1.66634383e+080, 5.17763068e+117]]), 3.5270774364471436)\n"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext line_profiler\n",
-    "\n",
-    "import networkx as nx\n",
-    "import matplotlib.pyplot as plt\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "\n",
-    "from pygraph.kernels.treePatternKernel import treepatternkernel, _treepatternkernel_do\n",
-    "\n",
-    "import numpy as np\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "\n",
-    "dataset, y = loadDataset(datafile)\n",
-    "G1 = dataset[100]\n",
-    "G2 = dataset[20]\n",
-    "data = [G1, G2]\n",
-    "# nx.draw_networkx(G1)\n",
-    "# plt.show()\n",
-    "# print(G1.nodes(data=True)20\n",
-    "nx.draw_networkx(G2)\n",
-    "plt.show()\n",
-    "print(G2.nodes(data=True))\n",
-    "\n",
-    "\n",
-    "%lprun -f _treepatternkernel_do \\\n",
-    "    kernel = treepatternkernel(dataset[1:40], node_label = 'atom', edge_label = 'bond_type', labeled = True, \\\n",
-    "    kernel_type = 'untiln', lmda = 1, h = 10)\n",
-    "\n",
-    "print(kernel)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- This is a classification problem ---\n",
-      "\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 185/185 [00:00<00:00, 2064.69it/s]\n",
-      "calculate kernels: 100%|██████████| 185/185 [00:00<00:00, 11170.00it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 185 built in 0.10836505889892578 seconds ---\n",
-      "[[0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " ...\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:24<00:00, 36.41it/s]\n",
-      " Mean performance on train set: 0.018072\n",
-      "With standard deviation: 0.000000\n",
-      "\n",
-      " Mean performance on test set: 0.000000\n",
-      "With standard deviation: 0.000000\n",
-      "\n",
-      "\n",
-      "  accur_test    std_test    accur_train    std_train    k_time\n",
-      "------------  ----------  -------------  -----------  --------\n",
-      "           0           0      0.0180723            0  0.108365\n"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext line_profiler\n",
-    "\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.cyclicPatternKernel import cyclicpatternkernel\n",
-    "\n",
-    "import numpy as np\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_path_acyclic/'\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', labeled = True, cycle_bound = 200)\n",
-    "\n",
-    "# kernel_train_test(datafile, kernel_file_path, treeletkernel, kernel_para, normalize = False)\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, cyclicpatternkernel, kernel_para, \\\n",
-    "    normalize = False , model_type = 'classification')\n",
-    "\n",
-    "# kernel_para['k_func'] = 'minmax'\n",
-    "# kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
-    "#     hyper_name = 'depth', hyper_range = np.linspace(0, 10, 11), normalize = True)\n",
-    "# kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
-    "#     hyper_name = 'depth', hyper_range = np.linspace(0, 10, 11), normalize = False)\n",
-    "# # kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, normalize = False)\n",
-    "\n",
-    "# kernel_para['depth'] = 10\n",
-    "# %lprun -f untildpathkernel \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, normalize = False)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/.ipynb_checkpoints/run_untildpathkernel_acyclic-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/run_untildpathkernel_acyclic-checkpoint.ipynb
deleted file mode 100644
index 05baadb..0000000
--- a/notebooks/.ipynb_checkpoints/run_untildpathkernel_acyclic-checkpoint.ipynb
+++ /dev/null
@@ -1,3183 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "--- This is a regression problem ---\n",
-      "\n",
-      "1. Loading dataset from file...\n",
-      "\n",
-      "2. Calculating gram matrices. This could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 0 of size 183 built in 0.08850574493408203 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 0.0, 'k_func': 'tanimoto'} is: \n",
-      "[[1.         1.         0.33333333 ... 0.33333333 0.33333333 0.33333333]\n",
-      " [1.         1.         0.33333333 ... 0.33333333 0.33333333 0.33333333]\n",
-      " [0.33333333 0.33333333 1.         ... 1.         1.         1.        ]\n",
-      " ...\n",
-      " [0.33333333 0.33333333 1.         ... 1.         1.         1.        ]\n",
-      " [0.33333333 0.33333333 1.         ... 1.         1.         1.        ]\n",
-      " [0.33333333 0.33333333 1.         ... 1.         1.         1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f89002ba8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 0 of size 183 built in 0.3581843376159668 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 0.0, 'k_func': 'MinMax'} is: \n",
-      "[[1.         0.75       0.5        ... 0.16666667 0.16666667 0.16666667]\n",
-      " [0.75       1.         0.4        ... 0.15384615 0.15384615 0.15384615]\n",
-      " [0.5        0.4        1.         ... 0.27272727 0.27272727 0.27272727]\n",
-      " ...\n",
-      " [0.16666667 0.15384615 0.27272727 ... 1.         1.         1.        ]\n",
-      " [0.16666667 0.15384615 0.27272727 ... 1.         1.         1.        ]\n",
-      " [0.16666667 0.15384615 0.27272727 ... 1.         1.         1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f86f185c0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 1 of size 183 built in 0.2037951946258545 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 1.0, 'k_func': 'tanimoto'} is: \n",
-      "[[1.         0.8        0.14285714 ... 0.125      0.125      0.125     ]\n",
-      " [0.8        1.         0.125      ... 0.11111111 0.11111111 0.11111111]\n",
-      " [0.14285714 0.125      1.         ... 0.8        0.8        0.8       ]\n",
-      " ...\n",
-      " [0.125      0.11111111 0.8        ... 1.         1.         1.        ]\n",
-      " [0.125      0.11111111 0.8        ... 1.         1.         1.        ]\n",
-      " [0.125      0.11111111 0.8        ... 1.         1.         1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f86ee2da0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 1 of size 183 built in 0.4422006607055664 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 1.0, 'k_func': 'MinMax'} is: \n",
-      "[[1.         0.7        0.16666667 ... 0.05555556 0.05555556 0.05555556]\n",
-      " [0.7        1.         0.13333333 ... 0.05128205 0.05128205 0.05128205]\n",
-      " [0.16666667 0.13333333 1.         ... 0.22580645 0.22580645 0.22580645]\n",
-      " ...\n",
-      " [0.05555556 0.05128205 0.22580645 ... 1.         1.         1.        ]\n",
-      " [0.05555556 0.05128205 0.22580645 ... 1.         1.         1.        ]\n",
-      " [0.05555556 0.05128205 0.22580645 ... 1.         1.         1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f86eafef0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 2 of size 183 built in 0.33296751976013184 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 2.0, 'k_func': 'tanimoto'} is: \n",
-      "[[1.         0.5        0.11111111 ... 0.07692308 0.07692308 0.07692308]\n",
-      " [0.5        1.         0.09090909 ... 0.06666667 0.06666667 0.06666667]\n",
-      " [0.11111111 0.09090909 1.         ... 0.55555556 0.55555556 0.55555556]\n",
-      " ...\n",
-      " [0.07692308 0.06666667 0.55555556 ... 1.         1.         1.        ]\n",
-      " [0.07692308 0.06666667 0.55555556 ... 1.         1.         1.        ]\n",
-      " [0.07692308 0.06666667 0.55555556 ... 1.         1.         1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f86e5e518>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 2 of size 183 built in 0.5694379806518555 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 2.0, 'k_func': 'MinMax'} is: \n",
-      "[[1.         0.4375     0.125      ... 0.03333333 0.03333333 0.03571429]\n",
-      " [0.4375     1.         0.0952381  ... 0.03076923 0.03076923 0.03278689]\n",
-      " [0.125      0.0952381  1.         ... 0.16981132 0.16981132 0.18367347]\n",
-      " ...\n",
-      " [0.03333333 0.03076923 0.16981132 ... 1.         1.         0.9245283 ]\n",
-      " [0.03333333 0.03076923 0.16981132 ... 1.         1.         0.9245283 ]\n",
-      " [0.03571429 0.03278689 0.18367347 ... 0.9245283  0.9245283  1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f86e17160>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 3 of size 183 built in 0.5317063331604004 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 3.0, 'k_func': 'tanimoto'} is: \n",
-      "[[1.         0.44444444 0.11111111 ... 0.05555556 0.05555556 0.05555556]\n",
-      " [0.44444444 1.         0.08333333 ... 0.04761905 0.04761905 0.04761905]\n",
-      " [0.11111111 0.08333333 1.         ... 0.35714286 0.35714286 0.35714286]\n",
-      " ...\n",
-      " [0.05555556 0.04761905 0.35714286 ... 1.         1.         1.        ]\n",
-      " [0.05555556 0.04761905 0.35714286 ... 1.         1.         1.        ]\n",
-      " [0.05555556 0.04761905 0.35714286 ... 1.         1.         1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f86e4afd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 3 of size 183 built in 0.7160298824310303 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 3.0, 'k_func': 'MinMax'} is: \n",
-      "[[1.         0.38888889 0.125      ... 0.02631579 0.02631579 0.02777778]\n",
-      " [0.38888889 1.         0.08695652 ... 0.02409639 0.02409639 0.02531646]\n",
-      " [0.125      0.08695652 1.         ... 0.13043478 0.13043478 0.13846154]\n",
-      " ...\n",
-      " [0.02631579 0.02409639 0.13043478 ... 1.         0.94366197 0.83561644]\n",
-      " [0.02631579 0.02409639 0.13043478 ... 0.94366197 1.         0.78666667]\n",
-      " [0.02777778 0.02531646 0.13846154 ... 0.83561644 0.78666667 1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f88f87e48>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 4 of size 183 built in 0.7884619235992432 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 4.0, 'k_func': 'tanimoto'} is: \n",
-      "[[1.         0.44444444 0.11111111 ... 0.04347826 0.04166667 0.04347826]\n",
-      " [0.44444444 1.         0.08333333 ... 0.03846154 0.03703704 0.03846154]\n",
-      " [0.11111111 0.08333333 1.         ... 0.26315789 0.25       0.26315789]\n",
-      " ...\n",
-      " [0.04347826 0.03846154 0.26315789 ... 1.         0.95       0.9       ]\n",
-      " [0.04166667 0.03703704 0.25       ... 0.95       1.         0.95      ]\n",
-      " [0.04347826 0.03846154 0.26315789 ... 0.9        0.95       1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f86e7d780>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 4 of size 183 built in 0.8283765316009521 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 4.0, 'k_func': 'MinMax'} is: \n",
-      "[[1.         0.38888889 0.125      ... 0.02222222 0.02222222 0.02325581]\n",
-      " [0.38888889 1.         0.08695652 ... 0.02061856 0.02061856 0.02150538]\n",
-      " [0.125      0.08695652 1.         ... 0.10843373 0.10843373 0.11392405]\n",
-      " ...\n",
-      " [0.02222222 0.02061856 0.10843373 ... 1.         0.82417582 0.67010309]\n",
-      " [0.02222222 0.02061856 0.10843373 ... 0.82417582 1.         0.70526316]\n",
-      " [0.02325581 0.02150538 0.11392405 ... 0.67010309 0.70526316 1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f86f26da0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 5 of size 183 built in 0.9662420749664307 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 5.0, 'k_func': 'tanimoto'} is: \n",
-      "[[1.         0.44444444 0.11111111 ... 0.03703704 0.03333333 0.03571429]\n",
-      " [0.44444444 1.         0.08333333 ... 0.03333333 0.03030303 0.03225806]\n",
-      " [0.11111111 0.08333333 1.         ... 0.2173913  0.19230769 0.20833333]\n",
-      " ...\n",
-      " [0.03703704 0.03333333 0.2173913  ... 1.         0.88461538 0.74074074]\n",
-      " [0.03333333 0.03030303 0.19230769 ... 0.88461538 1.         0.85185185]\n",
-      " [0.03571429 0.03225806 0.20833333 ... 0.74074074 0.85185185 1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f86e453c8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 5 of size 183 built in 0.9853420257568359 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 5.0, 'k_func': 'MinMax'} is: \n",
-      "[[1.         0.38888889 0.125      ... 0.01960784 0.01960784 0.02040816]\n",
-      " [0.38888889 1.         0.08695652 ... 0.01834862 0.01834862 0.01904762]\n",
-      " [0.125      0.08695652 1.         ... 0.09473684 0.09473684 0.0989011 ]\n",
-      " ...\n",
-      " [0.01960784 0.01834862 0.09473684 ... 1.         0.74311927 0.56302521]\n",
-      " [0.01960784 0.01834862 0.09473684 ... 0.74311927 1.         0.6173913 ]\n",
-      " [0.02040816 0.01904762 0.0989011  ... 0.56302521 0.6173913  1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f86df2cf8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 6 of size 183 built in 1.2535755634307861 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 6.0, 'k_func': 'tanimoto'} is: \n",
-      "[[1.         0.44444444 0.11111111 ... 0.03333333 0.02857143 0.03030303]\n",
-      " [0.44444444 1.         0.08333333 ... 0.03030303 0.02631579 0.02777778]\n",
-      " [0.11111111 0.08333333 1.         ... 0.19230769 0.16129032 0.17241379]\n",
-      " ...\n",
-      " [0.03333333 0.03030303 0.19230769 ... 1.         0.83870968 0.57142857]\n",
-      " [0.02857143 0.02631579 0.16129032 ... 0.83870968 1.         0.71428571]\n",
-      " [0.03030303 0.02777778 0.17241379 ... 0.57142857 0.71428571 1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f86df8f60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 6 of size 183 built in 1.2414467334747314 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 6.0, 'k_func': 'MinMax'} is: \n",
-      "[[1.         0.38888889 0.125      ... 0.01785714 0.01785714 0.01851852]\n",
-      " [0.38888889 1.         0.08695652 ... 0.01680672 0.01680672 0.0173913 ]\n",
-      " [0.125      0.08695652 1.         ... 0.08571429 0.08571429 0.08910891]\n",
-      " ...\n",
-      " [0.01785714 0.01680672 0.08571429 ... 1.         0.68       0.48201439]\n",
-      " [0.01785714 0.01680672 0.08571429 ... 0.68       1.         0.54887218]\n",
-      " [0.01851852 0.0173913  0.08910891 ... 0.48201439 0.54887218 1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f85512668>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 7 of size 183 built in 1.61334228515625 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 7.0, 'k_func': 'tanimoto'} is: \n",
-      "[[1.         0.44444444 0.11111111 ... 0.03125    0.02564103 0.02631579]\n",
-      " [0.44444444 1.         0.08333333 ... 0.02857143 0.02380952 0.02439024]\n",
-      " [0.11111111 0.08333333 1.         ... 0.17857143 0.14285714 0.14705882]\n",
-      " ...\n",
-      " [0.03125    0.02857143 0.17857143 ... 1.         0.8        0.47619048]\n",
-      " [0.02564103 0.02380952 0.14285714 ... 0.8        1.         0.56818182]\n",
-      " [0.02631579 0.02439024 0.14705882 ... 0.47619048 0.56818182 1.        ]]\n"
-     ]
-    },
-    {
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f85534668>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 7 of size 183 built in 1.5151872634887695 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 7.0, 'k_func': 'MinMax'} is: \n",
-      "[[1.         0.38888889 0.125      ... 0.01666667 0.01666667 0.01724138]\n",
-      " [0.38888889 1.         0.08695652 ... 0.01574803 0.01574803 0.01626016]\n",
-      " [0.125      0.08695652 1.         ... 0.07964602 0.07964602 0.08256881]\n",
-      " ...\n",
-      " [0.01666667 0.01574803 0.07964602 ... 1.         0.64963504 0.43225806]\n",
-      " [0.01666667 0.01574803 0.07964602 ... 0.64963504 1.         0.48993289]\n",
-      " [0.01724138 0.01626016 0.08256881 ... 0.43225806 0.48993289 1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f8555fbe0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 8 of size 183 built in 1.8512804508209229 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 8.0, 'k_func': 'tanimoto'} is: \n",
-      "[[1.         0.44444444 0.11111111 ... 0.03030303 0.02439024 0.02325581]\n",
-      " [0.44444444 1.         0.08333333 ... 0.02777778 0.02272727 0.02173913]\n",
-      " [0.11111111 0.08333333 1.         ... 0.17241379 0.13513514 0.12820513]\n",
-      " ...\n",
-      " [0.03030303 0.02777778 0.17241379 ... 1.         0.73684211 0.41666667]\n",
-      " [0.02439024 0.02272727 0.13513514 ... 0.73684211 1.         0.49019608]\n",
-      " [0.02325581 0.02173913 0.12820513 ... 0.41666667 0.49019608 1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f854dab38>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 8 of size 183 built in 1.6855223178863525 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 8.0, 'k_func': 'MinMax'} is: \n",
-      "[[1.         0.38888889 0.125      ... 0.015625   0.015625   0.01639344]\n",
-      " [0.38888889 1.         0.08695652 ... 0.01481481 0.01481481 0.01550388]\n",
-      " [0.125      0.08695652 1.         ... 0.07438017 0.07438017 0.07826087]\n",
-      " ...\n",
-      " [0.015625   0.01481481 0.07438017 ... 1.         0.58169935 0.3964497 ]\n",
-      " [0.015625   0.01481481 0.07438017 ... 0.58169935 1.         0.44785276]\n",
-      " [0.01639344 0.01550388 0.07826087 ... 0.3964497  0.44785276 1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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UM5LsQhgpvi3JtwxoZcBISO4yO6FGQoKTCn8bShW2Lg/rWgl50bd0s++4sLBjzYWJHZNBY0u/BcNAmmgWqDLNwo4q4k28HLR1Q8Xa0CwME3ZkefOSAfFbqjXOkLqXXYloLWzM1Yr8uSERuTWehX+fEbnuf8iZ49tUJEju3KhledRtVQEJERZUkkAoBSVEaDIAWN2M+nndapoFVUgwIxSMQKV8dpUIdyq/GvyN35n5B7/7MfwBgH1/8VkAwLZXP4Tsf2ZvIa1QCWgU9TDdqKpW9JYBYOCDjJx0aN8m+F07uRea1INw9+G/Pbjp4Idaaf4dAEw+wseDN0HqTX4js0uWeHV50ZBW+B92iLOuVUw92Fg8J30u/KHRDudDx0Nh23Ai4RmzS0HWbTgRGQMvzmDy4SAdPXXJAnUfmNSJpRPbwkLbjjawaPEb/zy83yhsXpqC7lcvY25X47FFr7BrJVkU2lk3yc23fxqRAbvxWlGZMIVB8hQHQikQllXbBs+i4+DsoIMOWsJNoVkshrnnWIgzjiXo2WAaBQAc3fX3eHyFJT+ZRsGwffcpsVz+q+Wp/63C0yDCUbzLWHKdG4lmWsTNgtSlZTJrrzHiU43ar6O0biJcD9wUpKyM0kt3Jd6Ny798NwBWuEabKQsSFgCMf2EgQNLi/AlOurLSUWgXvZyRb73yDDZ9/8OCtAUEfR19ry3uzFIv50XEgUc4aCKKkx9LCQIXx4UTq5B9Q4JWoqIeaN/+NlRsH6QrzFnWLFJAKjXQeBQnP5EL/b4e8QmPywEw0pdScWC5PhOl4nIN3M/po1dCttI6SBuZoePvX7ymiB+xGYrcy+0xFhvQbG6uH2f2nV5Zvei8HcoXyZxhqjyhFES3Yac1aKcmV0T3plYTp7AvRb20ez0AQC3ZgoilHb/YVtapsXUYVCYBIteB1/4axcLF25eU5Sda8eV6shQnbtWTtlKjMoobbAy+sDQhqJ74RMo1rN1SFoQugJG65B4dWok93OUhEvrbdrEYYYlUakuSvgBG/OJCgod/lYrp/g/etJyIldm/Qrp3G0V4WyWACbRAmloMTZP0Qpx8YYIieclgiVw+GGkVqmGsKJGsVYp8dFoHVSTB7AyNbrQJybrNoyGcQ8GX4yWdaRY+OjfnYnAeRj2a8SU41IoeqlkA5QaOxureeRSSg4Gx5fIgOMNyKc1iaR4HAt9zHofVJArDGaLtcB9C59cCH0LMqV1ORws8iMXQLBuzGfekHlZMhhxlj4w/ykA07ZprFgDgROSgZhCJtKVZhIFKt1g0BJQCpimqcI8/ksCGL80KXgWAAO9C0j3pznkUatUIRD0mvrgBn+raKHgYALD7tz4BrWgicUluypfgIKYFUsdlIAslVL48hKGSd8E5N2PjrzG/xuSfu6nEy+VBuMe7GAeBFEroez2zKI8DCOdyjD0R/iZZ/9Wl99sKmt74IWiH0yHpdms8iMWwRCRoKR4H0U1cfls3++CexlWvzIOuUONpRbNInC0wnoYiexGMantaoDax0CCw2qls1omGdNBBBy3h5tAsXPC+HvWcCyDIu4jXN4ML4VEYXURwMXb/1icAMB7G703fjadH70H2B4u/pZo18SkPEWBCCn4GMPNHzIk68HuMn1F63zLlcIuJQlZCRqW3UXPwl6MN+37k78KdfKf/g4LUmxpWH7z2b0mxalSB3t1aUyMjGUHPsRX6LJaYm5lePMqkFoCBF1ympWuGTD7ci1VnVpii3sI5s9MRyAVgbkcWkuUWsf760hHCABLRBgcnbjkz5BohNcoeFq3IHvzfm74bf9T3Br76vZ8GEE6uWgqJCRr6WSlf/5BcfGaJ4rsh30u1Zg5IBdEr1z8yFplrzSFKnGt/q6qFFiI57kuErLRlQpuQCyt3ZpJyjTF42yjA48ctJyzmnhtCHK2F0LhmkbjEhMbTo/fgq9/7aZz5xc/i8T9/bFn7Lw+RgMDgmkV8hp1Kzs8YwQrL07WAUM3CJyDCvo/Mhb/JU29qmHnIQO7Zqze/VtC6ZiEhvMbX1cPSmoUBuO0dOeXgevE2mGahIz5lCs2iXdAwzaIN3BQ8i1TXarp7w8eA0y7d1rZx/rd3oP81U1Sm0savAKYFp1BE7evdInxpdNsYesHL9eBIn695uSGuM9Nfq/NbB1iXgm2vfgi1cyls2jGGHdlx/P1B1pK17yUVVhyo9BNBNCqsJxjYp6M8oEFznZxq0YKZUhC7zJxNygzbV/KL7P+Bo8GanQ9sY3UkD40NY/saRuF9Y+9mWFtYJKfvaRaNmB+RkLxIMfOQidSbGop3sbfe4F4Fl/ZYWPOMd7yKL+nNSgQFBP+Oj0dnvBwQ2RcGlOeY6Xf8/8yiHrFzGqrrDcTOeQ9T9ArF/P0m1Ongw546DySm2T71tDeXwvpGdXfo3zwHHZ8Ln5cdDb7HtEt5nPvF/oZtAEDEVRL1LBCfZNcqkmf/K/0S9Cxbp/f1CswUm6+ZklHJ8YYh7F//j4ogugkaUcX/epCqq1n4zNTJf9e/or4huTeqKA17kZ6IW7jHX/wmNs4KOBHTElyW2bcNQbIo1LIDM+HdD44SUvzGoejeP91Yg3Psyy3X4Ow4ODvooIOWcMuZIRwDuz1TpLJ/EEaKBBLB0ucX/72fGv5Y9jGMzWexIzuORJZpH9U+DWYCqA1a4KeJLQOJyaBtqxYbVdFD+zZh++5TQpPwjwOMQn5ojLWDtQYtcSGKq5n8thIUpdUE6rSK4l2GeIMX3bHIbHirPbkarhbzcaliBP7Xw6/FcFTXG4H/DEzLMPuCPgf7soZyH9MoKgPeCysyz978fBkA1LnGY1hqfmHwb9e/T/5d+hwVmo2ZcueWk6AV2WvXyLDvpLzLznT9OiTEv0PMxkpZWpGKbfghtp8i0IoUWskR/Aw9JSNStFEcVEAsB6qb2WwmJOguIYzTvSWLInHC1YpNq4HY5dcqmkErO4zod7sU7G0V/pqZy0XtXAoA8Fj2MTy3+Tnc8ZVP4Gncg/duOAIAePaVh1AbtBC9pAgh0Q5iU0SYIFxgHDi6Eakp3011kdVdfIALjosxlNayi5e8IIk8ECuhIDrLflda60ApX7ucgegVCstnbvjNDy4suFkShsgCDTU5IgsUVmxl8+YmBke9YIgsUMg1Nh4QVAUbACswI0wPAJGiDT21/HR8P2KzbqlAhwmi2KwjygcqugTZcKAWbWEW6CkZasEG3CLVaomZHq08+BzRORtGOrh+ZN4GlQlqWRnROVsIJ0lfYZ9Y3KLCgtfMBFyfRYnl42ptdLfbtIOFu8bms7jjK5/AmV/8LB47+RieHr0HAJCYplBLMua2W+h7hd1Q7CGwYaYU4SNJTBooD2jInAkKlOrOClDQ0Ds8HxAah9LMV3Hg6EYoq9nb4o29m4EtFWzffQoTnxoBAFzaY6D3ZRWzOxwkL0hCiAy8Akz+NIWeiwR8FUC4v8JKyOI/AETr3krcN6BdYrksC5sBfkebfcwnUV3PNBuu3VTXMyFWy/kYoq6GUR4g6D3MzoWelqG7+TiF9QSy66LgmoDZHdJ3tAm0S/kG4QAENRa9i4hl7mfSuwgKa7zbPHOOzbM0qIhq8rLuMiQzS8+H+yzEZ8NkmoPL5zKSTIuo5iRoeTZfplkQ6GlZ5A5pRYrSkAatSEEVCZX+xR29ToK9WIjp9Q2xI6TBX6FnZTgKgVZ0UOuWhXCKFG3Gzq2PhsitC6dbUlgAgD3CVMa1vfPLMkN2ZMfF/6dxDx47yTSMx06yKMnFvgxMt6NitY9dYK5hGElJODgBBJb9eGDbWZzPd6N3mOnd5/OM/XdobDhgnhwobMQDrrOz2s1zSxTUeghowkQtp4ImLPd7FTRhApCEAOBCwy8UAAhBEQbuSJRrjVqT37Qw+0yQsiL+87lZsUYThIM7NvW6iuv2IkzypRyczaBng8tcIFlRbyzii5KbIZqEHfHmuZSDU6xXx8MRNHvHK6jkL6bEBAptME2MFGEl73yQDbYOrwReH/3gppCZkJpGRuod/kYbGksz3JLC4sKJVaIK93LBox6JbBXv3XAET496AgMA7vnmk8IMqfYHL4hWcsTFUIvswjQUcr8Yw4EC0yi4sJjPJ4TpcT7TzT77vj80Ngy1h91gShmo5Shi5zRYCSpMgVoP3IfWaUuzqIf/4QRYNSkArrnjPSRmn8nMnrIqhAPXNsIQmacNQoKNA5Z7ksKEhl84NBMUkTpqjJ4N/17P1vlLFij0LIGZlqH7q6G5DyvXLAAIAbGYoAAA6oZQudDQCu42qCsICrQhdcfvszBSCiJFG0bKNUN8PgtbY3PkPgta95xT1fuNX9DxMUchMOMS1LIjBA65ClHPTjSkgw46aAk3hWZBLApi2nA41dmhSI5RyFVHdDPf8mc6SyqzbWTfkERfj8nTcfSWbWjlYCk89TKzwdWKLtQ2P4W77yXX/u7T8OwrDyExTXGxL4N7vvkkAODIf/40dh78AEqzPZDcl6g2KyN6fgb1L8boeZ+X3MXAKzaq3W59xR+x2hNd8DqlVY/nwAuSU8RwDuzzjk8eAgA8v/8eKLkqarMxKLkq1B96lCS1JCF5ZJm1HerU5/oboPewDr3LPyrDIwdw/cPxLQcx9e8bafTd32EqRaSuEmDk5KVWZgyAJah1n2jkgLQCpWgicVlF5HIJk7u9baTOAclJW5TEk8634DR3XC3Nx+DMHUm1NA+57PUNicxqUEoGIrMa1OkiKvezcn+l1b4Sjkc8tiiZnGaDti32nRxLNC/YWw9KganZxkzUNnrT3hTCol3407B56nW9TUYTUZByjf0PyQC1XF8WD4+qJdkXKgV2HvwADu78J2w88wk4CdcnkDRB403SpHX28BA3A9GKScL7X3Pr1ERnvYY2pWGCqJtmkN9qIzIlIzoLjJfZzUzjNh7ecBp7K1uRSdZQjTFhUVltQy5LoMtM125asNedtx2RAqptLSshOs/OcX49+23mnIP8egmRBa8FAxcE0tkYnI1BgbEwAqTGAL0+vNjGMRDTaii5r6dZ1zhuAkQKbJ7F1UFB1n3cQaVXgawHjUVbIyiskYV+nd7fQgUy94XmJzMaWS1g6lX61dDKV5JhC8vEyGqQDBul4Sgyug1bbTTdikPs8ZQsIKa65pEvzd7RZOjdwWOKzOqARGDFZChV2wuTUkDSQkyrNgJUN72w6DvQOObv4OWHvxTeUqj0e07L6CUFc9vZTRC9xE5JabYHG898Amd//rPY/IVPAgCcZOuFXardEmo5QO9nggBgQgHHZCE8+P+MO5bfasN5eh0bvNfAK1/fDmwysHCsB9Ympt6kD2vY9aFDGP9C66382oHeJaOWldxlJgS4YOACIb9eQuacg1pWEmP+vi2ZF9kNrGcIjAyFs7GKImLwG/HOxirwL+3NrV4IAMxX4L08JLGcushZpBKLXqUJ5JKB3oNMQJVX8QpiFPHWCIxNYSQl4Vcw48z5XR5QhfDyHOJa0AGdZExgf5p4bKoxlUBq8vK3EkqDU1vPReAoBGrRQrUvIjQZtWiv+GG/6YVFGFiVKH8FKNst18+u2Pbdp1D6HOui3qxilVcrkvEo+l6RUe0jwpkpGYCTsLH5C5/Eyf/4GQDAb07ej1OV4dDt1ZshqQlG5orOygGhkJqwkJoAZu5VkBxn+yoNEyhVIPmahIUtbCx9WENlkAb+A8CuDx3C95/bjg218bbOmcAilc4BXguSvYGi80yzyJxj55oLES4o/OBCQysClT6fEzFPgNfjiE9TMa7UAEzFgVrrXBlq2UIAcOgux4BrFvEZC5GCBD0tie8A9rbV00yA8arqWpEiOu8gdoWIyAltpSRgiBkSnbdZe0Cwh9JKyEhMmqIloVKWIRk25LIJbY79rrYqAW2uCiuRBDFtJCfZddEz3oOfGfXo3qLKl88MUcoW7EjQgS1XLaFZxKZ1oVlIhs2ufUNj5KUPmaPj4Oyggw5awi2pWfibCi/XZ8FZhtxHUVhPAkxNbVaGkjThJE385uT9AIC/HHgN74rfET6pOp9FcUgRGoXezyW/DH7K2Zj3Fimvs107k32uDFLx3+o1UXHf9i+OjsBcY1wzn0WlXw1oDcy8kHzLYZ89+FmaRsZmnEePAAAgAElEQVT/2iLis5Fxh9r0Weh1bMVgCUGAn1u/H8NIE+i5CIw0geNrMMQ4EG5jKd4BvZUmQyE+i1pWhlpxtQDHM0uI4zObEjIUX4vCWlaGZMRY2D2uCY3CX2qQZ+VLFgEJ8VlYCSW0dSJVCCuf6NMiSExBZIU+i5si6zQj5+iuyLtQeYSxJ+PjJVaWzs0yBYDz//vdgSxUXqCXZ5U6qSjky14g/vjvDAtKeOXLrPQdTy8vDxH0vbY4TyN6fk44M3mHdBqP4Nvf+Sru+MonxHo8W/Xbn3krzKR35lftayzg0wqUK0yw0Wh4nJ/UTNCoiolHulEc8YTbA9vOMjr5ae+B2PK+k2KZ+3P6XqMwQ2jXszvYfbD5b5fXvMg/v1Yx+5Y+lFZ7c+HUcj+Hg3+OjmtY/5Wplc2tmQnmPoCXH/HqqIaxRXsPW4hccbdBKRxNxtyWCAafu7iygr3NIhK+bc4/tAaxGROOQlDrYde4+/vj4dsLqzVKKebevgZawQmkqP/4+3+FQnHi9q3u3Qo4Jdyjg0NUuEpMUJQH2FuEJ4VxCjdnYzYjG/qp4QCjix8fHUQ3gNi0dxH0HBM0SxGn+DqCjekKCyeuQaoYMLvjUOcqghqtXcrD7I4HBMGBoxsFpTwgIMaGoZxwwz5uCrx5LAa1SlHtZn4StcrmPPAKWy2Mgs0ZlfVszzDylDpXCRUYYVTqmYe89WLntEAqvJVg8+KCI32OtkbH1oP79pOreKKY+K7uTVsZIIhPUlQGCLInHFT6XQ3KZYHO3Ksgd8T1eeQtSIaNzDkTTrJ12nr4nIO+EuH/8gmLak5CNReBVqCIzbjaTSLWVq9Ttcwo4H7WZ7OmzmG4bYXFUqinaHNBUU+TDYOf6bnt1Q+5maqNmsBigqLei10PO6pAqhjiAQ3UnqhZODQ2DKvABF7v8DxmxrMs98RXJ8MqaECSQikRMXYmtglqFcLc4VoGFxrN5uL/v1zwB5k/wOq0xwr1axNcUPB1gEbqeDMsxrykmhqqXfjHuEZhR0gDlTxAG0/LUFvrh9w2OEPTXzFcMEQBkZXarogKS1IjbeSXdRycHXTQQUu4rTULXvOCl+v3+ywSrwVVam6OqEtkrm7aMYax+WygHsa2Vz/k+iuo8FtkzjT6ROprTfg/13/Haz2E1XeQKgZwMYsHfG0V12XcbmwXYzh0kfknHth9CgeOboSVhqidka0jWHKNgtfRSJ8Ir5PRKpr5LPwmAF8nOpuC2de4bliCmq5rDWZE23MzGjNG2UKj1mKF2KGRBQqtwOtZsHBkLaciUapcc5+FkSZITtigkpf4RsrVtnwWobtoo8TebSsseLLZ6t7wwrwmT+BxC9fwUnncDImeD9/ujuw4jo8OiiI52179EI7u+nvs/O4nAw7OpVLIA36KEJ8F91Vw34UTZyaHXDPFsr9kX+/wvEhM4zif7xaZr/7veGYrANR63GI7LhGwnbTxMCzms6g3QwAEyvLxlHi/sOCfI/OtpZAvBlI1AwKjPhnMb2aEOTgBn41PIRLTrrbPQqCJGcLRrs8CYH6L5dbwvCmiIWmph+5SH4U0sg4AMPNTPej79iioZYFW2EOpv/UuXHiXgs2fnwdV5UCXMGmhBBqLALOeJ3/qfXeI3qMbP8zewDN/tAFK2YKVUKDmFyfgqJfmRHiSh0NpNIKpd/QG1jOTBGqJ4uDvfwbvOf0oCn/G3uCxieU165Hcrmr1zjcOYpigmoqF7bnQqIbf92DGiPjM193xyR9j79Gt2LPtGABg79GtAIB1/8h+Ezu/wmhIG7kG5S29gv6+FJSqg8SJmeVOi2GJaEj1zlViSDKchtRxyXBw/t1MUBObID5B0L+/DHV8dmWaRbP2D37N4o4BRqySvIK78sWZtjQLeyjXUM/iR8eeQr5y6Sc7GqKVro0QNJMkEPXgpsd7Tj+KZ0e+g3fgV6/JfuuhVD3GKuAJBjbOx+QGB6ZfUAAQy8efufs6zDoIua56kxWToFSdgACp/3wtwVmYABoEBcC6oiUu8rc9o4rTkPWuzdxsENNhl7zFdothIKYd1EbaUBZuKmFhZZgu3Lt/ruG74pCKdd8wcPJXstj86WkxzjUMUtUDzFUjSQS3nrcU5A2ADu3bhJGnZpecD6lrS1f/GYAwPQp/Nox34Ffx0uc/BwB4/C3vXnL7oeB9KRZpice+627QLMwYEVGOhnm6697xJRuj2NLw/Z3/zxt49e+3I7X/+rUvBHoaBEGzz9WcgnhxedwVb2NN3uBuo50wAVGPwe8F780zv5TFyJ9UGvqShvYZbdZ7tFmTId82HU2GbDoY/5mMyBUZfmqsea/TerjrUVUGnOXlwnSiIR100EFLuDl8Fskhunvol+CMuTUaHIorv7QTXaerUEpuNODyFeHDOPXH96DruFu6LE3Q97rewFmIj5cE3Zs3KfY31k3+K1PFDu3bhNgUYTUzAVHJauAVG1ZMQrVbcpPCGIW791BZEK4AN0kpF0F8jIVR+L6+9cNvYOfBD2DhTLdY10nYeGInq1fxzMHt+K8PfQsA8Fdffi+iu5mmk/g841DP3akgM+pgeidB+izgFt3CwD4bk7tlJC8QMS9uerD5eueB185Qqg7m73A5GYfZcdpRGXLNhh1l60fGmHdv+O8nxe+5PyM6psHeUoJ8wqupoc0D2iOzuHLeIyPQuI2eH6qieK2R8t5Fc49WoR5jjkBzK5tD7ptRRBbYHLlJoncpiCx46ejcNIlfKODUR71zKddYxS25BlHrsrajguQ+l7zmOgSLwwTm1gqkszEM/ZshtAcjJWNmJ4FaIIi4ykL2jAGlaMKJyJB0G1bKR+gyHJgpBdo8ux/5fUkMC+ffn4ORZfOPTbmaUL8DYrN5RWcJajkKKlMxxqEWCPpeN3Flm7ev7Cl2XR23b4hkU1bcF4BaNCCVmDZ94X290BYAtUxFgpxsUlR7Q/qGUGD183k4UVV0pXM0BfuPfOb2Z3Au3MmFHIV1UoYZl8QJA4B4i0mZ293wIgoao0y7T2W1W4YVI25+h9sKIOf9zh/pCCtbx+thvCf9aGD85UusJ+oTOw/hzQoL6VbWm4IxWu5nD68dBUoDEqxeAwWosHrdgrj9bDm1r1EpVKoOYnONYwCEYKmHXAvO/fn99+CRB1mFc+EExVbscWtreNCwq28cL5aCMUY9o4ErrP7sUzoRE0KCTjCBHJ/ynMx8HpGF4Jz8fg0y5Al7B+xZcABU3e1hIoaKKIHovky6KLRjcRhdbranK0yrPZKoJ1LcyPbRe8iE5JLfpJrV8HBEdFt8Twxf2NvnK/cXMeYV2Ws5iugsgVIiImXcTBGoRYriegrJoojMuwWGswS1DG8FwLYjWUD8AjPBJMMKhFqtJCCb7D8AWE2SPSJzFFLFYPN3fRZSxQCxbvNWAFcD9WX6e4fnRUFdP/R+G9HZ8C5fi2HhTDfek2ZOT56I9svd+/CBp38DUn8No6Ucjk943vdCMY47hy5jAj1svzkb2rwMUnET1CreHEjFLWwSAr+Dc7HxeiHBEb8oY2+cCYU9247hxdER7Nl2DHuPboUaZ0/FHf2zODe2TmgeAHDnelb16mwmgUje215twH0jzksw55hGptaaz4GPNZtfPehETAiR6Otx1HZUYFUVxKe8pLD4NIW5tQp/4h5/gAFA0t3/PkHh/++HZISM6RCOz8oA2261nyI66wqoHBCdpVArFGbc1QB0CrVMYWsSJMMR1dgkA6j2E0iGV6BJqfj26xMUsSkKyWLr1yM6R1Hr8cajC5T9tr66dxuGxU+ssPCDJ2H1Ds+L4rn0RznUckBkSg7JHm0dvzl5P/5y4DV3eTcAwJmK4vff8ix+YYK1g797M1ODjk+sgjLILnBkVkZlkCIyK6O2xkB0jN38lcH6PVw7vDg6goc3nMaLo6w9wcMbTotxc40hBAQADCfYeRvPr0PFJVrVBmzQGDtn2nkZ5vKq4glwjYSDDFUD2gZfRxmqitL6ZKgKnGK/czQJVZdX4kSoV107cvVMcW5yRGck8CeRCSW3CE2Z/S+vkqCWKWo5CkeToFbYA1x1NUvHlwDrLJIMq2freqfMUzgKUOsmiMzTtujcS6Hj4Oyggw5aQkezADNJ6pmOXWA1M/NbbWSOcfU12JMDYDRtKyFDuxLcJq/b+cvd+4RG8ZcDr+GZxHZ0D+Txh2PvQTrFbPg3Tg6jeyCPxzcfxcsvPQAAmNtlIn1YQ3HEhjKjQs+x7WWPSNBznuPPj/qwI+co+LkKSl30kTs4FfEZwtx4eMNpvD49LLSL16eHxfgLL96HM3HPiTO8gWkWRoYiNcZHZdQG2JK/nQJvBcD33QoUoEGLAAB7LgK5m9cP9dbhTs/yXCRQUzR2xa36lSOo5YJmiNNGohz3PRDDghPxyvXr3RRqgaDW63iO1xyFWmR1KXgvGtmgcFRAK7J19K7F39u8FocECDPC0Zimoms+5nCWwFFY2oKeJcLMUEsUUJVGM+R61eAkhJwHUARgA7AopfcTQroB/COAdQDOA/gApTScc70C+KMhStntZ9FG6oDoZr5vE1JTBIfSbrk8NxoSm2PRELil8BjY6VosW5TjiZ2H8PKlDfjA078hxp5JbMe5n/0cnsoP4k9eflxERp7f9yCGNhcwWsohMeXWjjylITnpoHCvjfQRCXO72HhiiqJQllHthnBm+oUGL/IKBJ2aPErCnXo8GlKP5P2zyLtOS+6TeOHYfXjnwz/GCy/e537uQWSewFgLmBVNrEsqMrrHvFZ+si4hNc4egum3m5DnmGlgd7PlSr8qoiEcepccGKv/zEEnYnBiDqSqFIiyRF9ny7yLujEvIb/Fhno2BsBC1I0Q9RyVMbOTbSsy5z6wuQjUogXH9SPwlAB2LA7siATFbbTEoyGyYaGWY5m9HGba9VUInwHzH1R7ASvpmiMFguJ69p0Vl4Q5IRlA5nxjNMTMRt152FDcjve2RmCmmO8izG+hlD2/h56VYHXFG7geVGnduLgaZsjDlNL7KKX3u59/B8D3KKUjAL7nfr7pwVO46+GPgCwHUr9XA7R7II+n8oP4eCa8BP7P9h0Ry3q2uR3NIyPXGrm+gtgf1yqa7T/XV4CSqzZU8DbSJKSiFRMYK4HdbQqNwuiiMLoo7LkIjAytq9DFYGaDWpg/cna1oRZa27ZaIKHrmnHJje65f/Hmj6lSan4sViJ0eNm4FmbIEwDe4S5/CcBLAH77au9kpaFTnoW53c3cFKZIhkVEqsdzKA2z7c3c65XC62XKwJKh02cObscTOw9htJTD77/lWQDAH469B3/y8uP4EwDnfvZz2HnwAwCAjY+OYkNyFn9z5q2obHffXFVgeiegzKiY22VCmWFv5ZntBIAhOBR+KFWnIUTKtY6w9YHGqEPptRywhXFF8qWoiITkS1GMPHgBAHD83CDKmwzscR2eAn3Avte248pdTIvhkRAAiI1qqG5w38auhhEWOpV1J8D/iE95D7nfwSkDwJAVME2ix+KwoxTGoImiW1/E2VhFZl8cpd0VACrmR9h4LUeROsdCmNV+to/IrA6pZsGJKpBqFiQ9eG6Uoi9S4iuyE50lwgxRfA5OzdVuZIOFSdUy6wECAOVBgsQlB1fuIZAMiuRFNofSagmVPtcJ61IvJJMgc5y9dPyhU9mgMFPhDk69K+jgVEsUykKlwQy5nqFTCmAvIYQC+BtK6VMA+imlnNlzGUD/CvcRivoanO2CaxK8ezlvUlzvs6jlIKpwt+Oz+K8PfQtvVgZxfGKViHqkUxVhenAeBgBs/MdPYMPbZvHQ4Ch++M8sdDq3FUifZb6LxCkNZbcVQPdLKmprmLlRLxjCSFncZ8HNk+hsMIGu3meRvH8WO/rYuXl9ehivTw+DVGTcsX4WJ44xAUvAojXYBhEpAYBMkt3QKfd8RfLeXEq7K5Ddh50/4JX+aIgZoiCygAZSFhDURkhVBq0qIFUZ6rx7L2ytQD0WR2xUE+HbYjSG/BYbmIsAcJC4zLalFQkWtgAAj1wAVkqFAsCJyOIzh0fKctPDfT4LTrgCALlCIOlArdeB3s19IhS1HBjPwqVam2kWNgUoHI0EmgvFp12fhMJbAXhmiFo0ILkPu54lkCymXXCehZkgzPSgQZ+FniXoOqE1kLLaMUNWKizeSimdIIT0AXieEHLC/yWllLqCpAGEkI8D+DgARLVM2CoddNDBTYQVCQtK6YT7f5oQ8q8AHgQwRQgZoJROEkIGAEw3+e1TAJ4CGN27nf3GJyRUhlYWQH5j72YAgDVo4YHdp/DG3s04UNjo8SwQE5EQbo5w1JsdYWbIX335vaisZxKc8yjeODmM5/c9CICZHhv/kRX+Pfvzn8XISx+FMxUFfdBlXJ6WMbfLQPqwBiML0Tdk5kEb0TEN2TONKfbMDAk/L/XrNyM/Oc/24PuDnqOmtsZAdFbGuX9bhy1vPw8AOPdv6/C2xw5h79Gtgmtx/NwgZisaevIU029nx83NDQDoejEmGJ3yFPO6pS40eqTjl4Pz0nwEr65DQcJBpV+CMWgCrmaReTEGOwIsbDdgxlymJYBVz0RxZRuBHQFmdrpZuAWC3oMOyqskUW1cm2EaDzc1tDpSlpLXPXKUL02i6wSLdADMzJjfTNBz2Gu47KiAZAJq2fbMkFUKEpdNTL5FgVJx0HOUnbP8OhW1LglWkpG9AMCJEGQPuwl+psfAzJ60URyWhVYBMOeoIxPoGQmRvAP+qpZ1B1K+AqnomSESwDJZW8SyhQUhJAFAopQW3eU9AP4bgGcBfATAn7r/n1nuPprB35FsuWaI5RawVeCaIlsqeMDn5DyHnCBk8UzO8jp2A/ujIc3MkOjuWUTBmJkc3QN5DG1mTsMNyVlseBsLTYy89FGcfscX8VR+EH/92feyYxykSJzSREsAXpwmdVpG4V4DxQtqIPeDrSOFRkOYGcIeXJ53UJ8bwn81t8sUoVOzoiHXV8As0sj1FTBTZndlbY0hBAUnYw1vm8d4OYvxN9eJh1r3KYwLmyi4TszNieKlMDMkPBqiLFSZOeFCqkrMnKkqTGAAmMsyk4RUZUiXPJ/FlW0EzsYq7KNRdLm6r5ECFkYkmGkqoiHV1YkWoiHuOefRkJKOhS0Q0RDiMJJXYZ1ncnCoZUm0ja0MURgpFU6EoppTUHNDpzwcKs97dG+1Auj9SXceXjSkuFpuIGwVBxU4KouCGCnZ10VdhjaXboyGTF6faEg/gB8QQg4D2A/gW5TS74AJiUcIIacB/Dv3882Ni7GAD4M7P6OznO7NqLu8DWE7uHPoMo5PrMLxiVV4aHAUAIt68BwRgDE6eZQkOk8RnWe9QiJz7v95AqvXhNVrIjp//RL/cn0FzE6nRVRkdjotPiszKs5M5YRfg8PIUGgF9uenfa80+gEAcrcu/vj2/NoL4EU9tDyBliew57ykP9lgFGvOouQhzqsJM814FmbGCYyJ5RT741EQtUAgmRRWEgENoVUodRUFrCSLgqgl9t9Msr+rgZsi6zQTG6C7h34J9thFAAB1KGqP70TschWXHmIdqld/6QRg23CqNZR+9j4U1rIHVy1TZM4yKX/uF9gFSL2pYfifx7wd8MYwvhoR+UeYGVJcLaG01sHAK6zcHI+NP/TEIYyXs5h4ep14uytVgvX/EN67QlSI4k2GHlwjksIqLoU7fokKHsXMdgXpUbbdmQcdpE7LiM5T/OhPWavEkf/5SXzyse/iM8/9DPrvmUL5GyyPZOE+E/FRFWu/1nrrv9B5NkH1jl5Ue70HsNorITbDbvyFEfZu6TrtYGEkvDFy/m4TP7fztcA2n31uF7InWDl7AEI9H/h2G53gTQulHauDc+2WRUIWACQum3A0CYW1QYW591AFC3fE0HWmisn/4plj2reZ6sNDu2u+cn7JadCQmhjV7WshcXWeAqXVGpIThiim46gSJNOBXDWF+aL3xhGZqWB+axrZYwXkN7H7fOqnvecx+wY7X8QC+r7JeEH+2hfmlmHU+oKNmmKXa6ASgZlWoRZMYYYQ04Y82hiy/+H8vyBvzrQU6+3QvTvooIOWcEvSvQtrZU+VdLkVdkyGMAgB0HgUpFJj/wuN1Z/m3beklaBIXpBwaY8BUlYEHfr5/feAxm3gXkM4FyuDFDSqwolroocGbwCkTTJVnVe4mrtTgR1l2aMRN2t1bpcJ/ZQGPUuhVFl4FGB+iMogReFeEyP/k3VsP/1Ln8GGf/k13LfrDI5cHIJ9H1O7u36sYuE+E1ZfGpIefMs5keDllHQLTkQR/wFAzgcbRVM3TChfYfU48hs1GBlOQaaILACX3+4gOaqwhsZgn7sPERgZIsYqq9wGvDEL3/rXtwAAjDSF3WUhphPM3utpFHYEsLss9O1PNVyXZpCvFDG/ydd+MA1oBUAtUhQ28F4fKhbupEhcBBKXeE0NguKaKAobCNIXJJCXmSpUXUVR3koRn5RAuM+yq4X51GlmxLRQHFICtU61MkV+gwbN1XjK/RISUw6Uqhqg5DtqArJBYcdUoVFEL8uorbIRvSyj7Pr945cAZNjciGV72klOg2RSFIYVQWMvDcdAZVaYt7Qm6tG9Kw5SM8nGOqCF9ij3txxiM26BjxUgeZGdsNJqguJdBnpfVlHrIaIegZKr4uENp/HK17cLM4RDqhiB0vy8bL8fmVEHpQEJ2rwsfp8+zCjcACNcpV3Ncm6XgcQpDemzKj70G98FAGz4l1/D6L//GyYw7h3FmacZn2HhPhORSQXKQmOHG6na6BfgY+K7+pu9roht6qKFis5ui9g0UO0Del+VAVAssA4D6H1VxswuG8lRBbpbJyKy4DoJ1Sgef98PAQBH5ocAAGcXhpE9DnHNorMAJlRIxfAO982QPh90hlZ7JJgp1t4BAJKTNmJXCArrgPkt3kOZfUmHkYrA0STQh5i9ZOdjyLwWgZn0yE+k3KQmoR8hZQMT0zaIWzE7Osc4MMmLlqjFEVlgDlO5agl+Rq03iuhMDeW+BBIAevez+c7fRaGUJNRW2ciccPkecYBU3HNle8JCy1uo9GlCUABA4rIOKhEYaYW1t+BV/kwHqNYahUVYdfAmuCWFRbWXNGgW7YK3zlOnVaTe1DC7wwFNmIidY1pEbTbGir1sCmoWACuXzzuE8TL9ct1bfnongdVrgFRkoVkUR2wU7nW96S4zE2BCpDJIUd5k4jPP/QwA4L5dZ4TAuOOlj+KxDx4AALz8dw8g8e7LsL6bFvvyaxhh2oV/nGsWNCKD+BiKXGhc2aoKAWB221DnZFhR1jQ68ybbRnENExgLm6gQEvw3dKDWqFkUCMqPecLNAVCdj2HgZa9wDp8LnxfXeDjkKyYm3+pdax4N0woQLMapIQWxGUDWgdwRtr1qj4T5kQjMFIFStoRmIa+isP6XBVTG0oBLqKKJGBOmquL9r4crbP2+n9m7FcRm2DaqvQRKGZjeqSI+6Y71E8SmKNSqikovm7daoij3JUQN15kHvYc2flGGtiBDMl2iV5VpyoCrWbjXqjygwdYIlCoVqffVnhgclRG7Kr0R0ag6PuMgeynaKCzaKP57SwoLYOXc/tSbTAAU7zJgJRQkL0io5VTROk/JVZFJ1rBwrMcLX7o5EfWahF/L4EifBQou5bi2xi3FNqMifYRdHM7MBADDrfOQOKWh6x3McXnk4hDuu3cUd7z0UZx5xxex5fPMPEE/Rf50L7YshJfsD9MuAuP8Zm9SFj857lUNjywwzUGpAclRRZgakQWe70GFkOCIRE3ozHeM99/1YxyZH8LZhWEkfpAWarVWIIgBoZoFn1fY/HjyIEMj1Tl7woGRIjBTRPR/MVME2VMW5t0waNU9huhIHvRHXciUWBgV8GkWfN9h5yhEs8iMOoLurRUpjARBfIZCK7qRmbIEtexAqdiIu37pap+K2LSJ/HoNkuWg6yjbQGkdUFltQylJUHk4ltBQzUKtOCA2+x3XLtSKAyoDZkxCfNYWmoVStm9/zaL7ePhNHaZZcAHQCop3uR3IplVEZwlKax3QhCU0C/WHSVRjSVh+zcJ9+FvRLAobmXAhFVkUrtFztsgeVWZUQeFOH9ZgxYDyJgOqG/Ww7zNx5ukRPPbBA9jy+U/ixK+wKMn2P34SuQdnYHVdG82iNCyFaBYIaBZ6F2sCXVmFBs3CPpFCN4sQY+9rb4GZAjQA5lsLeN8GrwXB1w7eDyfVnmbh5QMFNQuO+S2S0Cx4L1s7IqE04G2r5zDbRuVyF8pr2TqZdUzw0meXp1nkN0gNmgVrsuyaZv0EsSkCtSoFNAtjvQYzSeAokkiXV0pA+jRbhyoupdwK1yzMuBSiWUieZpGTfZqFhFhsZZpFJxrSQQcdtISbXrMIQ/qCHeBZAIBctcEPp3iXAfLPbj+RSrgTbXCvu+5q4uNZqKj1eOtUVttIH9aw60Ms+evF0RGQmgntUj6wLblmNvAXBvbZKLul3XgpvOwRCYkpl1uxnaD7JTeT9EGb8SyOqZh+KBj1ePnvHgD6Kbb/8ZMAgEO/+2ls/R9PIj0dzrNoJv35uJhnk/Ygva/rPp6FhGovYTyL0xIW3JwxzrOIX/Z4FvHLrvNyzsH8Fq+OA0f26ST25pgvQ9YpsvAiMAGU6v5zmBZWv+BXmZ0GnkXPUY9nUfZpE5xnATCKOMfQSxSVXgnGOMs0Jgvnw0+KD5xn4Te++l43Bc8ic5bxLHJHPZ5F5pzHs8icbORZyFUTq/YzLbMw3KQLfJ6dK+rjWSTHaoJnkXRp8n6eRXI8yLOgxZCL3qxnSQhuSWHRPHTKkHpTWzJ0emkPu+jqtAqlTDD50xQ0YYK4xU3UkgS5LGHXhw7h+89tZ/taY4BGjXAzZJ75MXjodHK3LMwQDj0HFMqy6/swUFvDxqNjGgr3GigAiJ9mJguPeiTefRn5073IPcha9239H0/i2P/2aez5/kfFdq+GGeDJpSQAACAASURBVCKV2PxndkQCZgjgQL+kwI5SyK7c5YSs/F0W1Dl2fPm7XIfirCwK4Zop5uTU1hcx1R9DLOv2cQXw+IZjeGP/XWL/S5shRUzdHzw2M+1ALRARZanlNMg680EkLvFiuQRXtsZQHmKhU9XtVFdZRTC9U4K2NY/yBHNa0K7UssyQ6R2qMEN4Qd5aTwSq246At7hUqxHR7MlMEiS6UqhlCax0BLPb2HW34l4+TMX18UgG0OcPnXKTcU0Utlsli+9XT8cZTZwCGFSEVNPKFNkVhk5vCgYn73Xq3H8nAECZLYIUy4Fep7M/f2+gj8hSvU5P/l8b0XWciL4iQHiFq8gs+87fCwQAkkcmQ3udXvzZPmx530lBCeeVtXpfpw0Vq1ITVmDMn0Iem7NFHkf2jCFyN3p/wBiiVl8aykIVVldM/AcAZboAqy+Nvf/8RVEPg/cm8fclAVhNDW1agVIm2PgocyRM/e16KDWKWpfHkQCASJ49rGbCe/P6e3rwfh5+VPpVwZ0AWHfvzPFiaAXs8oZMw7ne8n+/EehNAkD0J7Firr2+tgyzoqHvJRWJy57/ivci9bccNFOK2Ic45ylVpLvHx0uBEv76KvYAqvPsRJz5YBqpCwSVfoqu06znCMCK68SmCGo7Kuj+jltJbdYSc5Br3hwkg50zR5MDY/7P9VDzNVE2DwCrOwEEGiOf+hWm8qbPECQn2T6iM0ZDRzLJsOBE1cbGyBQoro+hsM7zr+hZgtEv/Tmqk+O3d9+QVsAcYqw4DgBUemXEZ2zx3w/eyXypMv/FEXazWQV2cz/g9h0xYzIASbw5wvp01Pf18K9TX5ymnnBVD389DH9vEn/OyRM7D+GZg9thAJgouA7RKAAQ1/FFhcDg1PSus42RHblmN/TzAIB4OPM9FP6HmC8/v/8e7HF7lOyF237A7U/irwMKAC+f3Y7M6aCzu744jb+vB4cCVrQGCPb6AABtjr2IqNtImAxVUanF4Gyswpjyeo2QoSqqiEE7FodsBKMHtW4Z2aNlbxvuw0mJ1yOEI2wMAIhuBiNqXGvxCQsASJ1l9S94X5Hk6WpoNEOqWaFd1M0ES2r0VwSX2kjZ6Tg4O+igg5ZwW2sWiyFMg2ileRAA0WNk0e232OxnqXGuYfg1DUm3RBMjAKKRkb+JEQCMlry6FENpFmO8EMtBqVEo1XDzs1lzn8UaArWCsIY98Ysyq4AC1tBovJzFeDkrtAoAormRNdCoNSx3vxxc0yCEv2lVOBs9Fqe/ZB8ZqiJ+KgbZ4JR1zwQihuVtg1fQqvcNNBkD0MCqDUPiooTYnAMjQTzNwFfbIgBJCtUs6nuMAKwKV6v4iRUWywVvSDQzzphU6zJz6B2eB/1RrqGr+fUCb2Tkb2IEAL//lmfxh3gPAIjuZ+kqhRWFiL9zDxjPjO05husKf1k+3nLgYV9tz71Ht+LhDaext7w17OdXFf4an5X+8IdIcoUFcWigadH1glam0HuWf59F5qnowt4uOsLCBfdXLFXmv77tIcDqdnYBUKtUCIyl+noEenn4ljmciNKUjQl4fUkArzeJvy8JwAoEH59YBaukCsfniz960K2JEXwY4m70oJ1eHmGQKuFz5kVw+TLbFwKCAfB6lXCocYPVAa3KbfX1CAOhNOC3oK5TkZjsXPo1Ce31OOqD7naEwHSZoaCAVrQRu+KAasrKfBbNggw+n4UdcUv/+yt2q0pbmgXg1e0Uc5JaFzy3tbDg0RDeV4TXrIrP2IGCuxyt9ANJnVZCoyFqlUVDeFWtareM2FyjecEjIKkJS0RGUhNeQd3km8H9caHBQ5+SO8b7kgAQvUn8fUkA4E9efhzatIJ4meDlAbZudJ5CqVFY0fBoiD/C4Z97WP8OKyYFGvjIOoVa15hZrOsWw+XLACsOzKMhvHp519YrWDjmkV3e+fCPsffoVvTtlwIRK165yt842Y5IUIvB16a/2lV0yoHsExZGt3vt5r0TEX09jmo/RSRPYZxl35tZB9FJmVXqetN1LvKIxJwttrNcyFV/YWArNH3A1oDCOvag97zpOtm7Yg3RELYREhoNiU1RlIe866WUALsJrSMMHQfnMrF9zXjTXiPXG9xH4e9LUt+b5KHBUTw0OAorGraFG4dcXwG5voKoBMYri3NwLSOs98i1gJGhogqXmXVgZh3I3bqIjHDY2o0xOQGvr0jbv6vLp2q3MldHWHTQQQct4bY2Q64Fz4KbIH6exfl8N8zjOZdrwdBKEyD/OvW8jKV4FryJEQDRyMjfxAhgjYzec5pFTPz8i1oXgd5NYFUhoiKFDexWGHw5SGoCWNSDN/8JjOttFE4pmg3LpddysLd47No711/Ci6MjGHnwgigE/OLoCPZsO4bnK/eg96Bet836fTRGP/xcDLkU/H09z4I7OOU5FcU1EB3PAObPyOyLC1o1J2LNj6gY/LeFFfMsAgjhWciGx0rlTYiyh8N5Fs18FlYy0eDglNvgWdy2wmKpdgH1QqFVBycAKCfigNuzkncyu1jtaYiGtOrgDAP3VTQLnWrTMTxzcLsY+0MwZ6Y27V3S95x+FM+OfAcHdQM/9/yvAwD6akAtSxCZc1l83bzPZ3MhyZ2eK3Z+1jk4tXmgcoF57BQAZ+I50AsJDPucnvRCAi9iBFK1NSV4MSco1ZQGYhYAwTiNTbnXLw/UdnhlCLgQ0QpUREMAVj2bF0u6quA0c5+wiM5SaCUHlACVVcu/DtF5CmJ7c/YvL4XbVli0C1HivUWuBS/9bqWB8/nuhhMZxpuoH/N/rv9uKc1CKRPUu8Gskop4OSiwDuoGdkY0SOXwG0yuKw7VDneiHfjf+HxZqVIoVW++tYqGaJVgvJwVmoVSJahVNMhYnDPRCuoFhfjsagVKk8JdPCdG1qnH4HQoZEOCEyHXjmdRp1lIBg12PW+TZwEAkkkh+QVEG7LuthUWvLdIs74i9dGQVjQKgHVdx5ZKoHXAfD6BrhgJhE7n79CWlRsSPcfW9UdBwqIhGx8dFRTuoXQBxydWsQjJwAbRcuDlSxvwc8//OqSyjLM//1kAwL3nn0R0nqKWJe7Dyu4WXtatuNbzgC4vNyRcr62uTjTkhsztMkWbgXwpChXA+rdfwoljwzgeZxEddUsJqGjQFgiMXi/qcC1yQxa2G5DnVDgxB5l9cSxsd8XxoAlSlXFlm4TUBXadtCKFVrTRe5CI7bB5XZvckMI6glqPAkdhXAkAsHpTbeWGSAYwv1mG4m7e0QD75dYdtR0HZwcddNASbpKs0276U9IeKGtYgdfS3auQ2HdG9AkBALp9MyZ3JzH89CVQVRF1KkQKeiwKOu/VmSi8cxOUigMrLmHiXUzaj/ydBalmwomqILbbws2NaTvxYJUt5cI04Gad8l4giEaw8MAAzBgRHcI4r2L7rzM+wB1fcgk+bdBo/VAnGFHBScZBDBNUU8V/gKWSO8k45nZkRRjUijEtwYoR1qDIFx7lqnXNpfoe/u1PY/23fhXbN5/H6vgCvnHoPgDAxn9wzbBCo4OzHUg1K1ytDkn3Lm7ugp5ufF/5tRXx86qD5Ol8w3hbWIJWXbjbo8erJRtmMqgNqCUbC08yh6zlsErhfa/XGuqbtIumvVx8pk1tQw6S5cBRJNECMXJhLtysISE8CwDGmm5QiYjfA8CBA3+NQmniJzvrVKmsrBdqM5iuuaH6bP1qN8Heo1uxZ9sxjGLLNdlvPZQaBTdgGcnKI1wJAdFFhJDgnczWf+tXce7xz+H9Zx7BxUoXvrvnLwEAv/LN32LbWqGwaAey7iDiK4tnRQgUnQYESKTgwIpcH06DWvI18PEJCp4PIhsOrJfdQjkOQB9agHUygdaLOS4fkuWAGA5k0xFd3pcDuWoFnZptKAu3rbCw4tKiAoP3/fCz5eyoIoraLIZqNxEaBceebcGkCh45qHcYhkUU/D1H6wl1NCIzzYLfICU2VusiIr+DaxUAY2Zy6N1e1IMLje2bz+P9Zx7B1+94HqfMMn7nAuutKpr4RhpvCX//ET9C121y/vw2uZhfWhYMUFmnsCNEfLYjfB0JdgRQq+HbaNh/nRPT/xup/g1ep+2YSZn18dAIZIOKor8eAUsR/W7ligSczkAyzfAiOW2gXrsnIUWBzbgCWXET11zNgCpyc80iBI4iNWgW6NC9l0aYUGhFUABoEBTh2289e3OxcV5BKlBcV7dd7aHxRvF79C3fPLkjc3V8ARcrXThllrFJTaAezaIwYeNLRWwC64aELJUQc4MLDVn3PnMNKmwby9mvQJ3w8DSI4H9vWw4AN4wcoZB1X/bnChAmHOohGw4kiwkLns/hbzgU3GC4GSJZDmDToLDoREPaN0O4VsE1jsVOjD/qoVYpaj2SMEO87cmLahV+bSJMs+AaxWIIhvpCBEeVQu8mkH3kq28cug/f3fP/s/fmQXJc953n5+VRWXdV32g0AAJNAAIB3pdISzJlyaYt0ZJHtEYj27Nh2dLIK3pDntHMemYjNmL3nwlPhCccsw6HtHZobPmQZNk6VrQpyaREEhQPkBRvAgQJsHGj76u6zrze/vFeHtUH0A2QMmn2L6KjsrKzMl++zPzl7/x+/0dsUXx79wMA/KzzWWB1a2EjciHLInpwL2YhBCnQMjPlFa3Hsrjg2KD7wY4sglUe9siqgG6lkTunrpOQIN69QHiw8IZbFrEsS8dGEtoR+vfGLQtjA5iby2UzG7Ipm7Ip65K3lGUhCyrFUDw8teI92R7IsvXHS5z5V1u7GNJj9O5Wd0WNnzdiYN9df6veHMd+ywIsSkcybPvHbky4KKLdFVFoLwv2tTvM3CgZfoyY23Jpm4Gfg53fgFe+ew1X/eFLAJz5jeEV57eicOsC/4uQr1cj3THqTZzFcgyFBwqPIn9ext2joEq4o8rMqI7iyq8FfOYf/0Mco4gsike+9Gfsuu/fsf+/XhjU56KyhklupqgBo1HbfVn8FGO7WxbkpiXNoeTNmKlJ3LJgcbfJ7qcvb2yrMaB3S9Lt2k7hVETo4fmJDju+n1R2Bj/OMP6fGuT/18ucs/W87Xf0YDY8zn6wTHO72n7f/7060dRa4l7dT3aq+1hita7VNeRtZ1msRTq0HikdyTDwYzsmGHoz5NBXb+DQV2+4+IZvMYmyJJuyMYnoEH9a0v+iR+9zBr3P/fQf3bdEnUUlNyx/ZvCTBOOKC0OGkvZdN6mKu5Z+sGfm4rqL8797E+VTGo06b1A91ohjDZFkxmsrqABkylJ45Q8ViE3pSIbsrGRBU+5FMPYDL3QIHINO1SQ/qRRUc8im+vICXm8+3s8KFnV9rG3fXeSBp65V0HFagqzCcADVRBUth/f2xbynu76mrsfilRlKZ31mD9gUz4TUt6ubY+DZDtM3OhTPhvG4othIkDVpDiVv6vT/o8rMyqvKYlnOrm6fV2/H+x6/l/e+eDcA548NqLmcN/B3t7COJxWUmQVB8+Ym4Ww3Kvrgk4KsbpBLpx/H3ycpva45X69U/y+cMek73K38O2UTpxas+J4fW+C1307qIMyOim2YHbCX1DUbufM0E/+g+BUyGoa/MSK462NPcO/3bmP4icSy8AomtV+r0T5WoaQZ1ErnAuy6T5AxMN0Qr5jKpLghtSvsGNA4wkgxmi6vfroas5q1n+nFdBXnTGFEc308WUW8ewHLCPFDdR0bizkKlRbtYxWGHw+YutGM57U6pmM7pg7sBjJuSS+ebmMtKCv66OdLFMZsrAb4OlZtNRSFgFcNwJBkz2sKzUGf3d/w8IoWdl1XLecsnnnij6nPn/2XXWcRkQwBlM5Y+DmTINWYlRlf336W9rv4JzKAxBv0iEKMnapF4AjaPUa8Ti2vX37h1he5P5/Awdl5l8W6rpjaV4+xGx7Z2h/jTrYGlCJyK4JmJ2IpTygFWwOKuLh4dvVjrlbQtBF574t38+i13wbg7vwvAPDcqzv5yN7D/EPj+tSWFvdc+wh/cey2eE0l16Z5ZIjI0Wj1J/MlelosXZnRy+pci48nisbQIDZWx8DohIS6RDudMcnsStpMO21b8aq2bYJxNadn5qsEcWOX5u8YDPjmMzfDkHpA2lU1tk6PQeN0GduFuuZvqZwI4/Jxww27SslNN6Q4HsQZiQhdCxJlBdDp08RC2xdZPKmtjuEQTpexGgIR7bIkcc9m8LWbaLhqH/XRgMyiGqPUT6fwoXJSzVl0/Ej8vMRwBX5ep74tgdfrQ6jPf4s67+x5C7PZgkBiRhk2L9wQBufbzg3ZlE3ZlH8eedtaFm+0KKtipXSqkL2E+FWUSr3z6sMxKO3PjR7j/pcP0D9YY7Ge7cKa9JoZ3VSluR2qktyUYgVzFizNDgZg6HWrvxHWQglfDom3lpw/NhBbFN/e/QCfP38LvOskZ5tVzIKaoy29NWbGh3h07kpaLWUtXLvtHACvlbeQWUrGFrVwy/lMbFHIefWbtLsRSRomb/n3u0ZXognfN3YAdqlxuSdKyJ1twpZFdiZxx3KnbbiuBiRuVLs3sQi8AfX2Xc4Jsvy7XfcR7urzu3RcWRGF0RqN06rBLz+u3sXi3QvIJ6tYTcU4pvYlsOuq4cxw/bi5y6obtAcEhptsazXBbEZMaMmc5U7bGL7azu3tHld2wqK9Nbmnc9MS4QWYYRhXcJpesDos3xqyqSyA1i4Xe8rGG/RSSsOk3aNo+iL3o3MJsaw0WnWkHGamytx59eH4e3uHS/9gjZmpMhXNsu0sQGsQ7DmTTlXGNIGKqu/NKWVfLp8/fwt/vPVpdj/8KT689zBsU+tfPDtCMOzzqeHH+ArvAVSxF8DJmozdj3a/jGsm7EUDv+fyxnNwfHe8XG853DV6mLtGDyuFoUWMZzGG27T71a2dHW7AlHp4g4xBR1/LMCOx6wKvKHEqUSZtA4CUa0h9skhxR42FqRKF1Lpo2dZYP80t6vhie5Mw42A1dSdpMSSzYBKmasjDC9STtwZDnLmU+z1nEGYM2lt8nAnVpfpGyTtWWeROqCvQ2uWSO5GhtctFNBTVn5KQ7HzI4i6Dyono4VQXJV28tZZkT2e4nwMrLIsHD1+PP+Bx/8sHYh7U7IzJDGX6B2tY06r3YOKOkIFDZgysGzWH5aYV96jZ6VwUe6Kr8GvZG3ut6svMvMFzr+5UX951kt0Pf4rj7/8Kux/+FFt6VRD3j275O/7jd36T33v4N2Jrg20w1SzhlgXFc8l8RZaF2RFwMhsvu2UJhHGsIopRRMvp9dFyvZXEOO4aPczB8d1Mn6/y8Zt+AsB9L9zOXR97gvvGDmAsaSLk8QKlJbhz9DCHuBVnXu2r3auOZ9cFwZGoxbxNmImUyYU9dGnr4iwvwK6L+L5pWeAeriCqYawYikN1rJerWE2JrzlJ8xOK/zTzQgHD9eL1xTGTxraQ3JRBe4u6vukgeVqcBRWQX7g6IKMVhop9SMpHLTq9ElPHQiJldDnyjlUWrV3d6dPIsqDR/XZxVkllX0xRgOLsvFO7HZE8NLaHD/zc8zw7tZ3Fepbdu1Q25MTBnTGuQyTFMcVu297qUxyzaG/VD/cxgyArNb6EWpVWGp1qqko0pSA6VZ310L9ZrdcDwN/d4iN7lbl/tlnlw3sPdykMgC/MfQIBfOSG53l2RllHU80Si61snIWIJMou1Q54GDl1PLdlYS5YOtPRffwo+xEpj/Q2aTfkvrEDbO9ZgK3wrccUU1H2uhrf+ZEKuEaNtzIb0hgx+OYzN0eGkfr/HCzu0eXT+Sh7Y10wGxJmDCxdah1lQwCaw2G8j2J/A4C8EdJcUKZUBmVJWA2BX+ien8yBBfzjpdjl6PSG9BxWD7wzr90YXxLk1VikKbB0gLKxTeIXQ4pjJvXR5B6QmRA/b2L4Aq+qgYbqFkHe3uwNuRRJWxaRGyIaVpcbsrhrdTdkPZaFebQYc3am3ZAHH1IZhT23nuLoYfWg7bvjJNONIjNTZbJ7dBagDQt7oXLEorlFUjmijrewRyE3OQv+qpZFOjaRtiyWA9esZVlYx3Nx1sMseLBNxSgihQEqYzK47RzPzmzn96/8AQA/XDzA2WaVk1SY36djAZUAmVUPZPmwHbsGUU+FU/NXWBZRHCNa79SS5UgpgFIC87kOdwwf5yDKPakfGiDY4fHxm37Ct4+oc3jP6Ale+rv9OPsX8PJ9LF6pr2VfSOWYQXOLxDMjK0OnmnVcIkoxxvPphhirzHl+3EAKtQ//TBXrhgXaz/WSV+8CmlTITwispoyzIc0tgvyEZGZbjgpQOq2zGRlBbQ8EmW6l0qvh/9O9LoWzgsY2o0tRlF81kZaJW1Fs7LkJNefOvMRsekhTdHed/ksuytqUTdmUfx55x1oWaUnHLOypyA0JqZxYPWaxEdk9NLMsZtGHP+DxyomtMZziiYM74yCn9UB3zGJpBzgLIrZqqsdCFvb8dHT8lt4aL54d4Y9u+Tu+MPeJuFjr0Wu/zZ6/+Rx+j88X5j4BqGxIFLPoOarmq9Vv0tbBTq/UvW8Vs9iYRNkUJ+tx49azPHt+G98+cj23jyoswkPlfj5+0094cX4ES8dHHmvtoeBAT7bFIlB5XY1tEQOvqHx8ZyZy3VTRUuRypC2LQMcwIsvCz2t4vaaLV5QYflLXIE6XoT/AbOtCqwOLePUq0hCxuwHgFQX22QwQsrRD/T6zAG5VklkwYq6SzIJAZgzVCOamC8sgOyWoF1UWBaA9IAkzYNcErSEZx8LNDu9MNyQ3LXVW4NIlOxtNmFIUpSMZ/Fw6lmHGimKjxVigkKshw4nTO/F2qH0++ND1OPMCZz5DY68b36Q/++HnuP/lAywc7sPao86r9znB9G0BA4dM1TMxpca7sMdYNY7yRklmQRDdFjPjQwTDPv/xO7+JAAZ1enTP33yOY//2S+y679/FKdMXz44QNGyGzoVM3qEeqNxpI3Y5CudkF1FQupBpvZJ7KUp95nie/bj9EobbHHrsKn0Mwfe/cTuta1rc/eFD8e8efuI2Xn92O702zNyg+zzGIT8hWdxNKqiduB4XS6NaKZrG/ISIkdHy501qu6E0JjRAEQTfr2C6Cu9U6NuuOWiQnwqpayXRe1TNWX3YJDstaA/IGG280yMV8M2yMRTPhdS3GWQnkjhV5fUQaUKnLJRrI6PxX74b8rZUFperKADmb+6uq2j3yxW1Ful4BSQxi/UEODO/MMNtg2e4/+UDXLVLsYMdz/fjXqH+f+foMbhaLUfbHM/34zyuaKLciqA4ZrGwV3GfNBWvMfkJWNzvk5uxyeteuHTsIk0vkOb1iMrAK7pUeK0AZ/PmJvdc+wgAj85dyaeGH+P3Hv6NrmCm3+PHvSSfP38LANv2LrAzO8vfPPuLlA/ritcUTP7sDWFsGUSSn3Ti4GUUl/DKFnbNj2MYQTpLcksSDe20bW4fPcF0q8hxVFl6rWqRmbQIWxb3fk8FOs19S7hXQe/+GZzHe6kcU3PS7oXF3eCVJK6u7gyeVdZEBAScDnBGAc+MfriMenIui3uSAKdomliDLeZ7MmQm1e+9ksReElgNI1EWwyFe0SC7ZwGeKlHbocZVHw0ojplkFgSBTplmFkQc4BRSxtgmc1cL/KLKhCR1FiZ+UeJVfewFM7YsnDmD0kmTwDHjCs7QNv7lWxZvhETuxlrFWKCUw6W+xWdP9vBQfSVXoNdMkuaRe3LVrvNsL8wzXSxSryplYbVVYZZyQdRnNCZ7zlyRCo0kWAOCbr1l4OGsE5dwt1oZvsJ7MAteVzDzC3Of4Npt5+I6DIA/mhvlZFt1bUZKwqskY8xOmbjt5fORjClSDr4jMFMKwk8B4bTmk6Iq0TZ4bX6AvT3TnMkqLe6OZwkc2Ds6zvGcUiAfHT3MfS/crsaTF7R79X6LEmdO4JUkopPUXoQZI3Y5VkufhpZ2R9Kp0yWBbOiHOYTMDg9O5LHraYtFYDWJA5z2kirK8lH9TVFq06ob+Hk1ltUktIzYGc7MC/xid0GW1QTDExCaZBaT8nK7IWMcjOhzo7IZ4NyUTdmUdck71rJYLqtZGM7C5VkXkFgNANtH5+Ny77S8cmIr26+e58bBMzy5oDorm1sSqwKIP/MTgsX9Ad1sM2+OXLvtnKrM1AVXP1w8EK9/8ewI2/Yu8EdzihbxC71jvOa9xIPlW8jORHswYhPfLRsE1eVuz8aAZwe2Jhei3nJU2nR8NzduVV11h05chRxWbpbQzWUvDivE+DuGj/O410dWs7wv9kk8TQwsnejNfGlz6pVkHPdw+wO8xRxywCdTs+N1dl27JMvIiOuTRYqexM9HeJ8hhjY+o8pN4wKICt0uiAqOhhkILYnbQ+yG2PXVf78R2VQWb5JEPuxyEU1TdZ4OQqWobuyZZoYzjY3VQm/U3Vhr+9WkkusGEooKrs42q/H3oGGzMzsbux6veS+tiukZSZhNbuioOCutLNbTdZqu4Oy0bcbbFeoth+ls8gSGLYv5di52XebbKWIi78KuWLrTdLWu0zBjrNp1mhbRMZRzZcqudRcSMzUumUkwR1cdo7+6+5mcg1jThTG8kMAxMTxd27JBd+StoSykhDBERpFZGZJZ8BBewOytyvfs++6UwioMAnLTEksT0/pZA6MTYAGTtypNXj4hER0XPE9dvAgQNYVIVDqpV01kcBYkjWFdKKQh8yd/tYXxuua41J3Rfk4g2h72XIKWFH2PuB+iY/U9YdOpZHi9UuDM4k4A3Iqk9zR0KkUe/0kCkNO3KDlzZCduReJeo3EScj4tO4scbuNkPYKjKveYnQtpzZhUXllW+ggYTQ97bvUpjpjCotRbhJUZY2bq8Q8+KXSbuWoKO6mRqjI1yUkq6jzKgqFzIX/z7C/G+3+wrAKdL//eF9l1r0Lf2rvnPIudLPWDg4Q2pDCyAKgeWdmh50yvPn48n+wPEzyLLHDk0aso1yXTRTU3/XWJW7Twn+lncEoHTI/20dcM+NH0bfRPtZh499IQPAAAIABJREFUt7qmv/n+R/javXdQPm4gNfNX7nT3wa1lc5kBiO6lFA7M4FOk7keB3RJ4eQO7qas6zwjsVoDZCrtgFKxmSPG8QW68Te0KpWiNtqB68zQzR/qpvhLhWYBzWs1VGqS3/6USImQZZ26ANMFqhPgFIw4LWc0Qc3oRMwXiawLCXT8m51tDWWxQsvMB7Z7LI+ktaHixxqBJbZdg4AWfTtmkU020enhli8pDOZqD3ZpetL0LfgfIzYSAgbMIzUG1rnRarc/NwOx+k9IZddGm7vCoPpchPwU/e5fuc/iO7nP4zu103gW9GqBlfp8gOyMuCekauCgStQKu0fUBS6opLOr1iCoze46q9KiqylTnELkeu+79LCc++mcAfPLEB+jJNnmuOEDleELCHJnVq5EUX0gKU91v1XbVoLHFIKvpDpyFELspWBg1OaczTVZNsOMBl3bVwa3Y/NsPHQTga0dvpnBOgcbI6PKuA6V7NSRuZzHp5LQbsLTdonjWj4PQVlNlV8y2D9qT6vQ52IsuS9vzOPMm+Qnd/7IDpo71M7h/Bvf4gF4nGHhYjy11fKsV0NiSIbST+7N8qo00BF7RIjubgmJ0w67fxrIB8KvNAOembMqmrEvelpbF5VoVoBqUAJra/VhuVcTbVZJ1bmX9WtgtGbFF0h6ONLqJqf3X9nCAoxGRzDmbTgXSvqpblrw4P4Jblty9/3nu/8nt+j9yRTXkGyle0exCuFKWg67CrKjzaPWb5E6rjtIkPaq22bvnPJ888QEA/nbXg3x1qY8nB3bjTVi0e/Xbt35pgcR2tfvd1u5VqcO2nje7YeAV1LryaxoRqxe8gkW7V1AZC/ja0ZsB+PV9P+FbT70fALfn8joy/bwRWydCglcQuGUTWwc9FeGVUJdXklpn4RUEwgtjwijR22agb4np2RI5fe9lVnqcatxlK/5dvK5kI01FZSANK06dmq3gshvw35bK4s2Q1RQFKAWRWbz0zEN7OEDmAr0MpTNGVyVj1xgqyXKUOQiqPi/Oj3QpiEsplb4UifAo2v2S7IyIm8La/UllZjwmnfVY7GTpyaqYzleX+viN0ix/MNjAK1bwS5c37nZv9zE7WvkEunaidEZt0+kPcDT+R9SQFW2blqj02u27dC4NUPUbES9LpyIIbXU/2Q3idRG4jZ9f/UUXtagP9C3Fn3NVldGJIPfWkvT9ZLUMpKng9dxSErPIty7vHGEdykII8efALwNTUsqr9bpe4BvATuAk8Akp5bwQQgD/D/BhoAl8Skr57OUMsDK2DvovLeUTb9xD1PuDHAt7VNyCZ/MX/8EbJFHlYa4jeH1hO7ma+kzjn6SxKN9qUj84yHNF5Ws/ObCbPxhs8PJtX+XqJ+/p2s4duXSU9ssR5ymVOfnLmfdRnZYsXPPTARK6mGRn1TgWnh6M1+16r6K8WOxk4S/+WYbVJeuxLL4C/AnwV6l1/wX4kZTyvwkh/ov+/p+BDwF79N+7gS/pzzdc0tmQS5Harij7Ac6C7PoeSek0LJEjP9UNAhtWEuVhLDYJK/mY5yOSuV9qIc/lsOcNMic1ytWQZOoO9ZDkxjLUf0a9bqoP5VjYKwl6PYYe0n0Z10HPK9D4cI3Co2W89ypbtOf/KzI5lKMxmseZUfnBKKMRZi38UmJsWkte/P/WNhVtL4wpfpSIISxi+Yp4PcbfJxE9alnOZ7AXlRVRO+DFZdxeSfV6zN4Qkp1S5+aWDcJsSGhD5bg6vjdh4RUrXP3kPSpL8oPPAHDDLWOcXOyltaMa92IYOirvF22sukeYMfU4VXDQmlyMeUaBuK/GmUvequM/71N5yaD8mkl+MnGPpm62MHVQtXA+So2aOL8yiTzbizWv5sAfKGM2OsiMhXB9gkIKUNgLCAo2pi7zjjlyPZ+FvSqICQpk12rA/DUh7T5LnwO0BiyslkVrIHmh2XW1/yBvMfmBJLja94Sa5+m/V+X1hg/+lkZ8XNFU131xp4XhKyTzdp+ah+aQQf2KkNIJgVcQBDnNddvrsHW82MUMJ20TObt+l/6iykJK+YgQYuey1b8CvF8v/yXwMEpZ/ArwV1LxCxwSQlSFEMNSynViba9fLlVJLJdOj0qJmm0F1e/rtLyzEMUrZBx7SMcsRMdbdTkS+3Ae70ATb87BS5VQmHPqRmiNupjnNJrToDqOOWfT6k+IgqMemMaI5GMa+OX+/tvJ9dRTnZKJGG1/xQWNFEmkWFb8ZllGovS62YXC7fcAJ7MYOT/GowBl+ooeNy7hTgquzDjr0e6Vseux6wef4cQvfRlQcH1PTozyrrlkTFFmxKqr5ejqGqnUXlI8BV5JEJQDQsfE0C5RfswmyIBfTOIiXgGKp1XDGCQxqNagpPHCIKIU8tkP3w/Ag39zS1w/IbwAs9E9Z5brJ/UVqcyJ6SYuR2tAEmRU2XbhvG7+26tS9VZLYqRqLuymZGGvqn8oHFPz2BwOcfUYI0g8wwdzUVvYfhBnZKyWxK2IGIcTVLl3dsqIl4UOphQmQ+i4GK4XZ0BEB0SwfsvqUp+4oZQCmACG9PIIcCa13Vm9blM2ZVPe5nLZAU4ppRRCbDhYIIT4LPBZgKy18fD+5bohkURuR0e//YOVvV8xAbGbCkBKR1kIou2p5Xp31aN3oKnckNTqIAtBr0ZjmrMRI+ptYU7mk/Vjar+Bo2oXQiBTS0xtsyPxgE6/s8JaWM0NCbMWRtun069MXqvWPc7YDdHfl64MVqBwmx2hoPA6Fw60qcpMO66jSGc9brhlLO5Q/eOtTzPVKTHZO5q4IXo75Yawwg0x6K6EtJcMQkdiLyXrmqMelZdswmVGVH2HIHR0BaY2Au2GwLuhjgF8fUxlSPoLTuyGABdxQ/Q/PJ9Ob4DwdWZLByM7/QGNrdE6aGwFqyWWuSHKovRzJs1hDfFX9DE8HaHSmxo+BJWcPq4bWwZRJiS0knk2PGUBCymQgtgNaQwZVJzMSjfEXP/zc6nKYjJyL4QQw8CUXn8O2J7abptet0KklH8G/BlAJbvln58WbQ0Jr2zB5BsX4DTn7FgxXEiCqg/nbFrzOXKgiHKAHhQW5VPc8oaN6WLiliXmgtX1fSN4FO6Ix8nFXp6cUH0kU50Sf7vrQX6O0Q2Nw6olN7ZXClcsmzUTb42K86C8Mhvg1hy2bJtj5iUVVOynuWKbdY2rnqrK1O5IsMZLLHaPilJnSJYV/NUt/LxyIeo6RpOZXzuuENELxFQCLdmFz2E137geonXRF+qYxT+msiF/CMymApy9UsrfF0LcBfxvqGzIu4E/llLeusZuYykbvfLdxp2YVynHUtQayGYzpisEaN15XRedYUSIHNMT5rLI+cV4n2d/6yrKp4KY3hBWx6GISrfTlIQAzqvnIavfLBHtYdZh+me3Mv0+L25xjwBpe496XW3jzSGb/KTXhTWRphfMT3rxculUO6YX7H1cYV8EfSWMpTZhKRt/giJMDvpKXPGlMR546lq1L43+nKZHBEWRmJlXN1BEj7jtH1V7e6dsdvVd2DX1tpm+0aF4JsK/XEkjmJaoViUt1SOLq1ZmtnZUcHSMotOr5vWhv/gyo9/6HUChigMraBL93S3CWYfhH4suTpQIzSrdv1G7wqbnWLdZ4RUt6sMmudmQwrlWEpgEFvdXMTxJ8ZS6P47/mxKFc4J2v6Q8pqgPQSnH7IzgQ//mCR7+Ew0IPJ+A0bglE6l1Q3YuUFgYJTMuw85NebQGbaSRtKjH5+FJ8uNtvLKyJuyai1nT5xDpmxAm/qtefqCX0tlUvKTd/fxaLR+vaClrQ6gyb1Al4c1+k9oeyJ/TMaUByakv/xGdk28QfaEQ4uuoYGa/EOIs8H8B/w34OyHEp4FTwCf05t9DKYrjqNTpb61nEG+WRBSHpTPqNDu9Ns6cF39eitS36TeD7lL1BhU2RnRjRJ9rkfqk16+1vB65/+UD3Hnri+rLrQk/SbqrNdhXp3mqgNUS8bpOuQ+ntrKxLGIzX849CqrJKw2cG495jWKh1SQNURctj37rdxj71T8F4O7jv8BUs8TvX/kDvsAnyOXUQ72/b5ptexf4p8Wb2f6jlQC6aek51ulSHtGxeo6tJOgBKJ3stiQ+9sFDfPvI9aoI7q9u18RE8DHNTXLfd26noH2D0BaYrqJDrLzeRApdVBX1XbT8eFkdy0MK0bUuEqPtYzYvfD8uHa9SPGXgF2BhVN3PWw8udqNeRfNSd5X/ahB3nWaAmWsqeL0etWLKEtpAgdx6siG/tsa/PrjKthL43XUffVM2ZVPeNvKOreA02ytN5fVA/EMC8HvB/XfCC5IAXYwgKJIIQi36jJYjEiOAO69O+DSsaZsZysl3/RkRMkekahdCzlpuQUTt4mkioGi79Lrlv+va1g1i9yRBejK4+3g3VeJXxt/Dlt4aE3PqHF48O8KLjKwb+eJC5EDSNldtLY/Gdd/YAe7e/zygAszFnHIHDo7v5q7Rw9z/6O2YrkYBywsM701orVqjBd2ZMbDrEhGKFZgY65UwI3EmrLgitL0lWOEWXUjescriUiViMEuLcknMZa3CPz050+iJuUnSEuF6tpuZrr4A3xEr3JCoZHg1/tE3U6aaKhMWQfTdffwXuHvb8zyavxJQyuLabed4rrHzTR9Lp21zcHw39ZaD2y/50LCqLhtvV1Zsa3iS0BYxHeJPU1qDl1Z16vaGZCdMDP2eTAP9rkfescoisiDSAa9LtSpUsDPEaoWxwogYw5ZbEBFjmNkJY5aw/EQQr18ezJeOiXA9pKMvbF2tixjPQCmLKGZRPTDLjYOq1OWhsT3IUwWyLcGuO1TgdIYCVkcSOKLLushN696GsomlU5RdjGarBDi9soWfUjpWx1gTjyJKiUbLoIKXEa7nV8bfw93Hf4Fv736Aa5789fh391z7CCfbfRyetPCKqRThKgHO5fD9QDfobqv7fxGcv63f5nfvfz6mFnj+6f0xt+odw8e5b+wA7ohEhGpusrMhhidx5kO1n2ho6WLf5cbbausA00inPkNEa2X8ojnqATZBTlI4q1G1cnY3rH80BEMgpGq9Txc1ZOYMWjs8hJsCQd5Ad9k7VllcqhsSWRYRDV1CptxtWVyMMcxsB11wfWsFONdyQ8yjFe5vKjckYj17dmo7C4f7ePCwQq/ac+spto8e40yjJ2Y/G+pIOuUIOVvExMXNIXXDDj3jreqGrGZx2DW/C1z3Qm6IVfe6qjQBrONFvqBj41t6a9y97XmuefLXeendX+PehspOfeFpBQ7sDvnY9e4xXAyuH1ayinWNSQcVo3F967FbkdmQxw7vwbimFVsWB8d3U8x16Jwrx2XkQipXZPFKg8rr3ooA52rBzAsFOGNZww3Jj9nkJxW0/5zuZzEPeqsGOKUpVgQ4Adxeh/IrNkIfLrRhZgNx/nessrhUywJYwVe56v6diER5dSUQZM2LbgNrWxZ+TmLnLxw3ibE/C/O8kt+q1+qCI4cYem65rBWbWCuWsdb3rv9lzCQTmEnM3yjrMTFXjl2Pext5PlpQmYovoBjan1tzz92yPBuSjmGsBYUXFWEBmAuWggBMsrcxnF/6Jawg+taGsLtksYw1FcYbLcYGE4Kb4Debsimbsi55x1oWlypRzCKhOVw9ZuHnjFW5PaLYRH4y2TazyJoxi7VEXNGIg5r3v3yA+19WJMwRSzskMQurJbD3RfDOFk4tpFM2MDsyti4i9vN0sZaZIi1ejfE8cIxlMYu137IqvhDEy6BiFvv7VJDjxbMjvHh2hHuufYQvPP0JvqB/d/z9X+Hz52+hfNh+Q2IWaesijlnoIqhffc9TfOdHt5EdbmA8XeabLVU1u3d0nGNHRrpiFoUJFbPoeYU3PmaximWRjlkolvWNxyyKYya1q5KYRWbO2IxZvJmyWsp0tZhFutowLenYRHqbjRZlpcmK0jGL+18+EK+/8+rDPMQe2s0MpLb341hFGplLLVdfX39RFqztyqzYR+qhjpbDWYdte1Xg5kVU1uNkuy+hICDJkuweuZmBFy5clGUuQ+SG7pjFcjfEWlYIFQU0QcH753Sr/rU95zgzXIUXymTndIu7RuTu9LzBMYs1xKyZ2A3ILAnaA3rd8xuLWfh5sOesuHfHcAViA7fdW0NZSECGiJa+88IQPD9G8wZitG+/v4h9bg48HZzS6N3C9brQu6PoPoChg4Nu0UGEFm7RoPRyUhoOkDnf/V36wQrEbuH5ZM9kKJ+QMbJWp5PBmQdLR7Bbuo27fHQl2ciFJtta0C3I+pgRPoapQVejTzwfc3aJwYfL/Ph1hRDuDwfc3ziAaJkMPpUgcT3QvBajZWAScZiCrTMC9jJMocXdyrLZ+sBlEqmuAXprTSbzG6nU4R8P8U+L6u1tAs81dnJ40sId8uMYRfmwze6Rmzn+G1/iw3/6scsa2nKwXaPWXcHZemibClVMlsm4UKsqO++7r6kS7+HnfOyGPj99ey2OmlgTlzlnqwHpLpPBp6rkZjosbcvE0AXm5MaOa9crlE/KlIKQnL9AUHq5rKs35M2WSnaLvL3nVwmmZ9UKGRK+93rsqSUF6Q/IuQWklMhWi/lf626i6jlaJ3BMQicJnGVfn1Y9HVkHqYFd6CSvwRP/4ep4OT8uYyzOqAu196hL4BgsbTMpnVWz2ykb9D49fUHwG7mk+gxe+/3dcVep1LgV0fdoXdRQVn0uw+K+ALO3w9avKwtgfq9F+WTA+HsF1VcEC1ep67TtwZDJmy22PuZ2gduA6jqNukuBLnAcd0CNIXtOjXMF+M2UOvFX//0VMRLXXaOH47qDu0YP863HVJuP6HHJvZQjvKUWUwoObF2g3nLI/rAUo3C3q0YMhdfYGcR4FKJjYNUMhp8IVnUb0uui75kz83zvke8AcNqv89+nfo4RZ4G/PnYrnbZOxba1OnYNyq+q5dq7fDLTJvaBGr1/WYiRsGtXmDS2aQunoo6349sGdsMnyBiK27SQqHfDCwltA0vD05lNndmptTl6TxU0i/pvvv8Rvnb0Zj5z4DH+4huKKuEDH32GB++9CbOVUDtG+JztPW22ftdm5lqNGTroUzpuYXgJtorVgr7D+lp2grhz+MSv9uIXQqyGQfWWqJcTKk6bsWe24/d57Nyh3Ly5fxxh6CfNFa7JU89/kdrSuXXVfG8GODdlUzZlXfLWcEM25W0lTtajK7f4U5LTvgrS7rCKjOgilWJ2ZdDEx4oZyMmECTaGvfIFKpelPoOMsSpTV2gbhBkB2jiUVrKNzIRgJvt2HE/vS+17ILNEkJEIXxA6GmQ4wtVwfEIrc9EUbETWbKTqbcKMJLRXJ1EOMxLDSW1rg7QE0hCQDoqKN7CRbFMuTcx2V2wplsj9MAHRStH3tQz8VhozQn3aNQOQ+hOivS4P5MXHXcMHXWv7lb8nNuuB2AW5b+xAjO5949azPM9+Om0b0Tbi7Tptm1WwgwCFmemVdNxkycArrQxGrjbO9Pf/PvVzAIw4C/znvmMxmM4HdrwGwH2P3sQtt7zGM6d2QARx7BoYLlw9NM5Z9nSPac4gyMi4PsTwugOeEc0fKGVhuHJV+kBr1opBZn5w/iqWpovcl78mBsIBBYpjeOqY8e+a0Difx/Alhs5QOFNWjKbeHlDHyo8bcTA3HdA0XEG2IWiN+EzPqrL50DWZdgKshsAtmZw6rwr0Sh4IX4KQXW7IRkiGNpUFCXcIJIhZQFzpGH2uBeG/mgTZJNeQjlWEuRAr58OIj9TKoTlkIEZaWECrV1Mm1qDVp/k6SslxW70mXlmnDTsrA2NBqjDKSmEIX6jBqvv3keWgJIpbbO9ZYF43Vj17fhtuv+T20RO8Nq9C83cMH2e8XeHIo1fF/B7tXtEFwR8B0ERv1zBjrMhoLF+X/j6SKnmNsiSfR4HpRPLMqR30VevMF9U8FgYbeNNlBp0lzgLtSlSOr9GmihIxqM4rtO04gLlWzCLUFkUUswAISmEcswDYsq2b9/CJ2V0sF68gsZoCa2uT0Mpj6VuksUel5d2kF7BrWZrd92CkUCIKgclx1SroDl4iY90FZFNZaHHmuxUFEHN8XopEloU8l4uVRTDnYLSMeF1kWbhbPWhZmHN26u0r8UoiJpiJPr2SwK6Jn4plcd/YAe4aPcz0+SpsVQoB4NtHrofhNtOtInt7VAAtCoSW65LGFl1HkeqOdOZEHICOoPAMd2Ua+kKWxV8fUwHWyPX4PAqi77bnPx5v49cy7LxijskR9dDcMDTOc4fLPHh6L4W8gRvzwyiWer+YelN7YZcbstyygISYOO2GmEtGbFlMTlf4zesO8ZVnfiZ21F47OxRbXBGiVYTotWtglgUrH69XlpCqDDU8DZuXcjOWp0rtLU3cucSeM+ctwIJKgD1lx+N6I+QdG+B05rth/5crClCFShuxJrp+uyi6FAWA2duJU5gA9ryhqALOa9zNXg97SWIvSRojAntp5YVebd0bKfaSQIxnEePqBrxv7AAfv+knzIz1cnB8NwfHd3P76AnEeJbj4wM8e34bz57fxt6eabb3LOAWBdk5SXZOxj0gkRgdESNxp2Hx1iudtk2nbVNvO9w6eIqpTonbnv84h67/Joeu/ybWkuAjNz/HoLOENW1jTdu8PDmMXRd88fqvYniSzIL6i8SqC8S5LOLcWg7U+sSZM5SLsWTzlafeA66B1VTKoVhuYTXBbqSQyRoCqyE59sL2GJ3bzys3pLNNKdFge5tge3utQ5JZBPOlIkNXzDE5XmVyvIrVMDA8QWZK2QFWQ6i/1uXfN+9YZbEpm7IpG5O3rRtyuejekSURkQx1qoJOT7e14dRUGVx+OvL/1j9d7RubcC5HNsVmFjgK9Tucc8hqXhGAykM55jR/a2FCR9Idm+J4wOSIRc/RkPl96jz7XvZo92fwShbOBmIWXkmNPbNGC3kkI3ee5sy89ntPqFjAfS/cTva6GvVDKj5xqNxP4ZygVrVwtQVy6MRVAPTXJc6CujZ2w6CkiSHGf94nr5HLm6MeZs1cFTPzQjGLuI4CFcyM5F3PfA6AVz/9Jd71P9Wyo+HiOsfK3PTRo3z67z9HP5L8jJozu2kw968auDWH4qtqXOksyGoZkbl9FoPP6TlPvahvet+rTDRUYOHUqQGEa5AdarD/GgUL8NTze7j17qNMNMpsKXTXzJ+q9RD+ZADvBmWGiaNFhu+3AIl8SdXMiECysDuDnxcMPp3qPv7ZeTpLWcVipmMUfiHE2tEgDAwMM8Rt6Tnf61E8n8MrGth1XV9iiw09P29bZXG5FAD5cXW1m8OKYKjTo+IMy8UtC5xa97FEx4upANaS4uN5mkOS9o3NrqKs7LN53IokyErsw0qRBI5ySbyeMA5ELlwlyc0KctPgltQn6IenowquVisTtpeSdUbbJ9SdtMtpA5aTC0Uy8Q87CHThkNzZRoxnuetjT/CdH91GsEMpso/f9BO+/43byUxacYu7HG4TtizcooXdjAh+RFyUVXnJiNOZlZdsvAL0HGsnpd/6vBOGsjD+vlq8Jcp6+LUMv/heVe/5rv/5OV799Je47fmPU3tcIXaHjuSVb+7jpo8f5dTze+P0aWOrQe7RIk6GmNTYbvh4BSsOZsbVmqjUZf9LboyJke5QfvEH++K2b7EtwFwyaPtFjjyxD4Di++Y58u19WE3JXNz9C1ZD0h4Q9LYDxFEV4MnOwvj7QwqnLBp7lDtSOJZh+IkWoWV0QSvIR3oo+ZD9pSlmjvTrfRqErxdx5gWdHomtpy5/ysGZb5FZ6C7Kil6665G3rbJ4I2WtbMjSNl1VdwnZkEj8loU1spKv1d3qkRtTT8/CDW4c7KxdoS5J4SzUdqqAo1cScQ9G7QoL901kUU9L2LIwhtvcN6b6TT5+008AeHF+hNY1LcKWxd7RhGxuvp3Df6afhVF1Ln5R8WeAYjWPAp7LeT3WLTq96GPFWY+dV3RnHqIYxp6FTwGwe2iGiVM7mG/n8fKChs7UNLaFlMYMxSAWBQGfubRheYWEPFu4gty+BVqvVeP/18+VWY6E5+cVbUB7Txt/LENWFy83hyXCNWhc4YOG7Wtc4cMTqx+7viMkC5jblZVqvFQEBG5Fqt6PWBdcfszibakssvMB7Z6NQYItF2cxmbzmsKB8QuJnuxUHQOlsECuLjWRG1LaC/GQmhvzPLAqcRYmzCEvYOLpdwsv5GOftLrb2wnnlevS/GOAWDTLadGwMmzEt3psh0bgBsjM27X4LYylHFp0FAayTWe7+8CHu/d5tHM8p10SMZzE7MDgVck5X0pdfM2M28/xk2EU6dCkSlXArCyXDfDHH5EgVa1rNr1MX1B4fZM/Cpzj2/q8A8MkTH2C2Ljn5+HZyeRGXeJfGDHIzIW7VID9+eePKTQuspi7jrhssUaFygriGoXzUxPAkVisJcrYGBHYTxGyG0BYxMbLKgAjqO0zy5zV/6VYJrGzwyyxK/LzBwtODcZq+eFYSmuCVBXYtqamIsEMvRzYDnJuyKZuyLnlbWhaXa1WAKoSCxO2IApzLJbIqIHFDLhavAFjaLnB14U+UPm3MObiaTCe8ssVSVscy9PfGnEPlqK690PUWrT5DkQCnApftfoE/bscXLx27iAKZ0F0aHNEaRk1IaRq7tDRGBO3B5HfZ4QbN8QIyG/Ke0RMAPNZSlZDmviU+qgmbXxweYb6dwzvah6XpFju9SckzGCvYwvLT1pqNZFEMI91YVnuX3jYTgmtQGGxww9A4L1eH1fGOlQkdye6hGT554gMA/O2uB9k/tA/7wCLWyXLMk9EalIBBe0uAV9LHej2JVxhed1GWmjOB4avzScdROlVJp1dvY0oKuxZZ8qoxw3unqmo6AichGepUlZtgbW0QHi7EVIT1HSrd6edD2pok289LvLxGdstaWPq6tftVlacsJnPYbGUILfDKEruQuCGZBfHOLfcunlfBHz9nIjqqfNpcJTuwlkRuqidnAAAgAElEQVSKoXxC4tQCajusODMCiie095VQZR10cDDd0Xkx8Q40yRzOk5+S8JpSCoEjWNynxlh5PB8vb/lultmrBQYw8JzyPZd2ZOl5uMP8Hoee13zqw0qJDDzXZPZAjsAxurIdF5PgApB3abnrY0/EVIm50zZMlSktQWPE4KW/2w9AwYGHn7gN9yqVKUlLXzNgxwPq2qQftqmbLYqn1dzWd+gHY9iMCYDWI5npiP/UxHDBmy7z3OFy7N7c9NGjvPLNfUyc2sFsXR1r/9A+jtzzRfZ/8R7yMz7lMwlD15lflmQmLCrH13f8mWtNtv545Xi9Kzp87saDAPzFN36R8FAPwXDI1R95FYCX/2Ef//rXHiZvdnhm8QoAjkwPsaVc47VXtpGdD5m4XZ1D8bRB+ZSGRjD0yyaUzO9Tyn7w6cQdGbnzNKce3UHmdCbuUDU8aPeHbL9unIwRcPKQAkLq+dlJ/LG+7myIJbrAiy4mb1tlUd+agLnkJu0VLermRVKEUYq0tkuQnoZOj6aon7BpDli4ZUGnrK6EWxYUXl3f+IzXc7hViXegO7hpv57D6wmp/0wT5pTymb1aKE5VYGG3OlZtVOCWHLySYD5lLSzsztEYERTHeVPk3u/dBkP6gdCMXHeOHuabz9yMs1+VW/dkW7z+7HZ69ydUiVF154+mb6NdVeeVLvc2XVjU2DKhExKUA/pe2pgXbB9I0o5XD40z6Czx4Om9fPH6rwLw6b//HDd9/Cjz7TwnH9+uf7PI/i/ew5F7vsh7P/871PrVQ7e0E3KnBV5BMq/xgnKPJIA6pht2pU8NL6T/xVTaMtUjImYzfPm7dwLgbQl0Y5nk5X9Q2RDjtnn+/uvvx2xBoB9qryCZmOqBfQGhJcgs6B6bHSGL14Wq+lIXZJlnsmx9ZGXM4tz9OyAP+Q9OJb0hY+oAZ5/bijQkQhvBjXu3MLDUxOwk6GLSEhdEN1subw08C3tAvvva30U+f0StkBJz9y4aVw1QeOqkWrVUhzAkdD3Edfvi30rHZOpGFWsefijREGJhCem6iEwGqblKZaq82L8haSpKA8h6mr+zMFbD78nFrNlqOwt7fB6ZsZEZdRWMepOwmMdY0HgWDWUZtG8aTf3uwg9F4BgEGYHpSnJTUZ+CQZgxsBor32ShbWAvtFdwisqM1XUuZl0xggvXj0FpRXNZKsLWimhGac/mzVd0jy01di+fvIVCW+AshvE601PoUbmpDm5FuzzN1S29OE1ac2P0Kml3u5bp9cILMGeXWLpuS3zsZExGjFqVHqevx2U1VW1FaAse/eM/5Y7f+awar8alSFNZWg2fIJe4ImnqABn3hKj7Iczqc5xeonZtf4x6FtUuZJaCFV2u6XH6OQOrFeKWTD72fz7Aff/7B/Q2aj9B1oyXQ9sgO9MmtAyspU583Zs7q6oTNiVmO0QaAmkKRNDdNObMtlfgWRw6/KfU6uvDs3hrWBbCwDg7RfrWCkt5Cq9M07h1JwD5H70c/y8oZ3DLSdxgy2PzyIzF+M+pyHzpvE/pyQvb6J724b2SSbPfoHLCwyuZdHSsYPxnlJ8y8IyDV0jmcnBcPVTCTTR9ejkef8ag3asegKghLDcbkp1TZzm/x6YwoW6G6ZsE1aPqd+P/SRM//7iKfN8C4sdVWlskfS/oupAhxUw19OiyWmoUpL25TIFEN9ZqZMVqAlaub1eTB7fTY+DMq3EuXqnOo/J6yMwNksoxk7b21bM6gznx7hz/9kPKJP/aUeXOOE8VKZwP6VTUPEao0gNPJ+ewFvJ2ev3yh69dUb0eGd1fFimFRtWIsx5WXVA+E1Lrt7njdz7LwT/9MwBGf/jbVB938POCpe3KEtr2gzrWxfhb9XwZS0lRThTHUOcm6QwKMktgtpI3uPAlVjuIW5FD28au+SyNWHz/37+f1rB6FGevV/v6nV98gK//ibJWWkOCXV9vqE5lP4izLIYX0u61FQmyltKZAGlIvKyFnUKNN70Qc6amYhQpA2E5etiFZDMbsimbsinrkreGZbFBSVsVlypeSb09m/3aV9y6+lQ0thhkdPOWW1p/MMgtmbT6DNr9Mm7JbvcL+l42VWVjvySzpDtMawK31L3/1hZJsJjD3CLJ7lmkOZEU+TS3XF5dwIXEK5gxJV+7V3U8tnsNsnPQ6dMWBgb5cfX/qGtzsU99RrByAL++TxVx/eXM+zBcU2cgEki5jUrtim5XRbWZSzp6auymQWOrERdcgcp6+DmDpZ1QPhUw+sPfBmDs5/+c/a/eo85zy+VRNrZ6TKx2co+4ZcGSsChMqv02Bk0KU2o5iNDfswZm3sTPCYwgwXTN7qrxm3sP8Zev3Ya3Te1/LX4Pr2ThZ0UXhIHh20hDEFrgFjMxQHBuJiCz+m7WLW9LZQFJK/Z6o/zLJVISmSWJsxSwpJVFpBhKJyDQ/mB2Pgpmqd9E8QpQLojM2Ihmd6349E2C7AxkZ0S8z3a/YFq3NJROwIIOvQw8E7Kwx8ArS8rfV7yajQOSyk8c/A8uIJ+s0rhCYzo8LJm6yaCzpURmrqXHoKPnGQu3N0GwSv+/s0UFwJyz2ma3LWVS2923QO3XajROqz4He0nEmYbFPSGVY1E6E/ITksXdxOnBiKz3a/feQeGcWv7WU+/Hz0N1WuL8yiSNF1QJtndDHbfmsLi/SulkN2iun7e7ULej70atGbsWkIDIOKku3rl/1SD3aDEuuFKish650xq9/HHlcux/9R6O/O4XGf3hb5M5qdZ5vXnMlkdomxheQJBLXWc/pDWcJX9ezWlETiXaHrM3hXHmIjNrklmEuesC5nJKQWRPWMxfKzCbNv6A/l1DIAuSzFmJnzUp/7KKWE/Ml/jrP/9FDKCkiwBFIGleqfy97FQTo6bGMHmLgTMnsFokqVvLoD7qk5k38QsSSyvm+dBi12yZIG/FWByBYxJOr18FvOWVRe5sY93bls5fGuBHp5S8saK3e3E8oLbDpDmiejTS/1uP2LUUzP4qv1NvA3UzNLYoRZGW/LiBV4Tm6TKVVHiiOWCQObAID745sHbtYxXsFMyEV5SxwmhuiWoMBIu7FVy+V+oed/m4gb+snmLhmhB5theh29INFECM4fVf0hhlRhJkJH5R/UW1E27NwclAa0DiRgA8WwIyExZeQdLptePAJ6i4xdjP/zm77v1svC60TaRlrEA5S+NXQBKQFW0PWfDJaoXTGQjwCwLDNchMWHqfEmfKxGpDO0ze79aUQ3tXh07VZvK1wa79B1lYHIyOJSlMrJwHZ05QH/VxZsy4rN6ZMbEXTMymwGyJ+PrkJwShZRCaBkKfi1ylWe5C8tZVFsvPQwgw9EkadDOWC4EUxNwN6vdG12/W2r+rg27mcrJgobbJjwv8bOo3ET9EFNQUQi1Hx9aEMc4cLF0ZYnQS3EWjI+I3cWsoJDute04qyRs6QkUSviatNSVuCSo7lUXgnumlca6EPV9PuCqiTy/Ank8sHCmEKrwSomt9lywLcJbGVGEQgDfg41TaBEdKyHyAZ+q3+YypYNuGfIQmUY6Qu6VhxI1Zbo/E7VM3sTVv8dkP3w/A18duZualQa48lQShI+vI9sOu7E1EAAQJCjco4qMY4cpTF6j4qo0UEORkXMLtlQwqx2H+ADhzXhzMbG8JyJx02HXvZznxURX0/ND/++sIL4gzMMszNMWlThJwTc1b/piDrU/FLxj4PT7mokn5pLruc1dD9ZjEasuukn6rJWlvMcnN+hRPKiXSvLGFO6eL9bTGMusG+dM61+8HiED9w5mXuLMmdl3EoD5mSyBsMIKoMVKtL50JsGbrWMsCnMYageXVZDPAuSmbsinrkrdEnUVZ9Mp3Gz+PtUvl+GWjCa12zBMCENx+TRePCLp2IuIFEU4GWUveVLO/kjBz9RxVdrxXzmDX3PgTFO8H0MUFAmCcnEA4SttLfUzhZJj48I4VzWbOvOIZiSj1IrGWvK5S7DSvhzPTiUuwM9MtWtuU7V589qw6ZrWEaLSQhVz8Cbp+pFritU/1ruAhEcu6W+W5HLlJgdVWna0AI98zsesBXtFcs7nISBUmRbKczwM0EnbqfA03JHd6cdV0rD9QxmyoaxYU1ByM3Z3nYx88BChErk7b5u79z8f8JKAoBQ+O76b10AC9R1Pt96my7Hh+l7WVQ3cVqTPbicvdQcUoAKwlNa7vf+9r7PrBZ/jItS9w8Ku3ELxPdfr9L3ue4ssvvQfj9RzZGXXt81MhdjNU9SZz/uXRF6Yqj4UXYLQTq1XtU/Lqp6sUzhh0+hKraeDZZjf4bjSEVbxlIeH0nXmueO9pFjvKEpscrzL9n/+E5tSZt1GdxT+DiM7KEPN6cCqgm5RoLVmuKCKJ8CaMtt81+Wkcii6JHrz0A+j5lE4Jmm2lQKLqTyDGy1gu5lx0XpEiWF1RrIYfsZxDNFIc6R4OuDDOp9lITPhIaRTOFeJO1rv3P8/B8d18+8j1yGyIuaBm5zs/UmxgOYgVQVQoFhECpWV5P0ekTEw3JMhZXXUUUTAzGteuH3yGE7/0ZT554gN4hcTs/vJL7+FDew9z8OlbyE+r/bX6DZgBUxdaRdicoZlgdUbLG5FYUSyT3ISB3ZDYdXCrq25yUfELISee2o4RoY4P+qkW9ovLO1ZZREpBpC7OehQFrGxjX02i0vPlCiN6uMKs1bXNmlWetgWu1521sC2aQ7JLSUTSGpIx05k5Z4Nugw9z3XdFVDG6XJY/fOn1kaWRBqxZa/vlEsUg0svtfsnd+5+P19dbDrePnuCxw3sINe1AdlgHuCfL8bEuhGiVtjSW/395RWkUzIxiEx+59gU+eeID/O2uB7naS6qEP7RXNcu1eyX2UlIZaqYqMiPU78hyCC3jkiAkpGkigpVxhNaWEMMzkObaqdSLieEJgu1tvI4636HhBaY3oM/+xSqLi2FeXKpl0RwW9BwNCXQDToSBsdwFMTrBqpZF9KAt/9+ab+U1LIvqMXAnE9epOSTJPJvXOB26/2GHhvdDNa4B2HW3ywVxizproKtM+w63V7UsVoO6uxAS93IRrr+iSrM8Bvf/lWpECxxw+yXPP70f45pWzGFkPF3GK0ky7upEyF3jtFcSBKUti5X/CwhJqkQPfvUWvAJc7e3j5d/7Irt+8BkA/unwzYQZqJwmhuXzcgb1YZOl0ZCd//DGWRarKQqA6lGFmWG3JNM3XFqdSu910/jfGsDQhwgZwNhAAvFfrLK4WBv7ZVkWQ8aKdvblloFfUi3ky5VC1EJudIIkZtH24/Ur+lrXsCxWa4FvA65uVAOFJh5JFLMojOsW+KKxqmXhFa2LxiyiT69orXBDrG7gqliCgrMiZtEYEXGzWjHX4UPDxzk4vpsPDSdtoN9s3Uyup0WtWqAy1s3jEUHgdU3XGjGL0DZwZrv7YqI6isiyCN63GLsekUsCxGRGD87dAlLTGTQkuZkQv6CtnTfIsgiz9qquSGtQkJuStPsMvMGVFArrldpuYjckzEjkBvTZZjZkUzZlU9Yl/2ItizdTVgPJ+WmLW5Ursh8AXk/YZVHIczmVb9+avK1MV8bVqZF18WbzkawmblnyMQ2ec3B8N+PtCndo66LeUtbH3tFxru05x3dfuw24vLLsi0mU9fjQ3sP80+GbY4vij7c+rYKeRRmTPYEKbmanfzrz1ulVbOlBFpyzUWHXxooQJ0/1YqRiFsCGLItNZXEJshp72XJZD2NYepu1mMTWktykoEWCGh5JdtzEba1cn+ZVvZAYbrgiFrB8rFGw82IxhK7fp+IV0XJ2RsRgwHdppXHf2AGKuUTZHTsywpnhqv5d0rIdpU2XxyHWCrgaXriiClP43esiRQGQKrRMgp71fTHWppcX0F2p/oaI8FafQ2dOZUPMjtCYnBsXo+hhnsliazeks5kNSaR43o2RtABs/VaIaiwuRQZe8Jm+zorBcyJkLcMNu2DsOv3OBXk9rKUkfmEtdjbc49K+USFxAeRXQeICFdTM1CRmRzJ7dQS17+mH2upSAPkJ9YDOHshRHNfcGql06Wq8pF5xOeycsWazUlCwYzi4oKBiBR/6N09w33dUgPP+R9WnOyLpnCsTRY/cEQkvlBl+zo8VQ5gRGK5coSjm9ln0v9R9bcOMYOZak/4XgxXZkNawrvzUdRbG6zkOPn0L7V5J5bSOUaBK3q+uq6Dnrf+H4iXJLoYKv2M2ZG6fQ6iDTdVjPoYv8QoGS9uVgu496jG3z+6qszD0MO2mpHKiTXNQzVzhPJhLK++b3/7X/wTA1//kTrYcUv+f258jOx92BSmtVohXNGhXDaRBfC0bgyaVx6F2pYxrRcDC7Fv/s/DWKcoSH8TsV4zP4RVbEEdPgpSEuvjKHN1B/cAAxUMnEZaF7Kj1wnGQTVWUFS4lTRTBtbtj3ozpm1TB0/CDMypYmLGRugzcaKi3b1jo7rUQ41MIWwfANLu2sG3cPVtp9yePRKbmEzgGZz9oUjhrsPVHKsLnl7OYDa8L5zLMWHg96ga159vxQ2PPt+gMqU4s57Bm5amUEM02Mp+NPwFYXIJKidnbBmMXwnQlhivxigat3uQBKk4EGK7EdENqOzRF4kfm8X/cS2Onuoly59QNveP7upy8LxdH9kXamkg1IEUiMwlRMKgMgH1+EbFKUVbQV4qbr8K8mr/Z6xLG3+hc2r0G+cnkuM0hg+xcSPGcq/AjU8cKLaOL1Ty0ugFrAIJcotDshXYXDkXQq+4LUyuLcz/fR35aAfrkZwKa/RrGz044Sp/6gy8BsPuh3yL/bI6hJy/fvOiCg/RDjM7Koqz563sxfIVsnp/Sgeaau4L7FDR5cihV60EKb7O1NYeXN2JrwvAlL93/P1haOLuu9MpmgHNTNmVT1iVvLTcksnJCvRx2m72xfxWGqW11A9MyCynq4xdSxuhESIkIJVLKpBEsjRqk283VfmWyT62dpZQgJZlFP4bfQ0EqIAJBulXRqrsr0KmElFgaps/oePEYSa1fLtFbOvqUejk3k2LLcgxEKEEqszMOXkZsU6GM2+SXQvVmMZsGwf/f3psHW3LVd56fc3K569uXeq82VZVUklBpsYSEJCOEgDFq1GKEGzcD3RMy3kRDO6anY9oRjSMmPG0bz8S0x3ZM28MyHtCoO0wbm+4G2sI0NMiSGe2AFkollWp/VfX27e65nDN/nJPLve+9qvckIQrzfhE3bt6TeTNPnsw8+ft9f7/f91fQa8KF3Ua4Jh5Cew5uY5208XqAzCVbiTDuGs+8yGaQsUzZl3FxSaXsV2FZIENNcUEhdEZBV5k26j6aVLPJKO6ibhxCd1cKgwxrEZEybsk8w1UzMG5T26/yrKI1KnGbmrAkuwoZh2VBcUVxxXd+CYBX3/UFrjn8iXT8kuQubWMrRKzS5bR7PZR2645Te537QOu0sLHXUJm2oDbY2Trrhb1P3ZZ5BsAQ9m7FvXtpTRZvoIgtMH1vRQyzdJziHzKICfsdymcFzV1vnkmXxxuSgDDf2rpOLpwg6HNwgmxdQtfH0QGcjkDcasyP+DFjGiQ3/ZshBiS15xBKlGcmDMPrmVDwvXlj6jVVGsJdn3RSTgwn1NA0fSl/z5ir1xw2fBjvfP4BCouvHQPbrKREwi1FVLaxHhejAOyRqCjxV+N0snDgJ3eyEEVjl8up2TXnkOfkrD5z+qL7yvN0TnzXoJF5js7q4YXuY1tNYz0+zbwsXl1g4ES2TXvUo9Mn2PFUA+1LXv3vjZvk4IMLa/7by5GZ1zycenfA0Hp2f17yHJ9geD7zHJ9geD4NU5dg7Fnz8I1/r030cgVpcRj1N8ZuP/8vGojHBtn1rbVRVb2aht8MNly3ofREoCayHt/nyuUSZeuNDL1k2lcOOOz+67VjuiXpGVPRDruC8pQn0hDu2oEs4Cpxj5YWVIpRCA3vfN5wet5z1wdfV7c2vNY5zAIM4Dx9awl9m4nhv+xfNNbX5DaoBdJ4ex/FhbDLAyI20k7W686lAHAO+Dv07X33ES9bFietETcewlmqgc34VCurKbt3+++/tYspq3xiFV1wULn8A+/kzAXZvad/8QaADSnzRp9vEgz5BFVJcck8EO0hh+HHz6GqWZj1RuzeJ//pW3ACkLk5QBVMPgQYt2GyPHgkY83a/W1z49R2uVRmY+avcxk4rlg5YG7c8e+FzN7kMfFE541lyrLs3kd+80Ca/5COZV3QnFSUzydMWZrytGDloEq3TUhWxp+CwoqtzVGWKfv38pXgJC674Ri3Lhl9Xm+aKcudXual35i056lwF1ziPoVTy1T9t77jZZ7/66sJK5rSXFbgJ7ysg1jwmfyuTsl1W0OOYbiqRJSPGlfGxBMXLsK6eHWB0eezyQIMu/fDj3w5NU/ixEUtYd8ewzZ/8tQYY5Mr1JpF7rEu4kSO1cc4++ABFt9tzCP/1VJaX8UGiyJi48oNBgSTjzXSzNmXP1lm19gy517cgU64PRoe+ArhKISjUS1zffvH6vT92360zMx55Qqee+SPaJ3/Scs6lT39TYhmEvKaC5HfJOvzu9gC+U1pXuHXTV2QfD1TtxGjZa6id1OsnbWT3z3kN4ENua5MZcfXkpTVSUvQTpKxKNL2JJbAa2lEpCnNmZDc0lzG6Jws95Lf6J6+9a7fjCQkOwC1VwftOAh0OUaLJO/BsFXrcoxuuOk2YKpyJwi9FqS2ttuUeDYnTESOHQO9ps/0khjlf0f22xGmmHFkvhOKvelGPyIyNWWTeIjOMHz8pr/hT7/yXtxWpgW5bY2WmuLJjLgG0e1lUT1xGSoXi5831674zi/x6ru+AMCBL38MGQgK+2qMlYx37szKJO+9+QinW0M8MbcPgGbHmH3twGO4oZHni3ZMSGt5JAFTQkGrKnF6YvB+861f51Pfvg+/Lgml6ZzXEqh9Af/shu9Qlh1+9/F7AegrdvAaiqgscZsJvkJa/X0zsu0N2ZZt2ZZNyaWjWfTaTr0ekdzyulFnWneDNYnHRG0A2HXZbRBUrTejpxthWeIl4GDSp97j5r/teZRmDLN3czILgkmqcwG48wKnad/8SiOUMDycdpOwJCgummrbfk3TGjPbDhyznoMg7vKmQOYBSs8rt14Gm8MW2s8OpyzelQOr1GeqtFyojjaIzhhNoz0RUT7nIJpOei2C0RjRkURFkWkQmrRWiHYNNyYYc8RtQHExXtNndM955H7/4l2Pps1/fe4tAMzMDdBxDTZ16tQYYneMCARe3QZwOZov/PndhBNxCqCCMTv9BcdyZiYZtzZrVGffeRnMlVrMezrilsOBL38MgOMf/CzXPfmPuG//C3zp4TsAuO/uJ/nSw3fgtgTtUVvPJGE4P9BAOVmQVlzQdAYEMoKomGhrmsHj4Zro1P/tKz+P2NUmrhW56mcMjveusZd5bOEgf/it9yFGOvzWz34VgN9/8BcY04GpZZLcL9HWqqtfOpPFj1Gao4buP+gTXdhFc4eHX1dElSxTc6uSxya8VTMheKumLcEzlq4yPJ3eqqC+26infkNT2+XiNiComIcLSNf/qMTJAfuN0/1U964S/NAwjrs3GhNFnO5n9Qpwx1v4ew2+EK6U0Bg1uLbH3FZhRRgeUcBtmICivFwopX09SYsWFUJqc1Umdi/yizc8wYNPvd30K5A4NUnp6mVqmD5X9q+gnhhC+4qo6NAZT7hOBf4KRBVBNLQ5XTxfTGjNOovHXPfkP+KFW/+MK77zS6na/tj05TiBQIbZJJEwb7//4Iv8TfVWXPviaO6NCJbcFK8AQ+7cd1rj9NAIywgmx5c50xij3zc4xme+f6fBLcoxzlSR346NGZKgbDJUJmjrNchFJwshxOeBe4FZrfW1tu1/AX4NSOoF/qbW+mG77pPAr2Cyfv4HrfU3NtWTLWIW63T0NWEWAKV5418HujCL8kxIY9Kjcj7MjrtJzKK1wzIq7dApMW97zLQFQ6Yt+T3ynGB1nyAYUlQfN8daOeBTnYqYfatHeS5j5hp9MaA9UkD5zpYwi3xZwwtJc3fMwJ6V9PfybB9iUFGWivb3Ld/8aEzfccHSkA8nzG2oxyJwNGFZUp0yD1/Q76T1MJauU7j2bd8ZjYmLkrDPWRNxeSHM4lcPfTdt/qvydQA8+OzPQmzWF3c0aEdVWq8MMnDCbFcLB4knTe1RvxbjW3yiJlwWb4iRgcRZSZBEdUHMIqxIXBsk3OVillDYZ3Z83/4XUgwj0Tb2DSzyzMgwTlMSjVmvW8Mh6tM8fPwQwyuapWvsfVeI8WouMtLExSReRqfu0rwE4xFTr47jNiRzLRMBPDZS49du/lt+79n3ceCW89w78QIAf3LqHrPPgkydA8qT3c/MRWQzmsWDwB8DD/W0/6HW+vfzDUKIa4APA4eAncC3hBBXaq0vrgNv0QxZUzfkNZohfk3jthX+itUqerpRWFWpCi+Us2kzRMSC4rygOG+jYTDAW3tE2GVNZzhjFhdK4C9lRWv9msbpKMrnNX5NpbyLMlB4ST2JLZghm5XKrhorJ425UT4vqQBeHZrLQ5RtHWSnbYrq+DNuWibAX7Wh6804vTZeIzNJ2iMulXOmH42d5saPSnJLZsgX/vxuAGJfp56VElko9jXXnePw41d3nXNhUXDt+1/mxa9djfKitKRgZcbU9fCn3ZSFO29+rGeG1PY4lGbspjkzZN+euRTM/NLDdyAxQOfxD34WgCsf/Dj/5kNf4GhngmZsi2GHFUa8Bg8evpWoINCu6dfA9wppPkce4KzvcmhOai77z1l/3n/TD/jaMzfiLwumntgFGDasTx27j8HLlllql/jDb70PgHvveYYfPHsjsS/SQDjliq76tReTi+rVWutHgQ0oTdbIfcC/11p3tNYngFeBt13kP9uyLdvyEyCvB7P4dSHE/cAzwP+ktV4CdgFP5LaZsm1vuLzWSmS9EvQJ3I7csIBQUJW4jc2p8HlJsIr2KCnAabCLDJOrzZYAACAASURBVOST1kWW2PVhf5ZJ2dghKSxLWjsEfsN8AwyckIRVsWnAMpHNbq+fHIRJq8Hdukx9pkp1Rx0faFocwD+0Qvz1ga4CQwnAWT0jcJvmHKKyTAFO5ZtYC3Pu5rs0uzUyyXf/t88CMGZticcX9vPK1A6q/can+NQPDlJ9xxL1s/30HzHXrDOoefFrVyNvW4IjfWhbRLgx7lA84aI8zeK1Zv/VqQsff/jI+v09eWqMMysmBuS+u5/ksenL2TewyJUPmgzVVz76ad7yuU/gtKE5uRbghAzzaOzShH0OhSVNy+IrpVnN4NGAgRPd9+g3/vpmxICiuTdidLfBk8YqdeabFRZfGiEejrjqOpOY+O2/vIWxdoDb0Clm4UBXSPvF5LVOFp8Gfgdz5/8O8H8Av7yVHQghHgAeACg6fVvuwOstX5iIXzNZmX5NrDth+PXMDKGy+UmjParXmCFejdQM8WpmIoGMgNVbFWmcRWXGcFyWZjReQ1GayeIwvLreNAaRyGa3F7cugy1fqJ8cpAK4Lw7SnDCBWABhfRAn0F3lDb26LQrUilNTym2K1ERojbn0nTTLjZ22bdyj7+TmJ4xvf9XUfsybIUWApolReNs/OMLh/3A1VbIw8cKy4B9+5BH+4ot3ARHCgpSV2Zil6wWFWYfBo5t7YBav9hh/Zm1/xyZXeO/NRwBjhjiB4JmRYf7Nh0zsxVs+9wleeuD/4pWwwWfn32H2FVZY6pR5/tSuLuC0clbQN2Xut/KsaRMKlg/61Pdq9v/HDIH+nQ/9Gf/yGx+mfNpldd5kbDebo7QmY6686Qy+E3P46X0A/PP7v8ZfPP/3CPodk1+CiVgNK5s3Q17TZKG1nkmWhRD/N5BYUmeBPblNd9u29fbxOeBzYCI4twpwujVz0WTgpCHaXam+mwQ4/brCq8V0+h38usav2xj8RmgnCR/HJlG5vrNpgFM7pqye18xuBBkJWibiHK+RBWh5jRivYZOjWvZYLQ+nFeG1PNxmjNfK1nuWRepHEZTlSpUFWNkH3W0a5D4JdNJS4LY0bkOm2yTitBROwjuaO6zbcrMArVYuMG0LQVlJUJKIRBfDddKv6UZ/uuzabeMClJ0OTstMIG47u0ecpofbJi1qfFGwL7c+X5uj1ixyujWUnpsMTaLe0c6EOU4bXgkbXOlVKDmm4+eWBxgotNBNFxmbanVg8Ks0ATC5dRVo4aT1VNPjxiWclsTpkKbvOx1wWpLFVhnPiXHa1suifNP/vCNgi06R1zRZCCEmtdbn7c+fB160y18F/kwI8QcYgPMg8NSmdrpFgFNsAOpl/98cwCksMBpUTTxDfr8aiCoO/mIecNs8wCm0SYpKVL2wklUdT2IrkmUUhH3ZfhLwrzkmKU+bGqcAAy9rwpLoPvc3EOCMVMZ3EJUNuBmVBVFFd7ULbT+2LSmMHJckJEGgmhTFb41ppC112Boz9VPz1zGVCwCciQtaFbKoTbdJWr90orLKYtmoLcmYCwXPrlxGnETBq6yf0VhAW/lpScHi/EUGJ9etfPboPQd+mEZmtkfNZBuNhSmY2ZxUfHb+HZSckN8dN96JD6zs5O6RH/KDwV0op0y4w0winRWf8ly318+ME3i17hffv5u6lag/Jl5204jhsCqIRkOWVioMDTQIdpiJ+7sLV9gsU22+AbVFF+pmXKdfBO4CRoUQU8BvAXcJIX4GM3wngY8BaK1/KIT4EnAYQxD4TzflCdmWbdmWS14uOllorT+yTvP/c4HtPwV86vV0ajMS9psIn7ggcRe8NYlkcpMJip0+h06fkwvKspT88z7BkI3fnzCZme0hh+LxLfSxzxRabkxYEyLQaXX1xk6RVk5vTLg0d5l1nbEsSa09VsSra1rjHl7dbNsZKxNWX1tQzWaksVICC1x6ddGFVTQncgFr45LmpFqTdAbQGTFv1Ki8MZ4UVjev7STiWfMotiZIWNGElaw9kahMGvHaGdQcnttBWNFEJYmy7GdRUSIaWxtHeYFM9CTXw21YLazhsBBW0rbFsMK55QE+sGI0n/908Bt84OjdDPa1iIoVpG/eqXExi9zMaxYy1Miwu7+NwMcbbBPNZ2XrE4o9vxCysFRFNI1mVwsLmUaR+74Yv0ZefmIjOBMeTaewAWaxSSnUYrzVmPouH7+mKdjQbrceIIOYqOqn2ZsyKF1oV2v7WNOm5Fwj83rU9hsgs3JOpeG7lemQwNYQKczZ2qteheJcm8Z4hdJsSLDfT9dXBrcOCG9WKgMtAsse7dXNhJFMVOVpa05VBeVZw/Xo1bv/7zYV3kpgl3NZwPVCit949QT43PqEkR2HNOrRzSH6bkPjNsCzWIoMBBP9q0zPDuG2FN6qeZqcsoOuaNzZQoqlvFHiNgRRn2YkCTIBljplBgot7h4xWacfOHo3/+ngN7jy0fsZaWsTdQkUFqGwbO/jHGYR9LtrCgK1Ao84dKgsCjrDWbtoOLScAsJ5g8/rDd3bmyjtsWK6/Ho0i9pOF3a662oW9T1FG+5tDPKgKjetWXirgtp+TezL1Nb2a4LkAVm4Pls+f7ubhnsvHTKeCCfQNMYrhFXByn4/1SaWDvXTHhKUZjfXj61K++gA0ai5WZXvIPY08Z+r4B9aZn63mSy9KZ/6XkHx4HJKRl+fMWNUPSep7THaUS/SnrhOLd/Xlolt2gdNSLNXiGicK+PubLJ/bIGjzxlM/dTqEO0xQftgG7Fg3/Q7G7zy0m64OqY851DbZa5vVBL4U5r2/g7tCfP2rf7lhY+fB6vzcqw+Rjuw/u8DDd5/8EUePn6IBw/fmrY9f2oXuunyg0ETSTDY1+LKR+/nlTsf4ub/+nGE1RpWDkWAh/IyXEQLKOW8aok0GwX+yY2P8hnu5JYDpwB48sgB/GpApdRhab4Pd8yM2YmXJ9kdmRIQee/LViqSXRp8Fu6ovv2qB4hfOpq2uXt207l8HP+FkwCoupmldRAgr7+6i8Nh+ZDx/w8/MZ3+X9caEAbg+dBZy2cR3WISkYQlfNVud0Xwwpll1EAZEcYpwYsq+zjnFjLyXMhIdWu2f02jhTTvuAoZ6TVlDRPVXAYa5SdeB0Vr1EWGmr7j5lWdVMsCukKPnVZI1F/AXe2kBLgpqYvnEg1mZoy73EzXJ1XincW6PV8HEcVo17pUl0yId/2Oy7Pj2j7KQG9oUoTJ+YSm9mf5bBtVNPvM09rH5ax6WFQy6/3lAKfZ7YqMy15XW/Jbzq+wcutuwKjPMjJAnXKzG165xrMRFfNRipa+zxX8/P/8Tb7+P95l+htrkysy6FBaMDtwGxd+crQr1pAWO/OrzN61Ez/RHh2jeRVWNFEhmyxlpJGxWQ/G1HDbmrAqeOZffZp3/LoJDXfaCqejiAsyfaiVK/AaEcqVXaTDq9eNEhVF1wMvYwPYJ7wV+dSI0lyIiHVXbsgzz/wJq6ubI+y9NDQLIWG6G4rW1RKFY7N0rtsHgPt4RhoSDpXS2AflOww9O48uuCzeZlxV5ZmQwvMNLiT1PTb/v6Hw6jHNHV76G6B58xixveGqNjekM+AweG5zKsvCtR6FJY0MLF0b0BmUdIbsPqcU9d022/HFkPagJKqCco2JMfN2zdhTkrm3KQZflLRHLeL/VMD8tT4Tj8fZZLEJSbSui0VbzN7kpAFCRtXXxhtShj5LylLbKxg+ErO610ldlclksnpZhfJ0MikIorKguKCYeXdE5aiZZJPApMu+7q+ZLC4k89dbtm1fIwOJ20q8IWZ9eGMdcaRKcQGKC1kfpm8X+MuSv/qNd9OaNOPQGRT033uemVfGqZ40WsjEExeeLJrjPn0n126z+O52ykchA2MeLV2j0xDuZDxlR6ReD+nHqIaHCAXv+PWP8dgfm9Dw/Q//KqWTBQrL2cRSXDSTtnIFXkY3wvwN0mggXV0SBOMRhWmPqKxTzhS3Kdj5mERLkbJjaUdsySOyzWexLduyLZuSS0OzeA2y1QjGjSSsSMKK7PoNpG/90oymM2COFV4A3V9POkMCGUBrR9bXBFFP9g+wss9D+WbdzNvNrF+cdtJMxPo+0mzH1T1e+iZdT2SwBSN0HfGXBfUDCcgriaqK6nGHzrBKzSZ/GeqTDvUDcZpJGvsK7WtkW1Dfa/YlhtuMjdRYfnocyDQKXY0Qdbe72JM1B2WozLIrs99WOuPZuRVmXRoHAwgkhVlzGydaRXMy8xzU90L1tKS+VyFDxcLP2PHdv8r0ktHimjdZ+sHHYmQ7RDsOIo5RxcwUFKGici7XzxwLt/9qKVX344KmuTeCQszA95IC0JrKWeMZ66xYL17RgJkrhyKctmb/w6Zi+4l7/pQrHvkoAeC9YrGfPsHgt4zpIXJ1Ury6oDOkcVuC1q6sDkzgK8I+hVcXafxL3wkonq+jPSc1q7XjbClt4Cd2sni9UrC8mp1ctfV8DdALiQgjtHfhoRt6JaI94KQ5HYkMnIwIy5LmuKQ8ay58e1CuidFvT5gHsTzl0Nwd0380m1z8FYtHrEP02mWa5Dg2U/wiOYdo/Ztk8HiEb1O222MCf9mhsVsx9EPB6kGzTTCoKc4JqseddOKSPoBg8OY5Zo+aOPaxkVq635HHPYKBJGTdJyqDs7qW81LYCNbkocw/HH2vZmPeHtV4sx4yEHR2m3Oe/C8u5+9SiECShCe6DUH/qYiVG7qD837xyif4t583WazBogFuZdvkS4o4tr+7TSSnFnf1J5HqaZ1S4XUGBMGSi1dz0+zRsM+hbyrGaas04CoqCuv18HA6HUonzcRyxSMf5dW7HuSGpz5C0wLC8kQpLYRE7roNHIvpDEgWr1dpsajKWU35vI/Q2NIDZhzKM5EhKO5EWRAf4ZYIe39qJ4s3S2TQXTdzPYmq4Cx1txWnHdoTMf6yk76932xJ+l6alYAmtozb/rKkPabxl0XKwp3I/OFRxq8x+NPcQl/XhJGX3jDxTfUn9+wW5wVBv8EvvNlEA9BUTrk0Louo77Vp8GWbLj/rERdjPnb3NwH4f1+5DYl5w7+RIiPDbZn3OBSWNn4glWdihQoWiwiAG576CM+97YscfMgkooW7NyYSVi74ixLlJsfXaClsH1736XTJpTNZrMkNkSAF/pz1MgiRFv1Zw/TjmDyQokW1lSuy/fXu10qyjyRABQx6nPwefT6ktsulsUswcDxD1k1s/To5Kz25IcoxSH2vyWDaDYNUcizZIb3YQy/YrNNdmoEjDjI0odHazW645i5tx6dnElnvd/6T9DcvPb+VI9C2L0nf2xMxhaVs38GgpjQjupivkglx8CVB8KpJgCkNCBYHi+y/4zRzf7EnPUc01PfFTD7CliTKhbkkxEEyFMR7jIquXygY0ySUlM8lmb4CLTXxnjYydPjiH78XgHA39K1qVsZzNI2byaFZZ/y0k3kdkoCquCjStta4MElhMttOS/NbaPOAJ2Cm90qZ5pVw8KGPc/R+Uyrx9uc+iBZmQhRSpCHr2v6/syOmMGN2EPumP2jM053cNmmuVfb/rco2wLkt27Itm5JLR7NYk0hmy7StU55wTTHY2ABiXRyJFynxluyjO0BF50JsNTIyqly2rbCMXOskuPUkksnY/N9tdpshpt0AcKkfvSDSiMNk1i+fM292pwVC6C73mAyS8el5Raz3O/9J+puXnt8yzo6V9L085aSp3WBA0M6QMUO6+gTIGOp7E/Ys4zZc6RTTsTTjCP6Ss+U3nJujwi+fl6kZ4pwxtoSINZWjPo3LIpo7E5euKdfnnCmivDjFkGRotteexknMvM3EHPUm52mNiDPtxG1rE+bfzhLvSrN2WWXbJb+1MBpm0SYrhn0CeaJEuLvD7c+Z4kWP3/Bl7tH/nfmj0hnmYP+faBVgcLfEDBF5WCpNzNzkea4jl0RQVlJF3d1tott0q2UKA+WqqIsbrzYBRTa0+2JV1Bv/zaF0uXLM1HmL+ws4q530G9hyFfWlu/bTGpUpV2dSa6T/eAsZxKmXRvkO3lL7glXUk+XCTH3LVdRf+dhYdn62Nklc6CbFdQIozmucAFb3mYdk53c7yEgRlt20JF5emjs8yjM2fD4XgJSvoq59iQgUcXntu6ZwemndClvRxCDOihnreMCM9ewng7Q2SWHenEPzQEj5eOaFaB4IcVYdxp+C0rzpV+zLdfu+fIXP8JF2V1tYdlm62mPoSEhhqYOzmMXfNC83MdLl0+b+OPLAEKVpSWtCMXhEpOQznWFFYVHyy//wG/yH3/s5wNRDSfpQ2+2mwPjg8RARGc7M+i5zLwweDVg+6HfVOk2iV90W9J9q0xky51yabqdgZkoxoDUPf/PPuf/Unbz40CEKK3ZiKZn6q/kXnuHrlLQHJVoY3g6A5qgB29vXN5EnzfiHIxFz//sf0Tx67icoKOtHJMXZDiqfO2JrQ66Hwm9WSnMhrdGs2kz1rEXOgxgRKhzr6nujXLsXkr5j1r27aImAfJFOCgCVc9qS92jaI+ZSy0ghAoXjGnLaRBLODnZkD+pGotz1H9bXItVT5hyS/BPwKM/kX2AeXgNK8xe/ZlFZrCHZzYty5QWD0ipnjFdKhqY4cmnWPtCNzFvVCxp69YhgwEu5NmJfpizczUnzn4ETgvpeU9QoSTM3miWARrmyCztbT+4/dScPXfYot7QPpZ685Ss8ZCxTDhYA6WSRrYgMF2vsFBSWoDNVoriQaFce44X1Aej15JKaLJI3OABxbKuWJ37tCJSiffUkhRfPQGTfco5jto0iiDO9y6vHaFcaINOGNC/eZAhKyjMhpZMWfu6pUt51/ATMsvvVwoCTeQbwNJxWCpBw5m4Ter7nmzWjVeT2K8mS3WQQ4dWycO00Cc4eS0QxxHH3N6Dtcv+rWW5JUBH4DZOB2Xsza4G9acxv5cp0QsvL1Hv6GX0+pHq6nU4i+Tqm2hGplpR8C627Hk4ZKdPPddyyshmk7al795vDRDZhMuH2iEu6KwUiLmn8mqC222fgmE3o68Rp2HLeJB1/Os6Id5LjFl3Gn7aEQrVOl8u4OGttP9vWGdF4dePN8Fqa9ojV2IrgdARf/OP34lvvj9dQOC3F9K0lJh9bP1o4T66bZ7haMzZBlEZmikil/REJOK80Lz50iFvah3j6U5/m4CMfBeDyP2ita1IUhaA31bByWrN0TT/l8yI1M6tTmpfPD27Yr165pCaLPM6wxjyyGIaIdTcOoXpsSCtdN5OlbU/UNRlphK2hmmENqjt+Yr1jYFiqS3NRGp8R2/h/ERsPRWqX19tr4yCUwk3U4DBCJjhCvj2RBBsJwuw7kSCkej6mbYPFOkOCjqXrGzkcpcFjzXFJ0yZJJe47obTRtpSxbRPOz+aemPq8y9iTG7g618noFZ14LUK+gVkrmrkH1W7TNxWxfMDWGKlCa1xRmZIsXpdNZkM/FLTHTMr5yPfba/Z7MXHzhajDuKt/ctUGY9n7o3xeEAwaPGPuRkE4bu6RwpRPc6dm4okYt5VcM2Nq6NtWcP/qdfooNyqMnAyD1hRWNIWlmIOPfJSjdz0IwD3/6hfWH+8NvDrzb9WMPksaW6HcrSXzbXtDtmVbtmVTckkAnAPeuL698n7i1dW0zTl0FWKlnpomemUVrTU6CIjefVPX/wtTK2jPRRdyYdVTcybbtFCAlvXD57JOFz90Y7pcXIyJC4KwItNEsurpJsp3iCpumo0YVVxKh8+jc2CoaLTQlRJi1WZztszb6tQnDMBaytnfyicFwpxAp0llQy/H1Habvo8/a1TjzqiPvxLRmPTxmirVFqqn29T3Fuk71cZdtoZyV9Zp1rf8+mjMKKbeeaPvrsk6XTTtL/3egfT/pdOWY2EZGrs1FZucGFagelaxeK3AX+p+i42+EKYFiIP+THFd2ZdxcEaWFnDgVET5TLdGFZe8lIc0/9uZWebYr11mx1GnyVlgIloBxJ1L6EeHbJs5VntUsOu9pzn7X/Yy+nyYho+HfS4zt0gKiyLVuoZe7qk83COL15QYTRIU7dvZna9x5LeH+M23fh0wJQVlZAoAvf+mHwCGhft3PvRn1OIS/27KpK03Ap9W4NFsFJj8jz7zNyTYjWDg2Nq6Ie1BSWOX4LKHV9Os04e/85fsf/hXKU75hH2WO7YtCPd0+PB1z1CQEQ8+aaq1/cptj/GtT77DlOO0iY3KFTz7xP/5E1hFvVdSDk0biHUh16lSCKUgzilKF3Gd5hHkoN9MEqZiU2InKjrDJdxGTFxITA65ltdzA9epv2wiM2VEOil4DU3YZ/I8wr4stbi2x0H5pr09bsBTGWqa4z6xLxCxTCeZ9njBLOfcyl3fXebTOu1511/yyUnluMlWNGNkTIPivCCqKho2n6U4K6jvlkTVmMjmHviWE1MoaEwYl0wyKST7SsK9wbhlnbZecy2F6m7L/44qCSs1FBuC9pjCm2gSvWA60akV6YugvlelWbDtMcWpv90LZVC+oD2cMGUJCouC+oGIYMFc3+EjXFCKS2rtvac1u8aW+dS37zP93dVmcnyZqVfH+doz5oUkBhT/8hsfxmlJon4zEXiDbeLQ4Z/c+Chf/vrPpeUgOkOazoCJyOzis1hUyFh2XbP9D/8qJ+75U/Z/5QH2XWE4tM/MDaGbLl86/FbUgk9hwrx8Pv/oO9ntGRduvsjQVqqoX7qTxY9YEg0iSRzLJ5PlJao4uI2tM3B5DY0T0pUb0vEFpRmdksIkyWHJA5d8A6zucSktqBwj9pujAbqNLKU6KkNhUbJ8bUz1uJMmmNWrJhzdX5QEw2Yck29DXZedc9CfxFzoHO+EuGAy3MZ9M9dI+ZrWLlsicbHIjp81TEDLT49T/HuzFO0ymKQ1/7RP+T2z8L3h1DsQ9gncFhTmnbScwcVko/Dpcy/uwE8S6mpFzjTGcBsyjUNp7o0on3ZxOhAvW/Kd+QqVRcFnuJMdUZZm7rYEi9cr/EVJZ4cZ78KMQ2VWd3k9AIpTPvu/8gAn7vsc7/qhmaycEyVUn0I1zGwTnTYIcmVWIjshqpzVqxGRiYvZrPzUThYbTQ5v3P5F18OfSH7yWG99IiXLx9AakZQWFC2LzFen4y2VnNuqRBVSzSKZAPxFmU4UQJqrkqzfjLRHuieI15IbMnhLRg+WzzuZSRD98Yj5w6M4e5pdLPdRyWzfW+2qM2zqrgaDr2889XiHUBqN8KqfOU2/32auVU1LCo7uXmZ1fgQtRcrCnRz/lgOnOE1KIUZrV0zprINyu4Ot1pOwT7Hvihne9cP7+M6hrwDwLu6jz+9weGoSITQHJ82Ynfz2vtd1jrANcG7LtmzLJuWnVrPIS2EpTl2hiXkCUJjv0BktrK30vQlxQk1k328JgJZgF0lbYo4MnIyo7XSJqiaCD6C+p0RlukNrpITXzDSL0nSbTn95y7wVm93ebXQn1/mLMjVL+l9OUtc1A8cU4KQaQjCYgI4x/afMOQR9Hq4tjtTckRUkkqExq9zXMK6JqMBh5vwgzpJLwZonUUXhNiTyhSrVKTPmzZaPDEEdL+G0A/rO2FiPyEO5ksK8g9PanGaRuk17+9Lw8Ow+3jX2Mp/5/p2MjdRSTo2xSp1mcxSnQ8qlmpg0Tx45wK5Yk6TUl846VM6alIA8GO60NbKHgNdpC87MDeGcKPEujBnynUNfMWHi5wtEgxF3jBwD4FS0D1UQuG2FStz9EVsK/b50J4u0opg9sQtlnUqJlrKrXVwk6zT/QGibCdrVbrNe8xms2u3JODUdWzfrNKGiN/vs/k6WE7VcOUkWalZZymQymnbtkAJgWproPFX0TKBa0tdcn7vG0H4nRC5OvoJa8slJc5cmHM6HqJv0dO2r1HOifNOnqJqRzCjfYAlJv9NzsJp0/TJFcdaaLwOmwllYdXHq3cFKJq9BrPt7oJDFWcwVErPITdPk3b0N1LEqINIsTuWawj/pvmxVLy0NuOktO4hkbC8yZ4TVDIdIAWMhwFeofeY8Hls4iGp4/NrNf8unjpkHeL5ZoTUZG4BzNPP0iIaDXw1AlwgssU/gK8rn/TS/I+lrVDZRnsXcNQv3dNBNF9Wn6PNNhOvtz32Qx2/4Mtd3PsIVw/N4dlYKhjQy1Gu8IZvKtE1H+lKVHu9C97q12wqtk2DP7v9tRO6Ra24POfg1RVCVXWxYUcnBq0UpwWxKWnuRZKz8/ouLmvaw9Ybk4p06gyLdpjMgTfWvGoT9GRdo0O8ayv1SRpQT9nvmf3lPRq+Ho7df6227Qb/DwRhsNGVx2qU9EdF/xCUqOwQmONXUN+kXhINRShSp3CQ0WhFWzW0VVLMw5r5cUd+EkEW5a9OlhaarLf/7+LOGxVv5ZrIJxiMYiHEsU5aKJYUlQTCgCS2wGvZr9txwnqnv70Q7grBot3VNMpvTFJsG+dqDksrptWMmHMU/u+E7APzht94H5Zjfe/Z9DF5m3NGLL41w5U1nWGyVWVoxgKNfCGk5BSqlDlqWKEyb6x72KUNck6SZY5bbg8ZDko/M/PB1zxivR8Pl8JQpzMz5Atd3PsLzb/si/3rxcj7z/TsB6L9qCR7pM+OZzHMqvXybkksXs8i/qXu1A9H7ESY023IEmM+FNYv8/4tLMUGfBGHIdZOZ123FhH0ubis2n2aSMtjzVl5vdrb7bo8ICsuawrJxm2ppyhQWlnW6TWFF4TZNu7ca4q2GhBWJvxoRVgReSxFWTBFbbzUkq1n5Oj4b9Vvq9NPeGVKYdegMa2Qk8FdMTEPYrymsKrxlB39F4K8IZGQ+UUXi1SO8emTyUiKjUocV8+bOfxD0XDPbvt5vIBoJiUZCGO0QTIQgNd68a2qmSpCOojOkEZHAW9X2I/BljJbGBevVIrxahIwgqphr4LTN52Kik/uq554SjqYsO5RlBzHSwV1wuWJyDtdRuI4iHo7wnRjPiRkaaDA00KDd8hGOZmm+D6EMqByVLXeJsBmjdoxEnBuvnBRkhFrwQWiTmSw08WDEFcPz/OvFy/mNOhr5YAAACLFJREFU4WPsnVhk78QiUirIj7vIpSpsUrY1C0jrnUKWQpzf75q+bEGz6NqntqaHtm3JMXO/0wpR9g0QlUT2bbf9UWoWxXMe7YmcGeKCExgtojSd2FO2D7mUa3Ln2HXe9ndc0qlGEZe0rbCutqRZ7Ns7l7afOjeS7ctWFgtaHp7tUzKOQsHJJ/YgcnU4zH6tKdSX4QUXk+r5eN37SbVcfvfxewH4rZ/9Kr8d38u9Ey8YLQO46rozHH56H05bpLVHk0ph7lgbLZ2UhTusZppXfiwrs/GaZLMHn3w7hYkm0elK6vW4Y+QYnoz4zPfv5OGJa1MvycGHPk5VxjihTs1EobbmOr10NYtt2ZZtuaTk0tUsYOOkJG2K90ACwGXtm5UkmcZvKGRHUajFBBXZXXlcg1eLUwZkUXI31ip6q6hrKCxqisvZ9l5d0xmSuWWLdncUQjv4tSzT02saNurynMJtxCnRqwhjU9Bmo1PdanuPtMcjiufMbVGaszhEU+PW3dSr43QMQl9YzFK3kzKGblOl18ZpxZRt6Hd7uEBlxrQ3dljvRUlyEXrSLln8zyZuQXnQl8urSwLWmleGlE8VAI0T2Ou7LBi6c4bGV01NmSTjtjQfs6RcytMi9ZBcrO5nY9yhaAIlu7btH6vTVzQA4+8/+AuUgT85dQ/33vMMAN/+y1v45/d/jaby+e7CFYCpPQqmUhhkpRj7ThhyXYB8+cLGhEtjp+jCTH7ltsf4/KPvpDIr0ziKU9E+giFN/1VLrLYLKY/n0fs/zTu/+wDKETg2ClW5iWa1ObkkckMS8htnzBK6dDqonipiztVXIFYb6CT7MrQoelJxzHPRjSzSJ7ztmnTZP2vzISpFRKOdfgOIps0bKfcwt87Mg29h8uSYvsfSew/iNdSaoK6Bl9dma8pm0J1RmKsY5i43UWXzqMiVJtGYKVvoHp0y/eqrmpyWUjH7BnStjuirsnj7ZOp6zbtk8xGi+aCvhMlq/PuW7MeVXZXOggEzQRQXgpTkJp+inq8Ulixrz0mzVgFkqHDmVtZNUdcDVUgyfQvmvGdvG6Y5mXhTNMGw6ooKBVIGca8OO54211e7oou5K5HOkE9hqce74gqikotXC5FBjDOf5R/Fo/0oV+IumJnu+D/eQVRRyFAwfENm8sycGkZWQwb+v2LK2I02xZUbk5K+M3HmcrfPk4w0YdWYGk5bGY+OYI3XTUYafyUyqQQYun6RsIonmJLWnP4HO/BWwa9p5t9qjrHnmzHKyyIywbCuydC+TETmmQL4m89+joMPfRztZdtP/69/RHP2JzE3JHdieVepWdftSl3znx6wrsu9al2I2hEI62IVvQS2a8huxbrL/qqiPdwNIXsNBVIiwhjtZUxZsh117zfv2sy5M2VNrj2vjUBJu251X3d/C0tGU2nsEl1txSXjMlu6yvRLS4HTisxNFGuk5c8oWkalcMAD++ZxcjkweRdmshwXuschLjiZa7ZHlO8i7aSbVEdbPQjhsGkrTLsUpx1ae0P6X8oIeFbfEuItuvSf1KlrU0uxrhpgXJvdbVoKwqrE6Zjrkx/HuOyiHIlr2y674zQnntpDvKdN9OUxVo0SgNzTxjlTZPVyTWHFjLvb0virMcWFkM6Qm3rKnJbRCONCls/jNjRBv2OO3fNyNrk/GY6gPcfQ9UN2TyhoX9+kM1WifF4w+qw937I0Ho1cRK/bNkmHSSkAx6agK0ekJMAJXd97Jl/hD35/3cu1rlxak0UOPFqXzyKXWLbmP+vwWXT9N2lTKv3u+t8a/kq97rKwHJp5kZHdn1Kp21G2e7gvk2Oo7HhpXYreBLCkX72f3LrSnO7SKPIcl/k2EWtkrNOAqCQxSyi9bs0Ir54R8WyU0JUsO514jWaxkekog6xeRRIgVj4rWK1a5qjAJNaJQHYlN4lAIgPjEUjnB6XXNRm8ulrbrjRe3ZhGIgGGrTjNCOHKtG2lU0QGgrDjIOMsRybsOHiBoDgvTMJiMgbKJGYJReYp04ZHxemoNEdGO8K8UDbQLLSTlRTs4tzI8VnIk4bhSkSZCe011bqahddUazQLx/KNJnEYAAe++cuI+On1Lte6sg1wbsu2bMum5NLSLP4OifLdixYuTtTx1zJj57WKvLj19RPULlboKJGo5KbVz53wwn61vFaR/N4oxseo19kymLDxRNoTMcVpa8J5pAWFsnDzi2Nr+WzXrnZXmOjbnssRFxx07hxmzg/CeMSOyWUUY10FlEzpRBd5KgMHk3NVbhZtmWhFyssC0pykb4K0EHGvGzQ18RwHwdpi0eFIhAw9qlO6SzvpTTMXkU09V6SV1PPHe8/kKxz45i8DcPznPk95C0FZl9Zk8QZjFv5CC1V0Mzq3VmCwBfvd9b9NYxYhrTE3BbS8eqaym48tdFT0WFMIqAezWHc5G4ALYhbKJc1/KFoC1+KioLbbQdqHsrioDE9HoChYzgbZiY3ZE3ebIcnE1h4v4NYz9Tkdz3UwC71ewNsGmIUWAmHXJdymnYmI0cfNLeg1TUBFa9mhNJeZbkJL3IameqZ9UcyiOSYpznW3aSmo73QYOhrZgKSsfympsm0betrDbUHw3BilpmbwiAWKT5n2oftP035mp/lLZE2xVsTq/gLFObNt9Zx9cgUsviUhNFLMX+d2PbyJyVia1RQXSQHOtBgQdGEWgxM1fv3OR/jT3/4A5VkzmUy/rUBpXlNczBH22pySTr8JMiwum3Vn36MZfNHhL1p3ULEh62858QmuHf3kmnHcSC4Jb4gQYg5oAPM/7r68yTLK9jn/NMilfM6Xaa3HLr7ZJTJZAAghntFa3/zj7sebKdvn/NMhf1fOeRvg3JZt2ZZNyfZksS3bsi2bkktpsvjcj7sDPwbZPuefDvk7cc6XDGaxLduyLZe2XEqaxbZsy7ZcwrI9WWzLtmzLpmR7stiWbdmWTcn2ZLEt27Itm5LtyWJbtmVbNiX/PxQwL+NOVUkQAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f85504240>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 9 of size 183 built in 2.147176504135132 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 9.0, 'k_func': 'tanimoto'} is: \n",
-      "[[1.         0.44444444 0.11111111 ... 0.03030303 0.02439024 0.0212766 ]\n",
-      " [0.44444444 1.         0.08333333 ... 0.02777778 0.02272727 0.02      ]\n",
-      " [0.11111111 0.08333333 1.         ... 0.17241379 0.13513514 0.11627907]\n",
-      " ...\n",
-      " [0.03030303 0.02777778 0.17241379 ... 1.         0.73684211 0.38461538]\n",
-      " [0.02439024 0.02272727 0.13513514 ... 0.73684211 1.         0.45454545]\n",
-      " [0.0212766  0.02       0.11627907 ... 0.38461538 0.45454545 1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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98v00l9hMniy78gm/96T8IH/+huyYoCxxiQKqUsl2+GTHT1xrYYiO4lT1xHEgDNn53pPSW+btIolNBMTuceWrxB39mQdeBcDy620ayxzqO0O0pWgukeun18o6WPsHj6dGL2Xbovq6hUNsCapURDcah9hLtOenRxvd9TINTOvMmGaMmvveejKx+fnUiTG6GFPb6tJcF6A8s/Nvl9/bHiz64qPy7JxmgaWyI2EYpvyktpquh261UOVSOnZJO5AeOwD2/vdTmTwlZmCzxbuu+B5Xf0/KgfQ9o5g5TjP/fujbJobl7kiJxjKHxkpY88ktxE1pV4UCyrbk/sY2oJSSeY3jrM22euY1PW4FAVgWynEy16lt4521lrBsY/sxnXnS3/7/swmrWk5tcSklGm7uyALw1Cc2sOS2mOZi4yY/EPPoD/6axvSuF88xhFij/YAlt8mA7Xy9YvAOT2wUZnJP+4vLUxuGDoJUnYOcTSIHTLG+Oo8rBkVI5G0aSxsx++9cwXBo7CPKQvtK1EqtM7hP4KN1trgS+spnXs+SsQjvwXkALO1ornjkChrv6PCps6/jkx+9WHgyvCj8HDCGQ20KGONj2HtcSL8znpoMqiXCY8ED3fQa/2knBUclRxsQu8dXHns9AIsOSvv2i0I+/Qtf4qofvwO7EPOps68D4C9/6+JDni+eBAuFLwtb5Xz5vngcFDnVPPl9lNhPdK+3JJkzIzSGNrfTY0xtvIC2LIqTXQa2uQJGAwrT0k8VZsKmZ3vTForEgxWn4619M5OBsfgnfMz6X1tW+nneY22qe4sU93fSeQYoTPnUdxYoj7fY/cp+ABone3z6F74kNpAgzDwicYyG1PsCoJWS9nyb4SHtS9I3rY2HLsp4BIq7pim4DiqKKBw0digdmz7n+mWMoALMynmKgCW3xVRGZyia39vtAMs/8qx+x4awsCxUwWXHBTJ0C+6w0K12aqMAemwYr1/zst5zbc4mkVDerpG3aRx8up8F98bEnexlU74jCzmO0YmXw/dRtn2Ia9DpiCEtNte5rQi7Y7HuE02uHriIiQuEr9XfFZvCv2VPSBaYCsJsYczW9KLIuNhUdr8oSm0i0GsX6REWtsLpk+cnNpH1fzbN1UMXsf7gNFiKqwcuAmDv6xyW3NbtsSOAuP2SZ+b7onwH7XmH9E8bwxoYe07C92Fce3bLS+csLtrCr7GNJIjWtJ9h75wdwl8yVgl4zTfG7TCUuTS7eOpSDY2BNwzTObZbPm7DwWn6OJ1yatdymj7asbCaHsuuH5Xf1ypcPSQ2kOW3dsWmkOuzjiL0YTaJpE1Zqndek/HRImzya0/ZtthAXAd/2SDdIdGeKj8JodNBK2uWUM7ZInLtbjMUe4ZZK6rt9bh9n4+OiWNIZWSZ3njq5bg/Ma7TKOLAN5ZgfXUeblv467tne+oN+d7Td7H+zl8D4KSF4+z+mzV4/So9AgCs/9QEdLro/jrsNwWjct6QoW/LYjmzf5Rv7jqdO065kSf8Nr+38wIAnrh5HZ3jPd5y6iZu/sY5AJx/0d08/vbVYsxyE9U3QldKMDUjqvn0DABb/2Y1AG9e/xBLipMpXz+ZXgnAotI0j09LEuimX+Sa4/8RgLde/REAznvn3Xznpo1YJzQJtldxV4ia69xbJ3xpg1VX7EnvqVw3M/rNmk+dWMM9s5i7nvCZqOGJup7w/b/WYxv0rz8YYfcHvHn9Q9z4xAau2PAv6X2/uet0du4e4sLTNqVt491+7r1jPU7bvACOxltojJodm8K0uW+/8HjCHz2Val2qWJBd0fcF1p3gTpKNINY8+b/Ew6TdnCu6P2DjqmcBuHPLcVx42iaWFCf55q7TAXjpyCg33XAOK18zyt7rVtBa0qtxB8d3cLcIFmXVZ7egSiWBoQ/2pUZL7fmoYkGOxIlmWCya42vE9N+X8P5Jaicd2KCxhj1q95ZpLZY+hH0RlZ0ObousbYGPfcAlmhcwcnuB/adLe/9WC28AOisCSrtkQ+ouDQS1PMt1Onne8Uz8csD6leNsfUCgALELfc9YuA1NoaVpLTTjG8Hib29HzzQg8YCFIXdPf4vpaP+L5xgSF8AbdCkknQgUf7X+n7hi8IpUO+grFlBao22b9Xf+Gk+c+xUA/npyJV/pF0zD8OpcFblOF1wX1e6inQQCbInUdmzuu13ccPetXMF1G69l/Z2/jtdxufIlPwLgoXlrKFZ9bvzRS4mPlxfrxh+9lOPbOwVnERoNxKiB2vNkdzDPqt5fxu+DG4IzcIq5o8yooFXDRT6FHbJDfPnXPsMb7pAjk14Tps+KRiJq99YpdSGcqAPQXBNSu7cO3o70lglEWAazF5SVxox4Gc5Cx1rcglYOzGN25KHHFJGxIwQHHIKaww3BGRS3Ffms9Yr01tdtvJb33HYVN+TqGeuuzfzNsO8s4WHoIQu3KeNUPJAXYqqXJyCFPge+AXaZlzI5nsWa+jZzvs+dw4Oaw50NQZb1P+5wg5Lxvm7jtQC8/fb3s2hrxJMLlzEEeCPC2/ADFk5H05opU5zSPfxoz8dqF1KPk/YDiCOJx0nsOQYsRxxx8McrmT8hQs3f5uIfKFPbHVGcEj47ww592yOcbkxxStaHN1ak0NC0FhWpTgTEj0h7eTKi0LCwA5fyXqNddd00bkVrnWoLlT0Bla1Fnmwuo3/UaGgJzqIV43QiVCzj77RidKcj98lpHT+NsjDnDZmjOZqjI6JjQrP4aemkheP89eRKAD40OMpXgO6Qopq7RvfXUe0u8bw+1Pj+Q+4RDIp0TmBGJy0cZ2+7zocGRwG42rRtaq3A2i9XxcMB8VAda8ZGG2+MCkLivgpWHKPLRZgSdd7vOzzvyXMV4A9m6vTSBXJUmdi0EBDNg66N369xuipV3d1JaVPVXG8LuWNIHr6rFHFdVGzVNseOlo2ullEtW3AnZWMsm5wW/moqBYv9eyioPkd7TeE2dfoZQFXKmWejXJI+eK54upIdz89FYz7fs2uHbw/LFhDjDapZ7Qq/D4oCzxF+KmWU003nGUB1vdRLltqZSkUZxyDEHzg8b/mxCMsSlJe0BTUJCpTPVjom5cnZdxGyikUwEcfpMeKnoKhsoeo10UpyQD3VPXJ94ZiwWdT7l+qRj/8Waz8urjG0ZuLXN/DVj3wyNU66zxgEZ6vN9H/bgNefTfwDH/8c32lV+JPff1faNnTL1l6XGshiNDaL9tliU4gLivY8m0JLo6IMnlwbiwhqVmoYTKh677NiYc8Z1SgWM+y+UZ/9DXK+DmoOOieSUwSnpbBCg+Bc4lCckd+5BjGahKInsN2o3IvgTO070OMeO4QS12aK4BSbgPb91EUnX8hzoxNWpMbF2LWICzZBzUnRkQm159kMbu3i92cLV8Wa4v4u/pDYSYr7OzkEp07jVmLXuEMfnoXghF43MbMQnKeuMQ/KuhcXbMKKMeI2Qvx+F+0IfyAIzvJYC29BhWuu+Wsuu+xDwts+ccmH9SJOwwjSJ54VdGsQGne2OZYcDsHpOGJbiSK6G9dRGk0QnDXiok1hX4uoatIUOBZ2WxCcSVtcdLCCiNi12f7BiJWfNkCrmS5xwSGqur0Izns3HxbBGSwaIKw6FEzktVYKZ0ZAWSqMss0AMgRnDlB4j/e9FxeC86elvKDoDim+06pwQbXNn+SuUfUautOF/jocOFRc+3UTo+GCN6gMvFrRHTKuvDF5jlYWhYYRAHWLan8N1fEOMXAqxMeuG4K6SxawX7d6Yhkss1FqC+xAFp7seAZx2MqepeIM2pxAmlWsCaoOhUo566ub22l6ci5keTuUZx7cdcQw13VkpzI5IhK+o7IjbkogKlrEBcvwYuPXspfYG1SEVQe/nrWpGJy2S2Cuc5oOoeHbCjVJ2oS4KAPiJNoE5NC7QW9/cgbOBPKue4SFlc6lirPxTrQIt21RLDspT0GK7JRnhBUbKzDn+kpZ+Oh2IZlnkFgRsxunj3YLKT4nqNkUS3KPqOIQFS2csktUMRqpo0CD5VhpW1SysT1FVLSBKO2b5TvERRk3EztIWHVwCq54SHIGTgouYVX6ZntmbCyFFbgoW4GniMtmLLXGrlaxcpqJCkOUf0RyQsbniK98ASkqKpbfEvRIvEVvGeWSj384hXAv+6BtEopYTJ4cp8bMKvAnv/8u/gS45y/+FoBV372UoR8IqIpGS/zcIAY02wZlMb1aFk1U1qj1DVoTFQmEWi9HlgVvOMhnl36Xi679MHnTztC/tNHdbrZjxxEqiojbHdm9jaExCQzqzFfEhewFtjuJCxRs4wkMX9qgYwLI+t8hXo5lpRYHulWeHRvG3VWkukuu9QYUxSlN5fYM7o0TZElV8i40ZaFSyLIBfSXGukS9n4UjaS0spBpPWLYIS9KH8l5Fa2nu1usbNCZrtBfl4d5w8MQSfWfuA2DyzhE6C2KGH1RYgcbpGu2oJL8p5N20JlmM9gMoZLgFneOvtdAYlXMQ87AE3XlGhd+raC+S8VbrRfhNP1zHbReZXmnz7v/xYcL3CJhu6g6BVxcnNZWi0SYf6kIUo30fy3FknhHNgjDsTUATxWJMjiJmltuU9pVTHoOqwgpLdAcT6L6idFAAVUmbX1O4bZugolh+TcT218l66n+mgNevaC2LWXKbCTrrtyj6AdrqxeJE/WUaSxy8QUXkJsmRoGIr7E6E5YUEA9nxqfRMi9jzUqzHnIFzjuZojl4QOiY0i3+L6v+YWAqnn/faVd+9FIBn3/h5zv+fr/0PPfexW47nVxasoQScfN6WtL117Qs7ZBM/lO173CTpGpjSFKc03oDsHAtfvYvJG5a8oDz8R2hoc0yjIbv24LMR1d3H1n7U+RfD2zOyuybRqUeb5j0qO3xlT0BYtSnvt5mFVT3qdEwYOPvtYb2x/Ab2veM0QBLXFJ/cnYKwgB6QVt9DArgCUtCVqtfQrUw1v/nhW1l/56+loC2AiXM1pT023QUR6//c6PVKoctFQR1qnXo52LMPNTgAQYhuSkIbVavR+PsCy+uTXLfyNkBwHj8+uIbRLwrWI8k7seILkmCgBzAFvTaFBHhULaPMsUBPTafPAkT9TcK2Ad3tokoltvzl4vQ2eeBXAvoCAX7du0/+/shqiRH5xB9fQmyDFYlPPqHkjL/si1syHi2JDVGuKxD7QhYHostFmG702hdAMCjG/qC7XbkH9KIKzXhs/dhaoorYaC7ceD9LipNc/dAvccWGf2HMGwTgxic2ABC1HNb/7jbz+9wLbvgDOWol450Y9lS7i261UZUyODaYWJ80N0XBTT0uT/7+8bzlF+/l/9xzFsuO28fyuozpnQ+t49wNW9l004kseECubS10iG1oLVGs/vy2LDakWJCjbicH3LNsAzvXWZtJZNNjKAfhxbZ74lhwHPa9cQ1BXQk2xBz9Vv7lw6haVeJI8jlZ/SDFY6T2DWDoFovHrj+RmeNM/o8xi2e/8Cnae3e+iAyclkI5TpozszzpUsyBsIAekFafAVwBKehKd7piozCUALd6QVsH2M8Qw6sPZiHeli1xJmFosPtJPglHEKDGewKy+D+57ltcfP2VrB+TrIFRaHH5qbezf3wVzUUO3jxjvU9yIeQBU5CBppKErZhAo8SQl9htuiZBcRSJRyBZOLaN7nZT0BfMAn6NZikKw0U+179C7Dhvu1W8SisnQhpLHKoTIdqC5iLpW9OAwbSXy55kWQYiHcn45KDBSmt0p3tI7Ef+XP98gWRDjym6Q/L8GyrSB3dLmc9aryA0BrviNnnpy91ZIK6ED9vKhduHWQ7LRBB3u/IiWUpeWjP+yculdJzab+rbLG7oP4P60w6ffP3Xedv3PyjtTzvcaa1j8daI4v5kQzL2gpFIvCS58HVlW/J3MjZJ/EkuRkXZYU/i53TTTgLJoijtl4oiqhMh7AXLi7ECY5T2A1Sni3ad5wwky7uc73zkVJbsjtBK5qSyL8b2jlxZODaExU9JCYYCyHAU/XVoZKnmEixGgsOYTapudm7LIq6VUJ5oFnHF7Ei7OvIcP0A3mj2/CQYjTl04DsAju5bwocFRvl63ze5sBECCgyjM0iySyTPBRSDJX1XXTLbx3Kh6TYRFGPV4CHSng6rVnhfHAT0eRvrmSx9MYCDAAAAgAElEQVSCWh/eoKI0bRHbKvMaTBqPQqWcYQlsYxBOdt9cpG9cK2FFUYY/AOHXslEGYo7Kdv2eYC4jQBJswZGSMh6gnqhT2852a88XfpRKk9paDYn7UbWqJLwNcm50EC+Hc2jm7MNRWLZSV3BQs9KxU7WqjAVAuZTt5kkErG3JZhBFWZtjQxyjknimZF14MuaqUEg9QckYhmULO9d3VXBR1YrMT9746lmCMI2i1CX9XKR/ilPYMXUM6b5cwq53vsbm+E8+m+IqACbee0aKu3Ce3JFhKKAXR2Fo6jVrUxfrAx//HAAbP/p+Cq0Yv2oxdNMT2e/dQrbjJ/f1PFmIswLJ9r7lRGrjIb4J0HK6Ma0FNv5509xwxue59IO/BUDldrn/v4mBSHbqYjF7/nNEnabZvU0wVPCStek1eSxHHlClLZVmIS9PymLc89YO3z3nc7zx7g9QLIbccMbnAXjfBwR/UL4tl67PpKSfHU6djJlutw9ZjNoPsiOTn8OjHEaziE9dk7qGvaEi2oHClOA5kgDXJJhLhTHOpq0ZXwkZ/iDDQyT8yeD4ouEUCj3zmWoCrpu+lNHpx+PNK1I86HFwfYXauDy7MOXjDxQojbfZeZ5EnQanNfnuOZ/jsss+RPmuLWmQm3IdEzLuZ9nmlUo9Dz1tuRIP+TyySqnetWfbqCULRSjGMXHF9O3hLahiUVyqOa+RjqI06jSftqH76lOpbJ8h7BNBard97nny80x3xo9Iah8b1p05mqM5Oubp2DiGKEApplcJO8tvMTuSwVUAPbiLpZfamfoGvTgKQxPnaoZXi09940ffDwgO48rdZ/F/N21g6CZzoW3LzgmgM7VQK8uccXs1r9Z5TTqb6nQWm1wHkzZ9L9nP/E/18e6RD7P0Y4KsbNye9M3KMBCQyztggZUkmbGkbknPmEjyG6UUWqke1VspxeS6TP3PYzkSHAcIlkOfJniDmaflCLX8God3f+vDLN/joy2Xd49I3tLyb+9m4odLWX57Zkvp4YXeXUrZlinoc5hcHUl/LStLGxBnc5nspjOrKsQGH9BYLn2o7rJpLQXLT7ATBu3pw7wHn2cDTPixVKZthFbGk6UyRFe+OJL5PLO6zMwqi/oOO51ngNqYQ3OJYp5bZfn3BPcT3FPi3d/6MOFvHqB8T44vdYRHK1MXhtnHkPz3qaHZIljQR1S2aS5yaS+UZyx92FxnqSN67r7TXBaEddoj8p6VpgrEz/wbKRRm0bEhLDQQRWk2Y6cVisEml2vgyaeWsLQRc/Dpfggnep1KOeNfQqU9NvuRzNxLDSryyt1n8ZnF9/ODm8/MCYFIhE2S2j5Z/LOTpRgKtlfpm8oMr24T9m8bot/zcJs2f77s2wBcHr8u+30P5DD33GQxhGFPdGXyPZAWjMkXnNFRlGbKBoims3wWeYNV7CiaBuxVNohey4twm7GpJqZwm9KP3111Ex+det+hx4XE1pC3OUCa0GX2+JCUVjCfZ3+X3hdwupo4TJLcSD4LtxVTPGiltZ2Sflohhwqx5J75uBgz3ukGkgCPkujg2bzlbEdOV1OYBqcTp/MM8ndxysL2NMpA1pNxfN9xt/NP0fEZP/nxy/U3nev8c/PXpt9rtCVGzfz4qTDG8hXthYr2styYm2Q7z5tLMxYXvOXHOCZjvuXFPUmkno+ODWGhANtOM2sXJx3cgpsmAQFYv3aM/XeuYMG9MThOj+dDJwf23C7XXRClKE//Hslq9X83beAHN5/Jk+/9HOd/yoRb27a4npQIi+S+OrR77SKG3BUtvAN1ugtMnEPBYnj1QeJiH0HN4g2f/x0AVliPpvfv0SzINAtldmLlOJnwm5VWLxEO6VnXUijsNJ0+gN/Pc2oWSR4Mz0RZxUVbYl5akog3gT9fee1lLHzLLviy6tUALGPk1LpXs3BMdq588hsd99oQotz3h9EswpJKNYukD05b4Q3pVLNIcmvYPoffPZOdFQyG3k69a8KDaGeJsTYN2U+yeeV28LCk8PuhOG3hrmjiHRDNwm1ZeAOKqKgkQXBuHP/y2gtZZj+ezZ/KjV+uv0kuip7vDqdZWCqzWSRk22hHoPcL7+3ibc25qxOb0vMF2lkKb0ARF6wUQet0rUyoHgEdEwbO+sBSfc66S1GPCTZBa83Tf3w6S26LUwNX4bHtEIbEnS7D/1LmvtslX2cwGLHiOxq/bqcQboCVX9kunoN6LcUuALJzW4qbN8s54fT73870jn5e9pItLC8f5Gv3bgRgaJNNcxlYJzSp3CovWvu1TVZ/ZEomOJ81u1hAN1so10397affIc+88enTKBUyt9aDZ10PwC89/ia+ZBLevPLbH+btv3A3AD+4+lxAjjuFH9d5z/tu5u++ej7ve+fNAFz3qddz8W9/j1vPOznrUxBkL1LeO2EMawA6iVQ8OJUa+3S3m1raE74PXL+QRlsMYKuGD7BhYBc3Pn0ab17zMN/bkZVMnN7Rz2tf+ghbp+enbS2/QOvHIxSSpNRF8IZkfS06a5yx/QMALBkWVb56STd7WaJI+E3wBeUkVsS4dNtt2l8TF1DFzdyUGwZ28c+7ZWc/fWQXd2xfQ6kQML1DDJErTphgdOcItcE2/f9Yp7XQvOwONM7o8vZTfsL1j54JwPr/sTsTio6d8ZavG5Kmz4skFiiO+Z9338KlX5B8JPNfvpuXjWzj6z98GZU1sgaW9k/zxFNLsGfstO2cxaM8uG8pp4/s4qGrN1C+WLxrYw8uojqm6CzQlPbJnHZHNMd98kmpo5rLZ7Hr10/inLc/yF1jqyibNVZxA3Y9spDClEVhBprLzYYUKdb97W50o9lT8+bug99gOtg3Z+Ccozmao58dHRPHEG0pYtfGNpJcxTFRX0RcENVLGjNj2pn9o9y3UhBcLhAXisSuBIWlpAwIJ2/IsiXCD9vm9PvfDshOf7ZzEWf2jzLmDeL2i786KlaJyjEj9RaT80QdnVc35fa6uSJDiRHPBKklhsiv3b2RU07awc1nf45VbpZoIXnuNzdcy+vu/QAgGb4CE5rqmaCoefUW+4ZrfPrO12Kf2OHTdwp8vTZP8ek7X8v67mjW1fwuOLvattE0kghKbVRc3e1mgXVk2IWZB4bxFssutcvtx7Fibj77c1w1emGqFQGc7VzElqkF/MPx16Vt28J+rrj3MrrzDCuLQkaWCW5k/P5FhPNkRxx/VtIJHudnMHpVKMjZvutJ3tUEoZtkV1eKiSmZh0IhcxM6VsyfnvBNAC797qX88L99klVujbMdyS36hXX/yJtu+R1++9LvcI37qylv3khE9bESX2tuTAs1p+H73S6qr56OpfZ9VByLOz3RLAquzLfWXHL3b1ARDz8TU3UeKy7GbVoEmwSFuusM6Nvs4nQ07Rlpu3V7P4VpxZaNAVagGb9fxsTtKhqrY+atPcD+Z8XmNrzqYJpSgDhO3cNOW7NlagEfXv/PfOKBN8j8uSFu08JpS5Fs11S9q45pyZbv5TJl5RMNHwEdE8IiKoI3r0g1SSEfSfm5rzzw+rRYTLlURPsK5Tt8c9fpado0gMv/+Uq8QZVGGoLAkZXWArhq5MAxSs6ziZp6tnMR953+DV7+6JuZ7pTS+148eiWLT9nDzmdHYIUszvboMH2Vacm+nE9+UythdbqygMxEVnY6PDmzijfuv4xqKVObk+e+MbwsLVV43zu/wmn3vQOAljFeNUeHsVd3KW0p47RdQgPMbC2LKO1ye2w2mPyVwCHJb9IcnEZYqCiCgptFHibHk4TvcSjtl7759QJP1gd44/7LCJ7q4+zmRemt7zv9Gxz/9x/gjY3L0javW6B/QnNwowibgQcKNMYlFqNyACq7E9uS+YGVs+eYPqg4Fp4SdGuSPVxbOMY7Eea6/mR9gMuWSR6T6pjFG38i433f6d8A4KS7L6O+J+YP7rqAvvkW3RVyv8H7pFhVbDsUJ80L4zjCRxxL2oG8obLggu+TxI0r100Bd9bOEgPbZI0cLNR5cqDGvK0xvgGdde4fpH+vMSzqxLgreTLH713EfC+mMm7W+f4Yf0LRmBxhYI/Jd7JvhHnWhKk8l9kz+kdDdt+7iD/YdQG1zUnuDKjviHHbMU47xm2Zam1t6YOyrWyji3Uvcu956JgQFioEtxVmluoo4qujZ+E2dZqwlzBM0/XfccqNrL/z1wFBahZaGu1AayKDOqtgRjIBeWEG8QUJQVYxL3uJ7Gpn9o/y8kfffEjCXndGsWt8iAvPvr83YW+wWizric0ijFBeiI5jeQHNS+idLLDg81dt7k3YO7gSMAl7h2Q3efmjb+b6DX8PwFt/3Juwl1MkfD0xVFZNwl7dYymPDgH3pDS7IpnhM/m9muX1mTlOYxvlJEnYe/6qzdzY3cA7V96f3vblj74Zf6nPBas2p23j3X7u3bme0qgs3M6CLGGvN3Rowt5FOobYSscRpYS/MMpASukLq2kvMlD850rY6x/HhWa8X/7om9Pxv2nFOaxftZu9d67IeJsPHSRhb2wS9hJFwkesZdyi7NkSkp7lBk3nO46Zv2EPnS2SsLe9KMYa9ujszifsDVHx7IS9Xpqw13umwPTaxCsiCXu7SwLQJmHvkiynh5QKkHt0B238pb4k7D2YJex12hZhQ1EoWKnToBtZ1H9i+pDMuY5/qli1Y0NYaHrqQgA02iUGI7BMghi0Tl1NT/htvI4M5N52HRVpVKiwvN6ALZ38Jm2L03/Ly+IpGfMGme6UeMJvs75QYW9bdi8rAN21Ge/2pwlrxrv92a6TYPHzz8ipdOWKl/0mR8lzlxQnmQpEuN03vZz1BfmcpCyQ5yrqlS6TYY16RdRyL6xTr3SlaE5C+ZerkmvPGzir5oVodyXbUrkkyYFmqaFx/ihXiilXPMa7/ZQrXhrcBTDdKeGWA1aWspSFroq4P8oS/MQoMKX2dCki6jjpZ0ACzvJCTgtfhFHKr/KMd6rVSX+H2zvOyZjeV16ejvd0R8ZhZWk/cVGzpDLN/hxv2oKwqilXPDwT+KbKZeGhVESbeZZhNMGGJn5IOpfFXsyvNNheWJD2rVzxiArl7FhciokLEAXZUdktB4Rlx/xfSPsWFSXpEaFK3ceESo5mli0etKQWratwywFLKtM8ae6rnZioYGEXIPJJky+r2KwNz+8tlm0duWpxTAiLqAjdkQL1xJIfhFz7ki9xxe1XpLVHa6Wi+Mldl9/beUGahftDg6O8ZOgDdIeyxDUAulhARTFxpYiazmX3VhbKsVOvh9vvcd3Ga/m9nRewt13njlNuBGDNo+/nJSdt466tx2GZKt13bT2O4ystrJl2dgyxQnSliNXqoIsumBcifFAs/3etLvdk9w6mjQ2hFEFDrr3+jVfz8kffCshunDxLLw6JNw1T26OYDoalXws03U3DjATbswHMxZ+ofEDR4XJwOja66KJakgZQF80xpG1U2yfsFDIe1AoEtQJ3rS5T3Fbk291T01tft/Fa3vN3V/GX3V/OxrxrM7gLpk7MsnsnCW8sj1wOzlyU6CE5OH0oFrJ+GM1IOTZ9m5PkN1kXg1qBr+2Ruaxsd7ire9wh2b1HnoYfDp5MdVilYLrhB0ySou4AAzvMi+b7En/S6aIHa1gzxhARBFl8Rz4HZ9FFWYpH7lvJ0h3CZ1hy8ccGmDca4bbkGWG5QMUcQ5I2b6JGtQF+vUZlX0Rk+ta3M8KvWViRk2b3tgNHxsEyWo85OtZ2+TQfrvHDfSfTv8V4eWyb+liW3dvxTMBlLGtDB35WWDoMfyrNYs4bMkdzNEdHRMeEZuG0obqzLWoxglr8tZs+wNJdIRMvFYk5/zsdCQryfZ64+RQemic5Kq4GloxF1MYkFR5I4prhPY+jHQe1q5Mlq1USKqxDm6FNct+oWOXi0StxZxRWIBoFwNPv/FtevfkCBu7N1fJ8poAae5bYDzLgUaxRMw1JhNpy0p1n4CnRRrx9BWInwz4kCEtt21jGdndx80qKBmH5/d/83wC8+rYr+fgrv8Uff+stTJ/pMf9W2SGCqsJtaeIcdkTZeYBaLoxcKdRMAnowIDI/QHU6xL5gM1QrAy8B1HeGWVq9kkVUUHj7ChSnYjqTWbrqi0evZHhbTHEqV/80gsarWnzx7C8DcEntN1izfC/tv12MFYLdNUmBS2bspmfSsovK5JfoAaCZv03H6NuRlBzMpiQqKPwJub44LfzETpGLR6+UedgB1YmA6CGX2njA31wugXOXlC5l4EGXgadiSpPmvo1mmpZABYGMUTJ2rXZvGLrnyThGMUOPLaUwJd/17RDQU3mfj901+TaLisJ0iB3EaVvpoIXTjQlLFpWxLlPHydjuPcPCH45Ys3ac8C8k07vbsojb7Qx0aMLr3RmP/m0u5b0Wlf1mjVuK0kEf5cdY3ZByemyC+MCkeJuS3Ck529WR0DEhLGIHwpqLm7jxEHeif8884uUmms+x0dpB2Tad4z2KVZmckxaOs/snUpHss0u/C8CvLFgjiWsOV5EMwHFoSjoKonLM4lP2sGt8CN21eclJkmDl1Zsv4Icnfod1P/kArjHMBf0a5g1KCbjZCXtnVSRrz5eJ7SzSxE7OIJfk4HTBNpW7Fp4xLl4X4G2PvQeAt5zyIP988ESc45ro7VXaC8wLZklo91Ate3HzCXZmw3dnVyTDVCRjVkUyDN/dQTsVFkFFEZYVnUWaqGDRWpb1Y/Epe2iMLaK1NCecAtCjVf5swfkAFHcWeDpYyOCwheWDa/oelOX/eq2avgBJRTJmVSTLJ+ztmMzr+WNIWFZ0h+XauGDRWirjvfgUyWU6oRZSPuCYSmQOf7ZdeCvtdOkOSwbzJDFuOUnYayqSWUdQkUyFEa1FivpOk3N1SNL6Fxou3SFhNCwBysHu6rTN71O4TWWuLdBeLPft32phdxyethayaMA2c6LoK5cPqUgWlF06IxbdIbCi5BgCVuDidCKwFH7dTddFob8PrRov7oS9VmhqWibGuChi/7YhlrZiVnwhCQiK0liRt5y6iRt/9FIANrVWsKwpMR2SXBdKIIlQwlDOacnulLMEWydIfoeReoudz45w4dn3M97t566tksJ/4N4C637yAba+63Oc8UeChyhsnBSpnE9yG0XZMxJLOtBYbSZ/5RTVYrYjHWjIS14qBDSaYk/Y+ewI554q4ddPfFGQqf/8Bpvo9iG6a0JKMxYNk5xm6CGbV73/Hh7/8lBuAPPBXL1Yk/Tsn+AVEj6TMUkyRxnNorFcYQUGjl3TBLWY/pVTTJcHWHz83vTWO58dwV4ZU187lbZ1fRf7oTpj31oJgFuE6KDDvAt3sfPOpanPP6hpKhsOwjdjsHTGV8pf7/gm/UqSI/XaLGKKi8VT1ChXqa+V8U6E78D6SZoTQwTHdyhsKWa8mZV/5jse4f5viC1mIEFHxlHvPMeGJx1nBmEzjjoMaa/zaG+XF7C5Avz+GLdt0zZZ06KKJirZgrMwbf5gjDtjEfTFlPdlniK7q3FbiuCgw/ir5flrVk/Al2PRwuI4FVid+QUaK2NY5NFA1pJ2JKeI27JwOk7qDSGG6gMm4c5hDPJHQseEsPhp6eZvnJOWFJQCQLFJ1y8Dc/J5W2heLRmuksQ1symBcE/Oq8OKkJu/cQ5WQGrMBHCnFWf80QfY9HuSD2P1rb/OosZeydmQ5HaItWQm6nR7FvmCe2Rn9saGmMwt7oop4+cPKAbM5wNnRTz8TYFSK4Pfcm4ZhDIsuNPCimLiZ+R5X/uTv+Adv/sRBjuPZjfNGTVnH0NIVOc0j4MJ0DPHkNnZvUceDtN4jbCkCIvSh6EDmsmJhdmFK0KGHlN09mZCyw1hcGvI1HGyrAaeFmPdzOaljDTizKevgQcH0J3tmaDLFVPu6U9OWAw+aY5wOdkYFhX+dvFgDY7FNPaa8TbYmPDOIUY2+6DLFBpBWvtz4JkQu6vZvPtkBjrm2Z1uusmkY2XGTvtB7zHEBP/pKGbk9gK1saRoc5GgrKjvCqga7IQ3YFGZ8LGDmOp4cpy0cLoh3UGb2o42ti8aoNuKCMsWpYM2xRkDlOtbyqA3nmphCX+V8S5Dj1Xwdpap7knqzUDpQIjTjbC8CKctx0SnHRG32pLJLLcpz2X3nqM5mqOfOb0oNYvzL7o7PYbEwwFg9xS7AVC1msB26zX05NQh92i/VjSOefUW7dFhzr/o7p5jCM8UCPo1hY2TrL5VAGDbXvsF3lC/QMrZJSi4XGo5VSymmox48zT9Kyef8xgyZY4hNFxO+1UBNyXHkPgNk3D7EHvOjSlNOHQNuOlVP/gtODdm6PsZniKfNFfNOoakqfAScJbj9aSSS4rnaGMI3Xeak2IR5BgifTg4OsDi47PK7e3RYQ6erKmvzQBnXd9lX7mOa5S5qTU2XRNIZvsWbtPYLGrSVr+tnPr502TAz1VkSGsmTzD2np5jiKa4WB64d3uV+tqDVIs+7VFxNTvnHuSAP0TrrA7ViczQnGg/zeUxtR3yuVYuCR++j6rXZJ4hTQSsbasH7q2KUmRo3yt8bF/uPXmCKTVpuT3HkO5Q8TDHEIegL8bplDl4koEIbLcI6or2Qk15n7GDjGiGisVD4N7NRSUOnqxhURd/S3YMqe10cVsOTkfnjiEuC56qEINgNhD08U9jszgmok77nRG9sfor7LjiFACGHw2pPbwb7ftoEw35uvvG+MpnXo/TgXn37M1ycA7VUeMHpIJUs53es/GlCp9c93UALv+EWMZb5zUJDBpy9UeMALEsMQIGoQFcmRd/bC/MGzwkB+dNd32H1TdcxtJ1cn7vhg5Xn/hVfvujV9BYYtNZKOO59jOCKuyBYkNvPoMkOXBfVYxqkNYczefg1H6QTnCS3Xv0XSvF4Aq4a2dSSPn+bdmxoLy4yePnSGTrutsvAWDBN0rMLLPp2xmhLWgskTevsUZU0xP+cFtmxLNNkqFiIctvaUhXSqiD0z15OdEa3e5moJ9OJwsVz0VLJnDliV89Lq0Ap86YplrymXp0mIFT9tPqyn2DpyTS1O4oVv3t08wmZVkZZD3JE5qHubc6EmlZqYihIhfFCmSlHIEdl56APmsavamfzR/8LGv+RYzNhc1l/BM7DH+vSN+zsu46C4rMLLOZOc3nxP9/nNgYiFWlLHieTidL7WepDIGcy8GpwyhLiZDm4JR0jklGdZDNoLFxBdpS2F7MzDIZ0wVfeQSrry7H7SQmyFLgeWKDygkWgK1/s5qRm4o0lhto+R7N1hs+RWNq1xFJjGNDs4ilCtTwozKR5Ym2DHaYnR+v/t55LBmLcJuhZPQ22bmtGRsd+KiOl1aQAlhe97j4+islhN3kUuxsqtM3pSVPgSWTS9eTGIBIEHsJECf2A7GGJ+d7QHU9Vt9wGdvecg0Xj74SgMf3LeRt3/8gi2wlYJiOkeSJ5tH1eoVF8sLlM181M5BX/llaa9npwjD9nfYDVKXCm9764/T3Nz59GoEJmNj2lmvS9l96/E2svkFiN1599mMAbLZPpj4mtgTb09TH5AVOjI/KsTOjgG1ngXNub1JYFcfZ9wlpLe7tHOgnrQ1aKKT4nyQbmfPG/aysyGbw7P55BKHNha+7k+/tOJH5fSKgz3md2GZuuPncLDva7CxXVo5fM95pXEeSVt+2xDuWtCcFgh0nFeDDr9rNnuk6q14zyuobLkvzoQy/Zg/721X2vMrGMhqdimXsrKgAjp0KRWWZ2AvHyexati2Z0ZXqaVMJf+TMObYtdpOER8TEs/9kB38gxmk7FA8aAWvyfWJbvfldHAelTCKgtJatZmigyb4ziiw9dTcA25+ZT3DLi8wbIoNop8ll3VaBotub/GZo/QG8B+cRuy5F10GFZqdN6jS4TibJgetW3sr6sWWcunCc3bcJJqOzOELbUjckU8sdQXsGxnOSIDNtKzWZpxPsOCxdt5eLR1+Z1Q3pX8mPh9Ywev9aQKWl9JLd6pC6IUHOoHiYuiHknqVA1HDbyjI9m89f3/yS9Db5uiGJEAM4c94OonVyv18ZehCAh6unpnVDJNBJeEsyVesgyDwqpqSgct00IjNlvViQuiHMIjt7cXQYpu7q/H2ThCsHn5jHvopAyJ+rbkjSz2gkzMolzK4bog9TNySZx3ZXNA7HkaNDmDP0+oG8lGbsdzyxMKsbsm7vIXVDmneNUJzurRvSHQI8P1eOwHgsktodyTiauiFpW+p5yQkvkPVh270pHS2b6pimMGOZuiHmFkEoxzats7Ex/UnrhuSmZt3gPh7bMcIOVwzVtTGLfbmfPR/NGTjnaI7m6Ijo2NAsAOKY4oxIWasbCa4iilPX2b6xAZZ2NG7L+LfNeV8lhWXCKEunj1QKi0KLR3YtYaFBDhYmbdymgHfyBWBUEKbBWMpEculYZ3iEnG+9Gzo8vm8hf92/EpDYlM8+8gqGuhoVQ9hMQsVz/vi82pxHzCUqevL82b/D4B+0zuWOlM/RtMspJ+0A4PJ5/5rmzDj96Y3p7f9ow3e5fVy0qq/vOxsQBGmisFqWxAxAlkeDpDiNMAHY2RjkI12Tcbdm7Tf5qMYk+1Vy31k2C6etqKxp9PThR0vH+dDgKM8GcmzaslQCtCaa9Uzj0fm8n3bv88yxROWjbXWc8ZKPuEz4NZ8Li1pcPu9f+f7iE+iGDu9Z8K8APLJ4Ee9Z8K880j0RK4h7x9FEyvbk0pwVHZrmU823mQjqPI4kvSYX8Jjw6g0KctfywZuf+03Sr5ztMV/QKW+TfM+Cf+WKoRMpLJKjX7dbS+f/SOjYEBaWQhUKHDhFFp4VlegbL4s9wah3173mGq545ArsjkVpeylVr+K+CqrVFoNbLnnsjw+u4fJTb5dAs9sEVNX3kv3s3yYVyVLD3KwiQ6mBc6aRRZcmKl6pyNUnfpW3ff+D/HhIXsLPPvIKtr7iS7zsW++nscyiY3AaiUHyiIoM1ctZkaGkUlqpKMLLjjL1GtBxhCoWKE04PKtcdzQAACAASURBVDWxGoBXr74qDVZLAtUAXj15VVqR7NKHJedDPdBMr7TpH42IbUVjmcECDJpF5WSQ9XyRIXW4IkNd79AiQ2GUXReGOb5ziXWNsCjvVUR3yHHj1VPSB/uJKut2X3JIRTKnCzjG+PscRYZUMm75IkMgWJNiwRQZSkLiw3SekszqxTvrvLp9FbVHilz9m5/OKpJtdXjvxG8wf5/G8mSN2YHD9EobbzgyaQq76fgpx5Fjh5MdY3XCX9Lm2BLmnmSTz6cMSAycpovKdRl6IiCsWthdzfBPstojaV6NPL7GCBCBzmfC/L23/gZLHotoTAoupbIvZk905A6OY8Ib0mfN0xudX0adJIVzDpw+wPC3NqOjODVkds47g7F3BKz7RBMOTqf4eFWtEs80UJVyVr8S2PfWk6UYUN2m8XYxZs6/uozlRcRFm+LDo3KhiUJNJ8tMZjw1japVBZCTFJApl5h55RpiW6WJTZyuxgrhrr/6W8595Fep/qFMhPOE7PrYWYYvINstINMsTC5HIPO8VJIcC3FPkSHtieuzdW5WZMivW6lN0sqbRCywgwS6LRd86xN/wYWb38X/OfHLLHJqnPvIrwJQ/QPD9+PPZjewlPBuW8JHLoGxcmyZm9lJjf0gfXl7wGtkKNGkrXvmGrRjPg/aaEviO7x+K93xBGwHKtJU7t7KIZTwByIAHCedUxA7hvb8NMQ7zW2SGJIdJ7U3eOccT2eeQ2kyIqhJxTaA4nSE129T3e1x4KNiAL9pw99z4eZ3Uf7zAQqPjGZrpOCCsnqLDFkq807k2pJ8sHnSQdhT2CkZr/i4pcQFByuIiKoigJ17nxDPkzGKps8ydXtJjNCGpt94CrUdHUIDAXdaIfdt+iwzrbEXjzdEmexV3ojkdJhaB8NFyR+Q7OrNJTafOvs6rh64CLfdTetu6nIR1e5kXoMcNRc5eIMqrbr17pEP4zYlK3Mp8eUnO6dRtZOQbdVyZCLCDH6sikUaS2zjQTAW6RgayyzOfeRXufPUb/LKAank7iQ7yGzNIl//MtEyyqVMbU5+VyyKl8iOJSdE0m4yXSXxGwkPCVm5nSJGpa7R8gG56PwH38uDZ13P6fe/l0rR585TJSXdL/Ubvt1Ms0gEnSq48uLn3aQFVxL/FHKYiDjOPDgg90leZK1RidA0L4gV6nRXV6ZKsxXKcS7pU9JPFeYWfn4884LB8IpSWfyDZYmGM6siWfq/46RZ1q0gRsXyf2OJm3qKrCDGiixUGNPZJHn5ztcyjr84eJkY4xNPkTFOqijKMOVKoQiFr3yx5DjK4pXSinRxms1Kka0J5UVYZhxUkAgcC9yCCO5sRNLShSJ0slqzVqSx/BDL/N7yoxdhKQCkM0Fd2Fl9YzM9+yaaz+TJMZ/86MVMXGCz5s9Hsx1tagZ0jG40enbwznxlihTrtKTg0o89xZ8v+zZv+Pzv0H+TqXqdTGCyeDpZyjE9PdODn9eNJp2FGqdjpV6PsKnoLIxZ9Id1XjlwKbddK4Lp9WslSzdebxGX1JWYpIYHVK6IbqrpNZrZ2TOnWWBZ0GzRHczu6w0oYidJnZ/j1ybFfSRjs+DPirxy8FJGJn1QxVS4/cM1f8WFf/xRSrdlWBUxaijwpBwB+UrdrhSjxsuWkNYG+p7moggOb68xbX6/k/LdHcr60Bm2UiGhrUSIWBQ7mWs8JaXSyFWiKOMneSmDkNjzUOYlTHbr1FuVg3d7Ay7dIYUVOuk8y8UOnSGLwozLqm9I4arw+yVeOXgpf3z1Nfzpab+YVTE3JQm1H6D8zNWblBTMt/WUAkjGMAjRlngH01oxtk1UL6ILFmO/WKazQsb3+A9IH8TdGmTPCsJUg9U571tnyKK8r4A3YI6GVlZv5khozhsyR3M0R0dEx4bNor5Ev2zFu4mfGv1/7L15mF1Vme//WXs486l5SGWshAwEEkIQwqQCEVAxgiKgDA60IkMr3m7tvtrDvT9bW7vtprttacWpEUUEFDAqIqICyphAQhKGDEVSmYea68xnD+v+sdYeTqWAcLX7F59b7/PkSdWuc9Zea+29137X+37f71cdkD57/8cKup+tqmpUwNi2K4xh9N22lOxataevN8GM31ZxMyaFmdFbrnv1y1CrhTGN0PRqHuh6/ODJ08jstqgtqZDO1EKGq5ZtPuUug8I8n+6n1FcPngaL/6FfYTOCoiJfKje9rPbvATLwgW2Ps2L9pQz2tTdwRl5+umrsB+tX8KnTHgTgq997J8YKhSjN36kQiwfOgI71gswV+xn92XRaVikgTf3b00h8+ADZa2XEPu04oecg4gFHiLg8WlRMgv2HlOtqGorpOcBElDRSdu0++qsKKn3/liW0NpcY7GunY/4QAzsjWr3Mbotpb9nD9l2RboiVcsk9niFR0HwYaahrcepPf/gu/vaXlwDwufN/BMAd554ezaPnRfEj14vGEfS/UmHzvysovhkr+W9tLjGwR7OSvf1fOfO+TyFtn4wuGS8vqLN47j42757GnDtMyl3quJeEeR/cSt2z2LR+LgCLvrg99OJCcBVEGBPfj4B/ARrT9zjlNwf57pPKkxQZl472AoVyissWrlPjfOEUZnaOcGC0KTx2XevT3FVYwk/3n0Dtlh6u/3s1J59dt4qmX2WotYuQSLjWKph16zZ1zarV0Dvq+9slzD5pLzv2dWAHAe6aRTLtUB1KYw+bmAtUDMxzDRb85ZDy/AKP1jB44tBdjDmH/nhiFv83Vm/6w7Sz9PhdbB6f+6qfcTLxcskjsxXrFWv42fa7aEoe7j6vPG4zG4szVfvNkuARd9PRuQLVsdIMSUvs7wk4nPL/NSyUAniNz3356XO5aNlzAPzHiu9zfsbhbPtdPLLkx1yYe1v4uc3jc7l94R38TezYSD3NDhagqUWpTBPUOpQr/bdPX8RZp7wY/gxwbH3P6xrD505V0pCd5nh47PyMw8V5JZPw1nXXMHvxAZqS1fCarjxuM48+toRjlu/FZVrYt2qn4NlnFtC+YIg3nKz0aYs0bhknmqxNPudbit0NfbwyP8Tix9/Pd58+A4Cvr/wOf3rPR7DKgu+OqGP3dZ1AYTjLE+f+G5fyyXBOLNujPE1Q7fHwkprPottTyFj38I3A7Qvv4APict4xTSFdO60Cn994wWGfs17IAkPqBRGUDtRjsgBHYEfFYuFbBn42GeLYpedRmuNR77NC6HDSTiCoI02Tdy9+jnuck8LvO+ss6nmDSlcMQm3bas8X0J+DevvqN8d9fcsA+PmKr7Fq8FoumPuiKiSbpzyW2kCCSo+kuXeU2l5Vb9HcO6LSgtVaVOykz0FN613oGMVgX3v4kO1wojL5C9aoNO7NJ93BtU+pdGZywTjLupXnsLGtJTxXdbiN0b4uRHednX3qDZ5vEwz0dbHYeblhrNFkNHJwHl5IZilPqFZTMOGw5kT1O9WfYHVdze3a3tl8wfB5ZMmPOfv5dzVohKwavJaLNl0danYA7Hba+VKLQrIC1Do8cjPVg13f2MKj46oMPzGsr0fdOayQLEwTBx5FMB7T5KYt5wKE6lsAXzD8sF/nrfkUG6/4ATucIqsGFcz9is4neWbPCfztxT/l083XhbGmWrtPdrfBoGhnSKqg5SJ3a1Qrks9FC7Krg5NuTGcjYat5dAVPb51F02Z17940/Vy+marh9eVIa8zNZ/veSXavwKrIEHlcHm8mNW5w0aarsUxBol+9LoyaoDLLJT+tQCGpsDP5zmKYJYnXezT1wUWbruafF/+Q69dfCUDSdvH6cjQdFBh1KGnOg6b9Op7kuoggAxNkTY7QjorFAqEWjGBdF0Igk4rsoyEAo13tGcmRBhJcaZlIk1DvUzeiPh+PnAcq2oYIJQXn2jmyqXoIlw7a9a0kvuWTTdZDPopssq7bFVG7QRBwwrmk7dOUrLLDKTaIDAXnnWeNYWuxnGyqTk9KbYs2WNG5ypYES2LYPp5OMUoLsGRjOjboBzSCvoJ5iP/fcCzqc4BdkJYE7eYXqkl6W0fY4RRpSlYbxpFN1cnYDvOsmDQkuiI0wGFZkpStg4embjv4DBzOLB2qoMcyReE4fcq6uMz1o7H3to6w3VWM3r5NON9BYd08awxpwvZ6F9LQ86f7Jk11nfAn8cLj13ji/MWOCSEwE36Yui5XE8xsHuNgTYTjLFSTSrrWiMbu26oPGduhZsTnBIyqQcp2KdZUo8EcTjRpKLnC7fUuanpuPM/ArIkwbR5oxWLIycfwOmwqwDllUzZlR2RTi8WUTdmUHZH9XtsQIUQ/UECB310p5clCiDbgLqAX6Acuk1KOvFIboEAkhhNV4EkpMcdNjLqPUY/w8UHu+JmxXuhXkSqn1cOoSwwnIsPVjSigS9wtD+s8vFC3M1BRf6a1l9np4RAubdYkZkUwVMiGVHhDhSzN/qiCFAcxgKAuQNcfBJHmIOtxwZrrX0FF/UoePFXR9Z29+pPYWs8iGTtXalBw/cUPNaqoP/12PvzBh3goNUFFPRjnK6mop/XxSkVVI6ZSKrI/Ad/R9IbBUEV9ZvMYS5r2ccGa63n3/A2hTitEKup/svXK8FipnsBwCFXU7aLF2JDKrMRV1HvmqcxPoG8aXRtfA+EiFXUR45+Y1qIajquoL2nax2c2KxTqeadvCOc7kIn8k8SVFI6vc9NL59LsSFIKJkFizKRwUpXLYyrqAVGwSKXUfAakRgFnhh/j4PS98Hrfdvq3ueYlpaI+raXAkqZ9vJjrbVRRPy6nVdTV2N88XamoL2o5yHN2Dz2nRCrq+e0GY6UO8lrcfGysg47E4GEq6m5GsKjlIDe9dC5tLUU9Nw57clmEa2C4Aien7oux+YLuVBIRLx0wTCj99+IszpFSniilPFn//mng11LKBcCv9e9TNmVT9kdu/xUBzouAs/XPtwGPAP/z1b4gg2BS7C3jJ5V+aRjgjAX0elJjuD0agYdaIePBo9AOC1IZgMrnn/OCSlXde+K3WOVeS09qjBnJEaUUhkLFSVsFJOstqo1Uwjm8zeA8oOC1gYr6+hWsPG4zN590R0MQ8JwX1Jv44eNXs2K9YmJKTy+GAdYAl5BKOFRb4CvrzkEuqPGVdecAkG0WfGXdORzLwOHnn/CzNESoEN4Q6DSMhj7HbWRTB/5Mleodq6U4WGvi5pPu4I6B07n3xEiMepV7LQPVHA8fvzo8tsMp8o4n/pKaVmys9kTZkD0bp+G1O+HPAIvon3wMuu9AAx/DeFW96Z1YgPNgrYm7ltwKwMpf/BnfOvc/mWeNscpV2ZCHj1/N8b+5gf+45lt8+s7rwr7VOn1SW1P8wF0BXmwu4oV+rxbgDObR97luw1VhTc54NcnBWhOGI6i+qDypsZNqZF+2scpQrqtjvzy4BGvEYuCMUaQRzYnpKKq/zPwxiv2qs9nexiByYIYDA9Uc/7HsjjAb4noGhiMwXBAuIVN7do+Y5Jp7k7T6yvb7LhYS+KUQQgJfl1J+A+iWUu7Xfz8AdL/it7UJX4LrN2wZrKKhcOzBNiTAzvuSF8Z6SOzSSt+tPobrq8hvHM4Q00aNSET8sAT4tkWKbu6tT1+PszPLC209SntUSwoadaXrUSimQxbu0WIavGLUfvC/74f/B+78p057kI3FmVz71AfCrAcQbj1WrL86VPqef8d1PDdzNgCpYfX94WKa/BC8+13PsvruN4bMWL/69ZmsWvIsz6XmR9gJ348qMeNl5FJE1H1pTQYTK18m/rO22SfvZaSs0se24WMZHtc+9QHesmBzmPYFcHZmWTr/OVasj5TV29JlTAdsDcqySya1YfVwLDlrOxt3zlA/n6KK1ZxUKgKWBWMINE+9WB+1WaYf9is8ZnhcuO6jAHzgtCfC+Q4U6lekLqW2pMJntl6M6chwfhMFg8qZRT619GH++am3hnMnfV8tUF5sXvRWUyQSYWFj/N564A3f4NxNfwFAxlRz5uZ8ehYMhP0tH1eFcTs8dm7PFh4bOIalzfvY5x4Tzsmm9XNp2mZQKbeQH9RQ+PEWSAwpur5qLbyf3Qwsbd7HZ7ZezLRmtUUr1JK4OR/DUYuGq7ch4wsE0+/31RYkKJqcSPn4Gvb7LhZvlFLuFUJ0AQ8JITbH/yillHohOcyEEB8FPgqQTLVM9pEpm7IpO4rsDwb3FkL8f0ARuAY4W0q5XwjRAzwipVz0at9N98ySJ59yI9nHtgCqlPmtT+0OCXoBOh7eHRL4lu7tCsl4QRHy1loF7qkRrHvuX5cR5WpE6Isq9ZWui7AsXvrrXtXuvGHWLP8hb970bsYqKb657LsAXHXnjUw76UAoVhPY4q+MNXBmCsfFz6cxBkYhnQoVyXZ+9FicZtlApgsRoW56epHaDgXB7rviFpatuRyAwm4FTZW2xMw72FvSWGX1FgGodXokB0zmfXN71Kn4GyLuKQgRqZFrL4RKVQUPg6IsHUgM+n3gskWhbkg9D25ejcHZ1kTL0kh4es3yH7Lo29djHRehKWvVBM2Pphg+TW03Wp5NoJHjKrAYEjSo/3ru2haBsgJh5IAjI7gvAyJjKdn5IQX39uOKZHmJP0uNJb0hjX+qIv4NvLbjn7yS/H15Dq50adqQYHyZaq91jY1dhuKMCFY97b6XI3X5jtaQAFpqFTdZLEVcH6mkmjvHZdufzmLaU8rzHT7Wot4iad8oQxqDSqegeYcSRi5rtu16i8AuSErToWu9T3G6rg4e9KnnBaXpgvRBda5Kt6D3XzYpcKEvwyK5yinHsO9Mi/oMh9yLGtRmQX6Xj132sco+lQ71Wbvsk1+/X11nzehO3eHJsXsZcwf/a+HeQogsYEgpC/rn84G/A34CfBD4B/3/6lduRZnhQGLMiSrkpOTrL76J1jGJXdQ3v+OEDMlfX/R93vFbFX2e2T2iGbYMKjtjkn71MYUGrDoRh4H0FYks8L43PqmalSbL1lzOnSd+m8WJTKhmnhwSoVJYIAC07OIXGa61Ks7OmNKXqDrKfXXcSPFsxShJYFn3vhBwBYRZjxnJkXDrsWzN5WxY8QP18yM3ALD0shd59hfHkT91gJFNHbTqBzXxUCfJ8wbgu7FycTfaewas1voihQ+bTOnPF0qqn8kEslJtZJQCRpf4GDqr5LW55FrLLOvexwZDclZPxK69bM3lyAUlblj82/DY3lor9/SfSWabOle1Hardqv3qdIk1ohXmW9Wx6T+OLXLBGJIJRVgbLHLBuEoVSnP1nNvRCy7XWuadvYpV60fmiazo2UtPaixcfG9Y/Fu+8sIqzj3+JTb89oSGvhVnS5KLRym+pGIDiuZAkdnIWj16IfhSXfNaPdxmStfTDGcuS87oY+cORYZUmuuQ6ypRHGwJ5R5l3kFaCawS4TGru0RpKI3VXqG0L8voUjU2b4uNl1TzJlw1X9VuN+LjkH64RSp3WcgFJc6d+zK/rqjsmLR8hGuTKAjsokGpR9cM+YZaUOxEhJYN7pEjtN9nG9IN3Kf3yhZwh5TyF0KItcDdQogPAzuBy36Pc0zZlE3ZUWJHRdVpvmWmPH3hNYjn1ZtLSknf3y9nxiM+h05W69ncm7eA6+JXquz9+Bsoau1Pe8Rk+u/Uz+afazHcX89kztdeiDggYnR7ATvRofcob6HWLijN8sjuNDFcqHSr+Xjwin/ivc9fjbe6A0e7k3ZR0n3PlsPlCzW3g7Cs8M0zdsHxSrS3TYQQY4hwFPVmEQbbBt/gk39Z9XXDX35Vjff+a7jtLd/kmh9cjzymRPtqtQ8pdxlkDvm0rN4YNWqaEVx7wvUMyWkCvILehgUcDg26HkD5rMX4Cc3VkRJ4CTWG1LBsqL0pzfLoXGtQ6YjV43hQPKXCw2/+CgBveexjvGHOLvq/tlAxXk2ox8s+uLGBxl8IEfUvZMaOrt3YhUqTdKKKek1nkHL7PAqzTKSl+geQ22HSsbHGyLFJWvocbvvGvwJw9iM30vp4kuSoxNIcrdkHNyrJA89T25G4irppNsoXahZzKSXD714S6omUZiRxU4LcPifcztWaTTIHHYy6j9OkRY0ziqm72mbSsrXEvjcqKH21U+J2Opy6aDv7vqS8lXreoOXOZ6KMoN66+Scdy9iCDPUmQeZQTL5w2MWseBg1F6dF44bKLtaGl9WWSt+7Ukqeqj3AuD90RO7FFIJzyqZsyo7IjopCslfDWXjJRqYngLddEckXuj11pKHkC2elFCfDfpPJ5QtjOIvS2yL5wmJ/B2+7olG+8C2P3Mh7lq7nV+8wlUgxSlJQ/DI3uXyhEIoKT3NoHjgDeA35wmEtXygLNksvU+Xbc+9XzFU73vFNFj/+fi58+1P8fMdxHHiTenO0PSc48Caf1ofSYZuvS75Qc3iGHKYT5AsPnTS5fOHgBPnCYn8HQyccLl9oeoKVv/u4mpq6wVA1y9ASgVk3D5MvnPfbV5YvDJ2QmHzh8HHae3oF+cKDMfnCopYvNM8aZshX8oXpgWTYN1kzGT7ZRZTNSL7wsUxYdfp65AsPnVPHcBvlC327Ub6w0jGZfKGJ0+Rj1jLYb1ZB+PrGNtDzNjo/ki9snUy+cHqKoRMk9FSpTipfmGiUL+z7/eQLj4rFQsQxEdqMmkC4saq5GNHtT+4/Da9Tu6dVE+Er3sahqnoQReC5Bu0GFqNWTzymMhEDHTnMeVV+cv9pGI5ATlcP1f8++8f8avg4vEfbIHguH20DWVJYjfgAQgn7CGfRsV7gZAXV4TZVPaotFeTOWyCvoceF0ys8+wu1LbrtQ2obsvjx9/PSmd9j3g+vo2P+EOlnVZbEyQnan52APpNRRWGDivqEvoWfDXAhMYbxwNo2+/gBI11a4KUMqsNtNA/CwHgEmTHnVWl6LkWlEMklChe8xY3bkPZUiZGX0YQ4r7LljY2hYU5jltdcwg3bkJRB7ZC6lu27JeMFNd/mPLUtqK5ro6vPxUulMTyP37xJ9e3sR24kvy6ltiGVuCxAhJ+Jz6WMUfxDI16ldU2C9CH1QnCTCdyMQXa/S2pEX+tmg9wBB8ORpHQJs5MxsKo+lTZB5lCNkWdUmbyflZDwaU+VKO3REgXjkz/Q6cE6TX0p6oNpsvtUv3wTMgMeZlX9Mxytol6JKab7r3IdXsWOjsXCB6Pi4McGkxwysCoOyWHdRS1vj+dhHFsk97S6QerNEqtSQxqCHXvV26RlVEbaknGNkYAeHZOrP6pqLb78+HmktqRhaYF8poq/TrXx9z9+D9YxRarzXbofV3fnwTP9MFoe8EZIz0eYWuPEjIBlmSsULm20r0uVlGu7/uKHAIXMfPe7ngXgvvveSP5UBda55gcK+HTh259i3g+vY/ultzD3Jx9l8VU7ARj5xmxaP7oL8fPIm5CxbEgDU5YhGrMMANWaytwkEshqTfUZwn7vX1WPuC1aq3Q3Fxjt66L7zEOM9kdp5NSWNNY7B6gPR2XrvmMiRhOsvPtT4bG1/hxSHYKxcyq4Y/rGbVYPVsvDdhRrCa6RbatMQ6BVGvy9UmH0PJVHt+xovN3NBXbuUdcsd8YY1Z2tYEl1TYH6ggp7WpP4aYeOjYR9Mz3BtHfuouZZ7NqiFsGWR2x1PW07us6qE6D5UUTsHpWaH/WUq5/jibuXq+k9qcyMjlEOPNVDbaa6R1L5MqM7s1hlER7r7B5m/1CejvYCleF2rrnsFwDcvO5s7L1J1ibm0KKRw9U2EUkVetH9PLgkjX3BACN7WigfpyUKLJ9CXxp73MIuSsrT9RA8i3lbExEDOigi6P9GUNYfxjxfpfiCoiZfkj4kMcsu6UFd9KIXCulLnJ1ZUoFMQ1VgVnSwc496UJKjEhksLo4TtasRgtLz+MYdik3IPK6CVbap7Mwy4ubIHdTFOyfXkDuzpMYNDH1xUgcsFfRy3QbWahmcw40Kt0Z/Np3SDInormPEaPWC88oFNVbf/UY1BkfBrAHEMWor9fMdx9Exf4i5P/koOy78Bsu+pFKqOc9n7+peZpSej+bPNEN3PhCSDi3UXI3RwbkiSlO7IjoOtD2apKqDll7aZm86h+ius3d9D+bMCCJrlW1GN3Yge6ItFj5ceubTPLBTKcF/7YTv81x1Dv++YxXND6fDQGRyTDNOlysR9MKyFI19qaYCxuPFhn4B2C+pIG98G7I3nQMNI3d+3ok4pYZh+1hldd/UPIPuNXDgzQKr7JKZr9r9/PGr+cx/fgi7BLmA46KshJz9qquKydwJQeEYs5SwrPB6P/Gj5WQ0JsJ7KcPeXJqmPZDfofpQnJOgc4uPWfep6WNOppO2qmR0fpJZQ3Vu+alGkfbU+at330PJT/L1de9UlygjFXIzgKObESZjcGMHtHqktuiUuaEEj62KxK74CA2Nzwx6yGJJkx7FAv8T+U9exY6OxcI01JsvEIkVKvLu9Vs0bddq14FQiyGw55RwD0SehZe2cLIWWc3SVmsR+mK6eq8ZtBsIr5hhFeeXHz8PNwP2nBL5TJUxRz20XQ/ZlLsNCvNd/Je1tsU0ne9OJRs9C1tR5SsBXnWullX7aAF29nWFxDVAeN6vrDsnhHDfd98bQxyFebtyRw+8ySf9bBOLr9rJsi/dEGZJTv/kdcy4qB9xVyZss8GzyLyCZ2HrPe1YQbNlKc8iXEx0v4fPqjV4FjOaC+zs62LG8v3sjHkWbgZaThhkKOZZSN/kwVvPIDWuHpyPP/in1FoEFjB2TpmlM/cC8Ma2l/naxjfT9ZP04Z5FNqE8Cy0SFOiQykoFZ7G6F+KexYyYZ2FfMIDc2YpnGSGITZg+h1YAQuJmTFI/Vmjhzz7wQSpLPDoXHSRp6szQ99PgS4zgXgyqTh1HZUkqRmxbJ7VGieCMS9aHnoWzWHsWtbhnUWMgl8UqGzHPYoxB7VlU17cj5yivKbklw82Pv4dKhyBV0gtQUkT6IDHPotJh0HLCAAN7WqguUgu5afn4dhp7XOEsAs+i3GPStDar7gkr8tapHnmOEdMHZgAAIABJREFUYyobMmVTNmVHZEc9zsIuqlU/8fzO18RZDCxTLt60t+whecnY74WzyO+AepMgMS750V//EwArf/lnLP70y/+lOIvAL7cqEjet8ueGF0Gcn7zpFk7/5HVHLc6itc9hbK46Z36PSz2n5ulowVmMztd92+1iVXyqrdZRgbOodCtPyi56uGmTWosRqrEdLTiLo2Ib8moBTrMa7K2jAKd7amFCgNPDyVokR9X3R+6ZQU+qplKnuRy+rnuIBziv+vMHAB3g3GPjnqoCnFUd4LRLEicnWHndU1z+Vzpgd6aPSKUQmUzjNiSZUItGwgYdM0h8+AAJYGBCgPPDH4wCnKuWRAHO5HkqwBnfhrQ/a9L60V0qRnFRP6C2IU/edAvveCRi1Y5vQ4xXCnBqASfGCkrRLKhgDBYT3e/dl7mHBTgH+rpom3+IgXiAc4+NfO8ApYkBTpkgobchxR6TWougenwFw5ANAc7rT/gtv3pq/mHbECObQboeRubwbcjAheqBnBjgHNDbkOT5YxSCAOceNa7S8gql2SrA2bxdAesAStNMRpYIHr/onzlz9ScBOPapJiXtoDVeRUbvZfQ2RFYqjdsQrWR34scOD3Duawhwlhh4xQDnCMXb2jn0Lj22LRmy+ySVDhFSI/gzqrT9LHvYNmTgpCz2BQOM7mlhLB0FOM2+NPZ4YkKAM8G8nc1KqiJQt3PdSPv1COyo8CwCrVPv9KUA2EMl2HewQes0riNi7Dr4mlqn226ZT3ZtOtQVARhZmFSLQFYw7YHdgC4SCkRqdWEQvLLW6c5rFnHRZY9x94tvAMAbs0kdsOha52K4MlQKa3tqv8o8xDQ9oDFbEdRriGI5zFb4h1TsItA6FbaNLJURWXXj+mPjGM1N3P/sL8Ly8Lg2ScDQBYpTI6iFaDnrgJrbr7QjPHBySmQ3UP6qNat+tz6xJ3wgpOOosugAZxCPjVh6Tx+vS0kn4cDApFqnorkJWdbzqBeC836+if/YcLaax4EU0vbpnDOi9ElSajyd3aqupvJoJ7Nui2pTwn7E9D2wTKUVG5M0VELPvqqZGS00aJ0aTXlI2KG+7OZ/mQMjCczOKolNGcq96sG28g5uwWbxwr0Uv6zkGwxHIjxVn9H+xAEY0wFZQ6g+Sam8FFC4jQnHsEw1d5apivqCbFWtjl8qH6Z1+tI/LCLVXsFamw8L37ru26pwRJaJqNajc4lAW9VrwOC8+NnZpNqq1CrqWHfnGM9ddzu1HXv+eDyL/yr7Q2mLxM1pblxclx6/K1Qzb7Aj0PUIK0H/LyzQJQFeVZvkd4fUAjwwqjyA6a/QXqBXIuv1GP/Ha9xDlWp086PG80qvHhmbj+DnLz99Ll9/820AfGH7O2hKVvnJgl9wYe5tdCbVw/ft2SoIPG/Hta/el6A/k527VlMP0GTHY9mAz526mm/ufBN/Ne9+PrbrIyxf3A/AddMf4ZZ9Z7NxzTFMpzF74GT0uB29RQlAbrV6xIlhiGheYwuAlBKhyWnC+Qm2PpPZ88qbLk8T0WeD7W9MAkLW6iB9vWBEo16+uJ+XDk4L9Vdu3n42RvW/l1ZvyqZsyv4fsKPCsxBCgGlS7VCumFl1MWKiQkCD6FAqEBCCUERI2LYCLGiLCxE56zRstkvgjQnqzYQxB2GZkEwgXAXgCtW3TVO1aRjhai9sG3vBOPf1LePdi5Vq1w3tv+Mt8z5BfZuN8FXaFiKYcoMAENF5EUKBetBcDoE7H6R5bVthOFwdXIv9XbpeKGIENAgZxdmsbj7pDp5aMAeAOW0Klj2amx3+3cuLUK282hZ7WwVIV9NECqG2IDGiV0CVuBdLEUMXKDfbNBsV34MgcwCSi40x1Z/gs9MVluDxE+5lh1Pk7Oev4tZFt4daIGc/r8aYmzke4h7iJoUIgVJSp8qD/gEKv+O6qv9aFCjsm6YrCNq9acu5rDv5Ls7ceDH2gnFumnMfAFe99AFuX/xd3nXvX2KPq+tX6VTnqbaroGyAWxF6zqTrRihfQ6iy+xjyV0pDA/kivE44hiBmEnzfNGnabGGXJGYNBk+KPourhYICj8RQ5w5QunFv6qY5P+Wtj/8FNyWVWNPY9tYQ2n8kdlQsFqAWjABm7FuGcnlie/0G0aFA1Ed9MWok5jbHhYik3r/6CYk0hRIjOkwkSBwOOZ4E3ZZN1XFcM+TMnGvnsJIu0rB13wOuy5jTNpmSOBE6MX4eMdn5jcP/HogYAQ1CRnEm8XnWWEi805ZUGIWRWFfiWYUwY2MIiHFcRvNsNI7jFUR3GvoY/9wksTFpSQqaVzMYQyRmpGIVwRjLjn3Y98N+TeyLcfgxoa9xQ9/i40MJBO1wihSqSbKperhgFapJtrvNjQJKkcD65H2aaIYATx5+7JVswn0gA5EiQSjWFB+bfK0tI7DdbcasiVCsyai99ncauvu6Pj1lUzZl/8/a0eFZ6KIdq6JWTMPxiOuEAI06IoEmCDQWSMVy8oG2SKArAkpXJNADCfU1qrXIZcukQgYsRewrGwqKhJQMbm9j+3u+zlX9ZwOwvO80nLEkhguGJzFrMdo1aNT0gOi88SKuIFoPIb2d0OcN6NwCZKZfrWKkkg1Zj7g2SaBLAopJPKDxW7ZCaakarkRIlec3axJDv+0C/EegnaEmzFRvaceJ9DwC81UaOUy9BtegUmnEesio3XDbpT2UpjcM0pEpNYzh7bNfZPna99GSUZmt0ztU9diWx86kMxAkMSZ4bdpzFKap9Uhj5M/pmAZIjOlKDTqp+qXfytNaClyw5nrmdgyx+flZfAalRzKzeYzPbL6YwvF1cjolG8xjakhvI4OtaiKhtmHSDzEsCqPhIKzYMcsK8RtAIxZoogaplLgZKE+XWGVBvk+PN2Gra2CZh3ukGmYQXh8p+czmi3FyPjO1/srOpjReLNP+WjblWUzZlE3ZEdnUYjFlUzZlR2RHxzZEu1ABPLYhgKntcNGhSf5vECIaxe2phyJEoKoVfUurW0+qKh6V7MaDj/Gf09OLnPPCRZzcvguAz534M94y8gmkYeAjJhc6muR3aQil6/EqnxMQBcHiASxDhCJGQIOQUSBiBFpgZ1z9Hrjw0lB4gyBgplUyQnGjSe2VgpkTAmvCZ/LgHigBpsC11tuIkU0d2Cd6DWP4/P63ce+J3woDth/epSpzk8ePHiaIdFj/4sJAsXkOf4+LCE1i49UkN590B/9r20WkpxdD8aKrXvoAdy25lVWP/SUJnQ2pN5lICEWL4uM8rF+gA5xMft/GvyfEpIFPw4XcTgOrKhk5vpHBvfE88S1a4/1115JbeevGvwjFmoya8UeYDRECkUgwfKx60gwnTe5AUj1QOiV148oH+d7zb8dqMknuToVpJT+fVtT8qQQitqd+eqCXO8+6BYAbfncjAHJZgeLOLPacEnxP7xFTSRUv0Mzcfl4jJ8cLUQwjqAlIJnjh9O8z755r8Raqi/Lo/vncedYt/PnPPkZhhkllmn4ggr5MFHLRe1Phi0gAqCkbsnCHtRxJHTtwPbW/1alTkVBcC5ltiRBw9dSCOWHWI4hRABw/fiUvnK7ElBY++kEAuh3J+CyTpt0e0oDCDDXnxbka2eh6MZIgqeILyYTqXxx9mkkhhseiGhn9+aCiFVDQ+qD2JJ461YtGfieMFJQS142l95FN1Rnd1MF7l/ZQ0hF7Z5tC1pkVgXSHmGjCMKKHwnXD+Q5iQKJU0SlGT6XI9cMUph0NI7xW9SfaudF5H3JdMy/+6VeZ/7Bi1Uq8mOa8oY/TsdsPFwsvbTA+y6RyTF1xprhRWYLQbcqwlsMPU8fBMaHnOkylBouY66q0qW1H5fu2TdtmF2kIzJqPb+o5ddzwng9T6/pcCpDlN5A0nffYx+ncJCmMqZKCtoOSwfqRI7intiFTNmVTdkR2dHgWUoLj0NSvVtfkSF3BY2Nvo39/diU9wz520Vf6DcGbuFxTq3nNaYC8fmreg7z3oRto6irSNKIl3PpypIcENSeHTKgovKjUFOza85DZtGoPVOVhTb01wjei47Lw0Q/ylhXP88629QDcPbCCazZ8gFTGID3kh264bMmrdh23wbMI1cyFCCUFjUIl0vUISGkcHdVPJhRxjeajoOBC3qLlrAMhhHtO20iIowiyHqC2HoFHsfUsBas+7WfXkR7yKXcYWFVUnwERlLU255ScZNAH01D/az2PwESlhmzKNUTtZSaJKJYir8rzkeifW5sj0Z6cqnMZOdkJyXcW6zGs6U2zsHWA2elhAH7knAhA7WAmAlzFPTXTQOpaFFJJdQ4hImnHhI3I5/CbsxhD49G19DxEa4vySEdUBqo8y+PYthFemp1h4aMf5Jz5WwH4VfE4zp2/lUeWnkByVHs8aUF6yMffnMBvy2PEAWeWqTIz8YrfVFJ5kvqYtFU2RJqm4voMwIAVG1ksKqKmGGlTYaZFvQmSI0YI/BO5LLIph0zZiJL+frUOtipwk66nihy1nTN/K0/0LqMyQ7XrZA3c1BTce8qmbMr+wHZUVZ2K45ROwsgJLbT97KWGqtPq+cvZeanP4n8Yg9HxsGhIZDO66jSDrEaFREPvWUL2gIuTMzh0iWpj9tctjJqHnzRJbOxXHwzgzFrkNqhW9MfGEfmcWv11NavIpCm8eT6+qVZlQOE2HMkP/+UmLlj/ETr/QXkO1ku6fWuC8xbMd4AYRWMQ9J5TlkrhudAksfF8vNTs3OUz5odN1nNmiCgMqkhBBfdMR/3u6EKxp/7pFpavfR+3nnAb3abDBes/AkDXFzXU/sX+CFcSxCM061h8LCIo2Y6PT0r1Fp2k6rSB7FZ7BrVTFoQB62qrhTQgOe5RazJDGHqiqGM1HqSf2KIHOeFtGMcqBFDzoOLTcZC1eqToFas6DcYYVHfWTl1Itd0mNeLi5MyQQyQ55ilOiv01Kn+jvJDHTriX5WvfR/u/Zkhs6o8qkwN6QMdV3oXubxwOHo5Bc6sE8wM6lmKah1Wd+nNnIpMmwvXx0mps1tqXIgatmNcnPY+QmDk4n5SMv2Mpud0VnJz+ftllzfqvMl7a98dTdSqEosGrdSl27uHjBG0PJVXwRm8tCrMsvvzG27i57VLsag0ZTG42jdBalCFQC0UWU5hhUWsV/Ox0pVz+oR9/Ervo4+QMkgEZq3YXheepGzoZuIMVDUTyQrdaJJOMzzLJ7/XCG8kExnpNLnnxA6w/5U7OblVU/paty88T9qQBzobIfDoVyQjGKfq1qjeuaKy3SNgRg/nEuYxjeYDxWZqvUW83lq99H+tPuZPlaz9IJlkPQVzntKh+p20r2oaYBghD1VQIo8GlJRGQ2sZAWb6vqA+DufVlA1epmFDNKibCn+GwcQW/C9cPF6HGTFZUji6D/ggRufU62CgSiZAPAoj+1zVIQAhQE54Mr3Pwu5Dq/6GnVEB2eU3N45variVp21HVqG2BoRjn4/0VwXwEx4KFS2fqwntXaj4Ny0IEWzjLQjgeGGoeRCJYcAzVf8tsqAER6AXDMMLFSYEMQTgehqf6YDg+k8uWT25HxWIhpSLYTR5Sb9W2F22o1ZRnoR/U/G6XTzx2OYuHx9SFCR6qkolfr0PVipiNAMOD7AGX1JjBqidVcdXsg3WMmoddMqM3dbWq9neaz0KUlBfh1x2F7vS8qF2rRtNuj3rOwIjd1M39Hj887rssX/sROkd0LCVgI6o1lqGLlCZ1id/wMT6DMKpeq6kbJ5FQbyn9APqui2EYOLnJd5BOJlZPY0DTbtXRQJD31hNuY/naD7L+lDvZ7xZZvlZ7FqO6n4YZbU4NlTaWtZoqg455bsLz1BgnpgodN7xxpesiApcnmTyskMzNmlEtTdB/Pa6gZN7w1O92kcO9NAiLEEGjXoP7IjhXwItqGCrOFXgWmrRIlYpr9qqs/j9nhtcZwHBMnIyBl7FoP03xgty86AcsX/tB2ocdnb2IkJlCCFUAacS8CCnVSm4EaFPNKRvcJ8EC6ktdhOZGngUufi6Bb5uIePGZ9kAwjMZz+RJhaE6LYG5AjyERjhNiUIQjsKNisQgtwFtYhw9AGgIz4R+OOzCCyWr8jm9qHIEpSAYFZYatcAaGiG78eLGa5gaI92Xiz9JQW49AIdvQ5+ixcmSSdRAxPgMI387h92MPXMM2ZDIuBiHCN9ZEPgizGr0SvLwItyEB3Dzoa3Dc0s13mw6ZZJ39bjHqMyB1v4kvboZQqT5TP2gTHlZZrU5aCTqp6cUfogfEqPkIvRg4GT23VYmbFOE4gnFKMaFvQR9ElPoMt0oN17QSLfbBAxX8TXNOBAu0Wfep5xUM3snF+lBTMH6j7lOu2w3ziFDb33Bbo/sk6/VowQoeXN8Pj0n9UE8sAJOOOymeRDgeQggMx8PTW2AcR12D+DYk2PLobYiM4UrMmkS4imUcUKUTR07ufXQsFuE2pFNFyUcXQkeycRtSnGHyLytu5+aWS7HL1Wgbkk4iyhWtgN144xZ71DbknpO+CcCHOj+JXTRxcgapILL+StuQkjXpNqQwI3BPgzcBFGYZnLnxYh4/4V7O1u68FWwbXu82JPhesA0xJ9+GxGMTInbBjZhr7yNCHEWwDblg/Uf0NuQjZJJ1Hj/hXgDOaQ62T1ZEmBLfhtSdI9uGaG9I/T5hGzKBQ9JwpVK2J8rGGK4SjArGFIxTuLH99yttQ3RfX9c2xLIQug+G4yuKR8enMMMOtyGG42N4BsL1qaxTGIULpJrHN7VO2IZoj0J43oRtiM6KvdY2xPMn34bUPAw9D8J5jW2ILyfdhhiexKi7GPr7Rt1rVLB7DZvKhkzZlE3ZEdlR4VkElZ1eSq148+4tqJXfiyTXxhZIbvqzqzj0Vou5/9YfvWVGxkD6yEKhoclaq6A438UeMfno9f8DgPSf7+Ov5t7Pjd+6lub7ddYhWO2DN01Zr8SeD2PjoesMIMcLFOZ72EWDWquO6LcLaq2S7GfznNN8Dbd+Xal037D4fPWdamNF4GTZJ1GPCSwFJChaexStehWO1zCgWKLWbIb7+jiDeFA9CgrCHSAzgzd39xcTnNNyDV2jNaRIhh7Fw//5TZb94w1Mf6QcdSxAO1b1Gzm+DdCM5gG5b2iOE7rksl6Pov8xacdgPpycRb1JnaM0zdDatoJKl0AEO4t05IUkS+WGfoVzGsuGhPMdy8ioLYGvYgnB/GpUrqg7IZFSuTtBcbqBNG0K8z1U+FoxiJc7DRKjFnPvVhyp3i9SnNNyDd//xk1cu/itUWxKv9Gl4yLqgSdlqHP4suEYvh+NRXuZ0vMVctk0w34J08RtVTibfW9MU1ms9pQL/6QejT9Oq+dFFdsyliUpzDBJjKeptqm5SaTMI+LBCOzoWCxeh814ZHKexSOxA7+eyV+MfpRp79kDN/8BOxWzS/7+LwDoYsN/zQn+i2zZP97Ahv/5Vd7+9dP+/+7KH5Vd9KW/ZNp/47We8UiJ6ouvo678D2hHB84iO12eMeMq/H7NuO1Lhq5eQduLZcySXrF37FW1G9UaL3/pFNqeD95Ogq5ninhpi9K0aE/d+tA2lV/PpEP25jgb1tDdirp2/NkOMvth/BiJn5Y0v6TeJvndLtVWk8JsQeeGQJfEYu7Xtqk9YkzdG8vS5LUWUr/93vrsAb789Lmk+hMNzEZNb1BvppFNHcw+WSl0jdwzg9El6k0w6wH12UMnWbRt9tm/qk7bo0mGz1LzMOtui92XuSz+60ORjkXdidKRiVhcgVjNQLOm7D80FKb3qNWiN7Du9wPbn+L0De8B4GBfBzLrkepPUO2tk9wTxScy+2H8jVXE7lR4zE9J2jYIklrvwskYOCobzvwrt7LhkYUALDtbISNL788hNapT1WmIENMR1pcEcZ1KlS1/p7RepBkL4mY97AOqX3/3njv57PcvR1qSjJKapTAH/vpd9/D5n11M78/qVDvUZ92U4K/+93f5i3WXILaoTs77960KZRnEh+IpWUvFtgK+kTAN6nlkfmrz8rCSIxjf0YLf5IIrWPv2fwNgxY//nBtXPsgzY73826z7AfhVeSbvy48w/+GrmXmHRddntgOw9vljmPZbg1qz0GLSUM8Len68Q/FijBdCj2PL1xZhmBL2J/EyQdDSwM94tHQXGB3Mgafuizcs3kHlMqux9sc0eXLoR4zVD/4R4SwkKiUUYyI2HXVMuNqdaojqCjz9TBh1qfLgrmwI+oWgFH+SY4ZBoaxu8tp0h9RgArMWtQfK7TVcieGIsBrWcFATLY0IXOXL6Byxc/VXO7ho2XOsrp8EVtT34Lz+zCojZeVa+rbAqOhMUDAuB3xLbQGqHSJ09/2E/lnGziv9iApv4uIfBhCl7qLGOwSe/ARF7dM3vIcnl90DwAWpC1jYdIjV9ZPUWPwTw8+lBhN8aOmT3CpPD48lki7GulyYzaq2CRxFSM1AJYexqBj+DJCp1mJFa3oMwXxOUPyWUjL7eLUCpGNcqwubDrFaLAPgwZElVKe7YPmkBnWqeWaFzz3zDozpVYRLrG8Gn3rmUty6ibWgHM1dnHQp5M5T17whIxXDjWwe6KYzr8bWcnyFZW17yRh1zl//JwAcu2Q3//7MSijanD+oRJiXde3jy9u7+NDSJ/m196ZwTt558np+9/wp1FqjKux6s942TcjmpDJ1rlj4DLeJ01g6Q6V0C/Ukp3fs4MnBuRTSKS5bvA6AO393OotlfzTOcCBHng6ZCnBO2ZRN2RHZUeFZSEMgbQsRC7Y4WfATJkZCu4SxgE+91cMZirru2wZe0sBNx2v5TZ06MlRRTnhckbnO7VDlznvsZur5BPVWD1I+Tk69kdyUgZMRuDkZFtu4OakCjaYZaUKgwEnSECpNqANW929Zwn+s+D5re2eHpLSgKNoAxmopbEO1cSgPXpurz2uF53LSglRrFS9tk2qt6r9nSbVW1TYomC8z9sYxJwQcg7dICDc2dD81b4IZC7ihth4XpJTS+88X/Zxflm3W9s7mguYN/KZjQdhsPZ9gbnKAaR1j4bFK3cZLKtwJgJsGJ6fO39/XTe/8g+HPAIvdHREmIg6DNiKgFbGg6A+PvQOADjMbnvOXZZutvV0APLp1AdN7BylUk9Tz6jpO6xhj8Jluelbsx0+2h7B3Nw30ZzDnVGhvCQSCgtSs0diHANxUrYb9FSZq7jzIJOvser4HgKcvuYl1tRb+sf/tjG1vBWDdZXdx7O+ux6wIxhx17NHRLIzZzJ03gJcU7NZz0p/oJN2i5i24b92shtEbXsSLAXib88xdOsCMjlG+qJnIu02f9265nF3P9yBtydNDvQBk95jRGDS6WDG5c8R2VCwWCBSPoojcPicrkLaBtDUCzRAgDYQhMJsdnFxssUiY+AkDNxVr0xAhpfph7NqGwYktSnLdMnw251swmx3SmVq4WHgJgZsWODkfNxnERzS/QwMITF8EocFX+gK3Npc4P+PwBcOnt3UkPP2SJlUVerDWhKVhoPvyPeRay/q8zeG5vJRBd3OBvekcM5pVdqScyNHdXAh5GUBVJUY6mI3OYvi5OO+EMFRmIOhzzGTWY2HTIUA9iMEYzs84DePYnG9hZXonv2k5FB4bqafZkWhH6JiCnwQvG6iju/TmVSXpzmx7eI1ig1D9MgxFVqT7HfJPGIIHy0rGoNMcD792fsbhFlNtS3JNFWw935vzSi392JZDPJrqwjY9XNsIOSf9BHhpSXtziVn5UQCKhqn6EaiKBXNniPAlE/riHnpRkcxrGWIgrRaBB8uzuTI/xCdGmvEzXjiPXlJB14Nj+aYKBddgZXonX7MFIqvVz2wPZAIv62MXdTYmq8GIwlDbBt0vPwEr0zv5jnkGD5UWq7mxCuwbacZP+9jDJvtG1P0kEugxxO7d15EJgaNksfAtAz+bDCGz0vMadEIAkjEdkbgmCChdkHreaBDuFYG2iNYVUQeNMA15X5/a5/58xddYNXgtF8x9kf3VZp6Yp+IItYEElR5Jc+8otb2KUKa5d0SXjNeicumAFLVWU4CgmrrAga5HXNMDIl2Pm0+6g2uf+oAa24JxlnWrRWRjW0t4rupwG6N9XYjuOjv71Nsz3yYY6OtisfNyw1ijyYhRHwkR6WfEQF8iYatUn2mEoKpQ37Q/oeIswNre2XzB8HlkyY85+/l3ceui28OmVw1ey0WbruaLx94bHtvttPOllgUEgLVah6f0PoD6xhYeHVcBysSwvh6TBGZDfZKA1CUYj2ly0xald5GOyR18wfDDfp235lNsvOIH7HCKrBpUCmZXdD7JM3tO4G8v/imfbr6OanuQ8vbJ7jYYFO0MSbV4LXK3KjRtvQ75XKQq52pAletGMZ6EHeqQPL11Fk2b1b170/Rz+WaqhteXI11U5/ps3zvJ7hVYFYlw1XyXx5tJjRtctOlqLFOQ6A/YqwSVWS75aQUKSRXHyHcWI2Sn74fPSVMfXLTpav558Q+5fr1iREvaLl5fjqaDAqMOJaHaaNqvaCCk60Ye/ERi4Newo2KxMFwfo1TDD25o6ZPdaZIYU9qmADj1UBj5vpdOJLk9cu3tYhXhm6QPxfAMjqMubt2JYSX8kMn73fNVuusT/ZfgbGvivuqJpDO1sN3kqI+XMBhLt9CmsQvD/S1Mr40qkdwgE+FLxabl+Sqnr7dKHfOHwocsLi0YnPeOgdN5ywJFi/fwb05kg6HOkQ6U1ftbaB6E7jMPsXd9DzOWq+BeeU0PbfMPNSwQcT3VuJYqEDJwhYtGqaSQjpaFrNUblcKBam+di5YpAaULmjdwfsbh7OfVonfhtkvCZp1tTay+4p/4m32RQPNIPU1yNCoQk7ZJEa0h2VvjrIXbALVdABqYwYMxBJqqwThCJqlKhU8u+hVwuGdxcd+7AcjMHwvnO2DYumPG6ZRm+nxuxztJjnmkAsFww6A0y6dj/hC9zcrjKQYygJal5i2Y40Cj1I09XAETlu9x6sIdPF1TVcCJfIIKAAAgAElEQVSfX/QrrswPsXjs/VRGlKv7b/N/yp/O+AhWWVCdoeY731WkMJzlN0tv5VLvk9R71XWybI/081mKbhPpg5rFrNakFgjtWQT38/h8+O3SW/nAtsu55tjH1dxYBT5fu4Dx1jT2sIk5X72oyqW84rmwrEbY/mSUia9gR8Vi4dsGbnMaM4DC+j7FhQ4t2218Wz0EKTuBEC7SNPnYiQ/zVeOs8Pv1jUnqOYPSzKhNRT0vFZVarPAm8Cwe2KXecutPuZMVxUu5oncte2utrK6eAEBlJEtpls/0RYcYOaAqDacvOqhITKq1GKRZE9QEcGgNzhnY2cqFubdx66LbQz5JUFWfAPee+K3Qy2hZOshZPUr09xddp4fnGhjvZrS/E3NmlZ1awTzXJRjo72Sx2x+NNVBOg8NrNUJJgphnkUyomgL9MxD2O7nHDrMev+lYQG/rCLcuup0Lt13CTxb8Imx2RfFSLt98VYO3sd1t5mPtC8IbsDrNpXOW2rqMPdfBI2XlKieGYiplseuFYShYeSLmWQSpX8vicxtULCWRiL7X2zrCJ2YqZfpr1l/D6nd9k7l2jhVFJRr9Nz2/YO3+E7hy1dN8vfViKt3as+j0yO4yGUi0Mugrz/FYd1vkWTTlGz2LgH4v7lkkVYnBM/3TyW9V9+7n2i7gru4BeCEfaDvzqecvIbNfeRZItQAVK80kxwSXb74KzxbYu9V1MquCWqdPx9xhBlH96pg7PKlnkd8Ol2++ig/NfoLPP/sONU22i3gxT34cEgVJqa7SUZmDUi1wv4dnMZUNmbIpm7IjsqnFYsqmbMqOyI6KbYiXhFp7kmwQbPN8PnHmQ3zv2bdjaU6BdCqJrAtE3eLePcu5/bRvhd+/4Vc3UmsViMVRfYhMJxFS4udSiIImotFpVGFZjO1SUeIV1qWsWf5D3rzp3YxVUmG7V/XfyPSlB9m9oxPmKLe33N9BU2YM4ftI7b4Lx8XPpTAqVbUH1y5iZrfF5vG5rBq8NmTeBsLzrnKvxdmpUoBrrvgey9ZcDkBplnK7i/0dmPOqpLaksco2rirIpTTLI7XHDtGFQCODeJzqPs5yXYnxPARVthDFDYJ+7ycENNXzCTbnW1g1eC3OtqbQtQdYs/yHLPr29awqXBseq1UTNB+QDJ+m9uUtzyYo7Ffbp8wQZPYFVZj6C4YZReT1GISveSqDlKkmpkEaWOuUS+3Ghr4538K1s1SgOLvXYNUzar7XLP8hAMc/eS35gz6ffeJCmroMqnNUe61rbOyyxDctkiPaFbcs1Q+tECdiinEkbMXyrtlihG2rY0Jg7E7Rsl3dI8OJPJtbcrRv9UMag8raVpoP+VhVGQK9rKqBXZDsf7qHrppPZr++zwd96gcEhZFOWg6qcxUGOmk3DqjtdIy/o7nfZd/TPXx2z4XkXtQBYgvyu3zsso9V9rFLas7tsh8F+4OYhS/hdSREjg64d36GPGP2B/H7dqoD0mf/x1bQ+VwVq6hZjPp2hzR7W765jMzWKJA3/bEKbtaiMCNa+7p+9jJUqiHtnmokKt6Z/Wt1cbeMdrP/6R7qM+vYaQd7g4ovNG/3qXQaFHr9EFo+vESy6KZ+Bbt1osBgSDFnJ0JavPpPOrh94R1ctOlqMnYUvV/UorAGA9UcS5tVBuTOn7wZuUB9r/XnagEZOkHS1Cew3jnI6MYOWk5QMHFxVwfyvYN0fqweUgvK+N4/FcsfBxF8UOS6AAcHVFmzaai4hc65B/3e9s1FfGjpkwDMTQ6wMr2TizZdzeqlt3L55qvCpvc/3cOWD3+Ni/vOC491poqsvfVEDN2d8jRBrV09cFZPmWUzFLx9w94ZAMz/1HAUKA6KpixL7avTmqBYz7OsVjn/cXV/dFrRS2Fleicf2KYW2rJj43gmGdth/9MK93D8WX08t2EeK07axsG/m0dhts5GdAkqM1zmLTxA0tQdfp8bxrSEYUQESUGGxvMa+2snwPeY/2CBnz6nsmufOP1XvDf/PG9bdw2FMTWGz522mv/1wKVYJYEzUy3aPd2jHBxqpu+cW3nTx67l0HsV6ZJlefBMM9Vun+SAWkBqnT6L/v7l8JoFAc6tf3c8L7/3Ft63YyXv6lAE0gfcZm7ddjrjg1msYZvMQpUWrm1s4Zhv7FJxi2AhNgyeOHQXY86hI1oyjgrPwrcM5QHEUqeFYzya+62QySeeOr1k2TruEVHqtL7Jpp43KPdMkjpNJRGaxzOeOt06poJHty66nVWFa7lw7ov0pga5qaqqRZOjCUozJfkFo1QOqc/mF+jUqWFEC7JhqCCiowNzNTWG7bu6+Jvc2/jisfeGAkAAf7JVpbgePn41K9arN7V13Dg3LP4tAF9f887wXJVCG/XhHLKnztCwetizHYLScI5OdyCM1jfoXMYzDAHWBKJAlk6dBgG7ialTsTsVQrindYzxm5ZDfPHYe/mbfW9rTJ0WruXivvO4d/5D4bEdTpF3tC0Pf692R6nTcl8za8u9AJhDuo/uoYhsKAjQBkxTAa9I0Jjj8N2XTwUaU6e/aTnEN+b/AICVv/gzvnXufzLPGgs9nnvnP8TxD9zADe/4DZ9uWUi5Kwhw+qT3WWxPdYX1E8dZeyMyJduKsB5SqrqQkhMDbokwdfrw7gVk+9Si+92uU9nUNZPKSy0EJUFf3XEW6f0GVjkiGdpXbccasbi47zxqTQbebu06VgVeu0+2d4wSygvN9o7ph1wtYMGc5LcbXNx3Hv9j5kMNqdPKSy1kxwT2OJQ8lYrPHlQcH7JaVVwpoDNhUwHOKZuyKfsD29RiMWVTNmVHZEfFNkRIGVWEajNqAuHKiAE6Vh23v9rcQLoifE3FNpHxOmg3/D2qcCzVldu43W2mVk2wv9qMLbzIHfdAOFCt29h6S1ut24e3GZwHGgherJTLSD3Nbqe94aPBeXc4RdrSCuI9PJpjb601PG9wLuGC75jgg/SjfvmOqQK4OmgZlN039AVNTReQvWQ0yGlIz/NkAVFUmXlCc5ZW6nY4hpF6mu1uJOxZqyboTBUb0Klz7Zy6DroLwhXU6+oW89MSXCP6GdT2LQCFxcdAVCUbt5pz+O06Uk+z21NbNJH2wvmuVaN59pPQaxUVrVzIFg5eUmKlXNzxGGYmmL/D7h1NnlyNzbmeu6Z0lREr6uNIPY1vR9+t1G38BPgu+AkZ9tWvmHSmiuz1ozkRnkB4at4CAqB6XeNhTLOBw9W3VZyo1yqGQfRSNYFvS6XpaxH2w08oeoaArhFQbb4OUNbREeDMTpdn9lyJt0vVa0hfMvKBFbRuLlHoVXu55vtfCPkstn9hBW0vqu86Weh8toiXsdlzjgrutb3o0/KrrchqTemJ6OAdEAY4d31CAY98GzIHJOPzNCO46gLFs0rI/ix2oZHPovcb28CpR0VGvuaz0NwQAS/EgQ+rmEqthQax5ECIVhqqDB8gMSopzlE/u3PUzWBaHp5rIkcTXHrm0zx46xkAtLzsMHqMzfTvPB81Gi8ei5cci3jkO1JVw7YikNYEPovBy5eHD5SXVDUytRZIjkI1tu5lDkikqcrQw9P58MLHv8rix98PwD+eeA//sWslg3fPQrhgaQLcoNam8+5oDGHsIs4KFvyOKgkfuGyJnsTYnxOCugaJJkelYg0zVf8AKp2C5u0+xVkG056ssOdGNe5b3/AdPvKNj2MXIKUV61p++kIUYE2l1HVGZeeEaUREuEF/NZ/Fng8fT9tLmiu2x8JLCXL7PWr5qIYjMa70ZYJjbgbMKngpaN1SZ89KXZOUknz5Xd/h33eey/i3Fcqwnhd03bY+CtDr+amduZjRY2ycvCA1oF8KBqRHfMyqj1nzqTfreZWQf3izilPEmMWeKv+MMX/ojyfAKS0Drzkb3TBSMroIMoeSjB6jJrclYYNnIBwXqywYOCVyI5p3pHByBk0nDwBQKHTSqrMCIpOK6OA0y7IwDbSoONV2GD7NIdWfwHBg9DjV7ndWfJd/6L6AvT/uZfQYnX4qKji1NETjzZ1MIH1Po//UTZMoSJwMgGhITwXnrTWDrclNhk9zyGxTN8tDb/4KACt/93EefvNXWHn3p3hg52JS45pecK5NYlxGxK8QBgXV1DUu/iHSNMiK6GNywt+DficLfsj54JtCF4UJ5eHF3kLDpzm0PxmrSUF5FIsffz8vnfk9AJY8dSUrZ29lyJ1FsiAJROOTmjNExJnPE7YKbOrMQzgOLW8oiBZXP7aWCFOGavSJglosEITp2/TLCZLjHkXfoNqZ4KUzbwVg0e+uJl1W3zGc2AKQsBFE1xkU9R4JWxHhBv2yrVAcyi5IzJpacExHvc3Nmk+Qr6s2GyTGPc2qrTU7PIFVlVQtA+FLzEpU2fyJpy/ngkXP86yjskbC1YVspqkCq/phNysehmuDTygmFYgnmzUfo+Zh1gz9WV/LMfiRWDW8Ls9iKmYxZVM2ZUdkR4VnYTg+5kgBNyYS1Pa8JDVQpW1zQBqrRHek5yEtSdtz0TqXHCxhFS1GHlcAoNYdnspHV2sKmBTkxrUbJ72oVLna49LybIL/w957R9lVnXf/n33KbTN3+qh3JASiilAMGAOyjW0FjI0JLtg42BDZgDs4sd/4zSKkOImJ39g0J+4xLjR3DMbGBgKIDgKEGiqoSzOacu/cdsr+/fHss8+5krDl95f1WllLey2tGZ259+xyztnnKd/n+61P1sQoe973d36Q/OYcfh561om1MTrfFTyFwdgDYlmEobyZY21xAWER6lMUzYGojVbPr3qmXyN2hICXEhP/9f91lZy25djfbz72Vj5y75UAlLeEVKe6bYJKKopeNQGWFLYl/Bva1DfY8SdMVGaNgpJjXYuwKGXmzYEI7bs0pqR4jp6nctSmSHrUjiNUfPH4Ozl6uaTxXnjNrfzD0EJqUxROKATCALkx02dGI0NpUTNLigXT8adu1YRJjevMKy7OQ6tHPlMYVjSmynr3PCUW09iREcFal/qUmKmPNu3Ylp92C2c+fjVhEVpdch26Wi0ZRxSDuc7JGJSO2/AsumXWTsdEBUVtkm/HGBXBbXr2bV+boshVHeJAEZSStRX9mtoURe8abV3VuDvgV6/9Mj8Y+xNqk4270Y1hfTPX0Fg39Uk5alMUre6Y5L2vXYhdD6+h8RoejR45XhqKyDebUnmaxKn2F3/7He2g2Cy0o9D5XMoErWMafQ5RIZ1slyG/UY6iOSXEr6YmcFTwCDs86pNlETq2OaLd4Lpi0maZsQFcl2afLNLgzBEq2wdpThHeRK8hSzJ/1i7WBVOI9nhWmarRp8Wn1bo9355UJGbIb1rdypZoF/z0JhsbFq7GzhnjNPdIDlxFisZk+cwps18BYLjRQX9hgifi2TzbmG2Vs3MVUdFWWX4KY57K2u3lhliT05DfaCG/sUphbkLmIvMJOrBUeEGnJuqI6ZwxTpUuWxQGUNk+SKs3tjgKkEDcja8sYcks4dj8h6GFfHZgNV/vPZtg1MHUNKEMrkFlYxOJiY0RCrIIzrS1elK/PGlRR0xuksRbWpvLdr0T5GjnjHGCYg9MbRAWXZbMehGAzw+dRqsLtKusW6MMsZGKM9cZE2x1XWzEEVISIS0xHb+i7BjDckxhyCUO0nGHRQftaIKOlDvWq2ma/TFh0aPVJ/du30CF63e9gZumL+fW8uvl+72JiEo7UVCUF9CbGmzSqovbrT3wJ8z6aghNf+FEyu1itUSi6L+36lQp9XXgXGCX1vpoc6wP+AEwB9gIXKS1HlHiOP8bsBSoAX+utX76gEeznzbw9Pjv/1Dy2Wf+MDKP39Vqt0yjd8Ch/8ItjK+c8fu/8N/UNt4spLbDRytGXobCgOJLG85tu1CNo+r/z8bzh7ah22YyHM4E5I369d6zWfeeW1j891e0fW58QczUP8L4Hrn5RADqkxTlHZqh17Xa0MB/rNa11gRD1wzwYHmA+YPH846LHgHgnyY/y1v++o/Pun4glsU3EeL8b2eO/RXwa63155VSf2X+/5fAW4AF5t8pwM3m5+9uGpO2Ssh5RS5ORbHF51u9h1ij6q7Vxwg6Jfgm5LrtaVKdpLcyqc3k59SThB9i+xNTKQ1Ds89FFyKcJBYagtOCzQ/PYNCwVbstxypuZdm928y6ZIE++AM+99j5tFb0JHw4ALbfLSumcPSZwui86fbDaEyT7+ZsXy65imbs7Drdvykydra8PXMrcziORnV3pWm8DM9CG7u346Smc69Je+4cks/m81ZPNbs28y9eY8ljN66bjOoIaa3ogTlNxp4dsKcuDUO8qEZtXZpOjYuazhDyJnDrhBCMOiz++yt45n/dxOHfkpL8U86TLMiucjl1p+IoHVeSjSADZa83CDvNvZBx61RHSLRexvuBD9zNLXe+haYr4wOorOtGv20MvakLJ2rZsbkBBBfuoSP0CDrMmuWNuHY+36asph0X5RkrtZmBexvS5Gmv28KmZ4UtPs5r6AoYXRxx5DyB8+9ZNYPx8+o0xvP22DmTVvLIyGE8t3U6sVfg+Pc9D8BvVxzB5Add/KrDb78oSNrF5dOY2rlaLIN6w7qWI0covKkThNtLtCYZy7HlMLo4wh3xyI051A1Pxmik6HkoJ1abcT0d14HGgYctf+9mobV+UCk1Z6/D5wNnmd+/BfwW2SzOB76t5clerpTqUUpN1Vpv/119KK1RQdjG7u1PaJGTaxm/MfPQ58ZSC8KvapwgQjdTF8IMPBXoiTNmnEmdbh0SFyDsjyht88iNKaK6h181N1Mjxq8r/KpjbWG/qqQ+IDk/yPmVybIox/b1uV9eyJknreSB8UVtN3fSb9QfsGKTRLu7NXhJot4ALfyqAjThWI5mt+KYGVJXMaTmEo7l0LWMfkrWx8/gJpTWac2Fody37N5RlI6ZdDN+7reHWxbuOfN3Mqe8hwfGF3Hm4WstHwVIUdhx07daCLcspoPXVDbr0epW1vU4/FsfZs37Rc3+qEcvJljTxfzG6n3n4LhWYMoM2I5v8nypjyl4GT6L8h5+2zwCgC/f92Z0XyxSAKZoLeoPiB/vIZ4d4rTidGxditbyfupTI556//UAXPzFc9N+tUrjQHGEjlWbyJJl99Yx61+ZRK5h0sFH7eaI3l088Pgi1j8k+fA5p25j6L7pdDdg/VY59uWuWXhVxXFnrWF3MJeHfyNpYaegaXY5NHuwLkKzG5G1SESSdHKPKo6avpUnRg6jd6pY4Hk/ZOfaAdyGMGUpExfrWuvKvWEkKwB00OL/Bbv35MwGsAOYbH6fDmzOfG6LOXaoHWqH2v/w9v87wKm11kop/fs/2d6UUn8B/AVAIdfdxu6tYwkExb6DymUKjcxbs9UtuX8QNyT2XeK8a1m4TQdpbjoJDCXHlGL6gFTjbd8wFZScUxcigk4JnEYFh6CohJ3azC4w7N7KyTCGJ0Exy5gtfV13zh187rHzye1x2kBZU+dJv1tWTOHokzYAsOnxwwh7E0rBlBwYwOtukR9zeW2fcG7+SM/F626hSoV2Md5k2lnCXsdJEZydAm5TEzXLXG3HTFqMdtxZ7W7Ipo5+cnscHlizIGW4Qpb/ua3T06IwxA0J88riKHJj2gYzTznvBY56VDIRL556K5dOP4NdN5TbsjoyZpUyqEPqXinFznXiBmUttU0d/XiG6f3K837BLXe+RdY7uTzDPs7JozibuohzjkWX5sY16pw9qNDjlIc/BMB8x7z/TOl8ShZsqlALBeuGKKVlrLHDvFm72LRH3JCd6wbY2d2N7oiYd4y8N19aNYPCSRWqr+KGTPEdTj9bXLPfrjiC/DigHCsyhFYWwanqDXvvRQXNc1un4zQcRrYLMk21HHRHRNRSuE2F7hBLaeyYmOl3OOhiwVpryvehcuD2wv+tZbFTKTVVFk1NBRKK563AzMznZphj+zSt9b9rrU/UWp/oex37+8hB0UrH7/ljDwGAm1e8jptXvA6ADx/74B95NH9YG19gFMrWdBGs6eLSV87gG7Me+iOPStpnjroHta4Dte7guwcrsxSVWcqu3x+7HRDc28QsfpbJhvwLMJwJcPZprT+tlPpT4CokG3IK8CWt9cm/7/xdTp8+xTkHdYL4xM7oBHrnkIV3A21yhmrb7nSHN/KEqlhoU4xae+0x9L2grLwhwPjcEl5DdED6frsRIFV60jGqULCBSz02jursECJeU+KuikV2vOsIvHOH2POSACO8mqK4S9G7qokTaguvLT+9Tc6dYbCGvQKQhh9TV2uWCzMeGrZ9AVJWXKujSsV0XN1dnHP/Gv7tMWG7zkokJvKIIBKJZUMRMnKizGved6XeJuxwcZqxVXFLpBU6X9xpuSd1aHQqDIKxjd/TcYVUN3uskCce2mPTujoIbZpOlTttXUMSvPz5E3cz704pJc/vdtGepjkjIL/Ft4pz4SQZd+8TPlNuX2MWMWs9ZSyAjiIMjxoLz/RrZAdxHBGbTuDjQYgz0CeYk5rEc1Z/7nByexyagxE9Kx2q5rUXlmO8isNnL7iTb37ifADcVoyKNI0Bn67nh1HjVXNeA6eONcpYc7pak7XSKfJWuw4qiiGMpCwhoQpoBehabR9h5O3/OY2jBnfwwvcWWXh6333r5X7yXFtjo5tNUI5IbGYU+VTOZ+2VswkGQhwj/s1Ak6Frv0Rl9Y7/Hri3Uup7SDBzQCm1Bfgb4PPAbUqpDwKbgIvMx+9GNop1SOr00gMZBIByFNpLtS9E1yKdQ5yTnLjVPkjHZ3Qz2ucblWKrFp3AdmNfEYdaZOGc9huOWNwTC5u2Ggu6TT+i0aeYU5pgd0kKv0rzK0QP9qI9B61TqHQKBNvrOmT7baQwdDv+rFZFMj9oG5dSihufO4uvvO5bAFw77TwrZDRQSutg/OMjRipCNpzApi34x1OoSMYMWDVzXa2lQS/VPpb2eQjYTWWZohOXYj8aJll3I/l93p3LWP+OrwBw+ooLqDTyfOnoO7j6hQspF2Rt/mb+TwG4cvdlTFGvYggn/VQm9tXEcBx0dUIeqqy+CqCrE21M14+943rOf/F9PHzsXSzacQXzT90IiNjS0tVL+cc73sFUw+yT8Kw0yw5qvGpra8gnBMktdCVdR12ryUaV9Oe6EtA3okp2fYKUVS3bxtf38MzyPjwXqtNlDr018xILnZTYWDnSd1Og6enG3WL+qZtoRh4/WCj8H9dsfTO3jfn7dvYq7UCyIe9+lT+9fj+f1cCVB9z7oXaoHWr/Y9pBgeBUSgKRtaliandEGmckjwpaqFCGOLoopnN7jjjvCkdk8vYrFlCNhpi2GWjwha95gjtLpvLTgG4qsxS5MZdWNwwkJl4uJ+xXocmbF00BWq0urkEUpdJ/uRzqhDE2DPVz4WueAOCK/od4/ejH6Njuo2LXQqW7sufPtiQ1p5RNc6piQfoHG9hTuZyBt0vhj4U9uy46iol2F/iH9UL//vCxd9lS8UReAETI6KMTIj1wZJ+gL0d7Z9m/ByVQBr44McW8rcIwXVtXFLoSXEnbXPI5eTNnLSWtbTEWCIQ7rc6N2lK8IK7H6SsuaJvDpavfy48X/4cth7/uZWEOKy4cTStns01nrLIoSsdoJQ5akiaOY1Q+b3EbSsc27Z2M65xnPsDTJ/6A01dcgDphjBvn3QbA6Ssu4TtHfpu3/fjTUpAF1AcNvHuaXEfrMsSRpF2jGKWSlL2GQOjs7DEwsojtTGY6MlT/rptS9rsunZsc/AmN24ShEzJp+ySVn7iDplgywRdlgww3zbuNN333Gs6pfQCAsfW9OOF9HGg7KDYLEDM7TqqpPUcir1mTMR+jHUfMv6w52aZjmv4+PT+CZ3gZtJcokGuB9+Z0u9mfuDF7cSrsDwrbUWgRhC7T8/LwzfU78fIh2vHN2M132vzqbDFDBgeRnD/L47C//p19/6792IoXbQiqVpukkKGcm+eNWZ6DvryYySPZZzv7e3InJC6Z7dBJf2bnsT+YsGrPrLRVNe4nNqY9bd2nZA5d+YaZi1ARJnOsBa9iLmckI21z9j2mzDVuG1t2fkCtkWNDUKXSyNNRaNkNq9LIsz7sbsuyWIH1/T1B+3OXHAWR3vfYq7W97gPtSJ9atWeDkrnp33Uu09aH3bhNRc1wfTjNPwzxfFBsFlpLYVNph1FlGqu3KZABdK7xyY+IQplutVLfrunL54KgzS++4dmz8VeLpZIblRuuY4uLPxHj1ZT1HXWjKWzdcSxv+GbCYRAJm3MUpcVYQcDo8wNc+KaHueHZswG4f8Z23Jc6yI+FNlgIWPbtrFoY0K4YljxAjaZ9E1rEogm0Kt9HTzRRBmUYT4Q4HSUGZ49Y0Z+zXnivfajeMmulPf3fbX8zo89LuvHxObIW08YjVARBp4Pb0HbMkeGYyCL8kuChLRvPFq/F8b7qVgBRLQ0SR7HUeoD48kk9jbmxmzMCvnT0HQBculrm8JMF9/DWtW9mMC+WUjLHeXctYyDDZWrH4aScHUrrVNks2ZSTMRoFtsQ60VGMyuckEGie+M8ddzeXrn4vXzj6Dq664zJuLC8B4AtH38GNW5dQmxoTvCxzyJt1LO5UKbeF6c+OyfKLJptoZqyuQQPvRS2gTJGfIrTWpCKkcnhIYbuHV4fCziR466XXoI30SMBiOlOODnDj1iVwVIXPHXs3ADeUz2LbgYcsDo7NQhl6/toUeSA6whhvd6pABrQplBV35FK0p1EcE2r2NDKfVS1rrZAHdGIG5Pc4UkSWmKM5oXRXYSSuQELx77pi0hoJRJAHt+eYIX7xyiKuOv43AHy8dyOHb3s/zZeLqBjqAyagZNyKNrUwaM8eJBe4WEhdneRmMmS8OoyEVCc5nye/J4pnQJvqWaJ4BqJ69s5jpALj8F7h+ni564h0KHlFYhVbndis6pajBGOQSApmyIDJ+ZKF2vutbor3gPaAXhimboi5pvktPle/IJKIP14sSmJvXftmfrLgHtZ3U9UAACAASURBVOtWJZKJA3P37Ku2hsFAJL+HYbreyVgbTfleGFoFMTu2RILQHLvuuaX84pSbOf+Zy+k5Zogrp98PwCeev4gvHnMbn9i+AL8i90JSZVqfrNBhKBW0yH2jHdc88Nh1tIjZZKxaMDB6L8tLh6Gl67cbredRXuOJG9KAoZMyFcRJP9mK2DDcrxty5fQHuer+ZVynRdkt2tBpyZgOpB0UmwXIzppQyDthSn+XNNUUkhAVGbirpcjLLEcGLr612UtomLaTYkGnpVCR/ExiE9QbJKW6uqMoRCfpoPYZ50Qjx6SuqqXB2xC8QNj0hE4uxr6prQWRXLikmX61oyR1ZvrRHWlqFIy1q7WAr8arqE75Xtxo4JQKUIjt21fMZXnr9pTSIrO5ficTxuScVRS8yHrTZVhUUn+TBOzNGiWxEiAFtIXhvmlSrVHFomXhBvNGazTbCXiSN2ahsM9mEeWwWY9kDoP5aptblcxx40hvu8xB0hImbsxGm3lQwKRT41jWvRW0jy2fl3iMefOXjOtRLjQZnShaVvZyock8b4woB1HOVOlm1k2Zc9t5Oo6k4pNN09ToKCMbAcgmGoYZJrPkhKpdU9WsYZyDKFDyDCSEQDlfUuyem27aiQsWmVqrjGUxzxsjyms6jWs6ltdtrujva4fIbw61Q+1QO6B2UFgW2hQ8FYaMoNBEc5+YRVZV3SqkQ6qSbuTkk5ZVWver4s8Xd7kmoqys2a/DSPRI4hjVdNPjUSRxg71iFsHaLk590/PctvJPAFg9YzL59XlyFYlZ6MQvT4hT9o5ZJOaqTFwORlFqnlrQkHlTJdH6rNp5K2Bw8hhfm/VfAG1K7acObLB9ffCV11o18TsC4RydVhVf24naYxZhMYHap0AetE5jFqSulYy/JX/f+2JGUYrpyJrdWffGzDucFFgcxXUvn5eJWVxoLYpkjvOeXIYOh/furR3entwDyrFKZiryzLVMCIoyMQvjiiT32KcW/orrXj6Pv5n/U6664zI+NSjq7H8z/6d8atPbafbHxCa2kzPrWBg295JOXQPlOALmS9iXndi6d8kxpQ0OIonv2HshtuuWxixgYo7ELKK6Ip9QZiZkS9nK5zi2VkVbRgb41Ka3486vWjX6G/yz2JFB8P++dsiyONQOtUPtgNpBYVkkTSWxisi83TK+vtsEFWoIk79leBiyb0PTogmPYqP9vG5LOBbcFhbiKylTR3b9iXqqIWq4Ctqox7QQq9559+lEg2Ih7KiW8RqgIo0KYxxDd59AxMU/T+dh+83O2/fRE3sR2iQ+tzmPPZ/5vf7APOZtEKh054xxm1pc/V+n28/ljxq1RLDNnaaQLIpQYYxfNRAFszY2k1NvpJH5JCXnGjrBbOZDG/nDoD1CpvdnbeznvCAQ7it3XwYIjqIW+JL1mLuHjSMSE5r3pMxx/QVfYelnX7fPaZPxARlm8NjmNnWtZikZ906n6mZLgpzmDX7tXRdROHKUK++8DK+uWLlD0K9XPnoZ7twqfc8rCjslxhJ05+R6B6BrdVtqoGItzG+t1PpVSol1o9PAOq6555yMlYCxwJRK8RemDTzm4tdi3ECzZ6HJtLVaaeFdsG+AM7HYk7ZyxwyKD5a5dp0Argu7FW6TA24HiRTAdH3ajPcSbxBKOR1rhi47mf4XargTJkW6fgvEMXG9wdovnkR5fbqYkx+fICp5TExJg219964VDgBTOwK0YSnqPxTatR2jZbyny9SmxuhCRNdKOUfXKxH1PofqbOhdJWs0coRi3o0vW9NcBqtTKQDXRRv90dW3HMF1p/yY61e/wea1Aab0CL33eCOP58pNWntokIm5cr6pv5EbYc8iRXkDjL6xjv9SieBI2WQGf1Jg91sbLPjEtnQBs1qnr0J+Y7Mr4xUJCGbGDFi48prPH8+so6T68vYjvsu9tVlcv/oNYqI/t9Se2nu6zGXvu9tKCoJoZhTv7rIs3BNTlaXCCztjy0eRVI8ece261EVLAFcm8Lc/8pu7V0kB3VCUQtrvrc3iPzadAcCmLQP0DlSoNXJWRDl32jC1Z/vo+pMhur5QpjJTXNPaJBlbMKtJT4+cb8oH98g49q46DSNJsbZa6UspkiwVsWbLN6ZYEqB177mFWyv93L7jRF54Yi4Ay995PWd89Rq8OtQnyTWP+kKccY+PvPEefviX57D5TcZ1y8eUNvgEXRrP0OOFHZr5//iiwcBo66pu+Mtj+dA7fsF3N57E3cd+E4ABt4O3rX0TLzwxl9iHY48Xt/Tlnx7GrFvXW01eOXHIo2M/ZCzcfUCAi0NuyKF2qB1qB9QODjdE0Y5idEQoRmcKrJKCKhD0os6aacog29ws6s1Jv7cftGHJF4sllwsJXTknfsqyrB1kDG4GrZcEg7LFbDpKx5bpx/ViBt1xirmAMIOITPoNYgffkbdM1QWMclS2L+2A50doV34mf09+329zXmX/z6JB94sSNW9RV1P0xDQYcDvsHAbdcXIZHEvoipp5VqRYzpPqeiSoQxDUYcJwZRGIr1YY9iotsSgG3LScfNAdt2uqvNiud2jGUMwFTDhQ8gO0k5LzJtfW9WLyGULl9rkk44v2XVe7jpqCH2IIqRiKJhh0fSpB3qI7B9wOtKuJXWWPKS9Gu5pBryJjSdbE1fba27Vz9uo3So8PehVKfsDOKPnQhPTtyrkqgUnhO7z6vXGA7ZBlcagdaofaAbVDm8WhdqgdagfUDh43xHMzpn1M0KHQvoP2DQ7ekayFchRud2DJWgDinEuccwizAD/HaGtkafXAEvYe3yOipp4Ts6rcg9sdUCw1CTqN5mROERYVQWdstTmDTsEd4KR0dGAo4JTTVtTU2z3BOaWAf3Bi5vSmehtHd0lgcmezC8+Iim4rT6Wzt2b67bZ9RQWHyd0VthY7md4tgdFarpPJ3ZU2fIHOFtbtZWraz7W5bQlfiLOPK6A7Ig7vEuKzX9Z8O4dzSkHbPFaVe1hS3MT9PbvssZFWkQ25fiN5KAJAUYfBCnSEzCkLinRTR7+9RplJyLgcR7AqifiQpbZT3FuTitlBN5WHOKcUcIuJqHZ21fHNeq8qCzHyET27eKAwCd+NCP1UXCrOQVTU9HdPMLMsVIdVR6psbXAzyy2SICMznknCdzKvZ5jdRcne3FubxcXlYT420k1ciuw6RnlE1NocK3fVqYQOS4qbuNlXqA6Zg+dHoHNEHTF+1SBdO2Lj9ggyNBlXnIMlxU180z2N+yaEOGrQq7BtpJu4GOPvcdk2IveTypG6z3tzfhxgOyg2C+0q4lIuJerQivqUmKDDIwlU5AxWXrsur5m7gYcrh9vvhyWXVtml0Z+Je/i+RNJ9r12QR8nN8KttCwH4xyPuYtnMS3jN3A3MKu7heztFn6G1w6UxoMlPm6C1SSLr+WlVy7qkdKb+wfdEuMdzhTQH2L2lhwvKb+QbC7/Tpj7+mVVSkv2Do7/BW5/+CwDimQ3OmyMcjD/vfq3tq7mrzKYtA9AfyE+gq1uxe8sAi7wd6ZSyacEk9ZuZK4BOCp1cobXHdSXrkBS8mayIv8Pnx+o4ANbMmcQtbsA3Fn6HC9a9nY/NSMuZl828hEvWvpt/n/89e2xz1MmHuxZY7dFWTyoAFK3vtCzcCWdm2wOZVP56nqRe/b1uTde1WY8kRgFwixtw13wZ17wfLuPH50p5+7KZlwDw11Pv4bHdx/K1Bd/jPZ2fomXEmlrdMYWdDruLPezeLA/6IucVk7Z0ZR2TDSv25P+GAcsur+eiY8XTm6fQ+bKM9z/mncGdhQmCTR3ka9LX/9n8Rgq7FV4dtCufqwZd+GMOl6x9N0HJwd0mu5jTFFW13KQadU9KAPJ9dXnIjahRcpd3blJcsvbdfG3B97jw+UvN2gQEmzro3OngNqGak/hO17A2c3DauEX3n+fefzvkhhxqh9qhdkDtoLAsVKRxJprEtrAqpmOLg19t4VXNWyQBz0QRD68+jO4XZehBJ/iVOiqG4q50m9RBIECVZstWBFqGcO2weFDckMt/djkdWx0ebh3G48VZlDbJefNjMXHOoVLsoHerjGvXpg5o7RY8RZDCr5OqP60cC4J55C1f5E1PX84bH7+aOFOs+cZTnwNgyT2f4JLXiOLUXbeeyR2uwLEHt8n3d27qoH+zpvO0MYK7B/GXStWov62P/Dlj8pYwmI4szL1NEjApSgLL90kUCW7AAIR04oaYcf/tO77PvSOiYfHAmgV0dtV54+NXU5o/xuXPXG5P3bHVodbvs+SeT6TdFSN6RrVlpS4MK1qbxSr7wAfu5sv3SZXslef9AoBffnWxUOFl+leGrsCWVmfWObGulJeC3Dq76sz7oQFuvf0rzP+urHfHVpnXkuonOPWtL3HmfR9nTiWic4vcI4XdisV/8RzrK/1WIEgnOjNaS4l7gkEJQ6mMLhUFp5JZR+KITx77a/6p+hYAqlsG2NNXxJle5yPHSdXq9U++kaPPW8+mkV4+crjA16/s2cz3K718ecPZ5KoxV553LwBffuZs+n9doNlXpnNU1rHVUxYOVsdBVyoWRDY+P6YU+Jx538dxC7J+u5su/vQ61R4fb4+PM13AfM25IfxU1tWSLmVd/wNoB8VmEXsOcWdBGIKQ+ojKYRHdGz2bDs37OanhcF0uPO5p7lQn2O+3nvdplR1qU/dyQ6IICnlUgn5MHmbX5cFNcwD49du+wLlPLuPCuSvZ3ujmkcZh0t9ojokZmvKCUSq7+gAoL9gjJeyNZltFIYU8BIGUcJtK19N/eDWzjtzBivd8z5ZbQ8pk9dU3fJ1ly8VUzp8yxslThQR9xcxFtq/xSh+NTb2ok5roTWIql2e6VDb1MlB5uW2utmUrQ5VKS+6NyJD2PFTOF2JX8zuAbsiDce2t76YxTc4xbc4QvhOz4j3f46wX3saP3/Yf9tTnPrmMIHL56hu+bo9tDvr559UXWrawxtTIaqHecudb0EbP85Y75cGaN7wq5XpI1L8Md4atrbGIR5feAXlQs+la34n58bkyrvnfvZp177mFDUGVcw3y86vHf59PfnkZ3/roTfzVLz/E+Gx5OJqDMY/ddhzVWTEqeQrCUKpQWy0od6YcqQZVqavV1A3J+bKOoeKfHnszXS/I+N0lw3QVmmx7qYcbXxCWr6ln7OCVO+fh1zU3PiHHvtgb4487lE/Zjecruyb5pmLolJDylArDu6XytjxYJb5lzL7skuek5yVFcLjLt87+Kh9+RmQW8uWQ6ot9dO0UkaGJSJC7xXVAOEQ8UUuveRC2ITx/XzsoNguUbBjJO1Ep1c6MZT8nFzrLggWgPVfUo3MZNGoS9NubScsEsBJGqbl+Jx2FlmW+Ss4be3liL6Yj32LEDKwj30p9632Yttr7SpissuXWkDJZzfPG8A1uoaPQYmpByqGf89K+ap4GT+P4MZEhM9Ye4Ol93wiJ758th0/WIfuz7Vg6ZkvC4mkwb+5KI8+c3hE2BNUMgxV2zCU/sGXcdt5ZNilPW1HoZgZLkOJV9nKYbQDOyZRsJ/OMLRI2i1uZ0ztiY0KxnzJuJQxh87wxtAvrW5MEu+ClY9MJvibej+O+Nwn0qzCDKaVwc7HFQtQaOWZ0j7Gzqew8K428xCaddO6xL2Mo+QFNJ7sm4DQcCn5ItSknLbwKDkQb/Mj61iSaZm2iyBG9EAfcwBRNglD7/QEiyPtrB8VmEeWh2Z+nI9nxopiPnX4f//nUW/CMgnmxkEe3FKrlcdeWxXznNV+137/iVx+l2atQR1bsMV3Mo7QWi6WSENqIOJDyPMZekRvsZO/PeHzx7bzu+bczVi/Y875340eZdsxONm8YhNlysWobB+gqjQmzVvLGDkLizgJOvSHBT7PrlzZ7rBqfy7lDy+yNC9h+zw2XEWyS4NPj7/lPjntceJEnZspOX904gDuvQWF1Ea/mE8oLgomZEYUtflrDAmI9JDdCdrNQCl0ynKJ1U7sQRfJWTN4oCUlMMu7tCMcp0CrnWFXu4dyhZQRruzi5+mf21I8vvp2FX/sw51aW2WPNRo7uHZo9r5ENseepnFUzLw1jJQVtUM3AqrNzUHEsY7Iq6mbttGMh3GFm6qvKPTaY2bHV4dwnZb0fX3w7AEc9uozyzphrH3krXZMcGrPlfL2P+/g1Tex65EfMS8bzZBxxjC4VUratZEytFolKkZAt+aAUzuYCPevlHtmTK7Oqp5P+NTGtTplb/YleunfFeA1tEVZew8GvaLY/NpVJzZjSdnOfD8W0digqI4P07JS+KrsH6Xd2SKA+CcAC3RtDtj02lWu3vJXOlcYy86D8Soxfi/FqMf6ErLlfkzkkxDoyL30owHmoHWqH2n9/OygsC7cBxZ11y/Goo4gv3f8mZuyM8CsG5twwHBdhyCmDG3nXAx+y35+5M8KvOYw9V7bHVG0PutHAqXgiAAvo0LH0ZrOPkNTj1w+/laMeXcbSuSuZUxiy5+15BXaoKfQcOUL4sMQsvNP3oCbqkn5MhImjCAfjazuOrf6rLWixZNEq3jP4aJup/oGc+Ja/OerHnFyQN/VRj17MFUdKkdRXHhSf1j1zD42n+2gtqNOMHJQpOut8psjE4r0qQJup5WIZwBBsgjLVrDqxIJJxeh66Xk/TaGbtK7MhniHfmTIwxhE9u3jP4KN8d/qp/PXUe+y5j3p0GUeduc6mLUFcgD9d+WmKL8tbbuzINGZRWddN1C99JJKH0zLpSTsHzxO2LcMcpiITx6rVyJ0mfBbZmMURPbvsuJZUP8FXj/8+87wxjnpULJ4XT72Vo568gm+d9VX+6t4PWRzN2BEx+SGH+rwWNSOxOPWnHjSNFoq5zoD833Xb+EmT663DkPzCMfaMCq4jd9owp0zaykP6GJv2HzxhB2PhFLwa1KYaUaf+AG/E45jT1rHl5flU5piiwimKqKApzR9lbKNYoR1zRs0YHLG4EhX1BT5HnbmWj8+4jw93m5iFHzLc3UduzMMfh4mZ0l/HFo/yCplDEjzW8R/mmhwUVafdxan6tCnvJtxsKil1TOWiU+haV8GpGnWszduk6rTZZPNnT6V3jSxYWHTofX6cuOjRGEzJcDsfXItuNkWpbCItC09IUlfdJBH/8os5Sjtjxmc7xHlN9zr5XMeOgGaPR3WaQ/9KuZGHF+WY/p+r5KZJyGgM3b1uBSjXITYZCueeftY8NYuOLe1ap5Wj5FyltTmaR8tDOfCLPKOHy0Wb9qDp6+g8PetCtrzBYdLjsMvous3+WcCmc32O+JdXJEgJ7UHNfIYQOPM3VZZ4Qzw8YsFqyZgBO+53PbeB654UiQFvY4GooOnY4jAxIzWVAUo7Y3adoiluSycX56FndUx+XK5N0OESGFKd+tvGiB+XB8o5WUBQsz5eETkBSANtCd1cPt92XNcbbPjLY+X3jD0cFTSF3XLg2Le+xIu3H4l2ZXwAlZkOL37kJhbdfAUzfjVBq082i6DkcPQ1K/jlk8fQuVEenplfW5Upc6edP9TzJBsyLLEtK+ATazZ+fRanztgIwMO/PIawJM/Uv73tmwB88vuXsvz913N/fQoFR67vrTtP5Zz+F/nb+97O3B+F7LpK7oXG2m4mPxbT6nTEdTBjHfz1K+A6xHtG7ZpM/HAyW9ZMorDLtX06AYQlzZmvfYFnd09jbLW86D7zpz/izrOOtdke+bDLo6N3MtbceUA7xkFhWcQ5l6ivC2enpAe11gwdr8hVSvglubj+kHA4qihmzhs2smpKIqkaU9pVIuh0GJuT3rjlJ4uCxOvsSGv9HeEmVK5jEZOfvPwnXPvIWzly7jaml8b4da9sItGzPhPTFcHCOmh5y02cVEfdWZIdPrmRIkPya1SvEl7NVZuncNjirXzugp+yvjXJjuv6l0Ry8MbLv8pn1ghAa9uSPt5w1EsAPLnrONtXVCgSFwN2vE5ZX3nkiDxxMRCfOglKBkHKwZhlD1fK6pHE3RIfUZWqZB4SwJHJQiTj/rufXYAzTTaOqSdvx3cjPnfBT7luw3lcfO5j9tTXPvJWTlm4niv+9H57bI5X5U9v+DRVE4CsT4lhqknvbuoiNrEfZ1OXuR4TaRYkjmUOyWaRWEjJtdPaSjOW/Ew2xI342gIBhp1538f51kdvYn1rEtc+8lYAvnXWV1l08xWs/PBNnPHiMkbnyT3SGNQ8ePdi1LwGE7PSjIyO45Sd281YPYm2jNVE0fL5MCLvhyz/iWxkXafvprvQ4OWV0/j4nQKUmn7ydl5789V4dahNMSX7AwGPjyzk5FPXsPGxw6ltkvO6EWw/Q6EGG8QjhrK/t8HAPQEqcsQqMNd67BdTOfnPVvH9uffz+pUy30ozz9D6Ppb/5FjcJsRz5Pp/6ZYLmFHc0m6Fum66cRxAOygsi3LXDD35s5/ksL9fIQeiiF3vX8zfXP0tbrhETHVv/XbBBUzU2H3xYvvdZq/izo/8CwB//pefssd7H92KrjWgu1P0L8GyLOO6jJ+9QLryFbVJDn5V40RQH5AL0b8yoDrVI1fV5Iwr1Cq79D6xQ/ANiVkfxehCDsaqqHxO0mtA/TWCMG12u21vQjcwUGhX2d/HZ7rkx4y5uCO033MijVeL8WoRYcmYxIbXpfTERntOZQJtydrZ5jip2I7VwmzJOBOt2ESCwOAHWifMt4Q4cd4l9h2a3S75sYhGb7oZ1yY59K1q0exJ3zdOpCnubNEYlHMWdzYJi679m9My5zWkt7kVG9NsTD4vAVkzPkv+k7HgWsfMll8zWZTYdwhMENyvRDR7PLQj45P1jOl8pU59aoGHbvgKZ1wl7klxh2xiQVcOf9xIUKzeLHq3zSaqq5ziWBIphHo9TZ3m81aEqnLyLDpeFncrGCwR5V3yu2tE5kUX5xy8iQAVRPZYWHJxmzFR3mH0iir9/0ci2N5ok7jgEXZ4eLXQfNYj/+gqYQ7PSBIydRL1Wd2EHS75PYl0JHjjTVQzMsH3BN8O7o5hsbL99EX36NiPGIuG/udYFiiYd/t4anJqTWUO/OvHLmbXEnko56wJbbxhYrqiOZg+FMuWfZyg0yG8VHza+m8G6TWAGRWEKYdmohQFTEwxb5h+aMxuUdiYwwmgPk0+e+MV/8HnNy1l64/mWLUugN4glLdPwkcZRajAQRvFrQQwU5vkEZSg0a/ahGgKhkay2Q2FPWazOK5Faa3cRHf87RcBWPLQR7j/jC+z5LarKc2vUviRmPBBp8KvakoZdS4dZsRz2tjO47Q2JFmDRBksjtqOJ99rDPhWKCkoKqK8zKEwrKhPTu+pxuwWfs2nNik95kQw/M6Ql07/BgBHL7+YJbNe5JGbTyRf0egkY5tAFaLIpkYT4BOxoehP5pGZZ0JcE2fcuiiPhXB3blGMz3bQHjbrEXTmyFVzjM5zOeOqZTx0g2irLnzoEooPd5If1XhlGUP3SwIII4qFszPJhkQx2hU2tlTfI7LArInJLn5VLLfq9BxBCbrcElFeztvodujY4eC2YiucHZQUXkPT6HXo/2KJbaeLJdUczKEGmyxduIKn/sko6nU5DD5i+o5ju8EGA51UZvk0uxUdJXP9HUVx2MVtxDjNiKDbWCz1GGebsGepJO4S7ZVm/z3tUDbkUDvUDrUDageFZeEEMe5IhTCj2dG/QlPYVad/pXnzNJpmJzfELE+l+1x+dxW/4jP6oOT0e1+OhBex2RTT1iqaC9hHR46VSmwORvQ+7lOfJOZ9ct73Fy6nsNnH96DnZTEHRw/zrBp21jwmNMzRUWT7ivLQGFQ0++M2ubncmGv6jclVpK/ex30aphDzrN9+VE7bdDnrtx/FjRR/d9SPufYX7wegvDlkYorbrg6W6F3up1kEZGJBGMi8faskx824w4Ki0SfjCotS2djsl0rHrDXX+7hYFc3BjLZLCN/5k2+y8CHx1ZefdgufHzqN+iSFG0CrS95+ufEko5CBqesYnRmfHX/m7ZdYMdmAcZyTojAQCHdzUNa793F5o44dEROUHBqDmuIjDRY+JJiM1Wd8m+OWXyGWSaecsKvVknEEIdRUujZBKMezQj4ts3axJvaV1T6tTVJERfAaHm5L5lmfpMiPO2hPERYMVZ6pZK5NUkLbmMBkOkOeft2NfH7oNGqDMq5Wt2QIE9yHtQIHc9QmKYIujYqT4jDQjofX0HgNl0aPnKM4FJFvNoUBPbGYsvyyB9AOis3i/6Z59XYK+z+0VU4wkoYvFPBrmjrCdZi0nmd8GlKKgNvYa0Hz+TQb8ipt3vvX8NSTC+jYvFc2xPRbWFOgfrrEN3p+3kF1lvTR+7CY2ntODCk/XWDKea/wma//OfWj5cbt3hAzcrRiSlf5D8uG9Iobo4ekTDwbt8i2z/7Nt7n6SQO+2lgiKmo6NjtMzIzpeCWdiF/TjBwbUtyW3kJRXnPZv3+Eokk+nfn41bS6oLxDE1y4h9Zy2RHVOTIG54G+fbIhVjXMzCMBj+lmy/J5ZtczKmoKO+VBWfwXz/HYbcehXRkfQH7I4ehrnuHBuyXOVXxYskLHLb+C5665ibk/vZzSRhO0LOTFrUyCxMkYTNrU6ey0MansJha/cYRdE+JGuBsKhJ2aZh987i13AfAPP3wHcz61mo3jfSybI7UhD48t4Ly+Z/jYfe8lKrp86mL57PUvvoGzvnA1zT7oH5I+vLrC6elGOQ5xdcKu1ZZzNMQhhV0e9clpNqQ2XaMmNYn35ITkGug/fISOJ/ISIM1kQ2gduBbAQbFZaFeQhrYISsdUpzt07MjRsUXuPOV7aMdBhSHBwjoT45KhaHVB18Y8Ycm1SLzaoEM556O0Uc7OPhRKuAnedcyTAHyv+hpi1yNYWKdYalJpyEPVszYm9h1OfPcKVm6TDEl1VizRe89L3+SxlgBjJOpPiS5IK/LoXzDMkOoXSLFp7076DU/m6mN+A8BNz55H/kgJwuafk0yBqrnkRzXNyMOfgMGFOwFo/NcUHj7/TMFFUgAAIABJREFUC1z2rxenbxqwvv8+qu0JjqKQoljxDR1AlCpWJUps1zx9IaG5gdzZdfq7JxhS/QzMH2Z3rteeNnY95h2+g/WFNNPjFUL8h0u2kCwsyrUdel2LjtCjPtVsCKHHZ466h+/Gp6ZZJQOZV56LVk46j2QjDEOCWbI5uplCsv7uCXYX5Zqtr/RTnRWj/ZjYlILX57X45ZPHoOY1CLpy5E1xVpSHuT+9nA3n/QeH3WYwO0mmwXXbNFR1sq6Z4jIpo89BHPG2uSu44/tnSn9HNhjorzC6YoC/e0pS0Gp2nUeeWohXdfi7YTk2e/Iw12y8kHmH76DZNZUvvvR6GdfqMqWqJs4rdi82sYkpLQZ/pkFJcDO597pWeQycu4UNnQP4pkwhaHp4W/P4LxTJVWBiunx67NkBBnN1sSySuIvj8Kom6X7aQbFZqEijao00EAl0bo3xKi2cShKRTgKcEf7qor3o+VHwKk2cwKeUz4RgWkYo2WumlYu26lTz/edPlL5jRX5EE68u0iwU6HnFVEyORCgNT9x+LD11uRCdr3iG4Tluw1loY6JmTdXnn5nLn5y4lmHd31Z7kPRLpPjC8jcB0Duiqb4kAJzeRmT78uoxr6yeTKcHedfUrDRiTv/xpziisi6da9Y83rveIrEsRiRaH0exFORpz44ZsGuvVnfgLZANur+nyszyKMO6nzndexiK++xp8yNaxhSl/YXjOQojMY7J8rS6XGIXSmvyBB05nnr/9QCc8vCH+NvbL+Kw2up0nDbQKqlTO4+M+5SwcGc5M2eWRy0fxaZnp0lRmLmmALVI0bnRY2KWwh9v2GBmq9OltNHnsNs+xMsX3QLA0uuWWByChhQ6H4by/2bKm6/NOhJrvv3YaeSL0l9PzwRzuvfwVKGf3Bp5ofW8ZifVp0u4TWg25Nim7dPwaor8GUPo8YhgpbwkooK4NbELHZsN98Z4XmQXlGqj9w+L5r4Y98lNN5ZyscnYsATrw1AAXgBd6xy5d+sNmw3RUbRvLdHvaIcCnIfaoXaoHVA7KHAWXU6fPsU5B/UnUp7tjE6gd+y2OiFAm46I2rorxQkYXRBVKlrNDoDV/3CM1RaZ/Li8kcbnFfEamrCg6L9/I2ACe54nvmqxaAN9yTnR2p5XFQu8cvkRDCzZxisviQBNbuoE+YfL9L/Uwglimj3i/5YfEb2GvZW/rXmdqazUcWyPx7sFeKQ6SpLTz/noWl3GAuixcVR3F6v+ZQbXnfJjgDZtkkSXBESbpPWIxAlqpkBtzg9DnEgTdHi4rRgnMKneyfL9nl+tbfdpHZUK+GbnkrgvWdh5HBNXJ1I4cauVupb5fJoGNRKPq//XYTz2DrE2znnmA9QaOT533N1c99xSSqb4LpHau/aui5j/rxlrKmlZfY84TseYGZ9uNNLS8yRt2GpJbCIzr7ufv58Tnnwnv1z8dc668RoGlgii+I4jb+XCly5mx/KpTFlugGWtGCfSVGbmGfjlenStns7TUWKFWBfLMWLHGaFi121Hiyb4jUD4V5Trptae67Lmfy+iuMvBbYigNMCMrzyPKhXbdWyUA0HLpnmzLHG123rpydf50QLhzrho/ev5+dt/Tn3n5v85OAulHJTvMTFDgCkdgDNagaCFCmWII8fEdOzK41c8CsNp/YMqFaHZNCrdqUn1jjMe485uyVP3vCyBqvG5DrkxiS73J35bLpei87S2DyX1Rqr8neiT5nLok8bYOVbmHWcImvGK/od4fe1jlHb5qBjL5VBOLvTeMQSLH4hTEpJiwSItMdwUiZq5jmJ5+JKbyffl95GcpZl7+sQfWM6MhC8D4IYTvstHg3cBcESfwJRHH5xl/94qO1YNvDpNbqqeRH3bjlfJvIOgfS75nAQns5yfWstYLcoxzjwM0T7cCbk9Due/+L62OVy6+r384pSbbdn5dS9LrUzhyNE2zEV2fFlAmh1jAkZrtsR9jWMBXCVumTZZF5VmPU548p08feIPOH3F+9AnjfGNhd8B4PwXL+E7R36bt939adyGrE2S/ajMVPTrVPhHxVGK50kW1xHXQUoNMmubxTkkILTI8FW4rvDOAriukEFNaNwmDJ2QETpKMmFR2peOYutuZ02Bbyz8Dm/67jWcMPZOAMbW9+IcOJ3FwbFZaHPhSttld3bGatBsoqPIptd6Vjrkh+p41Ra62UotC68hn2k00hQpcMfykyivM6xXe8SyKL/i4tVj8mNOyoLUaFj5Q1XIt7NPNVsQR2nKrNVCP93N3Dds5I7lJwFw77Qj6FyRpzAS4AQxTph5c0DbmACrtAVpdbCuN9KbfK9UpvJ94kaIkyAtowjlOriDDT477+cAnL7iAioN2RDnDqTiwf977fnop+Whe2mWbMRzR0JUpAk6XdymtpaFdg0i1fPSzcKQuybWV9tckmDfXgTBOgwzIs+xBQC1ZWmcJH0c8fCxd7XN4QtH38H5z1xOuSDxgUQ4+co7LwNniH1aVr5Q63SMlg3KswFL3Wzah0oHoVzvDOT5l4u/zukr3sfDx97Fohuv4Mo+kfl7+Ni7WLr6IhoDmqhoOCaSdSzlxLJJxpComblOChdXDvgms5McS0ie95IvVK7c8yrObkCa6uyYwi4Hrw7F7ekmYueWsfCUG9n4RtayuHL9Rcw8aSs/WCjw+GsmvZnb/oAd4KDYLJTjoopFNp8taa2B5wt01pvQatmgyiVX/YL//NJb8OpF+mtNnJox2/vKUtfQ3YmTWbCZh+3mC2+5DYArxgS7MPHmKsGmDvzZVQYeMFHtrrJwPhjEnu6VMagggN4umyUAKcZaeeVNzLtzGTMPF1brRuhxw0f+jU9ecxWV6T51g/3vfsSMvNzZXtlnSV1U+jbo6kg3P1MTocqdchOHkWwwSRS+KL/nni9x1SuiE+ovGLecGatemGm7Kk6rsvLKmwA4/AHBaQSdBcZnunRtjgg6FZXp5g05X27M3rSINDXxy52ycXalVb26VEDtGWsn1tUaVSikqcd6PXVJtMZCOM0D0rPSYdGOK2ReJ4zRUWhx1R2X0XPMEKMTYuFddYfM0aun5MPZJlmLBAof2/VOeDyYqEMDyVQVC2mtiSHTVU6aXTjrxmvQJ42x6MYrWHnlTcz/jeBFFv3qClqL6gys0uRG5X6oT84zPtNl/LgWk+5zMxkGlZ7TMq6rVO42yVo5gvq1LlRGD1cV8sKXYVwL5ftMfyBGOxq3GTM+M+GjyNSxJJZpQtCcoD0zm8WabZMZ/Hmes2ZdA0Bxp8Zr/HKfNX21dlBsFsQxutVi4Hm5kMUdNcHhh6F9q9/wizczfWuEXw0lc2Ko8pxxFx20UPWmWAmmzSo3eee9VwIwe7uco/50ma5RTXO4DI6hk2805SaLhPDEGZdMQNwKcGqNFHAFqEaT+b+5lIF5e5hVFrP+0skP8c57r2SqqyhvjfDq5uIkG1ej2b5ZJA9SVoGtWrNkOtm+tClWIgzt93QrQJVK1OYELD5yIwDXz/6hNds/wwX2vD84+hvM/81HADh7/hoAVrpHU94a0ep0cJua8tbEDk3KsTMSbInl0GiK+9NIswFqf5aF1uJzJw91Bratcjn7UCYPSHUmzD9V5nDjvNtYH3ZzY3kJV06/35b1f2rw7TLuHVNS6Hq2zyxDuOva9bbENUlpueuIOLOFcEdi7Xie3cAHlmzjGwu/w5V9FzH/N5ey7myBrS+dtpS7F97N0SuuoDgkm2vsQnlrRFTMgefaTdE+vF6GVd51bTl49phKxkfGyjQixzoZI5LdHFng4dXAbTiMz5eVnGLclYRZ3l4GzxN3J4rS+1Br1p39DeZv/xAzjpVYzKaXJxH95MBxSoeyIYfaoXaoHVA7KCwLjQSACkOGC2K8LjiJTMyi62VFbrSVxiyyb+AglBhHBj788LNH2ZhFblRiFp1bBbvgTzhpFWaCm4iF5yLLJq1NzCKF/QbkVhYZeMNOHn5WqkpXTJtKeY1HfkxiFknVmPWd986G7C14hMmG2OKetC/5gpI4QGZcBAFeOeBD034LwHtfusTGLGZ0p0Q7733pEnIrxZz/VVUyTXPHImFTD9pjFlHOmK9hlMYsojjNhhg28L3HrvbKpukotq5bNmahHdcGKLWJWYTlmLsX3g3A6SsusTGLTzx/0b4xi0cvQ4eJVkq2slaJrgcmzpSMMRuzCBOW96A9ZuG68gY337njyFs5/8VLJGbxqytYOk1U4+9eeDdLVy8lKKdauHmzjsWdjg2i2vUzWRm7MlFs7yN7TGuJU1jqvjRoqQ1jfDZmUZtmYha+omBEz3UUC5lRwjSetDBMsyGZa7Z09VJmH78tjVl0vZnbDhzAeXBsFgoJUjUGxM8shjHOHh8VKpsNGT9MU96cQ3sO+aFcGhkv5FGNhpQ4Zxbm9OPX8LAjD3TfKjHxq9MV+VGHZo9iIInYJ/yKUSy8nYmZOFGz0GO7Mfk+rUV1hmodnH68mPWXTn6Iy3Z8kM6tLk7kUDd1Fd1JwHJv4tektF2ptgcucUOsWer7YsL7vtzwCYO364LvE1Z8btl2FgDfOfLbqRuyqt0NeeOwuCFvSNyQXx2N0kKo4jY1jhHUrQ3Kz779uSFKSf/ZjS5BrSbzAYlZuM5+syGJIA+kG6ZXcVi6emnbHG7cuoQvHnNb6oZsEjfEnVtNTe293ZAkZpElU85l1isMIZ+TB9BN1twgbjPu0YUvXcx3jvw2S1dfRGtR3W5kS1cbN+SeK1Dmtmt2uyiNVOIaxvdknniePPCZNKluyTW3x0y63gZGk80mdmWD9b22bEhpm2PcEM3EjCQY6khsw3NTrlIMsC2KJaCacUPuXng387/7IS6MhVVr08uTUFE2SPW728GBs1B9+hTnDbiL5OFW1Rrx7mHLjAW0M2ftGrZ1EQkTlirkpdjMtE2fOoHeNZFl0gKozerAbWqivKJz+Ub5YLNplaZUPmff6HF1AqdUAp1iPZxigT3nHsnOJaGljvMaUNyt6drQQIUxYVlu0uKL22SMe1kW2ayAJX6p1SydfzQyavuyOIt6wwY+40oVp9wJt+dZ85SkQbNsXAkTFwgbV3mzPBzDx8iNN+endVSkiUoeTiu23BVhh9xUxbW70nU0FPj7xVm4riWLyc4n3jNisRU6+T7glDttTCnJCP3Zb5/hH+94BwCFIWHDrk0VRq4ES9Dsl/P3Pa8Y+FkG8Wk7TbMhqlREm/XLsl2pUhHCCF2ppDiLMMTp65UMyoRYnus/uYj8HkVjQNO7SlOdLptSUNb4FcULH7uJ17/vgzKfplgWrb4cpdVDqIbB59Tr6cuhx5D8jIwJP0YcW2U4laQ3W4FgPsz112EomA2l0jS7Ukz7tWJp3wr+8Z8vJj8ma9LzX5vsHBOLWAeBbEom7Z/cz6qjxKZ3zaQxGOOZ4G6rPya44e/Y+uLo/xycRdISbYvmvEH83cNt3Axd6yfYdlY3M7+/UVKtGfNNa70PSfHkpwLyQ3WigsfmN8tbd9YvRlFBJPqpidkXC+ZeYNu6TZ4OHbf/P5ZNwbm3QH5MLoITCG/A8Kfr1J/uZ+7tkrq0wdZ4r8048/8kSJvlSch+TmstZv7e1YFaU/23GUwzEXR/PLARss4t6Zs+Nx6QG5dx5kfl6av/9TjDy6fQ/5od1Fo+9acFtDX3NklL6rFUR1RSe2bMe6+NMmlKJxNYazTl4dvPCyhbn5P8/s1PnM9URzYgtx6DguBlF78SEBmCnNhUZxZ2NvddS0jHB0Lgk3xGpddXD4+IpbHXOutqNd1UgCnLQ9xGTFR0yI0GNpipXVARvP59H+TX//k1AF674gKGl09hzo9GYXTcvlCEhcwEok3RHspBD4+0pTL1XqCsZE10GLbVoCRt8ycO4xZvAX1RDceUH8Rj4ybDE6QbuXLQYSBAQq3bzj/43BS8iZCgLI+9V4948pWOfdf0VdqhAOehdqgdagfUDg7LQimU61qeyOr0HH05HyLX+nKNwQKVo5vozpIoRyUglkIe1WpJBWAGETcxxQOKBJ0OwXGCbgyWF3CaEXHeJbc51c1Qvi/mdALMAlSzKS5DFKVBopxPfXIeFWtzfnCbGjfw+PnxN7BUX0Z4r5jY3tb0/G0tibVkzExVyNsAlYVH53yxKmLdhuBUxmVKirVA0IRJmMEJ0+OtLteCiBLi3OXH3sXi5ru4YeH3mOwGLNWCY4juMSXWWzJsUC4SS8wZhbDMXCzNXDYekyA4k0KlFmkMyCAYZery023FVkQqmUN+PKI2ybfI0lzVkP925/ASBGgWb5FFIEYZjszErDdVlkprocJLgqytpBgMW27utGLqgz6FkZD65Lxl5MqPRTS7XUrbA167QmJC/2XWMfhtidzmjOUXCYIzy2iFE6dFkna9InNNEwazzPd90fdIxqVcB6cRovMuKoyJDEO5l8gttgk2Rxa92TYGrWmVHXKjEU5LronTjPZvrb1KOyg2C2UCP81JslnsWaTouy8vD6nxuSozPf7ttd/ihr4/w280JW8N6I4iqtGUhzwDB45dqEz3aPYqfnbqzQD8+Y8+hV+NCTod8rlMQDER3Yk1Om9utnpdzhlGaeVmXoA45a2RvZFcYGyOy4UrL+GZk77PWb2iB+r5piQ8y48JKeQ5q7pVLNjS9qSyUeXzKSQ8VGmtgxUJepW1zHorCL8nQHFY+lr8xLt45qTvs/iJ91PKt3jmpO8DcHaPjLvoeynq0nVAOSLTpxzL1wmYDSSyUniy6HFazg1yIyabRYbOzUoWRvveqHvPK/m/CuMUANamFJZiDHQynkyAUzmOlSW09RiQ/jSymCA8ocm4kuuc/F9p+Tm8XGqCFjdlHc/oW0be99M4j++BkwYpk/GqZD2SY0l2KHHjkns3cVU8D0Va56KCCBxZB5XLBHr9nASPs2uGyaQ4Tho/0mYOQYRj5BWcIG67X35fOyg2i8TPjX25sebdPi4PaIbRKcvJOfebu+3iWo7NsF23McvTuWzZxwEIPzLMXxz2ANd/9UJ6sqm/JDMRxzYCHUfCs6kTQWaAMGT8uBZOlKORVGsrRXMgYvI/9XBG7zL+3nA8fv6kJTK1DD+mTDWtDbHWQpCm/OzfswxXSQ2D+buKIsvxCe08n4UU7U2zG+qHyYMQm4zQ5C+WOKNvGf17AlAlzugVAttb//16zv/nT1NcnnlaI6TWIEy5MW0zfJk63CtalE3j6ThFbcY6TckaVqfGgE/TlIxPTJM5FHcK16dK9JyHTYA0gMJTyZ2ducMdbbMsyXhUJgOlkzRiaNKR4f/X3nuH23WV576/Mcvqa/eq3mW5CBdsYYMBdzCYmGYDJrnHJIBpgRPCPTeNhAs5J5zgA0lsQgsmJDi2qYGDjbGNMcVYSJaNLat3aW9p761dV59t3D/GmGPOJQkscp7cKMn+nsePl+Zae44yxxzjK+/3fiec5FFyulYWZ6ksFviFDHMv8BTgCsiPWTQGBU4jo3wUgP9DNY8/vuOzXP+Ca1I5P0pbiJ+Tmisr8UGl82PSn6PUuoi1zvialHiD6iAdfUmW6GylKa+4NR5z6l7C0mhZpVmk19vMKhunUaDRq9Mg5hzk9tP3RJwR0ZBy5yJ52Yq3IXfsUxciyYE/uYjhxwPcitIsnB2HwA+IGk2q31nE1E/UDu91RSz5foBfsplbkjiFFt27D9lsIUrFxGln6QQf2+KPtjwKwP/1s9/GOpxj4PwxBgoVnvn5SgB6tgpqw4L6mhb9j6lFM/Eyj7P/5JgK1cUOKZ0xGkc0Il2j5JKfTLGzOsjGXcuxM4l59PeXKgfZbb94Kw9c9DkArrz7Q5x7mcqoHPnCKgDGr/Do/nmGi299mse/dgGXveEpAJ6+43zOf+/THH7LkClJ2FZFPVVkCEhKAfQoqLYYGVcqum2rbEytrkcVtQCL38uzY2IQgELWY0XXJBt3LWfDmv1sPrDU3NY6nOMVV2/m0cOrzbWOfJPKQ0O4mvwmzAlaipeGBS89wr5DiihnxRIFlc++J4OYq5p5BIWLkEGQjENrXLLe4Mhd6pmna3+u6Jpky+FFAKqa+cZXYGcirMPq77NrZwlDi6wbUP5iB7VBtUYiVxBdM82Ny5/hyxsvA+DsDx9SL3Sc6xGHanUpAOnYMKPXkpS6+HbE/b94iDVfVgl8ubNmOLt/jE2b1rB6/WEAphoFZuYK+LNZ1q5RBbBvHHqahyfXsSA/y6b/dRGFt2lU5dML6NgraPQLs/E3e2HFFw+CYyNnK2ZjOPC753L1jZv48chKClm1HivNLLUDndhNQWZGqHIMQJSJOPt/HlNjid952+bx8XtOu27IGbFZdGaH5KU9ryccGzfXgqsuIntk1lT+Cscn1O7se0zdeqmhzAco7J1C5lyCzry55jy9B+l5WNms8VSn5dB/UyQ0Th269gU0um2iDJQPqftmZjzCgkN90KU0ol7K6sIsXd95zixoQGkjtm3ChHFId+cdKuO1Y4fTVgogrllqBZjCMANbQrOIe7apvlYXZ8mP+0ycn6UwJqlrZu2hjQ2Obciz+O93q1RkaOeyPCHLNe6nVVInUzQ7p9Ri11H4kfgE1v0e+/oqugoqSnNo6zBRPqJjh8PcWQHlXYki2rUv4PCrI4p7kvYiBwa2+NgtnfY+4BrOyelzJHZTfY4JWdbefsAUgDIAJNdRgKl4HDE5T7PF7o+drz6nOTjzEaW9ql/VtR4dWzNIi6T26FkOG258hie+vZ4l354yJ3Sj32X8hhbZrXlCTVyz4hPP6UQ9Tbmfrg1j24higSgOzcYaqZTs/fAL2PVbytRddfdthKUIq+gz0Kc2lvEd/Wy4ZCdHql34Wqs6NtJNV3+VmYkSa77gsfcNamFE/R5D92fwCwJXU0f6ecHAA/tACKLZOTNX/8+2Tdz66Nso7MvQGFLXLE8gB1vsveou7ql080c/vxGA/t4KPbdMtkf4bJufVb7FrDd+WpvFfDRkXuZlXk5LzgifhXRs6CghJlVcWkaSmZUZehtF7Jx2VM3MKhssDJk8X+LtS+EJZkqEBYfaUHKtZ7s+mfK5JJoR24JCMPBSpfYdmykzlSlTH46QuZBAt9dxSKExq0sBVIRk+ixB9yN5XdM0cdzhOCp6kkp3FoWAj274Z25fkBDTQEJOM9fMUtBowql6P7XlGg8xm7QVZDM0L6wTbi/gr1MncO1IjuaFdfgH0U4oq6VNs9DOPaC9bqerE51S12PVdm5/F13nKM1i4xtu58H6Em5fcDUfW/swH+253tx6KlPm/Zfez5cHNphrLd+herQDWyPTa8PCkOxGWUn/Oari3NgexYQsfT8ZQ+zgcxyEbRvgluGfiCR73qLo746HNdPmg/UlfH6F4vWoHunDvnKSejPDVEaZXZnLJvnp98+j48UT+D8rU12o5qc+ILD352isaxq6PhMtsWyTPar6EConYqPRTiXgqihV7qwZVt2teDz3vOUzfKXSy1ePvZCtm5arebz5di7/wodwGtAY0CZpT8Dc/i7ef833+Oa3riXKaod9y2Z2hYXfIXFqmmW9KOn/ekNB21MVyW77yjt5/+sf4O7hi3ls/ZcA6LOL3Lj7OlbdfRuRC+vP3w/A3u+spDdXVRGsGBio/TmnK2fEZoGFmniTvhvhdQiirI3la8+tJioVlsDqa+FNJiZHlLUJsxZ+MaVN2baCwzqOAsCYHyta+8v6lX9ka3YBO7pKWH0t8oUW3ogysoOcwC8JvM7IhB29TplkFaZAYcLRKr1lmwfZ11vhlvIkn8+12vI1zu1Qm9RYqwNHM4882tVHaaCm2+00bQUFi4V9M4yU8izsU+pvPTfMwr6ZthwTqclugfaCySTQamN/W0K9DEIghZV44/Xvoo6AF/Qou3pLq8uM4ZbyJPcOTpj77ugqcXN5K88OLDLXpr08+3OdRK72WeRV/gcAHT5ndSszc6yz0zyj1CBUZMOyVO5IXF4xfmEtwVcqCkDWbyeHwi3lSb6eU3M31ZOnQ8/3ji5FNbBhYITHCt105poE2S7jFA7zEJQkfb0VlnWqQ6pq2aof8UYRz2UUJSjJeNql0HMXcnb/GBuPqc3pK5VebilP8rFnBgg7QjOPyuQU5lq5p0aFIjeXt/K13HXQqXZY1w2RlktQjnDqSQ4Nln7GVmTg+GEObi5v5bu58/jHuXPU3DgVdo4PEJYi3CmbnePKTyRyaELiFIfGKVL+f5U872YhhPgi8GpgXEp5rr72Z8DbgXj1/KGU8n793R8Av43ypf+ulPLB523DjxCzVVMTBKBnR4A7UVdp4kCkU7ZlGFLamKc0mniSMxM1nLyLFaSce42EDOdEAhqA+x5RTi23atG7K6IxmifM5Ok9oO6bn/DIVFzcuk35SEz4q7EFqcLIMk7L9gOV0BNXI6/nWPfT3yTcU2KslTyUbaVl6la+ICipF2nwGUn1uNqkSqM6euG6FI8GHHtimI4jcKw1DMCCUZ/RJ4ZZKfe1o/5iSbNcQRL2jUNoMbGKbSuYcao2hvq9oKCL9378wCt5/3Qn4Z4S62Z/E55L+Cx6d0W84qy309jeZa5FrmT4aGh8FnbLIXdctTtzQchjP1fJbLKYikjEfpc44hT7g9LJbChE5FePKT9TxU8g8++f7sQ/qPwQ1sIGo9u7GGsJenepv/uxPA9cyd5tC1gzUaXD1mUCmw6tHph5po8nc2oTWtvabhzgUvclnkOT4Bfzm+jkPyklmzadg9WrfD5fPfZCPvbMANtf/A8s//Y7zDwiQNqSmLy52chAIHjFlrczMOYhfTVPxc469niB7KyNpeuOZKeTjV42k6hfUA55xZa3Uzncwea80lirfpbtL/4HVj5yK+WFMzx5keJ0Wbf13WrtxpR/cBJK9PnkdDSLLwF3AF8+4fonpZSfSF8QQpwNvAk4B1gAPCyEWCOl/JXkXdJWyThmQUeSRp9N7ngmyWp0FRZCCovaAkmgomEPAAAgAElEQVR2RoONilA8lCEsuDS7k+HkXJ2o42baCGxizaKwSp32/pZuvJKgtkAS5qXKSAXspkuzx6Y+ICjq6uH1AWFo9JMydtoMiZN/NODlpjVb+PLGy8hXRZtDLm63ua2L4dVqr20+O0htsVrcvduFaSs3LWgt8invd2kt0jkrrrqG65oXKX0+tHFixtoDJLgD206wALEqDabfm175Ka596m2Aol2LCiH5qqAxnSOX2oe8kqAym8c5QYttlS3iV9n2JZGe+nUrRtn3YxVNWXGeihKIUgFZ0WMQyWYhSIGqYqBFEBi1Pl0OMiqEZHWuw/te8APu3HoD0lb9Uz9W1cw/8PVbCQsZU1LQ9iR/8spv8LEnX2VYuIl5IGJ8SQzN1vMqS4UUhFuo5x2GrF5/mNmWOqi2blpO2BGy/NvvYP9rVLRr5X238aev+So/r6zkjoWKjvHOmcXcXN7BJT94H90lm3UrlDa3Y9tiBqsSaUGmqibXK4Mol5V26CfZrE6nR2U2j123ePzJtQBYLcHy7e9gaOkkY+OdZsN6+SufZfyzBbUpx6F8zYVxuvK8v5RS/giYOs37/QZwj5SyJaXcD+wBLjnt3szLvMzLGSv/Jz6L9wohfgvYDHxQSjkNLASeSP3miL72q0UI5eSM/2kJVTrPsbDcJP1Y6h0x6Ahp9CVdl45F5AjCbOqM1XavsC3zd+q6SrmO/QhHLoTGpm6CjgByEYEG4oRZQZCDsCBpdWkbsSATzkcDLVecmNLSQCBtY9/93MV89sov8ZE9NxiuCUj4JmYvbOFa6h7T/QJZVkdwSxfODQuSZqdFrlynujRDrtzS3xfJlWs6iesUtueJqqVuw9DJmX6K5HM8L8Al3/o9zjpXnfxbbrqX79ddPrLnBj616jv8/tY3mNs2NnXz0Rf9M5/e/7LkmucS7eyh2ak1saHEwTm1YxHLLlX+mu07lJ9jXXV/4muxUuhOK5nHuP9CCJ64WTGB99lJ8tP36y6fOnwNALdvvobhy49RaWZpbFK1RPovPMbv3XMrCy85SvT9XtO3xoDgv3/z9YilDbpepAo48WlL9SO2643zVyd2Tc+m+qtPaGEx1SgwuUuZMhtvvp0trS4+fuCVpnjR3ps+w1lfeBd2Q7ByUFVGkz0et89ez0ev/Rqf/cbrzZyQC5ldmcEvtzs4B2fnkrmJQcD78vzZG+/j8wcv5841iqNi0I64eeebOfDsAnAlK846CsDmb5zHEvsANJsqNQKUKf1rFEf+l24Wfwt8FKWhfRS4HXjbr3MDIcQ7gHcA5NwORYtnEGsR+eMRds1H1FPAo0gxTxcOO3Qc1HZbXmDXfZCQm0q9KL6XpOima2dKRXKzfbfawzq2uXSOR4jIIcpAYVxNXmY2AOEQ5mwKx5Rd3exRnBkyZWujJ0HlGSS27aL+ad7z9d+hOCLM+gLYfrZyvBX3utTPVv6Ywf0R0lEPsDCmxtvoy1I65jNzsEj/zogJjZMojPlMHCwqR2Dsi/GDhHsxbXLFxDWQ0PL5mlA3Zg7XkOK437975YP89WaFPj3rx+8izEJxRPCehb9D4WiyKXWOR3z4gTeSP5oMLspA11xEZk7dK1O1CHRuytwNDY4/pOY8d7Gyr0Uuq2rHnjAGhQJNKpHF/bv8C4o7UtqJ7RNmMWQw596wj0NfX4GwVP8AZoMhnnjvJ3jJ3/4+i2pVisdUf7JzFss+uJPHn1xLdYvyY3QHU9p0BSKS9RiFKs+lo6wyWHV/Ygj3zFyBDZeo9PnLv/Ah5cwU8Kev+aqaxy+8ix2/87c80rAZ8dUm9rWxF3Jl3w4+/MAbWVbxyfXpGrl7S/RuU7SHbk3nxRQt1XYugxw7biJuyy49zIcfeCO5cYvXbfo99cg9QVCUbHjxDp6bGOLQFjXnf/n2L/O5uy5tpxqwEy6Q05F/0WYhpRyLPwshPg/8b/3PEWBx6qeL9LVT3eNzwOcAOnPDMt4ITMcaEuGHiCAmBUmgq24NnGbCQC38EMtRJe2NxCxEqQSmVNvYc7Zpx2lK3BqEPji6rqntR9hNidOQ2JpNymnIBHod56bE6fExTFdfPzbTgVMXOA3ZBsoy7daBOWWXO02Jo6N3lpe0ZfkSpy6wvQinbpnvnXo7HFhVqdI+lFRpP0JSuRAnzI04IdFI32vz7DKoqn7ZDYEI9RzpsZjn01Qnn1NP3TZQfor4OUS+QGqNoTmXpVNj46pz2fhBpCqRqTEIoRKoDCw6BXl24ox+O9m0VP/U54PT3bh6vuPn6NThB40hnIbKi4j7Jh3BgbkenKqFHdOgaJqCBKadbF5xSkDbWtIOTn82y5Fql35uAAJpS35eWWnm8ZGGzVX5kPdOrTR93ewuw6kJLD+iqeck1xBYnlQJitrBGTlqnkSoc4V0JG5d1zEO1BbjNDDas+0r0NqRahe1ehZHz/kV+Qk+J3WCWfyeScG/evlCIcSwlPKo/udrga3687eBu4UQ/wvl4FwN/Pz57vcvc3Cqrv+fOjjrc90gredxcCYVsn8tB+f0ZYjAPcHBqUOgXuLgrKccnP52x7SVm7ZpLfJppRycfofzr+rg/NTi73LtcQX3nvWVg1MELs2FPsg0K5aFv6iFFImJFWUkueMW8bLyC8KEs9etGGXfyFLzOX6mJkHuNBycMUbhRAen1HVN37fmJ9y5STk44x26PizJWR71IUlYyOBpMy/ICd657Cd8bPJVpqTg8zo43RQJb8rBuXbNiHFwNgYiFR6NhHFmrhy8gBG/m/dOpRycxVHl4Fy0Ar/kJA7O5mK8soXXIZC6La+cSiS0k6Sx7+48i3BRi8jJEhZ05mxLEJYi/Mgi8i1aA2r+PnDkWjWGEx2cv8ZucTqh038CXg70CSGOAH8KvFwIcb5u6QDwTgAp5XNCiPuAbUAAvOf5IiHzMi/z8u9DnnezkFK++RSX/+5X/P7PgT//tXphCZUangJltboEYc4xtG9pUFYw6NEaUSeaX4Ioq3wLJlwGGgkY6KrcKSeedkJeuuAAAA8d7MRpWgSDLdy8T+uY8inkptTu7nVH+EW9w3dHKh06hdQk1Og+XxinKsBt3Rv55sB66nOdRKkD+aW63e+PncvVw8rO/UbXEM6gskN8XRHN647wCxb9g1P4hX76B3Wot9BD/+CU4l2MT760nXOCZhHPiDSp0RqUFTtlTwBlPVxfxAsG1Mn/2EyRckeD+lwn5YEq1UZn0kzTYnhwhtFmb9JcPiQoZLF0seQgr4BtANcObONvOpaYzwDfty84ySGrtLYEEGU0S9si7NGYkZSpVe5oUPUVfd17ug7zye6IyFX9A/B7fb4ydilBn09QsPELum9ZwU9nV7N0cJKDRxfoNmzz/7bCQTFKN4xSAL8kvfzGoaf5+OOvVJd7Aso9NZqNDHfOKItc9nh8beyFHJzu5s7iqOnrPZVFDA/OEOb7zZzsHBkkyOXwS0nmrV/SWdGBfn76eUdjOYbXjTMa9GDn1JkctmzcvM+xkW6cKRexWNmJPx9ZwjJnRvnVdCbwv8sq6gqckwBxZCRxK1LxHHqxg0v7HyKJPemS0ZmNQgosP8RuCdx6auHFvoqYCATaSEGemlDe58yswK2oewZ5h6IuFeo0I9yqwJ2zcJqqD+6cY1KdjS9ASkOco9Kd1RjurZxLZapIbs5CpsAIcbvOtMNPJpT96lYkNY1Ijf0C7pyN04w4Olmmpyk5PqkAUYsbkqOTZfqD8cR+jlm40/3SYlKy0z6ASLNMx32O5wZ4U3mav9qnUH/MulQCi9ycRWWqSHY22YzdimRsshNnOllCUcPGbib+AmkJnLr6/Pj0SpyqMJ8BbYO3j8GkV5+Ysh9JrDlNqpNycFYCC3dWvTz3VLpx9XzHma/OtMO1vc/x8+m12C3P9A3ghp6n+NCBNxhOSkUHEKk07yhMzLtI+1Zs66R5JAx5eHIdXf0qe3ZufxcVihAIbi7vAOD22eu5sm8Hm91l5to9lUW8qTzNH092sqgVmTmJqi5OSxLWwWlpn0Wddp9YzArf6zE22Yk97RAWYp+WhR8IugYrzIgSVJTjfP26ERqhNkPi94xfT86MzcISJ8G9/fIvh3uHvT614ZSt7NqE2eTUANTpIHR1qLRmoX0WF/QfAWDni3yObhwm7PVx8z5eWWkWQc7CLwn8johmt9qE/I6UZpEqVqMgyu2axXeOrufxqz/Fbzx7KwU38Zms7VK+4YnLZjivU50y9yxYiNOrvHTNnqJpq9Ej6OutMLMqS19vRX/fR1/vtNIsfB0BSQNr0id1WrMw5fV+tWax6tFb+S/n/QyA5SsmuDJ/kN949lZ+cN5dvHnHW82tj24cZs8Vd/G6PdeYa/25Kpt2nk/TSUKnMeHuL0YW8oKX7zKfAVYFU8kmp8dgQuSxZhET0VqC913zPdWOkxR/vjJ/kN/arZTfv9l/BeUNExRc9UwBzrtsD//vQ6/lkkt3MfbQCprdCcDu/Q+9lRVrjpG9XJdFvDOZozbNIubE9PzU/CaaxYL8LE9OLAPg/dd8j5vLW3nFlrdzyQ8Us/pHr/0aH37gjTg1wSWLVgAwPDjDH092sueKu7j86+80c1LorzG3tJPmYER2QvW11R8xFIRKy0ppFmIyw56bP8Ob9l/JjX2KwuBY0Mlduy9lZqKEM+VSWKN8ZFsfXc1K+5Bikm/TLE5/yzgzUtQLC+TaN3yQrnu3qAsyonntBRx8Y8S6v9B5FWMTyDBCNhpMvfVik6LulyzG36BetCWfTfa+zLYjqrhxsUA0pxdXarOYeu256pIvcVqSVodFkIfChFrchZEmXncGr2xTOqTuX12Sp/tHBxQXRKqOh6GYczOGKbpy/XmA8tynrYTI1S+4lVDguXVJbVD9qP8p/fdLCxTGPRr9GXKTPs1eZcuUDtWpLinQ9aP95p5tfBapWqqGmRuMg1POziVO2lTMPe5344pzDDtVmBWK98EWWKEkdJPNOD71Wh3J4EQEpSNeQnkoJUFePZPIEaZGSUxyVNy4/ySNKOGz0E7HeLNoNqm9RKEU21LUXYGvT9VMNSJ01Xyn+1c+7FEbdmm9cYbeT6owqQglYd7G67BNqDf3i0NJOnpqs5C+nzzjWLTznChk+ro1dOxT6n6zL0eYE+THPPySHntG4FZCLD8y18K8hd2KCLMWP77js7zsHQppmZlRIdSg5OLU1LMLig75J3apw1RGBhov1y6ltqSIXxDkpnVUSQgysz6WHyJaoaHgQ0oyByYUJUDMbhYE/Gz6G8wGE6eVJHJGaBZSCHo2jhOlzJDKIofVn68zeUk/AD3fGtM0c5LjF0iiZ7THvSRY9leCsOBw8Do1Mb3PSnqe/dVmSP6tKphzdNMwhaMWs6tV1mm4TU3kzMoi9QURmVmB7akXcOocQdcPo1ObIUCa1u9df/41/mTjb5A5kG1b3MMXq3aPPDPEuRerF/7gV1cyc56OdhSVZuO+dJLpzb28/abv8ZnvXIdcqhaqfW+O8RubdG3MJFRu6Q0/bYZYVtK3eIHEZogpyNtuhgz8wT4mGqoPh/cMIoo+mQNZvGUe7uFEmysctahfXiU8XDDXorxkZk0GuxFrPOD1RHTstjj/N5/lp4+qDfrFV6jg2fjrywkuJK4inmJ5Mv/W/T58nb5vyqwTRR97VPXrPTc8yGe+/kqkrfoHUFkW0fiNBvWDLss/VWD0xXozFfDBW77BJ7dfhb9N+TxWPhW3LZFEJ5khwnUTlnJjdkoKbxtl79PK7xFlJXT6SD+BcG/fsYhcn0dzLmuuXTuwjcenV/KLkYW87B3v4LHPKWj4ddtfzZGHl9AcjOjbota4VxbkN+tShY2mmZsDrykj19YIjhaI9N4qPIEs2NjTWTKzFo1lur+h4Ow/DQ3LOeiIkzitfQKY57OYl3mZl9OUM0KzEGGoigOnTsXySIAz26Q0qruoWZqREZ27LPJa7cpPgzPXxPIcOvfGKEhf2Ze+Dy2r7b5Eyu4beUrZtG5TkD+u0n7DrEWHZv0ev9Cic5eF3ZQGSVc6aKkyibp4LWBAPNIPVFUzff0jW16N44ZYLdG2Jcft2j48+5RKjBo8HhHuVCd/Y1AnDz3TQ1SU3LHl5TDskd2pTnC32sLZWYDW0STz9cRCRmZiEzNENDR9ni5FKCJp+gxJ1uemrSu54YXK/j2Q6TdjcNzQMF0B5I9HeE4IqWsiFIQ5SVDSjrlOn56+CtGuPn74zFlYmiHrh8+cBcA678BJWacikm3FiUz/ggCZ1VpSysFp5hj4m6euIKvnO39cs3UNCZq7O7FDcGZatPrVGolKAbc/dzXhzrJh7sL3dNapVulTXB8yUvQDZq7D0GhAB59eQNSvx9Gycd2QYmedHds0PjEXEu4tkWsIdjTVtZ0jg0RVl0J/jcyMx3XbXw3Ag+v+N8v3vJ2eBbOga7og0RyzmiVcr2evNyLvhMiGQHbpeRLQ1Vdl1inQdDN09SnHa2tzjy7VmYCyZGTz6/gszojNwrAxxwAiGeGVbHI5B7+kHljGshCaPbrVBZlKGmbsEGUdWp06LFa0k9J72tEZi7SUE604oq5VVkR4xxRXpIjAK+kwaV+I3XBwa8JAlv2yzhfwg4RMJi7RF6c2a/W+4+EC9SFBY3GA1Uz6Wt6nPleXKPUcwCtLwpiPpF+r5Z4FmQh3JMsfvvbr3PFTVbkryNsUR6Xh+gQSoBAkOSDQlt8gq2rRxDwfMghM7oyaF9XvoR9Z/HjrxQDkuwCZobE4IL+1SKs/CVl6xwRs7iTsTa6JUPBXN36J929UDseHX/I33D5+NT8q9zH4I9v4N7IxjWU9NYa4fEAQqD4FqSgYgBAU9idFf4zIDM1h9fL0PpLj+AY1394xNZ4wJxn6meTo5YIo5yD6lem25aV38vJP/D6Fqkz8SH6Q0PrlssmBEIbJJhabdZquHyHo2CvIbVKb0OwKC2m52OMFBnXW6OzKDL3bQixP0fEDBLkcTksyt7QTqHPkYRVWXr7n7ey/4fO8e+RF/LS7T48BokYzWcfaGb3wYZg6q5NwMKKwQ8P5Bdibuhmak1ihpLlVwcsHRn2Vsep5iZPW85PxnIacEZuFtC1kLpswPklBfcCiOJqh3qeuleL6kbZNY6mP7SfghY59LkHRMSjI/HGbkqPQdSKTsu0tS6EWbduc4L2rJ6lM9yuEYiAMTfqq1UfZYw3hTzkm56Q+pElaIYkiyEjZfrquZDyGVq+gORxSHqq0EczO1tQCKKyapVFXEGERCpqD6jcb1ipSnslmkd5cjU2ZpdSiLI0+tVCchkWjT7RvEHZCunPiSZEgIbUHnOAkmnlI+C5anYKWWl/4JUlYjCgPVagGHfQtT5KPK9P9eN0RxWUJsY/nOfz1wau5fq3ySdw7exGfXvgEq/rPx61ahrzXRL3SkRs9hrh/hnHMfK/Yo4A2h3FYjMgM6Ep2PWUz35Xpfj3PM3jPdiH6mwRFh+vXPgPAXxy/jFYPRFlhyjoIWx0yIko957gPMSI4PiQ0XT9S0ugX2BpW7XdIgnJEdtY2/fTLEq+kast6HULPrSCsQ3MwIii5NAfV2u1ZMMu7R17Epxc+wTkFxePa6o3URhEn1+k+BHlBczBC9LfwK5pZzIFMReAXwG1gkiv9okbuBkGClE6xxp+OnBGbhYgkouW1mQv54xF2w2fgJyqSEatfMgzJHXHJjycvhd3wERIW/jBefCpOL+O6IylnZLyTxslHx/f30DUmQapaHPF9g78cYrjL5uhVAdk59dv8hJMkpqWS3k6VSJadloRZm0q2RLWV0ix0u9UDnZSPq8+WJ00B6NEHFbv3zCqH2pGIri7BZ7fcQK6m2stUIrwukZy4tMO9TxQzS3EOhulnDBVvTyTLVFInrRC4VTWG/JjNcXrMfbvGJCKwqJEAtUQAc98q8qSvwoD1QZuvlK/i9Tc9zg8/ealZmJmKpLJEtD3vuARDOrkt/ncsTi2JJMXiVm0ajvLulWYkkxNqvrvG9Kl+oJNyPSKazuDUmzz5cfUC1vtteo9HTFwgKB6O2w4Rlu5Xat3E19MbselnJMlNYsh1Vb6MIq6J+SicmkoKsz1pwtwiUBGb7ISFU2sZZyZbevlpdx/nFC7kufd9GoD/NnY+v/ijrCrinRKnKclO2DSdjOH0kLZaT25DIkJpCHSceqTXbarg0YllMZ9H5h2c8zIv83JackZoFtISyFQiGTKi0WepIr86m9LSCTTCtmku8nGaiRkS5pUZ0upMneCxGeK6KUBSosY1+9V9+5ZPUZlIzBBbg8DcmkWzW7BqxTHmOhTqstH/K8wQXWncqPPdguZgSLm/2m6GzCozpLhslubcyWaId9AybWXmBM0eQVCQRp10axbRwua/mhnilQWeVhaCojZD+qtUWyeYIROnNkO83SWELjzU6lSw9Y8PPs0F5ctoxUqIFLT6ol/PDNH9gZPNkGyPCit7XWUz35WJfj3PM/hPdWF1NwkKjvGbeJ3gNAT+kIc3lyI+PpUZEkndvxSeJWWGNHsxKNCgqM2QaRuvnPTbL1pEjlRJYSgzJKorwFVQdMx1pPJRtHoj/tuYKn3w8cGneaV40clmSE7Q6o+wuj2C6cQMiTICP6/MkCij+1WwjB/vX2qGnBGgrA7RIzeIq3CWq6xEWW8QzcyaOiHQXkckmpk1XA5xXRCRcdu4HCbfepEBbhX2qkXuD3YgggjpWLhbD6i2PC8hh824xqkV1esKGBRFpqaGyGapXXMOx891KI5o0E+3oGe7T268rkAwZbXwnD2jhpszLW3s2zFQqt4wZQAjXRBJxKzXrqOKJWk+iqhawyoV2f4Xa5P5S9UmCRLYA1aguEwBKovUpjD401mEHxKVMooCoKV5QbqVKp/Zc/Qknoy04y+5uaUAYGlAWDajnlu8qFNqsygVDUYhLoN49O/6mdunuUcPWkgLKmtUfZJIT1Ntmbp/30ab/q8/x0kSE9kCopBX7ev+gQJ5iWJB1Tyt1hI8RxhidXWqNaYr3u/+03MoHrGoLo1Y+FjE9GqdAbwgojBqccnrn+Hwf1WwbKsZIPwQb7BIbuexxCFbbxigmSir3ULOziE6ysavZeYmihQc3/fa+D5jZ2ZSG1bwwL4neOmzryX44qDZQbse2ZvMQWxaeL5CoOZyyoTT74/I5zn01hXU1zcQY2otZZZVOfh/f5bGntF/P6AsQIWl4nRpx1GTZWF2viBvk3EdhOu0laeL2YOEbSOtZOH6ZQHjqEiGG6PmbCxPEGUs3PhkjiMCkdRw7aQMnOqDlURpNKzb64rIzKlrbk0SFC2ijIMFyEzsvLOQgZW8OLGkNALDvG1biaaSakt9l0R1zPe2Ta63AVvLpg/xZlFfkGz+6gVU8+Qp3BEya4OlIPJCiJPtUNtOQcBD1V48B6mxCNtKkr7a/vYEmHRqHMabr78/p/8YTz3R0zaG3FEHtyYJNZQ9d1RrevVU/ktahJXMqZX00WhetvpehKpfCbVApOZfSLOW8uMWbk2SG7eQljRcHblxxdtxfc8zfMZZ3TaPgCKQSRdtjpm2UozqMpdBpDlFApQmJaVaJylWrtiZaXwUlsVLn30tPzrvm2zIvsugNUU2ozYpIZIcmzgCFrOhxffNZXHq4O7P4eocnVZQZnnh+Mlz+kvkzNkspDREN0kSWOKAsT1FiOIt7saZmGznk4iSyt+xOA2J1Yqw4zqmQHXYpT4kGNrYbEd16l1cpKs1QYIAjSWKsFsRTt0xCV+WB3ZTKnhtEDFyuTqhl/2imdz/hHGaj3GUJl0HNNVWPBcxiY+RMMTZlDBt2y1MSVGTFIVygMVM29np2LEWqf/CyPQZYPQleRb+sIacS/IuVB5CZBjK2sYihDqRU6aEbDbbCXXS0mgmz0xXiNv6T+ea9ykeg9MAu4mBjIcaDWr7Mnk26U0jVU9VVipJH1NmWTQ1o2DkJzzPqFpr4yaxm6ofTgPsVoStQ96OK7Cbkv/xP2+hJ6y3zePoS7Is31JJtE/HAStSLNwpKkM5dlyVukzn6GjMTzw/QDsmKCXBFwfZkH0XG//ib7noyZsAKNw8rQtBW23rQ/otZIz0jE2OZgu7uYDOPZioVOcu2DEyeMr2TiVnzmZh2UQlZXdZUaQmPUwK7zZ6HTJTWZo9Gcr6O0BVFPc88/tYasMCy9eFbY/qwjJDgvrikNYul0yqXF5spxJGCSy61VL3lFFS6MZ1mFvskJ0S1Ib1zwZC+jbbZCouwldhXUiBjNwTpvhUxXBdJ2GyilXYGHeg+R9l6nsZRmSnJfUhHdG5UBoIdHlP8vJOnxMRaWKYVpfGHeRdRMZG2hZh0UJoCvrGuibNbVmKz6Q3JdQJ56psxbax2DbS80+OxNh2W+Vu0vZxbALoFzk3HVFdaLWNITdmc/ziyPg9srow8tRam9KD8WGSas+ykmS5dB/TxZO0bR7jIkzfQp19q59JmFH9yB8VzC12mFul+pubENQWSQY3SqyGWgthKYPI2KpIsY7SqQenE73ie8f9jQsVx9ekzlOKNbP04ZDWzuKxCMhNh1z05E2G3v8V4QYIbYSQ7ZtMih0uXYh5Zp2kZ6sg1CaeY2Mqx5+OzEdD5mVe5uW05IxwcHZmB+Wlna8lPD5prkUvOR/32KypFB6OHzen/NybX6Qg3Vqyh6Yg014Y2X5mjzr5Mq5REdMy+ruqQoFTl3QeCGh220SuoHREOYTcuRZh3qUxkKFwVKmI9eEc5e9tbXf2xQVy9YkQOwf3/neFguzY0+69D3QaveUnzsj+X/jUB9SJ2Llbqbn1BTnyxz2On5snf1xFhwD6t9SYuLDI8L07Twn3jh2lscT9FJrwV87OJSeX7xsbP+73ri+uJ1fQ5LE7ykQZNYa5VVDel3pmBwIOXWcbRCpA5ELfVg+7oU6zxkDGRHGmzxInFUZecede5RCEk7NO04lvun/7/1AzYywM25cAABerSURBVKezeDNQOqjuO7cqomu78nV1HlDjnl7t0vHqo8w+MMzCByfw+1SSXLM/w5FrJR07HAK9bJbc8WwCvIqiNu1O2BYinzcO6LQ/5uDvnc+nb1WlFW/7yjsJc6oAkNOpnfD78iy79DDruo7x3Z0qmS4ayyF7PcRkhtVfqXLgNcqs9HojFj6sAFcx90aQE3Q/tFc5kKemjRbxvf0bWXnvbZQOWjQGtFkcQKs/5K5rv8ADc+u57wm1zq+96FkOX5tpM9mFbfGz6neY9U6vivoZYYbIjAP9PYhZbS/LiPEXFuh/2sKp6gmv1ZQq3mhw7Fqfwq4kA3KB30VQdKgsTIYzsK+IMCnq+mIqRf3SN6n8h50zg4xuHMZb5OHmfaq/UIupc59Lo9+isiyiZ6t6q6fOlXQ+Xk5eNDgpRT2WJReO8I9r7v7lfBbNUsJnUXopcrVm7L1fvdST6yUde3K4109w/Jk+utYrvs7ZSh/u9ROI+0vGzuVXpKjHdV5lhxqXaLVOmaIei2VL3rJmMwDLz0v4LH50Ap/F6MZh9t78tyfzWdx1PlagOUtTfBbOcI1zFqqMy5i7oS0ylNosOEWKOpbgttc/oNr5JXwWBd/FX2NTcH1GNZ/FOS/bzdO/WMElb9zB2PYVVJak+FSjgL5XHyFr6/n7Yv6UKeroFHXCEJHPJf3VKepX36iqmQO8//UPGD6Lyqwaw5+98T4+/MAbOVBbTLhIHVzD68YZm+xkz82f4fIfvxO5Vj3/vBMydVbMZ6HD8P0R3Q+p5ywyLoTq+sp7b2PvL+GzuPXRt+FMuXRoPovHvnc+K0uH1FqJNwvLgsq/s9wQaQmiXCZFEydoDEqCgo0I1cO1bBsBSGGxbtlRdlQTEvGg6OCXLFrdqaQmTbBKxm1zKimshsXjIyqJ64PrHuYjR17DumVHWViY5ZEJtfPnxy2aPcBwi9ZhvXCHmyrEZVsJ3Vuc1+J5il5Pt7V/tI/fEm/mE+u+yj5vwPTr9u1XA3DnC+7mD3a9DgBvoc/Vy1UYbHPHC0xb3vE800e6oDtk4ojySnV1CGaOdNHnTCbkvLq8AdBO7Z7OiYkLTNu2IvCJ82b07w0W5WiWvxcvAmBh3wxfsi/jE+u+ym/tfjP/Zcnj5n4fOfIa3rT/Sj6w6CFzbZlT5VXlC0Cb315nZHIxgqMFNk3HYUetGjiziEA/c1SI0BRsjsdhaPVs7j6gtLX05vsl+zL+brWqmfGyhz7A31/xBfZ5A3zkyGsA+MCih7jtoXdzz/IfcHlxtckf8jskuXGH/aU+w7K+zjqoCZYs85xB2/2OjjDEm5eeOxnAj0dWUtinNr67hy/mu7nzqBzuwNaM7J8/eLmKqDQgctQhNxr0YE87vGn/lfgFQXBUHUiyIQg1hLupy0NY3bpGjK5TIoSak9JBizftv5J7lv+Aq7ap8VZaWSqHOygctbFbUMmrMFh5UpioTVtU6vRhFmfGZiGCCKtSVxmRgIwkHXsgM+1h13TdEM83jqRdTy6h80Cii2ZmGtgtp42cRbZa6m+arURN11XUZRSRz6iH/rEnX0VpW4ZdU0vYkZd07lSLtHA8wAptKuQpjqnV7+3MK8yDkyK/iSGzcVk5fd3NBrxq6Fne9dQttFJV1Hu6VELXu566haFOdUKWtmV4pKE2qWFd76K5M09xVFI/OyS3M0dzrdIiCuM2s/kQ0fSSPni+CZGKEyIRMa2eqGm1Pu6nZbeVwov7HRYizlt4DID/sfSbPFRbx7ueuoW3n/VTPvbkq8x9S9sy3Pjip3jXU7eYa8WcR25CqsgFABZeQ53E3kBA97BS8aaPdiT9jiNgQaDGoCn14nEYPg4/4H5dKXwsTJ79Q7V1vOHZWwGwc6GZ79I2Nefv6ryFoCC5attryE75FLUZKCKLxqDEzQZkFupIhK+K7kjHAV05PZ5DgWf6BmjOCyAMKWQ9ZofUOB5b/yX+ce4cNucrpqTgnWv+iddt+j2kEIaF286FhAWLG/ue4jPTKw0fhexSSWF+JWcg3MF0zlBKpp2pjQHJjX1PcdW21/DI2d8GVIX5D3S/isc3r0U6khefr9jJnho9G1qemu848pbmejkNmXdwzsu8zMtpyRmhWYDgxNi8tNXltuv6c+RiMgVBheKk1U5f93wSq7JzbqAgsi5IJyKKQ32WykaUTgJ4kk4qLn6imFKCOp295dDvVMi6AWHqJIzbDUKLSkunFTuqbdWubdqKbLCdCCz9f5Rzz3ai9srwv7RPFqb8X1PzLaT/5hR/Z3kWFU/1a9COzBj6nQpOCrYuHWUfZ1PXas0MeQuj5UgbU+NDeJb5bVyjRLZaKRDaCX05BQo0KVtYM9f6nYqZ04mWTbas5jtuN+sGhL5SzztEqm+WcjL7LYdiXjvAhUVbGcUTRPp+0t84fissKs0slidMH/udClU/a3g2Bu0IyxPYPuZa2LKxPItjQSdSCIQXJ+/p/xxMKr50MMjMtikK1DOotLIcD2um/aqv+hNJQVVXnLdiy8332ssX/hrxjTNisxBhhKg322LFpdEQe66FVVcqYpQiv+nYa1EaTX7rzDWxfJdCqlLVLyW/0XLkmSEA3KpF+ZCq+BVmLMojmo9xysPyXbBscpNqkZcOu4r8xnGSSESK/MYQygDZvM/HnrmecE8Ju5X064iOSli+ICipF2HwUITQTsHclGfaKkyEVPbkyY9JIjevv/ex9+QVulTDp9vIb04ERMXfxTkiqbJ7cZ/Vdc2PWQi5tG8/ADfvfDOj052Ee0p8rHU9YlsCBCsfirhr96U0tneZa5Er6ZmODBAsshUfCMDMBSFju1VejCwmL9qvQ35z4+7rAKj4iXN7dLoT/6CaU3dhg+pzPdgtQfmQ+rvJzh6iguT4vh565qrkJ+PDwKG+UOKMZJmdVC/PkH+snfwmBcGW0lFAtEC/dZGi3ZNSUjvQCYNqw7lx93XsHB9g+4v/geXb32HmMShKpA2hfuZu3scPBHftvpSBWR9ZUP3q6qtib+omUxEmYzTKJGhM6beMM7jVH3LX7kupHO7gA93KRKz6Wb61+kFWHrqV7q4a31r9IADriu9Wm51tJ6U3T6yL+zxyRmwWSL1AUvaT0wgRfoKCSyM63YrEqaXQhH6AsIUJ2cW/l5oRKo3KjCUzo9F5dQUlDioCO4O5r/AinEaIW7Nwmuq+bk2Dk0SqjF2MWJQaGKPtwaam9u8Ya9d4YoeeFYDla8h4PSRT0UjFRtKW3Qxx5xRa1J1LvnfnMm2U7m3IyhMK3ZqXMM0Zmkq5TtKV1e+6Biv87Lhy/h7aOkyUj+gYE8x15ynPJfd16xFzx4sUU+UBIkdgN32zWaRp9+1pJwmd6lNUODaylZrHuB9RlIwjNcatm1S/2gh78xGlMU0o1OWa+Xbr6u8ysw4bbnyWJ769HtEKsZtJ38RAC3drPjl1Y5r9GNEbV0nTgD1RLChkZGoekRK7Kdh11V0ArLr7NsJSxMpHbmVoqYICHHh2ARtevIMj1S78SPX12Ei3ouufKDHke9jTagOcdQoMzUnNR6Hmxs/rKJcQyBQS9q5rv8Ctj76NwlGbxzcr/4jlCVYeupW9V93FPZVuVj6i/Dn9G8bhr2Mkbuyc/xWa8inkjNks0uE/ALsRqM0i5VCKF06mJnFSG4MIQmgJrFbqHppzIv0CpyWjF76q4xmRyViEHua+VlMlUTkNB0snWzkNmUCv0/DaGJKdyp1wNWGO5ZFy+IGlkYkiUNoFKK4Bt6o3ET0Gp5FRm0VV4jbav3erUpHumhcqtRm2EfYmUHfjSNT9lGF0Up8BZo6XqOjwoHQl7pSN5anxZFJhNqce4Uy5uKkNRDoKJm3mq+mgHfdkZi2s+EBrJc5Ls+nKlIaTqsdpmKylTIo1pWj13Cnb1Cp1plwz347eLNw5eHpiAXYLhB+k+mYTTWXIVCAIUqhOfcikIfam/mkKhWrmLorIzAjuqSjGoMhVfSovnGFsXKfZupLnJoao1bNE+oBwplxmhKLrF60GGV37pOlmsEKJ2wCh0ZVuQ89D6nkCPDC3HmfKVVB5jeCNpKC7q8Y9lW7eVJ7mL7uUeTIxVaYnHE/GCSq94d+bGWIyGFMqdKsniz2XMx5YheFX4KfakIVIlfnKTGSJ8i5+V6Ke5hzHAGtOxVFZXaIXU9XCrTk0+izCDDgtdd+8lHhll0afhVNXamqjz6LsOkl4D72Q4pomtm3MEHu1inrURLsZ4ms1NG2GFI861IbVSAsTWdOW5WeoL1Ce+7oumuXvy6prbsLS3Pa8TwBlxS3HmZ6ybptU7HSuggGZhYKb1qmSDBsnlzE63anGsKpKzUvMELfmUFgzQy1sN0PKRxxsTfbT7LIIdK3TxjIPUdNtxWZIJNvqiYIOecPJNVDDkPXnK/PoRDOkmtGm3cIGtbCgCk7V1N/XFkuinT1Ey0KiUha/09V9sxGBpLZQGpBY8hx1clrcB00/YNR41TH1vKWkMRTxRz+/EYD15+9n5/gAT150H8u/rcyQFWcd5dCWhThNTO1RsbgOlQyFNTOEpZxh4e7qq9Lc2k2YbTdDunxNh2fbRku874lL6FgzQyXfYaIexgx55Fb+sqtmoOHrPvtutTbShZ/TlfVOQ+ajIfMyL/NyWnJmaBackN0JCCkV8OkUO58IE99CmI9DFaf2TZwkOtNP6HqcxRGJW49ohhYigvggI1J9IAKnHp+EbtLWqUaRuh4GFs5zRTqOysTDDsyu0u0eEcytVp/deoTQtqxdj80uV/ltQofC8ZD6sG2+F2E76vKETiSfT5X9GftyTtFngIvW7eeeH1+q+2gjMtBxVFKvlSmMpdT/ekTrmS6KKaRwlBEgQ+yGmsTC8ZBAV6WfCQUdu9UYZs/TfpSMa/hKTkf2fkeButJHnMhAx6TqV2t5QH4PYEnjsygecXjve7/JX3/mdRBh+pY/HtK7ZprZp/vo2PNLzsz03EjZxsmRNleiTMSgrhi39zsrETlYt/XdvPyVzwKw+Rvn8Zdv/zJX5Cf4wJFrAVV7dP26EbY+uhpkA/R6bG3uYWDUxy/axpQKCgpqTi6bZCqjINyPfe98ypNC4ShQUY91xXfTv2Gciamy0iiA7e/8NNffceXJ74hz+k7OMyM3xOqVG7KvpHGNQi/mj9WxDhw1RCAAe/78Ahb+MMKtBmT3jJnqUKJcQs7MIopFU1ULoOd+wU+fWQPA0m+rMU68wCU7I2l1CZbdo6DHNFtKPQsjZCGH0FGOaHIaq7ND9UEzaVvFAjtvX0BPV5U13Qp+fevgj/mdh36b4UctrFDS6FELb+iBw+r+vt/+0moSG1Kp80iJjM2Eo+OmLSmlIhyu1kxuRzQzi9XVybY/HuaCdQcAuH3pN9kXKPv4D3a8zjR177l3cc1PVAm9K1YpNXXbJ85FSPALikA2zjqsLFSLZtF9+9pQk1iWGkPMBhaLnrM2s0dK5PQMaOIeWq2E4DaTMQCrmMdj9/uWs+rSgwDcueI+9gWd3DlyJe9Z+ANWOIrE5oMHX6v6fWyIle9Xc97mZ7GsZMHHPq4YVavHIGt1BdNueQnIq9WCbFb1S4eh6/9Q4K61/8h79t3ErtFB9lyhnJbX77ye+9fez7l/9W76f6HWh1e2EBJmVtksvecIUqcqiFxWmSyNRoKw1Rm6yCi5FmdJp7NjQfXFDxKCYP33h992Fk5d0SHMrFPPZ83HtiNKJTX+VrLpxuAywjCZBym5/9kfsOru21i0XoHuDu4dYOKP/5r6xOHT8nKeEZtFh+iRG6yrsVevAEDUGkSTUyqioR9k81UXUzgwh1VvIo9Pmesip5iyrGyWKJUwduydF5nwasd2hY9vLixjeRFRxiK3Rdm/suUl5DfZrAkrRbUGVj6n+qB3c5HLMnPDOUxcCKVDasG2eqB3a0hhpInlBaZcXGbnKLLlneQviX0HQEJ5l8oriZmeYmYskXGRjabJSYjmqlgdJfZ/ZqG5Tzo8G/tEQPlFep9Vz3dumervoh9UEX5IWMgo5KwuPO316tDsUweTzvoeCFU2IE7wMn23lZ+p7Vo2SzQ905ZTYchoyqlcFj2W7R9dyooVKlfm8KaFagznVOC5MmFWc0ysUr6f3GNlhv/xFExZKfIb4ThmYzfkN7HfwXWRtXqiSfk+olRU49LJbJnv5Nn2+AoWXzxC/YsLmFDcviw9f5SDuuLY8n9u6bkNEX5Ic6hAccvh9tKGMflNTCIUM2FJaa4J2zIJarLlJS+156t7xXlMAJbFrs+uxd2fozOVmNj3jecQhbwO6YZJW7adkErHKfuRZNcfrWXPWz5jQtB/tuTbXHappDl6epvFmWGGCEBYRJ0KH29JCXOuqhOiHW/VBTbZqSzYAjHnJqdfNqu0gYzblrs/tzJCCg3dHlGLs97v4DQlQU6Qd1Mmhd7lRS6bwKbje2reA1AvbmWJxaL1oxxyFU4jM1yjMl0mM+di+TatLnVfV0r19yeEpuINom0x6BMOkkUu4jJzji5bZ7gyleOt1XD56IZ/BuD27NXUNaR8UVeSZDXXzFKZVYVqGgvVGPySixU6+EUH24uwNJ9Fs0fdPydTEGA3o0w2S+dspMeiyWRi+j/AkK3Ep2cb2csJCxfAqtvcu1bldVxbfxv1ZoY/WX8/H5XXU8qpTfuDax8G4CN7bjop6U3dRBhNRUZRkq0az5fjGNo8XCfBlWios5RJv761+kEunL2Ze9f+Ey9f8iEWrVeJfveu/SfeEN3CsSeG8cu6ULdnYYUOjV6HYtoEzmbVRtFqJRqlqxmtZEIMJKUAGan/p0oKouvQCNs2YW1h24ixLG5V1beJrdA4eiOESCJ+bkZtGDq7NP1OLFp/jBt3X2ewFzftux4RfvfkOf0lMu/gnJd5mZfTkjNDs5CAjLCq6gQQTS/BLugdMz8ZYdd9RL2lS7mlEpDCUIW3UrtoccQyFdHtujqlcjMZrFaE07RSaltgMBzS81KVsPQ9owS4JPyA/Jjk4N4BSiM6PNgsUZiIcGoBlpcUHBYxt8UJhL0xnBvCxCRptkzo0MTA478LNFdG3C8pEUHAYP8sd+x7OQCz+7oNjPhgR8LpYbUserRT0i/GILTAVDO3vAjL0/VCcjG/XcrhFUOM476kxxJJpYmlSJJFNtPOEJUCfVm2ZZyZRrvqa/GhkVe0jeGO8ssJ95eY1WbIHa4aY25CnITFUTcWZk5Vgl8KlwMq+cqyjWrehk2xVCp63Meb9l3F7L5uPjTwCvOcAT7U8QoO7h1A9EYJDqelqqJn5xwT0gRUH2Puy3TlL9tSOO7Yh2NZJsNVel5ikka2MkXSzGJhSGZZlVZQpnNX4qIRtpWk0sdaqqfDu0Im1fK0HNw7wKde8TfctO96AO5b8QiFX2MHODM2C1DqVEsvPN9vL4QCuLUI4SmgVhQmhVKEAV9FbZ79zKwkfzwgyFsIbZfbDfVyiAji6uEGrp0G3oC5p2JhTh5aYSIkM2mTmVXXchOqb5YXIrwAu6mxBBrUI2OaNC0iVWndLP4whDh/JNUWKBU03Qc0InVsvJP8DmVe9Y4m+StzK5PFUToMhQkNDe6J1Wdla1uebfqs5ku/yI6TkAXJCEKS4jup+RVhqMaYHk+8wcfqdwr0peayHVq+bGiSJ+87T41hUo1hbmaQrmPSUNjPjSmOyO6DpwbXtVHs2Rkz30b9tgSiUNBrKsUjGml/QRSZ/uz82lp6pyVPHjqP7omA3i1qLp/cfR69FcmN73uUH939orZ5zMwE4NgJjqXZVH0SlvE7yVYL0dHZnuUZKsJgqQ85c4jEKNITfBauE3LPmz7JO//wA2Rn9NooFpU/KWUqK4Smhchm1POKN/PeLnq32LzlyH/F1XGAs3rWcG7fH548p79EzggHpxBiApUddPpUw/8xpI/5Mf9nkDN5zEullP2n88MzYrMAEEJsllK+8N+6H/9/yvyY/3PIf5Qxzzs452Ve5uW0ZH6zmJd5mZfTkjNps/jcv3UH/g1kfsz/OeQ/xJjPGJ/FvMzLvJzZciZpFvMyL/NyBsv8ZjEv8zIvpyXzm8W8zMu8nJbMbxbzMi/zcloyv1nMy7zMy2nJ/wf3fOSVOu3KJgAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f855b7b70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 9 of size 183 built in 2.0564873218536377 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 9.0, 'k_func': 'MinMax'} is: \n",
-      "[[1.         0.38888889 0.125      ... 0.015625   0.015625   0.01587302]\n",
-      " [0.38888889 1.         0.08695652 ... 0.01481481 0.01481481 0.01503759]\n",
-      " [0.125      0.08695652 1.         ... 0.07438017 0.07438017 0.07563025]\n",
-      " ...\n",
-      " [0.015625   0.01481481 0.07438017 ... 1.         0.58169935 0.38728324]\n",
-      " [0.015625   0.01481481 0.07438017 ... 0.58169935 1.         0.43712575]\n",
-      " [0.01587302 0.01503759 0.07563025 ... 0.38728324 0.43712575 1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f854d7160>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 10 of size 183 built in 2.443324565887451 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 10.0, 'k_func': 'tanimoto'} is: \n",
-      "[[1.         0.44444444 0.11111111 ... 0.03030303 0.02439024 0.02040816]\n",
-      " [0.44444444 1.         0.08333333 ... 0.02777778 0.02272727 0.01923077]\n",
-      " [0.11111111 0.08333333 1.         ... 0.17241379 0.13513514 0.11111111]\n",
-      " ...\n",
-      " [0.03030303 0.02777778 0.17241379 ... 1.         0.73684211 0.37037037]\n",
-      " [0.02439024 0.02272727 0.13513514 ... 0.73684211 1.         0.43859649]\n",
-      " [0.02040816 0.01923077 0.11111111 ... 0.37037037 0.43859649 1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f86de0b38>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 10 of size 183 built in 2.350839853286743 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'depth': 10.0, 'k_func': 'MinMax'} is: \n",
-      "[[1.         0.38888889 0.125      ... 0.015625   0.015625   0.015625  ]\n",
-      " [0.38888889 1.         0.08695652 ... 0.01481481 0.01481481 0.01481481]\n",
-      " [0.125      0.08695652 1.         ... 0.07438017 0.07438017 0.07438017]\n",
-      " ...\n",
-      " [0.015625   0.01481481 0.07438017 ... 1.         0.58169935 0.38285714]\n",
-      " [0.015625   0.01481481 0.07438017 ... 0.58169935 1.         0.43195266]\n",
-      " [0.015625   0.01481481 0.07438017 ... 0.38285714 0.43195266 1.        ]]\n"
-     ]
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1f86e5e1d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "3. Fitting and predicting using nested cross validation. This could really take a while...\n",
-      "calculate performance:   0%|          | 2/13860 [00:00<13:28, 17.14it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/sklearn/linear_model/ridge.py:154: UserWarning: Singular matrix in solving dual problem. Using least-squares solution instead.\n",
-      "  warnings.warn(\"Singular matrix in solving dual problem. Using \"\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "                                                                            \n",
-      "4. Getting final performances...\n",
-      "\n",
-      "best_params_out:  [{'depth': 2.0, 'k_func': 'MinMax'}]\n",
-      "best_params_in:  [{'alpha': 0.07943282347242814}]\n",
-      "best_val_perf:  9.997519678873179\n",
-      "best_val_std:  0.8300102352356199\n",
-      "final_performance:  10.733201547185335\n",
-      "final_confidence:  5.674809916065444\n",
-      "train_performance:  5.4765013560475015\n",
-      "train_std:  0.23352968995162204\n",
-      "time to calculate gram matrix:  0.5694379806518555 s\n",
-      "\n",
-      "params                                                      train_perf       valid_perf       test_perf           gram_matrix_time\n",
-      "----------------------------------------------------------  ---------------  ---------------  ----------------  ------------------\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '1.00e-02'}   42.32±0.81       42.41±0.79       43.41±6.46                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '1.00e-02'}     11.33±0.42       14.84±3.42       14.33±3.66                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '1.00e-02'}   38.22±0.71       41.10±1.37       41.97±6.37                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '1.00e-02'}     10.47±0.27       26.86±7.07       18.53±24.16                     0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '1.00e-02'}   34.88±0.52       42.17±3.52       41.20±13.03                     0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '1.00e-02'}     6.04±1.42        24.64±7.70       29.59±31.75                     0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '1.00e-02'}   28.11±0.49       66.39±18.97      84.47±114.38                    0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '1.00e-02'}     51.98±193.56     203.10±618.19    198.30±673.21                   0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '1.00e-02'}   19.95±1.57       54.94±14.26      40.43±57.71                     0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '1.00e-02'}     42.18±95.39      268.51±577.11    169.75±280.85                   0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '1.00e-02'}   18.09±1.62       58.68±21.89      33.96±12.40                     0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '1.00e-02'}     45.42±64.13      253.47±261.03    349.89±490.15                   0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '1.00e-02'}   14.49±0.97       69.15±13.11      79.04±116.21                    1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '1.00e-02'}     101.44±318.73    740.76±2656.68   699.40±1944.24                  1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '1.00e-02'}   14.48±1.34       73.34±30.65      78.79±81.69                     1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '1.00e-02'}     199.01±686.71    1064.00±3605.01  1224.24±3274.23                 1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '1.00e-02'}   14.90±3.57       79.58±21.24      105.43±115.74                   1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '1.00e-02'}     96.65±180.19     395.95±314.77    672.60±1045.01                  1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '1.00e-02'}   14.43±2.48       82.87±20.21      82.90±86.66                     2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '1.00e-02'}     68.04±68.71      404.44±372.45    351.74±344.39                   2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '1.00e-02'}  14.39±2.22       72.83±20.96      73.24±86.32                     2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '1.00e-02'}    67.44±149.21     411.60±914.99    468.77±744.76                   2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '1.41e-02'}   42.32±0.81       42.41±0.79       43.41±6.46                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '1.41e-02'}     11.32±0.42       14.35±2.39       13.99±3.09                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '1.41e-02'}   38.21±0.71       40.71±1.07       41.76±6.20                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '1.41e-02'}     10.46±0.27       22.60±4.98       16.75±17.01                     0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '1.41e-02'}   34.89±0.52       40.71±2.35       39.66±9.78                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '1.41e-02'}     5.25±0.53        17.97±3.79       21.40±22.78                     0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '1.41e-02'}   28.05±0.49       55.14±13.11      67.61±77.83                     0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '1.41e-02'}     30.91±73.52      133.89±328.37    117.78±294.95                   0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '1.41e-02'}   19.66±0.92       44.88±9.52       34.52±38.66                     0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '1.41e-02'}     47.58±113.12     210.11±422.78    107.80±169.12                   0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '1.41e-02'}   17.71±0.95       47.66±15.05      30.17±8.10                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '1.41e-02'}     69.13±158.72     370.77±980.73    263.75±422.53                   0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '1.41e-02'}   14.14±0.72       53.96±9.05       60.65±80.08                     1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '1.41e-02'}     36.25±36.61      199.29±170.57    198.99±212.11                   1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '1.41e-02'}   13.95±1.12       56.42±18.09      61.81±57.55                     1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '1.41e-02'}     207.92±631.69    1115.80±3523.44  463.61±927.33                   1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '1.41e-02'}   14.30±2.51       61.86±14.80      80.17±79.28                     1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '1.41e-02'}     832.03±4232.86   1984.30±9289.73  7236.35±38021.47                1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '1.41e-02'}   13.53±1.02       62.28±9.70       61.63±58.57                     2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '1.41e-02'}     37.59±33.06      187.44±114.59    226.13±266.69                   2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '1.41e-02'}  15.08±3.41       63.87±21.09      60.31±59.63                     2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '1.41e-02'}    29.87±21.20      197.52±203.13    255.95±271.57                   2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '2.00e-02'}   42.32±0.81       42.41±0.79       43.41±6.46                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '2.00e-02'}     11.31±0.41       13.96±1.68       13.72±2.74                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '2.00e-02'}   38.21±0.71       40.45±0.95       41.60±6.09                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '2.00e-02'}     10.45±0.27       19.58±3.51       15.50±11.98                     0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '2.00e-02'}   34.90±0.52       39.68±1.59       38.62±7.79                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '2.00e-02'}     5.00±0.42        14.68±2.81       17.01±16.71                     0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '2.00e-02'}   27.99±0.49       47.19±8.97       55.71±52.05                     0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '2.00e-02'}     17.81±30.36      54.41±77.99      77.22±161.79                    0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '2.00e-02'}   19.59±0.78       38.11±6.47       30.70±25.44                     0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '2.00e-02'}     16.41±24.71      72.53±101.17     69.27±145.21                    0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '2.00e-02'}   17.47±0.62       39.95±10.23      27.61±5.54                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '2.00e-02'}     80.91±249.44     455.85±1356.56   353.46±1028.08                  0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '2.00e-02'}   13.97±0.59       43.44±6.19       47.99±54.52                     1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '2.00e-02'}     18.35±18.86      127.61±196.94    102.08±117.13                   1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '2.00e-02'}   13.62±0.97       44.82±10.55      49.58±40.28                     1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '2.00e-02'}     30.56±38.74      158.08±193.73    190.97±313.69                   1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '2.00e-02'}   13.68±1.78       49.42±10.10      61.15±54.11                     1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '2.00e-02'}     130.65±499.79    248.13±379.19    558.04±2064.02                  1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '2.00e-02'}   14.15±2.16       52.37±9.10       50.91±39.62                     2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '2.00e-02'}     52.54±69.20      256.53±340.01    212.27±241.27                   2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '2.00e-02'}  15.58±9.62       48.54±13.06      55.56±58.51                     2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '2.00e-02'}    83.81±194.46     588.26±1568.45   322.88±617.46                   2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '2.82e-02'}   42.32±0.81       42.41±0.79       43.40±6.46                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '2.82e-02'}     11.31±0.41       13.66±1.20       13.51±2.51                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '2.82e-02'}   38.21±0.71       40.25±0.91       41.46±6.01                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '2.82e-02'}     10.45±0.26       17.43±2.47       14.61±8.44                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '2.82e-02'}   34.91±0.52       38.95±1.15       37.91±6.63                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '2.82e-02'}     4.89±0.31        12.34±1.78       14.14±12.47                     0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '2.82e-02'}   27.92±0.49       41.57±6.07       47.34±33.96                     0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '2.82e-02'}     5.56±1.59        17.74±5.03       17.52±13.19                     0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '2.82e-02'}   19.58±0.69       33.40±4.34       28.06±16.37                     0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '2.82e-02'}     10.67±10.41      58.97±103.68     34.23±33.80                     0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '2.82e-02'}   17.33±0.47       34.54±6.84       25.84±4.06                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '2.82e-02'}     10.77±7.93       49.39±33.46      43.68±39.86                     0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '2.82e-02'}   13.91±0.52       36.18±4.19       39.31±36.48                     1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '2.82e-02'}     12.07±9.08       61.36±57.20      72.92±111.20                    1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '2.82e-02'}   13.44±0.84       36.93±6.24       40.83±27.89                     1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '2.82e-02'}     15.52±11.99      86.53±129.75     79.59±97.06                     1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '2.82e-02'}   13.25±1.31       39.93±6.89       47.84±36.09                     1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '2.82e-02'}     25.53±44.06      136.67±341.60    169.13±467.04                   1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '2.82e-02'}   13.08±0.78       40.73±5.19       39.89±26.19                     2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '2.82e-02'}     15.80±13.47      67.13±36.88      64.90±52.90                     2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '2.82e-02'}  13.12±0.71       38.00±6.65       38.18±28.73                     2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '2.82e-02'}    21.19±22.84      101.93±116.64    121.58±144.93                   2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '3.98e-02'}   42.32±0.81       42.41±0.79       43.40±6.46                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '3.98e-02'}     11.31±0.40       13.42±0.89       13.32±2.37                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '3.98e-02'}   38.21±0.71       40.10±0.89       41.33±5.94                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '3.98e-02'}     10.45±0.26       15.89±1.75       13.97±5.99                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '3.98e-02'}   34.93±0.51       38.44±0.92       37.42±5.98                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '3.98e-02'}     4.94±0.27        11.02±1.32       12.37±9.44                      0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '3.98e-02'}   27.87±0.49       37.63±4.06       41.53±21.44                     0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '3.98e-02'}     4.88±0.41        13.55±1.79       12.90±7.69                      0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '3.98e-02'}   19.63±0.63       30.15±2.88       26.26±10.33                     0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '3.98e-02'}     6.42±3.13        21.05±9.59       18.93±13.63                     0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '3.98e-02'}   17.26±0.39       30.75±4.48       24.62±3.31                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '3.98e-02'}     7.14±3.76        26.32±17.76      26.57±23.12                     0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '3.98e-02'}   13.95±0.48       31.20±2.81       33.42±23.83                     1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '3.98e-02'}     7.27±1.01        29.10±6.02       30.17±16.80                     1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '3.98e-02'}   13.38±0.73       31.61±3.81       34.62±19.07                     1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '3.98e-02'}     8.26±1.28        32.71±5.48       31.17±14.12                     1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '3.98e-02'}   13.11±0.97       33.75±4.66       38.52±23.24                     1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '3.98e-02'}     8.91±2.12        37.38±12.89      35.01±18.16                     1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '3.98e-02'}   12.86±0.45       34.14±3.22       33.68±16.95                     2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '3.98e-02'}     9.38±4.11        37.88±20.27      37.65±26.16                     2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '3.98e-02'}  13.04±0.59       32.84±4.64       32.77±19.75                     2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '3.98e-02'}    8.63±1.80        35.88±10.73      40.20±22.02                     2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '5.62e-02'}   42.32±0.81       42.41±0.79       43.40±6.46                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '5.62e-02'}     11.31±0.39       13.22±0.70       13.17±2.27                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '5.62e-02'}   38.21±0.70       39.96±0.87       41.20±5.89                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '5.62e-02'}     10.46±0.25       14.78±1.24       13.50±4.33                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '5.62e-02'}   34.96±0.51       38.06±0.81       37.08±5.62                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '5.62e-02'}     5.13±0.24        10.29±1.02       11.30±7.25                      0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '5.62e-02'}   27.83±0.50       34.90±2.69       37.58±13.07                     0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '5.62e-02'}     4.95±0.22        12.13±1.12       11.41±5.56                      0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '5.62e-02'}   19.76±0.58       27.96±1.87       25.06±6.65                      0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '5.62e-02'}     5.30±0.38        14.45±1.82       14.54±5.92                      0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '5.62e-02'}   17.27±0.35       28.13±2.85       23.77±3.00                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '5.62e-02'}     5.90±0.63        18.01±2.46       19.05±11.16                     0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '5.62e-02'}   14.09±0.46       27.84±1.87       29.47±15.11                     1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '5.62e-02'}     6.70±0.63        22.31±3.43       22.82±11.06                     1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '5.62e-02'}   13.44±0.64       28.09±2.41       30.28±12.97                     1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '5.62e-02'}     7.19±1.17        24.49±5.14       22.81±10.78                     1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '5.62e-02'}   13.14±0.75       29.56±3.22       32.00±14.26                     1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '5.62e-02'}     7.42±0.86        25.37±3.62       23.82±9.67                      1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '5.62e-02'}   12.94±0.39       29.96±2.22       29.91±10.66                     2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '5.62e-02'}     10.82±19.08      43.73±102.72     32.02±42.58                     2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '5.62e-02'}  13.29±0.83       30.58±5.83       30.05±13.67                     2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '5.62e-02'}    7.55±1.58        25.66±5.21       30.04±22.79                     2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '7.94e-02'}   42.32±0.81       42.40±0.79       43.40±6.46                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '7.94e-02'}     11.33±0.38       13.06±0.58       13.05±2.20                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '7.94e-02'}   38.21±0.70       39.83±0.85       41.06±5.84                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '7.94e-02'}     10.49±0.24       14.00±0.90       13.16±3.25                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '7.94e-02'}   34.99±0.51       37.79±0.76       36.82±5.42                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '7.94e-02'}     5.48±0.23        10.00±0.83       10.73±5.67                      0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '7.94e-02'}   27.83±0.50       33.09±1.81       35.05±7.94                      0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '7.94e-02'}     5.28±0.18        11.53±0.82       10.81±4.25                      0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '7.94e-02'}   19.97±0.54       26.58±1.21       24.32±4.85                      0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '7.94e-02'}     5.48±0.27        12.99±1.12       13.63±4.95                      0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '7.94e-02'}   17.37±0.33       26.38±1.79       23.22±2.93                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '7.94e-02'}     5.96±0.43        15.63±1.50       16.45±7.82                      0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '7.94e-02'}   14.35±0.44       25.65±1.29       26.90±9.40                      1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '7.94e-02'}     6.62±0.45        18.62±2.24       19.24±8.12                      1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '7.94e-02'}   13.63±0.57       25.84±1.58       27.33±9.08                      1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '7.94e-02'}     6.79±0.39        19.49±1.87       18.00±5.14                      1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '7.94e-02'}   13.33±0.60       26.88±2.23       27.53±8.25                      1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '7.94e-02'}     7.06±0.58        20.60±1.93       19.31±7.21                      1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '7.94e-02'}   13.15±0.36       27.20±1.56       27.17±6.93                      2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '7.94e-02'}     7.16±0.66        20.80±1.85       20.69±7.71                      2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '7.94e-02'}  13.32±0.49       26.90±2.22       26.86±9.78                      2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '7.94e-02'}    7.05±0.45        20.39±2.19       20.95±7.88                      2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '1.12e-01'}   42.32±0.81       42.40±0.79       43.39±6.45                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '1.12e-01'}     11.36±0.37       12.94±0.51       12.96±2.15                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '1.12e-01'}   38.21±0.70       39.71±0.82       40.92±5.81                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '1.12e-01'}     10.55±0.23       13.46±0.67       12.93±2.61                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '1.12e-01'}   35.04±0.51       37.58±0.73       36.62±5.31                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '1.12e-01'}     5.98±0.23        10.03±0.70       10.55±4.54                      0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '1.12e-01'}   27.88±0.50       31.98±1.27       33.57±5.36                      0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '1.12e-01'}     5.79±0.18        11.39±0.65       10.71±3.40                      0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '1.12e-01'}   20.27±0.51       25.83±0.82       23.96±4.30                      0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '1.12e-01'}     5.90±0.23        12.47±0.81       13.37±4.54                      0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '1.12e-01'}   17.59±0.31       25.30±1.19       22.92±2.97                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '1.12e-01'}     6.30±0.34        14.56±1.07       15.11±5.74                      0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '1.12e-01'}   14.75±0.43       24.33±0.97       25.35±6.23                      1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '1.12e-01'}     6.84±0.35        16.57±1.21       17.37±6.59                      1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '1.12e-01'}   13.99±0.51       24.50±1.09       25.46±7.01                      1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '1.12e-01'}     6.96±0.32        17.39±1.33       16.17±4.01                      1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '1.12e-01'}   13.72±0.51       25.28±1.55       24.62±4.92                      1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '1.12e-01'}     7.18±0.49        18.26±1.35       17.12±6.04                      1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '1.12e-01'}   13.54±0.33       25.49±1.17       25.72±5.32                      2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '1.12e-01'}     7.26±0.45        18.38±1.27       18.32±5.70                      2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '1.12e-01'}  13.72±0.47       25.49±1.62       25.50±7.65                      2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '1.12e-01'}    7.20±0.35        18.18±1.51       17.80±5.96                      2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '1.58e-01'}   42.32±0.81       42.40±0.79       43.38±6.45                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '1.58e-01'}     11.43±0.37       12.87±0.47       12.91±2.12                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '1.58e-01'}   38.22±0.70       39.59±0.80       40.77±5.78                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '1.58e-01'}     10.64±0.22       13.13±0.51       12.79±2.28                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '1.58e-01'}   35.09±0.51       37.42±0.71       36.46±5.26                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '1.58e-01'}     6.66±0.23        10.33±0.62       10.68±3.77                      0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '1.58e-01'}   28.00±0.50       31.39±0.97       32.86±4.47                      0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '1.58e-01'}     6.48±0.19        11.56±0.54       10.96±2.86                      0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '1.58e-01'}   20.70±0.48       25.57±0.63       23.90±4.23                      0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '1.58e-01'}     6.52±0.21        12.45±0.63       13.52±4.42                      0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '1.58e-01'}   17.97±0.30       24.80±0.94       22.84±3.08                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '1.58e-01'}     6.87±0.29        14.21±0.84       14.53±4.47                      0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '1.58e-01'}   15.33±0.43       23.71±0.85       24.59±5.09                      1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '1.58e-01'}     7.32±0.31        15.70±0.92       16.53±5.82                      1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '1.58e-01'}   14.54±0.46       23.87±0.84       24.45±6.22                      1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '1.58e-01'}     7.41±0.28        16.42±1.04       15.39±3.73                      1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '1.58e-01'}   14.32±0.45       24.50±1.14       22.96±4.18                      1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '1.58e-01'}     7.61±0.44        17.11±1.01       16.11±5.53                      1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '1.58e-01'}   14.14±0.31       24.60±0.99       25.11±5.14                      2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '1.58e-01'}     7.69±0.39        17.24±1.00       17.22±4.66                      2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '1.58e-01'}  14.32±0.45       24.82±1.27       24.86±6.77                      2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '1.58e-01'}    7.64±0.30        17.14±1.12       16.22±5.12                      2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '2.24e-01'}   42.31±0.81       42.40±0.79       43.37±6.44                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '2.24e-01'}     11.54±0.36       12.88±0.44       12.94±2.10                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '2.24e-01'}   38.24±0.70       39.49±0.77       40.64±5.77                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '2.24e-01'}     10.81±0.21       12.98±0.41       12.75±2.15                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '2.24e-01'}   35.17±0.51       37.31±0.70       36.33±5.23                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '2.24e-01'}     7.52±0.23        10.87±0.56       11.09±3.30                      0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '2.24e-01'}   28.19±0.49       31.18±0.79       32.66±4.29                      0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '2.24e-01'}     7.33±0.20        11.99±0.47       11.47±2.53                      0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '2.24e-01'}   21.26±0.45       25.70±0.56       24.08±4.26                      0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '2.24e-01'}     7.34±0.19        12.78±0.52       13.98±4.43                      0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '2.24e-01'}   18.54±0.29       24.77±0.87       22.96±3.23                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '2.24e-01'}     7.68±0.26        14.36±0.69       14.49±3.73                      0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '2.24e-01'}   16.12±0.42       23.65±0.81       24.46±4.97                      1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '2.24e-01'}     8.05±0.28        15.52±0.77       16.36±5.48                      1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '2.24e-01'}   15.34±0.42       23.79±0.74       24.13±6.08                      1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '2.24e-01'}     8.15±0.24        16.19±0.85       15.28±3.79                      1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '2.24e-01'}   15.17±0.41       24.36±0.91       22.36±4.57                      1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '2.24e-01'}     8.33±0.39        16.75±0.80       15.87±5.44                      1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '2.24e-01'}   14.98±0.29       24.36±0.90       25.17±5.35                      2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '2.24e-01'}     8.41±0.35        16.90±0.83       16.94±4.25                      2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '2.24e-01'}  15.17±0.43       24.73±1.10       24.78±6.55                      2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '2.24e-01'}    8.38±0.26        16.89±0.90       15.61±4.90                      2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '3.16e-01'}   42.31±0.81       42.40±0.79       43.36±6.43                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '3.16e-01'}     11.74±0.35       12.98±0.42       13.06±2.11                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '3.16e-01'}   38.27±0.69       39.40±0.75       40.51±5.78                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '3.16e-01'}     11.09±0.20       13.04±0.35       12.83±2.15                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '3.16e-01'}   35.27±0.51       37.24±0.68       36.24±5.23                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '3.16e-01'}     8.56±0.23        11.65±0.51       11.75±3.10                      0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '3.16e-01'}   28.48±0.49       31.21±0.69       32.75±4.31                      0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '3.16e-01'}     8.38±0.20        12.66±0.41       12.24±2.36                      0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '3.16e-01'}   21.97±0.44       26.13±0.53       24.47±4.30                      0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '3.16e-01'}     8.37±0.19        13.42±0.46       14.74±4.52                      0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '3.16e-01'}   19.34±0.29       25.12±0.83       23.28±3.44                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '3.16e-01'}     8.74±0.24        14.90±0.59       14.90±3.35                      0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '3.16e-01'}   17.15±0.42       24.03±0.78       24.80±5.04                      1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '3.16e-01'}     9.07±0.27        15.85±0.68       16.73±5.37                      1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '3.16e-01'}   16.42±0.39       24.16±0.70       24.35±6.16                      1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '3.16e-01'}     9.19±0.21        16.51±0.72       15.71±3.95                      1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '3.16e-01'}   16.30±0.38       24.72±0.79       22.63±4.92                      1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '3.16e-01'}     9.37±0.34        17.00±0.67       16.20±5.57                      1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '3.16e-01'}   16.11±0.28       24.66±0.84       25.76±5.49                      2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '3.16e-01'}     9.46±0.31        17.17±0.73       17.31±4.21                      2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '3.16e-01'}  16.31±0.42       25.11±1.00       25.17±6.56                      2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '3.16e-01'}    9.45±0.23        17.22±0.77       15.71±4.99                      2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '4.47e-01'}   42.31±0.81       42.39±0.79       43.34±6.42                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '4.47e-01'}     12.07±0.33       13.24±0.39       13.33±2.16                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '4.47e-01'}   38.31±0.69       39.33±0.73       40.40±5.80                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '4.47e-01'}     11.55±0.20       13.34±0.30       13.09±2.24                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '4.47e-01'}   35.42±0.51       37.23±0.67       36.19±5.23                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '4.47e-01'}     9.81±0.23        12.68±0.48       12.69±3.09                      0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '4.47e-01'}   28.87±0.48       31.40±0.63       33.02±4.40                      0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '4.47e-01'}     9.64±0.20        13.58±0.37       13.27±2.32                      0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '4.47e-01'}   22.87±0.42       26.76±0.52       25.03±4.36                      0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '4.47e-01'}     9.67±0.19        14.35±0.43       15.78±4.65                      0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '4.47e-01'}   20.38±0.29       25.77±0.79       23.81±3.69                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '4.47e-01'}     10.11±0.23       15.80±0.51       15.71±3.18                      0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '4.47e-01'}   18.44±0.42       24.75±0.74       25.48±5.10                      1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '4.47e-01'}     10.42±0.26       16.63±0.62       17.57±5.37                      1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '4.47e-01'}   17.80±0.37       24.89±0.68       25.00±6.34                      1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '4.47e-01'}     10.58±0.18       17.31±0.63       16.59±4.12                      1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '4.47e-01'}   17.76±0.36       25.47±0.72       23.50±5.19                      1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '4.47e-01'}     10.77±0.29       17.76±0.58       16.99±5.82                      1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '4.47e-01'}   17.57±0.27       25.39±0.79       26.75±5.54                      2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '4.47e-01'}     10.88±0.28       17.96±0.67       18.22±4.33                      2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '4.47e-01'}  17.78±0.41       25.88±0.95       25.95±6.61                      2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '4.47e-01'}    10.89±0.22       18.04±0.69       16.42±5.18                      2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '6.31e-01'}   42.30±0.81       42.39±0.79       43.32±6.40                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '6.31e-01'}     12.60±0.31       13.71±0.37       13.80±2.28                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '6.31e-01'}   38.39±0.68       39.31±0.71       40.32±5.85                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '6.31e-01'}     12.27±0.19       13.94±0.27       13.57±2.42                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '6.31e-01'}   35.64±0.52       37.28±0.67       36.20±5.25                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '6.31e-01'}     11.30±0.23       13.97±0.44       13.91±3.22                      0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '6.31e-01'}   29.37±0.48       31.73±0.59       33.40±4.54                      0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '6.31e-01'}     11.16±0.20       14.80±0.33       14.57±2.39                      0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '6.31e-01'}   23.95±0.42       27.58±0.52       25.77±4.44                      0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '6.31e-01'}     11.26±0.20       15.60±0.42       17.13±4.83                      0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '6.31e-01'}   21.69±0.30       26.66±0.74       24.57±3.97                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '6.31e-01'}     11.81±0.22       17.06±0.45       16.92±3.13                      0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '6.31e-01'}   20.01±0.42       25.75±0.69       26.39±5.19                      1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '6.31e-01'}     12.13±0.26       17.82±0.58       18.86±5.46                      1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '6.31e-01'}   19.51±0.36       25.93±0.68       26.02±6.55                      1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '6.31e-01'}     12.37±0.16       18.54±0.56       17.90±4.30                      1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '6.31e-01'}   19.55±0.34       26.55±0.66       24.82±5.49                      1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '6.31e-01'}     12.59±0.25       19.00±0.51       18.24±6.12                      1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '6.31e-01'}   19.39±0.28       26.46±0.76       28.07±5.58                      2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '6.31e-01'}     12.71±0.25       19.21±0.62       19.61±4.52                      2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '6.31e-01'}  19.60±0.41       26.98±0.91       27.08±6.66                      2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '6.31e-01'}    12.75±0.21       19.31±0.63       17.67±5.38                      2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '8.91e-01'}   42.30±0.81       42.39±0.79       43.29±6.38                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '8.91e-01'}     13.41±0.28       14.47±0.35       14.54±2.46                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '8.91e-01'}   38.52±0.68       39.34±0.69       40.29±5.91                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '8.91e-01'}     13.32±0.18       14.90±0.26       14.33±2.68                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '8.91e-01'}   35.92±0.52       37.41±0.67       36.27±5.26                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '8.91e-01'}     13.05±0.23       15.54±0.40       15.45±3.41                      0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '8.91e-01'}   30.00±0.47       32.18±0.58       33.91±4.69                      0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '8.91e-01'}     12.99±0.19       16.34±0.30       16.20±2.54                      0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '8.91e-01'}   25.23±0.41       28.58±0.53       26.68±4.55                      0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '8.91e-01'}     13.21±0.21       17.20±0.43       18.84±5.04                      0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '8.91e-01'}   23.27±0.31       27.79±0.69       25.60±4.27                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '8.91e-01'}     13.90±0.21       18.72±0.41       18.55±3.15                      0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '8.91e-01'}   21.88±0.42       27.03±0.64       27.52±5.32                      1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '8.91e-01'}     14.27±0.27       19.46±0.55       20.59±5.60                      1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '8.91e-01'}   21.56±0.38       27.29±0.68       27.39±6.77                      1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '8.91e-01'}     14.60±0.16       20.23±0.51       19.65±4.53                      1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '8.91e-01'}   21.70±0.34       27.96±0.62       26.53±5.83                      1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '8.91e-01'}     14.86±0.23       20.70±0.46       19.97±6.43                      1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '8.91e-01'}   21.57±0.30       27.90±0.73       29.71±5.64                      2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '8.91e-01'}     14.99±0.23       20.93±0.58       21.48±4.74                      2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '8.91e-01'}  21.80±0.42       28.42±0.87       28.58±6.70                      2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '8.91e-01'}    15.06±0.22       21.04±0.59       19.43±5.60                      2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '1.26e+00'}   42.31±0.81       42.40±0.79       43.26±6.35                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '1.26e+00'}     14.56±0.25       15.56±0.33       15.59±2.73                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '1.26e+00'}   38.70±0.67       39.42±0.68       40.32±5.98                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '1.26e+00'}     14.77±0.18       16.26±0.25       15.42±3.02                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '1.26e+00'}   36.29±0.53       37.63±0.67       36.42±5.28                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '1.26e+00'}     15.10±0.22       17.41±0.37       17.34±3.65                      0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '1.26e+00'}   30.81±0.47       32.79±0.58       34.58±4.87                      0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '1.26e+00'}     15.20±0.18       18.26±0.28       18.19±2.79                      0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '1.26e+00'}   26.74±0.41       29.76±0.55       27.78±4.69                      0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '1.26e+00'}     15.57±0.23       19.21±0.43       20.93±5.32                      0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '1.26e+00'}   25.13±0.32       29.17±0.64       26.93±4.56                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '1.26e+00'}     16.42±0.21       20.81±0.37       20.61±3.28                      0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '1.26e+00'}   24.06±0.42       28.62±0.59       28.88±5.51                      1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '1.26e+00'}     16.88±0.28       21.56±0.53       22.79±5.82                      1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '1.26e+00'}   23.96±0.40       29.00±0.68       29.16±6.98                      1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '1.26e+00'}     17.32±0.17       22.40±0.47       21.89±4.82                      1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '1.26e+00'}   24.22±0.35       29.73±0.61       28.65±6.16                      1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '1.26e+00'}     17.62±0.24       22.89±0.42       22.19±6.72                      1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '1.26e+00'}   24.15±0.33       29.71±0.70       31.69±5.73                      2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '1.26e+00'}     17.76±0.22       23.12±0.56       23.83±4.97                      2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '1.26e+00'}  24.40±0.44       30.23±0.84       30.48±6.73                      2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '1.26e+00'}    17.86±0.24       23.24±0.56       21.70±5.88                      2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '1.78e+00'}   42.33±0.81       42.42±0.79       43.23±6.31                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '1.78e+00'}     16.11±0.22       17.06±0.31       17.01±3.09                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '1.78e+00'}   38.94±0.66       39.58±0.67       40.42±6.06                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '1.78e+00'}     16.66±0.17       18.05±0.23       16.87±3.45                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '1.78e+00'}   36.77±0.53       37.96±0.68       36.66±5.29                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '1.78e+00'}     17.50±0.22       19.62±0.34       19.61±3.93                      0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '1.78e+00'}   31.82±0.47       33.61±0.57       35.43±5.08                      0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '1.78e+00'}     17.82±0.17       20.60±0.26       20.58±3.13                      0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '1.78e+00'}   28.48±0.41       31.17±0.56       29.09±4.87                      0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '1.78e+00'}     18.40±0.25       21.67±0.44       23.46±5.68                      0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '1.78e+00'}   27.29±0.34       30.84±0.60       28.63±4.84                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '1.78e+00'}     19.43±0.20       23.37±0.35       23.11±3.54                      0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '1.78e+00'}   26.58±0.43       30.56±0.53       30.54±5.76                      1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '1.78e+00'}     19.99±0.29       24.17±0.53       25.48±6.11                      1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '1.78e+00'}   26.75±0.42       31.11±0.68       31.36±7.18                      1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '1.78e+00'}     20.56±0.18       25.07±0.44       24.63±5.20                      1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '1.78e+00'}   27.14±0.36       31.91±0.61       31.18±6.49                      1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '1.78e+00'}     20.91±0.27       25.59±0.40       24.93±7.01                      1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '1.78e+00'}   27.14±0.36       31.95±0.68       34.05±5.84                      2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '1.78e+00'}     21.06±0.23       25.82±0.54       26.69±5.21                      2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '1.78e+00'}  27.41±0.45       32.46±0.81       32.82±6.79                      2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '1.78e+00'}    21.18±0.25       25.94±0.54       24.49±6.24                      2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '2.51e+00'}   42.39±0.81       42.48±0.79       43.22±6.27                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '2.51e+00'}     18.35±0.66       19.20±0.71       19.08±3.44                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '2.51e+00'}   39.27±0.66       39.82±0.66       40.61±6.15                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '2.51e+00'}     19.00±0.16       20.28±0.22       18.70±3.97                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '2.51e+00'}   37.36±0.54       38.41±0.69       37.03±5.29                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '2.51e+00'}     20.29±0.22       22.19±0.32       22.27±4.28                      0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '2.51e+00'}   33.07±0.47       34.66±0.58       36.51±5.32                      0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '2.51e+00'}     20.89±0.16       23.38±0.26       23.41±3.57                      0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '2.51e+00'}   30.51±0.42       32.84±0.58       30.63±5.09                      0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '2.51e+00'}     21.77±0.36       24.70±0.65       26.52±6.25                      0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '2.51e+00'}   29.80±0.35       32.85±0.58       30.76±5.15                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '2.51e+00'}     23.06±0.59       26.52±0.62       26.23±4.19                      0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '2.51e+00'}   29.49±0.43       32.91±0.49       32.55±6.12                      1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '2.51e+00'}     23.87±1.26       27.51±1.30       28.92±6.69                      1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '2.51e+00'}   29.94±0.44       33.66±0.67       34.04±7.41                      1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '2.51e+00'}     24.34±0.21       28.27±0.40       27.93±5.64                      1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '2.51e+00'}   30.48±0.38       34.54±0.62       34.17±6.83                      1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '2.51e+00'}     24.76±0.34       28.84±0.44       28.26±7.30                      1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '2.51e+00'}   30.56±0.39       34.66±0.66       36.85±6.00                      2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '2.51e+00'}     24.90±0.25       29.05±0.54       30.06±5.48                      2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '2.51e+00'}  30.85±0.46       35.14±0.77       35.62±6.91                      2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '2.51e+00'}    25.13±0.54       29.26±0.78       27.82±6.67                      2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '3.55e+00'}   42.52±0.81       42.61±0.78       43.25±6.22                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '3.55e+00'}     26.55±9.61       26.88±9.46       26.63±10.74                     0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '3.55e+00'}   39.71±0.65       40.18±0.65       40.93±6.27                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '3.55e+00'}     23.99±5.74       25.41±6.73       22.92±7.41                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '3.55e+00'}   38.13±0.55       39.04±0.69       37.56±5.29                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '3.55e+00'}     27.75±15.90      29.37±15.83      29.32±15.18                     0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '3.55e+00'}   34.60±0.48       36.00±0.58       37.86±5.62                      0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '3.55e+00'}     30.56±22.50      33.06±23.69      32.82±23.23                     0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '3.55e+00'}   32.88±0.43       34.86±0.58       32.44±5.36                      0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '3.55e+00'}     27.29±5.35       29.63±5.42       31.61±7.82                      0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '3.55e+00'}   32.70±0.36       35.27±0.55       33.38±5.51                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '3.55e+00'}     40.98±41.35      43.13±38.99      44.21±45.43                     0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '3.55e+00'}   32.85±0.43       35.74±0.46       35.01±6.63                      1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '3.55e+00'}     31.25±6.27       33.76±5.10       35.64±9.24                      1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '3.55e+00'}   33.59±0.45       36.72±0.67       37.25±7.71                      1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '3.55e+00'}     33.45±7.70       36.26±6.78       36.34±8.64                      1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '3.55e+00'}   34.28±0.40       37.67±0.62       37.63±7.23                      1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '3.55e+00'}     41.87±30.47      45.51±31.78      44.91±32.47                     1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '3.55e+00'}   34.45±0.42       37.88±0.64       40.12±6.23                      2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '3.55e+00'}     45.92±34.01      47.48±27.86      50.03±37.75                     2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '3.55e+00'}  34.86±0.73       38.41±0.93       39.02±7.21                      2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '3.55e+00'}    85.04±145.54     89.49±150.88     89.98±154.82                    2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '5.01e+00'}   42.81±0.81       42.90±0.81       43.40±6.17                      0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '5.01e+00'}     23.32±0.25       23.89±0.32       23.74±4.59                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '5.01e+00'}   40.32±0.64       40.71±0.64       41.44±6.44                      0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '5.01e+00'}     30.52±12.51      31.20±12.68      28.34±12.47                     0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '5.01e+00'}   39.15±0.55       39.93±0.70       38.35±5.32                      0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '5.01e+00'}     47.17±59.52      47.48±55.53      47.51±56.52                     0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '5.01e+00'}   36.51±0.49       37.71±0.58       39.57±6.02                      0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '5.01e+00'}     38.64±15.76      40.63±16.80      40.58±17.77                     0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '5.01e+00'}   36.88±4.84       38.59±5.24       35.87±7.48                      0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '5.01e+00'}     35.08±9.77       36.96±10.33      38.06±11.35                     0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '5.01e+00'}   36.26±0.92       38.37±0.99       36.75±5.90                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '5.01e+00'}     35.06±9.77       37.36±10.04      37.19±9.71                      0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '5.01e+00'}   37.64±2.55       40.15±2.93       39.01±7.64                      1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '5.01e+00'}     33.68±2.30       36.14±2.69       37.35±7.63                      1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '5.01e+00'}   39.71±7.54       42.36±7.37       43.13±11.67                     1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '5.01e+00'}     34.93±5.09       37.38±4.48       37.07±7.38                      1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '5.01e+00'}   64.08±51.87      65.46±49.67      67.67±51.51                     1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '5.01e+00'}     34.35±0.89       37.10±0.92       36.94±8.06                      1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '5.01e+00'}   40.68±5.18       43.66±6.23       45.73±9.16                      2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '5.01e+00'}     34.50±1.01       37.19±1.25       38.59±6.19                      2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '5.01e+00'}  45.50±24.39      48.01±21.96      49.16±25.10                     2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '5.01e+00'}    34.90±1.45       37.48±1.17       35.60±7.79                      2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '7.08e+00'}   46.66±10.75      46.44±9.92       47.35±13.11                     0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '7.08e+00'}     26.89±0.26       27.34±0.31       26.99±5.18                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '7.08e+00'}   89.38±255.20     92.15±268.95     90.31±254.10                    0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '7.08e+00'}     28.75±0.33       29.45±0.35       26.51±6.16                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '7.08e+00'}   43.15±8.85       43.69±8.44       42.06±10.20                     0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '7.08e+00'}     31.35±0.42       32.39±0.42       32.56±6.02                      0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '7.08e+00'}   55.06±63.86      56.68±65.01      58.88±68.54                     0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '7.08e+00'}     33.39±0.36       34.76±0.43       35.08±5.42                      0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '7.08e+00'}   44.91±18.28      46.05±17.53      43.03±19.36                     0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '7.08e+00'}     35.36±0.46       36.94±0.57       38.69±8.14                      0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '7.08e+00'}   98.41±111.49     102.58±116.80    97.45±110.18                    0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '7.08e+00'}     36.98±0.40       38.94±0.63       38.29±6.16                      0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '7.08e+00'}   64.43±49.84      65.76±47.91      63.19±49.36                     1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '7.08e+00'}     38.37±0.51       40.39±0.65       41.66±8.12                      1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '7.08e+00'}   50.90±14.75      52.54±15.28      53.93±16.98                     1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '7.08e+00'}     39.41±0.53       41.56±0.61       41.49±7.16                      1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '7.08e+00'}   50.89±13.20      52.96±13.70      53.03±14.54                     1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '7.08e+00'}     39.84±0.58       42.12±0.63       41.75±8.64                      1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '7.08e+00'}   58.06±41.50      60.30±44.49      60.68±40.70                     2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '7.08e+00'}     39.90±0.57       42.14±0.84       43.43±6.49                      2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '7.08e+00'}  1400.75±7387.37  1620.99±8583.99  1383.33±7280.24                 2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '7.08e+00'}    40.13±0.52       42.34±0.80       40.79±8.35                      2.35\n",
-      "{'depth': 0.0, 'k_func': 'tanimoto', 'alpha': '1.00e+01'}   51.17±11.57      51.06±11.27      51.51±12.80                     0.09\n",
-      "{'depth': 0.0, 'k_func': 'MinMax', 'alpha': '1.00e+01'}     31.04±0.31       31.35±0.35       30.84±5.68                      0.36\n",
-      "{'depth': 1.0, 'k_func': 'tanimoto', 'alpha': '1.00e+01'}   67.11±78.15      67.15±78.78      67.95±80.94                     0.2\n",
-      "{'depth': 1.0, 'k_func': 'MinMax', 'alpha': '1.00e+01'}     33.18±0.33       33.73±0.36       30.28±7.09                      0.44\n",
-      "{'depth': 2.0, 'k_func': 'tanimoto', 'alpha': '1.00e+01'}   71.87±66.66      72.27±66.16      70.60±64.13                     0.33\n",
-      "{'depth': 2.0, 'k_func': 'MinMax', 'alpha': '1.00e+01'}     36.15±0.45       36.94±0.43       37.33±6.71                      0.57\n",
-      "{'depth': 3.0, 'k_func': 'tanimoto', 'alpha': '1.00e+01'}   67.22±58.95      68.20±62.46      68.66±55.42                     0.53\n",
-      "{'depth': 3.0, 'k_func': 'MinMax', 'alpha': '1.00e+01'}     38.72±0.36       39.83±0.42       40.16±6.14                      0.72\n",
-      "{'depth': 4.0, 'k_func': 'tanimoto', 'alpha': '1.00e+01'}   47.93±6.57       48.57±6.26       45.27±10.05                     0.79\n",
-      "{'depth': 4.0, 'k_func': 'MinMax', 'alpha': '1.00e+01'}     41.20±0.47       42.46±0.58       44.24±8.95                      0.83\n",
-      "{'depth': 5.0, 'k_func': 'tanimoto', 'alpha': '1.00e+01'}   45.87±0.91       46.90±0.85       45.87±6.75                      0.97\n",
-      "{'depth': 5.0, 'k_func': 'MinMax', 'alpha': '1.00e+01'}     43.16±0.40       44.77±0.65       43.91±6.98                      0.99\n",
-      "{'depth': 6.0, 'k_func': 'tanimoto', 'alpha': '1.00e+01'}   47.41±0.68       48.80±0.79       47.26±8.65                      1.25\n",
-      "{'depth': 6.0, 'k_func': 'MinMax', 'alpha': '1.00e+01'}     44.75±0.48       46.36±0.61       47.58±8.88                      1.24\n",
-      "{'depth': 7.0, 'k_func': 'tanimoto', 'alpha': '1.00e+01'}   48.76±0.61       50.31±0.72       51.46±8.88                      1.61\n",
-      "{'depth': 7.0, 'k_func': 'MinMax', 'alpha': '1.00e+01'}     45.87±0.52       47.60±0.59       47.71±7.76                      1.52\n",
-      "{'depth': 8.0, 'k_func': 'tanimoto', 'alpha': '1.00e+01'}   49.92±0.63       51.55±0.71       52.35±8.50                      1.85\n",
-      "{'depth': 8.0, 'k_func': 'MinMax', 'alpha': '1.00e+01'}     46.37±0.58       48.19±0.61       47.75±9.25                      1.69\n",
-      "{'depth': 9.0, 'k_func': 'tanimoto', 'alpha': '1.00e+01'}   50.28±0.51       51.91±0.59       53.72±7.41                      2.15\n",
-      "{'depth': 9.0, 'k_func': 'MinMax', 'alpha': '1.00e+01'}     46.43±0.56       48.21±0.82       49.46±6.97                      2.06\n",
-      "{'depth': 10.0, 'k_func': 'tanimoto', 'alpha': '1.00e+01'}  50.52±0.57       52.17±0.74       52.95±8.36                      2.44\n",
-      "{'depth': 10.0, 'k_func': 'MinMax', 'alpha': '1.00e+01'}    46.70±0.56       48.44±0.84       47.08±8.98                      2.35\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "calculate performance: 100%|██████████| 13860/13860 [15:31<00:00, 12.99it/s]"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext line_profiler\n",
-    "%matplotlib inline\n",
-    "import numpy as np\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.model_selection_precomputed import model_selection_for_precomputed_kernel\n",
-    "from pygraph.kernels.untildPathKernel import untildpathkernel\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "estimator = untildpathkernel\n",
-    "param_grid_precomputed = {'depth': np.linspace(0, 10, 11), 'k_func': ['tanimoto', 'MinMax']}\n",
-    "param_grid = {'alpha': np.logspace(-2, 1, num = 21, base = 10)}\n",
-    "\n",
-    "model_selection_for_precomputed_kernel(datafile, estimator, param_grid_precomputed, param_grid, \n",
-    "                                       'regression', NUM_TRIALS=30)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 0.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 0 of size 185 built in 0.09047365188598633 seconds ---\n",
-      "[[ 1.          1.          0.33333333 ...,  0.33333333  0.33333333\n",
-      "   0.33333333]\n",
-      " [ 1.          1.          0.33333333 ...,  0.33333333  0.33333333\n",
-      "   0.33333333]\n",
-      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]\n",
-      " ..., \n",
-      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]\n",
-      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]\n",
-      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 43.616902\n",
-      "With standard deviation: 2.132120\n",
-      "\n",
-      " Mean performance on test set: 41.620214\n",
-      "With standard deviation: 6.453003\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 1.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 1 of size 185 built in 0.1754138469696045 seconds ---\n",
-      "[[ 1.          0.8         0.14285714 ...,  0.125       0.125       0.125     ]\n",
-      " [ 0.8         1.          0.125      ...,  0.11111111  0.11111111\n",
-      "   0.11111111]\n",
-      " [ 0.14285714  0.125       1.         ...,  0.8         0.8         0.8       ]\n",
-      " ..., \n",
-      " [ 0.125       0.11111111  0.8        ...,  1.          1.          1.        ]\n",
-      " [ 0.125       0.11111111  0.8        ...,  1.          1.          1.        ]\n",
-      " [ 0.125       0.11111111  0.8        ...,  1.          1.          1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 40.832861\n",
-      "With standard deviation: 3.441465\n",
-      "\n",
-      " Mean performance on test set: 38.844613\n",
-      "With standard deviation: 6.446482\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 2.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 2 of size 185 built in 0.3448960781097412 seconds ---\n",
-      "[[ 1.          0.5         0.11111111 ...,  0.07692308  0.07692308\n",
-      "   0.07692308]\n",
-      " [ 0.5         1.          0.09090909 ...,  0.06666667  0.06666667\n",
-      "   0.06666667]\n",
-      " [ 0.11111111  0.09090909  1.         ...,  0.55555556  0.55555556\n",
-      "   0.55555556]\n",
-      " ..., \n",
-      " [ 0.07692308  0.06666667  0.55555556 ...,  1.          1.          1.        ]\n",
-      " [ 0.07692308  0.06666667  0.55555556 ...,  1.          1.          1.        ]\n",
-      " [ 0.07692308  0.06666667  0.55555556 ...,  1.          1.          1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 35.746142\n",
-      "With standard deviation: 1.611340\n",
-      "\n",
-      " Mean performance on test set: 35.291451\n",
-      "With standard deviation: 4.781298\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 3.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 3 of size 185 built in 0.5539388656616211 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.05555556  0.05555556\n",
-      "   0.05555556]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.04761905  0.04761905\n",
-      "   0.04761905]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.35714286  0.35714286\n",
-      "   0.35714286]\n",
-      " ..., \n",
-      " [ 0.05555556  0.04761905  0.35714286 ...,  1.          1.          1.        ]\n",
-      " [ 0.05555556  0.04761905  0.35714286 ...,  1.          1.          1.        ]\n",
-      " [ 0.05555556  0.04761905  0.35714286 ...,  1.          1.          1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 28.464581\n",
-      "With standard deviation: 3.001371\n",
-      "\n",
-      " Mean performance on test set: 29.484499\n",
-      "With standard deviation: 3.903507\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 4.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 4 of size 185 built in 0.7706489562988281 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.04347826  0.04166667\n",
-      "   0.04347826]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.03846154  0.03703704\n",
-      "   0.03846154]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.26315789  0.25        0.26315789]\n",
-      " ..., \n",
-      " [ 0.04347826  0.03846154  0.26315789 ...,  1.          0.95        0.9       ]\n",
-      " [ 0.04166667  0.03703704  0.25       ...,  0.95        1.          0.95      ]\n",
-      " [ 0.04347826  0.03846154  0.26315789 ...,  0.9         0.95        1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 19.251747\n",
-      "With standard deviation: 3.428930\n",
-      "\n",
-      " Mean performance on test set: 22.669312\n",
-      "With standard deviation: 6.280526\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 5.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 5 of size 185 built in 1.015580415725708 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03703704  0.03333333\n",
-      "   0.03571429]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.03333333  0.03030303\n",
-      "   0.03225806]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.2173913   0.19230769\n",
-      "   0.20833333]\n",
-      " ..., \n",
-      " [ 0.03703704  0.03333333  0.2173913  ...,  1.          0.88461538\n",
-      "   0.74074074]\n",
-      " [ 0.03333333  0.03030303  0.19230769 ...,  0.88461538  1.          0.85185185]\n",
-      " [ 0.03571429  0.03225806  0.20833333 ...,  0.74074074  0.85185185  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 16.886016\n",
-      "With standard deviation: 2.605194\n",
-      "\n",
-      " Mean performance on test set: 21.795626\n",
-      "With standard deviation: 5.522502\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 6.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 6 of size 185 built in 1.3330223560333252 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03333333  0.02857143\n",
-      "   0.03030303]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.03030303  0.02631579\n",
-      "   0.02777778]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.19230769  0.16129032\n",
-      "   0.17241379]\n",
-      " ..., \n",
-      " [ 0.03333333  0.03030303  0.19230769 ...,  1.          0.83870968\n",
-      "   0.57142857]\n",
-      " [ 0.02857143  0.02631579  0.16129032 ...,  0.83870968  1.          0.71428571]\n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  0.57142857  0.71428571  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 13.109746\n",
-      "With standard deviation: 2.584308\n",
-      "\n",
-      " Mean performance on test set: 20.604920\n",
-      "With standard deviation: 5.499831\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 7.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 7 of size 185 built in 1.602663278579712 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03125     0.02564103\n",
-      "   0.02631579]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02857143  0.02380952\n",
-      "   0.02439024]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17857143  0.14285714\n",
-      "   0.14705882]\n",
-      " ..., \n",
-      " [ 0.03125     0.02857143  0.17857143 ...,  1.          0.8         0.47619048]\n",
-      " [ 0.02564103  0.02380952  0.14285714 ...,  0.8         1.          0.56818182]\n",
-      " [ 0.02631579  0.02439024  0.14705882 ...,  0.47619048  0.56818182  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 12.015210\n",
-      "With standard deviation: 2.592798\n",
-      "\n",
-      " Mean performance on test set: 20.347932\n",
-      "With standard deviation: 5.176314\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 8.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 8 of size 185 built in 1.8121819496154785 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02325581]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.02173913]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.12820513]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.41666667]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.49019608]\n",
-      " [ 0.02325581  0.02173913  0.12820513 ...,  0.41666667  0.49019608  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.798096\n",
-      "With standard deviation: 2.130816\n",
-      "\n",
-      " Mean performance on test set: 19.822797\n",
-      "With standard deviation: 5.137687\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 9.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 9 of size 185 built in 2.2172586917877197 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.0212766 ]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727  0.02      ]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11627907]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.38461538]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.45454545]\n",
-      " [ 0.0212766   0.02        0.11627907 ...,  0.38461538  0.45454545  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.799656\n",
-      "With standard deviation: 2.095494\n",
-      "\n",
-      " Mean performance on test set: 19.873364\n",
-      "With standard deviation: 5.103689\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 10.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 10 of size 185 built in 2.4100613594055176 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.778685\n",
-      "With standard deviation: 2.100015\n",
-      "\n",
-      " Mean performance on test set: 19.870809\n",
-      "With standard deviation: 5.092173\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 11.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 11 of size 185 built in 2.7440149784088135 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.778685\n",
-      "With standard deviation: 2.100015\n",
-      "\n",
-      " Mean performance on test set: 19.870809\n",
-      "With standard deviation: 5.092173\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 12.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 12 of size 185 built in 2.723442316055298 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.778685\n",
-      "With standard deviation: 2.100015\n",
-      "\n",
-      " Mean performance on test set: 19.870809\n",
-      "With standard deviation: 5.092173\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 13.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 13 of size 185 built in 2.6163382530212402 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.778685\n",
-      "With standard deviation: 2.100015\n",
-      "\n",
-      " Mean performance on test set: 19.870809\n",
-      "With standard deviation: 5.092173\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 14.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 14 of size 185 built in 2.629500389099121 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.778685\n",
-      "With standard deviation: 2.100015\n",
-      "\n",
-      " Mean performance on test set: 19.870809\n",
-      "With standard deviation: 5.092173\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 15.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 15 of size 185 built in 2.664158821105957 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.778685\n",
-      "With standard deviation: 2.100015\n",
-      "\n",
-      " Mean performance on test set: 19.870809\n",
-      "With standard deviation: 5.092173\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 16.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 16 of size 185 built in 2.7301340103149414 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.778685\n",
-      "With standard deviation: 2.100015\n",
-      "\n",
-      " Mean performance on test set: 19.870809\n",
-      "With standard deviation: 5.092173\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 17.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 17 of size 185 built in 2.6328580379486084 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.778685\n",
-      "With standard deviation: 2.100015\n",
-      "\n",
-      " Mean performance on test set: 19.870809\n",
-      "With standard deviation: 5.092173\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 18.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 18 of size 185 built in 2.592944383621216 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.778685\n",
-      "With standard deviation: 2.100015\n",
-      "\n",
-      " Mean performance on test set: 19.870809\n",
-      "With standard deviation: 5.092173\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 19.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 19 of size 185 built in 2.6368520259857178 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.778685\n",
-      "With standard deviation: 2.100015\n",
-      "\n",
-      " Mean performance on test set: 19.870809\n",
-      "With standard deviation: 5.092173\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 20.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 20 of size 185 built in 2.52734375 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.778685\n",
-      "With standard deviation: 2.100015\n",
-      "\n",
-      " Mean performance on test set: 19.870809\n",
-      "With standard deviation: 5.092173\n",
-      "\n",
-      "\n",
-      "  depth    rmse_test    std_test    rmse_train    std_train     k_time\n",
-      "-------  -----------  ----------  ------------  -----------  ---------\n",
-      "      0      41.6202     6.453         43.6169      2.13212  0.0904737\n",
-      "      1      38.8446     6.44648       40.8329      3.44147  0.175414\n",
-      "      2      35.2915     4.7813        35.7461      1.61134  0.344896\n",
-      "      3      29.4845     3.90351       28.4646      3.00137  0.553939\n",
-      "      4      22.6693     6.28053       19.2517      3.42893  0.770649\n",
-      "      5      21.7956     5.5225        16.886       2.60519  1.01558\n",
-      "      6      20.6049     5.49983       13.1097      2.58431  1.33302\n",
-      "      7      20.3479     5.17631       12.0152      2.5928   1.60266\n",
-      "      8      19.8228     5.13769       10.7981      2.13082  1.81218\n",
-      "      9      19.8734     5.10369       10.7997      2.09549  2.21726\n",
-      "     10      19.8708     5.09217       10.7787      2.10002  2.41006\n",
-      "     11      19.8708     5.09217       10.7787      2.10002  2.74401\n",
-      "     12      19.8708     5.09217       10.7787      2.10002  2.72344\n",
-      "     13      19.8708     5.09217       10.7787      2.10002  2.61634\n",
-      "     14      19.8708     5.09217       10.7787      2.10002  2.6295\n",
-      "     15      19.8708     5.09217       10.7787      2.10002  2.66416\n",
-      "     16      19.8708     5.09217       10.7787      2.10002  2.73013\n",
-      "     17      19.8708     5.09217       10.7787      2.10002  2.63286\n",
-      "     18      19.8708     5.09217       10.7787      2.10002  2.59294\n",
-      "     19      19.8708     5.09217       10.7787      2.10002  2.63685\n",
-      "     20      19.8708     5.09217       10.7787      2.10002  2.52734\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 0.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 0 of size 185 built in 0.1027534008026123 seconds ---\n",
-      "[[ 1.          1.          0.33333333 ...,  0.33333333  0.33333333\n",
-      "   0.33333333]\n",
-      " [ 1.          1.          0.33333333 ...,  0.33333333  0.33333333\n",
-      "   0.33333333]\n",
-      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]\n",
-      " ..., \n",
-      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]\n",
-      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]\n",
-      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 42.787136\n",
-      "With standard deviation: 0.675806\n",
-      "\n",
-      " Mean performance on test set: 42.645892\n",
-      "With standard deviation: 6.560629\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 1.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 1 of size 185 built in 0.18301701545715332 seconds ---\n",
-      "[[ 1.          0.8         0.14285714 ...,  0.125       0.125       0.125     ]\n",
-      " [ 0.8         1.          0.125      ...,  0.11111111  0.11111111\n",
-      "   0.11111111]\n",
-      " [ 0.14285714  0.125       1.         ...,  0.8         0.8         0.8       ]\n",
-      " ..., \n",
-      " [ 0.125       0.11111111  0.8        ...,  1.          1.          1.        ]\n",
-      " [ 0.125       0.11111111  0.8        ...,  1.          1.          1.        ]\n",
-      " [ 0.125       0.11111111  0.8        ...,  1.          1.          1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 38.880117\n",
-      "With standard deviation: 0.623999\n",
-      "\n",
-      " Mean performance on test set: 39.174317\n",
-      "With standard deviation: 6.195371\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 2.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 2 of size 185 built in 0.33235955238342285 seconds ---\n",
-      "[[ 1.          0.5         0.11111111 ...,  0.07692308  0.07692308\n",
-      "   0.07692308]\n",
-      " [ 0.5         1.          0.09090909 ...,  0.06666667  0.06666667\n",
-      "   0.06666667]\n",
-      " [ 0.11111111  0.09090909  1.         ...,  0.55555556  0.55555556\n",
-      "   0.55555556]\n",
-      " ..., \n",
-      " [ 0.07692308  0.06666667  0.55555556 ...,  1.          1.          1.        ]\n",
-      " [ 0.07692308  0.06666667  0.55555556 ...,  1.          1.          1.        ]\n",
-      " [ 0.07692308  0.06666667  0.55555556 ...,  1.          1.          1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 35.348332\n",
-      "With standard deviation: 0.727833\n",
-      "\n",
-      " Mean performance on test set: 35.604226\n",
-      "With standard deviation: 4.539211\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 3.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 3 of size 185 built in 0.5400393009185791 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.05555556  0.05555556\n",
-      "   0.05555556]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.04761905  0.04761905\n",
-      "   0.04761905]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.35714286  0.35714286\n",
-      "   0.35714286]\n",
-      " ..., \n",
-      " [ 0.05555556  0.04761905  0.35714286 ...,  1.          1.          1.        ]\n",
-      " [ 0.05555556  0.04761905  0.35714286 ...,  1.          1.          1.        ]\n",
-      " [ 0.05555556  0.04761905  0.35714286 ...,  1.          1.          1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 28.047646\n",
-      "With standard deviation: 1.077805\n",
-      "\n",
-      " Mean performance on test set: 30.192177\n",
-      "With standard deviation: 5.110324\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 4.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 4 of size 185 built in 0.8054666519165039 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.04347826  0.04166667\n",
-      "   0.04347826]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.03846154  0.03703704\n",
-      "   0.03846154]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.26315789  0.25        0.26315789]\n",
-      " ..., \n",
-      " [ 0.04347826  0.03846154  0.26315789 ...,  1.          0.95        0.9       ]\n",
-      " [ 0.04166667  0.03703704  0.25       ...,  0.95        1.          0.95      ]\n",
-      " [ 0.04347826  0.03846154  0.26315789 ...,  0.9         0.95        1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " Mean performance on train set: 18.878595\n",
-      "With standard deviation: 1.711897\n",
-      "\n",
-      " Mean performance on test set: 23.751530\n",
-      "With standard deviation: 7.808559\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 5.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 5 of size 185 built in 1.0195980072021484 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03703704  0.03333333\n",
-      "   0.03571429]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.03333333  0.03030303\n",
-      "   0.03225806]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.2173913   0.19230769\n",
-      "   0.20833333]\n",
-      " ..., \n",
-      " [ 0.03703704  0.03333333  0.2173913  ...,  1.          0.88461538\n",
-      "   0.74074074]\n",
-      " [ 0.03333333  0.03030303  0.19230769 ...,  0.88461538  1.          0.85185185]\n",
-      " [ 0.03571429  0.03225806  0.20833333 ...,  0.74074074  0.85185185  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 16.339135\n",
-      "With standard deviation: 1.397693\n",
-      "\n",
-      " Mean performance on test set: 23.482309\n",
-      "With standard deviation: 7.727117\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 6.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 6 of size 185 built in 1.2962956428527832 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03333333  0.02857143\n",
-      "   0.03030303]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.03030303  0.02631579\n",
-      "   0.02777778]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.19230769  0.16129032\n",
-      "   0.17241379]\n",
-      " ..., \n",
-      " [ 0.03333333  0.03030303  0.19230769 ...,  1.          0.83870968\n",
-      "   0.57142857]\n",
-      " [ 0.02857143  0.02631579  0.16129032 ...,  0.83870968  1.          0.71428571]\n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  0.57142857  0.71428571  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 12.523830\n",
-      "With standard deviation: 1.040404\n",
-      "\n",
-      " Mean performance on test set: 22.745367\n",
-      "With standard deviation: 8.028051\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 7.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 7 of size 185 built in 1.5462064743041992 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03125     0.02564103\n",
-      "   0.02631579]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02857143  0.02380952\n",
-      "   0.02439024]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17857143  0.14285714\n",
-      "   0.14705882]\n",
-      " ..., \n",
-      " [ 0.03125     0.02857143  0.17857143 ...,  1.          0.8         0.47619048]\n",
-      " [ 0.02564103  0.02380952  0.14285714 ...,  0.8         1.          0.56818182]\n",
-      " [ 0.02631579  0.02439024  0.14705882 ...,  0.47619048  0.56818182  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 11.371668\n",
-      "With standard deviation: 0.925446\n",
-      "\n",
-      " Mean performance on test set: 22.831602\n",
-      "With standard deviation: 7.978369\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 8.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 8 of size 185 built in 1.8658208847045898 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02325581]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.02173913]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.12820513]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.41666667]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.49019608]\n",
-      " [ 0.02325581  0.02173913  0.12820513 ...,  0.41666667  0.49019608  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.132106\n",
-      "With standard deviation: 0.525580\n",
-      "\n",
-      " Mean performance on test set: 22.586071\n",
-      "With standard deviation: 8.067887\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 9.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 9 of size 185 built in 2.185042381286621 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.0212766 ]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727  0.02      ]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11627907]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.38461538]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.45454545]\n",
-      " [ 0.0212766   0.02        0.11627907 ...,  0.38461538  0.45454545  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.078464\n",
-      "With standard deviation: 0.518149\n",
-      "\n",
-      " Mean performance on test set: 22.766801\n",
-      "With standard deviation: 8.005709\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 10.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 10 of size 185 built in 2.35276198387146 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.075607\n",
-      "With standard deviation: 0.672820\n",
-      "\n",
-      " Mean performance on test set: 22.869720\n",
-      "With standard deviation: 7.944560\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 11.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 11 of size 185 built in 2.6274359226226807 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.075607\n",
-      "With standard deviation: 0.672820\n",
-      "\n",
-      " Mean performance on test set: 22.869720\n",
-      "With standard deviation: 7.944560\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 12.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 12 of size 185 built in 2.7209105491638184 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.075607\n",
-      "With standard deviation: 0.672820\n",
-      "\n",
-      " Mean performance on test set: 22.869720\n",
-      "With standard deviation: 7.944560\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 13.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 13 of size 185 built in 2.699059247970581 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " Mean performance on train set: 10.075607\n",
-      "With standard deviation: 0.672820\n",
-      "\n",
-      " Mean performance on test set: 22.869720\n",
-      "With standard deviation: 7.944560\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 14.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 14 of size 185 built in 2.6328344345092773 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.075607\n",
-      "With standard deviation: 0.672820\n",
-      "\n",
-      " Mean performance on test set: 22.869720\n",
-      "With standard deviation: 7.944560\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 15.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 15 of size 185 built in 2.6556999683380127 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.075607\n",
-      "With standard deviation: 0.672820\n",
-      "\n",
-      " Mean performance on test set: 22.869720\n",
-      "With standard deviation: 7.944560\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 16.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 16 of size 185 built in 2.621814012527466 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.075607\n",
-      "With standard deviation: 0.672820\n",
-      "\n",
-      " Mean performance on test set: 22.869720\n",
-      "With standard deviation: 7.944560\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 17.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 17 of size 185 built in 2.5938243865966797 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.075607\n",
-      "With standard deviation: 0.672820\n",
-      "\n",
-      " Mean performance on test set: 22.869720\n",
-      "With standard deviation: 7.944560\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 18.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 18 of size 185 built in 2.65336275100708 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.075607\n",
-      "With standard deviation: 0.672820\n",
-      "\n",
-      " Mean performance on test set: 22.869720\n",
-      "With standard deviation: 7.944560\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 19.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 19 of size 185 built in 2.628486156463623 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.075607\n",
-      "With standard deviation: 0.672820\n",
-      "\n",
-      " Mean performance on test set: 22.869720\n",
-      "With standard deviation: 7.944560\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 20.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 20 of size 185 built in 2.682689666748047 seconds ---\n",
-      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
-      "   0.02040816]\n",
-      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
-      "   0.01923077]\n",
-      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
-      "   0.11111111]\n",
-      " ..., \n",
-      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
-      "   0.37037037]\n",
-      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
-      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.075607\n",
-      "With standard deviation: 0.672820\n",
-      "\n",
-      " Mean performance on test set: 22.869720\n",
-      "With standard deviation: 7.944560\n",
-      "\n",
-      "\n",
-      "  depth    rmse_test    std_test    rmse_train    std_train    k_time\n",
-      "-------  -----------  ----------  ------------  -----------  --------\n",
-      "      0      42.6459     6.56063       42.7871     0.675806  0.102753\n",
-      "      1      39.1743     6.19537       38.8801     0.623999  0.183017\n",
-      "      2      35.6042     4.53921       35.3483     0.727833  0.33236\n",
-      "      3      30.1922     5.11032       28.0476     1.0778    0.540039\n",
-      "      4      23.7515     7.80856       18.8786     1.7119    0.805467\n",
-      "      5      23.4823     7.72712       16.3391     1.39769   1.0196\n",
-      "      6      22.7454     8.02805       12.5238     1.0404    1.2963\n",
-      "      7      22.8316     7.97837       11.3717     0.925446  1.54621\n",
-      "      8      22.5861     8.06789       10.1321     0.52558   1.86582\n",
-      "      9      22.7668     8.00571       10.0785     0.518149  2.18504\n",
-      "     10      22.8697     7.94456       10.0756     0.67282   2.35276\n",
-      "     11      22.8697     7.94456       10.0756     0.67282   2.62744\n",
-      "     12      22.8697     7.94456       10.0756     0.67282   2.72091\n",
-      "     13      22.8697     7.94456       10.0756     0.67282   2.69906\n",
-      "     14      22.8697     7.94456       10.0756     0.67282   2.63283\n",
-      "     15      22.8697     7.94456       10.0756     0.67282   2.6557\n",
-      "     16      22.8697     7.94456       10.0756     0.67282   2.62181\n",
-      "     17      22.8697     7.94456       10.0756     0.67282   2.59382\n",
-      "     18      22.8697     7.94456       10.0756     0.67282   2.65336\n",
-      "     19      22.8697     7.94456       10.0756     0.67282   2.62849\n",
-      "     20      22.8697     7.94456       10.0756     0.67282   2.68269\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 0.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 0 of size 185 built in 0.3893899917602539 seconds ---\n",
-      "[[ 1.          0.75        0.5        ...,  0.16666667  0.16666667\n",
-      "   0.16666667]\n",
-      " [ 0.75        1.          0.4        ...,  0.15384615  0.15384615\n",
-      "   0.15384615]\n",
-      " [ 0.5         0.4         1.         ...,  0.27272727  0.27272727\n",
-      "   0.27272727]\n",
-      " ..., \n",
-      " [ 0.16666667  0.15384615  0.27272727 ...,  1.          1.          1.        ]\n",
-      " [ 0.16666667  0.15384615  0.27272727 ...,  1.          1.          1.        ]\n",
-      " [ 0.16666667  0.15384615  0.27272727 ...,  1.          1.          1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 12.207923\n",
-      "With standard deviation: 0.700182\n",
-      "\n",
-      " Mean performance on test set: 12.682718\n",
-      "With standard deviation: 2.748815\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 1.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 1 of size 185 built in 0.4729621410369873 seconds ---\n",
-      "[[ 1.          0.7         0.16666667 ...,  0.05555556  0.05555556\n",
-      "   0.05555556]\n",
-      " [ 0.7         1.          0.13333333 ...,  0.05128205  0.05128205\n",
-      "   0.05128205]\n",
-      " [ 0.16666667  0.13333333  1.         ...,  0.22580645  0.22580645\n",
-      "   0.22580645]\n",
-      " ..., \n",
-      " [ 0.05555556  0.05128205  0.22580645 ...,  1.          1.          1.        ]\n",
-      " [ 0.05555556  0.05128205  0.22580645 ...,  1.          1.          1.        ]\n",
-      " [ 0.05555556  0.05128205  0.22580645 ...,  1.          1.          1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.279220\n",
-      "With standard deviation: 0.914688\n",
-      "\n",
-      " Mean performance on test set: 12.609828\n",
-      "With standard deviation: 2.372778\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 2.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 2 of size 185 built in 0.576836109161377 seconds ---\n",
-      "[[ 1.          0.4375      0.125      ...,  0.03333333  0.03333333\n",
-      "   0.03571429]\n",
-      " [ 0.4375      1.          0.0952381  ...,  0.03076923  0.03076923\n",
-      "   0.03278689]\n",
-      " [ 0.125       0.0952381   1.         ...,  0.16981132  0.16981132\n",
-      "   0.18367347]\n",
-      " ..., \n",
-      " [ 0.03333333  0.03076923  0.16981132 ...,  1.          1.          0.9245283 ]\n",
-      " [ 0.03333333  0.03076923  0.16981132 ...,  1.          1.          0.9245283 ]\n",
-      " [ 0.03571429  0.03278689  0.18367347 ...,  0.9245283   0.9245283   1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 2.588811\n",
-      "With standard deviation: 0.557162\n",
-      "\n",
-      " Mean performance on test set: 8.060609\n",
-      "With standard deviation: 2.470450\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 3.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 3 of size 185 built in 0.7169125080108643 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.02631579  0.02631579\n",
-      "   0.02777778]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.02409639  0.02409639\n",
-      "   0.02531646]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.13043478  0.13043478\n",
-      "   0.13846154]\n",
-      " ..., \n",
-      " [ 0.02631579  0.02409639  0.13043478 ...,  1.          0.94366197\n",
-      "   0.83561644]\n",
-      " [ 0.02631579  0.02409639  0.13043478 ...,  0.94366197  1.          0.78666667]\n",
-      " [ 0.02777778  0.02531646  0.13846154 ...,  0.83561644  0.78666667  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 1.272670\n",
-      "With standard deviation: 0.760432\n",
-      "\n",
-      " Mean performance on test set: 9.755135\n",
-      "With standard deviation: 3.049170\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 4.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 4 of size 185 built in 0.8342421054840088 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.02222222  0.02222222\n",
-      "   0.02325581]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.02061856  0.02061856\n",
-      "   0.02150538]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.10843373  0.10843373\n",
-      "   0.11392405]\n",
-      " ..., \n",
-      " [ 0.02222222  0.02061856  0.10843373 ...,  1.          0.82417582\n",
-      "   0.67010309]\n",
-      " [ 0.02222222  0.02061856  0.10843373 ...,  0.82417582  1.          0.70526316]\n",
-      " [ 0.02325581  0.02150538  0.11392405 ...,  0.67010309  0.70526316  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 1.032293\n",
-      "With standard deviation: 0.728380\n",
-      "\n",
-      " Mean performance on test set: 10.319167\n",
-      "With standard deviation: 3.616673\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 5.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 5 of size 185 built in 0.9938209056854248 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.01960784  0.01960784\n",
-      "   0.02040816]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.01834862  0.01834862\n",
-      "   0.01904762]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.09473684  0.09473684\n",
-      "   0.0989011 ]\n",
-      " ..., \n",
-      " [ 0.01960784  0.01834862  0.09473684 ...,  1.          0.74311927\n",
-      "   0.56302521]\n",
-      " [ 0.01960784  0.01834862  0.09473684 ...,  0.74311927  1.          0.6173913 ]\n",
-      " [ 0.02040816  0.01904762  0.0989011  ...,  0.56302521  0.6173913   1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 0.923543\n",
-      "With standard deviation: 0.660532\n",
-      "\n",
-      " Mean performance on test set: 10.659250\n",
-      "With standard deviation: 4.120523\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 6.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 6 of size 185 built in 1.1753439903259277 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.01785714  0.01785714\n",
-      "   0.01851852]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.01680672  0.01680672\n",
-      "   0.0173913 ]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.08571429  0.08571429\n",
-      "   0.08910891]\n",
-      " ..., \n",
-      " [ 0.01785714  0.01680672  0.08571429 ...,  1.          0.68        0.48201439]\n",
-      " [ 0.01785714  0.01680672  0.08571429 ...,  0.68        1.          0.54887218]\n",
-      " [ 0.01851852  0.0173913   0.08910891 ...,  0.48201439  0.54887218  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 0.878589\n",
-      "With standard deviation: 0.603598\n",
-      "\n",
-      " Mean performance on test set: 11.102521\n",
-      "With standard deviation: 4.330554\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 7.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 7 of size 185 built in 1.4358420372009277 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.01666667  0.01666667\n",
-      "   0.01724138]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.01574803  0.01574803\n",
-      "   0.01626016]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.07964602  0.07964602\n",
-      "   0.08256881]\n",
-      " ..., \n",
-      " [ 0.01666667  0.01574803  0.07964602 ...,  1.          0.64963504\n",
-      "   0.43225806]\n",
-      " [ 0.01666667  0.01574803  0.07964602 ...,  0.64963504  1.          0.48993289]\n",
-      " [ 0.01724138  0.01626016  0.08256881 ...,  0.43225806  0.48993289  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 0.944049\n",
-      "With standard deviation: 0.694844\n",
-      "\n",
-      " Mean performance on test set: 11.352962\n",
-      "With standard deviation: 4.305459\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 8.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 8 of size 185 built in 1.7005987167358398 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.015625    0.015625\n",
-      "   0.01639344]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.01481481  0.01481481\n",
-      "   0.01550388]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.07438017  0.07438017\n",
-      "   0.07826087]\n",
-      " ..., \n",
-      " [ 0.015625    0.01481481  0.07438017 ...,  1.          0.58169935\n",
-      "   0.3964497 ]\n",
-      " [ 0.015625    0.01481481  0.07438017 ...,  0.58169935  1.          0.44785276]\n",
-      " [ 0.01639344  0.01550388  0.07826087 ...,  0.3964497   0.44785276  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 1.033979\n",
-      "With standard deviation: 0.775622\n",
-      "\n",
-      " Mean performance on test set: 11.298981\n",
-      "With standard deviation: 4.349648\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 9.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 9 of size 185 built in 2.0194287300109863 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.015625    0.015625\n",
-      "   0.01587302]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.01481481  0.01481481\n",
-      "   0.01503759]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.07438017  0.07438017\n",
-      "   0.07563025]\n",
-      " ..., \n",
-      " [ 0.015625    0.01481481  0.07438017 ...,  1.          0.58169935\n",
-      "   0.38728324]\n",
-      " [ 0.015625    0.01481481  0.07438017 ...,  0.58169935  1.          0.43712575]\n",
-      " [ 0.01587302  0.01503759  0.07563025 ...,  0.38728324  0.43712575  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 1.003187\n",
-      "With standard deviation: 0.572070\n",
-      "\n",
-      " Mean performance on test set: 11.332669\n",
-      "With standard deviation: 4.324120\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 10.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 10 of size 185 built in 2.243326187133789 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.015625    0.015625    0.015625  ]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.01481481  0.01481481\n",
-      "   0.01481481]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.07438017  0.07438017\n",
-      "   0.07438017]\n",
-      " ..., \n",
-      " [ 0.015625    0.01481481  0.07438017 ...,  1.          0.58169935\n",
-      "   0.38285714]\n",
-      " [ 0.015625    0.01481481  0.07438017 ...,  0.58169935  1.          0.43195266]\n",
-      " [ 0.015625    0.01481481  0.07438017 ...,  0.38285714  0.43195266  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 1.002272\n",
-      "With standard deviation: 0.570937\n",
-      "\n",
-      " Mean performance on test set: 11.343515\n",
-      "With standard deviation: 4.327265\n",
-      "\n",
-      "\n",
-      "  depth    rmse_test    std_test    rmse_train    std_train    k_time\n",
-      "-------  -----------  ----------  ------------  -----------  --------\n",
-      "      0     12.6827      2.74882     12.2079       0.700182  0.38939\n",
-      "      1     12.6098      2.37278     10.2792       0.914688  0.472962\n",
-      "      2      8.06061     2.47045      2.58881      0.557162  0.576836\n",
-      "      3      9.75514     3.04917      1.27267      0.760432  0.716913\n",
-      "      4     10.3192      3.61667      1.03229      0.72838   0.834242\n",
-      "      5     10.6593      4.12052      0.923543     0.660532  0.993821\n",
-      "      6     11.1025      4.33055      0.878589     0.603598  1.17534\n",
-      "      7     11.353       4.30546      0.944049     0.694844  1.43584\n",
-      "      8     11.299       4.34965      1.03398      0.775622  1.7006\n",
-      "      9     11.3327      4.32412      1.00319      0.57207   2.01943\n",
-      "     10     11.3435      4.32726      1.00227      0.570937  2.24333\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 0.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 0 of size 185 built in 0.3775763511657715 seconds ---\n",
-      "[[ 1.          0.75        0.5        ...,  0.16666667  0.16666667\n",
-      "   0.16666667]\n",
-      " [ 0.75        1.          0.4        ...,  0.15384615  0.15384615\n",
-      "   0.15384615]\n",
-      " [ 0.5         0.4         1.         ...,  0.27272727  0.27272727\n",
-      "   0.27272727]\n",
-      " ..., \n",
-      " [ 0.16666667  0.15384615  0.27272727 ...,  1.          1.          1.        ]\n",
-      " [ 0.16666667  0.15384615  0.27272727 ...,  1.          1.          1.        ]\n",
-      " [ 0.16666667  0.15384615  0.27272727 ...,  1.          1.          1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 12.120872\n",
-      "With standard deviation: 0.500467\n",
-      "\n",
-      " Mean performance on test set: 12.579966\n",
-      "With standard deviation: 2.732346\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 1.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 1 of size 185 built in 0.4563324451446533 seconds ---\n",
-      "[[ 1.          0.7         0.16666667 ...,  0.05555556  0.05555556\n",
-      "   0.05555556]\n",
-      " [ 0.7         1.          0.13333333 ...,  0.05128205  0.05128205\n",
-      "   0.05128205]\n",
-      " [ 0.16666667  0.13333333  1.         ...,  0.22580645  0.22580645\n",
-      "   0.22580645]\n",
-      " ..., \n",
-      " [ 0.05555556  0.05128205  0.22580645 ...,  1.          1.          1.        ]\n",
-      " [ 0.05555556  0.05128205  0.22580645 ...,  1.          1.          1.        ]\n",
-      " [ 0.05555556  0.05128205  0.22580645 ...,  1.          1.          1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 10.224322\n",
-      "With standard deviation: 0.734261\n",
-      "\n",
-      " Mean performance on test set: 12.621509\n",
-      "With standard deviation: 2.188664\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 2.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 2 of size 185 built in 0.5852782726287842 seconds ---\n",
-      "[[ 1.          0.4375      0.125      ...,  0.03333333  0.03333333\n",
-      "   0.03571429]\n",
-      " [ 0.4375      1.          0.0952381  ...,  0.03076923  0.03076923\n",
-      "   0.03278689]\n",
-      " [ 0.125       0.0952381   1.         ...,  0.16981132  0.16981132\n",
-      "   0.18367347]\n",
-      " ..., \n",
-      " [ 0.03333333  0.03076923  0.16981132 ...,  1.          1.          0.9245283 ]\n",
-      " [ 0.03333333  0.03076923  0.16981132 ...,  1.          1.          0.9245283 ]\n",
-      " [ 0.03571429  0.03278689  0.18367347 ...,  0.9245283   0.9245283   1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 2.718851\n",
-      "With standard deviation: 0.732922\n",
-      "\n",
-      " Mean performance on test set: 7.429032\n",
-      "With standard deviation: 2.693953\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 3.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 3 of size 185 built in 0.7065560817718506 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.02631579  0.02631579\n",
-      "   0.02777778]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.02409639  0.02409639\n",
-      "   0.02531646]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.13043478  0.13043478\n",
-      "   0.13846154]\n",
-      " ..., \n",
-      " [ 0.02631579  0.02409639  0.13043478 ...,  1.          0.94366197\n",
-      "   0.83561644]\n",
-      " [ 0.02631579  0.02409639  0.13043478 ...,  0.94366197  1.          0.78666667]\n",
-      " [ 0.02777778  0.02531646  0.13846154 ...,  0.83561644  0.78666667  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 1.540000\n",
-      "With standard deviation: 1.138134\n",
-      "\n",
-      " Mean performance on test set: 9.024680\n",
-      "With standard deviation: 2.508084\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 4.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 4 of size 185 built in 0.8479568958282471 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.02222222  0.02222222\n",
-      "   0.02325581]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.02061856  0.02061856\n",
-      "   0.02150538]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.10843373  0.10843373\n",
-      "   0.11392405]\n",
-      " ..., \n",
-      " [ 0.02222222  0.02061856  0.10843373 ...,  1.          0.82417582\n",
-      "   0.67010309]\n",
-      " [ 0.02222222  0.02061856  0.10843373 ...,  0.82417582  1.          0.70526316]\n",
-      " [ 0.02325581  0.02150538  0.11392405 ...,  0.67010309  0.70526316  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 1.360291\n",
-      "With standard deviation: 1.423990\n",
-      "\n",
-      " Mean performance on test set: 10.081112\n",
-      "With standard deviation: 3.647700\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 5.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 5 of size 185 built in 1.0008597373962402 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.01960784  0.01960784\n",
-      "   0.02040816]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.01834862  0.01834862\n",
-      "   0.01904762]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.09473684  0.09473684\n",
-      "   0.0989011 ]\n",
-      " ..., \n",
-      " [ 0.01960784  0.01834862  0.09473684 ...,  1.          0.74311927\n",
-      "   0.56302521]\n",
-      " [ 0.01960784  0.01834862  0.09473684 ...,  0.74311927  1.          0.6173913 ]\n",
-      " [ 0.02040816  0.01904762  0.0989011  ...,  0.56302521  0.6173913   1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 1.085175\n",
-      "With standard deviation: 1.062063\n",
-      "\n",
-      " Mean performance on test set: 11.300476\n",
-      "With standard deviation: 4.441634\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 6.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of path kernel up to 6 of size 185 built in 1.1979196071624756 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.01785714  0.01785714\n",
-      "   0.01851852]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.01680672  0.01680672\n",
-      "   0.0173913 ]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.08571429  0.08571429\n",
-      "   0.08910891]\n",
-      " ..., \n",
-      " [ 0.01785714  0.01680672  0.08571429 ...,  1.          0.68        0.48201439]\n",
-      " [ 0.01785714  0.01680672  0.08571429 ...,  0.68        1.          0.54887218]\n",
-      " [ 0.01851852  0.0173913   0.08910891 ...,  0.48201439  0.54887218  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 1.064431\n",
-      "With standard deviation: 1.001911\n",
-      "\n",
-      " Mean performance on test set: 12.186014\n",
-      "With standard deviation: 4.888158\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 7.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 7 of size 185 built in 1.4372029304504395 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.01666667  0.01666667\n",
-      "   0.01724138]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.01574803  0.01574803\n",
-      "   0.01626016]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.07964602  0.07964602\n",
-      "   0.08256881]\n",
-      " ..., \n",
-      " [ 0.01666667  0.01574803  0.07964602 ...,  1.          0.64963504\n",
-      "   0.43225806]\n",
-      " [ 0.01666667  0.01574803  0.07964602 ...,  0.64963504  1.          0.48993289]\n",
-      " [ 0.01724138  0.01626016  0.08256881 ...,  0.43225806  0.48993289  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 1.199119\n",
-      "With standard deviation: 1.340313\n",
-      "\n",
-      " Mean performance on test set: 12.753387\n",
-      "With standard deviation: 5.145288\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 8.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 8 of size 185 built in 1.68448805809021 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.015625    0.015625\n",
-      "   0.01639344]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.01481481  0.01481481\n",
-      "   0.01550388]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.07438017  0.07438017\n",
-      "   0.07826087]\n",
-      " ..., \n",
-      " [ 0.015625    0.01481481  0.07438017 ...,  1.          0.58169935\n",
-      "   0.3964497 ]\n",
-      " [ 0.015625    0.01481481  0.07438017 ...,  0.58169935  1.          0.44785276]\n",
-      " [ 0.01639344  0.01550388  0.07826087 ...,  0.3964497   0.44785276  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 1.358221\n",
-      "With standard deviation: 1.843147\n",
-      "\n",
-      " Mean performance on test set: 13.047098\n",
-      "With standard deviation: 5.271835\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 9.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 9 of size 185 built in 1.9654510021209717 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.015625    0.015625\n",
-      "   0.01587302]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.01481481  0.01481481\n",
-      "   0.01503759]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.07438017  0.07438017\n",
-      "   0.07563025]\n",
-      " ..., \n",
-      " [ 0.015625    0.01481481  0.07438017 ...,  1.          0.58169935\n",
-      "   0.38728324]\n",
-      " [ 0.015625    0.01481481  0.07438017 ...,  0.58169935  1.          0.43712575]\n",
-      " [ 0.01587302  0.01503759  0.07563025 ...,  0.38728324  0.43712575  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 1.360024\n",
-      "With standard deviation: 1.848342\n",
-      "\n",
-      " Mean performance on test set: 13.178933\n",
-      "With standard deviation: 5.277067\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when depth = 10.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of path kernel up to 10 of size 185 built in 2.2494258880615234 seconds ---\n",
-      "[[ 1.          0.38888889  0.125      ...,  0.015625    0.015625    0.015625  ]\n",
-      " [ 0.38888889  1.          0.08695652 ...,  0.01481481  0.01481481\n",
-      "   0.01481481]\n",
-      " [ 0.125       0.08695652  1.         ...,  0.07438017  0.07438017\n",
-      "   0.07438017]\n",
-      " ..., \n",
-      " [ 0.015625    0.01481481  0.07438017 ...,  1.          0.58169935\n",
-      "   0.38285714]\n",
-      " [ 0.015625    0.01481481  0.07438017 ...,  0.58169935  1.          0.43195266]\n",
-      " [ 0.015625    0.01481481  0.07438017 ...,  0.38285714  0.43195266  1.        ]]\n",
-      "\n",
-      " Saving kernel matrix to file...\n",
-      "\n",
-      " Mean performance on train set: 1.362078\n",
-      "With standard deviation: 1.854262\n",
-      "\n",
-      " Mean performance on test set: 13.253773\n",
-      "With standard deviation: 5.264247\n",
-      "\n",
-      "\n",
-      "  depth    rmse_test    std_test    rmse_train    std_train    k_time\n",
-      "-------  -----------  ----------  ------------  -----------  --------\n",
-      "      0     12.58        2.73235      12.1209      0.500467  0.377576\n",
-      "      1     12.6215      2.18866      10.2243      0.734261  0.456332\n",
-      "      2      7.42903     2.69395       2.71885     0.732922  0.585278\n",
-      "      3      9.02468     2.50808       1.54        1.13813   0.706556\n",
-      "      4     10.0811      3.6477        1.36029     1.42399   0.847957\n",
-      "      5     11.3005      4.44163       1.08518     1.06206   1.00086\n",
-      "      6     12.186       4.88816       1.06443     1.00191   1.19792\n",
-      "      7     12.7534      5.14529       1.19912     1.34031   1.4372\n",
-      "      8     13.0471      5.27184       1.35822     1.84315   1.68449\n",
-      "      9     13.1789      5.27707       1.36002     1.84834   1.96545\n",
-      "     10     13.2538      5.26425       1.36208     1.85426   2.24943\n"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext line_profiler\n",
-    "\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.untildPathKernel import untildpathkernel\n",
-    "\n",
-    "import numpy as np\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_path_acyclic/'\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', labeled = True, k_func = 'tanimoto')\n",
-    "\n",
-    "# kernel_train_test(datafile, kernel_file_path, treeletkernel, kernel_para, normalize = False)\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
-    "    hyper_name = 'depth', hyper_range = np.linspace(0, 20, 21), normalize = True)\n",
-    "kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
-    "    hyper_name = 'depth', hyper_range = np.linspace(0, 20, 21), normalize = False)\n",
-    "\n",
-    "kernel_para['k_func'] = 'minmax'\n",
-    "kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
-    "    hyper_name = 'depth', hyper_range = np.linspace(0, 10, 11), normalize = True)\n",
-    "kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
-    "    hyper_name = 'depth', hyper_range = np.linspace(0, 10, 11), normalize = False)\n",
-    "\n",
-    "# # kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, normalize = False)\n",
-    "\n",
-    "# kernel_para['depth'] = 10\n",
-    "# %lprun -f untildpathkernel \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, normalize = False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# results\n",
-    "\n",
-    "# kernel Tanimoto with y normalization\n",
-    "  depth    rmse_test    std_test    rmse_train    std_train     k_time\n",
-    "-------  -----------  ----------  ------------  -----------  ---------\n",
-    "      0      41.6202     6.453         43.6169      2.13212  0.0904737\n",
-    "      1      38.8446     6.44648       40.8329      3.44147  0.175414\n",
-    "      2      35.2915     4.7813        35.7461      1.61134  0.344896\n",
-    "      3      29.4845     3.90351       28.4646      3.00137  0.553939\n",
-    "      4      22.6693     6.28053       19.2517      3.42893  0.770649\n",
-    "      5      21.7956     5.5225        16.886       2.60519  1.01558\n",
-    "      6      20.6049     5.49983       13.1097      2.58431  1.33302\n",
-    "      7      20.3479     5.17631       12.0152      2.5928   1.60266\n",
-    "      8      19.8228     5.13769       10.7981      2.13082  1.81218\n",
-    "      9      19.8734     5.10369       10.7997      2.09549  2.21726\n",
-    "     10      19.8708     5.09217       10.7787      2.10002  2.41006\n",
-    "     11      19.8708     5.09217       10.7787      2.10002  2.74401\n",
-    "     12      19.8708     5.09217       10.7787      2.10002  2.72344\n",
-    "     13      19.8708     5.09217       10.7787      2.10002  2.61634\n",
-    "     14      19.8708     5.09217       10.7787      2.10002  2.6295\n",
-    "     15      19.8708     5.09217       10.7787      2.10002  2.66416\n",
-    "     16      19.8708     5.09217       10.7787      2.10002  2.73013\n",
-    "     17      19.8708     5.09217       10.7787      2.10002  2.63286\n",
-    "     18      19.8708     5.09217       10.7787      2.10002  2.59294\n",
-    "     19      19.8708     5.09217       10.7787      2.10002  2.63685\n",
-    "     20      19.8708     5.09217       10.7787      2.10002  2.52734\n",
-    "\n",
-    "# kernel Tanimoto without y normalization\n",
-    "  depth    rmse_test    std_test    rmse_train    std_train    k_time\n",
-    "-------  -----------  ----------  ------------  -----------  --------\n",
-    "      0      42.6459     6.56063       42.7871     0.675806  0.102753\n",
-    "      1      39.1743     6.19537       38.8801     0.623999  0.183017\n",
-    "      2      35.6042     4.53921       35.3483     0.727833  0.33236\n",
-    "      3      30.1922     5.11032       28.0476     1.0778    0.540039\n",
-    "      4      23.7515     7.80856       18.8786     1.7119    0.805467\n",
-    "      5      23.4823     7.72712       16.3391     1.39769   1.0196\n",
-    "      6      22.7454     8.02805       12.5238     1.0404    1.2963\n",
-    "      7      22.8316     7.97837       11.3717     0.925446  1.54621\n",
-    "      8      22.5861     8.06789       10.1321     0.52558   1.86582\n",
-    "      9      22.7668     8.00571       10.0785     0.518149  2.18504\n",
-    "     10      22.8697     7.94456       10.0756     0.67282   2.35276\n",
-    "     11      22.8697     7.94456       10.0756     0.67282   2.62744\n",
-    "     12      22.8697     7.94456       10.0756     0.67282   2.72091\n",
-    "     13      22.8697     7.94456       10.0756     0.67282   2.69906\n",
-    "     14      22.8697     7.94456       10.0756     0.67282   2.63283\n",
-    "     15      22.8697     7.94456       10.0756     0.67282   2.6557\n",
-    "     16      22.8697     7.94456       10.0756     0.67282   2.62181\n",
-    "     17      22.8697     7.94456       10.0756     0.67282   2.59382\n",
-    "     18      22.8697     7.94456       10.0756     0.67282   2.65336\n",
-    "     19      22.8697     7.94456       10.0756     0.67282   2.62849\n",
-    "     20      22.8697     7.94456       10.0756     0.67282   2.68269\n",
-    "    \n",
-    "# kernel MinMax with y normalization    \n",
-    "  depth    rmse_test    std_test    rmse_train    std_train    k_time\n",
-    "-------  -----------  ----------  ------------  -----------  --------\n",
-    "      0     12.6827      2.74882     12.2079       0.700182  0.38939\n",
-    "      1     12.6098      2.37278     10.2792       0.914688  0.472962\n",
-    "      2      8.06061     2.47045      2.58881      0.557162  0.576836\n",
-    "      3      9.75514     3.04917      1.27267      0.760432  0.716913\n",
-    "      4     10.3192      3.61667      1.03229      0.72838   0.834242\n",
-    "      5     10.6593      4.12052      0.923543     0.660532  0.993821\n",
-    "      6     11.1025      4.33055      0.878589     0.603598  1.17534\n",
-    "      7     11.353       4.30546      0.944049     0.694844  1.43584\n",
-    "      8     11.299       4.34965      1.03398      0.775622  1.7006\n",
-    "      9     11.3327      4.32412      1.00319      0.57207   2.01943\n",
-    "     10     11.3435      4.32726      1.00227      0.570937  2.24333\n",
-    "\n",
-    "# kernel MinMax without y normalization\n",
-    "  depth    rmse_test    std_test    rmse_train    std_train    k_time\n",
-    "-------  -----------  ----------  ------------  -----------  --------\n",
-    "      0     12.58        2.73235      12.1209      0.500467  0.377576\n",
-    "      1     12.6215      2.18866      10.2243      0.734261  0.456332\n",
-    "      2      7.42903     2.69395       2.71885     0.732922  0.585278\n",
-    "      3      9.02468     2.50808       1.54        1.13813   0.706556\n",
-    "      4     10.0811      3.6477        1.36029     1.42399   0.847957\n",
-    "      5     11.3005      4.44163       1.08518     1.06206   1.00086\n",
-    "      6     12.186       4.88816       1.06443     1.00191   1.19792\n",
-    "      7     12.7534      5.14529       1.19912     1.34031   1.4372\n",
-    "      8     13.0471      5.27184       1.35822     1.84315   1.68449\n",
-    "      9     13.1789      5.27707       1.36002     1.84834   1.96545\n",
-    "     10     13.2538      5.26425       1.36208     1.85426   2.24943"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/.ipynb_checkpoints/run_untilnwalkkernel-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/run_untilnwalkkernel-checkpoint.ipynb
deleted file mode 100644
index a74151e..0000000
--- a/notebooks/.ipynb_checkpoints/run_untilnwalkkernel-checkpoint.ipynb
+++ /dev/null
@@ -1,12297 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "--- This is a regression problem ---\n",
-      "\n",
-      "1. Loading dataset from file...\n",
-      "\n",
-      "2. Calculating gram matrices. This could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8016703128814697 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 1e-10} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2466cb70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8038928508758545 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 1e-09} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb245da0b8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8428130149841309 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 1e-08} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21368cf8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8060216903686523 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 1e-07} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb213277b8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8030860424041748 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 1e-06} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb213a4908>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8137733936309814 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 1e-05} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb212da7b8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.7620131969451904 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 0.0001} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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ACEkGCzN73MyumtnLpdvOmtmPzOxXxf9nitvNzL5pZpfN7CUz+9AyGw/g+ER6Fk9IunvutkckPe/ud0p6vvhdku6RdGfx75KkR4+mmQBWLRks3P3Hkv40d/N9kp4sfn5S0mdKt3/HJ34i6bSZ3XZUjQWwOm3HLM67++vFz3+QdL74+XZJvy897rXiNgDXuM4DnO7ukhpny5jZJTN7wcxeGIze6doMAEvWNli8MT29KP6/Wtx+RdL7So97b3HbAnd/zN0vuvvFzfxEy2YAOC5t072flfSgpK8V/3+/dPvDZvaUpI9KerN0ulLPXfb2u1JepLTmmbL+aCbF2/NsfznD+VTuqtRuzw5SiSuXN0wsQ1iX1l2XDj3/HG3TsaPbtU0nT23XdEnBBQ1SuJscg+dqvbzg/j5S21ugg1yRcl6Vit1EZPu8eN5yavm7e8G5AdN9VKSlW4OM+2SwMLPvSbpL0i1m9pqkL2sSJJ42sy9I+q2k+4uHPyfpXkmXJb0j6fPxpgBYZ8lg4e6fq7nrkxWPdUkPdW0UgPVDBieAEIIFgBCCBYAQggWAEIIFgBCCBYAQggWAEIIFgJC1qe4tSconscs3F5s1X+07pZx+XVepu426quBH+RwRy64efhyaVBJvVDW8rUD18FSF8GWZpnlHKoHXqaoGbg3mgK5HsMgy+c1/IxtMXggb7Gl4/oQ8P/gC5v2xsr3Jgb1zcvZTVvWhS5Xs758+/Mtd90GOzp3on2n34Y4GgWUtBTA813HHTcr1N5zrceLWvzZszKw8P/yLPhy2+zrccesfW2031bN0AKqaB/Lhs79r9Dz98eLxvZTHJwNxGgIghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASBkPepZSBpv95QPDmopeG4ab5brWah039y2FQVdUmuZpgqvVEz9lxSvZ9F6LdJokZe9JRXbaVKPokKT4jDJtUfnpOpRpGz1Fou/lLWtZxGpR3GYmzf6ycdU1bPYqChmc5iqehZN0LMAEEKwABBCsAAQQrAAEEKwABBCsAAQQrAAELIeeRbuyt/alfeK2JVlyvvjmdyKcc/21xGZXxOkKqdiXFpzpCqnIpUvUXd/Xf7E/HO0XtcjmD/ROo8jtV3D3IeF/TfZ3hrkdOTeOg9iKrX9dCGfQ5tRketRlQPRRGT7jXySU1HO6Xh7b6vR82xVfCizBu8BPQsAIQQLACEECwAhBAsAIQQLACEECwAhBAsAIQQLACHrkZQ1lU1i13h7sVnzxXBSyklSVcVx2qormtOxrkjzdiy7uM5xaFBop0lRnbYixXVSBXSWZZqMFSmUU6eqWI6JpCwAR4xgASCEYAEghGABIGQtBjg9M412tpXtTmbFZbt7Gr5nW54dDGhmA5cVk+b6O7aw/bx8ePjAzWAn0aaagcxode/hmXYDch4c9LPBcqp7b597t9P2kZmbU8NhosT6nDtu/WPT5sxIVeFuO3v0Y7f8ptV2U1uWnqL89mhxhuknd15p9Dy7vnh8T2XxAVN6FgBCCBYAQggWAEIIFgBCksHCzB43s6tm9nLptq+Y2RUze7H4d2/pvi+Z2WUz+6WZfXpZDQdwvCI9iyck3V1x+zfc/ULx7zlJMrMPSHpA0geLbb5lZs2GvAGspWSwcPcfS/pTcH/3SXrK3fvu/htJlyV9pEP7AKyJLmMWD5vZS8Vpypnittsl/b70mNeK2wBc49oGi0cl3SHpgqTXJX296Q7M7JKZvWBmLwz33mnZDADHpVWwcPc33H3k7mNJ39bBqcYVSe8rPfS9xW1V+3jM3S+6+8WN3ok2zQBwjFoFCzO7rfTrZyVNr5Q8K+kBM9sys/dLulPST7s1EcA6SM4NMbPvSbpL0i1m9pqkL0u6y8wuSHJJr0r6oiS5+ytm9rSkX0jak/SQu6+mWgiAI5UMFu7+uYqb//2Qx39V0le7NArA+iGDE0AIwQJAyFrUs5CZxhv5fj0LqahxsTlbz6J8X9l4c3GXeaLuRF29iv191hS2zYbBVc4bFKOd0QvWgxgsJzG2ST2KKlsb8eXjm9azSNWjSEkVu21bzyJSj+IwJ/Pd5GOq6llsW7C4SqGqnkUT9CwAhBAsAIQQLACEECwAhBAsAIQQLACEECwAhBAsAISsRVKWjV29v/TlvUns8l6mbOCziVi9g2Ss+QWEqhKwxqV8n6pFiFKLBdUlX9WtXj6f5NV6EaBoslXLnKxUsljTRKku2+cNEteybNw6aWoqtf1Gnp7zWJUYVpUw1URk++kK6OUEsD+Pm5V2qEriYhV1AEduLXoWU9OexXhj8a/TfPp3cl+l3kRVOnhbdWnidenhy7L0dPJj0CS1vEkaeVuRdPJUyviyTHsUkdTwOlU9i8zoWQA4YgQLACFrcRrimWnv5Jay4WQQJxuONLx5a2YwMRu6bDTpMg1Ozsa4qlOD1ADm4FSi+5VV32/BWad2dhB63MLT1jzvvNFwOXH+9nNvdtp+M4sXRms6YPnhs79r2pwZG4m2vb3XbqCy6Wrm8yKzR6sGM//5RLNTkqEvfrZuajAOT88CQAjBAkAIwQJACMECQAjBAkAIwQJACMECQAjBAkAIwQJACMECQAjBAkDIWswNkSbzQabTyj3PZCOXlVL5Pbf9uSLzM4mrZhaX55VUzR2x1BSGUU3xm7raLnNzOrxm+5RRcDtrOUU9NfdkNO729+PdBtvnDaaob2Yj9cfdPq6p7bey9DT4qvklXVf6imw/nT9SnkdSNdfjMBu2+OE1xT+n9CwAhBAsAIQQLACEECwAhBAsAISYNxxRXUojzP5H0l8l/XHVbTlmt4hjvhGs8zH/vbvfGnngWgQLSTKzF9z94qrbcZw45hvD9XLMnIYACCFYAAhZp2Dx2KobsAIc843hujjmtRmzALDe1qlnAWCNESwAhBAsAIQQLACEECwAhPw/LvSDOWuiMpAAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21329be0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8332343101501465 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 0.001} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.7803995609283447 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 0.01} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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ACEkGCzN73MyumtnLpdvOmtmPzOxXxf9nitvNzL5pZpfN7CUz+9AyGw/g+ER6Fk9IunvutkckPe/ud0p6vvhdku6RdGfx75KkR4+mmQBWLRks3P3Hkv40d/N9kp4sfn5S0mdKt3/HJ34i6bSZ3XZUjQWwOm3HLM67++vFz3+QdL74+XZJvy897rXiNgDXuM4DnO7ukhpny5jZJTN7wcxeGIze6doMAEvWNli8MT29KP6/Wtx+RdL7So97b3HbAnd/zN0vuvvFzfxEy2YAOC5t072flfSgpK8V/3+/dPvDZvaUpI9KerN0ulLPXfb2u1JepLTmmbL+aCbF2/NsfznD+VTuqtRuzw5SiSuXN0wsQ1iX1l2XDj3/HG3TsaPbtU0nT23XdEnBBQ1SuJscg+dqvbzg/j5S21ugg1yRcl6Vit1EZPu8eN5yavm7e8G5AdN9VKSlW4OM+2SwMLPvSbpL0i1m9pqkL2sSJJ42sy9I+q2k+4uHPyfpXkmXJb0j6fPxpgBYZ8lg4e6fq7nrkxWPdUkPdW0UgPVDBieAEIIFgBCCBYAQggWAEIIFgBCCBYAQggWAEIIFgJC1qe4tSconscs3F5s1X+07pZx+XVepu426quBH+RwRy64efhyaVBJvVDW8rUD18FSF8GWZpnlHKoHXqaoGbg3mgK5HsMgy+c1/IxtMXggb7Gl4/oQ8P/gC5v2xsr3Jgb1zcvZTVvWhS5Xs758+/Mtd90GOzp3on2n34Y4GgWUtBTA813HHTcr1N5zrceLWvzZszKw8P/yLPhy2+zrccesfW2031bN0AKqaB/Lhs79r9Dz98eLxvZTHJwNxGgIghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASBkPepZSBpv95QPDmopeG4ab5brWah039y2FQVdUmuZpgqvVEz9lxSvZ9F6LdJokZe9JRXbaVKPokKT4jDJtUfnpOpRpGz1Fou/lLWtZxGpR3GYmzf6ycdU1bPYqChmc5iqehZN0LMAEEKwABBCsAAQQrAAEEKwABBCsAAQQrAAELIeeRbuyt/alfeK2JVlyvvjmdyKcc/21xGZXxOkKqdiXFpzpCqnIpUvUXd/Xf7E/HO0XtcjmD/ROo8jtV3D3IeF/TfZ3hrkdOTeOg9iKrX9dCGfQ5tRketRlQPRRGT7jXySU1HO6Xh7b6vR82xVfCizBu8BPQsAIQQLACEECwAhBAsAIQQLACEECwAhBAsAIQQLACHrkZQ1lU1i13h7sVnzxXBSyklSVcVx2qormtOxrkjzdiy7uM5xaFBop0lRnbYixXVSBXSWZZqMFSmUU6eqWI6JpCwAR4xgASCEYAEghGABIGQtBjg9M412tpXtTmbFZbt7Gr5nW54dDGhmA5cVk+b6O7aw/bx8ePjAzWAn0aaagcxode/hmXYDch4c9LPBcqp7b597t9P2kZmbU8NhosT6nDtu/WPT5sxIVeFuO3v0Y7f8ptV2U1uWnqL89mhxhuknd15p9Dy7vnh8T2XxAVN6FgBCCBYAQggWAEIIFgBCksHCzB43s6tm9nLptq+Y2RUze7H4d2/pvi+Z2WUz+6WZfXpZDQdwvCI9iyck3V1x+zfc/ULx7zlJMrMPSHpA0geLbb5lZs2GvAGspWSwcPcfS/pTcH/3SXrK3fvu/htJlyV9pEP7AKyJLmMWD5vZS8Vpypnittsl/b70mNeK2wBc49oGi0cl3SHpgqTXJX296Q7M7JKZvWBmLwz33mnZDADHpVWwcPc33H3k7mNJ39bBqcYVSe8rPfS9xW1V+3jM3S+6+8WN3ok2zQBwjFoFCzO7rfTrZyVNr5Q8K+kBM9sys/dLulPST7s1EcA6SM4NMbPvSbpL0i1m9pqkL0u6y8wuSHJJr0r6oiS5+ytm9rSkX0jak/SQu6+mWgiAI5UMFu7+uYqb//2Qx39V0le7NArA+iGDE0AIwQJAyFrUs5CZxhv5fj0LqahxsTlbz6J8X9l4c3GXeaLuRF29iv191hS2zYbBVc4bFKOd0QvWgxgsJzG2ST2KKlsb8eXjm9azSNWjSEkVu21bzyJSj+IwJ/Pd5GOq6llsW7C4SqGqnkUT9CwAhBAsAIQQLACEECwAhBAsAIQQLACEECwAhBAsAISsRVKWjV29v/TlvUns8l6mbOCziVi9g2Ss+QWEqhKwxqV8n6pFiFKLBdUlX9WtXj6f5NV6EaBoslXLnKxUsljTRKku2+cNEteybNw6aWoqtf1Gnp7zWJUYVpUw1URk++kK6OUEsD+Pm5V2qEriYhV1AEduLXoWU9OexXhj8a/TfPp3cl+l3kRVOnhbdWnidenhy7L0dPJj0CS1vEkaeVuRdPJUyviyTHsUkdTwOlU9i8zoWQA4YgQLACFrcRrimWnv5Jay4WQQJxuONLx5a2YwMRu6bDTpMg1Ozsa4qlOD1ADm4FSi+5VV32/BWad2dhB63MLT1jzvvNFwOXH+9nNvdtp+M4sXRms6YPnhs79r2pwZG4m2vb3XbqCy6Wrm8yKzR6sGM//5RLNTkqEvfrZuajAOT88CQAjBAkAIwQJACMECQAjBAkAIwQJACMECQAjBAkAIwQJACMECQAjBAkDIWswNkSbzQabTyj3PZCOXlVL5Pbf9uSLzM4mrZhaX55VUzR2x1BSGUU3xm7raLnNzOrxm+5RRcDtrOUU9NfdkNO729+PdBtvnDaaob2Yj9cfdPq6p7bey9DT4qvklXVf6imw/nT9SnkdSNdfjMBu2+OE1xT+n9CwAhBAsAIQQLACEECwAhBAsAISYNxxRXUojzP5H0l8l/XHVbTlmt4hjvhGs8zH/vbvfGnngWgQLSTKzF9z94qrbcZw45hvD9XLMnIYACCFYAAhZp2Dx2KobsAIc843hujjmtRmzALDe1qlnAWCNESwAhBAsAIQQLACEECwAhPw/LvSDOWuiMpAAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21348f28>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.7787373065948486 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 0.1} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21304400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.7911996841430664 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 1.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb212eaa20>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.778780221939087 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 10.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb213332b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8241212368011475 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 100.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2127e080>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.7918579578399658 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 1000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb211de7f0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8034930229187012 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 10000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2135c080>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.83528733253479 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 100000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2123e198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8089466094970703 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 1000000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21187c88>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8145177364349365 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 10000000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2116fa90>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.7873256206512451 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 100000000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2119e780>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.7759017944335938 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 1000000000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb211d4c18>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.804816484451294 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 1.0, 'lmda': 10000000000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb212b5f98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.711700677871704 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 1e-10} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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ACEkGCzN73MyumtnLpdvOmtmPzOxXxf9nitvNzL5pZpfN7CUz+9AyGw/g+ER6Fk9IunvutkckPe/ud0p6vvhdku6RdGfx75KkR4+mmQBWLRks3P3Hkv40d/N9kp4sfn5S0mdKt3/HJ34i6bSZ3XZUjQWwOm3HLM67++vFz3+QdL74+XZJvy897rXiNgDXuM4DnO7ukhpny5jZJTN7wcxeGIze6doMAEvWNli8MT29KP6/Wtx+RdL7So97b3HbAnd/zN0vuvvFzfxEy2YAOC5t072flfSgpK8V/3+/dPvDZvaUpI9KerN0ulLPXfb2u1JepLTmmbL+aCbF2/NsfznD+VTuqtRuzw5SiSuXN0wsQ1iX1l2XDj3/HG3TsaPbtU0nT23XdEnBBQ1SuJscg+dqvbzg/j5S21ugg1yRcl6Vit1EZPu8eN5yavm7e8G5AdN9VKSlW4OM+2SwMLPvSbpL0i1m9pqkL2sSJJ42sy9I+q2k+4uHPyfpXkmXJb0j6fPxpgBYZ8lg4e6fq7nrkxWPdUkPdW0UgPVDBieAEIIFgBCCBYAQggWAEIIFgBCCBYAQggWAEIIFgJC1qe4tSconscs3F5s1X+07pZx+XVepu426quBH+RwRy64efhyaVBJvVDW8rUD18FSF8GWZpnlHKoHXqaoGbg3mgK5HsMgy+c1/IxtMXggb7Gl4/oQ8P/gC5v2xsr3Jgb1zcvZTVvWhS5Xs758+/Mtd90GOzp3on2n34Y4GgWUtBTA813HHTcr1N5zrceLWvzZszKw8P/yLPhy2+zrccesfW2031bN0AKqaB/Lhs79r9Dz98eLxvZTHJwNxGgIghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASBkPepZSBpv95QPDmopeG4ab5brWah039y2FQVdUmuZpgqvVEz9lxSvZ9F6LdJokZe9JRXbaVKPokKT4jDJtUfnpOpRpGz1Fou/lLWtZxGpR3GYmzf6ycdU1bPYqChmc5iqehZN0LMAEEKwABBCsAAQQrAAEEKwABBCsAAQQrAAELIeeRbuyt/alfeK2JVlyvvjmdyKcc/21xGZXxOkKqdiXFpzpCqnIpUvUXd/Xf7E/HO0XtcjmD/ROo8jtV3D3IeF/TfZ3hrkdOTeOg9iKrX9dCGfQ5tRketRlQPRRGT7jXySU1HO6Xh7b6vR82xVfCizBu8BPQsAIQQLACEECwAhBAsAIQQLACEECwAhBAsAIQQLACHrkZQ1lU1i13h7sVnzxXBSyklSVcVx2qormtOxrkjzdiy7uM5xaFBop0lRnbYixXVSBXSWZZqMFSmUU6eqWI6JpCwAR4xgASCEYAEghGABIGQtBjg9M412tpXtTmbFZbt7Gr5nW54dDGhmA5cVk+b6O7aw/bx8ePjAzWAn0aaagcxode/hmXYDch4c9LPBcqp7b597t9P2kZmbU8NhosT6nDtu/WPT5sxIVeFuO3v0Y7f8ptV2U1uWnqL89mhxhuknd15p9Dy7vnh8T2XxAVN6FgBCCBYAQggWAEIIFgBCksHCzB43s6tm9nLptq+Y2RUze7H4d2/pvi+Z2WUz+6WZfXpZDQdwvCI9iyck3V1x+zfc/ULx7zlJMrMPSHpA0geLbb5lZs2GvAGspWSwcPcfS/pTcH/3SXrK3fvu/htJlyV9pEP7AKyJLmMWD5vZS8Vpypnittsl/b70mNeK2wBc49oGi0cl3SHpgqTXJX296Q7M7JKZvWBmLwz33mnZDADHpVWwcPc33H3k7mNJ39bBqcYVSe8rPfS9xW1V+3jM3S+6+8WN3ok2zQBwjFoFCzO7rfTrZyVNr5Q8K+kBM9sys/dLulPST7s1EcA6SM4NMbPvSbpL0i1m9pqkL0u6y8wuSHJJr0r6oiS5+ytm9rSkX0jak/SQu6+mWgiAI5UMFu7+uYqb//2Qx39V0le7NArA+iGDE0AIwQJAyFrUs5CZxhv5fj0LqahxsTlbz6J8X9l4c3GXeaLuRF29iv191hS2zYbBVc4bFKOd0QvWgxgsJzG2ST2KKlsb8eXjm9azSNWjSEkVu21bzyJSj+IwJ/Pd5GOq6llsW7C4SqGqnkUT9CwAhBAsAIQQLACEECwAhBAsAIQQLACEECwAhBAsAISsRVKWjV29v/TlvUns8l6mbOCziVi9g2Ss+QWEqhKwxqV8n6pFiFKLBdUlX9WtXj6f5NV6EaBoslXLnKxUsljTRKku2+cNEteybNw6aWoqtf1Gnp7zWJUYVpUw1URk++kK6OUEsD+Pm5V2qEriYhV1AEduLXoWU9OexXhj8a/TfPp3cl+l3kRVOnhbdWnidenhy7L0dPJj0CS1vEkaeVuRdPJUyviyTHsUkdTwOlU9i8zoWQA4YgQLACFrcRrimWnv5Jay4WQQJxuONLx5a2YwMRu6bDTpMg1Ozsa4qlOD1ADm4FSi+5VV32/BWad2dhB63MLT1jzvvNFwOXH+9nNvdtp+M4sXRms6YPnhs79r2pwZG4m2vb3XbqCy6Wrm8yKzR6sGM//5RLNTkqEvfrZuajAOT88CQAjBAkAIwQJACMECQAjBAkAIwQJACMECQAjBAkAIwQJACMECQAjBAkDIWswNkSbzQabTyj3PZCOXlVL5Pbf9uSLzM4mrZhaX55VUzR2x1BSGUU3xm7raLnNzOrxm+5RRcDtrOUU9NfdkNO729+PdBtvnDaaob2Yj9cfdPq6p7bey9DT4qvklXVf6imw/nT9SnkdSNdfjMBu2+OE1xT+n9CwAhBAsAIQQLACEECwAhBAsAISYNxxRXUojzP5H0l8l/XHVbTlmt4hjvhGs8zH/vbvfGnngWgQLSTKzF9z94qrbcZw45hvD9XLMnIYACCFYAAhZp2Dx2KobsAIc843hujjmtRmzALDe1qlnAWCNESwAhBAsAIQQLACEECwAhPw/LvSDOWuiMpAAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2123e1d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.743802785873413 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 1e-09} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21166470>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.8793838024139404 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 1e-08} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb211b1c50>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.8132786750793457 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 1e-07} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb212b4b70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.9745256900787354 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 1e-06} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb213dd278>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.7534687519073486 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 1e-05} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb211e3fd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.7800660133361816 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 0.0001} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb213cae10>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.9411191940307617 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 0.001} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb211f5e48>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.7407543659210205 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 0.01} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21274b70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.7607641220092773 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 0.1} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21331940>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.9025001525878906 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 1.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21262a90>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.862701654434204 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 10.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2128d438>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.8413772583007812 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 100.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21283898>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.809281826019287 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 1000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21367198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.8215384483337402 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 10000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2132d208>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.7482171058654785 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 100000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2134f9e8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.6674375534057617 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 1000000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2129a978>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.7299928665161133 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 10000000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2134fa90>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.73073673248291 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 100000000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb211e79b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.7332351207733154 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 1000000000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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ACEkGCzN73MyumtnLpdvOmtmPzOxXxf9nitvNzL5pZpfN7CUz+9AyGw/g+ER6Fk9IunvutkckPe/ud0p6vvhdku6RdGfx75KkR4+mmQBWLRks3P3Hkv40d/N9kp4sfn5S0mdKt3/HJ34i6bSZ3XZUjQWwOm3HLM67++vFz3+QdL74+XZJvy897rXiNgDXuM4DnO7ukhpny5jZJTN7wcxeGIze6doMAEvWNli8MT29KP6/Wtx+RdL7So97b3HbAnd/zN0vuvvFzfxEy2YAOC5t072flfSgpK8V/3+/dPvDZvaUpI9KerN0ulLPXfb2u1JepLTmmbL+aCbF2/NsfznD+VTuqtRuzw5SiSuXN0wsQ1iX1l2XDj3/HG3TsaPbtU0nT23XdEnBBQ1SuJscg+dqvbzg/j5S21ugg1yRcl6Vit1EZPu8eN5yavm7e8G5AdN9VKSlW4OM+2SwMLPvSbpL0i1m9pqkL2sSJJ42sy9I+q2k+4uHPyfpXkmXJb0j6fPxpgBYZ8lg4e6fq7nrkxWPdUkPdW0UgPVDBieAEIIFgBCCBYAQggWAEIIFgBCCBYAQggWAEIIFgJC1qe4tSconscs3F5s1X+07pZx+XVepu426quBH+RwRy64efhyaVBJvVDW8rUD18FSF8GWZpnlHKoHXqaoGbg3mgK5HsMgy+c1/IxtMXggb7Gl4/oQ8P/gC5v2xsr3Jgb1zcvZTVvWhS5Xs758+/Mtd90GOzp3on2n34Y4GgWUtBTA813HHTcr1N5zrceLWvzZszKw8P/yLPhy2+zrccesfW2031bN0AKqaB/Lhs79r9Dz98eLxvZTHJwNxGgIghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASBkPepZSBpv95QPDmopeG4ab5brWah039y2FQVdUmuZpgqvVEz9lxSvZ9F6LdJokZe9JRXbaVKPokKT4jDJtUfnpOpRpGz1Fou/lLWtZxGpR3GYmzf6ycdU1bPYqChmc5iqehZN0LMAEEKwABBCsAAQQrAAEEKwABBCsAAQQrAAELIeeRbuyt/alfeK2JVlyvvjmdyKcc/21xGZXxOkKqdiXFpzpCqnIpUvUXd/Xf7E/HO0XtcjmD/ROo8jtV3D3IeF/TfZ3hrkdOTeOg9iKrX9dCGfQ5tRketRlQPRRGT7jXySU1HO6Xh7b6vR82xVfCizBu8BPQsAIQQLACEECwAhBAsAIQQLACEECwAhBAsAIQQLACHrkZQ1lU1i13h7sVnzxXBSyklSVcVx2qormtOxrkjzdiy7uM5xaFBop0lRnbYixXVSBXSWZZqMFSmUU6eqWI6JpCwAR4xgASCEYAEghGABIGQtBjg9M412tpXtTmbFZbt7Gr5nW54dDGhmA5cVk+b6O7aw/bx8ePjAzWAn0aaagcxode/hmXYDch4c9LPBcqp7b597t9P2kZmbU8NhosT6nDtu/WPT5sxIVeFuO3v0Y7f8ptV2U1uWnqL89mhxhuknd15p9Dy7vnh8T2XxAVN6FgBCCBYAQggWAEIIFgBCksHCzB43s6tm9nLptq+Y2RUze7H4d2/pvi+Z2WUz+6WZfXpZDQdwvCI9iyck3V1x+zfc/ULx7zlJMrMPSHpA0geLbb5lZs2GvAGspWSwcPcfS/pTcH/3SXrK3fvu/htJlyV9pEP7AKyJLmMWD5vZS8Vpypnittsl/b70mNeK2wBc49oGi0cl3SHpgqTXJX296Q7M7JKZvWBmLwz33mnZDADHpVWwcPc33H3k7mNJ39bBqcYVSe8rPfS9xW1V+3jM3S+6+8WN3ok2zQBwjFoFCzO7rfTrZyVNr5Q8K+kBM9sys/dLulPST7s1EcA6SM4NMbPvSbpL0i1m9pqkL0u6y8wuSHJJr0r6oiS5+ytm9rSkX0jak/SQu6+mWgiAI5UMFu7+uYqb//2Qx39V0le7NArA+iGDE0AIwQJAyFrUs5CZxhv5fj0LqahxsTlbz6J8X9l4c3GXeaLuRF29iv191hS2zYbBVc4bFKOd0QvWgxgsJzG2ST2KKlsb8eXjm9azSNWjSEkVu21bzyJSj+IwJ/Pd5GOq6llsW7C4SqGqnkUT9CwAhBAsAIQQLACEECwAhBAsAIQQLACEECwAhBAsAISsRVKWjV29v/TlvUns8l6mbOCziVi9g2Ss+QWEqhKwxqV8n6pFiFKLBdUlX9WtXj6f5NV6EaBoslXLnKxUsljTRKku2+cNEteybNw6aWoqtf1Gnp7zWJUYVpUw1URk++kK6OUEsD+Pm5V2qEriYhV1AEduLXoWU9OexXhj8a/TfPp3cl+l3kRVOnhbdWnidenhy7L0dPJj0CS1vEkaeVuRdPJUyviyTHsUkdTwOlU9i8zoWQA4YgQLACFrcRrimWnv5Jay4WQQJxuONLx5a2YwMRu6bDTpMg1Ozsa4qlOD1ADm4FSi+5VV32/BWad2dhB63MLT1jzvvNFwOXH+9nNvdtp+M4sXRms6YPnhs79r2pwZG4m2vb3XbqCy6Wrm8yKzR6sGM//5RLNTkqEvfrZuajAOT88CQAjBAkAIwQJACMECQAjBAkAIwQJACMECQAjBAkAIwQJACMECQAjBAkDIWswNkSbzQabTyj3PZCOXlVL5Pbf9uSLzM4mrZhaX55VUzR2x1BSGUU3xm7raLnNzOrxm+5RRcDtrOUU9NfdkNO729+PdBtvnDaaob2Yj9cfdPq6p7bey9DT4qvklXVf6imw/nT9SnkdSNdfjMBu2+OE1xT+n9CwAhBAsAIQQLACEECwAhBAsAISYNxxRXUojzP5H0l8l/XHVbTlmt4hjvhGs8zH/vbvfGnngWgQLSTKzF9z94qrbcZw45hvD9XLMnIYACCFYAAhZp2Dx2KobsAIc843hujjmtRmzALDe1qlnAWCNESwAhBAsAIQQLACEECwAhPw/LvSDOWuiMpAAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21233f98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 3.7009294033050537 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 1.0, 'lmda': 10000000000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2119b2e8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.795102834701538 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 1e-10} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2120e128>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8175323009490967 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 1e-09} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb212f6b00>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.7915070056915283 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 1e-08} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb211c4f28>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.789095401763916 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 1e-07} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb212eef60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.781489372253418 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 1e-06} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb213e5588>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8251757621765137 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 1e-05} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2120d278>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.7852787971496582 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 0.0001} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2121eba8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.816478967666626 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 0.001} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21221e48>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.821610927581787 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 0.01} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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ACEkGCzN73MyumtnLpdvOmtmPzOxXxf9nitvNzL5pZpfN7CUz+9AyGw/g+ER6Fk9IunvutkckPe/ud0p6vvhdku6RdGfx75KkR4+mmQBWLRks3P3Hkv40d/N9kp4sfn5S0mdKt3/HJ34i6bSZ3XZUjQWwOm3HLM67++vFz3+QdL74+XZJvy897rXiNgDXuM4DnO7ukhpny5jZJTN7wcxeGIze6doMAEvWNli8MT29KP6/Wtx+RdL7So97b3HbAnd/zN0vuvvFzfxEy2YAOC5t072flfSgpK8V/3+/dPvDZvaUpI9KerN0ulLPXfb2u1JepLTmmbL+aCbF2/NsfznD+VTuqtRuzw5SiSuXN0wsQ1iX1l2XDj3/HG3TsaPbtU0nT23XdEnBBQ1SuJscg+dqvbzg/j5S21ugg1yRcl6Vit1EZPu8eN5yavm7e8G5AdN9VKSlW4OM+2SwMLPvSbpL0i1m9pqkL2sSJJ42sy9I+q2k+4uHPyfpXkmXJb0j6fPxpgBYZ8lg4e6fq7nrkxWPdUkPdW0UgPVDBieAEIIFgBCCBYAQggWAEIIFgBCCBYAQggWAEIIFgJC1qe4tSconscs3F5s1X+07pZx+XVepu426quBH+RwRy64efhyaVBJvVDW8rUD18FSF8GWZpnlHKoHXqaoGbg3mgK5HsMgy+c1/IxtMXggb7Gl4/oQ8P/gC5v2xsr3Jgb1zcvZTVvWhS5Xs758+/Mtd90GOzp3on2n34Y4GgWUtBTA813HHTcr1N5zrceLWvzZszKw8P/yLPhy2+zrccesfW2031bN0AKqaB/Lhs79r9Dz98eLxvZTHJwNxGgIghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASBkPepZSBpv95QPDmopeG4ab5brWah039y2FQVdUmuZpgqvVEz9lxSvZ9F6LdJokZe9JRXbaVKPokKT4jDJtUfnpOpRpGz1Fou/lLWtZxGpR3GYmzf6ycdU1bPYqChmc5iqehZN0LMAEEKwABBCsAAQQrAAEEKwABBCsAAQQrAAELIeeRbuyt/alfeK2JVlyvvjmdyKcc/21xGZXxOkKqdiXFpzpCqnIpUvUXd/Xf7E/HO0XtcjmD/ROo8jtV3D3IeF/TfZ3hrkdOTeOg9iKrX9dCGfQ5tRketRlQPRRGT7jXySU1HO6Xh7b6vR82xVfCizBu8BPQsAIQQLACEECwAhBAsAIQQLACEECwAhBAsAIQQLACHrkZQ1lU1i13h7sVnzxXBSyklSVcVx2qormtOxrkjzdiy7uM5xaFBop0lRnbYixXVSBXSWZZqMFSmUU6eqWI6JpCwAR4xgASCEYAEghGABIGQtBjg9M412tpXtTmbFZbt7Gr5nW54dDGhmA5cVk+b6O7aw/bx8ePjAzWAn0aaagcxode/hmXYDch4c9LPBcqp7b597t9P2kZmbU8NhosT6nDtu/WPT5sxIVeFuO3v0Y7f8ptV2U1uWnqL89mhxhuknd15p9Dy7vnh8T2XxAVN6FgBCCBYAQggWAEIIFgBCksHCzB43s6tm9nLptq+Y2RUze7H4d2/pvi+Z2WUz+6WZfXpZDQdwvCI9iyck3V1x+zfc/ULx7zlJMrMPSHpA0geLbb5lZs2GvAGspWSwcPcfS/pTcH/3SXrK3fvu/htJlyV9pEP7AKyJLmMWD5vZS8Vpypnittsl/b70mNeK2wBc49oGi0cl3SHpgqTXJX296Q7M7JKZvWBmLwz33mnZDADHpVWwcPc33H3k7mNJ39bBqcYVSe8rPfS9xW1V+3jM3S+6+8WN3ok2zQBwjFoFCzO7rfTrZyVNr5Q8K+kBM9sys/dLulPST7s1EcA6SM4NMbPvSbpL0i1m9pqkL0u6y8wuSHJJr0r6oiS5+ytm9rSkX0jak/SQu6+mWgiAI5UMFu7+uYqb//2Qx39V0le7NArA+iGDE0AIwQJAyFrUs5CZxhv5fj0LqahxsTlbz6J8X9l4c3GXeaLuRF29iv191hS2zYbBVc4bFKOd0QvWgxgsJzG2ST2KKlsb8eXjm9azSNWjSEkVu21bzyJSj+IwJ/Pd5GOq6llsW7C4SqGqnkUT9CwAhBAsAIQQLACEECwAhBAsAIQQLACEECwAhBAsAISsRVKWjV29v/TlvUns8l6mbOCziVi9g2Ss+QWEqhKwxqV8n6pFiFKLBdUlX9WtXj6f5NV6EaBoslXLnKxUsljTRKku2+cNEteybNw6aWoqtf1Gnp7zWJUYVpUw1URk++kK6OUEsD+Pm5V2qEriYhV1AEduLXoWU9OexXhj8a/TfPp3cl+l3kRVOnhbdWnidenhy7L0dPJj0CS1vEkaeVuRdPJUyviyTHsUkdTwOlU9i8zoWQA4YgQLACFrcRrimWnv5Jay4WQQJxuONLx5a2YwMRu6bDTpMg1Ozsa4qlOD1ADm4FSi+5VV32/BWad2dhB63MLT1jzvvNFwOXH+9nNvdtp+M4sXRms6YPnhs79r2pwZG4m2vb3XbqCy6Wrm8yKzR6sGM//5RLNTkqEvfrZuajAOT88CQAjBAkAIwQJACMECQAjBAkAIwQJACMECQAjBAkAIwQJACMECQAjBAkDIWswNkSbzQabTyj3PZCOXlVL5Pbf9uSLzM4mrZhaX55VUzR2x1BSGUU3xm7raLnNzOrxm+5RRcDtrOUU9NfdkNO729+PdBtvnDaaob2Yj9cfdPq6p7bey9DT4qvklXVf6imw/nT9SnkdSNdfjMBu2+OE1xT+n9CwAhBAsAIQQLACEECwAhBAsAISYNxxRXUojzP5H0l8l/XHVbTlmt4hjvhGs8zH/vbvfGnngWgQLSTKzF9z94qrbcZw45hvD9XLMnIYACCFYAAhZp2Dx2KobsAIc843hujjmtRmzALDe1qlnAWCNESwAhBAsAIQQLACEECwAhPw/LvSDOWuiMpAAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb211b3710>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.7589621543884277 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 0.1} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb212a4e10>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.7933294773101807 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 1.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb211e6f28>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.7772436141967773 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 10.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb212822b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8266870975494385 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 100.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2112c198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 2.0591745376586914 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 1000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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ACEkGCzN73MyumtnLpdvOmtmPzOxXxf9nitvNzL5pZpfN7CUz+9AyGw/g+ER6Fk9IunvutkckPe/ud0p6vvhdku6RdGfx75KkR4+mmQBWLRks3P3Hkv40d/N9kp4sfn5S0mdKt3/HJ34i6bSZ3XZUjQWwOm3HLM67++vFz3+QdL74+XZJvy897rXiNgDXuM4DnO7ukhpny5jZJTN7wcxeGIze6doMAEvWNli8MT29KP6/Wtx+RdL7So97b3HbAnd/zN0vuvvFzfxEy2YAOC5t072flfSgpK8V/3+/dPvDZvaUpI9KerN0ulLPXfb2u1JepLTmmbL+aCbF2/NsfznD+VTuqtRuzw5SiSuXN0wsQ1iX1l2XDj3/HG3TsaPbtU0nT23XdEnBBQ1SuJscg+dqvbzg/j5S21ugg1yRcl6Vit1EZPu8eN5yavm7e8G5AdN9VKSlW4OM+2SwMLPvSbpL0i1m9pqkL2sSJJ42sy9I+q2k+4uHPyfpXkmXJb0j6fPxpgBYZ8lg4e6fq7nrkxWPdUkPdW0UgPVDBieAEIIFgBCCBYAQggWAEIIFgBCCBYAQggWAEIIFgJC1qe4tSconscs3F5s1X+07pZx+XVepu426quBH+RwRy64efhyaVBJvVDW8rUD18FSF8GWZpnlHKoHXqaoGbg3mgK5HsMgy+c1/IxtMXggb7Gl4/oQ8P/gC5v2xsr3Jgb1zcvZTVvWhS5Xs758+/Mtd90GOzp3on2n34Y4GgWUtBTA813HHTcr1N5zrceLWvzZszKw8P/yLPhy2+zrccesfW2031bN0AKqaB/Lhs79r9Dz98eLxvZTHJwNxGgIghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASCEYAEghGABIIRgASBkPepZSBpv95QPDmopeG4ab5brWah039y2FQVdUmuZpgqvVEz9lxSvZ9F6LdJokZe9JRXbaVKPokKT4jDJtUfnpOpRpGz1Fou/lLWtZxGpR3GYmzf6ycdU1bPYqChmc5iqehZN0LMAEEKwABBCsAAQQrAAEEKwABBCsAAQQrAAELIeeRbuyt/alfeK2JVlyvvjmdyKcc/21xGZXxOkKqdiXFpzpCqnIpUvUXd/Xf7E/HO0XtcjmD/ROo8jtV3D3IeF/TfZ3hrkdOTeOg9iKrX9dCGfQ5tRketRlQPRRGT7jXySU1HO6Xh7b6vR82xVfCizBu8BPQsAIQQLACEECwAhBAsAIQQLACEECwAhBAsAIQQLACHrkZQ1lU1i13h7sVnzxXBSyklSVcVx2qormtOxrkjzdiy7uM5xaFBop0lRnbYixXVSBXSWZZqMFSmUU6eqWI6JpCwAR4xgASCEYAEghGABIGQtBjg9M412tpXtTmbFZbt7Gr5nW54dDGhmA5cVk+b6O7aw/bx8ePjAzWAn0aaagcxode/hmXYDch4c9LPBcqp7b597t9P2kZmbU8NhosT6nDtu/WPT5sxIVeFuO3v0Y7f8ptV2U1uWnqL89mhxhuknd15p9Dy7vnh8T2XxAVN6FgBCCBYAQggWAEIIFgBCksHCzB43s6tm9nLptq+Y2RUze7H4d2/pvi+Z2WUz+6WZfXpZDQdwvCI9iyck3V1x+zfc/ULx7zlJMrMPSHpA0geLbb5lZs2GvAGspWSwcPcfS/pTcH/3SXrK3fvu/htJlyV9pEP7AKyJLmMWD5vZS8Vpypnittsl/b70mNeK2wBc49oGi0cl3SHpgqTXJX296Q7M7JKZvWBmLwz33mnZDADHpVWwcPc33H3k7mNJ39bBqcYVSe8rPfS9xW1V+3jM3S+6+8WN3ok2zQBwjFoFCzO7rfTrZyVNr5Q8K+kBM9sys/dLulPST7s1EcA6SM4NMbPvSbpL0i1m9pqkL0u6y8wuSHJJr0r6oiS5+ytm9rSkX0jak/SQu6+mWgiAI5UMFu7+uYqb//2Qx39V0le7NArA+iGDE0AIwQJAyFrUs5CZxhv5fj0LqahxsTlbz6J8X9l4c3GXeaLuRF29iv191hS2zYbBVc4bFKOd0QvWgxgsJzG2ST2KKlsb8eXjm9azSNWjSEkVu21bzyJSj+IwJ/Pd5GOq6llsW7C4SqGqnkUT9CwAhBAsAIQQLACEECwAhBAsAIQQLACEECwAhBAsAISsRVKWjV29v/TlvUns8l6mbOCziVi9g2Ss+QWEqhKwxqV8n6pFiFKLBdUlX9WtXj6f5NV6EaBoslXLnKxUsljTRKku2+cNEteybNw6aWoqtf1Gnp7zWJUYVpUw1URk++kK6OUEsD+Pm5V2qEriYhV1AEduLXoWU9OexXhj8a/TfPp3cl+l3kRVOnhbdWnidenhy7L0dPJj0CS1vEkaeVuRdPJUyviyTHsUkdTwOlU9i8zoWQA4YgQLACFrcRrimWnv5Jay4WQQJxuONLx5a2YwMRu6bDTpMg1Ozsa4qlOD1ADm4FSi+5VV32/BWad2dhB63MLT1jzvvNFwOXH+9nNvdtp+M4sXRms6YPnhs79r2pwZG4m2vb3XbqCy6Wrm8yKzR6sGM//5RLNTkqEvfrZuajAOT88CQAjBAkAIwQJACMECQAjBAkAIwQJACMECQAjBAkAIwQJACMECQAjBAkDIWswNkSbzQabTyj3PZCOXlVL5Pbf9uSLzM4mrZhaX55VUzR2x1BSGUU3xm7raLnNzOrxm+5RRcDtrOUU9NfdkNO729+PdBtvnDaaob2Yj9cfdPq6p7bey9DT4qvklXVf6imw/nT9SnkdSNdfjMBu2+OE1xT+n9CwAhBAsAIQQLACEECwAhBAsAISYNxxRXUojzP5H0l8l/XHVbTlmt4hjvhGs8zH/vbvfGnngWgQLSTKzF9z94qrbcZw45hvD9XLMnIYACCFYAAhZp2Dx2KobsAIc843hujjmtRmzALDe1qlnAWCNESwAhBAsAIQQLACEECwAhPw/LvSDOWuiMpAAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb211609e8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.90696382522583 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 10000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2116f240>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8194646835327148 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 100000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2134f3c8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8314118385314941 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 1000000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2134fef0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8367934226989746 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 10000000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2116fe48>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8164896965026855 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 100000000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21362fd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.827906847000122 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 1000000000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21118b38>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 1.8394818305969238 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 1.0, 'lmda': 10000000000.0} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21365358>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.65642762184143 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 1e-10} is: \n",
-      "[[ 13.          14.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [ 14.          20.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [  4.           4.          13.         ...  29.          29.\n",
-      "   29.        ]\n",
-      " ...\n",
-      " [ 20.          20.          29.         ... 365.00000001 365.00000001\n",
-      "  365.00000001]\n",
-      " [ 20.          20.          29.         ... 365.00000001 365.00000001\n",
-      "  365.00000001]\n",
-      " [ 20.          20.          29.         ... 365.00000001 365.00000001\n",
-      "  365.00000002]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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iNO2yqt6Jfn8PwOWK6yCiBVC1BeenVfW2iFwC8AMR+b/JD1VVRdLbPEbB5UUAaLmVisUgopNWqWahqrejn+sAvgfgEwDeF5GrABD9XM/47kuqelNVbzakWhNjIjp5pYOFiCyLyGr8O4A/APAWgNcAvBDN9gKA71ctJBHNX5XbkMsAvidhMhgPwN+p6t+LyI8BvCoiXwHwKwBfql5MIpq30sFCVf8NwH9Kmb4J4PcLLcwJZKkNdBMjn0ejqAftMAeFW5/SVCPKouSvjPJV1DdScl4cG0V9epGyRjPPG9cjzkdh7j06ZjwTU5bWveo5FJK8XlTug2qPsbTA15u79m6eXjeA16v4PF6AYMpA7M2t4t1O6z3FQadiuRygOQPEN6IO2V5vVMbDs8VGlfc6k/kshPksiGjWGCyIyITBgohMGCyIyITBgohMGCyIyITBgohMGCyIyITBgohMFmLcEB368O9uwi0tHU2TTtiaU7d3wp9XLobjiDTqQC+9eaTbHbUAHVxem/y8PRp3wg2mt4Bs3EsfUax/IaPTW9Q47miksJLjelhbZvY+UKz13pGM8Txrh7Wpn1s1CrTK7F60X6vcQMytW6ep72WXr3fJsPFjs/QHgqBZfQyX5HggabpXwnUkxxcZtoutd7A2OVqc1u3LYM2CiEwYLIjIhMGCiEwYLIjIhMGCiEwYLIjIhMGCiEwYLIjIhMGCiEwYLIjIhMGCiEwYLIjIhMGCiEwWotfpOGk2UiZKOJbIoMBABxFtRDFxULFLJZDZKzOohx/IcAbrqFCOPIGX/kU3qN5z8kSdxm41rGO856tMduQ8WVX2Q8V9yJoFEZkwWBCRCYMFEZkwWBCRCYMFEZks1NsQaTXDX5wDhmNvPbwwR2RwZglymPFGxE9/NC3D8Em/vzzKwVnrTn+rEo+GPrGsjKffLsq5GdTD+NvolBvlPB7NPM9RzsyCst56xKN4FxnZPI3XtW/3YMn+eF69cqOcj6v3spfht4rn4AxqQPNe9Vc13pRyhesJ16GjUxit9WLrHa6mjKLu25fBmgURmSxEzUJqDm51BcHO7mja9WtQEbiotqGHYUZv+fU2+r/z+NgCwh+1bns0zU1GzPrG/tHv2x89P7VMXr+ZOl1leiRubofl3HwqIwt4jtqB8ZDMuN1BXKPY+nC160etb/++FtiGxq5i++mKNQsBagfZK1UUX369I9j/6EGVUgECaC+nphjt1truaL4zN7YKraY/mDy3pGVvKMKaBRGZMFgQkQmDBRGZMFgQkQmDBRGZMFgQkQmDBRGZMFgQkQmDBRGZMFgQkQmDBRGZMFgQkQmDBRGZMFgQkQmDBRGZLEQ+C4iDtNvQbu9oktZrUBH4Z1cAALWtTjgdmMjlEOdFGC6PNqex3Z9cz3DUd1+C6bkLhs30ONrcmd7/3/XDz8uOw6HGI9KomNFqXJzhqkg+ijRFc1RY1fcBr1stiYfmbFpjt/jy6/vAwV49f8YpVPL3g7dVi9Y3KuPO7lKh9QQp5QwG9uPNmgURmTBYEJEJgwURmTBYEJFJbrAQkZdFZF1E3kpMOy8iPxCRX0Y/z0XTRUT+UkRuichPReTjJ1l4Ijo9lprFtwF8bmza1wG8oao3ALwR/R8APg/gRvTvRQDfmk0xiWjecoOFqv4QwL2xyc8BeCX6/RUAX0xM/1sN/ROAsyJydVaFJaL5KfvM4rKq3ol+fw/A5ej3RwG8k5jv3WgaEd3nKj/gVFUFio/OIiIvisibIvLmYdDL/wIRzVXZYPF+fHsR/VyPpt8GcC0x32PRtAmq+pKq3lTVmw3XTpuFiBZI2eberwF4AcCfRT+/n5j+NRH5LoBPAthJ3K5k830Em/cg7WjIPxFgrxe26t7cBgDoI5fC4QxFUDtIb3LtbXWPfu9fWR19EA9vWB8N/eZyxh9ubh+mTu9eaqR/IVqHHw23KOXGRTYPTNy9ONu33vEgxUWaa6cp0oT74IJ9ZYNVIKjNYGDkTvY6Dy4ZDtrY1wcHAm2UPNgJyWEJ0/hXw+4Lw4PRfEvt9HM0S/NMd2LaRsM+fGFusBCR7wB4FsAFEXkXwDcRBolXReQrAH4F4EvR7K8D+AKAWwC6AP7IXBIiWmi5wUJVv5zx0e+nzKsAvlq1UES0eNiCk4hMGCyIyITBgohMGCyIyITBgohMGCyIyITBgohMGCyIyGQxsntHpBU193buKBN33MA3me3b9TPaaieydyeb5aZl//Z605voxlm6J8qYkRVcXbiSOCt4fb9c0+Q4y3YeNyjZLjvja3FW8apZw+v79nkHq/nzxFSAxk7FtuiYXj5/KX/5aRnCvc3qf0bJrN1pDlpRZu5EJvDuxnKhdRysDCam+b69vrAYwcIJZHkZwfbO0ST9rQ8BDnBe2BZeDofheb6+if1PPZG6mPrKqN9GWh+H5t1R79aN312bWqT6ufS2+oE3/aC274WBbONj5dLDez3bwQtmfOSaW+FJuP10tWBRJF1/kb4ejR1B/+nqvZO7+1N2nFd82922h6tPrefPOG0ZotjutabOc64WXry2d0YB4rMf/nmh9ewOJtfxD017/xLehhCRCYMFEZkwWBCRCYMFEZkwWBCRCYMFEZkwWBCRCYMFEZkwWBCRCYMFEZkwWBCRCYMFEZkwWBCRCYMFEZkwWBCRyWLks4BAGnVocihGFya8gcuPZ0EjGqfTFUiOkjdr1TwrZb9fPb9LNRXXn5YcZlHUPB++zP6Ud1ItB0jTG5ba7Q7Vx34tYjGChRPAO55sRmvhWRecCUdYd7vZiU/ED3ea3x6dqfW9lGxawSgLleSMB+s30g9ffT8vw1b4uZtMSmQSTB8fd1SOvdmeKPVeuLzawelFq2mDFE/Mu5+TuMbAFw/ws9fpOsadn1DvOGzuLVUpFkTyM1Z1dtrRL6OkSrc6FwqtZ2N/MrNWb2jfpwt8HSCiRcJgQUQmDBZEZMJgQUQmDBZEZMJgQUQmi/HqdOgjuHsP0o7GNRCH2l4//H19EwAQXLsSjiMSnEHtIP29Z3JckO5jKxOfq4xem7mMcYpi8fgf4/auZOyyaNGBF73aKvlmMx6/I0/v0mwHGfJbUVuViu/uG7v2ch1csg2oBEQDAJUY12PctNejcrlfeHn9FQ/nGyXfkydsd6cPGPTI5W0AwO5a82jahVaBEZ0APL66OTHt3TrHDSGiGWOwICITBgsiMmGwICITBgsiMmGwICITBgsiMmGwICKTxWiUFZMwdkmjPtk0qEAynHGlkuNkyVhE4E3/fOZKrifIOuLzSLpTYJ2LklSn5h1vEHgSyXTSxAl2qhymtGQ5RZa3IIeAiBYdgwURmTBYEJHJQj2zkFbUScYJMDx+b5jMyVkbZHRACtKnp+Xo9A5suTQnl5Uxf3Q7GOfuLJsjM86Fmac/KHf3mlX+OPdnkbyYaeoF+jYNCub7dNvVT9d6J/v62F/JX/7EMwpfsHVvstNiYYncmmk222GezyAYlf/nm5cKreLi8uTBOfDt+3QxgoVzcKsrCLZ3jiYFH7kOFYEX9RR1h+FZLnfuovOZ68e/H83TaI16FGpK58Lm5qhX4daN6Qf4cDX9pPKbqZNH67gbBpmtJ8tV2g6mnMxJQXO2CXub98J9uP/Rg0rLOdibftInacPe69Tb9HD1qfUyRTriRKcm1y3Te3Tr3gr+y9M/rVIs1BDgV93zU+dZq4fH5RfbowDxjd98vdB6NoeT5/wvC0R33oYQkQmDBRGZMFgQkQmDBRGZ5AYLEXlZRNZF5K3EtD8Rkdsi8pPo3xcSn31DRG6JyC9E5LMnVXAiOl2WmsW3AXwuZfpfqOoz0b/XAUBEngLwPICPRN/5axEpPiYcES2c3GChqj8EcM+4vOcAfFdV+6r67wBuAfhEhfIR0YKo8sziayLy0+g25Vw07VEA7yTmeTeaRkT3ubLB4lsAngDwDIA7AP686AJE5EUReVNE3jwMskdIJ6LFUCpYqOr7quqragDgbzC61bgN4Fpi1seiaWnLeElVb6rqzYZrlykGEZ2iUsFCRK4m/vuHAOI3Ja8BeF5EmiJyHcANAD+qVkQiWgS5fUNE5DsAngVwQUTeBfBNAM+KyDMIx916G8AfA4Cq/kxEXgXwrwCGAL6qqhldl4jofpIbLFT1yymT/8eU+f8UwJ9WKRQRLR624CQiEwYLIjJZjHwWAqB+PA+CikA9FybCmZj/+LRRstzZZZ3VeSSwBeYfvitut8ps82wkuYrLbnrDWZ4iR2qw5+VI064NKm/baViQYCGAd7xVuNbCo+qvtgAArpudmCTO/jRcSmTC6k4eQBmOpmVljIoFjfTptZzcMLVBeNDdcPp8WdKS9qTxurM9670oQ5f2Tq91fm3Xvq76vmC716q0PgHg+9nReLu7XHyhnXpu4po8ThTdYcYJF/n13hoAYGNnlMDmrd61rNlTvXMwWc794P+Zvz/v6xgR3ScYLIjIhMGCiEwYLIjIhMGCiEwYLIjIhMGCiEwWo53F0Edw9x5kKeyqLiLw9g7D3+/cBQD416+Egw4NzqCWMVpY+/1RI4i9a4lu73FLHB29p3fD6Y1g2nfT17H3aE7bgCiLoJRsp9PYts3XvTLbRjxB1K6l6uXD27K3nfCv9vNnihy06jhXq94nsbOTnQ7hkcv5O3+88dRme+loAKAq4nYUWW5e/A8AwLvLZ4+mXa1vFVrH0+13Jqb9oNY1f581CyIyWYyaRWQ01qkDhscvzYHnABH4a23U+ulX1WQLzWS73rjp9nB5dNWztsScWEfGxU2jsBsPb1i2haVnHOu0bAvRrObcGrW2L9KqMk19377dw4MC6xLF9k6JFpbjpowpuruWMzYlJndfELhjQwqWlWyZmSauURz4o/L/qPNEoXVca02m0u0F/2H+PmsWRGTCYEFEJotxG1JzcCvL0J3do0nDx84DDqgHYfUrHkXde2cD208eH0U9vs0IvKWJaUmtzcOj3zd/e3rez+FS+q7xc/oyNaNnZFsfK3efcHjWVjUftmf7gLO1Hu6wMzeKPTQbt7ObPUr5uKX2Yf5Mke7GMj774Z+XKdIRB8WtzoXMzy+07COKx36+eanwaOZp8jqFxQ8zk7ce//3R/11oHTspibFf9ezJslmzICITBgsiMmGwICITBgsiMmGwICITBgsiMmGwICITBgsiMmGwICITBgsiMmGwICKTxegbEii014O0oo4XInD9sG+FbIX9RYIPXAUcoOfOZHZRb3RGAxEdnB914oj7iRyujrr31nK6JdT30tfRPzu9C/ZgJfxcDsvFYa9j6+I9WCuZCCZj8cPV8IP+oNopEexldwEf1zxjT7xysDLA7qDaIEMAsLGf3c398dXN3O87HD8vLi7vY3M4vXu5RdoAQElx4ppkN/O0vh7TrLnJ/lC1AvUF1iyIyITBgohMGCyIyITBgohMGCyIyERUZ5txqVQhRDYA7AO4O++ynLIL4DY/DBZ5m39DVS9aZlyIYAEAIvKmqt6cdzlOE7f54fCgbDNvQ4jIhMGCiEwWKVi8NO8CzAG3+eHwQGzzwjyzIKLFtkg1CyJaYAwWRGTCYEFEJgwWRGTCYEFEJv8fTiV/vJn+AcQAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb21310cf8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.41731262207031 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 1e-09} is: \n",
-      "[[ 13.          14.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [ 14.          20.00000001   4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [  4.           4.          13.         ...  29.          29.\n",
-      "   29.        ]\n",
-      " ...\n",
-      " [ 20.          20.          29.         ... 365.00000015 365.00000015\n",
-      "  365.00000015]\n",
-      " [ 20.          20.          29.         ... 365.00000015 365.00000015\n",
-      "  365.00000015]\n",
-      " [ 20.          20.          29.         ... 365.00000015 365.00000015\n",
-      "  365.0000002 ]]\n"
-     ]
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb211e2f28>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 35.13930344581604 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 1e-08} is: \n",
-      "[[ 13.00000004  14.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [ 14.          20.00000008   4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [  4.           4.          13.00000004 ...  29.00000004  29.00000004\n",
-      "   29.00000004]\n",
-      " ...\n",
-      " [ 20.          20.          29.00000004 ... 365.00000148 365.00000148\n",
-      "  365.00000148]\n",
-      " [ 20.          20.          29.00000004 ... 365.00000148 365.00000148\n",
-      "  365.00000148]\n",
-      " [ 20.          20.          29.00000004 ... 365.00000148 365.00000148\n",
-      "  365.00000202]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb212395f8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.420260429382324 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 1e-07} is: \n",
-      "[[ 13.0000004  14.          4.        ...  20.         20.\n",
-      "   20.       ]\n",
-      " [ 14.         20.0000008   4.        ...  20.         20.\n",
-      "   20.       ]\n",
-      " [  4.          4.         13.0000004 ...  29.0000004  29.0000004\n",
-      "   29.0000004]\n",
-      " ...\n",
-      " [ 20.         20.         29.0000004 ... 365.0000148 365.0000148\n",
-      "  365.0000148]\n",
-      " [ 20.         20.         29.0000004 ... 365.0000148 365.0000148\n",
-      "  365.0000148]\n",
-      " [ 20.         20.         29.0000004 ... 365.0000148 365.0000148\n",
-      "  365.0000202]]\n"
-     ]
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468c8d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.514784812927246 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 1e-06} is: \n",
-      "[[ 13.000004  14.         4.       ...  20.        20.        20.      ]\n",
-      " [ 14.        20.000008   4.       ...  20.        20.        20.      ]\n",
-      " [  4.         4.        13.000004 ...  29.000004  29.000004  29.000004]\n",
-      " ...\n",
-      " [ 20.        20.        29.000004 ... 365.000148 365.000148 365.000148]\n",
-      " [ 20.        20.        29.000004 ... 365.000148 365.000148 365.000148]\n",
-      " [ 20.        20.        29.000004 ... 365.000148 365.000148 365.000202]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.89564752578735 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 1e-05} is: \n",
-      "[[ 13.00004     14.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [ 14.          20.00008      4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [  4.           4.          13.00004    ...  29.00004     29.00004\n",
-      "   29.00004   ]\n",
-      " ...\n",
-      " [ 20.          20.          29.00004    ... 365.00148001 365.00148001\n",
-      "  365.00148   ]\n",
-      " [ 20.          20.          29.00004    ... 365.00148001 365.00148001\n",
-      "  365.00148   ]\n",
-      " [ 20.          20.          29.00004    ... 365.00148    365.00148\n",
-      "  365.00202   ]]\n"
-     ]
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe2ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.520052671432495 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 0.0001} is: \n",
-      "[[ 13.0004      14.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [ 14.          20.0008       4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [  4.           4.          13.0004     ...  29.0004      29.0004\n",
-      "   29.0004    ]\n",
-      " ...\n",
-      " [ 20.          20.          29.0004     ... 365.01480072 365.01480072\n",
-      "  365.0148    ]\n",
-      " [ 20.          20.          29.0004     ... 365.01480072 365.01480072\n",
-      "  365.0148    ]\n",
-      " [ 20.          20.          29.0004     ... 365.0148     365.0148\n",
-      "  365.0202    ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a630>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.7362539768219 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 0.001} is: \n",
-      "[[ 13.004     14.         4.       ...  20.        20.        20.      ]\n",
-      " [ 14.        20.008      4.       ...  20.        20.        20.      ]\n",
-      " [  4.         4.        13.004    ...  29.004     29.004     29.004   ]\n",
-      " ...\n",
-      " [ 20.        20.        29.004    ... 365.148072 365.148072 365.148   ]\n",
-      " [ 20.        20.        29.004    ... 365.148072 365.148072 365.148   ]\n",
-      " [ 20.        20.        29.004    ... 365.148    365.148    365.202   ]]\n"
-     ]
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f8208>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.73691654205322 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 0.01} is: \n",
-      "[[ 13.04    14.       4.     ...  20.      20.      20.    ]\n",
-      " [ 14.      20.08     4.     ...  20.      20.      20.    ]\n",
-      " [  4.       4.      13.04   ...  29.04    29.04    29.04  ]\n",
-      " ...\n",
-      " [ 20.      20.      29.04   ... 366.4872 366.4872 366.48  ]\n",
-      " [ 20.      20.      29.04   ... 366.4872 366.4872 366.48  ]\n",
-      " [ 20.      20.      29.04   ... 366.48   366.48   367.02  ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2466cb70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.62600350379944 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 0.1} is: \n",
-      "[[ 13.4   14.     4.   ...  20.    20.    20.  ]\n",
-      " [ 14.    20.8    4.   ...  20.    20.    20.  ]\n",
-      " [  4.     4.    13.4  ...  29.4   29.4   29.4 ]\n",
-      " ...\n",
-      " [ 20.    20.    29.4  ... 380.52 380.52 379.8 ]\n",
-      " [ 20.    20.    29.4  ... 380.52 380.52 379.8 ]\n",
-      " [ 20.    20.    29.4  ... 379.8  379.8  385.2 ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468c8d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.593005418777466 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 1.0} is: \n",
-      "[[ 17.  14.   4. ...  20.  20.  20.]\n",
-      " [ 14.  28.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.  17. ...  33.  33.  33.]\n",
-      " ...\n",
-      " [ 20.  20.  33. ... 585. 585. 513.]\n",
-      " [ 20.  20.  33. ... 585. 585. 513.]\n",
-      " [ 20.  20.  33. ... 513. 513. 567.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468cfd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.402854681015015 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 10.0} is: \n",
-      "[[5.300e+01 1.400e+01 4.000e+00 ... 2.000e+01 2.000e+01 2.000e+01]\n",
-      " [1.400e+01 1.000e+02 4.000e+00 ... 2.000e+01 2.000e+01 2.000e+01]\n",
-      " [4.000e+00 4.000e+00 5.300e+01 ... 6.900e+01 6.900e+01 6.900e+01]\n",
-      " ...\n",
-      " [2.000e+01 2.000e+01 6.900e+01 ... 9.045e+03 9.045e+03 1.845e+03]\n",
-      " [2.000e+01 2.000e+01 6.900e+01 ... 9.045e+03 9.045e+03 1.845e+03]\n",
-      " [2.000e+01 2.000e+01 6.900e+01 ... 1.845e+03 1.845e+03 2.385e+03]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb689026d8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.69613790512085 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 100.0} is: \n",
-      "[[4.13000e+02 1.40000e+01 4.00000e+00 ... 2.00000e+01 2.00000e+01\n",
-      "  2.00000e+01]\n",
-      " [1.40000e+01 8.20000e+02 4.00000e+00 ... 2.00000e+01 2.00000e+01\n",
-      "  2.00000e+01]\n",
-      " [4.00000e+00 4.00000e+00 4.13000e+02 ... 4.29000e+02 4.29000e+02\n",
-      "  4.29000e+02]\n",
-      " ...\n",
-      " [2.00000e+01 2.00000e+01 4.29000e+02 ... 7.35165e+05 7.35165e+05\n",
-      "  1.51650e+04]\n",
-      " [2.00000e+01 2.00000e+01 4.29000e+02 ... 7.35165e+05 7.35165e+05\n",
-      "  1.51650e+04]\n",
-      " [2.00000e+01 2.00000e+01 4.29000e+02 ... 1.51650e+04 1.51650e+04\n",
-      "  2.05650e+04]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb211f6e10>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 35.21447205543518 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 1000.0} is: \n",
-      "[[4.0130000e+03 1.4000000e+01 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [1.4000000e+01 8.0200000e+03 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [4.0000000e+00 4.0000000e+00 4.0130000e+03 ... 4.0290000e+03\n",
-      "  4.0290000e+03 4.0290000e+03]\n",
-      " ...\n",
-      " [2.0000000e+01 2.0000000e+01 4.0290000e+03 ... 7.2148365e+07\n",
-      "  7.2148365e+07 1.4836500e+05]\n",
-      " [2.0000000e+01 2.0000000e+01 4.0290000e+03 ... 7.2148365e+07\n",
-      "  7.2148365e+07 1.4836500e+05]\n",
-      " [2.0000000e+01 2.0000000e+01 4.0290000e+03 ... 1.4836500e+05\n",
-      "  1.4836500e+05 2.0236500e+05]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb6c1443c8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.99727129936218 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 10000.0} is: \n",
-      "[[4.00130000e+04 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [1.40000000e+01 8.00200000e+04 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.00130000e+04 ... 4.00290000e+04\n",
-      "  4.00290000e+04 4.00290000e+04]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.00290000e+04 ... 7.20148036e+09\n",
-      "  7.20148036e+09 1.48036500e+06]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00290000e+04 ... 7.20148036e+09\n",
-      "  7.20148036e+09 1.48036500e+06]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00290000e+04 ... 1.48036500e+06\n",
-      "  1.48036500e+06 2.02036500e+06]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb246370b8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.714210987091064 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 100000.0} is: \n",
-      "[[4.0001300e+05 1.4000000e+01 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [1.4000000e+01 8.0002000e+05 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [4.0000000e+00 4.0000000e+00 4.0001300e+05 ... 4.0002900e+05\n",
-      "  4.0002900e+05 4.0002900e+05]\n",
-      " ...\n",
-      " [2.0000000e+01 2.0000000e+01 4.0002900e+05 ... 7.2001480e+11\n",
-      "  7.2001480e+11 1.4800365e+07]\n",
-      " [2.0000000e+01 2.0000000e+01 4.0002900e+05 ... 7.2001480e+11\n",
-      "  7.2001480e+11 1.4800365e+07]\n",
-      " [2.0000000e+01 2.0000000e+01 4.0002900e+05 ... 1.4800365e+07\n",
-      "  1.4800365e+07 2.0200365e+07]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f8320>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.71897006034851 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 1000000.0} is: \n",
-      "[[4.00001300e+06 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [1.40000000e+01 8.00002000e+06 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.00001300e+06 ... 4.00002900e+06\n",
-      "  4.00002900e+06 4.00002900e+06]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.00002900e+06 ... 7.20001480e+13\n",
-      "  7.20001480e+13 1.48000365e+08]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00002900e+06 ... 7.20001480e+13\n",
-      "  7.20001480e+13 1.48000365e+08]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00002900e+06 ... 1.48000365e+08\n",
-      "  1.48000365e+08 2.02000365e+08]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb5d7e25c0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.76906633377075 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 10000000.0} is: \n",
-      "[[4.00000130e+07 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [1.40000000e+01 8.00000200e+07 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.00000130e+07 ... 4.00000290e+07\n",
-      "  4.00000290e+07 4.00000290e+07]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000290e+07 ... 7.20000148e+15\n",
-      "  7.20000148e+15 1.48000036e+09]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000290e+07 ... 7.20000148e+15\n",
-      "  7.20000148e+15 1.48000036e+09]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000290e+07 ... 1.48000036e+09\n",
-      "  1.48000036e+09 2.02000036e+09]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1588>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 35.22616124153137 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 100000000.0} is: \n",
-      "[[4.00000013e+08 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [1.40000000e+01 8.00000020e+08 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.00000013e+08 ... 4.00000029e+08\n",
-      "  4.00000029e+08 4.00000029e+08]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000029e+08 ... 7.20000015e+17\n",
-      "  7.20000015e+17 1.48000004e+10]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000029e+08 ... 7.20000015e+17\n",
-      "  7.20000015e+17 1.48000004e+10]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000029e+08 ... 1.48000004e+10\n",
-      "  1.48000004e+10 2.02000004e+10]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe2ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.935295820236206 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 1000000000.0} is: \n",
-      "[[4.00000001e+09 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [1.40000000e+01 8.00000002e+09 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.00000001e+09 ... 4.00000003e+09\n",
-      "  4.00000003e+09 4.00000003e+09]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000003e+09 ... 7.20000001e+19\n",
-      "  7.20000001e+19 1.48000000e+11]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000003e+09 ... 7.20000001e+19\n",
-      "  7.20000001e+19 1.48000000e+11]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000003e+09 ... 1.48000000e+11\n",
-      "  1.48000000e+11 2.02000000e+11]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb689026d8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.634655714035034 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 2.0, 'lmda': 10000000000.0} is: \n",
-      "[[4.00e+10 1.40e+01 4.00e+00 ... 2.00e+01 2.00e+01 2.00e+01]\n",
-      " [1.40e+01 8.00e+10 4.00e+00 ... 2.00e+01 2.00e+01 2.00e+01]\n",
-      " [4.00e+00 4.00e+00 4.00e+10 ... 4.00e+10 4.00e+10 4.00e+10]\n",
-      " ...\n",
-      " [2.00e+01 2.00e+01 4.00e+10 ... 7.20e+21 7.20e+21 1.48e+12]\n",
-      " [2.00e+01 2.00e+01 4.00e+10 ... 7.20e+21 7.20e+21 1.48e+12]\n",
-      " [2.00e+01 2.00e+01 4.00e+10 ... 1.48e+12 1.48e+12 2.02e+12]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAADaVJREFUeJzt3UHMFPd9xvHnqSFEiRLF1Aki2G1diiI5TYvMK/MKWYhQKbWtqpiLsQ8NiqySSLZ6xenFuUSKD9ErRWqMiIpMDrHDxTIHWmLRAwfLSbCEHBw1zUuCZd4XgxOqJAoqyUt+Oey89bDssr93Z3Zn353vR0KzOzs78/vP8j6a+e9/Zh0RAoBB/qTpAgCsDoQFgBTCAkAKYQEghbAAkEJYAEhpPCxsP2T7J7bnbT/TdD2jYvuC7R/ZPmv7TDFvve1Xbf+0mN7ZdJ1V2D5i+4rtc6V5Pdvojm8Un/ubtu9vrvLh9WnzV2wvFJ/1WduPlF77ctHmn9j++2aqHk6jYWH7Dkn/JulhSfdJesL2fU3WNGKfjYitETFTPH9G0qmI2CLpVPF8NXtB0kNd8/q18WFJW4p/ByQ9P6Ya6/aCbm2zJM0Vn/XWiDghScX/7cclfbp4zzeLv4FVoekjiwckzUfEzyLid5JekrSn4ZrGaY+ko8Xjo5IebbCWyiLitKSrXbP7tXGPpG9Hx+uSPmZ743gqrU+fNvezR9JLEXE9In4uaV6dv4FVoemw2CTpndLzi8W8aRSSvmf7DdsHinkbIuJS8fhdSRuaKW2k+rVx2j/7p4vTqyOl08tV3eamw6JNHoyI+9U5/H7K9s7yi9EZdz/VY+/b0MbC85I2S9oq6ZKkrzdbTj2aDosFSfeUnt9dzJs6EbFQTK9Ielmdw8/Ly4fexfRKcxWOTL82Tu1nHxGXI+JGRPxB0rf0/qnGqm5z02HxQ0lbbN9r+wPqdP4cb7im2tn+sO2PLD+W9DlJ59Rp6/5isf2SXmmmwpHq18bjkj5ffCsyK+lXpdOVVa2r72WvOp+11Gnz47bX2b5Xnc7dH4y7vmGtaXLjEbFk+2lJJyXdIelIRLzVZE0jskHSy7alzj7/TkT8p+0fSjpm+0lJb0t6rMEaK7P9oqRdku6yfVHSs5K+pt5tPCHpEXU6+a5J+sLYC65Bnzbvsr1VnVOuC5K+KEkR8ZbtY5J+LGlJ0lMRcaOJuodhLlEHkNH0aQiAVYKwAJBCWABIISwApBAWAFJGFhYrvZq0NAS6NWhzO0xLm0cSFkNeTToVO3SFaHM7TEWbR3Vk0farSYGpM6oRnL2urtveb+EPeF18UB/SR72+VSPEaHM7THKb/0+/1e/iujPLNjbcuziPOyB1duaD799MCMCYfD9OpZcd1WnIwKvrIuJwRMxExMxarRtRGQDqMqqwaMXVpECbjOQ0pEVXkwKtMbI+i+ImpSdGtX4A48UITgAphAWAFMICQAphASCFsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAkAKYQEghbAAkEJYAEghLACkEBYAUggLACmEBYAUwgJACmEBIIWwAJBCWABIISwApBAWAFIICwAphAWAFMICQAphASCFsOhybe92Xdu7vZHtTrryvilPm6y917av7d2u+blZzc/N3vT6/Nxs6v1Va8iss7z/etU17LZHibAAkOKIaLoGfdTrY7v/rukygNb5fpzSr+OqM8tyZHEbS7u3tXr7w1ravW3V1o7+OLIAWowjCwC1IywApBAWAFIICwAphAWAFMICQAphASCFsACQQljUYJIvAhtUW9MXgvUyCfVkLu6qcgFYE6rWywhOoMUYwQmgdoQFgBTCAkAKYQEghbAAkEJYAEghLACkEBYAUggLAClrqrzZ9gVJv5F0Q9JSRMzYXi/pu5L+QtIFSY9FxP9WKxNA0+o4svhsRGyNiJni+TOSTkXEFkmniucAVrlRnIbskXS0eHxU0qMj2AaAMasaFiHpe7bfsH2gmLchIi4Vj9+VtKHiNgBMgEp9FpIejIgF25+Q9Krt/y6/GBFhu+dlrUW4HJCkD+pDFcsAMGqVjiwiYqGYXpH0sqQHJF22vVGSiumVPu89HBEzETGzVuuqlAFgDIYOC9sftv2R5ceSPifpnKTjkvYXi+2X9ErVIseJX1Hvj19Rz9Uwrb+iPvTNb2z/pTpHE1LndOY7EfFV238q6ZikP5P0tjpfnV693bq4+Q3QjJXc/GboPouI+Jmkv+0x/5eS+MsHpgwjOAGkEBYAUgiL21java3V2x/W0u5tq7Z29MfdvYEW4+7eAGpHWABIISwApBAWAFIICwAphAWAFMICQAphASCFsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAkAKYVGDSb4z96Damr47dy+TUE/mjttV7srdhKr1cvMboMW4+Q2A2hEWAFIICwAphAWAFMICQAphASCFsKjBJIwL6IdxFsNhnMWtCAsAKQzKAlqMQVkAakdYAEghLACkEBYAUggLACmEBYAUwgJACmEBIIWw6NLU8OdJGOI8SHnflKdN1t5r29f2btf83Kzm52Zver3XcOc6au9eR2ad5f1XZRj2OPc9YQEgheHeWLGFgzu06bnXmi5jqiwc3CFJK96vVT8LhntXwGlIf8v7ZtNzr3Eacpt1DHMasum514b6o7/zf26s+D3D4sgCaDGOLCrgyKI/OjhzNdDBCaDVOA0BWozTEAC1IywApBAWt7G0e1urtz+spd3bVm3t6I+wAJBCByfQYnRwAqjdwLCwfcT2FdvnSvPW237V9k+L6Z3FfNv+hu1522/avn+UxQMYn8yRxQuSHuqa94ykUxGxRdKp4rkkPSxpS/HvgKTn6ykTQNMGhkVEnJZ0tWv2HklHi8dHJT1amv/t6Hhd0sdsb6yrWADNGbbPYkNEXCoevytpQ/F4k6R3SstdLOYBWOUqd3BG5+uUFX+lYvuA7TO2z/xe16uWAWDEhg2Ly8unF8X0SjF/QdI9peXuLubdIiIOR8RMRMys1bohywAwLsOGxXFJ+4vH+yW9Upr/+eJbkVlJvyqdrgBYxdYMWsD2i5J2SbrL9kVJz0r6mqRjtp+U9Lakx4rFT0h6RNK8pGuSvjCCmgE0YGBYRMQTfV66Zchl0X/xVNWiAEweRnACSCEsAKQQFgBSCIsaTPLNdgfV1vQNd3uZhHoyN9GtcqPdJlStl0vUgRbjEnUAtSMsAKQQFgBSCAsAKYQFgBTCAkAKYQEghbAAkEJYAEghLLo0Nfx5EoY4D1LeN+Vpk7X32va1vds1Pzer+bnZm17vNdy5jtq715FZZ3n/VRmGPc59z3BvoMUY7g2gdoQFgBTCAkAKYdGFDs7+6ODM1TCtHZyERZfFndbizlR/T+3bnXTlfVOeNll7r20v7rTO7zuk8/sO3fT6+X2HUu+vWkNmneX916uuYbc9SoQFgJSBPwXQNp883cxXyU1tdyXKNS4/brruXtv/5OnQZn3pltc3f/dL+iu9PvD9VWvIrLO8/zbr1rqG3fYoMc4CaDHGWQCoHWHRZbkXvYntTrryvilPm6y917bn52Z1cvGsTi6even1k4tnU++vWsNK7gy+XGtd2x4lTkOAFuM0BEDtCAsAKYQFgBTCogvDvftjuHeuhmkd7k0HJ9BidHACqB1hASCFsACQQlgASCEsajDJQ7UH1db0cO1eJqGezBDsKsO0m1C1Xr4NAVqMb0MA1I6wAJBCWABIISwApBAWAFIICwAphAWAFMKiBpMwiKgfBmUNh0FZt2JQFtBiDMqqgJvf9MfNb3I1cPObEeLIAmgGRxYAakdYAEghLLrQZ9EffRa5GlrbZ2H7iKR/kHQlIv66mPcVSf8s6b1isX+NiBPFa1+W9KSkG5L+JSJODiqCPgugGXX3Wbwg6aEe8+ciYmvxbzko7pP0uKRPF+/5pu07cmUDmGQDwyIiTku6mlzfHkkvRcT1iPi5pHlJD1SoD8CEqNJn8bTtN20fsX1nMW+TpHdKy1ws5gFY5YYNi+clbZa0VdIlSV9f6QpsH7B9xvaZ3+v6kGUAGJehwiIiLkfEjYj4g6Rv6f1TjQVJ95QWvbuY12sdhyNiJiJm1mrdMGUAGKOhwsL2xtLTvZLOFY+PS3rc9jrb90raIukH1UoEMAnWDFrA9ouSdkm6y/ZFSc9K2mV7q6SQdEHSFyUpIt6yfUzSjyUtSXoqIm6MpnQA45T5NuSJiNgYEWsj4u6I+PeI+KeI+ExE/E1E/GNEXCot/9WI2BwRn4qI/xht+fVjUFZ/DMrK1dDaQVnjwKAsoBlcSFYBRxb9cWSRq2FajywIiy6LO63FnamgrX27k668b8rTJmvvte3Fndb5fYd0ft+hm14/v+9Q6v1Va8iss7z/etU17LZHidMQrNjCwR3a9NxrTZcxVRYO7pCkFe/Xqp8FpyEAaseRBdBiHFkAqB1hASCFsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAlhllnZv09LubWPfLmEBIGXgnbIATJY1//VGI9vlyKIL97Pob3nfLBzcwf0sbrOOYe5nsXBwx/9feboS7x3/1IrfMywuJANajAvJANSOsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAkAKYQEghbCoQZWfnxu1QbUtD4ueJJNQz8nFs7UsM0mq1stwb6DFGO4NoHaEBYAUwgJACmEBIGUiOjhtvyfpt5J+0XQtY3aXaHMbTHKb/zwiPp5ZcCLCQpJsn4mImabrGCfa3A7T0mZOQwCkEBYAUiYpLA43XUADaHM7TEWbJ6bPAsBkm6QjCwATjLAAkEJYAEghLACkEBYAUv4I7XczZv1yHfoAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256f2940>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.149678707122803 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 1e-10} is: \n",
-      "[[8.00e-10 8.00e-10 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [8.00e-10 1.20e-09 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [0.00e+00 0.00e+00 8.00e-10 ... 8.00e-10 8.00e-10 8.00e-10]\n",
-      " ...\n",
-      " [0.00e+00 0.00e+00 8.00e-10 ... 2.64e-08 2.64e-08 2.64e-08]\n",
-      " [0.00e+00 0.00e+00 8.00e-10 ... 2.64e-08 2.64e-08 2.64e-08]\n",
-      " [0.00e+00 0.00e+00 8.00e-10 ... 2.64e-08 2.64e-08 2.64e-08]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1fd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.24059534072876 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 1e-09} is: \n",
-      "[[8.00e-09 8.00e-09 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [8.00e-09 1.20e-08 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [0.00e+00 0.00e+00 8.00e-09 ... 8.00e-09 8.00e-09 8.00e-09]\n",
-      " ...\n",
-      " [0.00e+00 0.00e+00 8.00e-09 ... 2.64e-07 2.64e-07 2.64e-07]\n",
-      " [0.00e+00 0.00e+00 8.00e-09 ... 2.64e-07 2.64e-07 2.64e-07]\n",
-      " [0.00e+00 0.00e+00 8.00e-09 ... 2.64e-07 2.64e-07 2.64e-07]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f8358>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.805413007736206 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 1e-08} is: \n",
-      "[[8.00e-08 8.00e-08 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [8.00e-08 1.20e-07 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [0.00e+00 0.00e+00 8.00e-08 ... 8.00e-08 8.00e-08 8.00e-08]\n",
-      " ...\n",
-      " [0.00e+00 0.00e+00 8.00e-08 ... 2.64e-06 2.64e-06 2.64e-06]\n",
-      " [0.00e+00 0.00e+00 8.00e-08 ... 2.64e-06 2.64e-06 2.64e-06]\n",
-      " [0.00e+00 0.00e+00 8.00e-08 ... 2.64e-06 2.64e-06 2.64e-06]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe2ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.43400478363037 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 1e-07} is: \n",
-      "[[8.00e-07 8.00e-07 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [8.00e-07 1.20e-06 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [0.00e+00 0.00e+00 8.00e-07 ... 8.00e-07 8.00e-07 8.00e-07]\n",
-      " ...\n",
-      " [0.00e+00 0.00e+00 8.00e-07 ... 2.64e-05 2.64e-05 2.64e-05]\n",
-      " [0.00e+00 0.00e+00 8.00e-07 ... 2.64e-05 2.64e-05 2.64e-05]\n",
-      " [0.00e+00 0.00e+00 8.00e-07 ... 2.64e-05 2.64e-05 2.64e-05]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1f98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.632941246032715 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 1e-06} is: \n",
-      "[[8.00e-06 8.00e-06 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [8.00e-06 1.20e-05 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [0.00e+00 0.00e+00 8.00e-06 ... 8.00e-06 8.00e-06 8.00e-06]\n",
-      " ...\n",
-      " [0.00e+00 0.00e+00 8.00e-06 ... 2.64e-04 2.64e-04 2.64e-04]\n",
-      " [0.00e+00 0.00e+00 8.00e-06 ... 2.64e-04 2.64e-04 2.64e-04]\n",
-      " [0.00e+00 0.00e+00 8.00e-06 ... 2.64e-04 2.64e-04 2.64e-04]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1f98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.6206476688385 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 1e-05} is: \n",
-      "[[8.00e-05 8.00e-05 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [8.00e-05 1.20e-04 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [0.00e+00 0.00e+00 8.00e-05 ... 8.00e-05 8.00e-05 8.00e-05]\n",
-      " ...\n",
-      " [0.00e+00 0.00e+00 8.00e-05 ... 2.64e-03 2.64e-03 2.64e-03]\n",
-      " [0.00e+00 0.00e+00 8.00e-05 ... 2.64e-03 2.64e-03 2.64e-03]\n",
-      " [0.00e+00 0.00e+00 8.00e-05 ... 2.64e-03 2.64e-03 2.64e-03]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468c8d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.250969409942627 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 0.0001} is: \n",
-      "[[0.0008 0.0008 0.     ... 0.     0.     0.    ]\n",
-      " [0.0008 0.0012 0.     ... 0.     0.     0.    ]\n",
-      " [0.     0.     0.0008 ... 0.0008 0.0008 0.0008]\n",
-      " ...\n",
-      " [0.     0.     0.0008 ... 0.0264 0.0264 0.0264]\n",
-      " [0.     0.     0.0008 ... 0.0264 0.0264 0.0264]\n",
-      " [0.     0.     0.0008 ... 0.0264 0.0264 0.0264]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688e59b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.387526512145996 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 0.001} is: \n",
-      "[[0.008      0.008      0.         ... 0.         0.         0.        ]\n",
-      " [0.008      0.01200001 0.         ... 0.         0.         0.        ]\n",
-      " [0.         0.         0.008      ... 0.008      0.008      0.008     ]\n",
-      " ...\n",
-      " [0.         0.         0.008      ... 0.26400015 0.26400015 0.26400015]\n",
-      " [0.         0.         0.008      ... 0.26400015 0.26400015 0.26400015]\n",
-      " [0.         0.         0.008      ... 0.26400015 0.26400015 0.2640002 ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256f2160>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.552900314331055 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 0.01} is: \n",
-      "[[0.080004   0.08       0.         ... 0.         0.         0.        ]\n",
-      " [0.08       0.120008   0.         ... 0.         0.         0.        ]\n",
-      " [0.         0.         0.080004   ... 0.080004   0.080004   0.080004  ]\n",
-      " ...\n",
-      " [0.         0.         0.080004   ... 2.64014801 2.64014801 2.640148  ]\n",
-      " [0.         0.         0.080004   ... 2.64014801 2.64014801 2.640148  ]\n",
-      " [0.         0.         0.080004   ... 2.640148   2.640148   2.640202  ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f81d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.285762071609497 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 0.1} is: \n",
-      "[[ 0.804    0.8      0.      ...  0.       0.       0.     ]\n",
-      " [ 0.8      1.208    0.      ...  0.       0.       0.     ]\n",
-      " [ 0.       0.       0.804   ...  0.804    0.804    0.804  ]\n",
-      " ...\n",
-      " [ 0.       0.       0.804   ... 26.54872 26.54872 26.548  ]\n",
-      " [ 0.       0.       0.804   ... 26.54872 26.54872 26.548  ]\n",
-      " [ 0.       0.       0.804   ... 26.548   26.548   26.602  ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb5d7e25c0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.075997591018677 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 1.0} is: \n",
-      "[[ 12.   8.   0. ...   0.   0.   0.]\n",
-      " [  8.  20.   0. ...   0.   0.   0.]\n",
-      " [  0.   0.  12. ...  12.  12.  12.]\n",
-      " ...\n",
-      " [  0.   0.  12. ... 484. 484. 412.]\n",
-      " [  0.   0.  12. ... 484. 484. 412.]\n",
-      " [  0.   0.  12. ... 412. 412. 466.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24637da0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.010215520858765 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 10.0} is: \n",
-      "[[4.08000e+03 8.00000e+01 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
-      "  0.00000e+00]\n",
-      " [8.00000e+01 8.12000e+03 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
-      "  0.00000e+00]\n",
-      " [0.00000e+00 0.00000e+00 4.08000e+03 ... 4.08000e+03 4.08000e+03\n",
-      "  4.08000e+03]\n",
-      " ...\n",
-      " [0.00000e+00 0.00000e+00 4.08000e+03 ... 7.35064e+06 7.35064e+06\n",
-      "  1.50640e+05]\n",
-      " [0.00000e+00 0.00000e+00 4.08000e+03 ... 7.35064e+06 7.35064e+06\n",
-      "  1.50640e+05]\n",
-      " [0.00000e+00 0.00000e+00 4.08000e+03 ... 1.50640e+05 1.50640e+05\n",
-      "  2.04640e+05]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.062121629714966 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 100.0} is: \n",
-      "[[4.00080000e+06 8.00000000e+02 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [8.00000000e+02 8.00120000e+06 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00080000e+06 ... 4.00080000e+06\n",
-      "  4.00080000e+06 4.00080000e+06]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 4.00080000e+06 ... 7.20148026e+11\n",
-      "  7.20148026e+11 1.48026400e+08]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00080000e+06 ... 7.20148026e+11\n",
-      "  7.20148026e+11 1.48026400e+08]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00080000e+06 ... 1.48026400e+08\n",
-      "  1.48026400e+08 2.02026400e+08]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAADeZJREFUeJzt3V+MVOUZx/HfU0GMRqOUliDa1lJiov1DZAMbogS3iVXTFLgRvKjEmKIJprdgb/TGRC9kE5MqwZSIF/7hxsgFLRp6YRNjFRNi0dQ6KEZ2kbWlsY1YdPHpxZzFYXaGeXbOmXnP7Pl+EjIz75yZ85wz7C/nvPOed8zdBQCdfCt1AQAGA2EBIISwABBCWAAIISwAhBAWAEKSh4WZ3Wpm75lZzcy2pa6nV8zsqJn9zcwOmdnBrG2+mb1iZu9nt1ekrjMPM9tlZhNmdrihreU2Wt3j2ef+tpndkK7y7rXZ5ofMbCz7rA+Z2e0Nzz2QbfN7ZvaLNFV3J2lYmNkFkn4v6TZJ10m608yuS1lTj93s7svcfSh7vE3SAXdfKulA9niQPS3p1qa2dtt4m6Sl2b/Nkp7sU41Fe1rTt1mSRrPPepm775Ok7P/2RknXZ695IvsbGAipjyxWSKq5+wfu/qWk5yWtTVxTP62VtDu7v1vSuoS15Obur0o62dTcbhvXSnrG616XdLmZLepPpcVps83trJX0vLufdvcPJdVU/xsYCKnDYrGkjxseH8vaZiOX9LKZvWVmm7O2he5+PLv/iaSFaUrrqXbbONs/+/uz06tdDaeXA73NqcOiSm509xtUP/zeYmarG5/0+rj7WT32vgrbmHlS0hJJyyQdl/RY2nKKkTosxiRd3fD4qqxt1nH3sex2QtKLqh9+npg69M5uJ9JV2DPttnHWfvbufsLdz7j715Ke0jenGgO9zanD4k1JS83sGjO7UPXOn72JayqcmV1iZpdO3Zd0i6TDqm/rpmyxTZJeSlNhT7Xbxr2S7sq+FRmW9FnD6cpAa+p7Wa/6Zy3Vt3mjmc0zs2tU79x9o9/1dWtOypW7+6SZ3S9pv6QLJO1y93dS1tQjCyW9aGZSfZ8/6+5/MrM3Je0xs3skfSTpjoQ15mZmz0laI2mBmR2T9KCkR9R6G/dJul31Tr5Tku7ue8EFaLPNa8xsmeqnXEcl3StJ7v6Ome2R9K6kSUlb3P1Mirq7YVyiDiAi9WkIgAFBWAAIISwAhBAWAEIICwAhPQuLmV5N2jAEujLY5mqYLdvck7Do8mrSWbFDZ4htroZZsc29OrKo+tWkwKzTqxGcra6uW9lu4Qttnl+ki3WZza/UCDG2uRrKvM3/0+f60k9bZNlkw72z87jNUn1n3vjNZEIA+uSvfiC8bK9OQzpeXefuO919yN2H5mpej8oAUJRehUUlriYFqqQnpyEVupoUqIye9Vlkk5Tu69X7A+gvRnACCCEsAIQQFgBCCAsAIYQFgBDCAkAIYQEghLAAEEJYAAghLACEEBYAQggLACGEBYAQwgJACGEBIISwABBCWAAIISwAhBAWAEIICwAhhAWAEMICQAhhASCEsAAQQlgACCEsAIQQFgBCCAsAIYRFky/WrdAX61YkWW/ZNe6bU+tXTmtLYaqO5rba9mHVtg+f83xt+3Do9XlriLzn1DJTtRa17l4iLACEmLunrkGX2XxfaT9PXQZQOX/1A/qPn7TIshxZnMfkyPJKr79bkyPLB7Z2tMeRBVBhHFkAKBxhASCEsAAQQlgACCEsAIQQFgBCCAsAIYQFgBDCogBlvgisU22pLwRrpQz1RC7uynMBWAp562UEJ1BhjOAEUDjCAkAIYQEghLAAEEJYAAghLACEEBYAQggLACGEBYCQOXlebGZHJf1X0hlJk+4+ZGbzJb0g6QeSjkq6w93/na9MAKkVcWRxs7svc/eh7PE2SQfcfamkA9ljAAOuF6chayXtzu7vlrSuB+sA0Gd5w8IlvWxmb5nZ5qxtobsfz+5/ImlhznUAKIFcfRaSbnT3MTP7rqRXzOzvjU+6u5tZy8tas3DZLEkX6eKcZQDotVxHFu4+lt1OSHpR0gpJJ8xskSRltxNtXrvT3YfcfWiu5uUpA0AfdB0WZnaJmV06dV/SLZIOS9oraVO22CZJL+Utsp9STQbTz1/D7tap9SvP+fXv5rZUNbVq41fUi9f15Ddm9kPVjyak+unMs+7+sJl9W9IeSd+T9JHqX52ePN97MfkNkMZMJr/pus/C3T+Q9LMW7f+SxF8+MMswghNACGEBIISwOI/JkeWVXn+3JkeWD2ztaI/ZvYEKY3ZvAIUjLACEEBYAQggLACGEBYAQwgJACGEBIISwABBCWAAIISwAhBAWAEIICwAhhAWAEMICQAhhASCEsChAitnAozrVlmo28/Mpw0znkRm388zKnULeepn8BqgwJr8BUDjCAkAIYQEghLAAEEJYAAghLACEEBYFKNs4hUadakv9K+itlGF/Ms5iOsICQAiDsoAKY1AWgMIRFgBCCAsAIYQFgBDCAkAIYQEghLAAEEJYAAghLJqkmmaubEOuW2kcGt54m7L2Vus+tX6latuHVds+fM7zrYY7F1F783tE3rNx/+UZht3PfU9YAAhhuDdmbGzrKi1+9LXUZcwqY1tXSdKM92vez4Lh3jmkOqwepNOQxY++Vv7TkNFh1UabTkNGS3oaMjqsxY++1tUf/RX/ODPj13SLIwugwjiyyIEOzvbo4IzVQAcngErjNASoME5DABSOsAAQQlicx+TI8kqvv1uTI8sHtna0R1gACKGDE6gwOjgBFK5jWJjZLjObMLPDDW3zzewVM3s/u70iazcze9zMamb2tpnd0MviAfRP5MjiaUm3NrVtk3TA3ZdKOpA9lqTbJC3N/m2W9GQxZQJIrWNYuPurkk42Na+VtDu7v1vSuob2Z7zudUmXm9mioooFkE63fRYL3f14dv8TSQuz+4slfdyw3LGsDcCAy93B6fWvU2b8lYqZbTazg2Z28CudzlsGgB7rNixOTJ1eZLcTWfuYpKsblrsqa5vG3Xe6+5C7D83VvC7LANAv3YbFXkmbsvubJL3U0H5X9q3IsKTPGk5XAAywOZ0WMLPnJK2RtMDMjkl6UNIjkvaY2T2SPpJ0R7b4Pkm3S6pJOiXp7h7UDCCBjmHh7ne2eWrakMus/2JL3qIAlA8jOAGEEBYAQggLACGERQFSTPAb1WlC11QTFJ9PGSYvjkyim2ei3RRa/RTCTHCJOlBhXKIOoHCEBYAQwgJACGEBIISwABBCWAAIISwAhBAWAEIICwAhhEWTU+tXJhluXIYhzp007pvG25S1t1r3qfUrVRsdVm10+JznWw3PLqL25veIvGfj/sszDLuf+57h3kCFMdwbQOEICwAhhAWAEMKiCR2c7Q18B2eLjkQ6OOMIiybjN5nGbwr19xS+3rJr3Dfjq21aW5KaVk9f9/hq05ENO3Rkw45znj+yYUfo9XlriLzn2f2X1VrUunuJsAAQ0vGnAKrmyr+k+So51XpnorHGK1/1aW0pTNXR3LZE9017fskL9+lHer3j6/PWEHnPs/svq7W5rm7X3UuMswAqjHEWAApHWDSpbR9OMmvzIMwU3bhvpnrwU+2vxpqmtY0Oa//4Ie0fP3TONw37xw+1XDZ3DU3vEXnPs/svq7WodfcSpyFAhXEaAqBwhAWAEMICQAhh0YTh3u0x3DtWw2wd7k0HJ1BhdHACKBxhASCEsAAQQlgACCEsClDmodqdaks9XLuVMtQTGYKdZ5h2Cnnr5dsQoML4NgRA4QgLACGEBYAQwgJACGEBIISwABBCWAAIISwKUIZBRO0wKKs7DMqajkFZQIUxKCsHJr9pj8lvYjUw+U0PcWQBpMGRBYDCERYAQgiLJvRZtEefRayGyvZZmNkuSb+UNOHuP87aHpL0G0mfZov9zt33Zc89IOkeSWck/dbd93cqgj4LII2i+yyelnRri/ZRd1+W/ZsKiuskbZR0ffaaJ8zsgljZAMqsY1i4+6uSTgbfb62k5939tLt/KKkmaUWO+gCURJ4+i/vN7G0z22VmV2RtiyV93LDMsawNwIDrNiyelLRE0jJJxyU9NtM3MLPNZnbQzA5+pdNdlgGgX7oKC3c/4e5n3P1rSU/pm1ONMUlXNyx6VdbW6j12uvuQuw/N1bxuygDQR12FhZktani4XtLh7P5eSRvNbJ6ZXSNpqaQ38pUIoAzmdFrAzJ6TtEbSAjM7JulBSWvMbJkkl3RU0r2S5O7vmNkeSe9KmpS0xd3P9KZ0AP0U+TbkTndf5O5z3f0qd/+Du//a3X/i7j9191+5+/GG5R929yXufq27/7G35RePQVntMSgrVkNlB2X1A4OygDS4kCwHjiza48giVsNsPbIgLJqM32QavykUtIWvt+wa9834apvWlqSm1dPXPb7adGTDDh3ZsOOc549s2BF6fd4aIu95dv9ltRa17l7iNAQzNrZ1lRY/+lrqMmaVsa2rJGnG+zXvZ8FpCIDCcWQBVBhHFgAKR1gACCEsAIQQFgBCCAsAIYQFgBDCAkAIYQEghLAABszkyHJNjizv+3oJCwAhHWfKAlAuc/78VpL1cmTRhPks2pvaN2NbVzGfxXneo5v5LMa2rjp75elMfLr32hm/pltcSAZUGBeSASgcYQEghLAAEEJYAAghLACEEBYAQggLACGEBYAQwgJACGFRgNr27n9+rtc61VbbPly6+vP8nF9R9o8fKmSZMslbL8O9gQpjuDeAwhEWAEIICwAhhAWAkFJ0cJrZp5I+l/TP1LX02QKxzVVQ5m3+vrt/J7JgKcJCkszsoLsPpa6jn9jmapgt28xpCIAQwgJASJnCYmfqAhJgm6thVmxzafosAJRbmY4sAJQYYQEghLAAEEJYAAghLACE/B/atTMOrx3OqQAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.070118188858032 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 1000.0} is: \n",
-      "[[4.00000800e+09 8.00000000e+03 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [8.00000000e+03 8.00001200e+09 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000800e+09 ... 4.00000800e+09\n",
-      "  4.00000800e+09 4.00000800e+09]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000800e+09 ... 7.20001480e+16\n",
-      "  7.20001480e+16 1.48000264e+11]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000800e+09 ... 7.20001480e+16\n",
-      "  7.20001480e+16 1.48000264e+11]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000800e+09 ... 1.48000264e+11\n",
-      "  1.48000264e+11 2.02000264e+11]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256f21d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.060213327407837 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 10000.0} is: \n",
-      "[[4.00000008e+12 8.00000000e+04 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [8.00000000e+04 8.00000012e+12 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000008e+12 ... 4.00000008e+12\n",
-      "  4.00000008e+12 4.00000008e+12]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000008e+12 ... 7.20000015e+21\n",
-      "  7.20000015e+21 1.48000003e+14]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000008e+12 ... 7.20000015e+21\n",
-      "  7.20000015e+21 1.48000003e+14]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000008e+12 ... 1.48000003e+14\n",
-      "  1.48000003e+14 2.02000003e+14]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.099493503570557 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 100000.0} is: \n",
-      "[[4.00e+15 8.00e+05 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [8.00e+05 8.00e+15 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [0.00e+00 0.00e+00 4.00e+15 ... 4.00e+15 4.00e+15 4.00e+15]\n",
-      " ...\n",
-      " [0.00e+00 0.00e+00 4.00e+15 ... 7.20e+26 7.20e+26 1.48e+17]\n",
-      " [0.00e+00 0.00e+00 4.00e+15 ... 7.20e+26 7.20e+26 1.48e+17]\n",
-      " [0.00e+00 0.00e+00 4.00e+15 ... 1.48e+17 1.48e+17 2.02e+17]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f8358>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.103667974472046 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 1000000.0} is: \n",
-      "[[4.00e+18 8.00e+06 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [8.00e+06 8.00e+18 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [0.00e+00 0.00e+00 4.00e+18 ... 4.00e+18 4.00e+18 4.00e+18]\n",
-      " ...\n",
-      " [0.00e+00 0.00e+00 4.00e+18 ... 7.20e+31 7.20e+31 1.48e+20]\n",
-      " [0.00e+00 0.00e+00 4.00e+18 ... 7.20e+31 7.20e+31 1.48e+20]\n",
-      " [0.00e+00 0.00e+00 4.00e+18 ... 1.48e+20 1.48e+20 2.02e+20]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb5d7e25c0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.023816108703613 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 10000000.0} is: \n",
-      "[[4.00e+21 8.00e+07 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [8.00e+07 8.00e+21 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [0.00e+00 0.00e+00 4.00e+21 ... 4.00e+21 4.00e+21 4.00e+21]\n",
-      " ...\n",
-      " [0.00e+00 0.00e+00 4.00e+21 ... 7.20e+36 7.20e+36 1.48e+23]\n",
-      " [0.00e+00 0.00e+00 4.00e+21 ... 7.20e+36 7.20e+36 1.48e+23]\n",
-      " [0.00e+00 0.00e+00 4.00e+21 ... 1.48e+23 1.48e+23 2.02e+23]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb689026d8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.056624174118042 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 100000000.0} is: \n",
-      "[[4.00e+24 8.00e+08 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [8.00e+08 8.00e+24 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [0.00e+00 0.00e+00 4.00e+24 ... 4.00e+24 4.00e+24 4.00e+24]\n",
-      " ...\n",
-      " [0.00e+00 0.00e+00 4.00e+24 ... 7.20e+41 7.20e+41 1.48e+26]\n",
-      " [0.00e+00 0.00e+00 4.00e+24 ... 7.20e+41 7.20e+41 1.48e+26]\n",
-      " [0.00e+00 0.00e+00 4.00e+24 ... 1.48e+26 1.48e+26 2.02e+26]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe2ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.005533933639526 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 1000000000.0} is: \n",
-      "[[4.00e+27 8.00e+09 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [8.00e+09 8.00e+27 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [0.00e+00 0.00e+00 4.00e+27 ... 4.00e+27 4.00e+27 4.00e+27]\n",
-      " ...\n",
-      " [0.00e+00 0.00e+00 4.00e+27 ... 7.20e+46 7.20e+46 1.48e+29]\n",
-      " [0.00e+00 0.00e+00 4.00e+27 ... 7.20e+46 7.20e+46 1.48e+29]\n",
-      " [0.00e+00 0.00e+00 4.00e+27 ... 1.48e+29 1.48e+29 2.02e+29]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAADaVJREFUeJzt3UHMFPd9xvHnqSFEiRLF1Aki2G1diiI5TYvMK/MKWYhQKbWtqpiLsQ8NiqySSLZ6xenFuUSKD9ErRWqMiIpMDrHDxTIHWmLRAwfLSbCEHBw1zUuCZd4XgxOqJAoqyUt+Oey89bDssr93Z3Zn353vR0KzOzs78/vP8j6a+e9/Zh0RAoBB/qTpAgCsDoQFgBTCAkAKYQEghbAAkEJYAEhpPCxsP2T7J7bnbT/TdD2jYvuC7R/ZPmv7TDFvve1Xbf+0mN7ZdJ1V2D5i+4rtc6V5Pdvojm8Un/ubtu9vrvLh9WnzV2wvFJ/1WduPlF77ctHmn9j++2aqHk6jYWH7Dkn/JulhSfdJesL2fU3WNGKfjYitETFTPH9G0qmI2CLpVPF8NXtB0kNd8/q18WFJW4p/ByQ9P6Ya6/aCbm2zJM0Vn/XWiDghScX/7cclfbp4zzeLv4FVoekjiwckzUfEzyLid5JekrSn4ZrGaY+ko8Xjo5IebbCWyiLitKSrXbP7tXGPpG9Hx+uSPmZ743gqrU+fNvezR9JLEXE9In4uaV6dv4FVoemw2CTpndLzi8W8aRSSvmf7DdsHinkbIuJS8fhdSRuaKW2k+rVx2j/7p4vTqyOl08tV3eamw6JNHoyI+9U5/H7K9s7yi9EZdz/VY+/b0MbC85I2S9oq6ZKkrzdbTj2aDosFSfeUnt9dzJs6EbFQTK9Ielmdw8/Ly4fexfRKcxWOTL82Tu1nHxGXI+JGRPxB0rf0/qnGqm5z02HxQ0lbbN9r+wPqdP4cb7im2tn+sO2PLD+W9DlJ59Rp6/5isf2SXmmmwpHq18bjkj5ffCsyK+lXpdOVVa2r72WvOp+11Gnz47bX2b5Xnc7dH4y7vmGtaXLjEbFk+2lJJyXdIelIRLzVZE0jskHSy7alzj7/TkT8p+0fSjpm+0lJb0t6rMEaK7P9oqRdku6yfVHSs5K+pt5tPCHpEXU6+a5J+sLYC65Bnzbvsr1VnVOuC5K+KEkR8ZbtY5J+LGlJ0lMRcaOJuodhLlEHkNH0aQiAVYKwAJBCWABIISwApBAWAFJGFhYrvZq0NAS6NWhzO0xLm0cSFkNeTToVO3SFaHM7TEWbR3Vk0farSYGpM6oRnL2urtveb+EPeF18UB/SR72+VSPEaHM7THKb/0+/1e/iujPLNjbcuziPOyB1duaD799MCMCYfD9OpZcd1WnIwKvrIuJwRMxExMxarRtRGQDqMqqwaMXVpECbjOQ0pEVXkwKtMbI+i+ImpSdGtX4A48UITgAphAWAFMICQAphASCFsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAkAKYQEghbAAkEJYAEghLACkEBYAUggLACmEBYAUwgJACmEBIIWwAJBCWABIISwApBAWAFIICwAphAWAFMICQAphASCFsOhybe92Xdu7vZHtTrryvilPm6y917av7d2u+blZzc/N3vT6/Nxs6v1Va8iss7z/etU17LZHibAAkOKIaLoGfdTrY7v/rukygNb5fpzSr+OqM8tyZHEbS7u3tXr7w1ravW3V1o7+OLIAWowjCwC1IywApBAWAFIICwAphAWAFMICQAphASCFsACQQljUYJIvAhtUW9MXgvUyCfVkLu6qcgFYE6rWywhOoMUYwQmgdoQFgBTCAkAKYQEghbAAkEJYAEghLACkEBYAUggLAClrqrzZ9gVJv5F0Q9JSRMzYXi/pu5L+QtIFSY9FxP9WKxNA0+o4svhsRGyNiJni+TOSTkXEFkmniucAVrlRnIbskXS0eHxU0qMj2AaAMasaFiHpe7bfsH2gmLchIi4Vj9+VtKHiNgBMgEp9FpIejIgF25+Q9Krt/y6/GBFhu+dlrUW4HJCkD+pDFcsAMGqVjiwiYqGYXpH0sqQHJF22vVGSiumVPu89HBEzETGzVuuqlAFgDIYOC9sftv2R5ceSPifpnKTjkvYXi+2X9ErVIseJX1Hvj19Rz9Uwrb+iPvTNb2z/pTpHE1LndOY7EfFV238q6ZikP5P0tjpfnV693bq4+Q3QjJXc/GboPouI+Jmkv+0x/5eS+MsHpgwjOAGkEBYAUgiL21java3V2x/W0u5tq7Z29MfdvYEW4+7eAGpHWABIISwApBAWAFIICwAphAWAFMICQAphASCFsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAkAKYVGDSb4z96Damr47dy+TUE/mjttV7srdhKr1cvMboMW4+Q2A2hEWAFIICwAphAWAFMICQAphASCFsKjBJIwL6IdxFsNhnMWtCAsAKQzKAlqMQVkAakdYAEghLACkEBYAUggLACmEBYAUwgJACmEBIIWw6NLU8OdJGOI8SHnflKdN1t5r29f2btf83Kzm52Zver3XcOc6au9eR2ad5f1XZRj2OPc9YQEgheHeWLGFgzu06bnXmi5jqiwc3CFJK96vVT8LhntXwGlIf8v7ZtNzr3Eacpt1DHMasum514b6o7/zf26s+D3D4sgCaDGOLCrgyKI/OjhzNdDBCaDVOA0BWozTEAC1IywApBAWt7G0e1urtz+spd3bVm3t6I+wAJBCByfQYnRwAqjdwLCwfcT2FdvnSvPW237V9k+L6Z3FfNv+hu1522/avn+UxQMYn8yRxQuSHuqa94ykUxGxRdKp4rkkPSxpS/HvgKTn6ykTQNMGhkVEnJZ0tWv2HklHi8dHJT1amv/t6Hhd0sdsb6yrWADNGbbPYkNEXCoevytpQ/F4k6R3SstdLOYBWOUqd3BG5+uUFX+lYvuA7TO2z/xe16uWAWDEhg2Ly8unF8X0SjF/QdI9peXuLubdIiIOR8RMRMys1bohywAwLsOGxXFJ+4vH+yW9Upr/+eJbkVlJvyqdrgBYxdYMWsD2i5J2SbrL9kVJz0r6mqRjtp+U9Lakx4rFT0h6RNK8pGuSvjCCmgE0YGBYRMQTfV66Zchl0X/xVNWiAEweRnACSCEsAKQQFgBSCIsaTPLNdgfV1vQNd3uZhHoyN9GtcqPdJlStl0vUgRbjEnUAtSMsAKQQFgBSCAsAKYQFgBTCAkAKYQEghbAAkEJYAEghLLo0Nfx5EoY4D1LeN+Vpk7X32va1vds1Pzer+bnZm17vNdy5jtq715FZZ3n/VRmGPc59z3BvoMUY7g2gdoQFgBTCAkAKYdGFDs7+6ODM1TCtHZyERZfFndbizlR/T+3bnXTlfVOeNll7r20v7rTO7zuk8/sO3fT6+X2HUu+vWkNmneX916uuYbc9SoQFgJSBPwXQNp883cxXyU1tdyXKNS4/brruXtv/5OnQZn3pltc3f/dL+iu9PvD9VWvIrLO8/zbr1rqG3fYoMc4CaDHGWQCoHWHRZbkXvYntTrryvilPm6y917bn52Z1cvGsTi6even1k4tnU++vWsNK7gy+XGtd2x4lTkOAFuM0BEDtCAsAKYQFgBTCogvDvftjuHeuhmkd7k0HJ9BidHACqB1hASCFsACQQlgASCEsajDJQ7UH1db0cO1eJqGezBDsKsO0m1C1Xr4NAVqMb0MA1I6wAJBCWABIISwApBAWAFIICwAphAWAFMKiBpMwiKgfBmUNh0FZt2JQFtBiDMqqgJvf9MfNb3I1cPObEeLIAmgGRxYAakdYAEghLLrQZ9EffRa5GlrbZ2H7iKR/kHQlIv66mPcVSf8s6b1isX+NiBPFa1+W9KSkG5L+JSJODiqCPgugGXX3Wbwg6aEe8+ciYmvxbzko7pP0uKRPF+/5pu07cmUDmGQDwyIiTku6mlzfHkkvRcT1iPi5pHlJD1SoD8CEqNJn8bTtN20fsX1nMW+TpHdKy1ws5gFY5YYNi+clbZa0VdIlSV9f6QpsH7B9xvaZ3+v6kGUAGJehwiIiLkfEjYj4g6Rv6f1TjQVJ95QWvbuY12sdhyNiJiJm1mrdMGUAGKOhwsL2xtLTvZLOFY+PS3rc9jrb90raIukH1UoEMAnWDFrA9ouSdkm6y/ZFSc9K2mV7q6SQdEHSFyUpIt6yfUzSjyUtSXoqIm6MpnQA45T5NuSJiNgYEWsj4u6I+PeI+KeI+ExE/E1E/GNEXCot/9WI2BwRn4qI/xht+fVjUFZ/DMrK1dDaQVnjwKAsoBlcSFYBRxb9cWSRq2FajywIiy6LO63FnamgrX27k668b8rTJmvvte3Fndb5fYd0ft+hm14/v+9Q6v1Va8iss7z/etU17LZHidMQrNjCwR3a9NxrTZcxVRYO7pCkFe/Xqp8FpyEAaseRBdBiHFkAqB1hASCFsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAlhllnZv09LubWPfLmEBIGXgnbIATJY1//VGI9vlyKIL97Pob3nfLBzcwf0sbrOOYe5nsXBwx/9feboS7x3/1IrfMywuJANajAvJANSOsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAkAKYQEghbCoQZWfnxu1QbUtD4ueJJNQz8nFs7UsM0mq1stwb6DFGO4NoHaEBYAUwgJACmEBIGUiOjhtvyfpt5J+0XQtY3aXaHMbTHKb/zwiPp5ZcCLCQpJsn4mImabrGCfa3A7T0mZOQwCkEBYAUiYpLA43XUADaHM7TEWbJ6bPAsBkm6QjCwATjLAAkEJYAEghLACkEBYAUv4I7XczZv1yHfoAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2466cb70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 29.060596466064453 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 2.0, 'lmda': 10000000000.0} is: \n",
-      "[[4.00e+30 8.00e+10 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [8.00e+10 8.00e+30 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [0.00e+00 0.00e+00 4.00e+30 ... 4.00e+30 4.00e+30 4.00e+30]\n",
-      " ...\n",
-      " [0.00e+00 0.00e+00 4.00e+30 ... 7.20e+51 7.20e+51 1.48e+32]\n",
-      " [0.00e+00 0.00e+00 4.00e+30 ... 7.20e+51 7.20e+51 1.48e+32]\n",
-      " [0.00e+00 0.00e+00 4.00e+30 ... 1.48e+32 1.48e+32 2.02e+32]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAADaVJREFUeJzt3UHMFPd9xvHnqSFEiRLF1Aki2G1diiI5TYvMK/MKWYhQKbWtqpiLsQ8NiqySSLZ6xenFuUSKD9ErRWqMiIpMDrHDxTIHWmLRAwfLSbCEHBw1zUuCZd4XgxOqJAoqyUt+Oey89bDssr93Z3Zn353vR0KzOzs78/vP8j6a+e9/Zh0RAoBB/qTpAgCsDoQFgBTCAkAKYQEghbAAkEJYAEhpPCxsP2T7J7bnbT/TdD2jYvuC7R/ZPmv7TDFvve1Xbf+0mN7ZdJ1V2D5i+4rtc6V5Pdvojm8Un/ubtu9vrvLh9WnzV2wvFJ/1WduPlF77ctHmn9j++2aqHk6jYWH7Dkn/JulhSfdJesL2fU3WNGKfjYitETFTPH9G0qmI2CLpVPF8NXtB0kNd8/q18WFJW4p/ByQ9P6Ya6/aCbm2zJM0Vn/XWiDghScX/7cclfbp4zzeLv4FVoekjiwckzUfEzyLid5JekrSn4ZrGaY+ko8Xjo5IebbCWyiLitKSrXbP7tXGPpG9Hx+uSPmZ743gqrU+fNvezR9JLEXE9In4uaV6dv4FVoemw2CTpndLzi8W8aRSSvmf7DdsHinkbIuJS8fhdSRuaKW2k+rVx2j/7p4vTqyOl08tV3eamw6JNHoyI+9U5/H7K9s7yi9EZdz/VY+/b0MbC85I2S9oq6ZKkrzdbTj2aDosFSfeUnt9dzJs6EbFQTK9Ielmdw8/Ly4fexfRKcxWOTL82Tu1nHxGXI+JGRPxB0rf0/qnGqm5z02HxQ0lbbN9r+wPqdP4cb7im2tn+sO2PLD+W9DlJ59Rp6/5isf2SXmmmwpHq18bjkj5ffCsyK+lXpdOVVa2r72WvOp+11Gnz47bX2b5Xnc7dH4y7vmGtaXLjEbFk+2lJJyXdIelIRLzVZE0jskHSy7alzj7/TkT8p+0fSjpm+0lJb0t6rMEaK7P9oqRdku6yfVHSs5K+pt5tPCHpEXU6+a5J+sLYC65Bnzbvsr1VnVOuC5K+KEkR8ZbtY5J+LGlJ0lMRcaOJuodhLlEHkNH0aQiAVYKwAJBCWABIISwApBAWAFJGFhYrvZq0NAS6NWhzO0xLm0cSFkNeTToVO3SFaHM7TEWbR3Vk0farSYGpM6oRnL2urtveb+EPeF18UB/SR72+VSPEaHM7THKb/0+/1e/iujPLNjbcuziPOyB1duaD799MCMCYfD9OpZcd1WnIwKvrIuJwRMxExMxarRtRGQDqMqqwaMXVpECbjOQ0pEVXkwKtMbI+i+ImpSdGtX4A48UITgAphAWAFMICQAphASCFsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAkAKYQEghbAAkEJYAEghLACkEBYAUggLACmEBYAUwgJACmEBIIWwAJBCWABIISwApBAWAFIICwAphAWAFMICQAphASCFsOhybe92Xdu7vZHtTrryvilPm6y917av7d2u+blZzc/N3vT6/Nxs6v1Va8iss7z/etU17LZHibAAkOKIaLoGfdTrY7v/rukygNb5fpzSr+OqM8tyZHEbS7u3tXr7w1ravW3V1o7+OLIAWowjCwC1IywApBAWAFIICwAphAWAFMICQAphASCFsACQQljUYJIvAhtUW9MXgvUyCfVkLu6qcgFYE6rWywhOoMUYwQmgdoQFgBTCAkAKYQEghbAAkEJYAEghLACkEBYAUggLAClrqrzZ9gVJv5F0Q9JSRMzYXi/pu5L+QtIFSY9FxP9WKxNA0+o4svhsRGyNiJni+TOSTkXEFkmniucAVrlRnIbskXS0eHxU0qMj2AaAMasaFiHpe7bfsH2gmLchIi4Vj9+VtKHiNgBMgEp9FpIejIgF25+Q9Krt/y6/GBFhu+dlrUW4HJCkD+pDFcsAMGqVjiwiYqGYXpH0sqQHJF22vVGSiumVPu89HBEzETGzVuuqlAFgDIYOC9sftv2R5ceSPifpnKTjkvYXi+2X9ErVIseJX1Hvj19Rz9Uwrb+iPvTNb2z/pTpHE1LndOY7EfFV238q6ZikP5P0tjpfnV693bq4+Q3QjJXc/GboPouI+Jmkv+0x/5eS+MsHpgwjOAGkEBYAUgiL21java3V2x/W0u5tq7Z29MfdvYEW4+7eAGpHWABIISwApBAWAFIICwAphAWAFMICQAphASCFsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAkAKYVGDSb4z96Damr47dy+TUE/mjttV7srdhKr1cvMboMW4+Q2A2hEWAFIICwAphAWAFMICQAphASCFsKjBJIwL6IdxFsNhnMWtCAsAKQzKAlqMQVkAakdYAEghLACkEBYAUggLACmEBYAUwgJACmEBIIWw6NLU8OdJGOI8SHnflKdN1t5r29f2btf83Kzm52Zver3XcOc6au9eR2ad5f1XZRj2OPc9YQEgheHeWLGFgzu06bnXmi5jqiwc3CFJK96vVT8LhntXwGlIf8v7ZtNzr3Eacpt1DHMasum514b6o7/zf26s+D3D4sgCaDGOLCrgyKI/OjhzNdDBCaDVOA0BWozTEAC1IywApBAWt7G0e1urtz+spd3bVm3t6I+wAJBCByfQYnRwAqjdwLCwfcT2FdvnSvPW237V9k+L6Z3FfNv+hu1522/avn+UxQMYn8yRxQuSHuqa94ykUxGxRdKp4rkkPSxpS/HvgKTn6ykTQNMGhkVEnJZ0tWv2HklHi8dHJT1amv/t6Hhd0sdsb6yrWADNGbbPYkNEXCoevytpQ/F4k6R3SstdLOYBWOUqd3BG5+uUFX+lYvuA7TO2z/xe16uWAWDEhg2Ly8unF8X0SjF/QdI9peXuLubdIiIOR8RMRMys1bohywAwLsOGxXFJ+4vH+yW9Upr/+eJbkVlJvyqdrgBYxdYMWsD2i5J2SbrL9kVJz0r6mqRjtp+U9Lakx4rFT0h6RNK8pGuSvjCCmgE0YGBYRMQTfV66Zchl0X/xVNWiAEweRnACSCEsAKQQFgBSCIsaTPLNdgfV1vQNd3uZhHoyN9GtcqPdJlStl0vUgRbjEnUAtSMsAKQQFgBSCAsAKYQFgBTCAkAKYQEghbAAkEJYAEghLLo0Nfx5EoY4D1LeN+Vpk7X32va1vds1Pzer+bnZm17vNdy5jtq715FZZ3n/VRmGPc59z3BvoMUY7g2gdoQFgBTCAkAKYdGFDs7+6ODM1TCtHZyERZfFndbizlR/T+3bnXTlfVOeNll7r20v7rTO7zuk8/sO3fT6+X2HUu+vWkNmneX916uuYbc9SoQFgJSBPwXQNp883cxXyU1tdyXKNS4/brruXtv/5OnQZn3pltc3f/dL+iu9PvD9VWvIrLO8/zbr1rqG3fYoMc4CaDHGWQCoHWHRZbkXvYntTrryvilPm6y917bn52Z1cvGsTi6even1k4tnU++vWsNK7gy+XGtd2x4lTkOAFuM0BEDtCAsAKYQFgBTCogvDvftjuHeuhmkd7k0HJ9BidHACqB1hASCFsACQQlgASCEsajDJQ7UH1db0cO1eJqGezBDsKsO0m1C1Xr4NAVqMb0MA1I6wAJBCWABIISwApBAWAFIICwAphAWAFMKiBpMwiKgfBmUNh0FZt2JQFtBiDMqqgJvf9MfNb3I1cPObEeLIAmgGRxYAakdYAEghLLrQZ9EffRa5GlrbZ2H7iKR/kHQlIv66mPcVSf8s6b1isX+NiBPFa1+W9KSkG5L+JSJODiqCPgugGXX3Wbwg6aEe8+ciYmvxbzko7pP0uKRPF+/5pu07cmUDmGQDwyIiTku6mlzfHkkvRcT1iPi5pHlJD1SoD8CEqNJn8bTtN20fsX1nMW+TpHdKy1ws5gFY5YYNi+clbZa0VdIlSV9f6QpsH7B9xvaZ3+v6kGUAGJehwiIiLkfEjYj4g6Rv6f1TjQVJ95QWvbuY12sdhyNiJiJm1mrdMGUAGKOhwsL2xtLTvZLOFY+PS3rc9jrb90raIukH1UoEMAnWDFrA9ouSdkm6y/ZFSc9K2mV7q6SQdEHSFyUpIt6yfUzSjyUtSXoqIm6MpnQA45T5NuSJiNgYEWsj4u6I+PeI+KeI+ExE/E1E/GNEXCot/9WI2BwRn4qI/xht+fVjUFZ/DMrK1dDaQVnjwKAsoBlcSFYBRxb9cWSRq2FajywIiy6LO63FnamgrX27k668b8rTJmvvte3Fndb5fYd0ft+hm14/v+9Q6v1Va8iss7z/etU17LZHidMQrNjCwR3a9NxrTZcxVRYO7pCkFe/Xqp8FpyEAaseRBdBiHFkAqB1hASCFsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAlhllnZv09LubWPfLmEBIGXgnbIATJY1//VGI9vlyKIL97Pob3nfLBzcwf0sbrOOYe5nsXBwx/9feboS7x3/1IrfMywuJANajAvJANSOsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAkAKYQEghbCoQZWfnxu1QbUtD4ueJJNQz8nFs7UsM0mq1stwb6DFGO4NoHaEBYAUwgJACmEBIGUiOjhtvyfpt5J+0XQtY3aXaHMbTHKb/zwiPp5ZcCLCQpJsn4mImabrGCfa3A7T0mZOQwCkEBYAUiYpLA43XUADaHM7TEWbJ6bPAsBkm6QjCwATjLAAkEJYAEghLACkEBYAUv4I7XczZv1yHfoAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.390531063079834 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 1e-10} is: \n",
-      "[[  8.           8.           0.         ...   0.           0.\n",
-      "    0.        ]\n",
-      " [  8.          12.           0.         ...   0.           0.\n",
-      "    0.        ]\n",
-      " [  0.           0.           8.         ...   8.           8.\n",
-      "    8.        ]\n",
-      " ...\n",
-      " [  0.           0.           8.         ... 264.00000001 264.00000001\n",
-      "  264.00000001]\n",
-      " [  0.           0.           8.         ... 264.00000001 264.00000001\n",
-      "  264.00000001]\n",
-      " [  0.           0.           8.         ... 264.00000001 264.00000001\n",
-      "  264.00000002]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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Y77jKkZnNG0Y7+a5w2K5bkWQEZpDKir7W64fH9R+/4kYRnWq2tgF2nY8wjVuS/+0sbFpojWDSdNDoSq/G7c7xNvpt3DoQfi5BNo76P/Odin579iyISIXBgohUGCyISIXBgohUGCyISIXBgohUGCyISIXBgohUGCyISIXBgohUGCyISIXBgohUGCyISCUXs06HSTm4DkOvlkhCpuTUVwibrToC7mzN7JUttldYfYrCaMuQXLOGX7+99LqxZ0FEKgwWRKTCYEFEKgwWRKTCYEFEKrl6GiI1TzLD1mB5Z29VdbdS+TDTCi4JLS07L+RAlfVG8D5624Qcw2rtC1luf3Wrr1eWEpSn9ohrl8vNmZlU2N17t3p7ksrmQUoN/ROnVk2fR7RbFNTm0lWm9yqthucIbVeT/zp0i4LapWS5MIN4q6MHMQXLOV5/2b4LyXKSBlVdlwRvN3sWRKSSi56FWBasicleJm8AKJyw0xkXSvZfUPcvffviJXQ/eypwP8WpycDlvZ9fWOx937j3psh1S6vBPYi47NfV+SYAoH5PdBbwMOVV3V/brFm4h7k9ivpdwWNctEpr+u1NgkEp1SWD+U9mP+eo9nWLyXsI1SVg8Z7s43dkLfrFMEX7/Skv99crn1xJdIz2ZsCv+4S+t8aeBRGpMFgQkQqDBRGpMFgQkQqDBRGpMFgQkQqDBRGpMFgQkQqDBRGpMFgQkQqDBRGpMFgQkQqDBRGpMFgQkQqDBRGp5CKfBSzLzpLVbPaXeTJjAYCpX4ndTduTCau03PT93Gz18w5IJzp3QXsiOI7GZcCynNokRV3CKx9tnorKSnjGpzTcDFdJ8lFkVV3S54+orHRQXtnej+vEcvJ8GZWrBmvL2/+alRfstpUb/WUrM7WQtYMVGv7Xz2zp+wvsWRCRCoMFEakwWBCRCoMFEanEBgsReVpEFkTkdc+yaRH5lYi87Xw95CwXEfmhiLwjIq+JyN3b2Xgi2jmansUzAB4YWvYEgHPGmBMAzjn/B4AHAZxw/p0F8ORomklE4xYbLIwxvwawPLT4DIBnne+fBfAVz/KfGNvLAA6KyPWjaiwRjU/aexbHjDGXne/nABxzvr8RwAXPerPOMiLa5TLf4DTGGACJq7OIyFkReUVEXtnqrmdtBhFts7TBYt69vHC+LjjLLwLwlvo67izzMcY8ZYw5bYw5XbYmUjaDiHZK2vGzLwJ4FMD3nK8/9yx/XESeA3AvgBXP5Uoo026jU6/DmuyXH5SVVQB2uULAU84QgKwHl4srzPWHhG/ddtT382KxHxutVnRnyC1DOGztluCyhi63MHJa2sLEHx4f7dBnt0hxkpKCQZIM4V69UT+8evNgEZ1q9gLE1aXwY67elHz/m9OCTi1bMWlgsCxhkPXb7GkGG54yh6UDIVWuQ1SOrvmWWRX9tIHYT5yI/AzA/QCOiMgsgG/DDhLPi8g3ALwP4GFn9ZcAPATgHQBNAF9Xt4SIci02WBhjvhbyo88HrGsAPJa1UUSUPxzBSUQqDBZEpMJgQUQqDBZEpMJgQUQqDBZEpMJgQUQqDBZEpJKP7N4OqfWzFXszcQMYyPZthQz39m0zZCD7dyN63bBjaLOCp82+HdcuV3FjtG+dm1U8yXDtIEnOe/NgsnOYWEiefXtY5Wr4+bVq6fY/cSn7e+HN2h2kU/FnEO9eSJbde3XKPyy929b3F3IRLMSyYE1MolOv95YV7vyY/dVdp2nn1m+f/wCtL54O3E95Ijole3m2n5Zj8b7omfOVw+XA5Z1K9Is7eclu59xnJiPXC1Ne0U3O6FSz/+J41ea6AID5T2bbb5J0/UnmekwsCBr3pKyv4LUS/hkxlW7i3ZXrRRy6ux6/YozlRvTnZaJi/6KvLvQDxF/f9cdEx1hpVX3L/qsaXdrCi5chRKTCYEFEKgwWRKTCYEFEKgwWRKTCYEFEKgwWRKTCYEFEKgwWRKTCYEFEKgwWRKTCYEFEKgwWRKTCYEFEKgwWRKSSm2AhZX+eAVPUNa9blF7yFqIwVjF7rdTtUC6kS5S003KR/AaWBZQGk830AsXMIfurUyg5cPO2/SFoT1V6y4qNgKKxrX6mIHebMGFJbkqr0W9swcmwVUhWs7ZHG/SiMj6l4Z5XaS06gdAoRRUpHla5aiIT12h0AUg7/JilRvJfh+qSYPHK/gytsnUj2gUArWU7cY23gPIby9clOkZQgp31lv41zU3PgojyjcGCiFQYLIhIhcGC9jbeF1djsKC9LZ8PSHKJwYKIVHLx6NS02+jU67Am+492rEYTgF0nBPDUEdmaQbfpL5YCDNYFWf/YUf/PPd9bwbvocet/DGvcPhG5XbeUrPCL77iLutoVjVtGG+fbVfuj0M04FmFiWd+vX71Jf6xWTVLV9RgW9Xi0dVPy592tqRJqkymfk3t464EEOXar/dlenu7/jhzffzXRMU5Oz/mW/WtZ33b2LIhIhcGCiFQYLIhIhcGCiFQYLIhIhcGCiFQYLIhIhcGCiFRyMShrWFAiHMDOcZFmKP9OJMbp5vKV9Nst7cyr4QQ62YeJ7R7sWRCRCoMFEakwWBCRSq6uYKXmmUzTGpzp5c3J6ea59GkFzw4LytGpzaXp31c1ZLn91c3dmTZHZly7XIXNdHE+LDeoe1+nupRqtz1JzntzOtm9pHI9+8c1Ku9nayo+H+XwPQppC1Yv78vYqsHcmkEW99l5Pr25Ol+7eEOiY0xPNX3L1jv6HJy5CBZiWbAmJtGp13vLrE/cAQAobDm/tOtbAIDO2+9i/cynAvczUYp+wcuz/Vl6S1+ITnba2hechLVdjf6A75+127t4X7rkshuHddu1sk1u9aldsn/JF+8JCcRKa8v68+7UYqb+ekxcKuLQ3fX4FWNEJddNM3t09fI+fPmTv8/SJADAWw3/LGmvYxMfAgB+P98PEH/38RcTHWOp7Q9q3y2HJ8IexssQIlJhsCAiFQYLIlJhsCAildhgISJPi8iCiLzuWfYdEbkoIq86/x7y/OxbIvKOiLwlIl/aroYT0c7S9CyeAfBAwPIfGGNOOf9eAgARuRPAIwBOOtv8SESiH1EQ0a4QGyyMMb8GsBy3nuMMgOeMMZvGmPcAvAMg+DknEe0qWe5ZPC4irzmXKU71YtwI4IJnnVlnGRHtcmmDxZMAPgLgFIDLAL6fdAciclZEXhGRV7ZMcNp9IsqPVMHCGDNvjOkYY7oAfoz+pcZFADd5Vj3uLAvax1PGmNPGmNNlCR5CTUT5kSpYiMj1nv9+FYD7pORFAI+ISEVEbgNwAsBvsjWRiPIgdm6IiPwMwP0AjojILIBvA7hfRE7BrhR5HsA3AcAY84aIPA/gTQBtAI8ZY3Qzo4go12KDhTHmawGL/yli/e8C+G6WRhFR/nAEJxGpMFgQkUpugkVQkl4Tk5+it15BYArbn5SXdrdyIZ+3zyYKW+Nugkoukt/AsoBSeWBRL1DM2OO9pBk+FkM6duKW1lR/H4WmP7GKeDJpudmzwoQluSmvRm/nHrewUY5cL4w2+3a5kWr34ftzzkvWdm50flx2qIF1G8ByYzLzMb2ZpoatLiTPKFReLsQmrtH4cLMS+fO5hp20x9vG//nwRKJjvLd22Ldspf2Wevvc9CyIKN8YLIhIhcGCiFQYLIhIhcGCiFQYLIhIhcGCiFRyMc7CtNvo1OuwJvvP0aWxDsAuKgR4ig7NzKC4Hly7uvpeP6HX6p1HfD+32gc930e3qTYXXGznykfjxk9km25fXdJV9GrcnukwPqZg/90wRX3hnyDlBf3guPXb9IOROpUSJirZ2gYAreXw9+fYrdqEcH2L+/b3CgBl4Y6jCPNXx/8MAHhrqj+m446Jy4mO8Zf73/Yte63EIkNENGK56Fm4vLVOZbjWqTOiU2YOBY7ODNpmmHeEp3Yk5jCrHV2ezx35mXaEZVy7XIWN0cZ5d+RoklGVQZKc90bC0aJpRlgOizq/5enkI0S7bRkoKZhW3Lm5PQrvSM9/X/x4omPcVvMXsl3tvK/enj0LIlJhsCAilVxchgRVUZebTwIACmsz9oJ1+4Zj580/ofnwp0P2NB15nOpsv49cv8t/A9SrXZ0IXN6JqaJem7cvX+qn082C3ZrSdc23DuguV7T2XXAun06uZNrPyoz+UqF0QF+1vHuhhr++649pmjTgjeXrQn92fP/VxPt77eINiauZB4mbFObezPReevzLR/4z0TGudJq+Zed4g5OIRo3BgohUGCyISIXBgohUGCyISIXBgohUGCyISIXBgohUGCyISIXBgohUGCyISCUXc0NMt4tuszmY/MadC+LMF5Gb7Sm6hZkZFDaDk9+Ulvtj35s3+JOctDxTkAsx0xIqK8HVq5rHol+yzQP23A5LP+1hgHaK98bR4NcgLXdOSnsz20ei0NBvXzm6pl53daqNlVa2xEJAdKGik9Nzifc3PdXEUntfliYBCC4A5OUmrvFOMw+a6xHlUMF/7sUE/QX2LIhIhcGCiFQYLIhIhcGCiFQYLIhIRYwZbcalVI0QqQNYA7A47rbssCPgOe8FeT7nW4wxM5oVcxEsAEBEXjHGnB53O3YSz3lvuFbOmZchRKTCYEFEKnkKFk+NuwFjwHPeG66Jc87NPQsiyrc89SyIKMcYLIhIhcGCiFQYLIhIhcGCiFT+Hz/SJ046PtnwAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1588>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.39858675003052 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 1e-09} is: \n",
-      "[[  8.           8.           0.         ...   0.           0.\n",
-      "    0.        ]\n",
-      " [  8.          12.00000001   0.         ...   0.           0.\n",
-      "    0.        ]\n",
-      " [  0.           0.           8.         ...   8.           8.\n",
-      "    8.        ]\n",
-      " ...\n",
-      " [  0.           0.           8.         ... 264.00000015 264.00000015\n",
-      "  264.00000015]\n",
-      " [  0.           0.           8.         ... 264.00000015 264.00000015\n",
-      "  264.00000015]\n",
-      " [  0.           0.           8.         ... 264.00000015 264.00000015\n",
-      "  264.0000002 ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb689026d8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.318459033966064 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 1e-08} is: \n",
-      "[[  8.00000004   8.           0.         ...   0.           0.\n",
-      "    0.        ]\n",
-      " [  8.          12.00000008   0.         ...   0.           0.\n",
-      "    0.        ]\n",
-      " [  0.           0.           8.00000004 ...   8.00000004   8.00000004\n",
-      "    8.00000004]\n",
-      " ...\n",
-      " [  0.           0.           8.00000004 ... 264.00000148 264.00000148\n",
-      "  264.00000148]\n",
-      " [  0.           0.           8.00000004 ... 264.00000148 264.00000148\n",
-      "  264.00000148]\n",
-      " [  0.           0.           8.00000004 ... 264.00000148 264.00000148\n",
-      "  264.00000202]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1f98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.18604373931885 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 1e-07} is: \n",
-      "[[  8.0000004   8.          0.        ...   0.          0.\n",
-      "    0.       ]\n",
-      " [  8.         12.0000008   0.        ...   0.          0.\n",
-      "    0.       ]\n",
-      " [  0.          0.          8.0000004 ...   8.0000004   8.0000004\n",
-      "    8.0000004]\n",
-      " ...\n",
-      " [  0.          0.          8.0000004 ... 264.0000148 264.0000148\n",
-      "  264.0000148]\n",
-      " [  0.          0.          8.0000004 ... 264.0000148 264.0000148\n",
-      "  264.0000148]\n",
-      " [  0.          0.          8.0000004 ... 264.0000148 264.0000148\n",
-      "  264.0000202]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688e5208>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.15291094779968 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 1e-06} is: \n",
-      "[[  8.000004   8.         0.       ...   0.         0.         0.      ]\n",
-      " [  8.        12.000008   0.       ...   0.         0.         0.      ]\n",
-      " [  0.         0.         8.000004 ...   8.000004   8.000004   8.000004]\n",
-      " ...\n",
-      " [  0.         0.         8.000004 ... 264.000148 264.000148 264.000148]\n",
-      " [  0.         0.         8.000004 ... 264.000148 264.000148 264.000148]\n",
-      " [  0.         0.         8.000004 ... 264.000148 264.000148 264.000202]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24637da0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.9378080368042 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 1e-05} is: \n",
-      "[[  8.00004      8.           0.         ...   0.           0.\n",
-      "    0.        ]\n",
-      " [  8.          12.00008      0.         ...   0.           0.\n",
-      "    0.        ]\n",
-      " [  0.           0.           8.00004    ...   8.00004      8.00004\n",
-      "    8.00004   ]\n",
-      " ...\n",
-      " [  0.           0.           8.00004    ... 264.00148001 264.00148001\n",
-      "  264.00148   ]\n",
-      " [  0.           0.           8.00004    ... 264.00148001 264.00148001\n",
-      "  264.00148   ]\n",
-      " [  0.           0.           8.00004    ... 264.00148    264.00148\n",
-      "  264.00202   ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2466cb70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.21824765205383 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 0.0001} is: \n",
-      "[[  8.0004       8.           0.         ...   0.           0.\n",
-      "    0.        ]\n",
-      " [  8.          12.0008       0.         ...   0.           0.\n",
-      "    0.        ]\n",
-      " [  0.           0.           8.0004     ...   8.0004       8.0004\n",
-      "    8.0004    ]\n",
-      " ...\n",
-      " [  0.           0.           8.0004     ... 264.01480072 264.01480072\n",
-      "  264.0148    ]\n",
-      " [  0.           0.           8.0004     ... 264.01480072 264.01480072\n",
-      "  264.0148    ]\n",
-      " [  0.           0.           8.0004     ... 264.0148     264.0148\n",
-      "  264.0202    ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb6c144390>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.12432861328125 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 0.001} is: \n",
-      "[[  8.004      8.         0.       ...   0.         0.         0.      ]\n",
-      " [  8.        12.008      0.       ...   0.         0.         0.      ]\n",
-      " [  0.         0.         8.004    ...   8.004      8.004      8.004   ]\n",
-      " ...\n",
-      " [  0.         0.         8.004    ... 264.148072 264.148072 264.148   ]\n",
-      " [  0.         0.         8.004    ... 264.148072 264.148072 264.148   ]\n",
-      " [  0.         0.         8.004    ... 264.148    264.148    264.202   ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb68902ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.32614278793335 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 0.01} is: \n",
-      "[[  8.04     8.       0.     ...   0.       0.       0.    ]\n",
-      " [  8.      12.08     0.     ...   0.       0.       0.    ]\n",
-      " [  0.       0.       8.04   ...   8.04     8.04     8.04  ]\n",
-      " ...\n",
-      " [  0.       0.       8.04   ... 265.4872 265.4872 265.48  ]\n",
-      " [  0.       0.       8.04   ... 265.4872 265.4872 265.48  ]\n",
-      " [  0.       0.       8.04   ... 265.48   265.48   266.02  ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688e59b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.2137987613678 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 0.1} is: \n",
-      "[[  8.4    8.     0.   ...   0.     0.     0.  ]\n",
-      " [  8.    12.8    0.   ...   0.     0.     0.  ]\n",
-      " [  0.     0.     8.4  ...   8.4    8.4    8.4 ]\n",
-      " ...\n",
-      " [  0.     0.     8.4  ... 279.52 279.52 278.8 ]\n",
-      " [  0.     0.     8.4  ... 279.52 279.52 278.8 ]\n",
-      " [  0.     0.     8.4  ... 278.8  278.8  284.2 ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb6c1443c8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.11435890197754 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 1.0} is: \n",
-      "[[ 12.   8.   0. ...   0.   0.   0.]\n",
-      " [  8.  20.   0. ...   0.   0.   0.]\n",
-      " [  0.   0.  12. ...  12.  12.  12.]\n",
-      " ...\n",
-      " [  0.   0.  12. ... 484. 484. 412.]\n",
-      " [  0.   0.  12. ... 484. 484. 412.]\n",
-      " [  0.   0.  12. ... 412. 412. 466.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1c50>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.42665195465088 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 10.0} is: \n",
-      "[[4.800e+01 8.000e+00 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [8.000e+00 9.200e+01 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 4.800e+01 ... 4.800e+01 4.800e+01 4.800e+01]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 4.800e+01 ... 8.944e+03 8.944e+03 1.744e+03]\n",
-      " [0.000e+00 0.000e+00 4.800e+01 ... 8.944e+03 8.944e+03 1.744e+03]\n",
-      " [0.000e+00 0.000e+00 4.800e+01 ... 1.744e+03 1.744e+03 2.284e+03]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2466cb70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.08107781410217 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 100.0} is: \n",
-      "[[4.08000e+02 8.00000e+00 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
-      "  0.00000e+00]\n",
-      " [8.00000e+00 8.12000e+02 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
-      "  0.00000e+00]\n",
-      " [0.00000e+00 0.00000e+00 4.08000e+02 ... 4.08000e+02 4.08000e+02\n",
-      "  4.08000e+02]\n",
-      " ...\n",
-      " [0.00000e+00 0.00000e+00 4.08000e+02 ... 7.35064e+05 7.35064e+05\n",
-      "  1.50640e+04]\n",
-      " [0.00000e+00 0.00000e+00 4.08000e+02 ... 7.35064e+05 7.35064e+05\n",
-      "  1.50640e+04]\n",
-      " [0.00000e+00 0.00000e+00 4.08000e+02 ... 1.50640e+04 1.50640e+04\n",
-      "  2.04640e+04]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1fd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.154428482055664 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 1000.0} is: \n",
-      "[[4.0080000e+03 8.0000000e+00 0.0000000e+00 ... 0.0000000e+00\n",
-      "  0.0000000e+00 0.0000000e+00]\n",
-      " [8.0000000e+00 8.0120000e+03 0.0000000e+00 ... 0.0000000e+00\n",
-      "  0.0000000e+00 0.0000000e+00]\n",
-      " [0.0000000e+00 0.0000000e+00 4.0080000e+03 ... 4.0080000e+03\n",
-      "  4.0080000e+03 4.0080000e+03]\n",
-      " ...\n",
-      " [0.0000000e+00 0.0000000e+00 4.0080000e+03 ... 7.2148264e+07\n",
-      "  7.2148264e+07 1.4826400e+05]\n",
-      " [0.0000000e+00 0.0000000e+00 4.0080000e+03 ... 7.2148264e+07\n",
-      "  7.2148264e+07 1.4826400e+05]\n",
-      " [0.0000000e+00 0.0000000e+00 4.0080000e+03 ... 1.4826400e+05\n",
-      "  1.4826400e+05 2.0226400e+05]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f8358>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.17109155654907 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 10000.0} is: \n",
-      "[[4.00080000e+04 8.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [8.00000000e+00 8.00120000e+04 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00080000e+04 ... 4.00080000e+04\n",
-      "  4.00080000e+04 4.00080000e+04]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 4.00080000e+04 ... 7.20148026e+09\n",
-      "  7.20148026e+09 1.48026400e+06]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00080000e+04 ... 7.20148026e+09\n",
-      "  7.20148026e+09 1.48026400e+06]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00080000e+04 ... 1.48026400e+06\n",
-      "  1.48026400e+06 2.02026400e+06]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAADeZJREFUeJzt3V+MVOUZx/HfU0GMRqOUliDa1lJiov1DZAMbogS3iVXTFLgRvKjEmKIJprdgb/TGRC9kE5MqwZSIF/7hxsgFLRp6YRNjFRNi0dQ6KEZ2kbWlsY1YdPHpxZzFYXaGeXbOmXnP7Pl+EjIz75yZ85wz7C/nvPOed8zdBQCdfCt1AQAGA2EBIISwABBCWAAIISwAhBAWAEKSh4WZ3Wpm75lZzcy2pa6nV8zsqJn9zcwOmdnBrG2+mb1iZu9nt1ekrjMPM9tlZhNmdrihreU2Wt3j2ef+tpndkK7y7rXZ5ofMbCz7rA+Z2e0Nzz2QbfN7ZvaLNFV3J2lYmNkFkn4v6TZJ10m608yuS1lTj93s7svcfSh7vE3SAXdfKulA9niQPS3p1qa2dtt4m6Sl2b/Nkp7sU41Fe1rTt1mSRrPPepm775Ok7P/2RknXZ695IvsbGAipjyxWSKq5+wfu/qWk5yWtTVxTP62VtDu7v1vSuoS15Obur0o62dTcbhvXSnrG616XdLmZLepPpcVps83trJX0vLufdvcPJdVU/xsYCKnDYrGkjxseH8vaZiOX9LKZvWVmm7O2he5+PLv/iaSFaUrrqXbbONs/+/uz06tdDaeXA73NqcOiSm509xtUP/zeYmarG5/0+rj7WT32vgrbmHlS0hJJyyQdl/RY2nKKkTosxiRd3fD4qqxt1nH3sex2QtKLqh9+npg69M5uJ9JV2DPttnHWfvbufsLdz7j715Ke0jenGgO9zanD4k1JS83sGjO7UPXOn72JayqcmV1iZpdO3Zd0i6TDqm/rpmyxTZJeSlNhT7Xbxr2S7sq+FRmW9FnD6cpAa+p7Wa/6Zy3Vt3mjmc0zs2tU79x9o9/1dWtOypW7+6SZ3S9pv6QLJO1y93dS1tQjCyW9aGZSfZ8/6+5/MrM3Je0xs3skfSTpjoQ15mZmz0laI2mBmR2T9KCkR9R6G/dJul31Tr5Tku7ue8EFaLPNa8xsmeqnXEcl3StJ7v6Ome2R9K6kSUlb3P1Mirq7YVyiDiAi9WkIgAFBWAAIISwAhBAWAEIICwAhPQuLmV5N2jAEujLY5mqYLdvck7Do8mrSWbFDZ4htroZZsc29OrKo+tWkwKzTqxGcra6uW9lu4Qttnl+ki3WZza/UCDG2uRrKvM3/0+f60k9bZNlkw72z87jNUn1n3vjNZEIA+uSvfiC8bK9OQzpeXefuO919yN2H5mpej8oAUJRehUUlriYFqqQnpyEVupoUqIye9Vlkk5Tu69X7A+gvRnACCCEsAIQQFgBCCAsAIYQFgBDCAkAIYQEghLAAEEJYAAghLACEEBYAQggLACGEBYAQwgJACGEBIISwABBCWAAIISwAhBAWAEIICwAhhAWAEMICQAhhASCEsAAQQlgACCEsAIQQFgBCCAsAIYRFky/WrdAX61YkWW/ZNe6bU+tXTmtLYaqO5rba9mHVtg+f83xt+3Do9XlriLzn1DJTtRa17l4iLACEmLunrkGX2XxfaT9PXQZQOX/1A/qPn7TIshxZnMfkyPJKr79bkyPLB7Z2tMeRBVBhHFkAKBxhASCEsAAQQlgACCEsAIQQFgBCCAsAIYQFgBDCogBlvgisU22pLwRrpQz1RC7uynMBWAp562UEJ1BhjOAEUDjCAkAIYQEghLAAEEJYAAghLACEEBYAQggLACGEBYCQOXlebGZHJf1X0hlJk+4+ZGbzJb0g6QeSjkq6w93/na9MAKkVcWRxs7svc/eh7PE2SQfcfamkA9ljAAOuF6chayXtzu7vlrSuB+sA0Gd5w8IlvWxmb5nZ5qxtobsfz+5/ImlhznUAKIFcfRaSbnT3MTP7rqRXzOzvjU+6u5tZy8tas3DZLEkX6eKcZQDotVxHFu4+lt1OSHpR0gpJJ8xskSRltxNtXrvT3YfcfWiu5uUpA0AfdB0WZnaJmV06dV/SLZIOS9oraVO22CZJL+Utsp9STQbTz1/D7tap9SvP+fXv5rZUNbVq41fUi9f15Ddm9kPVjyak+unMs+7+sJl9W9IeSd+T9JHqX52ePN97MfkNkMZMJr/pus/C3T+Q9LMW7f+SxF8+MMswghNACGEBIISwOI/JkeWVXn+3JkeWD2ztaI/ZvYEKY3ZvAIUjLACEEBYAQggLACGEBYAQwgJACGEBIISwABBCWAAIISwAhBAWAEIICwAhhAWAEMICQAhhASCEsChAitnAozrVlmo28/Mpw0znkRm388zKnULeepn8BqgwJr8BUDjCAkAIYQEghLAAEEJYAAghLACEEBYFKNs4hUadakv9K+itlGF/Ms5iOsICQAiDsoAKY1AWgMIRFgBCCAsAIYQFgBDCAkAIYQEghLAAEEJYAAghLJqkmmaubEOuW2kcGt54m7L2Vus+tX6latuHVds+fM7zrYY7F1F783tE3rNx/+UZht3PfU9YAAhhuDdmbGzrKi1+9LXUZcwqY1tXSdKM92vez4Lh3jmkOqwepNOQxY++Vv7TkNFh1UabTkNGS3oaMjqsxY++1tUf/RX/ODPj13SLIwugwjiyyIEOzvbo4IzVQAcngErjNASoME5DABSOsAAQQlicx+TI8kqvv1uTI8sHtna0R1gACKGDE6gwOjgBFK5jWJjZLjObMLPDDW3zzewVM3s/u70iazcze9zMamb2tpnd0MviAfRP5MjiaUm3NrVtk3TA3ZdKOpA9lqTbJC3N/m2W9GQxZQJIrWNYuPurkk42Na+VtDu7v1vSuob2Z7zudUmXm9mioooFkE63fRYL3f14dv8TSQuz+4slfdyw3LGsDcCAy93B6fWvU2b8lYqZbTazg2Z28CudzlsGgB7rNixOTJ1eZLcTWfuYpKsblrsqa5vG3Xe6+5C7D83VvC7LANAv3YbFXkmbsvubJL3U0H5X9q3IsKTPGk5XAAywOZ0WMLPnJK2RtMDMjkl6UNIjkvaY2T2SPpJ0R7b4Pkm3S6pJOiXp7h7UDCCBjmHh7ne2eWrakMus/2JL3qIAlA8jOAGEEBYAQggLACGERQFSTPAb1WlC11QTFJ9PGSYvjkyim2ei3RRa/RTCTHCJOlBhXKIOoHCEBYAQwgJACGEBIISwABBCWAAIISwAhBAWAEIICwAhhEWTU+tXJhluXIYhzp007pvG25S1t1r3qfUrVRsdVm10+JznWw3PLqL25veIvGfj/sszDLuf+57h3kCFMdwbQOEICwAhhAWAEMKiCR2c7Q18B2eLjkQ6OOMIiybjN5nGbwr19xS+3rJr3Dfjq21aW5KaVk9f9/hq05ENO3Rkw45znj+yYUfo9XlriLzn2f2X1VrUunuJsAAQ0vGnAKrmyr+k+So51XpnorHGK1/1aW0pTNXR3LZE9017fskL9+lHer3j6/PWEHnPs/svq7W5rm7X3UuMswAqjHEWAApHWDSpbR9OMmvzIMwU3bhvpnrwU+2vxpqmtY0Oa//4Ie0fP3TONw37xw+1XDZ3DU3vEXnPs/svq7WodfcSpyFAhXEaAqBwhAWAEMICQAhh0YTh3u0x3DtWw2wd7k0HJ1BhdHACKBxhASCEsAAQQlgACCEsClDmodqdaks9XLuVMtQTGYKdZ5h2Cnnr5dsQoML4NgRA4QgLACGEBYAQwgJACGEBIISwABBCWAAIISwKUIZBRO0wKKs7DMqajkFZQIUxKCsHJr9pj8lvYjUw+U0PcWQBpMGRBYDCERYAQgiLJvRZtEefRayGyvZZmNkuSb+UNOHuP87aHpL0G0mfZov9zt33Zc89IOkeSWck/dbd93cqgj4LII2i+yyelnRri/ZRd1+W/ZsKiuskbZR0ffaaJ8zsgljZAMqsY1i4+6uSTgbfb62k5939tLt/KKkmaUWO+gCURJ4+i/vN7G0z22VmV2RtiyV93LDMsawNwIDrNiyelLRE0jJJxyU9NtM3MLPNZnbQzA5+pdNdlgGgX7oKC3c/4e5n3P1rSU/pm1ONMUlXNyx6VdbW6j12uvuQuw/N1bxuygDQR12FhZktani4XtLh7P5eSRvNbJ6ZXSNpqaQ38pUIoAzmdFrAzJ6TtEbSAjM7JulBSWvMbJkkl3RU0r2S5O7vmNkeSe9KmpS0xd3P9KZ0AP0U+TbkTndf5O5z3f0qd/+Du//a3X/i7j9191+5+/GG5R929yXufq27/7G35RePQVntMSgrVkNlB2X1A4OygDS4kCwHjiza48giVsNsPbIgLJqM32QavykUtIWvt+wa9834apvWlqSm1dPXPb7adGTDDh3ZsOOc549s2BF6fd4aIu95dv9ltRa17l7iNAQzNrZ1lRY/+lrqMmaVsa2rJGnG+zXvZ8FpCIDCcWQBVBhHFgAKR1gACCEsAIQQFgBCCAsAIYQFgBDCAkAIYQEghLAABszkyHJNjizv+3oJCwAhHWfKAlAuc/78VpL1cmTRhPks2pvaN2NbVzGfxXneo5v5LMa2rjp75elMfLr32hm/pltcSAZUGBeSASgcYQEghLAAEEJYAAghLACEEBYAQggLACGEBYAQwgJACGFRgNr27n9+rtc61VbbPly6+vP8nF9R9o8fKmSZMslbL8O9gQpjuDeAwhEWAEIICwAhhAWAkFJ0cJrZp5I+l/TP1LX02QKxzVVQ5m3+vrt/J7JgKcJCkszsoLsPpa6jn9jmapgt28xpCIAQwgJASJnCYmfqAhJgm6thVmxzafosAJRbmY4sAJQYYQEghLAAEEJYAAghLACE/B/atTMOrx3OqQAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.225682973861694 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 100000.0} is: \n",
-      "[[4.0000800e+05 8.0000000e+00 0.0000000e+00 ... 0.0000000e+00\n",
-      "  0.0000000e+00 0.0000000e+00]\n",
-      " [8.0000000e+00 8.0001200e+05 0.0000000e+00 ... 0.0000000e+00\n",
-      "  0.0000000e+00 0.0000000e+00]\n",
-      " [0.0000000e+00 0.0000000e+00 4.0000800e+05 ... 4.0000800e+05\n",
-      "  4.0000800e+05 4.0000800e+05]\n",
-      " ...\n",
-      " [0.0000000e+00 0.0000000e+00 4.0000800e+05 ... 7.2001480e+11\n",
-      "  7.2001480e+11 1.4800264e+07]\n",
-      " [0.0000000e+00 0.0000000e+00 4.0000800e+05 ... 7.2001480e+11\n",
-      "  7.2001480e+11 1.4800264e+07]\n",
-      " [0.0000000e+00 0.0000000e+00 4.0000800e+05 ... 1.4800264e+07\n",
-      "  1.4800264e+07 2.0200264e+07]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb689026d8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.07739186286926 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 1000000.0} is: \n",
-      "[[4.00000800e+06 8.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [8.00000000e+00 8.00001200e+06 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000800e+06 ... 4.00000800e+06\n",
-      "  4.00000800e+06 4.00000800e+06]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000800e+06 ... 7.20001480e+13\n",
-      "  7.20001480e+13 1.48000264e+08]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000800e+06 ... 7.20001480e+13\n",
-      "  7.20001480e+13 1.48000264e+08]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000800e+06 ... 1.48000264e+08\n",
-      "  1.48000264e+08 2.02000264e+08]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1c50>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.102808237075806 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 10000000.0} is: \n",
-      "[[4.00000080e+07 8.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [8.00000000e+00 8.00000120e+07 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000080e+07 ... 4.00000080e+07\n",
-      "  4.00000080e+07 4.00000080e+07]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000080e+07 ... 7.20000148e+15\n",
-      "  7.20000148e+15 1.48000026e+09]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000080e+07 ... 7.20000148e+15\n",
-      "  7.20000148e+15 1.48000026e+09]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000080e+07 ... 1.48000026e+09\n",
-      "  1.48000026e+09 2.02000026e+09]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1fd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.14411973953247 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 100000000.0} is: \n",
-      "[[4.00000008e+08 8.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [8.00000000e+00 8.00000012e+08 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000008e+08 ... 4.00000008e+08\n",
-      "  4.00000008e+08 4.00000008e+08]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000008e+08 ... 7.20000015e+17\n",
-      "  7.20000015e+17 1.48000003e+10]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000008e+08 ... 7.20000015e+17\n",
-      "  7.20000015e+17 1.48000003e+10]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000008e+08 ... 1.48000003e+10\n",
-      "  1.48000003e+10 2.02000003e+10]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.30718159675598 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 1000000000.0} is: \n",
-      "[[4.00000001e+09 8.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [8.00000000e+00 8.00000001e+09 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000001e+09 ... 4.00000001e+09\n",
-      "  4.00000001e+09 4.00000001e+09]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000001e+09 ... 7.20000001e+19\n",
-      "  7.20000001e+19 1.48000000e+11]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000001e+09 ... 7.20000001e+19\n",
-      "  7.20000001e+19 1.48000000e+11]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000001e+09 ... 1.48000000e+11\n",
-      "  1.48000000e+11 2.02000000e+11]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f81d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 34.202890396118164 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 2.0, 'lmda': 10000000000.0} is: \n",
-      "[[4.00e+10 8.00e+00 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [8.00e+00 8.00e+10 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
-      " [0.00e+00 0.00e+00 4.00e+10 ... 4.00e+10 4.00e+10 4.00e+10]\n",
-      " ...\n",
-      " [0.00e+00 0.00e+00 4.00e+10 ... 7.20e+21 7.20e+21 1.48e+12]\n",
-      " [0.00e+00 0.00e+00 4.00e+10 ... 7.20e+21 7.20e+21 1.48e+12]\n",
-      " [0.00e+00 0.00e+00 4.00e+10 ... 1.48e+12 1.48e+12 2.02e+12]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f8358>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.765599966049194 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 1e-10} is: \n",
-      "[[  33.           26.            4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [  26.           40.00000001    4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [   4.            4.           33.         ...   49.\n",
-      "    49.           49.        ]\n",
-      " ...\n",
-      " [  20.           20.           49.         ... 1417.00000026\n",
-      "  1417.00000026 1349.00000028]\n",
-      " [  20.           20.           49.         ... 1417.00000026\n",
-      "  1417.00000027 1349.00000029]\n",
-      " [  20.           20.           49.         ... 1349.00000028\n",
-      "  1349.00000029 1287.00000047]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256f2198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.46338510513306 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 1e-09} is: \n",
-      "[[  33.00000003   26.            4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [  26.           40.00000006    4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [   4.            4.           33.00000003 ...   49.00000003\n",
-      "    49.00000003   49.00000003]\n",
-      " ...\n",
-      " [  20.           20.           49.00000003 ... 1417.00000264\n",
-      "  1417.00000262 1349.00000278]\n",
-      " [  20.           20.           49.00000003 ... 1417.00000262\n",
-      "  1417.00000267 1349.00000291]\n",
-      " [  20.           20.           49.00000003 ... 1349.00000278\n",
-      "  1349.00000291 1287.00000474]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.3702609539032 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 1e-08} is: \n",
-      "[[  33.00000032   26.            4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [  26.           40.00000064    4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [   4.            4.           33.00000032 ...   49.00000032\n",
-      "    49.00000032   49.00000032]\n",
-      " ...\n",
-      " [  20.           20.           49.00000032 ... 1417.00002644\n",
-      "  1417.0000262  1349.00002784]\n",
-      " [  20.           20.           49.00000032 ... 1417.0000262\n",
-      "  1417.00002666 1349.00002907]\n",
-      " [  20.           20.           49.00000032 ... 1349.00002784\n",
-      "  1349.00002907 1287.00004736]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.134641885757446 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 1e-07} is: \n",
-      "[[  33.0000032   26.           4.        ...   20.          20.\n",
-      "    20.       ]\n",
-      " [  26.          40.0000064    4.        ...   20.          20.\n",
-      "    20.       ]\n",
-      " [   4.           4.          33.0000032 ...   49.0000032   49.0000032\n",
-      "    49.0000032]\n",
-      " ...\n",
-      " [  20.          20.          49.0000032 ... 1417.0002644 1417.000262\n",
-      "  1349.0002784]\n",
-      " [  20.          20.          49.0000032 ... 1417.000262  1417.0002666\n",
-      "  1349.0002907]\n",
-      " [  20.          20.          49.0000032 ... 1349.0002784 1349.0002907\n",
-      "  1287.0004736]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe2ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.77328538894653 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 1e-06} is: \n",
-      "[[  33.000032     26.            4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [  26.           40.000064      4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [   4.            4.           33.000032   ...   49.000032\n",
-      "    49.000032     49.000032  ]\n",
-      " ...\n",
-      " [  20.           20.           49.000032   ... 1417.002644\n",
-      "  1417.00262    1349.002784  ]\n",
-      " [  20.           20.           49.000032   ... 1417.00262\n",
-      "  1417.002666   1349.002907  ]\n",
-      " [  20.           20.           49.000032   ... 1349.002784\n",
-      "  1349.002907   1287.00473601]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a630>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.08638668060303 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 1e-05} is: \n",
-      "[[  33.00032      26.            4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [  26.           40.00064       4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [   4.            4.           33.00032    ...   49.00032\n",
-      "    49.00032      49.00032   ]\n",
-      " ...\n",
-      " [  20.           20.           49.00032    ... 1417.02644033\n",
-      "  1417.02620029 1349.02784013]\n",
-      " [  20.           20.           49.00032    ... 1417.02620029\n",
-      "  1417.0266603  1349.0290702 ]\n",
-      " [  20.           20.           49.00032    ... 1349.02784013\n",
-      "  1349.0290702  1287.04736051]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.63325810432434 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 0.0001} is: \n",
-      "[[  33.0032       26.            4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [  26.           40.00640032    4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [   4.            4.           33.0032     ...   49.0032\n",
-      "    49.0032       49.0032    ]\n",
-      " ...\n",
-      " [  20.           20.           49.0032     ... 1417.26443272\n",
-      "  1417.26202868 1349.27841344]\n",
-      " [  20.           20.           49.0032     ... 1417.26202868\n",
-      "  1417.26663004 1349.2907195 ]\n",
-      " [  20.           20.           49.0032     ... 1349.27841344\n",
-      "  1349.2907195  1287.4736514 ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1f98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.54682493209839 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 0.001} is: \n",
-      "[[  33.032        26.            4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [  26.           40.064032      4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [   4.            4.           33.032      ...   49.032\n",
-      "    49.032        49.032     ]\n",
-      " ...\n",
-      " [  20.           20.           49.032      ... 1419.6472735\n",
-      "  1419.62286876 1351.78534411]\n",
-      " [  20.           20.           49.032      ... 1419.62286876\n",
-      "  1419.66900512 1351.90895058]\n",
-      " [  20.           20.           49.032      ... 1351.78534411\n",
-      "  1351.90895058 1291.74114165]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256f2940>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.84195923805237 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 0.01} is: \n",
-      "[[  33.32         26.            4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [  26.           40.6432        4.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " [   4.            4.           33.32       ...   49.32\n",
-      "    49.32         49.32      ]\n",
-      " ...\n",
-      " [  20.           20.           49.32       ... 1443.76870688\n",
-      "  1443.48756    1376.974512  ]\n",
-      " [  20.           20.           49.32       ... 1443.48756\n",
-      "  1443.96152288 1378.265576  ]\n",
-      " [  20.           20.           49.32       ... 1376.974512\n",
-      "  1378.265576   1334.875648  ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.495763063430786 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 0.1} is: \n",
-      "[[  36.2      26.        4.     ...   20.       20.       20.    ]\n",
-      " [  26.       46.72      4.     ...   20.       20.       20.    ]\n",
-      " [   4.        4.       36.2    ...   52.2      52.2      52.2   ]\n",
-      " ...\n",
-      " [  20.       20.       52.2    ... 1715.6528 1708.44   1640.952 ]\n",
-      " [  20.       20.       52.2    ... 1708.44   1714.7888 1659.776 ]\n",
-      " [  20.       20.       52.2    ... 1640.952  1659.776  1813.648 ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb246370b8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.454060554504395 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 1.0} is: \n",
-      "[[6.5000e+01 2.6000e+01 4.0000e+00 ... 2.0000e+01 2.0000e+01 2.0000e+01]\n",
-      " [2.6000e+01 1.3600e+02 4.0000e+00 ... 2.0000e+01 2.0000e+01 2.0000e+01]\n",
-      " [4.0000e+00 4.0000e+00 6.5000e+01 ... 8.1000e+01 8.1000e+01 8.1000e+01]\n",
-      " ...\n",
-      " [2.0000e+01 2.0000e+01 8.1000e+01 ... 9.1250e+03 7.6650e+03 5.5890e+03]\n",
-      " [2.0000e+01 2.0000e+01 8.1000e+01 ... 7.6650e+03 8.4950e+03 6.7820e+03]\n",
-      " [2.0000e+01 2.0000e+01 8.1000e+01 ... 5.5890e+03 6.7820e+03 1.2811e+04]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.75584816932678 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 10.0} is: \n",
-      "[[3.530000e+02 2.600000e+01 4.000000e+00 ... 2.000000e+01 2.000000e+01\n",
-      "  2.000000e+01]\n",
-      " [2.600000e+01 3.880000e+03 4.000000e+00 ... 2.000000e+01 2.000000e+01\n",
-      "  2.000000e+01]\n",
-      " [4.000000e+00 4.000000e+00 3.530000e+02 ... 3.690000e+02 3.690000e+02\n",
-      "  3.690000e+02]\n",
-      " ...\n",
-      " [2.000000e+01 2.000000e+01 3.690000e+02 ... 4.739057e+06 1.074417e+06\n",
-      "  2.755890e+05]\n",
-      " [2.000000e+01 2.000000e+01 3.690000e+02 ... 1.074417e+06 4.328477e+06\n",
-      "  8.014190e+05]\n",
-      " [2.000000e+01 2.000000e+01 3.690000e+02 ... 2.755890e+05 8.014190e+05\n",
-      "  2.210647e+06]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.70102143287659 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 100.0} is: \n",
-      "[[3.23300000e+03 2.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [2.60000000e+01 3.26440000e+05 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 3.23300000e+03 ... 3.24900000e+03\n",
-      "  3.24900000e+03 3.24900000e+03]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 3.24900000e+03 ... 3.03369858e+10\n",
-      "  7.88943417e+08 1.25719749e+08]\n",
-      " [2.00000000e+01 2.00000000e+01 3.24900000e+03 ... 7.88943417e+08\n",
-      "  2.99503080e+10 5.95792049e+08]\n",
-      " [2.00000000e+01 2.00000000e+01 3.24900000e+03 ... 1.25719749e+08\n",
-      "  5.95792049e+08 1.69987489e+09]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe26a0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.31402778625488 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 1000.0} is: \n",
-      "[[3.20330000e+04 2.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [2.60000000e+01 3.20640400e+07 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 3.20330000e+04 ... 3.20490000e+04\n",
-      "  3.20490000e+04 3.20490000e+04]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 3.20490000e+04 ... 2.89507275e+14\n",
-      "  7.62870621e+11 1.13346785e+11]\n",
-      " [2.00000000e+01 2.00000000e+01 3.20490000e+04 ... 7.62870621e+11\n",
-      "  2.89123007e+14 5.77952908e+11]\n",
-      " [2.00000000e+01 2.00000000e+01 3.20490000e+04 ... 1.13346785e+11\n",
-      "  5.77952908e+11 1.65314474e+12]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f81d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.52541899681091 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 10000.0} is: \n",
-      "[[3.20033000e+05 2.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [2.60000000e+01 3.20064004e+09 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 3.20033000e+05 ... 3.20049000e+05\n",
-      "  3.20049000e+05 3.20049000e+05]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 3.20049000e+05 ... 2.88150433e+18\n",
-      "  7.60286826e+14 1.12134428e+14]\n",
-      " [2.00000000e+01 2.00000000e+01 3.20049000e+05 ... 7.60286826e+14\n",
-      "  2.88112030e+18 5.76195029e+14]\n",
-      " [2.00000000e+01 2.00000000e+01 3.20049000e+05 ... 1.12134428e+14\n",
-      "  5.76195029e+14 1.64851405e+15]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2466cb70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 45.6383421421051 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 100000.0} is: \n",
-      "[[3.2000330e+06 2.6000000e+01 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [2.6000000e+01 3.2000640e+11 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [4.0000000e+00 4.0000000e+00 3.2000330e+06 ... 3.2000490e+06\n",
-      "  3.2000490e+06 3.2000490e+06]\n",
-      " ...\n",
-      " [2.0000000e+01 2.0000000e+01 3.2000490e+06 ... 2.8801504e+22\n",
-      "  7.6002868e+17 1.1201344e+17]\n",
-      " [2.0000000e+01 2.0000000e+01 3.2000490e+06 ... 7.6002868e+17\n",
-      "  2.8801120e+22 5.7601950e+17]\n",
-      " [2.0000000e+01 2.0000000e+01 3.2000490e+06 ... 1.1201344e+17\n",
-      "  5.7601950e+17 1.6480514e+18]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb246377f0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 44.595426082611084 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 1000000.0} is: \n",
-      "[[3.20000330e+07 2.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [2.60000000e+01 3.20000640e+13 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 3.20000330e+07 ... 3.20000490e+07\n",
-      "  3.20000490e+07 3.20000490e+07]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 3.20000490e+07 ... 2.88001504e+26\n",
-      "  7.60002868e+20 1.12001344e+20]\n",
-      " [2.00000000e+01 2.00000000e+01 3.20000490e+07 ... 7.60002868e+20\n",
-      "  2.88001120e+26 5.76001950e+20]\n",
-      " [2.00000000e+01 2.00000000e+01 3.20000490e+07 ... 1.12001344e+20\n",
-      "  5.76001950e+20 1.64800514e+21]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.45240020751953 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 10000000.0} is: \n",
-      "[[3.20000033e+08 2.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [2.60000000e+01 3.20000064e+15 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 3.20000033e+08 ... 3.20000049e+08\n",
-      "  3.20000049e+08 3.20000049e+08]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 3.20000049e+08 ... 2.88000150e+30\n",
-      "  7.60000287e+23 1.12000134e+23]\n",
-      " [2.00000000e+01 2.00000000e+01 3.20000049e+08 ... 7.60000287e+23\n",
-      "  2.88000112e+30 5.76000195e+23]\n",
-      " [2.00000000e+01 2.00000000e+01 3.20000049e+08 ... 1.12000134e+23\n",
-      "  5.76000195e+23 1.64800051e+24]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb68902ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 44.201547384262085 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 100000000.0} is: \n",
-      "[[3.20000003e+09 2.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [2.60000000e+01 3.20000006e+17 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 3.20000003e+09 ... 3.20000005e+09\n",
-      "  3.20000005e+09 3.20000005e+09]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 3.20000005e+09 ... 2.88000015e+34\n",
-      "  7.60000029e+26 1.12000013e+26]\n",
-      " [2.00000000e+01 2.00000000e+01 3.20000005e+09 ... 7.60000029e+26\n",
-      "  2.88000011e+34 5.76000020e+26]\n",
-      " [2.00000000e+01 2.00000000e+01 3.20000005e+09 ... 1.12000013e+26\n",
-      "  5.76000020e+26 1.64800005e+27]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.103229999542236 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 1000000000.0} is: \n",
-      "[[3.20000000e+10 2.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [2.60000000e+01 3.20000001e+19 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 3.20000000e+10 ... 3.20000000e+10\n",
-      "  3.20000000e+10 3.20000000e+10]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 3.20000000e+10 ... 2.88000002e+38\n",
-      "  7.60000003e+29 1.12000001e+29]\n",
-      " [2.00000000e+01 2.00000000e+01 3.20000000e+10 ... 7.60000003e+29\n",
-      "  2.88000001e+38 5.76000002e+29]\n",
-      " [2.00000000e+01 2.00000000e+01 3.20000000e+10 ... 1.12000001e+29\n",
-      "  5.76000002e+29 1.64800001e+30]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688e5208>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.929738998413086 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 3.0, 'lmda': 10000000000.0} is: \n",
-      "[[3.200e+11 2.600e+01 4.000e+00 ... 2.000e+01 2.000e+01 2.000e+01]\n",
-      " [2.600e+01 3.200e+21 4.000e+00 ... 2.000e+01 2.000e+01 2.000e+01]\n",
-      " [4.000e+00 4.000e+00 3.200e+11 ... 3.200e+11 3.200e+11 3.200e+11]\n",
-      " ...\n",
-      " [2.000e+01 2.000e+01 3.200e+11 ... 2.880e+42 7.600e+32 1.120e+32]\n",
-      " [2.000e+01 2.000e+01 3.200e+11 ... 7.600e+32 2.880e+42 5.760e+32]\n",
-      " [2.000e+01 2.000e+01 3.200e+11 ... 1.120e+32 5.760e+32 1.648e+33]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb68902ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 37.003591537475586 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 1e-10} is: \n",
-      "[[2.000e-19 1.200e-19 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.200e-19 2.000e-19 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 2.000e-19 ... 2.000e-19 2.000e-19 2.000e-19]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 2.000e-19 ... 1.052e-17 1.052e-17 9.840e-18]\n",
-      " [0.000e+00 0.000e+00 2.000e-19 ... 1.052e-17 1.052e-17 9.840e-18]\n",
-      " [0.000e+00 0.000e+00 2.000e-19 ... 9.840e-18 9.840e-18 9.220e-18]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 39.74063420295715 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 1e-09} is: \n",
-      "[[2.000e-17 1.200e-17 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.200e-17 2.000e-17 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 2.000e-17 ... 2.000e-17 2.000e-17 2.000e-17]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 2.000e-17 ... 1.052e-15 1.052e-15 9.840e-16]\n",
-      " [0.000e+00 0.000e+00 2.000e-17 ... 1.052e-15 1.052e-15 9.840e-16]\n",
-      " [0.000e+00 0.000e+00 2.000e-17 ... 9.840e-16 9.840e-16 9.220e-16]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2466cb70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 38.531572341918945 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 1e-08} is: \n",
-      "[[2.000e-15 1.200e-15 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.200e-15 2.000e-15 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 2.000e-15 ... 2.000e-15 2.000e-15 2.000e-15]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 2.000e-15 ... 1.052e-13 1.052e-13 9.840e-14]\n",
-      " [0.000e+00 0.000e+00 2.000e-15 ... 1.052e-13 1.052e-13 9.840e-14]\n",
-      " [0.000e+00 0.000e+00 2.000e-15 ... 9.840e-14 9.840e-14 9.220e-14]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 37.05235052108765 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 1e-07} is: \n",
-      "[[2.000e-13 1.200e-13 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.200e-13 2.000e-13 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 2.000e-13 ... 2.000e-13 2.000e-13 2.000e-13]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 2.000e-13 ... 1.052e-11 1.052e-11 9.840e-12]\n",
-      " [0.000e+00 0.000e+00 2.000e-13 ... 1.052e-11 1.052e-11 9.840e-12]\n",
-      " [0.000e+00 0.000e+00 2.000e-13 ... 9.840e-12 9.840e-12 9.220e-12]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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Ke5hqTEeOWZhy8Tp2IO3K56t8LaBT8d5+R2IiAOLjT+4kkIyuNgd/12lU6gOQd2D9Qw2xdLbKInU20Jk4bYwsjTFW3qmXkYwjnAHtpkCsKT6k9oyFqPeWCHS5hlyc5fECaNTB+P4jBW6l+Bupd90XBZJ9tCheFmadZz+oapwnoAbevF5JlTOmIA8OuTWL2ibv61pJHUgGYPa825cOjGFP448ur9SLVY+rPx57dDJwnuhEJzqK7oVkAeBacMg0gGrvWI7FLZftGzeEsNf9mTFzDLo6DXT2Bry1GcNL0IdUsCB7xkXrJ0za3xQ1azNxqUbJbWJu3xBKMqx4QKI79PeRlG1HzfgOrG3tgjaJJ4/ZjMZp3LwPXLsx1WsUIxArNWk6zvzJZZwijV3FKI/xuudHpJ1r3T69/muge8EsJEbI0DexIfEqpVBLqL0apGWAK8BsEmqjaEBXD86LkdRERNMzq7Dl3M8siXOij2J49NGeoY4cq6pD3BjpaDYrMRUmtlf5OfJNq2wKGTAFADGUmJI0BzpbKQCrmh+QsACLOdwXPv9i0BegIqbFOJjYPAxtuHiNQI3SenEmx2SadSpmV7+ZZ8NE3T3qZg24DQD4K1/ax2YY1Z6TmOwONrfaflCdJ26fmVOIeU4y64AnGq0rUJWOHBc70Ve/rF6pECGdLzaLyjZChsmYd6ra9APiag7a9GW8LqmvdZq+ib1GEjiLxpYR0LPt/hwA4Pu/AmFWz5jNF0A4n8NdlngemXm1WdjfvqxJ/NrnwNsxA8AAQP5pG8H9IroXzOIgHQpGsp+qYCXzdjReDzsmxgLaMjJubQ9CDe4KoXg5rM9qLBJMD4+QWPISyBiS54GQnV/Di0FT5qkAql0ZhTGhH4rnJSbbi/3eD2oBr9eIuAV9pbmSeYZs5xpHfakOSSyYeHGMpsbmYVAGNE1qE9VDcohZUCzxHjZvGDBJGwtjuCZQTczqX9tfDthUmnPyTi7q6dhVL5YZflMbbWb6kqc8JsYY8nUqbxUZo4oR9PSq6P5mxB7H4p4H9t3G1wWSTQMcbW4+BZARZQ8H7Qa4YSwennRcA/ZrvCEC7PrGS0NT290L6P4yi9r7YWSLVHk4Wq9HZflNWAzDYeQ+uZIkMJUsKi/HdldJFqXP7CHx1U4965J3o/Lve/9ib0XyVADqoTDJgtLDYh6WqWSBqNLVngRgD2n98o5B4cyVhwIDt2qMPdBjekluIFlMd3aEoPMK+y8tullZD5OoakwHs6IWo6gnon6IzThokuENJQs7VmZd+yLNZ0CF2ZHVIsPSZeaBCSbDXOm2BuIZtB0Uv/G6JItrVAc5W0IcgUIVSDbrkmRRJad+gWQRzufgjYd0lbv7wJpdR/eKWTRRp5MHtsFdNGoEDksWCYtR2zyk7/f1uJtKFobPqCQE1R1VV5Wx8rffpWQxlQCMUdWp72znPBDunb9aZjDbtWvsQ913Ta9JspAJ9oIMolzbaibr04zndUsWz6+yi5eMIeoAitSTwV6JEW97xUbctWThuLh4bQwh3kyyGBVnIv52ksXJG3KiE53oKLpXksULQ9QX84y7MAyF/pB2dZJmN8oiK3FJovveu1kfDR9+1F7c7CCW/CaEYv2vr9X5Zkcj7zUatR9AJOD33tHu3n+0v2tMkt9Ivbu4oVwXSAFd+1xfklRFq2UD5d1LpgvorslUrPMAMPTNsWZ7oXceADEeh324RfIbqfJU2ry5CrM3j8W1SWPOloiP0j27JvmNHPJWVR4ZmSa/6fsGT+FWyyIhBG7nmBCYGfhnIQIXZ8Cjj+4++U1SU+XirBh6v/MBsPYZI6OTeEHyG5fwH828jveY3Ctm8dopSnGtAq/HlXQwnXqBnNMNFv+V6Rj3bJ3QFihrUv8O6MtwA5H0tVMUCKdPxOvdgXdIUqtACfV54CD9pKTivOGEQbrZ3fKaIc3pls/o/VJDrvMb14cce3MO9RFCWbBXpXjNON/UA3STOUyljkNSyD0ije2gfVvJmyROhuA6R8bUBnWHWdavo5vYGPboFcd7PyQLAsCuKU/Hq1Vxo6EYfuIHjzRxjYmD3quBqo49ANRAaYlpEtWqh/va9+mXQaHAspiBxqAJUQDg2aWKfrEEl1HXQXa9GpGqWA5aLfILaElk+Af/XGNoAgB0PlunedMXa/kYIEuNJfGfXGq/F6tsjKJhzEYp2uwgy7kaAifZnKTzjQWe1lvFCwxjntfBcwBIStojP/JDoKGFOWeLenpxwsLDbUfQENqozSGAh1DuQ22kXHTZ8m/niEi+Vt2PpL6snYYAPHmO+K//K7rGtoZjROyK+7Wx8qex8hBBUSNiw9LDP0nGTBGEpXo0fMI2RGbEVZfnxes2qYzOMcVlrPT++w+e4urf+QvoLnVdoyPEGcNvAsZFmRPbeZ15Q5L6FwQQIM7078WHVQ5UWz4CAhFix/BPd1mN2PzbfwG7dx3mT8r9CguG20R9p6Rcx/pz24BQjSs+OR5ncb+3mBOd6ET3hu6HZHFTqpOpStQdagouMlBWuEYtsB02ZRWiYVSXmRkgDYYbK/05BAU1oYIcp3DxLOkYnHhXwuhztKYIaDT/ehX6HgXozSWcrpV0Zho1cMhwTDlvxHDACBwn+mw/aNs4FlvKoXMAREvVthnaPpjymC1i0iWJgIZKpYsoUadGNbR6KFGUee2GsYRTjy2Wo26nUYFvvEluacMoBEk7swHt0jo7zhehMYKGqOA0orwrUxAwEaTjLMWQjOpKHiPgQ85aBQAyVFnCUFzOtBvgr0JObceeEUcHtx5AY2VwtxQAlsW9Y+3DzGlp7LxL94dZxwEAjkBjBHsGb/sssXaXI8QT/LpIFtxHuF1UMSC2kgVFAe8CXJXv4iY2tk8ns6jxBMRFxzU6ZgEqXbTRT2trteMUpTeBGR9BwgSS6hp53PvfhW0caFMDOtab2YwrgZeOHskNabqWVT7L/TWrcAcsgKFaJ0AfIdmf+23HVn0K6b+8GjlvSHkptUJa8vowlXwSKC+veVHoGg/Py8dVX5vK3/UyxBY7YmoCSFUme1Ty+Fx5fq693wyIA5of03WFCMRtJnA6mAr5eLq/zGKaKLYGEnmvOTOBlM3K7dV5yAjIA7kmAEAWCTFpNovVQndry3Ox2SLnETDAkmN14c66nM+AAMj5qoRtW6j7+VKlBZsLVP823ZzXff5OQ0A40/H4lGdSVnPQegeZuQYNSCGU608zUHe+yVVAKV9DgyY8cA4AULIXje8sW5sFKhuDYYFWHm49gnuX4wxIks2iD3lHrMPX49l8zz4hZ7OcXLaOVwDQtHMfwDGif1dd66b38xARZhVz9cZEygvCgwOJHjuuHOY5bF4QzjqEWUGLSrfAeObBQ1T7wFVZq5iuw70eO57pui36EesvdZg/NYmBEGaM7sphWJWxuSFJcGmMYUaAABzS+qR2TuUihahBcw7vzBE7wuyJz+u4/uIMm88xltUajAuC31Q2Cd+ymW4TMSyreJGuZewvovvLLIDGwLkf95EWNSa//lSaMM9H7S+v+shirkGhk0icHzTzzDRitWg2JaBiDim7Uu4vian9uGfgJFNrAL1eFZ/BfSjXBIqIPwZNxkJVX6aaTI2VIs0DRimbFg1jUXkOnFOPm7dDC0EmyshaqXZP7kOTRdqYRaOaZBVFk67sQZtjzA8+T1TFup2GAPQDeJvWNon3FNR4aV7jzCy47NQ8iqoiUeCYyhiCiuSQYrSkIcKna/PEwElDa+DML04/oFvHrArEjkEj9O8adDqq9ywzupFAAUUN8frFmFGdsFeY4HtlYLwuOInuKiLMCX5dPdeB4CsDZ+wqySKogZOqR4DC5L15Ad1fZsFVsBMwkSxcm4NzHEu+TEDFYyGFbjtXINw1GMl2VBOPZ52Kg4skMVw59STUL6l32ROSJYt+0OxKlmbNvDczXyQj22Cdy1Z1ro6lGBGWnWYySlmP4szrMVX+RQDqOZl1mpl6Ks5PJAuMQduIsgRx6BwApd7nomvsP1J5Q8xmERYOzhPEMeLcJAsB9Qyuxd4KEBXnHuRbbwiigC3xzFSyqNqZGTTrEJa2NpVkMefywlkWKl8Ym9tF0MjgUTBcOHBfMqSFhUdYMLhPa0CUJAtWyaIaz3WShZ916M8ZNNrYCOOcAHiMlWTBY/J6pE7DnDQbgo09Heov0/PjuXiPHIHSi89DlxnXcO6we8ioH9Ew1yxhkrTEUDk7KCZBs5IsmlIBL6GTN+REJzrRUXQvJAsiBnUesqvEWlJzjFVgGt//IP8mfV/UkISnQAiaCg8AxoDw6CNcl/IOAPAs4RkSdJs2W/U0XKUdznZckWKwE1EchaUBBDR93uVVTqOXK5N9+GQveKgx8tVBSQD4Sdq903V5rfU7KF2XQglqou0OePTxgUA1alKmWdh8DT0+dA6AXMSp+/aBKld1DlEgR4c2UZ9JxZLFvM2+nebqprUtAOCjx/k+umsS9roUbBZ3OyxszQ1qH6XU36j7NWkMUDUuqYNz74rkGATuUu9HjtL86Ak6y/L+koS9nUUdX63xLlf5Ook0QnUY28zjlvncok6dK1nbRRDOFfpu3hDh4qUBA/yhPnd1wt6Hl5/HxbIDb6soU0d7amT+ut7mADgjd3UYXn6I7gWzOEhVxmMAaELWrVIYkhEvRG3L+Q3x0oS9hrXPN9ASnNZhxWYkNcbkj0/Yi3mp9CSNpfwAs7AHzHIyohLVLdFrnX/CO2A+v5OEvbJatPaf2jtj4CxO4f/9WNqiqh21ETc/tNVLART1yy2XN0rYG88X+fqAMj7pHGB6d1b3uAkB5+0AECHOfRsazoTYObiUxt+tFrdK2Du+u4Rbu3ztOHNwm2FSCkDtJvYsxLkv2b2BDJQy46R4AvVFDek2K0wT9g4PlxgedI0hFpSYhXlbKibsOvfpT9gL4FoD5bVp9dJDLyPKg1VjJ156vepBTh4GxVmYMVSrk1EVI0AixzufKmMmxbIz511xUjdE7BwzkAIHkZA1PuNOyHbAeh6JqWWjrkfOmk31cSGq8XecjNsYXIXJuA1lHd5MDMYkskG1xLkYg6cxKiOTCKYAMWNmjBDP4Ch73p8bjyvEylAYk/Gyxf5QSOOwtUzMg1LYQLZlJaOxDCjnXwPTphDBg4ArSWKaC0Reo6Xh/jCLl1ETDFUiGEEJlDWJdHxZ3ZBSNiDVudhNxDHDONSxKiRH1w1BVduk7Jph4i+3rDrJTSZSpblLv01yRmYmdEflC3m6DtNM2kCJuB1DVd9ECtMz6ab+bag8PSYZ3LR84bbfO5aGyhBuL2JtEI4RtBtUdRodME+G7TGCxljg5IBC929RN8Q927V1Q1JKPtdfr4ZQUkOEFZxlQm8GgrkyLrgIulzvqSHucqcMp1JDwIlBHsjubWrIqXzhiU50ojul+ytZvKjIEDvUJQWzDaEyxL3UZtElndOMdFZtvSrHJ97pjm/nMR9vs5h1Bw1vWQ2pU90hGTbrXd/+Fk7h2ybCJ//XXdksFvOJrahCdFboQkS0RjzDpHhXCvxUmBXbQfP5APiGNgtZzpvzEdW2k/u167l2nc3oK/PyjIgTwCWbRTqfb2mzCA8X4GSzgCN1925cE9iWpdTKJZxtFgLEZLOwqYlncOWypvN9m8V4PsfwYAa/rqRJVgxMlsiqtHqfCZvFwezel1qqLlp27xyFuoBst0Xs7zr93nWIT0shIn7nob6Q3udUeDlxDVDSyFlE6WKuAKv08MdPngBd16oYXafeGTNIAppSbbkArtYqgq5S1awx7MVhwPvyMm93Tf5LEn0RYor+5PMz9eQYMtXWZrsFLRbAw/M2HoaogS4DKNGmVlUbSXyu6o7aQ8/JsCkxNuXvAFRp2FL7fAba9Wo/qVPXj0G9TNNoWwC8mJe1trk8PC/jcC7HM6Cy6AuReg3OV1WsTRunka9vL8YoVexOLMcGBn/8tMxrMQN7B7pMEc2fe4C48KBRcS9m+ERErhpmqkFcdJDOwZ2p0TUzLKiniKQYM/UESfeo2iAq+4LbJC/aJ1d7awcA4XPnSZVathupeaasz44r5k7NhrT56hm6yxFhXjGXP/ysIDivoTo5r32viyXrD/bkVVQtak64aw3gPOn3AAAgAElEQVSzTh8w2zG4SvdfXcsYRQ4ZH1hvel1SD4DMuyb/IYAmhFw9B+k7U4Gfm/chJZc1AFpmMi5laOp8i+oEmhB4nW/yrkglMdluxqW/vDYiGip/Ddw7d7vodIOchKhjCIrKxD7V62HzjgvfQsAP6NniGRgJNAbEtEYlXLzdvafj1GNCPjauOtBlQSnJcgZxDpwM43HhEZYelODeNLPylYLoGSSl0llcet3F14ThovQZO0b0BO8Y47IKUU+oU4NfX5ewl9czHKKw9IiOFGRmksXKY/fQAbFKw7BwcPWaVM/DuGAgeoQalHUDQ8T9ZRZ7CVuqWJEalWnf6yrqSEwkUokdAVojVRXbAegOS6jES+eK6FlfyxiFHWfxJJb122JDEiK0oRphmdCVgO6eMk/jyQjQhAqdMrG+V5fuvGvStoGocVsC6i2IM5+iKyt1oXZj2guRmIoygnbtp+jKcJakEebmN2ZuPSQ11euRmUVXGHKdz4IAzoxFDX1uCDmHRI2mjFVcxKE4Bx7KseOZh6/ym5h0wDttC0uPceXAA2vMSKWO6d+A2+m4hpUHGHAbh/6CQQmaGTtSiDVTi+C02JAEvw7p0w2T2I1nh/NLjCuX+7Uo4PHcYfeA4YaydsOS26TiFdx7OGMIA2MdG3JCcJ7oRCd63XR/JYtp0ldzGTpNjmt2BLMpyOQcGRTVKcNQMl1VqdmtClXWo4EcFGbn532luhbtenXXGaZj16ubbbvLRiUAoOfrm9kskp4f0/X5cq19mu0j/S79AKy34MruoBdU1CJNbBY8eO077YgWZZuNmEMl6YjAfXK1Z7NojKZQUdlsFvVvNAZgu2tdjvZbVaDH5u2BYhD2LkdaNihEouz+9I9bUBeFkL9rHwf2vspm4a46vS+JXDLQms2i6xzclYKl4tyDkx2BROA9K0DOkvuuO0TP4HWPs/+PMxJSvALCeDuiW1SgrIwRMaNlUkMmeVius1nM07lc5aLwa4Jfz9A9K+7u+dxpgFyiui7IcKEArjDfj4Y9hu4vs5iqIXUVpcr70ISib3fVMTN9+WuvRFVDg1YJDWjM4XyVg8IAAJdXpRBRdS0sF3oDTI1hRrxYatRkil4FALlYvTCEPIePA8AwQsxQ9ux5GQ9QCvrk0osBtFogPliV5ChAym3Q6vC8HVRd6cds+OTdoA+sQU+SsYuhL3R496yJJgUOqyHuqgP3oVVDemUejRchkZwty3qkeY/vrvLLErti4BRHBZzkNKDKXe0QLlKI+o3UkJiPHc88FlUBnnA+h3QOPqlH/edWqoaMgnHF6J4Zs0hqSBQ4CyRLasH8Y8b6yzPMn7ZqiF/HI9WQ9mVdXpOLZfvFpfa7Kfc8LAjrzzmsPq4YwpLR1cdUasjuIWP+zGFY0cHfX0b3ilnURYb2JIthUFDKOAI9v1yy2O5KSQGLDakfYmNGN5QscLXW3Tt7J3bKKHa92g0SwyIrNFPT65QsrOhNTc41Own1gwKEarRoAhyV7FKJeV2uISJwjt+cZFGlAHD1NYiKR8UlO8iuL8bQO5IsZp7RzTtgjOgWvnhDRMsIZOAcAHelxmT/ZIOzKHcuWSwluVBrqWHubiRZzJ55+KsxRwoDyMzvGLpXzOJ1U86gldLdE8kegvFWfdaUK4ElA+zbykh9KPtUHlOLm9BAsMl5RDl4722RFf7VkOzqxa8RmXc9BkpGb6aSQUsUk4Gx8tTwvqv6rseV6QZGyaaP9KzKLR/Re8Us6iJD02IrqlaMcO+9i/DR4yJFWFGbENuoUiYA6o6zkoL83jsJix9zFu7s509l93I+inGsYjPKtWS1hObGrIrmDmO2WdDFuZ7y+MnhCM+q/zoSlJJEYpJJBLI0hRgLIGrQcdKsayWLlBqwYWZRc082GcJ2vXqKptDrs6Xuco+fZAmvXctqHgn7YRG7ue8XlC+s4ek5PqLut09jF9Ex1XMTUfXwoyfteVHa8nwvKV/I3kGuimSBdSoQlXA43HnQVmH6vCvlC5v6q5YkyKlXTBadRuoeKF/ILyhfeG2RoSrDfU3OnpXlLMd7+A8ew308a8oXYlK+sL4//N4D8G5Q+4ut2Xi8ZHHyhpzoRCc6iu6HZEEA2CFeFX2NLy4a5GFM3H/87vvwX/tqRmDSfAbZbFTyyMFcosbMQe0CtpOF9x+V/n/wz+n5KchIzpcNFNZ9+ETDzEXKrpGAUjKvMmU9X2uND9uhH+vuF/7VH9gzFIZZyVnpL3sEy185RIznCsaZfecTnefnL+Aud4oz6MeMQ3CXW8SLJQIzeNcaEuO8ywZLAHDPtojzDrwbEBOOg3dDo2oEa//2IwiA3Te/nrNB5X6TEdHE1/HcwV8GuF3MlnUSNSLybixp6qr0euP5PK+HzVuYtM4IkoGzorqdhwD30XOsv/Xn0zwTXLyXXG8DqIx1TQ5OjezkQTCcMVbvl114PPMIc8L8Y20LC4fx3OV+/WW5f3uZss51vKs/vcIHf+VrmD8xQy0hzAjdVcRwVnkdemnGGGcABGATUNObeP4dy9uKrCoK6ZzDjDF/PGj2bgCP/+L3Y/NFwvJRuaPDitCty98VXgtCQHclGM7K+ozfPp4F3A9mcQzV4lqKFcjf6xT6+fiQyglWId11H1VUJwlpct2JITB/VunhMI6KuLQHchybtPx2Le5DMciZ2E1URLmxlB2gkIrz1AjTISZ1JzYlCqyNJOx5W7i6PgBgGPV69pm+T8+x9QJSjsZhIsZOYlzEEdwQ8wudDx2Cpt2v1wvQ0OwhFGOjvdMoIdlTcbxu17Uc4VMOzpBsUMoIapHavohmvQbAOwEHAY3JJZtVS8DtAgCXQ7xpo/PlISKOWiioLI/dV1MnEsPaDfBrgd8kb8cIUID+XcUi8aAQcDZvyKh2o8wQDP9nOSxqZsEABwIPAr8p96dbC8bnyNe2eXXV37F+w0UT9jZrdoN0ASc15EQnOtFR9OmRLKZkrk/zQBBV2Iy4L2lc20/lzQAK+7T6HLEYJW9a70KmfdZUtxGlOg9og4+Ytd1iUupj7zIBTm20rNYmB0Elj4pUgVG5iA9QvAjZqGc4l0n/NyzQu1+/JBVTnnQjrlpHFoild3Cty1JIE9vKq3qwqP1+MN6CAKkPpPZYU/Hyp+csiVnC3kMkTCUiuRqLJeytPR/X9XEsnSSLE53oREfR/ZYsmixN1XdXuYesmhgzcgg1oHkcaCyfmOwgFsSVAqssL4LUUsS0XyLA+7YAsU/fLZDMjKkzt4fJkLnLhjwaYjFGDoDMGBIrF1nHkIFyaHTJf6ltkdwep98zcPZeDZzpN2B/d8jtKQo1LBy4r9cdCF11bShyEKKIxoygjAIHaASwpQGorqbFgtL32phpOSmnEaN1OxOo07T92pdJOtyUAjB0pDQ7NoODQAbBOGfMrOgO67lhzlnaCHPGuGJwT3qNWMaUDZxJkjJ0Zpx3GFYE16c+Ok3Hz4EbpCQPhgS150P/zlkcnd0PMyZTMZozQbyiSHkXc3LjYUUYzgG/qQyWy7IGer12WYW5MXC+sahTIvoTAM+hb9MoIt8iovcA/M8A/jyAPwHwsyLyyS36bqTLjEkAEkingGNA+6Adizato07rl7eECHNmFoixwKUTs6hLxwlThmnXsG2ZVchMq78xO/Ayd648dB3nF4Sj5Beyy8zCAZyg2WOVgJYoowSnOA6ZuwadxzMPmTtNbJvaD51j8wD0hZmCduoHGNBQZxqBECRXBMu1P0eXQ9yb5DcdF3tnXUk8LVKdY0EHX7Uz4CpmYS+cY8E4LyK6tUsS8fP4heBYEOaUoyyJKXkYKI8nLByGJcM5QZhRU4wnzO2a6UVNkZsydxjPCOPWxpCYxYiGWbi+HWOcQ70hg36a1yJXWGu8IYRxQamgkMvP/rAijGeC8bJiFmcoyDJJXpdExhiG8+o9OD73zWtRQ/6SiHxTRL6V/v5FAL8rIt8A8Lvp7xOd6ESfcroLNeRnAPxk+v7rAP5XAH/zpp2I4fBtp51UB8/GsTGo228ShyF9n+JIqNQfrfrgTcJpjIrl4HXfuhiTy7SOk6AQge1ODXfWvt3prmwIzHQtf9mXQC/bLIYItizO26HgEWKEv+KmvKGWqRNgO4JCAG0lj4G2o8ajTNygrvfgOv381Rau11qnzqpuHTjH1gsAZk+H/YpkO4tnSO7C0cHtAngbclIXrUgWmxoWtQvVXRW3Ze4/uUUBgK+pdcqp1imtt5g9SUlqqopk7qiKZKJlDKPLGAUKUXf2hcClMbtd0DU8otaprZt7tsXyw1XBWaSKZLPnEX5bBZIdWZGse56e1UlFsu4KqdbpkF2nq488QIzF4ypw7EpxFtdWJNtEDM/rADccTa/KLATAPyQiAfA/iMivAPiSiHw3/f4+gC/duveTzeJkszjZLD4bNgsAPyEi3yGiLwL4HSL6583ARCQxkj0iol8A8AsAsMDqFYdxohOd6K7plZiFiHwnfT4iot8E8GMAPiCir4jId4noKwAeXXPurwD4FQB4wO+93AM8RXCWjtLvdSIYPhrBqVWiEsIwVOhDAIdyQh6L4KQhloSyduygxky9bgRMBIyG2CzHUogqBth4rIhNSgbD474a8joQnLwLbWVtKlkFrUq525KK9UPM6e+sGrmO23otKgqPVeEfU0fGeCMEZ1YhLIp4jCmhb0JXjkka8VQhIgXcaxEgXhQpBEFzU4gr5/tNuB2Cc4OcZ4KCGlz9JkKqnCyqBhV4NwUCpz7r3d0qxMOh5O10aR4TBKffCLorgt9WyN+o7aaGcHW7KbwagvPWzIKIzgCwiDxP3/8KgP8KwG8B+HkAv5Q+/96t+rcEvFZkx3I1DtDs0kgybeeBIeXErCIMaTZrPgEArihoskzyWa+Zo8LZDNwHhGUSy5+wZm9CsfRL50EyhyxmJWfmGCBni2zbsOjR8XyW4dDGWGTGWaT3VwwxT8IQMVx0+pA9TerAaga37iGOwX1JjEshIC46fai37YsfF77xhvjUxtsRMeVWOHQOAPhPdD2Gh11O1KJjr70X2jYsGX7L8J5y8lcKAPcM74oaYvklSATjWZdftJypiSlBrve9IXW72wV0uwG7d3QA2RsyMMYF7ashXF5At9PjeBRsH3JOm0+RMZ45DEvK9ocwY/QXDNerN2RWJdbJ3pCdXqy/SN6rZwtsvkhZfQ0zVdPCjBqvA/fKLKyfsAAoEii03hu/LXEzxrTFEaLTc4UoQ8I3X2CsvyJNmPy4ArpLulYN6S7bccXDKT8P0qtIFl8C8JtJL/cA/o6I/H0i+j0Av0FEfw3AnwL42Vv1/iJ0X5WEpKkYdhNEYC1tcGlrkJFWRaq+1k0oJ/NJp9dCi0j528IIojQlCylIkS7s6Q8RJLjbvBN1jEodAl4JdJruvmqzOVT3o0nsYr+hIAlfeQ6Cxkhon/VuWSq5ARxQSTdSzr8hkvTQOPK16zHVAtpkjPY7ReUT2TyS51CqlCHI4RwWVR97bel7bQS4bR4Lo1szCxH5IwB/8UD7xwD+8k36OlRFXY2YY6mi/sGH5RrbXXkgd73mVlhvtRALAMSI+MGHkBBBm032gtT5LvwnlzZgwDH8JlUtv0qGz84rnqOuFA4gfvQY5Dhn4Y79AHr2PGe4snwUFj0KVJZ5ooyjQIzZmAkilSiqwsj+ecq4tRnU02BZm8xz8+hxVh3ykrGDrzJOSd/DsQNi0E/g4DkAEJ9rOr/VH120L8+Bwsgrg3PfoDDybDdmZpELI3/45OgiQ7LZ4MKMoHWN2FcojNxdDm1h5I+e3bzI0JPn+FL3tdzHqxdGTv1PCyN/8AzTIkP++edvVhj5qt8rMvRnz0/lC090ohO9Zrq/cG9usz7lehoxgBbzkmNiPtMcjfNZY4iksxXQD5pRyo6tEvrKRZJCLLflag4aQt4NeJ1ySQAlp2TnwednWgPDKnldriHnK/ClZjgyiXD8/EXGUeRrdpx3XV4PpVhOiAgrzZ1hEsX4YAHejWqzGELegXg9IK46uC+8ezAhcJzgLNSmMzbJgafnAMhlDfsvT8ZNlA2bNoZx6eC2ms8iu04FJfO0qRuxfFrxHlsH/XwvGzKnSYHrdu4D+JPn2HxFs5CZDYVHUTvFAZuF2QC0yvgCFLRehl8n21IQhKVDmBHmnyQ36KLDeHYczmI803VbfNvj6Q8tMH86y2MIM6C7mmc3po5V18WKDBnOQiupI7szVx8WO5fZjsQBYfXeHs7i+deX2HyesXhc7vk4J3QbKTaLKiGv6xeKs6jqhoQ/OR7CeX+ZxZRqhb9OG2Z6cQgAkmhIlMsFCLBf4RwoqcgkpUxbqxqSl9HsE43eLTmJLlVqB6GoH3Ytd7krfeSUeJRRMBRE/wYUzrzuGy8E70bVf7djqrJd2RGG+PJSA0BJClyVPzx0DoCsRvknu+Za4igzYcNCuJRXgrcDaEzMJsQsvk/VEIoCdzVk/dk8C3XZgWlS4LqdxgBZbzF7WkR9/SKpZmirhkTPhaH0UUsDEkCjz/o9DxEcBJwMqADgH1/BXWnCXnguFc1RVKdcCuCqJD9affgQ3WUCjDlGWDC6q7ZMII2S0vOZ2sE5xwYIGcBlCXdix9n7EzvC/NFaEwFf7fLzv/xoDgoes0qVEFYDqKSyhnURoW49gncB8zokYLKhvYjuL7OImlz3oE2mrnsBJCbgGkNkU9Yw7GtbufzgGPQmzhTolRPVAEUXzkhELi9kVRjXMmgBKIyhc029TgCAL7o0tmPJRh31JQOrjQLQF4K2Y04Um1P5DwME7qXlEQGzIXh19ValEvfOQfE2hYXPyWB07MVWYUwjzHW3lypGx9yEdf3O0okWmS6I1nROVSpxr/Rg3T4E0HaXmVVmBCEiegK54jK1cWZQFgNx4fKLyjY21n6Ei+EvLmZa4jCVZeQ6lqgqmQggV0ejyw7jkjUmBmprCDMGBdeUCeRBDaom/ZhERDF5ixba7teVjah6bMPZTKWdqnbJuGKMywIIA9RTJPkRoIZZiOvgOs72Eb3G8VbP+8ssXkShYCcoqsdCJjU2JShc2z6nRCaOV/U+qDIwZs9IzZRSOnsByrXGUdWcseoPavwzqSTXL40RGE31CM24uNe/bVfnIej3UbQ9T0y0nuhu2JMSqPamAKqGpTFnr8ChcwDEXKB3aMZFzBDbfXy1NgkjkZcntYkvRrwC7xbdwSb3gTZ9gdOPhyULjEmyGAN4l8o2WO3ZKFr4JwtwhuwsVdS5yujlgawnUohwqS9jjrzt05pHwIdWshhaySIHzu0G+KuY1RvxBBoFft3iVTioZBG9BcMVF3PtsTApJ6ZsZAAggeCuerBn8LbPG5O/DJh5ytcGANcTeBdxqIq636hk4Sppgm7gCbo/zOKaQcuBFz1nvAbybkcJrARA3YtHSxapDys0bJb+MFQMycAzcjPJYpKsRSrJgrbVjQzJqi+cvR7CqToXszKK7EUR3TnvULJoMj4T5QfcOFac664rUnZ5ANpG7cMPqGQVPWeAUK6dcVPJYp48VUmCoDHBzU2grGwrOYkMlxc4zB2ceRuYsrqSPRS3lSxWDA6p3StUnKStKWqShY0xpGMoavu4MDWkMLwoBv2+RrI4c+jPOYO3tF+G85S9IVnaAhD9q0kWJ2/IiU50oqPo/kgWU5JWbK1rWTSVxcZRxa1xVI+IHbPdtarIpA/aJIOkiPqvza9vEkKqt0GpBigA7Wu7VVUlRWlKPyi0PFcySxGMl9tyXlWYpiTpjcUHTqTXDzEfy+tU62QY0ADPRFTFeXoJmWAmwK4xFErfA+z0OC7epOk5tl4A4D5Zt6qX47zDmkTgrtIc+hGUkaWSbC+uQZvab6p2pS5ToBo/fp5xC3QNzoIqnIX/ZJM6MLEhSWRTE0lXJDgeYlYnrFq6jinC7bT8otU0dY+fgS+Pw1nwZerr6SWWHzyEu0rHesVZ8HpAVxs48/pYMFwyzBrOIh3r0liaEo6e4T98voezWK5m8JtZ47WxjOlm4KwlB7ce9nAWnw0D5yShjYnPEqFMwXTvrlOdvKtjcSm7VxvXaV3ecDnXQw0YY2n+LcX/dqdw7ypsHJ0HLRatGrLeat1UK7ScHqZ4sXyhgZMmBs64ULg3JzVExeEIgVO7DJUXNM478MPzYnexOXU+qxUAQOutqiHDWNSNA+doe0qH/+6q0bVrA2cW12dObQG7Mbs8SVCygtsDmtQ/iVpoOK+HqRxyUTKgT9SQup2GAAIwvLvU61cGztBx8bLUaoiF0w8Rru9AUTAufbYJqFrCiDNG8S4+aNWQdWWzyGpI8lAkNcSLYPPlObrnRUUKc4a/8gcNnNkbYiHqQFJDtH3xuMyBBzOaMkAPVA15ustMePPlBTbvOiyelrULHcHvYs7TWhs43W4Otw2NGhL/3+OVi3vBLCRGyNDnKucSBTFVZjJkodURoflca4akOiKYR6AfIMSIjwtq0n3h81rhfD4DNroj0WqZLlgZLodR1bsUW5IDyR59DMyVoZRrzYGH5/pSWmi3c4gPVlp7FMjFlAOzputHMYZFcmXHixGREuZiVClDAEVmAnBfeFdrksw7rW0yLzsZPzxHeO/8YAHjGq/g5x3iwoN2IT/shmbM5yQ7gDdDZ+fAaPut62UC6vbjIUlGJnWQMnT3bFuYc00Xq1znxMLi+y+cZdxCXeBYCMVtOGNwH+FnPseU5DomfXteXUMk9xUJ49KB+4iwIMw/2FW/qiRqUsH2yysM5ww3aAaw7rJsQHGm3guLDRnO1JOy4ncau0GYMUIHUGT0dd2QtCSWX8K8IjwpjFwbKzPtIq6+b47YEbqHPp/TnzH6h5QlNR0XIV7ZdSlfBwCGrxC6y0lh5ANrdh3dC2ZxkF5kpY21N6RElx6sLRKqdldcrnmHNQllGHUHrksKJpG9vpZmhQ7FeBmjWs/rOiPQaMQXRoVOIkFzgJepCSmSlZjKJ1SNoGFs6pIAKr00dUkArU0yhKJiIWEfKtdzU/JPBLwb95jQ9F54T+W46jfuQ17HKdXrYVd0267MQVwZl0GWAXCKWEWQDIWuI0BjJQXFcX+XrKuog6kpzCQdg6LLbX4bVPxP5xjDUhenei+MuQkj1yHpriL8Ol1nELhURb0dR8KWvKSKunl8puQ3HWQQuG3Mkt/sStPtza5q78b1VdSFWQsQ1TErN4g6PRk4T3SiEx1FJ2ZxohOd6Ci6v2rI6yAzkmavA2PPdH7jPmn/k6vfDlTyviuSyvZwbSEj5j1ZUxwBsUDNgYTreMWluRXxZB0jJfEeuV3qNb5DqosY1VgNAkrOCVtyQlO06E2QFXwSf7ydoTm/mDJuRfeXWRwCi2QXZMmrWefaPJin03J0Tih7AUzn7rzaE6ydKLsV62uJYz3WrPeONW5gUrXMcl/WVOfItPyYQHpHUhKaHEqe8npK59UFZl4OdpDOq+vtBTk+AbXcx47BscRrSIwK9EpVrPI8EkQ6zv3e2k/zY45LpxmdmPbyabre75UbmK6HzbvO95kT4qR+8nme4BiQrcO4tDILyVjr6KUGTuufHWFccb62jkONpry28WgOTtdHjHMCL8zTowZPqrKmjUtGdISZJwxnnG0PZuAEcJSBM0xsFvP54VdyXDGiB0hKiYL+jDFcEPoqMfBwRk0ynNrAOa5SiYK3lIPzzqipE5L+zt/rWiBVfZDm5bG4BasrMiV7+QyDMfOKmLR6IK5gFpprcarZYVgCZvXrW1k8G3eq11FTXdfDanoAavS0dstHEa0WSed1jMbEfGEWe8yoqksCAJzGJa7UKDEDp43N0JmWWyMs3d4uPs1iNS4ZPOpxzW+s8zpUWrFeD5t3XaMkVsxCiLLh1Nqdo+zyq2t42HfgsGXfOcnHDktuEhpr1GlpCwvNvCXMCHNCSIyGhFLfBJNM9TiNvRjOCS5lQA9zjTql2CbGjbluSPo7jZVLUfc8pkM0LrRfHhnM5pEhDBeAX1cej/MJo5/VzAKgkbS2SKKbMIuTzeJEJzrRUXRiFic60YmOonurhsgkzLkuOpQLCAGliFBPhwsRWREiINsgAEU35uOg4j31Q0mGk/rM39O1aBgVvBUKXoO3g55bBbO5Z9sXFgHKBYAAYBjzjbBiP3S1LQWN+iGDxaTvQest/LwrId+AhrdXRYyAlG9CEix7KPgP8Vyg1xWUnaKge7Lbw1nsFQAaOrirQZPSVL9xH0BX2xYmbXNPkb22DgAwq8LZ4y6pP3ECdd5psR3qR8w/SejWKhFNY7Po9ve+Gmfheq/3JZ8g8J3LbbNVB+4deBS4FaN7lqJcpUSJWrJcHhxiR3C7iNUHAfOnlodCgVB+HdFtJghOVLaKa3AW3ZMdDtFixtpvhaE4eySg4LD6uNyv4fn1OIvdljF/JhgqtYUPwzoO0r1lFlMjG1HKoBzjcQZOn3Rn7wqTYAKiRYXe0sCZcnPmjFqDojml84rdN1vAXRs4F74BZYFTBGVlnSdJ+SkqyLauTYnajYs0hrVX5OwbNHCOSwceCyqzTtjirLqYI/BA4LG7cwPnuHLZWNmfKWALACioPYRDSV4znDmEGeDX7o0YOIczTtXMOHszhiXdyMDZP1CP11ghOD8TBs4parCJ0TgGwTmOmrA3xBITEjkFl/CtEZyKDJUcXEVj0J17DACXfBJ3jeCkXYvMBEX1etTMoh/Vvmv1PABwP0IiZwSnwdQtk/kbR3CahJZeRAoC9lRS+5GiJGkId4/g3ASAVAoQBlyuBSKgwKBQJAtN1U/g/s0gOLt1h+hVsrAXnOLNEJxhxuiuZJL9/ODlDtL9ZRYvirO/iev0gNsUEm8tWWgJwxJZiV3i5BN8xV1LFnJA5JZu33UqXkX97Dodk+s0Z9pO65PUvDcpWcS5268l4tWDxVVwmBvUQ3LnrtM5Y1wynIsIHcFZ8Jjfd52GRcpCRXgzrtPlq7tOw6TE1I0AACAASURBVIIw9rd3nZ4MnCc60YmOonslWVi+CWLaE32tfof0fVOS8Do1RIaUdm6o+OHQ52NuHUjWD6X4UOqHdykVHZFGxOINBJJthzajFRRwVbeZeM39CLHkuWMEnGQDp9k9KBmE36gasvFZTaDAOZBMuBg4OVUT520Pv0kSyV2pISniU8sdAl2VJ4IHzSliJQejJ7DXRMTdVXf3asil16jTy1Ayt3l/IzUEYMwuY05LCAD8mVBDpnRInXjh4aT6O1WgLGJdnUMgrWPJOc3rUEODPSs4i6mUWbz9FY4jomZNNO9ki1YVz5pDI3IRTZ1WiqekrGYbh3PIsv8bpJL+Ls1HdNy2cQhTQcneNVHJhRFmxchKAuwlkyGkFHpvYFyw9dH1qlWvm1Ds0vzqQOMbnP/pYRY3LR34onPkBux0Sskb05ZP1E+KOKiv3xk1yYQJxNJeP6bx1qUEIpRRTEoJ2nFvi7QkY0q+G0oYNYnCrZuC1Xc6Dh0DV4mA69KLdflBq/vxpsYlibM2hatvQvacVnUMb7IFn2wWJzrRiY6i+ytZTL0hzpX4kGO9ISEWvAU0a9Ir4yxmnYrFlsdw0BgP6b26+dhiBO4YZzH3beIaTt6QCk/hRBAXHZg5ez1o0HoftmsGq67e+TfuDQmLYrMI8xTLk9LX1ynxeWTQ7g3gLJYOw5mD6yP6c26KPscZJReqNg1nrJXWF/4N4SwcolNpxtSIm3pDhgcEDpOYlZM35EQnOtHrpnslWfByAUDh1TKxqJP3kHGEe+9dxE+eZGg39b2Cr/q+OSdDtMcxeyjonQcZ2CUfaa5LK65D63VTMT1utiDL4F1di1cLIEopHDQGMAC6XKux80zzfPK3H2FasZyr7NvS9+Cqsrn/JNXKTDlHKQat0O4YMdVBAaDlEoc+58zM800GQlcbgmMEr33rvekHnaOl/zOJJUW3zv74UalgbjQxLs4sCfKkwjxCULj69HwA/PQyr4fNe759J3tTOqdGWIqGDalsQlCj5/IPHrXjmVz/UG6JXB0tpGTMT56Xac1nKiUm6P8yfA6LTrNuL1ZdzvpNFtYfQpN02Kqyf+7/vgJtUvgos0Y81/VlgVL8ye5jVc29Ge+zq705AIBbvwOQGlQNY3P+B1cI53MtlWlrMPOa/d3+riTN3RfP4K/Gpu2PN8fbgu4Vsygp9w8YcFJpgINFhw5RbB82bYttxa7bUJQMYLL+yUotJrQh8Aa8IenaRrV4WtpEvQr1eKOo10Mm6xPegoEzSjuHpiRl+/3WRr0bjQfZCNiM59C47JjxzRheEQFwetZeYS1I5NbP5v1gFgSAXc7oDQDunYdN6UGraxE+eAT/9R8oFdGXC8jVGrRcgK42pcv5DLLZaJX1VKw4fvBh/l1+5IcAALzRALDxnSV4O+RYie7bH0NWCyBEcJJMZDHX5DHLWT7OfXKF8O4ZnGO9CY+fAAB23/x6LiBsFBYuIxVnT4ecn4F3AcND7W/1RxcAtJq5f7JDWHi4zZBtC+6TNcK7K83CPfHJx7lv8iF0T7SKF+/GnMX70DkAVKIA8OzHvlYS1SayallG/YX66/0mNr/5rZbx491EshBgeDjL62HztkAsYJL8Bmja3S5i/v4lPvm3vpraEkahF4xVPouYckXkrFYA3FY9Kq4X9BeEiz/7XB5T/8AhzAmrR2Oe1+4Bw++03/mzCq9g10zZvXcPdLzv/sst/uzfu8DyI8nHhQUweyroH5SxufS4Wj6LMNdxaXV1pLgP4OEfv5fnkKHYBPRnhDgDlh9F+K1e6/1/c4X190WsvnuRrzOcAd1lWcdQSukADHTP5xjK4Rj+5fGWiPvBLA7RC7N7V7tgjHs7FICS1TuEg33lIKxU7IcGFTGbor7TfkU0BmQIJfX/GDTa0qJVYwEMTetocF+lagsxG9+0FqiCfgpoTOuecsocnnewtMsywj54iqmxQnEfFIiUPnPb9BxbL+hLyjWzYIIza6i9gDsdLw8CZ9gMUeARDbG4Pau15L7MgVP1eIqUDZlTqtvdTjOZu769j/nvLBwVDIRJWa4XcEhgqWSk1LEJXK/p/G1cfkOIXuB6NWT6TSu52dwBIPp0n4cAv1GmpMeJzmtbCtfnsQpAI+X+KCJHfUaLdRzKWts1hYBuDYRA8JsSn+LXgL8i+LLHQkjbrXxhHVWqv7WFh07ZvU90ohO9djoxixOd6ERH0f1VQ5gUyXeIaqgzURGl7fMYVF1Vf7SBbk/zeFaRhjeFnNt4cp81zLbJCo5c0cus5SCFHWt7BeN2JW/lnVElptbXksrxYdmvrY2C2QrKvCR90WhN5Dm8tvGbuiHlbx1bUUPEniNSUb+pGm7n36CS+HXjyNe2Pqs2ayep2qhcv7axlDlQ8QS5a8ZX9bHXRihZyV8T3V9m8SKqwUipEtdeCn6XQFrOHXwYiuuKIUSQzkESIMj6bT4BgAmSwtNzjU+v33NB4lwPtOSMyGHNHecEtLJjhOQCc3E/y5N4ynEnMsQMtmJrc7zHFGPnmgS6PEsh61EKeOrAOXm9oMbMbKNIZMY9eyjHBYGDjtkClcjrAeIjkPRkWzkRPdYAcDbXOqX91MA5bfedy+MYq/GMcyoAMzPmUcUURFICHTWA5hePNaFN7CjXSB2XhGFFEKf98liPr10DKwEYO4dxCYyLclxYANxrglwjdjrOMLfj0NgUrF9bT2GAbKykiW7iTMdosU3jChjPRNsSjSu1meRxVyWAwWonOiXsPdGJTnSndH8lC2IQvcAnnHZCcaySRQW1Bh2vhohLO3jajcrOoyn/KX1H/jxsvZ9SFslR72ZFzRFX1CfxBPFJlK8qlsfOku1wEU89t6L0XdBE9cgivSu7XnSA+GpuERCvlnaxor/mDYmpJombrMcNqagW9qlSACoXo/WfvQteITq6npQh4aY2RX/78TTjqtQI+7tRAShpS5WqRKFVmXTs+hk95WLL8ZrxqRoo7flcVCGKeK3iwEmyONGJTnQU3V/JAkhGzvS9hvV2vuSf9FoNTLxrw21nnYKx7HPSRwY5JQNmWGkgmAGGhClJFygSgCNgroCscGaJbmcIZx14rQozJef6eO7KjlWlYjMQE48OYaHtbqsFcABglaSYcengtkFtEFURInelkN+wYPhJGbtx6TAuq8QmgwZfeV9S0h06B0gQbigwybAE+ZhFq6/3D60Pzro7CeA3DBqRcQDBsCiiFbUcF9sAoPq937RtRnW73xC6Jx36i/ZYtwXCEgVnkewB9U4fO7Wv8A7oL0ohIoqE/oIwLimv2e4BYfcuIWwI4xKo856Ue5VAWe/q38OFx+7zATxYoSIgLNWS2b9T1tFtbc4JvLWKoEgZayOpGNLwUWWzCOX7cEEIc4AHzn3s3hPMvrRGvzkv9+rhiNj5jLMIi+peOkGYM4Z3Crgi3oAD3G9mUVMdb1ADrQymXMPAiTR2YRzL56QPlzJT0aAlDt1aMz85bw+TqkANnDcCtOtb++quh7vqQAnladfylwFuKMld05ecP9HtQn77eBT4LTe5EQztqICvmBMEA5r9iYe4h8akUbRSmPVxNWjbbtQoUewjOK3dSiLMLmMBBqWxc1q2WHlD/FYykhBIKMmdNKhVzvEdgN9U/aaX0G8lIzVdfxjB6XpFcPJ2wOy5Ad7SMalygwGLwtbUuvIS+I3AbaEG2VkR7XkUzC6TgTkxt/lTld/9TuA2EwRn6jsz0nTvuucj5o+XmD1Na7QFhp4we4omb4TbAYhANCPt1umzIIDVeLXxAjp+TnucfhfEGTB/WhCc80881ucrLJ5Wz0bv0V1S9r7UVdpIgO454HaVEfwzUQpA4l7tECMaQ34paXCQcdTPnP1bdGM5AsFJgz5t3DtwH0owUtCs3RgLOhPDeDSC0+0iOF3D7BQUBcFSwm1LejQaIrynXOMjn78dII51XPae9aO+8FXquUyvAcHZvNRIen32XuSTlFmsAyi9NBQUpel2sTA9m595JPrYtINvhuC0F8nCxN2QLP/WXbL813YAt9PjeBSEjuFTCjrLeqWoxtQ241shOLvnQLdOEsOoEkG3lsYLx70mRwqG4ExMrric9bhuXWcPL67T6PYRnN0l0D1hzEpsHMZA6C6Lq5ZruDdeDcF5f5nFiwyczMXA6Z0aNp1rDZwvc52ayzCpIeYKNXFfVZtk4ByLyiMxHuU6rV2Bpo7EGSPMijSR8zIwISy5MXDGGYNGzS1hrkcAILt2VQ/U6LW5Tqv0euIqd57VzMiqB2e1imJa6lHKy2tBdbGta2qqXq03HuM6NfXDXKexV3XBHvhozKIycIoTxF7doOOZrjMAUND4j3FJ+Rrj4nau0+EMGXId5jomHjROw8h5ZWoxqUrjojCM2kBpKp8aONO8HCF67LlOhzNgeBDhL8s9H88EEMoGzjhhFifX6YlOdKI7p/srWbwsT+YLwodF5Pjcghb6K8j5HnNfFq586Fovodp7W/JfllyYJCVoDJJEa0FxAwq03gdxc11KuSHvFMVZjz0kwBXK2PJaVfYCDXBL485qSPkNUtYkZ6e+qcvSzs+frRpSH2fjyp/p2Kz6her342/rQWo89XJ9O8n+HPIYqBxn47OxMyQDx/aue2ju6Tna+/0Vn5n7yyyA65PfxhK6TkFzXFAo5QEaW8XLbBYhADFFnQ4BZIa2GDVJbJ3nIcQbRZ1ObRZ1ChnqY/6bhgjuNdWdJablqopYY+CMGs1Kd2Wz2O7bLExWlaSn+416TLiP2cFkNgseDtssXB+zzSIzupvaLJJhL9sPbJx2uew9kIM2i3Ej4J31IfA7FdfNBgDczmbh14Df2DpoQly/KZgJoNgszMNhUadTm4VP/as3pDBVCnIw6rR7zuiqfDkkGoVqNguaGDA/9TYLIgZ1HlI/OM5puO8DDb4PKbMVgH1pIoq+yGcJXxsC5PKqFExOxtDaYMp1iDqS12EI+aWUxRzSOfNAKXkHPLvUF9rsGNud2itSfg27Fu9KMeK8aQQGJW8Fb0dIMP05wqc4FKlyWopTWLd4KSnz09v5ssLLAErx5WFsijBPzwGQCzL7dSilAwEo5Lz16tCo3hq3i9m7oCHqLTOgarekKtzfvCTuWV/qg0yLL1ft3AfQeovuMoXRd8Xu43ZFsogVVNoWnROjoGC7tUkWGmLvqXiE5le9ruEQETuGr+qG1MWY63Vzz7ZYfHyG+dOYxxBmgu5K4PrKwDlCXeC+uI0tOzjFUiXM1lOohKuLE8w3EbEjzJ4MeaNbPPYQZiwel/s1XhG6jRRvSJWD0/WCbhMxPK/d6zia7gWzOEh1gBiwr5bkLS3V6rA6IUjPSUh1SQMXl2ndR+1pcawVyWsm5FiZxRiVSSCJzWNoYoRk1MJDYswjmJcllsrnJoVEAapixnkH5uQ2jdIYXqVzKjlxiX+QLhls+2GvmI/UKf8BHZeIFk+qiiJNz6nHzbvQiq6MHOthyEzb2ZQBlLlQlFTXIjHEzHRicdHWXW/Lg8+TDGh1Ow0B6IdyXesqpTcsKkXa9Wcl3oMi4LYxMTDO8Si66wowo8JY1gN8ujZ3DrwubxKlYlXGSPOL0w/qMt7ZmhCE1N1bJ841hmXSGaBJfqNL0o0Vd7f7PAna81cjYsfg9ZAxRuqqluaF76LA7SQbOGvXqF9HuG1opI2bZCA7GThPdKITHUX3V7KoDYBTMlsEoBJAiCBXZbk6Jk9nnWkLULdrXcwmpMxOIlnloBuEqFNlGM0SBjj3QTHmEG5FLWkBYwOBUZTyvZKCyKSlO6T6egLOUpS5QgOzqhJRqvgP6E5PRaKobS5W0QsAcEDKOIoqiULHI5BKtTARgUY1Cup3lX44luxe1k5Macd/NQsnV8ZICjous0kYUUDKf0n5HEhSyUKRJLhaG37JOpnNg6vxB6bGuCuvscrcSbI40YlOdBS9lFkQ0a8S0SMi+v2q7T0i+h0i+oP0+W5qJyL6W0T0h0T0T4joR48eyVSKSBmz5VBG70NeEvOQ3LAMXza8mSSTv6e+zBtSu1CPIXO9HnK/TvqiprxgTJ4YtQFQiLrzpb70+w1M2DelyRSpHq+NIbnkaDJHknrMKiXRGJOXR/K/G69lNRYrL1hKC0qTu7SM2caIxl2thYIkS25q+HzN2cPNjpPHW3ltBO0a2zjD/j9bp+tKJB7qN5d7bD4nbtxb0jFqyK8B+G8B/O2q7RcB/K6I/BIR/WL6+28C+CkA30j/fhzAL6fPmxNTK/abQXNM9RhsoQyhOeva87uZLrJ9ApAqNkRSdm4MahyNZ3NQX7Jgu61m/YZ3gFmlmcGLOWTe5etRFMjZstzQnXpFxvN5SdibqK75YAFhAMBjxHjWAQLMUuxGWHq4qwHinVrnLVlPCDrGi1VTERxAU/EMAByRVgLbDaX62YFzAGhdD2gW7gzLBoAa7m3Jb1YMv/n/23u7UNuW7DzsG1U151x/e+/zd8/tvt1qSbY7sdx2rGBZIg4CoZCAQ0DkJcQPISR2lAebvPkhIeCAMeQhPxACAYUYxeDY6C3CGAWESewHW44cTBQJtd3pTt/u293n3PO7914/c86qGnkYNapqrr3OOfvse8/tfVtrwDlr7Zo/VbPWnDWrxvjG90UREFbkJYvjUx5C7a8Cc/cLV1KuVUWM5jkqta96VpebMcCOHv2dpKLelMhBqEiG1KlZR0NsB1CQZdM4N+iyQ7aoiuUksG4Gv7IwAyO2NEFG7kdD/Eq2LTYLbB6YjBgNrSR8hZYmyl9m1OhE2q+jNHhJW3Jy3Fj6TsOsICC2LUJr0LnCiL55YLF9WBz7gJynWSenLRdUK4CkDL+nSNZcf2n9xsGCmf8+Ef3EXvEvAfiF9P1/BvC/QwaLXwLwN1hc7P+IiO4Q0ReZ+fvXbtGrrB5dK5xFZvcOJWoh5YK7oLiHv0iWE8RClIiKsnu76kHZmwUQM+A9qOKlgPcSjtTwrIYHhyARFiDP38xQxjhh907fo2AWJnWN8kZGYvfOXu0obTf9eCUMaqr6AQCjl6r1M33fP0b7C0Dylk9DpznKkEBU1pCs/4dYwqSMcg16qIYpo4Qvc3REow+9L7iPvbdnXS5hbQ+7U19ICZ2CY4F7p7uZDTLgS/Ad4kOItswgKKSwK0qI0vYJlzJGRG/gtmWwj5rTowOp4lb6Ec2mJNWZIP/cjlGDoIxP/dAUn8VEWDl95HCpqb47iWSYkeG2Ib+Emg1jXFPOS5HrwhtDp1RpFn4W7N7vVwPADwC8n75/CcB3qv2+m8qOdrSjfc7tE0dDmJmJ3n5FRES/DOCXAWBGy0M7THEWk+8lkQzGCM4iYS1So1ALJquwcY1cUzwDpbr074xzIBIAVEROUGNLIqPYuCJN51wWMU7XBQAIrS2gJOXlbGxJCAsxT70pRIROEJwKuuLGyNsss2lpOjUl6bzXCy/Lvi7vV4sw7x8j3ah8DDbregCYZp2mt3VOZoqck8IUY1F75pGXIylpTsGiraJf3aRvJlaXGwI1LieBhbwMIYS2YFDqmUVm5TIGxsl0388Jtk91W5akrxmhacsyyy8MzJAYteKBZYj2wcLk/huXlAFYugypgVZAWoZEqkSGKGuMCO9EOv6itEUjJHrfhtbA9DHzgoxLwrgC3K7U42eC4j00swid9Efdrs8ikewREX0RANJnEqHERwB+rNrvy6nsijHzrzDzzzDzz7Q0u2Ezjna0o31WdtOZxa8D+PcB/Jfp83+tyv8SEf1tiGPz5XX8FRwjeBwyyxRHBl8K4D2+EFYRlTMkJ/Bl3goYnwDwOIKcm8gTmi++Lz6M+SyPzKbrSp26tk5reF62gofQNeSTZ7BzETnWusx8Dj5bIc5cli90APzdBZz6GnQmYKgsWav1eGa03vefGAIDsB+L/CE392Cfr8HzFrQdwHN5JZlnFwCfYHhvCbubOnVreUQAaK1JjFtNYdraur1j5G8VKY4NTdihJ23WYzqSNbkp6EflFLXnA8zuAIaY5pl4h7zUuXuvzc66fYlEzcGQuiJaovyWDFmykCcOvFrKUC0GcXzaJEl48rK0jW0DNsiw7ssvdxhOCbYH/BzoXprJuYmRfRP9qVy7GRYYV4UJK7Zp1uCnM4v6euQTACjLGqq5g0LFjMsPbJoJtdmXMS4J4xmLQzPZeIIyw871pG0roD03GAux1qT/3mRvHCyI6G9BnJkPiOi7AP4KZJD4NSL68wC+DeDfSbv/XQD/JoBvANgA+A+u35Q3WO0AmzBlVQljk/1jFQK9ukrKiWS+YqSqEsQm55zUlRK5MklOAoPtEfWY8fXygvvJXTlxKlTtSUlr+qnbaQxTecR07loeEUhOVC+K5OqYM2Oc7JOdjimkafv4yuQuNbelg/vZPuR+3LdJf6TrrqUSJ+rvFbALMCKLGGIhv6mSuvaBT/umEoe2Z0THJScIiTGKTS6zA8PuCHaQZKuJPGIKP+pD77bCe0GB0awr8psgSV/NhieQbavObHWUev3tp/fmvs5sLt/Z5JTlvNRzG0ZzQXCVg5PN9O+ak0O27S09Ps1EMmb+c6/Y9K8d2JcB/MXrV3+0ox3t82K3F+69b7VCWc1+VTNi1WYTm5Q6QJGWHoq5UIdaygKNrYWJMWMfbH3Oqi62IjKUj3fCRmU1bDtUjrnXMFllFitAHIUVQ5e2h5KgEXypj6yKHFUeMAAgwTzEahkSe9mPAuflCQUzSUzT8ib10SHGqv0yP6fMmbm/zaR+3Le6P/S6RdCoWlokbAAbwKUpmHBIGjhnJkS/gOwXqqXHoWVIcRIKu1XtSA2dgZ+VMmW5YkPpGnWNVbJEdVbm53Lu2BiMS8Bu95YhAfCL6q1uDy1DkDlf6zYdMj+XBDkzluQwvyCMJzK7yPstMRUZqpYhfsUwgYRNa69/rmOfn8ECEml4q7CLSQ+G5mPg7by/h8+JyZqwliFkY94qf+QT20Qt7cB2g6kWih5DhExYmH0sZpKx+pkbIUvuSSSKc/lEYewdWuaVoBSNyPcNTyUGtb2WKl7Sd2xUPm/aF3ngvGFXfq4Gi1eS4bzKEmy6ZtC6lg7qa8+JKfBIIc+AOEg/yweuriseuAOULyEwoG+wPdaqTFDzLiHk1zHFMDGQWbcAYQziCrz0Di0zS3ECTFVw6iuQaU4w8bdgx/5ExuVzP3HuupZT+W/YlZ+fweJNCmWHzNqiWAadmcS3n6FMzpnezFUUIKua2UoV7R1brXim7agVz7QsWoJxVM0gRCtVl3RZAc19Nu2+YtqPOmNLTOATNKbDBNL8riwriRnBbChWI5Pq8rS9tcLZOzcqM5+3gWjXFh2KcPMN7PMzWHCcErVcJxoSgkQqJm/gRAxyw2iIQqFNZo2KCdqdaPEzLd67jYbYPk5g2flNXL2BzRBgLQltH5cyrkhrtF4KP4xoSIGAOxiwlRlFdCUqYDx9ZtEQtxMmKztIJCPT+OnMIpTzuS0hBoYZPptoiNvaxAxW9hdavetHQ0JHaNbTZcxnAfc+2tGO9gfMPj8zi9quEw05sByoE8puHA0hmcZPYeEJbl7ZZxENMfWMiYRKro6GcG/yEkkzMo2bRkOy6C6rt/6zi4ZIZKCKehAAm5Ko0hsxtJRnQe88GtIS/Ewcm7EhxKb4LEJLk7dw6Mq5P5NoyCxFQ4ZCivO20ZDYMfyCkrxi6Zfr2udzsLjuMgSQNfABp+ONlyExAp7KVDum5YAPMmBo1ulnAMoy1TKEifbHK1kijQQKEXYsZbAl8mF8ddBnvAyZMombEjp1JeNSiYAp8rsHZfUMtxO0J9tq6ZCZucr5YkMIzWcHynI7i+gZrrrmtwVlRaegrJstQ27VYEFtyrIZfWbJLhsNgAhaLcHbLThpc4KjfOc4PcaXhzl7/Jfz4r94IZpvSrRrYhQS3MRTEfseSvBb14XVAuQDrA42/Qi77kXr1BhwOt4+ubhCjkuNg00JaLTZgfT76NEknokMLX9+Ad7sQLteSIGVPXy7BQFwrSu4E0DCpDsLW4VJafAwvgGNITs+zW4AW5ujH9RLe9kJHqP7weWVh93tJXk1L5pMtltvo1FYuFU3tTY7+twfet0tUabeczrjiSxO6ZpKMEV05h9JCoBygtAY83cpvwoaKDKVEd2igX1StP7MpgNbC3MhcmLzzqJZC7v3uLJoLtKxLMS6pkLCNucWsTOwQ8Sdb4xoLuSaY2PkodyGLDoNlNlA5txQfhI/fVq7x2scMjYn2cmqofCzZwGz5w7d83KfhZmd6M3WjuvNQ4fuPEyg9TqIXcdux2BBAIxF3Gxykb17Vyj905uWE6lMePQY9qt/CGabHp7FDOZiDV7OYWeSkMbMws3ZD/nhB4D4+En5/i/9EQCA2QrJzXB3BrMLCHPpkpm1iKuZvJ130qM874AYEWct4iLlhjxjhJNZecCeSG7H5md+Ai79aPqghplBSD9U+8Ln77aP6O9IvSfpht9+cYX25SDkL30h5XHPtxjvzhG6Kd8CIIroWRoQQPd8EBX16sZ12+bKMQAw/+eSC/j8z3ypwJyT7Uv3DSeE9kLe9Fn9nMUh2FyGosOhUAlm9HeazEdRZ4/qbOGqinopd1sZKJ7+y6epPbKPGVK2pi6pVEW98vi7HRLcXdTfT78tO1EE+lMDPwdWP5Cs52Fl0N8xsDtGmBG6F1VuyExnQ1JZf0e23f39Hh/9gsP8UZP2A8IM6F4Aw2m5HjOkLFDNOl1IyF0zfHWZcvaNNve1vvWZINKLHbB4FLOT8/Gf6rD7yoDuu2Wt4VcRzflhFXUmoD13GE5Lmf8/cG07OjiPdrSjXctux8ziVWYI0JfnBK1YORRt4rYwhc+CgMPCyFSv39I00MlxsTGgSqyYDcmywqFgFCwBJNR4eT8rzkblodCs09gRgjISkTq/KMGXhR9BY/QUTS5Xx2xsRGAoNkYg2uoIs9LW2JrM3pSvqTUTp1hAPwAAIABJREFUh5/UIftpew8dA+0vTB2Gan5vZuHn4mijULZRAjLZxlwFfLE4DJXhqs4e1bfnfr11OUVZeuiMIlPQkbzFdWah22taPQAwQXAxfl4wChRl/9BR5tfwM4F7A/JpK54I5ZvIfTIv/ecXEX6mfCBAmDP8juAXpa+VgyIkXr+wiKIxkpYB+w5QUSQr1+Pn0l5ftcMvGN1JjzAvs8WwCiBPB2cWsAzvDcKq8nV9BnwWRzva0f6A2e2eWdQ2AVZVaec1+3Zth7ROq31M1uRIDE9JWzRrXiR28QnrcwQoBNBos6OLQkoX34ucmKFoVOirlq2BNRotiUVBzUfY0WSos7RPrsmEKQmulvGAKbEuhMXJVp5uM0QYS/lTy/aPyf2FlKZd+yyq9b960e0OsKOQy8ZBZxacNUVrXY/S35ydfMVDX0BG+2+4utz2nPRg0zadZA0ss769n54N8mvQDkh6IcIyljk4o/wdXXE+uh0QtgS7E6im+idq07KwLf1pN27KS0GA7SVqlK+/19mXlpmsGFajcVVdbH9m4bbSZrcrfea2Brt1i26Xq0F0VtLn6SpEnUFwG8qzau2H69rtHSwMARWx6GQZ4mxZhjhb/uWwZ3zzMiRT2slgEVqRENQ4N7sK25Ck6wr13jWWIS1lYlR9EEJn8rTddqbURULvJtPthLNohP07OgKqZQQ3FuEdLkP2sQpsqmWIMljPJdhEkfJ0XB8C21PJ8tUlJCsLd3Jw6lKswdstQ5R6TonVDMEvUJYhyXnIdoqvMAPBWsAvSj0U0jJkXq7vpsuQsIrwF7oMYYQFw/TTZYix0ke6LAjLCASSwaK6zTVSwbYMYmzplcuQxekO/bJy4q8CvCewEcq+MJ8ytX+SZcjtHSwAXNE3nWybQrjl31sMk5WOR+a0iihvKWYJTe6ze9/EuHxS9b3WCc1/68PMKVHJUklwSm38NDQgrtXe/TbHqixWn3oMa7ulaKKmzgUfcOP284HPuh/32wmkhLDS1kkb9spubFUfFU2V6S50qO16bJX6XvRjaPKbv8piNFd+L/mk6d8A3jLv7IodfRZHO9rRrmW3e2ZB1Vhm9pYkVC0tDF2BW7M1IGPyJ4CJqrWCeXiQ49mlf7Y+L9LiMU3DiUAJ6q2M13ASsYBGV0zx+O+nL8emREPYUiWWk74z8vAdG6k/OoJJ7cvncZLtGP30mutoi5zD5P008nLoGO0v+RsIdbo7lel9ZufugLAjmAYTDscYUtRjP4XaJCi60/bLp0+waP1eW11OAYnRvNSvFtry1tYpfh0NCYEQbYqcdFwySQ2n/irtCTPKS5wwmy49dNmhJ9b9YkvgeciYmTAD4pxlOVIvAeRmymU8DwAT4qDLDml7TIA1JlR8rnJeP+cJriTMI+4vt3g8X+Ra7MojDBUadl5hcSzDDw14Wd2Yb6GFepxZHO1oR7uW3d6ZBaWh8VXbai0PnWlo4tdb+BbYyijMRInrodTBVlLOMzmvpesrgBNVUZBUF1VLSVe+R0cZsadveOFUMFCeDI1EcGPeKWvUPiNU/ZbWWVfmmDClTOjwJP0/40fSC4xYyktU5RO0DdPzsEVe0+dyW74bB9BQ2qwzIQqUj58wid3ELFdtYrD+XafdJIdjfYyop08dHHqvRFvo815JfWcAZ2JhFQPkXAZgYlCmHvt07BYPFuaVUySuBYjSwMG2eOGvw4aVSWKoekAJ5UG0RvIlIpeBqab3v4bti8RMHjxDB2/ujOWnBMwyaV8q2z/xzf06q0Kl2mZtf9bcoUSkYkpZJoihkv9g0mDP6abVdscbtj+3q0Qfpw9SNZiwS9N6lyDVBoiOq7bJ7y0kNzdqTqnWcGkTQe5bkge27ESTgZgMgwPJvpaBMO3j2JQx5FV0/UyMxobJc2KIEXTAiPxWy4w32XEZcrSjHe1adntnFryn91GFRUkZsAARDlYGKy1jYVbiGPPn/jky+MoL6MmMykSk501CyUmYWOqNgBe9DjOaXL8ZYxZB5syUxTDKapRGd64ctraP+W87MGyPBL6qjh9iEsiNZVo9Sn0cqdLWSNsGgq2mpGaMMAPlz/q662PytSEBripQFhvKyzqjDsqUAGb74pijKEAkM1YhUq8hZ1Ez1wQzdTTHKuV7f6pdl9uBJcN1t78PJglXIb2djStOS7cRIR/jAbc2GdBkPMO2ApxyfVXXjuC26fwTUBZNyhSDYQYGLhvYTb0cs7Abgm0rKck+QcwT9iZQIwrqaTmkswi9xlixeJNPDl8WwJi2164tPr5YwaxLPSO1sGsr91wkxFDN4kj6Y2yrx/4Qd+sr7PYOFiHilTiLyCUF3YfqX1Eyp649fGyyrPA9RqFS4DRweEVVBlHWigCl9HHaJ9h5w/kVwaiXYQIjsq7ny3YzJAQnkNW8jJ/Bbj3izMKMIUdDqB9hh2aS/vxpGrHwNmQLXHwV+ToUxVkQnAAyglOzS+usUwomczeYvER4u+VI5oLQQWFkmKEm8kn7DSWb0ybkpBlFQKjZFnyNCTKQ6MA0Lm62PIIvOS4UUt5MLBEdLRcMBpdjOA3WDHCj90L6RBlAzAgMB7g+KQDDYPOAD0hEigLysoaqwUKXZje12ztY7Ns+3Hu/nBmTRLI3wL31TUrM+S1NsUCSZSOBOE7JQq4L9x4LRDvrNY9c4N6ewQkOTiHVy2VnCnIheVCr2kVRZh3vCu5dCGmkDQWCnM7Ry4AhEG7K/Wi8cGiqf8XUfKChmnGkrrL9zeDe+fxj8mmnarKvtXIuGl/g3sYj3wMU5XiqUKRuxzeDe29fAfeuEKAK9655+CdwbyXDUadmBffGq+DeO4PdtkFX1R03Bm5X4N71uP+jAfdmiSlPJhKGANOCtzIvy8Q4gKiWp4edZw0QI3jRgS4THwYRuG1Aw5g/AWRINoDMW6HOUr+wsIYwnsg+nbOInYOhAErUe9xZIBjERQO/lOPtWr7bdVIjT2JD47I4InWK7bsCx6Zo4RPc28wMdmcGJiDzVvi5AXkHtgQHFDq+voGfO4m370VF/MJgnFdLncGJ2rehrPp96BgAmbRnOCHYGqthBXsBlIzN4SRhOhoDv9TrIfitUvin69LBkBnj3CCmJYtmjfqOEN3ht3pdHh2jWzQYztJxc70+gXsXaHgaYFw53q0N7E5g1dsvRHTPUts8MK4I/RnQXkrZcEro78oSQ3AUpS+1Th0k+rupfGXh3x/Qe+mkMGOEkwA2DuPdatm7pQn8mlce8EYiOW0Eevl9h6cu9TXy4BibgrOwvYFNs6P+vYAf/9JTfHt4L9djT0b0XZejLzyrJS4ZsW0Q71Z6r28x27gVgwUZI6+ImunKyN/2nvwq4dnzsm0Yix9hN4J2gyR+nQiJCWIEXlwIYY4PmTiHh0IL5F5IGYUAGIMuxMTUnZijZo1EHsYIpAcYRDBPX4IuG7j0cNHFBrPBgxLbEq/lc/GDIc9eNNrSOsqRANtHtFnLA3AbK9eQRn23CfLmCRGIgK2Ibmwf0D3qYfopI1XsGhnQdL/zHWLXwPQjYpcGswPHAMjMYSffuT9JnqtFijQkGlqC8Qy3jpnIhqL4aOQayjJB+pjRcVlG2F6OOXk5Zkq7uMdyVZebMcA+ucjENTnNPPAkzV37NjZliWN7lqUHM7pnBt1Fmdm5Xt603bnUtfxegF9ZmEEAW+6y9Lnm0OjMzK+kvYtvr3H6T88we8a5b8K8QfuSMS7LYGNGmY3ldPh5J7MI0jC57Df/OOXPNMWXEhrC7GVAaA26Z0P2q8Vmhh88+QB3ih44QtvAbTizjtX9antGs2aMy/LifbKeDtKvs2M05GhHO9q17FbMLN7WapUxSfgKCSXEefubJleasEOBwUiRl8DFlxE4RUqKPscE/HIdUwefRmmMyRBeCrFA2AODosl1av1Gna+h+E0oxIn/4lO3agaQTaEfOUFMZhZZ7Sxt079zUpUvv4c4/NLfb9uP0HqvflIojkAy2hbKb0FN9Vf/gPqkKHC6DnxiVbFavYwipT6YgrD2k+hKIl7y8ygMXf054Mn3V9Ybpr8Xsc60uCTRfUr2uRksVFWMAXDjityes0LR76bTWOpacAz5EwCoWoYou5BRfsxlA9MHhFnyRVxSyhkxhVTVEnjWguct4iwR844eYdXBKjnvJvkcli6zX2cOzs4gdmXpoSnqdojwSwsw0FyOqX1WoieNgUVh9rJ9SMe1E7JaQPwdoY6SREbsnKTUp6XUoWMAwKbo0XBqM82/dFpJKVff3HBCaC8FSVrndLiepo7dSohpXBrYXvtBfTmNMGzjKgV+XW57C7Pp0J+msKPS6A/CS5k5OLWdprTVthI9MaP4KFxffCz9CSG2QLNRX4hDf2rgeobvCF2l/KVt1iWUtqV72mL3ACIwBU0jl4d/OKmuZ0D6zdP5ZulhT5EUFStWWn+RQ0Du93FuxXfELjtZd/cJ/fsBFMpv7leM5lxAcGDkfBpABlF/QRirdr0K8HXIbs9gsYe6JGvAbApGok4kcxYclFtC9DXQuBxOZZPQnCbxXhh75RxZti/R1wnfAnJCkFDtWZhKYyQ2FsYVJfXclibxaQC5Lrm5Uht1AtEV+jwzq7gzLGGcy01Ta1iYziavuMmJa7G1ef1Me9BDOX+5RtdYhM6Aoi0q6geOAZAT8UJHVxCc6iPICWDzMnjod0VwOgKg16iDhrOTBDflZBC2ajMpm1Ss5Sx8IdnJ2JX2hHnl4Kz4LDLOYivhUWqA/kxwBtI2cdyOK3mAcn/M5UELM0Lor7Z5sl/qv/Ekwm2qwWIhUSK/Kvd07ClR+SUn7zJFkiLEb+HU+ZvuCVeiUNEmf0c35f3wK4a5M2C8mOWysIygaDL+ROsD0sAUCGOtov4WjojbM1jsGXsvDs8UweBKF4S2PVDT7PeDhEsr8hve7IC+l5eOOjirc7jzFGUZgyiIh5jCc4mef/Cwm0Ho7VVXghl0uYUZPUyi0KfLLRwR6FKQPOpM7Z4OmY0rw71teejtzhemrMiwgwMiw25k9tM9N7B9EBYvX5YhZuvREGDX4xVnpdlcdXCajTg4zeawg1PLeSP9sXjsp/T0pggU6VTZz4UC321iGWxYZkjkGRnSHMqU34w2OzybNKC5tb+2g9NcbDILtw6IxssMIDs4VR/VUsZcuF6YvyhK1EOdmeRlRuEvCLNnqtUS0V5ez8HZXkoF7dMdTr/ZoXuuTkchqmnPI8ZlhUEZJDSub/IwM5Plg17T4rEuecvMIlqg2cbk4Byzg3P17Rm2uzlmT6rzdFZ0Q3RmUc0kzcho1tN2/aAO+b7Bjg7Oox3taNeyWzGz4BjB4wByaV0dGbyRN3V88RJApSPinHwm0R0yJCI8LSP+4HE+J33pC6BtC17MQBci3GIX86xOFtMshNiDQgA3M0FzKoLqyQvYRdIhSW9ds5gh3j9FnLmM02gai+H+Am1a1pjERxBmFrSdXmfoTNb1KL4HwG1DfrPYJ+fSvlkD92yNOGthdgPiTObY9tk5gFPsvrDIuiSA+EVqXRIAaBcN/EJ0Q3Jdm4A6Gy7rhoT7QASGEzPhjpR9pn/3p4TuJYFaszc9N+jWA8zmqshQ6GbFh5OaePnlLqMnQ1eARGwq8FMrCmHzzmJYTZcsbjddHuxT3wHyhh4XArAaTgnL75U+8+k31NnCxVdaDGcCyhqXhO55LXVIIOYMBe/PSJY7doXte3Ltsh+StCFNdEMUtBUmnBw0BXOhAuHVkzsPvPxJh9AB3Z02zzh2DwjbDzwolMd4OGW057WvpZxnPGO0zw3G03LyUFYwb7RbMVgctCvapckHEMIUaFWBrybHNE6WKo0DVGhoGLOjVEWC1Ivtlw4ufcrhNgOV6rp0oPCL9NCv5XvTNXKzJ7i2X1Xcn8lq0FQGTKVrG06m4CgFesVFI4pYqb3mUsrG1dXsU7+YPrxmsBLrp7IWBpJPJ133uJTrmDUWiOK4i3tAnX3AVH9X/AjR8WRbdLKcOnRT1f2h1z2cUs6x8HPkqXOduepngoRs1i4L+9QAqUJKc/jG1/OHrQCuFB8ByLWGOeUlxXBG6O8y7Fb8DRPN0BkApuwX6e9JdGz82KB/6GG8gumE+IatQV+BsnI7EkFPTOAss51O7vtHhyf7/V1OTlGCSQPM7kHE6RcvcLk9y/vFuyNiLaxVEfA0d3r0dgZzrzj6P3egrIO2z6cZOScn1MlhBxPGAGTW71glmAElvKoKYjlxa5ogpufU71oX+eTbSPtRiOLI81Fe2JpINvBrE732k7v0Dat1anIajaF8ahvGIHkY9fmJYIc4YQMzPjFujwxrtV1R0vkVIp1h6xJi1DV+bftJXiElX9lhX8+Tcz/uW90fet11Xgab4sFnU5WTzCzMGKvErnR8gmW/zuqkMLujibao62Vtr2V2JwOFJMhVb30Nd3KBodudcIzYMcKuDawmuaXQpd0VZ6ruD1TO2Ggm5ZM2HTC7FQe83RWwm9sQLi9nk3rG1k3+DhXp9dg0cBsD/yOXSLavgu6cpCmOfkqVV9HnTaIdTVqutK5IGAYjERNTqaA7daQZmIouL58zfde6wrxBbErUIXYyQ2hmDjCUHZ9vor1TyjsAiN5UdHsmb4eqtbtQmMWtlNVRDwA5jFl7y+3CYFiKZzxk1GOKtCTnmk7tZ2nmUlPdqe1T3vk5YLc0ERnSc2s/7lvdH3rdfl6cv35eCICiKwNUbGS6P65sXmbUFHdvmlkUEwh3rKMyHSHMKJeNS5lRsCUMd2MWRTJBZjiSx5HasJQZRH9KCMtCq6czC7vH7p0jYnszC967zw8pwQMS+QgtMO4IOkD6RcRqtcPloqw1eOnhh8Mzi5MHa1wMJ2hOK4HTt+C7uL2Dxb4quvdlZjGMWdBYv9MwTiMmwyhCvLuxCPWGkGcbuq7WjFK39jCbMXeInlO/6zntZgC1rqiQbz2ac4mcsDG5LncZrmiRItoMAHJrn9Mk3Tag1XDoUNpD/QhDlD91u9mMaC6bieI2E2BmFqHKQGzOPSha2G2ETYNgs/aw1cxCBwaz9SBmdOcx64yq1UrccpDJ+9Xb3JZzP+6bu7SlP9J1dy9NUTkfSDhOkwix+ixiw7AD0FyErD2qb2OXZgtqh3wWOhuR85lJhKNrJDyqZd1zC4op1BoMZk81twVwnYCtdLZBLAN/9zKie+zQpWwEt5EBuz1HHmyA2mdRQq51eW7T+WEF++GpFZ/F80o5ngzO5ydYPCn1DEO757Mo2y7jKbonFmNfymj/t32NHaMhRzva0a5lt3dm8UmNGapXcYWT86b6H4DwW9Sp7syZp0Agvu8Qir1vVVWU21ItC7jAgcnxpHxfv4Ji/GT9clOr2kFgZC2PujzyzTVbbtgmE6ZteJXex2f5e6vC2I11TuLeb/+WdnsHC9qbHtUiybXKWK08tq9aZuiqUlk6d5YCGBM6szWgsSiN5XPqd63LGURXfBYufWcrfPOFUv/1imGqFgYAMWVP5jrSdkGKGvBoC0zbqjBzUTwDkFXVaqSk/k2htNeMPGG/KhDpguDcvxn31cLCjBB2ikisBqdY+nHf6v7Q6/Yd5Rt3P3Sa6f3Vr2MpR3rCK8Kltf+i2HR7rHw9oZNzalnoihSAn8nSQzpHjhXSHc7nEgJggl9G+MsqdDpjmHHfZzGNhmTZgr2I1iFhatlfzm23lEOnfsEwJ2OOzAEQdbTKV1YLI/MywG8N4rIKuf8oIDiv2NuO4KpSFmIZJNIDwm+jXHblvBHEtrx1Apc3ny+JaO/ceO+tRjrjqR9eYePSxCZp/3T2U1CWh9fK79JqLU5KsOes6BVKuQmY6Ka+u/awRDNYnJk1wlLZuSYJYb6gLN+5VbOKCTnR29iY4OV8eEB6k92qwYIVkFK9+bKFIG9V76fsVzUjVr08GBNcPIQ842Dvq9BpYboCJKQocG/FDnNxslZ10RhAtiRFUQgSflSmrup8r2Oy2mev0pBcfbyyculnaYPsPzk/IV1nFdtPYVI7FLCZCTqzSIfpQ+nlGmr2qvy77L197K7sV2/TNtF4dcCs+0Ovu2Z9mty/NOUBtYOcd5+56iqT1esdnGFLkz7TpDAtc1vJL7E9p5CtdoD8p+xacqz4ae0Q4dYuh2hlaSI8nrFKRMuO0aj3DU3Ky36HXzZuI8FAt+E8QLkNYbhoJqHS6Mzk7wmtnpVjuGbKeot3xNHBebSjHe1adqtmFhPbR3BWforrIDi5a2TW0DaF3JdMfvncHMHZIM4dxkVK7d4IpNquE85C1cjfNYIz4SeyJZTmBME5WoxLCzaU1/bRFfATgMzmxI0FmD9TBGd/ShlaXiM42SCXh07e0M25fecIzv6M0N+TY/yychYnn4WAsrQPOEHJPyME5z3JICVPku6Ot0dw2rMBve1AdysEZ/OjgLPYN0Ml1fw6lhTK2JmcPk7OCjJzH/D1FsaNPHxZk9QZAQ45AXHt82q8K5uogQEpT6EolwFI2qoyFVXKOZOEdkpadxpEuh/CrUAFfKXKYBQYsaHsDGULhAaI3bufBEsbOA2unPuGojgzUaAx0q4ZY9zLm3l3bWPASDv8DX+q2WzExnY3Jh+6VYOFmafELe8nfJmysXBysvJrAoVj04fJMZR4OpWjE4BwdMYIBuAeSYKagrJmgweGMXNr8npT+DGquuxyBrMh2G0i0N0M6J4auBdbsDFCIAzhZnwdR6byYwKSNt6cp9di4sKcfdeBLjagywbUj6DL9LZ4eQnHjIW5M3GmsjUTjk9A1r9uk5jINdiyHhFbm52cbSL7UZKfu/9sl9PDc7v3EJnjiUNzIenl9TYzBtjzXQHBVbbYLHJ/5OseFtmJGBsDdgB5idDUsGwKDDtE3P19+R3qdPE6ulGjM3OblFp/iPAri8W313lb97RF6Azap4LVjnaF8WMDO8aULJf8WlEGMOMLPH5cGIxzQnfBeO+3LGYvxJEQWoPQAO3aY6g4OG1ySoZm2qf7zsqTD/fEUfT4YQa20heair/8CNh+eBfvfVzug3HZolmXc9a/z+WXznDnKcMvKiHlzfUHu9sxWBAAYxHX5Ye07z8sWaYAMMoD77//A9DP/HGY85SVeraAebFGPJ3DPlFpa0ZcdKCXa/CsAfVpEHn8JJ9//fP/IgDArSULc/N+g2YTM/z5rjHwd+egEGHP5SYNZ3L+8aTJy4bl9ww2X2ixTA9f892nAIBH/8aXhVdArw8ynVc27PnHizyFd1tg+1Ccju83XwYAvPzDMyw+PoOfG7h1zFP3+aMzbL/QYVgZNOupM2xcGoyr8uMvHgWMS5M4DBTB2Vw5BgDu/1/S99/510+ys07brlN9Xfb0DwK6Z3M0F8CYOJKJxQk3e7osQj7VmLN5YNCk/lA+hXEFNGttx6RZk/JmDdz5xoiPfiFN9Rdy3XbjEFYxL6myYrjlTLGHywbwBLt18O8POP2nMmWnCOweAONJxOk3BS69fQ/oH3rYtUFYBnSPy+Phl8kJupay/qEMDu/9lsXZv/ddfONb70u7lz1OVls8enSKO++d5+PXmw7MhMVC7qWHJ5cYg8VF30qU3sj5P/wnianbFOcjG2C4H0BLj/ZbM7hEYt/8mef4C3/kH+JXv/lzuZ6v3nuCrz95CCIGM+HOovyYD5sB33xyH3/owdNc9q1fv34453YMFofM+0m4lKu3qNkM2Y+g383WTd5otB0kyzR97p+juZROsusRMITupRFGba/kNyPsxkrYMddlK65FlQIY0L10sOs0IKV9uxdXYdN2MPDpxdG9iJm+zm2j4DQYhfzmZYvm0oO8hdsEmKBZriOaCyfs1JvpYGFHzh5+OYcknLlNzG+2Q8fk/gIwf8IlKQqQwWJWvgPiC2lfAs2G840r1wF0L2P26Nd4jWhL9MJqItmO8gBi99Li6/Jmw2guRswfJX9OTvMH/EUJY2t+Rq0pazeU1dJ632YWbgGwGbiNycQ1gIHxDnYn5+oqQnnFUehAqj6K2QuPb3zrfXTfa1IbGjxfztA9NXhZ+RJs8k1czGVgOp8vJUw7aN6RtOvs4+SXo9J/op3i4OcW84+RpQCefXiGv9n8aTz/8G6u57fPl4jP2uz/eTFflYuwDPO8we9elFwS319/2XyMhhztaEe7lt3emQVVLvs9Y1dnnRKISKjxaqSmMdN/e1YcfgbCt0mTTFCQojFj5sCAJTDSfimGzpWDU06oWaOEqDO8dHhoCk+kiPSkzSE5IrnOOiVEa8COwK5Q28FJWWjNlfVuqBCieg7dr0Zw7h9Tt1sQnNWMjipUoV7HDIg7IPhqGyM7JwuWoK6H8rIkO1VbZH3SuKc2WZeHIH2uM5w66hFmXM0sUlNqVXMuWIOp05IyUY3+lqGTaAaY4Oc8TfVOL2N92/s55/5rlj1C8lWFRQQvPMK6BS9KByj4U5dKzXJEZEJQ53uaWYSsUYMCmTEpyjJPOim6PFkEfGF5gUeLMoNZLHe42Nk8s3DzssxwTcCut5itKn/gW/jjb/FgYSYXQhWUmys2b27k+4Q0N5pE1Ft97p0jQ629dGxoDchXKcLOIrYWxpOkuwPZMRgdvXGwEJh1aq+mJ1cp5HU6ObHAlgUurYS9MhWWdnFJZ2+FfDc0gK1AP8B0MALSYJH204Hp0DGyIbV7VoBD2vbyEKZj5oxxEPLXOnQpmZicBZ8z6pLlYcuDRWaLouzg3Ic51+Xi1CtQ7DAvvqCw4PxOiXONoHBOvWZjRdmLgHASMqs7BYafCWS6EAGnwSemgaVqk4Y8tW8ybLsBTlZbPF8m5/zCY7Ya0G8cmmV5KEfTAJHQLGSZerLawgeLoXEwpqzXvDr5Kw5OjbzEuXCe6uDXLAd89eQxvr56mI+/v9xgt2tgDCNGwmpRUF+tC+i3Dc6WxY9B5jAI7JC9cbAgor8O4N8C8JiZ/3gq+y8A/EcAVAvpP2Pmv5u2/acA/jzGn4L7AAAgAElEQVQkk+M/Yeb/7dqtqS2Gqc+iQmeafix+hJ0DjV487bUXXhGc+rl3Dk2XthvxWTRr8Q3kLhk97Hac+iy24rNw1mTMgNl5uE2E2SlgXz6b9YFU72DyDdBeRJhQfBahFQen3Y7p+A7N2oOCtCuL5G5GuLUDRXPF/wBgki+i2+v9Dh2T+wtA+/Kqz0Jl9ApAkrLPwlRd7rZAs+aDPovQlrTzorJefBP7SMK6vNkw3DageyHb/K6gH01P1cxCB4jS1tpnwcahfVl8FmwJxhPacyXJldmk3QG2lzRzNRVaVp9FVplbezx6dIruaRps1y36jUP71GCIZSR1yWfhN/IyeLZuDvss0jXu+ywoGPidtEl9Fhcfz/EPTv8w+scluvGdwU18Fs/n1dsj+SwehTIT4QN5PK+y68wsfhXAfw/gb+yV/7fM/F/VBUT0xwD8uwC+BuADAL9JRP8CM7994oGxQCXrOplZtA4YNOHKwSZq/qxyzix0es6Vz71zqJOMvMSvx4UR8I0CpZxFbJ1EQwadxSStjLnN+zWzivwGgEl1CZ3dVXBTjoDsTP7OlKIYLNcDCBlM6CzCXFiglRavSWV1WE5tWJoJc3OzLfsd2n9SnmZPwylpd6WOB3y6F7NuyJ0EWDI0iYawTbwUOpPLeRTCaZmjQhoNWVLRgd0DftXlbIUrVDktNUHLbafJWqojCgNw6nvbWlAQar7xbokKURRdD7/i3J7hFOjvRriNnLfmo9B6dEapgKthaXDnvfPszORFQLMcMMQ53IMy6o6bRpYFCxmUV8sdIhO2u6Q/kwaL4eQk93seLEjqi4uI4dLBpSWpe7DDzz78Nn7jvAwWH9w7x/dMGQzm8zK7mbcjHttTvP+gjIKPmuvPLN44rDDz3wfw7Jrn+yUAf5uZe2b+FoBvAPjZa7fmaEc72q21TxIN+UtE9H8T0V8nIo3dfAnAd6p9vpvKjna0o33O7aYOzv8BwF+FuJb+KoD/GsB/+DYnIKJfBvDLADDD4uoOHF/ps0CMhTI9hETKyyXrVEl668+9c5icdRqBSEJs6zmraCEIYS+FQvhLKe3deC4K4T4myb5Y6oaS105BWWZExvXLOarvAyeympQz4GWJZEZJM68Vyc3IsOPVyIYdgVjTK1b72bGU7R+j1wtMSXQBmQJrlmj2A+wkI9MMDFspwZuB9/RE67YUh13J3OTcH/s6snW5HbSP0jb1F/WyWi2rPcVZcM6yFYo8YcQ2W8p1U5Q6Yk+F2q9P17ajhG0o7VEYvZZprocdGetNl3EUgcSZ6bZGlh7JaCs4Go1NrKmTaEjCOfh0/cvaP1RFQ+yOADLSxgR6GzcNPlzfw7gt9TzbzKVejb5U6bzD6MAbh5fr4kvh+On6LK4YMz/S70T0PwL4O+nPjwD8WLXrl1PZoXP8CoBfAYBTc+/twOoRmKSwJ5aqK4zg17WK66EwISXeh7ouLjfhdUwBXIwS9Sh1lr8lrVm/l7ootYfqdsWCWHxnVp2/5pyYVKtt5mq/1Fc57Z3LgcTl2ugtGKVr2xf5lXPW5yrn12dEWbd03xpVCp5ew02tfiDBQGbM3vu9Dx4TxVel0ZvaT5EdxK9qHwMRhJqhm5mqe/jTvVVuNFgQ0ReZ+fvpz38bwP+Tvv86gP+FiP4biIPzqwD+8Y1bVyVF0YQFy5SHNuEo2NIUZ/Gm0KkyZSmuwSX8hPaIFWcmEeWwotZzrdBpQzD7Ycqa3dsVvIFRvAKXN1h0JHU1hJiwFdpetvTuQqctpiSuVEKdGWfRMWJHCJ6K8G7CM0RHWYtCB0mw1KP9oW1869BpPq4MCmFWnohQZVjmtkYjgzwTwjxmXAmlcG7ouEgK3jB0ulj0GZnJ84BmMcJvbHZmAmVGoWWLhUhr7hIs2zUh9c2stL960g+FTt3C48uLF/j9xft5v7uLLXbbchMsqtDpvB3feej0bwH4BQAPiOi7AP4KgF8gop9Ol/P/AfiPAYCZf5eIfg3A70H65y/eKBJytKMd7dbZGwcLZv5zB4r/p9fs/9cA/LVP0igAwk1RU71Vswx25o2gLEF5Uv68eo70Bm9MAmVJzF3fJmwtYiehU8q8mDbXrzocbOU759lHhTzUN7S+5VrkN3HoypuSQgIccUkVFz5Ik1GYYQLKojRrmL6NY0OTzMvQlP0ySvHAMXpNUu8UH1HPLDIoaxHhdxKSVFSlLkOk/xSUVU4TugrBmenwkaUEapk9YFpuvPyOIYUvw6Is5sPy9YlkgSSRDAB45eHTDEBmD6r/Ua49ziNCNPktntuvMwtFlqZZTGwsHp5cSq4HBJl5stri2brBallCp2t6RSKZDZNEsueLlV7aBNQX5xG08Aidy+Wr5Q4/tfg+fmv1lVzPB6uXuNh1BxPJls2A88UMDxZVwuaPhG7I6zg3a8ZuVQ6LyE66t2GpFt5FQHkfi+8gOTgjC/M1xPmYB4U3GVcPnY4ZqR45f1mDm5Ck8ioHJ8WEAUlr/aLzwdOH+VO2K+zR1XS48GISyKc2VgOC+l40OW3q+2Bc8cu8QU3siuXjKdeHijYuOyoCwMqZGapr8gUUp7+P8WUp9NbtSTYGm+uOTPDp71j5MvQ718cAsi8AFQlTrk+e+LEO1xuZsGOXzwEAPhqpS+u7Id/mIbu9g8W+1YNHxMTRmAlf9EGOKTpRfe6fgyooMii9BauHGSREMhQ5g4zYUJYwtKPejJLRmbklUh3GV84qo3WWSEBNSqvbKJZroSgIwysPmEYCRi4PZbIwlogBIA9tSPuFtO+hYwDkaI7ZI6FlU8GOdfI00JXBtVwDl7ybqo91m1xLhcDUSISb3tR1uRk4RZ3SA5AjSqlt+vPWaEh1GAaCGRIjdkQZuKOwTlWUpdKerUnREDONhthpNEQZrszIuOjbjMQMTiDcNJgMuAIgUY9I2KVR/8IGgXuPAvf2CgDT9tjq/rFSXySXoiFSvt01eDycYhjLY/x0t8S2gnvbyiex8w67TYsnm8IHED538oUMWTLsj6BK0AsUdCYqL3u1H5x5u5lFHUwhunpMzYZdefU/sR04B5vk/a7KCts1T2Ykn1o7rtm+iaO/nlSlNueBMBYPft5vb9bxqjpu3NRU/5U3LzGQQpFspD4mAG2cDNxUDR6fxPbYEye5HtMGlzd9XhmbiK7x2PZ7mXTEuXGvmxwY4oP1vUXQ7tp2KwYLMkYeeF9eadQ24MSMBUCYq5LF1hYItk3e7hjBp2nE9G/2qWa9jEHCbOrFz+vyVYcwE40OXQLEmYXdXo8spNbrzFSOFtnzLrR4dScI50NIMPRxSXC7wqnp87raTng2P22LrlDHabv22b3ZsoTraLofSNqtuSV6fRQEvp6jFjdsv2IxMiaDpg/TBKuhyxCG8Ex6Anqbo11shWeTXcnIvalZE3PdVLXRVu3xabajUQ9rIloH+GCw7VucLKTTXnbis+AKsv6qAc0eoMfrrIe1DCKWd6j99NasRz6Lox3taNeyWzGzOGTsU7ZoK9Ozml/TXuwyd6YFQP0wHfViBJ3vwNutZBdut1fOMftYFn6m94AxgpIcIlxieja9h9tamCGUugiwz9cwmxbNeUoAer7GPDLsc/Ew80ZmQKuPfOZrzPibriiDNRc+k9CSZ7idIPw0G3bxcRBx5Y2B7QPcZVozbz1mz0jYs/rpLKfrHMK8TAuaFz26zsH0Hl2Kshw6BgDoXNp/9q17U5QnoYr8SNH4hOC2jGYTyyyHAdcnBKy6Vyokpx0LCjVclGxbzVANe4S8dbntI7rHa5x9o01l6reRGZcuE2NKhhPyYjmP2xVk6fDUYf6xOquB5oLg5waLxwWh2z8ycD3DdzQRKdY6tV3Kwn3y4Q4f/pP3MsNV6Bz8fIazF1VSGASZSbHgKJ4vVuLMTC9+nVGsPpS/o6XsX4pWsl5jazF/EnL27sfLE/za05/F7HvlMf7m4hTugqCCTedtaYPxwMkFcH5SCEFofWTKOtrRjvYp262dWRCROB4Pb8xRAzZmirJ8W0uoTE7nVLwBm8RSNSLrkdRKTm++gGotreekss5nZ8r1WZTIiyI1iTLKNFrK3njeo/v/tI2T7yH/bSj7LJSti03yyZjC4EWhOGp572VFND3P2+hrTtpmrn6yRYY75xlc5RuKo7wR2UiZzpIsxD/FlW/pxiFpUzkh0/Xv92O+H6g6JiJNjYuvTCNJsamiIY6AQ5KFBMDwpL+1DnX88gRH8cnum9szWOzhKjglcPEhB40meAElWaxKGLuWsrXu4iOISaIOKSwKQGQKh4S1SNT45i0GizrfA3pOYyril6JfYrzqkQKkEn+jkMiwAewYEdPdZIYAM15/6vi2Nmk3ADCDNBSalxWSkEWhSOkJ5oInS5iclMecjlHn383bJvWXz3rZo+A74ysMS/pOQUh8XM/VsdMEt5vaJIQcS9h80o/7uTSh3ocK/4aGsmMJs/Mr7mfFmdTtj1zquZo788nsuAw52tGOdi27PTOLfTN0NYBdb9MpPFH5W8FTkov3etMdbL2kKdN9mATEMQZIs5taAexNVmMQ8hLClKVVvZyISY0LgavlRgXFDjRZ0rAzwCsEdD+xVcun3PY8vd9bhthK6QycaOn4yjJJ8QysYcu8/e0AF7kPJsuQ4iQs/V2WIZRmDzi0DEnhanWG3nSGwaZaWqWlEZtpPyLhPepjKF5dsmTFM0d5RhEbgj2gIs+HliGoloIBmKbq/ggsQzhG8DiAEp8bRwZvkojQUyHpsvfvCZeEtYKj2KZgvjXCvdk24B98XE76Y18UucLlHJT8GdQW4EtIDy15GVjGOx3cEMv09eMXaLbCs0GXEuGg1QLh/gph7uAX8gt1AHYP50ik0LDpvLGjDN3NKd4OOXrQrMvDYweWm8QSmkdCeRYW99A93iAsW9j1gLCUtruPLwA6xfqDDq7iMQCEErDGYMxaIyJDm6bQ8l068Y+kCMK4TBocmztABIYlodlMTntFom88kSVFtMi4hegENt1tI9z66lMX2/YK/+flBxZ2l2DPldYpCHBJ8c3PALezYHOSBZqUYNdt8UatUwrA0IqqeZgBs5clwjHOLUwAmq206+VPOvR3GXZr4FeM4Wl5CjV3R3VS+nsJSzHMMNwPsP1U65TCzbROFaVa+yhsYFz+uLRhPLEwqrd6P+L0/Utcrq+nddrc6bF7MoO5V6KCsbv+gH0rBotrWS0NUNP7v4LuXx2fbOngeKrOQ/VDZCkATbTaryN9spG36ZUU9b1Zx5uo+jVBDBD/RE6HrqQE5NwGJn3qdm0nV+dnopT2Xl+jlEVH5aFuZKagSMIMwCICDE/o+fN59mn6OxSK/mqbUPYXx+yr+kOvu05RrxPgmIq/I7aE6MUBWFjBU5PjNAFN6fknlq6TYnqQJ3KHKS09t6cMCqGt6uGUYMdAzMlwnGcRtPTwKWQd5pJK7neEuKgGx8R4rg8vpVT1SNNHUJMVr/TfTFLwQ2PzTCouIh6s1jhflPDobDVgVwkHUZUmP58POJ83mFdp6/i8JpJRl34d76cZp4BEJJhhTk+AXQ9OjNuUvtOuB1fHUIwA1UlCEK3T5Mh0LxPOIumgti8czGaEGZPWaTqnfte6yM8l1p5zNCLcNoL6pIua2JS7Z2PGTKiZpD0q9Y0waSnhtiEvT7TO9sUIs+7hAsPsBrh0HbTr4V72aM4c7K6+GQnEBOPLw+C2EYCR9qWHprkMk+mxOuFU5mD+5Corud+bWZjRoHsp+9Xb3Jal3ZurWqedo9wfet1+1hapwxGTmUUuV6ckA4tHepzU6XY8mUkdQobahElwO1Fr655VyTPsEDpC9yypyN1pQVEQqOOO0D1Pfc6ijEYRWZKSPIk2a2C035phnia1Ivdg0J4Dw2V5vDSfQ/Ekqg9S558AwPzJYfTxeGIRGotmUxyfiw8dvslfwOI7pZ7hxQqL86pPKsHriwcN2ucG600ZXPAps3v/cGyP9WoSSg2xGuLT9yoaoqY+giISJPkj7KzQ8QEZGk5jAIUA0s7Tc+p3rSsnkx3oZEvg5DO2fYmi5M2VH4bGkOnhaAwZwJUp/MYAeGlT/kzbKQSh8qsHQieZoGb/TaFhtBy1YMTW5GPzOr8x4MDyUA1x7xzTaw1dtV+1zQ4x9+OVrqn6w1bJcJpsZnwJH8cqjd54Tmt7ygNIOed+IsuVanP0w/YMuy0yBUAlp9hXSXQ90gyoTuLTyEmJ/thB1Myjk6WJ0vNTkGiR3XJm4a7bSlU2rJTvtXd3+E1vekikZawAZxvAXdiJhCRbmvxdJysOQZZD9czvbcLFx2jI0Y52tGvZ7ZhZELCvom7eew+IQRyaQHZ4+idPYX76j4EuE/T3ZAH7skE8mZeRj1lms704PvMM4aNMHYrtvyoq6s2lBwywediK2vhK6ju7fIDxLKmoX8rw71eyTPILB5/2cxtCmBG4S38/Eofssz/5Y1koR63WDVk8cZWKOmP7nhEH2sUDAMDFT84xf9LBLwzcZYBPjsj5osX2CzMMS4N2PZ127+uGLB8zxrnICao+CDt35RgAWP1z6fsf/CuLyZvpkG5If4/RPXdoLg+oqD9z5S2qb2ZmbB7YqyrqS8rT+qIbkvoktcEvZJ+zZwGP/5T2f1pabM2bdUPWqhti0L8XEJtZbtvuPsGvGKtvS9nuAWH3QHVDprOmXGeSNNw9kLqWH4ma+bMPp7ohFx/fTDfk4+UrdEPui27I4kOX+2b7c2v82a/+Hn7jGz+V6/ng3jm+9/SwbsjDdsTjO6d4WOmGfDQ/vOw5ZLdjsDhg5CT+xGkNryI4AOBXLVxacoRVCzN4+JMO7YWmdDLCqoMdff4EAGzKOfq7isoUEZvtfXE+9mcJ8z9vMJ42Mt1PIazxtAUMoT+z6E9TfsOmxea+hdvI4GWfyuf2IcFfpOakafe4EmYmuUCDMZEiNWvC5ouyLh9P5Rq2DwwoOPg5oXWEYaX5FC22dy2GM7qSfTqeEMZqOUrBYjyR/caTFEk4cIz0ozyImw8iXD0IUWmzZla272+wWS3QvDAYT/WOBpoLIzwQuzIlV9s+JIzr0g8AMJ4xmotUdjIdWOvy5oIwe+6w+0pSmD+Re2K3brE43SEmhur7iVvSmYjGSuUfX6wwDBa7bYMf/9JT/ODJB7lt/fsB5s6A7U5CKtsPPE6/eIHLyxlWqx3O51VexYk4CoZ0j51+UX7c7Yd38Rf+yD/E32z+NADgC8sLfPXkMf7B6R/Gzz78dj7+w/U9RBC+vBDJsZ9afB87dng8nMJU4c1fe5pkdgwXYh/DOH3/Eg9Wa3yTvwB3Iffun/3q7+G/++D/xF+uYr4/f/J1/Oa9r8EQIzLhJ2ZP87Z77hJ/7+4fxS/e/f1c9p93e6Gv19itHSzYB0wILsbSIXY9gnYpuauxQD/Arl1xikaGvexBuwH20oGSE5Orc3QvZF+3CQAB81bkAPUGNzsPt/YwPoKSNKHb2MT43cAmFGVzPmDx1KA5lzq0rvljzo5Chdy6LcGnhLDZswi3LY46TuhODTvOnjm0FwF2MJI0lqIDbu0xe2lhB0K7ni44h52ZiPkungYMO4N2HTHs5IE6dAyAPHtafP9kugY2xcGp/o1hu8LsJaG9QE68AyQcPHsWi8RBRX7D1uSZhdtp+LjMLHRwUKvL3YbRPffovisDmuqVdjugXzbZV/F4LlOgmvzGrC3MQOh64NvDe7iTHJEUWAbTixlmT3Rwc7jcnsFtCJeLDosn9cyizCQB4DIpkL33ccSvfvPn8PxDoVJ4tDjD11cP0T9eTJTCxq1onSq57m+tvjIhv1HTpLB9rdPL9RnOFydYfKfMLH7jGz+Fv2w8/s7/+8fz8b995yv46OnZK7VOHz85xT97ULRRn/XfwnXt6LM42tGOdi07DhZHO9rRrmW3dhkCQ0CtllTR6nFjMtybVRdkL8mLWycIzvS5fw5ldDaDhEP9jIRlO7N7C4Rczp/OaQjcGISZxZgQkV0n37tO41mJ6WpBJZSXZth+TvDJIRjWlKf3FJMTkZGvy3cCBw8twQ4FwMVG2LrHJU0U0wFxGI6rMp0fL0zeT52Kh47R/pK/92DKVJx7ugzxZx5mcPCBig+GAWKCXxOa5OMJGhpmuXZd4qnfZDwp/hxfaCHzdWo5G0KYWfiV+qnkRNFZxFXI/WxXGh/m7AcYqUUMhLgxsCcjQkI3EotzMywjQvrthlNGvDtibB146TEMFeI31R0VxHd3TP3V4qv3nuC3z+UCFssd7i83+M7g8MG94kh8tpmDmXA3sW1/sHoJHw2e7uS4zkrbv7kQ9WemklvJqb7ZasDwYpUBgB/cO8fPn3wdv33nK7meP3nvIzBTZvd+uLjI286aHX4HwJ+4//1c9nX3I+DgRKzgcsAEpGWGkP+mMYJ8AA1+wsFJgxd8QvrcP4dNEF8BWAm82G1j/iHISwZqnYlqhgAYgm1M9reaPqDZRph+ittoNoxmD9wkbaO8Xc1tGc2lDC5aV7MVHAM7ATEpoa0ZA1wfEdcmw5TzqfdQrM02go3Jn1p26Bga5GZtLnElGkL7KeCNQ3NJaC5LoUZDmi0fjIY0ayr9oc2k4rPYz46sy92GYXcBzXki6vEaRSL4ShApDIpyBcKVaAih77rqvEBzLgOplrXnhNg2Eg0ZGrQVuMl7dWgn5GsadJo14+tPHiI+k4HlYmex2zWIz9qJmrlGQ1QA6GLXHYyGOPXd7EVDYttg11sszguO4ntPz/Cb976Gj6roBzNNoiHPNwUPP29HPH5yit+p+rn3108Bvr2DBYDXso7ubyN6/f5Xjk+fBgXsRVVCUL1PVj+7WSJOBj5ROWedaDQh7KWyb064MlQd9xqej0/LqtMfJOyl1L66v+KBsvokVF3vTZs/ja6muricMJdzGZBSVEH3nSSxaVs/YXcS8aRtxvDVc165XaXdxnC6dXmynxINA3htSr8Q9pYXj56HDIMjTSItn9Ru92DxOpbuQ2zctSbpG8+dPiOyIM1E66Pep9ZCvcGAUd6w5Zy1bkj+Xm9npJBtmo/mfZVt/B0OGFX3TVYksWwv+qFVe/fLqpnFRNv1pvcvTz+v8DXk8pKxqcQ4um+RI0D5vT/h87SvLxojXT1n9dvmY5D2RVkhX7kngAlL+r5FpnyO+rycyuKNR+ardrsHi/oNWquJ1bqmKdWbjZnsf11FMnaUkrBUvauq2yT4tvpHksbqtRTJmpKRmbVv2pKUVeuSGi/ficvxoUkJazYllGWWqpLI9k4UydppqjYTSp+kSwwzFgW36npkCSXnLzoj6cFkmqSH58+3VSRTfVFVB+MExNKxXgFGhBw6jSH5ogDwLCA2Nh8bs9ZpSSS7iSLZncUWL+YCHnFzj9Wix/N5OwFEMRMYRXv0zmIL5qLroSzcypnJhstASHxQkWw+H/ATs6eT8OjDxQWeb+YZZ3FvWdaUn1SR7BgNOdrRjnYtOw4WRzva0a5lt2MZwgBimJDfqOCQ5ou4L34BHCPMcgkEBiU0Zo5YMIMvy/Qqfvk+KAjsO/NqqtiyMVMfAAo8Oa+zNztBh6bvgKBFt19aws+EVAYAxpMG/ZlBey6kMuZeCX3Va+t8qUbrLWVZAJcAu5apqx1maDYebBu4rUd0yWu+GWH7DuMXaRL9YCN5FL6ABtHvDIbTJKycYd5GWKRS/eOplPcPl7r5qgNy/5Vi+arfIR1jB75CcqPXaJMkoS45xlUVIl0J4xMFWb5l3o+OER1h89CVdqmQD5Ljd698v13sWPY1PMlUpUAgX7hBxzNGc6fH2DQ4ebDGZZTfEhHgZQBGys5GezZgNhtx+aUzPGyGXLdrAloXAMuYtyVVXyUGtWzZyO+889NHsCwBp/Hr5k6P+XzAxYMGQ7pfHrYj7rlLqS/ZWbOb1Kv1AMAvPvg6+vA1fO2shE7/kb0+PdjtGCwO2V6aM/uQQ6l1OHQSIq3DqzsP9APMtsC9MYzJWRlgd8qtkEKd2yjhOe0RPWf6rnU1lx6ILj/0bu3RnVuBaRPBJI2RZs2vDW3uhzObBAPPIcwUjrWNyZ+63e4Cmkt7JVHN+BJWBIDuXNK7mzXDpy5oL6M8oMlpa5LGplt7CXFelPCi2n5YM3QGzYWEN+ttbsO5H/etqUK9et3tuclhQFMR7jAJdBzQRDKgOw9oU+i0DmP6iirAD1PmMN1HP2PboFmXa/MX4s9oEgS+fW7Q2xncxuBiOEH3pPg3/NYAsZyvtx02tsOdp4xvPrkP81zq3vUW/baBed7gsT0t15TykvrEbna+SMlrmymz0MkFDtruyQznc+GjUNatx3dO8ffu/lE8flLq+R1g8rfWAwB9+Bq+/fheFmUGgO14tc9eZbd3sLB78SJDEN50TIBWE/BVdUxsLawV+UFO+1IIGemiMoF2lBtlnBuQRwZbIZ0TwKSu0FmEuck0daEzGBeE2FkwAS45Ct8EmlLAFAABTaXyDI5KQK8ws7BjzO3l1gkorAZ9AVDpwBrcNG4IfiG8DLmuYITfIr2mMyjLGTCmQCm1fcDUeCfC9hZspvWxIYwXJnNn7F+79kfOOl1VQK+lcGISp1CyOnrnEu70M4PhNP12FUBKvwMAL69WPKb+jM4I4GpZHs7xBBiXXNpzGmHuDfCtQ3M6YOw15g3EZQC4SEXQ3QFkGX6xwB968BS/eyHTpdlqwNlyi0fhDO9X2Z0v14J3OEvJbupkrEWKgakAUG3m3oD5osd6c5Idsg8fnOMX7/7+JNfjT9z//gRHUTszv3b2fYzB4qfvfzeX/Y67/szi6LM42tGOdi07DhZHO9rRrmW3dxnCe06yyKUsVhR6+j3GyTGUaPYErl3R4gEAcxHMSZ/Gc/53sI70acYIMxbyWRMYdmAYdaKmTzsU0lk1OxBi8h0Yz7ADVd+R69AySu2hvXbJ/pwdhlJxwnZUOAo7MMKQ2MPT0knsJFEAAAFJSURBVNSOZboPFFo3CoJXMANKW7RJe8tas6O8X71Nr3n/uvf7Q6/b9qX+6KZLH6dK7IZgE9Wd7ZXAR4+n/B0Awv7SNbVV9/U7O7k2MwDWUe5H0xPGjYPZWoy2QbNTOCXA1goXZyobNg4w0v4nmyWQWMp72+CcGNhZnG8qf4H6KvY8w/U+2qZDFjYOW2LYXfFZnG9m+Fb/3uQc31+cXjmn2rebe3i+meO78zu5zMfrzxeIr4N2fMdGRB8DWAN48sNuy2dsD3C85j8Idpuv+ceZ+b3r7HgrBgsAIKLfZuaf+WG347O04zX/wbAflWs++iyOdrSjXcuOg8XRjna0a9ltGix+5YfdgB+CHa/5D4b9SFzzrfFZHO1oR7vddptmFkc72tFusR0Hi6Md7WjXsuNgcbSjHe1adhwsjna0o13LjoPF0Y52tGvZ/w9d3p6xIk1iNgAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468c8d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 36.662347078323364 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 1e-06} is: \n",
-      "[[2.000e-11 1.200e-11 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.200e-11 2.000e-11 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 2.000e-11 ... 2.000e-11 2.000e-11 2.000e-11]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 2.000e-11 ... 1.052e-09 1.052e-09 9.840e-10]\n",
-      " [0.000e+00 0.000e+00 2.000e-11 ... 1.052e-09 1.052e-09 9.840e-10]\n",
-      " [0.000e+00 0.000e+00 2.000e-11 ... 9.840e-10 9.840e-10 9.220e-10]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe2ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 38.916892766952515 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 1e-05} is: \n",
-      "[[2.000e-09 1.200e-09 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.200e-09 2.000e-09 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 2.000e-09 ... 2.000e-09 2.000e-09 2.000e-09]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 2.000e-09 ... 1.052e-07 1.052e-07 9.840e-08]\n",
-      " [0.000e+00 0.000e+00 2.000e-09 ... 1.052e-07 1.052e-07 9.840e-08]\n",
-      " [0.000e+00 0.000e+00 2.000e-09 ... 9.840e-08 9.840e-08 9.220e-08]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1fd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 39.015607833862305 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 0.0001} is: \n",
-      "[[2.00000002e-07 1.20000000e-07 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.20000000e-07 2.00000002e-07 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000002e-07 ... 2.00000002e-07\n",
-      "  2.00000002e-07 2.00000002e-07]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000002e-07 ... 1.05200001e-05\n",
-      "  1.05200001e-05 9.84000008e-06]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000002e-07 ... 1.05200001e-05\n",
-      "  1.05200001e-05 9.84000008e-06]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000002e-07 ... 9.84000008e-06\n",
-      "  9.84000008e-06 9.22000008e-06]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1588>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 39.7978618144989 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 0.001} is: \n",
-      "[[2.00000160e-05 1.20000000e-05 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.20000000e-05 2.00000160e-05 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000160e-05 ... 2.00000160e-05\n",
-      "  2.00000160e-05 2.00000160e-05]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000160e-05 ... 1.05200103e-03\n",
-      "  1.05200103e-03 9.84000752e-04]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000160e-05 ... 1.05200103e-03\n",
-      "  1.05200103e-03 9.84000752e-04]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000160e-05 ... 9.84000752e-04\n",
-      "  9.84000752e-04 9.22000804e-04]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256f2198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 37.74085330963135 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 0.01} is: \n",
-      "[[0.00200016 0.0012     0.         ... 0.         0.         0.        ]\n",
-      " [0.0012     0.00200016 0.         ... 0.         0.         0.        ]\n",
-      " [0.         0.         0.00200016 ... 0.00200016 0.00200016 0.00200016]\n",
-      " ...\n",
-      " [0.         0.         0.00200016 ... 0.10521032 0.10521032 0.09840752]\n",
-      " [0.         0.         0.00200016 ... 0.10521032 0.10521032 0.09840752]\n",
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1588>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 38.34471583366394 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 0.1} is: \n",
-      "[[ 0.201604    0.12        0.         ...  0.          0.\n",
-      "   0.        ]\n",
-      " [ 0.12        0.20161616  0.         ...  0.          0.\n",
-      "   0.        ]\n",
-      " [ 0.          0.          0.201604   ...  0.201604    0.201604\n",
-      "   0.201604  ]\n",
-      " ...\n",
-      " [ 0.          0.          0.201604   ... 10.62461674 10.62462998\n",
-      "   9.91626513]\n",
-      " [ 0.          0.          0.201604   ... 10.62462998 10.62470302\n",
-      "   9.91641722]\n",
-      " [ 0.          0.          0.201604   ...  9.91626513  9.91641722\n",
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 38.08292031288147 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 1.0} is: \n",
-      "[[  40.   12.    0. ...    0.    0.    0.]\n",
-      " [  12.   68.    0. ...    0.    0.    0.]\n",
-      " [   0.    0.   40. ...   40.   40.   40.]\n",
-      " ...\n",
-      " [   0.    0.   40. ... 5812. 4962. 3816.]\n",
-      " [   0.    0.   40. ... 4962. 5996. 5030.]\n",
-      " [   0.    0.   40. ... 3816. 5030. 9688.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688e59b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 38.2300386428833 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 10.0} is: \n",
-      "[[4.16200000e+06 1.20000000e+03 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.20000000e+03 1.61616200e+09 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 4.16200000e+06 ... 4.16200000e+06\n",
-      "  4.16200000e+06 4.16200000e+06]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 4.16200000e+06 ... 4.58167818e+14\n",
-      "  8.59206324e+13 1.21226362e+12]\n",
-      " [0.00000000e+00 0.00000000e+00 4.16200000e+06 ... 8.59206324e+13\n",
-      "  3.57910702e+14 5.91280962e+12]\n",
-      " [0.00000000e+00 0.00000000e+00 4.16200000e+06 ... 1.21226362e+12\n",
-      "  5.91280962e+12 1.68787581e+13]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688e59b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 38.85551071166992 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 100.0} is: \n",
-      "[[4.00160020e+12 1.20000000e+05 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.20000000e+05 1.60016002e+17 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00160020e+12 ... 4.00160020e+12\n",
-      "  4.00160020e+12 4.00160020e+12]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 4.00160020e+12 ... 4.48100809e+26\n",
-      "  8.00584079e+25 1.12091211e+22]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00160020e+12 ... 8.00584079e+25\n",
-      "  3.48098011e+26 5.76151612e+22]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00160020e+12 ... 1.12091211e+22\n",
-      "  5.76151612e+22 1.64839642e+23]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAACjpJREFUeJzt3M+P3HUdx/HnS8AajUYatEEgSkwPwsEN2aAHYmpI+HUpXghebAxJPcAfACc8cjEkJEpSk4Z6EOyF0EMjkF44qdSkYlGJjZbQWloVgwZikfL2sN+GSe26b3Z25rs/no9kMzOf/c7u+9Ntn5nv7ExTVUjSSj429gCSNgZjIanFWEhqMRaSWoyFpBZjIall9FgkuSvJa0lOJHl47HlmJcnJJL9NcizJ0WFte5IXk/xxuLx67DmnkWR/knNJjk+sXXaPWfLE8HN/Jckt402+esvs+ftJTg8/62NJ7pn43CPDnl9Lcuc4U6/OqLFIcgXwQ+Bu4Cbg20luGnOmGftmVS1U1eJw+2HgSFXtBI4Mtzeyp4C7Lllbbo93AzuHj73Ak3Oaca09xf/uGeDx4We9UFWHAYa/2/cDNw/3+dHwb2BDGPuRxa3Aiar6U1W9BzwD7B55pnnaDRwYrh8A7h1xlqlV1UvAW5csL7fH3cBPaskvgM8muXY+k66dZfa8nN3AM1V1vqr+DJxg6d/AhjB2LK4D3pi4fWpY24wKeCHJr5PsHdZ2VNWZ4fqbwI5xRpup5fa42X/2Dw2nV/snTi839J7HjsVWcltV3cLSw+8Hk3xj8pO19Lr7Tf3a+62wx8GTwJeBBeAM8INxx1kbY8fiNHDDxO3rh7VNp6pOD5fngGdZevh59uJD7+Hy3HgTzsxye9y0P/uqOltVF6rqA+DHfHiqsaH3PHYsXgZ2JrkxycdZevLn0Mgzrbkkn0ry6YvXgTuA4yztdc9w2B7guXEmnKnl9ngI+M7wW5GvA29PnK5saJc89/Itln7WsLTn+5NsS3IjS0/u/mre863WlWN+86p6P8lDwPPAFcD+qnp1zJlmZAfwbBJY+jP/aVX9PMnLwMEkDwCvA/eNOOPUkjwN7AKuSXIKeBR4jMvv8TBwD0tP8r0LfHfuA6+BZfa8K8kCS6dcJ4HvAVTVq0kOAr8D3gcerKoLY8y9GvEt6pI6xj4NkbRBGAtJLcZCUouxkNRiLCS1zCwWH/XdpBMvgd4y3PPWsFn2PJNYrPLdpJviD/Qjcs9bw6bY86weWWz1d5NKm86sXsF5uXfXfW25gz+ebfUJPslnsn1LvULMPW8N63nP/+Yd3qvz6Rw72su9h/O4vbD0h3nbh/+ZkKQ5+WUdaR87q9OQFd9dV1X7qmqxqhavYtuMxpC0VmYViy3xblJpK5nJacgWejeptGXM7DmL4T8pPTyrry9pvnwFp6QWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqunObOSU4C/wIuAO9X1WKS7cDPgC8BJ4H7quof040paWxr8cjim1W1UFWLw+2HgSNVtRM4MtyWtMHN4jRkN3BguH4AuHcG30PSnE0biwJeSPLrJHuHtR1VdWa4/iawY8rvIWkdmOo5C+C2qjqd5PPAi0n+MPnJqqokdbk7DnHZC/AJPjnlGJJmbapHFlV1erg8BzwL3AqcTXItwHB5bpn77quqxapavIpt04whaQ5WHYskn0ry6YvXgTuA48AhYM9w2B7guWmHlDS+aU5DdgDPJrn4dX5aVT9P8jJwMMkDwOvAfdOPKWlsq45FVf0J+Opl1v8O3D7NUJLWH1/BKanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpJYVY5Fkf5JzSY5PrG1P8mKSPw6XVw/rSfJEkhNJXklyyyyHlzQ/nUcWTwF3XbL2MHCkqnYCR4bbAHcDO4ePvcCTazOmpLGtGIuqegl465Ll3cCB4foB4N6J9Z/Ukl8An01y7VoNK2k8q33OYkdVnRmuvwnsGK5fB7wxcdypYU3SBjf1E5xVVUB91Psl2ZvkaJKj/+H8tGNImrHVxuLsxdOL4fLcsH4auGHiuOuHtf9RVfuqarGqFq9i2yrHkDQvq43FIWDPcH0P8NzE+neG34p8HXh74nRF0gZ25UoHJHka2AVck+QU8CjwGHAwyQPA68B9w+GHgXuAE8C7wHdnMLOkEawYi6r69jKfuv0yxxbw4LRDSVp/fAWnpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRbSlD721a+MPcJcGAtpSh/85vdjjzAXxkJSi7GQ1GIsJLWsGIsk+5OcS3J8Yu37SU4nOTZ83DPxuUeSnEjyWpI7ZzW4pPnqPLJ4CrjrMuuPV9XC8HEYIMlNwP3AzcN9fpTkirUaVtJ4VoxFVb0EvNX8eruBZ6rqfFX9GTgB3DrFfJLWiWmes3goySvDacrVw9p1wBsTx5wa1iRtcKuNxZPAl4EF4Azwg4/6BZLsTXI0ydH/cH6VY0ial1XFoqrOVtWFqvoA+DEfnmqcBm6YOPT6Ye1yX2NfVS1W1eJVbFvNGJLmaFWxSHLtxM1vARd/U3IIuD/JtiQ3AjuBX003oqT14MqVDkjyNLALuCbJKeBRYFeSBaCAk8D3AKrq1SQHgd8B7wMPVtWF2YwuaZ5SVWPPwGeyvb6W28ceQ9pyfllH+Ge9lc6xvoJTUouxkNRiLCS1GAtpHXj+L8d4/i/Hxh7j/zIWklpW/NWppNm78wsLY4+wIh9ZSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqSVVNfYMJPkr8A7wt7FnmbNrcM9bwXre8xer6nOdA9dFLACSHK2qxbHnmCf3vDVslj17GiKpxVhIallPsdg39gAjcM9bw6bY87p5zkLS+raeHllIWseMhaQWYyGpxVhIajEWklr+C1snaM2NmQcwAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 38.63768792152405 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 1000.0} is: \n",
-      "[[4.00001600e+18 1.20000000e+07 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.20000000e+07 1.60000160e+25 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00001600e+18 ... 4.00001600e+18\n",
-      "  4.00001600e+18 4.00001600e+18]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 4.00001600e+18 ... 4.48001008e+38\n",
-      "  8.00005840e+37 1.12000912e+32]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00001600e+18 ... 8.00005840e+37\n",
-      "  3.48000980e+38 5.76001516e+32]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00001600e+18 ... 1.12000912e+32\n",
-      "  5.76001516e+32 1.64800396e+33]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1588>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 39.028568506240845 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 10000.0} is: \n",
-      "[[4.00000016e+24 1.20000000e+09 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.20000000e+09 1.60000002e+33 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000016e+24 ... 4.00000016e+24\n",
-      "  4.00000016e+24 4.00000016e+24]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000016e+24 ... 4.48000010e+50\n",
-      "  8.00000058e+49 1.12000009e+42]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000016e+24 ... 8.00000058e+49\n",
-      "  3.48000010e+50 5.76000015e+42]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000016e+24 ... 1.12000009e+42\n",
-      "  5.76000015e+42 1.64800004e+43]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 38.40130877494812 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 100000.0} is: \n",
-      "[[4.00000000e+30 1.20000000e+11 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.20000000e+11 1.60000000e+41 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000000e+30 ... 4.00000000e+30\n",
-      "  4.00000000e+30 4.00000000e+30]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000000e+30 ... 4.48000000e+62\n",
-      "  8.00000001e+61 1.12000000e+52]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000000e+30 ... 8.00000001e+61\n",
-      "  3.48000000e+62 5.76000000e+52]\n",
-      " [0.00000000e+00 0.00000000e+00 4.00000000e+30 ... 1.12000000e+52\n",
-      "  5.76000000e+52 1.64800000e+53]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2466cb70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 37.19001770019531 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 1000000.0} is: \n",
-      "[[4.000e+36 1.200e+13 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.200e+13 1.600e+49 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 4.000e+36 ... 4.000e+36 4.000e+36 4.000e+36]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 4.000e+36 ... 4.480e+74 8.000e+73 1.120e+62]\n",
-      " [0.000e+00 0.000e+00 4.000e+36 ... 8.000e+73 3.480e+74 5.760e+62]\n",
-      " [0.000e+00 0.000e+00 4.000e+36 ... 1.120e+62 5.760e+62 1.648e+63]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb6c1443c8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 36.65269470214844 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 10000000.0} is: \n",
-      "[[4.000e+42 1.200e+15 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.200e+15 1.600e+57 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 4.000e+42 ... 4.000e+42 4.000e+42 4.000e+42]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 4.000e+42 ... 4.480e+86 8.000e+85 1.120e+72]\n",
-      " [0.000e+00 0.000e+00 4.000e+42 ... 8.000e+85 3.480e+86 5.760e+72]\n",
-      " [0.000e+00 0.000e+00 4.000e+42 ... 1.120e+72 5.760e+72 1.648e+73]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2466cb70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 36.98673963546753 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 100000000.0} is: \n",
-      "[[4.000e+48 1.200e+17 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.200e+17 1.600e+65 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 4.000e+48 ... 4.000e+48 4.000e+48 4.000e+48]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 4.000e+48 ... 4.480e+98 8.000e+97 1.120e+82]\n",
-      " [0.000e+00 0.000e+00 4.000e+48 ... 8.000e+97 3.480e+98 5.760e+82]\n",
-      " [0.000e+00 0.000e+00 4.000e+48 ... 1.120e+82 5.760e+82 1.648e+83]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAACjpJREFUeJzt3M+P3HUdx/HnS8AajUYatEEgSkwPwsEN2aAHYmpI+HUpXghebAxJPcAfACc8cjEkJEpSk4Z6EOyF0EMjkF44qdSkYlGJjZbQWloVgwZikfL2sN+GSe26b3Z25rs/no9kMzOf/c7u+9Ntn5nv7ExTVUjSSj429gCSNgZjIanFWEhqMRaSWoyFpBZjIall9FgkuSvJa0lOJHl47HlmJcnJJL9NcizJ0WFte5IXk/xxuLx67DmnkWR/knNJjk+sXXaPWfLE8HN/Jckt402+esvs+ftJTg8/62NJ7pn43CPDnl9Lcuc4U6/OqLFIcgXwQ+Bu4Cbg20luGnOmGftmVS1U1eJw+2HgSFXtBI4Mtzeyp4C7Lllbbo93AzuHj73Ak3Oaca09xf/uGeDx4We9UFWHAYa/2/cDNw/3+dHwb2BDGPuRxa3Aiar6U1W9BzwD7B55pnnaDRwYrh8A7h1xlqlV1UvAW5csL7fH3cBPaskvgM8muXY+k66dZfa8nN3AM1V1vqr+DJxg6d/AhjB2LK4D3pi4fWpY24wKeCHJr5PsHdZ2VNWZ4fqbwI5xRpup5fa42X/2Dw2nV/snTi839J7HjsVWcltV3cLSw+8Hk3xj8pO19Lr7Tf3a+62wx8GTwJeBBeAM8INxx1kbY8fiNHDDxO3rh7VNp6pOD5fngGdZevh59uJD7+Hy3HgTzsxye9y0P/uqOltVF6rqA+DHfHiqsaH3PHYsXgZ2JrkxycdZevLn0Mgzrbkkn0ry6YvXgTuA4yztdc9w2B7guXEmnKnl9ngI+M7wW5GvA29PnK5saJc89/Itln7WsLTn+5NsS3IjS0/u/mre863WlWN+86p6P8lDwPPAFcD+qnp1zJlmZAfwbBJY+jP/aVX9PMnLwMEkDwCvA/eNOOPUkjwN7AKuSXIKeBR4jMvv8TBwD0tP8r0LfHfuA6+BZfa8K8kCS6dcJ4HvAVTVq0kOAr8D3gcerKoLY8y9GvEt6pI6xj4NkbRBGAtJLcZCUouxkNRiLCS1zCwWH/XdpBMvgd4y3PPWsFn2PJNYrPLdpJviD/Qjcs9bw6bY86weWWz1d5NKm86sXsF5uXfXfW25gz+ebfUJPslnsn1LvULMPW8N63nP/+Yd3qvz6Rw72su9h/O4vbD0h3nbh/+ZkKQ5+WUdaR87q9OQFd9dV1X7qmqxqhavYtuMxpC0VmYViy3xblJpK5nJacgWejeptGXM7DmL4T8pPTyrry9pvnwFp6QWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqunObOSU4C/wIuAO9X1WKS7cDPgC8BJ4H7quof040paWxr8cjim1W1UFWLw+2HgSNVtRM4MtyWtMHN4jRkN3BguH4AuHcG30PSnE0biwJeSPLrJHuHtR1VdWa4/iawY8rvIWkdmOo5C+C2qjqd5PPAi0n+MPnJqqokdbk7DnHZC/AJPjnlGJJmbapHFlV1erg8BzwL3AqcTXItwHB5bpn77quqxapavIpt04whaQ5WHYskn0ry6YvXgTuA48AhYM9w2B7guWmHlDS+aU5DdgDPJrn4dX5aVT9P8jJwMMkDwOvAfdOPKWlsq45FVf0J+Opl1v8O3D7NUJLWH1/BKanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpJYVY5Fkf5JzSY5PrG1P8mKSPw6XVw/rSfJEkhNJXklyyyyHlzQ/nUcWTwF3XbL2MHCkqnYCR4bbAHcDO4ePvcCTazOmpLGtGIuqegl465Ll3cCB4foB4N6J9Z/Ukl8An01y7VoNK2k8q33OYkdVnRmuvwnsGK5fB7wxcdypYU3SBjf1E5xVVUB91Psl2ZvkaJKj/+H8tGNImrHVxuLsxdOL4fLcsH4auGHiuOuHtf9RVfuqarGqFq9i2yrHkDQvq43FIWDPcH0P8NzE+neG34p8HXh74nRF0gZ25UoHJHka2AVck+QU8CjwGHAwyQPA68B9w+GHgXuAE8C7wHdnMLOkEawYi6r69jKfuv0yxxbw4LRDSVp/fAWnpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRbSlD721a+MPcJcGAtpSh/85vdjjzAXxkJSi7GQ1GIsJLWsGIsk+5OcS3J8Yu37SU4nOTZ83DPxuUeSnEjyWpI7ZzW4pPnqPLJ4CrjrMuuPV9XC8HEYIMlNwP3AzcN9fpTkirUaVtJ4VoxFVb0EvNX8eruBZ6rqfFX9GTgB3DrFfJLWiWmes3goySvDacrVw9p1wBsTx5wa1iRtcKuNxZPAl4EF4Azwg4/6BZLsTXI0ydH/cH6VY0ial1XFoqrOVtWFqvoA+DEfnmqcBm6YOPT6Ye1yX2NfVS1W1eJVbFvNGJLmaFWxSHLtxM1vARd/U3IIuD/JtiQ3AjuBX003oqT14MqVDkjyNLALuCbJKeBRYFeSBaCAk8D3AKrq1SQHgd8B7wMPVtWF2YwuaZ5SVWPPwGeyvb6W28ceQ9pyfllH+Ge9lc6xvoJTUouxkNRiLCS1GAtpHXj+L8d4/i/Hxh7j/zIWklpW/NWppNm78wsLY4+wIh9ZSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqSVVNfYMJPkr8A7wt7FnmbNrcM9bwXre8xer6nOdA9dFLACSHK2qxbHnmCf3vDVslj17GiKpxVhIallPsdg39gAjcM9bw6bY87p5zkLS+raeHllIWseMhaQWYyGpxVhIajEWklr+C1snaM2NmQcwAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468c8d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 36.94209051132202 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 1000000000.0} is: \n",
-      "[[4.000e+054 1.200e+019 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
-      " [1.200e+019 1.600e+073 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
-      " [0.000e+000 0.000e+000 4.000e+054 ... 4.000e+054 4.000e+054 4.000e+054]\n",
-      " ...\n",
-      " [0.000e+000 0.000e+000 4.000e+054 ... 4.480e+110 8.000e+109 1.120e+092]\n",
-      " [0.000e+000 0.000e+000 4.000e+054 ... 8.000e+109 3.480e+110 5.760e+092]\n",
-      " [0.000e+000 0.000e+000 4.000e+054 ... 1.120e+092 5.760e+092 1.648e+093]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1fd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 36.80334544181824 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 3.0, 'lmda': 10000000000.0} is: \n",
-      "[[4.000e+060 1.200e+021 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
-      " [1.200e+021 1.600e+081 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
-      " [0.000e+000 0.000e+000 4.000e+060 ... 4.000e+060 4.000e+060 4.000e+060]\n",
-      " ...\n",
-      " [0.000e+000 0.000e+000 4.000e+060 ... 4.480e+122 8.000e+121 1.120e+102]\n",
-      " [0.000e+000 0.000e+000 4.000e+060 ... 8.000e+121 3.480e+122 5.760e+102]\n",
-      " [0.000e+000 0.000e+000 4.000e+060 ... 1.120e+102 5.760e+102 1.648e+103]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.22227382659912 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 1e-10} is: \n",
-      "[[  20.           12.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [  12.           20.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [   0.            0.           20.         ...   20.\n",
-      "    20.           20.        ]\n",
-      " ...\n",
-      " [   0.            0.           20.         ... 1052.00000018\n",
-      "  1052.00000018  984.00000018]\n",
-      " [   0.            0.           20.         ... 1052.00000018\n",
-      "  1052.00000019  984.0000002 ]\n",
-      " [   0.            0.           20.         ...  984.00000018\n",
-      "   984.0000002   922.00000032]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 41.80288052558899 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 1e-09} is: \n",
-      "[[  20.00000002   12.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [  12.           20.00000003    0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [   0.            0.           20.00000002 ...   20.00000002\n",
-      "    20.00000002   20.00000002]\n",
-      " ...\n",
-      " [   0.            0.           20.00000002 ... 1052.00000179\n",
-      "  1052.00000181  984.00000181]\n",
-      " [   0.            0.           20.00000002 ... 1052.00000181\n",
-      "  1052.00000188  984.00000195]\n",
-      " [   0.            0.           20.00000002 ...  984.00000181\n",
-      "   984.00000195  922.00000315]]\n"
-     ]
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb689026d8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.09841823577881 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 1e-08} is: \n",
-      "[[  20.0000002    12.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [  12.           20.00000032    0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [   0.            0.           20.0000002  ...   20.0000002\n",
-      "    20.0000002    20.0000002 ]\n",
-      " ...\n",
-      " [   0.            0.           20.0000002  ... 1052.00001792\n",
-      "  1052.00001806  984.00001808]\n",
-      " [   0.            0.           20.0000002  ... 1052.00001806\n",
-      "  1052.00001876  984.00001954]\n",
-      " [   0.            0.           20.0000002  ...  984.00001808\n",
-      "   984.00001954  922.00003154]]\n"
-     ]
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256f21d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.24132227897644 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 1e-07} is: \n",
-      "[[  20.000002    12.           0.        ...    0.           0.\n",
-      "     0.       ]\n",
-      " [  12.          20.0000032    0.        ...    0.           0.\n",
-      "     0.       ]\n",
-      " [   0.           0.          20.000002  ...   20.000002    20.000002\n",
-      "    20.000002 ]\n",
-      " ...\n",
-      " [   0.           0.          20.000002  ... 1052.0001792 1052.0001806\n",
-      "   984.0001808]\n",
-      " [   0.           0.          20.000002  ... 1052.0001806 1052.0001876\n",
-      "   984.0001954]\n",
-      " [   0.           0.          20.000002  ...  984.0001808  984.0001954\n",
-      "   922.0003154]]\n"
-     ]
-    },
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1f98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.24935579299927 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 1e-06} is: \n",
-      "[[  20.00002    12.          0.       ...    0.          0.\n",
-      "     0.      ]\n",
-      " [  12.         20.000032    0.       ...    0.          0.\n",
-      "     0.      ]\n",
-      " [   0.          0.         20.00002  ...   20.00002    20.00002\n",
-      "    20.00002 ]\n",
-      " ...\n",
-      " [   0.          0.         20.00002  ... 1052.001792 1052.001806\n",
-      "   984.001808]\n",
-      " [   0.          0.         20.00002  ... 1052.001806 1052.001876\n",
-      "   984.001954]\n",
-      " [   0.          0.         20.00002  ...  984.001808  984.001954\n",
-      "   922.003154]]\n"
-     ]
-    },
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 41.932133436203 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 1e-05} is: \n",
-      "[[  20.0002       12.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [  12.           20.00032       0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [   0.            0.           20.0002     ...   20.0002\n",
-      "    20.0002       20.0002    ]\n",
-      " ...\n",
-      " [   0.            0.           20.0002     ... 1052.01792018\n",
-      "  1052.01806017  984.01808009]\n",
-      " [   0.            0.           20.0002     ... 1052.01806017\n",
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.69877338409424 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 0.0001} is: \n",
-      "[[  20.002        12.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [  12.           20.00320016    0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [   0.            0.           20.002      ...   20.002\n",
-      "    20.002        20.002     ]\n",
-      " ...\n",
-      " [   0.            0.           20.002      ... 1052.179218\n",
-      "  1052.18061656  984.18080912]\n",
-      " [   0.            0.           20.002      ... 1052.18061656\n",
-      "  1052.18761912  984.19541516]\n",
-      " [   0.            0.           20.002      ...  984.18080912\n",
-      "   984.19541516  922.31543964]]\n"
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.39898371696472 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 0.001} is: \n",
-      "[[  20.02         12.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [  12.           20.032016      0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [   0.            0.           20.02       ...   20.02\n",
-      "    20.02         20.02      ]\n",
-      " ...\n",
-      " [   0.            0.           20.02       ... 1053.79380088\n",
-      "  1053.80765645  985.80891211]\n",
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb689026d8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.85403847694397 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 0.01} is: \n",
-      "[[  20.2          12.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [  12.           20.3216        0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [   0.            0.           20.2        ...   20.2\n",
-      "    20.2          20.2       ]\n",
-      " ...\n",
-      " [   0.            0.           20.2        ... 1070.10088288\n",
-      "  1070.226048   1002.171312  ]\n",
-      " [   0.            0.           20.2        ... 1070.226048\n",
-      "  1070.95207088 1003.692176  ]\n",
-      " [   0.            0.           20.2        ... 1002.171312\n",
-      "  1003.692176    953.938048  ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.31627321243286 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 0.1} is: \n",
-      "[[  22.       12.        0.     ...    0.        0.        0.    ]\n",
-      " [  12.       23.36      0.     ...    0.        0.        0.    ]\n",
-      " [   0.        0.       22.     ...   22.       22.       22.    ]\n",
-      " ...\n",
-      " [   0.        0.       22.     ... 1250.1088 1249.608  1174.032 ]\n",
-      " [   0.        0.       22.     ... 1249.608  1259.6168 1195.136 ]\n",
-      " [   0.        0.       22.     ... 1174.032  1195.136  1278.688 ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f81d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.66733121871948 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 1.0} is: \n",
-      "[[  40.   12.    0. ...    0.    0.    0.]\n",
-      " [  12.   68.    0. ...    0.    0.    0.]\n",
-      " [   0.    0.   40. ...   40.   40.   40.]\n",
-      " ...\n",
-      " [   0.    0.   40. ... 5812. 4962. 3816.]\n",
-      " [   0.    0.   40. ... 4962. 5996. 5030.]\n",
-      " [   0.    0.   40. ... 3816. 5030. 9688.]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468cfd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.950223207473755 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 10.0} is: \n",
-      "[[2.200000e+02 1.200000e+01 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
-      "  0.000000e+00]\n",
-      " [1.200000e+01 1.940000e+03 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
-      "  0.000000e+00]\n",
-      " [0.000000e+00 0.000000e+00 2.200000e+02 ... 2.200000e+02 2.200000e+02\n",
-      "  2.200000e+02]\n",
-      " ...\n",
-      " [0.000000e+00 0.000000e+00 2.200000e+02 ... 3.958972e+06 6.327120e+05\n",
-      "  2.222640e+05]\n",
-      " [0.000000e+00 0.000000e+00 2.200000e+02 ... 6.327120e+05 3.959012e+06\n",
-      "  7.481240e+05]\n",
-      " [0.000000e+00 0.000000e+00 2.200000e+02 ... 2.222640e+05 7.481240e+05\n",
-      "  2.076862e+06]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24637b70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.9415488243103 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 100.0} is: \n",
-      "[[2.02000000e+03 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.20000000e+01 1.63220000e+05 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 2.02000000e+03 ... 2.02000000e+03\n",
-      "  2.02000000e+03 2.02000000e+03]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 2.02000000e+03 ... 2.96981803e+10\n",
-      "  4.64741652e+08 1.21301784e+08]\n",
-      " [0.00000000e+00 0.00000000e+00 2.02000000e+03 ... 4.64741652e+08\n",
-      "  2.96873087e+10 5.91356384e+08]\n",
-      " [0.00000000e+00 0.00000000e+00 2.02000000e+03 ... 1.21301784e+08\n",
-      "  5.91356384e+08 1.68795632e+09]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb68902ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.234039068222046 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 1000.0} is: \n",
-      "[[2.00200000e+04 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.20000000e+01 1.60320200e+07 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00200000e+04 ... 2.00200000e+04\n",
-      "  2.00200000e+04 2.00200000e+04]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 2.00200000e+04 ... 2.88881802e+14\n",
-      "  4.49657807e+11 1.12913809e+11]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00200000e+04 ... 4.49657807e+11\n",
-      "  2.88869914e+14 5.77517955e+11]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00200000e+04 ... 1.12913809e+11\n",
-      "  5.77517955e+11 1.65196715e+12]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.92475128173828 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 10000.0} is: \n",
-      "[[2.00020000e+05 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.20000000e+01 1.60032002e+09 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00020000e+05 ... 2.00020000e+05\n",
-      "  2.00020000e+05 2.00020000e+05]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 2.00020000e+05 ... 2.88088018e+18\n",
-      "  4.48165618e+14 1.12091218e+14]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00020000e+05 ... 4.48165618e+14\n",
-      "  2.88086819e+18 5.76151620e+14]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00020000e+05 ... 1.12091218e+14\n",
-      "  5.76151620e+14 1.64839643e+15]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.67373847961426 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 100000.0} is: \n",
-      "[[2.00002000e+06 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.20000000e+01 1.60003200e+11 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00002000e+06 ... 2.00002000e+06\n",
-      "  2.00002000e+06 2.00002000e+06]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 2.00002000e+06 ... 2.88008800e+22\n",
-      "  4.48016560e+17 1.12009120e+17]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00002000e+06 ... 4.48016560e+17\n",
-      "  2.88008680e+22 5.76015160e+17]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00002000e+06 ... 1.12009120e+17\n",
-      "  5.76015160e+17 1.64803964e+18]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468cfd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.39040184020996 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 1000000.0} is: \n",
-      "[[2.00000200e+07 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.20000000e+01 1.60000320e+13 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000200e+07 ... 2.00000200e+07\n",
-      "  2.00000200e+07 2.00000200e+07]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000200e+07 ... 2.88000880e+26\n",
-      "  4.48001656e+20 1.12000912e+20]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000200e+07 ... 4.48001656e+20\n",
-      "  2.88000868e+26 5.76001516e+20]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000200e+07 ... 1.12000912e+20\n",
-      "  5.76001516e+20 1.64800396e+21]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f81d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.562543630599976 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 10000000.0} is: \n",
-      "[[2.00000020e+08 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.20000000e+01 1.60000032e+15 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000020e+08 ... 2.00000020e+08\n",
-      "  2.00000020e+08 2.00000020e+08]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000020e+08 ... 2.88000088e+30\n",
-      "  4.48000166e+23 1.12000091e+23]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000020e+08 ... 4.48000166e+23\n",
-      "  2.88000087e+30 5.76000152e+23]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000020e+08 ... 1.12000091e+23\n",
-      "  5.76000152e+23 1.64800040e+24]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe26a0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.47181940078735 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 100000000.0} is: \n",
-      "[[2.00000002e+09 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.20000000e+01 1.60000003e+17 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000002e+09 ... 2.00000002e+09\n",
-      "  2.00000002e+09 2.00000002e+09]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000002e+09 ... 2.88000009e+34\n",
-      "  4.48000017e+26 1.12000009e+26]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000002e+09 ... 4.48000017e+26\n",
-      "  2.88000009e+34 5.76000015e+26]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000002e+09 ... 1.12000009e+26\n",
-      "  5.76000015e+26 1.64800004e+27]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.51755976676941 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 1000000000.0} is: \n",
-      "[[2.00000000e+10 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.20000000e+01 1.60000000e+19 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000000e+10 ... 2.00000000e+10\n",
-      "  2.00000000e+10 2.00000000e+10]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000000e+10 ... 2.88000001e+38\n",
-      "  4.48000002e+29 1.12000001e+29]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000000e+10 ... 4.48000002e+29\n",
-      "  2.88000001e+38 5.76000002e+29]\n",
-      " [0.00000000e+00 0.00000000e+00 2.00000000e+10 ... 1.12000001e+29\n",
-      "  5.76000002e+29 1.64800000e+30]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb6c144390>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 42.55279183387756 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 3.0, 'lmda': 10000000000.0} is: \n",
-      "[[2.000e+11 1.200e+01 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.200e+01 1.600e+21 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 2.000e+11 ... 2.000e+11 2.000e+11 2.000e+11]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 2.000e+11 ... 2.880e+42 4.480e+32 1.120e+32]\n",
-      " [0.000e+00 0.000e+00 2.000e+11 ... 4.480e+32 2.880e+42 5.760e+32]\n",
-      " [0.000e+00 0.000e+00 2.000e+11 ... 1.120e+32 5.760e+32 1.648e+33]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe2ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.88088607788086 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 1e-10} is: \n",
-      "[[6.50000000e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 7.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.50000000e+01 ... 8.10000000e+01\n",
-      "  8.10000000e+01 8.10000000e+01]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 8.10000000e+01 ... 4.64900000e+03\n",
-      "  4.54500000e+03 4.54900000e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.10000000e+01 ... 4.54500000e+03\n",
-      "  4.44700000e+03 4.44100000e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.10000000e+01 ... 4.54900000e+03\n",
-      "  4.44100000e+03 4.47100001e+03]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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UY/RDXmVLE5sj6OQYbK6JPey68lUYD6KUOdpLLKhbimFbbI5W4oLa8yTjijK33gNXS/ADnV+WoLa4Uppx+/xRbXFN3bHyO3MnhxH+6fPa2m0asUyXE6BfaTE1TbI+eBxB9yUlml5k50CFlRE//TwpsFRI5h38ZVuN0xTjLmBYvLzaKiRDvz9c/BDgPMhBDrKX3AnLgoHtFU+r73YWIU2qH5nF1GTTxNOS3V3nNC0fuPZ1ncYehgFk8GcTuoFuDYU5vms45XdmEUSu3YTCFOaURrtllKVZIyYOBc5Ev2OWP9T1yN8BGEYJdgLZ/B7HbSqAm1Twmth9pTyvvCPGwOa6QO9zMc6UZpxiV15HQqhjGfo3J+umsDpTGl0qVUl/p36SZi0xIdfMFTPLXE8rf5kzAvUNlnPcCWUBDWCVtSEGwjLUXgnSSoArIIN2vM+uByB8EuYPjla30W2blsMgpmvXqdKRr+PjJ3VOXs/lz04mmAMB35iiSm7Ny2IKm00dR2hmgMugLqduWIo5WGxBYyTu4f0Xgr4A5PhB5Bwr2fS1q2JzHkU506zbJglqfBU/opkGCp3fhr5fXO6sq6H5LH+v1+I/+rAOuE6DpUA2vcvAnMUVpiZ129SgKyi+oOtEIXgPPr/Iv806+U7dG/fxRxqIjSmzksZi57HvvEsvNB/NK5cBCoBizYZQoZjMRbMYBYcggXR7bp5f7o7TffXj5AY5C6J7h7joMiDM5mDIbnKVefrKh6DNAG7tngP4ky86KCvkDIdlO2i6fO96mMqfLSBpN6bvRRPbTSyOWZ0rRACTtKcpL6KcGjPQ1LSop+QtKDMUaTUOaXwcolhM+pl+HwZgM7kucjXoy65Ng4EWD+JxnJD96BiaBgCDl6utDAUwyVIMOftTZXqYRfnuWs3WqLJKunOtFKYoznRgWZF5s8rXWnyfxLvaYkjXSDm7VoLl1PpLEPj1Jl0PtW2+V7bolFklU8zeg84vtpGoHIG1KobyWizwWjw/XGaQVrv5POnKZ4VqiuVqCbdqK+ubJqn2KhsSj0Drvi5ZuEE90PujLErcRZHhKPEUW5V/djPLFJSlSK1qczBcQ1elmqjIVlTnMstAJ5zGEWg7oGRjgqykN7IsrC5GlRgVqyG5Ig3HLNmYl+A4AKTVeCtdVqQV03giA15X26lloZZUwiN0bQ6MFZYFxR1ZhHI+JpZFheko052O8hgsih8C0Czy/ntaFukYZfbJvlbLAprmpsU8YTi4a7PLYtkJIN/TxifcBh8vtiwL7GlZYGpZADstCz45ygFW27drtywLLgh+AGScBRHiyQyubQTjYfLJe5YNSVJVne6IYRjuguNLLYvkepTxjRKHYXJTy6IvYL06LoqcKxZ7W2HGW7UsDMdh15NWqqlbYNDy8vtd8ztIXGEX9gG4JctCxyhzM4lnTO/RdRSBb9KyuLxKeBBqfF6hp8xVEHdTyuYHkHe3b1lcuK0MB8d4I8vC9wPQD/XCsUu5XiOHbMhBDnKQveROWRapRD3EilwXKHAXD+5X1aMGtOKAajUyN6PCYXz4AQxSHZ8+lf0m+Ih0BI7gWGMTODq4tqlRikZQq0hJw3qETz/fjWkorYlyFTL4so3HsBtmRaUxCIKTinJjAnYD2NoayQhAVkLitPon1+LhfdAwXot9qI5cWBlbNsR1NHe7gnbzWY0OLTEhlHYEPIHmR4gvw2VcR55TYCeqEn3j9DQrqSRZdi5lddgOyzEXnY1O7v2De4iffF5zcQBbGIfpGNNsTGMGBY6i2m0xl2OeHudg9w8+BfymuiZzs6u/7RgG9KvOuX+25E4pixfKTVNA9iCUD5C5Ba9DeW8PfWVaFgi9N5iqeqFsuWn6WZrl0zQoACOvTYcx+LEhMt+mVHOIieafyNsYWwwwYpgq47ZLOAIBUoty+yPLmagQX/18Y0hp1SQ3ONidUhZJo+56mWO8HnfxIikYpRLV3Wu+0Fv1DMX0vz2mLK79/DSA7aDnls+/i9Jtwrz1VqSMOZRxgTLYZ+XWb3lsRJQxHDbOEr9TFh++DUnI4FxCcOMzX5MZ3FfujrIgqoJPbj6vA3f6EobHT+AfPMgBzKYR7IG5B0ChHPq63Zu6HgDgv/yxbKO4A4nWx0xOcnEp2Isx5KCkZgGoa3P16Hoj+xps+lxYmN03vi7R9PJh8h48V/dotUnQXuoH8PFCsjFPzuU4p8egdS/jGcY8rtUadKQuiGUk7KVvmnR8AKDlOgdV5+LipRoGM1cN6vxE5oZ++icyeYq9qM6BPYGUaj8uWtB6lOBrm6PpNASZn+TamRUmGYM03oJ7k9YadLaaCQ1SGsaBZ61gAy6uwH/2J/U69SUNLP9WCUcN3ErqIizbYK4EDVKN6i83aWzxZI7YODTPpA0gew9uJXsW3YRExpP8tlY3RK/bPzrH6ud/Gu35kLaL3sGvR4wnSmgzZKUcOn1OlGHNjQw3RIwLOd78sxWspQEVmaIwbxBbj+bpKmVeNj/7r2DzoMHsaV6g4szBr/P5YkPpfBQYzTpgnFulMBD/YE8uVxwCnAc5yEH2lLtjWUwkMS8Zx2Xp31bFYVpRWLA2IUgKT+DTQ7Y4ylLvEhrOBGz6DJ/Ng6jN9yhIU0JOUfI4An1GiVqwzK17JJq5lGYtUqBjKNKhUajdygCtWSVGX1cG5oaxpqSz/cpjAmKpqfmcgnVlKbUdv5hTulpnXIAF6YzLwiojY5RzhQiMGf+R4h5TNyeyWBCTJkE0jMnaSIVfNq4Snj2OwNDDGZ6gNP+LUm/qR9AYZdUuAo00quvpXL5eZrirDajNSFu32ghyU1PNVKYVnRNchTUpMktvvUH3tM8Wi3NCbdeP2aIwnE9gNGqRxEYDqFEK2txGV3uz2JzLTYqcg98McN7DXa3SeLvzHhSBZlk8442D60Oax/Scegc3BFA/wne5UpjGLwAoi4ikU9gucZRMNYmcUw2IInq5P2f+PlM+huxsB1GgV8w1Ea/CqlzCmMvPEoSkJdUUUXOBNgo+4vra4B1wm6GRSQ0Hu8l4AQElcRFfiFqTECkBjChlBGJ93FepC7lmfOwJiMU86jgNeESBxd7WbYmN/9NK2V2NaH3V8Zi7bPeSKN02she3mlcALC8xcQG0cgDDZVfLxr3jnWaSTA0T1c2y9NwEKrJNr3eJwB1WFgBqdGDqm4GK3QjGIFQQ8zJz4pjYyTUBTdsBUvpNBCzmtRVgxLnepTQuEQFdK8dMvBFLTbmJ32uIUD5ZSFFVyA8CN16IWYmEEckQfusefLIAM8MpKIfnncQ1ulaKjEqS27aRcSTCHL2utgEvcl+TBBEexvR9Iqc1AJPxeuj1xvvHIAOW2XQ1dcwiLFq49Qjqmu2YxXrIFoSVqhMhnsxBG12VlZyWj+egVZ/HA1kZaYzpmnjWyH4xItyTWA23okSnyMdx4eE3sXau9RrcEMTnP1cwm3MIZzNwm2MT8WQBnnlQYLneTWFZNA6xdRITAcAzubZmDFh+ZYaZ8kJwQ4ie0KwDhhONSY1q+TAQZjmGAACuZ1BghIUMemFl8wDI4jFEGO8tEGYO3WMPp9ye6y8tsH7oMS84KcKM0LwoZrGKGPVcFAH+k/0jEXdbWewjU5QkkNCGVnW3M8ofCsUCKKQ4YrqqVp+ArKAxCsxb/64YwIvjk9HMpX1jMvuEhasY9xhlJS5clgrJWNRQJHIYM5NLyHTprowBcGLS08TdSPNm12am8hCSUkgr2whQYd24Ud2pwHJ8qBURtu+FHYdCkVZOAbyQzXqu6fnSeB0JkUzxEsl2xZzo3LtWFQ1hwu4N0DiB46sJzo6y62mLgi4aVYAzRjj29XcAECL8hpPLwZGAhkBDhOvVJR2KOWJTiiTjihIANeVBIRaweVsQRdnZ/bF77PsIv3FwY5myd3CbmDNLhhVyDBoZfhOyxcN4f1OnlRg12S6hwrxyXvxdR8XERDHbzD2xlb08RskdaXUkRJl8xHv1jX2+EU0jzNbG8gQArpd/u0m3LDPTS3BO4/NKHJp8LshKxRHwlhWw/Z0WiNl4vZf9YgkBz8dH2Yuj8bnWodhfrs/JfhPmJu4agAqFYqZ9kXWInRfLe4iIc109QwR5AgW/VaHJzkkmwa7V5oALeHZpWVDOZnDrU1o1qq/NaqIT60tn0zCTOED0LgGpKAIuRERHiJ2DG3R+xojYecRZvidMJBZDcOnlzXOploW+wGZZwDuMCwe/yuOPLYkVMbfMhylfIHZy3NCJa0ERcA0hzCnPrcZMnMXrvAM7Qpg5+NaDYpOudzgi+D4DyEJLkCIfPV9rxxClVY5L3hHsLYdsyEEOcpC95E5YFkQEalrw0JdfAkDqZl5CvCuykqFPaDtXdByLj59cT3kHgC8u63MZnZxVRM5n8u+y8IYZ8fllVeLLIYKulpmwV60h//jZziIpVxQQucIs9pdLMeGNwbofxDIaRvlc57mh9Qbx0ZPsXpVUb0VlZeKPKHqqcBFhL2M0Bon33/scO6UI1HqbsxjhSy5JZomNFJR2gGQ0qKBv80sNQj55ulWQlqwPy3AYtHwY0H5X8RmlW1hkRrqy0KocV5HV4FOFdIeIVn1/0k9+8jQTC5fkvABADq78Tq8xrje498dF/IgkwEtjwLwcg33afFvFqm4b7x3rXKk1RpQrWZ0DHj9Fq8+jjeFk3eN43m1VN1NQ96osICQCXS63KpDd8iX9Ywu5E8pil5AvzP+pVLTyGux02aQmazQzJeyNeZISWIu5zkAU5DU8azOnISB+rNHH2wM7jlK2ntKY+vDPZ1lZlIjEEixURvXVtUgBR+/F7rO0ny8ePO/rku90nglh79Aj1aNMCXsTWrJWIny8yMFjoC6dbrIignPy4LY5DWcBU3MXUuqv8VX8xRik3HK+RdhLXiqLyeZR55YN2DWZz5JSH54kDtG4wt1jSWPrCxKOFRSnMaHYevgrJb9ZLWT+TIlWPKqu/q4o7R8/OEnHABG4a0CrIbsqEYnRyq6dZz4BxWiIGO9LANpbANU7uKVu2zo0G70GlzuShQfHGE9n8Os6ZkZlvKuIuzntJJcAcO8jYS8DmMKUOQT5bxe8u2opKHT9BCHXBbAX5DrR1LEENjNxr05eP4ii2PRZWUybCr9IyloLU1IlZmEM1epH+ple5q7NAb1SYY3y4t8gLnUjoRCrICWVQVCznrwDWDI9FQltiFI2bdeg+1ovj5zBCq+WPp1S+DGDQqHMoqI/S/yAKTF9gfyV4WvkxfVjBK1vWEIwETeEfD4iAKMoyjFjPZLCsBzooGndGEEhwGnmJbUidC5lpXjYHS2gMcL1oc7aOLVOTFmYJfO66WHcEWWxU16EuZ+yKLEpjEJ29Q0pFVKpUDwkPVqsfqmvwySbwYOCZuz0+nJt9Q3ZFObdS3gzLQ+PEICZrnzDWAd5S4BQiPu3L7Tf9+wbssWnULZdaAyerpbOGCoXDcygtgG3RSYCXAdjgfRvXq+33JA0r3Ztxq8RQnbFrnFDyhekYhjvhxxAPZqn+aQxAMHnjMxq9UI3BDvcEO57uOermvymbUD9ANoUhEV6H1KZgPZlTY2PTNek+5MXDnJOeqZM3BB3sRIlVbohCo6buiEEgK5Wh/aFBznIQW5f7q5lMUFlVlIAsOA9QNpFPfln7qUxi9xaTlaRdK6yaY4FDIuGRnvHLGZdveLZZ8mPWf67bSorhu1vo7MrXYHm9mIWMN4EkxJlWjasAUC+8H9tRfMux100BUsw16V252h+w5iFAc7M6rMYUwn9Nt4KTfVyENYrm3uLZZAWx3HrEwEuLV4tZhHvHcFd6TxqmthtmtSSsIR7p3G1XnEq4k6EE41ZqJvEvngmPcGdHG/FLOLZEcaTTmIWJQ5HrWTmun2hU9rB9zpmAd7B7m3m8FrYvZ1yTpKXjtLJfNWHCz4gWHs7AP7sRLbXqlQAmbgGSDUJXFaUWi0JIFkPe+jNHGwb0PExKq7LYZCH/mop31tFqNVulC+e88JfCYA3m8TnyXYMQFjFAdDxkRDVNA2iKSSIqUyLBejkuAZAWTzEWKcBYJxJcHEMOSi43uRsQVF16o8WmRhlCvZSRUy9XovxPDKDSn86RskqTUxbhiiGslIYAPgkeJI1AAAgAElEQVTkKMVlWMfNdi0WDIViOI6PkqKz+o0pBycXmQEq+xERSWVv40GPnuXbcTSXQPaVVp3eP5OuZjEiKkpVfpCXjphz5axyWdLpURVTohiBAUh9X4HkYhgUHUBWFEMAIuAv5Hl3Ty93uuDxgzMZw8m8jnVFzohbQBRU4T6nmiAQ+i+forkcENtizr77BUBwVvBuE1uJ2xbgvv5322ZUpRwAOUyuUpSw20trtgt1XeXPkc9pSCpfGkfC/Gwv3xjkhSyzFQCwmEs6rXyhixJyAjLcmyj70s+KVVep+QGkT+57oeufdzWhrI6vKlFfbbT2gLfJYw3EZqvMSmMDx4v8wtmLbNdnf89bCQoy1xkSLWTjcYcfbPNRXDcfzwUeDuQSfIOVW1yj9cAQQMuAeKJpz8ZpHIOrmohw3MGtamp7YlnNaT2CWw+/KVr9nRxJ4ZUqt3Ck8O/IiAWMHVHOGT3BGa9m68EE+MsNNh8u0J2bZSG1Ia4PCMc650MOEtuLyk6u1W9iyuAAQDeEnbyY46mMzV8NcjwA4/05+vsNZsXLP849mnXePyawm4C62FECZUltyv6BzzurLF4kJSrT/r1VPGauRdlRu+x9YYEmU0BNI8qmMOOnQTcitShKRVLWpgCZcLdRVvFQ3IwSYdn4GlVZtK1Ln46Sgsq9WPVchvBETpVx4+Whs9WrNzeqeKnN8iACKGZOjbUU0sWuKejkXNrHkJWArF5WyVnVhgC121ZImg/9N1CY4kBCiLInCe7FEsEJRa7mVCIxJK08RZZOYPccWRUCSyqzTLu2ekyfjxtnjbhTrUPU14OYE4oy1cfMxNpy6wFh7hAtzdnkPqtBU6fO5aKy2OXnzhJvzlNWIqWLW0jsPGInaVa7gjD3GOcOzSzfgzB3Vjcn+xW1IeNCFOFoCE4unv895BDgPMhBDrKX3FnLYkrwWvJbGE0+AKHwD1E+y32U2j41AALqVWULk7HUoKMGmELM5KxFGz4Mg5jbZt4NmiKb9NGgi6vtmMXGJ1OcNxvQpohZ2GpuVavLpdAAKodGirVoGwAqiVmt8KmnCimZYhUh5nZ+1khH4wJl1y1mhnt6sTNmQUUcwa82OWZRpuFilOrVXX1DLorOcHrdrjy/05UbEEvRXB6n/x4D/FPpJnZdzMJddbsb/SoSlhsPvsotFJwC3Cxm4dtGanNiFOtpyHOTrDXjvrC6m2HE0feuMhKSKHUyby6si3rxDJgFRVTFLGzZdue7YxZdYwHWbLXNNyPa513m0gDQdU0Vw8iIUUI46eCvBsTOYoOoWLxeJndWWUxjFuQ9WLMaZdl5WYpexSy6NjUASqYpOSkyA+US9V5f7qMjUQaGJbha5oZCFs1uGokl2IMCgDZeUI/akcx6NvDpsby4ZWVpUUJOVz7HEVYb8JnAffH8Io8HSznfep0CoDyOoKOFwJYnTXDQ+ByBBySuYKg9dTeckrgAgoPgmY5hKaQ38cFpgj+XCNRUOg4gHnXyckzdkCGIO7gDSJfmA0jXXZbDs3MSf0jBWcN2SPUnLTeIxzoH17gh43ErmYFSzA1ZjeCZR1PEA+L9E4lj6N/Dw2Nw54DACHMPr75/MtcdUol6nDXghtBc9Fh+7QizJxpTUjfEbUJFq3edG+LXEW7k5IbMIypMisnmS8eIrUN7mReg8aTF5r7H/EmO04wLh2aV9y/dkM2Zw+y8xbgwFDEQ/+n7GuC0dJn325bFoNyKZkW8xLLgTa+NfApE4o4mxze2LK6WVcwCvTZQthfEgoNEt2tZADk+wspV6r2kCU2MB6PIpiAUQKoYMyBpKdfvFGxlvwO4NcvClyjXFEehKpqfgGmbXprk4PYsi+aRBnwjozXu0+IYZac03zZgT3AXKxwx37plMVNlSn1+FpqL9kaWxexJC7ceKgVvZfT7yN1SFi+RF7Jn7d4BqWUhUMOmX1V2BYRKHMXbkjLIe925rfirTNmV21oQ1b57lxGscozTa5mO/7bHASW/KeHabsfY3ua4SnkVxjYgWTcVmfENDnWnlEXZZAhcrxDUtdJk6IMHCI8eVxDu1ISnZMLyLscoVNO6hw9gmA5j4U5Ww8R05hDS8cpz0ZGwcGfYtLoeZlE8kCrZ+OgJtoh5nAOvc9ak7HfJU9yHVbL6IX2m31erjAtJx6ZUZ5CuwVZ+zviRqot6QbtPZ6cCrT5/vtVDdSs6b53rzaIpzrfdxEZ/K5jO7brd9LhFX84pzB6zDvzsXH93uZ5o2r5wuhgo+I21uNBiVQASaC3jcLSHa2TQ0NSgN8uk2XOijZH59Aj+B48LblMnLnQIcIYnKetnJsqGJ3PFm019X21qLIN0NE+Ln/v0CVzb5paaUDfzmvaF7sEZaN2L9Wi/H9oXHuQgB3nTcncsCyLEdS5ickdHE74F0dzjJ5/Cf/wl6UIOAS/xciVdyMumw7qKSE8P7TnyaeZqcN/4unxa34qTRdU3xD9+lnqJWFEYzbSz+WKeMRIXVxK8M9DNI0Fg8k9/QxCAJdt21yAcSSCseb5GXGgAbNljvC/Iz/a70qIvPjyFu1oDs05YpxVs5c4vwfckMJf4K+0cXYtwnDk43flSxtkPAoAChPsTyAhOA0j9UOam/+ZPpgrIDMpyElRULsnxuEFzJb5znGXGMeoj/NWmrvgEgMgID46kohJI1z02AjKSCZH7HFsnEXoLpi6kF4h/dI7Nv/Fn5D52ghcoA4MA0J86tFcRoNrUZiL4dUDsHOafr9PYNg/niC1h/pl81x81CDMPGhncEPymBjeFmUO71GdJr3v+3XN88u/9OI4e6Xi9BBXbVcTmTJ+lnoVAl4FROThjA4AAvwH8wBiO5Puz7/QJy5HoDR3Qn7UY54Sjz/o0Z4/+nZ/A6iPC0Wf5GRsXhGaZLRNjyopKgNYu87koAuPjGsT2Irk7ymKHVK3WSihnaWqnMu6yTJdSAA6F+Vu5KWUZNZDIdbl4wBG5DtapC0NWvg6kv6e0/G6tNPdF2o0A+CIFl+tLAtxmrACnKW1XXoeJVkxuEfbGmlCHeknzwipYgZzpMESmoVr1OpurYStlyCECQzbxG0Do5o03VM9NQ6w5Ko1XIUYh+DUeSR2L34SkrNP4LOtiGagYJWA3DInrwY2SsSAG3BiLeWvg10HZyHUOlIPTDRFx5KSEiBl+OYJmmVfTX4nCsxoXV1yLcwS/8XKfAJAGBmkzYHbOaC+NQpAQW0KzLPYd7PkD/EyVYiPKg4L87jQ+4jYh1QKV6eP2YoTfiHI1pTt7HhAbj/Yqt7DwvWRD2IkySMrCA24EmlWE73M2jMK2y3Od3Gllsa9s9W80KXEI2zvl35zL5LovC4BaHMKQmcaXMC0X12CqlAnbePRhddDf8gpcEdrad5HBxNvjsr/L/h52zvJay9/jZFsb83RuymNEAI5BcGAUL6VmIgShWtQpGBamDMCVYyvrJ1SJYBIfQZh8H+Q6BTNjeXQq5icjFt0QQUHGURH2BhmX/VbObznvNEZRtjHKi1z21PCSDbHvklKOEX7IhL3RE4gcKHAm6g02P0Dm9HfKuyEWBIU83vTMGNpYrw2ESpG6gfXc+dlwSsyrcdoUZxBiYBlnomVhVGjPl8mdVhYv7OdQBLbSdvaQ7h+zqTMGcrB8LO+kfsLF+rd9hUhuenlMG/aknwgT5W7o9p1Bs8tt7d+vm9V5ybjlXJzGJkVq9jsURIVcWxBlP9J2h/Id53QjFd+X13sTMewNAYQ8t5YhS9F+RxWMWXqHAHDI/UTGvGq/bkaDC7cn3ePSFQKncabt9GUWogkkSyg1BXKUsUYlW1kplPEaVV8R/b5cqNi0x2vIIcB5kIMcZC+505bFtWKdwoC8Ejs/Yb/yuegqrWiu/h1Iqx4rzLeqogS28+pOOSNsu40WgRkrUkGpT0BllrNXhCUpV6RxK8SorQA4aW9BTJKgMifgIzm3zyk2i590bY3gbBsBMAGZv6OAVwusua3mMc5biUfYcUm6e7GjtDCloCYBsUBQOgA8+GzqF/wX1hgIQKrY5NZlEjEDKzUOGDOsmbXVgGuadN7QOqXRZ8SGkik9HkvRnVgWeuoIkAZNQ5ebBKFxiDMvlZgpuOoTglMAUEV5gCdw63KLAkViurbBcOzQrC0WITELMDAca2ymiFkEbQUQWwAguAFwIydU5ax1AsQjyqEYTwgzL+Nft/A6j8OxR38irQDs3oSOikeYCgSnBGWbhuomQzfAbLyWsiCibwO4gBj+IzP/DBE9BPA/A/gGgG8D+GVmfnrdMfY/WeF2OJcrQa2mwDtwifQ1QpqSmKYMjFqpuL1o87Z6gd0uMJMjwXvMu1QlSv0AXswyMlNxFOGok2CmxSggCmQ8kfO2Q0A4khfVx4iwkOPZDeFOOnFx64XDcqbnW+rL1jWV35yOf5qzIa2VPnuHqFkSNyGKMeViCM/htEWzMndOzedGqiItGzKcerQXYuaGWb4vvtHYjwUGYw7shkWbvJgwz30vWlNSiRRGKytVWYRFA984uKs2dfgKM82GDJwCeACwOfPyclB2SeSFAJqVQ5gR2gs9DwPDSYMwI0QtLx9OW4S5S8ctu5Gzl9Lu5srpNchn87TD+gPtl2LbtUDXENYPZBB+QzkbMi+UBQHNiuEGwnAs38+feLhRsydNvrb1gwbjnOCGNin29QPC+iPAhazIx2NCe5nvSVJOjcxFe0kYTnI2JO6fDHkjbshfZOZvMvPP6N+/DuD3mfmnAPy+/v3mxdErI9m25EVIvNc9RznDJYBpCs4pYyYvQjPeFbFh7YNi3AJf4Y08eazzxtX8ZUWRxrkLdVlt83pxi/J8GSV5zcZFfMK2m453a999nsEdx936/TXlNtyQbwH4Bf33bwH4XwH8p6991LLnxxhyyi/GXD9RBjg3G60p2GyT1QK556c2yKWrtUbOM+qOmGsikshS0wFkspbNRorCFPdh52ier3Pa09KCY0Q7CHLTrfuEtqQhoH0+6aKuLM+0GQRlV/DoUj+CVv1W6pTaBm0RwacrrU4dRjjbZtLrNLGB6bG6J+tErmIYBfg6YOiGJjFau76sYAxwqyEhDK24DiHCX/Y5RakpWW80/UDqP8KT1Klbaa3Dao3umeI0WpfaJXKbTXC/FuKX6KloB8hwQTIEsXWVi9U9cwgLD6cEPLPNiNj6nalTVko+S50aOY67XOPkBxGzp2PaLs4IzWVAs1YXyrIihSUmrgpLlmLM37eXY3aDrCWidzjqI2Ln0D1Zp9Tp8acdaPSYP4vJFQut9jrVeGZZSOaGaa9ThuvzM/cyeV1lwQD+ARExgP+emX8DwMfM/EP9/RMAH7/mOURKN6RwOaT2g1LBVJK2ydyTqVip8EHNjbA0XteCQyaDSW5IGStwJOZ612ZQ1qaR5sVWFGbgrEUrZDkFlT63PrkeFEKq+EQU05w4Jxy4FdZp9l6o840cZ7WR74rYRAnKikeZKcsNo1bIEnjR1dtOQFkWwwnHbQZlqe8Mp25IKEBZK7kPoQBlSV/SUOBadO68Q5w3yZiI6lJV/vKLQFnOwbctxoWcK3Z1zMKUxXDqRUkQErEMBVk7/EZiFtZmkAIwHnmEuUOrL77EMEpQVr73GZQlY7brbp612NwjuKF2Q5ikyhMQUJa9vNYYOcUsegVlWczimZ7f5fQsO8J47DHOCX6T/YbNmcfmAcGNOX08zmUOmaSHa7D2hQ1AI6HtqAJlvU2mrJ9j5u8T0ZcA/EMi+mflj8zMqki2hIh+DcCvAcAcR685jIMc5CC3La+lLJj5+/r5GRH9DoC/AOBTIvoKM/+QiL4C4LNr9v0NAL8BAGf08OW2UOmGhJgzDAYEMpMXEAtiUNIb+5wcozLhqW4POBloxnFElnJyotRgmIdB+CiskMh6Oix7cWFKBGeM8NZ4x0qTIVaGXw0JqwAATovfaIrgdCTm/XrMaExbyceQA5hQl6MsOQfq3huFm5UQnBd9BddORUuFK9JqR3O5BjWxmYV3YghF4+N8HL8akrWQklNDyA1+rKDNe7k+c5sGaQ3IfS8QcwC8cQnklFwSAC5Il/DoXQp8upHh+qgBUZdQkRQi2ssRFDKCs1mP8K3PQL3SDfGEpvWJxNdbJmu1wfxJxOyZuicaDG6WIVkbCb4dMzw9zCg1WaYRaNYaDF3JM8NNdpnYO8yeBLSdQ3O+Sfd9/uQITB6z5xlJ216JG2I4i9QY2Qnfp19HdAUHpxvfghtCRMcAHDNf6L//EoD/EsDvAvhVAH9DP//uK56gdgFKN6RrwRvz01thwW7b/MI6ApqZvAyzWWEW54mxVni02og/erIAxphazvnLpTA9l/u1Qn7DR/OcDWEGnx1nPgqrYbm/gNuMQv9u5uTMIywaMBHa55uUFfCrAf2DucCXL4RbIZzO4Ja9+MmrIWctxiCuhptnDoXrsiFKiU/9iHgitSHusq4NScdVZvT1R4tE+GpNaljdkES6cuTRrKKkI4sHz28i2pJt22IXzBjuzxMxjc0BO6C91DjEi7IhqxHNMGLzoVxbmFHthqj0Jw7tsgE7gTcDgAsytmYTMc4cjnTposjYPGgxLBy8EeDO/R7ZECX31es+3gx4/g2feC1jA8QOaC8dNvcLNwQQd1PdjdBJdsQNgOsZo7kGoZVsiCPQmF2b4dhhnBOOOyXAAXDxYx5XXwWOPvE5dbqQcxvc27Ih4oZ4tJdcZUPCH74dN+RjAL+jq24D4G8z898joj8E8NtE9FcBfAfAL7/GOV4uUxg0oNiGPffTIJMFNJPxYbDnshz9pqjJqMe3UxarcIL/6nbEABiZ1UuhyOz1vBWkG28NTpe6WhkkXcdvNRe5hZj9x4nspYR1Jyi4bit4xhuG6CfnogDAo4YsMwNMoiSAjGzUuU3zG1i/A6Yk8DcWRlosiFWRTedmcg277n0ab5T5mZIP7zxvpHo7zoqgPM/rYTftWLcJG95T7rkP+GfbX6y6qPuzM/A4wp2dAgDGzx7JDzHAf/Cwdjk2GzHPteM6hhHh0eNUfZoYpYpJbb70YR6Az6ZnZsHWxsjLIg3hHOIPP62BXsMg7QiML0KDrP4rXy72m7wU0zSdQrtLmjtoExxj0a4KyZwDPn+yzUjlqG4y1A+YNhPauQ+Q+rT4r365+rmCGpe9Xr2rGyNbrUnXbjVGrorLbPwA8Ohp0WSouJ9c1No4D8QgFcRf+3K9rSNhw7agrbpW3LjUgJhilOpchc5bMx8aBP8iDYjl3rlHT+tnoWpfSPV35oYuV4g/+bWUoWAi8EzcFQN7pdqTwCmgaByfEsgOGM/U8lPXzqgAAQCNg//kqVzDepNbZX71Q4STmbgr5eI3RmHrijETPwFwlyvB7BTAwz/4zm/hfP3JXlr7APc+yEEOspfcXbj3pMCnJPClrkuNbIxBK6UAbffZTBrydF1mEipSq3wqBLk0jLKyz7uKzwL9oCnKNvNUtg3o+EjIcw0XsFyCjo6EwxIQjk4A8eFpTiNazKJxGe69ylyIrh8RTmdA5NS+bjyby+o0awVnYKv1qkc8nsPxg+0S9YIQGBCchTFQJ6LgCc7CLAMXBWQ7fOV+Zny2EvUJziLOvJRSj7PMFA2kOEMSq0h1DuGozZWZncC9m5KTIzXDUZyFrZ4zQbK68wv0XzmT/bVx0rRJTpg7uE2sxiuVpUcSB7AGRpBVfjhplJtSzz37UFZ6tQAqi8g5Setu7FnQ1Omn53j2r55g/sSCkYTYEZplTHBvV7g8ljoNbY67+IGxvi/HO/p0TK6fn1uKGfBHHyG0Dt3TjLO4+DNnWD90mJU4i47QrDN/RsJZOKBZHcOvc5yJIhA+218F3F1lMZGKjDfmbIjEFeIkGyLksEa6O+1wDhRZAWbpHbqStn7JLSMCnETNy3ZxRqKbsjH9AGCZafH0XE5JZihyZtMeCbTJvBdUuBZu2VdmqluPmaB1Up5NQ8itBuwagIoQGIAAxcgBMSTm80z/ptkQrWmxYzXn6zoQ7FyOuZhyW+Wx5ewCJ/M9KLkNldmQ5ZCO6zSWUbUdsIyRKTEz3dfKTr5eoznX9g2FgrCXGwD80sGNUXAGrc05i5uhzOHhyFykiPZCaPFNifknl3V387F2Q1xTdFxvshty9OmQArUCyvLwVwOaK8PycDqnBXLjzMtYveBKDLjVrAMMTGUB4dh5tJ9dovEe7mqVXNLFZ8fwfSvcGUU0wQ0xKcY0V6SZrn7M9UPMXxDC3sjVQ1tZFpSZoqsiscTVILEKijF/2s4mZkFoepO7FhXachgzHX3Bt0lNI4xZ5r9HTq0GASSuTMyk7yZTtizQaAcsItBmyH71IDUg7AGnaTGzKFhTeCmz0A/ArKnbARagLJ4V7QvtOvsB0NYHuZy/BmWxspTFo26b/MbXVp69YFx2CfPKyUCUkY9GrBIYvGhycZh3Em84OQI2NflNJuXJ1hIGIRIyJcRei8dYFXEj5wlzDz9EzbSo8iEGn3SiAByl+hZAXtjYFN3CjhfgmU/tBKlgyoI2USZ9gVPWbN2jv9ekgCI3uXhrPLLUKdJ8Wuo0tpT4LNzo0J+qIt7EFCBN18CMcG+B2Ho0DskaG84abO7lbJTcG83iKAjMlEVsCKFzaNYB49yAdMhxlT3k7iqLiVSWRUGYYnDviikLEELZEEEu7LQsqp4bTNsmva28JflpZMSkpFR5jSOwXifllSyL1SZnMcxliTGtVjQGQWbqGNwqr7wAskUxBCWZKcYxBGC13rYslEErzc1mIy0MY9hqNTDFWSR8yNWmJqQpOsybwvLqXtEYMzlsEDIfbn3mjCjYrrAZkgXACq+ky+WWZYGJZYFhFMti6OGv1IUq07OeUjbD9SFZgplngzNeQYOPgFpCGOG0L6lc+wq8ud6y4NKyMIus7zF/MqAxy8ITYuPg1yNcnzutyzlzoWKJiKUxgkmUvF+HpChKnIU/X8FNLIvumWBzjOrPrtH6lFTtCR2kT2o/wheWBU1dxxfInVAWDNSrPpDcAXu4txolT7M4RGmV4vEGloUpDe81kq4P07rPbNHFA72vZZE6ehcxCziXqkexRs4kDGPqfp04MrWfKDt9eWyV2QSxgm7Lsli02xya5csHIHZSGwIXCwAWi+UQY97fLAtmtaKyXw+6uWUR5zpWLXcvXTxALAu3CWIFUF6VY5fjEKk2hKWuJDYOrFW2r2pZbO7neJlhUrhxhWWhafLIqclQCRqjkTFqfKNdElg7rKdrc7TTsujPWmwe+CpNIfiQHTELD3htmvyqlsUhG3KQgxxkL7kTlsVOmfBJVi5EWTBm/Sv6QdCagKx4vXYkK0BVlSuzyvgJIpJjFjBu2YgrqDRCBK9WcuwCZ8HWAxU5UOjOL/N+hdlMy+IaLTPhSEzeGLNls+plPGo9lKscrXvws+fbmIlVjbPgEmexrqtiq32AlDHyjy/q38uyeh2b02uyLl82V2a+m3VD2kUOY4C7zJ3AyAq0nj2/Ec7CP73aGhOaTKrTaIVrig0BYums9H45yjiWMaJZS0tDyy7Qk/NXwlkc/3+XGU3rnFggmyEVqAnwSlxai1NJYDYITiQEtM+Vb8TaLzYuwbrZe/hH51s4i8X3O3Tns5ShSeeyYH9p1Vpl9Rik25pKte9L5O4qC2uOo1K5IV2bbhqVJDeFUNdtAaZKJUNHAvfGMEovz7YRs9Zg3OuNPBBtk334xoMWi8oN4eVKeo8u9WVYySffO9mqDSkfYurHHOAMCuGOOYsSj+cSm5gpeMf6oq57Idvhs9yq7zo35Gq15YYkpTFxQyyrET48q90Q44oogpxChBNBQ4bHw+pFjHAHkH0AkJOq08R72Rn7ld/bDaHzS4QPTuRUjasDnFwEODcx9RsFNHU6zJPLkrI3Y0Q4aqXs+6nGWNyDm7shnzlcfuOkKFGXqthmFbYCnGWthrUzoCgZm+FExrB4NEhg0hGcza0n8OyhuCHnq+SGrL5+ivVDj+4ipgBrbKQGZBrgZA/41dGWGxI/ed9Sp2x8FLkAyTpHxaX04bA+ItRJ747UWWo+Aw8jyHsEQ3kCcA/vAxuX+4oAoMVCtM3UShkhLw3nhzQ+egKazwRZvLYeJTPQybHEI8wC0K5UBMBK3QEkhquamTs3LqZVn8vM1yPg5rJkf67Xyw9AF1fAYg6s1vIJgJ89B/EZwsOTvAoVtSGhKFFv2kbG0Y+pdN1Z/019KS2G4pSxu583ubmwxRwal0vHIVmEZog1z4UWLtHVOmV0SqHmNGMqVPqPjuGX1lDYwVi5aOT0UseZl74h3m/R6rkgqUeT4bRBwnmrMAFx3qJdjggzj/l3s8UXOw9ylKyCzZdPhIUrSNaibIwcW4fYZIr/MHMAAXPnsDlz8MrrERsh0AUBm3uqULRviOynCtdrbcxK+580ljIPFY+GydW/dIzQEWbHTRrX5p7H+oGDK6Z7OKJURg9YKbxmQz72aC+bVIeCCIQ/eju1Ibcrk4AnIEFPAupeIFV/kGIfcz2mVPOAmMaTdoHWYyPR7O2qCdHWfDSMGY9hrQvN9LPIt5HTlOcv+nqUeAjaDNmMNYtJe5GUn+n3fsh9SWx8RHVfEp0bAuS61rmKlVOrw+258VdDftmLAGfq5wHtG6Jd1GnIJi0NQUznHV3UK7IelaZo4ssFgKusL/GBtbo1puY6rnFiyUSGm0DprbdIOq9aH24zSk+QQpH5q0ECnmrd+JVWoY4xAc/kGIDrBbtgitQNyp0xRiyeBrQXmfyGG9LqUb2kMl2bmv4QQIDbCDlPVAvAL/udGYr2MsA3hGY1pvTv7FkACJidZ+VifUPS+SzA2QDDkUN3EeGHjBty23rpWjkEOA9ykIPsJXfXsniZlM1xdjURKsSsgGoN2tV0p2weFAt3JTXdKYp1UhcwCcZtNToybESZ4i2DtqVfPsFzpN/t++nvZUUsUDelKQiCy/2rhkYREAstB10AACAASURBVIe2Br4BqLgkqt+s+Q+QUqSCZC3Wm5DnYktKrEjZiMmwBmSl/FGCdGbhxbx9teJaFWyR0nVFaXu5ne1rDYSqazWUrm5D3mIJuepTPl0+JwDy+smcmvcAkHgJSzcxsygSfB4AK9WCi3JIr1wbRm6MsONZSMdwWi2bj+sGVx3f+/p89jBwBFwn8ZFk6TC27v+L5L1SFi9sOrRzB1fv5wg3akC0exD1pzb9oUTDd8MxvoGxpEZGZRMjG5tTYoMyq5GCfyiug/BODE2ziBVeb82MUlOEKYHxrY6lKBcoapPYYTcBr7sZTuF1REiJ9d+v+IxFjaW8qrxXyiJJWSJe9geZ9gUpwEwA6sCmZU8sNdpKgVcCa9kx7d92TCIpX7cAZ6/7JJBWzkxYmz+Tsq8HtU3VyyN9b+O1XiRdK2O0bVcSRE19Sey6tFzbCtUA5Kh+dDmV2Pj08rGbZH8gwcDUYqAIcKZ+HgDiUZs4OdJxAa0XGXLfkELY5sPmxs5lvxtsXPuTOA3vx9aJDllThns3eZUvwWLjcbOt76Ku9kTgzsG1+ZGP81bIhWw8BQentRuQE0pWoYS9h5kA1dxqRH/qU22HkQU3jjCcWKFgARybWXZCApxNS6AxxzK6Zw0wbL/RYeGkb8iYrZvhtEF/moOrADAuHJqCECj3OiWMC+HrNKKess3jPnJ3lQW9QGOXvUDK1GnZsk57i1hfkeq4HLf7hixmEqi0h8n7QqEU5/IOPO8ypLkXFisy5aEBynA82zJ7Syardow5Q8Gcv9dzWi8SnnXaN6RLY+BZl/uSAMn1KPuSANKbxNCORhTcKLs4lCvDmvhA4RXDWYdmaXBtfQGsi7qat8NZi5Y0FTjLD6rbBCku23HLos0HkK57OG1hzzWnmgnpT8J6rrDw8CsHt+wxnOlL3TntD1ori819j/aqPrs1B26unDBdPc3zM5x1iDMHt5S5H04ajHMHF4TotqzNiC0htIRWBxzmDkxAe+Gw/MhJBBGSooyNZCTWDxQev8mWSZjrfDSqLJYEPwhzFgDMnnYTN0Jkfd8LQxh7eA1grh46rD4mJHZiAMMJob0s0bb62RLCTFChxpSFSNLNfU+5u8riTchtuARTN+QuiOnVyZjMdC3dN77m37Lv/v7rbUgaL7BtIbyt+d5xmtSXpJq7tzyuNyDX9jLZUw7ZkIMc5CB7yd21LHbgLJKUjYN2NRMCUiMiLrMaLWUcg9LlWXMguhLehNQ8KARgqLEPGHpgnAn3hfmhozJU94NAfS1Sfb7cwlmUTYDoaiV9PQDQapOJbg3efbVKDY1SYyNAyImvVmiswAqAVbaWTYwAwK17sLJXW39Mt1zn7uwx5iyJSvd4vYWz8Eb8q2P3m5BwFmXMgoYAulztxFm48ybhLOy6O0KurDRQlhlues/cahT3ZwyYPV7nbTVbUbqYft29EGcRW58JiwF03ku/VSVJ7p61aJYSqxi16AqAlNg3AsJy+l175YSLog84++6I7tk2zqJZKuDtBjiL9ulqJ85i8UiIepplriA++QGhXflEvANozOIanMXm1GP2PGB8bjGLzKiwj9xdZTGV0twrGwrZv6cBTkeAd3XMgki2cZSDlraPc4CbpAKncRNyAtn2RfDTuxzgJJIOYIAEQMc69cJNUb5d8X264vsyy6Lb9MW2jhJsPAc4pZaBG5eaDgMAh4Jvwj4bn/goESjDzzWrw60DGzX2NMBpMYfOCxhrGuAEJHazK5VdzkeTx5SwbY3WbkyUBTuCcwQemtQF7LoAZ+wcXKjvGWuAE1GaHpdVqtxq4FfvZeycBjgjwiI37qGQEZY2rqBcGH4jzN6NVZNqgJMCJ0YqLrp+bQU4EcEjZcr+yXyW1xZbqhRPmAvjtx3Tjk+xmJMywHkENBuX+q0S38w1eX+URZXzDwVeQf8dQm2NKHlOZVmUv5myMR4MQ2GWyEyzKMpzjaFmqg6y6lkhWtq/H2qkKdQdtofViqwAOWZv4ymQqVHQmunTfu+FlyC9fMwARVDUl8iyIUNBmKuXQGPIOAhmyebYMWKEWw8Vm5dcowNGn4K3Tsl7pF9LcX3DKOX2Y726V/MhB5CPzZjG6EaX6k+YMvZBlBrn3iq4XlmAMsIyCSv57XoEj75mJ1sPwnliFs86aAtLOa5f5ZYIriEgFoVXgeFaISbqLkLuaaJ1KW4T0BrrWRGwdIqeZE1z+7XgLMyyoPWY5rmUZhlEOa1CuuY2MmLToL3M27uRqxYGRrbDDoiNR3sVQCFbFi9lEC/HsPeWb1telA0pWxKWbQqnLQ5jqC2L9JLEzO9gvBmLWc18bEVkQH0u7yQNWGQ/uG2koI0oV58ez3OxlknX5m7mIeaWgkDu62EFaouZUOHNZzLGshBsPhNGK4NwK01d2R4RkJ6i3HpJH1ra0WDp6oZYFaZxc45n85fWhownLZpLeWErDs6+gQthJx4mHhe8pXrd42l2G6K5Iboqp9qQTmDXbjNgvKd9Q66pDenvNWivJiuzNvZpl5IWnV9mjtLxbC7H1+sdjxuEuc9WAeXnxlKnlikKc3mu3Drg6ktNesasNqRZ+RvVhlibweZqtrM2ZHO/kdoQT4kKb/VRi9WHdbZPakNKtwdpXMOxuD7WsZ1idlP2kUOA8yAHOchecrcsC3UjyPutACeHAPJeKkyboiVh2aawbHG46bfMYSHb1XMoCCkxca0kQJraEtoxgfpc642sesZGvd7AFTwHrEVJdLUWU710n4r2grTaFGPpc+DNArDaEpGI0mf6fb2Bu8is4+kcjc84Cmgws5HqV2tPSJshoRMpFC7aegNmRvN8ve2GeJfbCgJoxijdzyOnLuyAuCG07jN1XyFpPoB03Y1zqU2jMxdE+12kQrJGTH1artGcN+m7XW6IG7oXuiG+9ZndHEDzXGM/GuzuzjvEldDqxaJjOoDEG5rcpo0HPKF5vsbxZ13q8F66IW5odVz5uQzdi90Qf7HZ6YbMH3eC37gcqgCoGxvMn+RxdnN3rRsyLhzaq4jOcBgsTZn3lbulLF4gN4Z6uwKCnWDfLEgC9xoG1QRnQaQNgjRA+Dbh3iVs2xRAhaPwTtymglODi+Cu/Q4g0Q++baQFl/OpkG+GA2mQJQHIXuee7T0WDfhpqTyPGemY7msRLI9FYPrWxd5votRx/qbCnvQa9bm54d1+b5TFlpQPz8seJC7Kzqf7lESxzPnlUWalalt70cqeJtcpMecykUv5XUnyUo5heg2WsXBu+3c7doqHcD7OJOC3Nc7ysyTmsYI470F+UkjmNPjIOoZGx051IReijHWXYmfn6rm145hF5lyuDXFFmN5TKrKyF9NSp6A6dSroz3oeLXXKjfBt+orsVzJbliER5SmvEBeKnzlbAjYuVgSmnJeKFTxzcuR4QHHOpk6dIroqdVrNcyHR6zkcJQM6tq46N6CkOoVhUqZOo4cSCtvc1P1gXibvr7LYt+r0ugrIV606jVFfirKKk1P6strnNqtOQ8FHoZWk7JRxu1QAgar9jfouVZxOzvtWq07HmOocJNomSoPKcQVKlZa3XXXqxoioNISunN90TymNgbzUrCC8parTkQHInKfx3rTqtJVgqhstdbpHP9VC3i9lkayAPQrJnAdcqOj2BMRjq9orFpI1jeIccldznrWZb9JWz9suJJsVt87o79om13oAiZqf+oJ7MnK2WspsiLKbv9VCskUu/Eq9RKyQbCwKyTyB++bWC8nCUZMLyeYOTcqiIWVDrCgszBy4ITTz5q0Uko3HXnAWgSVFjpsXkg3H0m9lWKh7VcRK9pFDNuQgBznIXnKnLAun7NwcYorem0h/0xH+gwcIT58VtHlBGwqFep+oVkXklNWgh/c1AxARn0hvz3Sc9Tq7EgC47/PxinP5owWwGkDrnIOn5Vp6nRKBtOs7//DzrWuwjmZy/CGT/oYAuhTmautm7uJTacG4Xsv1aV8P7nsxcafmoyPJ8FygiqOQ0tSlLIAREZtbYmM4PQKGEf47n27TCRKBjHUbUhmb6AhLa44juB+2rxsALVf5ez1nuzrLu5q1w5x6uMg8qGXWNmj/xSdpPGl8xbV2TbNtwpdM3d5nYmUA/vmlBKg1g9UyC/N1iIhHs5SpgeJYMIa6fWHbIJzMcP+PPsvtMC2eFSLmZsWUY7LnyzJSE1JnXq62QYQAjszSWrQJ23L2f36K03lXZXgs+1XNq87Z8PEZmotNFZRtVvsTvNwpZZGRhds+GytSc1dabqdEhuSG8nFJ06w7fep9xVoPFGNOKUiHjLS8bdnya0sjsbi+aZm8sWYVKE4Awtc5hrebDSnRrdYFLDKY8vjMP2fa/6F+rfFo3KWOm8QcAC/njXO3s1sXU+5DyG7iDcUY0bH9eu0ld0dZEKWiLgBwx8fVw2QrWXz8BM3Xv5ZWWlospJP5fJ6+QwigWSc0/bMuvcDh0eN8up/+Cfk06v37x0q5r7n8730OPl7Iw2o9RhZzuWnHC0Sjs396gfjgFM4i6ufPAQD9N38SzdVQvahx3mI4Ff+4e7JGOFaOiYse64+kNcHxP/sMgHQzb87XiEcd3NUGUf11//gC4cMzYeFWAlvLy8d5i+Eso0K7x2splFoPGM8EIdo8X0u0X3ET1uXLf+dTMICLf+vHE4O1GwV5GFuH2FHyy/tTj+4iCNJxYUEHwG8Y3bNNTaEPiZ2sPzpCo232Rm1OHOYe3YXeG+Oz6BxcH+GNO+O4QXs1ov3hc5z/3Ddk/xnBBVQ1GwCwuU/oLpSez5I+6pe3y4gwI5x8LzOMr77UYZwRTr8nz11/T/ksNJPRlHiFhjDOCd2loli17uPsTy/x7b/yZRz/UGMWjcQJ2kvG+gPFTqyRxjMukLaDA5ol4HpgkC4HePD/BEF8ulyAxkRYfuQxLginPxjRPpf5/cHPfxXLr0YcfT8vFOMx0BYta8Isn48C0F4epXMRA/0Pdtei7JK7oyxeJqVpVrkbcSuQCHLiyuhKscuSSHUTQUxM6QjOKPNOND0uswQbhzEH8UZltB5rNnG3CYmV2kxM1wc02tSHhpjZo8eYKxxV3KAr3CDZiTITQGOUXpoGcrJzUoYjyxgGcPSgzZjASga4Ii/ZiRzMVMDVMlTVliAJqsWQe3O2Cjl2Y+EGMEtkfyjnL2dV/CbmbuX6SVGqSuWatJhrlMyCHach0srTMVVTUlCezCBwZrsXsfFoVgx2eVykFqZfa48O49CMjGYZAaZE6tMsI2hECpz6osN49AQ3kuwDgKw3Uj+iew60VznAGTpGu+QEtXaqn4QlXI/XqSLZMNyAVPzVrCMoSIbWWW9YB3SXEW50aJYx3cv2okP3zMm5zWMMJH8TJFC8yalTGmWcFPLc3MRgOwQ4D3KQg+wl749lMZWptbD1d6w/pzLFEkTUPul1ov02Ugp2l2UDtVjMP3Ql9kJXtjLHvSvfPY0plONirlieM1Zkcpxyu7DjeDu+dyMXYwQYeUUu2a4pTq7B2LBjXulT4C7qCl+ME0RwiLkUPXUa53wsFOflvAraikiBQT5DXtxo4xLMiWwLgG3MVF0/RYYLlEvRRwZ55ZfQv00cAB4pfZfYvQPDjdkgdWDZLjBI8QypNwcDzpDZZPgPpGuxbUg5VZM1TbKfNVFOXB+j7l8g3GU7FF3UOd0KO0bisNC52VfeX2UxDfKUaMV97KWK42KCelSRgFvMeIubBpYMjTiFNAOZqg0CRGLt6FVGr3kXhHw63jcsBncGRFGgGmcxdgdwLHgq9Xu4DDxKD7Gvj4sb5Pa3xmZCUMQnMuDRPCKHApmoSob0P2vnh7zv69LNlfuzjaeImySOjlKPEymMPI/broGdokN9Pe87z2vzwMX++j1X2xJupBl2yPujLMoJqwhqJi8TIBrZwFXXlbq78qUkAR6NAO9SQqXVYMzeRU0FCjIcgzpzI3ETgssvW+MS3Be+Hje7GnrLXjqMsVf4dAlTtvqAKURcIc1pqM4ppNrleoJdkGu7TigIKuRVmbVsPLaZ7Tq2BDcI7NheVCYCeR1nmX3Rl4IbB7Zep1bO7QlkhDb2YjTytEf49HdsvbJ1UTq/WDsKZzaDpSVZVQsFQEQgBxCTlI+nmh6FaXtKL2VsSWIJoxy3JJHhRn6LCpiymAM3DrFDVQoeWwkohi4rLPtIJeodADayH87fNwTHnMBpcq/kWKETkhxbUGInAczQUrLmQge4IVsWNgZWqDeNyOQ3pkT3lPdHWZRSFIdla2Ly4lghmcu1CpWmtdXNCrA8gZjyy7Or3sRW9ZLZikgo5yZKhlsHDA6MHOBkV9cQ2L+d4f7L7E9p+ZTjBQB7eW2soVBGRZ0AJ+SlT+dKXeI9CVNWug57AAnRyFGCKQfp82mmtjywUuplCEFAgnRpHoFMOs2kiMWsJORcDryxeg/5LnRO1ARx+ptGsbhSU2FVFs6hyoaEmZr5lOcvu06E0NartL3YaVytQ+hknJI9yHMZW5IsjCE4C2UxziVDI3/LtqHLTN45CJy/MzbvhgA4QtSsBXtVwjIJur8omTCDMmYZipQQFow4o6QdwxxwIxXKwsYv7pAbgaAZGQqFVbaH3F1lYSvUdTEEV7/sALIC8QCidgmLu2sVck2C7J/+ThuQWCchJmg4ewfqJcOSlIPVLEzOQSPnmEV6aWo/mFK0m5BrHXIqK/fSKBWA0Pe5ociQpFqLTNcvY9BMTwgpE5HKn1nn1wqv2OoNuMoYmHtURs0lC1Kb1RTy30Z/Z5BtpjqWYnRuri+uQR92D4CGXDPie6nHoBBrX52LeIQe2g3yQsQyG6i+OkW1lIweb8jXlEr6hwjvtTdHpKrGglgWqJTR8eZqRfghc1lGjRO4keH/f/beLtaWJEsP+lZEZObe+/zcn6qu6qJ/poeZYcbGICMseEFoJBBokNGIF4t5wSCL4cEWL0bC8GJeLBkJsJAsWRqEZeYBG79hkCUkIxvPizUaLOOhYRj3/LS7qrt+bt17zz3n7J0/EbF4WGtFRO5zbt1zq7qb280J6WifnTt3ZGTkzsiIb33r+yart8FPWruKbJgDw811uy2jLCtU5PskJOzmGlVys/ytMItZjleWOaByLLdIGLckkqWK99yl3EdD7st9uS93Km/uzOKorJYSwVcF6ZWwbVWlpqEDlhnUd1Wlu1kqGMnJ6MRp20nWoVJpy2TAZhP2/S6ANzUhzB8m5F0Pb5RbnRnEkyCdm7nMJvPgsZzpU3cJkvgE0VKMO79KwMqDhztE5N7DL6mSwKDLgsHXi2dU4F1XjHgAUeHOvYcjQjxVApg9yYMDYkZWGT4zN5rPfNGOFDYlaRp0FYudzpwocwdGbEhZHACv4jHSd3biQNzV9sat9EErNJv7ugxyMxfpuHjqETwhDB3mU9knDroMiRUrAISUlTusQE9KAjSGPSFugeG5/o7IYT51iFtJCgOA5cxj2RL8IjJ33aFZhgRg2RIGnZksW3nd7HqMbzH8aEsZmfqzI4xv6XUoOqd1CZAGnTkdBP+JO3m//YTgFwE4ywyJCOMjQjwhdIfqODe9BczvRPipdsJywsi9LUMIaWNLSZmBpA1hPtcZWqJV/72qvLGDBdFammO1lIiNzmPOMoVeWRV6zVHIgL0e1WH6lSb/78YIyrmOJwYqcqygICCErLFRK1qiyOIfqWqF6yhU4CbfBAC6S/nxuiUhaJoCpYxw0Gm2HstNCfBUyFlFl1El/8OS5bjWBwCIGQ2EALefQYsHTYtoZgKicKX1IOeqQaoM2f4ylRuVFMB0i1n3yVd7El1JN+e6rE51WWGDBEW5JsSAP+SyRPJjAhzBj1yFbvVmM+czW4a4xCKkOy2FPelnBVtZMZPmp9HtWcBF7QgXta26tChLlsjor/NqadFfMPxUGZyt4hQHQhgdwrVcB69Yi9/PGJ6eoL+wJYPckP2LGgVzi7SVsnwGCMhoIK1bgKDnH6Zcjl8yWQOweQbEA9BfRHRX0mfD0w5xG9C9qEsxPwp71JaPFVuRJUp3VQc2O/Zdyxs7WHCrtA2sGZzMZQAofAZNKLPP4T6bxmrsQlKGJ/VBeAq2Ts0y0JCpdwMgr226JUfA3pcBSR3NKef6lKMGcFPHbgDC91+y/OjNNyQOoDkKLTtmiAACRLpuySqS0hxL23KDZ8EMUzpf7UtH261fUnXZJmYJj2aBXsqNFljXzgz2Fel3CwtOYWvoWAcxl6rWBEcHqGt60YzQ68WKQVStDl+usa3NnWPFIqydsj1Fnf0wNbiL9LmLDD/LbEv6V7AZP3FhlCbnBcfIawwGkOcRZW7sAWofu6W2BSDABidrr92QXHEqt8jAJVoYdRYm7+W7RQ8jMpadq4Ndw4nxE8HPXAMuTiNCxMqz0MuOilG0fJXXKW/sYHED4DwKndqNVox+24zDlF4dDTEdhiihT+484BhZ9SC8c7LkYF55gdDiim8HAFEP73zZx46VB11WJFd+CDk4mfISwc2iNi0fqJo0oyiK515uEu48WHUprA08eHlyLGu9De78ynuUO21nqircRTNTw5zlPBQcTltXnogGcLJbRz3i1slU39dlCCmW5sfm+xYOzSznapdn4wsXwC0KHjfREBCKrkcaHCgFcJDcCNlHn8pZp9F6YZcdAHbIoUZiKMl0mx0jbgjdxpaBGWlwWHZUrkPqnZoHm5rUUTRkQ2UAsLZw57GcAvHSrrHOHjKKp2jWFSplIO60D3roYEFwS80ZiRsHF4RubjML9tLncSP94VS/YjkhzA+yUPxtwNwAgFwzyjU3hH0FhqPlhiR6rWjIPcB5X+7LfblTeXNnFq8oJe28XQ400/HXqKh8jyzd3LZ/FuX6FYXa6f9xeIp1DdueA0P+WrvDpNP8Y2q30YF/EKWZ5iJzZWainXrr/03YsrRfv2ftX7W5pVoz1tyRO5SyBOD6t2qD7ZeP/m/2dw2VvXz+mtPxW9vV9kNu2qefF5YnH31HsYzaHtb2c/1t55f303H4eFV/8/pFVBmsvNmDxcswi1Yfs8UsjhzJPpNn0WSdcsnu5DJ1Nm2DgonovsJNSCvrwJJdimYQmwXQI8uPgEzjvJKg3JLKDU9Lgp/y6kZ1qnNJiQRfsfV/qpyDkuFpA4ynksm6Osclws2h/C/tdqrTYOer4OHEJdvSoiHkaQUOClgmmAWam8A3HAAA0mYng4Zv9DGtfiYqcvvFMpGxyjr1XvahmODHio8YFmEZlADQ7SWtnB2tliGUWdb1qGAmZcmEZecKZiHXQ7Jr3VHWKSUhm9VtFW8K10A4SNtykCzdcOBCiDLMwrgeAJBazCKijCYGxrKreShiWiRos59y0dDorhndlUPYNw+eLFmnZRmy1OWRWyQlvrWIfB2exRsxWBARKHTgpWoNiKNYhjuTBVarRXEjbTwzOCbQ6YlsWyL48krCq0Q1zNqmts91G2UCxkVvzuoIhi6Acy7rfPYOGMdVvgiPo0RuxrXvh7+edBDhsv7mpYYV3WFZ2Qt2qmhVtDYBmLK3uIrl0gaKee3DUQaopdogAqCrg3iPLhHOfEPGJozMXKz7WF/751MdhDLknnBuNQvwBwFdXcyCUVhzl7zKk6BmIHJTKhEkNybBN64mMZUGqg+L+ZNYP+07aeNhRP9c2s7BRH0V69AxpLv2JUJTIjKaiEaRRXW7PGTE5s/NDNIBYLiYBCtSrKYVtjE2rLmXGQbkXuxx+sFDDI0xcu4J4ZBL6LWks2cuYdocDMiVwXN8pCH7MdcU+SmXOvvnEgbvno0lonXy0QA/eQwvcumD3On3CDDtUEDCsOHACIdUQtd1EL1beSMGi1sL3ZL70H5ccj8ExISjYj1IzCKzpzOOW2cW9qNxKgVvA1Ajzpv7ALdEsIF7apUoDu0VTOVlqQORRVli87Qy8JMZWBrpe4ugGNiauPApAOV+LGnlYM5DLz/aaalWic1yZjVhXWQA5BgryGumSkQyo7I2FBOiZmbCLElhOUtuhYGhScOjEWXW1M78zELRTTIoiKp2nWFJUhdJCHpu+DIA4FOdwcnJgdQ/tUQ4zNqBpDI7B2M35t4VSrkD4A9RWbIVzDQ9jrShOrAcZrgYNILlVr6opBR/0wNxUa/TEhGmXGdLer3dnOFbynmWbFY7h7RxcDOraTPgdQw3ub2W15I7J4PEnODGuTwk/Cg3e8s+DgeJptjMwrJOnSP0l4uYHxXmL3CDufwZ5R7gvC/35b7cqby5MwvOONaIqJ9VHILMq6PxU1gZ+7y0fpu3Zc2KtFBqnSGQ6n4WzYXXkRVSzEPq0mN5V8AqSk0WD+dq21c0H5w8QZNqZtpTdYmfO8X7rqVVuLIptITebCmk/hkxl6UGJS7vDTex/WlJmv2q50D4XABtYYYaXgAAyBXM0xyU1juEkoLJicuMBNCZH0mS2g2vkddtV2xmqkDhcNANoLcCji4qZ8OUwbJhWXo+TLVdL3n4y7kqH8P2MS5POdYRsvoFyv3MAqjT49f97K716jLplfXe5Vg/RHvEVnvjTu2wX5NyKOS7TV1O9/mi59B+/Tjbl47aS/X1ZboVrbbIF26PtclZW9o+eMl3VxwiWmt/vOx7Wo7PaWUHiaPjf8HyypkFEf1lAH8UwMfM/Id022MA/wOAbwD4fQB/jJmfkSyM/2sA/waAPYB/l5n//quOwQBuKFppqO02NW9uw6QWBeFcKddHhsi3ltZlDJpFytWEiJYImKy64RB4jfG5Vc+yGQaJRoVJxRcauWEHuUYBYJiGzSxsxhHTD9T3c3WsDMAr1sIEprpdQoNcFK5K1ixXXU9aNGpk2a+59sPnapt1/ioyVkOyRbkrVVtDYV3qk5eq3ialLPitoy8+s1CFMHmD0oYVi1TbVmYZQQHmLHhOYWvOMtPNjKrKdRwbbs7dZhElZGqzbPvcBu3vw0PmLsuQvwLgLwL41WbbnwHwvzLznyeiP6Pv4tI6LwAAIABJREFU/2MAvwDgZ/TvXwTwl/T185XV6FpvEAqhoPcIQUx9u64ChsygzQCMKK8A6g8bAJ8IZc6iA/l0Iyi0gXizRFKKWhY0ErHZANtNBVMvCXx2Aro0AFEGqvRoJ8h5I9jLnS+uWv5qrmzRw4Ll4UZyOz4Waea06+D3C3gbgGkBa/TFXR2QNwEUzkCHdW4I9x3yyVDO0V2EkmCXT0RIwdTMWRmyrNEXUj+N8Uu7gsJL6FQjAb5GEuLOwx8yXMorFqo3EWLr56BsTiKk874sT9ImyE3VKJSbjkjuNLxZfDIC3CHCp4zprY3uQ2VpwY2exXzq0B00dFrCg/Lqp4zcEfoXtq5ymB8EpL4OFml3VhzJOFChhgNA9sK+7VSh3M57kzMufqLD7okKDntpX7f3mM5taaFtYS66F5bA5Wf5fD6X7WcaThVNDf3dOMJydoK4IWw/6UQ1HsDl13oc3iFsP6n3RhokPGpPtirKA/g5oLtmLCc2kALpm3d/8LxysGDmv0tE3zja/IsAfl7//+8A/B3IYPGLAH6VBVD4e0T0kIjeY+bv3blFL21Iy6G4JXSacxF2IaKaW3KcY2LFBhu9mWmKMtKvjnkz14JjlBCl3aD63hKxCk/CQqPMFelnLtmstKS6BlS17vaJaQlk1Q+0iVLEDDrMNZLQYCOtpwTNS1EjLxGZqQlVmt8JajQk7GPlSihHhGNePZkCIOrkMdcnKsva3zQ0pF0MOJkZrUKnGpJ0h1jCgDYY+pn0qazRmZwlHBwjgiqB58XBSG3ZV/6HcT2KLB30qR6z6GrGqvZFkSV5L1UNEDcn4cbELBGnJnTqnFD0i0q6zVDGGcNFRnelUS4vilamAg40OSwJCDpYVMq6Jprpr6GEToMrEZbsCe4gSW7haoY7yDUcXmSJlFzXnJU8AmGs0RAbcLKX7eGQ4ecanfthREPebQaADwG8q/9/BcB3mv3e12335b7clx/x8oWjIczM9NJF1csLEf0ygF8GgA12N3dw1D5MV8uQ1n4Pzkmy2PE63nuBqe31uOj0WwBjAm86WevqMsTvSZ52PtW1tvdiP9h3dRkyBXDfgSYlblki2bYDWYSjXYZsxLzXMyOrubFzQNoGeTJe67Ko93BZXLqYfeUCTK5oaZRi7es75F01GXKKu8AReNuv97VEPSOBmQ7HLlRGo7qUs6PVEzxuPfyYwNEhbYx5KcxPI1xpt8KUzNImlCe1LUNW6+ijZQibj8g2wDkHHwKWnSXZ2VOZVynqy4lDOAh7c4VZJHlKp95VKroH4s4hDg7dtRLsOne0DGkSyXQZYpEoW4aETY/pkSuq3eyh0nwoyxBfGJxc9C9lZqHRjIWwnMn2/soLg9MDbJm4jpBI0trd3COYnsUDh/Ety0TVSzYcMTj72q44EbqeVsuQ16Hcf96ZxUdE9B4A6OvHuv0DAF9r9vuqbrtRmPlXmPmPMPMf6Whz2y53L6Y9YRqZXwTZbutsX79APVz+bqlfS+uiJe91n5epkP8wyq2RBn3jqEQYbqhuW1tXquS4/f/Xak/zV9pE621NFIZv26+JTB33+fejlOPecq1uikG/or3tfq/Zhvb1+1U+78zibwD44wD+vL7+j832P0VEfw0CbF7cCa9QLKBoUHAuBsH5UzEMNjtD6oJEO8xSkEjwhxBWlHD/pbcFi9huyzbaDIqeN/F2M7o92YBy5T7w02dwexnEilXiZgM+3YFPNmUG4piRH57AN65gABCDE4As5xrp7lyh+/oWsV+S6C6CgCdi2Bw6D/fsEny6A13twac6+3r+Ai54zF86QbAZhs4WWntEQERquPNwU0Q8k0dMaFW9Y0beqlrX4RxgRtr4Ago61DWz2QoC8vTy49omkL0MiCsKd1NoE4r7mJ33+KUBfZMeDqDYJBalrBOPcB0w5FwUteMgCuQuyhPTkKblhG7kOmRPyBugvxIhmJOnY/ksnniwF4YnAFx/dStP7yhP/nCo6f45CBbRq4hQ3Mi5u/kU8xkQrnUACgImxkRYFLTM1leoKeocZEDorqEp6bLdj7kAzG25+KkecSts03BQVbNzwvyA0V3VUWE5Xc/Yin1hB+QB6C+o2BeimXncpdwldPpXIWDm20T0PoA/Cxkk/joR/QkA3wbwx3T3vwkJm34LEjr99+7elKPyGZmAHGOlcNv/x+FSAzbbpLPylHY1R8LEZg6zGicrcJlyqdOEdhCjEIPGpRKMYhIA7sg53F8vAt41BDGXgU7bUBSrANC4oLtayjGsPYgJmJpX+3ya4fd9zQNJDDiZJjbBAbg5CUa5pHJDuDnKDzeJV+nx3LK/XKqloE3ZOw+eKuUcECUwSrnoUQCQhK+Wwn1bf7THGmQ5AwiBi4nAM5VcDkDCpW6SJD/z+PT9Ot+jLeF6faMRy40e9glu4gIOAkB3GUUZSxXHuqsBlJwMVhsqdomWg2L1SHvV6yVmbJ8wNs91YA3QG1rjzpDkMAs7p30FHOGUnh2B1FmblltDuf2LDn4EuutcdC42n8oDZ/O0uS4jIezrvWM6JDnIYDpcVHFgWwbdtdwlGvJLL/noX7llXwbwJ+9++PtyX+7Lj0p5c+nen0UiacHO4h9y9IhsMYx23e8goVYDKIuPhgCJRpQiolJn0fskTToLfuUvwu2xrLzCBKgYAOmxy3arw7s1FtOYIsE5NTGy9sk0V5Sx6jFZj+dird95aae0ORfDGvYOlDJS54pJsfFS2FMx/wEgfh8jAc6vnuyctf9uI40FV8Kjdt6pd+UpmoMrnA7KXJdAnRoye6pPSTMZIqyOn3oRv20LZdk/L5INaj4pckwz7fGl3tzJ8kIMi2yNJfuWftB92Ul9aaCVmY94rFAzxa94VfHxCKTp+7LyLUBk526N9JsQcAvoJjMZ6us5t2peAMTMSI+XNkAa69KEmF4L13hzB4vj4tyNqf5nFrvZj4ldnD57ILpLvU1hR4KQl4Hph8Sgb9phtoGr97ZP2z7bVgZNrAZS9j+ktjeluLUp+FheXbOdsPJO+YG1paVoH0VUKphb27W2SfwBt6097ue8a4tTWwHRXu/7PzqDRVsaXc1Wa/OVxYDNRkW7hDVVI6E4dAFF57Pk6HgnzFrfpDVbHUeDSHEMa8RZWscwDtVZinwzI6D6OXmn1oiuaa9TR7R2YMo6WxCnshYNN2S+2AM6BTd0dlF+7EpAy71DLiQinVkEqk5hEBDSnoAGTFpHWbj5uOTOFUl8O+/cC0ZR+sZmCqrnAO3r4mDWOHFRIjjitTbocMvMgnWWMKvbWDuz6J2038K2wbQ35ZjZzI+VTZk6as6hEr/irtoamP4nJSo6nSJOrPuadqfphGa1Hhiac7zlJpZZBBVxHUC0PuMJV+cziNVAi0PYrCN3MsvIPZWZBSoX7E7lR2uw0PwNU8ECUJSwblUqtjBZs4wAp8peBFDyCmLGymkMDbDZvidVjjZndKo3WztoFMewlm3aOIZRrKpSlFJVFef6OdLRn32ecnU8A0oOhzmeHQ+bTGjyFLJkbbomZwIQD1fKK8erKlNIxSkMgAjGWHZkC6gukqlLt2T9uqVmzhZHrWXtzC7cGl7dLJItimqLAAhArQAnNfPoYErXTaksSXEba0HaYmVgzNIkruouSb2t9B5lVbFScNEFXZoEQtiLwhggN2oO0g5Tz/JzG8aUbbYMCaMpZdW+WamN2eVZAJBoYtgAL1YKVBXEoLTuGvAp/ZujDBISabIZE3BD8vEzyps7WNx28xcNx5bunW9us30zV9k9YPXDJktFt6VNyqCY6nSPa0pzFZfJTYRFOzxpHsOxTqcNFO2NE3MjPFLzH9DI5NcU9eZY9lrOS+X+jgYARxm85PK0oGzJS7lJ32cQsvx689FxWfI7ioKX/dAkm6zK2M9CSaaUiwoYAJUmPBogm3M3CrcRrsRnROuEyeHVwRb6iYtyrnajgppoSPMzES+To8FCCUuSb8HrwSIqHV3b5WaG85LUZZL8AIreKKhSt/0idVNUO4HZBoE6sJigjURDrEH2u5FIlMjooYwm4plyy2AxSwPadHSxNsBqgORx/d4GU0oMPxP8hGpfmHFDv/Szyn2K+n25L/flTuXNnVkcYxDt08r7ulyw/xtDYQBrQM8K1yc5D5ptaaSsIQiwVnw0SKjdQOVihCCYRecb02K6NfKRt2ElWgMAvAlC6wbgDqEQomjpynZvFN8hgEYvUn5LLH4icLItDx7eMIUs55k7h7St/eBMTo6o2jIGJ7MndVEvTu46W1lOQqET38AsdPoaT72sm9kXkplcCoLb1+zfW/tD/weEFFXNlBWz8GYQVCMmlBiBxeIRkLW6uGmtMYvpzN1A9w2zAAQvsExfQLJn0+DQ628hbZySskid0KnUUfAMrqQsdsAAYHpUqeGGWWTvMD2Q74cRL8UsUrfGLNIugOebM4v5hIQMNzkEJW3N54TpMSMc6kkvZ1RmDtJ/FbOIW/EyKaQsRnW6v0N5cweLz5Jnb3Q1Sf+n40iJ6Vy0pCzjwTuq2ZdGgpqiDBwWLmyIXi0BjFIWHU1bPiedtqckA5PeEO4Qlay1vvCm7k1zhLNM0HkppClk08KMNWPUXu3zJUr9RVhXsBQHwDf+nLRkOMUBLD2cFrFFRNbtR7kB3XW8QcrKneRL2BQ+eBJLwZRB6YiUNS8r7crymfUHUM47XIfariQRB8tBKSpbSdmczCtC1G2kLPa3k7K8kqkoVcFdAELUilw1LVVBW1SsXMEciMVOkF0lZVGWtH2XMoZnjP7yJinLllTtMsSWJjdIWYoz+H28nZR11SPNQLev1o79Cxlk+hft0gpHpCyUdlEmdJeqoQHAnNfuWt6owaK4ZR3L+kMjBjGCthvwYawp4SpIK/hAo8acswCaTV202RVmJ18KjbyYJucsvAKb0SyL1GHt0TrpZAfap8rPiAm0n4RhSQQMEtj2Ty6kjuYp60KAu9ardxjhO01mm2cEvcHyKPZV7uJSaObzIqrnpsI9TqCLK/g2mQ4Q4HUkYSPabCom8BJAKYnALwDajzXpjhmsFgHoApgSuu+9qDe7tt2rqLGtpcPQyQ3WyhFCcaD22jTFN4xYrzO2oZ15earhUU9le1AsBYkxfHAhnwePIlvYhHv7bbcSHAbkRmcvEgTcBdDzy7q/CRy9kN/CZugkipUZcdfVdPRcvUNbdW+bXT76rRH+ygAKmcnRkrAx8+1YVc8tGmMzPrcIk9Z4MOHJ5a2YxUnnC2hg+z741h4nH3XoXlRmbB78yg6i8Ggc4fBuj/55LCbUQAVm71LenMHCefA01bdnZwLk9XLz8Swdkj59ivATXwPrTUXbDfjqGrTdlm3IoibF0wEINTckN7kj/Ad+So6zl++kB1tRT9J8i+47nQjkpFSo4bwdgCUin+5qduqzS+STDbzdzM/lBz398z8Nf4jFHBiQC7mcSv3986VIsofriOntAWDgRAfM+b1zhIsJadvBX0/IGxXNeXaN9NapLEOuzRdVcza2axf14dMRufPwhwXxgcTLwoXZBUpkwMR4ut/7EABw8S99o9CcKaGEM4UIJT+s+dShv8qgWKfVxILO98/nGnkxP1oGprc2RY9i2UnWae6pULgr4cppREDqiDuPsE8YPrjA83/ubdlWXNQl38OWMtNDeXKyQwV59Ry6g2R8nn5wqtsZh3c6LFvC2fvn0q5TX3JDcgDCWG+PHMS+0MyZLXv0we/s8e1fOMHuu1vtVwlz9peM8bHNLLQSrjaFRpbyI8S+UHNGHv32tqhzO7PudcD4SKwVTz9I6C/lgw9+/gSHryRsP7B1BRB3jP7SXNQbElgnfdFfesxntW+Wv393nsg9wHlf7st9uVN5c2YWR4WIXk4wc64hZblCVGq+rDoWrr4el4ZqXYx8UKeJUoer/Ak9FivVu5KrhFBVpuNmMNwLzRpNanpqsk5z58p0kCehDJtOJCAAWSF/NQbGIBKD5c7BhfV5cXCrKaYZ47DuD1TMhI9e7bhxIJDRyAtmQUp/RtnHzw7O8QoEBBu5TUPOcBKuVt2JvFQyFkiyR31fjwEouYlciemlDUk/Bl8k6dJGZwyeisEwIE9tt2CtlJUA0cVUUNKk6lTRKg11WxpoNbNow4qpU7q0kr5sZpGDU2KUvu8VTIxCmLJjaYeUbVnPm50QvdJOz7enyg6tCoCIGyrkr6RgatoycLaImbWWeMJCUyc5XtpY/zIoCngbdxZyx48xKctKi7Yf8xtetf1lnzOv7Oxf9p1CAiuEHfm/2AWgbjePUpXpLYItAFTAta23+bJ+Lq83z1mOh4Y01ZxDK5NmYrZHxzr+rC0uNW1sbrS1Hyeq3LwBvWz7HF+H5rX5vhyrJWXpZ4kKP8TaQHl9DrKt/pV6k73nylto6nct4YvX52Hfd0n3I1qBf84xcqrbbIlAmeGWup2ijnUJJbekfMYNu9LJw9BFyeWgpj5iAE1/m7es7VelAQm8OLFw1H2d1aWDheWJOD0fO8fSrtfgWfzoDxZtMXAyQclMub4elyPtwfKDPK66PZZFO9QjA0AlVxXSlEZDYh1Eqh6kukWRAHh14NAfSWrO4WiQONYCdSk3N1R9bQcLU5OmJPu3+xrJamVeXOpA3dd++K65yaO0z8WKrJcBM9cwYbsaFibm+lxcRKNgrXWTMjONrLXo/ykXQpSIB1tbK2bhlnqzZu1ApzeES3Kzl/YwtF/aG43hFju/qrhtZ+N8JWW5Rv2K4ppiDbdmSlbBXsBNOrMhhtOb2SWs0sbtiV/9aiS8yrOQslZtmJ2cs53DLG0xzKLMVFlmFn4G0tQMYj82g8XLkscsExOK9iqyXCz6zPqwfT0ubdaor0lUJRRndnWpWeJYRqWn1fdXPAuqywxBwWtbS5YjSW5FEVO1/z1KBiR7zSL16/YhyLbsnYRFgRISbnNWABRGpORXuLKPfYZ2/1UbdZMHQMYxqDdV7lpA0g4mswLpP2tD1gFWQpw1x0P7wNf+brM5ialOgDqt07uy5Em9zgoSCVBo++oSQI6lzUoyKKQkyw4T0KGoy6tmGWLXBySh0txmb3b617TT+jEPXOrNnWR1uqHJwSgXpFkWDNCBVWYxaWiXIaxiQijtSp0sucq1sDq2CXmoEak0yIBR1L213hwA5xlporKtzEDuWN7sweIOhTI3D+HXGCatMBfqNlr/Bz76v329a9GppLVwNWtpp+XNkoOacCglBkLTDmvD5znP1yh1BiDr5drOth1YaT+upsztEqpp72ofcFG4unu7mlc+em1LszwqfBhtV10S6PLjaPn3uUrTD7itTe3klNfbKNP6c1t+5PVS99a7mgHLFqzHY/3Nra/P98GQ7D4acl/uy325W3lzZxaWgVjetyi/L8QiDkL35i4AB9shCz3au/p6VEdSpWiaI0CEuPVwTbSiN0p0rssIOAfe9EgnfaFPu+se8aSDu7bAuXx/PnMAgihVG0fqxGM6V37G6LGcaR2JMZ/K987IEH8Hvxf1bDenoqIdiJA2HstZw5zUpKt4EjA9rFNSP/YSHSHC/EBp5ou00/gM8UR5H0qUmh4SskZ2XGSYEIxkLKLsAwApEpZGmL3bE7prX/QzTfSdWM9PL+dy4vS1Pi1T0dekVfbodObAXghXdty4VRxlqXwFABi/JMsHaDQBQImadJfCZdh9YpgQYXooEQbjioyPCMupRid6oLuqdeeesJzUJKzlVL5z+t0O7isHjONO+1WWGrlzmL4sHeb2vvp4nCmLdZNABEyXHdzoyvb5/R5+QsGKADmX8UvAcpbRXZOuD4HxvYh/8usf43enL5e+9Q9njNuhLEN4k8rxUiLEpz34sfKGogP3d59yvLmDxTHdezU9r2xNikr3jmk904qaAWmvR6VQmlX70U+SUk7NkqOkiZcFdFaqdVcBx3kRpp/pTuq+3XWGH9M6OmEuUwSEMVU68JTQ7cNqyu4myQj1moVYWHlJBV1do6tpYKuD/Ji0+EOESw5+jEXuvrASo2ZzFkkMqaO/rKnVLaDpYkXRcwd0ewXauA7AYVynuJujGWVGd8jFNCccpA8oV3q26VC4hVbZo0yyD00J3WUF9sQ8qMFMIOv5/hIqSiPb7IYLewFjC2ORge5KtgVN8e4vWcDGReo9pk27RfYBal/4Q0L8ZIOTC8M9gDwQuhcoBD8/1mjYMkmD8yB5Rt1BBqdl6bRvWMBMqroV7ID+uWhy9JcZnfZZ/6nHt8/eQves5tgsywb9RUPKslB9H+Aiob8gzHGofXOk//FZ5c0dLI5nFselAIHKuWgBzuOkspfVDwX8TDmKUIBAEBVBnDIjeR21JhLwi7jqD3Ajn589lWVo9k6xgSrOwt6EbKiCqoAAnOHuF/h1CxOBXcUYyo1HKKChgJ7S3jbd2c7PuB4mwmveo6UfXiN5adU2Y6k7ksHcKTBqPxPjJ/jaVkc2u0Dx9AAsPApV4/6C/enbtgE5cOkLaxdQo0S2n/Vv9gzTR2FPyJm0j+oA9LL+cC634zXgrK8hAKp99n34yby5gwU50Za85SNuTYU0MsKOqn3hHeT3Wum5lq9fOleJUGJlVwlbNN1S2cvqJ6xvEld/MBKlkP9zJ+i9S000xKkalUU0bCDs/A9Wyo1QI032w9PzKOfmZGlCiVc3vtyQNepR969Eo/b9a5fmhgQTMhjZ1xmQDWziN1rPx+Xms259Hjm8/Ga8a2HH9WbUwQrttS6DbzOAeAYnAgcGZ2p+F7KKzh3KINjOnlaFAOczYmBwE682ujsDdRByle/zecs9wHlf7st9uVN5c2cWnF8aCjUCFQCYkpQQgpRmzC8JyrW4xzHrMTeEGN1eGJjFS6QCdq0jO275n7RNLZmqMA4JK/KTi6zMyRo6LbJxxBpGq+dbsIDjkG6uT9naTv38iO1Jho+UEGNz3BWrkkXbY8V0FEo0NSnO9j8lLk8gSzu3fi0MzCzXp7VEvMkEbd4fhz2VxegSwAk1PGoMxYbqYe109pkRmrT/V1hMG0ptGZTSDWtlqZZ9GxsGp0PDtKz9Vdpn5xVJjhGVXt7uo2oH1q7CorWQcLkOQIpejm/NMpapnYOxSF1t0+qa4e7ljR0s+GXybADADF4047LvwCmLtNzSgIx9X8hahRV5C+Ygrt8V9DKmI2KqJkFF/MaXZUubU8GhjZjoFJ50Ld2wJKlTbELBK/stiF6DVncQpJrSDm6/gE97uDmV6IuYIW2QN90NNW7LDi3vVdi3FQeumMgRCU37RpYQtT8ooXDaCkuRRKNBbliq++pAU7Q5yg3Pta+BknuSNzdJTkll/ovcfUfwJsN/hAFI++odXUSUkyw9AMVSAsrNXoyDlLpAEQVMTWdOoiukUY1Y+1LIVlR0JywKw8GBfV2OtVhEu40dg7zkaEhbGegAzAJisTfmr7A120HMLcD4WCJSqaOi7p09QK7+dgAAoYodwwMc9HgdI3lGmh3STq9DbJbddyhv7GDxmYlkzDWRrH26GrCZkmgntK/AemZhwjFFKDWBYkZu8QDn1poJRCLuMsaCVFMRojH3MqnXj0miArmuZ92SEQ7CchLtxvo0D5NedG/gIAOeapq33RRO9Ba6fYSbakQHkAEqXNer76YIZA83RnR7DYdqNMRS1At2o+3u9rkIwJoEPjGBcrUGDPtKO27BUD+rII1J6OvMAgz4KZc+87Mct7+qgjbZoiHzOkVdjpdAU0TXRGks1yM1dO/uUiIY3ACORve2iEebnxIOaiBsYjJXGS62KepNNCSQREOu6k0t1zmiez6gU5kMG1S6q6ri5WYAUFEfpXWngQv9W/Q8XfmNuKgDQbnm4iTmZ0mRD3uNhlwE7J9tsL1qZ2gO3SpFXR9eQWZA/SWKL4zlm9y1vDGDBTm6kcJBXUC+FvIEHWeVNnRv6jtw3wHX+7rPbVmnLVej4V5I5EH4Gm3WZjmWFUeaZerBg4Ge8n/JOjXDGpXUby0CU+9Wku8mo+8WcfOWm3MdpREwsKFlO6F+p8GDNBRp/qrcO6RNbX/uPLh34OiL67fX7NUcHBwR2M5X250GapYLGt0IhNTVaXXcymd+rtmX8mN1KzMi4lysCHJHyNGVfgDJD9lpKDMXKjfBe1cGobiVLFjuQjlW3FDJ9RA9C913J+1qB4t2OTA9JOyeaNvUzzRtKgVcMjuphE7bkjuSrFYdJOLOrqNHPMtF8s94Fi4SljMdHJvQqWWdpo0s63wPRK6zkNTLXZ59feqzJyy7ygnxs3wQTxn+wYx44csgGHe6tNRBOhevU8lhoVzbZQZHdy1vxGDRun+VotqT/u3HAID05Gn9LKby46aUwfMiffPogWxbIvjisojplNdG7s1fTaUuYo9wIYOSeXfy2Q7ppIe/nsE7NUjuPOjJc/hpKTMAvj4gxATWQc0EeDafjKJozdWLxB0iuktZsrg5FQk8Shm7j+VJnk4tBs5IuyBP6kGIWQDAQwdKGZvvXFVpQJPy6wLCs8pSclejDKZLxOZK6z1I+7xzQM5wKrbDe2n/6ftVvEZmazpYuZpDMTyXJ5mfErpNJZa5RfCU1OQqyPXI6F/Eit+oItnJ07F4j7Yp8xRzmS3lTYAbI+j5ZRGuacOlua94we4T4VGkvi7HXGRZejBkoCjrffEnDWP1NN1+JGJBlMSpzdnsExLByb0vPJWsg2734QUe/8N3sf1UZ0geiBuH/iph91GdYVniWmoGJhcBEOAWxnwm2/urLOStri6Zckc4+a4oXA1Pp9Jnjx48wP7THYbnFU9iJ7wRU/ayZR47Qn8tM7m4099dZnzUPF9fVe6jIfflvtyXO5U3YmZxazHdiJd9bjiEd6ip6IaKvQQYbUuLdUTJwSbmlZcHGciqHiP0OqQs5hJxKF4VwXwsJXJT0X1NN09cTYgSr/GKxo+EbhF0/X4WaiInjLoSI8URmFTUNnJlayrACRPYRQt4NLMeAAAgAElEQVRoCtGhpKN73GTo3qVdxmj0MkMQ344KoAqZAwUbAVA0LIzxWbxPEiOrizjF12/LqrQRCj2+RMPq8qNGdbDaBovUGDzR6FW0uM2t/aGRDZMMAFB8S4B1BOrHm5TVWhTq+1K6UMOkXZAlydCvw5RDL/qZ+gpgBXDmU1lauOsJIEI6HwTg1KhDNy2CGXhfDInYE9xuA240OB0z8sNTOPvBqgDw9HgDv4+rNq01OF1Z53ZXEdOjTqbKOsVcTgO6y0XTj2NR5gpjRNp1MiU2DU49v7zpsJzXZUivtohuXBDP5XzDC2O+elBKVdvzhSRCHN7pC4BmAGfuSM1+pd751KG/FpXplRXAlOHHqjtR0vUBzA9CmVbHnTBT44lHd6nTeouK9E4o49FwCNHg7JeIwzsq2d9XPYvWKHh6KMDicW4ISMDM1BM2z3VqnxmHtzxSD4RR+mQ594gbGQhzIISx+b0UDU61MVBs6Hw8weVPoiy9zCawuyRMjxQEVUcyYiCq1aBEXRhe6d7TY8U3JqfAMTVLCODw2CPuCKeDQ/9C+uHFTzgcvpIQP6jLvrhjdFeuYham7t0BfiJ0lw6LaXBmIP0a7lzeiMFCHra3PC0dFaHeQuWGgpoNoEgqd7dSRfZeBhh7PSqmkEydF89PZUu22gC58/AxA0lvsM6LzV9oZO68L9ulQr1BOgINXliOzhDwCnCmrS9gJCWPZeskzNfoTuTeCwrvqLSXB4/cO5CjgmMUZmPnkZublztpJ6c6CBb5QO+E5df4pACSyGUApUukjEhaAX5xK+fpJ8ayq09Pdg5urhJzRcDGKRCpIdM4yI+ZParfhoVOFfw05mEa5OZB8Fi21o9UwrZpoMJ5KABnw8qUmYPccGlDCCOV7amXhDADTtm1snrNiAOo7wbBqTRgkdXrHJYHWUBGyHHTlldAYn4JwElZBo00Vam74lsSUJiwHCRkGncKyiooHU8Y7tGM5WpTQ81bLqFbyo1gby+aIpSq3N+KDn6H8kYMFreWlMBLLBTu1neUDlP1+8jCuaBrAGYKFCN4nATQ3B8KsNnWEZ4rsrNEIR0tScBIu3mmBf56Ao3VB8NlBl/v4VIFWPl6LzajGomxwW3z8Sjh2UbDk4NDvhCuhhsXdHasJcEvWaake5ktDE9dyVh1cwKrkYw7LOifOZH8n4yToQBn38Htq+KKu9zLYDovJWRKeyEKmLS/69WOQOs6e3+qSyHWccPXqAygN/AiSW4FzMxqfThXvwzLDXFq22j1lqS2Q5TzAGo+T3Arq8NebQfoxXVR4S4AJ6/BzrgVcK8aHENVqCQqlfsKZlJkhFHUvLdPNDt0EiEZ8yM5ltTPvSscEnuohE+v8eg3dwXgNF3Qbp+x/bjmyAB28zYDni4/3JJLFuvJR6kI83id2XAgODUi2jyZy2/k4f9zjsPTLYZnVfsiB9KQsAKcJlLkCd1BwN6iyJ6B7za+qK8q9wDnfbkv9+VO5c2YWTCLMY2rSwALQaZPJWRafES6ILOOUYZEIpJZRtchf/KkfN+9+yVgnEDbDXAlJjK028Ecv+xJ5jSUmE+3wNIYIz99BndQL4iDcj22W/DDc6TdUDAE3wUsj08QnuhTRI2D5l2Av14b8ebOYzmTz4cp1qfTGBE1BNn/o2dyzOFt+KdXyCdbuOsD8om0hZ5egNwjTF8+LU858yZpMREA6J93ggGMqepWXPRqEygp6qbr0SkYOz8IFbPQZUTuqOhfAMBy5tFfMJLzZUosJ08YLqbCQm1L2p3V8K/23fVXt+g0pJs7XfIE4VAUVuXGwR8yNkOH5bThgih1u80YHR9RSSEvfc7CzOyvsswiPqqP0uVckvJsBnH19S2WrSxD0qamqEsoU7gm/ZVcv7iV9p72D3F4lwqpKmsWa+oZ41tG3KICMBbfkADAAeEacEuV4Dt7X3RafduFifHsp3ukDbA99wij7Lx/l3B4L5djA8B8BvSXlepq9eYAxFOZsc7Gs8iE9L/duFQvLW/GYHGHQqSOVbYEMF5GS75qoxXmgerc2gdV1+NV+l9fh/UrvK/LmjJFDuAuiH7moFoFQYhPUCq4UcONNOUakLYlTeVuTZQqZCpfsYVC+Jr8ql08iEcnKZZihLU0CEBnP8ywV/JW5iKekw++LC2yo9KGLnggZcSNK6w+8pUwZWQpAFi24rlJqQrHSHHIvYeLN39WafBlGWLHjJuKY4gup/yoXSI4X9fwYKGrr0lZUPJUPf5ySjWfworiAiKBT4UfIfVInTZoL1tCPJEpf9zW5Y0Bhbmr9S8nOrj1DvM5o3thGIb8EVdP0TartVgBqNcpk5LA9KaOWwfvbkZB4okMYPFK+rlsexixNNya5ayxJ0RrBQDEswQ3eyznlaH744FZ3FaKgnbTmW0ItM0lafe9JUzXJmwBGqrMGdAfL5rEtPL9LDkoopqdyzYkO0Y9FkWuoVcriUs4jFKuIbvc0JutXRo6pZjLa2lDlEhECU0q85Mir8KGkoyW1/kpKUuUR8+rtEFFflzkVXgRABAF/LMIheQuCFPQNfkTlCx57iZY3XqlFuAzNuHBgqvqzKLsQ6oiziU3RfIm9H2T7eVnKmpepbDULcfCCgQXyvrN9rhFJrmtKrdVZu31MwpV3M/rfQWHYPhpHQ0BULZRFlq6W7CaRbT93xY3o+xf+mYm0OhX59y2RQ6kB2aGGx3cTKLEhSZ8e8fyozNYeC/RoBixomC3bunH0nud0MBL5MQ58UslQjZZvlYER6nfsm9TX5OIlred0KgtMasPSBuPLniRqDcGaBBa9upi+MostCSvUm9X/7f2sCqM22s5B00MsyeieXGmwRXHcACIG4+0lXNqZzQcSJWYct2+G1AMgE2FW+sxwNCeWKkJpbZPTWdA6C18FEtos/8BpXtvap0iWiPq3nZTitq3Q9x15Vg5QK43r5chqb9J04ayIXOQ1zb5zpSyS3s2GvHwwPwA5bdlIVp2QJqtbyVCNJ/71XFtZuG7Rt27+Q2kRm2bPeDse2W5sPYrKd/binJ32qAqifcAb9JqtpR6wDd9UI7XAfnRgjj2JZHsxycaclwa5/SVcbL9n9LqKU5RkshoicXgmJilHnIlkcw4FDSlmlxm9ZrBr/E0YqzGuNp1tCT4MUlUJVLZ10+pJKeVNs2uINxuSSVsKHXk1bFoSaCYpF36ap/TJMcsDuQ2s8g1TAuIdB+xSL/ZD99NERyd8FhSRtD93Szm0mGs8neFRJVluWCYRXeQ87B8ECt+znBzutVF3U+pYBZ23uHgS3TCRRlosufyZAZkQAkHhh9j8R4V6rRiFs2huqu1FJ7tm2KVzmsp3GGUu8X6MeyFwOUWAKScDShmEWQm0LVSe0HkE/sXoWw3zCLsGd2VYRYoS0MbcNeYBZB0NhAO6yS69tzcAoR9nVmEa4J/HtBd1/3Y0eq9zfxyADh06C4rvvK6Lur30ZD7cl/uy53Kj87MAsBL9S1uKybu0mAWZcp1GwHsderNWIvncPvZF6QO37GsqcNc/D2IuUk754IjrO0PWd42gjaCvfxgaeS3FjskK8bijJ1pbUUREvpBF9PRsKSvlVgPH0kmMAqL9IdS7FozboK4dyzFva2p63XKj9ZgYdGQ1mWsdR473tdS2Y8ZnOSqAK59L0gWZnEaa+tsjsXqQMatsG8rsuOMBKOOYa1DWOMAJlNud2N7azsAsyOgph79P3eu5GAATsOh1fEMUBJYILgGhzAHtxVWU+qV/Y05WMZWFdUhbqe0pFqRLcCpIsf+5oS1dVCz827xAlM9z2EtflNwhYb+nDqCc4JcrtS9e7qJWVgkw9zgmt+Cua/ZtZQQMer/KhxDTBX3MNykQ9EcTRsuWBErNpLnimNQrgCniebkTpY1pCbG7XFvE3LJnWIyJfdDj7PhwtIEgDxwsSe0fQAg9Yy0yRqF03b9uDqScRvtcG4FOhYw8mjA4JylL0pilPVyWtOeAbn52BdFKfcSgJPYtAaaXnbNPrnSlP20pppzV0On3PmSVxHa0Klr2mPaGfpqn3PnV0CkzRrYi81dBX31wBlr4NbanJs6orBNjW4MAGzr3Z6EBk41dBpG0d+wcCYgN9VKRawpaXBwsy//A4JHlPwHVcJKnXqGWHcGFDaiHSttgJwEiGwHh+UEN6IhlIWX4RbhOBjtHVD9im3VMEnFlpHXSlfajrQhJI0kZHU7p8xYjvQsWMFgo3tzo01htO7csahYsQDdcauh4sEh4OYML22Eyi05HlrXKYMezIgnm9oHZ7mEo6Wvtb0Dg3tG3DKyAZw/inoWx4VuU6/OWW6UcVqrX7WKWO0yJSbZ3oJtsf5PRn82KvchgpZUw4UvATgxL3Cjr9NPVcqChiSh0n6mZNUCnK2SlZsiur0+wceIcJ1Wx3KTgLM01lf7nMaIsE/VA6SYHRO6JjrgxiQhxyki7CuYCidxSooZbrbtEWBeKTEVUtZCRcEKAIZACNepZH1a8XMW7YnpJsDZ7WNpr82S+itXlLIsQiPhz8aUmGUfN8aiUpWW20lZOeAGKYsYSGNVwSptANBfBbilUrj7q075G4w03wQz09Rsk/tcCGOfdBgu1gBnd13b1gKcJoSTA60ATn+wPom3Apz9cwnF9i9y9Tl55pA2A4ZnzYAdPfrL+r3URFnSlsR/ZLEo2vr6varcA5z35b7clzuVN3JmcWtxrupy3onBqduCL2tojk6WIuQ+N4MTXdAlhNLFg0ceAny33veHweAsTwhflz5p48r6uLsWBicSl/rdJExTDgTy1a6Rg9dlyA+XweniEYOzI7gAeF1OxA2BstT7g2Zwxi1hOVnLBUrnKD7QVzwhKoMzDT8sBqfI+lmWr2x7PQZn2mVQ9FjOa2Lb6xg+/cgMFnQbUPnZX5DUde9K5iq8AxKqAO/nKBxc0ZUEoCQpKpqZryWQ80UKNTgEADG3WZv3ZAUsnabfAxBwVB3QHCpBCl1YM2N/GIUaUpwaPFl+CNVViJxX9xq/6s9Z7PhiRlRvcrup1kZJCjgOr/Gb/IJtk9T9mrn62nV0rMZRn68Nb9RgUdKlU16lkwNYaXLy9b7oagK4VWPTdDpNoxMA8OiBkLCY4Z9cyHc0YS2YJ6oBnuNUQ66ado7MoLMd/NUEN2qdS0S4nOEuD/LEPhOD3M13LkQjs8FRWo1MdzUiPJfzpcOEE9XTNC3M8NEFeH+AH2fwPMOPc/ncf+ywca6oepnOZ6vxCUB0PicvWMyoxKMXYwUgEyNs5CeQTge4OeH8W1diFo2KhRhoafjLZtfD72egSekHBA9xL/ZrnEjLJmeQnkPYaB/Mp1WZPNQBjQMVvGQAij3Dg98RGYAcXLEdaIHm0+92QkBri/aNHyNy59F9eFE+Oh9PkDuH8KmwmE77h6IVkhjzuS+eouK8RmpzYLMjJwMFA+/+esbwTGUQNLLlx1yNrxsMoszkdFAKI5f6AWD73etbldByd17c12w29aV/kDD+foftp7W/467iQPI9A5CBy68EbJ/klcjyxwfcubwZgwUBcB55rBmB/q3HwraclT5tCVrf+xDun/05+VECyA9O4J5eIj84hX/2Qr6cEni3AV1cgk+2ZRmSP/ykRKUO//LPAQD6ZzNAhP17A/zEiFvZ98E/6BDfOoVbEtyLgx5rB+SM6e1tmdbv3r/G/is77PSp7L/7KQDgw3/zJ0W+feHytF9OHMa35Ol/+t2M6YF8sHma8eIbotD8lb8j5/v8Z0+x+2jB/CBg83TB9FAGlpN/fIWrb5xiOnfYPlMwVH+M85nH/kv1sXH+nSjisZcJ1+9IvScfm4s6qVCs/KAf/u8fAwB+/5e+jF670UV5muZeFJ5saTC+xRiensAtKFNtYgHrTj94KLYGUPBMIwYXP9FhuJDt0yOn7QW2T2wJpUuMnbAUzcB4ekQYnjEe/daIb//CiexzwnALie7DULki7isHxE826j2qYc9IYM/ong+IZxmP/+G7snMGLn8SWB5kPPpNGeAP7xLmc8n1SD3Qv6i3R9pI1GPziWYVazLWu7+e8XN/+pv427/1s3L9+4jtbsLlJ6f42tc/AQA8ud6JFScT3nsgnfvW5hoOjH98+QgvxgHvnQkq+e1f+zr8KP1ezI88sP/Ggv7hBPfNU2w/0YH0j3+K/+in/hb+wu/8q8W+8KcfPsH//ek7cCTPuse7QzneGDv8oydv42feluzsQ+wQfu1mhvDLypsxWNxWUlrPLhr/UtpPVfhlH4BlAY2T5I3ovjTNkgeir8d1dBfyy/dXIqs3PPUi6GKK27OK38QM0mO5a1nX9xce2Xw49jOGp30VcdFoyO5JRneVVMBGLmQYa6bo8CwWzGF4Ljc1MRfl5s3ThO5qEX+LqxoPdPsZw7MIP1dJOotSuIVRHGgA9M8jQu8QrmN5AvfPpS5LOS+JbfrUP/keo7vWbfZj7URBywYLPxL6C4lYREuHZpGuG57HShcvCXjA7olHd6WDm16OcF1l7lpRGD+xhE8h1PD+MsNfzdh9V/K708aiIWscYRx3OLmgOmXXc2AvniJx54tIDVizdC/qNmKH7kW1AmijIaJU5UvUwzCK4VnE3/6tn8Xwe5pq3zP2/RbbC8L74ztyDnvNBGbgW2cy4H2rzzKQXnv40eG3z0Tr7vH3WJLGXO0nOZ8Oy6cBJ99jDNpn3/vtL+E/j/86nv3u47Js++jBA7hnXTne063s+60uA4kQngf8H092el0I4/gyI9Wb5T4acl/uy325U3lzZxbAy13JWgJWy9QsX7RtzatUWPdpGJys0QHONTOy1NkaGjknNomNh4ZFFioRSpc83liaFZg1IpW5kpfsTsvq5IZ9aRmc9p2GGGYgYLvGl2PSCt2243NoyE+NjwQ3bM3aRjQMTlaNCdW1tIlCAf+qfB24tumGyztpfxQWqYKFDSOyOMoHFEew0p4g16vY9vWVH3DsNi4kLpTHILWAZSftAGTZVPb3zbl3689KX4b1NiODsSf4PiL3TXZnr1mqvTzVc2PxCN3mhgRyQFocEnPZnrtQ6PslqEFN+5XHAQA8ZJxvJjztc7lP/JCQ+1BmFu3xOImuK22U2xLda00X3tzBghyKYSVwdKM7EZsB5FUHD7JQZ0rNzXs7clyo1gqsZU9A4xXK3oH7ACAKuAoJZ2LB6oZg51Zp2dQMDLkjENULYmpLgKDo5f9OPDYp19Bt7iWkJwNJ41XaiWAv++bG5zrAtCSldqCpvpt10GC+STPPnag8AcLgrDcaFRwg9bIUQCPOK5L2onNpAzlFhmXDSr261Oir0E07YMo5oFK+9b1Fmor4bKdjslPSkfHoNow8UMkQlTYoMWsQWrapcktbhRVZ6lX6dx0sGsJXZ4NbDZFan293E/b9Vq8bg7cJ6UDlpszc9NEg24atrOnGRGDy8FsZ/dIgZqs5VDYqex2AekZWb1WpJOHd3SW+vX27tHOzWXC9qYOF1zZ0fUSKDrFnhF62Jd8kGN2hvHKwIKK/DOCPAviYmf+QbvvPAPz7AD7R3f5TZv6b+tl/AuBPQIKU/yEz/y93bk1b2pR0YB3WW2JRpMK8CEaxxDVm0aauG827qaOwH2fRtwhjAi25JmfFBDosoJRAswm6BiDlqqoNYT66qUnLNs/QQxaPTvP7BAAG+iA3SriqEn5hn9BdifaFpcCHfS5S/36MZcZD04JwSAChIP8m6BIcFVYoIJ9TYrgpIRwUY7G0dhXnsRR1SyLrrris1aXt8sNNfU2NZkfoX1QBHEABThWELb4hZt2YGN3eF2aomUPH1AjoFhdxoXsbZpG9Qzhk0JIKOzOqa7lbGG6oYdbcOXQvdEC0mYVSmrsrsRTsrwyfYEnXzoRub7gJFy0N39Eq3T3PQuEueI4OAH7MuPzkFNuLZrA9EPoLwjjIKBRMVi8DUdXBD4OMSu7aI8yEqEza/oWI77QAJzuxS6QEdNeMoJ6v/mmHb378ZbhPK+5wPTuE56F6nW7luo9dB2Sgu3BYyFzvqIo93aHcZWbxVwD8RQC/erT9LzDzf9FuIKI/CODfBvBPA/gnAPwtIvqnmPn18+TU16JcrnaG0HeAWff1nRKVOtDenk5evE/H+npcRzyVDjYF7eU0wM1VDGbjnDzlI4EmJUr1wkVIJ10hFoXLDvG0Q7jU+nR2M53XsJkNCsuJw/jIwM6A6VyfcovH9NBB1Kpd2TdcB8Sdh5tD9RjpPOLOY3rgaxRAb+Ll1GN8VC9+2AekjUPnSfYH4BZpZw6iQGW6lhudPY1v1WQqS3IST9Cq8jS+JX1JEUWVWkx4VevCjJGzLGMocTlX6Rs9x3MCoCQ2fbrHrepXKEg/PZDZz2bbYXysEZMTufHd3AjMAJi+vJQpuD3MjSORO8nVKJaCWXw9ljMuKtzjW0Kk8pPUa3oUgMwklrNK4bYo0HLm8bWvf1LATO4zaJMwDj36r0pIdrruYVLpu3OJ+J1uJniX8eTiFMuhw8kDiVpM33l4IxrCDji8k5HPI7rLHjYSuq9c41/7+m/hfxr/mTK7/MrjF/jw5AGg0ZeTnVADToYZKTt8ujvD229L5GWKHr6/+635ymGFmf8ugKev2k/LLwL4a8w8MfPvAfgWgH/hzq25L/flvryx5YtgFn+KiP4dAL8B4E8z8zMAXwHw95p93tdtr18+S3NC9SIBVNJTG2ZVjUxuXo+LhRuRs/iGRNFXLOtB1a0omhh2rAzQkku6NdQQGEZgMr7FLPVRAgym9Y0uoyg41+m+n5UvoN93pmeZ7HxqGJKS1m9ajBY6nV3JSARkxsGztM+OVc4bGjqdDVCR7X4EnD7VXbIntCxHqv4kFa3KbHqOLGtscepulzHydG+1Iy0Em8faBzXWKbMK2x5GO9dcZhvsbRmiX7UZ1t4XJe3Cs1CjJDdLyLdokWbRq8wjFV8PP8qSy89Sp288NUgzd21b8SVZGE+udxIehYCZmcXMaLqW6RLvfcEQ9k6mQjE60Xe+7oHJYR9k++mss1HXtJWAcCAsPsCPtW+W6x6/d/0Wln1X+uDZsEW6rpiFraSWxSMnB1wHXAwagk4OKTUz9leUzxs6/UsAfgrAHwbwPQD/5etWQES/TES/QUS/sfD06i98VnkdUZzbyktozmQDxo0PNKJhIPct/V22HdXdfg8EvFRP4KhJ1SuTX3rMtv7jz2/bdmu562/nqH2rujOX0Enb5pttpVV7X/X3yia95NfMTa5F6zl6o87j60n1r1C9b7lmRHxzO7UHq98jx/JHgHO5fL4K6LH8FYEja6tjbYtGzRwjuLyun9pj13pJj812/KYddy2fa2bBzB/VjqL/BsD/rG8/APC1Ztev6rbb6vgVAL8CAOfu8d0hWfly87SvM4ECiL6GEhYlwRTKj9paovoZ1Oho2L53qre54GyVNuAzNSpVlBugsHnykc6gRCW8zm5+0KpRVfmrnocpQ5Xt+WibtTk3CuMMGIOTmKv6Vb57P67KUbta1ad6fCi4Z4ApQF73b5Styn2c1+fweQqrIXNpY9a/8jRpPiuXUb18MwHNRJmStokbpa6XHpgQswOa2QGX60X1ffP6RcrnGiyI6D1m/p6+/bcA/J/6/98A8N8T0X8FATh/BsCvf+FWHhfz6AAkjOqaUCoAkHifwlF5BbDKSjVznNBV4xqwK8rJovQtZHxLDuMgvA0JdWpdQf+3aEXjGeoHB1BlcKZefTUJK9/T3Dkk9amwUGIaasjUwqWAgLe5E4/PEuZVboeEB2s32H5uaTxWrZ5AYKrbrW/itlmGWIDH6jXP1q2xKBlRyYA2cIifSb0hAblB40AIRum27NEdkPbWLujxdf5s/biVLFAOrhj0CMAJuEnCoSUachaxTIbOorQhdww3i8enhW/NpLjdFrfyXgDOdfZm7kW4xvQoimfp4PDegxeFmYk+ww0JcXEFzNy7AeTk4XB+LkDmyTCj8wkfMmEeA87PDtqGbZm5FoCTgHiagLOoRtGyfXM24Q+ef4hvnr9XBoN3zq/wwRzK1MkAzrPNhMSEDxePtx+ICfYcAz7ydx8p7xI6/asAfh7A20T0PoA/C+DniegPQ8aw3wfwHwAAM3+TiP46gP8LQATwJz9XJOS+3Jf78saVVw4WzPxLt2z+bz9j/z8H4M99kUYBUF2HZpxpPUFcdVHn4OTJf0TKYpJpnr0C62V2JQMJb5+V6WhPGfYaOl1QNS860YaQjEF7qq9Ng61UvUZXnnLGwpP/a4gyDUI4IoYSwSQXIQ++WAeWWUQnloG5IWAZd+2YlJUbUlZx5G5IY66R2+OWwdnXxzITCXmp0XlMg8rvLZUoRSwKViI/p6E9U7tSslNLypJrVxmVlWGqpKyS8dqwYRtHcDgCE4sOhAGcm4Q8BMEWFKi2RLI0sJKydGahOhdpw3WGp9eMMq/0NuV6sfyFuq/0myRpfathSg7bBYehw+lGnuoGZuZMOBlk2vZ4u4cD42o74Ary5AeAJ3o+7FFtDhzAHcP3SZmwsnm3mfD14VOcbKcSOn007PFkcwJHjMxU6n24OWCKAaFLOO2kDZPLcN9PUtb/Z+VV6/LiCIa6IFNC1I309s8oa5yirl8pCRHInMGkfq66EbbqcXrxbCxr9C9v4CCgugBlXdBDIx82ZTc/kwxxHue1QxWlVNW8ra5GY2EF8hko12539bPV9qLPcVv/1BusbDds7hYcwXxKV6rnzffF5wQK0h2dg/Xl8fujwZgheF8LQJNCB8QA2zo+A+gqvmFLK9IdWyVxu5b21/aFMGZ53S5AdUG4LntKfzK8juIGZhIROq/JdGBsQpMgWNZSFQ8qy5AsJ+t9lnaUFTDDI5eBAgB6n0pdrmlDoAQXGCEkbNvj3p5QcWt5cweL49IaCOWMG0I4zEVligCwMUBbJmirLVGsA1lMgmdegV3sVcE756rk7eRm9lPTFjUIspvcDI38pDasBewAACAASURBVGCVpmkDEuoLByUq5YoN2GfIKPoQlBnZV9Wqwp70HpSB7sBwmsZtWZ6hI4SGwekmRkCGHzM6Y/2ZmVF28HNG0BmLmS216eEU5ZyZgEAobfGHhkG5VBDPQsUlbyYqIp8Fd7C+ddon3TUKG7HcsFkMgSw8mDohabkllbClWCkKKYypYgvTZYfuoCI6pswdCZgJbiL4vl4LZDmP3NdBLVyjKFe5Tt6X6xxl5LVtNZNY0szpWrGvxWFMBHft8eRCmFuzkbIy4UO9sa+2Eip9cb3BMgY88YJ5uATtQ9SB0AP+RcDMhLNrIKgGxbOLE/zm/qu43ldm2u9fPMbV5UZyYjIQlaF5NQyYosf+2Ra/6x/L5Ykec7q7qNCbMVgwQI7WQQyTv1MaNfWtJ1uNDlDOAnISVbq3CaM0r8fF+AaC1It3qFsyXKg3Dy1ZnuTJ9BmUZxEznK9Prpb2bMUvxrOoTx0X5eZikv/9Um9KN8vswgYd+X6GiyI6U9zBUhJOSONrWngNsXIYAJmxcCT1CV3vW3gcNtU1fkfr21mk4mXaXzxBF72hlmbfLIOAn3PpC7fooJ7VP3Sp3wcAF3idhm3nHesMwN7L9dFtswwULqFOJwC40cHP4mrGOoC4CIAlvT5y04Yk9aSJmhR/WnmPrj1DZRC0bbWPGC/GAX5UkJkZTELhXg76m510KZqBWV3VrrTaZQzgTDjsZY11Osk1oFQHUDZOyOTk+uh1iGPAdw8PEKdQJtdXw4A8VoBzKjQahxQdaPIYD3KslBxyPnrofkZ5IwYLan1ArAwDEEUZCwDyiypZzJuu5GJwH0D6RKCH51LfvFR/DH09LnFruRISWameoLomfXCC+HCQXApbhZwO8Jdj8RqVCiSacTx9X3b69Et16WEaj4Cg6MvWnk6iDwkG4rmEM8aHvojTMPWIJ3KA7sWA5XTt72HpiZKsVduQ1Uckm0WAbiuvuUZUbJq/nKI8qW35kwZCHgA3WxSDEUbBQyxCQRquGx/5crNRrtjFfK7rHgDLmfIrPEoynbVbolJ16ZMGQhoFW7LIS9rJDEbo3vVBkM8ilqUDXBUcyonAPoNYku/msxoNmR4z4o4LZT0NqJ6jA4qloPQtELdcVLhtP/aE984uix4F+gy/jYizKxTufRjMmrVEPc42ExwxnvgTHPY9vvbOMwDAhw+38JOcvg387ARb4V1a+dluz0f8gbMP8c2zLyNrX797fonvzL4c71SjIafDjKupx7Mx4PREpmhL8uq/crfyeUlZ9+W+3Jf/n5U3YmZxa0lppWzFjeeHuzwUnUe6HoFphiMCm8I2M/DiCjjoItdem/o2Kj5IYwQcsFVquJnQ0JLgDxFOM08BwF/PcM+u0C9JOBgA3MUVNlleARQ90PNvz5KN2uhEDp3D5qlQf7uriOG5qnsfEih1SouWY+0+ighjgpsy/JhWHiPbJwvcmEQHEyhU8/55wNAoPXfPDuDOi8/ItTwK/aWyZT0BidE/1/R71f589NtJDIMBGKlqZWgEYPsJIUyismUp35QFZ/BjLudryxA3Z5xxxUv6Kz3vMeP/be9KeiQ5rvMXSy619jJNDskRh9ZCSyTgmwHpIkMHy/oZ/gM6+k/45ItPBnzTzUcDhmAYkACfBOlg2SZkLpYlkDPicKb3qsotFh/eiyWrm8NukhJbUj2gUdVZWZEvIysjI9773vcVl8w9yjO1wOAVmcCnGmpjoJ9d4uAdhimXInJw0nvyq/+gpJhQFoAmRi1aathSRO0RaYmFy9QCsyfU54sPiFYx6JGEiljyS8BUEuWKfneBfnHyeI1f//tDHP7G834atipRXnh07+8DIAh38MVM6ByeVeCyflp6fLhP2xe/8pCWMkBBH8RpgfkHgKk1Zh8aFOxD+5MlfvD+tzF5IkPyB4+rBeo1zUaEA7qS4iatoljH4cpjmN+jPnAAVr9vMYuPs4/LiFxXur4NUYuIR5/tmu0T1/sOHpKyH+4aTc3tdr0HjI3pWHhPcZMtRGnQGB21x7EDL+j4wiTfY9wjxmJ8zM5QdD8/Z4wV2kPgdkjrbwDxc2FtHITCwEdEFQ4IAUoXgqVbSEspIL2Hd3lcQXD8xUOGQCLHbkJZO8B+M3ozxm+Q1Yh0LtZlxG72NMiEOJHvaR9hEwVgKL8mtGbKJKmOYhzOpfiXsCnuEbIf4dyk8TFQClA8Q0nWh7UpvhH80kg+qMjx6Ub1NHS9OfbRpnZjpi3+bhAzMbJPKmMU4PRUrxRiP9bH6mWiQkx1PKoRFOMI5+URlzGhjwAafFRD34kEQC71x03sbg8WH0f9n8sCjDRNZfr8hha0S8P3RviJgA6VIRNx83ZTe1uYjNBEJmkXCHgEfCxRD9qewmPEz4CMBfu3YV4i+SiT/15l5yEZC2HyPvGR/SvGQTxdF8fnEM9N4Qou5aa+xVeHmMaODwQZrlvCswhBQU6nQgwnb08wOxb5orLs1K38EmPfnMa4dkgKJNFq3qYAoiTg7EcYsxUgmEMkzI5sIXCdSlmULlDj44d40Eie8HMIONyJwcJ7jyv1HJzxiDT8uTlHVP8AhLKkaWoTsW747HkmXHrqwnsILamClH/8oushN4po8cOS5xY/8IjPYGVwgH7fImRbhiRAJHsLYRQ97VhKT9WaSG+kgOxtTN+KboCsbj51vK3lWRY4T8sVDwAiVs86hSgxGAl/Pc2UaLYQZhAhi0TT+pDi9ZLvlNv6FiZFJjw1fXyCAvyUtrx28uk74WntJeLSQg4+BoljOvlTmrQpe+MEZ4ls8lcwjka4tM2FbI4Lsx/arlsfOThSVfJzjhuqb8MlE5xJ8antz8t2Ac6d7WxnN7I7MbO41qQYob1Hli05vBRJrewTeDevtAGACsb4uwoZAEvCFxJ+kEll7DbLEJ6+C2RtZuS4XmWiOkqm6XxchoDIVb0fpX+9Urfz45bmRVoeRcUwRotGKDlPk6VJXJekyM5T+5BW5oe8EP4q5PxTnMJoGeLJV+Lr9HF7WAbE5QY/6bG9RAr7ayQQmb39bAcIcPR0vLAsCNsishT5Eo8n0wqjeJDTAtJ62EKMpBjUNSwOYbnhs4lajtgV7E/c/hntbgwW3pPGB9d2eOfhOYPhLkiURe3vwVtHUoTewzeczVCSvltXcE+exibFK/ch1gp+PoW45Hz/pKaptXewrMSlOtLmMHsTyMGmeMDxKTQva/yKYHtyPoO7t4RZVDFrUmqJ7sUZKh5QJNeR9MsCxaUZBRxtpdAe0HGnvYOZsW7IicXAOIrZf1O+XU1fQPHRCnZvAnXewO5RtFw9O4evDrF+OEs6HKxNYicS7X5aokyeabiSFKq6fTpufVzSja8oSBl8mBoHOIfNCyplDELVaSmingcAtAcC9SkwTGXMCgA0xS/PLIrTjDWGbVjMIBmtGZDY518tUV4wzV9BN78taUoepuD9TKBclZgViTLQsG6IGjxjDqjB9gWgPBuPQsIB7aFAde4xTAVmj1NWrTlUo3jA6ddKmBkFHO0EKAJyypN/tiY1cyBpnbpiic2fDIBI5+FKDzMVaF5kZG2TYlVmzkjfwgPSQ11oEjViTdL5BwEZmwYu1QEnbyqYqUf3qIRe07FWrzlUX75EI5ZxX7NvoM8ycSTWDfGlh5wNwNMK7iAs1yXsv9x8gLwbg8V1ds3sIEoD5CCu8D4EOoMFuYB8e5bZCAK5MgoZy9FrkQstB61UKYnNOy9RlwzQ2nram5rEg/MnqC1lLGRy2fsiex/kE20hoZWCKxQkv4bPXaFIqFinx5QX1L7NtDfDk9RlBXKJnZqihPmTFiDgWBArDrEHGixSUNLMBExD4C2TlcRTib8aERpf6Q9kJeqTxDw1AmWJ8BxmUFYPQCYRZjMFBVf7MQhtWGTMX2zE7E1oTTNFum4gElwzTWpotqY/r+g7OYLTMhN4YDozEyBIHJT7HYZjzf1Kg4WwgFvSwDQoHYPkWHBMqrRQyqH3Aq6T8FPLfaOvDf6aqYdZWNhax1mGXVq8enCGt5ezuF+536HPUJliwgTSlUFVD1g1OpbOG6Oi+PVN7E4NFqLkKz+YESYCAN2wzkDuLQk3MfDo2Ch636jxd5wDl/qlQWIxo6CjsdCnNDORa3otj0kTVIWbsh8A2ab3ACBbiHkNtR4iDgDGoViZqA/qp3T3TD/qab9Mt1K2RSTMLU9aKOZe0OcdZuFHzNqr5WkLuW6gJeJr+FyfN6hmGroJj/6UkhSZcIjeWIKVNxYVD2bFauACLsoihGCmmxQQg8XisYks3CG16woBV8rI2l00GuW54Rsx3XyqcyhOW8j2alB68rSAXrGyW890c0pEPdGoos7T8JRelZF9e/6IKeyroEiWqkABoFgLlJfjYKVwlE0oVw5mIlCdpPn8vJKwpUD9jPyaLBXMigYJWyPyRgifljblBbU/TGl5Jhwg35pjFnAWmtCmxdozuS6nUMPMgomXQ/XoYs0zGe7H2Yfj2Wiw7lEJW2sUFz4OFvN3Crx3+SqWH6Rr0C/mWCawM2zFg5iu0Ox5TE8FhuNl7Bu0N1+f3KnBIje/jW/I0qXe2JguC++9GUsHSOdjzUgiylFx7RgzJ5zpkN0ADAYi1B5bS23z+3gsKSmTMXaW/Mn0Q9R6ICnCrHhNeR/PIcgUApThCECbUDErG/an6dMrfy6aHqq1I5xG4GxUGZAoUvApkej5jaP0qwNjSxgMVSpIIVBc2CSTEPpYyQiWCteiWBnAe8g+DU6yt5BtT4LQW6ZDfwDQoQir0Wm6zWlEaX1MNQKA7qhux2nSbAUA28mIk8gHC4gkZpyuDbWrNw6ql6N+Ly8K2FJCbtivtgLAoKxSpKwOs1epLgGlAJpxuUJg8jRJChKALdD182+hT8xgYQAKcQ3d0KAXINzF6vrBQq8LwpF0CSdRH1M8qzrJfvddkisAkMr6NQ2AxSUSqY+/XbZklw3Z2c52diO7GzMLAUAquM0mblIHB4B3EVYdAp72/AnUG69DXNK+fjGFOF/BL2dQQWUsZBDWG6AsYtm4f0zUoR5A980/BQCU5z28ANoXJ1C9i9PBedvDHsyowvSSVdSXU8B7mP0atma9jc6MdUOekGrCs+9+BdWFpScnD+TDTEXdkNmTMmqL1CdTXL5KOiD3V6Qudfm1JSYfzTAsNcqzAf2S2p88KtF8aYFuT6E6SwFOABgWGs1hGv/njwXphjiP5oWxAG6YKQwL+gksf0598/gvXonT51xF3VYiohS7e0B1UpDuyCxfBnjMnlRQbYZCBQDncflqiYqn8N0e+dgvBerjEBehXW0toNqkG9IvSdBo770NHn2H1uZ24iEMCxhn5DftywblsRpxfQiGTpfnGmbucbC3x74BF69JmJnH/ts0Ld/cFxzgpNJ1vU7n5grAzD3KU467cJjghf+wqP76GL955wUAgK8cUFmokwLyAQXGh3VJMQsvUC9oDTGtO2jpcXo+g2k1JhxHaH+yJN0QiRGt3uo1B7u0mL9TxD47+26D773+C/zwnTejn0cHl3h6vEBg9w7KZ5Oqx9RJnL0yx/49itwOVgH/dPOpxd0YLK4zrQFnAdDJCpWmu25aQvLywc4r6LaHm5ZQK7ohhPdwkxKyKeIrgFH+qeOshOC0VXuooDpJa1EAs7qEWVQMmKIfuZmXEM6j39exJqK4KNHtKxQXfIMVdKzmBQGnFdSQakP6uUBLvykIo9AdBGSnwvoVmh7aOdVwtIcSqi/oxnJAd8DZl/MK7SFnBkImllWu+oVEcz+7eRsFUws4rdEchaBlCMQRN2e/oO2LmvzfvOJQnjEAjHknbEU3aBgs+hcNzERDdQL9Xij1B4qVhOpUkh3gwUY4j+bFlFJt73F/7KW+CWJBZuah1yJequ6QmKxmTwo0D/iHvRjgBwn0Epgk+ONXHn6EXy/uQUoHydyS1igI6bA5raH2emyOqXRVWKB5YCEPejQnlGlqXnaw+waiVfC1hcqyCq72EHs9bE2O2n2uz/hVgb/56r/hb833AADLusP96SXe+ugl/NXD/wEA/N/6HrR0ME7izeWHAICH1TEUHP5r8yU8bvbwxoK2/+D9b0MxJ0ccLBRQffkSrx6c4b3LV2Mq/nuv/wJ//+An+D4Axz+Gby3ew48O34CEh4PAwwk9vB6Up9i4Ej/e/zq+c/Q2AODcTPGPVUba8Ql2dwcLt1VIlr2XzRBL1OWG1vaj+IBzEJsOfhjiK4DIjQEA1WmQCaSAX32iKBgYoumDgWoNRGdjXEO1FMisCgnNKEq16lCfFFAr+nUHxOn0I4diHbRIqEnVS0jOG9ZnLmYdqguH6YeM4ORMQnVG8ocAUGxMXDDKzqC8dJADUJ2PZxaqzzjXANQnFrYSKFYpJVyf0LmEmYXimINo+In3SCaJPia/IYq/VEOhugLFBa3F9SZhKvSGzmW7BgQemDzN2uXNxUqgPuGbOlDu1eCZBe2kG4HywqG46DF5REVRdiIhLPnjKhUHi192L6E4pZmFyclvPDBZCZhzheosDWTmkcKwqlGdBr8khtOSZiyFQpHdR7YEzKxGdUrHGrhgb3Js8Hf/+5c4/SVRKZyUDr+eHEEeF/jn9s9o301BA7sVeGv5MgBEKrz1poLpNN5avETtPSHOCq9SNsYroBFLvL2cYflBilH88J038X0A//reNyJb1k+XD3F8MifafydGM4tu0NgcT/HuM5q9GqPwrP0Zbmp3d7B4nl1X3PVpLUCauZ2RxsUnFZV9goW2cgr9CFTyGUx5W4IAGFHwX2n3s6GTP9n8+H1OrRd92PLvKoVg1k62z5X2P4OP4pp2w/tw8wSvr/TnNd/51K74pLfqt7Zvb/Rb/oVtgY9C+TTbveLrNebAAtdXnLrq42e1XYBzZzvb2Y3s92dmkbN7a5mwThKg6k4Zi8PgPVBoCCnh+RVATGsCgONAZqiEJGBOYiFKx0V6HAgBX2qYWkUG67LUMBOJklm5ZdTfELTsyJiIbClgAlNWkQBNxVrATsD43QSEAgBXEnN4BE85Ss8NUxGXTCGcYyYysj6F/23FAsgciynZb1tKKJV4GQKDuZkhKpoHrkxb0vIgxCyGGelneJnplHiKuTjmzKT+IiCXcJ5YqAIAi0FQw5wVxpGAWnbCVZu877AQVDVaEYKRfGTqvT7EOhiTsd9jGGoE5S6AmLKgPYSTMNMUI3GagE52ktKv/YLEj1VP55xX97rKY1g4CKPYL/ZlKvG1/Wd4woFTVVnU9YB1L/HgkNDHp9UkMle9uKTg4kG1QakscWZWFe4zOOJxteBKYyBmOCUhM8v9Dv1iDsnAsKODS3xr8R5+unwY/Xz94ClsBso6mDbxeMYpvIsjvH70DADQmAIf6bQ0/yS7u4NFJoFH/2f4gcFGdm/BMGUxmHijee+BwVAWJLxutREqDWVvASGgWwfZMVgfjEGIDN8uHdd76NamKXBvoBuXQFl8DL3xtN2kH65WFAQEAN26GPDTrYvbQzBVt6xR2jp+5eWJJcLgYiOyCkr+jhYj5W/dOCLLbR0KFr0M5018DQ464xwFCOIcYgshQEk6pQkW7UqBYhX4M8fZENUlzgfKhtB11JuEUSjWnsu6BfQmi4/wMXM9T6epL2VnUV6GQSyAsmjACNeinVQoz1maIdRlWAZ/XQrAJR9CQFb4RBpcXgoIx1wUBcYxi05AWImSAU8Bq6A3Fr84fhHylOHepca61tBnmtTMgZH26KOebrlA17+6rOFajfc5dlSvMz6KjHVcn2n0TmB5ma7P0+MFfnT4Bo5P5slPJ3B6PI+D04rJfJ/WM1grKWaBFLPozM2HgLs7WAD4WD6L/LPIZZHAV3xdbmY5x0RW4ORDexnHRbwCNzTPmLBt/gkvEJ+64ViB2SjMfqhISCDqbMbFt8jvz9+OhT6IfoY/Ebd71u2INyU/DaP8AMDxGRELmkaFYJ/CtjVIo3+Z35FbIvchP5d4LXz06bPyg0hu+6pvPtvGcZ+Mph8AVS2IpDma81HEOMjH9ZcAJHxUO4ub+XgCIlem+Mx2tweL52mHZBqnEUGZzyxuap46NbYZrm9ozye2q1u1C2R6oOF7PJjxAzcFQHMGJxf3EdbHANxIg+PzCBA+z7LAoUc6fvTXM62dHwdbt/VP6Tx97Nd0jlfipTeyUYDU5/2Ytgceh9hFPFmM+0YmsuTr9vW5rYUJ1LZv4wBnPgIDzgtIQQxk8CKtdJkZDcx18VyvPAc4txi6vQexj6Rb4nP5ydztwSIf8bN4AxWIhaeypBL1AO0GqId4e/wcWzGLoIAlaVbitABcpvwVZhYyKyWXkjAcSiaYseT33HY4FimJCQp5ZOXHeUFXZNwuaDs9nWX8nLgkRWTN4gNwgVhWMs6PUarhSN3ktMgUzXhbkdoHsvMNBWwV4po4qI/bMhRscVyhJu5LLxM+IiiSkb/p5mOyrJG/qWgM8fjB78ivGdi9SzpXr2QG3GIJAyHgqjR4+prYr2lmEZY3Al6Tv65KPgjHlaRl8sFWXP0piDVcmixmUfDnVfIh9PnhtMEJV3eidFC1hZ2oqDO68WlSmmuPKulgrEQnEwt3V85jNiQuQwRVj4qJha107KtqMuDh5CSmRwGKUaw2iU08Z/e2XqBtSuzPKI7RGx1FiG5iu2zIzna2sxvZ3Z5ZfIx5IdLUjLMhV0raw7brPgOSxqciJKRXApAZmUuIV2wdy4M0UdP30wwgfg9cfajClDvsS9uTtir7Iul9PlUM63+atWDkF7WTfT+Ssm6Ru2jaFjgzY7v8mXdI2iOZ37FdjxGnZSR/LbhtJL+8T+cs87gAn1/4DNl3aLbB72PpPOBM0joN+xCpTviehxQCzpMm6UjrtNQci0gxAV94eE1apSn+lMrJo5ZKIM3xfuQbANjSw1V+5Gc4l3v1Gu8VHGyuLIrSoC2KqGs6DEnHI9ce1cKSKJCTmPO+reJ+yh7jXgK+9CgqA6er6Nek6vGgPMWk6kdap0/rWYzbhXb36wbGSZxUM+xVlGpqVHGrmcXdGCw8AGfH5DdM/e+Y5EYdHQHOQk4mxJvJZeNisIAxgHNwqyx8/fIR4KZw8wqK95VlQfycUiaUYWS9Jg7JGMlfbSKRjeAydllo9C8tYKtE+mLnJbqlRHVSUObggMt/Q7R+SAtaW6nE2DxQfQNApd0hJSdXdCzdzKAve0pxrgeoOvjSQjVT2PsKw5Qh3CX9wMwk8E7QMbqFIg4HrWINh2ExJacAWaTajuH+kuMk48wEQNT6kesRYAW1dI7BgjxjeXm16lT1OmYiDC9zXIUkulSD2cES/wT5S5mH5n6ZWMc5GyKMgMz4GKwVcekQhnhhAauor4UByqwiU3U08AdpRzMHzMJCthLuYIDXXD5gBWzt4EsPy5wadurgC4/LBxqtKSKjj7cC1hBE34aKXispCAnA8sXpjIbUHp1RsEZi1ZV83YmFe9vkbEBVD2j2fExXT53ExpXohnQbG6dgbRppwvGMk/jm4a9w0kzxYHoOAGhsgf+8BcLvbgwW15nbOgmTcVzk6dAsRTpKr3YDRNtDFjrxUWS6p7rlQYJTnrpxUF1KifqMFDgey1jo1UDl4IE6fz2gOi8gWx68mMuh4NRpXm6cpzZ141Bw/EK1DsUqrLFt3CZ60g4Jr+Fz3VoUKx25G0J6VhqZKPwAVBcWupMo1jZGyYq1i5kW4r9g3y47wHsUq2mWOk1pzZDSBKjYq1j5FIwL57cBdGNJxW3LirWPqd5w3uU5MVgBgG3BRWuUog21IcNcoLj0KM8MykseUHmwUD2lNIOZkxLl+XgWKRxge0p5CicihB4AikuCjQe/qhMJ2SvIXsC0JaVbQefoCgUz8ZGJSxgFLz0mzxzefXYU2alcqWBKj+Jc4njKKmVrHWc6Hw50Drqw0NpiczqB6BROWdbwcOVjP4/saUXENacCBadvz16Z48f7X4/1LgDwLo5G/wepwpNqhpNmiidP9tAHrIhVNNDd0O7uYCG3wilSpEdmDrTKwFcj4FahiHJPZxyazsUlheEntWIwlZkw21QQzZEyApXisbSCKyRsLWMhmSsVzETAF4p0HfhmDaCprP5tBJoyEzkCSoXt4Zi2lhEApviVTl3B1ApmKqCGMaOVqbdAWReSKehkfIKXKwZ5abrphgjKoqfhMEcEZQXGaVOLCJYCgH5JoCxh6Wkc+1yQLKQ0V59WwyyByOJsZo4oiWgrIBStyV7EYwU5RVdK9HzvmSkJ8diOA5zh+Ic9epNEggGeWUxp5jYsPMw0/UaGBQG8AgNXv/AYljRQ2SlJHlLDHIydOki+2YelI7BULfD60TP8/BkXqNUWurQYRIWjI7qrz6tJnFkc7REoa170mOgBv1SHaJsySQrO78XlWm7uoMd02WI4XkaMx/69Fb5z9Has9QCA14+eRRwFgBjM3KtaPJieozcK37j3EQCgtRqPbgHK2gU4d7aznd3I7u7M4nm2pfJ1ZRuAbVXzbRvhFpDy26Ml3JU2U9L6uuKlvAgt5u9zsIzLsQaZGtT2cRFwAD5iFfLpfsASbCfRhfcJI4wcH4HxsUCpSZFhSEbfiX3K22z6AwBpOWbgfJyFpHPy1/Y99W+GceD2I+7Bi4RRcGN/cz9iW1s+AYA38grzk3BZjMNidL7CBR/C/yJdl/AX+sQCsPm+6bPGFLHfvZEUI7ECHU/3rZXx3HtGTHYcWDSGYgyD5SWWw5VrQjtK4sxkfAhAy4hzM4UxaSrSmGL0fzheowo0tqClh6VtrS1uVWD2+zNYPA+gdY0J71moCNlN5SlmcdO2tpF9IVaRgXDohqMAqRfZsQSwjabx+bbtz7f3vcGcLw5SjmIWVypD+YefD1rxJlRIYjQAwcyDYlbuI7/m2+N7sXXIa875Ey1cCkffFXGwSIMIDUo+tS2TD6PjZzUhaRv/Ped6hDbioOppKSbygRdbGz6wYgAAANlJREFUbfO+0oAyCllfCVZxVxGl6SNiM2QflHRQ0kFKP/rcP6cPhfAEITLBf49aDqP6o9Bm/h0AKKVFf9365hbXS9wWlfjbMCHEUwBrAM++aF9+x3aE3Tn/MdhdPufXvPcv3GTHOzFYAIAQ4mfe+z//ov34XdrunP847A/lnHcBzp3tbGc3st1gsbOd7exGdpcGi3/4oh34Amx3zn8c9gdxzncmZrGzne3sbttdmlnsbGc7u8O2Gyx2trOd3ch2g8XOdrazG9lusNjZznZ2I9sNFjvb2c5uZP8PRwrkfvjPVvsAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1588>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 51.048593521118164 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 1e-09} is: \n",
-      "[[6.50000002e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 7.20000003e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.50000002e+01 ... 8.10000002e+01\n",
-      "  8.10000002e+01 8.10000002e+01]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 8.10000002e+01 ... 4.64900004e+03\n",
-      "  4.54500004e+03 4.54900004e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.10000002e+01 ... 4.54500004e+03\n",
-      "  4.44700004e+03 4.44100005e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.10000002e+01 ... 4.54900004e+03\n",
-      "  4.44100005e+03 4.47100008e+03]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1c50>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.604299545288086 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 1e-08} is: \n",
-      "[[6.50000022e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 7.20000031e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.50000022e+01 ... 8.10000022e+01\n",
-      "  8.10000022e+01 8.10000022e+01]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 8.10000022e+01 ... 4.64900039e+03\n",
-      "  4.54500039e+03 4.54900042e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.10000022e+01 ... 4.54500039e+03\n",
-      "  4.44700040e+03 4.44100045e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.10000022e+01 ... 4.54900042e+03\n",
-      "  4.44100045e+03 4.47100076e+03]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb5d7e25c0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.84423804283142 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 1e-07} is: \n",
-      "[[6.50000224e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 7.20000312e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.50000224e+01 ... 8.10000224e+01\n",
-      "  8.10000224e+01 8.10000224e+01]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 8.10000224e+01 ... 4.64900392e+03\n",
-      "  4.54500389e+03 4.54900422e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.10000224e+01 ... 4.54500389e+03\n",
-      "  4.44700403e+03 4.44100454e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.10000224e+01 ... 4.54900422e+03\n",
-      "  4.44100454e+03 4.47100759e+03]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.50824785232544 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 1e-06} is: \n",
-      "[[6.50002240e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 7.20003120e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.50002240e+01 ... 8.10002240e+01\n",
-      "  8.10002240e+01 8.10002240e+01]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 8.10002240e+01 ... 4.64903916e+03\n",
-      "  4.54503895e+03 4.54904218e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.10002240e+01 ... 4.54503895e+03\n",
-      "  4.44704026e+03 4.44104542e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.10002240e+01 ... 4.54904218e+03\n",
-      "  4.44104542e+03 4.47107588e+03]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f8358>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.558002948760986 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 1e-05} is: \n",
-      "[[6.50022400e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 7.20031201e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.50022400e+01 ... 8.10022400e+01\n",
-      "  8.10022400e+01 8.10022400e+01]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 8.10022400e+01 ... 4.64939159e+03\n",
-      "  4.54538951e+03 4.54942183e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.10022400e+01 ... 4.54538951e+03\n",
-      "  4.44740265e+03 4.44145419e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.10022400e+01 ... 4.54942183e+03\n",
-      "  4.44145419e+03 4.47175889e+03]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.628111362457275 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 0.0001} is: \n",
-      "[[6.50224019e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 7.20312061e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.50224019e+01 ... 8.10224019e+01\n",
-      "  8.10224019e+01 8.10224019e+01]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 8.10224019e+01 ... 4.65291887e+03\n",
-      "  4.54889780e+03 4.55321930e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.10224019e+01 ... 4.54889780e+03\n",
-      "  4.45102939e+03 4.44554332e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.10224019e+01 ... 4.55321930e+03\n",
-      "  4.44554332e+03 4.47859354e+03]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb5d7e25c0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.301332235336304 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 0.001} is: \n",
-      "[[6.52241921e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 7.23126085e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.52241921e+01 ... 8.12241921e+01\n",
-      "  8.12241921e+01 8.12241921e+01]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 8.12241921e+01 ... 4.68848458e+03\n",
-      "  4.58424911e+03 4.59129182e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.12241921e+01 ... 4.58424911e+03\n",
-      "  4.48758275e+03 4.48657940e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.12241921e+01 ... 4.59129182e+03\n",
-      "  4.48657940e+03 4.54739909e+03]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461aeb8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 51.817808389663696 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 0.01} is: \n",
-      "[[6.72592640e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 7.51812813e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.72592640e+01 ... 8.32592640e+01\n",
-      "  8.32592640e+01 8.32592640e+01]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 8.32592640e+01 ... 5.07487390e+03\n",
-      "  4.96576790e+03 4.98191149e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.32592640e+01 ... 4.96576790e+03\n",
-      "  4.88307472e+03 4.91167067e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 8.32592640e+01 ... 4.98191149e+03\n",
-      "  4.91167067e+03 5.28282860e+03]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a630>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 51.42012095451355 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 0.1} is: \n",
-      "[[8.93840000e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 1.09772800e+02 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 8.93840000e+01 ... 1.05384000e+02\n",
-      "  1.05384000e+02 1.05384000e+02]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 1.05384000e+02 ... 1.39665408e+04\n",
-      "  1.31096732e+04 9.99189165e+03]\n",
-      " [2.00000000e+01 2.00000000e+01 1.05384000e+02 ... 1.31096732e+04\n",
-      "  1.36994003e+04 1.09159036e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.05384000e+02 ... 9.99189165e+03\n",
-      "  1.09159036e+04 1.90906862e+04]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1fd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.30138349533081 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 1.0} is: \n",
-      "[[5.4500000e+02 4.2000000e+01 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [4.2000000e+01 1.6000000e+03 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [4.0000000e+00 4.0000000e+00 5.4500000e+02 ... 5.6100000e+02\n",
-      "  5.6100000e+02 5.6100000e+02]\n",
-      " ...\n",
-      " [2.0000000e+01 2.0000000e+01 5.6100000e+02 ... 5.5201405e+07\n",
-      "  2.7070565e+07 3.7657900e+05]\n",
-      " [2.0000000e+01 2.0000000e+01 5.6100000e+02 ... 2.7070565e+07\n",
-      "  5.6227287e+07 8.7973800e+05]\n",
-      " [2.0000000e+01 2.0000000e+01 5.6100000e+02 ... 3.7657900e+05\n",
-      "  8.7973800e+05 8.0506750e+06]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256f2198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.570582151412964 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 10.0} is: \n",
-      "[[8.55050000e+04 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 1.82399200e+06 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 8.55050000e+04 ... 8.55210000e+04\n",
-      "  8.55210000e+04 8.55210000e+04]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 8.55210000e+04 ... 1.45800903e+16\n",
-      "  1.04720467e+15 7.94346077e+09]\n",
-      " [2.00000000e+01 2.00000000e+01 8.55210000e+04 ... 1.04720467e+15\n",
-      "  1.46179765e+16 1.05982134e+11]\n",
-      " [2.00000000e+01 2.00000000e+01 8.55210000e+04 ... 7.94346077e+09\n",
-      "  1.05982134e+11 2.70394568e+12]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe26a0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.20673108100891 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 100.0} is: \n",
-      "[[6.59424650e+07 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 1.32861113e+10 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.59424650e+07 ... 6.59424810e+07\n",
-      "  6.59424810e+07 6.59424810e+07]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 6.59424810e+07 ... 9.76031932e+25\n",
-      "  7.28718337e+23 4.86537429e+15]\n",
-      " [2.00000000e+01 2.00000000e+01 6.59424810e+07 ... 7.28718337e+23\n",
-      "  9.76064507e+25 6.46947761e+17]\n",
-      " [2.00000000e+01 2.00000000e+01 6.59424810e+07 ... 4.86537429e+15\n",
-      "  6.46947761e+17 1.63044342e+19]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1c50>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.444000005722046 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 1000.0} is: \n",
-      "[[6.41922241e+10 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 1.28480608e+14 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.41922241e+10 ... 6.41922241e+10\n",
-      "  6.41922241e+10 6.41922241e+10]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 6.41922241e+10 ... 9.37328139e+35\n",
-      "  7.02676137e+32 4.63309425e+21]\n",
-      " [2.00000000e+01 2.00000000e+01 6.41922241e+10 ... 7.02676137e+32\n",
-      "  9.37328460e+35 6.17559179e+24]\n",
-      " [2.00000000e+01 2.00000000e+01 6.41922241e+10 ... 4.63309425e+21\n",
-      "  6.17559179e+24 1.54524551e+26]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.26343107223511 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 10000.0} is: \n",
-      "[[6.40192022e+13 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 1.28048006e+18 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.40192022e+13 ... 6.40192022e+13\n",
-      "  6.40192022e+13 6.40192022e+13]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 6.40192022e+13 ... 9.33539995e+45\n",
-      "  7.00123103e+41 4.61050310e+27]\n",
-      " [2.00000000e+01 2.00000000e+01 6.40192022e+13 ... 7.00123103e+41\n",
-      "  9.33539998e+45 6.14714984e+31]\n",
-      " [2.00000000e+01 2.00000000e+01 6.40192022e+13 ... 4.61050310e+27\n",
-      "  6.14714984e+31 1.53692259e+33]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468cfd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 51.19285559654236 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 100000.0} is: \n",
-      "[[6.40019200e+16 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 1.28004800e+22 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.40019200e+16 ... 6.40019200e+16\n",
-      "  6.40019200e+16 6.40019200e+16]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 6.40019200e+16 ... 9.33161991e+55\n",
-      "  6.99868305e+50 4.60825025e+33]\n",
-      " [2.00000000e+01 2.00000000e+01 6.40019200e+16 ... 6.99868305e+50\n",
-      "  9.33161991e+55 6.14431489e+38]\n",
-      " [2.00000000e+01 2.00000000e+01 6.40019200e+16 ... 4.60825025e+33\n",
-      "  6.14431489e+38 1.53609224e+40]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24637da0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.172040700912476 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 1000000.0} is: \n",
-      "[[6.40001920e+19 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 1.28000480e+26 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.40001920e+19 ... 6.40001920e+19\n",
-      "  6.40001920e+19 6.40001920e+19]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 6.40001920e+19 ... 9.33124199e+65\n",
-      "  6.99842830e+59 4.60802502e+39]\n",
-      " [2.00000000e+01 2.00000000e+01 6.40001920e+19 ... 6.99842830e+59\n",
-      "  9.33124199e+65 6.14403149e+45]\n",
-      " [2.00000000e+01 2.00000000e+01 6.40001920e+19 ... 4.60802502e+39\n",
-      "  6.14403149e+45 1.53600922e+47]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f8208>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.8695502281189 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 10000000.0} is: \n",
-      "[[6.40000192e+22 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 1.28000048e+30 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.40000192e+22 ... 6.40000192e+22\n",
-      "  6.40000192e+22 6.40000192e+22]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 6.40000192e+22 ... 9.33120420e+75\n",
-      "  6.99840283e+68 4.60800250e+45]\n",
-      " [2.00000000e+01 2.00000000e+01 6.40000192e+22 ... 6.99840283e+68\n",
-      "  9.33120420e+75 6.14400315e+52]\n",
-      " [2.00000000e+01 2.00000000e+01 6.40000192e+22 ... 4.60800250e+45\n",
-      "  6.14400315e+52 1.53600092e+54]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.321784019470215 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 100000000.0} is: \n",
-      "[[6.40000019e+25 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 1.28000005e+34 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.40000019e+25 ... 6.40000019e+25\n",
-      "  6.40000019e+25 6.40000019e+25]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 6.40000019e+25 ... 9.33120042e+85\n",
-      "  6.99840028e+77 4.60800025e+51]\n",
-      " [2.00000000e+01 2.00000000e+01 6.40000019e+25 ... 6.99840028e+77\n",
-      "  9.33120042e+85 6.14400031e+59]\n",
-      " [2.00000000e+01 2.00000000e+01 6.40000019e+25 ... 4.60800025e+51\n",
-      "  6.14400031e+59 1.53600009e+61]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 51.805800676345825 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 1000000000.0} is: \n",
-      "[[6.40000002e+28 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.20000000e+01 1.28000000e+38 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 6.40000002e+28 ... 6.40000002e+28\n",
-      "  6.40000002e+28 6.40000002e+28]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 6.40000002e+28 ... 9.33120004e+95\n",
-      "  6.99840003e+86 4.60800003e+57]\n",
-      " [2.00000000e+01 2.00000000e+01 6.40000002e+28 ... 6.99840003e+86\n",
-      "  9.33120004e+95 6.14400003e+66]\n",
-      " [2.00000000e+01 2.00000000e+01 6.40000002e+28 ... 4.60800003e+57\n",
-      "  6.14400003e+66 1.53600001e+68]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 52.11367106437683 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 4.0, 'lmda': 10000000000.0} is: \n",
-      "[[6.4000e+031 4.2000e+001 4.0000e+000 ... 2.0000e+001 2.0000e+001\n",
-      "  2.0000e+001]\n",
-      " [4.2000e+001 1.2800e+042 4.0000e+000 ... 2.0000e+001 2.0000e+001\n",
-      "  2.0000e+001]\n",
-      " [4.0000e+000 4.0000e+000 6.4000e+031 ... 6.4000e+031 6.4000e+031\n",
-      "  6.4000e+031]\n",
-      " ...\n",
-      " [2.0000e+001 2.0000e+001 6.4000e+031 ... 9.3312e+105 6.9984e+095\n",
-      "  4.6080e+063]\n",
-      " [2.0000e+001 2.0000e+001 6.4000e+031 ... 6.9984e+095 9.3312e+105\n",
-      "  6.1440e+073]\n",
-      " [2.0000e+001 2.0000e+001 6.4000e+031 ... 4.6080e+063 6.1440e+073\n",
-      "  1.5360e+075]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2466cb70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 45.042237520217896 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 1e-10} is: \n",
-      "[[3.200e-29 1.600e-29 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.600e-29 3.200e-29 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 3.200e-29 ... 3.200e-29 3.200e-29 3.200e-29]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 3.200e-29 ... 3.232e-27 3.128e-27 3.200e-27]\n",
-      " [0.000e+00 0.000e+00 3.200e-29 ... 3.128e-27 3.030e-27 3.092e-27]\n",
-      " [0.000e+00 0.000e+00 3.200e-29 ... 3.200e-27 3.092e-27 3.184e-27]]\n"
-     ]
-    },
-    {
-     "data": {
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94ief7SWS+SbAbXeieZlnzYc0IyKky/W+03oWCn6VHB2cRznKUa4ld0OzwD5MmGOS1fJAEhLHOF0d1fbLajdfZ7Us9qCbZAByMS96Oa5hwpuKSVE+CJyxkGZ2IBJnF4xtPzGtBgN1vkXZy8BkY37oh8QA1BSM5phoQKRYhpTt7GGY7KpvDExSBynZK8xg8XOzNeM/CNlUOpDd+dao22QSutigUPmAZmGPld+kusPHavJyNicOgan0XNa0AKvhWc2ovC9vOupV7sZiwfl/xs5UPgpF7U1AWjEKjgI26oFiegAowC1rZ1LbVny/picP+l0zUdvi02dTkFe+lzs5ER+HLgTjCGqb6sAr2ax+37lqfArc99N8kMUChNoHt1oi9UMBhik4Le06uOUC/uH9+rIVJ60BfQEVXxBjdbapOaPwZbVpkziDabWsWBDrF7K5EouFLF56HBAwaYzg9bo8GytusQD3xvcDwH/w2PhQss2ukS577xjF32EjVvNIEwBatAWnMLl3IyYtLTzS8xf1/NVSHJx5Q/IfPJZx0vdDF3MFf+nCB0h0IoO8+OykmgzqxG7GYlJMgGImEsSOJEIRUznO680e3J0B+G9+JNcezTvlHXi5qP4SYOLE1XNKu77xIdyur34TAPj2Vx6UVQdsEvWYnJNBRrPJKv9Q1UL0pewxs+15z4HIMcoqPwwTjz/HVIAwum8U0NQskawgCGMCu/xQLR+CgqP6ofhCJglanKTtc5Sidn+2S5boQsyayTCIj0bbnkFV1ASAHXizPcjvYKMUpG3DNDKhvBGHnNIJmESVALGBJ4lZjsADpr4Bs2iwhgiv4mzouoNtl71INqOJ1jk7xrtdXYjaZrpoZkdtdXBmv0gIwLMXExi4AK0iSH0sdjwm5EZUo1qqde26gxBslyNBcL6Gpi93wDpM+zRPgDPoYTo7rUA06PO6fs7Nl3KxsBGOCZ7CslopQk5xGCozxiTMNYuiMQwHNQt4P8n840E0C52EqrG4xeKVmgVmmkVh1lJPd46wUN4pCux914HatuI4gLrIWRwHUBxoZDAdjDoxxRlYzydi4GQFukKzUPMCTQtSs8j+PsaKEpxJGQ8dRwB0spqQ/ZSFZx5GZxYn4Emo97xCs5ijGZH7qykB0EmHqlnoMVqtZPKnlBcL1dwqrJz0+tkxDmbw+SncTLOg8c00C7y4qONs+3B+JtdQKHju7000C4GGNxXyzww8+7JFQ1RekXU6wV0YG+1KzeJAhumhzMqbahbo+zrhgIrH4JyxqHF8nYy3pVkAr8ZxaLtnIVIwi18movhptA0CEBrfmWYxnxQWyzH9ccJ80b0NzSJdrjP8m2XSzc28uYbgSCbmNty+ZvH8xb4fgtONNAu32YoZZTeUeH1/zTEacpSjHOVacqc0i1elqCvuwj1+NE0J1lV4thpT21aTIq+8/oNH2Xk6ID59NjmfI/Kqba4zX+EVyGN2dIWAcyc7gmI9xk8+y7+xmkXVEDhx9TMcyNQsWoUqN7F+X5CTExMi9/VQ8henuqv3/dR5p2bThx+Adx3Ss33sg5xg8A9We7gm+c0EiauBqIUpAaEOWpv5qWPjHWi5FBwEcBgDAUxRrXtf5oiZ3XVnx5x3cm2PqaOYdOePtR/5GdDjh0jf+2Sa3Dj3bxh5U/IbnGQz6P49sDq7v/N7Nya/Kf1+A7lTi8UXKnYyGMDUxNP+ptedq/X2mleFub5omZkg5a7OTV+W2QvL1vQAKslLSnglh8YtyJTBi2tINI3757wLUiEbClazVI+zmpXGrI1xgpa8VTFtoQMpENe6xKgmD8q1bhJRvVuLhY07z+RVuItDUnZYC7XN8f63j6vPeBTm93gXYhcsK3YRySFezdlQsVpIuVw/vN0i+iYya6u2qfgNrLyDRXiilXlnqAVi+b6I8lYcot2/DdHxGIap1nMDIe/AQwLSm3kf7tRiMYlmNG1VSYHi1IsvXwpxjca72xap66a1RDJ0m/t+kithTY/w0dfkuoo7OFlNkmz44lLwBONocBqCp6Cz0wn5CZ2dFo96eiG4kPD7flAiGwachRDASzGPaLOrsOhdB753JhPiibSRzs8EoNU00g/FSazXAqk24d8C5AkBOFnV8Vxv5OUfx5KxqbkRGt0ozNbPngMA3Ld+pEZkTL4Bgi+RC142cLtB2mvZroYRtOv3TUPFIqjzV3MmiEBbxafkFzh42a1VrV80oG4Av3gJ9+M/Kr8PEoWgyOUzAMSzBfxmEAdu2T0BOIC6CHiCv1CiG0a6dwJuPMKTCznUBOmPbgbzqEIbQNs85hqd+vwZdj/7b6J9uqtj5QiuGzGey7vn+gQmsWbiQrNOqXznhoTxVK63+L1LOH1nVGshQjpZIC0DwpPLMmbxj/4EuocNFs+G7EEG4sLB72pCHDcyEMkTXGS4XURa+vJ8+R9fvxrg0cF5lKMc5VpypzSLuXDiw3U9JmnYsaYhF2o8V2qJYDjMVl14I3JmZElSsiAVTlOTSE2YzKoMiDZE291eqJY32wz5NeZCSsVHwP1QYdFjFE2DDb2u7mpqOpnwGA+D2PC6U9sUbNv+rhNGKkMNqEjT4hhTzUC1E6V1y+2Fc5nXwuAZhjGn06faTgX42GxaEyamXV/vYVTqYrYV9X+GfO2Fwo/7Hu5yU9puUYx6PRqiaCG+4l3AwhdRnoMJh9J6V3AsAEDbXUVwZo2siPfCw6HvjWp62x0Wn23gLgytXvBAP6DZ5euaVH2v703jy3EaIlwnWohmkLKj6g9xDv5ZDxc86HJTxqz5fAMalvCXNUUgOAfqx6pZBJN1OkTRGlWzY5Zj15Q7vVhMKoVNvqD6MjgFI5kX5CZ2pHrhbRq5Sia/KY63G+SIEBGYHIBqSk3SzL2bfnaUVWbDkanp17M2kSIwb0ssyY0dFwuactmvYElmACBSBRjp5exv7LVu6t5RX4sjFF4dopq+koFOcK62ISXJUUliItSRjLVNhQv1hu1RmY0T+wwws6aQYkP0mAM0T2SCL3EOrO+MTTs/8E6zpuKb33NOZ2dPILsOHPJv3VDu9GIxkQJEmaI1yWfEXJjyOxQEpOWasPQE2bbnnfAu0molE1Mx+tvKT8BjhSS7xQJYLSU3APLM6fSkvhf6gM9Pp/Y7ADShMiKtt5VJadeDzzJXQ/Yp8LIV23TRgrq+7mR5Z6Dloiad6Q7VNOCTZe3jxVpeumEo/dXrkCJZG22DXCs9OgftlESo7t7s606YVg3cVnwW3NZXiIac4GfBdTrBz1YyHrlvIAJOVwV9WHgXFLFa/COt/C4x0gNhtuYmL6IJgK+TYDxv4dczfgzIBHK7EQgO7sWm9CndP0FqPYJqbWcn9drOTXZd9gReNHCbvrYBgIsRmx9YYbHQHBlC8g5+N2K4J9qC76IsYiw+BWDus2CMp/L7VeQKVtN3kQjx8RnSwqP5vC1jtvvmGXaPApZP6zOIrUPY1nYn9VkEghsZYTtiXOV3IDHS735ZEZyvktfEhm1yWFH/Felp0I9F5ki/lPJ/dfcjoglaE8jhshjLzq51LnkWySmq78wMqRDiaRiuaEOaUJUM+tJKIfSN4HktTKIp8UlKkssSY72vmgb6eRYZcWMyaFJV3dNkEaDRhBSjDX/Owsp2N7PmUWJpAXNpl2ZWso5dybYd5ZwYAb0vkSxczGBTDsH1CTQkwFN5PsQQkp6UwHPNIXI1ifK9CMiLBU8cnJSy9qAmixlj17OMGwBOBAfADQmuVzPDjJ++CiyOWTewnDu4Og7ZKWsXXeryQqzjgbrQ0Mh1/EiOIyu1OhCUCG5IoD7Bu2oO0uz1epXc3cXCESas2EazmGY77qv4Jc1czQv9rR2ZYldnNT94WSjUhtcMzpgAnydJCPK7bArodchVshVWUpQm5IlasyU5+Hr90fhYQpIdmhnOcDSSeuV9MtGC3AbHoDFfV/sUwiSjsLSLuarlOl5qyqimoYtG42tKtE58omr7AtJWImBM4KX6PNRvMBYtgVQPZjELSk2OPAaSlJf9LkazmCzQ6ofxHryo9j6iTLZk2hsXHhQT2Luyc+uC4IiQggMNyosZwY1DXAb48swpaxZUfTXaZ0/gNpSFsmgWzmFcOTRNjXLE1gGRixYBgomG5J2+lYMcGOyAuKR8XMokIDiA8tgEB248uHWT3I+4cBhXhLB15SVILQn2L98v5XFIDcE7AiUuERlKvJdF/yo5RkOOcpSjXEvuhmZBOVvSIAjVBNCq3BbibaHDSqnHXSdUeADQ94KpYBYKvAOAHp4R0/J2V52dyD4Nu5tDVPV4uQZtNuU8jlGiIcXLnv/97CmUj/MQDZxtEQPC6swJyHiICUkL0YQUB9ud9O8AYa91nCZbLOj5NEIxT0rS2q/+Ox9PB0ozHE0/SPsRDWGvtuVkWXdkHfeuF7+LXnIjfqL09Nke98UeYS8REgthr/+d/LqamhjeaJSBSEwvo+mBudQ5cTECD+7JdRPDDyPCZzWik54+q6bfAdj0pG35vrEfcP8fNTVKAsj7Mo5obTEkHQ8Tsat4jgH8KNPqaeTKuQkGJT15Bp+zZ3XMTvoBJzY7Vu+RcUYT8CBR4cpoTJqAW7++bnDp1rXPfNeiNPwHxJYmLFl2RKa4TXptKYBSAcwAv8hewzvwop3CeZ27WSkAvafNNFSn3xyBmcFAqqIjeBRgDleSGsrXsynfE9v2iyDsnWRJujp5bJQjU8uX9qYkJkATwMus6g/6XGZONB3v3e5mpQDOT6WtJZMyt0nfE+/El9OEajal7LzN/U3n4kim/M6kxpewJ1k+ixsQ9sYP79fQqcvmyravDuziW6oO9NQGMYW8h+sGDI+kXX4rACtuXDGPODg4dXIbwl5+cI7x/hJuO05MRxpTjoYw2Nexcm3zFSDsPUSrlwlsD9LqTZKSUl0UFJ14HVo9feicit+C8/VUaIzC8q0Pwl1/YNnS+s85G3QHtMlf2RladuBFW39nrsUxyeJ0WzLG6U44UuVoMP1A4gluRB22NMaau6A1PPqh4hcAmdRENw//DiYCVnJGjEOXBf3JzKCBSh/sgu8uMlYjca7v4Uok6E3D0dSPFZ2aCZBojFUztc9R67AMEZSS+EDGCJ8xGe4yv2/egbr9yM5ExgjXR7jelNjMTlAaZXGkVDWLt5U7sljcUOZRhMRgxKr+Kk8AX103ZAItJwaPOS8gOzMrXb35rWXyfk3dEKhZA0zMEDZENTZzkxMDKU5JeZyr5QsN/RyPt1y+cFKLw2ggxuTQXZaiqY2Rcu1TnSScoyXMk2rjFF25143KF+pmYIo2kasLB+V2CDlRbYNlwCINUadcMlALE2nfbX9n781VdUP8i3UFu2XtlIcBtJ26BIuJhOws19oi4whXIk25LclV2H3wwrVB07oh/uUl/JBrgdhExkNmiPbPgheBY/nCoxzlKF+83FnNgl6lpprCMuQ92I3iaLMUa6/xWRRVPtunahLYojmCCjXs0f765QuxWtbV/lAJQOuzYAaaKWFwsSu1iJIeZwZCuD2fxelJvV6q/hxxQhv8hGI6sg1ewsSu+jYKchOYZpLq98PqZj4LLTLkjB/FwL05J6GVxDegajvaT33ueYflJpQdU5zaN/dZpAdnoHUeXyJ5dv1g/Dl1PEv5wsaLbyH7ftI9cWy7tZghbHd/7+HOTg/6LNLZUswVY8VTLk41rYBGmXbwy+6z4Pw/M3m0vGBh9zZZqLyr9GllMUiM9Pnn5ZLu5KQ4A3XSWOIaVRv14ZfJlx9SvFwfZvc+EyebPgRqgjhLL9eAc3CUEZQ5d2OiZjcBaPJk7rqaubjrQCcyEdKzZ6X9mk3L41gne9eBFgu487NqC+dxIWsqAPJyqANYj6uZoYtFvq4/OZFIjsmynajchq6NFotars++1DFKVMkCv7QtpycV5KQ4i5OT6mgmmrzYk4UzJvhxNc3LyOq2LZ9IaIF+mOAjpI1OokkhlKxeuf9KxvdSImP04H7Gt7AgbdUM0KrvQPUjBA8OHu70BDym6hfJIDZk5yUgk5dnfgcak0zgfgCNEe5lNrGevhBzdNYF/uCRPLdla8CHCRjTtNZp28j4z60L7zB8dB/h5Q6pNTiX713fuLgbi8UNRZhVDy3wAAAgAElEQVSo0+QzNaGE/wCUkBSFYEreZ4RhSuL1B6oDdbWUHU0f8GZToy72XjCTENnhWIBSVHYROjmR1HJLNGNSyNkZLYCoePqRF0dtD62Wkri2kkWIx1E+r5b74VWTAi992MlESUkcpoCkq1snqxZk3oo9y48fmuvWKIPu2gDAqwVoq556M1l1whxwMOt4AKjlEM5PKgTcpKjbYtRogkzQcZQ0/nysJLKZUHE8X8KvTQgzCwcnqeVNmBD68j2pnqYExXy6EvBTSrLzm82LvQC2JnBvItDFFt3Xz9Ao5NpLfoqkqMtC6PpY+sdt/tfJeX47gsaE1Mo4tlq8eCbjfWmbv+wKDH18sEL/sEVr4N5p6eF2U5i6tNchLjzYE6KmqDOQwldhsbCIzb3vLCozf7bHkM2YnGQ2oTLTxBtT30NuJ4jGgsy0yWX2XkoBb5OigqW4q7h+GmcJXwZhSTbZyft6XCe6tjGbPpPwbj5/spvle074JQpdPU/vm/8jkwtTxq8JBUZeojXeFWQlkCeKVvg29+PcF/gDIe88HqWdep1RxyBHSEKuyRL13h4IEgovmlhGWZJzNTQIQT+6fl+tLip/4+Gsw68J8l2o102tB0VFctp+SZhVJ6qiWDl4xIVDUHRpXgSIgbQwbcntjJPzAEoe5Kicy8EfLCqUWmmb63zRutLCY1w6NK1ZMBd+AmHXxSA1DnFJcIOvi4VlzbqGHB2cRznKUa4ld1ezOEStl/ktCk0+UMOW/fQ3PArnAg9jLXtneBA4M1sVnwUw8VmUa+rnfC9qQikoBED8EptdVbH19y8vDvssst3NXVd8KWyrYKtKvN6IzyLGHKKM9fvLtYQJrYOTCBh8NSEg46QlEIuqvetq2xNPQ8ScQE+e1zZc4bNw2+v5LCaitPlA6bcbY8W7KJbDOn2RtZuUpC9PhM2LrvBZtJe7wxgb7wRFGoKgGLNQdvyqz8J5B5ffEW6bihfJ4+uB2gflzIgRJ7/9slYkUyd2jHAvc4ax8Vk0Jg+lYiJidYY+ewk+wIXaNEHuaUyUdjcgPF8W7AgANG0zHQNfNbd4toC/7NC29Zlrstt15O4uFnMzxBEoZ73Y6INNRZ+wHLdNBTBZZ+jMZ0HZZ0GnJ3Jc4+DbXY2Y2HstFvKyqiq92Ym/IcXq3AJA987FqWa5L00KOV2saxGaEID75/n4RWmPA8Q3sd1JdAWQCXJ2Ctw/n/oWsl+BFzUaQttO1NphFF8GAHqpZkhuq/ZxuxNb/fGDsqCVNHE/TWBKJ4vqVJvT6nl/2Geh4wGUfqf7pwZ45CSSoDR5ms3qhbSFNjvwafb35DTyCUIRwHhviXB5wGeRfQ3ceIF86/FH9+VY/jt+cE/MksiIJwFuq+Q1QiLDjopPhNuAFBz8RYftv36OxdPMTK++iC6WFHWXKf2AfTMkbCNoSMUMWfBhQt7+o3tIrUO46Es+5HjWYPeowerz+szHVUDY1t9bM6S/57F4vsC4yu94BNJvfVl9FnYnmyM6hxGkrE+JX69Z7DrRAIahZjtaINMbaha4XBdfAgDRKFKsTFaDCQXepmZxiHjYO1nICmCoB5yXnWpzReg0t5c3WyAluAz8kcdxy5pFP1ReEsvIZYsK5fty1xek5W1pFl59UpwZrQyrlvpUCogpeDjvQJcbnDDfvmbxvexn6vryDrvV4kaaxWLRSK3TRsPK+IpoFjO5kjXrVZJZkwqV3QHH0c2v6fbht+qUfBMI81u1xZgTh8ZHsRHJOCv1eGbxsiUDr6wIdltCM+ezMk5Z1mz9/k2e/xu2SaIfhp3KDovFmswrwL2LthG9uafRz9p6w+vcqcViUmRotroq3sB/+Bjx08+q7yET3Oi/RbwvO5XmktgiQ8rCrZDrlAvkKB8FUqwAK3MvRwq2qqYNVIMB4B5LkaH4+RPMyxeKDyHjO2ICuvzwYjS5H/Jv0kzWmIvO2O87qXc65Qd1ABjMs51Vf6caxG6aZagLhHtwH+h7pJcXry9faGDa1y1fSLyuWl3u9+Rd1QVsVr90wuKen9khKDaAKVvaXBTEZcsMjuPkmGvaCoJTPtHcLylJmKR6PCA7NhH4wT3g488Oly/U6M0ryheW8XpN+UKvIe6zkxqJ+/RzuBD2NQk7BiblwD+8P+GPBXCEex/lKEf54uVOaRbFDkbWMsyKqyt3/ORT+MePauLOcgHe7gRVqPZ4tmVT1wkyM1+jlBRErusBsdWJSDgzre342VO5dkoT4JZU8z6pDs6XF+K8y/fQEnv04z8M2vY1UxMALxqkM3FUuhcb8Co7Hdc7xEcCOPK//Ymc/PiB8HQuhIuTF9kR+fwl8PC+8HBq9WwFSy2akoINAP75pajT3QC+Jw5d9zJXEc8JVHrd9D3hC4l/6FtSEwQoKEP2hNgGuIwxGM5ahLXwhMSF9awLErHgPwxsPD66B5cBWOlE+j22AeGlcnBS6QN1Ayg7ONNJK87Jz59h/MPfkmMLcUJK3ZCq2XQPG7QvRmF/MiYaB4ewHpFah/aTXDGdGf3XThFbh+V3xWcxni/ArQONcl2y9rwjjCuPsNbaJ7LPtr/zFJ/8mR/H2cfZ+RsIKRDCJqF7KO9I2HEhFR6VESsQmIBmy/A9ozuXE+7/yy1cL9m6ZGgEN4+XGFcOq493Zcye/8k/gM1HDqcf13YOK0KzqX+nJr+XjdQNadaM4TSbzREY/45JD3iN3KnFYk84AYZjsYhVs3Kq9BTHX6tTX1n/0qAfmVwh1yVr3ui9rG9gEFr6AjAaRvHyq/NOEZzbXqIV5t7yDucHZdXWYZQJan1N2ZGrtPslBRqQyTjGEl0oICrmCegIu04iQMMA2hiHLCCAMeXoRDV//GUnVPLalwxqoyGW9gVA0rJjjVoQC638xJOfZLFBYlko8ndul02f3VgXPIXPD3FC2OuSlBHgfihkvK6P4hBW34ImXBIhXPal0E9+kAADrh/hOlcRtYkRLgfQwpc2h5f8SsJe1+8T9mLXYfU0oXmRzbzgZLEwpLm+SxmABYSlRieEoZxGhu8TKMr1/G4EDVFyRgy3avu8Q9h6hJe7MmaL5yPYB7Qva2Z12Dr4bSzmlBL2ciC4QQh7w7YS9rrx+l62u7tY7JWvS4e/09TquZ2XcQPl3/k1JklYeh5PCXcOpbbHaxL2xlQXMrXrlbBXbW7DBUHjzOdiyEwmRMJ6ncS3R9hr+RcsH2XhkHDS3phA6jRLqFEMMourQxnXEoq1ZDA3IOydQOf1eem9kReRmISD0tc2kI6vtqk8iwQKxpk68BsR9vouGcJeBrEsNL6TBcANxvdF5nosk9X1Ca7Pi2V+DyiHhgGAPQ4S9vouwXdC+GtyGuCHJCUBuBLypkSyKH1fEPZe9Z1SvVlH23Wub6IAk8zKkszkKluX4U+4sdhM06s+++pVn0Qt9LjmnQAVan6bRYxtGzX6Y9qreAjSzFwAQF5YciYokCe0jbbYRLG3EQdwoprVqsqn5rzk/Aw9Rkl2asmfySePcp1ScwY4uDlcR9iRIYnW2iWESTaYg4yP/oYAAoF9XthUEfKCJ7JlGXFVlIoAdnqtOgZSTwRg24AvIGpzdHAe5ShHuZbcXc0CmIbQLKJzToCru581Tw4lmFmdy/J1ElUOzDlfpNEm9DxBcObfN0EyNzVMplwDi6aqtLojBw9eZNBUjKZ0YBJORjZ7QRPEAemdUKQZlir2TgBYM9YmLNqC1ASyXyRX4VJHJiloTMFbGfGpGk1aNaBeHWBcigwrshEA0jLA7eS+mi1J7AEagd4+s6qR8CKAdlmtVntf/QNABbkpUlTNJUW5NgEpc3uKX0H8S0VbAaS4MHPJ/JSTxRlJfeal1JKC3iEtAuLCI5TyC04SxNRnYfrCQc7Xt0OLK/mmwXDmih+APRWn4nCezZDOydbPQDQ+CzDDDwwXCMNZzjp9FuAoFyVSi9gT4qqRosebSrMwnAX05w6+96VC27gkNB7FDNG2pECIC0LwVAoaUQTS9eks3m6xIKJvA7iAGAUjM/8UET0C8DcB/BCAbwP4s8z87KprXPteGodOKFRkAISchkgyOi2DdNuKnZv/rT/OHxX+rICt1UJsQUs6k0FDlaWbhI/iZFUXla4XCLdCpDOOIp0txZk5Gr/AImC8J9GQZkyIp7liVUyIZ/K5zeTa3AZxui7aSdQCFwDaBmnRFGdmSR1fthjv1yrqIZPTkPclSuLnRDG6uOQ4/nB/Ab/NL5Pa4cEhLXxB+/X3GrQv5WWPy/oK+c4jjKnWAlHTCkA8XZSJFnM0JC09gqrYGZYcl0H4KPO941kLf+nh19sCn45LWbhcZKmLkdfM3WOPRaCinsvzlYnZXEbE1tWKZezQ32+RFoTmhfRhvLeQrM0xgYOD76qpl/IkazMsW2HbqxdLrL/uQClHlbxMzGbpsHskjfC72p4xPx4OGe69YfgO6M9lrJZPArjL716o793uwxbDCcHFVRmzzYce62+SODWyjKeE5sIsTnmtTS2BRkZ76dCfZZxLrNGS68gXYYb8cWb+SWb+qfz3LwH4DWb+MQC/kf9+J0JzROCrT369HVd2RjfVZm7WqP3P8/s62n8SV7XvlpGMe0VnTI1Tpvo9k7YR2GebMUJmly/HXvObq0R9AfO22uvpQkGYLBrlXCf/cenTFzyepi12vDBr69442+OK0lSt7Iom7l0bs7+/4K7dhhny8wB+Nn/+FQD/C4D/+G0vOkHB2ZyIlMNG9phz4L4XxJ3+O7tGqbGZMzNpvRUzZjTRAs4RBxuGy5XJNeGMuw50sS4YEb2Xe7ERM8A6+WJEk3dM2nbwGvLsBoTnu8m5tMksz10vkQQliQGAfoDfdvuh034QbUL7mGud8jDAa7RhIzkM5HLoVM2mbJ4sPt/WkKGaUJT5HTRi0kvyk1T/rjgLGqK0VzUeE1UJL3dF49B9MLzgvVqnblbr1O2k1invOrRPch3YYoZIopSaY75r4DejOAxNlIZightSrkiWIwFjwuJZh7gMUrcVQLsbXxk6bQ/UOqWLNc6/E7H6PB93UpEsrEeEbZPHS94hMlXK4sKV0KUbGO2lXK952Zeqaq7P72JwOPm9lGudbsqYnX/3BL4PWD0di3aVGkLYplw8mqcVybr9Wqe+e3ehUwbwd0nKjP+3zPzLAD5i5u/l7z8G8NFb3mNfvKsVr5We33sgKT4gTbg52SlYy1xDWa/UNm4zB+asxgeRYeFWn0XbVq9630sWpfJdZiizAq4modMmVNMjpWpaxIR40gpOIt+a20bMizx5eEJqI9mlZQOxoKzTWhjZ51KCRFSzXU0iFFnzJvd7PGsLLT1iDn06h9RUrsvxpEHYDEBw1QxhhvMOfqhhT1ZTDuILKX3L94zBlRdwDsqCBWU5B2y2xXyRiSYvu8067R4EtF52YtVmtJRf2Eak1kmB5Pwsx5MGcenQZP9DXDWvB2Vlc6mAsl4ssHvk4PtshgRCCtKfnYKyOlcm77BSn0Ue9o4ROkZ/JseXT4Pc1xGSmt5EGO63GFfie9Ex6x547B4T3OiLO25YEdq1q+USlWq2kcLIzdpNQFkpXF/9eNvF4meY+btE9DUAf4+I/h/7JTNzXkj2hIh+EcAvAsASJ4dOOcpRjnKH5K0WC2b+bv73UyL6NQB/BMAnRPQNZv4eEX0DwKdX/PaXAfwyANyjR6/XhSygam6GALnOhpoLmYU5p3cfcnAWFX6MYobslAw274q1nRMzhLW6lXrvMxFsSdDSBKv1LqMveVJsxmfiHNk9s/kwRvh1J9EGVeHVYdoJCrQgPhWYYwh3yj2HoTgwAVQo+zhWEJHW3sgJRxodSXlMw/NdBT8ZjkvyvvhVmiEK3HqIxTOvf1NXWa0pZZgzs7BWa/VvyG4Z+qGU6NOKa4UuUM2QrpdrbivM2RuTyCI4XZ/gdyNScKUiGSWBoSOJaq99ozGhednBDU1BrIZNV/k93ZRoBt7B50pjMgihjPHpxxGLJ/l9yhR5fjPC9TlioiCpyGi1MPLCQetG+y4iZKey34hzlxsH12VHceOx+GSDZhkQnlyWMVt9egZwg8XzsYxB6wlhF6sZohpbdti6XcTC0Or54R2YIUR0CsAx80X+/CcA/OcAfh3ALwD4y/nfv/WG1y/OKQCVgWochYAm+wioaSRcuViURYSI5e+Uco7JAdatTP5KGykGxGdCfqMhMbrciMnBXM2QpgGdnIDOTyunZWIhotFz8ssYH53B7YaSXwEAqQ0S9XAyKVWt9usO/QenIGYscu5Gun8Ct+4kZLnpSgjRjRHpbCll79aZuOeqaMiTzNW56xHvS26If1GJdm00hDLPQ/fNM3lhgbx4iYMytdUMGU4DwibCxVTsXzAj7CLCM6PWKq9mShgfnZacE+03hxOE53mRfWU0pIcfR2y/Ic8sLggUZewVNg0A20ceyxcRyVMxTwQWDoRtQlw4rD7RMUvYfW2F8cThNN8rLf3royEvtYJ5joYMI57+eMD57+ZFIACxJbSXDbaPpA1hKwELSsBwou9CHqIdw3cBQ46GPEiAz2Felyu+syP09wOGE8LZ0pcxe/GjLS5/kHD6e03Z3cYVob0I1QxRa7gluD6gveRJNGT8zXdjhnwE4Ndy9CEA+OvM/HeI6B8C+FUi+gsAfhvAn33jO1zF06Dflc9TODczv94RPIFTHzqeKnxZtZebIvzS9DcFF5GP698UtXzhrF1jBBpf8iAAyGJ0RcrMFyJzCHCyEGWTB5Jk3Moimeo4Kh5jAqFnnh6XM2/WNh2vlKHMSSagThRi+SyLB5djTHq8wr4p4zRI09EBvOmg2jaU+zMXZjc9DjbvAFefyqQPGZ6un18p+bcHxwD1GOaf31DoCyGEeUu55x7zT7t/dwJhdqen4H6Ae/QAACZV1P29e5M8fd5upRBLrqLOuw7xyVMUboQZLwUA+Mw7ITfz5VxSx2Wm1afLykIE7xE//qTW6ABKTY/CLqUJWV/7sPzsYDjXHlPGbc71KvR7w7lY6OcAwDukz55U4JLlq2xMHVTlsOD9IkPKT1HAWNnMCR99WOHFWmRIozQ6NuoI1vJ/eiyK01a1IC12U0y8LAVI9emT/fKFtiiU+Zv7Af7rX8vjVUPQHHyd7EQoxaVtkaHNTv5OCelB1igVQ+KpmhaffJ77m9+bOS+E9hmoZuh2C/rR31cT4ojESbvrKxanbAqp9t0WKe4HpIe5XbluKTde6p4C4CaAPv5M7qk8JwDomx8hna2mtU5zzZJDVdTp5eWkhCIA/G+f/U286D+91qp9hHsf5ShHuZbcbbi3NUE0RJrixD+BtgH6HqSwYD19tRQMRdtUCLbdsc5zwZohsyUt21JZGxDMAoIXBKWppOVOToREV3EW6w3o9KRwOyblvnj8QH7HXDXAJpR6E7TpSik96nqk+1I20F3I79P9E9EmFuKAK+dm4lpHH+zjLAwhMDDFWZAWN5rjLFQTyTwc8Qc+qPgCk8hkE5vSIojTMDJ4YXbwQbJcC9DJ1vQ4XRRHosK2/aKFm+EstFxhyVBdtsIb+fwlxh8QbTAFV3wRE8Le7EuxiWTEDBrP5Xo5XR6QXX48b5Eah8Vn8uxc+41X4iz4AM7CffIUz//gQyw/1xR1Kinqw5lMLzdw9SEsKu4BDLhRsA7bD+R6p98TLg92BK8s3I5AZz9QcBY6ZutvPcbmg4Dl81j8NrEVnIUiOBWhyZ4QNg/3cBbpf/8q8FnMM+0mKeozjglgEg0h75C0XMCkwvl+NASAmBVbiXKQdYYSiVpn2qIkuqqGpq6ThMICytJoyLa2TSfCGEUlzynqNp28RAt0seoGaY+qmLpgOSfw71xqwN7TEgIDEKCYkhzbUgC5z2zyUwpx8fN17X6quRdkzBC3HYRvoR/A2QlHpkIYZwcmIpcJ6tZ1vF0C4CBlBwYT5cntQoyVcmAjJh5vt/Avtnk4XTGN2OSX+LUUAeLGl0WMotybnYC3FG5PMaF52YtDU4FaT55XMmCiSdSNvJf+a5RKzbr1Biff60qkBkSSO7PpES4V5KBRr1QWmbQIpa2uG0FJ2uW3ArDiUDEhvPAIHz8Xk+tyU8Zs+ck53LAUQp7iCwHcUKMhBT3rCP6lEBo3yuieCYuuK3d3sTgQwShiH6RqHEptD0gJAFPWsDg+J6CsPGDDgFLez6ZcWw6Ici8ChSDlA7VCWIy19KH+DhDQVNYsClzau1pGsOsrMKwb5CXKkQ8AVaMIDtSNtV1dJ9/ZcoC6QJnyiIB40WWSj6DVqo4dAC1ArC+9soHx6bJW3dK20zRlmtv8ordNmZSc8qRzKBqEJKJB/AjLRb1unjB876yEAXFF6LSAtIYRKUdu2ADEZDLkfI2TBn435uS3POaOke6vZAIRFd4JOT9MoOhazvCq0CkfCJ1iGNA9MkWtPUmJAEcYzrMG1Vd+CY2ipJCdtBHwjUN3P4dOt8LJoQlxcjIjPjxHWgYE58qY9Q8W2D0MWGStBchIzV3to4Ku2BPCKsDtIpIJnfJ3ru/UvbuLBYA9AhyVONMymGWBMKfwMErIU/+dScEoKBuU7sjeOMssQU0+l8dxQnrK4wja7qqDszBl5ZohphI5jWRIaGrClTjhuslOoBoFdZkpyxKrDiN4szmsWdixydB0HurOU+gIZ5pFofm/2E77fIhzoxuLZsSDKVKU+1qrh8szoZiAbV/a4NTh9/LyoGbBsTI/oc+aRd/DXWaMSPD13QgGht6NssB6X0KxwjJW2bHSSXa+xgh/2U/MDXp5WYsuzzQLeC/Ob1ucGQBvd1h+1iG8qPSA3Hi43VhwEiUKlBKCLpQ5i5dJ2q3P3W8lRYC9MxmyBPdiDTfTLNonO7jI8OvBsIUh11alTDtYHZxu3QlDnNEsrKn1OrkjiwVPTQSgeqLVBzD/ha0yhuzd1wc59K/VLIoa2ZuUbaCaDLtOgEIK7IKYgdfXLHJFq2Qo3ryvqeK7voKX+kEiCMygjLNg9ZY7JwuFTqZhuFXNIp1VzQJq5zsC+1qDMy0DqBOTiU11KxpEGyvUeiWkzZMiRawArxtqFpwneslTSZj4ReIqaxaeJgliFBNoSFKwqFAGCu6Fg4Nb5933jTWL6i9jRwKoaoOkzAMT5iqrWYAhk70LJZ09bFxl9VJAlXMHNYvh4RK7xwELT2WxiK0TUJamqFtQ1lnzVprFMRpylKMc5VpyRzSLK8RqGwYjIZW28jpnqn5p3RGQQ9p1ACdRuw/gLHhdHXnwXjQMR1XDgHjS2dLqMYO7TkwPg7Ow2kcxCZ6/rFEQQ1yDC8hObftJJHU/Yyz3F2SpEx8FUCudkeAW0rPnh3EWpuKW1jJh5lKm8SqcRamt8umMesRwUmjb/AsW9X8YS20MxFR2ZMWKFNNpjKAXl/WSnTh5+elzpAM4C3tM/+Z+gP/8hRw0Dk5rhnhtRxOmplDBWTD4LGtYw4iw6yYs6fz0+StxFnQFzuL0Xz6b4izaBtT1CCVZsWbf6nurtVQ5R3/Cc2kX9bniXhNqBTbvgSfPpA7rdlfGZ/ntgPbJqvym9DemfQcnkZgwM5zFHAPzKrm7i4WbcUioWsksYVJ9aG0DGkepQ2qcVW65EBbuti3q+iR0eiahUx4GGbx2mn2J7U5U9bapJQZCAC0WEzMEl2upPZrLIZbJ/fC+TBb7gnhzn36o1xhGKRGQAJdBYHy6Ev/GIpsj1nw5WcLRw9ebIetNzQ3JZojNDbFmCD+TosPpaw+rGmwdnJ6qo7YRSDTGZEKnkNwQBQQB1dE4jOLgLBm+OXzcNnAHzBA3M0NcN4BfvET82sP8HIyzNbgyUeJJA78ZhPFKoziJQcNpmTg6cWmUDOC08Gg+y+e2zY3NEPr8GS6/9RBLm6K+cAibEeNZTlFXMyTVFHXN4qUkOS39fbne6pNdaatT57F3oJOFmCFPLsuY7X74MbYfNFi8qD4e9tnBeSh0un2wb4ZcfNlCp5z/ZxaElFfV+FKqUE3qiAxjCVU6yCJAKSB+9qRc0j+8Ly+kwV+Q9xXCrfcaR2GUXmamLJdfvKfP4LKmUu61WMCdnwGrZcVjAJPcEGrz4LeNXC8ZuLh3SHnS+21XixhvdmLHewgyE4CjD6QmyckJeLORWiUA0rPncPQQ6eFZeXHJTCytSwIALkhuCPqhpK67Fzlfw7ucop6L9zIDMWI8XcDnMGdll6bqO4CE/Xy/K+nr5UHECHqxrc5jI7Ro6y6WfzN+eA5/qXki0q7UeKlPYij8/HaAcxKSBFDSyMv7oGvueahw6izsCOOqRViP4Nah/Z2n5bt4Itga3cGHr98vNUlSmyn19TqBEBcezUXOb1l4gICWCLsHHr7LeRweZTfvHkh7wzaVqITWDWEv+SbtOsF3lYrPbUdBZM5k80P3MK4clksv4VUA3cOA3SOCN/R/wymhWZtQv9YNaYHYBrQXCcOJLqRA/KfvLkX93UquI2JrgUzqg1ixRW1nPI8gqi+07h67TlQ0rQdir2nvFYUwpiRvxSgOyjHjPLQUwGZXrqkyqeux62omaN+XpLByz1yLhPu+/pv7xX1f65KY9hFQ6pIA2XGqNUd2WrhZQGg0CjR6wiYOCF5gVkUd3pV6HoDMTQ3xTrzp2s5DVdTzeGg7AcAHB9KCRjnaQnmhULwLxZizW7kWJLqiinpLOFhF3Zsq6hZfE17uREvKi5hfD6UmSVqEEs3QkLrbRfiNFnXOyVox4uSzEe3zmnWqVdRLNuw1qqiHXNfFabbyTJoXK/itR7gcSpLd8skAcIPl09rnsL26ivpw6tC+GBF2VbO4Sd2Qo4PzKEc5yrXk7moW81DqpLCQCbXqZ3vMnj+/jsqsELFWNSt3sYWW5/cyxXkmhYkm1H9RtIpZpbSikVjsRIzlc1LbMxcuohjLv3I7lt1Wixhp23MSlSUIRskO5doObbuaZHPw2zCaduXdPUPWy2QTjvQAACAASURBVPGhttfuSzTGUsx5T3Q8zHWkUNHMiTjm/hhtCWO2yW2Bn4wYJVN8Sej+Dtw7/5byuE76ClRqg5hBZZFBIU18N+zEVKslBbO2kBi+SxJKhmAi2EmI1mmRoT4WH0phB88aiOtivaaOzYFixQVMNqaidbkuIuz8hNHLuzj522nFuJzO74dU0/cZ04zr18jdXSzm8qqiQ6863zhJiejtM3Vz9Wxz0YrNcIRJ5bB3JYVYmPbaxo6Kil/OLX4GA7QiwVK8c9F2ZQo+JuU3NeA45+oYv4P2KC1fmVQREzwHkJ23NhP3lqXczwnu4o2u4c11AHDJZb+e3N3FwtYJmR8j2v9sj9lzbcUpe3lT9wOAJFSRCZ2SnWAmzVfP0ZdkyE7E8jJnzWDRTCtyAZO6HtQPk1oe5bhO3lyLhEKo/+bvKYRalwQomsWkLgkgu7bPaEeNwoRQx2SMU0dtYuEOtb8HKioz7+zppIVTP47lBh1G0K7DIdqDMh75M4ApL2eOtnDjxSZPJvLSCcJWeU21toeS1KiMZ+3BcnypcfD5d96k8KdVK8cutTRBg9RmB+fCo3JECKLSFmFOrZeFeDeivx/g+rb0gx3BB4fhXnZm73whcopLjXDkCEXj4PpU6ok0T9uDHC7xJCC2TgBmWcsY7rXYPfCVNBnAeOoRbAJfqz4LwnDi4AY/cXCyv/5qcWcXi0mdkPl3phaIrQ9Cpgp7qS3iqibAmvuRUg0xaiThZClqtE4e72pkw97Le5nYFn25aGsIknPE4PwETtGXWSyTVRhjiVD4xOW4vsylFsnJStqo7V1vgJNVrUsCFNPD1iUBpDaJTqZCFFwQq14WC63knkO2w6MVwmV+LVT1zcS8SuTb32/RuspspeJ3I/wwgrYHXvY8HgBKv4f7CwR9zhoNaWXyqHM1roI4HjcOwyMZA2WzcrEiFAFg+2GDZbu/McQFoV0IC9bqRR2f4dFKjq3lusO9ttQkSS3B52sRS+QirhzawujlwETw6wGX3/QA8oITCMkDzcZj+zijMrdcSnuMK2lv8hJhaS4cfM/lePtsBbcznCRZdo8bDPmc5lKew/qjgM03CKB6fn9GaC/rGMTWREMWhNhQYeWiyEg3WAHu7GJxG6JApC/gQtc79q7EmhjztpikqsmxuckCXM1KdksyqYehC3o2AyYtcQdqj9yG2Pqk5nZSy+Oq39xym77Ie876cdOaKcdoyFGOcpRryZ3VLA5lipbvTOEg2GJChwoRaREiK84VshpFXNLFegKFTfmaACb3okUrmAFFHGaGau77yU7tn1/u4yxMESC6WMNrYtVmi/Ak27IZ1q2Fi9hRyR4FIBDu9UYyENWkUN+IKWIEQBKORoETe3tMtY1oIjI5y7b9dL2Hs2DvSvEfAFh0i4KzcDOfBa83B3EWOh4ASr8XzJUu0DlBH64zOjN78d1OMklpjNI2XI2z8LvlQZwFG5wFXVSYf/tpkGM5ea990kjN2ZiQVkHwEUC5DzuC32Qzs/UCbBsi7v+rAYun+ziLJvtCroOzSPl4eHJ5EGdx8kmLFBzCeiiRonu/06G9bEqBIwAYV1fjLPp7HovnI8ZV9Vn4/vqa9p1dLOYikYwbmBCacWl8FvAeyHkdBYxkMkJJuSVfJT47M331bXDwch9HNSTrHchkaspvXXWMej8hltkryOx96UPJHoX43PT8EorUHADvi+0PABhzjkTmdNT2liiIuS+FAEq5atfoy71qW33lkGh8TdE340WJS3vnouOhn/U6JXSbF4sJ/2c+DpZcFPW/yO8IoKmDM7W+Fl02khoHCk6+M+3lcixPqDZI8aCRMC49SqlRzyU64oZU2pAaBzcExKVD0tRzDZ0aaDcY1cHZKvRfzqUkQLpyrnmuVmLjxJ/TGX/EwmNcEmJjj1EFFmLm4FwRwtaZdvGNzLu7u1jMPJsTX8N1cBaZbYmsZmHYvwtzlK7iwyAT3Z57CGcRc75HUFSnICQ5xUnMmrpBtASbjwLUCTMMk2Q0RREWnMUwSNvCWP7VtvM4Av1gUsFZFgHVrJQTY6i8E9BMf81JoSmCU3EmE2RoQXDGCRbEWf4P278xJ9Qd2BnLeMBEfLZDvZd3QvVXwpV5HIgqrkTh7WOqOAsTUg3eFdq7yb2Dk36NqfJnAOWYalJ+04NHibQER7Uym8nvoVzq0I0J1DhQP6J9MQo3BgCt4O66EU1+DhOchS42qoFsR3HW9nnR3vUHxy9sRnDnJAU/X7d5yWAvUHYVFxluZ5zqO40qOSnYfDmWzYC4jvN15O4uFodCp/pVCDXTNH+mEKah0xCA2E81C5uZp/wOmrF5sprQ2uG5rxEOm6jlvYRAdUceR4mObILsqsqofe8UtPETgA0vmlrNnLmWFARKXQ/6JJj25AQw5tJe2u5Aq5VEFBTCrUCrtilRD0AAQAJxrhEIPwrlmvJklJBtNhHGx2evzQ2J50v4C1/6VJ5LN8DFdBCvUcYDKP0eHyzh1/ncICX3hBSmhgfTIsDtBrhhxPg4J//Nc0OydI9atC/3X+nYOIR1K7khm8qPMjw+A7cOTV4sxgfLHGnhrC3UZDT2UsO0uVBaPC/1Tz9LuPjBFqeN0RgcwW+jMGjhdbkhAb7jYhr49enB3JDu8QLjkrB86op5tP36ApsPHU5NBEhyQ+oCYHNDhlMC+xa9li9MeOdV1I9ylKN8H8jd0ixU7SfaB1jECJATurxM6gpgyidhfsNdX/gcSvpu3xdzRlO1C4FtCBXElO9XUtPtvTZb2fE1DXvXgV5KuUQ213Mv1+L0tGq6KS/Im22FTG+3pVJYHKvTU0sllpKJuQ283Ur26GDal8Fivrdqdmb76gd41XC2O2l7xpsodJi3QjAcnlzumSHqlykw7SEWtibra6ExynUOJZLpeOTzAKBJqWgrhd07+MqNAXGgUjcAmy2C+jM0jdyUV9R2+fW+GRKyGYImFHZzAAhPMuAtY0yaz1uhvUtCrFvp+CDmRXAF1i2+DoJ/fonz312ieZo1FmOG+F2uImfMEC2oPDdDUps5OF+sD5ohq49bpNbDX+wqDWBihG2L1iSSLZZ+aob4aoaMS8maLeULGXBfRQfnxMS4rrhcQbxAioXQ5GDRn2tfUx2nBxCi7xJrYXES2h5DdDI57n3l9tSFwpEACLTt3uMg/PGW+2DJWcp/M2i3dfDeprDCzUsKvzpZDRJXm+Yw4c24/baZz28Iyy+cJAXweLPnfXcXi1f4LK4D9y55IDanxHqZSzQj/+ucRBrKxD8M9y7/WQi5o737I3jQ6KbxmxCqr8PNIiN6nMyk9uK9J1+9+JSTwORlNlEeQNoUjI/GHWivLhQaDZl7w5tQoyyqzXgnx/Mp3Hhg8OV8Fda2+H1vvo6HfgZkspVjWhc1uInTjX2uOOZcLVuQoyHWIQpINEQdhVaUrIcbXykCAHCTQ6cK8Q8O3DggIsO7NTKDolmoE5ubvADnSEaYhESFE1PDodK/w6FTSh6UiynLmPg9Tg69X2odnNF40sJjXDo0xmcRFzVqBUxDp6kVhKxGZCjxjRwRd3exmJshSnUGXCsawso2beuEmu9KFueNs05Z8Bi68KScdcqzFL7bzjpVFi5te871mGSdlsI65l4pyTalxxVLkfL4veOs03KdjBUh5gkHCZlnc+tZp4NonRQjHNHUDGEJ4ZZjThZ0iumdZJ3SEOG0jeObZZ2yE1YubyNOX4ms07lmQc5kkl5Ds/AOnPKOrC+vc5VU5Q0TyRCCnGtqokrdyiFjDLJNeuuJZO007KnYi1WNhmiuCxHV6ytPZqaY40In6ACm95dIZjAUkrpeMR3OOaAbbj+R7ET8AkgBaeHLZKeYisnhfB6D1guL92XzThLJxrNWKtnHWtrgTRLJAGB8w0SyYzTkKEc5yrXkTmkWys7NwwhbUR1AqVnqP3wsXJulFkgEOGV6PfObxIZ5OoOJPvxAPN39gJgJaktGad4RK1Bq2Ct7yDHCn5yIx193X2apbL2RY+7Bfbn99z6V6t9ml7VVznmohL1pHEFaK1UjCZ8/KQWNEGOtGDaM4GfP4XiKZyUiAX3Zqu9ZC0FKBUehFeelW1ydiQ/vCyDot767T1EITKqbuyYUMBtZRGSMSKNhmra/33X1uvk3fn1evzeV5C1jdwGGNQH0W9+t92QxMcnswoumnRYGyuIybyt5j7St0RB6eTE55hPDe2kDnyyr2aOm3Rgry3ouZ5genOHeP/iOlIqsnQFSRKPPOqYKlJv4uiSKVkB1ANJ6s09IBGBpsqOVi3T1f/42TpaLGtHL15+kGBhnd/zmY7gXmwmK1W/3I1dXyZ1aLDCbnHvfcbqy6NBcZBFxIOIaLt11sqDc0As8kRRLGFfbyplxip0r+SS3LrMJzcpbAVQ1ljOXZZwuorV8VSpudtr1ByfarYo1V+wEsVXVtO3vItJkiyIlrhykGqJNqZZdSAlIrhYteldt6/o3jgxRFOY0phs4KozcqcWCzcvqlsvJiqzfxZcvEb7+Ua0GfrJCurgUOv5tJb2l1VLOOVmB8m/Ts1oTw33rR+T3F3lHf3QOZwrX+u98LNccY73X6YmwgT9+WH0dT56DHz8o3BLp5YW08w99C/6ym9TWTKsGw/0FmIDF51uMZ2Lnhuc7dN88AxJj9Zuye8Yf+ADu+Rp8uoS72BbWbv/pM6SvPcR4uqjFeDUhbdUWzgcAaD9dS67Hti/ox/Ak1+/IPoji48i79vqP/X40a3X4qS9EciV8J33p7we0L0YpNLyqu1TYRjRPt6bqF5eEteEb9wokejwXDXJcebTPc7KeRguWHn4XS0RkPA0I6xHN7z7B+t/6/XJsSXAj4EaeIBA3Hzgsn+U264bKQGyAxcuEcUk4++1NOX75gyeIC8L5t+XY9uECcenkumFaM5QDZcLbmNspm8X5//scv/Xnfwhn35H2pgCkBmgvGdsP5ZywEd4NYsaQ0ZOpAUBAWANhx+jvy/HH/2wo41xycYiw/maD4ZRw/jtjGbNP/+1/A+sfZJz9Th2D/hxoX8i1wUDK5PZxAVAE2pf30d/LMPQR6P+Hfe6Mq+ROLRZW5k4yGxNms/OUz3PVeZTiQzTWIkSTuHJhxpaXi3ZSIHkStlKvvNmpeRwLazaQF7Gu3ysy5HaDTBqNSACgnuC32Wk2xJJ7QDHCb0bZ8DUHQYE3g0Q9rJefxiSQ7G4KcgJRJa4BZBcaJTu1QLhzv0s0Rs2u3O5mPRaqeRql7Sk4NIll8QDQBMmqROL6AvGBaIRmj6YEtx3Ld1q8uNF+oGIHKLJkmprn6dcdMAwIa42iOLjIQt5ikqgWLwnNOgGEGhJmIBByweFaUBmRETYRlGqt0+ZigO99yTJVWDWQw7yxlgLwGqLteiyeAYuLDE8PhNgA7Toh5oUs7BjsOIOg5GdJict2gO+4hJX8Lkllc09lvNkRFi88fO+kjXnMFs9PMJ4QmguuTOID0FxyWSyU/Ca18l17yXBaryoC7gZUlUcH51GOcpRryZ3VLF4pbGzHcmzmhyhJY4f9E2WHUYxCxlDsXWduV2c27+IIZbFt55qQZEZy0VyAbDOqWZJqeBAxTSpt630pVX/LxI5n2VUnNjUg2pWN2cckG5a9vmInSMyDuUZGg2G1jgw4hhuBlNOupW/Vprfp0DSmYu/Px44SlzZQVL+JBWBljWx0OcuU89+Zt4IZTp18g4T9JCU+mV1VTAh2ZDAy+bvIwMhlzCklOXectsuNCTQymGkCDiNOcD1N2qVj7HuGG+z9CG7gwhXhh9qmgnEobZbaHW7Q5K783E3bKcn1XdDnzuW3viP4oWomzhP8kKE0bG4EOU/alY9EfDVwFq/jryhOHhuTLqrnDRQmw3C9B6H2wm0w4cO4riisNlX0JNs2E1W9zmcMSeIp34Kycs/bdZvOPnv9DHPmjAyvcHIUuHillefaXsU+qAtKcSCap3CD2L6Vyfhx5ZhAnQ+ZmbveQ0ohyG/Z1bax1g8yLN5vKuzMK6f3Jyo7mY6fTN56TO9v6e4UrMXBCb0CcDWknMy9D4yB9luPv63c2cXilXIoT2Q+gRxN/51JIZ7RA95N/AtyEletw97Hm5yAnEcwvz97k0NS2oJKTjODjJeXRu81zzex/dCJp33Q33hfJ6r20XvAxzp5NKHJu4NkPxyoQITdmF+8kKHPY7XLXV4w1DfAIHjNoZhrZ7m9c8IhO1HVZ5GCgxs9VNNIwYE8wZnFJgWSIYx5wci3iQ0hhDzZPCb3crEe02eRMsdD8dt46TtR9llY2HkQ8hnlh9AxYu+QGiop6HINAUGpv4ASMrSbELM/WX0WlAHAepwdBBpu/S5OrpcaGYPiDG7keinUBTO2gO9lkSDmch/5l+D76segiK8I3BuYTJAJ27c9rqjJ+QLifcmjOKiFKAIzT2bO5ykikOTiB7SNnMehGA6fP9vcDQCxDQLN1d8Bgu/XHIDMtARAYv3tdHHg4Gp7vKsOQKDySwxTyDU3YcK27ZpQMnQVNVmyRHOuhyIwFS8xLj2abEYkR2WxiAtXSmfEpVDKWzYoYtnFJd9DE7Dy2MWEZHIaOPc7Nq7UCC05DBnh6Mb6txsbIIRyr7h02WRgocfPi9O4ynU/Jw5OLYgsLFJ6H/07tvWZx6Uv7N7saVIqJDUO44kruSeKxFw0AcOZZe0mpFaur5EPJvz/7L1bqC1Jmh72/RGRmWutfTm3qurqy9w89FyskRGysB89oCcL2bIRCOvFthAePUj4xQ+WbYxsjEAPvmAQCMZYyPNgyXrzYA3I2GAEAsluzIylHkbt8fR0V810V9W57cu6ZGZE/H74/z8icu196uxT1TWcbnbAOWvtXLkiI2NlRkZ8//d/H1jz9OaN7meDg5cBIpbtDsTyHad3MjthX84bwrCqvqpxA8xnjPiytnM+EfUtuVAIaajHoygXy6Tq3rK8xJ3L2ztYaIaolRsZco1v6fE2AqpSVkOMWtTRYgBEEjdfzCA0LTvlJlGLSh5H2dNyFprcDQBi7puB1oSZEsNNWaag5hYGSJ6BrlXLINaSkyxnAhB6OZGkbbekIQCYY1V30r8pi1KWpYK3OR0Ua76FRUP8mAsKTxb6jFluHGvuVNf4BcewtTQzch90P4l6EFDxFUBwAyIJkY6mPFUf+200xAUn+8RYfDl50rU7S/i0RBJGwQlyIDAZNiHqVDK4oFmqEtzEoJ7LVN0fUlGPOo6GuCgRBq/p3wUKmCP8XiMaAJwHIghhZISdbAujDVi1rSkRkAXP8BPgNQpuFAj2VCnvBHS7DGK36LOwB8JW8BGrN5BEWGQmU7G5HAE/Av2Wy3SaEuDeALO4j4bcl/tyX+5U3t6ZxVFplyEUAth4EqpZQcGDDw0ZaBiEU9D1jZhLM1NZWRKXuIrndSeJSfpULPMVAx4BeaIPA3g9FPKW2w/ImwFuL+wXUgLXfNpL50ZXnlx5FTBpcpGbEuJG3ndzwnwSQMzodQaRhwC3n8F9AI2xUHz9BetyJpQMRljK8qbH9KAmkg3joIlYhHSmEn5lKeCBOSFvVIFalyPTg4BO19+kT9McSJYeOqOYHnj0lzJltqQkMMAhw+9DfSKayxgc4iaYbCnSRhzIbcoNoCzJ4toj7H0Rxp3OO/SO4C56TGe2VCK4BDXJqTPLw+O6BCmAI8tTtr/OSANheGlLA1G7njeEjS4Bp/OuEL5yQHEbB6QPptOaEm/yeP0nAw7vMcLelf1yL8uq/XuyT9iRPJaZMJ9ofT0AYoQdwR+A6Vy2x+87+LECnfLjALt3POIJIexrstz+XcLhywl+9mVmEU+AtDL8S8hYcj0JxyNeUjkWJfxomgwtSFkx3gAuOaZmmwfmSUhZ+npchzs0pCzn4Iwj3+Ibzi14+yACjyNoH4qeA48jaDeW3AA7VtjOKmGfC+joDkB/qSY6c0ZQWXkqBKEKOLopgZ0ShphLCrToQmT46VDk+IuQbubiFAYAtBtFYXycimamKVxhFuWrkj2qy5H+IgrhCigMTEeAm+uN019qqvOcwaSDqxkEz6kqbDdR2bBPsjQD4E2hehvhr2T+7ey8x7BYhvSZCwGtu9bvT65M6fMgeAQg6//+SvQujdlJiSVkODH83GBdidFfJYBEcxMA+hcTwvBqUpYfPbpLXQIo9kS7EatPCKuXCv56RlwRhssqqeBHACR91G3rYENJQFR/QAmdCikrI/cOXlPNc+eweZoQtw79i6n02erpGmnl0b+spKywI3TXXJYhho2kjhAOjP5aBijpA8Et7lre3sHCtChui2YcuYJzSiBzN7fPXydx3vIXTPMic+UppCSzjpwLO5Nu0Rn4tPopCdRd8AaNFBBUK8HAtjkJhyCjkcpjYYr2nRy3eKtGaeMXtIAsehJQnIEJUI6Fxfdz7wQHiFxmAJQh7xODUuNKDijfpHJMCo38DcN5BbPwXNfjTSqOXPza9oajAMUhKNYBgGIuvhluUgp3K1bzBoVSxQaIZGYi7dN2J67hTW6+wwyKUDZqPUcXWXkdFTvK3c1blbKAlm6u55utb+xYuemHz1ne3sHiKGS5XIZ40aoAipIUhdAQo9LroyHW+XOU7L9eps+8qtEB7sRLg5IpKfm7R0MGqY8aL4zce4lWkDxBS+QiZ8R1WACcPHjw3OlrqMujLoAHL8uvLyIasvbloqDoij5DGipVOm4cmALcnBFPjKYt0313aJS6Zo2GZDHRsUEzrVXxivBG0ZC4OVqGZEbqqNwo8ynBJY/sUZYnlBkuybQ+9YRO6fAUM+LGYTp1WGmfpcF9pmjIdA7MF7YM0VlDphJ1yKECjvHErg/pAD9KWNP8R+PGwXnJx3EWjg23R0PmM8L0UGYK1gdpBYC48S6p0ZA04nNFQ+4BzvtyX+7LncrbO7P4tNJSisumZlvmql92l7rakGlq6tClUKGWv4mpMrNO6QGbC1JhCi2PayHHhQRglvRyzn7ZRluufJHDfBtBZgaDloY0bKFelOkzsa6bc1OB0sUlzNnQqjMvGI5v2q4yxebmvX3ODOKGUFW+Y+2tbSjLk885RT9uQ1mSHLX3xn7tdqvLljSp6e9XMXb1u2XZYefL9fwWffM5y9s7WBwJgNzIOuWKLTDf8oO/jmdRsAFbR6cl9wK2Zm8GIc2luBPPwjIwcxbKNwBQhDeptjnB+YpZhIPyMlKzrjcJtTbr1N63mpQ/QJ5F2KeyhqeYwd7BO15gFhxEd9LNuUQdiCF6knMqA5loPsg50VTPwabyTHgjnkXlODgZpJjhYmUvdgMh7BkcGls+vXH8QfJYin5lzAj7XEFkKHFSB5A34Vl010C3N4CT4BKh2zPStezkx7osqFwV4c64yXgY0H2tX6nkn+QMdDu6wbPotozuUk2FGiyk29Zlj+Ws5E6YnZ+HZ/F2DBZEwmZpla7Ul9SUp9LHn9TPWmFe85iYJ9CpOlaNE3i7lQFjaiwEm++ZXSBiBJJSkZmrJeBmJZhFTKDC9iSwie+Y2tT+IPiGbbeL/HJf7APLk2FyCAagjhO8paGPM8ILXZ+aLiez5oxYXxgCpolWF/viw1Ec0w5jMR0GAN7uhAUaY03CMqUoVb4yBa2sIG73fF8HJmu7MUl1IPT7oAMWC0YBABmLgUIapNL6c4TfTXWw0P5w20ONzujA6cyfxAbN3SjWh7s9+meqV9JV/KRVJw+7rqS/t7ICYCXJtU/onBH2EX6kEhnzL3fVk8S5pX+Hd+j6IP4jQMWsrrY4/07E8KzaF+bg4PcRYasanFMu9GsDUXMgnW3JALR/V/fdi1UjN/aJzhG6Fxl5FcTXRfvs9MMThH2H4WVsQtBLHY6Whh72Ce6QsDbfkMyFTHaX8nYMFrcUaoV2bysmYOtdpXsbWJcSckoyk7DX47LIp6hMyTZnhFed3PCWTxG0TdNc5e7t76PwbKsxsUgEsgvQuXJDFJAxMXil0oJE4E0PmqIMWkXgZhBAdpqqJker/L1vbohplpvJjJl0m5x3LrMvADUC0io/ZZaIDbMa4ZhMIavNYGxuQC4DRTpVc52x+Zy5ius66ZfiPo8KDFMIokXSLP14nhcK56U46OCpszlVyua+odInRrgay2CXTnQwniSak9augMfuxbX8Pq1aejkWAXOoru/2e0xz1aAAJOfGiYFy2Okgbn07p8KOTSsPP2ekTmY74aCDnwLiqavnxb1D9/ISbgqLPvOHhDD6wmYFAB8ZfkzgQBKtssHCEcLLEW6KyIdQ+vZ4Nv1p5R7gvC/35b7cqby1MwtmARZvhXYaHIFJlyHmbg7call/ax3AUuORCER1Ck5zkqdLo51x50kbV4C05VkYm9OmmoA+eVQotmAvmhtAyerRaXlMNe34iygtyMpc08wdFcNeyVuQGRyM6JRU75PEug9Ao/YVlyK8n0NDUt4YlqT1GJeABGdxVHEMw53KEmisOFHugxDJPqeOpotVW4QY4FnCxTVvpn5WdCzUs0N4FXVfN8s14zNqf/PtaH3RuYjNNQYopwXKR9J9P9cZSnlrB4vXlmPS1VEm6huX275ja9/XodKfVqdrvveKV7Z9mHEjFf22oMHrCGefp7Tn25ZmoFv0Q6t9YfoJx587Kmv2G997g8K3HfdV+9jHR5aOZbAu7f5sbVkes63/1W2i5lEjCXZc3nPzfaJluz7t4VCiSlz//qKujtcOFkT0NwH8SQAfM/Mv6LbHAP4nAD8J4HcB/BlmfkHyC/y3AP4EgB2Af5eZ/+/XN4NxQ9E7JRkZb1Pzzkf720xDNSnZ5No/rRRHsrzsXIOlx0mehtO8DK3etdzmhqY/JDt98jTtZ3PYmo8wA3MNs3qaCMYXUhpT4nIemmZe0Qm3aB+AylZt2kaz0vI1KlNmaJ91ZmEzR+fKbEIydi1VU0ykmBtVr8QlhAsiuEb31DEju5rq/1kLZVQFLtSISg2NW/vqFnPtxQAAIABJREFUjLhkGUOwA6N2+1FmspnrzOxVWIHVYQI/cnyZZXBGE7r/gURO7zSz+FsA/jqAX2m2/WUA/zsz/zUi+sv6938I4F8F8HX99y8D+Bv6+tnK4ilrCUtJHMA0F4O6TiT++24B1rlhEDqCvgIo+Q8AwKcb+f5hkqfm6VpuFPMc1YEHIVQQzjvQyQa02TR6GAQ6PyttJd4CANLjc7jDtBDU4SEgnQj4Fy4PyGtNKtuOiI9PAGZ03xNxgnwywG1HATzVARwA6OIavBpAQw/a6UBq4dChQzrblHP0L68FcBtn8LlkMNHlVs9LIiwl+qJRkfnL53Am2JsN9CXRo9CLPm4Cwl4Gc9PnIGbQlOF3Ux3YgpcnXWbExyfFoyJpAh3OV0WhPJsIztCBxrksOdKmh9tNIADTlyTalXqn/AhB/21qPz7w6K+yqkdRaRewgj9IzojldlByGJ+skAfCRsHJ/GAN7p3I6gVa2ADCkbBbVfnc3NB7AC+/3uPkI1/OI3eEbituYUANjVIGZtO9MCO4UT4/PJLtD4ASOi0KXp4wvrNGXDusv1/77OKnN9i977D5qEkkWxH6LRdlLhO6SR0QxhW6bVUYpwSk79yd4v7awYKZ/wER/eTR5j8F4Bf1/f8A4P+ADBZ/CsCvsNy1/4iIHhLRl5n5e3du0V1Kmz268HZoQpyTXMxsM5SjUp6AKQmirqHUG9Z7R2tBzBE8TVV7co7AYaxPe1t7HiZ5oqZcIywHbjJFY31ixCRq4K3m49Ss+5kXswlKSdprxkH2dGdeGP/iIIlkPM+gnYZ6beCLYkZTLAVNz+K6hjiNb0BEi6dv0FAkxfp9Sqxof6pRDyOmMcPv5wY30NDpIdYBr+GcWL8BgMsZdJjA04xwrZyMzgl/glmUrZqfKGyjqH01KmKkeha+4S4gZnTXESlVUZ6wm9R0OS/o9IDgNG7q4HZ6nViy3GHE6nlGf6GDiFLju22snArNhaFcs1NTTyW/xY8MJrWgsNCpd4sISz+OCHuPcHkofbZ6kZADYbjIlWuyJ4RdrolknVHOCWEv4eKwr8l/lktzl/JZoyFfagaA7wP4kr7/KoAPmv0+1G335b7clx/y8rkBTmZmotvsaD+9ENEvAfglAFhhcxPF+7R1rfeVtBO8rGFDqBqPgDxRXSyvABYp02YIbGpQvOplJmLT/d1B9SsdKOmYqglk1Pd1GTJNwGqoTmT61MybHu6gVnKNrF7a9AAJG92WAA4y3QYzumshTeVVB5flO465yuqNk/ACnCtdRs0yJJ+sajfNUZYhRGLH1+wLJT9ZG2xWFs+Gxs+ESyIZd66sy9MmwI8ONOeSFEaZ4SYvkQh7BDVgYtp0ZUaRdPmV+1AuQD5ahtix8qaX2dJuj/lMDYx7JWVl8Q2xq28696KS5QhcKtaIwyxGP92VNi04zGcBce3QXWpi27p7/TLEtDdtGXIxYP+Ok2Q3AOxl1pA7wvhAZwujq4lkugxJvSwT3Cy+IoeHsr2/DPCTLJlMCVyWgQ5x7UBTLn12eOxVM8OXDNc0AN2K6jKkq8uecCB0W7dYhrR6IK8rn3Vm8RERfRkA9PVj3f57AH6s2e9ruu1GYeZfZuY/xsx/rKPhjQ5OFqX4QUUFjhF829a+foHllWi3O3pvCPkX3CZD528g+8bmpObv5jvH+x3vc6OuNy0k/xZq483ftV3HEYYmQmJto7Y++tSIw+sKL/qhtqO8f03V3LSl/k2Lba8szTnfaf/PUT7rzOJXAfw7AP6avv7Pzfa/RER/BwJsXtwJr2D9r2X7KYCZLi8BoNoZdgEcY6VXE8F8UNPTak/o33ki99ZmXfMMhkETzurTHvMMzABO1nWNDSA/fwE6HCQXx+wL5zVoswGfbapSVkzID07gplnQdj1+7EXEZcGQ63xJwQ4XjKRPqTDN4LABQMDHz6T9Qy/WiOenoMtr4Fyp7M9fgvoO8d0zeNPDsByCxh4RAAZWpuV+RnwoM4vOZPlVWNdAVr89A1jsCLviPVIFY1PnSl5E7h2wjbfcoEcU7racr0okQpigjPHJUGcUppS18vBjX3Qy5tOA7jqgmyNSXwV7XWSZATR55NOpCvY2hR0hrgl0IeLCm+9U4+jpQS90a8Uhdj9+VpSyUk8Ih6rVkTvCvCasXpqil5Pz3Z9jegDMl/oEV3Vvl1yxJMxblJlOEeYN8q+/gKTUF/cyoWQfl6uf2SBuAGCFfiOVjecO40MWu0I7p/NGJQwoKeppAPYdoX8JTJJBISnqVVjtteUuodO/DQEz3yGiDwH8Fcgg8XeJ6M8D+A6AP6O7/xokbPrbkNDpn7t7U5blmKK9AB6n6nBO+l4sBZs4tlGGX0FntQvawqy0OyzCklnrBLA4FoZBTYR1GRKjRBtiXIQECxDVUoZzRjB7wt2h6kbsR4SXS6UttzsIMLkfy6u1y+1H+OteLBcBGSx1oAot32RUS8Zpht/6so0daVJVujG17F9O1eqwkcfzY1eT0RhFrcm0Fazulo7clhaYa5cefqvnEPTmm7KaF1XhF6fWksUXVZcKN0WOevSXN8PmqXMCfPauAqoA+pcr2baVbf3lCn4U5ay0ciXHgrLqW+xdtS88eAF/54yT32esnxoYKQOU3yeQhjzCPpfpvsnxsZeBpd9m+JER1/rgUEr2cVk/HxB3hP4ylgS3k48TiB02H9drvNtqYpkWG4RSL8rfqxeMoCkBkmh241CvLHeJhvzZV3z0x2/ZlwH8xbsf/r7cl/vyw1J+aBicC4ey21zIjvELchXbaPdNLElCja4mgGK6s0j6uo0laolhtp9zAja64/pIwNF2RtSYALGv4q/k3cIcyD4Xn5LmtdQjpj901Fb2VE2Mmrahqb+tl5vkLnIOyFlNbCzAa09L35j/iGqUaWbmpt0uKiB8y/o/N6ZIi6WHKWR10q7cOYUVqGynWc6jmgyJERDFXMO0WPqCLI6t5kA5uMXva6ZCaM4ld2JglHvRyAQUCOwcck/V86TXjODgRKC3CVGyFx6HGQdRruK7xntgr2DoVJ/8gNTH6Wb/GWiam4zb1BHSquqN2n5+ar9Xt4tPChcRX8q4iUt9SvmhGSwAvDmg6YQjwOVGlovsc5WjQaakYQNyY97mlvZFlBZENDOfI/DT3KvIueVFccu+rTvaH2RpwdIK9BFa8sRtjm9fVFuYZLBYqGsDDfhYwVKm2wenL6S0wOlnBPaPbRXfFAx9aweLhQPZcWl1NVutzXa97h34eD2mlbEZ+Oj3ARRNysKU1DrL+3bf4OsTmUiejuaZasdQx7B2aGo1Ml0XFrqYtr1r2lP0Pu0VGhIOfuHwRVER/U6czYppzrY+kQuJKPgKcCoAqp0CAEWDEkDVwQyuALOA6HS6UdrbbgdUjyLcvKwWDmp63nHliyitzCzkie2oEMpF+zNmwFHRvbQ2uplKKjoAzBsHf1i2R/YnuEncxoZG+NYcyHrdlgeHNEjYNXVUFLeZqdgRmh1CWtUBeDoj9JfWV3XmNJ3q9x3BJGNbgNPyw/JImDfWpnCryFtcCVCbrkXfExDN0ekcmF42IO8Zob3obBaRBkJcq4uZhk5dqm24S3lrB4sbGhStQ1mjw2BKWHSkW8HM8pRvn0jeAzkKbdu4CVbnHBcKWFZnqUuPVfIk2notwtLMLMwxbKEI3ipZzXGhXmXbC5iq6lsUVb1c68kpwUWV1W+c18k5IObqeGbt0rJwXPeqldAobiMId8Uf0iJ/AkBZftj2sPfl/eInOuj5xpufLRzU9Lz92NeMTJ1ROOJFHomfcqGdtypV5kjfMhC7nRMa+vGxsytuYy0TtjiQ6TY3s6iCRQZ1rQyg1sNidyB/6NLDEforRrfTQS8Q2DPCLqO/tggHNxnG8nVbhnTXYlVgA4A/1OuiLX5k4YxMXH7f7prRXwq9u54sFn8nw8AngAMh7FEGLqeU+buWt3awuFEWyU188/3x4GLJZsd0bXttk3ugN9PxIHBrnTow2LqSNVHJtmsRO7+8jMakVKwG5DOtP+VqQVC+n2s05ziqo98tCVSZAWQgk0QSyn6WiNYMCsdJYkWrsqFt24BV6OcJLro6eMy5GUjqk52SKFzdoMy3/WHtsnqsP3Tp4bQtJVU/atsbDU8Xc4mGUDP19CNXOndTmKD2hXlho2jb0JxX9iJcI+db+8TBgTNKSJeNzJRFGs/k6yjLwOCmDD8ZKYuLmY9NHC0a4mcusntyvnlB+y/nNsuA6VLtBz8z/IHLsQGRzmv/rmsNhpvE6tBrZLu1K7hLuRe/uS/35b7cqby1M4tPxSy6AJqm5fsuLDCLhe2gFW6eekZznpTqu+plitpiFvZ+OtJdND8O288rvkEkJC8oTTnnxbSXVwPSqdoFHvpqHThOZbthFrzqgZ3iGlPFN8h7oXWvQp0BSEOETr5ufEMO6olChDxUrASQCAcBjXuYPGHjSfN9I3spZuEUp5nOO/Taty1m4YITzcxbZhbJ+kP7BhDCVTHutSjDoE5curyIG4/ADJ+5tK1iFnmBWRwe1ezLxbGV25BWHt2qspDiSUBaeQSVMoxrj7h2cFEjD0oCE5MfQhxceRLHtVC4+xfA4QkVq0PDLLqBsH8sx+12/pWYRe7FrtAwi81pDxxuPsOnUycu8aND2CY9X7FI9M3+0zkhdc0ypMUsNoAfCdN5xSx+JOwLb9XNNBLO3Gg06nua45FLeoM32NS7CZvZurC4jR0mIVDpNDU34r3tsZCyfDfUaX1R226K2021zqb4a1+OZxmiNM7w10vxXXeYhOhlhC9tb04JbpwXWZyImjk7KsnJ1sdT1Ol7KqK0hZSluhXuKAoStvEGKYs8wcVKyuodlX0sJ8LqpnG+VU+k9AdQjtldh9quWcKapKpRtjwJzILn5FzSw80N7ZiUxYHQX91CyjoIKcvPuQo127nOuaTnh91GlyayljcNTRH8JbiRSxsoSvjaxYzVM8ZwcZOUxe4WUtbhdlJW0BveX0+3krL6qzX8SOiuU/ldVi8ycnDFOlH65lWkLMY0EYYLLpaFlPHDa19orlis9O1FUYFbNwzI41i0KTIAnqPaVRyt6x0J2GY3+2pV/uYLoZEXtqFZIlobrE59b8fycS2sTdtvmkG7A3icJFTby5OLn75YKosDQBfgt0Id58MIKI2c9wd4HbSSsUZfXooSt6bEtwKxfHEJ186cVAmcxglu5yqYpraHlDKczXB2e+WfKGBsYFoXACJ0Hz4rs6Nia0AkAsnaRnfRF6EhtJGPGMG7fQWNm0LadmsDAHQmjmu/r/FiiCrAaQI7zNI2QMDYW+wtw/PVYjCwYpoeCB788rL+HNo/fCnZZX3fyUwrMcJpX0HcmKvMoZ531wVwJ0mMj795BXepqul2DnPE8LGaZc+phKZtJsc6IyW1PSjpA5+8vFUWctMHaQNzEU4++60dNr8/IFxUVmruw2KwKZwW73F4f4PhxYjcRMBaJfDXlbdqsOAGRXer1QIos5s6XV4ivP8l8EE6iNZr5Ost3MmmbGNF/Hk3gjZNqOzps1r/z/60vF7vhAz08BSIWawBAfjvBtDZidysKp9PJxtgnMDnp3WJ8uwl+GRdJfV1EIp/9Gfgt/NCkTqvOsznvSDoz/aSaQqhQu+/fAowY/ObUm/86mP4iz3yqoe73oM3cuH5pxdI7z0SWXgVQSkDybrH/Hhdjtd/vJUQ735CfCK5JUY3Rxfk3NbSBvq25Ptt/5WfK9Ncl0TCnr1oNFjkYTrz6K4TXORiKQiW6EL/7LAASEX8JmP60mnRo5jP+hImLRRuX5cK/lCfnvEkIGwjug+f4eqPfkX2GRrxm+YK3j9xWL1gFb+RbcTyvtsyUk84/fCR/hiM3VdWiGvC+bdl23TelbyTHJaS+hwI84lDrzOItJIDnH3rJb79p5/g9IMz3U8IUP0VY/+uRkN2msOSxeUckCxQJiDsIS7qmq/xzj89l4iWKoRb3+zfDZhPCGffjaXPfv+PP8b2xzNOPjgpy6+4Afor1KxTW4b0MovoL0NdhkRg/tbdYct7gPO+3Jf7cqfyVs0sFqXlVQBLZqT39W8jZRFVjgNxBRzt9aiOQqryXvUafAEJ5fjC4CPfsDJVNwM6BQUghsxdQ0QymvLgi9KRDcnc+UIs4s4jDbpO7TzSoGQbVynN3jmlRPumXUKR5t7VNtg59WHhBM6dfE+8NJoZhX5G+h3rB0BNfTUcyrP0Qw4kJCQlJMWVZHey55IYJcrVrtChZWPVzEy9E4UrKP2alNjUV+IXoOAlV3DV/DUQan/Na8kMdQlqjGxgKCHucXNm4eUpGodK4qIkpsFxVYHMtHIl61QwhnouOchx/WjZsVT6MZ5y0anInWRyugjNEpVfiD0ABuZTra/nwlZlB8RN7dsAAU/L0kUzZ+OGFn0WN0A6SyUJDQDmM+VskBzPZhZ5UBf5SKUNbv4RIWXdKLeGRbDkUbSlcCIqweeGyK++UoYAlTkDJnTT4gHtd4rEf8OzyHlRH4DioSniqTUmX2LouSHEqDNVG0UwYpKJvCzqZ1aA74g7kStvoWzPpNv5aF9CazFgfSM3YUNGYpZxuInvu4SyDHA2njOqT2fbXyTTbxGwbc6NUNLMARQavh2nbE/1XCvPorZhEQCbpe3MVH82traJmzq1v3tatllk+Q30O5ac0wEq1jZYf7oZzb5yo1KUf4C+z1BSFZr96vGMLepKe6TfZE+R9rfjUNMGmpz8Bnp4P5FkkupgUdLVHSkfBJVnkd6MZ/HDM1i05TZfkBvamcub4LjcIL7ojVHqMaDN3gMo2hkp18SxpOvrI1CvqDtz9T4hZrmYdT3Z3lhmNFw1PZr31j4029qBx1iQMVdDYGsDKTEsH+2rgHEla9UbZmFg7KhGCLipl63NdvOh6Ttrc0O/z82NmhnkqEY0tO2A3DQUa3vNR6MdXNvBqr3Ype2l80q7bD9KWMjyC4OxaWMU71S58akOsHpKfm5vVCp94WZqBgv1SdWbW85BnuCUAW/BGol3yyDQ7NuaGVPTtX5m5BmLPnMzQLPUUX6bWY/n5Hhl5kA62MxcB6ZYj3WX8lYPFkR0KxtwkTXqnNzM3jfIeLNMeUViV8lWLFmYBIYvSLEnknyMmMrAwN7JdH2RMaq6Bt4f1d/YFjaZrRZCkwzIZnsnAq6WA2L5HOxI0H8TebG8lEb9mbIr52Qq2aUOy061vmkyPym7JuvUptHNVJ1ykdVLfQU4cyDkgYCpyrbJ0kGTr46T0pzWu8gwVVDT+DTNZzIwNTkjqopmYGbqSMbyrMK3ltfSkywDPKqsng4Ultth/e/ISdbmUJdAHOwYKmDTSM7lQEgdFeamtYU9Ia24ZHdy0Dp1OQIAOdbBomSBrnSmxfK7Z1sudLIczbccO9vxLYN1API6C+Br4/AgyyubWZiKeGrqt23iV4M7l7d6sPjUcjyItLONVy1Zbvm+PD3r5gWh6JgSfhv341MKMTTe2h4XOgPlxX42TW3pyHJOHjeWQplxa7bRD7iQPuUY2t6mGWbcVpJD2ydiWWrp3zkv3LhoWdVnaBcv3/Px5/USaNtX+vn478/TmKYufbvsk6P9jt/fWAZwM2Nql223FGr6vL6KNYLNXn+Q5T4acl/uy325U3l7ZxbH+gU2zY9KyR7rtBzkgKGvCtsAaOiBcSyvABZkIXP6plkySeNZDzflEk0IRSDG12hD8CD0SGcr5F72668PiOcr9NfK+9CoyPioAxNJRETPJZ4EHJ5YclGH8aFSsKeM/WOJApw2+/qtV1XsWBSxPYC06TCfBfQGqWjUJZ722L9bGZX+IO0M3mF83NfzBZB7idZEpZkPnbzu3nEYVE/SzZo23pFSjeVRdXjsVOBF0qSlc4BuIIRdV2Tfyk/IrihdA6LCzWQp3HJc04qcNw7dztVjPfKSLfl8hf0TiwJQAftMTAYAdl8VVe7jaEgOQP+SkNbA+pkB2MD+HYf5FDj5vrRt+57XuoXeHXb10Zw7YHpISPq7G217870V8FNb7EYzQGLkXmTy9l/TLN1Lj9zJDCifK7FtlUCOMV308Nce6bGAFuOHHXIns13DRdgB268S5nOG3/vSZ9sfT/jnvv59fHv+cmknPZowPx3qMmSjnJlNxDh7TE87xHfMCZ6QV3effry9g8WNZUbzd2NWLO81B6PJKuVZdTrnqtfZ1uF3S/qz385qRqPhvpwFr4hNOnxMwDTDbye4yawAZoTrSWwOUQek/iIiXE9SXyNEPARZT/pdRK/4gj9ErC6STCV1ORV2YtjjDxE0NantKcPvZhCzHBd1ACAGVn2dLIZrMc1xuwm9yt37rVKuJ9HDKFNVJcStXmR0W4uMCBgbgoRK/WTzYqC/kvRwlyobMOyFml0ySWMupKz+qtK1bT3uJ1c0Mw038AePsE81e5SB/moGHSasXsjx4x6afVnX5IDgBcNzXq7FGYCSsuKe4PfatswYXni4iQqte/2cEHdUSFnh0AwWQST9jVodd1T6OH/wACef6H4dIfeE7pLBLuhvaRgRMF+pncEgum/rLcGPwDTJiQyXkgbProKm7IDNR4R5S1g/T6XP1r+/xu8MX8L6I19+x3m7Qn/RWAEMlnMT0M2E4SUw7jUnaQZoujto8fYOFp+mjHRDJcpAyruvqrgBHQsg5ysoSc6BuyB5JyGUfe/atUy6P2NhQweSH599ldTPCkxSRvEtKQAnicxdqaMLCym5H3hplJRELUpeQfUmZ1cBOEuQIiZwEMYm69PXWR+z1tN8/7NI1ttsgZ3UCTCyb/ACZ31b22pRJvvMOBVmEZjDUpbusxT2TYo5aZ+0NA09NjWARv3ta/TC/qbUWBfi1cle7ACELGCuja2EojjGqPX+IACHt3ewOCZlHZdiVehqmNO/AepXOlFIT3DiaV10CrxEHWhu0P3wJvVTiVjYhWQ3HwgyMDWRALk4uByDHQn13JEqX+u+XVjqhP6ACxPqhc9qMqTJUUz1SWceoyW6kPSGcY16lYG5GoI1S0EOdbB+o7YtBgsAEFWrEiXXvpUBANouAqnBEDeS+1DiU+6wuDE/S2EbHKxt1l/O+ksfEnYjQwYYGRRY+1a2Z09wXqMmNlF+xWDGDnAh3xisJNKkIPTR4PR5yj3AeV/uy325U3l7Zxa3Ea8Wn9vck5dsTdv22vrRfF/XsYylctQxUetNQqdtmxqilU2JkZtQYja2Zz0GqTIUO8axupU9qb+IchyOK8diXoYdjaG6IGUBraIVaeYvJWGyVvaknN+bnkMbei3Hyze3U2Y4UzJrQqgtEc76+03Vom5tV/v9NhzL9Xe/GUZdfmY9UZi7iaqc3ysm2BIilunKcRvqvzpL/Lzl7R0sGp3NG4W56jyqaIs4jZsmRIbrOiVB0u1hdEPLYwJnBeI4l4uJpxl0GOVzy3ANvsjwl1wNr++PlgYcXLlwKavWQe/KlJJS1cp0k4CbTCgmOBTP4LYj8oO1AJHGvNwdQPMJ4rqHPxLbzZ0rUQUAIuDbOVBwSLo0KF6dnfA3bMngjOjTAQv7yzLFJ8nRgAx2fhZ03zUXslzoQLgaF+2SAXgFmlvgVAVom3wRQIRqKFcx3LQipINoXZRliOZZHN/oOcjvShmgRlou9TWyYRm1xAymTkBaFQ1OD73mhggpq+UpWEQoqUFPmxvCfZXNs2xSDpr/AYBHXRYxkFb22zCy5xJxqrqYgJ9Ul1P71k+M7fsB80aiRqnYETBcVzjhcvyBkRu7gTxw2c6B4SaHeGIA9NK97HXl7R0sjjGLhVZFqozEckFWLQoCJN2dubwe10FjKt+nDBGbzbmAcgu6t2EhRMBhBO2nSpMeJ7jdVPUd2C7KCDdJZMCsCGjK6K6TOG/NuYrL5oywz/IkMBXvJN9zFunQGw3Bg7KIsDi13bMUdQ+gbxLJ3G4CBQfaTwhbDZ3uNYISJYJU9tY6hssMv7cUdbmpXSLNo5Bz668z3GQzHx38VBvBzamyQjUsDSefldyOWR57dFHFZFhFYdy0TFG3vqRxLqIuLqLQvXNH5andvxThF3YoTFZiSRHv9rnONgAgQ0R2ycHpQNxfJPjx1Snqfq4p6pZQ5nYT+qdnGF7agC03dH9Rw7pBk9soi1KV7KcRoVFS1O1u95NEmdhVujl7wvpZRjgQ+otU+mz1fMD16Qr9JUof0OyWKeq7ejw3A/0lF4vHBc38DuXtGSwawRMAMt32Hll1IhZ06pZObPJ3XVfFZJhBw6dnnRb6tJkGBQeONYTnUhOebZcfd8067R3ceEz3puLXmYMrT1P2Tii7JvSi35GnHylj0x4dCoh9kVmnlkynFy17uQGKGf1A8DOBIpUbgjIkW/X4d9RzyYHgjVKuUaE0vGHWqR4rDqT5IUb31natgbinAjICdXbgEmE6I2yawS0HQupRgNfPnHV6kkvmpwwWkjBWs05R6N62zZ74QqVX+jdkhuE0SuOa796adboG8llEXPdlsIinsgS7oWcxWA7LD3vWqaWXc51JUN+Dpwn+3ScAgPRJFa5BSlWhibkI1NATETGhaUZ+eSHKTNfbotDUkrL81b7URQDchRjm0qww+sNz5LMN3NUOdCq/MPcd8OwFMM9FGo63O7iUwFv5vh2r/2grIjC5RjjoEFX2Tp66reT++qODGBU/tBxmRjxfwcWMvBlEIg8An65BKaP/7nNAB1JTVvJdh/XFqvbh1VaiOvOMXpc3ZvLsnAPnDN/J+WYV+Dn9zq7iEImrY1io+SWD+lS4MaG71sGmURBPJ51+LlEcd4joLucyAHRX8ptvvrMryy6L8AwqymPLrm7Vgw4T+OVlEa7JnSsDaQ51vb5+5uD3Gbld7mUuS4+Nq7kdnAmrFwlhdPA6yzz71rUMwGrrUGQLIQM9D12ZzRVlq4+e451fP8f6E93uCGnt0F1GnHxspDsBJcxDFdA0/1kC1O74AAAgAElEQVQG47DP2CtZr9vlsvywdufe4ck/2SIPHt3T2mdPHn0Jq2cdVi+arGcihH2SwSbywimtv4wI+4ioOq2UGb93fXcs4z4acl/uy325U3k7Zha3lFeCm/aZzRKceHZSG7X4NH5GrUReMwNIBaAsknBZhG4XS4O71KuFLBKSM2C6Bl7YOZw1DdvSpWO+IVRLqbJJZYaiFc8RFL+4n62NCFHO4AiZCSUUZJ3JlZnEwu08ij4GKWBIcwIRST8mVz1TgjGU3rBYJEPT/wkMR65GGrK2Y86w56BpikBT5E1bxM0yAxHs5fOFQ1o8B2TRn2XkReUrSkTIFR9Viyrp16PpaLgiq/epxzX8xi5nr8Bz5EUU5k2TIG8rb+1gsfAoBRbWANT3IngLAH0nDmN9v1gr03olF5S+li9ryeeytKDtQdbUDzZA4qL05OcoeEbwReUb3oM2a/D5aWFaEjP48YNyEZBGaab3TkRzMuYyf8tDwPRAczFejIgbma53lyMO761BzNj8rixj4lmP7nJC2gT466mItIbDiHTSI236Gxqc+YYGp7A9aT9hNg3OZ4ZZyHQ/mwanitZef21T6M8lJV2jLGbdN5179FdJ1+CVgBX2GWEfCzBnbXbMGJ+s0F1LO+ezABAwPejRv5Rl02s1OGPC7iuybxoEcHWJVSlLmrB/x2F44Sv5DRpepA7dThS2Vy/q1H77fifRn738DuOj4Q4anNoG0+CcE178PGE+URp3gNC9rzwORYMThWk6NxqcIPks7D327xn4G+AnBWl1icgO2H6lUw3OUPrsxc8EbH8s4+SDaoEQT3SZp6WmpgN+9Dc0OOOv3z18/ZYMFoxXppXv9YZYgJONg7j36k4elq5dr5PVM3CwC4BzyL1EGcxzNHySxU90cpVV2QUBMu8AcKbegQYvT9GiP+CRBzFSTqtQLjg3d4gbATiLU3jnkAZf9CEKxbvvkAdp6xcBcIq8n+IxCnAKEEggDQXOGwLIw0+M6dRmZAx2Dn6UNTsAsfpzQHYd8kBImkcS1xIupIQ3AjhNuk5AWICyaEfYU3k+BdxECwanyN0zQOJqHiyKMTFSB8znVESHc6DPBHBODzPm51pHJ+FRyoTpzEBLKtGQeMp6XgxkKg7s8YRLvezk+MYAzd3tAOd8CuDJiPFqVQbMuAbA9XgFOO2BvP9RADhvKZzU49PyMpolAG/3gHIXaGeg4g5kI3GM4P3hUwHO8EyH3zkC3iHoPt6MhOYId3UQ1W71/nAA+PoaFGNt1/V12Q5UgHP1e9cyIzEPVAAheHQX+rTdz+jsRp0iTtRaz0Kbwye7miA2J7itTlt3B3SfOOGAmOy9zmb8dY/1ts4s6HIry6txQqehXbpWIFel/f21PhEV4Dz73ea4SQcvNVI2ivamdzJdnhJWqwqWCWg71wFoktkZzQmbKZV6u8sAJoLfTTKzA0p4uu9C8XkFgLAaQIcRfHlVVLhz76o5UajLkJPve4RdEpGYIgwkWb0uZWRfwUxKGWHfIW481t/fl/ZyHyrA2UrqB4c8hJKIZ+fonl7g3W88wOZjvca8RHm661SyWd1sAGc1PJKIjvJSxoSDZuWe/t4El4Sebt6u3El/p8HJdaF99s4/6bH9eIX1s7oEz4HQ7ZOEXjMXcSL2AnyGbUI8sfA88OHu7suTe4DzvtyX+3Kn8nbMLFj/a1K5WTUo0qX4cFQfEckc4rI8IXkKUb/wBfHvPAEfDsVXBACcd8JTYK6Yw/4gAOTpRmYZxpN4/gJ0OAhGpOFG2qxBDx+AT9Y1dOYd0jvn8Po9p7oQ8WxAuGRgrqM+B4d4LovI/lA1KsJuVBtAD/9bT6We/sviSXJ+Crq8Fq8SAPz8JajvML//QMKwqKBs60sCAP2zDrkP8LsJ8aGsc7unvcwQgoQGzUrQzHz2jwZ0V1ZvJQUZlgCofeGLCWmoituAuji+3MG9uL7xE+cHawQLO+p57378DP2ltCsHYW3mwalOpKaCrz3CboO+7zCdy/cMV6DINfEPokexfn5zDZ4eevQXCWnlcPat2rbx0SChV51BbH/yDFHrjitCtzesS5YhaSAMF2Z1KO097T2uv0ogpWBmL+zP1BN27+mMcstF5q+1L8wB6C+EqBVP9Pr5LsMd0uIpTinhxc9tENeEkwcBYSfXwvX7HtuvmY4o6W9D6C9rHxijNw2CL62eBUxnWm8G0v/1Q4dZ3FKOtTOdE3SeeYlDLLCJ5jshFCyj4BvkAKSFj6nxNcoa3ijUbRZrcyxWWX4Tv3HeV7q3uVEBhTTV/hQtpiA04YojFKzB188NHzEiWPm8CzetBoiQe7UaMP5WH6QdsdYfLO29cyD9jlRbiUnm/t16nRqWAKhcvdaXGq9TYhTzouPSksgKqWhF8KOt9RXLGQjecWFgxrVEXsRGoX5PVLGrLiegVgC7mxe/HEcIV+X3RSVh2ZIirhzmDcHPFZMAUDU8BxT247wWXCANR1YAAYX7YWAmmMpg0QKcHEQgmD2V7UnxqBvnsBGv0riqmFI8AeJ5rkZPUNwm1rbHlZ0rEE8y/OgwnxsY/yOCWdwGeHIb7jx+n49A0jZ0aZ3fdkyRwOf69w2Jfz7aR8JcnDMo1f1aJe+qVs1YSO3rMaqa9lKev2zn+vnCZqCV7FdZfGpCiUxYyPXL9gxEunksIiBZSLYhtzEv1b0bmf6FFUCss47l8W45Z/ussS5YSNmXY8g/Dho+LHkkKgKTqjR/kc9XFW4rbj6W78eiDhexaNvxNhcZfq71FyVuwwN8FaTxqkHhUoYbKzXbMbQfK5Xazaz6G3UbZSAnuqG4LeHoW85hNgZmjVK5GXAHWlC2/bikcLtG3Tt3YgdglHNKqCH5O5S3d7A4nll4X2cWxzL9xSOz+Y5zQN/Jv3YWMUFmARaWLfU4+aXb7a0FgB6L10OJMgDC6kybAO+9iN2Y0lagWmfTphLVcK5OodvtraGReZLaq33uhCpuzugUVMhl8JJEZDOLdUBceQRH5anMnbSTvYMj+Q4A8GYFZAkZFtVx41V4Kv8AFKdw+8yKqHU3fduU0h/2HjJVt3blXlXEOwJ1DBeNPi1P6XDaN8roBKhYRjuzEAXxmzMLe9rnpg1WT7strmo0ZHxQw68uElInA5kBhmJYJEsySdI6PhaXiIyoctv7+spBGJaUGsXt4MDh5h2cVjKziauqF5I7IK/qcQAUZfHaJ3X7/EgYt3Ft/A+8EWr59g4WxzOLlhDV5m3Y+2Mz5ZwlShCPHM45Awl1qmwu6nMSwpPt1hK/2mNNszyZjUQzR7i9oPdkxwRAUy51WqGpQePnVMhLmGPZbsekOUldc6yv9vkc4fcJbjRHb5HsBwO+kdVzY0LIIttX5P3nJPsrZuF0GWAUa3/IVUOzmAoxPKFsDwdf3re6MW7U8z1yjl/0h76XenLhMlAi9fekxSwm9w5hJ9T4ynuomEUr1x92vJDCK8dm6HeXFO6yTTELwyhs1lAS1xLD6UAUrA3kkCeRPwzXQRIBYZgFo9szuq3xLOpgYiO5DSphC9Eb1QeSH5vroilhK9hEt2dNxAPCFgiXbqkVGpbaoTYDdhHInUfYoib/aX7NXct9NOS+3Jf7cqfy9s4sbimfRgG/UQyraDELMkzhDYbTo0JJMITSktZi0L1hGz9vObbiYy6eEdJWBnnpgwKaZcjSKMv7QimPaUlq+wMopPRsaaudCql7mE2VhYtgVPEvtLBOzVmdyYoQUiV+LQSAmnZ+0WUh7HMLpnGX4hobxc9SfqgGi+JQ1mITr3IeM21OewXk1e6klgEKVIeudl59XCc5TdmmZYp7cDW3pMU3fEWuASwcw1o3LvjGSczVz839DPZqn3u3xAAcitiwpX9bHYUBuhAN1vZzi5XUeoseBRv+4opTGKDswtZdzLo8suJBt4TjGge1Yv7ckKfMpcyyJB0qZuFmae/SDUxSuBfOXR1wm7itOYm1WIucl24rmbX1+KkDXMlcraHOmsVZ+zd3aMhPGmbtqLiPuanFabDYL/dYOJVlT0WIqC25s/OjMrDmHsg9L34D2a8JnfZ1exrsO7JN7Bxv9teryts7WBzfqAZuAiBf2YT2fuF2DsjF31gDSEmFZwFjGRqVe+jkxrftViewPBagClQacoSuAU2zIlV+gJu6Co4CyEMo7Ll+6BDXWkdft5fBa+jEqrAPIH2VNvgSgnXKe3CFx1Gp1tB2lZwL084IzStzFf+NCcgZ84kDKS3bqUx87p3kgOipTKeuhDxLbggAEISVOt+8rEp/6HtA6dP7CnBKO1XHQ5/gcXBwo0RD5pMatpRoRWUoAuLrYXTs5bFFuGZeS5q5lflEthlQnAa1HvQCSC4tBMUjxU9U6jQx4vFJRn9h/argpQOmh/V3MSWs+cy2KTDpHPyBMCsNvFwHR2U+EZr28KLiJtNDIL83YXxRZQmmRxnc3AdJwcy0Ej+T+dRjfmCJftRgKa8vb9dg0eTkHwOczCy8gGleqF8tFbGaxJ9Z9qN5brbV7xmt2hSu3G7SjM5cjscm3dcci8ZZFKgMKJujUICjqneptF9RsmoAzlbJyu2mInFH+wn9ZSz1lfaMk7TTXvVz2k/ormb4XaN6paVvbAL8boabM2g/o7tSiu+YBKnKAnY6b8edwczoL9JNUtaBioIVIE/UTr0rin8KIAlg+wk03pRfapW97LxXL105FneqfTGJb4aFTimbUta0UKm6jZSVel98PdqS9lRVsHbViKq/WMGPrlC4h4sBfpK6U1dvSuNZ+IkwXKp2yCwyf2E7Y/39FdbPWoAT6LdcBuaWlNWZcpXOaoSUxQi6vb+M5SHQltWzHmEPrF4mdNfy+erjgNQPWD+t6wrxYql/V1KWzHSGF4D7jEpZ9wDnfbkv9+VO5e2aWbTlaBlCzXT+LgxOMqd1y0oFaij0czA4oQxOWxbAO3kf/OI7XzSDMw0ebrJM1ySqUX1lOQJA7qWtLubKp+i8ALH6agxO47H8gTI41w7+oPX0ssxJK3m1GUNcO1B06LrwxTM417Is8bPwKMr1pHRvW84AknnL2n9/MAxOWYoYHR14cwZnWjH8TCXzlRJ+RAR7byu3kH0+dV/vFwAneS+Zp29Sz1FhGxQaMlcOTvJOjED1B1EarNZASzGraUlSAkxStwQ4OQhQK65r2hfBA/kPdqIprm3Wj4INMS0BOnEyc4ub/Attj0MxH8q6YqGs7aR6c9k+rSTAF9o2V4+f+s/2O4mHaqPo/YYBprdqsKBBknR4jot0cgALTU5u0s5LCvr1dvkd0+lUjU4AoCePJESYM/jpCzmWJqS5JJYApq2ZtE4Ai2O5kw3oai+Dhh7HX42S+k0EfngOAEUjkxt6cauRSVdb9JqUxLs91tpG1lRx99Fz0fWcZ2mjYi+834OevkCvClQAYDqfrcYnoJjEHEBTRP+JrrVfXguoSQRKGe5aNTgfnoKmiLNvvSw4TmGjele0MQGg/2QA7STRb+iaS2iOwFXz2zSlB4pmqJ232583quWuaFrAVXC6fyEzHHZO2gYUncySQq9l871V8X9ti/m9cufhPnpetp/NSbY9vQAgSWFp8HApYzrvigiQqZiLnqd6s+q+HAhf/ocRw3PVQ3UyaPsx4fy76ik6phI9KzNLvWnDPoHmOvMbPnhZxZaa8nD1rrSB62D6pW8ccPidDuun+7JfXAeEff1+bqJWV18LOPkoFnFhMON7uxuHemV5qwYLyzQFAH9+LpoWCjKyOqSnjz6G//mvw70UPQp+dA569hJ4eA7/XH505AQ+3QAvLsBnJ8BeTjN/76NS/+EX/zAA0Y2Ac9h9dQ03cenIB9/okN59IKbEFzJo5Ien4Jgxvn9asi0337nE/sfPsDFw9vvikPvRv/GzWD/PxeQWAOZTh+378r2zDxIOj+X9yfcTnv9sAGXga39f2vryDz3C5nsjxscdVp+MGB/LDXby/73A9c88wuGhx+YT1bEYFR1/EHD9lfqke/A7M9LKob+IuPqaXLhnH5ralIMfM6YHcrzzf/wBAODbf+4nMbzQ36AoNgkS7/WaPLzHWH0iIbxJxkYQA901cP6dyrQ0Y2XKwMuv91g9l+37dwTMnB4AJ79vTE2pZzoj9FcMp/f84Qlh9Yzx+JtX+PafFvHmeMqaU0Ei7mKz9p/aIn/wQOz8bAWZAe4Z/dMzxJOMd35dGkwJePHzhOlhxrvfeAAAuP6qTNHdSMgDI1zX2yN3wPgkY/39VWkDAHz5H0b8wn/+/+Dv/YZcT25IGNYz9p9s8BM//TEA4MMX5+j7iJwJP/ZIBrx3Vlt0LuFbL9/F86sT/NQ7su93/tefRLeFuqjrsT1w+XMR/eMDwq+flj7b/YWX+E9+9tfwX/zWnyjU/J958gm++fH7cMTITHhyIqPB+yeXOJkH/L8fvYuvf0mu0etpgP+Nm4Prq8pbNVi0hWNcJP1wQxii3aEMHrQ7gMdRXmOlRNN2jzzNcPp6XEf/XGcUVyKrNwyytu9sujtOIn4zxyLhR9sAignd81DW7LTdY3g+gLZyJ9mxTr8f0V2IorUtDcI+gJSsv346wZtz9rMRZx86Id2ocvPq6SyyecwIF4fFua+eTvBjh/6ltkup127qoc9wqff5iNx5+OsJJ7rc6PS8w+BBY9Lv1IH69APGcKU3+8xFtSmuSWjJAMJe3MQpM+aLuq7v9hnDs6lkwxYH+cQ4+cijv9BIT5Tzni8J66eaXt9ZNMCh2+VKaT54DBcJ7nKP0w8ktzquLTGMkXoULGU3nuLkkzplt5IDMLyUB4GpcFNizCc95ue+CNdQFjUuibKgULgB4U30F65EPQyjGJ6P+Hu/8Ydx8ttVVi8NK5xeED7Yvy99fuUwBRnUvnUm5/DPhgwQw18GhD3wW49E5vHdD1miMKrlCdhSLGA6P8XZB7n02YfffIL/dP7XcfhnD8rp/uMHD9A/98UK4IO1DI7fWb8Hmgn9C4/f/EgEkigSDrt6vbyu3EdD7st9uS93Km/tzOJTgcIWYDTPEdcwIrmyG18FZhYykmWXegJnWsTtoetPi8SwHbdxQDdg8bi9xnLkxuuUvZJzCEXbErD3gPotyrbQHOuW45lTNwBQwwptiUQt27ToFvh6TGoySWu7GzKSZoBLu6mkO+dAyF55L3YFsXAMjEkKoFDPCUp0KuxU2Z6bduWGnSnRBC5/i0v5ceYmARCeRaHc9eqT0QCR4Ib92GHRj9kIVNYG5Ug4jX7kpm/YK+Gqyby1fnRDWtgXlmP1tsTiYrnIg85W+gxyQpTKicB9jTyxanY62G9ldfKyz3rGyTBh11d1b/SiHWszC2sDeiFr5Y7rNoc6LbtDeXsHCycMwyr5T8vPLMSo/qMS9WiQadKbnJqbfVGHvg9ebwYhGBekOQRhT+p7ABIWTLmAWHacdrCwY1n6M7Er+5YUapLjlAtsELctyigMwxwIeRXk4ul8iVpw34mTV9OG9jU3XWD7vGrf5XnUtOdUSI4mHiuYguXk5r6GL00kxsyIc3BVid00GhSUM5wn9Rr1CFgMIPJKgjk0tHfWB4E5kuUeZRBLQ73ecy8+n9ljiVlQZWcaw5WS7JtWKO0qA6W6leXQZnMu6eTtQD+sZ6RhVftvzcg7KgNDHtU7NQPQQSGsIogY89ohZQ9ayXWeVgGUZX/T08hKDeew7LO8yni83uGjTS64jV9HCWcr8c7a4FcJifR+0TYw0Q82RZ2I/iaAPwngY2b+Bd32nwH49wB8orv9x8z8a/rZfwTgz0Oytf59Zv77d29OU1LCUjimGQEtbRsAGaOz2YaUgE4iKhSbyEpTh6V3W8q5P0RhDVpiUIzqaZrAxgKdZiBJangZkFOS9HI9hh0r7LIi3Wkx0HUrY/XF8lT3u4j+ugOYiwhv2Ce43QTvxNHLGd17nBB2Bmxayrf+HRy6XcOoHMX3xI2x+pdaWjvL97xFIFQAub9m9NsGsyBSzQUgjPa0dxgusyaCNee2Z/h9rH4XJnaTGN22R6cenSX/I7nSrmKZqH1nZsXdQLLPHNFfacp4BCha2nX5GuLaobvkMnOTH0Rusv5CQNPusp5/d+Ul7VsZkTZgi7o3V1k9aH6JE2YmgJJQ5seE/ScbnF7YAwHIO0J/CUS1XeiudVbEwJyUWt7LDd1dOYQdYWTBDvpLSbNvAU52Yr8AJvTb6kXbP+/x2x+9g/6pL4PFPK3Qv2zo3kqnTzsPPwPdBYGdXkuRRBzpjuUuM4u/BeCvA/iVo+3/DTP/l+0GIvrnAfxbAP4QgK8A+N+I6GeYOeFNiwm+3DKz4KEDDlV8BiGIyM2+WYasBtDhUF+BCoBCfDkAoDtEwAHzeQ835fKU6b2Xur0DaYdzF8DeI54NJdTlLgf57qVEK0hDieMjzfsYq8zdfOZxeCzajWHf4fDIcjAC9o8JxFRCsvNpQLjuMJ91cGNEPJF6QxcQTzuMD0P18dQ8jfm8KzZ4ANBd96I07QjjY7mr/EHamQcPN3rMqmvZqTL6/l1X8i282u6lnjCfVJ2E/Xuy9KMs0QtAbr50zQjbJuTYKI0dHtYLenwg0+TpARXA1xKeplNCf02FGLZ/TGDXYfh4wF59OOJGB4tZZxla7/5rUW4EhyKjDybkXkyK4wbFUpAy4/CuyPWbCvfuPYf5ROvtUPQorH3Tw0rhNhLV+Xd7/MRPf1zATO4ZPGTEZwHupySKtn85AJ0AnCePBAjfDBM6n/DR83PsrzucvCNRi8O3HxRz53aw2H2FER9G9Fdd6bP4Ewf8a1//Tfzq9C+UPnjy5BpPPz4va8D+RB4+55sD5uRx9dEpzr4kOqTTFOCGu9+ar52EMPM/APD8dftp+VMA/g4zj8z8bQC/DeBfunNr7st9uS9vbfk8mMVfIqJ/G8A3APwHzPwCwFcB/KNmnw912w+0UMoF1KKk2ajHuo9RTYnt9ajYNJdyBrJO2edcQ245y2dpuRSiOVahXED+HlMh0nC2kN8yIQoA3OjgD/X4Znjj54xgvBqzt5vlnPwk5CNviVVJ6gz7qmhl7fEHj9BMnd2YAJbPLQzYtt1NqdCtLazcqk35ufIkmOoyJOxItB4TlzU8sSRE+alqZ1CSsDGljDBWXU0/ajr6toYnbTnDjrTvpI5u5xH2orJVFaCoziwa/lK49Ag76MyiWYaMVPrXXNUoszqFUaM8JU9jNwtQ2ipOWZp52NYZi/Xxhy/O0V1Z9iwjj4TummRGAcBfeVmGZGALCVseVj2IGOmyh986bDvBPJ4cWPktVe+TdbkCCghbLn3GFz2++fLLwGVXZhbP/QncZSgA56S40cvJI88e4SLgqtNp0UzI6e6gxWcNnf4NAD8N4I8A+B6A/+pNKyCiXyKibxDRN2aMr//Cmx9g+XpUmMrvvQApF9tv+55TtN+Qf1dfWwDVaMMApJcdCkrPHiXSYhRtiW4s2yevNRLTvs+BahtUU9Pqtn9QVJ29K4Cr7Vu+Z+1UENHcs9i1IChK9EXAxuZcFv+WdPNlv6FEsdhp/zfamFZ39jVSlDW123Qyqxao9Gd7ruyVzuyhddR/ljLOGomyf7af/c3B/lHzvm7L/nib9HHfR3Bg+deAkegY6Fj3ZXDHcH2C6xN8SOj6CCiBzIUMF7L2Tb0O5Z9oZuSel30WMk7CVI8dGD4kcMfgLoP1+OgYvpPj5r62AX3+4qMhzFyokET03wH4X/TP3wPwY82uX9Ntt9XxywB+GQDO6fHNFt82W2hLbvQxj3Ur7mACW/rIVLlZ3i+2J1GqLpTtT2vPbcfI1r4mFKmvx+rcpmBUlKsYovSs/WBeqgvVqy+g0FEfiMGv0IyLKhRTUbAqClKMYkJctDYZIEj/LlSxPqvoVaNSVZSqWuUn28ZHA36zb1ETZ2uz4B+fp+RMN9rQmhKj+buIIGcdeFWxzLabhytnwNklnjWGfVyYENlVpXndhqxRubYNb6Jy84rymQYLIvoyM39P//w3AfxTff+rAP5HIvqvIQDn1wH8n5+pZUcAZwl/AgICumXoVLY1AGfwJUvUwqxt5qpx9L0XVDoNmvVopjn2XU24KscCwL0r3+80A7Rrs0KhmZmaQVmOuXLiRanHmTWM1w/iV0GNGE0aJEMyDR5BXwEAziENki1ZzqHUX/1A7RxT7+DnXL05e1c+86hZo3aO8wkVqrX3FuZVf1ND3E8U/GMUcxy7MNPgS75HGXQyY14TggLFxbN0Q6VdFhaNG4lIWMJv3BDiQfoi2uz5VJYFfq7AKADk84j5SiidvOh3NfLZoGSuEjPmE6FtF0vBDS0AzvbHS70I15geRZsl+mOPXhZmJg8Z6DPmFAqYucUark9gJjx8KKDn6TBhCBHfzY8whR6PdHvcrGD8liKmS8B8lpEfzIibofRZ93CPf/HRd/FbD98vUjDvPbrC92Kdom4U4Hy42WNKHp/MDu8+EoDzMAc89Xcfue8SOv3bAH4RwDtE9CGAvwLgF4noj0BO63cB/AUAYOZvEtHfBfCbEJ+vv/iZIiH35b7cl7euvHawYOY/e8vm//5T9v+rAP7q52kUAJlVvGra76qLuqSM307KWrwet9NINabvEAiZXZF3E2+OINL5reZF/HRSlhVx8lZdT/0oqxYk68yieEgMTkOAJCFg3TcPQdamna8koL5D7tyCwdkSm26Qsnx9XexreMRRhrWxD4E6nZf1MpBSJUWZk3ka7GAoDuY2W3FJeBqURUIuFek86yM0ZKzltht/U/XWyL09erFIJHOrJB4eBLCvSybuWPuTy1PZqVdHWrFoV6ASr0QZqxKwrH0cuDJNzefDEd5ZbSXXAwD6jLCKSL3HZpCn+mHVC5aQCae67eFqj95FnKw3SMmV7S9Wwn9gjwK8shd8wnV50WfDEPHV/gVW66nMLB6u9vikP4VzjJyptOF8OGA393BdxqarWcHuR4LBaU5ct1iEVWoAACAASURBVBXmI3cy3ddwjJQK689eX1Uo57qe42axmzPo2Ask5jI4FDBSAbuF6RFQoghgBqHWb99rcYeFd4OlJzNkoCqOZ7rvHOXm87UNC7bjgu6NKirrjwYWAySLnoQ17JVdVTEDYlCSZZP1l2AAgln4QsoSzOIYqyiMy4Y+3Q4aMui1A6ACuQWQtkoarAAAuaq63q7js687+bn9AoBcVbyzApE50WJgKG1tBhAOTaTCpXJS5BhELIQrb0tohvfykBmCpvm7iE2YxO0NdV8otlPwGEi/csfourTos+AyVqSJcdrU3kV4n6VeolLvys9wxAhdwmlfAwrO/SgMFi0hC1hK7KseZ9lOSg1vZhakmhjUaGO0dbgjIxc3SaajXQSCvstMoqhpOQeaZvh9LEa4mCPCvjET0mN1ezXBiTVd2s9cwnEu1vAgAPgDV6Up/Zw7XxSY7YLmTlLZ+60wRAFU85/OlRAeoFoJGfD7iH4r9XrVOqAsRkHBaOQ6IIYtECy8O3PRUGBfb7SwkxuMotjlSQWCI1ACktbZStb7sQ6QpvvYX6CwRdNUb8zumsuxcu/QbzPoEGt4maiwOKHWAQAwXfRYb03F22YWgJsd/IjFjJCShk4bUld/AbEAmGVm9/+39yW9kmTXed+5QwyZ+eZXVT2RYnNo0lwZkAEZECBI9sKAAPsnaOsfYXjlf6GNllp5a8AGBAmUFjIgwASaTZAie2DPVfXqjTlExp28OHfKfFXN14PUr8k8QHfmi4q8ceNGxI1zz/nO96lF7hLvJwSayIKQ2KjUisvM5XWkQWgYwq1vBB6fc8Wnu25gpQY88L4/AgBM+wmIAq6up3BzhU8a3lcbDmx6WV4iQQHNuYTxPSbVmJ1dTvCPN9/Hct7mIPrb4hSryw6xdAYmsqnNhxbDWsOc9fgVHnC/rMT6OeTKL7L7M1kQbXoSnqNcuTy8Ilkh6zIugKwrS4JMsBvxET6Uzy3LhLDGIYii3J09BmMg1oZxGlm1zIIsK3ql+geyjM+gqMKVcBZyZMyBGH1+ewtF+eESJmTcglw7yDVPAogl7nIdYdpa8Oda5T6I0UOuqQQSbcJQeEZdpnEyHoIIZH2emNK+JHh7njQ38CFlQgPxEAYByBT4HPg/4cLGkkWtA5P2pv7E8nwKfK65xH0IsZAMGxMmwHUU0pR95Zr3IecyRiWhG7MORjQ5l1nrs8ZZgLi/rqlxHQFqJXlSSOpqa/a0hGHPqe4beUAOZVu6pmQ8zm+meSLzjuC8hFoSVpFYSC542QgPjIrXYM5xmZibK5ARWN3wem6yDDy2orwgvCXIFcsWymocMdd45+YEYaEyTmWhO9BC5TWkjdvnnuBHCbUQGPu4DjRcPHlXux+TRaocrWKh1LUIo4F8wIQn/vIq/1vo2wKC6lvQcsVv/SMmMcFociYDdZaksgSfFusm/i0hjMiR8XB8AHM84ZqRJIy730Ncr+AbWXFasqJ5SJNZPNZ6jyn1xVgyImYmGR5NQDOXGGexTmQlYfbYpfZHMwDA6lSCfMfQaEEwe3w8ddljPFARNLQZcOBsS+U6txKuFRCjzKQ+iXPTZw7NmB2IMaDxoLj2wpRsiJ1QfljHfUSZQXC/03URwOqBzqAu8hyzkKPHcEQIxMccDrldryn3K8UxzIRTtZkwaAKogYvpxnh57SSKBBvAt/nwcMcG46gzjgOIKw3J31wXMhyePLB6GGCnAcNBzGBNUzYkxkfq7FkDmFlh4c5cmq3E66dPMh9FaDyoc1iHJkO4F7pjDEWgnPWYRbj3J80+VjctvvPaGQDgyYNXoVZxcl6XJaPZC7AHFnaq85ipkyX+6OQ9vHt8kh/6l46v8VE4zO/e6ZTfTgf9gOuhxY2ZYe+Y+zCOCuJzZEO+KChrZzvb2e+Z3Q/P4nlm7G0x5Gh0s8yVoDRfIqxH0M0C6Nq8b1gseQlzdZOXMnUb7ceca6ZhDQiB3nFwLrNdGwu5MhDzdV5iiMUaOL9CY2zh4Ly4RhsCcHENAPlYB2+vIAdbRIsBNBcK3TOG4urrEd15jCMsLQ5TYCtWkE4/4diIXDnIlYFaRg9gtOgfDxArC7HgV33qnz5v0Fz0+RzVs3nk5hwhF/wqTBSBQcnI+hUZnhb8Fjz5mSlixb4QvPpGZJfffipYQNmGLDJEjun95MqVZZfxCMTLrAOgVEvG9b0aHFRk+0Is0HKdghxsliuczBrI+Qjx9BKnP+N1ve2IAUshVrBGz2/9oUZ7HTaCgFw6D8jRw0tAL9PSLUAYBdsRZh9F7Zj3A+NEonB0FqsGt2enMuu7uIoz8zf/5zt48GEKkgq4TqG5DhjeZVfoJFaRkos4CnDWA55jFJNlwJMHXBVx8E6MnUkqYsuKsPchYCYSs4+GPGbLnxzgr9/9E0w+KXGbi26Kg3nIMQvf8P1wrRnO/mgeMM4O+To4gK630mGfYfd3stiy4LfiGfl7lQ2pzTkWJoqf222IBPbyAQGc+cjINyBmV7DZbsq4GJsRlcHHIKrfDKKKMZanhwBKdQTkENacZiXni1q29aWmIokgxQxI0lbNQkKeswtitIXYNamWC4IYSs0298sDxkKMmyJGFEIRRqrGVK59ocWLkwUkbaCC5ToGhG2AqB9K47m/KbPiA3vyofo38IMbCBCDy/0KMXshAdDaFLToICBGPo8UX1EQFYK0PChecz0OuULUg8C1FsIGCFGk/4QNmWM0xQbEwCX9TKvnN9TMk6RgEgDKGR5joRfIgkQsWcn1LUmFXY68HBN1VstSmcgGlNoVw331QEabirgdQWyMmV4E6GvieqCUObGAXiLXhrgUKNZMP5D6BOBzq6jf38niM9KdNaENKtnCzNAk7zBb1oQ4aX+B/IZDosmXAsGn9uVnZha3+x+EAHlfJAMTHiPWa+Q0a0XVn7U1BN2WGATHSMJnjc1XYakvAPeBsEHbHwSxpxF8SdW6km1I2RDpAYg4n6eaGsRajy8gmVCnfVMgKGl0pO0pHZxiIOQ4YFozk7EJJH7R5IV80TV5nTpPZEF1bRDXzPA7rejQRjyH5Lk17yuJEeC6pMFdU4rdto/L7F0oEieCEChm4Fx1Ul/BLXNPJovoHdRbTCTsXQ23d7c2p/rIyOJFRNLcYO8wXcZ9KFWlKslv9VgoQKs1pFYsxfccavvfZmQjTsMVbwEeIOU5tz86+PS2WlsIo/lNM2cXUzYKYrD8Vo+fAC+bxL+gVgX5UOj5A0Ces00CIhMDBUE50yNUSUUK63npld7Uo+WJ3fDSJFfHVuLNn8dyBa8QPJbp+UkBWVsqNfMb3Mc3qA38Lli43JbXGkGELMv4RU1YlHMGixSlbA3/e4jp7/ImFybkvgkXcjBTrXyWZczEQPb505hwyNW3OSvUBAbDxfqdEFO8X4WczS7AubOd7exOdk88i+fYFihrw2ppwag4RtU2CgG3nbbntBF/H5IqO1FeMnBxWmw7BTPvsryp26dUTp3ajNuI3ftccq5lcbGrFGxoJa/7JS9pAF5i1cuSr9oCVcAlH5dAorjS3Dew0pmvhImJ4D2v7VOxWgiS1+rx3FO/t0mC79y3mmwYfI1rct9ckq6QqfvIxZhBLG33lZpXLl/XKUj7xTyMXOqe2qxK5HO/iCJ5czkXCrHk3BY0rlcUuWApexS+oVt4FABFQS1yZZRtlJdqdR++rN2PySLE/1XBxZRV8NecZRCTCZeLR4rnsOQlBwmB4DyICO7x09ykfOURxHwB2ptBJIzGRPByxwf4SSQmuRhZ4/NkBlq7HDPwzy4gojKXj8pkYjZFOD2GPehz1kRrhfHRPvQncZ0e6emWJx2ay3XW9AAA12sMD3gxPfnYwxzw9/bxMov9NG/yOdDsVahPL+GO9iCuFnBHXNWIZxegSYvld/ahrzjSncBPbqIwnJQA5+RxA6cF1NJifcLn23/a8A2lJcg42Bn3oYvl+ItXNNqrWNuRg2MEMxE5k7A8lZicOXitYCblLtRLgr7w0JfXty7x+rRHE7VJfHw4b96YoD/nfrmGlyasS1oQnONMoLnpMWkUVg94jFjbgxGlrpI6XLxKmDy+PREtXlLon3nYnnDyZoFlLl7RWScEAC5+NIGdcHzAdYXohgmHuSK3exZxORN+KA+7B7j+kUWIKN8ECR/3JZav8O/1TaoDIpi9GAhVzDfRnEvIFcHs8b57H8YgZxWjkOuAp/9Ww8wC9t6boL3m6371BhC+N8fil7O873jk0FyUl5rruB3Xe4Teo3miMB6n5Q3B/sPvBNz7M94+SpUAZ/quFG4xgAMF8LVlvougLFVASkTlrShTm8DGsSBiYVcWFBb8ttrSObW9gFrJrbJ4LkVPx0vgGt2pvD15L76VCErCdwoifgKAkPzd9gJytVk45xoW9s3nqLhvIYoCAxUoq2E2c7+lm2mmBDlGuLaqJwtmKgcYvGQXsaR9Uo5HQXB/x9u3VRqP9B3gBy4JGXvNnovtIygsjhuLG3FGxsRyeH6gAW+KBwEAZj/ALG7fNwzsItgJZTBaOlc7KazjtucydmEia3jFQ+I1l8anrIWZ8uQWBKE5HjDuz+J5hEjOS7CHMWhBKha/Af6A419Ce2jtYHwPrwXsgY19lc91A8wswEQR5MSGZg49Xj+9xHufTso1OB5hKqSa72OMZmr5eIOAPuRJ21kByG/oZEFNVMfaxlgAIKUQrIXYmyGsVoV8N31frTZ/Yx3Xinifg6d0sM/BTGMYgwDGaQCAPms4rRiXAbnN9D0eC10DOV9nklwYC3UzgtYjLzFmfOH6TwdWFKt0K+WygXB9PN4yp+bUszlmSY08BnT12RI0X0IJkT/Tv6tnc3SdhJrHwKv1gEBOTSZTCxOp/Cy68zgJ3kQltuhZZD3TSQesR+y9b6FvIoYlBTQloe1kDgSqVYPmgr2utlJRl4ODejYHrW4zn/WfdjweQJWS7DJuIXkbbk4QY8jpTLkWzL4dAvbejxiHqCSeAoH5+CuJ/vz2UsK1hObKwXUC+qyIe+69z8rs7VPeNj1QGxIHid2bPBeVtReE7pLbtx1nUygA6qesFAYga480C4/mRsfrUPppo0frI63/5Io9BzvlfWcfDTk9W9veexPYiUR7GTKk/+AtiQ+uXsXhb8p+436P5rpMAC5KS7hWw+wF7J0TzBPG3GgH0HD39cm9mixq28BVAJtew2hycRjF7zSazd+EwBDmyrMIWjE2Qal8Q2dw13LgCSY+3D62CWDjWBAi4yeSUQBPQgLZo1HXQ2kzmff5oaflkAefVusMtEnHEssBwRjQap0/U7/Eas0FYanOw7NwMFkPPbclbJ3X8pSLzTgzEScK6zOrle/YQ2suR8hFrMepJgu51pwZiuebJh25rnAd69jf8bZ+Zh4PlJuumajSL5/Eh9nDSMdWCxc1PhSaS243NIKXDj5seaANmuvbmSunBUsvNCL3AQCay463RXCbWs5Anicir0VeCggbWAph8Fk2gKUTBbwmTD8OWVIwUQLIlcss3Grlc9o2kxDFatpmwXU7GcJ9uS6YmMra6x5qFXL8BQCmTxwoCEyelJeEXtAGliJ5Xq4BbpRAexEgxhobc+tQL7RdNmRnO9vZnexeeRa1irqYTjnQGd+0Prrn/vETqO9+B+ImBqoOZhAXV6D9PciUSXCOsxnzAdQ2eRniP/g4t+/+/Y8BsLsfiDC8MtvQDZmMBuFwD7AO8pqXLOFwD3Ae9rDPa99mMLAzDdHHdeITLgi6/E//Bu2lZYXz+PIzM4XlA9bM2PtogvUht9E/meHqew0QgIfzRwCAxRsn6B7vYTxs0TwbYI4YJty9pzC8foL1kUL3LK5/49vZ7DdYPCqXdP/9NVP+XQesXoq6JkkWsOUSdbPPS7/+/7Ev++Q/fB/tJS+lhIlVp5rX8mm9vnpA6M56kK8KyQIjCmcfTvNypfBYBFx9b4LugrcPx3ze632B6ZMo8BPfgGZGGyXqw5FAd+Gx94slPv6PxwA41iEivqBWJFt826H/uN/IRFBgWcPuvIXtgZMjHl9ywMUbCmYGnL7JYzB/ian7Eq3edon6eAh0UXckUfw9+qcBy/96iQ/figWPTYDvPJrzBvYPol7NVYOgmDdFH/Igtq2FEh5nlxNgrqFOeCm0/EmlG5JK1ImDmebQ4+Atmcfsoz93+NMf/xx/97MfIqWqpidLLJ5OMtxbTNlL6ScjrJE4e62HPuU+OCvh//dXSKv3dRlpxWXoaQmQ5AoB+FkHkZYLs56V0qc9RJxQgpAIXQssVP6s2wCA9RG7iGQ6gAjDsYIwIVdtThoNe9AxXX4+VgdYj/GogU3KYpcdhmMNdckPs4hB0eUjgSAV5LoQ3ox7AotXIqx5VBhO0oOmMX+NkYh+xjGN5amCMB2GIwXhAoaTmC151mN1qjEcExCimzukak6J5cvFLW/mGrYjBNlg+SBVuMZofiegBsniPwAmsa5m8VqAjUFLuebUW+KfVDF4OLzs4DoJsiy8A/BDydBjDbUu2ZTElLV8SWRXnEWKgPVhyEHTVO077gPNNUHGytXVQ5ZEnHzcYvHtyH2x50CjABmC730GYH33B5/infYREJmyASB4gtAe81kHv2fRPYvX3QKLb3ngZI3Fk66c+76HGAi+C1DXxfH2TYB/OMI1PE52n9sf3tH4bz/8X/jv5r8AAKbtiON+iV8/PsV//sHPAQBvXb6MqRphg8AfHr0PAMxwRSP+8eb7eOfmBH908h4A4K/f/RPoa2YXT0TCQXDW4/XTS3xw9Woesz/98c/xV9/+e/xFINjIr/LHR7/G35z+CEp4WC/w+vQZj03/FBd2ir998gb+7OE/AwDOzAz/s6tmxN9i93ayCDGVV/6uCsmWayDHGtYI1oGGdSG3CR60HBBGkz+322gvIm/EnAvJunMFsiGTysI6LtYaS7CV1ga0XKM5V9AxiyBulujPGoibGDiLx5p+6tFcu1xMBYBVtoIECOjPLYSNxUiXFtOPNUvnxfVqd+mgFhYtAXJh0CYE52jRXjnIUaA7jyxJMWAo1gqgEkPoz8a8Xp/G/jbxN7oRoNHzb4Ccqp69T9BRJpBh0pz7t5cllSqNRHPJ691Usk2ePYv2skJwRj4M8gGTxxLtVbqe0Su7Ql5vp7X1eEloFiV1KAeB7tJDXQ2YfsCvc9uLjF7MBMsA3jUvo3/MGh01rR4AlhPsG3QXMc7jAqYfSKxvOvTPkgdEsBNZPItlvfYXWF906M94m51Er/Bshf/xiz/H8EsuGls2AY8nHs2ZZKUwALjWCIo5Mn5xyMplXc/XYTlvERYK7x6zZzL5hGs9vESOJwQFLH45w3ufTnD4mzJmf/ezH+IvAuHvf/GDTH7z04NXsTqbIPFZ/HTCZPttbzCuFXDW4q9OoxdkBM5WP8Fd7d5OFgBwqzjshftxEVYOcN7ld8/xvihJAmz8HQp5zt09ttKPgsMpkNzA/yX3mULZlgvJEiVf3K9myr7zuHxB24BRp/+w+bndLwqb23lbHE+/2Q5VNRKfy8Lm93ysjWvGxyvAMmSXfGN862uQx/MLgsUClWu8cS2rfm/dmiHBinwM6vqqv55j8vl+edF9lzyKSooghC92DnexXYBzZzvb2Z3sfnsWFaCp1g3JgKu0D0WVrVSM5gPjJaQsn1UbQHFflWDYtWuYhTuzeyevYpvur9HwXdHx0I2G7RV0ZOVOxyo6Gb4AjDrKOhteUwZQNZIYSRiQ5RJdQ0h8DYEAl8BTnvkxzJSgVpEPI0bC7FRinNXAMAXXcml0AjQlXIRrJaRwsNNN3ZBxr7i/otYNmRISpMFOefnhZYDr4sECBw29JsiKezMQQ7MZtxDTeC0AAsZ9yuLDifk7MYklCr9xnyANwTcKNmKPzF6AHAlkAN+GvNSgoxFm0fGf1QvWtwFkBOws5GvhZYCdArZHjqWM+wQz4xJ812KTsFcD45HPgDUzK2P8xslT/N+DSOPVeMjewowdTk44MH4up1CKyVQfHt0AKOzeb4tTLHSHl44Z9XrRTUE2ekYRyBWIkZl0PGLc7/OYTU+W+OOjX+OnB69mj+L102d425/mfu9POY53MllgsBof4AjfengBAFgajXN1d4j7/Z0stti9a7LdmoMTzgHe8bYqZpHJcyqAV91GjtiPFkQEtXIQoy8uuItcktXvKX5PvAcAgNFArWypTE2EvUsmgpHG5xoQLZNmJefem4iCVINDc6N4JnQJ+OQhjGOSmdFBpf46Dzl46IXg46LELJQkNPMykaqVBVnmQEi595qPgUYPleotYnyouWLCXIBFfEJ8cMkXIl/XccaCXfw05oBeAHLwhTTGh0jEHdAsAlSEi+uENRCoOB+Q26ljFk4zB4MYLZqbeP09Izg5G1K4NsxZi+aKNieLwC+A5gYQjjLJMQKgb8AZikzKQxVh73bMghBIZMBTIey1eOvJS2jOIzJWS7hOorkUrGYOQFwrWB0AjywA9LSZQUqP1SVzZn4UmJDmYB4iH0UBpgVBaC4kjG/RXBdOisXTCf7m9Ecco4j2tj+FOesRiHlUzpb8ErvqOzgrgbMWH4BJg70RGO3vIPnNLXseHDxrhdxhdVXpihQ6/PySQtLWJEvFkxHEHAGfo49coMZ/bnyvCrPSd4rH5X6VdXeQlc6pIHwV3AQvtOpBy4VKlKDNZZ+EXtwoOktFS6lsveJPDtXvv+iyelMKAFmntN6eJoqsh1LFOQMVb6EWHf6y/CCiUkALhIpDongGgcKGZyuSZADPpsWJjv0MssQfXlgERiwHsK1XGmK7AaG+zb+0fXMni+fpfdaexW+zKtKU2YLqcfe+cFH4annzOfvIFbDx4UkBv5ghyIHA9D2gHCtUOIVI+Zf2/e0ltV/C6kBkDBYmfZA6QJu1WXNQuQTkUmFWGq+kn7qtG/J5bTvwmvuwFXgNQLmmgR+8FAx9Lt/Fl9SO9aF4N2nM+BhUtgXauG7eU6VHSsWJTufj6n694EkPgPX1Gy71gWtyqWr3q4iJfyMniw3hoFwKXscxBDNoCSqf220kvYxYku61YJc1rVOTZ+FFVWJeSqx9LmWX/D2XzJeYhNdi48HwmrKCl1cElxS2KmandCyvKbM7BSU2RIK47dKHTBnfiLz252PEQrKBcmoyeVFeCabyj7GQ9NbzbYkfsGZoVO5qSym4axmkBM/buWFOrXpFmRAH1STsmtKHBMByLW3AkVPbzgDpAXFtHAtZxs610SOQyFIEAOAnDq4V0eMoLoVvA9ySclupv67lqsy6P7aLJUUaG0JFrgFcH/L52q6M8cl0iQ96XnKEJiC0Hm4l0ESd0dEQq5mHoj06iezeZlSwnjILt296psITyMQ1QXA/fe/gWp3PQUwtXp8+y+lRgGMUZ0udQ23NxOTtaytxs1DYm/F6chzV5xIZ2mVDdraznd3J7q9nsUV+88JsiBAxKU3VwiyU7emzagNAflOn3zGJSnnT5fbqxR6xpxK0yFWSkPF78mzisVzkUPS+tOEV5WxL8g4A9m58zH5kLkfJ3lNIhDnJk6HCMZn6kCHcmjZVxTUXOgUt8vbkUSXymo3zReU18Eawvgdv8zEG4Vs+P/Kh7Bt4vySXGH+dr5nTxWtL3oBrK48i6aC2BDemX8W/m4AgZdFIbQN7cFRprQIQEwvXqs3YUwjwbYheXZEkTPqrvineFnsayO2Kqp4r6aImzyJlgbwWeGl6jd/0D3lD4yE7B7eU2J/wG/xylJCasyGHE4Za77cDOmkwH1rMPeGg532vk9ZsdesFwXwUYmrhWp3HoZ+M+G7/FG1fqsFOJgtc9V32LLazIYtph+PYh6XWHPO4o92vyaJm1o4IzVQvIg4PmOQmBM58xOwDGebjJOczSQ0A4OUHoNmUoeGJKKdrGe0pRXbdU9WlsMxALVNQcbGEiOnQTLTTNjCPDuBameHJbtZi3JdoWw1IgoxCR8JxRF9WDNGuLUQrch3y+lmuXeaAoFiHopZHkNcDVK8gFmvIWYQpz5dQq0O4RsFMqyWLBMxE8M0ch3HclzA9T4SZC6KTvIxqGMqdyGvcKyccG3EldVp0QWlDqlCMyEJCrqpGlyPL+WV6/8rUusvU9mrgvqx06ZdruT+25wBpqoy0E2AcCcNLk/zwkiWIEbcqJtdGQpvnLDlViNkTyiXxPO4SflUyJHYiYKee09pHDj4SIQmbJtFQJrcuwOuAm9cUpqYFxeMGEnDEmSTjYobEyHJN4ralaSAoYFhr+FHieuBZTy0CmvntpUHoI//FXsBNfHFYI3Fhp4zMjDZYzVmPNCbx+2A1/vDkfZzNpzjt+R5b6ga/+l3QOg1bEZlgbInS1HwXVYp0Q8t0GBGGNWipcxk6AMAHBOMLZ0CcdNTKghIdP1DSrul7PJa6HqLEHV8EOV+jvWwhhpj7S3wUi5DbTFanNtXKQsfUqRhcvkFSCjOlY8Xgymf8dzE4NDcezRX3L6VnhZG8/o43ZntpoVYCem4RJN/l+sawJ9WIDb1XcbUE+YDm+iD3JUOuR+SUJgDYayo3dHWZmkXYoKqvLY0Hf4/Q80ugu4iTTsPxkVSwlo+9JrRXAe3FOuuNpPSmMJVnBGA802gvbx0aYuSUp7CU+wCwfomwlEl8u2cKci0gRkDPVS4kI88eiJlJtAxRgDTsQU0fW/zq8YPMTsXkNxL6inDzmMEY6krBN9z3pyZec+2htIM566EWAjcRuPFoi64/9/WJghkE9s4JbRyzs9d6/O2TN4Cz4l59gKONv29iXdRi2uFsPsXykxnejPfuN1frdMs2lh0ALydSpqACWtXgq3qZEZQESRY3ziISgUli4AV8Im2J3oPtFaRwBWyVAF3AxrF8o+A6zqUDQNMwa1Wi40vFagk0lQBTwCZoyvZqAyiVtidwVAJ6+U5mIFj6d99JmInIBWRpqWImYkNO0PYCrhUgKzHWoCzBq4KA7gAAA09JREFUIDQpKYsEQUoE8hj3qXgWcf5zDWWwFMDFXqkmZKyOBwL6TsIPt2+rGkSWzns8ANQWUMtMKWqgpmMxGY3XEuM+75uAU1lmMJ3vqcF6Va3D8rgzmMrMeFyTJRBWAqaNe8y2JdcE24cNvVTfAObAsxwlADsL0RMS+MGjp/j5Yy4ADE0AGo8gFPYe8Rv8Rk8hGr4PHhzxtok2mDVr/AoPMPZNkRSMAkDbNh476MM1zJNp9rr06Qp/9vCfc60HAHzr4UXGUQDIwczjyQqn/RxvGonvPeTK6KVpcKZuT+wvsl2Ac2c729md7N56Fs+15yWNPyORHBJku7aKY6H+HUWlr42c+/ZvQ6gwA1s4jSiok4wcbrXHGhEox6u+iy2wV1In2/is/q3GBzC2IOlQhAzg2ihGqzAOIZ2rCxsq5ACiBkbpb+731vai7PWcc37OtaAKN1D/NvcrFnyJqKORtgtXziPrcJjSpw3AkqFbcQwgxjiyvka1VLWlrdQHsqmvFVYj9d9QiZukax4C5mPL4D0gBlcZzDcmLlJD8DHwPWy5/c5KwJR9mxeohJElOCuYCi+lsK3EmZnBmzIIS6M3/k7tLrXGUjdwVmJpmrLv50DIfXMmi1qycDtDsb0NwEa1aAJpVaCtIDZ/l9S0NtB8223WdSJVtL30sfyd6NXq9phKDeV41XdfYlJ5GxItP221k6ne03EDSJTzKDtic2JLp/G8mJZzkWsSpV/V5/b29N1Xd1A+5+fABdO/bbe7udMtfFFRQ499AyIGwm/2CQCgw8ayJLehOAvi9eb4sGRA1R+BkknZHiPidvI5EPLkNmvWCJHcOKgA6ICgApqGZ5a1DhCa78FO87a0DJHKwWmZ9/XyOeMCIMgAKRkpmiZSqRxO9Ty3ndqt/07tTrSBoAAhPFrJ26wXEJ8DIUfbgcSvw4joKYAFgLOvuy//ynaK3Tn/Pth9Puc/CCE8uMuO92KyAAAi+qcQwr/7uvvxr2m7c/79sN+Vc94FOHe2s53dyXaTxc52trM72X2aLP7y6+7A12C7c/79sN+Jc743MYud7Wxn99vuk2exs53t7B7bbrLY2c52difbTRY729nO7mS7yWJnO9vZnWw3WexsZzu7k/1/NPjAjD8+tQ0AAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 44.124547243118286 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 1e-09} is: \n",
-      "[[3.200e-26 1.600e-26 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.600e-26 3.200e-26 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 3.200e-26 ... 3.200e-26 3.200e-26 3.200e-26]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 3.200e-26 ... 3.232e-24 3.128e-24 3.200e-24]\n",
-      " [0.000e+00 0.000e+00 3.200e-26 ... 3.128e-24 3.030e-24 3.092e-24]\n",
-      " [0.000e+00 0.000e+00 3.200e-26 ... 3.200e-24 3.092e-24 3.184e-24]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 44.02215909957886 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 1e-08} is: \n",
-      "[[3.200e-23 1.600e-23 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.600e-23 3.200e-23 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 3.200e-23 ... 3.200e-23 3.200e-23 3.200e-23]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 3.200e-23 ... 3.232e-21 3.128e-21 3.200e-21]\n",
-      " [0.000e+00 0.000e+00 3.200e-23 ... 3.128e-21 3.030e-21 3.092e-21]\n",
-      " [0.000e+00 0.000e+00 3.200e-23 ... 3.200e-21 3.092e-21 3.184e-21]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb246370b8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.968430280685425 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 1e-07} is: \n",
-      "[[3.200e-20 1.600e-20 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.600e-20 3.200e-20 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 3.200e-20 ... 3.200e-20 3.200e-20 3.200e-20]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 3.200e-20 ... 3.232e-18 3.128e-18 3.200e-18]\n",
-      " [0.000e+00 0.000e+00 3.200e-20 ... 3.128e-18 3.030e-18 3.092e-18]\n",
-      " [0.000e+00 0.000e+00 3.200e-20 ... 3.200e-18 3.092e-18 3.184e-18]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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94ief7SWS+SbAbXeieZlnzYc0IyKky/W+03oWCn6VHB2cRznKUa4ld0OzwD5MmGOS1fJAEhLHOF0d1fbLajdfZ7Us9qCbZAByMS96Oa5hwpuKSVE+CJyxkGZ2IBJnF4xtPzGtBgN1vkXZy8BkY37oh8QA1BSM5phoQKRYhpTt7GGY7KpvDExSBynZK8xg8XOzNeM/CNlUOpDd+dao22QSutigUPmAZmGPld+kusPHavJyNicOgan0XNa0AKvhWc2ovC9vOupV7sZiwfl/xs5UPgpF7U1AWjEKjgI26oFiegAowC1rZ1LbVny/picP+l0zUdvi02dTkFe+lzs5ER+HLgTjCGqb6sAr2ax+37lqfArc99N8kMUChNoHt1oi9UMBhik4Le06uOUC/uH9+rIVJ60BfQEVXxBjdbapOaPwZbVpkziDabWsWBDrF7K5EouFLF56HBAwaYzg9bo8GytusQD3xvcDwH/w2PhQss2ukS577xjF32EjVvNIEwBatAWnMLl3IyYtLTzS8xf1/NVSHJx5Q/IfPJZx0vdDF3MFf+nCB0h0IoO8+OykmgzqxG7GYlJMgGImEsSOJEIRUznO680e3J0B+G9+JNcezTvlHXi5qP4SYOLE1XNKu77xIdyur34TAPj2Vx6UVQdsEvWYnJNBRrPJKv9Q1UL0pewxs+15z4HIMcoqPwwTjz/HVIAwum8U0NQskawgCGMCu/xQLR+CgqP6ofhCJglanKTtc5Sidn+2S5boQsyayTCIj0bbnkFV1ASAHXizPcjvYKMUpG3DNDKhvBGHnNIJmESVALGBJ4lZjsADpr4Bs2iwhgiv4mzouoNtl71INqOJ1jk7xrtdXYjaZrpoZkdtdXBmv0gIwLMXExi4AK0iSH0sdjwm5EZUo1qqde26gxBslyNBcL6Gpi93wDpM+zRPgDPoYTo7rUA06PO6fs7Nl3KxsBGOCZ7CslopQk5xGCozxiTMNYuiMQwHNQt4P8n840E0C52EqrG4xeKVmgVmmkVh1lJPd46wUN4pCux914HatuI4gLrIWRwHUBxoZDAdjDoxxRlYzydi4GQFukKzUPMCTQtSs8j+PsaKEpxJGQ8dRwB0spqQ/ZSFZx5GZxYn4Emo97xCs5ijGZH7qykB0EmHqlnoMVqtZPKnlBcL1dwqrJz0+tkxDmbw+SncTLOg8c00C7y4qONs+3B+JtdQKHju7000C4GGNxXyzww8+7JFQ1RekXU6wV0YG+1KzeJAhumhzMqbahbo+zrhgIrH4JyxqHF8nYy3pVkAr8ZxaLtnIVIwi18movhptA0CEBrfmWYxnxQWyzH9ccJ80b0NzSJdrjP8m2XSzc28uYbgSCbmNty+ZvH8xb4fgtONNAu32YoZZTeUeH1/zTEacpSjHOVacqc0i1elqCvuwj1+NE0J1lV4thpT21aTIq+8/oNH2Xk6ID59NjmfI/Kqba4zX+EVyGN2dIWAcyc7gmI9xk8+y7+xmkXVEDhx9TMcyNQsWoUqN7F+X5CTExMi9/VQ8henuqv3/dR5p2bThx+Adx3Ss33sg5xg8A9We7gm+c0EiauBqIUpAaEOWpv5qWPjHWi5FBwEcBgDAUxRrXtf5oiZ3XVnx5x3cm2PqaOYdOePtR/5GdDjh0jf+2Sa3Dj3bxh5U/IbnGQz6P49sDq7v/N7Nya/Kf1+A7lTi8UXKnYyGMDUxNP+ptedq/X2mleFub5omZkg5a7OTV+W2QvL1vQAKslLSnglh8YtyJTBi2tINI3757wLUiEbClazVI+zmpXGrI1xgpa8VTFtoQMpENe6xKgmD8q1bhJRvVuLhY07z+RVuItDUnZYC7XN8f63j6vPeBTm93gXYhcsK3YRySFezdlQsVpIuVw/vN0i+iYya6u2qfgNrLyDRXiilXlnqAVi+b6I8lYcot2/DdHxGIap1nMDIe/AQwLSm3kf7tRiMYlmNG1VSYHi1IsvXwpxjca72xap66a1RDJ0m/t+kithTY/w0dfkuoo7OFlNkmz44lLwBONocBqCp6Cz0wn5CZ2dFo96eiG4kPD7flAiGwachRDASzGPaLOrsOhdB753JhPiibSRzs8EoNU00g/FSazXAqk24d8C5AkBOFnV8Vxv5OUfx5KxqbkRGt0ozNbPngMA3Ld+pEZkTL4Bgi+RC142cLtB2mvZroYRtOv3TUPFIqjzV3MmiEBbxafkFzh42a1VrV80oG4Av3gJ9+M/Kr8PEoWgyOUzAMSzBfxmEAdu2T0BOIC6CHiCv1CiG0a6dwJuPMKTCznUBOmPbgbzqEIbQNs85hqd+vwZdj/7b6J9uqtj5QiuGzGey7vn+gQmsWbiQrNOqXznhoTxVK63+L1LOH1nVGshQjpZIC0DwpPLMmbxj/4EuocNFs+G7EEG4sLB72pCHDcyEMkTXGS4XURa+vJ8+R9fvxrg0cF5lKMc5VpypzSLuXDiw3U9JmnYsaYhF2o8V2qJYDjMVl14I3JmZElSsiAVTlOTSE2YzKoMiDZE291eqJY32wz5NeZCSsVHwP1QYdFjFE2DDb2u7mpqOpnwGA+D2PC6U9sUbNv+rhNGKkMNqEjT4hhTzUC1E6V1y+2Fc5nXwuAZhjGn06faTgX42GxaEyamXV/vYVTqYrYV9X+GfO2Fwo/7Hu5yU9puUYx6PRqiaCG+4l3AwhdRnoMJh9J6V3AsAEDbXUVwZo2siPfCw6HvjWp62x0Wn23gLgytXvBAP6DZ5euaVH2v703jy3EaIlwnWohmkLKj6g9xDv5ZDxc86HJTxqz5fAMalvCXNUUgOAfqx6pZBJN1OkTRGlWzY5Zj15Q7vVhMKoVNvqD6MjgFI5kX5CZ2pHrhbRq5Sia/KY63G+SIEBGYHIBqSk3SzL2bfnaUVWbDkanp17M2kSIwb0ssyY0dFwuactmvYElmACBSBRjp5exv7LVu6t5RX4sjFF4dopq+koFOcK62ISXJUUliItSRjLVNhQv1hu1RmY0T+wwws6aQYkP0mAM0T2SCL3EOrO+MTTs/8E6zpuKb33NOZ2dPILsOHPJv3VDu9GIxkQJEmaI1yWfEXJjyOxQEpOWasPQE2bbnnfAu0molE1Mx+tvKT8BjhSS7xQJYLSU3APLM6fSkvhf6gM9Pp/Y7ADShMiKtt5VJadeDzzJXQ/Yp8LIV23TRgrq+7mR5Z6Dloiad6Q7VNOCTZe3jxVpeumEo/dXrkCJZG22DXCs9OgftlESo7t7s606YVg3cVnwW3NZXiIac4GfBdTrBz1YyHrlvIAJOVwV9WHgXFLFa/COt/C4x0gNhtuYmL6IJgK+TYDxv4dczfgzIBHK7EQgO7sWm9CndP0FqPYJqbWcn9drOTXZd9gReNHCbvrYBgIsRmx9YYbHQHBlC8g5+N2K4J9qC76IsYiw+BWDus2CMp/L7VeQKVtN3kQjx8RnSwqP5vC1jtvvmGXaPApZP6zOIrUPY1nYn9VkEghsZYTtiXOV3IDHS735ZEZyvktfEhm1yWFH/Felp0I9F5ki/lPJ/dfcjoglaE8jhshjLzq51LnkWySmq78wMqRDiaRiuaEOaUJUM+tJKIfSN4HktTKIp8UlKkssSY72vmgb6eRYZcWMyaFJV3dNkEaDRhBSjDX/Owsp2N7PmUWJpAXNpl2ZWso5dybYd5ZwYAb0vkSxczGBTDsH1CTQkwFN5PsQQkp6UwHPNIXI1ifK9CMiLBU8cnJSy9qAmixlj17OMGwBOBAfADQmuVzPDjJ++CiyOWTewnDu4Og7ZKWsXXeryQqzjgbrQ0Mh1/EiOIyu1OhCUCG5IoD7Bu2oO0uz1epXc3cXCESas2EazmGY77qv4Jc1czQv9rR2ZYldnNT94WSjUhtcMzpgAnydJCPK7bArodchVshVWUpQm5IlasyU5+Hr90fhYQpIdmhnOcDSSeuV9MtGC3AbHoDFfV/sUwiSjsLSLuarlOl5qyqimoYtG42tKtE58omr7AtJWImBM4KX6PNRvMBYtgVQPZjELSk2OPAaSlJf9LkazmCzQ6ofxHryo9j6iTLZk2hsXHhQT2Luyc+uC4IiQggMNyosZwY1DXAb48swpaxZUfTXaZ0/gNpSFsmgWzmFcOTRNjXLE1gGRixYBgomG5J2+lYMcGOyAuKR8XMokIDiA8tgEB248uHWT3I+4cBhXhLB15SVILQn2L98v5XFIDcE7AiUuERlKvJdF/yo5RkOOcpSjXEvuhmZBOVvSIAjVBNCq3BbibaHDSqnHXSdUeADQ94KpYBYKvAOAHp4R0/J2V52dyD4Nu5tDVPV4uQZtNuU8jlGiIcXLnv/97CmUj/MQDZxtEQPC6swJyHiICUkL0YQUB9ud9O8AYa91nCZbLOj5NEIxT0rS2q/+Ox9PB0ozHE0/SPsRDWGvtuVkWXdkHfeuF7+LXnIjfqL09Nke98UeYS8REgthr/+d/LqamhjeaJSBSEwvo+mBudQ5cTECD+7JdRPDDyPCZzWik54+q6bfAdj0pG35vrEfcP8fNTVKAsj7Mo5obTEkHQ8Tsat4jgH8KNPqaeTKuQkGJT15Bp+zZ3XMTvoBJzY7Vu+RcUYT8CBR4cpoTJqAW7++bnDp1rXPfNeiNPwHxJYmLFl2RKa4TXptKYBSAcwAv8hewzvwop3CeZ27WSkAvafNNFSn3xyBmcFAqqIjeBRgDleSGsrXsynfE9v2iyDsnWRJujp5bJQjU8uX9qYkJkATwMus6g/6XGZONB3v3e5mpQDOT6WtJZMyt0nfE+/El9OEajal7LzN/U3n4kim/M6kxpewJ1k+ixsQ9sYP79fQqcvmyravDuziW6oO9NQGMYW8h+sGDI+kXX4rACtuXDGPODg4dXIbwl5+cI7x/hJuO05MRxpTjoYw2Nexcm3zFSDsPUSrlwlsD9LqTZKSUl0UFJ14HVo9feicit+C8/VUaIzC8q0Pwl1/YNnS+s85G3QHtMlf2RladuBFW39nrsUxyeJ0WzLG6U44UuVoMP1A4gluRB22NMaau6A1PPqh4hcAmdRENw//DiYCVnJGjEOXBf3JzKCBSh/sgu8uMlYjca7v4Uok6E3D0dSPFZ2aCZBojFUztc9R67AMEZSS+EDGCJ8xGe4yv2/egbr9yM5ExgjXR7jelNjMTlAaZXGkVDWLt5U7sljcUOZRhMRgxKr+Kk8AX103ZAItJwaPOS8gOzMrXb35rWXyfk3dEKhZA0zMEDZENTZzkxMDKU5JeZyr5QsN/RyPt1y+cFKLw2ggxuTQXZaiqY2Rcu1TnSScoyXMk2rjFF25143KF+pmYIo2kasLB+V2CDlRbYNlwCINUadcMlALE2nfbX9n781VdUP8i3UFu2XtlIcBtJ26BIuJhOws19oi4whXIk25LclV2H3wwrVB07oh/uUl/JBrgdhExkNmiPbPgheBY/nCoxzlKF+83FnNgl6lpprCMuQ92I3iaLMUa6/xWRRVPtunahLYojmCCjXs0f765QuxWtbV/lAJQOuzYAaaKWFwsSu1iJIeZwZCuD2fxelJvV6q/hxxQhv8hGI6sg1ewsSu+jYKchOYZpLq98PqZj4LLTLkjB/FwL05J6GVxDegajvaT33ueYflJpQdU5zaN/dZpAdnoHUeXyJ5dv1g/Dl1PEv5wsaLbyH7ftI9cWy7tZghbHd/7+HOTg/6LNLZUswVY8VTLk41rYBGmXbwy+6z4Pw/M3m0vGBh9zZZqLyr9GllMUiM9Pnn5ZLu5KQ4A3XSWOIaVRv14ZfJlx9SvFwfZvc+EyebPgRqgjhLL9eAc3CUEZQ5d2OiZjcBaPJk7rqaubjrQCcyEdKzZ6X9mk3L41gne9eBFgu487NqC+dxIWsqAPJyqANYj6uZoYtFvq4/OZFIjsmynajchq6NFotars++1DFKVMkCv7QtpycV5KQ4i5OT6mgmmrzYk4UzJvhxNc3LyOq2LZ9IaIF+mOAjpI1OokkhlKxeuf9KxvdSImP04H7Gt7AgbdUM0KrvQPUjBA8OHu70BDym6hfJIDZk5yUgk5dnfgcak0zgfgCNEe5lNrGevhBzdNYF/uCRPLdla8CHCRjTtNZp28j4z60L7zB8dB/h5Q6pNTiX713fuLgbi8UNRZhVDy3wAAAgAElEQVSo0+QzNaGE/wCUkBSFYEreZ4RhSuL1B6oDdbWUHU0f8GZToy72XjCTENnhWIBSVHYROjmR1HJLNGNSyNkZLYCoePqRF0dtD62Wkri2kkWIx1E+r5b74VWTAi992MlESUkcpoCkq1snqxZk3oo9y48fmuvWKIPu2gDAqwVoq556M1l1whxwMOt4AKjlEM5PKgTcpKjbYtRogkzQcZQ0/nysJLKZUHE8X8KvTQgzCwcnqeVNmBD68j2pnqYExXy6EvBTSrLzm82LvQC2JnBvItDFFt3Xz9Ao5NpLfoqkqMtC6PpY+sdt/tfJeX47gsaE1Mo4tlq8eCbjfWmbv+wKDH18sEL/sEVr4N5p6eF2U5i6tNchLjzYE6KmqDOQwldhsbCIzb3vLCozf7bHkM2YnGQ2oTLTxBtT30NuJ4jGgsy0yWX2XkoBb5OigqW4q7h+GmcJXwZhSTbZyft6XCe6tjGbPpPwbj5/spvle074JQpdPU/vm/8jkwtTxq8JBUZeojXeFWQlkCeKVvg29+PcF/gDIe88HqWdep1RxyBHSEKuyRL13h4IEgovmlhGWZJzNTQIQT+6fl+tLip/4+Gsw68J8l2o102tB0VFctp+SZhVJ6qiWDl4xIVDUHRpXgSIgbQwbcntjJPzAEoe5Kicy8EfLCqUWmmb63zRutLCY1w6NK1ZMBd+AmHXxSA1DnFJcIOvi4VlzbqGHB2cRznKUa4ld1ezOEStl/ktCk0+UMOW/fQ3PArnAg9jLXtneBA4M1sVnwUw8VmUa+rnfC9qQikoBED8EptdVbH19y8vDvssst3NXVd8KWyrYKtKvN6IzyLGHKKM9fvLtYQJrYOTCBh8NSEg46QlEIuqvetq2xNPQ8ScQE+e1zZc4bNw2+v5LCaitPlA6bcbY8W7KJbDOn2RtZuUpC9PhM2LrvBZtJe7wxgb7wRFGoKgGLNQdvyqz8J5B5ffEW6bihfJ4+uB2gflzIgRJ7/9slYkUyd2jHAvc4ax8Vk0Jg+lYiJidYY+ewk+wIXaNEHuaUyUdjcgPF8W7AgANG0zHQNfNbd4toC/7NC29Zlrstt15O4uFnMzxBEoZ73Y6INNRZ+wHLdNBTBZZ+jMZ0HZZ0GnJ3Jc4+DbXY2Y2HstFvKyqiq92Ym/IcXq3AJA987FqWa5L00KOV2saxGaEID75/n4RWmPA8Q3sd1JdAWQCXJ2Ctw/n/oWsl+BFzUaQttO1NphFF8GAHqpZkhuq/ZxuxNb/fGDsqCVNHE/TWBKJ4vqVJvT6nl/2Geh4wGUfqf7pwZ45CSSoDR5ms3qhbSFNjvwafb35DTyCUIRwHhviXB5wGeRfQ3ceIF86/FH9+VY/jt+cE/MksiIJwFuq+Q1QiLDjopPhNuAFBz8RYftv36OxdPMTK++iC6WFHWXKf2AfTMkbCNoSMUMWfBhQt7+o3tIrUO46Es+5HjWYPeowerz+szHVUDY1t9bM6S/57F4vsC4yu94BNJvfVl9FnYnmyM6hxGkrE+JX69Z7DrRAIahZjtaINMbaha4XBdfAgDRKFKsTFaDCQXepmZxiHjYO1nICmCoB5yXnWpzReg0t5c3WyAluAz8kcdxy5pFP1ReEsvIZYsK5fty1xek5W1pFl59UpwZrQyrlvpUCogpeDjvQJcbnDDfvmbxvexn6vryDrvV4kaaxWLRSK3TRsPK+IpoFjO5kjXrVZJZkwqV3QHH0c2v6fbht+qUfBMI81u1xZgTh8ZHsRHJOCv1eGbxsiUDr6wIdltCM+ezMk5Z1mz9/k2e/xu2SaIfhp3KDovFmswrwL2LthG9uafRz9p6w+vcqcViUmRotroq3sB/+Bjx08+q7yET3Oi/RbwvO5XmktgiQ8rCrZDrlAvkKB8FUqwAK3MvRwq2qqYNVIMB4B5LkaH4+RPMyxeKDyHjO2ICuvzwYjS5H/Jv0kzWmIvO2O87qXc65Qd1ABjMs51Vf6caxG6aZagLhHtwH+h7pJcXry9faGDa1y1fSLyuWl3u9+Rd1QVsVr90wuKen9khKDaAKVvaXBTEZcsMjuPkmGvaCoJTPtHcLylJmKR6PCA7NhH4wT3g488Oly/U6M0ryheW8XpN+UKvIe6zkxqJ+/RzuBD2NQk7BiblwD+8P+GPBXCEex/lKEf54uVOaRbFDkbWMsyKqyt3/ORT+MePauLOcgHe7gRVqPZ4tmVT1wkyM1+jlBRErusBsdWJSDgzre342VO5dkoT4JZU8z6pDs6XF+K8y/fQEnv04z8M2vY1UxMALxqkM3FUuhcb8Co7Hdc7xEcCOPK//Ymc/PiB8HQuhIuTF9kR+fwl8PC+8HBq9WwFSy2akoINAP75pajT3QC+Jw5d9zJXEc8JVHrd9D3hC4l/6FtSEwQoKEP2hNgGuIwxGM5ahLXwhMSF9awLErHgPwxsPD66B5cBWOlE+j22AeGlcnBS6QN1Ayg7ONNJK87Jz59h/MPfkmMLcUJK3ZCq2XQPG7QvRmF/MiYaB4ewHpFah/aTXDGdGf3XThFbh+V3xWcxni/ArQONcl2y9rwjjCuPsNbaJ7LPtr/zFJ/8mR/H2cfZ+RsIKRDCJqF7KO9I2HEhFR6VESsQmIBmy/A9ozuXE+7/yy1cL9m6ZGgEN4+XGFcOq493Zcye/8k/gM1HDqcf13YOK0KzqX+nJr+XjdQNadaM4TSbzREY/45JD3iN3KnFYk84AYZjsYhVs3Kq9BTHX6tTX1n/0qAfmVwh1yVr3ui9rG9gEFr6AjAaRvHyq/NOEZzbXqIV5t7yDucHZdXWYZQJan1N2ZGrtPslBRqQyTjGEl0oICrmCegIu04iQMMA2hiHLCCAMeXoRDV//GUnVPLalwxqoyGW9gVA0rJjjVoQC638xJOfZLFBYlko8ndul02f3VgXPIXPD3FC2OuSlBHgfihkvK6P4hBW34ImXBIhXPal0E9+kAADrh/hOlcRtYkRLgfQwpc2h5f8SsJe1+8T9mLXYfU0oXmRzbzgZLEwpLm+SxmABYSlRieEoZxGhu8TKMr1/G4EDVFyRgy3avu8Q9h6hJe7MmaL5yPYB7Qva2Z12Dr4bSzmlBL2ciC4QQh7w7YS9rrx+l62u7tY7JWvS4e/09TquZ2XcQPl3/k1JklYeh5PCXcOpbbHaxL2xlQXMrXrlbBXbW7DBUHjzOdiyEwmRMJ6ncS3R9hr+RcsH2XhkHDS3phA6jRLqFEMMourQxnXEoq1ZDA3IOydQOf1eem9kReRmISD0tc2kI6vtqk8iwQKxpk68BsR9vouGcJeBrEsNL6TBcANxvdF5nosk9X1Ca7Pi2V+DyiHhgGAPQ4S9vouwXdC+GtyGuCHJCUBuBLypkSyKH1fEPZe9Z1SvVlH23Wub6IAk8zKkszkKluX4U+4sdhM06s+++pVn0Qt9LjmnQAVan6bRYxtGzX6Y9qreAjSzFwAQF5YciYokCe0jbbYRLG3EQdwoprVqsqn5rzk/Aw9Rkl2asmfySePcp1ScwY4uDlcR9iRIYnW2iWESTaYg4yP/oYAAoF9XthUEfKCJ7JlGXFVlIoAdnqtOgZSTwRg24AvIGpzdHAe5ShHuZbcXc0CmIbQLKJzToCru581Tw4lmFmdy/J1ElUOzDlfpNEm9DxBcObfN0EyNzVMplwDi6aqtLojBw9eZNBUjKZ0YBJORjZ7QRPEAemdUKQZlir2TgBYM9YmLNqC1ASyXyRX4VJHJiloTMFbGfGpGk1aNaBeHWBcigwrshEA0jLA7eS+mi1J7AEagd4+s6qR8CKAdlmtVntf/QNABbkpUlTNJUW5NgEpc3uKX0H8S0VbAaS4MHPJ/JSTxRlJfeal1JKC3iEtAuLCI5TyC04SxNRnYfrCQc7Xt0OLK/mmwXDmih+APRWn4nCezZDOydbPQDQ+CzDDDwwXCMNZzjp9FuAoFyVSi9gT4qqRosebSrMwnAX05w6+96VC27gkNB7FDNG2pECIC0LwVAoaUQTS9eks3m6xIKJvA7iAGAUjM/8UET0C8DcB/BCAbwP4s8z87KprXPteGodOKFRkAISchkgyOi2DdNuKnZv/rT/OHxX+rICt1UJsQUs6k0FDlaWbhI/iZFUXla4XCLdCpDOOIp0txZk5Gr/AImC8J9GQZkyIp7liVUyIZ/K5zeTa3AZxui7aSdQCFwDaBmnRFGdmSR1fthjv1yrqIZPTkPclSuLnRDG6uOQ4/nB/Ab/NL5Pa4cEhLXxB+/X3GrQv5WWPy/oK+c4jjKnWAlHTCkA8XZSJFnM0JC09gqrYGZYcl0H4KPO941kLf+nh19sCn45LWbhcZKmLkdfM3WOPRaCinsvzlYnZXEbE1tWKZezQ32+RFoTmhfRhvLeQrM0xgYOD76qpl/IkazMsW2HbqxdLrL/uQClHlbxMzGbpsHskjfC72p4xPx4OGe69YfgO6M9lrJZPArjL716o793uwxbDCcHFVRmzzYce62+SODWyjKeE5sIsTnmtTS2BRkZ76dCfZZxLrNGS68gXYYb8cWb+SWb+qfz3LwH4DWb+MQC/kf9+J0JzROCrT369HVd2RjfVZm7WqP3P8/s62n8SV7XvlpGMe0VnTI1Tpvo9k7YR2GebMUJmly/HXvObq0R9AfO22uvpQkGYLBrlXCf/cenTFzyepi12vDBr69442+OK0lSt7Iom7l0bs7+/4K7dhhny8wB+Nn/+FQD/C4D/+G0vOkHB2ZyIlMNG9phz4L4XxJ3+O7tGqbGZMzNpvRUzZjTRAs4RBxuGy5XJNeGMuw50sS4YEb2Xe7ERM8A6+WJEk3dM2nbwGvLsBoTnu8m5tMksz10vkQQliQGAfoDfdvuh034QbUL7mGud8jDAa7RhIzkM5HLoVM2mbJ4sPt/WkKGaUJT5HTRi0kvyk1T/rjgLGqK0VzUeE1UJL3dF49B9MLzgvVqnblbr1O2k1invOrRPch3YYoZIopSaY75r4DejOAxNlIZightSrkiWIwFjwuJZh7gMUrcVQLsbXxk6bQ/UOqWLNc6/E7H6PB93UpEsrEeEbZPHS94hMlXK4sKV0KUbGO2lXK952Zeqaq7P72JwOPm9lGudbsqYnX/3BL4PWD0di3aVGkLYplw8mqcVybr9Wqe+e3ehUwbwd0nKjP+3zPzLAD5i5u/l7z8G8NFb3mNfvKsVr5We33sgKT4gTbg52SlYy1xDWa/UNm4zB+asxgeRYeFWn0XbVq9630sWpfJdZiizAq4modMmVNMjpWpaxIR40gpOIt+a20bMizx5eEJqI9mlZQOxoKzTWhjZ51KCRFSzXU0iFFnzJvd7PGsLLT1iDn06h9RUrsvxpEHYDEBw1QxhhvMOfqhhT1ZTDuILKX3L94zBlRdwDsqCBWU5B2y2xXyRiSYvu8067R4EtF52YtVmtJRf2Eak1kmB5Pwsx5MGcenQZP9DXDWvB2Vlc6mAsl4ssHvk4PtshgRCCtKfnYKyOlcm77BSn0Ue9o4ROkZ/JseXT4Pc1xGSmt5EGO63GFfie9Ex6x547B4T3OiLO25YEdq1q+USlWq2kcLIzdpNQFkpXF/9eNvF4meY+btE9DUAf4+I/h/7JTNzXkj2hIh+EcAvAsASJ4dOOcpRjnKH5K0WC2b+bv73UyL6NQB/BMAnRPQNZv4eEX0DwKdX/PaXAfwyANyjR6/XhSygam6GALnOhpoLmYU5p3cfcnAWFX6MYobslAw274q1nRMzhLW6lXrvMxFsSdDSBKv1LqMveVJsxmfiHNk9s/kwRvh1J9EGVeHVYdoJCrQgPhWYYwh3yj2HoTgwAVQo+zhWEJHW3sgJRxodSXlMw/NdBT8ZjkvyvvhVmiEK3HqIxTOvf1NXWa0pZZgzs7BWa/VvyG4Z+qGU6NOKa4UuUM2QrpdrbivM2RuTyCI4XZ/gdyNScKUiGSWBoSOJaq99ozGhednBDU1BrIZNV/k93ZRoBt7B50pjMgihjPHpxxGLJ/l9yhR5fjPC9TlioiCpyGi1MPLCQetG+y4iZKey34hzlxsH12VHceOx+GSDZhkQnlyWMVt9egZwg8XzsYxB6wlhF6sZohpbdti6XcTC0Or54R2YIUR0CsAx80X+/CcA/OcAfh3ALwD4y/nfv/WG1y/OKQCVgWochYAm+wioaSRcuViURYSI5e+Uco7JAdatTP5KGykGxGdCfqMhMbrciMnBXM2QpgGdnIDOTyunZWIhotFz8ssYH53B7YaSXwEAqQ0S9XAyKVWt9usO/QenIGYscu5Gun8Ct+4kZLnpSgjRjRHpbCll79aZuOeqaMiTzNW56xHvS26If1GJdm00hDLPQ/fNM3lhgbx4iYMytdUMGU4DwibCxVTsXzAj7CLCM6PWKq9mShgfnZacE+03hxOE53mRfWU0pIcfR2y/Ic8sLggUZewVNg0A20ceyxcRyVMxTwQWDoRtQlw4rD7RMUvYfW2F8cThNN8rLf3royEvtYJ5joYMI57+eMD57+ZFIACxJbSXDbaPpA1hKwELSsBwou9CHqIdw3cBQ46GPEiAz2Felyu+syP09wOGE8LZ0pcxe/GjLS5/kHD6e03Z3cYVob0I1QxRa7gluD6gveRJNGT8zXdjhnwE4Ndy9CEA+OvM/HeI6B8C+FUi+gsAfhvAn33jO1zF06Dflc9TODczv94RPIFTHzqeKnxZtZebIvzS9DcFF5GP698UtXzhrF1jBBpf8iAAyGJ0RcrMFyJzCHCyEGWTB5Jk3Moimeo4Kh5jAqFnnh6XM2/WNh2vlKHMSSagThRi+SyLB5djTHq8wr4p4zRI09EBvOmg2jaU+zMXZjc9DjbvAFefyqQPGZ6un18p+bcHxwD1GOaf31DoCyGEeUu55x7zT7t/dwJhdqen4H6Ae/QAACZV1P29e5M8fd5upRBLrqLOuw7xyVMUboQZLwUA+Mw7ITfz5VxSx2Wm1afLykIE7xE//qTW6ABKTY/CLqUJWV/7sPzsYDjXHlPGbc71KvR7w7lY6OcAwDukz55U4JLlq2xMHVTlsOD9IkPKT1HAWNnMCR99WOHFWmRIozQ6NuoI1vJ/eiyK01a1IC12U0y8LAVI9emT/fKFtiiU+Zv7Af7rX8vjVUPQHHyd7EQoxaVtkaHNTv5OCelB1igVQ+KpmhaffJ77m9+bOS+E9hmoZuh2C/rR31cT4ojESbvrKxanbAqp9t0WKe4HpIe5XbluKTde6p4C4CaAPv5M7qk8JwDomx8hna2mtU5zzZJDVdTp5eWkhCIA/G+f/U286D+91qp9hHsf5ShHuZbcbbi3NUE0RJrixD+BtgH6HqSwYD19tRQMRdtUCLbdsc5zwZohsyUt21JZGxDMAoIXBKWppOVOToREV3EW6w3o9KRwOyblvnj8QH7HXDXAJpR6E7TpSik96nqk+1I20F3I79P9E9EmFuKAK+dm4lpHH+zjLAwhMDDFWZAWN5rjLFQTyTwc8Qc+qPgCk8hkE5vSIojTMDJ4YXbwQbJcC9DJ1vQ4XRRHosK2/aKFm+EstFxhyVBdtsIb+fwlxh8QbTAFV3wRE8Le7EuxiWTEDBrP5Xo5XR6QXX48b5Eah8Vn8uxc+41X4iz4AM7CffIUz//gQyw/1xR1Kinqw5lMLzdw9SEsKu4BDLhRsA7bD+R6p98TLg92BK8s3I5AZz9QcBY6ZutvPcbmg4Dl81j8NrEVnIUiOBWhyZ4QNg/3cBbpf/8q8FnMM+0mKeozjglgEg0h75C0XMCkwvl+NASAmBVbiXKQdYYSiVpn2qIkuqqGpq6ThMICytJoyLa2TSfCGEUlzynqNp28RAt0seoGaY+qmLpgOSfw71xqwN7TEgIDEKCYkhzbUgC5z2zyUwpx8fN17X6quRdkzBC3HYRvoR/A2QlHpkIYZwcmIpcJ6tZ1vF0C4CBlBwYT5cntQoyVcmAjJh5vt/Avtnk4XTGN2OSX+LUUAeLGl0WMotybnYC3FG5PMaF52YtDU4FaT55XMmCiSdSNvJf+a5RKzbr1Biff60qkBkSSO7PpES4V5KBRr1QWmbQIpa2uG0FJ2uW3ArDiUDEhvPAIHz8Xk+tyU8Zs+ck53LAUQp7iCwHcUKMhBT3rCP6lEBo3yuieCYuuK3d3sTgQwShiH6RqHEptD0gJAFPWsDg+J6CsPGDDgFLez6ZcWw6Ici8ChSDlA7VCWIy19KH+DhDQVNYsClzau1pGsOsrMKwb5CXKkQ8AVaMIDtSNtV1dJ9/ZcoC6QJnyiIB40WWSj6DVqo4dAC1ArC+9soHx6bJW3dK20zRlmtv8ordNmZSc8qRzKBqEJKJB/AjLRb1unjB876yEAXFF6LSAtIYRKUdu2ADEZDLkfI2TBn435uS3POaOke6vZAIRFd4JOT9MoOhazvCq0CkfCJ1iGNA9MkWtPUmJAEcYzrMG1Vd+CY2ipJCdtBHwjUN3P4dOt8LJoQlxcjIjPjxHWgYE58qY9Q8W2D0MWGStBchIzV3to4Ku2BPCKsDtIpIJnfJ3ru/UvbuLBYA9AhyVONMymGWBMKfwMErIU/+dScEoKBuU7sjeOMssQU0+l8dxQnrK4wja7qqDszBl5ZohphI5jWRIaGrClTjhuslOoBoFdZkpyxKrDiN4szmsWdixydB0HurOU+gIZ5pFofm/2E77fIhzoxuLZsSDKVKU+1qrh8szoZiAbV/a4NTh9/LyoGbBsTI/oc+aRd/DXWaMSPD13QgGht6NssB6X0KxwjJW2bHSSXa+xgh/2U/MDXp5WYsuzzQLeC/Ob1ucGQBvd1h+1iG8qPSA3Hi43VhwEiUKlBKCLpQ5i5dJ2q3P3W8lRYC9MxmyBPdiDTfTLNonO7jI8OvBsIUh11alTDtYHZxu3QlDnNEsrKn1OrkjiwVPTQSgeqLVBzD/ha0yhuzd1wc59K/VLIoa2ZuUbaCaDLtOgEIK7IKYgdfXLHJFq2Qo3ryvqeK7voKX+kEiCMygjLNg9ZY7JwuFTqZhuFXNIp1VzQJq5zsC+1qDMy0DqBOTiU11KxpEGyvUeiWkzZMiRawArxtqFpwneslTSZj4ReIqaxaeJgliFBNoSFKwqFAGCu6Fg4Nb5933jTWL6i9jRwKoaoOkzAMT5iqrWYAhk70LJZ09bFxl9VJAlXMHNYvh4RK7xwELT2WxiK0TUJamqFtQ1lnzVprFMRpylKMc5VpyRzSLK8RqGwYjIZW28jpnqn5p3RGQQ9p1ACdRuw/gLHhdHXnwXjQMR1XDgHjS2dLqMYO7TkwPg7Ow2kcxCZ6/rFEQQ1yDC8hObftJJHU/Yyz3F2SpEx8FUCudkeAW0rPnh3EWpuKW1jJh5lKm8SqcRamt8umMesRwUmjb/AsW9X8YS20MxFR2ZMWKFNNpjKAXl/WSnTh5+elzpAM4C3tM/+Z+gP/8hRw0Dk5rhnhtRxOmplDBWTD4LGtYw4iw6yYs6fz0+StxFnQFzuL0Xz6b4izaBtT1CCVZsWbf6nurtVQ5R3/Cc2kX9bniXhNqBTbvgSfPpA7rdlfGZ/ntgPbJqvym9DemfQcnkZgwM5zFHAPzKrm7i4WbcUioWsksYVJ9aG0DGkepQ2qcVW65EBbuti3q+iR0eiahUx4GGbx2mn2J7U5U9bapJQZCAC0WEzMEl2upPZrLIZbJ/fC+TBb7gnhzn36o1xhGKRGQAJdBYHy6Ev/GIpsj1nw5WcLRw9ebIetNzQ3JZojNDbFmCD+TosPpaw+rGmwdnJ6qo7YRSDTGZEKnkNwQBQQB1dE4jOLgLBm+OXzcNnAHzBA3M0NcN4BfvET82sP8HIyzNbgyUeJJA78ZhPFKoziJQcNpmTg6cWmUDOC08Gg+y+e2zY3NEPr8GS6/9RBLm6K+cAibEeNZTlFXMyTVFHXN4qUkOS39fbne6pNdaatT57F3oJOFmCFPLsuY7X74MbYfNFi8qD4e9tnBeSh0un2wb4ZcfNlCp5z/ZxaElFfV+FKqUE3qiAxjCVU6yCJAKSB+9qRc0j+8Ly+kwV+Q9xXCrfcaR2GUXmamLJdfvKfP4LKmUu61WMCdnwGrZcVjAJPcEGrz4LeNXC8ZuLh3SHnS+21XixhvdmLHewgyE4CjD6QmyckJeLORWiUA0rPncPQQ6eFZeXHJTCytSwIALkhuCPqhpK67Fzlfw7ucop6L9zIDMWI8XcDnMGdll6bqO4CE/Xy/K+nr5UHECHqxrc5jI7Ro6y6WfzN+eA5/qXki0q7UeKlPYij8/HaAcxKSBFDSyMv7oGvueahw6izsCOOqRViP4Nah/Z2n5bt4Itga3cGHr98vNUlSmyn19TqBEBcezUXOb1l4gICWCLsHHr7LeRweZTfvHkh7wzaVqITWDWEv+SbtOsF3lYrPbUdBZM5k80P3MK4clksv4VUA3cOA3SOCN/R/wymhWZtQv9YNaYHYBrQXCcOJLqRA/KfvLkX93UquI2JrgUzqg1ixRW1nPI8gqi+07h67TlQ0rQdir2nvFYUwpiRvxSgOyjHjPLQUwGZXrqkyqeux62omaN+XpLByz1yLhPu+/pv7xX1f65KY9hFQ6pIA2XGqNUd2WrhZQGg0CjR6wiYOCF5gVkUd3pV6HoDMTQ3xTrzp2s5DVdTzeGg7AcAHB9KCRjnaQnmhULwLxZizW7kWJLqiinpLOFhF3Zsq6hZfE17uREvKi5hfD6UmSVqEEs3QkLrbRfiNFnXOyVox4uSzEe3zmnWqVdRLNuw1qqiHXNfFabbyTJoXK/itR7gcSpLd8skAcIPl09rnsL26ivpw6tC+GBF2VbO4Sd2Qo4PzKEc5yrXk7moW81DqpLCQCbXqZ3vMnj+/jsqsELFWNSt3sYWW5/cyxXkmhYkm1H9RtIpZpbSikVjsRIzlc1LbMxcuohjLv3I7lt1Wixhp23MSlSUIRskO5doObbuaZHPw2zCaduXdPUPWy2QTjvQAACAASURBVPGhttfuSzTGUsx5T3Q8zHWkUNHMiTjm/hhtCWO2yW2Bn4wYJVN8Sej+Dtw7/5byuE76ClRqg5hBZZFBIU18N+zEVKslBbO2kBi+SxJKhmAi2EmI1mmRoT4WH0phB88aiOtivaaOzYFixQVMNqaidbkuIuz8hNHLuzj522nFuJzO74dU0/cZ04zr18jdXSzm8qqiQ6863zhJiejtM3Vz9Wxz0YrNcIRJ5bB3JYVYmPbaxo6Kil/OLX4GA7QiwVK8c9F2ZQo+JuU3NeA45+oYv4P2KC1fmVQREzwHkJ23NhP3lqXczwnu4o2u4c11AHDJZb+e3N3FwtYJmR8j2v9sj9lzbcUpe3lT9wOAJFSRCZ2SnWAmzVfP0ZdkyE7E8jJnzWDRTCtyAZO6HtQPk1oe5bhO3lyLhEKo/+bvKYRalwQomsWkLgkgu7bPaEeNwoRQx2SMU0dtYuEOtb8HKioz7+zppIVTP47lBh1G0K7DIdqDMh75M4ApL2eOtnDjxSZPJvLSCcJWeU21toeS1KiMZ+3BcnypcfD5d96k8KdVK8cutTRBg9RmB+fCo3JECKLSFmFOrZeFeDeivx/g+rb0gx3BB4fhXnZm73whcopLjXDkCEXj4PpU6ok0T9uDHC7xJCC2TgBmWcsY7rXYPfCVNBnAeOoRbAJfqz4LwnDi4AY/cXCyv/5qcWcXi0mdkPl3phaIrQ9Cpgp7qS3iqibAmvuRUg0xaiThZClqtE4e72pkw97Le5nYFn25aGsIknPE4PwETtGXWSyTVRhjiVD4xOW4vsylFsnJStqo7V1vgJNVrUsCFNPD1iUBpDaJTqZCFFwQq14WC63knkO2w6MVwmV+LVT1zcS8SuTb32/RuspspeJ3I/wwgrYHXvY8HgBKv4f7CwR9zhoNaWXyqHM1roI4HjcOwyMZA2WzcrEiFAFg+2GDZbu/McQFoV0IC9bqRR2f4dFKjq3lusO9ttQkSS3B52sRS+QirhzawujlwETw6wGX3/QA8oITCMkDzcZj+zijMrdcSnuMK2lv8hJhaS4cfM/lePtsBbcznCRZdo8bDPmc5lKew/qjgM03CKB6fn9GaC/rGMTWREMWhNhQYeWiyEg3WAHu7GJxG6JApC/gQtc79q7EmhjztpikqsmxuckCXM1KdksyqYehC3o2AyYtcQdqj9yG2Pqk5nZSy+Oq39xym77Ie876cdOaKcdoyFGOcpRryZ3VLA5lipbvTOEg2GJChwoRaREiK84VshpFXNLFegKFTfmaACb3okUrmAFFHGaGau77yU7tn1/u4yxMESC6WMNrYtVmi/Ak27IZ1q2Fi9hRyR4FIBDu9UYyENWkUN+IKWIEQBKORoETe3tMtY1oIjI5y7b9dL2Hs2DvSvEfAFh0i4KzcDOfBa83B3EWOh4ASr8XzJUu0DlBH64zOjN78d1OMklpjNI2XI2z8LvlQZwFG5wFXVSYf/tpkGM5ea990kjN2ZiQVkHwEUC5DzuC32Qzs/UCbBsi7v+rAYun+ziLJvtCroOzSPl4eHJ5EGdx8kmLFBzCeiiRonu/06G9bEqBIwAYV1fjLPp7HovnI8ZV9Vn4/vqa9p1dLOYikYwbmBCacWl8FvAeyHkdBYxkMkJJuSVfJT47M331bXDwch9HNSTrHchkaspvXXWMej8hltkryOx96UPJHoX43PT8EorUHADvi+0PABhzjkTmdNT2liiIuS+FAEq5atfoy71qW33lkGh8TdE340WJS3vnouOhn/U6JXSbF4sJ/2c+DpZcFPW/yO8IoKmDM7W+Fl02khoHCk6+M+3lcixPqDZI8aCRMC49SqlRzyU64oZU2pAaBzcExKVD0tRzDZ0aaDcY1cHZKvRfzqUkQLpyrnmuVmLjxJ/TGX/EwmNcEmJjj1EFFmLm4FwRwtaZdvGNzLu7u1jMPJsTX8N1cBaZbYmsZmHYvwtzlK7iwyAT3Z57CGcRc75HUFSnICQ5xUnMmrpBtASbjwLUCTMMk2Q0RREWnMUwSNvCWP7VtvM4Av1gUsFZFgHVrJQTY6i8E9BMf81JoSmCU3EmE2RoQXDGCRbEWf4P278xJ9Qd2BnLeMBEfLZDvZd3QvVXwpV5HIgqrkTh7WOqOAsTUg3eFdq7yb2Dk36NqfJnAOWYalJ+04NHibQER7Uym8nvoVzq0I0J1DhQP6J9MQo3BgCt4O66EU1+DhOchS42qoFsR3HW9nnR3vUHxy9sRnDnJAU/X7d5yWAvUHYVFxluZ5zqO40qOSnYfDmWzYC4jvN15O4uFodCp/pVCDXTNH+mEKah0xCA2E81C5uZp/wOmrF5sprQ2uG5rxEOm6jlvYRAdUceR4mObILsqsqofe8UtPETgA0vmlrNnLmWFARKXQ/6JJj25AQw5tJe2u5Aq5VEFBTCrUCrtilRD0AAQAJxrhEIPwrlmvJklJBtNhHGx2evzQ2J50v4C1/6VJ5LN8DFdBCvUcYDKP0eHyzh1/ncICX3hBSmhgfTIsDtBrhhxPg4J//Nc0OydI9atC/3X+nYOIR1K7khm8qPMjw+A7cOTV4sxgfLHGnhrC3UZDT2UsO0uVBaPC/1Tz9LuPjBFqeN0RgcwW+jMGjhdbkhAb7jYhr49enB3JDu8QLjkrB86op5tP36ApsPHU5NBEhyQ+oCYHNDhlMC+xa9li9MeOdV1I9ylKN8H8jd0ixU7SfaB1jECJATurxM6gpgyidhfsNdX/gcSvpu3xdzRlO1C4FtCBXElO9XUtPtvTZb2fE1DXvXgV5KuUQ213Mv1+L0tGq6KS/Im22FTG+3pVJYHKvTU0sllpKJuQ283Ur26GDal8Fivrdqdmb76gd41XC2O2l7xpsodJi3QjAcnlzumSHqlykw7SEWtibra6ExynUOJZLpeOTzAKBJqWgrhd07+MqNAXGgUjcAmy2C+jM0jdyUV9R2+fW+GRKyGYImFHZzAAhPMuAtY0yaz1uhvUtCrFvp+CDmRXAF1i2+DoJ/fonz312ieZo1FmOG+F2uImfMEC2oPDdDUps5OF+sD5ohq49bpNbDX+wqDWBihG2L1iSSLZZ+aob4aoaMS8maLeULGXBfRQfnxMS4rrhcQbxAioXQ5GDRn2tfUx2nBxCi7xJrYXES2h5DdDI57n3l9tSFwpEACLTt3uMg/PGW+2DJWcp/M2i3dfDeprDCzUsKvzpZDRJXm+Yw4c24/baZz28Iyy+cJAXweLPnfXcXi1f4LK4D9y55IDanxHqZSzQj/+ucRBrKxD8M9y7/WQi5o737I3jQ6KbxmxCqr8PNIiN6nMyk9uK9J1+9+JSTwORlNlEeQNoUjI/GHWivLhQaDZl7w5tQoyyqzXgnx/Mp3Hhg8OV8Fda2+H1vvo6HfgZkspVjWhc1uInTjX2uOOZcLVuQoyHWIQpINEQdhVaUrIcbXykCAHCTQ6cK8Q8O3DggIsO7NTKDolmoE5ubvADnSEaYhESFE1PDodK/w6FTSh6UiynLmPg9Tg69X2odnNF40sJjXDo0xmcRFzVqBUxDp6kVhKxGZCjxjRwRd3exmJshSnUGXCsawso2beuEmu9KFueNs05Z8Bi68KScdcqzFL7bzjpVFi5te871mGSdlsI65l4pyTalxxVLkfL4veOs03KdjBUh5gkHCZlnc+tZp4NonRQjHNHUDGEJ4ZZjThZ0iumdZJ3SEOG0jeObZZ2yE1YubyNOX4ms07lmQc5kkl5Ds/AOnPKOrC+vc5VU5Q0TyRCCnGtqokrdyiFjDLJNeuuJZO007KnYi1WNhmiuCxHV6ytPZqaY40In6ACm95dIZjAUkrpeMR3OOaAbbj+R7ET8AkgBaeHLZKeYisnhfB6D1guL92XzThLJxrNWKtnHWtrgTRLJAGB8w0SyYzTkKEc5yrXkTmkWys7NwwhbUR1AqVnqP3wsXJulFkgEOGV6PfObxIZ5OoOJPvxAPN39gJgJaktGad4RK1Bq2Ct7yDHCn5yIx193X2apbL2RY+7Bfbn99z6V6t9ml7VVznmohL1pHEFaK1UjCZ8/KQWNEGOtGDaM4GfP4XiKZyUiAX3Zqu9ZC0FKBUehFeelW1ydiQ/vCyDot767T1EITKqbuyYUMBtZRGSMSKNhmra/33X1uvk3fn1evzeV5C1jdwGGNQH0W9+t92QxMcnswoumnRYGyuIybyt5j7St0RB6eTE55hPDe2kDnyyr2aOm3Rgry3ouZ5genOHeP/iOlIqsnQFSRKPPOqYKlJv4uiSKVkB1ANJ6s09IBGBpsqOVi3T1f/42TpaLGtHL15+kGBhnd/zmY7gXmwmK1W/3I1dXyZ1aLDCbnHvfcbqy6NBcZBFxIOIaLt11sqDc0As8kRRLGFfbyplxip0r+SS3LrMJzcpbAVQ1ljOXZZwuorV8VSpudtr1ByfarYo1V+wEsVXVtO3vItJkiyIlrhykGqJNqZZdSAlIrhYteldt6/o3jgxRFOY0phs4KozcqcWCzcvqlsvJiqzfxZcvEb7+Ua0GfrJCurgUOv5tJb2l1VLOOVmB8m/Ts1oTw33rR+T3F3lHf3QOZwrX+u98LNccY73X6YmwgT9+WH0dT56DHz8o3BLp5YW08w99C/6ym9TWTKsGw/0FmIDF51uMZ2Lnhuc7dN88AxJj9Zuye8Yf+ADu+Rp8uoS72BbWbv/pM6SvPcR4uqjFeDUhbdUWzgcAaD9dS67Hti/ox/Ak1+/IPoji48i79vqP/X40a3X4qS9EciV8J33p7we0L0YpNLyqu1TYRjRPt6bqF5eEteEb9wokejwXDXJcebTPc7KeRguWHn4XS0RkPA0I6xHN7z7B+t/6/XJsSXAj4EaeIBA3Hzgsn+U264bKQGyAxcuEcUk4++1NOX75gyeIC8L5t+XY9uECcenkumFaM5QDZcLbmNspm8X5//scv/Xnfwhn35H2pgCkBmgvGdsP5ZywEd4NYsaQ0ZOpAUBAWANhx+jvy/HH/2wo41xycYiw/maD4ZRw/jtjGbNP/+1/A+sfZJz9Th2D/hxoX8i1wUDK5PZxAVAE2pf30d/LMPQR6P+Hfe6Mq+ROLRZW5k4yGxNms/OUz3PVeZTiQzTWIkSTuHJhxpaXi3ZSIHkStlKvvNmpeRwLazaQF7Gu3ysy5HaDTBqNSACgnuC32Wk2xJJ7QDHCb0bZ8DUHQYE3g0Q9rJefxiSQ7G4KcgJRJa4BZBcaJTu1QLhzv0s0Rs2u3O5mPRaqeRql7Sk4NIll8QDQBMmqROL6AvGBaIRmj6YEtx3Ld1q8uNF+oGIHKLJkmprn6dcdMAwIa42iOLjIQt5ikqgWLwnNOgGEGhJmIBByweFaUBmRETYRlGqt0+ZigO99yTJVWDWQw7yxlgLwGqLteiyeAYuLDE8PhNgA7Toh5oUs7BjsOIOg5GdJict2gO+4hJX8Lkllc09lvNkRFi88fO+kjXnMFs9PMJ4QmguuTOID0FxyWSyU/Ca18l17yXBaryoC7gZUlUcH51GOcpRryZ3VLF4pbGzHcmzmhyhJY4f9E2WHUYxCxlDsXWduV2c27+IIZbFt55qQZEZy0VyAbDOqWZJqeBAxTSpt630pVX/LxI5n2VUnNjUg2pWN2cckG5a9vmInSMyDuUZGg2G1jgw4hhuBlNOupW/Vprfp0DSmYu/Px44SlzZQVL+JBWBljWx0OcuU89+Zt4IZTp18g4T9JCU+mV1VTAh2ZDAy+bvIwMhlzCklOXectsuNCTQymGkCDiNOcD1N2qVj7HuGG+z9CG7gwhXhh9qmgnEobZbaHW7Q5K783E3bKcn1XdDnzuW3viP4oWomzhP8kKE0bG4EOU/alY9EfDVwFq/jryhOHhuTLqrnDRQmw3C9B6H2wm0w4cO4riisNlX0JNs2E1W9zmcMSeIp34Kycs/bdZvOPnv9DHPmjAyvcHIUuHillefaXsU+qAtKcSCap3CD2L6Vyfhx5ZhAnQ+ZmbveQ0ohyG/Z1bax1g8yLN5vKuzMK6f3Jyo7mY6fTN56TO9v6e4UrMXBCb0CcDWknMy9D4yB9luPv63c2cXilXIoT2Q+gRxN/51JIZ7RA95N/AtyEletw97Hm5yAnEcwvz97k0NS2oJKTjODjJeXRu81zzex/dCJp33Q33hfJ6r20XvAxzp5NKHJu4NkPxyoQITdmF+8kKHPY7XLXV4w1DfAIHjNoZhrZ7m9c8IhO1HVZ5GCgxs9VNNIwYE8wZnFJgWSIYx5wci3iQ0hhDzZPCb3crEe02eRMsdD8dt46TtR9llY2HkQ8hnlh9AxYu+QGiop6HINAUGpv4ASMrSbELM/WX0WlAHAepwdBBpu/S5OrpcaGYPiDG7keinUBTO2gO9lkSDmch/5l+D76segiK8I3BuYTJAJ27c9rqjJ+QLifcmjOKiFKAIzT2bO5ykikOTiB7SNnMehGA6fP9vcDQCxDQLN1d8Bgu/XHIDMtARAYv3tdHHg4Gp7vKsOQKDySwxTyDU3YcK27ZpQMnQVNVmyRHOuhyIwFS8xLj2abEYkR2WxiAtXSmfEpVDKWzYoYtnFJd9DE7Dy2MWEZHIaOPc7Nq7UCC05DBnh6Mb6txsbIIRyr7h02WRgocfPi9O4ynU/Jw5OLYgsLFJ6H/07tvWZx6Uv7N7saVIqJDUO44kruSeKxFw0AcOZZe0mpFaur5EPJvz/7L1bqC1Jmh72/RGRmWutfTm3qurqy9w89FyskRGysB89oCcL2bIRCOvFthAePUj4xQ+WbYxsjEAPvmAQCMZYyPNgyXrzYA3I2GAEAsluzIylHkbt8fR0V810V9W57cu6ZGZE/H74/z8icu196uxT1TWcbnbAOWvtXLkiI2NlRkZ8//d/H1jz9OaN7meDg5cBIpbtDsTyHad3MjthX84bwrCqvqpxA8xnjPiytnM+EfUtuVAIaajHoygXy6Tq3rK8xJ3L2ztYaIaolRsZco1v6fE2AqpSVkOMWtTRYgBEEjdfzCA0LTvlJlGLSh5H2dNyFprcDQBi7puB1oSZEsNNWaag5hYGSJ6BrlXLINaSkyxnAhB6OZGkbbekIQCYY1V30r8pi1KWpYK3OR0Ua76FRUP8mAsKTxb6jFluHGvuVNf4BcewtTQzch90P4l6EFDxFUBwAyIJkY6mPFUf+200xAUn+8RYfDl50rU7S/i0RBJGwQlyIDAZNiHqVDK4oFmqEtzEoJ7LVN0fUlGPOo6GuCgRBq/p3wUKmCP8XiMaAJwHIghhZISdbAujDVi1rSkRkAXP8BPgNQpuFAj2VCnvBHS7DGK36LOwB8JW8BGrN5BEWGQmU7G5HAE/Av2Wy3SaEuDeALO4j4bcl/tyX+5U3t6ZxVFplyEUAth4EqpZQcGDDw0ZaBiEU9D1jZhLM1NZWRKXuIrndSeJSfpULPMVAx4BeaIPA3g9FPKW2w/ImwFuL+wXUgLXfNpL50ZXnlx5FTBpcpGbEuJG3ndzwnwSQMzodQaRhwC3n8F9AI2xUHz9BetyJpQMRljK8qbH9KAmkg3joIlYhHSmEn5lKeCBOSFvVIFalyPTg4BO19+kT9McSJYeOqOYHnj0lzJltqQkMMAhw+9DfSKayxgc4iaYbCnSRhzIbcoNoCzJ4toj7H0Rxp3OO/SO4C56TGe2VCK4BDXJqTPLw+O6BCmAI8tTtr/OSANheGlLA1G7njeEjS4Bp/OuEL5yQHEbB6QPptOaEm/yeP0nAw7vMcLelf1yL8uq/XuyT9iRPJaZMJ9ofT0AYoQdwR+A6Vy2x+87+LECnfLjALt3POIJIexrstz+XcLhywl+9mVmEU+AtDL8S8hYcj0JxyNeUjkWJfxomgwtSFkx3gAuOaZmmwfmSUhZ+npchzs0pCzn4Iwj3+Ibzi14+yACjyNoH4qeA48jaDeW3AA7VtjOKmGfC+joDkB/qSY6c0ZQWXkqBKEKOLopgZ0ShphLCrToQmT46VDk+IuQbubiFAYAtBtFYXycimamKVxhFuWrkj2qy5H+IgrhCigMTEeAm+uN019qqvOcwaSDqxkEz6kqbDdR2bBPsjQD4E2hehvhr2T+7ey8x7BYhvSZCwGtu9bvT65M6fMgeAQg6//+SvQujdlJiSVkODH83GBdidFfJYBEcxMA+hcTwvBqUpYfPbpLXQIo9kS7EatPCKuXCv56RlwRhssqqeBHACR91G3rYENJQFR/QAmdCikrI/cOXlPNc+eweZoQtw79i6n02erpGmnl0b+spKywI3TXXJYhho2kjhAOjP5aBijpA8Et7lre3sHCtChui2YcuYJzSiBzN7fPXydx3vIXTPMic+UppCSzjpwLO5Nu0Rn4tPopCdRd8AaNFBBUK8HAtjkJhyCjkcpjYYr2nRy3eKtGaeMXtIAsehJQnIEJUI6Fxfdz7wQHiFxmAJQh7xODUuNKDijfpHJMCo38DcN5BbPwXNfjTSqOXPza9oajAMUhKNYBgGIuvhluUgp3K1bzBoVSxQaIZGYi7dN2J67hTW6+wwyKUDZqPUcXWXkdFTvK3c1blbKAlm6u55utb+xYuemHz1ne3sHiKGS5XIZ40aoAipIUhdAQo9LroyHW+XOU7L9eps+8qtEB7sRLg5IpKfm7R0MGqY8aL4zce4lWkDxBS+QiZ8R1WACcPHjw3OlrqMujLoAHL8uvLyIasvbloqDoij5DGipVOm4cmALcnBFPjKYt0313aJS6Zo2GZDHRsUEzrVXxivBG0ZC4OVqGZEbqqNwo8ynBJY/sUZYnlBkuybQ+9YRO6fAUM+LGYTp1WGmfpcF9pmjIdA7MF7YM0VlDphJ1yKECjvHErg/pAD9KWNP8R+PGwXnJx3EWjg23R0PmM8L0UGYK1gdpBYC48S6p0ZA04nNFQ+4BzvtyX+7LncrbO7P4tNJSisumZlvmql92l7rakGlq6tClUKGWv4mpMrNO6QGbC1JhCi2PayHHhQRglvRyzn7ZRluufJHDfBtBZgaDloY0bKFelOkzsa6bc1OB0sUlzNnQqjMvGI5v2q4yxebmvX3ODOKGUFW+Y+2tbSjLk885RT9uQ1mSHLX3xn7tdqvLljSp6e9XMXb1u2XZYefL9fwWffM5y9s7WBwJgNzIOuWKLTDf8oO/jmdRsAFbR6cl9wK2Zm8GIc2luBPPwjIwcxbKNwBQhDeptjnB+YpZhIPyMlKzrjcJtTbr1N63mpQ/QJ5F2KeyhqeYwd7BO15gFhxEd9LNuUQdiCF6knMqA5loPsg50VTPwabyTHgjnkXlODgZpJjhYmUvdgMh7BkcGls+vXH8QfJYin5lzAj7XEFkKHFSB5A34Vl010C3N4CT4BKh2zPStezkx7osqFwV4c64yXgY0H2tX6nkn+QMdDu6wbPotozuUk2FGiyk29Zlj+Ws5E6YnZ+HZ/F2DBZEwmZpla7Ul9SUp9LHn9TPWmFe85iYJ9CpOlaNE3i7lQFjaiwEm++ZXSBiBJJSkZmrJeBmJZhFTKDC9iSwie+Y2tT+IPiGbbeL/HJf7APLk2FyCAagjhO8paGPM8ILXZ+aLiez5oxYXxgCpolWF/viw1Ec0w5jMR0GAN7uhAUaY03CMqUoVb4yBa2sIG73fF8HJmu7MUl1IPT7oAMWC0YBABmLgUIapNL6c4TfTXWw0P5w20ONzujA6cyfxAbN3SjWh7s9+meqV9JV/KRVJw+7rqS/t7ICYCXJtU/onBH2EX6kEhnzL3fVk8S5pX+Hd+j6IP4jQMWsrrY4/07E8KzaF+bg4PcRYasanFMu9GsDUXMgnW3JALR/V/fdi1UjN/aJzhG6Fxl5FcTXRfvs9MMThH2H4WVsQtBLHY6Whh72Ce6QsDbfkMyFTHaX8nYMFrcUaoV2bysmYOtdpXsbWJcSckoyk7DX47LIp6hMyTZnhFed3PCWTxG0TdNc5e7t76PwbKsxsUgEsgvQuXJDFJAxMXil0oJE4E0PmqIMWkXgZhBAdpqqJker/L1vbohplpvJjJl0m5x3LrMvADUC0io/ZZaIDbMa4ZhMIavNYGxuQC4DRTpVc52x+Zy5ius66ZfiPo8KDFMIokXSLP14nhcK56U46OCpszlVyua+odInRrgay2CXTnQwniSak9augMfuxbX8Pq1aejkWAXOoru/2e0xz1aAAJOfGiYFy2Okgbn07p8KOTSsPP2ekTmY74aCDnwLiqavnxb1D9/ISbgqLPvOHhDD6wmYFAB8ZfkzgQBKtssHCEcLLEW6KyIdQ+vZ4Nv1p5R7gvC/35b7cqby1MwtmARZvhXYaHIFJlyHmbg7call/ax3AUuORCER1Ck5zkqdLo51x50kbV4C05VkYm9OmmoA+eVQotmAvmhtAyerRaXlMNe34iygtyMpc08wdFcNeyVuQGRyM6JRU75PEug9Ao/YVlyK8n0NDUt4YlqT1GJeABGdxVHEMw53KEmisOFHugxDJPqeOpotVW4QY4FnCxTVvpn5WdCzUs0N4FXVfN8s14zNqf/PtaH3RuYjNNQYopwXKR9J9P9cZSnlrB4vXlmPS1VEm6huX275ja9/XodKfVqdrvveKV7Z9mHEjFf22oMHrCGefp7Tn25ZmoFv0Q6t9YfoJx587Kmv2G997g8K3HfdV+9jHR5aOZbAu7f5sbVkes63/1W2i5lEjCXZc3nPzfaJluz7t4VCiSlz//qKujtcOFkT0NwH8SQAfM/Mv6LbHAP4nAD8J4HcB/BlmfkHyC/y3AP4EgB2Af5eZ/+/XN4NxQ9E7JRkZb1Pzzkf720xDNSnZ5No/rRRHsrzsXIOlx0mehtO8DK3etdzmhqY/JDt98jTtZ3PYmo8wA3MNs3qaCMYXUhpT4nIemmZe0Qm3aB+AylZt2kaz0vI1KlNmaJ91ZmEzR+fKbEIydi1VU0ykmBtVr8QlhAsiuEb31DEju5rq/1kLZVQFLtSISg2NW/vqFnPtxQAAIABJREFUjLhkGUOwA6N2+1FmspnrzOxVWIHVYQI/cnyZZXBGE7r/gURO7zSz+FsA/jqAX2m2/WUA/zsz/zUi+sv6938I4F8F8HX99y8D+Bv6+tnK4ilrCUtJHMA0F4O6TiT++24B1rlhEDqCvgIo+Q8AwKcb+f5hkqfm6VpuFPMc1YEHIVQQzjvQyQa02TR6GAQ6PyttJd4CANLjc7jDtBDU4SEgnQj4Fy4PyGtNKtuOiI9PAGZ03xNxgnwywG1HATzVARwA6OIavBpAQw/a6UBq4dChQzrblHP0L68FcBtn8LlkMNHlVs9LIiwl+qJRkfnL53Am2JsN9CXRo9CLPm4Cwl4Gc9PnIGbQlOF3Ux3YgpcnXWbExyfFoyJpAh3OV0WhPJsIztCBxrksOdKmh9tNIADTlyTalXqn/AhB/21qPz7w6K+yqkdRaRewgj9IzojldlByGJ+skAfCRsHJ/GAN7p3I6gVa2ADCkbBbVfnc3NB7AC+/3uPkI1/OI3eEbituYUANjVIGZtO9MCO4UT4/PJLtD4ASOi0KXp4wvrNGXDusv1/77OKnN9i977D5qEkkWxH6LRdlLhO6SR0QxhW6bVUYpwSk79yd4v7awYKZ/wER/eTR5j8F4Bf1/f8A4P+ADBZ/CsCvsNy1/4iIHhLRl5n5e3du0V1Kmz268HZoQpyTXMxsM5SjUp6AKQmirqHUG9Z7R2tBzBE8TVV7co7AYaxPe1t7HiZ5oqZcIywHbjJFY31ixCRq4K3m49Ss+5kXswlKSdprxkH2dGdeGP/iIIlkPM+gnYZ6beCLYkZTLAVNz+K6hjiNb0BEi6dv0FAkxfp9Sqxof6pRDyOmMcPv5wY30NDpIdYBr+GcWL8BgMsZdJjA04xwrZyMzgl/glmUrZqfKGyjqH01KmKkeha+4S4gZnTXESlVUZ6wm9R0OS/o9IDgNG7q4HZ6nViy3GHE6nlGf6GDiFLju22snArNhaFcs1NTTyW/xY8MJrWgsNCpd4sISz+OCHuPcHkofbZ6kZADYbjIlWuyJ4RdrolknVHOCWEv4eKwr8l/lktzl/JZoyFfagaA7wP4kr7/KoAPmv0+1G335b7clx/y8rkBTmZmotvsaD+9ENEvAfglAFhhcxPF+7R1rfeVtBO8rGFDqBqPgDxRXSyvABYp02YIbGpQvOplJmLT/d1B9SsdKOmYqglk1Pd1GTJNwGqoTmT61MybHu6gVnKNrF7a9AAJG92WAA4y3QYzumshTeVVB5flO465yuqNk/ACnCtdRs0yJJ+sajfNUZYhRGLH1+wLJT9ZG2xWFs+Gxs+ESyIZd66sy9MmwI8ONOeSFEaZ4SYvkQh7BDVgYtp0ZUaRdPmV+1AuQD5ahtix8qaX2dJuj/lMDYx7JWVl8Q2xq28696KS5QhcKtaIwyxGP92VNi04zGcBce3QXWpi27p7/TLEtDdtGXIxYP+Ok2Q3AOxl1pA7wvhAZwujq4lkugxJvSwT3Cy+IoeHsr2/DPCTLJlMCVyWgQ5x7UBTLn12eOxVM8OXDNc0AN2K6jKkq8uecCB0W7dYhrR6IK8rn3Vm8RERfRkA9PVj3f57AH6s2e9ruu1GYeZfZuY/xsx/rKPhjQ5OFqX4QUUFjhF829a+foHllWi3O3pvCPkX3CZD528g+8bmpObv5jvH+x3vc6OuNy0k/xZq483ftV3HEYYmQmJto7Y++tSIw+sKL/qhtqO8f03V3LSl/k2Lba8szTnfaf/PUT7rzOJXAfw7AP6avv7Pzfa/RER/BwJsXtwJr2D9r2X7KYCZLi8BoNoZdgEcY6VXE8F8UNPTak/o33ki99ZmXfMMhkETzurTHvMMzABO1nWNDSA/fwE6HCQXx+wL5zVoswGfbapSVkzID07gplnQdj1+7EXEZcGQ63xJwQ4XjKRPqTDN4LABQMDHz6T9Qy/WiOenoMtr4Fyp7M9fgvoO8d0zeNPDsByCxh4RAAZWpuV+RnwoM4vOZPlVWNdAVr89A1jsCLviPVIFY1PnSl5E7h2wjbfcoEcU7racr0okQpigjPHJUGcUppS18vBjX3Qy5tOA7jqgmyNSXwV7XWSZATR55NOpCvY2hR0hrgl0IeLCm+9U4+jpQS90a8Uhdj9+VpSyUk8Ih6rVkTvCvCasXpqil5Pz3Z9jegDMl/oEV3Vvl1yxJMxblJlOEeYN8q+/gKTUF/cyoWQfl6uf2SBuAGCFfiOVjecO40MWu0I7p/NGJQwoKeppAPYdoX8JTJJBISnqVVjtteUuodO/DQEz3yGiDwH8Fcgg8XeJ6M8D+A6AP6O7/xokbPrbkNDpn7t7U5blmKK9AB6n6nBO+l4sBZs4tlGGX0FntQvawqy0OyzCklnrBLA4FoZBTYR1GRKjRBtiXIQECxDVUoZzRjB7wt2h6kbsR4SXS6UttzsIMLkfy6u1y+1H+OteLBcBGSx1oAot32RUS8Zpht/6so0daVJVujG17F9O1eqwkcfzY1eT0RhFrcm0Fazulo7clhaYa5cefqvnEPTmm7KaF1XhF6fWksUXVZcKN0WOevSXN8PmqXMCfPauAqoA+pcr2baVbf3lCn4U5ay0ciXHgrLqW+xdtS88eAF/54yT32esnxoYKQOU3yeQhjzCPpfpvsnxsZeBpd9m+JER1/rgUEr2cVk/HxB3hP4ylgS3k48TiB02H9drvNtqYpkWG4RSL8rfqxeMoCkBkmh241CvLHeJhvzZV3z0x2/ZlwH8xbsf/r7cl/vyw1J+aBicC4ey21zIjvELchXbaPdNLElCja4mgGK6s0j6uo0laolhtp9zAja64/pIwNF2RtSYALGv4q/k3cIcyD4Xn5LmtdQjpj901Fb2VE2Mmrahqb+tl5vkLnIOyFlNbCzAa09L35j/iGqUaWbmpt0uKiB8y/o/N6ZIi6WHKWR10q7cOYUVqGynWc6jmgyJERDFXMO0WPqCLI6t5kA5uMXva6ZCaM4ld2JglHvRyAQUCOwcck/V86TXjODgRKC3CVGyFx6HGQdRruK7xntgr2DoVJ/8gNTH6Wb/GWiam4zb1BHSquqN2n5+ar9Xt4tPChcRX8q4iUt9SvmhGSwAvDmg6YQjwOVGlovsc5WjQaakYQNyY97mlvZFlBZENDOfI/DT3KvIueVFccu+rTvaH2RpwdIK9BFa8sRtjm9fVFuYZLBYqGsDDfhYwVKm2wenL6S0wOlnBPaPbRXfFAx9aweLhQPZcWl1NVutzXa97h34eD2mlbEZ+Oj3ARRNysKU1DrL+3bf4OsTmUiejuaZasdQx7B2aGo1Ml0XFrqYtr1r2lP0Pu0VGhIOfuHwRVER/U6czYppzrY+kQuJKPgKcCoAqp0CAEWDEkDVwQyuALOA6HS6UdrbbgdUjyLcvKwWDmp63nHliyitzCzkie2oEMpF+zNmwFHRvbQ2uplKKjoAzBsHf1i2R/YnuEncxoZG+NYcyHrdlgeHNEjYNXVUFLeZqdgRmh1CWtUBeDoj9JfWV3XmNJ3q9x3BJGNbgNPyw/JImDfWpnCryFtcCVCbrkXfExDN0ekcmF42IO8Zob3obBaRBkJcq4uZhk5dqm24S3lrB4sbGhStQ1mjw2BKWHSkW8HM8pRvn0jeAzkKbdu4CVbnHBcKWFZnqUuPVfIk2notwtLMLMwxbKEI3ipZzXGhXmXbC5iq6lsUVb1c68kpwUWV1W+c18k5IObqeGbt0rJwXPeqldAobiMId8Uf0iJ/AkBZftj2sPfl/eInOuj5xpufLRzU9Lz92NeMTJ1ROOJFHomfcqGdtypV5kjfMhC7nRMa+vGxsytuYy0TtjiQ6TY3s6iCRQZ1rQyg1sNidyB/6NLDEforRrfTQS8Q2DPCLqO/tggHNxnG8nVbhnTXYlVgA4A/1OuiLX5k4YxMXH7f7prRXwq9u54sFn8nw8AngAMh7FEGLqeU+buWt3awuFEWyU188/3x4GLJZsd0bXttk3ugN9PxIHBrnTow2LqSNVHJtmsRO7+8jMakVKwG5DOtP+VqQVC+n2s05ziqo98tCVSZAWQgk0QSyn6WiNYMCsdJYkWrsqFt24BV6OcJLro6eMy5GUjqk52SKFzdoMy3/WHtsnqsP3Tp4bQtJVU/atsbDU8Xc4mGUDP19CNXOndTmKD2hXlho2jb0JxX9iJcI+db+8TBgTNKSJeNzJRFGs/k6yjLwOCmDD8ZKYuLmY9NHC0a4mcusntyvnlB+y/nNsuA6VLtBz8z/IHLsQGRzmv/rmsNhpvE6tBrZLu1K7hLuRe/uS/35b7cqby1M4tPxSy6AJqm5fsuLDCLhe2gFW6eekZznpTqu+plitpiFvZ+OtJdND8O288rvkEkJC8oTTnnxbSXVwPSqdoFHvpqHThOZbthFrzqgZ3iGlPFN8h7oXWvQp0BSEOETr5ufEMO6olChDxUrASQCAcBjXuYPGHjSfN9I3spZuEUp5nOO/Taty1m4YITzcxbZhbJ+kP7BhDCVTHutSjDoE5curyIG4/ADJ+5tK1iFnmBWRwe1ezLxbGV25BWHt2qspDiSUBaeQSVMoxrj7h2cFEjD0oCE5MfQhxceRLHtVC4+xfA4QkVq0PDLLqBsH8sx+12/pWYRe7FrtAwi81pDxxuPsOnUycu8aND2CY9X7FI9M3+0zkhdc0ypMUsNoAfCdN5xSx+JOwLb9XNNBLO3Gg06nua45FLeoM32NS7CZvZurC4jR0mIVDpNDU34r3tsZCyfDfUaX1R226K2021zqb4a1+OZxmiNM7w10vxXXeYhOhlhC9tb04JbpwXWZyImjk7KsnJ1sdT1Ol7KqK0hZSluhXuKAoStvEGKYs8wcVKyuodlX0sJ8LqpnG+VU+k9AdQjtldh9quWcKapKpRtjwJzILn5FzSw80N7ZiUxYHQX91CyjoIKcvPuQo127nOuaTnh91GlyayljcNTRH8JbiRSxsoSvjaxYzVM8ZwcZOUxe4WUtbhdlJW0BveX0+3krL6qzX8SOiuU/ldVi8ycnDFOlH65lWkLMY0EYYLLpaFlPHDa19orlis9O1FUYFbNwzI41i0KTIAnqPaVRyt6x0J2GY3+2pV/uYLoZEXtqFZIlobrE59b8fycS2sTdtvmkG7A3icJFTby5OLn75YKosDQBfgt0Id58MIKI2c9wd4HbSSsUZfXooSt6bEtwKxfHEJ186cVAmcxglu5yqYpraHlDKczXB2e+WfKGBsYFoXACJ0Hz4rs6Nia0AkAsnaRnfRF6EhtJGPGMG7fQWNm0LadmsDAHQmjmu/r/FiiCrAaQI7zNI2QMDYW+wtw/PVYjCwYpoeCB788rL+HNo/fCnZZX3fyUwrMcJpX0HcmKvMoZ531wVwJ0mMj795BXepqul2DnPE8LGaZc+phKZtJsc6IyW1PSjpA5+8vFUWctMHaQNzEU4++60dNr8/IFxUVmruw2KwKZwW73F4f4PhxYjcRMBaJfDXlbdqsOAGRXer1QIos5s6XV4ivP8l8EE6iNZr5Ost3MmmbGNF/Hk3gjZNqOzps1r/z/60vF7vhAz08BSIWawBAfjvBtDZidysKp9PJxtgnMDnp3WJ8uwl+GRdJfV1EIp/9Gfgt/NCkTqvOsznvSDoz/aSaQqhQu+/fAowY/ObUm/86mP4iz3yqoe73oM3cuH5pxdI7z0SWXgVQSkDybrH/Hhdjtd/vJUQ735CfCK5JUY3Rxfk3NbSBvq25Ptt/5WfK9Ncl0TCnr1oNFjkYTrz6K4TXORiKQiW6EL/7LAASEX8JmP60mnRo5jP+hImLRRuX5cK/lCfnvEkIGwjug+f4eqPfkX2GRrxm+YK3j9xWL1gFb+RbcTyvtsyUk84/fCR/hiM3VdWiGvC+bdl23TelbyTHJaS+hwI84lDrzOItJIDnH3rJb79p5/g9IMz3U8IUP0VY/+uRkN2msOSxeUckCxQJiDsIS7qmq/xzj89l4iWKoRb3+zfDZhPCGffjaXPfv+PP8b2xzNOPjgpy6+4Afor1KxTW4b0MovoL0NdhkRg/tbdYct7gPO+3Jf7cqfyVs0sFqXlVQBLZqT39W8jZRFVjgNxBRzt9aiOQqryXvUafAEJ5fjC4CPfsDJVNwM6BQUghsxdQ0QymvLgi9KRDcnc+UIs4s4jDbpO7TzSoGQbVynN3jmlRPumXUKR5t7VNtg59WHhBM6dfE+8NJoZhX5G+h3rB0BNfTUcyrP0Qw4kJCQlJMWVZHey55IYJcrVrtChZWPVzEy9E4UrKP2alNjUV+IXoOAlV3DV/DUQan/Na8kMdQlqjGxgKCHucXNm4eUpGodK4qIkpsFxVYHMtHIl61QwhnouOchx/WjZsVT6MZ5y0anInWRyugjNEpVfiD0ABuZTra/nwlZlB8RN7dsAAU/L0kUzZ+OGFn0WN0A6SyUJDQDmM+VskBzPZhZ5UBf5SKUNbv4RIWXdKLeGRbDkUbSlcCIqweeGyK++UoYAlTkDJnTT4gHtd4rEf8OzyHlRH4DioSniqTUmX2LouSHEqDNVG0UwYpKJvCzqZ1aA74g7kStvoWzPpNv5aF9CazFgfSM3YUNGYpZxuInvu4SyDHA2njOqT2fbXyTTbxGwbc6NUNLMARQavh2nbE/1XCvPorZhEQCbpe3MVH82traJmzq1v3tatllk+Q30O5ac0wEq1jZYf7oZzb5yo1KUf4C+z1BSFZr96vGMLepKe6TfZE+R9rfjUNMGmpz8Bnp4P5FkkupgUdLVHSkfBJVnkd6MZ/HDM1i05TZfkBvamcub4LjcIL7ojVHqMaDN3gMo2hkp18SxpOvrI1CvqDtz9T4hZrmYdT3Z3lhmNFw1PZr31j4029qBx1iQMVdDYGsDKTEsH+2rgHEla9UbZmFg7KhGCLipl63NdvOh6Ttrc0O/z82NmhnkqEY0tO2A3DQUa3vNR6MdXNvBqr3Ype2l80q7bD9KWMjyC4OxaWMU71S58akOsHpKfm5vVCp94WZqBgv1SdWbW85BnuCUAW/BGol3yyDQ7NuaGVPTtX5m5BmLPnMzQLPUUX6bWY/n5Hhl5kA62MxcB6ZYj3WX8lYPFkR0KxtwkTXqnNzM3jfIeLNMeUViV8lWLFmYBIYvSLEnknyMmMrAwN7JdH2RMaq6Bt4f1d/YFjaZrRZCkwzIZnsnAq6WA2L5HOxI0H8TebG8lEb9mbIr52Qq2aUOy061vmkyPym7JuvUptHNVJ1ykdVLfQU4cyDkgYCpyrbJ0kGTr46T0pzWu8gwVVDT+DTNZzIwNTkjqopmYGbqSMbyrMK3ltfSkywDPKqsng4Ultth/e/ISdbmUJdAHOwYKmDTSM7lQEgdFeamtYU9Ia24ZHdy0Dp1OQIAOdbBomSBrnSmxfK7Z1sudLIczbccO9vxLYN1API6C+Br4/AgyyubWZiKeGrqt23iV4M7l7d6sPjUcjyItLONVy1Zbvm+PD3r5gWh6JgSfhv341MKMTTe2h4XOgPlxX42TW3pyHJOHjeWQplxa7bRD7iQPuUY2t6mGWbcVpJD2ydiWWrp3zkv3LhoWdVnaBcv3/Px5/USaNtX+vn478/TmKYufbvsk6P9jt/fWAZwM2Nql223FGr6vL6KNYLNXn+Q5T4acl/uy325U3l7ZxbH+gU2zY9KyR7rtBzkgKGvCtsAaOiBcSyvABZkIXP6plkySeNZDzflEk0IRSDG12hD8CD0SGcr5F72668PiOcr9NfK+9CoyPioAxNJRETPJZ4EHJ5YclGH8aFSsKeM/WOJApw2+/qtV1XsWBSxPYC06TCfBfQGqWjUJZ722L9bGZX+IO0M3mF83NfzBZB7idZEpZkPnbzu3nEYVE/SzZo23pFSjeVRdXjsVOBF0qSlc4BuIIRdV2Tfyk/IrihdA6LCzWQp3HJc04qcNw7dztVjPfKSLfl8hf0TiwJQAftMTAYAdl8VVe7jaEgOQP+SkNbA+pkB2MD+HYf5FDj5vrRt+57XuoXeHXb10Zw7YHpISPq7G217870V8FNb7EYzQGLkXmTy9l/TLN1Lj9zJDCifK7FtlUCOMV308Nce6bGAFuOHHXIns13DRdgB268S5nOG3/vSZ9sfT/jnvv59fHv+cmknPZowPx3qMmSjnJlNxDh7TE87xHfMCZ6QV3effry9g8WNZUbzd2NWLO81B6PJKuVZdTrnqtfZ1uF3S/qz385qRqPhvpwFr4hNOnxMwDTDbye4yawAZoTrSWwOUQek/iIiXE9SXyNEPARZT/pdRK/4gj9ErC6STCV1ORV2YtjjDxE0NantKcPvZhCzHBd1ACAGVn2dLIZrMc1xuwm9yt37rVKuJ9HDKFNVJcStXmR0W4uMCBgbgoRK/WTzYqC/kvRwlyobMOyFml0ySWMupKz+qtK1bT3uJ1c0Mw038AePsE81e5SB/moGHSasXsjx4x6afVnX5IDgBcNzXq7FGYCSsuKe4PfatswYXni4iQqte/2cEHdUSFnh0AwWQST9jVodd1T6OH/wACef6H4dIfeE7pLBLuhvaRgRMF+pncEgum/rLcGPwDTJiQyXkgbProKm7IDNR4R5S1g/T6XP1r+/xu8MX8L6I19+x3m7Qn/RWAEMlnMT0M2E4SUw7jUnaQZoujto8fYOFp+mjHRDJcpAyruvqrgBHQsg5ysoSc6BuyB5JyGUfe/atUy6P2NhQweSH599ldTPCkxSRvEtKQAnicxdqaMLCym5H3hplJRELUpeQfUmZ1cBOEuQIiZwEMYm69PXWR+z1tN8/7NI1ttsgZ3UCTCyb/ACZ31b22pRJvvMOBVmEZjDUpbusxT2TYo5aZ+0NA09NjWARv3ta/TC/qbUWBfi1cle7ACELGCuja2EojjGqPX+IACHt3ewOCZlHZdiVehqmNO/AepXOlFIT3DiaV10CrxEHWhu0P3wJvVTiVjYhWQ3HwgyMDWRALk4uByDHQn13JEqX+u+XVjqhP6ACxPqhc9qMqTJUUz1SWceoyW6kPSGcY16lYG5GoI1S0EOdbB+o7YtBgsAEFWrEiXXvpUBANouAqnBEDeS+1DiU+6wuDE/S2EbHKxt1l/O+ksfEnYjQwYYGRRY+1a2Z09wXqMmNlF+xWDGDnAh3xisJNKkIPTR4PR5yj3AeV/uy325U3l7Zxa3Ea8Wn9vck5dsTdv22vrRfF/XsYylctQxUetNQqdtmxqilU2JkZtQYja2Zz0GqTIUO8axupU9qb+IchyOK8diXoYdjaG6IGUBraIVaeYvJWGyVvaknN+bnkMbei3Hyze3U2Y4UzJrQqgtEc76+03Vom5tV/v9NhzL9Xe/GUZdfmY9UZi7iaqc3ysm2BIilunKcRvqvzpL/Lzl7R0sGp3NG4W56jyqaIs4jZsmRIbrOiVB0u1hdEPLYwJnBeI4l4uJpxl0GOVzy3ANvsjwl1wNr++PlgYcXLlwKavWQe/KlJJS1cp0k4CbTCgmOBTP4LYj8oO1AJHGvNwdQPMJ4rqHPxLbzZ0rUQUAIuDbOVBwSLo0KF6dnfA3bMngjOjTAQv7yzLFJ8nRgAx2fhZ03zUXslzoQLgaF+2SAXgFmlvgVAVom3wRQIRqKFcx3LQipINoXZRliOZZHN/oOcjvShmgRlou9TWyYRm1xAymTkBaFQ1OD73mhggpq+UpWEQoqUFPmxvCfZXNs2xSDpr/AYBHXRYxkFb22zCy5xJxqrqYgJ9Ul1P71k+M7fsB80aiRqnYETBcVzjhcvyBkRu7gTxw2c6B4SaHeGIA9NK97HXl7R0sjjGLhVZFqozEckFWLQoCJN2dubwe10FjKt+nDBGbzbmAcgu6t2EhRMBhBO2nSpMeJ7jdVPUd2C7KCDdJZMCsCGjK6K6TOG/NuYrL5oywz/IkMBXvJN9zFunQGw3Bg7KIsDi13bMUdQ+gbxLJ3G4CBQfaTwhbDZ3uNYISJYJU9tY6hssMv7cUdbmpXSLNo5Bz668z3GQzHx38VBvBzamyQjUsDSefldyOWR57dFHFZFhFYdy0TFG3vqRxLqIuLqLQvXNH5andvxThF3YoTFZiSRHv9rnONgAgQ0R2ycHpQNxfJPjx1Snqfq4p6pZQ5nYT+qdnGF7agC03dH9Rw7pBk9soi1KV7KcRoVFS1O1u95NEmdhVujl7wvpZRjgQ+otU+mz1fMD16Qr9JUof0OyWKeq7ejw3A/0lF4vHBc38DuXtGSwawRMAMt32Hll1IhZ06pZObPJ3XVfFZJhBw6dnnRb6tJkGBQeONYTnUhOebZcfd8067R3ceEz3puLXmYMrT1P2Tii7JvSi35GnHylj0x4dCoh9kVmnlkynFy17uQGKGf1A8DOBIpUbgjIkW/X4d9RzyYHgjVKuUaE0vGHWqR4rDqT5IUb31natgbinAjICdXbgEmE6I2yawS0HQupRgNfPnHV6kkvmpwwWkjBWs05R6N62zZ74QqVX+jdkhuE0SuOa796adboG8llEXPdlsIinsgS7oWcxWA7LD3vWqaWXc51JUN+Dpwn+3ScAgPRJFa5BSlWhibkI1NATETGhaUZ+eSHKTNfbotDUkrL81b7URQDchRjm0qww+sNz5LMN3NUOdCq/MPcd8OwFMM9FGo63O7iUwFv5vh2r/2grIjC5RjjoEFX2Tp66reT++qODGBU/tBxmRjxfwcWMvBlEIg8An65BKaP/7nNAB1JTVvJdh/XFqvbh1VaiOvOMXpc3ZvLsnAPnDN/J+WYV+Dn9zq7iEImrY1io+SWD+lS4MaG71sGmURBPJ51+LlEcd4joLucyAHRX8ptvvrMryy6L8AwqymPLrm7Vgw4T+OVlEa7JnSsDaQ51vb5+5uD3Gbld7mUuS4+Nq7kdnAmrFwlhdPA6yzz71rUMwGrrUGQLIQM9D12ZzRVlq4+e451fP8f6E93uCGnt0F1GnHxspDsBJcxDFdA0/1kC1O74AAAgAElEQVQG47DP2CtZr9vlsvywdufe4ck/2SIPHt3T2mdPHn0Jq2cdVi+arGcihH2SwSbywimtv4wI+4ioOq2UGb93fXcs4z4acl/uy325U3k7Zha3lFeCm/aZzRKceHZSG7X4NH5GrUReMwNIBaAsknBZhG4XS4O71KuFLBKSM2C6Bl7YOZw1DdvSpWO+IVRLqbJJZYaiFc8RFL+4n62NCFHO4AiZCSUUZJ3JlZnEwu08ij4GKWBIcwIRST8mVz1TgjGU3rBYJEPT/wkMR65GGrK2Y86w56BpikBT5E1bxM0yAxHs5fOFQ1o8B2TRn2XkReUrSkTIFR9Viyrp16PpaLgiq/epxzX8xi5nr8Bz5EUU5k2TIG8rb+1gsfAoBRbWANT3IngLAH0nDmN9v1gr03olF5S+li9ryeeytKDtQdbUDzZA4qL05OcoeEbwReUb3oM2a/D5aWFaEjP48YNyEZBGaab3TkRzMuYyf8tDwPRAczFejIgbma53lyMO761BzNj8rixj4lmP7nJC2gT466mItIbDiHTSI236Gxqc+YYGp7A9aT9hNg3OZ4ZZyHQ/mwanitZef21T6M8lJV2jLGbdN5179FdJ1+CVgBX2GWEfCzBnbXbMGJ+s0F1LO+ezABAwPejRv5Rl02s1OGPC7iuybxoEcHWJVSlLmrB/x2F44Sv5DRpepA7dThS2Vy/q1H77fifRn738DuOj4Q4anNoG0+CcE178PGE+URp3gNC9rzwORYMThWk6NxqcIPks7D327xn4G+AnBWl1icgO2H6lUw3OUPrsxc8EbH8s4+SDaoEQT3SZp6WmpgN+9Dc0OOOv3z18/ZYMFoxXppXv9YZYgJONg7j36k4elq5dr5PVM3CwC4BzyL1EGcxzNHySxU90cpVV2QUBMu8AcKbegQYvT9GiP+CRBzFSTqtQLjg3d4gbATiLU3jnkAZf9CEKxbvvkAdp6xcBcIq8n+IxCnAKEEggDQXOGwLIw0+M6dRmZAx2Dn6UNTsAsfpzQHYd8kBImkcS1xIupIQ3AjhNuk5AWICyaEfYU3k+BdxECwanyN0zQOJqHiyKMTFSB8znVESHc6DPBHBODzPm51pHJ+FRyoTpzEBLKtGQeMp6XgxkKg7s8YRLvezk+MYAzd3tAOd8CuDJiPFqVQbMuAbA9XgFOO2BvP9RADhvKZzU49PyMpolAG/3gHIXaGeg4g5kI3GM4P3hUwHO8EyH3zkC3iHoPt6MhOYId3UQ1W71/nAA+PoaFGNt1/V12Q5UgHP1e9cyIzEPVAAheHQX+rTdz+jsRp0iTtRaz0Kbwye7miA2J7itTlt3B3SfOOGAmOy9zmb8dY/1ts4s6HIry6txQqehXbpWIFel/f21PhEV4Dz73ea4SQcvNVI2ivamdzJdnhJWqwqWCWg71wFoktkZzQmbKZV6u8sAJoLfTTKzA0p4uu9C8XkFgLAaQIcRfHlVVLhz76o5UajLkJPve4RdEpGYIgwkWb0uZWRfwUxKGWHfIW481t/fl/ZyHyrA2UrqB4c8hJKIZ+fonl7g3W88wOZjvca8RHm661SyWd1sAGc1PJKIjvJSxoSDZuWe/t4El4Sebt6u3El/p8HJdaF99s4/6bH9eIX1s7oEz4HQ7ZOEXjMXcSL2AnyGbUI8sfA88OHu7suTe4DzvtyX+3Kn8nbMLFj/a1K5WTUo0qX4cFQfEckc4rI8IXkKUb/wBfHvPAEfDsVXBACcd8JTYK6Yw/4gAOTpRmYZxpN4/gJ0OAhGpOFG2qxBDx+AT9Y1dOYd0jvn8Po9p7oQ8WxAuGRgrqM+B4d4LovI/lA1KsJuVBtAD/9bT6We/sviSXJ+Crq8Fq8SAPz8JajvML//QMKwqKBs60sCAP2zDrkP8LsJ8aGsc7unvcwQgoQGzUrQzHz2jwZ0V1ZvJQUZlgCofeGLCWmoituAuji+3MG9uL7xE+cHawQLO+p57378DP2ltCsHYW3mwalOpKaCrz3CboO+7zCdy/cMV6DINfEPokexfn5zDZ4eevQXCWnlcPat2rbx0SChV51BbH/yDFHrjitCtzesS5YhaSAMF2Z1KO097T2uv0ogpWBmL+zP1BN27+mMcstF5q+1L8wB6C+EqBVP9Pr5LsMd0uIpTinhxc9tENeEkwcBYSfXwvX7HtuvmY4o6W9D6C9rHxijNw2CL62eBUxnWm8G0v/1Q4dZ3FKOtTOdE3SeeYlDLLCJ5jshFCyj4BvkAKSFj6nxNcoa3ijUbRZrcyxWWX4Tv3HeV7q3uVEBhTTV/hQtpiA04YojFKzB188NHzEiWPm8CzetBoiQe7UaMP5WH6QdsdYfLO29cyD9jlRbiUnm/t16nRqWAKhcvdaXGq9TYhTzouPSksgKqWhF8KOt9RXLGQjecWFgxrVEXsRGoX5PVLGrLiegVgC7mxe/HEcIV+X3RSVh2ZIirhzmDcHPFZMAUDU8BxT247wWXCANR1YAAYX7YWAmmMpg0QKcHEQgmD2V7UnxqBvnsBGv0riqmFI8AeJ5rkZPUNwm1rbHlZ0rEE8y/OgwnxsY/yOCWdwGeHIb7jx+n49A0jZ0aZ3fdkyRwOf69w2Jfz7aR8JcnDMo1f1aJe+qVs1YSO3rMaqa9lKev2zn+vnCZqCV7FdZfGpCiUxYyPXL9gxEunksIiBZSLYhtzEv1b0bmf6FFUCss47l8W45Z/ussS5YSNmXY8g/Dho+LHkkKgKTqjR/kc9XFW4rbj6W78eiDhexaNvxNhcZfq71FyVuwwN8FaTxqkHhUoYbKzXbMbQfK5Xazaz6G3UbZSAnuqG4LeHoW85hNgZmjVK5GXAHWlC2/bikcLtG3Tt3YgdglHNKqCH5O5S3d7A4nll4X2cWxzL9xSOz+Y5zQN/Jv3YWMUFmARaWLfU4+aXb7a0FgB6L10OJMgDC6kybAO+9iN2Y0lagWmfTphLVcK5OodvtraGReZLaq33uhCpuzugUVMhl8JJEZDOLdUBceQRH5anMnbSTvYMj+Q4A8GYFZAkZFtVx41V4Kv8AFKdw+8yKqHU3fduU0h/2HjJVt3blXlXEOwJ1DBeNPi1P6XDaN8roBKhYRjuzEAXxmzMLe9rnpg1WT7strmo0ZHxQw68uElInA5kBhmJYJEsySdI6PhaXiIyoctv7+spBGJaUGsXt4MDh5h2cVjKziauqF5I7IK/qcQAUZfHaJ3X7/EgYt3Ft/A+8EWr59g4WxzOLlhDV5m3Y+2Mz5ZwlShCPHM45Awl1qmwu6nMSwpPt1hK/2mNNszyZjUQzR7i9oPdkxwRAUy51WqGpQePnVMhLmGPZbsekOUldc6yv9vkc4fcJbjRHb5HsBwO+kdVzY0LIIttX5P3nJPsrZuF0GWAUa3/IVUOzmAoxPKFsDwdf3re6MW7U8z1yjl/0h76XenLhMlAi9fekxSwm9w5hJ9T4ynuomEUr1x92vJDCK8dm6HeXFO6yTTELwyhs1lAS1xLD6UAUrA3kkCeRPwzXQRIBYZgFo9szuq3xLOpgYiO5DSphC9Eb1QeSH5vroilhK9hEt2dNxAPCFgiXbqkVGpbaoTYDdhHInUfYoib/aX7NXct9NOS+3Jf7cqfy9s4sbimfRgG/UQyraDELMkzhDYbTo0JJMITSktZi0L1hGz9vObbiYy6eEdJWBnnpgwKaZcjSKMv7QimPaUlq+wMopPRsaaudCql7mE2VhYtgVPEvtLBOzVmdyYoQUiV+LQSAmnZ+0WUh7HMLpnGX4hobxc9SfqgGi+JQ1mITr3IeM21OewXk1e6klgEKVIeudl59XCc5TdmmZYp7cDW3pMU3fEWuASwcw1o3LvjGSczVz839DPZqn3u3xAAcitiwpX9bHYUBuhAN1vZzi5XUeoseBRv+4opTGKDswtZdzLo8suJBt4TjGge1Yv7ckKfMpcyyJB0qZuFmae/SDUxSuBfOXR1wm7itOYm1WIucl24rmbX1+KkDXMlcraHOmsVZ+zd3aMhPGmbtqLiPuanFabDYL/dYOJVlT0WIqC25s/OjMrDmHsg9L34D2a8JnfZ1exrsO7JN7Bxv9teryts7WBzfqAZuAiBf2YT2fuF2DsjF31gDSEmFZwFjGRqVe+jkxrftViewPBagClQacoSuAU2zIlV+gJu6Co4CyEMo7Ll+6BDXWkdft5fBa+jEqrAPIH2VNvgSgnXKe3CFx1Gp1tB2lZwL084IzStzFf+NCcgZ84kDKS3bqUx87p3kgOipTKeuhDxLbggAEISVOt+8rEp/6HtA6dP7CnBKO1XHQ5/gcXBwo0RD5pMatpRoRWUoAuLrYXTs5bFFuGZeS5q5lflEthlQnAa1HvQCSC4tBMUjxU9U6jQx4vFJRn9h/argpQOmh/V3MSWs+cy2KTDpHPyBMCsNvFwHR2U+EZr28KLiJtNDIL83YXxRZQmmRxnc3AdJwcy0Ej+T+dRjfmCJftRgKa8vb9dg0eTkHwOczCy8gGleqF8tFbGaxJ9Z9qN5brbV7xmt2hSu3G7SjM5cjscm3dcci8ZZFKgMKJujUICjqneptF9RsmoAzlbJyu2mInFH+wn9ZSz1lfaMk7TTXvVz2k/ormb4XaN6paVvbAL8boabM2g/o7tSiu+YBKnKAnY6b8edwczoL9JNUtaBioIVIE/UTr0rin8KIAlg+wk03pRfapW97LxXL105FneqfTGJb4aFTimbUta0UKm6jZSVel98PdqS9lRVsHbViKq/WMGPrlC4h4sBfpK6U1dvSuNZ+IkwXKp2yCwyf2E7Y/39FdbPWoAT6LdcBuaWlNWZcpXOaoSUxQi6vb+M5SHQltWzHmEPrF4mdNfy+erjgNQPWD+t6wrxYql/V1KWzHSGF4D7jEpZ9wDnfbkv9+VO5e2aWbTlaBlCzXT+LgxOMqd1y0oFaij0czA4oQxOWxbAO3kf/OI7XzSDMw0ebrJM1ySqUX1lOQJA7qWtLubKp+i8ALH6agxO47H8gTI41w7+oPX0ssxJK3m1GUNcO1B06LrwxTM417Is8bPwKMr1pHRvW84AknnL2n9/MAxOWYoYHR14cwZnWjH8TCXzlRJ+RAR7byu3kH0+dV/vFwAneS+Zp29Sz1FhGxQaMlcOTvJOjED1B1EarNZASzGraUlSAkxStwQ4OQhQK65r2hfBA/kPdqIprm3Wj4INMS0BOnEyc4ub/Attj0MxH8q6YqGs7aR6c9k+rSTAF9o2V4+f+s/2O4mHaqPo/YYBprdqsKBBknR4jot0cgALTU5u0s5LCvr1dvkd0+lUjU4AoCePJESYM/jpCzmWJqS5JJYApq2ZtE4Ai2O5kw3oai+Dhh7HX42S+k0EfngOAEUjkxt6cauRSVdb9JqUxLs91tpG1lRx99Fz0fWcZ2mjYi+834OevkCvClQAYDqfrcYnoJjEHEBTRP+JrrVfXguoSQRKGe5aNTgfnoKmiLNvvSw4TmGjele0MQGg/2QA7STRb+iaS2iOwFXz2zSlB4pmqJ232583quWuaFrAVXC6fyEzHHZO2gYUncySQq9l871V8X9ti/m9cufhPnpetp/NSbY9vQAgSWFp8HApYzrvigiQqZiLnqd6s+q+HAhf/ocRw3PVQ3UyaPsx4fy76ik6phI9KzNLvWnDPoHmOvMbPnhZxZaa8nD1rrSB62D6pW8ccPidDuun+7JfXAeEff1+bqJWV18LOPkoFnFhMON7uxuHemV5qwYLyzQFAH9+LpoWCjKyOqSnjz6G//mvw70UPQp+dA569hJ4eA7/XH505AQ+3QAvLsBnJ8BeTjN/76NS/+EX/zAA0Y2Ac9h9dQ03cenIB9/okN59IKbEFzJo5Ien4Jgxvn9asi0337nE/sfPsDFw9vvikPvRv/GzWD/PxeQWAOZTh+378r2zDxIOj+X9yfcTnv9sAGXga39f2vryDz3C5nsjxscdVp+MGB/LDXby/73A9c88wuGhx+YT1bEYFR1/EHD9lfqke/A7M9LKob+IuPqaXLhnH5ralIMfM6YHcrzzf/wBAODbf+4nMbzQ36AoNgkS7/WaPLzHWH0iIbxJxkYQA901cP6dyrQ0Y2XKwMuv91g9l+37dwTMnB4AJ79vTE2pZzoj9FcMp/f84Qlh9Yzx+JtX+PafFvHmeMqaU0Ei7mKz9p/aIn/wQOz8bAWZAe4Z/dMzxJOMd35dGkwJePHzhOlhxrvfeAAAuP6qTNHdSMgDI1zX2yN3wPgkY/39VWkDAHz5H0b8wn/+/+Dv/YZcT25IGNYz9p9s8BM//TEA4MMX5+j7iJwJP/ZIBrx3Vlt0LuFbL9/F86sT/NQ7su93/tefRLeFuqjrsT1w+XMR/eMDwq+flj7b/YWX+E9+9tfwX/zWnyjU/J958gm++fH7cMTITHhyIqPB+yeXOJkH/L8fvYuvf0mu0etpgP+Nm4Prq8pbNVi0hWNcJP1wQxii3aEMHrQ7gMdRXmOlRNN2jzzNcPp6XEf/XGcUVyKrNwyytu9sujtOIn4zxyLhR9sAignd81DW7LTdY3g+gLZyJ9mxTr8f0V2IorUtDcI+gJSsv346wZtz9rMRZx86Id2ocvPq6SyyecwIF4fFua+eTvBjh/6ltkup127qoc9wqff5iNx5+OsJJ7rc6PS8w+BBY9Lv1IH69APGcKU3+8xFtSmuSWjJAMJe3MQpM+aLuq7v9hnDs6lkwxYH+cQ4+cijv9BIT5Tzni8J66eaXt9ZNMCh2+VKaT54DBcJ7nKP0w8ktzquLTGMkXoULGU3nuLkkzplt5IDMLyUB4GpcFNizCc95ue+CNdQFjUuibKgULgB4U30F65EPQyjGJ6P+Hu/8Ydx8ttVVi8NK5xeED7Yvy99fuUwBRnUvnUm5/DPhgwQw18GhD3wW49E5vHdD1miMKrlCdhSLGA6P8XZB7n02YfffIL/dP7XcfhnD8rp/uMHD9A/98UK4IO1DI7fWb8Hmgn9C4/f/EgEkigSDrt6vbyu3EdD7st9uS93Km/tzOJTgcIWYDTPEdcwIrmyG18FZhYykmWXegJnWsTtoetPi8SwHbdxQDdg8bi9xnLkxuuUvZJzCEXbErD3gPotyrbQHOuW45lTNwBQwwptiUQt27ToFvh6TGoySWu7GzKSZoBLu6mkO+dAyF55L3YFsXAMjEkKoFDPCUp0KuxU2Z6bduWGnSnRBC5/i0v5ceYmARCeRaHc9eqT0QCR4Ib92GHRj9kIVNYG5Ug4jX7kpm/YK+Gqyby1fnRDWtgXlmP1tsTiYrnIg85W+gxyQpTKicB9jTyxanY62G9ldfKyz3rGyTBh11d1b/SiHWszC2sDeiFr5Y7rNoc6LbtDeXsHCycMwyr5T8vPLMSo/qMS9WiQadKbnJqbfVGHvg9ebwYhGBekOQRhT+p7ABIWTLmAWHacdrCwY1n6M7Er+5YUapLjlAtsELctyigMwxwIeRXk4ul8iVpw34mTV9OG9jU3XWD7vGrf5XnUtOdUSI4mHiuYguXk5r6GL00kxsyIc3BVid00GhSUM5wn9Rr1CFgMIPJKgjk0tHfWB4E5kuUeZRBLQ73ecy8+n9ljiVlQZWcaw5WS7JtWKO0qA6W6leXQZnMu6eTtQD+sZ6RhVftvzcg7KgNDHtU7NQPQQSGsIogY89ohZQ9ayXWeVgGUZX/T08hKDeew7LO8yni83uGjTS64jV9HCWcr8c7a4FcJifR+0TYw0Q82RZ2I/iaAPwngY2b+Bd32nwH49wB8orv9x8z8a/rZfwTgz0Oytf59Zv77d29OU1LCUjimGQEtbRsAGaOz2YaUgE4iKhSbyEpTh6V3W8q5P0RhDVpiUIzqaZrAxgKdZiBJangZkFOS9HI9hh0r7LIi3Wkx0HUrY/XF8lT3u4j+ugOYiwhv2Ce43QTvxNHLGd17nBB2Bmxayrf+HRy6XcOoHMX3xI2x+pdaWjvL97xFIFQAub9m9NsGsyBSzQUgjPa0dxgusyaCNee2Z/h9rH4XJnaTGN22R6cenSX/I7nSrmKZqH1nZsXdQLLPHNFfacp4BCha2nX5GuLaobvkMnOTH0Rusv5CQNPusp5/d+Ul7VsZkTZgi7o3V1k9aH6JE2YmgJJQ5seE/ScbnF7YAwHIO0J/CUS1XeiudVbEwJyUWt7LDd1dOYQdYWTBDvpLSbNvAU52Yr8AJvTb6kXbP+/x2x+9g/6pL4PFPK3Qv2zo3kqnTzsPPwPdBYGdXkuRRBzpjuUuM4u/BeCvA/iVo+3/DTP/l+0GIvrnAfxbAP4QgK8A+N+I6GeYOeFNiwm+3DKz4KEDDlV8BiGIyM2+WYasBtDhUF+BCoBCfDkAoDtEwAHzeQ835fKU6b2Xur0DaYdzF8DeI54NJdTlLgf57qVEK0hDieMjzfsYq8zdfOZxeCzajWHf4fDIcjAC9o8JxFRCsvNpQLjuMJ91cGNEPJF6QxcQTzuMD0P18dQ8jfm8KzZ4ANBd96I07QjjY7mr/EHamQcPN3rMqmvZqTL6/l1X8i282u6lnjCfVJ2E/Xuy9KMs0QtAbr50zQjbJuTYKI0dHtYLenwg0+TpARXA1xKeplNCf02FGLZ/TGDXYfh4wF59OOJGB4tZZxla7/5rUW4EhyKjDybkXkyK4wbFUpAy4/CuyPWbCvfuPYf5ROvtUPQorH3Tw0rhNhLV+Xd7/MRPf1zATO4ZPGTEZwHupySKtn85AJ0AnCePBAjfDBM6n/DR83PsrzucvCNRi8O3HxRz53aw2H2FER9G9Fdd6bP4Ewf8a1//Tfzq9C+UPnjy5BpPPz4va8D+RB4+55sD5uRx9dEpzr4kOqTTFOCGu9+ar52EMPM/APD8dftp+VMA/g4zj8z8bQC/DeBfunNr7st9uS9vbfk8mMVfIqJ/G8A3APwHzPwCwFcB/KNmnw912w+0UMoF1KKk2ajHuo9RTYnt9ajYNJdyBrJO2edcQ245y2dpuRSiOVahXED+HlMh0nC2kN8yIQoA3OjgD/X4Znjj54xgvBqzt5vlnPwk5CNviVVJ6gz7qmhl7fEHj9BMnd2YAJbPLQzYtt1NqdCtLazcqk35ufIkmOoyJOxItB4TlzU8sSRE+alqZ1CSsDGljDBWXU0/ajr6toYnbTnDjrTvpI5u5xH2orJVFaCoziwa/lK49Ag76MyiWYaMVPrXXNUoszqFUaM8JU9jNwtQ2ipOWZp52NYZi/Xxhy/O0V1Z9iwjj4TummRGAcBfeVmGZGALCVseVj2IGOmyh986bDvBPJ4cWPktVe+TdbkCCghbLn3GFz2++fLLwGVXZhbP/QncZSgA56S40cvJI88e4SLgqtNp0UzI6e6gxWcNnf4NAD8N4I8A+B6A/+pNKyCiXyKibxDRN2aMr//Cmx9g+XpUmMrvvQApF9tv+55TtN+Qf1dfWwDVaMMApJcdCkrPHiXSYhRtiW4s2yevNRLTvs+BahtUU9Pqtn9QVJ29K4Cr7Vu+Z+1UENHcs9i1IChK9EXAxuZcFv+WdPNlv6FEsdhp/zfamFZ39jVSlDW123Qyqxao9Gd7ruyVzuyhddR/ljLOGomyf7af/c3B/lHzvm7L/nib9HHfR3Bg+deAkegY6Fj3ZXDHcH2C6xN8SOj6CCiBzIUMF7L2Tb0O5Z9oZuSel30WMk7CVI8dGD4kcMfgLoP1+OgYvpPj5r62AX3+4qMhzFyokET03wH4X/TP3wPwY82uX9Ntt9XxywB+GQDO6fHNFt82W2hLbvQxj3Ur7mACW/rIVLlZ3i+2J1GqLpTtT2vPbcfI1r4mFKmvx+rcpmBUlKsYovSs/WBeqgvVqy+g0FEfiMGv0IyLKhRTUbAqClKMYkJctDYZIEj/LlSxPqvoVaNSVZSqWuUn28ZHA36zb1ETZ2uz4B+fp+RMN9rQmhKj+buIIGcdeFWxzLabhytnwNklnjWGfVyYENlVpXndhqxRubYNb6Jy84rymQYLIvoyM39P//w3AfxTff+rAP5HIvqvIQDn1wH8n5+pZUcAZwl/AgICumXoVLY1AGfwJUvUwqxt5qpx9L0XVDoNmvVopjn2XU24KscCwL0r3+80A7Rrs0KhmZmaQVmOuXLiRanHmTWM1w/iV0GNGE0aJEMyDR5BXwEAziENki1ZzqHUX/1A7RxT7+DnXL05e1c+86hZo3aO8wkVqrX3FuZVf1ND3E8U/GMUcxy7MNPgS75HGXQyY14TggLFxbN0Q6VdFhaNG4lIWMJv3BDiQfoi2uz5VJYFfq7AKADk84j5SiidvOh3NfLZoGSuEjPmE6FtF0vBDS0AzvbHS70I15geRZsl+mOPXhZmJg8Z6DPmFAqYucUark9gJjx8KKDn6TBhCBHfzY8whR6PdHvcrGD8liKmS8B8lpEfzIibofRZ93CPf/HRd/FbD98vUjDvPbrC92Kdom4U4Hy42WNKHp/MDu8+EoDzMAc89Xcfue8SOv3bAH4RwDtE9CGAvwLgF4noj0BO63cB/AUAYOZvEtHfBfCbEJ+vv/iZIiH35b7cl7euvHawYOY/e8vm//5T9v+rAP7q52kUAJlVvGra76qLuqSM307KWrwet9NINabvEAiZXZF3E2+OINL5reZF/HRSlhVx8lZdT/0oqxYk68yieEgMTkOAJCFg3TcPQdamna8koL5D7tyCwdkSm26Qsnx9XexreMRRhrWxD4E6nZf1MpBSJUWZk3ka7GAoDuY2W3FJeBqURUIuFek86yM0ZKzltht/U/XWyL09erFIJHOrJB4eBLCvSybuWPuTy1PZqVdHWrFoV6ASr0QZqxKwrH0cuDJNzefDEd5ZbSXXAwD6jLCKSL3HZpCn+mHVC5aQCae67eFqj95FnKw3SMmV7S9Wwn9gjwK8shd8wnV50WfDEPHV/gVW66nMLB6u9vikP4VzjJyptOF8OGA393BdxqarWcHuR4LBaU5ct1iEVWoAACAASURBVBXmI3cy3ddwjJQK689eX1Uo57qe42axmzPo2Ask5jI4FDBSAbuF6RFQoghgBqHWb99rcYeFd4OlJzNkoCqOZ7rvHOXm87UNC7bjgu6NKirrjwYWAySLnoQ17JVdVTEDYlCSZZP1l2AAgln4QsoSzOIYqyiMy4Y+3Q4aMui1A6ACuQWQtkoarAAAuaq63q7js687+bn9AoBcVbyzApE50WJgKG1tBhAOTaTCpXJS5BhELIQrb0tohvfykBmCpvm7iE2YxO0NdV8otlPwGEi/csfourTos+AyVqSJcdrU3kV4n6VeolLvys9wxAhdwmlfAwrO/SgMFi0hC1hK7KseZ9lOSg1vZhakmhjUaGO0dbgjIxc3SaajXQSCvstMoqhpOQeaZvh9LEa4mCPCvjET0mN1ezXBiTVd2s9cwnEu1vAgAPgDV6Up/Zw7XxSY7YLmTlLZ+60wRAFU85/OlRAeoFoJGfD7iH4r9XrVOqAsRkHBaOQ6IIYtECy8O3PRUGBfb7SwkxuMotjlSQWCI1ACktbZStb7sQ6QpvvYX6CwRdNUb8zumsuxcu/QbzPoEGt4maiwOKHWAQAwXfRYb03F22YWgJsd/IjFjJCShk4bUld/AbEAmGVm9/+39yW9kmTXed+5QwyZ+eZXVT2RYnNo0lwZkAEZECBI9sKAAPsnaOsfYXjlf6GNllp5a8AGBAmUFjIgwASaTZAie2DPVfXqjTlExp28OHfKfFXN14PUr8k8QHfmi4q8ceNGxI1zz/nO96lF7hLvJwSayIKQ2KjUisvM5XWkQWgYwq1vBB6fc8Wnu25gpQY88L4/AgBM+wmIAq6up3BzhU8a3lcbDmx6WV4iQQHNuYTxPSbVmJ1dTvCPN9/Hct7mIPrb4hSryw6xdAYmsqnNhxbDWsOc9fgVHnC/rMT6OeTKL7L7M1kQbXoSnqNcuTy8Ilkh6zIugKwrS4JMsBvxET6Uzy3LhLDGIYii3J09BmMg1oZxGlm1zIIsK3ql+geyjM+gqMKVcBZyZMyBGH1+ewtF+eESJmTcglw7yDVPAogl7nIdYdpa8Oda5T6I0UOuqQQSbcJQeEZdpnEyHoIIZH2emNK+JHh7njQ38CFlQgPxEAYByBT4HPg/4cLGkkWtA5P2pv7E8nwKfK65xH0IsZAMGxMmwHUU0pR95Zr3IecyRiWhG7MORjQ5l1nrs8ZZgLi/rqlxHQFqJXlSSOpqa/a0hGHPqe4beUAOZVu6pmQ8zm+meSLzjuC8hFoSVpFYSC542QgPjIrXYM5xmZibK5ARWN3wem6yDDy2orwgvCXIFcsWymocMdd45+YEYaEyTmWhO9BC5TWkjdvnnuBHCbUQGPu4DjRcPHlXux+TRaocrWKh1LUIo4F8wIQn/vIq/1vo2wKC6lvQcsVv/SMmMcFociYDdZaksgSfFusm/i0hjMiR8XB8AHM84ZqRJIy730Ncr+AbWXFasqJ5SJNZPNZ6jyn1xVgyImYmGR5NQDOXGGexTmQlYfbYpfZHMwDA6lSCfMfQaEEwe3w8ddljPFARNLQZcOBsS+U6txKuFRCjzKQ+iXPTZw7NmB2IMaDxoLj2wpRsiJ1QfljHfUSZQXC/03URwOqBzqAu8hyzkKPHcEQIxMccDrldryn3K8UxzIRTtZkwaAKogYvpxnh57SSKBBvAt/nwcMcG46gzjgOIKw3J31wXMhyePLB6GGCnAcNBzGBNUzYkxkfq7FkDmFlh4c5cmq3E66dPMh9FaDyoc1iHJkO4F7pjDEWgnPWYRbj3J80+VjctvvPaGQDgyYNXoVZxcl6XJaPZC7AHFnaq85ipkyX+6OQ9vHt8kh/6l46v8VE4zO/e6ZTfTgf9gOuhxY2ZYe+Y+zCOCuJzZEO+KChrZzvb2e+Z3Q/P4nlm7G0x5Gh0s8yVoDRfIqxH0M0C6Nq8b1gseQlzdZOXMnUb7ceca6ZhDQiB3nFwLrNdGwu5MhDzdV5iiMUaOL9CY2zh4Ly4RhsCcHENAPlYB2+vIAdbRIsBNBcK3TOG4urrEd15jCMsLQ5TYCtWkE4/4diIXDnIlYFaRg9gtOgfDxArC7HgV33qnz5v0Fz0+RzVs3nk5hwhF/wqTBSBQcnI+hUZnhb8Fjz5mSlixb4QvPpGZJfffipYQNmGLDJEjun95MqVZZfxCMTLrAOgVEvG9b0aHFRk+0Is0HKdghxsliuczBrI+Qjx9BKnP+N1ve2IAUshVrBGz2/9oUZ7HTaCgFw6D8jRw0tAL9PSLUAYBdsRZh9F7Zj3A+NEonB0FqsGt2enMuu7uIoz8zf/5zt48GEKkgq4TqG5DhjeZVfoJFaRkos4CnDWA55jFJNlwJMHXBVx8E6MnUkqYsuKsPchYCYSs4+GPGbLnxzgr9/9E0w+KXGbi26Kg3nIMQvf8P1wrRnO/mgeMM4O+To4gK630mGfYfd3stiy4LfiGfl7lQ2pzTkWJoqf222IBPbyAQGc+cjINyBmV7DZbsq4GJsRlcHHIKrfDKKKMZanhwBKdQTkENacZiXni1q29aWmIokgxQxI0lbNQkKeswtitIXYNamWC4IYSs0298sDxkKMmyJGFEIRRqrGVK59ocWLkwUkbaCC5ToGhG2AqB9K47m/KbPiA3vyofo38IMbCBCDy/0KMXshAdDaFLToICBGPo8UX1EQFYK0PChecz0OuULUg8C1FsIGCFGk/4QNmWM0xQbEwCX9TKvnN9TMk6RgEgDKGR5joRfIgkQsWcn1LUmFXY68HBN1VstSmcgGlNoVw331QEabirgdQWyMmV4E6GvieqCUObGAXiLXhrgUKNZMP5D6BOBzq6jf38niM9KdNaENKtnCzNAk7zBb1oQ4aX+B/IZDosmXAsGn9uVnZha3+x+EAHlfJAMTHiPWa+Q0a0XVn7U1BN2WGATHSMJnjc1XYakvAPeBsEHbHwSxpxF8SdW6km1I2RDpAYg4n6eaGsRajy8gmVCnfVMgKGl0pO0pHZxiIOQ4YFozk7EJJH7R5IV80TV5nTpPZEF1bRDXzPA7rejQRjyH5Lk17yuJEeC6pMFdU4rdto/L7F0oEieCEChm4Fx1Ul/BLXNPJovoHdRbTCTsXQ23d7c2p/rIyOJFRNLcYO8wXcZ9KFWlKslv9VgoQKs1pFYsxfccavvfZmQjTsMVbwEeIOU5tz86+PS2WlsIo/lNM2cXUzYKYrD8Vo+fAC+bxL+gVgX5UOj5A0Ces00CIhMDBUE50yNUSUUK63npld7Uo+WJ3fDSJFfHVuLNn8dyBa8QPJbp+UkBWVsqNfMb3Mc3qA38Lli43JbXGkGELMv4RU1YlHMGixSlbA3/e4jp7/ImFybkvgkXcjBTrXyWZczEQPb505hwyNW3OSvUBAbDxfqdEFO8X4WczS7AubOd7exOdk88i+fYFihrw2ppwag4RtU2CgG3nbbntBF/H5IqO1FeMnBxWmw7BTPvsryp26dUTp3ajNuI3ftccq5lcbGrFGxoJa/7JS9pAF5i1cuSr9oCVcAlH5dAorjS3Dew0pmvhImJ4D2v7VOxWgiS1+rx3FO/t0mC79y3mmwYfI1rct9ckq6QqfvIxZhBLG33lZpXLl/XKUj7xTyMXOqe2qxK5HO/iCJ5czkXCrHk3BY0rlcUuWApexS+oVt4FABFQS1yZZRtlJdqdR++rN2PySLE/1XBxZRV8NecZRCTCZeLR4rnsOQlBwmB4DyICO7x09ykfOURxHwB2ptBJIzGRPByxwf4SSQmuRhZ4/NkBlq7HDPwzy4gojKXj8pkYjZFOD2GPehz1kRrhfHRPvQncZ0e6emWJx2ay3XW9AAA12sMD3gxPfnYwxzw9/bxMov9NG/yOdDsVahPL+GO9iCuFnBHXNWIZxegSYvld/ahrzjSncBPbqIwnJQA5+RxA6cF1NJifcLn23/a8A2lJcg42Bn3oYvl+ItXNNqrWNuRg2MEMxE5k7A8lZicOXitYCblLtRLgr7w0JfXty7x+rRHE7VJfHw4b96YoD/nfrmGlyasS1oQnONMoLnpMWkUVg94jFjbgxGlrpI6XLxKmDy+PREtXlLon3nYnnDyZoFlLl7RWScEAC5+NIGdcHzAdYXohgmHuSK3exZxORN+KA+7B7j+kUWIKN8ECR/3JZav8O/1TaoDIpi9GAhVzDfRnEvIFcHs8b57H8YgZxWjkOuAp/9Ww8wC9t6boL3m6371BhC+N8fil7O873jk0FyUl5rruB3Xe4Teo3miMB6n5Q3B/sPvBNz7M94+SpUAZ/quFG4xgAMF8LVlvougLFVASkTlrShTm8DGsSBiYVcWFBb8ttrSObW9gFrJrbJ4LkVPx0vgGt2pvD15L76VCErCdwoifgKAkPzd9gJytVk45xoW9s3nqLhvIYoCAxUoq2E2c7+lm2mmBDlGuLaqJwtmKgcYvGQXsaR9Uo5HQXB/x9u3VRqP9B3gBy4JGXvNnovtIygsjhuLG3FGxsRyeH6gAW+KBwEAZj/ALG7fNwzsItgJZTBaOlc7KazjtucydmEia3jFQ+I1l8anrIWZ8uQWBKE5HjDuz+J5hEjOS7CHMWhBKha/Af6A419Ce2jtYHwPrwXsgY19lc91A8wswEQR5MSGZg49Xj+9xHufTso1OB5hKqSa72OMZmr5eIOAPuRJ21kByG/oZEFNVMfaxlgAIKUQrIXYmyGsVoV8N31frTZ/Yx3Xinifg6d0sM/BTGMYgwDGaQCAPms4rRiXAbnN9D0eC10DOV9nklwYC3UzgtYjLzFmfOH6TwdWFKt0K+WygXB9PN4yp+bUszlmSY08BnT12RI0X0IJkT/Tv6tnc3SdhJrHwKv1gEBOTSZTCxOp/Cy68zgJ3kQltuhZZD3TSQesR+y9b6FvIoYlBTQloe1kDgSqVYPmgr2utlJRl4ODejYHrW4zn/WfdjweQJWS7DJuIXkbbk4QY8jpTLkWzL4dAvbejxiHqCSeAoH5+CuJ/vz2UsK1hObKwXUC+qyIe+69z8rs7VPeNj1QGxIHid2bPBeVtReE7pLbtx1nUygA6qesFAYga480C4/mRsfrUPppo0frI63/5Io9BzvlfWcfDTk9W9veexPYiUR7GTKk/+AtiQ+uXsXhb8p+436P5rpMAC5KS7hWw+wF7J0TzBPG3GgH0HD39cm9mixq28BVAJtew2hycRjF7zSazd+EwBDmyrMIWjE2Qal8Q2dw13LgCSY+3D62CWDjWBAi4yeSUQBPQgLZo1HXQ2kzmff5oaflkAefVusMtEnHEssBwRjQap0/U7/Eas0FYanOw7NwMFkPPbclbJ3X8pSLzTgzEScK6zOrle/YQ2suR8hFrMepJgu51pwZiuebJh25rnAd69jf8bZ+Zh4PlJuumajSL5/Eh9nDSMdWCxc1PhSaS243NIKXDj5seaANmuvbmSunBUsvNCL3AQCay463RXCbWs5Anicir0VeCggbWAph8Fk2gKUTBbwmTD8OWVIwUQLIlcss3Grlc9o2kxDFatpmwXU7GcJ9uS6YmMra6x5qFXL8BQCmTxwoCEyelJeEXtAGliJ5Xq4BbpRAexEgxhobc+tQL7RdNmRnO9vZnexeeRa1irqYTjnQGd+0Prrn/vETqO9+B+ImBqoOZhAXV6D9PciUSXCOsxnzAdQ2eRniP/g4t+/+/Y8BsLsfiDC8MtvQDZmMBuFwD7AO8pqXLOFwD3Ae9rDPa99mMLAzDdHHdeITLgi6/E//Bu2lZYXz+PIzM4XlA9bM2PtogvUht9E/meHqew0QgIfzRwCAxRsn6B7vYTxs0TwbYI4YJty9pzC8foL1kUL3LK5/49vZ7DdYPCqXdP/9NVP+XQesXoq6JkkWsOUSdbPPS7/+/7Ev++Q/fB/tJS+lhIlVp5rX8mm9vnpA6M56kK8KyQIjCmcfTvNypfBYBFx9b4LugrcPx3ze632B6ZMo8BPfgGZGGyXqw5FAd+Gx94slPv6PxwA41iEivqBWJFt826H/uN/IRFBgWcPuvIXtgZMjHl9ywMUbCmYGnL7JYzB/ian7Eq3edon6eAh0UXckUfw9+qcBy/96iQ/figWPTYDvPJrzBvYPol7NVYOgmDdFH/Igtq2FEh5nlxNgrqFOeCm0/EmlG5JK1ImDmebQ4+Atmcfsoz93+NMf/xx/97MfIqWqpidLLJ5OMtxbTNlL6ScjrJE4e62HPuU+OCvh//dXSKv3dRlpxWXoaQmQ5AoB+FkHkZYLs56V0qc9RJxQgpAIXQssVP6s2wCA9RG7iGQ6gAjDsYIwIVdtThoNe9AxXX4+VgdYj/GogU3KYpcdhmMNdckPs4hB0eUjgSAV5LoQ3ox7AotXIqx5VBhO0oOmMX+NkYh+xjGN5amCMB2GIwXhAoaTmC151mN1qjEcExCimzukak6J5cvFLW/mGrYjBNlg+SBVuMZofiegBsniPwAmsa5m8VqAjUFLuebUW+KfVDF4OLzs4DoJsiy8A/BDydBjDbUu2ZTElLV8SWRXnEWKgPVhyEHTVO077gPNNUHGytXVQ5ZEnHzcYvHtyH2x50CjABmC730GYH33B5/infYREJmyASB4gtAe81kHv2fRPYvX3QKLb3ngZI3Fk66c+76HGAi+C1DXxfH2TYB/OMI1PE52n9sf3tH4bz/8X/jv5r8AAKbtiON+iV8/PsV//sHPAQBvXb6MqRphg8AfHr0PAMxwRSP+8eb7eOfmBH908h4A4K/f/RPoa2YXT0TCQXDW4/XTS3xw9Woesz/98c/xV9/+e/xFINjIr/LHR7/G35z+CEp4WC/w+vQZj03/FBd2ir998gb+7OE/AwDOzAz/s6tmxN9i93ayCDGVV/6uCsmWayDHGtYI1oGGdSG3CR60HBBGkz+322gvIm/EnAvJunMFsiGTysI6LtYaS7CV1ga0XKM5V9AxiyBulujPGoibGDiLx5p+6tFcu1xMBYBVtoIECOjPLYSNxUiXFtOPNUvnxfVqd+mgFhYtAXJh0CYE52jRXjnIUaA7jyxJMWAo1gqgEkPoz8a8Xp/G/jbxN7oRoNHzb4Ccqp69T9BRJpBh0pz7t5cllSqNRHPJ691Usk2ePYv2skJwRj4M8gGTxxLtVbqe0Su7Ql5vp7X1eEloFiV1KAeB7tJDXQ2YfsCvc9uLjF7MBMsA3jUvo3/MGh01rR4AlhPsG3QXMc7jAqYfSKxvOvTPkgdEsBNZPItlvfYXWF906M94m51Er/Bshf/xiz/H8EsuGls2AY8nHs2ZZKUwALjWCIo5Mn5xyMplXc/XYTlvERYK7x6zZzL5hGs9vESOJwQFLH45w3ufTnD4mzJmf/ezH+IvAuHvf/GDTH7z04NXsTqbIPFZ/HTCZPttbzCuFXDW4q9OoxdkBM5WP8Fd7d5OFgBwqzjshftxEVYOcN7ld8/xvihJAmz8HQp5zt09ttKPgsMpkNzA/yX3mULZlgvJEiVf3K9myr7zuHxB24BRp/+w+bndLwqb23lbHE+/2Q5VNRKfy8Lm93ysjWvGxyvAMmSXfGN862uQx/MLgsUClWu8cS2rfm/dmiHBinwM6vqqv55j8vl+edF9lzyKSooghC92DnexXYBzZzvb2Z3sfnsWFaCp1g3JgKu0D0WVrVSM5gPjJaQsn1UbQHFflWDYtWuYhTuzeyevYpvur9HwXdHx0I2G7RV0ZOVOxyo6Gb4AjDrKOhteUwZQNZIYSRiQ5RJdQ0h8DYEAl8BTnvkxzJSgVpEPI0bC7FRinNXAMAXXcml0AjQlXIRrJaRwsNNN3ZBxr7i/otYNmRISpMFOefnhZYDr4sECBw29JsiKezMQQ7MZtxDTeC0AAsZ9yuLDifk7MYklCr9xnyANwTcKNmKPzF6AHAlkAN+GvNSgoxFm0fGf1QvWtwFkBOws5GvhZYCdArZHjqWM+wQz4xJ812KTsFcD45HPgDUzK2P8xslT/N+DSOPVeMjewowdTk44MH4up1CKyVQfHt0AKOzeb4tTLHSHl44Z9XrRTUE2ekYRyBWIkZl0PGLc7/OYTU+W+OOjX+OnB69mj+L102d425/mfu9POY53MllgsBof4AjfengBAFgajXN1d4j7/Z0stti9a7LdmoMTzgHe8bYqZpHJcyqAV91GjtiPFkQEtXIQoy8uuItcktXvKX5PvAcAgNFArWypTE2EvUsmgpHG5xoQLZNmJefem4iCVINDc6N4JnQJ+OQhjGOSmdFBpf46Dzl46IXg46LELJQkNPMykaqVBVnmQEi595qPgUYPleotYnyouWLCXIBFfEJ8cMkXIl/XccaCXfw05oBeAHLwhTTGh0jEHdAsAlSEi+uENRCoOB+Q26ljFk4zB4MYLZqbeP09Izg5G1K4NsxZi+aKNieLwC+A5gYQjjLJMQKgb8AZikzKQxVh73bMghBIZMBTIey1eOvJS2jOIzJWS7hOorkUrGYOQFwrWB0AjywA9LSZQUqP1SVzZn4UmJDmYB4iH0UBpgVBaC4kjG/RXBdOisXTCf7m9Ecco4j2tj+FOesRiHlUzpb8ErvqOzgrgbMWH4BJg70RGO3vIPnNLXseHDxrhdxhdVXpihQ6/PySQtLWJEvFkxHEHAGfo49coMZ/bnyvCrPSd4rH5X6VdXeQlc6pIHwV3AQvtOpBy4VKlKDNZZ+EXtwoOktFS6lsveJPDtXvv+iyelMKAFmntN6eJoqsh1LFOQMVb6EWHf6y/CCiUkALhIpDongGgcKGZyuSZADPpsWJjv0MssQfXlgERiwHsK1XGmK7AaG+zb+0fXMni+fpfdaexW+zKtKU2YLqcfe+cFH4annzOfvIFbDx4UkBv5ghyIHA9D2gHCtUOIVI+Zf2/e0ltV/C6kBkDBYmfZA6QJu1WXNQuQTkUmFWGq+kn7qtG/J5bTvwmvuwFXgNQLmmgR+8FAx9Lt/Fl9SO9aF4N2nM+BhUtgXauG7eU6VHSsWJTufj6n694EkPgPX1Gy71gWtyqWr3q4iJfyMniw3hoFwKXscxBDNoCSqf220kvYxYku61YJc1rVOTZ+FFVWJeSqx9LmWX/D2XzJeYhNdi48HwmrKCl1cElxS2KmandCyvKbM7BSU2RIK47dKHTBnfiLz252PEQrKBcmoyeVFeCabyj7GQ9NbzbYkfsGZoVO5qSym4axmkBM/buWFOrXpFmRAH1STsmtKHBMByLW3AkVPbzgDpAXFtHAtZxs610SOQyFIEAOAnDq4V0eMoLoVvA9ySclupv67lqsy6P7aLJUUaG0JFrgFcH/L52q6M8cl0iQ96XnKEJiC0Hm4l0ESd0dEQq5mHoj06iezeZlSwnjILt296psITyMQ1QXA/fe/gWp3PQUwtXp8+y+lRgGMUZ0udQ23NxOTtaytxs1DYm/F6chzV5xIZ2mVDdraznd3J7q9nsUV+88JsiBAxKU3VwiyU7emzagNAflOn3zGJSnnT5fbqxR6xpxK0yFWSkPF78mzisVzkUPS+tOEV5WxL8g4A9m58zH5kLkfJ3lNIhDnJk6HCMZn6kCHcmjZVxTUXOgUt8vbkUSXymo3zReU18Eawvgdv8zEG4Vs+P/Kh7Bt4vySXGH+dr5nTxWtL3oBrK48i6aC2BDemX8W/m4AgZdFIbQN7cFRprQIQEwvXqs3YUwjwbYheXZEkTPqrvineFnsayO2Kqp4r6aImzyJlgbwWeGl6jd/0D3lD4yE7B7eU2J/wG/xylJCasyGHE4Za77cDOmkwH1rMPeGg532vk9ZsdesFwXwUYmrhWp3HoZ+M+G7/FG1fqsFOJgtc9V32LLazIYtph+PYh6XWHPO4o92vyaJm1o4IzVQvIg4PmOQmBM58xOwDGebjJOczSQ0A4OUHoNmUoeGJKKdrGe0pRXbdU9WlsMxALVNQcbGEiOnQTLTTNjCPDuBameHJbtZi3JdoWw1IgoxCR8JxRF9WDNGuLUQrch3y+lmuXeaAoFiHopZHkNcDVK8gFmvIWYQpz5dQq0O4RsFMqyWLBMxE8M0ch3HclzA9T4SZC6KTvIxqGMqdyGvcKyccG3EldVp0QWlDqlCMyEJCrqpGlyPL+WV6/8rUusvU9mrgvqx06ZdruT+25wBpqoy0E2AcCcNLk/zwkiWIEbcqJtdGQpvnLDlViNkTyiXxPO4SflUyJHYiYKee09pHDj4SIQmbJtFQJrcuwOuAm9cUpqYFxeMGEnDEmSTjYobEyHJN4ralaSAoYFhr+FHieuBZTy0CmvntpUHoI//FXsBNfHFYI3Fhp4zMjDZYzVmPNCbx+2A1/vDkfZzNpzjt+R5b6ga/+l3QOg1bEZlgbInS1HwXVYp0Q8t0GBGGNWipcxk6AMAHBOMLZ0CcdNTKghIdP1DSrul7PJa6HqLEHV8EOV+jvWwhhpj7S3wUi5DbTFanNtXKQsfUqRhcvkFSCjOlY8Xgymf8dzE4NDcezRX3L6VnhZG8/o43ZntpoVYCem4RJN/l+sawJ9WIDb1XcbUE+YDm+iD3JUOuR+SUJgDYayo3dHWZmkXYoKqvLY0Hf4/Q80ugu4iTTsPxkVSwlo+9JrRXAe3FOuuNpPSmMJVnBGA802gvbx0aYuSUp7CU+wCwfomwlEl8u2cKci0gRkDPVS4kI88eiJlJtAxRgDTsQU0fW/zq8YPMTsXkNxL6inDzmMEY6krBN9z3pyZec+2htIM566EWAjcRuPFoi64/9/WJghkE9s4JbRyzs9d6/O2TN4Cz4l59gKONv29iXdRi2uFsPsXykxnejPfuN1frdMs2lh0ALydSpqACWtXgq3qZEZQESRY3ziISgUli4AV8Im2J3oPtFaRwBWyVAF3AxrF8o+A6zqUDQNMwa1Wi40vFagk0lQBTwCZoyvZqAyiVtidwVAJ6+U5mIFj6d99JmInIBWRpqWImYkNO0PYCrhUgKzHWoCzBq4KA7gAAA09JREFUIDQpKYsEQUoE8hj3qXgWcf5zDWWwFMDFXqkmZKyOBwL6TsIPt2+rGkSWzns8ANQWUMtMKWqgpmMxGY3XEuM+75uAU1lmMJ3vqcF6Va3D8rgzmMrMeFyTJRBWAqaNe8y2JdcE24cNvVTfAObAsxwlADsL0RMS+MGjp/j5Yy4ADE0AGo8gFPYe8Rv8Rk8hGr4PHhzxtok2mDVr/AoPMPZNkRSMAkDbNh476MM1zJNp9rr06Qp/9vCfc60HAHzr4UXGUQDIwczjyQqn/RxvGonvPeTK6KVpcKZuT+wvsl2Ac2c729md7N56Fs+15yWNPyORHBJku7aKY6H+HUWlr42c+/ZvQ6gwA1s4jSiok4wcbrXHGhEox6u+iy2wV1In2/is/q3GBzC2IOlQhAzg2ihGqzAOIZ2rCxsq5ACiBkbpb+731vai7PWcc37OtaAKN1D/NvcrFnyJqKORtgtXziPrcJjSpw3AkqFbcQwgxjiyvka1VLWlrdQHsqmvFVYj9d9QiZukax4C5mPL4D0gBlcZzDcmLlJD8DHwPWy5/c5KwJR9mxeohJElOCuYCi+lsK3EmZnBmzIIS6M3/k7tLrXGUjdwVmJpmrLv50DIfXMmi1qycDtDsb0NwEa1aAJpVaCtIDZ/l9S0NtB8223WdSJVtL30sfyd6NXq9phKDeV41XdfYlJ5GxItP221k6ne03EDSJTzKDtic2JLp/G8mJZzkWsSpV/V5/b29N1Xd1A+5+fABdO/bbe7udMtfFFRQ499AyIGwm/2CQCgw8ayJLehOAvi9eb4sGRA1R+BkknZHiPidvI5EPLkNmvWCJHcOKgA6ICgApqGZ5a1DhCa78FO87a0DJHKwWmZ9/XyOeMCIMgAKRkpmiZSqRxO9Ty3ndqt/07tTrSBoAAhPFrJ26wXEJ8DIUfbgcSvw4joKYAFgLOvuy//ynaK3Tn/Pth9Puc/CCE8uMuO92KyAAAi+qcQwr/7uvvxr2m7c/79sN+Vc94FOHe2s53dyXaTxc52trM72X2aLP7y6+7A12C7c/79sN+Jc743MYud7Wxn99vuk2exs53t7B7bbrLY2c52difbTRY729nO7mS7yWJnO9vZnWw3WexsZzu7k/1/NPjAjD8+tQ0AAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 44.13302397727966 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 1e-06} is: \n",
-      "[[3.200e-17 1.600e-17 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.600e-17 3.200e-17 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 3.200e-17 ... 3.200e-17 3.200e-17 3.200e-17]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 3.200e-17 ... 3.232e-15 3.128e-15 3.200e-15]\n",
-      " [0.000e+00 0.000e+00 3.200e-17 ... 3.128e-15 3.030e-15 3.092e-15]\n",
-      " [0.000e+00 0.000e+00 3.200e-17 ... 3.200e-15 3.092e-15 3.184e-15]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb6c1443c8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.93401503562927 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 1e-05} is: \n",
-      "[[3.200e-14 1.600e-14 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [1.600e-14 3.200e-14 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
-      " [0.000e+00 0.000e+00 3.200e-14 ... 3.200e-14 3.200e-14 3.200e-14]\n",
-      " ...\n",
-      " [0.000e+00 0.000e+00 3.200e-14 ... 3.232e-12 3.128e-12 3.200e-12]\n",
-      " [0.000e+00 0.000e+00 3.200e-14 ... 3.128e-12 3.030e-12 3.092e-12]\n",
-      " [0.000e+00 0.000e+00 3.200e-14 ... 3.200e-12 3.092e-12 3.184e-12]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468c8d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.997790575027466 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 0.0001} is: \n",
-      "[[3.20000002e-11 1.60000000e-11 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.60000000e-11 3.20000002e-11 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 3.20000002e-11 ... 3.20000002e-11\n",
-      "  3.20000002e-11 3.20000002e-11]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 3.20000002e-11 ... 3.23200002e-09\n",
-      "  3.12800002e-09 3.20000002e-09]\n",
-      " [0.00000000e+00 0.00000000e+00 3.20000002e-11 ... 3.12800002e-09\n",
-      "  3.03000002e-09 3.09200002e-09]\n",
-      " [0.00000000e+00 0.00000000e+00 3.20000002e-11 ... 3.20000002e-09\n",
-      "  3.09200002e-09 3.18400003e-09]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 44.6544508934021 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 0.001} is: \n",
-      "[[3.20000160e-08 1.60000000e-08 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.60000000e-08 3.20000240e-08 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 3.20000160e-08 ... 3.20000160e-08\n",
-      "  3.20000160e-08 3.20000160e-08]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 3.20000160e-08 ... 3.23200229e-06\n",
-      "  3.12800211e-06 3.20000214e-06]\n",
-      " [0.00000000e+00 0.00000000e+00 3.20000160e-08 ... 3.12800211e-06\n",
-      "  3.03000196e-06 3.09200199e-06]\n",
-      " [0.00000000e+00 0.00000000e+00 3.20000160e-08 ... 3.20000214e-06\n",
-      "  3.09200199e-06 3.18400274e-06]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe26a0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 44.26693940162659 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 0.01} is: \n",
-      "[[3.20016002e-05 1.60000000e-05 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.60000000e-05 3.20024003e-05 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 3.20016002e-05 ... 3.20016002e-05\n",
-      "  3.20016002e-05 3.20016002e-05]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 3.20016002e-05 ... 3.23222885e-03\n",
-      "  3.12821085e-03 3.20021445e-03]\n",
-      " [0.00000000e+00 0.00000000e+00 3.20016002e-05 ... 3.12821085e-03\n",
-      "  3.03019585e-03 3.09219945e-03]\n",
-      " [0.00000000e+00 0.00000000e+00 3.20016002e-05 ... 3.20021445e-03\n",
-      "  3.09219945e-03 3.18427449e-03]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f8320>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 44.429144620895386 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 0.1} is: \n",
-      "[[0.03216167 0.016      0.         ... 0.         0.         0.        ]\n",
-      " [0.016      0.03224328 0.         ... 0.         0.         0.        ]\n",
-      " [0.         0.         0.03216167 ... 0.03216167 0.03216167 0.03216167]\n",
-      " ...\n",
-      " [0.         0.         0.03216167 ... 3.2554357  3.14960373 3.22194735]\n",
-      " [0.         0.         0.03216167 ... 3.14960373 3.05010307 3.11249761]\n",
-      " [0.         0.         0.03216167 ... 3.22194735 3.11249761 3.21242132]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 44.200169801712036 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 1.0} is: \n",
-      "[[3.2000000e+02 1.6000000e+01 0.0000000e+00 ... 0.0000000e+00\n",
-      "  0.0000000e+00 0.0000000e+00]\n",
-      " [1.6000000e+01 5.3600000e+02 0.0000000e+00 ... 0.0000000e+00\n",
-      "  0.0000000e+00 0.0000000e+00]\n",
-      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 3.2000000e+02\n",
-      "  3.2000000e+02 3.2000000e+02]\n",
-      " ...\n",
-      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 3.9599184e+07\n",
-      "  1.8790076e+07 1.9904800e+05]\n",
-      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 1.8790076e+07\n",
-      "  4.5132236e+07 5.0194600e+05]\n",
-      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 1.9904800e+05\n",
-      "  5.0194600e+05 4.7488000e+06]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468c8d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.947789669036865 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 10.0} is: \n",
-      "[[6.52864162e+14 1.60000000e+04 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.60000000e+04 6.52896808e+18 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 6.52864162e+14 ... 6.52864162e+14\n",
-      "  6.52864162e+14 6.52864162e+14]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 6.52864162e+14 ... 9.71153321e+38\n",
-      "  4.83215703e+36 2.92253118e+26]\n",
-      " [0.00000000e+00 0.00000000e+00 6.52864162e+14 ... 4.83215703e+36\n",
-      "  9.73580847e+38 6.40218246e+28]\n",
-      " [0.00000000e+00 0.00000000e+00 6.52864162e+14 ... 2.92253118e+26\n",
-      "  6.40218246e+28 1.60883971e+30]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb6c144390>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.95116639137268 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 100.0} is: \n",
-      "[[6.40128006e+27 1.60000000e+07 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.60000000e+07 6.40128010e+35 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40128006e+27 ... 6.40128006e+27\n",
-      "  6.40128006e+27 6.40128006e+27]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 6.40128006e+27 ... 9.33493318e+71\n",
-      "  4.66723328e+67 2.81704975e+49]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40128006e+27 ... 4.66723328e+67\n",
-      "  9.33516655e+71 6.14653487e+53]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40128006e+27 ... 2.81704975e+49\n",
-      "  6.14653487e+53 1.53671603e+55]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.93626260757446 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 1000.0} is: \n",
-      "[[6.40001280e+040 1.60000000e+010 0.00000000e+000 ... 0.00000000e+000\n",
-      "  0.00000000e+000 0.00000000e+000]\n",
-      " [1.60000000e+010 6.40001280e+052 0.00000000e+000 ... 0.00000000e+000\n",
-      "  0.00000000e+000 0.00000000e+000]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40001280e+040 ... 6.40001280e+040\n",
-      "  6.40001280e+040 6.40001280e+040]\n",
-      " ...\n",
-      " [0.00000000e+000 0.00000000e+000 6.40001280e+040 ... 9.33123732e+104\n",
-      "  4.66561633e+098 2.81601050e+072]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40001280e+040 ... 4.66561633e+098\n",
-      "  9.33123966e+104 6.14402534e+078]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40001280e+040 ... 2.81601050e+072\n",
-      "  6.14402534e+078 1.53600716e+080]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.99435877799988 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 10000.0} is: \n",
-      "[[6.40000013e+053 1.60000000e+013 0.00000000e+000 ... 0.00000000e+000\n",
-      "  0.00000000e+000 0.00000000e+000]\n",
-      " [1.60000000e+013 6.40000013e+069 0.00000000e+000 ... 0.00000000e+000\n",
-      "  0.00000000e+000 0.00000000e+000]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000013e+053 ... 6.40000013e+053\n",
-      "  6.40000013e+053 6.40000013e+053]\n",
-      " ...\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000013e+053 ... 9.33120037e+137\n",
-      "  4.66560016e+129 2.81600010e+095]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000013e+053 ... 4.66560016e+129\n",
-      "  9.33120040e+137 6.14400025e+103]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000013e+053 ... 2.81600010e+095\n",
-      "  6.14400025e+103 1.53600007e+105]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1fd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "../pygraph/kernels/treePatternKernel.py:169: RuntimeWarning: overflow encountered in double_scalars\n",
-      "  kh += kh_tmp\n",
-      "../pygraph/kernels/treePatternKernel.py:168: RuntimeWarning: overflow encountered in double_scalars\n",
-      "  kh_tmp *= lmda * all_kh[str(pair[0]) + '.' + str(pair[1])]\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 44.15428304672241 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 100000.0} is: \n",
-      "[[6.4000e+066 1.6000e+016 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
-      "  0.0000e+000]\n",
-      " [1.6000e+016 6.4000e+086 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
-      "  0.0000e+000]\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+066 ... 6.4000e+066 6.4000e+066\n",
-      "  6.4000e+066]\n",
-      " ...\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+066 ... 9.3312e+170 4.6656e+160\n",
-      "  2.8160e+118]\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+066 ... 4.6656e+160 9.3312e+170\n",
-      "  6.1440e+128]\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+066 ... 2.8160e+118 6.1440e+128\n",
-      "  1.5360e+130]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe2ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "../pygraph/kernels/treePatternKernel.py:170: RuntimeWarning: overflow encountered in double_scalars\n",
-      "  kh *= lmda * (G1.node[n1][node_label] == G2.node[n2][node_label])\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.97559952735901 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 1000000.0} is: \n",
-      "[[6.4000e+079 1.6000e+019 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
-      "  0.0000e+000]\n",
-      " [1.6000e+019 6.4000e+103 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
-      "  0.0000e+000]\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+079 ... 6.4000e+079 6.4000e+079\n",
-      "  6.4000e+079]\n",
-      " ...\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+079 ... 9.3312e+203 4.6656e+191\n",
-      "  2.8160e+141]\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+079 ... 4.6656e+191 9.3312e+203\n",
-      "  6.1440e+153]\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+079 ... 2.8160e+141 6.1440e+153\n",
-      "  1.5360e+155]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb213dd748>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 43.95881152153015 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 10000000.0} is: \n",
-      "[[6.4000e+092 1.6000e+022 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
-      "  0.0000e+000]\n",
-      " [1.6000e+022 6.4000e+120 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
-      "  0.0000e+000]\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+092 ... 6.4000e+092 6.4000e+092\n",
-      "  6.4000e+092]\n",
-      " ...\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+092 ... 9.3312e+236 4.6656e+222\n",
-      "  2.8160e+164]\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+092 ... 4.6656e+222 9.3312e+236\n",
-      "  6.1440e+178]\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+092 ... 2.8160e+164 6.1440e+178\n",
-      "  1.5360e+180]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb68902ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "../pygraph/kernels/treePatternKernel.py:170: RuntimeWarning: invalid value encountered in double_scalars\n",
-      "  kh *= lmda * (G1.node[n1][node_label] == G2.node[n2][node_label])\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 44.18199348449707 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 100000000.0} is: \n",
-      "[[6.4000e+105 1.6000e+025 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
-      "  0.0000e+000]\n",
-      " [1.6000e+025 6.4000e+137 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
-      "  0.0000e+000]\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+105 ... 6.4000e+105 6.4000e+105\n",
-      "  6.4000e+105]\n",
-      " ...\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+105 ... 9.3312e+269 4.6656e+253\n",
-      "  2.8160e+187]\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+105 ... 4.6656e+253 9.3312e+269\n",
-      "  6.1440e+203]\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+105 ... 2.8160e+187 6.1440e+203\n",
-      "  1.5360e+205]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1c50>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 44.00055909156799 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 1000000000.0} is: \n",
-      "[[6.400e+118 1.600e+028 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
-      " [1.600e+028 6.400e+154 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
-      " [0.000e+000 0.000e+000 6.400e+118 ... 6.400e+118 6.400e+118 6.400e+118]\n",
-      " ...\n",
-      " [0.000e+000 0.000e+000 6.400e+118 ...        inf        inf 2.816e+210]\n",
-      " [0.000e+000 0.000e+000 6.400e+118 ...        inf        inf 6.144e+228]\n",
-      " [0.000e+000 0.000e+000 6.400e+118 ... 2.816e+210 6.144e+228 1.536e+230]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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Qmpqb8caFlwAEf/HKYeC0efayecpS9aVt4FSBkcMQXcsw4D2K1IqBk+bxOXbIuS4eLDxUZ7p+4eP8xwi6R7+WdvkFiJmnzzVffjxyubkzY7gStU7HOlz6gaYVXdfvJ6/1gcJ0vxx5u+AeG3LkbaxauxOHD2zzBwq/PL0tJr1nxtA64pUFIDfiUKkBOlAoXRRT/5n6wQW2WaRI0nAE5WL688/xxoWXMH3xIuTpjyFPf1xpSTVJbvhkpSWUFR4sGIZxou4NnAzD2OFTpwSRTdcsYyovM68NQGW2JStMukQ2i8y8NmSuvRYim/XzuGxlrgRKn9KcufbagvRycumeLl8D7TvK0HR/RbbKx92if+merkT11r2BU05Nlbw8OVl5W4VJ1+Dll3H33If810D1eLM2odogJy8WrNKk/Rm6kBv9HAOf/rggzdR38vLlckmaqfO3LibYYg4f2Jbo86/7waKRofsoejP3V1hNNNQgVw0aasVwHYbLylcQdf8Yov6zhKFH2Aorj+ZTv4IuddjKd4nEFURTc3NRVC+1j0JcvwhNzc3OfRGkO9vRjsl13UX9FSfqu15HpnMxsh3tvmZx/SK/HSY9Jm002laSiGQDv3nS19DU3IxM5+KifEB+z0pYRDJaL02jEckm13U7R6dvmns1muZeDSBaRLKB3zzp54kTkazuBwuGYdKhoVZDKrFtuFbgvolHJbeip1Fvw4YvZBgmGrx0yjBM6vBgwTCMEzxYMAzjBA8WDMM4UfODBYcvLC0cvtBNh+m9a/hCdVzAViaHLyRUw2qIWgKL4/zG1VEN9b6tL3tlO9oL0uMsyekbjFy0ubRX6VYoh7nU+UyYY9w42lW6yVGQqk+9BgodFiuHunGd31CHNbZ8AJy8e+ufq9JHnd8on55R+zCJd28AePPYc+wpKypxvXVHrcPmlFZPT+o9HEjvHIjSrTStXL8LLYb60kD33O3i3Zt6Bk/q3TsOLt69ddJy+JvUu3eLcP/8an6wUL/ATblcbD+S6pczzPdj3A04qty+Gx7xv9gu00JbfUE60h70VN/QgW7l+l3G/wi6D02bxqDrun5Te8L60PQfUc9bqo1Uph+E1d07/L6hA9vyTbtxfO8WAPk+BQB1lpR+xmHfO9o2NVjq9ak4JzRPVGreZsEwTHmo+ZmFGnGTeKemswh1mCeH4l8f+v58V0c+35kxnO/qQC7gmZ/+QqxcvwtH9m8tKntyXTeO7N/qvw+aHtvSlSaFizbaDltdSrf69TuyfytWrt+F3GvDfn/RNoX9apuum7SrdF3b+a4Ovz7abyvX78IRb1ax+PlnAACLDkv/sxx99g50fu/NgrJWrt8F6hni/W9djUWHc/h4lUAn8Yup63j/W/mDXJ0jwPQnSwHc7udb/Pwz6MTMbOEIeTRQs47Fzz+DD364B9OfvICbfrUZp7w2mPowSn+OPnsHOkdm0lS/+u0fmdEOADgWWHQBNW/g9A2T1y3AlU8+jV2GPn0MewyJYuCkjyEK2/MsLd82YNimpaUwcFLjJn0MoQObrj/OY0hUAyfVQ1ndvaPoMUQPL0Dr1vsyjoFT/16oz40aM5W9gGo3PoZ43r1dH0P0dqmQirrBXtlz2MAJ4Mqn48nuj+ilOtDDdAp1pOXdO6wcl3qKvHtHdFfvgk1H1DYFea5eM38zBsb3BOrwvXuHeBm31RPmTZteb913FNibf51WnwZ591bXGt67d1xfDYqo/hh0nwqu97juMYjjH4KWr+oIK8fFF4UqV+HqdyEKSsfQdH+BHlNf6XkoQT4awgYKdb/ug0Lp0/OZ6rLppa9Ney/S3Huiv9frs+3rCaNuBguGYUpL3QwWSV2flSMob5Q6qiFIsELXYrNXlBNb/wTtX7iz76lSyWkI6sZmkRSTESyIODYL3Viaph6lQzeEpWGz0HcfxtEWhtIRtAJl06Nfs2lrPn4qVEdSm4XNmKobdV33pETF1n/USBq3rppfDWEYJj4NFRhZjZhi1mwMXvoFgPjRpUu9gzPKzEInDR1x0JfwlBab/qBlSlqmKT2ONtf6h6b70df5KA6OPm28J6kO0+ej95ctT5iuKEuntnvS+M7Ujc2CYZjSUlePIWk//5XzF5zWaaKWnOmW6xxGHKpVm22WVGrYByfDMKkTOrMQQrwI4A8AjEspb/PSWgH8CsCNAD4EcL+U8nMhhADwPIBvAJgE8G+llP87TAQbOBmmMqQ9s/gpgDVa2mMADkkplwI45L0HgD4AS72/hwG84CKCYZjqJ3SwkFIeBjChJd8LQMXsewnAfST9ZzLPmwC+JIRYmJZYhmEqR1ybxQIp5Vnv9ScAFniv2wGcJvnOeGkMw9Q4iQ2cMm/0iLykIoR4WAjxlhDird/iUuz6fSsyO+wtCUGHoGz6ww4ppXloKqh+Pa1aHfa6HD4Lqtv0/Unru0uJO1h8qh4vvH/V+fAxANeTfB1eWhFSyp9IKVdIKVfMwpyYMhiGKRdO+yyEEDcC+GuyGvI0gHNSyh8JIR4D0Cql3CaEuAfAd5BfDekG8KdSyq+Flc+rIQxTGVLd7i2EeBnAXQDmCSHOAPgBgB8BeEUIsQnA3wO438v+OvIDxSjyS6cbI6tnGKYqCR0spJQPWC4VTQU8+8W3k4piGKb64B2cHtTrlYuXqijeqGgdtvL19DiespQHqVJ4yqJ/k+u6i/orjl5du/oL6wfdSxn9Ux6s1B+93+TZSi9fadDzmgyGKs/Exp6C8lQ61aRrF13LMLGxBxMbeyC6lmFyXXcsD2Qnd/YUvDd5+FJtVNdU30Q1etb8qdMw0j7fYSrPd6wrBFChszZhFnVFb9MGiGwWcmoKACCbq8+4TB3bqHgu5T7D4RIE6FLrHPztdD+Wb9pdBkUzxD0DpQcgikrdDxZpf8kCA+M4DBQ0QpRLehRdQ9P9RR7KTd6x5ZUr/mtx0W3ZWo8CRtNpfWmgQiMC9sHZpiWtiGTKE7bCNPDOmbiE3qYNOD7dHxqRTA8FYMOlD2meKBHJaJ441P1gUaqZhSnEnktUNFvEsKSRxIam+4vKsM0sMvPaICfzbghdB6lS6ablqEEgbGYRqGVhayR9+vXV3TuQOTuBwZD/1DTkwPJNu6Fq7bvhEUx5GlTZU0QTTaOxTr/oyEcvoTFMbNCZxU27dmOJpiuofaY8rtT9YOGK+iUrhVt/l3v0a2mXX4BowhsXXsLdcx/Cmi8/Hrnc3JkxXLFci4ut/8NCARRd1+8nr02u8Ezu8q4U5SpGjryNVWt34vCBbX5QZL88vS0mvWfG0OoFMZIAciSgURRoUGSlixIWmiAKbOBkGMaJunJ+kwT1bB8WoYvmV/nCon7Re2zTft1o5VqmrXxVVtKIZLRcNaU939WBlpEzuHJmrMgVYVxo5Kwwm4V65KKfl7pXn2LTZ3jRtazoV1UvP2lEMpvrwSAnw5S4LiGD3lM9uq4W0eq8KavuB4tyrIb4aRVeDbENQBR9NUQFZ0oSKzYtTF9mk//KcmnR0TVk5rVhYHxPxbQlHViAaDs4636wYBjGDrvVYxgmdXiwYBjGCR4sPKJu9047MLKeXo2BkU3bvW2+OOJojxMYmW71Vluw6R+93yWQcZzAyC4+P/TrLv5MXAjzW2HyqRG3Pt5n4RG20y+tOvRNRwo9Pa6etDZJUfQdk0f2b/Xfq3/Tis2q6ze1R/WVviuy74ZH/M1UalUk6qasOIRtyjL1zeruHQWbsuLuqoyyKUtdi7spq+YNnGmsRLha4eNa5U3Wa9uo7lJfOVcHXJYFKS7xO+Na823l2OrX09bM34yB8T0FdafRl7bviWnZMiiPrcwgjaa2BmnSaajwhYqm5uZEy39Rp/1x91mUSo/pHhdtrvssKHFOR4Zh0q7SdW1BfWN61FCogSKIOPsswrTpp04V9LSq6tPca8OhGsP067r1awV9dOyQc9l1Y7OYvngx0f1pTaNd6nCpqxx6XNG1HNm/tUJKZrD1T9B0/s6+p0olJxCq6eBHzxm1H9m/tSr6NYi6GSwYhiktPFh4lMIwaKrDdcYQV4/65UpzZqLrXrl+V2pl6+i6Te2wHVEHgo1341+dnUycA1H6/fjeLanXr8+s6HdBXRsc3u7/RaHmDZxpoQxAtmdRHZrPdObAVoc62qwbm0TXsoL0OIY3/XndRZtLe5VuxeDwdt/fg7o/qWMVk3aVrmujfaVeA8XHxoH8SoO6f2JjT8EJUVP5Ext70HbiAs7dNrcgrykfALTuO4qxV29F+x++4+dT95r6Rhkkl2/ajYtrzwMAmg+0+ANH1D78+ekjePD6lQW6dN1Avj/VNWoref/FP2kcA6f6T+XiSyKoDPovUJrVkLA0U55qWA1R0F8i069SmIVfLzPt1RCqif5qF6yQ7J1JU/ck1fHufU+gFzNlHN+7Bb37NhTo0T+z43u34Ja/fALv3vfETDw/gutqyHXtH2Noeua9GiRN392kHr3q5jFEXL8o0f1x157j1OFSVzn0uKJrWfz8MxVSMoOtf8rt4s4Fqml19w6j9sXPP1MV/RpE3QwWDMOUlpp/DFGIf/rnRPdnzuqxn93yX/Feu3hXypydcDaARdVjKr+3aUOoNtoO13IXHZbAdyPLC0Tp8P1ZeOmmx4TB4e1WA2fbiQuJdLSduIDM2Qm0oTAmp96Pqh7d4md6PKOPRPT6u/c94b8+9d3vAwB6v5fskUg9ApnqU9eonpYX/8S5bDZwMkwD01BH1H3DFQdGLgkuh6RM/RakMY2DZzYNpnSVxoGRk1HzjyFr5m8GAAxNvRLbqr1m/maIrmUFZwcAoK/zUWNdQLSlU3UfXR6kZU12L8HhA9twZ99TUDsBRNeyovpN91JKsXSq+oYy+uwd/jXVX3f2PYXm46cAFPebi/6oS6e0frUzc/yrs5HbWBh0h9Y5ML4n1EFxnKVTWzuUrgsbe4zfgbFXb/Vfqz7t/N6beb1EZ5jmVWt3+q+/8JZH9frWzN9sXDrFi+7bvWv+McTfH5HNYvDyywDiuxurhoNkNtLQEYckB8loml6mKT2ONtf6h6b7sebLj2PgN08a70mqI8lBsjBd1XKQrOYfQxiGKQ81P7OgpPWLRcurBkexQPqR1UpJ2MyiklSrNtssqdTwzIJhmNSpeQOn+vXPtLXGHomHpvuLDkuFbbOO4s9C/Wq4HCSj5du8ZdlmPKWIG2Lqm5Xrd1mPU1NdUbZ7x4kbYvNApe91CLKj6OWXKm6ILU3HFF8kis2C1uOioUW06rdbqavHEIZhosGPIQzDpA4PFgzDOMGDhYd6BqUu3oOgO+Zc8tOyTfn1dNcydU3K/b2rNpf26u71R5+9o6i/4ujVtau/sH6g9enaJjb2FPzR+ycMG7b08pUGPa9pR6TKQzdXKQ1UGy2Lpo29eivGXr0VExt7MPrsHf7GrCj8/PSRgve6btpX6prqm6h7fWrewJkW6qCQy8Eq270u+RR6fr1e1zKD6nApx/UgGWXR4VxRf4WVEQWq2aRfP8RHaQsoq+3EhaKDX7b+MeW15Wk+0FJQnjqEprTRQ2k07Rxa/HKu+sdcSG1mVr68FUsws4tU1037Sl2Le9iu7gcL170SUwtbgTNjfswHBKwO9DZtKPBJoFYtMjd3Yuq90eA6FFr5er1KjytD0543q4WtvjabpfzSPV3IjX6e1+7tHAzqowLdAD5eJXD1Ga2/DG2KglrFWN29w4/9odKHtFUh2le6NhWLQ9FGdJ27bS5aRwrr1ft5+abdTnE8lm/ajeNenlv+8glg30x5qh6ljdZL05SnrHNowcRX8v/FO18LrBZA4YrLkQd24cFtM56y9DbSvlIneFUfRfX9UfeDhStqmczFPZ4tnzz9ceR7bNdcdcS5J3fsQwx8+mPcPfeh0HMHpnI7R2Z+KePoDKrDpR9omn5dHwzor6x+jsN4/76joTMKlW/V+E4cPrDNd6mnylMaVNlUU0HaPlKeQ50mqEs9pYti6j9TP7jANguGYZzgmUWKJI1dUi6mP88/gkxfvIimkNkQYyc3fLLSEsoKDxYeaoeeS4QuIN45FBodyhZlKygSVxhBOxttiPbr8i/et3/x9Shb57s60DJypqC/gPA+C8Lm98EU4UvfPUvRbRiZsxMmnpDJAAALaElEQVS+LtNxd72fXVcIhqb7/SPo1KN2tqPd3/2ptNHdoDSNxjr9oiNv4Iwakezkzh4s2WY/Sm/6PlOv47yDk2EYJ3gHJ8MwqcODBcMwTvBg4cE7ON108w7Omfe8g7POyMxrw9Rn51IvTw/nZ3KdVk4y89qKghhl5rVhYHg7Vq3d6Vvupz47VzFHK0Gs7t6BS61zMGfiEgY9zQBw1fi/pP4ZBqE2ZR0f3o5V43kNueGTBf5RVb7je7dgzf8K36eSNtklNwIArpz8MNJ9epiAqJuy6t7AqfsaSNvfIk0T2SzklbQ2PaejS0eFepSXLwMAmr70uwCAgfE9FR8wXH2hlkuLjq4hc3MnBn7zZMW0xfU1S4li4Kz5wUJ1QNJYp+qXQhHmsJd6dzYF3NXLB1BUhwla/vG9WyI5v1H30LLCtNm8VNO6dN3TnyxF03XvW/WHfZlN15WO43u3YPmm3b4e2yBo60s/fqhFE00zlT/26q1oPtCCi2vPF+zM1PtRPXq0/+E7JXN+E8dhL63H1flNwwwWDMPEh5dOGYZJHR4sPNROt2xHu3HXoCk/vce1DrpSQdHTXcu0la/KCivHpb2qXJV3cl23f49eX1xU2aoeha2v9M9L3auvjtD7TSsrevmiaxmyHe1FefU+oqsMur9MuhtV7xuaZvqLimmVRn+v746NW1/Nr4akZbNQR6EVYTaLomPSDg576QpK2Ac1tbC16Gi2SYd+jzEtQJvLkXylW20jX/z8Mziyv3hLuf6cHMVmQbW7HM9X/aNz7ra5RluGzWZhur8NlqPeRJPaqq2fcrUR1UgbxTBvG1CTBLUyEWqzEEK8COAPAIxLKW/z0p4A8O8B/IOX7T9JKV/3rj0OYBOAKQD/QUr5RpgItlkwTGWIYrNwmVn8FMCfAfiZlv6slHIXTRBC3ALgmwBuBbAIwH8XQvyelHLKRUwc/BFUCCCmsdZ0ACtsZsGhAOyhAOLMLMoRCuDOvqfwtwf/Y0HdevnVFAqgXKshroTaLKSUhwFMhOXzuBfAL6WUl6SUpwCMAviasxqGYaqWJDaL7wgh/gjAWwC+L6X8HEA7gDdJnjNeWsnwR9wES8B0JKaGLX00D3TtFvDrbQocE7aByjarMN1bpElPS2CzoL9EynZxxHN/p35VdV1hz+Zh9hYXm4XqH9G1rGAmoV6r3YnKftHbtAEXNvaEaiuVzSLqBiqXYE2m67ZZncusJgynfRZCiBsB/DWxWSwA8BnyXsv+M4CFUsp/J4T4MwBvSin/q5dvL4CDUsr/ZijzYQAPA8BVyC3/uvhGrAak9RjisnMw7k5C0wdo++Bc6ivnjkbXKbYi7mNIXG1B9etpa+ZvxsD4noK60+hL2/dE76+wPLYyozyG2O6xlZH6Dk59sLBd84ybkFI+6V17A8ATUspAp39s4GSYylDyTVlCiIXk7ToAJ7zXvwbwTSHEHCHEYgBLARyLU0e5ofsSSrXPImh927QeH5VS7bNQ5Zn2QlRqnwVtn2m/Au+zMOux6XIh1GYhhHgZwF0A5gkhzgD4AYC7hBC3I/8Y8iGAPwYAKeU7QohXALyLfKiCb5dyJYRhmPIROlhIKR8wJO8NyP9DAD9MIioKqW7KimCziLspSxngwkZ1padaNmUNDm8v2JR1yrBsWc5NWfrnpVAHzPTlU9uzvQ5vyrJT8zs4VYfEHShUGROepdw/hQmzRVlBvyym4DWm+6hjkrDVkHO3zY28GqIH2FFpQdrCvvS0T9QKwwc/3IPlmwRa9x1NbTWEag/TrPJQbUB+5ePi2vP5oD8e6gRqb9MGjL16a8FJUhMX157HOeRPndK4HromFSCI5gmiHlZDan6wSGtmsXzT7sIv/r70V0OosxGXD65aVkP0ZcjpT17Iv95bnLfSqyEAio6oF+SdRip1R4VnFlXAmvmbAQBvXHgp9hdgzfzNaFu8qCi9r/NRY13ATLxIFTsyaE1J3WeqAwBWrc1HtqK0nbhQVH8YphiWYdpoO0yY+uamX23Gqe/ay4yqm+pQr13ijJpoPtAC3Ge/LywCW/OBFrSduODHIbVpovFNSwHV6RI1ruh+8l1Ni5ofLJS7NZdftKAyhjxPUZPrugEAOQAHR58ufK4mrt38OA8j+de5gGmzum/IW+PXNc4heV32X9japzTpaUHaaDtMqL4B8tu8AeDU/q1YuX4Xcq8NGx9DDo4+bdVu00+1h2kGZlwZTq7rLth6rmY/i59/Jq/1u9/36xx99g6c8mK72pj4isRV/5jDxFdkQUhBXZOKTeq6Wdr1O2nqz6D4uXrZ6n7dDWEajyF8RJ1hGCfqylNWWs/CtLxKPNuaKLeOJLiuPFSCatVm241aathTFsMwqVPzNgv16y+y8ZuiW/EB86iedDUkLet0uVdDop4NcSnTNa9LOXr9ptnD0HS/0VCYRl/aVs30/rLlCTNgBmm0zZTSWsmj1NVjCMMw0eDHEIZhUqfmBws1DUv6GKL+NR280fPFKd92wCfoIJGtvjQ22LjickjK1G9BGuMemrKVY6tfT8vc3FlUd1o6TO9dvktKV1CZLn0Z1q402smPIQzTwPBjCMMwqcODBcMwTtT9YFHq51OaJmbNLrpWLmy6TM+0TbkcxKzZELNmI3PNNchcc01Z7SA2XG1H5dISZE8C8tHMK6ktzn1JqPvBgmGYdGADJ8M0MGkHGapq1M60pP4sbtq1Gx9snQl7F+Yp6+TOvNOVJduO4uTOHizZZvdJrKZ/eh0maPkfbN0SaSepuoeWFaaNtsOm3UU3rTNsh6bputLxwdYtuGnXbl+Pqa1Bmj4ZW4Tr2j+2aqJppvJ/fvoIVr68FUce2IUHr19ZoI/20c9PHwEAPHj9Suddri4nP026ouzgpPW4aIgSZKjmB4u0WLLtKGAOsmXPb3gddk/vtuIYImno0ct31eaiXZXrst07LkpH77YNWELSTf9Jepu8PIb+yf/nNddh8htiun8JjuLBbSsL0vV+ogOJri3oP6g+AKS19Z3WZXpPB5y4dbHNgmEYJ3iwYBjGCTZweoiuZZAjbxcEvA3Lr/Kpe13qUF6nbQ57VbprmbbyVVlh5bi0V5Wrwhe+/62rsfQvvrCGL4yD0jFIQiMCdpuFykPjewwOby/wcwrkPWdRh8mt+44WlUXLn9jYk3erd9vcgrx6P/qOnT2nxWE2C/26jah9GHa6VNdjslmkGpGs1FTDYMEwjUhDbff2R0nh1N7AMvggWXBdNX+QbF5b6IGruDpM750Pks1rCyyTD5IReGbBMJWhoWYWaUHjlpYq1imNy6mjp7uWaStflZVGrFMagzTb0Y7Jdd0Vj3Wqf17qXhWDlGOdmvXYdLnAgwXDME7U/GOIb/0VAojZFpOVOGwHZ9TyVZl6mo5LfXF1xMHF0k+pdESyQB+c8zdjwIuB4hrty1VHEh+cVI+pzCCNprYGadKJ8hhS84NFGK5fBtelU1UezafSMjd3BgaEKeXS6dB0f0HgZRu9TRtw6Z4uHD6wDWu+/DgGvKA7QX1UrqXTIO36F7/US6cmLXo+FdCIXrMNqGkunboMQkF5qQZeOmUYxgk2cMZA/UJRw1VYfnqPax2uBk7XMm3lq7LCynFprypX5R199o4C414aBk5qkKR6bH2lf17q3omNPQV/9H4acd1W/sTGHoiuZUV59T5S5etlsIGTYZiGhweLmAwObw+1D5SbatMThWrpz+N7txh16GnUXtEosM2CYRqYmlsNEUL8A4AvAHxWaS1lZh64zY1ANbf5X0kpr3XJWBWDBQAIId6SUq6otI5ywm1uDOqlzWyzYBjGCR4sGIZxopoGi59UWkAF4DY3BnXR5qqxWTAMU91U08yCYZgqhgcLhmGc4MGCYRgneLBgGMYJHiwYhnHi/wNBtBeXgUw0EwAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 44.096922874450684 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 4.0, 'lmda': 10000000000.0} is: \n",
-      "[[6.400e+131 1.600e+031 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
-      " [1.600e+031 6.400e+171 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
-      " [0.000e+000 0.000e+000 6.400e+131 ... 6.400e+131 6.400e+131 6.400e+131]\n",
-      " ...\n",
-      " [0.000e+000 0.000e+000 6.400e+131 ...        inf        inf 2.816e+233]\n",
-      " [0.000e+000 0.000e+000 6.400e+131 ...        inf        inf 6.144e+253]\n",
-      " [0.000e+000 0.000e+000 6.400e+131 ... 2.816e+233 6.144e+253 1.536e+255]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb6c1443c8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 49.5947208404541 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 1e-10} is: \n",
-      "[[  32.00000001   16.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [  16.           32.00000001    0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [   0.            0.           32.00000001 ...   32.00000001\n",
-      "    32.00000001   32.00000001]\n",
-      " ...\n",
-      " [   0.            0.           32.00000001 ... 3232.00000222\n",
-      "  3128.00000225 3200.00000239]\n",
-      " [   0.            0.           32.00000001 ... 3128.00000225\n",
-      "  3030.00000237 3092.00000262]\n",
-      " [   0.            0.           32.00000001 ... 3200.00000239\n",
-      "  3092.00000262 3184.00000434]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688e59b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 49.63289785385132 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 1e-09} is: \n",
-      "[[  32.0000001    16.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [  16.           32.0000001     0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [   0.            0.           32.0000001  ...   32.0000001\n",
-      "    32.0000001    32.0000001 ]\n",
-      " ...\n",
-      " [   0.            0.           32.0000001  ... 3232.00002222\n",
-      "  3128.00002248 3200.00002392]\n",
-      " [   0.            0.           32.0000001  ... 3128.00002248\n",
-      "  3030.00002369 3092.00002625]\n",
-      " [   0.            0.           32.0000001  ... 3200.00002392\n",
-      "  3092.00002625 3184.00004341]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688e59b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 49.70455551147461 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 1e-08} is: \n",
-      "[[  32.00000096   16.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [  16.           32.00000104    0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [   0.            0.           32.00000096 ...   32.00000096\n",
-      "    32.00000096   32.00000096]\n",
-      " ...\n",
-      " [   0.            0.           32.00000096 ... 3232.00022216\n",
-      "  3128.00022484 3200.0002392 ]\n",
-      " [   0.            0.           32.00000096 ... 3128.00022484\n",
-      "  3030.00023686 3092.00026246]\n",
-      " [   0.            0.           32.00000096 ... 3200.0002392\n",
-      "  3092.00026246 3184.00043412]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb6c144390>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 49.85604548454285 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 1e-07} is: \n",
-      "[[  32.0000096   16.           0.        ...    0.           0.\n",
-      "     0.       ]\n",
-      " [  16.          32.0000104    0.        ...    0.           0.\n",
-      "     0.       ]\n",
-      " [   0.           0.          32.0000096 ...   32.0000096   32.0000096\n",
-      "    32.0000096]\n",
-      " ...\n",
-      " [   0.           0.          32.0000096 ... 3232.0022216 3128.0022484\n",
-      "  3200.002392 ]\n",
-      " [   0.           0.          32.0000096 ... 3128.0022484 3030.0023686\n",
-      "  3092.0026246]\n",
-      " [   0.           0.          32.0000096 ... 3200.002392  3092.0026246\n",
-      "  3184.0043412]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 49.93108248710632 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 1e-06} is: \n",
-      "[[  32.000096     16.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [  16.           32.000104      0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [   0.            0.           32.000096   ...   32.000096\n",
-      "    32.000096     32.000096  ]\n",
-      " ...\n",
-      " [   0.            0.           32.000096   ... 3232.02221617\n",
-      "  3128.02248416 3200.02392006]\n",
-      " [   0.            0.           32.000096   ... 3128.02248416\n",
-      "  3030.02368618 3092.02624609]\n",
-      " [   0.            0.           32.000096   ... 3200.02392006\n",
-      "  3092.02624609 3184.04341226]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f8358>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 49.449198961257935 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 1e-05} is: \n",
-      "[[  32.00096001   16.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [  16.           32.00104002    0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [   0.            0.           32.00096001 ...   32.00096001\n",
-      "    32.00096001   32.00096001]\n",
-      " ...\n",
-      " [   0.            0.           32.00096001 ... 3232.22217717\n",
-      "  3128.2248565  3200.23920574]\n",
-      " [   0.            0.           32.00096001 ... 3128.2248565\n",
-      "  3030.23687824 3092.26246855]\n",
-      " [   0.            0.           32.00096001 ... 3200.23920574\n",
-      "  3092.26246855 3184.43414602]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688e5208>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 49.37942147254944 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 0.0001} is: \n",
-      "[[  32.00960128   16.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [  16.           32.01040176    0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [   0.            0.           32.00960128 ...   32.00960128\n",
-      "    32.00960128   32.00960128]\n",
-      " ...\n",
-      " [   0.            0.           32.00960128 ... 3234.22331772\n",
-      "  3130.25005023 3202.3925739 ]\n",
-      " [   0.            0.           32.00960128 ... 3130.25005023\n",
-      "  3032.37042487 3094.62545487]\n",
-      " [   0.            0.           32.00960128 ... 3202.3925739\n",
-      "  3094.62545487 3188.34380269]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.683305740356445 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 0.001} is: \n",
-      "[[  32.09612806   16.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [  16.           32.10417616    0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [   0.            0.           32.09612806 ...   32.09612806\n",
-      "    32.09612806   32.09612806]\n",
-      " ...\n",
-      " [   0.            0.           32.09612806 ... 3254.38853506\n",
-      "  3150.64970169 3223.97744677]\n",
-      " [   0.            0.           32.09612806 ... 3150.64970169\n",
-      "  3053.86931114 3118.33161895]\n",
-      " [   0.            0.           32.09612806 ... 3223.97744677\n",
-      "  3118.33161895 3227.67299453]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe2ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 49.749770164489746 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 0.01} is: \n",
-      "[[  32.972864     16.            0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [  16.           33.05776064    0.         ...    0.\n",
-      "     0.            0.        ]\n",
-      " [   0.            0.           32.972864   ...   32.972864\n",
-      "    32.972864     32.972864  ]\n",
-      " ...\n",
-      " [   0.            0.           32.972864   ... 3472.20027986\n",
-      "  3370.10823335 3445.0014973 ]\n",
-      " [   0.            0.           32.972864   ... 3370.10823335\n",
-      "  3286.04208239 3363.15539345]\n",
-      " [   0.            0.           32.972864   ... 3445.0014973\n",
-      "  3363.15539345 3644.95802609]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a630>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 52.6299684047699 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 0.1} is: \n",
-      "[[   42.944         16.             0.         ...     0.\n",
-      "      0.             0.        ]\n",
-      " [   16.            44.3264         0.         ...     0.\n",
-      "      0.             0.        ]\n",
-      " [    0.             0.            42.944      ...    42.944\n",
-      "     42.944         42.944     ]\n",
-      " ...\n",
-      " [    0.             0.            42.944      ...  8346.13431859\n",
-      "   8037.8729408   6232.308736  ]\n",
-      " [    0.             0.            42.944      ...  8037.8729408\n",
-      "   8507.94753363  6732.5824384 ]\n",
-      " [    0.             0.            42.944      ...  6232.308736\n",
-      "   6732.5824384  11086.190464  ]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb6c144390>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 52.260963439941406 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 1.0} is: \n",
-      "[[3.2000000e+02 1.6000000e+01 0.0000000e+00 ... 0.0000000e+00\n",
-      "  0.0000000e+00 0.0000000e+00]\n",
-      " [1.6000000e+01 5.3600000e+02 0.0000000e+00 ... 0.0000000e+00\n",
-      "  0.0000000e+00 0.0000000e+00]\n",
-      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 3.2000000e+02\n",
-      "  3.2000000e+02 3.2000000e+02]\n",
-      " ...\n",
-      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 3.9599184e+07\n",
-      "  1.8790076e+07 1.9904800e+05]\n",
-      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 1.8790076e+07\n",
-      "  4.5132236e+07 5.0194600e+05]\n",
-      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 1.9904800e+05\n",
-      "  5.0194600e+05 4.7488000e+06]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 51.67429780960083 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 10.0} is: \n",
-      "[[7.77920000e+04 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.60000000e+01 8.18672000e+05 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 7.77920000e+04 ... 7.77920000e+04\n",
-      "  7.77920000e+04 7.77920000e+04]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 7.77920000e+04 ... 1.39109795e+16\n",
-      "  7.18668723e+14 4.54391680e+09]\n",
-      " [0.00000000e+00 0.00000000e+00 7.77920000e+04 ... 7.18668723e+14\n",
-      "  1.42558312e+16 9.54906688e+10]\n",
-      " [0.00000000e+00 0.00000000e+00 7.77920000e+04 ... 4.54391680e+09\n",
-      "  9.54906688e+10 2.40390375e+12]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688e59b0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 49.85410976409912 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 100.0} is: \n",
-      "[[6.52896320e+07 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.60000000e+01 6.56177043e+09 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 6.52896320e+07 ... 6.52896320e+07\n",
-      "  6.52896320e+07 6.52896320e+07]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 6.52896320e+07 ... 9.71197172e+25\n",
-      "  4.87507385e+23 2.94958331e+15]\n",
-      " [0.00000000e+00 0.00000000e+00 6.52896320e+07 ... 4.87507385e+23\n",
-      "  9.73625794e+25 6.40475930e+17]\n",
-      " [0.00000000e+00 0.00000000e+00 6.52896320e+07 ... 2.94958331e+15\n",
-      "  6.40475930e+17 1.60897659e+19]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb246377f0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 51.49191212654114 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 1000.0} is: \n",
-      "[[6.41280960e+10 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.60000000e+01 6.41601761e+13 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 6.41280960e+10 ... 6.41280960e+10\n",
-      "  6.41280960e+10 6.41280960e+10]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 6.41280960e+10 ... 9.36859917e+35\n",
-      "  4.68617006e+32 2.82902806e+21]\n",
-      " [0.00000000e+00 0.00000000e+00 6.41280960e+10 ... 4.68617006e+32\n",
-      "  9.37094141e+35 6.16941595e+24]\n",
-      " [0.00000000e+00 0.00000000e+00 6.41280960e+10 ... 2.82902806e+21\n",
-      "  6.16941595e+24 1.54317278e+26]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.46095323562622 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 10000.0} is: \n",
-      "[[6.40128010e+13 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.60000000e+01 6.40160018e+17 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40128010e+13 ... 6.40128010e+13\n",
-      "  6.40128010e+13 6.40128010e+13]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 6.40128010e+13 ... 9.33493322e+45\n",
-      "  4.66765328e+41 2.81729956e+27]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40128010e+13 ... 4.66765328e+41\n",
-      "  9.33516660e+45 6.14653512e+31]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40128010e+13 ... 2.81729956e+27\n",
-      "  6.14653512e+31 1.53671604e+33]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f81d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 49.47657823562622 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 100000.0} is: \n",
-      "[[6.40012800e+16 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.60000000e+01 6.40016000e+21 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40012800e+16 ... 6.40012800e+16\n",
-      "  6.40012800e+16 6.40012800e+16]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 6.40012800e+16 ... 9.33157326e+55\n",
-      "  4.66580529e+50 2.81612992e+33]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40012800e+16 ... 4.66580529e+50\n",
-      "  9.33159658e+55 6.14425345e+38]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40012800e+16 ... 2.81612992e+33\n",
-      "  6.14425345e+38 1.53607159e+40]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468cfd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 49.4469039440155 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 1000000.0} is: \n",
-      "[[6.40001280e+19 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.60000000e+01 6.40001600e+25 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40001280e+19 ... 6.40001280e+19\n",
-      "  6.40001280e+19 6.40001280e+19]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 6.40001280e+19 ... 9.33123732e+65\n",
-      "  4.66562053e+59 2.81601299e+39]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40001280e+19 ... 4.66562053e+59\n",
-      "  9.33123966e+65 6.14402534e+45]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40001280e+19 ... 2.81601299e+39\n",
-      "  6.14402534e+45 1.53600716e+47]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 49.54963159561157 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 10000000.0} is: \n",
-      "[[6.40000128e+22 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.60000000e+01 6.40000160e+29 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40000128e+22 ... 6.40000128e+22\n",
-      "  6.40000128e+22 6.40000128e+22]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 6.40000128e+22 ... 9.33120373e+75\n",
-      "  4.66560205e+68 2.81600130e+45]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40000128e+22 ... 4.66560205e+68\n",
-      "  9.33120397e+75 6.14400253e+52]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40000128e+22 ... 2.81600130e+45\n",
-      "  6.14400253e+52 1.53600072e+54]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2466cb70>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 49.59786868095398 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 100000000.0} is: \n",
-      "[[6.40000013e+25 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.60000000e+01 6.40000016e+33 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40000013e+25 ... 6.40000013e+25\n",
-      "  6.40000013e+25 6.40000013e+25]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 6.40000013e+25 ... 9.33120037e+85\n",
-      "  4.66560021e+77 2.81600013e+51]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40000013e+25 ... 4.66560021e+77\n",
-      "  9.33120040e+85 6.14400025e+59]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40000013e+25 ... 2.81600013e+51\n",
-      "  6.14400025e+59 1.53600007e+61]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe26a0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 50.56888294219971 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 1000000000.0} is: \n",
-      "[[6.40000001e+28 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [1.60000000e+01 6.40000002e+37 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40000001e+28 ... 6.40000001e+28\n",
-      "  6.40000001e+28 6.40000001e+28]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 6.40000001e+28 ... 9.33120004e+95\n",
-      "  4.66560002e+86 2.81600001e+57]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40000001e+28 ... 4.66560002e+86\n",
-      "  9.33120004e+95 6.14400003e+66]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40000001e+28 ... 2.81600001e+57\n",
-      "  6.14400003e+66 1.53600001e+68]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAACjhJREFUeJzt3M+P3HUdx/HnS4o1Gow0aIOASkwvcHBDNuiBmBoSfl0KF4IXG0NSD/AHwAmPXoyJiZLUpKEeBHsh9NAIpBdOIDVpsBiJjRZpLa2KQaOx2vr2sN+GSe26b3Z25rs/no9kMzOf/c7u+9Ntn5nv7ExTVUjSSj4y9gCSNgZjIanFWEhqMRaSWoyFpBZjIall9FgkuS/JW0lOJnli7HlmJcmpJL9McjzJsWFtR5KXk/xmuLx+7DmnkeRAkvNJTkysXXWPWfL94ef+RpI7xpt89ZbZ87eTnBl+1seTPDDxuSeHPb+V5N5xpl6dUWOR5BrgB8D9wG3A15PcNuZMM/a1qlqoqsXh9hPA0araBRwdbm9kzwD3XbG23B7vB3YNH/uAp+c041p7hv/dM8D3hp/1QlUdARj+bj8C3D7c54fDv4ENYexHFncCJ6vqt1X1L+A5YM/IM83THuDgcP0g8OCIs0ytql4B3rtiebk97gF+XEteBT6V5Mb5TLp2ltnzcvYAz1XVhar6HXCSpX8DG8LYsbgJeGfi9ulhbTMq4KUkv0iyb1jbWVVnh+vvAjvHGW2mltvjZv/ZPz6cXh2YOL3c0HseOxZbyV1VdQdLD78fS/LVyU/W0uvuN/Vr77fCHgdPA18EFoCzwHfHHWdtjB2LM8AtE7dvHtY2nao6M1yeB55n6eHnucsPvYfL8+NNODPL7XHT/uyr6lxVXaqq/wA/4oNTjQ2957Fj8TqwK8mtST7K0pM/h0eeac0l+USS6y5fB+4BTrC0173DYXuBF8aZcKaW2+Nh4BvDb0W+Arw/cbqyoV3x3MtDLP2sYWnPjyTZnuRWlp7c/fm851utbWN+86q6mORx4EXgGuBAVb055kwzshN4Pgks/Zn/pKp+luR14FCSR4G3gYdHnHFqSZ4FdgM3JDkNPAV8h6vv8QjwAEtP8v0D+ObcB14Dy+x5d5IFlk65TgHfAqiqN5McAn4FXAQeq6pLY8y9GvEt6pI6xj4NkbRBGAtJLcZCUouxkNRiLCS1zCwWH/bdpBMvgd4y3PPWsFn2PJNYrPLdpJviD/RDcs9bw6bY86weWWz1d5NKm86sXsF5tXfXfXm5gz+a7fUxPs4ns2NLvULMPW8N63nP/+Tv/KsupHPsaC/3Hs7j9sHSH+ZdH/xnQpLm5LU62j52VqchK767rqr2V9ViVS1ey/YZjSFprcwqFlvi3aTSVjKT05At9G5SacuY2XMWw39SemRWX1/SfPkKTkktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLVsm+bOSU4BfwMuARerajHJDuCnwBeAU8DDVfWX6caUNLa1eGTxtapaqKrF4fYTwNGq2gUcHW5L2uBmcRqyBzg4XD8IPDiD7yFpzqaNRQEvJflFkn3D2s6qOjtcfxfYOeX3kLQOTPWcBXBXVZ1J8hng5SS/nvxkVVWSutodh7jsA/gYH59yDEmzNtUji6o6M1yeB54H7gTOJbkRYLg8v8x991fVYlUtXsv2acaQNAerjkWSTyS57vJ14B7gBHAY2Dscthd4YdohJY1vmtOQncDzSS5/nZ9U1c+SvA4cSvIo8Dbw8PRjShrbqmNRVb8FvnSV9T8Dd08zlKT1x1dwSmoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqWXFWCQ5kOR8khMTazuSvJzkN8Pl9cN6knw/yckkbyS5Y5bDS5qfziOLZ4D7rlh7AjhaVbuAo8NtgPuBXcPHPuDptRlT0thWjEVVvQK8d8XyHuDgcP0g8ODE+o9ryavAp5LcuFbDShrPap+z2FlVZ4fr7wI7h+s3Ae9MHHd6WJO0wU39BGdVFVAf9n5J9iU5luTYv7kw7RiSZmy1sTh3+fRiuDw/rJ8Bbpk47uZh7X9U1f6qWqyqxWvZvsoxJM3LamNxGNg7XN8LvDCx/o3htyJfAd6fOF2RtIFtW+mAJM8Cu4EbkpwGngK+AxxK8ijwNvDwcPgR4AHgJPAP4JszmFnSCFaMRVV9fZlP3X2VYwt4bNqhJK0/voJTUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLSvGIsmBJOeTnJhY+3aSM0mODx8PTHzuySQnk7yV5N5ZDS5pvjqPLJ4B7rvK+veqamH4OAKQ5DbgEeD24T4/THLNWg0raTwrxqKqXgHea369PcBzVXWhqn4HnATunGI+SevENM9ZPJ7kjeE05fph7SbgnYljTg9rkja41cbiaeCLwAJwFvjuh/0CSfYlOZbk2L+5sMoxJM3LqmJRVeeq6lJV/Qf4ER+capwBbpk49OZh7WpfY39VLVbV4rVsX80YkuZoVbFIcuPEzYeAy78pOQw8kmR7kluBXcDPpxtR0nqwbaUDkjwL7AZuSHIaeArYnWQBKOAU8C2AqnozySHgV8BF4LGqujSb0SXNU6pq7Bn4ZHbUl3P32GNIW85rdZS/1nvpHOsrOCW1GAtJLcZCUouxkNaBF/9wnBf/cHzsMf4vYyGpZcVfnUqavXs/uzD2CCvykYWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFtIGtu0Ln5vb9zIW0gZ28dTv5/a9jIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGpJVY09A0n+CPwd+NPYs8zZDbjnrWA97/nzVfXpzoHrIhYASY5V1eLYc8yTe94aNsuePQ2R1GIsJLWsp1jsH3uAEbjnrWFT7HndPGchaX1bT48sJK1jxkJSi7GQ1GIsJLUYC0kt/wUTFWjNk6oV2wAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1588>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 52.24024176597595 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 4.0, 'lmda': 10000000000.0} is: \n",
-      "[[6.4000e+031 1.6000e+001 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
-      "  0.0000e+000]\n",
-      " [1.6000e+001 6.4000e+041 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
-      "  0.0000e+000]\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+031 ... 6.4000e+031 6.4000e+031\n",
-      "  6.4000e+031]\n",
-      " ...\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+031 ... 9.3312e+105 4.6656e+095\n",
-      "  2.8160e+063]\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+031 ... 4.6656e+095 9.3312e+105\n",
-      "  6.1440e+073]\n",
-      " [0.0000e+000 0.0000e+000 6.4000e+031 ... 2.8160e+063 6.1440e+073\n",
-      "  1.5360e+075]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 82.40116333961487 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 1e-10} is: \n",
-      "[[1.45000000e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [6.60000000e+01 1.24000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 1.45000000e+02 ... 1.61000000e+02\n",
-      "  1.61000000e+02 1.61000000e+02]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 1.61000000e+02 ... 1.67010000e+04\n",
-      "  1.65970000e+04 1.62110001e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.61000000e+02 ... 1.65970000e+04\n",
-      "  1.65150000e+04 1.61070001e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.61000000e+02 ... 1.62110001e+04\n",
-      "  1.61070001e+04 1.58470001e+04]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24637da0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 60.26471400260925 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 1e-09} is: \n",
-      "[[1.45000001e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [6.60000000e+01 1.24000001e+02 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 1.45000001e+02 ... 1.61000001e+02\n",
-      "  1.61000001e+02 1.61000001e+02]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 1.61000001e+02 ... 1.67010005e+04\n",
-      "  1.65970005e+04 1.62110005e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.61000001e+02 ... 1.65970005e+04\n",
-      "  1.65150005e+04 1.61070006e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.61000001e+02 ... 1.62110005e+04\n",
-      "  1.61070006e+04 1.58470011e+04]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461aeb8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 60.560508012771606 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 1e-08} is: \n",
-      "[[1.45000011e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [6.60000000e+01 1.24000012e+02 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 1.45000011e+02 ... 1.61000011e+02\n",
-      "  1.61000011e+02 1.61000011e+02]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 1.61000011e+02 ... 1.67010048e+04\n",
-      "  1.65970047e+04 1.62110055e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.61000011e+02 ... 1.65970047e+04\n",
-      "  1.65150049e+04 1.61070058e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.61000011e+02 ... 1.62110055e+04\n",
-      "  1.61070058e+04 1.58470105e+04]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1550>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 61.513394832611084 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 1e-07} is: \n",
-      "[[1.45000110e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [6.60000000e+01 1.24000118e+02 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 1.45000110e+02 ... 1.61000110e+02\n",
-      "  1.61000110e+02 1.61000110e+02]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 1.61000110e+02 ... 1.67010478e+04\n",
-      "  1.65970472e+04 1.62110547e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.61000110e+02 ... 1.65970472e+04\n",
-      "  1.65150491e+04 1.61070579e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.61000110e+02 ... 1.62110547e+04\n",
-      "  1.61070579e+04 1.58471053e+04]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468cfd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 59.259434938430786 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 1e-06} is: \n",
-      "[[1.45001104e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [6.60000000e+01 1.24001184e+02 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 1.45001104e+02 ... 1.61001104e+02\n",
-      "  1.61001104e+02 1.61001104e+02]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 1.61001104e+02 ... 1.67014776e+04\n",
-      "  1.65974719e+04 1.62115469e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.61001104e+02 ... 1.65974719e+04\n",
-      "  1.65154913e+04 1.61075786e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.61001104e+02 ... 1.62115469e+04\n",
-      "  1.61075786e+04 1.58480531e+04]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1588>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 59.096699714660645 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 1e-05} is: \n",
-      "[[1.45011040e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [6.60000000e+01 1.24011841e+02 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 1.45011040e+02 ... 1.61011040e+02\n",
-      "  1.61011040e+02 1.61011040e+02]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 1.61011040e+02 ... 1.67057768e+04\n",
-      "  1.66017196e+04 1.62164699e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.61011040e+02 ... 1.66017196e+04\n",
-      "  1.65199140e+04 1.61127872e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.61011040e+02 ... 1.62164699e+04\n",
-      "  1.61127872e+04 1.58575342e+04]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468c8d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 58.009583950042725 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 0.0001} is: \n",
-      "[[1.45110420e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [6.60000000e+01 1.24118460e+02 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 1.45110420e+02 ... 1.61110420e+02\n",
-      "  1.61110420e+02 1.61110420e+02]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 1.61110420e+02 ... 1.67488609e+04\n",
-      "  1.66442755e+04 1.62657545e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.61110420e+02 ... 1.66442755e+04\n",
-      "  1.65642284e+04 1.61649561e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.61110420e+02 ... 1.62657545e+04\n",
-      "  1.61649561e+04 1.59526266e+04]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb6c1443c8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 58.62494492530823 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 0.001} is: \n",
-      "[[1.46106049e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [6.60000000e+01 1.25190017e+02 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 1.46106049e+02 ... 1.62106049e+02\n",
-      "  1.62106049e+02 1.62106049e+02]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 1.62106049e+02 ... 1.71890463e+04\n",
-      "  1.70778052e+04 1.67641098e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.62106049e+02 ... 1.70778052e+04\n",
-      "  1.70162400e+04 1.66950729e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.62106049e+02 ... 1.67641098e+04\n",
-      "  1.66950729e+04 1.69322250e+04]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468cfd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 57.8918981552124 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 0.01} is: \n",
-      "[[1.56246080e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [6.60000000e+01 1.36457170e+02 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 1.56246080e+02 ... 1.72246080e+02\n",
-      "  1.72246080e+02 1.72246080e+02]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 1.72246080e+02 ... 2.26768195e+04\n",
-      "  2.23045489e+04 2.23285833e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.72246080e+02 ... 2.23045489e+04\n",
-      "  2.25500437e+04 2.29275891e+04]\n",
-      " [2.00000000e+01 2.00000000e+01 1.72246080e+02 ... 2.23285833e+04\n",
-      "  2.29275891e+04 3.01003948e+04]]\n"
-     ]
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468c8d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 58.05191445350647 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 0.1} is: \n",
-      "[[2.77160000e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [6.60000000e+01 3.22271949e+02 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 2.77160000e+02 ... 2.93160000e+02\n",
-      "  2.93160000e+02 2.93160000e+02]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 2.93160000e+02 ... 6.95075231e+05\n",
-      "  3.75446134e+05 1.77422769e+05]\n",
-      " [2.00000000e+01 2.00000000e+01 2.93160000e+02 ... 3.75446134e+05\n",
-      "  6.06927235e+05 3.37486233e+05]\n",
-      " [2.00000000e+01 2.00000000e+01 2.93160000e+02 ... 1.77422769e+05\n",
-      "  3.37486233e+05 1.90218793e+06]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461aeb8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 58.13757634162903 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 1.0} is: \n",
-      "[[4.57700000e+03 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [6.60000000e+01 8.91640000e+04 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.57700000e+03 ... 4.59300000e+03\n",
-      "  4.59300000e+03 4.59300000e+03]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.59300000e+03 ... 2.01159621e+13\n",
-      "  3.10057363e+11 2.42784376e+09]\n",
-      " [2.00000000e+01 2.00000000e+01 4.59300000e+03 ... 3.10057363e+11\n",
-      "  4.70005886e+13 3.01441455e+10]\n",
-      " [2.00000000e+01 2.00000000e+01 4.59300000e+03 ... 2.42784376e+09\n",
-      "  3.01441455e+10 4.04190794e+12]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 59.23965072631836 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 10.0} is: \n",
-      "[[1.49598500e+06 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [6.60000000e+01 3.44783080e+10 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 1.49598500e+06 ... 1.49600100e+06\n",
-      "  1.49600100e+06 1.49600100e+06]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 1.49600100e+06 ... 1.13768199e+29\n",
-      "  3.31210879e+22 9.96117761e+18]\n",
-      " [2.00000000e+01 2.00000000e+01 1.49600100e+06 ... 3.31210879e+22\n",
-      "  4.45961208e+29 8.59201597e+20]\n",
-      " [2.00000000e+01 2.00000000e+01 1.49600100e+06 ... 9.96117761e+18\n",
-      "  8.59201597e+20 4.16855423e+24]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 58.99919033050537 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 100.0} is: \n",
-      "[[1.30059054e+09 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [6.60000000e+01 2.16311217e+17 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 1.30059054e+09 ... 1.30059056e+09\n",
-      "  1.30059056e+09 1.30059056e+09]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 1.30059056e+09 ... 4.75063841e+47\n",
-      "  6.90580493e+35 4.43539095e+30]\n",
-      " [2.00000000e+01 2.00000000e+01 1.30059056e+09 ... 6.90580493e+35\n",
-      "  1.89563663e+48 4.03114835e+33]\n",
-      " [2.00000000e+01 2.00000000e+01 1.30059056e+09 ... 4.43539095e+30\n",
-      "  4.03114835e+33 1.44634079e+39]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1c50>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 57.70133352279663 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 1000.0} is: \n",
-      "[[1.28204910e+12 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [6.60000000e+01 2.05928848e+24 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 1.28204910e+12 ... 1.28204910e+12\n",
-      "  1.28204910e+12 1.28204910e+12]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 1.28204910e+12 ... 4.34301799e+66\n",
-      "  5.56520941e+49 4.06947164e+42]\n",
-      " [2.00000000e+01 2.00000000e+01 1.28204910e+12 ... 5.56520941e+49\n",
-      "  1.73677414e+67 3.72852519e+46]\n",
-      " [2.00000000e+01 2.00000000e+01 1.28204910e+12 ... 4.06947164e+42\n",
-      "  3.72852519e+46 1.29135037e+54]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf98>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 58.04664945602417 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 10000.0} is: \n",
-      "[[1.28020481e+15 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [6.60000000e+01 2.04912664e+31 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 1.28020481e+15 ... 1.28020481e+15\n",
-      "  1.28020481e+15 1.28020481e+15]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 1.28020481e+15 ... 4.30411880e+85\n",
-      "  5.44017562e+63 4.03435025e+54]\n",
-      " [2.00000000e+01 2.00000000e+01 1.28020481e+15 ... 5.44017562e+63\n",
-      "  1.72160449e+86 3.69944820e+59]\n",
-      " [2.00000000e+01 2.00000000e+01 1.28020481e+15 ... 4.03435025e+54\n",
-      "  3.69944820e+59 1.27668843e+69]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 57.89458084106445 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 100000.0} is: \n",
-      "[[1.28002048e+018 6.60000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
-      "  2.00000000e+001 2.00000000e+001]\n",
-      " [6.60000000e+001 2.04811264e+038 4.00000000e+000 ... 2.00000000e+001\n",
-      "  2.00000000e+001 2.00000000e+001]\n",
-      " [4.00000000e+000 4.00000000e+000 1.28002048e+018 ... 1.28002048e+018\n",
-      "  1.28002048e+018 1.28002048e+018]\n",
-      " ...\n",
-      " [2.00000000e+001 2.00000000e+001 1.28002048e+018 ... 4.30024696e+104\n",
-      "  5.42775940e+077 4.03085248e+066]\n",
-      " [2.00000000e+001 2.00000000e+001 1.28002048e+018 ... 5.42775940e+077\n",
-      "  1.72009448e+105 3.69655206e+072]\n",
-      " [2.00000000e+001 2.00000000e+001 1.28002048e+018 ... 4.03085248e+066\n",
-      "  3.69655206e+072 1.27523034e+084]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a630>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 58.90051460266113 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 1000000.0} is: \n",
-      "[[1.28000205e+021 6.60000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
-      "  2.00000000e+001 2.00000000e+001]\n",
-      " [6.60000000e+001 2.04801126e+045 4.00000000e+000 ... 2.00000000e+001\n",
-      "  2.00000000e+001 2.00000000e+001]\n",
-      " [4.00000000e+000 4.00000000e+000 1.28000205e+021 ... 1.28000205e+021\n",
-      "  1.28000205e+021 1.28000205e+021]\n",
-      " ...\n",
-      " [2.00000000e+001 2.00000000e+001 1.28000205e+021 ... 4.29985996e+123\n",
-      "  5.42651865e+091 4.03050285e+078]\n",
-      " [2.00000000e+001 2.00000000e+001 1.28000205e+021 ... 5.42651865e+091\n",
-      "  1.71994355e+124 3.69626257e+085]\n",
-      " [2.00000000e+001 2.00000000e+001 1.28000205e+021 ... 4.03050285e+078\n",
-      "  3.69626257e+085 1.27508461e+099]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461aeb8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "../pygraph/kernels/treePatternKernel.py:150: RuntimeWarning: overflow encountered in double_scalars\n",
-      "  kh_tmp *= lmda * all_kh[str(pair[0]) + '.' + str(pair[1])]\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 57.89000582695007 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 10000000.0} is: \n",
-      "[[1.28000020e+024 6.60000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
-      "  2.00000000e+001 2.00000000e+001]\n",
-      " [6.60000000e+001 2.04800113e+052 4.00000000e+000 ... 2.00000000e+001\n",
-      "  2.00000000e+001 2.00000000e+001]\n",
-      " [4.00000000e+000 4.00000000e+000 1.28000020e+024 ... 1.28000020e+024\n",
-      "  1.28000020e+024 1.28000020e+024]\n",
-      " ...\n",
-      " [2.00000000e+001 2.00000000e+001 1.28000020e+024 ... 4.29982126e+142\n",
-      "  5.42639459e+105 4.03046788e+090]\n",
-      " [2.00000000e+001 2.00000000e+001 1.28000020e+024 ... 5.42639459e+105\n",
-      "  1.71992846e+143 3.69623362e+098]\n",
-      " [2.00000000e+001 2.00000000e+001 1.28000020e+024 ... 4.03046788e+090\n",
-      "  3.69623362e+098 1.27507004e+114]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb6c144390>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 61.51721000671387 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 100000000.0} is: \n",
-      "[[1.28000002e+027 6.60000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
-      "  2.00000000e+001 2.00000000e+001]\n",
-      " [6.60000000e+001 2.04800011e+059 4.00000000e+000 ... 2.00000000e+001\n",
-      "  2.00000000e+001 2.00000000e+001]\n",
-      " [4.00000000e+000 4.00000000e+000 1.28000002e+027 ... 1.28000002e+027\n",
-      "  1.28000002e+027 1.28000002e+027]\n",
-      " ...\n",
-      " [2.00000000e+001 2.00000000e+001 1.28000002e+027 ... 4.29981739e+161\n",
-      "  5.42638218e+119 4.03046439e+102]\n",
-      " [2.00000000e+001 2.00000000e+001 1.28000002e+027 ... 5.42638218e+119\n",
-      "  1.71992695e+162 3.69623072e+111]\n",
-      " [2.00000000e+001 2.00000000e+001 1.28000002e+027 ... 4.03046439e+102\n",
-      "  3.69623072e+111 1.27506858e+129]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb65cd1588>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 60.46738958358765 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 1000000000.0} is: \n",
-      "[[1.28000000e+030 6.60000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
-      "  2.00000000e+001 2.00000000e+001]\n",
-      " [6.60000000e+001 2.04800001e+066 4.00000000e+000 ... 2.00000000e+001\n",
-      "  2.00000000e+001 2.00000000e+001]\n",
-      " [4.00000000e+000 4.00000000e+000 1.28000000e+030 ... 1.28000000e+030\n",
-      "  1.28000000e+030 1.28000000e+030]\n",
-      " ...\n",
-      " [2.00000000e+001 2.00000000e+001 1.28000000e+030 ... 4.29981700e+180\n",
-      "  5.42638094e+133 4.03046404e+114]\n",
-      " [2.00000000e+001 2.00000000e+001 1.28000000e+030 ... 5.42638094e+133\n",
-      "  1.71992680e+181 3.69623043e+124]\n",
-      " [2.00000000e+001 2.00000000e+001 1.28000000e+030 ... 4.03046404e+114\n",
-      "  3.69623043e+124 1.27506843e+144]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb68902ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 58.43429613113403 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'untiln', 'h': 5.0, 'lmda': 10000000000.0} is: \n",
-      "[[1.28000000e+033 6.60000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
-      "  2.00000000e+001 2.00000000e+001]\n",
-      " [6.60000000e+001 2.04800000e+073 4.00000000e+000 ... 2.00000000e+001\n",
-      "  2.00000000e+001 2.00000000e+001]\n",
-      " [4.00000000e+000 4.00000000e+000 1.28000000e+033 ... 1.28000000e+033\n",
-      "  1.28000000e+033 1.28000000e+033]\n",
-      " ...\n",
-      " [2.00000000e+001 2.00000000e+001 1.28000000e+033 ... 4.29981696e+199\n",
-      "  5.42638081e+147 4.03046400e+126]\n",
-      " [2.00000000e+001 2.00000000e+001 1.28000000e+033 ... 5.42638081e+147\n",
-      "  1.71992679e+200 3.69623040e+137]\n",
-      " [2.00000000e+001 2.00000000e+001 1.28000000e+033 ... 4.03046400e+126\n",
-      "  3.69623040e+137 1.27506842e+159]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe26a0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 53.51155614852905 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 1e-10} is: \n",
-      "[[8.0000e-39 2.4000e-39 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
-      " [2.4000e-39 5.2000e-39 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-39 ... 8.0000e-39 8.0000e-39 8.0000e-39]\n",
-      " ...\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-39 ... 1.2052e-36 1.2052e-36 1.1662e-36]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-39 ... 1.2052e-36 1.2068e-36 1.1666e-36]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-39 ... 1.1662e-36 1.1666e-36 1.1376e-36]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb5d7e25c0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 53.128520250320435 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 1e-09} is: \n",
-      "[[8.0000e-35 2.4000e-35 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
-      " [2.4000e-35 5.2000e-35 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-35 ... 8.0000e-35 8.0000e-35 8.0000e-35]\n",
-      " ...\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-35 ... 1.2052e-32 1.2052e-32 1.1662e-32]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-35 ... 1.2052e-32 1.2068e-32 1.1666e-32]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-35 ... 1.1662e-32 1.1666e-32 1.1376e-32]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb6c1443c8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 51.308215856552124 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 1e-08} is: \n",
-      "[[8.0000e-31 2.4000e-31 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
-      " [2.4000e-31 5.2000e-31 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-31 ... 8.0000e-31 8.0000e-31 8.0000e-31]\n",
-      " ...\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-31 ... 1.2052e-28 1.2052e-28 1.1662e-28]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-31 ... 1.2052e-28 1.2068e-28 1.1666e-28]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-31 ... 1.1662e-28 1.1666e-28 1.1376e-28]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1fd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 51.26672148704529 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 1e-07} is: \n",
-      "[[8.0000e-27 2.4000e-27 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
-      " [2.4000e-27 5.2000e-27 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-27 ... 8.0000e-27 8.0000e-27 8.0000e-27]\n",
-      " ...\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-27 ... 1.2052e-24 1.2052e-24 1.1662e-24]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-27 ... 1.2052e-24 1.2068e-24 1.1666e-24]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-27 ... 1.1662e-24 1.1666e-24 1.1376e-24]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe2ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 51.09047985076904 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 1e-06} is: \n",
-      "[[8.0000e-23 2.4000e-23 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
-      " [2.4000e-23 5.2000e-23 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-23 ... 8.0000e-23 8.0000e-23 8.0000e-23]\n",
-      " ...\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-23 ... 1.2052e-20 1.2052e-20 1.1662e-20]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-23 ... 1.2052e-20 1.2068e-20 1.1666e-20]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-23 ... 1.1662e-20 1.1666e-20 1.1376e-20]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256e1c50>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 51.712746143341064 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 1e-05} is: \n",
-      "[[8.0000e-19 2.4000e-19 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
-      " [2.4000e-19 5.2000e-19 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-19 ... 8.0000e-19 8.0000e-19 8.0000e-19]\n",
-      " ...\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-19 ... 1.2052e-16 1.2052e-16 1.1662e-16]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-19 ... 1.2052e-16 1.2068e-16 1.1666e-16]\n",
-      " [0.0000e+00 0.0000e+00 8.0000e-19 ... 1.1662e-16 1.1666e-16 1.1376e-16]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb68902ac8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 53.57017707824707 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 0.0001} is: \n",
-      "[[8.00000006e-15 2.40000000e-15 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [2.40000000e-15 5.20000004e-15 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 8.00000006e-15 ... 8.00000006e-15\n",
-      "  8.00000006e-15 8.00000006e-15]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 8.00000006e-15 ... 1.20520001e-12\n",
-      "  1.20520001e-12 1.16620001e-12]\n",
-      " [0.00000000e+00 0.00000000e+00 8.00000006e-15 ... 1.20520001e-12\n",
-      "  1.20680001e-12 1.16660001e-12]\n",
-      " [0.00000000e+00 0.00000000e+00 8.00000006e-15 ... 1.16620001e-12\n",
-      "  1.16660001e-12 1.13760001e-12]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688e5208>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 53.36650323867798 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 0.001} is: \n",
-      "[[8.00000640e-11 2.40000000e-11 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [2.40000000e-11 5.20000400e-11 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 8.00000640e-11 ... 8.00000640e-11\n",
-      "  8.00000640e-11 8.00000640e-11]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 8.00000640e-11 ... 1.20520111e-08\n",
-      "  1.20520114e-08 1.16620086e-08]\n",
-      " [0.00000000e+00 0.00000000e+00 8.00000640e-11 ... 1.20520114e-08\n",
-      "  1.20680118e-08 1.16660090e-08]\n",
-      " [0.00000000e+00 0.00000000e+00 8.00000640e-11 ... 1.16620086e-08\n",
-      "  1.16660090e-08 1.13760101e-08]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468cfd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 53.98498606681824 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 0.01} is: \n",
-      "[[8.00064002e-07 2.40000000e-07 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [2.40000000e-07 5.20040005e-07 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 8.00064002e-07 ... 8.00064002e-07\n",
-      "  8.00064002e-07 8.00064002e-07]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 8.00064002e-07 ... 1.20531122e-04\n",
-      "  1.20531398e-04 1.16628618e-04]\n",
-      " [0.00000000e+00 0.00000000e+00 8.00064002e-07 ... 1.20531398e-04\n",
-      "  1.20691794e-04 1.16669014e-04]\n",
-      " [0.00000000e+00 0.00000000e+00 8.00064002e-07 ... 1.16628618e-04\n",
-      "  1.16669014e-04 1.13770133e-04]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256f2940>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 53.3620331287384 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 0.1} is: \n",
-      "[[0.00806419 0.0024     0.         ... 0.         0.         0.        ]\n",
-      " [0.0024     0.00524049 0.         ... 0.         0.         0.        ]\n",
-      " [0.         0.         0.00806419 ... 0.00806419 0.00806419 0.00806419]\n",
-      " ...\n",
-      " [0.         0.         0.00806419 ... 1.21651795 1.21679544 1.17498286]\n",
-      " [0.         0.         0.00806419 ... 1.21679544 1.21880968 1.17581221]\n",
-      " [0.         0.         0.00806419 ... 1.17498286 1.17581221 1.14809156]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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ABoQBCP72qidy/UGrU6S8NtnXbBvGbCU0RvEomMoGKscRHNOZ4dl1GTiOxyZVNs8rJOMAbHLAfJ+EmJm1C0Loe1Dfl6Xsk/ttz0vzmRSfWQV/hBWu8m4qi30VkDsMSxEToDiM6SGm2YGJZcFDv9+ysCsDIJZF22bzVs9b39WyiCvLNo9nr2URUYjPxXHEsSlCMK2MfV88sAXaMji41h1lWcCiJYF0jH2ozGJ+7RwZSHuBO9Ax5wPLHFVN/h7YC/fecSlsZqGq9loWKQDbNgJl9wE0a4Eua/AdyyzeS/YB7jVYFm4xz1aQZo7q+k6WBc1n4G1dWhbDe5AN2ZFDuIvbLAvmQlGUq3P5+6MtC93Ppua2XXoRdlb3V2RZ7GAUyO31UveXWttrNOnXvdiSuNsrsCzKF3s4GONJRDF7v83ywpZF12Ush4297Ds3OXDEU/C2e/WWxdq41ObZu5Nl0XUpM5T2v4NlccqGnOQkJzlK3i7L4pYS9YS7WC6PKlG3xKyq9auLCzGlh6EMhgIHV8TdcZTuClDFHL6Y91XMl/urq90fp4K3PefbWxy35//4meoKOKbk2BGoQsaRHIisV5fn4H5A2GwOzIVBzRa8IEdmi/YB42rrepiqVosRCAxqxP0Ltjp03ymOSWoU45jcCwvwqqrkziXcgg/GgpAMi3twCf/kWbbQ9mWPCsviUJbkgIWsEsfmFmfJjfCPv4znsdXavPssxe00n4nbfE8u2bdLWdwiYia/WDpIH8B9VXl3GEj5PyBpubjthY59n3HsE2vqHiCvzX+6vN8doL8vXYrU424qUOpjXucYpunQSXo2sCiM10V+E7LyxB44wVEyDJJWvac/8XYpi9tegBQTOG6i9vquw1BAie8rRepVHxpzjtcht9HK7/jI03nds43H8fUpunTSA+OaxkGAvUHqVzIeDb4S7SqtfbGc4Z4v7n2EQ+ZZuY84V2SX7ipvmbKw2Yz95DfcdUWfhoKQRg+jRTcxi6DmoHU9EmuW5thnM9lf4dSrTYyM+52cv2ubXBOx2YAWCyCayCEGyKpHj8Q10Wg8IlQ7ku7wdmsIb3rQ+RkQGCG6L+78DLztMmGLZkO2HWg+SxF3OWl8AJom1yMAEqGvKmDIdRUJgqwZh3gdCieuPv4K0OciKQBi9lq8ytkSvN7KPTGRdYxjCSoL2cynxTzzUDR1NvG7XAsjA3CJpAUAaNaCux687VB99FHct4pB31C6Mou5jN2a2SEAROBhADUN2MCmabEA2gb85FkaF7UtePSguirh2q4qtul8hidP4f7kT8F9eZ3HX1VA14PPFrKvUSis90fHPXrQMCJcxH0/fWzAWLkcgOZzoK7AN6s0x/VP/gTGjy9Rf/9ZcXwyWRzW8zgHMMNte/C8zXPwrfy8PE9OAc6TnOQkR8nbZVkcKwXgKqf+snXhy5TjbaAsDfz1fYQG7/GX9/3OsiuZ1FmBPDVFPfIV59ViGHJ5sPfAZlu4Abp6sLIg2XiC9wjW4kk/4jLd1/cFAjKda/obO+71prAIEhYABmvAq0SJR2YeWc+fuELUz44w9skc2RRsct+UOWqyD3sPVsuwynEWHg3F4jDIWG3VaYjzFCsui4LBbQeMZgxqGYUAtnBruXjBZCiVgN6fcUT15bVwSgCJzwJdl2ILBc1jtKCornN17+jhNBWtoDhy2boiAg83CROirg9fXaNO9yxiYCpXuuq26tQLBwk25rW/Q8zl3VQWViIa0frv4oLc4Rgul0yXbQcpIvfub4AVFG/22AZMhEjvTgElMcwUUAUUbs0rFzP2VL6t26sqvphZQVMAmCgDvaZjV3dMlc6dh1NC6YXv0gFstjsWTEGt0H4lGiJxaav4UiU31sk8A/cPVupzEj8raVK+TobSKuRriP9XlUDSLYgqOKByIJ/32Ts2cuAqnqeaHNfOETQG82LydiuLQy9FVSFxZmpvzchHkX6qCMg9XBOAxCgApIIxWi5kJdCYQi9+oPTTGNNn1I3EDLSs+WYFd36WUHR6Lro4l9XFWiazmSADAVmJ1H/tOpCW13/+hfx+uQCv1hGiO+T4xnoNalvQYp78fV2haD4T3zZKuLoGtY3EObTDmkEaImSiWB9XK/fwQeaOVIuibQpUJT84B12tQE0DzLL/i36Q1Xpai1NVcGdL8KBkxG2eW02HmhWXxzGRAdF8Dt5uhejlUuYIbSP3chhzOTyAcLEAbePYLYr18hykvrrGJyoHujgHz9t8rqaRuIce13JU1LXENHRbnM/w+WP0P/ERms9yzCI0FWjdwT+QuBgNPmVpwzw+N62kZl3vQd2A8ZHELNp/GrJFYheO8yXQNnBPrhJamH/oQ2x+9AKLf9aKwgEQli3cqssxoSYSMtcxZnHTIZzP0mXx6viYxdutLA7JvnTgoRThgQxLQiAyi0UxjmJW0yS6bc3/EOR4w5C1tEaop+fph0S6klbnccy/8x4YtZgtgDRTo4dVyK66IXZlURckuQDxJe4nmRjvwX3cX7+zrkAwVa6JN6PPqTmLnLSW23or82VhxVohbODIbN0Q/Q4QpUFO5lEL8CwOxAQ4QRRdA87BUB17CMKRoTD0tQN1Q7IU09x4ub8C/TcpyH4AIStF5l7+Hr3cKxvgnGxLszEMqK870CbCyCsHjDVo28Ol+57nnIdItReVHIUADCNqU6iWqBMNSpY2ndSuGMSmu9mifToDmUpaFwJo2+cEQbSwSBeHbQ9nnml6L2pDDnVWgpiOdvVicgUTUyr5Vrq8PV1Z9GYls75pQTSmlR/rtWRDdB9AMgdeMghppScnq2FK98VztU18kE0qsG1yVoKDrGSAnH8xF+aom3hzm0auh0heJH24xjFbJLY+BmIBWMtC2Zo4hPwbW+VJlLMnmjKcz4A+uxFE0Qevcs0Jny2k4nEYU2SdfJC/TQYrKd54rTpHZK0RvYapZaHmc+QE5b5PVhDPGlAQJc9qZQDgs1g/UVfgOp5r8CnjwMu5cGPGa8OsRTifgyJ/Jjkn9yFaFoVdq5aF/q39O24aDI8WaKNFg8ohLBo4AEEtiz7Og2fwQubbz+IcBYbrRoyXcm2zpzNRLnUFGnImg2eNPD9RcQJiSW2/MsPZepGGGeY1XFVJ6iJkywK1KAvnXGlZGGa158kpG3KSk5zkKKHXDsTZI5f0Af8Z+jeLbRbeDaCk1bO5fXIpTrCXVu+ApCZDU4krmpvN9tLqhfW6jKXsq3idHv8Iwho153X1LJrQYOJiEJUUcNbC2ANoKoKi+6p1zfZUKXnLGPdWfZq4ScGRARyklwub7a71uMOl6lImwc33dJh3e9Y7mroh2eVMtIWm8Y9mFw6RFd8qHODOz8tszpS9XcXOl+0bMgwpZpVKHYiy20UEf7PaIex1i4VYjlNg2KFivj20er87/DauwuOjIuZvrxtym1gMPxHYu6JhbLphB15kwLghcpD922ezAvFGJGXFRxH2GuLbIqMAlHwN+nddy7nUHI9mP4/KOxEluiRkeCdeKmHvYr47NvlBTlkq+U8/ZFAWhzT+FMQdht1SaSC5Kc7foSPZOAiIanqs2hAjx3mlusrjCkFSi5U8I4njchzlvtQVENOeTtO+tqw9jdmV22wrgA8fZdJccgIk226zm8k5rZwWuqaRMbSNxLeUG3S9zbGGKscbnAIMDWEvXZwDDy7g9DdRuB+SW26zL7zt3k/C3lSWvA/ebbEEWpLrkaPEx9DqTYhNtK9FEYCMXaV4Ehs4SjQwacbLVRUhtxGPoMcbOQf4dBVu22JFLI71Cq3BFJRN14Go7EJO5TU1MESchVoBEWdB3mcC4yCA6YSkVUVK41HW1s7YNGthcBaFYlP0Z5A4hezjRZGNosyKgG5dA2OVg7/3lWE0aMsYiB3Hoq1ELsJTzEok2u0kYKmoS9ZCPqKcFTnUE9Z7UD/krBgQFaYHK0XDXTvV3yJvrbIAcNicsnURh7Ieh3guVOyqEVxKjybLwAKpJsc9qn3hvhZ79qG01oWjDODSwKkyaCcQmBnvMLy69oXbCSWefanVokv8pAaApRmZqgI503hI58i4Iopr2MfKdWvfEMvencZni+ZCGqe1pGzWJgVJfQB8X8DmhRrxHn1Drq7LmiDFReyDvmuvW7V4dV+dK31ubD8T5xA22x03hG9WKYtXAOlMW8QdlnM+tS88yUlO8orl7bYsDpj9VBmIryI41cQHyljFgZjFtHIvtddrcopRYxRJNN14dJOhcjVBPQm82fM3NUgh08hBXJqQtOpqRPftov6cmEURa4lj34k7xPgKFdBug3VRX1vHEa+naDlIDu6OTYYUSLdj7djWgDF1m+bBB5C6RYajgkhg4VTXQEydujbcL2bx4LKAe1PTiGswbTI0hXtHV5RDyKC51Ub2rUwTIkdwYb4bszg/A11egNYb4+IRDsG9qR/ez5iFrTIFkF96V5Vmf9zO3oNNhoDqOr0MCVVpeSA1HqA3X79TgM4hDk6DPkznanf5JYtqVRVrHmvdho5FEXjPY/eON5vaNmcggPwwW05K53Z5KXvk4FdllJKpsN0hyNHjpoyHuCvaJEcl/X5fuz7tQwpkZGLbgqqsUJOrMIU3M4N8XQC1dDsMiE4qRkcABjQXgqncDRkxqvtXVXK9UoMk70GLRXbJlAXd+3RcrSCmthWQWXIXRXmnzmhAWRauc6B/jxLv0L/5+npvzM1dnqeFqjjuMOaaGQBc1yXfRVLmBHp4CVzf5MArAFwdHzt6e5XFLaIvkP2cHoi00x4wllmJXVvCXGk+E78zTqQte7fn0v9TbCGWtU/Rk242i4VL5sZPSsiLEnUF+cSHmeYzYBPyy2zPV9eg2Sz78AreMiXwAOQhig95ygLElB5FJZtK8jdbySRcLHLfVV3BFJSlf58tJeqvQUK9nnGUF2zfw67zYa4Fi7lA4oF8nKmiqGvQ0Mt16xxpBiT4TGEAgM4WRXk2ID45OQf0PahtEUxsgZYLUNNIUR6Q4fjjKOeo8zhIsxPxxaTZTKyCoQc+fAh6FkvfSepVqOsFog3sL1F3MbvUDwkwBgDU7Z8/WiyEcXy9SfNDDy7gv/Kg4EvjeSsIzjR/Crl3Ur7ODLaguMfvaysAWyRTUNgrUtOIoxjJN9iDGDwjR8bdyC+Emsv5fBNUJrmsKLRDdt/LC+qidtdVVZGFNi1rEJZsumzD+4y8TOzgERVqUKMAJGjWRDSfyUQAkJXOPggxNUcccjrTZBTYpmqJpDnPPNecUKVWV52QlQDkwY6sSwV/BjkJ0O1z+wzSMs1d22YXyr5Etpt828qq60NWeLM2QbitsuKzhSgGIxSDfASIcroxyno+l/mJLgTNWkF5DqO8WOnAkq7muko1GLwQZYHtFuODBere4CzqKtZzxFRvn5VFmMXFqJEiMLdt4LoB/lLuf/XlLKFMrfByDm4bgWorCvVsge6DGRZXph7ofCYwc4Xc64LXVOBZhQpAOLMIzuMti1OA8yQnOclR8tYiOHfEMmdZyvkDgcwUs3A5/agxi2lHMvvdc/uG1A1sJy7pdF4jbDs55oQ/oJBbYhaJeekeMYsEvnGuDNwOQzbr03mHHCAM2Q3R5jopdlFM/TRmMXuhmAVMzGJnG5X3JZ3XIiKLmIW13NpdXE4Rs6h2YhYwMYtUTcxBrEWDF0kr9aAVqrGb2TCKxWLRn/F8ycqzboXGG2y8yufaHX52tT9mcX6Wnynb9+X8DHx9nXc8FLMgkjjMZlNYz//L57+OZ8Nn7xmCM/IBACiyD0UpuulmTnHSigZAkSuAXMhoQA1unZ8VkWL/VI4JoDiXNqJJsYHVCu7yIuW0E03fxbmY87bCz5SQh6vr7BpstlIaDiCY8YSblcQuIpUeAClbXyykpF4rNlXJmUI1Oe5GYhtdl4JavFpn14xDHs/1DcAM98EjU/q+3w3BgwvQs2sp5rJuSD9IkHkPkC7NB5Cum86W+UVtmuTvA8bPryNF3Xab79khN+TyDG4zwYmoG7LZAos5wueP85geXAqt3hfCkk0PLpMbEi4WcFcxYM4MjlSAbi1KgRczme8vn2H42ieoP49s7tENcestwsOIyrzVDRlLN+SPsNcNwccfgpsa7iYH8flsgfWPXmCXDsqjAAAgAElEQVTxzYkbctPtdUPGBzM0X6zhz+MzEhj87HgV8O4oixARjwadBiA345k0Z1HAT9EAyNYoxBVGX+5wsyoBK/aYxbkiCjDGKHgYCx9bV9VwfbNjWfA4Jj4E7vs8Hu8RnjzN1xnHw+MAbCL9/Cak73mzSaXMVqhy6eFI51tvSstk0mQmVWH2sUHPl0/2WhZsLYuuu7NlYecjlXlvtnmb7aRm5lzTlexDfokOWRY3K4TbLIubVWFZhGhxJYXlPei6RvAB9KxJ/Wv1GOk3AOhGLIuwWqMOYceyCOMIUgi4uU/ugGVRPX6OZcEyhhCZvACAnrVYXq0Ky8I9Li0LMhbb7FPhNqlskL3fVeyH5N1RFi9Dbil7v/8hTbryQDn8KxPjThyET1PZvLhwoaYv26vu0H6b7CtS07+Z92YIXt1QSLAaMS3LJmCYePQpKrfq+GzCSxvffc9p66fuIW+XsjimydDZWdlk6ACsWx58AU9pS8Hq/AypyZCm7KzVAADPaV+YuR115XO5nSB8bjKk2t4ew/uyXsAQ0UxX4+c2Rt5TL8DMuy6A96mICciWRTqfuk3nZ9JkyFhi6bjxOhOHyDjevX1hv4s1KMSS/RTzoFmR5rlVodR1+1tAFAc0UHKLowAyJ0qI12HIhdiXWRqOxXTu/Azhy6cF2E0OyZmU5pj2hQbkt3fY2+ieLRbJVQtPn4E2m13IwN4mQw5OOUbt4nGCe5/kJCd52fJ2WRbWoigwFXmFCasV3HxeAHxCP0R4tVb2eSjPBdVZH9qWgtWjR7KvdtC+OJeAoXaz/vJpavdmI+DsvcCOTddrd3EuPjmyRVF/9ZOd5ro0nwMaqLy+yZiL9UbQdQDC974PAHCPHiaeTu76FEhUzk9qmoTcS+Cp+Ry0NExZz64kELvdwp0pL0gsx444Cx2DtsKrv/ZjuXu4jr1pJNAYV6Hw8BzV05siig9ASq03G7Mii3vEPsBdXuS5VkxJXQm8GQZnUVfCuB3jBW45B6+34Otr1D/+I3JdEbOheIiEfn2wRLWWLJZycFKEVNOmk6Dk50/yeB9egGct6PuP47hmGWfR1FIurtLU4FkDdxNjXTrP3/sM/b/xr2D+Pbn/XBG4rVFdbzF+KFam6w1Cdx7vYyuNlV3nUW1H9B/I8Rb/+DPJsEysLH50CW5r0OOrHHf5+r+I66+d4fz/y71Q/FmD+qZP189NfH+aCoEZ1U0Hb5myfv8wf8lU3i5lcaSwD9nc5Ii7t2S9jrIpdoiDU4OLaoZ1nbw8dqcpBX9M4QnnZjbjuet3zee+3+XE7Pr8u2EEY5uOIUS3hpNAkYaKArVVrBGSzSYAJxdORRUp94OUvg9DhgQnMt4YsEzBwvi7tTFrfYjpulDUnLjrjWQofEggJTHRvYzTcHBSiN9ZanxVRh0SgpN1oXCVLBpKdw+ke6NkwzT65CZIjYyMwSEGbG09i+XgtFW2PoA2HcjwffImCFVfzIqlUgMA6CtQnxU0qeIcR7SPtyBVekSiaDYdao0PGA5Ot9FsiAY4GdQPSDmsrk90hhne7iJBcg3ebNL8uWdrLL6fFRgAuH4UxegmMaBa2Nhp24E6EwAdj3dD3kllcYxob9SDPVJTqXbEKGivz2MCoNOWAVahcBkLKL/LcQp5kfIYRDFxcZz0suk+6XxccFzYHhvkTfArSCbF9itJBUfam2Oq5HyujxEl7AAKRWsF0mMGD8SSeFalfUhMcZhl8Jr6+nodaXvQHjBmflIcJ0htiWYHxohZCJzxDLF8m0PISsacB8HMlyoOrQGZBlWJ8jyabnDK86n7kHJRKHGRnpc5WzxmTmj0OSsRt+30Ix3HfH5zva4bC4XJ0SKhoMrCPOc+JD7S4r4cKW+vsnhO5qJ4uA6Rg9x6/FzlmLSvcyWoShvNTLX0XaXIlsj/cl4tnHIJbm2BR2k1Z7NS6u/8KwTTpSyLy5gMV2ZVyDl5MDU1Z4O3uk2zNOzyuOXH8brumTlSpmolEZ72JqlcattHgOyrGI5USxJBXjbTcd8euPaxcCS9PPb0SylEt1UEDiZtHOeJnDPVxIefO65ctCLM7/Ufc7Yw7kLcdEBOAc6TnOQkR8nba1ncItKiLZpiRLmvhY1bVBU4AlmmLFEAMsxZsQazWUmzv47HrgztWh1XUlM9yuMogbHk50fTcz6PMYqcFksIS0fgkCHevO2A+Ux6VsRAKTWNHLOuQWHIzXT6XrY1ZjXScy7mRSsAeC/Xs9nm7WrCajVqqnaNvvjZIgU4UyuApslcEQDCxRnczVpWT4U0a8DRBqmjVULEgiTVudffGL6QBEFWuHKdmwwh+u8avE0BztELsjIKn82lb4iCyHQOZq1wOczbTF8HgBcz8HyWC8nqGryY5QCnRYPWlRSXKbhtEQOD6w2GD5dohwxPD/Majgj+oQSVXZ9jFiG2AgiN0PXTEOA2I4ZHcm3zZytxW4iydUJUFpJFayE8OMP2kxnONrkVgF80qFZ1tiyaXHVKDLhVVxaSfe818VkQ0TcBXEPACSMz/ywRfQDgvwfwNQDfBPALzPzk0DHucDL5n7k0O5UM13QOk79dJPJ1hmrOlouXuH2aSXWjhUvb4+tnIX3N1aMUX8SEzFTFMJ+Vufp4bF7O5WZHBQFAov/Leek/zlqBeSvM2lbDVpUoKMUHxDgFzec5Sg8A26gkfMhZElVqlQP5Kl+HBiWX88wrMYoLxm0jyir64P6B9N8g5/JLo7GfYcjnsC5d2+S+qKpoZ00KFKrS4aYGDYaT8mwBYgZttmDNJC1iXUw3guc5GzM8mqO+qaSbobp4g7gbbuUQzmaonkq2iuoKYTlDWLaon9Tp2sPlAm47phc+SdvItvhnuJQX1D1psPmoQbWKiqx2CLMKdUDKcFTbqMyZMZzFcoKZAzug3gbUswrbj+Q6Zn8cq12JgJBdiPBgCT+v0XR9mrP+0RyrTyrMHueXf7is0VRZCYdWRuxbURZN4zBcmpKA+nhl8TLckD/LzF9n5p+Nf/8ygN9h5p8C8Dvx71cnL8EXOygvC9FILvn9lhHq3od7lddsfd67XD9R6R/r7zXmYY8L5H3vIWyPf9e50DiFPdbLEDeZLwcwyT/sO8XB7bT/3wERxXh4WGkML0FehRvyDQA/Hz//GoD/EcB/+MJHtWlFG8G3yES7e2wpWLQWtMewqUTnBNPgfUlgG7gMcIaQUq5sairC1bUhoonR8usbSY/qiouYHtx24t5st3kF9kHIU0LI+fGYimNNUZo0Hnc9sN3upk69T+QsAIQopR9kbDquVFRnqjnNnNLjp7k2QetxtpWYxPElq2MbPB6GHFlnlnRv15V1D3Ee+Xpl2iLG1KAPOT25jY+iq2Se9Lj9IJ3D+wHumVgFlVLfK3lPvK/tphd3w9LoD7Ft4uhRbfvCXXRPbkDbIY+h61Ctt9IZfZo6rSpUBttSRQxG2Gxx8UcrVF/kQjKeNaD1FsuNpr9zNqSJFlRoa0k7M4P6EfVNtPBWm1QlnHrDOofqe1+iamrw9Q1CtLra7zzDB/wAzWc3yQWvn9SCHI1uSKP3IuJXaNuhNpaI644PMr+osmAAf5eIGMB/zcy/AuATZv5e/P5TAJ+84Dl2pOgIndwQVxbgPK99oTJP6YvWNsBIJeWYnKyMkk/Ib7jvxYXpSyATzedgbHNGANHFSa7HmBr68Habff9n8tDRrM0xC++NG9LJNsu1qdc9mxWgrNTomTkDwNTt0vlSXksteloucsGWdRuUmxIAny+k4pQotS9UN6RQ5MkNCcnNS/MQsyt52wSU5eKLspyLe9j3qWVgEbOYNen+hMsF3LoXQheLLwAEvzCfwam7iBizWM7grnIvjwKUZV3QCMpKil+Zra5vsP1wjvlW3TtCmNWoAIyPTMwiKgavMYvYvtCNErNQl2X5uAGGmBFBbm/JF0twW8ONeX7DgyU2H7eob/LL7xcNqpsqWRu2MTIFRnVTl6Csb7+mmAWAn2Pm7xDRxwD+HhH9v/ZLZuaoSHaEiH4JwC8BwBzLFxzGSU5yklctL6QsmPk78f/PiOg3APxpAN8noh9i5u8R0Q8B+OzAb38FwK8AQn5zx/PmPywwSd0Fj7IAaw/wpLAEqiqhBAv/0BEwTio6vS9h3N4LstAUhQFIXIlSxh2BS9sug3d8yK5QYGCzFSsnsUb38fzZHJcxOWAcEbZjRmMaFKUtJONt7Lw9jim0a3tvFM2Lkvu02oXdx0CnWmMuQr1525lOadHlU2tGNqbr4+02A5r6+Cvl7ASAoeTgTG5l8KmTFmsDY1s6ruQxAKphBIZRkI6RNwLDmLIaRcdw78XkZ86uSdcDfZ/6oRQI3MgEntCnyR3tMf90BaccnJV0JKPVBrVacanhUUjcr9xKcJedAw0j5poxUQ6Uus5uSF2DvnwmGbKbVbqH1eNrnLUV3JVBcF5vJTgcq3W18XHlnIyj6+FucoCThtfghhDRGQDHzNfx858D8J8C+E0Avwjgr8X///Z9zzE5ofzPnFiwAEgaU+G5JgrvWofQA65tEJTGwsQjSHtebrbyIlxcgIYhmbp0s4ppy/xCqX9sU5ThyVO4hw8SH0UC0jy8lIyHph8BINYeAJAYhboemy3CVx6CPIO+HVOYF2dCdFPXQvyiadarayGaratEP68vAZ0ti2wIfflU3KHVGhTb4/GVeah9EPJdIPvnH3+QUqeSDXHgppYUZVRKwwdL1E82oMUMYRlN2hBA2wF0bdwjIALIHPDwMhHJpjFWDu4quj+HsiHnS7ibNcLTZ8CHDwGIqY0g0OawyLUhw8M56tUArhxCrIlwnUDC3XaAv5ij+a4k5qiuET68xHgxQ6vxp7YpsyHmJUTbwJttKRsyjnjy0w9w8c04/orglzXaL+fYfiz7VF0AGKDAGM7llRsX8kxUA6PaBGw/kO2PBh/bQlbAEBWLczkb8mmbCHC2X/sQX/70DB/8PxXUnxvPKrRXgwSQOWdDQkMgDzRXfZENCZ+/HvKbTwD8RnwRagB/k5l/m4h+D8CvE9FfBvAtAL/wAud4voTd4KUohef4YgZqbSHVKZUH7IFI3xHhN4Hukh2nOQ+HAPKcLSFImi1RyVnIerIGXh2PQnGdsVybCiskzpOtnQlIfnnuRBYkXDSlEbgDxLgQi5OJ5yqQrAyZK2K4QdPKAcQQRRzhzulYCrm/L3JTxxKQa2SY5F7qeOL/+n36PxBAAHnAjYzkrGt5/OjTInDb6MjHazDnQoAcu4DYv3hK5K3l4Ly1i/qkQzkPIyhyCwCSqSi6jO8R2y08NRgCchQ9UufZXiRwDuH6OqazlNfC5+InI0XH70OdvnXuqyoFBxNISlOtWuRkTGLtqr2vA7mFwSfeCwsM29e1XK8DSPNdjFM/KgAqcOaZNH1HmYVmL1lB+mIOfflCxnRquL7e4Z9ILfqmfwfhMpHfuzQPO60DANmmAdPo6iTGqItoYY1jqopVF0/urZmv2zq8G/6J6sMPio7niK0hCpi2zo/Op3KSKv3j+XkaLwBxQ7S61FViWUUOTp2f6vwMtFyUhY02gzchReJtLJY04/rd7W/h2ZFd1E9w75Oc5CRHydsL9yYH7E+kgNqmbFjjfcFYDCCzY+9pLQigsEKIKGnoRGy77UQDG8ZoqmtQ02YWaGR+iRBTj3ou9+ihBKgUTg7IsdU3X20yYW/Xgy7OpIQ6+qN0cSaxg7YFhiGPa70BnS1RRZ4LGYTyWcwKuHe4upa52na5PZ6yTWkxVkzl+ifPZPMnX8kYB3WDIlltOu7lEu56IylGkzp12k1cr1ebAAMCI9fjxlW/Olvm1dM0U0qBUsQU9HYr8/zxR3K8aOFM4d5hOYPrx1jgpihUKTvHMMp1xLgJNTX4bIHQ1qg+l3hTNZ9JzEr3tcxcdV1ui/MZPn+M7me+htmnggHh2kmK83oL/0BiFuSzm1mkToO4fG49YPtVseiW33waA8pOGhsBABHcg3NBwT65SkHh8LUfxvonzrD89irHkhc1qlWfLNcE964daPBwNx2CTZ3+w/eFz+JQ1an32ZzT7IMPoFTVSSWR775siOkWzhGUlfpsqmi5r3lREomuMUMTua4dTww+FtmQcUxs4ulvQFypCApLgCaNaA+DjCllQwg8DM8lBAaQSYGVgyPO3fQ3AJIbwk+viu8Fmi5zkbIh2y4S3W5z97JYDo+qyq7UOMaofMg9PIEE+w5X1zlGk5Cdkb5OffvNVsrshzHVzWh/U9YMTTxGdSNzSE2TsiE0euk2PsHHYPSgqxXcrElZB76+EbyJdh8vMCNUdr3TxWGzweyffQlcy98u1svwZos6Aus0zsQhoFYcT9tIpmrWgIYRy1iirpkbbupMQlTXwOMnQgTcdSlTVH36GGeDh4tZHQCovozPyqQFBIhEMY+jkPrqZe1jEj8gb6+yeA6vRHqYIBkIaggWqVm0NZykNQGUrQl1hY2sSvGL5HNbzoXUkUxv+iakVoN2XwF5jSl4CiBR6gNiTSSglbYgcC6nNqNFkTgMVOF0I6hxRTvAFG+ZtEcEEHtbDDmOoMdXBGfTFNulKE7nS3z3VAquc3+2kIe6qrJFYCyoohAtIS0rsGZ1NX6wzEVryTLUNolqWczamE7kDJjTfUOQrIG26Ju1gti0EGkiyfj4kABfsjOLVWR71i7msfeIl2yTZYN3laz0Ok/a52UYhKFLjxuzR8QMPosFXpbPIqVO6xygdQ7jA1GwzSZm0KJ1oWOli3MZ/w0BVVRu50uMjxZobBc4VTIaE9PrqxwQWxsmaxAArt7X9oVRbJft9DbukLg8B2dhXzTnJIAYQs4EGLanfMyQlYE3ymHb7SikomdITIdQGDIrk3Yh12Nvt2VASi0K7ZZuSVnHUQiHp4G9SeFaamSkZDV75mmaoeDNZicYyaMpCItzxhHfkIKRwSfSmfRSayZIsSkpAxXnLrYp0OuVc5SWRWIF8z5bg5Wx4myvU4XGVy4zYHsvlkMMSidl6r0oPOcMU9Y2PQe8x7KAsSwS3H8cUT2+TvB8xaNw12V8hSU8Su5WlV22YUCtQcc+WsL6TOq8b6RvLRvLwl2v0DgHMr1EQGJ5qpWcUKjOyW/HEdiY134fefIBeWuVhT6EOx2m8g7xQyaUSTdwGJ9rWSSNq/6+mrNaur7ZJuKUonL0SMuC1MycRsD1Yem6vEL2ceVnThyZ1DTRnHSRJUlLrgegrl+hZZH5TdN81XVZvLaYi4Ikn88XKrFIgs+UgKnGhIFZ7meRrIi7WhaKS6nrrBibjLPgxSzR6iXLIgSZy0g/kBROPB43NbCJ8Y37WhYPz+F0rtSycC7jSTT9HDi5RxpLIC9uQziPFarXayQmNlt0eMiy+Ohc+paoNLVYD47kfLWxLMb5C1kWp2zISU5ykqPkrbUsbhVrakcznb3BATgCR1LSQ5aJDXCCOeEpyO4fSrNeocHsfQ44Bi/ByQnOQrMjctC4ytmVCoAw1kJWo6vrwsfk9aa4DvgciOK+lx4a07hOP4A2B3AWOt49v9FrAyD5fCsmo5GsMQ0GjyN4ayy0OH5r6kN7zZr5SBbgZvN8nIXuEzzCVezFYrEfVZVdlmcx81I5YzmyoFMj/Z4dGz/rC1g3bzb3w1l8+9PUdlKyGDVC34OexXuplo8GTmEs2egmuoiszUHvKpMZV5U8TxOchfv+F6ivV9F1yVZciNZssDE6InluJjgLvBcBzltEAFu2etJlRVHsc0uAU6s/Y1AzNenVANRmK24Dc/anowti3RDebFLDWSC7Ie78LBLCmjhEXWcA1jTAuVyIr6xuyNlSfM/GFT09ue9BizkqG5k/4IZw9HOPcUPCjTys7uGDXMU6DXCq/ztr5SEzxxXU4ZgaEMtFqBntZF7VRdO5m7UZzDRxQ9i4Idz14G0nPWXjdWrAEDGYCEDqLQbJwCQOTiWojfuml8N7gd/PWtCXoiAVUHabG8JTN+TJU4Sv/RCqx9dpXnnWwK23GdofCXXJh+QCcFtnF7gbU5q1/v7THNBWF8I5VMuFsHXdrJJyo69+BcNXH6D5zDZGrgQqTyTzYgKcNIxwUzfkWxO39RZ5e5WFpvK0ZiFFt6W0Onduit3PAyN0OdCjCEpbR0K1dGDnkOMIqXflYl5YEWG9zn1AtTGyD6C2FfSnDZQtF1mhxBWHmsYwa8fzNy4rqe02afiwHWNOvYL/vqzAVdtIT5LZDKHrpFcJgLDZoqoqifDvKYtPJfBRtDE0LWNk/vomE9J4n/ACTgOq81muy7DZC5NJCMs5XNdHjgtd5QnwUQkOu6uVm5kO5xq3ubwAxeKwFAOK/UlSSm8+A9VbgRGokpm38gJGxZDu2fkCbl02RubKAbMFaL2VTMTjTNpGhi4AAOjBhbzgw4gwayUlCYhFGetjlPKfl0L3R6PHcDmDU+4KIolHjD4pALfNbQ380jRGdgS39aicS9vrfsgxHyuffIQwr+Xex7nx5wtsP2pRm+bG/nyG6saQDGmJelOBW4f6WYfxPCsL/s57ng0pzMMD/UFSbxFm811cbZzpyaCRau39sVNjMjlvJMChZPaJic/aY0N33ebIehLKfT2KisZhSBZFqv7sDD7C4iSU0Od5fUkACbBGrIgqXVZKeQVlTY7Bq43As4GcvZhA2t11FatIfU5FAvK7PQ2bi/kwQnqdALRHCQ2UxwlJyfIQMxTReqOUKfJAnx/2SufASoRUCybEl42TVwIsC6p0N1tZjbUuI7UfFO4MbPvcRDlmfpgDms/XIC2IIxLFv+1QqWVliJlok5UiEwk94TCiGTM50T7X2a02cF0lWRHFVDxbYfFpDffMlEJ0Yya/AZKF5ZyL3B1rNKbSlPbcq0NyCnCe5CQnOUreScvCNg4qmgndRaYNYbWC0iBDi65n8VypctRWrZrgUhqjNrexK703TYBCSCtwagCzb3zT//WzDbxaTgob/I3VojvH1wrSwurSY/l8bQaMpuMHINaExmNsYFebH+0B1Ol8pM9AxpCksUswz1bZsjYN0v0BMMXfTecscneU18MgjDkOUsyjB49U0P/BxzmMiMt0DNIKYJ2DEWBhD6PekhSrZWSa+RjrK1MsCnUBDdKMqGAn29esePQJ4JYAicOIajOUx4/HS/Eik9LFEIOq712Toak8p+nQ/p/kOMdLE5vDR7z5lsX6TYltkKRxk4hkpMqVYzPoxjx2V5bnvy6ZjBmIQWu910qEe98GT3cej8wZ15Wh4ud8fp075yZNi17T2ICS7u8OwrVLz8R95N1RFkZsL5CiP4hZ5bS3SMHXaUUDaqql5zMpKkt9Q9YZEm7OBaJUvg4ggX1S/Uc6ngTACkCX7evhfea/DJmEJnFwai8SjfzrePtBsh7alwTIqT7Tl0Q2xzqJGJgFkHuRaoBTr1ebFi+XOeKvlkVd534eAPjyLLUwtJylXA+yfc90p/kA0nXT2SL3L9Xxxf4kCQQWWyJgGHOQtm1k9R19zhgACA/OQJMAJ/kgL35VSduCdSa0oeVSajPStc9TgJPns2yNxQCn7aHKy7lkGLoe/ccXSLNA0uvUNTX8IylWJEOKy1pIVjtwRai2I2g7wivc++pmb4A4cXAqcxmA8Ogcmx8+S3UlABDOZnArU3+khWRNBb9oUDPD274h334fApyTQrHiK9MLpOgPMlpKPFf+Pz2GxQIAuX/GPPNJJAVgziVVmG2uGI0sVqwpKg3MLeeixEzv0aKvx3Zb9PJIaTZF7cVeJBRTjjpe2pB81r4k9hpsXxJAXrK2kYdLI/99ny0KRzmlGsfI5wvQJs6ZmqsR6ahm9fhwiaYbhBZuliPr1FUH8/Y6H/oZkBcuEbxoOi/2J9E7ycu5mNLbnIrkRZuQj7aL+/hogaopH34aPLip4IgQLuZwT4xyO18gzNtEicfzGcK5NCoKyzbD8QOD5428rIpHuVwARKieXmP78QxVVAhcEUJToa4I/YeRKWuTlcWY+oYQuCLUqxr12mP7kVx/893ct8XKeDFHWNRoBp+KzcZHC9z8cI32aW4yNFy2aEwDKts3JLSiiIcHZg6q462Mt1dZvCyZTvw93Jl3QiZ9SQDcbnI6At70NBDtd4+mn4GX60o+T6bnvs29fF3u0aF5uoPsNFu+6xBe7OcnOclJflDk7bUsbonS2sZBZTMhm40oK/52jqH9I6J/Hq6uY3VkhkVbbIOei5wrGwQNg8CWJ1F4fna1i7PwPjUB4vUmxwC2HejLp8W4beMiiyRkZRMHkpugxWq2iZEcN+bkxzGR6vC2S7532eMjrlZfPAVPcBbY1kjNfwA0PnJEeG+YvAEe+kTdtjPfOh9AdtW6PgOQtFgtYkB4uo/3gBL0XNcZZ2FKzNtNdyvOolrNBCavl/zFUwG/Rai/qxyqrhc36GyRAFhgTkQ0irOoNp3Q540jzv/xM7inBooecRbzTYz9mOxD0+7HWdRPxJXgp1d7cRb1p08l9rLJGIr220/wQf8AzXe/zPs9nu3FWcA5ISN+ukL91DQZ6ve/H/vk7VUWt4ltHFQ0EzK7EAlBjTO8lMpLSKZ2QLkV2gbco6zaTMfM56II2U6+ct+DZjNBItqAZtNK1Z99IU2PVAlU5qCjjZXk8cQSc/2n31eVxCdseoxig6S2KeI9NJeGxCkQOfT5mqvc6xTDKPvNZ7m14KEA53IuL3FdlwFOR6LA9in6OB/6GYCgM3WsbZMyTewINOSHnJwThagB4UijvxPgPJ8XHKSACXAyS4DzysaQZhLgXNVpPBrg9A8WqBSO7UNm59K08nIOnjdw3mN4OEfTWwRnnWIkwPMCnHUZ4Pyi3ev28HIObip5plJf2hn6Ry3qZzlmEc5mcLYBlQlwdh/OMR98bjLEuVXAMfJOKgvLUVHwVth9NN8fMucC6XPCIUecFcG57WKRjomATzkqIq8CvM/YioiO5MiolXAV223mpEXV0HEAACAASURBVFDZ2N4ZGW3J47iL4Izjga6qQ7Z4MAz5+3itqcOYRVSOogAEYRr37QegMtgNy9uhBXVqsSTFVxfEuHRVJf6NYhVUnMMea47jfNj5lDFk7IYGlAtGqjjHGEZwiCu9Fk4ZUiAAcIHLeg5EbEzlBCk6jkWmgddroK9zUeFmKwHXEFDpKh7PT71gKhQJSyGAeqERaD67BmmLhcgoxtsOlV6nvSfryDYW622mOIuC48OIu17L/HR95sToBiyck7YSUaptn8lvgFw05hxmANyzFWhryJ/H99yyOCp1qilTG4Cy1YyaBdBU52JeRtcPpU7jb1M2ZBDeTku2AgDubFk01gFihkMzIBxy7xEg9fVIqdOF8EpQ24oy0NRi5L6g5SI/uAqVtu0RAfDNOtWoJAtCuTFiBWOaB+1xcnGeTfnRcHPY2pBHlxLsCqHIRqAfxMrZVxui8wGTcVouMqelzmddSQ2OtTg66VGqvV6K2hBTQOgfnO3UhiBEy2ItXdgt7SBdnEshmRZmLRcIZ9K+kWcNMMiYKMTUaV0lK4SXc3Dt4LYd+h95gNbwZXJTgVZbjB/KPdXaEOBAbchmwPBQ5mR2vdo7f+HBOXhWwT1bpxfcP7rA6mvnODeurtSGGDfE1Ib4ZQ34C3hbG/LHJz6Lk5zkJC9Z3h3LIkGqI+jneW5I4p0og4PJzJ9UbKYWhMb12OeGoEdR2MW9FIFxBDsp5VlYrXfdENNe0AYCue9zpzAdXxxPItw1Xdq574Hrm91A2DCW17vtgCEWnFk6uD0YllRoFru/p+sFBCZs3BAHgFcrsdR68wgNY9na0YjOhxw3WmrjmHEZ2y6CxSgHLwGJlWgneI0hbTux9iZuSKXnL05s3JBtV35/fQNsbH8Ogtt24BCkxFyD0YDEiZzLLQWHUTgjblZov/NsrxtSj9nFUtEmzDxxQ9poEfFqvd8NeXIlgd/NJs1f5QPOmeEeZ5Jld9MWbojOT+Uc6la6u7vrbA2+lvaF74SQQqD97vb7HlKBWSoJjixdwV8b5NtR+dLruW0O3sVAbhXyNVteCtNbVRmzX7vY4LOCxSxQSIPRrwPPoAQ5yn2hQdbA+yHWTSZgfi2iyNv6nnDvppYAsCECvou8k8qCHIGZis/CsFTshB0locJh9+GLjWRtDQCl4J89l6QpE7oznUsPHVmMFFlq/EmqqrwSuowQFTLYPePZ979+Jle+9DoOjUcAJRJwmiUgElLaxFWpBUcV4GKsAkaR2BqIWrMzvtzufM5CTWSKuk3H1ZiOq/J+lqSocoZXw6B2tR2fSZ2iqXfrW2LqVBnUuZhHITNiqzDt/U+rc3zBlDBI50DjAm2TlUZMnVJd5QyKGU7qcxJTp/q9sn5TVe1/iXXONaMXr9cvGjiTEeKmFuTpntRpug6z/10AXu+ksjiq6vR5KM37Vp1W8TtLRquuQ4HzeA1Vp7bPq6ZtDTJTmcKKKtVYcar9OYrKTQ6vteqUrNunijmNI2eKNKv1yqtOtdp0FDIiyxhGdt51DvS711R1mr4313unqlMNUr/3VadGjsmGoKpAiOk48/ByiCvHPQvJpCtZZulGzDSQxgJsrckrLCTDYp4fsGkhmZ2r+byoAdG5kbGFVJxFm41YaK+zkGw5B1cxo9M0pYWlD3RTx270/OoLyc6WkjEZRum6Zsx1jl3ZEovYcg5ua9C2w/A6Cskuz6TGBUiK9K6FZONFi8Y5+AuTMTtlQ05ykpO8bHm7uqir/zthygZQdFW3HdUPSeq0bjIU1eV5AhKFjWktB8i5bbfxPWMAALdcJgCW/JxTUxkAqYeqv7rZNcdNl/PEvA2IKatWjGV3DtGcVDdDx0uUODnzwPbofaLMfq0uQNcVwcwEhDo/E2LcPYzbMvTMum1JkIuu7eqS7XumdH7jPACAs3yhluqvqXddoaYuGdP3yb4grWXqJme4W2N8wGxzy2WaL+mWlnuM6FgSDF2tzItzhCdP0zMmB4oYFiVZnrBs5/1cclX1/ieW8Im4aHnSfJ4wPv7zLxLHar4mV8LtTfzKPXoo4D8T5/lfn/0PeDZ+cVTg4u1yQ26JMzy36dChY4XshqRuUy+gIDn66qmCz8RMyNEuL+Yrkuk1HCKuSWnmwlfXWEzIgcJuf8rzlYodk8ZQNB5k4zFA+TK+KlEWqpjiznGpkAPgZuwcS+dfi+h8DP1+fpYjhFUx2ft8h4O9ZcrCjHy60nNeGd3ZWUYvzqQ4yM1n+YHiEHs3DHBtjsInawJA9fFXZNfow7qHD4SIV7uKf/oZ3GIuxL9K0hr7odLFIqMvv3wC98Ej4EthjdaVof7ajwHrTaHl6WyRWaEfPxUEIwC+XgEffyCf/+jbMp5PvgJ+eiWxi80mn+/pM7iHD6SOQQudohVEyyX4PNcJ4Iun8vv1WpCZQG4uHC0XWsqK5b/3qRzjp/+FhIJUpCBHPgsX53f46gWaz26A0YMX0YILEMbv69VuR7PAwIcPMzP2mXBBoG0S0W3BZzGMoNjtnC+WoOu1XPef+OfkcMsW8AzXDQizHDPpP5yjuRkky6AZ2SEg1A7VdYdw3qL+9hdp//CVh/BnLZpvfZ7GFS4XoH5EaGu4q/y88LxBmNWonsm2cBljPX/0XTz9xs/g4lvx2ioHP3Non/VYfxL5LLYeFKdiOJdV3c8c2AH1JqBeeWw+lut49H89BnW7sPjhqw8R5hXa716leez/tT+JL/+lGT76g6yw+gc12qdjun4/UwRnLD57OqB/mOcs/E9/B8fK26UsbpNJVmFn+2Rl1ah8EZ23x0hNglRjx4h2P4GHT7IQ7D1oHBMrNXsv5rvP0XEACaKsrNW6TSsr2Rtm7eDlu8BZ0SswavQ7NRjsgwTapizcfZ+JawCpAtXiLoVwq0J18bha2aop33WXH9bYBZ3inGvGprrqZR+TolMuyqL611gw1A2p7sZmCVIwVX8To/kJ/LSOzaKHIdVquMiBSsOY2wYCaG4quLWS+8RxjQEVANp24qmpOxYCaNNLclhdi20HF+eLegleJvEe1dCkbU7v6Thi9tQLxBoAVxXcUMGtOrSRot91ylQOuFHJbyLrdh9QbcdEUkPdIHNQuZzlIEJ9tUWIY9Jnr7nqsfiiQX1jrFkG6usuWUIuNoHiWv6ub0oGePLHmxanAOdJTnKSo+TdsSwOia4U0zhEmKxuU7HWRlzpEThXnd4i0qnb4gv2+PreZ/bqmK7lEMS0dyS/sWnVafXf1FKx18dBgErTIOCUuTm2X2TT3yPti9g4ehKnoNFnzIDCrtW6SKzSPqUu0zwwx+stxwly2UJLeAaDUfF59UxiK1cjpsMGaTH6HIexUOrtKGNTwJnOSYg4lsFjx0IdcwyLIgaBYrl+gV8AxL3RbQkSH1BvfYJNk2e53aNPFkXijGCGU3Sqxnp9AHUe1dbER/bNZYSXIzaf1uM2m1BAtl3n4hzI79XyYq5AYwD1I6rt/uLK58m7qywMKzWgiMT43V3idBb+jD2oRw8DSb6jIeZIFIVFVCbG8QlNmgb4LHu0wnst+tKyeL8q0eu0bobd7nQclPgQyIds/k/Hp0FUCzl/EbEZIhN4ZCJ5qZ2BRDPnrJLC3yFKhImAirCP8/IuwsbtsZ/t9zRdzFKAXMaQYJ76+8oEVA9wTnDk/uAqA/GS0J7n7AXl3VQWzuXV6TaOSfv/VBKoKvrRbSOryRTrP1UksVAoteAjyixPMMHlppFjkwnSNk2C9WJrCHRGL6Af+0A1NbCNqbDRFePSxr8KQkskv3WdSr3lHNqXtc5gs0F7ilYgRzu1DTxrMzxZmyLPmpiWlLkKyxa0HXINBQCuOffWtKsVkWyzUOwIlebKgRSApCXqTQ0aXCbsnbegcZSUpvahnTcgz+BhBM/q9KL4s0ZewvgS6f2hRmDSYV6nLmFKYBRmNZymEtsGPJ/J3DZ1garltgHP6hz0jYFwqmsMlxWaZ02aMz+vQYNPbQJdHwOczBiXMl9h5sBEcENATUB/KdtnTS3XTpTfTiLwokVYNHCrJll+Ydmgu3RYzJv07IznjRD9OAIY4BgLCbUDBUYNYLywAL3jF553R1lMi6bsV1ocY9vExRqFslYh2B8V+6aV3E4eOeyo7NgvIuXQY9fsVHOgx62rmPNGVliVSy8XmVUOTlB/xeqTVumyzoP1u3pSrwEIfZxtEO2q1Iw5IR3TOav0mzSHkJc1oVD1OOnliXwWTYWqFjwC26KmMTZ9VpVp7hPXFWhw6TMAmQudRx13Uwtjl76oug9RVkxNBbjYQKmp0i0KswpuDPKi2HM7ghsDQmuURTyOHMulMfA8nmNeg01FLTc1eNaAI3GM7keVwzh3CK1WkxL8zKFqKviFPhMAWIK4fiHXPs5ljFUHkK/kb0BqRqKFmRo+Vw5hVsPPa1SmeM3PKwznlIKjADAuHKquSsrCz6KyaKRAzvU1xqWpJbmD4fHuKIsdM27iGtjiLn9ENkQh3LryhdJSoWgKkqfipdYaBdvBvKg5sD1QgXwsPb/6vMZ8prpOPrjtBp9WfWsdabGT8V2zfz8WfI8cfPb/99UW+ByfSNmQYSz6ZSSglHFJaJTaEjKKm0ZzvYkYaBDl4UOm1NPjUszSaCZCFQlitiRxnMbP6sfruWxEP352fZCxNRU4pgrJE6jzWRHr/A6jxCsozy8NAr3WObRzKW5M3kZKaOMD3MBwMW7A7BCCxAdcF9K4wAwKjKqJ1+lkpafAIAaqfrJQNHW2nqtK4h9Oakn02XN9QNVxUkQAUHUMGiQDR4GTxieWNLLrRtRrs1DeAWdxyoac5CQnOUreWstC4MXWJTD5/MiqDMjqy+RAVVV0yKa2zbRxSnBjsw8RPsu8Ep/wwblQr51FUJMGEps6E8rUNWguv01NgboOeHCRi5HUn3x4Dne9KbIN4eIsFQzVISQAlXt6g+GDJcCM5juxSOhyKUQsZwuxUhaxAG21BmYtwnIOd62NjeL1XZ5hfLhM52u8F3Ldqwrh0aWcS7+MFYh8GYudHguobPjqBaorZaX2gJMYRWiqZD3c/PgC598G3LzO/i8D9U2PylQ1konr+AdncDfRJI4Nevy8RhNdkrCU44RZDdeNgpcAMD5aom5qUNdj/FDGOly2oDGg3vjUtAcAVp80mF01ACHFLKpO3JL26YDugwb1Y3XHHPqPz9A/rNF8HoF4DxboPpzLcRcVZo8zeMkvG4xnFWafy7buQ7kfZ0+v8eRPVHBe5j3UhGHpsJg5XP+4jK1eI1lW3QOZg3EpN6NeAe0V4+ZHZbzL7y5QbQRYRtowiQjrHz3HcO5wERjVUznu1dfm+PJnAppVm4Jl2w8cFl9UKdiv7o2fiRWxeNxg86FxW/7+8X7IW6ssdsSWf1vzMLJfFfUaTgBKypQ1ZbwCAF5v8++rSpCE41jGBhxJui1lByKak1xmfdp2oGfXCeWp56qe3ggwizNxirtZZ77HbZ9Ncx9QP9lIADC6PO56I+PaCBkwFEVKBPQDXNcnJqcUY/AeTZcBOnyzEhbu7TYpCda6msh8RRNF2nx2k0FZEeZM20FiFPE6zr8NuM0It9qijqAe8l6IYLddDrJGSnoOAdWzVQLCuTjH7hmDrmU81ToGA7XzWQQe1cMIulkjdB3qJ+u47yCLxhjg+haISqzqPKr1iNBWGGNsoNp6VKsBNPjCFaJhRPvFCs4vUiVp/fkAtxZq/qap4VYG8ds2aGa13BcAbh3v/2qNR//EY/mdiOysHcaLBu3nGzi/SONCEIWhym04q+BGdR0Cmk0c73Un1x8VpNyUGstvXyMsGtSfXyXU8eU3LzEu51h+v0/KYv7EobkehCE9cIpnhMZJMPW6x/xxDnDW3XuQOk1FSfvShBHBB0Do8wKnkmkA8t3zGKuCviQSg6CmER6DIccihBU7FDiG1DXddlFXHgcrPvJVBJ9JTiKtPZD9eSAqnMUsxz8gDzNvt4kghsmn68UwyHFUCRZjMQFZ78F1XSJR0wsTEZzTcStXhX6OgTbtyA6IReFWW1A/ZNr5iEgVxGlUYuMILYXHPMdHyFD7JYyDxiNI8CkW+5AwFmqxaJp5lAVCrzn0Nagf4caANmIbaBAsBfUD3FqIe3VuaJihWg05MF5XiWODND5l5pLGTH6TLEYOqNeCXwAAFxzqFcH1Y2pp6LqMwXAxZlFryG1kVFuf4NjU9fIM+gkfBs0zviXFlzyaG0a1HtO98SyWGTsq4hEUGPCiYGmwHCbvgbIAUCoKGyS0tPR1DXK9NAvW1R78/GyImsjRssCslX21RsFJupI4r/aohBcBdU5FUlWB2szunc7VSgoL3mQ9Zq1wKiAqg3guAhCWoixSkDamDFHXogw1bbitcvNjDVpqCrVpit6jaNqkBHOfEw2axtqQyEeRsiGLNgctKy84iqaWrEfcPl60qD3DVQ5Bm+zGv2kYi6CzpEhDkZLVOYCSv8TrlTHH2hCzL40eXFUpXRmWjQQGBw+/bJOiGS4bSZE2Lq2oVedBfUC1cfCXLdxNnv+wbDFczlA9VsbtGuFsBtpW4HkNN02dLho4ZTiP1+3qGpsPa7TP5G+uCcOZpF37yyaOQdLJFIDhImZDFg5gwHlGvXHYfCD3ZbGcAX0l7F06j3UFf9bCLxu46zalb4fLFpuPHRaP25w6jZmOUBEomGxIS3CjBFOLXqd3oIE8BThPcpKTHCVvt2VxyA0JpRug2+5Veh4YCfJp6O04KFTbmPB3bag8LQlmzmlD/ZyuJ4jhY6j8OASxToIHQqbjk9+9PGReOWbkccX54FpdAp2HaJH5AGjMIkzmCpq+ji6jSX1C0Z536OAN5PSgApzgGc6kUXU7jSGtgjTEOWQGjZxh9cxSKTuFVd9DKNh7KSu6XHPcIaZHC1EoSoCMK8WvZJ5Ixwjs0geqBAb5SdqaYyo1yGcy53lRebuVhZUCI2E+68M5bQXwPJyF4gtYzEPEiskit+4nCii2I6RxTO4Ge+mPulN1qv47h7Sv0sezozJmMY4SHOQcQ3BDbGVAFKtOzUM+joCn3arTegB1BnBjq061wnVadVpH10394K43fJAGHDTm49Y3vSA4bcwicIpZUKUPuVHChqeywIJodWm6L76sOt10uddpDPg5nQeNYcQ5q68rVOseXLsEQ3e9+Pm0HYQmL7luAW7bCyzcHMet5G/yPgcY4/4UQtrmVppuGDF/6lGtYvVuREq69YD2Orq6vSgs8gwKxjVhNjGL+IzE3qccXFZszqFa9bGOpE+cKc3NgPnjBvV6TMrHeUa9GsAUsRV9jOc0DjQGVKseja00eB9qQ8gR2AMupgwLdqxpEC+INtZ9ue8R+vjyHei9yYYglYkkcm+CpDSfSWzC+8z+rPtvu/zSeS9t8KY9RjabsqgLESSl8ObY8hCAZGGuI0hLYwvexkpcBmDF1n7c9Tkjk4KEPisFII2TxxwASyXhRBOrJwbupnwUEbRm6yeqUbIzBSltCKLQpgAyQMakJftAKvPmvs8sTwqWivGolPEaR+mxMo5wsbkztrHM2vvcYhBArcFBW5+hFs84SjNjY83RtocbTTPs9SY9B6iqksgoona1PFyzU7ztsPjjG7inuW+Ia2rQpsv9T0NI1oe7yvGRZPFse9BwIT+Pzy0xp3OACLTeoGoa8M0q3cP6sytcEqH+PPcNQVMLF0i0Xp1h99YsU3uV41r0XjRGJncrvMzSyZMTdFt64LwHOE7081yHqsqkvo4KCDX9/+y9SawtWXYdtvZpIuLe+5rfZcesKpboYpmkaYGABdEDAaahkQUahAcWrIkbCKYHEjzxwLInsgcCBLiDARkCKFiQODBlzUwYBARYgEBAjW1aHpCSbRZBFqsyK9vfvHeb6E7jwd6nifvu//n+z8zSz9I7wMO9L240J05EnNjN2mu1DeI8gVS5kdPElCcFuRFvUNH56sGpJ5uUIVhQ2BcpxUysS8SSiuPEQcr0pm2kTmOeF+zTAG6QHsXUT19NUilVKlRzeZt0Pkdq9KlqNCJmZCZmx+nRMCxrZ8SiiGdCASc3bZRzK0hYscoS/0V1fBAfP0+kQ8l4LSZFGSPoUidE45wn3BwwnWZgu2fMhyLERBYsDyWUygrp4XAAxSBVxeqIKk/xdc5WSMhjrKbKcpM6GNZHrUhsxEVbSENMM2LXMBxdHtpoRPy4tcWyaCzik6d8/KlMupgdHzu5tWkMZsc4Gh8WJQSxH/j+q9nmblFlnYfg1mvetbt21/65bq+vZRHDC62C+i0TQwRRvOEKvLDVaukhFKJWOvKn6zfay/S/3i4L+BC/qRWk/LukdCPAb/pEipveZMmM9lVs5gssO77RKgzLYvyJinVjhJ4/WUmQ65EAbkMSVpbfnUNN2BuBVysLT1ZR+j/EZSDQSBHchPIG9zym0TmOOaRtnfB0pNjS52mJX0P6yDGHsKyxSViRUOJXiDFbArmKNdeexCWvyKkWmAuDalc7WRl1n4DPxh3dor2+k8WLFMXqVnNMvCrPw3N4KrIS+yvtk0oEOnNYvKB/iTvjqF9cbny03g+rHfFPLB7wo6rYpetCpz/zz1/QOaRq42NT+gSnxI1jEiFLJn7eMa33XfGr5P2eeOdFuT+iYg6Okr6hEiv6LE4KKW77Ul8eVfvMyYKI/jqAXwTwcYzxZ2XZAwD/M4BvAvgugD8dY3xKfEX+ewB/CsABwL8fY/zHr9Kx5LOeYvOONYKzesKyuO9tWKrrtCXAQcxQrJnkmybhZT7Wy/Q/VNZLuoFiIcQJEVAVqtJLgNNN5VixijlUrFj0ZZLfVApr/L3EV7KSmEC44QOirteNnAVK+6oti4rnIsK92sReI3QB7qcEagGxxvIbvJrEYkD0EufK3KmBYxUNlj78q7QqbU/ec5m5P7IsUsq7RqxWqfrMdpUCqDpki+cGcU5q3jOHZgUlyJXRx2RKP6TU6d8A8FcA/Gq17C8A+Lsxxr9MRH9B/v9PAfwbAH5S/n4ewF+Vzy+0sfpY0W+IsysBz7SOsYhuzp8AFm8/ypkTqVfYrNlUFURjnLdsHWhdMgiiRqbaNmctwnYHdX6GIKzZUVJV6uKcJ6/0lgBAaTsixO2+lHIPA3CPC73w8WNed7NC3PcgK8dv5VLt9kBjodqmqHynG67rQFLgBgDx6hqwvF7SnQj7g4wb60sk1nD/+Alv9PDesjYEEASnzu6Uv9xwrUfnC2I0pUelHoYHoUK+nm3Kg5BMbjlHAIWcJxW4pRqadYd4GBC3W9Alj1FsLTJlYFXS7847qGFevpVdAHAOGieEtoF6tpXzj4iXZwgry9kdgNnR1x2nra2BOlQ0/8JnoXbC4i3jrD74GP23HqH7gSA4lWKSnesB0wMe85r8xosiWUJWKhehDzPGN3h/6++EnNFZaOE+uERsDNTj66z67r7+BrZ/ZIOL3y/ZDb820Luioh6SIplRIB+gdyP8WaVIVimqf1b7zMkixvibRPTNo8W/BOAX5PvfBPD3wJPFLwH41ch3yz8iontE9E6M8YNb9+g27Vj3E5JJWHT8M4BUVeoz++Pe3xD1XeiXylt+kTEQdu8bOI9RfPqqTiUChRfCufIG9pzGQzxi9665Nuu3n/QhTkcPNRFidb5xmvkBn+dSdJbSrf7ozZNSp/u+8JBKXIVCyHwTALh6VHATecx94HNKVkS1T4S4TJ2O7D7Eac5CPll6MokrJcsOkDRzAHo+h8SrmX1zaVoYv2OtdO+98Ir6/DbPy/sRquYm8R6UtU6LcBQAYNKgyeZxzPUozqF9POQCs6gV9GRBhwE2T1g+WxU08IOtWybtIYlbNImecJqRGeGrDAtd77nauu9z+lZf9Vh/bFmuMGdDNKi/mTqNWgtfxwgaq+psd3uT41Xt2beqCeBDAG/J93cBfL9a7z1Zdtfu2l37irfPHeCMMUail+Hb4UZEvwzglwGgw/rm7wLKOtlqdSjBWdBxUCsFSJ8XKE3ma+SiM2oaRlUm1+BwAJQGkStM0VrxDG1MdkPiNDEeI3FepAK3ruM3QAVZp7YpoKsQMqYiTsRmbYxAAp81Nhe5RRFN4nVndpUq7syMt2jbhRsC5xjDEWN2N7LLkmTukgyiSAPGzaoArRIs22imwpMxDxcrKCLOJKSiMB/ymyvjKJCCxA7oWrYoAHZDiPhNmS7XsRuiKjcEAE1T4RppbLEqmsI/6S86qH7m66UT+5VH9IIuXbdQz2SslEJcdwjrBjqVojcN83+IG0J14FvckIy6TXwm2x36Rx1WUnUalUJYGRgi5igBV4cmyLdfL3VDyEXo3mJ8yONongj/ilIlKKsU4zEakwvZAObf2L/dQA2rUnXaGZidyZZFaJJlkdwQs3RDvn97e+FVLYuPiOgdAJDPj2X5+wC+Xq33NVl2o8UYfyXG+MdijH/Moj21yvPbqejvyzJvn4iYnwy6qeMJ6PO3qKhEy48j8aS+sOO8Ujs1tnVU/nlR+hPb5Zu9ZmJX6vQxXraP6aE97tPxOp+RUYiE09u/VH+q7yrt98X7W3BfUvWnaNl3oudXhirC8/L5+byO+vV52qtaFr8O4N8D8Jfl83+plv95Ivpb4MDm1avGK3I2JPmNtZxhBQfmyDzzOITKx1TrNRADs3bncvYjXxrgfYEDpbXUfegHqERQm4KgyRpYddkqoHECbdag/kjz0mhghPiqBXEYRW4v+lAeJucyUXDYcgBOb9YI11vQesVkJ0nqsO+53PvifBkvABbyiKlvKZiYtk9MXtDM3ZAsEbXnEnk0tqqfkOxFIhqWMfedgbqq8vpAfpPHaTqp90qbVQlailUXLtaFlGfB7u0y+jFs2IpBFQsJDTOFkw+AJqRoldtY2COFrUiEuLbQW8/cnLW48sUGFFGswof34C860OjZOsj3S0RoLUJn8gPjzztAEczuDNO5RrMuQtyhUVCtxnwuTFl9FfacLgAAIABJREFUeWjnM7EsGkIwhGbnQVFzyTqwkG7MYzcD85sX8CuDxgUoGT+3sRjuKZwZlS20+dxwhiSFbMSC8Y1CaAjtE43pXmWVmttPkrdJnf4aOJj5iIjeA/AXwZPE3yaiPwvgDwH8aVn9N8Bp098Dp07/g1v35Li9AFgVk3hP9T3WwSugBByfk0at5QcBeQgTBBgo+5Tv6VikAwfcQgmUxVRPUO9/3y/rPwA2vSs189TbOIxQSfMzPaB9z9smacTU3xARxwl0KIGurBDeD/wApYBqKlYLPgcHMc2C6Qjcd71U7abr/U2Xap7Z7ZGJxhrNNSQx3igKS3UcN8ZbxgNAPm8FFAawyj1KKVgALJIj40tSG6JF4BrOg4YCm29iBB2OzscHzuQcBs5yVMVh6noPNU65X7TvoaVAjea2EOXECDU7qIPKOqPaB4Gae5y9N8A8LrUhKZOSHEIayz1gpLgsiDyBGpkkOBV80e6QwW91M08P0Hth75LJvPlkj8tWwT4uE6Dum0xJCAAmZUOshl9ZmKseaiyWPLnbRxBukw35M8/56U+eWDcC+HO3Pvpdu2t37SvTXl8E54vaQqGLbi4DCuGu1gDmsk6CU6cAYZrFjeE0Yy26c2OfVBi0auYqazmolsxlcMAuBp8ZqPIxMz/lkfBPzXCV+kMiAjTPCzEgFg6yBQIulgU1TSmgkn1kt6LmxUwFc4oKroQoB9IyCCi5GKKintKnYd1AH5ihqj4eAeyunLAK03ik7wC7Hpk/JKmhCzgujVpex84lqNw1pSS+KTgBv2mhjzOBnt0P7mu7GMfYNbz/FDxuLMK6gRoUs3ElqylGPo4pVIZx3SJqgt4aTJcWeidulFKIrQaFAJ9EhmwVlFwlN0QhaoI5KGijMquWtfbk+IV1g9AapgaQ6+I3LYb7Gt3H5Rq484Yf6oyzSExZGm6toeYG7vzVmLK+mpPFSzY6FUR81X09LwB4ChL9Zbd0XseeVt0XpZaAtSMBnvz9FGz6h90yRLrCSQA3+/xlHh8S5zCqCE75cDpAqKp1flhNURFpeskWLC0Cry8jMAS8zpPFqZqD/FPh1Vxybb44Op9bDOUip7SoMQylTm8eKqmr+lgAitBPWlbvK8UoPksxTC1VwtLyWoowppuxuikpqaYZDZqlfzXvRa1IVmcN0rGI+Ny0BMUyeY3EfKpAZh4ua7JSGACm67cGRH55PCd8pnQCPl2PRwIKWbOgGoAiTk2jFMtFa3I5eRqj2FpGZlbLACB0Gmo+uqWd4sDm6BA7s5w4RYEs8afCaITGQEnNRqyucVIv06PEHBrNAKwQ4dasGMbXQiG0GjRaOLEiahW0xJHJlkXVzbXKfaITk3ZWJNM6W2MhKZK1ptqPhppMnghCHeA0hNioEkwFXipL8vpOFi8KcMZSv7BkxDraJrkN0rK0HhUOhIwAdQ4LpbFYsWRVx6JEFvxZb+GkGFYHOCsmLlYLK0HYsjyW/kj9Rf5Mv9d1JwCb5CkwWFdQKsVp2uoGY14JWjKIgTMU0QdR6iqkPABAsypKYQAH5WYer8XEkpjBT127WkEtwavraskQAKg8UWSt0jR+She3YOTamkx0k0538EUpLJ2XXKukNragqJsdaKgmeB+gZpFH0JU7JyxXqK4ZzSFnicwhZMX0pNSmxhmmT+NVB7nlw0VxQzz04GAOOvfpVIA48V1QCHmyVQOze6sKkWkOiv9P1mVyu72GWyvQLCpmcl4vUzPy+k4WL2o10Uz6fop85hQnZPpe0eoBnFKMzi1dluN9Sj3CYntflQjXx5qk9LieLIwrVG2zy8CjOLslhRvA0OkYF5913+mIOCZGTsUSUN7KzoFmZtbKVlHdnxDLw57IWYapRONTNgSSrUiyeYepaKJUXY7zzGLFJzJQaTwAFMDVNOesBwEZgxEVLYFhs+MHtV43ZUOqMdd7k1m4UuN+ayYRUrR4EFVi3Mow9Inh0bODPtii8eI8g84U5WXqwDB4eI/mamaINeSFNDNbld4Jc3o1WSR4tTrKhiS4N+YZpwrbVC/aJ8OUKQP1fkT39Cj7ka5POp5kQ9SkYVum56sn2Jeh1bsjv7lrd+2u3aq9vpbFi2IWWnEhVPWdtEJ01XtOxHkWrSptzhRxFTwbRFwZCmS/HsDiWAAkG5Ki3z2bhSmbkN6+CaYcqrdK1xXI8jQXaHbwhYoumd9dB+oH7qf3ub/U9/y9awuvZsJWtE2GIQMCykpuWIZTmxKzcK4ok4v7EM/XoCScm2QRu2YRy3D316wU5nyBewPMh+kccIRPA5Bh2+k7IICrdA41KCsxh6d1BF+Rxi6u2ywcVGdD5odrmGZ5SyehZKUUwnkH9azwVcbzNWc/RBUtrjv48xZq0AiNzuCnaDRCaxFbDZ0rb1eIWkE9iTi802KThJElZmGuNMY3+JrqodwDbrOMWZiDhTl4DA/5PC4/WC1Il/O5XXQInYb1MVuh88M1tl83aK5KucR0z6J5djpm4dYK5l6H8V6VDfkiQVn/zNoXBcqKsbBP2ZI6vQHKGoZbgbIQI2ieKramwICpI189HobToKz0cByDstIDkfo3DC8GZZmhuAupsnUYl5yLtXJZcnOmWUh/5byOzfbt4SYoS8SOknlsrGHwUKyo9fEZoCwZD6ACZREtQVmVmZ8mJrU75PFNgCiaXXFDKvfNKrwYlJUqhNPxtweoqvK1BmVpoJABx8g1GQfKQC0N8EsiBKw/GKGfCZlwBcpqU4V5DcraPQeUNcskf+hPg7KuesSDXkgq2scHnH9fZ1lHAFDj0i2JFSjLnTcskzmlKuUvGJT1Q20vsCbyKtbwzZweOieRcrcc4JjfutWbXWuAAmKkG9qkYbdnKrz0oNT7rI5FnrMmNc0dP9gchMwYgu12Manx9i7DwuM0g+RY0TmEZ1e8Uij9iTOXuMeK/AaBEaMBWAY5leIHbBhKajixlVdBszhV1kZFmkLWIM7Sj2PWcC2WUy6DnhhaH8JN5vNT5MX1eAD5vFnSQK6PncsxUpl6tV8AeYwSBWImeZFG+8MNfz/KRBpmB9qbwiYu+yOtEOQBVFoz1b4PjPZM6ybVOl8xgfd9zpzZ735cNGRJcWxkdlDCHVLTD6bMi5Y6mSgEulb0R8P19mTMRxmTNWKzmt4PPsFm2yNebxfr1WNA1XGbexeg6x3UVbEskuzibdrrNVksOAOrWhCgvN3HEWq9LrUhjUUcRwYkVRBvIkLwDkrbkvLrK6HbR494f8PAgcGLc35jJ4m8Tz4FrVbCGyFaEW3LD3xVGxKurkGrVallkMnAfONdZlOuxXjXXeZaVFfbrIweDz3w8B6/wb73A/79zUeI2x0DvoYxuyHhegt1cQ5Ym0lQcm3IerVwQ/D0CtS2iKFn8hmgjKewYpPUjPiPuBZQffsnyhs1ZYoaK4zV/L97uOG3Wc0dGZmzQonFka5Duq50eZEh59kV0zpDuDPgKgkjy3jGzQq07/nB/to7vGzVSIbDcxpVjjfdX2XNjKwbIu6BOkzwZy3MB0/zuYWHF3CbFvb7n/J+uwbhbAWaHNef7KrHo7EIrYXaigV4tmI38/sf4vpPfBOb78lyrRA6DfNsxPhmEkZOYlFVbUin8m+m9+gfiRvyO0+gRhE2Ti8kIvj7G4TOwnx0lS2s6Wd/HE+/3eLB/zfkrMZ8btBc8fZ11WloWM/EXq8xX5RMT6iU4j+r3QU479pdu2u3aq+XZXHbpnVRkdJawEVFLJkZtJegq+OWK1C1wMJFyDjDjgGh1atKqhOSsIZtEwcWj0FgsRHdB+EmSMviqkEkgj4MOThH05zp1rLKujV8TsYAei4wdCK2KrqmCEEnZmDZf+7+VuDeok8BoMQItOLtmuWbJaybHHRMKuqxswyZlrTffNFAHzgeEtbS71ToOEwZG1HiOqKDka6PUAuGxnBRGJD7F1sLjKrAvdctYyS0zufmNwz3VoPj4yfL4tIABEZgJgNqVohEMADcWVNVkiqEdQO3MbApkNm1cGcN9KCYF6JikYqdgV/ZzJXpBMptjcFwX6F9Iv03lPEM02WqOg1AZOtrvBBh5I77aHtCsIThPnf4It1/RCVmpgj+rMG8NtBXbRFGPjfo3yBMP7A5VjVeah54xRcgWTC+KQTS45dVdfq6t1rr9CU3rL6HjJNIeecXhn1qan7gZtYl7T/9VbIDCFKafgwiE4q1G8c52V/RID0CjSEEBg/l1bh0HzFUoKz0Sbzd8bj5WGWNIjIgSZX+krs5Xovzfd6Y1etCAEbp+Ok3F5b4GMfrxHocA59/LlOXpmbWM+XoY8KVRBAi4ONCFT2dF4Vlf8jzuvxbNVn4ckwAZZxDBDnkfQdSIMf4hbQO+SiTBaAkoKhnsLiQ42XKlX4hMHCuANY4EKlSn3zpg575M9FPKQcoH+X6RqhZ7mcFUADUHHIf+IfTl+tU+2pOFqcmhhsPWnj+ukCZtVMmIWk9HK9/HKyLCclXaTocq3hBIvbeZ3UrQMA9o6in1ZmEIKpWMZZAmPPsdyYYdh30kqBljTwEwJZAzSXhBXFYIy2PJ7kjzQw1zgtJQuYndYuJzPSeJwznCyu1r/qUrKw0tjEss0UJBVkdv1bvogpFyhqpCYUp8YdBNEBmDzIq++um91Ajc3BGkwhxA8jJulOVMQsRNDmoqTCAYZqhewOa5Hyrscz2qSzTvTw6waPZRyhBa1I67uhg99wxPfpsWUTi7ZTnV7+aIvQQYPcyscwFHZzuj2g01DDzw1ppxprew14bmCo1a/eAPjiebAIQXJrgFZSP0L2DtVVQ2N9+tnhtJwtShBieE1JRKhdRsTnN1aWZK0Lh1m5IdDrXVBBQ8vZSXco3fFW/QCKYU7sFxpx2QxL/RVXnEDs2wUlo2gCAvEdYWX77Jdp9azjanmoqpDqUkjyeUsB0XHuil26FlvqTumakrsVI21QttHbphiiF2JqcggMAtzFQUwMighfSFyUmO/VjqWNJ4yjpxDwxNZbreDRlPopYBTgXvB+NzXiRNF5hLWNrFPy6ydbNvDFABIIhBMlb6kFBTQGaCG5jYJLr53jM3ZnNbggaC7+yUERMdFNlCkJrEVYGahR2bnEbjdIYLwirjfRNE+ZzXm8+k4pPQ1WAU0lfFSCWRrCE6ZzK+EstShrHaBRCZ0v/hX3drTXG+8RBU7lk80ZlKDkFwHdSoWoJygNqNpjPKvHsl1Cyf20ni1Ppt5Ot1rmol922MC8GZATLDdfgBW7BZ+63ckGOJ6z8W8oaVG+82oIQDYq8DcS1eEFq+QtvqX7g2E1yR25A3a8jvYx43F+BiceX03grY1Sb55V7k47P5nblAsg2Kmls5L5Ftjpu43q+oLErU/8vboEsYwFkLKR7U/xAeXFNFuvGXCi3OIdTx44yBserxKPPL6DdZUPu2l27a7dqr61lwW7I6WmRjCngKSvwZWMQpmmxDqkpfwJYsoULxgHzDJBCOF+BDgpxU+EUUjl4ehtpJpihzSpjBWi3R7zYgITbkQQNGC6ZX3KBcNx0mO/z/pt+QriQPPzsMN/rgIhMXRzWLfTuwOQs41Rg1VdsmoezVTGeJMYQLjdw91f5eE0/Ipx1UCHCX27ysfK4zQ5BluND3tv0sIPdpapGh0gEv7EIrc7Ub/u3LPToESaD+aJkQ8xWw4xTESlK4CGl4M67ApW+4DFwG4tG3p5+I/iWTkMNHnrP284P14zM3B8wyblNlwZqjjC9x7wx2aLYvmvQPU3FaHLJpoigge6JwvDQovkwlZJHjA87TJca3Q/YlZofrDG80cIcPNxao6tMdLdh830l7u/wBvf34oMVrn8CsHvBwVhg3hCiarH9Bo+j3bHLgQiM94UvdA1EDdgdobki7L7Bx7n/uy10L+fgUsaOsP+xFtOZgj6ssx7J9l2Dw08P2H/cZgtieERwnc3n71bihqz4+Os14fBmsRH8EefSi9prO1m80A05NtVjuAExjiKYnD5vtBS88gFQkRmIxrlI9QE3sx5RBHbHKac4g3NQ/YiQEJJyLH2YimBMJtCdYeRBpGkusNzZweznhZujJpdL16MPOQAYwcFTdRgLBDxVTR5G6Cq2kCstp4nXB4q6WhLTScvl2HZX+kWzzzqcKVAIAO21hT44Rv+p4sLpw7QsO69AWWoogVPV87lYXzgzE8OVmg1ocLl61DSG13EyRkCGKavRLczs7qlCcy2B4ZTtnhhGrg8OjaFFcNVuZ7atpV9mN6G1iierKcDsqpeP58xCWtamIOE4YfURob2SCdsQ9KTQXDl0n/I6NqdOAeV4mVtxNsT0Ec0uwK0E2dnPXEqvKY93JEL71EHPGmY3ZdDc6knA7r0W7VWoXByF7pnPJf5eyIJ9Q0AEuid+wfuilo/NC9trO1m8yLJAotLnFZGLvlIg8TbOVSayUQXVqKjECIhARjPvRAoGqoqi7zb7V0riJyovy+ERo3NwiaxhxCHFMlmRUN6RYD0q7ZKXlj14iZap9VN/q7LxHOQkcKGVC5m2jVzgDARRCbJOMg4pq5ICdq/Y/zx2RIAGoyVNJUCd+mmIHw4AhiR+oYj7mjAVxFmbYOlzj2c0pW8gIBi+B9N9mNCUCMiTWLr20UD6kPalQEbJWLu87ORxFSHoFEAtx4+KELmyoeoDQKe5q2/dXtvJ4jNbzlBIZqQCYp1iGnpuI8WTQqoaTRcmZUOcz3j+zC51ixaJMotWYqmKVRanZtuKrUWwCmquQFJaZAOISm2GbPeqtGq3aoRq0lWAUfKmJkSblhPcSqOZPEIjqUJAJjzKACtK8oiByuQp5/YqNHllsuGORqMQWrXAEoD4LTpvygNmnUewCr4jzjoBUD0/sL5RC7atV2nBoDzsWt7ilXUTFYBIoBBLNajh4KZvCOTKQx2MAlkN32roJJHYnu5fJCA0EcEiW1hR876CJijEL3SyuAtw3rW7dtdu1b6alkWN8PPhRvp0kV58LqIwgbI8YqBMlZeAPzGhC4OvCtQETViDt/J6S2sm0bnBh0oMqICYaHbF5Zkd1OgXbFTkAgdHqfQtnTs5z2/Z1K9MnVb6n4/nA7tzx0hJqWQtqU/+VHMQ5XE5hxhL5aLnTz0G6IHPRY+FZk5N0s86HpSugQuVDonAyKkqlkrn4hSLHyWUogv5HFJRmJ4VY1JcgB5UTi3qKUJNATWC2fQBeuK+mV6XcnHnoeYA04dCaQjD5zF7dhMquLeaPVudaWxmiSeEAHMoqVoEwPTcj0Rfp0e+H8kDRpaFnt0E8oDtI5zEFtTE46oIBYQGQFuFMKqMaE3na3cKZgjFslAEPQra0xf3iAIyWjT1AVimcz+rvbaTRUwTwAkm7hhjKXdOAU4fciUqYliCpk61mmbOe+DibIlo9J6rQavgKc0T81mqyuURd4K0vrl/fzSRtE0xxevS+X7kBz0il0VTCIi7PWizZl6KRNk/jnxzt6uSbci+rV6Ap2AMczlUrtCCwAeuIvJNACJVsiyB0apkNVdByoMWFUHvZyGgkeuQMCUhAtulYBJPROcFkeg5NRDXtrhoFe8Cc1WU/6PRxX2DuHhgjETK0ABA0GCOiDnCyrH0xHEVvZ+h5ph5Q1JTcxFKCusWodGgwNWa9ViGRsO3KgeQUzUnKSXxiRRRFbi1YsUxgDMvMXKcJcVSouJYhd1HKBczeS/NATTO0FPhC6XZY3q4gl9JLCMF1yU2UsO3gxFXhIhjKbqAsoIBTKPgumosX8K3eG0nixe2EPLNs6gNSRcsVG/d5ymSHRHH0DAtCXUBjoe4SmYQknmYplLoJBwVx9mYxBoVQ9mephlqn3JaFSENwNkCXwKcmF1h+yIq8HKpK6HDgDgIJVVW89KF8wDg8vuYFMykPHysuSRCmeTEstDbMWciKB1bEWdDZKybZ8IHOc2c5uMLARoYipx1OIT7M3owCrOGcBNBb33uV65dSWTA0k+lFOgwIMwuZ2kMwPUbs2fmbOlX90Qx1DkFM8Fvar2fGS69q4oCQ4DeT1xIJZO52vWw4EyU6g3UrlAaqMlCjWVZwsnGacLq0wB7JZkpTSBnYLcTVo8FRTpKNiTEzA7uVpRrRcwhYCWTCM0CzxdiHTk6mqcjdOqTlPp3TxzWH7YwO58tBPJAc51K1AEvSNbGEFsx1xOUq4oN59ubFq/1ZEFal4ewJhmtlmdl86YpxCQxANoCSKnQE9qb6U3tGL4du4YzMMIHUZi8K/dCa0AXvVMArD6+6rIKeWpxxbR35HyB7XYNguAJ9DAVLggf4M87VrlOO6jh3lIVC4DfKtaUqtZ0DnLMcF5wInrfMj7DFd6JXHVqDHN1rAqNIACEs6YkB2aGe4fOIFR0deMDCwoR6qDhhRuBXIRSCrofCxQ/1ThohVALCq35mNFqqDQ5S/9iJ6lT2Uc476C8B+2L+rc7a6A8WzVuYxiZCTCOwlAOZgKA6bWkPBX6tzsY4W+g2cFvGoz3LewHNvfL3WuhBsMUdpUL61eWtUblWO4e96X9sMHhbYXuacJZEKZzBeUi+kel6pSRlsB4keDe/DArF6FHjemS+3u5SgJMuqi4G4XpsoE70zDbLo/j8MBg9/WI9cdV5e050/UFgXsnKyJVna4U0D+s5BNeouqUbkBx/xm0C3oQf57+5GIZWSazUfJQhn15GNW6cA5Ca0RhLaINL4/DyLR1njMZscr3583uXfKXIG9zodLP3JrTBFqvWUg3xUOMYRKWpAgG8LFXq0xEk46lHz1CrmZVlQtQcXVSnbLr2lwwBaBMDrIsT5rOMZfndleWpW2sLSpnAJPviOBzfV48iAI2k/MIO9bqND/2zhISnTIxRCXtmFyaw5AnG3JStBZjnnAz5d04scuUxj/tZ7fPlk7WaxFSnvwyaBvEcUIcRui335TrUCDwsbHV+Uv9iTU560GjZ9eDiNdNE9k4c63OqoF6zLyc8XDgl47znCGrQH5QerEskx89fYbwc9+G/nSbxzWuW6jrA0Iah1QM6HzhGpVy92g1aJwzmM5+vAOX9BuordxT1jDhjWFh5yww/bW3Mbx7gfaTpWtFw5zHMWu0aAL1E7ODVypy//AP/yauhg9vNWPcZUPu2l27a7dqr7Ub8sKW3iZUYhcvo4GQWoxRRGUYQBXrrIFzOXjKh3oJ/AZQuTCFDIaSL+p9wWwkJTRBiAIM1Epv6qyBIus+Lw7zRbVYZXYo8U8Cpcxdq1yCX+uBpmBuLjdP5Dk+gHQs/X5VEFS2eBRKIVgpfY9aeD7IQ6VwQ0UDUCu+Q655XRL+qo25L1IxWsj7XBTWpaKw1FcpFKNZMmS+WjcE0Fj6/tzXfuDgKFVFZ9GopWWYXMEvwC746kwWFZlvXRtC1nCGwJjiLqR1QvnkVj0EK6mhSD78+Rmn/JKZOF0VYJYXczTVhqxXLB0AIHgPdXmBkFnChb/y3jkHOWumrFWLIP66erorJvy+R3h4wf3+gfBBblag6z3HUvrCwRmvJpYB6FogMT0nweH1GvGs1IbQp89AXcvm9fkZL9yyu5FIcUlcuuRGhTfuZcEceIEGN8yUldKG05sbNJ/uQXOLICXqCIAa2MzN7oaA0MhoxMuzDFPOPKEXG6hryZwk01hqVtQgAcPzNdT2gPDsiscIQFg3/IBOjt0Nub7jw44h3EQ5C6Akxan3E/ymgfl0l6+le+McvjNok7t0toa/KByc6roEOGNn4VsDfcXLvNT1qHnGk586w8V3k4tGcJ1G86zD8FaKT3ElKUXk8nDXcv2KGSPsLmD7Lm//aBAYvQSW+UIS3Nv3EDqN5gdtZvg+/JH7ePLTFg/+qcoBzulco33m+PxDzKX6vuE4SvNsxlRJAYSPbj8FvPaTxSla+Rr9yPEGzW/i2rJIgc3nBDjrmABpUQ8HEM7Ez3zylP09p0s2wxgOplpbIS2FQ+IodZrVv0OF1Oz44YpEoGHOgT7ECHfegkKESYG9xkC1Np9rRhlqnf3enLkRvZTYWoTKH9WNZRToZPI2ENIWDnBSoRGUAKffNCXI6gKgWUszWp1z9tM9A+VX0PsZ84VMfj4ARjFlfkorS9YDDRBWtrBJrRtE4hy/SvUtaTLsDEsKyoQT1g3UNIO0gpPgsNsYxg1MGu7M5hqK6VIDkpL0giw1fYCaI6IhjPctNvs0dh6+MxgeGjQfy3UwCu7Msop6p2ErzEoKcCYZQXfG49Zai/5NwupJovgnjOecfh3u8UiagUvIlY8lwHnGAcfJRdiVwviA8nGUQOvVIPeN1XAbA3emYZ82+bqPlxr7H4tYf1TzWRAAI3wWcRHg1FMEeYPxslgZ4UeBz4KDg8sirvy17wvTFQamsMdQUnbJVI8BcRwXFkfex9OrvG5UiuULfQAdJKg0O2B/YP7KNGEdeqbh955p5yHB1E+fFItCjkUfPS7bpaDa/gDzVPo4jlDXJcXYTFxIloJX+pNnOb0bnQMEtBOnGfTkCnCuVNkmsNM4Ql3t8jmGwyHT3+dCtBSIFc7SVCWbZA/sH36S07RRAFkqTc5yHvaTloOXs4NO7NDC3hWnuSIW8ryNc9DO5/HQ+57f/tNUNDsSZiRxqSaxpu0eGEeEfZ9ZuK2VYGmMsNZkF6D7QcOuUjW50uyyzoj9wC6Yy9txQvNxC/XpU7kXAtrHnD2CWcoGWKNhq2XtY6mSvbrG2/9gD/OJiBcphU1noXYDug+lMjm5CT4w+REYwp11SAeHCwlwNu8/ReZASe6cVjDgQCeudnxPA7j32w26pxdoP9xlozlazUWDErAvotnELk8/Yl0JQ5nD7SvJ7gKcd+2u3bVbtdfWsshKYTKLHuuIpN8zvyURwqFSZlqtWCW7sfntBa0LNDyZ9SJ0Q9YixlJ67ntWsAKAkMRwm8Cp3LYtcoKRNTHouD9di9iHAkeHmP7JXx/HnLbEOGVaufDBh9zVrmXdkFWH2A+gpDHS96DGgi7PMzi9qTLfAAAgAElEQVQn77/SJeEhU5yS7YesD5IZypNlIelmJaXlcbMqoKyaBi/peQDwlyuYT2ZO5VVFWBQjcOgX1yH/tl6XAKekHfHwXtbAiML4DcPYlpR2jesOtO+htC4M4F3L6chp5r7JMeYH60VZOQBEGIR1C7Xr2e17/LT8eLbmQrlkpT645JjFOMNvWhiJT7D+BrtiKY7hzztEeePv32yxniSdr1RGd06PTskXFnclGILZe5je5DhC8/2wAOvxwTzc199AaA1sY3OgeX6wxvZdC3tdXM/5ooG91rkMPYo75q2C22h0n06YLquYxfdvX5T42k4WJxtVcYoUh1jEJqpVDSuHpQDo8X4K7kD2s+o46ryqyG/yPqtjWcO5/5RD3x/4ht6KS5Gi0usuc0akFldtIbw5DGXimAoRTj5HAXolsFnqb+p7XHfLaDsxoCzFXABAjxOv5wOCkPWoYRSXgqPmGRgmKl/hYgWVAmsVYCqBpQAOJKrDzNyhm2py2iuRULyZXUjjkb4DTIKjq9gEILGa2bOaOQB/3kJH1vcMErx1Zxzg1L3JXJgAE9K0dmks0xwQGg0LBlK1H5UHy1+s4M5sdin8xQrjgxbmYDCfF1IdhAi/tgiNymQ90/0OURP00wa7dzTMXiZzw4CwVhEOb3Hf7KHcm5NwcLqO4dfNVqHZa+zf5HU2v79a4m/Sdg86uLXisRE+kOGNFrtvEDYflWvQPzRYGSp8FhKzcC1JPKNB/6CCsdsfhZjFqZYsixpI9pyCsSiptehv3riA+NNASTPNjsE4dXrtBHdk8qdzcDFySi54gXWnVFWSDKxrQGYHNaSgZLUP7/PyEEt/GIzly6eMQXSef6/qWEDEltQ4l8xRWq9KZ8YqpVf3IUiajSZXNFlyqlQv/je9L6nToZqkK0bz46YqCcW0Hxp90TQdWN9DBUnX5uWar40PWWpPD1xIRpNbwNvNwUNVb3E+rme06eSgBlPGEeDtB1WK98YZ5mCgRgdtVa6FISklIFeWmd4jGgI5j2bHrF0AEE0ABS3s3kLq21dFjvIQK8d1HPbAcO9mJxPENJcUddVM7wAYZjaXwKs5eDRXOh8bAJq94r6loLyQXpMvAd9mXyajl0EDfGUmiwXbd10cVhG1LNZPjN1tU9KsWiOCpQ2p5pgAeN1KVfzUPkHEKVdjCgu4bZiS78qKqyQPosC16+kmWoPQ8f61MYsMR1qeLQth8CajOQBbFXyR0Qv4NAKL/6ZsS+7uZgV/uYI2Omc91GEQKkIeg3Ah6u2iExoaA5rESqr6HbsyLm6lObCoaLE8YTJysdrRuecAtJx3WBnQLIHCtUVM3Bm6gT6IW9ZoaPBkkyDnvjOilRHLuIHZrvW0vPujJibq6RnCTRUXSGh4WSrI85sW87mBtgq7rzWQZDPUHOBXnA1SE/drPjOYzzX07gzTGWWmq2RZ6N4UTo3qNprX8qYXy4IZtBSmM1mpsSd1aOYzA9cp2E2DeN7m850ukY8NANNGQQ/6pGWx/YaCGTTGywRDwI9mIdmCNeuYVu94GTibkdXHs1IZ554j4g2lcPQDQ7zrnRyDnzyLEsP4Ukg2TwztnWYQFUuCDgO7P9WFp37Mb8I4jkV9bJqzL5wti37g401T+eSBYJq8fZ8xIjEEkFJcuVpbMvseOgTOAMzidg0DMGsp8ApQqQ/jyP9f9zlmUVPQxanELNrHlo8fwkK4h8YJcZpL9W/VVBoPIJ+3EXVzQKwNrfLknSwhZQ2oHzmjI9qjRpjFMc0Luv5O042YBVzgWMOuh41xAeFW1z3s7HOGw1z1HIMaPc4ANI8l9iIuD4jydWpDhN0ZqKsDzj7YoHkq8SOJWejtgLXEC+qYhTmcill4kJBh0r6/GbMA0D4eYVsNfTUs6BfOvrdC+6S42cpF2OvpZMxCeYvVxxP0WFy3lykku8uG3LW7dtdu1b4ylgUAPI/f4rktnIhjfBF94J2VYyR9jFSc9cNotcZJiIxwSlokFYkueYaWL7QxsjxeWO7jh9X3U+cgOIQk7Vircd1QZPsy+xNYIlDNIUOwKQTm4NBYxrFCXLC3f6mt1kZ5xWOqOSFJX+05+GpNFplYt5ownqc8lqDGRNn35u8JilyIeQFkvs1MmvO8fWrxe1O8QbHaFpPgEKKvYg4vUgzT1T60uiFQnFXOlC6fuR+cskw3KpHPQKQE+gG4DiVaA5r0Ij6SyHsIWKQ+oRRvn1wpWRwldZrGyq8tdMPrxbrfIQgn6okJvR6PFLNobSlRbyygGFTEeqOhrON8QcqCUZ7RRyj5PTW3MTcEedTsOWYxsdqYqcYxdrzMmkRoY+DXXJnqVzpLFEbPsZFoVM4I+c4gWiYVms4VOhn3aAi+1aDZZmh3rfqVlvmGhLyGYd3TeUJrmoV+a2p+beE7Dd2YjCh2G4PpkuBXZrF/NZvshmRh5FZh3ijYjcH0o6ZIdrIly+IWAU4ANy2LikKuqKiXG/g2AU5IEG9Bmluvl9KDrQVNdvFbbGwJcFpb5AuNgT8R4KQ0MWl9I8AZrQGGqtxcPmNz4pLGmEuVqZ5cE6EuBLcSI0JroGe58dNvrUgtJt6ejYZtDcgpxCp1SSFwEPMERD+Ph3wHgNAZqEPhbAAgTFk+81nEVgMHHvc0MfiVzQ9UuPGgHF1zo+BbBTUa+JXJEwMA+DYtS4FXjdAoPi9CuXZa9rPS0JIG9Z2WDInHeKEKfkITfKegJlsmgIq8dzxPDy9zSUQp6khBx1gHrqvmO415o9BYBSW6LPOZxvggsmyjtOlMQU0mM28l8hvXErzlySMFWblvNw713PbVmSyyUvhR1eXzGLHmGcd6IrFaJwW6cjrvtgFOABhKkIkZnAYuJIsq70/teg4m1gFArXOQKA5DfkPEcToZ4EysXOkzjUOcJtC+L3DkwKlTIio6pQAHBUPkYKqI9hSGMHFPJJiWdE/01YkAp/OIle5H+4llroUQ+K2fzm+cmHviVIAzjQeQz9sAGZSVxlqPwqieYO9BWMGmGWrLAUeafQ5wqipYt1KnA5xaApyNXwY49VUPNZUAp7ru0UiAU022FJLFCBoc9EFDbfkcGoB5UIcR5+87NI9l3SrAuZG3dh3gtLvTAc7EXqV2h9MBzk97mJ2BfnbI12z10Rrnf7BC9+lQzmlqnhvgDK1C83SCHl+NKesuwHnX7tpdu1X76lgWyTyPiV/hxQhOWMvmsNZ5W1Ihp2BfFcFJ1oDatiovN0yht2MZxZjg6D8MBGdys5wUT627sh8Auh9LPxLiNL31jWbmprRcM8/GDxXBed5BH1HthUYzw7a4J/5SZBr7Ppfff2kIzvMO0/2OZRHPDNrKjfWdge800tYJwWk++uEhOOeNhh5c5nF9WQSnb3n5AsH5ErR6X53JAgmYdct1ibicXKvCvBwUSH3OiL9tkGnmgGWJes1B8GU3ETACAEShBdRH8RwJeNJks3gSJXq8bKZWJes/bIpFVc4haqEb1PyXJxatAKNvANy+jMbHZkWz+VxnlwEhIloOmMeqv26jF7U4X2rfJO4RFS2Ady/T5jNCfIIcz2A2pttv/3pxcKZIdbiZGqo5ORO/JoDMsbkg90XF0ykcnQCgLi847jAX8FSOWaxWHOeoOCkT83V9LHV+joXUwDSDNmuEp8/Y8kg3T4I31+nIiiMz9lVJ/TTlgi7/hAud1NlZ5haNFWN2GEeotgWlfgBIPJ81x2c6N+raUuoMIOz2he8yBqAVC8kYjilUTOKZIcyYwukIsDzB/rAcB4CJgYfxNNx71ZWxTuXo52clLpSOESJPZrUmSmIWS/EWI9wlwS+yRLRZ3fD3E2AtThOoafg6pfXPNiBrEa64vFw9fMC8Js7DPziDupIYifMsqeB8BsKhbXiikMI8StQAaRIfJ8QzQcdWMZxYEy9rLkOn2RUr84OPT44fvfWoTPAriW9cH+AfXUB/VM4pdg0TEKWWOTgV5nfvwX64XWTM/tH/+9dw1X9wqynj9bIsqkmCbMPBvIQPSBWg+z30W28iCuOTujhnEt3Li7wseg9arxCutlDrVQ5geeGwAAD1sz8JANBPtgARph9/BLMdMSfi1P/rO1AP77PS+DWTsarLC75hH96Du+T1zO9/gPmbb8EkqbknfOGmf+1fRvN4YBy/GADzwzX6R3yhzv9gj+Eh3yDdh3s8/ZlLUADu/d3vAADGP/pNtN97gnC5hn68RbjH4GP9/Q8RvvkO5osWVohaUzBwevMcw5vlTXf2u1eY73WwH28xvcsExc37wuPRWNA0Y37znM/jH/8uAODZL/1RtM+k9mDgGoP5QsN1RSbw6bc17n/HwxxCZoqmENE981i9t2NRZyDT6iEE9N96hPYxB+L6Rx1AzOp09h4vS5WQbq24VuKKz+nwTov1ByPsdz/G9Z/4JgBguK9ADmj2EeNF0Tq9/glg9RHrZQS5s82BI/6rTwMObyu8/Q/5HiEf8eSnztC/SXj7HzBb1/7NFrt3NJpdxHRGOPtgk8dyOlcYLxTO3+dz273DD+Hbv/kYf/Bftmj+/iO+/g0wXUacfQ94+jM8Xs0VgeULgfFNefFcTlAqwl03sE801Le4X2/82k/Bbh2iUZnlK2rC0283GO8Bj37bofuY7+ff/7fv4xf/1P+O3/j1fxVZRf0dh/X3JRsSgfmMf/CbAATC5v0V9u+WyWj4r34EmLLicSai9j/6IUfc46Ev2h3V2yjK/7FeXu1DPeEJIO4PgCLYj7egfkQzSMHVPDOztw9scaR1vQdd7WDS27ofmPhEysXTsboPdhzpr7IFzeyh9x2gCPrTa3QSA1BXO5x/t8kaHwDQfrgFtnsmjdn3OcsRhhH68Raqn0FCSZcsAQtkhTAAUM+2sNMMut6hSanTa3lYJMWZ3jFBxvP8D3voncCyRTnMXtlcDQoAyq+xfr8HTQ7NVWH70vsJ6tmuWDKpTiZGdD9oM1v1SiaTZt3APOb+6J1UnbZcyJWo/Tazh352QNzvsfkeT47tE5YCUL3DamPzg2L3Ddorx2nPlCGeWfDHXk3onjaZhZtCxMV3DVZPTCauWU9rmD3HLNxKFwg3gK6zcBuTsx4pRkFXOzR//xHu/y6fc7AE1yl0j+ecdbCHCIABUeN7EovpVogaMPuIZhex/4Qn7c17W1DP6u6JAQxEuKcuMG8U1u/ts8Xz8HdW+HX783jrn/gyWbyvsXric0rUt6kWRQERWD1x6D4p1tgnN9kEntvusiF37a7dtVu119ayeGFTVSAxKajfWEcxsCd9ghMpuaXgYCaDUeVPtmdl9iqmo4iJumtF8LSutHwsLSrqddDzWKU9oecksIZIBXthFBd5JTq7Gkyl1DLIWn0uEHlpneesu1guLYpoE8CmelaX14Qor6tgCMEoqKBY0QsAAquaZ2IdIJMVk1AXFhV0xa8pVY6fCsiiFJPlcUhxGKq2N4RACmTUgkMyWInuUxXEC2BkqCbmbkjHQeD92OXYRqMQTeBzqa5rNMTHStun60iE0BReCD4O/x7EbPOW0fiI7CIB7K4EDaiZ+y11ZHzfaCrV0Pm6yrlV0pnBAKGLi4wGjwFKNkT6FYxUBOjSB3CXbt1e28mCMx/PCb7qQqILY/imSwhMIJehRwA13Pt4H2l7IkKwGnCVOA1RFrjJfA7Wcp8kQp/3IyjLusWGS9A5KyMXtzMIrQScWovQir/fNvBrhiqbJMDTGA6ipVJ3W2UtWmbbrsutAYYKh4XWqa6213n79FvaBkCe0HyroGaBPysARJw2bBVC4OXzWsGdW5g9ZfQgBTbtlTUZBVunaUNnoAXBmVCXoSlcmVHGJbSa3bHZ5P+jlMOHTpix1xyzAMAkNXKfzBuCnhSCQdYUNb2IBDuD6VxhLSlamj1cpzGea2wSL2aj4TsCBf5MjFc8Lhq+KyxYKSUJrTBdRjbzwQ/reKFg9xGzlJ1HSuODvGw+A09qhiQuJLGFNDZGQY9pnwquY43S0OhMDDRvCHg4YDrvshsynxNMz2NAgWUSub9g+cI9FQRn5a7dpn3mZEFEfx3ALwL4OMb4s7LsvwDwHwL4RFb7z2OMvyG//WcA/iz4Hfwfxxj/zu27U9oLhZGnuUTqp1lKuOdlzMI5xOrzRstqWSMiKdBhBA1TQVh6z9mBisAmjoympHHKk1VwguBME5UcS2+HrHea8uaKCEbedHQYMos27Xs0T7p8bgCgtgNnTGJclLOHaWJOiioynwhdlDUwtWUxcEl8HEbQXmIqWb5QIzrPDzcAL+fYXE1Q+yME5+yhrc4+9KpVaD7poSZXcWpExl4k+QMg67xGH6Cvh1yObogfENVqPhegSB2OFmqcc0TfXPE6cXYwz1IsJfDENDqo0WYa/KhaNFeO/fVEMjMFjllsJygXoa7FSQ8BzTPGqqhdiU20ipj8pjfQ27KcZgs12bysTdbiOOHse0D3WOJahieK7skEL5mmpHJOAXkCcB0Biiczu4+ZpMY8G6HGmTVc03XVCl2rYQZGhqZx3HzscfjOCpsPS7bFDArdE18si7Z8UgDapw4UymOvThDfP6/dxrL4GwD+CoBfPVr+38UY/+t6ARH9DIB/B8C/BODHAPxvRPTtGONRtPKz24LshhfwZ/ScfkxptMYCowY1dgHlpbZlZmf5lE1zi0IzBxHv9ZdrKKUQLiXd9b5iS4JUCdg1lnEbZ0Wfg3Z7hHtnINE6TVBp93DDtP5VgNPfW2N60CESsO5nuPt8LOMDhjdXQATWv1fASGbfMydmDZ660ojrjsFKiQ0pcWPe32B6WEBZXT8hnDN1nXvI2RSTqjmFU9Pf54g//YBvhcNbKzRX/F2NvF931sCvFNTID/T2GyIFMHpMF4ndG2i2hgOqSV7PC8OUD5gerGGlv/MDPu/53CBB4PwZ2+FuZWB6B73j/Y5vrNEqQO0PGN/kc5su2Qqz+4D5TOW36vYbGt2nrGqe8AN6ZDN99Vihf2TQfCTjGCOGt1oM93Rm4Z4erXF4y8LuLQcTm3L/zWdcMJYg3Alwdf+DNZ7+TMzBzGDZevBti2ff4u3tVjAuERgf8P7cOiKYiOZaobkCtt/ksb3/nQ76YAAqAc6oFbZfbzFdEPSwQSMvjqtvGnT/yhNcP36Q+zm8AUwfFVCWEwSBW/HxVx9Z9G+VF4r7e7h1+0wjJMb4mwCe3HJ/vwTgb8UYxxjjHwD4PQB//PbduWt37a69ru3zxCz+PBH9uwB+C8B/EmN8CuBdAP+oWuc9Wfb5W506DTGjDSlxOBy7GqIbkj+P9pGtDWHOotmDnM88j/xjvHFceJHBS+slbki/PIaaPBdEJayBLNOD57ee81mwhpyHHgPq4AolyTsnhXMJ0SgcFczFWOEZANDooSs+Rpodc0a6wvG5kMRzPnNKpvHUg88WhZoYZ6Em7rMSyjpz4BStGj30mIB0ETQF7mfNURH4M40HgJyCNT3l4ysrhWREUGPplx7ku3M8RhBVch+hR49gKBf12Z2C7dntSKlDPUZEHaHHwNslkJwP0EOEGWJ+g+vBwx40c2bSsgAsan5bp2UJwk2zQ3NFkh7lYGYkdj2SRWH3kd2QWODV5DgYbfaA3UXY6+I2qZndiOTiUWArKpLi8ZB7z+4iHj/Z4NEhZlfMdwS7B6KK2fUBAOUICECzizmOAQLUS9j8r5o6/asA/gUAPwfgAwD/zcvugIh+mYh+i4h+a8b42Rs8r6VJ4rY48OOWq1lP/JTIWUJ6CF7iGPUDU5O8ADwpHC+Py4mPfLz54D2HnPiLbBSP/5cbseozhVjGK/VX+k+hnAOq8aP6nE9N7p/ZMZK+ROkLyphV/5d+3vx90Yf8B9y4Ps/tw3OWVykFSg9ovbt87OUyVOtSIFCgxRiTl/sg9e3U8QNV1+foDyf+X/T7xad73F7JsogxfpS+E9FfA/C/yr/vA/h6terXZNmpffwKgF8BGO594/cX3UwxvPhme+mHuoJNJ/IUgRjfXPcl2o1JomIpWjBdhcJkVf0eZbKoRZ9jCMyJ+XI9eamWJ4yqL1T1AUC5mauhzjd2FpeuxrU63+MJ6dYtYZRimZwQ6v7Kd8nMcJ8AaOlvwCKGRBFQFdHOqzYS64n7QDnzkfpVTxT1soiSJUnjmMY1UtknuecMWARPFtXklMdFJrB6bD5ve6XJgojeiTF+IP/+WwB+R77/OoD/iYj+W3CA8ycB/B+vdIzj1GlddZrSpUDBRdSpS1Kl2rSqOq3v0ozRT6nTziDONpO5kFKiPRJKvt2YzA6ViFiUVszmlPpBKU1qoXqbeQUAIKxsTjXatskVk6qxmM9Yp6JJDEcrC2Mtw7IlXcorsy6rX1tQX9K8ABBXNpOwAIBt5HwOwgAFFMnElNZdLfcxn2koJwFOnYJkholfpKJzvGSyF2UV5vOqNiNYqGtbTP0UoI6RCWsGDgL6tZFjGRjRW0kpQ7fWi+Ce22iYHRMBzWe8znihoVxEJMMBTmnjfYJyilOSKbM+Rtb5HA3GC4WzShxqPtMYL1SulXAbg+mMCw/nNWVy3TQu47nKxWWpejQ2FuObPiMzo+EApx5VDmZm1yMCw8Mo5xkRbUSwjGFJMHC3NkgFXvkFQYTxQmG6IB53YT4f7xPeevcphss3cz+HhxFqVtkNywHONU8geqLcL4CxHrdtt0md/hqAXwDwiIjeA/AXAfwCEf0c+LS+C+A/AoAY4z8hor8N4J8CcAD+3KtkQu7aXbtrr1/7zMkixvhnTiz+H1+w/l8C8Jc+T6dSey4wi1SuCM06FaoAteo8+3NLxk0FUiIGu5A18AIOMlpzlSi5ItiSyqSV4pJlOX606gYoiwFHmt3MhMmwmmnOiPkeM0CrsXAr8VkzPyWXvsfGCI1e6S8DvgowLKYiNqNyXj2dYzAKSpf+JoAYjEYMAUGQiKn3vlV5DBL6MbQMCEqoQrcG5o2GIcCtkvUA6PFIznB2OVDnWwUt+/Uta3D4hjKILKme+0aBXISqlgeroZXKfJKuI+gZUJ55JZMJ79acIoyaciFZ6Pl+cCtW5EqWVHSBVbrOKIPjuK6DoJzwTVRqXb4hpsKzlPsAuRfocoLvVnLdGXDlOuK3OTiYmVyktCxcOEBHzMFCeQJdcNrfryyUjwiaoKWQLGgF3wJ+xcdP19KvgG/d+xT/91mxLNwZBzATKGve8PH8ml02X/ULwI8Ord4L4xZV6XeMkclnF2zXR/Dmz9rP8XohMCCrji2kGIYu0GMAi+95WcWwnZtCxgDUDMvZbKfqGAFMPhOPfGrJjERFZRLL0Ogl3Dsm+DeVvHuGVwsNX14/wZhP3DxRYOE5ZqEAlfzoRdBOYhtVIdnCn6/jGzHBl0vf+VO+q/L/Au4ufeTziYvjR13GPUX5KfADluIGSc0LMSKqFC+QB9jwQ1b+KhfSpN8LfBoAoBWUihleHjSQkJHBxHJuKZZqpcM6QrcegdjtIF3Gk0LkKoOUyQgCTZc+ZESwATZmmRyIRvpCaSxL/4HIdH7N8p68bXutJ4vnWhYxLG6evH7in4AvD9jzglc1nbrWUBPzOpYHQgngq8C9M9fDNEMNCfgvacmjYKgaPQdLE+0+AJoDo/kAIEaoBLpRCnqOHIxLXA8hcpzC88SXWaulL2ooPJUphaoHB7Ov3uzTDD0YkU30i3XTd51SqqGkJVOKlDyXNas5QI/loTJS7KocQ6m5vzKBxJgFjGmcs2WhXAnupoBdsytpWnMo19Mc6uUWamRukJQ6tT2//dUUpQ+8nd0RTB8RK7g3Q5xlPReLhTZ7mDFiqoKHZu/RbBWnQSP/nxpPzjEvayQtimmGu25g9rwfNQPRcD+aa5XHKwUxg1gFc7AIZGAOCmoC/JWMmYxnVFRAWUbBbrl61uxLGtxugf/n6dvQ1XxhrxTMnicJnqhl8nQAeUJzFYs1CGTY/G3aaz1ZACgcF/Wb34diEXgvWhNhAfe+Nc7CeVGhYo3JdJNinoFpXuiVxhAyziIxLMMH/n6Es9CDA00zoy8l0Kd6ByOmOE0Oqi/an7rnByqVm6uDEOQqlfuSz3d00ErdxFkMDuZwhLMYWBNVi5juDZxF0l6NaSLweQKh0QOaYAggr3N8uLlm3IIePEwv6EQXGQMwTMWKmV3O9unDzGMMQPdWrCudj69NuYH14PJyc5A+Opc1PYMlKBehh5C/A8wb0ex4WXoIbM+ThDkE6FHnPtDsYXcBdlXo/U1v0Ow1zCGAolpoiCZLJy1r9gVnYZ8wBwb3jS0xu49ohD7F7iJSmjRZUMqztaEmxq00n/L+7GGAPjiQVRmHE6xGs2Of0PQ+33vtVcT7n9zD/W3lVmhCcx3zZEFOAuYjgTzQbGNxoV4SZ/HaThaJIUptGI4chC8C0YO6trAutS3zTmgNdcbrxmlmq6BX5RNYZEPCuaiKi6iwu7+CUQrugvH8zfk54sUZMymnN+KqY1Ny3cFfMGxYP7asBv5YLA3JhkwPOjTgSSFNdPP9DoOQ35hdh+mBkN9MHsMDA4pAd8aw7OHtNdaTg7vsYLTK6ujqegd/uYJfW1hX1ccA8JcdhkeFcs08XcFfdkxyc4+3bw5STyLkN/5SzkMslv5NVgsHAD0wOGm6MBwnmHgcdl8j2F4jWEL/oFhCwSrQfJ5vcmaS4gdzfKNDI+bz+LAFJN6RrJgEG2fyG53XHR5aqLmDfdxk4qDhvoJybDFM55Rdkd03RPczuXsAXM8Vm6uGMF3ydebBiti+azA+IFzIsumexf5NjWbH2qNJUhAQ8ptLyizciTPzbN1BfWuX+Sh8A8wXXOuRINz2mgRHUZHfXEwgHeGvGjSfajQ/yzPL/ncu0OwMoqI8NlER9m9rjPeA1ZMiFbD9BvBv/vRv4+9854/nMRjecQi2SAHkmMUmgBwhWIVDRX7jX4Kh71VBWXftrt21f87a68XBWbWacxMAwn6ff1Pn57mQjJoGoWLY0EcAAByMSURBVB9Aja0Yu7k6NPEuFlHhcq76LYkgTzMXO63XvE/h0IzbHWi9Zv7O5AK0LeJ2y7yWUlEYr66Z0k94HIOI/5of/zrHO2IVbG0bxncQMYtWwnqME+K9cwZnPeX9xPsXXMGp1IJDM/Y96GzDLlLig0wcoevVgp08PrvmMvtDnzk+416qLrVml2YtjNkff8qL/8WfyKZ6EiGK1pSSfADucgW9HVknREq+4TmwSdOcBZhoFqtqnBDPN9kCim3DZv3sQDvpj02q9IYDu6lQcL0CDj3C9Rb04+/K9paDpzMLD6VYiDtvofuZuSTErVGT5yrV2SOubKkw9cxk7lcWzftP8/nGzYrHu7FF0wSMS4ltw7oeQClEfP9DbP/1n8LmPVmuWSHMPBsxi+WopoCEynTrhCvR7Jr4CHtw2L/N43jxu1sOwhqV2cKghWejtdCfXCGKlT1/+108+8kOl78/ljHoNOxWYkWxxEiC4eyKvp7gL4o58X/+1v+A6+37t2K1eG3dkBe2Y03OWrMzrxOXn8etptoLislmfVhqV95AYAYGaflQbnz5foNkdXYc46i0R8n5kkr1HpipnM80L4+V+pEg3/U5+8C0f24ZnMQ8F54PgH9XxLGcRA2Yz1v2OZeJCECO3eR1iDjTVKmX6Z7jKVwjk4hupGbmCOmZXbi5qp/xnpGHw1RIeNN6ST4huZmj5nP1xVfnc+b+K9FG5X5x/IGMAlWBTKpjSvm+4JoepaiM3zgxFUDqa0X+ywr1ZVmmDPABduuYCg8ApZjEOHP1KKQWJiboNu9P+TJO+uDQ7BIHCAfaY8AiaM7xLzl+EmA6TGivGo4xyb6si9CHmWMjASCZLJRWUIODOhyVVrwE7P71nSwSK9XJ31R5sBJTVk2Nf0pr83mNVN6OalIbIv5eMz8da5O8cL+SmlTlxlqwU4k2KgDOgIiOR2bLFu1Scr4wYwGA0uU8v6yW9u9DkRdIEgKQVKowcGdWLQAxKObfSLKMg1hVWiaaijHsM1PaJ9oi/ZtSrVYDFVclNCFanbEiigA9OcaVtDo73jRCrCb9cvfLqX4ZlfcbFVs1mggpuhsVxytYEpGXBU1QUX6zlVyFUfzuawxIgu2sf3riYSAqqVRVsigxM3qFz8YbvUR7fScLyWLU9P71b/kNOVPOeiTz7FaK20ncxjmQZ40ReA8SlqjMkOVcJgd+qeH2Pvc9CxspBQTBPcwzSOhy4zwDM+t3JtkCMprfIkpxwDaTrYwLl+ALb6nSNX2PEf9/e1fSI8lxnb94EZFLLb3N9HA4FNeDYBqCIcA2bFjw1QfDPvon6E8Z8I+wDj74poMBGzDgg2TKgqChJG6z9F5LVi4R4cOLLat7yJ4ZgmxS9YBCVWdnRUZGZkW+eO973wflcSGhClJLJgAK2Rq/b6DKj97ZwMsQNxieiEOq9wY6v9tYCOw5X5ErBsOTWSAGHgJBzwAZyHR6E7NngggUlhaDAUiANuNl3qsY9TaR68IT3AwmbmOvxI28LtlbfvIPFtSZlK5uupjxElkG7EYzDrL3Fb1+DGzBbTry1ywv3nlN2wU4d7aznd3K7q5nAeBGIl4guvgArhPZArfzLEIcwS8JhBDMiuXbEEKwOE227aVdOZEtb3y/w0tkrrhQigltAUTRHCF4SeI45pFQmq/vNn91v7Pz9MsQJzNIe1iGDCZ5OaHgTogUuA0xjxDkDd8ndrvFyz7QReZSW8ApCacoA6wxqtUpihBugvcuQOziB35Q357T2bLuNvfNDRZQsqGPVnuIfVjeWo97GFxE3VpJHpnJcPa4DAmkxLnQUgj6bhsxYtQqSojguMwVcCYt3ZyPPb2O3dnJIiwznM8u5MpTAGADV6WUcNZx5ehyGf8v53PYBqC6gl17V0zKGNARlee87Je8ZJhNIJo2rrfNcsUYDCSMB9kKtDeDqOtIc0cA8OAeyIOx3MZf7MM91vXItU4nVaTtk1+cwc09hd/ZZdyO33NFP+3PgNNzVu1qNsCc8Rd2uYKc1MAb98cuNQA3n2CYVwlA9OQCblKBFmvYff4++WxL1DrdY2wKdT1gLfqHB1BXfjkXgGt1EfU8AGD9gxkmnywAUcFMU2RdrjqIdQPnVdVGdrQfdU4CwrN/sAd1zlmEIMlnS8VuuQ8Y9nsV1GUDUipSAJpZwfUjmx42U9daPSpRno9/VFITuns1ivMW3X6B+ldJvWt4eIBhquKPYHj7GN1RBdUMrHV6GlTqHcxEw1QS5QmPeXdUwZFATSwAdEB7fG6SNTqqUmLxNmc49CotBdo9X9dRMtJTLxyKpcXqId/f9WfEwcx84uoHrH94H/2UMP20hvQcqYsPZjj5MUF2mdbpkUR9VsQ1cyASHkoBUwGTZxbNUXrYmN/ffkl7ZyeLLzMhZaTcD5/FdvAxztRZiXowZ8fs3AA/DfshPhXzNvNjhaeqy/ZzWl07visURKYpyts0TMVDLrVKOqM62x76HfRTA3N46C+JyJZNnqUqPLldoSJzNuCfvNrrvZbpqc5Rv8DuvTUJVxK28/0KT8Ha98/3rZ8RbK0hehNL3wFem8sgSL1lcTz8Z4DL0uUqFM75bVXKCoT+uLUECREnhn6iQMZBAaOS/G5GkP3W+bQEUxNkozDM5CjeYyuJYZaK32ypMEwIgMJQEXSZ9jWVRD8lKJ+16KdcSg8h0B4A/TSlKIdKQG0kur3wVKf44w3bTI2Msp/QHvhxKvUo/hGsnxK6GaEuJWgj4/l290w8dmhftVmJumfFGmqWKOhXAv1eVvPydZaof6P2ZVqnXtOU6opxFKHW33/OyXoBn9KUNIJ7Uz1FZP72BLvBc6HzK8ZlhJRo1mZ+LCEl3LoBBZo7Y0DLdfR0RO2JfE+vOFiZpVTJWmifenOLJSh4BMsV9BP/ZA2YifMrxmwsBfdx6S+wMXDLFSMuI6rV1yUIAd1n6bam5YBa20UVK9c0PHkSp2/DbeaqCug7FJ9fRdLhSIO30pCe4BcA5taxipe1oEXyLETbwS1X164FAFAYDyCedzHY6B2JDQdxpZRco+PZvbVxcR/1lFGO8rLk4ruuhyrSZCXXE6jl1rEHC6claNlALap43QGg+LyEPi8Ar1OqCw3qufZCTwvIS8887hxkoVBogrzgcZSbIbr4938xYPJpKJhhuQC52EBupn7fdE3C5GY1ZzLUykA1hr0BAPL55TW9VgCYflqjLiXUZRsn0oPfNABq7D1O51SfFNBXXVzuuFDNq4kJkk86lBdpzNTm+5A63cZNZKlUjobb0ecQIR9/h1JqFeAYwDBwWXmYFIKrvWm9kHGo/rMJO5EdK05AIVId2raWvYuw5mwazqjk+AgSscLUZjeE67oE9gkT06blvsk+vof/u8CgHbIAznEMZDAM5MrWz44EhFIxQ+GMBRRdw6GIsmDOlVUTJRTjpO2FmUN2R14ouHUDWDfCpbiuj4C4bYvjkV+eEPcAezFOSc54KJnW++E7SkWQlBh8hmMYgAx7oYXg88/N+lhKs4EwNk7qAECrhsvow1K3H1gWsjdw8zLFAQauP6K2j/2hFcFOCri6QPWsjZMxiEBKQqw3kYU753UNxDVOc0yDNlxnFDM9zebG7IxctaCN5L5570ufN5h9riDPkwahaA1jKWLVLj+ApZYw9RRy3SFHeMd4zy1slw3Z2c52diu7W55FrqKu1Kg8Pbi2drWCPDyEXfNsSpMJ7HIFmtawTUC8+IBn1zG5jfcMzGlSNFDvv8vtXi0AQXBv3gMtN6nArG05uOjdfgAMszYWYn+e4L6fP2NtD19ibC98qeGP/wR0uR49ee3+FN2hL+j6LAU15ekCm/fuAQBKD8e27z2CfHIKN5uAFiu4Ge9LT08gHh7DzGrIS98v7x3Zw1kqlAJQfHIONykh2h7mkAudZPCWfITdHnLg0/36YwBA97c/gr7yT0/P7m19cC9gAa7eq7D3uz1Qb9AH6LB10Mse6tlVitwH1KcxGN4+hrxkz8Ds1wAJDFON4jmfg5lykM5WErQxMYjX35tAn64hPn+O7kd8zfq5V29rDNPweVu8pVCfBa4P3iY7B6uA6mzA5khh/5c69nf9/iHafYmDX/iA69EEm+MSau3bzTzVYarQzyTqp3wdNscenv0/X+DxPx3i3i89+Y1ipbDpM4PL97wHsExcFe3hOGahF1w9uniHd3nn39+CXHd+3BJ/yOKDGboZ4eA3DfQ5j+OzvznC2U863Pv5cayRbO4L1M89V4djMiCAYxbCAe3+HM1x8hH6/7u9v3C3JovcpIQQLmZFIlfFMEDMplGqUOzNINoWYj5PJdvGQEwnEF0X37dteMDRawXASULzgzmKizLeBLPfa2B/zu5+PNYc6AeY4320R7zf5GqF9Q/mmPhIv/Dr8sV7U9RPPRdDqKB8o8TqDWaJOnL7aB7wTTotJM7+tIQwDm9+xFd3/e4U095gOKyhiTDc9yJBixX6h/vY3C9QP/FBUZ85aB5NsXyULulRt4/usEBNhNV7/P2Z/wGYWkM2PZpHvK6uP+a+nH1Yoj7hH1Sg1W/3yPNK8nfP/sximFTQS4fmgXe1DVCdauwJAeqyEndiV3fx/hSTZ9zu6iFH6zcHhP3Sj82hl+SbCeilQ3XO/Vm8rTD/RGK6aHD+Qx7z5piZsvSVQnso4g9l/eEGy09LTid6ghe95GDf5EmJ5dsO5Tlfdxoczj7UWD1yqPy2xVsay3cEikuJbh+Y/SFNvN2+QHvkMP+Yty3f4R/99JM9/MPf/xd+pv8KAGArB9zbYP2bGtWf88Pp9GzKYDzLnJkAM1xNVYtfnT/EZ88P8I8f/gIA8B8f/yXKy8LXcniglQROfszBTKDGzAtCnf2kw+O/+xe83/00wsgfvXuKL357DKcYMqo8A9fB3hrGCjx/fIj9D07jeeFfb58uvruThTFjzyJLJbnlKnFMrNYsNbhcjdbwdrmCG4b4vt1GCJa5dQMhBOo/FBCbFtM13wyuZ1lC13ZJKnHdwG1YdrC+8qnXxQL17yq4xYL/9sea/XYJWjaMyvTrx2lTozzlsm39bAm15Jufrhoc/UpyPt5/f/LJCrRqoH2xlQqxj66HfraAulQg71mEdf+kG1BcpBtcf34GdVlDXC4x89+nU06dkk+dTvwP2/qg5v1fbqCWifPBSYG68mXr/nLoVYHJ0w5yPaA+9aQtg4VaDxz4zJXSBNde7D0uoiwibbiPM0XQp3wO1bMsddoOoDXf5MXlBOp8DXe1wNGvOeDYfa7Zs9gYJjr298nqWYny0jKjVeBj3jBPiFoaTJ5plM/Xsb9HHxEmTxXKJz7AeVVg+rRkj6WWKM9S/MPUCv1UoTrx0oFP+drJpxf4t5/9Nd74X5+9UQLdvML0yRCVwoKuh7CI5LqBCk+2wOHCcZk5gLcebzh4KjM+C8Xp0X5K2Hu8ijGKez8/xvvdT3H/P1W8NsuPHuLBiYWTvC3Q/fXVBDQ4PDyxaH6dGHvF1fc8dQoAI5r512qHmazETe1kVP385yscyzlcA4pbXC/gceHl0j436Vm8qj7Kq1pGi5dkDPglrhXahXc3frfjv0M7Lz2aoQTEJVGdbY0M4V8j3QyEbeMCt7jf6w5pfjzg2omNdD2+rA0gaceQuz7uW5a3e5O8gsjuvVeWX8hsF+Dc2c52div77ngWuW5IXnUZsBmSRmlKoRSro/t33pgtawKoysOZ7aQAWQtbJZgwf0gl0JzeU3BVATvzS4hTBTsrQadq1E8z1aBuiGS3AMcJ+j3eT52rpBuy2GCYMr9BEchjawV55jgQmVV8wjpASZhZGasSY4BzWqaAIwB1WsJOS8hNBxP6u/ScHx43YX1gMUDSu/3k0lJQ/J5pDDXFmMXmiFCdE4xTMcAonOfj1CrxYWTwbDNREB5EFoBX/VxBNl4Qee7fJxJqTfHG7A40qC1ASqGfe92QfemZsjACJG3uM8ApkNUCDHqyimMq3Tzt6xShm0tm/PbAtH6vQHNPoVgRuiklUmJ4YeQZQXbcz+Ye92VSFdi8OWDzGbdhNdDPBdSGsDmGP18Rn/5RN2Tm4JSDvmTdkM2bXoS6ktAD823acCmFQHPEIK/6pIjSjs19gUfvnmL50cM0Bg8cyBCsBIQT6Ke+D7UDR30J64cZKOslZoDvzmSRu9/DkLROAzYi2xaAV7Fq9SYOzgCOCpyXqxZi04ECEtMxngE20xn1PAti04FCfcYwgJZtQi36Y6hlxzl/T9sHAHKloAN576aFXMrYl+KqZ3fYx1XkyvMWtMz5EEBK1jmItoNcihvAUy20Tj8IsWlZ/KjtIJd+38DHYFh7NMQRrI/LFBcD1IK3BfCPcI75Kz01fX3CBCuRrxQAE9z6fuZ8GABgLeSyi2QuAQUpjIuxiXAjUrcVs7hQ/HkYUFz28VhkHHNVZj/oodKoLswNWqdAcdVzfcYmEfuUFwMAFTke9JVErQRUYyA3MmaFAIB6BepU3FYH4aBNh8knCvVZiC8AqiFUZwbdU95HrxCXbdT7Cbhmuj+1Yk5T6x8GerGKfBQiK72vzwqolqCvutjf+rnDF789xoOTDPhnCNWpjdkQ7cF8Q8VL7fqEuTzj/t8rwt6b7AUFZrHYCpw6dX7bVy7XAh+GEKOFmZAE9wIm8VFR2Q0FZi4Aouy4yGj0OTTrC6uYQj7nbGB4ucio/GN593ZbaRCuf75p3xeViQuk8xU2ArsciQT0IcRtNkx+ka9BJEh1SBsTXeuDf8hd62tsI45jNqaRmwFwzhdLeZr9Ub8kYr/IuHgtrBQjrzRKJwQgXTjX7D31g9uNyMjsmrMEQepjgHHHIi4vUgyXJjGrgJyuP/eEAh9FlGWQfG848sfPr4PywUxvVqZxgEsSBU4CsGLUr5e17+Zk8YIg3ytTBLosWJo1PRJGfh3bDvjd9DkEDPNgoGGeglzr1Dr3woDX12bb/Q1BtG2tUx/hB7KgY65zshUgHmmnvkoN5Kg/fK1uomsQFvA1vBAGcCr0H+O+WT+urzue2wHN7T7dFHy0SAzc2f5BqxWwKRD8guym8BNQvHfAS49RMDcP8L6mfTcni7xoKz6Jt57+X8EQ5CIjFkPCneYio6grAe+VUFYSHrRTlUwMUZI/Xysk0760nVx6wmjJSmUC0DIdy0ni1KR10Nm+kPwSRKm//vydlonrMtxUvv38HGMhWSgYC09RJZnVKmz3xzVZoRLFAjWKSmqAV+sKNQceJyEcQJ1lqPP2j0+w8hj5/tpCxmMpHdb6vhCr5BRyoMWzpT8HIdL3KgL1DnZwMR4AsGtvGuGfrH4MBHsQxquqRa/H2qS0FjA8BcFUAsLyu8vG0lQ8BrHWItDpK4l+5qISnNGC+1GKqDMaldJd0h7tp/6p7wTEICILt9XEVHgk4iziSGCoiJcuBcX+DjWg9oIami/ym/LSg9sGhomI+woHDEuBYZouzcsoku2yITvb2c5uZd8dzyLPhuTkN2ENt+1BCBq/gLEvlhHaCCGYQISYICW1sdUmCV53Zk9q4QlUUn8CeYn3QDJ2bycpanoGHVIAkESsoZkt0J3y63zpPZRQWOW3WS1TkJXSMU32NGQeT/aMgqao3CILys8D4GpI5/vl/ILXKuInnh8+1vwk1goJyl/Wewd5fCdcE8vnE5/gkgBiHdNw/Og1FARhJKhLf7N3lLwmU3hu04Fgcj3SOv0vPDGF5ad9oQT/L8RYwNfCFCLyeRpNGEoBYfjdZMFiU463DWV2Tac28kZYBZgK7Fl4fBx5rVN+0vMgmgnD0GlgASAz9QWGSnBQOo+JCIGh9B6LJkgdPAuBg701+mqSrk3tvLeEEdzb1Hx8U6VtwMt5Fnd2sojoTV8vInTB2Q1IZrcOqErjGbStixWkAJjKvSr55asKRVUym3VO+GsMe7EhNhEyH/0QqfYjB2fXQxzswRU68kOIusawX6J8wvwT5LMi1q/dRVaiHgFDAFcyhorPwbB0IRCPKXrDJd1VwVWRg0eMdsx96QpKNPy9glMEUzPSMgbR9mq09yqUAIynoFeFZv4GyS55SFmWhwdRYDmmigOHpHU+km/jeVBvAeNG6UUxMMN35ELNTAT273DNDGALEdPHw0TGsu1hQtB+eTNMCMO8QHGwl8bLr/PJuLGiVoitGMTxpAExdSosEr0+GPItOxezPsOUU6kAsHiHQMantnuHfkowGrBlWH6xqHL/1gFDubPYQDxWGJo8huFEts1BGFYKC8phsrdRnjCOHfhHzmlZBVNP47GMFaNrAOcBhnYLjOWAzbsdiqtiJIz8MqGjOztZXAtiOpvKt7N06I0pUgBoWy6X3qg0iRjDE4uxoM1W6nTZjlKiNicLzo+1WHIqMXSraaBP1vwjJxFL3+Wy5dRmVkiWpzY5deqHv+1iSi5MgiEdKzZc8h1Tp77v6rIFXa3jeQkhoLYQlXSxQtUbhoUbLiQT6w2T+fiSdh28ktUazjkUF33khAil1QoppQkA9amGWnQ8OWT3nVx1nJq9oUQ9jgcQz7s8k1C+uIz6gjMOBUH0ltsCoA4qqPMG4moJfTVJ59ZbyGYA9ekWnkwEqrMtzdnBQRWccqwJcRwBoLjoIYyKZe3VSQeggGos1Eaifpb0ZvRUwVSE4txfJxJwZ4B+ssD0sxr1mS8pkAJ6JVCeD6if8mQTpA0BQHbei/Eq7cWlQ7FwMWYjs9RobpNnFv1KoDrpuNAMXBT2/PEhHp7kvxVCfZJKDIZlOB5QXBWYPLExfcvjeO1QL7S7O1nky47tf2VAqxx8NQpyKsWutUoMT4GaH0CkdkPjyUhmJYOyPHgJoU1gdCyhNVxZRDCTVApmVkAGEpYAwPKgqVyIOAdNqdNyBJQK26ugkO2BXq4qgEYlsWFJcFWBYVYkohtfg2GmJfr9jNjkgo8hNj3MjL9PC80ThZJcFDfnPigpIYxBd6DjhCM9ReAwLyJYCgCae4TqtIDo7eh4WvANedNkkYPIwnl3BwrUlv4Y3sMI4C8/ju2Bhugs6FLHMWoPFGhw0JrQz1Lgd/2ARulOAFAtu+U0MOBqUiXQWneg0e4TJrXvz75GcyRRrFiqULYeuOccuplEPxGQrQdlHUk4CUwrjdVbFtVzv8RSQD8REFaheSMEF1OfWl+WMUwcbMEixUMloqRgLgCUW3NE6PcEygsd+SiaY8L+B6ejWg8GXCVpgRDMHGo+JvWE9Ztp8rLp8n2l7QKcO9vZzm5lu8ni67CXUHX6xu3LCuTumMX47rXU6zfelRuxEbfeZ7u/X9X/b+P8XsHu7jLkdS2CmUz8MTvCtQrIaKG68ivwV25LTjACprbbDcCYa+CrbD93w/a8P6P2xu0Im4HFbB7sTbsJ68VvrM2Cg0yMwnJ6FhQgxcZ4ENoNAJ4AFApBvAw3MDpeDgbatpuAQgYxACwGx6pmioOmIehIg+NzGMx4jB347zxWZ8fAsbSvSGO2XSWb9UsYBxr8ez8OHNLgQEbE9sk4OCu83GACVjmbxidWyY6uSd7X8QvAC+8/Yfl/3LcQDQcGS9Bb7QubDXIIdFqAOv5+CKYi2+02dieEkYUQzwGsAJx82335hu0+duf8x2B3+Zzfdc4d32bHOzFZAIAQ4r+dc3/xbffjm7TdOf9x2PflnHcxi53tbGe3st1ksbOd7exWdpcmi3/+tjvwLdjunP847HtxzncmZrGzne3sbttd8ix2trOd3WHbTRY729nObmW7yWJnO9vZrWw3WexsZzu7le0mi53tbGe3sv8HuBfoF6qyzocAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb5d7e25c0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 53.35458517074585 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 1.0} is: \n",
-      "[[1.44000000e+03 2.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [2.40000000e+01 1.36040000e+04 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 1.44000000e+03 ... 1.44000000e+03\n",
-      "  1.44000000e+03 1.44000000e+03]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 1.44000000e+03 ... 5.60478297e+12\n",
-      "  3.30569724e+10 6.82240838e+08]\n",
-      " [0.00000000e+00 0.00000000e+00 1.44000000e+03 ... 3.30569724e+10\n",
-      "  2.54319069e+13 1.39916459e+10]\n",
-      " [0.00000000e+00 0.00000000e+00 1.44000000e+03 ... 6.82240838e+08\n",
-      "  1.39916459e+10 1.40365885e+12]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f8320>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 54.388861894607544 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 10.0} is: \n",
-      "[[6.40130618e+21 2.40000000e+05 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [2.40000000e+05 5.27567127e+34 0.00000000e+00 ... 0.00000000e+00\n",
-      "  0.00000000e+00 0.00000000e+00]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40130618e+21 ... 6.40130618e+21\n",
-      "  6.40130618e+21 6.40130618e+21]\n",
-      " ...\n",
-      " [0.00000000e+00 0.00000000e+00 6.40130618e+21 ... 4.65877907e+75\n",
-      "  1.09712635e+65 2.72264980e+54]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40130618e+21 ... 1.09712635e+65\n",
-      "  1.87682260e+76 6.70356268e+57]\n",
-      " [0.00000000e+00 0.00000000e+00 6.40130618e+21 ... 2.72264980e+54\n",
-      "  6.70356268e+57 1.40492776e+65]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f8358>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 52.921815633773804 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 100.0} is: \n",
-      "[[6.40000013e+041 2.40000000e+009 0.00000000e+000 ... 0.00000000e+000\n",
-      "  0.00000000e+000 0.00000000e+000]\n",
-      " [2.40000000e+009 5.12153620e+066 0.00000000e+000 ... 0.00000000e+000\n",
-      "  0.00000000e+000 0.00000000e+000]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000013e+041 ... 6.40000013e+041\n",
-      "  6.40000013e+041 6.40000013e+041]\n",
-      " ...\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000013e+041 ... 4.30327450e+141\n",
-      "  1.02470680e+123 2.54129819e+102]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000013e+041 ... 1.02470680e+123\n",
-      "  1.72143257e+142 2.65960796e+109]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000013e+041 ... 2.54129819e+102\n",
-      "  2.65960796e+109 1.27631386e+121]]\n"
-     ]
-    },
-    {
-     "data": {
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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468c8d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 51.73200535774231 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 1000.0} is: \n",
-      "[[6.40000000e+061 2.40000000e+013 0.00000000e+000 ... 0.00000000e+000\n",
-      "  0.00000000e+000 0.00000000e+000]\n",
-      " [2.40000000e+013 5.12001536e+098 0.00000000e+000 ... 0.00000000e+000\n",
-      "  0.00000000e+000 0.00000000e+000]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000000e+061 ... 6.40000000e+061\n",
-      "  6.40000000e+061 6.40000000e+061]\n",
-      " ...\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000000e+061 ... 4.29985152e+207\n",
-      "  1.02400707e+181 2.53953778e+150]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000000e+061 ... 1.02400707e+181\n",
-      "  1.71994184e+208 2.62182142e+161]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000000e+061 ... 2.53953778e+150\n",
-      "  2.62182142e+161 1.27508087e+177]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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vDrOQqgAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f8320>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "../pygraph/kernels/treePatternKernel.py:201: RuntimeWarning: overflow encountered in double_scalars\n",
-      "  kernel = sum(all_kh.values())\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 51.616614818573 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 10000.0} is: \n",
-      "[[6.40000000e+081 2.40000000e+017 0.00000000e+000 ... 0.00000000e+000\n",
-      "  0.00000000e+000 0.00000000e+000]\n",
-      " [2.40000000e+017 5.12000015e+130 0.00000000e+000 ... 0.00000000e+000\n",
-      "  0.00000000e+000 0.00000000e+000]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000000e+081 ... 6.40000000e+081\n",
-      "  6.40000000e+081 6.40000000e+081]\n",
-      " ...\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000000e+081 ... 4.29981731e+273\n",
-      "  1.02400007e+239 2.53952018e+198]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000000e+081 ... 1.02400007e+239\n",
-      "  1.71992693e+274 2.62144381e+213]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000000e+081 ... 2.53952018e+198\n",
-      "  2.62144381e+213 1.27506854e+233]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb6c144390>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "../pygraph/kernels/treePatternKernel.py:168: RuntimeWarning: invalid value encountered in double_scalars\n",
-      "  kh_tmp *= lmda * all_kh[str(pair[0]) + '.' + str(pair[1])]\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 53.70710635185242 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 100000.0} is: \n",
-      "[[6.40000000e+101 2.40000000e+021 0.00000000e+000 ... 0.00000000e+000\n",
-      "  0.00000000e+000 0.00000000e+000]\n",
-      " [2.40000000e+021 5.12000000e+162 0.00000000e+000 ... 0.00000000e+000\n",
-      "  0.00000000e+000 0.00000000e+000]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000000e+101 ... 6.40000000e+101\n",
-      "  6.40000000e+101 6.40000000e+101]\n",
-      " ...\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000000e+101 ...             inf\n",
-      "              inf 2.53952000e+246]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000000e+101 ...             inf\n",
-      "              inf 2.62144004e+265]\n",
-      " [0.00000000e+000 0.00000000e+000 6.40000000e+101 ... 2.53952000e+246\n",
-      "  2.62144004e+265             inf]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468c8d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 51.67221283912659 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 1000000.0} is: \n",
-      "[[6.40e+121 2.40e+025 0.00e+000 ... 0.00e+000 0.00e+000 0.00e+000]\n",
-      " [2.40e+025 5.12e+194 0.00e+000 ... 0.00e+000 0.00e+000 0.00e+000]\n",
-      " [0.00e+000 0.00e+000 6.40e+121 ... 6.40e+121 6.40e+121 6.40e+121]\n",
-      " ...\n",
-      " [0.00e+000 0.00e+000 6.40e+121 ...       inf       inf       inf]\n",
-      " [0.00e+000 0.00e+000 6.40e+121 ...       inf       inf       inf]\n",
-      " [0.00e+000 0.00e+000 6.40e+121 ...       inf       inf       inf]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688f8358>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 53.50304460525513 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 10000000.0} is: \n",
-      "[[6.40e+141 2.40e+029 0.00e+000 ... 0.00e+000 0.00e+000 0.00e+000]\n",
-      " [2.40e+029 5.12e+226 0.00e+000 ... 0.00e+000 0.00e+000 0.00e+000]\n",
-      " [0.00e+000 0.00e+000 6.40e+141 ... 6.40e+141 6.40e+141 6.40e+141]\n",
-      " ...\n",
-      " [0.00e+000 0.00e+000 6.40e+141 ...       nan       nan       nan]\n",
-      " [0.00e+000 0.00e+000 6.40e+141 ...       nan       nan       inf]\n",
-      " [0.00e+000 0.00e+000 6.40e+141 ...       nan       inf       inf]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 54.456220388412476 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 100000000.0} is: \n",
-      "[[6.40e+161 2.40e+033 0.00e+000 ... 0.00e+000 0.00e+000 0.00e+000]\n",
-      " [2.40e+033 5.12e+258 0.00e+000 ... 0.00e+000 0.00e+000 0.00e+000]\n",
-      " [0.00e+000 0.00e+000 6.40e+161 ... 6.40e+161 6.40e+161 6.40e+161]\n",
-      " ...\n",
-      " [0.00e+000 0.00e+000 6.40e+161 ...       nan       nan       nan]\n",
-      " [0.00e+000 0.00e+000 6.40e+161 ...       nan       nan       nan]\n",
-      " [0.00e+000 0.00e+000 6.40e+161 ...       nan       nan       inf]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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mOb73NK5ykJswuWQ2iGIzCy+bhfsNyeQGrLGRUeYXQ2bGWmQPP2J9vvgOy/FqIgfzwCEQO3SdjYdos1CZWbAlDqtfFTKuyszCu0Hf2Y3+4R8iM+sWqRxBZhY9TR8HAL50FcehmBxu9LznHpjT6jH4y3vQc/nfWXW+9BWpzaKn6ePSpTJrOzN9jeP3izqzqEmbRYIECcqPqvez8KTVE2cRdh9C0eql6izyFMOw8obYb24e2m3n82BQdodmxCS6lnfHNgyYYxbhCqmvh2m7E+vN00BHx0BzOc83D6fVq0uBEBKaAk5VbgB52TUNdHQMWmsLAICOjkJrboJ5/ARI4xTr2MgoiK5LmbUzM9bCOH6Sjy1MCm1KQ2BnJq2hIf+lzpaxoYE7mhnHT0Jva7FoCtsskhtyehi5vfugt7fBOHqsYAaTab+JO19JCWZU5Jo6FXTcYoAnugbS1AR6+jRM+5g2tRHm0LAjbwhJpWCOjUGf3g7jyFGp8ZXZfpDSkdu1p+A8qauH1tIE0jQN9PQZAABlTle6XnDfyu7dyU/YSzTHQ13gbKNAcsN/tPo69J9+HD2Nq7iNQoQ2pYHHCPQP/1B5rUp0HaQhDVJfl5+Wz1gLksuBpFJKIdAOOextXFJfj+yJH5RszczkBgCSrkf20PfRO/szoIQge/B7AKyEOEGMl2hvhTY0DDK1EUB+GRG0D4SxSdmybd79DwVlMhffgc1v/r3jWHf9cs+lS/bYo/yhDKss+k8/zkPoSeMUZPc/jEzn32KQjdf5n0P/ycesJZ7N18kM5140/wBgzLKWCAPb75WOFWlIF1yfmXULYFJkD37PSiVg3+f9+x+exIS9RR54UTF0p1dwejZSZ2eXNgxfxievbTSWv8EcGYU2paHA3lBqD05VVDp9YRwoZfpCr/aieHB64WxJX1i9NosiSkzc9WAJgABLSVDDUErx16Xf4Kinu345ulLLYA6NwBwasZYlo+Edmbx2Zrr0G7hxtSu1jC8vehpXOdismDGP+WR01y+PjQClGKKS9zBDnxui7H6sXWHhlV7Sq09Rkwvxejz6LP6+Xall/Lfvrl+OnsZVDrl6592G3nm3xSKPDHGMefUqiwQJElQVqncZUgSDZp8z6SzbInQd86ujGLy2uUq9DFHdHkyWIfGjUssQFVTDMqQmlYUSBBZu7piUSuWTCYXsN/uBuHu4bRRlCotFjZY6FqPYjeKWTUSp1u1hUM3s3ioylJNKMWH3LiEYC7eIuAhEAOeDyG0Q2tL8lqzEw9IN1bDxKLLJwOUUxoKlAtA7Z8K0g41U5BfLFOuzeE7MLBYnRI9QEXTJImgvvl4gm945ExgZDbSFyxWEfgNXvPr8C5HrsHZqmIen1tCAkesuAwCkf/JrnFx5tdXmmDXmrTsOgKZ0kOFR5Pb9Cak55wEAjEOHle+HkyuvRsubQ9Df3M2PGSdOQm9tQW7BXKu9l94AALxzz+XKffTCpFUWgJi8J58AhrFIedGj+b0tZLEZYoZqHvnq42Hp9qosRQ5OBkdmcaYkXL4pmelrQEdGpA+bSl5TUXYZxL5GVY4qOVdFdGlLQVE4psbBQ4HHWeQ2AaxYk+zb33T8bqzNX/zHHQ4ZxPPFZFVFy8ZtnjlNmdLqF++ru5SrliIxcCZIkEAJk9ZmwTW8kC3MkWYuos1CRM+0Gy0yVwi+HkFT88Ughwr8snEnNgtFGewZWrkIe6vBZjFplQU0HUQjjiUCtDy3Y9hlCGPBZjslPdNuRP+ZJ5QMnMWm7EGXISSVygd8BQhW85q69875LMzjJ7jS85K7WF2BPTJTKZ7j0y9grffC25HbudshT5BlCLtONu48CnN6e9FdKJH9vFjgm0y2qMsQbepU0LExaNPbkd3/sKMN1YC3QbOvIMCtWWvHKXMS7oYkSYY8oJLD1Ta8erF+VURuwEl8XKwPceSpVZGFJaxW8B4GajDJkPDCJLqObRP9kzw2JADi3gP3ejtVFB7T4YrLpQJXXhfZG7lcU33L8OvM/yLCy9eh3Aoj7IvJLWvQHDE1NbMAAiYZcr0l4nj7k3QadHw8z3FBNEAjfNlRthmGLDpUiGoFrKAzkk4D1IQ5YkWpFuO1CMoYHhmEQGPbqHVWhC4dHbMCxuwb2TwzBFJfB9KQhnH0WEnF0RoaLO6Q8QmQObOAQ0cBAHRsHKS+Dsax45VLMlRXD5qbiJRkiFx+Kchrf8gfqKvD1lP/NgliQxIkSFBVqLmZBVD5vCEqDldhlwCqeUPEsm7HKK3RCgU3h4c9ZzxefSj30sXdB72tDcbx41wO8Xypozsz7TfBOHGSjw33QWm/CebIKAZGNvKoZJElO6pczEiuAiZjlHYzrasBWHSOZ4UHJ5uOiRbqWFIBsGnx+ATndXAbBUs5VVdNBeC1ZKBjYzAkx9lDJ5arNDKzbimQwzh+HEBlDIeGy3PVLcP1194PEjALmArMkRHfMjzJUIT2GQcn81jNtK5GevZ5V6peX73KQtX6LabuY3YE0WszaLOMzckweN6QakSSN6T8SPKG1DgGxp4CEN/0OXvsUctnQdcDE8MmqG5U6+5QtcrlRs0riwQJEpQH1bsMUQRjAGKGx9hgGFI6dwa/VACVQLFUAH7XVFp+lVQA5ZYjSCqAWkBFUwEQQnYSQn5HCPkNIWSHfaydEDJICHnL/t8WqnKfdRyjxXPQ6o2Pg46P+/JvqsAcG4N58pSjrXKge8rKAmOkCM7yHVAxknS6ZKHhYaF3TK+0CIFAFi+saNtnlr4vcj16c7Pj+8Q56kmG4liGfIhS+l5h++WLALZQSucD2GJ/jx1E163dD9HASTT7T8nHhEPGxUh0nTMx87ZKBLaVBQBaYyPf+mTbdCIYyzcrowqx3lKj9/zPoff8z/mWo7NnlkEaJzKX3InMJXfKT7rvG0LyfwD2X9vs+F5O7L+2GWdWnIrcNulwziQunXlY/doofhaEkJ0AFlNKjwjH3gDwQUrpfkLILAA/o5ReUqyeKOzegMBSJeY/DcnuzeC1910t7N5BvS1ViXbKaWzLzLol0I5IpWn1xPSFIsoxZnzrVEhfGCZqV29t4TsienMzfjZtAKN795TFg5MCGCCEvEAIWWMf66SU7rc/HwDQGa5mn2WIwJzML7HZvVXSF/rBFJi93W2VcjqfaV3tmGm4wWw0AyMbpUsLkk5Db2uD3tbmODcwstHhw1ENS5Ls/ocL+qC3WavWQbMPg2ZfWZdPup1EibXHZNBbW0DSaTz3/DrorS28XDnx3PPrsP3J2yO1PWj2IXvsUejNzdCbm5E98QOM7dv7gur1UQ2c76eU7iOEzAQwSAh5XTxJKaWEEOlTbyuXNQDQgPJMjxMkSBAekZQFpXSf/f8QIeRZAFcBOEgImSUsQ6TzTErpBgAbAGsZUlCgyDKkO71CmhuE1FvEMzCMwBF1Duo5WCkFGdxtRXVwcrclgh3PXHwHsq7MWkDer8RryuzlwekuXyonrd53fR6b//AtpbKyPlSzB2cpZbruAw8AALb8/EvS83G0LetPE9pK78FJCJkKQKOUnrY/dwP4CoB/B3AjgK/b//9P2Da8MDD2lDSGguWsDAP3wysmGJKxZUfZOvVSFIBF8gIA2Xe+LT3PFI0stqPY1qmXzSLuLUBVRQFYuyHGkaMOORiqceu0+6ovg+54xVEuLtm8lAQDWbwQp+dNxbS+X4VuY9DsK3hRTZk1R/n6KDOLTgDPEss6mwLwI0pplhDyawCbCCGrAewCEG7P0c/wakgMmDHYKnhVwsyEGvHV69uuneDW8/x4aen6EiTwQvVGnWo6YBpSDU7SaT6jEPkveaSikP/UC+xNy+rJTF9jxYM0WcsPWeLfzIy1ypwKoowiuqeshNbYiOzRDY7ov94Lbwc9fcbTCYxtozL6vFK9bb3kjopM+01c9sysW5ANkajXz/rvtbzrnrJSnkDbhbBjql/8LmRf/7pUHsD6fTOtq2GOjfHta9LSBGP/QSW5vGQLshuSmXkzn8WJmBy5ThMkSFBVqMmZBVt7Ada03Bwd5ccBNR8EUSv3nvtpbP7TP3mWFVMKehGzRqG08zJmytB7wa3YvOshpTdNGHfvcvpZyNyn3edE+cvhZxHG3bscYxZ1ZiHW43b3rv30hYrLEHZOHACVZYh7oMVpcjHE4ZSl2lYccgRFpZSFCirtlOWFWlEWsjomxzKkiLFyYGQjj6FwpA5kl8qMnz5gD29P46oC92/ZsSiIoijYjGpSxIZ0ltfdO6qCpUsWxSSJE27nQq+2WQrEKBCduvTmZozPVo8NqdmoUzaz6J6ykpO7MhCNhN4YIVMLHcT8coeWE8yAl5DflB8lI79RCHysBvKb6lUW9vLI620g08b8WIQtVDo0zOvS6uvQP/xDPnthiYVKCfeuhxvMsq/CAyqiVEmYo8ArkXG1wis2JDI0/yBFumRRQWxIGLhjQ8anlTfqNEGCBGcBalJZMIbrwdwzIFreNkM0AqIRz6xb7jrE2UlP4yorSEvTAE0DqUtx9/GB8acDzyq81qFdqWXc/tGdXsEDwzKtq9HTuIrT+vVecCs/DuR5LtjyK8wyROUalfVzMbCdIzdEjo6eaTcCiH8ZwsbSDa8+FQvYk8FrVpGZebOnPEym7vQK/tv3NK5CpnV1Xi7TQM8V96LninuLth1lVsHuuYJlyD71ZUj17oZUOkS9cZXUVpGEqMeHJERdHdUQol69yiIiHLlFxLwi9mfZwxM2H4iYjkDMKSp7oFleD3N4mM8SisVuMJnE81G8LLv0GwBKoU2dCnMo/1Yh6TToRM4RNCfm7PCKRRFnDMwbUQaxbFjZmT2HZVfTpjTwz17te/lNiOfCyNWVWubY2hdlZDlGGMQZoQzu81G2SYsFKcqQZFGHcCOIeUVSqfy2ash+y360nqaP8weP1NmRr0JKQy9EMTqGfZvxG9E1c+MJdWbdAtMVfekFtwIppmzFc25X+8Cye8DLYEqXLIL24usFsumdM4GRUZ5HI8iYMqU7aPYhc8mdyHVY2eDZzENraMDIdZcBANI/+TXf9tTHrDFv3XEANKWDDI8it+9PSM05DwBgHDqsnPzpqo99Gy1vDkF/czc/Zpw4Cb21BbkFc632XnoDAPDOPZfjrbtuK6gjiLKoSZtFggQJyo/q3Tp1QzXpUMF1riREpl1HyCRE0ibqUlw+olvtMRf0YqjINqbtGQtKpWMaxIbglr9Yf8Rzpeq3l+xk68uQ3TlhDKycMDlVx72EjbfeAXnLWc4cHUX6J7/m393GSTeZQm7P3sCysDrdd7Jx4iSf4TAngrl3bwXuCtyEA7WjLEJiYOwpp6u4RiwDaIzIHnuUG1l7mj4ea92xQ7LOTqAOZtPp0m8468Zx0isL93aal6Jw51QI4xrcpS2F1tDgeV7F2FZy0hdCigZwyeBVpljgVSkRNIir2JgGHWcxSbasDi/ZVIPhwsTLlCu/Se0oixBLEHeuDzo+HtqwqQpTMOKV0sAZGpKdIcDeip3IQe+YDtMm4FGVX/wexMBZLpDFC4HfvVVwPEzeEi8fHndOEXcfVXN+BPHMZXW6c4Hozc0wLz7fcWzvl65RqrMYJrWBU55XJFreB7+AMpZjRCVHR7lyeTicjzz6rjU2QquvA509U1kud5li14jnQvfb/dsp/o77r22Wthcmb4noaAWA5yDZf22zlVfEhuZyoz6z4pSV98MHQcaF1Uc62vkf++6W59VPf0+5Xk/ZIteQIEGCswK142cRcDdEtl4kqVTeZhEyxaHf+p25MlPDqFo/i6JcG4mfhbIs3DflLPGzqB2bRUBIveZ0HYRQgJoFgalxGDiB/INg2pT27jYYurSljpuibAZOH8getjgMnHFunYYxcFIUjqlx8FBwA6fEUJl94xtSA+cv/uOOotcVq18FLRu3eRo4mdLqF++rZOvUA17box7h62zAVX8skYxVpX6/uuPMUeEpW0gEkbscENsM86D7HVOtS/Zi8ZMt7vHyu2/ibG/SKouBsafQnV7Bk/IAzrwiYWNDGAoeRNvYxmIVWCxEqWJDAskmwoM7oXf2Z2CeGXLSE1ZZbAhjeSpVbIiSDBfNs2TYuUfaRqliQ2SQzVKCxoYEQWLgTJAggRKglDezAAAgAElEQVRqx8CJ8Ov4uLNHAchv29njV5I2/Npnvx1z4WbHXLLxMihMxchQieWEtRVqva+IRuRBfqxPrI+lhGZte4OazvSXwhat28+irL+3GyGeXZJO8wRdJJXC1pGfKBP2TtplCEPcLrlcYUkiNssK8UaxXbj5jetSYFULSnmMDjULjcxAuPSQoWEaoLZCko2dV+h4WWST3G9RvT2D5gOe9MqiJFDYxi21B6c2dSrPxFbwJo4AvXNm2bZO9XNmIrfbDqASPUsdF6r3J+rWqWOGJkHuw/Icwvr8C0u+dZq77kqcuKgeHf+ynR87ufLqQFunAJA6pxPGUWunTmtpwljDWcDuXVEoTP9UFECULUSRuMZxc0dcVpYz6jS3a09edtnSSfyuoKAjR51S01IYHjtaqf96Qd5uGaJOU1teQMcW57EwUae5Q0d4/8wTJ5GemAzs3mVGUD+LMFPBkgWSlXjZUdJAMpfs7rb4d49peKyBZJRi0JDbdIqhpgLJXFHHzaRdua1kNyRBggRKqJ3dECGdoYr2ZTyVYbOse4H5C7CAn+zRDeid81nk9v3J0UapjV5+WdqZbAy9sz8DAMjtPyCtr+y7OQiesb3Usvm99WV+M+UycLL7Low/hliHG83adJwyj06y3RDbSq06QMwBi47nlUJ3/XJQw8CgsSnSD0wncqAjI3nRjp/ItxHAwScKRAcz93FRNgbzjPratFzw6kO1otLy0okcMjPWInv4kRgrVZ8s1M7MQoCDuRsotKQr9MnrLcLTCRgGiK5jYPxpB+FJl7ZUKZNWWPuBn5cjy5kCWEFfgNNQp3dM56HX5MBRfs49c/DqQ7m3W9190BYtgPnya/kgrZk3A7rO4ziiwDeI7rJ1MF59g48Nl+GydcCR48juf9j6DMB49Q1+XVS5ei+8HZvf+bZSWSZjlHYzC6wgkexrD54dgWTMOcbB3q1bjkfUMELvCnBX6vEJkIa0oy0GU0jUEjf8puWiU5VMDvP0GWi7bWs321qVoJR9CAK3HGS3c5nEiHjKgn1W2wVjs+9A3q18n3wZFwXm4aPqheNof3+45E6JgTNBggRKqN6ZhSp/ha7ns6jbMwuYec/AwM3aKQthGCDpemmZakgu7JWRjI6NwZAcd9tSqqEPmVm3FMhh2KH9FQnPdzmjuWW4/tr7QUowIxOD4bzAM5JFaJ9nJLOd0DKtq5GefZ7c00yCmp9ZsGl7XGvt7NEN1i6CriN76Pux1JmgOlCt7u9e8TrVhiqeWWhKswPGTNWlLc3zF5qU+/iHhqahd/ZnsHnfd6Wn3c435X4TqrApibJ5zSQqsWXKIBpYZbKz4+WUzcvJrJSs2SogW19Gy9ZodchibyaHU5biwy5ujdLxcesvNxG5eTo6BjrkbSCsNIIyZJN0uuys2n4Iw65dSbgZvMvdtipDeDG4mcAnzlGPDaleZeFB0uLGwPjTACytSerrrb9UXfTmW1tKRiISB4LaHOjYWFXYKUQYRwLsAlQB6I5XKtr2tL5fRa6HB83ZqDug7n9TvcoiQYIEVYWaVxaizSJO0NFR7iKdIEGCGlUWTEEAQP+ZJwDYBieWhEaLxukAAFpzk6dxM4E3uq7+SqVFSFAiVO9uSBGWbKYgCi6x1+RxJD4W4z3cIOl0aIbpuCAS4Ip+AYwQ2C2n23rPyGjiln1w29+plxX6wN3Q29pgHD/uINMNQqQcBXprCx9DOjaWd/duvwndU1Zi0OxDpv0mh7zlgiiLEcHXYtDsc7C/n8ZxOUmHBNWrLBS3Th2XpOzuGGbkrVPSOMXznHgjVWrr1CsCUoQom5dTViW3TjMzby6Qg6ESW6fGiZNFt067r/oyqP2glnvcuq/6Mk7Pm4ppEZ3C3OzfDeecRU5ZCRIkKA+qd2ZRZBnieYlhhr62oC4FF9wECc4mVK+yCLMM0a2JUsiwEFdd3n4e1WCzGBjZGMhmISY0YudKYbMIguyh79eUzWJgZGPFbBYD2++1ZBmMZrPInviBw2YxemDvJLBZ2LMDr7VhT+Mqq5gdbObgz0wtC9SUSCiSmbEWgDOrV0/TxwEA/acft9qM+cbtfdfnsfkP31Iqy2T1ulm9Asnc5aP2oevqrwQyZkrrkPQhrkCy9//VNwEA/+/ZLzjaKxYf4hdIVioFocIlGkfbsv40oU3ZZlG1yoLoumdeg56WT6J/+If8u3uwtYZ0US4HN7KHH0HvnM9i857vSFmImJKIC73nfw6bd/8D/66qKADEy5IUAVEVRakhKgmGqg0kq1K53EgMnAkSJFBCTSqL/pOP8c9s/eWYYpnBDZyb93zHqu/iO5C5+I5oAvq1JcwqEpQPlbTPFEO1yuVG1S5DlCHz1tQi6MCIGb0SJJis8FUWhJDHAPxPAIcopQvtY+0AfgxgLoCdAG6glB4nhBAA3wHwFwCGAXycUvpiGMGYF6af1uXbpcjPMniC3RAgNoNzZsZaoL0V2Te+EbquBAkmE1RewY8DyLiOfRHAFkrpfABb7O8A0Atgvv23BsA/h5bMxwOzK7UMXallMAXOCePMEIwzQw6Oi8DNHjgE88AhGMdPgu6xcoF01y/nrN9AcC6JIMi038S352RgW42DZp+Uo4Kk09Db2qC3tTnODZp9DkNaNXBbyPqgt7Xxc159LBX01hYA+bFhMuitLSDpNP/MysXWrt3nYhBlCQteR3Mz9OZmDJp98bp7U0p/QQiZ6zr8UQAftD8/AeBnAO60jz9Jrf3MbYSQVkLILErpflWBOHw4OBkVWXd6BXftzrN7I7SzBWP0JpSCTLX8FRhnBkMp9/yzxx4tep75SyQcnPGjYhycp0/7lqllDs5OQQEcANBpf54NYI9Qbq99LEGCBDWOyLsh9iwicJgnIWQNIWQHIWTHBCRvOR9mb7Y0GBh7CoA1xaKGYecMCe/unT32qPV2Nyn3aehOr0B3ekVe9lIuQ2bdwhPvyMDC8wdGNgZahgyMbHTkJKmGZUh2/8NlXYb4+TP4LUOee35dSZYh7pmrDM89vw7bn7w98jIke+xRvgzJnvgBxvaV3oPzIFteEEJmAWDMq/sAzBHKnWcfKwCldAOADYCVkayggJ3b1AuyAdbqLTo9apihc5nyuqY05NuyFVI5kN3/cNHzXuH5CRKUGkrpC22bxf8VdkO+CeAopfTrhJAvAminlN5BCPkfAD4NazfkfQD+kVJ6lV/9QdMXqsCR4lBMb2h/1jutFH+O1H8h0xKKWdHY1uugsQmZWbcU1MfSC5IDR7li6NKWcvJaNy8lk0mUV++c6atUvNCl3wBQitQFc5DblV8xknQadCLnoKUXUwvqHdMLZBs0+6z0gjayh77vaWsYNPt4fWFlZ6kDcfCIlSOmow04cjzf/v6HC9r3CjkXz4WRqyu1jCfqdsi48G7g0FFHGonMzJuLppVwn5eNoaqXZ2bBXci+9qBSWQCB0hf6KgtCyNOwjJkdAA4CuBfAvwHYBOB8ALtgbZ0es7dO/wnW7skwgE9QSnf4CaGkLFSTDtkQA5GYwYo9EACU2cO96hWRmb4GxokTAKXQGqwZCaXU14jIprthjI1hXYTZTe7OCys+OKbL0OcFd4BXsYAv8Rzrd5AM6oC/0dNL2dMli6C9+HqBbHrnTGBklBv8goxpd3oF6MS4pQQvuRO5jiYAFmU/AGgNDRi57jIAQPonv8bJlVdbbY5Z49264wBoSgcZHkVu35+QmnMeAMA4dFgpzQMAXPWxb6PlzSHob+7mx4wTJ6G3tiC3YK7V3ktWXtR37rkcb911W0EdseY6pZQu9zhV8HTb9gvvBXeCBAlqFrXjwRkiZB2wA9KEz7CdvdxMWu4ELEG27rJHN+SXPHW23USyHeaeEotvEHe7pWKIIhqx7L+UAoQUvLGCZFZ3B/AVk1fsa9RtWzdLmR+6tKWgKBxTlik9yDgzfxvRZpZ94xtS+sJf/Ec+bMB9vpisqmjZuE2a/KhLW8pnOP3ifXWXctVS1I6yCIn+M0+UZ8+eUgdHY7WCGoXr7ATqUNm5mKyoHWURcjtUdEbiW6slQpe2lNssGIlLMbBtQr9ycaNLW8ptQG7FoS1aALL7gJJcbs/DYn0Wz6l4LErhjttRjOM58NlrMPvJ1wqOa4sWBBaBbaG7d8gOfPYax3d9ujMt4IF/U2tL5b5x15m6cK7jeOrCudj7kXMdx/r/9BulOouhdpRFyGXIwMjGPDuUkGU9ci5UCQbNPmQ6/xYAYBw+7Fu+3EoCgFRBiDBfLnyovOCWv1h/xHOh++02cCsavM/5zi8h+7WD9JXBaxv9nO/80vrw0K0AAOPoMef5v7Tb8nnnBRmbc/7yNcAEcu/sdBzPvbMT53xnp0OennPfi8GIbJO1oyzi4NU0DMtmIamLKZTISxZ7C1W2FvbauuvSlpaNlckPMhtEse3QYsmDvcpGXQZ5URrK2hdjYoptq4aRQbxeZnPyKlusriA2FPEav7biWHrWJJ9FggQJyo8amlmESxwkRouiiM0iym4IQ5e2FKSu3mrXFbjF2hDLimXKtRsCQoraLDIzb4Z5+oyn3CJY4h3xuxfEc+xzUD8Ltzyyt6jUae6qLwO/e6tgTP2cpVRkcLQhHGcEv+zYkr+2qBO3/vjzResqNoZuLPnrb2Hrjz/PqRlYXZnW1TAvPh9Anuh3wbqH8Nr9tyrXLUPtKIuATlkMA+NP528QXQeBzZXhsn/EsQwZNPs4ua+MP7RY3WVbhvjYLCBhNfeSxc1yXq54E69lSFGnLEj6oeuOBy2QDPoNGDQ2AQAyl9wJ03bKYm1oDQ347x/5ewCWU5ZhO2UxpeHllBUERpqg6+qvQBcIoFhkqVln/Y6M2Dp3z+VhuulADSmLcAbOnpZP8s9aOg1zbAxEB+hYfAbO3gtv529sZgU3j/qnsq9ImLim5x8aQQEzBeLn7i7CLX+x/sTpZ+EFL9nJ1pelkY5B+srAZqokVcdnNsZb74C85Sxnjo4i/ZNf8+8tG7c5zrtfJbk9ewPLwup038nGiZPcz4JZ5+bevTWyn4VSbEipIXX3LjKTcE/b3G7EdCLn687t9XZlqQDo0DBIUxOyB7/nOB/U+FQqFM156XLlBvIRlX45J8rpg5G5bB2MV99wHlT83cPA19Box804ZGGgFEfWLkHHhm38e1xydadX+AYrXv4363Hiz0dx0arfFCh4VXTpNzhiglLnzcbOlu/htd+OKe1BJwbOBAkSKKF2liFlAuOwYGs9L1Q6MbIpSa9YLDGyrLx4TUW2ag8eKZCDoRSGXt83scueI02M7HqrxyGbCgXCjBdOo+HY1NCGfsCOhG5dzW0tADBl1v9Wvr56ZxZETTQxzSDRdf4XGXV1IOn66PUk8EYcv1MZwYyGlWrbSMfAPO9iw6cBulS9MwtFJywW+zFo9uW3nWJw4AKK5/eodK5TbUpDAdemw3DpOsbIfDyvqQQ62gDbyCgzujqOlwNsW1n4LspxdO0SdGwj5ZcLwNH3NOLEn4+i5alwu4JA3mbBgh5T583GvHZ1I2/1KotQiZFtwl4zutGWNDQUPZ8sQ2KAQFxTjmWIL3yWIddfe3+BcbFcsk3/7TDqhqZEX4a03+RYhjScp74MqV5lEQbsTSBLPBQUJYgdSZCgllG9NosECRJUFapXWSgmGXJcMjwMc3g4UpIhBuN43h/B3RbjwywFMq2ri3oV8hDpkY3QO2cWlUU852b3LmUfVJHd/7BnH8QAsHLJqi18t1QGdvy559dBW/jugnLlAGP3jtq2Oy9NOdi9Sw6SSkldphkYsayYGFlvbgYA0PFxmKPyNboq9LYWZC6+A9k3/95BYguE8/xTRfbED4qeZ9tsKmtlUU53+VL2QRUq7u+DZl/ZZDVfeV0qg9f3ciKutt2OaU1oK3mSoaoBe7ji9jwk9fXIvvn3sdaZIEEtoyaVhSd1nUbsv+jdom3Nkes4G/H+v/pmpUVIUCLUpLJIkCBB+VGTysIreTCdyNlBZNGdssjpYf9CFUTQZZdoMCwl/t+zX1AuW0yecslbDG4ZKilPXOPhriPWLOqVQjHjJoA89T77zghdgEiOKywEmRqGlUt1/GneFnNmoUsWlcyD048Ypiu1jBtc6ZJFAPKJbbq0pSCLF2L/tdYSqtMlpwi6ZBHI1pcr68GJfB+YHAc+ew3O+c4v8yQyV32ZyxoVflGnR9YusdIG2O2xskfWLsH1196P555fhyNrlzjkjQPXfegBbPnpl5TKHlm7BB2PbI3U3uJPrAcA7PjXwqRDxVC1ysIv16nohcZuApF4JixnAqN6z8xYy4PKxLYAWNmtQtWu0L4Pe5S4M6O9aFnvHbL87i3M/kMjAGsr2UvOUvYhCNx9mP3ka05+ht+9BQ2IRVa/N3Pnj38PA4Vj0/nj33MP2M4f/x5AIYdEFKgqClHGKOh49lXrw78Gu656+Syg5uqrmuRGtQ6xrmKEtEHcvYNMH2X1y+rzOu7XB69rihHtBoEKNaHsfBB37ygy+dVfzN1bVs49xsUo//xmNl5y+REhy+pw00R6ydBM2nGKHlNyea5aZcFyY8puLL2tDdmjG/h39wBkWlfz/JVecA9i70VfwOa3/S35cZDfZC65E9k3vqFUT1Q5gqKc6/KgfSi1bHG+bOKGysshTB2/oluUlUVNGjgTJEhQflSvsiiSOUycVWSmrwHg1Jp+xlEZ2Kwis/BuZBbeHfj6IIg6q0gQDpU25nqhWuVyo2qVhV+awe4pK9E9ZSVMSQJiczQ8ISx9ZzfoO7sdx3oaVzmYsyoZV8Hc2wfNPmlchd4xHdqiBdAWLXCcc2+9VUNsiKwPLKUgk1fvmF42WfVLL7H+2+1xGS69BHrnzPxnu1xccKcflEGUJSx4HZdcBP2SizBo9k2OrVPGZ+GldcVdA05+YwdZEV0PnZ6wf/iHACwvUebPwY5xjIxWjM/CETvi4qhwr2Ezrau9ZbOvrSifhUQON7KHvh+art8NvzU+OTUkLUNODWHz/of5Z7GuOMZNxVYmyhIV2dceDHVd1Ro4VVmeexpX8aAxlpSY5nK+SxFPdu9Zt1h1nBmC1tqCzXu+4zhfLezeIqu5Cjjzuc81ZWX3nnVLoCCxkrN7+/y2Xv4ekdm9bX+eYrj+2vtx6l1THCkFwhg49dYWzvCuNzfjZ9MGMLp3T2LgTJAgQXyo3pmFGwEzknEPQFdeETphzzhCLlNk2jwzYy2MY8cBSvnshjSki+f1oFQ5l4eqHCroSi2z+q7pFlepiyYuc9k6YN8BJbnEt5Tsu1dZ1m8vt31P2ZnXLrsPXPeEtvDdBWHmgOX12Pnj3xfIpl96CcipIZ7gJ8iYdqdXgE6MY9Dswwd6v4FTc+sAwMorQin0tja8fYfFPTHvrq14e6OVEcw8bZW76JkJ5Bp0pI+Ogu54Bbj6PZZMr++SjqFMtnk/egBtP21A55Z9/Fhu1x6kLpiDAz2zAQCdm6zxuO/FAVx9wc6COgghL1BKF6v0uXptFi4QXQ+1y6Gl05ykVkunQW2XcHPUqSzcTixB1qLZw49YDyE1QKZa3pPG0WMF5dwOP+JN4W63VHYQbs+xFcag4eLqcCf9gfdD5J7WF5NX7GsY5QhAyn+p8oB3aUthoHBMjVffCDzOnHxIoO//+eY7pU5Zb99pu1PfKcmuvtZbVlVctPIlT8fBjkcsI33WMVbKVUtRM8oiLAmvqGBoLgdqxMP8XdiQVS8dnwCQdyorBlU7QqxgzOeESFnQ9c6ZMO2HWVV+8bvXNeK5cuVEZaBLFnG3chFhdlm8cnywGBcGzUX4fNLOdeoHlfvGXSebqTHorS3ILZjrOLbza0uU6iyGmrFZkIAkvIzzov/ME/k66uugTWkAqSuBjrSZocmcWSBzZin94HRsrOz5TmkuZ22hGZsKYl4Ai0FLVa4ouU7L2W+y9WVpe2EYuLq0pdK3P9n6ssP46WZqa9m4rSDfqQxBxoXnOj1xkv+x72555t4dLfgMqCWbhU9gmRuy6bHW0GBllDIp6EQ4nk6/KXlm5s0ArC0/zymlvdaOsv0W2mahOHVnZf1kKBY/4VU2tOw+Ngu/OBKvc2Hk8hpHli/V3a7fLozfck75NxOyu6sgiM2iZmYWCRIkqCxqxmYRR5YxNquIK2OZtI0xa8biSf0nQKVM7CDFl3Pibogf3PIX6494jn0Ouhvih5733FNwrEtbyndDCmS6bF14Jyctn/fPsRvC6p6+Jr8bAmvnApDvhgBA1zVfBWDthqhCthsCAL0X3q68GxIEtaMsQmQoK6iCM4brgGtnJcpuiKONeutmMM8U3oTuqaaYJaxcuyG+OHK8IHuZ1xS4e8pKxzmePlICsU6v7Gi+CLkbcv2198O0vW4dY3rkODbvfzjcMlDgFfn55jutbGXIc5/0NK5y7IZc9bFvAwC2P3m7dcxjN6TYGLoxI5vG9idvcyhilnVs+m/bAOTjqOY/uB5v3aVctRS1Y7MIiEGzr+ga180yxY75MTLJbs7u+uX5XRf7zT1obML1195fUB9jsurcPoTnnl8HIM9wBcDacxfAZBLlpUsW8WuDgq2pcx++Eqn/yocFMB8U8SFgDwDZ+jLI4oUFsg2aVmZxhoHt9xa1WbD6wsp++d9YDE8zXjgNs07H0fc0Yvpv8/SHzz2/LpTNIoxczF/FfT9c8an16Hj5NAa238uPdV/1Zcd3N9zno9gsFn9ifSAGrCA2i5pSFmHftnHHP8gUkbuNYg5KcTtlMao9ZtwSfQG4PBfNAwDP9Aa83KWXVMQpi7k8d6dXSLcnu+uX54MLS+iUxdoP4sMx3rP4rHDKSgycCRIkUMLknVkIbx2VmUUgmwUhfG3q3qpSpddT2cYrKgNz1wZAUnWguYmCLTMxIpakLPOUV8BSGFrAIB6cUmg6iG4ZCt2zCcc46DdYfbS3u8N4cPK6JOPOjpG6eoccvKymWzM3gSxZLCPbFvYaGz95PcdQMKhy2MugIPR/PU0fR//px/n5ILR6tWPgDAqXoogLBTdcpZSt4HPCYhTcYMfKGUkaCKbhSSUgyjxobCqLsdfte1MwbhJZyza2QttRltXmUPgQ95qZWYicnCqDJPJ0urW6CkenF1gdvRdZ+TEYF0Hkt2xIOWTIXHInADkjV9Qw7TgRJsS6lAgySxHLl2PMpA5gMXCYTg4Dpw+fRc+0GwFY7tyc/MbO+QH4U+v53RjidI2lGOg//bjFCTD/Qv4gepHfhH3jZN79RQBA9vWvy8/PvBnZQ9+3PttKwXjrHWmbjBhYtrzS518I4613InkxxoFiik0sI8paKnyg9xv4+eY7ix7/QK8lJ/sexCM2Lhnr+3cAiOe3mhxRpz5KjMV8MAUhrsv9KPmKgeceGZ9AT8sn0X/yMccaDwByHU0O5RDnm8VLSfDztqJgcgAAeSsvhyPJkEtOEbmOJpC3Ks//yPrA5JAlGTJtWaPC78E+NbcOXVphkqFTc+t4kiG26xHnuH34ugfxX1vUnCBOza3jjl9hETbJULIbkiBBAiVU78xClexGF7wxbcu65dIdkoOTLT0aV4E0TpGLJrx1ys3ByZBpvwnEtR/vfmuKsrldsZmzWDnX3W5kFt4N8vs3HXIAAB66tSSerH7T9o4N25x2J9uXpgOWkfWKT61Hx2PbHHXFIZvKrOKKT63H0WsmcPEGZX5dKXrn3YYdf1zPv1+4sPFK1Wurd2ZB1ERjxL2DZh+IrvO/yM03NSFrk7RWI4K6TJsjo+HdrEuFQ0crLYET7pcTpfk/AB0vn3Z8Lyc6Xj6Nc7N65LbpcecL5k9H2pWv9TVwEkIeA/A/ARyilC60j90H4FMADtvFvkQp/U/73F0AVsNKB/m/KKX9fkJEIex10+YBsDOpF59ZeL1lMjMsp306NGwpjIPfc5zv0pZCa2go4CtQrT9OsPQEoiwknYY2bSoAqw/snPtN6NWHchs43X3Qp7fDOHosb7OYshKEEJijo5Fl87NZZKavgXH8OB8bvns2fQ3oyAj6h3/I89QYx4/z66LKlWld7WRtL1bWljFKu2IgX9wenI8DyEiOP0Qpfa/9xxTFnwFYBuBS+5rvEULCveZ9lFhXahm6UsscMws6Pg46Ph4pqjR7+BFkDz8Cc3yCKwrWFsPIdZdZBDIl8GPItK4uSn3PXLmZHCPXXca/D5p9GBjZyPvA5JSBXSf2oxJgfWByZA8/4pBnYGSjo49R4NfPt+94NwbNPvQP/9BR9u073s3TQbx9x7t5ubjGTVVRsPYjt3fs0VARv77KglL6CwCFhJJyfBTAM5TSMUrpHwG8DeCqwFIlSJCg6hDFwPlpQsjHAOwAcDul9DiA2QBE7rC99rHg8GHGYm63zN+iS1sKrdEiy6UTudBMWLz5qY3oPf9z2Lz7HwpcfNM/+XWkuovB7y3D3JG7p6xE2oeCTZTTHfpcyj6oIjPzZqSPyO0WooGzXLLOu2srILhZMBnmAcCd1jbuPBZ5W+iOUVJ0X/VlnJ43FfP6fhWpHveSp+Gc85QNnGGVxT8D+CoAav//NoBPBqmAELIGwBoAaEBjYQEfmwNbFgzmnslb/VkkaAwwh4bRf/KxgrYAiyi1VH4WbAnipTRYVOTAyEbOkcC4GLu0pTiz9H04s8LyTp0iyMmWa+z7yZVXo2Xjtor6WWQPfZ/3gftZ/NsCnPOXr/Ep/pK//hYMW9ZS4+2Nl6NLW8rHhskw70cP4KqPfRvbt9/LSWzKPW4shH3eRx/ARStfCl1P9sQPcMEjltfxrrVfwOiBvcrbK6F2QyilBymlBqXUBPAvyC819gGYIxQ9zz4mq2MDpXQxpXRxHUKwPVMToCZXEHHFa3TXL7ccvaiZ9wi12yoHzLExmMWIbyM4nJ3tqLQDmheuvGm9f6EqQKiZBSFkFqV0v/31rwAwVpR/B/AjQsh6AOcCmA9ge2QpZTLY26NU9Kng261maIXBorU0igEAAA3jSURBVDK765dzj1D3Vqw+5iTbjdMXgC2lPM/bTFxMDhFug9uSp77lKRu7tpJ+FjI5AACCXt76489jyV9/K5a2/AyS5um6fJknnccZwxXjo4hz3F54VN2TkrUfBbvWfiHUdb7KghDyNIAPAugghOwFcC+ADxJC3gtrGbITNkkYpfRVQsgmAL8HkANwC6URufASJEhQFfBVFpTS5ZLDnlY4SunXAHwtilAA/D047bf94PjG/NudbW/GxNfJtsvYDIOhdYcaoW2odluaip+vry+QwytkrpicrTsOeF5XTqiMZblkveiZCSk3pnj8omesJFJeHJqlBm+/AqheD06fZQTzqXDYLJhtIWQeUxHm2Bi3WbjtCDQV3UPUC8b+gzD2H/Q+LxAB05ReVJaw58oJvz6wMuVArkHejng816B7lisHKtl29caG+G2dutipBs0+7g1IDTPy1qk+vZ1HeLoZqMhw6dym2a6FF8RtXD85ip0vZR+CQEWOcsnKaPmLHfcqUy6kj46iUqQS1assJJRhDG4CEmZs8nPBdtQhEO7KDF+Gvf8vIzvJ7fuTb/09026EOTLiWb+nXG56NjHrOcDHRXRz94Iop9vPwqsPvRfeDvOw1XdzZLTAx0RFfpnxT29rg3n6NIC8ETkz82Y+zrJ6AGscmKyypMQquO5DD2DLT79UUH/qwrnY/PY3+QzSzYHivve6r/pyAcM5w4evexBAPihM5sJ95U3rfY2ZPS2fhHn6tMMVYNDYxP0spgntX7FmPV7cUFhf77mfxuY//ZM09D2Kn0XVkt+QunoHXZz7oe2d/RkAAB0Z4WzIrCwb8GIQH+DMwruRfcXbzNI7z/pBNv9xvXWTzTkPm3c9xOWKSn5z3QcewJaff8m/IICeK+5F/4sW/X7vBbcCgIOd2iH3Bbdi866HpA9was55yO3ZW3HyG9YHNp5eZURZS4Wua76KwV9KEhUJx1kyIP69zOQ3Xdd8Fdj2W0uGMpPfVK/NIkGCBFWF6l2G+DhBbd73XQD5KFEHAjouibMKlgKv/7dfzbf1R6fTjHHocKwenKqzCgB8VsHkENGlLbWiTm1fDXN42FM2dm2lHZXccuhtbTCOH3dEncYFv1mA/vouPoaM75Ud756yEgMjG3l6wTjHjTGyqUB/fReimu/9vIS9UL3KQiS1KQJxKzF/rA4YlhRWgDmtsD43/GwF5YDXzUrHxmBI5HOXr9Y+sPDrSigxtpxlY+OWoVQy+S2Z42pb1p8mtJU8NqTkILquZPXdvO+7hW+MVPhuydasCSYHqjUlQrXK5UbVKgs6Yc0q/DRqZubNvJw+Y4Z1bQRGqJ7L/w4AoB05CWNWe9EclQlqC+U2RqrCnaiqWpEYOBMkSKCEmlcW3HHK7IslOrT/pa+g/6WvACk9mVVMMlTjrAIodPqrVlStn0VUcGt6/XLubENSKR7iTe2s1YzlGgDPF6FSr4iepo/ztHCkzjKQDow9heuvvb+gPpbXo3P7EJ57fh2AfL4PAAVOP0wmumQRl5cuWcSvDYou/QaAUuSuuxKpLXkqA1m/rr/2ft4mWbywQLZBsw/dV+V3Zwa23+u5bBw0+3h9YWW//G+sXakZL5yGWafj6HsaMf23eUv2c8+vK+rv4nUujFzMWc49bld8aj06Xj7teNF0X/Xloi8e93nZGKoqusWfWB8oH8jkSDIUA9xkONQweMzJqXdZNP8tW/PnT71riuO7KsSdBZrLB/rI6js9byrwoeM4dbSl8DiAaTuc5VkdorzscxScuKgeHVvy37unrASdyDk8NsU2Le/BwnqY3CqIKveJP7dsUQ3HpsJIE5z481HUDUUfizjGk+HoNRNIn3KOid8YBRlDPxy+unRB3rUzs7CjUFW5I8RYkQKGa+ZCHQIyDZ+ZdQuMg4cc5zPtN/GtuALYfdFbLYXhWS6gHCpgMwt37M2g2Wf5rJwzA9h3QEkuvbXFUcb93ass63dQ0ljRRR9AQWSytvDdMF95veC6I2uXoPPHvy+QTb/0EpBTQ54esEVlEWYWH+j9Bs9U1rFhm/XbtrVxct15d23F2xsvB5Dno7jomQnkGnQr1mPHK4A909Vf3yUdQ5ls8370ANp+2oDOLXl+qdyuPUhdMAcHeiw2y85N1njc9+IArr5gZ0Edk3JmQerrA/sGsBBzt3LRm6eFekC9kN3/cIGlvWj99g0epwxB4PVQZA8/Emg/3y1/sf6I50L3W5bXQ4BMUQBAxyNbpY5MxqtvhJPDBhvH+v4dBSkFjePHLU5PGzIqvHog7x5gu3AHeYWxOt3eSLmdu9HxyG5HfffM+28YjEj2VvMGzgQJEpQHtbMMEeBIMuQyYAJO24RKHSLExMikIV3ghisSuoapP064CXsBOAl7/3cLP+cOGPPqQ7l3DNx9kBL2pomDQDcs/Pws5v3IIsOVEfbOyKax/cnbOWGvOFOIKpdX9GgxGaO0KxL2To5liA+fBcPA+NMFfBYgWmg+C5brNDPzZkfGchEtbw5VPNcpk0NEQa7TB77iKRu7ttIcnG45ABRwcHZd/ZVY2vJ7uNp+2iDl4Gz7aQO2P3kb/yzWFce4qSoKsf0oKBkHZ6VAdB00oBGSTLXJbscnIpPfkKZpnuf0N3eXLBVAEOhvOtelXdpS6M3NIB1W/kr92HFP2fQ3d8NA5QPJWB946PyFc5F7Z2feUNy6GrpGIgdPqaBzyz5rDG1jLJOhc8s+ZNpvQvbYo9yYWKlx69yyLzLFoAotgAxVqyzCUN7ToWH72ui0/fT0mch1JEgwmZAYOBMkSKCEqp1ZqLptM74DxkMAxJOIh54ZQmbWLcjuf7jgnDhFrZTNItO6GsapU45jBTYLQTZ3smU3u1glptWZBXcVyMEgMneVS7bcrj1Oj0/BqW/Q2ITFn1iPtl17uFyinKXG4k+sx+GrDVxstx8WjD2N4bxLm2qfVq9YKgDHbojARcmVxUTO1zjqZexiZDp0aBikqYlnUmcQ17Rh6o8TmfabADj9FkSbBT123FMpePWh3Lsh7j7IbBbQiENBh4Xfbkjvhbcjt3N3gc2i98LbQU+cRPbYo+i90Eo2lNu5m18XVS7GmalU1pYxSruizeKsotVjbNhx3eTZw48ge/gRQNcLFAVDbsHcWNqKityCuQWymBefj70fORd7P3JuUTmrtQ97P3Ku47x58fmxyep3jzCvR3d7B3pm82MHembzcnFBVVGw9qPi8Ifn4PCH5/gXdKHmlYW4DIkDmelrkJm+BjAMzpWRYHKg0js/XmDM4NWO6rVZVAjZoxsAwPLZ0OUJXfSX3kB/FfhZ6C9Z7srMuuN+c/Y0rkK/V67Tl96Aicr7WbA+9IuyP3Qr/ziw/V70NK5CHGmp/WYWnZteR1ZSpnPT6/y+YLEW2RjHzU3X7ydjVItckKhUETU/s0iQIEF5UL3Kwsfw2l2/HN31yx02CzqRs4ybEQlwACvhDNsJ6U6v4AluAOCdey5Hl7aUv1XifCtnZt5cdPnDvVRtOd6553L+vUtbigXrHoJ5YD7MA/O5nDKw68R+VAKsD0wO88B8hzwL1j3k6GMpcd+LA+jSlmL+g+sdMtz34gDmP7ief2blKjFu9704ELmO9a91Yf1rXYGvq97dEBcYPbsqZKQn+nRrlwATOem2o1c2La96RbBru6+8DwAw8MJ9vkQs7u1XsV2/pU3oEPUAPJRhEg8VG7eoiYzEDF3se1CWKVmGuUolWPJCFPKboJgcsSEu0PFw7tti3gnzzBAnAnZzSbAt0TBvi8yMtYCmo0tbCq0h77vv3p4U3bFZ+7wOlx+Ee4tTlNd9bRCQdNrKqnZOJ3KHjvAtZtnNyNphcssUrCi3Xx6KKHIDQOoCy4LPtlNTF8zhW6+AxY8RhCkrilyMHa0gC9y820CPn3SMhSyVoQi/80Hg9qOIEzUzsyjmdyGDmKRG9MNgysLthxF5ZmGTyjBlQerrizpNsQcQAIxTp8o2s2BRuqSuHjQ3UfBmziy4C9h/iMtVrC33TS5zFGMQlQ3rd9AHJOzMYvEn1qPj2VeRPfEDZ/7VSy5C9rUHY5lZLP6EtUxhxkMWS8IgRnoWg9cYymS74JFvYtfaL3C/CcDynei94Fa+NcrkWf9aF25bMFhQx1nlZ5EgQYLyoGaWISAaQINvGonJioiuA6b1TZtm8R6KWpy98UKJp+sWr0adRZuWPfED3zcte7MWm0GwN7I4C4kkZyoFmstBa2mCKfHgzL6W3/N3L40KyrpmBu43t/tc2LR5DKnzZhf97oUd/3ob8K8Smey+RhlPRxti3S7KQNWw8GJj6Aar073skC1DZLOKoKgdZRGCM9NN2GuOjPClzB/us1zi595tUZ91aUux82tLQtksRAIe80w+WvUPd17K62dt7P3SNXj109/DH+78G0cdC9ZZP/B5Qlmxjj/ceSmXl30OA9Nekr1x93xcdOs23g5boomEvawdJvd5D/zSUdeg2cflBoDX7r8VxRBFbgC49xfPAgAWrDsfuakUP/zFs5j/YN4T8a27bgtlswgjlxe7d9/bV+LvHl/pGIsF6x4qOjZ+54PAa7kRB6rCZkEIOQxgCMCRSstSZnQg6fPZgGru8wWU0hkqBatCWQAAIWSHqqFlsiDp89mBydLnxMCZIEECJSTKIkGCBEqoJmWxodICVABJn88OTIo+V43NIkGCBNWNappZJEiQoIqRKIsECRIoIVEWCRIkUEKiLBIkSKCERFkkSJBACf8fzaI6VNeS2YwAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb5d7e25c0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 54.954628467559814 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 1000000000.0} is: \n",
-      "[[6.4e+181 2.4e+037 0.0e+000 ... 0.0e+000 0.0e+000 0.0e+000]\n",
-      " [2.4e+037      inf 0.0e+000 ... 0.0e+000 0.0e+000 0.0e+000]\n",
-      " [0.0e+000 0.0e+000 6.4e+181 ... 6.4e+181 6.4e+181 6.4e+181]\n",
-      " ...\n",
-      " [0.0e+000 0.0e+000 6.4e+181 ...      nan      nan      nan]\n",
-      " [0.0e+000 0.0e+000 6.4e+181 ...      nan      nan      nan]\n",
-      " [0.0e+000 0.0e+000 6.4e+181 ...      nan      nan      inf]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb24fe26a0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 55.056718587875366 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'size', 'h': 5.0, 'lmda': 10000000000.0} is: \n",
-      "[[6.4e+201 2.4e+041 0.0e+000 ... 0.0e+000 0.0e+000 0.0e+000]\n",
-      " [2.4e+041      inf 0.0e+000 ... 0.0e+000 0.0e+000 0.0e+000]\n",
-      " [0.0e+000 0.0e+000 6.4e+201 ... 6.4e+201 6.4e+201 6.4e+201]\n",
-      " ...\n",
-      " [0.0e+000 0.0e+000 6.4e+201 ...      nan      nan      nan]\n",
-      " [0.0e+000 0.0e+000 6.4e+201 ...      nan      nan      nan]\n",
-      " [0.0e+000 0.0e+000 6.4e+201 ...      nan      nan      inf]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2468cfd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 59.41082525253296 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 5.0, 'lmda': 1e-10} is: \n",
-      "[[   80.00000004    24.             0.         ...     0.\n",
-      "      0.             0.        ]\n",
-      " [   24.            52.00000003     0.         ...     0.\n",
-      "      0.             0.        ]\n",
-      " [    0.             0.            80.00000004 ...    80.00000004\n",
-      "     80.00000004    80.00000004]\n",
-      " ...\n",
-      " [    0.             0.            80.00000004 ... 12052.00002528\n",
-      "  12052.00002538 11662.00002905]\n",
-      " [    0.             0.            80.00000004 ... 12052.00002538\n",
-      "  12068.00002698 11666.00003099]\n",
-      " [    0.             0.            80.00000004 ... 11662.00002905\n",
-      "  11666.00003099 11376.00005673]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb256f2198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 58.783164262771606 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 5.0, 'lmda': 1e-09} is: \n",
-      "[[   80.0000004     24.             0.         ...     0.\n",
-      "      0.             0.        ]\n",
-      " [   24.            52.0000003      0.         ...     0.\n",
-      "      0.             0.        ]\n",
-      " [    0.             0.            80.0000004  ...    80.0000004\n",
-      "     80.0000004     80.0000004 ]\n",
-      " ...\n",
-      " [    0.             0.            80.0000004  ... 12052.00025277\n",
-      "  12052.00025382 11662.00029054]\n",
-      " [    0.             0.            80.0000004  ... 12052.00025382\n",
-      "  12068.00026978 11666.00030994]\n",
-      " [    0.             0.            80.0000004  ... 11662.00029054\n",
-      "  11666.00030994 11376.00056734]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb2461a198>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 60.10993981361389 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 5.0, 'lmda': 1e-08} is: \n",
-      "[[   80.000004      24.             0.         ...     0.\n",
-      "      0.             0.        ]\n",
-      " [   24.            52.00000304     0.         ...     0.\n",
-      "      0.             0.        ]\n",
-      " [    0.             0.            80.000004   ...    80.000004\n",
-      "     80.000004      80.000004  ]\n",
-      " ...\n",
-      " [    0.             0.            80.000004   ... 12052.00252772\n",
-      "  12052.00253822 11662.00290536]\n",
-      " [    0.             0.            80.000004   ... 12052.00253822\n",
-      "  12068.00269784 11666.00309938]\n",
-      " [    0.             0.            80.000004   ... 11662.00290536\n",
-      "  11666.00309938 11376.00567344]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 183 built in 60.08261752128601 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'kernel_type': 'branching', 'h': 5.0, 'lmda': 1e-07} is: \n",
-      "[[   80.00004       24.             0.         ...     0.\n",
-      "      0.             0.        ]\n",
-      " [   24.            52.0000304      0.         ...     0.\n",
-      "      0.             0.        ]\n",
-      " [    0.             0.            80.00004    ...    80.00004\n",
-      "     80.00004       80.00004   ]\n",
-      " ...\n",
-      " [    0.             0.            80.00004    ... 12052.02527724\n",
-      "  12052.02538223 11662.02905363]\n",
-      " [    0.             0.            80.00004    ... 12052.02538223\n",
-      "  12068.02697844 11666.03099384]\n",
-      " [    0.             0.            80.00004    ... 11662.02905363\n",
-      "  11666.03099384 11376.05673453]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcb688ddf60>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "%load_ext line_profiler\n",
-    "%matplotlib inline\n",
-    "import numpy as np\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.model_selection_precomputed import model_selection_for_precomputed_kernel\n",
-    "from pygraph.kernels.treePatternKernel import treepatternkernel\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "estimator = treepatternkernel\n",
-    "param_grid_precomputed = {'h': np.linspace(1, 10, 10), \n",
-    "                          'lmda': np.logspace(-10, 10, num = 21, base = 10),\n",
-    "                          'kernel_type': ['untiln', 'size', 'branching']}\n",
-    "param_grid = {'alpha': np.logspace(-10, 10, num = 41, base = 10)}\n",
-    "\n",
-    "model_selection_for_precomputed_kernel(datafile, estimator, param_grid_precomputed, param_grid, \n",
-    "                                       'regression', NUM_TRIALS=30)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1e-10 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.36956548690796 seconds ---\n",
-      "[[ 13.          14.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [ 14.          20.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [  4.           4.          13.         ...  29.          29.\n",
-      "   29.        ]\n",
-      " ...\n",
-      " [ 20.          20.          29.         ... 365.00000001 365.00000001\n",
-      "  365.00000001]\n",
-      " [ 20.          20.          29.         ... 365.00000001 365.00000001\n",
-      "  365.00000001]\n",
-      " [ 20.          20.          29.         ... 365.00000001 365.00000001\n",
-      "  365.00000002]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  91%|█████████▏| 914/1000 [00:01<00:00, 751.28it/s]\n",
-      " Mean performance on train set: 5.993535\n",
-      "With standard deviation: 0.356922\n",
-      "\n",
-      " Mean performance on test set: 7.464904\n",
-      "With standard deviation: 1.718585\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 795.88it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1e-09 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.47467517852783 seconds ---\n",
-      "[[ 13.          14.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [ 14.          20.00000001   4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [  4.           4.          13.         ...  29.          29.\n",
-      "   29.        ]\n",
-      " ...\n",
-      " [ 20.          20.          29.         ... 365.00000015 365.00000015\n",
-      "  365.00000015]\n",
-      " [ 20.          20.          29.         ... 365.00000015 365.00000015\n",
-      "  365.00000015]\n",
-      " [ 20.          20.          29.         ... 365.00000015 365.00000015\n",
-      "  365.0000002 ]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 975/1000 [00:01<00:00, 654.33it/s]\n",
-      " Mean performance on train set: 5.963041\n",
-      "With standard deviation: 0.374107\n",
-      "\n",
-      " Mean performance on test set: 7.375105\n",
-      "With standard deviation: 1.769252\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 711.24it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1e-08 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.32968211174011 seconds ---\n",
-      "[[ 13.00000004  14.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [ 14.          20.00000008   4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [  4.           4.          13.00000004 ...  29.00000004  29.00000004\n",
-      "   29.00000004]\n",
-      " ...\n",
-      " [ 20.          20.          29.00000004 ... 365.00000148 365.00000148\n",
-      "  365.00000148]\n",
-      " [ 20.          20.          29.00000004 ... 365.00000148 365.00000148\n",
-      "  365.00000148]\n",
-      " [ 20.          20.          29.00000004 ... 365.00000148 365.00000148\n",
-      "  365.00000202]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  97%|█████████▋| 967/1000 [00:01<00:00, 809.48it/s]\n",
-      " Mean performance on train set: 5.965110\n",
-      "With standard deviation: 0.378249\n",
-      "\n",
-      " Mean performance on test set: 7.350689\n",
-      "With standard deviation: 1.780556\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 786.78it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1e-07 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.74151062965393 seconds ---\n",
-      "[[ 13.0000004  14.          4.        ...  20.         20.\n",
-      "   20.       ]\n",
-      " [ 14.         20.0000008   4.        ...  20.         20.\n",
-      "   20.       ]\n",
-      " [  4.          4.         13.0000004 ...  29.0000004  29.0000004\n",
-      "   29.0000004]\n",
-      " ...\n",
-      " [ 20.         20.         29.0000004 ... 365.0000148 365.0000148\n",
-      "  365.0000148]\n",
-      " [ 20.         20.         29.0000004 ... 365.0000148 365.0000148\n",
-      "  365.0000148]\n",
-      " [ 20.         20.         29.0000004 ... 365.0000148 365.0000148\n",
-      "  365.0000202]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  95%|█████████▌| 954/1000 [00:01<00:00, 735.76it/s]\n",
-      " Mean performance on train set: 5.966982\n",
-      "With standard deviation: 0.382093\n",
-      "\n",
-      " Mean performance on test set: 7.350999\n",
-      "With standard deviation: 1.781470\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 804.24it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1e-06 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.52131748199463 seconds ---\n",
-      "[[ 13.000004  14.         4.       ...  20.        20.        20.      ]\n",
-      " [ 14.        20.000008   4.       ...  20.        20.        20.      ]\n",
-      " [  4.         4.        13.000004 ...  29.000004  29.000004  29.000004]\n",
-      " ...\n",
-      " [ 20.        20.        29.000004 ... 365.000148 365.000148 365.000148]\n",
-      " [ 20.        20.        29.000004 ... 365.000148 365.000148 365.000148]\n",
-      " [ 20.        20.        29.000004 ... 365.000148 365.000148 365.000202]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  97%|█████████▋| 970/1000 [00:01<00:00, 759.32it/s]\n",
-      " Mean performance on train set: 5.969758\n",
-      "With standard deviation: 0.386318\n",
-      "\n",
-      " Mean performance on test set: 7.351225\n",
-      "With standard deviation: 1.780522\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 783.42it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1e-05 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.67099857330322 seconds ---\n",
-      "[[ 13.00004     14.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [ 14.          20.00008      4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [  4.           4.          13.00004    ...  29.00004     29.00004\n",
-      "   29.00004   ]\n",
-      " ...\n",
-      " [ 20.          20.          29.00004    ... 365.00148001 365.00148001\n",
-      "  365.00148   ]\n",
-      " [ 20.          20.          29.00004    ... 365.00148001 365.00148001\n",
-      "  365.00148   ]\n",
-      " [ 20.          20.          29.00004    ... 365.00148    365.00148\n",
-      "  365.00202   ]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 801.70it/s]\n",
-      " Mean performance on train set: 5.970557\n",
-      "With standard deviation: 0.390719\n",
-      "\n",
-      " Mean performance on test set: 7.348129\n",
-      "With standard deviation: 1.780293\n",
-      "\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 0.0001 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 36.80127692222595 seconds ---\n",
-      "[[ 13.0004      14.           4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [ 14.          20.0008       4.         ...  20.          20.\n",
-      "   20.        ]\n",
-      " [  4.           4.          13.0004     ...  29.0004      29.0004\n",
-      "   29.0004    ]\n",
-      " ...\n",
-      " [ 20.          20.          29.0004     ... 365.01480072 365.01480072\n",
-      "  365.0148    ]\n",
-      " [ 20.          20.          29.0004     ... 365.01480072 365.01480072\n",
-      "  365.0148    ]\n",
-      " [ 20.          20.          29.0004     ... 365.0148     365.0148\n",
-      "  365.0202    ]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 980/1000 [00:01<00:00, 889.41it/s]\n",
-      " Mean performance on train set: 5.942495\n",
-      "With standard deviation: 0.331983\n",
-      "\n",
-      " Mean performance on test set: 7.349836\n",
-      "With standard deviation: 1.781100\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 883.76it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 0.001 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 35.8681423664093 seconds ---\n",
-      "[[ 13.004     14.         4.       ...  20.        20.        20.      ]\n",
-      " [ 14.        20.008      4.       ...  20.        20.        20.      ]\n",
-      " [  4.         4.        13.004    ...  29.004     29.004     29.004   ]\n",
-      " ...\n",
-      " [ 20.        20.        29.004    ... 365.148072 365.148072 365.148   ]\n",
-      " [ 20.        20.        29.004    ... 365.148072 365.148072 365.148   ]\n",
-      " [ 20.        20.        29.004    ... 365.148    365.148    365.202   ]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  99%|█████████▉| 988/1000 [00:01<00:00, 886.54it/s]\n",
-      " Mean performance on train set: 5.933395\n",
-      "With standard deviation: 0.324965\n",
-      "\n",
-      " Mean performance on test set: 7.357745\n",
-      "With standard deviation: 1.780977\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 888.00it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 0.01 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 36.001843214035034 seconds ---\n",
-      "[[ 13.04    14.       4.     ...  20.      20.      20.    ]\n",
-      " [ 14.      20.08     4.     ...  20.      20.      20.    ]\n",
-      " [  4.       4.      13.04   ...  29.04    29.04    29.04  ]\n",
-      " ...\n",
-      " [ 20.      20.      29.04   ... 366.4872 366.4872 366.48  ]\n",
-      " [ 20.      20.      29.04   ... 366.4872 366.4872 366.48  ]\n",
-      " [ 20.      20.      29.04   ... 366.48   366.48   367.02  ]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 978/1000 [00:01<00:00, 863.94it/s]\n",
-      " Mean performance on train set: 5.940695\n",
-      "With standard deviation: 0.347431\n",
-      "\n",
-      " Mean performance on test set: 7.374269\n",
-      "With standard deviation: 1.791145\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 878.96it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 0.1 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 36.37146854400635 seconds ---\n",
-      "[[ 13.4   14.     4.   ...  20.    20.    20.  ]\n",
-      " [ 14.    20.8    4.   ...  20.    20.    20.  ]\n",
-      " [  4.     4.    13.4  ...  29.4   29.4   29.4 ]\n",
-      " ...\n",
-      " [ 20.    20.    29.4  ... 380.52 380.52 379.8 ]\n",
-      " [ 20.    20.    29.4  ... 380.52 380.52 379.8 ]\n",
-      " [ 20.    20.    29.4  ... 379.8  379.8  385.2 ]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  99%|█████████▉| 993/1000 [00:01<00:00, 860.40it/s]\n",
-      " Mean performance on train set: 6.427114\n",
-      "With standard deviation: 1.293674\n",
-      "\n",
-      " Mean performance on test set: 7.329299\n",
-      "With standard deviation: 1.913634\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 883.01it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.83972358703613 seconds ---\n",
-      "[[ 17.  14.   4. ...  20.  20.  20.]\n",
-      " [ 14.  28.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.  17. ...  33.  33.  33.]\n",
-      " ...\n",
-      " [ 20.  20.  33. ... 585. 585. 513.]\n",
-      " [ 20.  20.  33. ... 585. 585. 513.]\n",
-      " [ 20.  20.  33. ... 513. 513. 567.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 979/1000 [00:01<00:00, 616.77it/s]\n",
-      " Mean performance on train set: 6.624254\n",
-      "With standard deviation: 1.224196\n",
-      "\n",
-      " Mean performance on test set: 7.271336\n",
-      "With standard deviation: 2.207735\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 630.82it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 10.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.50818395614624 seconds ---\n",
-      "[[5.300e+01 1.400e+01 4.000e+00 ... 2.000e+01 2.000e+01 2.000e+01]\n",
-      " [1.400e+01 1.000e+02 4.000e+00 ... 2.000e+01 2.000e+01 2.000e+01]\n",
-      " [4.000e+00 4.000e+00 5.300e+01 ... 6.900e+01 6.900e+01 6.900e+01]\n",
-      " ...\n",
-      " [2.000e+01 2.000e+01 6.900e+01 ... 9.045e+03 9.045e+03 1.845e+03]\n",
-      " [2.000e+01 2.000e+01 6.900e+01 ... 9.045e+03 9.045e+03 1.845e+03]\n",
-      " [2.000e+01 2.000e+01 6.900e+01 ... 1.845e+03 1.845e+03 2.385e+03]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:   8%|▊         | 77/1000 [00:00<00:01, 764.71it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.069543502626658e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.1303298666315776e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.70249458866672e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.63992169055093e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.438093960487116e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0002169262936346e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.5920339281975188e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.5874866272574162e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.0599424240471626e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.468773818521402e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.958334441043603e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  27%|██▋       | 267/1000 [00:00<00:01, 654.82it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/sklearn/linear_model/ridge.py:154: UserWarning: Singular matrix in solving dual problem. Using least-squares solution instead.\n",
-      "  warnings.warn(\"Singular matrix in solving dual problem. Using \"\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.055618175730539e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.7159074038024934e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.895455126720251e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.400306511546424e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.206478316049589e-19 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.8083631222444177e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.49051280863482e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.339852738992424e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.277544863160196e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.458523723353626e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  48%|████▊     | 477/1000 [00:00<00:00, 685.70it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6380760737666547e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.3843421259537676e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.890544546973404e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.054758730954765e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.9172765626494813e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.4455093698440067e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.2914256710839066e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.65667341282596e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.852926745577629e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.285092924342139e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  69%|██████▉   | 694/1000 [00:01<00:00, 712.57it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.700250453064005e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6205193931367065e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.4925504318417794e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.0111387119813346e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.343123723749221e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0143662852277667e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.206690575125046e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.049999246995425e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.4232350203422674e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.350008400303505e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.251763015291957e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  90%|█████████ | 902/1000 [00:01<00:00, 666.85it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.924869742342744e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.4010401637647583e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.5117924740400373e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.626753798403599e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.911227588173856e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.0660043401009468e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.3099139652029694e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.2680602391853274e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.396574210735164e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  97%|█████████▋| 969/1000 [00:01<00:00, 600.11it/s]\n",
-      " Mean performance on train set: 6.816974\n",
-      "With standard deviation: 1.501822\n",
-      "\n",
-      " Mean performance on test set: 7.497870\n",
-      "With standard deviation: 2.368148\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 648.87it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 100.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.09455919265747 seconds ---\n",
-      "[[4.13000e+02 1.40000e+01 4.00000e+00 ... 2.00000e+01 2.00000e+01\n",
-      "  2.00000e+01]\n",
-      " [1.40000e+01 8.20000e+02 4.00000e+00 ... 2.00000e+01 2.00000e+01\n",
-      "  2.00000e+01]\n",
-      " [4.00000e+00 4.00000e+00 4.13000e+02 ... 4.29000e+02 4.29000e+02\n",
-      "  4.29000e+02]\n",
-      " ...\n",
-      " [2.00000e+01 2.00000e+01 4.29000e+02 ... 7.35165e+05 7.35165e+05\n",
-      "  1.51650e+04]\n",
-      " [2.00000e+01 2.00000e+01 4.29000e+02 ... 7.35165e+05 7.35165e+05\n",
-      "  1.51650e+04]\n",
-      " [2.00000e+01 2.00000e+01 4.29000e+02 ... 1.51650e+04 1.51650e+04\n",
-      "  2.05650e+04]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  10%|▉         | 97/1000 [00:00<00:02, 436.93it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.249229588791739e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6092761314568358e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6033357497241564e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.0333531111165975e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.073851980749357e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.497880470461594e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0349745182117167e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  17%|█▋        | 169/1000 [00:00<00:02, 372.64it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.227908145504113e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.1894008132724887e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.9131474526752795e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.0421770253846576e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.864916618602575e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.663676730244888e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  31%|███▏      | 314/1000 [00:00<00:01, 429.29it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.6989200751598342e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.9988176582222278e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.173259131422707e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.069621878854856e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.087601566853754e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.1827598831940232e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.428244298929586e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.1120965359644164e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.8329496119281176e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.5128147762765525e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.173155329882729e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  50%|█████     | 501/1000 [00:01<00:00, 516.57it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.874621241781873e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.9047959204426696e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.03000007539236e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.8198639503150797e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.679200342495213e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6211471280327221e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.74280825574767e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.685372827008377e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.9723233156997277e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.142362330339379e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.0042133764798303e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.987833375253946e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  71%|███████   | 706/1000 [00:01<00:00, 471.97it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.63949546549065e-19 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.76170805410039e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.3721058293845662e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.178277242767302e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.4883373934010664e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.526360275338589e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.827383891217367e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  81%|████████  | 807/1000 [00:01<00:00, 457.30it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.052622499085628e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.70793549450487e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.8190124240850417e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.349104192126423e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.132340452050677e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  91%|█████████ | 909/1000 [00:01<00:00, 451.90it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.78695142234395e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.8765535280551442e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.9917255115528226e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.781650263544808e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.581768670551366e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.0493867289518776e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.9787087068181396e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.756012232435961e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.800283208793992e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.468606690086715e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.119459703249427e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  96%|█████████▌| 956/1000 [00:02<00:00, 445.96it/s]\n",
-      " Mean performance on train set: 6.687664\n",
-      "With standard deviation: 1.348089\n",
-      "\n",
-      " Mean performance on test set: 7.428867\n",
-      "With standard deviation: 2.647892\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:02<00:00, 467.65it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.517051219940186 seconds ---\n",
-      "[[4.0130000e+03 1.4000000e+01 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [1.4000000e+01 8.0200000e+03 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [4.0000000e+00 4.0000000e+00 4.0130000e+03 ... 4.0290000e+03\n",
-      "  4.0290000e+03 4.0290000e+03]\n",
-      " ...\n",
-      " [2.0000000e+01 2.0000000e+01 4.0290000e+03 ... 7.2148365e+07\n",
-      "  7.2148365e+07 1.4836500e+05]\n",
-      " [2.0000000e+01 2.0000000e+01 4.0290000e+03 ... 7.2148365e+07\n",
-      "  7.2148365e+07 1.4836500e+05]\n",
-      " [2.0000000e+01 2.0000000e+01 4.0290000e+03 ... 1.4836500e+05\n",
-      "  1.4836500e+05 2.0236500e+05]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  10%|█         | 102/1000 [00:00<00:02, 330.46it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.374017095746491e-19 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.687507275679712e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.7645414168071277e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.8090152927008474e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.474194561968185e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.130856876335615e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  19%|█▉        | 188/1000 [00:00<00:02, 348.40it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.7794644716713837e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.3130943734340723e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.7505566440337117e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.3279670378456666e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.318466984022222e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.418445519765442e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  28%|██▊       | 285/1000 [00:00<00:01, 380.47it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.1356199672921913e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6464620684950592e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.179430869121561e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.473887201835687e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.570987725305032e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.854640029504099e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  38%|███▊      | 385/1000 [00:00<00:01, 389.24it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.3781828327775562e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.955507306233033e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.109947315270106e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.9378280303294975e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.866942525478256e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  49%|████▉     | 494/1000 [00:01<00:01, 398.83it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.636014964778956e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.6552163232757833e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.312233993243073e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.2794244316598437e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.406028628818668e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  60%|██████    | 604/1000 [00:01<00:00, 407.30it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.184686103929999e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.1281587780183657e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.367013528660628e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.155116554595105e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.443029464120917e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.4923079446940085e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.750703061909557e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  71%|███████   | 707/1000 [00:01<00:00, 402.63it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.4970615125032324e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.39494402062226e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.818999641865095e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.051275910233908e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.688197813410084e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  81%|████████  | 806/1000 [00:01<00:00, 404.11it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.43659662072146e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.4284104102664825e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.900304923444742e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.1112688931900636e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.941184656304436e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.746476431972804e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  91%|█████████ | 906/1000 [00:02<00:00, 407.57it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.327409345420052e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.0589341144557062e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.29154188313992e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.225020130252359e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.327720201864263e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  95%|█████████▌| 951/1000 [00:02<00:00, 373.87it/s]\n",
-      " Mean performance on train set: 6.819058\n",
-      "With standard deviation: 1.410085\n",
-      "\n",
-      " Mean performance on test set: 7.249143\n",
-      "With standard deviation: 2.655536\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:02<00:00, 414.03it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.193651783291256e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.19984276961351e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.0689487149937185e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.8956869823870564e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.790887064559792e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 10000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.01269268989563 seconds ---\n",
-      "[[4.00130000e+04 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [1.40000000e+01 8.00200000e+04 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.00130000e+04 ... 4.00290000e+04\n",
-      "  4.00290000e+04 4.00290000e+04]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.00290000e+04 ... 7.20148036e+09\n",
-      "  7.20148036e+09 1.48036500e+06]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00290000e+04 ... 7.20148036e+09\n",
-      "  7.20148036e+09 1.48036500e+06]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00290000e+04 ... 1.48036500e+06\n",
-      "  1.48036500e+06 2.02036500e+06]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  11%|█▏        | 114/1000 [00:00<00:02, 303.84it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6978549111114387e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.1828172674052679e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.547017114313022e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.990786470945978e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.8300974250606965e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.727582936838558e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  21%|██        | 208/1000 [00:00<00:02, 342.60it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.569354559683504e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.885865920757663e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.006883677471783e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.2491482969368813e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.596699463334369e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.74024827114128e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0002891123411383e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  31%|███       | 311/1000 [00:00<00:01, 371.07it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.478112292477647e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.3626069490970097e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.751107853461428e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.007160521891646e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.592912372477283e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  41%|████▏     | 414/1000 [00:01<00:01, 394.40it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.286966904954778e-19 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.330065717080935e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.0639972759819077e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.3250852692883386e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.32507703774876e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.514317701906229e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  51%|█████▏    | 514/1000 [00:01<00:01, 411.17it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.5186106207732215e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.2309907116861648e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.582391203608073e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.638503426307468e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0580872068659216e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  62%|██████▏   | 615/1000 [00:01<00:00, 424.96it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.633316922861427e-19 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.253166879599146e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.4688155478710103e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.3252803222906435e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.713726552669558e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.934042177466841e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.468592067289146e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  72%|███████▏  | 716/1000 [00:01<00:00, 433.84it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.66227030386163e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.5342528466878185e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.620745355332433e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.5797394734563764e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.109079490079661e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.548426603146641e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0484899604694826e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  82%|████████▏ | 816/1000 [00:01<00:00, 439.46it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.080827240476694e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.8279322282295696e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.0410721959495632e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.343375151645726e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.351177509861134e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.370583478449445e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  92%|█████████▏| 916/1000 [00:02<00:00, 437.07it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.3677978521118296e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0227997187914302e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.557088603475233e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.657645350184021e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.990628121216557e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  96%|█████████▌| 962/1000 [00:02<00:00, 393.51it/s]\n",
-      " Mean performance on train set: 6.934306\n",
-      "With standard deviation: 1.384412\n",
-      "\n",
-      " Mean performance on test set: 7.081832\n",
-      "With standard deviation: 2.624800\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:02<00:00, 420.16it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.2964047050969517e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.089708488833387e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.3234351109582e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.293818265362604e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.44555950404844e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 100000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 35.835275411605835 seconds ---\n",
-      "[[4.0001300e+05 1.4000000e+01 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [1.4000000e+01 8.0002000e+05 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [4.0000000e+00 4.0000000e+00 4.0001300e+05 ... 4.0002900e+05\n",
-      "  4.0002900e+05 4.0002900e+05]\n",
-      " ...\n",
-      " [2.0000000e+01 2.0000000e+01 4.0002900e+05 ... 7.2001480e+11\n",
-      "  7.2001480e+11 1.4800365e+07]\n",
-      " [2.0000000e+01 2.0000000e+01 4.0002900e+05 ... 7.2001480e+11\n",
-      "  7.2001480e+11 1.4800365e+07]\n",
-      " [2.0000000e+01 2.0000000e+01 4.0002900e+05 ... 1.4800365e+07\n",
-      "  1.4800365e+07 2.0200365e+07]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  13%|█▎        | 126/1000 [00:00<00:03, 261.95it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.0191112815027622e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.232307074954237e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.097885039345644e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.727869526025791e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  21%|██        | 208/1000 [00:00<00:03, 262.44it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.2411064955279154e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.149899322677468e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.642478117522784e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  30%|███       | 305/1000 [00:01<00:02, 265.15it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.785067039039337e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.225934530879337e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.562790184640486e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  41%|████▏     | 414/1000 [00:01<00:01, 297.05it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.135758789917749e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.564182826681079e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.542436590136228e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  50%|█████     | 500/1000 [00:01<00:01, 319.27it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.195315905739342e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.379873880613873e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.630975349505465e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.518071272961898e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  61%|██████▏   | 613/1000 [00:02<00:01, 303.76it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.9460047081015216e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.839254463570563e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.318583704180543e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  73%|███████▎  | 728/1000 [00:02<00:00, 300.34it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.3984244112232524e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.3291156014339405e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.707621088224988e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0690013288979288e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  81%|████████▏ | 813/1000 [00:02<00:00, 321.97it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.315773170165585e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.138544398203078e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.386508127676171e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  89%|████████▉ | 891/1000 [00:02<00:00, 317.18it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.6842499515474312e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.528434456947986e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.856433851414765e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  96%|█████████▌| 957/1000 [00:03<00:00, 259.36it/s]\n",
-      " Mean performance on train set: 9.394995\n",
-      "With standard deviation: 1.047066\n",
-      "\n",
-      " Mean performance on test set: 8.237631\n",
-      "With standard deviation: 3.665300\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:03<00:00, 299.25it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1000000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.056791553686018e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.644703618966645e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.15242050721053e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.77732253074646 seconds ---\n",
-      "[[4.00001300e+06 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [1.40000000e+01 8.00002000e+06 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.00001300e+06 ... 4.00002900e+06\n",
-      "  4.00002900e+06 4.00002900e+06]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.00002900e+06 ... 7.20001480e+13\n",
-      "  7.20001480e+13 1.48000365e+08]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00002900e+06 ... 7.20001480e+13\n",
-      "  7.20001480e+13 1.48000365e+08]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00002900e+06 ... 1.48000365e+08\n",
-      "  1.48000365e+08 2.02000365e+08]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  14%|█▎        | 135/1000 [00:00<00:03, 253.06it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.741195162637844e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.5965964498458038e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.983361443347492e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.7922291165206923e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.685526054240851e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  23%|██▎       | 230/1000 [00:00<00:02, 265.75it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6848871984797616e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.8811603375005575e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.7514073450053307e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.5976314128410034e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.790988115471154e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.477178586927344e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.035215871851048e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  33%|███▎      | 332/1000 [00:01<00:02, 277.35it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.287317576627726e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.886325173924881e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.8372812242318245e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.523017625167697e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.309735186090854e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  43%|████▎     | 431/1000 [00:01<00:02, 258.66it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.2092887442597021e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.444285941342485e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6650957319224102e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.778343353100153e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.067496740668901e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.832366528737191e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  53%|█████▎    | 534/1000 [00:01<00:01, 252.20it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.2368084459111367e-19 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.625050966790768e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.786992563738048e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.5350081600164477e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.2823286559994256e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.880362578796432e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.1100444346816681e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  64%|██████▎   | 637/1000 [00:02<00:01, 260.77it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.1335408080135885e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.4688002952482946e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.6678722631357644e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.288251804550535e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.895017980474164e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  74%|███████▍  | 741/1000 [00:02<00:00, 276.66it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.209157188853246e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.4519382674684447e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.5748326244710203e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.852436562697074e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.536506069365062e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.969036612017947e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  81%|████████▏ | 813/1000 [00:02<00:00, 297.62it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.309383987394578e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.565067260805818e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.516194197490843e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.041064934861363e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.499601220689098e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.051151158798192e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  92%|█████████▏| 915/1000 [00:03<00:00, 298.37it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.7472428919435347e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.703770718809819e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.2818242346374262e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.102554831016506e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.599188283622467e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0647003359802031e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  98%|█████████▊| 977/1000 [00:03<00:00, 278.57it/s]\n",
-      " Mean performance on train set: 9.635245\n",
-      "With standard deviation: 0.687560\n",
-      "\n",
-      " Mean performance on test set: 8.529828\n",
-      "With standard deviation: 3.580591\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:03<00:00, 284.18it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 10000000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.502409510736216e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0439081147173944e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.4602149061556115e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.9479003259500843e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.34621741763787e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.0245542507930726e-16 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.46095633506775 seconds ---\n",
-      "[[4.00000130e+07 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [1.40000000e+01 8.00000200e+07 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.00000130e+07 ... 4.00000290e+07\n",
-      "  4.00000290e+07 4.00000290e+07]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000290e+07 ... 7.20000148e+15\n",
-      "  7.20000148e+15 1.48000036e+09]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000290e+07 ... 7.20000148e+15\n",
-      "  7.20000148e+15 1.48000036e+09]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000290e+07 ... 1.48000036e+09\n",
-      "  1.48000036e+09 2.02000036e+09]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  12%|█▏        | 122/1000 [00:00<00:03, 231.16it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.200122265640733e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.627297027618617e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.893611596005168e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.1052758523976415e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.158312302718829e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.675650470006637e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  23%|██▎       | 227/1000 [00:00<00:03, 253.57it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.2230286797750079e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.0790289882373515e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.6170735381557016e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.90989130271085e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.4735492461286675e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.544548737558878e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  34%|███▍      | 344/1000 [00:01<00:02, 274.36it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.0569387542185164e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.8929851773550792e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.762490810329375e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.031994076021703e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.380795983197089e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  44%|████▎     | 437/1000 [00:01<00:02, 281.37it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.159845331824398e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.592173545119868e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.0031182975801337e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.315102488294594e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.427690586128571e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.36815306216013e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  52%|█████▎    | 525/1000 [00:01<00:01, 277.96it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.096509347533013e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.2037051514926243e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.641239932076709e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.911654384898199e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.195245830759744e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  61%|██████    | 606/1000 [00:02<00:01, 236.45it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.179739003035368e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.121167134816686e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 2.201750997217992e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.6143396276266097e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.876412427833992e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 8.158416120381036e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  73%|███████▎  | 727/1000 [00:02<00:01, 211.65it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.355737066205781e-20 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 6.778261189640049e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.992328403436096e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.166526583123927e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.566565138343654e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.272056103177315e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  82%|████████▏ | 822/1000 [00:03<00:00, 223.94it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.2435735437353417e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.471379508084743e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.686971341479104e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.827108937015577e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  93%|█████████▎| 931/1000 [00:03<00:00, 255.06it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.2357280081107672e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.559072238694825e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.45488311322705e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.6616151717441874e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.807701664283496e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  98%|█████████▊| 983/1000 [00:04<00:00, 220.81it/s]\n",
-      " Mean performance on train set: 11.059074\n",
-      "With standard deviation: 1.323635\n",
-      "\n",
-      " Mean performance on test set: 10.964175\n",
-      "With standard deviation: 3.358726\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:04<00:00, 242.35it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 100000000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 9.749823872976888e-19 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 5.347208969568296e-18 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 1.9981807042259307e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 3.298232968104139e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 4.391381083354749e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/scipy/linalg/basic.py:40: RuntimeWarning: scipy.linalg.solve\n",
-      "Ill-conditioned matrix detected. Result is not guaranteed to be accurate.\n",
-      "Reciprocal condition number/precision: 7.328796748008544e-17 / 1.1102230246251565e-16\n",
-      "  RuntimeWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.91001057624817 seconds ---\n",
-      "[[4.00000013e+08 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [1.40000000e+01 8.00000020e+08 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.00000013e+08 ... 4.00000029e+08\n",
-      "  4.00000029e+08 4.00000029e+08]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000029e+08 ... 7.20000015e+17\n",
-      "  7.20000015e+17 1.48000004e+10]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000029e+08 ... 7.20000015e+17\n",
-      "  7.20000015e+17 1.48000004e+10]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000029e+08 ... 1.48000004e+10\n",
-      "  1.48000004e+10 2.02000004e+10]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  99%|█████████▉| 992/1000 [00:03<00:00, 267.91it/s]\n",
-      " Mean performance on train set: 66.147687\n",
-      "With standard deviation: 11.979989\n",
-      "\n",
-      " Mean performance on test set: 63.221208\n",
-      "With standard deviation: 13.381090\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:03<00:00, 252.05it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 1000000000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 38.43676400184631 seconds ---\n",
-      "[[4.00000001e+09 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [1.40000000e+01 8.00000002e+09 4.00000000e+00 ... 2.00000000e+01\n",
-      "  2.00000000e+01 2.00000000e+01]\n",
-      " [4.00000000e+00 4.00000000e+00 4.00000001e+09 ... 4.00000003e+09\n",
-      "  4.00000003e+09 4.00000003e+09]\n",
-      " ...\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000003e+09 ... 7.20000001e+19\n",
-      "  7.20000001e+19 1.48000000e+11]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000003e+09 ... 7.20000001e+19\n",
-      "  7.20000001e+19 1.48000000e+11]\n",
-      " [2.00000000e+01 2.00000000e+01 4.00000003e+09 ... 1.48000000e+11\n",
-      "  1.48000000e+11 2.02000000e+11]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 976/1000 [00:04<00:00, 268.70it/s]\n",
-      " Mean performance on train set: 96.664827\n",
-      "With standard deviation: 1.871320\n",
-      "\n",
-      " Mean performance on test set: 100.134704\n",
-      "With standard deviation: 13.845906\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:04<00:00, 236.90it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when lmda = 10000000000.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 185 built in 37.32151246070862 seconds ---\n",
-      "[[4.00e+10 1.40e+01 4.00e+00 ... 2.00e+01 2.00e+01 2.00e+01]\n",
-      " [1.40e+01 8.00e+10 4.00e+00 ... 2.00e+01 2.00e+01 2.00e+01]\n",
-      " [4.00e+00 4.00e+00 4.00e+10 ... 4.00e+10 4.00e+10 4.00e+10]\n",
-      " ...\n",
-      " [2.00e+01 2.00e+01 4.00e+10 ... 7.20e+21 7.20e+21 1.48e+12]\n",
-      " [2.00e+01 2.00e+01 4.00e+10 ... 7.20e+21 7.20e+21 1.48e+12]\n",
-      " [2.00e+01 2.00e+01 4.00e+10 ... 1.48e+12 1.48e+12 2.02e+12]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance: 100%|█████████▉| 997/1000 [00:03<00:00, 268.42it/s]\n",
-      " Mean performance on train set: 98.175092\n",
-      "With standard deviation: 4.720613\n",
-      "\n",
-      " Mean performance on test set: 100.144883\n",
-      "With standard deviation: 13.958659\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:03<00:00, 260.49it/s]\n",
-      "\n",
-      "\n",
-      "       lmda    rmse_test    std_test    rmse_train    std_train    k_time\n",
-      "-----------  -----------  ----------  ------------  -----------  --------\n",
-      "     1e-10       7.4649      1.71858       5.99354     0.356922   37.3696\n",
-      "     1e-09       7.37511     1.76925       5.96304     0.374107   37.4747\n",
-      "     1e-08       7.35069     1.78056       5.96511     0.378249   37.3297\n",
-      "     1e-07       7.351       1.78147       5.96698     0.382093   37.7415\n",
-      "     1e-06       7.35123     1.78052       5.96976     0.386318   37.5213\n",
-      "     1e-05       7.34813     1.78029       5.97056     0.390719   37.671\n",
-      "     0.0001      7.34984     1.7811        5.9425      0.331983   36.8013\n",
-      "     0.001       7.35775     1.78098       5.9334      0.324965   35.8681\n",
-      "     0.01        7.37427     1.79115       5.94069     0.347431   36.0018\n",
-      "     0.1         7.3293      1.91363       6.42711     1.29367    36.3715\n",
-      "     1           7.27134     2.20774       6.62425     1.2242     37.8397\n",
-      "    10           7.49787     2.36815       6.81697     1.50182    37.5082\n",
-      "   100           7.42887     2.64789       6.68766     1.34809    37.0946\n",
-      "  1000           7.24914     2.65554       6.81906     1.41008    37.5171\n",
-      " 10000           7.08183     2.6248        6.93431     1.38441    37.0127\n",
-      "100000           8.23763     3.6653        9.395       1.04707    35.8353\n",
-      "     1e+06       8.52983     3.58059       9.63525     0.68756    37.7773\n",
-      "     1e+07      10.9642      3.35873      11.0591      1.32363    37.461\n",
-      "     1e+08      63.2212     13.3811       66.1477     11.98       37.91\n",
-      "     1e+09     100.135      13.8459       96.6648      1.87132    38.4368\n",
-      "     1e+10     100.145      13.9587       98.1751      4.72061    37.3215\n"
-     ]
-    }
-   ],
-   "source": [
-    "# tree pattern kernel, dataset acyclic.\n",
-    "%load_ext line_profiler\n",
-    "\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.treePatternKernel import treepatternkernel\n",
-    "\n",
-    "import numpy as np\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_path_acyclic/'\n",
-    "\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', labeled = True, \\\n",
-    "    kernel_type = 'untiln', h = 2)\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, treepatternkernel, kernel_para, \\\n",
-    "    hyper_name = 'lmda', hyper_range = np.logspace(-10, 10, num = 21, base = 10), \\\n",
-    "    normalize = False, model_type = 'regression')\n",
-    "\n",
-    "# kernel_para['depth'] = 10\n",
-    "# %lprun -f untildpathkernel \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, normalize = False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# results\n",
-    "\n",
-    "# untiln kernel when h = 2\n",
-    "       lmda    rmse_test    std_test    rmse_train    std_train    k_time\n",
-    "-----------  -----------  ----------  ------------  -----------  --------\n",
-    "     1e-10       7.46524     1.71862       5.99486     0.356634   38.1447\n",
-    "     1e-09       7.37326     1.77195       5.96155     0.374395   37.4921\n",
-    "     1e-08       7.35105     1.78349       5.96481     0.378047   37.9971\n",
-    "     1e-07       7.35213     1.77903       5.96728     0.382251   38.3182\n",
-    "     1e-06       7.3524      1.77992       5.9696      0.3863     39.6428\n",
-    "     1e-05       7.34958     1.78141       5.97114     0.39017    37.3711\n",
-    "     0.0001      7.3513      1.78136       5.94251     0.331843   37.3967\n",
-    "     0.001       7.35822     1.78119       5.9326      0.32534    36.7357\n",
-    "     0.01        7.37552     1.79037       5.94089     0.34763    36.8864\n",
-    "     0.1         7.32951     1.91346       6.42634     1.29405    36.8382\n",
-    "     1           7.27134     2.20774       6.62425     1.2242     37.2425\n",
-    "    10           7.49787     2.36815       6.81697     1.50182    37.8286\n",
-    "   100           7.42887     2.64789       6.68766     1.34809    36.3701\n",
-    "  1000           7.24914     2.65554       6.81906     1.41008    36.1695\n",
-    " 10000           7.08183     2.6248        6.93431     1.38441    37.5723\n",
-    "100000           8.021       3.43694       8.69813     0.909839   37.8158\n",
-    "     1e+06       8.49625     3.6332        9.59333     0.96626    38.4688\n",
-    "     1e+07      10.9067      3.17593      11.5642      2.07792    36.9926\n",
-    "     1e+08      61.1524     10.4355       65.3527     13.9538     37.1321\n",
-    "     1e+09      99.943      13.6994       98.8848      5.27014    36.7443\n",
-    "     1e+10     100.083      13.8503       97.9168      3.22768    37.096\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The line_profiler extension is already loaded. To reload it, use:\n",
-      "  %reload_ext line_profiler\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f6be3d4a8d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[(0, {'atom': 'C', 'label': 'C'}), (1, {'atom': 'C', 'label': 'C'}), (2, {'atom': 'C', 'label': 'C'}), (3, {'atom': 'C', 'label': 'C'}), (4, {'atom': 'S', 'label': 'S'})]\n",
-      "\n",
-      " --- kernel matrix of tree pattern kernel of size 39 built in 3.5270774364471436 seconds ---\n",
-      "(array([[1.99007809e+036, 4.00000000e+000, 4.00000000e+000, ...,\n",
-      "        1.00000000e+001, 1.00000000e+001, 1.00000000e+001],\n",
-      "       [4.00000000e+000, 6.37886713e+019, 4.34000000e+002, ...,\n",
-      "        6.37886713e+019, 6.37886713e+019, 6.37886713e+019],\n",
-      "       [4.00000000e+000, 4.34000000e+002, 1.99007809e+036, ...,\n",
-      "        4.40000000e+002, 4.40000000e+002, 4.40000000e+002],\n",
-      "       ...,\n",
-      "       [1.00000000e+001, 6.37886713e+019, 4.40000000e+002, ...,\n",
-      "        2.94561201e+119, 1.16903692e+080, 4.42354433e+082],\n",
-      "       [1.00000000e+001, 6.37886713e+019, 4.40000000e+002, ...,\n",
-      "        1.16903692e+080, 4.21212139e+264, 1.66634383e+080],\n",
-      "       [1.00000000e+001, 6.37886713e+019, 4.40000000e+002, ...,\n",
-      "        4.42354433e+082, 1.66634383e+080, 5.17763068e+117]]), 3.5270774364471436)\n"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext line_profiler\n",
-    "\n",
-    "import networkx as nx\n",
-    "import matplotlib.pyplot as plt\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "\n",
-    "from pygraph.kernels.treePatternKernel import treepatternkernel, _treepatternkernel_do\n",
-    "\n",
-    "import numpy as np\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "\n",
-    "dataset, y = loadDataset(datafile)\n",
-    "G1 = dataset[100]\n",
-    "G2 = dataset[20]\n",
-    "data = [G1, G2]\n",
-    "# nx.draw_networkx(G1)\n",
-    "# plt.show()\n",
-    "# print(G1.nodes(data=True)20\n",
-    "nx.draw_networkx(G2)\n",
-    "plt.show()\n",
-    "print(G2.nodes(data=True))\n",
-    "\n",
-    "\n",
-    "%lprun -f _treepatternkernel_do \\\n",
-    "    kernel = treepatternkernel(dataset[1:40], node_label = 'atom', edge_label = 'bond_type', labeled = True, \\\n",
-    "    kernel_type = 'untiln', lmda = 1, h = 10)\n",
-    "\n",
-    "print(kernel)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- This is a classification problem ---\n",
-      "\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "retrieve patterns: 100%|██████████| 185/185 [00:00<00:00, 2064.69it/s]\n",
-      "calculate kernels: 100%|██████████| 185/185 [00:00<00:00, 11170.00it/s]\n",
-      "\n",
-      " --- kernel matrix of cyclic pattern kernel of size 185 built in 0.10836505889892578 seconds ---\n",
-      "[[0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " ...\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]\n",
-      " [0. 0. 0. ... 0. 0. 0.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:24<00:00, 36.41it/s]\n",
-      " Mean performance on train set: 0.018072\n",
-      "With standard deviation: 0.000000\n",
-      "\n",
-      " Mean performance on test set: 0.000000\n",
-      "With standard deviation: 0.000000\n",
-      "\n",
-      "\n",
-      "  accur_test    std_test    accur_train    std_train    k_time\n",
-      "------------  ----------  -------------  -----------  --------\n",
-      "           0           0      0.0180723            0  0.108365\n"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext line_profiler\n",
-    "\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.cyclicPatternKernel import cyclicpatternkernel\n",
-    "\n",
-    "import numpy as np\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_path_acyclic/'\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', labeled = True, cycle_bound = 200)\n",
-    "\n",
-    "# kernel_train_test(datafile, kernel_file_path, treeletkernel, kernel_para, normalize = False)\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, cyclicpatternkernel, kernel_para, \\\n",
-    "    normalize = False , model_type = 'classification')\n",
-    "\n",
-    "# kernel_para['k_func'] = 'minmax'\n",
-    "# kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
-    "#     hyper_name = 'depth', hyper_range = np.linspace(0, 10, 11), normalize = True)\n",
-    "# kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
-    "#     hyper_name = 'depth', hyper_range = np.linspace(0, 10, 11), normalize = False)\n",
-    "# # kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, normalize = False)\n",
-    "\n",
-    "# kernel_para['depth'] = 10\n",
-    "# %lprun -f untildpathkernel \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, normalize = False)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/.ipynb_checkpoints/run_weisfeilerLehmankernel_acyclic-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/run_weisfeilerLehmankernel_acyclic-checkpoint.ipynb
deleted file mode 100644
index 0dbb8f9..0000000
--- a/notebooks/.ipynb_checkpoints/run_weisfeilerLehmankernel_acyclic-checkpoint.ipynb
+++ /dev/null
@@ -1,1755 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 0.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 0.3646550178527832 seconds ---\n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 985/1000 [00:01<00:00, 664.77it/s]\n",
-      " Mean performance on train set: 17.681582\n",
-      "With standard deviation: 0.713183\n",
-      "\n",
-      " Mean performance on test set: 15.685879\n",
-      "With standard deviation: 4.139197\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 681.36it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 1.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 0.7535510063171387 seconds ---\n",
-      "[[ 10.  10.   4. ...  20.  20.  20.]\n",
-      " [ 10.  16.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.  10. ...  22.  22.  24.]\n",
-      " ...\n",
-      " [ 20.  20.  22. ... 130. 130. 122.]\n",
-      " [ 20.  20.  22. ... 130. 130. 122.]\n",
-      " [ 20.  20.  24. ... 122. 122. 154.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  94%|█████████▍| 945/1000 [00:01<00:00, 713.00it/s]\n",
-      " Mean performance on train set: 6.270014\n",
-      "With standard deviation: 0.654734\n",
-      "\n",
-      " Mean performance on test set: 7.550458\n",
-      "With standard deviation: 2.331786\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 719.46it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 2.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 1.3278343677520752 seconds ---\n",
-      "[[ 15.  10.   4. ...  20.  20.  20.]\n",
-      " [ 10.  24.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.  15. ...  22.  22.  26.]\n",
-      " ...\n",
-      " [ 20.  20.  22. ... 159. 151. 124.]\n",
-      " [ 20.  20.  22. ... 151. 153. 124.]\n",
-      " [ 20.  20.  26. ... 124. 124. 185.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  95%|█████████▍| 949/1000 [00:01<00:00, 736.38it/s]\n",
-      " Mean performance on train set: 4.450682\n",
-      "With standard deviation: 0.882129\n",
-      "\n",
-      " Mean performance on test set: 9.728466\n",
-      "With standard deviation: 2.057669\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 709.22it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 3.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 1.7653727531433105 seconds ---\n",
-      "[[ 20.  10.   4. ...  20.  20.  20.]\n",
-      " [ 10.  32.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.  20. ...  22.  22.  26.]\n",
-      " ...\n",
-      " [ 20.  20.  22. ... 188. 159. 124.]\n",
-      " [ 20.  20.  22. ... 159. 168. 124.]\n",
-      " [ 20.  20.  26. ... 124. 124. 202.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  96%|█████████▌| 959/1000 [00:01<00:00, 724.60it/s]\n",
-      " Mean performance on train set: 2.270586\n",
-      "With standard deviation: 0.481516\n",
-      "\n",
-      " Mean performance on test set: 11.296110\n",
-      "With standard deviation: 2.799944\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 670.29it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 4.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 2.2821996212005615 seconds ---\n",
-      "[[ 25.  10.   4. ...  20.  20.  20.]\n",
-      " [ 10.  40.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.  25. ...  22.  22.  26.]\n",
-      " ...\n",
-      " [ 20.  20.  22. ... 217. 159. 124.]\n",
-      " [ 20.  20.  22. ... 159. 183. 124.]\n",
-      " [ 20.  20.  26. ... 124. 124. 213.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 983/1000 [00:01<00:00, 709.28it/s]\n",
-      " Mean performance on train set: 1.074035\n",
-      "With standard deviation: 0.637823\n",
-      "\n",
-      " Mean performance on test set: 12.808303\n",
-      "With standard deviation: 3.446939\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 646.12it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 5.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 2.706934928894043 seconds ---\n",
-      "[[ 30.  10.   4. ...  20.  20.  20.]\n",
-      " [ 10.  48.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.  30. ...  22.  22.  26.]\n",
-      " ...\n",
-      " [ 20.  20.  22. ... 246. 159. 124.]\n",
-      " [ 20.  20.  22. ... 159. 198. 124.]\n",
-      " [ 20.  20.  26. ... 124. 124. 224.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  95%|█████████▌| 953/1000 [00:01<00:00, 553.49it/s]\n",
-      " Mean performance on train set: 0.700602\n",
-      "With standard deviation: 0.572640\n",
-      "\n",
-      " Mean performance on test set: 14.017923\n",
-      "With standard deviation: 3.675042\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 621.01it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 6.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 3.1140964031219482 seconds ---\n",
-      "[[ 35.  10.   4. ...  20.  20.  20.]\n",
-      " [ 10.  56.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.  35. ...  22.  22.  26.]\n",
-      " ...\n",
-      " [ 20.  20.  22. ... 275. 159. 124.]\n",
-      " [ 20.  20.  22. ... 159. 213. 124.]\n",
-      " [ 20.  20.  26. ... 124. 124. 235.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance: 100%|█████████▉| 997/1000 [00:01<00:00, 595.50it/s]\n",
-      " Mean performance on train set: 0.691515\n",
-      "With standard deviation: 0.564620\n",
-      "\n",
-      " Mean performance on test set: 14.918434\n",
-      "With standard deviation: 3.805352\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 586.05it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 7.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 3.5894455909729004 seconds ---\n",
-      "[[ 40.  10.   4. ...  20.  20.  20.]\n",
-      " [ 10.  64.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.  40. ...  22.  22.  26.]\n",
-      " ...\n",
-      " [ 20.  20.  22. ... 304. 159. 124.]\n",
-      " [ 20.  20.  22. ... 159. 228. 124.]\n",
-      " [ 20.  20.  26. ... 124. 124. 246.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  99%|█████████▉| 991/1000 [00:01<00:00, 663.55it/s]\n",
-      " Mean performance on train set: 0.691516\n",
-      "With standard deviation: 0.564620\n",
-      "\n",
-      " Mean performance on test set: 15.629476\n",
-      "With standard deviation: 3.865387\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 627.59it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 8.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 4.081295967102051 seconds ---\n",
-      "[[ 45.  10.   4. ...  20.  20.  20.]\n",
-      " [ 10.  72.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.  45. ...  22.  22.  26.]\n",
-      " ...\n",
-      " [ 20.  20.  22. ... 333. 159. 124.]\n",
-      " [ 20.  20.  22. ... 159. 243. 124.]\n",
-      " [ 20.  20.  26. ... 124. 124. 257.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  96%|█████████▌| 961/1000 [00:01<00:00, 601.33it/s]\n",
-      " Mean performance on train set: 0.691515\n",
-      "With standard deviation: 0.564620\n",
-      "\n",
-      " Mean performance on test set: 16.214369\n",
-      "With standard deviation: 3.928756\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 603.90it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 9.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 4.497286796569824 seconds ---\n",
-      "[[ 50.  10.   4. ...  20.  20.  20.]\n",
-      " [ 10.  80.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.  50. ...  22.  22.  26.]\n",
-      " ...\n",
-      " [ 20.  20.  22. ... 362. 159. 124.]\n",
-      " [ 20.  20.  22. ... 159. 258. 124.]\n",
-      " [ 20.  20.  26. ... 124. 124. 268.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  93%|█████████▎| 931/1000 [00:01<00:00, 511.55it/s]\n",
-      " Mean performance on train set: 0.691515\n",
-      "With standard deviation: 0.564620\n",
-      "\n",
-      " Mean performance on test set: 16.725744\n",
-      "With standard deviation: 3.993095\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 550.66it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 10.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 4.984841585159302 seconds ---\n",
-      "[[ 55.  10.   4. ...  20.  20.  20.]\n",
-      " [ 10.  88.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.  55. ...  22.  22.  26.]\n",
-      " ...\n",
-      " [ 20.  20.  22. ... 391. 159. 124.]\n",
-      " [ 20.  20.  22. ... 159. 273. 124.]\n",
-      " [ 20.  20.  26. ... 124. 124. 279.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  94%|█████████▍| 942/1000 [00:01<00:00, 708.78it/s]\n",
-      " Mean performance on train set: 0.691516\n",
-      "With standard deviation: 0.564621\n",
-      "\n",
-      " Mean performance on test set: 17.186401\n",
-      "With standard deviation: 4.056724\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 711.43it/s]\n",
-      "\n",
-      "\n",
-      "  height    rmse_test    std_test    rmse_train    std_train    k_time\n",
-      "--------  -----------  ----------  ------------  -----------  --------\n",
-      "       0     15.6859      4.1392      17.6816       0.713183  0.364655\n",
-      "       1      7.55046     2.33179      6.27001      0.654734  0.753551\n",
-      "       2      9.72847     2.05767      4.45068      0.882129  1.32783\n",
-      "       3     11.2961      2.79994      2.27059      0.481516  1.76537\n",
-      "       4     12.8083      3.44694      1.07403      0.637823  2.2822\n",
-      "       5     14.0179      3.67504      0.700602     0.57264   2.70693\n",
-      "       6     14.9184      3.80535      0.691515     0.56462   3.1141\n",
-      "       7     15.6295      3.86539      0.691516     0.56462   3.58945\n",
-      "       8     16.2144      3.92876      0.691515     0.56462   4.0813\n",
-      "       9     16.7257      3.9931       0.691515     0.56462   4.49729\n",
-      "      10     17.1864      4.05672      0.691516     0.564621  4.98484\n"
-     ]
-    }
-   ],
-   "source": [
-    "# wl subtree kernel\n",
-    "%load_ext line_profiler\n",
-    "\n",
-    "import numpy as np\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.weisfeilerLehmanKernel import weisfeilerlehmankernel, _wl_subtreekernel_do\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_weisfeilerlehman_subtree_acyclic/'\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type')\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
-    "    hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)\n",
-    "\n",
-    "# %lprun -f _wl_subtreekernel_do \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
-    "#     hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 0.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 13.504083633422852 seconds ---\n",
-      "[[ 3.  1.  3. ...  1.  1.  1.]\n",
-      " [ 1.  6.  1. ...  0.  0.  3.]\n",
-      " [ 3.  1.  3. ...  1.  1.  1.]\n",
-      " ...\n",
-      " [ 1.  0.  1. ... 55. 21.  7.]\n",
-      " [ 1.  0.  1. ... 21. 55.  7.]\n",
-      " [ 1.  3.  1. ...  7.  7. 55.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 980/1000 [00:01<00:00, 773.79it/s]\n",
-      " Mean performance on train set: 28.360361\n",
-      "With standard deviation: 1.357183\n",
-      "\n",
-      " Mean performance on test set: 35.191954\n",
-      "With standard deviation: 4.495767\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 743.82it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 1.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 26.82917618751526 seconds ---\n",
-      "[[  6.   2.   6. ...   2.   2.   2.]\n",
-      " [  2.  12.   2. ...   0.   0.   6.]\n",
-      " [  6.   2.   6. ...   2.   2.   2.]\n",
-      " ...\n",
-      " [  2.   0.   2. ... 110.  42.  14.]\n",
-      " [  2.   0.   2. ...  42. 110.  14.]\n",
-      " [  2.   6.   2. ...  14.  14. 110.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 983/1000 [00:01<00:00, 751.78it/s]\n",
-      " Mean performance on train set: 27.933534\n",
-      "With standard deviation: 1.448359\n",
-      "\n",
-      " Mean performance on test set: 35.180815\n",
-      "With standard deviation: 4.500453\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 744.44it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 2.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 40.235626220703125 seconds ---\n",
-      "[[  9.   3.   9. ...   3.   3.   3.]\n",
-      " [  3.  18.   3. ...   0.   0.   9.]\n",
-      " [  9.   3.   9. ...   3.   3.   3.]\n",
-      " ...\n",
-      " [  3.   0.   3. ... 165.  63.  21.]\n",
-      " [  3.   0.   3. ...  63. 165.  21.]\n",
-      " [  3.   9.   3. ...  21.  21. 165.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  94%|█████████▎| 936/1000 [00:01<00:00, 694.10it/s]\n",
-      " Mean performance on train set: 28.111311\n",
-      "With standard deviation: 1.508915\n",
-      "\n",
-      " Mean performance on test set: 35.163150\n",
-      "With standard deviation: 4.502054\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 695.02it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 3.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 54.67040753364563 seconds ---\n",
-      "[[ 12.   4.  12. ...   4.   4.   4.]\n",
-      " [  4.  24.   4. ...   0.   0.  12.]\n",
-      " [ 12.   4.  12. ...   4.   4.   4.]\n",
-      " ...\n",
-      " [  4.   0.   4. ... 220.  84.  28.]\n",
-      " [  4.   0.   4. ...  84. 220.  28.]\n",
-      " [  4.  12.   4. ...  28.  28. 220.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  95%|█████████▌| 954/1000 [00:01<00:00, 748.03it/s]\n",
-      " Mean performance on train set: 28.390274\n",
-      "With standard deviation: 1.365711\n",
-      "\n",
-      " Mean performance on test set: 35.194634\n",
-      "With standard deviation: 4.498007\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 726.68it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 4.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 67.15217232704163 seconds ---\n",
-      "[[ 15.   5.  15. ...   5.   5.   5.]\n",
-      " [  5.  30.   5. ...   0.   0.  15.]\n",
-      " [ 15.   5.  15. ...   5.   5.   5.]\n",
-      " ...\n",
-      " [  5.   0.   5. ... 275. 105.  35.]\n",
-      " [  5.   0.   5. ... 105. 275.  35.]\n",
-      " [  5.  15.   5. ...  35.  35. 275.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  95%|█████████▌| 950/1000 [00:01<00:00, 737.07it/s]\n",
-      " Mean performance on train set: 27.974611\n",
-      "With standard deviation: 1.462223\n",
-      "\n",
-      " Mean performance on test set: 35.175314\n",
-      "With standard deviation: 4.501113\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 719.71it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 5.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 80.08806300163269 seconds ---\n",
-      "[[ 18.   6.  18. ...   6.   6.   6.]\n",
-      " [  6.  36.   6. ...   0.   0.  18.]\n",
-      " [ 18.   6.  18. ...   6.   6.   6.]\n",
-      " ...\n",
-      " [  6.   0.   6. ... 330. 126.  42.]\n",
-      " [  6.   0.   6. ... 126. 330.  42.]\n",
-      " [  6.  18.   6. ...  42.  42. 330.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 985/1000 [00:01<00:00, 735.71it/s]\n",
-      " Mean performance on train set: 28.018415\n",
-      "With standard deviation: 1.455644\n",
-      "\n",
-      " Mean performance on test set: 35.199713\n",
-      "With standard deviation: 4.507104\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 738.55it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 6.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 92.19254112243652 seconds ---\n",
-      "[[ 21.   7.  21. ...   7.   7.   7.]\n",
-      " [  7.  42.   7. ...   0.   0.  21.]\n",
-      " [ 21.   7.  21. ...   7.   7.   7.]\n",
-      " ...\n",
-      " [  7.   0.   7. ... 385. 147.  49.]\n",
-      " [  7.   0.   7. ... 147. 385.  49.]\n",
-      " [  7.  21.   7. ...  49.  49. 385.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 975/1000 [00:01<00:00, 721.42it/s]\n",
-      " Mean performance on train set: 28.373079\n",
-      "With standard deviation: 1.600565\n",
-      "\n",
-      " Mean performance on test set: 35.164471\n",
-      "With standard deviation: 4.498487\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 727.58it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 7.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 105.81170415878296 seconds ---\n",
-      "[[ 24.   8.  24. ...   8.   8.   8.]\n",
-      " [  8.  48.   8. ...   0.   0.  24.]\n",
-      " [ 24.   8.  24. ...   8.   8.   8.]\n",
-      " ...\n",
-      " [  8.   0.   8. ... 440. 168.  56.]\n",
-      " [  8.   0.   8. ... 168. 440.  56.]\n",
-      " [  8.  24.   8. ...  56.  56. 440.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  97%|█████████▋| 968/1000 [00:01<00:00, 739.67it/s]\n",
-      " Mean performance on train set: 27.960421\n",
-      "With standard deviation: 1.457425\n",
-      "\n",
-      " Mean performance on test set: 35.177115\n",
-      "With standard deviation: 4.500904\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 733.61it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 8.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 119.0216612815857 seconds ---\n",
-      "[[ 27.   9.  27. ...   9.   9.   9.]\n",
-      " [  9.  54.   9. ...   0.   0.  27.]\n",
-      " [ 27.   9.  27. ...   9.   9.   9.]\n",
-      " ...\n",
-      " [  9.   0.   9. ... 495. 189.  63.]\n",
-      " [  9.   0.   9. ... 189. 495.  63.]\n",
-      " [  9.  27.   9. ...  63.  63. 495.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  93%|█████████▎| 931/1000 [00:01<00:00, 752.10it/s]\n",
-      " Mean performance on train set: 28.199059\n",
-      "With standard deviation: 1.514897\n",
-      "\n",
-      " Mean performance on test set: 35.196848\n",
-      "With standard deviation: 4.505256\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 768.54it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 9.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 131.22810459136963 seconds ---\n",
-      "[[ 30.  10.  30. ...  10.  10.  10.]\n",
-      " [ 10.  60.  10. ...   0.   0.  30.]\n",
-      " [ 30.  10.  30. ...  10.  10.  10.]\n",
-      " ...\n",
-      " [ 10.   0.  10. ... 550. 210.  70.]\n",
-      " [ 10.   0.  10. ... 210. 550.  70.]\n",
-      " [ 10.  30.  10. ...  70.  70. 550.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  93%|█████████▎| 932/1000 [00:01<00:00, 763.55it/s]\n",
-      " Mean performance on train set: 28.266520\n",
-      "With standard deviation: 1.307686\n",
-      "\n",
-      " Mean performance on test set: 35.195635\n",
-      "With standard deviation: 4.501972\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 764.12it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 10.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 144.96362161636353 seconds ---\n",
-      "[[ 33.  11.  33. ...  11.  11.  11.]\n",
-      " [ 11.  66.  11. ...   0.   0.  33.]\n",
-      " [ 33.  11.  33. ...  11.  11.  11.]\n",
-      " ...\n",
-      " [ 11.   0.  11. ... 605. 231.  77.]\n",
-      " [ 11.   0.  11. ... 231. 605.  77.]\n",
-      " [ 11.  33.  11. ...  77.  77. 605.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance: 100%|█████████▉| 996/1000 [00:01<00:00, 820.73it/s]\n",
-      " Mean performance on train set: 28.416280\n",
-      "With standard deviation: 1.615957\n",
-      "\n",
-      " Mean performance on test set: 35.167588\n",
-      "With standard deviation: 4.497227\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 822.53it/s]\n",
-      "\n",
-      "\n",
-      "  height    rmse_test    std_test    rmse_train    std_train    k_time\n",
-      "--------  -----------  ----------  ------------  -----------  --------\n",
-      "       0      35.192      4.49577       28.3604      1.35718   13.5041\n",
-      "       1      35.1808     4.50045       27.9335      1.44836   26.8292\n",
-      "       2      35.1632     4.50205       28.1113      1.50891   40.2356\n",
-      "       3      35.1946     4.49801       28.3903      1.36571   54.6704\n",
-      "       4      35.1753     4.50111       27.9746      1.46222   67.1522\n",
-      "       5      35.1997     4.5071        28.0184      1.45564   80.0881\n",
-      "       6      35.1645     4.49849       28.3731      1.60057   92.1925\n",
-      "       7      35.1771     4.5009        27.9604      1.45742  105.812\n",
-      "       8      35.1968     4.50526       28.1991      1.5149   119.022\n",
-      "       9      35.1956     4.50197       28.2665      1.30769  131.228\n",
-      "      10      35.1676     4.49723       28.4163      1.61596  144.964\n"
-     ]
-    }
-   ],
-   "source": [
-    "# WL sp kernel\n",
-    "%load_ext line_profiler\n",
-    "\n",
-    "import numpy as np\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.weisfeilerLehmanKernel import weisfeilerlehmankernel, _wl_subtreekernel_do\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_weisfeilerlehman_subtree_acyclic/'\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', base_kernel = 'sp')\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
-    "    hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)\n",
-    "\n",
-    "# %lprun -f _wl_subtreekernel_do \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
-    "#     hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The line_profiler extension is already loaded. To reload it, use:\n",
-      "  %reload_ext line_profiler\n",
-      "\n",
-      " --- This is a regression problem ---\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 0.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 0.8530018329620361 seconds ---\n",
-      "[[ 2.  1.  2. ...  0.  0.  1.]\n",
-      " [ 1.  3.  1. ...  0.  0.  2.]\n",
-      " [ 2.  1.  2. ...  0.  0.  1.]\n",
-      " ...\n",
-      " [ 0.  0.  0. ... 10.  7.  0.]\n",
-      " [ 0.  0.  0. ...  7. 10.  1.]\n",
-      " [ 1.  2.  1. ...  0.  1. 10.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  95%|█████████▍| 947/1000 [00:01<00:00, 719.29it/s]\n",
-      " Mean performance on train set: 29.997498\n",
-      "With standard deviation: 0.902340\n",
-      "\n",
-      " Mean performance on test set: 33.407740\n",
-      "With standard deviation: 4.732717\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 653.54it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 1.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 1.717505931854248 seconds ---\n",
-      "[[ 4.  2.  4. ...  0.  0.  2.]\n",
-      " [ 2.  6.  2. ...  0.  0.  4.]\n",
-      " [ 4.  2.  4. ...  0.  0.  2.]\n",
-      " ...\n",
-      " [ 0.  0.  0. ... 20. 14.  0.]\n",
-      " [ 0.  0.  0. ... 14. 20.  2.]\n",
-      " [ 2.  4.  2. ...  0.  2. 20.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  96%|█████████▌| 956/1000 [00:01<00:00, 721.27it/s]\n",
-      " Mean performance on train set: 30.160338\n",
-      "With standard deviation: 1.094235\n",
-      "\n",
-      " Mean performance on test set: 33.423458\n",
-      "With standard deviation: 4.721311\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 723.53it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 2.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 2.6603214740753174 seconds ---\n",
-      "[[ 6.  3.  6. ...  0.  0.  3.]\n",
-      " [ 3.  9.  3. ...  0.  0.  6.]\n",
-      " [ 6.  3.  6. ...  0.  0.  3.]\n",
-      " ...\n",
-      " [ 0.  0.  0. ... 30. 21.  0.]\n",
-      " [ 0.  0.  0. ... 21. 30.  3.]\n",
-      " [ 3.  6.  3. ...  0.  3. 30.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  94%|█████████▍| 944/1000 [00:01<00:00, 650.98it/s]\n",
-      " Mean performance on train set: 29.928570\n",
-      "With standard deviation: 0.787941\n",
-      "\n",
-      " Mean performance on test set: 33.433014\n",
-      "With standard deviation: 4.724408\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 688.71it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 3.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 3.477631092071533 seconds ---\n",
-      "[[ 8.  4.  8. ...  0.  0.  4.]\n",
-      " [ 4. 12.  4. ...  0.  0.  8.]\n",
-      " [ 8.  4.  8. ...  0.  0.  4.]\n",
-      " ...\n",
-      " [ 0.  0.  0. ... 40. 28.  0.]\n",
-      " [ 0.  0.  0. ... 28. 40.  4.]\n",
-      " [ 4.  8.  4. ...  0.  4. 40.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  95%|█████████▌| 954/1000 [00:01<00:00, 725.15it/s]\n",
-      " Mean performance on train set: 30.011409\n",
-      "With standard deviation: 0.909674\n",
-      "\n",
-      " Mean performance on test set: 33.407319\n",
-      "With standard deviation: 4.732434\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 720.71it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 4.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 4.5436692237854 seconds ---\n",
-      "[[10.  5. 10. ...  0.  0.  5.]\n",
-      " [ 5. 15.  5. ...  0.  0. 10.]\n",
-      " [10.  5. 10. ...  0.  0.  5.]\n",
-      " ...\n",
-      " [ 0.  0.  0. ... 50. 35.  0.]\n",
-      " [ 0.  0.  0. ... 35. 50.  5.]\n",
-      " [ 5. 10.  5. ...  0.  5. 50.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  94%|█████████▎| 936/1000 [00:01<00:00, 568.04it/s]\n",
-      " Mean performance on train set: 30.184162\n",
-      "With standard deviation: 1.108902\n",
-      "\n",
-      " Mean performance on test set: 33.425625\n",
-      "With standard deviation: 4.721660\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 564.24it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 5.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 5.6617820262908936 seconds ---\n",
-      "[[12.  6. 12. ...  0.  0.  6.]\n",
-      " [ 6. 18.  6. ...  0.  0. 12.]\n",
-      " [12.  6. 12. ...  0.  0.  6.]\n",
-      " ...\n",
-      " [ 0.  0.  0. ... 60. 42.  0.]\n",
-      " [ 0.  0.  0. ... 42. 60.  6.]\n",
-      " [ 6. 12.  6. ...  0.  6. 60.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  99%|█████████▉| 993/1000 [00:01<00:00, 519.25it/s]\n",
-      " Mean performance on train set: 30.041068\n",
-      "With standard deviation: 1.018451\n",
-      "\n",
-      " Mean performance on test set: 33.406717\n",
-      "With standard deviation: 4.726409\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 548.91it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 6.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 6.148027420043945 seconds ---\n",
-      "[[14.  7. 14. ...  0.  0.  7.]\n",
-      " [ 7. 21.  7. ...  0.  0. 14.]\n",
-      " [14.  7. 14. ...  0.  0.  7.]\n",
-      " ...\n",
-      " [ 0.  0.  0. ... 70. 49.  0.]\n",
-      " [ 0.  0.  0. ... 49. 70.  7.]\n",
-      " [ 7. 14.  7. ...  0.  7. 70.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 985/1000 [00:01<00:00, 498.31it/s]\n",
-      " Mean performance on train set: 29.905596\n",
-      "With standard deviation: 0.782179\n",
-      "\n",
-      " Mean performance on test set: 33.418992\n",
-      "With standard deviation: 4.730753\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 534.86it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 7.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 7.603543519973755 seconds ---\n",
-      "[[16.  8. 16. ...  0.  0.  8.]\n",
-      " [ 8. 24.  8. ...  0.  0. 16.]\n",
-      " [16.  8. 16. ...  0.  0.  8.]\n",
-      " ...\n",
-      " [ 0.  0.  0. ... 80. 56.  0.]\n",
-      " [ 0.  0.  0. ... 56. 80.  8.]\n",
-      " [ 8. 16.  8. ...  0.  8. 80.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  95%|█████████▌| 953/1000 [00:01<00:00, 586.15it/s]\n",
-      " Mean performance on train set: 30.175921\n",
-      "With standard deviation: 1.103820\n",
-      "\n",
-      " Mean performance on test set: 33.424820\n",
-      "With standard deviation: 4.721550\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 546.00it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 8.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 7.972221612930298 seconds ---\n",
-      "[[18.  9. 18. ...  0.  0.  9.]\n",
-      " [ 9. 27.  9. ...  0.  0. 18.]\n",
-      " [18.  9. 18. ...  0.  0.  9.]\n",
-      " ...\n",
-      " [ 0.  0.  0. ... 90. 63.  0.]\n",
-      " [ 0.  0.  0. ... 63. 90.  9.]\n",
-      " [ 9. 18.  9. ...  0.  9. 90.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 980/1000 [00:01<00:00, 490.30it/s]\n",
-      " Mean performance on train set: 30.136537\n",
-      "With standard deviation: 1.074854\n",
-      "\n",
-      " Mean performance on test set: 33.412196\n",
-      "With standard deviation: 4.715539\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 536.66it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 9.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 9.070842504501343 seconds ---\n",
-      "[[ 20.  10.  20. ...   0.   0.  10.]\n",
-      " [ 10.  30.  10. ...   0.   0.  20.]\n",
-      " [ 20.  10.  20. ...   0.   0.  10.]\n",
-      " ...\n",
-      " [  0.   0.   0. ... 100.  70.   0.]\n",
-      " [  0.   0.   0. ...  70. 100.  10.]\n",
-      " [ 10.  20.  10. ...   0.  10. 100.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n",
-      "calculate performance:  98%|█████████▊| 975/1000 [00:01<00:00, 527.13it/s]\n",
-      " Mean performance on train set: 30.032887\n",
-      "With standard deviation: 0.921065\n",
-      "\n",
-      " Mean performance on test set: 33.407050\n",
-      "With standard deviation: 4.731928\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 600.62it/s]\n",
-      "\n",
-      "\n",
-      " #--- calculating kernel matrix when height = 10.0 ---#\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "\n",
-      " Calculating kernel matrix, this could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 10.02536916732788 seconds ---\n",
-      "[[ 22.  11.  22. ...   0.   0.  11.]\n",
-      " [ 11.  33.  11. ...   0.   0.  22.]\n",
-      " [ 22.  11.  22. ...   0.   0.  11.]\n",
-      " ...\n",
-      " [  0.   0.   0. ... 110.  77.   0.]\n",
-      " [  0.   0.   0. ...  77. 110.  11.]\n",
-      " [ 11.  22.  11. ...   0.  11. 110.]]\n",
-      "\n",
-      " Starting calculate accuracy/rmse...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calculate performance:  97%|█████████▋| 970/1000 [00:01<00:00, 694.38it/s]\n",
-      " Mean performance on train set: 29.924232\n",
-      "With standard deviation: 0.790843\n",
-      "\n",
-      " Mean performance on test set: 33.416469\n",
-      "With standard deviation: 4.731694\n",
-      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 678.72it/s]\n",
-      "\n",
-      "\n",
-      "  height    rmse_test    std_test    rmse_train    std_train     k_time\n",
-      "--------  -----------  ----------  ------------  -----------  ---------\n",
-      "       0      33.4077     4.73272       29.9975     0.90234    0.853002\n",
-      "       1      33.4235     4.72131       30.1603     1.09423    1.71751\n",
-      "       2      33.433      4.72441       29.9286     0.787941   2.66032\n",
-      "       3      33.4073     4.73243       30.0114     0.909674   3.47763\n",
-      "       4      33.4256     4.72166       30.1842     1.1089     4.54367\n",
-      "       5      33.4067     4.72641       30.0411     1.01845    5.66178\n",
-      "       6      33.419      4.73075       29.9056     0.782179   6.14803\n",
-      "       7      33.4248     4.72155       30.1759     1.10382    7.60354\n",
-      "       8      33.4122     4.71554       30.1365     1.07485    7.97222\n",
-      "       9      33.4071     4.73193       30.0329     0.921065   9.07084\n",
-      "      10      33.4165     4.73169       29.9242     0.790843  10.0254\n"
-     ]
-    }
-   ],
-   "source": [
-    "# WL edge kernel\n",
-    "%load_ext line_profiler\n",
-    "\n",
-    "import numpy as np\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "from pygraph.kernels.weisfeilerLehmanKernel import weisfeilerlehmankernel, _wl_subtreekernel_do\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "kernel_file_path = 'kernelmatrices_weisfeilerlehman_subtree_acyclic/'\n",
-    "\n",
-    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', base_kernel = 'edge')\n",
-    "\n",
-    "kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
-    "    hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)\n",
-    "\n",
-    "# %lprun -f _wl_subtreekernel_do \\\n",
-    "#     kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
-    "#     hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# results\n",
-    "\n",
-    "# subtree with y normalization\n",
-    "  height    RMSE_test    std_test    RMSE_train    std_train    k_time\n",
-    "--------  -----------  ----------  ------------  -----------  --------\n",
-    "       0     36.2108      7.33179      38.6059      1.57064   0.379475\n",
-    "       1      9.00098     6.37145       6.76379     1.96568   0.844898\n",
-    "       2     19.8113      4.04911       5.28757     1.81899   1.35308\n",
-    "       3     25.0455      4.94276       2.3274      0.805733  1.81136\n",
-    "       4     28.2255      6.5212        0.85156     0.423465  2.23098\n",
-    "       5     30.6354      6.73647       3.35947     8.17561   2.71575\n",
-    "       6     32.1027      6.85601       3.54105     8.71922   3.11459\n",
-    "       7     32.9709      6.89606       6.94372     9.94045   3.55571\n",
-    "       8     33.5112      6.90753       6.97339     9.76975   3.79657\n",
-    "       9     33.8502      6.91427      11.8345     11.6213    4.41555\n",
-    "      10     34.0963      6.93115      11.4257     11.2624    4.94888\n",
-    "\n",
-    "# subtree without y normalization\n",
-    "  height    RMSE_test    std_test    RMSE_train    std_train    k_time\n",
-    "--------  -----------  ----------  ------------  -----------  --------\n",
-    "       0     15.6859      4.1392      17.6816       0.713183  0.360443\n",
-    "       1      7.55046     2.33179      6.27001      0.654734  0.837389\n",
-    "       2      9.72847     2.05767      4.45068      0.882129  1.25317\n",
-    "       3     11.2961      2.79994      2.27059      0.481516  1.79971\n",
-    "       4     12.8083      3.44694      1.07403      0.637823  2.35346\n",
-    "       5     14.0179      3.67504      0.700602     0.57264   2.78285\n",
-    "       6     14.9184      3.80535      0.691515     0.56462   3.20764\n",
-    "       7     15.6295      3.86539      0.691516     0.56462   3.71648\n",
-    "       8     16.2144      3.92876      0.691515     0.56462   3.99213\n",
-    "       9     16.7257      3.9931       0.691515     0.56462   4.26315\n",
-    "      10     17.1864      4.05672      0.691516     0.564621  5.00918\n",
-    "    \n",
-    "# sp\n",
-    "  height    rmse_test    std_test    rmse_train    std_train    k_time\n",
-    "--------  -----------  ----------  ------------  -----------  --------\n",
-    "       0      35.192      4.49577       28.3604      1.35718   13.5041\n",
-    "       1      35.1808     4.50045       27.9335      1.44836   26.8292\n",
-    "       2      35.1632     4.50205       28.1113      1.50891   40.2356\n",
-    "       3      35.1946     4.49801       28.3903      1.36571   54.6704\n",
-    "       4      35.1753     4.50111       27.9746      1.46222   67.1522\n",
-    "       5      35.1997     4.5071        28.0184      1.45564   80.0881\n",
-    "       6      35.1645     4.49849       28.3731      1.60057   92.1925\n",
-    "       7      35.1771     4.5009        27.9604      1.45742  105.812\n",
-    "       8      35.1968     4.50526       28.1991      1.5149   119.022\n",
-    "       9      35.1956     4.50197       28.2665      1.30769  131.228\n",
-    "      10      35.1676     4.49723       28.4163      1.61596  144.964\n",
-    "    \n",
-    "# path\n",
-    "  height    rmse_test    std_test    rmse_train    std_train     k_time\n",
-    "--------  -----------  ----------  ------------  -----------  ---------\n",
-    "       0      33.4077     4.73272       29.9975     0.90234    0.853002\n",
-    "       1      33.4235     4.72131       30.1603     1.09423    1.71751\n",
-    "       2      33.433      4.72441       29.9286     0.787941   2.66032\n",
-    "       3      33.4073     4.73243       30.0114     0.909674   3.47763\n",
-    "       4      33.4256     4.72166       30.1842     1.1089     4.54367\n",
-    "       5      33.4067     4.72641       30.0411     1.01845    5.66178\n",
-    "       6      33.419      4.73075       29.9056     0.782179   6.14803\n",
-    "       7      33.4248     4.72155       30.1759     1.10382    7.60354\n",
-    "       8      33.4122     4.71554       30.1365     1.07485    7.97222\n",
-    "       9      33.4071     4.73193       30.0329     0.921065   9.07084\n",
-    "      10      33.4165     4.73169       29.9242     0.790843  10.0254"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'O', 'C'}\n",
-      "{'O', 'C'}\n"
-     ]
-    },
-    {
-     "ename": "TypeError",
-     "evalue": "'int' object is not iterable",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-4-e54963002171>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     66\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabelset1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     67\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabelset2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 68\u001b[0;31m \u001b[0mkernel\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mspkernel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mG2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     69\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkernel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     70\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/spKernel.py\u001b[0m in \u001b[0;36mspkernel\u001b[0;34m(edge_weight, *args)\u001b[0m\n\u001b[1;32m     39\u001b[0m     \u001b[0mstart_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     40\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 41\u001b[0;31m     \u001b[0mGn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m \u001b[0mgetSPGraph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge_weight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0medge_weight\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mG\u001b[0m \u001b[0;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m]\u001b[0m \u001b[0;31m# get shortest path graphs of Gn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     42\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     43\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/spKernel.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m     39\u001b[0m     \u001b[0mstart_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     40\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 41\u001b[0;31m     \u001b[0mGn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m \u001b[0mgetSPGraph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge_weight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0medge_weight\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mG\u001b[0m \u001b[0;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m]\u001b[0m \u001b[0;31m# get shortest path graphs of Gn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     42\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     43\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/utils/utils.py\u001b[0m in \u001b[0;36mgetSPGraph\u001b[0;34m(G, edge_weight)\u001b[0m\n\u001b[1;32m     35\u001b[0m     \u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0mBorgwardt\u001b[0m \u001b[0mKM\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mKriegel\u001b[0m \u001b[0mHP\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mShortest\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mpath\u001b[0m \u001b[0mkernels\u001b[0m \u001b[0mon\u001b[0m \u001b[0mgraphs\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mInData\u001b[0m \u001b[0mMining\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mFifth\u001b[0m \u001b[0mIEEE\u001b[0m \u001b[0mInternational\u001b[0m \u001b[0mConference\u001b[0m \u001b[0mon\u001b[0m \u001b[0;36m2005\u001b[0m \u001b[0mNov\u001b[0m \u001b[0;36m27\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mpp\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0;36m8\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mpp\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mIEEE\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     36\u001b[0m     \"\"\"\n\u001b[0;32m---> 37\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mfloydTransformation\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge_weight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0medge_weight\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     38\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     39\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mfloydTransformation\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge_weight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'bond_type'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/utils/utils.py\u001b[0m in \u001b[0;36mfloydTransformation\u001b[0;34m(G, edge_weight)\u001b[0m\n\u001b[1;32m     56\u001b[0m     \u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0mBorgwardt\u001b[0m \u001b[0mKM\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mKriegel\u001b[0m \u001b[0mHP\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mShortest\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mpath\u001b[0m \u001b[0mkernels\u001b[0m \u001b[0mon\u001b[0m \u001b[0mgraphs\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mInData\u001b[0m \u001b[0mMining\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mFifth\u001b[0m \u001b[0mIEEE\u001b[0m \u001b[0mInternational\u001b[0m \u001b[0mConference\u001b[0m \u001b[0mon\u001b[0m \u001b[0;36m2005\u001b[0m \u001b[0mNov\u001b[0m \u001b[0;36m27\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mpp\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0;36m8\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mpp\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mIEEE\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     57\u001b[0m     \"\"\"\n\u001b[0;32m---> 58\u001b[0;31m     \u001b[0mspMatrix\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfloyd_warshall_numpy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0medge_weight\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     59\u001b[0m     \u001b[0mS\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mGraph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     60\u001b[0m     \u001b[0mS\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_nodes_from\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnodes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/networkx/algorithms/shortest_paths/dense.py\u001b[0m in \u001b[0;36mfloyd_warshall_numpy\u001b[0;34m(G, nodelist, weight)\u001b[0m\n\u001b[1;32m     52\u001b[0m     \u001b[0;31m# nonedges are not given the value 0 as well.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     53\u001b[0m     A = nx.to_numpy_matrix(G, nodelist=nodelist, multigraph_weight=min,\n\u001b[0;32m---> 54\u001b[0;31m                            weight=weight, nonedge=np.inf)\n\u001b[0m\u001b[1;32m     55\u001b[0m     \u001b[0mn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mm\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mA\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     56\u001b[0m     \u001b[0mI\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0midentity\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/networkx/convert_matrix.py\u001b[0m in \u001b[0;36mto_numpy_matrix\u001b[0;34m(G, nodelist, dtype, order, multigraph_weight, weight, nonedge)\u001b[0m\n\u001b[1;32m    446\u001b[0m     A = to_numpy_array(G, nodelist=nodelist, dtype=dtype, order=order,\n\u001b[1;32m    447\u001b[0m                        \u001b[0mmultigraph_weight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmultigraph_weight\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mweight\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 448\u001b[0;31m                        nonedge=nonedge)\n\u001b[0m\u001b[1;32m    449\u001b[0m     \u001b[0mM\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masmatrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mA\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    450\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mM\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/networkx/convert_matrix.py\u001b[0m in \u001b[0;36mto_numpy_array\u001b[0;34m(G, nodelist, dtype, order, multigraph_weight, weight, nonedge)\u001b[0m\n\u001b[1;32m   1061\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1062\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mnodelist\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1063\u001b[0;31m         \u001b[0mnodelist\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1064\u001b[0m     \u001b[0mnodeset\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnodelist\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1065\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnodelist\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnodeset\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mTypeError\u001b[0m: 'int' object is not iterable"
-     ]
-    }
-   ],
-   "source": [
-    "import sys\n",
-    "import networkx as nx\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "from pygraph.kernels.spkernel import spkernel\n",
-    "\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "\n",
-    "def weisfeilerlehman_test(G):\n",
-    "    '''\n",
-    "    Weisfeiler-Lehman test of graph isomorphism.\n",
-    "    '''\n",
-    "\n",
-    "    nx.draw_networkx(G)\n",
-    "    plt.show()\n",
-    "    nx.draw_networkx_labels(G, nx.spring_layout(G), labels = nx.get_node_attributes(G,'label'))\n",
-    "    print(G.nodes(data = True))\n",
-    "    \n",
-    "    set_multisets = []\n",
-    "    for node in G.nodes(data = True):\n",
-    "        # Multiset-label determination.\n",
-    "        multiset = [ G.node[neighbors]['label'] for neighbors in G[node[0]] ]\n",
-    "        # sorting each multiset\n",
-    "        multiset.sort()\n",
-    "        multiset = node[1]['label'] + ''.join(multiset) # concatenate to a string and add the prefix \n",
-    "        set_multisets.append(multiset)\n",
-    "        \n",
-    "    # label compression\n",
-    "#     set_multisets.sort() # this is unnecessary\n",
-    "    set_unique = list(set(set_multisets)) # set of unique multiset labels\n",
-    "    set_compressed = { value : str(set_unique.index(value)) for value in set_unique } # assign indices as the new labels\n",
-    "#     print(set_compressed)\n",
-    "#     print(set_multisets)\n",
-    "    \n",
-    "    # relabel nodes with multisets\n",
-    "    for node in G.nodes(data = True):\n",
-    "        node[1]['label'] = set_multisets[node[0]]\n",
-    "    print(' -> ')\n",
-    "    nx.draw_networkx(G)\n",
-    "    plt.show()\n",
-    "    print(G.nodes(data = True))\n",
-    "\n",
-    "    \n",
-    "    # relabel nodes\n",
-    "    for node in G.nodes(data = True):\n",
-    "        node[1]['label'] = set_compressed[set_multisets[node[0]]]\n",
-    "        \n",
-    "    print(' -> ')\n",
-    "    nx.draw_networkx(G)\n",
-    "    plt.show()\n",
-    "    print(G.nodes(data = True))\n",
-    "\n",
-    "dataset, y = loadDataset(\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "G1 = dataset[12]\n",
-    "G2 = dataset[55]\n",
-    "\n",
-    "# init.\n",
-    "kernel = 0 # init kernel\n",
-    "num_nodes1 = G1.number_of_nodes()\n",
-    "num_nodes2 = G2.number_of_nodes()\n",
-    "\n",
-    "# the first iteration.\n",
-    "labelset1 = { G1.nodes(data = True)[i]['label'] for i in range(num_nodes1) }\n",
-    "labelset2 = { G2.nodes(data = True)[i]['label'] for i in range(num_nodes2) }\n",
-    "print(labelset1)\n",
-    "print(labelset2)\n",
-    "kernel += spkernel(G1, G2)\n",
-    "print(kernel)\n",
-    "\n",
-    "\n",
-    "\n",
-    "for height in range(0, min(num_nodes1, num_nodes2)): #Q how to determine the upper bound of the height?\n",
-    "    if labelset1 != labelset2:\n",
-    "        break\n",
-    "        \n",
-    "    # Weisfeiler-Lehman test of graph isomorphism.\n",
-    "    weisfeilerlehman_test(G1)\n",
-    "    weisfeilerlehman_test(G2)\n",
-    "    \n",
-    "    # calculate kernel\n",
-    "    kernel += spkernel(G1, G2)\n",
-    "    \n",
-    "    # get label sets of both graphs\n",
-    "    labelset1 = { G1.nodes(data = True)[i]['label'] for i in range(num_nodes1) }\n",
-    "    labelset2 = { G2.nodes(data = True)[i]['label'] for i in range(num_nodes2) }\n",
-    "#     print(labelset1)\n",
-    "#     print(labelset2)\n",
-    "\n",
-    "print(kernel)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O', 6: 'O'}\n",
-      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S', 7: 'S'}\n",
-      "\n",
-      " --- height = 0 --- \n",
-      "\n",
-      " --- for graph 0 --- \n",
-      "\n",
-      "labels_ori: ['C', 'C', 'C', 'C', 'C', 'O', 'O']\n",
-      "all_labels_ori: {'C', 'O'}\n",
-      "num_of_each_label: {'C': 5, 'O': 2}\n",
-      "all_num_of_each_label: [{'C': 5, 'O': 2}]\n",
-      "num_of_labels: 2\n",
-      "all_labels_ori: {'C', 'O'}\n",
-      "\n",
-      " --- for graph 1 --- \n",
-      "\n",
-      "labels_ori: ['C', 'C', 'C', 'C', 'C', 'C', 'S', 'S']\n",
-      "all_labels_ori: {'C', 'O', 'S'}\n",
-      "num_of_each_label: {'C': 6, 'S': 2}\n",
-      "all_num_of_each_label: [{'C': 5, 'O': 2}, {'C': 6, 'S': 2}]\n",
-      "num_of_labels: 2\n",
-      "all_labels_ori: {'C', 'O', 'S'}\n",
-      "\n",
-      " all_num_of_labels_occured: 3\n",
-      "\n",
-      " --- calculating kernel matrix ---\n",
-      "\n",
-      " labels: {'C', 'O'}\n",
-      "vector1: [[5 2]]\n",
-      "vector2: [[5 2]]\n",
-      "Kmatrix: [[ 29.   0.]\n",
-      " [  0.   0.]]\n",
-      "\n",
-      " labels: {'C', 'O', 'S'}\n",
-      "vector1: [[5 2 0]]\n",
-      "vector2: [[6 0 2]]\n",
-      "Kmatrix: [[ 29.  30.]\n",
-      " [ 30.   0.]]\n",
-      "\n",
-      " labels: {'C', 'S'}\n",
-      "vector1: [[6 2]]\n",
-      "vector2: [[6 2]]\n",
-      "Kmatrix: [[ 29.  30.]\n",
-      " [ 30.  40.]]\n",
-      "\n",
-      " --- height = 1 --- \n",
-      "\n",
-      " --- for graph 0 --- \n",
-      "\n",
-      "multiset: ['CC', 'CC', 'CCO', 'CCO', 'COO', 'OCC', 'OCC']\n",
-      "set_unique: ['OCC', 'COO', 'CCO', 'CC']\n",
-      "set_compressed: {'OCC': '4', 'COO': '5', 'CCO': '6', 'CC': '7'}\n",
-      "all_set_compressed: {'OCC': '4', 'COO': '5', 'CCO': '6', 'CC': '7'}\n",
-      "num_of_labels_occured: 7\n",
-      "\n",
-      " compressed labels: {0: '7', 1: '7', 2: '6', 3: '6', 4: '5', 5: '4', 6: '4'}\n",
-      "labels_comp: ['7', '7', '6', '6', '5', '4', '4']\n",
-      "all_labels_ori: {'5', '4', '6', '7'}\n",
-      "num_of_each_label: {'5': 1, '4': 2, '6': 2, '7': 2}\n",
-      "all_num_of_each_label: [{'5': 1, '4': 2, '6': 2, '7': 2}]\n",
-      "\n",
-      " --- for graph 1 --- \n",
-      "\n",
-      "multiset: ['CC', 'CC', 'CC', 'CCS', 'CCS', 'CCSS', 'SCC', 'SCC']\n",
-      "set_unique: ['SCC', 'CC', 'CCS', 'CCSS']\n",
-      "set_compressed: {'SCC': '8', 'CC': '7', 'CCS': '9', 'CCSS': '10'}\n",
-      "all_set_compressed: {'SCC': '8', 'COO': '5', 'CCS': '9', 'OCC': '4', 'CCO': '6', 'CCSS': '10', 'CC': '7'}\n",
-      "num_of_labels_occured: 10\n",
-      "\n",
-      " compressed labels: {0: '7', 1: '7', 2: '7', 3: '9', 4: '9', 5: '10', 6: '8', 7: '8'}\n",
-      "labels_comp: ['7', '7', '7', '9', '9', '10', '8', '8']\n",
-      "all_labels_ori: {'10', '4', '7', '9', '6', '5', '8'}\n",
-      "num_of_each_label: {'10': 1, '9': 2, '7': 3, '8': 2}\n",
-      "all_num_of_each_label: [{'5': 1, '4': 2, '6': 2, '7': 2}, {'10': 1, '9': 2, '7': 3, '8': 2}]\n",
-      "\n",
-      " all_num_of_labels_occured: 10\n",
-      "\n",
-      " --- calculating kernel matrix ---\n",
-      "\n",
-      " labels: {'5', '4', '6', '7'}\n",
-      "vector1: [[1 2 2 2]]\n",
-      "vector2: [[1 2 2 2]]\n",
-      "\n",
-      " labels: {'10', '4', '7', '9', '6', '5', '8'}\n",
-      "vector1: [[0 2 2 0 2 1 0]]\n",
-      "vector2: [[1 0 3 2 0 0 2]]\n",
-      "\n",
-      " labels: {'8', '10', '7', '9'}\n",
-      "vector1: [[2 1 3 2]]\n",
-      "vector2: [[2 1 3 2]]\n",
-      "\n",
-      " Kmatrix: [[ 42.  36.]\n",
-      " [ 36.  58.]]\n",
-      "\n",
-      " --- height = 2 --- \n",
-      "\n",
-      " --- for graph 0 --- \n",
-      "\n",
-      "multiset: ['76', '76', '647', '647', '544', '456', '456']\n",
-      "set_unique: ['647', '76', '456', '544']\n",
-      "set_compressed: {'647': '11', '76': '12', '544': '14', '456': '13'}\n",
-      "all_set_compressed: {'647': '11', '76': '12', '456': '13', '544': '14'}\n",
-      "num_of_labels_occured: 14\n",
-      "\n",
-      " compressed labels: {0: '12', 1: '12', 2: '11', 3: '11', 4: '14', 5: '13', 6: '13'}\n",
-      "labels_comp: ['12', '12', '11', '11', '14', '13', '13']\n",
-      "all_labels_ori: {'14', '12', '11', '13'}\n",
-      "num_of_each_label: {'14': 1, '13': 2, '12': 2, '11': 2}\n",
-      "all_num_of_each_label: [{'14': 1, '13': 2, '12': 2, '11': 2}]\n",
-      "\n",
-      " --- for graph 1 --- \n",
-      "\n",
-      "multiset: ['79', '79', '710', '978', '978', '10788', '8109', '8109']\n",
-      "set_unique: ['710', '8109', '79', '10788', '978']\n",
-      "set_compressed: {'710': '15', '79': '17', '8109': '16', '978': '19', '10788': '18'}\n",
-      "all_set_compressed: {'710': '15', '79': '17', '978': '19', '10788': '18', '8109': '16', '456': '13', '544': '14', '647': '11', '76': '12'}\n",
-      "num_of_labels_occured: 19\n",
-      "\n",
-      " compressed labels: {0: '17', 1: '17', 2: '15', 3: '19', 4: '19', 5: '18', 6: '16', 7: '16'}\n",
-      "labels_comp: ['17', '17', '15', '19', '19', '18', '16', '16']\n",
-      "all_labels_ori: {'18', '19', '12', '13', '17', '11', '14', '16', '15'}\n",
-      "num_of_each_label: {'15': 1, '17': 2, '19': 2, '16': 2, '18': 1}\n",
-      "all_num_of_each_label: [{'14': 1, '13': 2, '12': 2, '11': 2}, {'15': 1, '17': 2, '19': 2, '16': 2, '18': 1}]\n",
-      "\n",
-      " all_num_of_labels_occured: 19\n",
-      "\n",
-      " --- calculating kernel matrix ---\n",
-      "\n",
-      " labels: {'14', '12', '11', '13'}\n",
-      "vector1: [[1 2 2 2]]\n",
-      "vector2: [[1 2 2 2]]\n",
-      "\n",
-      " labels: {'18', '19', '12', '13', '17', '11', '14', '16', '15'}\n",
-      "vector1: [[0 0 2 2 0 2 1 0 0]]\n",
-      "vector2: [[1 2 0 0 2 0 0 2 1]]\n",
-      "\n",
-      " labels: {'18', '17', '15', '16', '19'}\n",
-      "vector1: [[1 2 1 2 2]]\n",
-      "vector2: [[1 2 1 2 2]]\n",
-      "\n",
-      " Kmatrix: [[ 55.  36.]\n",
-      " [ 36.  72.]]\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel built in 0.0034377574920654297 seconds ---\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "array([[ 55.,  36.],\n",
-       "       [ 36.,  72.]])"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# test of WL subtree kernel on many graphs\n",
-    "\n",
-    "import sys\n",
-    "import pathlib\n",
-    "from collections import Counter\n",
-    "sys.path.insert(0, \"../\")\n",
-    "\n",
-    "import networkx as nx\n",
-    "import numpy as np\n",
-    "import time\n",
-    "\n",
-    "from pygraph.kernels.spkernel import spkernel\n",
-    "from pygraph.kernels.pathKernel import pathkernel\n",
-    "\n",
-    "def weisfeilerlehmankernel(*args, height = 0, base_kernel = 'subtree'):\n",
-    "    \"\"\"Calculate Weisfeiler-Lehman kernels between graphs.\n",
-    "    \n",
-    "    Parameters\n",
-    "    ----------\n",
-    "    Gn : List of NetworkX graph\n",
-    "        List of graphs between which the kernels are calculated.\n",
-    "    /\n",
-    "    G1, G2 : NetworkX graphs\n",
-    "        2 graphs between which the kernel is calculated.\n",
-    "        \n",
-    "    height : subtree height\n",
-    "    \n",
-    "    base_kernel : base kernel used in each iteration of WL kernel\n",
-    "        the default base kernel is subtree kernel\n",
-    "        \n",
-    "    Return\n",
-    "    ------\n",
-    "    Kmatrix/Kernel : Numpy matrix/int\n",
-    "        Kernel matrix, each element of which is the Weisfeiler-Lehman kernel between 2 praphs. / Weisfeiler-Lehman Kernel between 2 graphs.\n",
-    "        \n",
-    "    Notes\n",
-    "    -----\n",
-    "    This function now supports WL subtree kernel and WL shortest path kernel.\n",
-    "    \n",
-    "    References\n",
-    "    ----------\n",
-    "    [1] Shervashidze N, Schweitzer P, Leeuwen EJ, Mehlhorn K, Borgwardt KM. Weisfeiler-lehman graph kernels. Journal of Machine Learning Research. 2011;12(Sep):2539-61.\n",
-    "    \"\"\"\n",
-    "    if len(args) == 1: # for a list of graphs\n",
-    "\n",
-    "#         print(args)\n",
-    "        start_time = time.time()\n",
-    "        \n",
-    "        # for WL subtree kernel\n",
-    "        if base_kernel == 'subtree':           \n",
-    "            Kmatrix = _wl_subtreekernel_do(args[0], height = height, base_kernel = 'subtree')\n",
-    "            \n",
-    "        # for WL edge kernel\n",
-    "        elif base_kernel == 'edge':\n",
-    "            print('edge')\n",
-    "            \n",
-    "        # for WL shortest path kernel\n",
-    "        elif base_kernel == 'sp':\n",
-    "            Gn = args[0]\n",
-    "            Kmatrix = np.zeros((len(Gn), len(Gn)))\n",
-    "            \n",
-    "            for i in range(0, len(Gn)):\n",
-    "                for j in range(i, len(Gn)):\n",
-    "                    Kmatrix[i][j] = _weisfeilerlehmankernel_do(Gn[i], Gn[j])\n",
-    "                    Kmatrix[j][i] = Kmatrix[i][j]\n",
-    "\n",
-    "        print(\"\\n --- Weisfeiler-Lehman %s kernel matrix of size %d built in %s seconds ---\" % (base_kernel, len(args[0]), (time.time() - start_time)))\n",
-    "        \n",
-    "        return Kmatrix\n",
-    "        \n",
-    "    else: # for only 2 graphs\n",
-    "        \n",
-    "        start_time = time.time()\n",
-    "        \n",
-    "        # for WL subtree kernel\n",
-    "        if base_kernel == 'subtree':\n",
-    "            \n",
-    "            args = [args[0], args[1]]\n",
-    "#             print(args)\n",
-    "            kernel = _wl_subtreekernel_do(args, height = height, base_kernel = 'subtree')\n",
-    "            \n",
-    "        # for WL edge kernel\n",
-    "        elif base_kernel == 'edge':\n",
-    "            print('edge')\n",
-    "            \n",
-    "        # for WL shortest path kernel\n",
-    "        elif base_kernel == 'sp':\n",
-    "            \n",
-    "\n",
-    "            kernel = _pathkernel_do(args[0], args[1])\n",
-    "\n",
-    "        print(\"\\n --- Weisfeiler-Lehman %s kernel built in %s seconds ---\" % (base_kernel, time.time() - start_time))\n",
-    "        \n",
-    "        return kernel\n",
-    "    \n",
-    "    \n",
-    "def _weisfeilerlehmankernel_do(G1, G2):\n",
-    "    \"\"\"Calculate Weisfeiler-Lehman kernels between 2 graphs. This kernel use shortest path kernel to calculate kernel between two graphs in each iteration.\n",
-    "    \n",
-    "    Parameters\n",
-    "    ----------\n",
-    "    G1, G2 : NetworkX graphs\n",
-    "        2 graphs between which the kernel is calculated.\n",
-    "        \n",
-    "    Return\n",
-    "    ------\n",
-    "    Kernel : int\n",
-    "        Weisfeiler-Lehman Kernel between 2 graphs.\n",
-    "    \"\"\"\n",
-    "    \n",
-    "    # init.\n",
-    "    kernel = 0 # init kernel\n",
-    "    num_nodes1 = G1.number_of_nodes()\n",
-    "    num_nodes2 = G2.number_of_nodes()\n",
-    "    height = 12 #min(num_nodes1, num_nodes2)) #Q how to determine the upper bound of the height?\n",
-    "    \n",
-    "    # the first iteration.\n",
-    "    labelset1 = { G1.nodes(data = True)[i]['label'] for i in range(num_nodes1) }\n",
-    "    labelset2 = { G2.nodes(data = True)[i]['label'] for i in range(num_nodes2) }\n",
-    "    kernel += pathkernel(G1, G2) # change your base kernel here (and one more below)\n",
-    "    \n",
-    "    for h in range(0, height):\n",
-    "#         if labelset1 != labelset2:\n",
-    "#             break\n",
-    "\n",
-    "        # Weisfeiler-Lehman test of graph isomorphism.\n",
-    "        relabel(G1)\n",
-    "        relabel(G2)\n",
-    "\n",
-    "        # calculate kernel\n",
-    "        kernel += pathkernel(G1, G2) # change your base kernel here (and one more before)\n",
-    "\n",
-    "        # get label sets of both graphs\n",
-    "        labelset1 = { G1.nodes(data = True)[i]['label'] for i in range(num_nodes1) }\n",
-    "        labelset2 = { G2.nodes(data = True)[i]['label'] for i in range(num_nodes2) }\n",
-    "    \n",
-    "    return kernel\n",
-    "\n",
-    "\n",
-    "def relabel(G):\n",
-    "    '''\n",
-    "    Relabel nodes in graph G in one iteration of the 1-dim. WL test of graph isomorphism.\n",
-    "    \n",
-    "    Parameters\n",
-    "    ----------\n",
-    "    G : NetworkX graph\n",
-    "        The graphs whose nodes are relabeled.\n",
-    "    '''\n",
-    "    \n",
-    "    # get the set of original labels\n",
-    "    labels_ori = list(nx.get_node_attributes(G, 'label').values())\n",
-    "    print(labels_ori)\n",
-    "    num_of_each_label = dict(Counter(labels_ori))\n",
-    "    print(num_of_each_label)\n",
-    "    num_of_labels = len(num_of_each_label)\n",
-    "    print(num_of_labels)\n",
-    "    \n",
-    "    set_multisets = []\n",
-    "    for node in G.nodes(data = True):\n",
-    "        # Multiset-label determination.\n",
-    "        multiset = [ G.node[neighbors]['label'] for neighbors in G[node[0]] ]\n",
-    "        # sorting each multiset\n",
-    "        multiset.sort()\n",
-    "        multiset = node[1]['label'] + ''.join(multiset) # concatenate to a string and add the prefix \n",
-    "        set_multisets.append(multiset)\n",
-    "    print(set_multisets)\n",
-    "        \n",
-    "    # label compression\n",
-    "#     set_multisets.sort() # this is unnecessary\n",
-    "    set_unique = list(set(set_multisets)) # set of unique multiset labels\n",
-    "    print(set_unique)\n",
-    "    set_compressed = { value : str(set_unique.index(value) + num_of_labels + 1) for value in set_unique } # assign new labels\n",
-    "    print(set_compressed)\n",
-    "    \n",
-    "    # relabel nodes\n",
-    "#     nx.relabel_nodes(G, set_compressed, copy = False)\n",
-    "    for node in G.nodes(data = True):\n",
-    "        node[1]['label'] = set_compressed[set_multisets[node[0]]]\n",
-    "    print(nx.get_node_attributes(G, 'label'))\n",
-    "\n",
-    "    # get the set of compressed labels\n",
-    "    labels_comp = list(nx.get_node_attributes(G, 'label').values())\n",
-    "    print(labels_comp)\n",
-    "    num_of_each_label.update(dict(Counter(labels_comp)))\n",
-    "    print(num_of_each_label)\n",
-    "    \n",
-    "    \n",
-    "def _wl_subtreekernel_do(*args, height = 0, base_kernel = 'subtree'):\n",
-    "    \"\"\"Calculate Weisfeiler-Lehman subtree kernels between graphs.\n",
-    "    \n",
-    "    Parameters\n",
-    "    ----------\n",
-    "    Gn : List of NetworkX graph\n",
-    "        List of graphs between which the kernels are calculated.\n",
-    "        \n",
-    "    Return\n",
-    "    ------\n",
-    "    Kmatrix/Kernel : Numpy matrix/int\n",
-    "        Kernel matrix, each element of which is the Weisfeiler-Lehman kernel between 2 praphs.\n",
-    "    \"\"\"\n",
-    "    \n",
-    "#     print(args)\n",
-    "    Gn = args[0]\n",
-    "#     print(Gn)\n",
-    "\n",
-    "    Kmatrix = np.zeros((len(Gn), len(Gn)))\n",
-    "    all_num_of_labels_occured = 0 # number of the set of letters that occur before as node labels at least once in all graphs\n",
-    "    \n",
-    "    # initial for height = 0\n",
-    "    print('\\n --- height = 0 --- ')\n",
-    "    all_labels_ori = set() # all unique orignal labels in all graphs in this iteration\n",
-    "    all_num_of_each_label = [] # number of occurence of each label in each graph in this iteration\n",
-    "    all_set_compressed = {} # a dictionary mapping original labels to new ones in all graphs in this iteration\n",
-    "    num_of_labels_occured = all_num_of_labels_occured # number of the set of letters that occur before as node labels at least once in all graphs\n",
-    "\n",
-    "    # for each graph\n",
-    "    for idx, G in enumerate(Gn):\n",
-    "        # get the set of original labels\n",
-    "        print('\\n --- for graph %d --- \\n' % (idx))\n",
-    "        labels_ori = list(nx.get_node_attributes(G, 'label').values())\n",
-    "        print('labels_ori: %s' % (labels_ori))\n",
-    "        all_labels_ori.update(labels_ori)\n",
-    "        print('all_labels_ori: %s' % (all_labels_ori))\n",
-    "        num_of_each_label = dict(Counter(labels_ori)) # number of occurence of each label in graph\n",
-    "        print('num_of_each_label: %s' % (num_of_each_label))\n",
-    "        all_num_of_each_label.append(num_of_each_label)\n",
-    "        print('all_num_of_each_label: %s' % (all_num_of_each_label))\n",
-    "        num_of_labels = len(num_of_each_label) # number of all unique labels\n",
-    "        print('num_of_labels: %s' % (num_of_labels))\n",
-    "        \n",
-    "\n",
-    "        all_labels_ori.update(labels_ori)\n",
-    "        print('all_labels_ori: %s' % (all_labels_ori))\n",
-    "        \n",
-    "    all_num_of_labels_occured += len(all_labels_ori)\n",
-    "    print('\\n all_num_of_labels_occured: %s' % (all_num_of_labels_occured))\n",
-    "        \n",
-    "    # calculate subtree kernel with the 0th iteration and add it to the final kernel\n",
-    "    print('\\n --- calculating kernel matrix ---')\n",
-    "    for i in range(0, len(Gn)):\n",
-    "        for j in range(i, len(Gn)):\n",
-    "            labels = set(list(all_num_of_each_label[i].keys()) + list(all_num_of_each_label[j].keys()))\n",
-    "            print('\\n labels: %s' % (labels))\n",
-    "            vector1 = np.matrix([ (all_num_of_each_label[i][label] if (label in all_num_of_each_label[i].keys()) else 0) for label in labels ])\n",
-    "            vector2 = np.matrix([ (all_num_of_each_label[j][label] if (label in all_num_of_each_label[j].keys()) else 0) for label in labels ])\n",
-    "            print('vector1: %s' % (vector1))\n",
-    "            print('vector2: %s' % (vector2))\n",
-    "            Kmatrix[i][j] += np.dot(vector1, vector2.transpose())\n",
-    "            Kmatrix[j][i] = Kmatrix[i][j]\n",
-    "            print('Kmatrix: %s' % (Kmatrix))\n",
-    "\n",
-    "    \n",
-    "    # iterate each height\n",
-    "    for h in range(1, height + 1):\n",
-    "        print('\\n --- height = %d --- ' % (h))\n",
-    "        all_set_compressed = {} # a dictionary mapping original labels to new ones in all graphs in this iteration\n",
-    "        num_of_labels_occured = all_num_of_labels_occured # number of the set of letters that occur before as node labels at least once in all graphs\n",
-    "        all_labels_ori = set()\n",
-    "        all_num_of_each_label = []\n",
-    "        \n",
-    "        # for each graph\n",
-    "        for idx, G in enumerate(Gn):\n",
-    "#             # get the set of original labels\n",
-    "            print('\\n --- for graph %d --- \\n' % (idx))\n",
-    "#             labels_ori = list(nx.get_node_attributes(G, 'label').values())\n",
-    "#             print('labels_ori: %s' % (labels_ori))\n",
-    "#             num_of_each_label = dict(Counter(labels_ori)) # number of occurence of each label in graph\n",
-    "#             print('num_of_each_label: %s' % (num_of_each_label))\n",
-    "#             num_of_labels = len(num_of_each_label) # number of all unique labels\n",
-    "#             print('num_of_labels: %s' % (num_of_labels))\n",
-    "            \n",
-    "#             all_labels_ori.update(labels_ori)\n",
-    "#             print('all_labels_ori: %s' % (all_labels_ori))\n",
-    "#             #             num_of_labels_occured += num_of_labels #@todo not precise\n",
-    "#             num_of_labels_occured = all_num_of_labels_occured + len(all_labels_ori) + len(all_set_compressed)\n",
-    "#             print('num_of_labels_occured: %s' % (num_of_labels_occured))\n",
-    "            \n",
-    "            set_multisets = []\n",
-    "            for node in G.nodes(data = True):\n",
-    "                # Multiset-label determination.\n",
-    "                multiset = [ G.node[neighbors]['label'] for neighbors in G[node[0]] ]\n",
-    "                # sorting each multiset\n",
-    "                multiset.sort()\n",
-    "                multiset = node[1]['label'] + ''.join(multiset) # concatenate to a string and add the prefix \n",
-    "                set_multisets.append(multiset)\n",
-    "            print('multiset: %s' % (set_multisets))\n",
-    "\n",
-    "            # label compression\n",
-    "        #     set_multisets.sort() # this is unnecessary\n",
-    "            set_unique = list(set(set_multisets)) # set of unique multiset labels\n",
-    "            print('set_unique: %s' % (set_unique))\n",
-    "            # a dictionary mapping original labels to new ones. \n",
-    "            set_compressed = {}\n",
-    "            # if a label occured before, assign its former compressed label, else assign the number of labels occured + 1 as the compressed label \n",
-    "            for value in set_unique:\n",
-    "                if value in all_set_compressed.keys():\n",
-    "                    set_compressed.update({ value : all_set_compressed[value] })\n",
-    "                else:\n",
-    "                    set_compressed.update({ value : str(num_of_labels_occured + 1) })\n",
-    "                    num_of_labels_occured += 1\n",
-    "#             set_compressed = { value : (all_set_compressed[value] if value in all_set_compressed.keys() else str(set_unique.index(value) + num_of_labels_occured + 1)) for value in set_unique }\n",
-    "            print('set_compressed: %s' % (set_compressed))\n",
-    "            \n",
-    "            all_set_compressed.update(set_compressed)\n",
-    "            print('all_set_compressed: %s' % (all_set_compressed))\n",
-    "#             num_of_labels_occured += len(set_compressed) #@todo not precise\n",
-    "            print('num_of_labels_occured: %s' % (num_of_labels_occured))\n",
-    "            \n",
-    "            # relabel nodes\n",
-    "        #     nx.relabel_nodes(G, set_compressed, copy = False)\n",
-    "            for node in G.nodes(data = True):\n",
-    "                node[1]['label'] = set_compressed[set_multisets[node[0]]]\n",
-    "            print('\\n compressed labels: %s' % (nx.get_node_attributes(G, 'label')))\n",
-    "\n",
-    "            # get the set of compressed labels\n",
-    "            labels_comp = list(nx.get_node_attributes(G, 'label').values())\n",
-    "            print('labels_comp: %s' % (labels_comp))\n",
-    "            all_labels_ori.update(labels_comp)\n",
-    "            print('all_labels_ori: %s' % (all_labels_ori))\n",
-    "            num_of_each_label = dict(Counter(labels_comp))\n",
-    "            print('num_of_each_label: %s' % (num_of_each_label))\n",
-    "            all_num_of_each_label.append(num_of_each_label)\n",
-    "            print('all_num_of_each_label: %s' % (all_num_of_each_label))\n",
-    "                    \n",
-    "        all_num_of_labels_occured += len(all_labels_ori)\n",
-    "        print('\\n all_num_of_labels_occured: %s' % (all_num_of_labels_occured))\n",
-    "        \n",
-    "        # calculate subtree kernel with h iterations and add it to the final kernel\n",
-    "        print('\\n --- calculating kernel matrix ---')\n",
-    "        for i in range(0, len(Gn)):\n",
-    "            for j in range(i, len(Gn)):\n",
-    "                labels = set(list(all_num_of_each_label[i].keys()) + list(all_num_of_each_label[j].keys()))\n",
-    "                print('\\n labels: %s' % (labels))\n",
-    "                vector1 = np.matrix([ (all_num_of_each_label[i][label] if (label in all_num_of_each_label[i].keys()) else 0) for label in labels ])\n",
-    "                vector2 = np.matrix([ (all_num_of_each_label[j][label] if (label in all_num_of_each_label[j].keys()) else 0) for label in labels ])\n",
-    "                print('vector1: %s' % (vector1))\n",
-    "                print('vector2: %s' % (vector2))\n",
-    "                Kmatrix[i][j] += np.dot(vector1, vector2.transpose())\n",
-    "                Kmatrix[j][i] = Kmatrix[i][j]\n",
-    "                    \n",
-    "        print('\\n Kmatrix: %s' % (Kmatrix))\n",
-    "\n",
-    "    return Kmatrix\n",
-    "\n",
-    "    \n",
-    "# main\n",
-    "import sys\n",
-    "from collections import Counter\n",
-    "import networkx as nx\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "from pygraph.kernels.spkernel import spkernel\n",
-    "\n",
-    "dataset, y = loadDataset(\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "G1 = dataset[15]\n",
-    "print(nx.get_node_attributes(G1, 'label'))\n",
-    "G2 = dataset[80]\n",
-    "print(nx.get_node_attributes(G2, 'label'))\n",
-    "\n",
-    "weisfeilerlehmankernel(G1, G2, height = 2)\n",
-    "# Kmatrix = weisfeilerlehmankernel(G1, G2)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/.ipynb_checkpoints/test_lib-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/test_lib-checkpoint.ipynb
deleted file mode 100644
index 0b7ae52..0000000
--- a/notebooks/.ipynb_checkpoints/test_lib-checkpoint.ipynb
+++ /dev/null
@@ -1,175 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {
-    "autoscroll": false,
-    "ein.tags": "worksheet-0",
-    "slideshow": {
-     "slide_type": "-"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "\n",
-    "import paths\n",
-    "\n",
-    "from ged.GED import ged\n",
-    "from utils.graphfiles import loadDataset\n",
-    "from ged.costfunctions import RiesenCostFunction, BasicCostFunction\n",
-    "from ged.bipartiteGED import computeBipartiteCostMatrix, getOptimalMapping"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "autoscroll": false,
-    "ein.tags": "worksheet-0",
-    "slideshow": {
-     "slide_type": "-"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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12N8BegM3A7+qvjI9HV59FTIjfsZFAiWm57mb2Y1mttfMis3svjDrzzKzp0Pr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\nkMJdRCSAFO4iIgGkcBcRCSCFu4hIAP0v8ncXPBCruC4AAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f61fed58cc0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[0, 1, 4]\n"
-     ]
-    }
-   ],
-   "source": [
-    "import networkx as nx\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot  as plt\n",
-    "dataset, y = loadDataset(\"/home/bgauzere/work/Datasets/Acyclic/dataset_bps.ds\")\n",
-    "nx.draw_networkx(dataset[12])\n",
-    "plt.show()\n",
-    "print(list(dataset[12][3]))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {
-    "autoscroll": false,
-    "ein.tags": "worksheet-0",
-    "slideshow": {
-     "slide_type": "-"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "cf = BasicCostFunction(1,3,1,3)\n",
-    "N=len(dataset)\n",
-    "N=10\n",
-    "ged_distances = np.zeros((N,N))\n",
-    "for i in range(0,N):\n",
-    "    for j in range(i,N):\n",
-    "          ged_distances[j,i] = ged_distances[i,j] = ged(dataset[i],dataset[j],cf=cf, method='Riesen')[0]\n",
-    "        \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "autoscroll": false,
-    "ein.tags": "worksheet-0",
-    "slideshow": {
-     "slide_type": "-"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(0, array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))\n",
-      "(0, array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))\n",
-      "(0, array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))\n"
-     ]
-    }
-   ],
-   "source": [
-    "G1=dataset[12]\n",
-    "G2=dataset[12]\n",
-    "\n",
-    "print(ged(G1,G2))\n",
-    "print(ged(G1,G2,method='Basic'))\n",
-    "print(ged(G1,G2,method='Riesen'))\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {
-    "autoscroll": false,
-    "ein.tags": "worksheet-0",
-    "slideshow": {
-     "slide_type": "-"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{0: {0: [0], 3: [0, 3], 1: [0, 3, 1], 4: [0, 3, 4], 2: [0, 3, 4, 2]}, 1: {1: [1], 3: [1, 3], 0: [1, 3, 0], 4: [1, 3, 4], 2: [1, 3, 4, 2]}, 2: {2: [2], 4: [2, 4], 3: [2, 4, 3], 0: [2, 4, 3, 0], 1: [2, 4, 3, 1]}, 3: {3: [3], 0: [3, 0], 1: [3, 1], 4: [3, 4], 2: [3, 4, 2]}, 4: {4: [4], 2: [4, 2], 3: [4, 3], 0: [4, 3, 0], 1: [4, 3, 1]}}\n",
-      "[[ 0.  2.  3.  1.  2.]\n",
-      " [ 2.  0.  3.  1.  2.]\n",
-      " [ 3.  3.  0.  2.  1.]\n",
-      " [ 1.  1.  2.  0.  1.]\n",
-      " [ 2.  2.  1.  1.  0.]]\n"
-     ]
-    }
-   ],
-   "source": [
-    "l = nx.shortest_path(G1)\n",
-    "print(l)\n",
-    "\n",
-    "distances = np.zeros((G1.number_of_nodes(),G1.number_of_nodes()))\n",
-    "for i in l.keys():\n",
-    "    for j in l[i].keys():\n",
-    "        distances[i,j] = len(l[i][j])-1\n",
-    "\n",
-    "print(distances)\n"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  },
-  "name": "test_lib.ipynb"
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/.ipynb_checkpoints/test_modelselection-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/test_modelselection-checkpoint.ipynb
deleted file mode 100644
index 9df31af..0000000
--- a/notebooks/.ipynb_checkpoints/test_modelselection-checkpoint.ipynb
+++ /dev/null
@@ -1,2236 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "1. Loading dataset from file...\n",
-      "\n",
-      "2. Calculating gram matrices. This could take a while...\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 0.38582420349121094 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'height': 0, 'base_kernel': 'subtree'} is: \n",
-      "[[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 0.8528649806976318 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'height': 1, 'base_kernel': 'subtree'} is: \n",
-      "[[ 10.  10.   4. ...  20.  20.  20.]\n",
-      " [ 10.  16.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.  10. ...  22.  22.  24.]\n",
-      " ...\n",
-      " [ 20.  20.  22. ... 130. 130. 122.]\n",
-      " [ 20.  20.  22. ... 130. 130. 122.]\n",
-      " [ 20.  20.  24. ... 122. 122. 154.]]\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 1.3853302001953125 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'height': 2, 'base_kernel': 'subtree'} is: \n",
-      "[[ 15.   4.   0. ...   0.   0.   0.]\n",
-      " [  4.  24.   0. ...   0.   0.   0.]\n",
-      " [  0.   0.  15. ...   1.   1.   5.]\n",
-      " ...\n",
-      " [  0.   0.   1. ...  87.  58.  23.]\n",
-      " [  0.   0.   1. ...  58.  67.  23.]\n",
-      " [  0.   0.   5. ...  23.  23. 101.]]\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 1.9092471599578857 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'height': 3, 'base_kernel': 'subtree'} is: \n",
-      "[[ 20.   0.   0. ...   0.   0.   0.]\n",
-      " [  0.  32.   0. ...   0.   0.   0.]\n",
-      " [  0.   0.  20. ...   0.   0.   0.]\n",
-      " ...\n",
-      " [  0.   0.   0. ... 116.   8.   0.]\n",
-      " [  0.   0.   0. ...   8.  60.   0.]\n",
-      " [  0.   0.   0. ...   0.   0.  50.]]\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 2.3514244556427 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'height': 4, 'base_kernel': 'subtree'} is: \n",
-      "[[ 25.   0.   0. ...   0.   0.   0.]\n",
-      " [  0.  40.   0. ...   0.   0.   0.]\n",
-      " [  0.   0.  25. ...   0.   0.   0.]\n",
-      " ...\n",
-      " [  0.   0.   0. ... 145.   0.   0.]\n",
-      " [  0.   0.   0. ...   0.  75.   0.]\n",
-      " [  0.   0.   0. ...   0.   0.  55.]]\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 2.7743802070617676 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'height': 5, 'base_kernel': 'subtree'} is: \n",
-      "[[ 30.   0.   0. ...   0.   0.   0.]\n",
-      " [  0.  48.   0. ...   0.   0.   0.]\n",
-      " [  0.   0.  30. ...   0.   0.   0.]\n",
-      " ...\n",
-      " [  0.   0.   0. ... 174.   0.   0.]\n",
-      " [  0.   0.   0. ...   0.  90.   0.]\n",
-      " [  0.   0.   0. ...   0.   0.  66.]]\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 3.364100456237793 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'height': 6, 'base_kernel': 'subtree'} is: \n",
-      "[[ 35.   0.   0. ...   0.   0.   0.]\n",
-      " [  0.  56.   0. ...   0.   0.   0.]\n",
-      " [  0.   0.  35. ...   0.   0.   0.]\n",
-      " ...\n",
-      " [  0.   0.   0. ... 203.   0.   0.]\n",
-      " [  0.   0.   0. ...   0. 105.   0.]\n",
-      " [  0.   0.   0. ...   0.   0.  77.]]\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 3.6507043838500977 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'height': 7, 'base_kernel': 'subtree'} is: \n",
-      "[[ 40.   0.   0. ...   0.   0.   0.]\n",
-      " [  0.  64.   0. ...   0.   0.   0.]\n",
-      " [  0.   0.  40. ...   0.   0.   0.]\n",
-      " ...\n",
-      " [  0.   0.   0. ... 232.   0.   0.]\n",
-      " [  0.   0.   0. ...   0. 120.   0.]\n",
-      " [  0.   0.   0. ...   0.   0.  88.]]\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 4.038440465927124 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'height': 8, 'base_kernel': 'subtree'} is: \n",
-      "[[ 45.   0.   0. ...   0.   0.   0.]\n",
-      " [  0.  72.   0. ...   0.   0.   0.]\n",
-      " [  0.   0.  45. ...   0.   0.   0.]\n",
-      " ...\n",
-      " [  0.   0.   0. ... 261.   0.   0.]\n",
-      " [  0.   0.   0. ...   0. 135.   0.]\n",
-      " [  0.   0.   0. ...   0.   0.  99.]]\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 4.48335337638855 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'height': 9, 'base_kernel': 'subtree'} is: \n",
-      "[[ 50.   0.   0. ...   0.   0.   0.]\n",
-      " [  0.  80.   0. ...   0.   0.   0.]\n",
-      " [  0.   0.  50. ...   0.   0.   0.]\n",
-      " ...\n",
-      " [  0.   0.   0. ... 290.   0.   0.]\n",
-      " [  0.   0.   0. ...   0. 150.   0.]\n",
-      " [  0.   0.   0. ...   0.   0. 110.]]\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 4.945931434631348 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'height': 10, 'base_kernel': 'subtree'} is: \n",
-      "[[ 55.   0.   0. ...   0.   0.   0.]\n",
-      " [  0.  88.   0. ...   0.   0.   0.]\n",
-      " [  0.   0.  55. ...   0.   0.   0.]\n",
-      " ...\n",
-      " [  0.   0.   0. ... 319.   0.   0.]\n",
-      " [  0.   0.   0. ...   0. 165.   0.]\n",
-      " [  0.   0.   0. ...   0.   0. 121.]]\n",
-      "\n",
-      "3. Fitting and predicting using nested cross validation. This could really take a while...\n",
-      "\n",
-      "cross validation:   0%|          | 0/30 [00:00<?, ?it/s]\u001b[A"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/sklearn/linear_model/ridge.py:154: UserWarning: Singular matrix in solving dual problem. Using least-squares solution instead.\n",
-      "  warnings.warn(\"Singular matrix in solving dual problem. Using \"\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Exception in thread Thread-4:\n",
-      "Traceback (most recent call last):\n",
-      "  File \"/usr/lib/python3.5/threading.py\", line 914, in _bootstrap_inner\n",
-      "    self.run()\n",
-      "  File \"/usr/local/lib/python3.5/dist-packages/tqdm/_tqdm.py\", line 144, in run\n",
-      "    for instance in self.tqdm_cls._instances:\n",
-      "  File \"/usr/lib/python3.5/_weakrefset.py\", line 60, in __iter__\n",
-      "    for itemref in self.data:\n",
-      "RuntimeError: Set changed size during iteration\n",
-      "\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "cross validation: 100%|██████████| 30/30 [05:38<00:00, 11.29s/it]\n",
-      "\n",
-      "4. Getting final performances...\n",
-      "average_train_scores:  [[1.68678701e+01 1.68678894e+01 1.68679278e+01 1.68680045e+01\n",
-      "  1.68681583e+01 1.68684675e+01 1.68690939e+01 1.68703814e+01\n",
-      "  1.68730981e+01 1.68790907e+01 1.68932019e+01 1.69290400e+01\n",
-      "  1.70251737e+01 1.72811526e+01 1.79017302e+01 1.91812251e+01\n",
-      "  2.13896255e+01 2.45735919e+01 6.53261689e+01 3.24718364e+01\n",
-      "  3.72393499e+01]\n",
-      " [5.99543018e+00 5.99269850e+00 5.98746782e+00 5.97788732e+00\n",
-      "  5.96203429e+00 5.94229671e+00 5.94246941e+00 6.05118937e+00\n",
-      "  6.46062470e+00 7.33868161e+00 8.55810498e+00 9.78035133e+00\n",
-      "  1.08011538e+01 1.16456895e+01 1.25149375e+01 1.38052604e+01\n",
-      "  1.60229892e+01 1.93958918e+01 2.36723176e+01 2.95422013e+01\n",
-      "  3.41064041e+01]\n",
-      " [7.25861859e+02 5.43531296e+02 4.13700467e+02 5.70780096e+02\n",
-      "  3.95327690e+02 1.82308565e+04 2.00100597e+02 3.16087438e+02\n",
-      "  1.14834090e+02 8.15065622e+01 3.07967143e+01 1.46129446e+01\n",
-      "  1.03787365e+01 1.07381202e+01 1.25971111e+01 1.53797490e+01\n",
-      "  1.92106490e+01 2.45020446e+01 3.34717424e+01 4.30681871e+01\n",
-      "  5.79434542e+01]\n",
-      " [1.41054628e+04 1.60060358e+04 1.22510539e+04 8.68870874e+03\n",
-      "  1.40353379e+04 1.20685802e+04 4.91766693e+03 2.68915231e+03\n",
-      "  9.89636355e+02 7.66368843e+02 4.67568054e+02 7.82315480e+01\n",
-      "  4.83952539e+01 4.08742996e+01 3.92899666e+01 4.32191446e+01\n",
-      "  9.10086825e+01 7.15102584e+01 8.97278100e+01 1.07634205e+02\n",
-      "  1.21316512e+02]\n",
-      " [9.85094824e+04 4.49242724e+04 2.01994326e+04 1.09007892e+04\n",
-      "  4.02058824e+03 1.86614477e+03 1.00006947e+03 1.20661835e+03\n",
-      "  2.73598223e+02 1.45120165e+02 1.06706134e+02 9.10333560e+01\n",
-      "  8.39576743e+01 7.93396825e+01 7.56138840e+01 7.73405032e+01\n",
-      "  9.70130054e+01 9.83571738e+01 1.12771747e+02 1.24500484e+02\n",
-      "  1.32070346e+02]\n",
-      " [9.24578675e+01 9.24564320e+01 9.24535681e+01 9.24478553e+01\n",
-      "  9.24364618e+01 9.24137495e+01 9.23685148e+01 9.22785865e+01\n",
-      "  9.21004504e+01 9.17501270e+01 9.10710809e+01 8.97926701e+01\n",
-      "  8.75246416e+01 8.39736208e+01 7.98169294e+01 7.82394617e+01\n",
-      "  8.65653933e+01 1.02732995e+02 1.11473041e+02 1.23436397e+02\n",
-      "  1.31394256e+02]\n",
-      " [9.46604078e+01 9.46591308e+01 9.46565830e+01 9.46515003e+01\n",
-      "  9.46413631e+01 9.46211520e+01 9.45808870e+01 9.45007918e+01\n",
-      "  9.43419483e+01 9.40288339e+01 9.34190515e+01 9.22600584e+01\n",
-      "  9.01630992e+01 8.67371862e+01 8.22743593e+01 7.92834976e+01\n",
-      "  1.47231374e+02 9.95627718e+01 1.08557333e+02 1.21189826e+02\n",
-      "  1.29979287e+02]\n",
-      " [9.40117926e+01 9.40106789e+01 9.40084570e+01 9.40040245e+01\n",
-      "  9.39951835e+01 9.39775553e+01 9.39424296e+01 9.38725324e+01\n",
-      "  9.37338143e+01 9.34599801e+01 9.29251671e+01 9.19028103e+01\n",
-      "  9.00313975e+01 8.68988323e+01 8.25853651e+01 7.90804942e+01\n",
-      "  8.35445309e+01 9.41012021e+01 1.05951512e+02 1.19148392e+02\n",
-      "  1.28727245e+02]\n",
-      " [9.38541578e+01 9.38531720e+01 9.38512051e+01 9.38472813e+01\n",
-      "  9.38394547e+01 9.38238478e+01 9.37927449e+01 9.37308337e+01\n",
-      "  9.36078886e+01 9.33648912e+01 9.28891307e+01 9.19751315e+01\n",
-      "  9.02851072e+01 8.73960156e+01 8.32237965e+01 7.92911970e+01\n",
-      "  8.86093280e+01 9.13342176e+01 1.03175796e+02 1.16841839e+02\n",
-      "  1.27127503e+02]\n",
-      " [9.34167495e+01 9.34158737e+01 9.34141264e+01 9.34106405e+01\n",
-      "  9.34036871e+01 9.33898207e+01 9.33621837e+01 9.33071601e+01\n",
-      "  9.31978477e+01 9.29816175e+01 9.25575678e+01 9.17402218e+01\n",
-      "  9.02188031e+01 8.75818825e+01 8.36566798e+01 7.96297636e+01\n",
-      "  8.00497776e+01 1.18383169e+02 1.01478438e+02 1.15116378e+02\n",
-      "  1.25896162e+02]\n",
-      " [9.35852256e+01 9.35844288e+01 9.35828392e+01 9.35796680e+01\n",
-      "  9.35733420e+01 9.35607263e+01 9.35355794e+01 9.34855027e+01\n",
-      "  9.33859767e+01 9.31889401e+01 9.28018841e+01 9.20533332e+01\n",
-      "  9.06504744e+01 8.81847212e+01 8.44000755e+01 8.01844551e+01\n",
-      "  8.08931317e+01 8.97527647e+01 1.00248456e+02 1.13363357e+02\n",
-      "  1.24778323e+02]]\n",
-      "average_val_scores:  [[1.69841283e+01 1.69841453e+01 1.69841790e+01 1.69842466e+01\n",
-      "  1.69843820e+01 1.69846546e+01 1.69852085e+01 1.69863527e+01\n",
-      "  1.69887890e+01 1.69942430e+01 1.70073583e+01 1.70414861e+01\n",
-      "  1.71350562e+01 1.73878161e+01 1.80031755e+01 1.92639495e+01\n",
-      "  2.14149401e+01 2.44934074e+01 6.60059287e+01 3.21176934e+01\n",
-      "  3.67119744e+01]\n",
-      " [7.85937389e+00 7.85305279e+00 7.84070353e+00 7.81709015e+00\n",
-      "  7.77390414e+00 7.70218348e+00 7.60806271e+00 7.56107135e+00\n",
-      "  7.75679849e+00 8.42104223e+00 9.48696748e+00 1.06081833e+01\n",
-      "  1.15507445e+01 1.23277922e+01 1.31507252e+01 1.44223948e+01\n",
-      "  1.65976499e+01 1.98350699e+01 2.38896343e+01 2.94823684e+01\n",
-      "  3.38058003e+01]\n",
-      " [4.94991503e+03 1.89988251e+03 2.08134608e+03 1.35335497e+03\n",
-      "  1.20417430e+03 2.48785856e+05 6.50094731e+02 2.67431140e+03\n",
-      "  3.87612972e+02 2.34488265e+02 1.35217553e+02 4.38100880e+01\n",
-      "  2.22862605e+01 1.86759009e+01 1.88304867e+01 2.05418767e+01\n",
-      "  2.33993291e+01 2.77015242e+01 3.54006498e+01 4.45188348e+01\n",
-      "  5.89499028e+01]\n",
-      " [8.21829424e+05 7.17170907e+05 4.12104226e+05 4.16485446e+05\n",
-      "  1.55825222e+07 8.78342844e+05 9.83654626e+04 4.20400559e+04\n",
-      "  1.56244837e+04 7.01604006e+03 6.85690368e+03 8.22622574e+02\n",
-      "  2.30550200e+02 1.27163936e+02 8.74789787e+01 7.59601643e+01\n",
-      "  1.08310201e+02 8.90789724e+01 1.02911432e+02 1.16026203e+02\n",
-      "  1.26081807e+02]\n",
-      " [2.80375049e+08 8.70545512e+07 2.03864593e+07 5.71232809e+06\n",
-      "  1.53577087e+06 4.42802649e+05 1.40884097e+05 9.24867179e+04\n",
-      "  1.81170435e+04 7.09126398e+03 3.23883736e+03 1.56137510e+03\n",
-      "  7.71827749e+02 3.92453580e+02 2.16998235e+02 1.47174600e+02\n",
-      "  1.29165405e+02 1.29418485e+02 1.33599873e+02 1.36795977e+02\n",
-      "  1.38718563e+02]\n",
-      " [4.13371687e+06 2.07175228e+06 1.03832195e+06 5.20379871e+05\n",
-      "  2.60793927e+05 1.30692793e+05 6.54878200e+04 3.28080295e+04\n",
-      "  1.64295547e+04 8.22131202e+03 4.10833409e+03 2.04877227e+03\n",
-      "  1.02025479e+03 5.12209162e+02 2.71079128e+02 1.69658171e+02\n",
-      "  1.37876881e+02 1.33609573e+02 1.35834539e+02 1.38069238e+02\n",
-      "  1.39448160e+02]\n",
-      " [4.92535495e+06 2.46850900e+06 1.23716917e+06 6.20037377e+05\n",
-      "  3.10738812e+05 1.55722344e+05 7.80301168e+04 3.90918603e+04\n",
-      "  1.95766949e+04 9.79632771e+03 4.89530809e+03 2.44055622e+03\n",
-      "  1.21349779e+03 6.05072197e+02 3.12481334e+02 1.84824498e+02\n",
-      "  1.41318372e+02 1.33325127e+02 1.35053078e+02 1.37495897e+02\n",
-      "  1.39086668e+02]\n",
-      " [5.34743239e+06 2.68004978e+06 1.34319167e+06 6.73175454e+05\n",
-      "  3.37371892e+05 1.69071455e+05 8.47214660e+04 4.24464114e+04\n",
-      "  2.12588598e+04 1.06402626e+04 5.31902831e+03 2.65345589e+03\n",
-      "  1.32029275e+03 6.57800915e+02 3.36692353e+02 1.93741416e+02\n",
-      "  1.43347043e+02 1.33330200e+02 1.34811506e+02 1.37382895e+02\n",
-      "  1.39101265e+02]\n",
-      " [6.18827864e+06 3.10147120e+06 1.55440272e+06 7.79031754e+05\n",
-      "  3.90425733e+05 1.95661374e+05 9.80480004e+04 4.91254955e+04\n",
-      "  2.46063046e+04 1.23178878e+04 6.15967105e+03 3.07442857e+03\n",
-      "  1.53055308e+03 7.61721852e+02 3.86118571e+02 2.14468947e+02\n",
-      "  1.49462807e+02 1.33799683e+02 1.34090999e+02 1.36707449e+02\n",
-      "  1.38606321e+02]\n",
-      " [6.61394155e+06 3.31480946e+06 1.66132657e+06 8.32622064e+05\n",
-      "  4.17285952e+05 2.09124810e+05 1.04797135e+05 5.25094990e+04\n",
-      "  2.63037285e+04 1.31699821e+04 6.58802088e+03 3.29024796e+03\n",
-      "  1.63953662e+03 8.16533977e+02 4.12756444e+02 2.25927608e+02\n",
-      "  1.53136618e+02 1.34323189e+02 1.33792088e+02 1.36348814e+02\n",
-      "  1.38312432e+02]\n",
-      " [7.16699658e+06 3.59199429e+06 1.80024879e+06 9.02248825e+05\n",
-      "  4.52182713e+05 2.26615339e+05 1.13563880e+05 5.69039926e+04\n",
-      "  2.85069005e+04 1.42748810e+04 7.14245806e+03 3.56875639e+03\n",
-      "  1.77965586e+03 8.87056311e+02 4.47770247e+02 2.41928354e+02\n",
-      "  1.58798996e+02 1.35596582e+02 1.33904648e+02 1.36360159e+02\n",
-      "  1.38408221e+02]]\n",
-      "average_perf_scores:  [[1.33600956e+07 6.69562476e+06 3.35547707e+06 1.68143775e+06\n",
-      "  8.42430727e+05 4.21931354e+05 2.11182904e+05 1.05559400e+05\n",
-      "  5.26240869e+04 2.60971987e+04 1.28092632e+04 6.16270607e+03\n",
-      "  2.85508211e+03 1.23557635e+03 4.77206276e+02 1.62316414e+02\n",
-      "  6.90154592e+01 4.76336057e+01 2.00326762e+02 4.07854429e+01\n",
-      "  4.33643469e+01]\n",
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-      "  6.76498899e+04 3.54461253e+04 2.06691330e+04 1.51244951e+04\n",
-      "  1.22369276e+04 9.35733496e+03 6.40911455e+03 3.94009375e+03\n",
-      "  2.20567228e+03 1.12669856e+03 5.11555006e+02 1.95129823e+02\n",
-      "  7.24766838e+01 4.96137695e+01 4.41490465e+01 4.54105893e+01\n",
-      "  3.99001722e+01]\n",
-      " [9.55297375e+07 2.63419101e+07 1.09322506e+07 9.18930651e+06\n",
-      "  2.70747192e+06 1.13237909e+08 3.32095269e+05 3.10861486e+05\n",
-      "  4.19898558e+04 1.54505705e+04 2.91660636e+03 6.88049890e+02\n",
-      "  2.47457467e+02 1.39083425e+02 9.43441497e+01 7.70732800e+01\n",
-      "  6.87657383e+01 5.91119474e+01 4.97671198e+01 5.04300452e+01\n",
-      "  6.09575955e+01]\n",
-      " [5.39588261e+08 4.27957370e+08 1.56856784e+08 5.39062156e+07\n",
-      "  3.57453472e+07 1.33573132e+07 2.72762780e+06 7.82127045e+05\n",
-      "  1.76977489e+05 5.29199457e+04 2.83132912e+04 2.05816924e+03\n",
-      "  6.47103665e+02 2.83022019e+02 1.43454219e+02 9.03352903e+01\n",
-      "  1.12065429e+02 8.31730702e+01 9.94357795e+01 1.14842624e+02\n",
-      "  1.26061597e+02]\n",
-      " [5.15453440e+09 1.09430450e+09 2.36726392e+08 8.18770676e+07\n",
-      "  9.14434105e+06 1.64004014e+06 4.13464737e+05 2.63488379e+05\n",
-      "  3.41652432e+04 1.20547615e+04 5.27625022e+03 2.49840883e+03\n",
-      "  1.19965527e+03 5.67916346e+02 2.66641977e+02 1.39604753e+02\n",
-      "  1.05645346e+02 1.08159688e+02 1.19895089e+02 1.28727895e+02\n",
-      "  1.34233324e+02]\n",
-      " [6.09189358e+06 3.05313009e+06 1.53014063e+06 7.66837761e+05\n",
-      "  3.84280128e+05 1.92547161e+05 9.64531185e+04 4.82921545e+04\n",
-      "  2.41547794e+04 1.20580002e+04 5.99636091e+03 2.96050509e+03\n",
-      "  1.44307473e+03 6.90057947e+02 3.25660603e+02 1.64061371e+02\n",
-      "  1.12049084e+02 1.13178006e+02 1.19303929e+02 1.28089292e+02\n",
-      "  1.33702146e+02]\n",
-      " [7.11112910e+06 3.56395710e+06 1.78615977e+06 8.95150460e+05\n",
-      "  4.48587982e+05 2.24776598e+05 1.12605250e+05 5.63865205e+04\n",
-      "  2.82106469e+04 1.40897270e+04 7.01342708e+03 3.46868570e+03\n",
-      "  1.69558816e+03 8.13444823e+02 3.83031083e+02 1.87361038e+02\n",
-      "  1.67245318e+02 1.10518883e+02 1.17479366e+02 1.26546717e+02\n",
-      "  1.32619365e+02]\n",
-      " [9.39919731e+06 4.71069499e+06 2.36087749e+06 1.18317896e+06\n",
-      "  5.92931510e+05 2.97107053e+05 1.48843671e+05 7.45360762e+04\n",
-      "  3.72942954e+04 1.86296606e+04 9.27611125e+03 4.59004049e+03\n",
-      "  2.24489691e+03 1.07590653e+03 5.01123635e+02 2.31410380e+02\n",
-      "  1.25130078e+02 1.03617810e+02 1.13064335e+02 1.23286751e+02\n",
-      "  1.30360296e+02]\n",
-      " [1.05960170e+07 5.31053213e+06 2.66151459e+06 1.33386083e+06\n",
-      "  6.68457725e+05 3.34966209e+05 1.67824569e+05 8.40554132e+04\n",
-      "  4.20715808e+04 2.10302157e+04 1.04853338e+04 5.20190443e+03\n",
-      "  2.55686348e+03 1.23670567e+03 5.84865107e+02 2.74610803e+02\n",
-      "  1.44202156e+02 1.07770245e+02 1.11631349e+02 1.22535119e+02\n",
-      "  1.30583194e+02]\n",
-      " [1.36435585e+07 6.83790725e+06 3.42700175e+06 1.71749946e+06\n",
-      "  8.60718745e+05 4.31311218e+05 2.16097700e+05 1.08235537e+05\n",
-      "  5.41766066e+04 2.70833756e+04 1.35054137e+04 6.70191730e+03\n",
-      "  3.29518031e+03 1.59352962e+03 7.50920751e+02 3.45766772e+02\n",
-      "  1.70168683e+02 2.01869576e+02 1.12716551e+02 1.22651428e+02\n",
-      "  1.30998836e+02]\n",
-      " [1.26218368e+07 6.32584664e+06 3.17037673e+06 1.58889550e+06\n",
-      "  7.96277312e+05 3.99027216e+05 1.99930584e+05 1.00145983e+05\n",
-      "  5.01353915e+04 2.50710729e+04 1.25098520e+04 6.21569477e+03\n",
-      "  3.06378761e+03 1.48907248e+03 7.08809446e+02 3.32879337e+02\n",
-      "  1.70826776e+02 1.15159390e+02 1.10387108e+02 1.20450090e+02\n",
-      "  1.28760963e+02]]\n",
-      "std_train_scores:  [[2.97578042e-01 2.97577120e-01 2.97575281e-01 2.97571612e-01\n",
-      "  2.97564295e-01 2.97549706e-01 2.97520638e-01 2.97462808e-01\n",
-      "  2.97348063e-01 2.97121549e-01 2.96678420e-01 2.95824851e-01\n",
-      "  2.94229378e-01 2.91493636e-01 2.87987133e-01 2.86544885e-01\n",
-      "  2.91038709e-01 3.09332053e-01 1.28623682e+02 4.63290002e-01\n",
-      "  5.03544819e-01]\n",
-      " [2.10125574e-01 2.09851845e-01 2.09313789e-01 2.08270989e-01\n",
-      "  2.06301894e-01 2.02745659e-01 1.96748279e-01 1.87737129e-01\n",
-      "  1.78197998e-01 1.77995103e-01 1.93287224e-01 2.16256371e-01\n",
-      "  2.36569780e-01 2.48968721e-01 2.51533107e-01 2.43956187e-01\n",
-      "  2.27658537e-01 2.12092634e-01 2.38805351e-01 1.37633764e+00\n",
-      "  5.16968103e-01]\n",
-      " [2.31701414e+03 1.09541624e+03 6.47857606e+02 1.81472050e+03\n",
-      "  1.08858234e+03 9.53226954e+04 2.96379594e+02 7.68200492e+02\n",
-      "  1.50379823e+02 1.47410321e+02 4.22968478e+01 1.11527699e+01\n",
-      "  1.87904499e+00 5.83603528e-01 3.67667684e-01 2.93973458e-01\n",
-      "  2.55953775e-01 3.52504386e-01 1.22331596e+00 7.91798368e-01\n",
-      "  8.02192903e-01]\n",
-      " [2.51562747e+04 3.31149203e+04 2.51295043e+04 1.04820762e+04\n",
-      "  3.61882970e+04 2.74249943e+04 1.35757939e+04 2.95403496e+03\n",
-      "  9.67568065e+02 1.49663305e+03 8.30535690e+02 4.10911174e+01\n",
-      "  6.92440798e+00 3.20215006e+00 2.10213236e+00 1.49611731e+00\n",
-      "  4.95758143e+01 1.03585317e+00 9.08814748e-01 9.06464629e-01\n",
-      "  9.38941045e-01]\n",
-      " [2.07296777e+05 8.92420567e+04 3.73923774e+04 2.10626614e+04\n",
-      "  5.56971399e+03 2.13543845e+03 1.04227058e+03 1.78919760e+03\n",
-      "  2.21757861e+02 7.49233887e+01 2.96015039e+01 9.52206438e+00\n",
-      "  3.40118675e+00 2.73333466e+00 2.28066446e+00 4.44978935e+00\n",
-      "  2.66977985e+01 9.77866645e-01 8.76442082e-01 9.29886344e-01\n",
-      "  1.00358231e+00]\n",
-      " [3.85358054e+00 3.85352053e+00 3.85340082e+00 3.85316197e+00\n",
-      "  3.85268550e+00 3.85173518e+00 3.84984048e+00 3.84606579e+00\n",
-      "  3.83855686e+00 3.82366273e+00 3.79428293e+00 3.73691161e+00\n",
-      "  3.62675564e+00 3.42029398e+00 3.04559043e+00 2.42113201e+00\n",
-      "  5.62370832e+00 9.98399215e+00 8.22729308e-01 7.40181189e-01\n",
-      "  7.42022556e-01]\n",
-      " [2.96510001e+00 2.96504126e+00 2.96492403e+00 2.96469015e+00\n",
-      "  2.96422363e+00 2.96329324e+00 2.96143870e+00 2.95774563e+00\n",
-      "  2.95040561e+00 2.93587327e+00 2.90731889e+00 2.85204038e+00\n",
-      "  2.74803314e+00 2.56238009e+00 2.25991561e+00 1.83511194e+00\n",
-      "  1.33400859e+02 8.46900602e+00 1.03232669e+00 1.11625691e+00\n",
-      "  1.20854857e+00]\n",
-      " [3.60230105e+00 3.60225250e+00 3.60215563e+00 3.60196238e+00\n",
-      "  3.60157685e+00 3.60080783e+00 3.59927435e+00 3.59621826e+00\n",
-      "  3.59013478e+00 3.57805271e+00 3.55416433e+00 3.50733502e+00\n",
-      "  3.41696168e+00 3.24714524e+00 2.94104732e+00 2.42888992e+00\n",
-      "  5.60704104e+00 2.86218045e+00 9.22005989e-01 7.85145209e-01\n",
-      "  8.31917126e-01]\n",
-      " [4.05696272e+00 4.05690357e+00 4.05678554e+00 4.05655006e+00\n",
-      "  4.05608027e+00 4.05514309e+00 4.05327397e+00 4.04954764e+00\n",
-      "  4.04212485e+00 4.02736274e+00 3.99809856e+00 3.94044847e+00\n",
-      "  3.82824328e+00 3.61480078e+00 3.22621789e+00 2.58235723e+00\n",
-      "  4.56343582e+01 3.51619561e+00 7.82902232e-01 7.12033045e-01\n",
-      "  8.32789466e-01]\n",
-      " [3.75810804e+00 3.75805474e+00 3.75794840e+00 3.75773623e+00\n",
-      "  3.75731295e+00 3.75646858e+00 3.75478462e+00 3.75142778e+00\n",
-      "  3.74474225e+00 3.73145139e+00 3.70512386e+00 3.65333904e+00\n",
-      "  3.55286559e+00 3.36292154e+00 3.02069441e+00 2.45756403e+00\n",
-      "  2.96424004e+00 2.85067989e+01 6.48495083e-01 6.27853015e-01\n",
-      "  7.24343975e-01]\n",
-      " [2.91853285e+00 2.91849819e+00 2.91842902e+00 2.91829102e+00\n",
-      "  2.91801572e+00 2.91746657e+00 2.91637146e+00 2.91418878e+00\n",
-      "  2.90984305e+00 2.90120891e+00 2.88412556e+00 2.85059595e+00\n",
-      "  2.78578196e+00 2.66387079e+00 2.44457768e+00 2.07562553e+00\n",
-      "  4.85204039e+00 5.36960874e+00 1.41862107e+00 8.67791503e-01\n",
-      "  9.58386299e-01]]\n",
-      "std_val_scores:  [[3.53830893e-01 3.53830015e-01 3.53828264e-01 3.53824766e-01\n",
-      "  3.53817775e-01 3.53803779e-01 3.53775665e-01 3.53718827e-01\n",
-      "  3.53602464e-01 3.53358592e-01 3.52826149e-01 3.51589019e-01\n",
-      "  3.48507212e-01 3.40679499e-01 3.23450052e-01 2.98659885e-01\n",
-      "  2.84710944e-01 3.04992992e-01 1.32009704e+02 4.73116114e-01\n",
-      "  5.81205620e-01]\n",
-      " [7.46127188e-01 7.44981999e-01 7.42698270e-01 7.38146705e-01\n",
-      "  7.29087519e-01 7.11125934e-01 6.75994026e-01 6.10558541e-01\n",
-      "  5.04689878e-01 3.77824754e-01 2.88359870e-01 2.58943366e-01\n",
-      "  2.59342524e-01 2.74076938e-01 2.92314727e-01 2.97436331e-01\n",
-      "  2.71728102e-01 2.40375871e-01 2.79477858e-01 1.27965936e+00\n",
-      "  4.85482794e-01]\n",
-      " [1.76250737e+04 1.99700820e+03 3.87441359e+03 1.46519158e+03\n",
-      "  1.29569110e+03 1.32627083e+06 5.67266420e+02 1.13018963e+04\n",
-      "  3.59934280e+02 3.43535747e+02 2.78193063e+02 4.65590095e+01\n",
-      "  5.09305207e+00 1.46768847e+00 7.66856047e-01 5.77954220e-01\n",
-      "  5.02167116e-01 5.85163831e-01 1.19910490e+00 9.43207765e-01\n",
-      "  9.33853955e-01]\n",
-      " [1.53210830e+06 1.14446553e+06 5.39276446e+05 8.43235381e+05\n",
-      "  8.40398493e+07 3.42758905e+06 2.41124474e+05 5.80594374e+04\n",
-      "  1.45814194e+04 6.89162966e+03 2.45195767e+04 1.63147106e+03\n",
-      "  4.43814631e+01 1.25435952e+01 5.56907772e+00 2.32466567e+00\n",
-      "  5.28965641e+01 1.36695981e+00 1.20200772e+00 1.03991234e+00\n",
-      "  9.88075394e-01]\n",
-      " [6.09887406e+08 1.69112334e+08 3.88949772e+07 9.72309473e+06\n",
-      "  2.45589688e+06 6.16650542e+05 1.54785943e+05 1.17105410e+05\n",
-      "  9.49902091e+03 2.21843511e+03 6.11522371e+02 2.30475150e+02\n",
-      "  1.05488551e+02 4.83799775e+01 2.00569010e+01 6.79349189e+00\n",
-      "  3.21462243e+00 1.22792441e+00 1.07947425e+00 1.03779841e+00\n",
-      "  1.05291455e+00]\n",
-      " [5.24802609e+05 2.63019275e+05 1.31816811e+05 6.60598112e+04\n",
-      "  3.31032429e+04 1.65858328e+04 8.30752015e+03 4.15854024e+03\n",
-      "  2.07913385e+03 1.03698035e+03 5.14702120e+02 2.53010582e+02\n",
-      "  1.21975926e+02 5.65103317e+01 2.40825282e+01 8.65634002e+00\n",
-      "  2.32068402e+00 9.44495836e-01 8.35763930e-01 7.88193328e-01\n",
-      "  7.89398039e-01]\n",
-      " [5.05354319e+05 2.53274928e+05 1.26935955e+05 6.36164751e+04\n",
-      "  3.18815601e+04 1.59764259e+04 8.00497596e+03 4.00978742e+03\n",
-      "  2.00745056e+03 1.00390541e+03 5.00939689e+02 2.48846873e+02\n",
-      "  1.22451211e+02 5.89868265e+01 2.70603279e+01 1.10918139e+01\n",
-      "  3.62724559e+00 1.51838711e+00 1.34579388e+00 1.31352245e+00\n",
-      "  1.32555400e+00]\n",
-      " [5.87407178e+05 2.94397563e+05 1.47544884e+05 7.39441969e+04\n",
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-      "  2.33171811e+03 1.16525416e+03 5.80677053e+02 2.87765427e+02\n",
-      "  1.41076625e+02 6.77277578e+01 3.12216202e+01 1.31372314e+01\n",
-      "  4.32487023e+00 1.47544767e+00 1.20727493e+00 1.09373577e+00\n",
-      "  1.04389953e+00]\n",
-      " [7.72194940e+05 3.87008291e+05 1.93957659e+05 9.72031477e+04\n",
-      "  4.87110222e+04 2.44073889e+04 1.22267203e+04 6.12192874e+03\n",
-      "  3.06229321e+03 1.52885888e+03 7.60352296e+02 3.75246388e+02\n",
-      "  1.82348354e+02 8.58833157e+01 3.79979974e+01 1.50496398e+01\n",
-      "  5.19410977e+00 1.91168968e+00 1.30673151e+00 1.12243368e+00\n",
-      "  1.08224985e+00]\n",
-      " [8.12520920e+05 4.07221836e+05 2.04091110e+05 1.02284583e+05\n",
-      "  5.12604519e+04 2.56878093e+04 1.28711285e+04 6.44757388e+03\n",
-      "  3.22817478e+03 1.61466178e+03 8.06006405e+02 4.00749466e+02\n",
-      "  1.97690772e+02 9.59799819e+01 4.49828564e+01 1.91857982e+01\n",
-      "  6.28339179e+00 1.39571333e+00 1.22529131e+00 1.10962668e+00\n",
-      "  9.94367862e-01]\n",
-      " [1.04140777e+06 5.21936431e+05 2.61584028e+05 1.31098728e+05\n",
-      "  6.57011618e+04 3.29247373e+04 1.64976134e+04 8.26455181e+03\n",
-      "  4.13825267e+03 2.07021621e+03 1.03376495e+03 5.14346517e+02\n",
-      "  2.54071350e+02 1.23646988e+02 5.81471693e+01 2.49850329e+01\n",
-      "  8.55555299e+00 1.94636291e+00 1.37503421e+00 1.33562445e+00\n",
-      "  1.24402195e+00]]\n",
-      "std_perf_scores:  [[2.48931249e+06 1.24760728e+06 6.25280479e+05 3.13378237e+05\n",
-      "  1.57056826e+05 7.87105512e+04 3.94444405e+04 1.97648504e+04\n",
-      "  9.90185516e+03 4.95896785e+03 2.48226544e+03 1.24208359e+03\n",
-      "  6.22366981e+02 3.14338869e+02 1.62179451e+02 7.79573507e+01\n",
-      "  2.56173912e+01 1.06486481e+01 4.73297124e+02 8.51842051e+00\n",
-      "  8.22499386e+00]\n",
-      " [5.01641603e+05 2.51235198e+05 1.25931724e+05 6.34979226e+04\n",
-      "  3.28563114e+04 1.85421800e+04 1.22652220e+04 7.88963304e+03\n",
-      "  4.77146388e+03 2.77915469e+03 1.62668002e+03 9.40649055e+02\n",
-      "  5.30871674e+02 2.94492458e+02 1.62267929e+02 8.49038443e+01\n",
-      "  3.08529894e+01 1.30601340e+01 8.85510592e+00 9.90557460e+00\n",
-      "  6.68761844e+00]\n",
-      " [3.66430754e+08 5.74161356e+07 1.83486711e+07 3.42480432e+07\n",
-      "  7.95457651e+06 6.06707199e+08 6.18911152e+05 8.99497533e+05\n",
-      "  5.16058373e+04 2.65496634e+04 3.87119448e+03 5.35279444e+02\n",
-      "  7.79815991e+01 3.78606777e+01 2.87115435e+01 2.35036265e+01\n",
-      "  1.63918955e+01 1.08508038e+01 9.84911198e+00 1.14650945e+01\n",
-      "  1.24871119e+01]\n",
-      " [1.04214168e+09 1.11731132e+09 4.03585556e+08 7.98257620e+07\n",
-      "  8.40348601e+07 3.05028437e+07 5.41119694e+06 8.34144730e+05\n",
-      "  2.26058427e+05 8.20491051e+04 5.43260339e+04 1.34514632e+03\n",
-      "  2.14851453e+02 9.15554217e+01 3.90384732e+01 1.46332754e+01\n",
-      "  9.00678151e+01 1.10030220e+01 1.11195580e+01 1.06492344e+01\n",
-      "  1.03193622e+01]\n",
-      " [2.24088449e+10 4.53786311e+09 9.31537652e+08 3.54813812e+08\n",
-      "  2.68545927e+07 3.01086391e+06 5.69909200e+05 5.15586649e+05\n",
-      "  2.42463033e+04 5.29557280e+03 1.85470934e+03 8.28695442e+02\n",
-      "  3.93675326e+02 1.82277229e+02 7.95004389e+01 3.30037255e+01\n",
-      "  1.93408552e+01 1.37111465e+01 1.21417970e+01 1.11792655e+01\n",
-      "  1.06997127e+01]\n",
-      " [2.28812976e+06 1.14676100e+06 5.74721545e+05 2.88022677e+05\n",
-      "  1.44332868e+05 7.23173773e+04 3.62241479e+04 1.81347120e+04\n",
-      "  9.06857650e+03 4.52485992e+03 2.24782599e+03 1.10700378e+03\n",
-      "  5.35897282e+02 2.50571732e+02 1.08548593e+02 3.94302810e+01\n",
-      "  1.21922522e+01 1.99163423e+01 7.34512243e+00 6.73664286e+00\n",
-      "  6.64413088e+00]\n",
-      " [3.57190580e+06 1.79016037e+06 8.97172314e+05 4.49618102e+05\n",
-      "  2.25309651e+05 1.12889133e+05 5.65454325e+04 2.83067437e+04\n",
-      "  1.41539823e+04 7.06101385e+03 3.50652853e+03 1.72586976e+03\n",
-      "  8.34905748e+02 3.90897183e+02 1.72203935e+02 6.76947112e+01\n",
-      "  2.68458217e+02 1.49375830e+01 1.29120025e+01 1.24894486e+01\n",
-      "  1.21426131e+01]\n",
-      " [4.21751715e+06 2.11371408e+06 1.05931485e+06 5.30863417e+05\n",
-      "  2.66010320e+05 1.33269353e+05 6.67413240e+04 3.33984231e+04\n",
-      "  1.66875811e+04 8.31270492e+03 4.11607831e+03 2.01423908e+03\n",
-      "  9.63549008e+02 4.41771091e+02 1.88030727e+02 7.19783046e+01\n",
-      "  2.66958128e+01 1.28985955e+01 9.62338118e+00 8.83955668e+00\n",
-      "  8.61928715e+00]\n",
-      " [3.94079853e+06 1.97506388e+06 9.89862771e+05 4.96092553e+05\n",
-      "  2.48621224e+05 1.24591757e+05 6.24297762e+04 3.12749960e+04\n",
-      "  1.56606393e+04 7.83496487e+03 3.91291667e+03 1.94738238e+03\n",
-      "  9.62524613e+02 4.69246903e+02 2.22219142e+02 9.82032220e+01\n",
-      "  3.64588463e+01 1.38142864e+01 1.05694912e+01 1.00937701e+01\n",
-      "  9.86648345e+00]\n",
-      " [5.65378739e+06 2.83357226e+06 1.42011645e+06 7.11710442e+05\n",
-      "  3.56666403e+05 1.78722877e+05 8.95398831e+04 4.48425624e+04\n",
-      "  2.24409503e+04 1.12137744e+04 5.58730058e+03 2.76823804e+03\n",
-      "  1.35695061e+03 6.52401309e+02 3.03525605e+02 1.33703046e+02\n",
-      "  5.22810631e+01 2.08692163e+02 1.05659852e+01 9.12407226e+00\n",
-      "  8.55071239e+00]\n",
-      " [5.08401150e+06 2.54802026e+06 1.27701383e+06 6.40001627e+05\n",
-      "  3.20739248e+05 1.60729023e+05 8.05339481e+04 4.03412151e+04\n",
-      "  2.01971595e+04 1.01012735e+04 5.04145739e+03 2.50576074e+03\n",
-      "  1.23531270e+03 5.99313029e+02 2.81760879e+02 1.24399144e+02\n",
-      "  5.01442497e+01 2.48923664e+01 1.17405866e+01 1.07635945e+01\n",
-      "  1.00900206e+01]]\n",
-      "best_val_perf:  7.561071350024525\n",
-      "best_params_index:  (array([1]), array([7]))\n",
-      "best_params_out:  [{'height': 1, 'base_kernel': 'subtree'}]\n",
-      "best_params_in:  [{'alpha': 0.12589254117941676}]\n",
-      "best_val_std:  0.6105585412387886\n",
-      "final_performance:  15124.495121439606\n",
-      "final_confidence:  7889.633042663907\n",
-      "train_performance:  6.051189370764022\n",
-      "train_std:  0.1877371294126266\n",
-      "run time to calculate gram matrix:  0.8528649806976318\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fa65a76d6a0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fa65a704a20>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fa65a704b38>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fa65a6cf240>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fa65a67e3c8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fa65a683940>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fa65a6d1dd8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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ZHZP0rKR7zaxPkks6KulxSXL398xsWNL7kuYlPeHu56IpHUArmbvHXYO+at2+3jbHXQbQMqcf26juofj3Jpn0ov7XT1uY9zKDE4hB99BE6uZgEBZATNI2rEpYADHqHprQx/+WjntJCAsgZiueG0/FVomEBYBQCAsgAXp3j6t393iiWxeEBZAgvbvHE9uHQVgACbPiuXF9NHxH3GVchrAAEuhrD83oyAsbdeSF5AytEhYAQmH7QiChVu6qTAc//eYadW89HHM1tCyAxOveejgRd6oSFkAKJGE9DMICSInCaDnWDk/CAkiRlbsmYhslISwAhMJoCJAy1VGSs4Pr1TEy2bKfS8sCSKmOkcmWTg0nLIAUW/HcuAbf/6wlP4uwAFJuZO3ylnR6EhYAQqGDE8iAVkwNp2UBZEj31sORXY4QFkDGrNw1oTPbm7/NAGEBZFDXvpLODq5v6vckLICM6hiZ1JntG5rWyiAsAITCaAiQYV37SpKaMzWclgWQAx0jkzr95pqGvgdhAeREo8OqhAWQIyt3Tej0m2vqamUQFgBCISyAnOneeljdWw/rsx8s7ZKEsAByavlLEzp/3bWh32/uHmE5IYsw+0zS3yT9Oe5aWuwGcc55kORz/pq7Lw/zxkSEhSSZ2X5374+7jlbinPMhK+fMZQiAUAgLAKEkKSxejruAGHDO+ZCJc05MnwWAZEtSywJAghEWAEIhLACEQlgACIWwABDK/wOyNv1vJXnNTQAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fa65a6d1748>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fa65a67acf8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fa65a67bef0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fa65a67ceb8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import numpy as np\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.model_selection_precomputed import model_selection_for_precomputed_kernel\n",
-    "from pygraph.kernels.weisfeilerLehmanKernel import weisfeilerlehmankernel\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "estimator = weisfeilerlehmankernel\n",
-    "param_grid_precomputed = {'height': [0,1,2,3,4,5,6,7,8,9,10], 'base_kernel': ['subtree']}\n",
-    "param_grid = {\"alpha\": np.logspace(-2, 2, num = 10, base = 10)}\n",
-    "\n",
-    "model_selection_for_precomputed_kernel(datafile, estimator, param_grid_precomputed, param_grid, 'regression')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Automatically created module for IPython interactive environment\n",
-      "param_list_precomputed:  [{'base_kernel': 'subtree', 'height': 0}, {'base_kernel': 'subtree', 'height': 1}, {'base_kernel': 'subtree', 'height': 2}, {'base_kernel': 'subtree', 'height': 3}, {'base_kernel': 'subtree', 'height': 4}, {'base_kernel': 'subtree', 'height': 5}, {'base_kernel': 'subtree', 'height': 6}, {'base_kernel': 'subtree', 'height': 7}, {'base_kernel': 'subtree', 'height': 8}, {'base_kernel': 'subtree', 'height': 9}, {'base_kernel': 'subtree', 'height': 10}]\n",
-      "param_list:  [{'alpha': 1e-05}, {'alpha': 3.1622776601683795e-05}, {'alpha': 0.0001}, {'alpha': 0.00031622776601683794}, {'alpha': 0.001}, {'alpha': 0.0031622776601683794}, {'alpha': 0.01}, {'alpha': 0.03162277660168379}, {'alpha': 0.1}, {'alpha': 0.31622776601683794}, {'alpha': 1.0}, {'alpha': 3.1622776601683795}, {'alpha': 10.0}, {'alpha': 31.622776601683793}, {'alpha': 100.0}, {'alpha': 316.22776601683796}, {'alpha': 1000.0}, {'alpha': 3162.2776601683795}, {'alpha': 10000.0}, {'alpha': 31622.776601683792}, {'alpha': 100000.0}]\n",
-      "params_out:  {'base_kernel': 'subtree', 'height': 0}\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 0.3903679847717285 seconds ---\n",
-      "gram matrix:  [[  5.   6.   4. ...  20.  20.  20.]\n",
-      " [  6.   8.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.   5. ...  21.  21.  21.]\n",
-      " ...\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]\n",
-      " [ 20.  20.  21. ... 101. 101. 101.]]\n",
-      "params_out:  {'base_kernel': 'subtree', 'height': 1}\n",
-      "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 0.843524694442749 seconds ---\n",
-      "gram matrix:  [[ 10.  10.   4. ...  20.  20.  20.]\n",
-      " [ 10.  16.   4. ...  20.  20.  20.]\n",
-      " [  4.   4.  10. ...  22.  22.  24.]\n",
-      " ...\n",
-      " [ 20.  20.  22. ... 130. 130. 122.]\n",
-      " [ 20.  20.  22. ... 130. 130. 122.]\n",
-      " [ 20.  20.  24. ... 122. 122. 154.]]\n",
-      "params_out:  {'base_kernel': 'subtree', 'height': 2}\n"
-     ]
-    },
-    {
-     "ename": "KeyboardInterrupt",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-45-a7af9ee5c30f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     56\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mparams_out\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mparam_list_precomputed\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     57\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'params_out: '\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams_out\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 58\u001b[0;31m     \u001b[0mKmatrix\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcurrent_run_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mestimator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdataset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mparams_out\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     59\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'gram matrix: '\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mKmatrix\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     60\u001b[0m     \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/weisfeilerLehmanKernel.py\u001b[0m in \u001b[0;36mweisfeilerlehmankernel\u001b[0;34m(node_label, edge_label, height, base_kernel, *args)\u001b[0m\n\u001b[1;32m     52\u001b[0m     \u001b[0;31m# for WL subtree kernel\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     53\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mbase_kernel\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'subtree'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 54\u001b[0;31m         \u001b[0mKmatrix\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_wl_subtreekernel_do\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnode_label\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge_label\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheight\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     55\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     56\u001b[0m     \u001b[0;31m# for WL shortest path kernel\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/weisfeilerLehmanKernel.py\u001b[0m in \u001b[0;36m_wl_subtreekernel_do\u001b[0;34m(Gn, node_label, edge_label, height)\u001b[0m\n\u001b[1;32m    121\u001b[0m             \u001b[0mvector1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmatrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mall_num_of_each_label\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mlabel\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mall_num_of_each_label\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mlabel\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    122\u001b[0m             \u001b[0mvector2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmatrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mall_num_of_each_label\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mlabel\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mall_num_of_each_label\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mlabel\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 123\u001b[0;31m             \u001b[0mKmatrix\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvector1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvector2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    124\u001b[0m             \u001b[0mKmatrix\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKmatrix\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    125\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f04f99a2400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f04fa3ec240>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from sklearn.datasets import load_iris\n",
-    "from matplotlib import pyplot as plt\n",
-    "from sklearn.kernel_ridge import KernelRidge\n",
-    "from sklearn.svm import SVC\n",
-    "from sklearn.metrics import accuracy_score, mean_squared_error\n",
-    "from sklearn.model_selection import GridSearchCV, cross_val_score, KFold, train_test_split, ParameterGrid\n",
-    "import numpy as np\n",
-    "\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "from pygraph.kernels.weisfeilerLehmanKernel import weisfeilerlehmankernel\n",
-    "\n",
-    "print(__doc__)\n",
-    "\n",
-    "\n",
-    "\n",
-    "# Load the dataset\n",
-    "iris = load_iris()\n",
-    "X_iris = iris.data\n",
-    "y_iris = iris.target\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "dataset, y = loadDataset(datafile)\n",
-    "\n",
-    "# Set up possible values of parameters to optimize over\n",
-    "p_grid = {\"C\": [1, 10, 100],\n",
-    "          \"gamma\": [.01, .1]}\n",
-    "\n",
-    "estimator = weisfeilerlehmankernel\n",
-    "param_grid_precomputed = {'height': [0,1,2,3,4,5,6,7,8,9,10], 'base_kernel': ['subtree']} # param grid for precomputed kernel gram matrix\n",
-    "# param_grid = {\"C\": [1, 10, 100]}\n",
-    "param_grid = {\"alpha\": np.logspace(-5, 5, num = 21, base = 10)}\n",
-    "NUM_TRIALS = 30 # Number of random trials\n",
-    "\n",
-    "\n",
-    "# We will use a Support Vector Classifier with \"rbf\" kernel\n",
-    "# svm = SVC(kernel=\"precomputed\")\n",
-    "\n",
-    "best_params = []\n",
-    "gram_matrices = []\n",
-    "run_time = []\n",
-    "\n",
-    "param_list_precomputed = list(ParameterGrid(param_grid_precomputed))\n",
-    "print('param_list_precomputed: ', param_list_precomputed)\n",
-    "param_list = list(ParameterGrid(param_grid))\n",
-    "print('param_list: ', param_list)\n",
-    "\n",
-    "# Arrays to store scores\n",
-    "train_pref = np.zeros((NUM_TRIALS, len(param_list_precomputed), len(param_list)))\n",
-    "val_pref = np.zeros((NUM_TRIALS, len(param_list_precomputed), len(param_list)))\n",
-    "test_pref = np.zeros((NUM_TRIALS, len(param_list_precomputed), len(param_list)))\n",
-    "\n",
-    "# calculate all gram matrices\n",
-    "for params_out in param_list_precomputed:\n",
-    "    print('params_out: ', params_out)\n",
-    "    Kmatrix, current_run_time = estimator(dataset, **params_out)\n",
-    "    print('gram matrix: ', Kmatrix)\n",
-    "    import matplotlib.pyplot as plt\n",
-    "    plt.matshow(Kmatrix)\n",
-    "    gram_matrices.append(Kmatrix)\n",
-    "    run_time.append(current_run_time)\n",
-    "\n",
-    "# Loop for each trial\n",
-    "for trial in range(NUM_TRIALS): # Test set level\n",
-    "    print()\n",
-    "    print('trial: ', trial)\n",
-    "    \n",
-    "    for index_out, params_out in enumerate(param_list_precomputed):\n",
-    "        print()\n",
-    "        print('index_out: ', index_out)  \n",
-    "        print('params_out: ', params_out)    \n",
-    "        X_app,X_test,y_app,y_test = train_test_split(gram_matrices[index_out], y, test_size=0.1)\n",
-    "        split_index_app = [y.index(y_i) for y_i in y_app if y_i in y]\n",
-    "        split_index_test = [y.index(y_i) for y_i in y_test if y_i in y]\n",
-    "        X_app = X_app[:,split_index_app]\n",
-    "        X_test = X_test[:,split_index_app] \n",
-    "        y_app = np.array(y_app)\n",
-    "        y_test = np.array(y_test)\n",
-    "        print('split_index_app: ', split_index_app)\n",
-    "        print('split_index_test: ', split_index_test)\n",
-    "        print('X_app: ', X_app)\n",
-    "        print('y_app: ', y_app)\n",
-    "        print('X_app_shape: ', X_app.shape)\n",
-    "\n",
-    "        for index_in, params_in in enumerate(param_list):\n",
-    "            print()\n",
-    "            print('params_in: ', params_in)\n",
-    "            inner_cv = KFold(n_splits=10, shuffle=True, random_state=trial)\n",
-    "            KR = KernelRidge(kernel = 'precomputed', **params_in)\n",
-    "            current_train_perf = []\n",
-    "            current_valid_perf = []\n",
-    "            current_test_perf = []\n",
-    "#             print('split_y_app: ', list(inner_cv.split(y_app)))\n",
-    "            \n",
-    "            for train_index, valid_index in inner_cv.split(X_app): # validation set level\n",
-    "                print()\n",
-    "                print('train_index: ', train_index)\n",
-    "                print('train_index_shape: ', train_index.shape)\n",
-    "                print('valid_index: ', valid_index)\n",
-    "                print('valid_index_shape: ', valid_index.shape)\n",
-    "                KR.fit(X_app[train_index,:][:,train_index], y_app[train_index])\n",
-    "                \n",
-    "                # predict on the train and test set\n",
-    "                y_pred_train = KR.predict(X_app[train_index,:][:,train_index])\n",
-    "                y_pred_valid = KR.predict(X_app[valid_index,:][:,train_index])\n",
-    "                y_pred_test = KR.predict(X_test[:,train_index])\n",
-    "\n",
-    "                # root mean squared errors\n",
-    "                current_train_perf.append(np.sqrt(mean_squared_error(y_app[train_index], y_pred_train)))\n",
-    "                current_valid_perf.append(np.sqrt(mean_squared_error(y_app[valid_index], y_pred_valid)))\n",
-    "                current_test_perf.append(np.sqrt(mean_squared_error(y_test, y_pred_test)))\n",
-    "                print('y_test: ', y_test)\n",
-    "                print('y_pred_test: ', y_pred_test)\n",
-    "                \n",
-    "            print('current_train_perf: ', current_train_perf)\n",
-    "            print('current_valid_perf: ', current_valid_perf)\n",
-    "            print('current_test_perf: ', current_test_perf)\n",
-    "            \n",
-    "            train_pref[trial][index_out][index_in] = np.mean(current_train_perf)\n",
-    "            val_pref[trial][index_out][index_in] = np.mean(current_valid_perf)\n",
-    "            test_pref[trial][index_out][index_in] = np.mean(current_test_perf)\n",
-    "            \n",
-    "print('train_pref: ', train_pref)\n",
-    "print('val_pref: ', val_pref)\n",
-    "print('test_pref: ', test_pref)\n",
-    "\n",
-    "average_train_scores = np.mean(train_pref, axis=0)\n",
-    "average_val_scores = np.mean(val_pref, axis=0)\n",
-    "average_perf_scores = np.mean(test_pref, axis=0)\n",
-    "std_train_scores = np.std(train_pref, axis=0, ddof=1) # sample std is used here\n",
-    "std_val_scores = np.std(val_pref, axis=0, ddof=1)\n",
-    "std_perf_scores = np.std(test_pref, axis=0, ddof=1)\n",
-    "print('average_train_scores: ', average_train_scores)\n",
-    "print('average_val_scores: ', average_val_scores)\n",
-    "print('average_perf_scores: ', average_perf_scores)\n",
-    "print('std_train_scores: ', std_train_scores)\n",
-    "print('std_val_scores: ', std_val_scores)\n",
-    "print('std_perf_scores: ', std_perf_scores)\n",
-    "best_val_perf = np.amin(average_val_scores)\n",
-    "print('best_val_perf: ', best_val_perf)\n",
-    "best_params_index = np.where(average_val_scores == best_val_perf)\n",
-    "best_params_out = [param_list_precomputed[i] for i in best_params_index[0]]\n",
-    "best_params_in = [param_list[i] for i in best_params_index[1]]\n",
-    "print('best_params_index: ', best_params_index)\n",
-    "print('best_params_out: ', best_params_out)\n",
-    "print('best_params_in: ', best_params_in)\n",
-    "# below: only find one performance; muitiple pref might exist\n",
-    "best_val_std = std_val_scores[best_params_index[0][0]][best_params_index[1][0]]\n",
-    "print('best_val_std: ', best_val_std)\n",
-    "\n",
-    "final_performance = average_perf_scores[best_params_index[0][0]][best_params_index[1][0]]\n",
-    "final_confidence = std_perf_scores[best_params_index[0][0]][best_params_index[1][0]]\n",
-    "print('final_performance: ', final_performance)\n",
-    "print('final_confidence: ', final_confidence)\n",
-    "train_performance = average_train_scores[best_params_index[0][0]][best_params_index[1][0]]\n",
-    "train_std = std_train_scores[best_params_index[0][0]][best_params_index[1][0]]\n",
-    "print('train_performance: ', train_performance)\n",
-    "print('train_std: ', train_std)\n",
-    "\n",
-    "best_run_time = run_time[best_params_index[0][0]]\n",
-    "print('run_time: ', run_time)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[{'o1': 1, 'o2': 2}, {'o1': 3, 'o2': 4}]\n",
-      "[{'i2': 6, 'i1': 5}, {'i2': 8, 'i1': 7}, {'i2': 10, 'i1': 9}]\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "[({'o1': 1, 'o2': 2}, {'o1': 3, 'o2': 4}),\n",
-       " ({'o1': 3, 'o2': 4}, {'o1': 1, 'o2': 2})]"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "x = [ {'o1':1,'o2':2},{'o1':3,'o2':4}]\n",
-    "print(x)\n",
-    "y = [ {'i1':5,'i2':6},{'i1':7,'i2':8},{'i1':9,'i2':10}]\n",
-    "print(y)\n",
-    "from itertools import permutations\n",
-    "[item for item in permutations(x)]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Automatically created module for IPython interactive environment\n",
-      "\n",
-      "0\n",
-      "{'std_score_time': array([3.69876958e-05, 1.59321777e-05, 2.74488935e-05, 1.14532461e-05,\n",
-      "       1.88863033e-06, 2.37223491e-06]), 'split2_train_score': array([0.91666667, 0.96428571, 0.96428571, 0.96428571, 0.97619048,\n",
-      "       0.97619048]), 'split0_test_score': array([0.92857143, 0.96428571, 0.96428571, 0.96428571, 0.96428571,\n",
-      "       0.96428571]), 'split1_train_score': array([0.86904762, 0.96428571, 0.96428571, 0.97619048, 0.97619048,\n",
-      "       0.97619048]), 'split2_test_score': array([0.96428571, 0.96428571, 0.96428571, 1.        , 1.        ,\n",
-      "       1.        ]), 'param_C': masked_array(data=[1, 1, 10, 10, 100, 100],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object), 'mean_score_time': array([0.00021189, 0.0001657 , 0.00017828, 0.00015265, 0.00014174,\n",
-      "       0.00014162]), 'mean_train_score': array([0.9077381 , 0.9702381 , 0.97321429, 0.98214286, 0.98511905,\n",
-      "       0.98511905]), 'mean_fit_time': array([0.00046653, 0.0002929 , 0.00035262, 0.00029558, 0.00025451,\n",
-      "       0.00026101]), 'params': [{'C': 1, 'gamma': 0.01}, {'C': 1, 'gamma': 0.1}, {'C': 10, 'gamma': 0.01}, {'C': 10, 'gamma': 0.1}, {'C': 100, 'gamma': 0.01}, {'C': 100, 'gamma': 0.1}], 'std_test_score': array([0.05646924, 0.04639422, 0.03092948, 0.01785714, 0.01546474,\n",
-      "       0.05854856]), 'std_train_score': array([0.03705327, 0.01030983, 0.01546474, 0.01330993, 0.00987091,\n",
-      "       0.00987091]), 'mean_test_score': array([0.89285714, 0.9375    , 0.94642857, 0.98214286, 0.97321429,\n",
-      "       0.95535714]), 'split3_test_score': array([0.82142857, 0.85714286, 0.89285714, 0.96428571, 0.96428571,\n",
-      "       0.85714286]), 'rank_test_score': array([6, 5, 4, 1, 2, 3], dtype=int32), 'split1_test_score': array([0.85714286, 0.96428571, 0.96428571, 1.        , 0.96428571,\n",
-      "       1.        ]), 'std_fit_time': array([9.01377338e-05, 6.28426330e-06, 3.60406571e-05, 5.15247249e-05,\n",
-      "       1.17498278e-05, 1.70351493e-05]), 'split3_train_score': array([0.96428571, 0.98809524, 1.        , 1.        , 1.        ,\n",
-      "       1.        ]), 'split0_train_score': array([0.88095238, 0.96428571, 0.96428571, 0.98809524, 0.98809524,\n",
-      "       0.98809524]), 'param_gamma': masked_array(data=[0.01, 0.1, 0.01, 0.1, 0.01, 0.1],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object)}\n",
-      "\n",
-      "1\n",
-      "{'std_score_time': array([8.33272081e-06, 2.06132131e-06, 1.89343984e-05, 5.24080428e-06,\n",
-      "       6.61047489e-07, 1.83423550e-06]), 'split2_train_score': array([0.91666667, 0.96428571, 0.96428571, 0.98809524, 0.97619048,\n",
-      "       0.98809524]), 'split0_test_score': array([0.92857143, 0.96428571, 1.        , 1.        , 1.        ,\n",
-      "       0.96428571]), 'split1_train_score': array([0.95238095, 0.97619048, 0.97619048, 0.98809524, 0.98809524,\n",
-      "       0.98809524]), 'split2_test_score': array([1.        , 1.        , 1.        , 1.        , 1.        ,\n",
-      "       0.96428571]), 'param_C': masked_array(data=[1, 1, 10, 10, 100, 100],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object), 'mean_score_time': array([0.00018692, 0.00016367, 0.00017142, 0.00014895, 0.0001412 ,\n",
-      "       0.00014251]), 'mean_train_score': array([0.93154762, 0.97321429, 0.9702381 , 0.99107143, 0.98809524,\n",
-      "       0.98809524]), 'mean_fit_time': array([0.00044656, 0.00030571, 0.00029963, 0.00027484, 0.00025165,\n",
-      "       0.00027138]), 'params': [{'C': 1, 'gamma': 0.01}, {'C': 1, 'gamma': 0.1}, {'C': 10, 'gamma': 0.01}, {'C': 10, 'gamma': 0.1}, {'C': 100, 'gamma': 0.01}, {'C': 100, 'gamma': 0.1}], 'std_test_score': array([0.06376275, 0.01546474, 0.01785714, 0.02961272, 0.02961272,\n",
-      "       0.        ]), 'std_train_score': array([0.01297291, 0.00987091, 0.00595238, 0.00515491, 0.00841794,\n",
-      "       0.00841794]), 'mean_test_score': array([0.91964286, 0.97321429, 0.98214286, 0.97321429, 0.97321429,\n",
-      "       0.96428571]), 'split3_test_score': array([0.92857143, 0.96428571, 0.96428571, 0.96428571, 0.96428571,\n",
-      "       0.96428571]), 'rank_test_score': array([6, 2, 1, 2, 2, 5], dtype=int32), 'split1_test_score': array([0.82142857, 0.96428571, 0.96428571, 0.92857143, 0.92857143,\n",
-      "       0.96428571]), 'std_fit_time': array([9.50373959e-05, 3.66022995e-06, 1.56844048e-05, 1.16622698e-05,\n",
-      "       8.33527856e-06, 1.73377812e-05]), 'split3_train_score': array([0.92857143, 0.96428571, 0.96428571, 1.        , 1.        ,\n",
-      "       1.        ]), 'split0_train_score': array([0.92857143, 0.98809524, 0.97619048, 0.98809524, 0.98809524,\n",
-      "       0.97619048]), 'param_gamma': masked_array(data=[0.01, 0.1, 0.01, 0.1, 0.01, 0.1],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object)}\n",
-      "\n",
-      "2\n",
-      "{'std_score_time': array([3.39013698e-06, 2.39236739e-06, 1.81965083e-06, 2.35117470e-06,\n",
-      "       1.03924249e-06, 4.57831964e-07]), 'split2_train_score': array([0.92857143, 0.97619048, 0.97619048, 0.98809524, 0.98809524,\n",
-      "       1.        ]), 'split0_test_score': array([1., 1., 1., 1., 1., 1.]), 'split1_train_score': array([0.94047619, 1.        , 1.        , 1.        , 1.        ,\n",
-      "       1.        ]), 'split2_test_score': array([0.96428571, 1.        , 1.        , 1.        , 1.        ,\n",
-      "       0.89285714]), 'param_C': masked_array(data=[1, 1, 10, 10, 100, 100],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object), 'mean_score_time': array([0.00017661, 0.00015908, 0.00015056, 0.00014818, 0.00014067,\n",
-      "       0.00014156]), 'mean_train_score': array([0.90178571, 0.98511905, 0.98511905, 0.98809524, 0.98809524,\n",
-      "       0.99404762]), 'mean_fit_time': array([0.00038451, 0.00029421, 0.00026572, 0.00026315, 0.00024247,\n",
-      "       0.00025213]), 'params': [{'C': 1, 'gamma': 0.01}, {'C': 1, 'gamma': 0.1}, {'C': 10, 'gamma': 0.01}, {'C': 10, 'gamma': 0.1}, {'C': 100, 'gamma': 0.01}, {'C': 100, 'gamma': 0.1}], 'std_test_score': array([0.09902265, 0.01785714, 0.01785714, 0.04374089, 0.04374089,\n",
-      "       0.05646924]), 'std_train_score': array([0.06033671, 0.00987091, 0.00987091, 0.00841794, 0.00841794,\n",
-      "       0.01030983]), 'mean_test_score': array([0.88392857, 0.98214286, 0.98214286, 0.96428571, 0.96428571,\n",
-      "       0.92857143]), 'split3_test_score': array([0.78571429, 0.96428571, 0.96428571, 0.96428571, 0.96428571,\n",
-      "       0.96428571]), 'rank_test_score': array([6, 1, 1, 3, 3, 5], dtype=int32), 'split1_test_score': array([0.78571429, 0.96428571, 0.96428571, 0.89285714, 0.89285714,\n",
-      "       0.85714286]), 'std_fit_time': array([4.54199517e-05, 3.46733083e-06, 4.18932042e-06, 3.81609399e-06,\n",
-      "       4.63232022e-06, 5.49527672e-06]), 'split3_train_score': array([0.79761905, 0.98809524, 0.98809524, 0.98809524, 0.98809524,\n",
-      "       1.        ]), 'split0_train_score': array([0.94047619, 0.97619048, 0.97619048, 0.97619048, 0.97619048,\n",
-      "       0.97619048]), 'param_gamma': masked_array(data=[0.01, 0.1, 0.01, 0.1, 0.01, 0.1],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object)}\n",
-      "\n",
-      "3\n",
-      "{'std_score_time': array([1.44149616e-05, 1.05787750e-06, 8.49235466e-07, 4.57831964e-07,\n",
-      "       8.76005796e-07, 9.88431212e-07]), 'split2_train_score': array([0.89285714, 0.96428571, 0.95238095, 0.97619048, 0.96428571,\n",
-      "       0.96428571]), 'split0_test_score': array([0.85714286, 0.96428571, 0.96428571, 0.96428571, 0.96428571,\n",
-      "       0.96428571]), 'split1_train_score': array([0.94047619, 0.98809524, 0.98809524, 0.98809524, 0.98809524,\n",
-      "       1.        ]), 'split2_test_score': array([0.85714286, 0.89285714, 0.89285714, 0.92857143, 0.92857143,\n",
-      "       0.92857143]), 'param_C': masked_array(data=[1, 1, 10, 10, 100, 100],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object), 'mean_score_time': array([0.00018787, 0.00016254, 0.00016016, 0.00015181, 0.00014877,\n",
-      "       0.00014991]), 'mean_train_score': array([0.9047619 , 0.96428571, 0.96130952, 0.97619048, 0.97321429,\n",
-      "       0.97321429]), 'mean_fit_time': array([0.00039715, 0.00030398, 0.00029951, 0.00027311, 0.00025588,\n",
-      "       0.00027567]), 'params': [{'C': 1, 'gamma': 0.01}, {'C': 1, 'gamma': 0.1}, {'C': 10, 'gamma': 0.01}, {'C': 10, 'gamma': 0.1}, {'C': 100, 'gamma': 0.01}, {'C': 100, 'gamma': 0.1}], 'std_test_score': array([0.04374089, 0.03992979, 0.03992979, 0.02525381, 0.01546474,\n",
-      "       0.01785714]), 'std_train_score': array([0.02227177, 0.0145803 , 0.01546474, 0.00841794, 0.00987091,\n",
-      "       0.01760738]), 'mean_test_score': array([0.89285714, 0.94642857, 0.94642857, 0.96428571, 0.95535714,\n",
-      "       0.94642857]), 'split3_test_score': array([0.96428571, 1.        , 1.        , 1.        , 0.96428571,\n",
-      "       0.96428571]), 'rank_test_score': array([6, 3, 3, 1, 2, 3], dtype=int32), 'split1_test_score': array([0.89285714, 0.92857143, 0.92857143, 0.96428571, 0.96428571,\n",
-      "       0.92857143]), 'std_fit_time': array([5.56155415e-05, 1.26754851e-05, 1.82599488e-05, 2.66826502e-06,\n",
-      "       3.90808343e-06, 3.21367993e-06]), 'split3_train_score': array([0.9047619 , 0.95238095, 0.95238095, 0.96428571, 0.97619048,\n",
-      "       0.97619048]), 'split0_train_score': array([0.88095238, 0.95238095, 0.95238095, 0.97619048, 0.96428571,\n",
-      "       0.95238095]), 'param_gamma': masked_array(data=[0.01, 0.1, 0.01, 0.1, 0.01, 0.1],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object)}\n",
-      "\n",
-      "4\n",
-      "{'std_score_time': array([3.84623189e-06, 2.97307108e-06, 9.29144458e-07, 8.93115488e-06,\n",
-      "       1.71796883e-05, 3.76084054e-05]), 'split2_train_score': array([0.9047619 , 0.94047619, 0.94047619, 0.96428571, 0.96428571,\n",
-      "       0.96428571]), 'split0_test_score': array([0.82142857, 1.        , 0.96428571, 1.        , 0.96428571,\n",
-      "       0.92857143]), 'split1_train_score': array([0.89285714, 0.94047619, 0.94047619, 0.97619048, 0.97619048,\n",
-      "       0.97619048]), 'split2_test_score': array([0.89285714, 0.96428571, 0.96428571, 0.96428571, 1.        ,\n",
-      "       1.        ]), 'param_C': masked_array(data=[1, 1, 10, 10, 100, 100],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object), 'mean_score_time': array([0.00019467, 0.0001688 , 0.00015813, 0.00016057, 0.00016457,\n",
-      "       0.00017679]), 'mean_train_score': array([0.90178571, 0.95535714, 0.95833333, 0.97916667, 0.97916667,\n",
-      "       0.97619048]), 'mean_fit_time': array([0.0004366 , 0.00031209, 0.00028533, 0.0002737 , 0.00026488,\n",
-      "       0.0002774 ]), 'params': [{'C': 1, 'gamma': 0.01}, {'C': 1, 'gamma': 0.1}, {'C': 10, 'gamma': 0.01}, {'C': 10, 'gamma': 0.1}, {'C': 100, 'gamma': 0.01}, {'C': 100, 'gamma': 0.1}], 'std_test_score': array([0.04374089, 0.03891874, 0.03092948, 0.04374089, 0.04374089,\n",
-      "       0.02961272]), 'std_train_score': array([0.00515491, 0.01546474, 0.01785714, 0.01297291, 0.01297291,\n",
-      "       0.00841794]), 'mean_test_score': array([0.89285714, 0.95535714, 0.94642857, 0.96428571, 0.96428571,\n",
-      "       0.95535714]), 'split3_test_score': array([0.92857143, 0.89285714, 0.89285714, 0.89285714, 0.89285714,\n",
-      "       0.92857143]), 'rank_test_score': array([6, 3, 5, 1, 1, 3], dtype=int32), 'split1_test_score': array([0.92857143, 0.96428571, 0.96428571, 1.        , 1.        ,\n",
-      "       0.96428571]), 'std_fit_time': array([6.65989292e-05, 7.14460567e-06, 5.84338354e-06, 4.58917059e-06,\n",
-      "       8.89687927e-06, 2.05769875e-05]), 'split3_train_score': array([0.9047619 , 0.96428571, 0.97619048, 1.        , 1.        ,\n",
-      "       0.98809524]), 'split0_train_score': array([0.9047619 , 0.97619048, 0.97619048, 0.97619048, 0.97619048,\n",
-      "       0.97619048]), 'param_gamma': masked_array(data=[0.01, 0.1, 0.01, 0.1, 0.01, 0.1],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object)}\n",
-      "\n",
-      "5\n",
-      "{'std_score_time': array([1.85062584e-06, 1.10550147e-06, 4.28162198e-05, 1.62142164e-06,\n",
-      "       9.29144458e-07, 1.37349589e-06]), 'split2_train_score': array([0.98809524, 0.98809524, 0.98809524, 0.98809524, 0.98809524,\n",
-      "       0.98809524]), 'split0_test_score': array([0.96428571, 0.96428571, 0.96428571, 1.        , 1.        ,\n",
-      "       0.96428571]), 'split1_train_score': array([0.92857143, 0.96428571, 0.96428571, 0.97619048, 0.97619048,\n",
-      "       0.97619048]), 'split2_test_score': array([0.82142857, 0.96428571, 0.96428571, 0.96428571, 0.96428571,\n",
-      "       0.96428571]), 'param_C': masked_array(data=[1, 1, 10, 10, 100, 100],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object), 'mean_score_time': array([0.00018179, 0.00016308, 0.00018311, 0.00015223, 0.00014824,\n",
-      "       0.00015038]), 'mean_train_score': array([0.9375    , 0.97916667, 0.98214286, 0.98511905, 0.98511905,\n",
-      "       0.98214286]), 'mean_fit_time': array([0.00041962, 0.00029922, 0.00027883, 0.00028938, 0.00025576,\n",
-      "       0.00028121]), 'params': [{'C': 1, 'gamma': 0.01}, {'C': 1, 'gamma': 0.1}, {'C': 10, 'gamma': 0.01}, {'C': 10, 'gamma': 0.1}, {'C': 100, 'gamma': 0.01}, {'C': 100, 'gamma': 0.1}], 'std_test_score': array([0.08134316, 0.03891874, 0.03891874, 0.02961272, 0.02961272,\n",
-      "       0.02525381]), 'std_train_score': array([0.03078595, 0.00987091, 0.01030983, 0.00515491, 0.00515491,\n",
-      "       0.00595238]), 'mean_test_score': array([0.88392857, 0.95535714, 0.95535714, 0.97321429, 0.97321429,\n",
-      "       0.96428571]), 'split3_test_score': array([0.96428571, 1.        , 1.        , 1.        , 1.        ,\n",
-      "       1.        ]), 'rank_test_score': array([6, 4, 4, 1, 1, 3], dtype=int32), 'split1_test_score': array([0.78571429, 0.89285714, 0.89285714, 0.92857143, 0.92857143,\n",
-      "       0.92857143]), 'std_fit_time': array([7.58356620e-05, 7.24925794e-06, 4.00550309e-06, 2.77644424e-05,\n",
-      "       4.33887425e-06, 1.71334067e-05]), 'split3_train_score': array([0.92857143, 0.97619048, 0.98809524, 0.98809524, 0.98809524,\n",
-      "       0.97619048]), 'split0_train_score': array([0.9047619 , 0.98809524, 0.98809524, 0.98809524, 0.98809524,\n",
-      "       0.98809524]), 'param_gamma': masked_array(data=[0.01, 0.1, 0.01, 0.1, 0.01, 0.1],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object)}\n",
-      "\n",
-      "6\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'std_score_time': array([3.09198197e-06, 1.37349589e-06, 2.29303647e-06, 9.31054315e-07,\n",
-      "       6.05123955e-05, 1.57039859e-05]), 'split2_train_score': array([0.89285714, 0.95238095, 0.96428571, 0.96428571, 0.96428571,\n",
-      "       0.96428571]), 'split0_test_score': array([0.92857143, 0.89285714, 0.89285714, 0.92857143, 0.92857143,\n",
-      "       0.92857143]), 'split1_train_score': array([0.92857143, 0.96428571, 0.96428571, 0.98809524, 0.97619048,\n",
-      "       0.98809524]), 'split2_test_score': array([0.96428571, 1.        , 1.        , 1.        , 1.        ,\n",
-      "       0.96428571]), 'param_C': masked_array(data=[1, 1, 10, 10, 100, 100],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object), 'mean_score_time': array([0.00017935, 0.00016373, 0.00015998, 0.00015104, 0.00022823,\n",
-      "       0.00016546]), 'mean_train_score': array([0.91071429, 0.9702381 , 0.97619048, 0.97916667, 0.97619048,\n",
-      "       0.98214286]), 'mean_fit_time': array([0.00038064, 0.00030971, 0.00028497, 0.0002746 , 0.00040722,\n",
-      "       0.00030589]), 'params': [{'C': 1, 'gamma': 0.01}, {'C': 1, 'gamma': 0.1}, {'C': 10, 'gamma': 0.01}, {'C': 10, 'gamma': 0.1}, {'C': 100, 'gamma': 0.01}, {'C': 100, 'gamma': 0.1}], 'std_test_score': array([0.05282214, 0.05357143, 0.04639422, 0.02961272, 0.02961272,\n",
-      "       0.02525381]), 'std_train_score': array([0.01785714, 0.01785714, 0.0145803 , 0.00987091, 0.00841794,\n",
-      "       0.01030983]), 'mean_test_score': array([0.9375    , 0.94642857, 0.95535714, 0.97321429, 0.97321429,\n",
-      "       0.96428571]), 'split3_test_score': array([1., 1., 1., 1., 1., 1.]), 'rank_test_score': array([6, 5, 4, 1, 1, 3], dtype=int32), 'split1_test_score': array([0.85714286, 0.89285714, 0.92857143, 0.96428571, 0.96428571,\n",
-      "       0.96428571]), 'std_fit_time': array([2.67222985e-05, 9.33340985e-06, 8.74767969e-06, 9.21446169e-06,\n",
-      "       5.52532164e-05, 1.68831669e-05]), 'split3_train_score': array([0.89285714, 0.96428571, 0.97619048, 0.97619048, 0.97619048,\n",
-      "       0.98809524]), 'split0_train_score': array([0.92857143, 1.        , 1.        , 0.98809524, 0.98809524,\n",
-      "       0.98809524]), 'param_gamma': masked_array(data=[0.01, 0.1, 0.01, 0.1, 0.01, 0.1],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object)}\n",
-      "\n",
-      "7\n",
-      "{'std_score_time': array([1.38380370e-06, 1.73672634e-05, 1.37349589e-06, 6.54322188e-06,\n",
-      "       1.01152436e-06, 8.31870747e-05]), 'split2_train_score': array([0.88095238, 0.98809524, 0.97619048, 0.98809524, 0.97619048,\n",
-      "       0.98809524]), 'split0_test_score': array([0.78571429, 1.        , 1.        , 1.        , 1.        ,\n",
-      "       1.        ]), 'split1_train_score': array([0.94047619, 0.92857143, 0.95238095, 0.98809524, 0.98809524,\n",
-      "       0.98809524]), 'split2_test_score': array([0.89285714, 0.96428571, 0.96428571, 1.        , 1.        ,\n",
-      "       1.        ]), 'param_C': masked_array(data=[1, 1, 10, 10, 100, 100],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object), 'mean_score_time': array([0.00018364, 0.00017959, 0.00016695, 0.0001623 , 0.0001545 ,\n",
-      "       0.00025201]), 'mean_train_score': array([0.89583333, 0.9672619 , 0.9702381 , 0.98809524, 0.98511905,\n",
-      "       0.99107143]), 'mean_fit_time': array([0.00041223, 0.00032604, 0.000305  , 0.00029951, 0.00030398,\n",
-      "       0.00040394]), 'params': [{'C': 1, 'gamma': 0.01}, {'C': 1, 'gamma': 0.1}, {'C': 10, 'gamma': 0.01}, {'C': 10, 'gamma': 0.1}, {'C': 100, 'gamma': 0.01}, {'C': 100, 'gamma': 0.1}], 'std_test_score': array([0.05357143, 0.02525381, 0.02961272, 0.02961272, 0.02961272,\n",
-      "       0.01785714]), 'std_train_score': array([0.05670404, 0.02436117, 0.01330993, 0.        , 0.00515491,\n",
-      "       0.00515491]), 'mean_test_score': array([0.875     , 0.96428571, 0.97321429, 0.97321429, 0.97321429,\n",
-      "       0.98214286]), 'split3_test_score': array([0.89285714, 0.92857143, 0.92857143, 0.92857143, 0.92857143,\n",
-      "       0.96428571]), 'rank_test_score': array([6, 5, 2, 2, 2, 1], dtype=int32), 'split1_test_score': array([0.92857143, 0.96428571, 1.        , 0.96428571, 0.96428571,\n",
-      "       0.96428571]), 'std_fit_time': array([4.18887941e-05, 1.97113921e-05, 6.32904785e-06, 1.24610777e-05,\n",
-      "       4.97184205e-05, 8.18184646e-05]), 'split3_train_score': array([0.95238095, 0.98809524, 0.98809524, 0.98809524, 0.98809524,\n",
-      "       1.        ]), 'split0_train_score': array([0.80952381, 0.96428571, 0.96428571, 0.98809524, 0.98809524,\n",
-      "       0.98809524]), 'param_gamma': masked_array(data=[0.01, 0.1, 0.01, 0.1, 0.01, 0.1],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object)}\n",
-      "\n",
-      "8\n",
-      "{'std_score_time': array([7.51373230e-06, 1.75252860e-05, 1.23119306e-05, 1.40419233e-06,\n",
-      "       1.33812096e-06, 2.89677960e-05]), 'split2_train_score': array([0.89285714, 0.95238095, 0.95238095, 0.98809524, 0.98809524,\n",
-      "       0.98809524]), 'split0_test_score': array([0.92857143, 0.92857143, 0.92857143, 0.92857143, 0.96428571,\n",
-      "       0.96428571]), 'split1_train_score': array([0.92857143, 0.96428571, 0.96428571, 1.        , 0.98809524,\n",
-      "       1.        ]), 'split2_test_score': array([0.92857143, 0.96428571, 0.96428571, 1.        , 1.        ,\n",
-      "       1.        ]), 'param_C': masked_array(data=[1, 1, 10, 10, 100, 100],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object), 'mean_score_time': array([0.0001846 , 0.00017673, 0.00015813, 0.00014585, 0.00014281,\n",
-      "       0.00016087]), 'mean_train_score': array([0.92559524, 0.9672619 , 0.9702381 , 0.99107143, 0.98809524,\n",
-      "       0.99404762]), 'mean_fit_time': array([0.00045431, 0.00032181, 0.00026774, 0.00026602, 0.00025386,\n",
-      "       0.00027066]), 'params': [{'C': 1, 'gamma': 0.01}, {'C': 1, 'gamma': 0.1}, {'C': 10, 'gamma': 0.01}, {'C': 10, 'gamma': 0.1}, {'C': 100, 'gamma': 0.01}, {'C': 100, 'gamma': 0.1}], 'std_test_score': array([0.04374089, 0.03992979, 0.02961272, 0.02961272, 0.01785714,\n",
-      "       0.02525381]), 'std_train_score': array([0.01951619, 0.01297291, 0.01330993, 0.00515491, 0.        ,\n",
-      "       0.00595238]), 'mean_test_score': array([0.89285714, 0.94642857, 0.95535714, 0.97321429, 0.98214286,\n",
-      "       0.96428571]), 'split3_test_score': array([0.89285714, 1.        , 1.        , 1.        , 1.        ,\n",
-      "       0.92857143]), 'rank_test_score': array([6, 5, 4, 2, 1, 3], dtype=int32), 'split1_test_score': array([0.82142857, 0.89285714, 0.92857143, 0.96428571, 0.96428571,\n",
-      "       0.96428571]), 'std_fit_time': array([1.30075909e-04, 4.45017634e-05, 4.03202403e-06, 3.17363251e-06,\n",
-      "       2.87773793e-06, 1.10786100e-05]), 'split3_train_score': array([0.94047619, 0.96428571, 0.97619048, 0.98809524, 0.98809524,\n",
-      "       1.        ]), 'split0_train_score': array([0.94047619, 0.98809524, 0.98809524, 0.98809524, 0.98809524,\n",
-      "       0.98809524]), 'param_gamma': masked_array(data=[0.01, 0.1, 0.01, 0.1, 0.01, 0.1],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object)}\n",
-      "\n",
-      "9\n",
-      "{'std_score_time': array([1.12099525e-05, 1.45513482e-06, 9.72341588e-06, 1.22007665e-06,\n",
-      "       1.34241517e-05, 1.19803853e-06]), 'split2_train_score': array([0.92857143, 0.96428571, 0.96428571, 0.96428571, 0.96428571,\n",
-      "       0.97619048]), 'split0_test_score': array([0.78571429, 0.89285714, 0.89285714, 0.89285714, 0.89285714,\n",
-      "       0.89285714]), 'split1_train_score': array([0.89285714, 0.96428571, 0.95238095, 0.97619048, 0.97619048,\n",
-      "       0.98809524]), 'split2_test_score': array([0.92857143, 0.96428571, 0.96428571, 0.96428571, 0.96428571,\n",
-      "       0.92857143]), 'param_C': masked_array(data=[1, 1, 10, 10, 100, 100],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object), 'mean_score_time': array([0.00018686, 0.0001651 , 0.00016868, 0.0001542 , 0.00015867,\n",
-      "       0.00015223]), 'mean_train_score': array([0.90178571, 0.96130952, 0.9672619 , 0.97619048, 0.97619048,\n",
-      "       0.98511905]), 'mean_fit_time': array([0.0004074 , 0.00030303, 0.00029409, 0.00029194, 0.00027001,\n",
-      "       0.00028688]), 'params': [{'C': 1, 'gamma': 0.01}, {'C': 1, 'gamma': 0.1}, {'C': 10, 'gamma': 0.01}, {'C': 10, 'gamma': 0.1}, {'C': 100, 'gamma': 0.01}, {'C': 100, 'gamma': 0.1}], 'std_test_score': array([0.06858166, 0.03891874, 0.03891874, 0.04374089, 0.04374089,\n",
-      "       0.03992979]), 'std_train_score': array([0.02286055, 0.01297291, 0.01297291, 0.00841794, 0.00841794,\n",
-      "       0.00987091]), 'mean_test_score': array([0.88392857, 0.95535714, 0.95535714, 0.96428571, 0.96428571,\n",
-      "       0.94642857]), 'split3_test_score': array([0.96428571, 1.        , 1.        , 1.        , 1.        ,\n",
-      "       1.        ]), 'rank_test_score': array([6, 3, 3, 1, 1, 5], dtype=int32), 'split1_test_score': array([0.85714286, 0.96428571, 0.96428571, 1.        , 1.        ,\n",
-      "       0.96428571]), 'std_fit_time': array([4.94338875e-05, 4.75942249e-06, 1.19803853e-06, 5.52107629e-06,\n",
-      "       6.87187531e-06, 1.12618083e-05]), 'split3_train_score': array([0.91666667, 0.94047619, 0.96428571, 0.97619048, 0.97619048,\n",
-      "       0.97619048]), 'split0_train_score': array([0.86904762, 0.97619048, 0.98809524, 0.98809524, 0.98809524,\n",
-      "       1.        ]), 'param_gamma': masked_array(data=[0.01, 0.1, 0.01, 0.1, 0.01, 0.1],\n",
-      "             mask=[False, False, False, False, False, False],\n",
-      "       fill_value='?',\n",
-      "            dtype=object)}\n"
-     ]
-    }
-   ],
-   "source": [
-    "from sklearn.datasets import load_iris\n",
-    "from matplotlib import pyplot as plt\n",
-    "from sklearn.svm import SVC\n",
-    "from sklearn.model_selection import GridSearchCV, cross_val_score, KFold, train_test_split\n",
-    "import numpy as np\n",
-    "\n",
-    "print(__doc__)\n",
-    "\n",
-    "# Number of random trials\n",
-    "NUM_TRIALS = 10\n",
-    "\n",
-    "# Load the dataset\n",
-    "iris = load_iris()\n",
-    "X_iris = iris.data\n",
-    "y_iris = iris.target\n",
-    "\n",
-    "# Set up possible values of parameters to optimize over\n",
-    "p_grid = {\"C\": [1, 10, 100],\n",
-    "          \"gamma\": [.01, .1]}\n",
-    "\n",
-    "# We will use a Support Vector Classifier with \"rbf\" kernel\n",
-    "svm = SVC(kernel=\"rbf\")\n",
-    "\n",
-    "# Arrays to store scores\n",
-    "val_scores =  np.zeros((NUM_TRIALS,len(p_grid['C'])))\n",
-    "test_scores = np.zeros((NUM_TRIALS,len(p_grid['C'])))\n",
-    "\n",
-    "best_params = []\n",
-    "# Loop for each trial\n",
-    "for i in range(NUM_TRIALS): #Test set level\n",
-    "    print()\n",
-    "    print(i)\n",
-    "    X_app,X_test,y_app,y_test = train_test_split(X_iris,y_iris)\n",
-    "    inner_cv = KFold(n_splits=4, shuffle=True, random_state=i)\n",
-    "    # Non_nested parameter search and scoring\n",
-    "    clf = GridSearchCV(estimator=svm, param_grid=p_grid, cv=inner_cv)\n",
-    "    clf.fit(X_app, y_app)\n",
-    "    print(clf.cv_results_)\n",
-    "    best_params.append(clf.best_params_)\n",
-    "    val_scores[i] = clf.best_score_\n",
-    "    test_scores[i] = clf.score(X_test,y_test)\n",
-    "\n",
-    "final_performance = np.mean(test_scores)\n"
-   ]
-  },
-  {
-   "cell_type": "raw",
-   "metadata": {},
-   "source": [
-    "import networkx as nx\n",
-    "import matplotlib.pyplot as plt\n",
-    "import sys\n",
-    "sys.path.insert(0, \"../\")\n",
-    "from pygraph.utils.graphfiles import loadDataset\n",
-    "from pygraph.utils.utils import kernel_train_test\n",
-    "\n",
-    "from sklearn.model_selection import GridSearchCV, KFold, cross_val_score, cross_validate\n",
-    "from sklearn.kernel_ridge import KernelRidge\n",
-    "from sklearn.metrics import classification_report\n",
-    "from sklearn.metrics import accuracy_score, mean_squared_error, make_scorer\n",
-    "\n",
-    "from pygraph.kernels.treeletKernel import treeletkernel\n",
-    "from pygraph.kernels.pathKernel import pathkernel\n",
-    "from pygraph.kernels.spKernel import spkernel\n",
-    "\n",
-    "import numpy as np\n",
-    "\n",
-    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
-    "\n",
-    "dataset, y = loadDataset(datafile)\n",
-    "\n",
-    "Kmatrix, run_time = treeletkernel(dataset)\n",
-    "\n",
-    "import matplotlib.pyplot as plt\n",
-    "plt.matshow(Kmatrix)\n",
-    "\n",
-    "# Set the training, test\n",
-    "# Note: the percentage can be set up by the user\n",
-    "datasize = len(y)\n",
-    "num_train = int((datasize * 90) / 100)         # 90% (of entire dataset) for training\n",
-    "num_test = datasize - num_train             # 10% (of entire dataset) for test\n",
-    "\n",
-    "# Split the kernel matrix\n",
-    "Kmatrix_train = Kmatrix[0:num_train, 0:num_train]\n",
-    "Kmatrix_test = Kmatrix[num_train:datasize, 0:num_train]\n",
-    "\n",
-    "# Split the targets\n",
-    "y_train = y[0:num_train]\n",
-    "y_test = y[num_train:datasize]\n",
-    "\n",
-    "# Set the parameters by cross-validation\n",
-    "tuned_parameters = [{'alpha': np.logspace(-10, 10, num = 100, base = 10)}]\n",
-    "\n",
-    "print(\"# Tuning hyper-parameters\")\n",
-    "print()\n",
-    "\n",
-    "def loss_func_rmse(x_true, x_pred):\n",
-    "    return np.sqrt(mean_squared_error(x_true, x_pred))\n",
-    "\n",
-    "loss_rmse = make_scorer(loss_func_rmse, greater_is_better=False)\n",
-    "inner_cv = KFold(n_splits=10, shuffle=True, random_state=10)\n",
-    "outer_cv = KFold(n_splits=10, shuffle=True, random_state=10)\n",
-    "\n",
-    "kr = KernelRidge(kernel='precomputed')\n",
-    "cv = GridSearchCV(estimator=kr, param_grid=tuned_parameters, cv=inner_cv, \n",
-    "                  scoring=loss_rmse, return_train_score=True)\n",
-    "cv.fit(Kmatrix, y)\n",
-    "cv.get_params()\n",
-    "\n",
-    "print(\"Best parameters set found on development set:\")\n",
-    "print()\n",
-    "print(cv.best_params_)\n",
-    "print()\n",
-    "print(\"Best score set found on development set:\")\n",
-    "print()\n",
-    "print(-cv.best_score_)\n",
-    "print()\n",
-    "print(\"Grid scores on development set:\")\n",
-    "print()\n",
-    "means_train = cv.cv_results_['mean_train_score']\n",
-    "stds_train = cv.cv_results_['std_train_score']\n",
-    "means_test = cv.cv_results_['mean_test_score']\n",
-    "stds_test = cv.cv_results_['std_test_score']\n",
-    "for means_train, stds_train, means_test, stds_test, params \\\n",
-    "    in zip(means_train, stds_train, means_test, stds_test, cv.cv_results_['params']):\n",
-    "    print(\"train: %0.3f (+/-%0.03f) | test: %0.3f (+/-%0.03f) for %r\"\n",
-    "          % (-means_train, stds_train, -means_test, stds_test, params))\n",
-    "print()\n",
-    "\n",
-    "print(Kmatrix.shape)\n",
-    "# Nested CV with parameter optimization\n",
-    "nested_score = cross_val_score(estimator=cv, X=Kmatrix, y=y, cv=outer_cv, \n",
-    "                               scoring=loss_rmse)\n",
-    "print(nested_score)\n",
-    "# nested_scores[i] = nested_score.mean()\n",
-    "\n",
-    "# print(\"Detailed classification report:\")\n",
-    "# print()\n",
-    "# print(\"The model is trained on the full development set.\")\n",
-    "# print(\"The scores are computed on the full evaluation set.\")\n",
-    "# print()\n",
-    "# # predict on the train and test set\n",
-    "# y_pred_train = cv.predict(Kmatrix_train)\n",
-    "# y_pred_test = cv.predict(Kmatrix_test)\n",
-    "\n",
-    "\n",
-    "# print('y_train: ', y_train)\n",
-    "# print('y_pred_train: ', y_pred_train)\n",
-    "# print('y_test: ', y_test)\n",
-    "# print('y_pred_test: ', y_pred_test)\n",
-    "\n",
-    "# # root mean squared error on train set\n",
-    "# accuracy_train = np.sqrt(mean_squared_error(y_train, y_pred_train))\n",
-    "# accuracy_test = np.sqrt(mean_squared_error(y_test, y_pred_test))\n",
-    "# print('\\n Mean performance on train set: %3f' % accuracy_train)\n",
-    "# print('\\n Mean performance on test set: %3f' % accuracy_test)\n",
-    "\n",
-    "# print()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/sklearn/cross_validation.py:41: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n",
-      "  \"This module will be removed in 0.20.\", DeprecationWarning)\n",
-      "/home/ljia/.local/lib/python3.5/site-packages/sklearn/grid_search.py:42: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. This module will be removed in 0.20.\n",
-      "  DeprecationWarning)\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "True"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from sklearn.base import BaseEstimator\n",
-    "from sklearn.grid_search import GridSearchCV\n",
-    "from sklearn.datasets.samples_generator import make_classification\n",
-    "from sklearn.svm import LinearSVC, SVC\n",
-    "from sklearn.metrics import f1_score, precision_score\n",
-    "\n",
-    "X_, y_ = make_classification(n_samples=200, n_features=100, random_state=0)\n",
-    "# compute the training kernel matrix corresponding to the linear kernel\n",
-    "K_train = np.dot(X_[:180], X_[:180].T)\n",
-    "y_train = y_[:180]\n",
-    "clf = SVC(kernel='precomputed')\n",
-    "cv = GridSearchCV(clf, {'C': [0.1, 1.0]})\n",
-    "cv.fit(K_train, y_train)\n",
-    "# compute the test kernel matrix\n",
-    "K_test = np.dot(X_[180:], X_[:180].T)\n",
-    "y_test = y_[180:]\n",
-    "y_pred = cv.predict(K_test)\n",
-    "np.mean(y_pred == y_test) >= 0"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[2 3] [0 1]\n",
-      "[0 1] [2 3]\n"
-     ]
-    }
-   ],
-   "source": [
-    "import numpy as np\n",
-    "from sklearn.model_selection import KFold\n",
-    "\n",
-    "X = [\"a\", \"b\", \"c\", \"d\"]\n",
-    "kf = KFold(n_splits=2)\n",
-    "for train, test in kf.split(X):\n",
-    "    print(\"%s %s\" % (train, test))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.9733333333333334"
-      ]
-     },
-     "execution_count": 30,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import numpy as np\n",
-    "from sklearn.model_selection import train_test_split\n",
-    "from sklearn import datasets\n",
-    "from sklearn import svm\n",
-    "\n",
-    "iris = datasets.load_iris()\n",
-    "iris.data.shape, iris.target.shape\n",
-    "\n",
-    "X_train, X_test, y_train, y_test = train_test_split(\n",
-    "    iris.data, iris.target, test_size=0.4, random_state=0)\n",
-    "\n",
-    "X_train.shape, y_train.shape\n",
-    "\n",
-    "X_test.shape, y_test.shape\n",
-    "\n",
-    "\n",
-    "clf = svm.SVC(kernel='linear', C=1).fit(X_train, y_train)\n",
-    "clf.score(X_test, y_test)\n",
-    "\n",
-    "\n",
-    "from sklearn.model_selection import cross_val_score, cross_validate\n",
-    "clf = svm.SVC(kernel='linear', C=1)\n",
-    "scores = cross_validate(clf, iris.data, iris.target, cv=5, return_train_score=True)\n",
-    "scores  \n",
-    "# print(\"Accuracy: %0.2f (+/- %0.2f)\" % (scores.mean(), scores.std() * 2))\n",
-    "\n",
-    "\n",
-    "from sklearn.model_selection import cross_val_predict\n",
-    "from sklearn.metrics import accuracy_score\n",
-    "predicted = cross_val_predict(clf, iris.data, iris.target, cv=10)\n",
-    "accuracy_score(iris.target, predicted) \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Automatically created module for IPython interactive environment\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=0, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 1, 'gamma': 0.1}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.913 (+/-0.085) for {'C': 1, 'gamma': 0.01}\n",
-      "0.960 (+/-0.079) for {'C': 1, 'gamma': 0.1}\n",
-      "0.960 (+/-0.079) for {'C': 10, 'gamma': 0.01}\n",
-      "0.960 (+/-0.060) for {'C': 10, 'gamma': 0.1}\n",
-      "0.960 (+/-0.060) for {'C': 100, 'gamma': 0.01}\n",
-      "0.947 (+/-0.038) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=1, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 10, 'gamma': 0.1}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.927 (+/-0.101) for {'C': 1, 'gamma': 0.01}\n",
-      "0.947 (+/-0.064) for {'C': 1, 'gamma': 0.1}\n",
-      "0.940 (+/-0.086) for {'C': 10, 'gamma': 0.01}\n",
-      "0.960 (+/-0.027) for {'C': 10, 'gamma': 0.1}\n",
-      "0.960 (+/-0.027) for {'C': 100, 'gamma': 0.01}\n",
-      "0.933 (+/-0.080) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=2, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 100, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.920 (+/-0.039) for {'C': 1, 'gamma': 0.01}\n",
-      "0.960 (+/-0.060) for {'C': 1, 'gamma': 0.1}\n",
-      "0.960 (+/-0.060) for {'C': 10, 'gamma': 0.01}\n",
-      "0.967 (+/-0.059) for {'C': 10, 'gamma': 0.1}\n",
-      "0.973 (+/-0.066) for {'C': 100, 'gamma': 0.01}\n",
-      "0.953 (+/-0.070) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=3, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 10, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.940 (+/-0.117) for {'C': 1, 'gamma': 0.01}\n",
-      "0.960 (+/-0.060) for {'C': 1, 'gamma': 0.1}\n",
-      "0.967 (+/-0.044) for {'C': 10, 'gamma': 0.01}\n",
-      "0.960 (+/-0.046) for {'C': 10, 'gamma': 0.1}\n",
-      "0.960 (+/-0.046) for {'C': 100, 'gamma': 0.01}\n",
-      "0.940 (+/-0.059) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=4, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 10, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.913 (+/-0.042) for {'C': 1, 'gamma': 0.01}\n",
-      "0.967 (+/-0.022) for {'C': 1, 'gamma': 0.1}\n",
-      "0.973 (+/-0.037) for {'C': 10, 'gamma': 0.01}\n",
-      "0.967 (+/-0.044) for {'C': 10, 'gamma': 0.1}\n",
-      "0.973 (+/-0.038) for {'C': 100, 'gamma': 0.01}\n",
-      "0.947 (+/-0.037) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=5, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 10, 'gamma': 0.1}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.947 (+/-0.066) for {'C': 1, 'gamma': 0.01}\n",
-      "0.960 (+/-0.059) for {'C': 1, 'gamma': 0.1}\n",
-      "0.967 (+/-0.044) for {'C': 10, 'gamma': 0.01}\n",
-      "0.980 (+/-0.023) for {'C': 10, 'gamma': 0.1}\n",
-      "0.980 (+/-0.023) for {'C': 100, 'gamma': 0.01}\n",
-      "0.973 (+/-0.037) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=6, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 100, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.920 (+/-0.084) for {'C': 1, 'gamma': 0.01}\n",
-      "0.947 (+/-0.064) for {'C': 1, 'gamma': 0.1}\n",
-      "0.953 (+/-0.044) for {'C': 10, 'gamma': 0.01}\n",
-      "0.967 (+/-0.022) for {'C': 10, 'gamma': 0.1}\n",
-      "0.973 (+/-0.001) for {'C': 100, 'gamma': 0.01}\n",
-      "0.947 (+/-0.039) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=7, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 100, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.947 (+/-0.124) for {'C': 1, 'gamma': 0.01}\n",
-      "0.967 (+/-0.087) for {'C': 1, 'gamma': 0.1}\n",
-      "0.967 (+/-0.058) for {'C': 10, 'gamma': 0.01}\n",
-      "0.967 (+/-0.058) for {'C': 10, 'gamma': 0.1}\n",
-      "0.973 (+/-0.037) for {'C': 100, 'gamma': 0.01}\n",
-      "0.933 (+/-0.096) for {'C': 100, 'gamma': 0.1}\n",
-      "\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=8, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 10, 'gamma': 0.1}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.940 (+/-0.078) for {'C': 1, 'gamma': 0.01}\n",
-      "0.960 (+/-0.026) for {'C': 1, 'gamma': 0.1}\n",
-      "0.960 (+/-0.059) for {'C': 10, 'gamma': 0.01}\n",
-      "0.973 (+/-0.065) for {'C': 10, 'gamma': 0.1}\n",
-      "0.973 (+/-0.037) for {'C': 100, 'gamma': 0.01}\n",
-      "0.947 (+/-0.084) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=9, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 100, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.927 (+/-0.129) for {'C': 1, 'gamma': 0.01}\n",
-      "0.953 (+/-0.045) for {'C': 1, 'gamma': 0.1}\n",
-      "0.960 (+/-0.028) for {'C': 10, 'gamma': 0.01}\n",
-      "0.967 (+/-0.059) for {'C': 10, 'gamma': 0.1}\n",
-      "0.973 (+/-0.038) for {'C': 100, 'gamma': 0.01}\n",
-      "0.960 (+/-0.060) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=10, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 100, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.920 (+/-0.101) for {'C': 1, 'gamma': 0.01}\n",
-      "0.953 (+/-0.044) for {'C': 1, 'gamma': 0.1}\n",
-      "0.967 (+/-0.044) for {'C': 10, 'gamma': 0.01}\n",
-      "0.973 (+/-0.065) for {'C': 10, 'gamma': 0.1}\n",
-      "0.980 (+/-0.044) for {'C': 100, 'gamma': 0.01}\n",
-      "0.973 (+/-0.065) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=11, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 10, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.947 (+/-0.083) for {'C': 1, 'gamma': 0.01}\n",
-      "0.960 (+/-0.026) for {'C': 1, 'gamma': 0.1}\n",
-      "0.967 (+/-0.043) for {'C': 10, 'gamma': 0.01}\n",
-      "0.967 (+/-0.022) for {'C': 10, 'gamma': 0.1}\n",
-      "0.967 (+/-0.022) for {'C': 100, 'gamma': 0.01}\n",
-      "0.947 (+/-0.037) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=12, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 1, 'gamma': 0.1}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.927 (+/-0.069) for {'C': 1, 'gamma': 0.01}\n",
-      "0.973 (+/-0.037) for {'C': 1, 'gamma': 0.1}\n",
-      "0.967 (+/-0.022) for {'C': 10, 'gamma': 0.01}\n",
-      "0.960 (+/-0.027) for {'C': 10, 'gamma': 0.1}\n",
-      "0.967 (+/-0.022) for {'C': 100, 'gamma': 0.01}\n",
-      "0.940 (+/-0.024) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=13, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 10, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.920 (+/-0.091) for {'C': 1, 'gamma': 0.01}\n",
-      "0.973 (+/-0.037) for {'C': 1, 'gamma': 0.1}\n",
-      "0.980 (+/-0.044) for {'C': 10, 'gamma': 0.01}\n",
-      "0.960 (+/-0.059) for {'C': 10, 'gamma': 0.1}\n",
-      "0.973 (+/-0.053) for {'C': 100, 'gamma': 0.01}\n",
-      "0.947 (+/-0.065) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=14, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 100, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.920 (+/-0.086) for {'C': 1, 'gamma': 0.01}\n",
-      "0.960 (+/-0.027) for {'C': 1, 'gamma': 0.1}\n",
-      "0.960 (+/-0.027) for {'C': 10, 'gamma': 0.01}\n",
-      "0.967 (+/-0.022) for {'C': 10, 'gamma': 0.1}\n",
-      "0.980 (+/-0.044) for {'C': 100, 'gamma': 0.01}\n",
-      "0.960 (+/-0.059) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=15, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 1, 'gamma': 0.1}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.953 (+/-0.044) for {'C': 1, 'gamma': 0.01}\n",
-      "0.973 (+/-0.037) for {'C': 1, 'gamma': 0.1}\n",
-      "0.973 (+/-0.037) for {'C': 10, 'gamma': 0.01}\n",
-      "0.973 (+/-0.038) for {'C': 10, 'gamma': 0.1}\n",
-      "0.973 (+/-0.038) for {'C': 100, 'gamma': 0.01}\n",
-      "0.953 (+/-0.059) for {'C': 100, 'gamma': 0.1}\n",
-      "\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=16, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 10, 'gamma': 0.1}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.900 (+/-0.088) for {'C': 1, 'gamma': 0.01}\n",
-      "0.953 (+/-0.024) for {'C': 1, 'gamma': 0.1}\n",
-      "0.960 (+/-0.027) for {'C': 10, 'gamma': 0.01}\n",
-      "0.973 (+/-0.037) for {'C': 10, 'gamma': 0.1}\n",
-      "0.973 (+/-0.037) for {'C': 100, 'gamma': 0.01}\n",
-      "0.940 (+/-0.057) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=17, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 100, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.920 (+/-0.084) for {'C': 1, 'gamma': 0.01}\n",
-      "0.967 (+/-0.059) for {'C': 1, 'gamma': 0.1}\n",
-      "0.967 (+/-0.059) for {'C': 10, 'gamma': 0.01}\n",
-      "0.967 (+/-0.044) for {'C': 10, 'gamma': 0.1}\n",
-      "0.973 (+/-0.037) for {'C': 100, 'gamma': 0.01}\n",
-      "0.940 (+/-0.043) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=18, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 1, 'gamma': 0.1}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.927 (+/-0.059) for {'C': 1, 'gamma': 0.01}\n",
-      "0.973 (+/-0.054) for {'C': 1, 'gamma': 0.1}\n",
-      "0.973 (+/-0.054) for {'C': 10, 'gamma': 0.01}\n",
-      "0.967 (+/-0.045) for {'C': 10, 'gamma': 0.1}\n",
-      "0.973 (+/-0.038) for {'C': 100, 'gamma': 0.01}\n",
-      "0.953 (+/-0.070) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=19, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 100, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.907 (+/-0.057) for {'C': 1, 'gamma': 0.01}\n",
-      "0.967 (+/-0.057) for {'C': 1, 'gamma': 0.1}\n",
-      "0.967 (+/-0.043) for {'C': 10, 'gamma': 0.01}\n",
-      "0.967 (+/-0.022) for {'C': 10, 'gamma': 0.1}\n",
-      "0.980 (+/-0.023) for {'C': 100, 'gamma': 0.01}\n",
-      "0.960 (+/-0.027) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=20, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 100, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.893 (+/-0.107) for {'C': 1, 'gamma': 0.01}\n",
-      "0.953 (+/-0.059) for {'C': 1, 'gamma': 0.1}\n",
-      "0.967 (+/-0.059) for {'C': 10, 'gamma': 0.01}\n",
-      "0.973 (+/-0.038) for {'C': 10, 'gamma': 0.1}\n",
-      "0.980 (+/-0.023) for {'C': 100, 'gamma': 0.01}\n",
-      "0.953 (+/-0.080) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=21, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 100, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.947 (+/-0.038) for {'C': 1, 'gamma': 0.01}\n",
-      "0.973 (+/-0.065) for {'C': 1, 'gamma': 0.1}\n",
-      "0.980 (+/-0.044) for {'C': 10, 'gamma': 0.01}\n",
-      "0.980 (+/-0.044) for {'C': 10, 'gamma': 0.1}\n",
-      "0.987 (+/-0.046) for {'C': 100, 'gamma': 0.01}\n",
-      "0.973 (+/-0.065) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=22, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 10, 'gamma': 0.1}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.913 (+/-0.078) for {'C': 1, 'gamma': 0.01}\n",
-      "0.940 (+/-0.044) for {'C': 1, 'gamma': 0.1}\n",
-      "0.953 (+/-0.043) for {'C': 10, 'gamma': 0.01}\n",
-      "0.960 (+/-0.059) for {'C': 10, 'gamma': 0.1}\n",
-      "0.953 (+/-0.043) for {'C': 100, 'gamma': 0.01}\n",
-      "0.960 (+/-0.045) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=23, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 10, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.940 (+/-0.057) for {'C': 1, 'gamma': 0.01}\n",
-      "0.960 (+/-0.027) for {'C': 1, 'gamma': 0.1}\n",
-      "0.967 (+/-0.044) for {'C': 10, 'gamma': 0.01}\n",
-      "0.967 (+/-0.022) for {'C': 10, 'gamma': 0.1}\n",
-      "0.967 (+/-0.022) for {'C': 100, 'gamma': 0.01}\n",
-      "0.947 (+/-0.091) for {'C': 100, 'gamma': 0.1}\n",
-      "\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=24, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 10, 'gamma': 0.1}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.907 (+/-0.048) for {'C': 1, 'gamma': 0.01}\n",
-      "0.953 (+/-0.070) for {'C': 1, 'gamma': 0.1}\n",
-      "0.967 (+/-0.059) for {'C': 10, 'gamma': 0.01}\n",
-      "0.973 (+/-0.037) for {'C': 10, 'gamma': 0.1}\n",
-      "0.973 (+/-0.037) for {'C': 100, 'gamma': 0.01}\n",
-      "0.947 (+/-0.066) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=25, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 100, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.913 (+/-0.069) for {'C': 1, 'gamma': 0.01}\n",
-      "0.953 (+/-0.043) for {'C': 1, 'gamma': 0.1}\n",
-      "0.967 (+/-0.022) for {'C': 10, 'gamma': 0.01}\n",
-      "0.967 (+/-0.022) for {'C': 10, 'gamma': 0.1}\n",
-      "0.980 (+/-0.044) for {'C': 100, 'gamma': 0.01}\n",
-      "0.953 (+/-0.068) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=26, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 1, 'gamma': 0.1}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.907 (+/-0.091) for {'C': 1, 'gamma': 0.01}\n",
-      "0.967 (+/-0.059) for {'C': 1, 'gamma': 0.1}\n",
-      "0.967 (+/-0.059) for {'C': 10, 'gamma': 0.01}\n",
-      "0.960 (+/-0.060) for {'C': 10, 'gamma': 0.1}\n",
-      "0.967 (+/-0.059) for {'C': 100, 'gamma': 0.01}\n",
-      "0.960 (+/-0.060) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=27, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 1, 'gamma': 0.1}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.947 (+/-0.001) for {'C': 1, 'gamma': 0.01}\n",
-      "0.980 (+/-0.044) for {'C': 1, 'gamma': 0.1}\n",
-      "0.980 (+/-0.044) for {'C': 10, 'gamma': 0.01}\n",
-      "0.980 (+/-0.023) for {'C': 10, 'gamma': 0.1}\n",
-      "0.973 (+/-0.037) for {'C': 100, 'gamma': 0.01}\n",
-      "0.967 (+/-0.044) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=28, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 100, 'gamma': 0.01}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.933 (+/-0.060) for {'C': 1, 'gamma': 0.01}\n",
-      "0.960 (+/-0.060) for {'C': 1, 'gamma': 0.1}\n",
-      "0.960 (+/-0.060) for {'C': 10, 'gamma': 0.01}\n",
-      "0.960 (+/-0.060) for {'C': 10, 'gamma': 0.1}\n",
-      "0.973 (+/-0.037) for {'C': 100, 'gamma': 0.01}\n",
-      "0.960 (+/-0.089) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "clf.params:  {'error_score': 'raise', 'estimator__probability': False, 'estimator__gamma': 'auto', 'estimator__class_weight': None, 'pre_dispatch': '2*n_jobs', 'estimator__random_state': None, 'estimator': SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-      "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-      "  tol=0.001, verbose=False), 'estimator__tol': 0.001, 'estimator__shrinking': True, 'n_jobs': 1, 'param_grid': {'C': [1, 10, 100], 'gamma': [0.01, 0.1]}, 'estimator__max_iter': -1, 'estimator__verbose': False, 'iid': True, 'estimator__degree': 3, 'estimator__C': 1.0, 'fit_params': None, 'estimator__kernel': 'rbf', 'cv': KFold(n_splits=4, random_state=29, shuffle=True), 'scoring': None, 'verbose': 0, 'refit': True, 'return_train_score': 'warn', 'estimator__decision_function_shape': 'ovr', 'estimator__coef0': 0.0, 'estimator__cache_size': 200}\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'C': 10, 'gamma': 0.1}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.940 (+/-0.022) for {'C': 1, 'gamma': 0.01}\n",
-      "0.967 (+/-0.022) for {'C': 1, 'gamma': 0.1}\n",
-      "0.973 (+/-0.001) for {'C': 10, 'gamma': 0.01}\n",
-      "0.980 (+/-0.044) for {'C': 10, 'gamma': 0.1}\n",
-      "0.980 (+/-0.044) for {'C': 100, 'gamma': 0.01}\n",
-      "0.953 (+/-0.043) for {'C': 100, 'gamma': 0.1}\n",
-      "\n",
-      "Average difference of 0.007742 with std. dev. of 0.007688.\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcc5671eb38>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from sklearn.datasets import load_iris\n",
-    "from matplotlib import pyplot as plt\n",
-    "from sklearn.svm import SVC\n",
-    "from sklearn.model_selection import GridSearchCV, cross_val_score, KFold\n",
-    "import numpy as np\n",
-    "\n",
-    "print(__doc__)\n",
-    "\n",
-    "# Number of random trials\n",
-    "NUM_TRIALS = 30\n",
-    "\n",
-    "# Load the dataset\n",
-    "iris = load_iris()\n",
-    "X_iris = iris.data\n",
-    "y_iris = iris.target\n",
-    "\n",
-    "# Set up possible values of parameters to optimize over\n",
-    "p_grid = {\"C\": [1, 10, 100],\n",
-    "          \"gamma\": [.01, .1]}\n",
-    "\n",
-    "# We will use a Support Vector Classifier with \"rbf\" kernel\n",
-    "svm = SVC(kernel=\"rbf\")\n",
-    "\n",
-    "# Arrays to store scores\n",
-    "non_nested_scores = np.zeros(NUM_TRIALS)\n",
-    "nested_scores = np.zeros(NUM_TRIALS)\n",
-    "\n",
-    "# Loop for each trial\n",
-    "for i in range(NUM_TRIALS):\n",
-    "\n",
-    "    # Choose cross-validation techniques for the inner and outer loops,\n",
-    "    # independently of the dataset.\n",
-    "    # E.g \"LabelKFold\", \"LeaveOneOut\", \"LeaveOneLabelOut\", etc.\n",
-    "    inner_cv = KFold(n_splits=4, shuffle=True, random_state=i)\n",
-    "    outer_cv = KFold(n_splits=4, shuffle=True, random_state=i)\n",
-    "\n",
-    "    # Non_nested parameter search and scoring\n",
-    "    clf = GridSearchCV(estimator=svm, param_grid=p_grid, cv=inner_cv)\n",
-    "    clf.fit(X_iris, y_iris)\n",
-    "    print('clf.params: ', clf.get_params())\n",
-    "    print()\n",
-    "    non_nested_scores[i] = clf.best_score_\n",
-    "    \n",
-    "    print(\"Best parameters set found on development set:\")\n",
-    "    print()\n",
-    "    print(clf.best_params_)\n",
-    "    print()\n",
-    "    print(\"Grid scores on development set:\")\n",
-    "    print()\n",
-    "    means = clf.cv_results_['mean_test_score']\n",
-    "    stds = clf.cv_results_['std_test_score']\n",
-    "    for mean, std, params in zip(means, stds, clf.cv_results_['params']):\n",
-    "        print(\"%0.3f (+/-%0.03f) for %r\"\n",
-    "              % (mean, std * 2, params))\n",
-    "    print()\n",
-    "\n",
-    "    # Nested CV with parameter optimization\n",
-    "    nested_score = cross_val_score(clf, X=X_iris, y=y_iris, cv=outer_cv)\n",
-    "    nested_scores[i] = nested_score.mean()\n",
-    "\n",
-    "score_difference = non_nested_scores - nested_scores\n",
-    "\n",
-    "print(\"Average difference of {0:6f} with std. dev. of {1:6f}.\"\n",
-    "      .format(score_difference.mean(), score_difference.std()))\n",
-    "\n",
-    "# Plot scores on each trial for nested and non-nested CV\n",
-    "plt.figure()\n",
-    "plt.subplot(211)\n",
-    "non_nested_scores_line, = plt.plot(non_nested_scores, color='r')\n",
-    "nested_line, = plt.plot(nested_scores, color='b')\n",
-    "plt.ylabel(\"score\", fontsize=\"14\")\n",
-    "plt.legend([non_nested_scores_line, nested_line],\n",
-    "           [\"Non-Nested CV\", \"Nested CV\"],\n",
-    "           bbox_to_anchor=(0, .4, .5, 0))\n",
-    "plt.title(\"Non-Nested and Nested Cross Validation on Iris Dataset\",\n",
-    "          x=.5, y=1.1, fontsize=\"15\")\n",
-    "\n",
-    "# Plot bar chart of the difference.\n",
-    "plt.subplot(212)\n",
-    "difference_plot = plt.bar(range(NUM_TRIALS), score_difference)\n",
-    "plt.xlabel(\"Individual Trial #\")\n",
-    "plt.legend([difference_plot],\n",
-    "           [\"Non-Nested CV - Nested CV Score\"],\n",
-    "           bbox_to_anchor=(0, 1, .8, 0))\n",
-    "plt.ylabel(\"score difference\", fontsize=\"14\")\n",
-    "\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/.ipynb_checkpoints/test_scikit_ksvm-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/test_scikit_ksvm-checkpoint.ipynb
deleted file mode 100644
index e9abd47..0000000
--- a/notebooks/.ipynb_checkpoints/test_scikit_ksvm-checkpoint.ipynb
+++ /dev/null
@@ -1,1271 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Automatically created module for IPython interactive environment\n",
-      "[[ 0.  0.  1. ... 10.  0.  0.]\n",
-      " [ 0.  0.  2. ...  0.  0.  0.]\n",
-      " [ 0.  0.  5. ... 16.  2.  0.]\n",
-      " ...\n",
-      " [ 0.  0.  5. ...  0.  0.  0.]\n",
-      " [ 0.  0.  4. ...  0.  0.  0.]\n",
-      " [ 0.  0.  6. ... 11.  0.  0.]]\n",
-      "[1 4 9 0 4 1 1 5 9 1 4 2 6 3 9 7 6 4 8 6 8 7 6 0 5 9 4 7 3 4 9 4 9 7 9 1 5\n",
-      " 6 0 0 4 3 6 1 0 9 4 8 7 5 9 8 4 5 0 1 6 0 5 5 0 4 3 2 8 7 6 3 4 2 5 8 0 6\n",
-      " 9 4 5 4 9 7 3 3 1 4 4 2 6 8 1 1 0 3 7 4 6 7 4 0 5 2 9 2 1 9 2 3 1 7 7 4 5\n",
-      " 6 5 6 7 8 1 4 3 4 4 3 5 3 3 4 7 9 8 0 6 1 9 0 8 4 1 2 3 9 7 8 8 8 3 7 5 7\n",
-      " 0 1 7 8 3 8 0 4 8 6 2 3 6 7 3 7 7 1 3 5 0 9 8 5 3 1 2 0 3 6 0 3 4 1 2 3 1\n",
-      " 0 5 8 9 3 9 6 6 8 9 0 7 8 2 0 0 7 7 4 5 3 1 8 5 9 6 2 9 7 7 9 5 4 2 6 6 1\n",
-      " 3 4 7 2 8 0 6 1 6 6 5 8 4 3 0 5 2 9 9 7 8 0 5 0 6 3 3 5 1 5 1 7 9 6 4 5 0\n",
-      " 1 8 7 8 8 8 9 8 7 7 2 2 2 8 0 7 8 6 8 0 4 2 2 3 7 9 0 2 0 0 2 7 1 5 6 4 0\n",
-      " 0 5 5 3 9 6 1 6 0 6 4 0 1 8 2 2 3 7 6 1 1 2 4 7 4 9 4 3 0 4 3 1 3 0 9 4 6\n",
-      " 0 3 2 6 2 5 6 7 8 8 4 4 6 9 4 5 4 5 7 1 9 6 8 0 4 1 9 9 7 1 8 5 0 8 7 7 2\n",
-      " 1 3 7 4 0 6 3 1 2 9 9 2 5 7 3 0 6 1 6 1 1 2 5 5 3 2 8 5 0 9 6 9 8 4 5 8 1\n",
-      " 6 3 0 4 6 1 8 3 4 7 1 0 7 9 2 7 2 1 6 9 3 1 3 2 4 3 4 3 3 5 4 7 3 6 7 0 0\n",
-      " 1 1 0 2 0 7 7 4 7 2 0 1 2 4 8 1 6 0 3 4 0 6 8 4 4 9 0 8 4 6 8 7 8 2 8 1 6\n",
-      " 6 9 5 3 8 5 1 3 3 1 8 8 3 0 4 1 7 2 7 4 0 4 2 7 7 9 1 9 0 9 3 8 6 2 5 3 3\n",
-      " 7 2 1 0 8 7 7 3 1 2 4 5 7 7 9 1 5 5 2 8 7 9 4 7 0 2 6 1 3 1 3 7 3 6 7 1 6\n",
-      " 6 1 0 6 9 7 7 4 4 9 1 5 1 1 7 2 6 6 4 3 1 0 5 3 9 5 8 1 7 9 9 8 2 1 0 6 6\n",
-      " 4 4 7 8 6 5 8 8 2 2 2 9 8 8 3 6 0 4 4 7 6 6 9 0 4 6 8 5 1 9 9 3 1 6 5 9 7\n",
-      " 3 4 4 2 4 4 9 2 9 9 7 2 3 3 3 7 2 7 8 1 0 5 6 6 8 0 7 0 4 2 6 6 8 6 4 7 7\n",
-      " 0 3 0 7 4 0 0 2 1 8 4 2 2 9 9 3 3 4 4 2 6 3 7 2 8 4 2 9 5 1 9 0 9 7 2 6 2\n",
-      " 1 6 9 9 3 8 3 6 2 2 4 9 3 4 6 8 6 1 7 4 1 4 7 0 1 5 6 2 7 8 4 9 0 9 0 5 2\n",
-      " 2 4 1 8 8 7 2 9 7 0 0 6 0 5 0 5 1 0 8 6 6 0 3 4 0 3 5 6 9 8 4 8 5 2 7 5 5\n",
-      " 1 1 8 9 0 3 4 9 2 9 3 1 7 5 4 9 5 7 7 7 0 1 9 1 9 7 1 3 9 4 9 2 5 3 5 6 2\n",
-      " 3 0 7 3 2 5 2 6 1 7 0 2 9 4 2 0 7 4 4 9 0 4 9 6 8 2 6 4 4 9 1 2 4 7 8 8 2\n",
-      " 2 5 9 5 4 3 1 4 7 1 5 3 8 6 5 5 2 1 0 9 1 6 9 3 7 4 5 6 3 6 5 2 7 6 3 4 1\n",
-      " 1 4 8 4 5 3 3 7 7 8]\n",
-      "# Tuning hyper-parameters for precision\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'gamma': 0.001, 'kernel': 'rbf', 'C': 10}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.986 (+/-0.016) for {'gamma': 0.001, 'kernel': 'rbf', 'C': 1}\n",
-      "0.959 (+/-0.029) for {'gamma': 0.0001, 'kernel': 'rbf', 'C': 1}\n",
-      "0.988 (+/-0.017) for {'gamma': 0.001, 'kernel': 'rbf', 'C': 10}\n",
-      "0.982 (+/-0.026) for {'gamma': 0.0001, 'kernel': 'rbf', 'C': 10}\n",
-      "0.988 (+/-0.017) for {'gamma': 0.001, 'kernel': 'rbf', 'C': 100}\n",
-      "0.982 (+/-0.025) for {'gamma': 0.0001, 'kernel': 'rbf', 'C': 100}\n",
-      "0.988 (+/-0.017) for {'gamma': 0.001, 'kernel': 'rbf', 'C': 1000}\n",
-      "0.982 (+/-0.025) for {'gamma': 0.0001, 'kernel': 'rbf', 'C': 1000}\n",
-      "0.975 (+/-0.014) for {'kernel': 'linear', 'C': 1}\n",
-      "0.975 (+/-0.014) for {'kernel': 'linear', 'C': 10}\n",
-      "0.975 (+/-0.014) for {'kernel': 'linear', 'C': 100}\n",
-      "0.975 (+/-0.014) for {'kernel': 'linear', 'C': 1000}\n",
-      "\n",
-      "Detailed classification report:\n",
-      "\n",
-      "The model is trained on the full development set.\n",
-      "The scores are computed on the full evaluation set.\n",
-      "\n",
-      "             precision    recall  f1-score   support\n",
-      "\n",
-      "          0       1.00      1.00      1.00        89\n",
-      "          1       0.97      1.00      0.98        90\n",
-      "          2       0.99      0.98      0.98        92\n",
-      "          3       1.00      0.99      0.99        93\n",
-      "          4       1.00      1.00      1.00        76\n",
-      "          5       0.99      0.98      0.99       108\n",
-      "          6       0.99      1.00      0.99        89\n",
-      "          7       0.99      1.00      0.99        78\n",
-      "          8       1.00      0.98      0.99        92\n",
-      "          9       0.99      0.99      0.99        92\n",
-      "\n",
-      "avg / total       0.99      0.99      0.99       899\n",
-      "\n",
-      "\n",
-      "# Tuning hyper-parameters for recall\n",
-      "\n",
-      "Best parameters set found on development set:\n",
-      "\n",
-      "{'gamma': 0.001, 'kernel': 'rbf', 'C': 10}\n",
-      "\n",
-      "Grid scores on development set:\n",
-      "\n",
-      "0.986 (+/-0.019) for {'gamma': 0.001, 'kernel': 'rbf', 'C': 1}\n",
-      "0.957 (+/-0.029) for {'gamma': 0.0001, 'kernel': 'rbf', 'C': 1}\n",
-      "0.987 (+/-0.019) for {'gamma': 0.001, 'kernel': 'rbf', 'C': 10}\n",
-      "0.981 (+/-0.028) for {'gamma': 0.0001, 'kernel': 'rbf', 'C': 10}\n",
-      "0.987 (+/-0.019) for {'gamma': 0.001, 'kernel': 'rbf', 'C': 100}\n",
-      "0.981 (+/-0.026) for {'gamma': 0.0001, 'kernel': 'rbf', 'C': 100}\n",
-      "0.987 (+/-0.019) for {'gamma': 0.001, 'kernel': 'rbf', 'C': 1000}\n",
-      "0.981 (+/-0.026) for {'gamma': 0.0001, 'kernel': 'rbf', 'C': 1000}\n",
-      "0.972 (+/-0.012) for {'kernel': 'linear', 'C': 1}\n",
-      "0.972 (+/-0.012) for {'kernel': 'linear', 'C': 10}\n",
-      "0.972 (+/-0.012) for {'kernel': 'linear', 'C': 100}\n",
-      "0.972 (+/-0.012) for {'kernel': 'linear', 'C': 1000}\n",
-      "\n",
-      "Detailed classification report:\n",
-      "\n",
-      "The model is trained on the full development set.\n",
-      "The scores are computed on the full evaluation set.\n",
-      "\n",
-      "             precision    recall  f1-score   support\n",
-      "\n",
-      "          0       1.00      1.00      1.00        89\n",
-      "          1       0.97      1.00      0.98        90\n",
-      "          2       0.99      0.98      0.98        92\n",
-      "          3       1.00      0.99      0.99        93\n",
-      "          4       1.00      1.00      1.00        76\n",
-      "          5       0.99      0.98      0.99       108\n",
-      "          6       0.99      1.00      0.99        89\n",
-      "          7       0.99      1.00      0.99        78\n",
-      "          8       1.00      0.98      0.99        92\n",
-      "          9       0.99      0.99      0.99        92\n",
-      "\n",
-      "avg / total       0.99      0.99      0.99       899\n",
-      "\n",
-      "\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Parameter estimation using grid search with cross-validation\n",
-    "from __future__ import print_function\n",
-    "\n",
-    "from sklearn import datasets\n",
-    "from sklearn.model_selection import train_test_split\n",
-    "from sklearn.model_selection import GridSearchCV\n",
-    "from sklearn.metrics import classification_report\n",
-    "from sklearn.svm import SVC\n",
-    "\n",
-    "print(__doc__)\n",
-    "\n",
-    "# Loading the Digits dataset\n",
-    "digits = datasets.load_digits()\n",
-    "\n",
-    "# To apply an classifier on this data, we need to flatten the image, to\n",
-    "# turn the data in a (samples, feature) matrix:\n",
-    "n_samples = len(digits.images)\n",
-    "X = digits.images.reshape((n_samples, -1))\n",
-    "y = digits.target\n",
-    "\n",
-    "# Split the dataset in two equal parts\n",
-    "X_train, X_test, y_train, y_test = train_test_split(\n",
-    "    X, y, test_size=0.5, random_state=0)\n",
-    "print(X_train)\n",
-    "print(y_train)\n",
-    "\n",
-    "# Set the parameters by cross-validation\n",
-    "tuned_parameters = [{'kernel': ['precomputed'], \n",
-    "                     'alpha': np.logspace(-10, 10, num = 21, base = 10)}]\n",
-    "\n",
-    "scores = ['precision', 'recall']\n",
-    "\n",
-    "for score in scores:\n",
-    "    print(\"# Tuning hyper-parameters for %s\" % score)\n",
-    "    print()\n",
-    "\n",
-    "    clf = GridSearchCV(SVC(), tuned_parameters, cv=5,\n",
-    "                       scoring='%s_macro' % score)\n",
-    "    clf.fit(X_train, y_train)\n",
-    "\n",
-    "    print(\"Best parameters set found on development set:\")\n",
-    "    print()\n",
-    "    print(clf.best_params_)\n",
-    "    print()\n",
-    "    print(\"Grid scores on development set:\")\n",
-    "    print()\n",
-    "    means = clf.cv_results_['mean_test_score']\n",
-    "    stds = clf.cv_results_['std_test_score']\n",
-    "    for mean, std, params in zip(means, stds, clf.cv_results_['params']):\n",
-    "        print(\"%0.3f (+/-%0.03f) for %r\"\n",
-    "              % (mean, std * 2, params))\n",
-    "    print()\n",
-    "\n",
-    "    print(\"Detailed classification report:\")\n",
-    "    print()\n",
-    "    print(\"The model is trained on the full development set.\")\n",
-    "    print(\"The scores are computed on the full evaluation set.\")\n",
-    "    print()\n",
-    "    y_true, y_pred = y_test, clf.predict(X_test)\n",
-    "    print(classification_report(y_true, y_pred))\n",
-    "    print()\n",
-    "\n",
-    "# Note the problem is too easy: the hyperparameter plateau is too flat and the\n",
-    "# output model is the same for precision and recall with ties in quality."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "GridSearchCV(cv=None, error_score='raise',\n",
-       "       estimator=SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
-       "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
-       "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
-       "  tol=0.001, verbose=False),\n",
-       "       fit_params=None, iid=True, n_jobs=1,\n",
-       "       param_grid={'C': [1, 10], 'kernel': ('linear', 'rbf')},\n",
-       "       pre_dispatch='2*n_jobs', refit=True, return_train_score='warn',\n",
-       "       scoring=None, verbose=0)"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from sklearn import svm, datasets\n",
-    "from sklearn.model_selection import GridSearchCV\n",
-    "iris = datasets.load_iris()\n",
-    "parameters = {'kernel': ('linear', 'rbf'), 'C': [1, 10]}\n",
-    "svc = svm.SVC()\n",
-    "clf = GridSearchCV(svc, parameters)\n",
-    "clf.fit(iris.data, iris.target)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['mean_fit_time',\n",
-       " 'mean_score_time',\n",
-       " 'mean_test_score',\n",
-       " 'mean_train_score',\n",
-       " 'param_C',\n",
-       " 'param_kernel',\n",
-       " 'params',\n",
-       " 'rank_test_score',\n",
-       " 'split0_test_score',\n",
-       " 'split0_train_score',\n",
-       " 'split1_test_score',\n",
-       " 'split1_train_score',\n",
-       " 'split2_test_score',\n",
-       " 'split2_train_score',\n",
-       " 'std_fit_time',\n",
-       " 'std_score_time',\n",
-       " 'std_test_score',\n",
-       " 'std_train_score']"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "sorted(clf.cv_results_.keys())"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "dict_values([array([0.98      , 0.97333333, 0.97333333, 0.98      ]), array([1.        , 0.98039216, 1.        , 0.98039216]), array([0.00030899, 0.00021172, 0.00019932, 0.00017134]), array([1, 3, 3, 1], dtype=int32), array([0.01617914, 0.00902067, 0.03715363, 0.01592466]), masked_array(data=['linear', 'rbf', 'linear', 'rbf'],\n",
-       "             mask=[False, False, False, False],\n",
-       "       fill_value='?',\n",
-       "            dtype=object), array([1., 1., 1., 1.]), array([0.98999802, 0.98336304, 0.97999604, 0.97999604]), array([6.43618303e-05, 6.20771049e-05, 7.16528819e-05, 9.16456815e-06]), array([0.97979798, 0.96969697, 0.95959596, 0.95959596]), [{'kernel': 'linear', 'C': 1}, {'kernel': 'rbf', 'C': 1}, {'kernel': 'linear', 'C': 10}, {'kernel': 'rbf', 'C': 10}], array([0.00036526, 0.00039411, 0.0002923 , 0.00032218]), array([0.00824863, 0.01254825, 0.01649726, 0.01649726]), array([0.97916667, 0.97916667, 1.        , 1.        ]), array([0.99019608, 0.98039216, 0.98039216, 0.98039216]), array([5.54407363e-05, 3.25514857e-05, 7.09833681e-05, 3.70551530e-06]), masked_array(data=[1, 1, 10, 10],\n",
-       "             mask=[False, False, False, False],\n",
-       "       fill_value='?',\n",
-       "            dtype=object), array([0.96078431, 0.96078431, 0.92156863, 0.96078431])])"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "clf.cv_results_.values()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "print(__doc__)\n",
-    "\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "from sklearn import svm, datasets\n",
-    "\n",
-    "# import some data to play with\n",
-    "iris = datasets.load_iris()\n",
-    "X = iris.data[:, :2]  # we only take the first two features. We could\n",
-    "                      # avoid this ugly slicing by using a two-dim dataset\n",
-    "Y = iris.target\n",
-    "\n",
-    "\n",
-    "def my_kernel(X, Y):\n",
-    "    \"\"\"\n",
-    "    We create a custom kernel:\n",
-    "\n",
-    "                 (2  0)\n",
-    "    k(X, Y) = X  (    ) Y.T\n",
-    "                 (0  1)\n",
-    "    \"\"\"\n",
-    "    M = np.array([[2, 0], [0, 1.0]])\n",
-    "    return np.dot(np.dot(X, M), Y.T)\n",
-    "\n",
-    "\n",
-    "h = .02  # step size in the mesh\n",
-    "\n",
-    "# we create an instance of SVM and fit out data.\n",
-    "clf = svm.SVC(kernel=my_kernel)\n",
-    "clf.fit(X, Y)\n",
-    "\n",
-    "# Plot the decision boundary. For that, we will assign a color to each\n",
-    "# point in the mesh [x_min, x_max]x[y_min, y_max].\n",
-    "x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1\n",
-    "y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1\n",
-    "xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))\n",
-    "Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])\n",
-    "\n",
-    "# Put the result into a color plot\n",
-    "Z = Z.reshape(xx.shape)\n",
-    "plt.pcolormesh(xx, yy, Z, cmap=plt.cm.Paired)\n",
-    "\n",
-    "# Plot also the training points\n",
-    "plt.scatter(X[:, 0], X[:, 1], c=Y, cmap=plt.cm.Paired, edgecolors='k')\n",
-    "plt.title('3-Class classification using Support Vector Machine with custom'\n",
-    "          ' kernel')\n",
-    "plt.axis('tight')\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 69,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "- This script take as input a kernel matrix\n",
-      "and returns the classification or regression performance\n",
-      "- The kernel matrix can be calculated using any of the graph kernels approaches\n",
-      "- The criteria used for prediction are SVM for classification and kernel Ridge regression for regression\n",
-      "- For predition we divide the data in training, validation and test. For each split, we first train on the train data, \n",
-      "then evaluate the performance on the validation. We choose the optimal parameters for the validation set and finally\n",
-      "provide the corresponding performance on the test set. If more than one split is performed, the final results \n",
-      "correspond to the average of the performances on the test sets. \n",
-      "\n",
-      "@references\n",
-      "    https://github.com/eghisu/GraphKernels/blob/master/GraphKernelsCollection/python_scripts/compute_perf_gk.py\n",
-      "\n",
-      "\n",
-      " Loading dataset from file...\n",
-      "[ -23.7   14.    37.3  109.7   10.8   39.    42.    66.6  135.   148.5\n",
-      "   40.    34.6   32.    63.    53.5   67.    64.4   84.7   95.5   92.\n",
-      "   84.4  154.   156.   166.   183.    70.3   63.6   52.5   59.    59.5\n",
-      "   55.2   88.    83.   104.5  102.    92.   107.4  123.2  112.5  118.5\n",
-      "  101.5  173.7  165.5  181.    99.5   92.3   90.1   80.2   82.    91.2\n",
-      "   91.5   81.2   93.    69.    86.3   82.   103.   103.5   96.   112.   104.\n",
-      "  132.5  123.5  120.3  145.   144.2  142.8  132.   134.2  137.   139.\n",
-      "  133.6  120.4  120.   137.   195.8  177.2  181.   185.9  175.7  186.   211.\n",
-      "  125.   118.   117.1  107.   102.5  112.    97.4   91.5   87.6  106.5\n",
-      "  101.    99.3   90.   137.   114.   126.   124.   140.5  157.5  146.   145.\n",
-      "  141.   171.   166.   155.   145.   159.   138.   142.   159.   163.5\n",
-      "  229.5  142.   125.   132.   130.5  125.   122.   121.   122.2  112.   106.\n",
-      "  114.5  151.   128.5  109.5  126.   147.   158.   147.   165.   188.9\n",
-      "  170.   178.   148.5  165.   177.   167.   195.   226.   215.   201.   205.\n",
-      "  151.5  165.5  157.   139.   163.   153.5  139.   162.   173.   159.5\n",
-      "  159.5  155.5  141.   126.   164.   163.   166.5  146.   165.   159.   195.\n",
-      "  218.   250.   235.   186.5  156.5  162.   162.   170.2  173.2  186.8\n",
-      "  173.   187.   174.   188.5  199.   228.   215.   216.   240. ]\n",
-      "\n",
-      " Loading the matrix from file...\n",
-      "[[  3.   1.   3. ...,   1.   1.   1.]\n",
-      " [  1.   6.   1. ...,   0.   0.   3.]\n",
-      " [  3.   1.   3. ...,   1.   1.   1.]\n",
-      " ..., \n",
-      " [  1.   0.   1. ...,  55.  21.   7.]\n",
-      " [  1.   0.   1. ...,  21.  55.   7.]\n",
-      " [  1.   3.   1. ...,   7.   7.  55.]]\n",
-      "--- This is a regression problem ---\n",
-      "Starting split 10...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 12 with parameter alpha = 12.130000\n",
-      "The best performance on the validation set is: 36.004721\n",
-      "The corresponding performance on test set is: 47.691725\n",
-      "Starting split 11...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 33.084913\n",
-      "The corresponding performance on test set is: 35.493699\n",
-      "Starting split 12...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 18 with parameter alpha = 18.190000\n",
-      "The best performance on the validation set is: 29.476238\n",
-      "The corresponding performance on test set is: 36.525571\n",
-      "Starting split 13...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 9 with parameter alpha = 9.100000\n",
-      "The best performance on the validation set is: 40.272791\n",
-      "The corresponding performance on test set is: 37.359205\n",
-      "Starting split 14...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 42.973240\n",
-      "The corresponding performance on test set is: 53.123785\n",
-      "Starting split 15...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 18 with parameter alpha = 18.190000\n",
-      "The best performance on the validation set is: 38.216353\n",
-      "The corresponding performance on test set is: 37.697069\n",
-      "Starting split 16...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 88 with parameter alpha = 88.890000\n",
-      "The best performance on the validation set is: 32.988038\n",
-      "The corresponding performance on test set is: 37.515000\n",
-      "Starting split 17...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 4 with parameter alpha = 4.050000\n",
-      "The best performance on the validation set is: 33.530482\n",
-      "The corresponding performance on test set is: 43.448861\n",
-      "Starting split 18...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 64 with parameter alpha = 64.650000\n",
-      "The best performance on the validation set is: 29.671418\n",
-      "The corresponding performance on test set is: 29.196786\n",
-      "Starting split 19...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 7 with parameter alpha = 7.080000\n",
-      "The best performance on the validation set is: 44.854681\n",
-      "The corresponding performance on test set is: 36.111594\n",
-      "Starting split 20...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 19 with parameter alpha = 19.200000\n",
-      "The best performance on the validation set is: 35.660642\n",
-      "The corresponding performance on test set is: 38.151790\n",
-      "Starting split 21...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 14 with parameter alpha = 14.150000\n",
-      "The best performance on the validation set is: 41.607604\n",
-      "The corresponding performance on test set is: 32.158764\n",
-      "Starting split 22...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 46 with parameter alpha = 46.470000\n",
-      "The best performance on the validation set is: 36.461026\n",
-      "The corresponding performance on test set is: 36.247837\n",
-      "Starting split 23...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 49 with parameter alpha = 49.500000\n",
-      "The best performance on the validation set is: 28.540585\n",
-      "The corresponding performance on test set is: 37.377972\n",
-      "Starting split 24...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 32 with parameter alpha = 32.330000\n",
-      "The best performance on the validation set is: 33.397020\n",
-      "The corresponding performance on test set is: 35.840386\n",
-      "Starting split 25...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 30 with parameter alpha = 30.310000\n",
-      "The best performance on the validation set is: 36.391650\n",
-      "The corresponding performance on test set is: 36.120189\n",
-      "Starting split 26...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 67 with parameter alpha = 67.680000\n",
-      "The best performance on the validation set is: 39.558878\n",
-      "The corresponding performance on test set is: 35.711036\n",
-      "Starting split 27...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 35 with parameter alpha = 35.360000\n",
-      "The best performance on the validation set is: 34.563158\n",
-      "The corresponding performance on test set is: 51.215777\n",
-      "Starting split 28...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 15 with parameter alpha = 15.160000\n",
-      "The best performance on the validation set is: 43.309309\n",
-      "The corresponding performance on test set is: 40.394297\n",
-      "Starting split 29...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 14 with parameter alpha = 14.150000\n",
-      "The best performance on the validation set is: 42.797900\n",
-      "The corresponding performance on test set is: 34.218103\n",
-      "Starting split 30...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 42 with parameter alpha = 42.430000\n",
-      "The best performance on the validation set is: 45.422692\n",
-      "The corresponding performance on test set is: 27.041917\n",
-      "Starting split 31...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 9 with parameter alpha = 9.100000\n",
-      "The best performance on the validation set is: 33.447413\n",
-      "The corresponding performance on test set is: 38.341333\n",
-      "Starting split 32...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 46 with parameter alpha = 46.470000\n",
-      "The best performance on the validation set is: 31.638807\n",
-      "The corresponding performance on test set is: 43.374635\n",
-      "Starting split 33...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 49 with parameter alpha = 49.500000\n",
-      "The best performance on the validation set is: 37.702092\n",
-      "The corresponding performance on test set is: 31.198701\n",
-      "Starting split 34...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 28.013251\n",
-      "The corresponding performance on test set is: 30.116903\n",
-      "Starting split 35...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 13 with parameter alpha = 13.140000\n",
-      "The best performance on the validation set is: 38.520179\n",
-      "The corresponding performance on test set is: 37.478691\n",
-      "Starting split 36...\n",
-      "\n",
-      " Normalizing output y...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 35.836403\n",
-      "The corresponding performance on test set is: 37.447219\n",
-      "Starting split 37...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 47 with parameter alpha = 47.480000\n",
-      "The best performance on the validation set is: 31.172116\n",
-      "The corresponding performance on test set is: 39.504962\n",
-      "Starting split 38...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 36 with parameter alpha = 36.370000\n",
-      "The best performance on the validation set is: 40.025101\n",
-      "The corresponding performance on test set is: 41.314650\n",
-      "Starting split 39...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 28.474810\n",
-      "The corresponding performance on test set is: 38.093995\n",
-      "Starting split 40...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 38.056007\n",
-      "The corresponding performance on test set is: 33.570513\n",
-      "Starting split 41...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 5 with parameter alpha = 5.060000\n",
-      "The best performance on the validation set is: 35.329935\n",
-      "The corresponding performance on test set is: 40.309342\n",
-      "Starting split 42...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 59 with parameter alpha = 59.600000\n",
-      "The best performance on the validation set is: 25.235609\n",
-      "The corresponding performance on test set is: 36.117043\n",
-      "Starting split 43...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 30 with parameter alpha = 30.310000\n",
-      "The best performance on the validation set is: 27.596182\n",
-      "The corresponding performance on test set is: 39.069843\n",
-      "Starting split 44...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 24.493222\n",
-      "The corresponding performance on test set is: 34.064025\n",
-      "Starting split 45...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 15 with parameter alpha = 15.160000\n",
-      "The best performance on the validation set is: 45.540605\n",
-      "The corresponding performance on test set is: 33.544310\n",
-      "Starting split 46...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 34.661595\n",
-      "The corresponding performance on test set is: 26.174480\n",
-      "Starting split 47...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 5 with parameter alpha = 5.060000\n",
-      "The best performance on the validation set is: 34.837287\n",
-      "The corresponding performance on test set is: 45.463855\n",
-      "Starting split 48...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 31 with parameter alpha = 31.320000\n",
-      "The best performance on the validation set is: 37.528129\n",
-      "The corresponding performance on test set is: 51.123083\n",
-      "Starting split 49...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 20 with parameter alpha = 20.210000\n",
-      "The best performance on the validation set is: 32.480446\n",
-      "The corresponding performance on test set is: 31.618253\n",
-      "Starting split 50...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 59 with parameter alpha = 59.600000\n",
-      "The best performance on the validation set is: 32.584107\n",
-      "The corresponding performance on test set is: 31.376594\n",
-      "Starting split 51...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 9 with parameter alpha = 9.100000\n",
-      "The best performance on the validation set is: 40.867089\n",
-      "The corresponding performance on test set is: 32.363239\n",
-      "Starting split 52...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 97 with parameter alpha = 97.980000\n",
-      "The best performance on the validation set is: 33.801783\n",
-      "The corresponding performance on test set is: 41.200644\n",
-      "Starting split 53...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 17 with parameter alpha = 17.180000\n",
-      "The best performance on the validation set is: 44.010303\n",
-      "The corresponding performance on test set is: 34.562120\n",
-      "Starting split 54...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 22 with parameter alpha = 22.230000\n",
-      "The best performance on the validation set is: 36.759090\n",
-      "The corresponding performance on test set is: 38.376060\n",
-      "Starting split 55...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 29.830898\n",
-      "The corresponding performance on test set is: 24.811584\n",
-      "Starting split 56...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 18 with parameter alpha = 18.190000\n",
-      "The best performance on the validation set is: 34.627026\n",
-      "The corresponding performance on test set is: 46.684129\n",
-      "Starting split 57...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 5 with parameter alpha = 5.060000\n",
-      "The best performance on the validation set is: 43.343991\n",
-      "The corresponding performance on test set is: 41.169814\n",
-      "Starting split 58...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 39 with parameter alpha = 39.400000\n",
-      "The best performance on the validation set is: 34.908981\n",
-      "The corresponding performance on test set is: 48.932907\n",
-      "Starting split 59...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 10 with parameter alpha = 10.110000\n",
-      "The best performance on the validation set is: 37.767543\n",
-      "The corresponding performance on test set is: 28.512235\n",
-      "Starting split 60...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 37.890852\n",
-      "The corresponding performance on test set is: 28.082837\n",
-      "Starting split 61...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 36 with parameter alpha = 36.370000\n",
-      "The best performance on the validation set is: 41.402040\n",
-      "The corresponding performance on test set is: 31.964262\n",
-      "Starting split 62...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 34 with parameter alpha = 34.350000\n",
-      "The best performance on the validation set is: 39.216178\n",
-      "The corresponding performance on test set is: 48.626836\n",
-      "Starting split 63...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 35.222016\n",
-      "The corresponding performance on test set is: 50.344625\n",
-      "Starting split 64...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 25 with parameter alpha = 25.260000\n",
-      "The best performance on the validation set is: 33.803383\n",
-      "The corresponding performance on test set is: 40.058257\n",
-      "Starting split 65...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 56 with parameter alpha = 56.570000\n",
-      "The best performance on the validation set is: 29.170281\n",
-      "The corresponding performance on test set is: 36.104372\n",
-      "Starting split 66...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 14 with parameter alpha = 14.150000\n",
-      "The best performance on the validation set is: 40.405285\n",
-      "The corresponding performance on test set is: 39.262782\n",
-      "Starting split 67...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 58 with parameter alpha = 58.590000\n",
-      "The best performance on the validation set is: 24.638279\n",
-      "The corresponding performance on test set is: 35.165763\n",
-      "Starting split 68...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 56 with parameter alpha = 56.570000\n",
-      "The best performance on the validation set is: 31.681889\n",
-      "The corresponding performance on test set is: 44.049377\n",
-      "Starting split 69...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 5 with parameter alpha = 5.060000\n",
-      "The best performance on the validation set is: 30.735748\n",
-      "The corresponding performance on test set is: 50.708019\n",
-      "Starting split 70...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 29 with parameter alpha = 29.300000\n",
-      "The best performance on the validation set is: 37.273741\n",
-      "The corresponding performance on test set is: 39.351135\n",
-      "Starting split 71...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 6 with parameter alpha = 6.070000\n",
-      "The best performance on the validation set is: 48.033115\n",
-      "The corresponding performance on test set is: 55.674648\n",
-      "Starting split 72...\n",
-      "\n",
-      " Normalizing output y...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 31.903823\n",
-      "The corresponding performance on test set is: 32.937886\n",
-      "Starting split 73...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 19 with parameter alpha = 19.200000\n",
-      "The best performance on the validation set is: 40.825941\n",
-      "The corresponding performance on test set is: 38.535950\n",
-      "Starting split 74...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 34.181621\n",
-      "The corresponding performance on test set is: 34.089714\n",
-      "Starting split 75...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 39 with parameter alpha = 39.400000\n",
-      "The best performance on the validation set is: 40.264289\n",
-      "The corresponding performance on test set is: 47.412526\n",
-      "Starting split 76...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 27 with parameter alpha = 27.280000\n",
-      "The best performance on the validation set is: 35.842650\n",
-      "The corresponding performance on test set is: 34.785447\n",
-      "Starting split 77...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 33 with parameter alpha = 33.340000\n",
-      "The best performance on the validation set is: 38.896608\n",
-      "The corresponding performance on test set is: 39.158479\n",
-      "Starting split 78...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 28 with parameter alpha = 28.290000\n",
-      "The best performance on the validation set is: 31.053773\n",
-      "The corresponding performance on test set is: 33.711541\n",
-      "Starting split 79...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 54 with parameter alpha = 54.550000\n",
-      "The best performance on the validation set is: 36.129208\n",
-      "The corresponding performance on test set is: 34.191692\n",
-      "Starting split 80...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 3 with parameter alpha = 3.040000\n",
-      "The best performance on the validation set is: 42.796346\n",
-      "The corresponding performance on test set is: 40.531343\n",
-      "Starting split 81...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 1 with parameter alpha = 1.020000\n",
-      "The best performance on the validation set is: 50.420936\n",
-      "The corresponding performance on test set is: 43.764477\n",
-      "Starting split 82...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 36.720826\n",
-      "The corresponding performance on test set is: 40.242670\n",
-      "Starting split 83...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 43 with parameter alpha = 43.440000\n",
-      "The best performance on the validation set is: 38.601089\n",
-      "The corresponding performance on test set is: 46.145483\n",
-      "Starting split 84...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 38 with parameter alpha = 38.390000\n",
-      "The best performance on the validation set is: 29.823069\n",
-      "The corresponding performance on test set is: 27.458317\n",
-      "Starting split 85...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 1 with parameter alpha = 1.020000\n",
-      "The best performance on the validation set is: 37.295245\n",
-      "The corresponding performance on test set is: 41.040827\n",
-      "Starting split 86...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 6 with parameter alpha = 6.070000\n",
-      "The best performance on the validation set is: 46.779299\n",
-      "The corresponding performance on test set is: 36.893783\n",
-      "Starting split 87...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 30 with parameter alpha = 30.310000\n",
-      "The best performance on the validation set is: 35.570939\n",
-      "The corresponding performance on test set is: 31.014527\n",
-      "Starting split 88...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 11 with parameter alpha = 11.120000\n",
-      "The best performance on the validation set is: 42.125559\n",
-      "The corresponding performance on test set is: 34.059925\n",
-      "Starting split 89...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 32 with parameter alpha = 32.330000\n",
-      "The best performance on the validation set is: 33.276369\n",
-      "The corresponding performance on test set is: 34.010431\n",
-      "Starting split 90...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 14 with parameter alpha = 14.150000\n",
-      "The best performance on the validation set is: 48.542045\n",
-      "The corresponding performance on test set is: 51.204813\n",
-      "Starting split 91...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 51.240470\n",
-      "The corresponding performance on test set is: 25.204665\n",
-      "Starting split 92...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 8 with parameter alpha = 8.090000\n",
-      "The best performance on the validation set is: 28.042005\n",
-      "The corresponding performance on test set is: 40.903728\n",
-      "Starting split 93...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 24 with parameter alpha = 24.250000\n",
-      "The best performance on the validation set is: 46.378283\n",
-      "The corresponding performance on test set is: 38.717776\n",
-      "Starting split 94...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 52 with parameter alpha = 52.530000\n",
-      "The best performance on the validation set is: 28.152322\n",
-      "The corresponding performance on test set is: 30.532819\n",
-      "Starting split 95...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 42 with parameter alpha = 42.430000\n",
-      "The best performance on the validation set is: 36.952087\n",
-      "The corresponding performance on test set is: 33.163953\n",
-      "Starting split 96...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 61 with parameter alpha = 61.620000\n",
-      "The best performance on the validation set is: 41.047679\n",
-      "The corresponding performance on test set is: 27.036643\n",
-      "Starting split 97...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 42 with parameter alpha = 42.430000\n",
-      "The best performance on the validation set is: 36.858184\n",
-      "The corresponding performance on test set is: 40.745694\n",
-      "Starting split 98...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 89 with parameter alpha = 89.900000\n",
-      "The best performance on the validation set is: 41.871463\n",
-      "The corresponding performance on test set is: 37.287950\n",
-      "Starting split 99...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 55 with parameter alpha = 55.560000\n",
-      "The best performance on the validation set is: 41.040198\n",
-      "The corresponding performance on test set is: 34.121258\n",
-      "Starting split 100...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 9 with parameter alpha = 9.100000\n",
-      "The best performance on the validation set is: 38.421616\n",
-      "The corresponding performance on test set is: 43.772366\n",
-      "Starting split 101...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 23.640892\n",
-      "The corresponding performance on test set is: 41.408082\n",
-      "Starting split 102...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 38.527173\n",
-      "The corresponding performance on test set is: 52.468792\n",
-      "Starting split 103...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 6 with parameter alpha = 6.070000\n",
-      "The best performance on the validation set is: 47.154873\n",
-      "The corresponding performance on test set is: 39.077319\n",
-      "Starting split 104...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 12 with parameter alpha = 12.130000\n",
-      "The best performance on the validation set is: 36.653442\n",
-      "The corresponding performance on test set is: 47.172066\n",
-      "Starting split 105...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 12 with parameter alpha = 12.130000\n",
-      "The best performance on the validation set is: 33.976240\n",
-      "The corresponding performance on test set is: 40.620368\n",
-      "Starting split 106...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 22 with parameter alpha = 22.230000\n",
-      "The best performance on the validation set is: 27.799295\n",
-      "The corresponding performance on test set is: 38.034978\n",
-      "Starting split 107...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 17 with parameter alpha = 17.180000\n",
-      "The best performance on the validation set is: 43.202567\n",
-      "The corresponding performance on test set is: 36.783012\n",
-      "Starting split 108...\n",
-      "\n",
-      " Normalizing output y...\n",
-      "The best performance is for trial 99 with parameter alpha = 100.000000\n",
-      "The best performance on the validation set is: 32.312218\n",
-      "The corresponding performance on test set is: 38.186940\n",
-      "Starting split 109...\n",
-      "\n",
-      " Normalizing output y...\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The best performance is for trial 4 with parameter alpha = 4.050000\n",
-      "The best performance on the validation set is: 39.485731\n",
-      "The corresponding performance on test set is: 50.146953\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Author: Elisabetta Ghisu\n",
-    "\n",
-    "\"\"\"\n",
-    "- This script take as input a kernel matrix\n",
-    "and returns the classification or regression performance\n",
-    "- The kernel matrix can be calculated using any of the graph kernels approaches\n",
-    "- The criteria used for prediction are SVM for classification and kernel Ridge regression for regression\n",
-    "- For predition we divide the data in training, validation and test. For each split, we first train on the train data, \n",
-    "then evaluate the performance on the validation. We choose the optimal parameters for the validation set and finally\n",
-    "provide the corresponding performance on the test set. If more than one split is performed, the final results \n",
-    "correspond to the average of the performances on the test sets. \n",
-    "\n",
-    "@references\n",
-    "    https://github.com/eghisu/GraphKernels/blob/master/GraphKernelsCollection/python_scripts/compute_perf_gk.py\n",
-    "\"\"\"\n",
-    "\n",
-    "print(__doc__)\n",
-    "\n",
-    "import sys\n",
-    "import pathlib\n",
-    "sys.path.insert(0, \"../py-graph/\")\n",
-    "\n",
-    "import random\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "from sklearn.kernel_ridge import KernelRidge # 0.17\n",
-    "from sklearn.metrics import accuracy_score, mean_squared_error\n",
-    "from sklearn import svm\n",
-    "\n",
-    "from kernels.spkernel import spkernel\n",
-    "from utils.graphfiles import loadDataset\n",
-    "\n",
-    "print('\\n Loading dataset from file...')\n",
-    "dataset, y = loadDataset(\"/home/ljia/Documents/research-repo/datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "y = np.array(y)\n",
-    "print(y)\n",
-    "\n",
-    "kernel_file_path = 'kernelmatrix.ds'\n",
-    "path = pathlib.Path(kernel_file_path)\n",
-    "if path.is_file():\n",
-    "    print('\\n Loading the matrix from file...')\n",
-    "    Kmatrix = np.loadtxt(kernel_file_path)\n",
-    "    print(Kmatrix)\n",
-    "else:\n",
-    "    print('\\n Calculating kernel matrix, this could take a while...')\n",
-    "    Kmatrix = spkernel(dataset)\n",
-    "    print(Kmatrix)\n",
-    "    print('Saving kernel matrix to file...')\n",
-    "    np.savetxt(kernel_file_path, Kmatrix)\n",
-    "\n",
-    "# setup the parameters\n",
-    "model_type = 'regression' # Regression or classification problem\n",
-    "print('\\n --- This is a %s problem ---' % model_type)\n",
-    "\n",
-    "datasize = len(dataset)\n",
-    "trials = 100 # Trials for hyperparameters random search\n",
-    "splits = 10 # Number of splits of the data\n",
-    "alpha_grid = np.linspace(0.01, 100, num = trials) # corresponds to (2*C)^-1 in other linear models such as LogisticRegression\n",
-    "# C_grid = np.linspace(0.0001, 10, num = trials)\n",
-    "random.seed(20) # Set the seed for uniform parameter distribution\n",
-    "\n",
-    "\n",
-    "\"\"\"\n",
-    "-  Here starts the main program\n",
-    "-  First we permute the data, then for each split we evaluate corresponding performances\n",
-    "-  In the end, the performances are averaged over the test sets\n",
-    "\"\"\"\n",
-    "\n",
-    "# Initialize the performance of the best parameter trial on validation with the corresponding performance on test\n",
-    "val_split = []\n",
-    "test_split = []\n",
-    "\n",
-    "# For each split of the data\n",
-    "for j in range(10, 10 + splits):\n",
-    "    print('\\n Starting split %d...' % j)\n",
-    "\n",
-    "    # Set the random set for data permutation\n",
-    "    random_state = int(j)\n",
-    "    np.random.seed(random_state)\n",
-    "    idx_perm = np.random.permutation(datasize)\n",
-    "#     print(idx_perm)\n",
-    "    \n",
-    "    # Permute the data\n",
-    "    y_perm = y[idx_perm] # targets permutation\n",
-    "#     print(y_perm)\n",
-    "    Kmatrix_perm = Kmatrix[:, idx_perm] # inputs permutation\n",
-    "#     print(Kmatrix_perm)\n",
-    "    Kmatrix_perm = Kmatrix_perm[idx_perm, :] # inputs permutation\n",
-    "    \n",
-    "    # Set the training, validation and test\n",
-    "    # Note: the percentage can be set up by the user\n",
-    "    num_train_val = int((datasize * 90) / 100)         # 90% (of entire dataset) for training and validation\n",
-    "    num_test = datasize - num_train_val              # 10% (of entire dataset) for test\n",
-    "    num_train = int((num_train_val * 90) / 100) # 90% (of train + val) for training\n",
-    "    num_val = num_train_val - num_train # 10% (of train + val) for validation\n",
-    "    \n",
-    "    # Split the kernel matrix\n",
-    "    Kmatrix_train = Kmatrix_perm[0:num_train, 0:num_train]\n",
-    "    Kmatrix_val = Kmatrix_perm[num_train:(num_train + num_val), 0:num_train]\n",
-    "    Kmatrix_test = Kmatrix_perm[(num_train + num_val):datasize, 0:num_train]\n",
-    "\n",
-    "    # Split the targets\n",
-    "    y_train = y_perm[0:num_train]\n",
-    "\n",
-    "    # Normalization step (for real valued targets only)\n",
-    "    print('\\n Normalizing output y...')\n",
-    "    if model_type == 'regression':\n",
-    "        y_train_mean = np.mean(y_train)\n",
-    "        y_train_std = np.std(y_train)\n",
-    "        y_train = (y_train - y_train_mean) / float(y_train_std)\n",
-    "#         print(y)\n",
-    "        \n",
-    "    y_val = y_perm[num_train:(num_train + num_val)]\n",
-    "    y_test = y_perm[(num_train + num_val):datasize]\n",
-    "    \n",
-    "    # Record the performance for each parameter trial respectively on validation and test set\n",
-    "    perf_all_val = []\n",
-    "    perf_all_test = []\n",
-    "    \n",
-    "    # For each parameter trial\n",
-    "    for i in range(trials):\n",
-    "        # For regression use the Kernel Ridge method\n",
-    "        if model_type == 'regression':\n",
-    "#             print('\\n Starting experiment for trial %d and parameter alpha = %3f\\n ' % (i, alpha_grid[i]))\n",
-    "\n",
-    "            # Fit the kernel ridge model\n",
-    "            KR = KernelRidge(kernel = 'precomputed', alpha = alpha_grid[i])\n",
-    "            KR.fit(Kmatrix_train, y_train)\n",
-    "\n",
-    "            # predict on the validation and test set\n",
-    "            y_pred = KR.predict(Kmatrix_val)\n",
-    "            y_pred_test = KR.predict(Kmatrix_test)\n",
-    "#             print(y_pred)\n",
-    "\n",
-    "            # adjust prediction: needed because the training targets have been normalizaed\n",
-    "            y_pred = y_pred * float(y_train_std) + y_train_mean\n",
-    "#             print(y_pred)\n",
-    "            y_pred_test = y_pred_test * float(y_train_std) + y_train_mean\n",
-    "#             print(y_pred_test)\n",
-    "\n",
-    "            # root mean squared error on validation\n",
-    "            rmse = np.sqrt(mean_squared_error(y_val, y_pred))\n",
-    "            perf_all_val.append(rmse)\n",
-    "\n",
-    "            # root mean squared error in test \n",
-    "            rmse_test = np.sqrt(mean_squared_error(y_test, y_pred_test))\n",
-    "            perf_all_test.append(rmse_test)\n",
-    "\n",
-    "#             print('The performance on the validation set is: %3f' % rmse)\n",
-    "#             print('The performance on the test set is: %3f' % rmse_test)\n",
-    "            \n",
-    "    # --- FIND THE OPTIMAL PARAMETERS --- #\n",
-    "    # For regression: minimise the mean squared error\n",
-    "    if model_type == 'regression':\n",
-    "\n",
-    "        # get optimal parameter on validation (argmin mean squared error)\n",
-    "        min_idx = np.argmin(perf_all_val)\n",
-    "        alpha_opt = alpha_grid[min_idx]\n",
-    "\n",
-    "        # performance corresponding to optimal parameter on val\n",
-    "        perf_val_opt = perf_all_val[min_idx]\n",
-    "\n",
-    "        # corresponding performance on test for the same parameter\n",
-    "        perf_test_opt = perf_all_test[min_idx]\n",
-    "\n",
-    "        print('The best performance is for trial %d with parameter alpha = %3f' % (min_idx, alpha_opt))\n",
-    "        print('The best performance on the validation set is: %3f' % perf_val_opt)\n",
-    "        print('The corresponding performance on test set is: %3f' % perf_test_opt)\n",
-    "\n",
-    "# # we create an instance of SVM and fit out data.\n",
-    "# clf = svm.SVC(kernel = 'precomputed')\n",
-    "# clf.fit(Kmatrix, )\n",
-    "\n",
-    "# # predict on validation and test\n",
-    "# y_pred = clf.predict(K_val)\n",
-    "# y_pred_test = clf.predict(K_test)\n",
-    "\n",
-    "# # accuracy on validation set\n",
-    "# acc = accuracy_score(y_val, y_pred)\n",
-    "# perf_all_val.append(acc)\n",
-    "\n",
-    "# # accuracy on test set\n",
-    "# acc_test = accuracy_score(y_test, y_pred_test)\n",
-    "# perf_all_test.append(acc_test)\n",
-    "\n",
-    "# # print \"The performance on the validation set is: %3f\" % acc\n",
-    "# # print \"The performance on the test set is: %3f\" % acc_test\n",
-    "\n",
-    "\n",
-    "\n",
-    "# # Plot the decision boundary. For that, we will assign a color to each\n",
-    "# # point in the mesh [x_min, x_max]x[y_min, y_max].\n",
-    "# x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1\n",
-    "# y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1\n",
-    "# xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))\n",
-    "# Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])\n",
-    "\n",
-    "# # Put the result into a color plot\n",
-    "# Z = Z.reshape(xx.shape)\n",
-    "# plt.pcolormesh(xx, yy, Z, cmap=plt.cm.Paired)\n",
-    "\n",
-    "# # Plot also the training points\n",
-    "# plt.scatter(X[:, 0], X[:, 1], c=Y, cmap=plt.cm.Paired, edgecolors='k')\n",
-    "# plt.title('3-Class classification using Support Vector Machine with custom'\n",
-    "#           ' kernel')\n",
-    "# plt.axis('tight')\n",
-    "# plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "4841564986 / 3"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/.ipynb_checkpoints/test_spkernel-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/test_spkernel-checkpoint.ipynb
deleted file mode 100644
index 1442552..0000000
--- a/notebooks/.ipynb_checkpoints/test_spkernel-checkpoint.ipynb
+++ /dev/null
@@ -1,1136 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Author: Elisabetta Ghisu\n",
-    "\n",
-    "\"\"\"\n",
-    "- Script containing functions for computing the shortest path kernel\n",
-    "- The Floyd Warshall algorithm is first implemented\n",
-    "- Then the SP is calculated\n",
-    "\"\"\"\n",
-    "\n",
-    "\n",
-    "#######################\n",
-    "# - IMPORT PACKAGES - #\n",
-    "#######################\n",
-    "\n",
-    "\n",
-    "\n",
-    "import numpy.matlib as matlib\n",
-    "import numpy as np\n",
-    "\n",
-    "\"\"\"\n",
-    "### FLOYD WARSHALL ALGORITHM\n",
-    "Input:\n",
-    "- Adjancency matrix A\n",
-    "Output:\n",
-    "- Shortest path matrix S\n",
-    "\"\"\"\n",
-    "\n",
-    "def floyd_warshall(A):\n",
-    "\n",
-    "\t# nuber of nodes\n",
-    "\tn = A.shape[0]\n",
-    "\n",
-    "\t# initialize shortes path matrix\n",
-    "\tS = np.zeros(shape = (n,n))\n",
-    "\n",
-    "\tfor i in range(n):\n",
-    "\t\tfor j in range(n):\n",
-    "\t\t\tif A[i,j] == 0 and i!=j:\n",
-    "\t\t\t\tS[i,j] = float(\"inf\")\n",
-    "\t\t\telse:\n",
-    "\t\t\t\tS[i,j] = A[i,j]\n",
-    "\n",
-    "\t# Compute the shortest path matrix\n",
-    "\tfor k in range(n):\n",
-    "\t\tfor i in range(n):\n",
-    "\t\t\tfor j in range(n):\n",
-    "\t\t\t\tif S[i,j] > S[i,k] + S[k,j]:\n",
-    "\t\t\t\t\tS[i,j] = S[i,k] + S[k,j]\n",
-    "\n",
-    "\treturn S\t\t\t\t\t\t\t\t\n",
-    "\n",
-    "\n",
-    "\n",
-    "\"\"\"\n",
-    "SHORTEST PATH KERNEL: This is a fast implementation of the shortest path\n",
-    "kernel algorithm\n",
-    "Inputs\n",
-    "- Adjancency matrix\n",
-    "- List of list of node labels for each graph\n",
-    "- Total number of node labels \n",
-    "Outputs\n",
-    "- Kernel matrix\n",
-    "- Feature matrix\n",
-    "\"\"\"\n",
-    "\n",
-    "def sp_kernel_fast(adj_mat, labels, L):\n",
-    "\n",
-    "\t# Number of graphs\n",
-    "\tn = len(adj_mat)\n",
-    "\tL = int(L)\n",
-    "\tS = []\n",
-    "\n",
-    "\t# shortest path matrices\n",
-    "\tfor i in xrange(n):\n",
-    "\t\tif i%1000 == 0 and i !=0:\n",
-    " \t\t\tprint('haha') #( \"%d\" % i)\n",
-    "\t\tS.append(floyd_warshall(adj_mat[i]))\n",
-    "\t\n",
-    "\t# maximum length of shortest paths in the dataset\n",
-    "\tmax_path = 0\n",
-    "\n",
-    "\t# for each graph in dataset\n",
-    "\tfor i in xrange(n):\n",
-    "\n",
-    "\t\tS_cur = np.copy(S[i])\n",
-    "\t\tS_cur[S_cur == np.inf] = 0\n",
-    "\t\tnew_max = np.max(S_cur)\n",
-    "\t\t\n",
-    "\t\tif new_max > max_path:\n",
-    "\t\t\tmax_path = new_max # get max short path in all Ss\n",
-    "\n",
-    "\t# maximum length of shortest paths\n",
-    "\tmax_path = int(max_path)\n",
-    "\n",
-    "\t# initialize feature matrix\n",
-    "\tsp = np.zeros(((max_path + 1) * L * (L+1) /2,n))\n",
-    "\n",
-    "\t# compute feature map for shortest path\n",
-    "\tfor i in xrange(n):\n",
-    "\n",
-    "\t\tif i % 1000 == 0:\n",
-    "\t\t\tprint('haha') #\"Processed %d graphs\" %i\n",
-    "\n",
-    "\t\tS_graph = S[i]\n",
-    "\t\tlabels_graph = np.asarray(labels[i].reshape((len(labels[i]),1)))\n",
-    "\t\tlabels_graph = labels_graph + 1\n",
-    "\t\t\n",
-    "\t\tlabels_aux = matlib.repmat(labels_graph, 1, len(labels_graph))\n",
-    "\t\t\n",
-    "\t\tmin_lab = np.minimum(labels_aux, labels_aux.T)\n",
-    "\t\t\n",
-    "\t\tmax_lab = np.maximum(labels_aux, labels_aux.T)\n",
-    "\t\tsub_path = np.triu(~(np.isinf(S_graph))).T\n",
-    "\n",
-    "\t\tmin_lab = min_lab[sub_path]\n",
-    "\t\tmax_lab = max_lab[sub_path]\n",
-    "\n",
-    "\n",
-    "\t\tind = S_graph[sub_path] * L * (L + 1) / 2 + (min_lab - 1) * (2*L + 2 - min_lab) / 2 + max_lab - min_lab\n",
-    "\t\tind = ind.astype(int)\n",
-    "\t\taccum = np.zeros((max_path + 1) * L * (L + 1) /2)\n",
-    "\t\taccum[:ind.max() + 1] += np.bincount(ind.astype(int))\n",
-    "\t\tsp[ind,i] = accum[ind]\n",
-    "\t\n",
-    "\tsum_cols = np.sum(sp, axis = 1)\n",
-    "\tind_true = sum_cols != 0\n",
-    "\tsp = sp[ind_true,:]\n",
-    "\t\n",
-    "\t# compute kernel matrix\n",
-    "\tK = np.dot(sp.T,sp)\n",
-    "    \n",
-    "\treturn K, sp"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "ImportError",
-     "evalue": "No module named 'igraph'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mImportError\u001b[0m                               Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-11-effbaf3a1e10>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0;31m# iGraph imports to handle graphs and for graph I/O\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 16\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0migraph\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mGraph\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     17\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     18\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mImportError\u001b[0m: No module named 'igraph'"
-     ]
-    }
-   ],
-   "source": [
-    "#Authors: Elisabetta Ghisu, Felipe Llinares Lopez\n",
-    "\n",
-    "\"\"\"\n",
-    "- This script includes a list of functions for analyzing \n",
-    "parsing and formatting graphs\n",
-    "- The graphs are given in graphml format\n",
-    "- It also cntans functions for loading, processing the graphs\n",
-    "and extract graph statistics\n",
-    "\"\"\"\n",
-    "\n",
-    "\n",
-    "import numpy as np\n",
-    "from numpy import genfromtxt\n",
-    "\n",
-    "# iGraph imports to handle graphs and for graph I/O\n",
-    "from igraph import Graph\n",
-    "\n",
-    "\n",
-    "# ---------------------------------GRAPHML I/O FUNCTIONS------------------------------------ #\n",
-    "\n",
-    "# INPUT:\n",
-    "# filenames_graphs: list of GraphML files, where each file contains one graph in the dataset\n",
-    "# filename_labels: text file with labels corresponding to each graph in the dataset, in the same order as they are in\n",
-    "#                  filename_graphs\n",
-    "# OUTPUT:\n",
-    "# G: A list containing one iGraph object for each graph in the dataset\n",
-    "# Y: A Numpy array containing the labels corresponding to each graph, in the same order as G\n",
-    "def load_graphml(filenames_graphs, filename_labels):\n",
-    "    G = []\n",
-    "    for fname in filenames_graphs:\n",
-    "        G.append(Graph.Read_GraphML(fname))\n",
-    "    Y = genfromtxt(filename_labels)\n",
-    "    return (G, Y)\n",
-    "\n",
-    "\n",
-    "# Loads a list of paths to GraphML files from filename_list\n",
-    "def load_file_list(filename_flist):\n",
-    "    f = open(filename_flist, 'r')\n",
-    "    f_graphs = []\n",
-    "    for line in f:\n",
-    "        f_graphs.append(line.strip())\n",
-    "    f.close()\n",
-    "    return f_graphs\n",
-    "\n",
-    "\n",
-    "# --------------------------------COMPUTE STATISTICS---------------------------------------- #\n",
-    "\n",
-    "\n",
-    "# Retrieve labels of all vertices belonging to any graph in the list of iGraph objects G and\n",
-    "# returns the entire list, and a list with the alphabet of the vertex labels\n",
-    "def get_all_vertex_labels(G, att_name='label'):\n",
-    "    v_l = []\n",
-    "    for g in G:\n",
-    "        v_l += g.vs[att_name]\n",
-    "    return (v_l, np.unique(v_l))\n",
-    "\n",
-    "\n",
-    "# Retrieve labels of all edges belonging to any graph in the list of iGraph objects G and\n",
-    "# returns the entire list, and a list with the alphabet of the edge labels\n",
-    "def get_all_edge_labels(G, att_name='label'):\n",
-    "    e_l = []\n",
-    "    for g in G:\n",
-    "        e_l += g.es[att_name]\n",
-    "    return (e_l, np.unique(e_l))\n",
-    "\n",
-    "\n",
-    "# Returns a list where each element is itself the adjacency list of the corresponding graph\n",
-    "# The adjacency lit of a graph has the following format:\n",
-    "# it is a list where each element is a list containing the id of adjacent nodes\n",
-    "def get_adj_list(G):\n",
-    "    ad_l = []\n",
-    "    for g in G:\n",
-    "        ad_l.append(g.get_adjlist())\n",
-    "    return ad_l\n",
-    "\n",
-    "# Returns a list where each element is the adjacency matrix of the graph \n",
-    "# The adjancency matrix is in iGraph format\n",
-    "def get_adj_mat(G):\n",
-    "    ad_m = []\n",
-    "    for g in G:\n",
-    "        ad_m.append(g.get_adjacency())\n",
-    "    return ad_m\n",
-    "\n",
-    "# Returns a list where each element contains the nodes label for a graph\n",
-    "def get_node_labels(G, att_name = 'label'):\n",
-    "    node_l = []\n",
-    "    for g in G:\n",
-    "        node_l.append(g.vs[att_name])\n",
-    "    return node_l\n",
-    "\n",
-    "\n",
-    "\n",
-    "# ----------------- LOAD AND PROCESS THE GRAPHS --------------- #\n",
-    "\n",
-    "\n",
-    "\"\"\"\n",
-    "Inputs:\n",
-    "- list of graphs file\n",
-    "- labels file\n",
-    "- path to the data folder\n",
-    "Outputs:\n",
-    "- List of node labels\n",
-    "- List of adjancency lists\n",
-    "- List of graphs in graphml format\n",
-    "- Targets\n",
-    "- number of classes\n",
-    "- sample size\n",
-    "\"\"\"\n",
-    "\n",
-    "\n",
-    "def load_and_process(filenames_graphs, filename_labels, path_to_dataset):\n",
-    "\n",
-    "    # load a list of names to graphml files\n",
-    "    f_graphs = load_file_list(filenames_graphs)\n",
-    "    # sample size\n",
-    "    n = len(f_graphs)\n",
-    "\n",
-    "    # create a list of paths to the files\n",
-    "    f_graphs_path =[]\n",
-    "\n",
-    "    # for each graph in dataset\n",
-    "    for i in range(n):\n",
-    "\n",
-    "        # index the graph\n",
-    "        graph_name = f_graphs[i]\n",
-    "\n",
-    "        # path to the data folder\n",
-    "        path = \"%s/%s\" % (path_to_dataset, graph_name)\n",
-    "        f_graphs_path.append(path)\n",
-    "\n",
-    "    # If the data is DD have to delete an element (corrupted file)\n",
-    "    if graph_name == \"DD\":\n",
-    "        del f_graphs_path[148]\n",
-    "        n = n-1\n",
-    "\n",
-    "    # Load the graphs in graphml format\n",
-    "    # G is a llist of graphml graph\n",
-    "    # Y is an array of targets\n",
-    "    G,Y = load_graphml(f_graphs_path, filename_labels)\n",
-    "\n",
-    "    # Delete corrupted file in DD\n",
-    "    if graph_name == \"DD\": \n",
-    "        Y = np.delete(Y, 148)\n",
-    "\n",
-    "    # get adjacency list and matrix for all the graphs in G\n",
-    "    ad_list = get_adj_list(G)\n",
-    "    ad_mat = get_adj_mat(G)\n",
-    "\n",
-    "    # get a list containing lists of node labels\n",
-    "    node_label = get_node_labels(G)\n",
-    "\n",
-    "    return node_label, ad_list, G, Y\n",
-    "\n",
-    "\n",
-    "\n",
-    "\"\"\"\n",
-    "RENAME NODES: function to rename nodes from 0,...,num_nodes\n",
-    "Input\n",
-    "- list of list of node labels in each graph\n",
-    "Output\n",
-    "- L: total number of different labels in the dataset\n",
-    "- node_label: new renamed labels\n",
-    "\"\"\"\n",
-    "\n",
-    "def rename_nodes(node_label): \n",
-    "    \n",
-    "    # number of graphs in the dataset\n",
-    "    n = len(node_label)\n",
-    "\n",
-    "    # labels will store the new labels\n",
-    "    labels = [0] * n\n",
-    "\n",
-    "    # disctionary containing the map from the old to the new labels\n",
-    "    label_lookup = {}\n",
-    "\n",
-    "    # counter of unique labels\n",
-    "    label_counter = 0\n",
-    "\n",
-    "    # for each graph in dataset\n",
-    "    for i in range(n):\n",
-    "\n",
-    "\n",
-    "        # number of nodes in graph[i]\n",
-    "        num_nodes = len(node_label[i]) \n",
-    "\n",
-    "        # will be used to store the new labels\n",
-    "        labels[i] = np.zeros(num_nodes, dtype = np.uint64) # positive integers\n",
-    "\n",
-    "        # for each node in the graph\n",
-    "        for j in range(num_nodes):\n",
-    "\n",
-    "            # the node label to a string\n",
-    "            l_node_str = str(np.copy(node_label[i][j]))\n",
-    "            \n",
-    "            # if the string has not been observed yet\n",
-    "            # the corresponding node is assigned a new label\n",
-    "            # otherwise it will be named with the same label\n",
-    "            # already assigned to an identical string\n",
-    "\n",
-    "            if not label_lookup.has_key(l_node_str):\n",
-    "                label_lookup[l_node_str] = label_counter\n",
-    "                labels[i][j] = label_counter                                                              \n",
-    "                label_counter += 1\n",
-    "            else:\n",
-    "                labels[i][j] = label_lookup[l_node_str]\n",
-    "\n",
-    "    # total number of labels in the dataset\n",
-    "    L = label_counter\n",
-    "    print('haha') #'Number of original labels %d' % L \n",
-    "\n",
-    "    return L, labels"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "usage: ipykernel_launcher.py [-h] --dataset DATASET\n",
-      "ipykernel_launcher.py: error: the following arguments are required: --dataset\n"
-     ]
-    },
-    {
-     "ename": "SystemExit",
-     "evalue": "2",
-     "output_type": "error",
-     "traceback": [
-      "An exception has occurred, use %tb to see the full traceback.\n",
-      "\u001b[0;31mSystemExit\u001b[0m\u001b[0;31m:\u001b[0m 2\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py:2918: UserWarning: To exit: use 'exit', 'quit', or Ctrl-D.\n",
-      "  warn(\"To exit: use 'exit', 'quit', or Ctrl-D.\", stacklevel=1)\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Author: Elisabetta Ghisu\n",
-    "\n",
-    "\"\"\"\n",
-    "- Script for computing the kernel matrix and features map \n",
-    "using shortest path kernel\n",
-    "\"\"\"\n",
-    "\n",
-    "###########################\n",
-    "# --- IMPORT PACKAGES --- #\n",
-    "###########################\n",
-    "\n",
-    "import numpy as np\n",
-    "import argparse\n",
-    "import os\n",
-    "import pickle\n",
-    "\n",
-    "from numpy import genfromtxt\n",
-    "\n",
-    "# from sp_functions import *\n",
-    "# from parse_graphs import *\n",
-    "\n",
-    "\n",
-    "\n",
-    "##############################\n",
-    "### Command Line Arguments ###\n",
-    "##############################\n",
-    "\n",
-    "parser = argparse.ArgumentParser(description = \"Compute kernel and features matrices via shortest path kernel\")\n",
-    "parser.add_argument(\"--dataset\", required = True, help = \"Name of the dataset\")\n",
-    "args = parser.parse_args()\n",
-    "\n",
-    "\n",
-    "#####################\n",
-    "### LOAD THE DATA ###\n",
-    "#####################\n",
-    "\n",
-    "\"\"\"\n",
-    "- Here we load the data input and targets\n",
-    "- The data are assumed to be in graph formats\n",
-    "- They should be in graphml format \n",
-    "\"\"\"\n",
-    "\n",
-    "# path to the list of graphs and dataset\n",
-    "filenames_graphs = \"data/%s.list\" % (args.dataset)\n",
-    "path_to_dataset = \"data/%s\" % (args.dataset) \n",
-    "\n",
-    "# Load the targets\n",
-    "filename_labels = \"data/%s_label.txt\" % (args.dataset)\n",
-    "\n",
-    "# load and process graphs\n",
-    "node_label, ad_list, G, Y = load_and_process(filenames_graphs, filename_labels, path_to_dataset)\n",
-    "\n",
-    "# output directory\n",
-    "out_path = \"kernel_matrices/%s/sp\" % args.dataset\n",
-    "\n",
-    "# If the output directory does not exist, then create it\n",
-    "if not os.path.exists(out_path):\n",
-    "    os.makedirs(out_path)\n",
-    "\n",
-    "\n",
-    "#########################\n",
-    "# --- SHORTEST PATH --- #\n",
-    "#########################\n",
-    "\n",
-    "\n",
-    "# assign labels starting from zero to the nodes\n",
-    "L, labels = rename_nodes(node_label)\n",
-    "\n",
-    "\n",
-    "# Compute adjancency matrix \n",
-    "adj_mat = get_adj_mat(G)\n",
-    "\n",
-    "# Compute kernel and feature maps using shortest path\n",
-    "K, phi = sp_kernel_fast(adj_mat, labels, L)\n",
-    "\n",
-    "# save kernel matrix\n",
-    "file_name = \"%s/%s_ker_mat\" % (out_path, args.dataset)\n",
-    "np.save(file_name, K)\n",
-    "\n",
-    "# save feature map\n",
-    "file_name = \"%s/%s_phi_map\" % (out_path, args.dataset)\n",
-    "np.save(file_name, phi)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[[ 0.  2.  3.  1.  2.]]\n",
-      "{0: {0: [0], 1: [0, 3, 1], 2: [0, 3, 4, 2], 3: [0, 3], 4: [0, 3, 4]}, 1: {0: [1, 3, 0], 1: [1], 2: [1, 3, 4, 2], 3: [1, 3], 4: [1, 3, 4]}, 2: {0: [2, 4, 3, 0], 1: [2, 4, 3, 1], 2: [2], 3: [2, 4, 3], 4: [2, 4]}, 3: {0: [3, 0], 1: [3, 1], 2: [3, 4, 2], 3: [3], 4: [3, 4]}, 4: {0: [4, 3, 0], 1: [4, 3, 1], 2: [4, 2], 3: [4, 3], 4: [4]}}\n",
-      "[[ 0.  2.  3.  1.  2.]\n",
-      " [ 2.  0.  3.  1.  2.]\n",
-      " [ 3.  3.  0.  2.  1.]\n",
-      " [ 1.  1.  2.  0.  1.]\n",
-      " [ 2.  2.  1.  1.  0.]]\n"
-     ]
-    },
-    {
-     "ename": "NameError",
-     "evalue": "name 'plt' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-17-c1e1e7524d30>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     11\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ml\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     12\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ml2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 13\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0mS\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetSPGraph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mNameError\u001b[0m: name 'plt' is not defined"
-     ]
-    }
-   ],
-   "source": [
-    "dataset, y = loadDataset(\"/home/ljia/Documents/research-repo/datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "G1 = dataset[12]\n",
-    "\n",
-    "nx.draw_networkx(G1)\n",
-    "# print(list(dataset[12][4]))\n",
-    "\n",
-    "l = nx.shortest_path(G1)\n",
-    "\n",
-    "l2 = nx.floyd_warshall_numpy(G1)\n",
-    "print(np.array(l2[0]))\n",
-    "print(l)\n",
-    "print(l2)\n",
-    "plt.show()\n",
-    "\n",
-    "S = getSPGraph(G1)\n",
-    "nx.draw_networkx(S)\n",
-    "pos = nx.spring_layout(S)\n",
-    "edge_labels = nx.get_edge_attributes(S,'cost')\n",
-    "print(edge_labels)\n",
-    "nx.draw_networkx_edge_labels(S, pos, edge_labels = edge_labels)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import networkx as nx\n",
-    "   \n",
-    "def loadCT(filename):\n",
-    "    \"\"\"load data from .ct file.\n",
-    "    \n",
-    "    Notes\n",
-    "    ------ \n",
-    "    a typical example of data in .ct is like this:\n",
-    "    \n",
-    "     3 2  <- number of nodes and edges\n",
-    "        0.0000    0.0000    0.0000 C <- each line describes a node, the last parameter in which is the label of the node, representing a chemical element @Q what are the first 3 numbers?\n",
-    "        0.0000    0.0000    0.0000 C\n",
-    "        0.0000    0.0000    0.0000 O\n",
-    "      1  3  1  1 <- each line describes an edge, the first two numbers represent two nodes of the edge, the last number represents the label. @Q what are the 3th numbers?\n",
-    "      2  3  1  1\n",
-    "    \"\"\"\n",
-    "    content = open(filename).read().splitlines()\n",
-    "    G = nx.Graph(name=str(content[0])) # set name of the graph\n",
-    "    tmp = content[1].split(\" \")\n",
-    "    if tmp[0] == '':\n",
-    "        nb_nodes = int(tmp[1]) # number of the nodes\n",
-    "        nb_edges = int(tmp[2]) # number of the edges\n",
-    "    else:\n",
-    "        nb_nodes = int(tmp[0])\n",
-    "        nb_edges = int(tmp[1])\n",
-    "\n",
-    "    for i in range(0, nb_nodes):\n",
-    "        tmp = content[i + 2].split(\" \")\n",
-    "        tmp = [x for x in tmp if x != '']\n",
-    "        G.add_node(i, label=tmp[3])\n",
-    "\n",
-    "    for i in range(0, nb_edges):\n",
-    "        tmp = content[i + G.number_of_nodes() + 2].split(\" \")\n",
-    "        tmp = [x for x in tmp if x != '']\n",
-    "        G.add_edge(int(tmp[0]) - 1, int(tmp[1]) - 1, label=int(tmp[3]))\n",
-    "    return G\n",
-    "\n",
-    "\n",
-    "def loadGXL(filename):\n",
-    "    import networkx as nx\n",
-    "    import xml.etree.ElementTree as ET\n",
-    "\n",
-    "    tree = ET.parse(filename)\n",
-    "    root = tree.getroot()\n",
-    "    index = 0\n",
-    "    G = nx.Graph()\n",
-    "    dic={}\n",
-    "    for node in root.iter('node'):\n",
-    "        label = node.find('attr')[0].text\n",
-    "        dic[node.attrib['id']] = index\n",
-    "        G.add_node(index, id=node.attrib['id'], label=label)\n",
-    "        index += 1\n",
-    "        \n",
-    "    for edge in root.iter('edge'):\n",
-    "        label = edge.find('attr')[0].text\n",
-    "        G.add_edge(dic[edge.attrib['from']], dic[edge.attrib['to']], label=label)\n",
-    "    return G\n",
-    " \n",
-    "def loadDataset(filename):\n",
-    "    \"\"\"load file list of the dataset.\n",
-    "    \"\"\"\n",
-    "    from os.path import dirname, splitext\n",
-    "\n",
-    "    dirname_dataset = dirname(filename)\n",
-    "    extension = splitext(filename)[1][1:]\n",
-    "    data = []\n",
-    "    y = []\n",
-    "    if(extension == \"ds\"):\n",
-    "        content = open(filename).read().splitlines()\n",
-    "        for i in range(0, len(content)):\n",
-    "            tmp = content[i].split(' ')\n",
-    "            data.append(loadCT(dirname_dataset + '/' + tmp[0].replace('#', '', 1))) # remove the '#'s in file names\n",
-    "            y.append(float(tmp[1]))\n",
-    "    elif(extension == \"cxl\"):\n",
-    "        import xml.etree.ElementTree as ET\n",
-    "\n",
-    "        tree = ET.parse(filename)\n",
-    "        root = tree.getroot()\n",
-    "        data = []\n",
-    "        y = []\n",
-    "        for graph in root.iter('print'):\n",
-    "            mol_filename = graph.attrib['file']\n",
-    "            mol_class = graph.attrib['class']\n",
-    "            data.append(loadGXL(dirname_dataset + '/' + mol_filename))\n",
-    "            y.append(mol_class)\n",
-    "\n",
-    "    return data, y"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 82,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "SyntaxError",
-     "evalue": "invalid syntax (<ipython-input-82-ac9ab22d42ef>, line 48)",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-82-ac9ab22d42ef>\"\u001b[0;36m, line \u001b[0;32m48\u001b[0m\n\u001b[0;31m    Kmatrix[j][i] += (i == j ? 0 : 1)\u001b[0m\n\u001b[0m                             ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
-     ]
-    }
-   ],
-   "source": [
-    "import sys\n",
-    "import pathlib\n",
-    "sys.path.insert(0, \"../\")\n",
-    "\n",
-    "\n",
-    "import networkx as nx\n",
-    "import numpy as np\n",
-    "import time\n",
-    "\n",
-    "from utils.utils import getSPGraph\n",
-    "\n",
-    "\n",
-    "def spkernel(Gn):\n",
-    "    \"\"\"Transform graph G to its corresponding shortest-paths graph using Floyd-transformation.\n",
-    "    \n",
-    "    Parameters\n",
-    "    ----------\n",
-    "    G : NetworkX graph\n",
-    "        The graph to be tramsformed.\n",
-    "        \n",
-    "    Return\n",
-    "    ------\n",
-    "    S : NetworkX graph\n",
-    "        The shortest-paths graph corresponding to G.\n",
-    "        \n",
-    "    References\n",
-    "    ----------\n",
-    "    [1] Borgwardt KM, Kriegel HP. Shortest-path kernels on graphs. InData Mining, Fifth IEEE International Conference on 2005 Nov 27 (pp. 8-pp). IEEE.\n",
-    "    \"\"\"\n",
-    "    Kmatrix = np.zeros((len(Gn), len(Gn)))\n",
-    "    \n",
-    "    Sn = [] # get shortest path graphs of Gn\n",
-    "    for i in range(0, len(Gn)):\n",
-    "        Sn.append(getSPGraph(Gn[i]))\n",
-    "    \n",
-    "#     print(S1.nodes(data = True))\n",
-    "#     print(S2.nodes(data = True))\n",
-    "#     print(S1.edges(data = True))\n",
-    "#     print(S2.edges(data = True))\n",
-    "    \n",
-    "    start_time = time.time()\n",
-    "    for i in range(0, len(Gn)):\n",
-    "        for j in range(i, len(Gn)):\n",
-    "            for e1 in Sn[i].edges(data = True):\n",
-    "                for e2 in Sn[j].edges(data = True):          \n",
-    "                    if e1[2]['cost'] != 0 and e1[2]['cost'] == e2[2]['cost'] and ((e1[0] == e2[0] and e1[1] == e2[1]) or (e1[0] == e2[1] and e1[1] == e2[0])):\n",
-    "                        Kmatrix[i][j] += 1\n",
-    "                        Kmatrix[j][i] += (i == j ? 0 : 1)\n",
-    "    \n",
-    "    print(\"--- %s seconds ---\" % (time.time() - start_time))\n",
-    "    \n",
-    "    return Kmatrix"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 83,
-   "metadata": {},
-   "outputs": [
-    {
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-      "184\n",
-      "--- 70.3204357624054 seconds ---\n",
-      "[[  3.   1.   3. ...,   1.   1.   1.]\n",
-      " [  1.   6.   1. ...,   0.   0.   3.]\n",
-      " [  3.   1.   3. ...,   1.   1.   1.]\n",
-      " ..., \n",
-      " [  1.   0.   1. ...,  55.  21.   7.]\n",
-      " [  1.   0.   1. ...,  21.  55.   7.]\n",
-      " [  1.   3.   1. ...,   7.   7.  55.]]\n"
-     ]
-    }
-   ],
-   "source": [
-    "dataset, y = loadDataset(\"/home/ljia/Documents/research-repo/datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
-    "G1 = dataset[12]\n",
-    "G2 = dataset[20]\n",
-    "Kmatrix = spkernel(dataset)\n",
-    "\n",
-    "print(Kmatrix)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/run_treeletkernel_acyclic.ipynb b/notebooks/run_treeletkernel_acyclic.ipynb
index 56d1272..9f27e1e 100644
--- a/notebooks/run_treeletkernel_acyclic.ipynb
+++ b/notebooks/run_treeletkernel_acyclic.ipynb
@@ -16,7 +16,7 @@
       "\n",
       "2. Calculating gram matrices. This could take a while...\n",
       "\n",
-      " --- treelet kernel matrix of size 183 built in 0.4853649139404297 seconds ---\n",
+      " --- treelet kernel matrix of size 183 built in 0.47826528549194336 seconds ---\n",
       "\n",
       "gram matrix with parameters {} is: \n",
       "[[4.00000000e+00 2.60653066e+00 1.00000000e+00 ... 1.26641655e-14\n",
@@ -36,9 +36,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f98e32540b8>"
+       "<matplotlib.figure.Figure at 0x7f0055964160>"
       ]
      },
      "metadata": {},
@@ -50,7 +50,7 @@
      "text": [
       "\n",
       "3. Fitting and predicting using nested cross validation. This could really take a while...\n",
-      "calculate performance:   0%|          | 1/630 [00:00<01:18,  8.01it/s]"
+      "calculate performance:   0%|          | 1/630 [00:00<01:12,  8.65it/s]"
      ]
     },
     {
@@ -70,38 +70,58 @@
       "\n",
       "best_params_out:  [{}]\n",
       "best_params_in:  [{'alpha': 1.584893192461114}]\n",
-      "best_val_perf:  14.214089277459907\n",
-      "best_val_std:  0.7950978152856186\n",
-      "final_performance:  15.264883647635374\n",
-      "final_confidence:  3.652980498319737\n",
-      "train_performance:  7.3835358737013825\n",
-      "train_std:  0.37481098899403587\n",
-      "time to calculate gram matrix:  0.4853649139404297 s\n",
-      "\n",
-      "params                 train_perf    valid_perf     test_perf        gram_matrix_time\n",
-      "---------------------  ------------  -------------  -------------  ------------------\n",
-      "{'alpha': '1.00e-01'}  29.66±26.12   114.74±104.67  120.03±92.58                 0.49\n",
-      "{'alpha': '1.26e-01'}  51.13±89.42   171.35±229.94  168.66±208.15                0.49\n",
-      "{'alpha': '1.58e-01'}  60.74±185.03  167.81±433.71  285.25±995.56                0.49\n",
-      "{'alpha': '2.00e-01'}  26.25±24.38   80.66±63.18    98.06±123.24                 0.49\n",
-      "{'alpha': '2.51e-01'}  16.22±10.15   59.60±58.66    61.21±57.88                  0.49\n",
-      "{'alpha': '3.16e-01'}  15.24±16.69   53.27±75.97    53.33±66.20                  0.49\n",
-      "{'alpha': '3.98e-01'}  13.22±14.43   41.69±47.57    36.61±32.28                  0.49\n",
-      "{'alpha': '5.01e-01'}  11.73±14.79   31.17±39.05    30.08±34.14                  0.49\n",
-      "{'alpha': '6.31e-01'}  7.58±1.79     18.06±3.34     19.22±6.57                   0.49\n",
-      "{'alpha': '7.94e-01'}  7.02±0.75     15.87±1.77     16.82±4.71                   0.49\n",
-      "{'alpha': '1.00e+00'}  6.96±0.53     14.87±1.27     15.83±4.10                   0.49\n",
-      "{'alpha': '1.26e+00'}  7.10±0.42     14.38±0.98     15.38±3.78                   0.49\n",
-      "{'alpha': '1.58e+00'}  7.38±0.37     14.21±0.80     15.26±3.65                   0.49\n",
-      "{'alpha': '2.00e+00'}  7.78±0.36     14.27±0.68     15.37±3.64                   0.49\n",
-      "{'alpha': '2.51e+00'}  8.28±0.35     14.50±0.59     15.63±3.71                   0.49\n",
-      "{'alpha': '3.16e+00'}  8.89±0.35     14.88±0.53     16.01±3.85                   0.49\n",
-      "{'alpha': '3.98e+00'}  9.60±0.35     15.39±0.49     16.50±4.03                   0.49\n",
-      "{'alpha': '5.01e+00'}  10.42±0.35    16.03±0.46     17.11±4.25                   0.49\n",
-      "{'alpha': '6.31e+00'}  11.37±0.34    16.80±0.45     17.83±4.50                   0.49\n",
-      "{'alpha': '7.94e+00'}  12.47±0.34    17.72±0.46     18.68±4.76                   0.49\n",
-      "{'alpha': '1.00e+01'}  13.74±0.33    18.79±0.47     19.69±5.04                   0.49\n",
-      "calculate performance: 100%|██████████| 630/630 [01:10<00:00, 11.78it/s]"
+      "\n",
+      "best_val_perf:  14.495962226690725\n",
+      "best_val_std:  1.231113106094586\n",
+      "final_performance:  14.486961234514974\n",
+      "final_confidence:  3.0828755678322097\n",
+      "train_performance:  7.445811458092056\n",
+      "train_std:  0.44699023975297714\n",
+      "\n",
+      "time to calculate gram matrix with different hyperpapams: 0.48±nan\n",
+      "time to calculate best gram matrix:  0.47826528549194336 s\n",
+      "\n",
+      "params                 train_perf    valid_perf     test_perf         gram_matrix_time\n",
+      "---------------------  ------------  -------------  --------------  ------------------\n",
+      "{'alpha': '1.00e-01'}  80.89±188.06  270.73±507.22  566.39±2186.33                0.48\n",
+      "{'alpha': '1.26e-01'}  42.51±97.80   163.73±364.07  140.89±312.95                 0.48\n",
+      "{'alpha': '1.58e-01'}  16.53±11.13   59.49±49.03    63.71±64.12                   0.48\n",
+      "{'alpha': '2.00e-01'}  24.75±39.36   113.35±310.71  69.50±80.80                   0.48\n",
+      "{'alpha': '2.51e-01'}  14.39±14.38   42.48±32.86    46.53±43.66                   0.48\n",
+      "{'alpha': '3.16e-01'}  15.52±20.51   47.37±70.76    54.82±97.04                   0.48\n",
+      "{'alpha': '3.98e-01'}  10.48±7.77    30.43±26.87    30.20±22.35                   0.48\n",
+      "{'alpha': '5.01e-01'}  9.16±7.71     24.96±26.10    29.34±42.29                   0.48\n",
+      "{'alpha': '6.31e-01'}  7.15±1.17     17.36±3.20     18.40±8.21                    0.48\n",
+      "{'alpha': '7.94e-01'}  6.95±0.76     15.87±2.10     16.51±6.11                    0.48\n",
+      "{'alpha': '1.00e+00'}  6.98±0.55     15.08±1.69     15.45±4.65                    0.48\n",
+      "{'alpha': '1.26e+00'}  7.20±0.61     14.81±2.06     14.97±3.73                    0.48\n",
+      "{'alpha': '1.58e+00'}  7.45±0.45     14.50±1.23     14.49±3.08                    0.48\n",
+      "{'alpha': '2.00e+00'}  7.86±0.44     14.53±1.02     14.37±2.75                    0.48\n",
+      "{'alpha': '2.51e+00'}  8.37±0.44     14.74±0.89     14.46±2.62                    0.48\n",
+      "{'alpha': '3.16e+00'}  9.00±0.43     15.10±0.78     14.71±2.63                    0.48\n",
+      "{'alpha': '3.98e+00'}  9.73±0.41     15.59±0.69     15.11±2.76                    0.48\n",
+      "{'alpha': '5.01e+00'}  10.57±0.39    16.20±0.61     15.65±2.95                    0.48\n",
+      "{'alpha': '6.31e+00'}  11.53±0.36    16.95±0.53     16.33±3.19                    0.48\n",
+      "{'alpha': '7.94e+00'}  12.64±0.33    17.85±0.47     17.18±3.46                    0.48\n",
+      "{'alpha': '1.00e+01'}  13.90±0.30    18.91±0.41     18.20±3.75                    0.48\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/local/lib/python3.5/dist-packages/numpy/core/_methods.py:135: RuntimeWarning: Degrees of freedom <= 0 for slice\n",
+      "  keepdims=keepdims)\n",
+      "/usr/local/lib/python3.5/dist-packages/numpy/core/_methods.py:127: RuntimeWarning: invalid value encountered in double_scalars\n",
+      "  ret = ret.dtype.type(ret / rcount)\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "calculate performance: 100%|██████████| 630/630 [01:10<00:00, 11.33it/s]"
      ]
     }
    ],
diff --git a/notebooks/run_treepatternkernel.ipynb b/notebooks/run_treepatternkernel.ipynb
index 87ac05f..06b7445 100644
--- a/notebooks/run_treepatternkernel.ipynb
+++ b/notebooks/run_treepatternkernel.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
@@ -2017,6 +2017,17885 @@
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.89989757537842 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1.0, 'kernel_type': 'untiln'} is: \n",
+      "[[ 17.  14.   4. ...  20.  20.  20.]\n",
+      " [ 14.  28.   4. ...  20.  20.  20.]\n",
+      " [  4.   4.  17. ...  33.  33.  33.]\n",
+      " ...\n",
+      " [ 20.  20.  33. ... 585. 585. 513.]\n",
+      " [ 20.  20.  33. ... 585. 585. 513.]\n",
+      " [ 20.  20.  33. ... 513. 513. 567.]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.250953674316406 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 10.0, 'kernel_type': 'untiln'} is: \n",
+      "[[5.300e+01 1.400e+01 4.000e+00 ... 2.000e+01 2.000e+01 2.000e+01]\n",
+      " [1.400e+01 1.000e+02 4.000e+00 ... 2.000e+01 2.000e+01 2.000e+01]\n",
+      " [4.000e+00 4.000e+00 5.300e+01 ... 6.900e+01 6.900e+01 6.900e+01]\n",
+      " ...\n",
+      " [2.000e+01 2.000e+01 6.900e+01 ... 9.045e+03 9.045e+03 1.845e+03]\n",
+      " [2.000e+01 2.000e+01 6.900e+01 ... 9.045e+03 9.045e+03 1.845e+03]\n",
+      " [2.000e+01 2.000e+01 6.900e+01 ... 1.845e+03 1.845e+03 2.385e+03]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.04484176635742 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 100.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.13000e+02 1.40000e+01 4.00000e+00 ... 2.00000e+01 2.00000e+01\n",
+      "  2.00000e+01]\n",
+      " [1.40000e+01 8.20000e+02 4.00000e+00 ... 2.00000e+01 2.00000e+01\n",
+      "  2.00000e+01]\n",
+      " [4.00000e+00 4.00000e+00 4.13000e+02 ... 4.29000e+02 4.29000e+02\n",
+      "  4.29000e+02]\n",
+      " ...\n",
+      " [2.00000e+01 2.00000e+01 4.29000e+02 ... 7.35165e+05 7.35165e+05\n",
+      "  1.51650e+04]\n",
+      " [2.00000e+01 2.00000e+01 4.29000e+02 ... 7.35165e+05 7.35165e+05\n",
+      "  1.51650e+04]\n",
+      " [2.00000e+01 2.00000e+01 4.29000e+02 ... 1.51650e+04 1.51650e+04\n",
+      "  2.05650e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 33.83608937263489 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.0130000e+03 1.4000000e+01 4.0000000e+00 ... 2.0000000e+01\n",
+      "  2.0000000e+01 2.0000000e+01]\n",
+      " [1.4000000e+01 8.0200000e+03 4.0000000e+00 ... 2.0000000e+01\n",
+      "  2.0000000e+01 2.0000000e+01]\n",
+      " [4.0000000e+00 4.0000000e+00 4.0130000e+03 ... 4.0290000e+03\n",
+      "  4.0290000e+03 4.0290000e+03]\n",
+      " ...\n",
+      " [2.0000000e+01 2.0000000e+01 4.0290000e+03 ... 7.2148365e+07\n",
+      "  7.2148365e+07 1.4836500e+05]\n",
+      " [2.0000000e+01 2.0000000e+01 4.0290000e+03 ... 7.2148365e+07\n",
+      "  7.2148365e+07 1.4836500e+05]\n",
+      " [2.0000000e+01 2.0000000e+01 4.0290000e+03 ... 1.4836500e+05\n",
+      "  1.4836500e+05 2.0236500e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.33299779891968 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 10000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.00130000e+04 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.40000000e+01 8.00200000e+04 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 4.00130000e+04 ... 4.00290000e+04\n",
+      "  4.00290000e+04 4.00290000e+04]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 4.00290000e+04 ... 7.20148036e+09\n",
+      "  7.20148036e+09 1.48036500e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 4.00290000e+04 ... 7.20148036e+09\n",
+      "  7.20148036e+09 1.48036500e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 4.00290000e+04 ... 1.48036500e+06\n",
+      "  1.48036500e+06 2.02036500e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.42259502410889 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 100000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.0001300e+05 1.4000000e+01 4.0000000e+00 ... 2.0000000e+01\n",
+      "  2.0000000e+01 2.0000000e+01]\n",
+      " [1.4000000e+01 8.0002000e+05 4.0000000e+00 ... 2.0000000e+01\n",
+      "  2.0000000e+01 2.0000000e+01]\n",
+      " [4.0000000e+00 4.0000000e+00 4.0001300e+05 ... 4.0002900e+05\n",
+      "  4.0002900e+05 4.0002900e+05]\n",
+      " ...\n",
+      " [2.0000000e+01 2.0000000e+01 4.0002900e+05 ... 7.2001480e+11\n",
+      "  7.2001480e+11 1.4800365e+07]\n",
+      " [2.0000000e+01 2.0000000e+01 4.0002900e+05 ... 7.2001480e+11\n",
+      "  7.2001480e+11 1.4800365e+07]\n",
+      " [2.0000000e+01 2.0000000e+01 4.0002900e+05 ... 1.4800365e+07\n",
+      "  1.4800365e+07 2.0200365e+07]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.29456162452698 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.00001300e+06 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.40000000e+01 8.00002000e+06 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 4.00001300e+06 ... 4.00002900e+06\n",
+      "  4.00002900e+06 4.00002900e+06]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 4.00002900e+06 ... 7.20001480e+13\n",
+      "  7.20001480e+13 1.48000365e+08]\n",
+      " [2.00000000e+01 2.00000000e+01 4.00002900e+06 ... 7.20001480e+13\n",
+      "  7.20001480e+13 1.48000365e+08]\n",
+      " [2.00000000e+01 2.00000000e+01 4.00002900e+06 ... 1.48000365e+08\n",
+      "  1.48000365e+08 2.02000365e+08]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.014732122421265 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 10000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.00000130e+07 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.40000000e+01 8.00000200e+07 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 4.00000130e+07 ... 4.00000290e+07\n",
+      "  4.00000290e+07 4.00000290e+07]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 4.00000290e+07 ... 7.20000148e+15\n",
+      "  7.20000148e+15 1.48000036e+09]\n",
+      " [2.00000000e+01 2.00000000e+01 4.00000290e+07 ... 7.20000148e+15\n",
+      "  7.20000148e+15 1.48000036e+09]\n",
+      " [2.00000000e+01 2.00000000e+01 4.00000290e+07 ... 1.48000036e+09\n",
+      "  1.48000036e+09 2.02000036e+09]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.794917821884155 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 100000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.00000013e+08 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.40000000e+01 8.00000020e+08 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 4.00000013e+08 ... 4.00000029e+08\n",
+      "  4.00000029e+08 4.00000029e+08]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 4.00000029e+08 ... 7.20000015e+17\n",
+      "  7.20000015e+17 1.48000004e+10]\n",
+      " [2.00000000e+01 2.00000000e+01 4.00000029e+08 ... 7.20000015e+17\n",
+      "  7.20000015e+17 1.48000004e+10]\n",
+      " [2.00000000e+01 2.00000000e+01 4.00000029e+08 ... 1.48000004e+10\n",
+      "  1.48000004e+10 2.02000004e+10]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.659274101257324 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.00000001e+09 1.40000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.40000000e+01 8.00000002e+09 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 4.00000001e+09 ... 4.00000003e+09\n",
+      "  4.00000003e+09 4.00000003e+09]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 4.00000003e+09 ... 7.20000001e+19\n",
+      "  7.20000001e+19 1.48000000e+11]\n",
+      " [2.00000000e+01 2.00000000e+01 4.00000003e+09 ... 7.20000001e+19\n",
+      "  7.20000001e+19 1.48000000e+11]\n",
+      " [2.00000000e+01 2.00000000e+01 4.00000003e+09 ... 1.48000000e+11\n",
+      "  1.48000000e+11 2.02000000e+11]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.707022190093994 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 10000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.00e+10 1.40e+01 4.00e+00 ... 2.00e+01 2.00e+01 2.00e+01]\n",
+      " [1.40e+01 8.00e+10 4.00e+00 ... 2.00e+01 2.00e+01 2.00e+01]\n",
+      " [4.00e+00 4.00e+00 4.00e+10 ... 4.00e+10 4.00e+10 4.00e+10]\n",
+      " ...\n",
+      " [2.00e+01 2.00e+01 4.00e+10 ... 7.20e+21 7.20e+21 1.48e+12]\n",
+      " [2.00e+01 2.00e+01 4.00e+10 ... 7.20e+21 7.20e+21 1.48e+12]\n",
+      " [2.00e+01 2.00e+01 4.00e+10 ... 1.48e+12 1.48e+12 2.02e+12]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 29.498299598693848 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1e-10, 'kernel_type': 'size'} is: \n",
+      "[[8.00e-10 8.00e-10 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [8.00e-10 1.20e-09 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00 8.00e-10 ... 8.00e-10 8.00e-10 8.00e-10]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00 8.00e-10 ... 2.64e-08 2.64e-08 2.64e-08]\n",
+      " [0.00e+00 0.00e+00 8.00e-10 ... 2.64e-08 2.64e-08 2.64e-08]\n",
+      " [0.00e+00 0.00e+00 8.00e-10 ... 2.64e-08 2.64e-08 2.64e-08]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 27.96561574935913 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1e-09, 'kernel_type': 'size'} is: \n",
+      "[[8.00e-09 8.00e-09 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [8.00e-09 1.20e-08 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00 8.00e-09 ... 8.00e-09 8.00e-09 8.00e-09]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00 8.00e-09 ... 2.64e-07 2.64e-07 2.64e-07]\n",
+      " [0.00e+00 0.00e+00 8.00e-09 ... 2.64e-07 2.64e-07 2.64e-07]\n",
+      " [0.00e+00 0.00e+00 8.00e-09 ... 2.64e-07 2.64e-07 2.64e-07]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 28.048969745635986 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1e-08, 'kernel_type': 'size'} is: \n",
+      "[[8.00e-08 8.00e-08 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [8.00e-08 1.20e-07 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00 8.00e-08 ... 8.00e-08 8.00e-08 8.00e-08]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00 8.00e-08 ... 2.64e-06 2.64e-06 2.64e-06]\n",
+      " [0.00e+00 0.00e+00 8.00e-08 ... 2.64e-06 2.64e-06 2.64e-06]\n",
+      " [0.00e+00 0.00e+00 8.00e-08 ... 2.64e-06 2.64e-06 2.64e-06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8160>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 30.363208055496216 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1e-07, 'kernel_type': 'size'} is: \n",
+      "[[8.00e-07 8.00e-07 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [8.00e-07 1.20e-06 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00 8.00e-07 ... 8.00e-07 8.00e-07 8.00e-07]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00 8.00e-07 ... 2.64e-05 2.64e-05 2.64e-05]\n",
+      " [0.00e+00 0.00e+00 8.00e-07 ... 2.64e-05 2.64e-05 2.64e-05]\n",
+      " [0.00e+00 0.00e+00 8.00e-07 ... 2.64e-05 2.64e-05 2.64e-05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f548227f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 28.490288019180298 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1e-06, 'kernel_type': 'size'} is: \n",
+      "[[8.00e-06 8.00e-06 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [8.00e-06 1.20e-05 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00 8.00e-06 ... 8.00e-06 8.00e-06 8.00e-06]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00 8.00e-06 ... 2.64e-04 2.64e-04 2.64e-04]\n",
+      " [0.00e+00 0.00e+00 8.00e-06 ... 2.64e-04 2.64e-04 2.64e-04]\n",
+      " [0.00e+00 0.00e+00 8.00e-06 ... 2.64e-04 2.64e-04 2.64e-04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 29.05242395401001 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1e-05, 'kernel_type': 'size'} is: \n",
+      "[[8.00e-05 8.00e-05 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [8.00e-05 1.20e-04 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00 8.00e-05 ... 8.00e-05 8.00e-05 8.00e-05]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00 8.00e-05 ... 2.64e-03 2.64e-03 2.64e-03]\n",
+      " [0.00e+00 0.00e+00 8.00e-05 ... 2.64e-03 2.64e-03 2.64e-03]\n",
+      " [0.00e+00 0.00e+00 8.00e-05 ... 2.64e-03 2.64e-03 2.64e-03]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 28.77888822555542 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 0.0001, 'kernel_type': 'size'} is: \n",
+      "[[0.0008 0.0008 0.     ... 0.     0.     0.    ]\n",
+      " [0.0008 0.0012 0.     ... 0.     0.     0.    ]\n",
+      " [0.     0.     0.0008 ... 0.0008 0.0008 0.0008]\n",
+      " ...\n",
+      " [0.     0.     0.0008 ... 0.0264 0.0264 0.0264]\n",
+      " [0.     0.     0.0008 ... 0.0264 0.0264 0.0264]\n",
+      " [0.     0.     0.0008 ... 0.0264 0.0264 0.0264]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 28.845473766326904 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 0.001, 'kernel_type': 'size'} is: \n",
+      "[[0.008      0.008      0.         ... 0.         0.         0.        ]\n",
+      " [0.008      0.01200001 0.         ... 0.         0.         0.        ]\n",
+      " [0.         0.         0.008      ... 0.008      0.008      0.008     ]\n",
+      " ...\n",
+      " [0.         0.         0.008      ... 0.26400015 0.26400015 0.26400015]\n",
+      " [0.         0.         0.008      ... 0.26400015 0.26400015 0.26400015]\n",
+      " [0.         0.         0.008      ... 0.26400015 0.26400015 0.2640002 ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 29.189626216888428 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 0.01, 'kernel_type': 'size'} is: \n",
+      "[[0.080004   0.08       0.         ... 0.         0.         0.        ]\n",
+      " [0.08       0.120008   0.         ... 0.         0.         0.        ]\n",
+      " [0.         0.         0.080004   ... 0.080004   0.080004   0.080004  ]\n",
+      " ...\n",
+      " [0.         0.         0.080004   ... 2.64014801 2.64014801 2.640148  ]\n",
+      " [0.         0.         0.080004   ... 2.64014801 2.64014801 2.640148  ]\n",
+      " [0.         0.         0.080004   ... 2.640148   2.640148   2.640202  ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 28.69552230834961 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 0.1, 'kernel_type': 'size'} is: \n",
+      "[[ 0.804    0.8      0.      ...  0.       0.       0.     ]\n",
+      " [ 0.8      1.208    0.      ...  0.       0.       0.     ]\n",
+      " [ 0.       0.       0.804   ...  0.804    0.804    0.804  ]\n",
+      " ...\n",
+      " [ 0.       0.       0.804   ... 26.54872 26.54872 26.548  ]\n",
+      " [ 0.       0.       0.804   ... 26.54872 26.54872 26.548  ]\n",
+      " [ 0.       0.       0.804   ... 26.548   26.548   26.602  ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6518>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 28.828312873840332 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1.0, 'kernel_type': 'size'} is: \n",
+      "[[ 12.   8.   0. ...   0.   0.   0.]\n",
+      " [  8.  20.   0. ...   0.   0.   0.]\n",
+      " [  0.   0.  12. ...  12.  12.  12.]\n",
+      " ...\n",
+      " [  0.   0.  12. ... 484. 484. 412.]\n",
+      " [  0.   0.  12. ... 484. 484. 412.]\n",
+      " [  0.   0.  12. ... 412. 412. 466.]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 29.196213245391846 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 10.0, 'kernel_type': 'size'} is: \n",
+      "[[4.08000e+03 8.00000e+01 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [8.00000e+01 8.12000e+03 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [0.00000e+00 0.00000e+00 4.08000e+03 ... 4.08000e+03 4.08000e+03\n",
+      "  4.08000e+03]\n",
+      " ...\n",
+      " [0.00000e+00 0.00000e+00 4.08000e+03 ... 7.35064e+06 7.35064e+06\n",
+      "  1.50640e+05]\n",
+      " [0.00000e+00 0.00000e+00 4.08000e+03 ... 7.35064e+06 7.35064e+06\n",
+      "  1.50640e+05]\n",
+      " [0.00000e+00 0.00000e+00 4.08000e+03 ... 1.50640e+05 1.50640e+05\n",
+      "  2.04640e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98abac50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 30.727330207824707 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 100.0, 'kernel_type': 'size'} is: \n",
+      "[[4.00080000e+06 8.00000000e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [8.00000000e+02 8.00120000e+06 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00080000e+06 ... 4.00080000e+06\n",
+      "  4.00080000e+06 4.00080000e+06]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 4.00080000e+06 ... 7.20148026e+11\n",
+      "  7.20148026e+11 1.48026400e+08]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00080000e+06 ... 7.20148026e+11\n",
+      "  7.20148026e+11 1.48026400e+08]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00080000e+06 ... 1.48026400e+08\n",
+      "  1.48026400e+08 2.02026400e+08]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 28.894534826278687 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.00000800e+09 8.00000000e+03 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [8.00000000e+03 8.00001200e+09 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000800e+09 ... 4.00000800e+09\n",
+      "  4.00000800e+09 4.00000800e+09]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000800e+09 ... 7.20001480e+16\n",
+      "  7.20001480e+16 1.48000264e+11]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000800e+09 ... 7.20001480e+16\n",
+      "  7.20001480e+16 1.48000264e+11]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000800e+09 ... 1.48000264e+11\n",
+      "  1.48000264e+11 2.02000264e+11]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 30.132886171340942 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 10000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.00000008e+12 8.00000000e+04 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [8.00000000e+04 8.00000012e+12 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000008e+12 ... 4.00000008e+12\n",
+      "  4.00000008e+12 4.00000008e+12]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000008e+12 ... 7.20000015e+21\n",
+      "  7.20000015e+21 1.48000003e+14]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000008e+12 ... 7.20000015e+21\n",
+      "  7.20000015e+21 1.48000003e+14]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000008e+12 ... 1.48000003e+14\n",
+      "  1.48000003e+14 2.02000003e+14]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAADaVJREFUeJzt3UHMFPd9xvHnqSFEiRLF1Aki2G1diiI5TYvMK/MKWYhQKbWtqpiLsQ8NiqySSLZ6xenFuUSKD9ErRWqMiIpMDrHDxTIHWmLRAwfLSbCEHBw1zUuCZd4XgxOqJAoqyUt+Oey89bDssr93Z3Zn353vR0KzOzs78/vP8j6a+e9/Zh0RAoBB/qTpAgCsDoQFgBTCAkAKYQEghbAAkEJYAEhpPCxsP2T7J7bnbT/TdD2jYvuC7R/ZPmv7TDFvve1Xbf+0mN7ZdJ1V2D5i+4rtc6V5Pdvojm8Un/ubtu9vrvLh9WnzV2wvFJ/1WduPlF77ctHmn9j++2aqHk6jYWH7Dkn/JulhSfdJesL2fU3WNGKfjYitETFTPH9G0qmI2CLpVPF8NXtB0kNd8/q18WFJW4p/ByQ9P6Ya6/aCbm2zJM0Vn/XWiDghScX/7cclfbp4zzeLv4FVoekjiwckzUfEzyLid5JekrSn4ZrGaY+ko8Xjo5IebbCWyiLitKSrXbP7tXGPpG9Hx+uSPmZ743gqrU+fNvezR9JLEXE9In4uaV6dv4FVoemw2CTpndLzi8W8aRSSvmf7DdsHinkbIuJS8fhdSRuaKW2k+rVx2j/7p4vTqyOl08tV3eamw6JNHoyI+9U5/H7K9s7yi9EZdz/VY+/b0MbC85I2S9oq6ZKkrzdbTj2aDosFSfeUnt9dzJs6EbFQTK9Ielmdw8/Ly4fexfRKcxWOTL82Tu1nHxGXI+JGRPxB0rf0/qnGqm5z02HxQ0lbbN9r+wPqdP4cb7im2tn+sO2PLD+W9DlJ59Rp6/5isf2SXmmmwpHq18bjkj5ffCsyK+lXpdOVVa2r72WvOp+11Gnz47bX2b5Xnc7dH4y7vmGtaXLjEbFk+2lJJyXdIelIRLzVZE0jskHSy7alzj7/TkT8p+0fSjpm+0lJb0t6rMEaK7P9oqRdku6yfVHSs5K+pt5tPCHpEXU6+a5J+sLYC65Bnzbvsr1VnVOuC5K+KEkR8ZbtY5J+LGlJ0lMRcaOJuodhLlEHkNH0aQiAVYKwAJBCWABIISwApBAWAFJGFhYrvZq0NAS6NWhzO0xLm0cSFkNeTToVO3SFaHM7TEWbR3Vk0farSYGpM6oRnL2urtveb+EPeF18UB/SR72+VSPEaHM7THKb/0+/1e/iujPLNjbcuziPOyB1duaD799MCMCYfD9OpZcd1WnIwKvrIuJwRMxExMxarRtRGQDqMqqwaMXVpECbjOQ0pEVXkwKtMbI+i+ImpSdGtX4A48UITgAphAWAFMICQAphASCFsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAkAKYQEghbAAkEJYAEghLACkEBYAUggLACmEBYAUwgJACmEBIIWwAJBCWABIISwApBAWAFIICwAphAWAFMICQAphASCFsOhybe92Xdu7vZHtTrryvilPm6y917av7d2u+blZzc/N3vT6/Nxs6v1Va8iss7z/etU17LZHibAAkOKIaLoGfdTrY7v/rukygNb5fpzSr+OqM8tyZHEbS7u3tXr7w1ravW3V1o7+OLIAWowjCwC1IywApBAWAFIICwAphAWAFMICQAphASCFsACQQljUYJIvAhtUW9MXgvUyCfVkLu6qcgFYE6rWywhOoMUYwQmgdoQFgBTCAkAKYQEghbAAkEJYAEghLACkEBYAUggLAClrqrzZ9gVJv5F0Q9JSRMzYXi/pu5L+QtIFSY9FxP9WKxNA0+o4svhsRGyNiJni+TOSTkXEFkmniucAVrlRnIbskXS0eHxU0qMj2AaAMasaFiHpe7bfsH2gmLchIi4Vj9+VtKHiNgBMgEp9FpIejIgF25+Q9Krt/y6/GBFhu+dlrUW4HJCkD+pDFcsAMGqVjiwiYqGYXpH0sqQHJF22vVGSiumVPu89HBEzETGzVuuqlAFgDIYOC9sftv2R5ceSPifpnKTjkvYXi+2X9ErVIseJX1Hvj19Rz9Uwrb+iPvTNb2z/pTpHE1LndOY7EfFV238q6ZikP5P0tjpfnV693bq4+Q3QjJXc/GboPouI+Jmkv+0x/5eS+MsHpgwjOAGkEBYAUgiL21java3V2x/W0u5tq7Z29MfdvYEW4+7eAGpHWABIISwApBAWAFIICwAphAWAFMICQAphASCFsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAkAKYVGDSb4z96Damr47dy+TUE/mjttV7srdhKr1cvMboMW4+Q2A2hEWAFIICwAphAWAFMICQAphASCFsKjBJIwL6IdxFsNhnMWtCAsAKQzKAlqMQVkAakdYAEghLACkEBYAUggLACmEBYAUwgJACmEBIIWw6NLU8OdJGOI8SHnflKdN1t5r29f2btf83Kzm52Zver3XcOc6au9eR2ad5f1XZRj2OPc9YQEgheHeWLGFgzu06bnXmi5jqiwc3CFJK96vVT8LhntXwGlIf8v7ZtNzr3Eacpt1DHMasum514b6o7/zf26s+D3D4sgCaDGOLCrgyKI/OjhzNdDBCaDVOA0BWozTEAC1IywApBAWt7G0e1urtz+spd3bVm3t6I+wAJBCByfQYnRwAqjdwLCwfcT2FdvnSvPW237V9k+L6Z3FfNv+hu1522/avn+UxQMYn8yRxQuSHuqa94ykUxGxRdKp4rkkPSxpS/HvgKTn6ykTQNMGhkVEnJZ0tWv2HklHi8dHJT1amv/t6Hhd0sdsb6yrWADNGbbPYkNEXCoevytpQ/F4k6R3SstdLOYBWOUqd3BG5+uUFX+lYvuA7TO2z/xe16uWAWDEhg2Ly8unF8X0SjF/QdI9peXuLubdIiIOR8RMRMys1bohywAwLsOGxXFJ+4vH+yW9Upr/+eJbkVlJvyqdrgBYxdYMWsD2i5J2SbrL9kVJz0r6mqRjtp+U9Lakx4rFT0h6RNK8pGuSvjCCmgE0YGBYRMQTfV66Zchl0X/xVNWiAEweRnACSCEsAKQQFgBSCIsaTPLNdgfV1vQNd3uZhHoyN9GtcqPdJlStl0vUgRbjEnUAtSMsAKQQFgBSCAsAKYQFgBTCAkAKYQEghbAAkEJYAEghLLo0Nfx5EoY4D1LeN+Vpk7X32va1vds1Pzer+bnZm17vNdy5jtq715FZZ3n/VRmGPc59z3BvoMUY7g2gdoQFgBTCAkAKYdGFDs7+6ODM1TCtHZyERZfFndbizlR/T+3bnXTlfVOeNll7r20v7rTO7zuk8/sO3fT6+X2HUu+vWkNmneX916uuYbc9SoQFgJSBPwXQNp883cxXyU1tdyXKNS4/brruXtv/5OnQZn3pltc3f/dL+iu9PvD9VWvIrLO8/zbr1rqG3fYoMc4CaDHGWQCoHWHRZbkXvYntTrryvilPm6y917bn52Z1cvGsTi6even1k4tnU++vWsNK7gy+XGtd2x4lTkOAFuM0BEDtCAsAKYQFgBTCogvDvftjuHeuhmkd7k0HJ9BidHACqB1hASCFsACQQlgASCEsajDJQ7UH1db0cO1eJqGezBDsKsO0m1C1Xr4NAVqMb0MA1I6wAJBCWABIISwApBAWAFIICwAphAWAFMKiBpMwiKgfBmUNh0FZt2JQFtBiDMqqgJvf9MfNb3I1cPObEeLIAmgGRxYAakdYAEghLLrQZ9EffRa5GlrbZ2H7iKR/kHQlIv66mPcVSf8s6b1isX+NiBPFa1+W9KSkG5L+JSJODiqCPgugGXX3Wbwg6aEe8+ciYmvxbzko7pP0uKRPF+/5pu07cmUDmGQDwyIiTku6mlzfHkkvRcT1iPi5pHlJD1SoD8CEqNJn8bTtN20fsX1nMW+TpHdKy1ws5gFY5YYNi+clbZa0VdIlSV9f6QpsH7B9xvaZ3+v6kGUAGJehwiIiLkfEjYj4g6Rv6f1TjQVJ95QWvbuY12sdhyNiJiJm1mrdMGUAGKOhwsL2xtLTvZLOFY+PS3rc9jrb90raIukH1UoEMAnWDFrA9ouSdkm6y/ZFSc9K2mV7q6SQdEHSFyUpIt6yfUzSjyUtSXoqIm6MpnQA45T5NuSJiNgYEWsj4u6I+PeI+KeI+ExE/E1E/GNEXCot/9WI2BwRn4qI/xht+fVjUFZ/DMrK1dDaQVnjwKAsoBlcSFYBRxb9cWSRq2FajywIiy6LO63FnamgrX27k668b8rTJmvvte3Fndb5fYd0ft+hm14/v+9Q6v1Va8iss7z/etU17LZHidMQrNjCwR3a9NxrTZcxVRYO7pCkFe/Xqp8FpyEAaseRBdBiHFkAqB1hASCFsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAlhllnZv09LubWPfLmEBIGXgnbIATJY1//VGI9vlyKIL97Pob3nfLBzcwf0sbrOOYe5nsXBwx/9feboS7x3/1IrfMywuJANajAvJANSOsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAkAKYQEghbCoQZWfnxu1QbUtD4ueJJNQz8nFs7UsM0mq1stwb6DFGO4NoHaEBYAUwgJACmEBIGUiOjhtvyfpt5J+0XQtY3aXaHMbTHKb/zwiPp5ZcCLCQpJsn4mImabrGCfa3A7T0mZOQwCkEBYAUiYpLA43XUADaHM7TEWbJ6bPAsBkm6QjCwATjLAAkEJYAEghLACkEBYAUv4I7XczZv1yHfoAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 29.20766592025757 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 100000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.00e+15 8.00e+05 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [8.00e+05 8.00e+15 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00 4.00e+15 ... 4.00e+15 4.00e+15 4.00e+15]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00 4.00e+15 ... 7.20e+26 7.20e+26 1.48e+17]\n",
+      " [0.00e+00 0.00e+00 4.00e+15 ... 7.20e+26 7.20e+26 1.48e+17]\n",
+      " [0.00e+00 0.00e+00 4.00e+15 ... 1.48e+17 1.48e+17 2.02e+17]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 28.722581148147583 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1000000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.00e+18 8.00e+06 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [8.00e+06 8.00e+18 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00 4.00e+18 ... 4.00e+18 4.00e+18 4.00e+18]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00 4.00e+18 ... 7.20e+31 7.20e+31 1.48e+20]\n",
+      " [0.00e+00 0.00e+00 4.00e+18 ... 7.20e+31 7.20e+31 1.48e+20]\n",
+      " [0.00e+00 0.00e+00 4.00e+18 ... 1.48e+20 1.48e+20 2.02e+20]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 28.862783670425415 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 10000000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.00e+21 8.00e+07 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [8.00e+07 8.00e+21 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00 4.00e+21 ... 4.00e+21 4.00e+21 4.00e+21]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00 4.00e+21 ... 7.20e+36 7.20e+36 1.48e+23]\n",
+      " [0.00e+00 0.00e+00 4.00e+21 ... 7.20e+36 7.20e+36 1.48e+23]\n",
+      " [0.00e+00 0.00e+00 4.00e+21 ... 1.48e+23 1.48e+23 2.02e+23]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 28.767455339431763 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 100000000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.00e+24 8.00e+08 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [8.00e+08 8.00e+24 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00 4.00e+24 ... 4.00e+24 4.00e+24 4.00e+24]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00 4.00e+24 ... 7.20e+41 7.20e+41 1.48e+26]\n",
+      " [0.00e+00 0.00e+00 4.00e+24 ... 7.20e+41 7.20e+41 1.48e+26]\n",
+      " [0.00e+00 0.00e+00 4.00e+24 ... 1.48e+26 1.48e+26 2.02e+26]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acda90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 28.580508947372437 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.00e+27 8.00e+09 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [8.00e+09 8.00e+27 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00 4.00e+27 ... 4.00e+27 4.00e+27 4.00e+27]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00 4.00e+27 ... 7.20e+46 7.20e+46 1.48e+29]\n",
+      " [0.00e+00 0.00e+00 4.00e+27 ... 7.20e+46 7.20e+46 1.48e+29]\n",
+      " [0.00e+00 0.00e+00 4.00e+27 ... 1.48e+29 1.48e+29 2.02e+29]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 28.896726369857788 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 10000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.00e+30 8.00e+10 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [8.00e+10 8.00e+30 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00 4.00e+30 ... 4.00e+30 4.00e+30 4.00e+30]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00 4.00e+30 ... 7.20e+51 7.20e+51 1.48e+32]\n",
+      " [0.00e+00 0.00e+00 4.00e+30 ... 7.20e+51 7.20e+51 1.48e+32]\n",
+      " [0.00e+00 0.00e+00 4.00e+30 ... 1.48e+32 1.48e+32 2.02e+32]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483e898>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.25094389915466 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1e-10, 'kernel_type': 'branching'} is: \n",
+      "[[  8.           8.           0.         ...   0.           0.\n",
+      "    0.        ]\n",
+      " [  8.          12.           0.         ...   0.           0.\n",
+      "    0.        ]\n",
+      " [  0.           0.           8.         ...   8.           8.\n",
+      "    8.        ]\n",
+      " ...\n",
+      " [  0.           0.           8.         ... 264.00000001 264.00000001\n",
+      "  264.00000001]\n",
+      " [  0.           0.           8.         ... 264.00000001 264.00000001\n",
+      "  264.00000001]\n",
+      " [  0.           0.           8.         ... 264.00000001 264.00000001\n",
+      "  264.00000002]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 33.958739280700684 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1e-09, 'kernel_type': 'branching'} is: \n",
+      "[[  8.           8.           0.         ...   0.           0.\n",
+      "    0.        ]\n",
+      " [  8.          12.00000001   0.         ...   0.           0.\n",
+      "    0.        ]\n",
+      " [  0.           0.           8.         ...   8.           8.\n",
+      "    8.        ]\n",
+      " ...\n",
+      " [  0.           0.           8.         ... 264.00000015 264.00000015\n",
+      "  264.00000015]\n",
+      " [  0.           0.           8.         ... 264.00000015 264.00000015\n",
+      "  264.00000015]\n",
+      " [  0.           0.           8.         ... 264.00000015 264.00000015\n",
+      "  264.0000002 ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 33.81914472579956 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1e-08, 'kernel_type': 'branching'} is: \n",
+      "[[  8.00000004   8.           0.         ...   0.           0.\n",
+      "    0.        ]\n",
+      " [  8.          12.00000008   0.         ...   0.           0.\n",
+      "    0.        ]\n",
+      " [  0.           0.           8.00000004 ...   8.00000004   8.00000004\n",
+      "    8.00000004]\n",
+      " ...\n",
+      " [  0.           0.           8.00000004 ... 264.00000148 264.00000148\n",
+      "  264.00000148]\n",
+      " [  0.           0.           8.00000004 ... 264.00000148 264.00000148\n",
+      "  264.00000148]\n",
+      " [  0.           0.           8.00000004 ... 264.00000148 264.00000148\n",
+      "  264.00000202]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483ec88>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.115713119506836 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1e-07, 'kernel_type': 'branching'} is: \n",
+      "[[  8.0000004   8.          0.        ...   0.          0.\n",
+      "    0.       ]\n",
+      " [  8.         12.0000008   0.        ...   0.          0.\n",
+      "    0.       ]\n",
+      " [  0.          0.          8.0000004 ...   8.0000004   8.0000004\n",
+      "    8.0000004]\n",
+      " ...\n",
+      " [  0.          0.          8.0000004 ... 264.0000148 264.0000148\n",
+      "  264.0000148]\n",
+      " [  0.          0.          8.0000004 ... 264.0000148 264.0000148\n",
+      "  264.0000148]\n",
+      " [  0.          0.          8.0000004 ... 264.0000148 264.0000148\n",
+      "  264.0000202]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.222052574157715 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1e-06, 'kernel_type': 'branching'} is: \n",
+      "[[  8.000004   8.         0.       ...   0.         0.         0.      ]\n",
+      " [  8.        12.000008   0.       ...   0.         0.         0.      ]\n",
+      " [  0.         0.         8.000004 ...   8.000004   8.000004   8.000004]\n",
+      " ...\n",
+      " [  0.         0.         8.000004 ... 264.000148 264.000148 264.000148]\n",
+      " [  0.         0.         8.000004 ... 264.000148 264.000148 264.000148]\n",
+      " [  0.         0.         8.000004 ... 264.000148 264.000148 264.000202]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.18193459510803 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1e-05, 'kernel_type': 'branching'} is: \n",
+      "[[  8.00004      8.           0.         ...   0.           0.\n",
+      "    0.        ]\n",
+      " [  8.          12.00008      0.         ...   0.           0.\n",
+      "    0.        ]\n",
+      " [  0.           0.           8.00004    ...   8.00004      8.00004\n",
+      "    8.00004   ]\n",
+      " ...\n",
+      " [  0.           0.           8.00004    ... 264.00148001 264.00148001\n",
+      "  264.00148   ]\n",
+      " [  0.           0.           8.00004    ... 264.00148001 264.00148001\n",
+      "  264.00148   ]\n",
+      " [  0.           0.           8.00004    ... 264.00148    264.00148\n",
+      "  264.00202   ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.13133454322815 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 0.0001, 'kernel_type': 'branching'} is: \n",
+      "[[  8.0004       8.           0.         ...   0.           0.\n",
+      "    0.        ]\n",
+      " [  8.          12.0008       0.         ...   0.           0.\n",
+      "    0.        ]\n",
+      " [  0.           0.           8.0004     ...   8.0004       8.0004\n",
+      "    8.0004    ]\n",
+      " ...\n",
+      " [  0.           0.           8.0004     ... 264.01480072 264.01480072\n",
+      "  264.0148    ]\n",
+      " [  0.           0.           8.0004     ... 264.01480072 264.01480072\n",
+      "  264.0148    ]\n",
+      " [  0.           0.           8.0004     ... 264.0148     264.0148\n",
+      "  264.0202    ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 33.92162251472473 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 0.001, 'kernel_type': 'branching'} is: \n",
+      "[[  8.004      8.         0.       ...   0.         0.         0.      ]\n",
+      " [  8.        12.008      0.       ...   0.         0.         0.      ]\n",
+      " [  0.         0.         8.004    ...   8.004      8.004      8.004   ]\n",
+      " ...\n",
+      " [  0.         0.         8.004    ... 264.148072 264.148072 264.148   ]\n",
+      " [  0.         0.         8.004    ... 264.148072 264.148072 264.148   ]\n",
+      " [  0.         0.         8.004    ... 264.148    264.148    264.202   ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 33.99196529388428 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 0.01, 'kernel_type': 'branching'} is: \n",
+      "[[  8.04     8.       0.     ...   0.       0.       0.    ]\n",
+      " [  8.      12.08     0.     ...   0.       0.       0.    ]\n",
+      " [  0.       0.       8.04   ...   8.04     8.04     8.04  ]\n",
+      " ...\n",
+      " [  0.       0.       8.04   ... 265.4872 265.4872 265.48  ]\n",
+      " [  0.       0.       8.04   ... 265.4872 265.4872 265.48  ]\n",
+      " [  0.       0.       8.04   ... 265.48   265.48   266.02  ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7fd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 33.902352809906006 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 0.1, 'kernel_type': 'branching'} is: \n",
+      "[[  8.4    8.     0.   ...   0.     0.     0.  ]\n",
+      " [  8.    12.8    0.   ...   0.     0.     0.  ]\n",
+      " [  0.     0.     8.4  ...   8.4    8.4    8.4 ]\n",
+      " ...\n",
+      " [  0.     0.     8.4  ... 279.52 279.52 278.8 ]\n",
+      " [  0.     0.     8.4  ... 279.52 279.52 278.8 ]\n",
+      " [  0.     0.     8.4  ... 278.8  278.8  284.2 ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 33.79565358161926 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1.0, 'kernel_type': 'branching'} is: \n",
+      "[[ 12.   8.   0. ...   0.   0.   0.]\n",
+      " [  8.  20.   0. ...   0.   0.   0.]\n",
+      " [  0.   0.  12. ...  12.  12.  12.]\n",
+      " ...\n",
+      " [  0.   0.  12. ... 484. 484. 412.]\n",
+      " [  0.   0.  12. ... 484. 484. 412.]\n",
+      " [  0.   0.  12. ... 412. 412. 466.]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.03077268600464 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 10.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.800e+01 8.000e+00 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [8.000e+00 9.200e+01 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 4.800e+01 ... 4.800e+01 4.800e+01 4.800e+01]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 4.800e+01 ... 8.944e+03 8.944e+03 1.744e+03]\n",
+      " [0.000e+00 0.000e+00 4.800e+01 ... 8.944e+03 8.944e+03 1.744e+03]\n",
+      " [0.000e+00 0.000e+00 4.800e+01 ... 1.744e+03 1.744e+03 2.284e+03]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.141064167022705 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 100.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.08000e+02 8.00000e+00 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [8.00000e+00 8.12000e+02 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [0.00000e+00 0.00000e+00 4.08000e+02 ... 4.08000e+02 4.08000e+02\n",
+      "  4.08000e+02]\n",
+      " ...\n",
+      " [0.00000e+00 0.00000e+00 4.08000e+02 ... 7.35064e+05 7.35064e+05\n",
+      "  1.50640e+04]\n",
+      " [0.00000e+00 0.00000e+00 4.08000e+02 ... 7.35064e+05 7.35064e+05\n",
+      "  1.50640e+04]\n",
+      " [0.00000e+00 0.00000e+00 4.08000e+02 ... 1.50640e+04 1.50640e+04\n",
+      "  2.04640e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.923821210861206 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1000.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.0080000e+03 8.0000000e+00 0.0000000e+00 ... 0.0000000e+00\n",
+      "  0.0000000e+00 0.0000000e+00]\n",
+      " [8.0000000e+00 8.0120000e+03 0.0000000e+00 ... 0.0000000e+00\n",
+      "  0.0000000e+00 0.0000000e+00]\n",
+      " [0.0000000e+00 0.0000000e+00 4.0080000e+03 ... 4.0080000e+03\n",
+      "  4.0080000e+03 4.0080000e+03]\n",
+      " ...\n",
+      " [0.0000000e+00 0.0000000e+00 4.0080000e+03 ... 7.2148264e+07\n",
+      "  7.2148264e+07 1.4826400e+05]\n",
+      " [0.0000000e+00 0.0000000e+00 4.0080000e+03 ... 7.2148264e+07\n",
+      "  7.2148264e+07 1.4826400e+05]\n",
+      " [0.0000000e+00 0.0000000e+00 4.0080000e+03 ... 1.4826400e+05\n",
+      "  1.4826400e+05 2.0226400e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.16166019439697 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 10000.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.00080000e+04 8.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [8.00000000e+00 8.00120000e+04 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00080000e+04 ... 4.00080000e+04\n",
+      "  4.00080000e+04 4.00080000e+04]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 4.00080000e+04 ... 7.20148026e+09\n",
+      "  7.20148026e+09 1.48026400e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00080000e+04 ... 7.20148026e+09\n",
+      "  7.20148026e+09 1.48026400e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00080000e+04 ... 1.48026400e+06\n",
+      "  1.48026400e+06 2.02026400e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.23010802268982 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 100000.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.0000800e+05 8.0000000e+00 0.0000000e+00 ... 0.0000000e+00\n",
+      "  0.0000000e+00 0.0000000e+00]\n",
+      " [8.0000000e+00 8.0001200e+05 0.0000000e+00 ... 0.0000000e+00\n",
+      "  0.0000000e+00 0.0000000e+00]\n",
+      " [0.0000000e+00 0.0000000e+00 4.0000800e+05 ... 4.0000800e+05\n",
+      "  4.0000800e+05 4.0000800e+05]\n",
+      " ...\n",
+      " [0.0000000e+00 0.0000000e+00 4.0000800e+05 ... 7.2001480e+11\n",
+      "  7.2001480e+11 1.4800264e+07]\n",
+      " [0.0000000e+00 0.0000000e+00 4.0000800e+05 ... 7.2001480e+11\n",
+      "  7.2001480e+11 1.4800264e+07]\n",
+      " [0.0000000e+00 0.0000000e+00 4.0000800e+05 ... 1.4800264e+07\n",
+      "  1.4800264e+07 2.0200264e+07]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 33.99363446235657 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.00000800e+06 8.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [8.00000000e+00 8.00001200e+06 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000800e+06 ... 4.00000800e+06\n",
+      "  4.00000800e+06 4.00000800e+06]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000800e+06 ... 7.20001480e+13\n",
+      "  7.20001480e+13 1.48000264e+08]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000800e+06 ... 7.20001480e+13\n",
+      "  7.20001480e+13 1.48000264e+08]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000800e+06 ... 1.48000264e+08\n",
+      "  1.48000264e+08 2.02000264e+08]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 34.219242095947266 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 10000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.00000080e+07 8.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [8.00000000e+00 8.00000120e+07 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000080e+07 ... 4.00000080e+07\n",
+      "  4.00000080e+07 4.00000080e+07]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000080e+07 ... 7.20000148e+15\n",
+      "  7.20000148e+15 1.48000026e+09]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000080e+07 ... 7.20000148e+15\n",
+      "  7.20000148e+15 1.48000026e+09]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000080e+07 ... 1.48000026e+09\n",
+      "  1.48000026e+09 2.02000026e+09]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAADdtJREFUeJzt3V+sFOUZx/HfU0GMRqOUliDa1lJiov1D5AROiBKkiUXTFLgRvKjEmKKJprdob/TGRC6ExKRCMCXghX+4MXJBi4Ze2MRYxYRYNLUuipFzEGxpbCMWPfj0YufgsmeXfc7O7L6zO99PQnb33dmdZ2Y5v8y8+8675u4CgE6+lboAAIOBsAAQQlgACCEsAIQQFgBCCAsAIcnDwsxWmdl7ZlYzs4dS19MrZnbUzP5mZofM7GDWNtvMXjGz97Pbq1LXmYeZ7TSzk2Z2uKGt5TZa3ZPZ5/62md2UrvLutdnmR81sLPusD5nZHQ3PPZxt83tm9os0VXcnaViY2UWSfi/pdkk3SLrLzG5IWVOP3erui9x9JHv8kKQD7r5Q0oHs8SDbJWlVU1u7bbxd0sLs30ZJ2/pUY9F2aeo2S9LW7LNe5O77JCn7v71e0o3Za57K/gYGQuojiyWSau7+gbt/Kel5SasT19RPqyXtzu7vlrQmYS25ufurkk41NbfbxtWSnvG61yVdaWbz+lNpcdpsczurJT3v7mfc/UNJNdX/BgZC6rCYL+njhsfHsrZh5JJeNrO3zGxj1jbX3Y9n9z+RNDdNaT3VbhuH/bN/MDu92tlwejnQ25w6LKrkZne/SfXD7wfMbHnjk14fdz/UY++rsI2ZbZIWSFok6bikJ9KWU4zUYTEm6dqGx9dkbUPH3cey25OSXlT98PPE5KF3dnsyXYU9024bh/azd/cT7n7W3b+W9LS+OdUY6G1OHRZvSlpoZteZ2cWqd/7sTVxT4czsMjO7fPK+pNskHVZ9Wzdki22Q9FKaCnuq3TbulXR39q3IqKTPGk5XBlpT38ta1T9rqb7N681slpldp3rn7hv9rq9bM1Ku3N0nzOxBSfslXSRpp7u/k7KmHpkr6UUzk+r7/Fl3/5OZvSlpj5ndK+kjSXcmrDE3M3tO0gpJc8zsmKRHJD2u1tu4T9IdqnfynZZ0T98LLkCbbV5hZotUP+U6Kuk+SXL3d8xsj6R3JU1IesDdz6aouxvGJeoAIlKfhgAYEIQFgBDCAkAIYQEghLAAENKzsJju1aQNQ6Arg22uhmHZ5p6ERZdXkw7FDp0mtrkahmKbe3VkUfWrSYGh06sRnK2urlvabuGLbZZfokt1hc2u1AgxtrkayrzN/9Pn+tLPWGTZZMO9s/O4jVJ9Z978zWRCAPrkr34gvGyvTkM6Xl3n7jvcfcTdR2ZqVo/KAFCUXoVFJa4mBaqkJ6chFbqaFKiMnvVZZJOU7uvV+wPoL0ZwAgghLACEEBYAQggLACGEBYAQwgJACGEBIISwABBCWAAIISwAhBAWAEIICwAhhAWAEMICQAhhASCEsAAQQlgACCEsAIQQFgBCCAsAIYQFgBDCAkAIYQEghLAAEEJYAAghLACEEBYAQggLACGERZMv1izRF2uWJFlv2TXum9Nrl05pS2Gyjua22pZR1baMnvd8bcto6PV5a4i85+Qyk7UWte5eIiwAhJi7p65BV9hsX2o/T10GUDl/9QP6j5+yyLIcWVzAxMrFlV5/tyZWLh7Y2tEeRxZAhXFkAaBwhAWAEMICQAhhASCEsAAQQlgACCEsAIQQFgBCCIsClPkisE61pb4QrJUy1BO5uCvPBWAp5K2XEZxAhTGCE0DhCAsAIYQFgBDCAkAIYQEghLAAEEJYAAghLACEEBYAQmbkebGZHZX0X0lnJU24+4iZzZb0gqQfSDoq6U53/3e+MgGkVsSRxa3uvsjdR7LHD0k64O4LJR3IHgMYcL04DVktaXd2f7ekNT1YB4A+yxsWLullM3vLzDZmbXPd/Xh2/xNJc3OuA0AJ5OqzkHSzu4+Z2XclvWJmf2980t3dzFpe1pqFy0ZJukSX5iwDQK/lOrJw97Hs9qSkFyUtkXTCzOZJUnZ7ss1rd7j7iLuPzNSsPGUA6IOuw8LMLjOzyyfvS7pN0mFJeyVtyBbbIOmlvEX2U6rJYPr5a9jdOr126Xm//t3clqqmVm38inrxup78xsx+qPrRhFQ/nXnW3R8zs29L2iPpe5I+Uv2r01MXei8mvwHSmM7kN133Wbj7B5J+1qL9X5L4yweGDCM4AYQQFgBCCIsLmFi5uNLr79bEysUDWzvaY3ZvoMKY3RtA4QgLACGEBYAQwgJACGEBIISwABBCWAAIISwAhBAWAEIICwAhhAWAEMICQAhhASCEsAAQQlgACCEsCpBiNvCoTrWlms38Qsow03lkxu08s3KnkLdeJr8BKozJbwAUjrAAEEJYAAghLACEEBYAQggLACGERQHKNk6hUafaUv8KeitlqIdxFlMRFgBCGJQFVBiDsgAUjrAAEEJYAAghLACEEBYAQggLACGEBYAQwgJACGHRJNU0c2UY4txJ49DwxtuUtbda9+m1S1XbMqraltHznm813LmI2pvfI/KejfuvtrX7Ydj93PeEBYAQhntj2sY2LdP8za+lLmOojG1aJknT3q95PwuGe+eQ6rB6kE5D5m9+rfynIVtHVdvadBrS4nC/LKch8ze/1tUf/VX/ODvt13SLIwugwjiyyIEOzvbo4IzVQAcngErjNASoME5DABSOsAAQQlhcwMTKxZVef7cmVi4e2NrRHmEBIIQOTqDC6OAEULiOYWFmO83spJkdbmibbWavmNn72e1VWbuZ2ZNmVjOzt83spl4WD6B/IkcWuyStamp7SNIBd18o6UD2WJJul7Qw+7dR0rZiygSQWsewcPdXJZ1qal4taXd2f7ekNQ3tz3jd65KuNLN5RRULIJ1u+yzmuvvx7P4nkuZm9+dL+rhhuWNZG4ABl7uD0+tfp0z7KxUz22hmB83s4Fc6k7cMAD3WbVicmDy9yG5PZu1jkq5tWO6arG0Kd9/h7iPuPjJTs7osA0C/dBsWeyVtyO5vkPRSQ/vd2bcio5I+azhdATDAZnRawMyek7RC0hwzOybpEUmPS9pjZvdK+kjSndni+yTdIakm6bSke3pQM4AEOoaFu9/V5qkpQy6z/osH8hYFoHwYwQkghLAAEEJYAAghLAqQYoLfqE4TuqaecLeVMtTTanLfbpYpkzwTA0tcog5UGpeoAygcYQEghLAAEEJYAAghLACEEBYAQggLACGEBYAQwgJACGHRJNXw5zIMce6kcd803qasvdW6T69dqtrWUdW2jp73fKvhzkXU3vwekfds3H95hmH3c98z3BuoMIZ7AygcYQEghLAAEEJYNKGDsz06OGM1DGsHJ2HRZPwW0/gtof6ewtdbdo37Zny5TWlLUtPyqeseX246sm67jqzbft7zR9ZtD70+bw2R9zy3/7Jai1p3LxEWAEI6/hRA1Vz9lzRfJada73Q01nj1qz6lLYXJOprbFuj+Kc8veOF+/Uivd3x93hoi73lu/2W1NtfV7bp7iXEWQIUxzgJA4QiLJrUto0lmbR6EmaIb981kD36q/XWuphbfJNS2jmr/+CHtHz903vP7xw+FXp+3hsh7ntt/Wa1FrbuXOA0BKozTEACFIywAhBAWAEIIiyYM926P4d6xGoZ1uDcdnECF0cEJoHCEBYAQwgJACGEBIISwKECZh2p3qi31cO1WylBPZAh2nmHaKeStl29DgArj2xAAhSMsAIQQFgBCCAsAIYQFgBDCAkAIYQEghLAoQBkGEbXDoKzuMChrKgZlARXGoKwcmPymPSa/idXA5Dc9xJEFkAZHFgAKR1gACCEsmtBn0R59FrEaKttnYWY7Jf1S0kl3/3HW9qik30j6NFvsd+6+L3vuYUn3Sjor6bfuvr9TEfRZAGkU3WexS9KqFu1b3X1R9m8yKG6QtF7SjdlrnjKzi2JlAyizjmHh7q9KOhV8v9WSnnf3M+7+oaSapCU56gNQEnn6LB40s7fNbKeZXZW1zZf0ccMyx7I2AAOu27DYJmmBpEWSjkt6YrpvYGYbzeygmR38Sme6LANAv3QVFu5+wt3PuvvXkp7WN6caY5KubVj0mqyt1XvscPcRdx+ZqVndlAGgj7oKCzOb1/BwraTD2f29ktab2Swzu07SQklv5CsRQBnM6LSAmT0naYWkOWZ2TNIjklaY2SJJLumopPskyd3fMbM9kt6VNCHpAXc/25vSAfRT5NuQu9x9nrvPdPdr3P0P7v5rd/+Ju//U3X/l7scbln/M3Re4+/Xu/sfell88BmW1x6CsWA2VHZTVDwzKAtLgQrIcOLJojyOLWA3DemRBWDQZv8U0fksoaAtfb9mNLzeNL7dz95vbUtXUqu3Iuu06sm77ec8fWbc99Pq8NUTes3H/taqr23X3EqchmLaxTcs0f/NrqcsYKmOblknStPdr3s+C0xAAhePIAqgwjiwAFI6wABBCWAAIISwAhBAWAEIICwAhhAWAEMICQAhhAQyYiZWLNbFycd/XS1gACOk4UxaAcpnx57eSrJcjiybMZ9He5L4Z27SM+Swu8B7dzGcxtmnZuStPp+PTvddP+zXd4kIyoMK4kAxA4QgLACGEBYAQwgJACGEBIISwABBCWAAIISwAhBAWAEIIiwLUtnT/83O91qm22pbR0tWf5+f8irJ//FAhy5RJ3noZ7g1UGMO9ARSOsAAQQlgACCEsAISUooPTzD6V9Lmkf6aupc/miG2ugjJv8/fd/TuRBUsRFpJkZgfdfSR1Hf3ENlfDsGwzpyEAQggLACFlCosdqQtIgG2uhqHY5tL0WQAotzIdWQAoMcICQAhhASCEsAAQQlgACPk/JU0zGevO7RIAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483e898>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 33.884443044662476 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 100000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.00000008e+08 8.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [8.00000000e+00 8.00000012e+08 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000008e+08 ... 4.00000008e+08\n",
+      "  4.00000008e+08 4.00000008e+08]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000008e+08 ... 7.20000015e+17\n",
+      "  7.20000015e+17 1.48000003e+10]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000008e+08 ... 7.20000015e+17\n",
+      "  7.20000015e+17 1.48000003e+10]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000008e+08 ... 1.48000003e+10\n",
+      "  1.48000003e+10 2.02000003e+10]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54822470>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 33.85818004608154 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 1000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.00000001e+09 8.00000000e+00 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [8.00000000e+00 8.00000001e+09 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000001e+09 ... 4.00000001e+09\n",
+      "  4.00000001e+09 4.00000001e+09]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000001e+09 ... 7.20000001e+19\n",
+      "  7.20000001e+19 1.48000000e+11]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000001e+09 ... 7.20000001e+19\n",
+      "  7.20000001e+19 1.48000000e+11]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000001e+09 ... 1.48000000e+11\n",
+      "  1.48000000e+11 2.02000000e+11]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.081866979599 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 2.0, 'lmda': 10000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.00e+10 8.00e+00 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [8.00e+00 8.00e+10 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00 4.00e+10 ... 4.00e+10 4.00e+10 4.00e+10]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00 4.00e+10 ... 7.20e+21 7.20e+21 1.48e+12]\n",
+      " [0.00e+00 0.00e+00 4.00e+10 ... 7.20e+21 7.20e+21 1.48e+12]\n",
+      " [0.00e+00 0.00e+00 4.00e+10 ... 1.48e+12 1.48e+12 2.02e+12]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 44.68725848197937 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-10, 'kernel_type': 'untiln'} is: \n",
+      "[[  33.           26.            4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [  26.           40.00000001    4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [   4.            4.           33.         ...   49.\n",
+      "    49.           49.        ]\n",
+      " ...\n",
+      " [  20.           20.           49.         ... 1417.00000026\n",
+      "  1417.00000026 1349.00000028]\n",
+      " [  20.           20.           49.         ... 1417.00000026\n",
+      "  1417.00000027 1349.00000029]\n",
+      " [  20.           20.           49.         ... 1349.00000028\n",
+      "  1349.00000029 1287.00000047]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 44.01327109336853 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-09, 'kernel_type': 'untiln'} is: \n",
+      "[[  33.00000003   26.            4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [  26.           40.00000006    4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [   4.            4.           33.00000003 ...   49.00000003\n",
+      "    49.00000003   49.00000003]\n",
+      " ...\n",
+      " [  20.           20.           49.00000003 ... 1417.00000264\n",
+      "  1417.00000262 1349.00000278]\n",
+      " [  20.           20.           49.00000003 ... 1417.00000262\n",
+      "  1417.00000267 1349.00000291]\n",
+      " [  20.           20.           49.00000003 ... 1349.00000278\n",
+      "  1349.00000291 1287.00000474]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.516927003860474 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-08, 'kernel_type': 'untiln'} is: \n",
+      "[[  33.00000032   26.            4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [  26.           40.00000064    4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [   4.            4.           33.00000032 ...   49.00000032\n",
+      "    49.00000032   49.00000032]\n",
+      " ...\n",
+      " [  20.           20.           49.00000032 ... 1417.00002644\n",
+      "  1417.0000262  1349.00002784]\n",
+      " [  20.           20.           49.00000032 ... 1417.0000262\n",
+      "  1417.00002666 1349.00002907]\n",
+      " [  20.           20.           49.00000032 ... 1349.00002784\n",
+      "  1349.00002907 1287.00004736]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 44.351420164108276 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-07, 'kernel_type': 'untiln'} is: \n",
+      "[[  33.0000032   26.           4.        ...   20.          20.\n",
+      "    20.       ]\n",
+      " [  26.          40.0000064    4.        ...   20.          20.\n",
+      "    20.       ]\n",
+      " [   4.           4.          33.0000032 ...   49.0000032   49.0000032\n",
+      "    49.0000032]\n",
+      " ...\n",
+      " [  20.          20.          49.0000032 ... 1417.0002644 1417.000262\n",
+      "  1349.0002784]\n",
+      " [  20.          20.          49.0000032 ... 1417.000262  1417.0002666\n",
+      "  1349.0002907]\n",
+      " [  20.          20.          49.0000032 ... 1349.0002784 1349.0002907\n",
+      "  1287.0004736]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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s+8SLNnay6urpnq+RHp80XaNoJu2PPt65niLja9KJMwR0q2WbAGaSG9uOmUnf3hdmpMdyber05EQ1cpUI9EEOGxs8TEeE7skEeG9fZvTzCyAlePP80vZA3BJmB+css8xyoDwIzWJSOIkP4TrQCCcU1N/I/r5yN7NqTNGaUUyi6UzZrYeI3e+67ENrz1s7dRzqq50/vB+3FTuWfrTq2nC1/m2xF2PcRTnmDfsy5QOa8uuMc1Htip7t+bKCH5LdeWi/9PvU8cb30X4yVz+D+qyI6ji5Pf2zsIFx+2c165RTQrq4aHJD0vklAJTsUXd6CgVpFcAV0ICOiukBwL3+uD64amJM+RaYZVLouga8xB9+VEyjggD1Hu7NN2r0BJBjL3pgY8A0tl9AnQCsT0EBU9oXpTzLmZi0WokTUzk1XN522AL9Au673r4S9AUAToFfzcsSp52NKclD13f7TZUs3HclatP8RklU3SnIe9ftvOz87udaoJZ9wC2IKcmiUSIfdjKyNvfUi8EsfpgogDv3rPKAcN+BnBN8BYD0PZ8r+AfuXKui6zjqS50BXbSJ4JO++ppcbh8iuAFlqX/CmCGAWeBy83raTk1f/FwbIcnXG1cd/Lr2M3UOLtT7Z0FZ8d3XJFLSGVP108OngAcxWUzKVWnd1rsPTENW961qKsVHYX63+RHMO8lsrOdNqeQIcEoSnVDgjzr8rolWlEhFPi+NVomyf+GNML+H0IK+gPKCkfUx6Kprr3HsZxivStthd8xGLyHFKOM7XrmYJcq0j4djFLVoAGCBysvA3k176XWCsv4De/49k0X5HFzjSyKdbHIbrQdQl68reOMz4Oo/KvfMyzPADDrfNH2j7M+hjZnINAxeFpNp7UsnrrHQus9O7XqdNET5ZyY1UnTt1Jg4mdwaDfEItrKHO1nY6AfQ4i5sJMJGPWw+hXqbnYmcWEIZy5ikf9soB1GhULOaRcFnqEc/BIlOjBxa1HVXRivInsu5qlmsxcFIfS8az1iz4CR9vSbaIn2LgsmIo4nVaBYFZh4mxllln2YxJnhJSR7oQzULi+nQSVavw5pjnM0b6pptD9Usyradb+Du3Ms90r141QsWIwomo4RHM56DmIH8InLvJUQ6RPCiqxPDbTWL3SuQ/U76ip1Q3/6iy5pFPc9VmkU47eG9Q+otNuVwM+VhTRZXZJ02uAvm6zULqzlYHMZOpuORmoWuQoVzM1ULmblGQxTf0JzrBWoWYw1AV5vRSl9g43a7BqiT+2hX7fvSLCymQ7ERvEez2BeZeJGaxeUWNMjiQoOvoVPmgi0p45xDr7QJgrG4Y83CXZjESANlP0qzAOC2Ec5oFhaTcZ3M0ZBZZpnlIHlQmoVNUU+jFG1aLjP92JtN9miZmWNqcRRqLigOAwC98VrxPieldNPVvaBCc9anIjWBZkV0IxBL0TBCkHO9/kj+/uCjaXVeVXALlTacG0p+s5dfIqv+dHqy+xtwvWd/GFrtQc/76FSOfQjV3ZXkN2lS0yPvwePV1dZ2cVWzsAlWRatbLQUHIQeovx3q7S9AK5t05VCIagCpyZE1JoGJj0BxVqMlAjmH9PgE7oOPd6JrSlJUTz+69p3u5evcx9eipEpnq+Lode9/KqayuRc0NiONmejxGAix9WsdEQl6UJPFlaKh1BvsV9TiFxByHN/0pk+cirf6XoKbh4ZnzXXvjKE1te4zJDuWxChEPfpp5T76ti8Eaj/LwoFsat7/mF0LJ9gnSuhjdz+i+6+eGXIbZiJ9AG5YcwPYszKMUX/38WAfMw5Xrb7GV/BgRP0qL4AR/FZ9mPpu5VD27hcpt7lPt+zvw9AsiED9oiG/8W+83rzUymkZvvFNdF94t6hr1HXg7SC5HqrKMcuKmYlpVJJRsel7hfxGHXy8WlTyEwDu/FK8/olbTEc+V4kirLfg1QKUPdL8aWZQ/oFp8hvF5dM2NGZIWkpOhnsq+JJ0toLbBnGihYoxoO0AXvRyjWFkCnS+yUeg9SDXY64LIbaLiV7Hx8IePfzQ9+84F0umpFplCy+OMpNnQCwOQyHFaR9oYkZcdcXxVvaJNbqAcfanbQ8J7tkFNj/y/dKPjBOgwA1mINmQoAYdAmecBhCXDv2zofQ3Lj24I3TnmrwFpGWOhniCMwlahW9Cr2Ep47b46AKf/gffh/5Cr42QOkK3TohLm7DVRkM07YOS9EX/Xj4x93TkEE6e0D8byrGe/uS/g+0jh8Xzer/iguC35r2xzswE+G1CXNR+xQ8OnwJePc1illlmeSnyMDSLKcnsSpOVuabCpmP1TM0Na3aY/UrIUHEHCnKKIyixPRdXLaM44WIUzMEolZ6GXQclu7qfaAuoxxptT9nBSUEwBjY8SzlVfkcDSAmUTGx/CMVRp7iFqX3sp9vGHY2orIoa31ctYohwyfY5taE4Y+vTEHfCdMrcJOcfOY5NOwUBvvm80rPeo8jyez6P1tFgoqJZUOSGIUt9SpQYbgsw1zCti8L2pYxfbjB4hZDK8ZrjDBHdJcNt8u+B4DqSv20EM2edqvbjPDWOXJefcz2npKhrWFmeA+dJxiDfn+6SwZ7Rrc1xIuAazcL8FhhukH+lX0f4XB7uZOGorRS2dzsHoIUwN6nt14na7BN2OzsCsWk/AmfPZB4Gmzptz6uYnyQ0cDQ+xyhLs+nvfQlRmSQac8RlCgEFmTEDKW+rk2Csx7DHuans7J8nBXXZlhR1Muo35xeCSCZnXXycXpuh4LupW9r2yxxvp90en6Rv423Z9E/JcdjR3r4xoSw6O33iUR9uKQ93shhJQVMCDUEunJPw5Zg8R30VNh/Elkdc5bDdEORGrnpZ7TPqjjZbQeOhagPsHWjRC/Ivh7IIAJ+u6j3JoU8+6ctqVM7ZV2YmdxnAvdruSVigmNHlHANe9sBmkFyFIRabnmLuY+9FG2mO3/osnHMZiWjQhBP7SH+yT+hR3xC+AtVHoA9yXDn4tRDfWDSgG1JhYwLMQ5x9Fm7ss1h2ZVUf8yrYdooJPkQMj/vcll/umH0Wqjj2Ez6LgQEWP0RcOTizksalR+rqCh5PO8SVK74Qv673L+UxcHls4irfx23E+k2PfkFlu9QB3ZIQlxb8lIfCt8cb+zJONJpGhGQWr3DqkXoSH1beZ/2mx/Z1aq47LgBvSr8k8/hTAroNI5h+pe7w2eSVmSx2TA+LtBzH5gExCxSCPYUJCG3IUNmqdxCQNnKSYcdExkkYxSQoeA+jnjYZpAAwWDU4KaSjIvG47o8gaiwhM3aNrl+cg+11kfbRXCPZT3vddh8dLwBua9Ci5brzg21WwTIx2LHK7NE7IccEuFBNFMpLpgupODKpG53TtgdBw/qs6rN50VKyL6TRLFx9uSllU8TV8UcCHCUAFfFICsKMDA6tg1MZ1Gi0ANAQ0a0ZfpOvKTJSpPK3iossmoQ6OLs8ZkV7yMcLOka1r2oSUe6TjmO3Tki9a8wQihAHZ0HD7jo4yZh8NBr2q+ThThbkAGceXBv2sfUgvZMbOQajKHOWZdDCsHuM/IBxL8WV00KGxF86iS4QlYdIGKecREK06vUQ5HvJwswPw8Kbhzefo3NlBXWoHnZEJ9sz4HK/VOuQxCETDely3oLbxZyMNQvVlAhVg5jaB6iaW1x6OOPXYKLK7qTRkGWm0N9SszK5wM0J7ESbeg9ymlchfUyOCvXcjmZh2skTcOHLal40i8SyquoLp/s4M1lkG52YMZw6uEEZrhhx4ZCWBLfV0AQazcJK0Sx81a50/IZTKoPDnhB7AlNqNAsXpJ+60qeeQImKqaBjq1yeoDr5sZfvqSf4rS+TRThxGB615nrqpQ+SR0KtZhEBdq7RLI4xDedoyCyzzHKQPAjNghyJL2AwSTSOxG+Zq5lbroomiSol4YJMCXh8JseLCfzhR2hgukBT5ctlvozSh5zA4y91xeiMRlAzUfnJUxSYMCCw7efnBWquRMD+4+fYEeucHKWKu5zuzDn71G01YQ4lmlD7GuE++qQmrekxbB1MABwinHfgmApMfXIfQIonAVi+/6w1ZezxnNF2EhqOCa17kk76uo86nCODNtH4fuR3/+GT/c5j284M3mxxouze5vglGxTGWejabdR0WDmHtOpKf/0FFZMKAPxHTwtNHztqI0ejayqO3csN3ug9nKn3UbExxgRg7a/RmBqfhLnvQCb9rVGo/sNnokWbtH63eQNp6es+yM7QyJMOTn++FQyMMU26y2nY/pQ8iMliUpzf/5tNUdeog/flwWWIWs0xlk85pnnw1UGphXGU3MRODIuu5d90whUK52tOCFDTyQHA5wdMU87zscoxTNZi0+bzS5HNgh3WbH1u1Q7te5BvX3w1k8ppXcgO4JpKPrkPUMh70rLf7Ztrty1mwKY6XgUIJ/0vJoX6Z2ICXPXnFxNh2Td2uRXbLj6HiHjSt9tmH8DY7uaOTOU3hhuimFMLh2THlSSUqb4Qt1rI+GdQVuMMHqWUF/MtRITHfV1kvJhmfpMa56+ETutkkfps7jgAjgqAy2dzJ3mC31agV3e6BBNJiDVPYuGsQzjz8Os2TZ9CKvwb1mcB2k2dH4/7VfIwJos86zaSsoNyigTFJvTkBCWhOa/Yiev8NtXRlUAsDzIlQ9WOPClrKjYA8tcdddzH0fbetY7G8uAmMDK7eMrXsKye8gZ/ERKmY2UvRsiOLbJTU+1xxWpA/EOUEtjmZaUEBNrtN3N2JKj/6WbxvB1MQGIARrMoEwSK506wMiyhxwElGqIkO453nZZH9yu0jnCXnZO2rTh385NJQSYPigACV5/IUPEaur/fR8CbMnbCRK9SJ+0y5gBuGg6ekIcxWRwrNrqROR/Ytc475b1gm7055q4oG9doijoz2ZYKUFHod2KweuFjjozo8fTTZs1a08OKzWBUDSJrJOUBHnFGlrZh2DEpyDugqRuS66HE1PBv7OwDoIDJthMMXCq6uiowLSQoP2Qpv0hkHLfmNzveql0ZlXon58a2s5QdUN4GW3vF1twoR/BGs1AIOgCOrjiwKUrSH6dKFkNrKV9ImQPlKjOkEOMMAf4yNGZI6qTWKQ27Zki59s41dUTUn0o6WYzMELrYgEZmiL8MIPYSwcriCAeYIYb/4og8qdnBOcsssxwkD1ezIEKl1huJ940ZYjkxdd/rfBbF76GrYaHhc+UY4qMw5oSCvw7xWfTdTiLQVQ7OskJq+C//TSQrdgmURhY/wR35LHjR7WgWxTTz5jqYAZeKFsEZZyE+i7x6ZlOAs61eMAV6jcf6LJZKaahjmDUL7a4u/o5KXylU53Ba+Oq09nIvUl/No5v6LOJpB97UMUpeQss88lkgmWv3NeQL1FCsNwhO5+oY8ITPIp52CKce3jgp2RNc4B0KvnxDXn2fRWH3Xi6lITHSM4km8KefAgD866/ll28lnntV8zPGgftOCgBlcW++IZNI1xXaNKclCokqvZqq1MoArZPAk6cFe2CzTun11+R3zdYcAnjRSzSFask5DnE6e1P32wzViRkTsFR2b8n+dCcreYG7rsme5e0WtFggvf6o5TVQPIT1uYT8MmdAkvTXMH4DNZvydIUGoGZFzQpNw8k1Q8kCsPL56Pll9R3Za1/0dYLPL15681F9+bwzTrlqGrDa/+G0TjZ6PkabmawqfqoTfDUpxIfQfXpRt8+4FHcpz8Lw9plk1MaEuPQlF0Vfcj0GAKSFQ/KE7vGqGfeSl0LUvogMwI8mC1RfhkYluqcGfmlk886JTATDqrqsXHamWsd9R9VVhDYT9/ytHt1FQlrUtgb1eo08iMliSkoC2fSP7WqtLEtNkVy36yPIwsy1fKG29Z0gM0s0xNWITNEQcqSi803KN0YhSwDAopeQrhWbQp5q5IWDkL5Kt2voljLJrO4LABTyhNO5XarLcaHfElo0rFwu28klzOjKtoBoFuz2TBZZ4tLDE8l2thSeS3DjFHiVvqvo0XwtFrhWIiheJoiCDXWyklKQFxhAky5ur7fx/GcpjsWQkJYe/tyQ2y47ofxXGPrCIy4dOMpLSMH0qZOJTB2kceklL2MdEU5rH5KXSdt7alLBx7BuViI3RY3mZ8ytp1/JtHTiBKU6YYVTh+GMQMbhHReuRFG0P/U/hYRcAAAgAElEQVQ3AEyIZrI4Js/owU4WVxJ1WFSmRWqO9qdc34Osaj7CThTHYd/JQ95XVbeYGtmZSYretC+9z/kXW5fVvPxQZOSkFYuwbPJQUNXach2dL2hRqWNRkZbcedk+0Oj47WThIosq7OrL6IAmya0iOJ1odAvfFvSFeZGzxJWgTcmP2MQ9gYdu57rLefTBzH1MC1cJjDsq/WKqGZ/ckUQG8ssOtGhKiyAdoy4BFCeh84S4co0KnhYe3LuC4IxLJ9sMLKuvmfXKS15yQ6S/3dphOHEl9yP1uU8kCEsVjVikEhrN7eoXzRNAdzENGQirPFkglQk2rByGU4IL9TxhSU1leYvgDCfS57g013WE13J2cM4yyywHyYPVLHic/GX5LbTIjop+t2ZHyFwOITQFgAqH5toQ4wIVU5GPxdEmi2V0JsRH0WAkhgCsnXzaNPnz9S6d/dYV84c2g2gjEJ+FU9t9UFr6DbDZyjFC5a7gYQARwV2Mqp0D4ME16DwaIjg6cTyqPT8E0SJ03xKiFf+Df77Z8VnwyAxxm+qzGOeiYLOd9Fk02Ji88nW9b9qsU65yOZD4noaI/umuvW9NjylnXUnciwx/6eAuKkqYhtj4LBZPO6S1hE5T55pEMngSh3O+D37tJcFrE3Hy7VCcjJzNELdN6C6uMENGPouiWTyb9lksOjG3bUaw3yb4jUd/XvuZemr4KqwZEs4c/Jobn8Vngs+iSUkHxLmo9TNs2rlNRbemy6KXh7ZrzQECxPmUU9S1DB+frmpSGAA8Pwf1fdMH6ntx1Hmjzq4d0ukSruA08kNztroyhbykjwPAEAUmDcA/y+c8WWbzpAMNriJOmcGrBeLZYgcHYBPVAMBtgjjshmRQl76gRQEU3EH3NKvXj5Z7afVUwolHdykO3MYMiUm89SNmdrmexQ6F3vB4UZLWUtdOFuobUPiyXweEsz5vm80QA2YCrjFDQk5RN9DouOrAvUOXJ9Lt671sMzDCiSsmAbGch2J9ueLKIXXA8gnh8u0Oi+fZtMpmSHeZbmSGrPa8u5s3O7AjdJt6b8LKYfMaYWkSw8KS0JmMV2uGbB8T+nO0ZsiEn2efPKzJQlcB73Y0Cw6htNMhmsVmK2AkW4HK8FkoZ+bRmkWOehStYAhwzFWzyCFIOp8olPMCNQv/vGvRrRmyziPNgtZeoiYjyLll7NLxosTw4yI1uDvNotdIDQCvEQUFLo0KRLtt2FmdX7hm8anPTldGd+5qNESPbTQ5v/FgB/RPNafobjWLlRPyHovW7BbuKM2iu3TCDbrYncQOkYc1WVwhdBXu4uod60225Qtv3pG9n5zZo+5FbETI9mNnG4yC7RCHZ5rq/5309DChnFaNnIjFpn+Oj1oBb9OHitUwkw/n0HOEGS+dGO5p0Aj5fvNR2Agrt72/D2qycCcrAGjKBBbppcq5e+ctpI8+rhOAwrljbKHMRLsQ59cfFVh1YeHWyWO7hS11yNuhAqwKziIVbINGPQSXEGVFJQKfSfEfevJsGlqt0ZgMxdb+0WU2uzabOgYxAU77VX0sHELFZTQnGE1WKUn4r8FCxAKhBqqJwasliBnu41HWKbA7AXpXfBxjsiAeBvAEhJjWG4xrrjjDyF4AaxruHYW9edHBf/S0bpvP12bF7tcswAznnWhs+luXIzRZm/S9h8tZrP7SaFgme7lAxzsHzlmsq/eeVe1W77FlVNdj2L6P4eNjX9rOhcj2cdWVaFX34SUWSy8JfSqeWnZ1M0H0b56AtqnVPo/QLOZoyCyzzHKQPAzNgqRuSLR1Q956E6UoMFDqhsSvfQPd932xRXBuh/oJQMsB8jAIglP9AR98VP0QP/BFObWmL5/0oCEKJBiZj2KRIw7mXByiAK4Un3C+Bp+tQOfZ//BErmH7g18oSUEq3Ne6Id5ycAZGOBHswuIjQRiG11bwl4OAhgxE111skU4XGYvQ+gbSiCnLXw5ImWsh6f4T+wBA/76gX5//yBd27NgxT2M4IXRrYaAaM2X5TayrldFQ4soXp6WmbjOh2NdjJKFtdwNj8fElnvx73y3H6qcdnE0/qR5H2MgZYeVw8rFmCgoOInWExVOFgxPCiSvH7S4NuEnPmfulzsuz9zb4xn/8NhbP1IEpbFXdJRBW5nrUrWaZstj4MrJWdPKRyfjVYaR83I6wehJLHz76d9/C5g1gWYHLCCugW9e/rYMTDHRrRlgZh+i/OlxfeBiTxT7Z518YcXCWf1aUg9O5akbsKSFAzEKumyrgpW7HzXeKQrajW1FMwFCh3SVMO9Rsx1rFneEyZpoSA8q3GBNccDVzU4+b8y2QjCMyyQNGnBpCHKBw0hShIQoPTP7UtvE+djz8NrWqKaH6PLIq7LfIPBHJHiHzRJprsGnbkWtkwvSyZFmODGrbTkOSQkPF9DPHZPt3/pmqfe4HKTAkKelcGceZSzGekra+AdhlGr4eDY+m7qcTKWu2bUgNBydFobnzm5buwIUaVQGAlDk5lRKP88zgFdTn7G9ybSkCblNRpH7N8OsR3yfnv8W9ARoT9q7RmqWHWyGzGTLLLLMcJg9bs7gqemEda2On0RV5IVcey+ZMTB73SC/0gdtr8hFjdH4FKjnTh0LGelxXDhUedYGpnrsEVUj+MbWBlvp73l6T17SvmoaiALGxNnidTAwn1wBGrW/i6raataq/lz4lKtvdNLpg+wAzNs3fpu+WYrnJCrVj6OrvNjIzeb/NfRi3le8vUGbNYpZZZjlIHrZmsU+cq4Ck8eqvopwXvoUUN8dAnsmdOB8xGABSWcmNlqK8F5rIBQBbk0gG1HBo74pPQiX1FTRFgYujj0Lma0w1FMjegUOqBLK6n/7md2f6sYOTey8OTlRH5tQ+cpmKQGyXMSYLJJK2uMgaH7sCHaYkmaJaHwOodj6THFeTw6ozk0rZvh0Hp2l3REDnimNT7X7JDjXXYkoB1ApfjOQJLkq2ZdEiSPwHsacS4UydFAZij1x8yDhP87lZmQ0yapI7h7gihNzOnThgKQHRODg5AE0pgJyoVnworvZBx6xQ/BMQc5+6JZWKFnFJiCsgbmo/BZ1Ztc9kI+xJrts6OI8pBXCryYKI/grAMwhcJTDzl4noLQD/K4DvA/BXAH6OmT+5zXkANC86OwJZluT8EpOFZvic0ehrZqOdUGr176yidvpS1smilBSsF1wyTkv2aP6bDNGvHt+hNYXYpC27YCDYTPKgWzRiR8AGgJMH3PZL28aGFncOyaZFB+lbQp0Ep/bRcQTQ5A3IQcyLkn+Ki+rIsxEID+QXs0UryngQkKhpZ1ftqZ3KWLadhORG+6GTBoe2bkh5MdqbBrBui5IazkwFmq3njgtCWJLASHpqnN3jMdDaG2nhEFe1CljqCakXZ2S0L6UG6nrzyTVKwmWyyH+TrXUqfUs9EC9dca6GFRBOxcmpEleAzZZNO3AcQjitf9131unfYuYfZeYv579/BcAfM/OXAPxx/nuWWWZ5xeUuzJCvAPip/P23APwzAH//1kcdV0BXzH/QauOjfITtIPkkRCUnxOabFPLXIHkT7jKAUmpCicTclvtLSXI6UkXy0WYQ1J/WKM3b+8uwQ4ZKgQsDlLN4hMToXIRlOXebXM4wh2WLZcBcqpePw6Dce1CoqEF/sS2sVgUXsqfWqSbUdeexwVkIFqLiIgDARYLbMtw2VYIYSOjUm0SnEkJlwR3U0o15PJhLiNRS0El/ajsNCbQO6C9yeFcrkUcWDUCHccIMcQG1hGFypcK49CHBhRp69BuW7QfRWBqcxajWqWoE/iJg8ekCi+cVZxF7oL/kArqVvkI0nGLK5T4wGk1ISxEycQ2dOmlPHaF/FovmtnwiaNHFE5MLctmGUpMBkWroNJiSOW702lwlt50sGMA/JSFb/J+Y+dcBfJ6Zv5l/fx/A5295jl2ZfRazzwKzz+KV8lkA+Elmfo+IPgfgj4joX9kfmZmJpoN8RPRVAF8FgBVOpzaZZZZZHpDcarJg5vfy54dE9HsAfhzAB0T0LjN/k4jeBfDhnn1/HcCvA8Br7u3jAu7XxeeJDkZwSoVyynUkEhDNyqwEvJYE91AEZ+DapriCkGo2pTVlGDuFampqdSrb67VRTmi6CwSnG2q1cwAgR+NcJ4ASKGbko2b9p4yoHBVq0h0F2ZnPqcjVxEchOBXdSI3mQtXcUU3GV8ddNUMAN1plXcgaWx40v+EbITj9pqJBOUp/SiVzHeesWehxSoEhoEFrlrF31VGcvHBU7CA4Nwy/oWJayZhSRo/m58qWa4m3Q3DeeLIgojMAjpmf5e9/G8B/A+APAPwCgF/Nn79/wxPUtGCgjYZkXsryPQrRbvFb5GI9ZD+BhqczadZmzg1JqzY3xDknACj4CurpHLDshdRW1fqUkE76wkeh2aPhxFduRJ0feldU5c5FY4Yw4okDGOgyiUpceniW6AzZyElMYjr0HmT4JLV/NhqibWS5Pyf2AQCXyXWGR77NDaGReg8hXek2XFRuQB66QkGv8GmNhjAQT1zx0diyfmNSmKl2F4T8ZvvINdu6wEI+qxXTNJLgzGSxBVyQF2/7iNCtawQqLMXsUJ9M6oDh1MEP4gtpTJxRbsiQSXoXTzts3qRaYb4XjsvUAeHUTBZDaxbEZZ4gEhqfhd9W81jNIE2XTz1Aqd6fzRuE9Vvt5ByXQHdJULh3Gr3h3QWaaEhqH4cr5TaaxecB/F5ON+4A/CNm/idE9KcAfpeIfhHAXwP4uVucY7/Y5U6reR2DCDT7k34yGkdiqVRWKpodfng5Vp5kULUJmBeooau35y19hOmDHiNvc0e8GcTGVkYbWisresnHseOF8nfZLrXX0uwP7Gog18nU7TXHZdtWnKim/2nct+w3qCrTcf3Z0696ndfvo7ktxXdQ+td+3xfipNF5mvvxguXGkwUz/1sAPzLR/m0AP33MsUoV9WCAEt4DMZY6Hen9as3Qdqgv2hBKlEK5JJAS8K1vyzbrddmWt9U97Z4alzARuhzlcErPr5mlKdYix56Abz3JWkfebhjgn/WF4Ur5KBYfXdQXf8oJO3rhu+cOtsiRvxT9XmngXCmUJG3dt57uQtpdS6tHQ6jQ91GRHLsPAPBzyXY9/fqj5uFjQuX4GH26bawOVc5az8JoMYYFqh9qREf37z96Xs2rMeTaticGXazxOFMPWi9tGlUjlzYqmpgLErWBA6J1MEeWGhodwa9lTM6+fVGLPTk0jGGlWrxmMKtG9myNd1ZvweUoEHsCdwS3aVnENCmwlgKgch5AtDUA6HJfUlfNC/aE1YeXYO/gL4dyD/3mMYYz3zB6SVV4rkzpZly78wg3tAWb37s4fFaZ4d6zzDLLQfJg4d5EBDY0eoXAVyuAKTGu+i9s3RAi0GolfBZ9XfVtcd50JnEt5ejkZQ+EVOL9bhtllV7WFYY7B3eyEvJc5dK83Ai57qVhuILwUUwR3yqprNvEWpEscSmgoxpFOOvgN1IrQ7Egsl9AOukQ33g0jZmwnJiXw8E4C59xFtu3Vi0Hp6PK46gIzqUUsnFDt8NnYRO3YHAVcemqw67s86gZWyu2nUJC5wibt1vCXoqtTV5Wbap9dQG5kpiEGksqOTPiQkh3F89UYzoV3o3MZ+HXhoPT1HsBhJ8DAE6cw7Pv6QzOggrOIhgiXcVZVD6LamoQC0cIAKw+qdfQpNx3J0iesHjWlxD083c7bN4gLJ8Yn8WiTVG34+M3Ht2m7Vf8s8NNrwc7WQBAk3E6BmWNfRaUqiobhd5tp8K5UVfdNtQ2ImAztD6J4mE3alpCJdFVdX+zledyo7R3WUW8rNWui6ofkkC4IQ8Im5fSs/FbAAXc5Ia044+hwHDn6x2TgraupXLbDtKWknyOxrHsA0h5BQDd+W4Vdb3UpIWKtqoGJ5A6aXPEgzuqjlv1GySWbcuYZifvs80O43cR2x4SaL1F91wXCDV9uKrzQJkg2BQfcgPDb1PGLbgm6kBBSvmp07J/uoVf+2IuWCbwptQkpBQAALiLLVafcgFwsRenb7fm4kzVMQBXEyz1wloumBAq0RSdzKRUIZdjLj8ZkLxDdzGUCWv5pAclh96YEhrN0UnbQu7781QAZyqfCcJe5isuwpLwysbyafgW4bz8rZ/j4xtwlPztQYjVMEvGQae2N7GUHOh8rRAWUy01CEBhe9y5yoJUHmJXJ7QhNg+gFmbWBzQtM4V/DoHpi0A6p9hygCpdC8oq5Q8tH+TEPgCKZpZ6t4M8bVZsSD6Ey1yOxfHGJGX+TG2LMjkwIznayQ2x1c/GxLe2nTyBN74ybOm9Swqe0n7mT0dmzAVERolLWQHZWV5Ydua6ll3RgNKobqxqhIpYjcvsY+g9wrLmkchEJWuGLRPockhV+67ALXVw6rY2XGudmuGkEyBerEW541IiL26o50m9rY1NDbs32MFvuenXK1cY+WgxTFnlJR1PLimKZqKfIymqdhSNhIYoDzeZ440jLMxlBS5OtRBAgyvt1fEay4qn1pQ+sNrvBlcRUuOo06LDEp0Y9SGxUP2NnZXMIDaahZIZW2axiX3KthDzqzkfkWAHYF5Slr5bpizVLBJcndiKOVIxGHLK6iBVDYK60f2z7SGBQiw1PMtqmSHchXxYH3xXw4kUuajtVigJK1jqKp7BbQLAolnQWLMIrWahMxMNEd06NY5JioRunaRv5XxiCrGv2pWNOumYNUxZZmLrLgOSdzlNQHbs1lwwGCopyDEKX4aZcLpL0SycKXs5XhiukocxWTB2X3aVce0NoNUsbKTBUOVdq1mod1sbOgdOqbbbl92GQA/VLHpfJySqL1vRJrh96NkLXqBEPUoNjdxfSxhDuDPNghV2ruNEFiItH3GRodsmusAg0bz2LFR2BUs31Cw0Y7epG9IRdnAWhtKfInJESCDWJcJA8mKLdpT7c0PNIi4JLoP5ks8mBrtmBa+AsXyuDsVf0WoWdqyrRjelWYQlIZy0+R2xr6Q+sM8YAKbbaRZzNGSWWWY5SB6GZjElCrTK0vgw7OpIWcUOsZYeBIAh19vQkodA6yRVJvDs4FTNoFGHTZ0IAOI43W5BwZnozCDx7FHExV1sq+PNJIHZehFlTtfzm7i726i5k7c1wDA3JNDFroMTzlmD9TicRR6P7nlbr6WhzVNmckVBDrs4C1tC0dbs8Ot6P5WLxD+rGJhrcRbrLfpnuW9FI8srvt4yHVpXcRaVWBhIW1e5h5MQD6e+Vh7rnq7hD8RZeI2OXGyw+iQWrIY6V/2mxTNQ4qpBQvpNEUULUK3JHqdAyz2w+Hi9g7NYfdrDb13JVJV+KpK2VqRX6S52cRafCQcnHDVPqhamKc69Ao7xpaZpU7ilX4gfoeuqP8FCxjPQSnM/OBfpLSHGTcymgatFWzoHWixaM4SkbmrpXz5XOl1c6eAk6+BkFgi3dXCedBJdAHK0J1/CIMAnd7q61gzBejjYDNHJc3i8GPksqqraODgDww2ucaC52D6cxcGZGLF3Ta4DALjHNby8Y4aYdi3vODzOdWCLg1M8+5MOTp10cz/ByLVOudk39dUZSq+tGjPEpttXM0T2VzNkGRmXb3UlfZ69hE67tRs5ODHh4FQHcCXTWT6r11DLBAD01grsgf55hc2v3/RSv/R5HbfUA35bJ4umfOHZrhmyQzp0hTyIyYJTQrq8lBcRkBn4+TkAIH4sRRH8m68DieFXS+Gq0JqgGUdBAPjblZDLfdfbtdBxfhHotCI8i6ZSaoKIYws5Qch99AnQa/5IXtH6Hun1R+LfKHU8esSzhdQeJSqVwuRmZW1FF1hfXzyXuDzcFBLQy2TXfUuqbsU3Hkl4tO+ags10sYY7XWF45/TKuiSAYDZKYWR92Lep2LMAwHlF6zpxFEqdjvb+jB+otKBSmb2xiRPQP9vuYDlk7HuToi7nXH/u5ODckO6kL+nwNU8DTRhw34OfOglDxgVh9a2K4g1nHSgC/XN5Bi4/v8CgdUMm+CyIa25IOBEmtbR0GM5Q8jiEeSsf36SCC/8FNTgLoI61Tnj2nFbOv7tD6oD+whf/x3BG2L5OzeQeVmTqhlAzJpefo516JnGisN0+eRCTxcGiUQ3NKAVqVumY0VsjAOOIhm6TV9jimBwiYLJJOSZQLl9YMklz+UJOANSjzDm7NKZGlXZDvDIrdJwJWhK8SnnEKN+D+dTfQ2zrkgByblOXBMge+JDyNWaMREgth4G5DuQIwXgSGmeEsqOynf2NhpwJG3YfeDfULFndo6lRorTiahYqSRBTIa+ptTnyMYOpAwKAJh58fbkFMNaalX4TBXuh5xoYneOyontTYFjDnM5EK9hLX7pLlIhEihKRsBEKoDohkwbN8rjXDNy2v2OxxDy6+HSXhLiQ8xdhHhUZMiaKp2wOWu1v8nSTMjs4Z5llloNknixmmWWWg+TVMkOuKjo0uT21n0Dj5LxZHybs4sy4fVdp43vlkBh5ZilXKVmkpvCObocjuA1ehDQFjShTwSklnCPTzvczttmnTuX7CNtiQU65v8ewY9++b9KJY6jwrJScmRvu/2pNFiqWV9NybY45NmPa/5BpKrpGVXovz4M6Lr0rx1MQjKSAk3wq9HjIZQH03IU70l/Jkan8mICodyWK4ervJdeDuUYznMscoO5Kjk8AJVcDTDWlWnNhsiO34RzNyVVuNGZjfsy0JMQk2zV5BjmqNDXiqXcVSZ/HzvJ9CuV/djF5ANkPyZ5A5MCbVHgvLR/mdQ7OEiEZBB5to0Vx6SXMmdtirzydApJSUt7imGTAa4R8IVEddhkYFQ5xcGLk4KxQbfVZjMdaJWRuUEo1+hNOgHAmIeCy3YoaR4Qdk7gS2Hk4MeNzxMTxcCeLqzQAWwvE1gexK2iuLcK23eI2NE6eqYI4RwOal0cnCXMuEDV1Q5BRmSWcpyHUblw1BA2Tldb0AMTpmQo6MR+3cyUUSmxCol7OfV1dEkCcmckTfKpRixqipLJPEaIdwl5g9yUMSwcKgJLe1v2FhNhNoHG5r73VidbWKEmLSjJryWo1OiPXNposqH254sSLppfLJC+cZRJLeXLQNmW5UlYqGynYHYM8uXVAPCHErR5TEZzSXq5/VC1eJwtFnapTVUOyY0mLPBahOnjDSl58f1nPIyxYZlzNNcSl7GuJhI9xRMw+i1lmmeUgmSeLWWaZ5SB5uGbIVVXQcwEhAKWIEBE1RYRcLkTUcF8YoXUGamVQlnNO8AtKuhIiKBuaWjiIXCjZoIpGpCHCbYJgCEwym78criwCpAWA9BilX7k/dDkIH0VMQi+oWI8hAOvh2iJGgBDsIAnoy4faX+vgrEa9/N2fh0mwV3Oe6NGtBethf6MhwV8MkzgLT1SuU6+7W1Xy2RRcY4aUTNBBMBduSFg8q5mdAApJjcqUvW9xFi5IUaDS38TwvSttAngSUFZcErpLRVhySYVXc8FFh+QBt2UsP2Yszmvfkmd0mXm79ENxFr4FoY1xFv3z6ao/ixUh+Uq7BwCrTxwoEZamyFC4xAhnUb9vB0J/wYiWZ+Meiwzdn1i270MdnMwt67eVmzo4Owe2Ds7oJHty7XM+gdq/d+vgTAvfgrJIuB8b/oKUodnOIEeRv+fJQdnM9fz37eBUSv20IBNxoGLjs5d7kfILbPvzwh2cC4ewIvgBGE4IlTA3M2vH6qgMS2nr1u5+HJyr7ODkGt061sEZzmT/pvjREbbFqzNZKI8DcBiCM29P0XA5aDvRjRGciAziSpKjfAmUkiyJrCvi3SI4pb6HyV0giXp4U0WLQoJzOZ+BjGbRGYIbw/sA3C+C09YoITaaheeK7AxUkKh3jeAURi3JDWGHwl5Fqf4riVfEAtod+N4QnDLukFAyANBxCM60EG3JVlqj3Vu1V16dycLKIZrFVXF5s1Ifq1nAAZZFu+RH7KzGdxw67Qhjl5NkfNZ++MyJqVXI5XplstR3vImGvITQqdsTOnUlOUyyMz3R/YVOAzLXRT2Ghk4rpweKFncfmkVcaOgUNw+dLgC3vHnodHZwzjLLLAfJw9IsNGXXT8xhMQJdB94EYeS+zgyJWX235QeHoWab3jSRbIiAY2NCBNCmQh/VP3LniWTb1DgzmQRw1dYNqeUL2RQ0sqsJGUetlN27x0Syda0ITmnk4CxcDpQ5KSL8Jmfe3pEZIrwQCS5KP2yKugviw6BiZop55LcJ3aW/czOkv+Ts4KyJZOnIRDIQwV8y8Jk3Q+hIJYio/jPQ4TIZ3LQfzonpoba+dwLMyg5Yusr8eZFCIxVyCm7uMmVc58pvWhW98GEWsBYBN8UB31RsHVWCmEcQzoem3Tho71KUaVsqr9exEe5UebEKZRGJGXIMH8Tt+5bPe0N7IHWZN+iGXX51JotjxZYKGLfd9riZWKT8nZmsONGLOcdB/Rj9nThDuKltYy4Pu0pDFGwYuMaVve5FJk4pNUDzD54KT+V9iZZwrExf5l/TTz5qZb6VcP08Jq3cii2JeBOZfRazzDLLQfLqaBaOqilyKM4ijXAWuX4qiG6Fs5BEMqWpS0iLrlQNU5/BnUdDFq7mrCCbF6NoCFjwGDCMVlpAR7WImCMTXefA9x4NoZJdqjU8KInXXyubC58mw23dPeAspLK688KEpf4YqU/SrsxhleuDLO8pkWxVoyGl7choiDJ6NdGQOTdklllmedHyoDQLdyLQMo6xwLmLdB0QI9xbb4CfPC02LW82okFsNpUrE6hRhRALzyY/Oq0+ho+fSFvezl1uBFatrN3rdS1JqBwamy3odCX7q7YRE7qnLNsSgVdLAED//qc7kHVv8Bk0BHjDuO0yx6ZWM/dDEKJh1Ya0X9sBtB0KZ2YRdeZayVm0tgSjEAVTCct0RtNBSjj5/55gp87KyLmo9VPFT9L6SGiznaz14p5WkmW9bgqPDT8ptZW/C/ZJwHXce5z9lbDZWqZtbrTJndOW66QkzDw7IJcAACAASURBVOPuWQ0V9J0HO1fIik/xmrBuJ0ZY+RIN0T5R4Eok3LtSlf3tvxgKG7uSMtv6sjo2dixLsalRXVh/vpm4CMBtzmSzpSvawqOvDQinHt2FqeHbu6aoktU0L7+rR3+RGu1lHLW5Sh7UZMFTTkkVLQ0wVXRoSqYqLdnKXDeVqVKJMB7ze3NwMpoMdY+KTt23ffmsZkgZ85Swk1N/x9I46hKLqz5PQLRnnO9UuDqIyYRJkUqz6W/uf7yf+60hZSQclc8xPgaAGzs5H8ZkQQTqeqTnldPcv/OOrOiqYWxkxg2fvA//g38DtJHVgJc9aL0FL3q4CxNgVlZvV8OG+Na3y8/DD30/ABTq/fCoh9umUs18+f4zpGUvZflyEWVedLJaL7qSU+GfbxAfLYvd6z6W1e/5j3yhltvLp0+9KxwO3XkstrsbEoZHHsTA6dcfAZBq5t15kJViG0suSvd8wPB4gdRTOb5KXLimJkR/HhAXUvG81KWY2AeAaBQAPv6xtwvBi/Y9jfALw6mwRPstN7+5IRffHdeiYEY484WGv/geuloQ2NLTSz9ru98yTj7c4Fs//kaz7Q6tvfbFHMptASGtYQxnhLP3HzfXkXpg+amcK5wQhjMqxYP783odcaH9yvueyUle++uA9/6jBRZP1J8i/7oL5ZaoYwOg8FfERcVryBf5OP3Gab0GM4zhRPq6+jYXIuEPfnyFzXdFLL9Vb0I4ZXQXE2OSj9mde4SzeuDhXxweR30Yk8WxYvM9VOPYqXWat9mjTRQwVjFXRN11pnYqjffPRYfYpVJeT9mzC9hHQTuh5jdU6rjaD2fzNSJnBuu6Sal1mrgUqCl9Tww3YAc85ah1btGQ4IjKp7bt7KPjCGGCsi+7THQVWwDICyNZnK0mIyCpei9KV5K0l4zNoNexH4Rk290g6n8tUaAvGsBUQUqlfoij0lc3cM7pkO2Lg5AZbqAmw9VvxQEp23GZsMxAlBdVHZUuMPya4De1DwLoqs5V7SsAsGoFiUqI1hy+jA2bW8kkuSGUZOLUydyvCf7CwZnsVu+kXfdvtBAG/BptbZcjtMnZwTnLLLMcJPNkMcsssxwkr6YZYj3/CnO2sO4jysiX42UpKlqGdJM917FQbtJjmk/zvZTNy2ozOwPhdu15tV/2GHchtl/lGvZdh70GNm2j+1CZutF+voC+ogZOzL2r+IEC06a2vaRpj6/3JmLvCbXj02zD5lzjv+01AQJxT/X7lBR28aljmHF5UfJqThY2XGcnjWab7Ni0Dk4jJYQZOQOa5C43oCaH5m4yUSbSNSnq+XshAFZ2786+SflF9xXE5IYKoGKu6c56HckTvMshxUhNbgQ7yuX02qco9W2uAvcuk8e6ct6pfZrz5rJ6Raja5/oypgWQImWwUju2klLOpZ/yBYVpSq+tjFGWsYNz3M7eFSdjGUPiFpSlJLj2RWUFeTHiwkwiVJ2Rpf7oQtLg2XEhx6390PHI2xonbVwx4kb/BtISiMHsg/ooaB/TggEGXGyv2zpprT8jZrKduKjOjLRkpJOEaMBfccVlciSWe2WFmBBPjU9qBmXNMsssL1oermbhaH96nYFVl+/WXPDTq5QVq1Kzd8XkKO0uw7pTqjByA2Y6SKzpAPGOt+fN3zmry2xWYwKSdyVLtJgCnbu92nxtv+tXMUt0da9tycstKh5/rmpxofDTNPN8zFrl/Jb9KvdI+mGjBtpeik7HbIbktmQzSfPYKrXfTaUxBQhyPKWBtH3ndh/pF+fSB3mM9f47lB14z/PMDoBrkwSLqUX5uRp14TYyaxazzDLLQfJgNQsy1G8ACtwZkNVViwxJxSoS2K7ZnPsOFGP5HB9DQVWKjIsrJ6u5FnnJ/gKCq0Q7OVEqLj3iKieBbTzCiYdTApys8YQTqgk+uWNxUe1uF01BIEoIK1ehzpBiM26bkBYOxAZUtZaiOGnR+jEASfAKpkgNRY+0lO3ScrRymX1kvKT/wyk1iUlM1e7VlXt4pHazFOUp2zqCC9XWL/Y3C8GtLpBq78dFTbrSttIv0546YLH0BQil/XHb9vwNKMtoGbSSbcOp7RMhnAp5rfpFhkeE7WPAb4VUxvq69Dwp4ym2GdsVTgjh9QQXNBlNfAlyPIMV2QqXioKxeCnLPikoK6tHiyeaQNc6YcMJEJfCGJ4UGPZawslbl1hnKDgA8FmUBEV1oC5sSgAj9R7xUQVfWCzIdfJgJwu2BL1AfWFRAUsAxCxQAJWpPEZDAGIqn+NjKHKTYgIcwa+Fbr6ofGpujEiAaYhCa69AoCGiuzSsWLGyLhXS2eJsS6Ds0HJbLu5uihmjb8BjirR025RBWJa1SQBOO2jMlCuFZenWETFlBGfag+BMmqsi/e8uW1AWSJyZgKj80sZwW80rUMcpMmDIgMJMX/yWq8NQNe2hAp/cKBXItvstw28iuovs2BuqmWPL+RVHrK8vgd8IipOSOC0Ly1Zk8KV0Rq+3fw6ABcHpRwhOt9V+5YY8c3aXjO6pR/8896kH4gD0z6klxs2AMJ8nprjKLF8MIU3S9WxTr0Hb2AN9kIWif17HuH/qcHlygv65yaQdCN0FFTPHIjiJge6cEAbTr89EKYBUX6YdiYbZOtfUYKWf030BXIXgVEo6GqJoJl7o1dxWbdoE2kT5VHSmS4cjOIf6ghcfA7tKn7ZNxXh3kQUGzHUSc0MHv5HJyw0J6OtL7YbsY7kLBOeWdyaL0meqjd0mv+g6H3JGddo2DZ2y+IUUlUmsvhw6CsGpdHFJqfhCPoeeT6MrrvpFXJ6kKAK9r4lTJZwKrqzh6WYIzu6c4HPfxEcif1vN2A0QTUIT23I0aRzf9Gsu11AWLPXNjBGclwT33KM7b19+f0lFs3AGun9bBOfDnSyucnB6B9bfNJNTnZyAOCKvCZ0mzeVIwlupfAsazmOXQ6QBaIoIMx8eOs0uoRI2W9TQJoWaJ4IgzNLEqPVPOwL1Lj9wJszaOSnI6+8wdNrgTsyY5NVaVHIC2JgPnIfd8luE8pOcR80Q5aMwJtFBoVM1BfRavNQSKZyUqlkYB6d3BB4kRB5O6rkpSSg1rgjpoppFNwmdhlOG3+rfojW4OFGfg+tKryHOEuZM7XFF26gOzuSxEzqNJ4x0FhFMrVM1gXSysEWGCHPodJZZZrkHebiaxXVik7sS11Rr+9sVYtOjGz5N08YlISrP8LdMkx6rfOVvTSDTf7ZfnDkeUFfw+5Qmjbz1lTXcmOVvGDuYzedo29HhDpPRDlN9KNsVHgvzG9d7WZPcbtKR3X40x2DauZd792GafBZZj6F9nHJEMkpC2k57/nyRUfaHO1lc57NQ8hvNONXsU92XDss6pZiARKU6VrHXmaX6mNmf4nFZp2OfRYIr99wNCQnVZ+GC2N7ar5K16iGkKyVDNYmPI+3xP9zSZ+FGWadjzAWAXApA+qz+4OKzGKZ9FuU3c0yKx2WdqnOxvPABEJd/voRYVfgpn0W3bjNe/VY654wj+kZZp5dt1il4T9ap9VmkaZ+FOlLh2Pgs1GTZzTp1l058FKWf0l6iIdZx/FnwWZAj0KIHh+qNoc6DE4HOJL8/ffRxs0+Tf5AnBT7L5IIxgZ5fCKsUAM5MSGyIc/TlVrg3hVyHQw970ks4MVCxU7n3oOeXcCGChzx0m628cJlVizNbl9/EGg3J4iIXUJDfJFMzgw0815fr4y6HPeFKvwSUReifbScLL1s+C38xFFarqSLMug8AYbiC8FFYZi0BU6mPIV9HIPhBnJmNj2JolzJ7j+xDqZpHfx7KhJpGxZdtuxsS3MUW/bnc31JUOOZQps7vuegwm7C7H6pvQCYNM4FFAFsqNT3684hu7QqfhTdFiC2HKSA1TgGgf7rF8pO+RE7Ut9Cta2QDQIkM6QSSesqTh6TYhxON8NRxLxoaAcvLhNQRlk/rc7X8ZAFKDotn9TxxkZ2tOlmYN9xvGH6DJtxMoyjUVfIgJotJmapdar/bnBB1YhYHZ8ZGcKqfQHs8+0K4HB0Z0dSxF0q6QrLrCRSirWJXaPuUFLgU8wlG0ykh3cqdoH8D8nBT5MbBKaE+l+uUml0KLd9uMR8C4Ow1hCS76mf+Pt5HxqNqNHYc2O3mepQH2g5XrH/X/Je637jiO5AnVNXwxhXhTbtqbq7MczrJ5oWmVeqQPDfO06qlmNyfmEOXXdWYCo1eZFCkpsjQuOp5PXbKkS/tE8nzNHCzgruY72lBY4rGo6heV7QmvYZ6ruQJ3ZpF6zGLjN9yrjJf++Sz9lEQomZt6C7y5GnyUWY+i1lmmeWFy8PVLNIVU55lxkrZL2EL/BzK05mPRVFDW2wKyxg/iKqux1R3MccqadGxqrN6XhXKVcKKCZCUOYubVVfU1lt65K6RMTfmONcj9SgYB6tlUN62rrK1z4mqBnDTKjnFB6L+F/UBsFnVIYpcKQsY6+kKkxeyCUNZizgm32eyX8Zpy/Wc+5zDuk/pH1DyU/QaXajjtUNTaI5pCyXLAbj6Rnj3vLeRWbOYZZZZDpJrJwsi+g0i+pCI/ty0vUVEf0RE/yZ/vpnbiYj+IRH9JRH9SyL6sRv3TFf2Ef9k6YNyU9pVNqaWn/Oq61KIuA2bNk64TPuet2u2PVJ2VhmMV502gqBl8Sr/Juq/kabxwmU07tr3qVVy3EZZu9AVreEPZb1OfnErXj7muH+2zzacWssSmv7Zft6qH3oO3mkr7bZPozGgUf/sOF4Xgp28R3cgh5ghvwngvwfw26btVwD8MTP/KhH9Sv777wP4GQBfyv9+AsCv5c/jxTJfAU0SGDpfMQ+K3HSjea8TJu7yCZSaIAAQV7ki9yAVyuKqgwupVAmjTcw52DWRjB2BFz3Qd7UmBDP4ZFHPsd7k4/vWmQnx7KujrLusEQAKjHjiAAb6HAWISwe/SUiOJFSax8KvGbF3oNO+yRfR47ONhhCVaIJlEh/vA0DqegAIZ76NhqA699QbGpbZieYrMhSsuRpVlU7FsUuIqwr31n2Gx/3B0RDaRAynOVmrr2aRRhWkn6j9VP/3IOYJRUZYERbnKP2NS0LsURi2+bUOYSW5IqmjEvGwx1azS6uNdRc9Nm9SE+VIvWyvEQ7Zj5roRFy0E1da1v4C8tjZaMjmdSfXTV1hSd++Tti82Tpz4xJ7oyHhDPCXQDT94iMcEdduysz/nIi+b9T8FQA/lb//FoB/BpksvgLgt1ne5D8hojeI6F1m/ubhXdojTSTDfLfs3hbWbX0OFpORZRw6dUFChuRyO7M8gw1QK/cjxHqulCTCoGUQFWcRTSKZhhyH7FsB2uQwlgnDrg4uKrv4KJLALLiMIe2EQW06ASAToTOf2jbep1wHBJcwDp2WaINCqAmZLZtrOIV3MRMtk7bxF+iLvE3NGDT9Mu2CgYn1+GWMzEqe/wbypF7GnHMkAjk5K0/qDPAgF6j7+U0CSEOnaKIhWp6wjE0upem2MZdFQPndYjjKWAT5UycdijTSONpIk50s2GV27yh90ufKr4HOYDx0bK4LnTY+r3uIhnzeTADvA/h8/v49AL5mtvt6bptllllecbl1NISZmY4KE4gQ0VcBfBUAVnR2zdZozQzv6oqvBYydq0tWQjVjjDlDRvNIXTtPps6BiIsaLwxK5hi5TQsTwxYyzsWS7TkkMU0RnNpmChQng0cIGVNh+CxSR6Ao2zNTZXhy8t0WGi7XMDJDFKTlYMyNiX1kGLOKv2wTqISxqwVlxaUgBImpJmaxbNukPBsKq9RTvT15n7SoYLOxGdK0E8Del6SyktgWuSTgAagp9AbByY7AOXITl0ZDyOMfF9WsAbtSGFk4VKfMENk2aCLZwufCyLodIS3kfDuFkcdmCKMmkOVEte6iXj+Va1CTidBtHFxJJJOiQs6knEsiICrIz7zhUiKSGzPkGHXhpprFB0T0LgDkzw9z+3sAvmi2+97ctiPM/OvM/GVm/vLCraY2mWWWWR6Q3FSz+AMAvwDgV/Pn75v2Xyai34E4Np8c4q/gmJAuLkALpW9m8LlMsSGXHPRvvwVwgvdOShdmCDdiAhTW/fEn9Zjvfg60GUp5QwDAolIdF9s12/C0zA5OdSR++ARuKfnEtlRievMR0sLLqgig6z2Gxwv0mvLeZbi2mbyrjVjZrcjW1VSfChH6j7SE4yN0zzZICw+3jbVc4rM13OMV1p87aYhshK3apL0D6FZ+x8Hp17FxHJd071yk2LJwl21GDN5xQQWhqNfDEK2iPw/wm11GleGxlIcEUMbu8m0PP/h8zHZ7l9tTL99TV5nRy7ZbashdLNN3HRhBPgr7FeHsm6ZvjxzAhP5c+nX+rs/lC4G0ALrz6t+IC/ExaL7IcKba1QLhtDpJlTEciSbLFxZ2775t1zHv1tNK+vl3O6QeCKe+4C7CKTA8FvYslXDG4HN7f+vx1p8T7o1wapCpo9KUV8m1kwUR/WOIM/MdIvo6gH8AmSR+l4h+EcBfA/i5vPkfAvhZAH8J4ALA3zu8K0eITQ6zZQqtaAh1HF5VUQdncXSKo5IsaGqi+DGSsF0prR9SkpKHsd3WDXxlotc4uasAbwpc3PTH9ivDn215RCBbSiNr0AUGO3EsqurqIksXi5/OmBFQCPHVVqW8fLvbKeEPTYDiBBatSKR8rqE++ExUnHIwoCpkJithBqtmjezPzaw8Ff7Ul9EPGS5todGZqEfb3CBOQBcAENUXWTzdsGQyfsMC/0+aB6LPiDhM/YabSVlzMNSZmpSxS8+hTlZDaWjFb2RCEUdxblMHpynxy9T+XZ5T5Pu2HtFVvshEMmb+u3t++umJbRnALx1++llmmeVVkYcL975KLPuVZcSy4p1kjFoGLUcV4KXJYUkdmg7UcVtiYOQYZSfJZcKMVc+fOgfvsyPUODOvYrJSFisAwmTVmT4CklCWWbiafuU+NEWMcn/FuWZWkszGZY9PqS0loH1gL2MzxVg1brNO0PFvqXeTK3zqXcVDZJMoLqzzV74TtwlYqZNr486Vc1nWKmu+TJkhheafKJP/GkzCQpyG2qbMWbwVvEKhpGPIuDKKChaXgq1IHRBWKMWJGzPEuOL2miFasiBpn3YuQdpXKOaUmtBxBYQTRmeLDJ1yCcPKeeq9iCeiNcWVuT9HeC1fncniKpq9KTEve1N+8LYAd32ZTU0QqYBF5fPeZER/Ny7F17SRbTP7qced6KB6Ky9cSr/EDGFQU8ZRxpnvvlbKqE+2D4QaXdjZ5iUkTIwZ2g+W0bNwrLw6k8VVZDhTogxa+bu2HV0HdaofvjotK3yXQVrZ5b7EAsZAgkuzeKrsmyDjtpE8I7OfgsRexNjcREq/hA2sANFMu3zeb59schh44vy6zS2T0G4iVXM78q3n+kzcRF6dyeImmkU2QQoHBLNoFrdY/VmrhE1pFl7ql9ybjDQLW/GstDkCe26qialjDqiozIIpuW8xGgQ7AEnUe+VhYBJswDH1LW7TF115U2e0Bq6IyqZwsalwdh99A/L5b3hOVp6P7yjN4sBoCMUETiPvfMoTxg2jIS4IHZ569ikJ/BopgZiEhg/3FQ0xzF+OgG270rnI4EGiJs6kOzPX87hB7RCZTO8zGuJMNASoqj7HCnLStH2KuPtoyBbwnVyH99QQ0ghVgMnd8AzqJVLTrenOoyFuA5BHQ/Xn13RUNMQvXS0ToDKT38wyyywvWl4dzcLKIdGQsXMTMNoI3zwaQnLsEg3R7SytH+4nGuJG0RD21EQE3JCzIUOFmQvkF0WVbUBi9xwNkYhAjiJ0bTSkZK52gBamvOtoSOqRSyMS/v/23iVGsiTLDjvX7P3c45OZlVXZ3dVdPR9ytJjp0QwxmtEA1IfQlgIELghQWwmiFhK000LaSADBnT4bAQJGECFwIQ204GIkjECAKwkgCJEEwRlSRHfPdLO761+Vn8iIcPf3MbtaXLtm9z33qIrIyqqO7vELZLrH+9ozf8/etXvPPYcrZGg2M0x1K+d92Uvzv4psSGy+eDYkNozYigxiadjh8x2yn83B4jbTkMUUYs9ecRpCkWWKY0BZFFhAWUaN+6uYhsxdeAaRmylQ0RThvEuuvC6TaVgu2/Dz8/7UpiEp65GvRStUFZQVv3xQlh/StY2clODShmmQsNMQX/0UQFkhVQWnS7gzKKuRQc3bAeJ1grK+SnOtFPVzCOBpTjtM3oEDQGdnwK7P6yltSyGAx7KPxg4sGQ53bf7uLgVOrkS7fgrCW7FJcO1+yILKPIV8LprWQv9v5A/9boIbJnlrN9KlzbPtHjkuKqNctptKMdoU4Xfpeja7tCmBdgO490ISnISXaTfAxYhqVc8fDiJwb7RaIQ9oTLENnwYmNwbxJtKubkieVe0BZqw+7vcedvbz10/T+ky2a9dREBZuWl43IFKQ2p+JV0SK5dJvU7kSszA6nwAygc76ozHvByDzTpR27nsWedCZGKF1aJ+WJ6m68uDKobqW44ZuhXojJM2hpQK91jYlBCUAhGvxSNzIOPtRRL2JuW3sZbCwYs9WtxQogdHC8C7L2+dWb7BY9E0JuKbDNpeM9hmhuS79HWqa6c1a53b72KHacBaWBjB7uXye3YvBgohATYNwWTjNq689ATPD6wCSqOqn957BfedXQLt043Q1aDsgtg3cKvl9zJKVGCeAzCUaOYH+N34JgDBMM0ntgu+jqKkDWHU1wqqW4NogD3JoK6kTaD1iK796/ZIwndT5pvSfvgQAXPzW1/d0MkJdpgn1JuZqRz8yhlNx089W4p/2j2tUVwGxTsLGqZ6ivhwxntWITQmqqYWWZtOC5jIitDS7cX1f7e0DACf/Uvr+k995uHcDFbdfPsYTQrVhVDtDK8/yVqyvV/ntaQezcV3Ib3L1aE3ZW1hOZ+xyP8hA8em/2s7a4xN4qkxvSjszY/eA7BGMp8DJezq3AKYTUWHvnrb5usbTdNwmCSUnK8rt6XpO5fPBDwI+/IuM9lmV2saIDaO+8hhPrKc5b2NsI0SEeR5wXL/X5WvIGSsSFfXYAKtPkMlvXvwqw39tg+njVd6f1xPctTfSEpb+LcJfzVXUw/+BW9sxwHm0ox3tVnYvPIuDRpTrigDMMQDOIU+8lMvCuqBEBeZt4d4Wl5A5EUzgrzK6EgcCnHAklIhVCUiyp+R6zs8RDN2bWqwK/4P3RiSZTWWnK9uK6DLlf7JjCWTSorgz1vMAp1ZqUjDVpQf2AZDxIfKG54PbZI6JBogjIQaenY9YpwU877dFf1h4tboAe4E9nm8TqxLMnFealu+hMZ5cPrXEFZgksJeZqhhJaNi87ZvkQZANdqZjG2Ee3Vb7hruA0KagbcOIHSOMjLiyeWy5fhUu5jbK30teFeMd5Z+BZL/Q6O+TPLMu4Hzd40VXGurXE4Le0wAw8ywYcSKgMzeBW9ykn2FHz+JoRzvarez+ehZGmBjAHIoc4zzbcYh5WwOblu17xsGZvgcWLyYk8M/suOm8JuVKrFkGfVPzTI9ipnW6IL7lQGAFAAXOXg2FeZRelyEBgTDTE0lAsKUmKQAe5whONzF4LJ+6bLkPUALCkuUw6wm5vL3oh6YMxQRQyqZIvyDzXeoy2VH7Q/shrRhMMG6BqrXL/Zh0VReZAjcmZGU+j3pJQOE9TW2aJJWctUdSHMNVxdtyQwJmDanNBzITuix/jgzqHdxgvFZKfbSbp7FVCBlISYhYvMOibYJ8DZaD0/WU40Ias6De4XrbgPryzg/ey98kmaLlY+F2DqEycNi4HxS+ye7vYHHLaQg7B0rUehnWHfn205CYaNsqQow0c8vF9S8ZDK4cEPlW05BYlfqGLIxcFZde8vv5YjO5SkzXEKvUpoqkUlTPl6YWX+Y0hGcFJmUbpa0LraQIhaquTKUARuxRODIMYa/gTjhfu5y7dM6tpiEtyn6Qhyi2yOm/2JRBLWudEoFHgLxUXWoglaK69a9hGrKa5tOQVUQYCHE1z0qQnYZ0AQgEjinAmXEWrmyv/XfDNIS7CWcnOzxblcblaYg+PM08M/VFpiH3d7D4PDvgdSxxEbcxLWCCeQvqcoX55lz07Q87P9ahZfZYLG+BfD61TBVv8ARsbqIvyWzb+IblWXvD9hsv2meLwOy+d+3HQ43R48T99fZ8My8nYuZZHGrbq7WL9n5jOtBe20b7e1rLfWMK2W5sHgs/62yDXKxk7pnXZMeYxdGOdrRb2c+kZ8FEJkMByVIsK0kVfr2AYatlUEzaV9x1A4s2EG8TWJcqSF/g3pyg35mL0rBz5zk6lXNml9cbxu4AgRfba/TiSrLXc5g2JPZpWvAn2mwLUODlVJcMxKF9cj9C3G/ruUjfLK4jiehQRfPsQkgVrvmtTnm/WBn0ohHkybDuBVTbLqfIKQMk63LWg0mmHhrOMXiQzEVRM8jLQq5gpoucr0OBUqFRKDQhtDyLQ+QshYa60nQiVgTXTQiJI5VbBhrBxXBrMxFOHMQ0LXDdBGYCD4tsiP2dzTQkNDIVETKjtLgLeLDa4UVb2PHbbsB2LMf0TZlykIsYR4d6ZWG+uLUdPYujHe1ot7L761k4t1/vkddhHrRMDFiFQej2w2Umik27ZXisk2AiTZgVXd1FEzNPS43+A8yyvNyn71w8HuWdEJ4Jnnk6r8yUdBsjzI9P+9eh3o3V5wCnv4kQNUNSXuLz477qK2rx82of5nl+Xm74O1Q20AEx1XPkxhnP7YsYzZi9GPApaGGCM0yJHInMPgGAZxBBAp2Y33/aqhu5PIhRuQgyQcpM3JzCFq8g6XOj3d/B4rOMzLTjc6YbNx+jfGaX3z6IuZrUaEkmnsrbHn+J5Z+NYSWoXW76aN3kBMyi+YAmA8jtL/OVzLRzNsD5sl4HuLwsluvQ/spp2jxYmGO+gvGyH3WwWmSd2CMXyOVppJLVGM1SGZDNAPKqpg9nahs5nv2+uc2MMoCQDBJwAHkG69Qhg/I4V9vqxTkq3wAAIABJREFU4Lt/XqB2IaevAcC5mNsgmZbXN1gcpyFHO9rRbmX327O4IQVKU8wgIo5RpiuB59tbsNaB4+hbj4IEyFwC/hTxXWGYolQSLufVv4tmB8Wynf4NJLalsbzdgOSiQt+6+rd8d4O8BDJrUxIeVjFfW2JedC7m18Ues/Jj3V8/b9oHQE5BumG+jby5SyBWl/lewEHeYCrcwLOKRws4cmM5bvbUuADAeJHvt8vdiKQbko+ct/FUKAIpcTfwVDxEaadgTfyWZgLGfpDgtIKcvCfEXkvTaQ4CU+cyLYu9/o4RYVuhUgAWO0SqRJ+jLvMHGqSdMXV4oPRfTLiWNA3J7FyBclk7ecWoUPp90qm2Hp9uThA25THepOVCUQhMBnTFDFDvMG5NlPsOjsf9HSxCmCM4rSkyE+lhDzJ45NJqZnDzOVJLsQwWMmD4hIxMy6cINwZBT5py9NvyVJLBG+TIvqf847iJS0Zm4qyhqapdcjNLVN2NEUruI7wQhiznddsCx6Hq4/odAKhLg8qEjACV68CsjHuOyzDZoawLeremlf5M5wvz85M+m2ZW4AbpcxfkQc+VuqxtLQ9fKMWbd7PJZCgCQPq37UdNSnDZB5zEqrhMMzOC0yBhEeYAsWxM6McKmMobgmM6XkbLmvvkDgCsQ3Z/B4ul2VjB0oNYLiP6fLi3BQ5ZuLfZholAi6FXvIrPh3vPoOPJnIF7C3eneSvr/krUlYqf8jEW4CP1hKy9Frj3yDNhZCbrEaRjDJQJdbIMJKcH5VBMmrU/9FzpTX5HuHd+o2pYZ5IBogxKJkio/RgK3JsCld8nDRSxKvu/Mtx7WMC9XYJ7G1nB28K986ByS7j3dleDbIp393MO92YA5P38sSQCVRV4m8hK6tJUrn0hTak9wDViV8NdGYqgygOjK5/pmGoKzwXkxwidA5zwLgBA5xy4ccAIcFAor3gfsfWZ98JvHULn4LfpzZ/mAVPnSpAtnTY0BStAsYjmuBoYTsVNDSrA0yaYt+I2lANikPOFhvZc99BSVvcG5C0VWtlOYdmH9gGQIe2q9Vl+hwLFVg9jWgv+ofbCsyArhTFKBpp5gJMYmDoqeIbW9Ieqirfzm9Yuj5X8XsohoRgHNxLCivNAqlgUyXrId516UCD0bwU0Fz73zXgi2qDVltK1i3Zo7CnjLXJ7lnwWZ9KGaeXg3thhnOSiYhtB64CRasSzMuqGwYEiZeyFX0+CS4kE1wSErTR+vGjStXBmuWKfKmZbRrV1Rdv0YY9ffvIUfxKe5POs1j2u6y4HOGuDswAxRt+iPu/LspuCpwfsXgwWZDk11aoKiBH0xkMAAD97UbbvQ3lDjAHUT3ARiGfpzg0Md3ktgskhFBFlw75VX8oyiuJZuOQJZEHerkL0Di4wYqPII0L1YgN/7fN81G0GuCHAbeQuoq38EKtn0+zNIJ8FXOUGk2UBUO0osUTpXFvexJnpaSgDjxsY3Sf7jFRcuSw6DAB+M4ErB5piYeg6sA8AuEsZaE8+PJuDskx6VKdNsZa3XtVzBoERi0dCoWQXstcRgebaXEt6CE4+CHlAWU6r7HI3Mdqnu0xck4FgiTM0C0sbnlHdJk89mNFceNQqdpziRNWWUF/JsvVHUR7+KSJWhGpbHjQFjamXNa2kU07eH3D5L1aoL0t/hrZCdQ0EUzquU7SY3uqhreX+IM3KyHZtus1jVWImsQKal7KsvYjZ65pWHb7/9B00L8pvPtQdVlvK2TVbwu93wGoHhK4sdNvbexbHbMjRjna0W9m98CwO2iES3uV6/WSJNRTVrc93rfIcMXLJ+5s3OSXCXpsNuVM+nksbFfYMYin8QZrbayMikuYIz88fJFKn8Qvd7y7AsFeyWWyHzLm1z9UTK8s0oEuMrCjvbFCPbZ+/aruQz6XHkd8IixWFfVyzXRTT230y+2qcZVGJe1ez6mVs+mFeLLi/T/5MeAu73E0oGao5He3smBRo1p9ZhS6az9dk93ewWNL72yxEZdCdaQqzfJC5roRQNn3KMU3df+LQdIOcK7QejgrXpd8koJY31PYk6bDYVoipFoDGgNBVkikBQMnNnFYu80hmN76yJeRxRjwrsQZClYhfQyPTB+GpLNv6QVzi6aSC7+d3eWj9nLkqMkIi19XrPbQPANSp3eM68UIaW9aGTGsCb1PQ3UTp/ZCCiVoDYgaZ0FIOpuY2nrpbc3BWVx7TSZkGARKgnEsB6IWXtvqUsnSjxCSscNC4lhiSsmHHymFKMZtYU6YLAGzMQg6sbemeewwPS3wj1hJfYEeYLAfnoOu5HC+WgUXjMBr7AqHQx1K6dxoksSU51vCAER6PGM1cI6wjvJmKspECoJFQbQjT2gTx76D0dk8GiwNvSqcpoP2hkX0ZSLgSPgv2vrBHE0kcJPFcwGhu5GNoIRg7gShXMrxHDbSRzNEdI2uLxFq4Lbhy4Lqcn+vCeWH5LLJpgNNoVLipFH2xF00LoVnT/SWoKTDlMhjGpDcimYdlEdKcsNfXLvNhWBX15T4AMp+FqJmbDcgMFqkNodOLYgTVrFBPaaB8VxUviRCMRkh+wE15dVgUks2Ws8YCMNvfVfI9O2jKxWsRnBXlrIcNZgrHh1yLBlddYIRW7p/YYBboLf2aBrHMrUEIJxFhp0FwUSlfqpWzl13zYLFiIBjPzZtBJG2vXhB78S72ODZWjPa0x7ApTzx3ASGSpEkj5cI1QAYLYoewLsvugqa9J4PFAQtRApK1lmmaUXo3AZN5Q46TeHEaJGUG9YMEOIES4Axln+papQRiFrWhKcINyeMYI3wvlP9Og4LMcNtxvt12REUEtx1zWwCgeRlyOlQDmZUvD6fvGTmDFQE3OpEP3Mm5mkuhmWeSm7iAjISNvL6a9oKV/kCA06cAp78hwJmXpz5qX8wZvrRGRa6jvO3dxPA9I260z5HZsOyUST4Zbiw4Cx0Y6ut46wBndT1mFu6cUUoPfIZ7G91WbbNLzF/E82AmBfEoQktoX8bym2xdlhiotqWvlgHOKnkA9csJq/daE+CUY1bXQLicZ6ZmL4NmPkXQStxG4/iuDLbsCNVW+EPbiwJ8W33o0Q+n6F7YrI0XT0nG8vISQ0oL74DQlcHlLlIAxwDn0Y52tFvZvfAsOETEzaaIDDGDr0UEKHz8KQCgevKm6Ih4D0xBPIdkNE7iRhtdkPjNJ6DdCE66IgBARmRI334uMAiMsK7E7dO57qcv4VLqi3ayv+sajI9PEBufcRrNywrDgxrNCw8QwaeUamwIZNLZwHya4HueeRniQhNOnsp1s1ujfjkgthVcPyG28lNVL3eg8w7brzVz6DbNdUkAoN54hCbpjqTl1Y5nrqe2Z41zgBnTiva4LpfxhPGUUF/Jm3G2joD6OsD3B6aO51VZnhpw/Q1f0JMWoUglthDrpOPRrTCelLcyINvM3PIDKEfvCWEl244nkh5Vi5WkxhXVefUtL3GNUSj86qsUl+Iy3XHpN51OkArTGvRvRDCVaUhsBJ07nR6IWSQuDp2OaHwoK5YdCGZSYFx9mxAaRn/h8jb9G4z4pMeAQqsXTgP8VfEc9HwAwKcT3GWFeGJSwgu6wM+yezFYHLQlrNpyclqglQVfWY5N70FVFADXqGggc6OkwJ4GLxVkpZ/sXcH2p3Nx7fNAodvFnXyPjZebPM39p5X7TNCUAqYAce8VDKZuY+g8/C4NSlwGJ185ASitHCo3ny6EpvBUAgAFJ2AocuahjrN+mjIoSwKs44nlBi3ttjacyQljNV8XK6DaHXZWp45ygFnPOZ4UoaRg9DqZRM0cQNb4rDcFlHXjYNHO+xswNRyDAKkUHwEUkSGdUigoyw0Sy8iaoSkASQz4NMAP5ww4YFoRwqMR4yRzo9gyYhfB5DE9KA+l05hGl+7BFEsIg04PU+D02eGI43AewQ3DTS4PMOHBhLfevMQnfdmnPu8x+nITUFvacPZgiyu/xvrMgBf97dMl93ew+CyzxWE3FIuRplQD45DuaQEMKUhnv0AMi20QGC5EYekeyzo3zlOeAOZFadpsU+i1LO7K8OacLpNjulA+db1bQsyRpqimPFyP4ccU8zBam0xFL7MI8+qbjvfmsctBzw+Ut+OZvitmfWHN9ofzZnsN4g16EfJZ+k7g3rNCspzpKN9nK+x5x7Jt7KnEn9I6JjKFeVKo5XsJEM60TkkCrfZ47NL17vy8yI2dnG9r4wU68KSXQkoVUa8BV42J7F2CnK8nxJhg5Jr+7R0uN92M3Xvc1rO/7WOxrVvwzqOvbQppv89usp+dwcKS4Vjuihu4LLhywORnngWriLJJteaK0IqkWtHS5Wk6VrfxkmKVNJZmLRymlUN17aQaM90gn0d7ZxXVqTbZAJNm5US9R4aCDw6Jnm/pec3h5IC89cdVyagA4kpHX4Jr0yq90TqfhHf2CX6W5woN4NN2y1St0hMuTdLG5TuQvAIVZWpRUIeVTB8AZCo8kWbU9qSDMhbXewh/MvcObCA11pQ8l9KG0AFwjPEsgiYzDWk5TVNLRii0jPHUSQYiBZbVswiDn4sM0WHPQrNQ6lnE+rBnEVYMrhlhx8jwlTbibL3Dri1y7fVqxGho9axn8fjhFT6ezrE+KZ4F/azBvQ/aEnhkldOnUAYO/T6FuecwiFgyRpczJ2SKylzCG6iyt9/FvCxvO5r9AGAMIgg8uRyBd31AtREsAzvK2YZqG/e0SCmWB6naxgzWKjGLkq3wuwA3BIAof+p630c5vi0lT0CkYB6eaiuAJD+YWokknlzAVC4vJ2bU10atPNnePJoob2fX+UGyOYdiFtXO7cUsquvy9napCI44vbHTm5orWVftOGuP3jQNscVcpU1lW2AB4faiOq9Zj/rKg1hSrTT5nOGQWIXgNbIHwYSqkuyKf16hTpmP2BPijlBdEciAGHLMYldS4HLd85hFdX344a0vHGLNqK9Murmt8Gl7Bn9RHuMx0CJmUb5/jHPgRYNLw/vJ036f3WTHbMjRjna0W9n99SyWtlQou42pmtgyvnEX+r29YwJYeIq0PP5PwZQcZblMxIDmSD2KnN9ORT+DgdvHul6LzSDRjKK1YZYzl2VfRXvs+WdtY7PetvMr7rMvck6OdCCqc3u7v4PFZ2VDrMrYIeUxQGIcjkSx7KAiWQo0Jbc/VgQKhlTGws2z7IDbF1BWRTJHsETCn6cYZqHfVjGMDTKVvUuxFKNI5pxRKrP9k1Cfdk6e4gQaBwAEOWp5KzPq0RFyOfpCnGaZkgxtcuuZ5uuYskLb0mJVqk1z+bkRYY4NzaYhOgBLv8g0SqccNuNjv8dDfEemKbGZx19io3EeytcZWnmZhJYzH0VOnVoQVRJZjpWgMeOG8zFiI9MrG0PJMgqqmqbKZHqL5TjO4cc5toxY8+y+il1Eux7RmypSdEFUx/S8BsFZr0aMvYdfWUWyg6c7aPd3sFjaXT0LliwIHfIsvoDNsiuAZCKTLin08yuwg4VKi1NTapsWFel29u/sWUxfTbtntnhTz9imolkev5o3uPUeaLJel+mz3F6a6bd+6Wa9nlfsixhSoH9539zS7tVgoYMBeb8X4GRmkHPgEObsV4cYsQBJe8YITAZXYASVM1Ve5liYM2DNql6zMHJMDFdcGK9CLKlCKgHOz2OyWrJXZSq6dE6ahCaQJpc/dT2l7ZdcmX6RdhMWrwSdVodJ5RrzjrptCqwOmAVO9bqsxd5sZ9ZpinN53XKNtq9TYNeKMM9o820KkXNKdslctcdkdeDGtwHOJb+oBB1NSrcXHIUb5ZpLMLN8ZhHlSbwxNzLc1rBicQmIevPC1wAnlVtJli9BWcPhp9fvSoBVg8pu59Bv6ozhAIBQ+dnf0aRGg2e4rUN05rG/g8ThMcB5tKMd7VZ2rzyLmS1iFmRjCLdAcKJyQEg4Cy5v/oxjeGUEp0NofUYc+p1Q7PleEJwaC/myEZzTaqEfQhI/mNHqBSd/E5dKzZFm8/gpXQfXDoj46SE429QuBkTjQ2MABF8xwjV96QjO6USQmT4hOK14cWw5TT1k0XjGYMcJwTl96QjO8TymWIgHKUT+jgjO0/MdrvwKqzNLq/fziOC8o4gQey1TL8FIUmCXe3WHKnoj/ANxRWOFJLhDOUD5ZZtortq/pW2zgJ6XoF+IKLqqUeoWMuO4Bhtr9zr1aG5nBEOFV0BZ7AGqzfIbgqav26zKWmgZVWUGiypNHV0Z4GPHMy7XL7VtDtJfjsF3qOewtmpGXLsO/g4DhLV7NVi4lSDReJxyqXc2y8l5tcll58qxSSGADcem8nQqRycA4ehM8+bmUynYUtIaNwTQGLI3QdsepGXwqS00BVRnHXgX8hvU9QHtBaF+OYC9Q+ykS0/e6z+TI1P5MeW4Ec1L2U+5MFfOwW0GVLUHjQGVtmvTow2M2LpZtkWh3mx+UTcwqp2bzdOVSEeDZNm78QQExvmPpr2Yw/JBnVZSMq2l3Pl8E6N+OWSgm7VqUwu4DAUoRNzkduiAS2lgy20gZHmBBz9I+5ty8Vl248CA4kwMaVo5nLxfAh3dcyELql+m+6NqMK0kDjGeulLOnrJJLpSYx7QihNahvmac/1GD5lIHX0KsKlQ7xtRVph26PvGIGgIfABnOv/7khohp9OIVmzR4+7TG5btv4fyibBa6GitT+sFVCZw8f9JidUEYVsbzuMETPGT3YrAgIlDTILy8ysuqb34D0CpTADzIjxw/+hjxX/8O3EZ6OZzUqK4GhJMGVZc6gRm8qkHXPbgpLFbuo1KV+uLf/EU5z1aCf7tHHtWOMa7lhntYe0xnNWhi+K3cTGFdgT1hWkshFwCsnk7YPi7d2L0nsL/3/53HqHYpPZbu4dBRIo4BmhdNmcr0jP6RIPPe7N4AAFx+s0L3Qhi0ql3MD3X3PGD7RoXxBKi2836cVkBYlQemfcaYVrKdsnBXW7+3DwA8/ufSn+/92w38zjx0VEhcdNozPYioXnpU14V1iViYtNvntQnWpmMw0D+i3F4957QWRnAAmApiWdqZ2jB1ss3ZjyI+/IupHV1C1vYOvJpyB7suDeoOOZIYtpXoegzCwn35L1a5bcNDRjiJWL0n903/RkR4NIJ2HtwF+Ofld42rFARN5DnhkZzr/I8avPNXfojvfSAM291qwMPVDh8+O8dbjy7z/pe7FsyE006mAI9XG0zRYTM2cMSYEinRe99NTN2OM9qXHQMPd2i6EdNPTvLv8+3ffRd/9e1/jL/zwV/I5/nls6f4/su34MCIIDxqN3ld4wJ++PIN/NJ5eQ4+/tsH9A5usHsxWBw0VRpTM8Q1rp/yAOB7BxoDXD/NtqF+BMZJimqSZ2BTr3Wir3MJglw3af6sN94Y4LcuFYolBq6+TIX0re63Ac2Vg9/OvZDmspQ+69RgGkUhCwCaK8aUi5K4ZElSe5orFkh4kMHCJTkCv4uoNwIVrxZwcjcRgvntm+sIN8l2moE4tI/2KQA0F5TbqG0PGunPmRyH+orgd4XiDSzXVl+bzI7JIrA3mQmN5o8lZmE1NgDMlvueUW8i2mdyu6rr7wZ5u+ueIXksTKWtypruBsI4tTMIN0AIO1eIa8hhnGqJWTQuQ7gBZByFtlNjFM0l43sfPMH0qYx2l02Dq9UKuKjxwWAYrHby/bqVweppewpmQlCBoNRXmambOJcDMAHjRBjaGt1zl/vxhx89xh/438CffvhWPs8n1ye4uFzn8M97zYO8zjnG5rLFxaaoKfXT7YeAYzbkaEc72q3s/noWS8JeQ7bLjvKf7EVRXRCIBiOhWiSHNElgqjAn2S9WwlhdVMxp9h2ABEuJZlWfnL4XRKdWnaJUX2qzKhgEJ3J8gcP8eNo+G9xT2jX2BSUZlwjRal51GquyXa70PLCPHDe1u8ZBZKi9jtAALmmH2MyJxBtQ3ojqWLEiD8u8vpyrfLdml1OkRBykaM/iHc3IXRQVaVXNucR2Ylv0U5iROS2zOFGTsh4gyWoYb6fwhuqxyrV0qwGXTSJK6gLqdsLQeNRtiaHptyqJ/nSrAcyEYZg/gkqKI7GaMv3jlsFtQGxc7puuG/G17hI/Wj3K+593PfqxdOaqKeCbygcMg8eZCWrQHaLa93uwsGbJdpWIV797kptABxeWh57SA69wbzLHzMS5VRoAKiCGOYlurAiOgJhusOhdjuCXh4xmhLoF7l0euhyzqMvDHGxZOgtRLDEyrFvX66BjYeKhTjDjRQw4msFI2st5O32oD+1j+zfWM3yUZFk0FJRSwbFlhFEe4kxKm8h3Yw1Y6cD0bdYf0ZSaKwJyOVjY5S4gwb3T+TWGQpAycG2vQps9g7StVIESxJ3WASExjlGUjEfoilpbbCTtCXaIXcwVoroOMKCqTssEKjxc7WTqAaBuJ5yud3jeVzhZlTnhhmSA6jp5eB+udghM2FUVHAFTmmZetuvU16X/2APcRLg2IDZ17scHXY9vr57hu6uiSPbW6grbsQYl2YkH7XxguO6a2TLvXmPqlIj+FoB/F8DHzPydtOy/BvAfAfgkbfZfMvMfpnX/BYD/EAJ+/s+Y+e/eujXWPitmMQZBZiJlMaYokXYbsxildF0/gXnMotrNYxZVK3NjpoKg9H2cxyy8eCHepCjdIOXiKmis5fDVFnsxC4rlzV5vi96FH0qJeo6hbBnVjhGitNWWkmsmZhl/AOYPuq632x3aJ/cXgGqD/ZiFDjBmsNWYheq1asyi2uFgzCJWJWZR9FtLzGJJwmKX+17iP0pzFxRxORDCQCZmoaMUcp97G7OgGtV16Sd2gpvQZZIWFyKbMHhUVybTo1mLXuMI0pZqx/jw2TlwIaPd0Hg87yvgosYFr/P+GrOYdrLdbtscjllc3RCzYIAHh+qqIEs/fXGKf7j+BXz07DyfZztWs5jFy6ZEjjVm8a5heJ/C7bUAbuNZ/C8A/gcAf3ux/L9n5v/GLiCiXwXw1wD8GoC3Afw9IvpXmPnuCPrlNMSbGv3aw6ebO1YOpJ6FLRSrRSBWP1P78vqcH4+QByK9XQpQihBrCXBSguRyLdqjoXEZ3FNtEvnNxoDEIFF8XnhHoSv0cUrdptc6rZN8oYK6WkK1oyTPV2jxYi3fp25+bDknzbIhvi/bHdreLteU8bQuqTlpm3HB0yWOp3Iji0ZsWqdBzL5ctx0sphXlBblNa2SPZpkNmS13Qn4zJh0OJZVxO5IshTo3rS3mQLmuKA95PJuypCCxSAOEjjML93TKmB4ExK1DXMUZH0XW9UgekAKupq7CW48uczCzbiecrAZc8BqnD0q6ateKxkKXvI2zrkdkwm5IYK7kfm5SWpMdzzzTeBbgugnTZQdOHs8bD67xmw/fxaebk3yeb529wI8dwxEjMuGsLSN/7QLed+d4+/xlXvZjf/tH83MDnMz8fwN49nnbJfv3APw+M/fM/EMAfwLgd27dmqMd7Wj31r5INuQ/JaI/IqK/RUQaYfkmgJ+Ybd5Ny452tKP9jNurBjj/RwB/A+IA/g0A/y2A/+AuByCivw7grwNARyefszVmVaiWHi+TttgqVSXqNZ+y2B5DgUMMkHAECBFucaFVe9TqokrlYamspCV5bibsLXiC7BJPKJWmAYVEdzJVlrp/QKpwVQ3U0gYX0j4LD9JNyETCegzdLmMbDuxj+1cqPM0GVAK0JU5DoLSdrU8ROjpzDpMNcRPt0d3r9vrdGi22oWC2cYqFWdbHpKC3mYbQkH7bkRCGQqOPFMdQtS+9LrdzUiFKbkbTx+bagVLr4SYWwJXGJJCCmTsvU49kUy+P2g6lmOVQNiRrsVJB2bID4uAQyaNO1bMAsOkbfLB7gOu+HPNpfYJNPz+HWuUDdrsaF4azM8Tb+wuvNFgw80f6nYj+JwD/Z/rzPQDvmE2/lZYdOsbvAfg9AHjgHt+9KkFjn4mzQngI7n4YYoDzpBclsp7ElvV7PucdtCF1/1wSbps3O1eZ35dBR//xPJWp7F9fiPPoDrZsczrzHr+DXb/kT03b2RjGa2mTPSZMqhZk2mK2jQvCINO2L9ScRZl3vg2X5d/mb91necvO+mh5DXvnBSLo5vO/ZnulwYKIvsHMH6Q//wqAf5a+/wGA/5WI/jtIgPNXAPy/X7iVwLwKVVmpIKlTVkyEwVl8Xuo04xlsIZMvFZfsBLtB4HxcxTjcKnW6YK3Ky7JuaElbZhk+264KmWGcfcF/lPN/OalTrgAbjmbaT2uGhuEbefDsOi0Cy0zkupzluLlvtS13TZ0qO7hWlzKlatD0p6ZOCfmpi+zTg0fgNiJWNlCe2KcyS9WrpU5Puz4jM6smoOtGTLs6BzOB4lG0KXWqsG/FOeiZNhbTYgfCA6nT03bEk/YS67ac51G7wVXb5tTpeVfSpLULX3rq9H8D8JcAvElE7wL4rwD8JSL6zXQ5/xLAfwwAzPzPieh/B/D/QTyy/+SVMiFHO9rR7p197mDBzP/+gcX/82ds/zcB/M0v0igA+6Ase46kmi7fCUh8lRaUhUMq6sYUEekSZkLQjuXNzN5J6nRikKL+1LOoMENURo99z6ImRBW2Taui0fUQrkaNjwgoCwaUFWs5Rkg6HOWtTBncFRc07rKP+bsq2+W38oF9AOTS69DwHPNA5a2q8QFOYCYKBZRFyc1XzkxgPgUIDTKi1ep/xBs8C7s8BvFWYkqNaoo0AlJU9lmFZARgIplBrieEFEegmBCbKzYgMQaaKAJATcx0/XrNgIH+JC8m1lIU9rQVsg0tJNttG5x1c/3KQ4VktYuzQrJLBbktCsmoFWToVJf41cPVFn+u+xj/dFVyCF9fXeJy7G4sJLscWrzZXedl/ucCwflZZuIJOVZhafDuYMLRaY4bywNMk8ZDTBzh1sct2984D81xCvNgxbKeAhf+ydm2X27M4iZuz9n8P7V5yZUpauqLA/LiGl51Tm3IaADIoGYEjXIcoMisyHomIBJiWJDNaG84AAAZp0lEQVQoRwC271/RpuhMDIIQWOII8UCMwu4DAIEJY3RwOh3J94GJuzAdvPUiE/pYY4wGD5LOG9P9EZdxky9gP6ODxQ3LrWcRY2J9iTONUzV7gzBRyXrYeWKC3FpwlUgcljm1SAtiLxuiD7ocX7fFLBq/vHGJUZLZnM6/eMD07S7Sf/OOcOOCz2JikeRLn7psuY/0B+e/531TUJoK96aRStAymg1ZjqNYpnx9lAYW7Zuo2QyDjFwEju1ylyQYta0Kv6cA8QK0b1Q8x3Ppx0igicq2+ltE/WdRmpIxoV5IjPR8cu3z/lKGKzcCm7HJSMxhqLCrKoTJZcCVLhcVCmls7aLAvcc53NtmQPJ3D3DvMRLDj5TbcD00eDadzCpHnw9rXA9NjllU5se8IsncfNqU7GP4WePgZEBIepdWeYFwh88Oeyht/k26p4dsjx07r0B5aTu6eWC6i9lj2mXJlAVp2T7V15SN0j+6od1fgbFNo7oDy5CCmYtlsqH596p2Uz8ulhMB5Fmk+ah4jq4JuW1ZduA1vHjd4gdZqljctE9kqT1a1aN4A7w/OMkF3XwcTzKN0X83tel12L3wLIT+bjFY1IYZCwBfF+gsV65UDzqSt3JkxDPJHwtdP5KHgTx4WJxFjlmQvG2EEq/cPNO6RmhFR0STGqFzqLZBcA/KEp6+53ShnsuR5PutucVNoGUAxgOZOuXwJPiBBeZNyHDv0Aiv5iF6fJ26zP42/+y57DbSIfpE3fwA5bcwWdzHwr1eUZEeVE+EpRhNVck1ZqFSBQfbFebbHJoqEAOHhJE4Elg5WpM3QSxEOBnBnajz4DnfCzQheSHJGzHTKcpVyrpt8o5CijeYn3oK8vehKYAumdLUYwoOF1OXYxmXpuo0a8UQgECIk0M1lTZEJuxijcHUd+RBJzpEJkzmhgvBYZo8dlM92/62di88i6Md7Wj33+6FZ3HQVB9E8+KGX9NvhsKUBcANKQpu9D3cbgT1g4iE9fKqsxyd7UURRmYirKIENH2vLEwhaUhEkIonE6F62cPtKlSbVHV42aNj+QQA2sm5Vp8W4WId3DXjAki1YubUCAw/yNtIq2G756Xa0o8Mn6od/S6ivRQxX7fQ94g1zQhk66uAWNOMq/LQPgDgr6X96/fXswClxVloxqS5cPA94HelvJtYdD3cZOIs2fvSGEu69k3pA62gXKqe2eV+ANrnI9bvdanNss5N4mll7EPGyCC/BnObAjBeNGhfaNtE8T42QPOiHG965uFGKVa0IsWauVJdD2XhXn8S8N53n2SGq1gzLts1miuXi8KA5LVwwVFcdjzz+NSjWH2oWb7iQYgmjEOsKrTPinD10+89xu9f/Bbip+U8H7WP4DY+xzw+NXwf1BOqLeEnq9O8LGyPTFlHO9rRXrPdX8/is6j/zTqJDZDMtTXteRfJANJYBckhdVcvjFg0EUjRk3ccWtkEAfUzSwgQm2AhFWZrM09le149hqf8hv9SbBmctMFXvR6HTJuflzEBjgEy8aCM6eDEPl7O8apts5/5mHGx3gGx0qwUCSLVAVwVb85N6Vr1Or6IORMtJ/29eKYbQxqsJrNPKvOf/77m02RDsKidAZLH4SJm5R2z88/jZl9MFvneDBYHMBKfldlgzpT+ElyM4OhFFgA4GPTaMxugZCByClQGDWQx/CDkN6oD6tyBttxgWR8TWKTr2HyX5S4kfAcXN1dp5yV9W+6yWdHal2GLLBHPAqkl9UkBEli2tSwpGJmL7Ja4DA1avuLDaY8HlMBnTisbtLfS+KpmKQUJSmZJwghQldZ/wf6kQAWfk4r+lnUoy1oaCppqlrbxIoCKWNLzNyX3KAIxuhnWJKezdXCKr+/FcpyGHO1oR7uV3RPP4hXMwqtVllBH0dt4AOrKk1WZKipfTDIl8LFMF+7i/luswcz9tsvS9+jLNCRPPdRFTvuxcVPvOh26qy2nIeXc2mfFfc/LIsw0pHhBsiOKe4xXb/+yVD6rdGGx3EsRHQCZQoYydcr0hWYaor/rq3oY7Hj2W7Pfx5pYkJXuQ5zutwP3CvviUbBHYfy1Rgmv4Xm2TJXLyIDQXofdi8GCQ0Tc7uAaCXMzM/haQubxhcgt+a89kSwHAB4DaKvJfBZFMk8gIyIU33kC2tXgVQ2nIeh6/3JpYhAY09pL5iO5dPXHl6jWEmWmjWQKeN2if3OF2LqMh2gqQv+oQufSD2OqTjPKM/2WwRe8RLVjaHq86tP80gHdx4In4WqF9vmIaVWh2k6YVtL25tkO9EaH669XhacSAEio+Kz2Z9MJrZ7vOZ+33srURp8wpbhz/YlQza1oflzsa51OK6CeJDaRkcZeHoZ2G7O4krX+gZvrmgK4/rrLfJ/B0uoR4NLy2AhVX/RNFifSqlPXU6lAxX5GBZAsTWxk29AymsIoJ4TMUxKaAnD1bcJwHuF7Qlgx6osyqml1qwr8jOcxxUs88HCHMcVnuGVwEzEyEM8KmDAmxKdWxlIbZFaiOqXpvvOKD7Exigm4fifIcc+qjG7lRwPefnyBHxt9kpOzHpvLRM2HwiYOAA/PN3h2cYKHZ6Ve5IPu9nWe92KwOGjLia3l5LT0/pby35iUl98MMMpvPy0JryWYmUu8U+k7AJBXUhVDw69IrVTKLum6crLPo+q3x4izEnWX2xe9S29JZwJfLr8h5ylOSmXcpg2+vDl1/5jeZHm/pV6qoefPx1mWqLcsRLhxLj2glP1LYWUAqSCufNfjWvlCa+TLckqegQ6ElpbfDhDxgDBycTdkvaUNiE0qVFO914bBDSNGgFP5eukDLvEApOI6CY6g6UYMqUCN2wDXBvDgcmEbAMR0QS4JFatMwKil9AkurvKGS+Mmgtoo/ZHaULUT3lxd4f22EPaerXYYzOChbOIAcNb2uG4bnJsCt7sgPe/VYEEqPxgMDbaad0CIoAdnwHYAJa1TEMl3ojm7d2TA1FYAAJ+k1xcz6kvZ3/eFudv1AT51NPWjoDvTd0DQnm7sYKGDNDGqPiaXmxGSvmV3EeAWb+iqJYSk2F1fBlSqqN4zKL2i/VbO1VzWqDYjXPBwfYALZX195VBv/AIzIW6nHUCEFVyCevkG26WbPGMh5DO2DohA97Tk8dXUK8k/RU+or7ggTHX5wGhfhsxQPjOq4JVJPWFZxJvjtG85DhNyG/xAOei7+mTeHlEOsw///ptB0aR+ELX09qK0jYIMGO2FHL+/cHCTMGSFHaO+MgNNLfOdrKo2esl2RGD6yQm65+lhbxxiU6O6IkyXxV2qB22jDCpTGoh8qvOo0u/WPjv88I5nlajUb5HRo+O7a/yT8R3QRwVn8eGLDv6qvDivDM7i+o0O8bLGj67K9mF8vezePx1bsi3ZVKrNktisyR7t0FLx3IFilAFG56cpC0OB8798XC1A0+OGmOaeJWtijV1Js7qRs9htthE5neYCZ1fTGZo+bY8bI2iKIO/yp66nKUXc7UBIJbI+axNJ+izDvRmIi0EUEE+HAgQAtkzTLTaOg9nOrPOjDJ571w3J8uSsUtrHTQY2HmQqRpFLPCotpxTzcHkQo3xM6yYdeknmgrRBgG1+JhKtrr+2B6nwTnQs7ICqmRcdjGkEuBXPzO/IyBxIFsQPyCzccv5yLLkubd88C7IcqO11UEwDhdbL9YThukZjxJDYuQzgk/OU7yGI5iv7hTt5SztmQ452tKPdyu6FZ0FEoLqaq6i/8zYQIpzGAXYyzwofPJ2pqMd1DX89IKxrVNbzIAKNAdRU4k0AcB++yMd/+W/8gpwnBbdERT1mPRDXP8R0UiVYcFFRhxMVdQ1w+iFi6hyqJHBTpQDlp7/+BrwG+lKzQktZH6O9cDnQ53tG/1C/nwEArr5Rob2oEVpCtRM1dQDoXtTYPfIYTwS6a21azfVBuudOgoJEJTh4YB8AOP2J9OdHv9PNVNRFkUyuQyP143lE/dLBbyUQKCvlDds+b8rb0bwkhwciSgQAwaio52XZY0/9kNoQOtmmuWS8+NU0v7cq6l1RUafORJT1VthKaoJ6BzzsMa10KgoMDxhhxRli3b/BCA9ETJvbmNXL5JzpHkpEveGB3BPt0xrf/t138cOPHkufdyMedD0+fXGKNx4UkplN34BZqPAAIa6JTLgeJOiiBV1Pv/c497XF6fCjAVU7YXx3nT2Hb/z2B/jLb/8x/vCD7+Tz/OLZM/zw5eNcov6wLQWYlQt49/IhvnVWnoO/1/08qKh7jxmC07hOofN5mjKdVKAQMa0rVBd2mwo0hvwJYFYGP5ymoKWXtNfwQESFxtMUfGs9phMvrjKrAI9HrAjjCWFc68Pt0Z8TfIpqN2268R6WGz4PFh0wrXUAofyA+J6we0NofccT3T+JC7US7NSH2g8OwxlheEB70f/ppDz8gLjE04kEAadEYXBoH702AOjfCvCb4nCyQxb10ZT06o0ttqsV3JVHPFEgHMFtHSg6w5GR2sFA/4jz4KZ9MJ6ZZau5+22XV1tC+4zgvyZR/PO1vDiutw3OTnaZWOZB0vCsXESdUlGfbk7QjxW2uxq//OQpvv9U+KQpEMLjEe1pj36QWon4pMdbb17ictPhbL3Dp+1Zbk+7loe830jM4a03RXr98t238Fff/sf4A/8bAICvdZf49uoZ/uH6F/CbD9/N+3+we4AIwpNW9vtz3cfoY41n0wk8RexSpPj3L34LQEJmJmimI8bbjy/w5uoK/2R8B8O1bPuX3/5j/Odv/ClqM/f87dUP8PdPfwUejADCO3XJEK5dj39w+ufxu6d/kpf9o7oMJp9n93ewCGEetzDBS78LuXjMbwjUB1TeFRRoZPjdBBom+J0HpW3tMZqrFGzbSSox1vIGz6jKIcDvnBDHJGlCvw3wjkAsgTAAqK8D2pZQX+vbTj7bF0WCL2ud9pQHkOaCEfoy92YSRTINuLYXhHojhC9VzzkNW+0Y9ZXETarF7+wHwBvPob3gFNgrgblD+wBAtUnn/aTOEn1yQUVFTT2LXX+C+sqhuiZM6XzEcu7mEjk2YQcLdpTTpDqY+L54G9VCMc0u9zuguY6YPpaR8IWqivUOz1Zt9mBetDLykUtcFgDCpgImBxoIfxJKwRdFYIw1ho1H90LOPaDFJ70o2O3aDv6iPB59Jw+oehafpJfD+QXwdz74C/jTD98CAPxo9QjfXT3BR8/OZ0ph173IFSq57j9dfRNj9OinCo44l5lrUVh0yOnU6Bk/Hjzeb89BH7U5RvGHH3wHNQX8Xx8Wz+KPT76FH1w+RuUipuhmtHqOGO9ePsT3zoo26ovxQ9zWjjGLox3taLey42BxtKMd7VZ2f6chCuG2fyfjqqRRuXKponABJKocqHL5E4AwciXT/Ly698I+veBuIAEYaYxVmL0ps1UBMn2ZWgvmSnPtDmX+kQOcJZAXtySM3pDYQmiRU4TaPnac2LkLkEmmTCmQuUgVTx2J2LD+vS3b5cDngX3kOhT7wHtk6MrgnYOGJwFhlFTrDAjF0m5vGLXS4sxeLudK5z7hnNYO63m77HImYTTndZp6ps/gvXxP/dymYJ1g9GQOtAHAkRB3Hqt1j6HuctPCOoK7gNgkdfbTgPq8x7itUa9GjDY9noKnIfGr1Ocp4N7V+OWzp/jkWqYc512Pt1ZX2I7VLJD4tJb1Oi34+uoSgQnPB/nBNMD5Ufuo9LXJFJ+c9Thb7fDhiw6c7uNfPHuG3179AH988q18nl87fR8RlNm9NUYCAOuUv/318/fzsv/HH8KRH7b7O1hYnIP+nYwmzlWnAtFmIagx1HZuEpyCfgKYVbZqxF5z976XZVrrIMS8cUZV5yYGs2RA9AdzI0tMQfP3adtqV2IWBQpA+QaQdSUbogG9DFJKx/ROcACZMHYSMFS1k3PMzI42qQ0gzp952d4+0o8AUG1oLxtiSWSBRAyzoVl8RLMhfoeD2RC/K3GIPOhcl5gFLfL9drnfSR+46/RQa2Vw7+R72nerUOkbsiHXdYeVtpkB3ziEWNrgrzxG34J6h3F08FeGrk5p9FLMYvQy0q92wPdfvoWLS3no+7HGdqxxcbnGj02NkmZDrlrZ73LsDmZDXCJVWmZDNpcthsHDXxUcxQ9fPsbfP/0V/ODycWknaJYNed6Wt4dmQ6z14fZDwP0dLADcyGdhrBQX2aDc7YEmsn3Zb1as5NLbW++vOx52WcRzk5odE/KbJDOJE0qBm66Hgqzu2pC72aydhHmf5Lalvxfb2oKxGW/m7BpeQ7sAMygswXgS5ARSW4JsS4732+Z473e6q7kiUCnHJk63zz7AStm99c1PSrSbMh+l6JCL93xDYSQRw4NRGVUxB87H/IIKB3t2vweLW7J07217V7FHc4z8hmOIp8JlvSGKvttx5155thnNf/5e3sqqD7JcT1+y1ukMGWr+Lhqe2ONnsOzdS96J2Xrs98Nd25V3T/ID+6MwMhFSfmKYwJZjQg9ipARe1SLmuh6cdD4OkeFqmld1PVRnRLctXlxpF8XDuiHMhADKGiS5LUyJp/r13iP3e7C44Q3KBMPaRIntau5ZyNu4fAKYFZsV7VB5s8QKM61TZfyWu7+cNyYGrawdqrqjClHOfJsALXrXKoZFo91JoRQz6XXk9ijreC5d1/NTZoPKx6/mhV2qtxoNQ9ShfWx/xBp7kHEt4MrjQiOxFDeWdhMgKvFWK9UOOhWKxmnWOuVc52CLtgDMltNEqZAsPUnpk7l8BwCfKizJ6DxMkcCBwAzUTSh9norFuImZKT42ovzFDFBbYhlyzXKeqCQ3qSCMqxqP2g3eax4AAFbNiAftDi+bDmdtKdjSB1e1Rx+1G0Sj66Es3MqZycTIlAtUNFSvmlJq8LDd4p362Sw9+qS9nE09HrcFGNb6CRfDCk+6An70d1BYOmZDjna0o93KjoPF0Y52tFvZvZiGMDN4nGbkN0gl6PFC2Er8O9+ULMeDc8TABcI9RVAIoFCBroo7Fr5xnuo4il/ucSYZEecKUtOgDW3Vpr8e8vTFX2vJIOH6jVrg06uUIj0R+HW1dWAH1I8S3trO3dWWnIyLCkQAqBIS1Pce9XUE2KHaRnDi96g2AdWJw/YJFZYqyBQpdMjpWAAYRoF7x8ZAw1M6WNs2JpDh9q26JFNumMOXpE6RepxNFDlldjZ7u2I6MYjW1O7dEy5cEisuQV7P8G2ZGsQG2D426YEbgh7k9l1qZhTmNOKSkQFAI4FGI4p0OuHswRbbusXjh1f4GMITwZFQr0bE4BESMvT0fIdVM+L5kxaNC5mftfJBAoyOM+RclwPIy5r0eaUCzipfmDIdS3Ldh+cb4aN4o8vZoMoFrF0/C6Su3YDKnLc1qdF/6/y7GKPHr528Z9b/PJDfLIOURrPUpkNtitSmRt0YQX2A9w5uSB0yhZyS9YOWgqcfuedZShRmQMrkwGNAtYkSLNOBZMeor4veBw0FRv5Zqc1lOlMfsJzC1NTpUD51vR8E6u0tIxUBbiH8W28kYFttGU6L1rYMbwYEJbqpN+m81372QEmz5zeuaGpIytGu87uUgh73H2a/RYZ7K+O0HCOlDBNcIkPDU4oztsJyVW04pzJtGtOqwo/jvqNMqgOzcxh9i5W5tmoj0H29XndZ4cqvwTuPj6dz4EWjXYsxwbtd4iO58itcuw6rC8IPX76R2amGweO6a7C5bPG+K6Q0u528tK4TVP1ySCnUnXxOU9KhWRT6qT27OMF12yBe1qDEuvXu5UP8g9M/v5cOtX9fDKVYaIwe3794a6ZStgv/7OD5Dtn9HSyWwU0iKFrIAq0s+MrbAGZFQudfu8yGRUnqEBBxGqAMFiIJWMBW8ASuU4Arjc5c+/SWLoCqmL7r8TiDsmhvwLOgqQyYAgDmvDyDoxLQKzQEN1EGkcXaITQ0B30BAEkRmaWnCzspVqNYCtGw4GXM1aiJ3MUCpfJxFoCpcBowjTJg2nVMCVx2gOsjrChneoJ6ZeuYU4WhK56FTbOGVrAmsZHzApgDpAwtXL3a58sft3Xetj7vEbriaU5rRlhHKUwEEE8C1mc79HWD9ckOl0O5n/xKAp/RySOzOuvhfcSwavFL589wsZGOPFvt8KDd4d3o8PZ54fC7aOWHedDKyPRmJ4FHFSlWSUErAGTt4dkG512PH121mY/iW2cv8LunfzKr9bCAKwCzYOavnbyHiR1+/bR4Fn93T/L+ZjvGLI52tKPdyo6DxdGOdrRb2f2dhixjFswZzk0hZgi2fqewCG4FlrjDVLYVkJXup8vkwyVKvRwbMufLbYlpm6lwXQos3AZKU2xhmhPq5mUj9tbb5XZ/aQ/nT10vNHyGal+PvyDLdaOUuNPEuSx8b59ELSdanEmvdOHN84IfhQaXt7Pr3CjHOUirNxZV8twHI+XzW+JgodBT9KJ8dyPnuXpWZx/cDN04uQO3c9qHBoepr2A4dCVOMpjfcnDo+xph57FzTd4XAEJiRNc2DH0NIkY9EJ71awy9nPvaNVJy3lc5LgFIiTpgKAXTp26zG6vcJ4dsm/bnwec2XAwr/GR8PItLfDScz/62wc8fV4/xtD/BBwkTAmAWv/g8I74r2vFLMCL6BMA1gE9/2m35iu1NHK/5z4Ld52v+BWZ+6zYb3ovBAgCI6B8x87/2027HV2nHa/6zYT8v13yMWRztaEe7lR0Hi6Md7Wi3svs0WPzeT7sBPwU7XvOfDfu5uOZ7E7M42tGOdr/tPnkWRzva0e6xHQeLox3taLey42BxtKMd7VZ2HCyOdrSj3cqOg8XRjna0W9n/D89Ey9DBAHnAAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.72327423095703 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-06, 'kernel_type': 'untiln'} is: \n",
+      "[[  33.000032     26.            4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [  26.           40.000064      4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [   4.            4.           33.000032   ...   49.000032\n",
+      "    49.000032     49.000032  ]\n",
+      " ...\n",
+      " [  20.           20.           49.000032   ... 1417.002644\n",
+      "  1417.00262    1349.002784  ]\n",
+      " [  20.           20.           49.000032   ... 1417.00262\n",
+      "  1417.002666   1349.002907  ]\n",
+      " [  20.           20.           49.000032   ... 1349.002784\n",
+      "  1349.002907   1287.00473601]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 43.30772376060486 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-05, 'kernel_type': 'untiln'} is: \n",
+      "[[  33.00032      26.            4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [  26.           40.00064       4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [   4.            4.           33.00032    ...   49.00032\n",
+      "    49.00032      49.00032   ]\n",
+      " ...\n",
+      " [  20.           20.           49.00032    ... 1417.02644033\n",
+      "  1417.02620029 1349.02784013]\n",
+      " [  20.           20.           49.00032    ... 1417.02620029\n",
+      "  1417.0266603  1349.02907019]\n",
+      " [  20.           20.           49.00032    ... 1349.02784013\n",
+      "  1349.02907019 1287.04736051]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98abac50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 43.34777474403381 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 0.0001, 'kernel_type': 'untiln'} is: \n",
+      "[[  33.0032       26.            4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [  26.           40.00640032    4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [   4.            4.           33.0032     ...   49.0032\n",
+      "    49.0032       49.0032    ]\n",
+      " ...\n",
+      " [  20.           20.           49.0032     ... 1417.26443272\n",
+      "  1417.26202868 1349.27841344]\n",
+      " [  20.           20.           49.0032     ... 1417.26202868\n",
+      "  1417.26663004 1349.2907195 ]\n",
+      " [  20.           20.           49.0032     ... 1349.27841344\n",
+      "  1349.2907195  1287.4736514 ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6518>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.50049710273743 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 0.001, 'kernel_type': 'untiln'} is: \n",
+      "[[  33.032        26.            4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [  26.           40.064032      4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [   4.            4.           33.032      ...   49.032\n",
+      "    49.032        49.032     ]\n",
+      " ...\n",
+      " [  20.           20.           49.032      ... 1419.6472735\n",
+      "  1419.62286876 1351.78534411]\n",
+      " [  20.           20.           49.032      ... 1419.62286876\n",
+      "  1419.66900512 1351.90895058]\n",
+      " [  20.           20.           49.032      ... 1351.78534411\n",
+      "  1351.90895058 1291.74114165]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.623023986816406 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 0.01, 'kernel_type': 'untiln'} is: \n",
+      "[[  33.32         26.            4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [  26.           40.6432        4.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " [   4.            4.           33.32       ...   49.32\n",
+      "    49.32         49.32      ]\n",
+      " ...\n",
+      " [  20.           20.           49.32       ... 1443.76870688\n",
+      "  1443.48756    1376.974512  ]\n",
+      " [  20.           20.           49.32       ... 1443.48756\n",
+      "  1443.96152288 1378.265576  ]\n",
+      " [  20.           20.           49.32       ... 1376.974512\n",
+      "  1378.265576   1334.875648  ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7fd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.25333642959595 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 0.1, 'kernel_type': 'untiln'} is: \n",
+      "[[  36.2      26.        4.     ...   20.       20.       20.    ]\n",
+      " [  26.       46.72      4.     ...   20.       20.       20.    ]\n",
+      " [   4.        4.       36.2    ...   52.2      52.2      52.2   ]\n",
+      " ...\n",
+      " [  20.       20.       52.2    ... 1715.6528 1708.44   1640.952 ]\n",
+      " [  20.       20.       52.2    ... 1708.44   1714.7888 1659.776 ]\n",
+      " [  20.       20.       52.2    ... 1640.952  1659.776  1813.648 ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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tEN9P8xvTcxlDVovw8Rf7YLhDpJvXMMJ/XhgsAcVbZPs6CSSzjA0xIr4n/VKvCIhAOwNM/FTcs/Z99kRwl01R9/TcA8QvLqExT5luEMV6MnCe6EQnOoruhWTxMuLrOF8ODec9KeDlDU+MjzlqsrguydgrANwsUnJikziqL0A9BhV7bbjyJHT5rZAV0yeuZhpDkW6sSsIMmgg1rzSKPAfXzPFUnR3Szhy5SFyvYz71PZmmLpj+rp9eJZjUr17TKHCtZt2GtI05N/0r0L1gFhwjeLcDtaKTcgg5hZpGj1qQlgKuAIhNIoGvLPrQPXgg+rlJmONsdKA+tJAeUtukhyfH46ef7YvuzsE9flSJuTwGUOMzghPOeDHUOKv3NDYFHosngccxw8Xjk8/k1OWieBvSOACA+x7UdRKl+DLQF1DAXPalmcKmrTEyRrGVTFWVCeANjU+AsYnxkxn84grTlIgAgLatwG0A4D78vqK+THRnqlTGCbDKLgCivOC48bVIrrToMmOgpwYF2rYyX8lOxF///oK7UPUNKIZvC5pLkdIUxdNT4SxUfWz2Db2zRmJzTjbiTih+48PiOdFLAPDCZ3uJzIErmA0kGwoAeEL8gcfCLPXdJYD/2fGpDe8Fs5gjntEXFaSlng4A2dvBU5yu6nYc919+oCzu0nhtSGTOhqRsZ4hR2hsZrEyBY8Lr686S2rvOWzHxUHCoXxoMo/HGGNANszCXqcQ1XUBKuqCVcWXQj+x82Z7ivdg85oKipp4KmxRomnzmQIyJDQ7kMRkHDfOmkWqPVDZEav+cgKZeMtY521e1GL2vJVVFyKrtaNeDgzAc7tri4bCSlAFKcSNzRlebwkQss7AMcCp5THd8fZ+n76WOTe1AzmUmROsteNfUgDfL5DB1FJyJBGMYFr3MLjOhe8ssKlyFHlMrvPFwVF4Pa+lXLEbCYQCojFY5tiLjIhpUouMwFIu3kSyoaYSRZMkC4p0IofKqXIeDsJIF1E0M87K0jQjYU8kiRjnX4jhkcsoYLU3EbELy8ljPBFB2tuViXrKwpJGOU8bELEldZiQLmpEsLKZDIeAWcwCgQJtDFG+F7c/k/rOShV3ozhXsAmAki/SuLTqBgMeIuOzger/fhjKFRnAUFBhsvWG3lSz05/W8+hHPFnvzw+7sRpLF+GABv3GVFDc1Or+M7hWzyKpF2xTrvPlNcRc5RRkOSxYZi6E4DKDCYewtiCMlC1aR1eimbDmavccdShaYBoQdwHKQdxVWI8OMJy7LnHLtQL/37vU6JIupVGBVpjkdeybi97VKFuttlmrcMFY7NqhmAPJ+GFf3HUsWzrjf9d2jMdxIsmjHKO+nmadZte0AnbwhJzrRiY6ieyVZ1CHqNcdzi0XGXdjo0SxQhNrO4UzeAZUo3Nfez6JkSNGhexw/txtynsS8I5KoIdWOSknV2e1EzXgs6fjiJ58exDTICRPswxTvcCCJDCKL2nJWJ+GZIkABZBg7EWWAD/d9rTrojvj+I1A/ZAPrS2mye1VkpZbpNROiRbenxuxRmhteLYAn14RkH0LKmt8riXViwKbVquBaQpxISGlcKSpUo5zj+w9AHz15OSbjZX2dXncozd1Skj/xw/MC9vrOx4Cb5K6dSmV2fhufEKJGCrpBt+8Vs7gTsg/jtklDLLGqBKatQ+L7XdLkJeMZGTEbhO3LY9x16YB8hPB65uemZBGVSlNmFKMYHd9UX7Q/RvXDhBkTIEx7mqTprsgAz7L794ZEIc4w5HfVwHmEL/ha3MXL6HVkNSKHvYzS9rc3lTkJeGlsST5GVDMMa0gkyhISTV2hb4qyYdbs8kR7UtfUtXpnfamQlZMd2qIf1Z38pjEv1nB6QxJEcqyljRvQ/WAWJGnpbHk6i5MAkHNmxiefSuIaxQs0jRhtVD0AoNBaxSToLpVVDwD+B39AvmjgzqKtIMl0tRGPRuRyr5R0hharstOke+h18ctncv03f3ifcXiXcfm0G8WKDoCGEbwU74Z/IYFcvFqI4Up9+BpFuetFJA+xdu0BOdYhUz8UK36CiWfQ19SynrJQxZ/8cdAwVZ9QvWCx9XBDmPWG0C4Ud6xZSHHV5h1RxegYuICRdD4puXMVf+EcKEbQ8ysM/96Pp3PSJZwMzenc2Hk4Db5Sz1mQKFQaZZH4TdlswrIBNw7NpRgVA1BiNvQaJSLE1uU4DH2O/osrXP30H4PflXPZybVxoYy49DljQpyoABQZFBixlR+6F0MRWi0QzwGxcWif7fI8Xv3MH8O4dGi29b3dyOb/NP8NodnEPLb8XD4/HmdxMnCe6EQnOoruh2RxU4pmR5uzFxAVZKY1GFmx0magopQNihmkrNiK5FkkFimDYVxSmi15LIZJAAmUZXaGdK/sqoqx7PK8v8Nmt6r207o6QxSX3VRySbtwJs3WFGPZ7WeusXPj1kMd+GYQkto3x7Ib5nwMSiG5m2fE3EriUIzMdqhCsgGUMHObJSpECSTbasq5gg2xOAHN68BEGadDIYI20if2RQpBBPx2RGx9TnbsdoNIDMl+XeEVnIPflWNZQuwHNFcBXqNOneTNcH0AD+YdClwkIQDcFOMiMSMOyRbSR5kEqoF+bj3AOwe3GfIz7J6PcKOH20VojSr2BDfEktvDzs8u7EkWdEQBLKV3k1kYkozf2McCHN0AVb7v6qV1CWCUgS03vMcUgGPJMiNN9zZ5uGh8Sa+XKKeNu0Ni276qIMxVaDO3Xl5GPRYBQgSiWUgT4x/b+bjNGOw8pAXFjatsdDn5TRLraQD8GAXabPNLDEadeEX5midqmgLMsio0gx1hR3nhsq2gpvtKQ6DEQLiZnytOmAtuCpaGWI8DiJP5ekW638yiemkNN2x8ATfpYq9ClaPo7szlc9IGL5IOrzvbalFyUwDAJtXP8K6g8wCpSdm2+TxaAzhbySeQz+VVt79Yuka4OhHcui+LKjDiSvrjUz6D8GABt97JfcZQIL7bHrzw4OWiBg0B4LbJdhAAcOstuBXQjrWPTK+R8YqtJF6Yfqf5V31aKSwb+O0IhwaxKyhFN8RiIwGqHYy7ppQrSOPm8+WeHUPzMOTjCw/aBbgQEM5T3dt0vRsjYuPyQmDzPc+BJ8ROsnSFhUP3rM/3iwuP0Dq4Qe4dWo+wakBDBLcOflPmyt4TAMJK5q0bAnbvt+DnLp1HiB2hWTuMK3WvI9s0QqfnpZ+i/On/q8+4MBmVQojADxeIrUPrKc9N/6jB9rHD4nmRLMYlodkYW1FrpFpu0KwjxjOVzKS/x9L9ZhaW9gKLdCF6zPq4NapQPydkk7yCSBa5Ff0AzGVLYmbZKZQpMMtiVIOcEXPV0KoSCfVjyfhc7a68V/fD9aMwNzX2Ta3u9pjuKhNGgNS3yg1o1Rn9veq3aTcw4KkY9dLLaxeRRQAyoVZDgu52XCNiIYvamWPUp/mbGDixS22GCEqGO2cRiqEkdY6IaIaI6F3ejWUxyjPzfcwL0Y2xGBI1BCAy/GaUHV8T4SbyyQipx/IchAg3cH6f3MAgFgOnGykfYw8gyneZEzF86n31XLCML5pExOwpG0LJ9Isio9kxYOASzSb1haQtn+Y1NoRmLQbOZm3m76uAsyCa1HGcZkTSuArvRa91LieuQXQSPao1VGdcgtnrwcktl2JDeCUxI7TeSmoz5jxL7F12R2bJYhgkjmMwXgYk0ZRFxNUdlr0vOv4QcrYvtIR41gqWQOHErQdGKvdXr0XjE/7fMBu950SyUIlCs1vLPJq5ICrnaxtWVE9912Mx7YpMJC/jesw7rAsR1MdqjETKHOS+rGlPVbIgA0YzkgVPJAvsRN1UCScaRhCWJa8me/FYxAUhpB212TKaqwAmwvDAo9OXiuT88dyjWRe7zXWShUqDOm7vHfoLB79VWwZhOHfoIhA6lcxE5XAj551+OCP4nvNY1IPhNwRiEgkkIb9j60C7pLI0JdaHPWH3kLD8EplbxAZoN/LqicSi0gkwnrk9yeIm6snJG3KiE53oKLoXkoWWGKxK/yXAi1YztxBvWzKOh0GS63IPephSpo0B8dPPRLQ2CU6tSpET02q9kZSHUfMJ8LKTXU/h3BCxL764lGt0Jw4BtN7kIDgdg396maWhKkzYYhOMt8Q9S0bEc4Fx0yC7YcZCWLvJdgCefF4HsAEAuaznat9ATs4jDZCbDxLTAKb2k2fVz7PZvVOfEQIaG7XKDD5bgFFHW9IYq9DoHCX5pFTyOrTBZUVt6NH9kcnBORfOrr+p5wPJ2j+MgHdYREZ8uMp9c7sRzYtdFuvdk6doFGiVxrc39qQCNRoFvN3i/X/aFEnIOSBhNLJB16V+WCRo47Kah8AIDyWiVlUPvynqH4jgP34qYzZetosx4vw7jXil7JzNJexlBl1tq+zrcp/jy0LeC2YxS6mW5BzZpLTQ0HTvS4r5tMBIw5JVV7Yek86AUTQS0yIFnUN8sIR7vikvY7OfsJeAEk4OlLwRy648rJmiO5XxVj0czIiagzEZ5lx6mFYE5MbBLbr9Iro29yRQ5a6YVlez1wAoOUCXdYWqnBiZuagK6Tv1Y0m5n+wi3DXZEOk2Yneh3cRdq4Cms2WdTMaSTYwbI5gj+CwVnTaLUFRF22Hx0KjaQJHh1+ISZUcYL2R8rg/Jm0LwVyl2aLmoqq9VEZnJ85Azbufs4QHD42V+TnAkoLXdaBL2JqapUa4QYFtOnsuM4UEycO/EdRpbh+ZS+hU7D/c8lQLQ7OOQUgDDRZPtIEBSB0cWb8rIRc3whIZIagjbhL03QO3eG2Yxl/JeJYOXnU8axh1CwS0cE9RTxYyElKPBYAEoZkaRX5CbDah8TkOrddfKWJGYGZZmn+bWo9kMdVuAGPpu0o/bkJF4ql1KdzBPoFQKL5fg02uGgOaZQdLaHU7HdtsaxxPcitgqppKS7Ore1uoAgMBwY8xoTUr6Okd/IyPfHNHIBeeQ6nYQI2NlmCgfyyYTE7BGY4TfCWPxuyDG3754OPaydysxww0sqNUwmZtxMqgb4CkO0b1hFnv0kqAsuzuKP5n3rS8papNs9KZtU1UezaOQi/uk35M4Os2crDkmKjUkfcopySq+G0ochpUidPFZv7tzOZkM+2RgHRIzsfVOAWFqY6hrbiiRq9UGTcjDMeeQOJirQr0S275uw4qxalQeIH0aQ5FkkhpCaCsJRDxCABm8CkFEdD6QQm6WxlHUL6BSteB9YVQ5jsRIczEK+EulTu3bGOFilMWtTHC7kzHq852oIWTnydQN8Vd9UUNIigy5fqwSz+QSg9kYLUWGuJXU/o0rDFAxIRlk5knU44ka4q968ZLY8oUxSYEKyjJYD7rc7KkhNwkePBk4T3SiEx1F91eyoITOmfvJZH8il3ZTzYkJZHfpUTYLW4XMIjgjS+o0oHBtfwObxWJiE1GyRqc8ICqGOmsAgzGOWojzwr8dm4VFcDonu6kvkgcigMYEy41JBHcMNvtSBqbd1GaR3NrWZgFXZwLTucuu8chwKm2kYDAgCXZOgFnZLnRbm8WDRYF7exJ7SVNcveC0sxuodbQBa5ERlskFbWwpPJR3wZ/N2yzG80bUoGwX4dL/aGwWRGiAd99mMc3uDY6Il1cAgHh5CQBwFxdiU/AebLwPauAk76UAUCL3+BHAkq9SU+HZxDW5vKCmVGtbUVsUtfjisoiaJpM4vfeoZjAhSsTq1aYWiYeZsnKpqlT+XUONx5BxG/zshZy6XOR6qzb6Fv0A6lrww4u6bWUyU0aUslVnXXnbiyHYMEAAoAfnuS9k+k0wC6MvbdIY9kRa0urucwlcurZWpQBEvScgTCehP7n1xRaic28jVE1uVLYve4r9IJuZLkJiK3oxJrafleze3LXw3klpQADhgwcpNoQRzlu4rd5bxumGkr+CWy/I0PAg2W6SesIk9pIxFhPVjLlAsSGuDyAG3CB9cJfbWZvb+LX0vOPKIH8j3BBzP4HEiKNhHooCBePqRy/QvggVfDz+/jvGLG5MuoDsd1tSEEg6Nde7jiau4SBh5jBGy7YtGH4gLexJwlWf0KKN3y/+O8ltyYsVyI21cdK5Ars2gCiiYb/ob0rJr6UKqU2VyLR8Yde+NAQeAGiX7h+5gK9yweXa5agUUZT0AAAgAElEQVSJUeLjFaDJVYxBMSMrAcSuEZ0cE+ZkEJlT4kVX0KKpL/GsLeHw2u2c8TsZQxNMnMYB8cy4TpHsQ+b+YeHrIsFADv92fRAw27YYzPlsIYFX6RnGRSMLKSRLpC405wXUtOjgdhr4lqSjXUT/wRLN1kpd4okIK5lrN8QSQKYAPX3NBq4C91oN/Z/QeN4gekKzDdl4OTzsMK5cAZWl9qvgMN38GsogNAvxtpD86+j+Mou5FGl5IRsDln6fnC/qiS9qihxE2bImGAjN0GwW8x5Owom6kBGfQJEKdhOvjRoxbYCRQVhOUZWWiWh/KEW05mS2pl32VCJktX0TewJAXHNdU6sLdq4igxd1f5ionBuNMc4V22hM6EUKpp4nIEym8dXLn8k7sBZw8ubZJeY2jT9xiYnE1sliC4URTmNDyvw6hEk7yoy4cQirBt7XC4tbX5LwNoThrIHvI0Ln0JpxhNaBYllc43lSG4aAsHLwfemv5I4IeVHGxmeEpiI49ZObxJjUO9+4WWYhqjYQfYEUsEtI0F15xxSlqZRjQyDntlfAuLIG7L1bHaSTgfNEJzrRUXR/JYs5rIS1B6i4q9+HOgU9jyG5DE1bpn5eTrme08AjBYWJhKAuUf0OJCYcJB9kVgHGIDrvONGnt7s9NYGGsQDKhrHUsBhDDo7KBsjNNqXnj3V+zBAlO9emr3cgkpwcFZAt5a5EjKBkLMsSzTSwLM2vu9pWNgsAmKa0c1sJnb+JzULnTscOAM7YeEglogkmw++QXK8R/vk2TXGxWbgZm0VFyWZBY4Rbu1IxHQJggrFZ+Ms253zwnS/4Bma4ZDDMgWTbUdSaIWD5yU4C/4AiTY4R/kqNw3Yua9tSxmRon652s+9+u2iQAx01oG87otn4ymbRPp+oITlyFXB9i2Yb0F6ZZzbFY7yE7i+zmKoVVPIDVGHnNhTdiGPUeHCkZLhUw1qJUM1FhrTNs5UspBx6vinftdG2KV4O/W3bIz46l8XuXEnTd00IuYaPA7KA45lkNqdk2MVqKfdtGmFEWoQoBFDXIa666qWQgC8TqAbBasRVC7ctPn+37cFmkWpovHueQtTPl4WJKbYqqSEwaojbjHtqCA0BtKb96FcAfLYsWJY07vBgkW0MsfPZgh87B9fbyNIItx0Rk8fgZWrIlFQNcWNEWDXoTLLbeNaBWw+f5mZ8sMC48nBDxO69BotnaZNIAWBu4KwejWceYeXQfTmif9yge5ZSBRo1ZFyVuTmkhrihVkOWNuLWUP+oE0PtUHKesAO273ksn5YxvUwNufy6x/kTh8GoIYdyZczR/WIWM4s6/5TqgeZU9tdJFn0vOrnd5XZlV+GJy/BYyYKuNsIU1EYxjsIoIgMxZC8LJdCSpdcpWbjLbW2gBPYS49AYQOtUjs8k+LFZnvW+GhPj0nXV3N+RZNEYCcJKCKzI0dRfLd/g+6Y693VLFu2XDZpLsRm0l76GqSuz9LrIA/jSwb/Ywu0Wdy5ZLFphpupaBRIk/AaSRbNp4HcBnXlm7ishWbwustiKhGa8dVYtYD6js2bU8vuG1rsizbSU/5/J4sUpA9fe6+BdeSF1sdljb4qoXtzZ4+Ip4zI0zgfTWrZ33Cf2DuQNbN3VuB9OmA3/pjOimyC5m1L0JCF+t3xF7xWzoEWqZRkCeJJun0yRofjZ51UkKWv8hYUyuyQ6K0QWyAWAMIachdtKKNYVx+NYAFbmXmTco3KfBL/e7uReCf/Anz3FLLRamYlCsQHkmqwwtpQ0LiKq8B8cAiipIlX2MBuLYu0W01oRU5uF5pN4eC6/PX1+bQwMeQeeqePBgEhqc1D9JOnJPdOuaiqzswYOMoMG4xHQz0UH+iJlTrdQ7mkk7JSMbYa8B28NxNx7md+MtWkEFs5SmyPX51A7QYhZ6nKJEceHK7Qff2nAZUmymJYvnMS17EUe6+duvnyhenHCxSJLJe13vyz5SvQ2mrN0Zk78Bw8k+M+WL7xB3ZOTN+REJzrRUXQ/JAtKdUOurvIh//AhtKIWAHDKETl+9EdofugbJRq1TbU8urbkw9CdoB+qUPT4yafllt/8YfmSpA5edUBErrPgn17mMHOX7BO8aEUCMXVDaLsTY6bqhp89lX7+uz8i+uUElBUWKbpwOyImjIPbDgjJ0Ng+EQRnfHQG2gyIKQdlTNe5F1vEB0uBsWspPY3mbFxuEwDceshBTApocuuUg1IDjdRY+ET6vf7TP5aNi3WFc2QjXFi4nFNS54uSkc5vRqkpMqHxQQE06VjYEfy6hHbrMYqcpRCtCt58fonLb/2IHPNyL8E9mHssHfxOd3DkMYRWslKBgO6Z1lqRHJbsCYunMo+hcwl+LeOagpsEAGVAWQCWn6zx8c/9INorzu2yI7jA2ZDoeyC26TfNukZIyE2xG4wLOffs8wCaicodzxzGBeHs0xFNgqd/9y/8IMYzKvfWdq2woILsgtBech6bnjt85/iCRfeDWdyUKlTmjAvQUVFLrHpiz9krBaDoTgMY4lps1uvIGUDVGEQMzO0l63tvxFhVIRDhd+mBjhEOSfxN4dNViQPNszimNP4miS4FBnbDXpEhYl+JipJ/U9Qk2qR20zVZ5E+rTWuhNptxz52WjaPaeI/sRszQY+YcBl6F3qf7uD6WPJW9ZNt2gUsiHNXDVUWyyX1HEf8LgyoivI2QbUMqoqPMTee2N4tEeQkzmk2UlHepX806lBT9VLsVNcW+MtKc43MIaC8Z7VoZqzAwN3CVYxPbei4tw3OhnOt6zvcvGH2gvQzwO5Lnk/rQvZBxNRuzYaQiQyUmJE3vVlIMupErBCfdwBT0bjKLu6JpqLv1+1uaOzalORSjNssvOWe6MA+2MeNimx4z/++hKqe6slKcHKt064k7m825c6ovTRjA5NpKt572a+7/qc2DUdlNcqLaaTd0TNOEk7E+RpHBKKHdZA2+yb6ZpS3Y68pxqI0pct7hictuny09RJUEUN4JJLfbZAyBZdihwMNdKPfO+TRUskiSS1R0fwowc4GrurhfiYS9Ih28ZCT2RdQoU2tZP/Y+FpLtXUnHRtJmlaTmppbvQ8FdQJVzgSlFCdpxAbKrmpwEuY9Ed5sAx0LUqRyLGrlKEI9FKMeIuCSU8QUHMUda8+PGY5h4mhQCjbxQ0kL3MIlwAb/jVF+DquOAPIfsxrxl6WWpG2L+92mlZolSNiHLHLKUQ5P3Q4WyhnIGrNhSSeZj70sioUjtkfq4zfgtx6yocjs6GThPdKITHUX3V7J4Gc2pAHs5Ilz9B9SSgbq1VNfrmiqnZP5t2q5zdeCXTbev903n8UQ2j10DOAIT4DexLvDrHdjlVLeIXQO/7iVvBJeyAYQgQV2Ny/YGO4YKUamZmPqx2BY0mEvxBF0NdOKGADWwpVND61IfpcOhS4FTrujuHGW3zuUTUEv9e9m38hjSeNu6XzmQLMGu2TtEzQWRUuy7gSuEYvRkqoGVuY2NqGGhIzTr0h/J1UmlqHXnMJ753K5dHNNAt/FM5rn50kthn4QeDi0hdAQ3EoJmXHBieCWHbMhUg+e0yFB7ZaQ6W8C4ddKn1pVyJw1hXJEYddX4vASajbnOBPEO5w5YM4YzysduUgrglZgFEf0BgBcQxMzIzN8iovcB/F0APwbgDwD8PDM/fZX77NGc8THpirlvqaxhLm84IZsTAEgPpnF1MhclNYwyixpgo0fT/xmZmfoTFl7iGib9Vm+I60Ou5uV3QWpyWBuAPkRPMrvaryBGw7hoilioi7P1OYkKIMY3bgU3kD0v1t/PJglvYhbjylcVwXWuohH3Y0egQECCNpcOR7iBgGkVdpRFL98TY2od/Dbk7wBK0hZdwAsJD3eNR1hqhCpl46Z+B8Qb4sKUUVH2hljGAgLCUha26vCh89JGk4yA9hVoBQzlt5Tvpf0eHhB8r32TvzEQ+ouk3kTkOiaxK+0BwvDcaH5vzX2NQWG4cAgdwe88fJqb4UL+XF/SB4xnBKZiu8nRrcmWwQ4Yzo3N53hnyGtRQ/4cM/8UM38r/f/LAH6bmX8CwG+n/18/TcK/X0t7c//bUPMb3m/KtacW6pceP3R/95rHPUNME6ngZbcj85eNs1R/1/NeJ1V6vs7Pft9tP3nv79We57T9ym6R+jP9Y5fqk0774OTPvguc4qGYyvmH7qHnTa+t+nfdGK6hu1BDvg3gZ9P3XwPwfwD4L17rHaZW9FSi0EZcckISskUU2rJ3O1P13DnBHxCVxC+A/G8NnIDEdJAJlhpGuPW2BEkl1KffjiWrUpIK/Cbm3ZUil+8M2WGN2uO2gxgBhyAWcNuvGCU6cuo6HWN1Hm0H+X8McGqZ1wzo6jrVPiaMSrMu2aC06ncO9lLDZZIc/BArKz5F6Wc2cBoXqN+G7M1wqaaG34VrXad+F8R1uhsKxsGoNG4o331fVBNb6culEn72XDeyjJVdqQa2G0WEP+A6ZU/ZdaqivtsOWH7B6C7TPJJUIhM3ZelDlphUlWuTi9OJV4Mvk/t2GwFGDlwD5Pvimbh528viOl08byUz164YT9sr5HYrCa0B2nVynV6WeXiTrlMG8A+IiAH8T8z8KwA+ZObvpt8/BvDhK95jn6wrznhD9ooUhVg+gcpmkdUIBWU1EoSVobATcT1T4+XaHAgURA3J6f6TOLpoBEeR4wrkRVLVw/WhqAa70eRrVPVKPDHcSA7RrDZtJG4BqzKWg6CsVMSGiMAJ9FXsCRNQVqWGUD6XzY6da140gvUIzleYB2KC280Lq6KWyRxpghr25vW7BpTlrooaUnZJUSGqosBbWSgxB2yJjUWxBzo2dkBYOYwLKTYsfbw5KKtpPfoLApmK5WIHKeJ+syGEBUCRstgfvfxPydajLs5m6zJzySYpRxguBJTld4wmGZX6C8JwQRmzASSGHSmBvortJizlOVIsapd6U46lV2UWP8PMHxHR9wP4h0T0/9kfmZkTI9kjIvolAL8EAEucvWI3TnSiE901vRKzYOaP0ucTIvoNAH8GwCdE9HVm/i4RfR3AkwPX/gqAXwGAh+6DmzmAmUt+THPM1rDI6scBBGclwnstrsuAGsGIUiRmLBIJkaAhaSjHDiE4t0Mp2EsKjCpFZIhFogCSB2GMSUzVrSfm5CoASsBP40WF2QxVSUNAPB3OGnn7IRVPinDJC5ARnOYa6ba0316OFRjJ5jtQicD1ktfSb0I2VmpWaQoxSzesNU8ii1ShpfmGpIash5KDcxpJqbt6Ku9HY0CzKQhO0d85FR2WU9tUfDgsXH6zKQLtVRBJYlE8Ks0Q0VyGIslAUJKxK9m9bU4NbiR9nR7L4x4CuhdGDXGEcQm06wg3qgeK0WxF3VAJIiwIblBPDdDoNPSlHQv06p6NaBtCczlktXDxTAyZVg2hiFy1nQKKFLEGmk2EHzgbU4GCNzmGbs0siOgcgGPmF+n7zwH4bwD8JoBfBPA30uffu90NHIgmCXeVGl8WitYdbXzJVgVI7osQ86eeq8TLJJb3o0QPrlogMOJZSgbzTA2Krs5K3TbgRVeS2MSIeLbMeSGUiYVVW4rEZIivyy+Z34aSln6MGB61oJHhn4sLJS7brKpYz4kbI6LmNtgV5ghASgcab0hDlF2nMY3XbWvbgLpO/XP5HB40JcdB0rEFZCTivIynPIrxXO0YCVZt9XxNTONI1BtNHLP04tFp6KA3RJlIXHi4XYDbthgu0tyml50ii/ci3VMWoLhI1evgerkPsYjt559Iu6FzGM89to8cmrW0O648xpXLkGhlToD1hqQxJDXQX7W4+gaBv5uS3zTAeE6IXxL6B6qqCpqTgvQRAMYLwO2QF7UuWgqc3L2EUVXahhC6RqqyM7K3avu+w/rrjOXnVBITtUCzpow4jSk0SiDoHu0VV96QeAMO8CqSxYcAfiMZFRsAf5uZ/z4R/Q6AXyeivwrg3wD4+Vu1/pKKZDaL9kHY8rXt8+z3DEFWqLSFUN/0HpqVS2/jGAX3b+4ZyyKrsmNrCDYXOC/FOJ8Q93WS9jsJW9mMMphFmUr22TqbACZ9LZWxiIFS6hCCarwpabvmcy55iwsAJbd1/p1ZDJymD2DADyVtfoUFuQG5oe4TjaWv+RjvX6OfaqMARDIQKLyBi5t6IxVxMtry5P7MYNZ5p3zuq9KtmQUz/ysA//7M8c8B/PmbtDVbRT2lk3MXUhk9mIhRjKFICSkPBe168CM5l/oB8clnsnP2JVclG7Hdv9jozSX6MWVL0uLKfL6SlPdcSgqCSOp6aO4FiKhNl1dZesnVyJ+8KMbXdK6XCcpt5X55D/98B4oR4SJV0w5R7j+EDBgDRHpw2xHuky+y6qDkXJ2MhcdRCuzEmKudz10DIEf1rv7ti9qhblU7A/jSrE1ZekgxC3FZpJvsyesj2me74ulJ6lfzyZd78R6Z7PEoz/H8O4vyHHQNNK4qsBMbBylOXDw3bjukRECE4WEqDzkyFk8HLL5ElmKWHz9LWdpigforTfNPaL2Vqw0+/MdN9lDAkaQF3BUvmhYnst4Jbl1K1ycq8PBQM6an4afUfIAYU5d/+Fza64e8oX1tfA/DWQM38Uq5lBnN3g+MXDHelov411fHu0NOcO8TnehER9G7A/e2O0/bFINi46W+RlMPhZaLUgdkMJiKRLzSrFxJh30geRR199RaG9z6UvS2cXDLhdxL64ZstsBqKZ9A3o3iozMJKzfsOHaNqCBEgqMwGZ/UpqC7Rv94geZyQOikEA95tTlI4lp6/GDPwCnIUgP3Xu/EtpIg6QBmrwGQ53P8YLUXwBc7XxXZDUsHv42VLQWQXZwNfNoWaua2SAA5+Cw8LHOr/Vb8hx5PUpV7vkb/viQ1jq0AjtwQKxi2BlVZcj3DjTJ3YrtIY2tJDKEQwyYAuK89wHjW5nE161ILJibXuubqGJNta/Gxw/MfWWLxIuR7hJbQbiLGRbHxNCnPRugK7kHVBzcC6++Tc88+jUZqSp9EoB94IDiL50Puw9XXF9g+Jiyec1YzxiWh3ZTnZ+07vm/RriOGszJnX82KZDZcOJicCUrMFfQbw3iwwjmAKhUZGg+3TmnxRvXPk7wwm6G6lybRJa0NOgxyD030qwCpjSk6lMQ+vzYp0xTwhcSEeknKG5PBsbkcwK0rJfSGIpIisiTYnYLThrFOMzeM8heiAY3tXwMgq4D+qi6WlPsG1PD0tlT5BuRlFGAWoX8oC6nZhOT35yr5rYsAHOAud3kOqn4DmbHTNiUt3vVorlJfTXUvN5aFImH74qlQY6wbGe2LQfrrKcd0uD6iGWUcai/yL3biZbI5TrTPqVSBHnOaeGizw/JpKCoDAWHp0WwC/LbYS8SWwdm7FDqXmR0xZ/CAGi9DR3CJwcQOaJ/vRPVbDxnT0z1fAezhhzIH3WUsNVQDF0yKI3TPxfvUXpa5/mom7N0rTVhyHuaMWroQYiyJdecS7AJ1nVGtKsamlBxzLpir7RKR5G1s28JAYsylBvM5ECt+ftlyYhKXa3rSUPR9GsTrQc7lXSN0UmtTFkRx39JO9G9bDlCpqpQG5Izf5GJdCW16DZAD68KyKS47nTb12qiTpBVX715wGMlL2Wr2q5iYGwPcuSyx5OLAZyUrdgV7jijgMX3pd0OOq7HZuZR5AkBoveRroLIIKDKGi+LhsQbZsHQVgjGedaW9aUJkEulHGWdOZbBtU4UvlYxEwhlXPge8Va5ok8Y/LHzOlqXBXW6kZHdAlkrdyBgvOsSG0DGAQX4Yzl32ruizCQvb72IvExBYI+5UGyv5lShfOKWpZDE9bg13umtP0+hbsosm4SfAXGbEIjntoghBHBr6ewjisp1IL7QLFVoSAIiDBIVRwg6YfmkKPnVl2noXlArtal8pRNCu35MSKLr62DDmY/lec9cA2UDrt5P6rCYmRl8sl3ZwZxgeUgKW2LoKBUshLXxbBySK8c+tj5AsUhV1jGNGgGo+DNkMyrNR16zGXwBi9HRDzNcoDJwCZ9eo1jp1617GMyNZsCdgZyD8yuj7Ae1lRKMu4GRcdX0E96VvlOqnKqOLrUuJaOQ+XYJg+51gUNgjSzzsCM1lL+duimTRXkZQlHwdFTJXJQr1vCVqr0bQEKv6KjRROV9G94ZZ7OEpmIUR5Epfk11sGnXqXIl7sBLFIcnCgJ8AiKRhoNkYxmJusDiNG0gWmCR/OShZjDHZBZC9HuRbUT2ck3Z0Ue7k2J1KFtMXyNSeAJAh2JEK3DtnreKCkUgH5GtXxH21M7w2ySJR9AnIZEPUU9EiZWbFlSr6PHsq/bqlZDFclKRJILFbuIaulSyyzWKgbFvw22RXCVQB4mYliwuH4cyhaYubdQ6mLnMjfXsVyeLkDTnRiU50FN0byeJasmrIOBYJIETxw48jSDN5E2V8BcdYJAvTBml9BiLZfSc4i0y2/gMz0A9iDNSdMEQxoCrOIomI7sW2nKPWf6TzdDdWq3XjRd2IsSSj2Y6y6+2SgVUNhESgfgS9uNrDTFBKzKPEoxg82dTXmL0GxcDZPt3Uu7yqIRZnkSQwm1RHpQH2lOHe6tkhBvxlX3AWSTz3XzwvALADOAsyOIs2oVutwTk2JdmOGvbYuxpnsRZjMRwVDMgYJcN653MUrXt6eSucxdmTvsZZtAlnYSQySjiUyjs0JIkyMPwutTdykU6SfYUbQvfkcg9ncfZkkau+W9CVC7EECmYVmOEv+z2cBc3kHjlE95dZKKBJyX7v2qIaNB4YpKZpJmZQ15WSh6rKmIdfuU6JwCriqmqwHUTcBkr90oUHdW2lhnDfy70SGEv1yfhgaWJDZhZfLKX/KDJiK+5JDdmOyybBrVPRGDVw9iPCWQd6cH69GrLt8/XXqiHJmzO8t6oT1RLlWJaSzSp9jE0Rx3OYPO8ZPplZ7h/Uuu+ljfHh0WoIPQeGR4t8TCl6Kslqk56fIeppbumiRAkruYEQOif1SlN5APfexY3VEA9xYbZXai+Rhe53jUR6oiA0LUhqGqKuGbQ0xqRmFkD//Reihjzrs2ds/eEC/UUqc6BaeUriq89M1bHYAMsvZwyc//Idc51yjODdDtRqHrIITgWCw7PnAAD/4IF4PbpOqn+pfaJrZbcHwF+UhFzug/elbmnbAlp/9GxVpAvd9ZKEwcuFMJnkOsWTz+EW0h9O57hFB354Ae7a8jJuesRVB3e5lRdCCy6neqiknhqgCiF3u5DDzN1myC+R++QLaffxA9B6K7aJXQ9OfaEXV6AH5xi/dlFV+dZ7ql4PAH67yOhBxXH4qwN1QxIziguf4zUk+zWDksFQd2Abbm6JIsM/2xbbkaH46EykJCAXl959eFZiQ2ySHDbMIi3aZtVm4yQ7ypnFLYx6XLpstMwLnSUFXrMWz9Lyk3W54PESLjDa5zInmx9YCRYjxcRYzwl7WeDtuixmENCtGgwrKukKVXogZDyD33HGV1QLlQjNjqsw++YqZIOrpRc/vEBoCYtHTa6N0l8QxrM6S7iEwtt7pONLYPeozQxK51q9KcfQvWAWNyYbSWrrg1gR+2XxHM4krxkVxzBmK7hcFksAGquKEfM1xOXlEEt3+swqxlDaTGTrelQ7/DDmoLCsJiR8BNnP9DsNY12XBJAd3NQlAUTURuNS7Yx0bgKKESA7uLkeAPx6LEV+dTp9UUXyFO7qXB1yvvRtWlgZAGg3lIRDiZpNU1n8S+PIUghRMloy7+WS2IuZYM5Rm+WYRHK6XgBjds78ZsxqHSCeCAqy+GJr3KysUaiccRDUumykXDyPVdCZ1u7ItUAGiTq1fddnZM8D1Bu1N31orxi+4ZwcB5D7utFlqQZIEokN5lMtcUsYV1I75LZ1Q04GzhOd6ERH0bspWbwOmpM4jGTxqnRtESALADvUn5fRS86fTTc0PX8q6SZDIoW4/9v0+mwwntwsvqRfceZ7df6BeTeBd9mWoqaTSVGoOTSiFLLWdup7iA3Bjmfy/NUOk0wCUqzI9k3bKWqPqEipoI8Cw5hzSUIdOlFSBRWHwqXNuahiKRBE1f0pyH2dta04JGDaxEYzigHj0BiOoXeHWVxXdGiO1JioqoGmYXsVhjC9lpKvHqjS4L8RsjD0mTGxpsZPcQ2ZXFKSuYjxgk59PYzyRmTHkIyZ0UsuEyCpGnh9TPylZFShoBnMgcQUsbewbNGiOycqn7cNpeemqD9Vm0fSu8MsLNlaILY2iNWfr3u59Fx1HabaHzmwipyJNdFziys0Iy3HAPa+eBUS5boehnnYuh5VndDo9ut3aACYd/K7ek5c+n5NXRIg1SZpHKgPhSnYxLjJbbzf73qqYusqm0VYpb4m11+e0j5IjtJZEBwBagRUvb2hvNVqFi40wtypV8+JSwl+kRMHZbeoqwPJqlT/2qdkd3BIhs4vTZh9SkbkNilxjScMZ07KBiQDJpA8HB2lPBVycDxzYAKatUC13aB9k/IE7VXICXJsP7SPMS1cPxSvDQC0L9zs/Gl9k8zAUlvDBcEP5T7DGQHrcn0wTsLQEXwLjKs0LsKNGMY7ySxsLZCqPog9SWuLGC6sD4GZs4tRYdDKJLKL0VHBIKhk4qR0IDduf0ee+OFzXQ/LLExdD40HAQQ+rcd9ZhZe7t824rlRJpaOXVeXBEiLNzGFqIxJfeyKndD/E2J2PGtK3RCdr9ZVad7C0oGirzJ/6TxRP85KV3HVwimaMI3V1ijRfmRko0miC6TFvkqLOmWMcg1VDGJcub1kPK7llK+EMC5dBXUezxspDZiYRVi6ajEHM7bYALygbKhU7wYA7B45ieVI58WGwORz3RBxZ6bxdKY9Jwl45drkOn3uZyHYw8ohdMCCKWfV2j0k7B5TTqQDSJJgdsA0cjV6MXBSkExe8iNymr9j6J1kFkfTXYquh9p+E+JyIlt1y/5f15bQHcQcPNTHW4q3r4Oqvht8wGtt+9hzc9YePYi9OcuLcdWZQs8AACAASURBVPJZ0eQ5VMduOj6VAsjoQwfuPVvzhczfTP+OoZM35EQnOtFR9E5KFrZwUFVMyOIsZiJTyYs+SAk2CyBHn7r1VjwUimcIAax4AY0oVUyGiT4UbEFItgujo65ncBamCBBth2zFpn5Ao/iOhDal9U6iRlMf8yY3jqBtD79d7EVF2iJGQLKgjzEFK2nfQwlKY5baJkBWS5qr63EWrm8yzsJvJziL7bCHEpX58BlnocmNm2VToNZjgShHYyj2V2NCdALtC82GPo+z8Fs3i7PQ4kDNJiUdStRcii1Gc1M06w6+FzsKnbtcnEgiV0UNU7XJ70o5xPNPwizOQksaarZt2/dDOIvmcpj1UHSXDaIHmk1pa/k0wu8mOIvLAziLhrALhO4F53qvALL6dAy9O8zCZvs+1sCZYiVyHVISr4UNu76xgTNFp2YDZ4iIqxa09qgzgSeD3sRmMc3EJee6fPxYA2f2cmjbjkqhpPwiRoRVI2hRpSbdK4qJP2jxIQUrUZkTlTv3DJxLmYN9A2caS5wRWIlKjI0R83MEakM5n2YuvAyIOzcCFFyOwrRxH1WmrIYwTmJ7bHzF1MAJSvkydc7VwDkwto8cVhq6Tsk4uEP2foxnDsOKsIyMcUm5eJE1cGb7h60upmM4YOBkX78zStHrM+YKySpAK2u3IbSGGVgDZ/+Y0GyKgfOm9O4wC47FSswxSxb5O8eDCM6cY4JMopxYJAMAshtGg5TkWKDhXF5cRDmeF1eMcNtR4i/MfWmMJUFPIuqNpDGG4sINsSTknSI4XSyf6XcK+mdequT1qMKzOcHKre8+RiCWuIcM207xGNLvend2My+v6wMQuP4tsIxrBq7Mgfcqw9FYMmsTk8RvpcBAtcNoNi4aYzaQ5mvM9YAwlCquJZ3LjkBDRLNGqRwHgIKH23E+5kYWOHcEuivTt8DwO/ldF32zjslNksoCDgozp1xGMUPPbR+TodP3SKkBucJZ0Difvd0PKY5kMMFhgdFeopammOTcfE467ID2BeB7k/Eb+IriLCzZkoS2TOFUsgj1YtWFyMwSU4KyiDhlyiq7XpFIWIvFJI8Lt02WCmhIhWsnxsF41oE2VD34KjYkIpcUdGvk2I1mKlm0jUSjZi+NVG3XuiJpQFC8RzSYiqx6GG8LpazT3CRviEohaa7GB10dGwKIO9Z6QxY+38OOmywTnRCv2iypaGzIcGE8LyQ7e2ikarq+xIHElevS+XpPjQ2xhsfh3FXqgJwsXg6NDWlMjtLxvE0xIHLNuHIpNiQNXyuQe2HA45mTmhwQLwN7GfP2sUOnXhmFhgc+IjZEcnNSQDY2+m0zGxuye+ARW2DxHLl/28cO41ntEZIap/U9AIkNiR3QP6RcaAlUvCXH0MnAeaITnegoul+SBRtpYfpTiLKzb3firL4ukGwcwWMAoS94ib4v4cdq4LSBZKZU4aFAMtr2YrdQUXoY4bYlV0MxmPYvLS9I/VCkjmHMlcKODSTzV/2eukCeCo4CxpgZY06YS8zgUCQqlfc1IrR50e/nOJgiO5mzGlL9FljGNRdItjGGz9S8YAo0tNsYUYmKVEPJULsb0V5qGoEk1ZkEuADghnk1pNlSTidnJZ/mSqJ9dezti07KF46xNpYyqvsAQIwC1W5fDFh+6esK70ld0OhQ26eM+KR5NcRv5nEqy6cB3CT1J6vHDYYdoTMGztDWakiOd7xMUbk7Rmys0X3vVgfpfjGL64huKAg5qtPqEZWcEreknBzHZBJnn156716p7RuTnY459Go2ZhaDLgdI7o4UKZvLIvq3LGSSqjrIhXcAtTngDc8rCfAsx35wpYbJQVFb2u4GqKZXIYOpsMCym1DogMZEJd+U3i1mcVNKoc17CXsPBYwd80JOw7I1ICwhIDPqkVLVMrtLWC8MUTFCHXtv2w317AAloMu2n39LqeF1N2bOjAJsDIQ52YwrBko7bXYs02Q+Su7AvOq5k+/sSBhZHhTnrFJzQXg5y5S5v42JiU1KBGMvUyY0Fzuj0swUhIX5oDR29fMUt6cwM+vC5RSDpFKEG3DQdcoeQCBYsBbPoKXYCwrTU53sh72xQaQ+WlSmdZ2SIjZt8zd47b7azOIQInG6iJWOjTpVxvASuuuo0xxNaa+fjstGWk6PH7jfm4w6pWiyUkOZGXKWp3K/cj6Au4s61cvVC5Izx7OoQ3YK8hd17aZx3FXU6Qg41M/tplGnFAkuAMEy7q+iN4Rsmr1jcBZe0tRJhGW6bgwQH6E596Y4i2RP4YWC7gVn4dTeoe3dcSBZTvmnbafckza/osOIsGrhd8HAfkX1yJ6NFBTmdVxvMJAstq4kSddUeyxeCLUXMJHklBz83QeStYTxzMH1hN1Dh8WzNGWRC1ZCTVNnDsO5Q/fMv5lAsk4kBjcUz9tNA8l2jwWwJXVOEt1Asjh5Q050ohMdRfdKsqCFJtENxROh1LVSVf1rHyA+/bLs2Folve+rKulgzsZNLS2I9x8BQUBDnHJ7ZnVis0no0KRT9n2pWaI2j3GURLnGOwEA7vlGygl6B354LseePJ2vWG6yaWcpIkb45wlDkKqZYwwC/fZO5sKX6zAMcm3W3Y1OPrGR0BCAWHAUtBvEmKlw6iRRhEcruD6g/eiLPRXLT9S51vvkfeL6t8jAMMzujO5yne+pfW2DUSOcy/ksuHElrV6MEKSlR/edp3lceazTPB1T0mfAjM570NWmjEu9WskztvCENnlo2stWUtzpuBwlWL+0t0zG4+Fhh/d+95lBwIotimIsxZZQVIusHqidQcepc7OZhhKn68MjEDPGsxYhSSwPf+8ZLhZNrkoPINd0yf+bPiy/fob2asy1ZkGlXOIxdK+YhdKsGKt2gvFIX49xg2YdtB/q47fvYP3C5nvynrv0jVA0Lsz0Ytu+HZOQRyuivUki5tqYd8jmwbynGt1ln6b3ygWUZtaVm8ai3DGJSvaaPEM3nNP7wSyIQE2DuC6gdv/4McARHFL695ShO3zyBM03fzTvBrzsZLdYLkolcwBoGvB2J9XUE8Unn5XvP/njACTgCwDiRQdNvQ8A7SfPwMuUUVtriiw7YAyIj1d5h3BXW8TzZdHnnorEsv7TP4ZmM1YvGDeUczI065C/t5cjhgfyKFb/9gUAqWburwaEZQO/HTMCs326wfDeSrJwp5qiGavQOIxn5ZE2V6MY5saI8YGMpXmRxqIlApKNo/1Isop/8dPfQLOdGPhIPQHyb1hQxhCw4bvEQPdsLAvIGF13H3QZXTmuHLQ2RnsZq3bURZlRlCkB7fLjK3z+0z9QnUuxvv9wQWiuil1BThb0YrOWcaw+KziLzQce7IGzT+XYcO6kJmgysjpNPpHuOZwRustke0imj4uPevzBt99D9yKdGAE4MT4OF+k5bIBxmdpRk4kKGDuJqQnp97PvWsNoGcb2PYdxBVx8FHOG8e/+lfcwnDPaF8ZDcgjBecZonxGI2ypsvf8Xx2+c94NZHEMHPAeV68+KpNHEi/A+91fgkRZioTEe3NUqSPMYABMERmMAhZCBSNqC66Nkrrb9GrWWpSxgDT7KlnNr3Tc4AzBXNUgoMvw27EWHEtdipetTMaYxZgh3HnfyeuQXMs1jszUZsiXWTJhF+gSSxT3FZeTaoVEGv5e4Jc2p6zln8s5Gx4FL/VJTGZ2CicuIUm0cY9xjUOoKzAtljQJIUtt0FC+A7zXlfvF8NFtGbMs71GxjhnvrGPMwErNstjI32S3aB7RXECalU9nUwCjfS4kJYjFs6hiksrrMQ44ZGbjU/ciuE8nu7cb0fNI8NJfyY7OBefGkzWmuCzcQ2itUdUPETY2j6WTgPNGJTnQUvTuSxV0TkcCVp+xzDnfBXIOJZtTWKewYQMEHsP7V9o75rNzzbUgE7Nz5ts3J+ZYOqNo0bZeBaZCczSBlRd5Z24gCz6zd1e6cBl+Q+8nlf60+btvITfGk3bldkpMUxJOpJJXajNQYICXG0v1te6KWmGM20t0eV+klIqe/0z6AAXV4q0REKt1N5yH1Md/bVDXL0toIkQ5DmYeo40huaO2nG+VebmRECwa8gd3i3WUWJuqR1DNwC8MlKwQcAEzZO3YEdi5b4+WYu4lbOvdzDl7LriA4uUn3ZVRjYJsv07R3EFT2usgwAyt72ojJ2BIcF3GcFPREBgcx9WgZNQYE4AYiMIC9eWSHnLNz2r6K+45KmUD2JUJTQVISUfpqBsM8ntRHYa6l8hcF5MQ+mRyAoH2tcQ+MNNcaVPwyRLmT39nOgVEZqz6+It1fZuGofpnMA2XvZoOVKiKCgLXS51775pNSMdu+znY1va/eG0QZXMUpcc1elmy3H7YeWgFNyU4RqwfKnmqhoEt1NRUQZWNRCFIweBLgFds6IS18GhcbD8nMNYBxj1a2CfkSFlTVzRyXlI2gWf9lgg91DIVdhDaJbHUs36OeP7W9hM7Jd0/5hddwbz/U1bViI0yssq/EdI/IFUCJNZkMmTE4kkQ2g4CZrNSk7ebkN0u1sTjErizG2BLCooZ4h4bgdtJ+bHUMSapIkoG1ZeS582YeCZnhcU5+A4QlS9h8Nj4byQLI9wNL0psm0lcw+c1L4NSzIj5Qx4DMRK7WjdiVOt9ehmxPXJCVNALMW37y7lwMnMQFxCjtHDjf3GuPkmsvxzXY/k/zapi4h31VgrBnFEZZQNWpPOmr2cVyoh2Y3SurDQfGYJnRdFN3KIZV/Z/q6w4l9WWfRHKY3xIzoFiuA5CNmNZ7EBszJqp3Y2Uqtk6oUjTHs5RBhQFQhOSN4OJF0Xu7gD0JDgwQjPoFRmgooz7zaY1hwjn2pJZEbAyKC/u/fzViQxyllbWvXLOjkiovqSDsHeg6BjFHRCYNPZXU9i5FbI4xtys1OGQRVA6WWdsB0gtAGQSTVQ1AjuWK2g6hkzT2WWJJQCRiFZVTs60XaWGY8d7YwLD0f2Y+UwZrYlT2+l1JPOWFy0V0SXZWCmWXd6OK20BcpkjWSah7reIlr8iUn+glbP6f4zlJ3A+dsRekvoeF7O4A4DdAdym5OuV4UpEGYbphUSDY2aOjNovKHgMgmGO2T67YDKTavLkG5XwKyDkvw1KyZUUPwCOn8y9V1gGfjul3HidtRiA2XL1XKq2wR/VeqgRT2Vem47iGTt6QE53oREfR/ZUsyMiMQG28dMk6pOdNQ7OZU4IaEpi0iuCmjagJcjU4atnAb8ba2MUsOr4p4oLGI3YNogZTbT3iqoHbpgCxJEWEhQP61IzuzJ2TAjlIQVjZVy/GsLxzQ1LB+V3INoeqGBChKiZkA7zC0gQv9Y0k14U534aZM+egsFZh3wvaE7XHJVUSx/Z9h8VTBvuCQYkt51wULmNCkOc+dqUYjlb7Cp7MPQoE2Yrl48qJEa/12U6gnznDdtrJY1vUgCyuO+TiOtHYLGIDjAu5v6oGsSX0DyQxb1jUu/i4UBuF/N8/KLaWcVWCs8JS/sZVsQ2wR8ZCKPgqLBlhCanaHoD+sdxs8RRZjcmYMAKGc5Himg1lCHdYAfG9AeHFIks8w4MINja6uDBukmQjGh4Wt9JLjacTur/MYkrWHmE8FJjq6PqZEr/mz0kbOT9lENE/xwFQaYtbL4l0FTDkxLCawVAAMAa4zZgzbmlMi9/FIvon8dv3sSo/pwCm7D0Yy+LzW4moFLAYCt4/vSh+F6qYgNymSWag6fpzZTKgKhVQUYod8TuuwEixLcZMXaSLpyz6uGEglERkFzhX8vLbkOfeDSXlvcK8/S7Cb2dyZ8CAy2KayyGYzFPpJAZi5OyipKQmjCtCOEuXD0D3HNlrokbOZiv5L4cLl9trNpwiQYHQy/95LkdhQJovI5eI3Am4zivqNQizbTY1YM2NMkfaVyapbhY66dfyU1XndPMCvFY/WwLtlcxhuzHlCDYe7lmbxw0A7XOHZi32DBqBqNBwElWnuUIGgOmcHUv3l1mECfJyitpUb4hm5R5NWj2N/+Ck188gOEuWbcmm7HQqEoQaIUgpPpOlm4aQs3hrRmjJsl0yWldu8lSzg5VBOIh3A4AfIoKThe03mvKuLGbXB6ml4QhuCIiUJJd+BI1qOje7BkRaqbwynLJOW1Slfk/moGxXiJP5TYNxxpiZM0V7sTW4kdFdxnwupftlpKZxncbO5XvFxoNIJKRcH0RD0hXBqVgC/R446/vF0Ay0V0Vfx0IRqLK4gGJHcSNj8aVk4pa5EqmkWXNhAF4ySWUvBdfMYlwU92ez0/Yjmk2RQnzPwAvpk/bXbyVhLxk3b7ORNl0vn8rjBRkrCzrDviMVwySbBU5AcykSW5aC1OaSsBfKnEIn0HIJHkOev6+mgbNywxkDp/fFwJkj+tLMv8x1aqL/uHFiTAwxi+WNc2DvBfSi6ovmjDjKdSoGUTAXA6dW3SYUjwZkIY3nycCZ1A2bJ4IbV+DQps5qVqvSmxI7X9Ue9VsZl7OQ9aowckmr57P0hGpHjA1lI2fOUJ28GN1lRH+uzI/hBiD6YjC26pu4DXUekPJPGoNeNixLH5V5xDYVA/aUvQvBGCTHlV0QlNU5Fff9FmgvBYjUP6CqxgY7qfsZn6VxJcOtG0RlaUqAan5umpXKuk77h4zmUtUxYDyXPuW6pl6SzrAxfg4XSHVIkuFzLPchTtdSMXYqkI1dUR3YAcOjCNf7LFlwA9A6gb6iccl6YDwTyWI8w63oZOA80YlOdBTdX8kCmFcf8m+168/CYOXADeQrExqdRWdmUIx1erwboCYznDtCRG7ocNQHavoeSvEaqzJQZGim6xLwVYvHd0FTCDez5PvMu1+b0sSxSBTl3CTkaGEgq9pYty6T4AhuSsY9qZ9uLMeV3MjAVu1EnF2hbigp6OS5kgS45WpgN3hn7P2Gop4Qi8HSQtErOHe+RvuEqoRgdtuGcg0dWAbEAA1Ut2/uSaYPt5nuKd1vZmFparOw0aZ2Qdvzj7FZBAYhir5PANnw6imTiKKjglkiT5FsFsOMzYJhEpvIIVlsEdAwbFZxmktdTWVaQ8wGRBvXQJY5ZhtNar8PNfgqRikpaKI4i81CGFk2eEbT1/zCSQd8SkqbDZSxMEP1cOTr2NiIo8kFyeYeCRBlGciezcIaRiOnMSAfk4Z0oebJyaK9a5QRIy/cZlMWHlmdXqckMJptMkgGVLktiYExFQ8CxEAq7UQxRGobPaOBRK4qpNxvgZgMmc7YpLUPNBbVIofnU7kXUgLgHEticCWK3sxzs4W8p0CyScnx4CRMnyJyrdObZvm+F8yCUj4LthXEnAciwz1+AACIn5ZcFDDwZQm1lj8+F18VjQH84kpqh5ArCXMsw9E6GjEmxGDKbqQArLOF5MUcAkh9c40D+kGu0ZIA/QBaUym0nO7lN2MuvVdQdA5Ocy4OAW7n8hg0nD2mvBXckBi2VNdXo54n0Mjwz7YlW5eOq/G5DCIA0HYQ1/EYSkFm7aciOHUcKZtY92ysw8yp2BV0HOoedUPMOrwyC32pgQQ8I4G2uz7mF/r/Z+/dQm1b0vOw76+qMeZlXfbe55zuc7pPS5HaVqLEMYmCcMAILAjkRkD4JUQvDomJYrCTlzzEyYsDxuCHXCAYjBViHD3Yxm9xEkNIRIIfjAkOCKsVISzolvu0zj6XfVmXeRljVNWfh///q2rMNffea+3d3axurYLFnGvMcalxq/ov3/99VqbfX4zlPrS6rXIdc10eM2g/YHE5L2dvS+Tb5W3q1CWus7T6/Nb8yDNJwu5yKvyk7GiWOeLg0DfLSqznesDJp+vCMZE9IQcJmvbXTdZBAV82KGRPhajXJWA8tZS69q0h/HUTo7+SVHt/MZXM2PppQNgQwq4OpOznA1KFj4sko4vza+ZH3Lrdi8HiaHM0S4veYM8qYraK3CQClGyXASBr2s4+gVnqtIrsaEDO0rGGMoRHOukQLnINZgZXUoxl+5RUCMhSBXIMN9V0ZSHbZQYmsSzagKhJGhKjkNywI4znHbptlJStZRIWQQK8R8R8mOeM4TRFcG6o/YGj27Sfh8xPuVPhHm6QmZoeFZEfA0RkgQcwMD5SEuBGSrDArdG8yPtYB4VDuYbU3LPEwhtiKd0GUt1maWyQE6SmHmQE+m1C6h3YA5NS0oVBz8lXiLwfks7sOlg0CFRWlXd34GJRzLMBR9CTdNM9y5ipvseFDFbWz5pp0su5qEQ7gq8QOjw3xHI/ZbBrXA1Y6lutq9gMjgR0m3RDmOmVpRNH2kOA86E9tId2q3Z/LQvgtcVkNTioMQT7BG7OUq/ZHpDZgT3JDFbsORawVVtfcVd6TbVWDt0R5Ln6OCu9HWWucVlyCLtUg69mCB0Rzf2+tgMLzqVcyqttpmUSwJVLuaRHbUbO3hWLogQTG9wGMDeT79LaYB1DYwtNwZWshNlsW1i5otTzBGfPjcZKJuAGu9cdm3FFAFCGLRT3AoBydxxcg9Rsmxi0bCwMUsFkc9vG4/2zmIvVucyWG8dFc83etf14WhbvyE9QWlvZCdyd9+CV6lx09H8+wJJIxSTd3M/36/yOtUPujGPtFeJNLZ1dWdacm/3J/3fvGlP9mx3zsA+v2HbWmljMMf6HO/fLzeMhh8eafT9yrLI91f1VV+v2nWuvz7Hr9S7tjYMFEf11IvqciL7VLHuPiP4PIvon+vlElxMR/fdE9LtE9I+J6F95657ZSDxNJfhW2iv4ODFO8veWqUU6sDZoMCQN3i5l+ar1b7BW1UyIG5P8Dc3flCRzwJYG/D5ME3ft8y2bixl+lD835cKxWfv/9vu/kQ4sP+B2LztJtsL+CqS8nYHftm+5WhevW+dVx/KDcGv6keEnQaHeul8/wLmjbbdxQ/4GgL8C4NeaZX8ewK8z818moj+v///nAP4tAD+jf/8qgL+qn+/cDJ3JADj4qioevFwr3yhoMwNdB84M0k8A80KylWQ4LBrPfZAgn6mjW1aBCJSNjNcBfQde9EXHgwDwelnv1yjh5XjWS7CwdTccFeUtv0+luMsPwvRNDHQXgsXlzoGGBO4dMGb5BOCvR3AXkB+ti/p3qavwVM4LANxW0a2JwXa+O93GwLEacHPXkk8b3u+bNK71e34vpCiMkfuKLC2R/SbrAaC4MNNJqHBvPZfx/RX8LpZrY+fQpnqNhZymiOGR5Rdt6pyTKaeFEvM2gwf1oi5m5d5lgCDCeOaQPWGhbsjw/rKWdjepYjkPIK2cqJijBiLdmLD90KFrMh/sAYq+FJf5UWppiCsCFAr9psTwoyiLAQCe50o7WNC2wOajBdKCsPpC3VMAm48cphNJn5Z7RQeDlu4i9cDiJc0Ie2X57UeaNw4WzPz3ieinDhb/EoBf1O//E4D/GzJY/BKAX2MJrf9DInpMRF9j5k9v3aNbtBnYpxkgakpN4gAiJXBQY2LbTXXGY+PfzFlISoDZAzkzA/XBZWOxSVnqU4qYsPrIGlk/bC2uwWZdZIafagp3dl7m91smwPo6TKDDQrLs4Jq+0iAiRUi52JB0qGti52E1D7ta2yEbNGatDSyTvEhuqvKBhn1psx6zouEp1wI10oKtXazFcJbdIh2ksr2Ums1JqWHnqv6/1UsAmibNZtJbDIDrdkSzIrSw5xkfhmUc7Jloa1ssO+JtwLPJYkrorrnUnBiblp+aAjcdSIswMRTmbdiIWCn4XJPZbuMg/XVCHghhl8oz1F0xAEmdtoREhd2b60AflNfjMHX6w2D3/rAZAJ4C+FC/fwzgu816n+iyh/bQHtqPeHvnbAgzM9ENL/KNjYh+BcCvAMCSTu52TEelzJaDBw3AIVkveQeOrnze2EdntpjiIYIDwyErbsDtoyyLAKGiC+GdiBYbTmKKgu+wGduKwxa+YBYqxVtl4nIxIzUVqHEpbojNtNk7OM3ZU061jH0UV4YXLTmDfnoqoC4AItasRMZlfVv3wA0xNy+u3Bwz0OTpS+FbENciB18tMZZZ2wBXco72k563PiZpKYHONNa+3nRDGhxNynC+8lnMwFdNJaeJH7Gv5r7Q1lGTWdC+JUZcKufmYOceZm5IbuTGzQ3hAzeEO4/x0ZyKMHdAHgjxxPAbUvzmUp3Vc7C+iTWRlnVdylyQrHIswnjqkRYEN3B5acdzwnQmrkRBpirC08BxBUi3gLo9NKfduwOfxdtaFp8R0dcAQD8/1+XfA/ATzXrf0GU3GjP/KjP/PDP/fE/LV/TuFf7UsezAu2QI3hChL1H8Ox6jHSRwwNs5y3zo7zeOX17Uw/O9Uzfu1maZBsyCh/OIPZXPGaHsYTbkaHSeXp05eG3f9DqS9WHex8KdOVun9g2zdalmHd6xHX1uDpcdZiVo/nnjXJr+vjabQSjcoIfn+MY+3rG9rWXxdwH8+wD+sn7+z83yP0dEfxsS2Ly4TbyCc0YeBlDobAFYpQzTcxHDNTlD13Wg/VjkDCll8DCCiMC6LgNwH35FIOTLvsyatKhydNliAXuVQTxZSim3DdGfP4dfyyDGWykEcOsl8tkJ8rorA5nzHulsgaAPcuHr1DoCSrm68KGyb/shgb0iHbdTmXHCZy/1vM7hrgfk9QJuK58A4J9fAvEcw4drhJ3evlKeXOURASAsg/qwjOlU1u0va/8oc7FYOuWNyIFmloXR1YvPrpaBF+IaI1SxRszoL0axyg5aG8w0i2L71Q7d1oKWdRCRzEKdVSkxFq4OMK18YRsXyR3AI2p9BWR2ndaEbiNxgeWXtcM5dHBRIO4AcP2NvsoXtrUw+n9cAf2VWgbeBss10qJaBob+TD3XUnA21iyqlhiASMagVQOU3TbX2pemXXwzIC6B1AUEZWWLJ0BcMfqp7jd2mGWLCiP7mhHXdAPVmesr8cb2xsGCiP4WJJj5ARF9AuAvQAaJv0NEfxrA7wH4d3X1vwfg3wbwuwC2AP6D23floL0uxdZKErYyhUe2nwUZG0Zry3ZQS2xzKJp8KDdQKdJmQQAAIABJREFU1s2lloGYBXR1UMzmt/HGS0OMIiPY/kZTlRcsadQpAUlZuVIrVchwY4TfN/BnC8LmA/lCDUBSrmnCAurK4koUo8UBDNEeLYHXkg2hEjCTnQiTFx1kIyizZJfiwb3AQTBTW7f1JfPCvqlEJVQTPOl3InQbDS4aHeFhsC7jxotmLFVhl5H6eb1Hd+0Bh3K+bcAzd1TBUBpIdZPCxCEcE1YMt3jBBZrNRGDPWuFq96FyY+QSQIcyb9VAJgCETT4aGO8uGX4nfbT1Fy8YbiL0l3X93MmgXqw5vT9hS0grITAu9IIWDL1lu0025Jdf8dO/dmRdBvBnb3/4h/bQHtqPSru/cO9DP70VHWrZr+z7IZLPO1CUIiFqrQWzHg6KvIRvs1LxE3AjaArnJADnUFOGXgKOzlJ/hRyYXi8C5Amt8E9ZbojHzoOcsHLZJwCQKpnNRYzksxUxAiSIKsFIauIONfbCoMrIVfrfnEMJHM6vQ1w6sWLGXBmuoGXmVpR30NhRcwwq3bZ0bEtWLPuya0Zwo6xXgoNdXbf9njpCPgjY+ammM+NyXsAnpLgVK5K98HeaqnnrhqSeSuAQkPWYoKJCBN5aH2Tm7nJl9spNJWg9B9SdN0Az9nQ0klhEkWYaJeLehE29BiYkVK5P42akJWaK7XdFrt7fweL70ezFOBTjeZd2JLjaQprp8PcfUjtG3MJaUZtz87v1l6vJX7b/AZedHOtfS4Jj8QpuKPSkb5i5Oz+w1gQZjU4QAJArn8cMat5kXX5YTRjT327b3HENEL9F+/EeLIw963CQyLnO1LbMaeT8TTciZyC0T3JFG7asWmUGP2DvqrPqXD3sqGKY9mv2ad8PV08MBKoRce0PZYZLGcl4K5grQrCBE4sAMevspTtofWdLtQLzAabN8LzuxWmEkgoNwMG1NkCXFaUB8tK6bIFDzLY7rMfIoQrzlD65ZmY/zBB4HRAazodyurFl9pK/dv+GlHSJkXvMuC7ZEbLnma5q7vR8GtkCOVe1WFC3R7p5HdlDgphULZ7cyX7bkvOyXrs/+8yYWSZvzLQctB+twYLaJ/YWzbuZywGg/H+jRkFrP17H5AegwWdYnwRDwMqFQVODaDzC3tUiTo8iUZt1rV+zT/vOmL2oReGsGQCyF6Uz5BrwMl1XSlzMaACFl4Iy1yrMtkvt8dsBphkgXlu9mZrKyFKNitkLLJgSYcJujy3M1nMsgX22wcFjFHuUAcc3MyfWX0rVomrrTqZTKizY5n74qTl3FtLe1LvC0A3oIOIkuFmCrTz/vW2mrl4o+BKO1s8U5i2uA46bIExhh+xb7f+uLk9rBr2s17FMGLds93ewOOYy2JvcUuW19HlNm72s7W9FJkAfWM0O0CRFYwYDL+u2zVi1UMu1RZcjC1Qcdb9QKri2uSlXCyJxnbkTF3KbWTbEOEDtU38vBVkt7RsxaGRQM4MTs2iVNAMIbDDQojSjs2tf4MNyakuTln041fLQ/c+uecw3zrv8ptfTAFftwORHg0DPX56axp3rmQC48b93x7MhuRNa/bBvskF6fn6s2QdKQoHnEhfqOTu2n0itNFk3GJUeSwFYpQcUJm9KDBc1azPV2bywX6Xj2ZCWUvDwPIjk+JaMp8wIO5rR/9n/JW411hhJ2FA5R9kBbgygr2vfB0jKQ3toD+0PQru/lsVhoPAQL/GGbEjZ5lDJTD+5aIFohH7hgUE/8epsCKUE7kPJhpipWlwbi1kEJ5mBxqrJvUduKk0LJZ2nsrxkQ/oA2k9ifruqFUIaU2DXBFNZZujcu1nmwm+i4DJiRirXa+7ylNhNrhiGMvMbTV3vZjGLuJJsiEs8y0a4iV+dDfGuZp4aoWgu/jeV45d9QbIQNnNbhWTuxE1pNU4AYFoR/METbSCk1JNkMJpsCAdC6gldsMyYyBbyRDcwG5YlsthEXEp8yI88c1k4SFam21ZtEerqNbesD6sieh5qDML6dMzTzl7OO3sUSyL1DtMZwzdaKPFEsyMWdjKco6Jrc3egG/JjEbN4XebiFm7I0e2dK26IvRzFDRkUlDU06x9zQwBRxypuAyppcDO4iJLZfHs3puqzxlwlCRPDDQegrFGV1hLXT/1dfO25ucrgwshV+9v49+YTN4FCYXOyFSQYK3ySufwOvN4Nmckxvs4NSble6/JZ3RBJj0LrYep2fqgcGAaSaqs1D8uxX+WGlG1nfKSMkLmA2ygp6CnhlWAvcyPCTgctEhEj49zkKKAoN3FhAG/dkHLP6BVuSDzuhkjMg2cuhx8Z3RXNmLSI56AsitUN8YMIKLUu1l3ckHs1WFCvw2BKc6ZvQDIQMcKdLMH7fSncYmZgivLZbsMsHBdtmfFqIfBw70CXm3IsAHApSfm5zXrTCLYBKdqx5KWlOIGT+d1ZiWcTgAQopDw8u75JjusdnGYlaJjgNvo9Jri9nDsrH4a73ALDCAyTHF+5K3gcQZdAWHV1QGxqS1pbiBigJHqpJakyRLRZGp6kD7mXQrbl081NBOZBloM7rwjTeYATiUH74cZ5A5iRGjuFxC9azIdZS1ZEVWQDtJ+OsHq6K+sCmBHg2vU9Frsyot3cOYSXVWbMb8Vyc8rxsTwJQkScGGFwRYeVdACTQUAtsM4hd4J5efTtCWFfmcfZ0axQsI0ZlUyOFbrF+XmGy3a2qs0KEHOgYoU9+nZEXDmEbctCTjOKgRbTsvkooNvwLC39o8furTUVeVuHPP/+e8LDsJCaCN7LMJ0uLuF/5qdBg5wlL3rQdg9e9nCr1Xy/+wFYLuog8vmzMpBOf/SbAAC3nwAipJMOFGutRP/7PXi9EBPf6kdWPWiMyOu+uBD+co+8DPBa70DPLwAA1z//kzIjZ66VqJ6KynnYpvp9lzGdeoCBk+/K+Y7vLRE2EWnh4YdKlNNdDpgeLZADlYekpBl7N6sN6a4iOBAcUakN6a4PakP0Iey/K3U1z/74R1WAmDGneNMmlZoS8S8PnmYcFpcVhm7bEwPDIz8XWNY6kEMIt2EtikBwLzPn6ukOX/zcqaxTNDbmOIe0lId/Rn6jZC9ulIFl9eWq9G14REgdYfVM+pAWVKUCHeCnOvRmdVG6BnwFAOffnfDJL3boL/rSf/bSj0mLqc1qIq4pVOPhcJPKJSp4avV0ccMaZALiWiQZ15+KODIAfO9PBEyPE7qLrg5GCku3616kBzpG2ABucrUPBMT/C7duDwHOh/bQHtqt2v2wLF7VWoj34fICWiIcEusCKKb5q8rXS+zAmXnn4HKuvmpTlk4toa7iNArvhRMODIN7U9EzUROwAVvlvpqQpThLv6dOKw+pBvFYKy1npdRUA5xVIFn33znkhiaNPZVCsiqs3J5Lha0Xd6ABOpkVlnq6YVmYyngRKWYx0+WcUXbAFuvQAqv23NsAZb0ucx8+d1RQnTZLWqCznZHl+upM2oCN3ISyfVrWmZYtQNo3s68H0kokDXNPs9hB7lDAVoCsJ9sQ0orBVo3aA2khsZzcW7BbLAhG7W+Z3YPu20BdTkwCoyO0e1XK0D0KpJ0JoHVEvq7CyGmdgWtX7p/1AU4qT8OGENdtrOv27X4PFndp7wDrPopie1d48au6cEjTd3D8yv3QLDwy2L0STPOK5XenJzqy39teEjsH2/RdLuVd+n2kj6897yaWcON4bzpum5w7AKzd0BdtP2ff6WgfKgN6+2C8qr8HJ8zzWHRxZRiCFtXPt2k/moPFYRr1WLM05jG4N9obKi9vVZpqjuFq+hCA/J8zmLlZP8PFXLIrFXgk+xYuhJoOlO91xrDOUCt+DAVweRO95ZsPPddMQtEFdRluxq8oATmTRgQwU/WizHCuySppv2f6HE7Ej8W6kX17VfNqyWFJX1QRc8b8Wtr+yxNctz0EVh3GLESHw7I/dm3smDKDF7nEIKls9jdjKbZdsTjyzZfaJcBrCTilWmJe+1aXeY2/uMRVnNj6plyflhL1g/BNSFbFroEgLwWZWS1oUjh+9hVslT2V+2I6rHbNeXD6g96bnaS1C9hZ5TJ5wfB7zEBZTX3hrdr9HSzIoSThD1ubs3dO8AYzk//ABTnmhphZ7rTYKkgU3IKO9RgZ8LUyk+/ohjDQuAnVDXFTJXPJHSEunRC36n5zp/97kroKdTlycKqTieNuSIN7aN2Q4mbcwg0xM9dIX8xVSMWEJuTM6DZG6gIVu9HK0NKtKoxsFZN2DHNP3uiGhOqGWDDTTHlKwtHQ1krAaeXnQl40v6PCJTGeAZ26C5gkhZyWTR+8kNi4idX9eY0bsmzckNMMVlKh3AHxhOFGAltyz5neKhXcQ1xn0bo1gWo7h0AaCEV50XOo16y9P+yAcDYh73yVoewY/lqkGonagCojqfuYGmK6PxBuyIz239ph4dPr2kx7pI6ytS6izubFd3zbqtV2s8YNaesBDlNoZbuDnDsdszK+z222/9aIs7G7q3UYRV2M5+dTl1VLozXB39HJK/08xk5NGXDKq9laBy42/zd9rbUYb9crwzK0x7/tNhRpViNjadYi5qz7exX9X1acC80NxDnEH3hHX1DaQzbkoT20h3ardn8ti4PyTzoM+DWRYjpYBkBYv50rnwAOMhOqCG46pMEhIx8vs26RnJ6QFn5GYsOdq+Ak7WdcOnQpF1AQICZrXDqAJA9vcOAutWraZjZatsHDT7mY4AJEUgIaPV+zSnJHAsW2ru6dgHSSw3SibtNUwT0uNnBtvUbTaSVyMd3NHDDT58id/rY4EKkhicncqD5lwTAUmPLCiGPqjJi6anK72JCnrzRz4l0xn3MPWMl4IZEBMD4SRCM0awBItXdcSuFX7usESwRMJ+LGmEsa14S4VneqA1pLI3dCLFPu79r6QsAHA6a98rU6y4YA0xMxu9zGgzsGMoGXio1ZZIlX7j1ocEDQa9P7ivg0I9cB42NGXDP6K1csuPgk4oMnG3w5+HJitEiInSoaMQGdXGC/ioibTp7ddWNudbc3U+/vYPG6mAVQYhbFhDzIMhxCiw9bKyAjojJAaERzWr7OWY2IBjcNnXe0shUKU05ibxc3xtWKQIED15fd4MQWC2EvkfJDcWH2gtALuzyr+Czn1cCd/ZgRg9fqxDzbz6vEdsOmQpet5Y7KwCHnIS952PPMPPaH4EOqQVw/NkK/g1wXHmt/zQ+3MnBb7oN+Zy5oQ0uP+gEz27i7aglr7HroX8RM2IeJELYacNbT9XvWmIUcw4KYdjL9VJelRsiYL3oEjYWklQzmfksIL4P2l9G9kKBDXOuguMzqxpHQ87fBWwscN4Hi7pLgBoLf1+pbfxFw+WgJdxnqoPsI8FcVmJcttnIdQI7RXRKmGc/s7d2T+ztYOHq9n9XAhMle6LdIdzI1wUPvkI3eTVmmisI6xPqgO8BjSxDV7l0zmAmOQr6nhRMy2YQD68fVLERDA/hakpl3bc0LLudQ4zmF+o6EVs6PdZmQ58pvdVndbYsVYa8W4ZEaiNe1yslR95Ma66QEenuu+AuqL39cMdJCV52sr6+OB9y6X10GqLKU514HQ1NO03OfFYx1kkXhBYvMZpw/K7mrmZPc4XgkkhiLxYSpb3hYlJSjBIrtmnk+vo87tPs7WLyplayDLy8QHVaJvqbNOC3VSuBAxRwWajcHnxg3uCNv0wjlRhUoczP+5VCj+whiItPQZCcgVYUibVc5KnLnZgI0P5DWnKYNAKwvlp1HWgPdpoms7wkusK43D+DaPivXJdXZ8y36Va+hZD0smGlsULkH4iMbqQK6K9J1Dyj7iYol8C6NFgnsutI37jPY+dkgxP4geN1nYPLghRBbUIHhy8+trGLqj1htej1OFiOu+gwYdkKfOw4yGNVrNi/6e5v2EOB8aA/tod2q3V/L4sBEnaUtlT0KACglFc6ty4q5n/Ns3XafBdCUMmgCnAJfLI5QSsDbY2XJidOM2Qry3WbJRq+klF8XgVzAhnoXmzLiDLiRZuXhbuTCA9mWo7spFzapSvFmvzFcG7BS37+sjzq7GZy4xDjsGnEzAzLgSP1pEs0JORCQVRzZAD5+lKCeSwyYRGAT+6C+WkPCEkUFZAQ03JZqPtcydPufy0zrppoa9Dsq6dBEFRRlj7bf6XGi8DxYkZzsl+GHxkpzMoO7SWJVM8q+iQvmA0BDuccSpCwxB4LbeknTWno02Tk0xxqczPzwoETFOrJ1fcMI7sfiXczAXsiEi80KiI2cZ3YCVCPIp4HAgqSTKddj2T2+bbu/gwXnqkx+4zeuauDBS3m4/Vkz9bFXIDxLmfMuw8csJdqZETa6jynCb+VKW9Wpc24OZAKqbXZgo6VOagxE/9OClzXq70YuNPrdJlXSFztW7NBdTZhOg4gFmUbqdgKdBsS1rwHO5jK1LkuJtbim2nVflx0jWUlLlAfPRa5ukEcR0okroL/UYLsua/EB/fZmYHo4d2UgBgur96QKWbpITsUrTqkBaVkpeFttap+hVpwjLmtA08BXxFL92V0D/QXQX9WBcP/EIWxQArrDOaEAxbi6XXa9pvPGdbKXzAEUHdLKJhkZlNJCsiKA9CWeyMTDOphTJHDP8FsHN1R3zmpsWqU3NwK7D2Ufixe1rDydJoxjEKmH9h6ussRj+gbQcjqBY494mis4jlCyMLdp93ewAPDKQjKgDgKG3gTmWYvWqjgG9zbOBuWBIOW2LME9LxocSAxSDgr2BDdmIbExgtuocG/bn87QJfrfqHYJZ2W9gS2k2WDdLZNTQXESilXEnSBIwzYV4eWSQgVmrEluzJI6nXItZ1fLhYzsxlbWfYRtQzLD6kOrHGDlkUCBYedSj1MHjFTEn6v11LJuG8io29QsTVUZw9ESdRfzTL3sWAt72b6Fe1OUgcL6bMtFpYyLeDEg5eep46ZEve47ewHD1RJ1e+kZfuMQrmvMIPdicRla1g8G/6bK8t0KI0cC7Wx/ejkbXgoOhP5SrM+wrVmhcOERQyekvcXacIUdrBVGTlEyNpIWbt6HH71sCIsu6QHhDXUd8k7sXArzrha4d3DAcoG8XsBvmmnGObXlXAPXbi5MS7rihY7OjxnTmRKzaKXmjH1KMyQcHNJK+uO28t1tdfDwNSouuXIqD03SqlNJnVYLIC0cxlO5kYX7IhBcg90owULX9LvUgchnXHvBX2gLO0Jce4RtY2W0VhHkdwDoD/sN9XS8cDy0WQ6Lzi9eAuOZvuQTyyxPNaJfI/T6f5va1oHIcBqGObEqKGOZilbd2dUskM3CbhIIdxHwUUr+uGJRDYfM8v2FHOvqmxn9pXVGLui0boKKHTA+Jvi9HKN/WV8qC4zaIDE+1n595hCfROGUAJCWjOlRxuqpb+DxDDfII1do+Z5E0N7LzH46wX9maRq5TrkDHNtzg1INnLuG48kBZ1+5xvXuvMLqVxH0IoADA5HEytDrOj1mdC8dpsftM41bt3sxWBC5m8u6DhwT3PvvAQDys+f1x1wzFJQYNIxwzMjvncmyKYFeXIKnSTgzJyWvmWouz+/MSZab31+MYCJYRW8+XyGe9gjXI6gz3L9D9+UlaD/BG85jN6CfEmgnTqyR9PQXsZiqRfRYZ6Uy2w41O3DymcQ9pnN5wogZce2Lr1xm2qXcsuVn2zkTOYDw0s8GA7efEF56UEoIprR2ZBsAIB1oV1+mGRV9AW3xXJksdUC35eLWuFRn5EmBYcGpxTOK1mrx90cAJCLFpj06UwoDCj6Gle0svNwV4prWjO6uaszCitNaoWI/MPorSev2lw0Og2RAWj7jMticfz4hfeYKA1eLY8mqkVK4QT+T/i4/3+H8t87QX5jVI4N2dyUuA6CuCzfpZQBx1cEPjLRwcMk3KV2zPKjiPJhw+jQhdYTFy1jWGR4vsL9+gvXQxniclO4HcfFymSiB/kIs21ZF7otmfn1Te8iGPLSH9tBu1e6FZXG0taS8x36z6H1M9f+2vPy2Lctsy50Xl8PMMma4MYn5b+Xod0lTc5OlMD+0IbyRwKF8D5NohkrUXvveUYlJiM6HLKaYxV35QTa7fCQ+tGAE2llP4wNttoNrtsKUxguC1apeLemQeOaS3La13AwA4DKAqbk2JCa8EN40157ts8aLTJUt7IE74z0OmovzvhWtk6LN23xvtgFqFqlgU7Rfwmiu6wyveJ5ZXDHfWBaFrk/Puwo7vds5Avd5sDhs7cMVPMgIUs2kcq4R4slA10k2xT51HWtmzvu93LW88EATxDNiWybA6cDEzoP7Drxe1PVSRl73FT6uZt/4KEjwrmXgDg5pSQo1Tkhmrl8nxBPh4Fy8EPcoLRxCFJ7OsMsli+L3UczIx0v4nfS9QsEd4km9peFagqGUPOKJ+NRhoy5ZIceVPngN4u7er1yZLVluCcICiAtCGHiGQgWTihbVl1cWSxBiPHMzDk4RK+4KJ2gridgOjhbo89sJw6OaIbEXoQU+TScSAGxRqJRZsh4aQAwNl8P+vabPAHbvh1oDQwClunN2Ujti2R9zZ7pNh+1HPMu+sAPoVGj55Z7V8n7W7APrxfSDIGH379kAI+6DcGjWC3n9dY+4AtgHdFt51jYfM+JZRnfZ9NMGpnk4C3HFWH7ZwHF13Tbj86Z2fwcL0wOZphs/sXOSMgVUX8MDXaipU4N+t3+H+yi8EV5eYvX144nsN1wN4EDg7MFGiLvw8IoWLTKG3sl3i2E0gVPRt2i5KKgE9Igd4qIiQ/ePHPzEWLysfRSZQZT9AVIAl1ZO8AwNB4X8NuezMGlFN1QW7LnWKkpKFg0PRynO0r4bVLs8WARMpw5hW7MJggtRv1yPZdmEtBQODnthTHPDRRRH2Pxo9vLCWLwg9YSgjN+l2EwLyWTfdda2orC0QEll+oEQNkA8IUxriVEAalEwsP+A0Wkmw48sKuqTXAMbYOzeGa0dUAOv7AjjVyL8riv9n84Yi+eVvi57KJFucw3OE/zOYTrXNCnXe5mDwdD1fBeAG/S3hteDA9B9dYfJrarlQIDfOrDnWfaFF4x4wvBbQmpo9X7kApxHW3FDDgq2ANA4VaDUbgSSBBi5Ef/FMCqFPhUq/7Z6NFxbspo1cOWBzAiW1YgZfjOpa6BAqV0E7UexIozSfz/CE4H2yjaux1q8mGYAKKDO0IC8VJ2lIjMjbAXnYanN7rqyZLuU6/cpo7+I6C5H0RZpro3befhdxS673QSnwkgG9qLBaKY0dWrrj7J8/UWawZIN32D6G4A8/JTl5coX9RwMBFZSxeqGgIFFqm6KBXb7iwg/VAp96TTENdQ+dGpZuN1UWLhLkJKhZDHVAjJ2r4LJSI2mh6vmv/W/u6aCH+kvkwKvLBPWXAfFe1TMjAatr0Y8+q0zhI35RkD6UtYrAz+jcJZagDOHUCwAF7kMPm2gtEwUDlhcZuSOsHiRhDUewMknC4yXp1jsGjeENH2sGbRK8gT0l6zEPuW04I4rDxxtDwHOh/bQHtqt2r2wLDhn5GEABdNay8gbyTOm5zI8+/ceAynDhyCWxV6HxOVCrIjlAnha06v8ta+ChrHoigAArVawsvOSqtaZNnVe4dw6S3/+Am6pdrceyy0XSO+fIS9CBdxcd4hnC3RajkydfKZexF8oM5RcT+QFe5MvjCUV2V0nxJUHO8LyqeiOuA/O4K8GiYdsR+S12K/uxTXck1PsPlqVGca0SVpdEgAI216AZJELz0V3ZchWyMys1sJCrZzpxCGYuE6Z2WhW3p07QtixVo/qOsoZ2V1OxVpo2/D+EkFjLFExKtff6EscIzes3C0Dls2wy5NQcR6WDUz23XAmdFBWDsAJMlMAV5IetbZ7P8CPjP5SDnb5k0FYvVWWsQ0sZi88mmZB5F6uy3RyguFx696pZRMIk8icwA/VtSvcoGSBTAFl2XUM+5vcnwBw8U2P3AOL566mTp8A03kGGuhB7ngWAC+8HgvG9mOROmwti5Zi703tXgwWxxodRsvJCQ444QBo1YCv2thE8ODkxV2wHH4j1WcxC/tMqwC/iwVsFbSaFahAK1ZUJwfCtFZQ1iAvegkmNmhPDgRunMIWNBV2TSyjd5W0Ro8V1x3cbtL9NGXp3mtFLNUqQr1W09oV0Bcgit7T2qHbVomD3M+NybjWQeTSi5nsq4kN88+XVAYXQIBYTEAYGjAVjGDGHy09Fwr7GpcA5EUvPvyqVX+vNSdpIS9Q6l0R9kkrcTeMf6KeC2b/A1rDwQKmGh9TwUdYP+KKmmtD2L8nkPi4BBYvG4zJSjJDVvo+PFG34ZIwnefivgrGg9FfEKLGTeKqImvTkst6IEYeSN0u7UNXJRPaloP+9U38qmPk9yekbdVDmB5ndC+bwaMJYKb3JuDLHulxU6z04xCzuMF32aZR29RpC+luH9Is2pp8DO7dMGNbupWmPC8Q40ZzsikOQ2YgcQnAGYP2IZO4AXHaiLabGM6w+FxnasqV0MTOy42pnlN7bjkr/JpvpPwKoU0ppNO6h6Ywi2Kug2oWYlk5jzwrVrI+AhKotBkfkBfQT5ZOrccvBV/HUte5uRbWl8aCcArUKtfKGMMUyjxj9240T9v0ral7ta0tABN26zZVg1malZKAzNwgxGcUm/1oiKvEXfbSX5fkGs4L4gQoVgrJYr2mtsy0QfxeBwu7denmfbVztSIy6xclAu88XFN67ndu9j83JQXYe7HG9jqYNBPAbdq9HSxuWBbeV5xry17VCP/MLAvnwH2HvOzhFLnZChhXVXJZnTsHjrkiIIlqoK4JUKYTkYqz6L3vPYYnAd21WCKGkDTJvxZPkLs6i81g1a5ZbqJHva/ndFj/ogJDM3Oyl320OpZ04rB/5NBv6hPh9w5JmcQBKfACgO664WMo6VDdt8K9y/8LII0W9GwuebIg7pHpyjXXopx3dYOMZdtFUSU3tCtlWR4G12R9xLIwd6Fe3yb4WS5CDXqKyFCbLUJh7ZbtxaLwBGy+OWH9HTk5N6mFs5s4rtOiAAAgAElEQVT3d3zM8IND7nPZR+rEevADIdvEEKplkQt9HgBi0ZBuLAv2zajcNDk3Od+kKVn2DFqlitKEFJG5obGemufhn/lDn+OT3/xoTqv3Y2lZ2AwLyAtvA4d9z3NMA3IGTRFu9LVCtZmlLcNhn34XJQOifjWs9F2/AzLYuH0CHKGzDMSYsLhIosLucxksREB5PssGoLxwFFsF8VwKquxYYTuBogkxNyrqKak105SXm5o56SBm7+TIWCkPqD3kfswzRfWFhEgK3sSlvjKN29isMO5WIyTspPCurfqUWbZmXtom5etaNGai0qkpWlNNUikbb/Zp9Hr7XLRHC+Aq4cCKuRmzMPi3n6TWo4VwUxL8RaGpGxiLl6Lnsf5ON1NBN4vF4hj9S7EKumtGd+lKlsUlcWPcJK6mbNMMqvu6jIk0ZlFjP246HrNwE5Ch6xuDVk9wzzr4sb7x9MLNYhalfH/B+L1vfwXdSMBz7QzxnSyLh2zIQ3toD+1W7d5aFjfaq6Dfr2pmRRyJV7xLoySUae3+CkT7MG7yg24WH1FT9tB9oMTixaQKypqR27TxhQNFtB9Ga7Ut5BwYxonRWgwtGc4PvBlcorEmKDEcGrSqNhFWYtzJln/LZvEkYB5LudM+RocWAs537PePzmDRsn23KmOvUh3z7shvfGMZN8LIPnFh1y5xEPuux2IvJLqG+HROkZoO84yMEQE3D1irGCa+qX4PVamsCCMHB2foSV8zBQZBL8LL0OebxCwVzkxZLohBUpMX5Vhtmq9KAUiCV0qhdb8WB9UMSwv3FrRmkzmBWrVBYj+HrZU/LH1pwFOppwLjFi4JKuu4idEKArdxkpvf58+BgcSyKnLlJmZhamslFuJFGsCN4rrYYOEgqFBzlQDJjohEAiEtGXxt91Ircpt4TivzaDGE3LFeU01Lc9OnG1fP7osC4pqYT1pn8FVbxjAfWJOJMxPAywzeuFnZ+o9FzOJG4yYmcUw0+HCwKMVluaZMmwyKsV21/vGMAQv14abmfzclxEU/z2RoxgGox4orJ777wZ3nZgCwdKkfaB54s/MhhZUPscLLAXDnCxOX9AEyDkaAF83Lq/6/i1xSpLacHRVWJgASa8nAtKY6uzal3+wxK0ZikkFjpq7uCL2jo0Viya6Hfpdr1M7e8peDZVosim8DX2XmrqjEiha1/fUH2ZAclOHKDJXmFsc1zYKsHOqs3cZijJl7Om0yHAnwGnNJK2A6q8vZCU/GdKZo3EuH6RFrfxrzTQdg1wRD45JKIV7b4gkjrhjdtYPXgPX4JAPLhOlsng6ePDeTi16HswhMDukkz1jHcSRN+6p2vwYLdTUOiW4AyEsYAngYQG069JBn01pMsk1MBZqN3QRmBhEVHoUC5Va2K8NdWOq1HAPiglDMcEOq2ZSY5SUo/1uAUpisDtOIFhV3Y2WvcmOG3zepYABuSrLvsX7a725M6La5grLsEEwlKAcAfhB8hZsYYXtkMAXKw2TXob/mG6Asm33bykY/suIy2mCaBjiPWBZhm+F1sGAthOqv6othkgNFN8REgQMKN6mxVJneqICy2pfveICTcmXBalOt3bVqfGgfwkYkBCjNod12zi7WARrqlviR0b/w6C/LYrWGAOI6IVkQcpYNIzQBTlnebfPRAGf/kuC3ElC1NO7imcc0EfoWV/EqUNa+k36NKBqsAO7ElPUQ4HxoD+2h3ardL8uiaTdwFm316G0QnM5J3CJUhWlqpA7fGsHZCYLSSsH9PiqjVRIuhYJS/CEgOA/cprgWsaLKxCXuR9jm6ivn6jowBPUJAEurwv2hIjipoDJLFaea5oVWb0mKb/hhIDgFmVlp9eq+qlq7LBueSF/Xn//wEJwcNLajPtVdEZzxSUR4FhAfvx25xb0dLG40EuWxW3tYjsDBg7vm4TVglz9E7ty+FbCUNuHjdOBrJzGPOwgdvVOjefaDQxMEtb52JFqh7JoqTI2naAbHNFDbmMgPrTXnYHERyjoAtQG/jmbgqx9UawO/42OuLqNKH/o07+/wfpbr+65SX7fqG8r1qgPi3Y67erLD9PxMyiZs8x/VACethGMR01RKvctvLSfndld4NY1jUz7rNqQ8ncbRCQD5vTPxzZnhn29kPS3N7ieJcRi3Ju/3IAVItceidAY3ZDgDX00J/csIf7WHdw75XM7hTRyZbj/NeDH9RqZN48JcPHWg3QDad6BxAu3r7x5AvwqzZyUHusHxCQBL0zqxku+rCV3vlWCG0V9IH6bzHm7MOP3eWOMj2g75MdPCCadmyrPfKGX466EynTfNjamiW/W8mdYFAp47yVS4pByRutzY0JkI59+V+2BxEpfmMRMpApsfl5SCgCIjf+aw/LxGLrtNB3aEcCXPx3Rygv5S+uAHV4huJBsjLOMGIlt/LgMxe+CD3wA6jT9lzVL5KRerS/qksRljUbCkW9R0sZ7v8tl0dAxIXV/iHMYh8vh3gOl7fZU3gIDy/FiZyCpKGLjaneP0CyA/rWjdL+5Qon4/BgsiUOiQr6/LovDhV8HM8BrsZK38jN97Dvq5n4Xbyg1Op0u4iy3S2RL+WbW5OHjQZgfu6inS9z4v3zd//A/LcTYJ7IDhvQ5uYoyncnXf+8cB0+OlUr3rw3S2AMWM8f1liegvPxswPg5wgxy7eypVsk//9a+ju64ktoDMmBY1Xz5njKfyvb9ibD4W1N+H/0j6e/mTSyxfJMQVobvOmLRf689HbL62wLQiLC41EKnv5rQmDI/qy3vyWUJcErotY/9Y+/uyyuSRZT8APPmWQDm/80tP0G30ehl9fq9pSzuPlcCZww4Yz+2FEvP95NN1sVpaZOL2w/ryjY+osDQtXphZXl0BN9ag43QqQb1H357wyS8qg/ZKritNhHSai04oPhjAFz24y6CFDkx7D4oOfiMs3Oe/dVb6tv2IMX4l4pEuGx5LFacbCblvGagkPZpWQP/CBldJQX3wG8Af/U9+E7/+2z8r++0yzs+2ePH5GT76WBh7X25WcI6RksN7Z3JxPz69wDb22MUOl/sloqJav/zWE6HrD1wyLzlIP/3ZhO531iWYSr/8Bf7MT/8D/M3v/jHELNt/fX2F77x8D8FnpEw4X8p782SxxYthjacvz/HRY4vGAr/3v9wkl3pVux+DxZHGKWNePNbAdIcEWL3HMAmsex+bDAnL7zHVT1uuzTIJfq/0eZdOUo2WCZiSkN0wyozo9xHIGWHvCmzYjRH9hYczIho9VrdhdFsFPemzHAaCHwWO3V/n4qf21xn8qZdj6X4XVwlhlwB4hH2TfRkzuk0GZVeV0Q02PjlV+9Lj7TL8QEKYo2a8ZWCMvs4ZhFrPsb+qZdhGzmI5/oKzWEnWgRhFL4NYZshum2s6toGJd9cyaAG1f2lZiWfYMh0BRS1M7pMUw4V9Qn8hvjm3FHaX1X2a9ktRMycP0x6lLINLuCZ0F10hlyEWZnC/68r5siOErdN+VwEkAOBrGejtRbUYRbdN+PXf/lnQCwuoABdfLOAnwlMWZnp37ZHXcmN+/1Imld93GvQYHNzOISv24eRKhZxbRTQi5BCQJof+EujUkvji2Rn+WvoFvHh+Wi7q77vHYFUkA4AXkIHw87M9ts/XQCJ852VVNJri7d3Ph2zIQ3toD+1W7d5aFq9VI2vQjwW8ZJkO25YO/l7RSsWh4hGM1IatujM3/p+nIhWXm+rU3LVoz5pqkKBUE1HvaIbqa/tQUHxNf5iAoj5u6xs1XwNbb6sm88EdzZ3yXrTUc+1xD5CjMxCZYh+MmNcsC+G9FB8+l5okwSBkX2fE1l8+PGdAwWF6XMt0GKGO4RI4ABxpRkloHJzGlVnPR7k3qR6rqHWRZCJKzEBhz9y4V6BadJY6zPAOHKqlBVQ+0uzF9bBnNXcALzL8VGfsvMxAkmfHMA4uaFGdYQ1DtboKqVBz3cztKgA5ADk6nPQTXqA+DovlhOF6URnQe+nYNHlRe78OoKbqlA9vymvavR0siAh8RHxIf6yEvZ2mOMNBJuJNhL2GAgxOXppebqZlB+AJufMSxDORIYWEz0rKSb8fIElNH5S51mWIIhnqd91HXErQSshVNAXXEdLSK4Guq+k9/d6Wgs+ChOHmYODHZpAoD6BwVxb0YlM+bvsglV6UNF99MdNSB4ArKgzWlIAA8bUL83lrxjcp2TJgupombJeRq5WXqaMC2W5Zn4jlWseTyv+QFgoL7xncq5u49QgbQu6B6VEuCmyyTyHXTV/WYKCkNiVGERopyNRVd0yuQR18z8+2uPhCRg9eZPjzEbxbwi3lAnBy4MGBM0Cduhtne4xjAPcJOTmkaKn8DklJkw3dykHuS4V86/UNGT91/gyfvTwDq0t7show7juQY3AmdL1WEzuGcxOGbUC/VIZ3vlsm542DBRH9dQD/DoDPmflf1GX/FYD/CMAXutp/ycx/T3/7LwD8achY+58y8/9+6940jV+nGxJzjVmMXlCTU8JMLT3l+d/heRlyc0wQ7VAHihl9QxLjBolZlHhEcEAU8lyJJ0hfwi4VbRE7ltMycolZWMCPEJNKAeyrbki3zcgvJV3olJKu28l+48qLvqppgQ4JfggwolegyXRsEpgawt7I6DZJy55rZB+wWIL8LvuoqE0juBUrQ9mnm/E2roRWr+hTyGqFBLds34Iroy/L8yCWUuororIznIGXgcLiMN1Wy7ZjLhqfxhBm6vPlGAnwW1JrTAeFqNbCHlg99cXfBwA6BRbPK1KTA6G/EOIaifXU/ndZINy2rFeiYj9lvPj8rNSy+MnLQDEQoma43NbBpO54K6/c1XAq12x0omquIspu1MDwvlpyIpsg5yc6IXodR4/f+OxjjJu+XOsXQwBPrmAxhqiB99WE6WIBioThuWYdWzHUW7TbWBZ/A8BfAfBrB8v/O2b+r9sFRPQvAPj3APwRAF8H8H8S0T/LzK9yKF7fXmVZNFaEWRbc+bkbYnR6La1e07LR8E8OTKTYg0rVz1aXkXKZdXPnQASklS+zpN84xJWH35hFIp/TShmeMoq1kXpIBoRk4JiMRj+6ohlq68aFg98zck/gUSwfO7e0FLq8wjIVDfzjyv4BwI9O+TJzAV+17NQtN6cV1E2n1cowgV0TGq4BTt0+VVo8YUEH+uv68LVmfFzVgKGl/uK6rlNYr9WSsExAXAqEPXUOk1oxudd0Y8IMujw9iQgvA9jXgdhFEosjCA1/kRRMousR15WFezqVTI+LYiEZH4X0S2o9DMJdAFdLwkcfvyjBTABwy4i46XDyVcl8bC+X6FYTcnJYrmTEW3YRmYHNboFx3yF0ciHSlyfgAXN2bw+M7yXQacT0bFkC448/uMbPf/Rd/L/uG0iaDVn1E652C3ifkbND52UnXz29xqerM+x3fekDAXjW3b6E9Y0BTmb++wCev2k9bb8E4G8z88DM3wbwuwD+2K1789Ae2kO7t+1dYhZ/joj+FIB/BOA/Y+YXAD4G8A+bdT7RZXdugtZ8sz9VuTTzPJBpEZ5X8Fe04B1SWTvRVGh8ewvAtVwQDLgpI5tuCGP2ac2PYuYLGZGZ/k4tDbEGbOaiLKxZhzoPLQ9o1SCRbf1QTfgZz2dzXnY+Un06348UOt28NmHXcHnq7J1Ck8YDCtLS7ysoqiXZbc3nauVwOV6p9OVq6lv5OZncoFWjdtZXlAIqDrKOHwjJNee+8RIDaR4DSpoiHURwp6Yjpb/ZFMi0X1GJeRHmFclMUj1qy+Kq7v/lZgWnymp5mcHJwW0dtpeVOnt8Lt83GpuYNG4wDQEcHZJetKAunz0ngKaeLz3iJMe3Z/fiYo0vHp/i4nJdYhb+ccbuuuKNOo2b/N7wRI53sYDzWtDHdKfU6dsOFn8VwF+EXOa/COC/AfAf3mUHRPQrAH4FAJZY3/j9tTGLA1Ibyvo6tjiLY5/tLuyBUmUvP2Q1/QxjYJ+5UvA1GYVWgKb9jhJsBGA6muahDCyqWprhsIi66W0Kga0cKwyVjKYlmSUNsKa+VphaWbXESCrsW1SwZFtzr0o3vWx3OODEJQrIyUUZLN1QX1BABhQXZZ9lcGLJUrRENW2NSG62t2sQV7UU3FyU3HFxf2wfhefCyoGM6yJgNuhzx+heuBlPBmWUIKgbah9IXSgb+Oye+b2R+845TikD0yMuWRpfgp8M51hwFACQCDxIjKJbyYAwPl8iPBrBTAhdDTjmTBJknKi4gXAAjRZT0iM4IJ5m4DQiP60DwcnZHpEd1idDyWrsxw79aoJzPMt0fP3JBf7p5+/BnU5IOkAQMYK/PavQWw0WzPyZfSei/wHA/6r/fg/ATzSrfkOXHdvHrwL4VQA4d+/ffJvfxDjVWg7MEox7C5YqYWuqAT3XsF4Z43VhpEp32H8b3LOXx7XLuPieLtWHfsYQVfrS9vcV7Nnfx1asJK4ZEbMyyvIo5zMzTlh/O7hOZSDUxSKMDMxMgDv0i60PGfMAXZacacu0RZlgHKVEBwM7NLX6juxpKbnSD2Iqc1xutVJNnlA/UyIQMTgR0LBxV/Uy1IHtlXMmYUoeU5OmtUHikLHBYhrv0t5qsCCirzHzp/rvnwTwLf3+dwH8TSL6byEBzp8B8P+8Vc9eh7M4xpTlmxSpqXYfMmPP9i8fhZW5d3M3RLdj+w5UvVBf8Qn2vVSFFvYrTV02b3pcUBGnYV9TgdlXuHPtDxVWqxl7laZM2df+2HORO9XSLJaFVqfm5lih6TdwI3VqwUy5RDXVmX11cdISRaV7xu6tiusthZ8hQEWj86APoQlsNmlVc7UAuS5mXZhu5ytxFsuEuJ7fa0oM7lgqNJvjyfEZqW/7IClRC3CiSZ1KX7n0s6ROPfDe2aYgM7kDqMvgbSiBxE10CF0EM+F0LeagdwxHjJcARurRr1X+MiyQDc/RGqyB4fskz5X2d9VP+MnTF3h6dVZWPVmMuN4v4Myt0QDnuhtxerLHdt9jvdQAJ4lVdNt2m9Tp3wLwiwA+IKJPAPwFAL9IRP+yns53APzHAMDMv0VEfwfA/wcgAvizb50JeWgP7aHdq/bGwYKZf/nI4v/xNev/JQB/6V06BeAmKKv5zp5Ah6nT0KAoDeF5iOA8QC8CKLO3pQatsIqDOwrKIjWh2xlZOCoPLAtSv5ka5GGHwmeZujrTpgUhnspMaVWpOYi1IzNq1czgzhU1cZ4fss6cNrFrft7wCbJy/Y2omWmLZVTjBVY8lnrAdDcARUKSFJKZRF8NVBI0tT9nfHLzGbx4INb3bv5ZKP103Zkl1rFaLYS4roVktMgSYOwYBTAzOFCU+xufRMSVYh8iwMSI5wnZmNmo8kyk/pBykcs6ABqKPykK+30nAUQXMk7O9rgaTrHU+MS0nLSQjOB1Jv/o9Aq72MG7jOs+FstgCIJ9OCwks5vWIjiJGP/8yaf41uKj4t68v9piP3alkGylfQgu42w5YDd0OFu2kVvcut1bBOcN3ZC2ZVRnWUvOreRafr/FFWj98hLMbDIBqWqLGODqLjEL8zmNH3N2TIiZXWIWE4qadRuncFNGWngBVNmzOuUSeCyn0g5QBy4Xk/xegp4H2x3D5MwyPIoVEQo5WZ6WEpR1sc1syPUjrmXc845U39sGgki4efxmMKv9r/toT4wi5oI6dpyJgMnK/wncK9Br72dUeYAoeBU8A8lJM1H9RPtb05cm/bWN/exExlHoA+YyNhKjMPdgFzt0LmE/rbAfOiwXSoOQ9TlMVM7XJ6pBnza8wYSLtMIwhVkwMzOVKlZrMTt4l8Vjd01A4w5ho3s7WNxInR5mRgxopVYEtyplDphxcx4ZRNogITf1DJUlShiqWsuCPamIDoNDzZa4iStfZ+HQbAJTNmlnhRnTnNNSWKLNB9cqUFYQGKOQ6wJA7j3YSbbkUAzIT3PeSBcZflIOzsH6VX1tQWvaVCnL/VCzK23VaBUhBihJbMSNTXxjqgOkxV9auPehbCDI0rS2Qg1IushleR5kHeHhrLGOMvg4LpYF772IDC8YvDCzxsNvnRwzcBGj9qOU2U/n9QX0g6BL/Z6QeG5ZEMs9sGV5sHNk7GIH6KCVM8B9Ao0Om52YH9MgLzMnwkvrlcvYTyvk7OAcY7cTdJsvjFmNtdZJWjgxYTnUFPLVdoFt6hGzQ9YA5ov9CrtdDx8yUiIkHUTG5LEbO+yve3wZTsp5HQ4qr2v3ZrAg78BtLQEzqO+QN0pS09dIFrXqY8xA34EXHjdCwK87nlkTLNFj0+ksTS0VirlCoRU3YeXYsj3QajFYc7FCrG2GomwvEKsWZt0HJbU2DJYd5ThugpICU+m3U56JkkF5Bc6i/f3Guul4FsCNbToVKsAs54gyWMj/LtZjuCSDzPz4df9+rOnmAqPmBr9h11P3XTJIqX5vXx7JyBBmOq6DE/3PzGWmpySpXxcJOJ3gki/79aNadYV/gzSrBs2M1XPJAXBDU7be9Ptyv4Tb6WDBkgVxA2FUwiKODpgk6zGSDArXfcR+6OAc49HJDp999ggA0I16bu399XL92LuCQwGAcdfhy/EU+31Xznfre8QhIKUMjg7G3xyjF0rFoWZPJGtye9PiXgwWN/g2AVDXATEKMxYAvroqv3EfqovgHDBF0BCQn0jtPo3KbfEanIXN4NnqFYI8LCUKf77AdNbBDx7BMhTLADcZMqjZ2ey7/BMXmsJrTdGgGAMH8DWXmTpkg1YTpnO5JduvOKwhMZT+mkqcwg9e9n3k+DLYHWQDsvn3B33VaHtJMWq/RXeCZutmLWSyl3V8zFh+ITGXw2Kx8bSyVdFSGbAH0S+tRVhzHRI5fj3kMbEjylwUzIt+Z9LByc4tsBRrRQIpSMoNJOe0Y/jPFiXWkBaE/XsyqMz4PzOpOPTcRZOBk5uBn8p1i6nyUSCwFIUtuEK4iQuOomQ9ACwXE3a7Hp999gg/94f+KQDgN7/4wxVfMTSuhQe4ywC5cq/61YQTPypmQ9brQkJQwBdCwmIhN2jZRVxulkDIxWUh4tcVZN9oD3wWD+2hPbRbtXthWRxtzOKK2L9N5SjtpsJIRcMEigluP4L7ULal7R48jqAtgUeLzFUbub/SgNKYAQJWX8oM7BsIth8y/JAaAeMEd71HNyUEZcN2mwFLZriNOrPK97l+lkRjopnVuw2VbEjYC+MWoGLFiUtwCwDWX4guiIuCLjXEIEVGf50RNqmIGZsF0F059A1zVLie1HTN8HtlIzfhZ7UsOlWzop30f/3pQdVokx2x4OnihbpZseIOSK0UNzXRep31/cjA89yIC8vybpsRNgo9LhgWdT3MhQskVb6XA1aKXmxL83OoVlbqfTl+QYCqdUcRah1ZbERcFHYo7Flhr/B4lXtsNUbYQSkKlYdCLb3lswlffusJTq6aIHPoRNXsS4kNhEmOLcTKcg5DkPvtM6EbxaIAgOWX4gqxr/B5OGD1GSEtA06eZgTVRrn+3VP8b1/+SwiXtYjyBU4KWxpxCaVgF4DFC0KXAPZ96Sv2P4Ixizu3Y0Ara7exrQ6Cj0wEl3Mht7HfZtF4ItzQUG2U2WddMN/ysCsW3+A5mrBFOEp/6vrGPdH216XcxE30xWK+GUhkqckwBfOyLkjjNfN+S5Zmvov5l9qHgjS08zoMGdn1c/PfjGqwlPAD1cbVWErVYG1cpXLPuNDOtUjHw1J626YEdQ+yG8baXc49Aez1/GmuZp6hQeVSCVoHVDfVGhf2QFL3jC1ASgCN0pdcULANuXB77ZqakPZcJMPUxI8gtTFRqRSrIBSkbN9S0tpPn2qcplQK48g9e027v4PF6154B4H2AmDT92i1Se/iiBEVdqzsnTBLQyyM3Dm4sTJYc7jDfgGYlmQ+3I4Ub9GgMiWQyLN1rfZCpAO1j4Fu7u/73GYsXl4HK3BhsxLWKfHby4OXABDBZxZZQ8jLxQ7gRAXXIfu8KTJ8t/7Z/ZL6jZL61EEpd/WF8JplEj3Zei/8wIU0mP2xo9y+tbEMweAAvG8sLMsqNZNHDgyftP/NtagEP01Atwe6GrKrjSSOkTtfg896jILTsGv+fQg43N/BouAojtTbZxSSGaHnz+CcQcMdhsnGMqCJQU5gxVCPxY0J4XqSakcNpvJ0x5e0zHg6s3nN34OK2C8gM2ckqUg1Uh0OgBsYRmNvA5Wb5hJ83+9G7SxHEMi9VxdNH97Ui4nsIjcjgNR8uMiFhLdUTjJATXraXK636Zt8aoFbYskyNNaNWCx1ACkZp8hwXOUNxSpRzdd3xBi72GR1XE0jl/0SKt6G6zYGWadUg5l+35yD7tO/iq6fAZqcDCoWFNUqWtv/m+pL7nSe776Lh/bQHtofhHZ/LYs3NQNlOeHQhDssgXxDazgnRc2LtCjMld9z7+HGSsNfRJNvfQz5OKam1bohxuNpgTVATO3cy+w9I9kNVFOHP6hW4ji3cEOMsFcZwdzEpRxeBIKobFMCpf44cvRN7RCFmr3C9JtS7htuyCjYEWPKsp0UxrDFu5voOdTzlABnvXZA44bk+TbFDWndIIPaN3DztHi9G5J63+BoZLnQEzbPzY+LG8I5Iw8DqNc7nBmsYKx4KcJD/v33AM7wRMA4gbYaKl4vQftR8thfVEKv/PGHoC4grxdwhuxcLmog0saarZKXni8EdKUPkX/6Ak7JS+xYfr1E/OAU8SSUF7hbBIyPeiwU5WmKZnHt0F1LJsWbInjnMJ06MAGLiyoc1F9EpD6APWH5iQhT0Edn6C4HxNMe4XpEPJVr039+jfGrp7j6iQU60/fQgGEOhGnlysveXwdkL5yaw5n0b/kiyUOmfBZG10dJQEH7J67stwRgSQhwzA2ZToBugxkXBCAPZH+VEXY3XcfNRwv01/JEj6fSl4tvBnSX5qKhfLacGIblyL0rFaVmattLaC/C+JjRXYr5bS8aMbD7UPQ+2AGnT6vPcf11DzegiDVdfNOXwadFUAqKVnc8/WwAABZkSURBVHgxTP80B1mWuh7jV2KpLzH+khyECg9Q4ppTdWVDM6ERw208/FjrhFafCWt6Ozh0V8CLP8LIq4Thk1A4QPbfGLF8NGDvVnVlz5jaknf13brzEXsmpMGDNOhJjsEnt/fB7sVgcefm26Ix/X7Is3lQMg5glrHIaiV4HUhy52YzO1yzT9ccCzKjVfp4+X5YkxEXws7ULpYSciqFaBYI7ELl/rT+muWRQ/2033MQkJbXB89mECHFQRMJRylxL+zZVszlCQ4VGFbIb1bVz29Zu3JAQdimvsZcbgKXqAggty0tqECkDQ4el4DfHRwryCBGRfxXgx6ohWxGhnPINxvXLOS3TSOWl9yNpC93/T2u9Nx0WdZydcqS7ch6IctgsWIhBLbrqAFsfzYhFbEmKuhaOpULFicH6HffN4UoxEhMyiGb9RzbKrva8irBn00C91cCnv5sxHtnGzwd6mtspDqHMf7H51ts9j2iz/BKeEPECO72wYx7NVgUy2KaZrgKAKDgwZlAj1bAfgRMf3TvgWkC7T24wVGAubomZiKen8j/KaO7kKnH7WQ/nSdQzNXVGKeing7VQyXvgbxC2KeqsZkl4Ggs4elU8ujrL6LMsE0qM3QOfvAAAd11LKZwuG70LfVY3eUEt53QM0C7ycihgXFCfzFi8Sgg7M3+hgTREmHRpB3CTmpY3MRYFCWtLLocRADXeou47uBSxun3ah6/UPn5OeIy7Aidsnu35i1loL+Y4IablsXqC1eCt07PO3WhHKsMPDo2GFReeDQkS7T+tLFCGsvCWn/lSgCz7dPiBRC2onGyeFn7xj4ge8LihfRr8dwJ21eSAWRWdeqB7rpKMKZeeUYIM0lBSxW7CZieyejmBxSGKxus7VyXVoujKZGTp/lowHX4JCD3HmFbA7Lut0/x9HyNvlVN7xhhupkFebFYIq0z/N4hNhW0074hBHlDu1eDxWubb2o/ci74ANLvdFgXkiHM3hbTAIQBfEpA8FW02MBdUyqiybIy1+OVzIkMJhS5QtRNv0NjHlxe1Aga86z+IgPwBigaMwKUYi3mIqdoBWluSiLMPLnyab/TlGSgaSEVul+rPQFQtDpmUniZwVqg1m6XVg48CeioFKMZJuMgVcvOhJHnaUdKkFqaI9ILYZeK4LI9dGHvZ/EGOHtRUWb1Mmh0OkChFrS1xW0ANHN1MFgotsCPgslrM0ndNiN7KtfeBJApAumkcUOUFcxvuPKAEiMtCfGEZpKC7KH7rFXFM+o/GyzsHKwWRK912M/va71+AI8yUERloewvAMChb1yW1NOMkqCUFGwJ21P5NMi7TDA3j/Wq9pANeWgP7aHdqt0Py+KYivrjR6Kibi7ERpRz4xfPREX9WmzEdLqAu9whna7KuoBa5ts92K1FhAgAvvu0/L75BYHX9pcRTITxURD6NnUvTmMWl4Krino6XYBSxnTeF/PO72MhqAGA7lMpQv703/g6+iueCRXnQEWXY3HZFRX1xQVj/56UUX8QhURl87UF+ssVphN3oKK+wPbDBcbTRkXd0HsdYTivJujyRVYcQVVRt6nNYNXmr5//jqiof/onnyDobaixC91MrYC0AvzOzzIchqRcPw2Fz6JFpG4+cmX2Hc/V9TmpKupVgtEwBmbuO/iR8ejbEd/7E9p3C98cuEHxSYS/UBYjexQyIZ0mhAsPOGB4bKw1wOZjBgfg5BOFYD8RM56SKKXlhuSYHTA+yVg8UyKkTk748e8A9Mtf4ItnUsSYo4MLGXn0ePyBXMiLizVOzvZgJqx6dWlJqp2vtguMOyHZBQTC7VWEqS36239jRH82wv32qVoUwKN/81P8c48/x7eeV/Ib7zLGGOacFQB+8vwFfufLryJ93aHX37zLWJyOuG27H4PFsRYCKKVqkTVBs7yoVadp1cHtI/IqwF3X0+GFBw+hfAIAXLVZ41JrO6IHO8L+sUMYWF42ACffDZhOwwySHE8C3JQRV64waoWdx/6JR9iZnKIcK66pRPXN5IwrGSxAEKnE05pW3H5N4gfTWrbfP5aUhXBQoogETeuA8ZQQ1wQXzTWR/k2nhOFxfcD94BBXQHeNkkmYBssoyCBifThdyHGnkxZmCMApM5ZDYWzKTya4iw7hmjA90gFrIoQtIWxqGXdbkSoCQdqHM/kaV03MRAP6uZNlJpMwnTG6KxGBmh6ry7iOAAuLdjibkDXA+8GTDS4fLbFYTDhZyEtwsVlhHANi6HD2lWvsr5XRagLiWUb31R3GS6H7ms4z8vsTeOdBqwT3rPrzaZ2BZcKk/c3vK5X/93r8mZ/+B/hr6Rfkuekn/NT5M/zGZ/9/e9eyJMlRbE+8sl7dPdXSMGqNBANIBsYCgwXwH/wIX8CG34AdC/Ys7hdc006YYTYsrsTiMkgmpJmeqe6uV2ZlRDgLj1fmVGuqJUCFlG7WVtX5iIyIyox0P+5+/C387OIjAMCz+QksSbRO4TsnXOXoR7N/4NpNsHEVLncnmAXb4X8ufwLbMuApgulJxmN8r2Ew82yKaBD8cP4Uv/v2e/iV+jl8WDXfnX6G96+/i5G0aEnijRHbKPfNCt+bPcfjq4f48fyTNK7fRxfXAXK8i4VzoBKHKOxguXO5/KD1gGV7uLSVZW0hWps+AYB8NtAiOCgbxiFGN5xQNo7sJNaHsn9FKQBLkLWD3khe/QHI2mG8cJB1xD74WmZN0Ft0tBXVUIrbV01eRFQDjJ+zy0+2fK3RTU7oUg1BB1BK7TzX4PCACUlY0a5XIZovvnnN2kPXAmrnkwZRhXO84ghIFW7ICEqapUiuuYhJ6E2kcwv4xnKUSunJXVE/hRhUTSzeER8Q3IbeFuCgAqpWoAquU72OXobAgBXHVLMrUW8czDU/vH6VY5v9Nr8ALhsFeaPRVoRlpNWzXMNWtgKr7RmmTZ5zcyPRyglGYbwQEm5TQToBr1Si/QcAWkq0pzKBiW4TXNlLwh8++gUWL3jBWQD47OoUu3WFP8m3AQDXN1NMZw3aVuHTJWsgfxldoGk1rJeoa5OIc/WNYizGqISZuEqhlhN82mhUVxmj+MuLC/xK/Rx/X7+GteX+/Pn5W2isRqUtdlbjQ/kAAPD26RU+uHyAtlX46GrOwxWEtf1fHCrHu1i8Sr4kfXsUQWCANOJK/WYLur67UvCL2G4RjiyIw71Luj0RyFY6yWQUjw/t+O72f5d0KOhj3wmce1D0N9H7F/0q4yNSW3Efdc8HcPfgst75ECKA23E/zyt5pNyhEmQsgd50juv2+YuI9TKt0Fzuhhf+SL9PsT5IHgIzZ5FghquCul+EvkIhmX23gZBEAp4k1pbZsmL7zgs4L5nkPlzXf5EouJ4MAOcggwxykBy1ZsE8nEHK6KZbAq1KbYO0hJAyffbPS+5UxXwIdsxqcjdl2fM5RQIUs0wL2IAhmBv+bm5ie2GFF3yNckF344wdmHXWVGLEYPn2tWOBauXhRiJxduZ+cQhwqr8R9rXTXGwZAPwqsEBRwVIVmcFDsFbJZp7aiiHHACLjdRmt2Z56mBsGZJN2QIAMmZYlD2hJvNtPbbcmA6wRs4jAa8Qs7IzfjqQzu7ebcnq+2kqQofSzi5GDu4cOwEmxuI6XoIlNOE8Z15EAaENo5x5qK+EmHmKRJ92Ng1s0mIPtPGBmlcTD6RKfSFbtR+MWs0mDRaMTmKnmHvWOTY2Ipbw+YcB+UU+wURWMZvVhgVlimqdsbQEqVD4zRTi99Hh3+hn+/Pyt9Jy8c+8SHy4eQAiCUR7zMdtYlhQenS/wZHGOR+eMm3gSeHIHheN4F4s+10KXKjmbBs7z/667aAjL2+Nn3B4l80H6QGvPQKaJ9rr3iWlblGZIqEuqN9ETwd/Lcod8bOaGiDej3gpQuJG77N7EwTYF74TZhvqnxR/AC1hU99MY4tg3lAKF4hjNhsO9UwZjpBEMwU7YhH7b3O9E2BvIayJ2kcwHIaE34ZncFL+ZZ1Cz5BalcoHot0sZ19CRciBEcMYx6TVHiwpLmbtzFcofeUCt8gNtjYZaqs5iIZyAm3jmC13ogv8zxGBsZAZkWwFzJSGdgGxkAl9j/1uVAVlzFYmLCH+7eo0riwFoVlwVnVqJZSDs3a5GqCYtiARWNW+rdwaeBLZb5syMVHjSFXwUhTekdcyXqdscR7GzGu9ffxeN1XBh/j5cPEDT6hQB+2zNBDxvnKzw0dUcbavwZMEgL3tkcLAc72IRIgxfKZHHojSo7sBn0XlrF67AyHMhCtp9imnsB7cNxJDg3Ld8zbImKWSwY8uksaKWR6e/veG9RFm/Z4yv+t4RUXwW/S8DsEgDKBm/S29ldD71be3Yjiy+39IFKvpAe44lgMsnqgIbEdENi8y+HrWHsC1qY9KG7Ypun4fb+tTZJqCVz5n6BM65EJTCqgEknsxcKczDOhlYuH3RHverUzdEdccSRUmPkbSotE34CPNqEpQkeMoKeRV+jHKo/VvzVXK8i8WhS16i/P8C5yJoDQVBbQbLaL9mcUdJwGl/u6cEPgmHAHB265iyNiE6DUTQ9D8i/euU4KXtApyC8v59mkXZXmlu3UU6tU5Df0T5Bo7z6cG1QxA0iyrMmS3YuWNfnPjS8+l6DNmxorkv6otSb6WJ5zgnmP07mCHJk2Tz715mj/alJYmd1UnxNmGBYgI3kRq0/4K00+NdLPqaxW2YRaw41tMsSIhQ1Uzk0OwOZhE/ww9r2EVXJmz1U6JJACKEdqe0cxm+y9414huieBt7nW30Es+IiV6i0CxipXEeX243ahYxB6EUZ5DSo2O7LjBJldvKz5hiHtmnOzSCqQJY96H3I4JvRYeWjk0KdLJAUS4WRX87BYTi/EfmbsUag9zF3wUQNtd35WPDw9+KXCkMAIyHHwuUr0wRqPZIAG7i4VXh6hWMQWT8KqSsWw7WKjUjVxFiti7PQZ7Hs3GDBdglKisHU1k0dgQT6oyacQ44ibVHY6UwRwI1kFi4Gxk0iXIRTB0O90pxT70xWuJD+SC9eObjLZ6tZ3w7CsLE5DiKs0mNxWqKs0mNLyKDN2SQQQY5SI5Xs/g8U2KPV6OjbRDlFHVVbC+k5LEkwedw0lWvDUcFWS5XSXvpXOAle9aNBFPPucImjm9agVCxO7zRNkiZlGUNEJJF5fEilZzPBXwd7e88V16J9FYtvSUpvXuV9/WTrgDATTOIx7VMQr9L7grPY3BVgWMQ4GQeX9yWmbeRgr38iI+zUwZ2S8lh6Eh99wZJC+CO8c9DI2Li3BjqPLHwKw0oxgwA8B1+0sLZivsVX4+OI0hpRFnLGuW3d/k/wJfwpxaul6VJEjgfbfD0lN/WbasgJcFMWjw44cl+0pzj4fk1nJeYGkYntfSwXmLnFKxVqS7qVjO5bkmWQ5L5KOZnGyxG4zRn3zlb4L5Z4e3TqxRHYUnhjZMVKuk6psdP5x/jvWffx/3TdQoF19Jjov/bIjiJQLbtkt+EFHS3YhIc/fACcA7qZAbaWYgmoMeVhrAOonWgZc4t8RdzAFPY0xFMLEikQ6FjraC3MYIz2ooaeuOTS1Ssa+hYUGbFd7kGsH50AlIiuRzlzmD1poLecrqzep3VUbMi6DpiEMHdNpPpBjCbjAjqrYcMVaL0kkMM1c6gumkhvIZZ23SsWu0wvtJo7pnkbgQxe5arBG8LxzZOYDcXMMus5tuxhKsi3pDDw8dvciqjuRYwPOWpr3aCDoN05JlUTc6ABAC9Aao1waxfjiIaXYnEzZncw1MBF8bgxmEx8LxgpYhOwSzW6wsNvY7nsSdJ1XnBBQC7NhCSQSIR7HzZCJCtoJcC7ZwS7T8AjC8lE9qEKNLNWwT3WgvUCo/eeYon//8tnoedBI090OYC1fbcYnK+xXJ7hkUzxeYFT4QYOUjZor0e4R+T03Stvz/lYlknM15UTscNlPTY7gy8F1wACEzXvy8IqyaBdV3BTT02oRj1B5cP8L3Zc3xw+SAd9+h8kSI0ASST471n38dv3vkjfv3XX+Lds8u0/0+lTfMKOY7FYp/0wURrc1p64Q7tuEgLbUS0DmJnobYy81FYx8DlrnR1BnQ6uD+zS9SDbP4OAGQ9zNLBzlR6oHTtMHsqoRoHBXA1NCC5NmXp0i1cm6XrVLWUWa/CNc3GQ7ScBh4/4/5Y6lAX5LMkABWZriMCvqRQT5RS8pZuCLqJrtOslZh16DeZguw2uzXjGx9gbU6v+TrxAS7HLPZoLKK4VnqQbSa/kTuw5qYAcZUfmJhYZtYEGULT9VokQtwy+tKNVIp3yX0SsCc+uUU7RZtJQG1yfRBVC+CygnTAx48vYGK4NwG0lnAzn1LU9XON9sUpTp4Bn16dJfZ1Wmk0Gw1hBepQv7S9HkGe8D24qXnbtjEQAqhXFdAoLksHwLhe1fs4tkYxcU0tk2bhHko8vnqYyhECwJPFOdpWJUV7seJF7P7pGr/+6y+xrEd4/PxNnhtBd4rsPN7Fol8XRIiE+ZSBVp3gq9IUCS7VVCYAAFNVA5F7AkD6tFPZ0SxISUAX3wFAS6aU17nknVlLtBOBSskA4uXgJma5yl0qg6b8qhsoFbfH4Kh2KmFWkoOHjMy0c1qmIjrJHIpv6glgi6AsveFtgkQi62HaerAZIZHG4ctgsmj6hPm0E3QWi/YsvNn3aBZei5f4L3gOC7MojkVmc8ONkUBQ4XOBHTuN7WYzpKtZFNeYOrSymHAEzULlgKtY6gEIczCl1AdvADe38LUETR3wgncIYnCUFIHCsXbuAEnwnxpczG/wt6tAwTh1qMYtmhcTjCf81Evl4SwPejrmbVGzuNQztK3K4eCqSvyhpQjFrlhrKPFRVNLjx/NPOppEDLyKEjULJT3ePbvE4+dv4gfnT3m8JPF/h68VA8A5yCCDHCbHq1l8SaHC3Zjk84JvqPf5r7j+nmvsrToG3N3X328/ujxpz759x+/bH8M6Cu/vXonQQ++AO+cqlWBo6WItt39O+4de75WBX50+FdFl0V2Jrjs2N1C6hgswNMQ3iOL/GFEp9vzQ5X4St/x8koOtyn5EoLJs04e2+m3o4lhfqLviDjf8f89i0Q//vu17EOEJsC6EaGc6vkQV1zNzIuV+sqs95WjbyEUJsD0ukAleLEE3wWNCYAo8MKDYp3+XNgSABXXbl+qm736qlsE+kiJ/hv2ZwLcbLKbrQJkWH3ZiELJDRBwWLK85RV2moko8N3ZCKcYh9bsN1BaxVmnN5frKamBANin23X/MWUnpO8A8GXoVcJtIe29CUFd0fMRrtkh5KMIJpLyUMhhPe6ht75YmgOYt/NYwflX0zU2oG00qiTlRPACnO4uGaAVw2oKWoTr7hs3O2D8z4y+2VbCtghg7nIx5UKvVGK+fM/g+q0IV9ZgN6gVsq2CqQKNgAOypqzUat3j9ZIOP5Un6fS5Ol2i8xryIm9hag/mkTpGiUX549hQfb+a4N6pxtWNUWQuPsdpzsVtE9GtdfhUihHgGYA3g8lXHfs3kPoYxfxPkmMf8iIi+dciBR7FYAIAQ4n0i+tlX3Y//pAxj/mbI12XMA8A5yCCDHCTDYjHIIIMcJMe0WPz2q+7AVyDDmL8Z8rUY89FgFoMMMshxyzFpFoMMMsgRy7BYDDLIIAfJsFgMMsggB8mwWAwyyCAHybBYDDLIIAfJPwGpqVbIwe9R1QAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483e898>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.35808062553406 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1.0, 'kernel_type': 'untiln'} is: \n",
+      "[[6.5000e+01 2.6000e+01 4.0000e+00 ... 2.0000e+01 2.0000e+01 2.0000e+01]\n",
+      " [2.6000e+01 1.3600e+02 4.0000e+00 ... 2.0000e+01 2.0000e+01 2.0000e+01]\n",
+      " [4.0000e+00 4.0000e+00 6.5000e+01 ... 8.1000e+01 8.1000e+01 8.1000e+01]\n",
+      " ...\n",
+      " [2.0000e+01 2.0000e+01 8.1000e+01 ... 9.1250e+03 7.6650e+03 5.5890e+03]\n",
+      " [2.0000e+01 2.0000e+01 8.1000e+01 ... 7.6650e+03 8.4950e+03 6.7820e+03]\n",
+      " [2.0000e+01 2.0000e+01 8.1000e+01 ... 5.5890e+03 6.7820e+03 1.2811e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.23058772087097 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 10.0, 'kernel_type': 'untiln'} is: \n",
+      "[[3.530000e+02 2.600000e+01 4.000000e+00 ... 2.000000e+01 2.000000e+01\n",
+      "  2.000000e+01]\n",
+      " [2.600000e+01 3.880000e+03 4.000000e+00 ... 2.000000e+01 2.000000e+01\n",
+      "  2.000000e+01]\n",
+      " [4.000000e+00 4.000000e+00 3.530000e+02 ... 3.690000e+02 3.690000e+02\n",
+      "  3.690000e+02]\n",
+      " ...\n",
+      " [2.000000e+01 2.000000e+01 3.690000e+02 ... 4.739057e+06 1.074417e+06\n",
+      "  2.755890e+05]\n",
+      " [2.000000e+01 2.000000e+01 3.690000e+02 ... 1.074417e+06 4.328477e+06\n",
+      "  8.014190e+05]\n",
+      " [2.000000e+01 2.000000e+01 3.690000e+02 ... 2.755890e+05 8.014190e+05\n",
+      "  2.210647e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.21721410751343 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 100.0, 'kernel_type': 'untiln'} is: \n",
+      "[[3.23300000e+03 2.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.60000000e+01 3.26440000e+05 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 3.23300000e+03 ... 3.24900000e+03\n",
+      "  3.24900000e+03 3.24900000e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 3.24900000e+03 ... 3.03369858e+10\n",
+      "  7.88943417e+08 1.25719749e+08]\n",
+      " [2.00000000e+01 2.00000000e+01 3.24900000e+03 ... 7.88943417e+08\n",
+      "  2.99503080e+10 5.95792049e+08]\n",
+      " [2.00000000e+01 2.00000000e+01 3.24900000e+03 ... 1.25719749e+08\n",
+      "  5.95792049e+08 1.69987489e+09]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.19528579711914 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[3.20330000e+04 2.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.60000000e+01 3.20640400e+07 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 3.20330000e+04 ... 3.20490000e+04\n",
+      "  3.20490000e+04 3.20490000e+04]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 3.20490000e+04 ... 2.89507275e+14\n",
+      "  7.62870621e+11 1.13346785e+11]\n",
+      " [2.00000000e+01 2.00000000e+01 3.20490000e+04 ... 7.62870621e+11\n",
+      "  2.89123007e+14 5.77952908e+11]\n",
+      " [2.00000000e+01 2.00000000e+01 3.20490000e+04 ... 1.13346785e+11\n",
+      "  5.77952908e+11 1.65314474e+12]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.37443566322327 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 10000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[3.20033000e+05 2.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.60000000e+01 3.20064004e+09 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 3.20033000e+05 ... 3.20049000e+05\n",
+      "  3.20049000e+05 3.20049000e+05]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 3.20049000e+05 ... 2.88150433e+18\n",
+      "  7.60286826e+14 1.12134428e+14]\n",
+      " [2.00000000e+01 2.00000000e+01 3.20049000e+05 ... 7.60286826e+14\n",
+      "  2.88112030e+18 5.76195029e+14]\n",
+      " [2.00000000e+01 2.00000000e+01 3.20049000e+05 ... 1.12134428e+14\n",
+      "  5.76195029e+14 1.64851405e+15]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.92760157585144 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 100000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[3.2000330e+06 2.6000000e+01 4.0000000e+00 ... 2.0000000e+01\n",
+      "  2.0000000e+01 2.0000000e+01]\n",
+      " [2.6000000e+01 3.2000640e+11 4.0000000e+00 ... 2.0000000e+01\n",
+      "  2.0000000e+01 2.0000000e+01]\n",
+      " [4.0000000e+00 4.0000000e+00 3.2000330e+06 ... 3.2000490e+06\n",
+      "  3.2000490e+06 3.2000490e+06]\n",
+      " ...\n",
+      " [2.0000000e+01 2.0000000e+01 3.2000490e+06 ... 2.8801504e+22\n",
+      "  7.6002868e+17 1.1201344e+17]\n",
+      " [2.0000000e+01 2.0000000e+01 3.2000490e+06 ... 7.6002868e+17\n",
+      "  2.8801120e+22 5.7601950e+17]\n",
+      " [2.0000000e+01 2.0000000e+01 3.2000490e+06 ... 1.1201344e+17\n",
+      "  5.7601950e+17 1.6480514e+18]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.36195158958435 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[3.20000330e+07 2.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.60000000e+01 3.20000640e+13 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 3.20000330e+07 ... 3.20000490e+07\n",
+      "  3.20000490e+07 3.20000490e+07]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 3.20000490e+07 ... 2.88001504e+26\n",
+      "  7.60002868e+20 1.12001344e+20]\n",
+      " [2.00000000e+01 2.00000000e+01 3.20000490e+07 ... 7.60002868e+20\n",
+      "  2.88001120e+26 5.76001950e+20]\n",
+      " [2.00000000e+01 2.00000000e+01 3.20000490e+07 ... 1.12001344e+20\n",
+      "  5.76001950e+20 1.64800514e+21]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.25395631790161 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 10000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[3.20000033e+08 2.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.60000000e+01 3.20000064e+15 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 3.20000033e+08 ... 3.20000049e+08\n",
+      "  3.20000049e+08 3.20000049e+08]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 3.20000049e+08 ... 2.88000150e+30\n",
+      "  7.60000287e+23 1.12000134e+23]\n",
+      " [2.00000000e+01 2.00000000e+01 3.20000049e+08 ... 7.60000287e+23\n",
+      "  2.88000112e+30 5.76000195e+23]\n",
+      " [2.00000000e+01 2.00000000e+01 3.20000049e+08 ... 1.12000134e+23\n",
+      "  5.76000195e+23 1.64800051e+24]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7c18>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.43573451042175 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 100000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[3.20000003e+09 2.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.60000000e+01 3.20000006e+17 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 3.20000003e+09 ... 3.20000005e+09\n",
+      "  3.20000005e+09 3.20000005e+09]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 3.20000005e+09 ... 2.88000015e+34\n",
+      "  7.60000029e+26 1.12000013e+26]\n",
+      " [2.00000000e+01 2.00000000e+01 3.20000005e+09 ... 7.60000029e+26\n",
+      "  2.88000011e+34 5.76000020e+26]\n",
+      " [2.00000000e+01 2.00000000e+01 3.20000005e+09 ... 1.12000013e+26\n",
+      "  5.76000020e+26 1.64800005e+27]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.33890724182129 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[3.20000000e+10 2.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.60000000e+01 3.20000001e+19 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 3.20000000e+10 ... 3.20000000e+10\n",
+      "  3.20000000e+10 3.20000000e+10]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 3.20000000e+10 ... 2.88000002e+38\n",
+      "  7.60000003e+29 1.12000001e+29]\n",
+      " [2.00000000e+01 2.00000000e+01 3.20000000e+10 ... 7.60000003e+29\n",
+      "  2.88000001e+38 5.76000002e+29]\n",
+      " [2.00000000e+01 2.00000000e+01 3.20000000e+10 ... 1.12000001e+29\n",
+      "  5.76000002e+29 1.64800001e+30]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.34889626502991 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 10000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[3.200e+11 2.600e+01 4.000e+00 ... 2.000e+01 2.000e+01 2.000e+01]\n",
+      " [2.600e+01 3.200e+21 4.000e+00 ... 2.000e+01 2.000e+01 2.000e+01]\n",
+      " [4.000e+00 4.000e+00 3.200e+11 ... 3.200e+11 3.200e+11 3.200e+11]\n",
+      " ...\n",
+      " [2.000e+01 2.000e+01 3.200e+11 ... 2.880e+42 7.600e+32 1.120e+32]\n",
+      " [2.000e+01 2.000e+01 3.200e+11 ... 7.600e+32 2.880e+42 5.760e+32]\n",
+      " [2.000e+01 2.000e+01 3.200e+11 ... 1.120e+32 5.760e+32 1.648e+33]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ad76d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.54148292541504 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-10, 'kernel_type': 'size'} is: \n",
+      "[[2.000e-19 1.200e-19 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.200e-19 2.000e-19 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 2.000e-19 ... 2.000e-19 2.000e-19 2.000e-19]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 2.000e-19 ... 1.052e-17 1.052e-17 9.840e-18]\n",
+      " [0.000e+00 0.000e+00 2.000e-19 ... 1.052e-17 1.052e-17 9.840e-18]\n",
+      " [0.000e+00 0.000e+00 2.000e-19 ... 9.840e-18 9.840e-18 9.220e-18]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.57247352600098 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-09, 'kernel_type': 'size'} is: \n",
+      "[[2.000e-17 1.200e-17 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.200e-17 2.000e-17 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 2.000e-17 ... 2.000e-17 2.000e-17 2.000e-17]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 2.000e-17 ... 1.052e-15 1.052e-15 9.840e-16]\n",
+      " [0.000e+00 0.000e+00 2.000e-17 ... 1.052e-15 1.052e-15 9.840e-16]\n",
+      " [0.000e+00 0.000e+00 2.000e-17 ... 9.840e-16 9.840e-16 9.220e-16]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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Ke5hqTEeOWZhy8Tp2IO3K56t8LaBT8d5+R2IiAOLjT+4kkIyuNgd/12lU6gOQd2D9Qw2xdLbKInU20Jk4bYwsjTFW3qmXkYwjnAHtpkCsKT6k9oyFqPeWCHS5hlyc5fECaNTB+P4jBW6l+Bupd90XBZJ9tCheFmadZz+oapwnoAbevF5JlTOmIA8OuTWL2ibv61pJHUgGYPa825cOjGFP448ur9SLVY+rPx57dDJwnuhEJzqK7oVkAeBacMg0gGrvWI7FLZftGzeEsNf9mTFzDLo6DXT2Bry1GcNL0IdUsCB7xkXrJ0za3xQ1azNxqUbJbWJu3xBKMqx4QKI79PeRlG1HzfgOrG3tgjaJJ4/ZjMZp3LwPXLsx1WsUIxArNWk6zvzJZZwijV3FKI/xuudHpJ1r3T69/muge8EsJEbI0DexIfEqpVBLqL0apGWAK8BsEmqjaEBXD86LkdRERNMzq7Dl3M8siXOij2J49NGeoY4cq6pD3BjpaDYrMRUmtlf5OfJNq2wKGTAFADGUmJI0BzpbKQCrmh+QsACLOdwXPv9i0BegIqbFOJjYPAxtuHiNQI3SenEmx2SadSpmV7+ZZ8NE3T3qZg24DQD4K1/ax2YY1Z6TmOwONrfaflCdJ26fmVOIeU4y64AnGq0rUJWOHBc70Ve/rF6pECGdLzaLyjZChsmYd6ra9APiag7a9GW8LqmvdZq+ib1GEjiLxpYR0LPt/hwA4Pu/AmFWz5jNF0A4n8NdlngemXm1WdjfvqxJ/NrnwNsxA8AAQP5pG8H9IroXzOIgHQpGsp+qYCXzdjReDzsmxgLaMjJubQ9CDe4KoXg5rM9qLBJMD4+QWPISyBiS54GQnV/Di0FT5qkAql0ZhTGhH4rnJSbbi/3eD2oBr9eIuAV9pbmSeYZs5xpHfakOSSyYeHGMpsbmYVAGNE1qE9VDcohZUCzxHjZvGDBJGwtjuCZQTczqX9tfDthUmnPyTi7q6dhVL5YZflMbbWb6kqc8JsYY8nUqbxUZo4oR9PSq6P5mxB7H4p4H9t3G1wWSTQMcbW4+BZARZQ8H7Qa4YSwennRcA/ZrvCEC7PrGS0NT290L6P4yi9r7YWSLVHk4Wq9HZflNWAzDYeQ+uZIkMJUsKi/HdldJFqXP7CHx1U4965J3o/Lve/9ib0XyVADqoTDJgtLDYh6WqWSBqNLVngRgD2n98o5B4cyVhwIDt2qMPdBjekluIFlMd3aEoPMK+y8tullZD5OoakwHs6IWo6gnon6IzThokuENJQs7VmZd+yLNZ0CF2ZHVIsPSZeaBCSbDXOm2BuIZtB0Uv/G6JItrVAc5W0IcgUIVSDbrkmRRJad+gWQRzufgjYd0lbv7wJpdR/eKWTRRp5MHtsFdNGoEDksWCYtR2zyk7/f1uJtKFobPqCQE1R1VV5Wx8rffpWQxlQCMUdWp72znPBDunb9aZjDbtWvsQ913Ta9JspAJ9oIMolzbaibr04zndUsWz6+yi5eMIeoAitSTwV6JEW97xUbctWThuLh4bQwh3kyyGBVnIv52ksXJG3KiE53oKLpXksULQ9QX84y7MAyF/pB2dZJmN8oiK3FJovveu1kfDR9+1F7c7CCW/CaEYv2vr9X5Zkcj7zUatR9AJOD33tHu3n+0v2tMkt9Ivbu4oVwXSAFd+1xfklRFq2UD5d1LpgvorslUrPMAMPTNsWZ7oXceADEeh324RfIbqfJU2ry5CrM3j8W1SWPOloiP0j27JvmNHPJWVR4ZmSa/6fsGT+FWyyIhBG7nmBCYGfhnIQIXZ8Cjj+4++U1SU+XirBh6v/MBsPYZI6OTeEHyG5fwH828jveY3Ctm8dopSnGtAq/HlXQwnXqBnNMNFv+V6Rj3bJ3QFihrUv8O6MtwA5H0tVMUCKdPxOvdgXdIUqtACfV54CD9pKTivOGEQbrZ3fKaIc3pls/o/VJDrvMb14cce3MO9RFCWbBXpXjNON/UA3STOUyljkNSyD0ije2gfVvJmyROhuA6R8bUBnWHWdavo5vYGPboFcd7PyQLAsCuKU/Hq1Vxo6EYfuIHjzRxjYmD3quBqo49ANRAaYlpEtWqh/va9+mXQaHAspiBxqAJUQDg2aWKfrEEl1HXQXa9GpGqWA5aLfILaElk+Af/XGNoAgB0PlunedMXa/kYIEuNJfGfXGq/F6tsjKJhzEYp2uwgy7kaAifZnKTzjQWe1lvFCwxjntfBcwBIStojP/JDoKGFOWeLenpxwsLDbUfQENqozSGAh1DuQ22kXHTZ8m/niEi+Vt2PpL6snYYAPHmO+K//K7rGtoZjROyK+7Wx8qex8hBBUSNiw9LDP0nGTBGEpXo0fMI2RGbEVZfnxes2qYzOMcVlrPT++w+e4urf+QvoLnVdoyPEGcNvAsZFmRPbeZ15Q5L6FwQQIM7078WHVQ5UWz4CAhFix/BPd1mN2PzbfwG7dx3mT8r9CguG20R9p6Rcx/pz24BQjSs+OR5ncb+3mBOd6ET3hu6HZHFTqpOpStQdagouMlBWuEYtsB02ZRWiYVSXmRkgDYYbK/05BAU1oYIcp3DxLOkYnHhXwuhztKYIaDT/ehX6HgXozSWcrpV0Zho1cMhwTDlvxHDACBwn+mw/aNs4FlvKoXMAREvVthnaPpjymC1i0iWJgIZKpYsoUadGNbR6KFGUee2GsYRTjy2Wo26nUYFvvEluacMoBEk7swHt0jo7zhehMYKGqOA0orwrUxAwEaTjLMWQjOpKHiPgQ85aBQAyVFnCUFzOtBvgr0JObceeEUcHtx5AY2VwtxQAlsW9Y+3DzGlp7LxL94dZxwEAjkBjBHsGb/sssXaXI8QT/LpIFtxHuF1UMSC2kgVFAe8CXJXv4iY2tk8ns6jxBMRFxzU6ZgEqXbTRT2trteMUpTeBGR9BwgSS6hp53PvfhW0caFMDOtab2YwrgZeOHskNabqWVT7L/TWrcAcsgKFaJ0AfIdmf+23HVn0K6b+8GjlvSHkptUJa8vowlXwSKC+veVHoGg/Py8dVX5vK3/UyxBY7YmoCSFUme1Ty+Fx5fq693wyIA5of03WFCMRtJnA6mAr5eLq/zGKaKLYGEnmvOTOBlM3K7dV5yAjIA7kmAEAWCTFpNovVQndry3Ox2SLnETDAkmN14c66nM+AAMj5qoRtW6j7+VKlBZsLVP823ZzXff5OQ0A40/H4lGdSVnPQegeZuQYNSCGU608zUHe+yVVAKV9DgyY8cA4AULIXje8sW5sFKhuDYYFWHm49gnuX4wxIks2iD3lHrMPX49l8zz4hZ7OcXLaOVwDQtHMfwDGif1dd66b38xARZhVz9cZEygvCgwOJHjuuHOY5bF4QzjqEWUGLSrfAeObBQ1T7wFVZq5iuw70eO57pui36EesvdZg/NYmBEGaM7sphWJWxuSFJcGmMYUaAABzS+qR2TuUihahBcw7vzBE7wuyJz+u4/uIMm88xltUajAuC31Q2Cd+ymW4TMSyreJGuZewvovvLLIDGwLkf95EWNSa//lSaMM9H7S+v+shirkGhk0icHzTzzDRitWg2JaBiDim7Uu4vian9uGfgJFNrAL1eFZ/BfSjXBIqIPwZNxkJVX6aaTI2VIs0DRimbFg1jUXkOnFOPm7dDC0EmyshaqXZP7kOTRdqYRaOaZBVFk67sQZtjzA8+T1TFup2GAPQDeJvWNon3FNR4aV7jzCy47NQ8iqoiUeCYyhiCiuSQYrSkIcKna/PEwElDa+DML04/oFvHrArEjkEj9O8adDqq9ywzupFAAUUN8frFmFGdsFeY4HtlYLwuOInuKiLMCX5dPdeB4CsDZ+wqySKogZOqR4DC5L15Ad1fZsFVsBMwkSxcm4NzHEu+TEDFYyGFbjtXINw1GMl2VBOPZ52Kg4skMVw59STUL6l32ROSJYt+0OxKlmbNvDczXyQj22Cdy1Z1ro6lGBGWnWYySlmP4szrMVX+RQDqOZl1mpl6Ks5PJAuMQduIsgRx6BwApd7nomvsP1J5Q8xmERYOzhPEMeLcJAsB9Qyuxd4KEBXnHuRbbwiigC3xzFSyqNqZGTTrEJa2NpVkMefywlkWKl8Ym9tF0MjgUTBcOHBfMqSFhUdYMLhPa0CUJAtWyaIaz3WShZ916M8ZNNrYCOOcAHiMlWTBY/J6pE7DnDQbgo09Heov0/PjuXiPHIHSi89DlxnXcO6we8ioH9Ew1yxhkrTEUDk7KCZBs5IsmlIBL6GTN+REJzrRUXQvJAsiBnUesqvEWlJzjFVgGt//IP8mfV/UkISnQAiaCg8AxoDw6CNcl/IOAPAs4RkSdJs2W/U0XKUdznZckWKwE1EchaUBBDR93uVVTqOXK5N9+GQveKgx8tVBSQD4Sdq903V5rfU7KF2XQglqou0OePTxgUA1alKmWdh8DT0+dA6AXMSp+/aBKld1DlEgR4c2UZ9JxZLFvM2+nebqprUtAOCjx/k+umsS9roUbBZ3OyxszQ1qH6XU36j7NWkMUDUuqYNz74rkGATuUu9HjtL86Ak6y/L+koS9nUUdX63xLlf5Ook0QnUY28zjlvncok6dK1nbRRDOFfpu3hDh4qUBA/yhPnd1wt6Hl5/HxbIDb6soU0d7amT+ut7mADgjd3UYXn6I7gWzOEhVxmMAaELWrVIYkhEvRG3L+Q3x0oS9hrXPN9ASnNZhxWYkNcbkj0/Yi3mp9CSNpfwAs7AHzHIyohLVLdFrnX/CO2A+v5OEvbJatPaf2jtj4CxO4f/9WNqiqh21ETc/tNVLART1yy2XN0rYG88X+fqAMj7pHGB6d1b3uAkB5+0AECHOfRsazoTYObiUxt+tFrdK2Du+u4Rbu3ztOHNwm2FSCkDtJvYsxLkv2b2BDJQy46R4AvVFDek2K0wT9g4PlxgedI0hFpSYhXlbKibsOvfpT9gL4FoD5bVp9dJDLyPKg1VjJ156vepBTh4GxVmYMVSrk1EVI0AixzufKmMmxbIz511xUjdE7BwzkAIHkZA1PuNOyHbAeh6JqWWjrkfOmk31cSGq8XecjNsYXIXJuA1lHd5MDMYkskG1xLkYg6cxKiOTCKYAMWNmjBDP4Ch73p8bjyvEylAYk/Gyxf5QSOOwtUzMg1LYQLZlJaOxDCjnXwPTphDBg4ArSWKaC0Reo6Xh/jCLl1ETDFUiGEEJlDWJdHxZ3ZBSNiDVudhNxDHDONSxKiRH1w1BVduk7Jph4i+3rDrJTSZSpblLv01yRmYmdEflC3m6DtNM2kCJuB1DVd9ECtMz6ab+bag8PSYZ3LR84bbfO5aGyhBuL2JtEI4RtBtUdRodME+G7TGCxljg5IBC929RN8Q927V1Q1JKPtdfr4ZQUkOEFZxlQm8GgrkyLrgIulzvqSHucqcMp1JDwIlBHsjubWrIqXzhiU50ojul+ytZvKjIEDvUJQWzDaEyxL3UZtElndOMdFZtvSrHJ97pjm/nMR9vs5h1Bw1vWQ2pU90hGTbrXd/+Fk7h2ybCJ//XXdksFvOJrahCdFboQkS0RjzDpHhXCvxUmBXbQfP5APiGNgtZzpvzEdW2k/u167l2nc3oK/PyjIgTwCWbRTqfb2mzCA8X4GSzgCN1925cE9iWpdTKJZxtFgLEZLOwqYlncOWypvN9m8V4PsfwYAa/rqRJVgxMlsiqtHqfCZvFwezel1qqLlp27xyFuoBst0Xs7zr93nWIT0shIn7nob6Q3udUeDlxDVDSyFlE6WKuAKv08MdPngBd16oYXafeGTNIAppSbbkArtYqgq5S1awx7MVhwPvyMm93Tf5LEn0RYor+5PMz9eQYMtXWZrsFLRbAw/M2HoaogS4DKNGmVlUbSXyu6o7aQ8/JsCkxNuXvAFRp2FL7fAba9Wo/qVPXj0G9TNNoWwC8mJe1trk8PC/jcC7HM6Cy6AuReg3OV1WsTRunka9vL8YoVexOLMcGBn/8tMxrMQN7B7pMEc2fe4C48KBRcS9m+ERErhpmqkFcdJDOwZ2p0TUzLKiniKQYM/UESfeo2iAq+4LbJC/aJ1d7awcA4XPnSZVathupeaasz44r5k7NhrT56hm6yxFhXjGXP/ysIDivoTo5r32viyXrD/bkVVQtak64aw3gPOn3AAAgAElEQVSzTh8w2zG4SvdfXcsYRQ4ZH1hvel1SD4DMuyb/IYAmhFw9B+k7U4Gfm/chJZc1AFpmMi5laOp8i+oEmhB4nW/yrkglMdluxqW/vDYiGip/Ddw7d7vodIOchKhjCIrKxD7V62HzjgvfQsAP6NniGRgJNAbEtEYlXLzdvafj1GNCPjauOtBlQSnJcgZxDpwM43HhEZYelODeNLPylYLoGSSl0llcet3F14ThovQZO0b0BO8Y47IKUU+oU4NfX5ewl9czHKKw9IiOFGRmksXKY/fQAbFKw7BwcPWaVM/DuGAgeoQalHUDQ8T9ZRZ7CVuqWJEalWnf6yrqSEwkUokdAVojVRXbAegOS6jES+eK6FlfyxiFHWfxJJb122JDEiK0oRphmdCVgO6eMk/jyQjQhAqdMrG+V5fuvGvStoGocVsC6i2IM5+iKyt1oXZj2guRmIoygnbtp+jKcJakEebmN2ZuPSQ11euRmUVXGHKdz4IAzoxFDX1uCDmHRI2mjFVcxKE4Bx7KseOZh6/ym5h0wDttC0uPceXAA2vMSKWO6d+A2+m4hpUHGHAbh/6CQQmaGTtSiDVTi+C02JAEvw7p0w2T2I1nh/NLjCuX+7Uo4PHcYfeA4YaydsOS26TiFdx7OGMIA2MdG3JCcJ7oRCd63XR/JYtp0ldzGTpNjmt2BLMpyOQcGRTVKcNQMl1VqdmtClXWo4EcFGbn532luhbtenXXGaZj16ubbbvLRiUAoOfrm9kskp4f0/X5cq19mu0j/S79AKy34MruoBdU1CJNbBY8eO077YgWZZuNmEMl6YjAfXK1Z7NojKZQUdlsFvVvNAZgu2tdjvZbVaDH5u2BYhD2LkdaNihEouz+9I9bUBeFkL9rHwf2vspm4a46vS+JXDLQms2i6xzclYKl4tyDkx2BROA9K0DOkvuuO0TP4HWPs/+PMxJSvALCeDuiW1SgrIwRMaNlUkMmeVius1nM07lc5aLwa4Jfz9A9K+7u+dxpgFyiui7IcKEArjDfj4Y9hu4vs5iqIXUVpcr70ISib3fVMTN9+WuvRFVDg1YJDWjM4XyVg8IAAJdXpRBRdS0sF3oDTI1hRrxYatRkil4FALlYvTCEPIePA8AwQsxQ9ux5GQ9QCvrk0osBtFogPliV5ChAym3Q6vC8HVRd6cds+OTdoA+sQU+SsYuhL3R496yJJgUOqyHuqgP3oVVDemUejRchkZwty3qkeY/vrvLLErti4BRHBZzkNKDKXe0QLlKI+o3UkJiPHc88FlUBnnA+h3QOPqlH/edWqoaMgnHF6J4Zs0hqSBQ4CyRLasH8Y8b6yzPMn7ZqiF/HI9WQ9mVdXpOLZfvFpfa7Kfc8LAjrzzmsPq4YwpLR1cdUasjuIWP+zGFY0cHfX0b3ilnURYb2JIthUFDKOAI9v1yy2O5KSQGLDakfYmNGN5QscLXW3Tt7J3bKKHa92g0SwyIrNFPT65QsrOhNTc41Own1gwKEarRoAhyV7FKJeV2uISJwjt+cZFGlAHD1NYiKR8UlO8iuL8bQO5IsZp7RzTtgjOgWvnhDRMsIZOAcAHelxmT/ZIOzKHcuWSwluVBrqWHubiRZzJ55+KsxRwoDyMzvGLpXzOJ1U86gldLdE8kegvFWfdaUK4ElA+zbykh9KPtUHlOLm9BAsMl5RDl4722RFf7VkOzqxa8RmXc9BkpGb6aSQUsUk4Gx8tTwvqv6rseV6QZGyaaP9KzKLR/Re8Us6iJD02IrqlaMcO+9i/DR4yJFWFGbENuoUiYA6o6zkoL83jsJix9zFu7s509l93I+inGsYjPKtWS1hObGrIrmDmO2WdDFuZ7y+MnhCM+q/zoSlJJEYpJJBLI0hRgLIGrQcdKsayWLlBqwYWZRc082GcJ2vXqKptDrs6Xuco+fZAmvXctqHgn7YRG7ue8XlC+s4ek5PqLut09jF9Ex1XMTUfXwoyfteVHa8nwvKV/I3kGuimSBdSoQlXA43HnQVmH6vCvlC5v6q5YkyKlXTBadRuoeKF/ILyhfeG2RoSrDfU3OnpXlLMd7+A8ew308a8oXYlK+sL4//N4D8G5Q+4ut2Xi8ZHHyhpzoRCc6iu6HZEEA2CFeFX2NLy4a5GFM3H/87vvwX/tqRmDSfAbZbFTyyMFcosbMQe0CtpOF9x+V/n/wz+n5KchIzpcNFNZ9+ETDzEXKrpGAUjKvMmU9X2uND9uhH+vuF/7VH9gzFIZZyVnpL3sEy185RIznCsaZfecTnefnL+Aud4oz6MeMQ3CXW8SLJQIzeNcaEuO8ywZLAHDPtojzDrwbEBOOg3dDo2oEa//2IwiA3Te/nrNB5X6TEdHE1/HcwV8GuF3MlnUSNSLybixp6qr0euP5PK+HzVuYtM4IkoGzorqdhwD30XOsv/Xn0zwTXLyXXG8DqIx1TQ5OjezkQTCcMVbvl114PPMIc8L8Y20LC4fx3OV+/WW5f3uZss51vKs/vcIHf+VrmD8xQy0hzAjdVcRwVnkdemnGGGcABGATUNObeP4dy9uKrCoK6ZzDjDF/PGj2bgCP/+L3Y/NFwvJRuaPDitCty98VXgtCQHclGM7K+ozfPp4F3A9mcQzV4lqKFcjf6xT6+fiQyglWId11H1VUJwlpct2JITB/VunhMI6KuLQHchybtPx2Le5DMciZ2E1URLmxlB2gkIrz1AjTISZ1JzYlCqyNJOx5W7i6PgBgGPV69pm+T8+x9QJSjsZhIsZOYlzEEdwQ8wudDx2Cpt2v1wvQ0OwhFGOjvdMoIdlTcbxu17Uc4VMOzpBsUMoIapHavohmvQbAOwEHAY3JJZtVS8DtAgCXQ7xpo/PlISKOWiioLI/dV1MnEsPaDfBrgd8kb8cIUID+XcUi8aAQcDZvyKh2o8wQDP9nOSxqZsEABwIPAr8p96dbC8bnyNe2eXXV37F+w0UT9jZrdoN0ASc15EQnOtFR9OmRLKZkrk/zQBBV2Iy4L2lc20/lzQAK+7T6HLEYJW9a70KmfdZUtxGlOg9og4+Ytd1iUupj7zIBTm20rNYmB0Elj4pUgVG5iA9QvAjZqGc4l0n/NyzQu1+/JBVTnnQjrlpHFoild3Cty1JIE9vKq3qwqP1+MN6CAKkPpPZYU/Hyp+csiVnC3kMkTCUiuRqLJeytPR/X9XEsnSSLE53oREfR/ZYsmixN1XdXuYesmhgzcgg1oHkcaCyfmOwgFsSVAqssL4LUUsS0XyLA+7YAsU/fLZDMjKkzt4fJkLnLhjwaYjFGDoDMGBIrF1nHkIFyaHTJf6ltkdwep98zcPZeDZzpN2B/d8jtKQo1LBy4r9cdCF11bShyEKKIxoygjAIHaASwpQGorqbFgtL32phpOSmnEaN1OxOo07T92pdJOtyUAjB0pDQ7NoODQAbBOGfMrOgO67lhzlnaCHPGuGJwT3qNWMaUDZxJkjJ0Zpx3GFYE16c+Ok3Hz4EbpCQPhgS150P/zlkcnd0PMyZTMZozQbyiSHkXc3LjYUUYzgG/qQyWy7IGer12WYW5MXC+sahTIvoTAM+hb9MoIt8iovcA/M8A/jyAPwHwsyLyyS36bqTLjEkAEkingGNA+6Adizato07rl7eECHNmFoixwKUTs6hLxwlThmnXsG2ZVchMq78xO/Ayd648dB3nF4Sj5Beyy8zCAZyg2WOVgJYoowSnOA6ZuwadxzMPmTtNbJvaD51j8wD0hZmCduoHGNBQZxqBECRXBMu1P0eXQ9yb5DcdF3tnXUk8LVKdY0EHX7Uz4CpmYS+cY8E4LyK6tUsS8fP4heBYEOaUoyyJKXkYKI8nLByGJcM5QZhRU4wnzO2a6UVNkZsydxjPCOPWxpCYxYiGWbi+HWOcQ70hg36a1yJXWGu8IYRxQamgkMvP/rAijGeC8bJiFmcoyDJJXpdExhiG8+o9OD73zWtRQ/6SiHxTRL6V/v5FAL8rIt8A8Lvp7xOd6ESfcroLNeRnAPxk+v7rAP5XAH/zpp2I4fBtp51UB8/GsTGo228ShyF9n+JIqNQfrfrgTcJpjIrl4HXfuhiTy7SOk6AQge1ODXfWvt3prmwIzHQtf9mXQC/bLIYItizO26HgEWKEv+KmvKGWqRNgO4JCAG0lj4G2o8ajTNygrvfgOv381Rau11qnzqpuHTjH1gsAZk+H/YpkO4tnSO7C0cHtAngbclIXrUgWmxoWtQvVXRW3Ze4/uUUBgK+pdcqp1imtt5g9SUlqqopk7qiKZKJlDKPLGAUKUXf2hcClMbtd0DU8otaprZt7tsXyw1XBWaSKZLPnEX5bBZIdWZGse56e1UlFsu4KqdbpkF2nq488QIzF4ypw7EpxFtdWJNtEDM/rADccTa/KLATAPyQiAfA/iMivAPiSiHw3/f4+gC/duveTzeJkszjZLD4bNgsAPyEi3yGiLwL4HSL6583ARCQxkj0iol8A8AsAsMDqFYdxohOd6K7plZiFiHwnfT4iot8E8GMAPiCir4jId4noKwAeXXPurwD4FQB4wO+93AM8RXCWjtLvdSIYPhrBqVWiEsIwVOhDAIdyQh6L4KQhloSyduygxky9bgRMBIyG2CzHUogqBth4rIhNSgbD474a8joQnLwLbWVtKlkFrUq525KK9UPM6e+sGrmO23otKgqPVeEfU0fGeCMEZ1YhLIp4jCmhb0JXjkka8VQhIgXcaxEgXhQpBEFzU4gr5/tNuB2Cc4OcZ4KCGlz9JkKqnCyqBhV4NwUCpz7r3d0qxMOh5O10aR4TBKffCLorgt9WyN+o7aaGcHW7KbwagvPWzIKIzgCwiDxP3/8KgP8KwG8B+HkAv5Q+/96t+rcEvFZkx3I1DtDs0kgybeeBIeXErCIMaTZrPgEArihoskzyWa+Zo8LZDNwHhGUSy5+wZm9CsfRL50EyhyxmJWfmGCBni2zbsOjR8XyW4dDGWGTGWaT3VwwxT8IQMVx0+pA9TerAaga37iGOwX1JjEshIC46fai37YsfF77xhvjUxtsRMeVWOHQOAPhPdD2Gh11O1KJjr70X2jYsGX7L8J5y8lcKAPcM74oaYvklSATjWZdftJypiSlBrve9IXW72wV0uwG7d3QA2RsyMMYF7ashXF5At9PjeBRsH3JOm0+RMZ45DEvK9ocwY/QXDNerN2RWJdbJ3pCdXqy/SN6rZwtsvkhZfQ0zVdPCjBqvA/fKLKyfsAAoEii03hu/LXEzxrTFEaLTc4UoQ8I3X2CsvyJNmPy4ArpLulYN6S7bccXDKT8P0qtIFl8C8JtJL/cA/o6I/H0i+j0Av0FEfw3AnwL42Vv1/iJ0X5WEpKkYdhNEYC1tcGlrkJFWRaq+1k0oJ/NJp9dCi0j528IIojQlCylIkS7s6Q8RJLjbvBN1jEodAl4JdJruvmqzOVT3o0nsYr+hIAlfeQ6Cxkhon/VuWSq5ARxQSTdSzr8hkvTQOPK16zHVAtpkjPY7ReUT2TyS51CqlCHI4RwWVR97bel7bQS4bR4Lo1szCxH5IwB/8UD7xwD+8k36OlRFXY2YY6mi/sGH5RrbXXkgd73mVlhvtRALAMSI+MGHkBBBm032gtT5LvwnlzZgwDH8JlUtv0qGz84rnqOuFA4gfvQY5Dhn4Y79AHr2PGe4snwUFj0KVJZ5ooyjQIzZmAkilSiqwsj+ecq4tRnU02BZm8xz8+hxVh3ykrGDrzJOSd/DsQNi0E/g4DkAEJ9rOr/VH120L8+Bwsgrg3PfoDDybDdmZpELI3/45OgiQ7LZ4MKMoHWN2FcojNxdDm1h5I+e3bzI0JPn+FL3tdzHqxdGTv1PCyN/8AzTIkP++edvVhj5qt8rMvRnz0/lC090ohO9Zrq/cG9usz7lehoxgBbzkmNiPtMcjfNZY4iksxXQD5pRyo6tEvrKRZJCLLflag4aQt4NeJ1ySQAlp2TnwednWgPDKnldriHnK/ClZjgyiXD8/EXGUeRrdpx3XV4PpVhOiAgrzZ1hEsX4YAHejWqzGELegXg9IK46uC+8ezAhcJzgLNSmMzbJgafnAMhlDfsvT8ZNlA2bNoZx6eC2ms8iu04FJfO0qRuxfFrxHlsH/XwvGzKnSYHrdu4D+JPn2HxFs5CZDYVHUTvFAZuF2QC0yvgCFLRehl8n21IQhKVDmBHmnyQ36KLDeHYczmI803VbfNvj6Q8tMH86y2MIM6C7mmc3po5V18WKDBnOQiupI7szVx8WO5fZjsQBYfXeHs7i+deX2HyesXhc7vk4J3QbKTaLKiGv6xeKs6jqhoQ/OR7CeX+ZxZRqhb9OG2Z6cQgAkmhIlMsFCLBf4RwoqcgkpUxbqxqSl9HsE43eLTmJLlVqB6GoH3Ytd7krfeSUeJRRMBRE/wYUzrzuGy8E70bVf7djqrJd2RGG+PJSA0BJClyVPzx0DoCsRvknu+Za4igzYcNCuJRXgrcDaEzMJsQsvk/VEIoCdzVk/dk8C3XZgWlS4LqdxgBZbzF7WkR9/SKpZmirhkTPhaH0UUsDEkCjz/o9DxEcBJwMqADgH1/BXWnCXnguFc1RVKdcCuCqJD9affgQ3WUCjDlGWDC6q7ZMII2S0vOZ2sE5xwYIGcBlCXdix9n7EzvC/NFaEwFf7fLzv/xoDgoes0qVEFYDqKSyhnURoW49gncB8zokYLKhvYjuL7OImlz3oE2mrnsBJCbgGkNkU9Yw7GtbufzgGPQmzhTolRPVAEUXzkhELi9kVRjXMmgBKIyhc029TgCAL7o0tmPJRh31JQOrjQLQF4K2Y04Um1P5DwME7qXlEQGzIXh19ValEvfOQfE2hYXPyWB07MVWYUwjzHW3lypGx9yEdf3O0okWmS6I1nROVSpxr/Rg3T4E0HaXmVVmBCEiegK54jK1cWZQFgNx4fKLyjY21n6Ei+EvLmZa4jCVZeQ6lqgqmQggV0ejyw7jkjUmBmprCDMGBdeUCeRBDaom/ZhERDF5ixba7teVjah6bMPZTKWdqnbJuGKMywIIA9RTJPkRoIZZiOvgOs72Eb3G8VbP+8ssXkShYCcoqsdCJjU2JShc2z6nRCaOV/U+qDIwZs9IzZRSOnsByrXGUdWcseoPavwzqSTXL40RGE31CM24uNe/bVfnIej3UbQ9T0y0nuhu2JMSqPamAKqGpTFnr8ChcwDEXKB3aMZFzBDbfXy1NgkjkZcntYkvRrwC7xbdwSb3gTZ9gdOPhyULjEmyGAN4l8o2WO3ZKFr4JwtwhuwsVdS5yujlgawnUohwqS9jjrzt05pHwIdWshhaySIHzu0G+KuY1RvxBBoFft3iVTioZBG9BcMVF3PtsTApJ6ZsZAAggeCuerBn8LbPG5O/DJh5ytcGANcTeBdxqIq636hk4Sppgm7gCbo/zOKaQcuBFz1nvAbybkcJrARA3YtHSxapDys0bJb+MFQMycAzcjPJYpKsRSrJgrbVjQzJqi+cvR7CqToXszKK7EUR3TnvULJoMj4T5QfcOFac664rUnZ5ANpG7cMPqGQVPWeAUK6dcVPJYp48VUmCoDHBzU2grGwrOYkMlxc4zB2ceRuYsrqSPRS3lSxWDA6p3StUnKStKWqShY0xpGMoavu4MDWkMLwoBv2+RrI4c+jPOYO3tF+G85S9IVnaAhD9q0kWJ2/IiU50oqPo/kgWU5JWbK1rWTSVxcZRxa1xVI+IHbPdtarIpA/aJIOkiPqvza9vEkKqt0GpBigA7Wu7VVUlRWlKPyi0PFcySxGMl9tyXlWYpiTpjcUHTqTXDzEfy+tU62QY0ADPRFTFeXoJmWAmwK4xFErfA+z0OC7epOk5tl4A4D5Zt6qX47zDmkTgrtIc+hGUkaWSbC+uQZvab6p2pS5ToBo/fp5xC3QNzoIqnIX/ZJM6MLEhSWRTE0lXJDgeYlYnrFq6jinC7bT8otU0dY+fgS+Pw1nwZerr6SWWHzyEu0rHesVZ8HpAVxs48/pYMFwyzBrOIh3r0liaEo6e4T98voezWK5m8JtZ47WxjOlm4KwlB7ce9nAWnw0D5yShjYnPEqFMwXTvrlOdvKtjcSm7VxvXaV3ecDnXQw0YY2n+LcX/dqdw7ypsHJ0HLRatGrLeat1UK7ScHqZ4sXyhgZMmBs64ULg3JzVExeEIgVO7DJUXNM478MPzYnexOXU+qxUAQOutqiHDWNSNA+doe0qH/+6q0bVrA2cW12dObQG7Mbs8SVCygtsDmtQ/iVpoOK+HqRxyUTKgT9SQup2GAAIwvLvU61cGztBx8bLUaoiF0w8Rru9AUTAufbYJqFrCiDNG8S4+aNWQdWWzyGpI8lAkNcSLYPPlObrnRUUKc4a/8gcNnNkbYiHqQFJDtH3xuMyBBzOaMkAPVA15ustMePPlBTbvOiyelrULHcHvYs7TWhs43W4Otw2NGhL/3+OVi3vBLCRGyNDnKucSBTFVZjJkodURoflca4akOiKYR6AfIMSIjwtq0n3h81rhfD4DNroj0WqZLlgZLodR1bsUW5IDyR59DMyVoZRrzYGH5/pSWmi3c4gPVlp7FMjFlAOzputHMYZFcmXHixGREuZiVClDAEVmAnBfeFdrksw7rW0yLzsZPzxHeO/8YAHjGq/g5x3iwoN2IT/shmbM5yQ7gDdDZ+fAaPut62UC6vbjIUlGJnWQMnT3bFuYc00Xq1znxMLi+y+cZdxCXeBYCMVtOGNwH+FnPseU5DomfXteXUMk9xUJ49KB+4iwIMw/2FW/qiRqUsH2yysM5ww3aAaw7rJsQHGm3guLDRnO1JOy4ncau0GYMUIHUGT0dd2QtCSWX8K8IjwpjFwbKzPtIq6+b47YEbqHPp/TnzH6h5QlNR0XIV7ZdSlfBwCGrxC6y0lh5ANrdh3dC2ZxkF5kpY21N6RElx6sLRKqdldcrnmHNQllGHUHrksKJpG9vpZmhQ7FeBmjWs/rOiPQaMQXRoVOIkFzgJepCSmSlZjKJ1SNoGFs6pIAKr00dUkArU0yhKJiIWEfKtdzU/JPBLwb95jQ9F54T+W46jfuQ17HKdXrYVd0267MQVwZl0GWAXCKWEWQDIWuI0BjJQXFcX+XrKuog6kpzCQdg6LLbX4bVPxP5xjDUhenei+MuQkj1yHpriL8Ol1nELhURb0dR8KWvKSKunl8puQ3HWQQuG3Mkt/sStPtza5q78b1VdSFWQsQ1TErN4g6PRk4T3SiEx1FJ2ZxohOd6Ci6v2rI6yAzkmavA2PPdH7jPmn/k6vfDlTyviuSyvZwbSEj5j1ZUxwBsUDNgYTreMWluRXxZB0jJfEeuV3qNb5DqosY1VgNAkrOCVtyQlO06E2QFXwSf7ydoTm/mDJuRfeXWRwCi2QXZMmrWefaPJin03J0Tih7AUzn7rzaE6ydKLsV62uJYz3WrPeONW5gUrXMcl/WVOfItPyYQHpHUhKaHEqe8npK59UFZl4OdpDOq+vtBTk+AbXcx47BscRrSIwK9EpVrPI8EkQ6zv3e2k/zY45LpxmdmPbyabre75UbmK6HzbvO95kT4qR+8nme4BiQrcO4tDILyVjr6KUGTuufHWFccb62jkONpry28WgOTtdHjHMCL8zTowZPqrKmjUtGdISZJwxnnG0PZuAEcJSBM0xsFvP54VdyXDGiB0hKiYL+jDFcEPoqMfBwRk0ynNrAOa5SiYK3lIPzzqipE5L+zt/rWiBVfZDm5bG4BasrMiV7+QyDMfOKmLR6IK5gFpprcarZYVgCZvXrW1k8G3eq11FTXdfDanoAavS0dstHEa0WSed1jMbEfGEWe8yoqksCAJzGJa7UKDEDp43N0JmWWyMs3d4uPs1iNS4ZPOpxzW+s8zpUWrFeD5t3XaMkVsxCiLLh1Nqdo+zyq2t42HfgsGXfOcnHDktuEhpr1GlpCwvNvCXMCHNCSIyGhFLfBJNM9TiNvRjOCS5lQA9zjTql2CbGjbluSPo7jZVLUfc8pkM0LrRfHhnM5pEhDBeAX1cej/MJo5/VzAKgkbS2SKKbMIuTzeJEJzrRUXRiFic60YmOonurhsgkzLkuOpQLCAGliFBPhwsRWREiINsgAEU35uOg4j31Q0mGk/rM39O1aBgVvBUKXoO3g55bBbO5Z9sXFgHKBYAAYBjzjbBiP3S1LQWN+iGDxaTvQest/LwrId+AhrdXRYyAlG9CEix7KPgP8Vyg1xWUnaKge7Lbw1nsFQAaOrirQZPSVL9xH0BX2xYmbXNPkb22DgAwq8LZ4y6pP3ECdd5psR3qR8w/SejWKhFNY7Po9ve+Gmfheq/3JZ8g8J3LbbNVB+4deBS4FaN7lqJcpUSJWrJcHhxiR3C7iNUHAfOnlodCgVB+HdFtJghOVLaKa3AW3ZMdDtFixtpvhaE4eySg4LD6uNyv4fn1OIvdljF/JhgqtYUPwzoO0r1lFlMjG1HKoBzjcQZOn3Rn7wqTYAKiRYXe0sCZcnPmjFqDojml84rdN1vAXRs4F74BZYFTBGVlnSdJ+SkqyLauTYnajYs0hrVX5OwbNHCOSwceCyqzTtjirLqYI/BA4LG7cwPnuHLZWNmfKWALACioPYRDSV4znDmEGeDX7o0YOIczTtXMOHszhiXdyMDZP1CP11ghOD8TBs4parCJ0TgGwTmOmrA3xBITEjkFl/CtEZyKDJUcXEVj0J17DACXfBJ3jeCkXYvMBEX1etTMoh/Vvmv1PABwP0IiZwSnwdQtk/kbR3CahJZeRAoC9lRS+5GiJGkId4/g3ASAVAoQBlyuBSKgwKBQJAtN1U/g/s0gOLt1h+hVsrAXnOLNEJxhxuiuZJL9/ODlDtL9ZRYvirO/iev0gNsUEm8tWWgJwxJZiV3i5BN8xV1LFnJA5JZu33UqXkX97Dodk+s0Z9pO65PUvDcpWcS5268l4tWDxVVwmBvUQ3LnrtM5Y1wynIsIHcFZ8Jjfd52GRcpCRXgzrtPlq7tOw6TE1I0AACAASURBVIIw9rd3nZ4MnCc60YmOonslWVi+CWLaE32tfof0fVOS8Do1RIaUdm6o+OHQ52NuHUjWD6X4UOqHdykVHZFGxOINBJJthzajFRRwVbeZeM39CLHkuWMEnGQDp9k9KBmE36gasvFZTaDAOZBMuBg4OVUT520Pv0kSyV2pISniU8sdAl2VJ4IHzSliJQejJ7DXRMTdVXf3asil16jTy1Ayt3l/IzUEYMwuY05LCAD8mVBDpnRInXjh4aT6O1WgLGJdnUMgrWPJOc3rUEODPSs4i6mUWbz9FY4jomZNNO9ki1YVz5pDI3IRTZ1WiqekrGYbh3PIsv8bpJL+Ls1HdNy2cQhTQcneNVHJhRFmxchKAuwlkyGkFHpvYFyw9dH1qlWvm1Ds0vzqQOMbnP/pYRY3LR34onPkBux0Sskb05ZP1E+KOKiv3xk1yYQJxNJeP6bx1qUEIpRRTEoJ2nFvi7QkY0q+G0oYNYnCrZuC1Xc6Dh0DV4mA69KLdflBq/vxpsYlibM2hatvQvacVnUMb7IFn2wWJzrRiY6i+ytZTL0hzpX4kGO9ISEWvAU0a9Ir4yxmnYrFlsdw0BgP6b26+dhiBO4YZzH3beIaTt6QCk/hRBAXHZg5ez1o0HoftmsGq67e+TfuDQmLYrMI8xTLk9LX1ynxeWTQ7g3gLJYOw5mD6yP6c26KPscZJReqNg1nrJXWF/4N4SwcolNpxtSIm3pDhgcEDpOYlZM35EQnOtHrpnslWfByAUDh1TKxqJP3kHGEe+9dxE+eZGg39b2Cr/q+OSdDtMcxeyjonQcZ2CUfaa5LK65D63VTMT1utiDL4F1di1cLIEopHDQGMAC6XKux80zzfPK3H2FasZyr7NvS9+Cqsrn/JNXKTDlHKQat0O4YMdVBAaDlEoc+58zM800GQlcbgmMEr33rvekHnaOl/zOJJUW3zv74UalgbjQxLs4sCfKkwjxCULj69HwA/PQyr4fNe759J3tTOqdGWIqGDalsQlCj5/IPHrXjmVz/UG6JXB0tpGTMT56Xac1nKiUm6P8yfA6LTrNuL1ZdzvpNFtYfQpN02Kqyf+7/vgJtUvgos0Y81/VlgVL8ye5jVc29Ge+zq705AIBbvwOQGlQNY3P+B1cI53MtlWlrMPOa/d3+riTN3RfP4K/Gpu2PN8fbgu4Vsygp9w8YcFJpgINFhw5RbB82bYttxa7bUJQMYLL+yUotJrQh8Aa8IenaRrV4WtpEvQr1eKOo10Mm6xPegoEzSjuHpiRl+/3WRr0bjQfZCNiM59C47JjxzRheEQFwetZeYS1I5NbP5v1gFgSAXc7oDQDunYdN6UGraxE+eAT/9R8oFdGXC8jVGrRcgK42pcv5DLLZaJX1VKw4fvBh/l1+5IcAALzRALDxnSV4O+RYie7bH0NWCyBEcJJMZDHX5DHLWT7OfXKF8O4ZnGO9CY+fAAB23/x6LiBsFBYuIxVnT4ecn4F3AcND7W/1RxcAtJq5f7JDWHi4zZBtC+6TNcK7K83CPfHJx7lv8iF0T7SKF+/GnMX70DkAVKIA8OzHvlYS1SayallG/YX66/0mNr/5rZbx491EshBgeDjL62HztkAsYJL8Bmja3S5i/v4lPvm3vpraEkahF4xVPouYckXkrFYA3FY9Kq4X9BeEiz/7XB5T/8AhzAmrR2Oe1+4Bw++03/mzCq9g10zZvXcPdLzv/sst/uzfu8DyI8nHhQUweyroH5SxufS4Wj6LMNdxaXV1pLgP4OEfv5fnkKHYBPRnhDgDlh9F+K1e6/1/c4X190WsvnuRrzOcAd1lWcdQSukADHTP5xjK4Rj+5fGWiPvBLA7RC7N7V7tgjHs7FICS1TuEg33lIKxU7IcGFTGbor7TfkU0BmQIJfX/GDTa0qJVYwEMTetocF+lagsxG9+0FqiCfgpoTOuecsocnnewtMsywj54iqmxQnEfFIiUPnPb9BxbL+hLyjWzYIIza6i9gDsdLw8CZ9gMUeARDbG4Pau15L7MgVP1eIqUDZlTqtvdTjOZu769j/nvLBwVDIRJWa4XcEhgqWSk1LEJXK/p/G1cfkOIXuB6NWT6TSu52dwBIPp0n4cAv1GmpMeJzmtbCtfnsQpAI+X+KCJHfUaLdRzKWts1hYBuDYRA8JsSn+LXgL8i+LLHQkjbrXxhHVWqv7WFh07ZvU90ohO9djoxixOd6ERH0f1VQ5gUyXeIaqgzURGl7fMYVF1Vf7SBbk/zeFaRhjeFnNt4cp81zLbJCo5c0cus5SCFHWt7BeN2JW/lnVElptbXksrxYdmvrY2C2QrKvCR90WhN5Dm8tvGbuiHlbx1bUUPEniNSUb+pGm7n36CS+HXjyNe2Pqs2ayep2qhcv7axlDlQ8QS5a8ZX9bHXRihZyV8T3V9m8SKqwUipEtdeCn6XQFrOHXwYiuuKIUSQzkESIMj6bT4BgAmSwtNzjU+v33NB4lwPtOSMyGHNHecEtLJjhOQCc3E/y5N4ynEnMsQMtmJrc7zHFGPnmgS6PEsh61EKeOrAOXm9oMbMbKNIZMY9eyjHBYGDjtkClcjrAeIjkPRkWzkRPdYAcDbXOqX91MA5bfedy+MYq/GMcyoAMzPmUcUURFICHTWA5hePNaFN7CjXSB2XhGFFEKf98liPr10DKwEYO4dxCYyLclxYANxrglwjdjrOMLfj0NgUrF9bT2GAbKykiW7iTMdosU3jChjPRNsSjSu1meRxVyWAwWonOiXsPdGJTnSndH8lC2IQvcAnnHZCcaySRQW1Bh2vhohLO3jajcrOoyn/KX1H/jxsvZ9SFslR72ZFzRFX1CfxBPFJlK8qlsfOku1wEU89t6L0XdBE9cgivSu7XnSA+GpuERCvlnaxor/mDYmpJombrMcNqagW9qlSACoXo/WfvQteITq6npQh4aY2RX/78TTjqtQI+7tRAShpS5WqRKFVmXTs+hk95WLL8ZrxqRoo7flcVCGKeK3iwEmyONGJTnQU3V/JAkhGzvS9hvV2vuSf9FoNTLxrw21nnYKx7HPSRwY5JQNmWGkgmAGGhClJFygSgCNgroCscGaJbmcIZx14rQozJef6eO7KjlWlYjMQE48OYaHtbqsFcABglaSYcengtkFtEFURInelkN+wYPhJGbtx6TAuq8QmgwZfeV9S0h06B0gQbigwybAE+ZhFq6/3D60Pzro7CeA3DBqRcQDBsCiiFbUcF9sAoPq937RtRnW73xC6Jx36i/ZYtwXCEgVnkewB9U4fO7Wv8A7oL0ohIoqE/oIwLimv2e4BYfcuIWwI4xKo856Ue5VAWe/q38OFx+7zATxYoSIgLNWS2b9T1tFtbc4JvLWKoEgZayOpGNLwUWWzCOX7cEEIc4AHzn3s3hPMvrRGvzkv9+rhiNj5jLMIi+peOkGYM4Z3Crgi3oAD3G9mUVMdb1ADrQymXMPAiTR2YRzL56QPlzJT0aAlDt1aMz85bw+TqkANnDcCtOtb++quh7vqQAnladfylwFuKMld05ecP9HtQn77eBT4LTe5EQztqICvmBMEA5r9iYe4h8akUbRSmPVxNWjbbtQoUewjOK3dSiLMLmMBBqWxc1q2WHlD/FYykhBIKMmdNKhVzvEdgN9U/aaX0G8lIzVdfxjB6XpFcPJ2wOy5Ad7SMalygwGLwtbUuvIS+I3AbaEG2VkR7XkUzC6TgTkxt/lTld/9TuA2EwRn6jsz0nTvuucj5o+XmD1Na7QFhp4we4omb4TbAYhANCPt1umzIIDVeLXxAjp+TnucfhfEGTB/WhCc80881ucrLJ5Wz0bv0V1S9r7UVdpIgO454HaVEfwzUQpA4l7tECMaQ34paXCQcdTPnP1bdGM5AsFJgz5t3DtwH0owUtCs3RgLOhPDeDSC0+0iOF3D7BQUBcFSwm1LejQaIrynXOMjn78dII51XPae9aO+8FXquUyvAcHZvNRIen32XuSTlFmsAyi9NBQUpel2sTA9m595JPrYtINvhuC0F8nCxN2QLP/WXbL813YAt9PjeBSEjuFTCjrLeqWoxtQ241shOLvnQLdOEsOoEkG3lsYLx70mRwqG4ExMrric9bhuXWcPL67T6PYRnN0l0D1hzEpsHMZA6C6Lq5ZruDdeDcF5f5nFiwyczMXA6Z0aNp1rDZwvc52ayzCpIeYKNXFfVZtk4ByLyiMxHuU6rV2Bpo7EGSPMijSR8zIwISy5MXDGGYNGzS1hrkcAILt2VQ/U6LW5Tqv0euIqd57VzMiqB2e1imJa6lHKy2tBdbGta2qqXq03HuM6NfXDXKexV3XBHvhozKIycIoTxF7doOOZrjMAUND4j3FJ+Rrj4nau0+EMGXId5jomHjROw8h5ZWoxqUrjojCM2kBpKp8aONO8HCF67LlOhzNgeBDhL8s9H88EEMoGzjhhFifX6YlOdKI7p/srWbwsT+YLwodF5Pjcghb6K8j5HnNfFq586Fovodp7W/JfllyYJCVoDJJEa0FxAwq03gdxc11KuSHvFMVZjz0kwBXK2PJaVfYCDXBL485qSPkNUtYkZ6e+qcvSzs+frRpSH2fjyp/p2Kz6her342/rQWo89XJ9O8n+HPIYqBxn47OxMyQDx/aue2ju6Tna+/0Vn5n7yyyA65PfxhK6TkFzXFAo5QEaW8XLbBYhADFFnQ4BZIa2GDVJbJ3nIcQbRZ1ObRZ1ChnqY/6bhgjuNdWdJablqopYY+CMGs1Kd2Wz2O7bLExWlaSn+416TLiP2cFkNgseDtssXB+zzSIzupvaLJJhL9sPbJx2uew9kIM2i3Ej4J31IfA7FdfNBgDczmbh14Df2DpoQly/KZgJoNgszMNhUadTm4VP/as3pDBVCnIw6rR7zuiqfDkkGoVqNguaGDA/9TYLIgZ1HlI/OM5puO8DDb4PKbMVgH1pIoq+yGcJXxsC5PKqFExOxtDaYMp1iDqS12EI+aWUxRzSOfNAKXkHPLvUF9rsGNud2itSfg27Fu9KMeK8aQQGJW8Fb0dIMP05wqc4FKlyWopTWLd4KSnz09v5ssLLAErx5WFsijBPzwGQCzL7dSilAwEo5Lz16tCo3hq3i9m7oCHqLTOgarekKtzfvCTuWV/qg0yLL1ft3AfQeovuMoXRd8Xu43ZFsogVVNoWnROjoGC7tUkWGmLvqXiE5le9ruEQETuGr+qG1MWY63Vzz7ZYfHyG+dOYxxBmgu5K4PrKwDlCXeC+uI0tOzjFUiXM1lOohKuLE8w3EbEjzJ4MeaNbPPYQZiwel/s1XhG6jRRvSJWD0/WCbhMxPK/d6zia7gWzOEh1gBiwr5bkLS3V6rA6IUjPSUh1SQMXl2ndR+1pcawVyWsm5FiZxRiVSSCJzWNoYoRk1MJDYswjmJcllsrnJoVEAapixnkH5uQ2jdIYXqVzKjlxiX+QLhls+2GvmI/UKf8BHZeIFk+qiiJNz6nHzbvQiq6MHOthyEzb2ZQBlLlQlFTXIjHEzHRicdHWXW/Lg8+TDGh1Ow0B6IdyXesqpTcsKkXa9Wcl3oMi4LYxMTDO8Si66wowo8JY1gN8ujZ3DrwubxKlYlXGSPOL0w/qMt7ZmhCE1N1bJ841hmXSGaBJfqNL0o0Vd7f7PAna81cjYsfg9ZAxRuqqluaF76LA7SQbOGvXqF9HuG1opI2bZCA7GThPdKITHUX3V7KoDYBTMlsEoBJAiCBXZbk6Jk9nnWkLULdrXcwmpMxOIlnloBuEqFNlGM0SBjj3QTHmEG5FLWkBYwOBUZTyvZKCyKSlO6T6egLOUpS5QgOzqhJRqvgP6E5PRaKobS5W0QsAcEDKOIoqiULHI5BKtTARgUY1Cup3lX44luxe1k5Macd/NQsnV8ZICjous0kYUUDKf0n5HEhSyUKRJLhaG37JOpnNg6vxB6bGuCuvscrcSbI40YlOdBS9lFkQ0a8S0SMi+v2q7T0i+h0i+oP0+W5qJyL6W0T0h0T0T4joR48eyVSKSBmz5VBG70NeEvOQ3LAMXza8mSSTv6e+zBtSu1CPIXO9HnK/TvqiprxgTJ4YtQFQiLrzpb70+w1M2DelyRSpHq+NIbnkaDJHknrMKiXRGJOXR/K/G69lNRYrL1hKC0qTu7SM2caIxl2thYIkS25q+HzN2cPNjpPHW3ltBO0a2zjD/j9bp+tKJB7qN5d7bD4nbtxb0jFqyK8B+G8B/O2q7RcB/K6I/BIR/WL6+28C+CkA30j/fhzAL6fPmxNTK/abQXNM9RhsoQyhOeva87uZLrJ9ApAqNkRSdm4MahyNZ3NQX7Jgu61m/YZ3gFmlmcGLOWTe5etRFMjZstzQnXpFxvN5SdibqK75YAFhAMBjxHjWAQLMUuxGWHq4qwHinVrnLVlPCDrGi1VTERxAU/EMAByRVgLbDaX62YFzAGhdD2gW7gzLBoAa7m3Jb1YMv/n/23u7UNuW7DzsG1U151x/e+/zd8/tvt1qSbY7sdx2rGBZIg4CoZCAQ0DkJcQPISR2lAebvPkhIeCAMeQhPxACAYUYxeDY6C3CGAWESewHW44cTBQJtd3pTt/u293n3PO7914/c86qGnkYNapqrr3OOfvse8/tfVtrwDlr7Zo/VbPWnDWrxvjG90UREFbkJYvjUx5C7a8Cc/cLV1KuVUWM5jkqta96VpebMcCOHv2dpKLelMhBqEiG1KlZR0NsB1CQZdM4N+iyQ7aoiuUksG4Gv7IwAyO2NEFG7kdD/Eq2LTYLbB6YjBgNrSR8hZYmyl9m1OhE2q+jNHhJW3Jy3Fj6TsOsICC2LUJr0LnCiL55YLF9WBz7gJynWSenLRdUK4CkDL+nSNZcf2n9xsGCmf8+Ef3EXvEvAfiF9P1/BvC/QwaLXwLwN1hc7P+IiO4Q0ReZ+fvXbtGrrB5dK5xFZvcOJWoh5YK7oLiHv0iWE8RClIiKsnu76kHZmwUQM+A9qOKlgPcSjtTwrIYHhyARFiDP38xQxjhh907fo2AWJnWN8kZGYvfOXu0obTf9eCUMaqr6AQCjl6r1M33fP0b7C0Dylk9DpznKkEBU1pCs/4dYwqSMcg16qIYpo4Qvc3REow+9L7iPvbdnXS5hbQ+7U19ICZ2CY4F7p7uZDTLgS/Ad4kOItswgKKSwK0qI0vYJlzJGRG/gtmWwj5rTowOp4lb6Ec2mJNWZIP/cjlGDoIxP/dAUn8VEWDl95HCpqb47iWSYkeG2Ib+Emg1jXFPOS5HrwhtDp1RpFn4W7N7vVwPADwC8n75/CcB3qv2+m8qOdrSjfc7tE0dDmJmJ3n5FRES/DOCXAWBGy0M7THEWk+8lkQzGCM4iYS1So1ALJquwcY1cUzwDpbr074xzIBIAVEROUGNLIqPYuCJN51wWMU7XBQAIrS2gJOXlbGxJCAsxT70pRIROEJwKuuLGyNsss2lpOjUl6bzXCy/Lvi7vV4sw7x8j3ah8DDbregCYZp2mt3VOZoqck8IUY1F75pGXIylpTsGiraJf3aRvJlaXGwI1LieBhbwMIYS2YFDqmUVm5TIGxsl0388Jtk91W5akrxmhacsyyy8MzJAYteKBZYj2wcLk/huXlAFYugypgVZAWoZEqkSGKGuMCO9EOv6itEUjJHrfhtbA9DHzgoxLwrgC3K7U42eC4j00swid9Efdrs8ikewREX0RANJnEqHERwB+rNrvy6nsijHzrzDzzzDzz7Q0u2Ezjna0o31WdtOZxa8D+PcB/Jfp83+tyv8SEf1tiGPz5XX8FRwjeBwyyxRHBl8K4D2+EFYRlTMkJ/Bl3goYnwDwOIKcm8gTmi++Lz6M+SyPzKbrSp26tk5reF62gofQNeSTZ7BzETnWusx8Dj5bIc5cli90APzdBZz6GnQmYKgsWav1eGa03vefGAIDsB+L/CE392Cfr8HzFrQdwHN5JZlnFwCfYHhvCbubOnVreUQAaK1JjFtNYdraur1j5G8VKY4NTdihJ23WYzqSNbkp6EflFLXnA8zuAIaY5pl4h7zUuXuvzc66fYlEzcGQuiJaovyWDFmykCcOvFrKUC0GcXzaJEl48rK0jW0DNsiw7ssvdxhOCbYH/BzoXprJuYmRfRP9qVy7GRYYV4UJK7Zp1uCnM4v6euQTACjLGqq5g0LFjMsPbJoJtdmXMS4J4xmLQzPZeIIyw871pG0roD03GAux1qT/3mRvHCyI6G9BnJkPiOi7AP4KZJD4NSL68wC+DeDfSbv/XQD/JoBvANgA+A+u35Q3WO0AmzBlVQljk/1jFQK9ukrKiWS+YqSqEsQm55zUlRK5MklOAoPtEfWY8fXygvvJXTlxKlTtSUlr+qnbaQxTecR07loeEUhOVC+K5OqYM2Oc7JOdjimkafv4yuQuNbelg/vZPuR+3LdJf6TrrqUSJ+rvFbALMCKLGGIhv6mSuvaBT/umEoe2Z0THJScIiTGKTS6zA8PuCHaQZKuJPGIKP+pD77bCe0GB0awr8psgSV/NhieQbavObHWUev3tp/fmvs5sLt/Z5JTlvNRzG0ZzQXCVg5PN9O+ak0O27S09Ps1EMmb+c6/Y9K8d2JcB/MXrV3+0ox3t82K3F+69b7VCWc1+VTNi1WYTm5Q6QJGWHoq5UIdaygKNrYWJMWMfbH3Oqi62IjKUj3fCRmU1bDtUjrnXMFllFitAHIUVQ5e2h5KgEXypj6yKHFUeMAAgwTzEahkSe9mPAuflCQUzSUzT8ib10SHGqv0yP6fMmbm/zaR+3Le6P/S6RdCoWlokbAAbwKUpmHBIGjhnJkS/gOwXqqXHoWVIcRIKu1XtSA2dgZ+VMmW5YkPpGnWNVbJEdVbm53Lu2BiMS8Bu95YhAfCL6q1uDy1DkDlf6zYdMj+XBDkzluQwvyCMJzK7yPstMRUZqpYhfsUwgYRNa69/rmOfn8ECEml4q7CLSQ+G5mPg7by/h8+JyZqwliFkY94qf+QT20Qt7cB2g6kWih5DhExYmH0sZpKx+pkbIUvuSSSKc/lEYewdWuaVoBSNyPcNTyUGtb2WKl7Sd2xUPm/aF3ngvGFXfq4Gi1eS4bzKEmy6ZtC6lg7qa8+JKfBIIc+AOEg/yweuriseuAOULyEwoG+wPdaqTFDzLiHk1zHFMDGQWbcAYQziCrz0Di0zS3ECTFVw6iuQaU4w8bdgx/5ExuVzP3HuupZT+W/YlZ+fweJNCmWHzNqiWAadmcS3n6FMzpnezFUUIKua2UoV7R1brXim7agVz7QsWoJxVM0gRCtVl3RZAc19Nu2+YtqPOmNLTOATNKbDBNL8riwriRnBbChWI5Pq8rS9tcLZOzcqM5+3gWjXFh2KcPMN7PMzWHCcErVcJxoSgkQqJm/gRAxyw2iIQqFNZo2KCdqdaPEzLd67jYbYPk5g2flNXL2BzRBgLQltH5cyrkhrtF4KP4xoSIGAOxiwlRlFdCUqYDx9ZtEQtxMmKztIJCPT+OnMIpTzuS0hBoYZPptoiNvaxAxW9hdavetHQ0JHaNbTZcxnAfc+2tGO9gfMPj8zi9quEw05sByoE8puHA0hmcZPYeEJbl7ZZxENMfWMiYRKro6GcG/yEkkzMo2bRkOy6C6rt/6zi4ZIZKCKehAAm5Ko0hsxtJRnQe88GtIS/Ewcm7EhxKb4LEJLk7dw6Mq5P5NoyCxFQ4ZCivO20ZDYMfyCkrxi6Zfr2udzsLjuMgSQNfABp+ONlyExAp7KVDum5YAPMmBo1ulnAMoy1TKEifbHK1kijQQKEXYsZbAl8mF8ddBnvAyZMombEjp1JeNSiYAp8rsHZfUMtxO0J9tq6ZCZucr5YkMIzWcHynI7i+gZrrrmtwVlRaegrJstQ27VYEFtyrIZfWbJLhsNgAhaLcHbLThpc4KjfOc4PcaXhzl7/Jfz4r94IZpvSrRrYhQS3MRTEfseSvBb14XVAuQDrA42/Qi77kXr1BhwOt4+ubhCjkuNg00JaLTZgfT76NEknokMLX9+Ad7sQLteSIGVPXy7BQFwrSu4E0DCpDsLW4VJafAwvgGNITs+zW4AW5ujH9RLe9kJHqP7weWVh93tJXk1L5pMtltvo1FYuFU3tTY7+twfet0tUabeczrjiSxO6ZpKMEV05h9JCoBygtAY83cpvwoaKDKVEd2igX1StP7MpgNbC3MhcmLzzqJZC7v3uLJoLtKxLMS6pkLCNucWsTOwQ8Sdb4xoLuSaY2PkodyGLDoNlNlA5txQfhI/fVq7x2scMjYn2cmqofCzZwGz5w7d83KfhZmd6M3WjuvNQ4fuPEyg9TqIXcdux2BBAIxF3Gxykb17Vyj905uWE6lMePQY9qt/CGabHp7FDOZiDV7OYWeSkMbMws3ZD/nhB4D4+En5/i/9EQCA2QrJzXB3BrMLCHPpkpm1iKuZvJ130qM874AYEWct4iLlhjxjhJNZecCeSG7H5md+Ai79aPqghplBSD9U+8Ln77aP6O9IvSfpht9+cYX25SDkL30h5XHPtxjvzhG6Kd8CIIroWRoQQPd8EBX16sZ12+bKMQAw/+eSC/j8z3ypwJyT7Uv3DSeE9kLe9Fn9nMUh2FyGosOhUAlm9HeazEdRZ4/qbOGqinopd1sZKJ7+y6epPbKPGVK2pi6pVEW98vi7HRLcXdTfT78tO1EE+lMDPwdWP5Cs52Fl0N8xsDtGmBG6F1VuyExnQ1JZf0e23f39Hh/9gsP8UZP2A8IM6F4Aw2m5HjOkLFDNOl1IyF0zfHWZcvaNNve1vvWZINKLHbB4FLOT8/Gf6rD7yoDuu2Wt4VcRzflhFXUmoD13GE5Lmf8/cG07OjiPdrSjXctux8ziVWYI0JfnBK1YORRt4rYwhc+CgMPCyFSv39I00MlxsTGgSqyYDcmywqFgFCwBJNR4eT8rzkblodCs09gRgjISkTq/KMGXhR9BY/QUTS5Xx2xsRGAoNkYg2uoIs9LW2JrM3pSvqTUTp1hAPwAAIABJREFUh5/UIftpew8dA+0vTB2Gan5vZuHn4mijULZRAjLZxlwFfLE4DJXhqs4e1bfnfr11OUVZeuiMIlPQkbzFdWah22taPQAwQXAxfl4wChRl/9BR5tfwM4F7A/JpK54I5ZvIfTIv/ecXEX6mfCBAmDP8juAXpa+VgyIkXr+wiKIxkpYB+w5QUSQr1+Pn0l5ftcMvGN1JjzAvs8WwCiBPB2cWsAzvDcKq8nV9BnwWRzva0f6A2e2eWdQ2AVZVaec1+3Zth7ROq31M1uRIDE9JWzRrXiR28QnrcwQoBNBos6OLQkoX34ucmKFoVOirlq2BNRotiUVBzUfY0WSos7RPrsmEKQmulvGAKbEuhMXJVp5uM0QYS/lTy/aPyf2FlKZd+yyq9b960e0OsKOQy8ZBZxacNUVrXY/S35ydfMVDX0BG+2+4utz2nPRg0zadZA0ss769n54N8mvQDkh6IcIyljk4o/wdXXE+uh0QtgS7E6im+idq07KwLf1pN27KS0GA7SVqlK+/19mXlpmsGFajcVVdbH9m4bbSZrcrfea2Brt1i26Xq0F0VtLn6SpEnUFwG8qzau2H69rtHSwMARWx6GQZ4mxZhjhb/uWwZ3zzMiRT2slgEVqRENQ4N7sK25Ck6wr13jWWIS1lYlR9EEJn8rTddqbURULvJtPthLNohP07OgKqZQQ3FuEdLkP2sQpsqmWIMljPJdhEkfJ0XB8C21PJ8tUlJCsLd3Jw6lKswdstQ5R6TonVDMEvUJYhyXnIdoqvMAPBWsAvSj0U0jJkXq7vpsuQsIrwF7oMYYQFw/TTZYix0ke6LAjLCASSwaK6zTVSwbYMYmzplcuQxekO/bJy4q8CvCewEcq+MJ8ytX+SZcjtHSwAXNE3nWybQrjl31sMk5WOR+a0iihvKWYJTe6ze9/EuHxS9b3WCc1/68PMKVHJUklwSm38NDQgrtXe/TbHqixWn3oMa7ulaKKmzgUfcOP284HPuh/32wmkhLDS1kkb9spubFUfFU2V6S50qO16bJX6XvRjaPKbv8piNFd+L/mk6d8A3jLv7IodfRZHO9rRrmW3e2ZB1Vhm9pYkVC0tDF2BW7M1IGPyJ4CJqrWCeXiQ49mlf7Y+L9LiMU3DiUAJ6q2M13ASsYBGV0zx+O+nL8emREPYUiWWk74z8vAdG6k/OoJJ7cvncZLtGP30mutoi5zD5P008nLoGO0v+RsIdbo7lel9ZufugLAjmAYTDscYUtRjP4XaJCi60/bLp0+waP1eW11OAYnRvNSvFtry1tYpfh0NCYEQbYqcdFwySQ2n/irtCTPKS5wwmy49dNmhJ9b9YkvgeciYmTAD4pxlOVIvAeRmymU8DwAT4qDLDml7TIA1JlR8rnJeP+cJriTMI+4vt3g8X+Ra7MojDBUadl5hcSzDDw14Wd2Yb6GFepxZHO1oR7uW3d6ZBaWh8VXbai0PnWlo4tdb+BbYyijMRInrodTBVlLOMzmvpesrgBNVUZBUF1VLSVe+R0cZsadveOFUMFCeDI1EcGPeKWvUPiNU/ZbWWVfmmDClTOjwJP0/40fSC4xYyktU5RO0DdPzsEVe0+dyW74bB9BQ2qwzIQqUj58wid3ELFdtYrD+XafdJIdjfYyop08dHHqvRFvo815JfWcAZ2JhFQPkXAZgYlCmHvt07BYPFuaVUySuBYjSwMG2eOGvw4aVSWKoekAJ5UG0RvIlIpeBqab3v4bti8RMHjxDB2/ujOWnBMwyaV8q2z/xzf06q0Kl2mZtf9bcoUSkYkpZJoihkv9g0mDP6abVdscbtj+3q0Qfpw9SNZiwS9N6lyDVBoiOq7bJ7y0kNzdqTqnWcGkTQe5bkge27ESTgZgMgwPJvpaBMO3j2JQx5FV0/UyMxobJc2KIEXTAiPxWy4w32XEZcrSjHe1adntnFryn91GFRUkZsAARDlYGKy1jYVbiGPPn/jky+MoL6MmMykSk501CyUmYWOqNgBe9DjOaXL8ZYxZB5syUxTDKapRGd64ctraP+W87MGyPBL6qjh9iEsiNZVo9Sn0cqdLWSNsGgq2mpGaMMAPlz/q662PytSEBripQFhvKyzqjDsqUAGb74pijKEAkM1YhUq8hZ1Ez1wQzdTTHKuV7f6pdl9uBJcN1t78PJglXIb2djStOS7cRIR/jAbc2GdBkPMO2ApxyfVXXjuC26fwTUBZNyhSDYQYGLhvYTb0cs7Abgm0rKck+QcwT9iZQIwrqaTmkswi9xlixeJNPDl8WwJi2164tPr5YwaxLPSO1sGsr91wkxFDN4kj6Y2yrx/4Qd+sr7PYOFiHilTiLyCUF3YfqX1Eyp649fGyyrPA9RqFS4DRweEVVBlHWigCl9HHaJ9h5w/kVwaiXYQIjsq7ny3YzJAQnkNW8jJ/Bbj3izMKMIUdDqB9hh2aS/vxpGrHwNmQLXHwV+ToUxVkQnAAyglOzS+usUwomczeYvER4u+VI5oLQQWFkmKEm8kn7DSWb0ybkpBlFQKjZFnyNCTKQ6MA0Lm62PIIvOS4UUt5MLBEdLRcMBpdjOA3WDHCj90L6RBlAzAgMB7g+KQDDYPOAD0hEigLysoaqwUKXZje12ztY7Ns+3Hu/nBmTRLI3wL31TUrM+S1NsUCSZSOBOE7JQq4L9x4LRDvrNY9c4N6ewQkOTiHVy2VnCnIheVCr2kVRZh3vCu5dCGmkDQWCnM7Ry4AhEG7K/Wi8cGiqf8XUfKChmnGkrrL9zeDe+fxj8mmnarKvtXIuGl/g3sYj3wMU5XiqUKRuxzeDe29fAfeuEKAK9655+CdwbyXDUadmBffGq+DeO4PdtkFX1R03Bm5X4N71uP+jAfdmiSlPJhKGANOCtzIvy8Q4gKiWp4edZw0QI3jRgS4THwYRuG1Aw5g/AWRINoDMW6HOUr+wsIYwnsg+nbOInYOhAErUe9xZIBjERQO/lOPtWr7bdVIjT2JD47I4InWK7bsCx6Zo4RPc28wMdmcGJiDzVvi5AXkHtgQHFDq+voGfO4m370VF/MJgnFdLncGJ2rehrPp96BgAmbRnOCHYGqthBXsBlIzN4SRhOhoDv9TrIfitUvin69LBkBnj3CCmJYtmjfqOEN3ht3pdHh2jWzQYztJxc70+gXsXaHgaYFw53q0N7E5g1dsvRHTPUts8MK4I/RnQXkrZcEro78oSQ3AUpS+1Th0k+rupfGXh3x/Qe+mkMGOEkwA2DuPdatm7pQn8mlce8EYiOW0Eevl9h6cu9TXy4BibgrOwvYFNs6P+vYAf/9JTfHt4L9djT0b0XZejLzyrJS4ZsW0Q71Z6r28x27gVgwUZI6+ImunKyN/2nvwq4dnzsm0Yix9hN4J2gyR+nQiJCWIEXlwIYY4PmTiHh0IL5F5IGYUAGIMuxMTUnZijZo1EHsYIpAcYRDBPX4IuG7j0cNHFBrPBgxLbEq/lc/GDIc9eNNrSOsqRANtHtFnLA3AbK9eQRn23CfLmCRGIgK2Ibmwf0D3qYfopI1XsGhnQdL/zHWLXwPQjYpcGswPHAMjMYSffuT9JnqtFijQkGlqC8Qy3jpnIhqL4aOQayjJB+pjRcVlG2F6OOXk5Zkq7uMdyVZebMcA+ucjENTnNPPAkzV37NjZliWN7lqUHM7pnBt1Fmdm5Xt603bnUtfxegF9ZmEEAW+6y9Lnm0OjMzK+kvYtvr3H6T88we8a5b8K8QfuSMS7LYGNGmY3ldPh5J7MI0jC57Df/OOXPNMWXEhrC7GVAaA26Z0P2q8Vmhh88+QB3ih44QtvAbTizjtX9antGs2aMy/LifbKeDtKvs2M05GhHO9q17FbMLN7WapUxSfgKCSXEefubJleasEOBwUiRl8DFlxE4RUqKPscE/HIdUwefRmmMyRBeCrFA2AODosl1av1Gna+h+E0oxIn/4lO3agaQTaEfOUFMZhZZ7Sxt079zUpUvv4c4/NLfb9uP0HqvflIojkAy2hbKb0FN9Vf/gPqkKHC6DnxiVbFavYwipT6YgrD2k+hKIl7y8ygMXf054Mn3V9Ybpr8Xsc60uCTRfUr2uRksVFWMAXDjityes0LR76bTWOpacAz5EwCoWoYou5BRfsxlA9MHhFnyRVxSyhkxhVTVEnjWguct4iwR844eYdXBKjnvJvkcli6zX2cOzs4gdmXpoSnqdojwSwsw0FyOqX1WoieNgUVh9rJ9SMe1E7JaQPwdoY6SREbsnKTUp6XUoWMAwKbo0XBqM82/dFpJKVff3HBCaC8FSVrndLiepo7dSohpXBrYXvtBfTmNMGzjKgV+XW57C7Pp0J+msKPS6A/CS5k5OLWdprTVthI9MaP4KFxffCz9CSG2QLNRX4hDf2rgeobvCF2l/KVt1iWUtqV72mL3ACIwBU0jl4d/OKmuZ0D6zdP5ZulhT5EUFStWWn+RQ0Du93FuxXfELjtZd/cJ/fsBFMpv7leM5lxAcGDkfBpABlF/QRirdr0K8HXIbs9gsYe6JGvAbApGok4kcxYclFtC9DXQuBxOZZPQnCbxXhh75RxZti/R1wnfAnJCkFDtWZhKYyQ2FsYVJfXclibxaQC5Lrm5Uht1AtEV+jwzq7gzLGGcy01Ta1iYziavuMmJa7G1ef1Me9BDOX+5RtdYhM6Aoi0q6geOAZAT8UJHVxCc6iPICWDzMnjod0VwOgKg16iDhrOTBDflZBC2ajMpm1Ss5Sx8IdnJ2JX2hHnl4Kz4LDLOYivhUWqA/kxwBtI2cdyOK3mAcn/M5UELM0Lor7Z5sl/qv/Ekwm2qwWIhUSK/Kvd07ClR+SUn7zJFkiLEb+HU+ZvuCVeiUNEmf0c35f3wK4a5M2C8mOWysIygaDL+ROsD0sAUCGOtov4WjojbM1jsGXsvDs8UweBKF4S2PVDT7PeDhEsr8hve7IC+l5eOOjirc7jzFGUZgyiIh5jCc4mef/Cwm0Ho7VVXghl0uYUZPUyi0KfLLRwR6FKQPOpM7Z4OmY0rw71teejtzhemrMiwgwMiw25k9tM9N7B9EBYvX5YhZuvREGDX4xVnpdlcdXCajTg4zeawg1PLeSP9sXjsp/T0pggU6VTZz4UC321iGWxYZkjkGRnSHMqU34w2OzybNKC5tb+2g9NcbDILtw6IxssMIDs4VR/VUsZcuF6YvyhK1EOdmeRlRuEvCLNnqtUS0V5ez8HZXkoF7dMdTr/ZoXuuTkchqmnPI8ZlhUEZJDSub/IwM5Plg17T4rEuecvMIlqg2cbk4Byzg3P17Rm2uzlmT6rzdFZ0Q3RmUc0kzcho1tN2/aAO+b7Bjg7Oox3taNeyWzGz4BjB4wByaV0dGbyRN3V88RJApSPinHwm0R0yJCI8LSP+4HE+J33pC6BtC17MQBci3GIX86xOFtMshNiDQgA3M0FzKoLqyQvYRdIhSW9ds5gh3j9FnLmM02gai+H+Am1a1pjERxBmFrSdXmfoTNb1KL4HwG1DfrPYJ+fSvlkD92yNOGthdgPiTObY9tk5gFPsvrDIuiSA+EVqXRIAaBcN/EJ0Q3Jdm4A6Gy7rhoT7QASGEzPhjpR9pn/3p4TuJYFaszc9N+jWA8zmqshQ6GbFh5OaePnlLqMnQ1eARGwq8FMrCmHzzmJYTZcsbjddHuxT3wHyhh4XArAaTgnL75U+8+k31NnCxVdaDGcCyhqXhO55LXVIIOYMBe/PSJY7doXte3Ltsh+StCFNdEMUtBUmnBw0BXOhAuHVkzsPvPxJh9AB3Z02zzh2DwjbDzwolMd4OGW057WvpZxnPGO0zw3G03LyUFYwb7RbMVgctCvapckHEMIUaFWBrybHNE6WKo0DVGhoGLOjVEWC1Ivtlw4ufcrhNgOV6rp0oPCL9NCv5XvTNXKzJ7i2X1Xcn8lq0FQGTKVrG06m4CgFesVFI4pYqb3mUsrG1dXsU7+YPrxmsBLrp7IWBpJPJ133uJTrmDUWiOK4i3tAnX3AVH9X/AjR8WRbdLKcOnRT1f2h1z2cUs6x8HPkqXOduepngoRs1i4L+9QAqUJKc/jG1/OHrQCuFB8ByLWGOeUlxXBG6O8y7Fb8DRPN0BkApuwX6e9JdGz82KB/6GG8gumE+IatQV+BsnI7EkFPTOAss51O7vtHhyf7/V1OTlGCSQPM7kHE6RcvcLk9y/vFuyNiLaxVEfA0d3r0dgZzrzj6P3egrIO2z6cZOScn1MlhBxPGAGTW71glmAElvKoKYjlxa5ogpufU71oX+eTbSPtRiOLI81Fe2JpINvBrE732k7v0Dat1anIajaF8ahvGIHkY9fmJYIc4YQMzPjFujwxrtV1R0vkVIp1h6xJi1DV+bftJXiElX9lhX8+Tcz/uW90fet11Xgab4sFnU5WTzCzMGKvErnR8gmW/zuqkMLujibao62Vtr2V2JwOFJMhVb30Nd3KBodudcIzYMcKuDawmuaXQpd0VZ6ruD1TO2Ggm5ZM2HTC7FQe83RWwm9sQLi9nk3rG1k3+DhXp9dg0cBsD/yOXSLavgu6cpCmOfkqVV9HnTaIdTVqutK5IGAYjERNTqaA7daQZmIouL58zfde6wrxBbErUIXYyQ2hmDjCUHZ9vor1TyjsAiN5UdHsmb4eqtbtQmMWtlNVRDwA5jFl7y+3CYFiKZzxk1GOKtCTnmk7tZ2nmUlPdqe1T3vk5YLc0ERnSc2s/7lvdH3rdfl6cv35eCICiKwNUbGS6P65sXmbUFHdvmlkUEwh3rKMyHSHMKJeNS5lRsCUMd2MWRTJBZjiSx5HasJQZRH9KCMtCq6czC7vH7p0jYnszC967zw8pwQMS+QgtMO4IOkD6RcRqtcPloqw1eOnhh8Mzi5MHa1wMJ2hOK4HTt+C7uL2Dxb4quvdlZjGMWdBYv9MwTiMmwyhCvLuxCPWGkGcbuq7WjFK39jCbMXeInlO/6zntZgC1rqiQbz2ac4mcsDG5LncZrmiRItoMAHJrn9Mk3Tag1XDoUNpD/QhDlD91u9mMaC6bieI2E2BmFqHKQGzOPSha2G2ETYNgs/aw1cxCBwaz9SBmdOcx64yq1UrccpDJ+9Xb3JZzP+6bu7SlP9J1dy9NUTkfSDhOkwix+ixiw7AD0FyErD2qb2OXZgtqh3wWOhuR85lJhKNrJDyqZd1zC4op1BoMZk81twVwnYCtdLZBLAN/9zKie+zQpWwEt5EBuz1HHmyA2mdRQq51eW7T+WEF++GpFZ/F80o5ngzO5ydYPCn1DEO757Mo2y7jKbonFmNfymj/t32NHaMhRzva0a5lt3dm8UmNGapXcYWT86b6H4DwW9Sp7syZp0Agvu8Qir1vVVWU21ItC7jAgcnxpHxfv4Ji/GT9clOr2kFgZC2PujzyzTVbbtgmE6ZteJXex2f5e6vC2I11TuLeb/+WdnsHC9qbHtUiybXKWK08tq9aZuiqUlk6d5YCGBM6szWgsSiN5XPqd63LGURXfBYufWcrfPOFUv/1imGqFgYAMWVP5jrSdkGKGvBoC0zbqjBzUTwDkFXVaqSk/k2htNeMPGG/KhDpguDcvxn31cLCjBB2ikisBqdY+nHf6v7Q6/Yd5Rt3P3Sa6f3Vr2MpR3rCK8Kltf+i2HR7rHw9oZNzalnoihSAn8nSQzpHjhXSHc7nEgJggl9G+MsqdDpjmHHfZzGNhmTZgr2I1iFhatlfzm23lEOnfsEwJ2OOzAEQdbTKV1YLI/MywG8N4rIKuf8oIDiv2NuO4KpSFmIZJNIDwm+jXHblvBHEtrx1Apc3ny+JaO/ceO+tRjrjqR9eYePSxCZp/3T2U1CWh9fK79JqLU5KsOes6BVKuQmY6Ka+u/awRDNYnJk1wlLZuSYJYb6gLN+5VbOKCTnR29iY4OV8eEB6k92qwYIVkFK9+bKFIG9V76fsVzUjVr08GBNcPIQ842Dvq9BpYboCJKQocG/FDnNxslZ10RhAtiRFUQgSflSmrup8r2Oy2mev0pBcfbyyculnaYPsPzk/IV1nFdtPYVI7FLCZCTqzSIfpQ+nlGmr2qvy77L197K7sV2/TNtF4dcCs+0Ovu2Z9mty/NOUBtYOcd5+56iqT1esdnGFLkz7TpDAtc1vJL7E9p5CtdoD8p+xacqz4ae0Q4dYuh2hlaSI8nrFKRMuO0aj3DU3Ky36HXzZuI8FAt+E8QLkNYbhoJqHS6Mzk7wmtnpVjuGbKeot3xNHBebSjHe1adqtmFhPbR3BWforrIDi5a2TW0DaF3JdMfvncHMHZIM4dxkVK7d4IpNquE85C1cjfNYIz4SeyJZTmBME5WoxLCzaU1/bRFfATgMzmxI0FmD9TBGd/ShlaXiM42SCXh07e0M25fecIzv6M0N+TY/yychYnn4WAsrQPOEHJPyME5z3JICVPku6Ot0dw2rMBve1AdysEZ/OjgLPYN0Ml1fw6lhTK2JmcPk7OCjJzH/D1FsaNPHxZk9QZAQ45AXHt82q8K5uogQEpT6EolwFI2qoyFVXKOZOEdkpadxpEuh/CrUAFfKXKYBQYsaHsDGULhAaI3bufBEsbOA2unPuGojgzUaAx0q4ZY9zLm3l3bWPASDv8DX+q2WzExnY3Jh+6VYOFmafELe8nfJmysXBysvJrAoVj04fJMZR4OpWjE4BwdMYIBuAeSYKagrJmgweGMXNr8npT+DGquuxyBrMh2G0i0N0M6J4auBdbsDFCIAzhZnwdR6byYwKSNt6cp9di4sKcfdeBLjagywbUj6DL9LZ4eQnHjIW5M3GmsjUTjk9A1r9uk5jINdiyHhFbm52cbSL7UZKfu/9sl9PDc7v3EJnjiUNzIenl9TYzBtjzXQHBVbbYLHJ/5OseFtmJGBsDdgB5idDUsGwKDDtE3P19+R3qdPE6ulGjM3OblFp/iPAri8W313lb97RF6Azap4LVjnaF8WMDO8aULJf8WlEGMOMLPH5cGIxzQnfBeO+3LGYvxJEQWoPQAO3aY6g4OG1ySoZm2qf7zsqTD/fEUfT4YQa20heair/8CNh+eBfvfVzug3HZolmXc9a/z+WXznDnKcMvKiHlzfUHu9sxWBAAYxHX5Ye07z8sWaYAMMoD77//A9DP/HGY85SVeraAebFGPJ3DPlFpa0ZcdKCXa/CsAfVpEHn8JJ9//fP/IgDArSULc/N+g2YTM/z5rjHwd+egEGHP5SYNZ3L+8aTJy4bl9ww2X2ixTA9f892nAIBH/8aXhVdArw8ynVc27PnHizyFd1tg+1Ccju83XwYAvPzDMyw+PoOfG7h1zFP3+aMzbL/QYVgZNOupM2xcGoyr8uMvHgWMS5M4DBTB2Vw5BgDu/1/S99/510+ys07brlN9Xfb0DwK6Z3M0F8CYOJKJxQk3e7osQj7VmLN5YNCk/lA+hXEFNGttx6RZk/JmDdz5xoiPfiFN9Rdy3XbjEFYxL6myYrjlTLGHywbwBLt18O8POP2nMmWnCOweAONJxOk3BS69fQ/oH3rYtUFYBnSPy+Phl8kJupay/qEMDu/9lsXZv/ddfONb70u7lz1OVls8enSKO++d5+PXmw7MhMVC7qWHJ5cYg8VF30qU3sj5P/wnianbFOcjG2C4H0BLj/ZbM7hEYt/8mef4C3/kH+JXv/lzuZ6v3nuCrz95CCIGM+HOovyYD5sB33xyH3/owdNc9q1fv34453YMFofM+0m4lKu3qNkM2Y+g383WTd5otB0kyzR97p+juZROsusRMITupRFGba/kNyPsxkrYMddlK65FlQIY0L10sOs0IKV9uxdXYdN2MPDpxdG9iJm+zm2j4DQYhfzmZYvm0oO8hdsEmKBZriOaCyfs1JvpYGFHzh5+OYcknLlNzG+2Q8fk/gIwf8IlKQqQwWJWvgPiC2lfAs2G840r1wF0L2P26Nd4jWhL9MJqItmO8gBi99Li6/Jmw2guRswfJX9OTvMH/EUJY2t+Rq0pazeU1dJ632YWbgGwGbiNycQ1gIHxDnYn5+oqQnnFUehAqj6K2QuPb3zrfXTfa1IbGjxfztA9NXhZ+RJs8k1czGVgOp8vJUw7aN6RtOvs4+SXo9J/op3i4OcW84+RpQCefXiGv9n8aTz/8G6u57fPl4jP2uz/eTFflYuwDPO8we9elFwS319/2XyMhhztaEe7lt3emQVVLvs9Y1dnnRKISKjxaqSmMdN/e1YcfgbCt0mTTFCQojFj5sCAJTDSfimGzpWDU06oWaOEqDO8dHhoCk+kiPSkzSE5IrnOOiVEa8COwK5Q28FJWWjNlfVuqBCieg7dr0Zw7h9Tt1sQnNWMjipUoV7HDIg7IPhqGyM7JwuWoK6H8rIkO1VbZH3SuKc2WZeHIH2uM5w66hFmXM0sUlNqVXMuWIOp05IyUY3+lqGTaAaY4Oc8TfVOL2N92/s55/5rlj1C8lWFRQQvPMK6BS9KByj4U5dKzXJEZEJQ53uaWYSsUYMCmTEpyjJPOim6PFkEfGF5gUeLMoNZLHe42Nk8s3DzssxwTcCut5itKn/gW/jjb/FgYSYXQhWUmys2b27k+4Q0N5pE1Ft97p0jQ629dGxoDchXKcLOIrYWxpOkuwPZMRgdvXGwEJh1aq+mJ1cp5HU6ObHAlgUurYS9MhWWdnFJZ2+FfDc0gK1AP8B0MALSYJH204Hp0DGyIbV7VoBD2vbyEKZj5oxxEPLXOnQpmZicBZ8z6pLlYcuDRWaLouzg3Ic51+Xi1CtQ7DAvvqCw4PxOiXONoHBOvWZjRdmLgHASMqs7BYafCWS6EAGnwSemgaVqk4Y8tW8ybLsBTlZbPF8m5/zCY7Ya0G8cmmV5KEfTAJHQLGSZerLawgeLoXEwpqzXvDr5Kw5OjbzEuXCe6uDXLAd89eQxvr56mI+/v9xgt2tgDCNGwmpRUF+tC+i3Dc6WxY9B5jAI7JC9cbAgor8O4N8C8JiZ/3gq+y8A/EcAVAvpP2Pmv5u2/acA/jzGn4L7AAAgAElEQVQkk+M/Yeb/7dqtqS2Gqc+iQmeafix+hJ0DjV487bUXXhGc+rl3Dk2XthvxWTRr8Q3kLhk97Hac+iy24rNw1mTMgNl5uE2E2SlgXz6b9YFU72DyDdBeRJhQfBahFQen3Y7p+A7N2oOCtCuL5G5GuLUDRXPF/wBgki+i2+v9Dh2T+wtA+/Kqz0Jl9ApAkrLPwlRd7rZAs+aDPovQlrTzorJefBP7SMK6vNkw3DageyHb/K6gH01P1cxCB4jS1tpnwcahfVl8FmwJxhPacyXJldmk3QG2lzRzNRVaVp9FVplbezx6dIruaRps1y36jUP71GCIZSR1yWfhN/IyeLZuDvss0jXu+ywoGPidtEl9Fhcfz/EPTv8w+scluvGdwU18Fs/n1dsj+SwehTIT4QN5PK+y68wsfhXAfw/gb+yV/7fM/F/VBUT0xwD8uwC+BuADAL9JRP8CM7994oGxQCXrOplZtA4YNOHKwSZq/qxyzix0es6Vz71zqJOMvMSvx4UR8I0CpZxFbJ1EQwadxSStjLnN+zWzivwGgEl1CZ3dVXBTjoDsTP7OlKIYLNcDCBlM6CzCXFiglRavSWV1WE5tWJoJc3OzLfsd2n9SnmZPwylpd6WOB3y6F7NuyJ0EWDI0iYawTbwUOpPLeRTCaZmjQhoNWVLRgd0DftXlbIUrVDktNUHLbafJWqojCgNw6nvbWlAQar7xbokKURRdD7/i3J7hFOjvRriNnLfmo9B6dEapgKthaXDnvfPszORFQLMcMMQ53IMy6o6bRpYFCxmUV8sdIhO2u6Q/kwaL4eQk93seLEjqi4uI4dLBpSWpe7DDzz78Nn7jvAwWH9w7x/dMGQzm8zK7mbcjHttTvP+gjIKPmuvPLN44rDDz3wfw7Jrn+yUAf5uZe2b+FoBvAPjZa7fmaEc72q21TxIN+UtE9H8T0V8nIo3dfAnAd6p9vpvKjna0o33O7aYOzv8BwF+FuJb+KoD/GsB/+DYnIKJfBvDLADDD4uoOHF/ps0CMhTI9hETKyyXrVEl668+9c5icdRqBSEJs6zmraCEIYS+FQvhLKe3deC4K4T4myb5Y6oaS105BWWZExvXLOarvAyeympQz4GWJZEZJM68Vyc3IsOPVyIYdgVjTK1b72bGU7R+j1wtMSXQBmQJrlmj2A+wkI9MMDFspwZuB9/RE67YUh13J3OTcH/s6snW5HbSP0jb1F/WyWi2rPcVZcM6yFYo8YcQ2W8p1U5Q6Yk+F2q9P17ajhG0o7VEYvZZprocdGetNl3EUgcSZ6bZGlh7JaCs4Go1NrKmTaEjCOfh0/cvaP1RFQ+yOADLSxgR6GzcNPlzfw7gt9TzbzKVejb5U6bzD6MAbh5fr4kvh+On6LK4YMz/S70T0PwL4O+nPjwD8WLXrl1PZoXP8CoBfAYBTc+/twOoRmKSwJ5aqK4zg17WK66EwISXeh7ouLjfhdUwBXIwS9Sh1lr8lrVm/l7ootYfqdsWCWHxnVp2/5pyYVKtt5mq/1Fc57Z3LgcTl2ugtGKVr2xf5lXPW5yrn12dEWbd03xpVCp5ew02tfiDBQGbM3vu9Dx4TxVel0ZvaT5EdxK9qHwMRhJqhm5mqe/jTvVVuNFgQ0ReZ+fvpz38bwP+Tvv86gP+FiP4biIPzqwD+8Y1bVyVF0YQFy5SHNuEo2NIUZ/Gm0KkyZSmuwSX8hPaIFWcmEeWwotZzrdBpQzD7Ycqa3dsVvIFRvAKXN1h0JHU1hJiwFdpetvTuQqctpiSuVEKdGWfRMWJHCJ6K8G7CM0RHWYtCB0mw1KP9oW1869BpPq4MCmFWnohQZVjmtkYjgzwTwjxmXAmlcG7ouEgK3jB0ulj0GZnJ84BmMcJvbHZmAmVGoWWLhUhr7hIs2zUh9c2stL960g+FTt3C48uLF/j9xft5v7uLLXbbchMsqtDpvB3feej0bwH4BQAPiOi7AP4KgF8gop9Ol/P/AfiPAYCZf5eIfg3A70H65y/eKBJytKMd7dbZGwcLZv5zB4r/p9fs/9cA/LVP0igAwk1RU71Vswx25o2gLEF5Uv68eo70Bm9MAmVJzF3fJmwtYiehU8q8mDbXrzocbOU759lHhTzUN7S+5VrkN3HoypuSQgIccUkVFz5Ik1GYYQLKojRrmL6NY0OTzMvQlP0ySvHAMXpNUu8UH1HPLDIoaxHhdxKSVFSlLkOk/xSUVU4TugrBmenwkaUEapk9YFpuvPyOIYUvw6Is5sPy9YlkgSSRDAB45eHTDEBmD6r/Ua49ziNCNPktntuvMwtFlqZZTGwsHp5cSq4HBJl5stri2brBallCp2t6RSKZDZNEsueLlV7aBNQX5xG08Aidy+Wr5Q4/tfg+fmv1lVzPB6uXuNh1BxPJls2A88UMDxZVwuaPhG7I6zg3a8ZuVQ6LyE66t2GpFt5FQHkfi+8gOTgjC/M1xPmYB4U3GVcPnY4ZqR45f1mDm5Ck8ioHJ8WEAUlr/aLzwdOH+VO2K+zR1XS48GISyKc2VgOC+l40OW3q+2Bc8cu8QU3siuXjKdeHijYuOyoCwMqZGapr8gUUp7+P8WUp9NbtSTYGm+uOTPDp71j5MvQ718cAsi8AFQlTrk+e+LEO1xuZsGOXzwEAPhqpS+u7Id/mIbu9g8W+1YNHxMTRmAlf9EGOKTpRfe6fgyooMii9BauHGSREMhQ5g4zYUJYwtKPejJLRmbklUh3GV84qo3WWSEBNSqvbKJZroSgIwysPmEYCRi4PZbIwlogBIA9tSPuFtO+hYwDkaI7ZI6FlU8GOdfI00JXBtVwDl7ybqo91m1xLhcDUSISb3tR1uRk4RZ3SA5AjSqlt+vPWaEh1GAaCGRIjdkQZuKOwTlWUpdKerUnREDONhthpNEQZrszIuOjbjMQMTiDcNJgMuAIgUY9I2KVR/8IGgXuPAvf2CgDT9tjq/rFSXySXoiFSvt01eDycYhjLY/x0t8S2gnvbyiex8w67TYsnm8IHED538oUMWTLsj6BK0AsUdCYqL3u1H5x5u5lFHUwhunpMzYZdefU/sR04B5vk/a7KCts1T2Ykn1o7rtm+iaO/nlSlNueBMBYPft5vb9bxqjpu3NRU/5U3LzGQQpFspD4mAG2cDNxUDR6fxPbYEye5HtMGlzd9XhmbiK7x2PZ7mXTEuXGvmxwY4oP1vUXQ7tp2KwYLMkYeeF9eadQ24MSMBUCYq5LF1hYItk3e7hjBp2nE9G/2qWa9jEHCbOrFz+vyVYcwE40OXQLEmYXdXo8spNbrzFSOFtnzLrR4dScI50NIMPRxSXC7wqnp87raTng2P22LrlDHabv22b3ZsoTraLofSNqtuSV6fRQEvp6jFjdsv2IxMiaDpg/TBKuhyxCG8Ex6Anqbo11shWeTXcnIvalZE3PdVLXRVu3xabajUQ9rIloH+GCw7VucLKTTXnbis+AKsv6qAc0eoMfrrIe1DCKWd6j99NasRz6Lox3taNeyWzGzOGTsU7ZoK9Ozml/TXuwyd6YFQP0wHfViBJ3vwNutZBdut1fOMftYFn6m94AxgpIcIlxieja9h9tamCGUugiwz9cwmxbNeUoAer7GPDLsc/Ew80ZmQKuPfOZrzPibriiDNRc+k9CSZ7idIPw0G3bxcRBx5Y2B7QPcZVozbz1mz0jYs/rpLKfrHMK8TAuaFz26zsH0Hl2Kshw6BgDoXNp/9q17U5QnoYr8SNH4hOC2jGYTyyyHAdcnBKy6Vyokpx0LCjVclGxbzVANe4S8dbntI7rHa5x9o01l6reRGZcuE2NKhhPyYjmP2xVk6fDUYf6xOquB5oLg5waLxwWh2z8ycD3DdzQRKdY6tV3Kwn3y4Q4f/pP3MsNV6Bz8fIazF1VSGASZSbHgKJ4vVuLMTC9+nVGsPpS/o6XsX4pWsl5jazF/EnL27sfLE/za05/F7HvlMf7m4hTugqCCTedtaYPxwMkFcH5SCEFofWTKOtrRjvYp262dWRCROB4Pb8xRAzZmirJ8W0uoTE7nVLwBm8RSNSLrkdRKTm++gGotreekss5nZ8r1WZTIiyI1iTLKNFrK3njeo/v/tI2T7yH/bSj7LJSti03yyZjC4EWhOGp572VFND3P2+hrTtpmrn6yRYY75xlc5RuKo7wR2UiZzpIsxD/FlW/pxiFpUzkh0/Xv92O+H6g6JiJNjYuvTCNJsamiIY6AQ5KFBMDwpL+1DnX88gRH8cnum9szWOzhKjglcPEhB40meAElWaxKGLuWsrXu4iOISaIOKSwKQGQKh4S1SNT45i0GizrfA3pOYyril6JfYrzqkQKkEn+jkMiwAewYEdPdZIYAM15/6vi2Nmk3ADCDNBSalxWSkEWhSOkJ5oInS5iclMecjlHn383bJvWXz3rZo+A74ysMS/pOQUh8XM/VsdMEt5vaJIQcS9h80o/7uTSh3ocK/4aGsmMJs/Mr7mfFmdTtj1zquZo788nsuAw52tGOdi27PTOLfTN0NYBdb9MpPFH5W8FTkov3etMdbL2kKdN9mATEMQZIs5taAexNVmMQ8hLClKVVvZyISY0LgavlRgXFDjRZ0rAzwCsEdD+xVcun3PY8vd9bhthK6QycaOn4yjJJ8QysYcu8/e0AF7kPJsuQ4iQs/V2WIZRmDzi0DEnhanWG3nSGwaZaWqWlEZtpPyLhPepjKF5dsmTFM0d5RhEbgj2gIs+HliGoloIBmKbq/ggsQzhG8DiAEp8bRwZvkojQUyHpsvfvCZeEtYKj2KZgvjXCvdk24B98XE76Y18UucLlHJT8GdQW4EtIDy15GVjGOx3cEMv09eMXaLbCs0GXEuGg1QLh/gph7uAX8gt1AHYP50ik0LDpvLGjDN3NKd4OOXrQrMvDYweWm8QSmkdCeRYW99A93iAsW9j1gLCUtruPLwA6xfqDDq7iMQCEErDGYMxaIyJDm6bQ8l068Y+kCMK4TBocmztABIYlodlMTntFom88kSVFtMi4hegENt1tI9z66lMX2/YK/+flBxZ2l2DPldYpCHBJ8c3PALezYHOSBZqUYNdt8UatUwrA0IqqeZgBs5clwjHOLUwAmq206+VPOvR3GXZr4FeM4Wl5CjV3R3VS+nsJSzHMMNwPsP1U65TCzbROFaVa+yhsYFz+uLRhPLEwqrd6P+L0/Utcrq+nddrc6bF7MoO5V6KCsbv+gH0rBotrWS0NUNP7v4LuXx2fbOngeKrOQ/VDZCkATbTaryN9spG36ZUU9b1Zx5uo+jVBDBD/RE6HrqQE5NwGJn3qdm0nV+dnopT2Xl+jlEVH5aFuZKagSMIMwCICDE/o+fN59mn6OxSK/mqbUPYXx+yr+kOvu05RrxPgmIq/I7aE6MUBWFjBU5PjNAFN6fknlq6TYnqQJ3KHKS09t6cMCqGt6uGUYMdAzMlwnGcRtPTwKWQd5pJK7neEuKgGx8R4rg8vpVT1SNNHUJMVr/TfTFLwQ2PzTCouIh6s1jhflPDobDVgVwkHUZUmP58POJ83mFdp6/i8JpJRl34d76cZp4BEJJhhTk+AXQ9OjNuUvtOuB1fHUIwA1UlCEK3T5Mh0LxPOIumgti8czGaEGZPWaTqnfte6yM8l1p5zNCLcNoL6pIua2JS7Z2PGTKiZpD0q9Y0waSnhtiEvT7TO9sUIs+7hAsPsBrh0HbTr4V72aM4c7K6+GQnEBOPLw+C2EYCR9qWHprkMk+mxOuFU5mD+5Corud+bWZjRoHsp+9Xb3Jal3ZurWqedo9wfet1+1hapwxGTmUUuV6ckA4tHepzU6XY8mUkdQobahElwO1Fr655VyTPsEDpC9yypyN1pQVEQqOOO0D1Pfc6ijEYRWZKSPIk2a2C035phnia1Ivdg0J4Dw2V5vDSfQ/Ekqg9S558AwPzJYfTxeGIRGotmUxyfiw8dvslfwOI7pZ7hxQqL86pPKsHriwcN2ucG600ZXPAps3v/cGyP9WoSSg2xGuLT9yoaoqY+giISJPkj7KzQ8QEZGk5jAIUA0s7Tc+p3rSsnkx3oZEvg5DO2fYmi5M2VH4bGkOnhaAwZwJUp/MYAeGlT/kzbKQSh8qsHQieZoGb/TaFhtBy1YMTW5GPzOr8x4MDyUA1x7xzTaw1dtV+1zQ4x9+OVrqn6w1bJcJpsZnwJH8cqjd54Tmt7ygNIOed+IsuVanP0w/YMuy0yBUAlp9hXSXQ90gyoTuLTyEmJ/thB1Myjk6WJ0vNTkGiR3XJm4a7bSlU2rJTvtXd3+E1vekikZawAZxvAXdiJhCRbmvxdJysOQZZD9czvbcLFx2jI0Y52tGvZ7ZhZELCvom7eew+IQRyaQHZ4+idPYX76j4EuE/T3ZAH7skE8mZeRj1lms704PvMM4aNMHYrtvyoq6s2lBwywediK2vhK6ju7fIDxLKmoX8rw71eyTPILB5/2cxtCmBG4S38/Eofssz/5Y1koR63WDVk8cZWKOmP7nhEH2sUDAMDFT84xf9LBLwzcZYBPjsj5osX2CzMMS4N2PZ127+uGLB8zxrnICao+CDt35RgAWP1z6fsf/CuLyZvpkG5If4/RPXdoLg+oqD9z5S2qb2ZmbB7YqyrqS8rT+qIbkvoktcEvZJ+zZwGP/5T2f1pabM2bdUPWqhti0L8XEJtZbtvuPsGvGKtvS9nuAWH3QHVDprOmXGeSNNw9kLqWH4ma+bMPp7ohFx/fTDfk4+UrdEPui27I4kOX+2b7c2v82a/+Hn7jGz+V6/ng3jm+9/SwbsjDdsTjO6d4WOmGfDQ/vOw5ZLdjsDhg5CT+xGkNryI4AOBXLVxacoRVCzN4+JMO7YWmdDLCqoMdff4EAGzKOfq7isoUEZvtfXE+9mcJ8z9vMJ42Mt1PIazxtAUMoT+z6E9TfsOmxea+hdvI4GWfyuf2IcFfpOakafe4EmYmuUCDMZEiNWvC5ouyLh9P5Rq2DwwoOPg5oXWEYaX5FC22dy2GM7qSfTqeEMZqOUrBYjyR/caTFEk4cIz0ozyImw8iXD0IUWmzZla272+wWS3QvDAYT/WOBpoLIzwQuzIlV9s+JIzr0g8AMJ4xmotUdjIdWOvy5oIwe+6w+0pSmD+Re2K3brE43SEmhur7iVvSmYjGSuUfX6wwDBa7bYMf/9JT/ODJB7lt/fsB5s6A7U5CKtsPPE6/eIHLyxlWqx3O51VexYk4CoZ0j51+UX7c7Yd38Rf+yD/E32z+NADgC8sLfPXkMf7B6R/Gzz78dj7+w/U9RBC+vBDJsZ9afB87dng8nMJU4c1fe5pkdgwXYh/DOH3/Eg9Wa3yTvwB3Iffun/3q7+G/++D/xF+uYr4/f/J1/Oa9r8EQIzLhJ2ZP87Z77hJ/7+4fxS/e/f1c9p93e6Gv19itHSzYB0wILsbSIXY9gnYpuauxQD/Arl1xikaGvexBuwH20oGSE5Orc3QvZF+3CQAB81bkAPUGNzsPt/YwPoKSNKHb2MT43cAmFGVzPmDx1KA5lzq0rvljzo5Chdy6LcGnhLDZswi3LY46TuhODTvOnjm0FwF2MJI0lqIDbu0xe2lhB0K7ni44h52ZiPkungYMO4N2HTHs5IE6dAyAPHtafP9kugY2xcGp/o1hu8LsJaG9QE68AyQcPHsWi8RBRX7D1uSZhdtp+LjMLHRwUKvL3YbRPffovisDmuqVdjugXzbZV/F4LlOgmvzGrC3MQOh64NvDe7iTHJEUWAbTixlmT3Rwc7jcnsFtCJeLDosn9cyizCQB4DIpkL33ccSvfvPn8PxDoVJ4tDjD11cP0T9eTJTCxq1onSq57m+tvjIhv1HTpLB9rdPL9RnOFydYfKfMLH7jGz+Fv2w8/s7/+8fz8b995yv46OnZK7VOHz85xT97ULRRn/XfwnXt6LM42tGOdi07DhZHO9rRrmW3dhkCQ0CtllTR6nFjMtybVRdkL8mLWycIzvS5fw5ldDaDhEP9jIRlO7N7C4Rczp/OaQjcGISZxZgQkV0n37tO41mJ6WpBJZSXZth+TvDJIRjWlKf3FJMTkZGvy3cCBw8twQ4FwMVG2LrHJU0U0wFxGI6rMp0fL0zeT52Kh47R/pK/92DKVJx7ugzxZx5mcPCBig+GAWKCXxOa5OMJGhpmuXZd4qnfZDwp/hxfaCHzdWo5G0KYWfiV+qnkRNFZxFXI/WxXGh/m7AcYqUUMhLgxsCcjQkI3EotzMywjQvrthlNGvDtibB146TEMFeI31R0VxHd3TP3V4qv3nuC3z+UCFssd7i83+M7g8MG94kh8tpmDmXA3sW1/sHoJHw2e7uS4zkrbv7kQ9WemklvJqb7ZasDwYpUBgB/cO8fPn3wdv33nK7meP3nvIzBTZvd+uLjI286aHX4HwJ+4//1c9nX3I+DgRKzgcsAEpGWGkP+mMYJ8AA1+wsFJgxd8QvrcP4dNEF8BWAm82G1j/iHISwZqnYlqhgAYgm1M9reaPqDZRph+ittoNoxmD9wkbaO8Xc1tGc2lDC5aV7MVHAM7ATEpoa0ZA1wfEdcmw5TzqfdQrM02go3Jn1p26Bga5GZtLnElGkL7KeCNQ3NJaC5LoUZDmi0fjIY0ayr9oc2k4rPYz46sy92GYXcBzXki6vEaRSL4ShApDIpyBcKVaAih77rqvEBzLgOplrXnhNg2Eg0ZGrQVuMl7dWgn5GsadJo14+tPHiI+k4HlYmex2zWIz9qJmrlGQ1QA6GLXHYyGOPXd7EVDYttg11sszguO4ntPz/Cb976Gj6roBzNNoiHPNwUPP29HPH5yit+p+rn3108Bvr2DBYDXso7ubyN6/f5Xjk+fBgXsRVVCUL1PVj+7WSJOBj5ROWedaDQh7KWyb064MlQd9xqej0/LqtMfJOyl1L66v+KBsvokVF3vTZs/ja6muricMJdzGZBSVEH3nSSxaVs/YXcS8aRtxvDVc165XaXdxnC6dXmynxINA3htSr8Q9pYXj56HDIMjTSItn9Ru92DxOpbuQ2zctSbpG8+dPiOyIM1E66Pep9ZCvcGAUd6w5Zy1bkj+Xm9npJBtmo/mfZVt/B0OGFX3TVYksWwv+qFVe/fLqpnFRNv1pvcvTz+v8DXk8pKxqcQ4um+RI0D5vT/h87SvLxojXT1n9dvmY5D2RVkhX7kngAlL+r5FpnyO+rycyuKNR+ardrsHi/oNWquJ1bqmKdWbjZnsf11FMnaUkrBUvauq2yT4tvpHksbqtRTJmpKRmbVv2pKUVeuSGi/ficvxoUkJazYllGWWqpLI9k4UydppqjYTSp+kSwwzFgW36npkCSXnLzoj6cFkmqSH58+3VSRTfVFVB+MExNKxXgFGhBw6jSH5ogDwLCA2Nh8bs9ZpSSS7iSLZncUWL+YCHnFzj9Wix/N5OwFEMRMYRXv0zmIL5qLroSzcypnJhstASHxQkWw+H/ATs6eT8OjDxQWeb+YZZ3FvWdaUn1SR7BgNOdrRjnYtOw4WRzva0a5lt2MZwgBimJDfqOCQ5ou4L34BHCPMcgkEBiU0Zo5YMIMvy/Qqfvk+KAjsO/NqqtiyMVMfAAo8Oa+zNztBh6bvgKBFt19aws+EVAYAxpMG/ZlBey6kMuZeCX3Va+t8qUbrLWVZAJcAu5apqx1maDYebBu4rUd0yWu+GWH7DuMXaRL9YCN5FL6ABtHvDIbTJKycYd5GWKRS/eOplPcPl7r5qgNy/5Vi+arfIR1jB75CcqPXaJMkoS45xlUVIl0J4xMFWb5l3o+OER1h89CVdqmQD5Ljd698v13sWPY1PMlUpUAgX7hBxzNGc6fH2DQ4ebDGZZTfEhHgZQBGys5GezZgNhtx+aUzPGyGXLdrAloXAMuYtyVVXyUGtWzZyO+889NHsCwBp/Hr5k6P+XzAxYMGQ7pfHrYj7rlLqS/ZWbOb1Kv1AMAvPvg6+vA1fO2shE7/kb0+PdjtGCwO2V6aM/uQQ6l1OHQSIq3DqzsP9APMtsC9MYzJWRlgd8qtkEKd2yjhOe0RPWf6rnU1lx6ILj/0bu3RnVuBaRPBJI2RZs2vDW3uhzObBAPPIcwUjrWNyZ+63e4Cmkt7JVHN+BJWBIDuXNK7mzXDpy5oL6M8oMlpa5LGplt7CXFelPCi2n5YM3QGzYWEN+ttbsO5H/etqUK9et3tuclhQFMR7jAJdBzQRDKgOw9oU+i0DmP6iirAD1PmMN1HP2PboFmXa/MX4s9oEgS+fW7Q2xncxuBiOEH3pPg3/NYAsZyvtx02tsOdp4xvPrkP81zq3vUW/baBed7gsT0t15TykvrEbna+SMlrmymz0MkFDtruyQznc+GjUNatx3dO8ffu/lE8flLq+R1g8rfWAwB9+Bq+/fheFmUGgO14tc9eZbd3sLB78SJDEN50TIBWE/BVdUxsLawV+UFO+1IIGemiMoF2lBtlnBuQRwZbIZ0TwKSu0FmEuck0daEzGBeE2FkwAS45Ct8EmlLAFAABTaXyDI5KQK8ws7BjzO3l1gkorAZ9AVDpwBrcNG4IfiG8DLmuYITfIr2mMyjLGTCmQCm1fcDUeCfC9hZspvWxIYwXJnNn7F+79kfOOl1VQK+lcGISp1CyOnrnEu70M4PhNP12FUBKvwMAL69WPKb+jM4I4GpZHs7xBBiXXNpzGmHuDfCtQ3M6YOw15g3EZQC4SEXQ3QFkGX6xwB968BS/eyHTpdlqwNlyi0fhDO9X2Z0v14J3OEvJbupkrEWKgakAUG3m3oD5osd6c5Idsg8fnOMX7/7+JNfjT9z//gRHUTszv3b2fYzB4qfvfzeX/Y67/szi6LM42tGOdi07DhZHO9rRrmW3dxnCe06yyKUsVhR6+j3GyTGUaPYErl3R4gEAcxHMSZ/Gc/53sI70acYIMxbyWRMYdmAYdaKmTzsU0lk1OxBi8h0Yz7ADVd+R69AySu2hvXbJ/pwdhlJxwnZUOAo7MMKQ2MPT0knsJFEAAAFJSURBVNSOZboPFFo3CoJXMANKW7RJe8tas6O8X71Nr3n/uvf7Q6/b9qX+6KZLH6dK7IZgE9Wd7ZXAR4+n/B0Awv7SNbVV9/U7O7k2MwDWUe5H0xPGjYPZWoy2QbNTOCXA1goXZyobNg4w0v4nmyWQWMp72+CcGNhZnG8qf4H6KvY8w/U+2qZDFjYOW2LYXfFZnG9m+Fb/3uQc31+cXjmn2rebe3i+meO78zu5zMfrzxeIr4N2fMdGRB8DWAN48sNuy2dsD3C85j8Idpuv+ceZ+b3r7HgrBgsAIKLfZuaf+WG347O04zX/wbAflWs++iyOdrSjXcuOg8XRjna0a9ltGix+5YfdgB+CHa/5D4b9SFzzrfFZHO1oR7vddptmFkc72tFusR0Hi6Md7WjXsuNgcbSjHe1adhwsjna0o13LjoPF0Y52tGvZ/w9d3p6xIk1iNgAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6518>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.41978454589844 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-08, 'kernel_type': 'size'} is: \n",
+      "[[2.000e-15 1.200e-15 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.200e-15 2.000e-15 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 2.000e-15 ... 2.000e-15 2.000e-15 2.000e-15]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 2.000e-15 ... 1.052e-13 1.052e-13 9.840e-14]\n",
+      " [0.000e+00 0.000e+00 2.000e-15 ... 1.052e-13 1.052e-13 9.840e-14]\n",
+      " [0.000e+00 0.000e+00 2.000e-15 ... 9.840e-14 9.840e-14 9.220e-14]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acda90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.5938081741333 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-07, 'kernel_type': 'size'} is: \n",
+      "[[2.000e-13 1.200e-13 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.200e-13 2.000e-13 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 2.000e-13 ... 2.000e-13 2.000e-13 2.000e-13]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 2.000e-13 ... 1.052e-11 1.052e-11 9.840e-12]\n",
+      " [0.000e+00 0.000e+00 2.000e-13 ... 1.052e-11 1.052e-11 9.840e-12]\n",
+      " [0.000e+00 0.000e+00 2.000e-13 ... 9.840e-12 9.840e-12 9.220e-12]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acda90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.47510862350464 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-06, 'kernel_type': 'size'} is: \n",
+      "[[2.000e-11 1.200e-11 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.200e-11 2.000e-11 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 2.000e-11 ... 2.000e-11 2.000e-11 2.000e-11]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 2.000e-11 ... 1.052e-09 1.052e-09 9.840e-10]\n",
+      " [0.000e+00 0.000e+00 2.000e-11 ... 1.052e-09 1.052e-09 9.840e-10]\n",
+      " [0.000e+00 0.000e+00 2.000e-11 ... 9.840e-10 9.840e-10 9.220e-10]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.60181427001953 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-05, 'kernel_type': 'size'} is: \n",
+      "[[2.000e-09 1.200e-09 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.200e-09 2.000e-09 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 2.000e-09 ... 2.000e-09 2.000e-09 2.000e-09]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 2.000e-09 ... 1.052e-07 1.052e-07 9.840e-08]\n",
+      " [0.000e+00 0.000e+00 2.000e-09 ... 1.052e-07 1.052e-07 9.840e-08]\n",
+      " [0.000e+00 0.000e+00 2.000e-09 ... 9.840e-08 9.840e-08 9.220e-08]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.43672800064087 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 0.0001, 'kernel_type': 'size'} is: \n",
+      "[[2.00000002e-07 1.20000000e-07 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.20000000e-07 2.00000002e-07 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000002e-07 ... 2.00000002e-07\n",
+      "  2.00000002e-07 2.00000002e-07]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000002e-07 ... 1.05200001e-05\n",
+      "  1.05200001e-05 9.84000008e-06]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000002e-07 ... 1.05200001e-05\n",
+      "  1.05200001e-05 9.84000008e-06]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000002e-07 ... 9.84000008e-06\n",
+      "  9.84000008e-06 9.22000008e-06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.504371643066406 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 0.001, 'kernel_type': 'size'} is: \n",
+      "[[2.00000160e-05 1.20000000e-05 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.20000000e-05 2.00000160e-05 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000160e-05 ... 2.00000160e-05\n",
+      "  2.00000160e-05 2.00000160e-05]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000160e-05 ... 1.05200103e-03\n",
+      "  1.05200103e-03 9.84000752e-04]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000160e-05 ... 1.05200103e-03\n",
+      "  1.05200103e-03 9.84000752e-04]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000160e-05 ... 9.84000752e-04\n",
+      "  9.84000752e-04 9.22000804e-04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.47750806808472 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 0.01, 'kernel_type': 'size'} is: \n",
+      "[[0.00200016 0.0012     0.         ... 0.         0.         0.        ]\n",
+      " [0.0012     0.00200016 0.         ... 0.         0.         0.        ]\n",
+      " [0.         0.         0.00200016 ... 0.00200016 0.00200016 0.00200016]\n",
+      " ...\n",
+      " [0.         0.         0.00200016 ... 0.10521032 0.10521032 0.09840752]\n",
+      " [0.         0.         0.00200016 ... 0.10521032 0.10521032 0.09840752]\n",
+      " [0.         0.         0.00200016 ... 0.09840752 0.09840752 0.09220804]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.53379511833191 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 0.1, 'kernel_type': 'size'} is: \n",
+      "[[ 0.201604    0.12        0.         ...  0.          0.\n",
+      "   0.        ]\n",
+      " [ 0.12        0.20161616  0.         ...  0.          0.\n",
+      "   0.        ]\n",
+      " [ 0.          0.          0.201604   ...  0.201604    0.201604\n",
+      "   0.201604  ]\n",
+      " ...\n",
+      " [ 0.          0.          0.201604   ... 10.62461674 10.62462998\n",
+      "   9.91626513]\n",
+      " [ 0.          0.          0.201604   ... 10.62462998 10.62470302\n",
+      "   9.91641722]\n",
+      " [ 0.          0.          0.201604   ...  9.91626513  9.91641722\n",
+      "   9.3027898 ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.34999179840088 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1.0, 'kernel_type': 'size'} is: \n",
+      "[[  40.   12.    0. ...    0.    0.    0.]\n",
+      " [  12.   68.    0. ...    0.    0.    0.]\n",
+      " [   0.    0.   40. ...   40.   40.   40.]\n",
+      " ...\n",
+      " [   0.    0.   40. ... 5812. 4962. 3816.]\n",
+      " [   0.    0.   40. ... 4962. 5996. 5030.]\n",
+      " [   0.    0.   40. ... 3816. 5030. 9688.]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.71121406555176 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 10.0, 'kernel_type': 'size'} is: \n",
+      "[[4.16200000e+06 1.20000000e+03 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.20000000e+03 1.61616200e+09 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 4.16200000e+06 ... 4.16200000e+06\n",
+      "  4.16200000e+06 4.16200000e+06]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 4.16200000e+06 ... 4.58167818e+14\n",
+      "  8.59206324e+13 1.21226362e+12]\n",
+      " [0.00000000e+00 0.00000000e+00 4.16200000e+06 ... 8.59206324e+13\n",
+      "  3.57910702e+14 5.91280962e+12]\n",
+      " [0.00000000e+00 0.00000000e+00 4.16200000e+06 ... 1.21226362e+12\n",
+      "  5.91280962e+12 1.68787581e+13]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.44119429588318 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 100.0, 'kernel_type': 'size'} is: \n",
+      "[[4.00160020e+12 1.20000000e+05 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.20000000e+05 1.60016002e+17 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00160020e+12 ... 4.00160020e+12\n",
+      "  4.00160020e+12 4.00160020e+12]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 4.00160020e+12 ... 4.48100809e+26\n",
+      "  8.00584079e+25 1.12091211e+22]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00160020e+12 ... 8.00584079e+25\n",
+      "  3.48098011e+26 5.76151612e+22]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00160020e+12 ... 1.12091211e+22\n",
+      "  5.76151612e+22 1.64839642e+23]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.6218056678772 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.00001600e+18 1.20000000e+07 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.20000000e+07 1.60000160e+25 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00001600e+18 ... 4.00001600e+18\n",
+      "  4.00001600e+18 4.00001600e+18]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 4.00001600e+18 ... 4.48001008e+38\n",
+      "  8.00005840e+37 1.12000912e+32]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00001600e+18 ... 8.00005840e+37\n",
+      "  3.48000980e+38 5.76001516e+32]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00001600e+18 ... 1.12000912e+32\n",
+      "  5.76001516e+32 1.64800396e+33]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.44198703765869 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 10000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.00000016e+24 1.20000000e+09 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.20000000e+09 1.60000002e+33 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000016e+24 ... 4.00000016e+24\n",
+      "  4.00000016e+24 4.00000016e+24]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000016e+24 ... 4.48000010e+50\n",
+      "  8.00000058e+49 1.12000009e+42]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000016e+24 ... 8.00000058e+49\n",
+      "  3.48000010e+50 5.76000015e+42]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000016e+24 ... 1.12000009e+42\n",
+      "  5.76000015e+42 1.64800004e+43]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acda90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.698798418045044 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 100000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.00000000e+30 1.20000000e+11 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.20000000e+11 1.60000000e+41 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000000e+30 ... 4.00000000e+30\n",
+      "  4.00000000e+30 4.00000000e+30]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000000e+30 ... 4.48000000e+62\n",
+      "  8.00000001e+61 1.12000000e+52]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000000e+30 ... 8.00000001e+61\n",
+      "  3.48000000e+62 5.76000000e+52]\n",
+      " [0.00000000e+00 0.00000000e+00 4.00000000e+30 ... 1.12000000e+52\n",
+      "  5.76000000e+52 1.64800000e+53]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.56881403923035 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1000000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.000e+36 1.200e+13 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.200e+13 1.600e+49 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 4.000e+36 ... 4.000e+36 4.000e+36 4.000e+36]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 4.000e+36 ... 4.480e+74 8.000e+73 1.120e+62]\n",
+      " [0.000e+00 0.000e+00 4.000e+36 ... 8.000e+73 3.480e+74 5.760e+62]\n",
+      " [0.000e+00 0.000e+00 4.000e+36 ... 1.120e+62 5.760e+62 1.648e+63]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8908>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.60561800003052 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 10000000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.000e+42 1.200e+15 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.200e+15 1.600e+57 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 4.000e+42 ... 4.000e+42 4.000e+42 4.000e+42]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 4.000e+42 ... 4.480e+86 8.000e+85 1.120e+72]\n",
+      " [0.000e+00 0.000e+00 4.000e+42 ... 8.000e+85 3.480e+86 5.760e+72]\n",
+      " [0.000e+00 0.000e+00 4.000e+42 ... 1.120e+72 5.760e+72 1.648e+73]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54822470>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.46787214279175 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 100000000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.000e+48 1.200e+17 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.200e+17 1.600e+65 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 4.000e+48 ... 4.000e+48 4.000e+48 4.000e+48]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 4.000e+48 ... 4.480e+98 8.000e+97 1.120e+82]\n",
+      " [0.000e+00 0.000e+00 4.000e+48 ... 8.000e+97 3.480e+98 5.760e+82]\n",
+      " [0.000e+00 0.000e+00 4.000e+48 ... 1.120e+82 5.760e+82 1.648e+83]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.56626272201538 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.000e+054 1.200e+019 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
+      " [1.200e+019 1.600e+073 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
+      " [0.000e+000 0.000e+000 4.000e+054 ... 4.000e+054 4.000e+054 4.000e+054]\n",
+      " ...\n",
+      " [0.000e+000 0.000e+000 4.000e+054 ... 4.480e+110 8.000e+109 1.120e+092]\n",
+      " [0.000e+000 0.000e+000 4.000e+054 ... 8.000e+109 3.480e+110 5.760e+092]\n",
+      " [0.000e+000 0.000e+000 4.000e+054 ... 1.120e+092 5.760e+092 1.648e+093]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 35.544222831726074 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 10000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[4.000e+060 1.200e+021 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
+      " [1.200e+021 1.600e+081 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
+      " [0.000e+000 0.000e+000 4.000e+060 ... 4.000e+060 4.000e+060 4.000e+060]\n",
+      " ...\n",
+      " [0.000e+000 0.000e+000 4.000e+060 ... 4.480e+122 8.000e+121 1.120e+102]\n",
+      " [0.000e+000 0.000e+000 4.000e+060 ... 8.000e+121 3.480e+122 5.760e+102]\n",
+      " [0.000e+000 0.000e+000 4.000e+060 ... 1.120e+102 5.760e+102 1.648e+103]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.25954580307007 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-10, 'kernel_type': 'branching'} is: \n",
+      "[[  20.           12.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [  12.           20.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [   0.            0.           20.         ...   20.\n",
+      "    20.           20.        ]\n",
+      " ...\n",
+      " [   0.            0.           20.         ... 1052.00000018\n",
+      "  1052.00000018  984.00000018]\n",
+      " [   0.            0.           20.         ... 1052.00000018\n",
+      "  1052.00000019  984.0000002 ]\n",
+      " [   0.            0.           20.         ...  984.00000018\n",
+      "   984.0000002   922.00000032]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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Ke5hqTEeOWZhy8Tp2IO3K56t8LaBT8d5+R2IiAOLjT+4kkIyuNgd/12lU6gOQd2D9Qw2xdLbKInU20Jk4bYwsjTFW3qmXkYwjnAHtpkCsKT6k9oyFqPeWCHS5hlyc5fECaNTB+P4jBW6l+Bupd90XBZJ9tCheFmadZz+oapwnoAbevF5JlTOmIA8OuTWL2ibv61pJHUgGYPa825cOjGFP448ur9SLVY+rPx57dDJwnuhEJzqK7oVkAeBacMg0gGrvWI7FLZftGzeEsNf9mTFzDLo6DXT2Bry1GcNL0IdUsCB7xkXrJ0za3xQ1azNxqUbJbWJu3xBKMqx4QKI79PeRlG1HzfgOrG3tgjaJJ4/ZjMZp3LwPXLsx1WsUIxArNWk6zvzJZZwijV3FKI/xuudHpJ1r3T69/muge8EsJEbI0DexIfEqpVBLqL0apGWAK8BsEmqjaEBXD86LkdRERNMzq7Dl3M8siXOij2J49NGeoY4cq6pD3BjpaDYrMRUmtlf5OfJNq2wKGTAFADGUmJI0BzpbKQCrmh+QsACLOdwXPv9i0BegIqbFOJjYPAxtuHiNQI3SenEmx2SadSpmV7+ZZ8NE3T3qZg24DQD4K1/ax2YY1Z6TmOwONrfaflCdJ26fmVOIeU4y64AnGq0rUJWOHBc70Ve/rF6pECGdLzaLyjZChsmYd6ra9APiag7a9GW8LqmvdZq+ib1GEjiLxpYR0LPt/hwA4Pu/AmFWz5jNF0A4n8NdlngemXm1WdjfvqxJ/NrnwNsxA8AAQP5pG8H9IroXzOIgHQpGsp+qYCXzdjReDzsmxgLaMjJubQ9CDe4KoXg5rM9qLBJMD4+QWPISyBiS54GQnV/Di0FT5qkAql0ZhTGhH4rnJSbbi/3eD2oBr9eIuAV9pbmSeYZs5xpHfakOSSyYeHGMpsbmYVAGNE1qE9VDcohZUCzxHjZvGDBJGwtjuCZQTczqX9tfDthUmnPyTi7q6dhVL5YZflMbbWb6kqc8JsYY8nUqbxUZo4oR9PSq6P5mxB7H4p4H9t3G1wWSTQMcbW4+BZARZQ8H7Qa4YSwennRcA/ZrvCEC7PrGS0NT290L6P4yi9r7YWSLVHk4Wq9HZflNWAzDYeQ+uZIkMJUsKi/HdldJFqXP7CHx1U4965J3o/Lve/9ib0XyVADqoTDJgtLDYh6WqWSBqNLVngRgD2n98o5B4cyVhwIDt2qMPdBjekluIFlMd3aEoPMK+y8tullZD5OoakwHs6IWo6gnon6IzThokuENJQs7VmZd+yLNZ0CF2ZHVIsPSZeaBCSbDXOm2BuIZtB0Uv/G6JItrVAc5W0IcgUIVSDbrkmRRJad+gWQRzufgjYd0lbv7wJpdR/eKWTRRp5MHtsFdNGoEDksWCYtR2zyk7/f1uJtKFobPqCQE1R1VV5Wx8rffpWQxlQCMUdWp72znPBDunb9aZjDbtWvsQ913Ta9JspAJ9oIMolzbaibr04zndUsWz6+yi5eMIeoAitSTwV6JEW97xUbctWThuLh4bQwh3kyyGBVnIv52ksXJG3KiE53oKLpXksULQ9QX84y7MAyF/pB2dZJmN8oiK3FJovveu1kfDR9+1F7c7CCW/CaEYv2vr9X5Zkcj7zUatR9AJOD33tHu3n+0v2tMkt9Ivbu4oVwXSAFd+1xfklRFq2UD5d1LpgvorslUrPMAMPTNsWZ7oXceADEeh324RfIbqfJU2ry5CrM3j8W1SWPOloiP0j27JvmNHPJWVR4ZmSa/6fsGT+FWyyIhBG7nmBCYGfhnIQIXZ8Cjj+4++U1SU+XirBh6v/MBsPYZI6OTeEHyG5fwH828jveY3Ctm8dopSnGtAq/HlXQwnXqBnNMNFv+V6Rj3bJ3QFihrUv8O6MtwA5H0tVMUCKdPxOvdgXdIUqtACfV54CD9pKTivOGEQbrZ3fKaIc3pls/o/VJDrvMb14cce3MO9RFCWbBXpXjNON/UA3STOUyljkNSyD0ije2gfVvJmyROhuA6R8bUBnWHWdavo5vYGPboFcd7PyQLAsCuKU/Hq1Vxo6EYfuIHjzRxjYmD3quBqo49ANRAaYlpEtWqh/va9+mXQaHAspiBxqAJUQDg2aWKfrEEl1HXQXa9GpGqWA5aLfILaElk+Af/XGNoAgB0PlunedMXa/kYIEuNJfGfXGq/F6tsjKJhzEYp2uwgy7kaAifZnKTzjQWe1lvFCwxjntfBcwBIStojP/JDoKGFOWeLenpxwsLDbUfQENqozSGAh1DuQ22kXHTZ8m/niEi+Vt2PpL6snYYAPHmO+K//K7rGtoZjROyK+7Wx8qex8hBBUSNiw9LDP0nGTBGEpXo0fMI2RGbEVZfnxes2qYzOMcVlrPT++w+e4urf+QvoLnVdoyPEGcNvAsZFmRPbeZ15Q5L6FwQQIM7078WHVQ5UWz4CAhFix/BPd1mN2PzbfwG7dx3mT8r9CguG20R9p6Rcx/pz24BQjSs+OR5ncb+3mBOd6ET3hu6HZHFTqpOpStQdagouMlBWuEYtsB02ZRWiYVSXmRkgDYYbK/05BAU1oYIcp3DxLOkYnHhXwuhztKYIaDT/ehX6HgXozSWcrpV0Zho1cMhwTDlvxHDACBwn+mw/aNs4FlvKoXMAREvVthnaPpjymC1i0iWJgIZKpYsoUadGNbR6KFGUee2GsYRTjy2Wo26nUYFvvEluacMoBEk7swHt0jo7zhehMYKGqOA0orwrUxAwEaTjLMWQjOpKHiPgQ85aBQAyVFnCUFzOtBvgr0JObceeEUcHtx5AY2VwtxQAlsW9Y+3DzGlp7LxL94dZxwEAjkBjBHsGb/sssXaXI8QT/LpIFtxHuF1UMSC2kgVFAe8CXJXv4iY2tk8ns6jxBMRFxzU6ZgEqXbTRT2trteMUpTeBGR9BwgSS6hp53PvfhW0caFMDOtab2YwrgZeOHskNabqWVT7L/TWrcAcsgKFaJ0AfIdmf+23HVn0K6b+8GjlvSHkptUJa8vowlXwSKC+veVHoGg/Py8dVX5vK3/UyxBY7YmoCSFUme1Ty+Fx5fq693wyIA5of03WFCMRtJnA6mAr5eLq/zGKaKLYGEnmvOTOBlM3K7dV5yAjIA7kmAEAWCTFpNovVQndry3Ox2SLnETDAkmN14c66nM+AAMj5qoRtW6j7+VKlBZsLVP823ZzXff5OQ0A40/H4lGdSVnPQegeZuQYNSCGU608zUHe+yVVAKV9DgyY8cA4AULIXje8sW5sFKhuDYYFWHm49gnuX4wxIks2iD3lHrMPX49l8zz4hZ7OcXLaOVwDQtHMfwDGif1dd66b38xARZhVz9cZEygvCgwOJHjuuHOY5bF4QzjqEWUGLSrfAeObBQ1T7wFVZq5iuw70eO57pui36EesvdZg/NYmBEGaM7sphWJWxuSFJcGmMYUaAABzS+qR2TuUihahBcw7vzBE7wuyJz+u4/uIMm88xltUajAuC31Q2Cd+ymW4TMSyreJGuZewvovvLLIDGwLkf95EWNSa//lSaMM9H7S+v+shirkGhk0icHzTzzDRitWg2JaBiDim7Uu4vian9uGfgJFNrAL1eFZ/BfSjXBIqIPwZNxkJVX6aaTI2VIs0DRimbFg1jUXkOnFOPm7dDC0EmyshaqXZP7kOTRdqYRaOaZBVFk67sQZtjzA8+T1TFup2GAPQDeJvWNon3FNR4aV7jzCy47NQ8iqoiUeCYyhiCiuSQYrSkIcKna/PEwElDa+DML04/oFvHrArEjkEj9O8adDqq9ywzupFAAUUN8frFmFGdsFeY4HtlYLwuOInuKiLMCX5dPdeB4CsDZ+wqySKogZOqR4DC5L15Ad1fZsFVsBMwkSxcm4NzHEu+TEDFYyGFbjtXINw1GMl2VBOPZ52Kg4skMVw59STUL6l32ROSJYt+0OxKlmbNvDczXyQj22Cdy1Z1ro6lGBGWnWYySlmP4szrMVX+RQDqOZl1mpl6Ks5PJAuMQduIsgRx6BwApd7nomvsP1J5Q8xmERYOzhPEMeLcJAsB9Qyuxd4KEBXnHuRbbwiigC3xzFSyqNqZGTTrEJa2NpVkMefywlkWKl8Ym9tF0MjgUTBcOHBfMqSFhUdYMLhPa0CUJAtWyaIaz3WShZ916M8ZNNrYCOOcAHiMlWTBY/J6pE7DnDQbgo09Heov0/PjuXiPHIHSi89DlxnXcO6we8ioH9Ew1yxhkrTEUDk7KCZBs5IsmlIBL6GTN+REJzrRUXQvJAsiBnUesqvEWlJzjFVgGt//IP8mfV/UkISnQAiaCg8AxoDw6CNcl/IOAPAs4RkSdJs2W/U0XKUdznZckWKwE1EchaUBBDR93uVVTqOXK5N9+GQveKgx8tVBSQD4Sdq903V5rfU7KF2XQglqou0OePTxgUA1alKmWdh8DT0+dA6AXMSp+/aBKld1DlEgR4c2UZ9JxZLFvM2+nebqprUtAOCjx/k+umsS9roUbBZ3OyxszQ1qH6XU36j7NWkMUDUuqYNz74rkGATuUu9HjtL86Ak6y/L+koS9nUUdX63xLlf5Ook0QnUY28zjlvncok6dK1nbRRDOFfpu3hDh4qUBA/yhPnd1wt6Hl5/HxbIDb6soU0d7amT+ut7mADgjd3UYXn6I7gWzOEhVxmMAaELWrVIYkhEvRG3L+Q3x0oS9hrXPN9ASnNZhxWYkNcbkj0/Yi3mp9CSNpfwAs7AHzHIyohLVLdFrnX/CO2A+v5OEvbJatPaf2jtj4CxO4f/9WNqiqh21ETc/tNVLART1yy2XN0rYG88X+fqAMj7pHGB6d1b3uAkB5+0AECHOfRsazoTYObiUxt+tFrdK2Du+u4Rbu3ztOHNwm2FSCkDtJvYsxLkv2b2BDJQy46R4AvVFDek2K0wT9g4PlxgedI0hFpSYhXlbKibsOvfpT9gL4FoD5bVp9dJDLyPKg1VjJ156vepBTh4GxVmYMVSrk1EVI0AixzufKmMmxbIz511xUjdE7BwzkAIHkZA1PuNOyHbAeh6JqWWjrkfOmk31cSGq8XecjNsYXIXJuA1lHd5MDMYkskG1xLkYg6cxKiOTCKYAMWNmjBDP4Ch73p8bjyvEylAYk/Gyxf5QSOOwtUzMg1LYQLZlJaOxDCjnXwPTphDBg4ArSWKaC0Reo6Xh/jCLl1ETDFUiGEEJlDWJdHxZ3ZBSNiDVudhNxDHDONSxKiRH1w1BVduk7Jph4i+3rDrJTSZSpblLv01yRmYmdEflC3m6DtNM2kCJuB1DVd9ECtMz6ab+bag8PSYZ3LR84bbfO5aGyhBuL2JtEI4RtBtUdRodME+G7TGCxljg5IBC929RN8Q927V1Q1JKPtdfr4ZQUkOEFZxlQm8GgrkyLrgIulzvqSHucqcMp1JDwIlBHsjubWrIqXzhiU50ojul+ytZvKjIEDvUJQWzDaEyxL3UZtElndOMdFZtvSrHJ97pjm/nMR9vs5h1Bw1vWQ2pU90hGTbrXd/+Fk7h2ybCJ//XXdksFvOJrahCdFboQkS0RjzDpHhXCvxUmBXbQfP5APiGNgtZzpvzEdW2k/u167l2nc3oK/PyjIgTwCWbRTqfb2mzCA8X4GSzgCN1925cE9iWpdTKJZxtFgLEZLOwqYlncOWypvN9m8V4PsfwYAa/rqRJVgxMlsiqtHqfCZvFwezel1qqLlp27xyFuoBst0Xs7zr93nWIT0shIn7nob6Q3udUeDlxDVDSyFlE6WKuAKv08MdPngBd16oYXafeGTNIAppSbbkArtYqgq5S1awx7MVhwPvyMm93Tf5LEn0RYor+5PMz9eQYMtXWZrsFLRbAw/M2HoaogS4DKNGmVlUbSXyu6o7aQ8/JsCkxNuXvAFRp2FL7fAba9Wo/qVPXj0G9TNNoWwC8mJe1trk8PC/jcC7HM6Cy6AuReg3OV1WsTRunka9vL8YoVexOLMcGBn/8tMxrMQN7B7pMEc2fe4C48KBRcS9m+ERErhpmqkFcdJDOwZ2p0TUzLKiniKQYM/UESfeo2iAq+4LbJC/aJ1d7awcA4XPnSZVathupeaasz44r5k7NhrT56hm6yxFhXjGXP/ysIDivoTo5r32viyXrD/bkVVQtak64aw3gPOn3AAAgAElEQVSzTh8w2zG4SvdfXcsYRQ4ZH1hvel1SD4DMuyb/IYAmhFw9B+k7U4Gfm/chJZc1AFpmMi5laOp8i+oEmhB4nW/yrkglMdluxqW/vDYiGip/Ddw7d7vodIOchKhjCIrKxD7V62HzjgvfQsAP6NniGRgJNAbEtEYlXLzdvafj1GNCPjauOtBlQSnJcgZxDpwM43HhEZYelODeNLPylYLoGSSl0llcet3F14ThovQZO0b0BO8Y47IKUU+oU4NfX5ewl9czHKKw9IiOFGRmksXKY/fQAbFKw7BwcPWaVM/DuGAgeoQalHUDQ8T9ZRZ7CVuqWJEalWnf6yrqSEwkUokdAVojVRXbAegOS6jES+eK6FlfyxiFHWfxJJb122JDEiK0oRphmdCVgO6eMk/jyQjQhAqdMrG+V5fuvGvStoGocVsC6i2IM5+iKyt1oXZj2guRmIoygnbtp+jKcJakEebmN2ZuPSQ11euRmUVXGHKdz4IAzoxFDX1uCDmHRI2mjFVcxKE4Bx7KseOZh6/ym5h0wDttC0uPceXAA2vMSKWO6d+A2+m4hpUHGHAbh/6CQQmaGTtSiDVTi+C02JAEvw7p0w2T2I1nh/NLjCuX+7Uo4PHcYfeA4YaydsOS26TiFdx7OGMIA2MdG3JCcJ7oRCd63XR/JYtp0ldzGTpNjmt2BLMpyOQcGRTVKcNQMl1VqdmtClXWo4EcFGbn532luhbtenXXGaZj16ubbbvLRiUAoOfrm9kskp4f0/X5cq19mu0j/S79AKy34MruoBdU1CJNbBY8eO077YgWZZuNmEMl6YjAfXK1Z7NojKZQUdlsFvVvNAZgu2tdjvZbVaDH5u2BYhD2LkdaNihEouz+9I9bUBeFkL9rHwf2vspm4a46vS+JXDLQms2i6xzclYKl4tyDkx2BROA9K0DOkvuuO0TP4HWPs/+PMxJSvALCeDuiW1SgrIwRMaNlUkMmeVius1nM07lc5aLwa4Jfz9A9K+7u+dxpgFyiui7IcKEArjDfj4Y9hu4vs5iqIXUVpcr70ISib3fVMTN9+WuvRFVDg1YJDWjM4XyVg8IAAJdXpRBRdS0sF3oDTI1hRrxYatRkil4FALlYvTCEPIePA8AwQsxQ9ux5GQ9QCvrk0osBtFogPliV5ChAym3Q6vC8HVRd6cds+OTdoA+sQU+SsYuhL3R496yJJgUOqyHuqgP3oVVDemUejRchkZwty3qkeY/vrvLLErti4BRHBZzkNKDKXe0QLlKI+o3UkJiPHc88FlUBnnA+h3QOPqlH/edWqoaMgnHF6J4Zs0hqSBQ4CyRLasH8Y8b6yzPMn7ZqiF/HI9WQ9mVdXpOLZfvFpfa7Kfc8LAjrzzmsPq4YwpLR1cdUasjuIWP+zGFY0cHfX0b3ilnURYb2JIthUFDKOAI9v1yy2O5KSQGLDakfYmNGN5QscLXW3Tt7J3bKKHa92g0SwyIrNFPT65QsrOhNTc41Own1gwKEarRoAhyV7FKJeV2uISJwjt+cZFGlAHD1NYiKR8UlO8iuL8bQO5IsZp7RzTtgjOgWvnhDRMsIZOAcAHelxmT/ZIOzKHcuWSwluVBrqWHubiRZzJ55+KsxRwoDyMzvGLpXzOJ1U86gldLdE8kegvFWfdaUK4ElA+zbykh9KPtUHlOLm9BAsMl5RDl4722RFf7VkOzqxa8RmXc9BkpGb6aSQUsUk4Gx8tTwvqv6rseV6QZGyaaP9KzKLR/Re8Us6iJD02IrqlaMcO+9i/DR4yJFWFGbENuoUiYA6o6zkoL83jsJix9zFu7s509l93I+inGsYjPKtWS1hObGrIrmDmO2WdDFuZ7y+MnhCM+q/zoSlJJEYpJJBLI0hRgLIGrQcdKsayWLlBqwYWZRc082GcJ2vXqKptDrs6Xuco+fZAmvXctqHgn7YRG7ue8XlC+s4ek5PqLut09jF9Ex1XMTUfXwoyfteVHa8nwvKV/I3kGuimSBdSoQlXA43HnQVmH6vCvlC5v6q5YkyKlXTBadRuoeKF/ILyhfeG2RoSrDfU3OnpXlLMd7+A8ew308a8oXYlK+sL4//N4D8G5Q+4ut2Xi8ZHHyhpzoRCc6iu6HZEEA2CFeFX2NLy4a5GFM3H/87vvwX/tqRmDSfAbZbFTyyMFcosbMQe0CtpOF9x+V/n/wz+n5KchIzpcNFNZ9+ETDzEXKrpGAUjKvMmU9X2uND9uhH+vuF/7VH9gzFIZZyVnpL3sEy185RIznCsaZfecTnefnL+Aud4oz6MeMQ3CXW8SLJQIzeNcaEuO8ywZLAHDPtojzDrwbEBOOg3dDo2oEa//2IwiA3Te/nrNB5X6TEdHE1/HcwV8GuF3MlnUSNSLybixp6qr0euP5PK+HzVuYtM4IkoGzorqdhwD30XOsv/Xn0zwTXLyXXG8DqIx1TQ5OjezkQTCcMVbvl114PPMIc8L8Y20LC4fx3OV+/WW5f3uZss51vKs/vcIHf+VrmD8xQy0hzAjdVcRwVnkdemnGGGcABGATUNObeP4dy9uKrCoK6ZzDjDF/PGj2bgCP/+L3Y/NFwvJRuaPDitCty98VXgtCQHclGM7K+ozfPp4F3A9mcQzV4lqKFcjf6xT6+fiQyglWId11H1VUJwlpct2JITB/VunhMI6KuLQHchybtPx2Le5DMciZ2E1URLmxlB2gkIrz1AjTISZ1JzYlCqyNJOx5W7i6PgBgGPV69pm+T8+x9QJSjsZhIsZOYlzEEdwQ8wudDx2Cpt2v1wvQ0OwhFGOjvdMoIdlTcbxu17Uc4VMOzpBsUMoIapHavohmvQbAOwEHAY3JJZtVS8DtAgCXQ7xpo/PlISKOWiioLI/dV1MnEsPaDfBrgd8kb8cIUID+XcUi8aAQcDZvyKh2o8wQDP9nOSxqZsEABwIPAr8p96dbC8bnyNe2eXXV37F+w0UT9jZrdoN0ASc15EQnOtFR9OmRLKZkrk/zQBBV2Iy4L2lc20/lzQAK+7T6HLEYJW9a70KmfdZUtxGlOg9og4+Ytd1iUupj7zIBTm20rNYmB0Elj4pUgVG5iA9QvAjZqGc4l0n/NyzQu1+/JBVTnnQjrlpHFoild3Cty1JIE9vKq3qwqP1+MN6CAKkPpPZYU/Hyp+csiVnC3kMkTCUiuRqLJeytPR/X9XEsnSSLE53oREfR/ZYsmixN1XdXuYesmhgzcgg1oHkcaCyfmOwgFsSVAqssL4LUUsS0XyLA+7YAsU/fLZDMjKkzt4fJkLnLhjwaYjFGDoDMGBIrF1nHkIFyaHTJf6ltkdwep98zcPZeDZzpN2B/d8jtKQo1LBy4r9cdCF11bShyEKKIxoygjAIHaASwpQGorqbFgtL32phpOSmnEaN1OxOo07T92pdJOtyUAjB0pDQ7NoODQAbBOGfMrOgO67lhzlnaCHPGuGJwT3qNWMaUDZxJkjJ0Zpx3GFYE16c+Ok3Hz4EbpCQPhgS150P/zlkcnd0PMyZTMZozQbyiSHkXc3LjYUUYzgG/qQyWy7IGer12WYW5MXC+sahTIvoTAM+hb9MoIt8iovcA/M8A/jyAPwHwsyLyyS36bqTLjEkAEkingGNA+6Adizato07rl7eECHNmFoixwKUTs6hLxwlThmnXsG2ZVchMq78xO/Ayd648dB3nF4Sj5Beyy8zCAZyg2WOVgJYoowSnOA6ZuwadxzMPmTtNbJvaD51j8wD0hZmCduoHGNBQZxqBECRXBMu1P0eXQ9yb5DcdF3tnXUk8LVKdY0EHX7Uz4CpmYS+cY8E4LyK6tUsS8fP4heBYEOaUoyyJKXkYKI8nLByGJcM5QZhRU4wnzO2a6UVNkZsydxjPCOPWxpCYxYiGWbi+HWOcQ70hg36a1yJXWGu8IYRxQamgkMvP/rAijGeC8bJiFmcoyDJJXpdExhiG8+o9OD73zWtRQ/6SiHxTRL6V/v5FAL8rIt8A8Lvp7xOd6ESfcroLNeRnAPxk+v7rAP5XAH/zpp2I4fBtp51UB8/GsTGo228ShyF9n+JIqNQfrfrgTcJpjIrl4HXfuhiTy7SOk6AQge1ODXfWvt3prmwIzHQtf9mXQC/bLIYItizO26HgEWKEv+KmvKGWqRNgO4JCAG0lj4G2o8ajTNygrvfgOv381Rau11qnzqpuHTjH1gsAZk+H/YpkO4tnSO7C0cHtAngbclIXrUgWmxoWtQvVXRW3Ze4/uUUBgK+pdcqp1imtt5g9SUlqqopk7qiKZKJlDKPLGAUKUXf2hcClMbtd0DU8otaprZt7tsXyw1XBWaSKZLPnEX5bBZIdWZGse56e1UlFsu4KqdbpkF2nq488QIzF4ypw7EpxFtdWJNtEDM/rADccTa/KLATAPyQiAfA/iMivAPiSiHw3/f4+gC/duveTzeJkszjZLD4bNgsAPyEi3yGiLwL4HSL6583ARCQxkj0iol8A8AsAsMDqFYdxohOd6K7plZiFiHwnfT4iot8E8GMAPiCir4jId4noKwAeXXPurwD4FQB4wO+93AM8RXCWjtLvdSIYPhrBqVWiEsIwVOhDAIdyQh6L4KQhloSyduygxky9bgRMBIyG2CzHUogqBth4rIhNSgbD474a8joQnLwLbWVtKlkFrUq525KK9UPM6e+sGrmO23otKgqPVeEfU0fGeCMEZ1YhLIp4jCmhb0JXjkka8VQhIgXcaxEgXhQpBEFzU4gr5/tNuB2Cc4OcZ4KCGlz9JkKqnCyqBhV4NwUCpz7r3d0qxMOh5O10aR4TBKffCLorgt9WyN+o7aaGcHW7KbwagvPWzIKIzgCwiDxP3/8KgP8KwG8B+HkAv5Q+/96t+rcEvFZkx3I1DtDs0kgybeeBIeXErCIMaTZrPgEArihoskzyWa+Zo8LZDNwHhGUSy5+wZm9CsfRL50EyhyxmJWfmGCBni2zbsOjR8XyW4dDGWGTGWaT3VwwxT8IQMVx0+pA9TerAaga37iGOwX1JjEshIC46fai37YsfF77xhvjUxtsRMeVWOHQOAPhPdD2Gh11O1KJjr70X2jYsGX7L8J5y8lcKAPcM74oaYvklSATjWZdftJypiSlBrve9IXW72wV0uwG7d3QA2RsyMMYF7ashXF5At9PjeBRsH3JOm0+RMZ45DEvK9ocwY/QXDNerN2RWJdbJ3pCdXqy/SN6rZwtsvkhZfQ0zVdPCjBqvA/fKLKyfsAAoEii03hu/LXEzxrTFEaLTc4UoQ8I3X2CsvyJNmPy4ArpLulYN6S7bccXDKT8P0qtIFl8C8JtJL/cA/o6I/H0i+j0Av0FEfw3AnwL42Vv1/iJ0X5WEpKkYdhNEYC1tcGlrkJFWRaq+1k0oJ/NJp9dCi0j528IIojQlCylIkS7s6Q8RJLjbvBN1jEodAl4JdJruvmqzOVT3o0nsYr+hIAlfeQ6Cxkhon/VuWSq5ARxQSTdSzr8hkvTQOPK16zHVAtpkjPY7ReUT2TyS51CqlCHI4RwWVR97bel7bQS4bR4Lo1szCxH5IwB/8UD7xwD+8k36OlRFXY2YY6mi/sGH5RrbXXkgd73mVlhvtRALAMSI+MGHkBBBm032gtT5LvwnlzZgwDH8JlUtv0qGz84rnqOuFA4gfvQY5Dhn4Y79AHr2PGe4snwUFj0KVJZ5ooyjQIzZmAkilSiqwsj+ecq4tRnU02BZm8xz8+hxVh3ykrGDrzJOSd/DsQNi0E/g4DkAEJ9rOr/VH120L8+Bwsgrg3PfoDDybDdmZpELI3/45OgiQ7LZ4MKMoHWN2FcojNxdDm1h5I+e3bzI0JPn+FL3tdzHqxdGTv1PCyN/8AzTIkP++edvVhj5qt8rMvRnz0/lC090ohO9Zrq/cG9usz7lehoxgBbzkmNiPtMcjfNZY4iksxXQD5pRyo6tEvrKRZJCLLflag4aQt4NeJ1ySQAlp2TnwednWgPDKnldriHnK/ClZjgyiXD8/EXGUeRrdpx3XV4PpVhOiAgrzZ1hEsX4YAHejWqzGELegXg9IK46uC+8ezAhcJzgLNSmMzbJgafnAMhlDfsvT8ZNlA2bNoZx6eC2ms8iu04FJfO0qRuxfFrxHlsH/XwvGzKnSYHrdu4D+JPn2HxFs5CZDYVHUTvFAZuF2QC0yvgCFLRehl8n21IQhKVDmBHmnyQ36KLDeHYczmI803VbfNvj6Q8tMH86y2MIM6C7mmc3po5V18WKDBnOQiupI7szVx8WO5fZjsQBYfXeHs7i+deX2HyesXhc7vk4J3QbKTaLKiGv6xeKs6jqhoQ/OR7CeX+ZxZRqhb9OG2Z6cQgAkmhIlMsFCLBf4RwoqcgkpUxbqxqSl9HsE43eLTmJLlVqB6GoH3Ytd7krfeSUeJRRMBRE/wYUzrzuGy8E70bVf7djqrJd2RGG+PJSA0BJClyVPzx0DoCsRvknu+Za4igzYcNCuJRXgrcDaEzMJsQsvk/VEIoCdzVk/dk8C3XZgWlS4LqdxgBZbzF7WkR9/SKpZmirhkTPhaH0UUsDEkCjz/o9DxEcBJwMqADgH1/BXWnCXnguFc1RVKdcCuCqJD9affgQ3WUCjDlGWDC6q7ZMII2S0vOZ2sE5xwYIGcBlCXdix9n7EzvC/NFaEwFf7fLzv/xoDgoes0qVEFYDqKSyhnURoW49gncB8zokYLKhvYjuL7OImlz3oE2mrnsBJCbgGkNkU9Yw7GtbufzgGPQmzhTolRPVAEUXzkhELi9kVRjXMmgBKIyhc029TgCAL7o0tmPJRh31JQOrjQLQF4K2Y04Um1P5DwME7qXlEQGzIXh19ValEvfOQfE2hYXPyWB07MVWYUwjzHW3lypGx9yEdf3O0okWmS6I1nROVSpxr/Rg3T4E0HaXmVVmBCEiegK54jK1cWZQFgNx4fKLyjY21n6Ei+EvLmZa4jCVZeQ6lqgqmQggV0ejyw7jkjUmBmprCDMGBdeUCeRBDaom/ZhERDF5ixba7teVjah6bMPZTKWdqnbJuGKMywIIA9RTJPkRoIZZiOvgOs72Eb3G8VbP+8ssXkShYCcoqsdCJjU2JShc2z6nRCaOV/U+qDIwZs9IzZRSOnsByrXGUdWcseoPavwzqSTXL40RGE31CM24uNe/bVfnIej3UbQ9T0y0nuhu2JMSqPamAKqGpTFnr8ChcwDEXKB3aMZFzBDbfXy1NgkjkZcntYkvRrwC7xbdwSb3gTZ9gdOPhyULjEmyGAN4l8o2WO3ZKFr4JwtwhuwsVdS5yujlgawnUohwqS9jjrzt05pHwIdWshhaySIHzu0G+KuY1RvxBBoFft3iVTioZBG9BcMVF3PtsTApJ6ZsZAAggeCuerBn8LbPG5O/DJh5ytcGANcTeBdxqIq636hk4Sppgm7gCbo/zOKaQcuBFz1nvAbybkcJrARA3YtHSxapDys0bJb+MFQMycAzcjPJYpKsRSrJgrbVjQzJqi+cvR7CqToXszKK7EUR3TnvULJoMj4T5QfcOFac664rUnZ5ANpG7cMPqGQVPWeAUK6dcVPJYp48VUmCoDHBzU2grGwrOYkMlxc4zB2ceRuYsrqSPRS3lSxWDA6p3StUnKStKWqShY0xpGMoavu4MDWkMLwoBv2+RrI4c+jPOYO3tF+G85S9IVnaAhD9q0kWJ2/IiU50oqPo/kgWU5JWbK1rWTSVxcZRxa1xVI+IHbPdtarIpA/aJIOkiPqvza9vEkKqt0GpBigA7Wu7VVUlRWlKPyi0PFcySxGMl9tyXlWYpiTpjcUHTqTXDzEfy+tU62QY0ADPRFTFeXoJmWAmwK4xFErfA+z0OC7epOk5tl4A4D5Zt6qX47zDmkTgrtIc+hGUkaWSbC+uQZvab6p2pS5ToBo/fp5xC3QNzoIqnIX/ZJM6MLEhSWRTE0lXJDgeYlYnrFq6jinC7bT8otU0dY+fgS+Pw1nwZerr6SWWHzyEu0rHesVZ8HpAVxs48/pYMFwyzBrOIh3r0liaEo6e4T98voezWK5m8JtZ47WxjOlm4KwlB7ce9nAWnw0D5yShjYnPEqFMwXTvrlOdvKtjcSm7VxvXaV3ecDnXQw0YY2n+LcX/dqdw7ypsHJ0HLRatGrLeat1UK7ScHqZ4sXyhgZMmBs64ULg3JzVExeEIgVO7DJUXNM478MPzYnexOXU+qxUAQOutqiHDWNSNA+doe0qH/+6q0bVrA2cW12dObQG7Mbs8SVCygtsDmtQ/iVpoOK+HqRxyUTKgT9SQup2GAAIwvLvU61cGztBx8bLUaoiF0w8Rru9AUTAufbYJqFrCiDNG8S4+aNWQdWWzyGpI8lAkNcSLYPPlObrnRUUKc4a/8gcNnNkbYiHqQFJDtH3xuMyBBzOaMkAPVA15ustMePPlBTbvOiyelrULHcHvYs7TWhs43W4Otw2NGhL/3+OVi3vBLCRGyNDnKucSBTFVZjJkodURoflca4akOiKYR6AfIMSIjwtq0n3h81rhfD4DNroj0WqZLlgZLodR1bsUW5IDyR59DMyVoZRrzYGH5/pSWmi3c4gPVlp7FMjFlAOzputHMYZFcmXHixGREuZiVClDAEVmAnBfeFdrksw7rW0yLzsZPzxHeO/8YAHjGq/g5x3iwoN2IT/shmbM5yQ7gDdDZ+fAaPut62UC6vbjIUlGJnWQMnT3bFuYc00Xq1znxMLi+y+cZdxCXeBYCMVtOGNwH+FnPseU5DomfXteXUMk9xUJ49KB+4iwIMw/2FW/qiRqUsH2yysM5ww3aAaw7rJsQHGm3guLDRnO1JOy4ncau0GYMUIHUGT0dd2QtCSWX8K8IjwpjFwbKzPtIq6+b47YEbqHPp/TnzH6h5QlNR0XIV7ZdSlfBwCGrxC6y0lh5ANrdh3dC2ZxkF5kpY21N6RElx6sLRKqdldcrnmHNQllGHUHrksKJpG9vpZmhQ7FeBmjWs/rOiPQaMQXRoVOIkFzgJepCSmSlZjKJ1SNoGFs6pIAKr00dUkArU0yhKJiIWEfKtdzU/JPBLwb95jQ9F54T+W46jfuQ17HKdXrYVd0267MQVwZl0GWAXCKWEWQDIWuI0BjJQXFcX+XrKuog6kpzCQdg6LLbX4bVPxP5xjDUhenei+MuQkj1yHpriL8Ol1nELhURb0dR8KWvKSKunl8puQ3HWQQuG3Mkt/sStPtza5q78b1VdSFWQsQ1TErN4g6PRk4T3SiEx1FJ2ZxohOd6Ci6v2rI6yAzkmavA2PPdH7jPmn/k6vfDlTyviuSyvZwbSEj5j1ZUxwBsUDNgYTreMWluRXxZB0jJfEeuV3qNb5DqosY1VgNAkrOCVtyQlO06E2QFXwSf7ydoTm/mDJuRfeXWRwCi2QXZMmrWefaPJin03J0Tih7AUzn7rzaE6ydKLsV62uJYz3WrPeONW5gUrXMcl/WVOfItPyYQHpHUhKaHEqe8npK59UFZl4OdpDOq+vtBTk+AbXcx47BscRrSIwK9EpVrPI8EkQ6zv3e2k/zY45LpxmdmPbyabre75UbmK6HzbvO95kT4qR+8nme4BiQrcO4tDILyVjr6KUGTuufHWFccb62jkONpry28WgOTtdHjHMCL8zTowZPqrKmjUtGdISZJwxnnG0PZuAEcJSBM0xsFvP54VdyXDGiB0hKiYL+jDFcEPoqMfBwRk0ynNrAOa5SiYK3lIPzzqipE5L+zt/rWiBVfZDm5bG4BasrMiV7+QyDMfOKmLR6IK5gFpprcarZYVgCZvXrW1k8G3eq11FTXdfDanoAavS0dstHEa0WSed1jMbEfGEWe8yoqksCAJzGJa7UKDEDp43N0JmWWyMs3d4uPs1iNS4ZPOpxzW+s8zpUWrFeD5t3XaMkVsxCiLLh1Nqdo+zyq2t42HfgsGXfOcnHDktuEhpr1GlpCwvNvCXMCHNCSIyGhFLfBJNM9TiNvRjOCS5lQA9zjTql2CbGjbluSPo7jZVLUfc8pkM0LrRfHhnM5pEhDBeAX1cej/MJo5/VzAKgkbS2SKKbMIuTzeJEJzrRUXRiFic60YmOonurhsgkzLkuOpQLCAGliFBPhwsRWREiINsgAEU35uOg4j31Q0mGk/rM39O1aBgVvBUKXoO3g55bBbO5Z9sXFgHKBYAAYBjzjbBiP3S1LQWN+iGDxaTvQest/LwrId+AhrdXRYyAlG9CEix7KPgP8Vyg1xWUnaKge7Lbw1nsFQAaOrirQZPSVL9xH0BX2xYmbXNPkb22DgAwq8LZ4y6pP3ECdd5psR3qR8w/SejWKhFNY7Po9ve+Gmfheq/3JZ8g8J3LbbNVB+4deBS4FaN7lqJcpUSJWrJcHhxiR3C7iNUHAfOnlodCgVB+HdFtJghOVLaKa3AW3ZMdDtFixtpvhaE4eySg4LD6uNyv4fn1OIvdljF/JhgqtYUPwzoO0r1lFlMjG1HKoBzjcQZOn3Rn7wqTYAKiRYXe0sCZcnPmjFqDojml84rdN1vAXRs4F74BZYFTBGVlnSdJ+SkqyLauTYnajYs0hrVX5OwbNHCOSwceCyqzTtjirLqYI/BA4LG7cwPnuHLZWNmfKWALACioPYRDSV4znDmEGeDX7o0YOIczTtXMOHszhiXdyMDZP1CP11ghOD8TBs4parCJ0TgGwTmOmrA3xBITEjkFl/CtEZyKDJUcXEVj0J17DACXfBJ3jeCkXYvMBEX1etTMoh/Vvmv1PABwP0IiZwSnwdQtk/kbR3CahJZeRAoC9lRS+5GiJGkId4/g3ASAVAoQBlyuBSKgwKBQJAtN1U/g/s0gOLt1h+hVsrAXnOLNEJxhxuiuZJL9/ODlDtL9ZRYvirO/iev0gNsUEm8tWWgJwxJZiV3i5BN8xV1LFnJA5JZu33UqXkX97Dodk+s0Z9pO65PUvDcpWcS5268l4tWDxVVwmBvUQ3LnrtM5Y1wynIsIHcFZ8Jjfd52GRcpCRXgzrtPlq7tOw6TE1I0AACAASURBVIIw9rd3nZ4MnCc60YmOonslWVi+CWLaE32tfof0fVOS8Do1RIaUdm6o+OHQ52NuHUjWD6X4UOqHdykVHZFGxOINBJJthzajFRRwVbeZeM39CLHkuWMEnGQDp9k9KBmE36gasvFZTaDAOZBMuBg4OVUT520Pv0kSyV2pISniU8sdAl2VJ4IHzSliJQejJ7DXRMTdVXf3asil16jTy1Ayt3l/IzUEYMwuY05LCAD8mVBDpnRInXjh4aT6O1WgLGJdnUMgrWPJOc3rUEODPSs4i6mUWbz9FY4jomZNNO9ki1YVz5pDI3IRTZ1WiqekrGYbh3PIsv8bpJL+Ls1HdNy2cQhTQcneNVHJhRFmxchKAuwlkyGkFHpvYFyw9dH1qlWvm1Ds0vzqQOMbnP/pYRY3LR34onPkBux0Sskb05ZP1E+KOKiv3xk1yYQJxNJeP6bx1qUEIpRRTEoJ2nFvi7QkY0q+G0oYNYnCrZuC1Xc6Dh0DV4mA69KLdflBq/vxpsYlibM2hatvQvacVnUMb7IFn2wWJzrRiY6i+ytZTL0hzpX4kGO9ISEWvAU0a9Ir4yxmnYrFlsdw0BgP6b26+dhiBO4YZzH3beIaTt6QCk/hRBAXHZg5ez1o0HoftmsGq67e+TfuDQmLYrMI8xTLk9LX1ynxeWTQ7g3gLJYOw5mD6yP6c26KPscZJReqNg1nrJXWF/4N4SwcolNpxtSIm3pDhgcEDpOYlZM35EQnOtHrpnslWfByAUDh1TKxqJP3kHGEe+9dxE+eZGg39b2Cr/q+OSdDtMcxeyjonQcZ2CUfaa5LK65D63VTMT1utiDL4F1di1cLIEopHDQGMAC6XKux80zzfPK3H2FasZyr7NvS9+Cqsrn/JNXKTDlHKQat0O4YMdVBAaDlEoc+58zM800GQlcbgmMEr33rvekHnaOl/zOJJUW3zv74UalgbjQxLs4sCfKkwjxCULj69HwA/PQyr4fNe759J3tTOqdGWIqGDalsQlCj5/IPHrXjmVz/UG6JXB0tpGTMT56Xac1nKiUm6P8yfA6LTrNuL1ZdzvpNFtYfQpN02Kqyf+7/vgJtUvgos0Y81/VlgVL8ye5jVc29Ge+zq705AIBbvwOQGlQNY3P+B1cI53MtlWlrMPOa/d3+riTN3RfP4K/Gpu2PN8fbgu4Vsygp9w8YcFJpgINFhw5RbB82bYttxa7bUJQMYLL+yUotJrQh8Aa8IenaRrV4WtpEvQr1eKOo10Mm6xPegoEzSjuHpiRl+/3WRr0bjQfZCNiM59C47JjxzRheEQFwetZeYS1I5NbP5v1gFgSAXc7oDQDunYdN6UGraxE+eAT/9R8oFdGXC8jVGrRcgK42pcv5DLLZaJX1VKw4fvBh/l1+5IcAALzRALDxnSV4O+RYie7bH0NWCyBEcJJMZDHX5DHLWT7OfXKF8O4ZnGO9CY+fAAB23/x6LiBsFBYuIxVnT4ecn4F3AcND7W/1RxcAtJq5f7JDWHi4zZBtC+6TNcK7K83CPfHJx7lv8iF0T7SKF+/GnMX70DkAVKIA8OzHvlYS1SayallG/YX66/0mNr/5rZbx491EshBgeDjL62HztkAsYJL8Bmja3S5i/v4lPvm3vpraEkahF4xVPouYckXkrFYA3FY9Kq4X9BeEiz/7XB5T/8AhzAmrR2Oe1+4Bw++03/mzCq9g10zZvXcPdLzv/sst/uzfu8DyI8nHhQUweyroH5SxufS4Wj6LMNdxaXV1pLgP4OEfv5fnkKHYBPRnhDgDlh9F+K1e6/1/c4X190WsvnuRrzOcAd1lWcdQSukADHTP5xjK4Rj+5fGWiPvBLA7RC7N7V7tgjHs7FICS1TuEg33lIKxU7IcGFTGbor7TfkU0BmQIJfX/GDTa0qJVYwEMTetocF+lagsxG9+0FqiCfgpoTOuecsocnnewtMsywj54iqmxQnEfFIiUPnPb9BxbL+hLyjWzYIIza6i9gDsdLw8CZ9gMUeARDbG4Pau15L7MgVP1eIqUDZlTqtvdTjOZu769j/nvLBwVDIRJWa4XcEhgqWSk1LEJXK/p/G1cfkOIXuB6NWT6TSu52dwBIPp0n4cAv1GmpMeJzmtbCtfnsQpAI+X+KCJHfUaLdRzKWts1hYBuDYRA8JsSn+LXgL8i+LLHQkjbrXxhHVWqv7WFh07ZvU90ohO9djoxixOd6ERH0f1VQ5gUyXeIaqgzURGl7fMYVF1Vf7SBbk/zeFaRhjeFnNt4cp81zLbJCo5c0cus5SCFHWt7BeN2JW/lnVElptbXksrxYdmvrY2C2QrKvCR90WhN5Dm8tvGbuiHlbx1bUUPEniNSUb+pGm7n36CS+HXjyNe2Pqs2ayep2qhcv7axlDlQ8QS5a8ZX9bHXRihZyV8T3V9m8SKqwUipEtdeCn6XQFrOHXwYiuuKIUSQzkESIMj6bT4BgAmSwtNzjU+v33NB4lwPtOSMyGHNHecEtLJjhOQCc3E/y5N4ynEnMsQMtmJrc7zHFGPnmgS6PEsh61EKeOrAOXm9oMbMbKNIZMY9eyjHBYGDjtkClcjrAeIjkPRkWzkRPdYAcDbXOqX91MA5bfedy+MYq/GMcyoAMzPmUcUURFICHTWA5hePNaFN7CjXSB2XhGFFEKf98liPr10DKwEYO4dxCYyLclxYANxrglwjdjrOMLfj0NgUrF9bT2GAbKykiW7iTMdosU3jChjPRNsSjSu1meRxVyWAwWonOiXsPdGJTnSndH8lC2IQvcAnnHZCcaySRQW1Bh2vhohLO3jajcrOoyn/KX1H/jxsvZ9SFslR72ZFzRFX1CfxBPFJlK8qlsfOku1wEU89t6L0XdBE9cgivSu7XnSA+GpuERCvlnaxor/mDYmpJombrMcNqagW9qlSACoXo/WfvQteITq6npQh4aY2RX/78TTjqtQI+7tRAShpS5WqRKFVmXTs+hk95WLL8ZrxqRoo7flcVCGKeK3iwEmyONGJTnQU3V/JAkhGzvS9hvV2vuSf9FoNTLxrw21nnYKx7HPSRwY5JQNmWGkgmAGGhClJFygSgCNgroCscGaJbmcIZx14rQozJef6eO7KjlWlYjMQE48OYaHtbqsFcABglaSYcengtkFtEFURInelkN+wYPhJGbtx6TAuq8QmgwZfeV9S0h06B0gQbigwybAE+ZhFq6/3D60Pzro7CeA3DBqRcQDBsCiiFbUcF9sAoPq937RtRnW73xC6Jx36i/ZYtwXCEgVnkewB9U4fO7Wv8A7oL0ohIoqE/oIwLimv2e4BYfcuIWwI4xKo856Ue5VAWe/q38OFx+7zATxYoSIgLNWS2b9T1tFtbc4JvLWKoEgZayOpGNLwUWWzCOX7cEEIc4AHzn3s3hPMvrRGvzkv9+rhiNj5jLMIi+peOkGYM4Z3Crgi3oAD3G9mUVMdb1ADrQymXMPAiTR2YRzL56QPlzJT0aAlDt1aMz85bw+TqkANnDcCtOtb++quh7vqQAnladfylwFuKMld05ecP9HtQn77eBT4LTe5EQztqICvmBMEA5r9iYe4h8akUbRSmPVxNWjbbtQoUewjOK3dSiLMLmMBBqWxc1q2WHlD/FYykhBIKMmdNKhVzvEdgN9U/aaX0G8lIzVdfxjB6XpFcPJ2wOy5Ad7SMalygwGLwtbUuvIS+I3AbaEG2VkR7XkUzC6TgTkxt/lTld/9TuA2EwRn6jsz0nTvuucj5o+XmD1Na7QFhp4we4omb4TbAYhANCPt1umzIIDVeLXxAjp+TnucfhfEGTB/WhCc80881ucrLJ5Wz0bv0V1S9r7UVdpIgO454HaVEfwzUQpA4l7tECMaQ34paXCQcdTPnP1bdGM5AsFJgz5t3DtwH0owUtCs3RgLOhPDeDSC0+0iOF3D7BQUBcFSwm1LejQaIrynXOMjn78dII51XPae9aO+8FXquUyvAcHZvNRIen32XuSTlFmsAyi9NBQUpel2sTA9m595JPrYtINvhuC0F8nCxN2QLP/WXbL813YAt9PjeBSEjuFTCjrLeqWoxtQ241shOLvnQLdOEsOoEkG3lsYLx70mRwqG4ExMrric9bhuXWcPL67T6PYRnN0l0D1hzEpsHMZA6C6Lq5ZruDdeDcF5f5nFiwyczMXA6Z0aNp1rDZwvc52ayzCpIeYKNXFfVZtk4ByLyiMxHuU6rV2Bpo7EGSPMijSR8zIwISy5MXDGGYNGzS1hrkcAILt2VQ/U6LW5Tqv0euIqd57VzMiqB2e1imJa6lHKy2tBdbGta2qqXq03HuM6NfXDXKexV3XBHvhozKIycIoTxF7doOOZrjMAUND4j3FJ+Rrj4nau0+EMGXId5jomHjROw8h5ZWoxqUrjojCM2kBpKp8aONO8HCF67LlOhzNgeBDhL8s9H88EEMoGzjhhFifX6YlOdKI7p/srWbwsT+YLwodF5Pjcghb6K8j5HnNfFq586Fovodp7W/JfllyYJCVoDJJEa0FxAwq03gdxc11KuSHvFMVZjz0kwBXK2PJaVfYCDXBL485qSPkNUtYkZ6e+qcvSzs+frRpSH2fjyp/p2Kz6her342/rQWo89XJ9O8n+HPIYqBxn47OxMyQDx/aue2ju6Tna+/0Vn5n7yyyA65PfxhK6TkFzXFAo5QEaW8XLbBYhADFFnQ4BZIa2GDVJbJ3nIcQbRZ1ObRZ1ChnqY/6bhgjuNdWdJablqopYY+CMGs1Kd2Wz2O7bLExWlaSn+416TLiP2cFkNgseDtssXB+zzSIzupvaLJJhL9sPbJx2uew9kIM2i3Ej4J31IfA7FdfNBgDczmbh14Df2DpoQly/KZgJoNgszMNhUadTm4VP/as3pDBVCnIw6rR7zuiqfDkkGoVqNguaGDA/9TYLIgZ1HlI/OM5puO8DDb4PKbMVgH1pIoq+yGcJXxsC5PKqFExOxtDaYMp1iDqS12EI+aWUxRzSOfNAKXkHPLvUF9rsGNud2itSfg27Fu9KMeK8aQQGJW8Fb0dIMP05wqc4FKlyWopTWLd4KSnz09v5ssLLAErx5WFsijBPzwGQCzL7dSilAwEo5Lz16tCo3hq3i9m7oCHqLTOgarekKtzfvCTuWV/qg0yLL1ft3AfQeovuMoXRd8Xu43ZFsogVVNoWnROjoGC7tUkWGmLvqXiE5le9ruEQETuGr+qG1MWY63Vzz7ZYfHyG+dOYxxBmgu5K4PrKwDlCXeC+uI0tOzjFUiXM1lOohKuLE8w3EbEjzJ4MeaNbPPYQZiwel/s1XhG6jRRvSJWD0/WCbhMxPK/d6zia7gWzOEh1gBiwr5bkLS3V6rA6IUjPSUh1SQMXl2ndR+1pcawVyWsm5FiZxRiVSSCJzWNoYoRk1MJDYswjmJcllsrnJoVEAapixnkH5uQ2jdIYXqVzKjlxiX+QLhls+2GvmI/UKf8BHZeIFk+qiiJNz6nHzbvQiq6MHOthyEzb2ZQBlLlQlFTXIjHEzHRicdHWXW/Lg8+TDGh1Ow0B6IdyXesqpTcsKkXa9Wcl3oMi4LYxMTDO8Si66wowo8JY1gN8ujZ3DrwubxKlYlXGSPOL0w/qMt7ZmhCE1N1bJ841hmXSGaBJfqNL0o0Vd7f7PAna81cjYsfg9ZAxRuqqluaF76LA7SQbOGvXqF9HuG1opI2bZCA7GThPdKITHUX3V7KoDYBTMlsEoBJAiCBXZbk6Jk9nnWkLULdrXcwmpMxOIlnloBuEqFNlGM0SBjj3QTHmEG5FLWkBYwOBUZTyvZKCyKSlO6T6egLOUpS5QgOzqhJRqvgP6E5PRaKobS5W0QsAcEDKOIoqiULHI5BKtTARgUY1Cup3lX44luxe1k5Macd/NQsnV8ZICjous0kYUUDKf0n5HEhSyUKRJLhaG37JOpnNg6vxB6bGuCuvscrcSbI40YlOdBS9lFkQ0a8S0SMi+v2q7T0i+h0i+oP0+W5qJyL6W0T0h0T0T4joR48eyVSKSBmz5VBG70NeEvOQ3LAMXza8mSSTv6e+zBtSu1CPIXO9HnK/TvqiprxgTJ4YtQFQiLrzpb70+w1M2DelyRSpHq+NIbnkaDJHknrMKiXRGJOXR/K/G69lNRYrL1hKC0qTu7SM2caIxl2thYIkS25q+HzN2cPNjpPHW3ltBO0a2zjD/j9bp+tKJB7qN5d7bD4nbtxb0jFqyK8B+G8B/O2q7RcB/K6I/BIR/WL6+28C+CkA30j/fhzAL6fPmxNTK/abQXNM9RhsoQyhOeva87uZLrJ9ApAqNkRSdm4MahyNZ3NQX7Jgu61m/YZ3gFmlmcGLOWTe5etRFMjZstzQnXpFxvN5SdibqK75YAFhAMBjxHjWAQLMUuxGWHq4qwHinVrnLVlPCDrGi1VTERxAU/EMAByRVgLbDaX62YFzAGhdD2gW7gzLBoAa7m3Jb1YMv/n/23u7UNuW7DzsG1U151x/e+/zd8/tvt1qSbY7sdx2rGBZIg4CoZCAQ0DkJcQPISR2lAebvPkhIeCAMeQhPxACAYUYxeDY6C3CGAWESewHW44cTBQJtd3pTt/u293n3PO7914/c86qGnkYNapqrr3OOfvse8/tfVtrwDlr7Zo/VbPWnDWrxvjG90UREFbkJYvjUx5C7a8Cc/cLV1KuVUWM5jkqta96VpebMcCOHv2dpKLelMhBqEiG1KlZR0NsB1CQZdM4N+iyQ7aoiuUksG4Gv7IwAyO2NEFG7kdD/Eq2LTYLbB6YjBgNrSR8hZYmyl9m1OhE2q+jNHhJW3Jy3Fj6TsOsICC2LUJr0LnCiL55YLF9WBz7gJynWSenLRdUK4CkDL+nSNZcf2n9xsGCmf8+Ef3EXvEvAfiF9P1/BvC/QwaLXwLwN1hc7P+IiO4Q0ReZ+fvXbtGrrB5dK5xFZvcOJWoh5YK7oLiHv0iWE8RClIiKsnu76kHZmwUQM+A9qOKlgPcSjtTwrIYHhyARFiDP38xQxjhh907fo2AWJnWN8kZGYvfOXu0obTf9eCUMaqr6AQCjl6r1M33fP0b7C0Dylk9DpznKkEBU1pCs/4dYwqSMcg16qIYpo4Qvc3REow+9L7iPvbdnXS5hbQ+7U19ICZ2CY4F7p7uZDTLgS/Ad4kOItswgKKSwK0qI0vYJlzJGRG/gtmWwj5rTowOp4lb6Ec2mJNWZIP/cjlGDoIxP/dAUn8VEWDl95HCpqb47iWSYkeG2Ib+Emg1jXFPOS5HrwhtDp1RpFn4W7N7vVwPADwC8n75/CcB3qv2+m8qOdrSjfc7tE0dDmJmJ3n5FRES/DOCXAWBGy0M7THEWk+8lkQzGCM4iYS1So1ALJquwcY1cUzwDpbr074xzIBIAVEROUGNLIqPYuCJN51wWMU7XBQAIrS2gJOXlbGxJCAsxT70pRIROEJwKuuLGyNsss2lpOjUl6bzXCy/Lvi7vV4sw7x8j3ah8DDbregCYZp2mt3VOZoqck8IUY1F75pGXIylpTsGiraJf3aRvJlaXGwI1LieBhbwMIYS2YFDqmUVm5TIGxsl0388Jtk91W5akrxmhacsyyy8MzJAYteKBZYj2wcLk/huXlAFYugypgVZAWoZEqkSGKGuMCO9EOv6itEUjJHrfhtbA9DHzgoxLwrgC3K7U42eC4j00swid9Efdrs8ikewREX0RANJnEqHERwB+rNrvy6nsijHzrzDzzzDzz7Q0u2Ezjna0o31WdtOZxa8D+PcB/Jfp83+tyv8SEf1tiGPz5XX8FRwjeBwyyxRHBl8K4D2+EFYRlTMkJ/Bl3goYnwDwOIKcm8gTmi++Lz6M+SyPzKbrSp26tk5reF62gofQNeSTZ7BzETnWusx8Dj5bIc5cli90APzdBZz6GnQmYKgsWav1eGa03vefGAIDsB+L/CE392Cfr8HzFrQdwHN5JZlnFwCfYHhvCbubOnVreUQAaK1JjFtNYdraur1j5G8VKY4NTdihJ23WYzqSNbkp6EflFLXnA8zuAIaY5pl4h7zUuXuvzc66fYlEzcGQuiJaovyWDFmykCcOvFrKUC0GcXzaJEl48rK0jW0DNsiw7ssvdxhOCbYH/BzoXprJuYmRfRP9qVy7GRYYV4UJK7Zp1uCnM4v6euQTACjLGqq5g0LFjMsPbJoJtdmXMS4J4xmLQzPZeIIyw871pG0roD03GAux1qT/3mRvHCyI6G9BnJkPiOi7AP4KZJD4NSL68wC+DeDfSbv/XQD/JoBvANgA+A+u35Q3WO0AmzBlVQljk/1jFQK9ukrKiWS+YqSqEsQm55zUlRK5MklOAoPtEfWY8fXygvvJXTlxKlTtSUlr+qnbaQxTecR07loeEUhOVC+K5OqYM2Oc7JOdjimkafv4yuQuNbelg/vZPuR+3LdJf6TrrqUSJ+rvFbALMCKLGGIhv6mSuvaBT/umEoe2Z0THJScIiTGKTS6zA8PuCHaQZKuJPGIKP+pD77bCe0GB0awr8psgSV/NhieQbavObHWUev3tp/fmvs5sLt/Z5JTlvNRzG0ZzQXCVg5PN9O+ak0O27S09Ps1EMmb+c6/Y9K8d2JcB/MXrV3+0ox3t82K3F+69b7VCWc1+VTNi1WYTm5Q6QJGWHoq5UIdaygKNrYWJMWMfbH3Oqi62IjKUj3fCRmU1bDtUjrnXMFllFitAHIUVQ5e2h5KgEXypj6yKHFUeMAAgwTzEahkSe9mPAuflCQUzSUzT8ib10SHGqv0yP6fMmbm/zaR+3Le6P/S6RdCoWlokbAAbwKUpmHBIGjhnJkS/gOwXqqXHoWVIcRIKu1XtSA2dgZ+VMmW5YkPpGnWNVbJEdVbm53Lu2BiMS8Bu95YhAfCL6q1uDy1DkDlf6zYdMj+XBDkzluQwvyCMJzK7yPstMRUZqpYhfsUwgYRNa69/rmOfn8ECEml4q7CLSQ+G5mPg7by/h8+JyZqwliFkY94qf+QT20Qt7cB2g6kWih5DhExYmH0sZpKx+pkbIUvuSSSKc/lEYewdWuaVoBSNyPcNTyUGtb2WKl7Sd2xUPm/aF3ngvGFXfq4Gi1eS4bzKEmy6ZtC6lg7qa8+JKfBIIc+AOEg/yweuriseuAOULyEwoG+wPdaqTFDzLiHk1zHFMDGQWbcAYQziCrz0Di0zS3ECTFVw6iuQaU4w8bdgx/5ExuVzP3HuupZT+W/YlZ+fweJNCmWHzNqiWAadmcS3n6FMzpnezFUUIKua2UoV7R1brXim7agVz7QsWoJxVM0gRCtVl3RZAc19Nu2+YtqPOmNLTOATNKbDBNL8riwriRnBbChWI5Pq8rS9tcLZOzcqM5+3gWjXFh2KcPMN7PMzWHCcErVcJxoSgkQqJm/gRAxyw2iIQqFNZo2KCdqdaPEzLd67jYbYPk5g2flNXL2BzRBgLQltH5cyrkhrtF4KP4xoSIGAOxiwlRlFdCUqYDx9ZtEQtxMmKztIJCPT+OnMIpTzuS0hBoYZPptoiNvaxAxW9hdavetHQ0JHaNbTZcxnAfc+2tGO9gfMPj8zi9quEw05sByoE8puHA0hmcZPYeEJbl7ZZxENMfWMiYRKro6GcG/yEkkzMo2bRkOy6C6rt/6zi4ZIZKCKehAAm5Ko0hsxtJRnQe88GtIS/Ewcm7EhxKb4LEJLk7dw6Mq5P5NoyCxFQ4ZCivO20ZDYMfyCkrxi6Zfr2udzsLjuMgSQNfABp+ONlyExAp7KVDum5YAPMmBo1ulnAMoy1TKEifbHK1kijQQKEXYsZbAl8mF8ddBnvAyZMombEjp1JeNSiYAp8rsHZfUMtxO0J9tq6ZCZucr5YkMIzWcHynI7i+gZrrrmtwVlRaegrJstQ27VYEFtyrIZfWbJLhsNgAhaLcHbLThpc4KjfOc4PcaXhzl7/Jfz4r94IZpvSrRrYhQS3MRTEfseSvBb14XVAuQDrA42/Qi77kXr1BhwOt4+ubhCjkuNg00JaLTZgfT76NEknokMLX9+Ad7sQLteSIGVPXy7BQFwrSu4E0DCpDsLW4VJafAwvgGNITs+zW4AW5ujH9RLe9kJHqP7weWVh93tJXk1L5pMtltvo1FYuFU3tTY7+twfet0tUabeczrjiSxO6ZpKMEV05h9JCoBygtAY83cpvwoaKDKVEd2igX1StP7MpgNbC3MhcmLzzqJZC7v3uLJoLtKxLMS6pkLCNucWsTOwQ8Sdb4xoLuSaY2PkodyGLDoNlNlA5txQfhI/fVq7x2scMjYn2cmqofCzZwGz5w7d83KfhZmd6M3WjuvNQ4fuPEyg9TqIXcdux2BBAIxF3Gxykb17Vyj905uWE6lMePQY9qt/CGabHp7FDOZiDV7OYWeSkMbMws3ZD/nhB4D4+En5/i/9EQCA2QrJzXB3BrMLCHPpkpm1iKuZvJ130qM874AYEWct4iLlhjxjhJNZecCeSG7H5md+Ai79aPqghplBSD9U+8Ln77aP6O9IvSfpht9+cYX25SDkL30h5XHPtxjvzhG6Kd8CIIroWRoQQPd8EBX16sZ12+bKMQAw/+eSC/j8z3ypwJyT7Uv3DSeE9kLe9Fn9nMUh2FyGosOhUAlm9HeazEdRZ4/qbOGqinopd1sZKJ7+y6epPbKPGVK2pi6pVEW98vi7HRLcXdTfT78tO1EE+lMDPwdWP5Cs52Fl0N8xsDtGmBG6F1VuyExnQ1JZf0e23f39Hh/9gsP8UZP2A8IM6F4Aw2m5HjOkLFDNOl1IyF0zfHWZcvaNNve1vvWZINKLHbB4FLOT8/Gf6rD7yoDuu2Wt4VcRzflhFXUmoD13GE5Lmf8/cG07OjiPdrSjXctux8ziVWYI0JfnBK1YORRt4rYwhc+CgMPCyFSv39I00MlxsTGgSqyYDcmywqFgFCwBJNR4eT8rzkblodCs09gRgjISkTq/KMGXhR9BY/QUTS5Xx2xsRGAoNkYg2uoIs9LW2JrM3pSvqTUTp1hAPwAAIABJREFUh5/UIftpew8dA+0vTB2Gan5vZuHn4mijULZRAjLZxlwFfLE4DJXhqs4e1bfnfr11OUVZeuiMIlPQkbzFdWah22taPQAwQXAxfl4wChRl/9BR5tfwM4F7A/JpK54I5ZvIfTIv/ecXEX6mfCBAmDP8juAXpa+VgyIkXr+wiKIxkpYB+w5QUSQr1+Pn0l5ftcMvGN1JjzAvs8WwCiBPB2cWsAzvDcKq8nV9BnwWRzva0f6A2e2eWdQ2AVZVaec1+3Zth7ROq31M1uRIDE9JWzRrXiR28QnrcwQoBNBos6OLQkoX34ucmKFoVOirlq2BNRotiUVBzUfY0WSos7RPrsmEKQmulvGAKbEuhMXJVp5uM0QYS/lTy/aPyf2FlKZd+yyq9b960e0OsKOQy8ZBZxacNUVrXY/S35ydfMVDX0BG+2+4utz2nPRg0zadZA0ss769n54N8mvQDkh6IcIyljk4o/wdXXE+uh0QtgS7E6im+idq07KwLf1pN27KS0GA7SVqlK+/19mXlpmsGFajcVVdbH9m4bbSZrcrfea2Brt1i26Xq0F0VtLn6SpEnUFwG8qzau2H69rtHSwMARWx6GQZ4mxZhjhb/uWwZ3zzMiRT2slgEVqRENQ4N7sK25Ck6wr13jWWIS1lYlR9EEJn8rTddqbURULvJtPthLNohP07OgKqZQQ3FuEdLkP2sQpsqmWIMljPJdhEkfJ0XB8C21PJ8tUlJCsLd3Jw6lKswdstQ5R6TonVDMEvUJYhyXnIdoqvMAPBWsAvSj0U0jJkXq7vpsuQsIrwF7oMYYQFw/TTZYix0ke6LAjLCASSwaK6zTVSwbYMYmzplcuQxekO/bJy4q8CvCewEcq+MJ8ytX+SZcjtHSwAXNE3nWybQrjl31sMk5WOR+a0iihvKWYJTe6ze9/EuHxS9b3WCc1/68PMKVHJUklwSm38NDQgrtXe/TbHqixWn3oMa7ulaKKmzgUfcOP284HPuh/32wmkhLDS1kkb9spubFUfFU2V6S50qO16bJX6XvRjaPKbv8piNFd+L/mk6d8A3jLv7IodfRZHO9rRrmW3e2ZB1Vhm9pYkVC0tDF2BW7M1IGPyJ4CJqrWCeXiQ49mlf7Y+L9LiMU3DiUAJ6q2M13ASsYBGV0zx+O+nL8emREPYUiWWk74z8vAdG6k/OoJJ7cvncZLtGP30mutoi5zD5P008nLoGO0v+RsIdbo7lel9ZufugLAjmAYTDscYUtRjP4XaJCi60/bLp0+waP1eW11OAYnRvNSvFtry1tYpfh0NCYEQbYqcdFwySQ2n/irtCTPKS5wwmy49dNmhJ9b9YkvgeciYmTAD4pxlOVIvAeRmymU8DwAT4qDLDml7TIA1JlR8rnJeP+cJriTMI+4vt3g8X+Ra7MojDBUadl5hcSzDDw14Wd2Yb6GFepxZHO1oR7uW3d6ZBaWh8VXbai0PnWlo4tdb+BbYyijMRInrodTBVlLOMzmvpesrgBNVUZBUF1VLSVe+R0cZsadveOFUMFCeDI1EcGPeKWvUPiNU/ZbWWVfmmDClTOjwJP0/40fSC4xYyktU5RO0DdPzsEVe0+dyW74bB9BQ2qwzIQqUj58wid3ELFdtYrD+XafdJIdjfYyop08dHHqvRFvo815JfWcAZ2JhFQPkXAZgYlCmHvt07BYPFuaVUySuBYjSwMG2eOGvw4aVSWKoekAJ5UG0RvIlIpeBqab3v4bti8RMHjxDB2/ujOWnBMwyaV8q2z/xzf06q0Kl2mZtf9bcoUSkYkpZJoihkv9g0mDP6abVdscbtj+3q0Qfpw9SNZiwS9N6lyDVBoiOq7bJ7y0kNzdqTqnWcGkTQe5bkge27ESTgZgMgwPJvpaBMO3j2JQx5FV0/UyMxobJc2KIEXTAiPxWy4w32XEZcrSjHe1adntnFryn91GFRUkZsAARDlYGKy1jYVbiGPPn/jky+MoL6MmMykSk501CyUmYWOqNgBe9DjOaXL8ZYxZB5syUxTDKapRGd64ctraP+W87MGyPBL6qjh9iEsiNZVo9Sn0cqdLWSNsGgq2mpGaMMAPlz/q662PytSEBripQFhvKyzqjDsqUAGb74pijKEAkM1YhUq8hZ1Ez1wQzdTTHKuV7f6pdl9uBJcN1t78PJglXIb2djStOS7cRIR/jAbc2GdBkPMO2ApxyfVXXjuC26fwTUBZNyhSDYQYGLhvYTb0cs7Abgm0rKck+QcwT9iZQIwrqaTmkswi9xlixeJNPDl8WwJi2164tPr5YwaxLPSO1sGsr91wkxFDN4kj6Y2yrx/4Qd+sr7PYOFiHilTiLyCUF3YfqX1Eyp649fGyyrPA9RqFS4DRweEVVBlHWigCl9HHaJ9h5w/kVwaiXYQIjsq7ny3YzJAQnkNW8jJ/Bbj3izMKMIUdDqB9hh2aS/vxpGrHwNmQLXHwV+ToUxVkQnAAyglOzS+usUwomczeYvER4u+VI5oLQQWFkmKEm8kn7DSWb0ybkpBlFQKjZFnyNCTKQ6MA0Lm62PIIvOS4UUt5MLBEdLRcMBpdjOA3WDHCj90L6RBlAzAgMB7g+KQDDYPOAD0hEigLysoaqwUKXZje12ztY7Ns+3Hu/nBmTRLI3wL31TUrM+S1NsUCSZSOBOE7JQq4L9x4LRDvrNY9c4N6ewQkOTiHVy2VnCnIheVCr2kVRZh3vCu5dCGmkDQWCnM7Ry4AhEG7K/Wi8cGiqf8XUfKChmnGkrrL9zeDe+fxj8mmnarKvtXIuGl/g3sYj3wMU5XiqUKRuxzeDe29fAfeuEKAK9655+CdwbyXDUadmBffGq+DeO4PdtkFX1R03Bm5X4N71uP+jAfdmiSlPJhKGANOCtzIvy8Q4gKiWp4edZw0QI3jRgS4THwYRuG1Aw5g/AWRINoDMW6HOUr+wsIYwnsg+nbOInYOhAErUe9xZIBjERQO/lOPtWr7bdVIjT2JD47I4InWK7bsCx6Zo4RPc28wMdmcGJiDzVvi5AXkHtgQHFDq+voGfO4m370VF/MJgnFdLncGJ2rehrPp96BgAmbRnOCHYGqthBXsBlIzN4SRhOhoDv9TrIfitUvin69LBkBnj3CCmJYtmjfqOEN3ht3pdHh2jWzQYztJxc70+gXsXaHgaYFw53q0N7E5g1dsvRHTPUts8MK4I/RnQXkrZcEro78oSQ3AUpS+1Th0k+rupfGXh3x/Qe+mkMGOEkwA2DuPdatm7pQn8mlce8EYiOW0Eevl9h6cu9TXy4BibgrOwvYFNs6P+vYAf/9JTfHt4L9djT0b0XZejLzyrJS4ZsW0Q71Z6r28x27gVgwUZI6+ImunKyN/2nvwq4dnzsm0Yix9hN4J2gyR+nQiJCWIEXlwIYY4PmTiHh0IL5F5IGYUAGIMuxMTUnZijZo1EHsYIpAcYRDBPX4IuG7j0cNHFBrPBgxLbEq/lc/GDIc9eNNrSOsqRANtHtFnLA3AbK9eQRn23CfLmCRGIgK2Ibmwf0D3qYfopI1XsGhnQdL/zHWLXwPQjYpcGswPHAMjMYSffuT9JnqtFijQkGlqC8Qy3jpnIhqL4aOQayjJB+pjRcVlG2F6OOXk5Zkq7uMdyVZebMcA+ucjENTnNPPAkzV37NjZliWN7lqUHM7pnBt1Fmdm5Xt603bnUtfxegF9ZmEEAW+6y9Lnm0OjMzK+kvYtvr3H6T88we8a5b8K8QfuSMS7LYGNGmY3ldPh5J7MI0jC57Df/OOXPNMWXEhrC7GVAaA26Z0P2q8Vmhh88+QB3ih44QtvAbTizjtX9antGs2aMy/LifbKeDtKvs2M05GhHO9q17FbMLN7WapUxSfgKCSXEefubJleasEOBwUiRl8DFlxE4RUqKPscE/HIdUwefRmmMyRBeCrFA2AODosl1av1Gna+h+E0oxIn/4lO3agaQTaEfOUFMZhZZ7Sxt079zUpUvv4c4/NLfb9uP0HqvflIojkAy2hbKb0FN9Vf/gPqkKHC6DnxiVbFavYwipT6YgrD2k+hKIl7y8ygMXf054Mn3V9Ybpr8Xsc60uCTRfUr2uRksVFWMAXDjityes0LR76bTWOpacAz5EwCoWoYou5BRfsxlA9MHhFnyRVxSyhkxhVTVEnjWguct4iwR844eYdXBKjnvJvkcli6zX2cOzs4gdmXpoSnqdojwSwsw0FyOqX1WoieNgUVh9rJ9SMe1E7JaQPwdoY6SREbsnKTUp6XUoWMAwKbo0XBqM82/dFpJKVff3HBCaC8FSVrndLiepo7dSohpXBrYXvtBfTmNMGzjKgV+XW57C7Pp0J+msKPS6A/CS5k5OLWdprTVthI9MaP4KFxffCz9CSG2QLNRX4hDf2rgeobvCF2l/KVt1iWUtqV72mL3ACIwBU0jl4d/OKmuZ0D6zdP5ZulhT5EUFStWWn+RQ0Du93FuxXfELjtZd/cJ/fsBFMpv7leM5lxAcGDkfBpABlF/QRirdr0K8HXIbs9gsYe6JGvAbApGok4kcxYclFtC9DXQuBxOZZPQnCbxXhh75RxZti/R1wnfAnJCkFDtWZhKYyQ2FsYVJfXclibxaQC5Lrm5Uht1AtEV+jwzq7gzLGGcy01Ta1iYziavuMmJa7G1ef1Me9BDOX+5RtdYhM6Aoi0q6geOAZAT8UJHVxCc6iPICWDzMnjod0VwOgKg16iDhrOTBDflZBC2ajMpm1Ss5Sx8IdnJ2JX2hHnl4Kz4LDLOYivhUWqA/kxwBtI2cdyOK3mAcn/M5UELM0Lor7Z5sl/qv/Ekwm2qwWIhUSK/Kvd07ClR+SUn7zJFkiLEb+HU+ZvuCVeiUNEmf0c35f3wK4a5M2C8mOWysIygaDL+ROsD0sAUCGOtov4WjojbM1jsGXsvDs8UweBKF4S2PVDT7PeDhEsr8hve7IC+l5eOOjirc7jzFGUZgyiIh5jCc4mef/Cwm0Ho7VVXghl0uYUZPUyi0KfLLRwR6FKQPOpM7Z4OmY0rw71teejtzhemrMiwgwMiw25k9tM9N7B9EBYvX5YhZuvREGDX4xVnpdlcdXCajTg4zeawg1PLeSP9sXjsp/T0pggU6VTZz4UC321iGWxYZkjkGRnSHMqU34w2OzybNKC5tb+2g9NcbDILtw6IxssMIDs4VR/VUsZcuF6YvyhK1EOdmeRlRuEvCLNnqtUS0V5ez8HZXkoF7dMdTr/ZoXuuTkchqmnPI8ZlhUEZJDSub/IwM5Plg17T4rEuecvMIlqg2cbk4Byzg3P17Rm2uzlmT6rzdFZ0Q3RmUc0kzcho1tN2/aAO+b7Bjg7Oox3taNeyWzGz4BjB4wByaV0dGbyRN3V88RJApSPinHwm0R0yJCI8LSP+4HE+J33pC6BtC17MQBci3GIX86xOFtMshNiDQgA3M0FzKoLqyQvYRdIhSW9ds5gh3j9FnLmM02gai+H+Am1a1pjERxBmFrSdXmfoTNb1KL4HwG1DfrPYJ+fSvlkD92yNOGthdgPiTObY9tk5gFPsvrDIuiSA+EVqXRIAaBcN/EJ0Q3Jdm4A6Gy7rhoT7QASGEzPhjpR9pn/3p4TuJYFaszc9N+jWA8zmqshQ6GbFh5OaePnlLqMnQ1eARGwq8FMrCmHzzmJYTZcsbjddHuxT3wHyhh4XArAaTgnL75U+8+k31NnCxVdaDGcCyhqXhO55LXVIIOYMBe/PSJY7doXte3Ltsh+StCFNdEMUtBUmnBw0BXOhAuHVkzsPvPxJh9AB3Z02zzh2DwjbDzwolMd4OGW057WvpZxnPGO0zw3G03LyUFYwb7RbMVgctCvapckHEMIUaFWBrybHNE6WKo0DVGhoGLOjVEWC1Ivtlw4ufcrhNgOV6rp0oPCL9NCv5XvTNXKzJ7i2X1Xcn8lq0FQGTKVrG06m4CgFesVFI4pYqb3mUsrG1dXsU7+YPrxmsBLrp7IWBpJPJ133uJTrmDUWiOK4i3tAnX3AVH9X/AjR8WRbdLKcOnRT1f2h1z2cUs6x8HPkqXOduepngoRs1i4L+9QAqUJKc/jG1/OHrQCuFB8ByLWGOeUlxXBG6O8y7Fb8DRPN0BkApuwX6e9JdGz82KB/6GG8gumE+IatQV+BsnI7EkFPTOAss51O7vtHhyf7/V1OTlGCSQPM7kHE6RcvcLk9y/vFuyNiLaxVEfA0d3r0dgZzrzj6P3egrIO2z6cZOScn1MlhBxPGAGTW71glmAElvKoKYjlxa5ogpufU71oX+eTbSPtRiOLI81Fe2JpINvBrE732k7v0Dat1anIajaF8ahvGIHkY9fmJYIc4YQMzPjFujwxrtV1R0vkVIp1h6xJi1DV+bftJXiElX9lhX8+Tcz/uW90fet11Xgab4sFnU5WTzCzMGKvErnR8gmW/zuqkMLujibao62Vtr2V2JwOFJMhVb30Nd3KBodudcIzYMcKuDawmuaXQpd0VZ6ruD1TO2Ggm5ZM2HTC7FQe83RWwm9sQLi9nk3rG1k3+DhXp9dg0cBsD/yOXSLavgu6cpCmOfkqVV9HnTaIdTVqutK5IGAYjERNTqaA7daQZmIouL58zfde6wrxBbErUIXYyQ2hmDjCUHZ9vor1TyjsAiN5UdHsmb4eqtbtQmMWtlNVRDwA5jFl7y+3CYFiKZzxk1GOKtCTnmk7tZ2nmUlPdqe1T3vk5YLc0ERnSc2s/7lvdH3rdfl6cv35eCICiKwNUbGS6P65sXmbUFHdvmlkUEwh3rKMyHSHMKJeNS5lRsCUMd2MWRTJBZjiSx5HasJQZRH9KCMtCq6czC7vH7p0jYnszC967zw8pwQMS+QgtMO4IOkD6RcRqtcPloqw1eOnhh8Mzi5MHa1wMJ2hOK4HTt+C7uL2Dxb4quvdlZjGMWdBYv9MwTiMmwyhCvLuxCPWGkGcbuq7WjFK39jCbMXeInlO/6zntZgC1rqiQbz2ac4mcsDG5LncZrmiRItoMAHJrn9Mk3Tag1XDoUNpD/QhDlD91u9mMaC6bieI2E2BmFqHKQGzOPSha2G2ETYNgs/aw1cxCBwaz9SBmdOcx64yq1UrccpDJ+9Xb3JZzP+6bu7SlP9J1dy9NUTkfSDhOkwix+ixiw7AD0FyErD2qb2OXZgtqh3wWOhuR85lJhKNrJDyqZd1zC4op1BoMZk81twVwnYCtdLZBLAN/9zKie+zQpWwEt5EBuz1HHmyA2mdRQq51eW7T+WEF++GpFZ/F80o5ngzO5ydYPCn1DEO757Mo2y7jKbonFmNfymj/t32NHaMhRzva0a5lt3dm8UmNGapXcYWT86b6H4DwW9Sp7syZp0Agvu8Qir1vVVWU21ItC7jAgcnxpHxfv4Ji/GT9clOr2kFgZC2PujzyzTVbbtgmE6ZteJXex2f5e6vC2I11TuLeb/+WdnsHC9qbHtUiybXKWK08tq9aZuiqUlk6d5YCGBM6szWgsSiN5XPqd63LGURXfBYufWcrfPOFUv/1imGqFgYAMWVP5jrSdkGKGvBoC0zbqjBzUTwDkFXVaqSk/k2htNeMPGG/KhDpguDcvxn31cLCjBB2ikisBqdY+nHf6v7Q6/Yd5Rt3P3Sa6f3Vr2MpR3rCK8Kltf+i2HR7rHw9oZNzalnoihSAn8nSQzpHjhXSHc7nEgJggl9G+MsqdDpjmHHfZzGNhmTZgr2I1iFhatlfzm23lEOnfsEwJ2OOzAEQdbTKV1YLI/MywG8N4rIKuf8oIDiv2NuO4KpSFmIZJNIDwm+jXHblvBHEtrx1Apc3ny+JaO/ceO+tRjrjqR9eYePSxCZp/3T2U1CWh9fK79JqLU5KsOes6BVKuQmY6Ka+u/awRDNYnJk1wlLZuSYJYb6gLN+5VbOKCTnR29iY4OV8eEB6k92qwYIVkFK9+bKFIG9V76fsVzUjVr08GBNcPIQ842Dvq9BpYboCJKQocG/FDnNxslZ10RhAtiRFUQgSflSmrup8r2Oy2mev0pBcfbyyculnaYPsPzk/IV1nFdtPYVI7FLCZCTqzSIfpQ+nlGmr2qvy77L197K7sV2/TNtF4dcCs+0Ovu2Z9mty/NOUBtYOcd5+56iqT1esdnGFLkz7TpDAtc1vJL7E9p5CtdoD8p+xacqz4ae0Q4dYuh2hlaSI8nrFKRMuO0aj3DU3Ky36HXzZuI8FAt+E8QLkNYbhoJqHS6Mzk7wmtnpVjuGbKeot3xNHBebSjHe1adqtmFhPbR3BWforrIDi5a2TW0DaF3JdMfvncHMHZIM4dxkVK7d4IpNquE85C1cjfNYIz4SeyJZTmBME5WoxLCzaU1/bRFfATgMzmxI0FmD9TBGd/ShlaXiM42SCXh07e0M25fecIzv6M0N+TY/yychYnn4WAsrQPOEHJPyME5z3JICVPku6Ot0dw2rMBve1AdysEZ/OjgLPYN0Ml1fw6lhTK2JmcPk7OCjJzH/D1FsaNPHxZk9QZAQ45AXHt82q8K5uogQEpT6EolwFI2qoyFVXKOZOEdkpadxpEuh/CrUAFfKXKYBQYsaHsDGULhAaI3bufBEsbOA2unPuGojgzUaAx0q4ZY9zLm3l3bWPASDv8DX+q2WzExnY3Jh+6VYOFmafELe8nfJmysXBysvJrAoVj04fJMZR4OpWjE4BwdMYIBuAeSYKagrJmgweGMXNr8npT+DGquuxyBrMh2G0i0N0M6J4auBdbsDFCIAzhZnwdR6byYwKSNt6cp9di4sKcfdeBLjagywbUj6DL9LZ4eQnHjIW5M3GmsjUTjk9A1r9uk5jINdiyHhFbm52cbSL7UZKfu/9sl9PDc7v3EJnjiUNzIenl9TYzBtjzXQHBVbbYLHJ/5OseFtmJGBsDdgB5idDUsGwKDDtE3P19+R3qdPE6ulGjM3OblFp/iPAri8W313lb97RF6Azap4LVjnaF8WMDO8aULJf8WlEGMOMLPH5cGIxzQnfBeO+3LGYvxJEQWoPQAO3aY6g4OG1ySoZm2qf7zsqTD/fEUfT4YQa20heair/8CNh+eBfvfVzug3HZolmXc9a/z+WXznDnKcMvKiHlzfUHu9sxWBAAYxHX5Ye07z8sWaYAMMoD77//A9DP/HGY85SVeraAebFGPJ3DPlFpa0ZcdKCXa/CsAfVpEHn8JJ9//fP/IgDArSULc/N+g2YTM/z5rjHwd+egEGHP5SYNZ3L+8aTJy4bl9ww2X2ixTA9f892nAIBH/8aXhVdArw8ynVc27PnHizyFd1tg+1Ccju83XwYAvPzDMyw+PoOfG7h1zFP3+aMzbL/QYVgZNOupM2xcGoyr8uMvHgWMS5M4DBTB2Vw5BgDu/1/S99/510+ys07brlN9Xfb0DwK6Z3M0F8CYOJKJxQk3e7osQj7VmLN5YNCk/lA+hXEFNGttx6RZk/JmDdz5xoiPfiFN9Rdy3XbjEFYxL6myYrjlTLGHywbwBLt18O8POP2nMmWnCOweAONJxOk3BS69fQ/oH3rYtUFYBnSPy+Phl8kJupay/qEMDu/9lsXZv/ddfONb70u7lz1OVls8enSKO++d5+PXmw7MhMVC7qWHJ5cYg8VF30qU3sj5P/wnianbFOcjG2C4H0BLj/ZbM7hEYt/8mef4C3/kH+JXv/lzuZ6v3nuCrz95CCIGM+HOovyYD5sB33xyH3/owdNc9q1fv34453YMFofM+0m4lKu3qNkM2Y+g383WTd5otB0kyzR97p+juZROsusRMITupRFGba/kNyPsxkrYMddlK65FlQIY0L10sOs0IKV9uxdXYdN2MPDpxdG9iJm+zm2j4DQYhfzmZYvm0oO8hdsEmKBZriOaCyfs1JvpYGFHzh5+OYcknLlNzG+2Q8fk/gIwf8IlKQqQwWJWvgPiC2lfAs2G840r1wF0L2P26Nd4jWhL9MJqItmO8gBi99Li6/Jmw2guRswfJX9OTvMH/EUJY2t+Rq0pazeU1dJ632YWbgGwGbiNycQ1gIHxDnYn5+oqQnnFUehAqj6K2QuPb3zrfXTfa1IbGjxfztA9NXhZ+RJs8k1czGVgOp8vJUw7aN6RtOvs4+SXo9J/op3i4OcW84+RpQCefXiGv9n8aTz/8G6u57fPl4jP2uz/eTFflYuwDPO8we9elFwS319/2XyMhhztaEe7lt3emQVVLvs9Y1dnnRKISKjxaqSmMdN/e1YcfgbCt0mTTFCQojFj5sCAJTDSfimGzpWDU06oWaOEqDO8dHhoCk+kiPSkzSE5IrnOOiVEa8COwK5Q28FJWWjNlfVuqBCieg7dr0Zw7h9Tt1sQnNWMjipUoV7HDIg7IPhqGyM7JwuWoK6H8rIkO1VbZH3SuKc2WZeHIH2uM5w66hFmXM0sUlNqVXMuWIOp05IyUY3+lqGTaAaY4Oc8TfVOL2N92/s55/5rlj1C8lWFRQQvPMK6BS9KByj4U5dKzXJEZEJQ53uaWYSsUYMCmTEpyjJPOim6PFkEfGF5gUeLMoNZLHe42Nk8s3DzssxwTcCut5itKn/gW/jjb/FgYSYXQhWUmys2b27k+4Q0N5pE1Ft97p0jQ629dGxoDchXKcLOIrYWxpOkuwPZMRgdvXGwEJh1aq+mJ1cp5HU6ObHAlgUurYS9MhWWdnFJZ2+FfDc0gK1AP8B0MALSYJH204Hp0DGyIbV7VoBD2vbyEKZj5oxxEPLXOnQpmZicBZ8z6pLlYcuDRWaLouzg3Ic51+Xi1CtQ7DAvvqCw4PxOiXONoHBOvWZjRdmLgHASMqs7BYafCWS6EAGnwSemgaVqk4Y8tW8ybLsBTlZbPF8m5/zCY7Ya0G8cmmV5KEfTAJHQLGSZerLawgeLoXEwpqzXvDr5Kw5OjbzEuXCe6uDXLAd89eQxvr56mI+/v9xgt2tgDCNGwmpRUF+tC+i3Dc6WxY9B5jAI7JC9cbAgor8O4N8C8JiZ/3gq+y8A/EcAVAvpP2Pmv5u2/acA/jzGn4L7AAAgAElEQVQkk+M/Yeb/7dqtqS2Gqc+iQmeafix+hJ0DjV487bUXXhGc+rl3Dk2XthvxWTRr8Q3kLhk97Hac+iy24rNw1mTMgNl5uE2E2SlgXz6b9YFU72DyDdBeRJhQfBahFQen3Y7p+A7N2oOCtCuL5G5GuLUDRXPF/wBgki+i2+v9Dh2T+wtA+/Kqz0Jl9ApAkrLPwlRd7rZAs+aDPovQlrTzorJefBP7SMK6vNkw3DageyHb/K6gH01P1cxCB4jS1tpnwcahfVl8FmwJxhPacyXJldmk3QG2lzRzNRVaVp9FVplbezx6dIruaRps1y36jUP71GCIZSR1yWfhN/IyeLZuDvss0jXu+ywoGPidtEl9Fhcfz/EPTv8w+scluvGdwU18Fs/n1dsj+SwehTIT4QN5PK+y68wsfhXAfw/gb+yV/7fM/F/VBUT0xwD8uwC+BuADAL9JRP8CM7994oGxQCXrOplZtA4YNOHKwSZq/qxyzix0es6Vz71zqJOMvMSvx4UR8I0CpZxFbJ1EQwadxSStjLnN+zWzivwGgEl1CZ3dVXBTjoDsTP7OlKIYLNcDCBlM6CzCXFiglRavSWV1WE5tWJoJc3OzLfsd2n9SnmZPwylpd6WOB3y6F7NuyJ0EWDI0iYawTbwUOpPLeRTCaZmjQhoNWVLRgd0DftXlbIUrVDktNUHLbafJWqojCgNw6nvbWlAQar7xbokKURRdD7/i3J7hFOjvRriNnLfmo9B6dEapgKthaXDnvfPszORFQLMcMMQ53IMy6o6bRpYFCxmUV8sdIhO2u6Q/kwaL4eQk93seLEjqi4uI4dLBpSWpe7DDzz78Nn7jvAwWH9w7x/dMGQzm8zK7mbcjHttTvP+gjIKPmuvPLN44rDDz3wfw7Jrn+yUAf5uZe2b+FoBvAPjZa7fmaEc72q21TxIN+UtE9H8T0V8nIo3dfAnAd6p9vpvKjna0o33O7aYOzv8BwF+FuJb+KoD/GsB/+DYnIKJfBvDLADDD4uoOHF/ps0CMhTI9hETKyyXrVEl668+9c5icdRqBSEJs6zmraCEIYS+FQvhLKe3deC4K4T4myb5Y6oaS105BWWZExvXLOarvAyeympQz4GWJZEZJM68Vyc3IsOPVyIYdgVjTK1b72bGU7R+j1wtMSXQBmQJrlmj2A+wkI9MMDFspwZuB9/RE67YUh13J3OTcH/s6snW5HbSP0jb1F/WyWi2rPcVZcM6yFYo8YcQ2W8p1U5Q6Yk+F2q9P17ajhG0o7VEYvZZprocdGetNl3EUgcSZ6bZGlh7JaCs4Go1NrKmTaEjCOfh0/cvaP1RFQ+yOADLSxgR6GzcNPlzfw7gt9TzbzKVejb5U6bzD6MAbh5fr4kvh+On6LK4YMz/S70T0PwL4O+nPjwD8WLXrl1PZoXP8CoBfAYBTc+/twOoRmKSwJ5aqK4zg17WK66EwISXeh7ouLjfhdUwBXIwS9Sh1lr8lrVm/l7ootYfqdsWCWHxnVp2/5pyYVKtt5mq/1Fc57Z3LgcTl2ugtGKVr2xf5lXPW5yrn12dEWbd03xpVCp5ew02tfiDBQGbM3vu9Dx4TxVel0ZvaT5EdxK9qHwMRhJqhm5mqe/jTvVVuNFgQ0ReZ+fvpz38bwP+Tvv86gP+FiP4biIPzqwD+8Y1bVyVF0YQFy5SHNuEo2NIUZ/Gm0KkyZSmuwSX8hPaIFWcmEeWwotZzrdBpQzD7Ycqa3dsVvIFRvAKXN1h0JHU1hJiwFdpetvTuQqctpiSuVEKdGWfRMWJHCJ6K8G7CM0RHWYtCB0mw1KP9oW1869BpPq4MCmFWnohQZVjmtkYjgzwTwjxmXAmlcG7ouEgK3jB0ulj0GZnJ84BmMcJvbHZmAmVGoWWLhUhr7hIs2zUh9c2stL960g+FTt3C48uLF/j9xft5v7uLLXbbchMsqtDpvB3feej0bwH4BQAPiOi7AP4KgF8gop9Ol/P/AfiPAYCZf5eIfg3A70H65y/eKBJytKMd7dbZGwcLZv5zB4r/p9fs/9cA/LVP0igAwk1RU71Vswx25o2gLEF5Uv68eo70Bm9MAmVJzF3fJmwtYiehU8q8mDbXrzocbOU759lHhTzUN7S+5VrkN3HoypuSQgIccUkVFz5Ik1GYYQLKojRrmL6NY0OTzMvQlP0ySvHAMXpNUu8UH1HPLDIoaxHhdxKSVFSlLkOk/xSUVU4TugrBmenwkaUEapk9YFpuvPyOIYUvw6Is5sPy9YlkgSSRDAB45eHTDEBmD6r/Ua49ziNCNPktntuvMwtFlqZZTGwsHp5cSq4HBJl5stri2brBallCp2t6RSKZDZNEsueLlV7aBNQX5xG08Aidy+Wr5Q4/tfg+fmv1lVzPB6uXuNh1BxPJls2A88UMDxZVwuaPhG7I6zg3a8ZuVQ6LyE66t2GpFt5FQHkfi+8gOTgjC/M1xPmYB4U3GVcPnY4ZqR45f1mDm5Ck8ioHJ8WEAUlr/aLzwdOH+VO2K+zR1XS48GISyKc2VgOC+l40OW3q+2Bc8cu8QU3siuXjKdeHijYuOyoCwMqZGapr8gUUp7+P8WUp9NbtSTYGm+uOTPDp71j5MvQ718cAsi8AFQlTrk+e+LEO1xuZsGOXzwEAPhqpS+u7Id/mIbu9g8W+1YNHxMTRmAlf9EGOKTpRfe6fgyooMii9BauHGSREMhQ5g4zYUJYwtKPejJLRmbklUh3GV84qo3WWSEBNSqvbKJZroSgIwysPmEYCRi4PZbIwlogBIA9tSPuFtO+hYwDkaI7ZI6FlU8GOdfI00JXBtVwDl7ybqo91m1xLhcDUSISb3tR1uRk4RZ3SA5AjSqlt+vPWaEh1GAaCGRIjdkQZuKOwTlWUpdKerUnREDONhthpNEQZrszIuOjbjMQMTiDcNJgMuAIgUY9I2KVR/8IGgXuPAvf2CgDT9tjq/rFSXySXoiFSvt01eDycYhjLY/x0t8S2gnvbyiex8w67TYsnm8IHED538oUMWTLsj6BK0AsUdCYqL3u1H5x5u5lFHUwhunpMzYZdefU/sR04B5vk/a7KCts1T2Ykn1o7rtm+iaO/nlSlNueBMBYPft5vb9bxqjpu3NRU/5U3LzGQQpFspD4mAG2cDNxUDR6fxPbYEye5HtMGlzd9XhmbiK7x2PZ7mXTEuXGvmxwY4oP1vUXQ7tp2KwYLMkYeeF9eadQ24MSMBUCYq5LF1hYItk3e7hjBp2nE9G/2qWa9jEHCbOrFz+vyVYcwE40OXQLEmYXdXo8spNbrzFSOFtnzLrR4dScI50NIMPRxSXC7wqnp87raTng2P22LrlDHabv22b3ZsoTraLofSNqtuSV6fRQEvp6jFjdsv2IxMiaDpg/TBKuhyxCG8Ex6Anqbo11shWeTXcnIvalZE3PdVLXRVu3xabajUQ9rIloH+GCw7VucLKTTXnbis+AKsv6qAc0eoMfrrIe1DCKWd6j99NasRz6Lox3taNeyWzGzOGTsU7ZoK9Ozml/TXuwyd6YFQP0wHfViBJ3vwNutZBdut1fOMftYFn6m94AxgpIcIlxieja9h9tamCGUugiwz9cwmxbNeUoAer7GPDLsc/Ew80ZmQKuPfOZrzPibriiDNRc+k9CSZ7idIPw0G3bxcRBx5Y2B7QPcZVozbz1mz0jYs/rpLKfrHMK8TAuaFz26zsH0Hl2Kshw6BgDoXNp/9q17U5QnoYr8SNH4hOC2jGYTyyyHAdcnBKy6Vyokpx0LCjVclGxbzVANe4S8dbntI7rHa5x9o01l6reRGZcuE2NKhhPyYjmP2xVk6fDUYf6xOquB5oLg5waLxwWh2z8ycD3DdzQRKdY6tV3Kwn3y4Q4f/pP3MsNV6Bz8fIazF1VSGASZSbHgKJ4vVuLMTC9+nVGsPpS/o6XsX4pWsl5jazF/EnL27sfLE/za05/F7HvlMf7m4hTugqCCTedtaYPxwMkFcH5SCEFofWTKOtrRjvYp262dWRCROB4Pb8xRAzZmirJ8W0uoTE7nVLwBm8RSNSLrkdRKTm++gGotreekss5nZ8r1WZTIiyI1iTLKNFrK3njeo/v/tI2T7yH/bSj7LJSti03yyZjC4EWhOGp572VFND3P2+hrTtpmrn6yRYY75xlc5RuKo7wR2UiZzpIsxD/FlW/pxiFpUzkh0/Xv92O+H6g6JiJNjYuvTCNJsamiIY6AQ5KFBMDwpL+1DnX88gRH8cnum9szWOzhKjglcPEhB40meAElWaxKGLuWsrXu4iOISaIOKSwKQGQKh4S1SNT45i0GizrfA3pOYyril6JfYrzqkQKkEn+jkMiwAewYEdPdZIYAM15/6vi2Nmk3ADCDNBSalxWSkEWhSOkJ5oInS5iclMecjlHn383bJvWXz3rZo+A74ysMS/pOQUh8XM/VsdMEt5vaJIQcS9h80o/7uTSh3ocK/4aGsmMJs/Mr7mfFmdTtj1zquZo788nsuAw52tGOdi27PTOLfTN0NYBdb9MpPFH5W8FTkov3etMdbL2kKdN9mATEMQZIs5taAexNVmMQ8hLClKVVvZyISY0LgavlRgXFDjRZ0rAzwCsEdD+xVcun3PY8vd9bhthK6QycaOn4yjJJ8QysYcu8/e0AF7kPJsuQ4iQs/V2WIZRmDzi0DEnhanWG3nSGwaZaWqWlEZtpPyLhPepjKF5dsmTFM0d5RhEbgj2gIs+HliGoloIBmKbq/ggsQzhG8DiAEp8bRwZvkojQUyHpsvfvCZeEtYKj2KZgvjXCvdk24B98XE76Y18UucLlHJT8GdQW4EtIDy15GVjGOx3cEMv09eMXaLbCs0GXEuGg1QLh/gph7uAX8gt1AHYP50ik0LDpvLGjDN3NKd4OOXrQrMvDYweWm8QSmkdCeRYW99A93iAsW9j1gLCUtruPLwA6xfqDDq7iMQCEErDGYMxaIyJDm6bQ8l068Y+kCMK4TBocmztABIYlodlMTntFom88kSVFtMi4hegENt1tI9z66lMX2/YK/+flBxZ2l2DPldYpCHBJ8c3PALezYHOSBZqUYNdt8UatUwrA0IqqeZgBs5clwjHOLUwAmq206+VPOvR3GXZr4FeM4Wl5CjV3R3VS+nsJSzHMMNwPsP1U65TCzbROFaVa+yhsYFz+uLRhPLEwqrd6P+L0/Utcrq+nddrc6bF7MoO5V6KCsbv+gH0rBotrWS0NUNP7v4LuXx2fbOngeKrOQ/VDZCkATbTaryN9spG36ZUU9b1Zx5uo+jVBDBD/RE6HrqQE5NwGJn3qdm0nV+dnopT2Xl+jlEVH5aFuZKagSMIMwCICDE/o+fN59mn6OxSK/mqbUPYXx+yr+kOvu05RrxPgmIq/I7aE6MUBWFjBU5PjNAFN6fknlq6TYnqQJ3KHKS09t6cMCqGt6uGUYMdAzMlwnGcRtPTwKWQd5pJK7neEuKgGx8R4rg8vpVT1SNNHUJMVr/TfTFLwQ2PzTCouIh6s1jhflPDobDVgVwkHUZUmP58POJ83mFdp6/i8JpJRl34d76cZp4BEJJhhTk+AXQ9OjNuUvtOuB1fHUIwA1UlCEK3T5Mh0LxPOIumgti8czGaEGZPWaTqnfte6yM8l1p5zNCLcNoL6pIua2JS7Z2PGTKiZpD0q9Y0waSnhtiEvT7TO9sUIs+7hAsPsBrh0HbTr4V72aM4c7K6+GQnEBOPLw+C2EYCR9qWHprkMk+mxOuFU5mD+5Corud+bWZjRoHsp+9Xb3Jal3ZurWqedo9wfet1+1hapwxGTmUUuV6ckA4tHepzU6XY8mUkdQobahElwO1Fr655VyTPsEDpC9yypyN1pQVEQqOOO0D1Pfc6ijEYRWZKSPIk2a2C035phnia1Ivdg0J4Dw2V5vDSfQ/Ekqg9S558AwPzJYfTxeGIRGotmUxyfiw8dvslfwOI7pZ7hxQqL86pPKsHriwcN2ucG600ZXPAps3v/cGyP9WoSSg2xGuLT9yoaoqY+giISJPkj7KzQ8QEZGk5jAIUA0s7Tc+p3rSsnkx3oZEvg5DO2fYmi5M2VH4bGkOnhaAwZwJUp/MYAeGlT/kzbKQSh8qsHQieZoGb/TaFhtBy1YMTW5GPzOr8x4MDyUA1x7xzTaw1dtV+1zQ4x9+OVrqn6w1bJcJpsZnwJH8cqjd54Tmt7ygNIOed+IsuVanP0w/YMuy0yBUAlp9hXSXQ90gyoTuLTyEmJ/thB1Myjk6WJ0vNTkGiR3XJm4a7bSlU2rJTvtXd3+E1vekikZawAZxvAXdiJhCRbmvxdJysOQZZD9czvbcLFx2jI0Y52tGvZ7ZhZELCvom7eew+IQRyaQHZ4+idPYX76j4EuE/T3ZAH7skE8mZeRj1lms704PvMM4aNMHYrtvyoq6s2lBwywediK2vhK6ju7fIDxLKmoX8rw71eyTPILB5/2cxtCmBG4S38/Eofssz/5Y1koR63WDVk8cZWKOmP7nhEH2sUDAMDFT84xf9LBLwzcZYBPjsj5osX2CzMMS4N2PZ127+uGLB8zxrnICao+CDt35RgAWP1z6fsf/CuLyZvpkG5If4/RPXdoLg+oqD9z5S2qb2ZmbB7YqyrqS8rT+qIbkvoktcEvZJ+zZwGP/5T2f1pabM2bdUPWqhti0L8XEJtZbtvuPsGvGKtvS9nuAWH3QHVDprOmXGeSNNw9kLqWH4ma+bMPp7ohFx/fTDfk4+UrdEPui27I4kOX+2b7c2v82a/+Hn7jGz+V6/ng3jm+9/SwbsjDdsTjO6d4WOmGfDQ/vOw5ZLdjsDhg5CT+xGkNryI4AOBXLVxacoRVCzN4+JMO7YWmdDLCqoMdff4EAGzKOfq7isoUEZvtfXE+9mcJ8z9vMJ42Mt1PIazxtAUMoT+z6E9TfsOmxea+hdvI4GWfyuf2IcFfpOakafe4EmYmuUCDMZEiNWvC5ouyLh9P5Rq2DwwoOPg5oXWEYaX5FC22dy2GM7qSfTqeEMZqOUrBYjyR/caTFEk4cIz0ozyImw8iXD0IUWmzZla272+wWS3QvDAYT/WOBpoLIzwQuzIlV9s+JIzr0g8AMJ4xmotUdjIdWOvy5oIwe+6w+0pSmD+Re2K3brE43SEmhur7iVvSmYjGSuUfX6wwDBa7bYMf/9JT/ODJB7lt/fsB5s6A7U5CKtsPPE6/eIHLyxlWqx3O51VexYk4CoZ0j51+UX7c7Yd38Rf+yD/E32z+NADgC8sLfPXkMf7B6R/Gzz78dj7+w/U9RBC+vBDJsZ9afB87dng8nMJU4c1fe5pkdgwXYh/DOH3/Eg9Wa3yTvwB3Iffun/3q7+G/++D/xF+uYr4/f/J1/Oa9r8EQIzLhJ2ZP87Z77hJ/7+4fxS/e/f1c9p93e6Gv19itHSzYB0wILsbSIXY9gnYpuauxQD/Arl1xikaGvexBuwH20oGSE5Orc3QvZF+3CQAB81bkAPUGNzsPt/YwPoKSNKHb2MT43cAmFGVzPmDx1KA5lzq0rvljzo5Chdy6LcGnhLDZswi3LY46TuhODTvOnjm0FwF2MJI0lqIDbu0xe2lhB0K7ni44h52ZiPkungYMO4N2HTHs5IE6dAyAPHtafP9kugY2xcGp/o1hu8LsJaG9QE68AyQcPHsWi8RBRX7D1uSZhdtp+LjMLHRwUKvL3YbRPffovisDmuqVdjugXzbZV/F4LlOgmvzGrC3MQOh64NvDe7iTHJEUWAbTixlmT3Rwc7jcnsFtCJeLDosn9cyizCQB4DIpkL33ccSvfvPn8PxDoVJ4tDjD11cP0T9eTJTCxq1onSq57m+tvjIhv1HTpLB9rdPL9RnOFydYfKfMLH7jGz+Fv2w8/s7/+8fz8b995yv46OnZK7VOHz85xT97ULRRn/XfwnXt6LM42tGOdi07DhZHO9rRrmW3dhkCQ0CtllTR6nFjMtybVRdkL8mLWycIzvS5fw5ldDaDhEP9jIRlO7N7C4Rczp/OaQjcGISZxZgQkV0n37tO41mJ6WpBJZSXZth+TvDJIRjWlKf3FJMTkZGvy3cCBw8twQ4FwMVG2LrHJU0U0wFxGI6rMp0fL0zeT52Kh47R/pK/92DKVJx7ugzxZx5mcPCBig+GAWKCXxOa5OMJGhpmuXZd4qnfZDwp/hxfaCHzdWo5G0KYWfiV+qnkRNFZxFXI/WxXGh/m7AcYqUUMhLgxsCcjQkI3EotzMywjQvrthlNGvDtibB146TEMFeI31R0VxHd3TP3V4qv3nuC3z+UCFssd7i83+M7g8MG94kh8tpmDmXA3sW1/sHoJHw2e7uS4zkrbv7kQ9WemklvJqb7ZasDwYpUBgB/cO8fPn3wdv33nK7meP3nvIzBTZvd+uLjI286aHX4HwJ+4//1c9nX3I+DgRKzgcsAEpGWGkP+mMYJ8AA1+wsFJgxd8QvrcP4dNEF8BWAm82G1j/iHISwZqnYlqhgAYgm1M9reaPqDZRph+ittoNoxmD9wkbaO8Xc1tGc2lDC5aV7MVHAM7ATEpoa0ZA1wfEdcmw5TzqfdQrM02go3Jn1p26Bga5GZtLnElGkL7KeCNQ3NJaC5LoUZDmi0fjIY0ayr9oc2k4rPYz46sy92GYXcBzXki6vEaRSL4ShApDIpyBcKVaAih77rqvEBzLgOplrXnhNg2Eg0ZGrQVuMl7dWgn5GsadJo14+tPHiI+k4HlYmex2zWIz9qJmrlGQ1QA6GLXHYyGOPXd7EVDYttg11sszguO4ntPz/Cb976Gj6roBzNNoiHPNwUPP29HPH5yit+p+rn3108Bvr2DBYDXso7ubyN6/f5Xjk+fBgXsRVVCUL1PVj+7WSJOBj5ROWedaDQh7KWyb064MlQd9xqej0/LqtMfJOyl1L66v+KBsvokVF3vTZs/ja6muricMJdzGZBSVEH3nSSxaVs/YXcS8aRtxvDVc165XaXdxnC6dXmynxINA3htSr8Q9pYXj56HDIMjTSItn9Ru92DxOpbuQ2zctSbpG8+dPiOyIM1E66Pep9ZCvcGAUd6w5Zy1bkj+Xm9npJBtmo/mfZVt/B0OGFX3TVYksWwv+qFVe/fLqpnFRNv1pvcvTz+v8DXk8pKxqcQ4um+RI0D5vT/h87SvLxojXT1n9dvmY5D2RVkhX7kngAlL+r5FpnyO+rycyuKNR+ardrsHi/oNWquJ1bqmKdWbjZnsf11FMnaUkrBUvauq2yT4tvpHksbqtRTJmpKRmbVv2pKUVeuSGi/ficvxoUkJazYllGWWqpLI9k4UydppqjYTSp+kSwwzFgW36npkCSXnLzoj6cFkmqSH58+3VSRTfVFVB+MExNKxXgFGhBw6jSH5ogDwLCA2Nh8bs9ZpSSS7iSLZncUWL+YCHnFzj9Wix/N5OwFEMRMYRXv0zmIL5qLroSzcypnJhstASHxQkWw+H/ATs6eT8OjDxQWeb+YZZ3FvWdaUn1SR7BgNOdrRjnYtOw4WRzva0a5lt2MZwgBimJDfqOCQ5ou4L34BHCPMcgkEBiU0Zo5YMIMvy/Qqfvk+KAjsO/NqqtiyMVMfAAo8Oa+zNztBh6bvgKBFt19aws+EVAYAxpMG/ZlBey6kMuZeCX3Va+t8qUbrLWVZAJcAu5apqx1maDYebBu4rUd0yWu+GWH7DuMXaRL9YCN5FL6ABtHvDIbTJKycYd5GWKRS/eOplPcPl7r5qgNy/5Vi+arfIR1jB75CcqPXaJMkoS45xlUVIl0J4xMFWb5l3o+OER1h89CVdqmQD5Ljd698v13sWPY1PMlUpUAgX7hBxzNGc6fH2DQ4ebDGZZTfEhHgZQBGys5GezZgNhtx+aUzPGyGXLdrAloXAMuYtyVVXyUGtWzZyO+889NHsCwBp/Hr5k6P+XzAxYMGQ7pfHrYj7rlLqS/ZWbOb1Kv1AMAvPvg6+vA1fO2shE7/kb0+PdjtGCwO2V6aM/uQQ6l1OHQSIq3DqzsP9APMtsC9MYzJWRlgd8qtkEKd2yjhOe0RPWf6rnU1lx6ILj/0bu3RnVuBaRPBJI2RZs2vDW3uhzObBAPPIcwUjrWNyZ+63e4Cmkt7JVHN+BJWBIDuXNK7mzXDpy5oL6M8oMlpa5LGplt7CXFelPCi2n5YM3QGzYWEN+ttbsO5H/etqUK9et3tuclhQFMR7jAJdBzQRDKgOw9oU+i0DmP6iirAD1PmMN1HP2PboFmXa/MX4s9oEgS+fW7Q2xncxuBiOEH3pPg3/NYAsZyvtx02tsOdp4xvPrkP81zq3vUW/baBed7gsT0t15TykvrEbna+SMlrmymz0MkFDtruyQznc+GjUNatx3dO8ffu/lE8flLq+R1g8rfWAwB9+Bq+/fheFmUGgO14tc9eZbd3sLB78SJDEN50TIBWE/BVdUxsLawV+UFO+1IIGemiMoF2lBtlnBuQRwZbIZ0TwKSu0FmEuck0daEzGBeE2FkwAS45Ct8EmlLAFAABTaXyDI5KQK8ws7BjzO3l1gkorAZ9AVDpwBrcNG4IfiG8DLmuYITfIr2mMyjLGTCmQCm1fcDUeCfC9hZspvWxIYwXJnNn7F+79kfOOl1VQK+lcGISp1CyOnrnEu70M4PhNP12FUBKvwMAL69WPKb+jM4I4GpZHs7xBBiXXNpzGmHuDfCtQ3M6YOw15g3EZQC4SEXQ3QFkGX6xwB968BS/eyHTpdlqwNlyi0fhDO9X2Z0v14J3OEvJbupkrEWKgakAUG3m3oD5osd6c5Idsg8fnOMX7/7+JNfjT9z//gRHUTszv3b2fYzB4qfvfzeX/Y67/szi6LM42tGOdi07DhZHO9rRrmW3dxnCe06yyKUsVhR6+j3GyTGUaPYErl3R4gEAcxHMSZ/Gc/53sI70acYIMxbyWRMYdmAYdaKmTzsU0lk1OxBi8h0Yz7ADVd+R69AySu2hvXbJ/pwdhlJxwnZUOAo7MMKQ2MPT0knsJFEAAAFJSURBVNSOZboPFFo3CoJXMANKW7RJe8tas6O8X71Nr3n/uvf7Q6/b9qX+6KZLH6dK7IZgE9Wd7ZXAR4+n/B0Awv7SNbVV9/U7O7k2MwDWUe5H0xPGjYPZWoy2QbNTOCXA1goXZyobNg4w0v4nmyWQWMp72+CcGNhZnG8qf4H6KvY8w/U+2qZDFjYOW2LYXfFZnG9m+Fb/3uQc31+cXjmn2rebe3i+meO78zu5zMfrzxeIr4N2fMdGRB8DWAN48sNuy2dsD3C85j8Idpuv+ceZ+b3r7HgrBgsAIKLfZuaf+WG347O04zX/wbAflWs++iyOdrSjXcuOg8XRjna0a9ltGix+5YfdgB+CHa/5D4b9SFzzrfFZHO1oR7vddptmFkc72tFusR0Hi6Md7WjXsuNgcbSjHe1adhwsjna0o13LjoPF0Y52tGvZ/w9d3p6xIk1iNgAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6518>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 40.94797682762146 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-09, 'kernel_type': 'branching'} is: \n",
+      "[[  20.00000002   12.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [  12.           20.00000003    0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [   0.            0.           20.00000002 ...   20.00000002\n",
+      "    20.00000002   20.00000002]\n",
+      " ...\n",
+      " [   0.            0.           20.00000002 ... 1052.00000179\n",
+      "  1052.00000181  984.00000181]\n",
+      " [   0.            0.           20.00000002 ... 1052.00000181\n",
+      "  1052.00000188  984.00000195]\n",
+      " [   0.            0.           20.00000002 ...  984.00000181\n",
+      "   984.00000195  922.00000315]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.11429309844971 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-08, 'kernel_type': 'branching'} is: \n",
+      "[[  20.0000002    12.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [  12.           20.00000032    0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [   0.            0.           20.0000002  ...   20.0000002\n",
+      "    20.0000002    20.0000002 ]\n",
+      " ...\n",
+      " [   0.            0.           20.0000002  ... 1052.00001792\n",
+      "  1052.00001806  984.00001808]\n",
+      " [   0.            0.           20.0000002  ... 1052.00001806\n",
+      "  1052.00001876  984.00001954]\n",
+      " [   0.            0.           20.0000002  ...  984.00001808\n",
+      "   984.00001954  922.00003154]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 40.992021560668945 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-07, 'kernel_type': 'branching'} is: \n",
+      "[[  20.000002    12.           0.        ...    0.           0.\n",
+      "     0.       ]\n",
+      " [  12.          20.0000032    0.        ...    0.           0.\n",
+      "     0.       ]\n",
+      " [   0.           0.          20.000002  ...   20.000002    20.000002\n",
+      "    20.000002 ]\n",
+      " ...\n",
+      " [   0.           0.          20.000002  ... 1052.0001792 1052.0001806\n",
+      "   984.0001808]\n",
+      " [   0.           0.          20.000002  ... 1052.0001806 1052.0001876\n",
+      "   984.0001954]\n",
+      " [   0.           0.          20.000002  ...  984.0001808  984.0001954\n",
+      "   922.0003154]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.210148096084595 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-06, 'kernel_type': 'branching'} is: \n",
+      "[[  20.00002    12.          0.       ...    0.          0.\n",
+      "     0.      ]\n",
+      " [  12.         20.000032    0.       ...    0.          0.\n",
+      "     0.      ]\n",
+      " [   0.          0.         20.00002  ...   20.00002    20.00002\n",
+      "    20.00002 ]\n",
+      " ...\n",
+      " [   0.          0.         20.00002  ... 1052.001792 1052.001806\n",
+      "   984.001808]\n",
+      " [   0.          0.         20.00002  ... 1052.001806 1052.001876\n",
+      "   984.001954]\n",
+      " [   0.          0.         20.00002  ...  984.001808  984.001954\n",
+      "   922.003154]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483ec88>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 40.856850385665894 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1e-05, 'kernel_type': 'branching'} is: \n",
+      "[[  20.0002       12.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [  12.           20.00032       0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [   0.            0.           20.0002     ...   20.0002\n",
+      "    20.0002       20.0002    ]\n",
+      " ...\n",
+      " [   0.            0.           20.0002     ... 1052.01792018\n",
+      "  1052.01806017  984.01808009]\n",
+      " [   0.            0.           20.0002     ... 1052.01806017\n",
+      "  1052.01876019  984.01954015]\n",
+      " [   0.            0.           20.0002     ...  984.01808009\n",
+      "   984.01954015  922.0315404 ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.11492156982422 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 0.0001, 'kernel_type': 'branching'} is: \n",
+      "[[  20.002        12.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [  12.           20.00320016    0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [   0.            0.           20.002      ...   20.002\n",
+      "    20.002        20.002     ]\n",
+      " ...\n",
+      " [   0.            0.           20.002      ... 1052.179218\n",
+      "  1052.18061656  984.18080912]\n",
+      " [   0.            0.           20.002      ... 1052.18061656\n",
+      "  1052.18761912  984.19541516]\n",
+      " [   0.            0.           20.002      ...  984.18080912\n",
+      "   984.19541516  922.31543964]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 40.87431502342224 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 0.001, 'kernel_type': 'branching'} is: \n",
+      "[[  20.02         12.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [  12.           20.032016      0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [   0.            0.           20.02       ...   20.02\n",
+      "    20.02         20.02      ]\n",
+      " ...\n",
+      " [   0.            0.           20.02       ... 1053.79380088\n",
+      "  1053.80765645  985.80891211]\n",
+      " [   0.            0.           20.02       ... 1053.80765645\n",
+      "  1053.87791287  985.95551658]\n",
+      " [   0.            0.           20.02       ...  985.80891211\n",
+      "   985.95551658  925.15796565]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.06723380088806 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 0.01, 'kernel_type': 'branching'} is: \n",
+      "[[  20.2          12.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [  12.           20.3216        0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [   0.            0.           20.2        ...   20.2\n",
+      "    20.2          20.2       ]\n",
+      " ...\n",
+      " [   0.            0.           20.2        ... 1070.10088288\n",
+      "  1070.226048   1002.171312  ]\n",
+      " [   0.            0.           20.2        ... 1070.226048\n",
+      "  1070.95207088 1003.692176  ]\n",
+      " [   0.            0.           20.2        ... 1002.171312\n",
+      "  1003.692176    953.938048  ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ad7978>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.024009227752686 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 0.1, 'kernel_type': 'branching'} is: \n",
+      "[[  22.       12.        0.     ...    0.        0.        0.    ]\n",
+      " [  12.       23.36      0.     ...    0.        0.        0.    ]\n",
+      " [   0.        0.       22.     ...   22.       22.       22.    ]\n",
+      " ...\n",
+      " [   0.        0.       22.     ... 1250.1088 1249.608  1174.032 ]\n",
+      " [   0.        0.       22.     ... 1249.608  1259.6168 1195.136 ]\n",
+      " [   0.        0.       22.     ... 1174.032  1195.136  1278.688 ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.10013508796692 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1.0, 'kernel_type': 'branching'} is: \n",
+      "[[  40.   12.    0. ...    0.    0.    0.]\n",
+      " [  12.   68.    0. ...    0.    0.    0.]\n",
+      " [   0.    0.   40. ...   40.   40.   40.]\n",
+      " ...\n",
+      " [   0.    0.   40. ... 5812. 4962. 3816.]\n",
+      " [   0.    0.   40. ... 4962. 5996. 5030.]\n",
+      " [   0.    0.   40. ... 3816. 5030. 9688.]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 40.94809317588806 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 10.0, 'kernel_type': 'branching'} is: \n",
+      "[[2.200000e+02 1.200000e+01 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [1.200000e+01 1.940000e+03 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [0.000000e+00 0.000000e+00 2.200000e+02 ... 2.200000e+02 2.200000e+02\n",
+      "  2.200000e+02]\n",
+      " ...\n",
+      " [0.000000e+00 0.000000e+00 2.200000e+02 ... 3.958972e+06 6.327120e+05\n",
+      "  2.222640e+05]\n",
+      " [0.000000e+00 0.000000e+00 2.200000e+02 ... 6.327120e+05 3.959012e+06\n",
+      "  7.481240e+05]\n",
+      " [0.000000e+00 0.000000e+00 2.200000e+02 ... 2.222640e+05 7.481240e+05\n",
+      "  2.076862e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.258952617645264 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 100.0, 'kernel_type': 'branching'} is: \n",
+      "[[2.02000000e+03 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.20000000e+01 1.63220000e+05 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.02000000e+03 ... 2.02000000e+03\n",
+      "  2.02000000e+03 2.02000000e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.02000000e+03 ... 2.96981803e+10\n",
+      "  4.64741652e+08 1.21301784e+08]\n",
+      " [0.00000000e+00 0.00000000e+00 2.02000000e+03 ... 4.64741652e+08\n",
+      "  2.96873087e+10 5.91356384e+08]\n",
+      " [0.00000000e+00 0.00000000e+00 2.02000000e+03 ... 1.21301784e+08\n",
+      "  5.91356384e+08 1.68795632e+09]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54822470>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.04060077667236 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1000.0, 'kernel_type': 'branching'} is: \n",
+      "[[2.00200000e+04 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.20000000e+01 1.60320200e+07 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00200000e+04 ... 2.00200000e+04\n",
+      "  2.00200000e+04 2.00200000e+04]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.00200000e+04 ... 2.88881802e+14\n",
+      "  4.49657807e+11 1.12913809e+11]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00200000e+04 ... 4.49657807e+11\n",
+      "  2.88869914e+14 5.77517955e+11]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00200000e+04 ... 1.12913809e+11\n",
+      "  5.77517955e+11 1.65196715e+12]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.14581847190857 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 10000.0, 'kernel_type': 'branching'} is: \n",
+      "[[2.00020000e+05 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.20000000e+01 1.60032002e+09 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00020000e+05 ... 2.00020000e+05\n",
+      "  2.00020000e+05 2.00020000e+05]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.00020000e+05 ... 2.88088018e+18\n",
+      "  4.48165618e+14 1.12091218e+14]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00020000e+05 ... 4.48165618e+14\n",
+      "  2.88086819e+18 5.76151620e+14]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00020000e+05 ... 1.12091218e+14\n",
+      "  5.76151620e+14 1.64839643e+15]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.058295249938965 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 100000.0, 'kernel_type': 'branching'} is: \n",
+      "[[2.00002000e+06 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.20000000e+01 1.60003200e+11 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00002000e+06 ... 2.00002000e+06\n",
+      "  2.00002000e+06 2.00002000e+06]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.00002000e+06 ... 2.88008800e+22\n",
+      "  4.48016560e+17 1.12009120e+17]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00002000e+06 ... 4.48016560e+17\n",
+      "  2.88008680e+22 5.76015160e+17]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00002000e+06 ... 1.12009120e+17\n",
+      "  5.76015160e+17 1.64803964e+18]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.07671785354614 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[2.00000200e+07 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.20000000e+01 1.60000320e+13 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000200e+07 ... 2.00000200e+07\n",
+      "  2.00000200e+07 2.00000200e+07]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000200e+07 ... 2.88000880e+26\n",
+      "  4.48001656e+20 1.12000912e+20]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000200e+07 ... 4.48001656e+20\n",
+      "  2.88000868e+26 5.76001516e+20]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000200e+07 ... 1.12000912e+20\n",
+      "  5.76001516e+20 1.64800396e+21]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483efd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.05622744560242 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 10000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[2.00000020e+08 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.20000000e+01 1.60000032e+15 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000020e+08 ... 2.00000020e+08\n",
+      "  2.00000020e+08 2.00000020e+08]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000020e+08 ... 2.88000088e+30\n",
+      "  4.48000166e+23 1.12000091e+23]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000020e+08 ... 4.48000166e+23\n",
+      "  2.88000087e+30 5.76000152e+23]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000020e+08 ... 1.12000091e+23\n",
+      "  5.76000152e+23 1.64800040e+24]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.206252336502075 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 100000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[2.00000002e+09 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.20000000e+01 1.60000003e+17 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000002e+09 ... 2.00000002e+09\n",
+      "  2.00000002e+09 2.00000002e+09]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000002e+09 ... 2.88000009e+34\n",
+      "  4.48000017e+26 1.12000009e+26]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000002e+09 ... 4.48000017e+26\n",
+      "  2.88000009e+34 5.76000015e+26]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000002e+09 ... 1.12000009e+26\n",
+      "  5.76000015e+26 1.64800004e+27]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.20313096046448 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 1000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[2.00000000e+10 1.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.20000000e+01 1.60000000e+19 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000000e+10 ... 2.00000000e+10\n",
+      "  2.00000000e+10 2.00000000e+10]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000000e+10 ... 2.88000001e+38\n",
+      "  4.48000002e+29 1.12000001e+29]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000000e+10 ... 4.48000002e+29\n",
+      "  2.88000001e+38 5.76000002e+29]\n",
+      " [0.00000000e+00 0.00000000e+00 2.00000000e+10 ... 1.12000001e+29\n",
+      "  5.76000002e+29 1.64800000e+30]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 41.18393611907959 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 3.0, 'lmda': 10000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[2.000e+11 1.200e+01 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.200e+01 1.600e+21 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 2.000e+11 ... 2.000e+11 2.000e+11 2.000e+11]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 2.000e+11 ... 2.880e+42 4.480e+32 1.120e+32]\n",
+      " [0.000e+00 0.000e+00 2.000e+11 ... 4.480e+32 2.880e+42 5.760e+32]\n",
+      " [0.000e+00 0.000e+00 2.000e+11 ... 1.120e+32 5.760e+32 1.648e+33]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.285051107406616 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-10, 'kernel_type': 'untiln'} is: \n",
+      "[[6.50000000e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 7.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.50000000e+01 ... 8.10000000e+01\n",
+      "  8.10000000e+01 8.10000000e+01]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 8.10000000e+01 ... 4.64900000e+03\n",
+      "  4.54500000e+03 4.54900000e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.10000000e+01 ... 4.54500000e+03\n",
+      "  4.44700000e+03 4.44100000e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.10000000e+01 ... 4.54900000e+03\n",
+      "  4.44100000e+03 4.47100001e+03]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7fd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.16685366630554 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-09, 'kernel_type': 'untiln'} is: \n",
+      "[[6.50000002e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 7.20000003e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.50000002e+01 ... 8.10000002e+01\n",
+      "  8.10000002e+01 8.10000002e+01]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 8.10000002e+01 ... 4.64900004e+03\n",
+      "  4.54500004e+03 4.54900004e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.10000002e+01 ... 4.54500004e+03\n",
+      "  4.44700004e+03 4.44100005e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.10000002e+01 ... 4.54900004e+03\n",
+      "  4.44100005e+03 4.47100008e+03]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98abac50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.1623272895813 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-08, 'kernel_type': 'untiln'} is: \n",
+      "[[6.50000022e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 7.20000031e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.50000022e+01 ... 8.10000022e+01\n",
+      "  8.10000022e+01 8.10000022e+01]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 8.10000022e+01 ... 4.64900039e+03\n",
+      "  4.54500039e+03 4.54900042e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.10000022e+01 ... 4.54500039e+03\n",
+      "  4.44700040e+03 4.44100045e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.10000022e+01 ... 4.54900042e+03\n",
+      "  4.44100045e+03 4.47100076e+03]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.32983350753784 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-07, 'kernel_type': 'untiln'} is: \n",
+      "[[6.50000224e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 7.20000312e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.50000224e+01 ... 8.10000224e+01\n",
+      "  8.10000224e+01 8.10000224e+01]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 8.10000224e+01 ... 4.64900392e+03\n",
+      "  4.54500389e+03 4.54900422e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.10000224e+01 ... 4.54500389e+03\n",
+      "  4.44700403e+03 4.44100454e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.10000224e+01 ... 4.54900422e+03\n",
+      "  4.44100454e+03 4.47100759e+03]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.128589153289795 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-06, 'kernel_type': 'untiln'} is: \n",
+      "[[6.50002240e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 7.20003120e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.50002240e+01 ... 8.10002240e+01\n",
+      "  8.10002240e+01 8.10002240e+01]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 8.10002240e+01 ... 4.64903916e+03\n",
+      "  4.54503895e+03 4.54904218e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.10002240e+01 ... 4.54503895e+03\n",
+      "  4.44704026e+03 4.44104542e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.10002240e+01 ... 4.54904218e+03\n",
+      "  4.44104542e+03 4.47107588e+03]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.32317566871643 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-05, 'kernel_type': 'untiln'} is: \n",
+      "[[6.50022400e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 7.20031201e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.50022400e+01 ... 8.10022400e+01\n",
+      "  8.10022400e+01 8.10022400e+01]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 8.10022400e+01 ... 4.64939159e+03\n",
+      "  4.54538951e+03 4.54942183e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.10022400e+01 ... 4.54538951e+03\n",
+      "  4.44740265e+03 4.44145419e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.10022400e+01 ... 4.54942183e+03\n",
+      "  4.44145419e+03 4.47175889e+03]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f548227f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.280919790267944 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 0.0001, 'kernel_type': 'untiln'} is: \n",
+      "[[6.50224019e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 7.20312061e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.50224019e+01 ... 8.10224019e+01\n",
+      "  8.10224019e+01 8.10224019e+01]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 8.10224019e+01 ... 4.65291887e+03\n",
+      "  4.54889780e+03 4.55321930e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.10224019e+01 ... 4.54889780e+03\n",
+      "  4.45102939e+03 4.44554332e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.10224019e+01 ... 4.55321930e+03\n",
+      "  4.44554332e+03 4.47859354e+03]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.21030879020691 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 0.001, 'kernel_type': 'untiln'} is: \n",
+      "[[6.52241921e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 7.23126085e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.52241921e+01 ... 8.12241921e+01\n",
+      "  8.12241921e+01 8.12241921e+01]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 8.12241921e+01 ... 4.68848458e+03\n",
+      "  4.58424911e+03 4.59129182e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.12241921e+01 ... 4.58424911e+03\n",
+      "  4.48758275e+03 4.48657940e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.12241921e+01 ... 4.59129182e+03\n",
+      "  4.48657940e+03 4.54739909e+03]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.004716634750366 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 0.01, 'kernel_type': 'untiln'} is: \n",
+      "[[6.72592640e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 7.51812813e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.72592640e+01 ... 8.32592640e+01\n",
+      "  8.32592640e+01 8.32592640e+01]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 8.32592640e+01 ... 5.07487390e+03\n",
+      "  4.96576790e+03 4.98191149e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.32592640e+01 ... 4.96576790e+03\n",
+      "  4.88307472e+03 4.91167067e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 8.32592640e+01 ... 4.98191149e+03\n",
+      "  4.91167067e+03 5.28282860e+03]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8908>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.10876154899597 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 0.1, 'kernel_type': 'untiln'} is: \n",
+      "[[8.93840000e+01 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 1.09772800e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 8.93840000e+01 ... 1.05384000e+02\n",
+      "  1.05384000e+02 1.05384000e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.05384000e+02 ... 1.39665408e+04\n",
+      "  1.31096732e+04 9.99189165e+03]\n",
+      " [2.00000000e+01 2.00000000e+01 1.05384000e+02 ... 1.31096732e+04\n",
+      "  1.36994003e+04 1.09159036e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.05384000e+02 ... 9.99189165e+03\n",
+      "  1.09159036e+04 1.90906862e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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s3F22Aqqu/rKvR/Yxu/hYa71GtnAfvaE8GyF628Dc1D+4xi7L0jc/3q1/CyJZjICFJMmJRFsiGt7b697pVBJM2a9Bc1dfgiHXtTrZK9da61V0dpG6xpZI2xIOa9/zn1/tHqeiQZjFGFiWuA4XXCa9EObpNzD2WDHWlVC5FgBmnGwe089YCFlthoxLyeCcrrINEQgEURDJ4rCga0ToPDC2sndoIJke8RmjcFyGtYpu3++sEB0iWQgELsQqQ/cTBtIrkoVAMBRtuoyxQtRDLucxbZ39xQ8vzEIgGIp5RJ26+ugTddq3PWQbMgo6+ynMEW200coqaKXjqfETi9+913MsPwugPNlc68PRV3V6vJ0VS29j0+Gisa+fBdA8Cd3nZ0GE9OQJP10xQ3WnTiAQHEYs7yNxH6GXY9Oc0EZbdQp3F5+Hia0AvddzRKes/M6dcFvmoo69blM5ZenQdRUdnLKy198YRIMwC0GBZXYsW2YsYt0W9FsJs5gKXTTk9uch/Yfqx/Tvy0/hyjHh2vPG5I0I5cAIzattj+1Lia+Xh6wJffpnNvUG+nX7xHQAlFBZxGYbva5r/vpZqOq6ra8Ikl4GvHU9dV2DMIup0FVD3vVpMWX9LpGeelnoZpvHFsd3E7gYRa+xPTdy27jaZ86T4PUKje1NYA4RN381boPZtTatIApOgUAQBZEsBCaGSCBTSw8x26BlR9SBQJHz6rKd6Ln10CHMYlkwz2jPvhjLI7GrfibUh/e6Q+wO6UqWGaG52vksRmAKPgizmCfa/qwuJeIywOfcZDONJTG9FmP49AiRIfqu9fcpR7soDV3Jcm0Fpz1GsDsykwUPUGC2QXQW88Q8bpIh3oCq/TzgGyfkddk2rz5Zq11tfHEUnrGVhaPRJyX1y9FGvUBJ/VmHL7tWG/32dZuOAF0hCLOwQGtr46fJ87kea6/EHjMk6rdZHWL+ZKH2nrGS9fUqlZxyh06OHi1S9+l1W2/qDlaTlnm4Utsl6+uYXbqI2aWLtYuzqmvRlhw72k6DKvPQkhw/Zo1/xGprWT04B62tgXNGsrGBZP0IOGfTnEpJFNNPTm6A0tR/85fjVS+7rAOEWQgEgiiIzkKh3KNG59O09+2hJ2CEM1K+s+OkJ9ifjya9XhttLsck26eirKNyTqb/9C3IfvRSUXb/fjx9rrF9DlEh3Y22L2/kGKUE+fYO8quvNIbLt3ea637Pol8d0qOO+tNpNeiqDwXK7z0w2ucPtr30Ulo4UvHODihNkd+9B84y7L33GQDA7G/+Z9lv5FP/0TPgm7fqodLUzHNjH2qUZRUNADodri7MAjCUWmo7kG9vx9+wsV6R+tbC2IsnSNaPmDde6Eb3lfeJRWgT+3WRvYyyzH70EtLN08hu3a7E/Gzrbv0Hj7V2xKxhixNScvy4ecNzjnRjA7h0vvh+83VkN16t11jdyGUf6fFjyFQcCDNqD0mHp6aPhhPHkd26bYyf6bElRvr/4k5ONzaQ3b2H9JEz4PsPMPvb75n964rKgNKSbm+BZiuN/qs2Wh/qWuP0tEgQL4HG/QRt8rvoNxZNxnwxxPQ4JWzpJ/T0d8Hnuh7r7h1LW2tdj6ekTSclzWCs0Pg+V2yfm7kaX928Nl1drRf6+EnadB/3MRjPOC/mf40tvhW1sKKzsJAcOYLkyJH2il0Qkbegyo1gt/H1FzPWWFBKWE2ZqSSK9NQppKdO9bNEhGJnfN8tFIpWU7ufHD+O2ZOXMXvyMtJHztR1jzaVmenpk+Z6+dbPp6AGMLtwXitPHL9lc23S0ydBaYrZhfNIT54Apam5PYhZT86RXrpQVq8tK42xdSuIXibWEIFAMAVEZ6FQipgNReMYiBDj87t3m0q1rgrOseDpX9epZFt3i/c3tgb1ORT5vfum6E0J8nv3waXiUzdHNhSPALLbbwymLbv+av2F86bS1EV3uW7ZtevgnB0+FnFbk+zqNfcZJxM4ZgmzUJiLV6HDA9C4nrvr2uhjKekCW+fg1DXk5ntMnzHh6F3jTRpRlI7oTl9dZ3+BdfXoWloVhrauAiUT03QWvTL1l211RhNScHb+zSwIs7AxLwXjoFDsCWkM3axD3LmHhOPHtjOkspYDgiuG2FO5aJRboetqbCc99gMhbzKitvG0cZ3TdPXry5PRAaKzCGBuBx57FGzVocbLEl3pUwRaSsFkYwPJxoaf9rHm5FMcExUWCvUy6nZX7PWiSx9TL3N5gup0la/CK7NFWW37fOhl+veRHi7CLAQCQRRkGxLA3E5H9ykUW05AnzsitxL53bvx/YxFT6PcyixV1W1xthqDjsaYMXVMujhP4v1bfH4koe89IMxCcLjR5g4/dZ+V93Bk9OsC0boNIaLPENENIvqBVrZJRN8koh+X76fLciKiPyOil4jo+0T0jimJnxyL8KbUo0aHRpAuCstM+zxo69OvHR2qFJJLtH4xOovPAnifVfYJAC8w89MAXii/A8D7ATxdvp4H8KlxyBTMDZ1cqh2KxZh++3qZ+pSqIQ/Z0Fh9xnchSdvpUXV0xWvburkUyo1xbY/NlvFbPIlDaGUWzPwtALes4mcBfK78/DkAH9TKP88Fvg3gFBE91okiwWLR5UlmP6FDbe39e5+npk/iiqVhKEKm09a2gVwSId1LaF5dclLokkrP9e9rDTnHzCoG+BqAc+XniwB+odV7uSwTCAT7HIMVnMzMRNSZnRPR8yi2KjgCR7aiwwDd9m57Tba1m+oJansp6mPFiK2LiDq1tx1ALZ63JexV+StiaPGte+hwI0VDKOrUl1TCNS9X/zpCUaeucTosf1/J4rraXpTvN8ryqwAua/UulWUNMPOnmfkKM19ZwZycn2IwLyeotj/CsmFf0OiyKBx8V6JGXMlE6LuSXwXwXPn5OQBf0cp/t7SK/AqAN7Ttyv7AWBroVtv4gD28zz1YjetieH2ZoK0XsPfQLtqHrKGL7j7QdQO2h6NBq7aXb1WcJs2yis4Iz1BX+LgVBGfQqL8q787mejQCyeyQdKAOX2+8wiTraN2GENEXALwHwFkiehnAJwH8MYAvEdFHAfwcwIfK6l8D8AEALwG4D+D34kk5YIi5WaaID+la3qeeT+nWRcEZO35sOwDe4wW9xw46xqr8Hhx3kS++wqus1Lc3AUWky4ksNEa1zYs4NlEV+YLdOvwFW5kFM3/Ec6mR2oqLtFsfix9eIBDsF4gH50GC/TScUgk6hdejDl0Zao8VGt8pEXTsK2brYyin9e2ER7nbaK8rPwfoHLoecOQIl4/Fwdf+zAPLrPxbZtpCmJei2Tt+5K2xj9Z3qCJUmEVf6H/mruY/nzfhMvzxYsyTdnlf2kNt2pSktmejUkB2GcepBHaYXENgR5Yrva9ATkwjZ2bP0HnvaWguUl0ZtTpAmEVfaH/mTnkvfDfBUCuMR5w2TuFy3DQ0m4Fm2m60j+K0L+2eNo2Tw0JbC8Nq0PF804CycnbpYusNrOh0p7VjOD0stbIqW5ZV3gWNsQN9pG9+vHP/OkRnMQLmFsoeA2uv3Bbmznt7w8YYC5olIn/woL5J86ybLsbpNEVhJu1Adu2Gs1xvV61tm+u2y7pitxliIo5E/ov/17mNDpEsBAJBFESyGAN9XJZ9Gvi+T22fK/VYlgvbXXuo67avH/WuDv4JWSvsJ3LIdTrUl4Nu3tttp72kgWYzLVGuTQ9MmuzjBPPSx0I7DrELiuMK9WMW/dYR3t1r0NAFwizmjaFOU337H7PfTo5SPfpsUx57x/c4TXXpS48tCYnrmsencbP6nLIcjlQVX2hz2gqg4WzVJQK2I4RZHHRMxTymxFDpakh/Vd2IbNhdro/ZV28pdFiGb2EWi4QtTi/Dje3bVsQq4ELOUkO3LmOYlkNzaru5fb9R7FmnTnryZt0QdEVtkjque/qrHLLsOYeH0yEKToFAEAWRLGwMVTTG9O3r36dEHHOMvn0Z5R1P/u4zVp918Lkzh2h1uWp3pJPSFLwXkBAcUkXtTJUaxxe26jet9bAVnE6Fp/55gLu3MAuFkC1+KizDtiOEUPTlFGMBw7djbYzCfhiE/B1CegKjXm5+bktKAzScqaK9K+21seZX9WNvR0aAMAsF+08wleORQttTrM3VeWqrihpnSLsxvDq79mHfJN4sVh6rR2hdPYyk9UZve5oPeNoDugkW7ToLvawjRGdhgVZXQaurI3dKzZeFxHYZHxJvMVGcSbK+Xrg4A0iOH6/ek+PH4/7sMXS54jVaaLLdspOjRzG7+BhmFx9DevJE2U9S0W60P2aldPStnzOOpCirxqjGOWLVbW5NkmNHQQkhPX2yOKbShr198CA5fbqsQmasid7WToajJ7/pAJEsFMqn9SSu2y7R1UK+s+NvtyTQXcfze/eN904nlI/IyPJta90oQf5gG/zKtZKs+onbqAuN/iE03LlTf+Ec+YPt1jb84AE4Z+RvbHliS3L3Z3vs198oq3j6GHEbIpKFQCCIgkgWOro88dp8JHx6BZ893efuq/pxKdhcYxr5JjN/e9c8FB0hnwEfYtyV21yhq3JHVmpD3+OmhVZm4N09I2y72M/XIeEGeeVp5bUlgyyLQYA2bb60tgYupQm1FeCsoAcAUFknUiBNy6EIlCRAngNZDihriE+ypaSkP6vWghICra6AH+6CkpouzpS1JTXal+QWJ7Qr5PH/eWEWOrpE/7U58HgVZSotvH29Jbw61huwa5h2dHvrBraVZUZZi/KVqFnXdocOeVLqqfXV2EDFKHxh24pp6OUG89Ddru18m4pmnS7V7OGuNUZW9F3GYlQ3OVDlx9Up5JxB3KbwLmnVFatZBjzcLRlIMT6l1rwqxpoF5hwH2YZYmFTBqaA86bRXpaiz2/n6WwB0BWe6sVGUKQWnDp8icyzFq6XMrIsLRpGsH8Hs8gXMLl+wFJxH7J6aCs4eSE6Y81d9VkpHi2ad7uTkCTcNMQpOSpBsnirGSVNTYpjgCIT9zyxG+fPVEY/J8WNIjh9z9z3mTapHH6YpkhMb4/U9JvQb88wmkjObxZdL54s/6yNnkDxyxp31yWtZ6JcVykVbsnnavCkBJGc3cePXL+HGr19C/uYLZVVCcmKjcVMlm6eG03F20/ga6pNzLiSJkyeKLcPl80hOnWzUs7dSPmRPnCsecHoSo3LLYke4DsX+ZxYCgWAu2P86i5HNixwye3UNeorULXDO4O12c1srXDqXwdGOGp26ifDm60VZaXr0ppZTaGzDBj6nyj747r1q7Mpleusuznx/CwCQ3ryDvZI+vne/6Tmpm1NjJElHGT00c1/w1l2LVE15bI2bbN0H32+ab3U6DZqt/1V6Zxu540yQofk2XSBeAlv+Cdrkd1HjGJL9Da81xLKiuD6P0b/dV2z/vgjKWISiThtlDqWobb3R+2116HJbcox4CZ0+FbXZNZW+RZeew1S/SSvmpcV+2NYwlYdTbY28hwG5rCGz5rO+wTjVdztmpMSL+Texld+M2qPsf8libEzh7u3q0zAjdtxP9nH3HmoNadAQCCaLXUPXCV8u609XOtSeHaVEkWWaSbRFwtFN4Q2G5XcLN9yty7Eq64v+GQ5mQEmUy7htzamYkGMNnBYh1+8l1pAeKP8Yydpa0/W6D2xTZ8uTseGKPNTVW1PaRrXRoei1/kiVNUSzLCRHjxaa/bZthafPIO0R9CdH1iqFqbpxkvUjSB85W7yUsppzzM6fM+kBius6bfq6uWjW66n/zKmT9c0Y6e6dHj9WuXvPLpxvKGmdsJkr54W7N+e14jTRzdLmVneou7dsQ2y0OVsN7dMuC7bz+C6MRVcM9LH0eYS2K/bN0eYI1peu0GUl1udsZAhviPsx/iFtsNeiSwi/J2xc983w0mY74QHhcR19vMgvYItvRT2ZRLIQCARREJ2FjalD09vG8eVJiGk7BXyeoy59AwDDOzOmzyF0BaQLp6KQuV+C21ZabKVnhz7VOpL2PUaH0WesgRBmMRX6WkNC/bnadaEnpk2f+JghdWNjamLG84n/apvgcg4D6jZ9+mc2twKuDFnaNsO2UhTItXKPsK9bbpQ1JE2jmUq1rRmQ5Uy2IYChWKsUdr56A/s3y2pPx/TUKVQxIz4LQVuZbyxVf5COIDFgVmotAAAW50lEQVRyV6QbG8X75mmkm6fdCjNfSLqrrk8p6zO5ajRVCs40rcpmj1/C7PFLSB99pKqraNbHnj12rtm/D56bLH3qCYM2NY7yFqU0bSgvZ4+eBa3MMHv8orl+LquFRxHJOSN9y5OglVljHP1dKX4pLZimTleXhL2i4BT0Q1s0a1vbrm30dn3RJsH1vRfmEavjUrh3HVcUnAKBYB4QncVhQRedRcwTtqvzlKutayzX09IeK6QPausv5NXaR0LoLB158pm09VeZSR1blBgdBCWFErWhc2lvqiDMoi/6+GP4XLHt/obSpP6QuZb8pk1pGBrXpXOotPiBOXWh2e7bruNThBr6DcfNpNMW8TsZSsOQ74SWvMd73qhP8QkYka/GUQChU+19rux7EXSyohNW8hv/cDaEWYyBaFfqCKvHGAhls45Rnjb6s280j9m0DxoOX0PiUgJtI9ddxWq0OjvZ3pGRdZ1tHK7c0Wg1U2sZtMox+waZHXydxdg3p6O/9Mymo+IcaGnrO0kxu3SxCDjSrQC69WdjA8lGSy4N3UpRWXFGmothBSnoK2heAc1W6vJYj1cfOilgE9x67p11IiRlSbDqzM6fc1o6mpaeJl3KSlFZKmLcvVVbPSdHm8u2ZmV55d+9yxira44LsYaMgXm6X8fQ0EXj79q3z9OV3FnuEN9j3N3bdBYxc1eXVler3JnObYlOZxdpaKjOQpd67PSCLeMmqyvIrXD6F7NviDVEIBCMC9FZHBS43LJjRPdFS0QuzNGF2UvCrqZojEliPE/0HJf39gbRLJJFX7i8JIe069ufq48ufcXW9XlVdh1vLDT0KI7vDUtLvN6jVQ+hlwUS6rZes8PGQ3BZQ2LodNHbI0RdJIu+8AVYKcTs/YeYS139h0yZ0bEZDvNjbKxGW1yHLfF0jVNou/l9/XUpVxmsHAFnDRNpaT6mtD6bRLc+6CejNxSSeqYse06ONXRl0vIqOa3kP6puFRtijxcJYRZTwXfTeKM4OzKMmP5jyhv1PGZRF61daHbOtaMJtlUJ6+iPyK0kBTqL5L6Ud+4IV/N8jjp/hkdZ2pJTw5XbIhQYZp/1VJw5IpmyBALBHCCSRV8sswenPkYbbYv24PSNEevaPbIHp2GeDDp5qe1ENj8PThcZnT04660IJdTJg1MkixEwSs7OKUDqpDO/EtB5otiCYdAMzF95CmB27pGmAtJZZ/609VUop5fqA5f6HDokkkVfaE+ofGcnUNHdptO1GHgckvIHD4Jj5eoskFAMSWOv35IbMha2HqOkwaDZ5SLv1fsEDmV20er8Xjxqs1dfs67ZyXIz7F27Xj7ZLWlA0eGih5WjV7P7WFTKzr098K51kLJTWVEgu3qtLGpZJw8OL7Owxe8ym5I6wzPb2mrX7uvtfdeNMl1Dnhki4uz8OWSv3ap/fD0JrH7D+G6estwQb/WzMnyWC886uOhWxzrm9x4gOXEc2e03MLtwHgCQXX/VOKC3sTZ6vy7xXInGKdXxGQBoNqvnUWaLUklcOGekJ09UDI/W1sAPd4uzR8sjBenhLrJfXC2anzqJ7Nbr9biUIH3qCWQv/bSeaiCQjFLtgGPthn3421ew9sL3qnrJqZPIbt4qMo+j/B2UVaI8WZ0uXwBeu4XsqYuYXb2JfOtOubb3m9sgqjOX895uTcPKKvZ+7e2Y/Y8fmvQ/fFi31/4PRARwap43sh0vYYi791TwMRMXE3HdtHp9H7Pw7eX1ftvosbGoQ4Zi+m0TvT39VQxgqLu2J63e4EOG9Lqep75hOmXFeFYb9Bhj6f2PcMiQ6CwEAkEUDu82xIZPLB+CtqCm0JPS1iG49veuNr5+QuPo/ccmUrG3FH2kEV0P0MUaYo+vtiyJ5hxlDMNuC4crFL2NXhcoMZ2lEmo4W9UShL3titMhuMLKOctAKzPDNd0eu5IyOK+uGcrNTPws+oHIPJGs7WZu09bb1geg1rBbLtPqpK/gGAu0DoASI5mx0u0kx44iOXbUshzMgdZyvGT9iLamSUXT7PIFzC5fQHryRE2/XrdEdWKZ3q/+3jI+UJ5IVhUTyDpdzmV5SI6tAwkhOXWyuX72+IHtWnr6lJmAt6MLdxe06iyI6DMA/jWAG8z89rLsDwH8GwCvltX+AzN/rbz2BwA+iuJQx3/LzH/VRsSB1VmEdApd9BB9+rf7iu1/6M3dRWfhqm/Py+Um7kNXd++2azF1mes0/VFdmG7Y5Zd2CU2/rimjXVKMb1xXvRfzb2ArjwtRj9mGfBbAfwLweav8T5n5PxoEEb0VwIcBvA3ABQB/TUS/xNxm01oA7JsnZJ5ra9/ZcQgAcvdntVR6Wx9jcc3BeLIEXIh9267QDRcDzpp9BvtyKR1tpyLlABamQYnkrid5I3aj7Nvp1FQ3MusmVFsitd8rObJWWCCM8biyfCDLCqtEzkBJWzLTlJB7e5XVgnfdkaG1NSSv1pfStBhj1zbdOrZXCYGIm9fy+IdD6z+Amb8F4FZkf88C+CIz7zDzTwG8BOCd0dQIBIKlxZANzseJ6PtE9BkiOl2WXQTwC63Oy2XZ8sHlgDS2GVlXTrrGUgfKxDhruZSdzn7zbv02ygMiuX4AjuswHN0vJDi2RaOhvLX60Odhj2mPn2UNqUKdLu4OonLMwdVvWRYKJFPjGKJ+ltXZtnb3an+LnMFZDubiHUBV7lt/zjLTb4bLoxjzvLqmrnPO9fdyjkpiqdYi5j9ioS+z+BSApwA8A+AVAH/StQMiep6IvktE391FpAfkmLBdZmPs+Dp8lgp7DHss9SOpLYOu7HSK/wEFp2sOdtsYpzJDR+D5S7huUl+uSZc7sq2w0+fus+I05qspAT2WDNeNq0T45hiOMp0Z2tX1PJw6oyktDA19RJoCpY+HOjUMCdWv8sY1bmDP+pt5N4u1oTQFM1snjBVWD6M+gGR1pbKEGEytw3++l+mUma9XkyD6cwD/vfx6FcBlreqlsszVx6cBfBooFJx96JgEUzipefUiuk5hgCPUouDNIOVYwxhmM5iGtFkWCOYqiib86+l92+OMNW5AGtExhvNlr1+LiB7Tvv4OgB+Un78K4MNEtEZEbwLwNIC/G0binOB7Wvvq9jUPkpYpOpQpqc+NZEgr2lO+tU1dp3oKuyQB9dWm35YUnOP4+/PWc323y/WxbROibQa1+moEVDnn0/JCoVhV343M2eVLlyhoNiteaVJIG7NZUb8s94KSog99DgkZYzvXVdGlhQLoa9TF9tUqWRDRFwC8B8BZInoZwCcBvIeIngHAAH4G4PcBgJl/SERfAvAPAPYAfGwpLSECgaAzWpkFM3/EUfwXgfp/BOCPhhC1SCSlQ01+/75/z99Fv2HVc9q7iZCeOI787r1aolR6jTnDJ5ZTQqC1wiGLd3aQbmwgu3sP6enCISl/Y6u5D+4i+kY6ISla1FjJsaPgMkqViMAAkqNHQaUzFm/vIL99G0DhgJWpKNtyrrNHz2Lv+g1VUMWRFGZSR44K5S2qTJ05QJcvgP/Pz6p6ybF1ZFt3K/MoqzMCc64UnsmZTeRbd5CcewS8dQf8YLu5HraXam6tS86gN18E/+T/1oFqaWKagtVcuTTbZqjMtwVt8RB3bwv5tqZsHdvlW0VNKnu9prPI794z21FSHz/YAUYQUV+ZznOj5uUfmtIU2d17AOfI39gy28VYWQI6C5e7cmge/OCBpsgs+svv3wfsm0+VW8huv+7vPBavmZ4FuT22UmYCgKJx604RUXvzNvKdneYWpLFeHseva69VDKjof2a2t6JOuXzvg8Pr7q1bAbTFq9yXrfJBUHoBK9JQ3+cnp0+bbWIkC4eJ0rAE9DGdBpCePFG5T6ePnAEoQXr+HNLz54oKunUjpANS87ZvCN0yoM3HrqMjOXmi1hHkeV32treA3vYWpJcv1FLIyRONfX362Lno+fukruypi4aFITlxwqygWzvy4pWc3QSyDPkvPY709KmwVYoSt/mXc+y+/cnK6lI4fll1lEk258JUq97LVxfZQiQLwNxW7O6a5UP7tYv0H12/Kba33X/GNvNsc4CuVLa35+IsTuWlyFkGvv+gKL97t6yi+US4zLnGli53X9fH1+s6GGJF1/ZO/T0rmA0/3EVys5B4+H6dH4LW14Fbt7X+c/Cdu82+2XH2qCMUXGF29SaUDyVnGXh7u+hDS4pT1S/LeOsO8p0dpC+/CqwfAd9UdDlMt9VDRpmNuepz9ac3kGmSBVMCUzLT+lHVjOS/iMbhZRaefbWR9aotYjN2jOp7qT135BbI790vRG4ms46dX6LVDV03FfbYh7j0BaWWX4nXe+99BrO/LZK9qO1TtV0wXM6tSE/nejjcvXWpyuHuXW1VKDFF/oRATOAHD5Bp2baUHiK7dl2zjBT95Fsms1CRq43tjxW7UftUlFsKffu3vVNZZ4pl4OqmVdsNfrANms2Qb90B37yNr/+8MBq+7/ErBjPUxzfWuKTh/tsvYO3a9bpeuQYNustryPeMrQn2RnT3FggEAgCSKSuIIZJF36hTH3yRmGNjDD2N7WUZdCHvYjGZmLaY4EFXHV92sRZv03rc3Jnt230eSVNhHg0HjS/mfx19MPLh3YZMDa9VgMOfY26IKRm8K6x9HmPNG32c3rrG04TiWBpVPXoZfWyXB7C1PZoSsg2xYSeqGbtPu8x+GXV83osT38TeeA2PV6TPM3Ks9QvBE/PhSwbj9Nocm4aYPgNepQDMOJSW/pxet2009oBIFjb0p0c+kvOpz7GrtZ1n/KmfyN6ANMeTsmHO42ZWcTvnx5jMzhsh6qneMw1+JxpinvL2+imLh1q6vQ5SScycRpA8RLIQCARREGZho2+AWGyfdllwG+ILypqjG7hvLaJEbTvEPCJIrys6bkOi2g+lYcA2xNlH2zbEDpybCLINseFTQHaFLna7lIYx1pCQktSXx8LXT2y8Ruy5IV0tHK5tSJczSmKUi1r8RsNHouHshdqaELk98p29UegZVKwI105g2lkgRqRuRbd2oJFezmxuQTmr/TP0LOKpNqY+14qm+pqivRGbNHU+i0OPWNNlTPKZMdEpVH5C82tozCm798SRVEcE+BiTrtDukAvDqOdqV73XDmVVEFeubuq8cgIDYDhdOcdReTS1/nUvzSrVv31Nc9YyFLwdVBnCLPogSjkZYTrt2mdbm5DEEU1Ht1Rr0XD22VHp5nQd1y5rp3VVIDIVrkYDh2u567rev4usvV1Ped787DF1VkzOs/bFcZdW3MzebpNRVX1ZtHq8QueRVm9/Yqon2wJCyZ0WC1WuXj5diAt9wsqHoq9DVheGq6+H75prOJ8ewOqv2l7o5Xa/xudmMFzXuJ90Y6M6tyV+G5ebEkWXtiUOF7MQCAS9cbi2IT5Fo11ml3fpN7Z/u71d3/ZPCClD9SeZ65qr3Bbl1WfdhbjtyePaq/u2MW2nqLeBudW9uXKRdjg6uUK8vQcmw73lcCk4eW+vOKDY0U4/zLiSQCqdRb0t0I8U9NGjJB3e260S+NDqqj8Hpx34NpsVtKbWGnK8VCySBVDcOOUf0RDxfKZMVV/9eUN/YsM0apn01CtJMTt/DjRb0dol3bc3SZ2Dsv5ztsQP6PNw0l/SPFtBemazeP2zpwt6E8LsicuYPXEZNFupxdw2k7BnHDWWfrM3/txlmfLETM9s1nNeWyvofOQMcOWtwJW3Iv0nby67J6RnzxpbC84Z6VueNOc6W6nmq/9Gdt5Rmq1Uv9fer7292l7QygyzR88W9K3MQCszJKsrFZNQtCZveQLJ8WPIfvWfY3bhPHZ+85ex85u/bIxhvPR1UsgZP/6vb6vzes5mBQPRoTKMM1fXaHW1enXB4Q0ks5/U1R6//DFUlqq+AVxtN4jPJq68Rm0pR6dXPaVDEo2qa5d3NZ1q0oPxpJytmMo2PfipLV5BhVtHZqau6LaYWmMPTkllHlQ3AquzO8p5GOHfVCTNtU8T88IVFMcMWlurzwfJuTZT2pKFHsuRUH1SmZ6PQju+QEkpvlR/BVObGX1UOTRsWtPUOEBZ4cX8m9jKb0ogWS+MFSE5JeYQNOQethns5DoqMIa+MVLw6+dgAKWZUKWgszNG6YxCx5RHAYQQGtdKvtO6VlO4sDsg2xCBQBCFwytZ2Mo9W5Fo17Hh2sb4xtH79Inorm1JTJ4LmyY7U1bb1qlte+LIxVAp+uwnoM+fQR9H9emlx6M01drpikkj/R0lIGXJdKS0c+aICP0OPgct/TsXW4y8FPFdkla1BTHKkiK5bp6DKdEUn3vNscvfwClhJIm5jSq3G5UzlqKz3AoZylagk2R1eJmFDZdrdkz9mDaGhcMVJckY5UQyVz+xtAXreByIHNe6+U64dADtEZzGDa/rTfSM6Q7m67JwNPNGBHJTeBgJP3xouVdnRh1ju6bKdIetnM1UeB64PFQbp7fbp8hr61GdhWqsg7h7t2NM02nsWH2vLyMazkrqZorIPNU34Mm+WV0m0gyVArWopuk1HMyp7aiBqLq+bGAVfU1zbjWHSNQu3NZZJo16GrPU+y/PDHGeWxOJw8ssfJjS1TnGz2K/wJNHopOkMlaUZEVLfdZpIzu3UU8vGuH3XpDCOTj+BDQdXgWn7ZJrmE8j3aP7hLLHhCT3hTO7VYRUE+sH4ftsZNDqsBZd/9C6q7T+5DTGb7poNyI7NbjMr766jehOVafUoSgpxu6TEjJpV1DnjUZkuvKdGwIf/TY0Ccs4j7XDWQCHl1kIBIJOOLzbkC7u2K62bQpO9eRruF/n2jXFq/WnZfQGum4XEwavae+dc6iqUS3Ct1ktXGX6nJmb17S23gzWsWM6v2dV3/bY9pajoQfQfxevFaj84nAd18urU9QB8C4jWV0pvCjLtWl1hrR0DtVJ7JqEQbNZ0Y9u3VAOaJZbuXI+sy0z1EGiPfiSRUhP4Arxju1PE99n1fF9lhbaFYVY3bRci6YxoeR6H2yJpMr93OEmnD71pBG7YM9BP5IQQGUSDTEKr1htz9l7LW/evJqrd/rUk7U7cjUXx5gBGvVjHDnLTLNu+arnWtOrbvpX/v2vIlldQbJauLHr5mJwkbp/9sRl0MoqqAyDZ9sTs3xRQsgf7oJ398BZDs7Km51qhgLFXCwzsfG7aB6dlKZVrAfv7lUvZfWovqu1fvgQ//sv/kXxXTvukLsoWQ+tu/fU8Pk3tGXK6uNO3kWB2tXduytCUo5Np8+K4Os3xoXeZ5WobkKNPttt3iWJAW49id59msKlKLUtMi7Emm511/FGWcvYVV3NlKvqfHvvG9Hu3gdfsohF1zyRfRScymnKJ8IbisOO1hH9BuzSlz3fQDxH9dFOU9+inItCTOCUXddq1wjQa+uLzcN9qrlppldvW6qDy/QT0A0Fp6KrVCxW5ltKgDKug1Zm0IPOfPBZbexgMJ2BGArXUqLgnOuxKIEoOAUCweg4vArOw45F5OA8QPBtK8aqH+ho0DaRlJIUKPUl4sHZDnsP3xbj4WobrFNaK1yKPtWHbqHwuU37kt/Yf5qKfo87eZXJOmx9MPbfHmVitW92xnF4+tetN4Y1xOq/Ma+I+AwdjliPyorhsGAUW4N626Dm7syYrVlD9Ouc5Q2dgm0NUVsM3RrCWa3oJdIU4B69SHUKuoIr1sPeWinLyepq4Rqu958nFT0xWAoFJxG9CuAegNcWTcuccRYy58OAZZ7zE8z8SEzFpWAWAEBE32XmK4umY56QOR8OHJQ5i4JTIBBEQZiFQCCIwjIxi08vmoAFQOZ8OHAg5rw0OguBQLDcWCbJQiAQLDGEWQgEgigIsxAIBFEQZiEQCKIgzEIgEETh/wOqx2MgoMJNJgAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.19513201713562 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1.0, 'kernel_type': 'untiln'} is: \n",
+      "[[5.4500000e+02 4.2000000e+01 4.0000000e+00 ... 2.0000000e+01\n",
+      "  2.0000000e+01 2.0000000e+01]\n",
+      " [4.2000000e+01 1.6000000e+03 4.0000000e+00 ... 2.0000000e+01\n",
+      "  2.0000000e+01 2.0000000e+01]\n",
+      " [4.0000000e+00 4.0000000e+00 5.4500000e+02 ... 5.6100000e+02\n",
+      "  5.6100000e+02 5.6100000e+02]\n",
+      " ...\n",
+      " [2.0000000e+01 2.0000000e+01 5.6100000e+02 ... 5.5201405e+07\n",
+      "  2.7070565e+07 3.7657900e+05]\n",
+      " [2.0000000e+01 2.0000000e+01 5.6100000e+02 ... 2.7070565e+07\n",
+      "  5.6227287e+07 8.7973800e+05]\n",
+      " [2.0000000e+01 2.0000000e+01 5.6100000e+02 ... 3.7657900e+05\n",
+      "  8.7973800e+05 8.0506750e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.253121852874756 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 10.0, 'kernel_type': 'untiln'} is: \n",
+      "[[8.55050000e+04 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 1.82399200e+06 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 8.55050000e+04 ... 8.55210000e+04\n",
+      "  8.55210000e+04 8.55210000e+04]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 8.55210000e+04 ... 1.45800903e+16\n",
+      "  1.04720467e+15 7.94346077e+09]\n",
+      " [2.00000000e+01 2.00000000e+01 8.55210000e+04 ... 1.04720467e+15\n",
+      "  1.46179765e+16 1.05982134e+11]\n",
+      " [2.00000000e+01 2.00000000e+01 8.55210000e+04 ... 7.94346077e+09\n",
+      "  1.05982134e+11 2.70394568e+12]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.4303662776947 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 100.0, 'kernel_type': 'untiln'} is: \n",
+      "[[6.59424650e+07 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 1.32861113e+10 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.59424650e+07 ... 6.59424810e+07\n",
+      "  6.59424810e+07 6.59424810e+07]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.59424810e+07 ... 9.76031932e+25\n",
+      "  7.28718337e+23 4.86537429e+15]\n",
+      " [2.00000000e+01 2.00000000e+01 6.59424810e+07 ... 7.28718337e+23\n",
+      "  9.76064507e+25 6.46947761e+17]\n",
+      " [2.00000000e+01 2.00000000e+01 6.59424810e+07 ... 4.86537429e+15\n",
+      "  6.46947761e+17 1.63044342e+19]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.31696319580078 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[6.41922241e+10 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 1.28480608e+14 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.41922241e+10 ... 6.41922241e+10\n",
+      "  6.41922241e+10 6.41922241e+10]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.41922241e+10 ... 9.37328139e+35\n",
+      "  7.02676137e+32 4.63309425e+21]\n",
+      " [2.00000000e+01 2.00000000e+01 6.41922241e+10 ... 7.02676137e+32\n",
+      "  9.37328460e+35 6.17559179e+24]\n",
+      " [2.00000000e+01 2.00000000e+01 6.41922241e+10 ... 4.63309425e+21\n",
+      "  6.17559179e+24 1.54524551e+26]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.34011912345886 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 10000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[6.40192022e+13 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 1.28048006e+18 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.40192022e+13 ... 6.40192022e+13\n",
+      "  6.40192022e+13 6.40192022e+13]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.40192022e+13 ... 9.33539995e+45\n",
+      "  7.00123103e+41 4.61050310e+27]\n",
+      " [2.00000000e+01 2.00000000e+01 6.40192022e+13 ... 7.00123103e+41\n",
+      "  9.33539998e+45 6.14714984e+31]\n",
+      " [2.00000000e+01 2.00000000e+01 6.40192022e+13 ... 4.61050310e+27\n",
+      "  6.14714984e+31 1.53692259e+33]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.06614923477173 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 100000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[6.40019200e+16 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 1.28004800e+22 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.40019200e+16 ... 6.40019200e+16\n",
+      "  6.40019200e+16 6.40019200e+16]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.40019200e+16 ... 9.33161991e+55\n",
+      "  6.99868305e+50 4.60825025e+33]\n",
+      " [2.00000000e+01 2.00000000e+01 6.40019200e+16 ... 6.99868305e+50\n",
+      "  9.33161991e+55 6.14431489e+38]\n",
+      " [2.00000000e+01 2.00000000e+01 6.40019200e+16 ... 4.60825025e+33\n",
+      "  6.14431489e+38 1.53609224e+40]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 48.97752380371094 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[6.40001920e+19 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 1.28000480e+26 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.40001920e+19 ... 6.40001920e+19\n",
+      "  6.40001920e+19 6.40001920e+19]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.40001920e+19 ... 9.33124199e+65\n",
+      "  6.99842830e+59 4.60802502e+39]\n",
+      " [2.00000000e+01 2.00000000e+01 6.40001920e+19 ... 6.99842830e+59\n",
+      "  9.33124199e+65 6.14403149e+45]\n",
+      " [2.00000000e+01 2.00000000e+01 6.40001920e+19 ... 4.60802502e+39\n",
+      "  6.14403149e+45 1.53600922e+47]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6518>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.30951905250549 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 10000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[6.40000192e+22 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 1.28000048e+30 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.40000192e+22 ... 6.40000192e+22\n",
+      "  6.40000192e+22 6.40000192e+22]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.40000192e+22 ... 9.33120420e+75\n",
+      "  6.99840283e+68 4.60800250e+45]\n",
+      " [2.00000000e+01 2.00000000e+01 6.40000192e+22 ... 6.99840283e+68\n",
+      "  9.33120420e+75 6.14400315e+52]\n",
+      " [2.00000000e+01 2.00000000e+01 6.40000192e+22 ... 4.60800250e+45\n",
+      "  6.14400315e+52 1.53600092e+54]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7c18>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.138402700424194 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 100000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[6.40000019e+25 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 1.28000005e+34 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.40000019e+25 ... 6.40000019e+25\n",
+      "  6.40000019e+25 6.40000019e+25]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.40000019e+25 ... 9.33120042e+85\n",
+      "  6.99840028e+77 4.60800025e+51]\n",
+      " [2.00000000e+01 2.00000000e+01 6.40000019e+25 ... 6.99840028e+77\n",
+      "  9.33120042e+85 6.14400031e+59]\n",
+      " [2.00000000e+01 2.00000000e+01 6.40000019e+25 ... 4.60800025e+51\n",
+      "  6.14400031e+59 1.53600009e+61]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAACjhJREFUeJzt3M+P3HUdx/HnS4o1Gow0aIOASkwvcHBDNuiBmBoSfl0KF4IXG0NSD/AHwAmPXoyJiZLUpKEeBHsh9NAIpBdOIDVpsBiJjRZpLa2KQaOx2vr2sN+GSe26b3Z25rs/no9kMzOf/c7u+9Ntn5nv7ExTVUjSSj4y9gCSNgZjIanFWEhqMRaSWoyFpBZjIall9FgkuS/JW0lOJnli7HlmJcmpJL9McjzJsWFtR5KXk/xmuLx+7DmnkeRAkvNJTkysXXWPWfL94ef+RpI7xpt89ZbZ87eTnBl+1seTPDDxuSeHPb+V5N5xpl6dUWOR5BrgB8D9wG3A15PcNuZMM/a1qlqoqsXh9hPA0araBRwdbm9kzwD3XbG23B7vB3YNH/uAp+c041p7hv/dM8D3hp/1QlUdARj+bj8C3D7c54fDv4ENYexHFncCJ6vqt1X1L+A5YM/IM83THuDgcP0g8OCIs0ytql4B3rtiebk97gF+XEteBT6V5Mb5TLp2ltnzcvYAz1XVhar6HXCSpX8DG8LYsbgJeGfi9ulhbTMq4KUkv0iyb1jbWVVnh+vvAjvHGW2mltvjZv/ZPz6cXh2YOL3c0HseOxZbyV1VdQdLD78fS/LVyU/W0uvuN/Vr77fCHgdPA18EFoCzwHfHHWdtjB2LM8AtE7dvHtY2nao6M1yeB55n6eHnucsPvYfL8+NNODPL7XHT/uyr6lxVXaqq/wA/4oNTjQ2957Fj8TqwK8mtST7K0pM/h0eeac0l+USS6y5fB+4BTrC0173DYXuBF8aZcKaW2+Nh4BvDb0W+Arw/cbqyoV3x3MtDLP2sYWnPjyTZnuRWlp7c/fm851utbWN+86q6mORx4EXgGuBAVb055kwzshN4Pgks/Zn/pKp+luR14FCSR4G3gYdHnHFqSZ4FdgM3JDkNPAV8h6vv8QjwAEtP8v0D+ObcB14Dy+x5d5IFlk65TgHfAqiqN5McAn4FXAQeq6pLY8y9GvEt6pI6xj4NkbRBGAtJLcZCUouxkNRiLCS1zCwWH/bdpBMvgd4y3PPWsFn2PJNYrPLdpJviD/RDcs9bw6bY86weWWz1d5NKm86sXsF5tXfXfXm5gz+a7fUxPs4ns2NLvULMPW8N63nP/+Tv/KsupHPsaC/3Hs7j9sHSH+ZdH/xnQpLm5LU62j52VqchK767rqr2V9ViVS1ey/YZjSFprcwqFlvi3aTSVjKT05At9G5SacuY2XMWw39SemRWX1/SfPkKTkktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLVsm+bOSU4BfwMuARerajHJDuCnwBeAU8DDVfWX6caUNLa1eGTxtapaqKrF4fYTwNGq2gUcHW5L2uBmcRqyBzg4XD8IPDiD7yFpzqaNRQEvJflFkn3D2s6qOjtcfxfYOeX3kLQOTPWcBXBXVZ1J8hng5SS/nvxkVVWSutodh7jsA/gYH59yDEmzNtUji6o6M1yeB54H7gTOJbkRYLg8v8x991fVYlUtXsv2acaQNAerjkWSTyS57vJ14B7gBHAY2Dscthd4YdohJY1vmtOQncDzSS5/nZ9U1c+SvA4cSvIo8Dbw8PRjShrbqmNRVb8FvnSV9T8Dd08zlKT1x1dwSmoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqWXFWCQ5kOR8khMTazuSvJzkN8Pl9cN6knw/yckkbyS5Y5bDS5qfziOLZ4D7rlh7AjhaVbuAo8NtgPuBXcPHPuDptRlT0thWjEVVvQK8d8XyHuDgcP0g8ODE+o9ryavAp5LcuFbDShrPap+z2FlVZ4fr7wI7h+s3Ae9MHHd6WJO0wU39BGdVFVAf9n5J9iU5luTYv7kw7RiSZmy1sTh3+fRiuDw/rJ8Bbpk47uZh7X9U1f6qWqyqxWvZvsoxJM3LamNxGNg7XN8LvDCx/o3htyJfAd6fOF2RtIFtW+mAJM8Cu4EbkpwGngK+AxxK8ijwNvDwcPgR4AHgJPAP4JszmFnSCFaMRVV9fZlP3X2VYwt4bNqhJK0/voJTUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLSvGIsmBJOeTnJhY+3aSM0mODx8PTHzuySQnk7yV5N5ZDS5pvjqPLJ4B7rvK+veqamH4OAKQ5DbgEeD24T4/THLNWg0raTwrxqKqXgHea369PcBzVXWhqn4HnATunGI+SevENM9ZPJ7kjeE05fph7SbgnYljTg9rkja41cbiaeCLwAJwFvjuh/0CSfYlOZbk2L+5sMoxJM3LqmJRVeeq6lJV/Qf4ER+capwBbpk49OZh7WpfY39VLVbV4rVsX80YkuZoVbFIcuPEzYeAy78pOQw8kmR7kluBXcDPpxtR0nqwbaUDkjwL7AZuSHIaeArYnWQBKOAU8C2AqnozySHgV8BF4LGqujSb0SXNU6pq7Bn4ZHbUl3P32GNIW85rdZS/1nvpHOsrOCW1GAtJLcZCUouxkNaBF/9wnBf/cHzsMf4vYyGpZcVfnUqavXs/uzD2CCvykYWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFtIGtu0Ln5vb9zIW0gZ28dTv5/a9jIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGpJVY09A0n+CPwd+NPYs8zZDbjnrWA97/nzVfXpzoHrIhYASY5V1eLYc8yTe94aNsuePQ2R1GIsJLWsp1jsH3uAEbjnrWFT7HndPGchaX1bT48sJK1jxkJSi7GQ1GIsJLUYC0kt/wUTFWjNk6oV2wAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.21524238586426 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[6.40000002e+28 4.20000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.20000000e+01 1.28000000e+38 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.40000002e+28 ... 6.40000002e+28\n",
+      "  6.40000002e+28 6.40000002e+28]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.40000002e+28 ... 9.33120004e+95\n",
+      "  6.99840003e+86 4.60800003e+57]\n",
+      " [2.00000000e+01 2.00000000e+01 6.40000002e+28 ... 6.99840003e+86\n",
+      "  9.33120004e+95 6.14400003e+66]\n",
+      " [2.00000000e+01 2.00000000e+01 6.40000002e+28 ... 4.60800003e+57\n",
+      "  6.14400003e+66 1.53600001e+68]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.17125153541565 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 10000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[6.4000e+031 4.2000e+001 4.0000e+000 ... 2.0000e+001 2.0000e+001\n",
+      "  2.0000e+001]\n",
+      " [4.2000e+001 1.2800e+042 4.0000e+000 ... 2.0000e+001 2.0000e+001\n",
+      "  2.0000e+001]\n",
+      " [4.0000e+000 4.0000e+000 6.4000e+031 ... 6.4000e+031 6.4000e+031\n",
+      "  6.4000e+031]\n",
+      " ...\n",
+      " [2.0000e+001 2.0000e+001 6.4000e+031 ... 9.3312e+105 6.9984e+095\n",
+      "  4.6080e+063]\n",
+      " [2.0000e+001 2.0000e+001 6.4000e+031 ... 6.9984e+095 9.3312e+105\n",
+      "  6.1440e+073]\n",
+      " [2.0000e+001 2.0000e+001 6.4000e+031 ... 4.6080e+063 6.1440e+073\n",
+      "  1.5360e+075]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAACjhJREFUeJzt3M+P3HUdx/HnS4o1Gow0aIOASkwvcHBDNuiBmBoSfl0KF4IXG0NSD/AHwAmPXoyJiZLUpKEeBHsh9NAIpBdOIDVpsBiJjRZpLa2KQaOx2vr2sN+GSe26b3Z25rs/no9kMzOf/c7u+9Ntn5nv7ExTVUjSSj4y9gCSNgZjIanFWEhqMRaSWoyFpBZjIall9FgkuS/JW0lOJnli7HlmJcmpJL9McjzJsWFtR5KXk/xmuLx+7DmnkeRAkvNJTkysXXWPWfL94ef+RpI7xpt89ZbZ87eTnBl+1seTPDDxuSeHPb+V5N5xpl6dUWOR5BrgB8D9wG3A15PcNuZMM/a1qlqoqsXh9hPA0araBRwdbm9kzwD3XbG23B7vB3YNH/uAp+c041p7hv/dM8D3hp/1QlUdARj+bj8C3D7c54fDv4ENYexHFncCJ6vqt1X1L+A5YM/IM83THuDgcP0g8OCIs0ytql4B3rtiebk97gF+XEteBT6V5Mb5TLp2ltnzcvYAz1XVhar6HXCSpX8DG8LYsbgJeGfi9ulhbTMq4KUkv0iyb1jbWVVnh+vvAjvHGW2mltvjZv/ZPz6cXh2YOL3c0HseOxZbyV1VdQdLD78fS/LVyU/W0uvuN/Vr77fCHgdPA18EFoCzwHfHHWdtjB2LM8AtE7dvHtY2nao6M1yeB55n6eHnucsPvYfL8+NNODPL7XHT/uyr6lxVXaqq/wA/4oNTjQ2957Fj8TqwK8mtST7K0pM/h0eeac0l+USS6y5fB+4BTrC0173DYXuBF8aZcKaW2+Nh4BvDb0W+Arw/cbqyoV3x3MtDLP2sYWnPjyTZnuRWlp7c/fm851utbWN+86q6mORx4EXgGuBAVb055kwzshN4Pgks/Zn/pKp+luR14FCSR4G3gYdHnHFqSZ4FdgM3JDkNPAV8h6vv8QjwAEtP8v0D+ObcB14Dy+x5d5IFlk65TgHfAqiqN5McAn4FXAQeq6pLY8y9GvEt6pI6xj4NkbRBGAtJLcZCUouxkNRiLCS1zCwWH/bdpBMvgd4y3PPWsFn2PJNYrPLdpJviD/RDcs9bw6bY86weWWz1d5NKm86sXsF5tXfXfXm5gz+a7fUxPs4ns2NLvULMPW8N63nP/+Tv/KsupHPsaC/3Hs7j9sHSH+ZdH/xnQpLm5LU62j52VqchK767rqr2V9ViVS1ey/YZjSFprcwqFlvi3aTSVjKT05At9G5SacuY2XMWw39SemRWX1/SfPkKTkktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLVsm+bOSU4BfwMuARerajHJDuCnwBeAU8DDVfWX6caUNLa1eGTxtapaqKrF4fYTwNGq2gUcHW5L2uBmcRqyBzg4XD8IPDiD7yFpzqaNRQEvJflFkn3D2s6qOjtcfxfYOeX3kLQOTPWcBXBXVZ1J8hng5SS/nvxkVVWSutodh7jsA/gYH59yDEmzNtUji6o6M1yeB54H7gTOJbkRYLg8v8x991fVYlUtXsv2acaQNAerjkWSTyS57vJ14B7gBHAY2Dscthd4YdohJY1vmtOQncDzSS5/nZ9U1c+SvA4cSvIo8Dbw8PRjShrbqmNRVb8FvnSV9T8Dd08zlKT1x1dwSmoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqWXFWCQ5kOR8khMTazuSvJzkN8Pl9cN6knw/yckkbyS5Y5bDS5qfziOLZ4D7rlh7AjhaVbuAo8NtgPuBXcPHPuDptRlT0thWjEVVvQK8d8XyHuDgcP0g8ODE+o9ryavAp5LcuFbDShrPap+z2FlVZ4fr7wI7h+s3Ae9MHHd6WJO0wU39BGdVFVAf9n5J9iU5luTYv7kw7RiSZmy1sTh3+fRiuDw/rJ8Bbpk47uZh7X9U1f6qWqyqxWvZvsoxJM3LamNxGNg7XN8LvDCx/o3htyJfAd6fOF2RtIFtW+mAJM8Cu4EbkpwGngK+AxxK8ijwNvDwcPgR4AHgJPAP4JszmFnSCFaMRVV9fZlP3X2VYwt4bNqhJK0/voJTUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLSvGIsmBJOeTnJhY+3aSM0mODx8PTHzuySQnk7yV5N5ZDS5pvjqPLJ4B7rvK+veqamH4OAKQ5DbgEeD24T4/THLNWg0raTwrxqKqXgHea369PcBzVXWhqn4HnATunGI+SevENM9ZPJ7kjeE05fph7SbgnYljTg9rkja41cbiaeCLwAJwFvjuh/0CSfYlOZbk2L+5sMoxJM3LqmJRVeeq6lJV/Qf4ER+capwBbpk49OZh7WpfY39VLVbV4rVsX80YkuZoVbFIcuPEzYeAy78pOQw8kmR7kluBXcDPpxtR0nqwbaUDkjwL7AZuSHIaeArYnWQBKOAU8C2AqnozySHgV8BF4LGqujSb0SXNU6pq7Bn4ZHbUl3P32GNIW85rdZS/1nvpHOsrOCW1GAtJLcZCUouxkNaBF/9wnBf/cHzsMf4vYyGpZcVfnUqavXs/uzD2CCvykYWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFtIGtu0Ln5vb9zIW0gZ28dTv5/a9jIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGpJVY09A0n+CPwd+NPYs8zZDbjnrWA97/nzVfXpzoHrIhYASY5V1eLYc8yTe94aNsuePQ2R1GIsJLWsp1jsH3uAEbjnrWFT7HndPGchaX1bT48sJK1jxkJSi7GQ1GIsJLUYC0kt/wUTFWjNk6oV2wAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.872535705566406 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-10, 'kernel_type': 'size'} is: \n",
+      "[[3.200e-29 1.600e-29 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.600e-29 3.200e-29 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 3.200e-29 ... 3.200e-29 3.200e-29 3.200e-29]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 3.200e-29 ... 3.232e-27 3.128e-27 3.200e-27]\n",
+      " [0.000e+00 0.000e+00 3.200e-29 ... 3.128e-27 3.030e-27 3.092e-27]\n",
+      " [0.000e+00 0.000e+00 3.200e-29 ... 3.200e-27 3.092e-27 3.184e-27]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6518>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.87499785423279 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-09, 'kernel_type': 'size'} is: \n",
+      "[[3.200e-26 1.600e-26 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.600e-26 3.200e-26 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 3.200e-26 ... 3.200e-26 3.200e-26 3.200e-26]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 3.200e-26 ... 3.232e-24 3.128e-24 3.200e-24]\n",
+      " [0.000e+00 0.000e+00 3.200e-26 ... 3.128e-24 3.030e-24 3.092e-24]\n",
+      " [0.000e+00 0.000e+00 3.200e-26 ... 3.200e-24 3.092e-24 3.184e-24]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.97593379020691 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-08, 'kernel_type': 'size'} is: \n",
+      "[[3.200e-23 1.600e-23 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.600e-23 3.200e-23 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 3.200e-23 ... 3.200e-23 3.200e-23 3.200e-23]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 3.200e-23 ... 3.232e-21 3.128e-21 3.200e-21]\n",
+      " [0.000e+00 0.000e+00 3.200e-23 ... 3.128e-21 3.030e-21 3.092e-21]\n",
+      " [0.000e+00 0.000e+00 3.200e-23 ... 3.200e-21 3.092e-21 3.184e-21]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98abac50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.796093702316284 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-07, 'kernel_type': 'size'} is: \n",
+      "[[3.200e-20 1.600e-20 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.600e-20 3.200e-20 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 3.200e-20 ... 3.200e-20 3.200e-20 3.200e-20]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 3.200e-20 ... 3.232e-18 3.128e-18 3.200e-18]\n",
+      " [0.000e+00 0.000e+00 3.200e-20 ... 3.128e-18 3.030e-18 3.092e-18]\n",
+      " [0.000e+00 0.000e+00 3.200e-20 ... 3.200e-18 3.092e-18 3.184e-18]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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94ief7SWS+SbAbXeieZlnzYc0IyKky/W+03oWCn6VHB2cRznKUa4ld0OzwD5MmGOS1fJAEhLHOF0d1fbLajdfZ7Us9qCbZAByMS96Oa5hwpuKSVE+CJyxkGZ2IBJnF4xtPzGtBgN1vkXZy8BkY37oh8QA1BSM5phoQKRYhpTt7GGY7KpvDExSBynZK8xg8XOzNeM/CNlUOpDd+dao22QSutigUPmAZmGPld+kusPHavJyNicOgan0XNa0AKvhWc2ovC9vOupV7sZiwfl/xs5UPgpF7U1AWjEKjgI26oFiegAowC1rZ1LbVny/picP+l0zUdvi02dTkFe+lzs5ER+HLgTjCGqb6sAr2ax+37lqfArc99N8kMUChNoHt1oi9UMBhik4Le06uOUC/uH9+rIVJ60BfQEVXxBjdbapOaPwZbVpkziDabWsWBDrF7K5EouFLF56HBAwaYzg9bo8GytusQD3xvcDwH/w2PhQss2ukS577xjF32EjVvNIEwBatAWnMLl3IyYtLTzS8xf1/NVSHJx5Q/IfPJZx0vdDF3MFf+nCB0h0IoO8+OykmgzqxG7GYlJMgGImEsSOJEIRUznO680e3J0B+G9+JNcezTvlHXi5qP4SYOLE1XNKu77xIdyur34TAPj2Vx6UVQdsEvWYnJNBRrPJKv9Q1UL0pewxs+15z4HIMcoqPwwTjz/HVIAwum8U0NQskawgCGMCu/xQLR+CgqP6ofhCJglanKTtc5Sidn+2S5boQsyayTCIj0bbnkFV1ASAHXizPcjvYKMUpG3DNDKhvBGHnNIJmESVALGBJ4lZjsADpr4Bs2iwhgiv4mzouoNtl71INqOJ1jk7xrtdXYjaZrpoZkdtdXBmv0gIwLMXExi4AK0iSH0sdjwm5EZUo1qqde26gxBslyNBcL6Gpi93wDpM+zRPgDPoYTo7rUA06PO6fs7Nl3KxsBGOCZ7CslopQk5xGCozxiTMNYuiMQwHNQt4P8n840E0C52EqrG4xeKVmgVmmkVh1lJPd46wUN4pCux914HatuI4gLrIWRwHUBxoZDAdjDoxxRlYzydi4GQFukKzUPMCTQtSs8j+PsaKEpxJGQ8dRwB0spqQ/ZSFZx5GZxYn4Emo97xCs5ijGZH7qykB0EmHqlnoMVqtZPKnlBcL1dwqrJz0+tkxDmbw+SncTLOg8c00C7y4qONs+3B+JtdQKHju7000C4GGNxXyzww8+7JFQ1RekXU6wV0YG+1KzeJAhumhzMqbahbo+zrhgIrH4JyxqHF8nYy3pVkAr8ZxaLtnIVIwi18movhptA0CEBrfmWYxnxQWyzH9ccJ80b0NzSJdrjP8m2XSzc28uYbgSCbmNty+ZvH8xb4fgtONNAu32YoZZTeUeH1/zTEacpSjHOVacqc0i1elqCvuwj1+NE0J1lV4thpT21aTIq+8/oNH2Xk6ID59NjmfI/Kqba4zX+EVyGN2dIWAcyc7gmI9xk8+y7+xmkXVEDhx9TMcyNQsWoUqN7F+X5CTExMi9/VQ8henuqv3/dR5p2bThx+Adx3Ss33sg5xg8A9We7gm+c0EiauBqIUpAaEOWpv5qWPjHWi5FBwEcBgDAUxRrXtf5oiZ3XVnx5x3cm2PqaOYdOePtR/5GdDjh0jf+2Sa3Dj3bxh5U/IbnGQz6P49sDq7v/N7Nya/Kf1+A7lTi8UXKnYyGMDUxNP+ptedq/X2mleFub5omZkg5a7OTV+W2QvL1vQAKslLSnglh8YtyJTBi2tINI3757wLUiEbClazVI+zmpXGrI1xgpa8VTFtoQMpENe6xKgmD8q1bhJRvVuLhY07z+RVuItDUnZYC7XN8f63j6vPeBTm93gXYhcsK3YRySFezdlQsVpIuVw/vN0i+iYya6u2qfgNrLyDRXiilXlnqAVi+b6I8lYcot2/DdHxGIap1nMDIe/AQwLSm3kf7tRiMYlmNG1VSYHi1IsvXwpxjca72xap66a1RDJ0m/t+kithTY/w0dfkuoo7OFlNkmz44lLwBONocBqCp6Cz0wn5CZ2dFo96eiG4kPD7flAiGwachRDASzGPaLOrsOhdB753JhPiibSRzs8EoNU00g/FSazXAqk24d8C5AkBOFnV8Vxv5OUfx5KxqbkRGt0ozNbPngMA3Ld+pEZkTL4Bgi+RC142cLtB2mvZroYRtOv3TUPFIqjzV3MmiEBbxafkFzh42a1VrV80oG4Av3gJ9+M/Kr8PEoWgyOUzAMSzBfxmEAdu2T0BOIC6CHiCv1CiG0a6dwJuPMKTCznUBOmPbgbzqEIbQNs85hqd+vwZdj/7b6J9uqtj5QiuGzGey7vn+gQmsWbiQrNOqXznhoTxVK63+L1LOH1nVGshQjpZIC0DwpPLMmbxj/4EuocNFs+G7EEG4sLB72pCHDcyEMkTXGS4XURa+vJ8+R9fvxrg0cF5lKMc5VpypzSLuXDiw3U9JmnYsaYhF2o8V2qJYDjMVl14I3JmZElSsiAVTlOTSE2YzKoMiDZE291eqJY32wz5NeZCSsVHwP1QYdFjFE2DDb2u7mpqOpnwGA+D2PC6U9sUbNv+rhNGKkMNqEjT4hhTzUC1E6V1y+2Fc5nXwuAZhjGn06faTgX42GxaEyamXV/vYVTqYrYV9X+GfO2Fwo/7Hu5yU9puUYx6PRqiaCG+4l3AwhdRnoMJh9J6V3AsAEDbXUVwZo2siPfCw6HvjWp62x0Wn23gLgytXvBAP6DZ5euaVH2v703jy3EaIlwnWohmkLKj6g9xDv5ZDxc86HJTxqz5fAMalvCXNUUgOAfqx6pZBJN1OkTRGlWzY5Zj15Q7vVhMKoVNvqD6MjgFI5kX5CZ2pHrhbRq5Sia/KY63G+SIEBGYHIBqSk3SzL2bfnaUVWbDkanp17M2kSIwb0ssyY0dFwuactmvYElmACBSBRjp5exv7LVu6t5RX4sjFF4dopq+koFOcK62ISXJUUliItSRjLVNhQv1hu1RmY0T+wwws6aQYkP0mAM0T2SCL3EOrO+MTTs/8E6zpuKb33NOZ2dPILsOHPJv3VDu9GIxkQJEmaI1yWfEXJjyOxQEpOWasPQE2bbnnfAu0molE1Mx+tvKT8BjhSS7xQJYLSU3APLM6fSkvhf6gM9Pp/Y7ADShMiKtt5VJadeDzzJXQ/Yp8LIV23TRgrq+7mR5Z6Dloiad6Q7VNOCTZe3jxVpeumEo/dXrkCJZG22DXCs9OgftlESo7t7s606YVg3cVnwW3NZXiIac4GfBdTrBz1YyHrlvIAJOVwV9WHgXFLFa/COt/C4x0gNhtuYmL6IJgK+TYDxv4dczfgzIBHK7EQgO7sWm9CndP0FqPYJqbWcn9drOTXZd9gReNHCbvrYBgIsRmx9YYbHQHBlC8g5+N2K4J9qC76IsYiw+BWDus2CMp/L7VeQKVtN3kQjx8RnSwqP5vC1jtvvmGXaPApZP6zOIrUPY1nYn9VkEghsZYTtiXOV3IDHS735ZEZyvktfEhm1yWFH/Felp0I9F5ki/lPJ/dfcjoglaE8jhshjLzq51LnkWySmq78wMqRDiaRiuaEOaUJUM+tJKIfSN4HktTKIp8UlKkssSY72vmgb6eRYZcWMyaFJV3dNkEaDRhBSjDX/Owsp2N7PmUWJpAXNpl2ZWso5dybYd5ZwYAb0vkSxczGBTDsH1CTQkwFN5PsQQkp6UwHPNIXI1ifK9CMiLBU8cnJSy9qAmixlj17OMGwBOBAfADQmuVzPDjJ++CiyOWTewnDu4Og7ZKWsXXeryQqzjgbrQ0Mh1/EiOIyu1OhCUCG5IoD7Bu2oO0uz1epXc3cXCESas2EazmGY77qv4Jc1czQv9rR2ZYldnNT94WSjUhtcMzpgAnydJCPK7bArodchVshVWUpQm5IlasyU5+Hr90fhYQpIdmhnOcDSSeuV9MtGC3AbHoDFfV/sUwiSjsLSLuarlOl5qyqimoYtG42tKtE58omr7AtJWImBM4KX6PNRvMBYtgVQPZjELSk2OPAaSlJf9LkazmCzQ6ofxHryo9j6iTLZk2hsXHhQT2Luyc+uC4IiQggMNyosZwY1DXAb48swpaxZUfTXaZ0/gNpSFsmgWzmFcOTRNjXLE1gGRixYBgomG5J2+lYMcGOyAuKR8XMokIDiA8tgEB248uHWT3I+4cBhXhLB15SVILQn2L98v5XFIDcE7AiUuERlKvJdF/yo5RkOOcpSjXEvuhmZBOVvSIAjVBNCq3BbibaHDSqnHXSdUeADQ94KpYBYKvAOAHp4R0/J2V52dyD4Nu5tDVPV4uQZtNuU8jlGiIcXLnv/97CmUj/MQDZxtEQPC6swJyHiICUkL0YQUB9ud9O8AYa91nCZbLOj5NEIxT0rS2q/+Ox9PB0ozHE0/SPsRDWGvtuVkWXdkHfeuF7+LXnIjfqL09Nke98UeYS8REgthr/+d/LqamhjeaJSBSEwvo+mBudQ5cTECD+7JdRPDDyPCZzWik54+q6bfAdj0pG35vrEfcP8fNTVKAsj7Mo5obTEkHQ8Tsat4jgH8KNPqaeTKuQkGJT15Bp+zZ3XMTvoBJzY7Vu+RcUYT8CBR4cpoTJqAW7++bnDp1rXPfNeiNPwHxJYmLFl2RKa4TXptKYBSAcwAv8hewzvwop3CeZ27WSkAvafNNFSn3xyBmcFAqqIjeBRgDleSGsrXsynfE9v2iyDsnWRJujp5bJQjU8uX9qYkJkATwMus6g/6XGZONB3v3e5mpQDOT6WtJZMyt0nfE+/El9OEajal7LzN/U3n4kim/M6kxpewJ1k+ixsQ9sYP79fQqcvmyravDuziW6oO9NQGMYW8h+sGDI+kXX4rACtuXDGPODg4dXIbwl5+cI7x/hJuO05MRxpTjoYw2Nexcm3zFSDsPUSrlwlsD9LqTZKSUl0UFJ14HVo9feicit+C8/VUaIzC8q0Pwl1/YNnS+s85G3QHtMlf2RladuBFW39nrsUxyeJ0WzLG6U44UuVoMP1A4gluRB22NMaau6A1PPqh4hcAmdRENw//DiYCVnJGjEOXBf3JzKCBSh/sgu8uMlYjca7v4Uok6E3D0dSPFZ2aCZBojFUztc9R67AMEZSS+EDGCJ8xGe4yv2/egbr9yM5ExgjXR7jelNjMTlAaZXGkVDWLt5U7sljcUOZRhMRgxKr+Kk8AX103ZAItJwaPOS8gOzMrXb35rWXyfk3dEKhZA0zMEDZENTZzkxMDKU5JeZyr5QsN/RyPt1y+cFKLw2ggxuTQXZaiqY2Rcu1TnSScoyXMk2rjFF25143KF+pmYIo2kasLB+V2CDlRbYNlwCINUadcMlALE2nfbX9n781VdUP8i3UFu2XtlIcBtJ26BIuJhOws19oi4whXIk25LclV2H3wwrVB07oh/uUl/JBrgdhExkNmiPbPgheBY/nCoxzlKF+83FnNgl6lpprCMuQ92I3iaLMUa6/xWRRVPtunahLYojmCCjXs0f765QuxWtbV/lAJQOuzYAaaKWFwsSu1iJIeZwZCuD2fxelJvV6q/hxxQhv8hGI6sg1ewsSu+jYKchOYZpLq98PqZj4LLTLkjB/FwL05J6GVxDegajvaT33ueYflJpQdU5zaN/dZpAdnoHUeXyJ5dv1g/Dl1PEv5wsaLbyH7ftI9cWy7tZghbHd/7+HOTg/6LNLZUswVY8VTLk41rYBGmXbwy+6z4Pw/M3m0vGBh9zZZqLyr9GllMUiM9Pnn5ZLu5KQ4A3XSWOIaVRv14ZfJlx9SvFwfZvc+EyebPgRqgjhLL9eAc3CUEZQ5d2OiZjcBaPJk7rqaubjrQCcyEdKzZ6X9mk3L41gne9eBFgu487NqC+dxIWsqAPJyqANYj6uZoYtFvq4/OZFIjsmynajchq6NFotars++1DFKVMkCv7QtpycV5KQ4i5OT6mgmmrzYk4UzJvhxNc3LyOq2LZ9IaIF+mOAjpI1OokkhlKxeuf9KxvdSImP04H7Gt7AgbdUM0KrvQPUjBA8OHu70BDym6hfJIDZk5yUgk5dnfgcak0zgfgCNEe5lNrGevhBzdNYF/uCRPLdla8CHCRjTtNZp28j4z60L7zB8dB/h5Q6pNTiX713fuLgbi8UNRZhVDy3wAAAgAElEQVSo0+QzNaGE/wCUkBSFYEreZ4RhSuL1B6oDdbWUHU0f8GZToy72XjCTENnhWIBSVHYROjmR1HJLNGNSyNkZLYCoePqRF0dtD62Wkri2kkWIx1E+r5b74VWTAi992MlESUkcpoCkq1snqxZk3oo9y48fmuvWKIPu2gDAqwVoq556M1l1whxwMOt4AKjlEM5PKgTcpKjbYtRogkzQcZQ0/nysJLKZUHE8X8KvTQgzCwcnqeVNmBD68j2pnqYExXy6EvBTSrLzm82LvQC2JnBvItDFFt3Xz9Ao5NpLfoqkqMtC6PpY+sdt/tfJeX47gsaE1Mo4tlq8eCbjfWmbv+wKDH18sEL/sEVr4N5p6eF2U5i6tNchLjzYE6KmqDOQwldhsbCIzb3vLCozf7bHkM2YnGQ2oTLTxBtT30NuJ4jGgsy0yWX2XkoBb5OigqW4q7h+GmcJXwZhSTbZyft6XCe6tjGbPpPwbj5/spvle074JQpdPU/vm/8jkwtTxq8JBUZeojXeFWQlkCeKVvg29+PcF/gDIe88HqWdep1RxyBHSEKuyRL13h4IEgovmlhGWZJzNTQIQT+6fl+tLip/4+Gsw68J8l2o102tB0VFctp+SZhVJ6qiWDl4xIVDUHRpXgSIgbQwbcntjJPzAEoe5Kicy8EfLCqUWmmb63zRutLCY1w6NK1ZMBd+AmHXxSA1DnFJcIOvi4VlzbqGHB2cRznKUa4ld1ezOEStl/ktCk0+UMOW/fQ3PArnAg9jLXtneBA4M1sVnwUw8VmUa+rnfC9qQikoBED8EptdVbH19y8vDvssst3NXVd8KWyrYKtKvN6IzyLGHKKM9fvLtYQJrYOTCBh8NSEg46QlEIuqvetq2xNPQ8ScQE+e1zZc4bNw2+v5LCaitPlA6bcbY8W7KJbDOn2RtZuUpC9PhM2LrvBZtJe7wxgb7wRFGoKgGLNQdvyqz8J5B5ffEW6bihfJ4+uB2gflzIgRJ7/9slYkUyd2jHAvc4ax8Vk0Jg+lYiJidYY+ewk+wIXaNEHuaUyUdjcgPF8W7AgANG0zHQNfNbd4toC/7NC29Zlrstt15O4uFnMzxBEoZ73Y6INNRZ+wHLdNBTBZZ+jMZ0HZZ0GnJ3Jc4+DbXY2Y2HstFvKyqiq92Ym/IcXq3AJA987FqWa5L00KOV2saxGaEID75/n4RWmPA8Q3sd1JdAWQCXJ2Ctw/n/oWsl+BFzUaQttO1NphFF8GAHqpZkhuq/ZxuxNb/fGDsqCVNHE/TWBKJ4vqVJvT6nl/2Geh4wGUfqf7pwZ45CSSoDR5ms3qhbSFNjvwafb35DTyCUIRwHhviXB5wGeRfQ3ceIF86/FH9+VY/jt+cE/MksiIJwFuq+Q1QiLDjopPhNuAFBz8RYftv36OxdPMTK++iC6WFHWXKf2AfTMkbCNoSMUMWfBhQt7+o3tIrUO46Es+5HjWYPeowerz+szHVUDY1t9bM6S/57F4vsC4yu94BNJvfVl9FnYnmyM6hxGkrE+JX69Z7DrRAIahZjtaINMbaha4XBdfAgDRKFKsTFaDCQXepmZxiHjYO1nICmCoB5yXnWpzReg0t5c3WyAluAz8kcdxy5pFP1ReEsvIZYsK5fty1xek5W1pFl59UpwZrQyrlvpUCogpeDjvQJcbnDDfvmbxvexn6vryDrvV4kaaxWLRSK3TRsPK+IpoFjO5kjXrVZJZkwqV3QHH0c2v6fbht+qUfBMI81u1xZgTh8ZHsRHJOCv1eGbxsiUDr6wIdltCM+ezMk5Z1mz9/k2e/xu2SaIfhp3KDovFmswrwL2LthG9uafRz9p6w+vcqcViUmRotroq3sB/+Bjx08+q7yET3Oi/RbwvO5XmktgiQ8rCrZDrlAvkKB8FUqwAK3MvRwq2qqYNVIMB4B5LkaH4+RPMyxeKDyHjO2ICuvzwYjS5H/Jv0kzWmIvO2O87qXc65Qd1ABjMs51Vf6caxG6aZagLhHtwH+h7pJcXry9faGDa1y1fSLyuWl3u9+Rd1QVsVr90wuKen9khKDaAKVvaXBTEZcsMjuPkmGvaCoJTPtHcLylJmKR6PCA7NhH4wT3g488Oly/U6M0ryheW8XpN+UKvIe6zkxqJ+/RzuBD2NQk7BiblwD+8P+GPBXCEex/lKEf54uVOaRbFDkbWMsyKqyt3/ORT+MePauLOcgHe7gRVqPZ4tmVT1wkyM1+jlBRErusBsdWJSDgzre342VO5dkoT4JZU8z6pDs6XF+K8y/fQEnv04z8M2vY1UxMALxqkM3FUuhcb8Co7Hdc7xEcCOPK//Ymc/PiB8HQuhIuTF9kR+fwl8PC+8HBq9WwFSy2akoINAP75pajT3QC+Jw5d9zJXEc8JVHrd9D3hC4l/6FtSEwQoKEP2hNgGuIwxGM5ahLXwhMSF9awLErHgPwxsPD66B5cBWOlE+j22AeGlcnBS6QN1Ayg7ONNJK87Jz59h/MPfkmMLcUJK3ZCq2XQPG7QvRmF/MiYaB4ewHpFah/aTXDGdGf3XThFbh+V3xWcxni/ArQONcl2y9rwjjCuPsNbaJ7LPtr/zFJ/8mR/H2cfZ+RsIKRDCJqF7KO9I2HEhFR6VESsQmIBmy/A9ozuXE+7/yy1cL9m6ZGgEN4+XGFcOq493Zcye/8k/gM1HDqcf13YOK0KzqX+nJr+XjdQNadaM4TSbzREY/45JD3iN3KnFYk84AYZjsYhVs3Kq9BTHX6tTX1n/0qAfmVwh1yVr3ui9rG9gEFr6AjAaRvHyq/NOEZzbXqIV5t7yDucHZdXWYZQJan1N2ZGrtPslBRqQyTjGEl0oICrmCegIu04iQMMA2hiHLCCAMeXoRDV//GUnVPLalwxqoyGW9gVA0rJjjVoQC638xJOfZLFBYlko8ndul02f3VgXPIXPD3FC2OuSlBHgfihkvK6P4hBW34ImXBIhXPal0E9+kAADrh/hOlcRtYkRLgfQwpc2h5f8SsJe1+8T9mLXYfU0oXmRzbzgZLEwpLm+SxmABYSlRieEoZxGhu8TKMr1/G4EDVFyRgy3avu8Q9h6hJe7MmaL5yPYB7Qva2Z12Dr4bSzmlBL2ciC4QQh7w7YS9rrx+l62u7tY7JWvS4e/09TquZ2XcQPl3/k1JklYeh5PCXcOpbbHaxL2xlQXMrXrlbBXbW7DBUHjzOdiyEwmRMJ6ncS3R9hr+RcsH2XhkHDS3phA6jRLqFEMMourQxnXEoq1ZDA3IOydQOf1eem9kReRmISD0tc2kI6vtqk8iwQKxpk68BsR9vouGcJeBrEsNL6TBcANxvdF5nosk9X1Ca7Pi2V+DyiHhgGAPQ4S9vouwXdC+GtyGuCHJCUBuBLypkSyKH1fEPZe9Z1SvVlH23Wub6IAk8zKkszkKluX4U+4sdhM06s+++pVn0Qt9LjmnQAVan6bRYxtGzX6Y9qreAjSzFwAQF5YciYokCe0jbbYRLG3EQdwoprVqsqn5rzk/Aw9Rkl2asmfySePcp1ScwY4uDlcR9iRIYnW2iWESTaYg4yP/oYAAoF9XthUEfKCJ7JlGXFVlIoAdnqtOgZSTwRg24AvIGpzdHAe5ShHuZbcXc0CmIbQLKJzToCru581Tw4lmFmdy/J1ElUOzDlfpNEm9DxBcObfN0EyNzVMplwDi6aqtLojBw9eZNBUjKZ0YBJORjZ7QRPEAemdUKQZlir2TgBYM9YmLNqC1ASyXyRX4VJHJiloTMFbGfGpGk1aNaBeHWBcigwrshEA0jLA7eS+mi1J7AEagd4+s6qR8CKAdlmtVntf/QNABbkpUlTNJUW5NgEpc3uKX0H8S0VbAaS4MHPJ/JSTxRlJfeal1JKC3iEtAuLCI5TyC04SxNRnYfrCQc7Xt0OLK/mmwXDmih+APRWn4nCezZDOydbPQDQ+CzDDDwwXCMNZzjp9FuAoFyVSi9gT4qqRosebSrMwnAX05w6+96VC27gkNB7FDNG2pECIC0LwVAoaUQTS9eks3m6xIKJvA7iAGAUjM/8UET0C8DcB/BCAbwP4s8z87KprXPteGodOKFRkAISchkgyOi2DdNuKnZv/rT/OHxX+rICt1UJsQUs6k0FDlaWbhI/iZFUXla4XCLdCpDOOIp0txZk5Gr/AImC8J9GQZkyIp7liVUyIZ/K5zeTa3AZxui7aSdQCFwDaBmnRFGdmSR1fthjv1yrqIZPTkPclSuLnRDG6uOQ4/nB/Ab/NL5Pa4cEhLXxB+/X3GrQv5WWPy/oK+c4jjKnWAlHTCkA8XZSJFnM0JC09gqrYGZYcl0H4KPO941kLf+nh19sCn45LWbhcZKmLkdfM3WOPRaCinsvzlYnZXEbE1tWKZezQ32+RFoTmhfRhvLeQrM0xgYOD76qpl/IkazMsW2HbqxdLrL/uQClHlbxMzGbpsHskjfC72p4xPx4OGe69YfgO6M9lrJZPArjL716o793uwxbDCcHFVRmzzYce62+SODWyjKeE5sIsTnmtTS2BRkZ76dCfZZxLrNGS68gXYYb8cWb+SWb+qfz3LwH4DWb+MQC/kf9+J0JzROCrT369HVd2RjfVZm7WqP3P8/s62n8SV7XvlpGMe0VnTI1Tpvo9k7YR2GebMUJmly/HXvObq0R9AfO22uvpQkGYLBrlXCf/cenTFzyepi12vDBr69442+OK0lSt7Iom7l0bs7+/4K7dhhny8wB+Nn/+FQD/C4D/+G0vOkHB2ZyIlMNG9phz4L4XxJ3+O7tGqbGZMzNpvRUzZjTRAs4RBxuGy5XJNeGMuw50sS4YEb2Xe7ERM8A6+WJEk3dM2nbwGvLsBoTnu8m5tMksz10vkQQliQGAfoDfdvuh034QbUL7mGud8jDAa7RhIzkM5HLoVM2mbJ4sPt/WkKGaUJT5HTRi0kvyk1T/rjgLGqK0VzUeE1UJL3dF49B9MLzgvVqnblbr1O2k1invOrRPch3YYoZIopSaY75r4DejOAxNlIZightSrkiWIwFjwuJZh7gMUrcVQLsbXxk6bQ/UOqWLNc6/E7H6PB93UpEsrEeEbZPHS94hMlXK4sKV0KUbGO2lXK952Zeqaq7P72JwOPm9lGudbsqYnX/3BL4PWD0di3aVGkLYplw8mqcVybr9Wqe+e3ehUwbwd0nKjP+3zPzLAD5i5u/l7z8G8NFb3mNfvKsVr5We33sgKT4gTbg52SlYy1xDWa/UNm4zB+asxgeRYeFWn0XbVq9630sWpfJdZiizAq4modMmVNMjpWpaxIR40gpOIt+a20bMizx5eEJqI9mlZQOxoKzTWhjZ51KCRFSzXU0iFFnzJvd7PGsLLT1iDn06h9RUrsvxpEHYDEBw1QxhhvMOfqhhT1ZTDuILKX3L94zBlRdwDsqCBWU5B2y2xXyRiSYvu8067R4EtF52YtVmtJRf2Eak1kmB5Pwsx5MGcenQZP9DXDWvB2Vlc6mAsl4ssHvk4PtshgRCCtKfnYKyOlcm77BSn0Ue9o4ROkZ/JseXT4Pc1xGSmt5EGO63GFfie9Ex6x547B4T3OiLO25YEdq1q+USlWq2kcLIzdpNQFkpXF/9eNvF4meY+btE9DUAf4+I/h/7JTNzXkj2hIh+EcAvAsASJ4dOOcpRjnKH5K0WC2b+bv73UyL6NQB/BMAnRPQNZv4eEX0DwKdX/PaXAfwyANyjR6/XhSygam6GALnOhpoLmYU5p3cfcnAWFX6MYobslAw274q1nRMzhLW6lXrvMxFsSdDSBKv1LqMveVJsxmfiHNk9s/kwRvh1J9EGVeHVYdoJCrQgPhWYYwh3yj2HoTgwAVQo+zhWEJHW3sgJRxodSXlMw/NdBT8ZjkvyvvhVmiEK3HqIxTOvf1NXWa0pZZgzs7BWa/VvyG4Z+qGU6NOKa4UuUM2QrpdrbivM2RuTyCI4XZ/gdyNScKUiGSWBoSOJaq99ozGhednBDU1BrIZNV/k93ZRoBt7B50pjMgihjPHpxxGLJ/l9yhR5fjPC9TlioiCpyGi1MPLCQetG+y4iZKey34hzlxsH12VHceOx+GSDZhkQnlyWMVt9egZwg8XzsYxB6wlhF6sZohpbdti6XcTC0Or54R2YIUR0CsAx80X+/CcA/OcAfh3ALwD4y/nfv/WG1y/OKQCVgWochYAm+wioaSRcuViURYSI5e+Uco7JAdatTP5KGykGxGdCfqMhMbrciMnBXM2QpgGdnIDOTyunZWIhotFz8ssYH53B7YaSXwEAqQ0S9XAyKVWt9usO/QenIGYscu5Gun8Ct+4kZLnpSgjRjRHpbCll79aZuOeqaMiTzNW56xHvS26If1GJdm00hDLPQ/fNM3lhgbx4iYMytdUMGU4DwibCxVTsXzAj7CLCM6PWKq9mShgfnZacE+03hxOE53mRfWU0pIcfR2y/Ic8sLggUZewVNg0A20ceyxcRyVMxTwQWDoRtQlw4rD7RMUvYfW2F8cThNN8rLf3royEvtYJ5joYMI57+eMD57+ZFIACxJbSXDbaPpA1hKwELSsBwou9CHqIdw3cBQ46GPEiAz2Felyu+syP09wOGE8LZ0pcxe/GjLS5/kHD6e03Z3cYVob0I1QxRa7gluD6gveRJNGT8zXdjhnwE4Ndy9CEA+OvM/HeI6B8C+FUi+gsAfhvAn33jO1zF06Dflc9TODczv94RPIFTHzqeKnxZtZebIvzS9DcFF5GP698UtXzhrF1jBBpf8iAAyGJ0RcrMFyJzCHCyEGWTB5Jk3Moimeo4Kh5jAqFnnh6XM2/WNh2vlKHMSSagThRi+SyLB5djTHq8wr4p4zRI09EBvOmg2jaU+zMXZjc9DjbvAFefyqQPGZ6un18p+bcHxwD1GOaf31DoCyGEeUu55x7zT7t/dwJhdqen4H6Ae/QAACZV1P29e5M8fd5upRBLrqLOuw7xyVMUboQZLwUA+Mw7ITfz5VxSx2Wm1afLykIE7xE//qTW6ABKTY/CLqUJWV/7sPzsYDjXHlPGbc71KvR7w7lY6OcAwDukz55U4JLlq2xMHVTlsOD9IkPKT1HAWNnMCR99WOHFWmRIozQ6NuoI1vJ/eiyK01a1IC12U0y8LAVI9emT/fKFtiiU+Zv7Af7rX8vjVUPQHHyd7EQoxaVtkaHNTv5OCelB1igVQ+KpmhaffJ77m9+bOS+E9hmoZuh2C/rR31cT4ojESbvrKxanbAqp9t0WKe4HpIe5XbluKTde6p4C4CaAPv5M7qk8JwDomx8hna2mtU5zzZJDVdTp5eWkhCIA/G+f/U286D+91qp9hHsf5ShHuZbcbbi3NUE0RJrixD+BtgH6HqSwYD19tRQMRdtUCLbdsc5zwZohsyUt21JZGxDMAoIXBKWppOVOToREV3EW6w3o9KRwOyblvnj8QH7HXDXAJpR6E7TpSik96nqk+1I20F3I79P9E9EmFuKAK+dm4lpHH+zjLAwhMDDFWZAWN5rjLFQTyTwc8Qc+qPgCk8hkE5vSIojTMDJ4YXbwQbJcC9DJ1vQ4XRRHosK2/aKFm+EstFxhyVBdtsIb+fwlxh8QbTAFV3wRE8Le7EuxiWTEDBrP5Xo5XR6QXX48b5Eah8Vn8uxc+41X4iz4AM7CffIUz//gQyw/1xR1Kinqw5lMLzdw9SEsKu4BDLhRsA7bD+R6p98TLg92BK8s3I5AZz9QcBY6ZutvPcbmg4Dl81j8NrEVnIUiOBWhyZ4QNg/3cBbpf/8q8FnMM+0mKeozjglgEg0h75C0XMCkwvl+NASAmBVbiXKQdYYSiVpn2qIkuqqGpq6ThMICytJoyLa2TSfCGEUlzynqNp28RAt0seoGaY+qmLpgOSfw71xqwN7TEgIDEKCYkhzbUgC5z2zyUwpx8fN17X6quRdkzBC3HYRvoR/A2QlHpkIYZwcmIpcJ6tZ1vF0C4CBlBwYT5cntQoyVcmAjJh5vt/Avtnk4XTGN2OSX+LUUAeLGl0WMotybnYC3FG5PMaF52YtDU4FaT55XMmCiSdSNvJf+a5RKzbr1Biff60qkBkSSO7PpES4V5KBRr1QWmbQIpa2uG0FJ2uW3ArDiUDEhvPAIHz8Xk+tyU8Zs+ck53LAUQp7iCwHcUKMhBT3rCP6lEBo3yuieCYuuK3d3sTgQwShiH6RqHEptD0gJAFPWsDg+J6CsPGDDgFLez6ZcWw6Ici8ChSDlA7VCWIy19KH+DhDQVNYsClzau1pGsOsrMKwb5CXKkQ8AVaMIDtSNtV1dJ9/ZcoC6QJnyiIB40WWSj6DVqo4dAC1ArC+9soHx6bJW3dK20zRlmtv8ordNmZSc8qRzKBqEJKJB/AjLRb1unjB876yEAXFF6LSAtIYRKUdu2ADEZDLkfI2TBn435uS3POaOke6vZAIRFd4JOT9MoOhazvCq0CkfCJ1iGNA9MkWtPUmJAEcYzrMG1Vd+CY2ipJCdtBHwjUN3P4dOt8LJoQlxcjIjPjxHWgYE58qY9Q8W2D0MWGStBchIzV3to4Ku2BPCKsDtIpIJnfJ3ru/UvbuLBYA9AhyVONMymGWBMKfwMErIU/+dScEoKBuU7sjeOMssQU0+l8dxQnrK4wja7qqDszBl5ZohphI5jWRIaGrClTjhuslOoBoFdZkpyxKrDiN4szmsWdixydB0HurOU+gIZ5pFofm/2E77fIhzoxuLZsSDKVKU+1qrh8szoZiAbV/a4NTh9/LyoGbBsTI/oc+aRd/DXWaMSPD13QgGht6NssB6X0KxwjJW2bHSSXa+xgh/2U/MDXp5WYsuzzQLeC/Ob1ucGQBvd1h+1iG8qPSA3Hi43VhwEiUKlBKCLpQ5i5dJ2q3P3W8lRYC9MxmyBPdiDTfTLNonO7jI8OvBsIUh11alTDtYHZxu3QlDnNEsrKn1OrkjiwVPTQSgeqLVBzD/ha0yhuzd1wc59K/VLIoa2ZuUbaCaDLtOgEIK7IKYgdfXLHJFq2Qo3ryvqeK7voKX+kEiCMygjLNg9ZY7JwuFTqZhuFXNIp1VzQJq5zsC+1qDMy0DqBOTiU11KxpEGyvUeiWkzZMiRawArxtqFpwneslTSZj4ReIqaxaeJgliFBNoSFKwqFAGCu6Fg4Nb5933jTWL6i9jRwKoaoOkzAMT5iqrWYAhk70LJZ09bFxl9VJAlXMHNYvh4RK7xwELT2WxiK0TUJamqFtQ1lnzVprFMRpylKMc5VpyRzSLK8RqGwYjIZW28jpnqn5p3RGQQ9p1ACdRuw/gLHhdHXnwXjQMR1XDgHjS2dLqMYO7TkwPg7Ow2kcxCZ6/rFEQQ1yDC8hObftJJHU/Yyz3F2SpEx8FUCudkeAW0rPnh3EWpuKW1jJh5lKm8SqcRamt8umMesRwUmjb/AsW9X8YS20MxFR2ZMWKFNNpjKAXl/WSnTh5+elzpAM4C3tM/+Z+gP/8hRw0Dk5rhnhtRxOmplDBWTD4LGtYw4iw6yYs6fz0+StxFnQFzuL0Xz6b4izaBtT1CCVZsWbf6nurtVQ5R3/Cc2kX9bniXhNqBTbvgSfPpA7rdlfGZ/ntgPbJqvym9DemfQcnkZgwM5zFHAPzKrm7i4WbcUioWsksYVJ9aG0DGkepQ2qcVW65EBbuti3q+iR0eiahUx4GGbx2mn2J7U5U9bapJQZCAC0WEzMEl2upPZrLIZbJ/fC+TBb7gnhzn36o1xhGKRGQAJdBYHy6Ev/GIpsj1nw5WcLRw9ebIetNzQ3JZojNDbFmCD+TosPpaw+rGmwdnJ6qo7YRSDTGZEKnkNwQBQQB1dE4jOLgLBm+OXzcNnAHzBA3M0NcN4BfvET82sP8HIyzNbgyUeJJA78ZhPFKoziJQcNpmTg6cWmUDOC08Gg+y+e2zY3NEPr8GS6/9RBLm6K+cAibEeNZTlFXMyTVFHXN4qUkOS39fbne6pNdaatT57F3oJOFmCFPLsuY7X74MbYfNFi8qD4e9tnBeSh0un2wb4ZcfNlCp5z/ZxaElFfV+FKqUE3qiAxjCVU6yCJAKSB+9qRc0j+8Ly+kwV+Q9xXCrfcaR2GUXmamLJdfvKfP4LKmUu61WMCdnwGrZcVjAJPcEGrz4LeNXC8ZuLh3SHnS+21XixhvdmLHewgyE4CjD6QmyckJeLORWiUA0rPncPQQ6eFZeXHJTCytSwIALkhuCPqhpK67Fzlfw7ucop6L9zIDMWI8XcDnMGdll6bqO4CE/Xy/K+nr5UHECHqxrc5jI7Ro6y6WfzN+eA5/qXki0q7UeKlPYij8/HaAcxKSBFDSyMv7oGvueahw6izsCOOqRViP4Nah/Z2n5bt4Itga3cGHr98vNUlSmyn19TqBEBcezUXOb1l4gICWCLsHHr7LeRweZTfvHkh7wzaVqITWDWEv+SbtOsF3lYrPbUdBZM5k80P3MK4clksv4VUA3cOA3SOCN/R/wymhWZtQv9YNaYHYBrQXCcOJLqRA/KfvLkX93UquI2JrgUzqg1ixRW1nPI8gqi+07h67TlQ0rQdir2nvFYUwpiRvxSgOyjHjPLQUwGZXrqkyqeux62omaN+XpLByz1yLhPu+/pv7xX1f65KY9hFQ6pIA2XGqNUd2WrhZQGg0CjR6wiYOCF5gVkUd3pV6HoDMTQ3xTrzp2s5DVdTzeGg7AcAHB9KCRjnaQnmhULwLxZizW7kWJLqiinpLOFhF3Zsq6hZfE17uREvKi5hfD6UmSVqEEs3QkLrbRfiNFnXOyVox4uSzEe3zmnWqVdRLNuw1qqiHXNfFabbyTJoXK/itR7gcSpLd8skAcIPl09rnsL26ivpw6tC+GBF2VbO4Sd2Qo4PzKEc5yrXk7moW81DqpLCQCbXqZ3vMnj+/jsqsELFWNSt3sYWW5/cyxXkmhYkm1H9RtIpZpbSikVjsRIzlc1LbMxcuohjLv3I7lt1Wixhp23MSlSUIRskO5doObbuaZHPw2zCaduXdPUPWy2QTjvQAACAASURBVPGhttfuSzTGUsx5T3Q8zHWkUNHMiTjm/hhtCWO2yW2Bn4wYJVN8Sej+Dtw7/5byuE76ClRqg5hBZZFBIU18N+zEVKslBbO2kBi+SxJKhmAi2EmI1mmRoT4WH0phB88aiOtivaaOzYFixQVMNqaidbkuIuz8hNHLuzj522nFuJzO74dU0/cZ04zr18jdXSzm8qqiQ6863zhJiejtM3Vz9Wxz0YrNcIRJ5bB3JYVYmPbaxo6Kil/OLX4GA7QiwVK8c9F2ZQo+JuU3NeA45+oYv4P2KC1fmVQREzwHkJ23NhP3lqXczwnu4o2u4c11AHDJZb+e3N3FwtYJmR8j2v9sj9lzbcUpe3lT9wOAJFSRCZ2SnWAmzVfP0ZdkyE7E8jJnzWDRTCtyAZO6HtQPk1oe5bhO3lyLhEKo/+bvKYRalwQomsWkLgkgu7bPaEeNwoRQx2SMU0dtYuEOtb8HKioz7+zppIVTP47lBh1G0K7DIdqDMh75M4ApL2eOtnDjxSZPJvLSCcJWeU21toeS1KiMZ+3BcnypcfD5d96k8KdVK8cutTRBg9RmB+fCo3JECKLSFmFOrZeFeDeivx/g+rb0gx3BB4fhXnZm73whcopLjXDkCEXj4PpU6ok0T9uDHC7xJCC2TgBmWcsY7rXYPfCVNBnAeOoRbAJfqz4LwnDi4AY/cXCyv/5qcWcXi0mdkPl3phaIrQ9Cpgp7qS3iqibAmvuRUg0xaiThZClqtE4e72pkw97Le5nYFn25aGsIknPE4PwETtGXWSyTVRhjiVD4xOW4vsylFsnJStqo7V1vgJNVrUsCFNPD1iUBpDaJTqZCFFwQq14WC63knkO2w6MVwmV+LVT1zcS8SuTb32/RuspspeJ3I/wwgrYHXvY8HgBKv4f7CwR9zhoNaWXyqHM1roI4HjcOwyMZA2WzcrEiFAFg+2GDZbu/McQFoV0IC9bqRR2f4dFKjq3lusO9ttQkSS3B52sRS+QirhzawujlwETw6wGX3/QA8oITCMkDzcZj+zijMrdcSnuMK2lv8hJhaS4cfM/lePtsBbcznCRZdo8bDPmc5lKew/qjgM03CKB6fn9GaC/rGMTWREMWhNhQYeWiyEg3WAHu7GJxG6JApC/gQtc79q7EmhjztpikqsmxuckCXM1KdksyqYehC3o2AyYtcQdqj9yG2Pqk5nZSy+Oq39xym77Ie876cdOaKcdoyFGOcpRryZ3VLA5lipbvTOEg2GJChwoRaREiK84VshpFXNLFegKFTfmaACb3okUrmAFFHGaGau77yU7tn1/u4yxMESC6WMNrYtVmi/Ak27IZ1q2Fi9hRyR4FIBDu9UYyENWkUN+IKWIEQBKORoETe3tMtY1oIjI5y7b9dL2Hs2DvSvEfAFh0i4KzcDOfBa83B3EWOh4ASr8XzJUu0DlBH64zOjN78d1OMklpjNI2XI2z8LvlQZwFG5wFXVSYf/tpkGM5ea990kjN2ZiQVkHwEUC5DzuC32Qzs/UCbBsi7v+rAYun+ziLJvtCroOzSPl4eHJ5EGdx8kmLFBzCeiiRonu/06G9bEqBIwAYV1fjLPp7HovnI8ZV9Vn4/vqa9p1dLOYikYwbmBCacWl8FvAeyHkdBYxkMkJJuSVfJT47M331bXDwch9HNSTrHchkaspvXXWMej8hltkryOx96UPJHoX43PT8EorUHADvi+0PABhzjkTmdNT2liiIuS+FAEq5atfoy71qW33lkGh8TdE340WJS3vnouOhn/U6JXSbF4sJ/2c+DpZcFPW/yO8IoKmDM7W+Fl02khoHCk6+M+3lcixPqDZI8aCRMC49SqlRzyU64oZU2pAaBzcExKVD0tRzDZ0aaDcY1cHZKvRfzqUkQLpyrnmuVmLjxJ/TGX/EwmNcEmJjj1EFFmLm4FwRwtaZdvGNzLu7u1jMPJsTX8N1cBaZbYmsZmHYvwtzlK7iwyAT3Z57CGcRc75HUFSnICQ5xUnMmrpBtASbjwLUCTMMk2Q0RREWnMUwSNvCWP7VtvM4Av1gUsFZFgHVrJQTY6i8E9BMf81JoSmCU3EmE2RoQXDGCRbEWf4P278xJ9Qd2BnLeMBEfLZDvZd3QvVXwpV5HIgqrkTh7WOqOAsTUg3eFdq7yb2Dk36NqfJnAOWYalJ+04NHibQER7Uym8nvoVzq0I0J1DhQP6J9MQo3BgCt4O66EU1+DhOchS42qoFsR3HW9nnR3vUHxy9sRnDnJAU/X7d5yWAvUHYVFxluZ5zqO40qOSnYfDmWzYC4jvN15O4uFodCp/pVCDXTNH+mEKah0xCA2E81C5uZp/wOmrF5sprQ2uG5rxEOm6jlvYRAdUceR4mObILsqsqofe8UtPETgA0vmlrNnLmWFARKXQ/6JJj25AQw5tJe2u5Aq5VEFBTCrUCrtilRD0AAQAJxrhEIPwrlmvJklJBtNhHGx2evzQ2J50v4C1/6VJ5LN8DFdBCvUcYDKP0eHyzh1/ncICX3hBSmhgfTIsDtBrhhxPg4J//Nc0OydI9atC/3X+nYOIR1K7khm8qPMjw+A7cOTV4sxgfLHGnhrC3UZDT2UsO0uVBaPC/1Tz9LuPjBFqeN0RgcwW+jMGjhdbkhAb7jYhr49enB3JDu8QLjkrB86op5tP36ApsPHU5NBEhyQ+oCYHNDhlMC+xa9li9MeOdV1I9ylKN8H8jd0ixU7SfaB1jECJATurxM6gpgyidhfsNdX/gcSvpu3xdzRlO1C4FtCBXElO9XUtPtvTZb2fE1DXvXgV5KuUQ213Mv1+L0tGq6KS/Im22FTG+3pVJYHKvTU0sllpKJuQ283Ur26GDal8Fivrdqdmb76gd41XC2O2l7xpsodJi3QjAcnlzumSHqlykw7SEWtibra6ExynUOJZLpeOTzAKBJqWgrhd07+MqNAXGgUjcAmy2C+jM0jdyUV9R2+fW+GRKyGYImFHZzAAhPMuAtY0yaz1uhvUtCrFvp+CDmRXAF1i2+DoJ/fonz312ieZo1FmOG+F2uImfMEC2oPDdDUps5OF+sD5ohq49bpNbDX+wqDWBihG2L1iSSLZZ+aob4aoaMS8maLeULGXBfRQfnxMS4rrhcQbxAioXQ5GDRn2tfUx2nBxCi7xJrYXES2h5DdDI57n3l9tSFwpEACLTt3uMg/PGW+2DJWcp/M2i3dfDeprDCzUsKvzpZDRJXm+Yw4c24/baZz28Iyy+cJAXweLPnfXcXi1f4LK4D9y55IDanxHqZSzQj/+ucRBrKxD8M9y7/WQi5o737I3jQ6KbxmxCqr8PNIiN6nMyk9uK9J1+9+JSTwORlNlEeQNoUjI/GHWivLhQaDZl7w5tQoyyqzXgnx/Mp3Hhg8OV8Fda2+H1vvo6HfgZkspVjWhc1uInTjX2uOOZcLVuQoyHWIQpINEQdhVaUrIcbXykCAHCTQ6cK8Q8O3DggIsO7NTKDolmoE5ubvADnSEaYhESFE1PDodK/w6FTSh6UiynLmPg9Tg69X2odnNF40sJjXDo0xmcRFzVqBUxDp6kVhKxGZCjxjRwRd3exmJshSnUGXCsawso2beuEmu9KFueNs05Z8Bi68KScdcqzFL7bzjpVFi5te871mGSdlsI65l4pyTalxxVLkfL4veOs03KdjBUh5gkHCZlnc+tZp4NonRQjHNHUDGEJ4ZZjThZ0iumdZJ3SEOG0jeObZZ2yE1YubyNOX4ms07lmQc5kkl5Ds/AOnPKOrC+vc5VU5Q0TyRCCnGtqokrdyiFjDLJNeuuJZO007KnYi1WNhmiuCxHV6ytPZqaY40In6ACm95dIZjAUkrpeMR3OOaAbbj+R7ET8AkgBaeHLZKeYisnhfB6D1guL92XzThLJxrNWKtnHWtrgTRLJAGB8w0SyYzTkKEc5yrXkTmkWys7NwwhbUR1AqVnqP3wsXJulFkgEOGV6PfObxIZ5OoOJPvxAPN39gJgJaktGad4RK1Bq2Ct7yDHCn5yIx193X2apbL2RY+7Bfbn99z6V6t9ml7VVznmohL1pHEFaK1UjCZ8/KQWNEGOtGDaM4GfP4XiKZyUiAX3Zqu9ZC0FKBUehFeelW1ydiQ/vCyDot767T1EITKqbuyYUMBtZRGSMSKNhmra/33X1uvk3fn1evzeV5C1jdwGGNQH0W9+t92QxMcnswoumnRYGyuIybyt5j7St0RB6eTE55hPDe2kDnyyr2aOm3Rgry3ouZ5genOHeP/iOlIqsnQFSRKPPOqYKlJv4uiSKVkB1ANJ6s09IBGBpsqOVi3T1f/42TpaLGtHL15+kGBhnd/zmY7gXmwmK1W/3I1dXyZ1aLDCbnHvfcbqy6NBcZBFxIOIaLt11sqDc0As8kRRLGFfbyplxip0r+SS3LrMJzcpbAVQ1ljOXZZwuorV8VSpudtr1ByfarYo1V+wEsVXVtO3vItJkiyIlrhykGqJNqZZdSAlIrhYteldt6/o3jgxRFOY0phs4KozcqcWCzcvqlsvJiqzfxZcvEb7+Ua0GfrJCurgUOv5tJb2l1VLOOVmB8m/Ts1oTw33rR+T3F3lHf3QOZwrX+u98LNccY73X6YmwgT9+WH0dT56DHz8o3BLp5YW08w99C/6ym9TWTKsGw/0FmIDF51uMZ2Lnhuc7dN88AxJj9Zuye8Yf+ADu+Rp8uoS72BbWbv/pM6SvPcR4uqjFeDUhbdUWzgcAaD9dS67Hti/ox/Ak1+/IPoji48i79vqP/X40a3X4qS9EciV8J33p7we0L0YpNLyqu1TYRjRPt6bqF5eEteEb9wokejwXDXJcebTPc7KeRguWHn4XS0RkPA0I6xHN7z7B+t/6/XJsSXAj4EaeIBA3Hzgsn+U264bKQGyAxcuEcUk4++1NOX75gyeIC8L5t+XY9uECcenkumFaM5QDZcLbmNspm8X5//scv/Xnfwhn35H2pgCkBmgvGdsP5ZywEd4NYsaQ0ZOpAUBAWANhx+jvy/HH/2wo41xycYiw/maD4ZRw/jtjGbNP/+1/A+sfZJz9Th2D/hxoX8i1wUDK5PZxAVAE2pf30d/LMPQR6P+Hfe6Mq+ROLRZW5k4yGxNms/OUz3PVeZTiQzTWIkSTuHJhxpaXi3ZSIHkStlKvvNmpeRwLazaQF7Gu3ysy5HaDTBqNSACgnuC32Wk2xJJ7QDHCb0bZ8DUHQYE3g0Q9rJefxiSQ7G4KcgJRJa4BZBcaJTu1QLhzv0s0Rs2u3O5mPRaqeRql7Sk4NIll8QDQBMmqROL6AvGBaIRmj6YEtx3Ld1q8uNF+oGIHKLJkmprn6dcdMAwIa42iOLjIQt5ikqgWLwnNOgGEGhJmIBByweFaUBmRETYRlGqt0+ZigO99yTJVWDWQw7yxlgLwGqLteiyeAYuLDE8PhNgA7Toh5oUs7BjsOIOg5GdJict2gO+4hJX8Lkllc09lvNkRFi88fO+kjXnMFs9PMJ4QmguuTOID0FxyWSyU/Ca18l17yXBaryoC7gZUlUcH51GOcpRryZ3VLF4pbGzHcmzmhyhJY4f9E2WHUYxCxlDsXWduV2c27+IIZbFt55qQZEZy0VyAbDOqWZJqeBAxTSpt630pVX/LxI5n2VUnNjUg2pWN2cckG5a9vmInSMyDuUZGg2G1jgw4hhuBlNOupW/Vprfp0DSmYu/Px44SlzZQVL+JBWBljWx0OcuU89+Zt4IZTp18g4T9JCU+mV1VTAh2ZDAy+bvIwMhlzCklOXectsuNCTQymGkCDiNOcD1N2qVj7HuGG+z9CG7gwhXhh9qmgnEobZbaHW7Q5K783E3bKcn1XdDnzuW3viP4oWomzhP8kKE0bG4EOU/alY9EfDVwFq/jryhOHhuTLqrnDRQmw3C9B6H2wm0w4cO4riisNlX0JNs2E1W9zmcMSeIp34Kycs/bdZvOPnv9DHPmjAyvcHIUuHillefaXsU+qAtKcSCap3CD2L6Vyfhx5ZhAnQ+ZmbveQ0ohyG/Z1bax1g8yLN5vKuzMK6f3Jyo7mY6fTN56TO9v6e4UrMXBCb0CcDWknMy9D4yB9luPv63c2cXilXIoT2Q+gRxN/51JIZ7RA95N/AtyEletw97Hm5yAnEcwvz97k0NS2oJKTjODjJeXRu81zzex/dCJp33Q33hfJ6r20XvAxzp5NKHJu4NkPxyoQITdmF+8kKHPY7XLXV4w1DfAIHjNoZhrZ7m9c8IhO1HVZ5GCgxs9VNNIwYE8wZnFJgWSIYx5wci3iQ0hhDzZPCb3crEe02eRMsdD8dt46TtR9llY2HkQ8hnlh9AxYu+QGiop6HINAUGpv4ASMrSbELM/WX0WlAHAepwdBBpu/S5OrpcaGYPiDG7keinUBTO2gO9lkSDmch/5l+D76segiK8I3BuYTJAJ27c9rqjJ+QLifcmjOKiFKAIzT2bO5ykikOTiB7SNnMehGA6fP9vcDQCxDQLN1d8Bgu/XHIDMtARAYv3tdHHg4Gp7vKsOQKDySwxTyDU3YcK27ZpQMnQVNVmyRHOuhyIwFS8xLj2abEYkR2WxiAtXSmfEpVDKWzYoYtnFJd9DE7Dy2MWEZHIaOPc7Nq7UCC05DBnh6Mb6txsbIIRyr7h02WRgocfPi9O4ynU/Jw5OLYgsLFJ6H/07tvWZx6Uv7N7saVIqJDUO44kruSeKxFw0AcOZZe0mpFaur5EPJvz/7L1bqC1Jmh72/RGRmWutfTm3qurqy9w89FyskRGysB89oCcL2bIRCOvFthAePUj4xQ+WbYxsjEAPvmAQCMZYyPNgyXrzYA3I2GAEAsluzIylHkbt8fR0V810V9W57cu6ZGZE/H74/z8icu196uxT1TWcbnbAOWvtXLkiI2NlRkZ8//d/H1jz9OaN7meDg5cBIpbtDsTyHad3MjthX84bwrCqvqpxA8xnjPiytnM+EfUtuVAIaajHoygXy6Tq3rK8xJ3L2ztYaIaolRsZco1v6fE2AqpSVkOMWtTRYgBEEjdfzCA0LTvlJlGLSh5H2dNyFprcDQBi7puB1oSZEsNNWaag5hYGSJ6BrlXLINaSkyxnAhB6OZGkbbekIQCYY1V30r8pi1KWpYK3OR0Ua76FRUP8mAsKTxb6jFluHGvuVNf4BcewtTQzch90P4l6EFDxFUBwAyIJkY6mPFUf+200xAUn+8RYfDl50rU7S/i0RBJGwQlyIDAZNiHqVDK4oFmqEtzEoJ7LVN0fUlGPOo6GuCgRBq/p3wUKmCP8XiMaAJwHIghhZISdbAujDVi1rSkRkAXP8BPgNQpuFAj2VCnvBHS7DGK36LOwB8JW8BGrN5BEWGQmU7G5HAE/Av2Wy3SaEuDeALO4j4bcl/tyX+5U3t6ZxVFplyEUAth4EqpZQcGDDw0ZaBiEU9D1jZhLM1NZWRKXuIrndSeJSfpULPMVAx4BeaIPA3g9FPKW2w/ImwFuL+wXUgLXfNpL50ZXnlx5FTBpcpGbEuJG3ndzwnwSQMzodQaRhwC3n8F9AI2xUHz9BetyJpQMRljK8qbH9KAmkg3joIlYhHSmEn5lKeCBOSFvVIFalyPTg4BO19+kT9McSJYeOqOYHnj0lzJltqQkMMAhw+9DfSKayxgc4iaYbCnSRhzIbcoNoCzJ4toj7H0Rxp3OO/SO4C56TGe2VCK4BDXJqTPLw+O6BCmAI8tTtr/OSANheGlLA1G7njeEjS4Bp/OuEL5yQHEbB6QPptOaEm/yeP0nAw7vMcLelf1yL8uq/XuyT9iRPJaZMJ9ofT0AYoQdwR+A6Vy2x+87+LECnfLjALt3POIJIexrstz+XcLhywl+9mVmEU+AtDL8S8hYcj0JxyNeUjkWJfxomgwtSFkx3gAuOaZmmwfmSUhZ+npchzs0pCzn4Iwj3+Ibzi14+yACjyNoH4qeA48jaDeW3AA7VtjOKmGfC+joDkB/qSY6c0ZQWXkqBKEKOLopgZ0ShphLCrToQmT46VDk+IuQbubiFAYAtBtFYXycimamKVxhFuWrkj2qy5H+IgrhCigMTEeAm+uN019qqvOcwaSDqxkEz6kqbDdR2bBPsjQD4E2hehvhr2T+7ey8x7BYhvSZCwGtu9bvT65M6fMgeAQg6//+SvQujdlJiSVkODH83GBdidFfJYBEcxMA+hcTwvBqUpYfPbpLXQIo9kS7EatPCKuXCv56RlwRhssqqeBHACR91G3rYENJQFR/QAmdCikrI/cOXlPNc+eweZoQtw79i6n02erpGmnl0b+spKywI3TXXJYhho2kjhAOjP5aBijpA8Et7lre3sHCtChui2YcuYJzSiBzN7fPXydx3vIXTPMic+UppCSzjpwLO5Nu0Rn4tPopCdRd8AaNFBBUK8HAtjkJhyCjkcpjYYr2nRy3eKtGaeMXtIAsehJQnIEJUI6Fxfdz7wQHiFxmAJQh7xODUuNKDijfpHJMCo38DcN5BbPwXNfjTSqOXPza9oajAMUhKNYBgGIuvhluUgp3K1bzBoVSxQaIZGYi7dN2J67hTW6+wwyKUDZqPUcXWXkdFTvK3c1blbKAlm6u55utb+xYuemHz1ne3sHiKGS5XIZ40aoAipIUhdAQo9LroyHW+XOU7L9eps+8qtEB7sRLg5IpKfm7R0MGqY8aL4zce4lWkDxBS+QiZ8R1WACcPHjw3OlrqMujLoAHL8uvLyIasvbloqDoij5DGipVOm4cmALcnBFPjKYt0313aJS6Zo2GZDHRsUEzrVXxivBG0ZC4OVqGZEbqqNwo8ynBJY/sUZYnlBkuybQ+9YRO6fAUM+LGYTp1WGmfpcF9pmjIdA7MF7YM0VlDphJ1yKECjvHErg/pAD9KWNP8R+PGwXnJx3EWjg23R0PmM8L0UGYK1gdpBYC48S6p0ZA04nNFQ+4BzvtyX+7LncrbO7P4tNJSisumZlvmql92l7rakGlq6tClUKGWv4mpMrNO6QGbC1JhCi2PayHHhQRglvRyzn7ZRluufJHDfBtBZgaDloY0bKFelOkzsa6bc1OB0sUlzNnQqjMvGI5v2q4yxebmvX3ODOKGUFW+Y+2tbSjLk885RT9uQ1mSHLX3xn7tdqvLljSp6e9XMXb1u2XZYefL9fwWffM5y9s7WBwJgNzIOuWKLTDf8oO/jmdRsAFbR6cl9wK2Zm8GIc2luBPPwjIwcxbKNwBQhDeptjnB+YpZhIPyMlKzrjcJtTbr1N63mpQ/QJ5F2KeyhqeYwd7BO15gFhxEd9LNuUQdiCF6knMqA5loPsg50VTPwabyTHgjnkXlODgZpJjhYmUvdgMh7BkcGls+vXH8QfJYin5lzAj7XEFkKHFSB5A34Vl010C3N4CT4BKh2zPStezkx7osqFwV4c64yXgY0H2tX6nkn+QMdDu6wbPotozuUk2FGiyk29Zlj+Ws5E6YnZ+HZ/F2DBZEwmZpla7Ul9SUp9LHn9TPWmFe85iYJ9CpOlaNE3i7lQFjaiwEm++ZXSBiBJJSkZmrJeBmJZhFTKDC9iSwie+Y2tT+IPiGbbeL/HJf7APLk2FyCAagjhO8paGPM8ILXZ+aLiez5oxYXxgCpolWF/viw1Ec0w5jMR0GAN7uhAUaY03CMqUoVb4yBa2sIG73fF8HJmu7MUl1IPT7oAMWC0YBABmLgUIapNL6c4TfTXWw0P5w20ONzujA6cyfxAbN3SjWh7s9+meqV9JV/KRVJw+7rqS/t7ICYCXJtU/onBH2EX6kEhnzL3fVk8S5pX+Hd+j6IP4jQMWsrrY4/07E8KzaF+bg4PcRYasanFMu9GsDUXMgnW3JALR/V/fdi1UjN/aJzhG6Fxl5FcTXRfvs9MMThH2H4WVsQtBLHY6Whh72Ce6QsDbfkMyFTHaX8nYMFrcUaoV2bysmYOtdpXsbWJcSckoyk7DX47LIp6hMyTZnhFed3PCWTxG0TdNc5e7t76PwbKsxsUgEsgvQuXJDFJAxMXil0oJE4E0PmqIMWkXgZhBAdpqqJker/L1vbohplpvJjJl0m5x3LrMvADUC0io/ZZaIDbMa4ZhMIavNYGxuQC4DRTpVc52x+Zy5ius66ZfiPo8KDFMIokXSLP14nhcK56U46OCpszlVyua+odInRrgay2CXTnQwniSak9augMfuxbX8Pq1aejkWAXOoru/2e0xz1aAAJOfGiYFy2Okgbn07p8KOTSsPP2ekTmY74aCDnwLiqavnxb1D9/ISbgqLPvOHhDD6wmYFAB8ZfkzgQBKtssHCEcLLEW6KyIdQ+vZ4Nv1p5R7gvC/35b7cqby1MwtmARZvhXYaHIFJlyHmbg7call/ax3AUuORCER1Ck5zkqdLo51x50kbV4C05VkYm9OmmoA+eVQotmAvmhtAyerRaXlMNe34iygtyMpc08wdFcNeyVuQGRyM6JRU75PEug9Ao/YVlyK8n0NDUt4YlqT1GJeABGdxVHEMw53KEmisOFHugxDJPqeOpotVW4QY4FnCxTVvpn5WdCzUs0N4FXVfN8s14zNqf/PtaH3RuYjNNQYopwXKR9J9P9cZSnlrB4vXlmPS1VEm6huX275ja9/XodKfVqdrvveKV7Z9mHEjFf22oMHrCGefp7Tn25ZmoFv0Q6t9YfoJx587Kmv2G997g8K3HfdV+9jHR5aOZbAu7f5sbVkes63/1W2i5lEjCXZc3nPzfaJluz7t4VCiSlz//qKujtcOFkT0NwH8SQAfM/Mv6LbHAP4nAD8J4HcB/BlmfkHyC/y3AP4EgB2Af5eZ/+/XN4NxQ9E7JRkZb1Pzzkf720xDNSnZ5No/rRRHsrzsXIOlx0mehtO8DK3etdzmhqY/JDt98jTtZ3PYmo8wA3MNs3qaCMYXUhpT4nIemmZe0Qm3aB+AylZt2kaz0vI1KlNmaJ91ZmEzR+fKbEIydi1VU0ykmBtVr8QlhAsiuEb31DEju5rq/1kLZVQFLtSISg2NW/vqFnPtxQAAIABJREFUjLhkGUOwA6N2+1FmspnrzOxVWIHVYQI/cnyZZXBGE7r/gURO7zSz+FsA/jqAX2m2/WUA/zsz/zUi+sv6938I4F8F8HX99y8D+Bv6+tnK4ilrCUtJHMA0F4O6TiT++24B1rlhEDqCvgIo+Q8AwKcb+f5hkqfm6VpuFPMc1YEHIVQQzjvQyQa02TR6GAQ6PyttJd4CANLjc7jDtBDU4SEgnQj4Fy4PyGtNKtuOiI9PAGZ03xNxgnwywG1HATzVARwA6OIavBpAQw/a6UBq4dChQzrblHP0L68FcBtn8LlkMNHlVs9LIiwl+qJRkfnL53Am2JsN9CXRo9CLPm4Cwl4Gc9PnIGbQlOF3Ux3YgpcnXWbExyfFoyJpAh3OV0WhPJsIztCBxrksOdKmh9tNIADTlyTalXqn/AhB/21qPz7w6K+yqkdRaRewgj9IzojldlByGJ+skAfCRsHJ/GAN7p3I6gVa2ADCkbBbVfnc3NB7AC+/3uPkI1/OI3eEbituYUANjVIGZtO9MCO4UT4/PJLtD4ASOi0KXp4wvrNGXDusv1/77OKnN9i977D5qEkkWxH6LRdlLhO6SR0QxhW6bVUYpwSk79yd4v7awYKZ/wER/eTR5j8F4Bf1/f8A4P+ADBZ/CsCvsNy1/4iIHhLRl5n5e3du0V1Kmz268HZoQpyTXMxsM5SjUp6AKQmirqHUG9Z7R2tBzBE8TVV7co7AYaxPe1t7HiZ5oqZcIywHbjJFY31ixCRq4K3m49Ss+5kXswlKSdprxkH2dGdeGP/iIIlkPM+gnYZ6beCLYkZTLAVNz+K6hjiNb0BEi6dv0FAkxfp9Sqxof6pRDyOmMcPv5wY30NDpIdYBr+GcWL8BgMsZdJjA04xwrZyMzgl/glmUrZqfKGyjqH01KmKkeha+4S4gZnTXESlVUZ6wm9R0OS/o9IDgNG7q4HZ6nViy3GHE6nlGf6GDiFLju22snArNhaFcs1NTTyW/xY8MJrWgsNCpd4sISz+OCHuPcHkofbZ6kZADYbjIlWuyJ4RdrolknVHOCWEv4eKwr8l/lktzl/JZoyFfagaA7wP4kr7/KoAPmv0+1G335b7clx/y8rkBTmZmotvsaD+9ENEvAfglAFhhcxPF+7R1rfeVtBO8rGFDqBqPgDxRXSyvABYp02YIbGpQvOplJmLT/d1B9SsdKOmYqglk1Pd1GTJNwGqoTmT61MybHu6gVnKNrF7a9AAJG92WAA4y3QYzumshTeVVB5flO465yuqNk/ACnCtdRs0yJJ+sajfNUZYhRGLH1+wLJT9ZG2xWFs+Gxs+ESyIZd66sy9MmwI8ONOeSFEaZ4SYvkQh7BDVgYtp0ZUaRdPmV+1AuQD5ahtix8qaX2dJuj/lMDYx7JWVl8Q2xq28696KS5QhcKtaIwyxGP92VNi04zGcBce3QXWpi27p7/TLEtDdtGXIxYP+Ok2Q3AOxl1pA7wvhAZwujq4lkugxJvSwT3Cy+IoeHsr2/DPCTLJlMCVyWgQ5x7UBTLn12eOxVM8OXDNc0AN2K6jKkq8uecCB0W7dYhrR6IK8rn3Vm8RERfRkA9PVj3f57AH6s2e9ruu1GYeZfZuY/xsx/rKPhjQ5OFqX4QUUFjhF829a+foHllWi3O3pvCPkX3CZD528g+8bmpObv5jvH+x3vc6OuNy0k/xZq483ftV3HEYYmQmJto7Y++tSIw+sKL/qhtqO8f03V3LSl/k2Lba8szTnfaf/PUT7rzOJXAfw7AP6avv7Pzfa/RER/BwJsXtwJr2D9r2X7KYCZLi8BoNoZdgEcY6VXE8F8UNPTak/o33ki99ZmXfMMhkETzurTHvMMzABO1nWNDSA/fwE6HCQXx+wL5zVoswGfbapSVkzID07gplnQdj1+7EXEZcGQ63xJwQ4XjKRPqTDN4LABQMDHz6T9Qy/WiOenoMtr4Fyp7M9fgvoO8d0zeNPDsByCxh4RAAZWpuV+RnwoM4vOZPlVWNdAVr89A1jsCLviPVIFY1PnSl5E7h2wjbfcoEcU7racr0okQpigjPHJUGcUppS18vBjX3Qy5tOA7jqgmyNSXwV7XWSZATR55NOpCvY2hR0hrgl0IeLCm+9U4+jpQS90a8Uhdj9+VpSyUk8Ih6rVkTvCvCasXpqil5Pz3Z9jegDMl/oEV3Vvl1yxJMxblJlOEeYN8q+/gKTUF/cyoWQfl6uf2SBuAGCFfiOVjecO40MWu0I7p/NGJQwoKeppAPYdoX8JTJJBISnqVVjtteUuodO/DQEz3yGiDwH8Fcgg8XeJ6M8D+A6AP6O7/xokbPrbkNDpn7t7U5blmKK9AB6n6nBO+l4sBZs4tlGGX0FntQvawqy0OyzCklnrBLA4FoZBTYR1GRKjRBtiXIQECxDVUoZzRjB7wt2h6kbsR4SXS6UttzsIMLkfy6u1y+1H+OteLBcBGSx1oAot32RUS8Zpht/6so0daVJVujG17F9O1eqwkcfzY1eT0RhFrcm0Fazulo7clhaYa5cefqvnEPTmm7KaF1XhF6fWksUXVZcKN0WOevSXN8PmqXMCfPauAqoA+pcr2baVbf3lCn4U5ay0ciXHgrLqW+xdtS88eAF/54yT32esnxoYKQOU3yeQhjzCPpfpvsnxsZeBpd9m+JER1/rgUEr2cVk/HxB3hP4ylgS3k48TiB02H9drvNtqYpkWG4RSL8rfqxeMoCkBkmh241CvLHeJhvzZV3z0x2/ZlwH8xbsf/r7cl/vyw1J+aBicC4ey21zIjvELchXbaPdNLElCja4mgGK6s0j6uo0laolhtp9zAja64/pIwNF2RtSYALGv4q/k3cIcyD4Xn5LmtdQjpj901Fb2VE2Mmrahqb+tl5vkLnIOyFlNbCzAa09L35j/iGqUaWbmpt0uKiB8y/o/N6ZIi6WHKWR10q7cOYUVqGynWc6jmgyJERDFXMO0WPqCLI6t5kA5uMXva6ZCaM4ld2JglHvRyAQUCOwcck/V86TXjODgRKC3CVGyFx6HGQdRruK7xntgr2DoVJ/8gNTH6Wb/GWiam4zb1BHSquqN2n5+ar9Xt4tPChcRX8q4iUt9SvmhGSwAvDmg6YQjwOVGlovsc5WjQaakYQNyY97mlvZFlBZENDOfI/DT3KvIueVFccu+rTvaH2RpwdIK9BFa8sRtjm9fVFuYZLBYqGsDDfhYwVKm2wenL6S0wOlnBPaPbRXfFAx9aweLhQPZcWl1NVutzXa97h34eD2mlbEZ+Oj3ARRNysKU1DrL+3bf4OsTmUiejuaZasdQx7B2aGo1Ml0XFrqYtr1r2lP0Pu0VGhIOfuHwRVER/U6czYppzrY+kQuJKPgKcCoAqp0CAEWDEkDVwQyuALOA6HS6UdrbbgdUjyLcvKwWDmp63nHliyitzCzkie2oEMpF+zNmwFHRvbQ2uplKKjoAzBsHf1i2R/YnuEncxoZG+NYcyHrdlgeHNEjYNXVUFLeZqdgRmh1CWtUBeDoj9JfWV3XmNJ3q9x3BJGNbgNPyw/JImDfWpnCryFtcCVCbrkXfExDN0ekcmF42IO8Zob3obBaRBkJcq4uZhk5dqm24S3lrB4sbGhStQ1mjw2BKWHSkW8HM8pRvn0jeAzkKbdu4CVbnHBcKWFZnqUuPVfIk2notwtLMLMwxbKEI3ipZzXGhXmXbC5iq6lsUVb1c68kpwUWV1W+c18k5IObqeGbt0rJwXPeqldAobiMId8Uf0iJ/AkBZftj2sPfl/eInOuj5xpufLRzU9Lz92NeMTJ1ROOJFHomfcqGdtypV5kjfMhC7nRMa+vGxsytuYy0TtjiQ6TY3s6iCRQZ1rQyg1sNidyB/6NLDEforRrfTQS8Q2DPCLqO/tggHNxnG8nVbhnTXYlVgA4A/1OuiLX5k4YxMXH7f7prRXwq9u54sFn8nw8AngAMh7FEGLqeU+buWt3awuFEWyU188/3x4GLJZsd0bXttk3ugN9PxIHBrnTow2LqSNVHJtmsRO7+8jMakVKwG5DOtP+VqQVC+n2s05ziqo98tCVSZAWQgk0QSyn6WiNYMCsdJYkWrsqFt24BV6OcJLro6eMy5GUjqk52SKFzdoMy3/WHtsnqsP3Tp4bQtJVU/atsbDU8Xc4mGUDP19CNXOndTmKD2hXlho2jb0JxX9iJcI+db+8TBgTNKSJeNzJRFGs/k6yjLwOCmDD8ZKYuLmY9NHC0a4mcusntyvnlB+y/nNsuA6VLtBz8z/IHLsQGRzmv/rmsNhpvE6tBrZLu1K7hLuRe/uS/35b7cqby1M4tPxSy6AJqm5fsuLDCLhe2gFW6eekZznpTqu+plitpiFvZ+OtJdND8O288rvkEkJC8oTTnnxbSXVwPSqdoFHvpqHThOZbthFrzqgZ3iGlPFN8h7oXWvQp0BSEOETr5ufEMO6olChDxUrASQCAcBjXuYPGHjSfN9I3spZuEUp5nOO/Taty1m4YITzcxbZhbJ+kP7BhDCVTHutSjDoE5curyIG4/ADJ+5tK1iFnmBWRwe1ezLxbGV25BWHt2qspDiSUBaeQSVMoxrj7h2cFEjD0oCE5MfQhxceRLHtVC4+xfA4QkVq0PDLLqBsH8sx+12/pWYRe7FrtAwi81pDxxuPsOnUycu8aND2CY9X7FI9M3+0zkhdc0ypMUsNoAfCdN5xSx+JOwLb9XNNBLO3Gg06nua45FLeoM32NS7CZvZurC4jR0mIVDpNDU34r3tsZCyfDfUaX1R226K2021zqb4a1+OZxmiNM7w10vxXXeYhOhlhC9tb04JbpwXWZyImjk7KsnJ1sdT1Ol7KqK0hZSluhXuKAoStvEGKYs8wcVKyuodlX0sJ8LqpnG+VU+k9AdQjtldh9quWcKapKpRtjwJzILn5FzSw80N7ZiUxYHQX91CyjoIKcvPuQo127nOuaTnh91GlyayljcNTRH8JbiRSxsoSvjaxYzVM8ZwcZOUxe4WUtbhdlJW0BveX0+3krL6qzX8SOiuU/ldVi8ycnDFOlH65lWkLMY0EYYLLpaFlPHDa19orlis9O1FUYFbNwzI41i0KTIAnqPaVRyt6x0J2GY3+2pV/uYLoZEXtqFZIlobrE59b8fycS2sTdtvmkG7A3icJFTby5OLn75YKosDQBfgt0Id58MIKI2c9wd4HbSSsUZfXooSt6bEtwKxfHEJ186cVAmcxglu5yqYpraHlDKczXB2e+WfKGBsYFoXACJ0Hz4rs6Nia0AkAsnaRnfRF6EhtJGPGMG7fQWNm0LadmsDAHQmjmu/r/FiiCrAaQI7zNI2QMDYW+wtw/PVYjCwYpoeCB788rL+HNo/fCnZZX3fyUwrMcJpX0HcmKvMoZ531wVwJ0mMj795BXepqul2DnPE8LGaZc+phKZtJsc6IyW1PSjpA5+8vFUWctMHaQNzEU4++60dNr8/IFxUVmruw2KwKZwW73F4f4PhxYjcRMBaJfDXlbdqsOAGRXer1QIos5s6XV4ivP8l8EE6iNZr5Ost3MmmbGNF/Hk3gjZNqOzps1r/z/60vF7vhAz08BSIWawBAfjvBtDZidysKp9PJxtgnMDnp3WJ8uwl+GRdJfV1EIp/9Gfgt/NCkTqvOsznvSDoz/aSaQqhQu+/fAowY/ObUm/86mP4iz3yqoe73oM3cuH5pxdI7z0SWXgVQSkDybrH/Hhdjtd/vJUQ735CfCK5JUY3Rxfk3NbSBvq25Ptt/5WfK9Ncl0TCnr1oNFjkYTrz6K4TXORiKQiW6EL/7LAASEX8JmP60mnRo5jP+hImLRRuX5cK/lCfnvEkIGwjug+f4eqPfkX2GRrxm+YK3j9xWL1gFb+RbcTyvtsyUk84/fCR/hiM3VdWiGvC+bdl23TelbyTHJaS+hwI84lDrzOItJIDnH3rJb79p5/g9IMz3U8IUP0VY/+uRkN2msOSxeUckCxQJiDsIS7qmq/xzj89l4iWKoRb3+zfDZhPCGffjaXPfv+PP8b2xzNOPjgpy6+4Afor1KxTW4b0MovoL0NdhkRg/tbdYct7gPO+3Jf7cqfyVs0sFqXlVQBLZqT39W8jZRFVjgNxBRzt9aiOQqryXvUafAEJ5fjC4CPfsDJVNwM6BQUghsxdQ0QymvLgi9KRDcnc+UIs4s4jDbpO7TzSoGQbVynN3jmlRPumXUKR5t7VNtg59WHhBM6dfE+8NJoZhX5G+h3rB0BNfTUcyrP0Qw4kJCQlJMWVZHey55IYJcrVrtChZWPVzEy9E4UrKP2alNjUV+IXoOAlV3DV/DUQan/Na8kMdQlqjGxgKCHucXNm4eUpGodK4qIkpsFxVYHMtHIl61QwhnouOchx/WjZsVT6MZ5y0anInWRyugjNEpVfiD0ABuZTra/nwlZlB8RN7dsAAU/L0kUzZ+OGFn0WN0A6SyUJDQDmM+VskBzPZhZ5UBf5SKUNbv4RIWXdKLeGRbDkUbSlcCIqweeGyK++UoYAlTkDJnTT4gHtd4rEf8OzyHlRH4DioSniqTUmX2LouSHEqDNVG0UwYpKJvCzqZ1aA74g7kStvoWzPpNv5aF9CazFgfSM3YUNGYpZxuInvu4SyDHA2njOqT2fbXyTTbxGwbc6NUNLMARQavh2nbE/1XCvPorZhEQCbpe3MVH82traJmzq1v3tatllk+Q30O5ac0wEq1jZYf7oZzb5yo1KUf4C+z1BSFZr96vGMLepKe6TfZE+R9rfjUNMGmpz8Bnp4P5FkkupgUdLVHSkfBJVnkd6MZ/HDM1i05TZfkBvamcub4LjcIL7ojVHqMaDN3gMo2hkp18SxpOvrI1CvqDtz9T4hZrmYdT3Z3lhmNFw1PZr31j4029qBx1iQMVdDYGsDKTEsH+2rgHEla9UbZmFg7KhGCLipl63NdvOh6Ttrc0O/z82NmhnkqEY0tO2A3DQUa3vNR6MdXNvBqr3Ype2l80q7bD9KWMjyC4OxaWMU71S58akOsHpKfm5vVCp94WZqBgv1SdWbW85BnuCUAW/BGol3yyDQ7NuaGVPTtX5m5BmLPnMzQLPUUX6bWY/n5Hhl5kA62MxcB6ZYj3WX8lYPFkR0KxtwkTXqnNzM3jfIeLNMeUViV8lWLFmYBIYvSLEnknyMmMrAwN7JdH2RMaq6Bt4f1d/YFjaZrRZCkwzIZnsnAq6WA2L5HOxI0H8TebG8lEb9mbIr52Qq2aUOy061vmkyPym7JuvUptHNVJ1ykdVLfQU4cyDkgYCpyrbJ0kGTr46T0pzWu8gwVVDT+DTNZzIwNTkjqopmYGbqSMbyrMK3ltfSkywDPKqsng4Ultth/e/ISdbmUJdAHOwYKmDTSM7lQEgdFeamtYU9Ia24ZHdy0Dp1OQIAOdbBomSBrnSmxfK7Z1sudLIczbccO9vxLYN1API6C+Br4/AgyyubWZiKeGrqt23iV4M7l7d6sPjUcjyItLONVy1Zbvm+PD3r5gWh6JgSfhv341MKMTTe2h4XOgPlxX42TW3pyHJOHjeWQplxa7bRD7iQPuUY2t6mGWbcVpJD2ydiWWrp3zkv3LhoWdVnaBcv3/Px5/USaNtX+vn478/TmKYufbvsk6P9jt/fWAZwM2Nql223FGr6vL6KNYLNXn+Q5T4acl/uy325U3l7ZxbH+gU2zY9KyR7rtBzkgKGvCtsAaOiBcSyvABZkIXP6plkySeNZDzflEk0IRSDG12hD8CD0SGcr5F72668PiOcr9NfK+9CoyPioAxNJRETPJZ4EHJ5YclGH8aFSsKeM/WOJApw2+/qtV1XsWBSxPYC06TCfBfQGqWjUJZ722L9bGZX+IO0M3mF83NfzBZB7idZEpZkPnbzu3nEYVE/SzZo23pFSjeVRdXjsVOBF0qSlc4BuIIRdV2Tfyk/IrihdA6LCzWQp3HJc04qcNw7dztVjPfKSLfl8hf0TiwJQAftMTAYAdl8VVe7jaEgOQP+SkNbA+pkB2MD+HYf5FDj5vrRt+57XuoXeHXb10Zw7YHpISPq7G217870V8FNb7EYzQGLkXmTy9l/TLN1Lj9zJDCifK7FtlUCOMV308Nce6bGAFuOHHXIns13DRdgB268S5nOG3/vSZ9sfT/jnvv59fHv+cmknPZowPx3qMmSjnJlNxDh7TE87xHfMCZ6QV3effry9g8WNZUbzd2NWLO81B6PJKuVZdTrnqtfZ1uF3S/qz385qRqPhvpwFr4hNOnxMwDTDbye4yawAZoTrSWwOUQek/iIiXE9SXyNEPARZT/pdRK/4gj9ErC6STCV1ORV2YtjjDxE0NantKcPvZhCzHBd1ACAGVn2dLIZrMc1xuwm9yt37rVKuJ9HDKFNVJcStXmR0W4uMCBgbgoRK/WTzYqC/kvRwlyobMOyFml0ySWMupKz+qtK1bT3uJ1c0Mw038AePsE81e5SB/moGHSasXsjx4x6afVnX5IDgBcNzXq7FGYCSsuKe4PfatswYXni4iQqte/2cEHdUSFnh0AwWQST9jVodd1T6OH/wACef6H4dIfeE7pLBLuhvaRgRMF+pncEgum/rLcGPwDTJiQyXkgbProKm7IDNR4R5S1g/T6XP1r+/xu8MX8L6I19+x3m7Qn/RWAEMlnMT0M2E4SUw7jUnaQZoujto8fYOFp+mjHRDJcpAyruvqrgBHQsg5ysoSc6BuyB5JyGUfe/atUy6P2NhQweSH599ldTPCkxSRvEtKQAnicxdqaMLCym5H3hplJRELUpeQfUmZ1cBOEuQIiZwEMYm69PXWR+z1tN8/7NI1ttsgZ3UCTCyb/ACZ31b22pRJvvMOBVmEZjDUpbusxT2TYo5aZ+0NA09NjWARv3ta/TC/qbUWBfi1cle7ACELGCuja2EojjGqPX+IACHt3ewOCZlHZdiVehqmNO/AepXOlFIT3DiaV10CrxEHWhu0P3wJvVTiVjYhWQ3HwgyMDWRALk4uByDHQn13JEqX+u+XVjqhP6ACxPqhc9qMqTJUUz1SWceoyW6kPSGcY16lYG5GoI1S0EOdbB+o7YtBgsAEFWrEiXXvpUBANouAqnBEDeS+1DiU+6wuDE/S2EbHKxt1l/O+ksfEnYjQwYYGRRY+1a2Z09wXqMmNlF+xWDGDnAh3xisJNKkIPTR4PR5yj3AeV/uy325U3l7Zxa3Ea8Wn9vck5dsTdv22vrRfF/XsYylctQxUetNQqdtmxqilU2JkZtQYja2Zz0GqTIUO8axupU9qb+IchyOK8diXoYdjaG6IGUBraIVaeYvJWGyVvaknN+bnkMbei3Hyze3U2Y4UzJrQqgtEc76+03Vom5tV/v9NhzL9Xe/GUZdfmY9UZi7iaqc3ysm2BIilunKcRvqvzpL/Lzl7R0sGp3NG4W56jyqaIs4jZsmRIbrOiVB0u1hdEPLYwJnBeI4l4uJpxl0GOVzy3ANvsjwl1wNr++PlgYcXLlwKavWQe/KlJJS1cp0k4CbTCgmOBTP4LYj8oO1AJHGvNwdQPMJ4rqHPxLbzZ0rUQUAIuDbOVBwSLo0KF6dnfA3bMngjOjTAQv7yzLFJ8nRgAx2fhZ03zUXslzoQLgaF+2SAXgFmlvgVAVom3wRQIRqKFcx3LQipINoXZRliOZZHN/oOcjvShmgRlou9TWyYRm1xAymTkBaFQ1OD73mhggpq+UpWEQoqUFPmxvCfZXNs2xSDpr/AYBHXRYxkFb22zCy5xJxqrqYgJ9Ul1P71k+M7fsB80aiRqnYETBcVzjhcvyBkRu7gTxw2c6B4SaHeGIA9NK97HXl7R0sjjGLhVZFqozEckFWLQoCJN2dubwe10FjKt+nDBGbzbmAcgu6t2EhRMBhBO2nSpMeJ7jdVPUd2C7KCDdJZMCsCGjK6K6TOG/NuYrL5oywz/IkMBXvJN9zFunQGw3Bg7KIsDi13bMUdQ+gbxLJ3G4CBQfaTwhbDZ3uNYISJYJU9tY6hssMv7cUdbmpXSLNo5Bz668z3GQzHx38VBvBzamyQjUsDSefldyOWR57dFHFZFhFYdy0TFG3vqRxLqIuLqLQvXNH5andvxThF3YoTFZiSRHv9rnONgAgQ0R2ycHpQNxfJPjx1Snqfq4p6pZQ5nYT+qdnGF7agC03dH9Rw7pBk9soi1KV7KcRoVFS1O1u95NEmdhVujl7wvpZRjgQ+otU+mz1fMD16Qr9JUof0OyWKeq7ejw3A/0lF4vHBc38DuXtGSwawRMAMt32Hll1IhZ06pZObPJ3XVfFZJhBw6dnnRb6tJkGBQeONYTnUhOebZcfd8067R3ceEz3puLXmYMrT1P2Tii7JvSi35GnHylj0x4dCoh9kVmnlkynFy17uQGKGf1A8DOBIpUbgjIkW/X4d9RzyYHgjVKuUaE0vGHWqR4rDqT5IUb31natgbinAjICdXbgEmE6I2yawS0HQupRgNfPnHV6kkvmpwwWkjBWs05R6N62zZ74QqVX+jdkhuE0SuOa796adboG8llEXPdlsIinsgS7oWcxWA7LD3vWqaWXc51JUN+Dpwn+3ScAgPRJFa5BSlWhibkI1NATETGhaUZ+eSHKTNfbotDUkrL81b7URQDchRjm0qww+sNz5LMN3NUOdCq/MPcd8OwFMM9FGo63O7iUwFv5vh2r/2grIjC5RjjoEFX2Tp66reT++qODGBU/tBxmRjxfwcWMvBlEIg8An65BKaP/7nNAB1JTVvJdh/XFqvbh1VaiOvOMXpc3ZvLsnAPnDN/J+WYV+Dn9zq7iEImrY1io+SWD+lS4MaG71sGmURBPJ51+LlEcd4joLucyAHRX8ptvvrMryy6L8AwqymPLrm7Vgw4T+OVlEa7JnSsDaQ51vb5+5uD3Gbld7mUuS4+Nq7kdnAmrFwlhdPA6yzz71rUMwGrrUGQLIQM9D12ZzRVlq4+e451fP8f6E93uCGnt0F1GnHxspDsBJcxDFdA0/1kC1O74AAAgAElEQVQG47DP2CtZr9vlsvywdufe4ck/2SIPHt3T2mdPHn0Jq2cdVi+arGcihH2SwSbywimtv4wI+4ioOq2UGb93fXcs4z4acl/uy325U3k7Zha3lFeCm/aZzRKceHZSG7X4NH5GrUReMwNIBaAsknBZhG4XS4O71KuFLBKSM2C6Bl7YOZw1DdvSpWO+IVRLqbJJZYaiFc8RFL+4n62NCFHO4AiZCSUUZJ3JlZnEwu08ij4GKWBIcwIRST8mVz1TgjGU3rBYJEPT/wkMR65GGrK2Y86w56BpikBT5E1bxM0yAxHs5fOFQ1o8B2TRn2XkReUrSkTIFR9Viyrp16PpaLgiq/epxzX8xi5nr8Bz5EUU5k2TIG8rb+1gsfAoBRbWANT3IngLAH0nDmN9v1gr03olF5S+li9ryeeytKDtQdbUDzZA4qL05OcoeEbwReUb3oM2a/D5aWFaEjP48YNyEZBGaab3TkRzMuYyf8tDwPRAczFejIgbma53lyMO761BzNj8rixj4lmP7nJC2gT466mItIbDiHTSI236Gxqc+YYGp7A9aT9hNg3OZ4ZZyHQ/mwanitZef21T6M8lJV2jLGbdN5179FdJ1+CVgBX2GWEfCzBnbXbMGJ+s0F1LO+ezABAwPejRv5Rl02s1OGPC7iuybxoEcHWJVSlLmrB/x2F44Sv5DRpepA7dThS2Vy/q1H77fifRn738DuOj4Q4anNoG0+CcE178PGE+URp3gNC9rzwORYMThWk6NxqcIPks7D327xn4G+AnBWl1icgO2H6lUw3OUPrsxc8EbH8s4+SDaoEQT3SZp6WmpgN+9Dc0OOOv3z18/ZYMFoxXppXv9YZYgJONg7j36k4elq5dr5PVM3CwC4BzyL1EGcxzNHySxU90cpVV2QUBMu8AcKbegQYvT9GiP+CRBzFSTqtQLjg3d4gbATiLU3jnkAZf9CEKxbvvkAdp6xcBcIq8n+IxCnAKEEggDQXOGwLIw0+M6dRmZAx2Dn6UNTsAsfpzQHYd8kBImkcS1xIupIQ3AjhNuk5AWICyaEfYU3k+BdxECwanyN0zQOJqHiyKMTFSB8znVESHc6DPBHBODzPm51pHJ+FRyoTpzEBLKtGQeMp6XgxkKg7s8YRLvezk+MYAzd3tAOd8CuDJiPFqVQbMuAbA9XgFOO2BvP9RADhvKZzU49PyMpolAG/3gHIXaGeg4g5kI3GM4P3hUwHO8EyH3zkC3iHoPt6MhOYId3UQ1W71/nAA+PoaFGNt1/V12Q5UgHP1e9cyIzEPVAAheHQX+rTdz+jsRp0iTtRaz0Kbwye7miA2J7itTlt3B3SfOOGAmOy9zmb8dY/1ts4s6HIry6txQqehXbpWIFel/f21PhEV4Dz73ea4SQcvNVI2ivamdzJdnhJWqwqWCWg71wFoktkZzQmbKZV6u8sAJoLfTTKzA0p4uu9C8XkFgLAaQIcRfHlVVLhz76o5UajLkJPve4RdEpGYIgwkWb0uZWRfwUxKGWHfIW481t/fl/ZyHyrA2UrqB4c8hJKIZ+fonl7g3W88wOZjvca8RHm661SyWd1sAGc1PJKIjvJSxoSDZuWe/t4El4Sebt6u3El/p8HJdaF99s4/6bH9eIX1s7oEz4HQ7ZOEXjMXcSL2AnyGbUI8sfA88OHu7suTe4DzvtyX+3Kn8nbMLFj/a1K5WTUo0qX4cFQfEckc4rI8IXkKUb/wBfHvPAEfDsVXBACcd8JTYK6Yw/4gAOTpRmYZxpN4/gJ0OAhGpOFG2qxBDx+AT9Y1dOYd0jvn8Po9p7oQ8WxAuGRgrqM+B4d4LovI/lA1KsJuVBtAD/9bT6We/sviSXJ+Crq8Fq8SAPz8JajvML//QMKwqKBs60sCAP2zDrkP8LsJ8aGsc7unvcwQgoQGzUrQzHz2jwZ0V1ZvJQUZlgCofeGLCWmoituAuji+3MG9uL7xE+cHawQLO+p57378DP2ltCsHYW3mwalOpKaCrz3CboO+7zCdy/cMV6DINfEPokexfn5zDZ4eevQXCWnlcPat2rbx0SChV51BbH/yDFHrjitCtzesS5YhaSAMF2Z1KO097T2uv0ogpWBmL+zP1BN27+mMcstF5q+1L8wB6C+EqBVP9Pr5LsMd0uIpTinhxc9tENeEkwcBYSfXwvX7HtuvmY4o6W9D6C9rHxijNw2CL62eBUxnWm8G0v/1Q4dZ3FKOtTOdE3SeeYlDLLCJ5jshFCyj4BvkAKSFj6nxNcoa3ijUbRZrcyxWWX4Tv3HeV7q3uVEBhTTV/hQtpiA04YojFKzB188NHzEiWPm8CzetBoiQe7UaMP5WH6QdsdYfLO29cyD9jlRbiUnm/t16nRqWAKhcvdaXGq9TYhTzouPSksgKqWhF8KOt9RXLGQjecWFgxrVEXsRGoX5PVLGrLiegVgC7mxe/HEcIV+X3RSVh2ZIirhzmDcHPFZMAUDU8BxT247wWXCANR1YAAYX7YWAmmMpg0QKcHEQgmD2V7UnxqBvnsBGv0riqmFI8AeJ5rkZPUNwm1rbHlZ0rEE8y/OgwnxsY/yOCWdwGeHIb7jx+n49A0jZ0aZ3fdkyRwOf69w2Jfz7aR8JcnDMo1f1aJe+qVs1YSO3rMaqa9lKev2zn+vnCZqCV7FdZfGpCiUxYyPXL9gxEunksIiBZSLYhtzEv1b0bmf6FFUCss47l8W45Z/ussS5YSNmXY8g/Dho+LHkkKgKTqjR/kc9XFW4rbj6W78eiDhexaNvxNhcZfq71FyVuwwN8FaTxqkHhUoYbKzXbMbQfK5Xazaz6G3UbZSAnuqG4LeHoW85hNgZmjVK5GXAHWlC2/bikcLtG3Tt3YgdglHNKqCH5O5S3d7A4nll4X2cWxzL9xSOz+Y5zQN/Jv3YWMUFmARaWLfU4+aXb7a0FgB6L10OJMgDC6kybAO+9iN2Y0lagWmfTphLVcK5OodvtraGReZLaq33uhCpuzugUVMhl8JJEZDOLdUBceQRH5anMnbSTvYMj+Q4A8GYFZAkZFtVx41V4Kv8AFKdw+8yKqHU3fduU0h/2HjJVt3blXlXEOwJ1DBeNPi1P6XDaN8roBKhYRjuzEAXxmzMLe9rnpg1WT7strmo0ZHxQw68uElInA5kBhmJYJEsySdI6PhaXiIyoctv7+spBGJaUGsXt4MDh5h2cVjKziauqF5I7IK/qcQAUZfHaJ3X7/EgYt3Ft/A+8EWr59g4WxzOLlhDV5m3Y+2Mz5ZwlShCPHM45Awl1qmwu6nMSwpPt1hK/2mNNszyZjUQzR7i9oPdkxwRAUy51WqGpQePnVMhLmGPZbsekOUldc6yv9vkc4fcJbjRHb5HsBwO+kdVzY0LIIttX5P3nJPsrZuF0GWAUa3/IVUOzmAoxPKFsDwdf3re6MW7U8z1yjl/0h76XenLhMlAi9fekxSwm9w5hJ9T4ynuomEUr1x92vJDCK8dm6HeXFO6yTTELwyhs1lAS1xLD6UAUrA3kkCeRPwzXQRIBYZgFo9szuq3xLOpgYiO5DSphC9Eb1QeSH5vroilhK9hEt2dNxAPCFgiXbqkVGpbaoTYDdhHInUfYoib/aX7NXct9NOS+3Jf7cqfy9s4sbimfRgG/UQyraDELMkzhDYbTo0JJMITSktZi0L1hGz9vObbiYy6eEdJWBnnpgwKaZcjSKMv7QimPaUlq+wMopPRsaaudCql7mE2VhYtgVPEvtLBOzVmdyYoQUiV+LQSAmnZ+0WUh7HMLpnGX4hobxc9SfqgGi+JQ1mITr3IeM21OewXk1e6klgEKVIeudl59XCc5TdmmZYp7cDW3pMU3fEWuASwcw1o3LvjGSczVz839DPZqn3u3xAAcitiwpX9bHYUBuhAN1vZzi5XUeoseBRv+4opTGKDswtZdzLo8suJBt4TjGge1Yv7ckKfMpcyyJB0qZuFmae/SDUxSuBfOXR1wm7itOYm1WIucl24rmbX1+KkDXMlcraHOmsVZ+zd3aMhPGmbtqLiPuanFabDYL/dYOJVlT0WIqC25s/OjMrDmHsg9L34D2a8JnfZ1exrsO7JN7Bxv9teryts7WBzfqAZuAiBf2YT2fuF2DsjF31gDSEmFZwFjGRqVe+jkxrftViewPBagClQacoSuAU2zIlV+gJu6Co4CyEMo7Ll+6BDXWkdft5fBa+jEqrAPIH2VNvgSgnXKe3CFx1Gp1tB2lZwL084IzStzFf+NCcgZ84kDKS3bqUx87p3kgOipTKeuhDxLbggAEISVOt+8rEp/6HtA6dP7CnBKO1XHQ5/gcXBwo0RD5pMatpRoRWUoAuLrYXTs5bFFuGZeS5q5lflEthlQnAa1HvQCSC4tBMUjxU9U6jQx4vFJRn9h/argpQOmh/V3MSWs+cy2KTDpHPyBMCsNvFwHR2U+EZr28KLiJtNDIL83YXxRZQmmRxnc3AdJwcy0Ej+T+dRjfmCJftRgKa8vb9dg0eTkHwOczCy8gGleqF8tFbGaxJ9Z9qN5brbV7xmt2hSu3G7SjM5cjscm3dcci8ZZFKgMKJujUICjqneptF9RsmoAzlbJyu2mInFH+wn9ZSz1lfaMk7TTXvVz2k/ormb4XaN6paVvbAL8boabM2g/o7tSiu+YBKnKAnY6b8edwczoL9JNUtaBioIVIE/UTr0rin8KIAlg+wk03pRfapW97LxXL105FneqfTGJb4aFTimbUta0UKm6jZSVel98PdqS9lRVsHbViKq/WMGPrlC4h4sBfpK6U1dvSuNZ+IkwXKp2yCwyf2E7Y/39FdbPWoAT6LdcBuaWlNWZcpXOaoSUxQi6vb+M5SHQltWzHmEPrF4mdNfy+erjgNQPWD+t6wrxYql/V1KWzHSGF4D7jEpZ9wDnfbkv9+VO5e2aWbTlaBlCzXT+LgxOMqd1y0oFaij0czA4oQxOWxbAO3kf/OI7XzSDMw0ebrJM1ySqUX1lOQJA7qWtLubKp+i8ALH6agxO47H8gTI41w7+oPX0ssxJK3m1GUNcO1B06LrwxTM417Is8bPwKMr1pHRvW84AknnL2n9/MAxOWYoYHR14cwZnWjH8TCXzlRJ+RAR7byu3kH0+dV/vFwAneS+Zp29Sz1FhGxQaMlcOTvJOjED1B1EarNZASzGraUlSAkxStwQ4OQhQK65r2hfBA/kPdqIprm3Wj4INMS0BOnEyc4ub/Attj0MxH8q6YqGs7aR6c9k+rSTAF9o2V4+f+s/2O4mHaqPo/YYBprdqsKBBknR4jot0cgALTU5u0s5LCvr1dvkd0+lUjU4AoCePJESYM/jpCzmWJqS5JJYApq2ZtE4Ai2O5kw3oai+Dhh7HX42S+k0EfngOAEUjkxt6cauRSVdb9JqUxLs91tpG1lRx99Fz0fWcZ2mjYi+834OevkCvClQAYDqfrcYnoJjEHEBTRP+JrrVfXguoSQRKGe5aNTgfnoKmiLNvvSw4TmGjele0MQGg/2QA7STRb+iaS2iOwFXz2zSlB4pmqJ232583quWuaFrAVXC6fyEzHHZO2gYUncySQq9l871V8X9ti/m9cufhPnpetp/NSbY9vQAgSWFp8HApYzrvigiQqZiLnqd6s+q+HAhf/ocRw3PVQ3UyaPsx4fy76ik6phI9KzNLvWnDPoHmOvMbPnhZxZaa8nD1rrSB62D6pW8ccPidDuun+7JfXAeEff1+bqJWV18LOPkoFnFhMON7uxuHemV5qwYLyzQFAH9+LpoWCjKyOqSnjz6G//mvw70UPQp+dA569hJ4eA7/XH505AQ+3QAvLsBnJ8BeTjN/76NS/+EX/zAA0Y2Ac9h9dQ03cenIB9/okN59IKbEFzJo5Ien4Jgxvn9asi0337nE/sfPsDFw9vvikPvRv/GzWD/PxeQWAOZTh+378r2zDxIOj+X9yfcTnv9sAGXga39f2vryDz3C5nsjxscdVp+MGB/LDXby/73A9c88wuGhx+YT1bEYFR1/EHD9lfqke/A7M9LKob+IuPqaXLhnH5ralIMfM6YHcrzzf/wBAODbf+4nMbzQ36AoNgkS7/WaPLzHWH0iIbxJxkYQA901cP6dyrQ0Y2XKwMuv91g9l+37dwTMnB4AJ79vTE2pZzoj9FcMp/f84Qlh9Yzx+JtX+PafFvHmeMqaU0Ei7mKz9p/aIn/wQOz8bAWZAe4Z/dMzxJOMd35dGkwJePHzhOlhxrvfeAAAuP6qTNHdSMgDI1zX2yN3wPgkY/39VWkDAHz5H0b8wn/+/+Dv/YZcT25IGNYz9p9s8BM//TEA4MMX5+j7iJwJP/ZIBrx3Vlt0LuFbL9/F86sT/NQ7su93/tefRLeFuqjrsT1w+XMR/eMDwq+flj7b/YWX+E9+9tfwX/zWnyjU/J958gm++fH7cMTITHhyIqPB+yeXOJkH/L8fvYuvf0mu0etpgP+Nm4Prq8pbNVi0hWNcJP1wQxii3aEMHrQ7gMdRXmOlRNN2jzzNcPp6XEf/XGcUVyKrNwyytu9sujtOIn4zxyLhR9sAignd81DW7LTdY3g+gLZyJ9mxTr8f0V2IorUtDcI+gJSsv346wZtz9rMRZx86Id2ocvPq6SyyecwIF4fFua+eTvBjh/6ltkup127qoc9wqff5iNx5+OsJJ7rc6PS8w+BBY9Lv1IH69APGcKU3+8xFtSmuSWjJAMJe3MQpM+aLuq7v9hnDs6lkwxYH+cQ4+cijv9BIT5Tzni8J66eaXt9ZNMCh2+VKaT54DBcJ7nKP0w8ktzquLTGMkXoULGU3nuLkkzplt5IDMLyUB4GpcFNizCc95ue+CNdQFjUuibKgULgB4U30F65EPQyjGJ6P+Hu/8Ydx8ttVVi8NK5xeED7Yvy99fuUwBRnUvnUm5/DPhgwQw18GhD3wW49E5vHdD1miMKrlCdhSLGA6P8XZB7n02YfffIL/dP7XcfhnD8rp/uMHD9A/98UK4IO1DI7fWb8Hmgn9C4/f/EgEkigSDrt6vbyu3EdD7st9uS93Km/tzOJTgcIWYDTPEdcwIrmyG18FZhYykmWXegJnWsTtoetPi8SwHbdxQDdg8bi9xnLkxuuUvZJzCEXbErD3gPotyrbQHOuW45lTNwBQwwptiUQt27ToFvh6TGoySWu7GzKSZoBLu6mkO+dAyF55L3YFsXAMjEkKoFDPCUp0KuxU2Z6bduWGnSnRBC5/i0v5ceYmARCeRaHc9eqT0QCR4Ib92GHRj9kIVNYG5Ug4jX7kpm/YK+Gqyby1fnRDWtgXlmP1tsTiYrnIg85W+gxyQpTKicB9jTyxanY62G9ldfKyz3rGyTBh11d1b/SiHWszC2sDeiFr5Y7rNoc6LbtDeXsHCycMwyr5T8vPLMSo/qMS9WiQadKbnJqbfVGHvg9ebwYhGBekOQRhT+p7ABIWTLmAWHacdrCwY1n6M7Er+5YUapLjlAtsELctyigMwxwIeRXk4ul8iVpw34mTV9OG9jU3XWD7vGrf5XnUtOdUSI4mHiuYguXk5r6GL00kxsyIc3BVid00GhSUM5wn9Rr1CFgMIPJKgjk0tHfWB4E5kuUeZRBLQ73ecy8+n9ljiVlQZWcaw5WS7JtWKO0qA6W6leXQZnMu6eTtQD+sZ6RhVftvzcg7KgNDHtU7NQPQQSGsIogY89ohZQ9ayXWeVgGUZX/T08hKDeew7LO8yni83uGjTS64jV9HCWcr8c7a4FcJifR+0TYw0Q82RZ2I/iaAPwngY2b+Bd32nwH49wB8orv9x8z8a/rZfwTgz0Oytf59Zv77d29OU1LCUjimGQEtbRsAGaOz2YaUgE4iKhSbyEpTh6V3W8q5P0RhDVpiUIzqaZrAxgKdZiBJangZkFOS9HI9hh0r7LIi3Wkx0HUrY/XF8lT3u4j+ugOYiwhv2Ce43QTvxNHLGd17nBB2Bmxayrf+HRy6XcOoHMX3xI2x+pdaWjvL97xFIFQAub9m9NsGsyBSzQUgjPa0dxgusyaCNee2Z/h9rH4XJnaTGN22R6cenSX/I7nSrmKZqH1nZsXdQLLPHNFfacp4BCha2nX5GuLaobvkMnOTH0Rusv5CQNPusp5/d+Ul7VsZkTZgi7o3V1k9aH6JE2YmgJJQ5seE/ScbnF7YAwHIO0J/CUS1XeiudVbEwJyUWt7LDd1dOYQdYWTBDvpLSbNvAU52Yr8AJvTb6kXbP+/x2x+9g/6pL4PFPK3Qv2zo3kqnTzsPPwPdBYGdXkuRRBzpjuUuM4u/BeCvA/iVo+3/DTP/l+0GIvrnAfxbAP4QgK8A+N+I6GeYOeFNiwm+3DKz4KEDDlV8BiGIyM2+WYasBtDhUF+BCoBCfDkAoDtEwAHzeQ835fKU6b2Xur0DaYdzF8DeI54NJdTlLgf57qVEK0hDieMjzfsYq8zdfOZxeCzajWHf4fDIcjAC9o8JxFRCsvNpQLjuMJ91cGNEPJF6QxcQTzuMD0P18dQ8jfm8KzZ4ANBd96I07QjjY7mr/EHamQcPN3rMqmvZqTL6/l1X8i282u6lnjCfVJ2E/Xuy9KMs0QtAbr50zQjbJuTYKI0dHtYLenwg0+TpARXA1xKeplNCf02FGLZ/TGDXYfh4wF59OOJGB4tZZxla7/5rUW4EhyKjDybkXkyK4wbFUpAy4/CuyPWbCvfuPYf5ROvtUPQorH3Tw0rhNhLV+Xd7/MRPf1zATO4ZPGTEZwHupySKtn85AJ0AnCePBAjfDBM6n/DR83PsrzucvCNRi8O3HxRz53aw2H2FER9G9Fdd6bP4Ewf8a1//Tfzq9C+UPnjy5BpPPz4va8D+RB4+55sD5uRx9dEpzr4kOqTTFOCGu9+ar52EMPM/APD8dftp+VMA/g4zj8z8bQC/DeBfunNr7st9uS9vbfk8mMVfIqJ/G8A3APwHzPwCwFcB/KNmnw912w+0UMoF1KKk2ajHuo9RTYnt9ajYNJdyBrJO2edcQ245y2dpuRSiOVahXED+HlMh0nC2kN8yIQoA3OjgD/X4Znjj54xgvBqzt5vlnPwk5CNviVVJ6gz7qmhl7fEHj9BMnd2YAJbPLQzYtt1NqdCtLazcqk35ufIkmOoyJOxItB4TlzU8sSRE+alqZ1CSsDGljDBWXU0/ajr6toYnbTnDjrTvpI5u5xH2orJVFaCoziwa/lK49Ag76MyiWYaMVPrXXNUoszqFUaM8JU9jNwtQ2ipOWZp52NYZi/Xxhy/O0V1Z9iwjj4TummRGAcBfeVmGZGALCVseVj2IGOmyh986bDvBPJ4cWPktVe+TdbkCCghbLn3GFz2++fLLwGVXZhbP/QncZSgA56S40cvJI88e4SLgqtNp0UzI6e6gxWcNnf4NAD8N4I8A+B6A/+pNKyCiXyKibxDRN2aMr//Cmx9g+XpUmMrvvQApF9tv+55TtN+Qf1dfWwDVaMMApJcdCkrPHiXSYhRtiW4s2yevNRLTvs+BahtUU9Pqtn9QVJ29K4Cr7Vu+Z+1UENHcs9i1IChK9EXAxuZcFv+WdPNlv6FEsdhp/zfamFZ39jVSlDW123Qyqxao9Gd7ruyVzuyhddR/ljLOGomyf7af/c3B/lHzvm7L/nib9HHfR3Bg+deAkegY6Fj3ZXDHcH2C6xN8SOj6CCiBzIUMF7L2Tb0O5Z9oZuSel30WMk7CVI8dGD4kcMfgLoP1+OgYvpPj5r62AX3+4qMhzFyokET03wH4X/TP3wPwY82uX9Ntt9XxywB+GQDO6fHNFt82W2hLbvQxj3Ur7mACW/rIVLlZ3i+2J1GqLpTtT2vPbcfI1r4mFKmvx+rcpmBUlKsYovSs/WBeqgvVqy+g0FEfiMGv0IyLKhRTUbAqClKMYkJctDYZIEj/LlSxPqvoVaNSVZSqWuUn28ZHA36zb1ETZ2uz4B+fp+RMN9rQmhKj+buIIGcdeFWxzLabhytnwNklnjWGfVyYENlVpXndhqxRubYNb6Jy84rymQYLIvoyM39P//w3AfxTff+rAP5HIvqvIQDn1wH8n5+pZUcAZwl/AgICumXoVLY1AGfwJUvUwqxt5qpx9L0XVDoNmvVopjn2XU24KscCwL0r3+80A7Rrs0KhmZmaQVmOuXLiRanHmTWM1w/iV0GNGE0aJEMyDR5BXwEAziENki1ZzqHUX/1A7RxT7+DnXL05e1c+86hZo3aO8wkVqrX3FuZVf1ND3E8U/GMUcxy7MNPgS75HGXQyY14TggLFxbN0Q6VdFhaNG4lIWMJv3BDiQfoi2uz5VJYFfq7AKADk84j5SiidvOh3NfLZoGSuEjPmE6FtF0vBDS0AzvbHS70I15geRZsl+mOPXhZmJg8Z6DPmFAqYucUark9gJjx8KKDn6TBhCBHfzY8whR6PdHvcrGD8liKmS8B8lpEfzIibofRZ93CPf/HRd/FbD98vUjDvPbrC92Kdom4U4Hy42WNKHp/MDu8+EoDzMAc89Xcfue8SOv3bAH4RwDtE9CGAvwLgF4noj0BO63cB/AUAYOZvEtHfBfCbEJ+vv/iZIiH35b7cl7euvHawYOY/e8vm//5T9v+rAP7q52kUAJlVvGra76qLuqSM307KWrwet9NINabvEAiZXZF3E2+OINL5reZF/HRSlhVx8lZdT/0oqxYk68yieEgMTkOAJCFg3TcPQdamna8koL5D7tyCwdkSm26Qsnx9XexreMRRhrWxD4E6nZf1MpBSJUWZk3ka7GAoDuY2W3FJeBqURUIuFek86yM0ZKzltht/U/XWyL09erFIJHOrJB4eBLCvSybuWPuTy1PZqVdHWrFoV6ASr0QZqxKwrH0cuDJNzefDEd5ZbSXXAwD6jLCKSL3HZpCn+mHVC5aQCae67eFqj95FnKw3SMmV7S9Wwn9gjwK8shd8wnV50WfDEPHV/gVW66nMLB6u9vikP4VzjJyptOF8OGA393BdxqarWcHuR4LBaU5ct1iEVWoAACAASURBVBXmI3cy3ddwjJQK689eX1Uo57qe42axmzPo2Ask5jI4FDBSAbuF6RFQoghgBqHWb99rcYeFd4OlJzNkoCqOZ7rvHOXm87UNC7bjgu6NKirrjwYWAySLnoQ17JVdVTEDYlCSZZP1l2AAgln4QsoSzOIYqyiMy4Y+3Q4aMui1A6ACuQWQtkoarAAAuaq63q7js687+bn9AoBcVbyzApE50WJgKG1tBhAOTaTCpXJS5BhELIQrb0tohvfykBmCpvm7iE2YxO0NdV8otlPwGEi/csfourTos+AyVqSJcdrU3kV4n6VeolLvys9wxAhdwmlfAwrO/SgMFi0hC1hK7KseZ9lOSg1vZhakmhjUaGO0dbgjIxc3SaajXQSCvstMoqhpOQeaZvh9LEa4mCPCvjET0mN1ezXBiTVd2s9cwnEu1vAgAPgDV6Up/Zw7XxSY7YLmTlLZ+60wRAFU85/OlRAeoFoJGfD7iH4r9XrVOqAsRkHBaOQ6IIYtECy8O3PRUGBfb7SwkxuMotjlSQWCI1ACktbZStb7sQ6QpvvYX6CwRdNUb8zumsuxcu/QbzPoEGt4maiwOKHWAQAwXfRYb03F22YWgJsd/IjFjJCShk4bUld/AbEAmGVm9/+39yW9kmTXed+5QwyZ+eZXVT2RYnNo0lwZkAEZECBI9sKAAPsnaOsfYXjlf6GNllp5a8AGBAmUFjIgwASaTZAie2DPVfXqjTlExp28OHfKfFXN14PUr8k8QHfmi4q8ceNGxI1zz/nO96lF7hLvJwSayIKQ2KjUisvM5XWkQWgYwq1vBB6fc8Wnu25gpQY88L4/AgBM+wmIAq6up3BzhU8a3lcbDmx6WV4iQQHNuYTxPSbVmJ1dTvCPN9/Hct7mIPrb4hSryw6xdAYmsqnNhxbDWsOc9fgVHnC/rMT6OeTKL7L7M1kQbXoSnqNcuTy8Ilkh6zIugKwrS4JMsBvxET6Uzy3LhLDGIYii3J09BmMg1oZxGlm1zIIsK3ql+geyjM+gqMKVcBZyZMyBGH1+ewtF+eESJmTcglw7yDVPAogl7nIdYdpa8Oda5T6I0UOuqQQSbcJQeEZdpnEyHoIIZH2emNK+JHh7njQ38CFlQgPxEAYByBT4HPg/4cLGkkWtA5P2pv7E8nwKfK65xH0IsZAMGxMmwHUU0pR95Zr3IecyRiWhG7MORjQ5l1nrs8ZZgLi/rqlxHQFqJXlSSOpqa/a0hGHPqe4beUAOZVu6pmQ8zm+meSLzjuC8hFoSVpFYSC542QgPjIrXYM5xmZibK5ARWN3wem6yDDy2orwgvCXIFcsWymocMdd45+YEYaEyTmWhO9BC5TWkjdvnnuBHCbUQGPu4DjRcPHlXux+TRaocrWKh1LUIo4F8wIQn/vIq/1vo2wKC6lvQcsVv/SMmMcFociYDdZaksgSfFusm/i0hjMiR8XB8AHM84ZqRJIy730Ncr+AbWXFasqJ5SJNZPNZ6jyn1xVgyImYmGR5NQDOXGGexTmQlYfbYpfZHMwDA6lSCfMfQaEEwe3w8ddljPFARNLQZcOBsS+U6txKuFRCjzKQ+iXPTZw7NmB2IMaDxoLj2wpRsiJ1QfljHfUSZQXC/03URwOqBzqAu8hyzkKPHcEQIxMccDrldryn3K8UxzIRTtZkwaAKogYvpxnh57SSKBBvAt/nwcMcG46gzjgOIKw3J31wXMhyePLB6GGCnAcNBzGBNUzYkxkfq7FkDmFlh4c5cmq3E66dPMh9FaDyoc1iHJkO4F7pjDEWgnPWYRbj3J80+VjctvvPaGQDgyYNXoVZxcl6XJaPZC7AHFnaq85ipkyX+6OQ9vHt8kh/6l46v8VE4zO/e6ZTfTgf9gOuhxY2ZYe+Y+zCOCuJzZEO+KChrZzvb2e+Z3Q/P4nlm7G0x5Gh0s8yVoDRfIqxH0M0C6Nq8b1gseQlzdZOXMnUb7ceca6ZhDQiB3nFwLrNdGwu5MhDzdV5iiMUaOL9CY2zh4Ly4RhsCcHENAPlYB2+vIAdbRIsBNBcK3TOG4urrEd15jCMsLQ5TYCtWkE4/4diIXDnIlYFaRg9gtOgfDxArC7HgV33qnz5v0Fz0+RzVs3nk5hwhF/wqTBSBQcnI+hUZnhb8Fjz5mSlixb4QvPpGZJfffipYQNmGLDJEjun95MqVZZfxCMTLrAOgVEvG9b0aHFRk+0Is0HKdghxsliuczBrI+Qjx9BKnP+N1ve2IAUshVrBGz2/9oUZ7HTaCgFw6D8jRw0tAL9PSLUAYBdsRZh9F7Zj3A+NEonB0FqsGt2enMuu7uIoz8zf/5zt48GEKkgq4TqG5DhjeZVfoJFaRkos4CnDWA55jFJNlwJMHXBVx8E6MnUkqYsuKsPchYCYSs4+GPGbLnxzgr9/9E0w+KXGbi26Kg3nIMQvf8P1wrRnO/mgeMM4O+To4gK630mGfYfd3stiy4LfiGfl7lQ2pzTkWJoqf222IBPbyAQGc+cjINyBmV7DZbsq4GJsRlcHHIKrfDKKKMZanhwBKdQTkENacZiXni1q29aWmIokgxQxI0lbNQkKeswtitIXYNamWC4IYSs0298sDxkKMmyJGFEIRRqrGVK59ocWLkwUkbaCC5ToGhG2AqB9K47m/KbPiA3vyofo38IMbCBCDy/0KMXshAdDaFLToICBGPo8UX1EQFYK0PChecz0OuULUg8C1FsIGCFGk/4QNmWM0xQbEwCX9TKvnN9TMk6RgEgDKGR5joRfIgkQsWcn1LUmFXY68HBN1VstSmcgGlNoVw331QEabirgdQWyMmV4E6GvieqCUObGAXiLXhrgUKNZMP5D6BOBzq6jf38niM9KdNaENKtnCzNAk7zBb1oQ4aX+B/IZDosmXAsGn9uVnZha3+x+EAHlfJAMTHiPWa+Q0a0XVn7U1BN2WGATHSMJnjc1XYakvAPeBsEHbHwSxpxF8SdW6km1I2RDpAYg4n6eaGsRajy8gmVCnfVMgKGl0pO0pHZxiIOQ4YFozk7EJJH7R5IV80TV5nTpPZEF1bRDXzPA7rejQRjyH5Lk17yuJEeC6pMFdU4rdto/L7F0oEieCEChm4Fx1Ul/BLXNPJovoHdRbTCTsXQ23d7c2p/rIyOJFRNLcYO8wXcZ9KFWlKslv9VgoQKs1pFYsxfccavvfZmQjTsMVbwEeIOU5tz86+PS2WlsIo/lNM2cXUzYKYrD8Vo+fAC+bxL+gVgX5UOj5A0Ces00CIhMDBUE50yNUSUUK63npld7Uo+WJ3fDSJFfHVuLNn8dyBa8QPJbp+UkBWVsqNfMb3Mc3qA38Lli43JbXGkGELMv4RU1YlHMGixSlbA3/e4jp7/ImFybkvgkXcjBTrXyWZczEQPb505hwyNW3OSvUBAbDxfqdEFO8X4WczS7AubOd7exOdk88i+fYFihrw2ppwag4RtU2CgG3nbbntBF/H5IqO1FeMnBxWmw7BTPvsryp26dUTp3ajNuI3ftccq5lcbGrFGxoJa/7JS9pAF5i1cuSr9oCVcAlH5dAorjS3Dew0pmvhImJ4D2v7VOxWgiS1+rx3FO/t0mC79y3mmwYfI1rct9ckq6QqfvIxZhBLG33lZpXLl/XKUj7xTyMXOqe2qxK5HO/iCJ5czkXCrHk3BY0rlcUuWApexS+oVt4FABFQS1yZZRtlJdqdR++rN2PySLE/1XBxZRV8NecZRCTCZeLR4rnsOQlBwmB4DyICO7x09ykfOURxHwB2ptBJIzGRPByxwf4SSQmuRhZ4/NkBlq7HDPwzy4gojKXj8pkYjZFOD2GPehz1kRrhfHRPvQncZ0e6emWJx2ay3XW9AAA12sMD3gxPfnYwxzw9/bxMov9NG/yOdDsVahPL+GO9iCuFnBHXNWIZxegSYvld/ahrzjSncBPbqIwnJQA5+RxA6cF1NJifcLn23/a8A2lJcg42Bn3oYvl+ItXNNqrWNuRg2MEMxE5k7A8lZicOXitYCblLtRLgr7w0JfXty7x+rRHE7VJfHw4b96YoD/nfrmGlyasS1oQnONMoLnpMWkUVg94jFjbgxGlrpI6XLxKmDy+PREtXlLon3nYnnDyZoFlLl7RWScEAC5+NIGdcHzAdYXohgmHuSK3exZxORN+KA+7B7j+kUWIKN8ECR/3JZav8O/1TaoDIpi9GAhVzDfRnEvIFcHs8b57H8YgZxWjkOuAp/9Ww8wC9t6boL3m6371BhC+N8fil7O873jk0FyUl5rruB3Xe4Teo3miMB6n5Q3B/sPvBNz7M94+SpUAZ/quFG4xgAMF8LVlvougLFVASkTlrShTm8DGsSBiYVcWFBb8ttrSObW9gFrJrbJ4LkVPx0vgGt2pvD15L76VCErCdwoifgKAkPzd9gJytVk45xoW9s3nqLhvIYoCAxUoq2E2c7+lm2mmBDlGuLaqJwtmKgcYvGQXsaR9Uo5HQXB/x9u3VRqP9B3gBy4JGXvNnovtIygsjhuLG3FGxsRyeH6gAW+KBwEAZj/ALG7fNwzsItgJZTBaOlc7KazjtucydmEia3jFQ+I1l8anrIWZ8uQWBKE5HjDuz+J5hEjOS7CHMWhBKha/Af6A419Ce2jtYHwPrwXsgY19lc91A8wswEQR5MSGZg49Xj+9xHufTso1OB5hKqSa72OMZmr5eIOAPuRJ21kByG/oZEFNVMfaxlgAIKUQrIXYmyGsVoV8N31frTZ/Yx3Xinifg6d0sM/BTGMYgwDGaQCAPms4rRiXAbnN9D0eC10DOV9nklwYC3UzgtYjLzFmfOH6TwdWFKt0K+WygXB9PN4yp+bUszlmSY08BnT12RI0X0IJkT/Tv6tnc3SdhJrHwKv1gEBOTSZTCxOp/Cy68zgJ3kQltuhZZD3TSQesR+y9b6FvIoYlBTQloe1kDgSqVYPmgr2utlJRl4ODejYHrW4zn/WfdjweQJWS7DJuIXkbbk4QY8jpTLkWzL4dAvbejxiHqCSeAoH5+CuJ/vz2UsK1hObKwXUC+qyIe+69z8rs7VPeNj1QGxIHid2bPBeVtReE7pLbtx1nUygA6qesFAYga480C4/mRsfrUPppo0frI63/5Io9BzvlfWcfDTk9W9veexPYiUR7GTKk/+AtiQ+uXsXhb8p+436P5rpMAC5KS7hWw+wF7J0TzBPG3GgH0HD39cm9mixq28BVAJtew2hycRjF7zSazd+EwBDmyrMIWjE2Qal8Q2dw13LgCSY+3D62CWDjWBAi4yeSUQBPQgLZo1HXQ2kzmff5oaflkAefVusMtEnHEssBwRjQap0/U7/Eas0FYanOw7NwMFkPPbclbJ3X8pSLzTgzEScK6zOrle/YQ2suR8hFrMepJgu51pwZiuebJh25rnAd69jf8bZ+Zh4PlJuumajSL5/Eh9nDSMdWCxc1PhSaS243NIKXDj5seaANmuvbmSunBUsvNCL3AQCay463RXCbWs5Anicir0VeCggbWAph8Fk2gKUTBbwmTD8OWVIwUQLIlcss3Grlc9o2kxDFatpmwXU7GcJ9uS6YmMra6x5qFXL8BQCmTxwoCEyelJeEXtAGliJ5Xq4BbpRAexEgxhobc+tQL7RdNmRnO9vZnexeeRa1irqYTjnQGd+0Prrn/vETqO9+B+ImBqoOZhAXV6D9PciUSXCOsxnzAdQ2eRniP/g4t+/+/Y8BsLsfiDC8MtvQDZmMBuFwD7AO8pqXLOFwD3Ae9rDPa99mMLAzDdHHdeITLgi6/E//Bu2lZYXz+PIzM4XlA9bM2PtogvUht9E/meHqew0QgIfzRwCAxRsn6B7vYTxs0TwbYI4YJty9pzC8foL1kUL3LK5/49vZ7DdYPCqXdP/9NVP+XQesXoq6JkkWsOUSdbPPS7/+/7Ev++Q/fB/tJS+lhIlVp5rX8mm9vnpA6M56kK8KyQIjCmcfTvNypfBYBFx9b4LugrcPx3ze632B6ZMo8BPfgGZGGyXqw5FAd+Gx94slPv6PxwA41iEivqBWJFt826H/uN/IRFBgWcPuvIXtgZMjHl9ywMUbCmYGnL7JYzB/ian7Eq3edon6eAh0UXckUfw9+qcBy/96iQ/figWPTYDvPJrzBvYPol7NVYOgmDdFH/Igtq2FEh5nlxNgrqFOeCm0/EmlG5JK1ImDmebQ4+Atmcfsoz93+NMf/xx/97MfIqWqpidLLJ5OMtxbTNlL6ScjrJE4e62HPuU+OCvh//dXSKv3dRlpxWXoaQmQ5AoB+FkHkZYLs56V0qc9RJxQgpAIXQssVP6s2wCA9RG7iGQ6gAjDsYIwIVdtThoNe9AxXX4+VgdYj/GogU3KYpcdhmMNdckPs4hB0eUjgSAV5LoQ3ox7AotXIqx5VBhO0oOmMX+NkYh+xjGN5amCMB2GIwXhAoaTmC151mN1qjEcExCimzukak6J5cvFLW/mGrYjBNlg+SBVuMZofiegBsniPwAmsa5m8VqAjUFLuebUW+KfVDF4OLzs4DoJsiy8A/BDydBjDbUu2ZTElLV8SWRXnEWKgPVhyEHTVO077gPNNUHGytXVQ5ZEnHzcYvHtyH2x50CjABmC730GYH33B5/infYREJmyASB4gtAe81kHv2fRPYvX3QKLb3ngZI3Fk66c+76HGAi+C1DXxfH2TYB/OMI1PE52n9sf3tH4bz/8X/jv5r8AAKbtiON+iV8/PsV//sHPAQBvXb6MqRphg8AfHr0PAMxwRSP+8eb7eOfmBH908h4A4K/f/RPoa2YXT0TCQXDW4/XTS3xw9Woesz/98c/xV9/+e/xFINjIr/LHR7/G35z+CEp4WC/w+vQZj03/FBd2ir998gb+7OE/AwDOzAz/s6tmxN9i93ayCDGVV/6uCsmWayDHGtYI1oGGdSG3CR60HBBGkz+322gvIm/EnAvJunMFsiGTysI6LtYaS7CV1ga0XKM5V9AxiyBulujPGoibGDiLx5p+6tFcu1xMBYBVtoIECOjPLYSNxUiXFtOPNUvnxfVqd+mgFhYtAXJh0CYE52jRXjnIUaA7jyxJMWAo1gqgEkPoz8a8Xp/G/jbxN7oRoNHzb4Ccqp69T9BRJpBh0pz7t5cllSqNRHPJ691Usk2ePYv2skJwRj4M8gGTxxLtVbqe0Su7Ql5vp7X1eEloFiV1KAeB7tJDXQ2YfsCvc9uLjF7MBMsA3jUvo3/MGh01rR4AlhPsG3QXMc7jAqYfSKxvOvTPkgdEsBNZPItlvfYXWF906M94m51Er/Bshf/xiz/H8EsuGls2AY8nHs2ZZKUwALjWCIo5Mn5xyMplXc/XYTlvERYK7x6zZzL5hGs9vESOJwQFLH45w3ufTnD4mzJmf/ezH+IvAuHvf/GDTH7z04NXsTqbIPFZ/HTCZPttbzCuFXDW4q9OoxdkBM5WP8Fd7d5OFgBwqzjshftxEVYOcN7ld8/xvihJAmz8HQp5zt09ttKPgsMpkNzA/yX3mULZlgvJEiVf3K9myr7zuHxB24BRp/+w+bndLwqb23lbHE+/2Q5VNRKfy8Lm93ysjWvGxyvAMmSXfGN862uQx/MLgsUClWu8cS2rfm/dmiHBinwM6vqqv55j8vl+edF9lzyKSooghC92DnexXYBzZzvb2Z3sfnsWFaCp1g3JgKu0D0WVrVSM5gPjJaQsn1UbQHFflWDYtWuYhTuzeyevYpvur9HwXdHx0I2G7RV0ZOVOxyo6Gb4AjDrKOhteUwZQNZIYSRiQ5RJdQ0h8DYEAl8BTnvkxzJSgVpEPI0bC7FRinNXAMAXXcml0AjQlXIRrJaRwsNNN3ZBxr7i/otYNmRISpMFOefnhZYDr4sECBw29JsiKezMQQ7MZtxDTeC0AAsZ9yuLDifk7MYklCr9xnyANwTcKNmKPzF6AHAlkAN+GvNSgoxFm0fGf1QvWtwFkBOws5GvhZYCdArZHjqWM+wQz4xJ812KTsFcD45HPgDUzK2P8xslT/N+DSOPVeMjewowdTk44MH4up1CKyVQfHt0AKOzeb4tTLHSHl44Z9XrRTUE2ekYRyBWIkZl0PGLc7/OYTU+W+OOjX+OnB69mj+L102d425/mfu9POY53MllgsBof4AjfengBAFgajXN1d4j7/Z0stti9a7LdmoMTzgHe8bYqZpHJcyqAV91GjtiPFkQEtXIQoy8uuItcktXvKX5PvAcAgNFArWypTE2EvUsmgpHG5xoQLZNmJefem4iCVINDc6N4JnQJ+OQhjGOSmdFBpf46Dzl46IXg46LELJQkNPMykaqVBVnmQEi595qPgUYPleotYnyouWLCXIBFfEJ8cMkXIl/XccaCXfw05oBeAHLwhTTGh0jEHdAsAlSEi+uENRCoOB+Q26ljFk4zB4MYLZqbeP09Izg5G1K4NsxZi+aKNieLwC+A5gYQjjLJMQKgb8AZikzKQxVh73bMghBIZMBTIey1eOvJS2jOIzJWS7hOorkUrGYOQFwrWB0AjywA9LSZQUqP1SVzZn4UmJDmYB4iH0UBpgVBaC4kjG/RXBdOisXTCf7m9Ecco4j2tj+FOesRiHlUzpb8ErvqOzgrgbMWH4BJg70RGO3vIPnNLXseHDxrhdxhdVXpihQ6/PySQtLWJEvFkxHEHAGfo49coMZ/bnyvCrPSd4rH5X6VdXeQlc6pIHwV3AQvtOpBy4VKlKDNZZ+EXtwoOktFS6lsveJPDtXvv+iyelMKAFmntN6eJoqsh1LFOQMVb6EWHf6y/CCiUkALhIpDongGgcKGZyuSZADPpsWJjv0MssQfXlgERiwHsK1XGmK7AaG+zb+0fXMni+fpfdaexW+zKtKU2YLqcfe+cFH4annzOfvIFbDx4UkBv5ghyIHA9D2gHCtUOIVI+Zf2/e0ltV/C6kBkDBYmfZA6QJu1WXNQuQTkUmFWGq+kn7qtG/J5bTvwmvuwFXgNQLmmgR+8FAx9Lt/Fl9SO9aF4N2nM+BhUtgXauG7eU6VHSsWJTufj6n694EkPgPX1Gy71gWtyqWr3q4iJfyMniw3hoFwKXscxBDNoCSqf220kvYxYku61YJc1rVOTZ+FFVWJeSqx9LmWX/D2XzJeYhNdi48HwmrKCl1cElxS2KmandCyvKbM7BSU2RIK47dKHTBnfiLz252PEQrKBcmoyeVFeCabyj7GQ9NbzbYkfsGZoVO5qSym4axmkBM/buWFOrXpFmRAH1STsmtKHBMByLW3AkVPbzgDpAXFtHAtZxs610SOQyFIEAOAnDq4V0eMoLoVvA9ySclupv67lqsy6P7aLJUUaG0JFrgFcH/L52q6M8cl0iQ96XnKEJiC0Hm4l0ESd0dEQq5mHoj06iezeZlSwnjILt296psITyMQ1QXA/fe/gWp3PQUwtXp8+y+lRgGMUZ0udQ23NxOTtaytxs1DYm/F6chzV5xIZ2mVDdraznd3J7q9nsUV+88JsiBAxKU3VwiyU7emzagNAflOn3zGJSnnT5fbqxR6xpxK0yFWSkPF78mzisVzkUPS+tOEV5WxL8g4A9m58zH5kLkfJ3lNIhDnJk6HCMZn6kCHcmjZVxTUXOgUt8vbkUSXymo3zReU18Eawvgdv8zEG4Vs+P/Kh7Bt4vySXGH+dr5nTxWtL3oBrK48i6aC2BDemX8W/m4AgZdFIbQN7cFRprQIQEwvXqs3YUwjwbYheXZEkTPqrvineFnsayO2Kqp4r6aImzyJlgbwWeGl6jd/0D3lD4yE7B7eU2J/wG/xylJCasyGHE4Za77cDOmkwH1rMPeGg532vk9ZsdesFwXwUYmrhWp3HoZ+M+G7/FG1fqsFOJgtc9V32LLazIYtph+PYh6XWHPO4o92vyaJm1o4IzVQvIg4PmOQmBM58xOwDGebjJOczSQ0A4OUHoNmUoeGJKKdrGe0pRXbdU9WlsMxALVNQcbGEiOnQTLTTNjCPDuBameHJbtZi3JdoWw1IgoxCR8JxRF9WDNGuLUQrch3y+lmuXeaAoFiHopZHkNcDVK8gFmvIWYQpz5dQq0O4RsFMqyWLBMxE8M0ch3HclzA9T4SZC6KTvIxqGMqdyGvcKyccG3EldVp0QWlDqlCMyEJCrqpGlyPL+WV6/8rUusvU9mrgvqx06ZdruT+25wBpqoy0E2AcCcNLk/zwkiWIEbcqJtdGQpvnLDlViNkTyiXxPO4SflUyJHYiYKee09pHDj4SIQmbJtFQJrcuwOuAm9cUpqYFxeMGEnDEmSTjYobEyHJN4ralaSAoYFhr+FHieuBZTy0CmvntpUHoI//FXsBNfHFYI3Fhp4zMjDZYzVmPNCbx+2A1/vDkfZzNpzjt+R5b6ga/+l3QOg1bEZlgbInS1HwXVYp0Q8t0GBGGNWipcxk6AMAHBOMLZ0CcdNTKghIdP1DSrul7PJa6HqLEHV8EOV+jvWwhhpj7S3wUi5DbTFanNtXKQsfUqRhcvkFSCjOlY8Xgymf8dzE4NDcezRX3L6VnhZG8/o43ZntpoVYCem4RJN/l+sawJ9WIDb1XcbUE+YDm+iD3JUOuR+SUJgDYayo3dHWZmkXYoKqvLY0Hf4/Q80ugu4iTTsPxkVSwlo+9JrRXAe3FOuuNpPSmMJVnBGA802gvbx0aYuSUp7CU+wCwfomwlEl8u2cKci0gRkDPVS4kI88eiJlJtAxRgDTsQU0fW/zq8YPMTsXkNxL6inDzmMEY6krBN9z3pyZec+2htIM566EWAjcRuPFoi64/9/WJghkE9s4JbRyzs9d6/O2TN4Cz4l59gKONv29iXdRi2uFsPsXykxnejPfuN1frdMs2lh0ALydSpqACWtXgq3qZEZQESRY3ziISgUli4AV8Im2J3oPtFaRwBWyVAF3AxrF8o+A6zqUDQNMwa1Wi40vFagk0lQBTwCZoyvZqAyiVtidwVAJ6+U5mIFj6d99JmInIBWRpqWImYkNO0PYCrhUgKzHWoCzBq4KA7gAAA09JREFUIDQpKYsEQUoE8hj3qXgWcf5zDWWwFMDFXqkmZKyOBwL6TsIPt2+rGkSWzns8ANQWUMtMKWqgpmMxGY3XEuM+75uAU1lmMJ3vqcF6Va3D8rgzmMrMeFyTJRBWAqaNe8y2JdcE24cNvVTfAObAsxwlADsL0RMS+MGjp/j5Yy4ADE0AGo8gFPYe8Rv8Rk8hGr4PHhzxtok2mDVr/AoPMPZNkRSMAkDbNh476MM1zJNp9rr06Qp/9vCfc60HAHzr4UXGUQDIwczjyQqn/RxvGonvPeTK6KVpcKZuT+wvsl2Ac2c729md7N56Fs+15yWNPyORHBJku7aKY6H+HUWlr42c+/ZvQ6gwA1s4jSiok4wcbrXHGhEox6u+iy2wV1In2/is/q3GBzC2IOlQhAzg2ihGqzAOIZ2rCxsq5ACiBkbpb+731vai7PWcc37OtaAKN1D/NvcrFnyJqKORtgtXziPrcJjSpw3AkqFbcQwgxjiyvka1VLWlrdQHsqmvFVYj9d9QiZukax4C5mPL4D0gBlcZzDcmLlJD8DHwPWy5/c5KwJR9mxeohJElOCuYCi+lsK3EmZnBmzIIS6M3/k7tLrXGUjdwVmJpmrLv50DIfXMmi1qycDtDsb0NwEa1aAJpVaCtIDZ/l9S0NtB8223WdSJVtL30sfyd6NXq9phKDeV41XdfYlJ5GxItP221k6ne03EDSJTzKDtic2JLp/G8mJZzkWsSpV/V5/b29N1Xd1A+5+fABdO/bbe7udMtfFFRQ499AyIGwm/2CQCgw8ayJLehOAvi9eb4sGRA1R+BkknZHiPidvI5EPLkNmvWCJHcOKgA6ICgApqGZ5a1DhCa78FO87a0DJHKwWmZ9/XyOeMCIMgAKRkpmiZSqRxO9Ty3ndqt/07tTrSBoAAhPFrJ26wXEJ8DIUfbgcSvw4joKYAFgLOvuy//ynaK3Tn/Pth9Puc/CCE8uMuO92KyAAAi+qcQwr/7uvvxr2m7c/79sN+Vc94FOHe2s53dyXaTxc52trM72X2aLP7y6+7A12C7c/79sN+Jc743MYud7Wxn99vuk2exs53t7B7bbrLY2c52difbTRY729nO7mS7yWJnO9vZnWw3WexsZzu7k/1/NPjAjD8+tQ0AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.979199171066284 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-06, 'kernel_type': 'size'} is: \n",
+      "[[3.200e-17 1.600e-17 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.600e-17 3.200e-17 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 3.200e-17 ... 3.200e-17 3.200e-17 3.200e-17]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 3.200e-17 ... 3.232e-15 3.128e-15 3.200e-15]\n",
+      " [0.000e+00 0.000e+00 3.200e-17 ... 3.128e-15 3.030e-15 3.092e-15]\n",
+      " [0.000e+00 0.000e+00 3.200e-17 ... 3.200e-15 3.092e-15 3.184e-15]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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94ief7SWS+SbAbXeieZlnzYc0IyKky/W+03oWCn6VHB2cRznKUa4ld0OzwD5MmGOS1fJAEhLHOF0d1fbLajdfZ7Us9qCbZAByMS96Oa5hwpuKSVE+CJyxkGZ2IBJnF4xtPzGtBgN1vkXZy8BkY37oh8QA1BSM5phoQKRYhpTt7GGY7KpvDExSBynZK8xg8XOzNeM/CNlUOpDd+dao22QSutigUPmAZmGPld+kusPHavJyNicOgan0XNa0AKvhWc2ovC9vOupV7sZiwfl/xs5UPgpF7U1AWjEKjgI26oFiegAowC1rZ1LbVny/picP+l0zUdvi02dTkFe+lzs5ER+HLgTjCGqb6sAr2ax+37lqfArc99N8kMUChNoHt1oi9UMBhik4Le06uOUC/uH9+rIVJ60BfQEVXxBjdbapOaPwZbVpkziDabWsWBDrF7K5EouFLF56HBAwaYzg9bo8GytusQD3xvcDwH/w2PhQss2ukS577xjF32EjVvNIEwBatAWnMLl3IyYtLTzS8xf1/NVSHJx5Q/IfPJZx0vdDF3MFf+nCB0h0IoO8+OykmgzqxG7GYlJMgGImEsSOJEIRUznO680e3J0B+G9+JNcezTvlHXi5qP4SYOLE1XNKu77xIdyur34TAPj2Vx6UVQdsEvWYnJNBRrPJKv9Q1UL0pewxs+15z4HIMcoqPwwTjz/HVIAwum8U0NQskawgCGMCu/xQLR+CgqP6ofhCJglanKTtc5Sidn+2S5boQsyayTCIj0bbnkFV1ASAHXizPcjvYKMUpG3DNDKhvBGHnNIJmESVALGBJ4lZjsADpr4Bs2iwhgiv4mzouoNtl71INqOJ1jk7xrtdXYjaZrpoZkdtdXBmv0gIwLMXExi4AK0iSH0sdjwm5EZUo1qqde26gxBslyNBcL6Gpi93wDpM+zRPgDPoYTo7rUA06PO6fs7Nl3KxsBGOCZ7CslopQk5xGCozxiTMNYuiMQwHNQt4P8n840E0C52EqrG4xeKVmgVmmkVh1lJPd46wUN4pCux914HatuI4gLrIWRwHUBxoZDAdjDoxxRlYzydi4GQFukKzUPMCTQtSs8j+PsaKEpxJGQ8dRwB0spqQ/ZSFZx5GZxYn4Emo97xCs5ijGZH7qykB0EmHqlnoMVqtZPKnlBcL1dwqrJz0+tkxDmbw+SncTLOg8c00C7y4qONs+3B+JtdQKHju7000C4GGNxXyzww8+7JFQ1RekXU6wV0YG+1KzeJAhumhzMqbahbo+zrhgIrH4JyxqHF8nYy3pVkAr8ZxaLtnIVIwi18movhptA0CEBrfmWYxnxQWyzH9ccJ80b0NzSJdrjP8m2XSzc28uYbgSCbmNty+ZvH8xb4fgtONNAu32YoZZTeUeH1/zTEacpSjHOVacqc0i1elqCvuwj1+NE0J1lV4thpT21aTIq+8/oNH2Xk6ID59NjmfI/Kqba4zX+EVyGN2dIWAcyc7gmI9xk8+y7+xmkXVEDhx9TMcyNQsWoUqN7F+X5CTExMi9/VQ8henuqv3/dR5p2bThx+Adx3Ss33sg5xg8A9We7gm+c0EiauBqIUpAaEOWpv5qWPjHWi5FBwEcBgDAUxRrXtf5oiZ3XVnx5x3cm2PqaOYdOePtR/5GdDjh0jf+2Sa3Dj3bxh5U/IbnGQz6P49sDq7v/N7Nya/Kf1+A7lTi8UXKnYyGMDUxNP+ptedq/X2mleFub5omZkg5a7OTV+W2QvL1vQAKslLSnglh8YtyJTBi2tINI3757wLUiEbClazVI+zmpXGrI1xgpa8VTFtoQMpENe6xKgmD8q1bhJRvVuLhY07z+RVuItDUnZYC7XN8f63j6vPeBTm93gXYhcsK3YRySFezdlQsVpIuVw/vN0i+iYya6u2qfgNrLyDRXiilXlnqAVi+b6I8lYcot2/DdHxGIap1nMDIe/AQwLSm3kf7tRiMYlmNG1VSYHi1IsvXwpxjca72xap66a1RDJ0m/t+kithTY/w0dfkuoo7OFlNkmz44lLwBONocBqCp6Cz0wn5CZ2dFo96eiG4kPD7flAiGwachRDASzGPaLOrsOhdB753JhPiibSRzs8EoNU00g/FSazXAqk24d8C5AkBOFnV8Vxv5OUfx5KxqbkRGt0ozNbPngMA3Ld+pEZkTL4Bgi+RC142cLtB2mvZroYRtOv3TUPFIqjzV3MmiEBbxafkFzh42a1VrV80oG4Av3gJ9+M/Kr8PEoWgyOUzAMSzBfxmEAdu2T0BOIC6CHiCv1CiG0a6dwJuPMKTCznUBOmPbgbzqEIbQNs85hqd+vwZdj/7b6J9uqtj5QiuGzGey7vn+gQmsWbiQrNOqXznhoTxVK63+L1LOH1nVGshQjpZIC0DwpPLMmbxj/4EuocNFs+G7EEG4sLB72pCHDcyEMkTXGS4XURa+vJ8+R9fvxrg0cF5lKMc5VpypzSLuXDiw3U9JmnYsaYhF2o8V2qJYDjMVl14I3JmZElSsiAVTlOTSE2YzKoMiDZE291eqJY32wz5NeZCSsVHwP1QYdFjFE2DDb2u7mpqOpnwGA+D2PC6U9sUbNv+rhNGKkMNqEjT4hhTzUC1E6V1y+2Fc5nXwuAZhjGn06faTgX42GxaEyamXV/vYVTqYrYV9X+GfO2Fwo/7Hu5yU9puUYx6PRqiaCG+4l3AwhdRnoMJh9J6V3AsAEDbXUVwZo2siPfCw6HvjWp62x0Wn23gLgytXvBAP6DZ5euaVH2v703jy3EaIlwnWohmkLKj6g9xDv5ZDxc86HJTxqz5fAMalvCXNUUgOAfqx6pZBJN1OkTRGlWzY5Zj15Q7vVhMKoVNvqD6MjgFI5kX5CZ2pHrhbRq5Sia/KY63G+SIEBGYHIBqSk3SzL2bfnaUVWbDkanp17M2kSIwb0ssyY0dFwuactmvYElmACBSBRjp5exv7LVu6t5RX4sjFF4dopq+koFOcK62ISXJUUliItSRjLVNhQv1hu1RmY0T+wwws6aQYkP0mAM0T2SCL3EOrO+MTTs/8E6zpuKb33NOZ2dPILsOHPJv3VDu9GIxkQJEmaI1yWfEXJjyOxQEpOWasPQE2bbnnfAu0molE1Mx+tvKT8BjhSS7xQJYLSU3APLM6fSkvhf6gM9Pp/Y7ADShMiKtt5VJadeDzzJXQ/Yp8LIV23TRgrq+7mR5Z6Dloiad6Q7VNOCTZe3jxVpeumEo/dXrkCJZG22DXCs9OgftlESo7t7s606YVg3cVnwW3NZXiIac4GfBdTrBz1YyHrlvIAJOVwV9WHgXFLFa/COt/C4x0gNhtuYmL6IJgK+TYDxv4dczfgzIBHK7EQgO7sWm9CndP0FqPYJqbWcn9drOTXZd9gReNHCbvrYBgIsRmx9YYbHQHBlC8g5+N2K4J9qC76IsYiw+BWDus2CMp/L7VeQKVtN3kQjx8RnSwqP5vC1jtvvmGXaPApZP6zOIrUPY1nYn9VkEghsZYTtiXOV3IDHS735ZEZyvktfEhm1yWFH/Felp0I9F5ki/lPJ/dfcjoglaE8jhshjLzq51LnkWySmq78wMqRDiaRiuaEOaUJUM+tJKIfSN4HktTKIp8UlKkssSY72vmgb6eRYZcWMyaFJV3dNkEaDRhBSjDX/Owsp2N7PmUWJpAXNpl2ZWso5dybYd5ZwYAb0vkSxczGBTDsH1CTQkwFN5PsQQkp6UwHPNIXI1ifK9CMiLBU8cnJSy9qAmixlj17OMGwBOBAfADQmuVzPDjJ++CiyOWTewnDu4Og7ZKWsXXeryQqzjgbrQ0Mh1/EiOIyu1OhCUCG5IoD7Bu2oO0uz1epXc3cXCESas2EazmGY77qv4Jc1czQv9rR2ZYldnNT94WSjUhtcMzpgAnydJCPK7bArodchVshVWUpQm5IlasyU5+Hr90fhYQpIdmhnOcDSSeuV9MtGC3AbHoDFfV/sUwiSjsLSLuarlOl5qyqimoYtG42tKtE58omr7AtJWImBM4KX6PNRvMBYtgVQPZjELSk2OPAaSlJf9LkazmCzQ6ofxHryo9j6iTLZk2hsXHhQT2Luyc+uC4IiQggMNyosZwY1DXAb48swpaxZUfTXaZ0/gNpSFsmgWzmFcOTRNjXLE1gGRixYBgomG5J2+lYMcGOyAuKR8XMokIDiA8tgEB248uHWT3I+4cBhXhLB15SVILQn2L98v5XFIDcE7AiUuERlKvJdF/yo5RkOOcpSjXEvuhmZBOVvSIAjVBNCq3BbibaHDSqnHXSdUeADQ94KpYBYKvAOAHp4R0/J2V52dyD4Nu5tDVPV4uQZtNuU8jlGiIcXLnv/97CmUj/MQDZxtEQPC6swJyHiICUkL0YQUB9ud9O8AYa91nCZbLOj5NEIxT0rS2q/+Ox9PB0ozHE0/SPsRDWGvtuVkWXdkHfeuF7+LXnIjfqL09Nke98UeYS8REgthr/+d/LqamhjeaJSBSEwvo+mBudQ5cTECD+7JdRPDDyPCZzWik54+q6bfAdj0pG35vrEfcP8fNTVKAsj7Mo5obTEkHQ8Tsat4jgH8KNPqaeTKuQkGJT15Bp+zZ3XMTvoBJzY7Vu+RcUYT8CBR4cpoTJqAW7++bnDp1rXPfNeiNPwHxJYmLFl2RKa4TXptKYBSAcwAv8hewzvwop3CeZ27WSkAvafNNFSn3xyBmcFAqqIjeBRgDleSGsrXsynfE9v2iyDsnWRJujp5bJQjU8uX9qYkJkATwMus6g/6XGZONB3v3e5mpQDOT6WtJZMyt0nfE+/El9OEajal7LzN/U3n4kim/M6kxpewJ1k+ixsQ9sYP79fQqcvmyravDuziW6oO9NQGMYW8h+sGDI+kXX4rACtuXDGPODg4dXIbwl5+cI7x/hJuO05MRxpTjoYw2Nexcm3zFSDsPUSrlwlsD9LqTZKSUl0UFJ14HVo9feicit+C8/VUaIzC8q0Pwl1/YNnS+s85G3QHtMlf2RladuBFW39nrsUxyeJ0WzLG6U44UuVoMP1A4gluRB22NMaau6A1PPqh4hcAmdRENw//DiYCVnJGjEOXBf3JzKCBSh/sgu8uMlYjca7v4Uok6E3D0dSPFZ2aCZBojFUztc9R67AMEZSS+EDGCJ8xGe4yv2/egbr9yM5ExgjXR7jelNjMTlAaZXGkVDWLt5U7sljcUOZRhMRgxKr+Kk8AX103ZAItJwaPOS8gOzMrXb35rWXyfk3dEKhZA0zMEDZENTZzkxMDKU5JeZyr5QsN/RyPt1y+cFKLw2ggxuTQXZaiqY2Rcu1TnSScoyXMk2rjFF25143KF+pmYIo2kasLB+V2CDlRbYNlwCINUadcMlALE2nfbX9n781VdUP8i3UFu2XtlIcBtJ26BIuJhOws19oi4whXIk25LclV2H3wwrVB07oh/uUl/JBrgdhExkNmiPbPgheBY/nCoxzlKF+83FnNgl6lpprCMuQ92I3iaLMUa6/xWRRVPtunahLYojmCCjXs0f765QuxWtbV/lAJQOuzYAaaKWFwsSu1iJIeZwZCuD2fxelJvV6q/hxxQhv8hGI6sg1ewsSu+jYKchOYZpLq98PqZj4LLTLkjB/FwL05J6GVxDegajvaT33ueYflJpQdU5zaN/dZpAdnoHUeXyJ5dv1g/Dl1PEv5wsaLbyH7ftI9cWy7tZghbHd/7+HOTg/6LNLZUswVY8VTLk41rYBGmXbwy+6z4Pw/M3m0vGBh9zZZqLyr9GllMUiM9Pnn5ZLu5KQ4A3XSWOIaVRv14ZfJlx9SvFwfZvc+EyebPgRqgjhLL9eAc3CUEZQ5d2OiZjcBaPJk7rqaubjrQCcyEdKzZ6X9mk3L41gne9eBFgu487NqC+dxIWsqAPJyqANYj6uZoYtFvq4/OZFIjsmynajchq6NFotars++1DFKVMkCv7QtpycV5KQ4i5OT6mgmmrzYk4UzJvhxNc3LyOq2LZ9IaIF+mOAjpI1OokkhlKxeuf9KxvdSImP04H7Gt7AgbdUM0KrvQPUjBA8OHu70BDym6hfJIDZk5yUgk5dnfgcak0zgfgCNEe5lNrGevhBzdNYF/uCRPLdla8CHCRjTtNZp28j4z60L7zB8dB/h5Q6pNTiX713fuLgbi8UNRZhVDy3wAAAgAElEQVSo0+QzNaGE/wCUkBSFYEreZ4RhSuL1B6oDdbWUHU0f8GZToy72XjCTENnhWIBSVHYROjmR1HJLNGNSyNkZLYCoePqRF0dtD62Wkri2kkWIx1E+r5b74VWTAi992MlESUkcpoCkq1snqxZk3oo9y48fmuvWKIPu2gDAqwVoq556M1l1whxwMOt4AKjlEM5PKgTcpKjbYtRogkzQcZQ0/nysJLKZUHE8X8KvTQgzCwcnqeVNmBD68j2pnqYExXy6EvBTSrLzm82LvQC2JnBvItDFFt3Xz9Ao5NpLfoqkqMtC6PpY+sdt/tfJeX47gsaE1Mo4tlq8eCbjfWmbv+wKDH18sEL/sEVr4N5p6eF2U5i6tNchLjzYE6KmqDOQwldhsbCIzb3vLCozf7bHkM2YnGQ2oTLTxBtT30NuJ4jGgsy0yWX2XkoBb5OigqW4q7h+GmcJXwZhSTbZyft6XCe6tjGbPpPwbj5/spvle074JQpdPU/vm/8jkwtTxq8JBUZeojXeFWQlkCeKVvg29+PcF/gDIe88HqWdep1RxyBHSEKuyRL13h4IEgovmlhGWZJzNTQIQT+6fl+tLip/4+Gsw68J8l2o102tB0VFctp+SZhVJ6qiWDl4xIVDUHRpXgSIgbQwbcntjJPzAEoe5Kicy8EfLCqUWmmb63zRutLCY1w6NK1ZMBd+AmHXxSA1DnFJcIOvi4VlzbqGHB2cRznKUa4ld1ezOEStl/ktCk0+UMOW/fQ3PArnAg9jLXtneBA4M1sVnwUw8VmUa+rnfC9qQikoBED8EptdVbH19y8vDvssst3NXVd8KWyrYKtKvN6IzyLGHKKM9fvLtYQJrYOTCBh8NSEg46QlEIuqvetq2xNPQ8ScQE+e1zZc4bNw2+v5LCaitPlA6bcbY8W7KJbDOn2RtZuUpC9PhM2LrvBZtJe7wxgb7wRFGoKgGLNQdvyqz8J5B5ffEW6bihfJ4+uB2gflzIgRJ7/9slYkUyd2jHAvc4ax8Vk0Jg+lYiJidYY+ewk+wIXaNEHuaUyUdjcgPF8W7AgANG0zHQNfNbd4toC/7NC29Zlrstt15O4uFnMzxBEoZ73Y6INNRZ+wHLdNBTBZZ+jMZ0HZZ0GnJ3Jc4+DbXY2Y2HstFvKyqiq92Ym/IcXq3AJA987FqWa5L00KOV2saxGaEID75/n4RWmPA8Q3sd1JdAWQCXJ2Ctw/n/oWsl+BFzUaQttO1NphFF8GAHqpZkhuq/ZxuxNb/fGDsqCVNHE/TWBKJ4vqVJvT6nl/2Geh4wGUfqf7pwZ45CSSoDR5ms3qhbSFNjvwafb35DTyCUIRwHhviXB5wGeRfQ3ceIF86/FH9+VY/jt+cE/MksiIJwFuq+Q1QiLDjopPhNuAFBz8RYftv36OxdPMTK++iC6WFHWXKf2AfTMkbCNoSMUMWfBhQt7+o3tIrUO46Es+5HjWYPeowerz+szHVUDY1t9bM6S/57F4vsC4yu94BNJvfVl9FnYnmyM6hxGkrE+JX69Z7DrRAIahZjtaINMbaha4XBdfAgDRKFKsTFaDCQXepmZxiHjYO1nICmCoB5yXnWpzReg0t5c3WyAluAz8kcdxy5pFP1ReEsvIZYsK5fty1xek5W1pFl59UpwZrQyrlvpUCogpeDjvQJcbnDDfvmbxvexn6vryDrvV4kaaxWLRSK3TRsPK+IpoFjO5kjXrVZJZkwqV3QHH0c2v6fbht+qUfBMI81u1xZgTh8ZHsRHJOCv1eGbxsiUDr6wIdltCM+ezMk5Z1mz9/k2e/xu2SaIfhp3KDovFmswrwL2LthG9uafRz9p6w+vcqcViUmRotroq3sB/+Bjx08+q7yET3Oi/RbwvO5XmktgiQ8rCrZDrlAvkKB8FUqwAK3MvRwq2qqYNVIMB4B5LkaH4+RPMyxeKDyHjO2ICuvzwYjS5H/Jv0kzWmIvO2O87qXc65Qd1ABjMs51Vf6caxG6aZagLhHtwH+h7pJcXry9faGDa1y1fSLyuWl3u9+Rd1QVsVr90wuKen9khKDaAKVvaXBTEZcsMjuPkmGvaCoJTPtHcLylJmKR6PCA7NhH4wT3g488Oly/U6M0ryheW8XpN+UKvIe6zkxqJ+/RzuBD2NQk7BiblwD+8P+GPBXCEex/lKEf54uVOaRbFDkbWMsyKqyt3/ORT+MePauLOcgHe7gRVqPZ4tmVT1wkyM1+jlBRErusBsdWJSDgzre342VO5dkoT4JZU8z6pDs6XF+K8y/fQEnv04z8M2vY1UxMALxqkM3FUuhcb8Co7Hdc7xEcCOPK//Ymc/PiB8HQuhIuTF9kR+fwl8PC+8HBq9WwFSy2akoINAP75pajT3QC+Jw5d9zJXEc8JVHrd9D3hC4l/6FtSEwQoKEP2hNgGuIwxGM5ahLXwhMSF9awLErHgPwxsPD66B5cBWOlE+j22AeGlcnBS6QN1Ayg7ONNJK87Jz59h/MPfkmMLcUJK3ZCq2XQPG7QvRmF/MiYaB4ewHpFah/aTXDGdGf3XThFbh+V3xWcxni/ArQONcl2y9rwjjCuPsNbaJ7LPtr/zFJ/8mR/H2cfZ+RsIKRDCJqF7KO9I2HEhFR6VESsQmIBmy/A9ozuXE+7/yy1cL9m6ZGgEN4+XGFcOq493Zcye/8k/gM1HDqcf13YOK0KzqX+nJr+XjdQNadaM4TSbzREY/45JD3iN3KnFYk84AYZjsYhVs3Kq9BTHX6tTX1n/0qAfmVwh1yVr3ui9rG9gEFr6AjAaRvHyq/NOEZzbXqIV5t7yDucHZdXWYZQJan1N2ZGrtPslBRqQyTjGEl0oICrmCegIu04iQMMA2hiHLCCAMeXoRDV//GUnVPLalwxqoyGW9gVA0rJjjVoQC638xJOfZLFBYlko8ndul02f3VgXPIXPD3FC2OuSlBHgfihkvK6P4hBW34ImXBIhXPal0E9+kAADrh/hOlcRtYkRLgfQwpc2h5f8SsJe1+8T9mLXYfU0oXmRzbzgZLEwpLm+SxmABYSlRieEoZxGhu8TKMr1/G4EDVFyRgy3avu8Q9h6hJe7MmaL5yPYB7Qva2Z12Dr4bSzmlBL2ciC4QQh7w7YS9rrx+l62u7tY7JWvS4e/09TquZ2XcQPl3/k1JklYeh5PCXcOpbbHaxL2xlQXMrXrlbBXbW7DBUHjzOdiyEwmRMJ6ncS3R9hr+RcsH2XhkHDS3phA6jRLqFEMMourQxnXEoq1ZDA3IOydQOf1eem9kReRmISD0tc2kI6vtqk8iwQKxpk68BsR9vouGcJeBrEsNL6TBcANxvdF5nosk9X1Ca7Pi2V+DyiHhgGAPQ4S9vouwXdC+GtyGuCHJCUBuBLypkSyKH1fEPZe9Z1SvVlH23Wub6IAk8zKkszkKluX4U+4sdhM06s+++pVn0Qt9LjmnQAVan6bRYxtGzX6Y9qreAjSzFwAQF5YciYokCe0jbbYRLG3EQdwoprVqsqn5rzk/Aw9Rkl2asmfySePcp1ScwY4uDlcR9iRIYnW2iWESTaYg4yP/oYAAoF9XthUEfKCJ7JlGXFVlIoAdnqtOgZSTwRg24AvIGpzdHAe5ShHuZbcXc0CmIbQLKJzToCru581Tw4lmFmdy/J1ElUOzDlfpNEm9DxBcObfN0EyNzVMplwDi6aqtLojBw9eZNBUjKZ0YBJORjZ7QRPEAemdUKQZlir2TgBYM9YmLNqC1ASyXyRX4VJHJiloTMFbGfGpGk1aNaBeHWBcigwrshEA0jLA7eS+mi1J7AEagd4+s6qR8CKAdlmtVntf/QNABbkpUlTNJUW5NgEpc3uKX0H8S0VbAaS4MHPJ/JSTxRlJfeal1JKC3iEtAuLCI5TyC04SxNRnYfrCQc7Xt0OLK/mmwXDmih+APRWn4nCezZDOydbPQDQ+CzDDDwwXCMNZzjp9FuAoFyVSi9gT4qqRosebSrMwnAX05w6+96VC27gkNB7FDNG2pECIC0LwVAoaUQTS9eks3m6xIKJvA7iAGAUjM/8UET0C8DcB/BCAbwP4s8z87KprXPteGodOKFRkAISchkgyOi2DdNuKnZv/rT/OHxX+rICt1UJsQUs6k0FDlaWbhI/iZFUXla4XCLdCpDOOIp0txZk5Gr/AImC8J9GQZkyIp7liVUyIZ/K5zeTa3AZxui7aSdQCFwDaBmnRFGdmSR1fthjv1yrqIZPTkPclSuLnRDG6uOQ4/nB/Ab/NL5Pa4cEhLXxB+/X3GrQv5WWPy/oK+c4jjKnWAlHTCkA8XZSJFnM0JC09gqrYGZYcl0H4KPO941kLf+nh19sCn45LWbhcZKmLkdfM3WOPRaCinsvzlYnZXEbE1tWKZezQ32+RFoTmhfRhvLeQrM0xgYOD76qpl/IkazMsW2HbqxdLrL/uQClHlbxMzGbpsHskjfC72p4xPx4OGe69YfgO6M9lrJZPArjL716o793uwxbDCcHFVRmzzYce62+SODWyjKeE5sIsTnmtTS2BRkZ76dCfZZxLrNGS68gXYYb8cWb+SWb+qfz3LwH4DWb+MQC/kf9+J0JzROCrT369HVd2RjfVZm7WqP3P8/s62n8SV7XvlpGMe0VnTI1Tpvo9k7YR2GebMUJmly/HXvObq0R9AfO22uvpQkGYLBrlXCf/cenTFzyepi12vDBr69442+OK0lSt7Iom7l0bs7+/4K7dhhny8wB+Nn/+FQD/C4D/+G0vOkHB2ZyIlMNG9phz4L4XxJ3+O7tGqbGZMzNpvRUzZjTRAs4RBxuGy5XJNeGMuw50sS4YEb2Xe7ERM8A6+WJEk3dM2nbwGvLsBoTnu8m5tMksz10vkQQliQGAfoDfdvuh034QbUL7mGud8jDAa7RhIzkM5HLoVM2mbJ4sPt/WkKGaUJT5HTRi0kvyk1T/rjgLGqK0VzUeE1UJL3dF49B9MLzgvVqnblbr1O2k1invOrRPch3YYoZIopSaY75r4DejOAxNlIZightSrkiWIwFjwuJZh7gMUrcVQLsbXxk6bQ/UOqWLNc6/E7H6PB93UpEsrEeEbZPHS94hMlXK4sKV0KUbGO2lXK952Zeqaq7P72JwOPm9lGudbsqYnX/3BL4PWD0di3aVGkLYplw8mqcVybr9Wqe+e3ehUwbwd0nKjP+3zPzLAD5i5u/l7z8G8NFb3mNfvKsVr5We33sgKT4gTbg52SlYy1xDWa/UNm4zB+asxgeRYeFWn0XbVq9630sWpfJdZiizAq4modMmVNMjpWpaxIR40gpOIt+a20bMizx5eEJqI9mlZQOxoKzTWhjZ51KCRFSzXU0iFFnzJvd7PGsLLT1iDn06h9RUrsvxpEHYDEBw1QxhhvMOfqhhT1ZTDuILKX3L94zBlRdwDsqCBWU5B2y2xXyRiSYvu8067R4EtF52YtVmtJRf2Eak1kmB5Pwsx5MGcenQZP9DXDWvB2Vlc6mAsl4ssHvk4PtshgRCCtKfnYKyOlcm77BSn0Ue9o4ROkZ/JseXT4Pc1xGSmt5EGO63GFfie9Ex6x547B4T3OiLO25YEdq1q+USlWq2kcLIzdpNQFkpXF/9eNvF4meY+btE9DUAf4+I/h/7JTNzXkj2hIh+EcAvAsASJ4dOOcpRjnKH5K0WC2b+bv73UyL6NQB/BMAnRPQNZv4eEX0DwKdX/PaXAfwyANyjR6/XhSygam6GALnOhpoLmYU5p3cfcnAWFX6MYobslAw274q1nRMzhLW6lXrvMxFsSdDSBKv1LqMveVJsxmfiHNk9s/kwRvh1J9EGVeHVYdoJCrQgPhWYYwh3yj2HoTgwAVQo+zhWEJHW3sgJRxodSXlMw/NdBT8ZjkvyvvhVmiEK3HqIxTOvf1NXWa0pZZgzs7BWa/VvyG4Z+qGU6NOKa4UuUM2QrpdrbivM2RuTyCI4XZ/gdyNScKUiGSWBoSOJaq99ozGhednBDU1BrIZNV/k93ZRoBt7B50pjMgihjPHpxxGLJ/l9yhR5fjPC9TlioiCpyGi1MPLCQetG+y4iZKey34hzlxsH12VHceOx+GSDZhkQnlyWMVt9egZwg8XzsYxB6wlhF6sZohpbdti6XcTC0Or54R2YIUR0CsAx80X+/CcA/OcAfh3ALwD4y/nfv/WG1y/OKQCVgWochYAm+wioaSRcuViURYSI5e+Uco7JAdatTP5KGykGxGdCfqMhMbrciMnBXM2QpgGdnIDOTyunZWIhotFz8ssYH53B7YaSXwEAqQ0S9XAyKVWt9usO/QenIGYscu5Gun8Ct+4kZLnpSgjRjRHpbCll79aZuOeqaMiTzNW56xHvS26If1GJdm00hDLPQ/fNM3lhgbx4iYMytdUMGU4DwibCxVTsXzAj7CLCM6PWKq9mShgfnZacE+03hxOE53mRfWU0pIcfR2y/Ic8sLggUZewVNg0A20ceyxcRyVMxTwQWDoRtQlw4rD7RMUvYfW2F8cThNN8rLf3royEvtYJ5joYMI57+eMD57+ZFIACxJbSXDbaPpA1hKwELSsBwou9CHqIdw3cBQ46GPEiAz2Felyu+syP09wOGE8LZ0pcxe/GjLS5/kHD6e03Z3cYVob0I1QxRa7gluD6gveRJNGT8zXdjhnwE4Ndy9CEA+OvM/HeI6B8C+FUi+gsAfhvAn33jO1zF06Dflc9TODczv94RPIFTHzqeKnxZtZebIvzS9DcFF5GP698UtXzhrF1jBBpf8iAAyGJ0RcrMFyJzCHCyEGWTB5Jk3Moimeo4Kh5jAqFnnh6XM2/WNh2vlKHMSSagThRi+SyLB5djTHq8wr4p4zRI09EBvOmg2jaU+zMXZjc9DjbvAFefyqQPGZ6un18p+bcHxwD1GOaf31DoCyGEeUu55x7zT7t/dwJhdqen4H6Ae/QAACZV1P29e5M8fd5upRBLrqLOuw7xyVMUboQZLwUA+Mw7ITfz5VxSx2Wm1afLykIE7xE//qTW6ABKTY/CLqUJWV/7sPzsYDjXHlPGbc71KvR7w7lY6OcAwDukz55U4JLlq2xMHVTlsOD9IkPKT1HAWNnMCR99WOHFWmRIozQ6NuoI1vJ/eiyK01a1IC12U0y8LAVI9emT/fKFtiiU+Zv7Af7rX8vjVUPQHHyd7EQoxaVtkaHNTv5OCelB1igVQ+KpmhaffJ77m9+bOS+E9hmoZuh2C/rR31cT4ojESbvrKxanbAqp9t0WKe4HpIe5XbluKTde6p4C4CaAPv5M7qk8JwDomx8hna2mtU5zzZJDVdTp5eWkhCIA/G+f/U286D+91qp9hHsf5ShHuZbcbbi3NUE0RJrixD+BtgH6HqSwYD19tRQMRdtUCLbdsc5zwZohsyUt21JZGxDMAoIXBKWppOVOToREV3EW6w3o9KRwOyblvnj8QH7HXDXAJpR6E7TpSik96nqk+1I20F3I79P9E9EmFuKAK+dm4lpHH+zjLAwhMDDFWZAWN5rjLFQTyTwc8Qc+qPgCk8hkE5vSIojTMDJ4YXbwQbJcC9DJ1vQ4XRRHosK2/aKFm+EstFxhyVBdtsIb+fwlxh8QbTAFV3wRE8Le7EuxiWTEDBrP5Xo5XR6QXX48b5Eah8Vn8uxc+41X4iz4AM7CffIUz//gQyw/1xR1Kinqw5lMLzdw9SEsKu4BDLhRsA7bD+R6p98TLg92BK8s3I5AZz9QcBY6ZutvPcbmg4Dl81j8NrEVnIUiOBWhyZ4QNg/3cBbpf/8q8FnMM+0mKeozjglgEg0h75C0XMCkwvl+NASAmBVbiXKQdYYSiVpn2qIkuqqGpq6ThMICytJoyLa2TSfCGEUlzynqNp28RAt0seoGaY+qmLpgOSfw71xqwN7TEgIDEKCYkhzbUgC5z2zyUwpx8fN17X6quRdkzBC3HYRvoR/A2QlHpkIYZwcmIpcJ6tZ1vF0C4CBlBwYT5cntQoyVcmAjJh5vt/Avtnk4XTGN2OSX+LUUAeLGl0WMotybnYC3FG5PMaF52YtDU4FaT55XMmCiSdSNvJf+a5RKzbr1Biff60qkBkSSO7PpES4V5KBRr1QWmbQIpa2uG0FJ2uW3ArDiUDEhvPAIHz8Xk+tyU8Zs+ck53LAUQp7iCwHcUKMhBT3rCP6lEBo3yuieCYuuK3d3sTgQwShiH6RqHEptD0gJAFPWsDg+J6CsPGDDgFLez6ZcWw6Ici8ChSDlA7VCWIy19KH+DhDQVNYsClzau1pGsOsrMKwb5CXKkQ8AVaMIDtSNtV1dJ9/ZcoC6QJnyiIB40WWSj6DVqo4dAC1ArC+9soHx6bJW3dK20zRlmtv8ordNmZSc8qRzKBqEJKJB/AjLRb1unjB876yEAXFF6LSAtIYRKUdu2ADEZDLkfI2TBn435uS3POaOke6vZAIRFd4JOT9MoOhazvCq0CkfCJ1iGNA9MkWtPUmJAEcYzrMG1Vd+CY2ipJCdtBHwjUN3P4dOt8LJoQlxcjIjPjxHWgYE58qY9Q8W2D0MWGStBchIzV3to4Ku2BPCKsDtIpIJnfJ3ru/UvbuLBYA9AhyVONMymGWBMKfwMErIU/+dScEoKBuU7sjeOMssQU0+l8dxQnrK4wja7qqDszBl5ZohphI5jWRIaGrClTjhuslOoBoFdZkpyxKrDiN4szmsWdixydB0HurOU+gIZ5pFofm/2E77fIhzoxuLZsSDKVKU+1qrh8szoZiAbV/a4NTh9/LyoGbBsTI/oc+aRd/DXWaMSPD13QgGht6NssB6X0KxwjJW2bHSSXa+xgh/2U/MDXp5WYsuzzQLeC/Ob1ucGQBvd1h+1iG8qPSA3Hi43VhwEiUKlBKCLpQ5i5dJ2q3P3W8lRYC9MxmyBPdiDTfTLNonO7jI8OvBsIUh11alTDtYHZxu3QlDnNEsrKn1OrkjiwVPTQSgeqLVBzD/ha0yhuzd1wc59K/VLIoa2ZuUbaCaDLtOgEIK7IKYgdfXLHJFq2Qo3ryvqeK7voKX+kEiCMygjLNg9ZY7JwuFTqZhuFXNIp1VzQJq5zsC+1qDMy0DqBOTiU11KxpEGyvUeiWkzZMiRawArxtqFpwneslTSZj4ReIqaxaeJgliFBNoSFKwqFAGCu6Fg4Nb5933jTWL6i9jRwKoaoOkzAMT5iqrWYAhk70LJZ09bFxl9VJAlXMHNYvh4RK7xwELT2WxiK0TUJamqFtQ1lnzVprFMRpylKMc5VpyRzSLK8RqGwYjIZW28jpnqn5p3RGQQ9p1ACdRuw/gLHhdHXnwXjQMR1XDgHjS2dLqMYO7TkwPg7Ow2kcxCZ6/rFEQQ1yDC8hObftJJHU/Yyz3F2SpEx8FUCudkeAW0rPnh3EWpuKW1jJh5lKm8SqcRamt8umMesRwUmjb/AsW9X8YS20MxFR2ZMWKFNNpjKAXl/WSnTh5+elzpAM4C3tM/+Z+gP/8hRw0Dk5rhnhtRxOmplDBWTD4LGtYw4iw6yYs6fz0+StxFnQFzuL0Xz6b4izaBtT1CCVZsWbf6nurtVQ5R3/Cc2kX9bniXhNqBTbvgSfPpA7rdlfGZ/ntgPbJqvym9DemfQcnkZgwM5zFHAPzKrm7i4WbcUioWsksYVJ9aG0DGkepQ2qcVW65EBbuti3q+iR0eiahUx4GGbx2mn2J7U5U9bapJQZCAC0WEzMEl2upPZrLIZbJ/fC+TBb7gnhzn36o1xhGKRGQAJdBYHy6Ev/GIpsj1nw5WcLRw9ebIetNzQ3JZojNDbFmCD+TosPpaw+rGmwdnJ6qo7YRSDTGZEKnkNwQBQQB1dE4jOLgLBm+OXzcNnAHzBA3M0NcN4BfvET82sP8HIyzNbgyUeJJA78ZhPFKoziJQcNpmTg6cWmUDOC08Gg+y+e2zY3NEPr8GS6/9RBLm6K+cAibEeNZTlFXMyTVFHXN4qUkOS39fbne6pNdaatT57F3oJOFmCFPLsuY7X74MbYfNFi8qD4e9tnBeSh0un2wb4ZcfNlCp5z/ZxaElFfV+FKqUE3qiAxjCVU6yCJAKSB+9qRc0j+8Ly+kwV+Q9xXCrfcaR2GUXmamLJdfvKfP4LKmUu61WMCdnwGrZcVjAJPcEGrz4LeNXC8ZuLh3SHnS+21XixhvdmLHewgyE4CjD6QmyckJeLORWiUA0rPncPQQ6eFZeXHJTCytSwIALkhuCPqhpK67Fzlfw7ucop6L9zIDMWI8XcDnMGdll6bqO4CE/Xy/K+nr5UHECHqxrc5jI7Ro6y6WfzN+eA5/qXki0q7UeKlPYij8/HaAcxKSBFDSyMv7oGvueahw6izsCOOqRViP4Nah/Z2n5bt4Itga3cGHr98vNUlSmyn19TqBEBcezUXOb1l4gICWCLsHHr7LeRweZTfvHkh7wzaVqITWDWEv+SbtOsF3lYrPbUdBZM5k80P3MK4clksv4VUA3cOA3SOCN/R/wymhWZtQv9YNaYHYBrQXCcOJLqRA/KfvLkX93UquI2JrgUzqg1ixRW1nPI8gqi+07h67TlQ0rQdir2nvFYUwpiRvxSgOyjHjPLQUwGZXrqkyqeux62omaN+XpLByz1yLhPu+/pv7xX1f65KY9hFQ6pIA2XGqNUd2WrhZQGg0CjR6wiYOCF5gVkUd3pV6HoDMTQ3xTrzp2s5DVdTzeGg7AcAHB9KCRjnaQnmhULwLxZizW7kWJLqiinpLOFhF3Zsq6hZfE17uREvKi5hfD6UmSVqEEs3QkLrbRfiNFnXOyVox4uSzEe3zmnWqVdRLNuw1qqiHXNfFabbyTJoXK/itR7gcSpLd8skAcIPl09rnsL26ivpw6tC+GBF2VbO4Sd2Qo4PzKEc5yrXk7moW81DqpLCQCbXqZ3vMnj+/jsqsELFWNSt3sYWW5/cyxXkmhYkm1H9RtIpZpbSikVjsRIzlc1LbMxcuohjLv3I7lt1Wixhp23MSlSUIRskO5doObbuaZHPw2zCaduXdPUPWy2QTjvQAACAASURBVPGhttfuSzTGUsx5T3Q8zHWkUNHMiTjm/hhtCWO2yW2Bn4wYJVN8Sej+Dtw7/5byuE76ClRqg5hBZZFBIU18N+zEVKslBbO2kBi+SxJKhmAi2EmI1mmRoT4WH0phB88aiOtivaaOzYFixQVMNqaidbkuIuz8hNHLuzj522nFuJzO74dU0/cZ04zr18jdXSzm8qqiQ6863zhJiejtM3Vz9Wxz0YrNcIRJ5bB3JYVYmPbaxo6Kil/OLX4GA7QiwVK8c9F2ZQo+JuU3NeA45+oYv4P2KC1fmVQREzwHkJ23NhP3lqXczwnu4o2u4c11AHDJZb+e3N3FwtYJmR8j2v9sj9lzbcUpe3lT9wOAJFSRCZ2SnWAmzVfP0ZdkyE7E8jJnzWDRTCtyAZO6HtQPk1oe5bhO3lyLhEKo/+bvKYRalwQomsWkLgkgu7bPaEeNwoRQx2SMU0dtYuEOtb8HKioz7+zppIVTP47lBh1G0K7DIdqDMh75M4ApL2eOtnDjxSZPJvLSCcJWeU21toeS1KiMZ+3BcnypcfD5d96k8KdVK8cutTRBg9RmB+fCo3JECKLSFmFOrZeFeDeivx/g+rb0gx3BB4fhXnZm73whcopLjXDkCEXj4PpU6ok0T9uDHC7xJCC2TgBmWcsY7rXYPfCVNBnAeOoRbAJfqz4LwnDi4AY/cXCyv/5qcWcXi0mdkPl3phaIrQ9Cpgp7qS3iqibAmvuRUg0xaiThZClqtE4e72pkw97Le5nYFn25aGsIknPE4PwETtGXWSyTVRhjiVD4xOW4vsylFsnJStqo7V1vgJNVrUsCFNPD1iUBpDaJTqZCFFwQq14WC63knkO2w6MVwmV+LVT1zcS8SuTb32/RuspspeJ3I/wwgrYHXvY8HgBKv4f7CwR9zhoNaWXyqHM1roI4HjcOwyMZA2WzcrEiFAFg+2GDZbu/McQFoV0IC9bqRR2f4dFKjq3lusO9ttQkSS3B52sRS+QirhzawujlwETw6wGX3/QA8oITCMkDzcZj+zijMrdcSnuMK2lv8hJhaS4cfM/lePtsBbcznCRZdo8bDPmc5lKew/qjgM03CKB6fn9GaC/rGMTWREMWhNhQYeWiyEg3WAHu7GJxG6JApC/gQtc79q7EmhjztpikqsmxuckCXM1KdksyqYehC3o2AyYtcQdqj9yG2Pqk5nZSy+Oq39xym77Ie876cdOaKcdoyFGOcpRryZ3VLA5lipbvTOEg2GJChwoRaREiK84VshpFXNLFegKFTfmaACb3okUrmAFFHGaGau77yU7tn1/u4yxMESC6WMNrYtVmi/Ak27IZ1q2Fi9hRyR4FIBDu9UYyENWkUN+IKWIEQBKORoETe3tMtY1oIjI5y7b9dL2Hs2DvSvEfAFh0i4KzcDOfBa83B3EWOh4ASr8XzJUu0DlBH64zOjN78d1OMklpjNI2XI2z8LvlQZwFG5wFXVSYf/tpkGM5ea990kjN2ZiQVkHwEUC5DzuC32Qzs/UCbBsi7v+rAYun+ziLJvtCroOzSPl4eHJ5EGdx8kmLFBzCeiiRonu/06G9bEqBIwAYV1fjLPp7HovnI8ZV9Vn4/vqa9p1dLOYikYwbmBCacWl8FvAeyHkdBYxkMkJJuSVfJT47M331bXDwch9HNSTrHchkaspvXXWMej8hltkryOx96UPJHoX43PT8EorUHADvi+0PABhzjkTmdNT2liiIuS+FAEq5atfoy71qW33lkGh8TdE340WJS3vnouOhn/U6JXSbF4sJ/2c+DpZcFPW/yO8IoKmDM7W+Fl02khoHCk6+M+3lcixPqDZI8aCRMC49SqlRzyU64oZU2pAaBzcExKVD0tRzDZ0aaDcY1cHZKvRfzqUkQLpyrnmuVmLjxJ/TGX/EwmNcEmJjj1EFFmLm4FwRwtaZdvGNzLu7u1jMPJsTX8N1cBaZbYmsZmHYvwtzlK7iwyAT3Z57CGcRc75HUFSnICQ5xUnMmrpBtASbjwLUCTMMk2Q0RREWnMUwSNvCWP7VtvM4Av1gUsFZFgHVrJQTY6i8E9BMf81JoSmCU3EmE2RoQXDGCRbEWf4P278xJ9Qd2BnLeMBEfLZDvZd3QvVXwpV5HIgqrkTh7WOqOAsTUg3eFdq7yb2Dk36NqfJnAOWYalJ+04NHibQER7Uym8nvoVzq0I0J1DhQP6J9MQo3BgCt4O66EU1+DhOchS42qoFsR3HW9nnR3vUHxy9sRnDnJAU/X7d5yWAvUHYVFxluZ5zqO40qOSnYfDmWzYC4jvN15O4uFodCp/pVCDXTNH+mEKah0xCA2E81C5uZp/wOmrF5sprQ2uG5rxEOm6jlvYRAdUceR4mObILsqsqofe8UtPETgA0vmlrNnLmWFARKXQ/6JJj25AQw5tJe2u5Aq5VEFBTCrUCrtilRD0AAQAJxrhEIPwrlmvJklJBtNhHGx2evzQ2J50v4C1/6VJ5LN8DFdBCvUcYDKP0eHyzh1/ncICX3hBSmhgfTIsDtBrhhxPg4J//Nc0OydI9atC/3X+nYOIR1K7khm8qPMjw+A7cOTV4sxgfLHGnhrC3UZDT2UsO0uVBaPC/1Tz9LuPjBFqeN0RgcwW+jMGjhdbkhAb7jYhr49enB3JDu8QLjkrB86op5tP36ApsPHU5NBEhyQ+oCYHNDhlMC+xa9li9MeOdV1I9ylKN8H8jd0ixU7SfaB1jECJATurxM6gpgyidhfsNdX/gcSvpu3xdzRlO1C4FtCBXElO9XUtPtvTZb2fE1DXvXgV5KuUQ213Mv1+L0tGq6KS/Im22FTG+3pVJYHKvTU0sllpKJuQ283Ur26GDal8Fivrdqdmb76gd41XC2O2l7xpsodJi3QjAcnlzumSHqlykw7SEWtibra6ExynUOJZLpeOTzAKBJqWgrhd07+MqNAXGgUjcAmy2C+jM0jdyUV9R2+fW+GRKyGYImFHZzAAhPMuAtY0yaz1uhvUtCrFvp+CDmRXAF1i2+DoJ/fonz312ieZo1FmOG+F2uImfMEC2oPDdDUps5OF+sD5ohq49bpNbDX+wqDWBihG2L1iSSLZZ+aob4aoaMS8maLeULGXBfRQfnxMS4rrhcQbxAioXQ5GDRn2tfUx2nBxCi7xJrYXES2h5DdDI57n3l9tSFwpEACLTt3uMg/PGW+2DJWcp/M2i3dfDeprDCzUsKvzpZDRJXm+Yw4c24/baZz28Iyy+cJAXweLPnfXcXi1f4LK4D9y55IDanxHqZSzQj/+ucRBrKxD8M9y7/WQi5o737I3jQ6KbxmxCqr8PNIiN6nMyk9uK9J1+9+JSTwORlNlEeQNoUjI/GHWivLhQaDZl7w5tQoyyqzXgnx/Mp3Hhg8OV8Fda2+H1vvo6HfgZkspVjWhc1uInTjX2uOOZcLVuQoyHWIQpINEQdhVaUrIcbXykCAHCTQ6cK8Q8O3DggIsO7NTKDolmoE5ubvADnSEaYhESFE1PDodK/w6FTSh6UiynLmPg9Tg69X2odnNF40sJjXDo0xmcRFzVqBUxDp6kVhKxGZCjxjRwRd3exmJshSnUGXCsawso2beuEmu9KFueNs05Z8Bi68KScdcqzFL7bzjpVFi5te871mGSdlsI65l4pyTalxxVLkfL4veOs03KdjBUh5gkHCZlnc+tZp4NonRQjHNHUDGEJ4ZZjThZ0iumdZJ3SEOG0jeObZZ2yE1YubyNOX4ms07lmQc5kkl5Ds/AOnPKOrC+vc5VU5Q0TyRCCnGtqokrdyiFjDLJNeuuJZO007KnYi1WNhmiuCxHV6ytPZqaY40In6ACm95dIZjAUkrpeMR3OOaAbbj+R7ET8AkgBaeHLZKeYisnhfB6D1guL92XzThLJxrNWKtnHWtrgTRLJAGB8w0SyYzTkKEc5yrXkTmkWys7NwwhbUR1AqVnqP3wsXJulFkgEOGV6PfObxIZ5OoOJPvxAPN39gJgJaktGad4RK1Bq2Ct7yDHCn5yIx193X2apbL2RY+7Bfbn99z6V6t9ml7VVznmohL1pHEFaK1UjCZ8/KQWNEGOtGDaM4GfP4XiKZyUiAX3Zqu9ZC0FKBUehFeelW1ydiQ/vCyDot767T1EITKqbuyYUMBtZRGSMSKNhmra/33X1uvk3fn1evzeV5C1jdwGGNQH0W9+t92QxMcnswoumnRYGyuIybyt5j7St0RB6eTE55hPDe2kDnyyr2aOm3Rgry3ouZ5genOHeP/iOlIqsnQFSRKPPOqYKlJv4uiSKVkB1ANJ6s09IBGBpsqOVi3T1f/42TpaLGtHL15+kGBhnd/zmY7gXmwmK1W/3I1dXyZ1aLDCbnHvfcbqy6NBcZBFxIOIaLt11sqDc0As8kRRLGFfbyplxip0r+SS3LrMJzcpbAVQ1ljOXZZwuorV8VSpudtr1ByfarYo1V+wEsVXVtO3vItJkiyIlrhykGqJNqZZdSAlIrhYteldt6/o3jgxRFOY0phs4KozcqcWCzcvqlsvJiqzfxZcvEb7+Ua0GfrJCurgUOv5tJb2l1VLOOVmB8m/Ts1oTw33rR+T3F3lHf3QOZwrX+u98LNccY73X6YmwgT9+WH0dT56DHz8o3BLp5YW08w99C/6ym9TWTKsGw/0FmIDF51uMZ2Lnhuc7dN88AxJj9Zuye8Yf+ADu+Rp8uoS72BbWbv/pM6SvPcR4uqjFeDUhbdUWzgcAaD9dS67Hti/ox/Ak1+/IPoji48i79vqP/X40a3X4qS9EciV8J33p7we0L0YpNLyqu1TYRjRPt6bqF5eEteEb9wokejwXDXJcebTPc7KeRguWHn4XS0RkPA0I6xHN7z7B+t/6/XJsSXAj4EaeIBA3Hzgsn+U264bKQGyAxcuEcUk4++1NOX75gyeIC8L5t+XY9uECcenkumFaM5QDZcLbmNspm8X5//scv/Xnfwhn35H2pgCkBmgvGdsP5ZywEd4NYsaQ0ZOpAUBAWANhx+jvy/HH/2wo41xycYiw/maD4ZRw/jtjGbNP/+1/A+sfZJz9Th2D/hxoX8i1wUDK5PZxAVAE2pf30d/LMPQR6P+Hfe6Mq+ROLRZW5k4yGxNms/OUz3PVeZTiQzTWIkSTuHJhxpaXi3ZSIHkStlKvvNmpeRwLazaQF7Gu3ysy5HaDTBqNSACgnuC32Wk2xJJ7QDHCb0bZ8DUHQYE3g0Q9rJefxiSQ7G4KcgJRJa4BZBcaJTu1QLhzv0s0Rs2u3O5mPRaqeRql7Sk4NIll8QDQBMmqROL6AvGBaIRmj6YEtx3Ld1q8uNF+oGIHKLJkmprn6dcdMAwIa42iOLjIQt5ikqgWLwnNOgGEGhJmIBByweFaUBmRETYRlGqt0+ZigO99yTJVWDWQw7yxlgLwGqLteiyeAYuLDE8PhNgA7Toh5oUs7BjsOIOg5GdJict2gO+4hJX8Lkllc09lvNkRFi88fO+kjXnMFs9PMJ4QmguuTOID0FxyWSyU/Ca18l17yXBaryoC7gZUlUcH51GOcpRryZ3VLF4pbGzHcmzmhyhJY4f9E2WHUYxCxlDsXWduV2c27+IIZbFt55qQZEZy0VyAbDOqWZJqeBAxTSpt630pVX/LxI5n2VUnNjUg2pWN2cckG5a9vmInSMyDuUZGg2G1jgw4hhuBlNOupW/Vprfp0DSmYu/Px44SlzZQVL+JBWBljWx0OcuU89+Zt4IZTp18g4T9JCU+mV1VTAh2ZDAy+bvIwMhlzCklOXectsuNCTQymGkCDiNOcD1N2qVj7HuGG+z9CG7gwhXhh9qmgnEobZbaHW7Q5K783E3bKcn1XdDnzuW3viP4oWomzhP8kKE0bG4EOU/alY9EfDVwFq/jryhOHhuTLqrnDRQmw3C9B6H2wm0w4cO4riisNlX0JNs2E1W9zmcMSeIp34Kycs/bdZvOPnv9DHPmjAyvcHIUuHillefaXsU+qAtKcSCap3CD2L6Vyfhx5ZhAnQ+ZmbveQ0ohyG/Z1bax1g8yLN5vKuzMK6f3Jyo7mY6fTN56TO9v6e4UrMXBCb0CcDWknMy9D4yB9luPv63c2cXilXIoT2Q+gRxN/51JIZ7RA95N/AtyEletw97Hm5yAnEcwvz97k0NS2oJKTjODjJeXRu81zzex/dCJp33Q33hfJ6r20XvAxzp5NKHJu4NkPxyoQITdmF+8kKHPY7XLXV4w1DfAIHjNoZhrZ7m9c8IhO1HVZ5GCgxs9VNNIwYE8wZnFJgWSIYx5wci3iQ0hhDzZPCb3crEe02eRMsdD8dt46TtR9llY2HkQ8hnlh9AxYu+QGiop6HINAUGpv4ASMrSbELM/WX0WlAHAepwdBBpu/S5OrpcaGYPiDG7keinUBTO2gO9lkSDmch/5l+D76segiK8I3BuYTJAJ27c9rqjJ+QLifcmjOKiFKAIzT2bO5ykikOTiB7SNnMehGA6fP9vcDQCxDQLN1d8Bgu/XHIDMtARAYv3tdHHg4Gp7vKsOQKDySwxTyDU3YcK27ZpQMnQVNVmyRHOuhyIwFS8xLj2abEYkR2WxiAtXSmfEpVDKWzYoYtnFJd9DE7Dy2MWEZHIaOPc7Nq7UCC05DBnh6Mb6txsbIIRyr7h02WRgocfPi9O4ynU/Jw5OLYgsLFJ6H/07tvWZx6Uv7N7saVIqJDUO44kruSeKxFw0AcOZZe0mpFaur5EPJvz/7L1bqC1Jmh72/RGRmWutfTm3qurqy9w89FyskRGysB89oCcL2bIRCOvFthAePUj4xQ+WbYxsjEAPvmAQCMZYyPNgyXrzYA3I2GAEAsluzIylHkbt8fR0V810V9W57cu6ZGZE/H74/z8icu196uxT1TWcbnbAOWvtXLkiI2NlRkZ8//d/H1jz9OaN7meDg5cBIpbtDsTyHad3MjthX84bwrCqvqpxA8xnjPiytnM+EfUtuVAIaajHoygXy6Tq3rK8xJ3L2ztYaIaolRsZco1v6fE2AqpSVkOMWtTRYgBEEjdfzCA0LTvlJlGLSh5H2dNyFprcDQBi7puB1oSZEsNNWaag5hYGSJ6BrlXLINaSkyxnAhB6OZGkbbekIQCYY1V30r8pi1KWpYK3OR0Ua76FRUP8mAsKTxb6jFluHGvuVNf4BcewtTQzch90P4l6EFDxFUBwAyIJkY6mPFUf+200xAUn+8RYfDl50rU7S/i0RBJGwQlyIDAZNiHqVDK4oFmqEtzEoJ7LVN0fUlGPOo6GuCgRBq/p3wUKmCP8XiMaAJwHIghhZISdbAujDVi1rSkRkAXP8BPgNQpuFAj2VCnvBHS7DGK36LOwB8JW8BGrN5BEWGQmU7G5HAE/Av2Wy3SaEuDeALO4j4bcl/tyX+5U3t6ZxVFplyEUAth4EqpZQcGDDw0ZaBiEU9D1jZhLM1NZWRKXuIrndSeJSfpULPMVAx4BeaIPA3g9FPKW2w/ImwFuL+wXUgLXfNpL50ZXnlx5FTBpcpGbEuJG3ndzwnwSQMzodQaRhwC3n8F9AI2xUHz9BetyJpQMRljK8qbH9KAmkg3joIlYhHSmEn5lKeCBOSFvVIFalyPTg4BO19+kT9McSJYeOqOYHnj0lzJltqQkMMAhw+9DfSKayxgc4iaYbCnSRhzIbcoNoCzJ4toj7H0Rxp3OO/SO4C56TGe2VCK4BDXJqTPLw+O6BCmAI8tTtr/OSANheGlLA1G7njeEjS4Bp/OuEL5yQHEbB6QPptOaEm/yeP0nAw7vMcLelf1yL8uq/XuyT9iRPJaZMJ9ofT0AYoQdwR+A6Vy2x+87+LECnfLjALt3POIJIexrstz+XcLhywl+9mVmEU+AtDL8S8hYcj0JxyNeUjkWJfxomgwtSFkx3gAuOaZmmwfmSUhZ+npchzs0pCzn4Iwj3+Ibzi14+yACjyNoH4qeA48jaDeW3AA7VtjOKmGfC+joDkB/qSY6c0ZQWXkqBKEKOLopgZ0ShphLCrToQmT46VDk+IuQbubiFAYAtBtFYXycimamKVxhFuWrkj2qy5H+IgrhCigMTEeAm+uN019qqvOcwaSDqxkEz6kqbDdR2bBPsjQD4E2hehvhr2T+7ey8x7BYhvSZCwGtu9bvT65M6fMgeAQg6//+SvQujdlJiSVkODH83GBdidFfJYBEcxMA+hcTwvBqUpYfPbpLXQIo9kS7EatPCKuXCv56RlwRhssqqeBHACR91G3rYENJQFR/QAmdCikrI/cOXlPNc+eweZoQtw79i6n02erpGmnl0b+spKywI3TXXJYhho2kjhAOjP5aBijpA8Et7lre3sHCtChui2YcuYJzSiBzN7fPXydx3vIXTPMic+UppCSzjpwLO5Nu0Rn4tPopCdRd8AaNFBBUK8HAtjkJhyCjkcpjYYr2nRy3eKtGaeMXtIAsehJQnIEJUI6Fxfdz7wQHiFxmAJQh7xODUuNKDijfpHJMCo38DcN5BbPwXNfjTSqOXPza9oajAMUhKNYBgGIuvhluUgp3K1bzBoVSxQaIZGYi7dN2J67hTW6+wwyKUDZqPUcXWXkdFTvK3c1blbKAlm6u55utb+xYuemHz1ne3sHiKGS5XIZ40aoAipIUhdAQo9LroyHW+XOU7L9eps+8qtEB7sRLg5IpKfm7R0MGqY8aL4zce4lWkDxBS+QiZ8R1WACcPHjw3OlrqMujLoAHL8uvLyIasvbloqDoij5DGipVOm4cmALcnBFPjKYt0313aJS6Zo2GZDHRsUEzrVXxivBG0ZC4OVqGZEbqqNwo8ynBJY/sUZYnlBkuybQ+9YRO6fAUM+LGYTp1WGmfpcF9pmjIdA7MF7YM0VlDphJ1yKECjvHErg/pAD9KWNP8R+PGwXnJx3EWjg23R0PmM8L0UGYK1gdpBYC48S6p0ZA04nNFQ+4BzvtyX+7LncrbO7P4tNJSisumZlvmql92l7rakGlq6tClUKGWv4mpMrNO6QGbC1JhCi2PayHHhQRglvRyzn7ZRluufJHDfBtBZgaDloY0bKFelOkzsa6bc1OB0sUlzNnQqjMvGI5v2q4yxebmvX3ODOKGUFW+Y+2tbSjLk885RT9uQ1mSHLX3xn7tdqvLljSp6e9XMXb1u2XZYefL9fwWffM5y9s7WBwJgNzIOuWKLTDf8oO/jmdRsAFbR6cl9wK2Zm8GIc2luBPPwjIwcxbKNwBQhDeptjnB+YpZhIPyMlKzrjcJtTbr1N63mpQ/QJ5F2KeyhqeYwd7BO15gFhxEd9LNuUQdiCF6knMqA5loPsg50VTPwabyTHgjnkXlODgZpJjhYmUvdgMh7BkcGls+vXH8QfJYin5lzAj7XEFkKHFSB5A34Vl010C3N4CT4BKh2zPStezkx7osqFwV4c64yXgY0H2tX6nkn+QMdDu6wbPotozuUk2FGiyk29Zlj+Ws5E6YnZ+HZ/F2DBZEwmZpla7Ul9SUp9LHn9TPWmFe85iYJ9CpOlaNE3i7lQFjaiwEm++ZXSBiBJJSkZmrJeBmJZhFTKDC9iSwie+Y2tT+IPiGbbeL/HJf7APLk2FyCAagjhO8paGPM8ILXZ+aLiez5oxYXxgCpolWF/viw1Ec0w5jMR0GAN7uhAUaY03CMqUoVb4yBa2sIG73fF8HJmu7MUl1IPT7oAMWC0YBABmLgUIapNL6c4TfTXWw0P5w20ONzujA6cyfxAbN3SjWh7s9+meqV9JV/KRVJw+7rqS/t7ICYCXJtU/onBH2EX6kEhnzL3fVk8S5pX+Hd+j6IP4jQMWsrrY4/07E8KzaF+bg4PcRYasanFMu9GsDUXMgnW3JALR/V/fdi1UjN/aJzhG6Fxl5FcTXRfvs9MMThH2H4WVsQtBLHY6Whh72Ce6QsDbfkMyFTHaX8nYMFrcUaoV2bysmYOtdpXsbWJcSckoyk7DX47LIp6hMyTZnhFed3PCWTxG0TdNc5e7t76PwbKsxsUgEsgvQuXJDFJAxMXil0oJE4E0PmqIMWkXgZhBAdpqqJker/L1vbohplpvJjJl0m5x3LrMvADUC0io/ZZaIDbMa4ZhMIavNYGxuQC4DRTpVc52x+Zy5ius66ZfiPo8KDFMIokXSLP14nhcK56U46OCpszlVyua+odInRrgay2CXTnQwniSak9augMfuxbX8Pq1aejkWAXOoru/2e0xz1aAAJOfGiYFy2Okgbn07p8KOTSsPP2ekTmY74aCDnwLiqavnxb1D9/ISbgqLPvOHhDD6wmYFAB8ZfkzgQBKtssHCEcLLEW6KyIdQ+vZ4Nv1p5R7gvC/35b7cqby1MwtmARZvhXYaHIFJlyHmbg7call/ax3AUuORCER1Ck5zkqdLo51x50kbV4C05VkYm9OmmoA+eVQotmAvmhtAyerRaXlMNe34iygtyMpc08wdFcNeyVuQGRyM6JRU75PEug9Ao/YVlyK8n0NDUt4YlqT1GJeABGdxVHEMw53KEmisOFHugxDJPqeOpotVW4QY4FnCxTVvpn5WdCzUs0N4FXVfN8s14zNqf/PtaH3RuYjNNQYopwXKR9J9P9cZSnlrB4vXlmPS1VEm6huX275ja9/XodKfVqdrvveKV7Z9mHEjFf22oMHrCGefp7Tn25ZmoFv0Q6t9YfoJx587Kmv2G997g8K3HfdV+9jHR5aOZbAu7f5sbVkes63/1W2i5lEjCXZc3nPzfaJluz7t4VCiSlz//qKujtcOFkT0NwH8SQAfM/Mv6LbHAP4nAD8J4HcB/BlmfkHyC/y3AP4EgB2Af5eZ/+/XN4NxQ9E7JRkZb1Pzzkf720xDNSnZ5No/rRRHsrzsXIOlx0mehtO8DK3etdzmhqY/JDt98jTtZ3PYmo8wA3MNs3qaCMYXUhpT4nIemmZe0Qm3aB+AylZt2kaz0vI1KlNmaJ91ZmEzR+fKbEIydi1VU0ykmBtVr8QlhAsiuEb31DEju5rq/1kLZVQFLtSISg2NW/vqFnPtxQAAIABJREFUjLhkGUOwA6N2+1FmspnrzOxVWIHVYQI/cnyZZXBGE7r/gURO7zSz+FsA/jqAX2m2/WUA/zsz/zUi+sv6938I4F8F8HX99y8D+Bv6+tnK4ilrCUtJHMA0F4O6TiT++24B1rlhEDqCvgIo+Q8AwKcb+f5hkqfm6VpuFPMc1YEHIVQQzjvQyQa02TR6GAQ6PyttJd4CANLjc7jDtBDU4SEgnQj4Fy4PyGtNKtuOiI9PAGZ03xNxgnwywG1HATzVARwA6OIavBpAQw/a6UBq4dChQzrblHP0L68FcBtn8LlkMNHlVs9LIiwl+qJRkfnL53Am2JsN9CXRo9CLPm4Cwl4Gc9PnIGbQlOF3Ux3YgpcnXWbExyfFoyJpAh3OV0WhPJsIztCBxrksOdKmh9tNIADTlyTalXqn/AhB/21qPz7w6K+yqkdRaRewgj9IzojldlByGJ+skAfCRsHJ/GAN7p3I6gVa2ADCkbBbVfnc3NB7AC+/3uPkI1/OI3eEbituYUANjVIGZtO9MCO4UT4/PJLtD4ASOi0KXp4wvrNGXDusv1/77OKnN9i977D5qEkkWxH6LRdlLhO6SR0QxhW6bVUYpwSk79yd4v7awYKZ/wER/eTR5j8F4Bf1/f8A4P+ADBZ/CsCvsNy1/4iIHhLRl5n5e3du0V1Kmz268HZoQpyTXMxsM5SjUp6AKQmirqHUG9Z7R2tBzBE8TVV7co7AYaxPe1t7HiZ5oqZcIywHbjJFY31ixCRq4K3m49Ss+5kXswlKSdprxkH2dGdeGP/iIIlkPM+gnYZ6beCLYkZTLAVNz+K6hjiNb0BEi6dv0FAkxfp9Sqxof6pRDyOmMcPv5wY30NDpIdYBr+GcWL8BgMsZdJjA04xwrZyMzgl/glmUrZqfKGyjqH01KmKkeha+4S4gZnTXESlVUZ6wm9R0OS/o9IDgNG7q4HZ6nViy3GHE6nlGf6GDiFLju22snArNhaFcs1NTTyW/xY8MJrWgsNCpd4sISz+OCHuPcHkofbZ6kZADYbjIlWuyJ4RdrolknVHOCWEv4eKwr8l/lktzl/JZoyFfagaA7wP4kr7/KoAPmv0+1G335b7clx/y8rkBTmZmotvsaD+9ENEvAfglAFhhcxPF+7R1rfeVtBO8rGFDqBqPgDxRXSyvABYp02YIbGpQvOplJmLT/d1B9SsdKOmYqglk1Pd1GTJNwGqoTmT61MybHu6gVnKNrF7a9AAJG92WAA4y3QYzumshTeVVB5flO465yuqNk/ACnCtdRs0yJJ+sajfNUZYhRGLH1+wLJT9ZG2xWFs+Gxs+ESyIZd66sy9MmwI8ONOeSFEaZ4SYvkQh7BDVgYtp0ZUaRdPmV+1AuQD5ahtix8qaX2dJuj/lMDYx7JWVl8Q2xq28696KS5QhcKtaIwyxGP92VNi04zGcBce3QXWpi27p7/TLEtDdtGXIxYP+Ok2Q3AOxl1pA7wvhAZwujq4lkugxJvSwT3Cy+IoeHsr2/DPCTLJlMCVyWgQ5x7UBTLn12eOxVM8OXDNc0AN2K6jKkq8uecCB0W7dYhrR6IK8rn3Vm8RERfRkA9PVj3f57AH6s2e9ruu1GYeZfZuY/xsx/rKPhjQ5OFqX4QUUFjhF829a+foHllWi3O3pvCPkX3CZD528g+8bmpObv5jvH+x3vc6OuNy0k/xZq483ftV3HEYYmQmJto7Y++tSIw+sKL/qhtqO8f03V3LSl/k2Lba8szTnfaf/PUT7rzOJXAfw7AP6avv7Pzfa/RER/BwJsXtwJr2D9r2X7KYCZLi8BoNoZdgEcY6VXE8F8UNPTak/o33ki99ZmXfMMhkETzurTHvMMzABO1nWNDSA/fwE6HCQXx+wL5zVoswGfbapSVkzID07gplnQdj1+7EXEZcGQ63xJwQ4XjKRPqTDN4LABQMDHz6T9Qy/WiOenoMtr4Fyp7M9fgvoO8d0zeNPDsByCxh4RAAZWpuV+RnwoM4vOZPlVWNdAVr89A1jsCLviPVIFY1PnSl5E7h2wjbfcoEcU7racr0okQpigjPHJUGcUppS18vBjX3Qy5tOA7jqgmyNSXwV7XWSZATR55NOpCvY2hR0hrgl0IeLCm+9U4+jpQS90a8Uhdj9+VpSyUk8Ih6rVkTvCvCasXpqil5Pz3Z9jegDMl/oEV3Vvl1yxJMxblJlOEeYN8q+/gKTUF/cyoWQfl6uf2SBuAGCFfiOVjecO40MWu0I7p/NGJQwoKeppAPYdoX8JTJJBISnqVVjtteUuodO/DQEz3yGiDwH8Fcgg8XeJ6M8D+A6AP6O7/xokbPrbkNDpn7t7U5blmKK9AB6n6nBO+l4sBZs4tlGGX0FntQvawqy0OyzCklnrBLA4FoZBTYR1GRKjRBtiXIQECxDVUoZzRjB7wt2h6kbsR4SXS6UttzsIMLkfy6u1y+1H+OteLBcBGSx1oAot32RUS8Zpht/6so0daVJVujG17F9O1eqwkcfzY1eT0RhFrcm0Fazulo7clhaYa5cefqvnEPTmm7KaF1XhF6fWksUXVZcKN0WOevSXN8PmqXMCfPauAqoA+pcr2baVbf3lCn4U5ay0ciXHgrLqW+xdtS88eAF/54yT32esnxoYKQOU3yeQhjzCPpfpvsnxsZeBpd9m+JER1/rgUEr2cVk/HxB3hP4ylgS3k48TiB02H9drvNtqYpkWG4RSL8rfqxeMoCkBkmh241CvLHeJhvzZV3z0x2/ZlwH8xbsf/r7cl/vyw1J+aBicC4ey21zIjvELchXbaPdNLElCja4mgGK6s0j6uo0laolhtp9zAja64/pIwNF2RtSYALGv4q/k3cIcyD4Xn5LmtdQjpj901Fb2VE2Mmrahqb+tl5vkLnIOyFlNbCzAa09L35j/iGqUaWbmpt0uKiB8y/o/N6ZIi6WHKWR10q7cOYUVqGynWc6jmgyJERDFXMO0WPqCLI6t5kA5uMXva6ZCaM4ld2JglHvRyAQUCOwcck/V86TXjODgRKC3CVGyFx6HGQdRruK7xntgr2DoVJ/8gNTH6Wb/GWiam4zb1BHSquqN2n5+ar9Xt4tPChcRX8q4iUt9SvmhGSwAvDmg6YQjwOVGlovsc5WjQaakYQNyY97mlvZFlBZENDOfI/DT3KvIueVFccu+rTvaH2RpwdIK9BFa8sRtjm9fVFuYZLBYqGsDDfhYwVKm2wenL6S0wOlnBPaPbRXfFAx9aweLhQPZcWl1NVutzXa97h34eD2mlbEZ+Oj3ARRNysKU1DrL+3bf4OsTmUiejuaZasdQx7B2aGo1Ml0XFrqYtr1r2lP0Pu0VGhIOfuHwRVER/U6czYppzrY+kQuJKPgKcCoAqp0CAEWDEkDVwQyuALOA6HS6UdrbbgdUjyLcvKwWDmp63nHliyitzCzkie2oEMpF+zNmwFHRvbQ2uplKKjoAzBsHf1i2R/YnuEncxoZG+NYcyHrdlgeHNEjYNXVUFLeZqdgRmh1CWtUBeDoj9JfWV3XmNJ3q9x3BJGNbgNPyw/JImDfWpnCryFtcCVCbrkXfExDN0ekcmF42IO8Zob3obBaRBkJcq4uZhk5dqm24S3lrB4sbGhStQ1mjw2BKWHSkW8HM8pRvn0jeAzkKbdu4CVbnHBcKWFZnqUuPVfIk2notwtLMLMwxbKEI3ipZzXGhXmXbC5iq6lsUVb1c68kpwUWV1W+c18k5IObqeGbt0rJwXPeqldAobiMId8Uf0iJ/AkBZftj2sPfl/eInOuj5xpufLRzU9Lz92NeMTJ1ROOJFHomfcqGdtypV5kjfMhC7nRMa+vGxsytuYy0TtjiQ6TY3s6iCRQZ1rQyg1sNidyB/6NLDEforRrfTQS8Q2DPCLqO/tggHNxnG8nVbhnTXYlVgA4A/1OuiLX5k4YxMXH7f7prRXwq9u54sFn8nw8AngAMh7FEGLqeU+buWt3awuFEWyU188/3x4GLJZsd0bXttk3ugN9PxIHBrnTow2LqSNVHJtmsRO7+8jMakVKwG5DOtP+VqQVC+n2s05ziqo98tCVSZAWQgk0QSyn6WiNYMCsdJYkWrsqFt24BV6OcJLro6eMy5GUjqk52SKFzdoMy3/WHtsnqsP3Tp4bQtJVU/atsbDU8Xc4mGUDP19CNXOndTmKD2hXlho2jb0JxX9iJcI+db+8TBgTNKSJeNzJRFGs/k6yjLwOCmDD8ZKYuLmY9NHC0a4mcusntyvnlB+y/nNsuA6VLtBz8z/IHLsQGRzmv/rmsNhpvE6tBrZLu1K7hLuRe/uS/35b7cqby1M4tPxSy6AJqm5fsuLDCLhe2gFW6eekZznpTqu+plitpiFvZ+OtJdND8O288rvkEkJC8oTTnnxbSXVwPSqdoFHvpqHThOZbthFrzqgZ3iGlPFN8h7oXWvQp0BSEOETr5ufEMO6olChDxUrASQCAcBjXuYPGHjSfN9I3spZuEUp5nOO/Taty1m4YITzcxbZhbJ+kP7BhDCVTHutSjDoE5curyIG4/ADJ+5tK1iFnmBWRwe1ezLxbGV25BWHt2qspDiSUBaeQSVMoxrj7h2cFEjD0oCE5MfQhxceRLHtVC4+xfA4QkVq0PDLLqBsH8sx+12/pWYRe7FrtAwi81pDxxuPsOnUycu8aND2CY9X7FI9M3+0zkhdc0ypMUsNoAfCdN5xSx+JOwLb9XNNBLO3Gg06nua45FLeoM32NS7CZvZurC4jR0mIVDpNDU34r3tsZCyfDfUaX1R226K2021zqb4a1+OZxmiNM7w10vxXXeYhOhlhC9tb04JbpwXWZyImjk7KsnJ1sdT1Ol7KqK0hZSluhXuKAoStvEGKYs8wcVKyuodlX0sJ8LqpnG+VU+k9AdQjtldh9quWcKapKpRtjwJzILn5FzSw80N7ZiUxYHQX91CyjoIKcvPuQo127nOuaTnh91GlyayljcNTRH8JbiRSxsoSvjaxYzVM8ZwcZOUxe4WUtbhdlJW0BveX0+3krL6qzX8SOiuU/ldVi8ycnDFOlH65lWkLMY0EYYLLpaFlPHDa19orlis9O1FUYFbNwzI41i0KTIAnqPaVRyt6x0J2GY3+2pV/uYLoZEXtqFZIlobrE59b8fycS2sTdtvmkG7A3icJFTby5OLn75YKosDQBfgt0Id58MIKI2c9wd4HbSSsUZfXooSt6bEtwKxfHEJ186cVAmcxglu5yqYpraHlDKczXB2e+WfKGBsYFoXACJ0Hz4rs6Nia0AkAsnaRnfRF6EhtJGPGMG7fQWNm0LadmsDAHQmjmu/r/FiiCrAaQI7zNI2QMDYW+wtw/PVYjCwYpoeCB788rL+HNo/fCnZZX3fyUwrMcJpX0HcmKvMoZ531wVwJ0mMj795BXepqul2DnPE8LGaZc+phKZtJsc6IyW1PSjpA5+8vFUWctMHaQNzEU4++60dNr8/IFxUVmruw2KwKZwW73F4f4PhxYjcRMBaJfDXlbdqsOAGRXer1QIos5s6XV4ivP8l8EE6iNZr5Ost3MmmbGNF/Hk3gjZNqOzps1r/z/60vF7vhAz08BSIWawBAfjvBtDZidysKp9PJxtgnMDnp3WJ8uwl+GRdJfV1EIp/9Gfgt/NCkTqvOsznvSDoz/aSaQqhQu+/fAowY/ObUm/86mP4iz3yqoe73oM3cuH5pxdI7z0SWXgVQSkDybrH/Hhdjtd/vJUQ735CfCK5JUY3Rxfk3NbSBvq25Ptt/5WfK9Ncl0TCnr1oNFjkYTrz6K4TXORiKQiW6EL/7LAASEX8JmP60mnRo5jP+hImLRRuX5cK/lCfnvEkIGwjug+f4eqPfkX2GRrxm+YK3j9xWL1gFb+RbcTyvtsyUk84/fCR/hiM3VdWiGvC+bdl23TelbyTHJaS+hwI84lDrzOItJIDnH3rJb79p5/g9IMz3U8IUP0VY/+uRkN2msOSxeUckCxQJiDsIS7qmq/xzj89l4iWKoRb3+zfDZhPCGffjaXPfv+PP8b2xzNOPjgpy6+4Afor1KxTW4b0MovoL0NdhkRg/tbdYct7gPO+3Jf7cqfyVs0sFqXlVQBLZqT39W8jZRFVjgNxBRzt9aiOQqryXvUafAEJ5fjC4CPfsDJVNwM6BQUghsxdQ0QymvLgi9KRDcnc+UIs4s4jDbpO7TzSoGQbVynN3jmlRPumXUKR5t7VNtg59WHhBM6dfE+8NJoZhX5G+h3rB0BNfTUcyrP0Qw4kJCQlJMWVZHey55IYJcrVrtChZWPVzEy9E4UrKP2alNjUV+IXoOAlV3DV/DUQan/Na8kMdQlqjGxgKCHucXNm4eUpGodK4qIkpsFxVYHMtHIl61QwhnouOchx/WjZsVT6MZ5y0anInWRyugjNEpVfiD0ABuZTra/nwlZlB8RN7dsAAU/L0kUzZ+OGFn0WN0A6SyUJDQDmM+VskBzPZhZ5UBf5SKUNbv4RIWXdKLeGRbDkUbSlcCIqweeGyK++UoYAlTkDJnTT4gHtd4rEf8OzyHlRH4DioSniqTUmX2LouSHEqDNVG0UwYpKJvCzqZ1aA74g7kStvoWzPpNv5aF9CazFgfSM3YUNGYpZxuInvu4SyDHA2njOqT2fbXyTTbxGwbc6NUNLMARQavh2nbE/1XCvPorZhEQCbpe3MVH82traJmzq1v3tatllk+Q30O5ac0wEq1jZYf7oZzb5yo1KUf4C+z1BSFZr96vGMLepKe6TfZE+R9rfjUNMGmpz8Bnp4P5FkkupgUdLVHSkfBJVnkd6MZ/HDM1i05TZfkBvamcub4LjcIL7ojVHqMaDN3gMo2hkp18SxpOvrI1CvqDtz9T4hZrmYdT3Z3lhmNFw1PZr31j4029qBx1iQMVdDYGsDKTEsH+2rgHEla9UbZmFg7KhGCLipl63NdvOh6Ttrc0O/z82NmhnkqEY0tO2A3DQUa3vNR6MdXNvBqr3Ype2l80q7bD9KWMjyC4OxaWMU71S58akOsHpKfm5vVCp94WZqBgv1SdWbW85BnuCUAW/BGol3yyDQ7NuaGVPTtX5m5BmLPnMzQLPUUX6bWY/n5Hhl5kA62MxcB6ZYj3WX8lYPFkR0KxtwkTXqnNzM3jfIeLNMeUViV8lWLFmYBIYvSLEnknyMmMrAwN7JdH2RMaq6Bt4f1d/YFjaZrRZCkwzIZnsnAq6WA2L5HOxI0H8TebG8lEb9mbIr52Qq2aUOy061vmkyPym7JuvUptHNVJ1ykdVLfQU4cyDkgYCpyrbJ0kGTr46T0pzWu8gwVVDT+DTNZzIwNTkjqopmYGbqSMbyrMK3ltfSkywDPKqsng4Ultth/e/ISdbmUJdAHOwYKmDTSM7lQEgdFeamtYU9Ia24ZHdy0Dp1OQIAOdbBomSBrnSmxfK7Z1sudLIczbccO9vxLYN1API6C+Br4/AgyyubWZiKeGrqt23iV4M7l7d6sPjUcjyItLONVy1Zbvm+PD3r5gWh6JgSfhv341MKMTTe2h4XOgPlxX42TW3pyHJOHjeWQplxa7bRD7iQPuUY2t6mGWbcVpJD2ydiWWrp3zkv3LhoWdVnaBcv3/Px5/USaNtX+vn478/TmKYufbvsk6P9jt/fWAZwM2Nql223FGr6vL6KNYLNXn+Q5T4acl/uy325U3l7ZxbH+gU2zY9KyR7rtBzkgKGvCtsAaOiBcSyvABZkIXP6plkySeNZDzflEk0IRSDG12hD8CD0SGcr5F72668PiOcr9NfK+9CoyPioAxNJRETPJZ4EHJ5YclGH8aFSsKeM/WOJApw2+/qtV1XsWBSxPYC06TCfBfQGqWjUJZ722L9bGZX+IO0M3mF83NfzBZB7idZEpZkPnbzu3nEYVE/SzZo23pFSjeVRdXjsVOBF0qSlc4BuIIRdV2Tfyk/IrihdA6LCzWQp3HJc04qcNw7dztVjPfKSLfl8hf0TiwJQAftMTAYAdl8VVe7jaEgOQP+SkNbA+pkB2MD+HYf5FDj5vrRt+57XuoXeHXb10Zw7YHpISPq7G217870V8FNb7EYzQGLkXmTy9l/TLN1Lj9zJDCifK7FtlUCOMV308Nce6bGAFuOHHXIns13DRdgB268S5nOG3/vSZ9sfT/jnvv59fHv+cmknPZowPx3qMmSjnJlNxDh7TE87xHfMCZ6QV3effry9g8WNZUbzd2NWLO81B6PJKuVZdTrnqtfZ1uF3S/qz385qRqPhvpwFr4hNOnxMwDTDbye4yawAZoTrSWwOUQek/iIiXE9SXyNEPARZT/pdRK/4gj9ErC6STCV1ORV2YtjjDxE0NantKcPvZhCzHBd1ACAGVn2dLIZrMc1xuwm9yt37rVKuJ9HDKFNVJcStXmR0W4uMCBgbgoRK/WTzYqC/kvRwlyobMOyFml0ySWMupKz+qtK1bT3uJ1c0Mw038AePsE81e5SB/moGHSasXsjx4x6afVnX5IDgBcNzXq7FGYCSsuKe4PfatswYXni4iQqte/2cEHdUSFnh0AwWQST9jVodd1T6OH/wACef6H4dIfeE7pLBLuhvaRgRMF+pncEgum/rLcGPwDTJiQyXkgbProKm7IDNR4R5S1g/T6XP1r+/xu8MX8L6I19+x3m7Qn/RWAEMlnMT0M2E4SUw7jUnaQZoujto8fYOFp+mjHRDJcpAyruvqrgBHQsg5ysoSc6BuyB5JyGUfe/atUy6P2NhQweSH599ldTPCkxSRvEtKQAnicxdqaMLCym5H3hplJRELUpeQfUmZ1cBOEuQIiZwEMYm69PXWR+z1tN8/7NI1ttsgZ3UCTCyb/ACZ31b22pRJvvMOBVmEZjDUpbusxT2TYo5aZ+0NA09NjWARv3ta/TC/qbUWBfi1cle7ACELGCuja2EojjGqPX+IACHt3ewOCZlHZdiVehqmNO/AepXOlFIT3DiaV10CrxEHWhu0P3wJvVTiVjYhWQ3HwgyMDWRALk4uByDHQn13JEqX+u+XVjqhP6ACxPqhc9qMqTJUUz1SWceoyW6kPSGcY16lYG5GoI1S0EOdbB+o7YtBgsAEFWrEiXXvpUBANouAqnBEDeS+1DiU+6wuDE/S2EbHKxt1l/O+ksfEnYjQwYYGRRY+1a2Z09wXqMmNlF+xWDGDnAh3xisJNKkIPTR4PR5yj3AeV/uy325U3l7Zxa3Ea8Wn9vck5dsTdv22vrRfF/XsYylctQxUetNQqdtmxqilU2JkZtQYja2Zz0GqTIUO8axupU9qb+IchyOK8diXoYdjaG6IGUBraIVaeYvJWGyVvaknN+bnkMbei3Hyze3U2Y4UzJrQqgtEc76+03Vom5tV/v9NhzL9Xe/GUZdfmY9UZi7iaqc3ysm2BIilunKcRvqvzpL/Lzl7R0sGp3NG4W56jyqaIs4jZsmRIbrOiVB0u1hdEPLYwJnBeI4l4uJpxl0GOVzy3ANvsjwl1wNr++PlgYcXLlwKavWQe/KlJJS1cp0k4CbTCgmOBTP4LYj8oO1AJHGvNwdQPMJ4rqHPxLbzZ0rUQUAIuDbOVBwSLo0KF6dnfA3bMngjOjTAQv7yzLFJ8nRgAx2fhZ03zUXslzoQLgaF+2SAXgFmlvgVAVom3wRQIRqKFcx3LQipINoXZRliOZZHN/oOcjvShmgRlou9TWyYRm1xAymTkBaFQ1OD73mhggpq+UpWEQoqUFPmxvCfZXNs2xSDpr/AYBHXRYxkFb22zCy5xJxqrqYgJ9Ul1P71k+M7fsB80aiRqnYETBcVzjhcvyBkRu7gTxw2c6B4SaHeGIA9NK97HXl7R0sjjGLhVZFqozEckFWLQoCJN2dubwe10FjKt+nDBGbzbmAcgu6t2EhRMBhBO2nSpMeJ7jdVPUd2C7KCDdJZMCsCGjK6K6TOG/NuYrL5oywz/IkMBXvJN9zFunQGw3Bg7KIsDi13bMUdQ+gbxLJ3G4CBQfaTwhbDZ3uNYISJYJU9tY6hssMv7cUdbmpXSLNo5Bz668z3GQzHx38VBvBzamyQjUsDSefldyOWR57dFHFZFhFYdy0TFG3vqRxLqIuLqLQvXNH5andvxThF3YoTFZiSRHv9rnONgAgQ0R2ycHpQNxfJPjx1Snqfq4p6pZQ5nYT+qdnGF7agC03dH9Rw7pBk9soi1KV7KcRoVFS1O1u95NEmdhVujl7wvpZRjgQ+otU+mz1fMD16Qr9JUof0OyWKeq7ejw3A/0lF4vHBc38DuXtGSwawRMAMt32Hll1IhZ06pZObPJ3XVfFZJhBw6dnnRb6tJkGBQeONYTnUhOebZcfd8067R3ceEz3puLXmYMrT1P2Tii7JvSi35GnHylj0x4dCoh9kVmnlkynFy17uQGKGf1A8DOBIpUbgjIkW/X4d9RzyYHgjVKuUaE0vGHWqR4rDqT5IUb31natgbinAjICdXbgEmE6I2yawS0HQupRgNfPnHV6kkvmpwwWkjBWs05R6N62zZ74QqVX+jdkhuE0SuOa796adboG8llEXPdlsIinsgS7oWcxWA7LD3vWqaWXc51JUN+Dpwn+3ScAgPRJFa5BSlWhibkI1NATETGhaUZ+eSHKTNfbotDUkrL81b7URQDchRjm0qww+sNz5LMN3NUOdCq/MPcd8OwFMM9FGo63O7iUwFv5vh2r/2grIjC5RjjoEFX2Tp66reT++qODGBU/tBxmRjxfwcWMvBlEIg8An65BKaP/7nNAB1JTVvJdh/XFqvbh1VaiOvOMXpc3ZvLsnAPnDN/J+WYV+Dn9zq7iEImrY1io+SWD+lS4MaG71sGmURBPJ51+LlEcd4joLucyAHRX8ptvvrMryy6L8AwqymPLrm7Vgw4T+OVlEa7JnSsDaQ51vb5+5uD3Gbld7mUuS4+Nq7kdnAmrFwlhdPA6yzz71rUMwGrrUGQLIQM9D12ZzRVlq4+e451fP8f6E93uCGnt0F1GnHxspDsBJcxDFdA0/1kC1O74AAAgAElEQVQG47DP2CtZr9vlsvywdufe4ck/2SIPHt3T2mdPHn0Jq2cdVi+arGcihH2SwSbywimtv4wI+4ioOq2UGb93fXcs4z4acl/uy325U3k7Zha3lFeCm/aZzRKceHZSG7X4NH5GrUReMwNIBaAsknBZhG4XS4O71KuFLBKSM2C6Bl7YOZw1DdvSpWO+IVRLqbJJZYaiFc8RFL+4n62NCFHO4AiZCSUUZJ3JlZnEwu08ij4GKWBIcwIRST8mVz1TgjGU3rBYJEPT/wkMR65GGrK2Y86w56BpikBT5E1bxM0yAxHs5fOFQ1o8B2TRn2XkReUrSkTIFR9Viyrp16PpaLgiq/epxzX8xi5nr8Bz5EUU5k2TIG8rb+1gsfAoBRbWANT3IngLAH0nDmN9v1gr03olF5S+li9ryeeytKDtQdbUDzZA4qL05OcoeEbwReUb3oM2a/D5aWFaEjP48YNyEZBGaab3TkRzMuYyf8tDwPRAczFejIgbma53lyMO761BzNj8rixj4lmP7nJC2gT466mItIbDiHTSI236Gxqc+YYGp7A9aT9hNg3OZ4ZZyHQ/mwanitZef21T6M8lJV2jLGbdN5179FdJ1+CVgBX2GWEfCzBnbXbMGJ+s0F1LO+ezABAwPejRv5Rl02s1OGPC7iuybxoEcHWJVSlLmrB/x2F44Sv5DRpepA7dThS2Vy/q1H77fifRn738DuOj4Q4anNoG0+CcE178PGE+URp3gNC9rzwORYMThWk6NxqcIPks7D327xn4G+AnBWl1icgO2H6lUw3OUPrsxc8EbH8s4+SDaoEQT3SZp6WmpgN+9Dc0OOOv3z18/ZYMFoxXppXv9YZYgJONg7j36k4elq5dr5PVM3CwC4BzyL1EGcxzNHySxU90cpVV2QUBMu8AcKbegQYvT9GiP+CRBzFSTqtQLjg3d4gbATiLU3jnkAZf9CEKxbvvkAdp6xcBcIq8n+IxCnAKEEggDQXOGwLIw0+M6dRmZAx2Dn6UNTsAsfpzQHYd8kBImkcS1xIupIQ3AjhNuk5AWICyaEfYU3k+BdxECwanyN0zQOJqHiyKMTFSB8znVESHc6DPBHBODzPm51pHJ+FRyoTpzEBLKtGQeMp6XgxkKg7s8YRLvezk+MYAzd3tAOd8CuDJiPFqVQbMuAbA9XgFOO2BvP9RADhvKZzU49PyMpolAG/3gHIXaGeg4g5kI3GM4P3hUwHO8EyH3zkC3iHoPt6MhOYId3UQ1W71/nAA+PoaFGNt1/V12Q5UgHP1e9cyIzEPVAAheHQX+rTdz+jsRp0iTtRaz0Kbwye7miA2J7itTlt3B3SfOOGAmOy9zmb8dY/1ts4s6HIry6txQqehXbpWIFel/f21PhEV4Dz73ea4SQcvNVI2ivamdzJdnhJWqwqWCWg71wFoktkZzQmbKZV6u8sAJoLfTTKzA0p4uu9C8XkFgLAaQIcRfHlVVLhz76o5UajLkJPve4RdEpGYIgwkWb0uZWRfwUxKGWHfIW481t/fl/ZyHyrA2UrqB4c8hJKIZ+fonl7g3W88wOZjvca8RHm661SyWd1sAGc1PJKIjvJSxoSDZuWe/t4El4Sebt6u3El/p8HJdaF99s4/6bH9eIX1s7oEz4HQ7ZOEXjMXcSL2AnyGbUI8sfA88OHu7suTe4DzvtyX+3Kn8nbMLFj/a1K5WTUo0qX4cFQfEckc4rI8IXkKUb/wBfHvPAEfDsVXBACcd8JTYK6Yw/4gAOTpRmYZxpN4/gJ0OAhGpOFG2qxBDx+AT9Y1dOYd0jvn8Po9p7oQ8WxAuGRgrqM+B4d4LovI/lA1KsJuVBtAD/9bT6We/sviSXJ+Crq8Fq8SAPz8JajvML//QMKwqKBs60sCAP2zDrkP8LsJ8aGsc7unvcwQgoQGzUrQzHz2jwZ0V1ZvJQUZlgCofeGLCWmoituAuji+3MG9uL7xE+cHawQLO+p57378DP2ltCsHYW3mwalOpKaCrz3CboO+7zCdy/cMV6DINfEPokexfn5zDZ4eevQXCWnlcPat2rbx0SChV51BbH/yDFHrjitCtzesS5YhaSAMF2Z1KO097T2uv0ogpWBmL+zP1BN27+mMcstF5q+1L8wB6C+EqBVP9Pr5LsMd0uIpTinhxc9tENeEkwcBYSfXwvX7HtuvmY4o6W9D6C9rHxijNw2CL62eBUxnWm8G0v/1Q4dZ3FKOtTOdE3SeeYlDLLCJ5jshFCyj4BvkAKSFj6nxNcoa3ijUbRZrcyxWWX4Tv3HeV7q3uVEBhTTV/hQtpiA04YojFKzB188NHzEiWPm8CzetBoiQe7UaMP5WH6QdsdYfLO29cyD9jlRbiUnm/t16nRqWAKhcvdaXGq9TYhTzouPSksgKqWhF8KOt9RXLGQjecWFgxrVEXsRGoX5PVLGrLiegVgC7mxe/HEcIV+X3RSVh2ZIirhzmDcHPFZMAUDU8BxT247wWXCANR1YAAYX7YWAmmMpg0QKcHEQgmD2V7UnxqBvnsBGv0riqmFI8AeJ5rkZPUNwm1rbHlZ0rEE8y/OgwnxsY/yOCWdwGeHIb7jx+n49A0jZ0aZ3fdkyRwOf69w2Jfz7aR8JcnDMo1f1aJe+qVs1YSO3rMaqa9lKev2zn+vnCZqCV7FdZfGpCiUxYyPXL9gxEunksIiBZSLYhtzEv1b0bmf6FFUCss47l8W45Z/ussS5YSNmXY8g/Dho+LHkkKgKTqjR/kc9XFW4rbj6W78eiDhexaNvxNhcZfq71FyVuwwN8FaTxqkHhUoYbKzXbMbQfK5Xazaz6G3UbZSAnuqG4LeHoW85hNgZmjVK5GXAHWlC2/bikcLtG3Tt3YgdglHNKqCH5O5S3d7A4nll4X2cWxzL9xSOz+Y5zQN/Jv3YWMUFmARaWLfU4+aXb7a0FgB6L10OJMgDC6kybAO+9iN2Y0lagWmfTphLVcK5OodvtraGReZLaq33uhCpuzugUVMhl8JJEZDOLdUBceQRH5anMnbSTvYMj+Q4A8GYFZAkZFtVx41V4Kv8AFKdw+8yKqHU3fduU0h/2HjJVt3blXlXEOwJ1DBeNPi1P6XDaN8roBKhYRjuzEAXxmzMLe9rnpg1WT7strmo0ZHxQw68uElInA5kBhmJYJEsySdI6PhaXiIyoctv7+spBGJaUGsXt4MDh5h2cVjKziauqF5I7IK/qcQAUZfHaJ3X7/EgYt3Ft/A+8EWr59g4WxzOLlhDV5m3Y+2Mz5ZwlShCPHM45Awl1qmwu6nMSwpPt1hK/2mNNszyZjUQzR7i9oPdkxwRAUy51WqGpQePnVMhLmGPZbsekOUldc6yv9vkc4fcJbjRHb5HsBwO+kdVzY0LIIttX5P3nJPsrZuF0GWAUa3/IVUOzmAoxPKFsDwdf3re6MW7U8z1yjl/0h76XenLhMlAi9fekxSwm9w5hJ9T4ynuomEUr1x92vJDCK8dm6HeXFO6yTTELwyhs1lAS1xLD6UAUrA3kkCeRPwzXQRIBYZgFo9szuq3xLOpgYiO5DSphC9Eb1QeSH5vroilhK9hEt2dNxAPCFgiXbqkVGpbaoTYDdhHInUfYoib/aX7NXct9NOS+3Jf7cqfy9s4sbimfRgG/UQyraDELMkzhDYbTo0JJMITSktZi0L1hGz9vObbiYy6eEdJWBnnpgwKaZcjSKMv7QimPaUlq+wMopPRsaaudCql7mE2VhYtgVPEvtLBOzVmdyYoQUiV+LQSAmnZ+0WUh7HMLpnGX4hobxc9SfqgGi+JQ1mITr3IeM21OewXk1e6klgEKVIeudl59XCc5TdmmZYp7cDW3pMU3fEWuASwcw1o3LvjGSczVz839DPZqn3u3xAAcitiwpX9bHYUBuhAN1vZzi5XUeoseBRv+4opTGKDswtZdzLo8suJBt4TjGge1Yv7ckKfMpcyyJB0qZuFmae/SDUxSuBfOXR1wm7itOYm1WIucl24rmbX1+KkDXMlcraHOmsVZ+zd3aMhPGmbtqLiPuanFabDYL/dYOJVlT0WIqC25s/OjMrDmHsg9L34D2a8JnfZ1exrsO7JN7Bxv9teryts7WBzfqAZuAiBf2YT2fuF2DsjF31gDSEmFZwFjGRqVe+jkxrftViewPBagClQacoSuAU2zIlV+gJu6Co4CyEMo7Ll+6BDXWkdft5fBa+jEqrAPIH2VNvgSgnXKe3CFx1Gp1tB2lZwL084IzStzFf+NCcgZ84kDKS3bqUx87p3kgOipTKeuhDxLbggAEISVOt+8rEp/6HtA6dP7CnBKO1XHQ5/gcXBwo0RD5pMatpRoRWUoAuLrYXTs5bFFuGZeS5q5lflEthlQnAa1HvQCSC4tBMUjxU9U6jQx4vFJRn9h/argpQOmh/V3MSWs+cy2KTDpHPyBMCsNvFwHR2U+EZr28KLiJtNDIL83YXxRZQmmRxnc3AdJwcy0Ej+T+dRjfmCJftRgKa8vb9dg0eTkHwOczCy8gGleqF8tFbGaxJ9Z9qN5brbV7xmt2hSu3G7SjM5cjscm3dcci8ZZFKgMKJujUICjqneptF9RsmoAzlbJyu2mInFH+wn9ZSz1lfaMk7TTXvVz2k/ormb4XaN6paVvbAL8boabM2g/o7tSiu+YBKnKAnY6b8edwczoL9JNUtaBioIVIE/UTr0rin8KIAlg+wk03pRfapW97LxXL105FneqfTGJb4aFTimbUta0UKm6jZSVel98PdqS9lRVsHbViKq/WMGPrlC4h4sBfpK6U1dvSuNZ+IkwXKp2yCwyf2E7Y/39FdbPWoAT6LdcBuaWlNWZcpXOaoSUxQi6vb+M5SHQltWzHmEPrF4mdNfy+erjgNQPWD+t6wrxYql/V1KWzHSGF4D7jEpZ9wDnfbkv9+VO5e2aWbTlaBlCzXT+LgxOMqd1y0oFaij0czA4oQxOWxbAO3kf/OI7XzSDMw0ebrJM1ySqUX1lOQJA7qWtLubKp+i8ALH6agxO47H8gTI41w7+oPX0ssxJK3m1GUNcO1B06LrwxTM417Is8bPwKMr1pHRvW84AknnL2n9/MAxOWYoYHR14cwZnWjH8TCXzlRJ+RAR7byu3kH0+dV/vFwAneS+Zp29Sz1FhGxQaMlcOTvJOjED1B1EarNZASzGraUlSAkxStwQ4OQhQK65r2hfBA/kPdqIprm3Wj4INMS0BOnEyc4ub/Attj0MxH8q6YqGs7aR6c9k+rSTAF9o2V4+f+s/2O4mHaqPo/YYBprdqsKBBknR4jot0cgALTU5u0s5LCvr1dvkd0+lUjU4AoCePJESYM/jpCzmWJqS5JJYApq2ZtE4Ai2O5kw3oai+Dhh7HX42S+k0EfngOAEUjkxt6cauRSVdb9JqUxLs91tpG1lRx99Fz0fWcZ2mjYi+834OevkCvClQAYDqfrcYnoJjEHEBTRP+JrrVfXguoSQRKGe5aNTgfnoKmiLNvvSw4TmGjele0MQGg/2QA7STRb+iaS2iOwFXz2zSlB4pmqJ232583quWuaFrAVXC6fyEzHHZO2gYUncySQq9l871V8X9ti/m9cufhPnpetp/NSbY9vQAgSWFp8HApYzrvigiQqZiLnqd6s+q+HAhf/ocRw3PVQ3UyaPsx4fy76ik6phI9KzNLvWnDPoHmOvMbPnhZxZaa8nD1rrSB62D6pW8ccPidDuun+7JfXAeEff1+bqJWV18LOPkoFnFhMON7uxuHemV5qwYLyzQFAH9+LpoWCjKyOqSnjz6G//mvw70UPQp+dA569hJ4eA7/XH505AQ+3QAvLsBnJ8BeTjN/76NS/+EX/zAA0Y2Ac9h9dQ03cenIB9/okN59IKbEFzJo5Ien4Jgxvn9asi0337nE/sfPsDFw9vvikPvRv/GzWD/PxeQWAOZTh+378r2zDxIOj+X9yfcTnv9sAGXga39f2vryDz3C5nsjxscdVp+MGB/LDXby/73A9c88wuGhx+YT1bEYFR1/EHD9lfqke/A7M9LKob+IuPqaXLhnH5ralIMfM6YHcrzzf/wBAODbf+4nMbzQ36AoNgkS7/WaPLzHWH0iIbxJxkYQA901cP6dyrQ0Y2XKwMuv91g9l+37dwTMnB4AJ79vTE2pZzoj9FcMp/f84Qlh9Yzx+JtX+PafFvHmeMqaU0Ei7mKz9p/aIn/wQOz8bAWZAe4Z/dMzxJOMd35dGkwJePHzhOlhxrvfeAAAuP6qTNHdSMgDI1zX2yN3wPgkY/39VWkDAHz5H0b8wn/+/+Dv/YZcT25IGNYz9p9s8BM//TEA4MMX5+j7iJwJP/ZIBrx3Vlt0LuFbL9/F86sT/NQ7su93/tefRLeFuqjrsT1w+XMR/eMDwq+flj7b/YWX+E9+9tfwX/zWnyjU/J958gm++fH7cMTITHhyIqPB+yeXOJkH/L8fvYuvf0mu0etpgP+Nm4Prq8pbNVi0hWNcJP1wQxii3aEMHrQ7gMdRXmOlRNN2jzzNcPp6XEf/XGcUVyKrNwyytu9sujtOIn4zxyLhR9sAignd81DW7LTdY3g+gLZyJ9mxTr8f0V2IorUtDcI+gJSsv346wZtz9rMRZx86Id2ocvPq6SyyecwIF4fFua+eTvBjh/6ltkup127qoc9wqff5iNx5+OsJJ7rc6PS8w+BBY9Lv1IH69APGcKU3+8xFtSmuSWjJAMJe3MQpM+aLuq7v9hnDs6lkwxYH+cQ4+cijv9BIT5Tzni8J66eaXt9ZNMCh2+VKaT54DBcJ7nKP0w8ktzquLTGMkXoULGU3nuLkkzplt5IDMLyUB4GpcFNizCc95ue+CNdQFjUuibKgULgB4U30F65EPQyjGJ6P+Hu/8Ydx8ttVVi8NK5xeED7Yvy99fuUwBRnUvnUm5/DPhgwQw18GhD3wW49E5vHdD1miMKrlCdhSLGA6P8XZB7n02YfffIL/dP7XcfhnD8rp/uMHD9A/98UK4IO1DI7fWb8Hmgn9C4/f/EgEkigSDrt6vbyu3EdD7st9uS93Km/tzOJTgcIWYDTPEdcwIrmyG18FZhYykmWXegJnWsTtoetPi8SwHbdxQDdg8bi9xnLkxuuUvZJzCEXbErD3gPotyrbQHOuW45lTNwBQwwptiUQt27ToFvh6TGoySWu7GzKSZoBLu6mkO+dAyF55L3YFsXAMjEkKoFDPCUp0KuxU2Z6bduWGnSnRBC5/i0v5ceYmARCeRaHc9eqT0QCR4Ib92GHRj9kIVNYG5Ug4jX7kpm/YK+Gqyby1fnRDWtgXlmP1tsTiYrnIg85W+gxyQpTKicB9jTyxanY62G9ldfKyz3rGyTBh11d1b/SiHWszC2sDeiFr5Y7rNoc6LbtDeXsHCycMwyr5T8vPLMSo/qMS9WiQadKbnJqbfVGHvg9ebwYhGBekOQRhT+p7ABIWTLmAWHacdrCwY1n6M7Er+5YUapLjlAtsELctyigMwxwIeRXk4ul8iVpw34mTV9OG9jU3XWD7vGrf5XnUtOdUSI4mHiuYguXk5r6GL00kxsyIc3BVid00GhSUM5wn9Rr1CFgMIPJKgjk0tHfWB4E5kuUeZRBLQ73ecy8+n9ljiVlQZWcaw5WS7JtWKO0qA6W6leXQZnMu6eTtQD+sZ6RhVftvzcg7KgNDHtU7NQPQQSGsIogY89ohZQ9ayXWeVgGUZX/T08hKDeew7LO8yni83uGjTS64jV9HCWcr8c7a4FcJifR+0TYw0Q82RZ2I/iaAPwngY2b+Bd32nwH49wB8orv9x8z8a/rZfwTgz0Oytf59Zv77d29OU1LCUjimGQEtbRsAGaOz2YaUgE4iKhSbyEpTh6V3W8q5P0RhDVpiUIzqaZrAxgKdZiBJangZkFOS9HI9hh0r7LIi3Wkx0HUrY/XF8lT3u4j+ugOYiwhv2Ce43QTvxNHLGd17nBB2Bmxayrf+HRy6XcOoHMX3xI2x+pdaWjvL97xFIFQAub9m9NsGsyBSzQUgjPa0dxgusyaCNee2Z/h9rH4XJnaTGN22R6cenSX/I7nSrmKZqH1nZsXdQLLPHNFfacp4BCha2nX5GuLaobvkMnOTH0Rusv5CQNPusp5/d+Ul7VsZkTZgi7o3V1k9aH6JE2YmgJJQ5seE/ScbnF7YAwHIO0J/CUS1XeiudVbEwJyUWt7LDd1dOYQdYWTBDvpLSbNvAU52Yr8AJvTb6kXbP+/x2x+9g/6pL4PFPK3Qv2zo3kqnTzsPPwPdBYGdXkuRRBzpjuUuM4u/BeCvA/iVo+3/DTP/l+0GIvrnAfxbAP4QgK8A+N+I6GeYOeFNiwm+3DKz4KEDDlV8BiGIyM2+WYasBtDhUF+BCoBCfDkAoDtEwAHzeQ835fKU6b2Xur0DaYdzF8DeI54NJdTlLgf57qVEK0hDieMjzfsYq8zdfOZxeCzajWHf4fDIcjAC9o8JxFRCsvNpQLjuMJ91cGNEPJF6QxcQTzuMD0P18dQ8jfm8KzZ4ANBd96I07QjjY7mr/EHamQcPN3rMqmvZqTL6/l1X8i282u6lnjCfVJ2E/Xuy9KMs0QtAbr50zQjbJuTYKI0dHtYLenwg0+TpARXA1xKeplNCf02FGLZ/TGDXYfh4wF59OOJGB4tZZxla7/5rUW4EhyKjDybkXkyK4wbFUpAy4/CuyPWbCvfuPYf5ROvtUPQorH3Tw0rhNhLV+Xd7/MRPf1zATO4ZPGTEZwHupySKtn85AJ0AnCePBAjfDBM6n/DR83PsrzucvCNRi8O3HxRz53aw2H2FER9G9Fdd6bP4Ewf8a1//Tfzq9C+UPnjy5BpPPz4va8D+RB4+55sD5uRx9dEpzr4kOqTTFOCGu9+ar52EMPM/APD8dftp+VMA/g4zj8z8bQC/DeBfunNr7st9uS9vbfk8mMVfIqJ/G8A3APwHzPwCwFcB/KNmnw912w+0UMoF1KKk2ajHuo9RTYnt9ajYNJdyBrJO2edcQ245y2dpuRSiOVahXED+HlMh0nC2kN8yIQoA3OjgD/X4Znjj54xgvBqzt5vlnPwk5CNviVVJ6gz7qmhl7fEHj9BMnd2YAJbPLQzYtt1NqdCtLazcqk35ufIkmOoyJOxItB4TlzU8sSRE+alqZ1CSsDGljDBWXU0/ajr6toYnbTnDjrTvpI5u5xH2orJVFaCoziwa/lK49Ag76MyiWYaMVPrXXNUoszqFUaM8JU9jNwtQ2ipOWZp52NYZi/Xxhy/O0V1Z9iwjj4TummRGAcBfeVmGZGALCVseVj2IGOmyh986bDvBPJ4cWPktVe+TdbkCCghbLn3GFz2++fLLwGVXZhbP/QncZSgA56S40cvJI88e4SLgqtNp0UzI6e6gxWcNnf4NAD8N4I8A+B6A/+pNKyCiXyKibxDRN2aMr//Cmx9g+XpUmMrvvQApF9tv+55TtN+Qf1dfWwDVaMMApJcdCkrPHiXSYhRtiW4s2yevNRLTvs+BahtUU9Pqtn9QVJ29K4Cr7Vu+Z+1UENHcs9i1IChK9EXAxuZcFv+WdPNlv6FEsdhp/zfamFZ39jVSlDW123Qyqxao9Gd7ruyVzuyhddR/ljLOGomyf7af/c3B/lHzvm7L/nib9HHfR3Bg+deAkegY6Fj3ZXDHcH2C6xN8SOj6CCiBzIUMF7L2Tb0O5Z9oZuSel30WMk7CVI8dGD4kcMfgLoP1+OgYvpPj5r62AX3+4qMhzFyokET03wH4X/TP3wPwY82uX9Ntt9XxywB+GQDO6fHNFt82W2hLbvQxj3Ur7mACW/rIVLlZ3i+2J1GqLpTtT2vPbcfI1r4mFKmvx+rcpmBUlKsYovSs/WBeqgvVqy+g0FEfiMGv0IyLKhRTUbAqClKMYkJctDYZIEj/LlSxPqvoVaNSVZSqWuUn28ZHA36zb1ETZ2uz4B+fp+RMN9rQmhKj+buIIGcdeFWxzLabhytnwNklnjWGfVyYENlVpXndhqxRubYNb6Jy84rymQYLIvoyM39P//w3AfxTff+rAP5HIvqvIQDn1wH8n5+pZUcAZwl/AgICumXoVLY1AGfwJUvUwqxt5qpx9L0XVDoNmvVopjn2XU24KscCwL0r3+80A7Rrs0KhmZmaQVmOuXLiRanHmTWM1w/iV0GNGE0aJEMyDR5BXwEAziENki1ZzqHUX/1A7RxT7+DnXL05e1c+86hZo3aO8wkVqrX3FuZVf1ND3E8U/GMUcxy7MNPgS75HGXQyY14TggLFxbN0Q6VdFhaNG4lIWMJv3BDiQfoi2uz5VJYFfq7AKADk84j5SiidvOh3NfLZoGSuEjPmE6FtF0vBDS0AzvbHS70I15geRZsl+mOPXhZmJg8Z6DPmFAqYucUark9gJjx8KKDn6TBhCBHfzY8whR6PdHvcrGD8liKmS8B8lpEfzIibofRZ93CPf/HRd/FbD98vUjDvPbrC92Kdom4U4Hy42WNKHp/MDu8+EoDzMAc89Xcfue8SOv3bAH4RwDtE9CGAvwLgF4noj0BO63cB/AUAYOZvEtHfBfCbEJ+vv/iZIiH35b7cl7euvHawYOY/e8vm//5T9v+rAP7q52kUAJlVvGra76qLuqSM307KWrwet9NINabvEAiZXZF3E2+OINL5reZF/HRSlhVx8lZdT/0oqxYk68yieEgMTkOAJCFg3TcPQdamna8koL5D7tyCwdkSm26Qsnx9XexreMRRhrWxD4E6nZf1MpBSJUWZk3ka7GAoDuY2W3FJeBqURUIuFek86yM0ZKzltht/U/XWyL09erFIJHOrJB4eBLCvSybuWPuTy1PZqVdHWrFoV6ASr0QZqxKwrH0cuDJNzefDEd5ZbSXXAwD6jLCKSL3HZpCn+mHVC5aQCae67eFqj95FnKw3SMmV7S9Wwn9gjwK8shd8wnV50WfDEPHV/gVW66nMLB6u9vikP4VzjJyptOF8OGA393BdxqarWcHuR4LBaU5ct1iEVWoAACAASURBVBXmI3cy3ddwjJQK689eX1Uo57qe42axmzPo2Ask5jI4FDBSAbuF6RFQoghgBqHWb99rcYeFd4OlJzNkoCqOZ7rvHOXm87UNC7bjgu6NKirrjwYWAySLnoQ17JVdVTEDYlCSZZP1l2AAgln4QsoSzOIYqyiMy4Y+3Q4aMui1A6ACuQWQtkoarAAAuaq63q7js687+bn9AoBcVbyzApE50WJgKG1tBhAOTaTCpXJS5BhELIQrb0tohvfykBmCpvm7iE2YxO0NdV8otlPwGEi/csfourTos+AyVqSJcdrU3kV4n6VeolLvys9wxAhdwmlfAwrO/SgMFi0hC1hK7KseZ9lOSg1vZhakmhjUaGO0dbgjIxc3SaajXQSCvstMoqhpOQeaZvh9LEa4mCPCvjET0mN1ezXBiTVd2s9cwnEu1vAgAPgDV6Up/Zw7XxSY7YLmTlLZ+60wRAFU85/OlRAeoFoJGfD7iH4r9XrVOqAsRkHBaOQ6IIYtECy8O3PRUGBfb7SwkxuMotjlSQWCI1ACktbZStb7sQ6QpvvYX6CwRdNUb8zumsuxcu/QbzPoEGt4maiwOKHWAQAwXfRYb03F22YWgJsd/IjFjJCShk4bUld/AbEAmGVm9/+39yW9kmTXed+5QwyZ+eZXVT2RYnNo0lwZkAEZECBI9sKAAPsnaOsfYXjlf6GNllp5a8AGBAmUFjIgwASaTZAie2DPVfXqjTlExp28OHfKfFXN14PUr8k8QHfmi4q8ceNGxI1zz/nO96lF7hLvJwSayIKQ2KjUisvM5XWkQWgYwq1vBB6fc8Wnu25gpQY88L4/AgBM+wmIAq6up3BzhU8a3lcbDmx6WV4iQQHNuYTxPSbVmJ1dTvCPN9/Hct7mIPrb4hSryw6xdAYmsqnNhxbDWsOc9fgVHnC/rMT6OeTKL7L7M1kQbXoSnqNcuTy8Ilkh6zIugKwrS4JMsBvxET6Uzy3LhLDGIYii3J09BmMg1oZxGlm1zIIsK3ql+geyjM+gqMKVcBZyZMyBGH1+ewtF+eESJmTcglw7yDVPAogl7nIdYdpa8Oda5T6I0UOuqQQSbcJQeEZdpnEyHoIIZH2emNK+JHh7njQ38CFlQgPxEAYByBT4HPg/4cLGkkWtA5P2pv7E8nwKfK65xH0IsZAMGxMmwHUU0pR95Zr3IecyRiWhG7MORjQ5l1nrs8ZZgLi/rqlxHQFqJXlSSOpqa/a0hGHPqe4beUAOZVu6pmQ8zm+meSLzjuC8hFoSVpFYSC542QgPjIrXYM5xmZibK5ARWN3wem6yDDy2orwgvCXIFcsWymocMdd45+YEYaEyTmWhO9BC5TWkjdvnnuBHCbUQGPu4DjRcPHlXux+TRaocrWKh1LUIo4F8wIQn/vIq/1vo2wKC6lvQcsVv/SMmMcFociYDdZaksgSfFusm/i0hjMiR8XB8AHM84ZqRJIy730Ncr+AbWXFasqJ5SJNZPNZ6jyn1xVgyImYmGR5NQDOXGGexTmQlYfbYpfZHMwDA6lSCfMfQaEEwe3w8ddljPFARNLQZcOBsS+U6txKuFRCjzKQ+iXPTZw7NmB2IMaDxoLj2wpRsiJ1QfljHfUSZQXC/03URwOqBzqAu8hyzkKPHcEQIxMccDrldryn3K8UxzIRTtZkwaAKogYvpxnh57SSKBBvAt/nwcMcG46gzjgOIKw3J31wXMhyePLB6GGCnAcNBzGBNUzYkxkfq7FkDmFlh4c5cmq3E66dPMh9FaDyoc1iHJkO4F7pjDEWgnPWYRbj3J80+VjctvvPaGQDgyYNXoVZxcl6XJaPZC7AHFnaq85ipkyX+6OQ9vHt8kh/6l46v8VE4zO/e6ZTfTgf9gOuhxY2ZYe+Y+zCOCuJzZEO+KChrZzvb2e+Z3Q/P4nlm7G0x5Gh0s8yVoDRfIqxH0M0C6Nq8b1gseQlzdZOXMnUb7ceca6ZhDQiB3nFwLrNdGwu5MhDzdV5iiMUaOL9CY2zh4Ly4RhsCcHENAPlYB2+vIAdbRIsBNBcK3TOG4urrEd15jCMsLQ5TYCtWkE4/4diIXDnIlYFaRg9gtOgfDxArC7HgV33qnz5v0Fz0+RzVs3nk5hwhF/wqTBSBQcnI+hUZnhb8Fjz5mSlixb4QvPpGZJfffipYQNmGLDJEjun95MqVZZfxCMTLrAOgVEvG9b0aHFRk+0Is0HKdghxsliuczBrI+Qjx9BKnP+N1ve2IAUshVrBGz2/9oUZ7HTaCgFw6D8jRw0tAL9PSLUAYBdsRZh9F7Zj3A+NEonB0FqsGt2enMuu7uIoz8zf/5zt48GEKkgq4TqG5DhjeZVfoJFaRkos4CnDWA55jFJNlwJMHXBVx8E6MnUkqYsuKsPchYCYSs4+GPGbLnxzgr9/9E0w+KXGbi26Kg3nIMQvf8P1wrRnO/mgeMM4O+To4gK630mGfYfd3stiy4LfiGfl7lQ2pzTkWJoqf222IBPbyAQGc+cjINyBmV7DZbsq4GJsRlcHHIKrfDKKKMZanhwBKdQTkENacZiXni1q29aWmIokgxQxI0lbNQkKeswtitIXYNamWC4IYSs0298sDxkKMmyJGFEIRRqrGVK59ocWLkwUkbaCC5ToGhG2AqB9K47m/KbPiA3vyofo38IMbCBCDy/0KMXshAdDaFLToICBGPo8UX1EQFYK0PChecz0OuULUg8C1FsIGCFGk/4QNmWM0xQbEwCX9TKvnN9TMk6RgEgDKGR5joRfIgkQsWcn1LUmFXY68HBN1VstSmcgGlNoVw331QEabirgdQWyMmV4E6GvieqCUObGAXiLXhrgUKNZMP5D6BOBzq6jf38niM9KdNaENKtnCzNAk7zBb1oQ4aX+B/IZDosmXAsGn9uVnZha3+x+EAHlfJAMTHiPWa+Q0a0XVn7U1BN2WGATHSMJnjc1XYakvAPeBsEHbHwSxpxF8SdW6km1I2RDpAYg4n6eaGsRajy8gmVCnfVMgKGl0pO0pHZxiIOQ4YFozk7EJJH7R5IV80TV5nTpPZEF1bRDXzPA7rejQRjyH5Lk17yuJEeC6pMFdU4rdto/L7F0oEieCEChm4Fx1Ul/BLXNPJovoHdRbTCTsXQ23d7c2p/rIyOJFRNLcYO8wXcZ9KFWlKslv9VgoQKs1pFYsxfccavvfZmQjTsMVbwEeIOU5tz86+PS2WlsIo/lNM2cXUzYKYrD8Vo+fAC+bxL+gVgX5UOj5A0Ces00CIhMDBUE50yNUSUUK63npld7Uo+WJ3fDSJFfHVuLNn8dyBa8QPJbp+UkBWVsqNfMb3Mc3qA38Lli43JbXGkGELMv4RU1YlHMGixSlbA3/e4jp7/ImFybkvgkXcjBTrXyWZczEQPb505hwyNW3OSvUBAbDxfqdEFO8X4WczS7AubOd7exOdk88i+fYFihrw2ppwag4RtU2CgG3nbbntBF/H5IqO1FeMnBxWmw7BTPvsryp26dUTp3ajNuI3ftccq5lcbGrFGxoJa/7JS9pAF5i1cuSr9oCVcAlH5dAorjS3Dew0pmvhImJ4D2v7VOxWgiS1+rx3FO/t0mC79y3mmwYfI1rct9ckq6QqfvIxZhBLG33lZpXLl/XKUj7xTyMXOqe2qxK5HO/iCJ5czkXCrHk3BY0rlcUuWApexS+oVt4FABFQS1yZZRtlJdqdR++rN2PySLE/1XBxZRV8NecZRCTCZeLR4rnsOQlBwmB4DyICO7x09ykfOURxHwB2ptBJIzGRPByxwf4SSQmuRhZ4/NkBlq7HDPwzy4gojKXj8pkYjZFOD2GPehz1kRrhfHRPvQncZ0e6emWJx2ay3XW9AAA12sMD3gxPfnYwxzw9/bxMov9NG/yOdDsVahPL+GO9iCuFnBHXNWIZxegSYvld/ahrzjSncBPbqIwnJQA5+RxA6cF1NJifcLn23/a8A2lJcg42Bn3oYvl+ItXNNqrWNuRg2MEMxE5k7A8lZicOXitYCblLtRLgr7w0JfXty7x+rRHE7VJfHw4b96YoD/nfrmGlyasS1oQnONMoLnpMWkUVg94jFjbgxGlrpI6XLxKmDy+PREtXlLon3nYnnDyZoFlLl7RWScEAC5+NIGdcHzAdYXohgmHuSK3exZxORN+KA+7B7j+kUWIKN8ECR/3JZav8O/1TaoDIpi9GAhVzDfRnEvIFcHs8b57H8YgZxWjkOuAp/9Ww8wC9t6boL3m6371BhC+N8fil7O873jk0FyUl5rruB3Xe4Teo3miMB6n5Q3B/sPvBNz7M94+SpUAZ/quFG4xgAMF8LVlvougLFVASkTlrShTm8DGsSBiYVcWFBb8ttrSObW9gFrJrbJ4LkVPx0vgGt2pvD15L76VCErCdwoifgKAkPzd9gJytVk45xoW9s3nqLhvIYoCAxUoq2E2c7+lm2mmBDlGuLaqJwtmKgcYvGQXsaR9Uo5HQXB/x9u3VRqP9B3gBy4JGXvNnovtIygsjhuLG3FGxsRyeH6gAW+KBwEAZj/ALG7fNwzsItgJZTBaOlc7KazjtucydmEia3jFQ+I1l8anrIWZ8uQWBKE5HjDuz+J5hEjOS7CHMWhBKha/Af6A419Ce2jtYHwPrwXsgY19lc91A8wswEQR5MSGZg49Xj+9xHufTso1OB5hKqSa72OMZmr5eIOAPuRJ21kByG/oZEFNVMfaxlgAIKUQrIXYmyGsVoV8N31frTZ/Yx3Xinifg6d0sM/BTGMYgwDGaQCAPms4rRiXAbnN9D0eC10DOV9nklwYC3UzgtYjLzFmfOH6TwdWFKt0K+WygXB9PN4yp+bUszlmSY08BnT12RI0X0IJkT/Tv6tnc3SdhJrHwKv1gEBOTSZTCxOp/Cy68zgJ3kQltuhZZD3TSQesR+y9b6FvIoYlBTQloe1kDgSqVYPmgr2utlJRl4ODejYHrW4zn/WfdjweQJWS7DJuIXkbbk4QY8jpTLkWzL4dAvbejxiHqCSeAoH5+CuJ/vz2UsK1hObKwXUC+qyIe+69z8rs7VPeNj1QGxIHid2bPBeVtReE7pLbtx1nUygA6qesFAYga480C4/mRsfrUPppo0frI63/5Io9BzvlfWcfDTk9W9veexPYiUR7GTKk/+AtiQ+uXsXhb8p+436P5rpMAC5KS7hWw+wF7J0TzBPG3GgH0HD39cm9mixq28BVAJtew2hycRjF7zSazd+EwBDmyrMIWjE2Qal8Q2dw13LgCSY+3D62CWDjWBAi4yeSUQBPQgLZo1HXQ2kzmff5oaflkAefVusMtEnHEssBwRjQap0/U7/Eas0FYanOw7NwMFkPPbclbJ3X8pSLzTgzEScK6zOrle/YQ2suR8hFrMepJgu51pwZiuebJh25rnAd69jf8bZ+Zh4PlJuumajSL5/Eh9nDSMdWCxc1PhSaS243NIKXDj5seaANmuvbmSunBUsvNCL3AQCay463RXCbWs5Anicir0VeCggbWAph8Fk2gKUTBbwmTD8OWVIwUQLIlcss3Grlc9o2kxDFatpmwXU7GcJ9uS6YmMra6x5qFXL8BQCmTxwoCEyelJeEXtAGliJ5Xq4BbpRAexEgxhobc+tQL7RdNmRnO9vZnexeeRa1irqYTjnQGd+0Prrn/vETqO9+B+ImBqoOZhAXV6D9PciUSXCOsxnzAdQ2eRniP/g4t+/+/Y8BsLsfiDC8MtvQDZmMBuFwD7AO8pqXLOFwD3Ae9rDPa99mMLAzDdHHdeITLgi6/E//Bu2lZYXz+PIzM4XlA9bM2PtogvUht9E/meHqew0QgIfzRwCAxRsn6B7vYTxs0TwbYI4YJty9pzC8foL1kUL3LK5/49vZ7DdYPCqXdP/9NVP+XQesXoq6JkkWsOUSdbPPS7/+/7Ev++Q/fB/tJS+lhIlVp5rX8mm9vnpA6M56kK8KyQIjCmcfTvNypfBYBFx9b4LugrcPx3ze632B6ZMo8BPfgGZGGyXqw5FAd+Gx94slPv6PxwA41iEivqBWJFt826H/uN/IRFBgWcPuvIXtgZMjHl9ywMUbCmYGnL7JYzB/ian7Eq3edon6eAh0UXckUfw9+qcBy/96iQ/figWPTYDvPJrzBvYPol7NVYOgmDdFH/Igtq2FEh5nlxNgrqFOeCm0/EmlG5JK1ImDmebQ4+Atmcfsoz93+NMf/xx/97MfIqWqpidLLJ5OMtxbTNlL6ScjrJE4e62HPuU+OCvh//dXSKv3dRlpxWXoaQmQ5AoB+FkHkZYLs56V0qc9RJxQgpAIXQssVP6s2wCA9RG7iGQ6gAjDsYIwIVdtThoNe9AxXX4+VgdYj/GogU3KYpcdhmMNdckPs4hB0eUjgSAV5LoQ3ox7AotXIqx5VBhO0oOmMX+NkYh+xjGN5amCMB2GIwXhAoaTmC151mN1qjEcExCimzukak6J5cvFLW/mGrYjBNlg+SBVuMZofiegBsniPwAmsa5m8VqAjUFLuebUW+KfVDF4OLzs4DoJsiy8A/BDydBjDbUu2ZTElLV8SWRXnEWKgPVhyEHTVO077gPNNUHGytXVQ5ZEnHzcYvHtyH2x50CjABmC730GYH33B5/infYREJmyASB4gtAe81kHv2fRPYvX3QKLb3ngZI3Fk66c+76HGAi+C1DXxfH2TYB/OMI1PE52n9sf3tH4bz/8X/jv5r8AAKbtiON+iV8/PsV//sHPAQBvXb6MqRphg8AfHr0PAMxwRSP+8eb7eOfmBH908h4A4K/f/RPoa2YXT0TCQXDW4/XTS3xw9Woesz/98c/xV9/+e/xFINjIr/LHR7/G35z+CEp4WC/w+vQZj03/FBd2ir998gb+7OE/AwDOzAz/s6tmxN9i93ayCDGVV/6uCsmWayDHGtYI1oGGdSG3CR60HBBGkz+322gvIm/EnAvJunMFsiGTysI6LtYaS7CV1ga0XKM5V9AxiyBulujPGoibGDiLx5p+6tFcu1xMBYBVtoIECOjPLYSNxUiXFtOPNUvnxfVqd+mgFhYtAXJh0CYE52jRXjnIUaA7jyxJMWAo1gqgEkPoz8a8Xp/G/jbxN7oRoNHzb4Ccqp69T9BRJpBh0pz7t5cllSqNRHPJ691Usk2ePYv2skJwRj4M8gGTxxLtVbqe0Su7Ql5vp7X1eEloFiV1KAeB7tJDXQ2YfsCvc9uLjF7MBMsA3jUvo3/MGh01rR4AlhPsG3QXMc7jAqYfSKxvOvTPkgdEsBNZPItlvfYXWF906M94m51Er/Bshf/xiz/H8EsuGls2AY8nHs2ZZKUwALjWCIo5Mn5xyMplXc/XYTlvERYK7x6zZzL5hGs9vESOJwQFLH45w3ufTnD4mzJmf/ezH+IvAuHvf/GDTH7z04NXsTqbIPFZ/HTCZPttbzCuFXDW4q9OoxdkBM5WP8Fd7d5OFgBwqzjshftxEVYOcN7ld8/xvihJAmz8HQp5zt09ttKPgsMpkNzA/yX3mULZlgvJEiVf3K9myr7zuHxB24BRp/+w+bndLwqb23lbHE+/2Q5VNRKfy8Lm93ysjWvGxyvAMmSXfGN862uQx/MLgsUClWu8cS2rfm/dmiHBinwM6vqqv55j8vl+edF9lzyKSooghC92DnexXYBzZzvb2Z3sfnsWFaCp1g3JgKu0D0WVrVSM5gPjJaQsn1UbQHFflWDYtWuYhTuzeyevYpvur9HwXdHx0I2G7RV0ZOVOxyo6Gb4AjDrKOhteUwZQNZIYSRiQ5RJdQ0h8DYEAl8BTnvkxzJSgVpEPI0bC7FRinNXAMAXXcml0AjQlXIRrJaRwsNNN3ZBxr7i/otYNmRISpMFOefnhZYDr4sECBw29JsiKezMQQ7MZtxDTeC0AAsZ9yuLDifk7MYklCr9xnyANwTcKNmKPzF6AHAlkAN+GvNSgoxFm0fGf1QvWtwFkBOws5GvhZYCdArZHjqWM+wQz4xJ812KTsFcD45HPgDUzK2P8xslT/N+DSOPVeMjewowdTk44MH4up1CKyVQfHt0AKOzeb4tTLHSHl44Z9XrRTUE2ekYRyBWIkZl0PGLc7/OYTU+W+OOjX+OnB69mj+L102d425/mfu9POY53MllgsBof4AjfengBAFgajXN1d4j7/Z0stti9a7LdmoMTzgHe8bYqZpHJcyqAV91GjtiPFkQEtXIQoy8uuItcktXvKX5PvAcAgNFArWypTE2EvUsmgpHG5xoQLZNmJefem4iCVINDc6N4JnQJ+OQhjGOSmdFBpf46Dzl46IXg46LELJQkNPMykaqVBVnmQEi595qPgUYPleotYnyouWLCXIBFfEJ8cMkXIl/XccaCXfw05oBeAHLwhTTGh0jEHdAsAlSEi+uENRCoOB+Q26ljFk4zB4MYLZqbeP09Izg5G1K4NsxZi+aKNieLwC+A5gYQjjLJMQKgb8AZikzKQxVh73bMghBIZMBTIey1eOvJS2jOIzJWS7hOorkUrGYOQFwrWB0AjywA9LSZQUqP1SVzZn4UmJDmYB4iH0UBpgVBaC4kjG/RXBdOisXTCf7m9Ecco4j2tj+FOesRiHlUzpb8ErvqOzgrgbMWH4BJg70RGO3vIPnNLXseHDxrhdxhdVXpihQ6/PySQtLWJEvFkxHEHAGfo49coMZ/bnyvCrPSd4rH5X6VdXeQlc6pIHwV3AQvtOpBy4VKlKDNZZ+EXtwoOktFS6lsveJPDtXvv+iyelMKAFmntN6eJoqsh1LFOQMVb6EWHf6y/CCiUkALhIpDongGgcKGZyuSZADPpsWJjv0MssQfXlgERiwHsK1XGmK7AaG+zb+0fXMni+fpfdaexW+zKtKU2YLqcfe+cFH4annzOfvIFbDx4UkBv5ghyIHA9D2gHCtUOIVI+Zf2/e0ltV/C6kBkDBYmfZA6QJu1WXNQuQTkUmFWGq+kn7qtG/J5bTvwmvuwFXgNQLmmgR+8FAx9Lt/Fl9SO9aF4N2nM+BhUtgXauG7eU6VHSsWJTufj6n694EkPgPX1Gy71gWtyqWr3q4iJfyMniw3hoFwKXscxBDNoCSqf220kvYxYku61YJc1rVOTZ+FFVWJeSqx9LmWX/D2XzJeYhNdi48HwmrKCl1cElxS2KmandCyvKbM7BSU2RIK47dKHTBnfiLz252PEQrKBcmoyeVFeCabyj7GQ9NbzbYkfsGZoVO5qSym4axmkBM/buWFOrXpFmRAH1STsmtKHBMByLW3AkVPbzgDpAXFtHAtZxs610SOQyFIEAOAnDq4V0eMoLoVvA9ySclupv67lqsy6P7aLJUUaG0JFrgFcH/L52q6M8cl0iQ96XnKEJiC0Hm4l0ESd0dEQq5mHoj06iezeZlSwnjILt296psITyMQ1QXA/fe/gWp3PQUwtXp8+y+lRgGMUZ0udQ23NxOTtaytxs1DYm/F6chzV5xIZ2mVDdraznd3J7q9nsUV+88JsiBAxKU3VwiyU7emzagNAflOn3zGJSnnT5fbqxR6xpxK0yFWSkPF78mzisVzkUPS+tOEV5WxL8g4A9m58zH5kLkfJ3lNIhDnJk6HCMZn6kCHcmjZVxTUXOgUt8vbkUSXymo3zReU18Eawvgdv8zEG4Vs+P/Kh7Bt4vySXGH+dr5nTxWtL3oBrK48i6aC2BDemX8W/m4AgZdFIbQN7cFRprQIQEwvXqs3YUwjwbYheXZEkTPqrvineFnsayO2Kqp4r6aImzyJlgbwWeGl6jd/0D3lD4yE7B7eU2J/wG/xylJCasyGHE4Za77cDOmkwH1rMPeGg532vk9ZsdesFwXwUYmrhWp3HoZ+M+G7/FG1fqsFOJgtc9V32LLazIYtph+PYh6XWHPO4o92vyaJm1o4IzVQvIg4PmOQmBM58xOwDGebjJOczSQ0A4OUHoNmUoeGJKKdrGe0pRXbdU9WlsMxALVNQcbGEiOnQTLTTNjCPDuBameHJbtZi3JdoWw1IgoxCR8JxRF9WDNGuLUQrch3y+lmuXeaAoFiHopZHkNcDVK8gFmvIWYQpz5dQq0O4RsFMqyWLBMxE8M0ch3HclzA9T4SZC6KTvIxqGMqdyGvcKyccG3EldVp0QWlDqlCMyEJCrqpGlyPL+WV6/8rUusvU9mrgvqx06ZdruT+25wBpqoy0E2AcCcNLk/zwkiWIEbcqJtdGQpvnLDlViNkTyiXxPO4SflUyJHYiYKee09pHDj4SIQmbJtFQJrcuwOuAm9cUpqYFxeMGEnDEmSTjYobEyHJN4ralaSAoYFhr+FHieuBZTy0CmvntpUHoI//FXsBNfHFYI3Fhp4zMjDZYzVmPNCbx+2A1/vDkfZzNpzjt+R5b6ga/+l3QOg1bEZlgbInS1HwXVYp0Q8t0GBGGNWipcxk6AMAHBOMLZ0CcdNTKghIdP1DSrul7PJa6HqLEHV8EOV+jvWwhhpj7S3wUi5DbTFanNtXKQsfUqRhcvkFSCjOlY8Xgymf8dzE4NDcezRX3L6VnhZG8/o43ZntpoVYCem4RJN/l+sawJ9WIDb1XcbUE+YDm+iD3JUOuR+SUJgDYayo3dHWZmkXYoKqvLY0Hf4/Q80ugu4iTTsPxkVSwlo+9JrRXAe3FOuuNpPSmMJVnBGA802gvbx0aYuSUp7CU+wCwfomwlEl8u2cKci0gRkDPVS4kI88eiJlJtAxRgDTsQU0fW/zq8YPMTsXkNxL6inDzmMEY6krBN9z3pyZec+2htIM566EWAjcRuPFoi64/9/WJghkE9s4JbRyzs9d6/O2TN4Cz4l59gKONv29iXdRi2uFsPsXykxnejPfuN1frdMs2lh0ALydSpqACWtXgq3qZEZQESRY3ziISgUli4AV8Im2J3oPtFaRwBWyVAF3AxrF8o+A6zqUDQNMwa1Wi40vFagk0lQBTwCZoyvZqAyiVtidwVAJ6+U5mIFj6d99JmInIBWRpqWImYkNO0PYCrhUgKzHWoCzBq4KA7gAAA09JREFUIDQpKYsEQUoE8hj3qXgWcf5zDWWwFMDFXqkmZKyOBwL6TsIPt2+rGkSWzns8ANQWUMtMKWqgpmMxGY3XEuM+75uAU1lmMJ3vqcF6Va3D8rgzmMrMeFyTJRBWAqaNe8y2JdcE24cNvVTfAObAsxwlADsL0RMS+MGjp/j5Yy4ADE0AGo8gFPYe8Rv8Rk8hGr4PHhzxtok2mDVr/AoPMPZNkRSMAkDbNh476MM1zJNp9rr06Qp/9vCfc60HAHzr4UXGUQDIwczjyQqn/RxvGonvPeTK6KVpcKZuT+wvsl2Ac2c729md7N56Fs+15yWNPyORHBJku7aKY6H+HUWlr42c+/ZvQ6gwA1s4jSiok4wcbrXHGhEox6u+iy2wV1In2/is/q3GBzC2IOlQhAzg2ihGqzAOIZ2rCxsq5ACiBkbpb+731vai7PWcc37OtaAKN1D/NvcrFnyJqKORtgtXziPrcJjSpw3AkqFbcQwgxjiyvka1VLWlrdQHsqmvFVYj9d9QiZukax4C5mPL4D0gBlcZzDcmLlJD8DHwPWy5/c5KwJR9mxeohJElOCuYCi+lsK3EmZnBmzIIS6M3/k7tLrXGUjdwVmJpmrLv50DIfXMmi1qycDtDsb0NwEa1aAJpVaCtIDZ/l9S0NtB8223WdSJVtL30sfyd6NXq9phKDeV41XdfYlJ5GxItP221k6ne03EDSJTzKDtic2JLp/G8mJZzkWsSpV/V5/b29N1Xd1A+5+fABdO/bbe7udMtfFFRQ499AyIGwm/2CQCgw8ayJLehOAvi9eb4sGRA1R+BkknZHiPidvI5EPLkNmvWCJHcOKgA6ICgApqGZ5a1DhCa78FO87a0DJHKwWmZ9/XyOeMCIMgAKRkpmiZSqRxO9Ty3ndqt/07tTrSBoAAhPFrJ26wXEJ8DIUfbgcSvw4joKYAFgLOvuy//ynaK3Tn/Pth9Puc/CCE8uMuO92KyAAAi+qcQwr/7uvvxr2m7c/79sN+Vc94FOHe2s53dyXaTxc52trM72X2aLP7y6+7A12C7c/79sN+Jc743MYud7Wxn99vuk2exs53t7B7bbrLY2c52difbTRY729nO7mS7yWJnO9vZnWw3WexsZzu7k/1/NPjAjD8+tQ0AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.79515361785889 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-05, 'kernel_type': 'size'} is: \n",
+      "[[3.200e-14 1.600e-14 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [1.600e-14 3.200e-14 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00]\n",
+      " [0.000e+00 0.000e+00 3.200e-14 ... 3.200e-14 3.200e-14 3.200e-14]\n",
+      " ...\n",
+      " [0.000e+00 0.000e+00 3.200e-14 ... 3.232e-12 3.128e-12 3.200e-12]\n",
+      " [0.000e+00 0.000e+00 3.200e-14 ... 3.128e-12 3.030e-12 3.092e-12]\n",
+      " [0.000e+00 0.000e+00 3.200e-14 ... 3.200e-12 3.092e-12 3.184e-12]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.96503734588623 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 0.0001, 'kernel_type': 'size'} is: \n",
+      "[[3.20000002e-11 1.60000000e-11 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.60000000e-11 3.20000002e-11 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000002e-11 ... 3.20000002e-11\n",
+      "  3.20000002e-11 3.20000002e-11]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000002e-11 ... 3.23200002e-09\n",
+      "  3.12800002e-09 3.20000002e-09]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000002e-11 ... 3.12800002e-09\n",
+      "  3.03000002e-09 3.09200002e-09]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000002e-11 ... 3.20000002e-09\n",
+      "  3.09200002e-09 3.18400003e-09]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.982818365097046 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 0.001, 'kernel_type': 'size'} is: \n",
+      "[[3.20000160e-08 1.60000000e-08 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.60000000e-08 3.20000240e-08 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000160e-08 ... 3.20000160e-08\n",
+      "  3.20000160e-08 3.20000160e-08]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000160e-08 ... 3.23200229e-06\n",
+      "  3.12800211e-06 3.20000214e-06]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000160e-08 ... 3.12800211e-06\n",
+      "  3.03000196e-06 3.09200199e-06]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000160e-08 ... 3.20000214e-06\n",
+      "  3.09200199e-06 3.18400274e-06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.8766553401947 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 0.01, 'kernel_type': 'size'} is: \n",
+      "[[3.20016002e-05 1.60000000e-05 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.60000000e-05 3.20024003e-05 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20016002e-05 ... 3.20016002e-05\n",
+      "  3.20016002e-05 3.20016002e-05]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.20016002e-05 ... 3.23222885e-03\n",
+      "  3.12821085e-03 3.20021445e-03]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20016002e-05 ... 3.12821085e-03\n",
+      "  3.03019585e-03 3.09219945e-03]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20016002e-05 ... 3.20021445e-03\n",
+      "  3.09219945e-03 3.18427449e-03]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54822470>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.960174798965454 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 0.1, 'kernel_type': 'size'} is: \n",
+      "[[0.03216167 0.016      0.         ... 0.         0.         0.        ]\n",
+      " [0.016      0.03224328 0.         ... 0.         0.         0.        ]\n",
+      " [0.         0.         0.03216167 ... 0.03216167 0.03216167 0.03216167]\n",
+      " ...\n",
+      " [0.         0.         0.03216167 ... 3.2554357  3.14960373 3.22194735]\n",
+      " [0.         0.         0.03216167 ... 3.14960373 3.05010307 3.11249761]\n",
+      " [0.         0.         0.03216167 ... 3.22194735 3.11249761 3.21242132]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483ea20>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.83794116973877 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1.0, 'kernel_type': 'size'} is: \n",
+      "[[3.2000000e+02 1.6000000e+01 0.0000000e+00 ... 0.0000000e+00\n",
+      "  0.0000000e+00 0.0000000e+00]\n",
+      " [1.6000000e+01 5.3600000e+02 0.0000000e+00 ... 0.0000000e+00\n",
+      "  0.0000000e+00 0.0000000e+00]\n",
+      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 3.2000000e+02\n",
+      "  3.2000000e+02 3.2000000e+02]\n",
+      " ...\n",
+      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 3.9599184e+07\n",
+      "  1.8790076e+07 1.9904800e+05]\n",
+      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 1.8790076e+07\n",
+      "  4.5132236e+07 5.0194600e+05]\n",
+      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 1.9904800e+05\n",
+      "  5.0194600e+05 4.7488000e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.827232122421265 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 10.0, 'kernel_type': 'size'} is: \n",
+      "[[6.52864162e+14 1.60000000e+04 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.60000000e+04 6.52896808e+18 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 6.52864162e+14 ... 6.52864162e+14\n",
+      "  6.52864162e+14 6.52864162e+14]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 6.52864162e+14 ... 9.71153321e+38\n",
+      "  4.83215703e+36 2.92253118e+26]\n",
+      " [0.00000000e+00 0.00000000e+00 6.52864162e+14 ... 4.83215703e+36\n",
+      "  9.73580847e+38 6.40218246e+28]\n",
+      " [0.00000000e+00 0.00000000e+00 6.52864162e+14 ... 2.92253118e+26\n",
+      "  6.40218246e+28 1.60883971e+30]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.943642139434814 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 100.0, 'kernel_type': 'size'} is: \n",
+      "[[6.40128006e+27 1.60000000e+07 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.60000000e+07 6.40128010e+35 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40128006e+27 ... 6.40128006e+27\n",
+      "  6.40128006e+27 6.40128006e+27]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 6.40128006e+27 ... 9.33493318e+71\n",
+      "  4.66723328e+67 2.81704975e+49]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40128006e+27 ... 4.66723328e+67\n",
+      "  9.33516655e+71 6.14653487e+53]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40128006e+27 ... 2.81704975e+49\n",
+      "  6.14653487e+53 1.53671603e+55]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.8396418094635 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.40001280e+040 1.60000000e+010 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [1.60000000e+010 6.40001280e+052 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40001280e+040 ... 6.40001280e+040\n",
+      "  6.40001280e+040 6.40001280e+040]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 6.40001280e+040 ... 9.33123732e+104\n",
+      "  4.66561633e+098 2.81601050e+072]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40001280e+040 ... 4.66561633e+098\n",
+      "  9.33123966e+104 6.14402534e+078]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40001280e+040 ... 2.81601050e+072\n",
+      "  6.14402534e+078 1.53600716e+080]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54822470>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.909621477127075 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 10000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.40000013e+053 1.60000000e+013 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [1.60000000e+013 6.40000013e+069 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000013e+053 ... 6.40000013e+053\n",
+      "  6.40000013e+053 6.40000013e+053]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000013e+053 ... 9.33120037e+137\n",
+      "  4.66560016e+129 2.81600010e+095]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000013e+053 ... 4.66560016e+129\n",
+      "  9.33120040e+137 6.14400025e+103]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000013e+053 ... 2.81600010e+095\n",
+      "  6.14400025e+103 1.53600007e+105]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "../pygraph/kernels/treePatternKernel.py:169: RuntimeWarning: overflow encountered in double_scalars\n",
+      "  kh += kh_tmp\n",
+      "../pygraph/kernels/treePatternKernel.py:168: RuntimeWarning: overflow encountered in double_scalars\n",
+      "  kh_tmp *= lmda * all_kh[str(pair[0]) + '.' + str(pair[1])]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.983099699020386 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 100000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.4000e+066 1.6000e+016 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [1.6000e+016 6.4000e+086 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+066 ... 6.4000e+066 6.4000e+066\n",
+      "  6.4000e+066]\n",
+      " ...\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+066 ... 9.3312e+170 4.6656e+160\n",
+      "  2.8160e+118]\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+066 ... 4.6656e+160 9.3312e+170\n",
+      "  6.1440e+128]\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+066 ... 2.8160e+118 6.1440e+128\n",
+      "  1.5360e+130]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98abac50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "../pygraph/kernels/treePatternKernel.py:170: RuntimeWarning: overflow encountered in double_scalars\n",
+      "  kh *= lmda * (G1.node[n1][node_label] == G2.node[n2][node_label])\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.90620470046997 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1000000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.4000e+079 1.6000e+019 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [1.6000e+019 6.4000e+103 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+079 ... 6.4000e+079 6.4000e+079\n",
+      "  6.4000e+079]\n",
+      " ...\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+079 ... 9.3312e+203 4.6656e+191\n",
+      "  2.8160e+141]\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+079 ... 4.6656e+191 9.3312e+203\n",
+      "  6.1440e+153]\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+079 ... 2.8160e+141 6.1440e+153\n",
+      "  1.5360e+155]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.90343904495239 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 10000000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.4000e+092 1.6000e+022 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [1.6000e+022 6.4000e+120 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+092 ... 6.4000e+092 6.4000e+092\n",
+      "  6.4000e+092]\n",
+      " ...\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+092 ... 9.3312e+236 4.6656e+222\n",
+      "  2.8160e+164]\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+092 ... 4.6656e+222 9.3312e+236\n",
+      "  6.1440e+178]\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+092 ... 2.8160e+164 6.1440e+178\n",
+      "  1.5360e+180]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "../pygraph/kernels/treePatternKernel.py:170: RuntimeWarning: invalid value encountered in double_scalars\n",
+      "  kh *= lmda * (G1.node[n1][node_label] == G2.node[n2][node_label])\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 43.08435606956482 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 100000000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.4000e+105 1.6000e+025 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [1.6000e+025 6.4000e+137 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+105 ... 6.4000e+105 6.4000e+105\n",
+      "  6.4000e+105]\n",
+      " ...\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+105 ... 9.3312e+269 4.6656e+253\n",
+      "  2.8160e+187]\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+105 ... 4.6656e+253 9.3312e+269\n",
+      "  6.1440e+203]\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+105 ... 2.8160e+187 6.1440e+203\n",
+      "  1.5360e+205]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 42.954649925231934 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.400e+118 1.600e+028 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
+      " [1.600e+028 6.400e+154 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
+      " [0.000e+000 0.000e+000 6.400e+118 ... 6.400e+118 6.400e+118 6.400e+118]\n",
+      " ...\n",
+      " [0.000e+000 0.000e+000 6.400e+118 ...        inf        inf 2.816e+210]\n",
+      " [0.000e+000 0.000e+000 6.400e+118 ...        inf        inf 6.144e+228]\n",
+      " [0.000e+000 0.000e+000 6.400e+118 ... 2.816e+210 6.144e+228 1.536e+230]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 43.21850872039795 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 10000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.400e+131 1.600e+031 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
+      " [1.600e+031 6.400e+171 0.000e+000 ... 0.000e+000 0.000e+000 0.000e+000]\n",
+      " [0.000e+000 0.000e+000 6.400e+131 ... 6.400e+131 6.400e+131 6.400e+131]\n",
+      " ...\n",
+      " [0.000e+000 0.000e+000 6.400e+131 ...        inf        inf 2.816e+233]\n",
+      " [0.000e+000 0.000e+000 6.400e+131 ...        inf        inf 6.144e+253]\n",
+      " [0.000e+000 0.000e+000 6.400e+131 ... 2.816e+233 6.144e+253 1.536e+255]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.10898971557617 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-10, 'kernel_type': 'branching'} is: \n",
+      "[[  32.00000001   16.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [  16.           32.00000001    0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [   0.            0.           32.00000001 ...   32.00000001\n",
+      "    32.00000001   32.00000001]\n",
+      " ...\n",
+      " [   0.            0.           32.00000001 ... 3232.00000222\n",
+      "  3128.00000225 3200.00000239]\n",
+      " [   0.            0.           32.00000001 ... 3128.00000225\n",
+      "  3030.00000237 3092.00000262]\n",
+      " [   0.            0.           32.00000001 ... 3200.00000239\n",
+      "  3092.00000262 3184.00000434]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 48.652103900909424 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-09, 'kernel_type': 'branching'} is: \n",
+      "[[  32.0000001    16.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [  16.           32.0000001     0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [   0.            0.           32.0000001  ...   32.0000001\n",
+      "    32.0000001    32.0000001 ]\n",
+      " ...\n",
+      " [   0.            0.           32.0000001  ... 3232.00002222\n",
+      "  3128.00002248 3200.00002392]\n",
+      " [   0.            0.           32.0000001  ... 3128.00002248\n",
+      "  3030.00002369 3092.00002625]\n",
+      " [   0.            0.           32.0000001  ... 3200.00002392\n",
+      "  3092.00002625 3184.00004341]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ad7ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.07687473297119 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-08, 'kernel_type': 'branching'} is: \n",
+      "[[  32.00000096   16.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [  16.           32.00000104    0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [   0.            0.           32.00000096 ...   32.00000096\n",
+      "    32.00000096   32.00000096]\n",
+      " ...\n",
+      " [   0.            0.           32.00000096 ... 3232.00022216\n",
+      "  3128.00022484 3200.0002392 ]\n",
+      " [   0.            0.           32.00000096 ... 3128.00022484\n",
+      "  3030.00023686 3092.00026246]\n",
+      " [   0.            0.           32.00000096 ... 3200.0002392\n",
+      "  3092.00026246 3184.00043412]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7c18>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 48.684311866760254 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-07, 'kernel_type': 'branching'} is: \n",
+      "[[  32.0000096   16.           0.        ...    0.           0.\n",
+      "     0.       ]\n",
+      " [  16.          32.0000104    0.        ...    0.           0.\n",
+      "     0.       ]\n",
+      " [   0.           0.          32.0000096 ...   32.0000096   32.0000096\n",
+      "    32.0000096]\n",
+      " ...\n",
+      " [   0.           0.          32.0000096 ... 3232.0022216 3128.0022484\n",
+      "  3200.002392 ]\n",
+      " [   0.           0.          32.0000096 ... 3128.0022484 3030.0023686\n",
+      "  3092.0026246]\n",
+      " [   0.           0.          32.0000096 ... 3200.002392  3092.0026246\n",
+      "  3184.0043412]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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94ief7SWS+SbAbXeieZlnzYc0IyKky/W+03oWCn6VHB2cRznKUa4ld0OzwD5MmGOS1fJAEhLHOF0d1fbLajdfZ7Us9qCbZAByMS96Oa5hwpuKSVE+CJyxkGZ2IBJnF4xtPzGtBgN1vkXZy8BkY37oh8QA1BSM5phoQKRYhpTt7GGY7KpvDExSBynZK8xg8XOzNeM/CNlUOpDd+dao22QSutigUPmAZmGPld+kusPHavJyNicOgan0XNa0AKvhWc2ovC9vOupV7sZiwfl/xs5UPgpF7U1AWjEKjgI26oFiegAowC1rZ1LbVny/picP+l0zUdvi02dTkFe+lzs5ER+HLgTjCGqb6sAr2ax+37lqfArc99N8kMUChNoHt1oi9UMBhik4Le06uOUC/uH9+rIVJ60BfQEVXxBjdbapOaPwZbVpkziDabWsWBDrF7K5EouFLF56HBAwaYzg9bo8GytusQD3xvcDwH/w2PhQss2ukS577xjF32EjVvNIEwBatAWnMLl3IyYtLTzS8xf1/NVSHJx5Q/IfPJZx0vdDF3MFf+nCB0h0IoO8+OykmgzqxG7GYlJMgGImEsSOJEIRUznO680e3J0B+G9+JNcezTvlHXi5qP4SYOLE1XNKu77xIdyur34TAPj2Vx6UVQdsEvWYnJNBRrPJKv9Q1UL0pewxs+15z4HIMcoqPwwTjz/HVIAwum8U0NQskawgCGMCu/xQLR+CgqP6ofhCJglanKTtc5Sidn+2S5boQsyayTCIj0bbnkFV1ASAHXizPcjvYKMUpG3DNDKhvBGHnNIJmESVALGBJ4lZjsADpr4Bs2iwhgiv4mzouoNtl71INqOJ1jk7xrtdXYjaZrpoZkdtdXBmv0gIwLMXExi4AK0iSH0sdjwm5EZUo1qqde26gxBslyNBcL6Gpi93wDpM+zRPgDPoYTo7rUA06PO6fs7Nl3KxsBGOCZ7CslopQk5xGCozxiTMNYuiMQwHNQt4P8n840E0C52EqrG4xeKVmgVmmkVh1lJPd46wUN4pCux914HatuI4gLrIWRwHUBxoZDAdjDoxxRlYzydi4GQFukKzUPMCTQtSs8j+PsaKEpxJGQ8dRwB0spqQ/ZSFZx5GZxYn4Emo97xCs5ijGZH7qykB0EmHqlnoMVqtZPKnlBcL1dwqrJz0+tkxDmbw+SncTLOg8c00C7y4qONs+3B+JtdQKHju7000C4GGNxXyzww8+7JFQ1RekXU6wV0YG+1KzeJAhumhzMqbahbo+zrhgIrH4JyxqHF8nYy3pVkAr8ZxaLtnIVIwi18movhptA0CEBrfmWYxnxQWyzH9ccJ80b0NzSJdrjP8m2XSzc28uYbgSCbmNty+ZvH8xb4fgtONNAu32YoZZTeUeH1/zTEacpSjHOVacqc0i1elqCvuwj1+NE0J1lV4thpT21aTIq+8/oNH2Xk6ID59NjmfI/Kqba4zX+EVyGN2dIWAcyc7gmI9xk8+y7+xmkXVEDhx9TMcyNQsWoUqN7F+X5CTExMi9/VQ8henuqv3/dR5p2bThx+Adx3Ss33sg5xg8A9We7gm+c0EiauBqIUpAaEOWpv5qWPjHWi5FBwEcBgDAUxRrXtf5oiZ3XVnx5x3cm2PqaOYdOePtR/5GdDjh0jf+2Sa3Dj3bxh5U/IbnGQz6P49sDq7v/N7Nya/Kf1+A7lTi8UXKnYyGMDUxNP+ptedq/X2mleFub5omZkg5a7OTV+W2QvL1vQAKslLSnglh8YtyJTBi2tINI3757wLUiEbClazVI+zmpXGrI1xgpa8VTFtoQMpENe6xKgmD8q1bhJRvVuLhY07z+RVuItDUnZYC7XN8f63j6vPeBTm93gXYhcsK3YRySFezdlQsVpIuVw/vN0i+iYya6u2qfgNrLyDRXiilXlnqAVi+b6I8lYcot2/DdHxGIap1nMDIe/AQwLSm3kf7tRiMYlmNG1VSYHi1IsvXwpxjca72xap66a1RDJ0m/t+kithTY/w0dfkuoo7OFlNkmz44lLwBONocBqCp6Cz0wn5CZ2dFo96eiG4kPD7flAiGwachRDASzGPaLOrsOhdB753JhPiibSRzs8EoNU00g/FSazXAqk24d8C5AkBOFnV8Vxv5OUfx5KxqbkRGt0ozNbPngMA3Ld+pEZkTL4Bgi+RC142cLtB2mvZroYRtOv3TUPFIqjzV3MmiEBbxafkFzh42a1VrV80oG4Av3gJ9+M/Kr8PEoWgyOUzAMSzBfxmEAdu2T0BOIC6CHiCv1CiG0a6dwJuPMKTCznUBOmPbgbzqEIbQNs85hqd+vwZdj/7b6J9uqtj5QiuGzGey7vn+gQmsWbiQrNOqXznhoTxVK63+L1LOH1nVGshQjpZIC0DwpPLMmbxj/4EuocNFs+G7EEG4sLB72pCHDcyEMkTXGS4XURa+vJ8+R9fvxrg0cF5lKMc5VpypzSLuXDiw3U9JmnYsaYhF2o8V2qJYDjMVl14I3JmZElSsiAVTlOTSE2YzKoMiDZE291eqJY32wz5NeZCSsVHwP1QYdFjFE2DDb2u7mpqOpnwGA+D2PC6U9sUbNv+rhNGKkMNqEjT4hhTzUC1E6V1y+2Fc5nXwuAZhjGn06faTgX42GxaEyamXV/vYVTqYrYV9X+GfO2Fwo/7Hu5yU9puUYx6PRqiaCG+4l3AwhdRnoMJh9J6V3AsAEDbXUVwZo2siPfCw6HvjWp62x0Wn23gLgytXvBAP6DZ5euaVH2v703jy3EaIlwnWohmkLKj6g9xDv5ZDxc86HJTxqz5fAMalvCXNUUgOAfqx6pZBJN1OkTRGlWzY5Zj15Q7vVhMKoVNvqD6MjgFI5kX5CZ2pHrhbRq5Sia/KY63G+SIEBGYHIBqSk3SzL2bfnaUVWbDkanp17M2kSIwb0ssyY0dFwuactmvYElmACBSBRjp5exv7LVu6t5RX4sjFF4dopq+koFOcK62ISXJUUliItSRjLVNhQv1hu1RmY0T+wwws6aQYkP0mAM0T2SCL3EOrO+MTTs/8E6zpuKb33NOZ2dPILsOHPJv3VDu9GIxkQJEmaI1yWfEXJjyOxQEpOWasPQE2bbnnfAu0molE1Mx+tvKT8BjhSS7xQJYLSU3APLM6fSkvhf6gM9Pp/Y7ADShMiKtt5VJadeDzzJXQ/Yp8LIV23TRgrq+7mR5Z6Dloiad6Q7VNOCTZe3jxVpeumEo/dXrkCJZG22DXCs9OgftlESo7t7s606YVg3cVnwW3NZXiIac4GfBdTrBz1YyHrlvIAJOVwV9WHgXFLFa/COt/C4x0gNhtuYmL6IJgK+TYDxv4dczfgzIBHK7EQgO7sWm9CndP0FqPYJqbWcn9drOTXZd9gReNHCbvrYBgIsRmx9YYbHQHBlC8g5+N2K4J9qC76IsYiw+BWDus2CMp/L7VeQKVtN3kQjx8RnSwqP5vC1jtvvmGXaPApZP6zOIrUPY1nYn9VkEghsZYTtiXOV3IDHS735ZEZyvktfEhm1yWFH/Felp0I9F5ki/lPJ/dfcjoglaE8jhshjLzq51LnkWySmq78wMqRDiaRiuaEOaUJUM+tJKIfSN4HktTKIp8UlKkssSY72vmgb6eRYZcWMyaFJV3dNkEaDRhBSjDX/Owsp2N7PmUWJpAXNpl2ZWso5dybYd5ZwYAb0vkSxczGBTDsH1CTQkwFN5PsQQkp6UwHPNIXI1ifK9CMiLBU8cnJSy9qAmixlj17OMGwBOBAfADQmuVzPDjJ++CiyOWTewnDu4Og7ZKWsXXeryQqzjgbrQ0Mh1/EiOIyu1OhCUCG5IoD7Bu2oO0uz1epXc3cXCESas2EazmGY77qv4Jc1czQv9rR2ZYldnNT94WSjUhtcMzpgAnydJCPK7bArodchVshVWUpQm5IlasyU5+Hr90fhYQpIdmhnOcDSSeuV9MtGC3AbHoDFfV/sUwiSjsLSLuarlOl5qyqimoYtG42tKtE58omr7AtJWImBM4KX6PNRvMBYtgVQPZjELSk2OPAaSlJf9LkazmCzQ6ofxHryo9j6iTLZk2hsXHhQT2Luyc+uC4IiQggMNyosZwY1DXAb48swpaxZUfTXaZ0/gNpSFsmgWzmFcOTRNjXLE1gGRixYBgomG5J2+lYMcGOyAuKR8XMokIDiA8tgEB248uHWT3I+4cBhXhLB15SVILQn2L98v5XFIDcE7AiUuERlKvJdF/yo5RkOOcpSjXEvuhmZBOVvSIAjVBNCq3BbibaHDSqnHXSdUeADQ94KpYBYKvAOAHp4R0/J2V52dyD4Nu5tDVPV4uQZtNuU8jlGiIcXLnv/97CmUj/MQDZxtEQPC6swJyHiICUkL0YQUB9ud9O8AYa91nCZbLOj5NEIxT0rS2q/+Ox9PB0ozHE0/SPsRDWGvtuVkWXdkHfeuF7+LXnIjfqL09Nke98UeYS8REgthr/+d/LqamhjeaJSBSEwvo+mBudQ5cTECD+7JdRPDDyPCZzWik54+q6bfAdj0pG35vrEfcP8fNTVKAsj7Mo5obTEkHQ8Tsat4jgH8KNPqaeTKuQkGJT15Bp+zZ3XMTvoBJzY7Vu+RcUYT8CBR4cpoTJqAW7++bnDp1rXPfNeiNPwHxJYmLFl2RKa4TXptKYBSAcwAv8hewzvwop3CeZ27WSkAvafNNFSn3xyBmcFAqqIjeBRgDleSGsrXsynfE9v2iyDsnWRJujp5bJQjU8uX9qYkJkATwMus6g/6XGZONB3v3e5mpQDOT6WtJZMyt0nfE+/El9OEajal7LzN/U3n4kim/M6kxpewJ1k+ixsQ9sYP79fQqcvmyravDuziW6oO9NQGMYW8h+sGDI+kXX4rACtuXDGPODg4dXIbwl5+cI7x/hJuO05MRxpTjoYw2Nexcm3zFSDsPUSrlwlsD9LqTZKSUl0UFJ14HVo9feicit+C8/VUaIzC8q0Pwl1/YNnS+s85G3QHtMlf2RladuBFW39nrsUxyeJ0WzLG6U44UuVoMP1A4gluRB22NMaau6A1PPqh4hcAmdRENw//DiYCVnJGjEOXBf3JzKCBSh/sgu8uMlYjca7v4Uok6E3D0dSPFZ2aCZBojFUztc9R67AMEZSS+EDGCJ8xGe4yv2/egbr9yM5ExgjXR7jelNjMTlAaZXGkVDWLt5U7sljcUOZRhMRgxKr+Kk8AX103ZAItJwaPOS8gOzMrXb35rWXyfk3dEKhZA0zMEDZENTZzkxMDKU5JeZyr5QsN/RyPt1y+cFKLw2ggxuTQXZaiqY2Rcu1TnSScoyXMk2rjFF25143KF+pmYIo2kasLB+V2CDlRbYNlwCINUadcMlALE2nfbX9n781VdUP8i3UFu2XtlIcBtJ26BIuJhOws19oi4whXIk25LclV2H3wwrVB07oh/uUl/JBrgdhExkNmiPbPgheBY/nCoxzlKF+83FnNgl6lpprCMuQ92I3iaLMUa6/xWRRVPtunahLYojmCCjXs0f765QuxWtbV/lAJQOuzYAaaKWFwsSu1iJIeZwZCuD2fxelJvV6q/hxxQhv8hGI6sg1ewsSu+jYKchOYZpLq98PqZj4LLTLkjB/FwL05J6GVxDegajvaT33ueYflJpQdU5zaN/dZpAdnoHUeXyJ5dv1g/Dl1PEv5wsaLbyH7ftI9cWy7tZghbHd/7+HOTg/6LNLZUswVY8VTLk41rYBGmXbwy+6z4Pw/M3m0vGBh9zZZqLyr9GllMUiM9Pnn5ZLu5KQ4A3XSWOIaVRv14ZfJlx9SvFwfZvc+EyebPgRqgjhLL9eAc3CUEZQ5d2OiZjcBaPJk7rqaubjrQCcyEdKzZ6X9mk3L41gne9eBFgu487NqC+dxIWsqAPJyqANYj6uZoYtFvq4/OZFIjsmynajchq6NFotars++1DFKVMkCv7QtpycV5KQ4i5OT6mgmmrzYk4UzJvhxNc3LyOq2LZ9IaIF+mOAjpI1OokkhlKxeuf9KxvdSImP04H7Gt7AgbdUM0KrvQPUjBA8OHu70BDym6hfJIDZk5yUgk5dnfgcak0zgfgCNEe5lNrGevhBzdNYF/uCRPLdla8CHCRjTtNZp28j4z60L7zB8dB/h5Q6pNTiX713fuLgbi8UNRZhVDy3wAAAgAElEQVSo0+QzNaGE/wCUkBSFYEreZ4RhSuL1B6oDdbWUHU0f8GZToy72XjCTENnhWIBSVHYROjmR1HJLNGNSyNkZLYCoePqRF0dtD62Wkri2kkWIx1E+r5b74VWTAi992MlESUkcpoCkq1snqxZk3oo9y48fmuvWKIPu2gDAqwVoq556M1l1whxwMOt4AKjlEM5PKgTcpKjbYtRogkzQcZQ0/nysJLKZUHE8X8KvTQgzCwcnqeVNmBD68j2pnqYExXy6EvBTSrLzm82LvQC2JnBvItDFFt3Xz9Ao5NpLfoqkqMtC6PpY+sdt/tfJeX47gsaE1Mo4tlq8eCbjfWmbv+wKDH18sEL/sEVr4N5p6eF2U5i6tNchLjzYE6KmqDOQwldhsbCIzb3vLCozf7bHkM2YnGQ2oTLTxBtT30NuJ4jGgsy0yWX2XkoBb5OigqW4q7h+GmcJXwZhSTbZyft6XCe6tjGbPpPwbj5/spvle074JQpdPU/vm/8jkwtTxq8JBUZeojXeFWQlkCeKVvg29+PcF/gDIe88HqWdep1RxyBHSEKuyRL13h4IEgovmlhGWZJzNTQIQT+6fl+tLip/4+Gsw68J8l2o102tB0VFctp+SZhVJ6qiWDl4xIVDUHRpXgSIgbQwbcntjJPzAEoe5Kicy8EfLCqUWmmb63zRutLCY1w6NK1ZMBd+AmHXxSA1DnFJcIOvi4VlzbqGHB2cRznKUa4ld1ezOEStl/ktCk0+UMOW/fQ3PArnAg9jLXtneBA4M1sVnwUw8VmUa+rnfC9qQikoBED8EptdVbH19y8vDvssst3NXVd8KWyrYKtKvN6IzyLGHKKM9fvLtYQJrYOTCBh8NSEg46QlEIuqvetq2xNPQ8ScQE+e1zZc4bNw2+v5LCaitPlA6bcbY8W7KJbDOn2RtZuUpC9PhM2LrvBZtJe7wxgb7wRFGoKgGLNQdvyqz8J5B5ffEW6bihfJ4+uB2gflzIgRJ7/9slYkUyd2jHAvc4ax8Vk0Jg+lYiJidYY+ewk+wIXaNEHuaUyUdjcgPF8W7AgANG0zHQNfNbd4toC/7NC29Zlrstt15O4uFnMzxBEoZ73Y6INNRZ+wHLdNBTBZZ+jMZ0HZZ0GnJ3Jc4+DbXY2Y2HstFvKyqiq92Ym/IcXq3AJA987FqWa5L00KOV2saxGaEID75/n4RWmPA8Q3sd1JdAWQCXJ2Ctw/n/oWsl+BFzUaQttO1NphFF8GAHqpZkhuq/ZxuxNb/fGDsqCVNHE/TWBKJ4vqVJvT6nl/2Geh4wGUfqf7pwZ45CSSoDR5ms3qhbSFNjvwafb35DTyCUIRwHhviXB5wGeRfQ3ceIF86/FH9+VY/jt+cE/MksiIJwFuq+Q1QiLDjopPhNuAFBz8RYftv36OxdPMTK++iC6WFHWXKf2AfTMkbCNoSMUMWfBhQt7+o3tIrUO46Es+5HjWYPeowerz+szHVUDY1t9bM6S/57F4vsC4yu94BNJvfVl9FnYnmyM6hxGkrE+JX69Z7DrRAIahZjtaINMbaha4XBdfAgDRKFKsTFaDCQXepmZxiHjYO1nICmCoB5yXnWpzReg0t5c3WyAluAz8kcdxy5pFP1ReEsvIZYsK5fty1xek5W1pFl59UpwZrQyrlvpUCogpeDjvQJcbnDDfvmbxvexn6vryDrvV4kaaxWLRSK3TRsPK+IpoFjO5kjXrVZJZkwqV3QHH0c2v6fbht+qUfBMI81u1xZgTh8ZHsRHJOCv1eGbxsiUDr6wIdltCM+ezMk5Z1mz9/k2e/xu2SaIfhp3KDovFmswrwL2LthG9uafRz9p6w+vcqcViUmRotroq3sB/+Bjx08+q7yET3Oi/RbwvO5XmktgiQ8rCrZDrlAvkKB8FUqwAK3MvRwq2qqYNVIMB4B5LkaH4+RPMyxeKDyHjO2ICuvzwYjS5H/Jv0kzWmIvO2O87qXc65Qd1ABjMs51Vf6caxG6aZagLhHtwH+h7pJcXry9faGDa1y1fSLyuWl3u9+Rd1QVsVr90wuKen9khKDaAKVvaXBTEZcsMjuPkmGvaCoJTPtHcLylJmKR6PCA7NhH4wT3g488Oly/U6M0ryheW8XpN+UKvIe6zkxqJ+/RzuBD2NQk7BiblwD+8P+GPBXCEex/lKEf54uVOaRbFDkbWMsyKqyt3/ORT+MePauLOcgHe7gRVqPZ4tmVT1wkyM1+jlBRErusBsdWJSDgzre342VO5dkoT4JZU8z6pDs6XF+K8y/fQEnv04z8M2vY1UxMALxqkM3FUuhcb8Co7Hdc7xEcCOPK//Ymc/PiB8HQuhIuTF9kR+fwl8PC+8HBq9WwFSy2akoINAP75pajT3QC+Jw5d9zJXEc8JVHrd9D3hC4l/6FtSEwQoKEP2hNgGuIwxGM5ahLXwhMSF9awLErHgPwxsPD66B5cBWOlE+j22AeGlcnBS6QN1Ayg7ONNJK87Jz59h/MPfkmMLcUJK3ZCq2XQPG7QvRmF/MiYaB4ewHpFah/aTXDGdGf3XThFbh+V3xWcxni/ArQONcl2y9rwjjCuPsNbaJ7LPtr/zFJ/8mR/H2cfZ+RsIKRDCJqF7KO9I2HEhFR6VESsQmIBmy/A9ozuXE+7/yy1cL9m6ZGgEN4+XGFcOq493Zcye/8k/gM1HDqcf13YOK0KzqX+nJr+XjdQNadaM4TSbzREY/45JD3iN3KnFYk84AYZjsYhVs3Kq9BTHX6tTX1n/0qAfmVwh1yVr3ui9rG9gEFr6AjAaRvHyq/NOEZzbXqIV5t7yDucHZdXWYZQJan1N2ZGrtPslBRqQyTjGEl0oICrmCegIu04iQMMA2hiHLCCAMeXoRDV//GUnVPLalwxqoyGW9gVA0rJjjVoQC638xJOfZLFBYlko8ndul02f3VgXPIXPD3FC2OuSlBHgfihkvK6P4hBW34ImXBIhXPal0E9+kAADrh/hOlcRtYkRLgfQwpc2h5f8SsJe1+8T9mLXYfU0oXmRzbzgZLEwpLm+SxmABYSlRieEoZxGhu8TKMr1/G4EDVFyRgy3avu8Q9h6hJe7MmaL5yPYB7Qva2Z12Dr4bSzmlBL2ciC4QQh7w7YS9rrx+l62u7tY7JWvS4e/09TquZ2XcQPl3/k1JklYeh5PCXcOpbbHaxL2xlQXMrXrlbBXbW7DBUHjzOdiyEwmRMJ6ncS3R9hr+RcsH2XhkHDS3phA6jRLqFEMMourQxnXEoq1ZDA3IOydQOf1eem9kReRmISD0tc2kI6vtqk8iwQKxpk68BsR9vouGcJeBrEsNL6TBcANxvdF5nosk9X1Ca7Pi2V+DyiHhgGAPQ4S9vouwXdC+GtyGuCHJCUBuBLypkSyKH1fEPZe9Z1SvVlH23Wub6IAk8zKkszkKluX4U+4sdhM06s+++pVn0Qt9LjmnQAVan6bRYxtGzX6Y9qreAjSzFwAQF5YciYokCe0jbbYRLG3EQdwoprVqsqn5rzk/Aw9Rkl2asmfySePcp1ScwY4uDlcR9iRIYnW2iWESTaYg4yP/oYAAoF9XthUEfKCJ7JlGXFVlIoAdnqtOgZSTwRg24AvIGpzdHAe5ShHuZbcXc0CmIbQLKJzToCru581Tw4lmFmdy/J1ElUOzDlfpNEm9DxBcObfN0EyNzVMplwDi6aqtLojBw9eZNBUjKZ0YBJORjZ7QRPEAemdUKQZlir2TgBYM9YmLNqC1ASyXyRX4VJHJiloTMFbGfGpGk1aNaBeHWBcigwrshEA0jLA7eS+mi1J7AEagd4+s6qR8CKAdlmtVntf/QNABbkpUlTNJUW5NgEpc3uKX0H8S0VbAaS4MHPJ/JSTxRlJfeal1JKC3iEtAuLCI5TyC04SxNRnYfrCQc7Xt0OLK/mmwXDmih+APRWn4nCezZDOydbPQDQ+CzDDDwwXCMNZzjp9FuAoFyVSi9gT4qqRosebSrMwnAX05w6+96VC27gkNB7FDNG2pECIC0LwVAoaUQTS9eks3m6xIKJvA7iAGAUjM/8UET0C8DcB/BCAbwP4s8z87KprXPteGodOKFRkAISchkgyOi2DdNuKnZv/rT/OHxX+rICt1UJsQUs6k0FDlaWbhI/iZFUXla4XCLdCpDOOIp0txZk5Gr/AImC8J9GQZkyIp7liVUyIZ/K5zeTa3AZxui7aSdQCFwDaBmnRFGdmSR1fthjv1yrqIZPTkPclSuLnRDG6uOQ4/nB/Ab/NL5Pa4cEhLXxB+/X3GrQv5WWPy/oK+c4jjKnWAlHTCkA8XZSJFnM0JC09gqrYGZYcl0H4KPO941kLf+nh19sCn45LWbhcZKmLkdfM3WOPRaCinsvzlYnZXEbE1tWKZezQ32+RFoTmhfRhvLeQrM0xgYOD76qpl/IkazMsW2HbqxdLrL/uQClHlbxMzGbpsHskjfC72p4xPx4OGe69YfgO6M9lrJZPArjL716o793uwxbDCcHFVRmzzYce62+SODWyjKeE5sIsTnmtTS2BRkZ76dCfZZxLrNGS68gXYYb8cWb+SWb+qfz3LwH4DWb+MQC/kf9+J0JzROCrT369HVd2RjfVZm7WqP3P8/s62n8SV7XvlpGMe0VnTI1Tpvo9k7YR2GebMUJmly/HXvObq0R9AfO22uvpQkGYLBrlXCf/cenTFzyepi12vDBr69442+OK0lSt7Iom7l0bs7+/4K7dhhny8wB+Nn/+FQD/C4D/+G0vOkHB2ZyIlMNG9phz4L4XxJ3+O7tGqbGZMzNpvRUzZjTRAs4RBxuGy5XJNeGMuw50sS4YEb2Xe7ERM8A6+WJEk3dM2nbwGvLsBoTnu8m5tMksz10vkQQliQGAfoDfdvuh034QbUL7mGud8jDAa7RhIzkM5HLoVM2mbJ4sPt/WkKGaUJT5HTRi0kvyk1T/rjgLGqK0VzUeE1UJL3dF49B9MLzgvVqnblbr1O2k1invOrRPch3YYoZIopSaY75r4DejOAxNlIZightSrkiWIwFjwuJZh7gMUrcVQLsbXxk6bQ/UOqWLNc6/E7H6PB93UpEsrEeEbZPHS94hMlXK4sKV0KUbGO2lXK952Zeqaq7P72JwOPm9lGudbsqYnX/3BL4PWD0di3aVGkLYplw8mqcVybr9Wqe+e3ehUwbwd0nKjP+3zPzLAD5i5u/l7z8G8NFb3mNfvKsVr5We33sgKT4gTbg52SlYy1xDWa/UNm4zB+asxgeRYeFWn0XbVq9630sWpfJdZiizAq4modMmVNMjpWpaxIR40gpOIt+a20bMizx5eEJqI9mlZQOxoKzTWhjZ51KCRFSzXU0iFFnzJvd7PGsLLT1iDn06h9RUrsvxpEHYDEBw1QxhhvMOfqhhT1ZTDuILKX3L94zBlRdwDsqCBWU5B2y2xXyRiSYvu8067R4EtF52YtVmtJRf2Eak1kmB5Pwsx5MGcenQZP9DXDWvB2Vlc6mAsl4ssHvk4PtshgRCCtKfnYKyOlcm77BSn0Ue9o4ROkZ/JseXT4Pc1xGSmt5EGO63GFfie9Ex6x547B4T3OiLO25YEdq1q+USlWq2kcLIzdpNQFkpXF/9eNvF4meY+btE9DUAf4+I/h/7JTNzXkj2hIh+EcAvAsASJ4dOOcpRjnKH5K0WC2b+bv73UyL6NQB/BMAnRPQNZv4eEX0DwKdX/PaXAfwyANyjR6/XhSygam6GALnOhpoLmYU5p3cfcnAWFX6MYobslAw274q1nRMzhLW6lXrvMxFsSdDSBKv1LqMveVJsxmfiHNk9s/kwRvh1J9EGVeHVYdoJCrQgPhWYYwh3yj2HoTgwAVQo+zhWEJHW3sgJRxodSXlMw/NdBT8ZjkvyvvhVmiEK3HqIxTOvf1NXWa0pZZgzs7BWa/VvyG4Z+qGU6NOKa4UuUM2QrpdrbivM2RuTyCI4XZ/gdyNScKUiGSWBoSOJaq99ozGhednBDU1BrIZNV/k93ZRoBt7B50pjMgihjPHpxxGLJ/l9yhR5fjPC9TlioiCpyGi1MPLCQetG+y4iZKey34hzlxsH12VHceOx+GSDZhkQnlyWMVt9egZwg8XzsYxB6wlhF6sZohpbdti6XcTC0Or54R2YIUR0CsAx80X+/CcA/OcAfh3ALwD4y/nfv/WG1y/OKQCVgWochYAm+wioaSRcuViURYSI5e+Uco7JAdatTP5KGykGxGdCfqMhMbrciMnBXM2QpgGdnIDOTyunZWIhotFz8ssYH53B7YaSXwEAqQ0S9XAyKVWt9usO/QenIGYscu5Gun8Ct+4kZLnpSgjRjRHpbCll79aZuOeqaMiTzNW56xHvS26If1GJdm00hDLPQ/fNM3lhgbx4iYMytdUMGU4DwibCxVTsXzAj7CLCM6PWKq9mShgfnZacE+03hxOE53mRfWU0pIcfR2y/Ic8sLggUZewVNg0A20ceyxcRyVMxTwQWDoRtQlw4rD7RMUvYfW2F8cThNN8rLf3royEvtYJ5joYMI57+eMD57+ZFIACxJbSXDbaPpA1hKwELSsBwou9CHqIdw3cBQ46GPEiAz2Felyu+syP09wOGE8LZ0pcxe/GjLS5/kHD6e03Z3cYVob0I1QxRa7gluD6gveRJNGT8zXdjhnwE4Ndy9CEA+OvM/HeI6B8C+FUi+gsAfhvAn33jO1zF06Dflc9TODczv94RPIFTHzqeKnxZtZebIvzS9DcFF5GP698UtXzhrF1jBBpf8iAAyGJ0RcrMFyJzCHCyEGWTB5Jk3Moimeo4Kh5jAqFnnh6XM2/WNh2vlKHMSSagThRi+SyLB5djTHq8wr4p4zRI09EBvOmg2jaU+zMXZjc9DjbvAFefyqQPGZ6un18p+bcHxwD1GOaf31DoCyGEeUu55x7zT7t/dwJhdqen4H6Ae/QAACZV1P29e5M8fd5upRBLrqLOuw7xyVMUboQZLwUA+Mw7ITfz5VxSx2Wm1afLykIE7xE//qTW6ABKTY/CLqUJWV/7sPzsYDjXHlPGbc71KvR7w7lY6OcAwDukz55U4JLlq2xMHVTlsOD9IkPKT1HAWNnMCR99WOHFWmRIozQ6NuoI1vJ/eiyK01a1IC12U0y8LAVI9emT/fKFtiiU+Zv7Af7rX8vjVUPQHHyd7EQoxaVtkaHNTv5OCelB1igVQ+KpmhaffJ77m9+bOS+E9hmoZuh2C/rR31cT4ojESbvrKxanbAqp9t0WKe4HpIe5XbluKTde6p4C4CaAPv5M7qk8JwDomx8hna2mtU5zzZJDVdTp5eWkhCIA/G+f/U286D+91qp9hHsf5ShHuZbcbbi3NUE0RJrixD+BtgH6HqSwYD19tRQMRdtUCLbdsc5zwZohsyUt21JZGxDMAoIXBKWppOVOToREV3EW6w3o9KRwOyblvnj8QH7HXDXAJpR6E7TpSik96nqk+1I20F3I79P9E9EmFuKAK+dm4lpHH+zjLAwhMDDFWZAWN5rjLFQTyTwc8Qc+qPgCk8hkE5vSIojTMDJ4YXbwQbJcC9DJ1vQ4XRRHosK2/aKFm+EstFxhyVBdtsIb+fwlxh8QbTAFV3wRE8Le7EuxiWTEDBrP5Xo5XR6QXX48b5Eah8Vn8uxc+41X4iz4AM7CffIUz//gQyw/1xR1Kinqw5lMLzdw9SEsKu4BDLhRsA7bD+R6p98TLg92BK8s3I5AZz9QcBY6ZutvPcbmg4Dl81j8NrEVnIUiOBWhyZ4QNg/3cBbpf/8q8FnMM+0mKeozjglgEg0h75C0XMCkwvl+NASAmBVbiXKQdYYSiVpn2qIkuqqGpq6ThMICytJoyLa2TSfCGEUlzynqNp28RAt0seoGaY+qmLpgOSfw71xqwN7TEgIDEKCYkhzbUgC5z2zyUwpx8fN17X6quRdkzBC3HYRvoR/A2QlHpkIYZwcmIpcJ6tZ1vF0C4CBlBwYT5cntQoyVcmAjJh5vt/Avtnk4XTGN2OSX+LUUAeLGl0WMotybnYC3FG5PMaF52YtDU4FaT55XMmCiSdSNvJf+a5RKzbr1Biff60qkBkSSO7PpES4V5KBRr1QWmbQIpa2uG0FJ2uW3ArDiUDEhvPAIHz8Xk+tyU8Zs+ck53LAUQp7iCwHcUKMhBT3rCP6lEBo3yuieCYuuK3d3sTgQwShiH6RqHEptD0gJAFPWsDg+J6CsPGDDgFLez6ZcWw6Ici8ChSDlA7VCWIy19KH+DhDQVNYsClzau1pGsOsrMKwb5CXKkQ8AVaMIDtSNtV1dJ9/ZcoC6QJnyiIB40WWSj6DVqo4dAC1ArC+9soHx6bJW3dK20zRlmtv8ordNmZSc8qRzKBqEJKJB/AjLRb1unjB876yEAXFF6LSAtIYRKUdu2ADEZDLkfI2TBn435uS3POaOke6vZAIRFd4JOT9MoOhazvCq0CkfCJ1iGNA9MkWtPUmJAEcYzrMG1Vd+CY2ipJCdtBHwjUN3P4dOt8LJoQlxcjIjPjxHWgYE58qY9Q8W2D0MWGStBchIzV3to4Ku2BPCKsDtIpIJnfJ3ru/UvbuLBYA9AhyVONMymGWBMKfwMErIU/+dScEoKBuU7sjeOMssQU0+l8dxQnrK4wja7qqDszBl5ZohphI5jWRIaGrClTjhuslOoBoFdZkpyxKrDiN4szmsWdixydB0HurOU+gIZ5pFofm/2E77fIhzoxuLZsSDKVKU+1qrh8szoZiAbV/a4NTh9/LyoGbBsTI/oc+aRd/DXWaMSPD13QgGht6NssB6X0KxwjJW2bHSSXa+xgh/2U/MDXp5WYsuzzQLeC/Ob1ucGQBvd1h+1iG8qPSA3Hi43VhwEiUKlBKCLpQ5i5dJ2q3P3W8lRYC9MxmyBPdiDTfTLNonO7jI8OvBsIUh11alTDtYHZxu3QlDnNEsrKn1OrkjiwVPTQSgeqLVBzD/ha0yhuzd1wc59K/VLIoa2ZuUbaCaDLtOgEIK7IKYgdfXLHJFq2Qo3ryvqeK7voKX+kEiCMygjLNg9ZY7JwuFTqZhuFXNIp1VzQJq5zsC+1qDMy0DqBOTiU11KxpEGyvUeiWkzZMiRawArxtqFpwneslTSZj4ReIqaxaeJgliFBNoSFKwqFAGCu6Fg4Nb5933jTWL6i9jRwKoaoOkzAMT5iqrWYAhk70LJZ09bFxl9VJAlXMHNYvh4RK7xwELT2WxiK0TUJamqFtQ1lnzVprFMRpylKMc5VpyRzSLK8RqGwYjIZW28jpnqn5p3RGQQ9p1ACdRuw/gLHhdHXnwXjQMR1XDgHjS2dLqMYO7TkwPg7Ow2kcxCZ6/rFEQQ1yDC8hObftJJHU/Yyz3F2SpEx8FUCudkeAW0rPnh3EWpuKW1jJh5lKm8SqcRamt8umMesRwUmjb/AsW9X8YS20MxFR2ZMWKFNNpjKAXl/WSnTh5+elzpAM4C3tM/+Z+gP/8hRw0Dk5rhnhtRxOmplDBWTD4LGtYw4iw6yYs6fz0+StxFnQFzuL0Xz6b4izaBtT1CCVZsWbf6nurtVQ5R3/Cc2kX9bniXhNqBTbvgSfPpA7rdlfGZ/ntgPbJqvym9DemfQcnkZgwM5zFHAPzKrm7i4WbcUioWsksYVJ9aG0DGkepQ2qcVW65EBbuti3q+iR0eiahUx4GGbx2mn2J7U5U9bapJQZCAC0WEzMEl2upPZrLIZbJ/fC+TBb7gnhzn36o1xhGKRGQAJdBYHy6Ev/GIpsj1nw5WcLRw9ebIetNzQ3JZojNDbFmCD+TosPpaw+rGmwdnJ6qo7YRSDTGZEKnkNwQBQQB1dE4jOLgLBm+OXzcNnAHzBA3M0NcN4BfvET82sP8HIyzNbgyUeJJA78ZhPFKoziJQcNpmTg6cWmUDOC08Gg+y+e2zY3NEPr8GS6/9RBLm6K+cAibEeNZTlFXMyTVFHXN4qUkOS39fbne6pNdaatT57F3oJOFmCFPLsuY7X74MbYfNFi8qD4e9tnBeSh0un2wb4ZcfNlCp5z/ZxaElFfV+FKqUE3qiAxjCVU6yCJAKSB+9qRc0j+8Ly+kwV+Q9xXCrfcaR2GUXmamLJdfvKfP4LKmUu61WMCdnwGrZcVjAJPcEGrz4LeNXC8ZuLh3SHnS+21XixhvdmLHewgyE4CjD6QmyckJeLORWiUA0rPncPQQ6eFZeXHJTCytSwIALkhuCPqhpK67Fzlfw7ucop6L9zIDMWI8XcDnMGdll6bqO4CE/Xy/K+nr5UHECHqxrc5jI7Ro6y6WfzN+eA5/qXki0q7UeKlPYij8/HaAcxKSBFDSyMv7oGvueahw6izsCOOqRViP4Nah/Z2n5bt4Itga3cGHr98vNUlSmyn19TqBEBcezUXOb1l4gICWCLsHHr7LeRweZTfvHkh7wzaVqITWDWEv+SbtOsF3lYrPbUdBZM5k80P3MK4clksv4VUA3cOA3SOCN/R/wymhWZtQv9YNaYHYBrQXCcOJLqRA/KfvLkX93UquI2JrgUzqg1ixRW1nPI8gqi+07h67TlQ0rQdir2nvFYUwpiRvxSgOyjHjPLQUwGZXrqkyqeux62omaN+XpLByz1yLhPu+/pv7xX1f65KY9hFQ6pIA2XGqNUd2WrhZQGg0CjR6wiYOCF5gVkUd3pV6HoDMTQ3xTrzp2s5DVdTzeGg7AcAHB9KCRjnaQnmhULwLxZizW7kWJLqiinpLOFhF3Zsq6hZfE17uREvKi5hfD6UmSVqEEs3QkLrbRfiNFnXOyVox4uSzEe3zmnWqVdRLNuw1qqiHXNfFabbyTJoXK/itR7gcSpLd8skAcIPl09rnsL26ivpw6tC+GBF2VbO4Sd2Qo4PzKEc5yrXk7moW81DqpLCQCbXqZ3vMnj+/jsqsELFWNSt3sYWW5/cyxXkmhYkm1H9RtIpZpbSikVjsRIzlc1LbMxcuohjLv3I7lt1Wixhp23MSlSUIRskO5doObbuaZHPw2zCaduXdPUPWy2QTjvQAACAASURBVPGhttfuSzTGUsx5T3Q8zHWkUNHMiTjm/hhtCWO2yW2Bn4wYJVN8Sej+Dtw7/5byuE76ClRqg5hBZZFBIU18N+zEVKslBbO2kBi+SxJKhmAi2EmI1mmRoT4WH0phB88aiOtivaaOzYFixQVMNqaidbkuIuz8hNHLuzj522nFuJzO74dU0/cZ04zr18jdXSzm8qqiQ6863zhJiejtM3Vz9Wxz0YrNcIRJ5bB3JYVYmPbaxo6Kil/OLX4GA7QiwVK8c9F2ZQo+JuU3NeA45+oYv4P2KC1fmVQREzwHkJ23NhP3lqXczwnu4o2u4c11AHDJZb+e3N3FwtYJmR8j2v9sj9lzbcUpe3lT9wOAJFSRCZ2SnWAmzVfP0ZdkyE7E8jJnzWDRTCtyAZO6HtQPk1oe5bhO3lyLhEKo/+bvKYRalwQomsWkLgkgu7bPaEeNwoRQx2SMU0dtYuEOtb8HKioz7+zppIVTP47lBh1G0K7DIdqDMh75M4ApL2eOtnDjxSZPJvLSCcJWeU21toeS1KiMZ+3BcnypcfD5d96k8KdVK8cutTRBg9RmB+fCo3JECKLSFmFOrZeFeDeivx/g+rb0gx3BB4fhXnZm73whcopLjXDkCEXj4PpU6ok0T9uDHC7xJCC2TgBmWcsY7rXYPfCVNBnAeOoRbAJfqz4LwnDi4AY/cXCyv/5qcWcXi0mdkPl3phaIrQ9Cpgp7qS3iqibAmvuRUg0xaiThZClqtE4e72pkw97Le5nYFn25aGsIknPE4PwETtGXWSyTVRhjiVD4xOW4vsylFsnJStqo7V1vgJNVrUsCFNPD1iUBpDaJTqZCFFwQq14WC63knkO2w6MVwmV+LVT1zcS8SuTb32/RuspspeJ3I/wwgrYHXvY8HgBKv4f7CwR9zhoNaWXyqHM1roI4HjcOwyMZA2WzcrEiFAFg+2GDZbu/McQFoV0IC9bqRR2f4dFKjq3lusO9ttQkSS3B52sRS+QirhzawujlwETw6wGX3/QA8oITCMkDzcZj+zijMrdcSnuMK2lv8hJhaS4cfM/lePtsBbcznCRZdo8bDPmc5lKew/qjgM03CKB6fn9GaC/rGMTWREMWhNhQYeWiyEg3WAHu7GJxG6JApC/gQtc79q7EmhjztpikqsmxuckCXM1KdksyqYehC3o2AyYtcQdqj9yG2Pqk5nZSy+Oq39xym77Ie876cdOaKcdoyFGOcpRryZ3VLA5lipbvTOEg2GJChwoRaREiK84VshpFXNLFegKFTfmaACb3okUrmAFFHGaGau77yU7tn1/u4yxMESC6WMNrYtVmi/Ak27IZ1q2Fi9hRyR4FIBDu9UYyENWkUN+IKWIEQBKORoETe3tMtY1oIjI5y7b9dL2Hs2DvSvEfAFh0i4KzcDOfBa83B3EWOh4ASr8XzJUu0DlBH64zOjN78d1OMklpjNI2XI2z8LvlQZwFG5wFXVSYf/tpkGM5ea990kjN2ZiQVkHwEUC5DzuC32Qzs/UCbBsi7v+rAYun+ziLJvtCroOzSPl4eHJ5EGdx8kmLFBzCeiiRonu/06G9bEqBIwAYV1fjLPp7HovnI8ZV9Vn4/vqa9p1dLOYikYwbmBCacWl8FvAeyHkdBYxkMkJJuSVfJT47M331bXDwch9HNSTrHchkaspvXXWMej8hltkryOx96UPJHoX43PT8EorUHADvi+0PABhzjkTmdNT2liiIuS+FAEq5atfoy71qW33lkGh8TdE340WJS3vnouOhn/U6JXSbF4sJ/2c+DpZcFPW/yO8IoKmDM7W+Fl02khoHCk6+M+3lcixPqDZI8aCRMC49SqlRzyU64oZU2pAaBzcExKVD0tRzDZ0aaDcY1cHZKvRfzqUkQLpyrnmuVmLjxJ/TGX/EwmNcEmJjj1EFFmLm4FwRwtaZdvGNzLu7u1jMPJsTX8N1cBaZbYmsZmHYvwtzlK7iwyAT3Z57CGcRc75HUFSnICQ5xUnMmrpBtASbjwLUCTMMk2Q0RREWnMUwSNvCWP7VtvM4Av1gUsFZFgHVrJQTY6i8E9BMf81JoSmCU3EmE2RoQXDGCRbEWf4P278xJ9Qd2BnLeMBEfLZDvZd3QvVXwpV5HIgqrkTh7WOqOAsTUg3eFdq7yb2Dk36NqfJnAOWYalJ+04NHibQER7Uym8nvoVzq0I0J1DhQP6J9MQo3BgCt4O66EU1+DhOchS42qoFsR3HW9nnR3vUHxy9sRnDnJAU/X7d5yWAvUHYVFxluZ5zqO40qOSnYfDmWzYC4jvN15O4uFodCp/pVCDXTNH+mEKah0xCA2E81C5uZp/wOmrF5sprQ2uG5rxEOm6jlvYRAdUceR4mObILsqsqofe8UtPETgA0vmlrNnLmWFARKXQ/6JJj25AQw5tJe2u5Aq5VEFBTCrUCrtilRD0AAQAJxrhEIPwrlmvJklJBtNhHGx2evzQ2J50v4C1/6VJ5LN8DFdBCvUcYDKP0eHyzh1/ncICX3hBSmhgfTIsDtBrhhxPg4J//Nc0OydI9atC/3X+nYOIR1K7khm8qPMjw+A7cOTV4sxgfLHGnhrC3UZDT2UsO0uVBaPC/1Tz9LuPjBFqeN0RgcwW+jMGjhdbkhAb7jYhr49enB3JDu8QLjkrB86op5tP36ApsPHU5NBEhyQ+oCYHNDhlMC+xa9li9MeOdV1I9ylKN8H8jd0ixU7SfaB1jECJATurxM6gpgyidhfsNdX/gcSvpu3xdzRlO1C4FtCBXElO9XUtPtvTZb2fE1DXvXgV5KuUQ213Mv1+L0tGq6KS/Im22FTG+3pVJYHKvTU0sllpKJuQ283Ur26GDal8Fivrdqdmb76gd41XC2O2l7xpsodJi3QjAcnlzumSHqlykw7SEWtibra6ExynUOJZLpeOTzAKBJqWgrhd07+MqNAXGgUjcAmy2C+jM0jdyUV9R2+fW+GRKyGYImFHZzAAhPMuAtY0yaz1uhvUtCrFvp+CDmRXAF1i2+DoJ/fonz312ieZo1FmOG+F2uImfMEC2oPDdDUps5OF+sD5ohq49bpNbDX+wqDWBihG2L1iSSLZZ+aob4aoaMS8maLeULGXBfRQfnxMS4rrhcQbxAioXQ5GDRn2tfUx2nBxCi7xJrYXES2h5DdDI57n3l9tSFwpEACLTt3uMg/PGW+2DJWcp/M2i3dfDeprDCzUsKvzpZDRJXm+Yw4c24/baZz28Iyy+cJAXweLPnfXcXi1f4LK4D9y55IDanxHqZSzQj/+ucRBrKxD8M9y7/WQi5o737I3jQ6KbxmxCqr8PNIiN6nMyk9uK9J1+9+JSTwORlNlEeQNoUjI/GHWivLhQaDZl7w5tQoyyqzXgnx/Mp3Hhg8OV8Fda2+H1vvo6HfgZkspVjWhc1uInTjX2uOOZcLVuQoyHWIQpINEQdhVaUrIcbXykCAHCTQ6cK8Q8O3DggIsO7NTKDolmoE5ubvADnSEaYhESFE1PDodK/w6FTSh6UiynLmPg9Tg69X2odnNF40sJjXDo0xmcRFzVqBUxDp6kVhKxGZCjxjRwRd3exmJshSnUGXCsawso2beuEmu9KFueNs05Z8Bi68KScdcqzFL7bzjpVFi5te871mGSdlsI65l4pyTalxxVLkfL4veOs03KdjBUh5gkHCZlnc+tZp4NonRQjHNHUDGEJ4ZZjThZ0iumdZJ3SEOG0jeObZZ2yE1YubyNOX4ms07lmQc5kkl5Ds/AOnPKOrC+vc5VU5Q0TyRCCnGtqokrdyiFjDLJNeuuJZO007KnYi1WNhmiuCxHV6ytPZqaY40In6ACm95dIZjAUkrpeMR3OOaAbbj+R7ET8AkgBaeHLZKeYisnhfB6D1guL92XzThLJxrNWKtnHWtrgTRLJAGB8w0SyYzTkKEc5yrXkTmkWys7NwwhbUR1AqVnqP3wsXJulFkgEOGV6PfObxIZ5OoOJPvxAPN39gJgJaktGad4RK1Bq2Ct7yDHCn5yIx193X2apbL2RY+7Bfbn99z6V6t9ml7VVznmohL1pHEFaK1UjCZ8/KQWNEGOtGDaM4GfP4XiKZyUiAX3Zqu9ZC0FKBUehFeelW1ydiQ/vCyDot767T1EITKqbuyYUMBtZRGSMSKNhmra/33X1uvk3fn1evzeV5C1jdwGGNQH0W9+t92QxMcnswoumnRYGyuIybyt5j7St0RB6eTE55hPDe2kDnyyr2aOm3Rgry3ouZ5genOHeP/iOlIqsnQFSRKPPOqYKlJv4uiSKVkB1ANJ6s09IBGBpsqOVi3T1f/42TpaLGtHL15+kGBhnd/zmY7gXmwmK1W/3I1dXyZ1aLDCbnHvfcbqy6NBcZBFxIOIaLt11sqDc0As8kRRLGFfbyplxip0r+SS3LrMJzcpbAVQ1ljOXZZwuorV8VSpudtr1ByfarYo1V+wEsVXVtO3vItJkiyIlrhykGqJNqZZdSAlIrhYteldt6/o3jgxRFOY0phs4KozcqcWCzcvqlsvJiqzfxZcvEb7+Ua0GfrJCurgUOv5tJb2l1VLOOVmB8m/Ts1oTw33rR+T3F3lHf3QOZwrX+u98LNccY73X6YmwgT9+WH0dT56DHz8o3BLp5YW08w99C/6ym9TWTKsGw/0FmIDF51uMZ2Lnhuc7dN88AxJj9Zuye8Yf+ADu+Rp8uoS72BbWbv/pM6SvPcR4uqjFeDUhbdUWzgcAaD9dS67Hti/ox/Ak1+/IPoji48i79vqP/X40a3X4qS9EciV8J33p7we0L0YpNLyqu1TYRjRPt6bqF5eEteEb9wokejwXDXJcebTPc7KeRguWHn4XS0RkPA0I6xHN7z7B+t/6/XJsSXAj4EaeIBA3Hzgsn+U264bKQGyAxcuEcUk4++1NOX75gyeIC8L5t+XY9uECcenkumFaM5QDZcLbmNspm8X5//scv/Xnfwhn35H2pgCkBmgvGdsP5ZywEd4NYsaQ0ZOpAUBAWANhx+jvy/HH/2wo41xycYiw/maD4ZRw/jtjGbNP/+1/A+sfZJz9Th2D/hxoX8i1wUDK5PZxAVAE2pf30d/LMPQR6P+Hfe6Mq+ROLRZW5k4yGxNms/OUz3PVeZTiQzTWIkSTuHJhxpaXi3ZSIHkStlKvvNmpeRwLazaQF7Gu3ysy5HaDTBqNSACgnuC32Wk2xJJ7QDHCb0bZ8DUHQYE3g0Q9rJefxiSQ7G4KcgJRJa4BZBcaJTu1QLhzv0s0Rs2u3O5mPRaqeRql7Sk4NIll8QDQBMmqROL6AvGBaIRmj6YEtx3Ld1q8uNF+oGIHKLJkmprn6dcdMAwIa42iOLjIQt5ikqgWLwnNOgGEGhJmIBByweFaUBmRETYRlGqt0+ZigO99yTJVWDWQw7yxlgLwGqLteiyeAYuLDE8PhNgA7Toh5oUs7BjsOIOg5GdJict2gO+4hJX8Lkllc09lvNkRFi88fO+kjXnMFs9PMJ4QmguuTOID0FxyWSyU/Ca18l17yXBaryoC7gZUlUcH51GOcpRryZ3VLF4pbGzHcmzmhyhJY4f9E2WHUYxCxlDsXWduV2c27+IIZbFt55qQZEZy0VyAbDOqWZJqeBAxTSpt630pVX/LxI5n2VUnNjUg2pWN2cckG5a9vmInSMyDuUZGg2G1jgw4hhuBlNOupW/Vprfp0DSmYu/Px44SlzZQVL+JBWBljWx0OcuU89+Zt4IZTp18g4T9JCU+mV1VTAh2ZDAy+bvIwMhlzCklOXectsuNCTQymGkCDiNOcD1N2qVj7HuGG+z9CG7gwhXhh9qmgnEobZbaHW7Q5K783E3bKcn1XdDnzuW3viP4oWomzhP8kKE0bG4EOU/alY9EfDVwFq/jryhOHhuTLqrnDRQmw3C9B6H2wm0w4cO4riisNlX0JNs2E1W9zmcMSeIp34Kycs/bdZvOPnv9DHPmjAyvcHIUuHillefaXsU+qAtKcSCap3CD2L6Vyfhx5ZhAnQ+ZmbveQ0ohyG/Z1bax1g8yLN5vKuzMK6f3Jyo7mY6fTN56TO9v6e4UrMXBCb0CcDWknMy9D4yB9luPv63c2cXilXIoT2Q+gRxN/51JIZ7RA95N/AtyEletw97Hm5yAnEcwvz97k0NS2oJKTjODjJeXRu81zzex/dCJp33Q33hfJ6r20XvAxzp5NKHJu4NkPxyoQITdmF+8kKHPY7XLXV4w1DfAIHjNoZhrZ7m9c8IhO1HVZ5GCgxs9VNNIwYE8wZnFJgWSIYx5wci3iQ0hhDzZPCb3crEe02eRMsdD8dt46TtR9llY2HkQ8hnlh9AxYu+QGiop6HINAUGpv4ASMrSbELM/WX0WlAHAepwdBBpu/S5OrpcaGYPiDG7keinUBTO2gO9lkSDmch/5l+D76segiK8I3BuYTJAJ27c9rqjJ+QLifcmjOKiFKAIzT2bO5ykikOTiB7SNnMehGA6fP9vcDQCxDQLN1d8Bgu/XHIDMtARAYv3tdHHg4Gp7vKsOQKDySwxTyDU3YcK27ZpQMnQVNVmyRHOuhyIwFS8xLj2abEYkR2WxiAtXSmfEpVDKWzYoYtnFJd9DE7Dy2MWEZHIaOPc7Nq7UCC05DBnh6Mb6txsbIIRyr7h02WRgocfPi9O4ynU/Jw5OLYgsLFJ6H/07tvWZx6Uv7N7saVIqJDUO44kruSeKxFw0AcOZZe0mpFaur5EPJvz/7L1bqC1Jmh72/RGRmWutfTm3qurqy9w89FyskRGysB89oCcL2bIRCOvFthAePUj4xQ+WbYxsjEAPvmAQCMZYyPNgyXrzYA3I2GAEAsluzIylHkbt8fR0V810V9W57cu6ZGZE/H74/z8icu196uxT1TWcbnbAOWvtXLkiI2NlRkZ8//d/H1jz9OaN7meDg5cBIpbtDsTyHad3MjthX84bwrCqvqpxA8xnjPiytnM+EfUtuVAIaajHoygXy6Tq3rK8xJ3L2ztYaIaolRsZco1v6fE2AqpSVkOMWtTRYgBEEjdfzCA0LTvlJlGLSh5H2dNyFprcDQBi7puB1oSZEsNNWaag5hYGSJ6BrlXLINaSkyxnAhB6OZGkbbekIQCYY1V30r8pi1KWpYK3OR0Ua76FRUP8mAsKTxb6jFluHGvuVNf4BcewtTQzch90P4l6EFDxFUBwAyIJkY6mPFUf+200xAUn+8RYfDl50rU7S/i0RBJGwQlyIDAZNiHqVDK4oFmqEtzEoJ7LVN0fUlGPOo6GuCgRBq/p3wUKmCP8XiMaAJwHIghhZISdbAujDVi1rSkRkAXP8BPgNQpuFAj2VCnvBHS7DGK36LOwB8JW8BGrN5BEWGQmU7G5HAE/Av2Wy3SaEuDeALO4j4bcl/tyX+5U3t6ZxVFplyEUAth4EqpZQcGDDw0ZaBiEU9D1jZhLM1NZWRKXuIrndSeJSfpULPMVAx4BeaIPA3g9FPKW2w/ImwFuL+wXUgLXfNpL50ZXnlx5FTBpcpGbEuJG3ndzwnwSQMzodQaRhwC3n8F9AI2xUHz9BetyJpQMRljK8qbH9KAmkg3joIlYhHSmEn5lKeCBOSFvVIFalyPTg4BO19+kT9McSJYeOqOYHnj0lzJltqQkMMAhw+9DfSKayxgc4iaYbCnSRhzIbcoNoCzJ4toj7H0Rxp3OO/SO4C56TGe2VCK4BDXJqTPLw+O6BCmAI8tTtr/OSANheGlLA1G7njeEjS4Bp/OuEL5yQHEbB6QPptOaEm/yeP0nAw7vMcLelf1yL8uq/XuyT9iRPJaZMJ9ofT0AYoQdwR+A6Vy2x+87+LECnfLjALt3POIJIexrstz+XcLhywl+9mVmEU+AtDL8S8hYcj0JxyNeUjkWJfxomgwtSFkx3gAuOaZmmwfmSUhZ+npchzs0pCzn4Iwj3+Ibzi14+yACjyNoH4qeA48jaDeW3AA7VtjOKmGfC+joDkB/qSY6c0ZQWXkqBKEKOLopgZ0ShphLCrToQmT46VDk+IuQbubiFAYAtBtFYXycimamKVxhFuWrkj2qy5H+IgrhCigMTEeAm+uN019qqvOcwaSDqxkEz6kqbDdR2bBPsjQD4E2hehvhr2T+7ey8x7BYhvSZCwGtu9bvT65M6fMgeAQg6//+SvQujdlJiSVkODH83GBdidFfJYBEcxMA+hcTwvBqUpYfPbpLXQIo9kS7EatPCKuXCv56RlwRhssqqeBHACR91G3rYENJQFR/QAmdCikrI/cOXlPNc+eweZoQtw79i6n02erpGmnl0b+spKywI3TXXJYhho2kjhAOjP5aBijpA8Et7lre3sHCtChui2YcuYJzSiBzN7fPXydx3vIXTPMic+UppCSzjpwLO5Nu0Rn4tPopCdRd8AaNFBBUK8HAtjkJhyCjkcpjYYr2nRy3eKtGaeMXtIAsehJQnIEJUI6Fxfdz7wQHiFxmAJQh7xODUuNKDijfpHJMCo38DcN5BbPwXNfjTSqOXPza9oajAMUhKNYBgGIuvhluUgp3K1bzBoVSxQaIZGYi7dN2J67hTW6+wwyKUDZqPUcXWXkdFTvK3c1blbKAlm6u55utb+xYuemHz1ne3sHiKGS5XIZ40aoAipIUhdAQo9LroyHW+XOU7L9eps+8qtEB7sRLg5IpKfm7R0MGqY8aL4zce4lWkDxBS+QiZ8R1WACcPHjw3OlrqMujLoAHL8uvLyIasvbloqDoij5DGipVOm4cmALcnBFPjKYt0313aJS6Zo2GZDHRsUEzrVXxivBG0ZC4OVqGZEbqqNwo8ynBJY/sUZYnlBkuybQ+9YRO6fAUM+LGYTp1WGmfpcF9pmjIdA7MF7YM0VlDphJ1yKECjvHErg/pAD9KWNP8R+PGwXnJx3EWjg23R0PmM8L0UGYK1gdpBYC48S6p0ZA04nNFQ+4BzvtyX+7LncrbO7P4tNJSisumZlvmql92l7rakGlq6tClUKGWv4mpMrNO6QGbC1JhCi2PayHHhQRglvRyzn7ZRluufJHDfBtBZgaDloY0bKFelOkzsa6bc1OB0sUlzNnQqjMvGI5v2q4yxebmvX3ODOKGUFW+Y+2tbSjLk885RT9uQ1mSHLX3xn7tdqvLljSp6e9XMXb1u2XZYefL9fwWffM5y9s7WBwJgNzIOuWKLTDf8oO/jmdRsAFbR6cl9wK2Zm8GIc2luBPPwjIwcxbKNwBQhDeptjnB+YpZhIPyMlKzrjcJtTbr1N63mpQ/QJ5F2KeyhqeYwd7BO15gFhxEd9LNuUQdiCF6knMqA5loPsg50VTPwabyTHgjnkXlODgZpJjhYmUvdgMh7BkcGls+vXH8QfJYin5lzAj7XEFkKHFSB5A34Vl010C3N4CT4BKh2zPStezkx7osqFwV4c64yXgY0H2tX6nkn+QMdDu6wbPotozuUk2FGiyk29Zlj+Ws5E6YnZ+HZ/F2DBZEwmZpla7Ul9SUp9LHn9TPWmFe85iYJ9CpOlaNE3i7lQFjaiwEm++ZXSBiBJJSkZmrJeBmJZhFTKDC9iSwie+Y2tT+IPiGbbeL/HJf7APLk2FyCAagjhO8paGPM8ILXZ+aLiez5oxYXxgCpolWF/viw1Ec0w5jMR0GAN7uhAUaY03CMqUoVb4yBa2sIG73fF8HJmu7MUl1IPT7oAMWC0YBABmLgUIapNL6c4TfTXWw0P5w20ONzujA6cyfxAbN3SjWh7s9+meqV9JV/KRVJw+7rqS/t7ICYCXJtU/onBH2EX6kEhnzL3fVk8S5pX+Hd+j6IP4jQMWsrrY4/07E8KzaF+bg4PcRYasanFMu9GsDUXMgnW3JALR/V/fdi1UjN/aJzhG6Fxl5FcTXRfvs9MMThH2H4WVsQtBLHY6Whh72Ce6QsDbfkMyFTHaX8nYMFrcUaoV2bysmYOtdpXsbWJcSckoyk7DX47LIp6hMyTZnhFed3PCWTxG0TdNc5e7t76PwbKsxsUgEsgvQuXJDFJAxMXil0oJE4E0PmqIMWkXgZhBAdpqqJker/L1vbohplpvJjJl0m5x3LrMvADUC0io/ZZaIDbMa4ZhMIavNYGxuQC4DRTpVc52x+Zy5ius66ZfiPo8KDFMIokXSLP14nhcK56U46OCpszlVyua+odInRrgay2CXTnQwniSak9augMfuxbX8Pq1aejkWAXOoru/2e0xz1aAAJOfGiYFy2Okgbn07p8KOTSsPP2ekTmY74aCDnwLiqavnxb1D9/ISbgqLPvOHhDD6wmYFAB8ZfkzgQBKtssHCEcLLEW6KyIdQ+vZ4Nv1p5R7gvC/35b7cqby1MwtmARZvhXYaHIFJlyHmbg7call/ax3AUuORCER1Ck5zkqdLo51x50kbV4C05VkYm9OmmoA+eVQotmAvmhtAyerRaXlMNe34iygtyMpc08wdFcNeyVuQGRyM6JRU75PEug9Ao/YVlyK8n0NDUt4YlqT1GJeABGdxVHEMw53KEmisOFHugxDJPqeOpotVW4QY4FnCxTVvpn5WdCzUs0N4FXVfN8s14zNqf/PtaH3RuYjNNQYopwXKR9J9P9cZSnlrB4vXlmPS1VEm6huX275ja9/XodKfVqdrvveKV7Z9mHEjFf22oMHrCGefp7Tn25ZmoFv0Q6t9YfoJx587Kmv2G997g8K3HfdV+9jHR5aOZbAu7f5sbVkes63/1W2i5lEjCXZc3nPzfaJluz7t4VCiSlz//qKujtcOFkT0NwH8SQAfM/Mv6LbHAP4nAD8J4HcB/BlmfkHyC/y3AP4EgB2Af5eZ/+/XN4NxQ9E7JRkZb1Pzzkf720xDNSnZ5No/rRRHsrzsXIOlx0mehtO8DK3etdzmhqY/JDt98jTtZ3PYmo8wA3MNs3qaCMYXUhpT4nIemmZe0Qm3aB+AylZt2kaz0vI1KlNmaJ91ZmEzR+fKbEIydi1VU0ykmBtVr8QlhAsiuEb31DEju5rq/1kLZVQFLtSISg2NW/vqFnPtxQAAIABJREFUjLhkGUOwA6N2+1FmspnrzOxVWIHVYQI/cnyZZXBGE7r/gURO7zSz+FsA/jqAX2m2/WUA/zsz/zUi+sv6938I4F8F8HX99y8D+Bv6+tnK4ilrCUtJHMA0F4O6TiT++24B1rlhEDqCvgIo+Q8AwKcb+f5hkqfm6VpuFPMc1YEHIVQQzjvQyQa02TR6GAQ6PyttJd4CANLjc7jDtBDU4SEgnQj4Fy4PyGtNKtuOiI9PAGZ03xNxgnwywG1HATzVARwA6OIavBpAQw/a6UBq4dChQzrblHP0L68FcBtn8LlkMNHlVs9LIiwl+qJRkfnL53Am2JsN9CXRo9CLPm4Cwl4Gc9PnIGbQlOF3Ux3YgpcnXWbExyfFoyJpAh3OV0WhPJsIztCBxrksOdKmh9tNIADTlyTalXqn/AhB/21qPz7w6K+yqkdRaRewgj9IzojldlByGJ+skAfCRsHJ/GAN7p3I6gVa2ADCkbBbVfnc3NB7AC+/3uPkI1/OI3eEbituYUANjVIGZtO9MCO4UT4/PJLtD4ASOi0KXp4wvrNGXDusv1/77OKnN9i977D5qEkkWxH6LRdlLhO6SR0QxhW6bVUYpwSk79yd4v7awYKZ/wER/eTR5j8F4Bf1/f8A4P+ADBZ/CsCvsNy1/4iIHhLRl5n5e3du0V1Kmz268HZoQpyTXMxsM5SjUp6AKQmirqHUG9Z7R2tBzBE8TVV7co7AYaxPe1t7HiZ5oqZcIywHbjJFY31ixCRq4K3m49Ss+5kXswlKSdprxkH2dGdeGP/iIIlkPM+gnYZ6beCLYkZTLAVNz+K6hjiNb0BEi6dv0FAkxfp9Sqxof6pRDyOmMcPv5wY30NDpIdYBr+GcWL8BgMsZdJjA04xwrZyMzgl/glmUrZqfKGyjqH01KmKkeha+4S4gZnTXESlVUZ6wm9R0OS/o9IDgNG7q4HZ6nViy3GHE6nlGf6GDiFLju22snArNhaFcs1NTTyW/xY8MJrWgsNCpd4sISz+OCHuPcHkofbZ6kZADYbjIlWuyJ4RdrolknVHOCWEv4eKwr8l/lktzl/JZoyFfagaA7wP4kr7/KoAPmv0+1G335b7clx/y8rkBTmZmotvsaD+9ENEvAfglAFhhcxPF+7R1rfeVtBO8rGFDqBqPgDxRXSyvABYp02YIbGpQvOplJmLT/d1B9SsdKOmYqglk1Pd1GTJNwGqoTmT61MybHu6gVnKNrF7a9AAJG92WAA4y3QYzumshTeVVB5flO465yuqNk/ACnCtdRs0yJJ+sajfNUZYhRGLH1+wLJT9ZG2xWFs+Gxs+ESyIZd66sy9MmwI8ONOeSFEaZ4SYvkQh7BDVgYtp0ZUaRdPmV+1AuQD5ahtix8qaX2dJuj/lMDYx7JWVl8Q2xq28696KS5QhcKtaIwyxGP92VNi04zGcBce3QXWpi27p7/TLEtDdtGXIxYP+Ok2Q3AOxl1pA7wvhAZwujq4lkugxJvSwT3Cy+IoeHsr2/DPCTLJlMCVyWgQ5x7UBTLn12eOxVM8OXDNc0AN2K6jKkq8uecCB0W7dYhrR6IK8rn3Vm8RERfRkA9PVj3f57AH6s2e9ruu1GYeZfZuY/xsx/rKPhjQ5OFqX4QUUFjhF829a+foHllWi3O3pvCPkX3CZD528g+8bmpObv5jvH+x3vc6OuNy0k/xZq483ftV3HEYYmQmJto7Y++tSIw+sKL/qhtqO8f03V3LSl/k2Lba8szTnfaf/PUT7rzOJXAfw7AP6avv7Pzfa/RER/BwJsXtwJr2D9r2X7KYCZLi8BoNoZdgEcY6VXE8F8UNPTak/o33ki99ZmXfMMhkETzurTHvMMzABO1nWNDSA/fwE6HCQXx+wL5zVoswGfbapSVkzID07gplnQdj1+7EXEZcGQ63xJwQ4XjKRPqTDN4LABQMDHz6T9Qy/WiOenoMtr4Fyp7M9fgvoO8d0zeNPDsByCxh4RAAZWpuV+RnwoM4vOZPlVWNdAVr89A1jsCLviPVIFY1PnSl5E7h2wjbfcoEcU7racr0okQpigjPHJUGcUppS18vBjX3Qy5tOA7jqgmyNSXwV7XWSZATR55NOpCvY2hR0hrgl0IeLCm+9U4+jpQS90a8Uhdj9+VpSyUk8Ih6rVkTvCvCasXpqil5Pz3Z9jegDMl/oEV3Vvl1yxJMxblJlOEeYN8q+/gKTUF/cyoWQfl6uf2SBuAGCFfiOVjecO40MWu0I7p/NGJQwoKeppAPYdoX8JTJJBISnqVVjtteUuodO/DQEz3yGiDwH8Fcgg8XeJ6M8D+A6AP6O7/xokbPrbkNDpn7t7U5blmKK9AB6n6nBO+l4sBZs4tlGGX0FntQvawqy0OyzCklnrBLA4FoZBTYR1GRKjRBtiXIQECxDVUoZzRjB7wt2h6kbsR4SXS6UttzsIMLkfy6u1y+1H+OteLBcBGSx1oAot32RUS8Zpht/6so0daVJVujG17F9O1eqwkcfzY1eT0RhFrcm0Fazulo7clhaYa5cefqvnEPTmm7KaF1XhF6fWksUXVZcKN0WOevSXN8PmqXMCfPauAqoA+pcr2baVbf3lCn4U5ay0ciXHgrLqW+xdtS88eAF/54yT32esnxoYKQOU3yeQhjzCPpfpvsnxsZeBpd9m+JER1/rgUEr2cVk/HxB3hP4ylgS3k48TiB02H9drvNtqYpkWG4RSL8rfqxeMoCkBkmh241CvLHeJhvzZV3z0x2/ZlwH8xbsf/r7cl/vyw1J+aBicC4ey21zIjvELchXbaPdNLElCja4mgGK6s0j6uo0laolhtp9zAja64/pIwNF2RtSYALGv4q/k3cIcyD4Xn5LmtdQjpj901Fb2VE2Mmrahqb+tl5vkLnIOyFlNbCzAa09L35j/iGqUaWbmpt0uKiB8y/o/N6ZIi6WHKWR10q7cOYUVqGynWc6jmgyJERDFXMO0WPqCLI6t5kA5uMXva6ZCaM4ld2JglHvRyAQUCOwcck/V86TXjODgRKC3CVGyFx6HGQdRruK7xntgr2DoVJ/8gNTH6Wb/GWiam4zb1BHSquqN2n5+ar9Xt4tPChcRX8q4iUt9SvmhGSwAvDmg6YQjwOVGlovsc5WjQaakYQNyY97mlvZFlBZENDOfI/DT3KvIueVFccu+rTvaH2RpwdIK9BFa8sRtjm9fVFuYZLBYqGsDDfhYwVKm2wenL6S0wOlnBPaPbRXfFAx9aweLhQPZcWl1NVutzXa97h34eD2mlbEZ+Oj3ARRNysKU1DrL+3bf4OsTmUiejuaZasdQx7B2aGo1Ml0XFrqYtr1r2lP0Pu0VGhIOfuHwRVER/U6czYppzrY+kQuJKPgKcCoAqp0CAEWDEkDVwQyuALOA6HS6UdrbbgdUjyLcvKwWDmp63nHliyitzCzkie2oEMpF+zNmwFHRvbQ2uplKKjoAzBsHf1i2R/YnuEncxoZG+NYcyHrdlgeHNEjYNXVUFLeZqdgRmh1CWtUBeDoj9JfWV3XmNJ3q9x3BJGNbgNPyw/JImDfWpnCryFtcCVCbrkXfExDN0ekcmF42IO8Zob3obBaRBkJcq4uZhk5dqm24S3lrB4sbGhStQ1mjw2BKWHSkW8HM8pRvn0jeAzkKbdu4CVbnHBcKWFZnqUuPVfIk2notwtLMLMwxbKEI3ipZzXGhXmXbC5iq6lsUVb1c68kpwUWV1W+c18k5IObqeGbt0rJwXPeqldAobiMId8Uf0iJ/AkBZftj2sPfl/eInOuj5xpufLRzU9Lz92NeMTJ1ROOJFHomfcqGdtypV5kjfMhC7nRMa+vGxsytuYy0TtjiQ6TY3s6iCRQZ1rQyg1sNidyB/6NLDEforRrfTQS8Q2DPCLqO/tggHNxnG8nVbhnTXYlVgA4A/1OuiLX5k4YxMXH7f7prRXwq9u54sFn8nw8AngAMh7FEGLqeU+buWt3awuFEWyU188/3x4GLJZsd0bXttk3ugN9PxIHBrnTow2LqSNVHJtmsRO7+8jMakVKwG5DOtP+VqQVC+n2s05ziqo98tCVSZAWQgk0QSyn6WiNYMCsdJYkWrsqFt24BV6OcJLro6eMy5GUjqk52SKFzdoMy3/WHtsnqsP3Tp4bQtJVU/atsbDU8Xc4mGUDP19CNXOndTmKD2hXlho2jb0JxX9iJcI+db+8TBgTNKSJeNzJRFGs/k6yjLwOCmDD8ZKYuLmY9NHC0a4mcusntyvnlB+y/nNsuA6VLtBz8z/IHLsQGRzmv/rmsNhpvE6tBrZLu1K7hLuRe/uS/35b7cqby1M4tPxSy6AJqm5fsuLDCLhe2gFW6eekZznpTqu+plitpiFvZ+OtJdND8O288rvkEkJC8oTTnnxbSXVwPSqdoFHvpqHThOZbthFrzqgZ3iGlPFN8h7oXWvQp0BSEOETr5ufEMO6olChDxUrASQCAcBjXuYPGHjSfN9I3spZuEUp5nOO/Taty1m4YITzcxbZhbJ+kP7BhDCVTHutSjDoE5curyIG4/ADJ+5tK1iFnmBWRwe1ezLxbGV25BWHt2qspDiSUBaeQSVMoxrj7h2cFEjD0oCE5MfQhxceRLHtVC4+xfA4QkVq0PDLLqBsH8sx+12/pWYRe7FrtAwi81pDxxuPsOnUycu8aND2CY9X7FI9M3+0zkhdc0ypMUsNoAfCdN5xSx+JOwLb9XNNBLO3Gg06nua45FLeoM32NS7CZvZurC4jR0mIVDpNDU34r3tsZCyfDfUaX1R226K2021zqb4a1+OZxmiNM7w10vxXXeYhOhlhC9tb04JbpwXWZyImjk7KsnJ1sdT1Ol7KqK0hZSluhXuKAoStvEGKYs8wcVKyuodlX0sJ8LqpnG+VU+k9AdQjtldh9quWcKapKpRtjwJzILn5FzSw80N7ZiUxYHQX91CyjoIKcvPuQo127nOuaTnh91GlyayljcNTRH8JbiRSxsoSvjaxYzVM8ZwcZOUxe4WUtbhdlJW0BveX0+3krL6qzX8SOiuU/ldVi8ycnDFOlH65lWkLMY0EYYLLpaFlPHDa19orlis9O1FUYFbNwzI41i0KTIAnqPaVRyt6x0J2GY3+2pV/uYLoZEXtqFZIlobrE59b8fycS2sTdtvmkG7A3icJFTby5OLn75YKosDQBfgt0Id58MIKI2c9wd4HbSSsUZfXooSt6bEtwKxfHEJ186cVAmcxglu5yqYpraHlDKczXB2e+WfKGBsYFoXACJ0Hz4rs6Nia0AkAsnaRnfRF6EhtJGPGMG7fQWNm0LadmsDAHQmjmu/r/FiiCrAaQI7zNI2QMDYW+wtw/PVYjCwYpoeCB788rL+HNo/fCnZZX3fyUwrMcJpX0HcmKvMoZ531wVwJ0mMj795BXepqul2DnPE8LGaZc+phKZtJsc6IyW1PSjpA5+8vFUWctMHaQNzEU4++60dNr8/IFxUVmruw2KwKZwW73F4f4PhxYjcRMBaJfDXlbdqsOAGRXer1QIos5s6XV4ivP8l8EE6iNZr5Ost3MmmbGNF/Hk3gjZNqOzps1r/z/60vF7vhAz08BSIWawBAfjvBtDZidysKp9PJxtgnMDnp3WJ8uwl+GRdJfV1EIp/9Gfgt/NCkTqvOsznvSDoz/aSaQqhQu+/fAowY/ObUm/86mP4iz3yqoe73oM3cuH5pxdI7z0SWXgVQSkDybrH/Hhdjtd/vJUQ735CfCK5JUY3Rxfk3NbSBvq25Ptt/5WfK9Ncl0TCnr1oNFjkYTrz6K4TXORiKQiW6EL/7LAASEX8JmP60mnRo5jP+hImLRRuX5cK/lCfnvEkIGwjug+f4eqPfkX2GRrxm+YK3j9xWL1gFb+RbcTyvtsyUk84/fCR/hiM3VdWiGvC+bdl23TelbyTHJaS+hwI84lDrzOItJIDnH3rJb79p5/g9IMz3U8IUP0VY/+uRkN2msOSxeUckCxQJiDsIS7qmq/xzj89l4iWKoRb3+zfDZhPCGffjaXPfv+PP8b2xzNOPjgpy6+4Afor1KxTW4b0MovoL0NdhkRg/tbdYct7gPO+3Jf7cqfyVs0sFqXlVQBLZqT39W8jZRFVjgNxBRzt9aiOQqryXvUafAEJ5fjC4CPfsDJVNwM6BQUghsxdQ0QymvLgi9KRDcnc+UIs4s4jDbpO7TzSoGQbVynN3jmlRPumXUKR5t7VNtg59WHhBM6dfE+8NJoZhX5G+h3rB0BNfTUcyrP0Qw4kJCQlJMWVZHey55IYJcrVrtChZWPVzEy9E4UrKP2alNjUV+IXoOAlV3DV/DUQan/Na8kMdQlqjGxgKCHucXNm4eUpGodK4qIkpsFxVYHMtHIl61QwhnouOchx/WjZsVT6MZ5y0anInWRyugjNEpVfiD0ABuZTra/nwlZlB8RN7dsAAU/L0kUzZ+OGFn0WN0A6SyUJDQDmM+VskBzPZhZ5UBf5SKUNbv4RIWXdKLeGRbDkUbSlcCIqweeGyK++UoYAlTkDJnTT4gHtd4rEf8OzyHlRH4DioSniqTUmX2LouSHEqDNVG0UwYpKJvCzqZ1aA74g7kStvoWzPpNv5aF9CazFgfSM3YUNGYpZxuInvu4SyDHA2njOqT2fbXyTTbxGwbc6NUNLMARQavh2nbE/1XCvPorZhEQCbpe3MVH82traJmzq1v3tatllk+Q30O5ac0wEq1jZYf7oZzb5yo1KUf4C+z1BSFZr96vGMLepKe6TfZE+R9rfjUNMGmpz8Bnp4P5FkkupgUdLVHSkfBJVnkd6MZ/HDM1i05TZfkBvamcub4LjcIL7ojVHqMaDN3gMo2hkp18SxpOvrI1CvqDtz9T4hZrmYdT3Z3lhmNFw1PZr31j4029qBx1iQMVdDYGsDKTEsH+2rgHEla9UbZmFg7KhGCLipl63NdvOh6Ttrc0O/z82NmhnkqEY0tO2A3DQUa3vNR6MdXNvBqr3Ype2l80q7bD9KWMjyC4OxaWMU71S58akOsHpKfm5vVCp94WZqBgv1SdWbW85BnuCUAW/BGol3yyDQ7NuaGVPTtX5m5BmLPnMzQLPUUX6bWY/n5Hhl5kA62MxcB6ZYj3WX8lYPFkR0KxtwkTXqnNzM3jfIeLNMeUViV8lWLFmYBIYvSLEnknyMmMrAwN7JdH2RMaq6Bt4f1d/YFjaZrRZCkwzIZnsnAq6WA2L5HOxI0H8TebG8lEb9mbIr52Qq2aUOy061vmkyPym7JuvUptHNVJ1ykdVLfQU4cyDkgYCpyrbJ0kGTr46T0pzWu8gwVVDT+DTNZzIwNTkjqopmYGbqSMbyrMK3ltfSkywDPKqsng4Ultth/e/ISdbmUJdAHOwYKmDTSM7lQEgdFeamtYU9Ia24ZHdy0Dp1OQIAOdbBomSBrnSmxfK7Z1sudLIczbccO9vxLYN1API6C+Br4/AgyyubWZiKeGrqt23iV4M7l7d6sPjUcjyItLONVy1Zbvm+PD3r5gWh6JgSfhv341MKMTTe2h4XOgPlxX42TW3pyHJOHjeWQplxa7bRD7iQPuUY2t6mGWbcVpJD2ydiWWrp3zkv3LhoWdVnaBcv3/Px5/USaNtX+vn478/TmKYufbvsk6P9jt/fWAZwM2Nql223FGr6vL6KNYLNXn+Q5T4acl/uy325U3l7ZxbH+gU2zY9KyR7rtBzkgKGvCtsAaOiBcSyvABZkIXP6plkySeNZDzflEk0IRSDG12hD8CD0SGcr5F72668PiOcr9NfK+9CoyPioAxNJRETPJZ4EHJ5YclGH8aFSsKeM/WOJApw2+/qtV1XsWBSxPYC06TCfBfQGqWjUJZ722L9bGZX+IO0M3mF83NfzBZB7idZEpZkPnbzu3nEYVE/SzZo23pFSjeVRdXjsVOBF0qSlc4BuIIRdV2Tfyk/IrihdA6LCzWQp3HJc04qcNw7dztVjPfKSLfl8hf0TiwJQAftMTAYAdl8VVe7jaEgOQP+SkNbA+pkB2MD+HYf5FDj5vrRt+57XuoXeHXb10Zw7YHpISPq7G217870V8FNb7EYzQGLkXmTy9l/TLN1Lj9zJDCifK7FtlUCOMV308Nce6bGAFuOHHXIns13DRdgB268S5nOG3/vSZ9sfT/jnvv59fHv+cmknPZowPx3qMmSjnJlNxDh7TE87xHfMCZ6QV3effry9g8WNZUbzd2NWLO81B6PJKuVZdTrnqtfZ1uF3S/qz385qRqPhvpwFr4hNOnxMwDTDbye4yawAZoTrSWwOUQek/iIiXE9SXyNEPARZT/pdRK/4gj9ErC6STCV1ORV2YtjjDxE0NantKcPvZhCzHBd1ACAGVn2dLIZrMc1xuwm9yt37rVKuJ9HDKFNVJcStXmR0W4uMCBgbgoRK/WTzYqC/kvRwlyobMOyFml0ySWMupKz+qtK1bT3uJ1c0Mw038AePsE81e5SB/moGHSasXsjx4x6afVnX5IDgBcNzXq7FGYCSsuKe4PfatswYXni4iQqte/2cEHdUSFnh0AwWQST9jVodd1T6OH/wACef6H4dIfeE7pLBLuhvaRgRMF+pncEgum/rLcGPwDTJiQyXkgbProKm7IDNR4R5S1g/T6XP1r+/xu8MX8L6I19+x3m7Qn/RWAEMlnMT0M2E4SUw7jUnaQZoujto8fYOFp+mjHRDJcpAyruvqrgBHQsg5ysoSc6BuyB5JyGUfe/atUy6P2NhQweSH599ldTPCkxSRvEtKQAnicxdqaMLCym5H3hplJRELUpeQfUmZ1cBOEuQIiZwEMYm69PXWR+z1tN8/7NI1ttsgZ3UCTCyb/ACZ31b22pRJvvMOBVmEZjDUpbusxT2TYo5aZ+0NA09NjWARv3ta/TC/qbUWBfi1cle7ACELGCuja2EojjGqPX+IACHt3ewOCZlHZdiVehqmNO/AepXOlFIT3DiaV10CrxEHWhu0P3wJvVTiVjYhWQ3HwgyMDWRALk4uByDHQn13JEqX+u+XVjqhP6ACxPqhc9qMqTJUUz1SWceoyW6kPSGcY16lYG5GoI1S0EOdbB+o7YtBgsAEFWrEiXXvpUBANouAqnBEDeS+1DiU+6wuDE/S2EbHKxt1l/O+ksfEnYjQwYYGRRY+1a2Z09wXqMmNlF+xWDGDnAh3xisJNKkIPTR4PR5yj3AeV/uy325U3l7Zxa3Ea8Wn9vck5dsTdv22vrRfF/XsYylctQxUetNQqdtmxqilU2JkZtQYja2Zz0GqTIUO8axupU9qb+IchyOK8diXoYdjaG6IGUBraIVaeYvJWGyVvaknN+bnkMbei3Hyze3U2Y4UzJrQqgtEc76+03Vom5tV/v9NhzL9Xe/GUZdfmY9UZi7iaqc3ysm2BIilunKcRvqvzpL/Lzl7R0sGp3NG4W56jyqaIs4jZsmRIbrOiVB0u1hdEPLYwJnBeI4l4uJpxl0GOVzy3ANvsjwl1wNr++PlgYcXLlwKavWQe/KlJJS1cp0k4CbTCgmOBTP4LYj8oO1AJHGvNwdQPMJ4rqHPxLbzZ0rUQUAIuDbOVBwSLo0KF6dnfA3bMngjOjTAQv7yzLFJ8nRgAx2fhZ03zUXslzoQLgaF+2SAXgFmlvgVAVom3wRQIRqKFcx3LQipINoXZRliOZZHN/oOcjvShmgRlou9TWyYRm1xAymTkBaFQ1OD73mhggpq+UpWEQoqUFPmxvCfZXNs2xSDpr/AYBHXRYxkFb22zCy5xJxqrqYgJ9Ul1P71k+M7fsB80aiRqnYETBcVzjhcvyBkRu7gTxw2c6B4SaHeGIA9NK97HXl7R0sjjGLhVZFqozEckFWLQoCJN2dubwe10FjKt+nDBGbzbmAcgu6t2EhRMBhBO2nSpMeJ7jdVPUd2C7KCDdJZMCsCGjK6K6TOG/NuYrL5oywz/IkMBXvJN9zFunQGw3Bg7KIsDi13bMUdQ+gbxLJ3G4CBQfaTwhbDZ3uNYISJYJU9tY6hssMv7cUdbmpXSLNo5Bz668z3GQzHx38VBvBzamyQjUsDSefldyOWR57dFHFZFhFYdy0TFG3vqRxLqIuLqLQvXNH5andvxThF3YoTFZiSRHv9rnONgAgQ0R2ycHpQNxfJPjx1Snqfq4p6pZQ5nYT+qdnGF7agC03dH9Rw7pBk9soi1KV7KcRoVFS1O1u95NEmdhVujl7wvpZRjgQ+otU+mz1fMD16Qr9JUof0OyWKeq7ejw3A/0lF4vHBc38DuXtGSwawRMAMt32Hll1IhZ06pZObPJ3XVfFZJhBw6dnnRb6tJkGBQeONYTnUhOebZcfd8067R3ceEz3puLXmYMrT1P2Tii7JvSi35GnHylj0x4dCoh9kVmnlkynFy17uQGKGf1A8DOBIpUbgjIkW/X4d9RzyYHgjVKuUaE0vGHWqR4rDqT5IUb31natgbinAjICdXbgEmE6I2yawS0HQupRgNfPnHV6kkvmpwwWkjBWs05R6N62zZ74QqVX+jdkhuE0SuOa796adboG8llEXPdlsIinsgS7oWcxWA7LD3vWqaWXc51JUN+Dpwn+3ScAgPRJFa5BSlWhibkI1NATETGhaUZ+eSHKTNfbotDUkrL81b7URQDchRjm0qww+sNz5LMN3NUOdCq/MPcd8OwFMM9FGo63O7iUwFv5vh2r/2grIjC5RjjoEFX2Tp66reT++qODGBU/tBxmRjxfwcWMvBlEIg8An65BKaP/7nNAB1JTVvJdh/XFqvbh1VaiOvOMXpc3ZvLsnAPnDN/J+WYV+Dn9zq7iEImrY1io+SWD+lS4MaG71sGmURBPJ51+LlEcd4joLucyAHRX8ptvvrMryy6L8AwqymPLrm7Vgw4T+OVlEa7JnSsDaQ51vb5+5uD3Gbld7mUuS4+Nq7kdnAmrFwlhdPA6yzz71rUMwGrrUGQLIQM9D12ZzRVlq4+e451fP8f6E93uCGnt0F1GnHxspDsBJcxDFdA0/1kC1O74AAAgAElEQVQG47DP2CtZr9vlsvywdufe4ck/2SIPHt3T2mdPHn0Jq2cdVi+arGcihH2SwSbywimtv4wI+4ioOq2UGb93fXcs4z4acl/uy325U3k7Zha3lFeCm/aZzRKceHZSG7X4NH5GrUReMwNIBaAsknBZhG4XS4O71KuFLBKSM2C6Bl7YOZw1DdvSpWO+IVRLqbJJZYaiFc8RFL+4n62NCFHO4AiZCSUUZJ3JlZnEwu08ij4GKWBIcwIRST8mVz1TgjGU3rBYJEPT/wkMR65GGrK2Y86w56BpikBT5E1bxM0yAxHs5fOFQ1o8B2TRn2XkReUrSkTIFR9Viyrp16PpaLgiq/epxzX8xi5nr8Bz5EUU5k2TIG8rb+1gsfAoBRbWANT3IngLAH0nDmN9v1gr03olF5S+li9ryeeytKDtQdbUDzZA4qL05OcoeEbwReUb3oM2a/D5aWFaEjP48YNyEZBGaab3TkRzMuYyf8tDwPRAczFejIgbma53lyMO761BzNj8rixj4lmP7nJC2gT466mItIbDiHTSI236Gxqc+YYGp7A9aT9hNg3OZ4ZZyHQ/mwanitZef21T6M8lJV2jLGbdN5179FdJ1+CVgBX2GWEfCzBnbXbMGJ+s0F1LO+ezABAwPejRv5Rl02s1OGPC7iuybxoEcHWJVSlLmrB/x2F44Sv5DRpepA7dThS2Vy/q1H77fifRn738DuOj4Q4anNoG0+CcE178PGE+URp3gNC9rzwORYMThWk6NxqcIPks7D327xn4G+AnBWl1icgO2H6lUw3OUPrsxc8EbH8s4+SDaoEQT3SZp6WmpgN+9Dc0OOOv3z18/ZYMFoxXppXv9YZYgJONg7j36k4elq5dr5PVM3CwC4BzyL1EGcxzNHySxU90cpVV2QUBMu8AcKbegQYvT9GiP+CRBzFSTqtQLjg3d4gbATiLU3jnkAZf9CEKxbvvkAdp6xcBcIq8n+IxCnAKEEggDQXOGwLIw0+M6dRmZAx2Dn6UNTsAsfpzQHYd8kBImkcS1xIupIQ3AjhNuk5AWICyaEfYU3k+BdxECwanyN0zQOJqHiyKMTFSB8znVESHc6DPBHBODzPm51pHJ+FRyoTpzEBLKtGQeMp6XgxkKg7s8YRLvezk+MYAzd3tAOd8CuDJiPFqVQbMuAbA9XgFOO2BvP9RADhvKZzU49PyMpolAG/3gHIXaGeg4g5kI3GM4P3hUwHO8EyH3zkC3iHoPt6MhOYId3UQ1W71/nAA+PoaFGNt1/V12Q5UgHP1e9cyIzEPVAAheHQX+rTdz+jsRp0iTtRaz0Kbwye7miA2J7itTlt3B3SfOOGAmOy9zmb8dY/1ts4s6HIry6txQqehXbpWIFel/f21PhEV4Dz73ea4SQcvNVI2ivamdzJdnhJWqwqWCWg71wFoktkZzQmbKZV6u8sAJoLfTTKzA0p4uu9C8XkFgLAaQIcRfHlVVLhz76o5UajLkJPve4RdEpGYIgwkWb0uZWRfwUxKGWHfIW481t/fl/ZyHyrA2UrqB4c8hJKIZ+fonl7g3W88wOZjvca8RHm661SyWd1sAGc1PJKIjvJSxoSDZuWe/t4El4Sebt6u3El/p8HJdaF99s4/6bH9eIX1s7oEz4HQ7ZOEXjMXcSL2AnyGbUI8sfA88OHu7suTe4DzvtyX+3Kn8nbMLFj/a1K5WTUo0qX4cFQfEckc4rI8IXkKUb/wBfHvPAEfDsVXBACcd8JTYK6Yw/4gAOTpRmYZxpN4/gJ0OAhGpOFG2qxBDx+AT9Y1dOYd0jvn8Po9p7oQ8WxAuGRgrqM+B4d4LovI/lA1KsJuVBtAD/9bT6We/sviSXJ+Crq8Fq8SAPz8JajvML//QMKwqKBs60sCAP2zDrkP8LsJ8aGsc7unvcwQgoQGzUrQzHz2jwZ0V1ZvJQUZlgCofeGLCWmoituAuji+3MG9uL7xE+cHawQLO+p57378DP2ltCsHYW3mwalOpKaCrz3CboO+7zCdy/cMV6DINfEPokexfn5zDZ4eevQXCWnlcPat2rbx0SChV51BbH/yDFHrjitCtzesS5YhaSAMF2Z1KO097T2uv0ogpWBmL+zP1BN27+mMcstF5q+1L8wB6C+EqBVP9Pr5LsMd0uIpTinhxc9tENeEkwcBYSfXwvX7HtuvmY4o6W9D6C9rHxijNw2CL62eBUxnWm8G0v/1Q4dZ3FKOtTOdE3SeeYlDLLCJ5jshFCyj4BvkAKSFj6nxNcoa3ijUbRZrcyxWWX4Tv3HeV7q3uVEBhTTV/hQtpiA04YojFKzB188NHzEiWPm8CzetBoiQe7UaMP5WH6QdsdYfLO29cyD9jlRbiUnm/t16nRqWAKhcvdaXGq9TYhTzouPSksgKqWhF8KOt9RXLGQjecWFgxrVEXsRGoX5PVLGrLiegVgC7mxe/HEcIV+X3RSVh2ZIirhzmDcHPFZMAUDU8BxT247wWXCANR1YAAYX7YWAmmMpg0QKcHEQgmD2V7UnxqBvnsBGv0riqmFI8AeJ5rkZPUNwm1rbHlZ0rEE8y/OgwnxsY/yOCWdwGeHIb7jx+n49A0jZ0aZ3fdkyRwOf69w2Jfz7aR8JcnDMo1f1aJe+qVs1YSO3rMaqa9lKev2zn+vnCZqCV7FdZfGpCiUxYyPXL9gxEunksIiBZSLYhtzEv1b0bmf6FFUCss47l8W45Z/ussS5YSNmXY8g/Dho+LHkkKgKTqjR/kc9XFW4rbj6W78eiDhexaNvxNhcZfq71FyVuwwN8FaTxqkHhUoYbKzXbMbQfK5Xazaz6G3UbZSAnuqG4LeHoW85hNgZmjVK5GXAHWlC2/bikcLtG3Tt3YgdglHNKqCH5O5S3d7A4nll4X2cWxzL9xSOz+Y5zQN/Jv3YWMUFmARaWLfU4+aXb7a0FgB6L10OJMgDC6kybAO+9iN2Y0lagWmfTphLVcK5OodvtraGReZLaq33uhCpuzugUVMhl8JJEZDOLdUBceQRH5anMnbSTvYMj+Q4A8GYFZAkZFtVx41V4Kv8AFKdw+8yKqHU3fduU0h/2HjJVt3blXlXEOwJ1DBeNPi1P6XDaN8roBKhYRjuzEAXxmzMLe9rnpg1WT7strmo0ZHxQw68uElInA5kBhmJYJEsySdI6PhaXiIyoctv7+spBGJaUGsXt4MDh5h2cVjKziauqF5I7IK/qcQAUZfHaJ3X7/EgYt3Ft/A+8EWr59g4WxzOLlhDV5m3Y+2Mz5ZwlShCPHM45Awl1qmwu6nMSwpPt1hK/2mNNszyZjUQzR7i9oPdkxwRAUy51WqGpQePnVMhLmGPZbsekOUldc6yv9vkc4fcJbjRHb5HsBwO+kdVzY0LIIttX5P3nJPsrZuF0GWAUa3/IVUOzmAoxPKFsDwdf3re6MW7U8z1yjl/0h76XenLhMlAi9fekxSwm9w5hJ9T4ynuomEUr1x92vJDCK8dm6HeXFO6yTTELwyhs1lAS1xLD6UAUrA3kkCeRPwzXQRIBYZgFo9szuq3xLOpgYiO5DSphC9Eb1QeSH5vroilhK9hEt2dNxAPCFgiXbqkVGpbaoTYDdhHInUfYoib/aX7NXct9NOS+3Jf7cqfy9s4sbimfRgG/UQyraDELMkzhDYbTo0JJMITSktZi0L1hGz9vObbiYy6eEdJWBnnpgwKaZcjSKMv7QimPaUlq+wMopPRsaaudCql7mE2VhYtgVPEvtLBOzVmdyYoQUiV+LQSAmnZ+0WUh7HMLpnGX4hobxc9SfqgGi+JQ1mITr3IeM21OewXk1e6klgEKVIeudl59XCc5TdmmZYp7cDW3pMU3fEWuASwcw1o3LvjGSczVz839DPZqn3u3xAAcitiwpX9bHYUBuhAN1vZzi5XUeoseBRv+4opTGKDswtZdzLo8suJBt4TjGge1Yv7ckKfMpcyyJB0qZuFmae/SDUxSuBfOXR1wm7itOYm1WIucl24rmbX1+KkDXMlcraHOmsVZ+zd3aMhPGmbtqLiPuanFabDYL/dYOJVlT0WIqC25s/OjMrDmHsg9L34D2a8JnfZ1exrsO7JN7Bxv9teryts7WBzfqAZuAiBf2YT2fuF2DsjF31gDSEmFZwFjGRqVe+jkxrftViewPBagClQacoSuAU2zIlV+gJu6Co4CyEMo7Ll+6BDXWkdft5fBa+jEqrAPIH2VNvgSgnXKe3CFx1Gp1tB2lZwL084IzStzFf+NCcgZ84kDKS3bqUx87p3kgOipTKeuhDxLbggAEISVOt+8rEp/6HtA6dP7CnBKO1XHQ5/gcXBwo0RD5pMatpRoRWUoAuLrYXTs5bFFuGZeS5q5lflEthlQnAa1HvQCSC4tBMUjxU9U6jQx4vFJRn9h/argpQOmh/V3MSWs+cy2KTDpHPyBMCsNvFwHR2U+EZr28KLiJtNDIL83YXxRZQmmRxnc3AdJwcy0Ej+T+dRjfmCJftRgKa8vb9dg0eTkHwOczCy8gGleqF8tFbGaxJ9Z9qN5brbV7xmt2hSu3G7SjM5cjscm3dcci8ZZFKgMKJujUICjqneptF9RsmoAzlbJyu2mInFH+wn9ZSz1lfaMk7TTXvVz2k/ormb4XaN6paVvbAL8boabM2g/o7tSiu+YBKnKAnY6b8edwczoL9JNUtaBioIVIE/UTr0rin8KIAlg+wk03pRfapW97LxXL105FneqfTGJb4aFTimbUta0UKm6jZSVel98PdqS9lRVsHbViKq/WMGPrlC4h4sBfpK6U1dvSuNZ+IkwXKp2yCwyf2E7Y/39FdbPWoAT6LdcBuaWlNWZcpXOaoSUxQi6vb+M5SHQltWzHmEPrF4mdNfy+erjgNQPWD+t6wrxYql/V1KWzHSGF4D7jEpZ9wDnfbkv9+VO5e2aWbTlaBlCzXT+LgxOMqd1y0oFaij0czA4oQxOWxbAO3kf/OI7XzSDMw0ebrJM1ySqUX1lOQJA7qWtLubKp+i8ALH6agxO47H8gTI41w7+oPX0ssxJK3m1GUNcO1B06LrwxTM417Is8bPwKMr1pHRvW84AknnL2n9/MAxOWYoYHR14cwZnWjH8TCXzlRJ+RAR7byu3kH0+dV/vFwAneS+Zp29Sz1FhGxQaMlcOTvJOjED1B1EarNZASzGraUlSAkxStwQ4OQhQK65r2hfBA/kPdqIprm3Wj4INMS0BOnEyc4ub/Attj0MxH8q6YqGs7aR6c9k+rSTAF9o2V4+f+s/2O4mHaqPo/YYBprdqsKBBknR4jot0cgALTU5u0s5LCvr1dvkd0+lUjU4AoCePJESYM/jpCzmWJqS5JJYApq2ZtE4Ai2O5kw3oai+Dhh7HX42S+k0EfngOAEUjkxt6cauRSVdb9JqUxLs91tpG1lRx99Fz0fWcZ2mjYi+834OevkCvClQAYDqfrcYnoJjEHEBTRP+JrrVfXguoSQRKGe5aNTgfnoKmiLNvvSw4TmGjele0MQGg/2QA7STRb+iaS2iOwFXz2zSlB4pmqJ232583quWuaFrAVXC6fyEzHHZO2gYUncySQq9l871V8X9ti/m9cufhPnpetp/NSbY9vQAgSWFp8HApYzrvigiQqZiLnqd6s+q+HAhf/ocRw3PVQ3UyaPsx4fy76ik6phI9KzNLvWnDPoHmOvMbPnhZxZaa8nD1rrSB62D6pW8ccPidDuun+7JfXAeEff1+bqJWV18LOPkoFnFhMON7uxuHemV5qwYLyzQFAH9+LpoWCjKyOqSnjz6G//mvw70UPQp+dA569hJ4eA7/XH505AQ+3QAvLsBnJ8BeTjN/76NS/+EX/zAA0Y2Ac9h9dQ03cenIB9/okN59IKbEFzJo5Ien4Jgxvn9asi0337nE/sfPsDFw9vvikPvRv/GzWD/PxeQWAOZTh+378r2zDxIOj+X9yfcTnv9sAGXga39f2vryDz3C5nsjxscdVp+MGB/LDXby/73A9c88wuGhx+YT1bEYFR1/EHD9lfqke/A7M9LKob+IuPqaXLhnH5ralIMfM6YHcrzzf/wBAODbf+4nMbzQ36AoNgkS7/WaPLzHWH0iIbxJxkYQA901cP6dyrQ0Y2XKwMuv91g9l+37dwTMnB4AJ79vTE2pZzoj9FcMp/f84Qlh9Yzx+JtX+PafFvHmeMqaU0Ei7mKz9p/aIn/wQOz8bAWZAe4Z/dMzxJOMd35dGkwJePHzhOlhxrvfeAAAuP6qTNHdSMgDI1zX2yN3wPgkY/39VWkDAHz5H0b8wn/+/+Dv/YZcT25IGNYz9p9s8BM//TEA4MMX5+j7iJwJP/ZIBrx3Vlt0LuFbL9/F86sT/NQ7su93/tefRLeFuqjrsT1w+XMR/eMDwq+flj7b/YWX+E9+9tfwX/zWnyjU/J958gm++fH7cMTITHhyIqPB+yeXOJkH/L8fvYuvf0mu0etpgP+Nm4Prq8pbNVi0hWNcJP1wQxii3aEMHrQ7gMdRXmOlRNN2jzzNcPp6XEf/XGcUVyKrNwyytu9sujtOIn4zxyLhR9sAignd81DW7LTdY3g+gLZyJ9mxTr8f0V2IorUtDcI+gJSsv346wZtz9rMRZx86Id2ocvPq6SyyecwIF4fFua+eTvBjh/6ltkup127qoc9wqff5iNx5+OsJJ7rc6PS8w+BBY9Lv1IH69APGcKU3+8xFtSmuSWjJAMJe3MQpM+aLuq7v9hnDs6lkwxYH+cQ4+cijv9BIT5Tzni8J66eaXt9ZNMCh2+VKaT54DBcJ7nKP0w8ktzquLTGMkXoULGU3nuLkkzplt5IDMLyUB4GpcFNizCc95ue+CNdQFjUuibKgULgB4U30F65EPQyjGJ6P+Hu/8Ydx8ttVVi8NK5xeED7Yvy99fuUwBRnUvnUm5/DPhgwQw18GhD3wW49E5vHdD1miMKrlCdhSLGA6P8XZB7n02YfffIL/dP7XcfhnD8rp/uMHD9A/98UK4IO1DI7fWb8Hmgn9C4/f/EgEkigSDrt6vbyu3EdD7st9uS93Km/tzOJTgcIWYDTPEdcwIrmyG18FZhYykmWXegJnWsTtoetPi8SwHbdxQDdg8bi9xnLkxuuUvZJzCEXbErD3gPotyrbQHOuW45lTNwBQwwptiUQt27ToFvh6TGoySWu7GzKSZoBLu6mkO+dAyF55L3YFsXAMjEkKoFDPCUp0KuxU2Z6bduWGnSnRBC5/i0v5ceYmARCeRaHc9eqT0QCR4Ib92GHRj9kIVNYG5Ug4jX7kpm/YK+Gqyby1fnRDWtgXlmP1tsTiYrnIg85W+gxyQpTKicB9jTyxanY62G9ldfKyz3rGyTBh11d1b/SiHWszC2sDeiFr5Y7rNoc6LbtDeXsHCycMwyr5T8vPLMSo/qMS9WiQadKbnJqbfVGHvg9ebwYhGBekOQRhT+p7ABIWTLmAWHacdrCwY1n6M7Er+5YUapLjlAtsELctyigMwxwIeRXk4ul8iVpw34mTV9OG9jU3XWD7vGrf5XnUtOdUSI4mHiuYguXk5r6GL00kxsyIc3BVid00GhSUM5wn9Rr1CFgMIPJKgjk0tHfWB4E5kuUeZRBLQ73ecy8+n9ljiVlQZWcaw5WS7JtWKO0qA6W6leXQZnMu6eTtQD+sZ6RhVftvzcg7KgNDHtU7NQPQQSGsIogY89ohZQ9ayXWeVgGUZX/T08hKDeew7LO8yni83uGjTS64jV9HCWcr8c7a4FcJifR+0TYw0Q82RZ2I/iaAPwngY2b+Bd32nwH49wB8orv9x8z8a/rZfwTgz0Oytf59Zv77d29OU1LCUjimGQEtbRsAGaOz2YaUgE4iKhSbyEpTh6V3W8q5P0RhDVpiUIzqaZrAxgKdZiBJangZkFOS9HI9hh0r7LIi3Wkx0HUrY/XF8lT3u4j+ugOYiwhv2Ce43QTvxNHLGd17nBB2Bmxayrf+HRy6XcOoHMX3xI2x+pdaWjvL97xFIFQAub9m9NsGsyBSzQUgjPa0dxgusyaCNee2Z/h9rH4XJnaTGN22R6cenSX/I7nSrmKZqH1nZsXdQLLPHNFfacp4BCha2nX5GuLaobvkMnOTH0Rusv5CQNPusp5/d+Ul7VsZkTZgi7o3V1k9aH6JE2YmgJJQ5seE/ScbnF7YAwHIO0J/CUS1XeiudVbEwJyUWt7LDd1dOYQdYWTBDvpLSbNvAU52Yr8AJvTb6kXbP+/x2x+9g/6pL4PFPK3Qv2zo3kqnTzsPPwPdBYGdXkuRRBzpjuUuM4u/BeCvA/iVo+3/DTP/l+0GIvrnAfxbAP4QgK8A+N+I6GeYOeFNiwm+3DKz4KEDDlV8BiGIyM2+WYasBtDhUF+BCoBCfDkAoDtEwAHzeQ835fKU6b2Xur0DaYdzF8DeI54NJdTlLgf57qVEK0hDieMjzfsYq8zdfOZxeCzajWHf4fDIcjAC9o8JxFRCsvNpQLjuMJ91cGNEPJF6QxcQTzuMD0P18dQ8jfm8KzZ4ANBd96I07QjjY7mr/EHamQcPN3rMqmvZqTL6/l1X8i282u6lnjCfVJ2E/Xuy9KMs0QtAbr50zQjbJuTYKI0dHtYLenwg0+TpARXA1xKeplNCf02FGLZ/TGDXYfh4wF59OOJGB4tZZxla7/5rUW4EhyKjDybkXkyK4wbFUpAy4/CuyPWbCvfuPYf5ROvtUPQorH3Tw0rhNhLV+Xd7/MRPf1zATO4ZPGTEZwHupySKtn85AJ0AnCePBAjfDBM6n/DR83PsrzucvCNRi8O3HxRz53aw2H2FER9G9Fdd6bP4Ewf8a1//Tfzq9C+UPnjy5BpPPz4va8D+RB4+55sD5uRx9dEpzr4kOqTTFOCGu9+ar52EMPM/APD8dftp+VMA/g4zj8z8bQC/DeBfunNr7st9uS9vbfk8mMVfIqJ/G8A3APwHzPwCwFcB/KNmnw912w+0UMoF1KKk2ajHuo9RTYnt9ajYNJdyBrJO2edcQ245y2dpuRSiOVahXED+HlMh0nC2kN8yIQoA3OjgD/X4Znjj54xgvBqzt5vlnPwk5CNviVVJ6gz7qmhl7fEHj9BMnd2YAJbPLQzYtt1NqdCtLazcqk35ufIkmOoyJOxItB4TlzU8sSRE+alqZ1CSsDGljDBWXU0/ajr6toYnbTnDjrTvpI5u5xH2orJVFaCoziwa/lK49Ag76MyiWYaMVPrXXNUoszqFUaM8JU9jNwtQ2ipOWZp52NYZi/Xxhy/O0V1Z9iwjj4TummRGAcBfeVmGZGALCVseVj2IGOmyh986bDvBPJ4cWPktVe+TdbkCCghbLn3GFz2++fLLwGVXZhbP/QncZSgA56S40cvJI88e4SLgqtNp0UzI6e6gxWcNnf4NAD8N4I8A+B6A/+pNKyCiXyKibxDRN2aMr//Cmx9g+XpUmMrvvQApF9tv+55TtN+Qf1dfWwDVaMMApJcdCkrPHiXSYhRtiW4s2yevNRLTvs+BahtUU9Pqtn9QVJ29K4Cr7Vu+Z+1UENHcs9i1IChK9EXAxuZcFv+WdPNlv6FEsdhp/zfamFZ39jVSlDW123Qyqxao9Gd7ruyVzuyhddR/ljLOGomyf7af/c3B/lHzvm7L/nib9HHfR3Bg+deAkegY6Fj3ZXDHcH2C6xN8SOj6CCiBzIUMF7L2Tb0O5Z9oZuSel30WMk7CVI8dGD4kcMfgLoP1+OgYvpPj5r62AX3+4qMhzFyokET03wH4X/TP3wPwY82uX9Ntt9XxywB+GQDO6fHNFt82W2hLbvQxj3Ur7mACW/rIVLlZ3i+2J1GqLpTtT2vPbcfI1r4mFKmvx+rcpmBUlKsYovSs/WBeqgvVqy+g0FEfiMGv0IyLKhRTUbAqClKMYkJctDYZIEj/LlSxPqvoVaNSVZSqWuUn28ZHA36zb1ETZ2uz4B+fp+RMN9rQmhKj+buIIGcdeFWxzLabhytnwNklnjWGfVyYENlVpXndhqxRubYNb6Jy84rymQYLIvoyM39P//w3AfxTff+rAP5HIvqvIQDn1wH8n5+pZUcAZwl/AgICumXoVLY1AGfwJUvUwqxt5qpx9L0XVDoNmvVopjn2XU24KscCwL0r3+80A7Rrs0KhmZmaQVmOuXLiRanHmTWM1w/iV0GNGE0aJEMyDR5BXwEAziENki1ZzqHUX/1A7RxT7+DnXL05e1c+86hZo3aO8wkVqrX3FuZVf1ND3E8U/GMUcxy7MNPgS75HGXQyY14TggLFxbN0Q6VdFhaNG4lIWMJv3BDiQfoi2uz5VJYFfq7AKADk84j5SiidvOh3NfLZoGSuEjPmE6FtF0vBDS0AzvbHS70I15geRZsl+mOPXhZmJg8Z6DPmFAqYucUark9gJjx8KKDn6TBhCBHfzY8whR6PdHvcrGD8liKmS8B8lpEfzIibofRZ93CPf/HRd/FbD98vUjDvPbrC92Kdom4U4Hy42WNKHp/MDu8+EoDzMAc89Xcfue8SOv3bAH4RwDtE9CGAvwLgF4noj0BO63cB/AUAYOZvEtHfBfCbEJ+vv/iZIiH35b7cl7euvHawYOY/e8vm//5T9v+rAP7q52kUAJlVvGra76qLuqSM307KWrwet9NINabvEAiZXZF3E2+OINL5reZF/HRSlhVx8lZdT/0oqxYk68yieEgMTkOAJCFg3TcPQdamna8koL5D7tyCwdkSm26Qsnx9XexreMRRhrWxD4E6nZf1MpBSJUWZk3ka7GAoDuY2W3FJeBqURUIuFek86yM0ZKzltht/U/XWyL09erFIJHOrJB4eBLCvSybuWPuTy1PZqVdHWrFoV6ASr0QZqxKwrH0cuDJNzefDEd5ZbSXXAwD6jLCKSL3HZpCn+mHVC5aQCae67eFqj95FnKw3SMmV7S9Wwn9gjwK8shd8wnV50WfDEPHV/gVW66nMLB6u9vikP4VzjJyptOF8OGA393BdxqarWcHuR4LBaU5ct1iEVWoAACAASURBVBXmI3cy3ddwjJQK689eX1Uo57qe42axmzPo2Ask5jI4FDBSAbuF6RFQoghgBqHWb99rcYeFd4OlJzNkoCqOZ7rvHOXm87UNC7bjgu6NKirrjwYWAySLnoQ17JVdVTEDYlCSZZP1l2AAgln4QsoSzOIYqyiMy4Y+3Q4aMui1A6ACuQWQtkoarAAAuaq63q7js687+bn9AoBcVbyzApE50WJgKG1tBhAOTaTCpXJS5BhELIQrb0tohvfykBmCpvm7iE2YxO0NdV8otlPwGEi/csfourTos+AyVqSJcdrU3kV4n6VeolLvys9wxAhdwmlfAwrO/SgMFi0hC1hK7KseZ9lOSg1vZhakmhjUaGO0dbgjIxc3SaajXQSCvstMoqhpOQeaZvh9LEa4mCPCvjET0mN1ezXBiTVd2s9cwnEu1vAgAPgDV6Up/Zw7XxSY7YLmTlLZ+60wRAFU85/OlRAeoFoJGfD7iH4r9XrVOqAsRkHBaOQ6IIYtECy8O3PRUGBfb7SwkxuMotjlSQWCI1ACktbZStb7sQ6QpvvYX6CwRdNUb8zumsuxcu/QbzPoEGt4maiwOKHWAQAwXfRYb03F22YWgJsd/IjFjJCShk4bUld/AbEAmGVm9/+39yW9kmTXed+5QwyZ+eZXVT2RYnNo0lwZkAEZECBI9sKAAPsnaOsfYXjlf6GNllp5a8AGBAmUFjIgwASaTZAie2DPVfXqjTlExp28OHfKfFXN14PUr8k8QHfmi4q8ceNGxI1zz/nO96lF7hLvJwSayIKQ2KjUisvM5XWkQWgYwq1vBB6fc8Wnu25gpQY88L4/AgBM+wmIAq6up3BzhU8a3lcbDmx6WV4iQQHNuYTxPSbVmJ1dTvCPN9/Hct7mIPrb4hSryw6xdAYmsqnNhxbDWsOc9fgVHnC/rMT6OeTKL7L7M1kQbXoSnqNcuTy8Ilkh6zIugKwrS4JMsBvxET6Uzy3LhLDGIYii3J09BmMg1oZxGlm1zIIsK3ql+geyjM+gqMKVcBZyZMyBGH1+ewtF+eESJmTcglw7yDVPAogl7nIdYdpa8Oda5T6I0UOuqQQSbcJQeEZdpnEyHoIIZH2emNK+JHh7njQ38CFlQgPxEAYByBT4HPg/4cLGkkWtA5P2pv7E8nwKfK65xH0IsZAMGxMmwHUU0pR95Zr3IecyRiWhG7MORjQ5l1nrs8ZZgLi/rqlxHQFqJXlSSOpqa/a0hGHPqe4beUAOZVu6pmQ8zm+meSLzjuC8hFoSVpFYSC542QgPjIrXYM5xmZibK5ARWN3wem6yDDy2orwgvCXIFcsWymocMdd45+YEYaEyTmWhO9BC5TWkjdvnnuBHCbUQGPu4DjRcPHlXux+TRaocrWKh1LUIo4F8wIQn/vIq/1vo2wKC6lvQcsVv/SMmMcFociYDdZaksgSfFusm/i0hjMiR8XB8AHM84ZqRJIy730Ncr+AbWXFasqJ5SJNZPNZ6jyn1xVgyImYmGR5NQDOXGGexTmQlYfbYpfZHMwDA6lSCfMfQaEEwe3w8ddljPFARNLQZcOBsS+U6txKuFRCjzKQ+iXPTZw7NmB2IMaDxoLj2wpRsiJ1QfljHfUSZQXC/03URwOqBzqAu8hyzkKPHcEQIxMccDrldryn3K8UxzIRTtZkwaAKogYvpxnh57SSKBBvAt/nwcMcG46gzjgOIKw3J31wXMhyePLB6GGCnAcNBzGBNUzYkxkfq7FkDmFlh4c5cmq3E66dPMh9FaDyoc1iHJkO4F7pjDEWgnPWYRbj3J80+VjctvvPaGQDgyYNXoVZxcl6XJaPZC7AHFnaq85ipkyX+6OQ9vHt8kh/6l46v8VE4zO/e6ZTfTgf9gOuhxY2ZYe+Y+zCOCuJzZEO+KChrZzvb2e+Z3Q/P4nlm7G0x5Gh0s8yVoDRfIqxH0M0C6Nq8b1gseQlzdZOXMnUb7ceca6ZhDQiB3nFwLrNdGwu5MhDzdV5iiMUaOL9CY2zh4Ly4RhsCcHENAPlYB2+vIAdbRIsBNBcK3TOG4urrEd15jCMsLQ5TYCtWkE4/4diIXDnIlYFaRg9gtOgfDxArC7HgV33qnz5v0Fz0+RzVs3nk5hwhF/wqTBSBQcnI+hUZnhb8Fjz5mSlixb4QvPpGZJfffipYQNmGLDJEjun95MqVZZfxCMTLrAOgVEvG9b0aHFRk+0Is0HKdghxsliuczBrI+Qjx9BKnP+N1ve2IAUshVrBGz2/9oUZ7HTaCgFw6D8jRw0tAL9PSLUAYBdsRZh9F7Zj3A+NEonB0FqsGt2enMuu7uIoz8zf/5zt48GEKkgq4TqG5DhjeZVfoJFaRkos4CnDWA55jFJNlwJMHXBVx8E6MnUkqYsuKsPchYCYSs4+GPGbLnxzgr9/9E0w+KXGbi26Kg3nIMQvf8P1wrRnO/mgeMM4O+To4gK630mGfYfd3stiy4LfiGfl7lQ2pzTkWJoqf222IBPbyAQGc+cjINyBmV7DZbsq4GJsRlcHHIKrfDKKKMZanhwBKdQTkENacZiXni1q29aWmIokgxQxI0lbNQkKeswtitIXYNamWC4IYSs0298sDxkKMmyJGFEIRRqrGVK59ocWLkwUkbaCC5ToGhG2AqB9K47m/KbPiA3vyofo38IMbCBCDy/0KMXshAdDaFLToICBGPo8UX1EQFYK0PChecz0OuULUg8C1FsIGCFGk/4QNmWM0xQbEwCX9TKvnN9TMk6RgEgDKGR5joRfIgkQsWcn1LUmFXY68HBN1VstSmcgGlNoVw331QEabirgdQWyMmV4E6GvieqCUObGAXiLXhrgUKNZMP5D6BOBzq6jf38niM9KdNaENKtnCzNAk7zBb1oQ4aX+B/IZDosmXAsGn9uVnZha3+x+EAHlfJAMTHiPWa+Q0a0XVn7U1BN2WGATHSMJnjc1XYakvAPeBsEHbHwSxpxF8SdW6km1I2RDpAYg4n6eaGsRajy8gmVCnfVMgKGl0pO0pHZxiIOQ4YFozk7EJJH7R5IV80TV5nTpPZEF1bRDXzPA7rejQRjyH5Lk17yuJEeC6pMFdU4rdto/L7F0oEieCEChm4Fx1Ul/BLXNPJovoHdRbTCTsXQ23d7c2p/rIyOJFRNLcYO8wXcZ9KFWlKslv9VgoQKs1pFYsxfccavvfZmQjTsMVbwEeIOU5tz86+PS2WlsIo/lNM2cXUzYKYrD8Vo+fAC+bxL+gVgX5UOj5A0Ces00CIhMDBUE50yNUSUUK63npld7Uo+WJ3fDSJFfHVuLNn8dyBa8QPJbp+UkBWVsqNfMb3Mc3qA38Lli43JbXGkGELMv4RU1YlHMGixSlbA3/e4jp7/ImFybkvgkXcjBTrXyWZczEQPb505hwyNW3OSvUBAbDxfqdEFO8X4WczS7AubOd7exOdk88i+fYFihrw2ppwag4RtU2CgG3nbbntBF/H5IqO1FeMnBxWmw7BTPvsryp26dUTp3ajNuI3ftccq5lcbGrFGxoJa/7JS9pAF5i1cuSr9oCVcAlH5dAorjS3Dew0pmvhImJ4D2v7VOxWgiS1+rx3FO/t0mC79y3mmwYfI1rct9ckq6QqfvIxZhBLG33lZpXLl/XKUj7xTyMXOqe2qxK5HO/iCJ5czkXCrHk3BY0rlcUuWApexS+oVt4FABFQS1yZZRtlJdqdR++rN2PySLE/1XBxZRV8NecZRCTCZeLR4rnsOQlBwmB4DyICO7x09ykfOURxHwB2ptBJIzGRPByxwf4SSQmuRhZ4/NkBlq7HDPwzy4gojKXj8pkYjZFOD2GPehz1kRrhfHRPvQncZ0e6emWJx2ay3XW9AAA12sMD3gxPfnYwxzw9/bxMov9NG/yOdDsVahPL+GO9iCuFnBHXNWIZxegSYvld/ahrzjSncBPbqIwnJQA5+RxA6cF1NJifcLn23/a8A2lJcg42Bn3oYvl+ItXNNqrWNuRg2MEMxE5k7A8lZicOXitYCblLtRLgr7w0JfXty7x+rRHE7VJfHw4b96YoD/nfrmGlyasS1oQnONMoLnpMWkUVg94jFjbgxGlrpI6XLxKmDy+PREtXlLon3nYnnDyZoFlLl7RWScEAC5+NIGdcHzAdYXohgmHuSK3exZxORN+KA+7B7j+kUWIKN8ECR/3JZav8O/1TaoDIpi9GAhVzDfRnEvIFcHs8b57H8YgZxWjkOuAp/9Ww8wC9t6boL3m6371BhC+N8fil7O873jk0FyUl5rruB3Xe4Teo3miMB6n5Q3B/sPvBNz7M94+SpUAZ/quFG4xgAMF8LVlvougLFVASkTlrShTm8DGsSBiYVcWFBb8ttrSObW9gFrJrbJ4LkVPx0vgGt2pvD15L76VCErCdwoifgKAkPzd9gJytVk45xoW9s3nqLhvIYoCAxUoq2E2c7+lm2mmBDlGuLaqJwtmKgcYvGQXsaR9Uo5HQXB/x9u3VRqP9B3gBy4JGXvNnovtIygsjhuLG3FGxsRyeH6gAW+KBwEAZj/ALG7fNwzsItgJZTBaOlc7KazjtucydmEia3jFQ+I1l8anrIWZ8uQWBKE5HjDuz+J5hEjOS7CHMWhBKha/Af6A419Ce2jtYHwPrwXsgY19lc91A8wswEQR5MSGZg49Xj+9xHufTso1OB5hKqSa72OMZmr5eIOAPuRJ21kByG/oZEFNVMfaxlgAIKUQrIXYmyGsVoV8N31frTZ/Yx3Xinifg6d0sM/BTGMYgwDGaQCAPms4rRiXAbnN9D0eC10DOV9nklwYC3UzgtYjLzFmfOH6TwdWFKt0K+WygXB9PN4yp+bUszlmSY08BnT12RI0X0IJkT/Tv6tnc3SdhJrHwKv1gEBOTSZTCxOp/Cy68zgJ3kQltuhZZD3TSQesR+y9b6FvIoYlBTQloe1kDgSqVYPmgr2utlJRl4ODejYHrW4zn/WfdjweQJWS7DJuIXkbbk4QY8jpTLkWzL4dAvbejxiHqCSeAoH5+CuJ/vz2UsK1hObKwXUC+qyIe+69z8rs7VPeNj1QGxIHid2bPBeVtReE7pLbtx1nUygA6qesFAYga480C4/mRsfrUPppo0frI63/5Io9BzvlfWcfDTk9W9veexPYiUR7GTKk/+AtiQ+uXsXhb8p+436P5rpMAC5KS7hWw+wF7J0TzBPG3GgH0HD39cm9mixq28BVAJtew2hycRjF7zSazd+EwBDmyrMIWjE2Qal8Q2dw13LgCSY+3D62CWDjWBAi4yeSUQBPQgLZo1HXQ2kzmff5oaflkAefVusMtEnHEssBwRjQap0/U7/Eas0FYanOw7NwMFkPPbclbJ3X8pSLzTgzEScK6zOrle/YQ2suR8hFrMepJgu51pwZiuebJh25rnAd69jf8bZ+Zh4PlJuumajSL5/Eh9nDSMdWCxc1PhSaS243NIKXDj5seaANmuvbmSunBUsvNCL3AQCay463RXCbWs5Anicir0VeCggbWAph8Fk2gKUTBbwmTD8OWVIwUQLIlcss3Grlc9o2kxDFatpmwXU7GcJ9uS6YmMra6x5qFXL8BQCmTxwoCEyelJeEXtAGliJ5Xq4BbpRAexEgxhobc+tQL7RdNmRnO9vZnexeeRa1irqYTjnQGd+0Prrn/vETqO9+B+ImBqoOZhAXV6D9PciUSXCOsxnzAdQ2eRniP/g4t+/+/Y8BsLsfiDC8MtvQDZmMBuFwD7AO8pqXLOFwD3Ae9rDPa99mMLAzDdHHdeITLgi6/E//Bu2lZYXz+PIzM4XlA9bM2PtogvUht9E/meHqew0QgIfzRwCAxRsn6B7vYTxs0TwbYI4YJty9pzC8foL1kUL3LK5/49vZ7DdYPCqXdP/9NVP+XQesXoq6JkkWsOUSdbPPS7/+/7Ev++Q/fB/tJS+lhIlVp5rX8mm9vnpA6M56kK8KyQIjCmcfTvNypfBYBFx9b4LugrcPx3ze632B6ZMo8BPfgGZGGyXqw5FAd+Gx94slPv6PxwA41iEivqBWJFt826H/uN/IRFBgWcPuvIXtgZMjHl9ywMUbCmYGnL7JYzB/ian7Eq3edon6eAh0UXckUfw9+qcBy/96iQ/figWPTYDvPJrzBvYPol7NVYOgmDdFH/Igtq2FEh5nlxNgrqFOeCm0/EmlG5JK1ImDmebQ4+Atmcfsoz93+NMf/xx/97MfIqWqpidLLJ5OMtxbTNlL6ScjrJE4e62HPuU+OCvh//dXSKv3dRlpxWXoaQmQ5AoB+FkHkZYLs56V0qc9RJxQgpAIXQssVP6s2wCA9RG7iGQ6gAjDsYIwIVdtThoNe9AxXX4+VgdYj/GogU3KYpcdhmMNdckPs4hB0eUjgSAV5LoQ3ox7AotXIqx5VBhO0oOmMX+NkYh+xjGN5amCMB2GIwXhAoaTmC151mN1qjEcExCimzukak6J5cvFLW/mGrYjBNlg+SBVuMZofiegBsniPwAmsa5m8VqAjUFLuebUW+KfVDF4OLzs4DoJsiy8A/BDydBjDbUu2ZTElLV8SWRXnEWKgPVhyEHTVO077gPNNUHGytXVQ5ZEnHzcYvHtyH2x50CjABmC730GYH33B5/infYREJmyASB4gtAe81kHv2fRPYvX3QKLb3ngZI3Fk66c+76HGAi+C1DXxfH2TYB/OMI1PE52n9sf3tH4bz/8X/jv5r8AAKbtiON+iV8/PsV//sHPAQBvXb6MqRphg8AfHr0PAMxwRSP+8eb7eOfmBH908h4A4K/f/RPoa2YXT0TCQXDW4/XTS3xw9Woesz/98c/xV9/+e/xFINjIr/LHR7/G35z+CEp4WC/w+vQZj03/FBd2ir998gb+7OE/AwDOzAz/s6tmxN9i93ayCDGVV/6uCsmWayDHGtYI1oGGdSG3CR60HBBGkz+322gvIm/EnAvJunMFsiGTysI6LtYaS7CV1ga0XKM5V9AxiyBulujPGoibGDiLx5p+6tFcu1xMBYBVtoIECOjPLYSNxUiXFtOPNUvnxfVqd+mgFhYtAXJh0CYE52jRXjnIUaA7jyxJMWAo1gqgEkPoz8a8Xp/G/jbxN7oRoNHzb4Ccqp69T9BRJpBh0pz7t5cllSqNRHPJ691Usk2ePYv2skJwRj4M8gGTxxLtVbqe0Su7Ql5vp7X1eEloFiV1KAeB7tJDXQ2YfsCvc9uLjF7MBMsA3jUvo3/MGh01rR4AlhPsG3QXMc7jAqYfSKxvOvTPkgdEsBNZPItlvfYXWF906M94m51Er/Bshf/xiz/H8EsuGls2AY8nHs2ZZKUwALjWCIo5Mn5xyMplXc/XYTlvERYK7x6zZzL5hGs9vESOJwQFLH45w3ufTnD4mzJmf/ezH+IvAuHvf/GDTH7z04NXsTqbIPFZ/HTCZPttbzCuFXDW4q9OoxdkBM5WP8Fd7d5OFgBwqzjshftxEVYOcN7ld8/xvihJAmz8HQp5zt09ttKPgsMpkNzA/yX3mULZlgvJEiVf3K9myr7zuHxB24BRp/+w+bndLwqb23lbHE+/2Q5VNRKfy8Lm93ysjWvGxyvAMmSXfGN862uQx/MLgsUClWu8cS2rfm/dmiHBinwM6vqqv55j8vl+edF9lzyKSooghC92DnexXYBzZzvb2Z3sfnsWFaCp1g3JgKu0D0WVrVSM5gPjJaQsn1UbQHFflWDYtWuYhTuzeyevYpvur9HwXdHx0I2G7RV0ZOVOxyo6Gb4AjDrKOhteUwZQNZIYSRiQ5RJdQ0h8DYEAl8BTnvkxzJSgVpEPI0bC7FRinNXAMAXXcml0AjQlXIRrJaRwsNNN3ZBxr7i/otYNmRISpMFOefnhZYDr4sECBw29JsiKezMQQ7MZtxDTeC0AAsZ9yuLDifk7MYklCr9xnyANwTcKNmKPzF6AHAlkAN+GvNSgoxFm0fGf1QvWtwFkBOws5GvhZYCdArZHjqWM+wQz4xJ812KTsFcD45HPgDUzK2P8xslT/N+DSOPVeMjewowdTk44MH4up1CKyVQfHt0AKOzeb4tTLHSHl44Z9XrRTUE2ekYRyBWIkZl0PGLc7/OYTU+W+OOjX+OnB69mj+L102d425/mfu9POY53MllgsBof4AjfengBAFgajXN1d4j7/Z0stti9a7LdmoMTzgHe8bYqZpHJcyqAV91GjtiPFkQEtXIQoy8uuItcktXvKX5PvAcAgNFArWypTE2EvUsmgpHG5xoQLZNmJefem4iCVINDc6N4JnQJ+OQhjGOSmdFBpf46Dzl46IXg46LELJQkNPMykaqVBVnmQEi595qPgUYPleotYnyouWLCXIBFfEJ8cMkXIl/XccaCXfw05oBeAHLwhTTGh0jEHdAsAlSEi+uENRCoOB+Q26ljFk4zB4MYLZqbeP09Izg5G1K4NsxZi+aKNieLwC+A5gYQjjLJMQKgb8AZikzKQxVh73bMghBIZMBTIey1eOvJS2jOIzJWS7hOorkUrGYOQFwrWB0AjywA9LSZQUqP1SVzZn4UmJDmYB4iH0UBpgVBaC4kjG/RXBdOisXTCf7m9Ecco4j2tj+FOesRiHlUzpb8ErvqOzgrgbMWH4BJg70RGO3vIPnNLXseHDxrhdxhdVXpihQ6/PySQtLWJEvFkxHEHAGfo49coMZ/bnyvCrPSd4rH5X6VdXeQlc6pIHwV3AQvtOpBy4VKlKDNZZ+EXtwoOktFS6lsveJPDtXvv+iyelMKAFmntN6eJoqsh1LFOQMVb6EWHf6y/CCiUkALhIpDongGgcKGZyuSZADPpsWJjv0MssQfXlgERiwHsK1XGmK7AaG+zb+0fXMni+fpfdaexW+zKtKU2YLqcfe+cFH4annzOfvIFbDx4UkBv5ghyIHA9D2gHCtUOIVI+Zf2/e0ltV/C6kBkDBYmfZA6QJu1WXNQuQTkUmFWGq+kn7qtG/J5bTvwmvuwFXgNQLmmgR+8FAx9Lt/Fl9SO9aF4N2nM+BhUtgXauG7eU6VHSsWJTufj6n694EkPgPX1Gy71gWtyqWr3q4iJfyMniw3hoFwKXscxBDNoCSqf220kvYxYku61YJc1rVOTZ+FFVWJeSqx9LmWX/D2XzJeYhNdi48HwmrKCl1cElxS2KmandCyvKbM7BSU2RIK47dKHTBnfiLz252PEQrKBcmoyeVFeCabyj7GQ9NbzbYkfsGZoVO5qSym4axmkBM/buWFOrXpFmRAH1STsmtKHBMByLW3AkVPbzgDpAXFtHAtZxs610SOQyFIEAOAnDq4V0eMoLoVvA9ySclupv67lqsy6P7aLJUUaG0JFrgFcH/L52q6M8cl0iQ96XnKEJiC0Hm4l0ESd0dEQq5mHoj06iezeZlSwnjILt296psITyMQ1QXA/fe/gWp3PQUwtXp8+y+lRgGMUZ0udQ23NxOTtaytxs1DYm/F6chzV5xIZ2mVDdraznd3J7q9nsUV+88JsiBAxKU3VwiyU7emzagNAflOn3zGJSnnT5fbqxR6xpxK0yFWSkPF78mzisVzkUPS+tOEV5WxL8g4A9m58zH5kLkfJ3lNIhDnJk6HCMZn6kCHcmjZVxTUXOgUt8vbkUSXymo3zReU18Eawvgdv8zEG4Vs+P/Kh7Bt4vySXGH+dr5nTxWtL3oBrK48i6aC2BDemX8W/m4AgZdFIbQN7cFRprQIQEwvXqs3YUwjwbYheXZEkTPqrvineFnsayO2Kqp4r6aImzyJlgbwWeGl6jd/0D3lD4yE7B7eU2J/wG/xylJCasyGHE4Za77cDOmkwH1rMPeGg532vk9ZsdesFwXwUYmrhWp3HoZ+M+G7/FG1fqsFOJgtc9V32LLazIYtph+PYh6XWHPO4o92vyaJm1o4IzVQvIg4PmOQmBM58xOwDGebjJOczSQ0A4OUHoNmUoeGJKKdrGe0pRXbdU9WlsMxALVNQcbGEiOnQTLTTNjCPDuBameHJbtZi3JdoWw1IgoxCR8JxRF9WDNGuLUQrch3y+lmuXeaAoFiHopZHkNcDVK8gFmvIWYQpz5dQq0O4RsFMqyWLBMxE8M0ch3HclzA9T4SZC6KTvIxqGMqdyGvcKyccG3EldVp0QWlDqlCMyEJCrqpGlyPL+WV6/8rUusvU9mrgvqx06ZdruT+25wBpqoy0E2AcCcNLk/zwkiWIEbcqJtdGQpvnLDlViNkTyiXxPO4SflUyJHYiYKee09pHDj4SIQmbJtFQJrcuwOuAm9cUpqYFxeMGEnDEmSTjYobEyHJN4ralaSAoYFhr+FHieuBZTy0CmvntpUHoI//FXsBNfHFYI3Fhp4zMjDZYzVmPNCbx+2A1/vDkfZzNpzjt+R5b6ga/+l3QOg1bEZlgbInS1HwXVYp0Q8t0GBGGNWipcxk6AMAHBOMLZ0CcdNTKghIdP1DSrul7PJa6HqLEHV8EOV+jvWwhhpj7S3wUi5DbTFanNtXKQsfUqRhcvkFSCjOlY8Xgymf8dzE4NDcezRX3L6VnhZG8/o43ZntpoVYCem4RJN/l+sawJ9WIDb1XcbUE+YDm+iD3JUOuR+SUJgDYayo3dHWZmkXYoKqvLY0Hf4/Q80ugu4iTTsPxkVSwlo+9JrRXAe3FOuuNpPSmMJVnBGA802gvbx0aYuSUp7CU+wCwfomwlEl8u2cKci0gRkDPVS4kI88eiJlJtAxRgDTsQU0fW/zq8YPMTsXkNxL6inDzmMEY6krBN9z3pyZec+2htIM566EWAjcRuPFoi64/9/WJghkE9s4JbRyzs9d6/O2TN4Cz4l59gKONv29iXdRi2uFsPsXykxnejPfuN1frdMs2lh0ALydSpqACWtXgq3qZEZQESRY3ziISgUli4AV8Im2J3oPtFaRwBWyVAF3AxrF8o+A6zqUDQNMwa1Wi40vFagk0lQBTwCZoyvZqAyiVtidwVAJ6+U5mIFj6d99JmInIBWRpqWImYkNO0PYCrhUgKzHWoCzBq4KA7gAAA09JREFUIDQpKYsEQUoE8hj3qXgWcf5zDWWwFMDFXqkmZKyOBwL6TsIPt2+rGkSWzns8ANQWUMtMKWqgpmMxGY3XEuM+75uAU1lmMJ3vqcF6Va3D8rgzmMrMeFyTJRBWAqaNe8y2JdcE24cNvVTfAObAsxwlADsL0RMS+MGjp/j5Yy4ADE0AGo8gFPYe8Rv8Rk8hGr4PHhzxtok2mDVr/AoPMPZNkRSMAkDbNh476MM1zJNp9rr06Qp/9vCfc60HAHzr4UXGUQDIwczjyQqn/RxvGonvPeTK6KVpcKZuT+wvsl2Ac2c729md7N56Fs+15yWNPyORHBJku7aKY6H+HUWlr42c+/ZvQ6gwA1s4jSiok4wcbrXHGhEox6u+iy2wV1In2/is/q3GBzC2IOlQhAzg2ihGqzAOIZ2rCxsq5ACiBkbpb+731vai7PWcc37OtaAKN1D/NvcrFnyJqKORtgtXziPrcJjSpw3AkqFbcQwgxjiyvka1VLWlrdQHsqmvFVYj9d9QiZukax4C5mPL4D0gBlcZzDcmLlJD8DHwPWy5/c5KwJR9mxeohJElOCuYCi+lsK3EmZnBmzIIS6M3/k7tLrXGUjdwVmJpmrLv50DIfXMmi1qycDtDsb0NwEa1aAJpVaCtIDZ/l9S0NtB8223WdSJVtL30sfyd6NXq9phKDeV41XdfYlJ5GxItP221k6ne03EDSJTzKDtic2JLp/G8mJZzkWsSpV/V5/b29N1Xd1A+5+fABdO/bbe7udMtfFFRQ499AyIGwm/2CQCgw8ayJLehOAvi9eb4sGRA1R+BkknZHiPidvI5EPLkNmvWCJHcOKgA6ICgApqGZ5a1DhCa78FO87a0DJHKwWmZ9/XyOeMCIMgAKRkpmiZSqRxO9Ty3ndqt/07tTrSBoAAhPFrJ26wXEJ8DIUfbgcSvw4joKYAFgLOvuy//ynaK3Tn/Pth9Puc/CCE8uMuO92KyAAAi+qcQwr/7uvvxr2m7c/79sN+Vc94FOHe2s53dyXaTxc52trM72X2aLP7y6+7A12C7c/79sN+Jc743MYud7Wxn99vuk2exs53t7B7bbrLY2c52difbTRY729nO7mS7yWJnO9vZnWw3WexsZzu7k/1/NPjAjD8+tQ0AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.065951108932495 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-06, 'kernel_type': 'branching'} is: \n",
+      "[[  32.000096     16.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [  16.           32.000104      0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [   0.            0.           32.000096   ...   32.000096\n",
+      "    32.000096     32.000096  ]\n",
+      " ...\n",
+      " [   0.            0.           32.000096   ... 3232.02221617\n",
+      "  3128.02248416 3200.02392006]\n",
+      " [   0.            0.           32.000096   ... 3128.02248416\n",
+      "  3030.02368618 3092.02624609]\n",
+      " [   0.            0.           32.000096   ... 3200.02392006\n",
+      "  3092.02624609 3184.04341226]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98abac50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 48.92611074447632 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1e-05, 'kernel_type': 'branching'} is: \n",
+      "[[  32.00096001   16.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [  16.           32.00104002    0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [   0.            0.           32.00096001 ...   32.00096001\n",
+      "    32.00096001   32.00096001]\n",
+      " ...\n",
+      " [   0.            0.           32.00096001 ... 3232.22217717\n",
+      "  3128.2248565  3200.23920574]\n",
+      " [   0.            0.           32.00096001 ... 3128.2248565\n",
+      "  3030.23687824 3092.26246855]\n",
+      " [   0.            0.           32.00096001 ... 3200.23920574\n",
+      "  3092.26246855 3184.43414602]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 48.81668519973755 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 0.0001, 'kernel_type': 'branching'} is: \n",
+      "[[  32.00960128   16.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [  16.           32.01040176    0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [   0.            0.           32.00960128 ...   32.00960128\n",
+      "    32.00960128   32.00960128]\n",
+      " ...\n",
+      " [   0.            0.           32.00960128 ... 3234.22331772\n",
+      "  3130.25005023 3202.3925739 ]\n",
+      " [   0.            0.           32.00960128 ... 3130.25005023\n",
+      "  3032.37042487 3094.62545487]\n",
+      " [   0.            0.           32.00960128 ... 3202.3925739\n",
+      "  3094.62545487 3188.34380269]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7fd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 48.88551139831543 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 0.001, 'kernel_type': 'branching'} is: \n",
+      "[[  32.09612806   16.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [  16.           32.10417616    0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [   0.            0.           32.09612806 ...   32.09612806\n",
+      "    32.09612806   32.09612806]\n",
+      " ...\n",
+      " [   0.            0.           32.09612806 ... 3254.38853506\n",
+      "  3150.64970169 3223.97744677]\n",
+      " [   0.            0.           32.09612806 ... 3150.64970169\n",
+      "  3053.86931114 3118.33161895]\n",
+      " [   0.            0.           32.09612806 ... 3223.97744677\n",
+      "  3118.33161895 3227.67299453]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.10343670845032 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 0.01, 'kernel_type': 'branching'} is: \n",
+      "[[  32.972864     16.            0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [  16.           33.05776064    0.         ...    0.\n",
+      "     0.            0.        ]\n",
+      " [   0.            0.           32.972864   ...   32.972864\n",
+      "    32.972864     32.972864  ]\n",
+      " ...\n",
+      " [   0.            0.           32.972864   ... 3472.20027986\n",
+      "  3370.10823335 3445.0014973 ]\n",
+      " [   0.            0.           32.972864   ... 3370.10823335\n",
+      "  3286.04208239 3363.15539345]\n",
+      " [   0.            0.           32.972864   ... 3445.0014973\n",
+      "  3363.15539345 3644.95802609]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 48.9704692363739 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 0.1, 'kernel_type': 'branching'} is: \n",
+      "[[   42.944         16.             0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [   16.            44.3264         0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [    0.             0.            42.944      ...    42.944\n",
+      "     42.944         42.944     ]\n",
+      " ...\n",
+      " [    0.             0.            42.944      ...  8346.13431859\n",
+      "   8037.8729408   6232.308736  ]\n",
+      " [    0.             0.            42.944      ...  8037.8729408\n",
+      "   8507.94753363  6732.5824384 ]\n",
+      " [    0.             0.            42.944      ...  6232.308736\n",
+      "   6732.5824384  11086.190464  ]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 48.982431173324585 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1.0, 'kernel_type': 'branching'} is: \n",
+      "[[3.2000000e+02 1.6000000e+01 0.0000000e+00 ... 0.0000000e+00\n",
+      "  0.0000000e+00 0.0000000e+00]\n",
+      " [1.6000000e+01 5.3600000e+02 0.0000000e+00 ... 0.0000000e+00\n",
+      "  0.0000000e+00 0.0000000e+00]\n",
+      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 3.2000000e+02\n",
+      "  3.2000000e+02 3.2000000e+02]\n",
+      " ...\n",
+      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 3.9599184e+07\n",
+      "  1.8790076e+07 1.9904800e+05]\n",
+      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 1.8790076e+07\n",
+      "  4.5132236e+07 5.0194600e+05]\n",
+      " [0.0000000e+00 0.0000000e+00 3.2000000e+02 ... 1.9904800e+05\n",
+      "  5.0194600e+05 4.7488000e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 48.99586868286133 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 10.0, 'kernel_type': 'branching'} is: \n",
+      "[[7.77920000e+04 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.60000000e+01 8.18672000e+05 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 7.77920000e+04 ... 7.77920000e+04\n",
+      "  7.77920000e+04 7.77920000e+04]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 7.77920000e+04 ... 1.39109795e+16\n",
+      "  7.18668723e+14 4.54391680e+09]\n",
+      " [0.00000000e+00 0.00000000e+00 7.77920000e+04 ... 7.18668723e+14\n",
+      "  1.42558312e+16 9.54906688e+10]\n",
+      " [0.00000000e+00 0.00000000e+00 7.77920000e+04 ... 4.54391680e+09\n",
+      "  9.54906688e+10 2.40390375e+12]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.167264461517334 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 100.0, 'kernel_type': 'branching'} is: \n",
+      "[[6.52896320e+07 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.60000000e+01 6.56177043e+09 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 6.52896320e+07 ... 6.52896320e+07\n",
+      "  6.52896320e+07 6.52896320e+07]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 6.52896320e+07 ... 9.71197172e+25\n",
+      "  4.87507385e+23 2.94958331e+15]\n",
+      " [0.00000000e+00 0.00000000e+00 6.52896320e+07 ... 4.87507385e+23\n",
+      "  9.73625794e+25 6.40475930e+17]\n",
+      " [0.00000000e+00 0.00000000e+00 6.52896320e+07 ... 2.94958331e+15\n",
+      "  6.40475930e+17 1.60897659e+19]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7fd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 48.964667558670044 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1000.0, 'kernel_type': 'branching'} is: \n",
+      "[[6.41280960e+10 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.60000000e+01 6.41601761e+13 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 6.41280960e+10 ... 6.41280960e+10\n",
+      "  6.41280960e+10 6.41280960e+10]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 6.41280960e+10 ... 9.36859917e+35\n",
+      "  4.68617006e+32 2.82902806e+21]\n",
+      " [0.00000000e+00 0.00000000e+00 6.41280960e+10 ... 4.68617006e+32\n",
+      "  9.37094141e+35 6.16941595e+24]\n",
+      " [0.00000000e+00 0.00000000e+00 6.41280960e+10 ... 2.82902806e+21\n",
+      "  6.16941595e+24 1.54317278e+26]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f548227f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.25413680076599 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 10000.0, 'kernel_type': 'branching'} is: \n",
+      "[[6.40128010e+13 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.60000000e+01 6.40160018e+17 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40128010e+13 ... 6.40128010e+13\n",
+      "  6.40128010e+13 6.40128010e+13]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 6.40128010e+13 ... 9.33493322e+45\n",
+      "  4.66765328e+41 2.81729956e+27]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40128010e+13 ... 4.66765328e+41\n",
+      "  9.33516660e+45 6.14653512e+31]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40128010e+13 ... 2.81729956e+27\n",
+      "  6.14653512e+31 1.53671604e+33]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54822470>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 48.96194124221802 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 100000.0, 'kernel_type': 'branching'} is: \n",
+      "[[6.40012800e+16 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.60000000e+01 6.40016000e+21 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40012800e+16 ... 6.40012800e+16\n",
+      "  6.40012800e+16 6.40012800e+16]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 6.40012800e+16 ... 9.33157326e+55\n",
+      "  4.66580529e+50 2.81612992e+33]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40012800e+16 ... 4.66580529e+50\n",
+      "  9.33159658e+55 6.14425345e+38]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40012800e+16 ... 2.81612992e+33\n",
+      "  6.14425345e+38 1.53607159e+40]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7fd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.05475473403931 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[6.40001280e+19 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.60000000e+01 6.40001600e+25 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40001280e+19 ... 6.40001280e+19\n",
+      "  6.40001280e+19 6.40001280e+19]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 6.40001280e+19 ... 9.33123732e+65\n",
+      "  4.66562053e+59 2.81601299e+39]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40001280e+19 ... 4.66562053e+59\n",
+      "  9.33123966e+65 6.14402534e+45]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40001280e+19 ... 2.81601299e+39\n",
+      "  6.14402534e+45 1.53600716e+47]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 48.961668491363525 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 10000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[6.40000128e+22 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.60000000e+01 6.40000160e+29 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40000128e+22 ... 6.40000128e+22\n",
+      "  6.40000128e+22 6.40000128e+22]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 6.40000128e+22 ... 9.33120373e+75\n",
+      "  4.66560205e+68 2.81600130e+45]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40000128e+22 ... 4.66560205e+68\n",
+      "  9.33120397e+75 6.14400253e+52]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40000128e+22 ... 2.81600130e+45\n",
+      "  6.14400253e+52 1.53600072e+54]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.13634467124939 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 100000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[6.40000013e+25 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.60000000e+01 6.40000016e+33 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40000013e+25 ... 6.40000013e+25\n",
+      "  6.40000013e+25 6.40000013e+25]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 6.40000013e+25 ... 9.33120037e+85\n",
+      "  4.66560021e+77 2.81600013e+51]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40000013e+25 ... 4.66560021e+77\n",
+      "  9.33120040e+85 6.14400025e+59]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40000013e+25 ... 2.81600013e+51\n",
+      "  6.14400025e+59 1.53600007e+61]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAACjhJREFUeJzt3M+P3HUdx/HnS4o1Gow0aIOASkwvcHBDNuiBmBoSfl0KF4IXG0NSD/AHwAmPXoyJiZLUpKEeBHsh9NAIpBdOIDVpsBiJjRZpLa2KQaOx2vr2sN+GSe26b3Z25rs/no9kMzOf/c7u+9Ntn5nv7ExTVUjSSj4y9gCSNgZjIanFWEhqMRaSWoyFpBZjIall9FgkuS/JW0lOJnli7HlmJcmpJL9McjzJsWFtR5KXk/xmuLx+7DmnkeRAkvNJTkysXXWPWfL94ef+RpI7xpt89ZbZ87eTnBl+1seTPDDxuSeHPb+V5N5xpl6dUWOR5BrgB8D9wG3A15PcNuZMM/a1qlqoqsXh9hPA0araBRwdbm9kzwD3XbG23B7vB3YNH/uAp+c041p7hv/dM8D3hp/1QlUdARj+bj8C3D7c54fDv4ENYexHFncCJ6vqt1X1L+A5YM/IM83THuDgcP0g8OCIs0ytql4B3rtiebk97gF+XEteBT6V5Mb5TLp2ltnzcvYAz1XVhar6HXCSpX8DG8LYsbgJeGfi9ulhbTMq4KUkv0iyb1jbWVVnh+vvAjvHGW2mltvjZv/ZPz6cXh2YOL3c0HseOxZbyV1VdQdLD78fS/LVyU/W0uvuN/Vr77fCHgdPA18EFoCzwHfHHWdtjB2LM8AtE7dvHtY2nao6M1yeB55n6eHnucsPvYfL8+NNODPL7XHT/uyr6lxVXaqq/wA/4oNTjQ2957Fj8TqwK8mtST7K0pM/h0eeac0l+USS6y5fB+4BTrC0173DYXuBF8aZcKaW2+Nh4BvDb0W+Arw/cbqyoV3x3MtDLP2sYWnPjyTZnuRWlp7c/fm851utbWN+86q6mORx4EXgGuBAVb055kwzshN4Pgks/Zn/pKp+luR14FCSR4G3gYdHnHFqSZ4FdgM3JDkNPAV8h6vv8QjwAEtP8v0D+ObcB14Dy+x5d5IFlk65TgHfAqiqN5McAn4FXAQeq6pLY8y9GvEt6pI6xj4NkbRBGAtJLcZCUouxkNRiLCS1zCwWH/bdpBMvgd4y3PPWsFn2PJNYrPLdpJviD/RDcs9bw6bY86weWWz1d5NKm86sXsF5tXfXfXm5gz+a7fUxPs4ns2NLvULMPW8N63nP/+Tv/KsupHPsaC/3Hs7j9sHSH+ZdH/xnQpLm5LU62j52VqchK767rqr2V9ViVS1ey/YZjSFprcwqFlvi3aTSVjKT05At9G5SacuY2XMWw39SemRWX1/SfPkKTkktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLUYC0ktxkJSi7GQ1GIsJLVsm+bOSU4BfwMuARerajHJDuCnwBeAU8DDVfWX6caUNLa1eGTxtapaqKrF4fYTwNGq2gUcHW5L2uBmcRqyBzg4XD8IPDiD7yFpzqaNRQEvJflFkn3D2s6qOjtcfxfYOeX3kLQOTPWcBXBXVZ1J8hng5SS/nvxkVVWSutodh7jsA/gYH59yDEmzNtUji6o6M1yeB54H7gTOJbkRYLg8v8x991fVYlUtXsv2acaQNAerjkWSTyS57vJ14B7gBHAY2Dscthd4YdohJY1vmtOQncDzSS5/nZ9U1c+SvA4cSvIo8Dbw8PRjShrbqmNRVb8FvnSV9T8Dd08zlKT1x1dwSmoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqWXFWCQ5kOR8khMTazuSvJzkN8Pl9cN6knw/yckkbyS5Y5bDS5qfziOLZ4D7rlh7AjhaVbuAo8NtgPuBXcPHPuDptRlT0thWjEVVvQK8d8XyHuDgcP0g8ODE+o9ryavAp5LcuFbDShrPap+z2FlVZ4fr7wI7h+s3Ae9MHHd6WJO0wU39BGdVFVAf9n5J9iU5luTYv7kw7RiSZmy1sTh3+fRiuDw/rJ8Bbpk47uZh7X9U1f6qWqyqxWvZvsoxJM3LamNxGNg7XN8LvDCx/o3htyJfAd6fOF2RtIFtW+mAJM8Cu4EbkpwGngK+AxxK8ijwNvDwcPgR4AHgJPAP4JszmFnSCFaMRVV9fZlP3X2VYwt4bNqhJK0/voJTUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLSvGIsmBJOeTnJhY+3aSM0mODx8PTHzuySQnk7yV5N5ZDS5pvjqPLJ4B7rvK+veqamH4OAKQ5DbgEeD24T4/THLNWg0raTwrxqKqXgHea369PcBzVXWhqn4HnATunGI+SevENM9ZPJ7kjeE05fph7SbgnYljTg9rkja41cbiaeCLwAJwFvjuh/0CSfYlOZbk2L+5sMoxJM3LqmJRVeeq6lJV/Qf4ER+capwBbpk49OZh7WpfY39VLVbV4rVsX80YkuZoVbFIcuPEzYeAy78pOQw8kmR7kluBXcDPpxtR0nqwbaUDkjwL7AZuSHIaeArYnWQBKOAU8C2AqnozySHgV8BF4LGqujSb0SXNU6pq7Bn4ZHbUl3P32GNIW85rdZS/1nvpHOsrOCW1GAtJLcZCUouxkNaBF/9wnBf/cHzsMf4vYyGpZcVfnUqavXs/uzD2CCvykYWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFtIGtu0Ln5vb9zIW0gZ28dTv5/a9jIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGpJVY09A0n+CPwd+NPYs8zZDbjnrWA97/nzVfXpzoHrIhYASY5V1eLYc8yTe94aNsuePQ2R1GIsJLWsp1jsH3uAEbjnrWFT7HndPGchaX1bT48sJK1jxkJSi7GQ1GIsJLUYC0kt/wUTFWjNk6oV2wAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.124680042266846 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 1000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[6.40000001e+28 1.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.60000000e+01 6.40000002e+37 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40000001e+28 ... 6.40000001e+28\n",
+      "  6.40000001e+28 6.40000001e+28]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 6.40000001e+28 ... 9.33120004e+95\n",
+      "  4.66560002e+86 2.81600001e+57]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40000001e+28 ... 4.66560002e+86\n",
+      "  9.33120004e+95 6.14400003e+66]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40000001e+28 ... 2.81600001e+57\n",
+      "  6.14400003e+66 1.53600001e+68]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 49.06690073013306 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 4.0, 'lmda': 10000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[6.4000e+031 1.6000e+001 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [1.6000e+001 6.4000e+041 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+031 ... 6.4000e+031 6.4000e+031\n",
+      "  6.4000e+031]\n",
+      " ...\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+031 ... 9.3312e+105 4.6656e+095\n",
+      "  2.8160e+063]\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+031 ... 4.6656e+095 9.3312e+105\n",
+      "  6.1440e+073]\n",
+      " [0.0000e+000 0.0000e+000 6.4000e+031 ... 2.8160e+063 6.1440e+073\n",
+      "  1.5360e+075]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.07693910598755 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-10, 'kernel_type': 'untiln'} is: \n",
+      "[[1.45000000e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [6.60000000e+01 1.24000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.45000000e+02 ... 1.61000000e+02\n",
+      "  1.61000000e+02 1.61000000e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.61000000e+02 ... 1.67010000e+04\n",
+      "  1.65970000e+04 1.62110001e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.61000000e+02 ... 1.65970000e+04\n",
+      "  1.65150000e+04 1.61070001e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.61000000e+02 ... 1.62110001e+04\n",
+      "  1.61070001e+04 1.58470001e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.155569314956665 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-09, 'kernel_type': 'untiln'} is: \n",
+      "[[1.45000001e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [6.60000000e+01 1.24000001e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.45000001e+02 ... 1.61000001e+02\n",
+      "  1.61000001e+02 1.61000001e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.61000001e+02 ... 1.67010005e+04\n",
+      "  1.65970005e+04 1.62110005e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.61000001e+02 ... 1.65970005e+04\n",
+      "  1.65150005e+04 1.61070006e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.61000001e+02 ... 1.62110005e+04\n",
+      "  1.61070006e+04 1.58470011e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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xAFW1IPmeBfoCCvDLjO0kjm99NPoyVVWZFC1uwpiJ1NSp/34HAMVtNzXT7P0ICsqSPvrzs/KizvwikwiUInpnGIX8MuiYN/UUdKVtNzV4GOG8R7zbTrbb6IE/PxN/jEZO7KKjDk0TrYIjYBgFGGVMBt2ODPyzk2wab0flGYkh+xH45nbvROMfPchmqY0E0WoFTnklAIrfJve78LO4x4/AXQ+qDNfKJ18EUNZc5hwWeQU04KvJ7rx7nP19lieSIxp5gjDntG3BT7z4YIlMFERp2vM5oKlJMhsAdLNoSuqPpiDnVGTm/TkujvaCviaedCCHFplLP6Tf6WUwdu3BSIWN/szkUCIa71nJyfSLiIrmYVZLq+dkDeVAIhn3/UGNERzBs6QrdNNtTGUM9yYspgkVQHFQOyegrD0ENKSa7uw69RrZnDMvBgd8TtkJa/0x2y246yfHTBz9tj0AGFcCPJssKMdj0t+fycLiLmyEw+IpjDMzYzFSBAPAJJNwwqoFo1nY6ICNqmhbjiQyYWHhVbXzkLqmfna0YqZZZI3D9IefoVk8D8eR+6bONpOpKA/QDHasEYjFomgQz9EstM3SIMuKyvszTOeahUaA5DR00FxTGLle245moW0c0CwsTN+GhlWzUNQqLRcZQ0KLBuj6yTkAgPT83mfcBp2tn6lZ0HM0CzKaBQ5oFrReIZMWq4bV1Hs1CzqgWdB6KU5eGw3ZHm+mvFuTxTOzTme4i+dpFjmd2axoGdIdMc9iPFaz4GEUF4tlsrL4iGHm9bbyKjWLvZlCboJn0NV0eqGzbXOfiGWSet2ahfXiAzsMW1lmWuLr0iwi2mKe9f0uJmOuISieoutev2ZhIzUGzHcvzaLrJJ3ebruHZnGKhpzkJCc5St4pzeLZKeoFdzHBXOxL4YZxZiYVFIDgMBLiUslGpv4IzHwjs1WKGdRMh4y8AmFiaQNAePp07zUey9qW/TJz8hsVY27MIxJF3GQVAqyGos5X+d09uAT3A+LdZkcz2Okb7dceygH7Vvc9qrWvZ911BXJvnay1B1WVwUFM08T3fdwvYdJv4Vst27KZkz7rVZDCr02mLzuJDtGDS8TPnkw0pzkewsoh3Tn7TQ5EZqhJ+Iv1Kr8n4dPPdrg6dygI7DmWixeORAHv2GTxTHlRcoB9kOn7hEAPndNAmtk936H6OmUn3GmErFMuHxB3P0c+Ltz3CmVHPdf2dzg3wks95EeLzYxNILkdMZMsO0z9A2+ib4fAaUcIh13w4H3knZosnsX2pL8dtOl2D9j5LLY2H5y9jxLt4yGcxptinJq3fyTt/CHKNSGrfZ0IjmeL9QvsC6G+ib5N2tZUc6BoZfv68LIYjfvKMB4uF/EcoZRMNgmv32Nc36nJYicebclv1AnVtkJcY5KDYj+UXA/AgIGGZI6kY43XOLNmaahMz5nOw3cboK4zBwBQnEdUVbm9uG3hVktEtPk7APgPPgCGfqqFVFXJRGy74gEfetDZGRATdBgQ+O+2zUQzMOEyWq3EvJrxJVDTlHwEALzZisra9zljU3NPcjZrUm9Darf66oc7tPSa8ZhfmrMV6G4rWYy1MSXGETwMOw5JRAZWyxKW1GOISn/SWDjNeUn7ukUjTrztFtVXP5R964QFCVEiEnq9ywWoH+S8Gr1QB94wAnUFvlXzM0Ux6gp4msa8qiT7cwxA5afREO+n21KWaHzyFPj6n0P1RPAx7B1QeVDbI56tUh8KNoIX6fnyHnAADQE0BMRzIb+pPnpSold2IlouwHUFurkDpz64r/04hq+co/64EOZwU4Fa4+ROmAr2JP7gtgOnZ4GYgW82OFZODs6TnOQkR8m7pVk8S6y6ZMNwJjXaqt17HUY2dTevnmm1VDq7ebtzu1VZo2xas8kEzKupDadpMqzyVaRiN2RCc2hbuQZVg1VrSPR1E8BVCOA+7Nqus/04hf84BEDpK/cdY79utlONwBF4dNMUdbWb56nyc44LXU2ZZcU3YWPFIuT+GKYpZp6O7yj7ZSxDbxLVDLcFjYn3wjmQoS/k5ASksSraaxS0KY3GadlvBWyl12BNypT1mbelhDvue/gntznzk4iAShC9TuntDKw7Yxwq48QdA1w6b9bMXNGu4LyETr0Hb9s8Zu76DjUAurV8Fk40o3yzaLKdxxFuaxLKvpCgrLm8IMPxXnHOYOmnvA3sXAEn3dfJtg+fr2X0DAiJYjq3Q9nXEaDp8YGn53T0+siuHeUICVwsICMAk/IDGrGwE4NjgKmYBgkHUdLQqfx9EYclmeMjy7mdA5tIC6mvQSHNREDoEziPiulnU+MtadILCGvKvMrcJzTLqJ5sozRe+lITiePUObBTEJrbX0xIr9UR8jJnfS77omgvIe/2ZGEnBEtua/gjFKFoGa0Ag4DcwzUBIBP2ckoYo/VqSrKqtvScpKSqCtIPAG7vhLEohfUykOniXFKmbZ+aJtu6fLctqM2uyynK/PGnsu9yKav8YiHJTxpW3myBupEaEN2Ml3GxKGxSAPj2TvwkXSfXp8frdYVQUIaqWT24NElNqe+Vn4xDPF/D3W5Es1jINVAU9Ca3XdFMsiPOg87PJmTEAIDzswxjtiuuaggyDgug7YToRccooVdpDOJzSP0MF0u4bfJZ6MsXI4AzSZNvatDnpS4LX54jNjWcruDnZ+BFI+etPGjms+C6AqXngtN9dJHR/+gj1J8oixeBaw+36TE8kDF3vWqxQFyl+1gLQY/rA1w3YnggPovltxLHBxGo0ueOgEeX4KaCe3or4wEg/NAjbH5kjfWflNc4Lmu4zSALT5R2AIArB4oMt+kR1sVPwZ9/UXJDOOVizMWaBoc81RrnPlQ0x6rPMal8IUzRbY6AYRbGS5BmMt9pHHfa534oMfCchBRASNmsMYCVNi3EBJPmolkYNTzvk/sbwDHsmFI0juDemGKj9JNDKGqzRcAqzRpMJKofCnmshX17M9F2vai6IZTISkwmkGXXVnODY1HvgaJej8gTU55k1WywBLj9INeoC4T2P8RJfonb9KBuAPupGZInMj1O75s6Q3X8ul7OPQZQ2HVwUgh5m45yHEdUt0OeROAcaKxAbQ9fJS1yTCHLyMX0rJPWEBg0BFTeTPwhynXncCmBtp2MedfnMXObHs11A9eWSBYFBnWGtUvJbTwBgUFtBy2NQswTFO3z5J2dLATYcsDUcIZ30ftCYKITh8snSSrvLHsUyFEPAgSnX9dgoqJxbLbygCgDFJLdR1QYllBs1Ew1p003daFhU9OjqXO0gkKQaIucBLxsQJajsU6rp9rwuvIa7acU0U0vYVWVVRuQh6qqBDykx9jchlByEjJ8fdmAhtRffWgrL17+JLwWcA/1Q15hEaMcF2N+UZlCMTkWTQlLLpqiJuuLOtcsnNmXWXxAy9RWU8sLFaN8Tvcnrht5DioH1hd1CMAY5RpWTc7toBDBqwXiuoG/S2PjnWgWPmkWMKKahY5Bum6qKnQPGiw6ZfFyiMsKHkA4l21uSJMFM+JS2goLLy9rZLguYDiX7f5p0my8y33lykskp6lkgtPrPVugfVzDbxf5WYiLCt5TfkdiXaIhboyyTlnNwh94x/bIKRpykpOc5CihZ6H/3pRcusf8U/RvT+37Wors+PMzANhfICgJD6NU8LYVxzaFJXkf8MQtl/s7k1ZFWixkpemmILB4ezv1pajmMEOHHqqGvlfUURUjaJX6NdeGVF1P2sYhCjgLuDq6pCGQowTu7KxsmzvIdGwyYa/JhlWzZrXciYZg2AOkI4d4gBpwn3AIZUxtpuk+B95Mmyy8IhFO/R42ipZMnnhzs3tvTX8n2wxhr3/0YBo5SRwZtgDTDumRPjOUaPUuUxV1GxVSACIR4s1tOY/S6q3X4nOaR7hCKE5g+zz0w5SwF8A/2vxPuIqfHeUFfWfNkGd5/CclBMkMit4c5/C8UgAwYKKSCUjlQVeTxGLvU9Wzo0sB5AbMQ7Mvs1IzGCMXYhIllkksTJM8haqC66fcizIuDhN0X0qDn7Bw7zsGQExZr7RaTsfJpjgb0hQ4J+c3ZhWHKPuok1XVaE3HVnMuRZ9sZufzKpIBAKXJYvISGsbuiWlVm6hH25UsUTUfkhORKy9U+hAn74sQ9uLxQ5CCvZwDmlp8GJawV8PBam4p6XHqc7yQSdptWoBZTJ5NGu/KixN2Tth7eQF+cA7aGJ5YZvFtzKMhjmQc5oS93ftG2MvADsDhGbR6liZfXoYAgi/kusdAcHUfpWf3HhiSMwxp5QmpClb2j9wjd8KmoNsVmXVVjmWFZpaXLjJYV+G6mWACSop+zH18LWInR52E04TLsfhGxGEZCytWcuBxDCXOr/uHIIhFHdt72MkTiYpLMffBlgbkRKE3FCetvqSs+xp0KlUeNPrjUwgOCA1jLhlInoE+ObMtXJwLvZ/0Oz3DcRQ/lGqwW5ksqPcFoTscWPhDkAl5KA5OKIGPThaZr+TlQ6jvxmRxSA4lZe0DZc33fU75wknOv+FQzOdT8pwJGCwmtRZF6zlYvvAAs/O8pBwAC3vOsHWltNdJ06i5PI57mbg4BJCb8lE8L5txzg+ywwC9xwxBP+SVd8cMqatpNCT95WC4RQPtb2ufaGRGwW+2H5iaIaz9sBpW5BweByQkLdsF2CY4jJD780LlC29up2RAStU3uz62K71qQUnD0KgO20kug7KokPbYheNuI0ArS7WnEcAjzZBT+cKTnOQkr1zebc3iEEpzXh1LVWVbkPd55Qvnfg9deaxt772YHrb699E+ixllnO17cmrtlARMqnz+rn0LcVoUyfu9tH2vxGexWOx37FnUpfpXYsioTrJa2J6syEmmqx4Twv18FuoLMXVJcplHJF+Ihm5NASdBSLoc+pZDSfarqlwgiBaLFytfeHkxhXvXtSTvqV9MtS5rFtSpBKQj0Q406eyuFCvKfirn4FZhT5GhNfgy+SzmZsgcPUwEDMMXwGcBTJ0xJmc/tvowGXZvo/Zz9ioz2HjXqW4A+An5TSausf4Ek71q1cTYdXs94M7W24Q8HLRc5KxTGymYU+CTT0hIiC8kk/2MY8ZHxDtxlLmmluP1ZZmxiTvDlakPRXbi2fbqSuL1+rImIJKOs/bBpQxbm2VrX/6Jg1I5OA0v5uSa96i2tFhMmbGRXn7rnDTO1EkGsoKZMkakAO5srgunyMDE6FRVvO/AdYVookhusUj5FulFPz9LleBi5qucnCMySJ+JqgJVHm61zAA1AAX4pS8sAFv4J0+Z6oTsB8neTU7KeH2zy+cBwF1eQOHqZBfFEKa0elUl7ekCZyfwh5fiiLUZ2oeoDPfIuzNZzMU80Ds/eZ+x8vpZVgSzIiZ7n6jafXhQHtj8Ii8XgszUgVSqeyAzRWUmpaoqL296kechPFougN5N0KbzFPIcMWmR4dhIkwUtF+CtvMxs+zuMKZV6ARpKaA2OJinwAGQVch5wIVe6gjpWlQhXr3fbyst/ti5VyVQLqSpZlZVw92wF3G3zyp5lHOU8e8KZeTzMddNyWSqt6aqfVkStoJYnphDKGKkWZpPWAPB6KaAlK5rG3vUCDLN1Wc7Wk2gKLRYSyYhRohFWC/NJc9UJRIFltxvEL13CPS2ROPYO1PbgixTqtf4mhfgn4BT14qCMqxSl6fq9LO1Yr1KEpC3+tbMVxg/OJy9xXC4kEqOLlk4slUdsKjgAvDSRuu+9j5rFMTJRiWefZzNkri/i3EwFTiuEDa0B8kKkv5N9geLM1NCq9+WlT+omKwO2Pnh1qtxtVwmLsOyHCaoy06ZZ7gtFi4aQ+0udbKOmnkYitM2FQXCOAVR5MFfCVg1MnGZEbpoL45y8UOlw9gZdmZCVQHoph7EgKHXMdaXcN8HreOhnYNIWbMg4xuKoTfvwOJa8mrqSiNDOZLGHNi7R9BEg6Ex7fxeNvLybtK2pwauFmAVNPYk6cSV8FtkRuUoo1rbDcLFArRBrl9CjRIhnmndT+hhXOlk4sCO4zsN1PqM968/qgl61l7FeSs5JjBnZGc+W6B818LcLs18jCo1OFgnJyrVHXCTTaW0WlHtoFicH50lOcpKj5N3VLPYhS1Ni2cRnoZT5NtZst4dZASDF0M8xGbd3U1o1PWcg8fZtAAAgAElEQVRuN5kA6vjqS+IPb7aybwIfAUC8ud3hjiDDycB9X6jixxH09Co1lVau2zvhcNgmu3TL+fe4beHmpQQAUXe326x1ic9jyjyVNQgdJ9vHGMFPnu6GU+c+i7aV0O09fBZ2PHKGa9dPfRb76oa0beGk+Pwq78s2RKjje7fZVeGVkyMxZVm2NJc0k1wBHRBHZWTxGdmSgrOKZLjbJofngOZbn0zOQd4D4wh/o5nIxZyprOM6OSM5RtRJ29rnswAAl/Znkzfj2w7rmzVwczc5v72nzjilebUAbTt4W5HsHjSQ7+5kMfNZ2MSySYq6TUXvjX+grnYKAClXAABxTAEF33B+NvUUG6o+2xYtxSmW1ffNFnRxLg44Q4XmLs4FKm5vvEkh59u7bBrwZpure1tnG27vxHfRdvm4GO7gVkuh4Zs9zDZRDQBo24oa3/UFsaqOxOREVNwB390Jd8fjhxkglLMx52bIg3O4q9tdM6QfwHebvYSyeTyAct3na1CrIDTBZ2Q6PG2r8pJFud2KjwGHzZB4sQJtZwArNUPaDrxo4CwL94MLMTc++1w2PHog1HzDKOnuN205R+qfOiJ5tUCsPdzTW/R/+gPUnyY4djJDaNsjPEiI076MR9gxQ0a4bsSoZsi39hPyxq88EjPkpkQ+wvkK7Q+vsfrjYoaEdQO36Yuj3pghw2WD5rPtNEX9vS1faLWJecp3CIAWhJkU9TmgWfT9bgGgMeaVW6MX99UsciEa9XQPwniVb3A63+vWLEhZqYAcDeENTcO6/bATTcn1T3WM1f7tOokuvEnNom0RZ1XKNGci57V4jziO4nTVyfE1aRYUU3QoBvirWlir9Bzz0PNtJXyhmy2ayK9ds6DI0p7hOPU3d/fSLKq6AtoO3qY69F8EzeJdF4u5N3Du1wjEPiyueOInqjylnAwq5hHbY2bMYPcJo70SsRiY/B1pYjMIWzM5v5l+UfkHTD17lu1rbjq9TrHtvChcXp3wLyjv1GTx3CJDIUiRoZsb87uBdVvxPhcp1pKCkyJD6rNQrUFXdD3entO0lTUPjXpoBCTlH2jmq7JlW9HsWG1vUjYgawlJM+mRsQT5b/qdB0xWdHuOnSIzGv9Xn4ViLjIDeuJzTGaCXXkn57GfDRvWfHI8VFwHXVe0BdtH1V4UQDSnIYyKkakLRuJA+UIJ/z5jut5iMj5Rx0BNx0Rwo3lBe8sXDibqQQR3cS5FhubagOEmOVS+MHUCx5QvpG0rY71aZpxF/PwpcLfZW75wZ3EAQBcXAkG3z849asWcoiEnOclJjpJ3SrOY2PgKCdaVOBU6DtfXcGdnBczT1MJh2TRldo+yEsR+EK92OqUtKeg/+EA+aAXti3OwSbmOnz8tmaCGO5JDAC0X2cEZb25ldUl8A7n+xo/+sKzA1qG2XGS2J7q5y6ncfLcFHiUH50cfy+U/fihO0KaR8yiY5/ZOOBmqqrBdZ2RlI/U5dDyvbwQD0vdSawTFgaqw6lw35NMn0u7Xfrw4HRX8U1dTDs4Ha7irjTA6LYuzjLoB2GyLXW9wIHR5UQBNqYyeTQ/P9VoUcarp7eslaNMiXt/A/dkfk22LSpD8wyh90/v7YCn8k0BeBimwaABtj7hsUH3yNPcpProELytU3xMHJy8b8HoBGgK49qBNeja0f00Fuks+p3W6d9/9BNuf/fNYfl+ugx0hNh7VbY/+sYy574oPKCQOztA4gADfRfg2oHsk43j2h0/kuhxNQGHh4TniskL1yTWQ2LnHb/w53P7pJS6+XVLUx7MK1W0BnsWmMGWBgeq2x3huHJy/N+WGeZa8U5PF0bJHjZ2rU5ne/RDHYEI/skYxuk5Srme7WfWSFYbeu4kaz12/48zktkuclMUJx30/yS4kvccxSAQicmlfyW7GIC+dhTWPktZsCXFUJhZpAkixgXjnSdY4LOWH5GjctFPCXkoPrS/X7JwTJOQYSnvJWaqlDvI2QI7rh5LGnfpD/ZAzT5WbkobEharOUED2CaHwXIZEJRDj5Fnw5tzZrh8lo5OGEc46hZnhNi041KX40TZxUiYwGywatEvRMY3o5PIBA5rP+xI58Q4uTTR1GnNKPK7EDNfJK1cpB+cYQf0IfWXzuFpKfyK4mw1cW4G2XR6z6rrF6tMK/rYQQ7uugtsOmUtWeUDZk/Bzbnu43viD9rGGH5D3c7LYIzaSwce4Ga1tm/gGJCX9iMGbPaR703xtJEa5RC2ik3n6ss7rUB5KvTe/8XyiDGHieWdOORXRnDvzlLrd65j1g5lFK5i3H0LhwMw1MfjZ9m8I5VpM3U6FkDOlyQppgg/lmnJbGjkhzesxPiRAkLCJv9JeL+k1zccmnTOPY6o5IgTOU02XEiw8T2Ku+CNcHyb3ldIEmycJq/EqN4WmG8UIGmN5gfOzyJPngUZTr0bHYYzwXSiEwNKYTDbql2JN1ZfJAiHkfs3beJ68s5NFrkR9SObw7nlm5/MIYiyUO2fmOUwcZprJarJH7xXt0Bocc4/53CttPO+TWpuKh5gwbblsQrwJyXU4tE/6V4vk2IjBPHNXJweFH2eIfvp7Dy6FnfY5hUS9K7Bsl3Aa2j9AGMSVeNgk2pGex7sJCdGLyBwyzZTqiOhti3vuV2LbZucAx4WbRrUi5wDSzNvDrkV2qeyBHRsdA4fCVk+EXXf0/eTk4DzJSU5ylLyzmsUzJYFeAJQVS9VHFeXwPMTlqWnSiu5sGqFCU0eiRulm2gR5L05BPX4cBZlpQ5NIzsy+nzo4F83eUgDc9+IoZAY04trU2XblSFNkaWXYqICyQi8WhfAXkDFKCXI5gc3Cq0PIRYaQHI28WoAG5ZtI41lXE9U+nq/gbrcyNorgZAa5UpJRTuBy9q8khPXl2mTQi4mjQCFFiqZyBFgtxTTRMdLjmcWmr0tWcThr4DqhlGOvSFAPXtagbpS/6rxN8Oe4quFv0r2sK0kQSwAu2hrAWSXJg9n8WKUksc0G/aMFlsmMYE+IiwpwwKhFhoZihmiRoZCK/7gxlQJ4INfmn25KKYA8jiSJZAsPH2LePjxYYftBDdcusi8srCpUt16uP3KuT8KVaDL+rkI4M4lk3z5eX3ipyYKIvgXgBvI6jsz8DSJ6DOB/BPBjAL4F4OeZ+fOXaWdHLK2a92AM08phMXFaKtw7U8uZvuuLqg45fZgt0a4jgKmcV4E4TZ1fPm7bBMlOfBa2/oamUas0NeJ6CTjA9UN54GJEXC8m/oHs5a/raaU0bGXiaOqyr8KyV8tMogJAnKaLJsfnZWzSvs4Jj4Ju136fLYFtyXsBkWRj1j7buuGykc9VQNToDjPQpVoXk8xWAlOqx6G+kKYWk6Gp4Ow2lGiIZmrGs5VYMW2bIxBxVYuzrh/lxUzSP16ivhlEpVezLkSwI1S3vUwm11pFnRHXDcKqhtdIzHqJcLEAdUFeTDMhx6ZCXFX5hQkX0pfqSY3tBxWqNvXNO4SFQwOg+1KqBdJWuc3xTK4r1JJ6ULWMauux/ZJsX363zhOlNSHGh0uEpceiC9kc6B822Hzo0VyXZ3Y492hqByaAOEVdAMRGoiFN49E/qPI9i9XxIK1XYYb8LDN/nZm/kb7/MoDfZeavAfjd9P3dlbk/YJ9oLdQXra+qxwNlxJ+HpFPbc97HY459CZlUZJu1wwkNynvan9jG6d+ENd3Kq0I97u3H/l2l33uOf12G+HPvr/m37ziLIn3GeNmJMZ/X/vYK5XWYIT8H4GfS518D8L8C+I9faQs2nKle9sGEuRwJOamG7PY4OzWBjMeUSXq3lRDmDgLSmDaWlUjDln0veRya56FmzY3kdlgnIIUApyXzlJYdEh51V3cSIdFEqk0rKM9eyFAssQ+3nWSXzkOnliUaEELXvs/kMQBKHRQNnc5yWvyTa8POndCUbT+h329CEHV+GHP1bw05ctvtUvhxBN2WBLNs+jEXjUzNumQeZWRpCq9yP8gYAaCNkN+Q0g2m61+2A6hLmba2dOAwgkKEa+vJtbnPb0HbRR5H6gdUm1b2mYVOvXOigaTxqzShbLPF5bdaVE+S3eqckMzctVi3y9IHZgEbK6dEU4mmFSWaUt2m2qk32zLuhnKw/t6Iuq5A13c5dLr67hrE51h8f5O1tsUTD9oO4kBlFlZ1APAkYdptj+ZJwVn47s2FThnA7xARA/hvmflXAHzIzB+l378H4MOXbGNXJpGPtOIbrkYApURA+rsj+nAmLkxqaqk9apJspCnjs3AkhZGbOpsF1PegRVOSwhTCvVyA2pmHva6L6WHIXIg72R4Z+DztX1fZP5GzZyEvO1Ue8M20lgiwA8rCUAh2Mqu14WokA8rKKdjrZamVaUFZlc8hu3i+lOxN7wohDcvETBNgnYYJ3aR8oRZThnOF9m0GylK/Ca+Tz6Lr89hxkyaIIcjnJOPFAl4LI+ukGyKwqOG6QUoVbgvjNq8XUkj4xue2p6Aso3Zo+UA115JJRDe36B43OfQpPgs53/BQxtx1irMAxpVOFgLKcgPDbwP6hzIm9ZNGfCYTzZIQz1cCyjJ1dofLJbYfeFR35eUf1x71rc9mSFQzxBMoAtWtn4KyqjfkswDw08z8HSL6CoB/SET/3P7IzJwmkh0hol8C8EsAsMQ9qned5CQneSvyUpMFM38n/f2YiH4DwF8C8H0i+iozf0REXwXw8YFjfwXArwDAJT2+XwDYrta2aIuJ3x+N4GQGRSSUYNyxGSe1HpAcoi0KHHkchfxmjuBMZk0+F8Rk0SIzPAYQd6UPm1YAQqo2dn02pyyBMSUClGxezMfAAo8Sn+Ok5oitvWFBWYrgvNlMAEYgkuiEQUW6p3eyYvclXVqATGESUcIYkKuob9viiNXOJPQrgKLpzch6KATZZxhAtymVXE0PjYik56EegtyXymeNg4ZkMjELgtOAtdzNVoBKapq0HVyXUu+d2yHCpcrn8XNJ+4pdj+UnLdzTYoa4ZQ26a9EoKjWkvoYInxyyvKhlzIhAQ8gRE2p7SS6rfCGm8R7+8xu4yos5l8asfrLBWeNQXRe4t7910reERcmag3PilO56eNVEmAtA6wh54cmCiM4AOGa+SZ//MoD/HMBvAfhFAH87/f3NF23jYNtVVbz6dZXZse0LhaYCuigPbqcThzmH1vRshWCWLs4FrqzhubuNZK42dXnBEocmrVeFM/PpFejBZeajyC/ao8vEBFUmIF42EvUA4K7uTPitRfjgMsFxUwjz8rwwMbddUffHayHMdU7IbXA4GuKeJDNh22biGFSJEHgeDUnnCl9+mF8EjEHs/9oLp0V60frHK9RXLagLmc+RIoPaEe7mrvhodJKtKimzl0wAXi/FIeopRyc0GhJzNCS9jGcruEQOHD54INtWQn5DQ5Cq5Nqvhw3qO8mriBqa7CMoMHw7Yjyv0Xz3Ot+n8MEFxrMaC510mxqjjYbcFJMlaDTkSsZp1GjIMODJT5zh4o/lVYqeEFYezecLtF+RfXwbARazYDiTfo1LArGYIVXLaB/JIvFoSAhL54ChmDbjZYqGfG8h4wHg7scu8flP1Hj4h+XeDGuH5iaWaMiC0rgSKADN1TiJhoTvvBnC3g8B/EZ6ICoAf4+Z/wER/T6AXyeivwHg2wB+/iXaeL4kWLVWxALSSv3c4wxMWc025lK+MMYC2Ub5/d59m0O4M4zbnDvEsvpE83sQRxubfu2c83XIHIbuvSReGHp5GqNAlU1/1WGXYd2WPWx27WSdb0dK9m8w0r2Rv9PtAIHhhgKJBqTvNJZQNqV7S69iPDn9g7ygFBlktlmgjhrlFAGQ/JV7n3ZI39lA9OnQ4q/XGxlTDgFGwpBmEOirIFp5d6uoLxbgYdxbRX1SAV3VRXJwl6lCdj9ItXM1IfZcY67IrXBmrb2hXv9Eqz/hZySXs0otL8UEmq7VyBOvhTSxZ+qykHQlUYlcWLgVmqwRE1XXE5Q3Xt1gJ29kznKe2MUmvA/7jgFyVq+/uJgR6BgHmIUd+xQtULBYuu4Jw7hS4/XDtN3Uz/j0qozBPDxotye+UZ+oB63jTwseZdHyBNqvkMoepr5Tep5skpaaG/HplURjlHnMOszTc6LbLP+E//Ark1KMVCeWrXk1eVuUqfKi2SmzVSqMbE0PLVyEqkJ88rn0VZMTAbiHD0TLVKZ1QEwPLV40YxLDtt0pX/h/3P4mrsZPjwqynuDeJznJSY6SdxruPan3oatzCvfZ6lY2tJh3b5rd0oJmdaML0ULQDxISXS5lJbZ1NLyX4jzqvKwquKYW8lwNZd7egc7PwInFKaoC8PihnNs6SJtawpCUiF8Vpdn14Mtz2Vd5Gy/PxefR1Kn4UepXIq71VVW0DQv3XhZ+Ar69k352XS7Qw7pazeDe8fMEsv2hL5fVTdGVlZ8A1uLFEu62E96FZXGWYRh3ncQQh2auNYLknyCCXy2hle/z/at8cpQa2HzbgW9ugS8/zsdTcm4qtwUAxPMGrh0Rkz8ESGZIyuzk2gOt+icY8Uwg1NXHoi365UKQpmMAVx7OYFbgPbiu4BSfo2HvT55g8xd+GMvvJ99L5RAbD3/XZ78GhWKiKeI0LJyYLMmfsv1QtOWzb90AgQUXoc+HI9DlGbip4D+/yT608c98FZsfWWL93TabGXHh4TdD0cgM3Jv6CH/XYdR6Jszgf/xF5LMwpgQb0llWOzkYFY9GxAmRb9w5hzr0RHx5iew+REl1nEZDeGvS4cdRyH7H6YTEpkxefnlU9VWzRR1rjsSZGUKJCnSJoVmBVwo6Iwf0w3MJgYEUfVGatRm9nj1Gup2u++qmmLeJGo70GlLfvPat6wuITbkiUs4FkDAsJHB5W0krc0FcXRe6P1MOki1MftvKmA/JeQpM1Gjqi7Pb3QmgieuqTMRjkLa1Vqm+5GOAu9kAXV0iW1fXgqfQ6xhmmBG7TXEh2y1Wf3IDuk732zu4RQPatKgTUU72iySmcSBFQ1JuC4YR6xwNSQtMXRWW9boCPhcTiZMpAQD1957ivD+HM3wWgJgy7J1A3Y3pSNsOPI6ozcL6hSHsnSAvjWYBYIJuy3+j4Uy0ZQ3VyWV9B/ow6WSykLqbJV3ZhCFDsW/hvYTR8sPCudQggGxPamKa9ReQd5PksQy06gfpT+UzQhBNLRNFIkHJCUy9sGbZcoD5JZyVRwTSit33RePQuUSLCGtUR9nAlotdBKdzE38Fa3mBXLsVk7T7XCJQtQzmpDGkE6RShXS2LuxZJnQKGzpdNDImMZaIUFUS3eSzvoCpPKGmeAOS/r1eirZQlzwhMANNI7T9OlbrlbShCM6ZZjHZpn3pB4yXS1Q6Zil6BObCphWjOCKZERsFn6VnIjKodVkLaTa9aBaxaGgUInB+JoC1NEkDQLxYoX+0xMLwWXBTyG8YACz5TSptGJdFs8Cnbw6U9eZkHlVQ0QhICJMISCaq3ceqBZTVhBkIDOoK5gFAXhEnzrO0ejJQHjp1oM3wCpbUNjsRI8lLQE4wBvbBbbsJgU+uj5mK7k4KAI+jqOZz2nsL34ZMSJnEty3H7hyDMjHzpt11RgI5KQyQVVn6FEokIhHdknNlwtJzhwjq+jy2pA5EW2PEZBFPNIt07RxiMVlMYWDSuqdIk5SyehlCXAvnzn2LUUK53hUn8mYraQNaOmGPZpG3qaY3DKie3E2qnyuj1sScSxqwFvhhwwdCw4hazaYu4WqiM4WgZaww0yzc1R0WANxtqSXCXpL5KHN+GC6SxOjmDIoVh3BIe+TdmCwY2Il16suuwJiZZpEfPEA84FQVkFLy+D5Ts9AV0fgjEGLxoiubsqkfQomL8hjNQlLMZy+mKVzMpqiw1vGkyNl8UY86OTelqgsDgNetWZiHXCMOFpi2WoC6Xl7anB1bZUq8bDrFxGTFEaiaAgVXLeKemkW+Bu+zWp8LDqV+5Srxqgml4s+qWeQUdWbxndRV5rR8Uc0iPFrD66SZNAtyJBm8QAnfMmewmGofCIIX0VqndNeKjyMaXxeR+MVmmgWfr9F/cIYGyH4bXni47X5QFsblS2kWp2jISU5ykqPk3dAsjpG5g1MlmxsRZBZVHhUmPUzND/3d4iecKw5Oy7uoMWuVVOuDhxHUFZxFDHc7OIuJg1NVwX4QPgrtg5K/EoHHa9FKjOMM5MRHASSNIknXISZU4+SaUmTHjg1rhS9b6nB+DMqYRkWi6hjs8/Pc3onjbBynWAIto6g4i2yyRfDtbdGOkgofb++ej7PYbDLOgrQWywz7kU1H7brzkmyH5C/oOhkHR4DykMQopkLlC87i9u6FcBbVtz82MHpK2twAemr6mcwQxfG4hK+QaF5EfZOwQwb+np8P76RSGZFUZ1Ocxfc/xfL6bpJxzSEWPxlHkB2rrtvBWUyytZ8j7+5kQQ4TiisbOjWENhICjOK1V+ckIEWJxiH/3Tl9osZHyjpF3UiKuqlhikpU3GxXey/1To0ZErct3GqZixaxBjguzndT1BUspCnq+kCPQcA1zGKbIqnoycaW9tNM2HWg5RLO+53ckLkZwputPIzGDJnnhqgZEm9uZPPjh/sdnMrrCONIHMapf2IMkwkk3w+f2tFx1NCpljkADueGLBrJON2aerBqejBnZ+ekX94hah+C5ItQZHFwqv8iRvCikazTJ3LtXgFl9zBD4pOnGH7sQ1SfpVqn3oEXkhuiZgiSGUIxZjMkND6hPMUMGS5l3/r71wUgqNfmHNxyIaHbm7s8ifAPfRntD51h8em2mOe1zw5OMmYIp9wQajuwNUO+OTVbnyXvzmRh8QiqEQCIGgrUsKgnIASptQnANcip6CE98EBBaFJTl9XUroKZnj8AQVChHMvkFG7v4HTFyW3VcIuF4BnSS+Iig87Ocjgwz9pVNbX9ASjrFADho/BpBe77rH3Eq/TgVhXize1uYeS7rVTOOj8r9r5GYExdEgBS57KugbaSyUj7oGMRSmFkGgUFyJb+zkQvcj0PAHG9kPCpd9PQXIzC79HvmZzrUjs0r8oPL0CbwpAFQEKoMeaICicPPhwV9rBFI5pBShrL9+xiAW8UOjmBk5d20wkm4zND2qZ+B11dH14iaor6wktIUk9TV/IimrohTAQfItoHDVziroAnxNrDx4jxQXopTcHuuEwp6rUURvZtgOsCQkpdb3QSnkn46mOpR2ImvHC5QPulGvV1mdTG8waVK+ntpTCyQ1h41NcLjOfq5GXEb7+Z3JC3JtY0OJhdaiMN+86R63IUOLWF0u47J6esRRr6TEbD6tCbk+a0ba7bYSUr2/1QUgf6ISeF5WiK9qd3pVZJ+p37QSYKnYy0+K+pS6LXRoCYRroiqrM0qas8U0Np0xawl2aihlCcl4DwP7SdmH5juW7uhwnRzr7xAFB4OLzbqcOR65OYuiGa3aqJaAJvTuHFrvS/AooDU0WLN3e9ODnNREabdlq7pO3gmGW/2EyIhBACqKPSh5SZihCw+HQrmA0AIJLs0LbPL5fN7MwOziqFj/tRsk77NMnvi3IBcDetnHdbMBXV0y3WjYe/Kqat64NUkk+ThTPkN27doLpup3VD7hENOTk4T3KSkxwl76Vm8aIyqcI1L4ijXBDPq2WhYJkJ7iMW+z5vm2bCahuaTs5ssiVjnBQHyv2x/bS/zzNitZCRLWJk+wCU80cGnPk8v97RIF5NASBC0bRoGIsjbdJeGod9xYZMXwo2oxT4oZyhOkPbhjI2EwoC5uwgzDKMxd9i2pXzBGB0E02PxsRIZbN/x/QcGJ4MLYeZz4MECNPzDKFoWJmu0BTzMWZFOU+CdCcODuqSaWYLLFmZPw/pvK4LU4a4IX3X7mTHu4MbY+qXMR33K9575b2ZLJ5bdGifHCI6fRnCWHX2WdFSBG9aLG2d7ZMB4lCq9j2pqp2BVgZdSiQFb96WKALU+lSSkKHJe62S2qGIxMGZ2nQoC4QdI8WgvEmxY3RPYU8TR/V95b2ZLCZia4HY+iBWNL2baBpqS5K5J3X10NofVQkPFuJZDZeliIsBV2EYhSBnQ4W7wZ7frry2rkci7NF98nbta+oPNVJPJJce6Ach4NG6JEBxcC6m0RDSXBMDlcYwlDHhWOqkaIr1elXg2mo713Wp5wEgXpwJByeXUC+AXAZg35Ser9V85tWirLTZwemSX6gknVEryNecDNfUKTksTKIh8XIlgCQrIUrfnZP2Npvy23olORpKOJQKI2MIiKtamLWAfJ3sKfNy8nIhmkHbo//SGk1QUBaBKwe36TE+FCe7M/kXcakkP+rgHOG6McO9F1e3pWaKkXi+kgS1K2TtIj48Q/vhAuu20FKGsxr+rsoOBnVAc+0xnlWgwMXBycj1VY6R93KysKFT/awhwiy5lF6qK2IlcnmpbHZjTwXR6MqqQc5wDHg/5WzYbiVXI3FS5Ni8FscxaqNlsqKun9TyyAxXSjSrtUgUCar9dRJRyXVJgDIhmbokAIQZe1HnMGFuV68lFf8BINVfIPkG+kLQmF7glC2rL/D4cIl6KNGTfH1Kf4c9ksZDPwOQKEWerNMEkuqTaGmBHH5sO/BaPsd1A4wRrh9zrgUA9I+WqOvpSk+BEWsHT4R43qB6UibTeLFCXNWobvS8C4TzBVwfEJbyYkknJFs0Nr7UDTmXSvDueoPtV2q4vkRDQu1Q1x7dl5Qpy5AKn6doSEWIFaG+8/DbCt0j2af5aJlrplgZHywwLj0WQ4RLTtzu8QK3X/Worwu/S/+gQtP47EnPdUMWhFATgAX6CzPBvkHC3pOY3Im3KvO6JMBhdfMF1dBXLdY8eu72NzS+e2ttHBivV12X4yhRk+hFJMPH0/f7WvUv1upJTnKSHzR5LzWLXEAIKEWE5kAgm3WaIc5FC1B4dy4OpJwUOQmKp59TW+QTw7NSxo0jaNtK/N4mW13f7OIsTBEgvttkqC13vZDr2n7bwkX9NN7Pmy2cUqwBGdBmixgBgrjFQu0AACAASURBVNYUoNRQWMXbdgJOyz12BASG++y6IAQVZ1FVufgPANQhCMt0iHAWMdoPcv59EaU0HgDydXuTdIaqmmS26vgqUpRDAD1NgLVbn3EW3jgcl22/F2fhE87C3dUF1g/AfXYNV3mBogNwlUfdCk6E1gvQJuEvQgRVHh4Fx0HbPhP1XH7ztrB7E6FOOIv1Ju17BM6i+TyZiVc3e3EW9ccNKu/hNoWvZPXH1/DdOZqPCuVk86SZ4CxskaHxconq8y2az8s9s5iL58l7OVkc5eBMqix5L3kBgEBoY3kBAJQHOxUQhgnF7XNwoq4muQe50I734rXXfetawqP2xamq4iPo++IkNQWHslmTXlDrkwEAJiefa1PrVFPDq6oU8IEgKqWGKwx/x2D6OnV8EjCpoTp3cGIszj3qBlA1c3ASAUO/GwY246GfgQTP1muoqxIRcWTSs6WvFEL22xx0cK4bQa1aUQcns2Slmv6iqWW8bpWevwGvpI5ruFjC62UEKTo0zbxtwIsabhgxXC7QtNrf5OAEEBIj1bMdnH7i4PTmvk4uY9mA6/T8pn7EdYP+YYXqqrBdhbNaarTucXD2D2u4IWBcz+r5Hinv52RhQ6iW9dqKxvXnyEpd6XXV1pdbk2zM/vsQnDSMgAtgrsq2LvFG2IdJYc/WwQlMUJt532EszF2qBaX+oO/zX/2d+x5oq5y0BoidjxjzZKhtEJL2o9eV8lVYx6wzEZXIgK2Botefcm90PJyjzNehTlCkdtggPSdjtwcGTptCSEyWjk/T1AEAg0RYxjET2NIw7sVZOOZSTS03zHK+hOCMEwTnVjAjmi+S2LxoDPCVK6t4jMDgBbOgiNMxgLsRNIxoPtvA3RYEJ3sH6obychmchdumCc85iab0IzCMqFPVMrbIXCPudiuLXT/kCcD1A5aVK+hRQJCg85yWNKZMgL+WEg55DMLxjov3crKwJQknZQrtGOuDZ+Pi9sWd8TvQejUp93codKpJZzmzchxl5dXVWh/+1WoHvDUpL2jyMgCUuh5Pnub+UAjSz7b0l/tBGI/OVoXXQHkjFs00OhETl0MIpt2Y1X0OsZRrbFuZSJX7EygAp7qaREPCowtZvZQTQtvTgkj7ckN0PIB83XyxLrVEEjepwr1z6HRRi+o/hsyAzYsmvcBjyRcBMD5cw991tlmh1a8caNOJ1mCyjfnyHLysS+nJ8xXiWjSLuKqnPBS1R6xcLnUYz5aAJ/iuR/vVcyz0OdPckLsO46MU+ToiN2S8kHFc3W7254Y8PJNozNNtvi/jl85w+6MrXJhFbTxvUN0WM8TmhgxnldQuOS9jFv/wxGdxkpOc5BXLu6VZ2OzM+U+pBob+Ldv3J5LxKOow931W7ZUxiyNPqqgDkBKEKZ15fu7Jd6Vu0+OUBTxxNyirFm+3O2aILS/IXZ+vl9suVwrLfVVzoEUpmZh+57aTMTKJZAyIZmSrqLet+CjGsaj1XcrgVJ6LvK/Q+rnr210zpKomZohnzvR71M3MEEsxaMdOxwPI100hlExUNSdS1imrg3PrwWMAt21me9dyhHMzpBrGvWaIJqxR2yOa8XHXt6BtXej6njr4dpFIfusJqxZVyWeR7q9PpLh8e4flR7e5wjuI4JIZUu+Be2e/y8wM8TdJc7zb7jVD/GepfOGmOJCrGHHOgH9yW/a7m5oh3pgh1aKGu2vhb4yD802UL3zjsgeFecwxRFQcnIA84C8Ts59jAOYw5TeJt5jDtg0NG4BCqMslJR8GbIZYiirZ8oRvTJwr15DIZbTfuS/OAS6W4k+vuz9AGSNtUynu7H025M1veNReGGLO9exZBe6F2Xh/Jot7iiSNBUwsLcsSNc+D0JfqmBth+AKkMcNzGIt2tJNv4X0hm51MMK5st/2x/bS/O5dJfyZCbqf/lFiec26IfTntY65Jb8pFCihptryo3k8iF6JpYNpeSMl0+yYdO8laf5Izn+cvo46NXkPWPpJfo6qm41JXu2Oi9PuJvGYy0VdVIvctbXHlQSOmORQu/eYIFHVyleM4+TNyVIZIIkch5pod9nUsdTxc9mkRAF7IducdmHcnRq68XJ83z1hdIS785B5w7UGj3xs6Ze+kHKaiXJnvBSz7wk4Wzy3L+KJZp4lqb0JXFkN52ex+rzPr1OJHNJN0ngUaEy1gNPSAmqEKocHbGac3mXVq2dO1xoiWPNAQd4zlGl531mmKhED/zTJgKVLBf3ifIlD8RrJOaSwUhfma7pt1qm2ZfJAvZNYpAMk8VUzFc3AW5L2AqVRjAOQlUaDRiyaSVVLAJmMFxlG8+8MoK40+0K89kWxZiGuSH4cak7OCtKIpO7b2FwY/wlyiLJutvDhvMpFsvSwaVfIJaFgwR0PqKtUFDa8/kWy9lIjJGBHPFnDXClZIiWREBVS3XoBrD7/t0L2JRLLLtTB1AS+cSDZc1FgQYTwzQLp7JJKdoiEnOclJjpJ3o4o6Peafon+roBSDIR5JYquqh5ubaeRE+TvNMbnSulZZB+AeXGZ1Nt5tpudPfBm5OrqqqMCkLXd+XlRmPbauMmGvSzVUn1vl3EZ1OJaydlq/I2lGO/1K7MyZcFhPvc9RpY46Zd6Gid7kOhfJVj5bg4dhyrhtz2PbSiURd6p0p3b28Y6Q92U80nW71bIcr2MTE4jKEM8AkEri19eTa50UZdJrmT/PhqmbvJ9C52fYGHdxkdum1WpKL6iFoVRz9IKYpfMz8NOrEumxz0x2JBt8j/XxuIR1Ueo/ALHrdscfgHtwkfulEZX4yWdCj9AWbEm+N/nAwldCX3oEvt1MnMX/+ye/jqvh46PUi3fKDHkmuc286NDzzpXtzCmiETHuPlD3EfVtmIpXrI5NR+UBe90y8wvsJa4JKfcjGsYs9ZXo8friDfuJYl+naDU46QYDTGUCsr6MN9ahWPpgfUIhAo6LT0Y6LM/Rm7rf6j/q+v0UAMdIFD8TWxP+HrGcd2qysPBlqqrpipoenti28JeXMgMDcIsF4rYV21sTs1K5AO46qWGaVgOrTVRf/VD23WwF0fjgUhK/Ejs2f/Sx+BFCLISuWg/1bF34F548BT1+CE7Iy5hsYve1H08xcTNZrRbgs6WwQj+5zvwMdLNB+PJDAID/f/9Ydv6hLwNXN8JrsWkLu/fTK7jHDyWvQuHI6ltYrxAvisbhPruWVWizBS5F43HXKSav7OPJDxC+85Fs/9d+Am4zRXDyogI3VXbYdV9eY/HJRmz7dfH9UJuKF1s8BZE4K7/0MPdXuTvisoK7SvdEqfWbSmz8XM9zLXDmz54Cf+FfkW6talBk4Z1oykrdPV6gvh0BQobeuyGCK0J1O2A4q7H4l0/y/sOHDxBWVd7G5yuM5w1cHwQteVsmgth4xFWF6kqeheFc+tv80cf45K//JC7/ZepvRYiNQ3M9YPMV2adqlRcDGM5kUg8LAjug2jLqTcTmA7mOL/3BNVw/in/ELAj9h+cYVx6r794Bt+JjufvX/1V8/rUKj//5mJ3G3aXH4ipI5IYZYZHaawhgYHEV0D1IURoGwu8UFPHz5N2aLJ4lRqW3ptNBTk3dPufK1I+26nl08oCPY+YnZD3WmhIcE3CrELxwCFLHc7YCUtvLOa33ffDANq0MYygAohDgUo3LTH4zJEehFle2QJ0xgNDvsnD3QyauAcoqxDbb1QKuuFDu58I1m37KuK3hvVC0kfp2EDDRGCZmAHX9JBrBXDQbGd/0m5ZWiLGMgbY/JibxpOU434G6ARxCcV5GiaiI57+Mb3Pj4DcjmIpjz2nNju0ATyjPCTO8ZoVqvzadMIQPAa73OesUAPxQSfZp2qYvDvcDlk8jqru0UHmH2Dj4uwHNtbyUvkt9YIZLuTRhkSaznlG1ActKv8u1U8r1kQMJ1U0PGirQpstj1lyPWH3qUd+NRUFgoL4ZS4J1Jx987UCRUd8MANepP7hXbsjJwXmSk5zkKHl/NAsr++L4e/bhyBKn3+cLsdmqLmYcAM1i6/uyWREi2Jf9eJ8fJJZzqlCqwg5dNcwqtxcfEHm6jz33iB08BMZxmgWqGkmI5fwWcBXiLrR4DGUMNB1a8QXqBxoEg0Bheg2T77kPCu0uY6Tnn+BQNDytnxVnofR95t5QCECU/tEEYxCBMQqYVYdrjKKFxCi/5zFk0BhF89B+jQEYQtLcjMYBMWtooLJNMRQc4buYTTQKAnSiMWaNInNGMOCdfhZQlusjXB/hezPm83HyUk3MOSrs4wBcH1G1DBpivl7fkSTAJXeEGmkUkU0336kZwgWHcYS8n5MFDnn/pwQyR4kjTKDkFkGo3Ap52z0VMVXh98Frd1iiU1q2aUOyXBMkWjM2LSz6dcl8DOaoyoRSZMOtAEDsZGf6qj4LxMl5XpqpW9GnOhbzidq5nG3pmIEx7evN2DGDiQTBeA/I8/7+lHMwQdrR7Si/aZtAGiuWOWMyHjpOtobrgfvNJMdDr0Pbz22acXnJSwTe18nCsmgnKDCcmxZ5dU6co/oXKF5gGGDSmEJ2lReHkgH5yI57YNhVVcK8mh8wg1lznWxc7RsgACZN6W77nF5NYyJXsZDqyk+PnYTcHOBdXlWZ0qpU19OU8USSgxALeMrWFKVYUtR1jBaV0arSg1tXAk9WJWBZgdpRwnSGIJeYpULYLCGQiOR6bH3adG/UN5H7XVdis+s4LBtJ1SeSvgHCNsUMDGHSflhVuV19ASMA1MJyFRsPpz4hduCFR1wUyDgvaklNH5wAoGwkrREnLycNIq5S+Urv0Z97NE+VAYswLj2orzGuFcJNqa4p8rawVAesLEh9IvJd1em+E5W3kwhxVSMsK/hFnccxrCv0FySlD5OGMJ57KWWgEfpE2MsVgQKDQukXcL+J+72cLPIEAeQ8jck22Wn6dy4594LKdx8ntTtlorD5JMq+5fKkQmmVndTlyOebTjTsXckXMOcQ5KIHvFkAdIXW3IVJ8hpN+CXyL5Wf8DuQ5kOkWqW53dQ/SsdM+tgYVmuNhlTSb90eFx6oHMDTPAOMXibmMFsRQ5B2FJmY2oxNVbIitRSAviyqgtdersNMTLGRl8Pp5zQ5haUDBRlEfQmcExPCjVH21fuU7kWs3QTlGBcVHBFi48WJa8YlLHyGZcc0cfmqwrgihIXmfEg0hCuHcZWciySRCTAwrqT9sCAwESrHoAiMafLgysn4OYBYtRCHuPAIS1/GA0BYOAxnhNC4HA0Zlw6uk+PByNGQWJOYIaPHuDZO8C9EKQByIBcP/75PNbOVs/dFQ6xY29r5XT9IqmLNMZS2FPdvanwyp9qY+3wWcbrCInnwM6OWqe+ZsQ92glEtwE4UiSTG1h7NORsaSVDRfAhl+LL7ps8085XQECZ+CPFZTL3mboxSQ8Miq22ui2oJ2pcZYC6fpzesWnbiM9dWch1C7gOFKJ9Z/qnd7QaGG2KaAFSbJPEZaPs6OY7lfFkDGgJcl2qParQlDwwJB2fa5ro0nuMI30u7MgwkL2aI8K32K+bIQ345iQCOcEF8Cb434+OSxqr9qxxcF2TS0fGA+Cx8h1RRXnb1nfSFPU3uGUWCGxh+G1BVJoJ1ioac5CQnedXy7moWc8nQ6CCrq3rxq0pWXrsNEBisVgvLK5zBZ2ixn7TixPO14CXWAn7Kq3lVStzDe1BTg85WBVDVtuAH56A2AY4S9DY+WMOpbyWdK56vEC4bMBGaEBDP5Rzu6R36xysQM5rvSlPxYgnf9QK+GoOQzQLA7R140SCuF5niTbWGeHGG8WEB2dQhgJcLOEcIjy7kEhTJmcyYmKjq6DMBJnVfXqO+TYQ0g/Q9LCUVWjELd19d4OwjMSOUDg6RUW1GVFa78S5HfsKDlVDxARgvU1GfpUedHJHqA4gLD9cVTMX4cImq9qC2Q/9Y7tl4Jquu7yLGVeG+uPuwwuLKZ6cfINoGuxrN1Yj+QYX6iaZse3RfWqK/9Gg+a3K/usc1qm3EuHJYmIJEYeUxnHksP5VXpnssv108WePqzzi4MYHmKmBYE1aNw+2PSFvVRtHEQPcgmSErcUZWG6C+ddj8kGw/+94Crg1iStUlHX7zw0sMZw6XgVFdyXlvfrTG1U8GVNsqaxb9Q8Liicu26ahsigspy7h84tE+LjpC+L0vghkyFwuOGkzeRiaVNfkazgm0m2P+Oz8H3aVMw3EEvBfC1XGa86FO0zxxxMQvebctL2g/wF3dFiLY1Ia72gjgKRSnqbvdlhBb20vmJkStrq9aCXlprsatsGEpGXAGVXkhbfVdDyjblxLpRpZKYXqNtxsBNLVdflE5oSiV+Ur7EJJqu/hkU2x1zdhsR6Aqqv3ZR4DbjnCbIb+oNEahte+M4zan2TP81TaDiZS+v7pmUCK6pY28fF4dnGk86yGA7rbgbYvmidwzv63FFIkM11XZDKGRUd2NiI1HWCZ/QRfht6OYAhHZBUXDiMVnLWhsQG1qqx/htwuh5q89nOHzrJoKTVPB3bapD8pstcHlH0WsP0qLRO0wnnksnvRwo0xCbhBzyY2M5edyf8eVyyZA1TLqbRqTmx40CheGjhfXHmff2SIsK9Sf3mYk7MWfXGBc1Vh/XBCcyyuH+noU3tHIiHVaqGqC6xn1zYjl5+W1990XIXSaEpL2sVpNWLtDKBwAumqmpKFnn95gFJIfAiHkhzRqTYsQS4p6DBlfP+GZ2MPhkHkRbNycCKiMja7+iX4AdUGiMco0PSTIsxdauZzKPY752AlHhQzMpB8cotD1s8GBaEJZwHR7LC995mxIFcwlCcxnH0VsKpkohhGuLTky1I1TnMY4lsjV2BQ/hNY2MTkgGVPgFL/B5f7oPuov8OpHCYIjSNfgGw/XB5lEkjNVsRTUj/BbB2pNLZChQbUt95zrSia9MYV6DVSfxgiuYt6WyXwjC9YhfXfM4pPug0wSAHynzw/D9WlSSBEsNzB8GwWODeQ6IhiLn4nGiEgJP2HGw/UR1YZRbcMkSuqHCA7qx1CNHCkaEovv5/h5Qvp8v93foDzDwSmrovHqe6GHy4Qp+7AB83Mov0MI8kIuasnw1JqgyeRgLhmBcL7U8khOPPK+1DpFuWe8TDUxDBaBmxpxqauNqRUSGXGd8h00JJtChpliTqMcqT32rjgndeKsqwm7t2tq4d4YqxyazJyZWjRIz6uhxnVjNCnpO9fTEOl4UQt0uXUIZ2m8QoSbUdWTRnGcm/SLV03CBhC8rp6ak1NLFKmETmt5abzPeShhKdoEBT+pSTpcVGAnDsaYVHjfR7ghwrUO40WduS4xjAjrGv1ljepJaTucldwQbyfeRS3RkDRh6XXXTY32oUNzVYoHDWfu/2fvXUIt27LssDHXWvtzzrn3xo3Pey/zZZYqK6sqJUrVqIZwdYwpI6lhIyjUkS0M/iBcbki444ZlNyw3LFDDHwyCgjIWchkkWbjjwggEtjGyG1IiZIOryhhn/TLfe5nvExH3cz77sz5uzDnXWvvcGxE34r2XxEvfBcE5se8+e6+9ztlrzzXmmGPAhITpTOnelElRmiL1K9kWEtxgMD7g/m7WLUv1O5P5GtyvBn7l4K6a/L3PZxbDE8LqeVmGaLYlOgKFQiuPDcH4xOreldfpvZ7Ffbtv9+0Lb29vZPEaLWn67E1Lz6N8vqJXZzexhRzcHWjmy44Jnbz8n4TFR6GStIux9F8rb3VppGG8RgCf5zrv2ucXva+WLOSj0K1LOJ5Tmb5gFUAqadU6nV3rPbxu3zIdOpUUKvhUlBIoAIYKjlG2Vw5xwnswId2k9L9mo1RC+pQSHzNV/YzIT37dT3l0JqDsr9cUI68WKzzo9vFAjlhKSCvLmSDXnKmdn+sSAbzNk8XLMIu6BkG5Bsc30Kt4FnX1pUmi31hVnVbajzXvIIXA++nSQnCOG1Wno+hDVNoXZDwwmlx1mrMsPjAjsu6rcg2E25EzDIkxBfUwzdvAOMfCCmCas7hLXpcfV53qcRUXGMoxKMRc6gxfsg5u7wXM9JzxkbGhYV6CxIpZCBaTz6W1CSYs+RUAENyi6pSGOY8FiUWgBVir4wizaHaGwUxTyfPVmAVRwWN8gBk8rKVqbBOs4ToMmm0GPnksEhBd3qYgbZpmdFcRdq9VsgQKFnY/o5VslZm0PiVlgNVOJVtjxohOuA80zoJNpEVWye6YrJXHA0BzHdA9s3DbkCch4xPcLkBrQzJuIgxOt50zJfx1q07fjslCufX1zWItED3MmvUFw/V1+Vu9ltSn9zxnVy826B25gGz2txaSLfQrk9jxKYAJgFZ90X6sWJHJi9VgdfOl3b74j+i5ahtAvcwgaUXi85F+xgfWgYip0K9DyYxQRW/Pik21HaCOh/cLyjv7hkycOlbwV1WV9CauS/UB7keODCKfe5wXk7bzIZej5xJ3LYZT4BLg/teTld6oOqENYymzr2noVYEbzTPSOCFNE/cNQBokAxLjQoOzPcwlU5YVyUoERLthUThlhikL5gJgO8PDWK67Lh+wFtbZUr4vTmpxGLD54AD7THxDrOFU72FCP+rEXCIr1xamKkePCWbysPNarleK9KiSDyCC3Q8wjQNd7/KYtZ/scJ4Smqf7PAmlzsIM5XeX1JHMmKwT4i6LBslPhDEy1V84sJxIjFnIhSWtMzBKpQ5ccanKR3W2QJv+aJSWnRjM06xDAoC+Wz4pFRRUJifA2RhfMRFztqEUhS08L0Sur95GbQNl9BWDZGKB2WlmMFWzJGLCnKb5hgJ4Apb1QqomHkKZWOowPFYmQ5VT/KLpJB5SAXXFNpBCrJ7gZaLIHJZh4shEx7u2QQB4EshepxIhqmFT9V0l70uUp+fS4+ikJ32nEJG6JhtE08yO7/qbUcFcmmY+Xks5tZ22uxxx6aScmzWAt2V8qpQ9jUXdO4n1APkATFXUpku2nMFqmM0rk4dR/1HpZ2oqVnHjgKcXoNktx2yaYSprRAA8UUxztiNQ6wIi4pRrrTlylD17VbsHOO/bfbtvd2pvbWTxUiHhiruQVJCWYokg7gJY1fuqYG5MSFSFZbOXpckboEMVhyHVQrXypE1iUAygKE7VNS1E/LQVHkiqMJpby/O/qJaONDi0PqSqEM0Vr96X5UlM/CS2ttj+hQAK4HDeHtXfvEmZ+i1PQZI+8zElyph9WW6osHAMC5BVbQRU8evzNKr1NxIVrKrWBdF+1qCl1p9MMyhIRKlLoljV87ykvonxleo3aqgsCevPfQG/mbd2svixtuwoVi19PidCfmszdPuNXrtyLfpV+CI3qlq/rEZUOA46UdyyD4BSGas9k/9rxScFlGuodTg+r57FC74jBmPpaJ/q/y/S5vgimy6f6+PeUkiXqnGu9SjyvkSv7lt9DT+GNcIrJwsi+lsA/hyAT1JKvyjbHgH47wB8C8AfAvgLKaXnxL/o/xLAvwxgD+DfTCn9s1f24sZiG/yUj+l2Ne96rVUP6DHi/7IW9amv6TSbcQsADCIaKk+m120KvALliwyB7QON4BNRMwlRbAPDoio0q22FKmqqVbq+hJbqalkACbFEPTVZSxWwq2wIGxoXLQrMswCc/FTPKWjgzW7SHF0dYVk5lSpgJlEZx8zQ5RuQ6gyUE1exu/xeXtovLLNvR4ziXBlb91XHkCS1PJeMVo4kFRBO6XbjpiAKWfW5iEvRk+GUanpdmuZL2l0ii78N4G8C+M1q218F8D+nlP4GEf1V+f+/D+BfAvDz8u+XAfy6vH7+VpV51yEtWYsEDnMX4bOqg8srt+omEwcw/fHQyYZ/3KrafXnFPzprkYLsYwjUdaC+ywzQeL2FOT1BvBbVbFUCPzsVunh1k3VtYYhu9wXMPHAxGlICPhWl6XXPgJSznD1w0q/tlh3JmoazHTomADt9rSq15qtr3m+ass9IEvctfYLVTmcAgMfnBUwVwd7kWBcj60Y8WMFeHgBfXU9KHE4rcAjkbAilhHS6KenbjhmcWPcwUqNT9Cw4dZpD8HUPsx/4fnx4xmPeNRym+4jYuqLlcNrBDizYm4WPVbB38Ei9g7nYyXdpEB5sEFeu1NNsVkhrrg1JzVKwF40onO+kYFALDj+K2P7cGVYfCSPYGVYGvx4xPeTvws4xTyhhLYK9Ikpj5gg3BAyPeRxPvhcy3TzbO1iD+PAUsXdwn17BSCZm+qmHuPrpHqffb8oYrBzcds6/OWWyxoZL1N12gj+p2LRPS7Hcq9orJ4uU0j8iom8dbf5VAL8i7/8bAP8reLL4VQC/mfiu/cdEdE5EX08p/fDOPbpLO06d8ptFqK5Pllw/cdwy3yAwgj9NN/CAVEcHus17YDIlMvF+gVDniWkYkVSZW7MimPKXmmquRoyciqueIKo9CS/Rj/ZXU6fzXCKpepKsOzvNSEmK3/RcOhHUGR3uBG/fD0u0XLGTylLPEjGPZOFzKrwAX0UbavCT0jJ1StKf2Rebhaxf4UuGSa4njSN/N3KTGFmPU4j8XppLiTEIY3LKMNe6BOam1PqiZpDvQ/sl2RSNOhaZoXHmFHqtfC7j2T2dYbdS1GcMTGdhtiNaqiYsiSrsKA8ZEfChlEBjQKeT21i4OXWGxcweZnCgw5jHzF2OWH3q4K7LpJYrduVhkFOn1nDdzGFapEtfSPi6pb3pSue9agL4EYD35P03APyg2u8D2Xbf7tt9+4q3zw1wppQS0esvjIjo1wD8GgD0WN++zwuAMKqWHGTZYHZBHRYeA1efmhvsSgClkEwcsKhtOdrIS4MDm+laA9I1suEiMmqb/HmaJlDXgqaSAQAA9MKRqN3LWtHINLKuVC4AONxGSoCWzrdchg1rRBtUvqp5zoVrOQp50TJknks/1c6xXttWyxCNftJmtViG5LGtyE/+rGem4zRzUZged5Ql06LMX7I/XcsRBVC0OZqyhLi5DBHuw7qX6GLKGiJRiseSj0h90QwNJy3MwTP3I4OsMZfPx76BrSKLsOOxVgAAIABJREFUuG4RVg2abWUUvFiGVM9SXYaoVqkuQ663GJ607FAOfoKHzqIhwvRI9EqEwYlYNDhjq5FPkmUI96F53gI+irhwAZJj63gZUumTTuc99u852LGvZPUsmsZyGBDLeWJjuEp1a5fLEHf3eOFNI4uPiejrACCvn8j2DwH8VLXfN2XbjZZS+o2U0p9KKf2pBt0bduMLaLch10SS5vwcEPOL0OwXTIBZak8zMguk+5YsyY+zvSh7UWc6Xva5er8vKAuRXpEBSISSYdDzHV/Hbf16k3b8UcIrj5e074SsMp6ouq6qX+lFx6pxXt2Pyv+/6AzJm0YWvwXg3wDwN+T1f6i2/xUi+ntgYPPyznhFnabTGgwgg3gZsLSEFELJkihSHyOCmBMDgD3Z5Cdn9puwTVmn67kU3DrZiBcH/z1eX+dooV5XU9/xU1qBvXFCOlmzUlalBM45fFG6zlTtNjP2KFWMRu8BK2DqxSX3f9UzyLpZI+32mcoetzvYtkU6Py0sUF0/V/aIAGBDEJtDi3S6zteQGbAx5qe12e2RUmJLwaqYjv9oiq0ggNhbuCuOyPIP2Vqu9agp3HVb92WsJYqID9YwiqV0rC2aGi4DVwGeuOm49N37SrBXlNNTkjQtH2PeODRHtQ6JCHHTwF4lRGfgtpUh9tmKsQ+JpMKTM/jTjm0Re4fmqtwesbWInYWT70wVz7rtKaYTg06UxaNlwV7TWUxSCu4O5a7O9oUtIVlCs4v5/wAW1o3aCMD03iP4lYXxJ9nKct44jA8Jmx+V3910yureOlFGKVEPDSG0Fv1zk+0LAS5lv2u7S+r074LBzCdE9AGAvwaeJP4+Ef0lAH8E4C/I7v8AnDb9Hjh1+m/duSfH7WUVniFkIJHkPdVGtkCZbF5AaNEaiZxm1XqPmvhzvHwR4dg0zVXhUwANE2KIAEoKi3YHAebK8QgsjsLnHwrYOU4wV/wjDgqcHgbu2zDmVwCcUh5GVpZS9Sw9p2Y49AbWfnqfwcE0z6gdyzO9XVS5zeW+shSUvs+eVbhlPBpnOJsTU9aj0P1qsLduRscDZdlkiLIYjWaNSHxANBtiYuIJOaY8RjQ23PfZL+p2+oTi06otxpzZMFOb+wAA5uoAM/isHma2HVwEC/bOsRwrJdBkYfcmZ0MoG2JHbD6a0IiKVzKGBXarftgx5Ju3uZZJpTFIBrBDgB0D7FBlyW4hiTUXA+zesXqX/L3/bMBpt0L32aGca2jZo/UoG5Iag3nt0F5MsGMZM+PvjiDcJRvyF1/wpz99y74JwF++89nv2327b1+Z9tVkcFbGQbWZ0I196KafSE4ZKmCoKbqKl1Ef4/iYqsyVAT9rGahT74mq+IdCKAZAwMIEiA2AivFPNtlRYE6Ni9TtXPtliPeXQi6gWlo0rgC0elwt+FJdTOcKDqJ+HgBABkSJP19TpcFgq5r/AGAjnj0DsKpwBchiwLmFpWC59mq7gpmdK9GbFNNl3wxpqXNMtLImA8Kxbxn0NZSXdQDgNw3ccSQZEuAMczJWDUwNhLcNYu+4mhRA7BziysFYFinOVgApIbWOlzGVyVAyBHNtMZ+6DJImw54jLiX4TVHPyn1c6VKKma7JcZpX1au6trnVPCz2rNRlDy5Hjn7dYDwzWK0KQOvXFhSajFeEzLMw8BsDO7qilJUq7OQO7as5WdyhFaeyJaqsDL/PceAbaH8B7T4nKPqmbUG7rrdT+duiz9W2GlhNn2Nc3qQdAZ4F5MUSCP28AOTr9Ef74ihLzlEoQ1ODjem2h9SX1JJAM4mIJffeoEVbAFAAN4HZV7Sv5mRxnL043vaiVgF3RsFB/Zza67llCvbW80qEoS3Vfql6Dk0B1p+vHMPY+q9oOMTm6KsQlzMSOf1FSbs14mBWAZxEC8cz7m51k1VOZPlaTHHjgiiFxdZlolPue+OKUxiA2FnYxiGZuDgfgit9O2q1g1rKaVJbMBMlDzVWVM7L9hy1yblSZ4Fg8hM/n763MPNyHClERGdAE7uN2SpyDK1bbFP2JT9xy0SQKOW/mUEig8byZJIS5jWxSxuAaA0DnJMtNoHV70jdwGJDiBbQEEDdy9C4Bc6lLbYWoTNsnSBl6aE3mE/EvrA6vvG2AJxtAVRjA4TOwPcVEP8TaV9YC/gumIfp5jZtx7O+gHR17UAGB3246dB1fMyUeFK4Rc07V66qzoYyERcK0ZWnRijvF45hurO6nKn8XqjB21jqM476t3A8AzhisIVxCtFbuNGEm2Amv+gjgOI9qqDjyIIxygPJ1zeL7sRtvJaFy5gK21SVkWrZd8QoJJW9s0UsV5XQ1dckX8IQslNYbiHBhpTdxmrw1Uye79WsqcFuXsZH+FrIVmo7zBQK09RHWSZaNPuU9SjIRFBklXG3523qpg5UWQpZhrhDhB1CyZhU41Q3M0eevWPME6sdIpotu4xpc474//ocUSVvb+B7Ky5m1Xf2E+miXsvsxViyIfKejm7epMVm8ZaJBVjSvSFZES0e03Y8IcQIxIDkwRJ5AKPyXrMzy/J2FsWpjjHzE07Pp8QjVLJ3NY0cUgaeX/XvWXmqyMHxzeS5mjEXw4kKVD0ZSVEXiJhmXpdBx8QZliy1VxW1VZOAOZQakMVzSaQJb8tA0VxuVL1uqicmgG98nXx0QtHMSAg5S2N03Ge/+H7dzmVzotwkG4Jp5jRtfSNOM1uCZgWvmWXx5sDYwKjktIQURDu1ktVTMZvm2ufzJmN4wjnMcDvxQ62yIdkv9igbkit1K1p83ezgQcGw8rcMkdvP6K4cbHXNyRL/X6nmVTYk9IZtAxa/8RunemG7F7+5b/ftvt2pfXUii7pZW57s+v4otF4AnNpqzEKzBhpW9h3PxnU2wZYnf/1/apuy3zBwVabuG0u1JFXHBwCsekSRnDPTXCwQQ8jbczak74DDwDJ6IfArAOz3oK5F6ruK6yHX1TZIm0L3pklEZzAXavnBZlIWxZIl0ZLzeLqGscKH0KijbzNZCmBLwUa0IlNfkHgaZtB89GSXlsdD3gNCuNJISklZjp26sq3kumWuxT5lu8e4bnmfsVwXAIyPezTt0e9AMAtHhHDSobkobOFwsuKq0yveFtYtk7LGwE7oqpcJIWW1Fk1V4ZoswT5P2L/XwM7SN8EsmsZgeIeP6w7l8a2kLMUsmr2DO0SM55IN+dGqiAdVbT5tEXqDfo454hkfddi+b9Fel+98OrNoW3MrZuFXBHvWYFJSVgLSF0nKeivbi0hZVcukrNrdqrFluxKadCIYRiZl1SH0baQssTBckLLGGbGqIgUA2g+3k7K0f+NYbp5xyqXamZSlZCwlOSmrLyakcWIyk1adSoaHhqMvfpY+eZ9/gMkHwBTNB1L9SfmIub5JyiJ1eJPxcI1l+8eYlsuIl5GydDxQgFNjTBHvFUMjEnxlQcqS6lm1DlRlKJo9UoVRdLidlGWElOV8XJKytgeYqckEPbMdMykLQFnSpASaLeyectm6S4kn0BCx/niGu5DS9YqU1cvEXy9DdGlyvAwxk5CydofbSVlXI+zB8vXJ99I9G3GyMmifFeaymV5MyppOG7QX0wIE/kJJWT/WlunSETfARTIAAvMPvM9sTX3Pr7fgExXukDkGKWVdh/zDvt7yvqP6h5YvrH5PyuLUkvQQgcMBmGckYzjqABCvrjMNPR9nmoqB8jQXWvRc/FjzZHa9ZVXubElQ/p4Oh8zAzMc2PClgGHN0kgIDcozHFPo8WcOTQ0xI6lOiWYKnFzfYr0RUxIoB0DAiKbW+juiEhn+bLECUvwNloiZflNc165OPqefap4ynpOeX8ndTxr4CWO12X3Q58sCIo9w0M+9kX9iOFLhAL+1Y48I4CzvwBE/TnFmvSIn7F2Luu9k1mS+y+r3P8nGNjFWaZrQSsSywL822Zao//0asZogur24dP+ts8auVY7gPnuLscg26KMr3tmv5wSLHV8sCGIJ9dAZ7uYOrMm/Z1/YO7e2aLGJ1UypJSn/4XjxIhwH27CzXhlDfIR4GmK6rbmBR4PZefDol1bTd5eO7r3NVfRoGfqKdnvCTUe0Ff/gJaL1mQFP9MfuOn9brVVmGPL/kug31SJVzmJ/9Fj/9Q1HfSn2bqxXN5S5XX9L2gPDkASgl2D+SUpp3HrH0fdciHYZcD0CXV6AHZ5yKPCwp67Qu7u4A+EfUNsD+AKhbek368nItAMJHP+IP/eLP5Sdq1mzoJHUq4Nz0aIX2GZs8q6UgUgINvlgaAOUmiRHp4Vnpr/QxNTZTuHU5kWtDJLqJJz3MdkB6fon47fd5W890bzN5xK78hKfzFs2OQWrNCBm5Brv38JsG7YcXub/hySn8ukH3g+d83FWLcNIV+8K6GlXTrNc8SfoT/j6aP/gYn/3Zn8HpD8QawBJCb9Fezhje4bGxY+TQLQFeliFeajbslOAOCcMjngAe/s4pg5iWcmYoEWF6uIJfW/Q/3OYIa/tL38DFzzk8/H/Pcz/njUVzHaC+IXVtiAlAc9VjPqvSxz+6u/jNPcB53+7bfbtTe7sii7odGyPrEiWFBZ8BlslLNZDJZCaLRCa/cqvWghqKTVZow0KzzbRrMVtOlR6FsYBNmUat50+Nq8hOEiILlZmo4gK0DaJQc2nvSgVqwzRjJMBpJKWaFU6IS9Xxk9K6Nb1I5TP5SQ/Abi0fZ/ZF/k7BM8t0+Ew/VwrxqsnpNNIIrXWIrc2Rht9Y2EOTadF88gQLsAFQveY2BARC7JpM9orymdg6LgoDsmF06ixoDPkpFtctYwi2eH74lVRWylNc1VS0yhNUyEZmFrBPtCTapvQ3rBz82qLTKti+gV87WGsQOrPgfMSO96VZ+iDyeE3bYDwn9M8UiyD4nmC8w3jGV+EGAlsoAtOJjHPPbEo7JESXMD6gfB4DMGFOf/8GmE8c/Magfd5kTGU6NRgeJ0w/shl0ms4ILMAp59HIooXYKDoMYsJMCUiv4SD59k4Wd22R17THmK6ut18oo15vr8VUXyTDlz8XM0mHD8M+pem4SjZWhJda+i9U244FXSsMgo77XUvnxbQU1q3xmZrUpNaLyjlZ7JuW26tj53NHAND9St/ZMzQurxEAQnohyYcq+wZSzkJtHJTFeE0Rs0VFytI+A9nfk/+VsTLifcrGRrpvAgh53/r6yS89cimyT2n9Wo+L8WWbCfVxyjgYD5hAeX/ept8TYDyVbST7+7TYBxEAle8hRYIJ1fnlN2oC2yBm4V4A5Hm5oUK9mjRMphzDzjW2d+vXdWv76kwW9c14W/n68Y80Rt5PX49bdoaKHMV48eh4mUNTijnFWNzA0lIBvPIdzd4RtT/IJI5kIQJVoRIj/ChRiBKFQrx5U6dUvClQYRY+ZM0JHQPyAnBmUlZVOOd9jgKi3nBTKAVUkqHALE962ceOPEFSCKAg6WQ1HdbP5D4og7DoXyYfQaYiXAFljGQsMstznDMzVK8tWbkZ54hkis+nO0TYMSJZyjoNZpa+zgFmqh6jic2dzVRNTJOHGZl9iWQX4F/WqpmUxVrS6s0+wQ5ybY44yzEGuIOV8VL7QuRUEEXtn+AWIrNhfFyUvwMAGQN74IwKTeU7c4cItzOwU8pGy41NsIfIHU7IjmQm8KRkDwFNU0Xhr0HK+upMFvUyhGrk3NxA67O4C1WvABbLkKpWggyH9pRSsegjEnn+UniWMzG24lWo7FxWhdJUlS5DikkvGpcBOWrKMgQ+FNDOav2DA02OlyGLZY8patvKMMy1DRaxqpWwxtz4fK6qNYa3C7Ku1xham6s+tZo1NVZqJoRjsLIwo4MF8jKEgixDXEV5146kZc1Jks8kQ1mPInMaWslYZf5Fw+lRa/LYhV6WISawWrbsO68NJ9IcITaaOSCWroMsQ3Tp5yNiZ+FPSo0Og5isSM71HZX4Tee49kS0ILQWBM5hOiWEVeFPzGsDO9jMqUg2SfQITApwKq1mBpLlGg8AXFkKTnlmYSBnEFYWYcXcD/3O5rXB9IBfdcKc1wTjTZ5QdRkSG+IoZraY13UxHO7cvjqTxXF7WU3Ii+ofbmsxIdWp2pfwLF7qkvaSlpcsy4Mt3yd5+uSQG/JksUfLnjfrwxu346USUBzBX7SsOl7ypLRcVuX3r1n2qJ9K0ocEXgak5d94ySQbYnnlEH7ZJwplGfOmI8vLG/lPqp7WedvNI+dlQ1w+3fO41sujFzidk+AgvBQ7+qN+9gv8udxnQ+7bfbtvd2pfzcjCOUA1OJ3jsNe5TKgCAGrFXEdeASxWIUl5CxIah9MeZj/lbIIBeImSKi8PY5C6DmndF3Xn3R7xdAXayaJTyErhQQ8LMFYgS5SwabPicz/M8KeSq58DpvMWSMg65/GkZSm6rhUVbSH4XAKpaxFOu/LlqSjN2Sob2/A5+HpMSvDnfGRX62DOHvFMHM8lEhsfdWivtXJW+Ckrh9AbGAHGdu85kE+wLQu/8IACzc6gPRQ/E0b0GZ/xp10WpgmiLj1vHHoZXL/h5V/oLVdhCtNxfNyjAxOupnP+3HRqYUKCO0Reekjbfd0idCIqo6vMKSFaQn9hMJxb9B9LxBkMhkcti8f8kM89PeoxPHJwQ4TvDfqmEq1ZG0wbg7VUow6PuH/tRz2uv5Xg9roUBOYNIVqH7Td532ZX6NXTAz0eu4Y1W0JzTdi/zwNx/nst3M7zMkJ1K4iw+1qD6YRgDz06WZ5s3zfw39lj/3SdI4jhMSt8K2bh5QcVOgCJsPqMcHgiy+oExKq64VXtqzlZxLq0WUC1Y4qxViQeVSZqy+5YQtM2h5nBtGNGYqqMguU8VJn2sL7ltKwKBWD2XJlJvlQUmtGjuZ4ZqBp9qRacPZqd55BZAFIzMIBJ08wgacVMpGmG3VVpUF/oyU2tZzFMrHM5zrA7IZYplVvMdHK1pFxjs/Wwe7mWKrNCwXKZNIDu0sLtPMxUVUumBHvwpXRdxosSVwnbwRdw8MCvTUiZnq0TiZkdzFiqOJuWKc5pmnmMcn8Sk52qEDx0hPY63pgskgHcLqCzYMKT9Le59gC53C+3ndFaghsCzGjZ2UuamS3MXLa1KowzzVh9QugvBSh2BDMB3WXE/JT3cQdkgNPM8uBYsaK3OyQ0OyC2uq+HmQOSJxglZVlC/zzATgbN9ZzHrH+WsPtwhe6iWuYlg/4i8vWnIhYcOoAC0F+kxXqLXsO58as5WSwUlgTErBWr7qJepKBlBkMFiNTZXOTraJ4zGErGvN66Vo+5UIOSv9Xbnc3pPgUgI5HwN8xyX1OJ3nwZjVDKqQ0qVa2qzsBwYRXFlIFECoCR7yAXd1U8ELYUVMDvzfqf5QOER5EsK1plMNRwVBEdcr8AzgIkwzdyUmDSc9YkNPS51a6SLWPG5xH+QrUNiXIaN28D9yk0qfzfGpBNDNLm49+O7SQDJJcQXTGETob7ktSbRvMCVNLJb9re3snCEBDN7WlPlLCZrBGPBJu33WYqdNzyE9EYvllFWTrb3pHhUF2zH8DdQVOAw0DLak5aD5BsmdCSM7kPqXWMfs+x1GhY4vPrZKYTlrOIr9OP12ypyt5QAqL0U29O/gPJssTkCcRQyuY+ucJVDJySpI9TNRG/iYKfUrh1Yo2S9VAwMxm5WRvCvKomi8BKV6GlnFEx4BR2bLBU+3qDFi2qmxJ8zCq60ac8S/RLdsLxBBsb3V/2dYQUiLMiqn3R3d6/REBqeMKmEljwhGkBg9KHLwKdvAc479t9u293am9vZAG8MKpAjSNk0lIo2+6QXszravWriFGk7vQxxf9X9mLeVxl0uUhKCFNHuAiFlCsKoZ7GvlCma5ISE4bYZi9XW6qhr0mF3AVwOXoI8gg9SlGGuEyz6eeOU5z6t5qxKsdSWTkAgI8wKSGCg5sUlEjEeAH5CDvp9STpfyxjGAIQqVgIqqN5iFznRFSuIXM7Ir+PZV8l1mlRmJlNIWU5yulROyXYafk92DHBzLyvHU3GXcjHvC3L9ZGQuHyS1wqzsaZco4yTjpsbkFmRlJjebacIM5ncL0ocSWj/4kCgyEskNwBBinjNHEFzhKGCWYAI1BpmcPry27Nzgt0Z2LHgNtEyQ1NTsrbClMhDxqIAnK+TWn17J4uXLSVi4rJugP1DQ+CQdy5gHR1J67+osWbkBGDDx1BQKUQu967dz9RD05oXk7L0uCReoqG60fumrLtnD2i4Pkz5Zk7ZTCiyJsa6Z3BTSVnjyNWxm34JxgKAs3lZAICNgZwVIpcsLY6Fe49KpmsxFHYYT6wDQpTdt5NpYA8eRm443sjsQ8TIRjnATTq6ryZCAHHTlCWA9C86AxtScR9zhvUoaoFkAjKFu9JjiJbDbuNTpmObmcN0t2Oqs1Zs6nHsnPJkkTYtYscEp9gtxY9jy6I2uV+dLqkMkuVz89hQXm4kTRQZQQsssvMYDBAapmNT4GUJwBkoMwVhkfI12DlgfNzAd+zYpoLI0RKSTTABGbTk5W0SXAciCsxVp+QSQkcIlR3uTwYpi16MV6Au7qpp1socjJG1IFJ5vdE0hSh0b0wzb6vUvYvalqawDDCNwDgV4ZrZs77DvISVzTAxZVn0LgHOgLjtlOsizFjEVaxkPzI24fl6KN9g8oMmfqpiPxZBHI1GjMmaBwC4nynxq4i25M+oeLFcW1Rhm+0M0hJ1oW5byEQgP9720vMTcPIwg+IbianIof5uRO8xcPl67qdQ3u1Vyv3KUcckilyS/XEkgjPTXLI0QrCiOfAPWL7e/sLA7YIAf4KlzBFux+PbVJgRQoTbc4oyP6m3I1ow5d0OFnZbCeVMDmYs23LGcZrRf5bQXgoV3TGW02w9+md8LqVjU0xwQhP3fYnS3JAQn0p/p8BiwK4UsiVj0D2fYQcHux2zi1t/EbD62KHZhWKOHYHuSrJUEuUAkqUJCe1VgPHlN26+ktkQEaVZbjNZx6L2EYW1JedjjRj2tNnij6X+71Z1Sl7k3NqGJQfUFVxZoLXSlS0Vn1rFicbxe33yi7ZK7FsOm6taidQ3CJsWiQAzlApREyL8ScPhr5wrNTafj6a50L0NZ0lSV1V3eokKVh1i5ZBtdg3SquP07eqo6tRZwJuiqSFPq3nTIOOYcwQsZUk5bdMDxyHuwcCfSnQUEiwR2/uZMoFkc9/e5WKx2LOTfHQmK0RpNW7sJHWq9POTDs4z8KtcDL9murfK7SuzdDi36KxkGOQJbkcO3xtLOLzToH0q3/scEFYO0wOHXijgYdNiOmvgBlbCbqvfY+yW55rOxPW8bXB4l9BfyDEawrzhqtPhkVSdHiAAZ8J0KtWgG76Z7UQwc9keV46/Y1uMtJIzmM4azBuD5qrl8ZDr3b8fsfq03BvzCWWQk2LKk1JsAQoMVA/n5YESXwPbfTsmi1tWCmQNkvewp6cAgHBd1ICY6CQDJKrTaRhAD874s+OIuDsghYB4GEp2pPZCzaFy4BTp8yvUHps4PeEycO/ZCBlg9Hy7Y/6Epjj3e5iYEPci4qJP6E8vylJKMzdD8TSFD7CVElP70RU/6U9YpAbDzJNQCEDblJu8bfmp+/R5VoXKilb7PdyzSrBlf+B6lGkGiTJYVJUqYmc20n7LUqv7/rNl0ZoxOSWqUVfzzPLTfRhhr2WyCYEL5WLKpeQaVdE0w1zsMkZj5dVt91nmTmtirNbfqK/qRYc0jkj7QxauaRtXopzWZbyj/5jL21NnS9Zjjrz0IMoTRR7zpwfYvfBkADSfPEfTd4AP6Jwt/rIA4NxiWyOkvvT0Od777hO0n+3yeIV1A3s1ov9UJmiJyrgeRX43KweaI1JjYMaA6ZyPZ7e8JGXxHXn4tQ4nP7rkB8fVlv1qATz6nQb9xRr9p2PhThDzebLxtaqKWQO7n0DDjLNKN/X3d6/OHGq7z4bct/t23+7U3o7I4pb2yoKpnAlgE55aA+E2xubNE1TZDBV5UUBSzk+a/RC5vxRfgxwghVULrQ1bKjcXT2/NxMRUxFpb9iPJ5elZ2yDe8Ej5wtuR5gUlcS7zJVIiZWpm7CcVfEUiHvIi/OMFG6lk9j5XvzRDJU/rkg0yAspG5lGgYCE5S1ODrc7AzGEp1vMGzVRZqIQoZfFVZqrKUOXsg2Z/Zu5XLtLznA0y0mcAL9bJDJzpIV/0LKKooycIuzWvaz9/RdlbO1kcGxovStSbylDXsVEsNW6xzKC2AcaYXwEgxRJI0YZJ85p9SGcnyxqMZ5ccQjuLNBUA0XQdf7ZTvCGAHpzCSH+ifOnx4RnMfsggISCYwroFiGCeb4se5/UB4ckpEBPcR8/485se5noPtC3oMBbj5HHi5UnXgvaidq1U8/UK8XSVr9E8veIlzP6AdHbC2662Zdy8B0SDE6IdOr/3AHavgrqRUf3OLjQ4x8c9uqcDaG4R1rrkYIq6GabCqNTyd2cRHmz4b0AeA5ytYK4E5JHrC61j3QqZcMLJCmZ7AIXIYwSuVdE0ZuxsBveGRy2aa78gv5k5Mq167xFWDu1TOZ8zmJ5sEFYGq0HG72wtVgCs7emuyzIkthZx5eAueZvW9bTTjGd/vMfZSmpDLOB7g+6ixf5dviY3MsWaUsol6qETuveQ0OwTtl/nsXpyCEz3NgRTkeD8eyfwK4vVRy1oy9ew/fYJnn/H4tH/Y/IyZDoxGeCklBDUCkAyL91lwChWAJSA8Ed3By3ejski4VbcAmRK2rJuFVuTnBP5dXcERr4c4Mz6Dp41G6K4eGfQ8bPEWhDeFgTdiXxe7XpuWbrumN2ZeocUGu6TrBvjqkFYscM1Hbq8tqeQ4DcNo+U6sXQWGBtG9a0pgKyz5XNaL5I/U2T7AMA4i9SJrJ5+5qD9Foq7pm8VUFzVMvF8o8XOLVKy05kF+RbuEDLQZ0KCFTcvtFo3wVmPRMRrdC0kWzUZ0DZyo2apvc4BpqyP48rBTA0DnOsa4EwwU4Q/sZnBOZ4ZgBxCw8xMgAFOOyc7/NljAAAgAElEQVQkS5geuJxRMXNAWElx2ScCrjoDv3GwKte3kNUTgFN4JeqQ3jYOw2PC6pnelAJwBpul8oLI6pmQstSe3wBIwDwT/C5hEs1dv7awI4v3KEciNQbzxmHeGLSrBk4ijfHM4PC1iMMnlZ7FCQGwrKwXkdOkoSXYKcEEw9J74PN/9QDOW1oKUSIFjSgqcHIYSmSxZyATh2FB907eM8A5jrcCnLi4KucxBOM9UoywO1GZ9h60O/BkpRL2hwPL8IcAaJXh4QB6+rxYCyjA+aPn2cpPb0R77bLkO6YZ5lrrFAI68SzRydF9clU8Rr0HVBl7mmCeXSPNc/HA0GXX4QBXGc6k7RbYOvY5keNmCX+1EjiyROi+/6yE5ZrNUANluY72acuGQtMM90yzRwIO1+nnnK3xaOZiR9Bsmwx8JomOrCsAJ7zPloLNVcceKrtdVuHuFOCMqYgWAVj9sOEJyhQ+BKtuMTmub10GM8kHrAaP/pMG9jP+LVgf4D5tOHvkbCm6AwBr0DYuA83uU/mdXFzia999B+2nHJklaxF7B3s9ov9YIkddKoVUTYolUjNzwPSAx3H1wbUAk7Y8DKxBK9dqLrc5Gn782x1Wz1foPx6LKZMzXKBouNQgG05bkwv0TqoHivqx3qXdA5z37b7dtzu1tyeyqMhLSCnzKxaakTGBhESTlydqduvcwhfEnmyY/NR3iJC1vbX82VSqO9N04NXJyYbdsXTJcH1dnsbqpNV1oJMNqOuKCjgAPHxQBFs1uulb0CEtjIKpccWysOZODGM+XvzBR9z/vkO6vGIvkP0h+3vE7Q62aYDzs0zOUW+S1LeI62LPx8sQxjbSiehWXGiVrqTWpD9GIrl0smLCFyoiWNcs7QvPejSTZ75HXYSVEuMj1feQ22ZVnpSyb3hyBrPl/sZj+0J5qod1C7MdYZxFFK5I7HnJRpNnmTk55PSoX5SVA7La2bSw2xFh06L55Hn549man8SqafLuA4STFjRFhJVDc13c0mLnkBpTMIuTFskZtETYv9vATDy+yVHGCYZ3JR06lIjWr4V9me0LI+xgMT0Qw6Lvsz0hoboOHzD+9CP43qJfNRnwHJ70uH7fwW1LdDCfOTRXhVGs1behNZjXPfpnAfNp+c7i975qmMVtrQY05f9qDVDjEDU2sWhaMSoA6OLQRMUkSCniXcv1Crq9OmZ9LnKOKeYKhO4P7DvqVItSbrB1xzUQVflzWnUIAoy5/VAAzrEI4RQNTiF6dS33UaX8rQU6nhSMTkKimZHWHcJJlys6m2FmMlaMGYuxg/ADnF2StSzXNvuTthLVEdB21WSyFACMjxrYQwfyEWFTWQ8Yw0ZCtyik63joe4BBQqcJkpXaA7BuhoJ7uo8dRgQx9vFrx0rVo11UZA6PXNaZ0GbmiNgZtGAilfIj9Nh+4/KSIpy0GM8b2CFiPrGVRgSL8oSOchZjOm+RHNB81mL/rkErhkSxEUIYEQ6PhZeyr/CeU715uZS+vSY0e4PDE97ndNPB3FIyPz5sMK8Ibmgya3Z4ZLH/RsL6s/LgGs4JvWvybyCoFUDHojyUgOFhOX58jRng7Z0sXtLqtOoLJf9z8VcsT/b677qezoVbQiqyFQh6dMwkhVcUY/m8rtVjSb8CvFbOhWTaZp/FV+CXKtp5uxZQ+cD4hxclcV/9XT5L1TaKYBXuqVqDhrJfPpdnCjZ56YOCeIIBLNS9NRU6s3isbncHSff5uDifYgO30evzeOh7YHEuoxkMqTHJ20fZJ5RzWSuFZFMo0SgAN0S4YbkGJ89FXGYKcEOV/gWTl6ylKuUbYQdRCHfEyt86NgQgmdKHIUgUFNDsRIgHAHkCRYIdA5q9zf3SFjOdnzMn7pC437sKFJ5vpkrtEJHIwEwRRsamOSQ01wbuUK6paQ3cIeaaD1URJykCdEOC25eit59Mde9K36JOq+r74+hBaeDUtXk5QdbysqZiI2oWIzkLCjan+1Adsz4XrXsOv2XZYNoG4bSHvRSEX5+ejWXT4fp7b1wRX3G2gHDG5O2UC7pEQbx+BXj54CynM1UTzQcuIls1xfQHAK077pszlblRUwrffEDcSKi8WgGBbftUMj/Xv4i6t0YyfmXQNqqCXY3XLIZIdPPJmMdD3gOsDK6FaKF3IqNP8JZgDxppyM01zflcoTNcKJZs/jvAKcss0S9NIws7WPjeMgtTmip263ceVg7ziUVyhO3XHE70unxC6A1AQBBTJH9iMa8Nmqs15g0hSGGZRhZ2qFW0qz6ul5EFi+0apn+D2Zq3CfTOG4PQEfzKApKJmVeE+TTBryq695pgJ3NrZLH7BsEOJRtCCT8hhWQ3THtS3pZCuPH+huCN98V9XJcGAD/5jCkFVdmfYloUiC2OWZ9rGHl5oVyCaYa5HpiCq/gJkIufakdxOhRzW0wzSMLTNE2wktPXgi4zTlycNk7cR3V9DwEYJ5jtWBzIUwImWpCDtA82gvkeWqg1TEV5K0SYK+nDOAEpwm2nqrhL+hK5aEyf9t2zBmbHyw1bG08PMy+ZbnFR1/Hg93zO5spliTiaA/MjtK5EMIvUOpY8PIzZe5R8zJhFLdffN+YmZuEjUsPU6TalBYXbXY98LDlXc82Fd2aKOAHQPpe+xYS4t0iWMmZBKcFtDezViPUnK7QX0l/BLJqrGSv1M60iCzvehllEkKwHzG5cZmH02p55hM6g2c45au4tYf1hg+5ZoRcY79Bc+VsxC0SD1TMPO79ZIdl9NuS+3bf7dqf29kYWX2DLOMJtVOvXbcdUcnU9iwkwuB0f+bKbnDt7d2hJvBTZ1XTxTJWu99freJV145fRam+RALbdq8R6ku7zBdCVX9li5BOmytoQTJojm5aPVhGXoeOI9stqevmxlCS8brMzuJz/DYfy7Z0sjrMhdavXxbXz2G2fN1TwjBrXqMVr9P+101h9zPpcIn6TsQ3V6lTgSs/ROGAs1akAFo5h1tSsTIegTllU9acW1lHGqrivpYryTipgXDme8XEFF5krfMTZTLTK/czXK9WOs6SVqayjs1MYgLCycK3jEL8rSDyFJGN4S8Aq41GfM7YWJPhIah1rSjoGL5PqT7aWsRBrsmtZ7BwDnPJem18bmHmJWZA12V0sdrZonMqxY1f6qxgGCAi9QdyrzmtC6C1rQoyKb/D/k7WMWayKIE3sCHayBUuofnZzhVmwKTFjIZNiFo29ddIOvYFfGVY79/o9GMxnyOfW45vZZixCS/VDS5g3bNcwbwqD8ycDszhudd2HLSrb+p5u+4GqF2h2dgrl/8cAZ+NAIRTuQ3XM+lz8VDYLkZx6EsoZlNZxvUr95GmbnCK0lX0hOVu2K8CpzuwvAjgbCxqrX2FiSnMNOFrpG8WEWHlQgEj0DihPCORZJCiuXCX3VyYLtdUDgHnDNoDJRYRaTDY6ZmL65Q2rxzi2KoydhRX8QvvHAGsowrathd0zvqITg1/bbCQc+kpnY3PLZOETTxYj07UXAKe4qKuzemoYRGSuNIpAsRGNjFWZQELLClkUAqYHBL/W6yD4jmAmWzQqqt9mTp12oqRFQDIFdExdcbGvm18ZzGv2MiGhyE8bg/E8ZZtEPb7xBeBUPYvQCfjaUQZZv9qThd5oRDcAzhQTyBBTuSv1q4UiVr2/Uq2r7YVCjpsA5zDeBDhrNS05F5FhkFNTtt4z6UkNkIW3QbuBi75qgNOYMuDjVMRNhhHukoljGeBU9a0XAZy7gTkNAE9IxoD2ZvGFZg2McSrU8lmMmSOnERUkTZ6VutzleAPgTHMAjYWU1X/mWCOi1tuEAJzjtPA4yX+T8eBxkDSeMbwdgJt5gjCDZcPlQUDHxGpaaZxgr4VcNxdSlnqPAsDa0ksBTopHAOflCJpioXBfjlzJOQWEsclgJgDmdOwt7Jb3bcGTCR1GbD6K6J7eBDjXzU2AU9OpxwCnRnNmO9wOcD5do9lZuIsxK6ytPvM4+X6D/rMCcNrpxQBn6Ajdc58nVEr3AOd9u2/37Utob1dkUbcjzEKfRgDuxOAk5/gpb23hSxgwVwN4YwYnnMjqKYNzd+D3W5ZDy8K3XzKDM627QuDKgsBdZjkCAB0mpFUL8gFxw7RuK5FFslKRqzaMkk6df4wMznDWFqk9ldVruNpTl2Nqe2h2DfyXzOD0Jy2m8xZ2CFzNmgFxxgVCa7L25nTeIFmg7X48DM7p3GFeG7hdmx/xr8vg5CWJw/CwjNFPRNXpjXabjubLmoKClRI3hfBaa7Rbu6EAoa71rUFsLIycJxG94ghfTFNTJEAwFSI2Jqpdz6REPY0eKqyZdDwM4xUF+CxSdT+ulohYXgBYGBklWywTkpU+Nl/+TzU5g+T4dV4buK08JCIEzCw4hupWZM3WL7tvYsyUHHGJ/xs0v+bJIWMxL5KGeEGjVypS/RjaGT1Kv0x/uhR31aCgemD2PZL3MOv1QleTrGUrAGuLuC8Ae3qaC8a0fJwenDFhKATGGIBckGbWa8YfpA/h8uqGwxlZC/PonNNXykacJtDJBun5JWdeRK8zeRZwqceX2gbUSGnz/pCLx9I4wYgYT/jsKffn9JT73TQcWejnDgfQagXz4GwJnlq7ZKYCgA9ZzyJrXmx3PCaSQiV90lohqhmTtT0zviM1Mbmob7NG2u3581VBXZrmpXxA1Wi9KliGfIbOTgsI7Wwuq4arMgKqXhZjwZnahoFmqf3J51/3y2I1oJDwpplrep6WQjI6PWFW7cUlb3jnMUeYIcA/XMNeCXYTgkxgIeNEqWvzRJEswT7XEnXOotE0I26keK/GzToVybGcCBkDaPa5ANB89Omt45fefyd/hwr02u2I+fEGzSdFnzb1TcZ7ABQ3PGdweP8E/Sf7RQbpu//nr+Nq++Gdpoy3KrKowUDT91KLERZ/C1dXcN/8BtIVDxA9OEO8uIR5cIZ4yboEiJGrNa+u+YctVaPx6bNysl/6EwAA+2yLZAjTTz2E284YRVeg/z/+AHh0zsIx16wuRWenTJF+fIZZlZL+8FNMf+wJWlXIknMc/sU/ifb5tDAPnh52ODzhIT/7wwHjIznXpwOefWcDJODJ/8Jf7v4X38fqg2v4sx7u2Q7hobig/9EnmL/1HoYHLbrPZBKU5cL0eI3Du+XmPfveFvNZh/bpHsPXmbzc/3DLVAKpIh0f83G7f/Y9AMCnf/4X0F+IsO4YOa13YuFXlA1yLr9tcPYHEW5IGM7l6ZuA7ipi88GhmA/rjz4C2587yyDg8KSV4xpsPuIJQN3Y5zWh2YtpMYD9ew3WH89Y/d5n+OzP/gwAYDzn2pZmz6rYWt9w/a2E1SckPh68zQ0cBfSfJRzeJbz33Sf8+woRz/54j+Ex4WvffYfP9W6D/bsGzS5h3hDWnxTVsXlDmB4QNh9F2Zev++v/+yU+/o8Cpn/yPl9qC0xnEZsPDa6/w9drrxyL00TAv8PbutMRzkXsLk5gLhzWP8O/3c1//220u4hoKWd8kiFc/LzFeJ7w+P9KWH/Cx/i9f2WDf+3P/G/4O//wX8gpu/C1Ee7Dc03owJ/o0i8AAeg+eoDxfX0YAON/cvfQ4q2aLOq2yFyAsyH5/eFQJpbDAZjnIkoDcOn1wNGHvh4fwz0Tebn9AQSg+bQDDSO6UZ60swdt90g+lCftns9hLgwapSMfDmg+294Qv+k/PsBcL5+y/RTgpOrTPdvloiRzscPpDxynsmRi6z/eg652cD6AdgdYzb4MI9zTLcwgsnsoWYs2JJipiN+Yix3awcNs9+gk3DeX8gSUqtNWyU9yjWffn+B2ktGZuVCrveDUqdZxGN9h/UOmSreXkv5NgN172Ge7RYEbHzxh9VGT1aq1EKpbOTTPeNwaXfN3FmYs7u527uEuBqT9Aac/kLF5xjwLO0SElck3its79JdBjIEhn0+IltBeevQXLqtwU0g4WzmsnpksXGOmFdptAztGhM5kCjfAmIVfmzzhKUZhn+8w/ZP3cf49wV4cYwP98wA7iKxeVbg1fdjK8VpECzzYAs0uYf8pS2WdfDjADj57y3DHCMmsMG8MTj4Y4a44K3T+u+f4b5t/Hk9+N3cT4w979M9S9lcNvSh4dRZIQP8sYhCMgxLw6f7uk8V9NuS+3bf7dqf21kYWL20VwJiBz2NgMW+/fT5Mx4xLLWKqkWhjmOarYGbtUHa0343jq81hXU5vqRB0jKlIPwbRFidsAEV7U4u+8ufkfe2uVV9DnQ2oQM/iHFS93rKdgTwZm5AyqJYcISXdB+z6Xsu2pcRl5tYgaZYmyTlkvwxmKmPSLgFO3sa6Jbo9Wv6cIcoWgbEhGM/9ig3lyCI56b9BBnm5spJFdUJTZasQkSxrZqodoB6PPL/WVo7Rsi6mblP+QrIGsS26EOzszksf1QGNjfQj8TIFYAFdGP5/nMq+DPAqqap858ly9iS58r3HBkhtyp8FkPuikZX2MzYAUulfHpvXADjf3smiKkkHSuo0RQiar+lMw192TdXWz9ev1TEAFCDQiQNUY0HeZY1Eay0DaRPKcZuGf/gL71DLFOWj1G1sLXt0UmFJxs6VUubW5bSf6RuEFYvQKgAaWwvTtdyvSpGKnGNh3sbCKHilSxRnECph3cZx35JkbABw1kauP1U3u46MenoC8kOyBN9zKbj+8OY1wW8srEFmD5qQQMHCNdX3MAs5KES5Hi0xZ0p1bE3xOBXmaWwNKJYlT97H2szW9D3BBJ4U5rXJmMW8IZhJJzO5TDUgnpnmrGrkZo7wPW/T7zy0BqFlZmtoi+IVf3fMzMxq2dmz1GA6i8X5q+H0qNsb+LV+mic0isjb5o18Z5Z/H/Oplv8racvACvYTGwPfEXzP53fyXfo1oXt0wHR6WgR7N4DbM+GrPl/omIAVeiy8Tl9nbfHKyYKI/haAPwfgk5TSL8q2/xjAvw3gU9ntP0wp/QP5238A4C+Bc5z/bkrpH969O1WrStKBJd6gGQ0AXBoeAqPdFWaB2fMx9PXoGMray9mQ/QQapkxpTl48TH0o+Mg0sUPZMJUntBdHK91HzqGl3uoYzicRj0wimF0x6KXdgPZ5xzO98D7sbmKpf/Uq1YlumkG7ATYW5qEKupj9hKaSuaNhggFA4wy7E2Rf2YGBRXS0RFwnnPZqhlXMIvuPNiL0wv9ftQbdMwZv1YAYCbD7GXSYlpiFlMK76xFGMItGohrT2Xx+p1mvieneilk0jYHZT0jTjPaStxkvmMXInqTaonXoLjli0EjFTmxn0Gw9jHclwxEjuosWJtgsDwD5bvS4zVWVXZtY5yNv02hzmrH50KB/Lr9HC7g9l4IHyTq4Q8EsrFD0254nO3dIaHaJGbUA2osJduRy/SxMRDxJ2ImZoTpmq08TDr9/gvXHVQn8QOifF8xiYV8Yge4i5nMhIbuA3qXdJbL42wD+JoDfPNr+X6SU/tN6AxH9AoB/FcCfBPA+gP+JiL6T0m3VYK9oL4ksqGkyIEdNwyFr2/DNrK3rWPRGX/XD0jStZeSHPT9YwTqTSU3O8jHJGHYul3PBGKTTdRGNud4hPFjDXgtwJk/u6dEKjapLyXfjH6wwPuYn23roMZ/zFN+GwHqNCTgVTUR/2qHZMXGLxDUdAOjCIG16+Add/vKyNub5GuPjQjpa7yeEDe/nH/L1NuoYLtkQf86PHvuBZGHebdFe8XvNhvg1F0XZgX/0229YGN+yR+eZ3Kwpob226EcPqClOlf6cHvZo5QabHvG1TJUWpErr+7WF2we4Hf9/eKdDbwjtVYfhHY7hxzP2L3UHy5GNzFfbbxLmpwR1EAcAMzF3on9GGB6ZYikYEvbvNhgfUFbhHt7tcHhs0exZuEb1KACuzZhOKVO4lXDVf7DC9XfmDGbGhp/moXO4+jZ/trmuSFnnUtOyCUguwV1YtFcG+z/GY3b+ey3cTtXMNBsCXH/TYj4juIHHAwCuf5rw3i/9CBcXX8vHH55EzJ+YMlloZNEnIAGrTywO75bK6Fh+Lq9srwxCUkr/CMCzV+0n7VcB/L2U0phS+gMA3wPwz929O/ftvt23t7V9HszirxDRvw7gnwL491JKzwF8A8A/rvb5QLa9fnuJBWFSkg5K+Hxj/xjE1jDcaoVIYRkqm8mzpuRcUZVjWmpfpMTg3exLabWoSKWj/ljRjmQLRH4SmDnADmpuFGEyH4HTgEjlOiiwnkISLYra8AY+cgGUFnEJ6cdMPh8f4IjDiKajmuPkwjl5bzQKkP67oehJqsalsQRLlMfG7dk2z44hh9Xsah5Z0DbbSMYMcNo55mtQbUt3oLwuT1VVrB1j3u4O8j7G3C83MAfBjgnJFq2LZmfhDhAXcT6cnRKSYY6IO5SlFUKCGxPCQOzrAS74avZGNDPNogAMxGCrblMKN80e9srl9ChjJcTLC4koGhU7T4U9SYGf/s2W4PaAu7T5OzQ+AVT0NFIkNDu+JjsULdJmC3z87AybPXJ01XQGTvatNTbNzNhNs0sIVxWO9xox/5umTn8dwM8C+CUAPwTwn73uAYjo14jonxLRP50x3r7TLcKvL22vI5ISqx91LQyj/2K6ebzP49F53K/6/ynhWJCEcj9u2ffH3Chxf/h12Q8SERjkfWSCrTgWFKvrkH1y1S7djsjX2/PfU/UP1Rgt+lr6WfdX+7gU/Lll2xuOz+L96xwqLf/pWCOBJ94gY/WCrEVC/bnlcW7sW43n62RBtL1RZJFS+ljfE9F/BeB/lP9+COCnql2/KdtuO8ZvAPgNgOneb9AJftWn/+tOLNqyWS/KBKEtcFRyQ2nrjv0jnXTyuarjx+oLDcXYVk2Y9bryMarr/VKNkVN1nflGku1q5hsBI0pSVIPGalZcYRX5NS2v/U37BhzdFPHo7wnSL9k3ALDIfa0jNEqJAdpbBHJfq1XfZZI+LW7W435D+m3KZFsmNZkgkMox/Av6lzjqyBMhymST8syw7MPnaW80WRDR11NKP5T//nkAvy3vfwvA3yGi/xwMcP48gO++Uc+OAM7F+a0poi2ShyfnluNhpNrUVFWn1Z+Vo6+1ICz6ErKPqDHEniOVsTGs5crUtniKOucQVg2c+oZUnqFmdFlARs/hN1pVanOazHbsY0mJ+w0I/9+yspZ1tgjliGJU7KttmprtG/iTAhryfg3MoUFUkRitR5G0rl6vk3TnvDEwXoV4WGOCAU7KIfT4gNA/tzCTwXRStBEQAde6BbCpr2HtYFUZe13O1VwLsLnSdCBzDHRimjeGwU5n4SVNO50Qq0URstEwAEwPONwGIf8+7JQQWoIbWYxG6yIoiXjMmcmpU7+WfayBX1MW1wU4XTydUtaj0OrR1Dn4d+bMzIwtg4p2pAxm1oVb0yMem7CJgE2I1iFZwvzE5+tH5EK/LC1IfL7pTAFg7u90Dnz765/ho7PyfB4fRZi5Er+RFG1Y8aRvZ4PpYQX0f5G+IUT0dwH8CoAnRPQBgL8G4FeI6Jf48vGHAP4dAEgp/Q4R/X0AvwsWwf/Lb5QJuW/37b69de2Vk0VK6S/esvm/fsn+fx3AX/88nXpls8VFPTub30bKUs3M2xiW+fNcrZkaNtNVmTin2pohVKQsx5WctrAcVRsiRx9GSTtCnonILMnQCIuQhJSl5Keuge85nNRq1tAZsQ1kvU8lZRnnEFqL2BRimIbRsTGIFeswOcP7GZNd0DNj0hk26m2WYxM6yhoISAbJEEIv23LUxKlERxF+VQBOO0k5eSqS/YkIFCNCaxbEq2RE06FRUlZhRsZ6eyPvDROTACFl+QSKBL8qIbxfJ4QV8xcyo3IgwPBn/IayfCFCYom5DTI5TrUoyGvfyliGlsegKE8pg9OiOx0RpAI1NEy4antC2CiAXUrdw0ZA3pMZxiT4QJiDRXMyybWt2IDIAWaWyMIQQsdkqppZ6lcJP3/2Kb5/8s0cNsdNgF8ZAX55TAAgriMQhXi2rhi2XyQp621tCxxBAbWMPxQjotqQaNFMPhCQUlnWLNSuA+MFmjkRT1EYk0k/qmd5k25eva/WxMnw3xagVRTMglBRpVHcs6r1fvI+U5gXNG/wtnqyyH2zVPpb07vr7cpjqX88VCjoqZI6rJcJNxytUipZmpT4EnN2pMY3ODzX8xW6N0TbAtX/j85BuBXwW9C81fUyCrUaYDyjynYlwgKLiVao0vJaC8MkyzewbsvhuwGci2XffD1Acim/z3+zvM2YhKb18CTLXhtzfykmkCpxg/+fHBCblMdH+7Qy6vkr53CcIcrjqv2yCVAKeiP9Si9AQl/QvpqThUwGN1qtSiXp1TrNWrdaO5JTpyGnK3kbU4wRfRFeMcQMyskX5yvvWUHKL1OQdoxihlPqHIxPcINMEjHlJweIYOYkkYWsqUMCGmYqMgtSbk4RqbFDyAa5ei128Gh2FYNz8rCDldeQt/EA8U1tRfxV9T3cIcFIKbqZ2AbPzARnEowMmdvLcMxFst8EeRKGVLAUHWNKMHPMEzF5HoNmF3O/cpQEtt/T7c3e8Xsfcom8HRKMB8zM/3TCaracsqzrH4zXfZNEPpry5BL7ucKUmn1Ee83HoMj/L41rvnVbey0PlzFgd3GCB1LEHFueBN2BCVfaLwVjoxV8JBA8NTA7CzcQhksh3UWOCJKlzI5NFmiu+IHW7EMZm2vCb1+8DztQjizMpUOzLXRvHZswW1AgtFcornUJIH/3tMjbM1lIPj63mLhmYyrCM9qSL9wJErFaAEu696t4FrWfpzUwIztuKfcBQT1GC7UcPmSehU4WKUaY8RaehdzM5CNg5IYaA9xB8+kB9lC8P93AN55Sy+0g/IjBgObiBpZEJDd7gAKFZzH6bPunxzWjl/4u9808i3E5yTX74hfKkwUx2CZPPABotob5GENk/1BAZO5i4W0ATMGX79UNIetcuKGod9/gWcjY3cazUNp0dIl5FhPX6eTJ4pr5CKFJVW0IRxlu4Mk5c1cxmD0AAB9QSURBVFvmgGaf4Hcpl8zbwWaeBaWbPItkbudZmAuHZid9mzgKa3YJrbi9OeFBaDQFAHOQ5e5AMCPgngk1fO/hhsCFesJHie52nkV7DfzR04dod1U2xhk0W1SThXB8Ji6+a7apLDOB1+JZvB2TxS2TG7UNkvewp6cAgLjfl7+t+/Ik71rQ/sA4xqm4U04zZzJEM/NY8QoA4gnP5EZUpOYHPZydMJ9IduDsFPF0AxqnwgnYrED7AXHVZlp407A2ZCMFYHqu8WGLDhBZez7n/KDNNGG3bTGda1FTwPCQ9QbWpxsAwOG9Hus5MO3bUjnfdY/5rEdYWZhJqMtjoYiPD8tX2j5v+fNjgD8V/YVrcVHvLGi0WfuzlX7vn1j0rtRVACJ+0xfxm/3XCM2Bi67GB6XOoHMEO68rslnLS5Y5YnjcopPweXjMGpHsCcrXMAv1268M3KEsj8Zzvk7bOAyPZGwfMGbh9sB8Un48+/cTYksLUlYYZEnxlOna07lojsaE7dctpnNgEsGj6YHD4YmB2zG+QVWqYNoQpjPKKtyqmXm27rD+mausRxEbYD7lWg+lcLtLC+U+aNajOZlgbMRw2cM9czj5E6zgtf+/H6LZs++Hjnci4PAuYXqQsP7M5e9l937Cr/7s7+C3fv+X8y00vzsjNk2he2vB2joAnpCsw+F9jS6Rq2Dv0t6UlHXf7tt9+/9Zezs0OM2j9Mv0ZxbLENP3SCHCrDgCCNeiM5gS7MOHRQ+ya1lXsu+ARhW7uUoxTROobXNlaR1ZuG+wDFqaZ8Y/1uwiruredLXlbYchV4JS1yFeXYP6PmtPxqtrmLNTRJH5U8Us87PfYj3IiqeR2gapZ7d1c31A6uVcw4TwcANEwD5jebV4fsJaioZA45yftLTdI52d8LHFA0PxBuo7pHWpP6bLa6BpkIYRJIVzaSdSfNbwkkY0OMMnUkD8Cz+3pICLqG+9TPBnHdz1BJo84roUZtE4S+Gc7KseJbNHPOlBsuRJq5Y9QiZWI9OxAcD40OyzlmbarEC7/6+9L+mRJMnO+56Z+RJLRi5VrOqunuH0rBoRIEBABMUDqRPvOuqgC38TjzqKAH8Ab7rMhQAvEsSDyMYQw2nVzHT1VFdlZWXG6puZ8fCeLR4Z1Z1ZzWEnOfGA7ojyDA83N/cwf8v3vm8Hf7OE+/63eFgVs4qpgUWOQnjUL0qY3cAcGCZA7B2oZ9fdTUzU/aDBYVjUGKYak89W8XzdrGL4fmlY/FnMF0x+rNai7yKNhOpXr3D1Z9/D/IXcY5qVzsvrDu0jnhvVCarU+ShGNNQqhnZm67B9wh7L2c92IOvgtYLaSoerYe4TWxuUX6y4GxnA5vc+wM33CyyeD9H7HWqFYm1FRMqPqkq6dShWQ6QwBIC/+5u/wOrmszslLh5GGPJ17J29IW78um8xv8GZY7KWkZRDFsQdggFLHiNWEay0sO+RrFI/cD7E+yRtOFigD2l+F/MHcE76SLJjWTm2vI7+JvvG1vkAgupV7FkBpHICcMgWjiX7eK94vziekNTMPus5uUphPKGTs7GcvO1THoKc9H5YNy5VB4j3kCWaB8ecRG0XKz7xbg36rGF7w5/x1sVjKYBRk84xpYBcI7MZoHoL0h7eyuIqCwXnjhLQCZZzFbqlOC5qe6bh74e4+CEfl0PcprI8WblxKVEs11q3lrtHIWjXcC2lbEJDSmaaxkawF1knpEMJqeul7yaOaQj5HItyyQngHLFqttLi7j2coD9dTzCNhd71KZ7I8lB3sYe7WCh1UH8i2Ei/VPAUUW5wuEN0FS62Em2PIOuXMWj5wvCPLywY96D592E83id2pgybgXBMIDJbe+dSIlcTP2Wdg3cqXVRjDuJG/qXME40rTQFDojJsCvGTFoOL5DXegWHK5BJRT/BMgncVxp2zfN3HMmYxkI/4kdhwpQl+YBxCwMsoqXRFEiDBeiikUnM4L8JtJbC7mNOJ4MgT4128pkS8RB4eBIJPJWoDUM9jZiwM5BwUPHn4UsF3MreipXLLSErLRiUCJBVK0gS4VEp+r/nes4exWAjGYLTJWsC7GEKMzNpEzz+wpCGsBppG9r1D80GscAzwSoOMkye8PCG6DrTVzJsRnsb3OCUScpnYLCCn6AOdnbXxxqF+YEEf75kUGAAVhqUFiaI7DwC+7SJw6zdhlOFVyDrRhQXIZ/DjQknIkfRIuBQ7pNArnBcRewZKJa/tEC7lLmOTH4xXLuJrVFZFI6OgBsc4uFDSHVz0bEhRJA2GddxNq+i2fMA9TQ25sjkzXNHgIh9F7PfIMB2q94CTKlLnYjJTbXsut3cKKngrhxYK+V7d8/4hDLGl4mPLvCihlXTv3ZCTnefX/oajHe1ovxX2MDyL+5qiVBsTeUIiQiLnvccqqjSHC4oATxwSAIiCPX1yJ0mp+zXvRYRlFn4QJQh61qDmNXHN2yQAGCu7uxQKADLW3/AaH7yYcKygHGZSOBVc4xhyDNk4gyp5jrLNiHyhuBHwvr5FVHtT4G5LpYTuL4WJDMWnJGtIBN2zZ+ONSoCxTmQcC5Wuz3AP0EE+LpWFHErg6ZShUx2BNIDBpzZxSUAyWjRXkVPwThKqwZMq9BhEmM2H00KmHG75GE7z/ZTQnoT3jLKiPZzFQpJp4X1QMPcSWlBRYsTJKeEJaY7XSBFsEBkCoM9PgV3DSlhrobwry5RkC0pc6w1flPMFq03Jje5WaygJP9yOx6AmFmpxAkwncFJ1UERwT87Z1VQEks/asznUajtKmLppjUGo9IqXA9ycKxT6LYsJAYD5/7/isS5mwNsbYD6D32xBc8ZfuOUKqq5gP7xgXRIghlRuPsFwmnjSilclbF1CrXewZ7y/fiNVG9ENcQvmXVPDAFiH7ukcZiVzO9I61RE/sX1WY/ZiB0cEO0vU0nqjoLcN8OZ6fGkBuPMTxrSA+2IAoHt6geJaqgs1Yy9cyWS9IWHYn5Qoli200eiEGrCfs9ap3lnYSQrJNh8UkQszGJUK7aMC1dse3aLA/OVN/NvwdI5+ZqJAVPudC7TnBXTj0M8U6quER7C1wjBRqN/wfHVnBl4R5poFgLySapNOxL6rbwmCc4MYZket04rzFsXSo9gwjgIAZi+Iw4q8lb63WP6HU/RTwvyzEmbD41p+XOHq933sEgbA1IFXOh4vcHDaivtopq9qNBfhdwYMP737g+fhLBZ7NmLz3re8YSwmBPWYvVuFJ8vhyfABwh0AW6U0iZXZlOwxdgeJQJ+xbYfSYmDNDp6Hqw1UY/ba4hNDdVEkJnFl0nYTy6wMJvMFN8rF8crxXZnYvYO5UmOo0zajNT85VZbYC/sUJiqTAUilt4kGCfBIyXza2sDWGlrG1s8UbG24/DjJ5st6qMLE/Udjk/kI78OxtLRbB8ZvWzGsOjRf2VpB7/jYobV9mDEHpyewyJBYNyfobny91eAxVATdMA2AzzRTh4kebRtqjX5C8KSkoS4rF09Y/zTA6XtppQcR2jMfWc6DyJDuFPrF7X6bbiFTVXOvhxcPpDv1ca5HlS+xfkro5wRXKfiGv7c7IbjHLfpMDLtbSENfKNZJo99QMwCrnwH9SXZd7pH+elCLRY609HslHdIKfnCsSdq0id1b3vumHe/jmBIukskA7GV4z6UxIdj1wWu4XjOLtiS7rPP83UAsK/qmZUTotoEKZa3BQq0SFgOCCzGvl6Iono6vrUMVSo3LDUyAXq+3qF4KsjLAvd+u4HcNV2XkFQDcMECtNjCFibqbAQ+hb4Cqd6nEuW24pNn1MNeSOJUaPTRXm8J9TJMJfNth8vkGtBWCYvGKdFWMXOGF9Sgu18zavUyeBTU9aLWBb28npeN8APG81TCPWAa9MwyTNooTzTJPde8im3X9a27AKN8W3GwleIg4v7saxWrsa4dQSa9bFMuS8TNik89LlJMC6oa31ZMCpimgOodholGs5bucR1Fq1IWCuZZz2JQRy/Ho/3nMPxPMi2Gvolj2UX0uh42HBc8V3L/BvR4O00s+j/KL1bhkKzb/rISrFIrlEGkAz/6pB9kapz9PeJDpa4NiOcSwKHXJKnRzZh2vrhMHiWlwZ3tQi8XI9l0KpZKXkGMaYkeoHe/jPC8+WckuivtqHW/oiFVoWoaJ73ed5mOxlsusedVESTbecVwelM2xa1mKMKvMELJm17aNMbtvOygBS9lsYfLWAm0XX8N5+bYbjxWQhdFB5TIFst1rleLx0HIf2LdCWFYWPJ71Lt2ssSrCwtNhPsyN5kXH+TEupR/g226kWRtMhflAKnxRXSU8BRHnRDrHALCQ5mm5uuKNjoAo6hMmxmfeVUUUF5ZozrGocdPCDC4t6gBovYPphvhQoG6AahT3iswMEh+qgxoI1AxQYW4UYCcFXGUwfdVHSUEQwRQscRBYuEMvB4BIXOMNlzd1Y7lPSCDctG0O5k7MZoAXvtCQj6neNJjXCuV1Wix076KUA4CoF+ONwlBXjP3Ib5t3sXAdsGM15GhHO9qd7EF5FvkTiQJ0O3AoSELTLpfQT5+kpOV8BqzWoNkMKuQYLHeS+t2OYdnyhLSXb+L3qx9+l1+XG4AI9oNzqG2XYLy7hlXTrYXfiADxbMrJ19kETnQ8dNPCzidRN8S95eTe8Ic/hlk2o0RVfzpBd8bnNfl8il6SmsXVFpuPF4AHpgJ/Hr73IYqX13AnE6ibDfxcEpFfXMJ/8DuwiyqGFgFx6c5maC9S/Dr51RJuWkJ1PYZHnOA0wZMQWLWTxCf99DkAYPOf/iPKZWALd5wXmLKSWuiCXH27wMlnJ1CdQx91Q4BiZVG+2iTcgoRHZB2r1N/wE7A7qwEC+plBfclP5EGUwmzNnZ1GoM7tRYXqqoX57A3Wf8BE8d2JgrLckdpPVey4XD9TURQ4xOxBGLm+tmjONC7+QcIm67H+3hztQuHR34tuyOMazYVGsfPoJ4Q6k4K0E4VupjC55LkJTW0Xf3eFn/+3Gc4+SY1kw5Qwee2x+g7vX4TIxzMVHsDENV5zp2y54qYwAPjWTz6A2VnO2wQvkwjLjyt0J4Szf+pRveE5+/WfnqD9ozXqv13EcbaPPOrXk8junSuSwQPNeY3mcfw4+v9795rUg1oscqOAXoyqTMkJoukkdZ2ezEBtC5pPgV5CC6ViDB5eAYxCgv4Jd6gWAKAUth9NUS5LNBd8My2eV/Cnc/4hilvoF3PAWgyP5+jO+Uc/XU3RPJtiupKrIgvL+ndrTC4Nq0uJO7p7XGD7VHMnpp9j95hvuFmp8PZHBeCA2SecVd9+VGPezdGd16gAdI/5R10vN2g+mKF5VGAakpYS3zdPK6w/TG65bufozgxqo7D+Nn/vPKDjpbrRPOUfyvxTPu+3PzSYXIb2af7hdSeEfkbQ4u3e/J7FMClgth7NYynpOqC60jjzPi4qIcdBHlh+p8bkNd9u26f82p4TTioeV7vg69vPCcXao1ryZ9bPNOYThcXNFNc/EOGhR8xNYTYK3SkSU9aPtti8mMAbDy8EL3rDrFGTLwy2zxzqa1l0e4+3P9LYfeAwectjWD0z2H7EFP79icf0RcrH9AugPfOY/7KQ68Pff/LLGf77n/0N/rL4E75HSo/qYofdp3M8/YOXAJiu34NLqN/78BIA8MPFa0xUh7+/foZfvDnHf/3+PwAAfvKLP0a5NHCaFzqAEaJXv+/hHrcgW2MuyujtH63xj3/6P/ED++dxdfzxRy/xyfNnDDL0wPyEF5YPT9YYnMLz50/w8ceveKye8OKv7l5PfbCLhQ8sVfm/w/vtLvEybHZw/QBsdwm56Rz8dgvfdfGVd0yLRfGKl3ta7wBFmH5moJoBeidP5mHg+LEf4CVJStsGvutgAOi1fG61weRXFRASpnKsk1800Os2UssBgGoqlEtuJKu+2MJseMExywZnP5OGKDmv6ecN1LpFNTiodYPYSdz3qC53KJYd9I14FjI302aKYpkaycpfL2FuKqjVFicyN/pKHnOSg5g2/OMJcfvFTwcUm0Cqw56BnWhGBgZpxp3B9NUAs7OYvBXcgvMwa4viTUYl0EuS2Tqc/LKAEZlA3fIYZy8Vqks+h4kQINuJht5JDwOAclWjvGpA1yuc/4wfy91LDbKMesy1TrdvpqiuA/mNtNm3TMxTbCwmrxXq1yF563Dxjwq7Vwr1F5K0XFtMLwuYHVPTVVcp/2GlclJf8rbpZSH30Qp/9b/+Cx5/wp9jrdMTTL9wUSlslvFZBHLdX865KU43hHID/PWn/xkA8Ow5ExV5kzw5bwhqMOjnFU5/3sYcRf23C/zA/jlm/3saoUWfLr6L0zeAFz6LYcIL4YvqHMoCjy49Xv9cpHw8YFeZqvJX2INdLO5sX7dr1mdY833q/v1t9z1WaES7RdmXdDOCRa2IqLeR7R/0Q0Zj/s1YHAeQVLadH22PcgEee9swHqeT5rO986WMxvC9TI4VKPQpGy/rhtBo2y15g9F23LoW7zOe3G4x1fl0vNE+lI0h7sssXT7XVvkyjKHnHpD9Y37Vv9/HjgnOox3taHeyfzOexUgYWSm4ACUOHYOhuxHgJ+9XMGXlOhwQ/QyyPupKxNbnjKgWRCBj4Ooq8jgYY2CnZdIN0QE4xLohIBs9Czsx6OcMPqqudKy56zUDfuLYgVge86VheHX4t2XcwDAvY0ku5AbsrEB3mjFlXZWwswKqKzHMebxaQp+AmwgIzCIwfC10fALqlsE9w1xjqBV0y3/ozgj1jfAyTIJXxuxVvtKxASp1XRKGiYm5laHmOehOdGTKioCrqYIxSaOkWwhTVlWiF82VbkGggVBoj36aPJTmEcCM5AkI5bRnSLgTVi35uDOMO+jnBCcw9n5h0JwRilKhn9IIGRl0Q3QneZMz/qJFXcB+0KL9NYdWAfikG0LzWCj4KhU9iFZ0Q9zMAsZD3Rh4o9A/6ePcMEybsRFh/poLhW7BOAotpMPtI48ff/QSny6+m+bgiQVZzUS9/rZuCKCwe5q8139R3ZBvzJwfw7vz/MVgo7vuh4ErFHlt3znuJrUWJK/7Ro0kdiR5qbY9qO2hQwY8cCoMQwpDBubapKaN7Rl+GKC2CVsQjmXWPdROuAfkR2PWGmUgjN31KNYhQdmjXHF3ZMi76C13dapdepWJgNr1MIpAu5C4FfDUxqAsM8LeXceoy7aDEdKXgNeggXMWWtTKw7irG4tiJTkLSS6TA1Tro9ZpdcXgIN2P/WOzsbxQhGpIWNCdT/MBoIgt7IjjIqHgVsNezqJU/Jm2Q7EKuBeuhuidg8roCIZao77mCk5IKuvewyuPammZfFgIeMjyNkDHYxVLjdoUzPvZ8TkGU72GGtK22giNYtPDvDhDfSWLvAHMllC/9ehfCQfnBjEUUn1YZDnxWqyJOTOFlrFY94mPYkgPqfpKQ3fE8y44ivr1BJ88f4bTVOQDWY36TWL3tpuA4OTQrL70iAGFB9RtSMw77eEuFnuKZLfg3/vNVDms+76NVsLXMNo3tFGHxq/wt8DNsAd8Sm/Te0/E446NWVnDUP6e+D1h3JDkRXmN8uORqLHlzUthLVTAqDtL5ee1lyNQxPvtTZXP9xE4c0CTRWUtYpCPtz5KD5DNjh2AUqGKpDCeM8VzE+DSceyQHIlK2+NnlMoCe4Inn8YUcg7iUXhFEcZMTsarhOMhcIvAJcmB7JrzQhPGkV3LvW25VmjuyXiFKF+QbyPP1YfYSCZ0/U5jJHfgFUU+CsruG1ZZuz0mMo6TmSElE46tOZfhs2vpwyulbfexh7tY7HkWt//+nn87ZHkCMWfeisnFsO09OAFCkk/ex6Shz7Qs8/eZxgZZJ8K3Po3Lu6+fkPsSG323j/9Drq8BILI8RX2OPAG6J19I+wliB5B6j3M4lDh0e+OVbQqppBvIayno4oYxSDLx6yaMaW9sSYRZ/n3o63367EirNCSTs3G9i4E7JmlHyW95/fr0Fbfs4S4WX6J1mquMRRGhURMZ5yHCE/mQ1inyVnRpVfa9jvBYFTwCrUeeBXkf2535sBzzqr1juFJDGwV4nViUCh3jUK91UiQz3LjEYrnps15LW3h2PCJ+74yKILTEFKVSnCvH8FqxZqrsr0P+RmtpkZbvDUpqlYJq5bPyPbZU46aqOvQcqEgrT561Tzg/MHZXPPmRglo4b1cl5TFbpL9Z60HZv12hoJWCC4pkFdPak2OVsqRIBmEGT09ULV6GaQhDnTGhSU7A1kjjKkiuw1h9jOeA94+9FoFO32gMcwdbp+8YpqKAJtCb+GPOcgjD1MfyJjmK212h4KRJLhDXeMXHthMShbaQ32EcRSiPAvz9dpPa4wf5k53wAjRMKKqUsVgV7mzHasjRjna0O9nD9Sy+xEaShJn3MPIcQg7jXS3qEn9H3k6jOI+gcw8lD/CQPI1Me5Tbx/WtdvZAwgKX5SwMRU1PaCYu4eMofmLlHrXJ49XkSQFgz6ZQidJOnuS+0PHpG47BY1NRiSsSvWj23GKLeqjYlAQdkrAh3heQUxCsiU9dn7oa4QFtmCRnxI8q5or0VE/eRFIIi9tKAg1pvLaUzyhinVgAtuSnrbIYP/0r4YnIclDkPWzBXJusFpaqTraQ79fhWAq2AsiKtmjmpbHWadpmq3CdFPzURs5PV/DfXAnYmi+o6tMc2Yl4EFMHaA/ba6iOWNdD5sH1fM0DFZ7X7OkMNR8/eEK2YmTmi+o8eld24pnDgtK/ARmLB+vWTrJiwT3chYe1WGTkN7EFXaoMqq4ZqAIwA1P4u5MqgvexqxEA1MU5MExYkCh0O9YVs0RTxiwUuh6FJzG0//qcaj9k9/seOFuwqHEoZU4qpqAvmEiXRBQpxPgc54crmeJ6ljaU971Ncam0zFPnQLuWOzPbjn1/AGhbLnlWGkrKt2pwTLoyMyK8LO76okZ3xqQy/UwUr4LYsubuyl7Eh4pH5xzPZ3mA+CqyjkFukRyY3t6yMli8fNYzvf/2dt+z6n0s9QZkoi01+qlwScwUnGbZwaHW0a0fJoTupIC+WET5RArclSJNGM0zO1T+2KABIOOhrAdZgs66UtXAQj6hQtJPa/QznrvNRxQXYd1zOTSEKUAKM3bP5pwojvknSIiUtlFOnJvnFDQvTGoAIDKCuk2KcNF6DidcCXRz7h4N3zU4FeclbKMsfYQsBNLf3mJYzWHnGfDvHknOh7VYZLbPZ+GtS/mLrBxKWYl09Pm2Y+h106ayqpCYhvInkC1G225cEs2+Mz8Wrbej2I12Lco3O15YiOLCZNYdlzZzPoustEm7DkZKp2g7lDfjY+kNj5ua9BrH1bQollVqi5byLC9MqZHMvN0x3f2yiU8etWmQKAMHVMHrWW8B76R0KnT3Acdhi1jSBID6SqNYDUxbn10ms+55YTvEZxHmA4jnXb9VKK95m24NAvmN6hw3UwHQiwLldQd9s0lQdm9YvnBnofrk0U0uCfX1+L5RPcv1lUvR0mhSL0R1Y6GsiiXd+soKx4OHbpj7AQDggGLD+ZnqbbjPuH+jfrVF9fkp6ivBTxiCrYHq2mHyKjBlpTHpPnkxrgDKJUsKetFALVa7WMrNbfqqRj8DJldDlBhozms8f/4Ejy7zc1ZcHpVFIOBgbE0YVnNMX3qojJxI3YNq78EuFrdLpVnCMwNa5eCr0f5Gs0tszG1osVLwdegu5R+hnZZQDhFspbLvzI+FwsDXBZx0SWqjYacltNTJQzgSQFM5d2IOmiqvxkCpsL2KoK4KhQDA1K6Fk/GS1vB1hWFeZKAsTugO8wLdSaJUK98WGKYFqLXo5wI2WxUI7F6kCYOAsiqt4C3QnmrAy7kFWcSpjmApQKjb3jKjU5AdBPjpaW7Kg3wMOYgsnHd7qnmRQCZfWCvoVsVEb3eqoXoDUxj0CwFEnSro3qMoaATK2j0eh3IAhwC2ZvxGc0ZY1KkXoj3V6BaEufSl9CcazbmC2XqRKkwdtf2MMEwpLk7NeeD6NGif9WikV8QVzIJFTmH3REKAZSqZdufiVU0dUHhmIasoSgr2J+ZgJrG5IPQnYOIaOcfmMfDxx69SrwcggCsVjxeSmXbiYecOqjfYfRjwKoiasHexY4LzaEc72p3swXoWX2k55uE98A+HsAq/EfzCoYaxA5852Fh24DW+P6Qk5fde7zEuABzK+IQL+Kr5ONisdEjF7S72rvj5wFe9qynq0PYva6C61dyVbT/UDIb97dl8jxrXwrYvGQd54tzboWt26HZ+B2bD+z1vKpwTHfj8/rH29/0K+7ezWIz4NQ+8P9gtKtR4+zfvXRYX526DsZxnwFH+gxDw1IiODwGktL8AjMf3dRYn8uCEKeRVeUlEjs9BWce0eDYlKyNK0iWgVcwJHVzMsv8wTt7d9WbL5yMugC5PoiKOTw1+JNCjrCS082PujSlsf9eP/ODf9sfo5NiOcx1xzjygLEUgWhgvOZFlzMex/z5/BWJFCbJQBEAX+Wz7wbGBr5dLCWJynOAkP/7cqPvXJ3AadaKvalN15j72IISRieg1gA2Ay296LP/K9hjHc/5tsId8zt/x3v/OXT74IBYLACCi/+O9/8Nvehz/mnY8598O+/dyzscE59GOdrQ72XGxONrRjnYne0iLxf/4pgfwDdjxnH877N/FOT+YnMXRjna0h20PybM42tGO9oDtuFgc7WhHu5MdF4ujHe1od7LjYnG0ox3tTnZcLI52tKPdyf4Z3ITc7v41brQAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.19204807281494 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-08, 'kernel_type': 'untiln'} is: \n",
+      "[[1.45000011e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [6.60000000e+01 1.24000012e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.45000011e+02 ... 1.61000011e+02\n",
+      "  1.61000011e+02 1.61000011e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.61000011e+02 ... 1.67010048e+04\n",
+      "  1.65970047e+04 1.62110055e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.61000011e+02 ... 1.65970047e+04\n",
+      "  1.65150049e+04 1.61070058e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.61000011e+02 ... 1.62110055e+04\n",
+      "  1.61070058e+04 1.58470105e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.14300060272217 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-07, 'kernel_type': 'untiln'} is: \n",
+      "[[1.45000110e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [6.60000000e+01 1.24000118e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.45000110e+02 ... 1.61000110e+02\n",
+      "  1.61000110e+02 1.61000110e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.61000110e+02 ... 1.67010478e+04\n",
+      "  1.65970472e+04 1.62110547e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.61000110e+02 ... 1.65970472e+04\n",
+      "  1.65150491e+04 1.61070579e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.61000110e+02 ... 1.62110547e+04\n",
+      "  1.61070579e+04 1.58471053e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.4931104183197 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-06, 'kernel_type': 'untiln'} is: \n",
+      "[[1.45001104e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [6.60000000e+01 1.24001184e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.45001104e+02 ... 1.61001104e+02\n",
+      "  1.61001104e+02 1.61001104e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.61001104e+02 ... 1.67014776e+04\n",
+      "  1.65974719e+04 1.62115469e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.61001104e+02 ... 1.65974719e+04\n",
+      "  1.65154913e+04 1.61075786e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.61001104e+02 ... 1.62115469e+04\n",
+      "  1.61075786e+04 1.58480531e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6518>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.510759115219116 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-05, 'kernel_type': 'untiln'} is: \n",
+      "[[1.45011040e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [6.60000000e+01 1.24011841e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.45011040e+02 ... 1.61011040e+02\n",
+      "  1.61011040e+02 1.61011040e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.61011040e+02 ... 1.67057768e+04\n",
+      "  1.66017196e+04 1.62164699e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.61011040e+02 ... 1.66017196e+04\n",
+      "  1.65199140e+04 1.61127872e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.61011040e+02 ... 1.62164699e+04\n",
+      "  1.61127872e+04 1.58575342e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54822470>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.02294039726257 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 0.0001, 'kernel_type': 'untiln'} is: \n",
+      "[[1.45110420e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [6.60000000e+01 1.24118460e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.45110420e+02 ... 1.61110420e+02\n",
+      "  1.61110420e+02 1.61110420e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.61110420e+02 ... 1.67488609e+04\n",
+      "  1.66442755e+04 1.62657545e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.61110420e+02 ... 1.66442755e+04\n",
+      "  1.65642284e+04 1.61649561e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.61110420e+02 ... 1.62657545e+04\n",
+      "  1.61649561e+04 1.59526266e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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vU9OUSdHiJoyZSF2b+u+rF5+Sz4UPmBaCwFVQlvTRn63Kizrxi+TIifoOzPORIyv6MuiYd20NutJzdy14GOG8R7zZVNvl+Rhzf6DPgXc1LkafFxOtgiNgGAUYlZ9Tl7cjA//sJJvG21F5RmLIfgS+ut6faEKAf/RAjo01SJCWS3DKKwFQ/Da53yVHyj1+BN71oMZwrXzvCw7KKoAroEQ74mSXWyIJ+vskTyRHNPIEYdq054KvvPiafFUQpWnPl4CmeBpp2U2iKak/PJqcgPT7wRwXRwdBX1PQjxLBMJd+SL/Ty2Ds2lsjFTb6M5FqIp9u1+86QVsfFVHRPIy2YLWorKHckkjGfX8r0Q44gidJV9jV25jKGB5MWNSVHCh+EO8FlHWAgIZU051cp14jmzazA/s2rXgS3gUA3vQyOZtjKm3Ung8AxoUAz6oF5UifET6kycLiLmyEw+IpjDMzYzFSBANAlUlYsWrBaBY2OmCjKnouRyBqalh40+w9pK5rXxytmGgWWeMw/eFDmsU4gJq24DiAssKaByn3TR1pJlNRHqAJ7FgjELNZ0SBeolnIHzafglOU5HCG6VSz0AiQNDPBcliIfYKR67XtaRZ6jls0CwvTt+FX1SwUtUrzWYKlCzaDDqBwSdv3PuM2aLV8oWZBL9EsyGgWOKRZAKDlApm0WDWstjmoWdAtmgUt58B6W1i5YgQ2x5sp79dk8cKs0wnu4mWaRU5nNitahnRHTLMYj9UseBjFxWLTjy0+YjCw26m8Sc3iYKaQq/AMuprWFzrZNo3fWyap+9YszGQ6xXJUMtES70uziNgW82xXclkqWHYS0hBpCODd7v41CxupMWC+O2kWO9mX19YndbxmcYqGnOQkJzlK3ivN4sUp6gV3UWEuDqVwwzgzkwoKQHAYCXGpZCO1PwL1qjjVdJhBXT1k5GX2jn0AOcpYj/Ds2cFrPJa1LftlpuQ3KsbcmDoGy9+uWoUAq6Go81V+dw8uwP2AeLPe0wz2+kaHtQfTiQMbD6jWvq03qK/CArhiBFoPahqDg6jTxA99PSyh6rdwgJRt2cwBMiUCkHwrCZqeyX2dRIfowQXi50/2CG5u1bBu6Zluv5X8JmUl03KR35Pw2eeiGfBEQ7vlfDSfvXIkCnjPJosXyquSqh4iQL1LCPS29gyKkLNW/JKX6J5kmstRqaHWKQfUBC+yQT4jH7SV71P2clD0/HucG+G1HvKjxWbGJpDcnphJlh1q/8Db6Ntt4LQjhMM+ePAu8l5NFi9iltbfbkMoHjhg7zsniPJrx9VfwDbEhxxs9yHTsTpEO38Hglshq71PBMcBmVLVY6oZmQnlLfStOveByWk6uQG4U27FG5FhrCHudxBKyWRVeP0O4/peTRZ78WiOJgogL2HcboW4xiQHxX4ouR5ACQ+myIHqp9F4jTNrlobKtM3UDt+sgbZNnA3pXBqZaGb5fHGzhVvMEbGtzuE/+ggY+vqFaJqSibjdFQ/40INWKyAm6DAg8N/NFmgbwTSoibbZgBYLMa/UW6+kMm1TYvsAeL2RyMNQMjYzx4Jms6brCIl0pfnax3u09JrxmE2Z1QJ0s5EsxtaYEuMIHob9BLjIwGJewpJ6DFHpT7o+pzkvaV8368C7HrzZoPnax7Jvm7AgYwAMZoDnM4lgEOVktexEHUYZy2s1P1MUo22AZ2nMm0ayP7XdnVmYvK+3pSzR+OQZ8ON/Gs0TGT/2Dmg8aNsjrhbSrllAeJbuo5o8IYCGgHgm5DfNJ09K9MpORPMZuG1AVzfg1Af3jR/B8NEZ2s+uCwBu3oI2fZns0viwJyAwaNeXDFcA+D3z/SVycnCe5CQnOUreL83iWLFhOJManVdwC7S5Ba6dAT4KtU4sS3vK5wE0HafP/LfJBMxiw2mKLFe+ilTsRuHTzAxst3INuiKo1jDUDEr5nLtx35xirkJh3PcCGgoB2PD+eNgxUVNtvak1Akfg0dUp6mo3T1PlleNiYhIxs6z4JmysWIR8XYZpipnr8R1lv4xl6E2i2uiLBjQm3guLN1GnJEfJsFTtNQraVI+R8RoEbKWIV2tSpqzPvC3B77nv4Z9ciyYKgBSoNQxwSm+nz1CMBWfTJCduumdO77NqZi5WY4JrMT94s839dZc3aAHQ9SbfR9ruUrZxnQpPCVbO/VBwFnrPjpQPc7IAqvj6azWjNGgZSz8hu3GuON7u6mQ7hM/XMnoGhEQxte1Q9nUEaHp84LrNV6zodVyfqUQVEt19Pp8tP6ARiwwXZ8AxwFTMKzU7omkvt/sK10Dm+MgCNCIq+Tww+Ac1T4iAIJT55Bx40reKNiC+ouPQUeVngXewcJdpRnW17cBLzU4mHTYAroO+kfzsEqDLnG6bRtEcHQpI3Uk+nMnC5I1Y/ghFKCofRd5dEZAHuCYAZMJeTgljtFzUJKtqSxueDHIO1DRi/+tDd30jjEUprJeBTOdnkjJt+9R12V7km01BbW63OUWZP/1M9p3PZZWfzST5SX0W6w3QdlIDYjfhZZzNCpsUAL6+ET/JbifXp8en60IIBWWoRMEPLkxSU+p7k3JO0t/xbAl3vRbNYibXQFHQm7zdFc0kM2Ux6GxVkREDAM5WGcZsV1y72tN8Bmx3QvSiY5TQqzQGsPFZhPM53Cb5LPTlCwG4WEmafNeCnqawe9uCL84QuxZOJ46zFXjW5XZp4rPgtpGVGwCn++hCQP9Dj9B+L427J3Dr4W52GB+oz0I1DCAu0n1sHZgIrg9wuxHDA/FZzL+VOD6IQI3REs8W4K6Be3Yt4wEgfPUR1l9fYvlH5TWO8xZubYh42oTcbRwoMty6R1gWPwU//SLmhtiZ2ZoGBmVXiYYxbwtnWiRoTCpfCPkhs+3nVUPDkMOYzRUlFOGpOt8PJQaek5ACCOkBjAGstGmRM5lMxf5dfdprDuAYjCMyOTiHvrBQQUwX0sJBqjZPrpuGhDJU064fCnlsykAlQzcIJFV3DDJJW5NjHCs4cjYNORb1Hiir+og8MeVJVs0Gq4L3g1yjLhAZdRrle/rbrR1oN4C9q+4ZhQiMyXxUhKyaRkDmgKBdL/d1DKCw7+CkEPI2HeUYIprrIU8icA40NqDdALdOTswxhSwjF9OzVQcng4aAxpuJP0S5bh0D70GbNOa7Po+ZW/fonndw2xLJosDi4MzkTOm+eZJ+7Hp4o6nSF8EMEWBLpV/Kp75Q+sB4XwhMdOJwuZGiSgP1pJGiAATIC9G2YKKicaw3QCuZoDl/oRX2qsywhKT2Nk2B66qZ0bWFhs1sU/YkYpZoCyDEJPMOZDka27R6qg1v1OccTdAXXF/CtiurNiAPVdNIu3qMzW0IIZOt5Je+a4tK3CQ11rtqBefVXFa+YcwrrEw8KcKieSgUiskx68oLbL3x+qJONQtn9mUWH9C8K/dOcSEmRyYuO3kO0uoOpFV9lImGF12OTFCI4FmHuJzBr5MvxDvRLHzSLGBENQsdg1mpELZ70GG2UxYvhzhv4AGEM9nmhpj9E3Eu9yF2DmB5ud0QMJzJdv8saTbeyXgCMvZtA+4ameD0elczbL/Uwm9LFfc4a+A9ZRNYx4G9A4UI5wnRahamlMPL5BQNOclJTnKU0EGgyVuWC/eYf4L+ndq+b6XIjj9bAcDhAkFJeBilgretOLYuLMmHgCduPj/cmbQq0mwmK82uBoEp38Revc0JOtQtl8VcehkBCZWVgBbz/faBoq4nbeM2Cjib9PUikNuepCiBW63q8ZoSzeTNVGfDqlmzmNdOT0DwJvsdRbyFGvCQcAilGtekH3sy0SYLr0iEU7+HjaIphufqqnacTwh7q22GD8U/elBoD5ODlcexKsC0h/zVZ4YET0EXqYq6jQpl04YQ9X4bR6dbLsXnNEV0akRqAnrjfqjuGWLE39/+Jp7Hz4/yNr+3ZkjllZ9IVUKQzKDozXEOLysFAAMm2iOjTe0KUMtg71PVs6NLAeQTmIfmtkhGSnPPxCRKLDNhmaJkkri+vx/C3sX88GSRKO7zNuckzT71l5gl3brxxcxIoUOeXDOl6BP1fcVDmttWP5KOgzqY02RRvYSG2Djv2zTlPoYg3JsaJVHzITkRufGgRIhDff9KhL149ABOSXWck/T2zbaMQ9QQqUlFTyat9jmey6Lo1luAWfqlz7l3cGnfirD34hz84AyUjskyhsPRkO3uC0DYy8AewCFIgs8hePdeScEQQPCFXPcYCK7uo/TsyedhHZcIMeMvAAD+eGdQLuUHFG2FCMr1wKE4TlnxHZHBugq3XYUJsJB1au8RYmwnR52E04TLsSBRxWEZCytWcuBxDHmSyP3Xl0JxF3ewkyuJiksx57SlATlR6A3FSasvKeu1GXQqNR40+uNTCG4Rid7opCfPEIcIsjgLLvR+AGRMtHzFOJbIy0ZefNL6H8DtC0wIsiAMxcGZFxidLDJfyeuH29+PyeKucki9nkY8XlK+sCpTb1i3s3qq5DnTKMyRdUMqlmz1wGsbtqQcUKmcGbaeH3aT15L7Hu+tfOEeA/QhM6QfbjdD2qaOhqRPDoZbNNDhcx0SA56roOq5e2ZctB8KT9dzK58qJCQt2wO4TyuwAqJ2u1crX3h1XZkhrFR9k+tju9JnB3Nymuv420kuY0GokPbY+3uzliiPpdrTCOCRZsipfOFJTnKSNy7vt2ZxG0pzWh0rIw0Ny9XLyhdO/B40SazikLAFvpgTdCefxYQyzvY9ObUqWHQud6hAqHRrOEpo2BZF8v7ltH3Aq/ksZrPDjj2LukwmhbV/yWphB7IiK7YtV5Ko7uSzUMCZqUuSyzwC5R5aVGYIomkoJaJqdTF9b5riDwqzVytfeHGeC/1oKB27HqQ+C9W6rFnQphKQjkQ70KSzmw2U0yP3yzm4xQGfxWoJvpj4LNQMmaKHiYBh+AL4LIDaGWNy9uNWH6aShWrVfs5eZQYb7zq1HQB5qfMN7gpXpi1ZB6A8dEqxttsd9IA7fWANizfNZznr1NKj5fwU7ZP36Tjxhdi6p6qGarTFzWYyBrYYDSTSQ10n1bksQYyyY1vwlPelepi+rCkrU8c5Z7N2XQIElSxb+/JbEy1zcNqKYuk6OIHbpkJ6PSiYCpqX7OHs0E3jXGUgK5gpY0QK4M7mzHCKDFRGp6ri/Q5omyqK5GazlG+RXvSzVaoEF4Wvcrur24gM0meiaUCNh1vMM0ANQAF+RbPNgAizz0KdkP0g2bsJ6xEvr/b5PAC4i3PZv2nMhBdLbpK237XiP0mcJWQn8IcXoOt1cf4CwLPjfRnvz2RxBxH69lh9lxXBrIgJT0/U7LMTcQQ1CXylbc5ngszUgdztTHq80SyQHnbzouvLVPVxMS/IQ902SSHPEZNtgWNrzUuaz8AbeZkZ5QXjYUyp1LOMvoRqVyYFHoA8RPqbVrqaOFbzg7PZysu/WhZ/i2ohTSOaiRLurhbAzSav7FnGUdo5EM6k+QzoDTgN4j/Itr46PZOjWSuo5YkphDJGWq7ATKIAwMt5TbKr1+CdIB9nXfU7rZZVNIVmM4lkxCgArGA0UoW864s56+Q6r9eIX7qAe1ZWcE4p6nyeQr3W36QQ/wScon4EhhFxkaI0u/4gSzuWC+nTelueqfMVxo/OqpeYZ51cq95j1Swaj9g1cMzghQHF/fGHqFlMxSI2p2Lj6NNkJz1c64s4N1GBCYiuTAo6izcJnacPv23Tnku1A33R+17Qn5q8ow9emyp321XCIiz7oUJVZto0y31BVKNGAdBOtlHX1lEBPadFR44B1CS1WvtrnGYW2cnbnbwMs65EhLxBVyZkJQDwYiZISEVQ6pjrSnngnuXx0O9AdS7YkHGMIJf62bUSXRjHklfTCip1f7I4QBuXVHoCEjrTmLazTl7edZPPxYuZmAVdK+fQthtJTsuOyIWci7Y7DOcztDtTBKqRZyGuNO+m9DEqn0XrwY7gtx7U+4z2bD9v90LNABCXc8k5iTGjUHk5Q/+wg7+emf06OG+cmgbBqeeOS7Og3CEp8eTgPMlJTnKUvL+axQuQpZXPQinzbazZbg+TAkCKoZ+Goq5valo1bTN91zaz48uUSuT1RvY1qcrxQOEZMpwM3Pe5lB6HAHr2PH8HAL6+kbY3CScDyYmRAAAgAElEQVRg+CjiZgs3LSUAiLq72WRNSHweiXlK21UNQsfJqrwxgp882/NZ8NRnsd1K6NbU8tC+3eaziFfXxWeh2ae7vvZZHKobst0WToqnz/O+bEOEOr43630VXjk5ElOWrRvikrM4V0AHxFEZWRzItqTgpCIZbjbS7jii+9b3qjbIe2Ac4a80E7mYoo0z5lZyRnKMaJO2dchnAQgMyTkHNnkztNlieb0Bnl+X9rXfaR9nnNK8mIFuNvBWG7wDDeT7O1lMzBCbWFalqNtU9L72D0wLAFnuA5dg1RnfcLaqPcWGqs+eSwvRZPV9vQGdn4kDzlChuYtzgYrbG29SyPn6JnvLeb3J1b2tsw3XN+K72O7ycTEEuMVcaPgmD7NNVAPkYULbiqmk5o8+pMmJqLgDvrkR7o7HDzNAKGdjTs2QixXc5c2+GdIP4Jv1QUJZd36WofM5SrBclGtIPoH8Iqiq3UoGJzYb8THotgNmSDxfSMalFTVDtjvwrBMkpPb34QMxNz5/KhsePRBqvmGUdPfLNAGob4coOyJ5MROz4Nk1+j/xkVDbAdkMoU2P8CAhTvsyHmHPDBlB/YhRzZBvHSbk5Y8fI7Ye7qpEPng1x+YHVlj8UTFDwrKDW5cxiMYMGS46dE+3JUWdGfzBli+02sREsxCGZ1fQmy/TLPp+rwBQ7MuDotGLu2oWuRCNeqQHYbzKN1ijKfesWZDRFjQawmuqw7r9UArh2FCinYjTNcbdTqILb1Oz2G73qpRpzkTOa3GEGFKKu04s96RZUEzRoRjgnjUV2hPT0PN1I3yh6w26yPevWUSW8xmOU7ps76RZNJ82wHYHb1Md+i+CZnEPkus5vJHGDObewLnfUOt3k8yuNXH0UiqRR8U8qvpn2Lrk+NeHBN9JLAYm/50+tVwBORBxXZ/z3vslGIzMbWJPPWX7eltjZs/zqnB5dcK/orxXk8VLiwyFIEWGrq7M7wbWbcX7XKRYSwoeLDKURGt+lNJ4pk1zrqx5aNRDIyAp/0AzX8NzUwhJz5GyY/V8VdmAyWoe+yFjCfJn+l3rdlYkQMkEmmozWVNR2LRiLhRvonyOyUyYjktux343bFjTyfHW2im7XZmobR9Ve1EA0ZSGMCpGpi2Zl7eUL5Tw7y3TddrXjk+02ioAlwhuNC8o+3ksr8hgoh5EcOdnUmRoqg1YIJwFA+YJKPVbyxcaHM1BWW/kRV/MM84iPn0GrDfVMcpAv3c+AHR+LhB0C5q7Q62YUzTkJCc5yVHyXmkWlWNHIcG6EqdCx+HyEm61KmCergXvdgKvzja8rASxH8SrnZq0JQX9Rx/JF62gfX5WMR/Hp8+kbbWXATnHOIIW8+zgjJdXcBfnYmuiaBTND/2ArMC2rN2sk/g8ALq6KbiB9RZ4lBycn3wql//4oThBu07aUTDP9Y1wMjRNYbvOyMpO6nPoeF5eCQak76XWCIoDVWHV6vgMnz2R8/7oDxfgkjKPtU0Fu44PV3DP15JtOS9p2NQPwKb4IWxyHV2cF0CTOnnbJqeH53otbSPOzYwlmIPWWxnnP/mvyLZ5K0j+YZS+6f19MC/8k2rRjJJV7LY9eNbCf/Y894kfniPOGzTffZba7cDLGWgI4NaD1unZ0P51Degm+ZyW6Rq+8z1sfvrPYP5duQ52hNh5NNc9hkdyL1xfxiEkDs7QOYAAv4vw24DdIxnH1e8+KREKo5GEh2cI8wbN9y6BjfRr/OafxvWfmOP894vTc1w2aG5GKIBFOThjI8xczXWP8SxhepjBv1Nzw7xI3qvJ4mg5oMZO1alck/I2jkHlntQoxm4nKdf6u6FvL6dK4cq+OJk4BCmCM1X/t7vESVmccDwMBfA0Fh5PxCARiMjl/Ep2M0qqflXdfJS0ZkuIo1JZpAkgxQbiXWVHVg7l5GhUKnlpWLYpCjJds7vaysQwFpi6jOmYSx3Y4xFZ+pKiKVoIiPqhZJ6q83NoKicpAbLPMJQ07hglGpLgzhY8pW1nGz/xdNIwVqYFmEGbHVwsY0sbznyd1PgyDgCwS9Exjejo89UP6J72EqUAAEdwXQNa79AoPWEi7CVmuI28cs0s5ddEBvUjZjrWu77kjOizSwR3tYbbNqDNLo9Zc7nF4rMG/so4bfsAtxmKv6VJppCnzM/pejMG4/FmyPs9WXAE8BI4qiHsLU68I9yM1rZNfAOSkn7E4E1Tew+l+dpIjHKJWkRn4jcobUzS4fX7of6onT+dKEOoPO/MKacimrYzT6nbvw5AchYm7dN0nxCkv1W7XPpxG0EyTybgCR8FgFKTRV/GVJ9E2kgTGqU+Jg0yT2rDWPg7ufgEJHJk+CV0bGJMnBzpGsYxJ6NhrDVdSrDwHNFxxR/hepMQF8WZTGMok4RG8FD7EACAYgSNUXg6dUyYAVD1PFAiHLbjQUOA3wVQ4LIvCZ8IqV+KNR09EfaGUEdAXoBnmsp7O1nsEfZOxdWOor3MzpdFPfLKU9oAubIqKtuWIQe+c7QjQcsPesxtf6lkdNJ0u/Yrt+myCXEvMn2YlRWr6g+JpmGT/xzKvVBHdYaWo2A7UPZ75Tqh9pyT+84anVL4+IicH8LeVZXS9TqqXJnX6U/6zs7t30eHpGVqXyG+eecAx4WbRsfWOeSCK7dFP0iul83zk7WqdE62219TTg7Ok5zkJEfJe6tZvFAS6AVAWbFUfVRRDs/buDw1TVrVw66Tuh7qSNQo3USbIO/FdlUK/XEUZKYNTSI5M22R4LTtYCmAvhdHITOgEddZJ6qzd2AeamRp09Qrha7Qs1kh/AVkjFKCXEZwWnh1CCULNjkaJUlM+SbSeLaNUOFpWPdsAXedxsZwNpAba5Mla0QxJY0ln4OiPskkkilQqPFiCmmIciFlB7jvs3M4c3+MoUq3DqsObieUcpySqWj0Uix4N8rnts/Xz4sZ4qyF12eh8TmRDI0HbQwsvhVez6yFqKN6vcb28QzzZHKwJ8SuARwwXiQH5yihb2IgzJODc+bSbwy3CxgeyDj6Z+tSCiCPI0ki2czDa2o7gOHBApuPWrjtLPuOwrxBc+OzppITyRoCAsPfDAgrfQYhSW9HymtNFkT0LQBXkNdxZOZvEtFjAP8TgB8G8C0AP8vMT1/nPHtiadW8B2OoKochpixLhXtrvNw+x/qiqkNOH2ZLtOsIYCqTkGadzmb55ePtNkGyE5+FKw8TAbWq3bWIS/WQD+WBG02Kcto1e/nbtq6Uho1MHCkbE0CBZS/m4GWZLLRiNgMlSqL7Oic8Crpd+72aAwqZVrRn20h0IDnDwkUn9njjEefFs46dE0eiyWyVc6Z6HOoL6VoxGVoPZ7ehREM0UzOuFmJtbLc5AhEXrTjr+hFx1oDSfNw/mqG9Ti+KmnVjBHtCc93LZPK88FnEZYewaOGfJbNpOUc4n4F2QV5M85zFrkFcNNlpGc6lL83TFpuPGjTbFB1xhDDzAAG7L6UJYFsWsXEp1xU6ST1otoxm47F9LNvn32mBnZgS1oQID+YYFx7z7ZgnrP5hh/XHHt1lW8bg3KNrioM3dCka0kmWcdt5DBcGIt8cb568CTPkp5n5x5n5m+nvXwTw28z8DQC/nf5+K0I0qTl51EFHDIHWQn1D9VX3be3XQ9bdm1h7NyFB9d9Lj0v3wtZ0zfKmUI+6yqc5/eAY6go7uZb8/Q0b4jI+5tzar3xO8686zlyD+hzscS89L8p5Hb0Jft49uQ8z5GcA/FT6/isA/lcA/8kbPcOEnSmXx1NxJOSkGrI74OzUBDKtus03Gwlh7uWkGNMmhIKW07Bl30seh2ahqllzJbkd1glIzHAptMdKyw4Jj7rnNxIhyRmFO/F+9xJKy5gKQBKyttv90KlliQaE0LXvM3lMPhaQPlhSWEUxPr0y7NwJTbntRWNK19GFIOr8MMLvTJh1lDDyHoUfR9B1STDLpl+MJXSaHI+uaSqWMZfCq7zdZa2AboqZRG2TzaP5dgDtUqZtUq8pVSOjEOG2bXVt7uk1aDPL40j9gGa9zWaIDZ165+BN6LTRhLL1Bhff2qLRRDLvEGct3M0Wy52GgzUqwojJDIldI89alGhKc51qp15tyrjrc+4cmu8+R9M2oMubPGaL7yxBfIbZp5v83M6eeNBmKA7Uti5fSJse3ZNiOvrd2wudMoDfIiIG8N8x8y8B+JiZP0m//zGAj1/zHPuytyq7CjQEQGz9EPLnnqidGoKklnet1B41STZyKuOzcJKoRV2bzQLa7UCzriSFKaAmEbtUHva2rUyPXMOCd8X2f5r2b5vsn+BxLBGGXS8YAN/VtUSAPVAWhkKwk1mtDVcjGVBWTsFeziXLE6hBWY3PIbt4Nk9JWK6Q7bBMzKQTZBovOWBCqpOKKcMZu/xFoKx03TpGPE8+iyGAuzJZjBdzeC2MrJNuiMCshdsNiMsOflMo6Hg+Q1y2cFc+n7sGZRm1Q8sHqrm2VHDdNXaPO7g+gd48Ic6kPS12rLgGYmBcJPMqgbLcwPCbgP6hjEn7eZsp9/J4eYd4thAAmamzO1zMsfnIo7np8hiEZYOmlexdYiBmUBaBItBc+xqU9bZ8FgB+kpm/TURfAfD3iOif2R+ZmdNEsidE9AsAfgEA5li+ZjdOcpKT3Le81mTBzN9On58S0a8B+PMAvktEX2PmT4joawA+veXYXwLwSwBwQY/vFuC2moIt2mLi90cjOJlBURyVFYLSxt5Vk1HCme2urHwhCPnNFMG53iKTzmb0ZC8rbyIxId6VPmwTglSTfHZ9NqeAglkgIkFCqnkxHQMLykp8jlXNEVt7w4KyFMF5ta6T2hLAKMf/AbhnN7JiGySrAJlCFVHK7OIcBQauztVtGs9xLGaR4eBkA8rCOMp1DkPmkiClI9CISFpV2zH1KWkBsm8ymZjhLPAtRribpL6rabLdwe1S6r1zdYJWIujV8XNJ+4q7HvPvbeGe3eRxdfMWdLNFF4r5oQA0r3wWs1YKNnsCDQFOTZV0fm68qRrv4Z9ewTUeuLrJ9719ssaqdWgui4nqbwa4bZ/xQTlbN50H/QB/bclvjse6vPJkQUQrAI6Zr9L3vwDgvwDwGwB+HsDfSJ+//qrnuPXcXZeZqqhNanrK20h9A7oG2EV5cHc6cZg2VlIuDlshmKXzM4Era67DepPDjvkF61pR3ZeLwpn57DnowUXmo8gv2qOLAt3VyWLeSdSDCO75TanEvd0hPL6QtlPuBp+vJG+iFQ4CmOgNrRaiwiduhtuiIS5xamKzzcQxaBIh8DQaktoKX36YXwRVh3nWCKdFetGGR3M0lzu47YiwStcQGbQd4a5KtCE7m5tGyuwlE4CXc3E4umSj41A0JL2Mq4WUBuSI8NED2bZIleGHIFXJU7/6Bx3a6xHcEGIKnbqRQYHhNwPG8w7ddy7zfQqPzzCed5jppNu1GG005KqYLEGjIc9lnEaNhgwDnvypFc7/IPkiGkJYeHRPZ9h+WfbxuwiwmCHDSl7eMEv9GxjNlrF9KIvEoyGAdkFg2mp2eUI4T9GQT7o8ad788AWefqPFo98tpsSwdOguQzZD9DyxJbiR0V6GKhoSvv12CHs/BvBr6YFoAPxtZv67RPQ7AH6ViP4qgN8H8LOvcY6XS4JVa0UsIK3ULz1OoccGVcecnW8cY4Fso/x+574dhHBPtqf8hcxYnbeLo626nmmb9yG2n4AkbTmutBYaYzVeUPi07Z9lD7PXzCz28h05KrLzmZHuDRJ+Ifls1B0TOd/SnPvADBrL+BYn6+uPZ5WbwqJJVMZ3mijkuss2EEBR90/9Sd95LFoQ3bb4sxxfUYKw+WQGacnJN/DIfJBV1KsK6KoukoO7SBWy+0Hqb6gJceAac0VuhTNr7Q1VhxOtfsXPSE4yV6kwhms5uCm7lPJayCkOTF0Wkq7sVqHQ3InaX8BnWV1PUYn4/Ap7ORhTlvPE11DxPhw6BshZvf78fEKgY15oCzv2KVqQC9ZI/gPNuv3CyHslEaWf8dnzMgbTcKrdnsw/n6gHC+s6VTVU9fqEBrCwt/N2l/tO6XnKpkcCfAFAfPa88IQ4t88LYbZZ/gn/8Veqa9RM36qYj46RZlM3XjS75MBGKoycM069z4WL0DSIT55KXzU5EYB7+EC0TGVaB8T00ES0CZOYZASHit3s/7j+dTwfPzsq0HqCe5/kJCc5St5fuLcjkEWW6Oqcwn22ulUm5jVCXbdfWtCsqnQuWog64Wg+l5XY1tHwXmDdikVoGjgl3dVQ5vUN6GwFTixOWrDYPX4obVutZtZlZCZtdgWqvOvBaWWB8jZenInPo2urGiOciGt90xRtw8K954WfgK9vUim9UsSIdbWawL3j0wSy/eqXy+oWxd/CWmAnSVzN4dY74ZOYm9CppoFPkpcIKQSqTuHkn/CLObTyfb5/Ce6d728iLOara+DLj/Px6pjkWZPV8HjWwW1HRCIgw70lO5Y0zLpV/wQjrgRC3XwqWqufzwRpOgZw4+EMZgXeg9sGTvE56m/63hOs/+wPYP5d8QVx4xA7D3+9q+HeEBMjZJyFy9v8dsT2y7Lv8g+ugCCmca5t4wh0vgR3Dfyz6+xDG//k17D++hzL72yzmRFnHn5dylZauLfbBbh1Xwh7AfA/+iLyWZiXjg3pLCdgiyWiJSLEisg37rUBQ9wK+PIS2X2IUJXRAzKJri1TiESuKxuS38SUycsvj4nMMFBAP47EmRlCwX9oVSkD/pIfHNAPFQFuPo0hBNZj1ETSnI1Dx0i303U/vzKcHkINV7AQ6SXXvu36kguiXBEp5wJIGBYSuLytpJW5IJ5fFro/Uw7SlpHEZitjPhTnqVWjqW9yuy7VCdU8DgCSrr3eZhMzv+RjgLtaA7u2RLaeX0okRa/D0h4mqH/eltqP6zUWf3QFukz32zu4rgVtdmiVPCdHdoIAu5CiIcMoi8EwYqHRkG1aYNqmsKy3DfBUTCRO4wEA7R8/w1l/Bne9q/1BGr0ykTx2JEC/cURjFtYvDGFvhbw0mgWACt1WDkjOSea6rKE6uazvQB8mnUxmUnezpCuHolHkySYKt2fTlDIBG86lBgEU3oKUmFZpM95VyWMZaJXCfWh8RgiqRgEvk0OZnAZJcjLlAPNL2HV1bgvSit33RePQuUSLCCsoS0sizGf7CE7nKn8Fzzp5kHPtVlSQ9cy0pVoGc9IYUgNe9qXVsrBn6SSpZRJVs9ByfDGW6EDjs2OSGw/lruD5TM7tDXzeOdFqkrZQhYW7Tmj7dayWCzmHIjgnmkW1TSedfsB4MUejY+adrObMkmcDlPKXzJJkBoBbV5yQW5ejK926F80iFg2NQgTOVhIpSpM0AMTzBYaHc3TGGcpdk8lvLOiKGweXxjIDAAHgs7cHynp7ciiqACQClghmqiIgmaj2EKsWUDAKABC4IDANwlHar6MWSsybHzp1oE3wCpbUNjsReTDw6liv8ttdReCTtY5kylQFgEc55159CQvfRtJGlMRXGfgOHWP/XG9vdZxq3ygVAuaxaCxK5kPOlQkrRUA4RNCuL2Q66kC0NUZMFnGlWSTCGQ6xmCy6QHCi7td21QxSPghAng+FcztXFokQxRT0rjiR1xtJG0iaBQ5oFnnbUDS+5vPrHM4EUWbZIjvpAkBk+EbNAp9XfuoHtGo27dL9js4UgpaxwkSzcM9v0AFw15Mq6rro6f3Q7bteQu8GxTolH3qRvB+TRQojVaIve1a/a80iP3jQnwuACcPwUs1ij6AlVc/OHuzNNlXEjlWRoWM1C3Ttfg0LU7iYt9u6D22q6ZnMl8ydqR5wjUqEQfAe96pZGA5IjTiYsePFDLTr65dP1V+lHQQKaxdHoOmyyZO1iDtqFrmvmg+iBYw13D3v5AUzADKEKCr9GGRfTVFXraRtMqflq2oW4fGq8LklXAqtXdYsbPiWs2aRJovAcH2ba53SzVbCp9GAAYnELzbRLPhsif6jFTog+2249YKTSZNFhnM7Bxpmr6VZnKIhJznJSY6S90OzOEamDk6VbG5EkC6qzkncm1ls/AM4iwo/4VxxcFreRZ7U9ogsWabDCNoVnEW09TpU87EOTlUF+0H4KLQPSv5q4+dZY5GapYp/QLDksTvEhGqsrslUotKxYa3wZUsdTo8x26MiUXUMDvl5rm+EDGcci89C+UbJlfKExvnJ16Vqlqrw8frm5TiL9TrjLOjqKnWqxn5k01G77ryYAkjazW4n4+AIUB6SMYiDtvEFZ3F980o4i+b3PzUwekra3AB6NvGnmVoiml0r0byI9nJWjQ1MtIu8E/Z4IkSLs/juZ5hf3lQZ1xxivg/gaAh0nIzDBGdRZWu/RN7fyYIcKoorGzo1hDYSAhRGKVt1i5oWPA75c6/5RI2PlHWKtpMUdVPDVMyGkmcC70FdV5khcbOFW8xzWTydXNz52X6KugEL5exRyINLq4VMbjcJjr1aJtCTlwdbzYvdDjSfw3m/lxsyNUN4vZGH0Zgh09yQXAoglTBwjx8ednCaFHWedeJIVG9+ui8YQzWB5Pvh03l0Iu5agAheyxwAlRnCEzOEd72EjLUerJoeakqopMgCvEPUPoSQU9S5aws7dxOFKWvewj2RSci37Z3NkPjkGYYf/hjN5yVFnRO7t5ohGAtCV82Q0Pni4OxHDA/keWy/e1kAgnptzsHNZxK6vbrJkwh/9cvYfnWF2Webskg1Dm477js4nYPrx0yIlOX3arP1RfL+TBY2YUs1AgBRQ4GKfPPiwMl4hg45FT3oyoOC0KSuLaupXQUVgZk4B9x8DjZh0nB9A6crTj5XCzebJaYsGWQXGbRa5fBYnrWbprb9Abk+fbm2W8Cnm9b3WfuIz9OD2zSIV9f7hZFvNlI562xV7H2NwJi6JACkzmXbAttGJiPtg46FQYy6UVCAbOnvTPQip44D4IVGQ4QEV4ViFM2rPzA5t63QDJox4ouzQmOoGpX2S881n0mSnaPCHjbrRGMYxkLMC2GvcuuJhsLJd7DeCSbjc0PatpgJ54Ourg/OEVdzwWTMvIQktZnEFuauUy7LcgYQwYWI7YMObquMY8gMYOMDuRduFzL5TpynFPWURt5sRrjGIaTU9U4n4YmErz2WeiSJugAAwsUM2y+1aC/LpDaedWh8n5/vqJNF6xC6BdrLAeOqvPbx999Obsg7E5tJemt26cQs2GtDnXCGFMZCaQ+1ySlrkYYerFEPdeiF2vPNiZxmCqfPj3I/ZDwD90NOCsvRFO1P7/Kn/s79IBOFLdzrqKpLAqDUJomhTCwmGgOOBdil/bvZ7Jss41jqeUAS1DiVCqzo9fshZ4hOhS1Zj57Lu706HLk+iWoWQHJwcvHiD+k+xQjsyrk8UByYKlq8edeLk9NMZLTeVrVLaDcTErMxgENbEQnRMAovpvaBOee9zD7bCGYDkMm48aBtn18um9mZHZxNCh/3o2TGKofnZnuQ9dxdbeEaL+dPz1jzbINl5+GfF9PW9aGqJF+iLw5u2aG53MINJuv0DtGQk4PzJCc5yVHyYWkWxxQdmorNlNQY/mQ7gMIF8bJaFgqWqXAfsdj3eVudCavn0HAic8k0RIxVcaDcH9tP+/s0I1YLGdkiRrYPgLluLhwTh4oY22JAU8SpwT5kx7IND+s4HBLTl3zdYyjbcobqBG1rigBVFAQJe1LB/Iex+FvMeXOfR1dpejSmMGss58rh3+DLsdH0Wx2cYwBc2t6PRcPKdIVFW7BmRSmsnSDdQ/Kp7IyJfGi1nz4PqV23C9U9p37cewak7144M8YAGozpeIc80g9msnhp0aFDogVnDm1/VVFnX925cp47pl2/lljaulsKGVGq9m2dv6XYT8lGJaI7p4y/tuzRIxYnqq30TYYm776FHUlad+OBXlGgpq8G5GSLFr01uQOJ71S4qR3Vd5UPZrKoxNYCsfVBrGh6N1EdaktCBkwEQJyWQ5/rgeD6prRpzkVEFbgKwyj8nWsq3A3Afp0OPYeSzSTCHt0nb9e+plok1Am/Yi490A8SkdG6JEDl4LTREGIWR6uBSmMYyphwLA5GTbFeLoqtrn1v21LPA0A8XwkHZ4w1CKwXhOqhxSpfq/nOi1lZabOD0yW/UEk6oy3JeKUx4lQ3ZFoYOV4s4NYTn0WI4kNwDjzvQOt1+W25kByNTamZwssZMATERSvMWgA0V4M9wV0nx+FyLuxT2x7Dl5ZodcH3JP6BdY/xoTjZncm/iPM03o1MgG4X4HZjhnvPnl8Dw/7zGs8W4ji9RNYu4oMlth/PsNwWWsqwauFvTCi1VQenx7hqQIExrkzEzB8/cXyQk4UNnep3DRFm0VJ6WlcEE1Vci+toFGM+k1VFGbA0Xg7U5/JeJgp9+TYbQVQmToocm18kollrBhkmK9r1VS2PzHClRLNai0SRoPpSOomo5Lokpn+2LgkAYcaetZJgpojDTGOnWafpOlIgKZ7NMxZAVWvu2ioaMj6cox1K9KTcF5mgDz5+aTz0OwCJUug9SeFUbr1EI1QTWirydAdOEZ24aBPyccy5FgDQP5qjbeuVnsYoWaDOIZ51aJ6WFyWeLxAXLZqEcYjLGcLZDK4PCHN5saQTEvIMM59fmHCWoiHPb7D+SoezVCmdG0JoHdrWY/elxJS1LX0cVxoNETavdh3hNw12j2Sf7pN5rpliZXwwwzj3mI1RaPMA7L40x/VXPdrLcs+HC4+289mTbuuGhI6A2KF/YCbYt0jY+0HJXuXwN9KoqvRvR00+SjJN1ER1fh9lks4OoDKbyjW8w/GlF9TheEWV/rXkVc9J9Frj+B4/RSc5yUneJ/kgNYtcQAgoRYSmQCCbdZo9/kULUHh3Lg6knBQ5CYrr7+lc5BPD81iiAbTZSvzero6XV/s4C1MEiG/WJXNx1wu5ru23LVxkzavEJu4UIg5kQJstYgQIWlOAUoNkeiLhHbyXc0fD7elIVPvPLwsGxXrq0WgAACAASURBVIDZFJ4MAN0wSv8jw1nEaD9I+4cgxGk8AOTfnUk6Q9NUma06vrTrJWoSAuhZAqxd+4yzsCUG59v+IM7CJ5yFu2kLrB+A+/wSrvHgG4Hmu7YRPokQQMuZZHOm8aXGVzgO2vTZj3PxL64LuzcR2oSzWCb/yTE4i+5pMueeXR6sc9P+cSvtmozRxR9ewu/O0H1SKCe7J12Fs4DBWYwXczRPN+gW5Z5pTZNj5IOcLI5ycCZVlryXvABAILQKjTbU8wDEackm61TbBupztVKUOENxlaPCezFz1L/RthIetTe+aYqPoO+Lk9QUHMpmTdNIQSPjkwEAJiffW1PrVFORm6YU8IEgKnNxn8zfMZi+1o5PAqpiQFMHp6Y7x+UcTnkfrUMVAIYeHPdtbh0P/Q4goUXTNbRNiYg4KuFG50rBZXWC3ubgXHb7qrI6OJklK9Xsj66V8bou7fJC6riG83nxWcRYKntpfxedcEcMI8bzDu1W08mTgxNAWCUE5wsdnL52cHbdwck2LGfg1sEbpHNctOgfNmieF9RuWLXwdtEyDs7+YQs3BIzLST3fI+XDnCwsx0Tk/W2ArMCWFyFJXulN3Q8AIE2yOdS2/XsYRTPR2H+IAtcOoaoBmmHP1sEJVKjNvO8wFuYuXc1Tf9D3+VN/574Htk3F4sXKSJXqkug5CEn70XFI+SqcroctZDwysN4UjcXU7rAV35yjkohncRYhyLUcWBkPwcBpXQiJydLxeVcR6mIcpU+JBoBSrRBOyFIVx1yqqeUTs7SXEJyxQnBuZMJRvouEjqQQ4RuD1owRGBLhjiJOxyCRmmFE+/ka7rogONk70G4oL5fBWbhNmiycq3AW7S5plBaZa8Rdb2Ti3PU5H8b1A+atL+hRAG7X1lq2al6NFIz2zzdSagASLcsT4hHyQU4WtiRhVabQjrGGTq1zz764yu+gD+ByUZX7w/WNqdlZzqVJZ7mQTgjCiqWrtT78i8UeeKsqL2iZvIFS1+PJs9wfCkH6uS395X4AzWeS67EthD1EJDkTNjoRE5dDCOa8RbPiUBLJeCfkO1DuT6C8sG1TRUPiwzPJO2HOfJoAJLmM+XBuiI4HkK+bz5ellkjS2BTuTS5N5rNWVP8xZAZsnnXpBa41i/BgP3RKQZKpaL0TrcFkG/PFmbzwau6dLRCXolnERVvzULQesXGl1OFyBm4c/K7H9gfOMcuMYbKKu3WP8ZFEb16aG7ILGC7kPiyu14dzQx6uJDfk2Sbfl/FLK1z/0ALnBsQ1nnVorg/nhoxLD+IVhrOUtMdA/L0Tn8VJTnKSNyzvl2YxpbSzP6UaGPpZth9OJONR1GHu+6za8xizszJXUVeHopYgtKX+DiWS9UPF5JRZwBPdnqao82azZ4bY8oK86/P18naXK4Xlvqo5sEX+1N95u8vqOQDksovDUFdRV2fjOBaTYpcyOMfEc5H3Fc3CXV7vmyHelbKCEHVfU+mxLbY8TykG7dhtbIJagXjnTFT1FWWu0aTNbTx4GCSlXzEoqRzhFO7th/GgGaIJa7TtEc34uMvrVBsm0fU9c/CbDggR7rpkd2Z6Ol+o7jSxjK9vMP/OFdzlvhnSHoB7q49naoa466Q53mwOmiH+s0txwCqxM4AmRpwx4J8UrhB/XZsh3pghbUqd91dJG4zIZROPkfdrsniRHEBhHnMMERUHJwByx2fZHW7TeOyBfZjyu8ADuITInE6ySqhrIzLKJQkAsRRVYlvR/G2Jc/V9TQQzGtnJ+3hfHNL33h/K6fAVc7me3+I/LGHxfYs9b/Nqry23Xu5xflb54MJ8m3w4k8UdRQBYAZWlZZOmpkAlfamOvfm3Ve2KRTvay7fwJaJQTzCubLf9sf20v6cXqCRdGWLgCQsSEQkZkE4Ko33opw7cWLerTaWoTN5bX5LI1crOsaRt78lBoJXJaVGezwP75GvQc6lfo2nqcWmb/SQsvaZEXlNN9E2TyH3LubjxoBF1DkUiAGZHpYyBOY67ppDwpBR1hBJBsa9jqeNRJncCwLO0r6O68pse1yTyHeUoTdcbZ/WExV1Tp52b0GlsnISKDWrzVrDZAfnCThYvRWq+atapslhXUZOQsQ7T/e4t69TiRyJLUhhP+h9TKTv9BJAzVCEZp3vj9DazTjV7VttUzQIoxZ5jLNdw31mnMWWd6r9JBixFytdHY8gRpbeRdZrPZyvB3zXrtB/3s06nEb8XyAc1WZAjqYR+BM6CvJeVzqrh0eUX4ZUTyRopYEO2qvl8XkKq+kDfdyLZfF6Ia5T7smsryjTFTfB2V46H0TKYS5RlvZEX520mki3ndSJZsvcBlESytkkV38P9J5It5xlnEc/mcJdKOJQSyYgKqC7hLPy2R/82EskulhJlAV45kWw4bzFzrk4ku0NuyCkacpKTnOQoeT+qqNNj/gn6twtKMYTaKQdUVdXD1VUdOVETwByTK61rlXUA7sFFVmfjTR19UE0kV0dXFRWozuXOzorKnPvWZMJel2qovrTKuY3qpEpnAHJfs2Y0laRFuNWy2nxrpXatMm6LH038KADgVkvwMNSM27Ydey6NjEyrdKfzHOo3eV/7VgC4xbwcr2MTE4hqQjwD7xCvrqtrrYoy6bVMn2fD1E3e19D5CTbGnZ/nc9Nisae5ZXAYknbWNFLP49nzEumxz0x2JBt8j/UpuYSiVeo/AHG32x9/AO7BufRrPi9kwd/7XOgRtgUCnu9NPrDwldCXHoGv15Wz+H//3q/i+fDpUZ6L98oMOfhylB/lo+9v38funu1MY3drKPN1Jkj1bZiKV+xcfnGmnJb3JhPfwEHimpByP2LNmEX2eH3xhsNEsfcpgrBN94lYvG06AVlfxlvrUCx9CKEgZCNL5MD6ZHRxelv3Wx2rppTlnUWr91VD+qH6LAx8mZqmXunTQxO3W/iLC5mBAbjZDHGzFdtbE7NClON3O+GtSKtB1iYANF/7WPZdb8QX8eBCbO5kg8fvfk9s5BALoavWQ10tS93NJ89Ajx+CE/IyJpvY/egPCyv1WLQQXswyPbx7elW4La7WCF9+CADw/+IPpYNf/TLw/Ep4Ldbbwu797Dnc44eSV3GT0Ij6Qi0XiGeGz+LzS+nnegNciMbjLpWyPsG3U3X18O1PZPu//qeK3a/JcrNGvOzJYdd/tET32Vq4IrQiNzPcZgBdryt8AojEWfmlh7nEX+almDdwz9M90fFMfBal6tYCdL0BPn8G/Nl/Vbq1aEGJzyLMyiO8ezxDez1W4QcaGdwQmqsew1mH2R88yX0bvvoQYdHkbXy2wHjWwfVB0JLXZSKInUdcNGiey7MwnEl/u3/5Kb73V34MF3+QmOAbQuwcussB66/IPs2mvJDDSib10BHYA+2a0WwiNl8SzeLx/3NZfBxmUes/PsO48Fh85wZIDOM3/8a/hqffaPD4n43Zaby78Jg9D3kMwqycjyLQXQb0F4YR/bfK8/Iyeb8miyPFmk4HOTWdMUmmXJn61RY9DsjOuUqNZK6OkVk5lKQryCRGu34vU5D6IdcpzdsGD2zKi5gBRCFIyTkuaj0NyVGoxZVt1GEMIJhcCzWldn2lYla5IfryTdi9szNTC9es+33GbWaBPqdraW4G8bqPpZA0ccrStWzfXDSb6jctrRBjGQPVJAYvkQWbSLYbwCHAbXRfOR8NIX8HgK518OsRTMiOUqdFibcjGirRDDDDr0ueBwBgvUMDiVC43oPWRb33g4QkdZu+ONwPmD+LaJJTkR0hzjz8zYDZc83hiLmPbkz1ZloCO8D1jGYbEBtK+46lBKPRYpqrHq4XUJWOWXc5YvGZlwkyDzrQXo3ZG+m3KfmvdaDIaK4HUDQQ/fF4zeLk4DzJSU5ylHyQmsWtsfzJPhxZ4vSHfCE2WzVpImK+HMg0tcISB2dvkowO+UHStiqun6qw51XDrHIYJ07dzOBdx/rzbyP28RAh1HU8FHcRYlnVLeBK+2NlDEWjUCbzGIFgMAaDtEmhvobq79wHhXaXMcrAJotD0WQ9/W7wDIgxpfunbUE0CskQTd8B0BClb54Ka3WqBkYhgMeasZvGKHDnYM6lDNhAPZZEoB2VbYqh4Ai/i9lEIwVvjREuUe1lzggGvNPvSfMZGK6XNvKYT8fJO9F2KJ1fHbJ9RLNluKGMud/JuTXFOQOWGXAhwvUBfmdwFnfw332YkwVu8/7XBDJHiUKl83eDIFRuhbzt1RSxqq+HqO7owDmIUpZrDTPWmptvRbRf0z6n7FDWySQJO5KXXUsHqlPVoWrnjTF1Z3i4MUvTNs22dMzAmJCl3kDdIZmgfAti8m79QLk28z3bqpNIXd4GgB1LH+y+Or4W8n5AmGRs2ZjdbNsBv1Hb4cOcLCyLdoICw7maNMQ5cY7qJ1B5gSv4sxOILsW4/+BMJwjvJWSmYV6FQk9g4pJbEEs9DECAR5qKve0zoIjGIKX1YnlmuEk4fs2fqEJuKalpmnDUtlXKOLwXQNU4FtKXKemPpuTrGM0as/qmyaBtJM07RS7CvAFtR1DkQgqjiNTGHG/hzI0vuRaJ3FjuWWHxzmM0FNJfnneSqk8kfQMESMUMDKEipQmLkoymE1IEgFZYrmLnS9UZ58AzjzgrkHGetZKa3pMQ29hIWuvBs7Y42hPblPMew8qj0741hDDzcEODcZl8FqrpMPK2MJMJwu9kQerPZPvC5m84EzZetAjzBu66zeMYlg36c5LSh0kDHlceFHXQgaiEvS2BggMiMJjyhXeZuD/IySJPEEB66KjeJjvVn1PJuRdm1fS+LrRLDlnHTfuSrviNKf5rcg5yH7zfm3jYO3m4iWQCM/kE7D3ImSvQCUZzEKrktZTolIhf8lGNrxCNrmlSPoHZrqu+5no0k0muawqPQ0jX1Gi/E3Kw80DjAPbVZIGQoldhch0hyHkUmaj5Cq0vuANlwdKXRVVw3cf7PCHHTl4Ox4zYljEOcwc3ihmg/BE6jDw4xM4XhGjK3VBeCT1XnDVwAOKsESeuGZcw8xmWHdPk4J3DsJAJQsaKEGYOvvUY53KufEcYGBdyrjCjpNmwbJ+Xsc5QcC6aXJx5hLmvxizMHIYVIbYEXWbGuYPreS8aElsCRYYbPcaly/35YpQCIPfiDNFDqpmtnH0oGmKlip4cAPM4ycjkaNR+xf1r5Sokj7+prJVFQUvpOO0LjVEeZKIqBZzUfrcTTFr1KzNGaf2G0UQ2lAWrFBQGUhQkvawZPq05HXrcJJeCBjN2Ws07sEwU+gIOEewJZLPBba6LagmDmbCrqBSnazB5DZr6rd9Vc9R9QiiUiCFKn9RXoZGcgSVU2hK41bcFoOQ7EM3H5+vPk6IClwaBXlM/Sl2hSfq21z4DcKmgNscIPxS/ATMhNpJw5nfJ9zAyiCFEPL6MCcUowxoZvrcTbNJY06TLjYPbhXJ+pQroI/wuXYwqIT3D93J/rL+NIsENDL8JaJryPN2FKesUDTnJSU5ylLy/msVUMjQ6yOqqq2rTyMprtwECg9VqYbraWkdYAgbpahjPlqDtLoOm5EcSG1zxDN6Duha0WoAXApKi7RZ8sQJtE+AoQW/jwxXc1baChsezBcJFByZCF0IGULlnNxgeyffuO3KquJrD73oBX40hnw/XN+BZB150e4zg8XyF8WHpfzeMQq7rCPFhAmXpCp9AWTFR1dHnAkzqP1pmzAAN0vcwbxA7n1fPm6/PsPoEiF2D8VyJVBjNekQzmAxM73I0JZzPM5FsuJiDiRDnHm1aaRXcFWdekqsSBmJ8tEDTONB2h+Gx3LPhTAoA+W1MVHFyTTdfaTC7lAI7alq4wYMd0D0f0T9o0DxVomWP3UcL9Bce3edy7vF8hv5RB7+LCDOH7qmh7Fs2GJcOs8/k+P6RHHP2ZInnP+LgxgSaa4BhQVjMHK6/Lvs2azE1iIH+IpkLC3FONmugvXZYf1W2rz6ZSSYpISeBwRFuvr7AsHK4CIwm4TeufrDF8x8LaNZNfrR3jwjzz504lRkImrc4F1DW4nOPzZeSJsVA+AdfBDNkKhYcNRjwlKrydptzAljimD+nbSj6kRMZrbteV2jL7GkfDLw2Jn7Jm03ho+wHuMubQgSbzuGerwWYZYhT3HVRbWnbS+YmRK1uLneiFmuuxlrYsGgnZMAZVOUdqBdGLGV4ymppZKkUpkN2s4YbRvBGSgfoNgB5stA+hNRG99m62Oqp77QdgcZlFXr1CeA2I9x6yC8qjVGcnrs+OyuzQzMy/NU2g4l0kmsuWRCfQKav9+rgTOPZjhF0swFvtmifpvybbSumSGQBKsWi7jc3I2LnEZK/wG8j/HaEG0Tlz6ZLP2D2+RY0dkL/D6DtR/itmCHcNXA3BZTVXHp0szaXB/CJzZtv1rj4VsTyk8S81hCGswazJz3cKBOKgLJE5VcH57AS844Y8DtGu0ljct1LRbauyePFrcfq2xuEeYP2s+uMhD3/9jnGZYvl9wqCc3bp0F6O4pCOnPwZ4rNwPaO9GjF7ZtjFdl+E0GlKSKID3tqKtTsEScZRxCWQk4Ze3LzBKCQ/hLXto9a0CLEQ9o5jxtdXPBMWM5Ek8yLYuLkSowAyual/oh/gtsK6rVoMDaMgKb0Hj6GQ44xjOXaPfXzSj9twGvqbHmP+prFgMigIzwZFBthnH0XsGpko+gFuY/wxg9D35dodtq7J2BU/hNY2MTkgGVNACeeh/RuL7yf7CzxJ5CgEiW6ka/Odh+uFod0lZyqNEW6MoH6E34iGouejIaDZhDwxcSvOXQoMjLHilZA0+bIt+zsio9ly/psioVkHuD5knIXvY9IsSr+abVpUBtGQQpciR6mOSHUfxohIJJqdGRvXR7Q3jGYTYL37fojgINoMoi50Di4IVsVZ1Obxc8V7PFm8wMEpzNQlBEhenZHphh1iXJq2oXwUIcgLOWuFL0NrgnoPajyYS0YgGqFao6bJTjzyvtQ6RRl7nncy2xtSHJ51iHNp3++Gwj0RGWHVyUOuIdkUMoT3Vc0MpPOxd8XJqi9l11bs3q5rc63UHJrcmmjItIYqxBwompQ4Nbn1VYhyPG/lwd+Q1PyEvHzOidaTIw4axQl1TVReaI0UKqvnvOSGYAgldLoQMwzeZ1MlzEWboOCrmqTDeSNw65bACp9OoCfXOIznLfxVMueGEWHZor9o0Twp5w6rDm43Is4aeBs67Ro5V5qwwkqOaRuP7UOH7nkpHqRag+Zg+N5lR6aGSMc5ZW2j2TrsHsiYrebpWWpc1vC4cQirFuOigb9q830fzj02XybMnzX5wdNoi2AvUogWSbNIk0TODWHkcTpGTg7Ok5zkJEfJ+6tZ3EEyzd2rpp7HdLxR2zPtXUUHdwTM3LSZP3VKtuFFYzYhq/pcMm/VNHJusu9rXOcxMu2j7esEKp0h3tqvZHKRhZYnByeZfXOY+a6p1pP+UEhFcvL2pOqPBR2jiVIUooQwgxlfBlzgfXPujkL/P3vvEmtZkl2HrR0R53PvfZ/MrKzq6uqm2OzmR6A44EAwRzZoiBrYEEBoIlsw4A8E0wMJnnhg2QPLEwEa+AMbAgjQsCDTgCQL8MCEIUCADRuyBkSDMAc2KQhiU/2pruqqrMx8n/s5n/h4sPeOiHPfy8qXWVXtrNYL4OHed+6558SJe0581l57rViw85QSH/Pocx356ejVBKlDtZ1iZA+cTPt+cf0o8ueUad2UQ6mUEkgpnZ/DLfPmdhafhlnUOQjKGzjKRL1xwx+XOvvSJNFv9FmfMFXaj/W6PwXm5mcSVuA1761Zp2rxp3F84wHl5ftQoiw+CCOyWqsr10C4HfkBTLyWVQ/TvA1gL9aKZKVZpwjVulzbSwVxpmXWpznMBTcJkSncSrjSrNO95/rOvkRkYgSNfgkSK3s14z+yBh81o5SW/AoA8MusUzpMuS1IQEWbUsEsqk6saQzswbNcnb0Fs6iczsgHmMHDWirclJRgjcmYgQKf3BbSQck2ldhPPqC7irB7ydewBAoWbjejFUMhqw5gsXBD7FSWSXaIiAIe0zhzR2xSqZc1sDvDnd1QdEea64DumUWzraQdYkKz83kZYmbBcxwvQ9z2yBXuFbJO34zOQvn09YNtLRA9zJoVocL1dfmsXksmGRnmubh6TTP7YIjd4G2JZOpXwQK1xCHPWCUwrXrGLGIoep0QfOAwFNNkzybBihvkcx2GpZgt+ObO5KhxYsAUfMOZa1Go0rV9KJERJVbJP4xB1HaA2h7eL8LH7BsycehYwV9VVTJGEtKqVH2AoxPaMcXID7Fzi07bzZLyHmLuhHIynAKXQFbsTl6iG7XZMQAMYxELEqxGndKyraF4hqRp4jYCkAaJgMS4YNy2g+ffpVYNVyWqEEG7YSFQa4YpC+YCAHZ7GLUwrBTWAMZ4rLO5/Yw4qcVhwOYHe9gLjTIZuMaCDhN6wRxqZzPXFqaqsl7N5GH8Wq5XkvSoalsi2P0A4yxwvcu/e/vxDg9SQvN0nzuh1FiWO9DBTElg0glinOAuKw2SnwTfEKpvOmDZkZiSYEWaB2AMMzEBkA2ccanKRynePIbeNEa4FImnzBp1SAA/uPVIqYIxyuQEOBrjK0VlVfQKkR/sFJcK1KKZQZV0XLZCTFVnQYS06viGaYtxDHUtA7LTfMNANwFYzMPmmU2KQygdS63QrdeJqpM7th605abOoK76fA5TATOrjiJzWIapJJepTYBcG8AdZpap0/qoYVM9U/S+zPL0XFq005O6U+AORA2iaQ7cAYonSFwLIDuxizzaKkK1nbkdYuB7qe54vV9wbnJ7hSDZrjpYcNoA+QDUIWhdhmWNkIZDtFJPI7MPrWdqXfmt2gZ4esGg9DSXNpvmHHHJzaF6GCKwnGeaxCFoTGVmAuBGFO/Tyj3AeV/uy325U3ljZxafKiRccReSCtJSLDOIuwBW9b7qEh4TElWjlg+yNHkNdChVddQRSkRpCTLz0JmT6irWOS1EPNrKqJQqjOa1NRjvVO8jDY4q9JtzPazhunlflieqjWFt4VnM8vk8S/u+AkB8W7nl+1QtsfIsY/ZluaE5OjEstBvIB86E1ZH4M5Q6n4ZCLFhVpQtSAOwlT0PPT0FmlIrV1DiV2lMel8j6FKwYVmbKFMSWUkFy4NXB5FvKG9tZ/P9STLX0+YwI+SufF7iZHKd8kS8y+nFciArH4XjpV9fr+H3Wlijp4ZlnkbVBqmN8Fk2LWtC3KgzGUtkHKKSkui7H9f6sD1L9sx1roMi2ZAQkPT6XnH+hQ6Ed9B30P7J+RlWHz00v5Ki8tLMgor8F4M8B+Dil9Euy7RGA/wnANwB8F8BfSCk9Jx7y/hsA/zqAPYB/N6X0f7+0FjcW2+DeNKbb1byrHnrR+BXo+NKiBslJwk6UMm4BgEFEQ8vs0VcpCrwC1Q8Zgai8fX7P+0ZeDyv+ARQF7iRuYpUqVlbp+gJKqiMyAN/kwCLHJat41SOXuKQlX7QoMM8CcPKonkPQzgGvcwl5dnWEZdWjeoyMY2VVLWXo8gNIdQTKWc4Avsv98qn1QhVWlhnFsTLYcfg53x/8mapp5ahVrBic6faZBWnIv3YpI05FT4Y/T/T5DTR3mVn8bQB/E8BvV9v+KoD/PaX0N4jor8r//zGAfw3Az8nfrwD4TXn97KVK866ntGQtEniau5g+qzq4vHKp7lBxt9Ifh042fHOryvTlFe9nLVKQfQyBug7Ud5kBGq+3MKcn2dMCqgR+dlrChVr3ri0M0e2+gJmHAen8hK/tiShNr3vOAXCWowdO6rXdsiNZ03C0Q9sEYKevVZUId3XN+00TaMWgYxL3LR3BaqczAMBbDxahUxAVn005TzjtYa8HwFfXI1T1DBxK24E49JpON+VB6Fo+/2YFowrlWc/CgWZfAMN1D7Mf+Hl8eMbbWhbYIR+PmKUd7GEWwFtmN5Vgb+odzMVOfkuDcL5BXLmST7NZIa07zs1oloK9aEThfCcJgwqUfhCx/dYZVh8KI9gaxM7CXY+YJDnQzjF3KGFdCfYKhdsNAcNbkpj2R1Fk8SqfXCLEh6eIvYN7cpUjMdNPPcTVT/c4+14RPPIrx+FR+X1ja/P5zJzgthP8ScWmfVqJJb2kvLSzSCn9IyL6xtHmXwfwq/L+fwDwf4I7i18H8NuJn9rfJaIHRPTVlNKHd67RXcpx6JTfLARodGTJHp/HpdaCMMQzmNvwgKNZRfIemEpeRvJ+gernjmkYkVSZWzJmCVORmqtG4BQj6DDyLEK2ka57vcx+FurenkO/+vDVnWRd2WlGSpL8pm2jHUEd0eFK8Pb9UEKnMh2mEBaWelZp2rXHpmIWvlIGU4OflJahU5L6zD7bLJRQqVtElwjgfULgNgKyXimFCPiizOUS+46ywXHhWbBvKXNTan1RM0zMbfFlVCfRKyVnl5GhceYQ+pHyeZpmdM9m2K0kkhkDM1mY7YiWqg5LZhV2kM6itcjEqTGg085tLNyc3GFaA3O9hxkc6DDmNnOXI1ZPHOx2yuOgGUUFXTqLbE+o/JHDVDRBUTrTu5TXjYZ8peoAfgTgK/L+awB+UO33vmy7L/flvnzJy2cGOFNKiejVF0ZE9BsAfgMAeqxv3+cFQA1VSw6yIotWZ5kKj4GzT80NdiWAkkgm6t7Utjy65aXBgYk51oB0jWxYb5PaJn+fpgnUtSDFVvRcvXAkaveyVjQyjawrlQswEBsOpQRo6nzLadiwhkc/5WrMc05cy7OQFy1D5rnUU+0c67VttQzR2U/arG4wOFl3tFqGnPUlaUySwlJKoFHIWkezM3KOdTkkbTVrczSuRCiOliGoliE8u5iyKVNs+XvJR6Su0uA8aWH3nsV6daQOPK2nySP2DWw1s4jrFmHVoJGlBZ+vXobUqmWyDFEJPl2GXG8xPG4zuSkZ1v9oiDA9Er0S9Q2JRYMztoZnFiHJMoR/p+Z5yxmvlhbAyL/osgAAIABJREFUd2wdL0MqfdLpQY/9Vxzs2Od29L1F01ieBkQUDU6nyxC7XIb8GIyRPyKirwKAvH4s238I4Keq/b4u226UlNJvpZT+dErpTzfoXrMan0M5Rq61kLkZnXjVcttxX9ABqmbkIiKjx7gtSvLjLNmPVJH7o4jCK3z3ZdnAd6uPtJe5eZycCkHlfT7fcdt/HpEQYLn2e5Xro6PvoroP9Bh1e79Cye1zXK/PUF53ZvE7AP4dAH9DXv+XavtfIaK/BwY2L++MV9Tx/JSQ/DKykQFLS0ghlCiJ8hNiRDiUEcKebPLImf0mbFPo4Zk7IFjAyYa9OKTE6+s8W8j2hSEwuFmZ09I4AesVK2VVSuCpcTyzSKmiarcZkKN6xuHZQSoZg3RxyfVf9UiXV6DNGmm3z1T2uN3Bti3S2UlxHxP2ZG2PCAAmBB7R9xbpdJ2vITNgY8yjtdntkVJiS8EqmY4/NMVWEEDsLdxVWna0+jDWFO66bFalrWUWEc/XRZRH1bHFJlFzMOKpzGK8z20XW1FOTyKjL0/cvHFojpKuEhHipoG7jIjOwG2LhSXOVox9SJp8eOcc/pSVqmJvMzUbKSF2joFL+c1U8azbnmI6MehEWTwZFuw1k8V0KkpZh/KgLu0LCc2O29pLKrmZ/A3/VAIwfeUR/MrC+BMYuffmE4fxAWHzo3LfzacWahsLAFGOGxpCaC365wbjuVo1IDuh3aXcJXT6d8Fg5mMieh/AXwN3En+fiP4SgO8B+Auy+z8Ah03/CBw6/ffuXJNXKSFkIJHkPYv0VsDnLQlmuRjKHP8cZtV8j5r4c7x8EeHYnKCl26ZZgNQqXLY7CDBXjkcosnZpHAvAOU4w17z8CAqcam7JMOZXABxSHkamiKt6lp6zjtEDHJ0AmDwl4GCaZ9SO5RkUFlVuc7mvLAWl7rNnjQVpj8YSR3NiedB0vxrsXTS5tgfKsskQZTEajRopwKeEJHPNHXKKCeZKVLXGhs89+0XeTp9QfFq1xMjit8OIZg4FUAWrmZmhLfke25E7Gx9hfFOOJSCkdSZHQ0gNsUPA5oMJzTNZPhqDxplFPTSRDACaa42GcAjdDgF2DLBDFSU7ptwDaC4G2L2od0nb9J8MOO1W6D455P3coYHdFUBb1c+TNfAbh+Zygh0rBfjPM5EspfQXX/DRn7ll3wTgL9/57PflvtyXL035cjI4K+Og2kzoxj50i5+IFgUMj5c5ddLXLcdUZa6cfCTgXzYt0tH4SECYt1UmQNYujH/SkWJVNi5ychytlyS+qYkRUC0tGlHw0plFtV82NNLj6ExB60AGRJLIVlOlwWCrmv8AYDWtw8TH7QtYRnJOugVQXrSHgpndUbIU8dScQsrrdDZfigxUCyCcukaAY1ryLDYN3NFMUrkYFCPiqoGpgfCuRew5mxQAYucQ1g3MFBaqWEgJqXW8jNGl2KpBMgRrLeZTh2YrdTPEDuwxwm+Kelau46r4i0TH15ucwSxLlq5tbvATASD2DUJnYQ8uzwbDymE8M1itCldi3gjhTaPXTpc9Bn5jYCaH+aSSMXgFWO7L2VncoRSnsiWqTPHuceUXHHj5f91RfR6g6OsUoVlzHar6ad2OgbwabKyB1XTbbfoFl6re6qeSLED+BcDoj6kkV4BFQg2clnokQ0tTqi+yPvX5X8EYqC4xe5a8Xh2+nJ3Fi3ITXlYq4E7FUcooLFqXbhmCvfW84pClJdV+qXoOcQxbjHOVY5iRUV+PVzuJ5fpICFhDwbka1vCsQ7cp01Idz3J1q4esvl7tQCQ0zPVm4Jc1MAUA0wM1rjiFAYidhW0cEi3tA+FtqdtRWTio6cyidVkIJ1npKBor4i8ys3Cm4CoKcPbFNS21pd1Cz7aBdSHHwCZN7DZmq848igOZVd3TxmayVDLErmvg+4Vd2UzeFhvLdU4J85odwwAFOC3M5BBWR/cYkN3AYkOIFgCY5ep1X2cXOFeuqyiWN66k5PuVxXwi9oXV8Y23BeAUzCJ0hNgAoTPZKS1f5x3Ll6ezqAV8F8zDdHObluNRXqbede5ABgc9q4QvtBKOj5kSdwq3qHlnpmZ2t/JLnQtg4RiWfEVprkVxqn3V/Uxf86mULXmLwzvNYRlqU+Pfet/bOlaxSWSVqKXmRfYelTqaMUimZCxu4ihteJsxde2gptfK2ZK6lEoyo1jm/OT/bYnGmEFA0GPHsCFkp7BSpwiSSI4ZfVkmyvnNSGUp6iPMzMpavh69g+RgTJE5EFovw8vRZp+yHkVWqBo97IGXB9khHdUMQZYhbh9gx1giJsI2PS5mjtx7K7AKwB0Cmq2DPZT9nSP+X8eALCto4HsLO8Wli/or5D19eTqLWmYvxhINkffHy4ukyWbxlo4FWNK9IVERTR7TctwhxAjEgOTBEnlARuWZ3FXtr7J49Sgxz6BJRqBQKTTVilMVjRySBp5f9XPtaGqpfWu5HoLT8DXKOXzI9dWkLhAxzVw7KQ0pj1Oplz7IUsfsT7Kfcg7IotuROt0WgaLKkjCnYQ9zUSgn4qWHhmPrVG2V1asjL9Lu9e/rdjNTnesS5QGfZg7T1g/iOMFImwBg28KBadH2UHw7KFRJcPI72YNBDCww01z7fN5kDHc4g4fbiQxgFQ1RPc3jaEjO1J3mW6Mh9jCDvAVVx7IHj+6qga2v2fC+ubOVmYWZDELPsoNN3RG+wqr8XvzmvtyX+3Kn8uWZWdTF2jKy6/ujdfIC4NRSYxZZ61JGlb7j3rjyt8jH9H7xP6kfBwAMA6/BFbeIRzTlOiKy6hFFcs5McyZEwfu8PUdD+g44DCyjFwK/AsB+D+papL6ruB66fm+YhqyjyjgVjQmllh9sJmVRLFESRCaPpZNVWUrpqN+3C1KWf7hCIwla2QME4AjJfHNUrNtD3wNCuBJp1dSx4XNyhpcOMpLHdQsTE2ifst1jXLeZwl1jFuNbPZr26D4IQsa6Zo+T5lmJHMSTFcK6QXPFDOLQtwgnLWiKPPKrXqaQslJj8gPjTzskS7DPgf1XGtiZ66aYRdMYjI/FI2Yosx8lZSlm0ewd3CFifCDRkA/7Ww2y5rMOoTfofcwznvFRh+17Fu11IeJNZxZtdztm4XuCPW+LbwjwSr4hX87O4kWkrKpkUlbtbtXYsl0JTfowDyNP/+op9G2kLLEwrElZNM6IIaJOkaH9cIOUBaLiClCTsqY5p2pnUpaSsZTkpKy+mFjsdxgXpCwiAg1HP7wuP7zP6lVJVKsUt1lojgKg7eEGKYvU4U3awznDeo4xLTGeTyNlaXugAKfGmCLeK4ZGuoTS5ZGJnLGaUsrWgaoMRbNfAMMd0a2kLCOkLOdjEWqWa3VzKKQsSUnP2IhO7yUdHkQ5bd0lBoMpRKw/muEuJHXdGDghZWkmab0McbvbSVlmElLWfridlHU1wh4sX5/8Lt2zEScrg/ZZxVweX0zKms8c2ospg8CUPmdS1o+1ZLp0xA1wkQyAUJy0VBhX3vPrLfhEDWg5Hr2QUtZ1yDf29Zb3lRu6Tj6r35OyODUlPUTgcGBxXGOy+G68ur4pqDtNCwPlTIueix9r7syut6zKnS0JyufpcLihFpWMAHXDWCIJIXBn6n1m/aVx4ogFwB2P+pRoVOTpxQ32KxEVXgbABtJKra9HQaHh3yYLEOVzrQMApnBrp68mynpMPdc+ZTwlPb8sdU0pJwFqsVdtxh9Kw4ij3DQz72Rf2I4UOEEv7VjjwjgLO4wZQ8op8Slx/ULMdTe7JvNFVt/5JB/XSFulaUYrM5b6HrRZQFewGbG4tBohury6tf3skyYbS2u41r3/FGeXa9BFUb63Ku4sg4DNbWrgHp7CXO3hqg42+9reobxZnUWsHkolSemNL7kicRhgz85ybgj1HeJhgOm66gGWXAkvNGV5EMN2l4/vvspZ9WkYeMQ4PeGRUUhG5sOPQes1A5rqj9l3HAVYr8py5fkl523IaBDlHOabP53l8rWkVZezFc3lrgjH7AeEx+eglGC/J6k0bz9i6fuuRToMOTuUrq9B52ccijwsKeu06rOyNgC+iRoHHBKgbuk16ct7kGSphg8/4i/90s/mETVrNnRMEFMQeX60QvN8AM0hWwqyp4YvlgZAeUhiRHp4Vuory5DU2EzhzoQrWe7o7Cae9DDbAen5JeI33uNtK7brMxPbDGqZHrTsmUFF2k+d3+1hRtg0aD64zPUNj9lYuPvBczlui7DpYOaA2FjYXVmypNZxmPWaO0m/4d+x+e5H+OTP/gxOfyDWAJYQeov2csbwti5DNIoH+Do3hAA7JTT7iMMjvo6Hf3jKIKalEh4mwvRwBb+26D/c5hnW9pe/houfdXj4zx7kqeF8YtFeheyirrkh0bGLenO1wnxWhZt/dHfxm3uA877cl/typ/JmzSzqcmyMrEuUxArSC9YksJiOMpnJIpHJr1yqKapOxSbLtOGWzX7zdiNmy6nKDjUWsCnTqAEUQpVOx1UXomdKMlElq9c2iELNpZ3lfcDrcx0tnc6kVLPCWcYVKlp2ahzPbDS8SOU7saL+2q3l4/hQZjGqvG2Z7KQ0cz2GXzU5nJa9PLoGsbV5pjGfOJihgbGs3cA7JdiU2ABo4etBQBAfDNkeWwcYyR4dKwo3mHBlhjI1juuWMQRruI0A+LVj3VTDo7iW6ZQJVZzBqzMLk8G+eePQNKW+oXfwa4tOs2D7Bn7jYEeD0JmiqgWmgvu1Bc1cT6VyN22D8QGhf1bk8nxPMJ6p2ADgGpnNJWA6kXbuCSDAHRKSJYwPKJ/HAEyY0/vfcJv7tUHbNxlTmU4NhrcSpg/rNiBQFI2XlLIxcmhJbBRLvQAgvQIB9c3tLD5j0fX2Cy0F6u21f+jLSCoi8a9klpRY5j0d+6BG3PRfTWnpW1lLAqrXqpQsaBPTcl/ZthDWrYlp4ZbrUs5JvW/9WVWosinMMXjBDLTu7DEayzXmfW4h+dSf6zWlhBRJjrFcspCPC34M/6911esvbbtwGPPqeUvlXMIFIa1/df2kZKtqXyPXZgItjk0hwniTt2U/05hg5tI2hsDf9TGDh+plyoCigJ5zQiKAAren7pstDqn8DikSTJC6qUCvXC87tMfineoJFLi9KZWVvfFyfXM5l3qi3rV8eTqL+mG8zaD4xk0aeT99PS61dygZHg1rD9V8rvrhjjnEmCMl+n9+KOSmVw3NmMpizwcGlIiW7EdhXvJNUhGq9Pz1w67b9PjAghlpasBKSFfJV8pTdeJcxSKNmjY++cKMlAgF5sCp9UqmHKI8fAEUJJwcJCL1gtwb8kX/MvkIMhXhCljODOfCaKXJZ9JbvjYZNc2sXqy82Q0RduRtsSmYBUVuXzvVevkc4TBTzA8fk7Isq16lJfhnwL+NbjNDCau7fWFppsCy/3aOcIeU68XtCTQ6IY5aP8Yt3L5qpxiRUGjdZAzsIXDnMvk8c3OHBLcDXBWadZa9UyGYhWaKRZ9gAkdfmn3V1q9AyvrydBb1MoRq5NzcQOuzuAtVrwAWyxBFpb2EEZ3lnryeljvHyDgtH7BFbojKzmVFKFmGNK4IAGtdG5cBORKZNq5DQOxZo0GzIlPnQJPjei2WPaaobSvDMOc2OJ7iQ3c1JUflOOvUmMVxcyZjV2T6NZs1NTaH4ACWhjOTgwXyMoSCLENcWSLWhsOpsSyuC7AUnoCQqkeheR+5TXTm1rrMY9G2C70VuXtCWLs8qs9rAwoM5sVWIwcE8gkOsgyR45OPiJ2F39i8FEutQ+wtQEDslnkmnJthYUZdssjv7xzmU8p5INER5o2BHSzmtYYtSWZBwCQAp1/xTIM8OKx5Ui1DiBAbAzOV/Jiwsggr5n5oNGTeGEznhbvBbUAwnsOylHj5AfCr8QlmspjXyjnHvyBZp5+WExLjDZLWC4t4LORjfQrP4lNd0m4pN5YhQFExqs8l70kp1wA/sDHyr7lY9rxaHV6nLJYhNXdElwapTN/zsqq+nuMlz22/VUrA66Y/5npClhbl/1w//elieaVQLdOkvSmU633tlj2azlNcNFteEizrWO0bqu/rvVAvj8LtNaMkM4NUnU/fHy8xPofb5j4acl/uy325U/lyziycA1SD0znJ/nOZUAUA1Iq5jrwCWKxCUi/qzLL+C6c9zN5k3oABmOmYKi8PY5C6DmndF3Xn3R7xdAXayaJTyErhXEyMZp+XKGHTYnrIdOx+mOHPeJ/GR0znLSgBypKIJy1L0fUdr9lVZOYSQNsgnHbIcyfFHc5W2dgGAPphYrp0SgjnfGRb62DOHvFMHM9lJjY+6tA2uowQfsrKIfQGZuaW2L3jQD7Btiz8wg0KNI1BO/jCQDSMylOI8KddFqYJoi49bxx6aVy/4aVA6C3sEOB2Qml+q0dHBHvVYnrA35tOLYxPcEPkpYccY/ueRf+MlzcaAbFzQrSE/rnB8NCi/1haLRgMj1oWjxGuwfSox/DIwQ0RvjfoF0svg2ljsJYkrEF4Ee0HPbY/ndBkZiYvBZJx2H6d9212No/44wM9Hs9om2tCsyXsv8oX8eCPW7idZxEgFc0hwu4rDaZTgtv3UIL99j0D/wt7HJ4WdfzhkQjsCGbh5YYKPeMk85owPC4zulhlN7ysfDk7ixjKlNarGc8RE00zEo8yE7VkdyzvQUQwhxk0zktefuA08VRPr73n72Yg0oMO0zIrFIDZszsX+ZJRaEaPZiuA4OhLtuA0o9nq+l6Qbk3DnmYG4Grz3tnD7KmEQVWvcj+xDLxe48BZlTTOmQadqdxipqPb9RqbrYfdlxRyTXc33oAERe+uLNzOw0xVtmRKsAfuKGojH0qcJWwPcwYH7d4jEdCElM+vHYmZHcxYsjiblinOyQc0O20jXhLZMaL2se6fEdprsS+Qn0c7OLcP6Cxy1ialhObaA+Ryvdz1jNYS3BBgRgt3XRi4ZrYwc9nW2pJ/0z8hdFcSFnYEOwLtVcTqE4l8DLLUSciiPqFnINQdEpodMiDrdp5T6a2ByaQsoL8IsLOB25bM2v5Zwv79FdrLOoJl0D+PeWmtqe+h5SVL/zxCFxSKmdy1fDk7C6A8rEYToyog8S5qVZqDoOCoiMdkFSKRr6N5zlRoMubVln7KJKxs6LIYVU1vbhwDcZWsXyQS/oZZ7msq0ZsvohCqOlJJRDOE1FDeJ7YMMuaog0e+1qweVfFA6naIr+BVUZdilwAg8TGjo4I5GKmnZTXrfAmeR/HYUPEZEYGd0NDd7pdPq5cFaguC6GSbHpaABKknle8AAsa6EjFLjpACC+3kyPULlLESAbFJ0galbZLh71CFxyWzDAW/TnlzOwtDQDS3hz2FdJX3AwBj87bbTIWOSx4RRUNTdSCyVD+Zohup57oraArwj2+Ifzl5eFQNCmCEW+uQWodoJcksa2QSn1+VrbTDchbxVerxGkXVs1gq3si0vnQWbKRjmPAkWYsRYPUxU2W4Su5GCvxgFiu9qtN8lXqZcn4k7qhiS3l2wY7i3FFkxJ+Y55CcQWhKRMXAS4gVr2S0c1uJVcfAnRKft962ACHBnQUF3je0Zd/YMJcjdBZWtS+623/vZIDUcDvosZMQ0qIFDMoM6/NAJ+8BzvtyX+7LncqbO7MAbp9VABy3P2Y4xlCwhTuEF/O6Wv0qhFBUFJ1FGaoOZyr5qiZvxbRgHObj+1j287pN9CVpSVKiOTD70Bc1qmzoK2ZAWbMiRvFIKaSdfL1i1ZeLfu84xKmfpVQS3TKDMuW1MnyESYlnDZz0C4DX73aIIkOX8vf0mnMbhgAIU5N8qRuFKCK4tGRuAiAXC4tTfych1mlSmJmNsBEjz2yULDYzQ9HKDANgwpKZeF83mmwKrBJ6djTl3IZdzcnz/jXdmwSz0W1aF6QEN/C5AZ492JGtAq3g7XbSEChgBGYyI2MIDNQCQfY1UwTNEYao/A5EoJYB5rpt7JRgdwZ2RDWzSLATE7AoVks3JJiZl4u2yuJ/FePRN7ez+LSlREwl/bttOBW72pZSyqniL7IL1MKakRNwthEH7Vi2D2NOuwaQdSoZR3gBKUuPa4zE8asHvW/K+nP2QPY6nfLDnLKZUGRNjHXP0QUlZY0jZ8dubhFJcSI4K8WqR6mtXMUV79DvKr6guhaVGAqlBPgE6NJskuswgB08jDIgpRi5kUldv47p6L7qCAHETZPFfbMYrzOgxubfITrDehS1QLLMrimmDLoCyOrVxqdMxzZTQmwJbi9U5924OI6dUwY406ZF7Di6Erul+HFsDWJbtsVOl1RG8ImyRNKHNMotGGcNzSDnasAAoWEGJwWIeC93QmYK3KnJNdg5YHyrge95maxtFh2DpLUmRXQGyTJWofgJwEuz6BLcQDlC8pNDyqIX4BUAb1dQqqZZK3MwRtaCSOX1Rpmr6AMZfiBVs1KrkNW2qqS1iUVncn89e9Z3mI+jGZNoR8aCN4webjsxPhIizFjEVexBhHd035lnFZQfMNWqlASnfRG/ybMRYxbq1RgnfuDHKYu25O+oeLGCjipscz2BJJFLGZwWQJrLcdtLzyPv5GG0Ewr8P4X6twmSSMbp67meQnl3lzE7kmn6O02iyCXRKnctrmXTvNCaVAq3A/LMon9u4Pacnq2do5kj3D7BDn6BGcEHuL1sk87cXg9oAZgpwA42p6MDgJkamLFsyxHHaUb/SUJ7KeHrhrGcZuvRP5MIxyCRkJTgRn7Qfa9074TmEBGl02bB5MiKYUrnh0H3fIYdHOx2hNlzHfqLgNXHDu0uoM6b6a5CFg5uNBrScH5JexVgvPRMiWcady1vTmchojTLbSbrWNQ+ojwqynbLtGU0bbb4Y6n/O2adzpzVmdqGSW8qE6cs0FqIxAjo2LU5ixMNO4TXWaEAGOQTtXAFDFPfIGyExzE0hdMRIvxpy9NfOVVqHWe9StZppntLhmzqquxOr8dvESuHbLNrkPqW67A6yjp1FvAm8zd05J5PWjgFYb0FLJvmxNbmqMN0zlmf9mDgT2V25BOsFXs/jTSlhGzu27t888eeneSjM2gq0x5A6M6jzx6o4aSD8xFwDkG4GPOGKd52Mvk9AAwPLTrLUQ+NhriRp+/JEg5vN2ifFnp7WDlM5w690sg3HaazBm5gJey2WlrG3nLWqZxrOhPX88bh8Dahv5AoliNMJ5x1OjyUrFPR26GYMJ1yvfyGH2Y7EaaZ8nbNrE2NLVouzmA6azBvDJqrNs/MxnOL/VcjVk9s7izmE552RYmGaKcUW4ACA8taL0plRnOX8mZ0FresFMgaJO9hT08BAOG6qAFhriIUojqdhgF0fsbfHUfE3QEpBMTDUKIjtRdqnioHJOdAz694ba8zhNMTTgP3no2QwSN32O6YPyEdQDwMMHIeoERi7CeXZSRV7c5hgrncQRWSbKXE1H5wxSP9CYvUYJi5ExLXsPyQty3PDp4+R5rKsgsAaL+He14JtuwPnI8yzSBRBouqUkXEy7W9iM/IUqv7/rMlFmItzywqFzb33DJ9ehhhr4WcFgInysWEKIQ1ORFommEudnm9b+XVbfdZak9zYqwxnFGrvqrPGqR5RtofsnBN07g8sDSty9P1/mNWv06dLVGPKfDSgyh3FLnNnx5g9z6bMDdPLtB0LRAiOmuWBsXOoXM2D0iNDBbp2QXe/fZjNE/kfnIGYd3AXQ7oP5KOWKnxPuZ6xZUDzRGpMTBjwHQuQjlbXpJGAHYrg19jcfKjS87zudpmacCHf9igu1yjfzKiMAcBc/DsbxJjGaisgd1PoMOEs0o39Tu7l0cOtdxHQ+7LfbkvdypvxszilvLShKk8+rEJD1Wj0Us1KeR7eV/v2Yc0FbSb30v0Q0QBUnwFcoAkBKVUeWvobOg45VzqTjGV1PRWxHA1YqHEIx9A7hXyil+1LBLCEgDBTkIshDRreXZVM0tTEe9Vdiz5kGdRpFEdvd7XrZu+VqN1iQYZAWUjDIpxEACuQ73U9QFwBqY2VXrNQrHWnpCoTZU8hkojpN4GADRz9CgnlvkIBFmOarTsRScOKUdI9PvRGdELibxkyif87PfMG9tZ3DA0rlPUm8pQ17FRrKY6593bBhhjfgWAFMtEijbMp9foQzo7YRVpxSIumNJNziJNBUA0Xcfflf1MTKAH5zDSQSlQmB6cgg4jd2KKAaw6ximIYJ5vc36K2R0QHp3w5XzwjI+z6WGu90Dbgg5jYUWOE9KqA1YdK0EDIKWar1eIp0WD0zy9AtoGtD8gnfHxzdW2tJv3wFr2F+3Q+d0HsEoN95HJWJ0ttoIAxscrdE9ZgzOsZdmTmKJuhqmklyto5yzC+YY/A3Ib4GwFcynTd2nPqJYDsgSIJytWHA8R4bEsSXvGKTTNXB/E4VHLFG6z1OBMBLi9R1g5tE8FQHAG0+MNQm+wVoOgszX8SQszBTY33pZlSGwt4srBXfL94gUbameP5z/f41SxBgv43qC7aLF/h9tG9SYopZy27nvGD9yQ0OwTtl/ltnp8CDBCszfZm5Tgv3ICv7JYfdCCtnwN22+e4PnPWzz6pyYvQ6YTw9Rz+Wpo+XyhAewMtFdhYQUQvnd30OLN6CwSbu8+yZSwZV0qtmaW2BPtifzVlwCcWcdBuAxRVblVUPcZazOQtwVBdyKf59zCDT21zQ1Zvdg7GOU5KL7RNQirBjAAHTpEedAoJQY4YyrgYmeBsWFU35oMoJKzon1RRvDcGXVLWT3jLFLXcCKa6nQ0Wm+hcWv4VgHFVbklzMyoeuzcQs9iOrMg38IdQgb6TEiwlu0PIRoKGvVIRLxGj5qY1mRA2wxtbi9uIwczFsuEsG7Yudw5eGkvv2aquZki/MZmBud4ZgByHCbUyxwNq1JZwnTuct6LmQNCL8llT6QOzsCfNLCDYc2MKjU8dgJwSqjYn/AJ2sbh8JgT1QBhj24IJliM59KmHYOZJqQsaec3HLmYPcHvEqacYGZhR6axW+kUEn8mAAAgAElEQVQsUsNA7rwxaFcNnIR6p1ODw7sRh49LMt28IVAyAnByAhnAehZ2SqBocr3wpQQ4bykpRFkq6IyiAieHoYCHCmAehgXdO3nPAOc43gpw4uKKNwmd23j2wbQyWifvQbsDd1aVD2k6HPjcexlJDgfQ0+fFWkBDkB9dZCs/fRCtc7AXqv05w1xrnkJAJ54l2jm6j6+Kx6j3gCpjTxPMs2sG/TTLVpddhwPcVQEX024HbB37nMhxs4S/WgkcWSJ0339WeZ1KRyfZoxoSbZ+2bD04zXDPNHok4PDsC3dj9rIM8WjmYkfQ7GRGNM55ZqcS+dYxxV4l/Zurjm0Tdruswt0pwBli0U4FsPpRwx2UqXglYkaEENF3LoOZ5APWhxn9kxb2E74X7Ozhnkj0yNkCKgOAs2grRXUnHUy6uMS7334b7RNRjjeGB4rthP4jGXh0qRRS1SmWzsiMnrORAazevxZg0hZPFWfRyrWay21us0d/0KG/WKH/aCymTM5wiNmwDoq2QzLEYO9hxkk1oLj9PcB5X+7Lffmcy5szs9CYvLxXfsVCMzImkGWKcF6eqNmtcwtfEHuyYfJT3yFCRjJr+bupZHemaQaiB0423JPrkuH6uozG6qQVOtDJBtR1xb4QAB6eFyFXnd30LeiQFkbB5Gz2zKBpLtyJYczHiz/4gOvfd0iXV6D1Cml/YK8SAHG7g20a4PwUNMosQkHZVbcIW5qGl0t0GNmWEABdGGTZwRhzfYzM5NLJiglfqIhgXbO0Lzzt0EzsBlazHJESsNsD21ssDDersmySEt45h5HwoIYUFRtRVmXoW5j9COMs4kqXLA2DimJfqIuF6VG/SCsHmMKdNi3s9YCw6dA8uSjVPVvzSCwzx/D2A4Qzti8MK4fmqoS2Y+eQrIG7rjALS2iIsH+ngZm4fZMlxNbAEWF4h38Ld4g5cc6vhX2Z7Qsj3MFiOhfDou+zPSGhuo4QMf70I/jeol81uW3Gt3pcv+fgtmV2MJ85NFcV81SYpqE1mNeE1dMlZhH/6MuGWdxWakBT/ldrgBqHqLGJRakyRrOruB669jRVinjXcr6Cbq+OWZ+LnGOK+Uoeyr0I1DjVopQHbN0xq7FiVKZVh3AqN9B+KIZD4wwv24sGZ5sJYJjnXF+yFuhaBkD1ekQzI607hJPSWdAwMxkrxkwAswcGFxmPqchalvnB/qQtN0VFmFKyFABMD1vYwYN8zCQzgDkS5jBml7G6aHvoe0A6HZmKK1AaWysu5HKTn6hRz4ggxj5+41jterBFCxMsSNMepXObOSJ2Bi2YSNVUXrb+pIU/afKSIpy1GB80sINgITn6wqI8sSnRlOlBi2QB97TF/h2Ddiv1d4TQETpDODziujWHCu85KThGdEB7TWj2BofHvM/ppoO5JWV+fNhgXhHc0OS2GR5Z7L+WsH5SHuPhoUFvXR54lZQVWiZsUSykLK7vjVO9sLy5ncWnlDqs+kLJ/5xgViWd1Z/ndXlFp/YBZCsQ9OiYSdbJFGP5vq7Vo7ig6bnmkK3p6nOq+Ap8WKho5+05sSow/uFFSdxXn8t3qboGisQq3FO1Bg2y3yK5i9PFyR/VQcKRZqq25VAoA45ZvGZUanfKHUi+5hhRO8stPtPjqZfoGHIOSK534jW+7kOTvA+RVbfBoCXp/9WP6oYINyzPTZ5DmGYKcINZgOBM664o9VOEVYVwSyXvRXQoKJZENDsE1owIAc0uZXVv8qwtYYeA5mBzvbREmbkazw9qs2fFL7erQOFa6EiKPTB+Z6bSDm5IaK5NVhEHgKZL/H/OLJPjBmZ2avQlt88rRFS/PJ1FpW9Rh1X1/fHsIdPA2wY0aghP1LmJCginI7mzoGBLiLI6Zn0uWvc8/ZZlg2kbluS7cDyL0NGzsSBnc8YpANbNUG0CZ4t2hjF5ezYqdqIgXr8CEvnh46QgS6HAn8dVU0x/ANC6QzjtYZ3JURKzLWrZ8CE7k9vrFRA4ZGgmqYscR637coSiE4fxipEICJhoDAv0HJXcHvIeYAq18SqnxwJAyRC8JdiDytTJrG6aEeV7oTMwgSMMtdaD7w3MuDy3zizsYOF7y8xMKarYrb95WDlW+7aE7VcdTjRy6RNCbwACrKh7+w2rdzfXa8wbQpDpvs4sbG8xr26KSfjVcmbBD6th+re09W0CvfOJQegIzcoCYnDke8J8mvIxAZb0s2PJgalnFruvEexgMJ2VaMhPRiLZDdOelLelEG68vyF449kvg6Y5j9ap9rXIpsSCiYzTIkFsccz6XMPII7VyCaYZ5urA51P8BODErWleOIrToUr0mmbQXjqGaYKVtbDyNMw4cXLaKNEYdUwPzEEw27Gg5SkBE8GEuLjRzHZgPsJhLOSkaealEnEClbmSOowTEAPctiSd6YhroswkZERrnzumUIcIWxtPDzNjSbe4qGt78HvJmWhdkftTCT+NYkiSXWodSx4exuw9qu1Pk1/I9feNuYlZhIjUcAJYG9OCwu2EWq1Rj+aKowpmijghoH1e+CaxYxc1eyW0eABuZ2CvRqw/XqG9kPoqZnE9YyUZpjVmYcfbMIsIkvWA2Y1F+rAq/TOP0Bk027nwWAxh/cMG3fPK3yQ4NFfl/6bCLCgarJ562Ll0qK+SSHYfDbkv9+W+3Km8uTOLz7FkHOHz8Ny4YUkYC/3Y4HZ85Isu6nqmVO0qqsQYQkWJVvq4NUtqt7qt/TjL4vxMi0/CR8j6HrrP5/Hb3ak+UhcV8wHEnyOJ+5liYRCrw89GFb973eQvpqy6/qrF+Oo4r1He3M7iOBpSl9plrHYeu+37hgqeUeMaxxqe6jJWMzFvmC+L+I2rsA3V6lQdikqEF+NcHMCAhWOYrcyOyTkEdcqiqj61sI5mrorAMDuNVXNI4vT51Lo85SXFReYlPqJEq1zPfL0JsbWwMrVXlaXU2OIUBiCsHdyVpvZXmEVIBRc6LtIe9Tlj5zKwq/VmHYcCSsfOMRZiy7li5xjgBBZiP35tYOYlZkGeRWvM1HDkpPo9YmsZ83A2HzeII1noTXGPE03M2FB2JAsri2gJjbWMWazkGJYQO4KZLPxK759SH9UGjY1gFomxkGlT2nohi6Bt3hv4lUFzbWHknvVrg/kMC3Poec3n1nMWzIIwb4B2a4o+KX5SMIvjUmEYZIvKtr4ne8tVK1aRnZ1C+f8Y4GwcKITCfaiOWZ+LR/GSrs0fVI2vI0/rOF+lHnkal/UKbGVfSM6W7QpwqjP7iwDOxlbCujIKW0KoAD99RzEVRW29JkOgSLlDIM8iQXHlitzfWGjkobOwVG7StmuQYlwAqkiJmZju5m2VtD3kPcDgpHUKDOp1G6BS30qNyfiKPrx+bWE8b1+4qG9u6ywSdxYj07W76neLK3ZGb7Ve1rD4beQHOJOHxTs1rAzirmAAIL6npjOCl5yPaBngNJPNGhXJFCf3rFvRcmfBwr4FdExdcbGvS+gN5jV7mag40bQxGB8kzCdVaPZU7As1N6RToJPBV98T/E9EZ6EPGtENgDPFxASbEBbqVwtFrHp/pVpX2wuFHDcBzmG8CXAeqV+l2bPq91Dotcl7lr+TkKTyNmg3cNJXDXAS5dwPjFMRNxlGuEsmjmWAU9W3XghwHjL1GKJoZba0+EEzXXmcCrV8royZY8wgaRL/FXc53gA4UwigsZCyuk8szHZY6m1CAM6hAJl10fYAkK/bGRHLAeBqgNPHTOByYHA0jVNWqaK5kLJ0pAeAtaVPBTgppKxHAYCvdYqFwn09AonDx3Z0GcyklGBGh7gzJbmMiEOnhxGbDyO6pzcBzrUK8FQAZ7O/HeA04gNrtsOtAGf3bA23t3AXY07IWz9ZYfp+g/6TAtraaQlw1qSs0BG65x52qgDOW/hzLyr3AOd9uS/35U7lzZpZ1OUIs9DRCLgbg5Oc41G+YnAmA+ZqAK/N4IQTWT1lcO4O/H4r3AVdRnzBDM607vJMTHUj4rpfMjgPE9JKEqPUblFmFsmamwxOIpbV0wN8wQzOcNYWqT2V1RO6txXWo9oeml0D/wUzOP0JWyTaIcBvLHJLRsYoeOnBx5/OGyQHtN2Ph8E5PXCY1wZu1+Yh/lUZnKEnAA7Dwyrr9CeSwXmbjuanFX1wKyVuCuGV1mi3VsNJynp2x2LFZaMp38fksC+qUOmYYFJxU6vP7xiYTG1Tsg+1PQyT2QpuUqTqflwlESFp55rdxPi6YpBO04rxU/NjuFUtu5klS/JgCtsysF8qCFmdPTkmgaVKou6LLOrfmiyxRMFrlHkD9M+QtT4AvFLYjl6qSPVjKGf0KP0K/ZmS3FWDguqB2fdI3sOs1wtdTbKW19TWFnFfAPb0NCeMafo4nZ8xYSgExhiAnJBmVj1SiBnUDFfbGw5nZC3MowccvlI24jSBTjZIzy858iJ6ncmz72fdvtQ2WU8i7Q85eSyNE4yI8YRPnnJ9Tk8R93tQ24rBs6REHw6g1Qrm/GwJnooF48Lq0IesZ5E1L7a7EvGJCSQCPFDNSWOytmfGd6xEPpSKvlkj7faLduBrDgv5gLrQelWwDNXWODst+1qJMCn4XKlXZe8QxZnapiic1dGmdV+IanmjANJip5CelUQyOj3hbRes7Ym33+IZZgjwD9ewV5pAGDhlPISMb6SuzR1FsgT7fCfvOdJE44R4wr/pAjfThDlrWddkDKw3ojO8Dz+5tf3Su29na00Feu31gPnxCZqPrsp+q5a9d7MGS+l0D187Rf+jfQbTAeDbv/+buNr98E5dxhs1s1iAgV23ZG3KZ+HqCu7rX0O6YgFfOj9DvLiEOT9DvJRGi5GzNa+u+caWrNH49Fk52S//SQCAfbZFMoTppx7CbWeMIpza//4/52xSH5CuWV2Kzk6ZIv3WGWZZNrTffYLpTzzOStB6jsO/+qfQPp84l0B+uOFRh8NjbvKz7w4YH8m5ngx49vMbUEx46//gH3f/S+9h9f41/FkP93SL8IiFfN33Psb8ja9gOG/RfSKdoORszG+tsX+njHRn39nCn7Zonu4xvMcqU/0H3G6pZUPg6S2+odvf/w4A4Mmf/0X0FyKsO0aAgHnD1GU10rn8GYOz70a4IWF4IEu0CHRXEZsf7DMPgO0MAERg+60zdM+4sxgetxwuPDHYfMAPt7qxz2tCsxfTYgD7rzRYfzRj9Z1P8Mmf/RkAwPiATXzcHphPKYertj+d0D/h2YGKurgBSBboP0k4vE1499uPpb4Jz3++x+Ex4d1vv83neqfB/h2DZpcwbwjrj4vq2LwhTGeEzYdR9uXr/uo/vsRH/1nA9Lvv8e/fAfNpxPqHBte/ICDtpTxmEfBv87budIS1EfvLE9jnDv3P8O9y8j9/E+2OzZ3VwCk6wsXPWYwPEt76fxLWH/MxvvNvbPBv/dr/hb/zD/+V3Abh3RHuhw8gEVn4jS79AhCB7oNzjO/pYACM7999avFGdRaLUnUUABbr4HQ4lI7lcADmuYjSAJx6PfDsQ1+Pj+GecQeQdnsQEZonHWgY0Unad5pmmN2BR0sdEfd8DnNh0Cgd+XBA88n2hvhN/9EB5no5yvZzgBsEs/hkm9OazcUOp9+XEUc6tv6jPehqB+cDaD/kMGgaRrinW5hBZPdQohZNBE5q05+LHZrBw2z36GQ2Ya5EzVuyThvNlZJrPPv+BLeTiM7MHV3bOYTOFkcw32H9IVPIW3kQKLE7ur3Yl5G0IlytPmyyWrUmQnUrh+YZt1uja/7OwowhO4XbuYe7GJD2B5z+QNrmmVgBjBFhZfKD0uwce2ZQCQnamclU7aVHf+GyCjelhNOVQ//cZOEaM63Qbhs+bmcyhRtgzMKvTY56KEZhn+8w/e57ePAdwV4s53+snnnYUWT19koKBKYfSobrqkUywPkOaLYJ+0/OAQAnPxzY46RyJEuWkMwK88bg5P0R7pLb7MEfPsT/6P5lPP7DXE2MH/bon6Xsrxp6mSl3ljv05xHjk7KMebK/e2dxHw25L/flvtypvLkzi08rNcCowOcxsJi3394fZkKTgoQCrGVXMwUQTczRlJztWoOLwE32KAREMgTEUlceIQQEtaZYGRqD6IoTNoCivakYRAWoMgOzuubM+qSF/SBjGPJdg+W+eky7PEZ0ReyWhEyUHB83Jd2Ht1Eszuhs7CTXJREnCiJWLP4VNZgJkraot6ECOhfAp4EhyvaEsSE2qA+sVaklNlL/amZBSUlV3MaaqJZiRLKsmZkjWJaPR55fUxVZiZbPr9v0vMkaxK4se6Lof0ZXdECTPGUpIW8LDQADxFb+dF/LkapEQNQfTYDfKOBrsZoEUhc5G1dZ6I38PjKziA3l7RTlGnVikfBKbvZvbmdRpaTfKCrSC2FwHlO19fv1K5bh1wWD0xpRaHJZI9Fay+ntQPaWhEQMkrOVdyi/Pw7dxtbCtKw8rjd+bHk6nwiIXZPTq03fIKxYk1EBUP5+k1O7FRgjJ5TuprA6s6aHMwiVsG4j9Uy2eHRqJwlnkSqNRm2Z2JpcL32oQ2cROpMfkHlFmE8c3D5g3pSIAQUL11S/w8xK28y+LKnvyvoMnUGjDM5W08/5xtclT+gsnOMIjrI1fU8wgX0+543Jmgycns0PSxHsZcEXMxtMJ5RFdswc4XuDeUNFF1OIS5Q4/Bnb0paxW24rnqUG82nMaeKxYRZlsyP4tX6bcRWKyNv8SeJolOXBYz7l39ArbdwR7KRLG4LvCH5FC79VvyZ0jw6YT05zPf0G8AfuWCgCQWCX0AEUmMlZe52+ytripZ0FEf0tAH8OwMcppV+Sbf85gH8fwBPZ7T9NKf0D+ew/AfCXwDHO/zCl9A/vXp2qHGEWi+KLb2aaZ34/zQvMArPnY+grlpiFshvTPANzSQ3O2ID3IgYcCz4iadw0VGiz94w+6z5yDk31JvWrAGQ2IG93xUeTdgPa5x2PghKdsduRkfeUFuns/H6ESSW1WiMHZj+hqWTuaJj4lONcUsGVHRhYREe3a4fTXs2wilmoMM3sYBubeRKrzqB7xuBtnRLvdjPoMBVRHrVBCBHueswSeo3Masxk8/ldVBEcsS8USnPTGJj9hDTNaC+5XsZzvoidI+xgKwdxh/aKZwy5neeERIRm62G8y0xZpITuooUJFkZYmY6YH2GHANvbBRvUTNzZ6bZOZ1/jhPUPDVbPxOvUcUfRPw+Z4+AO4iGSuPMCgHDFnZ3bsxiNCfz7thcT7Mi4i8ogKK3dTswM1TbrP0k4/PEJVh8X3xB7IPQXFWbRKa+DO4/+eeR8FPDn9Dl7nf5tAH8TwG8fbf+vU0r/Rb2BiH4RwL8J4E8BeA/A/0ZEP5/SbdlgLylHM4tMjY4ANU1WOKam4ZG7bYDaNqDrWENTX/XLUuJGwEW5sf35CmZvM6nJWQN0TGiCanCKnWA6XSMKQche7xDO17DXDJJp6HV+2MMRLejQ/qzH+BZHAtajx3zOYdY2BAxv8/FO/8jlfZv9yG7pPiBtRLvzwiBtevjzLv94WRvzwRrjW4WUtd5PCBvezz/k61VvUdXU9A94qLPvSxTmnRbdpcx4Jo6G+LWF7w3syHfk9msWxrcwU1zoOba9RT95QKIzOSEqJUwPe7RKaHrE1zKdVklgG03QMrCHBm4nOpOPW3SG0F51GN5mcHA8MzCeFaHUhwMAtl8nrD7hhzADnCOP9v0zYsKSWgomjn6M55RVuId3OhweWTQHjv6oHgUA+JXBdEqZwq2Eq/79Na5/Yc5gZmx49uB7wtU3+bvNtcnnHB9yG4ZNQHIJ7sKivTTY/wm+3vM/btFsRYVL3dEJuP66xXxGcEOHXp6F6z9BePuXf4TLi3fzMmR4nDB/bPL168zCrzijdvrY4vBOyYyOldPky8pLJyEppX8E4NnL9pPy6wD+XkppTCn9cwB/BOBfunt17st9uS9vavksmMVfIaJ/G8DvAfiPUkrPAXwNwO9W+7wv2169HFGGF6HTKoU3k56OKcYxiK1huNUKMYf3ZKqsVvem1gqICQsNTbGFw+xBsv5OoiKVjjJcjWhHZlUqsLakHcr5VM9Rw4CqV6D7UohIXhK+fFUPH2HGSitTrsVMHnaosmbnACOajmZc7kvy3kxVO4CnzKo9qRwRYzlBTUc6t+d97BRhp8KzsGMQ+724bNvAS4a8rJn0XASrKeqaFUsEO8a83Q6J30dpOwCuIZjA2pXJUg7RNjsLO/DF5ZnFlBBnghsS3KGa2ocENyTOEPVan4jmYEQz08AdqjYnIJmyTSncNHu4S5fDowxmEtwh5RlFswNP+RMySEuBQWq3Jbg94K50NsfaphRTbu9kCc2Or8kdYr5vmh3w8bMzbIqoPZprgtshTwMUzyHP2E2zTUL7ljq9wpz/dUOnvwngWwB+GcCHAP7LVz0AEf0GEf0eEf3ejPH2nV6EWbyovK5ISi0Mo38x3Tze63h0xqNjvrDeWERDPq2ulNIr08rTK1DRKaVK2bp4dpLWsX6NckPWdZfrpcW1V9vr479u0a9L/Uq9uC1viLxU+2NxfWXbcWQgUfm77f9Pqxsdn1u/J3/58/pVvkchLerFnqWlDrc1Ax2fs/6wLvSC93corzWzSCl9lM9H9N8B+F/l3x8C+Klq16/LttuO8VsAfgtguvdrVIJfdfR/1Y5FSzbrxU0VrMCzktdS2qpvyFhIOfmzUBvnCkCVElQZm0Ji9e2649Jj/bgo+sc3cijXQWL2SzVorGbFFVbBN/5Rx/uaP5XWJz8Y2lGhbNcOI3dwAYBFrms9Q6OUYELKJsWvXWL5bVMqnWfdyaaqfotriYAJ1b7Z8Llq2xc91AlIkRazA5LrT6lEYOrzfZbyWp0FEX01pfSh/PvnAfy/8v53APwdIvqvwADnzwH49mvXjl4AcFpTRFs0fn/sG2Ik29RUWafVx3UoEoCIvoScpGMMsXlwZWwMa0GRbeSUn++MQegcXM3PACtFm4OTOvDXQ89iKyAg9i6HyWzHPpaUkJWxQ+9gRVnLuqJUpYpRsa+2KUeib+A3Va5G6xD7BubQlOxMzUdpuF30ep2037wxWVvBGgFO1xZ+VTgGLPZiJRwpSXry8LrW3ViGICWEtctLJDXamTcGzbVsW2k4kDkG2jHNGwO34zbwEqadTgjGExrDAjD6oI0PeLpdP1xm4oiAG1mMJqtfJWBeG4xnJodO/dpiOiFEa+BXlMV1AQ7LTqeU9Sg0ezR1Dv7tOTMzFeC0I2UwU5PQkIDpkYSENxGwCdE6Tlx7y+frR+REvzrSNJ0SpjOuo9tJHR4A33j3KX50/vW83/gowsxF/MZv+BhBAE4zG4yPtDOnzzfrlIj+LoBfBfCYiN4H8NcA/CoR/TJfPr4L4D8AgJTSHxDR3wfwh2AR/L/8WpGQ+3Jf7ssbV17aWaSU/uItm//7T9n/rwP465+lUgCQjXtvK7ZyUXecu0/OFfKUfl81M29jWObvc7Zmapjskok4qq0ZQpm1NI4zOTVtWuqSaiKSKcpETiXudGbRGYSWR5nYunwulq2TaaPqQbZGbAMNk8DkfMY5hNYiNsX8V6fRyVFm7PH/Rrw4TPbfyMxIZ4CQloxPsFZjPkZi9mgQQlLWSFjJiD/EzCWgBNhJ2iVJVqkvy5HYUCZeZWJTS6VerrAz+TpM/j+KtF4Qd3bfc1IbRYJflSm8XzN4x2nm0vQjt7/vCX5DJeMyJNmGTEKLjUjiedGbqNqS61+2KX8hWYvudESQrNHQMOEqXBHCRpeUJi9BgiR2mZMZxiT4QPDBojnl8L7vViDP9ddEMpZLBEIv7SNt41cJP3v2BO+ffC1Pm+MmwK8Mkk1CypKZxSayLkdnENYqREyvhFq+uQzOl5QbOEKMC1JWbT70qcu1DG4VhJhf5XgxleMqfVldxQEobfkm3Ryls6sDKpmGXEArdeUCIUdVAHDUpQK6ADBZLGF5TuXYmEKJXtTNoNS3pn0vtuvNX+pYX0siykI1ySzxi0VJKWfB5hKlfev1OkHo77KLdhZWKefI/yehtmdwrwIZFxT5il+h63iKQq2W89bK2Ex8KtfC567+qrHneFuevhvA2ljaTPLakgGSS4ttAADL74xJaFoPT7LstfoAM26RgWNp0+SA2CRpj/JbreyRLp5LSEZIWVQ6TdgEWGG2NnIvpdtQ0ReXL2dnEUu+xqJkZW7i8GqM+fW4ZAl30TtQNmJeJ5LgINEX4RVDzKCcPOwg5/IedvAVg7Okd/OPHvNobjyH63i/lEcOWE5HpojKMzUxvqDS/vpwCuXcHXx+KGs7wGZfAXiThxHtTHdY7qvvNaSq4ehmn2AmuaFnvvHsSEgm5ZvX7fkeM3NpLxNkJAyJRWfl/NyhcUhaO3ZF95tdhBW7wZKHYeH2IW9v9o7f+wAr9XKHBAqsH0m+PFTNNYcs67wM4xPMzHXjmY+GPDnFfvblPmr2UZSr+FoXbSk537qtvVYGZ8D+8gTnEr6MLV+L2zPhCuDwqIKN0Qo+EgieGpidhR0Iw2Vf2ibxTCsDxZbQXAkTtW6ba8I/uXgXdigdsbl0aHaUGZw6UAVvQYHQXha6PTM47x4SeXM6CyrxcgA8KhtCUg/MKiEs+cKdIBGrBbCke7+UZ1HNFgCYkR23TN6uHqOFWg4f7syzsENgFy8fASMP1BjgDhpPD7CH4v3pBn7wlFpuB+ZH0GBA0wwzCTAZ+HzGmZs8i9Fn2z89rhlfwrMYj3kWxS/UTLEkxMmIBwDNltmcdojsHwrODbFDLLwNPZf8rm4oPq+1H+nLeBbuEDPPQh9U9hhNsBMrhOksotkyHyG6hCCyHm7gWUZziJhmyu1Ac0CzT/C74tfqDhbN/o48i33hWdjnDs1WZict5KFOaC95H8dZ8TChdIpelMDsQDAj4J4JYH7wcENAbEzmo8RwO8+ivQa+9/Qhum2pZnIGzbXMKBLY5hFAmDhq8ll4Fm9GZ4C2E60AAB7KSURBVHFL50Ztg+Q97CknycS96DBEgNZ9Gcm7FtjtGcc4PeFt08yRDKLyimU0RD0+jdzQ83kPZyfMJxIdODtFPN2AxqkoeW9WoP2AuGozLbxpGviTDo0kgCmWMj5s0aUEMxdl5/m8xfCIE8nctsX0QJOaAoYH7Nq9PmWRm+HtHqs5sNO4pXK+qw7z+YoTz9Q8WFB7f9phfFh+0vZ5y98fA+YzfnrMVvQ6Ogsabdb+bKXeh7dsXhKo+M10YhknkJF9/y6hOTD+Mp6XPINoCcavywMZWiTijnF4q835FMNbfN2+I9iB6zUL9duvDNyhZL6ODyzM1MI2DodHTrYRz9L27AyuP+z+q4yNoFqOhFGXFxwNmc4L3Xv7VYvpATA95DaYzh0Ojw3cjvENqkIFk4jfaKRINTPPVy36n7nOehSxAeZTzvVQCre7sjmUqlGP5nSCsRHDZQ/3zOHkTz7na/gnD9Hs+R7R9k4GOLxNmB4krD9xmTi4ey/h17/1B/idP/6VvJqYvzIjuiZ3FhoNSesAeEIyDoevqd4Id253La9Lyrov9+W+/AtW3gwNTvMo/Qr92mIZYnrWxDQrngGEa5YdQ0qwDx/m6Tp1LdJ2x1qSjSp2c5aialdqJmet7em+xjJoaZ555rFmF3FV96arLW87DJyZCoC6DvHqGtT3IOErxKtrmLNTRJH5U8Us861vsB6kYg4AC+f2DUAEc30oa/txRni4AYUE85yPEx+cgIaZ4+3jXDQmtnuksxPQNCMdJINSSV99h7TuS8NeXPH1DyNIEufS7iANzNEm1eAMH0sC8S/+7JICThzhyMsEiOL2dgJNPvM0KPF1sJSe7KseJdOMeLoCyXQ/rVpWgpo8aLvPbcM/DOtvqm9IWvfsy3J5hfgt5hPEzmWCVeyK0PB81sLt/CKaYibBS+aAuHKw22J27M96+LXF6v3rfL1x0/GyshXzZympsUhdw34pQE4kND/4GM9+7Zs4+aHcY5bgVxbtxcRJgwDMlDJwqWZEvjOZ3OYOEft3eMby4J8dmOZvDcxewEvH2iexs2g+3oL2XIfdL76Ly282OP/unGdXfmXQXge+X1JaRJXsGNFc+yxhiAT8/j/+b3F9eTdtvTdjGfJZygtzQ+Ly9bhkfCMJuh+YSVkJxd5K9xYcI0cRQuCO60hklWbPeEhKxdrw/2vvynksO67zV9td3tbdM0PNkCOZlEzZsgEBAizITuTIuUMHjvS3HNqAnTtzosSAEht2YIiWQJAamttwpqeXt96tqhycU8t93UN2DymxJb4T9Ht9t1revXWrzvnO9w0WaNkH4FwipXWOiFtH6FEumz9zgE5Mwc+jNADQy+hLAXhw7HtasoVcmLB8U5LO60PYgf0qXXYsD3Qi1CdwsXBeiuhtXHaJkL8SIkZ5H4LDqOG3GBxds+2Ssnpst0uUA+BlXdeTr4aXNxJg9KaDzHxdekM+GG9l9K+Intb4Ubc09KP1kL2llPFARNz2RMPfc35GLvZjKfQYtsnMT1ZsHPmYgMgXoloLs05o3Ihk5XAKOWbJmakbG8FewqYcmhh9GrjPraHyh+DPsSiWmnJmgl/eAWpno1/HhciHFlA7C7XbE2G6hb7t7+1gMdIvjXiKsO0Gq6tIo8/aHsyxEBm0hCCeSqXSgLGPEv3CMjgRIDIxcT1DncOMQyt6ewwu4UckKArjHLxLNz+0vhY38pVa/rAHpi6JhE0RIMLfwSXmqQGA9BDCJWQpDzY+IDlzVrJXsYxZDMLDg/AjoW8iy5SRUcZRCgHZWcKcGBWj2BLkiCRGLH5QcQt5rswi+xkoHBvZukLSmPMp5TwLewqHOAuK+ScqzARU0oEtFcT2Gk+k4HCukSm0LjEKiUfqCvmKfZ7Z3RgsOO4+2uQ94F1cQozM2kTPP5CkIayCYN6JfSnDay1GOAZ4qSC0IyIbftP6piUWrK6Pb+NbLdi8TzMLju0J0A1KoVCbmtwP5Kj1nkiBAQijaRkjRIoqAPBtN6Lf/8rN+/SmtY5+B+khvEzK5kbGN1zEVHiSihQZCVEQP8Jg4aVMmb7X4VJuYOGN6yWHYZ2D7NLMQmgJOTg4ACqEdAcHWAphCykiaTCsg1QCSomr8gG3NNn7mLnqIKE6N8oaFQPPDl0Wag6hcus4g5e3b3uqa2vjctC/ZHYsBg/VUwZwmJXagsB20tG9J/nF6V45ISdr55e+wsEOdrBvhN2NmcVtTYo0v2J5QiFEWn5Iea1Qy7UmsuVLELoJZajx8kZIebvZRUxASxiChLqUmQq64jUmkmiOFKzs7kbCQYJFbH6rFgmGuaygthacnKzCJgaXODytT/UMzkpHNPxxOaLS7+ODL+QWFlG2EpRtKQnynoB0mWpXmQB6qrfwkHEpAvBElmH+kY/Vvtrbd0TuG1C0QsTZcvxtc1dO4OFQAs4mxCotR2npEbE7Rl1FxfI1HJM0x6TruJymMlOf/aEsQ4BR1ADex6WEb1g52xQY6Yjw8kQoSeArKWAvkzKTOjkCdg0pYa2Z8q4okpMtKHGtWaFsVhPnJaM13XoDyQOO46iDrC3kYg5MajiOOggA/uE9WjdLEZcR9ngGudqOHKZuUsEylZ7+7BJuRhEKdb6CndN29ZsP6brzCXB+CcympG0yI/yFW64gqxL29XukSwLEgdHNagxHiSfNPDWwkxJyvYM9pvPV6ZIffNINcQui1ZMDOWS7hzPoFfftSOtURfzE5nGN6cc7OCFgp0mDQm0k1LYBXpDqV47udifzqHPi2KfRPbwHc8HRhcrQer8gfZLgiOsXJcyyhXpu0DE1YD8jrVO1s7B1WpJtHhpUF3uO5kKivW9QnvfoFgazp5dx3/Bwhn6qUfAg0b55D+2Jgdo59DOJ6izhEWwlYSuJ8oz6qzvW8FJgJkgAyEuONjG5rq0UVt+mupkN4kDRzRkkVQJeA2bpYTaEowCA6ccEHMt9FKIbsPzBMfqJwPzDAmpL9Vq+VeLshz5iPwCgPZEoz1UsbwgcnBXl0UyeVWjuJVDW8Kubv3juzmBxG8sdjeG7UmP2bhneLNd3hg8Q7iBRWHCSWJF1yb5DU4WkM50Su6SEC1qnQBzwbKUhG72XFq9iKrY2iUlc6rRdxTCrJp+J0ZyspuP1vdH0UO35LrxRGDKhYKMVvTmljElcMlxHK8phCG9aXvMOtYLsuF5ZW2ylYt36qaT29Q5DJoUnBg+pVYSs5+a4P8L3UJbaBqbvkJpPsGoxpP/VjsoOqe3DREJaIquxdfp9u7mA6se/t+wpYUw1RAPgM83UoVa0jWdCQ0Xcm4Dk5LkEOBtqSfqnHLXoOZUeSqA99pHlPIgMqU6iX4ydjADQLcDtolwP0nsFumNGgJYKwqYBOFg/EehnAraSkEz6280F3IMWfSaG3S0A2ac8Gsus40NFAKx+CvSBDDwFZ25kd2qw2NcWHe+jaIGcTIisN7B783ff7Kl3O3auuWyEntQ0g+kHCCbYDVgFebEG2i7G9y1fk/9JZWkNsW3IgQTADxZylbAYYFyIfr6E2LUjSUY1WFQcYhPLDXRw+K02qD5lPoQA975Yw+8aisrwZ9gvVxtoo6PuZsBDyCVQ5uQuuxbKe4i2g75gx+lmR/3CodOYV1ZV8F2P+pMNxJYJigNr+NpEgl8AWFgPc7oGrINapRtbND2w2iQFt8xCfwCI7ZbDLGIZ1E4TTFrLGEoGgGpwic36U8I1F5UhZyHjIWIZ2wp6vRcaHBy8UVDrFmZZEH6Grf6kQFEbyEvaVtUGujGQnYOpFUy4lvMwK4XKSOgLbsOmiEuP+//jMfuIneuK6Pr1qk/qc7uE4g0DnjNE12+2FnrnMDmldphn63HIlm3+YQFbSZjlEJ2pJ+/2ELbC0XsJDzJ5rmGW6Z5zZcqC7mbEQl6dpxFCJ5L5L7Q7NViMbJ/5Sso0S8gHk4g1sONznKfBJwvZCa3p4VUKnj3g8WFuWort7zFljcxaCrM6Fz37AfwCR2v2KFq0a0mKMF8HB98KAN+2cQnruz4CbaJsQcMDTdvFz7DfB3yCG18bzkHmMgW83edCw9aSXyREasI1yoLqtt6lmzUA31h4OvSHvlRUX+fHuJR+IDDccHV9LUN/IC3dZVnEegkhKDSaJd4BjGtwDl6rCIgSfcLE+Gx2VQBR9jCac/BKQW4bGjj6tF+sd9DdkJjiuwGykZQfNNUJ7NY7SCkgmoH6FwAkLZ1cqTF51kdJQUjyi8htF1m4Qy4HgEhc4w1lLquGuFgDhFtsm5EodDC1HSBb4gsN/pjirMGsligu0mChWjfCUrigF6MlhqqEWQ+jsF5kEL+BHaIhBzvYwW5kd2pmMVJRD9DtoKLODk27XEI9/FZyWs6mwGoNMZ0mVJ1z5LHfdRAMbAIAe/oiXl9+/7v0udwAQsA+OoHcdgnGu2tINd1a+A2L6U4n5KGeT+EndJzYNaTtsWT49zk594Yf/wB62URxYQDoj2p0x9Su+pMJ+gUtWczZFpu3FoAHJgx/Hr73OszTC7h5DXm5gZ+xI/KzU/hHr8Euyri0CIhLdzRBez/BvesPl3C1gex6DPdZhT3MJIwG+gHuiK4rfv0BAGDzF3+GYhnYwmn6bCcatkxZkKtvG8w/nkN2LiaAAYBZWRTPNnEpF/EazpNK/SW9AbtjqmM/06hOabZg6+TH0DsLxSn17b0S5VkL/dELrH9ERPHdPNMNyWj11m9IEgXOg2UdpaxXFxbtkcLJO0E/0GP9vRm6ucS9X9Jv2d6v0NxT0A35OXIg0zCR6KYSk+fkyGxYN+Tkv1/gvb+b4vidEwDktBwmAtWpx+qP6HwT2Lc9UeFROz28ojTzYkVJYQDw7Z8/gt5Z9tsksNnyrRLdXODk3R7FGfXZpz+do/3JGtUvFrEPmvtAdVoTKtkn9TFbUfntcRWdqcID/X/dPEpypwaL3ITRDLYKG7Kp6aROsOX5FKJtIWaTKAbkvYdg30b4BDBaEvQPKEPVAICU2D6eoLgsYkbk4kkJfzSj6T5PC/1iBliL4cEsPvST9Q67N6aYrPnB5WjI+o8q1Kea1KX4pts9MNg+DA7FGXYP6PvUSJx/30A4YPoO/brbxxVm3Qz9cYUCQPeAHvZquUHzaIrmvsEkOC15fd88LLF+lB5e1c7QHWtURmH9HbruLKDjObrRPKQHZfYbavf59zXqU3bCNgSF7+YC/ZSkAQHg8s8thomB2fh04zmgPFM49mMpgaCstXyzQv2cbrftw5Q9Oi+pXu2Cft9+JmDWGiUPvus3FGa1xOJygou36bzmvid1rg3QHUXMG4Y/3WL7UU2OQ4Y5qw0J7tTPNLavO5SXPOj2Hud/orB75FBdUB1Wb2hsHxOFfz/3mHyc/DH9AmiPPbr/M/z70PVnH87w93/z7/gn/VO6R0qH8t4Ou/dneO1HTwEQXb8HhXvfekQvrLcXz1GrHv978QgfvDjB3/7xLwEAP3/yVyiWGk6TAjxA2bxnP/RwD1oIW2HGTt32J2v8+qf/iLeHn8V6/uDxU7zz5A0I7eCdwHxB9+Pr8zV6q/DBk9fw5luUB+S8wEf/cnPU6p0dLHxgqcr/D9+3u8TLsN7C9QOw3WUaIg5+u4UfhvhJJ6bBwpyu+fwdIAUmH2nIZoBipxSGgdaP/QAfGLe3DXzTQgNQnOqNyzXqj0qAnWRhBjT/oIFaNcRREXRDmhIFPwTlsx30hgYcvWxw8q4kohJu1+STBnLdohgc5LpBzCTue5SnO5hlBxXWydw3k2YCs0wzi+LTJfRlCbnaYs4DpTpjBx/7ICYNPTxhQL33q4HWtQCl10sBWytK/Q6I863G5PkAvbOoLhJZj1lbmBfbWH6cVVmHxQcmJnGpluo4fSpRnlIb6pr6xdZqlMNQrCoUZw3ExQon79JrufuUiJN1w1EIrtfuxQTFZSC/EVwWEeAUG4v6uUL1PDhvHe79WmL3TKL6jJ2Wa4vJcw298xhqgfI8zXRtpSicekptmPDAZz5b4p//7a/x4B06zhmFfjZH/cyRUhgQdT2ERSTX/WhGsyTVCJRr4F/f/0sAwOMnPVTjRnwWXlNqfD8rcfReG30U1S8WeHv4Gab/Ucc+eH/xXRy9SHDygR3unxQnEBa4f+px+h4lUQoP2NXVyMvL7M4OFl9kkfzmVS8QBiKfYc33tT329T5uKQUQPwOgiinqveBQ5XXXC8sEn5UfdDf2r/1bsCtyB7H9abAIdPO5NkekgMvr6Tj5bE8C4JU1Q3LH3Eu/ewifFOlH+hx5ffl7bMuXMX/1+4j2f6+Oo3NeWs8kJfEylYv8nPF3vsn8NeV+CTs4OA92sIPdyH5vZhYj3ZAcdh0yBkN2I0Bvsi9gyvKBh6FpAdbPENZHXYm48hciDe1CEINXWcBNeAlRGNhJAV2MmbKGiWb5v+TgtJWOYsDlmYKdcFmbHv0kMEAncA68JxyBSGzi3hLEepgVSf6QocB2atDnQsVnBezUQLYGw4zqq9ZMz1doiG6ICEwTGL4WKnaUagncM0xZGJmTndoTgXLJvAx1mJUJyq40KvFhZKTGQ62jbyUAx/q5gt5R+f00aHdIaC3ia6xbKKjWQBUGPWuUdHPSDdHKo5+kGU9zD4CTI6YsLz2clhCOWbW4Sk4T7qCfCjiGrPcLjeZEwpR0XWnT4xF0QxQD1poTOmdRF7CPWrSf0nTfGWCYkpp584AqZlbJoRg0O9zUAtpDXmp4LdE/7Lk/FWWjSk4K4/5rTyS6BS1/VEvXaO6Tj+L9xXdTH3zLQjgV2z/SDXEAILF7mMiBv1LdkK/NnB/Du3P/xWDjdN0zNmIU23eUQeq9h+DPfRM7jpd3PSCJaETsOqiA8bdEEothSMuQYaCy2w6Sj/NdD7ntIhAp+Fb0ZqCY/2DjQ6M3CoWmXBOx66EDQUvToViOiXPVtocYLF3DWsiAffAOshmgVZfawGWqTQ9TpMFC7DpCXXY99DprL0A5J9ZCbcb1Li8tzIr9QZFXgQhcFK+hqxcEDlK5LqwHzGagegZ/kiWfh3Aeet1HDISJqFHE8sMSRQ57PotS0TFdH/tIOOLdVI2DHFI0ZKgVqnPHLN/ss+g8vPIolxRhkIG42NM24WUsyywVKkU+C9WKEbhJdgpykHFbxcS7YtdBf3yM6owHeQ0MO4HqgtTM6XdHLFP2YZCV8NLDbATMCnCaBs1i1RM3q0QkaYYQKM8VZE91CvWtTmu88+QNHL1ISynhFKoXPhL22k1AcJLWaXXqEUZi4QF5gwTtYHd3sJCC3hLXKJLR/pTUxAdk595gdZUldKXvYnzdkPgls2PlHrnLHpV+uj4oWSpLx/aCjqPPdEMHaQFSJMuuJ4gnQeQJaILV2F6WGPQyJ85NE4m4bvF7SIjiBC0ATHMv4a1PbfBI8gQMlIrLaInUl+C2B2r/fTmDUH7eZwysG3EzeJ9mEKEg/p8SrHiTRRw8nBKJf8MRv6hTYny/CMGOjOt+T4yP489cgsBLRPmCXB4AALwXGW+Fj8fkOideCpZIEAklzIpmV3ROJSjqoRB3xmsyybLPfsvEdREugFvZ3R0s9mYWV/fv7RuhN2+ZPbjPhhXL33Nwvqow8t7YFXU649PkM61Tn84LTq7cGerdl3fI3dQ8/wnFRUcvIstTctBlxwUEYnzb7bXBAUK+Qhuu9NeeIzE6Wz0kUkjXi6zOkavDx/1f1mEsRnUL17ym7rnD0/GJe47XEStaZLB/SbkelH27X941ffJV2N0dLPZmFlf2ZdqiHhgnffFsIbyRr/NZxLTkkNJrJHyflL/izEKp0cxCeA8vU6qzFIISyULEI5RlJL3FvEosSkbFdag3aqQSZksB4dKMwRtOWtMypmIDfH9pCaclVGhD8Jobmda53MaYSMbnq/AW1ewTCToaQUmtlFCB3p8Y8eEKmZKqkJSx4ERU5hKetE+8Eomch5dUXni4IvF4BkUyV2bKY2GfkXCDhzDZ/0ZCCQEXMihLQSk/XkaVMoAASMQMjhTgEqTnaXaCgFYx4c/DFhK2QqpXKUlhzdOxJmvzUFFbQ65FUGKDVhimjhLgQP1ia6qjZUBUiBQJN/YheAXAAdKKuJ3aS7OOQFzjBWey1lR+gHAPNTBf7DDUVVqKTT1sphsSQVmsdTpUAsPEhy64Kij1OXaIhhzsYAe7kd3dmcXn2EiSMJs9jGYOwYfxshR1lc0EJBO7qOzNAzDJTrZQDDMNrdJxir/vpbM7ZmSGy3wWmvQy6TwR9TmgxAj0FI71oV45f6WQPLPJZhs+JCepdH0gkb2EGQaQ/AlaEulOcDaGiE2mPxr1Mw3VT7jkLKOZhcx0UQGluZ7xVZrqQnoeYRZBfWJN6u8wI7KlgLASskv/U//K2F+2ID1SN3iaWXA9bQXYAlGyMVTMGiqL1MLCDgdr6FrB72ILCVsAwgrYAqNZmi0EhiqrZ8hGUAJ+YmOKvTPEVWFLgnQDSKpfHmPtUeVhBwXb0TXofBl/+0iFJwXxUXD54Xe3FSEzPylOUj1rgqqHmVUsj2cWthZxG7y41czibg0WGflNTAvnKIesKopuABTd4OxBz4zb3vuY1QgA8t4JMNQkSBSyHauSWKKFSJ5mx6zNTC0fJON811MmavgOUJnHCxI15hCrr0uioH9GRLqCRZFI7ckncWCAuSDDDeTSM9VbyJD9F1LmWwuxaykzs+0gekaMti1kN8AWNSSHb2VPhLTDVLPwMj/UiwrdMZHKhNRoUxAXh9MSshvQzzl0ev+Esmm5LwBA2rC+J1LcILcYoiPS+lRvEFJS9JbS4PdM9j7JLPa0qLaFwhBCplMJp0h2cKhUnNYPlUC/0NAn89F0XjhPkolZ+YLX7zljtewBp6muwgqobeLbVD1FS0IIOnBGQACbxwLC8XJsIB4Ip9Oyy1YC/RTYPZ7z/ZPVzY79FiJfSUf/DwBFA5OwAHhAoazRq06KoSY+im5G2aPhWr1VY58G1+WKE9MD6jtbDKtZFGe+jvv28+xuDRaZjbgpAAopBv9FFg4VWYh0dHzbEfR626SwqiAvuncukrSGgUBuu3FI1Np4zUQOTDoXMnOIic0OxXlDA4sQcWDSaw5tZjD1PLQpdh30mmcjXQ8TQ6c21ue6FHVvLUTbwSx76CWntXN4VlhPd1QI1Z7viO7+cgfhKbdEbCk1XnLaehmYx9dbwDsUSxs5IWJqtUshTQCoXyiY1ZC0ONn0uh/R+4/3pVBvaHd1LmEuOy4rkOAQ4W1IJFNHBYqLDnK5hVnyAtxr0i5tLGQmfdBPBKrzcZ3kAOhGoFhynsouDRbF0kI4GUO69QsL4SgnRjUS9YvElFWsyZ+RIOAa1RlQPd2i/OQI5XmKXAwVUJ07dM94gF77+FCG0KktJZwBikva7yXDx1e7K3T9ADFc9VOgPktw/Pa4wgdPXsP90/xZkRQeDTgL9q3YWmBYzTB56iH7pBsib0FofmcHi6uh0szhmQGtcvDV6HytiFG6MPDbveFTSmLTBqJYkJ0UUNZHsJVUKl4z0vNrDRgNXxdwEzpPMShLsXxhWI4E0FTOnZiDpoqzYgSUCttLPt9OCmit4cuCSHRCfZUCygLDVEP2DATraakyTA26o0y+sDYYJgaitehnDABbmeQ47SUGBmWVSsJbAkEJVhVWLYOVpjqBpQDs7kuUFxpy8OgW4+WXviyS7khmOYgstLs9UlAt1aufERXcUEmoVsLwoN0tFGSvoY1Gv+AEtAVlnZqtIFAWW/Mgj/vyz9HRW1kOCs2JxKJOen3dQqE9EphxXkq3oGPM1qNbCKg+OJBpIBomAooHp+aElgrzWqN9o0f7nLOODZUnvMTuW7wEqFIdAyjLThxgPLOQiSgpGAWA9qy5J9DPQcQ1YRL6msCbbz2PuR4AGHCVwszBmWlrDzt1kL3G7lGIVolbgbIODs6DHexgN7I7O7P4XBvR5/mr20bHvqJegnNX8RUvK+M6hOg1iWKjpJ4sUei3bSGBDQCtlb8MxgH77dg/7ubXvjbJ6Zptn3vc3r6XHutvXt7nbr9u/3UYB5+5A3LfgE+hZp8n430RLsJf3Sc8pZnvJ9Xl2JOE5RFZWbdwVGT2+zNY3EJmDQAiZdx12Z3XDSBfNOgEi3R06fgIOgKux4WM6nXL7S8x4ZGctJbuAmH92JnmHDkpnUsgJO/hnSBHmE0AIG8d4Oxe2/bqln96XO2rz+m7fPCMg6RPzsjgpBOGHKlRoCf0r7XX1yO3ax6oqw9ytiFkZ4Y62uAIBQsHZY5SK7gufKwDw7fd9Q/7fl2uPLwYDSgi1uP6PgwOU3IuJwelvQLr3P8Mg5OH6IO+6rVFfKHdCWFkIcRzABsAp193XX7H9gCHNn8T7C63+U3v/Ws3OfBODBYAIIT4T+/9j7/uevwu7dDmb4b9obT54OA82MEOdiM7DBYHO9jBbmR3abD4h6+7Al+DHdr8zbA/iDbfGZ/FwQ52sLttd2lmcbCDHewO22GwONjBDnYjOwwWBzvYwW5kh8HiYAc72I3sMFgc7GAHu5H9P7epNGQe5WrwAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.22583031654358 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 0.001, 'kernel_type': 'untiln'} is: \n",
+      "[[1.46106049e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [6.60000000e+01 1.25190017e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.46106049e+02 ... 1.62106049e+02\n",
+      "  1.62106049e+02 1.62106049e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.62106049e+02 ... 1.71890463e+04\n",
+      "  1.70778052e+04 1.67641098e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.62106049e+02 ... 1.70778052e+04\n",
+      "  1.70162400e+04 1.66950729e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.62106049e+02 ... 1.67641098e+04\n",
+      "  1.66950729e+04 1.69322250e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.909806966781616 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 0.01, 'kernel_type': 'untiln'} is: \n",
+      "[[1.56246080e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [6.60000000e+01 1.36457170e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.56246080e+02 ... 1.72246080e+02\n",
+      "  1.72246080e+02 1.72246080e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.72246080e+02 ... 2.26768195e+04\n",
+      "  2.23045489e+04 2.23285833e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.72246080e+02 ... 2.23045489e+04\n",
+      "  2.25500437e+04 2.29275891e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 1.72246080e+02 ... 2.23285833e+04\n",
+      "  2.29275891e+04 3.01003948e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6518>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.43777418136597 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 0.1, 'kernel_type': 'untiln'} is: \n",
+      "[[2.77160000e+02 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [6.60000000e+01 3.22271949e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.77160000e+02 ... 2.93160000e+02\n",
+      "  2.93160000e+02 2.93160000e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.93160000e+02 ... 6.95075231e+05\n",
+      "  3.75446134e+05 1.77422769e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 2.93160000e+02 ... 3.75446134e+05\n",
+      "  6.06927235e+05 3.37486233e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 2.93160000e+02 ... 1.77422769e+05\n",
+      "  3.37486233e+05 1.90218793e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7c18>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.17743968963623 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.57700000e+03 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [6.60000000e+01 8.91640000e+04 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 4.57700000e+03 ... 4.59300000e+03\n",
+      "  4.59300000e+03 4.59300000e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 4.59300000e+03 ... 2.01159621e+13\n",
+      "  3.10057363e+11 2.42784376e+09]\n",
+      " [2.00000000e+01 2.00000000e+01 4.59300000e+03 ... 3.10057363e+11\n",
+      "  4.70005886e+13 3.01441455e+10]\n",
+      " [2.00000000e+01 2.00000000e+01 4.59300000e+03 ... 2.42784376e+09\n",
+      "  3.01441455e+10 4.04190794e+12]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.14870548248291 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 10.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.49598500e+06 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [6.60000000e+01 3.44783080e+10 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.49598500e+06 ... 1.49600100e+06\n",
+      "  1.49600100e+06 1.49600100e+06]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.49600100e+06 ... 1.13768199e+29\n",
+      "  3.31210879e+22 9.96117761e+18]\n",
+      " [2.00000000e+01 2.00000000e+01 1.49600100e+06 ... 3.31210879e+22\n",
+      "  4.45961208e+29 8.59201597e+20]\n",
+      " [2.00000000e+01 2.00000000e+01 1.49600100e+06 ... 9.96117761e+18\n",
+      "  8.59201597e+20 4.16855423e+24]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f548227f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.13812041282654 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 100.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.30059054e+09 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [6.60000000e+01 2.16311217e+17 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.30059054e+09 ... 1.30059056e+09\n",
+      "  1.30059056e+09 1.30059056e+09]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.30059056e+09 ... 4.75063841e+47\n",
+      "  6.90580493e+35 4.43539095e+30]\n",
+      " [2.00000000e+01 2.00000000e+01 1.30059056e+09 ... 6.90580493e+35\n",
+      "  1.89563663e+48 4.03114835e+33]\n",
+      " [2.00000000e+01 2.00000000e+01 1.30059056e+09 ... 4.43539095e+30\n",
+      "  4.03114835e+33 1.44634079e+39]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.19795370101929 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.28204910e+12 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [6.60000000e+01 2.05928848e+24 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.28204910e+12 ... 1.28204910e+12\n",
+      "  1.28204910e+12 1.28204910e+12]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.28204910e+12 ... 4.34301799e+66\n",
+      "  5.56520941e+49 4.06947164e+42]\n",
+      " [2.00000000e+01 2.00000000e+01 1.28204910e+12 ... 5.56520941e+49\n",
+      "  1.73677414e+67 3.72852519e+46]\n",
+      " [2.00000000e+01 2.00000000e+01 1.28204910e+12 ... 4.06947164e+42\n",
+      "  3.72852519e+46 1.29135037e+54]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.94748830795288 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 10000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.28020481e+15 6.60000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [6.60000000e+01 2.04912664e+31 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.28020481e+15 ... 1.28020481e+15\n",
+      "  1.28020481e+15 1.28020481e+15]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.28020481e+15 ... 4.30411880e+85\n",
+      "  5.44017562e+63 4.03435025e+54]\n",
+      " [2.00000000e+01 2.00000000e+01 1.28020481e+15 ... 5.44017562e+63\n",
+      "  1.72160449e+86 3.69944820e+59]\n",
+      " [2.00000000e+01 2.00000000e+01 1.28020481e+15 ... 4.03435025e+54\n",
+      "  3.69944820e+59 1.27668843e+69]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.22443652153015 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 100000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.28002048e+018 6.60000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [6.60000000e+001 2.04811264e+038 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.28002048e+018 ... 1.28002048e+018\n",
+      "  1.28002048e+018 1.28002048e+018]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.28002048e+018 ... 4.30024696e+104\n",
+      "  5.42775940e+077 4.03085248e+066]\n",
+      " [2.00000000e+001 2.00000000e+001 1.28002048e+018 ... 5.42775940e+077\n",
+      "  1.72009448e+105 3.69655206e+072]\n",
+      " [2.00000000e+001 2.00000000e+001 1.28002048e+018 ... 4.03085248e+066\n",
+      "  3.69655206e+072 1.27523034e+084]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483efd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.03231167793274 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.28000205e+021 6.60000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [6.60000000e+001 2.04801126e+045 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.28000205e+021 ... 1.28000205e+021\n",
+      "  1.28000205e+021 1.28000205e+021]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.28000205e+021 ... 4.29985996e+123\n",
+      "  5.42651865e+091 4.03050285e+078]\n",
+      " [2.00000000e+001 2.00000000e+001 1.28000205e+021 ... 5.42651865e+091\n",
+      "  1.71994355e+124 3.69626257e+085]\n",
+      " [2.00000000e+001 2.00000000e+001 1.28000205e+021 ... 4.03050285e+078\n",
+      "  3.69626257e+085 1.27508461e+099]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "../pygraph/kernels/treePatternKernel.py:150: RuntimeWarning: overflow encountered in double_scalars\n",
+      "  kh_tmp *= lmda * all_kh[str(pair[0]) + '.' + str(pair[1])]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.948474645614624 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 10000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.28000020e+024 6.60000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [6.60000000e+001 2.04800113e+052 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.28000020e+024 ... 1.28000020e+024\n",
+      "  1.28000020e+024 1.28000020e+024]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.28000020e+024 ... 4.29982126e+142\n",
+      "  5.42639459e+105 4.03046788e+090]\n",
+      " [2.00000000e+001 2.00000000e+001 1.28000020e+024 ... 5.42639459e+105\n",
+      "  1.71992846e+143 3.69623362e+098]\n",
+      " [2.00000000e+001 2.00000000e+001 1.28000020e+024 ... 4.03046788e+090\n",
+      "  3.69623362e+098 1.27507004e+114]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.88337850570679 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 100000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.28000002e+027 6.60000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [6.60000000e+001 2.04800011e+059 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.28000002e+027 ... 1.28000002e+027\n",
+      "  1.28000002e+027 1.28000002e+027]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.28000002e+027 ... 4.29981739e+161\n",
+      "  5.42638218e+119 4.03046439e+102]\n",
+      " [2.00000000e+001 2.00000000e+001 1.28000002e+027 ... 5.42638218e+119\n",
+      "  1.71992695e+162 3.69623072e+111]\n",
+      " [2.00000000e+001 2.00000000e+001 1.28000002e+027 ... 4.03046439e+102\n",
+      "  3.69623072e+111 1.27506858e+129]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ad7ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.987963914871216 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.28000000e+030 6.60000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [6.60000000e+001 2.04800001e+066 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.28000000e+030 ... 1.28000000e+030\n",
+      "  1.28000000e+030 1.28000000e+030]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.28000000e+030 ... 4.29981700e+180\n",
+      "  5.42638094e+133 4.03046404e+114]\n",
+      " [2.00000000e+001 2.00000000e+001 1.28000000e+030 ... 5.42638094e+133\n",
+      "  1.71992680e+181 3.69623043e+124]\n",
+      " [2.00000000e+001 2.00000000e+001 1.28000000e+030 ... 4.03046404e+114\n",
+      "  3.69623043e+124 1.27506843e+144]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.82059717178345 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 10000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.28000000e+033 6.60000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [6.60000000e+001 2.04800000e+073 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.28000000e+033 ... 1.28000000e+033\n",
+      "  1.28000000e+033 1.28000000e+033]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.28000000e+033 ... 4.29981696e+199\n",
+      "  5.42638081e+147 4.03046400e+126]\n",
+      " [2.00000000e+001 2.00000000e+001 1.28000000e+033 ... 5.42638081e+147\n",
+      "  1.71992679e+200 3.69623040e+137]\n",
+      " [2.00000000e+001 2.00000000e+001 1.28000000e+033 ... 4.03046400e+126\n",
+      "  3.69623040e+137 1.27506842e+159]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483ee48>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.216524839401245 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-10, 'kernel_type': 'size'} is: \n",
+      "[[8.0000e-39 2.4000e-39 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [2.4000e-39 5.2000e-39 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-39 ... 8.0000e-39 8.0000e-39 8.0000e-39]\n",
+      " ...\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-39 ... 1.2052e-36 1.2052e-36 1.1662e-36]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-39 ... 1.2052e-36 1.2068e-36 1.1666e-36]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-39 ... 1.1662e-36 1.1666e-36 1.1376e-36]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6518>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.29392218589783 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-09, 'kernel_type': 'size'} is: \n",
+      "[[8.0000e-35 2.4000e-35 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [2.4000e-35 5.2000e-35 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-35 ... 8.0000e-35 8.0000e-35 8.0000e-35]\n",
+      " ...\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-35 ... 1.2052e-32 1.2052e-32 1.1662e-32]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-35 ... 1.2052e-32 1.2068e-32 1.1666e-32]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-35 ... 1.1662e-32 1.1666e-32 1.1376e-32]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.02691984176636 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-08, 'kernel_type': 'size'} is: \n",
+      "[[8.0000e-31 2.4000e-31 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [2.4000e-31 5.2000e-31 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-31 ... 8.0000e-31 8.0000e-31 8.0000e-31]\n",
+      " ...\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-31 ... 1.2052e-28 1.2052e-28 1.1662e-28]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-31 ... 1.2052e-28 1.2068e-28 1.1666e-28]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-31 ... 1.1662e-28 1.1666e-28 1.1376e-28]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.20295572280884 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-07, 'kernel_type': 'size'} is: \n",
+      "[[8.0000e-27 2.4000e-27 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [2.4000e-27 5.2000e-27 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-27 ... 8.0000e-27 8.0000e-27 8.0000e-27]\n",
+      " ...\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-27 ... 1.2052e-24 1.2052e-24 1.1662e-24]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-27 ... 1.2052e-24 1.2068e-24 1.1666e-24]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-27 ... 1.1662e-24 1.1666e-24 1.1376e-24]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.21203565597534 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-06, 'kernel_type': 'size'} is: \n",
+      "[[8.0000e-23 2.4000e-23 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [2.4000e-23 5.2000e-23 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-23 ... 8.0000e-23 8.0000e-23 8.0000e-23]\n",
+      " ...\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-23 ... 1.2052e-20 1.2052e-20 1.1662e-20]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-23 ... 1.2052e-20 1.2068e-20 1.1666e-20]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-23 ... 1.1662e-20 1.1666e-20 1.1376e-20]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.22126078605652 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-05, 'kernel_type': 'size'} is: \n",
+      "[[8.0000e-19 2.4000e-19 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [2.4000e-19 5.2000e-19 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-19 ... 8.0000e-19 8.0000e-19 8.0000e-19]\n",
+      " ...\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-19 ... 1.2052e-16 1.2052e-16 1.1662e-16]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-19 ... 1.2052e-16 1.2068e-16 1.1666e-16]\n",
+      " [0.0000e+00 0.0000e+00 8.0000e-19 ... 1.1662e-16 1.1666e-16 1.1376e-16]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.27983570098877 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 0.0001, 'kernel_type': 'size'} is: \n",
+      "[[8.00000006e-15 2.40000000e-15 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [2.40000000e-15 5.20000004e-15 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 8.00000006e-15 ... 8.00000006e-15\n",
+      "  8.00000006e-15 8.00000006e-15]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 8.00000006e-15 ... 1.20520001e-12\n",
+      "  1.20520001e-12 1.16620001e-12]\n",
+      " [0.00000000e+00 0.00000000e+00 8.00000006e-15 ... 1.20520001e-12\n",
+      "  1.20680001e-12 1.16660001e-12]\n",
+      " [0.00000000e+00 0.00000000e+00 8.00000006e-15 ... 1.16620001e-12\n",
+      "  1.16660001e-12 1.13760001e-12]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.51435422897339 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 0.001, 'kernel_type': 'size'} is: \n",
+      "[[8.00000640e-11 2.40000000e-11 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [2.40000000e-11 5.20000400e-11 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 8.00000640e-11 ... 8.00000640e-11\n",
+      "  8.00000640e-11 8.00000640e-11]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 8.00000640e-11 ... 1.20520111e-08\n",
+      "  1.20520114e-08 1.16620086e-08]\n",
+      " [0.00000000e+00 0.00000000e+00 8.00000640e-11 ... 1.20520114e-08\n",
+      "  1.20680118e-08 1.16660090e-08]\n",
+      " [0.00000000e+00 0.00000000e+00 8.00000640e-11 ... 1.16620086e-08\n",
+      "  1.16660090e-08 1.13760101e-08]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f548227f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.34047889709473 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 0.01, 'kernel_type': 'size'} is: \n",
+      "[[8.00064002e-07 2.40000000e-07 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [2.40000000e-07 5.20040005e-07 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 8.00064002e-07 ... 8.00064002e-07\n",
+      "  8.00064002e-07 8.00064002e-07]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 8.00064002e-07 ... 1.20531122e-04\n",
+      "  1.20531398e-04 1.16628618e-04]\n",
+      " [0.00000000e+00 0.00000000e+00 8.00064002e-07 ... 1.20531398e-04\n",
+      "  1.20691794e-04 1.16669014e-04]\n",
+      " [0.00000000e+00 0.00000000e+00 8.00064002e-07 ... 1.16628618e-04\n",
+      "  1.16669014e-04 1.13770133e-04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.12360596656799 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 0.1, 'kernel_type': 'size'} is: \n",
+      "[[0.00806419 0.0024     0.         ... 0.         0.         0.        ]\n",
+      " [0.0024     0.00524049 0.         ... 0.         0.         0.        ]\n",
+      " [0.         0.         0.00806419 ... 0.00806419 0.00806419 0.00806419]\n",
+      " ...\n",
+      " [0.         0.         0.00806419 ... 1.21651795 1.21679544 1.17498286]\n",
+      " [0.         0.         0.00806419 ... 1.21679544 1.21880968 1.17581221]\n",
+      " [0.         0.         0.00806419 ... 1.17498286 1.17581221 1.14809156]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8908>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.193055868148804 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1.0, 'kernel_type': 'size'} is: \n",
+      "[[1.44000000e+03 2.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [2.40000000e+01 1.36040000e+04 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.44000000e+03 ... 1.44000000e+03\n",
+      "  1.44000000e+03 1.44000000e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.44000000e+03 ... 5.60478297e+12\n",
+      "  3.30569724e+10 6.82240838e+08]\n",
+      " [0.00000000e+00 0.00000000e+00 1.44000000e+03 ... 3.30569724e+10\n",
+      "  2.54319069e+13 1.39916459e+10]\n",
+      " [0.00000000e+00 0.00000000e+00 1.44000000e+03 ... 6.82240838e+08\n",
+      "  1.39916459e+10 1.40365885e+12]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.11925435066223 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 10.0, 'kernel_type': 'size'} is: \n",
+      "[[6.40130618e+21 2.40000000e+05 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [2.40000000e+05 5.27567127e+34 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40130618e+21 ... 6.40130618e+21\n",
+      "  6.40130618e+21 6.40130618e+21]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 6.40130618e+21 ... 4.65877907e+75\n",
+      "  1.09712635e+65 2.72264980e+54]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40130618e+21 ... 1.09712635e+65\n",
+      "  1.87682260e+76 6.70356268e+57]\n",
+      " [0.00000000e+00 0.00000000e+00 6.40130618e+21 ... 2.72264980e+54\n",
+      "  6.70356268e+57 1.40492776e+65]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.26025319099426 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 100.0, 'kernel_type': 'size'} is: \n",
+      "[[6.40000013e+041 2.40000000e+009 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [2.40000000e+009 5.12153620e+066 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000013e+041 ... 6.40000013e+041\n",
+      "  6.40000013e+041 6.40000013e+041]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000013e+041 ... 4.30327450e+141\n",
+      "  1.02470680e+123 2.54129819e+102]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000013e+041 ... 1.02470680e+123\n",
+      "  1.72143257e+142 2.65960796e+109]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000013e+041 ... 2.54129819e+102\n",
+      "  2.65960796e+109 1.27631386e+121]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.12768626213074 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.40000000e+061 2.40000000e+013 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [2.40000000e+013 5.12001536e+098 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000000e+061 ... 6.40000000e+061\n",
+      "  6.40000000e+061 6.40000000e+061]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000000e+061 ... 4.29985152e+207\n",
+      "  1.02400707e+181 2.53953778e+150]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000000e+061 ... 1.02400707e+181\n",
+      "  1.71994184e+208 2.62182142e+161]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000000e+061 ... 2.53953778e+150\n",
+      "  2.62182142e+161 1.27508087e+177]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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vDrOQqgAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "../pygraph/kernels/treePatternKernel.py:201: RuntimeWarning: overflow encountered in double_scalars\n",
+      "  kernel = sum(all_kh.values())\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.17251205444336 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 10000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.40000000e+081 2.40000000e+017 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [2.40000000e+017 5.12000015e+130 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000000e+081 ... 6.40000000e+081\n",
+      "  6.40000000e+081 6.40000000e+081]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000000e+081 ... 4.29981731e+273\n",
+      "  1.02400007e+239 2.53952018e+198]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000000e+081 ... 1.02400007e+239\n",
+      "  1.71992693e+274 2.62144381e+213]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000000e+081 ... 2.53952018e+198\n",
+      "  2.62144381e+213 1.27506854e+233]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acda90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "../pygraph/kernels/treePatternKernel.py:168: RuntimeWarning: invalid value encountered in double_scalars\n",
+      "  kh_tmp *= lmda * all_kh[str(pair[0]) + '.' + str(pair[1])]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.465033531188965 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 100000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.40000000e+101 2.40000000e+021 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [2.40000000e+021 5.12000000e+162 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000000e+101 ... 6.40000000e+101\n",
+      "  6.40000000e+101 6.40000000e+101]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000000e+101 ...             inf\n",
+      "              inf 2.53952000e+246]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000000e+101 ...             inf\n",
+      "              inf 2.62144004e+265]\n",
+      " [0.00000000e+000 0.00000000e+000 6.40000000e+101 ... 2.53952000e+246\n",
+      "  2.62144004e+265             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483ea20>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.34155797958374 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1000000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.40e+121 2.40e+025 0.00e+000 ... 0.00e+000 0.00e+000 0.00e+000]\n",
+      " [2.40e+025 5.12e+194 0.00e+000 ... 0.00e+000 0.00e+000 0.00e+000]\n",
+      " [0.00e+000 0.00e+000 6.40e+121 ... 6.40e+121 6.40e+121 6.40e+121]\n",
+      " ...\n",
+      " [0.00e+000 0.00e+000 6.40e+121 ...       inf       inf       inf]\n",
+      " [0.00e+000 0.00e+000 6.40e+121 ...       inf       inf       inf]\n",
+      " [0.00e+000 0.00e+000 6.40e+121 ...       inf       inf       inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8908>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.5672869682312 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 10000000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.40e+141 2.40e+029 0.00e+000 ... 0.00e+000 0.00e+000 0.00e+000]\n",
+      " [2.40e+029 5.12e+226 0.00e+000 ... 0.00e+000 0.00e+000 0.00e+000]\n",
+      " [0.00e+000 0.00e+000 6.40e+141 ... 6.40e+141 6.40e+141 6.40e+141]\n",
+      " ...\n",
+      " [0.00e+000 0.00e+000 6.40e+141 ...       nan       nan       nan]\n",
+      " [0.00e+000 0.00e+000 6.40e+141 ...       nan       nan       inf]\n",
+      " [0.00e+000 0.00e+000 6.40e+141 ...       nan       inf       inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.75461673736572 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 100000000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.40e+161 2.40e+033 0.00e+000 ... 0.00e+000 0.00e+000 0.00e+000]\n",
+      " [2.40e+033 5.12e+258 0.00e+000 ... 0.00e+000 0.00e+000 0.00e+000]\n",
+      " [0.00e+000 0.00e+000 6.40e+161 ... 6.40e+161 6.40e+161 6.40e+161]\n",
+      " ...\n",
+      " [0.00e+000 0.00e+000 6.40e+161 ...       nan       nan       nan]\n",
+      " [0.00e+000 0.00e+000 6.40e+161 ...       nan       nan       nan]\n",
+      " [0.00e+000 0.00e+000 6.40e+161 ...       nan       nan       inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 51.11916446685791 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.4e+181 2.4e+037 0.0e+000 ... 0.0e+000 0.0e+000 0.0e+000]\n",
+      " [2.4e+037      inf 0.0e+000 ... 0.0e+000 0.0e+000 0.0e+000]\n",
+      " [0.0e+000 0.0e+000 6.4e+181 ... 6.4e+181 6.4e+181 6.4e+181]\n",
+      " ...\n",
+      " [0.0e+000 0.0e+000 6.4e+181 ...      nan      nan      nan]\n",
+      " [0.0e+000 0.0e+000 6.4e+181 ...      nan      nan      nan]\n",
+      " [0.0e+000 0.0e+000 6.4e+181 ...      nan      nan      inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 50.82159113883972 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 10000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[6.4e+201 2.4e+041 0.0e+000 ... 0.0e+000 0.0e+000 0.0e+000]\n",
+      " [2.4e+041      inf 0.0e+000 ... 0.0e+000 0.0e+000 0.0e+000]\n",
+      " [0.0e+000 0.0e+000 6.4e+201 ... 6.4e+201 6.4e+201 6.4e+201]\n",
+      " ...\n",
+      " [0.0e+000 0.0e+000 6.4e+201 ...      nan      nan      nan]\n",
+      " [0.0e+000 0.0e+000 6.4e+201 ...      nan      nan      nan]\n",
+      " [0.0e+000 0.0e+000 6.4e+201 ...      nan      nan      inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.36336064338684 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-10, 'kernel_type': 'branching'} is: \n",
+      "[[   80.00000004    24.             0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [   24.            52.00000003     0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [    0.             0.            80.00000004 ...    80.00000004\n",
+      "     80.00000004    80.00000004]\n",
+      " ...\n",
+      " [    0.             0.            80.00000004 ... 12052.00002528\n",
+      "  12052.00002538 11662.00002905]\n",
+      " [    0.             0.            80.00000004 ... 12052.00002538\n",
+      "  12068.00002698 11666.00003099]\n",
+      " [    0.             0.            80.00000004 ... 11662.00002905\n",
+      "  11666.00003099 11376.00005673]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.43159604072571 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-09, 'kernel_type': 'branching'} is: \n",
+      "[[   80.0000004     24.             0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [   24.            52.0000003      0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [    0.             0.            80.0000004  ...    80.0000004\n",
+      "     80.0000004     80.0000004 ]\n",
+      " ...\n",
+      " [    0.             0.            80.0000004  ... 12052.00025277\n",
+      "  12052.00025382 11662.00029054]\n",
+      " [    0.             0.            80.0000004  ... 12052.00025382\n",
+      "  12068.00026978 11666.00030994]\n",
+      " [    0.             0.            80.0000004  ... 11662.00029054\n",
+      "  11666.00030994 11376.00056734]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.40266227722168 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-08, 'kernel_type': 'branching'} is: \n",
+      "[[   80.000004      24.             0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [   24.            52.00000304     0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [    0.             0.            80.000004   ...    80.000004\n",
+      "     80.000004      80.000004  ]\n",
+      " ...\n",
+      " [    0.             0.            80.000004   ... 12052.00252772\n",
+      "  12052.00253822 11662.00290536]\n",
+      " [    0.             0.            80.000004   ... 12052.00253822\n",
+      "  12068.00269784 11666.00309938]\n",
+      " [    0.             0.            80.000004   ... 11662.00290536\n",
+      "  11666.00309938 11376.00567344]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.42389798164368 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-07, 'kernel_type': 'branching'} is: \n",
+      "[[   80.00004       24.             0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [   24.            52.0000304      0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [    0.             0.            80.00004    ...    80.00004\n",
+      "     80.00004       80.00004   ]\n",
+      " ...\n",
+      " [    0.             0.            80.00004    ... 12052.02527724\n",
+      "  12052.02538223 11662.02905363]\n",
+      " [    0.             0.            80.00004    ... 12052.02538223\n",
+      "  12068.02697844 11666.03099384]\n",
+      " [    0.             0.            80.00004    ... 11662.02905363\n",
+      "  11666.03099384 11376.05673453]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acda90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.23563051223755 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-06, 'kernel_type': 'branching'} is: \n",
+      "[[   80.0004        24.             0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [   24.            52.000304       0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [    0.             0.            80.0004     ...    80.0004\n",
+      "     80.0004        80.0004    ]\n",
+      " ...\n",
+      " [    0.             0.            80.0004     ... 12052.25277579\n",
+      "  12052.2538254  11662.29053861]\n",
+      " [    0.             0.            80.0004     ... 12052.2538254\n",
+      "  12068.26978808 11666.30994209]\n",
+      " [    0.             0.            80.0004     ... 11662.29053861\n",
+      "  11666.30994209 11376.56735741]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.552465200424194 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1e-05, 'kernel_type': 'branching'} is: \n",
+      "[[   80.00400006    24.             0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [   24.            52.00304011     0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [    0.             0.            80.00400006 ...    80.00400006\n",
+      "     80.00400006    80.00400006]\n",
+      " ...\n",
+      " [    0.             0.            80.00400006 ... 12054.52809864\n",
+      "  12054.53855958 11664.90562073]\n",
+      " [    0.             0.            80.00400006 ... 12054.53855958\n",
+      "  12070.69824768 11669.09978907]\n",
+      " [    0.             0.            80.00400006 ... 11664.90562073\n",
+      "  11669.09978907 11381.67478133]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483e898>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.31679177284241 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 0.0001, 'kernel_type': 'branching'} is: \n",
+      "[[   80.0400064     24.             0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [   24.            52.03041056     0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [    0.             0.            80.0400064  ...    80.0400064\n",
+      "     80.0400064     80.0400064 ]\n",
+      " ...\n",
+      " [    0.             0.            80.0400064  ... 12077.31509978\n",
+      "  12077.41618227 11691.07968303]\n",
+      " [    0.             0.            80.0400064  ... 12077.41618227\n",
+      "  12095.01920703 11697.0347387 ]\n",
+      " [    0.             0.            80.0400064  ... 11691.07968303\n",
+      "  11697.0347387  11432.86869422]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7c18>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.44603419303894 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 0.001, 'kernel_type': 'branching'} is: \n",
+      "[[   80.40064032    24.             0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [   24.            52.3050584      0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [    0.             0.            80.40064032 ...    80.40064032\n",
+      "     80.40064032    80.40064032]\n",
+      " ...\n",
+      " [    0.             0.            80.40064032 ... 12308.59851448\n",
+      "  12309.24509061 11955.15483511]\n",
+      " [    0.             0.            80.40064032 ... 12309.24509061\n",
+      "  12341.9039208  11980.06421412]\n",
+      " [    0.             0.            80.40064032 ... 11955.15483511\n",
+      "  11980.06421412 11956.93600119]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.52083873748779 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 0.01, 'kernel_type': 'branching'} is: \n",
+      "[[   84.06432       24.             0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [   24.            55.14803684     0.         ...     0.\n",
+      "      0.             0.        ]\n",
+      " [    0.             0.            84.06432    ...    84.06432\n",
+      "     84.06432       84.06432   ]\n",
+      " ...\n",
+      " [    0.             0.            84.06432    ... 15002.11429494\n",
+      "  14958.81018152 14840.0543625 ]\n",
+      " [    0.             0.            84.06432    ... 14958.81018152\n",
+      "  15220.78202071 15212.13305927]\n",
+      " [    0.             0.            84.06432    ... 14840.0543625\n",
+      "  15212.13305927 18585.44572409]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.44258189201355 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 0.1, 'kernel_type': 'branching'} is: \n",
+      "[[1.26720000e+02 2.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [2.40000000e+01 9.57627392e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.26720000e+02 ... 1.26720000e+02\n",
+      "  1.26720000e+02 1.26720000e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.26720000e+02 ... 1.85409892e+05\n",
+      "  1.22282262e+05 8.22036957e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.26720000e+02 ... 1.22282262e+05\n",
+      "  2.17601318e+05 1.47122522e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 1.26720000e+02 ... 8.22036957e+04\n",
+      "  1.47122522e+05 6.59780160e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.27203369140625 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.44000000e+03 2.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [2.40000000e+01 1.36040000e+04 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.44000000e+03 ... 1.44000000e+03\n",
+      "  1.44000000e+03 1.44000000e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.44000000e+03 ... 5.60478297e+12\n",
+      "  3.30569724e+10 6.82240838e+08]\n",
+      " [0.00000000e+00 0.00000000e+00 1.44000000e+03 ... 3.30569724e+10\n",
+      "  2.54319069e+13 1.39916459e+10]\n",
+      " [0.00000000e+00 0.00000000e+00 1.44000000e+03 ... 6.82240838e+08\n",
+      "  1.39916459e+10 1.40365885e+12]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.39775466918945 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 10.0, 'kernel_type': 'branching'} is: \n",
+      "[[3.88080000e+05 2.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [2.40000000e+01 7.56538869e+09 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.88080000e+05 ... 3.88080000e+05\n",
+      "  3.88080000e+05 3.88080000e+05]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.88080000e+05 ... 9.49390179e+28\n",
+      "  1.01435536e+22 5.20690075e+18]\n",
+      " [0.00000000e+00 0.00000000e+00 3.88080000e+05 ... 1.01435536e+22\n",
+      "  4.06220361e+29 7.27100886e+20]\n",
+      " [0.00000000e+00 0.00000000e+00 3.88080000e+05 ... 5.20690075e+18\n",
+      "  7.27100886e+20 3.24424172e+24]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8160>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.385388135910034 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 100.0, 'kernel_type': 'branching'} is: \n",
+      "[[3.26440080e+08 2.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [2.40000000e+01 5.32842072e+16 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.26440080e+08 ... 3.26440080e+08\n",
+      "  3.26440080e+08 3.26440080e+08]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.26440080e+08 ... 4.65756603e+47\n",
+      "  4.26004511e+35 2.73637020e+30]\n",
+      " [0.00000000e+00 0.00000000e+00 3.26440080e+08 ... 4.26004511e+35\n",
+      "  1.87691028e+48 3.90801908e+33]\n",
+      " [0.00000000e+00 0.00000000e+00 3.26440080e+08 ... 2.73637020e+30\n",
+      "  3.90801908e+33 1.40520622e+39]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ad7978>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.35749077796936 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1000.0, 'kernel_type': 'branching'} is: \n",
+      "[[3.20640400e+11 2.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [2.40000000e+01 5.14051588e+23 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20640400e+11 ... 3.20640400e+11\n",
+      "  3.20640400e+11 3.20640400e+11]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.20640400e+11 ... 4.33435001e+66\n",
+      "  3.87487575e+49 2.55862917e+42]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20640400e+11 ... 3.87487575e+49\n",
+      "  1.73503949e+67 3.66943343e+46]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20640400e+11 ... 2.55862917e+42\n",
+      "  3.66943343e+46 1.28757276e+54]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acda90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.331318378448486 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 10000.0, 'kernel_type': 'branching'} is: \n",
+      "[[3.20064004e+14 2.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [2.40000000e+01 5.12204836e+30 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20064004e+14 ... 3.20064004e+14\n",
+      "  3.20064004e+14 3.20064004e+14]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.20064004e+14 ... 4.30325816e+85\n",
+      "  3.83794236e+63 2.54142527e+54]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20064004e+14 ... 3.83794236e+63\n",
+      "  1.72143235e+86 3.64635705e+59]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20064004e+14 ... 2.54142527e+54\n",
+      "  3.64635705e+59 1.27631389e+69]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.4583694934845 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 100000.0, 'kernel_type': 'branching'} is: \n",
+      "[[3.20006400e+017 2.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [2.40000000e+001 5.12020480e+037 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20006400e+017 ... 3.20006400e+017\n",
+      "  3.20006400e+017 3.20006400e+017]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 3.20006400e+017 ... 4.30016096e+104\n",
+      "  3.83426448e+077 2.53971047e+066]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20006400e+017 ... 3.83426448e+077\n",
+      "  1.72007728e+105 3.64405707e+072]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20006400e+017 ... 2.53971047e+066\n",
+      "  3.64405707e+072 1.27519291e+084]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.864622354507446 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[3.20000640e+020 2.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [2.40000000e+001 5.12002048e+044 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000640e+020 ... 3.20000640e+020\n",
+      "  3.20000640e+020 3.20000640e+020]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000640e+020 ... 4.29985136e+123\n",
+      "  3.83389685e+091 2.53953905e+078]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000640e+020 ... 3.83389685e+091\n",
+      "  1.71994183e+124 3.64382715e+085]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000640e+020 ... 2.53953905e+078\n",
+      "  3.64382715e+085 1.27508087e+099]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "../pygraph/kernels/treePatternKernel.py:186: RuntimeWarning: overflow encountered in double_scalars\n",
+      "  kh_tmp *= lmda * all_kh[str(pair[0]) + '.' + str(pair[1])]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.4601891040802 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 10000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[3.20000064e+023 2.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [2.40000000e+001 5.12000205e+051 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000064e+023 ... 3.20000064e+023\n",
+      "  3.20000064e+023 3.20000064e+023]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000064e+023 ... 4.29982040e+142\n",
+      "  3.83386008e+105 2.53952190e+090]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000064e+023 ... 3.83386008e+105\n",
+      "  1.71992829e+143 3.64380415e+098]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000064e+023 ... 2.53952190e+090\n",
+      "  3.64380415e+098 1.27506966e+114]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.492417097091675 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 100000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[3.20000006e+026 2.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [2.40000000e+001 5.12000020e+058 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000006e+026 ... 3.20000006e+026\n",
+      "  3.20000006e+026 3.20000006e+026]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000006e+026 ... 4.29981730e+161\n",
+      "  3.83385641e+119 2.53952019e+102]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000006e+026 ... 3.83385641e+119\n",
+      "  1.71992693e+162 3.64380186e+111]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000006e+026 ... 2.53952019e+102\n",
+      "  3.64380186e+111 1.27506854e+129]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.80697679519653 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 1000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[3.20000001e+029 2.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [2.40000000e+001 5.12000002e+065 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000001e+029 ... 3.20000001e+029\n",
+      "  3.20000001e+029 3.20000001e+029]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000001e+029 ... 4.29981699e+180\n",
+      "  3.83385604e+133 2.53952002e+114]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000001e+029 ... 3.83385604e+133\n",
+      "  1.71992680e+181 3.64380163e+124]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000001e+029 ... 2.53952002e+114\n",
+      "  3.64380163e+124 1.27506843e+144]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 56.761552810668945 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 5.0, 'lmda': 10000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[3.20000000e+032 2.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [2.40000000e+001 5.12000000e+072 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000000e+032 ... 3.20000000e+032\n",
+      "  3.20000000e+032 3.20000000e+032]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000000e+032 ... 4.29981696e+199\n",
+      "  3.83385600e+147 2.53952000e+126]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000000e+032 ... 3.83385600e+147\n",
+      "  1.71992679e+200 3.64380160e+137]\n",
+      " [0.00000000e+000 0.00000000e+000 3.20000000e+032 ... 2.53952000e+126\n",
+      "  3.64380160e+137 1.27506842e+159]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.79759383201599 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-10, 'kernel_type': 'untiln'} is: \n",
+      "[[2.73000001e+02 9.80000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [9.80000000e+01 2.08000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.73000001e+02 ... 2.89000001e+02\n",
+      "  2.89000001e+02 2.89000001e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.89000001e+02 ... 5.49090006e+04\n",
+      "  5.33010006e+04 5.52510007e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.89000001e+02 ... 5.33010006e+04\n",
+      "  5.18590006e+04 5.35710008e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.89000001e+02 ... 5.52510007e+04\n",
+      "  5.35710008e+04 5.61990014e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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mWYyiA3s0i2nUBJzGnn5r3p2kpUsv1izshMonxI5mMYhm8QIch3Sbixd+J4Jk8X73wg56Or9Is1A8g7WZxTANe17kfZqFnfiA0yryvcyJWWVNgxwKc6xZaBv7NAtA0ZCqWbi90DQL0zaoafIzp7oCcoiXy+ces6EYj/AGNAuazzKMPN/r7OxumsXZHLTejJ45dV+GaMhUDuEuDmkW+boJDuN5uIsjNIvyIMZRgBJ/R/n7fWoW7f4TYYrPyNBq99nI75EmmIe9J9v9aBajaMH+u01u4jAO96BZpM22hJrbkn/k6e9MfBSNt9v71yzW671zdBfNAtvtOLQNHIyS7ZNTNOQkJznJUfJuaRavOUXdA6cAwU4gJXDfj9VG4LCGMpFDYCtLlDKsR7q52f3yPh/IMX/b1484cUzt5Xusx8lowCihy2sZ8cEVeLPdi9/YlV306Atlz1gp0ljLMZmYNoCYBRlrcLD959jfzLt/t88ykE7NozgxkXSqiYpmKdpGQnhwheHxk/1N7lnGhzLK8+eH5tWnqKvJMjx+Ij6naSTmQHthNhOtY6Td7AE4HpB3a7N4zVIgsgWgIz/vuNDHNx37NnTRZLmDw+i1yj6z4FDobE80iIcD6eX3Lfv6vYd45oVhxNfVFzMtFOA1/dz7cThx8Wu8ib5B/VAvORfPy4I9Rt6tzeKQHez+doj8de/1k1OL+34n3+OussPKPP37gRTv1y07FPd7aOAOlRXYK133apvoS8iLbPmRvKm+HfTFpP1z/oaed5auA6fjw51exNk9TN6L4+f1HdssfDTD4SqAbJpw147qNBghjVfLR3UgHLOVNz3CYqH3s2zLGjm+DoDX6xw+815881xbe2mzFdyBetStjXh1pZuTW3x1Le0QgdebEgFpO9DiTO73TMyXcH4mG2OM8iJbv7ZbwViEkD3/FuILZ3XJdNQxQHEENNeqb5sJ3FjzF0zFjx99WCDWLpcDVZWBVKN8BBezRz/BWDiNjs7OCmTd+uh4GvLz0yhEnvP5TJx42y3ih49Km8YXWpWoEF0sRhBpL9x18jy138yMcL4A6hrp6bM8J6ibsm48a1iMoLoWohlArgOQrq8R/uDvR3hyXdqNAdi24AtZY9T1eT3zTMeuJg+6HtR2SJcK9/74M5l/yx7VeaKzM6CqwDc3+cCsvvkDGL7yAPHTp2WcTQ3atMX81Ha4iqAhAdsWsD4wg75T1suL5OTgPMlJTnKUvFuaxZGyzwSYpt7uA2WNrp+mhKuJQlOfA6ed+3LXuxCoQnWnNnbb7mABqOscsGgoyUzMsuOnkoma+9d18nev7g6DnC4utAcA2KYxPL3v5bRPnDWKUTp2YvmOdEJ+rDe74dMQxrY5a3LWMGT7WcaaMt8GAHheDGy35f8Olm9aEQfV8Py8uWt4GAoUPnT5/hR7lyU7SD/DxHE6DHJN27lrk2gZdZfHm9oWZElvYcwXQkRgpayTfnb5OcUvnoKX6nw1LE3X52eWwV0uu7TMkTBqhb4k3QmmxIXpOYCvbwQTYuFPAPzsBnFIokF6mLhPBsy4IMlG5b4vCE5OQH+8/+O93CwOSl4gd3QA+Yk1YBAFhfg6Z9tdfAAm0/RuQMBdDoRESVOYNb3ZX4cQRhsYW79eMZ/h+X2eKJyuXED5iAQOn0lmivWbwWYKZqJhyGMZ3f8lHXUZAh405X86FRTKS5kGAZtpX+1a1u8ixB2T5c5i97K2QwTgNtecju7S6Q0sFwOYQ+mD9dFzixLt9ywENXmm5M0TEF3+7HnRoiPkvdwsRig1CgAU4uyh3eZf2MM1AaBwDRiPw9lcbHjjFbDTzyV52X2pacrJsF6LPalsS9nWPl8AdkrlNhuQ2ou8WgPWh/UGdL4AATkMF87m8nlTi8/B+rXegKoKNJsVH4C12TSZ+BUAcLvU3IdW+gj1YwBigzuU4aCh3vDwQfHtWG5JiKAqZmgwnS/AyxUocZ5HAHJybzbl9HYsW7RYFB9A3egmuii+D5vPppZT256Zog7TWngj5Pu1bKDDMPKZ8NU5aLneffmJRLNqavD1rXzECXR5CZ7VGTxFi4WMR7Uj70ynGIBZA15p7o6N+4vH6H/gI1Sf6nNVzYI2W6QH6ofYdPJSJwafqa+jkg2C2h60btE/kmur3x7A3TTPiBAuHoKbGuHJdfGbfPVDbL5xhdl3nhXNcF6D1m2ZA/NZ1BHUJ4T1Fnym/itmYOOe3wvkvdwsjolmSM1Izj93LzB1lAthSHJq/IHsTlY2ZnL/p2HYDdMOAzKrtMkw5M1JQmBOY0hJzCB7yIMmL1n0xd0nmyWOk8HuTz5apNwZPKQdlZjs98npzm1XtJZhAFh5EaST8nnbFQejMkaJ6eCg25j42S0SBch1LCdr3lzzdVQIiSEoSEOMZhMgt8cgd4LTppW+hVC0F7Z1kMZzo32Sk13H1bXS5zTIHHQ+hyJKH/UzGxszI6y0XRt7lYTzY62buXNwZm3BOD/6AdT1CGs1azITOZyDGcC2BQ1JEittbjYtqlW3My5qu9Jer5twH0H9IPfJg+I7hfrf7c3ikHpIoWAbzD51L3dOCWfJ5fAUeFksP8H4DitlprITQ09wpAKZJs1END5EaUtPEvM1WFtVJfyPPi+jrkDGWTkU+5U4yQnPDF6G8v0c3+fCSh3IlTEoL37u3+ikb7WvhYkLscvjJ/uOn9qmLoQpQ8gqrc9U5HkjbfY9oFEWGhJySr9jz8obcVMDlkBc12Uxmy/E+qHRjfzkq0r8EhTK3M0aaY/V22+n6tkMlBK4iiO/CfWSFwIttwDr+6yRU/ZWx0ZBNQvJ+/CbnWkWOSKk80xEGC7noJVqY5rdSczghZ7gbczjTXPVQGZRfWSMsAoYLuTa2vJTYszPgYikr00tGpL5ec5maB80iDfzMgeNPecwjobUEejkkBtpFlOT8zlyioac5CQnOUroraD2JnJFj/iP0r8+/vA5tHr+lAOKn2Avrd4BGd1jmtkJie8fpNWT/2jjXE5Jf//6+Pi1d5yOqpC7WPsIvxACkveAlw6O/+/7Ns2gnX4nq8eTfvuszgkz+ZShHBBIcT7VPZDOq7t6mqW14458kTALvmQiU+dx7lPuA+eMUx4SgqctdFGd3B+/FvZxqI74WJHXaDaR1JFrbe7tm82BFknivi/+mH21QkIQ1m9g1Kcwmwm7+tRRfMC0YI2M+eje3+v/Fq7T46M8vO+sGTIyH3b/WH5Xry8FKum/5qk/8CIDk81iQvqa7zubib3pr9tuR86ng4S9BvLS/uxrK7dpi5tTBvsgECgEcC/2evaRsJC+kgMulWlxLwnwcqUA5uMXclyJTM0mHRP1fTGllO8BVZVp7bnr9qTGQ/poUZKpj+h5hL22WfjqcZ5vM0SQArXycxwGcQjGKA5ZdfRCKQgEqLXSMQyjTXB6kPrnbONKLRAefSCVxLT/VAvJTDYJ7TsOZEhNncOY3HbAw0v5fL0t5pVFocxEnhD20sU56OpSgGg5o5cd0XMazSutN19Owt6cMn6QVk9fSqMlS04LOCIkN4p9e8YnXzOj6wtEHLhb6NRi+05GjM2OmZpTkhMipeIoqyokf63HM9xnnoS/d0oSYpTOj0N56hwj74BNSXwQhkEYBvm+IVBtPPHlQni7Ua0EGtwziTo3hkPJ30vlxL691a8qWjd2YyrDl5HORW9YwpzcO0ayPTT+bI7cJM5qWisOZrmCcaTkMRxKcRhkvXDniJaICgJ0slm8qryzm8XzZER/t+dByP8n0YnpPWx3tpBrftaTyZ0CwJRj4oV1QzyIKnNKOHDVpPQeuEWueWrf9+zeXj0dhhczcVnf7lq+sG3HmpunlTf6e3/y+k0MGJsAQCau8aAyw42MWbkObICe/8NemhEt4H4NwJtXbEAtIJsyGRQXxqae8Vu8sG6IM0PSze3oeWcNxBHx7AD0chEpK6tQEvoAlPIFANjTAbo+pdWqsHt7sNkeMxHYb4ac2L1PcpKTvHZ5dzULCjiU/D8lnOVe1K3sbLMyg8/zWfjTzzvxPFTZI/OAglo8qshQNT5tc1tVCTFOC+S4uHeulK4nUKnInTKN3734LGazg07QTIdnfgVHB2dh4tw/nQvyz2Eyx+RNqqPKF9b5+6UUYsimkCWhiXnhcBbR+U78GBTpmZGnkxP5aJ/F1eUY7l1VgnVoSpicgOzTAVA4PoOYDaSJjVit1ERy4wqEwLP9RYYuzsWM8oBEr504YBe13ZfTZ+GzTAGUlz7EsdqfN4M0Jm4JESDkrFQAmbiG/Ys2Zfc21a/vxZkJFOcRkdwDKOokkLNOx6zfqbSlXSKPkXD4fam2Jf14Mbu3ZESGpt4bqTAW6vyZIjULSGkS9dGXKi9e72txi5WIkGxDscpfwDgXxVT+PcWDPGlQxq00ddlYPNqTaLypxSj4CWtTNyWebkI2rzvV1gt3ZbotUbWg7Wfe09lMXiRm0HwOMgCWVhQbSZTqZbFpwC7nBxyAoS14HO3TCGwHgFmBU62NS+Ys3S73+qTCxXk5EG3O1NRht+5HzwYYbZJ0dQksV+NM4eXxvox3d7N4nnitw36faCL7+B1GjlHzDeQU9WbnARf2qfHpR3WVFymroyxrO7b5nJ2p48vDvV0K+XpdigpvtsVLvy3ksbzZlmK/OZ1dtAxqGpdKrm24FHgAAg3XU7iU0htG4T3rg51OdH6RI0Ajgt26yp+PUtTrsoSo6yX7YM9ip/ms2PDaJs2a4ryzjTaGchIDCubqwG1bwsqaRk4+aQ0SHcBql+mLYpDoRFWNiGPofKGp9yUdnupa2q8imFULiJwh77nUYVPLprZaA195hPDUMaPFKJT7lnZuiEoAPHMlGGMAbQWByQsZWzCn+nQM5+dAFQVubpv2Bw8wPLpC/NQxdc0a0NbBvU3DihFcV9LneUlRx5e9FIAPq9rvsjmMLoJkEOlP/12nlueFrYhGf9JNUZkUSBc1jRyRVFWjgseA7vApjfN7PMKybceoymaC0dcNaIQaBYTSXV/eaWiWKocQtbFYzVRTf218GcFZkKFIgpLMmpC/j+ONwKyRLFnjufBjNCfhRGw+7HdATvLsuM3qeQTHJLBvQPpjDlINKxvKkkMc10mZzwTSPJUqygagL3juU11L/dPMNl7Ly9YPsjnmG7P0zyFAqZH8FmxbpPMZ4rpEVLiKY6SkS1DkuW7OMQKRENTUTee6Wfjn6mXWyMvedgVqPmswXDWIzxyHydlM2rbDy9ptanAdEVLK+Sn+78fIycF5kpOc5Ch5dxGcU3E+C+FCnPgspo7MUBxZI6arPaaJ/9sL64bEiBEuY5C8i1z93KcqT6jYnu+zUMaqO/gsRr6FME57t/v67FtgEhrlNFLjbSyHfBbZqejs4mmdEu76nZCjfMcRHXufhWl2ztcynfMpZsXCjtPQIDXNfpo751D2FckO+SwM+MbezHPV0e2e+dpZM6qinufSwrTeZ2HzrRoqjGPCnv8hn8VikfNsRmNenBV0J17gs5jPJOvYaYN/98n/gGfdZ0c5Lt4vM8R55Xeo7hwxiX2eXwZb9C4BLReAsTTvs7ORDcy3tzsRBJ+eXlLG14Kku3FgH4hDitt2bCP7FPLbZenDeg2y6t62cDXtnZpG7qPXpvUaYT4DLc4KAYu9NObLUOHNVuz0rgUM/Xi7HDkRDbHJ6w0YmqJuvgWf5GWp4wDo6kJSvSdmCPU9eLnCvtqhNh9+7mnhivPEqBmbooazd6a2HbDZZGSobTJWhTyP98Elwu2eyuxq61NTA188Ln16+EBo9YwW4OoyJ6nxYo5g/g+W6ARCkCI9gJhiIQCrNdIPfBXx8+vSjyqCNi34gUC4adseNkPWHWjbIl1KNCT8znf3AxG/+iFQVwg3q+JwPz9D+40rNL9bfBZ8NpM09D1mSH85Q/XFbUlwYwZuj09Rf380Cy9eizikWdD4hN+9x8THcKRmkcOmvtapr9CVfRYl8lKafH2axd6apPbCqeyrdTotMjNl5trRWPSae9EsphXJgJwzUUKjsQCozLdwX5qFZXxONQu7hwNw2Vyn7Rbh8uLeNQs6OxNHrefYqKo7aRaoKjmMnFP67z79H4/WLN4vn8W+PIOD197P0J5Vc6BfAAAgAElEQVTHQn0nNu3XLRmnEEZ8DrZYiNRMmSBU7fO32ncTx6SV+wuM+/0m+kDFkf3cNbePBe2eZIdB7WXaNQf9S8q7ZYa8TJGhA7BuWfxmRugtnlNk6PjCyHrSmwbhQEQ8lMzXdHu7831mhx+YZIKm7fg0flH5Qng6+Kx1MDiNT1ahn6PCdWnt59vKL/HqQooMHcjW9SPx2sOOXnoIXt9P8hemfw8oIUwPiLLP6ipnqY5g1/4mzysTYdqZW1tpO8ku9Yltru0M0nKEQ9aPcHWB9PTZXl5YUrPrqPKFa9XwDuT92HMJZ/OsnaRn14Amh/n7H2ovh/NtU04uZ+YIeb80i5Oc5CRvTd4tzcJrFN7n4P6WlkuJzxtAqK7EAegRgkk0AO47RVzqd11JwXglDsXsdDtfjPAI6dlNcaR5Z9sgNTDM95BulwgX5xkZmDSrsfraV4WP0nuvm1raAcDXtyM+Tnr0EGDG8PGnANTRuFpLKrPWJvHtoalzjQxfYyPDhgHws2ugruT7FwIQslTq7BhWB+fwRGpnVD/0g4UJvDfkaxSHnoG1HlyAnt3KyTR3zrKuBy+Xu1SAKQkk2uZaHZWoYkntNpyFOXQdLyavVki3S1Tf/31y31ktkOZ+KPU3AAwfXiI8U/vday8xgFYbYZp6rDU2EgMfPpRxffK5fGU2UzYs9Y9sXaJbFQXHYQ5UfXbpk8/Q/sSPYv7Pb3K7XEfQcoP+I0k7j6s2Z+8O5+rgrAM4EOK6R1y2aD+S5zb//z6R8VPRBhEIePRAxv3Z0wKI+9Hfj+U3L3Dxz4pzdVg0iMttHj/XqoU0kqIfb7YYLo3djMG/7vhTXiDv1mYxFWbsLcXoVb4DWafZrNiTEQpgxIUJIJPrkr838yhkx6w5C11XsvWmpQDMU73ZqLrOkk8CgFqAaTNqP/dVX/y8sbQuIuGiAwBkMa+H/PLlPk7Ai5ZHwH2fvfgeps3M5Tu20a7Wpe28+cZRmjzdqKMtDZLf4eZ0tDlafg2z9MU2G1JTZ4vssMuo0b6XTSffd6W8oKUUAPU6J4q0tDkPT4OkehMV5KJxsXYdqPdcqUnIfXvHi2pcpbZZeLMmBgFEmYO0L/2dfb4G3ZTcENKNpnqsfiPHiRk2ekCYs3YYQJsWjb3c9swoFIRuIND1Ug7G1To/9/hkibNZhXBTSIRo040QnKzzEAzct2kR3Sa4F8R2QN7tzeKQvEL5wSy+7mmgnOb7ouiQ5I+kw4S99rlxRHreCuZ8Yo7IgQFNU/YbVRrzSfhyAD43wsZg93BkPbkups+FsVM/ICeDjcQTAedow/i7UupQeSPMz8Rq//pEMt9vh5XIRMXseDpsQwXGG3xHI94HAIU8mBnsAxbbrkQeuCQEss51/p6OhZWfs2hCfUn4GtI4qsAh81RYP+0+tG4LlJ0IqCSdnuyltBeSPbeo5qBovVTadvl+lutU+iqbc86PsWfWdohLTSzL/C5yvxzVsfVTiSY2IiRiHq+5F8i7vVnc1eNrIbmwW5fyoEw82iNm6okpdLB+w76uWIbqFGyU23XALg7aRtlYQKHgPEZZq2/A+26RkoSSswGU05pIHc4uJJsCEFhzHsZZpxYCJuLR/e9a3iV/T6HpQFJ27sl9Y3TzqAeBJmFx3sgsBOoBdi8JI7DICZBzPkafWT+82DoLEKwIubExabathcQPuBZJas3I89j9W77fa5KTg/MkJznJUfJuaxaHxCeHhfHpDyCDq55bCsAyH1V9tKzTDFhRM1C0iQmwqqkLJ0PfS/Gg7ANxzswWI7MmZ52GACyXJTEqbYuz0zv8zHZ2vBG5/Fyg4m8wX0LT5ALLgNrDMUrSmjkiHagIQyky5JGjGcHpAUiOGJYvFuLoM3p8QLQMo5ezsLI/TaelAADAoU0z4KquRzR1NJ8LerPrS1+Nkj8lQJO2ACBdnktiFlG21WEZt20nz9ZMixhBZ3MpVHxrbWsRqD0OTqqiOHNJ+Tp13LTdon90jspMDUPSEpUiQ9su+27SmTk4I5gIoZWaId0jcXA218uMo2DHB0uLMyl6nBJgYdarc2y/eoazts9rO81qhNW2gO1MO621qNRqi2QIzgTg8zeUdUpEvwXgBvLm9sz840T0CMBfA/BDAH4LwE8z85ND93ipdmMYIf/YcjUmHAj+Zdu5h0vZBuThc9+Pszb1ARdHkxDBUtPkLFFqW6maZc5Gu9/5Akyb4qOAevo1bRltB9K0ZO578Lm+5J+j9GcrVbR8xiWWayXFdcS6PnXc7g/ZCG08OUpiPg0lismbi25SfHUOMpiz2b5VBM+aDPdODxaIVpvT1aCgTRzzUQKqVgd5Me0zhbyz1teQ/tT5frTelgrxVxeSHbvZ5qrkfNaAeuX7dGjE9qvnaD7HDmgpVQHhei3VuiySkBjpYoG0qFE902e+OJPx6H1pkkmaLueIZj7ouOn2Fsvvm+Oy1fmIhFQFVFXA5uvyLOqbDqkOIGa0l4rUbAgcgGqZUN90WH1D64Z8MgOtZQzZ3wCJ9AxnNZquzyZ2+5Vz3Pxgjfq2HBDdZY36WZU3i9TIPfp5RBgY9XWD7qps8Om332zW6R9n5h9j5h/X//8cgF9l5m8B+FX9/2sXCmPU4Z2RdH5BHfvdV0XreTva9+EQsu7QZ28Kben7OeG9PGSDGyTeJ9vdG8rR+jF9luovGvl6pn32/o9XFKbyL7c1+fuh78F/59B6PDR/03bdPaef740q3lHuwwz5KQA/ob//JQD/M4A//zob8IlKFs7koeRPUEglbNkVFW10D4dRMBITIaCdRFqSy8swzMV6DZgm0ffA7XLM4gSAr5XE1UVDsFyWcNx2CzZcSdeDnt5Ify1yYuxHVn3cIyu3W0n8moROaRiyWQVAkrqsLsUzicUbEtCqledEN/O8f/HUZVuqA3NDwKpU6IqfJmDbSujSxpOS4DLablQhPPfvdlmiGXbfm1skVfXzhrKSPJs8pq5DajXKoXVKw6oqJLVV4X+YtZ1oA9E5WZPiMYYBtHT0h0NCeHoD2jRCjAOI2bHcX+sUMSDe1CV0ulQNYb3B1bdvSiIZkfBOrLdiHkCjNIFAiVFbRbJaoyEDA9sWl1q+kG5XEqUJoZiDMSJ+9zFiXYGf3eTn3vzuEzzqHqD+9CbPQfVYktgsGsKKQ2mqKOts0yLOi/kXtntyaQ7Iq24WDOBvk7i5/1tm/gUAX2Pm7+rfPwbwtVdsY1cCZZfFyAyxxankNswp/5Q/OP+Bqa9GOdco0GdC5jKqWG5V1evaFVDuFEjkQmcoNq3cX1+EuhHTgwicir+Ah6GAm54KOConBFWVtG/93W7lRZg5cpYDoKyspm+QVf9cRNl8Ftau4TwWZ4XK38KQRtrTO59FYlDFmXWJEgsOYZrIFQgYpECQzX6em7nj+3wOKEuwFsXvwvasrFShSnp4jmAYCx8eJAKtt+C6Kn6IKKYEL2agZ9Z2PQZlVXtAWbbxm8/idonNR2c42xiGhMCziECE/gN5FnHVgSMBCRguFMxVB4CAsB0QlxXaD8WUOPtCma5iLCYaEfjqHDyrEVxoPD08x/rrM8R1ByuQnhY14q1jcvOgrCHtgrL++ZtjyvpjzPwdIvoqgL9DRP/Y/5GZmXK8bCxE9LMAfhYA5ljsu+QkJznJOySvtFkw83f056dE9EsA/giAT4joG8z8XSL6BoBPD3z3FwD8AiAp6ndq2NcN8QlH2QyhFyM4PRdEStksIdNCLC17UleBh0Hg0NEV0lmvd9i9eeU/036lrZy8gQSl6IBSvFqP0rC562Q8iizNSEfS7262Y3PB5sCfPNutmBtDKg5MG3fox6AsQ2te3+wkSwHIldhkHApy6rqsqWTgU9+PtSq7j40PKI7Ovt/RyBA3E1CWcFJy1xcG7U0hMfIIztj1ojkYBR6gJpyaXCGUtplBN0tBdeo8po0Ww9akszE/SgCWVTGbnGZ59ns3oMeqEaqWivUGtT0LB8qKzywaoqYUCev2XE0WbLZi3qEAwBAj8PlThCpKWoGaJ/GTp7hgRnyyLHPwjNQUVI1YNa8Ygsxl26K6Lhyco4p7L5CX3iyI6BxAYOYb/f1PAPhPAfwygJ8B8Bf05994uQYO8FAAI/4IqpTQ1jM8DXqNkttyu8cMsSjAVnD4dL4QWzET6m6Uw7IGuCyQ0EhuiEVDwrNr0IMr5xPQsOGjh3IPv4nNGol6BBIfhanVqzX4K4/kJfxdseDo8gK8XIvqvSmh1XR9AzpfjMruHYqGhMdPhcNyVch1WPs5jYakTzUM8/WvlCiAFeeJUcwNXfT9o3PEJytgGDJ3JAYGbVvQ05vC62lzHVna1xfNyGkRAsIzzalw0ZAwiYaEa81D+fADvaYB+gQaBqRZKRO5/coCzRcboApIlc75kEAMhFWLYV4hfiovNVJC+ugB+qs5mkzaXI+iIWFfNOTJMvcTAMJ3PsaTH/0AV7+hzzIQhnmF+skGm2+IxlwveySl9u8u5ZXr5+LQjNuE5rrH8uvyfD/4v1hMpiqWFzkEDI8uJBrynSfgG+nD5ltfw+M/MMOH/+8sT3Z/HlE/6wA1e3I05Cwitgn1dTuOhjxz0b8XyKtoFl8D8EvqmKoA/BVm/ptE9GsA/joR/RkAvw3gp1+hjf2SHBTWaw3HojYn9+IQxP7PUFsVhVzvJEYdI6PU+anTdNLOMMhGwf6kZ4FUs9LzuaSsu0B07yweAswsXTez1kPkNY+GBwczNq0q55+kEtJ2Y6MhFSanu/ZNfxJz7odNL7H0g1NC6N131NmH5MagfaLh1eeT/ONl9d8wl90yARTGbRADDAYNer3dQ/tD/fDC9HFSuDglLkuM9d5Jx87l2leVd5Ypy5iigjrsRlXUfaXvQJlXMmqFbN5sxzVE9gj5AsTkSr0ZaUxTA3UjWZT5SyT98KEsvxj9/Wez4uHfk9+Rq2gDBZ48DCNQFWIsEQRfj9Oqaj+PAQwY/33CDLYjlow1n2QhRl+jtEQYcokCM5s0X4WapjgiTf3ebsfgNA3FDte3pT9Tchv/ueaB2Frw0Or9xYBCcVQPSfAqyq4Vri5L34zjQiNEw+2ysL/vKSXhP/NFpuKjD0YVz4UKsFDpZfFsX+rAtp/WLw+Ey2uvqpCePhPTyIHewsWFgNZSyQ2xHJzpvBir1xiiz/h73d/EdfriqJ37BPc+yUlOcpS8l3BvQXA67kwKY05KFM1kX2lBAAiKmMzck2dzdQjplHRSF2PEN1k7BKedqOu1QKSNxUnbCg8fiKPJ82dWVYF1mzMN4sykywtxyKoTjy7OxcafzyU8q6cqbzagxRminV7ACO6dCYEB8O1Sxt+2uYiR9XMK9x6U6yN85aPiLzCsQwgjPAMv5qD1VkwnQ7JatqPLOiXVujhVCA5GbjU3qvm8cDOY1mLQbHtmZ3NgvUFabxAefVCuMXPMhRjT5RlotS3JXIBkCFt2qePQpKoCX5xJLY3PhOMizmaFcXyCsyCFtrOiWzNn5heP0f3IN1F/4nAWswrhdoNB4d6h7aWaXUpIC53vJgIMhD4hrFqsvyFa8fx3norT1Sc4EiFenAsfx5PrgsH55vdh/f2XwqVhVvksIqxEqyFmsPpuUh0RNlKtfYS6/Q2HBH6BvJebhVHFARjboJkMNRwdDQEgD3i90Qku6i+FgKQLUtqS++VShdDN4UA0xPrnCxrx1uH2XUV1Xq5FnbTNSmPt3HVyvYGpiIC+F6+4J/sBJE/FVSbnvpe06sQ5LbxUj9eK2lMw2c3N2PcTDYy1nfQtjKMhQ0ImEx5hTNTZuS6cCwbK4mfXY4IXALRW9dnGpNEc7jsXDQnZ/POO7bBWsqGmLtGQfhBwmuE4DFbPCXSzEnNKzaV0fV2qm4eSUpDn3THI2zNNbYfm9x6Djd09RoSmAa/XiGvHDq4+m6iO3Gi4FcV+zK14Uav0g6Eqm2tdI332BShGMSXsQPrsMc66HrTZlmemaewUgvhu3IbDmy2S5RbpHDyXinAi7+VmAaBMTnSJZDkUqaf5nrKGWewFVk5Camq55witOeTfAUhSjmox2VZXFqtss7Kd8rWEqrzd6iuSbd3L13Zi57ND7c3nmXtgzATeSvu+HKBpANW4FADW6+z3yJ+3DjHJXLQbl7g1RaNCK39lTWM+04pksWgRRIVbwqIe/QAE5ayYzUrZPQNNnS8yK1feULVMomf/ghX+NS2mGiM4aaLxjEBZVRQtre9l4/LP9GxeEs6g2qWWRkSIudapPTuq63KqWxLgMGB4eIFoh5YhOJlzvg9pVIkS5/KFBpaiQUK6wwO5tlrLi0/9UMK8wyA+japCuLkpB93lOfoPz1F95py0dZURnOQQnKgiaDsXwNeshE6x+pKXL9zBWXDCDgA/R0sOOPS6Cc6inbx4RCUaktuVKAx3joBkypRlzW+25bS2hTsM4/qkdqqmVF6IXAxINAo2VqgJU5avnM3OuTXCNmiRYE7lpM6npTnr9uFDfOQlBBCJhpL7Zn3p+gJZt8rnMcJwJfnzxApb59LfQKMaI6zhC4Ohjxx2QxqxibHVhHF9AiA1Ue1Ft/CtsV/ps8rmWEqg9UZOYMNZrDdysh/QLNhrFoZX6XpUnz8rYWzTdraFEIfzuIvmGGzDCwG83SLapmWmHDvndojg1WpHs6Bnt6gTA6uiteXnMykhYfVeeapZfBmYsvIEH1KT8stZFgv7fI1jNQvPr8lcFtlmK+FUXawAtCDysZpFU3JDVKiuSvaoq9/AbScYDObCkblYZCCUrzuR+v5eNQuczYtpYhgRKyaUimbBmy3QUMnStQ2t78eblwLkqJmXlzabBHfULLQOhwGxDGhlwudnO7R6lBhgqXQuL7E9JwYML6Mv28tqFunRZYkUKC6FYhxrFparYb4O1T6QEmhTY7iSa+NqIxvZxHTep1nQ5Tm6rz1A/Um5juuq0Oo5zYKj4DZeRbM4RUNOcpKTHCXvLM7C6oQYHoL9Lh/iKD3daNtC5qhI4+v3SFbFgHGM36dV13WJOOhnabM5DmcxwYJk8XFud9+Mu3BO2kxJh6L627XJmSHjm70azsKqaI36ZuLo8hCVu8J/pv3PCXKqEU01LKMaTOtN6c8xOIspBmQfZaFFSBxhb9puC1mRjc+bY50zQ14GZ/Hgahdn4SvaTeYHQGFXN7yKRbEcxJud1pVWq12cxdmZfM9xcGaHvq1J1wd5Di+Ps3hnzRAAuwvBPq6rMeOTZpmORDeb/HN6D79o7AF7tXy7ld+HoajoMcJKB2Zv+GaLMJ+VsnjaVrg4H5HUArpBGcuVAYUAgV2fLwDmXIqOFmdiPuhYaWSyzISteRrinJghrGYIOzOEnRnix5vU5g4PHzi/ii4sjQTkjWPWiH+gH0aRD+7VJ2NmBiCOPWDk4ERTC8TezBmMzRBMzBDebOV5KGR96uCchnSnKepRU9RHILchyb3nDUjLIEQzE23dHGGGpOtrpB/+fsTPFUYeA1ih4t4M4UCCXPUp6oqypG2L9FDCrPHjJ6WvVtw7BsTzBVBVYGeGhK9/Fd03HqL6rKSoU7U/RR1VRNh24nx2Zgh9583Ave9X9KXLGkIOAYUcwpSPLYckjlCbUlsEo9yQ7GdIXEJ6bSexeL+YAaT12tHTF+blYNR4+vKGlKRIcY7EOLzAepicqDQqRIyZbgCbbXlpdbOIVYV0u8wvi30vbbYIMSKcL8rCNfp9V5ckS1WBttuSA2Lzo4lGmR5OTx1pTy/yFHSaOg5Aclo227KRaDuS8NYWZ5+TYCcgAEDqqdLVZXkhbFFbfRLTpM7m7pqqXDMM4pxz0Yx0cYY4hUiHAD5vhPa/qZGePM1/MrqA3NblpWwe/VBsf0A2zUryY+hGn9lc6qKGNKB9OEPYFOQtR0kHtwhHWHVAJUlsw8IKIwdwRYjLDoEo1xOJfV/4Nex+PYBvfAVpViMGyv1KVwtsPmpw8bS8xsPlDDGE7FS3qAvPIlJ1jup6g+FcfT/M4E++rNEQZoCcqoXy+07Ztxx3PmBmZeegeuOtXkOuB+Lu6dsKurjsM2b1oE/aUXKakZnnEOjctqWcQN+XF8z3R2uU5J/2964rdUmsr0SjuiR2X7J+2wLUULFliWb+DRKuUV6uCp+FnVaa+ZkT1kIo5EE+SmPXTZ+Fmw8AZdxAPr05FU1AojppfA1zwa5YG0MabRYxhHKNEwpB65aM+TZ4uQK1Qq4DQBL2tH1KzmmdxPFNXZ/xItT3orUlRvPpEnS93Gkvmkm77YrDdVVbZ+XA2ragbYfazE3/XJ2EmxXiWk0TXWvh6S0WVZCCTzYH2xa0aYsWaA77ukKYNQi3K9C2rBvqn59/MurD0Vee5CQn+Z6W90uzuIu8oBBRju+bw0pDpEd5epSHQH7ngvUAHHhqGOMFgBHfBPsMUy00M5JBC+sw55+578w5OzH3JwhoyhMEjwoZmcaiuBK7fl+RoR2NiqhoKICc0GYGuq+yOtr21WzJ82HzADmdc1ja5s6ccDaf9n84J6+Oh4cE8piOzXYvIpFjUPzC5HkYwtX3R7NkjUnM5oEBgAsMnc2ByEkg1L5d1T5po1pT1+UQr2e/QhC+Eu460Fph2d0Bzazrxs8TALYtwnJbgHxQDdH/39oddM12JQw/yjA+Qt6vzeJViV/Vv7GvkvXxXZh817JW7f5vSHIRI2B/VMA+91mje+6RMyPvuHBel5D3RWVnaqFNBDD2jdyn+LISvliSmZ9edooW3bNkYuKw25djpZr09Y5z+n5tFiq+FsioPkgaXQRgz0OGaBPhzGDXerJp3ZDsld+6/A/XFoARB2euNTIhqRUwEUYnga/rQcMwquWRU9M1octqkVhEpjAztfK71iWR/mmbvi4JIATBMYAGKoAm8ztY6M7CzUsF+pydAXGcoJbrhliuwsV58b770gnTMgBO8nzY79pW9rFYtMUiUKSn/awRR27X54LK5Byc5F4AfngJutnz8mqNUKprkCM+prMzYNZkhyE1jThv+0GcmbZ5VpW8aDGWF2ym89z36D+6ROU0Bo4BtGmRPpDkMFqXwsh8ZrVO5bqwkjKHwwNxTIfb5X7t6GIhgLXr8lz44SXar19m8h4ASIuZJNOZg9NAWU2FdFYjDinXDSFm4LvHH3Dv5WYxqgXi64NMaNAyc/cejEEOMXrkYtuV3I2bm/HJYm1pHom9JLwVBCfRSh2HnmgWI/PCM1lR142uyQxXnwbXn7ZsYo7Bi5om1yUBUMhtfV0SQHJOmjqHCQEUlvCqAvVUQqrLlZgQVxeubogu2rou9TwADB9c5qhDzmAEtN5Hn1GiXjyRcM6gvVy4uiFVvh9t2hKJOj8TE2jbgnRsxmZF/TAi7G2/dolmyiEBIM0rhBik9sltcQby1YXUIDHKwYtFrknCTSG9BTNQV0iLBsEOkPkMCACt1lj+wAIXqWwWqQqIN1tsvy6bRXXT5exPY8pKNSFVhOZmQHXTYfM1mcfLzxYjJ3Uew8NzDIsKdT/k59B99QLPfniGR+vLfF131aC+bko0JDNlVeAINEToHpTQafpnX/bN4kh5FXPj8E3fkEr8MjKtS2K/79TdPLBA3lQ9Ei8uK3Lv5/dde+RAf8xPkz/bMT/xRtfBqCbJSz4nJoLVFAGA/VTah+UUDTnJSU5ylLyXmoUvHDQqJuSvGYr3v0Qq6uzgzGQ1ZrrcLsXcaLMjYIRjsLbIuC8M4KUZoDy4LFJAuBomOAtfBIiXq2yipO0W4bGChSxqYYWL1utS2Ej/vtN3K2S0nNi7Vsio6zPfwohN2zs0jRjmiycj5nO5lHLxH0CBQ8YtsSpLiLt+lBU5eh46HwCKada2pT9RarLQejOO0rSSKcnMgCItrRAQT3AWs67fi7OIhrOoKoGY25C/eIJQ10j6HYpRSHqHAVFJd3QipNDPM8pAuLCsBWcxDLj6x0+FgHnS3tzQqQ5nUTf7cRbV07MyT3twFtUnT2XNrdZZo2l++wt8uLwS1Ke1PW8KgtPaAVDXlYDWnt6ieuKKDLVfgqzTHXFs30c5OLUQ0chn4YoT7WSdKslLdnAS7Xdwakah2dhk8GbH5QlA/j4MBdmp986+Dn+Pth07Cl1/si/Ge91jFJ+D/d98NlF5OUyV1kJGjOKI5I3mSQSSl81xVZJe5yucWXtU14VfYdaU7FXXb9ax8D4zx0P0bdxNM6b0D0F4FxKPMlTZ+mIw8roW/xBNHJzzZj+1vdLuU12P0gKo1qJClq9R18rCFZEWcwQfmo5RIdtDngOuK9AwoD9vUBnYyhycQClA7KJOOw5ONXGSoipDVcn4J8KzRubGAen4bIb+skF46iD+vk0gR0C4qTBcNQibJrcF5jsRJ78/m4XbCTzuYIRF8LKPkdvzYNjpmVPhtb5GdLF1u961RYYXyAxRg6QyJ5Zq67bBWF0P368Ji5VFB3hIOycit620bynfHnnY96DtdoxaZQYNugHYAuiUh6Ibp42zJRi5hScs2aK1TDUqUD+uc6KsS9ZG7oLnnpjIqM6J99/lRDmlwttidDBIhEXLUw76xb7POAuvWZC2syNR8QxtNzq1eb0WzIhRG2w2GfsRiAp/xpAEwQkUKLZGYrgfUH1+A751EHflIQlZI3U4i03ZVDzOIrpktn2aWbhZyoa1bfMGSdsWDQDcFPRo2Hbj5Edrt6pQMYNuVohbh8O4A4Lz/dksnPiShKMyhT5hzGsW++5h0QFTFc80cStTx5VMRd9WZtWy61ZrCUuuN5olqtdenItK7TULV14wPLsufJm3y5wkZcWA6OxMal40jcCNLWrR9SUEawvXXqzZTMZlJ8/NrWgEiXNodlSS0BisAGC5BDMjPLjKc+JPd2qKNoGHV6Cnwjk54s9oW61punta2XwAKKUUF2d5k8waSl1Jzoe1PZ/l+it0eaHj1AhRP4ywA8OjK8Rnjo1dhesq54Z42kF6cEQeFX4AACAASURBVAWeNQimXZ4vpERh10tUxq6zhKymBt3IpsDzRsKhT6+x/eYjNB87DStGhNUG/UcSpQirEg3Zmxuy6tBp+cJms93JDQEAfvQAaV4hPr7NhDXpwyssv3mBi2+XDbO/nCHebHM0JLnckOGsQk2E4cJpFh+f+CxOcpKTvGZ5fzQLU52TchO+IJFMHJ9jaj32KpeenpkvYr1WtbawT+1NJOOUWcMBMRfMOcpUqNiyg/IA3Dttt4Xstu1KpTDrq5EAt23+aX/ntpXs0WmKetePqq1z24laPpQSfVJjhQp/BjszLPHYweahybFoSTQMOZEM0SWuDYO0uc8McZXms93fOpXZfAmq8eQxbbbSt77PmAwrMWjmgUm08U4lBjE7J4zd/Ox65PQMALBUAuBl5agWU04Zz1nQG2Eo55tbzH77ca4SBqgfre9RZeq9YoYY58rUDGluRdtKN7d7zRD6/Ik4TtfrkkjW97jYdoCWTgSA6roZJSkGC6dXFaq6AlbrkY/jjZQvfONyx5i2ODwNd3CAEOal+hHGMX+DBr9BqHcWs0cn9Vh9X8RM4xGtfIaHhzIWpgAKrzg3LyMeRBUMQxBHjmHfz3sV0ufIg2SO2kbEDmfh5zaENwf3Bso6e8kmuVKUrAeb3UHen83iZUR5LvZJPpEc8SvpzxeKzxuwcCowirZYIpLPc8I0AmLaSegLdb27loL6F1wNCYb4YSiGkk5vm4ZGScogHSDLMXDlDWNfzoPzxo9Cp3WJvlBdlxCt6zfpWGhKnuzmI/9ubY3QsSTcFb4eYFWBOAk3iY1Na3sQjR2cmM/G/CHWtiXNGfGQv7ePkMQgTstEmZ8DQE5Rh/eVVRqRIhL/hvczaAFmI7oRH5FGQ6ahU4uiKRKW6mq/j63W8gZtV8icZhLZiDfOXzKrc72W3A7Eb4Na0gTYc3De4ZB7fzaLCUXYy93DRVReIeuUh6Fcx87776MtbyLr1MwY1Rx4GEDeucisUYRhXCbBNoqUSt0Ol+X5ZrNO3X2YSsbpaC611uubyDqlIC+jI8WRzOKgc67rhgZxfA6DsGLdc9Ypd518t3fm9R2zTplZUgBGWadfxmiI2yiOTiQjVtq9UswnYzWal0skoxgkkSxTzUtCWOabtIV3z4lkNGvKnAxDyVnx0QlATkgqiWQwk0RxFrlCWivh3zeaSDafl5NeT+mcSKYef2pqLSOQ7j+RTP8Ppb/L1eSZSyKZ+WoMZ7Ft30giGS7Ppb2Uskb5UolkIcAq3xMzcAemrFM05CQnOclR8m6xewdL897jDXZV1X1F9UPiq6Sbxz0+uBK1u+sElgyMPf5eDsxLmM/HwCeIDZ60pGG4kMzIUYXwUcecr2Tf7zZ2g2P7n9YvIs10dX32Vdn9ZzHuRD1G7aomFS4vwFpTtMzBfubtfczXo+/sm7sQd+6XIwPWVxur9xspcIxixGAYlAPtky8+tNMtZez2mg+F0Wfh7CzPF53Nd+gFMQwlUqR1cMPVJYbHT8Ya1aTAz3geJuvMxmFarI/i+a8thNCZFmdZwxo++Syzg4/uv+/ZBEL84CHScjVaN3/35m/g2fD5Ufb9u2WGPMd+yvb7kbUZeRjEjPAgx812149w1y4OSW3q8sLZ3Tjx/tDdfYghRnPHOH+eF6T5VlLKC15emjS6DwAJhR4wIe5LRnkzfqPzeSumcr+JQy07NNOu74ZoNyTMb/B5m39q2945imFi/Kj8kr6/d2yzcJMwDVU5tu/g6nFS0wjjdVMXLEFiZfUufBAARuzf8aMP5VqLsT98IDT7etoNn34utvUwFKLZmfyfzi+yrZ6ePkN4+ADpqcS6TWOpfugHBZ3oOTbOzsBXyjfxxdOCqry+Ab7+FVl8v/E70p+vfAS+uZHao6t1Rj1aezSflWSuzIR9Br66KHP4xRNBcK7XgswECp6jqsQJp+X8+k8+k3Z/5FsImc9C+15X4q1X277/yhWqz65BiZEWxf6l9VbGMnWaJgZ99KiU2bNxn81KApbnszBeDAB8dQ66XiI9eYr4rR+W2y1mCN0gSMtZlSnLN993gdmn63H6ODNSU6F6tkaa1ai++7l+zOCvf4jhvEH9m1LSiy8W4MUM1A3gOortb1JXSBczxCfKfWE5GL/zMZ7+O/8yrn5Tx0aE1ARU11usf5886/qmR6oIxED7QMY51CT8EjcJ9U2P5e8TTfiDv/+ZjD9QmUci9N/3CP2ixux3n4AU09H+a38IT/7ADB/9w5Iq0F7VaJ52YK0BnDKfRUDoGc3TDu1D1egSkP7X/wnHyru1WRwp43wPd/JktW94Mbu3L9Gn9SYxpP2JNVlt15J5lnOh7XLX7Z585pl34Unuukwsw31fHFmDEpqw0xU6YQy3jMsRt2bfC12/qcnZEdkW4hpAAFKWPWsgNGPKsnIKcQwtDquNK2ysoVtm9cRLO9X1RjIpmbMTmBLreCdaS9D6JFpnE0CuE0op5XKCFkIlZsBfu4pgzYMJOobALKZCP4xMrOZJjbDSF83RBYZND1pvEYZx9IfWLSJQnKn6DAxGbtEMeR49om6Idl+bo7MvBsRrKzIEhKZCuN1i9rjWOZVSAGBGUGDgUEvYNK4HxFWL+RehzI0lDtozJ0K83oC2sk4MDt48a7H4tEa8Lf1sBkZ127pSAHLfuK5AfUK82aKxCCAzqD9eSzk5OE9ykpMcJe+lZuGlVPye7JAvqqI+vT7jESb759RpqCcyuf/nGL5vvldoOHPBGBnOgihrDVkcR8doXHqKjvwJlo3qr8n370b3IIXDl0riDnDlsR45y7Mv/VIIO8H6XK6xPlHvyhcqHH7k2PNFkic4C98vG3kud2h9sJM2Fc2GgrU/xsWETZerf+0QEffDOKlQNUTEEk7nTjEIKQkuweMVWIow22cZJDcMqJZ91pZkngDqeoSNVg5re3BHI7AU6YkfuoSw6VGtdE6MtV21WEBwJbRpEVSLzTiVdYf6ZhCNw/t/torrYAYPhvJlUDeAti1iLCbavnT4Q/Lebxb7skpfik4vEATWW7gviEji49MqV3fs38gD7ujiPNRavNjY5a0ARnDynfvdg+z0ax/1nUVfpp9RKKhK3Tho6hjcw5N5ZMfKT/unL8Xo78H1IelmG0j4KAwfY5vj64Dq+68HEnbyfdf4achzLJiLfA/lTBlB3A+hioP+i1TOGZ2XTAv4GmHy7/1mkWUaMjJ2b5o+JXc94ODPcRxJ2CcGvY7RvchUoMr+0ipqla2hLMYYBdxDBGxod2OIKGAnhQwjRBD1uxtOjIXU1i8qB5LKqehU6o/mk00XVO6D9bEutUOzRmEwdfPIN7WepFUhzGWW2hTBRTK8VFXZdIPbhIzQxkG5yftuGgWDBSpELkYsRCTta3tpVoFaIf8xEBQFBhClbQ+pJ6lJynUpsp0h1Ypy9ac1qihQ6tal0uucd4sKVYZxE7ipwLMaaT4ODTMzhoU5ONWXUBEoMTr9vIlx5Ni0nzxvpHxhXRcullmN7jxi3pRnNszFN8FRQIrms0izClRHxIExLBSGfshHd0Dey81ipE2E4D5zDzdvBgcmwxanOfwqZcqqJlMy2ZktTyIv8jXJAl/rSWEXzpodE4ZqxeUHAlaxMIlvtzmPYNy/reSA+P4Cpfaohz/b/R3bNlaVIi9LYeScJaq5HlOGLj6bjSHJei3Pm+xQTYsatK1AIeU8A7KQ9DTJDpDx1lVx0taVLFJfT9RKEsyFRyJrN/MZqO0kIc6uOWskYtEPo2hId9UgtIOc1C6XhgMhpoQ0bxBts4wB6azBsKhRGzp23hQ+i7oaa6gxIp3PEGyDNhRqDNg+jJgpVR0HQmoiqj6hfVDrcAkpyubTXulm0YimUy8TGgDtA9kIF8q+NU2wS+czDIsK4abJpmZ32WD9IWHxSVkb3YVtYqKplmhIRFBnprF7U+IcNTlG3t3NwrMlHfr7VHIp+fDiaIgzLYQ4J43ay5sCc1ZdKUakvpcT3SVbUbsnGmIY/8RFJR6GbNsykG1wqcQ1ZPo2vbFQyhlIycah9TWkdqdVBC85G9lbD4l85NwHY4NyuRg88XEAkEiI9cvMjGEYQZCD1cpMqeAjXIW0TOGHTsaWhnJP+x4T0Je8BnL2+SgaspFreBgQ7B7bLrdHA+dNuVr2oG4AOOSCwBgYca3Fr7tCzYe+B7U9aOYS4Tat2PApyTP2mJ4qIgTKERKz9dOQ0NwkhLXnNgXCtkN9o5ylm14UqcT5NBnmQh9IAyNsBzQ3E0xHDBKVAYAQEJZboE+gTeEtrW5bzJ7VoC7l+9a3vYxXzTPzKYU+gVqJhuTxDknm70g5RUNOcpKTHCXvrmYxFQ93rmtg0B0yxkykC0dWQk0jUYu6csg7pzlY4pYllp0vJANQzQFmzupwyn4EgfjSQhOOAEk1v7rIdG2GY+AHF6CbICe3qcQXC6QHC4mbf5qkyhQEb9A/OgcSI3z3U7l2MRfmZ0tSU7WXl0tpez7LGYU+wWv4oBSciX0v1xIBDwWUlfEMmhhGCk8nBWv1X7lCdT0GZXFTIy3qrFFsvnGB+ccETslRtAFxuUVoi7c+l9pjQnpwgaA8lelKxp3mNSqbGzUx0uUc4WaTNbDhw0vEECTZ6gOF0l80oC4htAOS0wxuf2COxcdCrGvJqMSQYj5PthgWNWbGlRlqdB+eo3tQo/pcnmW6mGO4nMt9m4h44zArsxrtgwazT+WkHi4FjFbdLPHkX6xAg4LhSABQ81nE9TdlbmbXCamSvmweSseGOSFFoLlhzJ9WuP5Bue/84znCLQlhj6sDs/n+K3QXERfDIPygAG5/6Bxf/CFCtZlnzWL7IODsi1pBYIx+JvfoFoTYMeaPG2weKYdnAoZvH68vvD+bhVfzveqc1eDBZYIiY+zHjFkuNKloQh6SqPVakSvb/+ZVtixNoICkVusRcImvb0u40TafZ7eiLqYh57zQ7Qqx1/TnbVvCVsOA+GQlYzG+i/VWCWyNTLZsjmg7YLPN6FMPS47OvOLlSpi2NtvMmZkZrozRysHAAQgy0whdzdHXdqBtWSrzjwm0buVzU2NTAm2FFNcyWTEUsFC4KdmU4UbmNlyvwJbvoeZB3GxHZkhMCbxcgds2oyfD2pkhTZ1NoQtmVM82SE0Fnumc9wm06UehTABAP6B+vAINZ6VfjzuE2w2QEqKmj2epIua3s8zBGW5lHtNmgw/+aY+zf66lFkJAWtSonq7xQOc2rMVBTQNj/rlsiv1ZMUOqVY/QKrv37VZBf1UxWauI+e9do5nVCI9vMnL34ndWGJoF5p9u81qaPYkCygqCGE3m4GwiwnYQUNYT9bcMCXHzZUxRnwqXTSLzPWQ27gNJPPtEsfJiqxai2IyadHkVI6yDd37tc6KmJPczvwXgQorCM0GVvqgaO6fEwmcA0Ta462Sj6Xqg0Ta6TjAc9xQ+Jc+doZwXgDgzM1o2JUUaFn6OjLNIg2PAdhvokApS0jb4u4b1vH9EsRA+j6T4G4bShqFPhwHUu81XcRqhdZiOShyvlMRR+bze+SgCDez6oL6RlICh9IttjlSC/i30jNCl/LJTJ0zqlFJxvg+pkOaM5oMReiC0Q64uxjEAgx56zKCkDt29yX13m//3c7PwsfG6Ft6HGMEWIk3h6GgIKRybmloAWebl1rAepQJcIgsf+miIXee87wDETGAGBxdWnTWFEcmZPDQMSOdz8MCFT6OppW/KWu7rjRiXxX1EQ9JiXkKJvYR5uYpSJ1RfwOFiJi9I1yOpOk4DixaybUsBJpv/YRixZVskAYHuFg3RPJR0Vkt4cGDwvMovZfugwaxPSHXMbNpyeieESGL2rHX++wHDYob+aoaoZgjXlfRNoyEjeU40ZP1RheapmomBMCxk3bQfyH2rZQQHUfu7K5mb7iwI3UrLSBVl0+BsMZc5qWI2M7mK+6MhVw2WXwuYP57lA6k/j5gF5OjL0JjZExC3rxYNOTk4T3KSkxwl76dm4SUlyTL1nz2He3MqHo7NBixyv7OH3d4ltZ2dSWTp7KbiG6TYwq+qspJvy0wVhYaX+6mmM8WDvCYhDwF2bYoqbxOFnMDlfRY50c5DyJMiLNmNISM/72iG5O9rn1ICHGM7MQo4zPBMRqWX9HcXFs6JVK9AWZDbMGgKO7OE3d+neJ1U/kYJ7lqFmmsfAYAOEHATA2Gw9vSzATLWIJ9Rvu8rDRHA+7pZeEyEOei8bwA4Pus06YMxZ6R/qFzsdGmqZJ36z8jnaZhYjsWQgKB/6zrQRlX0vmAuMAhmP+eB6PeRBnAv/fB1TdkwGfeAs6D1dpQNixDk5XMbVlxuxQnqwUMus5SNxMjGPgzi/PRZp2Zm3AVnoRiHAEiuh2E7zDl7UyOsO4kiVLZBK5ag7WRz8Q7xteZJTPvQi69plHU6wVnkOR4S5k8GxKVlnQbQUCGsOzTP5L5x3akvhEFJTICoUYrYJsRlh/kT7W/bidnIsWxskffjLG5azL+oUS27PAdhqCQLNYovx/AmcRZ3cRZ+sz9C3tnNQhiMgGA8Do4dy6ej5xdFWbQAIG23pWCyT2BykutVGITZuC6MNWk2k9Nb2bvlxhJdScAoVMrL1W4R5eVS0qGNINfubaHUtrw83PeZ1yH7FlLKUZRRurL+brU05FrnkPR8jNut1B4dUq50lqHCQYFlk0SyHT6KaX4IgKClAJGG7HNg1sQ4n7uixY7R9VLvwpMkBxLkqvXHkJWrOH5mOk/sijvTWsBqnBi0KpZ0vW0Bq+XqQ+2Ot9IjI2mzRdy2ecPi5Qq0rCRvhAKS5yKJAbitkIyvc6moz80Wi998Bnp2qxcSQhWBzRaNbSxdn9MRwlODhcesbdGmRWg1tL3t5Nn3bk3GCKw2iFXMkSFAiiU/6BLik5syXxYtI/cMbNydrJv6WWH3/nLUDTmU02F/dpPAXS/Xu2LF7IryPFe00HEOkeZcCRb6Mi1OY9ditcrZmHb/zJ7lJbn7ZVSmZo9SGOWF0KwRWLfDU8AcmdsW4FBYyJtGvPbaD7mt2wxdeb5R4SNl/c6aBU+o6XIExI3DksImyEwMA2jWSNTDigoPQ3HmXip2Q6t5s409I2ElHyf52qOhvNxTLXFaVTyznQXKBL8AykZZFWg49YOUcTRI97kSJptWVlfFebxcKZJXzQYX/eJBEwptY0luQ+1LEScKsg4N2ZvnNmFUKInnjWhbs1r+buaUkQApOa99xo+fgjsqNXkB0Za6YZxMN2gEzkovsK3nJGvGZxUDu1nVz5GTg/MkJznJUfLuahYv0AhyAWJ/vZ0Ex+yWztlmVcXZ3y9QtpV3vnOEsPc/2MmcU6jT2JcyaEnGIYHJMUY5SvxRjZCje/ESMqnZ4Ul2GV3+HUOb627k67Sq+aheBpGYUC4rmNEfj4Px4rUeO62BfF+K6hTettlRbTwa+eQ3wJmyUZHW7XgVIVelnqF5Jd4Jndelw2OomUyd4DzIa0fqvDUTbSfF382B4TK8M5rVeTtaKy9LC+Dk3d0sXiSvE5Q04mRwYBtLdTav9F1BRPpdOnD/nTFM09BDKBtLpq/b873XLTkhj8cvtc8i3bk2iDOTQp7PUak8f+3rKPXoU+3D+DP4djNkWhMTw/TzSR9foS/P/Tvz7vP17TueE3GKOd/P8+5vJR+99aj3e92r5IWbBRH9IoB/E8CnzPwv6WePAPw1AD8E4LcA/DQzPyF5K/4LAD8JYAXg32fm//NlOpZ36n1s3la1ChjVmszOsmPIahx3p08JZn8iAYKY9GHLY8XT74+0EyE1kapi5X4UeeSg5OROJePL1D7c61aRSvgWcKdaIOQyBVae0GtzXPqfv+0duNFlAkd+uQ0vR8CclkLFX2S+EU7ksmHN/yGRrgyb73vhCkEzIlV+KfHROR8qdojX3Jfs7Nb1YT9tnW9bjbCFMn9hPwygVKYray1XmVNNLvv27uCbOCTHaBZ/EcB/BeAvu89+DsCvMvNfIKKf0///eQB/CsC39N8fBfDz+vO1ijgDy2nPQKmPYddUNbjv8k8Ao5fdWK2xlepNtFjIwzEkobFgT4hTqapB81l2mKXbJcLFOZJFG7StcHUpTlZzaAKCytToDm6XwhYOSLWsB1cAM9Lnj+X7Z2cSQZjNpDpaI9/j2yUwm0mUaJIbQvOZjEOFn12Lc2yzzQljORcjxlxNDQCGJ8JOTh89KqhK2wgqrZOpJlF6cCG5HkMqiFFmcdit1+XFMW0oBtDFRYaB03wm6M2L89yfjIhtpAp4ZixfLMCrFdLtEvTwgTTV1DDCXo+0HD44R3y2FhPS0+pBnK1cV6BrzeGoKuDhFdJZg/D/s/dusbYt6XnQ91fVuMw5121fztln9zntbod2Y7ej2JYMQeLFEuYJJIsIIfICAgvzEIsXnuAlSFEkHiBICCmSgcjkIYki8UCEghCJRCIRR1YQTkgiaNvd7u7TZ599W7e55pzjVvXz8NdfVWOutc9Ze59L9mlWSUtrzjHHpUaNMWpUff/3f58ea7WKjmQRIOznoVNuG5AmosX8l/D0ObY/+wjth1Gl3AChdjDrDuNDSS4z2zGFMlV4JtQGTIDtA+x2QPeuXLfl77+QqVJJNzcG/PAE3FQwz89TXlP4+rtY//QKh9+7StUMbQV71efzjyFk31iYKNjrDzU3hMH/ZE9H5RPKp3YWzPx3ieibe4t/DcCvxM//A4D/HdJZ/BqAv8zyavr7RHRCRI+Z+cmta3SLUr75ZhqcBXVVw2+fGjrV0OYo9n0Y9lfc25YFES/RcB6G4q2nIyLRm5Aoi4YBMXvrps/ey41Zou9jMbeOmpsoti0tClIbFP5AqQ5ekHraFari8ZjMnLfR+m93RVJcjpCU6uLmahtDmqXnK2deSSlpF99w3OcOgAdKWptpXj7mUYi2W6yQrON9SoKjyac3NxVvVUuUE/DKziLyUqic2wcGdf0Mz4DWUTuLclRrJaFuNjKJ9W2eb6XzBOTBrhxo28Hp6CnqrpLPuhes6lZe+CmNRor6rO6dcmksgy43kkG93aXrbi62WD6Rjildm90oHWPkdaiSmXFyPtQNsEUnSNMr8JAbyptOHh8VHcDHAB7Fz+8D+FGx3odx2V25K3flK14+M8DJzEzp1Xn7QkS/AeA3AKDF8lPWvrZt4jmQtRKH39fAtBbMIf2Plc2/14UhsDFAVQvJSGPufR85ElkNiqyV41ZVYVQ8xqFzoZQEiDkQ9VmXEpGnEKchHDibEgPgZSvKRXGISXUt69jIsVBkfRjjVKnKb/VXTEMwTjJ96JCOm/QsYhw+8To0dX25mDFLBWQ1WZsSQDhawqwFF0hJYTETlYt5cop6WBZdjiG2g9aF63xN9qYhVExDZHQxZFMmnYb4INOQuA9/fwV7YQTHKhWsPcuooXKgtUamPHi1QFjWsDoqaMx8GuJumIboiEX1TK422D1aYjGqhgchNA7WGowPZOpXKlf5VTSxamzMGmW4K4f+HWkTe1aDRmnzdH2tAS9bmYaUpLuTFTbvtzgssk5962CvqmsMzlBZmNFfn4Z89MUbIz8losfSNvQYwLO4/McAvl6s90Fcdq0w828x8y8z8y9XaG5a5bUKpejBG56SshRLZPpzVEa+8Xh7hRXZLv9KVDzW6bWjMp+1RGXsT2wbKuqa2rGInkQ1c/o82lZNm8ze8cr93nQty78yGvJZ7pv9ctP5ESVM+Np5kP4eBZRVR+Wm+3GvMEG2N7L/G4/xOZY3HVn8DQD/LoD/PP7/n4rlv0lEfw0CbF68MV5R2BUCKC6CidTi+PYzBPXn4O02bW7aFmA7U8qi+LbhIhSpjDeiJZKXBoCw26W3cLIv5Ci20tQJnKT4xqO+sLoDRIm6R4wYxGV1nXUJ1lcpHV6Q+QhERQDOta0AlKul0JBXkcq+62QEcXSYvTZK+8LDYmSh9o1AVgbTUYMTAV012TX1Vtpw0cy0IFLbVw6Y5BxDW8Fcbvc6svi/7xFuiGDRwSpzHeKIIhyuYDRCUtgXoq8SH4KPVvI8jFOaf3MdJQHUgyVe1/GgylqYxSjSr2rYcZK37FVhqn1yKG9fre/9YwS1L2yd5GMAgrlUDv6wgVNMatmAiWC3O/THFs1pHCUSgZ2BGTzGKNgLoiRCoynqwRF8RWguPWhiTIs46honYNfNI14jMH3tHvzCoelHUGyH6bBGd49w8COT8ibHI0mPV72NUrCXXYWmssm+kAIjfPf2PcxtQqd/FQJmPiSiDwH8WUgn8deJ6NcB/ADAvxVX/5uQsOkfQEKn/96ta/I6pQxFFrkhZUlGwOXyQgRYgSoNlfJ2FxOrCiBxnwxTAF9liFXt9WbHv9okYK4sSvcNhcEtDyPMRUTTuaxPEEWs+F9/566PojiaHBbVvqibGdlwnBbA+6wMFqdd5L3UeX/6dr5OloKlKAwVORSOKEdVCrCMR8kZ2adnz9oDSOdtAkv0BACNTkZN0cAodSyXSIbWGskw3ZDWKdXYWyApWZXFVA7Y7kC7KnnRAoA5X8NuXPLANVcV7KjgcT2zKiRnQV0P2sT6DjK1YB9w+Ec7uGdRiSwaHFE/YKGRmN2QQN8qqoDDGQRnYLcDaDfgsFvGdtpKhG6vuBdXcJUDXe3SdLB5ssY9HKZjA4C9asSjVV+usWOpawe/qODOt7DbHAExw+1DqreJhvzpV/z0r9ywLgP4M7c++l25K3flK1O+mgzOMslsZiZ0w6rKw5htTkmRik3O5qT4f34czI+lQ299oxmT5Pllf3ET54QGXM43CxMgVdiKX7I5UGlIFOvJZsoKWmRA1hYmRnECoMlplctvFWtkvcnkJLAiKY5iPfU8KGqApumXNoNzyfwHEICxNAVKzcUs53sT4Sq2h34GIMcaXV6m0x1fhGTVb4Qon0MEW6UN8/UKiwq2u35LiznQKNuV17dyci4a6q3EHAgjyXINK3IMPWRrggAAIABJREFUQdbVTMQY1oC2Bn7h4ArfF3bC3A2LaIzMnMiDYRkB9MJLxDBjisBn4yx4ug46cl2BWwe7y4lzoakwHlrUTT62X9awnhMamQDOxsEvHOyugo/1IsZrkeO+Op3Fp/mI7K+uncTnBVzt1yUfaH6sV/H4v8gS08ivAZ8UgTu71wYKDHJpofglg6ZaSkBQLQZVg06LOph9mXVxRvQsgRjRuuE+KrOUv+hSHv4N7+ngChAVmJty3aJ8dTqLstyUm3Atz+JTGlTT2ZWcVVeSxl0qUN2UuxEfPgWZGJBt9o6njmHlHmYamVs308WcaWfG+tBO3rQ0DHPrvcrNHc9UR8K52X5o12WgtbDbk/OIxkV6vjpqKBzJUudTV0kbEwDCYSsq3EAOnSIC+9tsJ3hTe+jndCwdbahLWSNh6Fkqt4501KYhuobB+dnDOh01oP56Z82tg5m86IgWHScvGoS2htEweF0htNHtrBJwHADYSQgytBWsphQsarAxsAC6Bw7VOrJxSd7mFsBwIssqa8BOWm84jJYHFSE4oK4NKmvQ34sjixuc7ADArxqE1sJsqpSoNx032L5j0T7N10D1NfXeVWB1Wlj41sCtKoxHes3xE+JI9knlNopYIVyfmhhCkrjT4aQ+GApG3rTv4jsRCc3Z7mdAytsnvamVwVmONAolKx6z5gZ7D7PbA7WiyxkpC7QEDTXTsMxmtHRN3UkkA2Ny1yx71cqbu8ztiIIxtOtnNgdAjAIBablZd+nz7FbrB7ACp3tl5qCmHXRfzZWr2AgIWkSlMETZf2vnbmBBdCTKaYi77GG2ezRWAOwr0E44L6HIGzK7HsaHTC0fJ5hB1NRFCFjzPcSt3fpCo0K5J8agfTnlyAlkGkLbHvW5PLhmO6RpSBMtBHUa4rYjzHZAEx9q9MOcORqL3Q4wY6xbPGd30WP53M3UrwDId41ax2mIGRwGUwvnQzuIgJ8MpaxPLOV0JBGu5r1xpoHv9dIabSgfNEAQ8HKufMM+RegmrhPFZJQuzJpWrJ2PSu2Vb9lCxi5ZDcR9JHm7wuIgJZDNEslCFLOZ5opWHmDy0qnoiEDX4/xAzDQyA+cU+FSPQhxFtwESPRuQjjV9LqYvPEU69U1ShoX0YAr1llJ7AECSWp0o2ro8Ut6TBB9RjoYU7Wt24zyaFUvax56gDUYZ+WkHQuMko8bJi7Wh7quQMUj10k4tBNjdlNPyDYEmIx1PDONSN4LsXgfqDMiZSM8eRRoPkOtxQ2dL3SjUcPWdAaJFop9FpKyNiulKDtQcKs+wrYPppvko+DX0R+/Eb+7KXbkrtypfnZFF+ZZXybDyc5kdivgmZA+Y4hSLXjTRnHU/i1beeDqHX6/zfLg8FiB4gtLCu14sDffWVZoyxvzmpbYFH0kmIo1jpmaPU1qOZy9yfQaxL9ynZVPbgBbttVRwamqRjVOsZRiijuiY/VCUr5Ho1Sopt5E36NFKcAcgD4cVs4jb+geHsJp+XWIWXX/jEHrWHulzJFwpRUDxgejWrq3Gq4VMO7ouyfUFxSy8n0kUDI8OUN2AVXHrYKwRzGK9zsuPVoJZaMbwogEvG2D04DpGRoBEygrLKmnG87IRzGK9weaDFofxDZ4wi3WH7rFc02o9vhqzWNeo1iN270o7Hj1fzAyMtPh7S/iFQ11MNYd3D3Dxx2rc32bLyvG4Fo3NGzCL0BDMsMhksQBwdfvxwlensyjLa5CyXpXHv0/Kol0nUwx7S1JWoXnI0QpwNiTfbq+TsrrMzBOWozw8PE0wkXCUOsVdd2tSlmZ3cjdn/rFmtvqQ09mVlKXaoUoA0mHr5eY6KWscZ4pS1phkoUdF58BjFte91t7aHkA6b0K+DhRZrOS91Fc7wMBS58BAzOEwUdR2n5RVPzU3krKwjaSsbpixS83lBnbXJxFes+1kmB8CTAiZlOWDkLL6IaWo0+QlWsKM1Ycd7EvphEpSVqttWpCy7OXNpKzVEEHcze5GUpY93cDGbFZ96dXPrnBsCe5F7gDt9mZSVlU7TAc1qtMtbFcK9n6OpKwvtVDGAa7/JqFTslao3iVDk/k6qKbiKGXymFK/A6cHQrcLO8iDmIR454Izuq7InQ0zDABdl8RxFUEPVxska0U9/jiltzMXosIcWYvlscKui+cZMYoiGS49zGU7Rfoz90MGWSM+wT4DmTyJWjmPmEn/qWhxODu/juco30NHTf2QKfCl+JD3N3YUZXsAGeA0ZSp6yc+wNh+767IgT9QYYVXGDiHrNgCg7Q6hFCzWYoyMrqzN4CqAcHYuyyKLlK2JAsCSzp7aWdPufUiK37TbSfTJWrjvPckesrG9wjiBlFpe3JsmcWsMjKGUEm8is5PX6xvFm8zpufwOZL7Jk+doLzeiyK5tULmsJh6PAwBkDaqTI+DiCrYAhWn4qqp7lze/sZh5lha5IqZtZ2G40PUwdZUbuQAxqeBnhCJ3xD64L+vEh9ccHsiDFC+EPz2DaRp5AFRzoa5kFLBoJUsVAF9eyvQi3oQh3njug/dl31O+cFTX2Tn98qpwRt8CD+4BzDAfSiqNuX9PlteVjApUKGe9Bh0fgZzLFG5ti7YFxaE6AODsIt78HegwTn8UZHROtB9jboh/KaI79md+GiZpNkQwLaplmwju+XsrMSkOIVkKghmmG5Jcv6yYrwedHGc9Cs0edTZRuNO0rq1Fj0EB38OVjCguLkEfPI7rNDICmby0Tzyn8Z0V3NkOkohl0vkyEcymA7cV7PP40IUAPLwHv6rhfvRcjqX2ktG+kHb58WBnwasW5iJPWQAAP36K9a/+HFY/iOdtTHJg796Va+G2UzIqHotpCBvAdkGmIY+kHQ//8XNxoi/AVBAhPDiCX1Sonpwlqv3489/A+c8scO+7u9QG09KhuhKfEjCSjaNfWJgxwB0vMR3FKWlghPXtxW/uAM67clfuyq3K2zWy+KRSTlFKECsJnZqZ+jNZA/Ym/ZdSDO8SzTkqUFdRH6KgziYjmCQPF79XdQIGyVrJRFX6uJofNWLYLMzOWMemBi809u5yBmpnZXmRBIa6AjojI4hI7wbiMNRFUta+MXJhvAwA2EQgdpqy/kJB06a4DYBkhhyWDYyOPoyEG7lyUr+YCeoPagkL+kxpRpA3jxoAzQrP6dNcV4Kx1C65jGWAsxHnrtgOoW1g+hFsbQJTw4EQpygCkVqGowqm92BNqYdQmkU1KsAva5izCOzG79NBDacg76JBWNag0YIrO3uTcmXFEDoO20OUxzOVw+6BQXNaGCM3BnVg9PfiOVkSgJOB/liuo68JbIFqIykEu/tytIMm3wdlOv90UGM6qODOM5FtPK6we5dw8CSProaY1apkq5x1amAix0MJYKKk9ZNIyroJx/jE1Rmaur4veQdgFhkpORJUzhdv4m6EIFMi7YBCxAPCfAqU5N5Kr1MfUtw7ScIBgmtMUb491S+keTk47NU9pNT6WT1vypo1cRp207rFcsVWzFici3qSenkwkfgIUSQ2FOcTuRHJAEiXEcn3QsBY2jDzJdIyIGWdXvte8EO0o6ApACbv1wxSHyLKzMTA0hF6lnMrMazRw+i5AMK7GK2ca/ye1gVghty+NNq0f7dj+Q0R4CRpR7eTY9khIHgCBcBF20IKslPXB5ghwHWxg1ZRn8LcCfHYtjMzMp7pA6pNPO+4rusM7BjAXjonFcVhA5iBYXoPu4s5RYzX8u/96nQWZSnZmeUNmDQq8GpmZ9qHgngh53SUBsRAPMb1DiO5b8Xv7MP1t+kUgUXmvA/1JyXKHYEeSo9fakfqeiiAWnWfmvLDm7Cayc80FTn6kLAP+a2uDzzFaMieBiONU96HD+kNx5MvHkofH94A9ns3eakVUjSdRhnkXIM8VAUBLL1FnZ85fKmGaGJsArmjUHvIeBzbBxltOANC0Y5jiBhHSUYK0kGXxsqTB0afyFqztoSAgWmZdijew3X7nQWBRg8b07/NECR5MTDcTrEUJVbJtk4T4Pa9UaRxYAaJvlDRNrYPsDuWDq/sMOPxynvZknRapp/got8uRcPo25avZmdhbW5Ua6VhyiQu9ecEXp2ApDwDO6UsUsKUQk1iPWhAPifeqO2eWB6atB7Zguad9h8zQyfkfARXZIU6l2i75CxCU+VMSj0v56Se1iY5N9ZsVZsTxCimupKzaZ+yj5jDYk0+L62LNSDOOS5auMnyeQSIZoOz4MYlanBonEzDiIQWDYj9HkfvUc21iO3DJPJ3aSRVuaRwlaZFWg9rpe20k4ztwMZk5fXayYgiBOFCxPr61sLVDqEymT/gRVaPQkBonWhbyIUDNxZ+4VDpFM/J9IMg0w6MRdtUTrgXum6l7WkxrAxCE8/ZEKalhe0cpoUmolmwJZBnTMs4LWjlzW8dw3iHcanT1ygT6Gy+l6xFqC1CI9dX28wvLMZDwrRyaYTgFwa2l+OB8zTEtzI1M73D1OaRxeugll/NzmJ/SH7t94AkHfSqUoRWZ3b05b733uqvM2S7cfsbfkufWXr5tC5HR6mbpl+vOSV7rRJeXbfZSEinFWVuQWnQHL+zwfVpoO7vNZKYZtuX+yhGFvk3pHpROSUqR45xe9ofTb5B2Veg1e/pvip/5/l/CtjLR4p18yHVnekTXv86lUjnWSz/nO+Tu2jIXbkrd+VW5e0eWezpRgCQoa5zifxDlQP3QrkuiVlU1+BxSv+lFG/GyHdI/I2jlcT3NZrwFML1sEXvXDmZyx6sEjJP2x34+DCpcivd2T84hDk3yTAGAMLhCkOMvTfDiHAS1Z/HCf07SxAD9Q9itQ4XMLtOeAzDmNy/cbkGL1uEgwWs4htK9Do5xPAoU3+bcRLeAgB//0iOpQzGthF26ImsT9HcqHv/APVZFG3pJN4fGofxqIbbSDtefb3FQcxoHWJKNDHg1hWqPmeXkhXchRG5GfEa+vty3uNBhVavTIyqTEeNZI/GJKzh0YEwM7c7jO/IdsNRBTME2D7At3kEefYzFY4aARgTZZoB3xAWzxzGQ4uDMzU1sugeL9GfWNRPpRbT/RWG4wq2C/CtQX3Rpn37xqJ7WGFVy/GGSJlena7x8k8wzBRV241MMZZLg7Nvy+PVvLQItdSlexDbYMkIDmjODNoXBpffkuMc/dEC7gJQ/xG5EMD6p1fojwkPxmO4eN3PvlVj+ye3qNeLNKLYvUtYfmwRnFwT1fYcDwEzAsunFttHOj0Cpv/rJyUaUpKyysUzM57CnKYczimp51Wmt8q40xt7s5OcBJW7ZwaFvQxABeSUFgwgTBPM1TYx+7SYiy1o18/s7Y0xqF8AmgputAPsB9Qvu9mwkbZC86ZdDw4+p7Yzg3Y9rA+JlKUdFK0t6iKszNudMBG7HlbJREq4CkHOdx0ftjhVaJ7tYLaRgq1tM1Qwg09RguXHFu6iA0JAU0RDzG7MtHRgRpKzF7t0DvZCsB+zGxM9WxWuqPeSZh6PXRmhcIdhEMIVANMLwEmjhytCp0cNoX3eS0ehUxzPgCXYywG2c5meHhjNiw62z1qb7hQwvYRHuXaztHNbWdi+hTtVynkMle52OP4uYfVRvD6GpKM5H3BUSR3qdQBbAAw0FzF02ggpq9oG1JceIDkPd7ETevgMgyOsftyhuajgTjdJB/TohxPGf7TE6uMxdRb1xqI5nyIpixNmMS4N7MhozkZU2xw6tdeZ5a8sb3dn8Uml4D4wIA+g+lW8jliVIWS5PJNBRwUSvc+U5r1ktU8tGitPkniU/wqAEs6JMlMIMLrMGAERrZERTgF8XlO++jyLQWpbzXOAhiIjkMqGEGoHGj2CAn1eqNcUAUoAKVWaQ6Ry6/V5U3UpyvWiqKIdKpPn6XFEwZVJCVQ0sWhWROUr5bbQJGLFvjZzUPgNCts8kmEj7Mwk5x+XqUOYAlfByps/OAgPo5DBo8lJREcf5FfVj2Q/oaKEj7CBJLNZAEG4HLruZy1vbWdBhsDhFQ9FITKTHnYNKQK3A6wKa4F9PU0AKRrBSr0FXu8h1Q6BbQqHcoymsHYgut/KITgDMyHXxZoUOaEy8mGLOn4RJXaaAJIqGGuHUaluKcCNFW5KpBODIL6aRPmB1NCr5nDofi3NwsK3LUrhZiOdFyFGPSKYqSOKUBl45TNYBu0YQTsWjahAO73ifN+wsKX0MLIlka8zxTIjDy0FZE9pC8ADwVGifstyA3ZGSH0afapvfkzZAlzd0FmoPCF41mF91nIHcN6Vu3JXblXe2pEFf0qYchbOZCXnKPmJXy8spwStkijFXLAeX2PEMtsvZxZksT0lZmYmlCXGZ/IjCUk2joswWtrnFyFErHWchRcZZCKzVMORDCEzRZAT0PBdXFZK+Once3+/b1BSEhwjh0E9F+FRRDUpFnAVgNE6+xAl9Hz6DoZQoG8Il39qHWfblHWM4dASf2IG79mFleFVuYf1e7RbHEsSmwdQ4VphASnJF2FSloQ15livvVDtZylvbWcB4JUAZ6I7Q8BODqIRmQyDvE+p4p/6UHkvjM84LE7ApffgTjQlUjTFjnla4AocwhVTCi2RrssldbmuEHTYXsijoR/k5iFKadEUgjiRHayiNJ5EHULfw04evKozUauQsg+tK6oQpzK2QNZ1OmOienU1vwVCHaXXgKLztGBDot8IGTpTJ5J2iR6vN3kIOfM0dYaczxmIw2uGX9WJJKVCM9w60cyM9eHWiR6FMUmBnA0JEW8MMw1J38g0xPgA2pXLDdxV5FVEcBCApN5PWd80LBtxW4uZoyW7k2uHaeVgr6IEQRsjRs4h1EgYSZpOOIOpkfq6TtzHQkUpOuFrEb8xFzrViBjcFOR+GCi37ThhenyAcWXQ1i4R6Xxj4Fue8X98E6dBDmDIMQGJ0ISKYHuL4UCjIfxa05O3u7Moy37vX3Qiwv33GfRkShoQ+1oQaRelFiaRhBELBmUCJktjY5L9cj8UIwAP3nbXci9o28kxvM91HUaYS0mhhp9HOMxWHMoU/KPJg2MaeVnfZGi82WVtBo0IbXcZIAWiaEyMemzUkSyfN8Ypp7nHG84VUQtEEBA+iDJWPOf6rE9KVaYQf8UwShsqg3OKxsiI6k46aovApx0nYFs4fAEwU2yXeN7GGllnHGE2McU9hMjM9JkcBmDxzMFeDklYBpARhLuKkRrPuYMOAXbdgalN52UutxLxGSeYyuV2AMDOohm92DYCOX+k77H6KKA+jeJC1iC0Fu6ix+ppFNbdTInB6WLa+9RK/WzPqK4mLBVjGSZJ8LI5b4Zg0DzboboS20iOosSLZwMOftigvpzSyMEMjPpSU9QZIYZ6q7WBHQKqyyGJ31BgmOH2Q463u7Mgk6cI5VC+fIsbI+tVFbDLbw11Wi8d12c8i9KV3JBkYaoRDTAf+pfFCCCa5Ohi1CKJsGjWacyy5FgXAEIZboUmTRub3vZkDHzrIqMw5OPofy4eQEA6sbrKYWGdClQVuMyadU6WJed1ZHDUORkNqOmRckGaSobr2oaG4oilTg+IX1Yw3QiaTHrDUuBc97JwgGaulrL/CpjSrjAOAkT6zuepGzeibwFrpe0AyR4dJdcjtC6d/3goNGu2ORpifGR4esZ00sCe6n1E4KaCX7ocpWlryTodjIROy5dLZeFXdfJgTVmn1qI/ISxXej8QpoWF6T2GQ6XoO+ksAqOPWaFTKwCo2zFCVWE4iOfrIphdROZgDPyqkqzTtk4d63jg0N0Xerl2FuOBhfGMYGU64hsdWRjY0URujGbevl7WKV1LgPpnUI7oPv9JmrshUlWDpxEm6jWGTTa0NW0my8BaGbpbC3MgpB3edQhdLx2NsbnDKYo9EpJSGlkU+poARBhmsQBfXeVhtLXwF5egyuUU6mGEqass1xaPZR/cj/PqMA+dllqd5eiobea4S8y9QFR7TmIwPoCaGmF9lTkcqbPInRgAMVG2NpLT4s2cpOwpdhZxWK2iPY/enSk1pVwSDSUDOSrUD4W5s0/1VwKZEtK462XKpPdadB/jq0LCT0dU1syUvaiWzo6HAfadh3l73VeVP3MlPAquq+I6yigsmRhpSn6U1OemhjmLClzrq+h2xtI+ZQavdtDKzykV0f74t5KsHojED2W9zcJAPuMkGinitgJNIdkGTA+FHOdORVQIdQW63KRj8WYr0bniutPXHmF87xjVWRa/AbOoplsjx0s5N0Yk+fphJsPw9z76K7joP75Vj3EXDbkrd+Wu3Kq8vdOQT7EqnCVcBQZREb14hUjvTdurjiPp8cq3tfpV6JvhdSz0UpSGAfVKVW3JiANkqWhOoG1KIXcOqjfBZeSkWOeLKPv6HxxBZrImt42pJI085NT3EnRO040owotpEvxFR0Dk3yiawzqH39fbSCMWaV+d/gEoAFghOeS6RYHl0qzpDUtKlwdk1DVOs+jPLJktXUeOgLpEwqjAwMgHqf+nEABT5KRI/4cxUFOkfRmEz1re3s4CuDkSAgg+oeBeTFGnPVSfKgceQvoPYAZwmlWUo9/uBBU/PJwpSvH5RZ42FKnvpq5Aq2UWTT2/gDk5Bs4vAAChj8d6cCIgZJmpuWgRYk6KOV+nPBRabxAeHsvN85HoQfLBQqjQi1ZsCBdRt3JcixXAsk0K20kxa7HIlgIAzMszwSx2O9BxnHZF0VuoBmfcb9D8kvceCN0Y+aHnyiEs6qQSNT5YoTrdAj7AL+M5MIN2Q7YaiNdGKmKBk6MsVqx5LieHMOdx+K6YxaIRdzY99tEK5nIj4roP7wEQzIJGD0wB3NgERXWPl2hedFDPVNkBAEMCZjYVzLkM7YkI46Nj+IVDq1OzwxV42WT7wm1xLpWDP2hEexQQywAA5ocf48UvneD4D+OUw0geSXXeY/u+XOtqPcl0I3BSspqajFk05xMuvin33cPfCzC7UTCwQs/Cv38f07JC86MzmKhyvv32Ozj9uQoP/u9874+HDs35mDELTVFfGNg+oD4fMZxkdbNwdvsu4O3uLFDMsctEMqVMQ97AHB3E53NtKwBn/C+l6GWTI/cIGCuMOWvSA8wvI6hox/wWjNoScC5vr87ohcs5gCh7F8VoFEBranHRNgTq6nTD0eQxHbWC3CtAGr022RqZ7+sc3JB4axAloCt1gYVsHwCYqpJ6jGMGPlXHo6pkuz1ZPb+qc3K/Am2VhV9WoKjZMB5XIL+AGaYs/joxrCXYfsjAbWS/EmoElQ1EBAfjiMBuss8oAPHx8CFbJrQ17E4wKb+Suk4HNcwowjV+kbUc+hML29fwtUmhSDMJ74KphV86NDvNGZrgFw79fYfmSXxBWCvg6TAh1E7cyGPhxspxtzFRMAKczjlsHxGWz7KE3rgyIM/oTjS07RAswXhGdy/maqxEb8J1jOAq9DHBLLQV1M8j6SBZi2mVHdPVN6Q/ttg+ZqyeVBngXBGAKjFGNXw7LgnVjkA+S/tRAMJPgtcp6zBeb91iVBD6PoOOu51ME7o+G9n6ED0zg7wxbwidhjgSEKCRot1gAK5cWs7brSReKacDEECuMLfhvkc4PSvk+eOxnr7IyW36lruycBcR4OoH0EUOMdZx6Kr7Mc/Pk7WgJK/FEOc4gc4ugGlKoGop0Z/k5wGE7S7J35s4+giqsB2l/dX6TvdRff9ptjTUKYghVIU/h3shRkCYJtgXsRMKLJ3SOGal7lFVqieYKati2fVGOqFhROi0PjF6EUc8ailorjYI/QDe7ZIKt6urNOyvXDZirp+2knjnMsUeHHkUKuev0xDv0Q6jdBQvRPGbgkf1QlTirTUZVAZAxqJt6mQbUL2Indt6jff/zhXcU7mf2ErHTpsd6qcCuGuniRBwGDtzrp2Ef+OI7OBHsm710Vn2cC0MoexzoK0c+HKdRoEnv9di+ewI9bNNmm5IhGnI0zMV67EWNIygfsBCXxzMcNvb5zrdAZx35a7clVuVt3ZkUfqEAMDMRySwGPAAAKo0Ail9QdRbRH1FAAjzTUlT8U2mpjS0XIrDV5wGhN0uCcQmQx1mUNMIZhDfngGAOTpEuMgAJABQ00RtzinTpKsaiJ4Z6IcUzgxdlz77JzIysE2DcHkJs2gRdp14lUBGBrZygrHM3Lxo5ksi52hlutF1oIjRGEDO0RpQgVmo6DAfLAun90gEq6rk5wEA4aCFOR1FGrDAiogZvNlmLKUotFol53VEAhLuH8NcFTyLmIRGYzYl5kUDs+3kja14UvT2EOJaTqqb7q/gTq8dWhTLL7cyfYtmPQAEo7BWpAgA4N4xQsQsfFsnEhiYBbNoKlgdGS4asCUYImwftlhG1qvIHhoYAOM70ubuakwksWkVQ66VAVtCtZngKpt0QaofBXC35wQ/TQjfeA+hreAqJ74iEOzo6ms1Ti4ztiJ6IHlkpXwT3zr4hUHzssd4ELkxDIQnt09KfHs7i718itlPhbz/TPJ/KuZfyr4kmkcx1HQomgTpvJ9qmcMnngIVuprq6kSUHsA0199a+azZmgqGRqn+ckY4k+rfVDN5/gR2JkOiaC9QRRJOVWALVS0Prw499fzaRjCLWG+z62VIPE3Zk3Tj5NxcxHJ0SKrTqmWTUfwZmazJOo+HLcxVJ9mNhdcpANDGzUDdVArrAj1mWDbC4gQS3Tu0NcyQ0/B52QjuU7SRyvUjApFahuMq6UykwozQVpJOv8z0ct23X9Z5SrFs4A8amMHDr6oi34LBtYNfOpgI8vrDRjQtLyrsHljU57EdiRBqgwpAf5KJWvrQKsDpqzLjlNDdl+XL4rqWZTpsRNvzKl/f4bjG7l2Dg4/yOavMv94TCnBOS4NxaWBGRn/yZqSst7ez+ASyWBnem0v+71HCdR0N2VlkTCHshVm9x0zinwvF7tmxOEr6+7QsJYGVF1ml+nlvWTFnnlHE9aEpdSzVdkD/6+8hAqelzyuZCKjuHS/ERDTdPzPAXjQmQlYIV0KVKGfvtU0IWZIfUd07BElTCe/FAAAgAElEQVSYKuXyJy+4z03Xzu/VF4j2AqqWLaC10q1nKtpKNS9k+KlQ4dZiu3CjHZ8xglXQYFAKJNHoYYYph6tHLyI/wwTjTKZ0x/MxNhO1qHcgKyHwqrACQKRZ0zDBdrG9ep9yWFylwKvkhtguwPRZ3Xt2XctzGDysoRimld9d5+E2DqbP69udTd4pUnfdAQACbO+TwnjS77xleXs7i/1MzULfoqRwz2nd85EFOSesxiGiv1UhvWcylVbXFxAsRzVuHFm0rUxnFPF3DrxsBaw0eyObUoVcl6WELjuPoCTqN+XfjZF66n/93QhVnEIcbcR1ua1FgTrW2y5ahGULE1mFAICNk+iKsijbuI9FK3yIqhCv0bpHibeUcFVbMUc2NJuGpE5rP6lu/3x1FNM68KCAXyUCNZUFty499Fw7MSmOloIAsrJ28RkAfGtmpkOysuRHmKjOXY4yubIS9bA6VK/hVxWMM+jeadHEdc0Y4BsLdgYmUs7DwsG3DmZ3gHFBKQdDRxbcO3jN/xhs4WYejxVHFmY0sIMV+jcg6t036JX4hewvLCogRmKm1mJaEUJTtMHCIHT2+siiNdi8Z+E2LtHQKRSj0luUt7ez2Hs7pegIRTpw8jOVz9mjIxYlL41Tsa7Pb5ZxHgXgYQTGIYchXzGyoHEAs8tZkdMEs+1EVi8miAGQ+fkwzmT10A8ZDxhGwA15H7pcFZ3VmX0c0v/0+ziIObGi5dHdnWLeTLr8u07yG3bZXZ0HoQKLb8Y0qw97D9r2CZtImAVHo544ZbPrTpLT9i4ZdYO0w00kp9geANJ5m02fjq+u5FQ5oBwJNZVEOPo+eY8aII8+Crn++qKdSeGlek0iT2hi8lxavu1hPafzNBuRNqTRozEEG7EA8h40uETNBiRGZ/oJtNlh8dLDXcU2I4J1BmbTozmXjqXELGi6AbO4GtHGh5q6IUfWilJdDjC9lfNTF/XKYPHMwl3O13eXfXoJ2koT1hxAQH0xgLhwUfe3H1ncRUPuyl25K7cqb+/I4rOWQsTmRsziDQv7IMIqBV28TOL50hLzZl4RkequCVblFC7IqIvKURJT3l6TsPYxny/rHMoEKB/AjucJdUEwotl07osq2gYsLl8aDZM6MGDyHJ8DMtX6yyjMWfTnDenpIvSDPLX3jNcRxflqdhblPOtVzmNqlPyqaIhmORZuYxyy09irCpFgBnPdzjxPzzZ8Nrl+pW1Lx7A9l7B90djkcmbtPCsWyK5dGjHQ8y8dz3S96J6WjytCPWQNmAsRH6m8bK8gXplzUQjxclPNHcS0xDplI2rMfssCxXE/VRZyUSJVcgQrM0njtqUbGOl5F5iJbyxsdX2+r05iXO3hAZUTLVHFryKuofuiQQl6LPhG62C2mkpvwdbAOItpaTJmYQjBGdBgs/PXmLVK/UKWhUpEashb0BiSUxkKx7GyhMbBt1bC5mmZxbii5IYGCI5hepewCK2XXxhMrUFobMJSKOC15hZvb2fxiaHTTOGe07ppvv1+NIRi5KTQcUhK0009d1GP+wQwOxaAOcCpIVNVrVKxmraRdOmy4m2DcCh8CbuuZuFMXZ46tqaWB72qhAtQ6E4k3oPOvzliAdYmnQUAsBcq3IqCLl485CWg6z3Ye4SDBjaBykpTrxBWDYzJIbv2KoYxVzlsZwwJA/aGUYC2h34GJPyYckkS3bsSmrVKACwrYZn6AF5JG2l4UyX7tXQPK9i+kC+IZVo5NKOHX2XHdN3PdFCjjdfcR30LY0U5PIkRGyC0DuNRBbuL62o7Tx6b9wzqi9gOREnde/dO7FgcwUf6uVLARV2L0DTisL59V5YfLZobQ6fjYYXxwKA6t4l12z2osPkAOPxxvua7Bw4wGbhU4HRcGrCNGhj3FMAWkPW25e3tLPY7iSLkySVoGT+zZvrp6tMknULpMVKEMpX4kh7ubSegZ+F1wWVoU7cHhAylHIdpkkSv/bDglVDFZwAnbZPRTtJ4ABD6ISUoTTrM3XZyDl3+L1VhIVmtXaIel/4SpkT7u05MnPsh+XNwJJ4xx6F9pH+rdKA921wnZQ0VzDgl4LN5ZtP+TAkYdgNCP9zo1aLtAeROyDFnmTs9/jBKpxKH9zZuG6YJJnqf0DDdSMpa1Tb5epTFXjlRwerHrEcRz9Vsx9SO9qISHsU4wbRVAjMpMMzWwe7qpJRVjV4k/LsOx9+b0D6N7aukrE2Pw/gglgBnfXEzwEnRpIjW23xdi9I83aK6dHKfxM5i+VGHk2aB9uNMgnPbZgZwlqSsUBGa0x5upwAnXksp6w7gvCt35a7cqry9I4vPyOBUrUoYk4b2HBgpK/QNGZyqmER15AcQpSnDrHwZDE4dFRHJeTW1DPF19KzHmHziU0D1F50Fk8/TLm2jL5HByctiaqIKUotarpkujwxO2u2+cAYnLxqZGvUOYeGy3EgQjMIva1QqLRgZnFX15TA4/VGNcelgL9sk9/e6DM5QEczE6O/FNmD8hDA494s+5Le1G9MHyNq0LZmIV7yOiM3+bhV4LBzRkumRKfU+v+BSgp6atm9MZOplgFMBwqQRaiiRsog5p5OXUnVfUuHS0EgNmFSRXAFOVSG/AfT73OtjI8ZjSQhXfQR6PScFdY4p3WwiGarAQL7Quqlpkckd6+uWqaV0jrLT17veb5cGp4JvN2hmlpqcYdfldVRjc09rM+l0qkYnAHN8lPxKExkrzpVNXWU9Tkhy17X6GAsbdT4TC3GaQMsFwvmFMDxVVEfxipJeXGhkhl2XRXiHESYKwvgoTmOaBmEYhXU6Tjn9fhhAdS16oyl0GrLDWTnC8V7AUFXpBkRnMkZY2Ps0QqK2SZhCwlkUC9GIitKi2zZhKGX0iH2QfdwQnqamydqR8bzN4UHeZ+m0FtWepKFCDkmX+pcaQizOl1bLG+f7cA6IOq2hSOE3y6XknKxFgMfcO5GH3wfw8UHGUzRlfPL5vCvR+eQm6nRcXuV6GElv13tBRKF1RJujaGzjCGoYAU0UfP7yZrr3uw+h1pdpFHpxhXByCPPiLK/Y1Ek9HUAh0GwxPr6H6ulFysMBgN/5w7+Ei+52Gpxv18iieNjJuZnRkGaZhs0G9uEDcLzodHgo2ZmHB2kZM4MWC4T1GmaxSJ2FP82Nan7+nwcA2JfngDGYvv4QZjvAa7Ti934f5v49YBwRog+GOToU0O+d+ykKYP7oCcLX34WJF1h1MoZf+QU0L9TkNiLT91fYvN+CCTj6gzW6h9JBLD5c4+wX7oECcPK/fRcAMH7nG6g/PIU/OYB7cYFwXwRdzQ8+QvjpDzCcNKJjACRAcnp4iM3Xc9bp0f9zjmlVw71Yo//GfQBA8wNJy1RFKhWKpX8oxz3/N38Ji5cx92AzAQYYl07cxtfyAJ992+He708gz9g9zElJ7ZnH8vsX2R9kjKzWELD92UdongsQt3skdeyPLQ7/SB5Iv5D9dA8c2pcT7E46ls0HLVYfdnDfe4L1r/6cbP/AwO0YrmMMK5MMe17+Ccbxd8UqUEcAYIk8rD4K6E8I7/wD6YxpCnjxSyfYPiK8/3fk+m4fttg9sKh2jHFBqR0AGcZv3jM4/t4U6yAP4cO/9xRn/zXh6m9/Sw5ngfGAcfAhcPpLsn37xEV/D2B8X8DJxWGH2nmcP3uA5onD4hfk3jz47e+gPR0QrEn5JuwMnv9ii/4+49Hveix+LNf9e7/5U/j1f+1v4bf/x3818SW6xxOWPxQvEwRgWnG89yZQZ7D60Qqbr8frMxG6v/AToJRV0ruv/bbrsipWJ5GI2TIO4L6XyEH8v1+SovNmCxiCeyaCLoqAh2mSzsf7HDHZbMHew5yvRb0JMWX8xWUSldFjtR+tJWKgAjAA3ORxOHgwAfbFJRYxrZlOL3D0vajQFd/u1dNL8PoKNgTwdpuQ6ND1sC8uYLpFUn9WNTHHjINyJHO+httW4Kst6o/jXDZKslE/gIcRLo4sfezsjr6/yzRn3W9doTmrxXsDAPkDLD66AphRn8f5MgN204Musvo0FyOf9sN1koNbxHl/c1rDPZPr4CKmUq0boYHHyMvhFGBfrsG7DqsfXMXtJHRqBj/jGJipxeqjfuYzCkhEoD7tsFxVWYXbBxz/YYvlM5eEa5bdhPq8lv3WNlG4AeEr1BdNinokjOLyCld/+1t48E8jxmIIviW0L0eYUdqmPffwlcjcdT/UMG0D74AHF4z2PGB9Jp356ocXMOtOpmVTjnLdby2GQ4Plh1cwZ3IOD3/vEP8dfhXv/SOfO4sfWSxOpySrl5WyHMwELF5OWDzNSlnPNrefkt9FQ+7KXbkrtypv7cjiE0uhDE1EkcH4mv2ezumiCzsbmmt7KohZelQawjW/t9IMaH//Ju4vGRBRHh4XWbIUMzhFXDavm3CIAlBNjNFXndN+xudNGaCf9DtRfoXocRUU03VJgEdxR4/noHUnymQu1TwNEXgtzy2e/37WY3IZV4yF8udEfIuCvPqXtjX6W56GEMfl1szPwUqd2FIGL8u23s9i3l9W/Ma2qCMV9UvnEm+bgGvLZFsgKPSi19cYwHA6NhPy8aloGyvb6lSMjZ6Htp3uN34ulollJm5d3trOokxJv/ZbeZPFaIeENeNF9yhu7Fe0hj5w1gqQaS3gQsF0NEnUNlGEnQN8dMcqyED7VG0AmVrsOB+rckLOIUntZk0triv4VoRnnYKejYOp6xjNcJmeHtWp2Nr0UCbw0mbbPjnFGEkwlG0RywfP5AclKYTVBkZZkQHSUdROaMPxhpwWRpiVoxdHL0jEgLyDKdmtiWHKCHVW1dKpA7uC+RrrzZWkgtOUv2tdE3W5MXKTk7hx6YMytSRp3JFKDchQGwBCazEtbA5djxN8YzGuTL7mziDUJtbXwBZtGZzsFy63kzSbwXjA8JpibkjEcTcG0zJOAQaD4KQuumxaACBg8oSxN5gibu4bCxoruX+i+xlbi1ATfC111DabFgR/PGFcutwGS8K0iVTywAWDk2B7hm8IXmeOfv4u/LTyqZ0FEf0lAP86gGfM/Mfjsv8MwH8A4Hlc7T9l5r8Zf/tPAPw6xCzjP2Lm//X21cnlEzGLItWch0EwimmaYRb7jMprRSXexgnAJLTjYUz5ECEyH8vICQ3iXcr9kFO+vfh48t5xaCPuT6z2iJBOzmmq8q6H0Y5s16E6k/RolfAzV51I+DPL8Yroi9n1knSldggaZegG2HXhzzlIPTWNXrcHkHwpFBvQCIa77GGuImZRpIm7KcDEm7dtLNz5Lgrg5EQwsxvFM7bwOEm/rTtxxAJEP4JIKNt6HWL0wwKSJq+MznUH6geEcZLUeAB1YJjRg0YP2+VbeLk0qM+HGILN4UF2Bu6iFxGayDwFM6rzXjq5GPUwEK9yGiZw72bp7jTIKE+XaTyBxxEHHwLty4xZVBuD+mxIXqfVWtiexAwzxQ6vFiC22jCaC48QO2h32cn5G5MFlgyhOa9hxlgnZXA+91h+v8Ly+Zg6cttbtGfTdfvCjYGZGM3pBH3sKQDm9nq9txpZ/DaA/wbAX95b/l8x839RLiCi7wD4twH8PICvAfhbRPRt5tuSI/bKKzgLVLkchqtr8DAKqSp1ELKcogZnIi8VtUhalap6fbwC7YYsz/8xCfnKUKYvR6IUHa5y+GqzjWG2aJgbH+Dp4SHcqZGHQcOxxyt078krZDFMmO5FX4lxQvd4CTCw+MNIzz1ewe468dgYx+y1cX4BXi3gjxew2gmpNua9A/TvZd+QtutFf5I52+Ol/AzR1Az34vofy3F3X1uhOY0O4V2MQLUVhuMK1Vra6vIbDY5ZMjGHe5k6XF+MqLshAaOJGxECxocHcLG+4wNpg/G4wkI754UcczhpBGSMYGr3+AAtEehqg+5d2a6/5+B2DDsETAuTRg9n33Y4qnTKlK/11BBWTwUgPH4ZQ+rM2L6/RHdikgr3+M4S/UkF2wX41iQ9CkAStHbvuEThVsLV0bMlTn/JJzCTSd7uq6cWp9+RNm2fG/hGhv27dyOgvGCEOqB57rB4bnDxs3JzHv/hCtWZBSwl1TMmwsU3W/QnBLc7gGaCnH3bYfkvv8DFxcP0kts9IiyfVGlkNcXbZjximNFg+cRg+zjeNx6Yfge3Lp860WfmvwvgBhnUG8uvAfhrzNwz8/cB/AGAf/H21bkrd+WuvK3ls2AWv0lE/w6AfwDgP2bmMwDvA/j7xTofxmVvVl4xDZlpOcTksH1LP/ZeQqfx/35JQ2wfhNXYjbIsSvCx7rvc1st0h4qpBU+ThCH3woV2O8wSogCA+hHVegSTfLbRsAaTR7WZUHogmUES42iMCXFjnj7QOMFsxzyn1YSv3QC3HmfHAxF4HJM5Tlo3Llf3MT3Laj2ldU2hZ1k5go2h3uYywOwmwVg2GoZj2N2Yrfu0/YjAIcg+dWqxGxPIqcdXCnNlDcx2AMVRTbWOdfQ+eVywJdghwAwB5DOW0rwULogCnQBAzHAdwW0mMLmc6BdYnMKsyyHiq1FEeHsPO1i4q6ItxwB2lJalac4won3i0J7rlEEwimrt0T6Xe7c5D4IhMKBDHmFTGtSX8nsbpyx214n2Z6CsAWoM2nMP440kncWRZPuS8fxHJ3h0ETLAaQnNOSM40b+YdnI82xPMKGFaxbWMB8z1nL9XljftLP4igD8HuUx/DsB/CeDff50dENFvAPgNAGix/JS1P6EUeMCsU3hVlCJXYP5dNSluAESTr2o8ThnhUJo17W3HMTIwO5YxKUeATREZARCsAZlcfyaSh87s7YNZblSXoyIp+mCKtGo9JyOOZro8gaLR6Yz32ie4DOLxSCmKEaxJVQkOAo6iQNsVJzA06/RSx2Fp1g5MMSMy0ahV10LAWLI+fU/raAftCMGLTsmsDescmeDEhCf4KtKc99y32Blx5NJpopPrQ54RqjlYzM7A15SW6XWEMfAtw1cKcEr7sM1AYnAkJClGXtYAwTF8J2Ckr3PkI5XinvI1peMb1QytAVp4BJdBXl8DIeadgOUzIMdlI22hOAb768G9Typv1Fkw89N8PvTfAvif49cfA/h6seoHcdlN+/gtAL8FCN37TeoBIAOdr0tbL5WjgsmqTYVyFKlCeEmrft1j7CmO69ySAueHijkDhenNJyAtBQYHn/cTQjbO/QIKlUpKzIDPbaF1JEZUWeKEF+Rz4kwXTybQUv8kAKyqT29SNwCiSo1sDIy8XBWry3qFigTIDHt1CAzjGZ/VPJhCUbeg3/M5Eue6oVgPkLe7nIv2xCzXninVa/9FlI7LAAexRczLKLWPnGdRh89Y3qizIKLHzPwkfv03APzj+PlvAPgrRPQXIADnzwD43Teu3auSsvZVo8hISBEFem0l21T/A3sA5573J0cvzqBq16qIBeTe3omwCzcVOKo8k7XgtsrCOMkztILp6lkYOywqDIeyXdXW8AdyLHtRYTyUelRxP2FZw1ZVVKVyOXnIWnBbi/foVs1iOJ2D7gcAqroCL2pQV8EvI2ip2Z21+GIkb9QkbONg1E4g3qR+6TAcuXTjdScGbczUHI+K3IxQw5zP/TZk30Y8RCNo6Vd52+pMPUQiwHlYoZnynT0cVrCXNYxzGGPb9ccWrjFwOyMKU1qvB4TmwiaOgZZpQXA7h/7IYqntyGJS3N0zyVJwWjkMRxauIgFOp0KFa2EFDI16FJo9uqwcxveHxMxUgNNMNoGZQBxlMLB7FOL5BqAOYFcBIPRfG1MdzFBJ22snYID+xKC/R5hWDnYtx9o9JHz7Gx/j4wc/lTqD3bsCZIZKjqcA53DCMCNgRoPundjpewK/Rg9wm9DpXwXwKwAeEtGHAP4sgF8hol+U6uCPAPyHAMDM/4SI/jqAfwpgAvBn3jgSclfuyl15q8qndhbM/KdvWPzff8L6fx7An/8slQKUlPWKsVMcMQDIhKdi2a26p0JDkijqJhZEKTJGwrETFXJ6DsxjzBjMIwkhSO3Nh6u4jrPpDS0+FcVnxS8qh6kVAEwzMn1tYWsh5xjnEJToZEVLkm3B5NT92yjppsWKGpMwR+frppTwvXm8rwg+1osqWcdXMl/3UVPSt4RpYWE8Y4w+GBQA25g08gGQE8l8EC+NQt8S2MNHYqgvVCIzl8hPSoQik87N1xSH+iSkI53BLYV0FCwSZkEs60+tEVCx1Uk8Y2oI44pSvUJl4CvATCR6E1Ue2YaKohRexAs0qmoMFocdfBNDp0be5r4m+EVM4moJoQEQ4ogCgFmNsJXHtBKyWHUwxLZtENpKGMU6wlOsQY8fr5lvgW8evsSHy59K9ZyWjGkhBkb6XdomgHsSclcbRxbTl4BZfBnllR2F/l6AjmlZScrSKcwt9CW4VMTW4waJfCRnMN2/MkUL2vYMvNN93qAZIPTmOERmzpUPsl9GMd9n5EhKyOrcQkiLD9ceiCsMzqIeicFpsshJuY3+jlwVtpiDbMX5KGYRLGb4xV5jpijNTPWciu8Ry/BVARiq96yLYK8rvjsDE2ncqY6pwvnQwcnNTwyhBBbL9STTA6jtz0jDfbYCNsox98BTFaqxlL7LNga18/CqJ6OUaguEOqR1gosVjcts5dG2I9a2BRvAuohPKLYTKOMrPmp21hz1KLQjZZxU85R8roJQ2xXg1XpVQr4PNRCaeO0sXgvMeGs7i08cWQS+DvoEziMLpk9ncI7TbDsaJrH/02NGRzMOXOgsEDAEUD+KJR4A+CBz8b3Qrd1NYk4TON3kZpjgNkFuWs/Zdo4Itg8gn0cWZgpA5QTAK/QdKArD2M2YWagx9Ge2I+p1cb79ICzRYZT1i3URTYNSSFWNa9YBdif7MGOQDFlHqDYhgYn1WoBFMzHskAFbO0TtiaiXUI4sbB/SQ2kmBojRXHrYbTadBoC6NnDbMeEb9bqWdaZsB1htDFwfYHqGdRnMbM4Mqm1ID7vUCzAXDNsz3I5zVGgKKc1dj11tJoSKxFJwNBLOjoW8RdNQWqajHBpGnD97gAcX2uEIhbvaMJrnci3rS8B3BOMRMQpgWlmsbYvq3KK6Ai5fLFK9ZD+U2JXBGTRnDLAcX5m0zSnh/3j6x+B2GdBsXljUFyz1Y8AOSsCysB2hOWX4Ogv20nh7vvdb21mkjiLkByoVdRsDkoP4jGsRxXY/kWehTMZpArMB7YbIX4i99jQJVbt02Jqm2/MsNoPEw8cpdWJmJzwLAEA/wG5cqkt9KbwF3Y/ZDuJgZoy4cXVRNGeU4xmi6zyL/g14Fv11noU+wKabhKYcGDWQOrf23MFtJ5gxzB5Ku4kcAB1BqEsbs/BO4rHcldgV0MSvxbNIbUcEMwRJU/cujQbbFwb1pZ9Nx7Tzr64mhKoQ4fUBzfmE4KpUB1fZN+JZNE8c2vP4kBtg7A2aC4/FPs8iADokmhYWbIDqCqiuGIuPIsC93sBsB3kZxY7DWkJ73tzIs/jxDx7gnbMi+sOE9izISIazurftCGa4gWfxOdO9/5kUsbHzoIVQccM2Kxhj0SbVbmpbUVByTtSjAMmJqByop/QfmGMZ4VDWNZMQh6b7K5jdCH8gc093eACcHIqwTAyZ0nIJYAtetghRlt6cVQiHS5iz+DaNJJjh4RK1PtCxoxvvL7F93ABEONyNGB7I26QdJmzeq0EBuHcktOzd4wO0IQit2xr4I1nXrK8QTlbwqwqVtsFOKeJLdI+yHqM7XyCsxKl8jMeqr6TevGhAOwN/HDku8ebffK1G+1L257Y+id8MxzaNWi5/ysIMosmp2pFgoD0zMMNRuskpkrIwjOjeXaKJnWb/TgsmwrQgHHZy/ClGSPp7FZrKwMWR0O7dBqvBw5zV2D2Suu/uG7iO4TqHUf02AFx+CwC5nOUZ6xVqwrIxGA4ICxX78QEX36zRPyAc/EjuheG4RnffwnWCIamlICDiN9t3TVLh1vNuv99i8QtnSY8iWGBaAaF2icLdPrXwNYNCjnpUBwOsC7h8scDiI4f2X3gp7f//3kNzLpiFiwJAbAjrDxz6e0D7ssUikuUu/zngT/3y/4n/5cN/KUeEHgsOEpycu4rfjPcm2K2BX1hsPtAXLcFfd054ZXkNeOOu3JW78v/n8nZpcBaFqlpUqVSbcFNoJ65WeWpQVZKd6RxoIW9P7nvwOIGnEeSqJMlXgo324QP5EKcUtFiAQ8iq3Vcb0XTcbIuktQrhagPTNCkNO1xtYA5WSdtRM0HdB+/LZyUmAZLyrgloV9usrN314PvHYgh8ISpIfHSQE7IKbw7ebEAHBzIl6uaeH7Ros+4jAL64FI7GroM5lIQxlQhM2p6xff3pubTLt76Zjxup8Cr8q+0XDluYK8kMDcvodxGCZO32Y9aZHOMUsR/AB8s8bWprmYaME/gqJuBpdCpqSLJK860W4M0OvF6Dvv412b6JCtg+gBuXCE7TvQXcxS5HiyDTEJqCZJI6A+qzvmg4XiK0Faofn6bzFdV08SNJGbkA4CS9PfmvxIgPf/wcV7/6Hax+GDU4jYFvLNxlh+GhjFjsLrZDYEyrGBFqxciaJka1HrH5QO7do+9eprqaq3h9Y9p/WFSwT8/BcZQ9/exP4fxbCxx/r8vK662FWw9yroERovp5qA1s52HXXZKOBDN+9x/+RVyuf3wr4OKtnYYAwCsZk2UHp5EK5rmOB4f5//2iGENkIfI4YuYTqscpt48isTzN8x84pq7PDj8MibmYGEJEoJ385xAyXuBDnO4UTLwpbhuEYTiT19f0+THf+ADEtZ2yiQ6PgoPo+uW6rJ+1Y9Cp1q7Pkv3MybksTSkAmCt50BHxE0CG9RinORuShaXKGiHRTneMVPhdJ0K6AHhScWTpdFI9DQF9D/YBZsidfsnE1HZzFxDsaXIZyPQs2E/gmWgQKTAdkKJO3HWZOVsIPQMCPFMISRCYUoTMoz0dRAoPEBr9KNhIdab2hZmVa4bsvKbnYLZDynClYZL2piTRdwMAABsKSURBVMzgRCDQ1RZmkBejyijaiw7L55XgQQoe94L5sDGSEp9C0wZmN4J2/SwilD7forzdncWrwp6l+tQsR2Mvj+IW+ybibBdAmEc+osdn2tun+KDOq6i2ACHvs1TiMiYL2kDeHjRltWrJs3Cx07A5dBr9S7+wEkcScjCetTMX3BaGPDzJtxQAsQUmZHuBGBKmycz3G5XBbo/Dx1Lk2qS6OJsjURoOdiYrWI8eNMSQpzGz+rIx4Cove9MSSs6L+rWaIryuVG7O158NAUHqZVQpDfJQExFC7WD6WK/Cf3ZWrOa8aLw4tk08tuR+fEqO1GuUt7azUKtB7UVnpYyGIEYgCqn4fSGaG4u+uTRvIQ4T00Xremn44i1Hrwrl3lj/IG9StQkEwM7lpK8xC+3wNMmb2gdwnG5ptIKB/KbXepkvsLPQegPZGkE7uCTGEiXsxyknpoWQpPLTW1ejRtFsKU0t4vm9dtHtNcmOWTopzQ9SULxHzhmJuTQIQTrkKMCDODo0BmJH+RmKGXzmxBgZRdHk01ubxjgqCzl8TJPUy0wAppDATHPVASHA9MU06KaOIu7DjCzH1za3VkaBbGajvM8DbLgDOO/KXbkrtypv7ciCDH0ybbuYctDrTD/2t2dTpJ3nNx4bSU4THIDm29x2/4Yko7WgpKd6qhgvEHVAdVjt8nlVlYyiipEEqeHPa8THX6uUIwmtm07xSuFhZyX7NQ7haQJg45ROpyGqZ2Gia5tVwlvELF5DSyHVbf+/tWAlGZi4zNkkU0feywgIMkVJ4Kueh7W5zac3a1R2hRxBpP+LYO+cNUvxHtP14IVwZQuXMHZWpi3F1IMrl/VMy+NS9EhxBvB6L8n1Y6L5VOhzGBa8tZ1FdgyLQzFjkWjcxmRHbmvBgWFqO+NimOVS0Pm2AdSlikwG8jRycrkWUe2DE2FExghFePYiTT9CPJbhBuZgBVqtsl/ni1Pg3QfA0xcy11RQ7P4x6HIzm0bRcgH/QOL89skp+CiqtL44h78f5e0+/Eh+P1ghPH8pxkbbLUzkX/izLexqCTx+B0b1JKM3CR8sEU5WCU91T8/BTQ2z3ki0BQBF9yqqKgF1lW/iPeA9pvfvw15G1604DOa2Rlg1SX+y++AI7YeX4LpKZksA5PdtB46Rldn1fHiSfU5iBGX62j24FxJF4LoCDOBXjQB2kZTl7y1hTzcwp+cID45ku4M6+4bUuSNd//QKqx93mJcK0+MDNM92wk35/Y/SL/79+5hWFWxUkg3feA/ToXiS+IVDdan6pIzQSNZrE31D/FEt2pjfd3j+iy3ux7wZJuF1NOc1Lr4p59mee/iYE9SfaG6J5Jo0Z4z2vMH6A3kUHz/bSKSsdKcfJ2x+/j2MBxaH31+lKMnFd07w4hcI7/1OjoDtHlgsXvpE81av02FFCBWweuaxu599Q8ZnPwEmQ59Y9lPU95chdiIYkawC9ovLiVmA3Kzkw9xHch9IVCDU2QTiwchbgPbAT24qIYSV88a6go9ak7ZyCYQzzublEXhlNUZ2Lv2XChvAOYSmgt0VEQSSeqjadqpvBGlDK8utyW/Y0utUIwrTsgJFpqayKkNTyX7jHHw8sKhj3WfHmwKssyKas1e0PfQzIC5kTpfF+oXWwow2ze39wsHGdbSNpoMKthPANTT5GvXHhObiug/ouDKoripMBxXqwjN1WlYYDy1aDYO3FaalhTWiEq4AI7GEJMcDg+pS1h2XDiCg+f/au5YeyZKr/J2IuM98VHVXVz9mBjdjGGNAljeWvJgFEjIrdvwFJK/4RQgh/gBLxAavEAIhI1k2MmAPg2aame6u6qqsrKzMm/cRESxOvG5W9Uy1ZWbKM3mkUmZF3rzxyMx4nPOd7yNCe9+im8Vdl84B0Su0hy56pEWcLO7xo3a5HrAEoQXae/x2U2UhYjLqw1SinRHqQgaUcTsndA8HdLNkDA4Jsou5IYHde8a5Nd1aoDvwEHCE625jd2uySLVFd/Af/lgiqjIwegOI7N5dN3qP1azvmTo7RVVy0ljfB31LvxMQi0vexXhnl03Ys5O6iAh2sw1YBKMNxGoD4/MzHG6BTi9gN01MDANHB3K/tVyuINxzc7VG/gmv+INv7+ISpm0hVqvw6PtlVytIQWF3xfR1AnQJZEMMcWLTgFzYVJ67FbxpeMJxUPYwmdUVbNuheLYIcogeGi6zDGKVh53GVGuIc6cPuvL0sbwTsetNHLfEhBsPAKHfRduDrrhMNi4nZp3xscE5DHOtQZstLIDsOY+RuijCNakMw1F/AHUe8TjeylxBXG6gypy1Xp0VzxbIixz2kvuiMgV5lYMGwz9az+5tLGSmkF1IyAXfX16W4djz6F816v9140sEKAGxbqEa3i2qqz5ArD3OwmScEZytB6irHqUjEpYvL27Ua539zwS1w294x+X9n2+gmgoHv1iF6yYvCqjLNhx9QpZsqTDUEsVZi+qV50EBVPMVSCS7ZpSEh9Jox2ckjFHqCwBcYpaGNTIeD/xxx8kgjhLCdu/phXiHIexWgmee/4mhz00TsRbempgcN/pB9X2QFQwTk5dl9PIDCR7Cdi6nY0QjyMlz1LRj3wgRA55CBqtlvn3jok0+Qa0sOSq0Wl/HZHQ9t9FPiEQs++ja7s12PWzXXeNDHY1HYqRk9NhrzX6NbccTgPebbLmflGVR37YfAt6Fkp2CEiKKGe/U4yd4k0zeYrVmhnN/zOwcNF9roM6R8rwSwGPexlwWmzPIrvpkHSQFQ1i/7QILN227QIXniWvgskdFy7keHsJtN5sbI4Diass7CmMCQZM6XWEmKCwEAAKWImBi3GSqMgXzzgxy1UZyI+CNcBb7aMje9ra3W9nd2lkkKuojhyYwVlGfz4MQsZhUDLmu61AGa9gJ2jTBkQlgpKKunjJVqF2ueCV+eMSrmoNjiw8/Bk0nTNziHKeirnmVuXcQaflenMJOKpDb3polC/3iu7/HW1a/WgGw8wm64wlAQP5sAXPo4MAvL7B97xHIWmQ/dn14+jbE6Tkwm4CWVyDniMSLE4jHD2HmNcSFW1E8EvRwhv5h1A3JPzpjiHLbBeeg8Curh1UfOsfpBx8BALo/+g7ypUNlNj0g2MfQz/IgFHz12xNMP94AxqKfO6IbC6hVB/XyIkGFul2Utaw0v+Rx9E7YYZajeO6Og86PMRwUThCI79E9nCI/uQKen6L/w6cAWG9EtJz2rqt4DFn8bo75xwM8nwRXDuhCoDrp0E8VJv/p4PbGYvOtY7QHEoc/4SNAfzRBd5BDbTWGUiJPyW8Kie1RhvpT/ny6A+735Gef4sO/+AYe/ITH0RLT+NWnGotv8c+rPLNMrmuZCg9g4hqTWRTnhPLM4vJ33Mf+9wXkcntdN+QPDtHOiY8epzxmL//4ERbvt3jwo7dCO5tjQv3SsgKaBVzeG/oZp7zXR4fYPPLoVqD/6PZOi7s1WSRGUgI24bTwaE6rQXUVhINoMgFt21GZ1RpUlrDbNjzyxXHbro85OiC1AaTA9skcatOHL0H5LAPNZxxR8XVNJ0DfQ9+fQ7sfSX55he7JHPml++G6CWv9dIqqUJDrLqDo2ocVVt/IYAm43x+gecxf3Km1OP82Z3E+/neXWfnODFU/YDiaIDMW/SNur1peon9yiO2DHLVPNXZn6+7xDMt3Y3TiaD3HMMuRu/YAwNT9CH10o3vMX/LsI/4qLL5doD5xPKErl3U6kWiOovPw7DsEndcQA7B+FNOdy7MMB72J8GafG6INVu9OUD/nOtZvlwAB23uEe+D6e+ek2xxL1KeK6waw/GaOA0koL9e4eI8n/uYhIVsDsrHoZxQQR5vvb9D/tGamLOcjJA3o0mL6cYHtfUJ+4aJC2uL89zNsnljUJzyRXr2Vo3kooNYKw4RQncQfUj8hrN8BDgvfBu539WyGP//Tf8Bf4Qf83ZOAPhhYKez9VwCA02eHoErDGubMBJjh6jBr8E8vv4lPPjrCn33v3wAA//jL76M+zRjZ2UeOjFffZWemairM3DFz8X6LD3/w13h388OQH3P8dIHTD45gCwMYQMz58378YInVtsDpLw9Rv8eLZtcr0N/dPlx8ZycLPk/b0f/h6TY6eeymgdWGnWdp5GGzYWege9y9hzzh8J53+BWfLEFdD7lyKdxaA82WnXy+rm0Lu91Cniwgly7Eut7wLsGd4X1d0/++hFg1QTsDYBWy7KqCJSA7WbF+BgC5WOPoPwrHju3Smj9dgbYt1KkBNg0yx6dutYY6XWF6oUBL51RzfoO8H3C/mcU+vlhAXOTAao3pB26yPV/yaysOnXqHq3GPD37WQLodBLUakIQyV6hfKlDP46C2JcqTFqLTKM/dSq0t1LqHXKyinyiZLGYfXoX8iVnHzufpMwF1wjux3O3UypcF5KoNOSf3NzOoVyvYyxXu/YL9EdPnGfNZ9AbDRAUEZ76qMHnRMwVeFj3+ZCzyywFDLZEtnE9j0Dj6mcLkeYb8hH0hh5ctpp8WEK2GKSQ7Cp2ZQmH2SY7yBX/O00/dDvTVAn/zt3+Cxz91YXbJkZL6tMdy+QAA8GhpYBTTEL44Ygo8T4WnGuB4YTnNHMDbHzaQmw5WCkZmgnEUj/+5RjeTOPjFKvgoHvzoLby7+SGO/0UGPovu58d4/Io5K8gAQ8nf501dId9aHJwZNP91CAAoDICLr3ro1NhIq3dTotgbwLIjvVqkgBu9ltL5v6kUgG9L4FZIqOhcklWsB/x/IP1xz3ezgm8q+38ysparCv1HeCTjqO5N8prZHS/Xx93IloVjIHvDBiX3JVePlx8IbbBw1PqxD+lrqaRCbPev8LmO2oUwNmT95xvrDmXANRa70Fb/upc3IJs4fz8DDGj8PXw/KelrvO+vw/YOzr3tbW+3sju7s/hMwt4ULOV9GYJGQkPkGLf9I4CxbogHX3nnY+n1NOKQBCLfZOUhpYAij7wUSrET0YO8vG5InbMkYtImU2ToZ+yzUOcyaGXIJWGYsAyfZ7+yhQsretCSf9QapCT0rID06eFeUasugsMRAGSZw9YFRNtjmDkGsEuHPC0yRpw6IeigGzLPkKfCPUTQpUI/Vciu+KjSHggUC+aMGCaRz1Fo5VLa/bEvruKmzKJuiANg9XMFeVWE8QKA3vmMpIMp9wc55KYAZQpDHTU71FZAdAa6EmH1bB4S8rXcYcpiBS7RWfRTGdskBPqZYnZvx/kwzAu09xjspqvxOjqUEs2Rgtpwe9t7/NkVRY7tkwHbZz5bmHVDZCvRPHLfLUnOwUlBS2SoLWxmULxi39z2iXZjIyFaEaHoACAJzZFEe0iYvCjCODbHhOOnC3Q/P4aH7TYP4fRAeIcxOHBnN7eOj3MsjGzi1+Vz7c5OFgBG0ZBR8TCMYuCBfzNRDvtcDk4PZR4GBjQ1ifo3wPgDrRlT4beTXuu07SIx9zBANG2I30cOTnfuTmC7YtMiWzLyj7Yd5JUb/q5Htux5e+7qEhvm9aRtF+oE+HXadpAOkwBEnwVtWmSXY5AUwJgOuWrDc8AdMfo+cFIGwt6LPkQ9PCWg98p7H0t1lvE12qLwH48B+zpSLgrDvAxWG8irNrRHXjlQkLGhfplMUKnPIlvmfE0/IEs4MWVvQJ2BbOPCUb+QKC4G3okHrVMm780vewidMI8bg+KiB5BwcF7yvUSrYbZjn4VoFSAwKgMAtB3qjxWqc/f5E2FYE8rFgPq5m1AubBD9Eb0DZ1VO63RpUS5MmHTVahP5KPykS4TqTEN2AuqyDaC5+qXF6QdHePzKxGOMJtSvDMsyAkGqMLsCRG9RnRn4AwUZQFzHz73W7vZk8Ro+C6KYeDNK7gpinLc4XQXgkuNa8AlUKWybBE8kuwlqaf3A6Hl6zejP1ymIF4G03EkLWBN3CV6jlK9LEpUoSRS6qV1pWVKHL6f0tfTR90XGe5AQLlmJOCHJowIVBT4KT+FPwkZJBM/T4XdmggFIYZykT9ZLxwbJGGE8ZuEecaW2qdap38AoBJ3TcK0FrCs3nvvBjQP/n9bFbfR/KaBvtyz0hZyeSJCG4PExTlaA22UDYa/XHmU9VGYJ59ddPUoEPgq/PbLEymEs0xC/C0YBtnAEvH6dDHX7idLVlzF40MpYJnT6hfh8u9uTxetU1IHEEWivl93GEXnj++y43BrepdygUXJre50zMi3XJjgCo+PW8srs2bpSp+EXRYXo2MeswchRGXQ8rd1xICa7PSCyl3mNkXScf6X27Dx3juHUkcifISFkBFnAguD1VXf1VukGB+wbm4mOS0uJ89dZ0Drd7UPoRyzn91o+Mnt07WuIa8g5xVMH6Ujb9LPq/RXsbk8Wr5sobthNjHYbGm5lpviIsc8isCMFHVMJDHLMmrS7sxBuNXfCPb7eVEU91OV4IEmIUIeVEib3NGcynJU5pVqMPlCrBMOqFSevhRwIV2YzeV1FXUnYhJEakpPeSIjAxRj0TryK+g5LlMkdexQAq93ZORMwuQA56ruhcGrjhkJWI1nENtnIAAaAk+xUrMsmvJDYLcsERCbD0cd4JiuKSvAmF+HHaFIG7oq4/cnOgpXECSaX0AXF/hoDnQsMBYU2mExwfyxna8oUlJVLVhbzuRa+XikxTFjdDHA+i5L9JF5ndGjomvboUFtYxboeQ0mBhdtkEsLvLsLnyOPs6/cQ7qFkHMVQluG7M9R89Ajs3hWFctkRhoKgXZl5QxX1fTRkb3vb263sbu8sXmckxj6H9H9/iUtNf12KerpSg5g3EUOy2gORwCbelM/jUoZoCrnnJHdXaAkhJaASoFgmMZQSICBXMnAxSCEwVI7t2Z9HM5dMpRzZTXp/JWGLmCbvt9Y2VxiqREU9U7C54oiNT+VWMbrCKflJqj2AoRIhAzTIFRaKtU19inrNKzVZC11GZ5ksXOJeIKOJlHu6kGFF9LucoZLIvc5ooUKZ6FSgxRsqiSxnCgAP7R4qwZJ/xLqr3voZWEeEkhXT8kqfrQSGUox8UroS6OsYdeDMTAEIYCgFZKt2rhUhkjN4vRIlMdwfOGUdYMRrTRjWAv3cObtbVlEny2rmgNMezWxQCuvvOXBc7nZQQsTvrWA+in7GkSmf1t/PCI8fLLGpY0pDN7fIrhAUyXw0pJ9b6J6g1oSOQaysdfobm6Kemo1nSwCgLEdAdTqiFgAhGgJjx1mNeQbSBVCVgUFaFAVHFijqSHKGpGFOxEEDDqpshgHkOT093LvrQfMZbKbCpCLKAsOsgFIKXlIAQGDVDtmeAEhrCO/174d4fu4Hlv5DkjK/HRiu3pawbReYkszA8nVGTSB8fopnh6oy3oL7CWdaQc9zKGuh3SSiMhWo5a21MI4jQt07hB0GiMGOuSMBUCa53LVR9lF6UbZJuLpjhm+bCkI5E4OJMou9RyZGfg9dKRjFPBKdyCE9v0VBGKY5ssM5hEOQisFCdCyXmDqXRc9t2zWTEWRnIHsROTgByNYgayhEwfyEAALWj2U4R4nBYihFcEj6ew4loX9yD7QVQdnLCh4TMdgQ+RB95HYVPm2mJRhEpTDpOCrktguh0XEffFhWwrwzc+0CVtsC+TaJJHUOJu5+N16+UPeE7Vs9irMM2mudvuGv/+5OFjvmCXxBYhQOTUOko+vbjlO5m20SynPvsTomX3m5wKZlynj//uSeaV1Yb0BEEB4C3jRQZ1c8IQkKKdtyxaFCm6Rwp6FN2o7DmYGVyTsDXTjWSyP6UCKMBdoO6nILceXTxLkPUhvkROFLLi+uILY5aLVBlnJcEAF5xhqoPsKx3gBaI7/oQ7t8nT6s6cvL8zw8T02uWp6wb6CA8+OR3qfIJNQF90E2GSwR1CSDbHqIrftcugrZ+QZYXkEdREYo0WqIduCQprP6pUSxuP5Dk61EdunkANq4oOQXPcPBXVlx1kL0FrLVUGsVEupgOZGsnyoU524yH1ikOHu5xOTZBNWZ6zOxz6A4H1A/57EtLwx05icL73dxTFnnLCnod01ytQ2h0dQmJxrdWqA4a8P41UeHOP3lIQ7OUoe+QHVmIvmN86WoNaE4yzB9rkMbyMTJ6zb2GzNZAAgOzxRolYKvRpcqBSu6yG4FwAu9gESgxfNgKlsV7Pn3YKvknmldUAq2zGGr+H5bF4EFym+9PWgqDW+moClZ5tAJUMqX594Z6oFeRR4eQx+KHHpSBMGcESjrII+0egumw5NtlGUUFyzwY4ucQVlehtGFXbvDDLnHivhYfZ0HsBTA0n35gu+XlgOMi7A3cFmmIDLf7+4wg9zw+3WVAUTo52oUpu0PMshtDqkkhnkERMlGQm3dsc7Z5pFAtrnOMtVNBeQ2R3egUBSxvd1hhvZAonJl/TRDe6igGoFuJkDWXeuOW9t7EqrJXRsUrCCURYb1b2lULyMoSxcAoAL4ySgR8A7bY3cMKS1MwSLFRokgKahn5Y0cE819ie6AUL3KwnFw80igfm8Rcj0AuDpFCI96Z2Z3AOiCdzsjUNb14Xqt7R2ce9vb3m5lv1k7i1+n7SaH7SaN3ea9N/3vY+PeNzF6DSMcx+iaXdxIiq9IcRYuWYvStjrwU0iuGuERbmhH0lfa7YtBgp1wRyJtXIKT65txTlVBIy0V+ozxI3293+P3ApZBETHBzo+ZHV/vcQzX8Ax6fM+0PjL2+msBoxBxGmQcdiMt19b1GWPcgn99IMTENQ7Rh+vB4CcftieXFEYDQBIOJs/34PvePIb+frv97XrF2aOjMXCAK0SKGBrYR5G2a9SfW9hXd7KwY/g3gIjstI7gFghHFOuwEvY1AJjRfUf/3zza1qMZU4SkpIAVgEdG+ucqOSqF9tyA4HSIxmuoUU80k5Yb6yaozwepebElm9DSB7SiEox29DgHlTyXsb6AyNxFlqbj4Z+7+1wzcn3xbQ4fmQloUSMJQloYKUbe/BGSMrGAqJTjtlmHdAz9JDh0LXjC2J1bFBLwiHscNEzJKei+XGcEI2Pehc4oIjdzH2Gy/L5c8OvuF7+LHA11S+fkJATiZJMBddnCqEh4ZHJupx9bnY/rtQKwyncs+rduY3dCGJmITgGsAbz6stvyBdsD7Pv8dbC73Oen1trj21x4JyYLACCiH1trv/dlt+OLtH2fvx72Venz3sG5t73t7Va2nyz2tre93cru0mTxl192A74E2/f562FfiT7fGZ/F3va2t7ttd2lnsbe97e0O236y2Nve9nYr208We9vb3m5l+8lib3vb261sP1nsbW97u5X9H945fHcAg8t7AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8908>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.81055092811584 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-09, 'kernel_type': 'untiln'} is: \n",
+      "[[2.73000005e+02 9.80000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [9.80000000e+01 2.08000004e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.73000005e+02 ... 2.89000005e+02\n",
+      "  2.89000005e+02 2.89000005e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.89000005e+02 ... 5.49090058e+04\n",
+      "  5.33010058e+04 5.52510069e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.89000005e+02 ... 5.33010058e+04\n",
+      "  5.18590062e+04 5.35710076e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.89000005e+02 ... 5.52510069e+04\n",
+      "  5.35710076e+04 5.61990141e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6518>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.66093325614929 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-08, 'kernel_type': 'untiln'} is: \n",
+      "[[2.73000052e+02 9.80000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [9.80000000e+01 2.08000039e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.73000052e+02 ... 2.89000052e+02\n",
+      "  2.89000052e+02 2.89000052e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.89000052e+02 ... 5.49090582e+04\n",
+      "  5.33010581e+04 5.52510686e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.89000052e+02 ... 5.33010581e+04\n",
+      "  5.18590616e+04 5.35710762e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.89000052e+02 ... 5.52510686e+04\n",
+      "  5.35710762e+04 5.61991408e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6518>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.82304072380066 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-07, 'kernel_type': 'untiln'} is: \n",
+      "[[2.73000520e+02 9.80000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [9.80000000e+01 2.08000394e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.73000520e+02 ... 2.89000520e+02\n",
+      "  2.89000520e+02 2.89000520e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.89000520e+02 ... 5.49095823e+04\n",
+      "  5.33015807e+04 5.52516857e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.89000520e+02 ... 5.33015807e+04\n",
+      "  5.18596163e+04 5.35717621e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.89000520e+02 ... 5.52516857e+04\n",
+      "  5.35717621e+04 5.62004079e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.68968391418457 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-06, 'kernel_type': 'untiln'} is: \n",
+      "[[2.73005200e+02 9.80000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [9.80000000e+01 2.08003936e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.73005200e+02 ... 2.89005200e+02\n",
+      "  2.89005200e+02 2.89005200e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.89005200e+02 ... 5.49148237e+04\n",
+      "  5.33068072e+04 5.52578576e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.89005200e+02 ... 5.33068072e+04\n",
+      "  5.18651640e+04 5.35786215e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.89005200e+02 ... 5.52578576e+04\n",
+      "  5.35786215e+04 5.62130810e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.58039140701294 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-05, 'kernel_type': 'untiln'} is: \n",
+      "[[2.73052004e+02 9.80000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [9.80000000e+01 2.08039364e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.73052004e+02 ... 2.89052004e+02\n",
+      "  2.89052004e+02 2.89052004e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.89052004e+02 ... 5.49672935e+04\n",
+      "  5.33591234e+04 5.53196012e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.89052004e+02 ... 5.33591234e+04\n",
+      "  5.19206984e+04 5.36472554e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.89052004e+02 ... 5.53196012e+04\n",
+      "  5.36472554e+04 5.63399584e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.635085105896 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 0.0001, 'kernel_type': 'untiln'} is: \n",
+      "[[2.73520392e+02 9.80000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [9.80000000e+01 2.08394035e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.73520392e+02 ... 2.89520392e+02\n",
+      "  2.89520392e+02 2.89520392e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.89520392e+02 ... 5.54975795e+04\n",
+      "  5.38874235e+04 5.59395473e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.89520392e+02 ... 5.38874235e+04\n",
+      "  5.24818143e+04 5.43376428e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.89520392e+02 ... 5.59395473e+04\n",
+      "  5.43376428e+04 5.76235663e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.87043905258179 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 0.001, 'kernel_type': 'untiln'} is: \n",
+      "[[2.78239315e+02 9.80000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [9.80000000e+01 2.11979730e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.78239315e+02 ... 2.94239315e+02\n",
+      "  2.94239315e+02 2.94239315e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.94239315e+02 ... 6.14019386e+04\n",
+      "  5.97203418e+04 6.23949943e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.94239315e+02 ... 5.97203418e+04\n",
+      "  5.87148835e+04 6.16604577e+04]\n",
+      " [2.00000000e+01 2.00000000e+01 2.94239315e+02 ... 6.23949943e+04\n",
+      "  6.16604577e+04 7.20446557e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.75243496894836 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 0.01, 'kernel_type': 'untiln'} is: \n",
+      "[[3.29066102e+02 9.80000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [9.80000000e+01 2.52021310e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 3.29066102e+02 ... 3.45066102e+02\n",
+      "  3.45066102e+02 3.45066102e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 3.45066102e+02 ... 2.53323700e+05\n",
+      "  2.32084654e+05 1.58179756e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 3.45066102e+02 ... 2.32084654e+05\n",
+      "  2.62826620e+05 1.94161989e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 3.45066102e+02 ... 1.58179756e+05\n",
+      "  1.94161989e+05 5.32895305e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.70555472373962 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 0.1, 'kernel_type': 'untiln'} is: \n",
+      "[[1.35966890e+03 9.80000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [9.80000000e+01 1.54058349e+03 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.35966890e+03 ... 1.37566890e+03\n",
+      "  1.37566890e+03 1.37566890e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.37566890e+03 ... 6.36944280e+10\n",
+      "  1.91517990e+10 2.65875429e+07]\n",
+      " [2.00000000e+01 2.00000000e+01 1.37566890e+03 ... 1.91517990e+10\n",
+      "  1.25774247e+11 1.85335690e+08]\n",
+      " [2.00000000e+01 2.00000000e+01 1.37566890e+03 ... 2.65875429e+07\n",
+      "  1.85335690e+08 2.23841247e+10]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.70964002609253 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1.0, 'kernel_type': 'untiln'} is: \n",
+      "[[7.94465000e+05 9.80000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [9.80000000e+01 6.54077920e+07 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 7.94465000e+05 ... 7.94481000e+05\n",
+      "  7.94481000e+05 7.94481000e+05]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 7.94481000e+05 ... 2.55986593e+28\n",
+      "  2.60962745e+25 4.15559732e+16]\n",
+      " [2.00000000e+01 2.00000000e+01 7.94481000e+05 ... 2.60962745e+25\n",
+      "  3.08563086e+29 8.77762048e+19]\n",
+      " [2.00000000e+01 2.00000000e+01 7.94481000e+05 ... 4.15559732e+16\n",
+      "  8.77762048e+19 6.99690186e+23]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f548227f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.62440490722656 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 10.0, 'kernel_type': 'untiln'} is: \n",
+      "[[2.87822977e+11 9.80000000e+01 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [9.80000000e+01 3.13771963e+17 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.87822977e+11 ... 2.87822977e+11\n",
+      "  2.87822977e+11 2.87822977e+11]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.87822977e+11 ... 1.51063306e+63\n",
+      "  6.70551609e+53 2.90812361e+34]\n",
+      " [2.00000000e+01 2.00000000e+01 2.87822977e+11 ... 6.70551609e+53\n",
+      "  2.37576846e+64 2.34546697e+42]\n",
+      " [2.00000000e+01 2.00000000e+01 2.87822977e+11 ... 2.90812361e+34\n",
+      "  2.34546697e+42 1.95195993e+49]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.86648225784302 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 100.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.73902381e+018 9.80000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [9.80000000e+001 1.43693214e+029 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.73902381e+018 ... 1.73902381e+018\n",
+      "  1.73902381e+018 1.73902381e+018]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.73902381e+018 ... 2.82851776e+103\n",
+      "  2.10473043e+086 6.57854053e+055]\n",
+      " [2.00000000e+001 2.00000000e+001 1.73902381e+018 ... 2.10473043e+086\n",
+      "  4.51480263e+104 5.29726877e+068]\n",
+      " [2.00000000e+001 2.00000000e+001 1.73902381e+018 ... 6.57854053e+055\n",
+      "  5.29726877e+068 3.51812784e+079]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98abac50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.64919829368591 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.64825336e+025 9.80000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [9.80000000e+001 1.32289285e+041 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.64825336e+025 ... 1.64825336e+025\n",
+      "  1.64825336e+025 1.64825336e+025]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.64825336e+025 ... 2.38481637e+144\n",
+      "  1.87485880e+119 5.60767351e+077]\n",
+      " [2.00000000e+001 2.00000000e+001 1.64825336e+025 ... 1.87485880e+119\n",
+      "  3.81475652e+145 4.53136859e+095]\n",
+      " [2.00000000e+001 2.00000000e+001 1.64825336e+025 ... 5.60767351e+077\n",
+      "  4.53136859e+095 2.94059449e+110]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.76839423179626 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 10000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.63938327e+032 9.80000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [9.80000000e+001 1.31193290e+053 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.63938327e+032 ... 1.63938327e+032\n",
+      "  1.63938327e+032 1.63938327e+032]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.63938327e+032 ... 2.34439143e+185\n",
+      "  1.85330917e+152 5.51816056e+099]\n",
+      " [2.00000000e+001 2.00000000e+001 1.63938327e+032 ... 1.85330917e+152\n",
+      "  3.75093255e+186 4.46079900e+122]\n",
+      " [2.00000000e+001 2.00000000e+001 1.63938327e+032 ... 5.51816056e+099\n",
+      "  4.46079900e+122 2.88808302e+141]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98abac50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 65.07208275794983 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 100000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.63849831e+039 9.80000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [9.80000000e+001 1.31084125e+065 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.63849831e+039 ... 1.63849831e+039\n",
+      "  1.63849831e+039 1.63849831e+039]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.63849831e+039 ... 2.34038603e+226\n",
+      "  1.85116797e+185 5.50928133e+121]\n",
+      " [2.00000000e+001 2.00000000e+001 1.63849831e+039 ... 1.85116797e+185\n",
+      "  3.74460829e+227 4.45379921e+149]\n",
+      " [2.00000000e+001 2.00000000e+001 1.63849831e+039 ... 5.50928133e+121\n",
+      "  4.45379921e+149 2.88288119e+172]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAADUxJREFUeJzt3U+sXGd5x/Hvc+NgBAKBSWvcJC1pZCEF2lroKrCIqqDKkESoDgtHyaK4KKpZJOo6dBM2SGwQaqUSyahWzIKEeBEli7RgeZMVf0yFaIKKEoGj2PIfwIhWoAbs+3Qx5yrDzR3fZ2bOzDkz8/1I1sw999yZ5z1z/dP7vuc950ZmIkk7Weu6AEmLwbCQVGJYSCoxLCSVGBaSSgwLSSWdh0VE3BMRP4mIVyPisa7rmZWIOBsR/xURP4yIM822PRFxKiJeaR7f23Wd04iI4xFxOSJeGtq2bRtj4F+az/1HEfGR7iqf3Ig2fyEizjef9Q8j4r6h732+afNPIuKT3VQ9mU7DIiJuAP4VuBe4A3goIu7osqYZ+3hmHsjM9ebrx4DTmbkfON18vcieBO7Zsm1UG+8F9jf/jgJPzKnGtj3JW9sM8JXmsz6QmS8ANL/bDwIfan7mq83/gYXQdc/iTuDVzPxpZv4OeBo41HFN83QIONE8PwHc32EtU8vMF4ErWzaPauMh4Os58B3gPRGxbz6VtmdEm0c5BDydmW9k5s+AVxn8H1gIXYfFzcDrQ1+fa7YtowS+HRE/iIijzba9mXmheX4R2NtNaTM1qo3L/tk/2gyvjg8NLxe6zV2HxSq5KzM/wqD7/UhE/PXwN3Ow7n6p196vQhsbTwC3AweAC8CXuy2nHV2HxXng1qGvb2m2LZ3MPN88XgaeZdD9vLTZ9W4eL3dX4cyMauPSfvaZeSkzr2XmBvA13hxqLHSbuw6L7wP7I+K2iHgbg8mf5zuuqXUR8c6IeNfmc+ATwEsM2nqk2e0I8Fw3Fc7UqDY+D3ymOSvyMeDXQ8OVhbZl7uXTDD5rGLT5wYjYHRG3MZjc/d6865vUri7fPDOvRsSjwLeAG4DjmflylzXNyF7g2YiAwTH/Rmb+R0R8H3gmIh4GXgMe6LDGqUXEU8DdwE0RcQ54HPgS27fxBeA+BpN8vwU+O/eCWzCizXdHxAEGQ66zwOcAMvPliHgG+DFwFXgkM691UfckwkvUJVV0PQyRtCAMC0klhoWkEsNCUolhIalkZmEx7tWkQ0ugV4ZtXg3L0uaZhMWEV5MuxQEdk21eDUvR5ln1LFb9alJp6cxqBed2V9d9dNTOb4vd+Xbewbtjz0qtELPNq6HPbf4/fsPv8o2o7NvZcu9mHHcUBgfzrjdvJiRpTr6bp8v7zmoYsuPVdZl5LDPXM3P9RnbPqAxJbZlVWKzE1aTSKpnJMGSFriaVVsbM5iyam5S+MKvXlzRfruCUVGJYSCoxLCSVGBaSSgwLSSWGhaQSw0JSiWEhqcSwkFRiWEgqMSwklRgWkkoMC0klhoWkEsNCUolhIanEsJBUYlhIKjEsJJUYFpJKDAtJJYaFpBLDQlKJYSGpxLCQVGJYSCoxLCSVGBaSSgyLLU5tnOTUxslO3rfvho/N8GOXtW/33ps1ba1t1L5t11B5zbaO3zyPvWEhqSQys+saeHfsyY/G33RdhrRyvpun+Z+8EpV97VlcR9dDg67ff1JdD000G/YspBVmz0JS6wwLSSWGhaQSw0JSiWEhqcSwkFRiWEgqMSwklRgWLejzasWdauvjass+1DPOxWCLYtp6XcEprTBXcEpqnWEhqcSwkFRiWEgqMSwklRgWkkoMC0klhoWkEsNCUsmuaX44Is4C/wtcA65m5npE7AG+CXwAOAs8kJm/mq5MSV1ro2fx8cw8kJnrzdePAaczcz9wuvla0oKbxTDkEHCieX4CuH8G7yFpzqYNiwS+HRE/iIijzba9mXmheX4R2Dvle0jqganmLIC7MvN8RPwxcCoi/nv4m5mZEbHtZa1NuBwFeDvvmLIMSbM2Vc8iM883j5eBZ4E7gUsRsQ+gebw84mePZeZ6Zq7fyO5pypA0BxOHRUS8MyLetfkc+ATwEvA8cKTZ7Qjw3LRFzpN/RX00/4p6rYZl/SvqE9/8JiL+nEFvAgbDmW9k5hcj4n3AM8CfAq8xOHV65Xqv5c1vpG6Mc/ObiecsMvOnwF9ts/2XgP/zpSXjCk5JJYZFTy3CHIba0/XcT4VhcR1dfngH1w73/pdnlEX4xe+bg2uHObh2uOsyrsu7e0srzLt7S2qdYSGpxLCQVGJYSCoxLCSVGBaSSgwLSSWGhaQSw0JSiWEhqcSwkFRiWEgqMSwklRgWkkoMC0klhkUL+nyjl51q6+ONavpQzzh36F4U09brzW+kFebNbyS1zrCQVGJYSCoxLCSVGBaSSgwLSSWGRQv6fL7ddRazq6EPdY5j2noNC0klLsqSVpiLsiS1zrCQVGJYSCoxLCSVGBaSSgwLSSWGhaQSw0JSiWGxRVfLnxdh6fDwsRl+7LL27d57s6attY3at+0axlkqPu3xm+exNywklbjcW2M7tXGSg2uHuy5jqWz2EMY9rtN+Fi73noLDkNE2j83BtcMOQ67zGpMMQw6uHe59ANuzkFaYPYsp2LMYzQnOWg1OcEpaaQ5D1I4I6MHvksbjMETzZ1AsPcNCUolhcR1dTzp2/f6T6nrSU7NhWEgqcYJTWmFOcKo3HI6MZ7v1IX2xa6cdIuI48CngcmZ+uNm2B/gm8AHgLPBAZv4qIgL4Z+A+4LfA32fmf86mdC2Cvi9h7ps+H69Kz+JJ4J4t2x4DTmfmfuB08zXAvcD+5t9R4Il2ypTUtR3DIjNfBK5s2XwIONE8PwHcP7T96znwHeA9EbGvrWIldWfSOYu9mXmheX4R2Ns8vxl4fWi/c802SQtu6gnOHJxOGfuUSkQcjYgzEXHm97wxbRmSZmzSsLi0ObxoHi83288Dtw7td0uz7S0y81hmrmfm+o3snrAMSfMyaVg8Dxxpnh8Bnhva/pkY+Bjw66HhiqQFVjl1+hRwN3BTRJwDHge+BDwTEQ8DrwEPNLu/wOC06asMTp1+dgY1S+rAjmGRmQ+N+NZbllw28xePTFuUpP5xBaekEsNCUolhIanEsGhBHy/62bRTbX28aKkP9Yxz091FMW29XqIurTAvUZfUOsNCUolhIanEsJBUYlhIKjEsJJUYFpJKDAtJJYaFpBLDYouulj8vwtLh4WMz/Nhl7du99/Df3hj+/qh9265hnKXi0x6/eR57l3tLK8zl3pJaZ1hoadzwvj1dl7DUDAstjWu/3Pq3sNQmw2ILJzhHc4KzVsOyTnAaFpJKDAtJJYaFpBLXWUgrzHUWklpnWGzh2ZDRPBtSq2FZz4Y4DNFK2fzPdXDtcMeVXN+pjZNzqdFhiKTW7fiHkaVl0vcexaY+1mnPQqsrSr1vNQyLLZzgHG3pJjgzneAcgxOc0gpzglNS6wwLSSWGhaQSw0JSiWHRgj6fydiptq7PZmynD/WMc0ZjUUxbr2dDpFHWbhg8blzrto6WxK5d5NWrf7DNsyGSWudyb2mUJelRbNraqxiXPQtJJYaFpBLDQlKJYSGpxLCQVGJYtKDPi3NclDW7GvpQ5zhclCV1aF73ypwVF2VNwZvfjLZ0N78ZsW0cB9cOe/ObebJnIXXDnoWk1hkWkkoMiy2csxjNOYtaDSs7ZxERx4FPAZcz88PNti8A/wD8vNntnzLzheZ7nwceBq4B/5iZ39qpCOcspG60PWfxJHDPNtu/kpkHmn+bQXEH8CDwoeZnvhoRN9TKltRnO4ZFZr4IXCm+3iHg6cx8IzN/BrwK3DlFfZJ6Ypo5i0cj4kcRcTwi3ttsuxl4fWifc802SQtu0rB4ArgdOABcAL487gtExNGIOBMRZ37PGxOWIWleJgqLzLyUmdcycwP4Gm8ONc4Dtw7tekuzbbvXOJaZ65m5fiO7JylD0hxNFBYRsW/oy08DLzXPnwcejIjdEXEbsB/43nQlSsuj61PN09jxHpwR8RRwN3BTRJwDHgfujogDQAJngc8BZObLEfEM8GPgKvBIZi7XjQylFVU5G/JQZu7LzBsz85bM/LfM/LvM/IvM/MvM/NvMvDC0/xcz8/bM/GBm/vtsy2+fi7JGc1FWrYbrvebBtcN/cPHZUi3KmgcXZWkV9eHydi8km4I9i9HsWdRqqC733uxhLErPwrCQVOIwpKf60EUdpc+1LarNHsK4x3Xaz8JhiKTW2bPQTNkLGc/wHMQ8jps9C0mtMyy0Uro+e7PIHIZIK8xhiKTWGRaSSgwLSSWGhaQSw0JSiWEhLZiuTv8aFpJKdrxTlqR+6Wr5vD2LLbyfxWjb3Sei6xWRi3w/i83H7Wqd9L1nyRWc0oI7tXGSjYv7AfjknxwY62ddwSmtkI2L+1l7/yusvf+Vmb6PYSGpxAlOacENhh6zn/S0ZyGpxLCQVGJYSCoxLCSVGBaSSgwLSSWGRQv6vFR7p9q6Xq69nT7Uc2rjJLFrF7Fr9OqCPtQ5jmnrdbm3tMJc7i2pdYaFpBLDQlKJYSGppBcTnBHxc+A3wC+6rmXObsI2r4I+t/nPMvOPKjv2IiwAIuJMZq53Xcc82ebVsCxtdhgiqcSwkFTSp7A41nUBHbDNq2Ep2tybOQtJ/dannoWkHjMsJJUYFpJKDAtJJYaFpJL/BzeFcB7+UCsgAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 65.11009120941162 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.63840983e+046 9.80000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [9.80000000e+001 1.31073212e+077 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.63840983e+046 ... 1.63840983e+046\n",
+      "  1.63840983e+046 1.63840983e+046]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.63840983e+046 ... 2.33998586e+267\n",
+      "  1.85095398e+218 5.50839413e+143]\n",
+      " [2.00000000e+001 2.00000000e+001 1.63840983e+046 ... 1.85095398e+218\n",
+      "  3.74397644e+268 4.45309980e+176]\n",
+      " [2.00000000e+001 2.00000000e+001 1.63840983e+046 ... 5.50839413e+143\n",
+      "  4.45309980e+176 2.88236150e+203]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "../pygraph/kernels/treePatternKernel.py:152: RuntimeWarning: invalid value encountered in multiply\n",
+      "  kh = (G1.node[n1][node_label] == G2.node[n2][node_label]) * (1 + kh)\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.7658851146698 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 10000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.63840098e+053 9.80000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [9.80000000e+001 1.31072121e+089 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.63840098e+053 ... 1.63840098e+053\n",
+      "  1.63840098e+053 1.63840098e+053]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.63840098e+053 ...             inf\n",
+      "  1.85093259e+251 5.50830541e+165]\n",
+      " [2.00000000e+001 2.00000000e+001 1.63840098e+053 ... 1.85093259e+251\n",
+      "              inf 4.45302986e+203]\n",
+      " [2.00000000e+001 2.00000000e+001 1.63840098e+053 ... 5.50830541e+165\n",
+      "  4.45302986e+203 2.88230954e+234]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.64276957511902 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 100000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.63840010e+060 9.80000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [9.80000000e+001 1.31072012e+101 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.63840010e+060 ... 1.63840010e+060\n",
+      "  1.63840010e+060 1.63840010e+060]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.63840010e+060 ...             inf\n",
+      "  1.85093045e+284 5.50829654e+187]\n",
+      " [2.00000000e+001 2.00000000e+001 1.63840010e+060 ... 1.85093045e+284\n",
+      "              inf 4.45302287e+230]\n",
+      " [2.00000000e+001 2.00000000e+001 1.63840010e+060 ... 5.50829654e+187\n",
+      "  4.45302287e+230 2.88230434e+265]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.8443398475647 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.63840001e+067 9.80000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [9.80000000e+001 1.31072001e+113 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.63840001e+067 ... 1.63840001e+067\n",
+      "  1.63840001e+067 1.63840001e+067]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.63840001e+067 ...             inf\n",
+      "              inf 5.50829566e+209]\n",
+      " [2.00000000e+001 2.00000000e+001 1.63840001e+067 ...             inf\n",
+      "              inf 4.45302217e+257]\n",
+      " [2.00000000e+001 2.00000000e+001 1.63840001e+067 ... 5.50829566e+209\n",
+      "  4.45302217e+257 2.88230382e+296]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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qWQvRRmn179Q6lM6bS7epdwLfeWPhfSFLm5uUyF3ooYvgtl+q+IvmRe5GG0Ne3z04+xjy3Pu565M6z7KMP34/R9eNkUpL0VP3Vd9R0U6tOk2xppGF5QYfa28JD1J7O9Q0sqil7zxHFlx1SoqEN1wNhmKJrK3faCwIISZ2fhpSG2P5LOJ6POqK653CZ1Gag5d08fJZ9NV5Cp9FTnbuONQn1muv7FvPzxeWoM/iZ5lbzzaW5rPYnrcWn8XOGwtCSB46OAkh7tBYEEJM0FhMTFs6sfceD57k6vOWZ0mrbtPFeq71fQvxPhJx2n3q/dzfENm541CfnF4W6LNomMJRFTrwSs6yGpymW4ZEKKbQKRWBqKXvgLyu8Tmp8rFZlYPTM/RV8sL3ldUl5dYib8ovpiUsGGL5wo4RJk7Jj8tSunmHTsPjVNiy7ZxcnW06ptraplMMHZyEJPCemq0NGouGKW6keO5oObcGLH6Eqenit9gy19Qk59OIz6mhX9ugsSCEmKCxaJjiqdM210+d24cxoiG51OUxsEZDcjrM7djs0u9jjCQYDZkARkPyMBoyjF2Jhix+8xsvb3b4HxgnGlIqS51TQzSk9DrWa65oSE6/XIQk1HmoHm2RDus5uTrHjIZ0gdOQhqmmIVZZNT0ZY11q0K3WaUiKUKfr96T3D8mV1wSNBSHExOKnIUtj7PDYWI7IqcJ6NfpHulCacpZejzElit8Ly/bKPnPddHASsmJWlcHp8cTLhZS8kpFSYapQVi6U1SfxyJtcQlGb/qWwnFdotyS/LWyYat8QPVLHlnsp1xdWHXP3j9e9G7IzIwuvoelcIayah9Zb4hBlDaHK3DQlpC2qMGY0xPKZof03VP9Vhk6HdHwujOUdOi0tJGuz/t5hMCvWsF1sSELGyilIPbXbdO2SFOdByrimyOllDe+m2s/QKSFkNnZmGgL4TyHmmBrknny1T1FCSiOLOalVt7aRxZisysFJCJmGnfFZAMOdRKW5r4fPojRntswzrX4EL4dvqm8sI6A+6d6WuXab/yHnM+ni9OxKWEfJd2O9/rE/yJruHcqx6MA8C0KICU5DCCHu0FgQQkzQWPTEKwvRE2sGZY2kshDn1CNV3na8RLq2gcaCEGJi5x2c3rkSY6UMD8WS9gzUs0NTirbISw35LrX03dBM5RA6OEmR8IarwVAskbX1G40FIcQEjQUhxASNRU9q8NzHLD0aEv6fUw+LDnPr6UHXNuy8g5MQkocOTkKIOzQWhBATNBY9qdEvsHSfRQ16M4MzD30WDoTJRLXF3vsma81JDf3YZR/NpcCkrAKpfSK96ouZ88ZpexrGT+1tIlb4V8OTMr5Wc0dIwn6z7p0xpV5Ts/iRhefmJaU0Y25+82a9bZvflNKRuflNnpReY29+Yx1ZLN5YEEL6w2kIIcQdGouJafO2e/lUxpjT5urzlmeJOrTpYj3X+r6FNl9L3DexH6TkF+kiO3cc+376ytupDXuH1jGFzyIus+hlLR8D63w8PHeIz6KrbtbynM9iKrpeM6vPYvt+SZ6HUSz6LETkAQAfAnBWVd/XlN0D4A8AfL857U9U9anmvU8CuB3AGwD+UFWfLilBnwUh8+D984UPAvgbAA9H5Z9R1b8MC0TkagC3AHgvgF8C8M8i8quq+oZFmT4sbWTBaMh80ZCUboyG2H8KoOizUNVnALxqrO8IgEdV9XVV/Q6AlwBcY9aGEFItQ3wWd4rIxwCcAPBHqvoagCsBPBucc6opGw2Pp2cu+7J03KV+oP2pn3JM5eRNOd8uPY1TbSrp5zniiXVI6dpFt7HoKjc8v0t/5kZtHglkfY3FfQD+DIA2/z8N4Pe7VCAiRwEcBYBLcVlPNZY3DYnLcrSlj09pSKZ2cFoMdMpIhO+lPP1W3YZSmgbFBjenT18HZ/yZVB19225KyhKRqwB8cevgzL3XODehqn/evPc0gHtU9Stt9dPBScg8eDs434KIXKGqZ5rDjwB4vnn9JIDPichfYePgPADguT4ypmaKcKRlGjLU8ebt4CzpNpZDNXec0yemy1N5Cgdnm64pvfvIzh2H+gxxcBaNhYg8AuAwgMtF5BSAuwEcFpGD2ExDTgL4BACo6gsi8hiAbwE4D+COMSMhhJDpKBoLVb01UfwPLed/CsCnhijVhaX5LLavx/JZeBP2TU1JWaXQacpnEZ83JbuQlLX4DE6vaEiqLu9oSFtZ21DaWj4GOa/83NGQVD1tjuS5oiBb1hwNqYaljSziMote1vIxmDoa0lU3azlHFhxZDHYIhnWUyr3rD9/vMrKYkj461KB3jpp1C+kysih93ovFG4stQ2PoOa+7Z6dbIge5J8DQm2cIXaMhpae4d9SkS1KWxxO2D9Y294kuWUYQHtMQLlEnhJjYqZ2yvJ1ZU/oGQpkpljJ8Bub3D7RRq25zTUO5UxYhxJ3F+yzGjIZ4yeobDWmrr8ZoyPY9S53Wcy31xPLb1mak6vDM4AyPU9mTqXNK8tvOyY2UvCJ5ITs1DSFkl5CLNs9yPX9+NBmchhBC3Fm8sfAIhYUp2GGqcClluEv9qbpSfxZ5U4b/4rBkqq9S/damY+n9Lrq1yU9dy1i25/0TH1vupbZrrOfPQ8+fN/VlqV0e7eQ0hJAVw2kIIcQdGgtCiImdNxZjz0+96h1KTq82n0jp81Nj9R1NpYul7+bUrc/nhrDzxoIQ4gMdnISsmNH34KyJMTM4vbLgLJmPodySPGtGn+fqTusQduh+FpY+b9OpLYMzLsvV3xVrlmuX6x/X2WWVcnjvlnRw/ZEh4sv1ez7q8iUu1e8tY6ol8pbl7GPtK+JBSd/w2uTKPeWn5PW9R2gsCCEmaCwIISbo4JyY3Hy9NM/vWr9HXXG9OR+Dp7wuPguLjiWfxFQ+C+tOXV11KfVXrE/KZ2F1cNJYELJjyEUXmVeqrird2zPRqpQM1FdWbpFYKfGnhkSgOKktt1gr9V5bnV7XrU1+6lqWFlz11SN1bLmXLNfY0pehrNTiM492cmRByI6y57LLcOHcudZzVjWyWBq5p+oYT1tP2p6AnvIsT8QuI66SXt4ji9wIJ37fMrLsKjs+vnDuXOvoqqs8GgtCiAlmcAZ1xN5ri2feWv+2zi6/X9HF6x/q7clWVmpPydy54Xm5OnPvd0nK6jrCsOg2lNIeoHFWZk6f8BqX7rv4vg0/k6qjb9t33mfhYUxK9XWR0XZzpMq76lUyQtabNVd/qjyuuy9tuvdNg7d80UrtSukQnzNl6DSWwdApIcSdOKxKB2fF0MHZTQ4dnHbZueNQn21YlQ5OQsho0Fj0ZIyn91Bq06cLtfRn28iv7XgN0GdByIp57df/ESe++ePlODhF5PsAfgTgB3PrMjGXg21eAzW3+ZdV9RcsJ1ZhLABARE6o6qG59ZgStnkd7Eqb6bMghJigsSCEmKjJWNw/twIzwDavg51oczU+C0JI3dQ0siCEVAyNBSHEBI0FIcQEjQUhxASNBSHExP8DA9BQFFxHCJQAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 65.09978866577148 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 10000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.63840000e+074 9.80000000e+001 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [9.80000000e+001 1.31072000e+125 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.63840000e+074 ... 1.63840000e+074\n",
+      "  1.63840000e+074 1.63840000e+074]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.63840000e+074 ...             inf\n",
+      "              inf 5.50829557e+231]\n",
+      " [2.00000000e+001 2.00000000e+001 1.63840000e+074 ...             inf\n",
+      "              inf 4.45302210e+284]\n",
+      " [2.00000000e+001 2.00000000e+001 1.63840000e+074 ... 5.50829557e+231\n",
+      "  4.45302210e+284             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 58.03263545036316 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-10, 'kernel_type': 'size'} is: \n",
+      "[[1.2800e-48 3.2000e-49 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [3.2000e-49 8.4000e-49 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-48 ... 1.2800e-48 1.2800e-48 1.2800e-48]\n",
+      " ...\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-48 ... 3.8208e-46 3.6704e-46 3.9040e-46]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-48 ... 3.6704e-46 3.5344e-46 3.7464e-46]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-48 ... 3.9040e-46 3.7464e-46 4.0352e-46]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f548227f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.773536920547485 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-09, 'kernel_type': 'size'} is: \n",
+      "[[1.2800e-43 3.2000e-44 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [3.2000e-44 8.4000e-44 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-43 ... 1.2800e-43 1.2800e-43 1.2800e-43]\n",
+      " ...\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-43 ... 3.8208e-41 3.6704e-41 3.9040e-41]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-43 ... 3.6704e-41 3.5344e-41 3.7464e-41]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-43 ... 3.9040e-41 3.7464e-41 4.0352e-41]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 58.01287293434143 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-08, 'kernel_type': 'size'} is: \n",
+      "[[1.2800e-38 3.2000e-39 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [3.2000e-39 8.4000e-39 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-38 ... 1.2800e-38 1.2800e-38 1.2800e-38]\n",
+      " ...\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-38 ... 3.8208e-36 3.6704e-36 3.9040e-36]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-38 ... 3.6704e-36 3.5344e-36 3.7464e-36]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-38 ... 3.9040e-36 3.7464e-36 4.0352e-36]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.70176148414612 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-07, 'kernel_type': 'size'} is: \n",
+      "[[1.2800e-33 3.2000e-34 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [3.2000e-34 8.4000e-34 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-33 ... 1.2800e-33 1.2800e-33 1.2800e-33]\n",
+      " ...\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-33 ... 3.8208e-31 3.6704e-31 3.9040e-31]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-33 ... 3.6704e-31 3.5344e-31 3.7464e-31]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-33 ... 3.9040e-31 3.7464e-31 4.0352e-31]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.94135403633118 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-06, 'kernel_type': 'size'} is: \n",
+      "[[1.2800e-28 3.2000e-29 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [3.2000e-29 8.4000e-29 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-28 ... 1.2800e-28 1.2800e-28 1.2800e-28]\n",
+      " ...\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-28 ... 3.8208e-26 3.6704e-26 3.9040e-26]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-28 ... 3.6704e-26 3.5344e-26 3.7464e-26]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-28 ... 3.9040e-26 3.7464e-26 4.0352e-26]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.789767026901245 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-05, 'kernel_type': 'size'} is: \n",
+      "[[1.2800e-23 3.2000e-24 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [3.2000e-24 8.4000e-24 0.0000e+00 ... 0.0000e+00 0.0000e+00 0.0000e+00]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-23 ... 1.2800e-23 1.2800e-23 1.2800e-23]\n",
+      " ...\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-23 ... 3.8208e-21 3.6704e-21 3.9040e-21]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-23 ... 3.6704e-21 3.5344e-21 3.7464e-21]\n",
+      " [0.0000e+00 0.0000e+00 1.2800e-23 ... 3.9040e-21 3.7464e-21 4.0352e-21]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.61936712265015 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 0.0001, 'kernel_type': 'size'} is: \n",
+      "[[1.28000001e-18 3.20000000e-19 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e-19 8.40000006e-19 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000001e-18 ... 1.28000001e-18\n",
+      "  1.28000001e-18 1.28000001e-18]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000001e-18 ... 3.82080003e-16\n",
+      "  3.67040003e-16 3.90400003e-16]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000001e-18 ... 3.67040003e-16\n",
+      "  3.53440002e-16 3.74640002e-16]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000001e-18 ... 3.90400003e-16\n",
+      "  3.74640002e-16 4.03520004e-16]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483e898>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.96211338043213 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 0.001, 'kernel_type': 'size'} is: \n",
+      "[[1.28000064e-13 3.20000000e-14 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e-14 8.40000640e-14 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000064e-13 ... 1.28000064e-13\n",
+      "  1.28000064e-13 1.28000064e-13]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000064e-13 ... 3.82080281e-11\n",
+      "  3.67040253e-11 3.90400269e-11]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000064e-13 ... 3.67040253e-11\n",
+      "  3.53440234e-11 3.74640247e-11]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000064e-13 ... 3.90400269e-11\n",
+      "  3.74640247e-11 4.03520357e-11]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.62517333030701 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 0.01, 'kernel_type': 'size'} is: \n",
+      "[[1.28006401e-08 3.20000000e-09 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e-09 8.40064008e-09 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28006401e-08 ... 1.28006401e-08\n",
+      "  1.28006401e-08 1.28006401e-08]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28006401e-08 ... 3.82108118e-06\n",
+      "  3.67065350e-06 3.90426926e-06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28006401e-08 ... 3.67065350e-06\n",
+      "  3.53463422e-06 3.74664731e-06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28006401e-08 ... 3.90426926e-06\n",
+      "  3.74664731e-06 4.03555669e-06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7c18>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.94821310043335 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 0.1, 'kernel_type': 'size'} is: \n",
+      "[[1.28646664e-03 3.20000000e-04 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e-04 8.46482289e-04 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28646664e-03 ... 1.28646664e-03\n",
+      "  1.28646664e-03 1.28646664e-03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28646664e-03 ... 3.84953417e-01\n",
+      "  3.69634115e-01 3.93151231e-01]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28646664e-03 ... 3.69634115e-01\n",
+      "  3.55843348e-01 3.77182597e-01]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28646664e-03 ... 3.93151231e-01\n",
+      "  3.77182597e-01 4.07217537e-01]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.78296089172363 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1.0, 'kernel_type': 'size'} is: \n",
+      "[[3.34080000e+05 3.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e+01 3.20176400e+06 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.34080000e+05 ... 3.34080000e+05\n",
+      "  3.34080000e+05 3.34080000e+05]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.34080000e+05 ... 5.16160355e+27\n",
+      "  5.46357805e+24 3.26107809e+15]\n",
+      " [0.00000000e+00 0.00000000e+00 3.34080000e+05 ... 5.46357805e+24\n",
+      "  1.10109031e+29 1.86543832e+19]\n",
+      " [0.00000000e+00 0.00000000e+00 3.34080000e+05 ... 3.26107809e+15\n",
+      "  1.86543832e+19 9.61121973e+22]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.76944637298584 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 10.0, 'kernel_type': 'size'} is: \n",
+      "[[1.70492562e+039 3.20000000e+006 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [3.20000000e+006 1.72223446e+061 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.70492562e+039 ... 1.70492562e+039\n",
+      "  1.70492562e+039 1.70492562e+039]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.70492562e+039 ... 2.74513232e+168\n",
+      "  4.12274966e+144 1.68528138e+104]\n",
+      " [0.00000000e+000 0.00000000e+000 1.70492562e+039 ... 4.12274966e+144\n",
+      "  4.44743315e+169 5.11864282e+121]\n",
+      " [0.00000000e+000 0.00000000e+000 1.70492562e+039 ... 1.68528138e+104\n",
+      "  5.11864282e+121 3.38030630e+136]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f548227f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.825385093688965 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 100.0, 'kernel_type': 'size'} is: \n",
+      "[[1.63905546e+074 3.20000000e+011 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [3.20000000e+011 1.63921939e+118 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63905546e+074 ... 1.63905546e+074\n",
+      "  1.63905546e+074 1.63905546e+074]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.63905546e+074 ...             inf\n",
+      "  3.66054850e+269 1.48501330e+197]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63905546e+074 ... 3.66054850e+269\n",
+      "              inf 4.45926038e+228]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63905546e+074 ... 1.48501330e+197\n",
+      "  4.45926038e+228 2.88692349e+255]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8160>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 58.11895203590393 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1000.0, 'kernel_type': 'size'} is: \n",
+      "[[1.63840655e+109 3.20000000e+016 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [3.20000000e+016 1.63840819e+175 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840655e+109 ... 1.63840655e+109\n",
+      "  1.63840655e+109 1.63840655e+109]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840655e+109 ...             inf\n",
+      "              inf 1.48312496e+290]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840655e+109 ...             inf\n",
+      "              nan             inf]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840655e+109 ... 1.48312496e+290\n",
+      "              inf             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 57.945194482803345 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 10000.0, 'kernel_type': 'size'} is: \n",
+      "[[1.63840007e+144 3.20000000e+021 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [3.20000000e+021 1.63840008e+232 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840007e+144 ... 1.63840007e+144\n",
+      "  1.63840007e+144 1.63840007e+144]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840007e+144 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840007e+144 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840007e+144 ...             nan\n",
+      "              nan             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 58.6168372631073 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 100000.0, 'kernel_type': 'size'} is: \n",
+      "[[1.6384e+179 3.2000e+026 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [3.2000e+026         inf 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+179 ... 1.6384e+179 1.6384e+179\n",
+      "  1.6384e+179]\n",
+      " ...\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+179 ...         nan         nan\n",
+      "          nan]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+179 ...         nan         nan\n",
+      "          nan]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+179 ...         nan         nan\n",
+      "          inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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6i2mIzWfXh2mIt3lDdNJ+uG33TshrMueGmg8kqV5TXXEfclNeD/0+VR6Z70O/nlcxqnXMTNwMANh7+juR5eUqguyb5tpL0Tl4OLItJqpS5mqSYCAcGWp2amtoubaKPCRZMPVhWf3HeUMyoGcOL/MZRZfNg+gk72LU+6b98qFcux/LJC6fR9G5PmzykNQJNnAyDGPFyI4s0m7EKqL+POd1j9HChqXaCCGNfGn6q4ihdeLzZHZw/Z4I/wT9Wlp5ZNKi6dYWQHSDk8pzGs3esdtZej1QSRcQAjQ23vv37Bnr50+3toDGWhCnTw9eVDKlAwCNjcdONW0YWWVRBj5E/bZBj5zNZGPUkhaxsggoIhiMen/SRi99c1eVqxVxI5PG5OSAjSKqrO4+LZMwm1D7I2+MzbTG3rnVt6N7/C3sPbMj1KeNyUnsOfFE7n5ebO/E3OrbASyF7Nf7Zn79XQCAhf0PxdYV14c6rbWXYGH/QyGjrkzqTMuXheSZ3XiPZWui4dWQiGtZrPpJqyFZI1mVuRpSNK5XQ5KweT9c4+tqCBs4GYaxgpUFwzBWsM0iQB3yZ8XGZdd2OFmmd2WWVYhQ3zSaQLfj5TBe77ciPB+ZHiOrLEwfqjwGTl0RmAxVUQZOE1KeopdOk+6dndoaaeDU7zMZOKNQ+0O2Oy62RJTsqhymtpjaJg2c+o+BjBoVZ9MytcMke5EGTlvm19+VysC554U/t67bxMgqC52iNw/ZRLJSy/iy0cvk5TggSzCyMF6LQG1rXu9UXXH2iYr3EJzXZe2eOtXLx5ECKXvoh0XxswjJ1toSPGjJz6J/rl+h5meRom/aB3+DmXP+KORn0X9+cK6/fSCoPw+8GlLg3hATPu4NSQvvDakWXg1hGGao8XJkETWKSDO6UMsWGYlZrU+S15mrCBmisJ2Pp5JbmYbkoRR375hpSNI9odGoRS6PvkyNZunu3sZRcQHu3rzrFPZfkrSYFJaL4WyUgVY/5+tQG+h9IdUvlymOhPzSVqGEkxy2pltbsNjeGTq32N01aIcoQ7bWFlCDQt6+meqROVMBQHSryXXqO0mjENNIwHbkkiZYiY1iiRuZpLFZFKEY4uSzbUse2QZWN4Jf96xLznFLp2n7S1cUSeezYhxVG56R5bn6aGnog98UOQ0pep290OF8iXKkhach2fu0il2nPA0pkbRf2jR+Fup8NuqXvuyNZDMTNy8FrinQQarKjWSz530S3fdO9J6R8CupLnGWtZFsZuLm2G3c85fciYXffG3gfBUbyebXfhpi2Tno7DvQ76ssG8nmzr8Vu49/q19+xdTFnOuUYZhi8XIaYkLfhZlEkp9F1ulC3M5R9XrZ05E8Hpxx9VXpDFb4NCQnNvLoTmBVGV/T2IfS1FFrPwv272e8wYMf2irxdmQRN4KIihmRZuSQd2+FnCd2T50KZQPPW39WmYClObiK9FqMsok0JicBIDKbeVXI/pRzbr0dRXiuzq/9NBYO/lVsmblV27D76CP9Y1w5AOgcO1Z5n0n7TRGRutjAWQFF7nUoCpMcSbL5KHtZMol33k0uc/Jk6JhUzgmOfuCHbhrCMIwbeGSRER5ZFEsV/dk9mZw3pBv4LHRNvguGcqNEbUYWPrs1M36QNxT+qFObkUWVW7dN7tdVr9IkBdcBwrLpQVWqXuo1oW4ZV2XXNwFWJZv6vupLoovdXZhbcwc6r78ekrcq2ebW3AFaPoX2/pdz1aMbj889x94pqzbKokp8GMWo3oE2q0ayvIsvYRT6iodKlPIok6SoW7tf+3rpMkShPjtPX+h9/vbJV633htRGWVS9VOlaYdjkl1DljBpZuCRqZAG4UWpxe4miRhZV4cPIojY2C4ZhyqU2ymIglqLcdWfIf5kLovAOQvU5RT8rhubaS3tyqH868lyjiebaS+3uqZDO1VeCxsaN8SHV8zQ2Xknf0sTEwP/yDwAO3LYh9D+AyvrwwG0bcPSvx3rPj+gzG9rX/sfQ/xs2vGl9b32mIbo3m3RcKdqBRQhAdML/l/GcBDoHDydvE+8u7UrtHDwcPucBzed/iW7Elmx1q3aaZMF50Ld66/9f/s0X0dGXTCvqz8u/+SLoO1No51yybf3gF6H/X3xxpf29uZ48oix2d4VsAGnCtxeFycCpb4tW5YwycLqQXaLOnVU5Z8ZvcmbglHP62amtsQZOPTBw2fhg4KzNNKRq9p7Z0f8Cps1/URYmOZJkU9vhEl/6U36Z4lZq5PWkMnWDlQXDMFawsmAYxgpWFhmZGb+pP892Oe9XMcmRJJvaDpf40p/SFpFkk5id2lq53cI13hs4bd1qq3b3VnGxGcvUH6LdjuynqPSILjeSmWSV58owaCZ9RvRnD8gQF/i3ZPoh/HOsvpjaM5KpAFx7VDL+k/sz4jJQlBAAusXXmaJNPA1hGMaK2igLH/Y6MH6TNmM6E6Y2yoJhmHJJVBZE9CgRHSGinyrnVhLRIhG9GBwvCM4TEX2ViPYR0U+I6Kq8Ak43buRRA1MI1HS7F2bYsTFwPgbgawC+rZzbDuAZIcQDRLQ9+P9/A5gHsCH4uxbAN4JjrVDdqEW7bcw+VoUMEqlMqdUa8H6UW9mjonurWdGqRm2D7u6tt6OIH4zGihWJ8qju3nEemmp09yooK+dNmlyniSMLIcT3Aehb024A8Hjw+nEAH1XOf1v0+BcA5xPRxbbCDBOi3R5I8+earDE4fZC/iv7snjiRXCb48icpge6pU5UpCl/IarNYI4R4NXj9WwBrgteXAjiolDsUnGMYZsjJbeAUvSxFqRegiWgbET1HRM+dRf5IyVX7WVCr1R/Cy6NrTHIkyaa2wyVV9Ofek3+bWEYmXZLHuHJJZepGVmXxmpxeBMcjwfnDANYq5S4Lzg0ghHhECHGNEOKaMUyYijAM4xFW6QuJ6HIA/1cI8Z+C/78E4Khi4FwphPgsEf0hgDsBXI+eYfOrQohNSfWnSYxsS1JiZP2aTP2XZLhKcheOiiWpPiPuPlUemXbQFE08D9PNzf1gQbPnfRIAsOetRyPLq0Y/oBfhqvn8LyPbYqKqkZ9MKyhRUxDOrdqGzrFjhclkkw4xCyZ/kCJSFZooNH0hEe0A8CEAFxLRIQD3AngAwJNEdCuAlwHI1j2NnqLYB+AEgE+klt4RtoatIp5RdNnUKD8Q3ffSG/0aP/x5ZIQr13SOH890LdOzjrxRaH19PMg/bCJRWQghorYADgwFAvvFp/IKxTCMf7i3bDlCHy6bhvt5SEoCpPo4mJDymHZAFrnDdrG9M/T/7NTWgSXMfuId7Zm6P0Tc1nK1P2S700bEMiVGGsj1YRiuz625A91jxwYSB8npVdw0NQ41w9ncmjsALIW/0/tm/oq7AQALLz0YW2ea7fnzV9yNhZceDG2Vl9NFCnxKpDyzV92LPT++z7puE+zuXSDDsvN1WORk/MLKwFk2Phg44wyTUfWa6oqrJ+pe04hGHekUbuAsMfaHawNnEjbvh2tMfViWrIUaOOtKVOCVPG+K7r4c54mYNA1Ry6nHouXUiZuG6Pg4DTEhpyH68/JOQ/RnAPWehvDIQvulSXpG2g+UyTZiKhNlKyljZJEWPfkzjY1DnD2T2J8qlUUx05YdVRvGdHNzaKWBRxbpRhZss2AYxoqRnYbo6Bb/LKshSb/6aX4dykysozpl2cqiHn0mrl36agiTDlYWAfpQOwtJX6Y0U4gyP9RpvQHTTENckzgNYTIzsjaLImMCqHUW5aeRR44kQnIGXyD5pbKSu6Ao13ntP0WTVh5pxNRtIX1kMmchohM7y/tkguWI6N1G+1CaiN+N5oBPTU9Ee5uFt8oiTjlELU+mUQZZv2y2I5Aqf3XjlgNNKwjy/yoNaUmYloz163llmz3vk7F7YIClKVrSVK0/ShHCicEZKOa9YgMnwzCFw8oiI4vdXd4Z/kxyJMmmtsMlVfRn0qgCWJqOJdl1FjtPlrYT1FdYWTAMY0VtlIWLeWOZqfayEJcOMO4eH+T3pT+lLSJp5WS6uXnkVldqoyyqhqchxeJLf/I0JBpWFgzDWMHKgmEYK9iDsw5EOfyYrke9ZrLhog8bbjKr1UZZVLkb08XOT53Zqa2JcTr7cgqxtI05cMLzwag5t2pbPy6mPv9XPUurMiTqjljqcxc7T2Luyu3ovPjr/v8AKouXOXfldrQvWgH6p3/LV8+qbaEgxssuuOxq23trMw1x/eVlmLpTG2XBMEy5sLJgGMaK2tgsqsSHKY+a4Mdmw50sn7SRrErUubOOajuoKg6FbjfR/9/9ywdKlyEK9dl5+kLv8/eOHSoui/qwULU33dzq2zG3+vb+a6cQAURGOeZW3z64AiL/D+5xLj96MSxlHEt5LJrZ3/t8shxXbg8d48rNXbnd3WqIgxWR2owsqvam6x5/y/jaCYFF3iRH9/hbYYu99tq57AFdJa2g+rpI9vzrFxLLiFcOh45J5ZxkD7OJX1EC3sSzeFu8GRmsNo7MAW2UYCNxQXSjAvrqAXT1ZzeWLYM4cxaifTaVItOD0cio2DIitmi3sdjdZVw6jYoBMd24sZ/xO+oeKX/r0ksg3nm3V/bkqVAiHSv5DYF1qNlEY8UKdE/0UiXKbOaplk6FQCOIWG2ze1Rl9vc+P6Aoppub0Vp3GRb2P4TZ5bcAALonT6ZeOpXtndnUi5y994f39tq25o5+ZG3JB6//Iv7x6c/Gyjp30W3oHHsLi+2d/Ujfe8/sMC6dnvrD/4Jnn/qTgTrm130GC698BTOb7uvL069fWzpdvnIt3n3zoNXwyBtlERX8xhR5yiYwSpnBb2wo265R1hzeVdAeG5z3aUSEsCr6zBQVK3ekMSL8QDyDt7tHrZRFbWwWDMOUS22UhWvLPuM/o7alvGhqY+CsEmkzAHo2gMbkZKLrdRkySKSibExOhpZUgSW38KgYnFG2jCpQ2yD7U2bU0ttRxI9Ba91lifLIOb0+t9eZW7UNANApyRg7IFsBUcpN0xYisl469V5Z+GIj0FH9FtQUeE4Ilu/0L5g8F/pwacuouv+FK1TZTe0ogoX9DyWWkQoiTlGo10dptMLTkBzP8yGyE4Ce0U2I6EhZ+tKp/D+4x7n8qKY/5apHkhw2MvTldbFAoL6HFVIbZcEwTLl4u3SqMwyJkW2WcH1IjKzWMTNxMwDE+lMMZCSbmIA4fXrkEyPb5CHJgq+Jkb23WZSFzZcyD0lOU6px0YSUxzQsLjKehq4k5lZtgzh5EgDQPX06JLf+TN0Q2Y+ZYUDtD9nutLaJgexphkRAJge4uSu3Q7xyeGCPiTRiZk3aoyoK6R4u93DMLr8Fe959vH/9I9fdDwD43rOfi61zdmqrtQv5R667H9979nN9YyuAvnEWq1f1/v/FXwAAPvDxB/HPf3+3Vb1R8Mgi4lqWX8ikkUXUvSYlpSqvMkcWReN6ZJGEzfvhGh5ZeEaUMTBvWkNJUiSrpJGFLmdRI4vp5ubYe40jiwh3dR9HFibkyEJ/XpaRxex5n+zJrk0/eGRRET6MLGyfkdfF1gebRVrYZlEtvo4seDWEYRgrWFkwDGPFyNosdHSLfxmOQWmGkj5EspL4kCnMljgbRlURt+oKjywC1KhXWSNHGV1/ZWSqiEhW/TIR8pTBdGtL//X8JXdi/pI7Y8urEazm1tyBKz//5ehoVo5zkcgIVv1IVto19f3Ii03krUzISFjqnwd4ObIw/apGBZmJwxSoRn2GSueNo6FjXJ0Dy6OtLVhs7wz9cvXLKAa1yLoNRuYkOWyRwXNUmRfbO/uvF37zNQDxRuDO66+Hjuu+9DY6wUrJAI4N5jI4TeQ1S/lsHK72/OsXyjE4O4qElQSPLBiGscLLkUUVFOnBqf5SS3zx4Nx7ZkeqtrAHZ4+0btyj4GdR25FFVhfeJBa7u0JzflcGs9kVf4yZiZsxM3Fz4jZpqz5wYGuYX/vpfhuSkPEoy0Q6XEVeN9goqjL6zmy6Dx+8/otWfRXH/LrPhP6fWmWfvnDonLJs7RZJTllZv+Q2Ltt56s8rRxJJoxIruRvNQubVuWNI6kTEyIw8r12zkcdk95pubQFEt3dSfY4SFDrSSCm6gBCgsfHev2fPGIsZHeBaW0BjLQiT/Ugq/0AeGhs3bhZpToY1AAAJy0lEQVRM45TlrbKIUwpWAXult17BQVZNyXNDyXtTfPCKQo50TNMheV1eU8uGzpc0EisKW9fuqlH7sCrUqN95GUkPzoGhuBLgpVCC+vpLrEL0j85WAkQXEN3oJEPyV08pK18PTZKhAvpWhuuPlSNtkiG1bytCdAVEl4PfMAzjKfVZDan4V333kYcB9Ibvu4887NYzMGi7lEllQDYtxJ7aDpeoCXn05DxFoSfcMcoRrGYk5TWV1530myM/jNooC1/n2gxTOI68ZBOnIUT0KBEdIaKfKuf+jIgOE9ELwd/1yrU/JaJ9RPQrIpotS3CdqjX8zPhNfUNTFct6NpjkSJJNbYdLquhPm4TLMqhvUnDf2eW3WAUALgWPA/Y+BmDOcP7LQoiNwd/TAEBE7wewBcDvBvd8nYgqcWwfGFkomcILJahv75kdPWs0Uf/obF9EsH/AZB3fe2ZHeNlO3WsQ3FOEVT0vqhxGeQroW5vpjXSkUh2qosrtefdxJ/s2aGy8v9RaJYnKQgjxfQBvWtZ3A4CdQojTQoj9APYB2JRDPoZhPCHPasidRPSTYJpyQXDuUgAHlTKHgnOlMzANKXnp1PgcV0un3U680Uu9ppb1dMOSEQ/8gYw46EPRPgvRPlv5c7Mqi28AuALARgCvAvjLtBUQ0TYieo6InjuLiB2MKah6GjK//i7Mr78LIOofXU9D5tffNXBpfv1dsdOQfjscM3/F3Zi/4u7+6wEq6lu5h0Me48p95Lr73UxDWmOg1ljlz82kLIQQrwkhOkKILoC/wdJU4zCAtUrRy4JzpjoeEUJcI4S4ZgwTWcQIMUpp5JhsfPD6L7oWYajJpCyI6GLl348BkCslTwHYQkQTRLQewAYAP8wnoq1Q1fqXLex/qJ870yaHZhWY5EiSTW2HSxZeehALLz3Yf10G//j0ZxPLyF2hSbtDv/fs5xLL1I1EPwsi2gHgQwAuJKJDAO4F8CEi2ghAADgA4DYAEEL8jIieBPBzAG0AnxJCDNHEmGGYKBKVhRDCtOj9rZjy9wOIn/CVQNWbeRjGGQ72owA12hvCNguGKZf6uHvr25ddLJ26IumXRt91anufT/i6dOpo16kLvBlZ2MSo0K+bAvKq5/Ogh7Gryp18urk5dpRklCPJx0PbPOaFgqsLLvpQDTNQId6MLNLGxByIStVohs+1tixFKMrgOBOKhq0qLX1dXfFZAJDbSScpwItJgSa5/qrXo157jyfh8HWcuF2fc07lzwQ8GlkwDOM39VEW+i96WS7NQX39XZLdTv/oyn1anD0DcfZM5K5TNa6jLCtfD82u0wL6du6i2xLLyAjlcZHK5fXZqa2RMTPLpHviBLonTlT+XG+mIcOEPiUS7bZzGaQcUbYVU9ImeY8r9KzmwJJcZdiIOsfeipencSNAFD6qqFPail37p1tbQM1mLuU0YAujBs6lldbRvWszsuDgN0wS7IszSBrzrPfKwnYlwnVYOMZ/fJhu+Uaa8ZH3yoJhGD+ojbLgaQiThA8RwXwjzTTE2yRDOmkzqCdlJNOvNS9chd1HHu7n0IjKYh7rKGZIhKMalZqrVhojcKv3qfJ03jhq9DfJqxjVxDjzaz8NAFg4+FeR5efW3IHdr329H8PywG0bcPk3XzSGqTMZLYHqlLme70ON0j135fZQlvW8SYtmNt1nFTE8LWp6TElZ9pY0SYaGczVEzTImX8elqEuqCwAtmwod8cbRgRRwmSzgytb5ft0xZUJlj76Z/bmxIi3VJ5YlO/jQ8qnQ8dz/dgT0nbi2uHMjb1+0IvYa7StuMH36wnKco6jppwPa0CmLgRFGXtfl4L72ywdDR2OdSc8wXVf8A0J1R5Qxli149Kcul3b2HUgs397/cuh4/scm0Dbl1wSch+qjf/q3+GsF9uXEM9HPyoML3w0bhm4a4mtiZB1fEyMnETWNUKGx8UI+0IUnRm40B/dMCLHkH6GPPrWRY9Y+nRm/aWlzl/KcfrLj9tnBMHiBnKIrANHtu3BHOVuZZJuZuBk0Pma+R45Wg+fQ+Dj2nvzbwWKjmOuUYZhy8XZkkTaLOogGspuXmUVdBrltv3IIrXWXof3KoV4Bh1nUW2svGQiRN7/+LrQP/iYyi3pr7SUAlqY9rlaVZJDehZcexPwVdw+E1isii/p1/+NLePapP4kt85Hr7sf3nv1c/xhXDgDon/+9+izqEzcDAPae/k7uuupv4DQw8EGiBiA6S8eiCIZ38ks53dqChf0PLVmwHUQRpLFWSCaVhf0PYeacPxooK1/32+HYqU1VDsYYnAXEWE1SFEC6GJwAQn1bFTRefWRvoM7TkJI3ksmNROh2+kdnG8lOn4Y4fdq4+Wl2aiuEYoyUZeXrfjsco8phlKeivp1btS10jCs3t2pbqG+rwtVGsvoqC4ZhCoWVBcMwVtRGWVQdsHfPiSew58QT/dc+YJIjSTa1HS7xpT93H30kdIwrl1SmbtRGWVQdCzFxju2AKJtF0j0+yF9Ff86v+0ximbQ2i1GiPqshFS/50fJlvRenTvVenzpV6fPDwlBYJvXS8mWAaoRTXceJQu1wCa1YYXxdJAuvfCW50OpV4WNSuePH8wmVhYqz70lqM7LgvCFMEjOb7nMtwlBTm5FF1dMQuXt0unEjdh952K2fQtB2047WAdm0tABqO1yi7mA17WYtApsdort/8RehY1I5J/3GGckYhvGZ2iiLAZuFns+jKIL6Zjfeg9mN9wCNZv/oKrcFjY2DxsZ7cmjMbrxnIFeI/F/eY7qvamavuhezV93bfz1ARX37gY8/GDrGlfvAxx90kjeExsdB4w6e6+veEJ2yg98Y95sk1GuDWk/UvaZkSvou2yKD35RJUf1WFjbvh2tM9re8+2Ki4F2nGVCX7bIu3SUpszT1lrmcqX4Y586/FXPn32oli+ybP/jw//FiudWEXNI0LW0WvdRpsxRbJ+pj4MyJ7hCUyXCVENEqjbPRnhNPlGc8U5bedh//lpUs6tFn4hyldh99pNA+tVqKrRE8smAYxgoeWRSJyf5jEz+z4uxWpS69ZY2FWhVV93UWHDldJeGnVEmolvG8qx7BKoZcEQitDugrHEnPMFyn1lj/L2rVYSDkWiBHWSs66vNmNt2X6KykrlLMXnUvur/dYF6xkHXLflP/KkKuUsg//Zr6fuTlmk8Mxg8pgsb4GGishcb4WP+1D3ixGkJErwN4D8AbrmWpmAvBbR4FfG7zfxBCXGRT0AtlAQBE9JztEk5d4DaPBnVp83BOQxiGqRxWFgzDWOGTshitSCI9uM2jQS3a7I3NgmEYv/FpZMEwjMewsmAYxgpWFgzDWMHKgmEYK1hZMAxjxf8HCWKFgP85DBYAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 58.35140919685364 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1000000.0, 'kernel_type': 'size'} is: \n",
+      "[[1.6384e+214 3.2000e+031 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [3.2000e+031         inf 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+214 ... 1.6384e+214 1.6384e+214\n",
+      "  1.6384e+214]\n",
+      " ...\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+214 ...         nan         nan\n",
+      "          nan]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+214 ...         nan         nan\n",
+      "          nan]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+214 ...         nan         nan\n",
+      "          nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 58.882431507110596 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 10000000.0, 'kernel_type': 'size'} is: \n",
+      "[[1.6384e+249 3.2000e+036 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [3.2000e+036         inf 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+249 ... 1.6384e+249 1.6384e+249\n",
+      "  1.6384e+249]\n",
+      " ...\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+249 ...         nan         nan\n",
+      "          nan]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+249 ...         nan         nan\n",
+      "          nan]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+249 ...         nan         nan\n",
+      "          nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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NKwuGYYwY22lI0Sej6ZCw7idvXUNTI7lb7Uo22q3CQDdE0iZAaZsDSecK54fozAGiP/ggX6fVHrz2eyvvVUQfEAK0avXg45untMW0U+jOHGhVB2JpKf6FwWrwSJ5wmh0vZj4NaYSBswi62P5K1yFobAxJ9oa0vBK2bRZZ8gHBjyOlrGm9Vcimu37SfF/Xt1WwsPxAJfWEmNosqr5uFjyyUOrPWiBkeoOp+3rori8v7srrrahLYcxM7ojt4Zp0LdXwqWtziLzwLWx3lrFXRefZMemH7oZd6L/6Bxw6tXeoT1sTEzj4+v2VGBK7G3YBWEnZHzMKb9oNADhw5I7UepL6UCfb7KbdOHDkjmiTZmCQ6n9mcgfo9LVD8sxsvQUHH/lcrI48I4uxVRZZ56p6Qprc0DolleTGc+ENyYNrb0gW6kjSR9gbwjDMSMPKgmEYI1hZBMghvnV5MvLU61McQywsuzPnlXwyaf9HX2UeFcbWZlG1gVO1Jfhq4MyyebCBsxhs4LSED8qiSL0yaesy8shYVo4s8hhIE2VqtSO3nanruQqDnUl/mhiz5fLy8TxypbnB1bpM1plk3Qt5/md52sFxFgaoN4rp2pCs+tRjpmtDdPLUsTYkz3eT5J7dfFOp+opi8v1wtJB0ThfyXUSuxNiHhPsgb11FlWudnhO2WTAMY4SX05Ck4WyeqYhOM1e1PFs33ciydVRN3qmEaawHh3sH1zLYyyOSqdUei3Dvxo8sqh6WFRlmumShv99r+XzFRFEAfv/vq4ZtFrw2RCt3knwArw2JycVrQ+xR5zQkyStS16pT36YhpvA0hFedZjG2IwsV0zgLU7J2DCsbZ1EXrYkJa3EWRakrzqKwPMsP1B5noaNz/rm54izK0nibBcMw1eDlNESHugozCxdBWfL5ukcFVQc22fbmyNc0xYc+HZKBCAu9fVb6LI99KE8djZ6GFPnH2LBYj4pVfFTk9JVx7j9vRxZZocMyRUYOZcOlw3lif3FRGxlo86aSZVKjF9Vjqk2kNTEBAIm7mdsiLSs3YC+PR3f9TsyfvMeoHAD0XnllpBVIo0cWviAboXzJxK2TI0s2n2V3gXjjjUrLNQk2cDIMYwQri4LI+4t481RMGFmkTcnq3CclDz7IAAD9IGZhqr0ts1xfF9/QYBqjLEZ53sgwo0BjbBY2E9nqwq9tB1CpwTtJ+TRC2cKl9/I5wI3LNETeTjDNaG1LNrkPVZfoQn8/uhuvR+/FF4fktSVbd+P1oNMnsXzk6JBMeVENyWecds54bYxsGx9GMXJ0YJKilI+F5V1HiMqkeT9k2W3Jqvah+nn+hbtqlyGJqq6t9vlrbzxvvDEyT0MYhjGiMcqCYZh6aYyyiFmvw1V34WtVEEVLtGPXqfpaKcxuvmmQZbszB7TawzIFRMdabcxuvmmQDq/VXimftBLSElddfium13wI02s+FDsnH59e8yErfTt92odjn8M/ANjyqTuHPgOw1odbPnUnLp3/xOD6CX1mwvuv/PzQ54v/es342SxiyUrCyNSqI1SFAERv+HMd18ngwFO3Z8/jg2Xkct4D13YKmQd/eHOiPIeW/id6n7Rsu2rUpd6H3vgGgJU+e/yzH8fUvyvyVrBU34THP/vxgSxL5f5/h7//yaHPDz+6ZGyzaIyysMlCf/+Qd0H1NNiUA1gxcKrLonXH5HM6L4ltkpICq2VsGTh1YeeqsRXA0LJwm7i0zTVmGmKbQ6f2Rjd33v0v6kInh5rDQXfeB/l9kAFI99Co5UzLNgVWFgzDGMHKgmEYI1hZFGR69fZovu963h+ik2N69fbUea7cDpf4IANgbouYmdzhzG7hCu8NnKZhtbbDvWVcLIJSZQg/6/op7ZjLBVxJbXBFWh8CSE/8WzNT7W0AtYa8L6UzjRFhHZ05hq5TjuBk6sZloighAPSrrzNHk3gawjCMEY1RFq6HsAzTdBqjLBiGqZdMZUFE9xLRCSJ6TDp2FhEtENETweuZwXEioi8T0ZNE9CgRXVRWwKnWtTxqYBgPMDFwfg3AfwL4unRsD4DDQojbiGhP8PlfAcwCuDD4ey+ArwSvjUIO9xbLy9rdx2zIEJIU7g3Ew6jVfBbyrmi2kduQFu4N2JlmJoV765Czu9ugrr1iiai6fBZCiB8AeFk5fA2A+4L39wH4gHT862LATwC8lYjOMRVmlOAcnNXigwzAyo8/Szn1FxetKQpfKGqz2CiEeD54/3sAG4P3bwfwnFTuWHCMYZgRp7SBUwx2KcrtgCainUT0EBE99CbKZ0m2HWdBnU40hC+70W9V6OSgTie1b+R2uMQHGQBEmy5l3U+tiYmo7LhQVFm8EE4vgtcTwfHjAM6Xyp0XHIshhLhHCHGJEOKSVVhTUAyGYWxhtH0hEb0DwP8KIf4q+PxFACclA+dZQoh/IaJ/AHAjgKsxMGx+WQhxaVb9eTZGNiVrY2T1XGtiItquHkg2XBUJsZVzIGQZz2R5+ouLQxtCq/XZQpX7qstvxYM/vFlb1nTLybpI236wu34neq+8Yl2mvEy1tw2yiwfZ32KJnSokz/aFJq7TvQB+DOAviegYEX0UwG0ApojoCQBXBZ8B4HsAngbwJICvAri+gPxOCJVDnYarpHp1PzCfjGeqLK2f/cZbd3bv1VcBDH5waqrF8Jz3yNnXPNiLOCRzoiiESFoOGBsKBPaLG8oKxTCMf3i7i7pK1dMQtS7dcD+r3jTUTYB015djHNTrZrW3riH0zOSOmEs46VpqbISuzSFyLErY7rzZsXQbI5n0Q3fj9ei/8kosa1g49UybpprS3TgYRIf7e6h9M7v5JgCD3KlpJPWhTrbZzTfhwFO3Dy2VD6fStG7dkDwzF30aB3/xb7E68kxDxlZZZJ2rau5tckPrlJSsvFzbLPLg2maRhbrLmI+ou9zVKWelNguGYRiAlQXDMIawsgiQsyTVZenPM0T3ydugylJ0gxsbxDabMjzHZMPKgmEYI1hZBIRP94X+/toMSkn16kYRPhnfVFnk3cJ8Iy2Aqc7gpnGAlUWAy2lI2bJ1o5uG+CSfTDjV0AVl8TSkHGPrOi16s5s+8ev+MdU18jCSu6Is16WzU1dM0T6dam/T90e4mbMQyRs7h98LN1hO2DtVa9fSZPxOpNUe2vN2RcQGxFmkKYekmIg8yqDwjaH4wKuuvwi6eAz5nCxPVtCXq+lPVvyIrfgSeV1G2rQlGqUI4dWUMS8cZ8EwTOWwsiiIbAj15cmikyNLtjoNunnwQQZgxQiaZQxd6O0bO4MpKwuGYYxojLKw/WSSvSa+eAZMty5Uz/sgvw8yAMPelKxy4+ZdaYyysA1PQ6rFBxkAnoakwcqCYRgjWFkwDGOEHymVmXIkBfwEDA3x5bIZ32MMGKM+bIyysJkUxocENDOTO4ZyYyYFZIXBV1Ha+iAIzweDYnf9zigvpjr/l5PV2jIkqoFY8nUXevvQ3bIHvSeejj4DsJYjs7tlD5bftg70o18OyZS7HiWh8dozz7vY9LuNURY2f7yuFQWAoWzbScpLPhaWN03bZ4OkLNzA8A9hobfPzvaFyo9P/Tz/+G1wRVXXVvv8z68cq277QiaO6x9ZSJb71iSdoGtMXJA2RxZZx127TMPru5CBlQXDMEY0ZhpiEx+mIUB2lus0OX2YhgBm825X0xDdcdexFS6v35iRhe1hWXfDLnQ37IreOyWwyOvkiB0jWrHgEw21wyVhKn3XdLfsMS7X3bKHvSGjiG2N23/1D9r3Tggs8jo5Ysdk670Q7mUP6EvbCrpEPKvdmje5nAcpHmzhjbJQh8VZeSNk450uV0NZ0tyj6j4e6uY1pa5ruL9lYdepdA5Y2ejHxZSkCa5TW/3mg+vU++Q3uh3Ckn4U6rE0yiS/MaFuu0ZdN6ntpD15cN6nCRnCbCXlUbNilc40RoSfigfxWv9lo7lUY2wWDMPUS2OUhQ+WfYZpMt7YLEaJhf7+aDPa/uIiWhMTQ/YDWzKEhNOwmckdQ5GdAGLH1AjO0JZhW/5QhhCd7DJWXKf9/bE5fRLd9TsBAD1LhtkqDPi6aQsRGUdweq8sfLERqMjh0/JO3E4I3He6H1vsmLKQTA0Dd0WaorCJiaKQy41TAhyehpS4njeZslIWh8UyYQmxYqQTgjNlKZj+T6N+88BBYIvGKAuGYerFW9epStWbDKnnTK9RxF2VFZad5CKWZcqqo07Ua06f9mGIpaVcC9SspQ+Q9v0AEI+bkO53X8L2VdQYozrlbMQmQyp170iWFteRVG8aatCU7vqycdF0E6C8cuSlu34nxBtvDORaWhpcK8G4pholdW0OkY3AYbvz2ilUBZC1EVBId8seiGePx2xL7TPPxPzJeyr5UYZh4uFS8pnTP4KDf7ovOn/V5bcCAB784c2p9cxM7oj6XUbXzqsuvxUP/vDmyNgKDGwp3fU7gQ3rB59/+wUAwGXX3Y4ff+umWB2sLJB/ZGEa1FVmZGFSRlUWPows8uB6ZJFFWnCfL/g6shhbm4XOsFfGyJaWTyLrWlnb9ql1lJIzh/W+6rwJZY2pqjxVyeaLkTeCKIjYpJX3HjC2ykJNgS9r8yI3TtoS8fBaeZ5q6lOlqq0H8vjrw3T3an9Mn/bhYtcuue2Amn5f15a0H1bSOV+2Q4gQYtC2wHPlell8yNgqC4Zh8sHKwgO8GgIb4rvMrtPfNRHvIzhtoQ7x6/gx5Bnq+pLJCojLfeiNbziSJJu0HcVsZdxqKjyyCJCzXlWaOUoKr06qV6dEfMheFaJmsdryqTuTCzvOHJWW6SrKbCVnC/ORVnvlNXzvAV4qi6zAJVNCY6VsYEx6svReOhm9hu+Nr9OZi10zQnJNJ9WrkymvDGVJe+L2Xnxx6PMFX3w4ubxjV3yYnEY3Dek98fRKuLsHIQOJhDkr+r2h/BWu8VJZMAzjH2Nrsygawakb4SwsPxArJ0czJkWQqqnudPLoYivyjrLylNdGcCbYLHQRnEnI/VFnBKfOZhFGcKo2i3A5epngp7Bvq4zgHIqzSGhnWGfZCM48NH5kUbX/3Ct/vCFGMvs8h/eYUbwfijJy4d6mXoK8a0NMMUniW6b+snJkkTXKMJK71a5kLl06h6RKQo7MxOPKuaKjtanOHCD6gxPydULjZL+XbKgUfUAI0KrVg49vntIW09rxOnOgVR0IzVqSSPkH8lCnEyVnHi7WgLUhaUrBKGFvuMKw4iSrugzQQxmoC9x4ZZnqzGmnQkllgcHUSf6ejXUIZTBdNGabPH3vI2O5NiQWgCMleKmUoL7IxSpE9OrMwh481Yw2GRJ96SnYH51NhizuVm5arrtlz0pfjgGNURYMw9RLc5SF5af6/Im7MX/i7ui9U4K26+SYP3F3alo9uR0umX/hLtciAFjxZpiUm3/8Nr/jNSqmMcrC17k2wzSFTGVBRPcS0Qkiekw69hkiOk5EjwR/V0vnPkFETxLR74hopi7BVWzH/E+v3o7p1duj9z6gk2N69fZURSq3wyU+yAAM4iNMy5mWbQomI4uvAehqjt8phNga/H0PAIjo3QDmALwn+M5dRGQluD32g5B2Cq+UoL5Dp/YOXFFE0auzWIXALadzjcWOyesNWu2VdjgmUwZLfSsHUmWVO/in+7xau1E3mcpCCPEDAC8b1ncNgAeEEEtCiCMAngRwaQn5GIbxhDI2ixuJ6NFgmnJmcOztAJ6TyhwLjtVObBpSs+tUex1Xxq6MAKmhvpEXJ3m0SCkTXw2Jo9SHJSmqLL4CYDOArQCeB/ClvBUQ0U4ieoiIHnoTmgi0nNiehsxu2o3ZTbsBoujV9TRkdtPu2KnZTbuH+0aZhkTtcMzs5ox1C5b6NlzDYVLuqstv5WlIFkKIF4QQPSFEH8BXsTLVOA7gfKnoecExXR33CCEuEUJcsgpriogxBGdFYph6KaQsiOgc6eMHAYSeku8CmCOiNUS0CcCFAH5WTkRToex6gQ8cuQMHjtwRvfcBnRxZssntcMmBp253LQKA7FWhcjnTsk0hc4k6Ee0FcAWAs4noGIBPA7iCiLYCEACeAfAxABBC/JqI9gH4DYBlADcIIcZnUscwDSZTWQghdA7w/04pfysAs4lfhYzyYh6GGQUaE8HJNguGqZfGZMpBbXotAAAFmklEQVSKLV924Tp1RZ6Vj3LZUVox6avrdJT6sCTejCxMclSo59UcDFVuQ+cqZXyh/S4yfkhpC8mYkoxRH3ozssibEzOWlarVjscThBmKCgTOJCoq1a8up20HSgfpFEnwEmZZSqxTaotcNut7XuFpPMNI9WFJvBlZMAzjN81RFuoTva6Q5qC+aLVmvxe9ugr9DfM2Jq06VcuG5cWbp0Zn1amlvk3LUK6Wm5nckZgzs4l4Mw0ZJdQpkVhedi6DbsuApLLyMReyRzKEeVLDz463FpxqXTtIwx+8xuwR8pTWcmj/VGcO1G4PKafcCY9VWxi1cAaddbHp9xujLGwmv/FhH1LVZqPaeORzcnn5s/M2yImPq8g6Xlae/v5BYmDpNVEey676KuKIdPYwInrY9PveKwvTm6TI9oZFcf0j08mQNrJIK+8S30cWMXnGfGTRHJsFwzC14v3IwhSehvA0pLQ8PA1JxdtNhlTy3txZO5Kp59pnr8f8ibujPTSSdjEvMvQL/0ndDbsyM2nL8vReOqmNN7GdnLi78fqh7NtbPnUnHv/sx7Vl1alFiC2Zu1v2JGbo7m7ZE+2yDhSLabFBuHGRvCFUXTR/kyF5vlg2yU2QtIbWTg4+rp2M3scS2hS5hrR0PqrX5GtrJ+tL4JMTOn1Y7jP+7kRK4dZKv8l/llh+27r0c9Ra+fMUarej1/C9D/jbYwks9PcPP7nKhi4H4c/LRwfZAJePPhe9j6XKK3INKT4gqldBN2JaPvqcN2HZy0eODn1+6wefSx7l9Xsr/Sb/WYJ+9EsA+rB5+tEvV+JhPE6HJ8fB+BTHMXLKgvGAvvupK2MfVhYMwxjhrYEz7y7qIIrtbl7nLuphktvlZ4+hc8F5WH722KCAw13UZzftjqXIU4+pu6h3zj8XwMoUydXObrObb0pNrWdrF/WrLr/VKF1emNiXfvyrkU68lMfA2RzXqXojUQsQvZXXqggMY+EPcKozhwNH7oh+hJVey1SkVZ0hmWTUY2HZ8H3UDsdu1MwcnJYMknlycALA9GkfrlMcr2juNKTmhWThQiL0e9Grs4VkS0uRTCrqMbG0FJUXS0sr7XBMpgyW+ra7fqdxue76nVFfjgPNVRYMw1QKKwuGYYxojLKwHX578PX7cfD1+6P3PqCT4+Dr96faI+R2uMQHGQBg/uQ9xuVMyzaFxigL24FL8lzfhzk/kGyzSPNwjIzNwhJ5bRbjRHO8IZZdfnT62sGbxcXB+8VFq9cfFoaGZZJPqceU8HW5HS6hdclh2lbZsD5fuVdfrU8Wz2jMyIL3DWGYemnMyML2NCRcPTrVuhbzJ+52G6cQtF23ojV2TFnrIrfDJfKqVpfM//YLucq57jebNGZkwTBMvTRGWcRsFup+HlUR1Dez9RbMbL0FaLWjV1d7W1CnE8mkoh6jTicqT53OSjscM3PRp9MLWOrby64z2839sutux2XX3R715Tjg7doQlbqT3yRlmEqr14S8yWrUTFY+JL/JQ1X9VheyfL7IpBKugwntcHWuiWl+8psakN2gdbnx8tTriysRiMvy/is/70iSbNLcmePm6qwaVhYBcoBVXQFCSfXqnsa+BCkBcVkOf/+TjiTJJi1QatyCqKqGlQXDMEaMj3XGFQb5J32dOxciIX+INzjOZ2pEuBzfszyhfkljimwZL+v1CLwYoUdgyDugejgKXENOuJrH6xB5WApet0pUT0X/9xcmlqV2e6Xf5D9LpHkzLrvu9igJrk+JcFVaq1dFr+F7H/DCG0JELwL4M4CXXMtimbPBbR4HfG7zXwgh3mZS0AtlAQBE9JCpC6cpcJvHg6a0eTSnIQzDWIeVBcMwRvikLMbRCc5tHg8a0WZvbBYMw/iNTyMLhmE8hpUFwzBGsLJgGMYIVhYMwxjByoJhGCP+H9DDe+QNsmmeAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 59.124603033065796 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 100000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 3.2e+41 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [3.2e+41     inf 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     inf     inf     inf]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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XmpBGySxty2s2dP211taZv69YX6lOEJwyJ6J7x9Ja/Mtchc1fKial8VjdUw/M5PsBL+usqV4QvCK0xsJqxaZxpWTh2MUqT0fyfcBqJaWstBSCQhycgiDYIrQ9C5VouCL6VKXx2PIeJ5jI94PkwcqrWO3UC4JXhNZYWG5JN24FV1vQ9Xvqgol8P7DaKi5byYWgCJWxUNOjuzPbimY2jPR2b8aOE89Lz0IQfEZ8FoIg2CKU6yx6uzcjO3BKqyxJXwgUJ0aW9IX1RdIXOkfSFwqCIBgIRc/CTt6Q3u7NAIBs/4Dt5d63ffY72LPvW7jts98BoKXQU+w48XytaldsE3D+rRk0N971DADg/73yjYA1EfxkTqzgLIVd7OZU3TlVupHhts2oke73J2iPEF2iYyzcBNtV/gK1hduHgL1GH0WUiI2W+xkEwYj4LARBsIUYC0EQbBGZYQilm7SDMfs+ARUFSpWUrz1Slt02o8bM0mjqLfhHTcaCiI4BGAOQA5Bl5h4iagfwDwA+BeAYgLuZufZUYC3ztPLMWdu3qDUNqmyadhaazw3GsHZRYujqxqBVEEJOPYYhtzDzasP0yyMA9jLz1QD26r8LghBxvBiG3AngZv34ZwBeB/DNmqWec945SR86V1Ty0EjNathtM2p0vC3R1YXq1GosGMBuImIAP2HmFwB0MfNpvf4TAF01tgEAIH3pNYbsGw21rLiwrNqHYYhqK2pMLG8OWgUh5NRqLG5k5gEiWgRgDxF9aKxkZtYNSRlEdD+A+wGgu7sb7VhVoyqCIHhJTcaCmQf08iwRvQLgBgBniGgJM58moiUATD2Sei/kBUBb7g2LXeBu8lqoHBmqzPuQWrCQlyNizPtDNIdPgn+4NhZE1Awgxsxj+vF6AN8B8GsAXwbwfb38l3ooSov1nXUOpk7VTk5VNh29UO3yuqDaihpnP1+X0aIwh6mlZ9EF4BUiUnJ+ycw7iehNANuJ6D4AxwHcXbuagiAEjWtjwcxHAVxvcv48gHVO5VlmUT/8sSN5GzofQGpktFACQC6Xc6pWudyuvwYv6yxE2U4eHMDMqmWFCFYpBw7YWrjxrmcKm7/Uvo6Zpa1F6yU63h5Fbl4DkqdGcPHTHQBmhxv5libERicLi7E69v1Bu+kFX9QHAFy/aQsWfqDtpZlp1j6K40viaD6dQ3Jc28czfFUKbYczSH0wgB2nfuSpPms3PovJzhgSE1r8iabB2UV8M82EscuB9gOaC26yU1t1sHTXWez84ElP9QKAq556DjOLp7F4dxItR7S/u9Odzatf/VuMHmxHyyqthz01nUTz1V2SvlAQhPoSmngWnWdvLOpZlGUg0zN15QYHbcez2HDdY9h54LvYcN1j2onB2W99r7J6qbZ2HviuJ/K9Yt1Nmr5733gsYE0EP5mT8SxcBeNVgXZVQN8K2c3qio/BfeuJBAIWrIiMsbBKZ2iGiltZSG847P0qRT9THdYTSYsoWBEZY5GfcB7lSgXjVaUfPYtCAOCIQQPRXB8i+EdojIXVoivpWXiL9CwEK2Q2RBAEW4SmZ2FFbnjY0fUbOh9AXl9noXot7MM6i3xE11nEPzjii95GZJ2FfcKwziI0U6cLD30GecNS7rKp04X3AwByQ0O2p057r3wIO478YDahkGEYsvO8N6uPVFteJQHyitvXPA4A2LX/2wFrIviJk6nTUBiL0oxk61MbEe/SxtBq7UWpgTDm51D5QVRuEaD2vCBKZmlbXmOVv+PGu56R3B5C3ZgT6yyscnwY83N4kRfETL4fWOXvkPweQlCIg1MQBFuEt2dhlRDImMzHiyRCJvL9wCrZjyQDEoJCehaCINgitD0Lqzwhxvwchbwg6p46YCbfD6zyd0h+DyEoQmssrPKEGPNzFI7VPXXAVL4PWOXvkPweQlDIMEQQBFuIsRAEwRbhHYZYJBUyJvMpHLtIRORIvg9YJfuRZEBCUITXWDQkq1ZzU6r82OIeJ5jK94GcvufEbb0geEVojQVPVF9PQBdGyo6t7nGCmXw/SJ6q3pZVvSB4RWiNRay1BQCKNpcZya7oLDtW99QDM/l+oHaHuq0XBK8QB6cgCLYIVc9ifWojAGB3Zhtub73X9Jre7s3YceL5ojSBhfSELlIcVsJMvh9YpRGUNINCUEjPQhAEW4SqZ2GEEhaqNTWWHVve4wQT+X6Qb6m+ZN2qXhC8IrTGQnaduqsXBK8IrbGQjWTu6gXBK8RnIQiCLUIZg7O3ezOyA6e0Sl0/YwxOY8TuWGsL8iOjiLW2IHdhdrn3ntz2qm2qALUquc7MqmVIXJwuRO2O7zswu9bD0NbOwZ/YeiYVfds4bDBG3+54exQTy5sBaDMcZz/fpZ3/xX4AQO4/XoPkwQHwsk7QwGAhrwd/cAR0zZWeBda9ftMWzDutRUFPDc9oejcnClG3AeBsTwKL+rLgBDDRGS/cmx7MYd7750Bj5aH/xtZeVggJqJ7baSzRtRuf1e5fHENyjJEcZ8w0U6F+5NZJNO9LF93DcWCqg9H2IZBZQFi6a3YX8+l1izC1CLjsVe3vu/t3jzvSR/Hk+3fgpVf/tPB7ronRfDKGxlu1z9b5QwuRb9Xe5R9docWUXdI0giuazmH7sT/G8JF29H7ubQDA759cjXR/eXhIs/ivn/rFkzh621Zcte2vCudaVl3A6MF25FNaZHKerw3Nly4Zwm/WP1Umw0kMzlD2LOo5BSoIQn0IRc+ip6eH299bBZ6ZLpwrSwVwzaMAgNzBw7ZTAdz0hafxxr8+jJu+8DQAIH3YkEXdo1wPqq03/vVhT+R7xfWbtgAAfv+jBwPWRPCTORHduxSacD4jkTqfKSrdyHDbZtRQQw9BqEQohyGCIISPyPQseHra+qISYheni0o3Mty2GTWUM1MQKiE9C0EQbBGZngUlnQe24aZkURlzIcNtm1FDJSYWhEpE5hPCaef7MzILG4vKphHv93iotqLG+JK49UXCJU1kjIW72ZCpotKf2RD/9pHUk2aZDREsEJ+FIAi2iEzPItfZph30D9i+Z3hlc1HZls3XXa9KbUaNsz2R+SgIARGZT0h8cBgA4GQTettH40WlkuElqq2osaivjtv7hTlJZIwFiKyvKYHjVFS6keG2zajB0fkkCAERmY+Im9wd022pojJ+wfv8H6qtqGHcPSoIZoiDUxAEW4ixEATBFpEZhtCk892cDcOZotKNDLdtRo30oKyzEKoTGmMR7+pEtsq0aH7Yedq+xPGzRWX+ovczFaqtqDHvfclHIlQnNMbCCjc7Rnlysrj0YdepaitqmIXCEwQj4rMQBMEWYiwEQbCFGAtBEGxhaSyIaCsRnSWiA4Zz7US0h4gO6eUC/TwR0Q+J6DARvUtEa+wqIhG9BSHc2OlZ/BTAhpJzjwDYy8xXA9ir/w4AvQCu1n/uB/Dj+qgJxDs7EO/scHRPbmV3ocyt7C7IcCrHaZuq3SgxtvYyjK29LGg1hBBjORvCzG8Q0adKTt8J4Gb9+GcAXgfwTf38z1nLL7CPiNqIaAkzn65VUR4vT7xiReLcWFHpRobbNqOGSgAkCJVw67PoMhiATwB06cfLAJw0XNevnxMEIeLUvM6CmZmIHGcqIqL7oQ1V0N3djYVW1zfraemGhqpfaCDbMb+oTEx7H8FatRU1VEpBQaiE257FGSJaAgB6qZYtDgBYYbhuuX6uDGZ+gZl7mLmns7PTpRqCIPiFrfSFus/iVWa+Tv/9GQDnmfn7RPQIgHZmfpiI/hOATQDuALAWwA+Z+QYr+aWJkdenNiJ2he6cPHgYQHk6Q2OaQJWmUKU4BGpPT6hklrblNVZpBK/ftEVSDAp1o67pC4noZWjOzA4i6gfwOIDvA9hORPcBOA7gbv3y16AZisMAJgD8pWPtFcPVp1Kbjo+VH1vc4wRT+T6w8IPqAX+t6gXBK+zMhnypQtU6k2sZwFdrVUoQhPAR2o1kVkmFjMl81LGbRERO5PuBVbIfSQYkBIUs9xYEwRah/ZqyykBmzPyljt1kLXMi3w+sMoNJ5jAhKEJrLKyyhxkzf3mRccxMvh9YZQaTzGFCUITWWPBM9QVUNDlTdmx1jxPM5PtBcrx6/g6rekHwCvFZCIJgi9D2LNCqL5s+Yx7Tcmr5/PLj1vottTaV7wPDV1XPO2JVLwheEV5jMVJ9IVRj/1j5scU9TjCV7wNth6tHB7eqFwSvCKWxoMaUZTRv6j9dduwmArgT+X6Q+qB64merekHwClt7Q7ymp6eH299bBZ6Zjb5duhek98qHAADZj4+X1VVi3S3fw95//xusu+V7AICGExcKdTuO/KBWtSu2CQB7//1vPJHvFWs3PgsA+O22rwesieAnTvaGiINTEARbhHIYYoabBVdT7Q1FZfKc94urVFtRY2KxfG8I1YmMsYCLwDWJiVxR6UaG2zajRnIs+OGoEG4iYywo6/yfMDGVKyrdyHDbZtRIjouxEKoTGWPBCed7IrKN8aIy6UKG2zajxkwzBa2CEHJkoCoIgi3EWAiCYIvIDEMyKxYAABKH7N8zuLqhqOyaWVB3vSq1GTVGbo1m9nfBPyJjLFKfaEuunbgP2z/MFpVKhpeotqJG8z491cI9weohhBcZhgiCYAsxFoIg2EKMhSAItoiMzwLkfB0Ax6iodCPDbZtRg6O5PETwkcgYi7yLcPyZllhR2exDSH/VVtSY6pAVnEJ1ImMs4hcuAgCczDW0nMgUlUqGl6i2okbbh0FrIISdUBiLj/Z/jNF8H26LfbGsrrd7MwCAW5xn+Z5uSRSVDY3er4FQbUWNzIJoDp8E/wjFJ3vlmssLRqGUHSeeBwDc3nqvY7nz+/qLyvyo9+ssVFtRY+ku81ingqCI5gBbEATfEWMhCIItQjEMsQMt7dIODtofSoyvXlZUpg8P1V2vSm1GjdPrFgWtghByQmMs8iOj1evTzvNlTLXFi8pGFzLcthk1psRWCBaExlhYETuhheN3tJHst2eKSgzVL1WAVZtR47JXdWP9rWD1EMKL+CwEQbBFKPKGtFA7r6V1hXwg61MbEV++BICWJwQozyNizM+h8oOo3CJA7XlBlMzStrzGKn/H2o3PSm4PoW44yRsS2mEIN1X3L2TakmXHVvc4wUy+H0x2Vu/sWdULgleE1lhgpvrC7vhUvvzY4h4nmMr3gcRE9Z6eVb0geEV4jUWyumq5xlj5scU9TjCV7wPZdPVl11b1guAVoTUWNFl9Q1ZqeKbs2OoeJ5jJ94Omweq9GKt6QfAKGQALgmALMRaCINgitMMQqwxkxsxf6thN1jIn8v3AKjOYZA4TgiK0xiLfmq5aP744WXZsdY8TzOT7wdjltdULgleEylisT20EAOzObCsssCqdDO3t3owdJ55H67Gpwjl1HD9fv3gVZvL9oP1A9alRq3pB8ArxWQiCYItQ9SyMyApOd/WC4BXyyRMEwRah6lnszmwDoPkluEJ8CxWT0xjrUh3zydN108VMvh9YxcKUWJlCUIRi12lPTw+3v7cKPDNdOFe6y/RP7tF2Y87bvq+srhKXvfg0jn/lYVz24tMAgKV7Z6dAf/Mrb3ZuqraOf+VhT+R7xZPv3wEAePTa1wLWRPCTObHrtJT5R7WcH05MW+dvEsBX9BLA/KPeR/dWbeErnjdVV1569U8BAI9eG7AiQmgRn4UgCLYQYyEIgi0iMwzJJzV/g5PFzrlUcalkeEnO+5jAnpBrCt53JYQby54FEW0lorNEdMBw7gkiGiCid/SfOwx1jxLRYSI6SES310vRxOgUEqPOVlKm9e3c6cE80oP5ggyncpy2mY7gNvLmkzE0n5SOplAZOz2LnwL4EYCfl5zfwsxFgS6J6NMA7gFwLYClAP4PEa1kZidBuU2ZXNECAGh43/49g9fHi8rEREutathuM2o03joYtApCyLH8KmHmNwBcsCnvTgC/YuYMM38M4DCAG2rQTxCEkFCLz2ITEf0FgD4AX2fmIQDLAOwzXNOvn6uZ5Mi09UUlNJ/iotKNDLdtRo3zhxZqB73B6iGEF7eD1B8DuBLAagCnATzrVAAR3U9EfUTUNzho3QXmhhi4wZm6Kl5lNk3Ipqkgw6kcp21GMU5mvnUG+Vb/wgcK0cPVfw0zn2F/uigSAAAE9ElEQVTmHDPnAbyI2aHGAIAVhkuX6+fMZLzAzD3M3NPZ2elGDUEQfMTVMISIljCz2ohxFwA1U/JrAL8kouegOTivBvC7mrUEMN2i7fxsdHDPxGIuKpUML1FtRY0/usLUpgtCAUtjQUQvA7gZQAcR9QN4HMDNRLQa2urrYwAeAABmfp+ItgP4A7S4NV+tx0yIIAjBY2ksmPlLJqdfqnL9dwF8txalzMgnnfsBco1cVLqR4bbNqLGkyfuk0UK0ic4KzoTzf3RuzBWV+ToG9LVqM2pc0XQuaBWEkBMZY9Ew4jw1YeOpZFHZ4MPUqWoramw/9scAZNepUJlQGIuP9n+M0Xwfbot9sayut3szACC5osOx3PQnXFQmR72fGlRtRY3hI+1BqyCEnFAYi5VrLi8YhVJUZKzP/RdtZbmTYP9D1+aLyvSgk7kUd6i2okbv594OWgUh5MjOIUEQbBGKnoUdWt7U1gE48Vxc9fIUsEkvAST7z3ugmUmbALDJ86bqyu+fXK0d/FOwegjhJTLGgicmHN+TODdWVLqR4bbNqJHu9/7dCNFGhiGCINgiNMYiXyH0vyAI4SA0xkIQhHAjxkIQBFuEIslQC7XzWlpXSB60PrURuH4lAID7tA2tpYmFeu59DgDQt/Vr6Ln3OfRt/RrW3/DtQv3u3z1ek05KZmlbXnPVU1pbh79p3tZVTz1XsU4QnDInkgzlmrVl05W6PpkFVHas7qkHZvL9YGZx9SXpVvWC4BWhNBbxrk7ET2hhPyutq1i0f7LsuOGE3VCh1pjJ94PFu3WD9+Uq9RXqBMFLQmksAIBHq69XSJ4aKTu2uscJZvL9oOXIeE31guAV4uAUBMEWoXBw2smifuutTwIA4q/vt51F/bpvbMGBZx7Edd/YAgBY9NZscqF/+7dHa1W7YpsAcOCZBz2R7xWf+oX2fo/9N2/eixBO5oSDs5ShlVpewI7X7d+TXne2qBwa8z4wsGorahy9bat+JMZCMCcyxqLjnYuO78n+cyewQS8BdLzrXIarNgFgg+dN1ZWrtv0VAODo1wNWRAgt4rMQBMEWYiwEQbBFZIYh0ws0n0WDg3vGl1JROf9kqt5qVWwzarSsqt8aFWFuEhlj0TCUcXxPaa5TNzLcthk1Rg/qMTj/LFg9hPASGWPBcW3E5OR7O58oLpUML8lH5o0Wk09FM3ao4B/isxAEwRaR+R5Umc+d9CxyTVRUepk9vbTNqMHznedlES4tpGchCIItItOzmElrqjqZz5hq56JSyfAS1VbUWLpkKGgVhJATir0hZsFvMrd+BgDQsKsPQPlekVVPaHswDj7xIFY9sQUHn3gQn+99qlD/f3d8syadlMzStrxm9at/CwB458/+e8X6SnWC4JQ5sTfEaprTOEXpxdSomXw/sJrCHD3YLtObQiCE1lhYLcIyLn5Sx+qeemAm3w+sFkfJ4ikhKMTBKQiCLULbs6Bc9a5/LFt+bHWPE8zk+8HUdPU4olb1guAVoTUW+WT1Tk+2icuOre5xgpl8P1gwr3oaQat6QfCKUMyGENEggHEA54LWxWc6IM98KRDmZ76MmW1FhQqFsQAAIuqzO4UzV5BnvjSYK88sDk5BEGwhxkIQBFuEyVi8ELQCASDPfGkwJ545ND4LQRDCTZh6FoIghBgxFoIg2EKMhSAIthBjIQiCLcRYCIJgi/8PEN4DzAIXl/EAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 59.494457483291626 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 3.2e+46 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [3.2e+46     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     inf     inf     inf]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7fd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 59.01058530807495 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 10000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 3.2e+51 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [3.2e+51     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     inf     inf     inf]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.42774248123169 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-10, 'kernel_type': 'branching'} is: \n",
+      "[[1.28000000e+02 3.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e+01 8.40000001e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000000e+02 ... 1.28000000e+02\n",
+      "  1.28000000e+02 1.28000000e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000000e+02 ... 3.82080003e+04\n",
+      "  3.67040003e+04 3.90400004e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000000e+02 ... 3.67040003e+04\n",
+      "  3.53440003e+04 3.74640004e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000000e+02 ... 3.90400004e+04\n",
+      "  3.74640004e+04 4.03520007e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483ec88>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.00105285644531 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-09, 'kernel_type': 'branching'} is: \n",
+      "[[1.28000002e+02 3.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e+01 8.40000008e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000002e+02 ... 1.28000002e+02\n",
+      "  1.28000002e+02 1.28000002e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000002e+02 ... 3.82080030e+04\n",
+      "  3.67040031e+04 3.90400036e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000002e+02 ... 3.67040031e+04\n",
+      "  3.53440034e+04 3.74640041e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000002e+02 ... 3.90400036e+04\n",
+      "  3.74640041e+04 4.03520074e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.5651638507843 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-08, 'kernel_type': 'branching'} is: \n",
+      "[[1.28000017e+02 3.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e+01 8.40000085e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000017e+02 ... 1.28000017e+02\n",
+      "  1.28000017e+02 1.28000017e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000017e+02 ... 3.82080305e+04\n",
+      "  3.67040310e+04 3.90400358e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000017e+02 ... 3.67040310e+04\n",
+      "  3.53440337e+04 3.74640409e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000017e+02 ... 3.90400358e+04\n",
+      "  3.74640409e+04 4.03520745e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.10879063606262 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-07, 'kernel_type': 'branching'} is: \n",
+      "[[1.28000166e+02 3.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e+01 8.40000848e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000166e+02 ... 1.28000166e+02\n",
+      "  1.28000166e+02 1.28000166e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000166e+02 ... 3.82083050e+04\n",
+      "  3.67043097e+04 3.90403579e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000166e+02 ... 3.67043097e+04\n",
+      "  3.53443367e+04 3.74644090e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000166e+02 ... 3.90403579e+04\n",
+      "  3.74644090e+04 4.03527448e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8160>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.4424262046814 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-06, 'kernel_type': 'branching'} is: \n",
+      "[[1.28001664e+02 3.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e+01 8.40008480e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28001664e+02 ... 1.28001664e+02\n",
+      "  1.28001664e+02 1.28001664e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28001664e+02 ... 3.82110498e+04\n",
+      "  3.67070972e+04 3.90435793e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28001664e+02 ... 3.67070972e+04\n",
+      "  3.53473677e+04 3.74680901e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28001664e+02 ... 3.90435793e+04\n",
+      "  3.74680901e+04 4.03594484e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.33870196342468 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1e-05, 'kernel_type': 'branching'} is: \n",
+      "[[1.28016641e+02 3.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e+01 8.40084805e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28016641e+02 ... 1.28016641e+02\n",
+      "  1.28016641e+02 1.28016641e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28016641e+02 ... 3.82385225e+04\n",
+      "  3.67349958e+04 3.90758028e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28016641e+02 ... 3.67349958e+04\n",
+      "  3.53777052e+04 3.75049172e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28016641e+02 ... 3.90758028e+04\n",
+      "  3.75049172e+04 4.04265428e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8160>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.53222298622131 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 0.0001, 'kernel_type': 'branching'} is: \n",
+      "[[1.28166513e+02 3.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e+01 8.40848547e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28166513e+02 ... 1.28166513e+02\n",
+      "  1.28166513e+02 1.28166513e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28166513e+02 ... 3.85157151e+04\n",
+      "  3.70163699e+04 3.93990184e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28166513e+02 ... 3.70163699e+04\n",
+      "  3.56838759e+04 3.78748292e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28166513e+02 ... 3.93990184e+04\n",
+      "  3.78748292e+04 4.11033515e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8908>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.36703968048096 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 0.001, 'kernel_type': 'branching'} is: \n",
+      "[[1.29675307e+02 3.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e+01 8.48534972e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.29675307e+02 ... 1.29675307e+02\n",
+      "  1.29675307e+02 1.29675307e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.29675307e+02 ... 4.15495523e+04\n",
+      "  4.00833560e+04 4.27307767e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.29675307e+02 ... 4.00833560e+04\n",
+      "  3.90439684e+04 4.17422755e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.29675307e+02 ... 4.27307767e+04\n",
+      "  4.17422755e+04 4.84883326e+04]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ad7978>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.49422454833984 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 0.01, 'kernel_type': 'branching'} is: \n",
+      "[[1.45809808e+02 3.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e+01 9.30532023e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.45809808e+02 ... 1.45809808e+02\n",
+      "  1.45809808e+02 1.45809808e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.45809808e+02 ... 1.21791734e+05\n",
+      "  1.17992345e+05 8.76521581e+04]\n",
+      " [0.00000000e+00 0.00000000e+00 1.45809808e+02 ... 1.17992345e+05\n",
+      "  1.33241683e+05 1.02292362e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 1.45809808e+02 ... 8.76521581e+04\n",
+      "  1.02292362e+05 2.26975495e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f548227f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.357586145401 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 0.1, 'kernel_type': 'branching'} is: \n",
+      "[[4.59679334e+02 3.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e+01 2.59982750e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 4.59679334e+02 ... 4.59679334e+02\n",
+      "  4.59679334e+02 4.59679334e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 4.59679334e+02 ... 7.75315899e+09\n",
+      "  3.72331130e+09 6.25268196e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 4.59679334e+02 ... 3.72331130e+09\n",
+      "  2.27529538e+10 3.62728156e+07]\n",
+      " [0.00000000e+00 0.00000000e+00 4.59679334e+02 ... 6.25268196e+06\n",
+      "  3.62728156e+07 2.71377499e+09]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.51404285430908 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1.0, 'kernel_type': 'branching'} is: \n",
+      "[[3.34080000e+05 3.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e+01 3.20176400e+06 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.34080000e+05 ... 3.34080000e+05\n",
+      "  3.34080000e+05 3.34080000e+05]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.34080000e+05 ... 5.16160355e+27\n",
+      "  5.46357805e+24 3.26107809e+15]\n",
+      " [0.00000000e+00 0.00000000e+00 3.34080000e+05 ... 5.46357805e+24\n",
+      "  1.10109031e+29 1.86543832e+19]\n",
+      " [0.00000000e+00 0.00000000e+00 3.34080000e+05 ... 3.26107809e+15\n",
+      "  1.86543832e+19 9.61121973e+22]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.34250092506409 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 10.0, 'kernel_type': 'branching'} is: \n",
+      "[[2.40970359e+11 3.20000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [3.20000000e+01 3.08944831e+16 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.40970359e+11 ... 2.40970359e+11\n",
+      "  2.40970359e+11 2.40970359e+11]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.40970359e+11 ... 1.14793551e+63\n",
+      "  1.40790022e+53 5.78580366e+33]\n",
+      " [0.00000000e+00 0.00000000e+00 2.40970359e+11 ... 1.40790022e+53\n",
+      "  2.05801984e+64 1.72100340e+42]\n",
+      " [0.00000000e+00 0.00000000e+00 2.40970359e+11 ... 5.78580366e+33\n",
+      "  1.72100340e+42 1.35784126e+49]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.73621249198914 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 100.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.70501001e+018 3.20000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [3.20000000e+001 1.74815019e+028 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.70501001e+018 ... 1.70501001e+018\n",
+      "  1.70501001e+018 1.70501001e+018]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.70501001e+018 ... 2.74569802e+103\n",
+      "  4.18836088e+085 1.71064349e+055]\n",
+      " [0.00000000e+000 0.00000000e+000 1.70501001e+018 ... 4.18836088e+085\n",
+      "  4.44789216e+104 5.11961396e+068]\n",
+      " [0.00000000e+000 0.00000000e+000 1.70501001e+018 ... 1.71064349e+055\n",
+      "  5.11961396e+068 3.38109850e+079]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.23182082176208 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.64496426e+025 3.20000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [3.20000000e+001 1.64908161e+040 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.64496426e+025 ... 1.64496426e+025\n",
+      "  1.64496426e+025 1.64496426e+025]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.64496426e+025 ... 2.37767944e+144\n",
+      "  3.70621807e+118 1.50453482e+077]\n",
+      " [0.00000000e+000 0.00000000e+000 1.64496426e+025 ... 3.70621807e+118\n",
+      "  3.80904131e+145 4.51577997e+095]\n",
+      " [0.00000000e+000 0.00000000e+000 1.64496426e+025 ... 1.50453482e+077\n",
+      "  4.51577997e+095 2.92882187e+110]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.57425498962402 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 10000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.63905547e+032 3.20000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [3.20000000e+001 1.63946528e+052 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63905547e+032 ... 1.63905547e+032\n",
+      "  1.63905547e+032 1.63905547e+032]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.63905547e+032 ... 2.34368828e+185\n",
+      "  3.66113416e+151 1.48523606e+099]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63905547e+032 ... 3.66113416e+151\n",
+      "  3.75036998e+186 4.45926046e+122]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63905547e+032 ... 1.48523606e+099\n",
+      "  4.45926046e+122 2.88692356e+141]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.43630290031433 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 100000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.63846554e+039 3.20000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [3.20000000e+001 1.63850650e+064 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63846554e+039 ... 1.63846554e+039\n",
+      "  1.63846554e+039 1.63846554e+039]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.63846554e+039 ... 2.34031582e+226\n",
+      "  3.65665571e+184 1.48331878e+121]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63846554e+039 ... 3.65665571e+184\n",
+      "  3.74455212e+227 4.45364556e+149]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63846554e+039 ... 1.48331878e+121\n",
+      "  4.45364556e+149 2.88276542e+172]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.51315498352051 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.63840655e+046 3.20000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [3.20000000e+001 1.63841065e+076 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840655e+046 ... 1.63840655e+046\n",
+      "  1.63840655e+046 1.63840655e+046]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840655e+046 ... 2.33997884e+267\n",
+      "  3.65620816e+217 1.48312718e+143]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840655e+046 ... 3.65620816e+217\n",
+      "  3.74397083e+268 4.45308444e+176]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840655e+046 ... 1.48312718e+143\n",
+      "  4.45308444e+176 2.88234992e+203]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "../pygraph/kernels/treePatternKernel.py:188: RuntimeWarning: invalid value encountered in multiply\n",
+      "  kh *= (G1.node[n1][node_label] == G2.node[n2][node_label])\n",
+      "../pygraph/kernels/treePatternKernel.py:186: RuntimeWarning: invalid value encountered in double_scalars\n",
+      "  kh_tmp *= lmda * all_kh[str(pair[0]) + '.' + str(pair[1])]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.40178990364075 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 10000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.63840066e+053 3.20000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [3.20000000e+001 1.63840106e+088 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840066e+053 ... 1.63840066e+053\n",
+      "  1.63840066e+053 1.63840066e+053]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840066e+053 ...             inf\n",
+      "  3.65616341e+250 1.48310802e+165]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840066e+053 ... 3.65616341e+250\n",
+      "              inf 4.45302833e+203]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840066e+053 ... 1.48310802e+165\n",
+      "  4.45302833e+203 2.88230838e+234]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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J05U1iwqZzZC61CyA5GaIy5pFUtMj2gxxUbOIi3VQ7ayMmoUt1iyIqHCsWVRM2u35C4B87IxL0pqYQPdE/1oTWb8Vp7tT2DC2OfM3elwsSfGY5zsxlpzn39xHa2ICO2ce66vlXD35hQXbTHlrFpsuvhs7fn0fAGDTWVswd+zY/O/D0Z7w+FHs4PRUnZoepmjcrdNPR/f48b7n5FrhOmdMHA3Jjs2QHMrs4By0gEqdOji7MzN9HZ3T3Sl033vPWUxJ26PvZVnL5VnPq4h5TuLnrTVmfey37vwUTlx3GU5cN3Qh/VyGLthLxUmaY+F7oljwrRhXG624hhodiTF/9u18ZqpVdOesn/rLB+7KdyxLrFkQkRUmiwq0JifRmpzs2+bbt1+S9vkrE38XreJXXaZoVT5cQWrQc+vCnEI+dtGFqV8/6H3Lih2cRA3GDs4aqNs3XRyzEzFtzaLIjsVBxzafE2ds2bLcccj4eObXFnEhWZbznwWTRQSneycrcrp3ER1x5szMrNO9d7z5YO44dv3pB32P04yG2D5/kLD8ZQ/PshkygIvx8eicgTquzp13CnKZognEN1XHx2YIERWOyWIAH795iFzhpCzPWF8t6bFo/4FPorH5cm59O09x2GdhEplf36CsD9H8hU2RY1W5YEoW4QVSQHxn4YbWjRhbtgxzb789dF95r9+Yv5AsOIcbxjb39ju3fWBsO958MLZjucoLyczXRGPMemwTLyQjolKwg5OICsdkQURWmCxGSB06yZJUNQvRNo647aMmbZk4GjJCrvrstlq/oZfe/h184PDJWpdhlLGDswA+DcFFDRt58HVlqZCruGxi8Pl9jxMXLzs4K+brB8bmw+xyCf8kn7n+W/0bHC+Fn9Q0cXXe4pY8qOS4lR+RiGqJyaIBfKs5DDPx5At9j4u4EVBaPp+z7swMujMzlR+XyWKEmKsr1U1Y1Y8rQ9W3RBzFkY84acvJDk6iBmMHJxEVjsmCiKwwWRBl0JR+DROTRQF8/uAMnLos4mWHng/xDIvBx5sZDZM3XnZwEoD6zUb0het1WvNiB2cOZX/Tmjd/ia6Wba2EGY3DPnid9WsWxBu9+Mt2Sfzp7hRaS5ZkjtUcXo1bJTsptjIuEIvWMMLzZMYRty3PEv7mrNvofo58/VN9z+2sX9N3/DxYsyBqMNYsiKhwTBZVc3xRVFY+deYlxRKuN5lGltdERZtF0fgSz13QwZzHsGMV2axmsogofXRA4k+5T3+MpmifQLSPxeVoSvTY4YLCSf0BcXGGr8nj2ae3pn7NdHdq/rMQF1f7w8tPPWiNDd2XTVnzGtpnISIPA7gOwFuq+olg270AvgwgXMr5G6r6VPC7uwF8CcAcgK+q6s5hQbDPgsiNovssHgGwKWb7/aq6OvgXJoqPA7gJwCXBax4UkcFpscF8nOOQRtbYyypzlv0WEUvSPuJqYmNnLcXYWUuzjYIlHCMc6Rm0ryLKOTRZqOrzAN6x3N8NAH6sqrOq+lsABwFcliM+IvJEnuUO7xSRWwHsBfAPqnoMwDkA9hjPORxsI/Q6wtrP/gIImn51mQS1YBKQCKDaH3+wzUYRN/Ux92PezCfthKWrJ7+QKxagf+1T8/jRu8sBwNzv3zkVX0Gd3To7G3usaDx5Ze3gfAjABQBWAzgK4NtpdyAiW0Rkr4jsfR+zGcOol/Yz+/r+oOrSDFmw9F5Qhr7YU8zXKWIilBlP+Di861aaP4yiOzjjJkzFTQ2f7k6lOmeDmM2QaNnDeCqblCUiKwE8GXZwJv0u6NyEqt4X/G4ngHtV9b8G7Z8dnERulD4pS0RWGA8/D+Dl4OcnANwkIuMich6AVQBeiL6+6epQm6gjl0O4ccLOzOhzp7tTkHa7dp+DoX0WIvI4gHUAzhaRwwDuAbBORFYDUACHAHwFAFR1v4hsB/ArAB0Ad6jqXDmhE1GVbEZDblbVFaq6SFU/qqr/rqpfUNW/UNW/VNXrVfWo8fxvquoFqnqRqv5HueEXr4p+hGibNvzZd8MuJEuznyJjittmO1GpjPMe7nPH29/Fjre/27dt4+KbsXHxzdh18vH5voQ8MVQ5dMoLychOitGO0iXEEtfBN0yW1wzch0hvZmbXqFAb8ZqjE0WMVETjl3Yb2un0HxtIfO/S9FnwTnERRQ41xZE1l0D37e/L9OEHx+ehVHM5/kG96zZlmO5OYcPY5szJZ3pu+8AYotuL+sO0jS16TDOO6HBv+HPehBE9TjSe6PYsmCwqpvv2A6jPHItQ0oc/yx9h3rKHr0+TZKta2SrNOSkqpkHHKfJzxmaIp8zxed8SS5qYfIw/5FNscUnDupaWowxcz4KICsdmiGfieu99+gYEhn/j+Tyy43NsWVT5uWDNgoisMFkMMGrfQnnJ+Lj1orxVGTvjQws3GovFuLj/a9/CNVUcb8WH0VqyJNciyDbYwUnUYOzgJKLCMVlQvQ1ZE2LsogsrCsQwZM3MtIY1h1sTE5BFiyGLFhd63CiOhlC9DWlGzx04WFEghm6x104OG/HonjhR6PGSsGZBRFaYLIjICpMFAfBsmFgE0m5D2m5bya3JSbQmJwc+x8V5y3pZe95YmSyIyArnWRA1GNezyKHsdQ/aHzsXnVdfq996FpZVWNsrJTeO/x30/ZOZY0m6vDvtpfRFL34Tt7iNGYf5mjhZFu8ZtI/o5ywPJouIUv5gjdWKOq++Nr9542m3APDvQjGTjI/P35di0XO9dZrfX3c0V/t342m3YNfsDzOXOel1my6+GwDwV1+9H7984C7r1xXJTBLh+6uzswumyW887Rbo7Gzie99e8WF0jr4BoDePwnZ4NNyX+b6Fj/Nin4VDu/70A+z60w9Sv67syTcmM74De1biwJ6VhezzmnO/lns/UTt+fR8A4IOHOkOeWQ3z/Y2+z8Pe9+57x+d/1rlupmOnOZ4NJgsissIOzootWFC1JnxqKiXFMnbmmZg7dizVvrK8JurI1z+Fc/75P+djAxb2G8TFK+32/CrfWcXdrjDN7QvTdHAyWRA1GK86pcJ4NVkrwmZyUvv8ldUEY6j6nMXdN6SMGFizIGow1ix8NuSSal/5VMNIiqU1MZF6X1leE2WuxhVX20k8dyK5z+uwYxV5hz0mCyKywmRRNaPZV8V9VYsS15ueNfa8ZU7q2d8581jqfWV5TdSzT2+d/zl617Gk2abT3anCbgdp9llEz00YD+916gkfhhV3vv4Srv7I6r5tNlN9q7qtn42D91+BC+/a48VUeJub/rh637O+Z3HxcuiUiKywg7PBXK8BUbS6NNPqJGvzl8mCiKwwWYyQzvo1tZxKDvS+7f5w65ULbgrkoq8i7lt3lGo4WTs92WdB1GC16+AUkbcBHAfwO9exVOxssMxN4HOZP6aqy2ye6EWyAAAR2auqa13HUSWWuRlGpczssyAiK0wWRGTFp2TxPdcBOMAyN8NIlNmbPgsi8ptPNQsi8hiTBRFZYbIgIitMFkRkhcmCiKz8Pwnisz/TFerrAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.45088076591492 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 100000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.63840007e+060 3.20000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [3.20000000e+001 1.63840011e+100 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840007e+060 ... 1.63840007e+060\n",
+      "  1.63840007e+060 1.63840007e+060]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840007e+060 ...             inf\n",
+      "  3.65615894e+283 1.48310611e+187]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840007e+060 ... 3.65615894e+283\n",
+      "              inf 4.45302272e+230]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840007e+060 ... 1.48310611e+187\n",
+      "  4.45302272e+230 2.88230422e+265]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.3540358543396 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 1000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.63840001e+067 3.20000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [3.20000000e+001 1.63840001e+112 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840001e+067 ... 1.63840001e+067\n",
+      "  1.63840001e+067 1.63840001e+067]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840001e+067 ...             inf\n",
+      "              inf 1.48310592e+209]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840001e+067 ...             inf\n",
+      "              inf 4.45302215e+257]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840001e+067 ... 1.48310592e+209\n",
+      "  4.45302215e+257 2.88230381e+296]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.66941165924072 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 6.0, 'lmda': 10000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.6384000e+074 3.2000000e+001 0.0000000e+000 ... 0.0000000e+000\n",
+      "  0.0000000e+000 0.0000000e+000]\n",
+      " [3.2000000e+001 1.6384000e+124 0.0000000e+000 ... 0.0000000e+000\n",
+      "  0.0000000e+000 0.0000000e+000]\n",
+      " [0.0000000e+000 0.0000000e+000 1.6384000e+074 ... 1.6384000e+074\n",
+      "  1.6384000e+074 1.6384000e+074]\n",
+      " ...\n",
+      " [0.0000000e+000 0.0000000e+000 1.6384000e+074 ...            inf\n",
+      "             inf 1.4831059e+231]\n",
+      " [0.0000000e+000 0.0000000e+000 1.6384000e+074 ...            inf\n",
+      "             inf 4.4530221e+284]\n",
+      " [0.0000000e+000 0.0000000e+000 1.6384000e+074 ... 1.4831059e+231\n",
+      "  4.4530221e+284            inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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0pWkbJr/qNEXuyEHObd5yYrnBgXLWQtSRikoNrUPqvLF0a7u6ui2zNxa5L2Rqc5MUdaGypnX5OvhPxb6N5Lo8t7xUyK9JSDn1BYm9H7s+ofMs4WX//RiWPqzrn9Bx6DNtmNWq0xBLGllYbvC+9pbIgTXfZShdfErpu5wjC646JUncG64EQzFFltZvNBaEEBOzn4aURl8+C7+eHHX59Q7hs7CkKQ/hs2ir8xA+i5js2LGrj6/XBbJjOT9fmII+izMZW886puazWJ+3FJ/F7I0FmQclGOQ5QgcnmR0l74fh4ibGDS03lNiWs89oLAghJmaflFUadHA2k+Mep/Z3KMHB6R4P6eC07n0RcnBaoc+iYog5sXuxUjd7SXP0LhGKIXQKRSBK6Tsgrqt/Tqi8FZs2AxsnTacuysGZ88mQ8sK3ldUk5dYib8gvpiUs6GL5wvYxigrJ98tCug0xsqi7l+qMh3W04BL7TKwOOjgJCVC6c7R0aCwqhriRmnjKS7qxfV1K0C2mQ51uY01NLNGJKUR6aCwIISZoLCqGeOrUzfVD57YhFGvvSsyz3weWUUzdHH5sx2aTfu9jJBHqP39E2/YembyDMxeMhsRhNKQbg0dDGpB1w97SyeXNdv8D/URDUmWhc0qIhqRe+3qNFQ2J6ReLkLg6d9UjlWdhOSdWZ5/RkCZwGlIx1DTEKqukJ6OvSwm6lToNCeHq5CZQ+eeUqLsLjQUhxMTkpyFTo+/wWF+OyKHCeiX6R5qQmnKmXvcxJfLfc8uY7k2IQ8y4yNZzoD97L5sMoH8/jV+nVV6ODM7JjyyY7t0vc0731p+9N1i6t/u/7pxQnTEd6xy3oTq7MpuRRa4v0FghrJKH1mt8Y1FCqDI2TXGp+9L1aSwsn+naf131X+TIokvHx8JYQ48s6vwCucNgVqxhu7pRR185BbGQd+zcJklxOQgZ1xAxvazh3VD7GTolhIzGbKYhQP4pxBhTA4svo2TqnpAlkBr1jMVY/cYl6mQ0SvnyucjWcwaRkZKTWw/Ztq1W1qbzzzeda2U2Pgugu5MoNffN4bNIzZm7RkNy51nURYpCWLzxdSPAJnkWTaMhIT1zOzhTvhvr9a9LFV+jx49H++Dw8a+adGCeBSmSsSMnMUrVawg4DSGEZGfy0xAyHUp9cueckpTOGdPJzfuBBhMLTkNaUuLQtZREqTbk9rV01SOVvDUHw3Jk41Cj3zrlNISQJbFpc+uPzn5kkfsJ0FfKcFcsac9AOTs0hbCu0RlKF59S+q5rprILHZwkiXvDlWAopsjS+o3GghBigsaCEGKCxqIlRzbK+1EYdxVmabqlCK0gHUsPiw5j65mDpm2YvYOTkFyM6cjuy5n6mD74tKrutZxLY0FIA0qKHuWA0RBCSHZoLFpSol9g6j6LEvSO6eCHmsfWMwf0WYyAm0xU2vC0bbLWmJTQj0320ZwKTMpKENonMld9PiWsaQiV+U/t9dPR/SvhSelfq7EjJG6/WffOGFKvoZn8yCLn5iWpNGNufnO63rrNb1JOQG5+Eyekl/V6+3Ksm99YRxaTNxaEpIh92Xr9kSERwPlumaMomzYDGyfNMoPt2rIFh9+7byVv8/7VuScfCJ7LaQghJDvc/GZg6vZLCJW3rT9HXX69sWlDTnl105CUrKYrgvv4RbK66Vnd+/55FlLTDVde7Nwme3BOfmSR02npO7P8utvKCjmkUs6zOnlDOrfqnI6x/kk54No66PwVsrE+TJUN0X+WCFQdTRzzFt9IjjYnfRYicheATwI4pqofqcpuA/B7AF6vTvsjVX2keu8LAG4EcBLA76vqoykl6LMgFnKNvnpBVtP+tW+g9Yilgc/C9YucZTC2HMCRE/efPo7o0sRnYTEWHwPwEwD3esbiJ6r65965lwK4D8BlAD4A4DEAv6Sqta1nNOQ0jIb0Fw0J6cZoSMZt9VT1cQBvWioDsA/A/ap6XFV/AOAFrAwHIWTidHFw3iwinwXwFIA/UNW3AFwM4AnnnJeqst7I8fSMDRtTx03qB+qf+qE5ZkzekMPw1NM41KaUfrkdoaH5fehJn0t2G5rKdc9v0p9HNg4BIsF7t6vfwpRnISKXAPimMw3ZBeANrDYS/xMAF6nq74rI3wB4QlW/Up33ZQD/pKoPBuo8COAgAJyL7b92hVzXqgFTm4b4ZT5dpyG5sQ6x13SdhjTVrU6+Rbdc948vw5cVkxvri9A0ZPPOnTj5+utnnBNqo/teqp1v/eo/4Knv/jRfUpZvLGLvVc5NqOqfVu89CuA2Vf3Xuvrp4CR9Evui9JqU1fB9CyFjYZWXw1i0moaIyEWq+kp1+GkAz1avHwbwNRH5S6wcnLsBPNlGxtAM8bS2TEO6PvFyOzhTuvXlUI0dx/TxsfRjn3kWoZFqTNeQ3iFcQ+HKCPVXH3kWSWMhIvcBuBLAhSLyEoBbAVwpInuwmoa8CODzAKCqz4nIAwC+B+AEgJtSkRBCyDRIGgtVvT5Q/OWa878I4ItdlGrC1HwW69eWJ0xJPgs3mSnmF0jNw93z6t63kAqdppKShnZ0Nr1m1tDp+v2UvK7OTWAG6d65oiGhunJHQ+rK6obS1vI+iHnlx46GhOqpcySPFQVZM2g0JPCZHNGQyRuLqY0s/DKLXtbyPmgSDRlyZOHWYynnyIIjiywhMOsTPHf97vtNRhZD0kaHEvSOUbJuLk1GFqnP52LyxmKN5YlWR8zrnrPTLZEDS/7FGE9FV24qGpJ6iueOmrjyYpESazSiL6xtbhNdsowgckxDJr/qlBAyDLPaKSu3M2tI34ArM8RUhs/A+P6BOnrTbdPm1f/1itEmq0cDegEG3SIyZOs5gG5AzjsPG++8e6ZeHk1Wnc5mGkLKYKxh/uj4X8YGhiKbzIp1Vqq+/XZWcZM3Fn1GQ3LJahsNqauvxGhI6j23zvW5XXWzyO87ZyUWNQtlT4bOScmvOyc2UsoVyXOZ1TSElMkY07k5kDuVPgQ37CWEZGfyxiLHHNlNwXZThVMpw03qD9UV+rPIG9Iv4IclQ30V6rc6HVPvN9GtTn7oWvqyc94//rHlXup6jWP3T65714XTEEKMjDmdyuXnkS1boCdOAAA2bd+Ow+/c+7Sq7rV8dvIjC0KmwOadO7F5587sdVp59MfPAMApQwEAG+++20geRxaETIjcTk86OB36np/mqrcrMb3qfCKpzw+N1Xc0lC6Wviuh36ww3ZsQMgichpDZE3NMyrZt0OPHs8kAnKlBDz+MbN2Ds8kPI2ffsLdv+CNDp7HIs2b05VzdaR3Cdt3PwtLndTrVZXD6ZbH6m+LWUXetm1x/v84mq5TdezelQ9YfGSJ5uWrTZ7J8iVP155Yx1BJ5y3L2vvYVyUFKX/faxMpzyg/Ja3uPTH5tCFkOuXIN+mRMp2xIbk49OLIghJiYvM9iasSejrmemn0tPqrzn+SUV+ezSMmq829Y5XXVOfYkt+7U1VSXOt+EKy/mx2jis6CxIJPhDIPacHOZvpEtqxn94ffuO9s57kVGautp8Ctpbuq2byyuPu+3cfj/vnLqOGaEFrX5zdSiIX6ZT9doSG6snv41XaMhdZxx/sZJczQkpptsPQeHj381+2juyMYhXLXlQLC//AjHWddSN85433/tsg6P+m2UbdtOGYqrthyoraMJHFmQMxHnIVPAvZGD2Bdl0/nnYyPTblIxYxB7P0YTnSxTQ5fQuU1GFjQWA0OfRTM5k/FZOMlPIcw+iy0H7NMrkVPJVmf5LLYcwJET958hv6vPgtEQQoiJyY8s6LPITCBNuRSfRayemPyUbuu5fS8+C09Wnc/CLXfr9M999MfP4BMf2BOU68p330v5PR7TB837WUzeWKTI/cVqM9T1zwXyT0PqUqBdrDdrrP5QuV93W+p0b2tE205D6r6IoXNSBjVn6DQUDnXfi/lKGDolJBOnvmiFhWWBM8OkXfCNFX0WBXNkI7w3Qqy8bf056vLrHUKeX0+sryyfrTu39v2GhsKtw+2LUN+4ZaG/GDFDkeovX58u0FgQQkzQWLSkj6d3V0rTpwkl9OdVm/fXjvzqjvtm0/btg8oLQZ8FIUa6OMvXG+a60YymsoEzHaB+dCT1+VlEQ0TkdQDvAHhjbF0G5kKwzUug5Db/gqrutJxYhLEAABF5ymrh5gLbvAzm0mb6LAghJmgsCCEmSjIWd46twAiwzctgFm0uxmdBCCmbkkYWhJCCobEghJigsSCEmKCxIISYoLEghJj4f+AqDS9gIKfyAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8908>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.52321338653564 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-10, 'kernel_type': 'untiln'} is: \n",
+      "[[5.93000002e+02 1.46000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.46000000e+02 3.44000001e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 5.93000002e+02 ... 6.09000002e+02\n",
+      "  6.09000002e+02 6.09000002e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.09000002e+02 ... 1.95501007e+05\n",
+      "  1.93793007e+05 1.97299009e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.09000002e+02 ... 1.93793007e+05\n",
+      "  1.92719007e+05 1.95661009e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.09000002e+02 ... 1.97299009e+05\n",
+      "  1.95661009e+05 2.01707018e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98abac50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.62462091445923 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-09, 'kernel_type': 'untiln'} is: \n",
+      "[[5.93000022e+02 1.46000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.46000000e+02 3.44000012e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 5.93000022e+02 ... 6.09000022e+02\n",
+      "  6.09000022e+02 6.09000022e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.09000022e+02 ... 1.95501067e+05\n",
+      "  1.93793068e+05 1.97299085e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.09000022e+02 ... 1.93793068e+05\n",
+      "  1.92719073e+05 1.95661094e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.09000022e+02 ... 1.97299085e+05\n",
+      "  1.95661094e+05 2.01707185e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.41100430488586 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-08, 'kernel_type': 'untiln'} is: \n",
+      "[[5.93000223e+02 1.46000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.46000000e+02 3.44000121e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 5.93000223e+02 ... 6.09000223e+02\n",
+      "  6.09000223e+02 6.09000223e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.09000223e+02 ... 1.95501673e+05\n",
+      "  1.93793677e+05 1.97299851e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.09000223e+02 ... 1.93793677e+05\n",
+      "  1.92719730e+05 1.95661942e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.09000223e+02 ... 1.97299851e+05\n",
+      "  1.95661942e+05 2.01708846e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.72209644317627 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-07, 'kernel_type': 'untiln'} is: \n",
+      "[[5.93002229e+02 1.46000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.46000000e+02 3.44001206e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 5.93002229e+02 ... 6.09002229e+02\n",
+      "  6.09002229e+02 6.09002229e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.09002229e+02 ... 1.95507730e+05\n",
+      "  1.93799767e+05 1.97307508e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.09002229e+02 ... 1.93799767e+05\n",
+      "  1.92726299e+05 1.95670418e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.09002229e+02 ... 1.97307508e+05\n",
+      "  1.95670418e+05 2.01725460e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.9407434463501 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-06, 'kernel_type': 'untiln'} is: \n",
+      "[[5.93022288e+02 1.46000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.46000000e+02 3.44012064e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 5.93022288e+02 ... 6.09022288e+02\n",
+      "  6.09022288e+02 6.09022288e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.09022288e+02 ... 1.95568320e+05\n",
+      "  1.93860681e+05 1.97384091e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.09022288e+02 ... 1.93860681e+05\n",
+      "  1.92792005e+05 1.95755198e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.09022288e+02 ... 1.97384091e+05\n",
+      "  1.95755198e+05 2.01891673e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 73.01238059997559 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-05, 'kernel_type': 'untiln'} is: \n",
+      "[[5.93222910e+02 1.46000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.46000000e+02 3.44120666e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 5.93222910e+02 ... 6.09222910e+02\n",
+      "  6.09222910e+02 6.09222910e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.09222910e+02 ... 1.96175830e+05\n",
+      "  1.94471251e+05 1.98151075e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.09222910e+02 ... 1.94471251e+05\n",
+      "  1.93450774e+05 1.96604957e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.09222910e+02 ... 1.98151075e+05\n",
+      "  1.96604957e+05 2.03561050e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 73.05074119567871 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 0.0001, 'kernel_type': 'untiln'} is: \n",
+      "[[5.95231774e+02 1.46000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.46000000e+02 3.45209015e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 5.95231774e+02 ... 6.11231774e+02\n",
+      "  6.11231774e+02 6.11231774e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.11231774e+02 ... 2.02415691e+05\n",
+      "  2.00722352e+05 2.05937136e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.11231774e+02 ... 2.00722352e+05\n",
+      "  2.00212847e+05 2.05301262e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.11231774e+02 ... 2.05937136e+05\n",
+      "  2.05301262e+05 2.20998610e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.87431716918945 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 0.001, 'kernel_type': 'untiln'} is: \n",
+      "[[6.15587088e+02 1.46000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.46000000e+02 3.56329032e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.15587088e+02 ... 6.31587088e+02\n",
+      "  6.31587088e+02 6.31587088e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.31587088e+02 ... 2.84921175e+05\n",
+      "  2.80276455e+05 2.96324951e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.31587088e+02 ... 2.80276455e+05\n",
+      "  2.89012703e+05 3.15320832e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 6.31587088e+02 ... 2.96324951e+05\n",
+      "  3.15320832e+05 4.91673036e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.87815833091736 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 0.01, 'kernel_type': 'untiln'} is: \n",
+      "[[8.47529783e+02 1.46000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.46000000e+02 4.95055045e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 8.47529783e+02 ... 8.63529783e+02\n",
+      "  8.63529783e+02 8.63529783e+02]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 8.63529783e+02 ... 2.55779364e+07\n",
+      "  1.20546780e+07 3.86939834e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 8.63529783e+02 ... 1.20546780e+07\n",
+      "  3.10161390e+07 1.22073718e+07]\n",
+      " [2.00000000e+01 2.00000000e+01 8.63529783e+02 ... 3.86939834e+06\n",
+      "  1.22073718e+07 1.66002008e+08]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98abac50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 73.2267439365387 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 0.1, 'kernel_type': 'untiln'} is: \n",
+      "[[8.39688608e+03 1.46000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.46000000e+02 1.87880916e+04 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 8.39688608e+03 ... 8.41288608e+03\n",
+      "  8.41288608e+03 8.41288608e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 8.41288608e+03 ... 2.48592906e+18\n",
+      "  4.64186067e+15 7.68438971e+11]\n",
+      " [2.00000000e+01 2.00000000e+01 8.41288608e+03 ... 4.64186067e+15\n",
+      "  1.94230190e+19 1.08968744e+14]\n",
+      " [2.00000000e+01 2.00000000e+01 8.41288608e+03 ... 7.68438971e+11\n",
+      "  1.08968744e+14 2.41251380e+18]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 73.11900162696838 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1.0, 'kernel_type': 'untiln'} is: \n",
+      "[[3.47285450e+07 1.46000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [1.46000000e+02 2.86376444e+12 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 3.47285450e+07 ... 3.47285610e+07\n",
+      "  3.47285610e+07 3.47285610e+07]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 3.47285610e+07 ... 2.64910726e+52\n",
+      "  1.96187086e+39 1.56890251e+30]\n",
+      " [2.00000000e+01 2.00000000e+01 3.47285610e+07 ... 1.96187086e+39\n",
+      "  1.25100293e+55 1.91338422e+35]\n",
+      " [2.00000000e+01 2.00000000e+01 3.47285610e+07 ... 1.56890251e+30\n",
+      "  1.91338422e+35 2.06819567e+46]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 73.01346492767334 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 10.0, 'kernel_type': 'untiln'} is: \n",
+      "[[5.46678080e+013 1.46000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [1.46000000e+002 5.40887703e+028 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 5.46678080e+013 ... 5.46678080e+013\n",
+      "  5.46678080e+013 5.46678080e+013]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 5.46678080e+013 ... 1.04582014e+119\n",
+      "  2.35651978e+082 5.81137387e+063]\n",
+      " [2.00000000e+001 2.00000000e+001 5.46678080e+013 ... 2.35651978e+082\n",
+      "  9.91946619e+121 2.14331398e+074]\n",
+      " [2.00000000e+001 2.00000000e+001 5.46678080e+013 ... 5.81137387e+063\n",
+      "  2.14331398e+074 8.74328703e+096]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.90210103988647 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 100.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.36976313e+020 1.46000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [1.46000000e+002 1.55412261e+048 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.36976313e+020 ... 4.36976313e+020\n",
+      "  4.36976313e+020 4.36976313e+020]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.36976313e+020 ... 3.18336921e+196\n",
+      "  8.85119216e+133 4.13010998e+103]\n",
+      " [2.00000000e+001 2.00000000e+001 4.36976313e+020 ... 8.85119216e+133\n",
+      "  3.22830734e+199 1.68266448e+120]\n",
+      " [2.00000000e+001 2.00000000e+001 4.36976313e+020 ... 4.13010998e+103\n",
+      "  1.68266448e+120 3.11009126e+156]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAADD1JREFUeJzt3d+LXOUdx/HPZ02MKAbdpl1SY1sroaC0XWQxXkiJyGrMRaMXK/GiBhHWi/gHxCu9EbwRQaiBSEPihdrkQsxFWl32xiujEYKNUjHYiFljtm2KFqXRZL+9mLM6bPbHd+fXOWfm/YJhZs6cmfk+M7ufec4zzznjiBAArGSo7AIA1ANhASCFsACQQlgASCEsAKQQFgBSSg8L29tsf2T7lO09ZdfTLbZP2/6b7RO2jxfLhm1P2f64OL++7DrbYXu/7VnbJ5uWLdpGNzxfvO/v276tvMpbt0Sbn7I9U7zXJ2xvb7rtiaLNH9m+t5yqW1NqWNi+QtIfJd0n6RZJD9m+pcyauuyuiBiNiLHi+h5J0xGxWdJ0cb3ODkjatmDZUm28T9Lm4jQpaW+Pauy0A7q8zZL0XPFej0bEUUkq/rZ3Srq1uM8Lxf9ALZTds7hd0qmI+CQivpX0qqQdJdfUSzskHSwuH5R0f4m1tC0i3pJ0fsHipdq4Q9JL0fC2pOtsb+xNpZ2zRJuXskPSqxFxISL+IemUGv8DtVB2WNwg6bOm62eKZf0oJL1p+z3bk8WykYg4W1z+QtJIOaV11VJt7Pf3/vFi82p/0+ZlrdtcdlgMkjsj4jY1ut+7bf+u+cZozLvv67n3g9DGwl5JN0salXRW0rPlltMZZYfFjKQbm65vKpb1nYiYKc5nJb2mRvfz3HzXuzifLa/CrlmqjX373kfEuYi4FBFzkl7UD5satW5z2WHxrqTNtm+yfaUagz9HSq6p42xfY/va+cuS7pF0Uo227ipW2yXp9XIq7Kql2nhE0sPFtyJ3SPqyaXOl1haMvTygxnstNdq80/Y62zepMbj7Tq/ra9WaMp88Ii7aflzSG5KukLQ/Ij4os6YuGZH0mm2p8Zq/HBF/tf2upEO2H5X0qaQHS6yxbbZfkbRV0gbbZyQ9KekZLd7Go5K2qzHI942kR3pecAcs0eattkfV2OQ6LekxSYqID2wfkvShpIuSdkfEpTLqboXZRR1ARtmbIQBqgrAAkEJYAEghLACkEBYAUroWFqvdm7RpCvTAoM2DoV/a3JWwaHFv0r54QVeJNg+Gvmhzt3oWg743KdB3ujWDc7G967YstfKVXhdX6Wqt9/BAzRCjzYOhym3+n77Wt3HBmXVLm+5dbMdNSo0X884fDiYEoEeOxXR63W5thqy4d11E7IuIsYgYW6t1XSoDQKd0KywGYm9SYJB0ZTNkgPYmBQZG18YsioOUHu3W4wPoLWZwAkghLACkEBYAUggLACmEBYAUwgJACmEBIIWwAJBCWABIISwApBAWAFIICwAphAWAFMICQAphASCFsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAkAKYQEghbAAkEJYAEghLACkEBYAUggLACmEBYAUwgJACmEBIIWwWMbU3OGBfv5WTc0drm3tWJojouwatN7DscV3l10GMHCOxbS+ivPOrEvPAkAKYQEghbAAkEJYAEghLACkEBYAUggLACmEBYAUwgJACmEBIIWwAJBCWABIISwApBAWAFIICwAphAWAFMICQAphASCFsACQsqadO9s+Lem/ki5JuhgRY7aHJf1Z0i8knZb0YET8p70yAZStEz2LuyJiNCLGiut7JE1HxGZJ08V1ADXXjc2QHZIOFpcPSrq/C88BoMfaDYuQ9Kbt92xPFstGIuJscfkLSSNtPgeACmhrzELSnRExY/snkqZs/735xogI24v+MEkRLpOSdJWubrMMAN3WVs8iImaK81lJr0m6XdI52xslqTifXeK++yJiLCLG1mpdO2UA6IGWw8L2Nbavnb8s6R5JJyUdkbSrWG2XpNfbLXIQ1PXn/qr+U4Ur1daJ2lt5jPn7tPv8vXztW/75Qtu/VKM3ITU2Z16OiKdt/0jSIUk/k/SpGl+dnl/usfj5QqAcq/n5wpbHLCLiE0m/XWT5vyXxnw/0GWZwAkghLCqqyuMA6Lyqj/1IhMWyynzzxocmKv/Hs5Q6/OFXzfjQhMaHJsouY1ktD3B2EgOcQDlWM8BJzwJACmEBIIWwAJBCWABIISwApBAWAFIICwAphAWAFMICQAphASCFsACQQlgASCEsAKQQFgBSCAsAKYQFgBTCAkAKYQEghbAAkEJYAEghLACkEBYAUggLACmEBYAUwgJACmEBIIWwAJBCWABIISwApBAWAFIICwAphAWAFMICQAphASCFsACQQlgASCEssGpTc4fLLgElICywauNDE5UPjKm5w9+f0Blryi4A9TQ+NFF2Ccuqen11RM+iIur6CVj1T++VautE7a08xvx92n3+Xr72hAWAFEdE2TVovYdji+8uuwxg4ByLaX0V551Zl54FgBTCAkAKYbGMsgfuyn7+VlV90BOtISwApDDACQwwBjgBdNyKYWF7v+1Z2yeblg3bnrL9cXF+fbHctp+3fcr2+7Zv62bxAHon07M4IGnbgmV7JE1HxGZJ08V1SbpP0ubiNClpb2fKBFC2FcMiIt6SdH7B4h2SDhaXD0q6v2n5S9HwtqTrbG/sVLEAytPqmMVIRJwtLn8haaS4fIOkz5rWO1MsA1BzbQ9wRuPrlFV/pWJ70vZx28e/04V2ywDQZa2Gxbn5zYvifLZYPiPpxqb1NhXLLhMR+yJiLCLG1mpdi2UA6JVWw+KIpF3F5V2SXm9a/nDxrcgdkr5s2lwBUGMrHvzG9iuStkraYPuMpCclPSPpkO1HJX0q6cFi9aOStks6JekbSY90oWYAJVgxLCLioSVuumzKZTF+sbvdogBUDzM4AaQQFgBSCAsAKYQFMCDe+PxEW/cnLIABce9PR9u6P2EBIIWwAJBCWABIISwApBAWAFIICwAphAWAFMICQAphASCFsECtVfFnEqtYUycQFqi18aGJsku4TBVr6gTCAkAKYQEghbAAkEJYoO/06wBj2QgLtKTK/5DjQxOamjv8/QmdQVgASCEsKqKun4B1//TuRO2tPMb8fdp9/l6+9m781Ee51ns4tviynyEB0GXHYlpfxXln1qVnASCFsMDAqOrmUlXrWoiwwMCo6jTsqta1EGEBIIWwAJBCWABIISwqoi6DXAtVfZ7FSrUxzyKPeRbAAGOeBYCOIywApBAWAFIICwAphAWwiCp/w9OqdttEWACLqMsU7NVot02EBYAUwgJACmEBIIWwAJBCWABIISwApBAWAFIIC6BF/ThxazmEBdCifpy4tRzCoiLq+inFwW84+E1PcfAboBwc/AZAxxEWAFIIC9RaFcdLqlhTJ6wYFrb32561fbJp2VO2Z2yfKE7bm257wvYp2x/ZvrdbhQNSNb+RqGJNnZDpWRyQtG2R5c9FxGhxOipJtm+RtFPSrcV9XrB9RaeKBVCeFcMiIt6SdD75eDskvRoRFyLiH5JOSbq9jfoAVEQ7YxaP236/2Ey5vlh2g6TPmtY5UywDUHOthsVeSTdLGpV0VtKzq30A25O2j9s+/p0utFgGgF5pKSwi4lxEXIqIOUkv6odNjRlJNzatuqlYtthj7IuIsYgYW6t1rZQBoIdaCgvbG5uuPiBp/puSI5J22l5n+yZJmyW9016JAKpgzUor2H5F0lZJG2yfkfSkpK22RyWFpNOSHpOkiPjA9iFJH0q6KGl3RFzqTukAeinzbchDEbExItZGxKaI+FNE/CEifh0Rv4mI30fE2ab1n46ImyPiVxHxl+6W3z/qOpGHHcnYkayn2JEMKAc7ktVQlT+dl0PPgp5FT9GzQC9MzR2u5FTsMuuiZ9EHqvxpXVdVDAqpUVfVe2gSYQEgibCoqKp+CqI7xocmvu9hVBVhAVRIlQODsAAqpqqBQVgAFVTFzVDCAkAKYQEghbAAkEJYAEghLACkEBZAzZQ1NZywAJCy4pGyAFRLWXMw6FlURBVn7GVUfW9JjmfRORzPAqi5do6HwfEsgAHSq+NhEBYAUhjgBPpALwY96VkASCEsAKQQFgBSCAsAKYQFgBTCAkAKYYHKeePzE2WXUOkp7K1qt01M9wYGGNO9AXQcYQEghbAAkEJYAEipxACn7X9K+lrSv8qupcc2iDYPgiq3+ecR8ePMipUIC0myfTwixsquo5do82DolzazGQIghbAAkFKlsNhXdgEloM2DoS/aXJkxCwDVVqWeBYAKIywApBAWAFIICwAphAWAlP8DrxI2Jcv/VpYAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.38294816017151 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.27073025e+027 1.46000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [1.46000000e+002 1.36210900e+068 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.27073025e+027 ... 4.27073025e+027\n",
+      "  4.27073025e+027 4.27073025e+027]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.27073025e+027 ... 2.22354806e+275\n",
+      "  6.23033600e+186 3.10795445e+144]\n",
+      " [2.00000000e+001 2.00000000e+001 4.27073025e+027 ... 6.23033600e+186\n",
+      "  2.27464447e+278 1.28932345e+167]\n",
+      " [2.00000000e+001 2.00000000e+001 4.27073025e+027 ... 3.10795445e+144\n",
+      "  1.28932345e+167 2.19348628e+217]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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39bRWLi6kLqV16OAEOowOTgC1IywAhBAWAEIICwAhhAWAEMICqCDFDYpTXbxHWAAIYQQnUEH/bubTlGq4PUcWA5jPYjTms4itIzqfxbCvqttuEiM4M5DTpdJRw2pOden67YvDbt64Y/19uV7qX5fBto6DEZxIYpw/1DrfuH7zxh1BMc722nBElwvCAkAIpyFAh3EaAqB2hAWAEMICQAhhASCEsAAQQlgAHTC3aVP1ddRQR+flPLAn9XDsSVQZ/jxLNdRp5dq1ym1hnAXQYYyzAFA7wgJACGEBIISwABCSRQenmf1a0m8k/XfqWqbsbtHmLsi5zX/o7r8XeWEWYSFJZnbC3RdT1zFNtLkbZqXNnIYACCEsAITkFBYHUheQAG3uhploczZ9FgDyltORBYCMERYAQggLACGEBYAQwgJAyP8D2UQobzttBmIAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.95256662368774 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 10000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.26092801e+034 1.46000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [1.46000000e+002 1.34415833e+088 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.26092801e+034 ... 4.26092801e+034\n",
+      "  4.26092801e+034 4.26092801e+034]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.26092801e+034 ...             inf\n",
+      "  6.01381532e+239 3.02014369e+185]\n",
+      " [2.00000000e+001 2.00000000e+001 4.26092801e+034 ... 6.01381532e+239\n",
+      "              inf 1.25528792e+214]\n",
+      " [2.00000000e+001 2.00000000e+001 4.26092801e+034 ... 3.02014369e+185\n",
+      "  1.25528792e+214 2.11786759e+278]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.86998200416565 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 100000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.25994879e+041 1.46000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [1.46000000e+002 1.34237526e+108 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.25994879e+041 ... 4.25994879e+041\n",
+      "  4.25994879e+041 4.25994879e+041]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.25994879e+041 ...             nan\n",
+      "  5.99256579e+292 3.01149333e+226]\n",
+      " [2.00000000e+001 2.00000000e+001 4.25994879e+041 ... 5.99256579e+292\n",
+      "              inf 1.25193258e+261]\n",
+      " [2.00000000e+001 2.00000000e+001 4.25994879e+041 ... 3.01149333e+226\n",
+      "  1.25193258e+261             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+i/a4pfgsWsb+jiMLsghqVdJLhw5OsjpqXg/DJdVs0jH1hhLbUvYZlQUhxASVRWZqfzLGqEFudz2MEKWmcne986OrjhRPfdd/MeSNd2Ogz6Ihh03sOvD6nGU12eihi790YprfVwB2efprISarf0xo+9wM8VlQWaD/Jk5RPrD7jWQh+m7Kru1z0HdT+lhu2FQ3RixiEUp7D4UN2zJSyBE6b35/xY6Z8uCIpfhbFDxAB+docjvR/FBnTU/DOSnVzhzn1Q/7WkyDlHKFTKJUDxfmWTTkGAb6T5wuW7cGH0GL1QYfUt5UxvgtcrySoOv8xupPaT7FJuGlUBgcWRBCTHBkgfjbt1OX39YRy1KM/aYkXTZw32/mItSHft2lppQPuYasfThEZj+Tt6uOYxceweWyx1w2HZwNjIbEYTRkGmuJhnBkgZ/XvnOctJB2t/gnalAYob7xP7vbct6wfU/Nlq6R25zREMtvLOc+RTQkBfRZNOS4Kfs847VGRmJOs5KUDikPwT+vIRlj22uCyoIQYoLKwiF3uNLP6bDWX1NYdQw5c1lK4razdHtT1E8HJ1k9uZzXQN61Ti2+jD4fBh2cA2G6dxyme9vk6Ev3dv/7x4yNjPWF3FNfI6sZWaS6gUqFsGp1zrn4yqKGUGUsjOvSddPVEg0ZK8NU+bdyZDGl490OH3rSreV3lW0Jo9Z0M7r7/M85E8x8f0BXPbFQZQrZxpThjwD6Esz62jb0N2Ogg5MQYmI1ZgiQ3oQoYRrUNrIYStcTsgZqTasv1W+cok6KUcvNVyViuifTlefuT1D3qkYWUwnZfinLDTkGfSz1loiG9KVPu/ssZVqPtcrUJVuXPyu1g7PPd9OX7xDzY1nTvd16QufN/+3lsocrZZH6KB05iVGrXDmgGUIISc5qQqekfmp9cs8ZbqyNKaY2zZCR1Dh0rSVRagxz+YvGyjGHb6M2hvosaIYQQkxwZDGQuVKGp9KX9pxzgtNYuiIvNeS7xPq3lGxTMpVb6ODMTA03Wh+xaeFLWHSlVrat36gsCCEmqCwIISYYOh1JTbZ+S192aM2saUWppdBGQ6zQwUmIkZKO7LkeTk/q559R1R3LsVQWhAygxhHlFBgNIYQkh8qCkAG0oeZt8m20UFkkoBbnXIiQTG3OhftXEzXIY5lKXoOcQ5gq71YpixQntyuzr4Y5DaFtoXUV/L8aLnx/Tc/SSrhPoZbqt1IKng5OhxyTmfoWk6lt8Ru3zhYufhOWp/1skSPGmBTurjK6lhHk4jeEeORQrn0KcI4oimUFrb7p94yGEEKSwwzOzNQwQ3UMNcjd936MmIyW94lMlSv03pc+uaaONrrWdA2ZRVPhyAJxx1rK8v0yLXXG5Mjp3OpyOsaiKpY+HNMGf4ZsrL4umXI5B/tuTl/eoftjx7Z1z9HGXp+FiNwL4MMAzqrq+5ptdwP4AwDfbw77M1V9vNn3KQC3A3gdwB+q6hN9QtBnQSwsIXvSfdLnlLNPYcRkGeKzsCiLDwD4EYAHPGXxI1X9a+/YawA8COBaAO8A8CSA96jq61111KIscp7gpUVDYnL45IiGuOVYlrvvunlTmyH+9lYmawRnajQkZvqEZBwaDek1Q1T1KQDnLIUBOAjgIVV9VVW/DeBFbBQHIWThTHFw3ikiHwdwAsAfq+p5AFcBeNo55lSzrXpyhteA3U8Q/6nTJU/pZdxa2fqeXDFSPMlj5fj7cifMufV3OThT+hVC58Hi4BzaJ2OVxT0A/hyANv8/DeD3hxQgIocAHAKAS3HZSDHSkcPOjCXLdHmzQ+Q2Q0IXeivHGLlSRAFi9cXWyZxSn4VQm0IJWr7sU/rCdd62xJRE7Ny859dfMddnSsoSkasBfLH1WcT2Nc5NqOpfNPueAHC3qv5rV/m1+CzIOokqMREgUVLiUpOyzv/aP+HEN36SLoPTVxYicqWqnmk+/xGA61T1VhF5L4DP4g0H53EA+5bg4MxlhlidbbU4MQG7syy39z82wgHsN2UOB6crzxwOzilp80McnL1miIg8COAAgCtE5BSAuwAcEJH92JghJwF8EgBU9XkReRjANwG8BuCOPkVBCFkGnBvikMu+DdW1hNBpyAb3yR06DdXflXMwx4goNvKyhk59WYfWbfl9itAp070dctyAoUjC0LpLKQq33ikypLo5Y87MFJ7/KbKFtnXVPzUy0mUihhTWWKgsYEvumVq+X6blyTxnIpGVkG+gb2SRy9kXk8GS/lwi/NzXH7Hj+863RUGlCNOuxgxJdQPN4bW21luLQzNG17C6lOyx4bVL1003pxli+c3U/psqf9J07xyk8llMjVnP7eG3RENilFQkQ6MhOZ7iY6MhUyInFllidVmjIUPlyhkN4axTQogJjix6yithjoSo3URxKe0f6KJW2eYY8VjgSlmkGCkcaaROqCww/wV+7EL/4je14svpzkcI/eXO4nT/urZbIyep5Ep5bNcxXX2QmlWZIaROlhDpqZEcSYI0QwghyaGyQL1mSM6hc4yhZoh/nKXcKbINNUNyDNdTmCHWMmiGEFIhJc2puZLfntTPP6OqO5ZjObIgZAt44nvPTi6DIwtCFkRqpycdnBFS2ck1EptMZPEfxH6fm5A/xN2eW5aYP8A/bilMlXWrlAUhZDw0Q8jqiTomuQbnoDU4uZ4F8q5nEarLpdb1LKxD2BzrWXTJ1LdSlrsNqkn60i3DP9d9coTkD5UZW9Cna06Jv98v59iFzaxTKzRDPEIrMKUuf4mkWiUrBWPrzyF33ypd7vXl/k913YVWYPPr65K1C44syGKYK9cgJSWdsqF6U8rBkQUhxAQdnJlZ6qSqGuQO+ZQstn1fmXP4LGIy+r9zj5tSd9AnY6hja5fVI+tmKWZI19KJc9brYnXYD1EW9Flg/qdm6CK3PBFrioa0n4Hpq3v75VoZsjCvVbZUfdkV8erqE8s57huZuMRGFCnayZEFWT0l8ixCYUp3f6o6hyz8HDqW6d4Vs6T0YJca5O6bij3kJgHwszyLFHK1IcpQari7398+pX53xOL3zdQwaQgqC0KICfosHHL4AmJe8yHD1BKRiaE2cxdjh+Qxe7/r6dzp5BPT6NtEzC/VbouZKUNGFk9871l86B37d5Ufi8CE6vP5Ic4/Y62fPouBhDq9lrCi74W33Mw1RRj60rhzy9Inw9TpAWP7PuRMtf7OV1wMnRIyghqU/tz4SpBvJNtianBEpmRt7SlJLNRshcqCEGKCZshIarL1W0I26VKYav+3ZUxN9x6aPNW1r8vp6TLlnA1ts+/TGmKGUFkQYmSKT6NdMNeNZgytG/h5ZeJHR/p+H5J9yOreVSgLEfk+gB8D+EFpWTJzBdjmbaDmNv+yqv6i5cAqlAUAiMgJq4ZbC2zzdrCWNtPBSQgxQWVBCDFRk7I4WlqAArDN28Eq2lyNz4IQUjc1jSwIIRVDZUEIMUFlQQgxQWVBCDFBZUEIMfH/SUZ9UULeBC4AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 73.10574769973755 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.25985088e+048 1.46000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [1.46000000e+002 1.34219708e+128 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.25985088e+048 ... 4.25985088e+048\n",
+      "  4.25985088e+048 4.25985088e+048]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.25985088e+048 ...             nan\n",
+      "              inf 3.01062958e+267]\n",
+      " [2.00000000e+001 2.00000000e+001 4.25985088e+048 ...             inf\n",
+      "              inf             inf]\n",
+      " [2.00000000e+001 2.00000000e+001 4.25985088e+048 ... 3.01062958e+267\n",
+      "              inf             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 73.0615222454071 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 10000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.25984109e+055 1.46000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [1.46000000e+002 1.34217926e+148 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.25984109e+055 ... 4.25984109e+055\n",
+      "  4.25984109e+055 4.25984109e+055]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.25984109e+055 ...             nan\n",
+      "              nan             inf]\n",
+      " [2.00000000e+001 2.00000000e+001 4.25984109e+055 ...             nan\n",
+      "              nan             inf]\n",
+      " [2.00000000e+001 2.00000000e+001 4.25984109e+055 ...             inf\n",
+      "              inf             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 73.18728590011597 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 100000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.25984011e+062 1.46000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [1.46000000e+002 1.34217748e+168 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.25984011e+062 ... 4.25984011e+062\n",
+      "  4.25984011e+062 4.25984011e+062]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.25984011e+062 ...             nan\n",
+      "              nan             inf]\n",
+      " [2.00000000e+001 2.00000000e+001 4.25984011e+062 ...             nan\n",
+      "              nan             inf]\n",
+      " [2.00000000e+001 2.00000000e+001 4.25984011e+062 ...             inf\n",
+      "              inf             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 73.13353490829468 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.25984001e+069 1.46000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [1.46000000e+002 1.34217730e+188 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.25984001e+069 ... 4.25984001e+069\n",
+      "  4.25984001e+069 4.25984001e+069]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.25984001e+069 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.25984001e+069 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.25984001e+069 ...             nan\n",
+      "              nan             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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l9cRcG+J7vLS6ukuGkteGDDF2bYhv/SuXXLKrHrOu2GtDunXavkva6uLz+kK1LBRFEVGVg3PscvSU5vYUDsIQSnHQ1opkxXFN6HtDFEWJzmx9FsuGzepK6bdJgSubVa7pya4sXUqxIkKt2LH9qMpiJtguAjMkuaVkxWGT1/Y9pywlEirb2GPSYUgESr4BW9lodXVn5qN0gvszYpzF+vZJcZ/VspBs7HWqykJRFBFVzYYA/is8Y4c0D8UW5JwVGRpX+8ZMSMrFJiSVXSpCVubmDPeWxmP01dHlcto/39mQMScmx4rBWUVEKsUx5bVVnWUBxNHmrgi7voVCIXkrJNjad81k9MkqkUdqYfjIbPtNWlfIMUgYikgNme0YihANxecBNsZZbcu94bOQrA6Pl4WYZvNQp6d2YJr1uz7nkkVKnxwlyBgrHF65QHXDEEVRpqFay2LZ8bWoSvSjlChTH6WmJAit59jKzcu1RD22WWnmd1CTVclBLddZ9coitrY3ZzNqe/IpSkqqVxaxmTJzVAxa+Ws9BknOhinkmAOmxRxyjVTvs0gZFFPjBVO7NZRyXUhJAWBTMNZiVstCURQR1SsL9Vl0aBcqZXw7V1S6ckc8jirPZ0RobW3nP62teS8srFJZxFhy3Q3LtmW7HjPEGcq+Ld3f/C+SpU0IG5i8duwN5dpfXG9X7ghJeF0RpX0ypRiCTq2sHn35AQAAnz8PPn8ej776oNf+1YZ7m8RMeGvWOSYBSg5/x5Th3rFIFe7tamsoce5Q+ynCvX3QcG/FG0kGaJvlVBKSVZwxHdg+N5et3dqDsmzrjZYqKEtRlDyoslAURYQqi0rpWx5uc4aWGKgl8QnFNP2vu+yj4rJT+yZsbcfy2ZjXx6xeMuTqJNtNEdqh3bG9LSNRyvGqT92h07qxjyFGXan7tFv/9osvjq4zBdLZsdh9vhQLydqbeYy2NTu/6yG2JcYJ8TwPtdsiTRLjkyQllFSzPbmdg+Y5K8W5233AlSKXlCqVhaIo+aly6nRM0lJbHeb3bgBP6JM8dqamXOPlVO1MPd4vgVIWyYWiloWiKCIGLQsiug/AXwJ4jpn/pNm2H8C/AHgzgKcA3MLMvyEiAvD3AG4E8BKAjzLzf44RMMT5FwOfpLOKsgxILIv7AVzf2XYngFPMfBjAqeY7ANwA4HDzdxuAe+KIuZeY3v2henLOhgw5wEKVWOyp06G1L5L+muKVDGPO5dRDqRjtdxNC+0ydDloWzPwdInpzZ/NNAK5tPn8VwLcB/E2z/Wu8WHDyfSJ6PRFdycznpAJJWfbs3iFTpzGJkd07pQJOkd279nDvbj25pk4PGArgGQAHms9vBHDGKLfRbFMUpXJGOzgbK8J76SoR3UZEp4no9Gs4791uqrgDW8Le1MMQk6G2ShmGxKA0eYaYcqaohGFIqLJ4loiuBIDm/3PN9rMADhnlDjbb9sDM9zLzUWY+ehHWAsVQFDkrl146tQhVI8pn0fgs/t2YDfk7AM8z811EdCeA/cz8KSL6CwB3YDEb8i4AX2Lmq4fq981nISFnbk7JUuu+elLk4+jKFpLPwje/Q98xd6NkQxibb8IVOWuTyyf3ha3PfOsa6nef8+3Tvz75LAaVBRE9iIUz8woAzwL4LIB/BXACwB8CeBqLqdMXmqnTf8Bi9uQlAB9j5tNDQqRSFkAex94Ujq/YN9wUodGlhYyHJPRN+VAyiXHd2eqImvyGmT/k+GnP3d34L26XNKwoSl1oBKcyHzIkKbY51lcPHZRXYCRTXj108ILMRIs/X0L2CWT2yiKHx702rz5Qp8ylsWx9WOVCMh9yjCd92pA621ITMt7d2Wdl307W7RiL+nzpOkt3Pm8edzoYJXX50loYjzx9t9WRbHV8bh4frNOH9a0TvU7mmNdVldm9JaS6iPsyVOVkrIPTlrzV/D0H0R2chhJLJY/tRrzhTZ/E5pkNWSPtsGN7C6uHDmLz7LmFzO1wwnE/Oh2cRM59JHX4ODhnPwxR+skZcJacCO8Y8eHYvlsAQK4ogF3vdNk8s3FBZmbxTb+LjA97VRaKoohQn0Vm1GcxHqfPwhH4FdNnses8NU91W7tOn8XAUGfUeXF8D6nXxuyVRa6gGSkuWabweQTnCjHM/Sn6trtycuiztK6U8sRsr6++oe9jmL2yKG02pBRqlLkElrnfqpwNSZGD01Vf6GxB6jn4XOteUhIjXNm3Pel6Dx9Sy9WWGduurY4f8Cn8ll8QRXapg1NRFBGqLDqUmPfBh1b+Wo+hK/dUx5Gz3VxtmXlaQq6R2fssfKl9TDo3+ac6ntr70UZ7TKHHVr1lkSNTlqIoM1AWym50GCKve9nQYYiyi9rN51KGIXNk6YchiqLkoVplkXMBlLUtI4lJzKQrQ8fVGza8sm+vidnI5jQ7zePIzC55GjnWt0/ukifm0OF9x+4aLENraxfkMOlso7W1RdlMxBhamtdG+xf1JUOlkmotRTdc13mSzBWOEVc7Dl0Qvce9vbV3eyObs58yr9Q0sYWQJw1XPjV8X/D58/Z2O33blstF7LD0lhwvGSoGnQ1RpOj5HEeVyiKWlpUsPBqTRWkMXWeUdNg1djYkltyh9aaYDQmRKYVimdpZO3Y2pEploShKfqr0WcTQ+tInWGhbMZxRtv+piSV37HrHUIpMtQ+DqrUsWrM8RT6C0CFAqvZtZftWzdrkjR2oNTRjIx0yDdU7Zhhoq0sqW4xVnlJ8hpdj22nzmLRtLtVsCDB+LGjWZct0lPqJYGvf1W4pT6c+OUqQ0SbDyqWX4lu/uz+/MAOU0F8Sis5nIc3mFHMaNdWUbKnt+tBVpN08DNdd9lFsv/iiqK6VSy8Vl5XIBCziKFZPPWbNQdIqCpvFFeNhM5Tarv3exmY8+vID+MB7Po//+O5nFjKu3roo7DmVvb59EtvPHMYNb333YvdXXvHa3yefRdHKAhjOWWn+FnLD2SwJk+72kLq79bl+62PMMfqSaibAdhP7MGaGx6bcbOVCkMplUyASuVyyhV5DJpr8RlGU6FTps4jhr3DNhnSf4LFnQ6aaXZm6nRJnQ3KTckVtDqq1LGLOUAzVk3M2RFrW90LLORsiJeXNkuKcTa3wYocMzG5tyNAJN51HMayMIR9GCvr8LzHqSkFKC6TPWehTj2SbVI6U5L7OQtsr3sFpI8UwxFVfqFMu9QWQ6kLO+fTM5eA025vSwdnXrjo4FUWZDVVaFhJSTTFKog5zEHuh2BRxHjGejDHxkcccLubosxjXna0OfYu6spTkSEbTOk7NG4+vuUq8v5k0h6+5CnTR6xY/BCYhotV8bsfiHZyKIoVf20zehu3pfNHG85C2bMp40cbz2NxqIjZ5O0ge3sqXvGi2yqLV/inMxK633qeNoYhUaT1jZ2ukkYPd8n37+/Zz6DG4+nt987h1Nmkob4VPn3f3BYBHnr7bGmFrneXaPO7Vhu23XbN3WycGQ8376vXJlDV7nwUQd6wrnUVJzVifRXtRtWbso68+uOv3HNToszBlWLn4YnzrpX9Wn4WiKIrJbIchigzeTD/OnxOmWe+7wrN2VFko82FlX/Js5Ta/weqhg9g8syGroJ3x2N5a7Hf23EJmauKifN0CRP77BDJrZZFiLCldai1xnOWIbXCFj7syUvn4enxCs83fkoWKGw7ObtuAn1PZ5Xy17TMUri+JHF3fOrGnjiEkKRViUpWDc+w6gVg3pU2O3EFNrpt6qI9KcdACMsWUs1+7OSZs27tMfb7H1AOog1NRlATMehiSCvMpM8UT2dVu9wk4lWxShkz57uchaG1t1JvC+qyHPuuCr7kK9L0fi2UEFm8042uuwsrpX4Bfe3WXL8Mlm7W+1VUvJ3W3z5fqjWRTYeZLKCWJiblUvyvbyiWXYOWSSyaTbQhT9vXtkwvHHYkWQ0aXo5Vh5eKLsXLxxdllSEXoCuqWqnwWgJ/fovuEjfHEHYqQyz3G7uJ6Wtt+t9VVcnDZ1EFZoY7sGMSImLUd3+W0fz4Je210PetjnJ4ubOa82dbqoYMAgM0zG9apsxgRllK5WlYPHcQjT9+9q2wrW98+7XGMkTuUbn8+8vTduOFNn9wlTy4L7tjKzeBrrsJFG8/vCuFu5TO3tYvH6Hs/niwHSIx2fRyc1fosUj0Ju+Pldu1HF1M5iOfYBQxdAH2/b57Z2NMfQ7LFlH0MrRyuKd0YSKYV6Xs/xqal3W4/SX0UseSK2U6o8lWfhaIoIqq1LFJR40yCSYxZhVxIfAC5fAJDcgDTpjKM0bbN77FUsyEpzbdSZjmUOOj5HMegsiCi+4joOSL6qbHtc0R0logeb/5uNH77NBE9SURPENF1qQRvSeGzMKfxSqXPAWoeg1m+tJtFMlsT22cxpmyq/pPIFeP8mT6Ltk2fVwFILIv7AVxv2X43Mx9p/h4GACJ6O4BbAbyj2efLROSfK0yAOR8eE/OkmEOSXIpjqC3Jeo0SFYOUrtxTHUfOdnO1ZV7XIW0OKgtm/g6AF4T13QTgODOfZ+ZfAXgSwNXeUimKUhxjHJx3ENGHAZwG8NfM/BsAbwTwfaPMRrMtOrlWbOZ+SkunTn2Pu8QhVckBYDam7MNYbU/h4LwHwNsAHAFwDsAXfSsgotuI6DQRnX4N/vH8qYYhJiUPQ9Rn4U+pPgsJtfgs9sDMzzLzFjNvA/gKLgw1zgI4ZBQ92Gyz1XEvMx9l5qMXITyFe4yLqTvFmNvB6WqnRGugZUihTS27S4YSZOtSmjwugpQFEV1pfP0ggHam5BsAbiWiNSJ6C4DDAH44TsTMSN/fYJYLeN9DElb27XVwDskW+L6K6E/ZRo717ZO75Altx/YklrxXhNbWLsjRla9TLtZ7SmpxcA76LIjoQQDXAriCiDYAfBbAtUR0BAADeArAJwCAmX9GRCcA/BzAJoDbmTnfiw0URUnGoLJg5g9ZNv9TT/kvAPjCGKF8iBHhZ2rZ9r0Og/4QM+/AyLyPrna8tb9NjiHZEuSsDHpSRuxPF4++/MBgGWc+jI5MY/Jm1Er1EZyxfRbSulcPHdxZKdn+z9m+SybJtu7vY+XvEuIXiNmfLj7wns8PysbXXCXqR77mKq/XFs6BateGxMpJ2K3Ltt266vTsOevnse27Pvdt65NjSLaxstsIsSxi9qeL//juZwbLrJz+xYVXChp0ZVo5/QsAi3H4slC0snANMWzTgrbtfbjqEJcZMJtD8w5I8nQ4f+sZhjj7prOPpF/6kIYu7ykrGIaELq3uywHS7Ut+7VV7JdtbveW6stmGsZKpftv577sPXNetbdGYbZ9Zvb7QdpJdneejNLqWyc6++25Z/G5Jzb6rXfM9D5Z3N/gqCGn5vgsfRHvlbmTr22fnODzljkG3P9e3TizOgSFPqJLY09bqrb3vGj22cvNi1oO397xDtO3bnW1GzsxlSX5Tvc9CUZQ8FD0M6SNmuPcuDW2xtKwa3Cw30jrzeUL0lmXe2x9DshVgWQLYkSNpDgnJLItr2Nbtp4gzNqkjkbvthFpq1SqLZUfXhuRnLmtDzM+a/GZkfaWtoVDmTS3XW/GWxZBG7WrK2O3VciKVesk1DBlL9ZaFoih5qF5Z5MiUpSgpqeU6Kz7OIpRUyXEkwVttOUkKPNf+IXJI6Av0kpY195HEv3R/iy37UPt9AVnm9tDguaHtQ8OM7u9jcmn4Dmk0zqIhhfe6Rg++ROYS8zxMibQvlqnPindwdhmzyjRHKj6fNkq60LoZlCT4xETYHNGxzW/fBXmxYnQkSxJ8HPVSfI9rbH/P2rJIMQ3qu7hralx9UNtx5GYobeEyMmtloShKPKp0cMZYnt735OgrJ20vV/iuFOnwaLKFZAJiJawNlWXIgZpKrm7Z0HZt4d5L5eCcbOqU6MKKzfb/1BDtyL8j+5Bs5nFMSSPH+vbJXfLEPL+Sumh19YIcXfk65Wg1jssvl4I2r+uQNqtzcDqxLBNPSsSFZNHQhWS9bD9zGCt/8Mt+MTY37e12+qktVxNjF5JVb1nsUMpFrxTLDW9999QiVM18lIWiKEmpXlmknMYqeYqsby7dNiYtccpP4iyMOZ7ffuUVcdmQiNaUxDh/Zqq99viWaol6bEq8qWwMxQHYZnVKi6OQ3JBTnYvmRnQHAAAB0UlEQVQUsx4+bdnajjXrYl4fyV9fWBK6kEypnVqus+qVRewnj6l1a7AwlPqp5TqrXlnEpkRz3QeXz6IWUvosxsgxh7bGxlmoslAURUS1yqIdLqTUymaIdC5TcagtyerFWpy0Nkp2cNaOObwOOb4q14ZIiLF+ZKheE981I0OJWELlGMKM3rMpW0nyGlpbw6MvPyBK2tJHyNqGrix9nyVy+UY0utZmdOtw9c1QG77JiYYSELnkafFZGzJ7ZRH7CaGZsnbv03ehuspqpqy9ddWQKWs+a0MmxHaRDt2UXVMwlXLzRWpZ8PnzXpZFzOQ3LmuiW2ZIrpjD2D7LYkhRhlpnMSwLH6r1WSiKkhe1LCIwxTAkFaKn3Jb9ZcCphyGhDA1DQuvsyy0ROgUsuW66dUraitHns7YsUtyEY+t0eaJTzWBI6/WZheHNzT2e9ZwKzzaksZUZI5dk1slWztamtK4YpDwPRTg4ieh/AbwI4NdTy5KZK6DHvAyUfMxvYubfkxQsQlkAABGdlnpl54Ie83Iwl2Oe9TBEUZR4qLJQFEVEScri3qkFmAA95uVgFsdcjM9CUZSyKcmyUBSlYFRZKIoiQpWFoigiVFkoiiJClYWiKCL+H3AAV/QsY3KlAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 73.54867720603943 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 10000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.25984000e+076 1.46000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [1.46000000e+002 1.34217728e+208 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.25984000e+076 ... 4.25984000e+076\n",
+      "  4.25984000e+076 4.25984000e+076]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.25984000e+076 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.25984000e+076 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.25984000e+076 ...             nan\n",
+      "              nan             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f548227f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 65.47375583648682 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-10, 'kernel_type': 'size'} is: \n",
+      "[[3.20000e-58 4.80000e-59 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [4.80000e-59 1.36000e-58 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-58 ... 3.20000e-58 3.20000e-58\n",
+      "  3.20000e-58]\n",
+      " ...\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-58 ... 1.40592e-55 1.40492e-55\n",
+      "  1.42048e-55]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-58 ... 1.40492e-55 1.40860e-55\n",
+      "  1.42090e-55]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-58 ... 1.42048e-55 1.42090e-55\n",
+      "  1.45508e-55]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 65.12140083312988 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-09, 'kernel_type': 'size'} is: \n",
+      "[[3.20000e-52 4.80000e-53 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [4.80000e-53 1.36000e-52 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-52 ... 3.20000e-52 3.20000e-52\n",
+      "  3.20000e-52]\n",
+      " ...\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-52 ... 1.40592e-49 1.40492e-49\n",
+      "  1.42048e-49]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-52 ... 1.40492e-49 1.40860e-49\n",
+      "  1.42090e-49]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-52 ... 1.42048e-49 1.42090e-49\n",
+      "  1.45508e-49]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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KjNkuCnE+gHgNORe5GHTeUddA20a7XQlpuWvjHFE9GmR9oqND8GIZGkyaBTkCN634J84v4nN1BzNgMgG9OpFDRNJeeA8ynoi6ljlYLmO/AKA/PQd9/BXQ85fhviQf8HoNOjqKz1c/aL0OVQWuHKjtwMsV8N4jufzf/F7SKs3Y3OExMBqBT07j86nef4L+ax/A/ZunIJ3z6RS8WsXFK87rKPgsVuvUBwD0bPcl4GEuFrvIVVGLrDScj+ofl55mCzMO92PPIMXXM2+yLSGpz1m4qvdAXFRyktbECq5wcM3pGIj1Q9TVDRxA3+cqqfZTx2fOjbkPhRnCTZNCc2oC6VhDnzjE97nvUyKS/m61I2tOGLOMu0520sEM1SZzcKJpourNJfLQ+2AuhP4ultG5l7NnyzjLN4HbTtDkcZwMrNZyTeng5Eba02O6kLAHXSwz8y06QtVxqm1bx+1oJPltzMB6DTpfxv5Gx63JQOXVGlR12XPn1QruZAG0yfRgZlkYo1aTw9fLDQxfCjMkMx+GMg2v0Cwi56XsgOIFp5T91zTBPEg2LzmScwJ3I4DEtVjAdaNG4NLHQ3Wq98DM6WeItxvs00tYVbJza8qzaS/uFvbDD9dYzSL2zbPRmFwai3fpvp3u+uMEByafVOWwmwMSdZD7V5lmga4LL7W2pY9Ich/0Kdg+kmoQhWYBe65nsMmfoPE4LoA0rlO/DuaiUbgKNNK8Dy/jaTtgMkm7dt9LNGQ+AxkNgqYTQDXMAc1Cr4+7c9OCjw9AxmdB41oWkcMDObZu0nsYrmONSIT3gI/lXDo5Tc8Sbfp5OgFGI/F5GC2i++AIo3NDgFPXAC3Tc9d5GI1kHijXLHC+e4xjHw3Zy172spPQTdFgdynH9B7/cfqTg397Y7R6o/pyWr2r5LpOUXWwWs0ASOplqa7fF/T5sn5vy2rVn4Hb0+pdt2+X9ak8xsO0etGcu+mclhwgA87qMru27F/ZryFavQ0hymHptq2hPgyM75/w93DKL3Z6Wd9eM2TXKIeaIUTJqbXNNCmviz/S5vEAwtmw6fWduIKwNyNFvaTtdH4AA0UvfvCWD7FOVRW4GUgHvwPC3o1+Zyng5t7OZQCfaIsHJyGABEYqX2ZH4WPAppf/EsJedUpbD78CtGKfgtMzbjJ9L/6D0GZcjPs++jYUCMfNlg/czkP50fse1eFBvAeACNKLc6m+Hvt8g+kazz0IZsh6HU3U2BPnIjDPhk7dZAI6PBAHaexzcPyqQzUSDcnzejcJe3nLjmr+JpLwEnEH2yW8mDnfYFZi3XEw7IDbUSxRbBT1XTg/vBsA8BoxKLgQMmfmLTH+l8lm/kDiRoghyKqKjtpyzhkAX5TO1Jx5ivhm4cq4IFmMi+0vC+6DfbfhwEYf+mYdvVUljsxtms91+mWiZ9x1mw7VGALPnYtKYKM+D79eyxhcs7lRbLTrQU27qXV4FmctkMK2dwBLf3sXi13lxqCsIuYdd+FL1MVt11/GcZFFUhQcNHA7PWYg4BnOIst83EIyU/Jl2L7tAoEv2yn7pqLApwJYpv23zNoUuCQ3KCi2ZZHuwO6dnULDizJFxqv872RrKLVdxnU5OH879MsvV6YNMzdDYD39rgt2b18+Z+/yhdBybcR7tfCLYuO5bKPUDXjP7r2XvezlPuVhahbbEsmuew8rA6XxNq8xvpArfBbbyGi33X+jArgxWeT8ZDNHXoJ78lkMEdVm41B0INv2TP81UUx3WSrMEK1eHsZTNLbdZzHkByInbdt+uYSIjDiYATo7qgPSU02qsuzfjj4LN5tmEGolxrVh8tim+n2cE19G8LOogzMmEhZaLod52yhfeCBFhjIEZ5EAF+WdL1+4Td0e+nlIrd2WlbpxX3khIyiLNxmWoyMVMC+Vj1mGeRvGVDALTPzoCy7M2JsdODi56yKaNI0z4SfieaiyjzSO04qOg6TPQ76W5NNJGaIJ4VqowMyDZfsiBZ3+HBeSAUcz1blPyTuAYNq0HJypfULoV/BP2PvGLOLWvCMuAJW0v66Ki7Zm/aZ2XJgfM8/kEsbG9rcL8ziQPRrfL3VCBn+Hgum4afL3QccQIn1UIcPccNtlPgsuF1tj3tJ0AhgcDADgGowKb/9icVPZ9rHpsYKsVXdUmwq+/d4ug1/LS5+v0JryntvLBibewtyjNbBr0x9dFHyf9ze81BscwSYFHkAA4TgAfd7fMAbVUrQPYIab1HFnsnDvuGsjT1Hf2Lm2hK3jfCCNO1LTA1nauqAuDVxZnYAhGqKRozL3wc2mm6X89N5NC6oc/Do9DzeuJbJk4fIaAbPRNUj+Baoa0HCmgerTo8eAwsgBibK0bQSvRcQqIKnigDxPR6CuAzct3MFczn3+ctCpTuNaUtSDAxQA3HwOeu8x/LPn6byiLEFMVR+NgEq0mQwU1+zuiXiYi8WQGbJzqFXOi4uCrvRVJWqzRTSWqntQ83NeCn3pi2aqfCeKbZjQnUVV6vGYvaihNYsahW5ylHESRIxD5fLckN7Leew3Q5xhsbHjAJEgFYvthiqXIytn05Q9WdfpxFazNjedbDof8WdAdm8bsg24AZjoQjzHqPCC4GTpj2k/IkuteE5o2HH62LXvNK5jJCLm7vS9fNQmIklVJce0v+NazIO2A44OQJ0JE1fBbAgLAFartBjq86kceFSB1i1AS/BRCJ2+Ohl0UkYEp428zKbwjw9BJ2f5ebSWhQFIGue4BgKak6bTdOOzPYJzL3vZyx3LW4/gvFO5jEnrKkdgeQ8V5rzS1SAlnLn2ruqGDFUOu6xuyFC79hrOzZMNua+6IRvN5A7g6HPZ5mzcoW5IdAwO1A3J0JFb6oZYKTk7AAySSG+tG2KzZNXkCuAs4JK6IYEdrUTN0mSSFzm65PlFE8X0/dfX/ytO/fMHjuC8THYxQ+wLOeD4tAg/AEn9VBt+vR40Q7TYS6RVayR12i8W2YNyk0mofG0ccCaFnJfL9IIYm9XHFHVJe49FYwz9narLpQPOJqoB8uLF+9jyeDovBl6ulcDdwTyaG2yTvIwZQo+OwZrwVJghvmkHX1adDzv3WWp/VYmtX7k8O7OWDE47hmiaFGaIOzyIKeRpEsQM4fUaNK7Rn56n8w/moHENH8ZCk0lIJOuFoi9UKI9Jf44iWpImYhbwxQXoqx+BXp6Y9hx43cA9OpbrLzFD3LqVPj+RFHX3w98b9Je5x48kxd5UTaf5DPzxB3C/+2k6FlL6h8wQnk9BL08yc40+3X0J+HJpFpfJrpqFnquyzV+y7dhdaRZDfQA2d/pS7Ln2fMvZ8To1i20guFLTGRrjPWkWl9Y6LdnAQtjzdWkWQ7VOd9Ys1KFs+nAdzWLvs7gLuQrtee/t75D8pWHK27J+vS4pwqqvvd8FpmOQ3avs49su7nZ9fXBmyL0VGboKFj10X/3dhkcvKzJUwokvw4jcGMZeYoKLWP/GuIO6f1WRofsoX2ijJkNALCtWK7hm+cJ4q4HyhVkzBpaehR81qmU0J/YAiOAmk61Fhgb7YzER9tyCD2XjXn0PoN8oMjQIztsm7Dd5Wvdw773sZS93LQ9Os2DFPww5OONJRkswx+1uHzUA5ZUMHJGKR/DLZYI+F/Z8trqv17K7aJpzaMMdHAgE2God43FklvLLVeZ0dEdHAHv0wdnm5nOxRQOHZgYCGo+lb23OlenGdYaz8MuVAJGaVuqSIDgykez7yM0Zdsfq8aNNFu2qEkdjcHi6R8fiFCwAPtw0G2MGxH53s+mmg7MebdQfoXEtDk0dUwCAcdPAaRp3cEJazlQgOF6NAzD9wQHrNTCuhTsUADzDHR6AJmP0L1/FfllHd1ZjpKqAyUQYxJEclf3JKao/8m8DT23tjkoYwx6LgxOrdTQBeJY4OFE5AYtdLOE/fCzHf+dHycFsdn13fAwaVcIkHrAio699Fe2Pf4jRbxUOzsUqzYuaU/UI6P0mB+dnxkF9hTy4xWJnucKsKAv0RM7MMl15INszQ2Zy4IYs2tGPJnOStV3iXihSmLMoBYyqr9dbx10gbNkYQ+lk037acdnMTfab15g8g8T/GeDxystwsRAAVmFaXMrBGdK2AUTma5vanQhoEh+q9kc5TmNfV4j9iZT8AHB6fikHJwoVnJWiTgmGmjaOwy7GAMCuAyk3hs5JGCO9OstNkcrJebow2TkuihQxs2wWL8MmZefV9nWxCAtYWkj54gKjpxPA8FlwQITGTdKGgj3LmG1/rlF+8d1ZLErt4trX++AFH/Ikl9iKHJk5mHRWLhR6rIeE4DyDiOP1FCpsDd1nqI3BuiQ2H6Ho5yYx7rb7+o37wrtE2gsIia7Cre19PWdzaOHzeT0Tw7cQowvFIhYXSfOzWTgjqtP2XRckZrCNNGn1sg2Oix7scv9I1NZ8SWwbIgl2c9Fr1uuEbnUu1vegRkPQyR9BujAVleOU7zODsdtEMt2Q2Gd9cMs1fDYuzjcinYfeR/6MTK7hs3h3FovbLBSZ1z2yhQyft6tDb5uEjycD9Wyr7WDDlaaeyb2Ko5iXsRGaNKxLqT6Fhl59qnVhs063tQHcnsTHUcrejMdcwsMgaRakzGNx13ZxTDygCV1LyGWRBiIafh/tMVvXw7n0XhCBXdGvy2p/6LhM26zHzUJwF/VR9g7OvexlLzvJw9cstu32VySY2VIAQHC69SbhqiggbO+bFxnyAWWYhyZpPM4K7ugxC76JfWg70HQCAtC357E/3LQpwc1qPFUFN0pgom1FhrD01ygyFByKFmCkO3YVslzD2NzhAfz5BagyDk72Ug7Qc64xBOYsGtcbDk44F9XvjVIApsiQ1PLwqTjReCz+A+bcwXl4KGhIA34j9lKMuO2AegTW7FBHoNkMNBmL8xMAVeKAjkWGbNJZJWUPIoIz9KU/7YH3HsUiP3F8jmKRITKlDWIpgFFInOt60HIFfj84OBfLaC5ZfYIO5kLnf3Ye+Tfc0SH6j9+Da9tUDmEylsQ1Hb+ZV/IevFrliWTr3Qsj32qxIKIfADiD6OwdM3+biN4D8HcAfAPADwD8DDO/vE07mw0PLBCDpCn98LkwDqaQ2UnjMWAgxcPNplobEbbddgX0WuHjdXDAIamYoxGgVbW6Lr5w3PfpASr0OMCcE9zbZrlWeT/1wwp1MKIoHNpz7G9Wp6NPH3t0sM6mMQtT8gicRAkm4+SlPz6UrFPPcjxOUCMLQllyMfQtW0gB+YjDghSzaCcTYO0i2S/NZ2Ee+zSG+Uxg710Hquu4iPGjw/SBWZ9F5cAXC9B0CrJw6elExnuqEPtaoNBdn+ptqNTjGIUBECHTdLFE+5UjjDU1nghcSwEh/15YLC5W0VTwB/KceSIVydyqhTut0HwokZ7xZzV4Fd5jNS+IhJhXM2TV0Xx8iIuvz3H8xSzOrT+cw525mGmr9Ul4WoN6Bp26WKMEAPD89VZR/xPM/C1m/nb4/ecAfI+Zvwnge+H3hynktvsTdpWB66PtP4QA3IYKdLldfF9CuivTju0N2eeOLrez9Zzrypb72lqhsU+vW8p52Pazw/BXR0iqhD7rbb6P8rqy/fL/O5L7MEO+A+Cnw8+/BOAfAfgrd9pCGc4sjwEJG7EN1delUCJ7F0lXy4hEVgk8YC64RYoC+F5U36IdW2lcFxy/XgvZCRBp2eUPHGuHxrZWZncH8rKEbZdfr2Nf+qyal29aaa/v4Zc6bvXQB01smc+bPz3L+gVHEia1VPdPn0t/LMuUDU/anIiw8PnFImkcxiEZTSk1j1brPCKjbfg+JXat1inKURvtJCSyCVFN6gP3oW+2enjv4U/PQE2T5rjthC17IHQKtwItRqmfGunoWox/52lKRiMC6hH8ap3MDyUhYg/3MmhHqrkwg9cNJuF+XkPFLuWBEBH8Fy+E/Ga5iserp1/g6DcZ/Oo0PZuz81j6IHJ5IGmSvmlAlqjHmlpXyG0XCwbwD0higP8zM/8CgI+YWVEinwH46JZtbErGhXkzn0XKmUj2PpuEHvtxlvfNyG+09kMB19VyfWRp34LdqwlBqa1WVFzPqWReXQP9OiT/+M3yhWbXt36XsjQgVS73TZTkN0URJ5pMUj3W8NJCzR699mAuH6FzqXxhGEcWui3MEC4Ic6jx0kYgAAAgAElEQVRy4CXH/sh5QlAT+zmdyDl9n67TkoVKUqP2+uEBcCHZvxbHQJ6lHmg9TmNzUt8kM02CeUm64JmdWUFZQA7KwmoN//go80uQ9vPoUA4o7oE5grK4HsmxrgctVvBPgsny8gRaazWLPs3noFElfQtDoMNDNB8dY2zLF07G4OUKpJEfNVfrEdD1wGp04/KFt10sfoqZf0REXwHwD4no/7V/ZGYm+7UYIaLvAvguAEwxv2U39rKXvdy33GqxYOYfhf+fEtGvAPhjAD4noo+Z+VMi+hjA0y3X/gKAXwAkRf16DXvjwNoCoroOgpNcIky9sm3hmYzIQebA4VCYL+oktLyehelhve28XAkeQM9tGgFv9Ukdl7E5cO8HYdW+aaMDE0DqJ/sI805oTx+vye5hzQU1IwKhbIzeBKi3mAcGyRqAYkRa8HnTrNKxERH8ylSSV1RiUX3e+2VMloqaiY0u2ESql31KwVaNp+3MdQVaVU1FnTNFP8YTzFwqZFz7GZGcHvTsBfgs8WRgXMt41bzhZH7RRfjkQvQNIW3cBc3O65ya6BN5D396KtqgVpUH4F++wpgomMGhjYuFoDiNVgIgIma560AL89l3uwN3brxYENEBAMfMZ+HnPwXgvwbwqwB+FsDPh///7k3b2N54wa1gbMIoluh2wG+huRJaLV1zFyhQsvdtl3g09TutKjEtTIjSXyzgDuaJlCS05Y6OhHDF2Oeq9gKAPzuP6iAvV3DvPQH6Hv2zL+R6LUs3rnLymuUKNJ3AEaUFzoQZbTSET06BWl5cF6IwKRdDFh3tg5LuVE8eg9fGDAGAcS1RBx3Le49AL09lvpRIxXvwei2hySrZ48LZQDIeDZNqRKiqYigzj4aso7+ADg/A5xfwyxVcUOtpOg2+jF6iMRoJeHIMd3Yh9r7yTXY9iFnmbTaFfy6BOfIe7vEj8OEc9Hufxzmh2UzuO6pyIp0QDWElJwrj7r94geYPfx2T3/kiPGQCT8dwpxcx34MW67iB+WO5zk9GYAJc51GdLLH8muSRTH/zh7IoVRWoTSUO3KNjiYY8e57m8esf49W/+wEe/cazOAc8n8CdLmT8nHwWPK1BnYc7vcijIb9V1Na9RG6jWXwE4FeCXTUC8DeZ+e8R0T8F8MtE9BcB/C6An7lFGzcTZuAqR7BF/W1xmG7Ar6+D8NMd3KLoyj5ah99GjkSqWSk1Osxu740P4x4l7myaG2JgxeKETPki8Ib4xp6n47xhWnTRofS/Qp9LGLtnAB6kSkTsH0fIc3Yvb45Vu9vvVqgcm7YzlNBo8z4qAvVyfjTWY/5Kn96dnre+ztQHhKrCyOPciK+G9TW5A5Krt5cpS1m4r1NFXStRX8bLMHSPktsQQXuoqqS+Azmr0lViWbGyvvqN45Z30hmHoeWBtGAqALv347qyrd9ITsg4hqGksYLBHNjiLCY3zPlxmbh8gYy1Owa4L7JErbaLIDSlL5SPUvNRNNfimv3R5upxzmCl2Bhbw2WgqBT3vWhUfR/f3TRWl0w3RzkbVjynghvXaUGWhqLpm+XmAIn7wrz7/8T/bztXUd/Dvfeyl73sJA8T7j3osxhisLoE7l3sfjSeZeq93nODb3ID7t3kYUGFRM/nG7s/jUYphLlax1AgNw3c4YGYHsFOpoN5QnB2XeZjUdj4VXBvXi6vAfeWnat6dGzQqCkMDFNekQ4Pwefn4vNQBCezOBPVdALEyRZCrxlhb0SuTpL9XcC9rR+GV2twl0iNN0KnOr/zudzPlC9Ujkt0nTgVbeW42RRU1/DKZ1FJ1a4I97YFi+pa5lyfT3ge/ek53De/ATwLIGVHct5iCTo2oVNNeJua0CkQnJ5L9D/2vlz+w8/EjCnAZ+7wQAiCT07jPFYffoDux7+C0e8+Te/4ZCycFfo9qDY4kkJLG3wWz74MfBbK+2DZs/UFAa6OhhjPODna+NgBJE+yfXDKq2BwFVpyLrt/SaIKBJZq68k3amYA22TYiyoUsSFK15G8dEPErtwUfBy+j9GCWInL0sKFa6z4i4IdW8lukcwQfvEykcMYfo44Z8bBGe9r52PlAecioziAVKSpiPLwhXJycAKqhWdFRFk0RCNKqOssGuLX4eNxbTJVuQMWS2DUJlNvvc5BSta8adpE/Kv91Dn+9JlEkbRP47G0WbxTlqWdxnUkNfJtB6fzGBezhGtBVUXQl6XR8y9fofJe3h2d67PzlHofaqnG4WiukgFlXcecfbiLxQAr9HX8L9ZPEHdYz2nBUdSfCeNFrgtTX4K7Lq91qhLIRiz/gCZkAfLgErDLA+MqvfxAjiDs+7TT9D2YKSsHaLUs6/jkFvEF19J/ZYKcLTEAhKiE2vKqWSgiUn8PZQJj2jcg/5c+CuPMU9BbPJcIblwnTadKnv+NUgBtB3Cfax/qQDQp6jSdyCKrTuFwPxqP44djEac0HmdOTWVAY43iFAWGaTTaIK/xaw86mMNZR2stlcM06hNzd9gLMAwQgNUszBE1sXoZrwXBSr7NnPA0mWwgOGk2A44PZSHTEwP7Vnxf9PuonKB5DesaANDp6wNlvRkZjF5cF6pR7MoFk9SlrM1ePth4bemRt/czQuizc2PdUYQPzJToi6ZVgUOQ9odrim6QsWo/AzZETlKNqx/s+5AzkoFcNb5YJKcam/O1/wORmowsBjmmIpuLwmGZn6OLp3n+tv8XfUQ/Wp4N+9FHxKnBbUQHp8HPiHZaoFH79PwynM3JaeaM1I9yIyoEJJi4MZO56+D0uSs2wzkTDekjoU2mWSwWcF8ELdZC6Asei3g8wOgzfI+NCl4hb+9iYVS3y/5uk2Y2PvhLxNZ9gBY6ZuOzaI0/ILJK6S56tWahXu7MI61eehdAYBbCPZI6mhp9cWGXhAsLRqTba0Ejd3+axdh49u3uXFVpB5/NBAuBvsh+7VNI1V6v8+qNpgL5cK+jWcQ8hzBX0cdkNJ648xufBdUY5tVU349ec0PNwh0fZdVdI8eoYl66Lu38sRq6gaOv10mzCECxLLQe6oOUmoWbTYH3H4O+SPyfsQj0AK0e9f2tNIt9NGQve9nLTvL24ixUSjDL0N/1b87gAHYd17Y03pCevsldecv7bmlL7p12+ng8Euz2+fGrcCQ3lV0KFiFpLEPmWlmJK2pn5bnXHcNGxGsLHkTxF6EPtp8bVcJsla8bzmmWSGjfm221Z2GiUUVUymoTEcW6Dd/jqqQRxyYueT/1u7ghzuLtNUMukw1AVX+9jxNJVYzOS5vKixBitE7KcA533aYZMlD4KFLKW7nEwSlZpz5GUdQpxyxqOY1Mlms9Any1gxnSXdsMcbPZRop65siEONu4aSQDUmuNBhSqpedX4h9CDxpNUjjUhA13NkO8lAnUeZQGApy5dHBav4maRt7n5mKImtBkbMoDVFeaIbxhhqxRffxj8K+k1qmmqPNqveHgROHg1DFw28YMVf/8ZTA7c46OITOkOj4EPnwfePEqLTLWwWlS1FE5yX3ZMENeE1PWa5FtO3k8bh6o3RmGcBZWS4k7jz78On85fL9Blcd9H1fziE8ILFSlBqI1R+xxN6K0SAUWKgDgpoULEQdvqOf8ei2+ia6NHzt8Ly/1uI6pymD1AYyzlHGPlXyETWMce9aRSIkpK+JN0n0jo3dIRY8fynwmi5pLSEmEj4ybNi1Idj7G4w3aeZpOkh2si3WoT6Ip3zSdgGkN35hzwkIcMR16fD4HfAgLGrYumo4jlb43YcNqOglaGsex02wKUkzG2vg3Khc+9EXsF4gk7+RwBrJI30qcoXQYcjBWpsh2WEC4csCoAq0aEAA+CP6Np18MOsfd0ZH0jznNzWyG9oMjjF6dRYeCzJczxNDhD+Na3rfzBWgeFjEi4OJdWiyGxC4gV+Aptt6i4J+IFc+zSEtxT5a8g4w+Y6jWCJAyTMvaGWX7eo8iCqHU7zHjMsvLCJwGJZ2/rUsCZJTwEcAV1eM+XQNETYOVfAbF/U1Ugc/O05itF15JawaeRZZxq2IjFfY52uNNAmhFL36fSgGwS3Pqzs5yHIv2L9TbiPkk2qeQGRr71ZHU4GDlwLBkOU7O1We4DBuRZ9DL04izACSSgTbVDWHrcGyTZic4GsHe6KLph+YJkErsbZPVa+GLBepPX2ZtS+Zsk1HyAQBWVciGXeWb6jVMr72Dcy972ctO8jA1i7uQoQI9RfGgna8fcBxdWQSIcw2F+4FzbTsb7dGmM4tzgmAtZGQLGsXr1XnKua+He79pUrlwX4t3sIWA7Ji3iJ2PUjMDAK3jwUWtkbz6W3E9+3gdgEg3uNk4D2qAMcwb+8BJayEyPBQm61NxFjDh2dUq0xqjv0NNE0VUal/0HOUradtICzD03gAIEHiDvUB4DsvVhr+Muy71TdvtexlD32fQmOvUbtlrFteVIQ98yBl5K6QsXuRok3S4LKp0GQDtPqXslym0k8nr7J9C/KsqEQFvIxc2xYFeS78ozc/GHO0iiv8I11/3Hg9TsyidlpckjG0vBaB1Q5LX3ZLN8tpEWAoHacbBqVDmwqnnQp2MLHfFJnotfaohohycQEyT1lokqRRAilqQpoEXIDRblwRArE0iTlhTdiCmdlPGJQqIg0wdaDF6UblUzwMQz/3JqexUdXKoKmFu5nQu5gMwoCWbgFc6ONHm53AqW0CjUUoQM9EfIQwqcls8S3RiuQKNa6nzof2dTgQYdpKcuzL+Tkh4VAvQOaiqWFeUJhMJb55fAB+8B/fyxAy2EqDVsfBq8rpJC6EmcTknpQDWktyFx3KuWy4Hw6Q0n4nT+2KRUgKODuG/+mFk2ZL7T8UvUSSS0WgkSXfs87ohi3fdwTlE2FsuCleVGtSXLHrCxzGjE4B4+2PEJI+hU+XSR9+08iAKXoeU1WqhxqauR9tmtTzicWVi0lokGr7V/gbaOK1LErunCMNZehFIw7q9qblhQn/cm35qyHY+k7odQKrdUY9SPQ8AeHQUa4vA8jCsHaj3g9OeEQnrz7OpyfoN/Qv1SXSJpflMFgZTZ0Vre0QS3iD85HiYJMYsTmQS5Wg+k8XhIpHw0mwGHoVnY51/o1EiVdZ5IgJdLNB99Ah1dPiGxclRrBvizlcS/QBS3ZC6gh9XqC4auNMFmo+EKat+9lwKP5fzdzAHT8agtk11RY4Psfj9Bzj6InHY8vGBoDJDaFYZw/xkDFQExwx/ZJiyvnjXF4u95FKowln27a5q8hCJzD2L2O3GxHhdKv02uaT9G6n9dylZ7ZFbmGW3GMfeZ7GXvexlJ3mYmsVQnLiMF28rPqR/jmpj8G4vlyFacUkM2vdgVBLLNlEN4ZYoeCEUaWePmyJAlombu1bIdW3/QuEibpH+N333WGW8neQoK2IUx+g94DnG4i3qkz3nPBOAkKuUOIumTcV/ALjPniXiX8va3fvBbNhsPoBUQrEz0Ysq+Elc7kPxJtNTuTZotU5Zry7p7K5tNtjKLc6i9C3xySn4vIrXOCxC7ZMemEwSJ4n34KoCLhILPBm28/q3Pk0oUEB2/lYKPAFIhY+AZEqRQxVwFr5pMV7I2PqL5XBU6fnLRMijmsXnX+Co7eBfpOqgdH4Bb3AWZP1s8xn47DwvMtRuAui2ycNcLHZxcJIDoCFC69/wYmtqeJGTI4jQ576BAQenOgdt0Z7ohMsYvNxmKLaqUqGczsK9XXIUrlbp3OCMZDb99Qh+kyrZ9cQxM1SL8gJInA1Nk+6voKwIwx7F4+ylH+pcTKzm+XHMponYxTo4oSnemwu0zkf8GcHppqCuus4riakztHJAkxzJ8boBB2dkGrcSfAjg4OQt2a+0fqj+PhmLf+TQ2PXKyEWUoOXjsaAimYUh3H50LhQ91v64aquDk9Yt4Nbg4EegVyeDGxxNpzIXWiUOACYT9E+O4MxCRdOp/H3AwcnHB+JjmxsH56t3ns9iBwTnNnyC/lgiOJU34TIWauYQ3chj/4nsJd3fD9T1kJ0+QcctliKjcIv9uQzBacoZegYF3EW2K3kGmkY0gsDKJQhOjgDOsnydIDgHtDRbUvDsPEZ6sjolqkkNaRZmPmI+DhtNjjlhF0zpPtZxmHnOqAhMWNV7v4ngBIC1pPlbbow4VlOHA6EkY9RGjGaBUM8jq+Oi53/xImpaCGPg3sdq6LGyGwAOGoSGZH3AWVgtZGix4IsLcOC+iAt808L9HjIIO63WGc4itksE1/fwFxfRmR37tqM8zMViV81C64aU7nlmUPCiq1rqxnWWBOVXV4RODZemJBjlmoWbTjYgzm5cp3ojS8R7eFPXow+hUzeuhYWpyA3hthHeBRuK1BKM5v6AkKPEMoi6o2ltU9VclJsz1Hp1B4fxg7N0ejY3xD15DP/ylYQUi/KFwscxEDoN8wGkcZNV9QOuITKaR7V9LOxRTRMp8bLcEKtZPDqOdUgyGY3AiwVoPEZvzD13MAPqcUoCG49lZw7V2VM926CduApQ+rzZFCAndUQ+/grcF69SPyoHXq1Ajx/JgUtyQ9yqEWDV+1JjxJmaKVbo6FDes7PzCMxyhwdov/ERRt834fnAWTqUG8KTseSWmNoyWO6+BOwdnHvZy152koepWexihgw5PjOobE4zp+pfpEsbuqcmknUGEu172R3D3+L9VgNOz9KpaZyNVo1N/Un0eZljrtO+bkKjyajhrHRsfR81iiz9nH1SSX1yIm6YIYUK71++EvXdswCYbHvbzBBLzqsai9G8yJGYHJQ7OLWque2rLR3IlmOj74fNkMA2VpZ89BdLwK3S3C59ojdcLnNHryZ+aUJeUPV906L69OmwGZJxqIZ+agW20gwJcO+h9wYIzljnsoRD3/cY/baUNoxtL0bDcG9lqm+aaAoBSATBO8jDXCyuI9uQnXd5f/v/6xQLBAuAscFzytrUsYK8gXrf9zztIja1Wh3PjsQfczNemmu3L9gPZHR98AbWreQ1wWQit/vHdld9vLHUo8zXdV15dxeLq17+Ap0pjEUuizpcdm2CX6uTbYDPwiRfaRs2AmLvEY+36Vz2SNEc29/4kZsoT+yX1Yx82FWxiVgNDE0bgK7yenPfGB0ZjQJ5T3G+zsfQlOl8hJ9jW4b5HEihPjYfJetYI9tVSKiyHzGCL2RDwwzOygFYvkK4o4/AUeSqJFMNjl3os32nqiqFJ6fTTMOCcyAYCL9NUVcfjz6rgFbV+it2njIJ0SJLykyjkfBvWAen+qyK0CmqSpCsIQKU+rr7JvfuLhZX8VzcJuuUNzktNk55DVmnG+0XOzB7lnAwYKIOsrhF7o4yKvSas05jZCQsBrHyuj33dWWdKv+H5xxLAwg5sWFbZyARHL2urFNTbgHA9bNO2WdQeuhYd5SHuVjsFA0Jv2+pon7jRLKgVVj6PRqPU+gzvMmvN5GM4k6VRUPW68hIHXcTzXkJdnwsuvOGEskUFBaPlWzjIdKkjGTx2H0kkk0mMdJC81m07ZlNiQOtoBZwFtT3ryeR7PBAEsnOztOCc81EMp5NQK9OE/6DGVjunhuyj4bsZS972UnefnZvlaApDJHjbj1fRVfiySSRwd6UHdtVm2qiYduOO/VQ1eu7lKDlbEgBVLKV1wBIPzMuUvlZa5HeW3X2ISnGEJmuDWM1Wx/LVX27rZM2EDFrNftBekH77MnBHczhz8+H2x1iph9yhFvipG39D8z1FqvTn55uas5bqRoIbjaDX60zR/ivt3//HWT3tqS51zg/Y68qEHw364fPH64es228Ltk2lowa3m2eO8SR2Q1zP967lH3d4g/amcHsln1Jfdj03WRh4ciSdc+bgm0b4TndcEGMqNhr+CmsPJzFQqX0Q+jPdse359jcELMCu0AAoklE1eFBxmfRn51FB1bKaZDf3aSOtrq/WMjuEjgRtI3q8aNEfuvS7o3ZVOLzp2dRC/GLBaonguDrPn8q1z86hr9YBt9FY5CfS7jZTBCVWijYVBy36Dw+OQVqOc8dBKp5TcaqHGIJAgA+8GiMfuyj5GwLCUk0GoEmY7DmP3zwHvDFC8EjqA3ODF43ghodoPtzR0epzIFyYIzriLiM9PSTiVQ7U7Tn4QH4/AJ+uUL15Ikcm89EywhIy/jxfPAEdBLyJOxOXTnwxQI0ncJ/8Ty9A08eA7Mp/GdPY79oPpPoxbjO8QijEWg+BZ+exz4AQP/0C/if+hbGP0z35XoEOl/AfyX0dxGSv5jhj8J7Nx6BK0K1bOFOl2i+Ls9//M9/YPxfaWFyH7wHnoyBZy+iX8b9oZ/A2U9+gON/9lls2x/M4M4XCeatvBbTGtQz6HwBPkz8F/Rb/xi7ysNbLIDhHbU8dlXWaRl90BX7ElU3RkwMkxOCh3koD4TV0678kl0HWq/BWthGY96e4wcaQUkFe/YQu3dkvY4gpzYR1IQxSnJXvwHh1p+pyDrkdZOAPwrq0j9qOxfLNL5Gk9ZCdfkstyaZRFkOhjov2W/WW9G503PW6xR90XNXq8H26HwRnHsmpKp/b/IogJQtEBr+OMdNcES2Hdj3eanDMA/xmN6fPUYvl1J2UM9tpW6IO13EttU80Grprh7JB920oMUK9YuwMIWcIJh+AQAvVqCuh9dcHwBuscL06VqcrgoBZxZnblicouM4ZCDzYpUTBPW7a9p7B+de9rKXneRhahZWbuqDKDUBBbvQ1ffbhFkPXGPAM7Et71NxIcudEfAOmS2qPhrDMB3Fs7Bgb4zBp3BquK9aYIP290DfWTMpTdu6q8adbt3EbFi0Zp8a8nlY01DHEG3nlOWb1VQxGoPN1I33bymFTg0LN62bQC1QaBYBGk9dztiNtgO7Kh3rOqBxsTBxpvWwMHzHY03iYK0Wq6IyuVyrXB/ctogV4PSkNlAg9JIpSwuTFey9hFYNJgNtI9pOZ6rKr1YYna7k/oYvFE0L1vFb7hBmMfEsEOudqKK+q1zFtXldsZRlA8jMG4mNWuj9HZlCMFsUvK2s0vcILS+APxmdnOl7KuVoPsqYlaso1XCdLhgRMn1H/Q/5FRvru6MYPQB6eYROUK8JrGTOvaVweQ+3A3N2TCGnnH8imA9Z+cJtNHrKKq/cLfa+23BHt5CHuVjcxQIR4c9KslLJbl08ZKkVmv+csXt3wVlYujo0t6Agv4lcBG2b1eNEKE2HgNyNRLtEG1yakfMhhhUTeMrWsYx1P9kUXO7jYEBuAGY+GiVSHfVRKDO0AW7xep0gxHp+A7Db4q2vKpASx5i6phtALU391+P1aOOcOFdtKDOo7c2maYdVB58ncU42rZyrMGjv5T5KuqN9HNdA77IaqrFf9TjNiTJeLQl8MIU7T2A41AGQF0oS0ipBxVmJZ+oRmAjUdiDP6IPj0z11onHpogHItbWUpqTVOj336QTt4ynGz8fp3JCGHvuvc1aPQF5Qt2RIna/D5/kwF4shKQlnt7F+65/tyo7Nl/XSdhwl5GLTys8xE9IgQpmzojlUVTEHgBVdCVH9qa7zlT8WtK2A3hQwBqC1RzN2b0D6Ydi2abUOfBY+lQLQKIPmehQMXdq/2BYgL1pdJ7q+6QS4GIHIS7/1+DZnGbm80rjO8WgUcypsNCRbridCzc9tF6+jySQ6Xm3pA56HHA1T64NC/guHyA1fmDyKugZPx1kZAppOYzQkM6vqsTBMKcJW6fRPz9E9nmJ8kuadxzWo6yKTN8LiPhgNWXVwzOiO5frxaCTPiwhsNAuaT+W+FxfJjJtPsfxgjPEP07vjD6fiRN0WDWFOdVUBKZi8ozzcxUJVXk24kl/CD/7qaEhBlBNtRVtQt3J5YhQ52YJtHcxt0ZBQuVu6SqlNG30w5DIcqpDHXVe1AQ7JXrrLxehCqgEa294SDQH7LK1b/mb6bvvdtob0xUezhGUg0oV1I8ldnDz3sc4pkMopNI289JYRS8dNTuzna0RD4keiqebetA2AlmvxO4xGyQzxvRQ49vJ84wLddeCul9IFceydLJp9L/4B4/8hALxIi22kP2SP6rxJeSDBfOA2+SFoFaIsnmNEgaZ1shzaDqPzRJkQSYBUS6pcioa0XRYNmbwKPKt67mIt4w3XU6/z4EFdL/ex2vM+GrKXvezlruVBahbiXMt3WjnWFud0yRFXiNLYKWmJOzoUKjRNstG0X5OqrI49N5tGejR6/gL06Bj0/AWAZGu7R8fgi4VgKYJK6A4PwMcCjqKnz0EHAo7hk1PgvUDBphRvh4fgFy/FvrxYpH41bQIPaZVu3YWPDoFHR2mMnz2Tfp6dCwAJQlwDIMLm6Uj6E3fKD95LhXhCAhRNJ+DpJBK0rP6tDzH97WdAPwEfGYDPxVLIfQrfBHkPenSciF/CHPBkDPci9Ceo9Tyfwi1WgpcAgPcew714BX9yJvcA4I8OxNZfN+BZUv8XP/4Y00/PJUJSBS2oZ/DIoXpxDn80EzU+jB8fPkH7eIbRaSjsNJuBHx3KuCdjuJNEhMvTMfyjOarPpb/8KDzH5QrPvnWMD4zt389HqJ9NcPETAWj1qgWPCGBg9b6Ybd2U0I8JkzOP2eczPP8jMv6Pnx2CL5bhXTP8or//K+gPxxj/FoFDf9c/8RX86D8c4/cvnoifAsD6vQmmz1bwtQMY8BN5Bt1BBeqBybMF1h+mZ+af774EPMjFIgsDWvYlQwYToa1bIMyR2ShcZ7P5ojgnH7veN+SV+OUqsltz3wf6/Lwdf3Iq6cCqVkKIVeN1oSSf/MGDXgYKfjUzzs+Fa0Fp7xX96EgATparUe9zcpqYqsMYqWnAXRcXiYz0lj1QlCDAFy/ifTXblddr4GIUOSamv/1MwqerdXRacteJeWAqrSkClJnzOTo9F7X85DSVFND/z0eiauui23VSRsCUS6DVOoaaad2ICQdgvm6BxVIcjGERoaYFAomta02ZhL4HPX+FUdMmwNpqDVouYzarN1BuqkdwJ+expAIFFCU3DT745+eoPnkW3xk3mwAn5zhQf82csRMAACAASURBVIyCsnqP8adhUZzWKepxscKH67CAnl9EU0qBejQawf2bp6jGNfyrk9jfye88w1f/949Qf5b4P6vnFWixQqUO0uCzGNfiH+KLJebPk8/Crb5ETFlcIgaB+BB2vZ6c2HxCQ5d8BhsfI+92TwCCqQjYAuVooMr4RAzHQUzgMtwK3Pto80dcBcJLbmnazBxs6x2bKuDx3Co/nvrNyZ+jWIOqApFHDPn0gRTW0tj5PmFF4kIabGm9p2W77nH9sKXFW/QBm2JDgj6ha3URi30K85n6G3xEa0NvqO+MZ6DM3L4kn4KaLi5YxCz39H1iPrd+AT2vDZG3rgOtW1AbztFaKr3x0RhfSya9R7XuM9Qn6fyYtmRoZp5uGEJ9kIvFRjjT6//GwXlVNGSj1mkNtJR4H0JtEG47RFo6pajbJRoSa52mD5vGY4k2KKW7tuW9mBney66LEJWIIbQmOebaTtiOKrcJqNkSDSETDSETDYnXACkaMp0kCHcbogqjURat4aO5hOFsDYreg10jlPZqfqAN+AZpP76i2kdH14uGZLVO5QOl6SR+jP54LnDnepQiLl0vbTgnJtk65dPQdCpjUe3KkRxz14uGNB/MMVVoN5HwRjCjfyS1QNxiHR2cGg3pp1KHhHqP0ahC86Hs9rNPpwA1EqVQ87mqhqMhR3NcfDxB/XSenL2zMRyRREGMZsGTGtT24qg1uSHXiYbsHZx72ctedpIHqVkMpdhucA3sfjPRGDxHlVmPJ7Zqve/urEJyjyIhKIM+FynjPjgG7TmFuRHF+2vtCNfucwEtj3+yNHNdF0wP01/22biYWTSQAJXemIfrzqfto/atM7u/+ry73gDLglnnpehPHIOGG3ufYNVbDbnLhcrCVOHeZNX+4tUkBhgM6ryMwYaB2YuZFu+7BYDoGdQXc8Ccv1/e9OGW8iAXCytbc/OvzDpNuf3kfOJzuIxgRReOXXAWmmVpSXHbTlRMILP3ubflBJDODedleSR6LfP9ZZ12pm0iQWZaHMXFMtYEZWeqsTVtXCDi/dRn0Rj8RtPKnAyQ7VyKs9AxyI3DPKS23PlCnJRERVlGn7JOrS9jvQbZ6mfeizmmWacWZ+HF8zSEs6hfLLNKY+Q9eLW6POvUmqCLFcYvg2kWuD+JTG5KVQFDOIuLJeZPG8GX6ILX9cByJWa2QXBS28mYb5F1+vYuFoYZC0CR1DMwQPapapdlwtqyotoXgUNSETiVEaRRnaDWNneDOdT8SASsWuMju7/WIQmlBbWd7EO05L02VKtjUF9H4J6I9w7JR+U82LokAFI/2SfPfiRR8fGa7B4DfBRc0N2Tkswyx7J76tBVKDqAFCnhPtbjAJA5QOPiVQCudBPwfhmT1iJfp15vIk1y31YW/dK5rTvtcpmQsc5JtKFpM0d2dIAukc0vBxBZ1k/Ic3I/epr4OgFpo23jgp+S1zzoPHxyxmfmmwZVmCuvZRLNIiYbS5PqfoTj/uUrjL/P8KdnWbiabZ1ew/LNvSSiUYjoAPgS1A3ZoGILP8cEpt3zRrTQsZojNrYt8GAfcy9QSQV1WRisGTG8eGn+RUbDr5qGLbtHI1NOMJDSBhQfN02O5kMVkKVD1cpLlqnQT9vfgWvyX/O/R9p9GKetLbhsxxEcspGAx2ZiMqe5dZIAZRe82G/KzcmynELetyrL4bDlFqMTtevgF4tI5R/zIjSztR6BukCcvFwiq7GSpQ+EerIxcmLUe6v2u4D8bYv3MJwTzSNyycntkrPa5r/YBcAvFoi1bK1504fi1kNZxKZfjM2FWE7Z3TzZOzj3spe97CQPU7MY5Jjka62S6XoG0IuGYfkfA2OSXYnpuunqaobY66Iz1QCwwElzUDVX4+Iln0XJUXkfUu7s+nNQ/5M6nBjDovbhjW8hqMPRt4K0I16Zwj0k6gTULa7vM/+Irb6eOZcNToVK343ia24jbZeNX1nEyPYByI5xMDfQdmLSBSdl9NVYZrBt77UPvramyc7RbOVMrpFduk0e5mIxJLfgSBgs+zf09xuUjsvuba8v7hUTrlQue7j3yWcBZEjY7HDJbcGc+Sc2Fusis3fwPrcVo8LHexsuCA7tb5vf6Je6VR+uGI/toybj2XZdIuuJc2O4Ny4VcsNzoMfuYJFQuXKxIKJfBPAfA3jKzD8Zjr0H4O8A+AaAHwD4GWZ+STK6/w7AnwWwAPCfM/P/faOexWzGK1Z9E2rcQFzuch2MdgJE/wS3wYtvQ7JlzdBLb795bvR9DJ3PAanZh+hCARqLNmmpqdy1bOMyJZfvnhpipbRrClLTRls8tJhRdkvLZHWTvtkqZJYCQJ2sljdU+6XrX+Ec5aq6FJ25k6gvCqL1kM6NunPKMDmSJsbqV1CNJ3J8Gqf2Nic9MyggZzeP+43I1G1lF83irwP4HwD8DXPs5wB8j5l/noh+Lvz+VwD8GQDfDP/+OIC/Fv6/W7HcFRGpWbx82yqV6Z81fyEsMG46EfVNoy+aq1CiRZkkUqIVydZruMkkeuq1LTebbhLKmpoPfrFIfVit4Q4PxDMeWLb1nhFFGslrGtBIKmfZHA4AWU0JIOSGVA6+aeGUxVujPaHSmYbw/EoT6o7SC6vzpqQ96kB8dCy5HswJGQpxoHHTDJqDNJulimbax9k05YYo6nNch/T7Ps6jX64kGhCS6WgyTnBowz9CRyYJSzWL3ot2t14D9TjyWZD3UuXLMH7TeB4rkkXnst47OE1Zc0OUBf7kFPyNr8J9/iKdW9fg5TImvmHdxPcwJr4pYW/bgRYr9B9K0pn7nU8i9aJ9o+n4GDSq4E/PYiSm+vADNN/4EOPfSuzemE7Ai2Uk/4nvTT0Cul5Cy1OD8v3sDhPJmPkfE9E3isPfAfDT4edfAvCPIIvFdwD8DZa35deJ6DERfczMn+7co10kq4GxZeW8Cgdfrsbqn9hoivOf1ca1Gk2MkJjrum6zDXue5+xlLOtPqL0aNSvDs8G9FzCR5fA018R7GFBZqXVplGHjmvU6b9MF3IAdy/lFyKMxO3jItYBPUQ+2s9ka/g0Tbk35D8m+t5gOzUEBJ2yL5mFsRCKAWISYDS8I68JiMmIlOa/JfV0hBB4T6Gx43XWisURYf9L43IszeIOz4K6TfpMs/DZErhoEjap4H143qMLvXvM8zJwTkSxSVZUtpHyxQP35af7utG3i4PRsSJRczI/JwqWvgc/iI7MAfAbgo/Dz1wD80Jz3STi2l73s5YHLrR2czMxE1zDmgxDRdwF8FwCmmF9xdnnxkBlSrHtXmCGWg5OcJJBJ3NuYJ45CbF2bCmaI5eAMpkvphY9clgbBSaNRhlXQJC5Rsadhl9HCuzWwEgdVrOCt7RXUf7F/9v4Q8BRVwtUZuS0tO1ePDdAbTSZp51EEZ1XlHJzHh5Lw1vcJz6C7puHv0KgHUyjYrG2MDRXfkmN/4t/M7knTiZxjMCgYh6S2vs85QA8PgItlKmKsY2CWvo1r8HnALjCDplMpzKR0BSOSZL9ghljTNmE3cjMEqzX8+8cRCUuUkgy1MLJFcKoZwrUkkqHrxQx5PxRGPjnLqqDLQSd9HVXSNy0xczBH89VHGBsEJ8Y1sFxtcnCOKoGFr0aZGYLz+08k+5yIPgaA8P/TcPxHAH6fOe/r4diGMPMvMPO3mfnbNSZDp7wWsdGK0vtsPdPx33Xuvc2bfVl0wLYTwEtvjWR9G+iXZe/O2KnveAzbokrKvUnFv6yPLo8Q3EXfwliz8V6H3Vt/V7ZywyG6a/tbx1u2dwu5qWbxqwB+FsDPh///rjn+l4nob0Mcmye39lds8znocTsHtkCsq5LGEbdeitdGQprIkO1yH4Pv4Zv0M4AI/abKpZ2lCWQvEa0Ydq56tOlvcC6mWQNITtKVIeRtFQo9gV+tpUBva9PZe0FQTie5l93JrqjlEQGAuk60DeZYMrBMUY/jUAftuAbFyIuP98ZolNK7J2MhzXH2pa5iXgMXEHIAkh5eeOZpOk39UeTqJBDoqm0/nQq8XHd7iL3PHTI/DgBJDS99CgjaSZiLjNBGP2pFSs5moIO58GeOx8DCvFyjsCOrdjSfAURwyyX6gzGcJTquR9LWYWBTWyQIvJL4cu3AdQW3aOHaDv1Mnq/r80poAESrev+JpKhbP9d8itV7Y4x/QNAPgWeTjO8kEvZOxkBFcCcO3qaoP9s9mW+X0OnfgjgzPyCiTwD8Vcgi8ctE9BcB/C6Anwmn/xokbPp9iL72F3buyXVkyMF5zfKFMSfCONKEWOYS52kAUpXFaTPWK73/UolfzWK3WicHW9dFFZz7PuWG6D1Xa4B9yDvxWQ6Hb1o4ICfs7RELBEVSnVCyTpOmtC29hn3Kt1DTjs8vktPTFAAiy1714lWKYlgnoCbjDcy5zgdgTA9zzxhS7LrM8ekvFvHjiSxVwXmsjkgVQorqWCGiSHyTJdKdX+Skwet1coiqk1L7VlVyrh7re2ENZ0b9yfPI4qVORd80UW3nQE8IANVZWFSqSpyOTQterTEOoKzezJMVPjmTmq2mVCGev8TRv6rAL0/Siau1RPJMuQUgmah8fgFnHaJ3mRvCzH9+y5/+5MC5DOAv7dz6Xvaylwcj7w6Cs5QdmbI0+zKq5UXRnUGpKmM2BAxEgXrUiusWiGWLAEkBoOSEK52WWrhIyYlje75PCVQxDJti6tbBiSqweOnOCOOjqSoQ+pyBC8iLFJniPvY4TaeJM7Oss9L3g3D0WJEe1pmZiuPEBKrgSI0JV4GxymJgYiGglvJ+zae5KariAi3+uAYtjY+qHonTUivLj+R3Uke3NSPrkZhiqs2NazFJm1aYpxamMLKGRZXU2WTiRpxFVYnTcS3FmdU0oNFoGNA3GUv7gQYAkOfQPplj9MzgJmZTee+q9E7ovPJkLI7Yuakbcg0/3Lu7WAD34uwh65BSuUNI7Y3FOsQKpy0jOVHV7wL7P1DQEr4hsbB6VzgubwC1v5XYDcD54XdmF0fmXctQucZd5ZaESQ9zsciclpdoEMygijZNaOb8xQTCDtzknJRRW+izc0nDiZCPjAYeglYMy7pkODJptc6rhE2KiJDyemoKfbEYaMUzAClJqh7lFcWcC2S7JiU+3EsWEY7j8AprLzkwkXZgPc7zaeJlsJyfEI1pCBZvK6hF1OdknPwFWm0slP6jntLv6uzUc8ZjKRAEALUZ78FMyF+shDKF8L3wZp4men9MJhI6jXykIfRMJLt+fK5SUQ3TSeZ4BREYF+gez1Cfm5KAVQVihj+SHdwRgdWZfSjH1MFZXVQgz+ieyPH6k9GgzwLTCXhcy3up0PCDGVYfjnH0SWqbD2YCNx9wcHJdoZpOouNV+vquaxa7ODiBzVU/8lbQRs4F2qLS2NA92QNUY6PCllUby4ph9h6GyYp7b0h+fYpG2HOVlctU39L2bMUzGWrI7mwH7Kcy0jMgiruAKTFg0Z2EZKq4xUqQhsiDUbG8wMCzyCqo6bhtPdG+j87j7Dodj6OEqKyCI7ftckj0xTLVG7HSWeSl6dt6LTwPWtGs70MGaAci80H1Hkxe6oxGZ2gjZk1VYfRqCS7MEF43cGeh/spqHeHXzkDo1QzBcoXRy2Wcw8EykKu1VE/rTBnHiyWmz5q8bSJhw4pmddjU2g7+sdREoYWJgHypqqhvE5N4NfjnEord+41jW+/r08eXCEl8Woz0/gXRCHqf6PJsbRPPGbRY+2P7OUSHl7FngYVCrxyjRigsqIsplB+0adCaQNcNRkOy/1erwcJN3HWXzzfnY4Kh2pPsUBc1igjKAiKMPLbZuOjHyELri9Vg2JYopIEjfx/iYmPGDpKFCKt1jBRw70PKuFl012tweIbufBFD3tJPyStRv46NhsTEriIa4s4l0tMrhWA5f+smUe7pc8EKo5eLbKPhkAfDRTQEnfiduGlS3ghwrcXiLTC297KXvTwEeZiaxS4+C3LiGc/05JSAROMiCjCdAE1j4N6mElnpszCgLOo6saULB5ybTUMSlDEVppNEOdf3EXbr/VKgygCgWZHTCfiij1mnMYqy7kO172Q/x114PE73B+D7XqIq4W8ABLSkPgsD9/YB10GHB7GqWRYhmUxStbP3HsPpLm99Fut14MzEhsT50LmG2P3+QuHTwY9R1wKK0nvOZ1IGsu1iyUmazcRn0TaZzwIfPslKDobJFZ/F+YXUBLGgrMMDeSamX1qTBOM6ZclWLHVTJmPgNPULzoEXS7Rffx+1bbOqQIsl/FeeyNjPV9Fn0W/4LBq40wWar8m59auTjaRCAKBHRwLKev4yaafvP8H5H3qMIy03CYAP56DzxXafRdvBHxtQ1rtevvBaoKxttyizMAMoK/MNDNyTvRN1UJ2Lylx9T6CsmA1rwU9tB6Z1Dsoit5EezppH4DkDZWVmSIEWfK2grN60H0ylaEaYzEr138Q2tRpZ3yfEJnB7UJY+s95L39ZqWgTzcbXKQVnB5zIEyuJtoKxgbmyAssJ7sRMoS8f1/CUO/7/dQVluNgWfnMGtzTN/pwl7y8Swy1LRifIXN+7+fiMerwS4nC1ExT2ZAUK+qOgHp0lr0cHZbFzPxk8BS1rCnGqvFv2J27Tdri0UPUr4SEsHYXCQJo4KjdDkqeEaOvXL1bDN3CZb2p+cxSLUma+F/fBzKOdDx134YbK8E51f025Wp1XHYsO/bTfodxJOkl40MfPc/XIFWlPmf4nP1vts0WTXQWvdAoiV14gI/vNnm47Zksm9yKmJoWwl3dXFfOC9AQB/fpGu1QjW6bngPJZJs0D5/Ey7br0OY7YIzh38dEEe3mLBLCAbfej6s6syMyP+byMi5kXRXIno4Q9kNVEtXyxAozrbKZUwpiS/ybJOQxvu4GA7+Y0j2TFN1qk7OgSY0Yddwh3MhaikcrHeaDx3MoncBnJQQ5LjLKPTXyyTU0vNhQLebcl4AKB68iR/yRFMFZt1Gshv4DnLdUHTJvg4kC2og+Q3gbU6tgFEsytqMYb8pjoKWZyTicyzljRUkNLxkRC/2IQq1QDXjWSdmkLQdHgAms3gn30R+yPlEIPWYNZvNcVUA4wm5Mkp6Cf/EKrPnqeTA/kNHgv5Da2a5GA25DdcEVzbg86X6D8S8pvq+z+M5Dd2MaWjQ1Bdw798lchvfuwrWP/Br2Dyrz9P7/xkLMWhTckDAFK+sOvhJpPEcA4AP8oMqEtl7+Dcy172spM8PM0CiLwS8ech98SuhZF1tzSAHwDAYrHBZ6H3vTTrVAsjTyeyM9ndwTgg2YCy0LYC8mEGcBLOrUUlrWugT1W0tY6IhSNnfBaz5OCkVdB6WsPToaCiymUOznjNfJaqbbVhdx7XoMkkXuuPDsQp2PepPRZerCwrMlp9TgBYGqZTqPSoikWKooNzPBYcRROcybOZ+A8McI3mU8FOuFZAaGFX9Y8OBMdgQFDUC66GAAE2qW+IWRylhzPgVR37QPO5aEB1vuNSXQt8O2adBifh6TnWX5ljem5MgclYCiM/OQQgDk7d4bvjkHU6dvCVQ7XqMCLCKhRGnv9wIqFRlwh9iUiyYadj0HKZtKXjA5x/dYzxj5Km4I+mcFqXhjliMvysBnUejgg+FGwGAP78HQdlbS1ZeB0p48ta63QHsl+2FP36eykBA2D/Rn2fZ1lmGIwCM2Bo5uL5xf3Ldpk5s0Gzfpa4koI4Nh43plPMQVAQmpo7oRQe+sJHso1OAMjp24IvhjvTr1Dhjbvgy9GFsEs/RzOy602t1TRv1HQyfqJEwx9Ig7n3m+jOrhNTxgLDQklFIsp9KkRyvR4z464WXXL0EoGpDX6IsIGoWcEMtwqLPlcg5+HW0ofRatOPk6aLQyX40Cftb9OiXrD0S7lfV538rhSQOjdEAjrrTL+AvE7rFfIgFwsrgwuHdWxu+fg3PpLwEAbRc3mDOdKT/XCtU0VYGqasstxf9jJ28jHG3JM+sGNxsWiQvHSlk1WvQWs8nz595CVfJ3wAkJUvp60/qmCutkusXwBo3UTHXNQWQltSeSzX2uLP5cJlHIaqxShSNNVvbZLfSJGlro0Lhc4bIL4BbtsAOhqleWt7Ob90Qna9OEV14Wy7hA7lHCgnUPYmR5GG+ayWrSAxgajFcNuClqHOyrqNTlunPoQ+aLKdB7UdRucaBVJWbqRn7iTSRcx5rdOmxfikS6FUQPqxTlXsyGw21IUyiEsLynrHF4sNxm2fvPkAkNCUl5ghRWIVVVXAI9R645QpqbkO5ORnl6jT0LQpjwNIZkjlwH1gaDY1S0mdmnWdmKn7PjBWG6+5OhTV0RV5G9rohY81SE3WaYY7cKuYEBWzVrOIg6Gf03mpa0MqQ5H4xporPJvIgkGUKNo6KVJs81C0nCGjl/HoYjFKuJQIR9a5qMcBVcnp96aVfpucEl0oLAmQn0/hWoFDs51bRWrOpqBgYnHvxdSbT9PYAoEQt63Mg13slLKwVtrDMM/k0B1NUOk8EMn8tB38PB1Tkh095mdhsfCMCkB7LPebjGvpa+ViDW01O3lSyzyp1jUZY/X+CJNPEtaFp7WYbZWTYs6Kz5mMgFb4WqKTNYx5V3mQi8WQNpHV97jxjQvTwJfaye6sQpkUVcVJ2ZmiZmDMhTJ0O2SGeL/xkd+VZDgN3eF057Xwch/CpEOamDXxtv2sC/r1Opf+V5PRpxyZrAJYDHH2ZixGc4ymRyqORBspdLsJ2WejczJQKyQfCwACqA/n6yn6Htv97ZL32vXI3x/zvLa2fUPZR0P2spe97CQPUrNQQhgAsbJ5dkzPCUQxPECIol78WDTm6BBYLEEHwct9chqdUlEcgVDBzabp+lAgSJF12hY9OgZOz/PMzcND8KND2VTaNkG8X/bwT0JBmhDzp/kcvFyJmn3Rp9h4KBJD8zlcKEgUsSKHB2C9DwDXSmEe730seKO1VBXP4EIf/HmASX/wRODCEN8EAGA2FXV9KWNc/PhjzNetqNUKHfaQZCiLkjSlDeno0MzDQVLX9dg8RAkOZqCLZSKT+fAJCOJUVbZs/+gA1HSgVQM/n8ad/fwPPsL8Eynew8pA4Bm+rjD64gz9ozmcpqizh3//GN2TGeoXr+Tcgzn8kyPQsoGfjeFensU+83SC7skco08Dd+sT6QudnuGLn5zhw/ZJPLefjTB+NsLZN2XOJy86+JpADCw/kE+unRH8GBifMg4+G+OLf0dMg6//4AB8huDMTLwj3dfeQ3tYY9Z2AMkYVt94gk//fcL0aXrmqw8nmH0+AdcBXj4RDbQ9rEA9Y/b5DMuPUvSk/70vE9y7dNzpKQPZmtnfM5ixYPy5SbDc6BTcSA3vM8gt9z14udzMYlXuSPU7AFKlSm/VtEDIi+Cugzu7AHwqxscBGs7KjGRgzdy0gL+IocyYUm7uH9sI52vI0BbJ4bZL6D9VxU/OU5q3idxQ28Xfp5+eA4sluPcp5Tr0uURDao1RvlimtrVqWNMmeLZPZgOvUvaoOzmHX61knkMhHxeiPtwK2a3K/JMRqpcXknlpQFkOAF0sUfUe3jiY3ckF6j7NLfOFqNpNC1rVGQSfmhajtovHVCXvuw6PfrvF6FlYWIhQjWu4swscfCJ+iOpsDa4I8MDoQj7UflKBR4Rq2WP0conH82BWLpYyz0XZx+qLM1RnwqGp0P3JZ+d47zefoH6xiM+vWvdwJ4vIUzGq5b7jSQ10HtXJBebrdF/XvMsIzlKGaOGv47uwxDLOCRI0HBetpEMG1d19bpNmEksKpP/Jsj9VVVhQfN5WXedoRGAr2c6dimXSssxg6ggMtTEIbXSgURcWBkMMpOcK23Siyv//23uXGE2W7DzsOxH5/P/669Wv2/feeXAuZwgNR+IQIkyANmBC8JKArZXsjSHAsAXYgjZeWRt5Ye382BgiQMOG4YVsaWPAEGTY4EoQaUEgCJrjoThDzdyZ++pHdVd1Vf2vfMXx4sSJiPzrr+7q7ntnuu/8B2h0VVZmRmRkZuSJc77zfWTN6Jpu3K10HIkk65Fn46yBxxhw6fvVSboQ1oIzG4OZWouS2xcKY7/I2NLo3nJufQqVNv7OwePhjML/nFuwDpnWjKQarM+53y4DODOAhrbIj8/Gs8eWQDcvA9lqb+5kcZ04UPh78lL5Fy+IGr/UC+0fbv8wB/5EIMC4SQFg9HKK21deHkpekkSoCEUuD3KPSFpC5BmeWHge9KbTxoP0eVuqWWEIMFZeSv8zIA8e16VkOzTaDsQXMQgP8YjWL3AsqIDPywbfwoNv/NLDZz3Ui/QvCpcZhj3pg1n1MPMVkFlwkQfKfvb6o66wsK8ZLHZ5MllYAy799YU1FoGNASWavM4SyDGG0sKWViY5wIsB+eyHLhnLcvtzZwxcAXCRsKZZuVdsCTQgMr3Tq4Zvk+Ze8/id7WxnvyD25noWL/rqBHBRTDm+ErLTMUCSxuQ0VYkk7pGmONPjtv2cdpE3UHRpVSbHlB06Rd3FbczskX802h6AVGS2o1BHv7vrPRC3MX6x0wl6lAEMYCdfwRBXGFhKwz0iULYlAK8kLsD+nCOKwYS569p+bftdx9ELQ2uKVNOj5FGL1A0wKx/0bfuQzhzrlDi/bzJGWu26mULXtrcibBm2HadKqRMAWkBHDgziQcZNAVWdC32mboDpEsSpR5IGb6HvQa64ihR2DraJ7QHeMx2ceIPOxYD24L0x5nGq9yXszZ0sXmTpy7OJUWDGjX0udkK1719KJA9T4KlIHnJS3H1KrW/jujeES/RlTnAAKPKw/hzRo3l0HhCDlRgGqWgtCtnXY8BY+RaqImItAoApG2l/QjVKmyTekEgBpLUD8ZjE2dR8f5bJcT47wpkR3gQNfIbd5V5oJWlArzr2QLrk/jBLVifI+Nk4Rv0gVHj+dyIaxxV0qdQNo/ZdbsVV7gdZemhbeQaspJaFlQrAL5GoixB8mtRxPDbHMs/BVQEsk7/78XQ5gsfiqQAAIABJREFUyfLB940GiRU4H1w0lsCZAefAUPlajdzAFYT8UiaRoVD6u14ySmnFcteDjw/gyhwmy+JyLLcYCj9Z6D3IhduTPTiOfR9cYWX51hRB/Uz7f1N7KycLQVXS1W1qN4F7b0J/9UsZMP7makCTjPA4tF2c9QdR+7qSdWmaCH/Wvna9lKYDV6DZvFqHlwqApIMTab3w1faTEC+XV0rUeZMTQ/s5DCFFnHKHgt3VYxbLMQOX8doYiWdhT31KeHAx0+Oc54tINE68oDObOB4A4vn7PuHZ0C+1J9dVOP18ITDrYQhkNAR4OL0wfOsXN3tyKWlXJcMFpI+rBtw0sq/yT/rsiiGCU0Ki5Upe0L4HsmxM/tt2oK6D8xmZ8CIPA+rPVqALnzkhL7K9XCF/IilOWjUhRmPW8ny5IgMMpLjrcoXJgzyMid5nZj+JEYGeXcIWOdxyFfaxp3Ps/3Qi59cxGBxIxaEdh3EwXn+F5ktkKYy9u3mA762cLFK4t2ygMc6CGVu1TtND9IH2Ln1QPdfg3OXl9oBmqDpVyQBfPRqk7nxbenOS1CnyTKpLAQ8T95DhrhccxZAspbIMMF08NpXp2xAZCvR3ypeh++WZPLjbqk6Vrk+vw88lVFWx2rH3GRvV+VRY9ayG6fyLrlR3gxcGWq1GE3lwnfMCI4Ee+ACy9ke3+fEJfagq2ceroAMAqlKWHn0vEG5lmTqYwA4O7IOZAELRGwHggz3QpbzAClV3sxr0JArx0KSKbaX8J6ojq5wcHheCC4vmTgV75n8nAk9KmGFAf+ClAKyV6KADhgPZr68lqG46hyy3aI5L34VMJoM062UteFpLNet8ESZdN6uxuJ9h8lGCm5gWsOwnCeboWVQ5qHOwjuFmkVaPXyKzRlsrJn/Gtk/H/Ju0oYboZ+JQmp16AiZ5cYxnOiISUhh4fME2Zar09KmLmbItqXvphBhmxBxlreS407SnEu9stEdlOV4Lh8u6xu3Lva5GUkcSqPE3WJsozwJn5rhRM0pbct8hyh9ck1ZOrwOAqRINCvWKtE8bSxluu6h9kkCcA4As4DxaOUfKbG1MpDIEEvEmM4o/KeEQ3BD7lk6ceRap/P2LRlnUTxH6wnXMKOmE0/uUeJGDdQLx5f9h+ZR6i8HTHEZ94LZF9u59uIsI4KKyEECdTtyB1TxSDahmCmUZuGlBBwLy0r4gyyLRjqfp04IyHTM7m4FuH4MvLhPPTBi6gmeRjCu37YjgCQD+xfKf4Hx4cqO1yC4bsrOd7exG9lYuQwDE2TqR3HsVLynokSp35pWy6rQQ6iXOn5aPax8TD4M9z4IahcIsjU2QrFl1e+zw1YzB52ycfqUMgpufap9eKenX4i1jEr0N+T0UcW3yY7x6B+OPadGWjk0S3wgB8GHwnBQUjiML6evrjmfKMWGMLwx7frYs6sK4a8v307jYNmNmWeZuillpFgqIUofm9Z+Zt3Ky2FaifqWCMeXm3FYbUsR4AQCYaT1a27ulp1O3NqHEF2CSKfJQou4WS5jpJFDaB3d+bxrh3tpmXUfuxovL8DOv1jCHB7L96ansXFdSq1IUki3RmMNqBeQ5bFXGehR1w1OpAUD4JvNc6lemte+vFwG2xmdVfH98nYk5OoxBxy7JSOS5cEcAUq/x9JnEAnRpwMIgzk175eUgIqkH0QClP4YMRVc7TwBdiSoa7U3B84UQzfo6FqXr534Yc47e2oc5XyCUhPt+iUrXSuQVfG0IWYAOD7xYcB/vz6QOyyuFlwOQuM2kisf7cR4eP0Hzl95D+ZOnerHgMoe5WGBQKYBlIzEIx3D7/j4UAsQyTQ97vsLyl2Tfyf/biQobmZD2hCFZbpQF6OQ0QPTp/Xfw7DvHOPiTkzixTCuYy1WMRQQpgFxStPOlCDmr/SihNHiBvfGTxdZZVXklAFk7Dl5Z/CW+ViEWoiQzXsszvGw+wJkiGkMb1saA3IpG6tw6wQvdmxPknsKcyyIGBNs2vmjDIDfQOUCfuTwHsi6kMkN/SSjqQCZRN/Nf7CKP/BIAeG4Tej7/UJh1HDfm0csGQIJ4erzxyFafNlSMQHdYI2s7UNOBNVimuf22i2lFfVGtTWgDZVILyFsl+FXKvKrU6u24b9OAGorFe3u1BIW7HjypQuC0P6qRDxLUc4XK9jl5SYgkmKmB6L4HlwX623vInp6FMeG6BBkDLvMRWQ4VhQQZdYL2nBBkDRb3C+RP/XNDhGGvRDY4dMdyf7PcSNpycGj9tn4ixW62zVHmFsu7MmaTqhTPSwPugMghTmu4Ooc5zwE/mQ8HNS6+brH302l4Hfq9HDl8CpVZsi6Q4jbbDMiY0R8mHxR789TpmxvgVNtgaR5tAxDFhJKg43Mo6cNh+vJpIC3PJHiorN1tFzIGI3bvvvcQaD85aJBqIxUbApxpcNFE6Dd3fWgrfOF94RjgswOhGG4MFNO+brJfkbWj4JVru0CDT5mm5ro4bpykOZVNezIJLnVKyTYKKlZlSDWHcVRXPxVESlxqsiaeT8+VBm4TAacUwKVjy30fA5waDPYB8HDesohi0qENDkHicP9821QUQJHDaVDRB4810DxiyvL1GpsizW61QvbV96N2hycL4tU68nSmz0aSCQpj0LaxovbJaQx0B51XKRMga4XpXAOcB/vA3VvAk9N4fmNlArae7T6wfEt1duqlAsD/c/6/47w/2QU4d7aznX1+9sYvQ671EML2NLCTLEO2xSxSLyV4If5LQQROURVuALcJbgMasLOCX0g8EyrLBBKefBE3dT1s1PUQvkc/62uqyxo4lS+0xmuS5OC+C54B3AA4vwzywbrAjZnokgCAgdcmSb8mKzdKAwb9FO8FCYt3G/oFQJZd6mVB1va8bsZLNJBHcDq4VPTGGxWTWGbvKy6prsMyJHxp80wwG6ms5CpZOiF6Xezh8FoiRdMJmMfKbjAkcYjlSuj2FJym7SdFeaauAoM3FUUs33eCAqU8j3KLpSBojXOR7VzP64OcNPN8JYlCmC5fOLOyPFsLWMzN/NLgcfQugw0O9tYRkOcwCRKWphO0d/aQP0u0UOoKnFT4hmesyKWQ7vwSSOJaWNy8iO7Nnyy22Q20TlUuYKtUAFGyBPDub1UGYhkAQoe/RetUXf2gHdp4MpogD+h3LYSifuTKFnlYd5NKCMDjFZRS/9l57E/bRS5P7W8nEwnVVXyJFGmpWp3euO0CX2UAO7VtWFaw9tNfBzvjNTz9g6Z0/EUuxyt/5cGeUNIjBit1zLjtYjwpHfIiUvaHNqeTGOTRmEVRiPvtCSiprhGkClUjdTKRicyOXWp3NLvqKvsXHY4FSJVyVExqiVHoMqSupE9tJ9uTOp3AgdnHwKtqnbb3pihVL9XzXpIxGG7J0sJcZCHQGKQAMgNXGGSLAtZaNO8IOVD1abn1A8mzqQQ42zb0gQ/2MP9qhePPYsByOJjCGhM0TrVdV+dwVY6MGe4gAWU9+LJPFjew5xaV8ZiiH5C4ACt/4vNPPKKqB4Armqa6bZMQZ3Ch8IoV3al/67fsixg3uMKNmRYa+XgBdT04S75KWpCU1rxoOlSJfTbh320XA6fav8FEODwgWQ1/PJukvW4ct7luPPS6ueviVzLELjzILilKk/Rokm7turAPd7F9WrUjkiA/OOE8AkdPxrEVJvDAUK51GV0nQcVUtsHXp4T4USdAQDgnUgApvT5LnMQs/YSXsIfZpZ/0cwvqLcyyFWIdZfdOpQkSC5qu6dg0LYoLNxp3s24l+BuuyWfnAMDJebRfTBT3u4G9PZPFS/IfBLbvJEsS0IAU3bQQcbYaRHp+GIeKQvqiEX9rJeU2X4zSrMJX4clzkjaULyNAtvVv2XiGT3kt2P+v/SVPRBOqGpUzoyxHX1qUpXwBrQ2s4rRahb6h70P2x7RtZLzWZZuOt8/+hO3eBYfFKJvCbgCurkBG46E/h7EMIkNFqOkgqiJ8vhC26hFJsScFYuZwXQDg6gK03sjuqGeRZRJcTLEtRS5ZD0WoFoV4FJlF9+4R8gdapzPIfikCtCyETbzv0U4yZKUfX/Us2g7DRO6F6Yfwhddt6lkQM6jp0e/J8VmebRUr5qoElxmMD8oCAJcF2n0zKgZ0VQHbdFs9i+VXpthbt8G7AfBScO+3Z7LYBCZt/rxJqxdYkiPgJf36jxTIAQ89dvEh3XJOqJq5oaiDOQxCoecYSCaGoDGRnCNdi7J+mfS8G+v8oKLuMwPjjIiTr3undHAcrzOJ2wTl9KSIixUw5KtXFUvAgwvUdUGAeEPjJHB9ns8Fbu6vf3RNaZVuej2p5oZe95LGquRkYtWrtt114EZgyqn2aOhP0r45u7yiRg8gFoW5sUfInsJuREvovYL8AUXoNTPQZjJB+aUfO4ZpWvByheLRArj0tIWQmAWvG9inHgKexCyyELdJYhaLFcqHPga2bkZL13BtF3OJg62bkDqlwWHvozoWJwKwTooDN2MWdpVjOjDoYoEs8WKvCC89x3bZkJ3tbGc3srfHs3hFG8USXldXJJxjvGTg67yen5VpHOLKdhehyBvwc9UhHZHq/DwsgZYLJFkyCSGWYXnc/y/SlACJWdb6KQTbL/2ixgi2xqW+MBuRH73aKagbrpYPvIS9nZPFDbIhcddrhJPTKkdAUozcRqWxa7IhIEFkRs6GmPZLVdHIWlEMS2pXRophZj1WCcs3YLeqcmYopjqTvmuWBIiTBFlfTh64Kj35Td/Hda0/lyiwDTHLoufOshh41Rcjz6JSGCBoTp9hSPtNjuVatmVDdDyQgLKyLIlDCKkLZRmYnLCKARKT6HqwiWAvyvPIKZkqpVVlDASGjRzGUuJNyf3wWa0Qp8qzEJPiMgfaSFBMeS7xE4WsF7nEAxYGw6xEfp7cv8wK2EpRnswhNsBekYxzC5dbWCPLCeUMzawF7JbZoCqFb3SV8G1WBdrDAkUSp+K6lBiPXpPyjVQF3KSAXRTgBOX7MsTJb+dkcQOT0vXrMRojlmf4F965EQJy+7EOsPkoqASTMDklqcCREDI0BekfoGUWuTOaZgTT1v6QkZdnhJRsRBkdeXE1+2Dt+DwLEyL2WtYfXgwN8uqEpTiLScJnoefJC9mu5S8HE5hzrZFIgmV6LbzlAfTjoT8DCFBuAPGlr0rQugH3vp9lIRO34zhedRV1O5MXpT+ajIhdpFMsk1vXCYYiDXBOKoFwn6qEogQ8yUPRw7rfB0d5Ul2Be8M5NLdLZM+SlHVuYZjRHsm2zEay4v5QjhsKCXDmpUUOBC2P2V+UW8sWuC7lZb9cBFIeN5tg/p7F9Eex7f5wIi+1nyQU7u0mOZgAM6kCpwYggdab2ts5WdwkwBkCesnAp+nHlA0K8NofbnyjtgU4nRkzZTkGr9ZXeDoDk1Ua4FytY6Cx7RAYZ4YBfBn5EGJ/hijas6kbguVYwBiQQNooNdjGytBl1ChRcWUMQ0LaI+4pX8yvBDjJs3pp4M0+ehap81K2Lx9w3Oaaj5i99Lr7Pglw+nFqu3Hq9AKB9yIEL0PatA/aowCQPaDtAc5lBrdcyYSRBjgv5kIP6PvlFkuQpmqLPAYzmcWjWDchIEyeK4LbDpMPL4DT83Be4wOchRIXJQFOM/eTzEaAUyWYxuMUjU7PYS89KMwHtu3JMxx/Px+1na+aUYBTmcttkUt9ynyJfJUAyF5CN2QX4NzZznZ2I3s7PYubxCxeFMt4VQSnoUBXB0AQdWUJ0q+xVp1+0QjOqgRW3ovR85fjEnVSN32I8oes3J4bCE4sl+J6/ywRnJM6fulTWr2mjTBwvw/1/ReO4KSyEFxK1wNlEYsM/RiIVorfNq0FNXt+8TNBcEIRnE0b7vfLIjjZGlgA7nAa9ueHX/ZlyA1sBPdO19CvW2WbqnWpZUnw8BWUtl6tH5GzIVDfpbJ98IHEwpc0a1WnximMiX/Xvv+sLRU0oth/KnKwzrqeU+SLUo0fmSrDEQngSgl0hgiqStXruCrGILgv0lSwylCgDHxZ6/cK2GcmCBrJnP5lKlFXSzg5N8vBt5oG9JSjE8IvqeCjkWyA7p+Wk1/D4Ul5Md6PlatzBZARYhx4HtDncGQGfkw9h5aQawxAC+AUuToqgiN5SNN0okkmjtTyPJY6I5atS7McMwxFEeMHgYWMwxgGLk/dV4vN0klG9WG3PVM6vskxpsjHZes6+SnSVq93g6lrREWQ8qcW+dVnI+XTVC5L3T/LQ8EeAOFw9eXvZraXANaGwCEaStStCSXuGCKoTnlLU2IhdJF4ecRjqhyrXfQs3eXl1piP2RPPg4gCJwpfzmH2ZxjOniXXlEXvERgRPpvjQ7jTZ6Mg/suUqL+5nsUmvFsDh30PM5kEBKGpSrjVCqauI6qQnVRJNg2QlwEN6BJq9+z+O7Lt4lK+svfvghYr8L64aMMPfgy7NwUPg5D2wlclDgPo4BDwFYX8yQPQu/dgPnkwasP+6q+Anl16gl9/w44P0N0V17T48DHcoVfiPjlF++33QY5h//D70tY3vw48OBFl7/MLGM93MDx6DHv/HfBeDTqTasNAWX/7GP29g3CN+Y8eCKnOk1Pg/l3p14PH0mZVyXG3j+W8P/qJ9P/f+i6yM3nw7XINNgSeVugPK9i5vGgn393H7T+dg9oe7W1xgckx8tMVzKeP430LIkkM/vq7MKcSxHW39gEiDNMC+SfC9qPsTf1hjezZShTZAXTv30L+yVO4Ryeg73wLANDcncAue9hVh34WC76efKfGwY87sPVaHgBs6+ByQv3ZCs2dCtM/+VT6Ngxo/tJ7WNwvcPwHss3NpmjvTWGXAuEuHsUlyzAr0dwuJZgJoL0n97/84x/jz/+rb+G93/c7EtDMDPY/avDor8pLPX3oMHgV9cW70q9unzGUjOLMYPYR4+S35Bn9ld9dIju7FDlLXcIag8u/cg/NgcXxH5/BPBGynpO/8Wt472/+GGf/4NfDym9+32D/40F0SBjoa2mvOSKYFtj/6D4uvhpf++4f/5+4qb25k8VzPB5u2/j1a1uJDSTb0ljBNugsgMDGrC8zPT2Tr24TJxynMOnQlvcW5otY+df3oLPzq1+0x6cycaRfFXYofGm3O78ItPJ8OUf54RMAQK9flZMzuOUSZhDVdvVReBjgnp2D1k3ISATP6ewceSq6czkXrYvVGuaJfH104lN1LqOkLX68i4+fxiyAKpnPCxTnZcic3DYG9pMTsHOoLiLUmJcrr70xLoKDY5hHp0Fzg7oORARTFkL9BwBLaTOfV+DlOnhYOQA+vwD3PexDmViq+UpepKaFTVLFd7ojUTNPafWck3qTiwXsWRVZuJ1D+ZOnyJ/WgbiG1g3KdQNqOqn1uIyTRX5eSHrUZx40RsGrFd77fWD2g7Ow77TMYZ/N8Y6TiTg7byRFyYzZx6qibuByQj7vkJ+ukS/Ec7APn4qXQiZ6GIaw98MCk4nQ6jkfd7n1vUv89B99gHe+fxomzOmnNbKzZUiJqhTAUOcgx8jOliifxhjHh8ubg/F22ZCd7WxnN7I317N4HXuZIGMIWG4gOkd/3xK/uIHWKYC4Ztzo25XYwuayKyUwGUn3mavHXtevz9vSdo3XztwkxvV/AxBZwcMQb7n2a7VYXzC+6j1sjptuS6sp032T/odtI5Z1Dv8/byR1P8c8jhESXfkE87b7pcNGkP3TGIMGe3njmdzmBPjj2VE8n/YjvT/pOL3iI/J2ThbpC6wl6CnMmF2AeV8H9w6BRhNTiUJqE7MDIZia8kP2nh8xfRi3lPlSZgFrRuXllGUC2QUC8xIAAQBVotil/aIsA4pC9kuEYchIeTxZE6T4RnqhI2SpEWavpPQ+DXxJFmWjziXPQF3CT2pIGMK95igADJMMpi6FsDdBMpIvI49pXg/q8qXkYamWS6k45xHuHUr0rfVcEkk5e1KaDkDSmtSJylhdBkDXUGcCPsotuFTCXi9IXOTgSRkzCYMDl7mQ64axNXL9HNOfwTLRDTUKn9bAMBGamcHUl6jDAMNeAbMs0E38Pp0T9ioG+on0q5sYsAXYEmxToJlReBYQxIcii5grMrgqk7So78NQZWiOgGEa4zbDJINdyRjAcSAu7icWtiWBmVeJENXnCfcmov8JwO8AeMzM3/Hb/ksA/zGAE7/b32Xmf+r/9l8A+I8gb/PfYeb/68a9uaFd1fbgKxkOjeRfR4KToh8ZEKaoNIPBLiIJOUbj2TGo62Ku27GUUG+0wx4ZqPwZADwFHCRmkZTC87qBuVh4tKVHeC5XQquXlIbrtfPax1I05qFFV00T0mIAPOOUROY1CBr2hRDPhBiNN5ovo8SAj6pz3wuy0beXn5TA+RzshqjIzSxtdJ0yFY71R1armG3xY0BZBpdkJwCZWLhpQ9aCfMk8+3PoPkp8QwlZTHGSwVxelQKAlwIwSbAazDAXC2RDovfqGcq574WwJu2vczDMYZtOJG5w2P+ogX02D7uaZQG6WKB66PksFmv5oDiGaSXrURYWnBHMSqQA9mv/8ZovRQohJdppO5jzBWjt+6T34ekCRz+skD2JimRmVcFcLAVnwQzrJ7VsngO9g5kvkScfT9PfPGZxE8/ifwbw3wP4Xza2/3fM/F+nG4jo2wD+fQC/CuBdAL9PRN9i3oKKeg2jPIspMCVxSbVOfaEXuyH8f+Ucmn7yUgA0mwHLZdCmwMXcF1thXD8yOCG7mUqQiNcNzMF+fMF8W3S4D1zOR4VNNJvBHfsMSNeBZh7k2/Vwdw7FlT+RQCft7wmoSjMwCrZaN6C6kn4q34I+wPvx/ADEI6lr0DCAvC5J0MhQEJrPssDDzd3dIxgftFReSZ7WcNMKtJTfFx8cYtr1UgB14LU8mOW4ro+MWIE8B6CDfYAuQz8BwO1V0WP398PNapjLFci/wO7uEQz85H64DwAYjvZATQdatXCTGOC8/OY+pp8U8rVU79sxXG6RP5mjP6hhL+JLPdw9QndcofRZJZpNMdyawSxbDJMi8lFAPJj2qA4QbgVc0cUlHv3VKgQzAaCbZKgeFnj2bdmnfjqBywjEjIWn/O9rgiuB4pwxfVDh5LvimXztwxlw4ZegOlkYQvuVW+hmGaaaYQKw+OAIn/01h/rkMLS9vFtg+rDCkBsQA0Ml/W32LUzPmDyosLwfx2z45Ob4lRcGOJn5nwE4fdF+3v5dAP8bMzfM/CGAfw3g37hxb3a2s529sfY6MYu/TUT/IYA/AvCfM/MZgPcA/Itkn0/8ts/XtgW/thR9bd2upq6954II6mFN4hZv8BMK14Ffnii2gb2Lv9nOuvH8kQkrUdeBFmtxkZUT0p+Xlo248rqzFqvp1yVNzXpGr1BwpEuXpoWZRyyJazuJSaQFY2kh25DK/PnA3rKJ/VLF8LUApmgt+xbPOvGYBidqW3p82425PVT/wnlmr8StlrYotK/xEEMk1+a3m/lafh6G0L6Zr4VnsulGgbvytIe9bEQ4R5chA8NYAq0aUTPX++QYZtkgy00c29Ua5kIo8Uw/REJkiJeUWQrbzEUWxmj60CE7914YEahzMIs1ap+izM9bH7DkECPoa4LLCPnSoThvMfFMWbQW4WNWPRw5KbKLNagvgNU63PfyrMXkpxNklzF9XVmCvWhhferUrn0BW8ei2H6xRp0nQLbrKrO32KumTn8XwAcAvgvgAYD/5mVPQET/CRH9ERH9UYfmxQe88ISvlwWmNGpMNHqotu6bBt62QZE3syDpdvKIyHRt7SHb7Hy8JTl+K8rWl1BHqLdE0Nma8I800j+K/JskuOmj7iOujGRfz9+BjX05S/qtx2/GCUK8Ii4N075vnlP7xdaM27IKA796DaN2SYBYOlGwBgINBHOwJUsRzq/mOUDZGoF32/hPxjTZlvl/xmDICZwZaceSxI2sgctkQtAx41ywFS6X7UMh/WVD4AzgDON7ER+A5Pw23HfOCK6AtBfGQPrgMiPnzvx+GWEo5BqGwoR/L4H2fjXPgpkf6c9E9D8A+Cf+108BfCXZ9X2/bds5fg/A7wEC936FTmz87q7/24tMGZISMVrfxyv7vbSl6avRdjd+oa60JcFO2uYxfZGsVumLnkLidXwASb0NWyZThWZvgrLCOTYg9q/bT8cj748YPr3IIFYmcQbnun8M8AISz6Dh9ceSGKNrkn7wKPgL0Cj1SazHxf8BeBZzBxi+0fNGDpG4OelLaDug+V7p0kb2SpMFEd1n5gf+178O4P/zP/8fAP4hEf23kADnNwH8y9fu5aaZjS8bMGLxDl9F4HqPI6kaBSTgx8MAKCJQ6zjIgbUkwRopSsujbogwXxcjwSDAp/TabnQjUZVw0wowgDkrIpPSIhPBXB7vS55Zi9ouMlIpq1ZdxZoPXULo+b0p2Q4vVyGAGKoui1weqnC9Mo5uVsE4zZj4008q2e5/X9/KUTyoAOfgZrE94xxonmh06kTJHMYjjA0AN61gL4vxtr0ahjlgNIa9Gna+lK+z36ffr2DWGYwxowDn6naGbFEJ1kDT1YPDUGUw6x7DQRXSpADg9mu0xxVqZcuuS/T7FezSYJgUkVwXAE9K9Idl4KPQ6tEsy7B4lwIyE5A0pWnrEMxkivDz5V3j9yH0FVCdGpi+wOJ9Cn0gzWLpfSBCd1Ch27fIH5ZhCbw+LrD+5TXaw3QMLExXYSg0wCnn1QCnbUusbyVjkH++qdP/FcBvA7hNRJ8A+HsAfpuIvguZr34C4G8BADN/n4j+MYA/A9AD+M8+70zIzna2s5+PvXCyYOb/YMvm//E5+/99AH//dTr1IgtIQf1Z13BpNaLZ8Dw2LQjG+vWsB2VxCmrSfYKwsfHqX/aFoCwFJ7G1oQ+cJWChzMa2sgyuFM4Fo2Axz5lBmZXrU1CVIdlmTehXCrTSWgDZHuMTvAnKoiRukZgrMhjtl8oV5AIKokq+wH1F4CoHdQOGygfmWKpIZU3tgUv2uSDxAAAfp0lEQVSK02AWbyyL1waSNfxm3Cds2/idfD8AgAsDZgseMrg6Cy52VxOGUvALzquDm87B5QauyNDXFrkHZfHg4AqLfmIiZWFmJTaQy/9ItFw4l7W+bgt0dIZ8UZh6sgK4Kgsbirg0mCmgLNnW7QFDyWg7Qjcx6GZ+6VbkAtazJtL0E8EVBn3p2/fj21eEw6MF+mksHuwmhKE0GEpB2PY+ddpNANtK3KKv4juxjQHxOns7EZzX2Uus5QOprSpmW3M11qPM2CHY6ULQUMlFJNBk4/n02HQCScSAeBOGDAiakCDBsQ0dDqoxjqPoubIEKamTkTUBsQcA1poYINzgYxAEKF0RmWGbTCB6TeQDh34YpKKRR0HNFByd6o2ErebqdXOeTLphIvGBQ722ZB/2E4CzBmTSAIBvroAEXzFex7vCBzcTugIdtxHVibUi/NPL/5wErl0+3uaKuMwdSh6582ylH07BrT6YSQz0frUylIyhZrgFgS3gKt9fgxjDSmIeQ0kYSuHyNH48hoJwa7pEQ3GycIUGUGVghoLCdrbSb53EQns3tDd3stjE/CfGzNtjEalnoQ/LixCcKmff9ZEGXk+3AfeGkUpA6qNcnWOGaTqpEUgtTSPqC9oPMOskzqBfDmtgegcaOMK1nZTZBwSixiV8Co7WbUhtatDONB3sIuXE7EBNBzc4kbWDIA4BCNJycDCJ7B4A2FUX+T4H8dCo62HX8SUrL11I/2qAkHoXKPsDZF4rf5nlZx2PfgAMwSyTtnyq1C6s/Oy320UbxtJ0XgJw3cM0Pah3Pkgp5y0uGHY1gDPxMACZNPLLAdQ7mC4SMsu197BtHoKktG6QLQqRFGQeiR1bA+SlDduyhfdQ+h7FmUHu5QeZZFIzqx7FufQrXzpkDQEsMQp5PAhuQSgugWzNKJ56z2/wk3BmY3rfGBQXfeijPrvlpcOHj27h/ZbDV6q4YGSLAaYzAAMmZF8NbMvIL/vQB7lvuLG9uZPF8yLmqjaG+KIoBiIc+yKcRULYG5SmlDnbH8eKkwhtiaKVUMd5BbFhEBjyBmEJLVbgxqtLaQ3Hag1z4b+gTQvyZdncC+QXg4NT9ONiBdf1AIkaVxBediyTABBxFjpprJuAvgQUZ+HhwYoZ0H39z5HwxsOFL1axX16KgBxL0NE/vPWjGrRYSym3eiz9AFquBb6tXoSW5zsHWq4jpsKf33SRsFe/deRYsATKV3KxDPB2msuYZ0SCs+h6UXDxz8D0YYHsbAXOLexGbYi5XCHLbcSVDAPs+QplHglxCEJwS20HanrQIqrE0eCQ+/sCRCJc7jrMPmLkp358DWCbAvZ8hekDcSOK8zbUhpheJhmtDcnWjOJZj9mHnmpwvgSv12OSJ2uFK2RdyHPhr6F+1KD4swnK0wRqPjCKp2uwIjj9OGSLDLZ1yE+XmKaORXfzNMmbO1l4zyJ8CTYo9QOkuMjBfSfq5p4qnrUQx1Poj1iX9Bweak2+WhLHB6B5JL8xT09B0ymoaeC8d2LKEty2MNMJ2JPf0HwBHB3I/0Boy905hDnLBAyly4Rbh2jvTAECyraDO/IcjX2P1Xv7IAaKTx8CAIZ3bkl2YTqBsSbAy2m1Bs32wNM6eJDhBTicob23H66xWK7As6nUddwSSHDQvSgLOc4T8OCJwMzb9w+Rn/oajKVwbwyzCv1+GcR7n/5qhTvNHqhzaO94GLpjFGclbJo69R4E2g7DnUNY1fu8NZPz1jkK7105Jb85qpGdRfKb9r0jFE5qWIZ7cg3rOzWy9YBs3qHbL8JX9clfLnE4sbIMMBqzYAwFYfIgR3NcYu/JLDwLy186wvJuhtufefj5rEbzzh6yeYd+Lw+SggAw7JVY3asCC3fgzHz8FCe/1Qc+ChChmRH2axsg3JOHmWAoGCHr0c0cXCUexezDAmf/jkw2R39+jOy0lGWx9wbZGsy/sY/1ocHtxWG47yffrvGbv/M9/PmPfzWMweJdg9lHFkMpnkxKfmMbYPZxjsuvxOVV//2bBy1eD8m0s53t7BfG3lwOzud5Flk24ofkvpdSbI2WB4HemOffNFNpIZnySuaj9lzTwJRlZMsCAoejcjde2Q+I7vxsJm6+ei6AqH9rTn/dJHycvXg6wxAqIKmuImYjrTptO8FGJNWo6s2YRMQIANxiJRyTbQfjt2u1q/JcBs5QpQO8dRxjDZ57UpXOAp5jtif6HH0f2L15cAJvT8rpQzakbQXvoUVsRQHlxQzMXVomnmdgz+IFAKau4FZrcNvCHnivqfRCPF7fQ+NSNJsCy1VEWAKyT9IvjfMI43kt2JcnvvTJed7MThTc0qpTValnz06m4+zOL4C//CuBxQvGCOXAfBm8Nlp7uLfjgBXhIgeMxChovkT3rhSi5R8+lGu3Ni4dDQnepsjhnp2H5ad99x7WH9xF9aPHYQy4zGWpFLJMsaSeuh68XI+Eof7ws3+I8+bhjdyLN3cZ8hzbWnZ+BenI4/83d09V1ElSopsTZ0B1bpz3Sjl8319tx08UWnsCQMrN1y6kYGMJtxPq+7StYRyTGcVE/EQRl1cJoW2iNB76qerv6b4DQlxmdHnrJl6Lj8qzc1Jtq1mMRaI+Tm04Lw9xCbJpnAQ400kk1KrotXt191TdPtAQ6GSjLwazxDp030t4iQADKB9GItAUXsLQp06AY7ps0noc50bq6gBEUlDjVdJ4GOPs7DKUz4N8rUnTABcU7wMgY6j1Np4YGETg9RrZaVxCKzo1BLUdZJJqbKQ9AMDzBcqHlzJGOn5tG2JNcByzTdYf27YbdUY3h0G9lZPFVksZpK7TN73muBEztpKxeClDNi1UrzTFd9zYUsar0XYTU6cBVzAgzCyGAMpArpMah3TyewnCktcy7aPWkgRsComnkWpqDgARS18VHasTsdZyJIjEa/EvL+qPtg95iWBNJDLTOhNF1QLBqwj3WQPYzmfUsuz6Op4bGifYB3jJSU7ue8D/mOTeWX9PM4/vSV5qOBZMSvBIs+0vNUlNisnGfw+1IgYjLM7rriHe3Mkimbmv/s0lP8Z0qQuz/g1mioTunthrUToGwadE204COsOQSBPeHMcRa01ceFgICC+NZmF0X+osOCFXgW8bzo08nPS4L8TSL60uobRaUr901oRK0PCVchyzRwl1f6DFx8a9fBVcr35R9XfngmMjf/egOccbUgIM5l76nWR/yBMfpVIJr2I08vJIsmCDS+pn/N8cRwi3qrT7JVcIZq7WHhqQYEKu+/oPDtQNwqgV0vQJc1z6nrzWFfpTfw7n2NnOdvYLYG+uZ/E825g142ZdI77MqWjkQoZliOmvuqevUgafLHPk92TJkxLbGgIGHu9rk3V3UJH6gpcgidcS+qhLkQTtKUFml8QAhlDMp4HbzbjRFeGbl1gvj7voQWqqVrYhXgRrRml0dAnPauKhQaHzoT+vWIFqknvsuVuhcQMAgtTaGAP11Pw1hGWIIVleJUuPkejSqF1/X7Isxrb0eTYky+fNgsvXsDd/srguW6PbA5rHXM2Y+Ac3KllRODY8TE0DsIPZE2q8EOVeLOLyw0X3l3xUOo2Gm8MDOK9RGjIT+/uiiJ32aToJtH3uyalodgJwFxcwB/sgAP1PP5bj96aiLeIj/9pf1zSgsoSZzaK4kAc/0cTT/el1Pj0TMaHFIuBKgk6HVyrT/gynz2Qcbh+Dl3pe7+PnBWhShe3uq3dhPnosBMdJZB1LyVoEhfXEyI8HgJBBoVtH4HNPtadEup7uLwC4Dmbg80u4ebwGmk7E9W/HWqf9e8ewTy7DvQIAcgX4+EAEn6Y1+JMHYX+6fQye1oDXErG3jgSX0nbgqoRRCj5moCqlIlQVy2dTgAjm4Qku/8o97P0w0VwtMpjzBdqv3AIAZBfrUEvSHXj6wMJgKAnFRY/8dIX5NyTTM/vnlzJOaQxiGEBfew+uzmE/exqWUu7r93HyG/u498/iJNcfTUQ3JNTWeHj6JAdnhPxkgf4o6obwn9xcCvHNnyy2WMrYfS2LNxmAE6j25jl0MHVDloFsHwNgSDwVN/6drB3pm1KWJe0oX6cPWqaTXZZJysyfQwuryNqwPd03/C3pbzi2yMPLzIOHrGcZONHBJCveAPu/ARgxgrOJRVRqXBahgCnwiRae3dtvH/YKWE0BJ/2mXjlPr07wYTz0Zz021IZkYRv5dOdoH0OBDZ0rSb0SM7iM7Xd7eSh5D9fDDFfm0t+yGHmLXBZwdR6K95DnYfy4zEZjw3kGNylgL/NwrLJeNQcWk4lv1wGuykDrDt3M38O+iJPFvmfbLmWyAACzLrA+lL/vFznQXCVTcnUuvKBZBhi578OkwOo2wVXxmrtZDrMqpAAPiOzeezmYAFvn6GZxzPglPI63Z7JIcBe8Meum/4+2p4xXQNQTTfL74fjzCwnEJWzT285JFoF1WzY6uMUyIkp9G+7icswWDgiBr8djuNU6nIPbFnTydNzW+UXoZ9rfcCxzhG77CcktliE1ByCk1LjvwZ7cl71IskLXnd9uVCf05DQwbqtXROsGtFgI/BxA8SMKnhQtomqX81/7bS5zGA8gXDe1bQw4qtu+XvtAqQ8EPj2LX1Kv6UkeXu+6PmBrAKDuesF/bJjJMrjlCjRfjLVOT05hzvMoT2lI7n/fw2xqv64y2MsF3MJ7R03rl7CE4z8+A51EmlprJJA61dTrah0myvyhx8FkFmytH9sVbi8EnZriKFKznz2FzTJJ0frJuPjwMd7jOzCfnYT9JmcVeLWOyx3fbqET/sUc9Xn0/Exz8+KQt2eySG2TgWlzm9qGVyHkNT77sQEBV5r/5zJuMYfUViTaudoGgJgPT8/XtjFTMAyAQhSU3j9tyufbVWh4c4Kkbsx3KWzQCY4DCGtpyrLrWb90LV0Uko1ZrcYYFEjGKOAfAHDy4o/d5euFkVN8ANIMho4/s6zV207K2bV/iq3wOIFwjPO4jnRionnQ2hiZZhaGYTyOq5XgEsIHx4ks5TBE9XlAnEWOUgeAX5KWQkJknpwFSUHAe29djFlw28WXV5eOZGCsLJ1d04ZMw5COUzpM60Y8CseB6Z0vLlF8mo3ahsdSXNGUsRa4e0s+TOn9eYk4zS4bsrOd7exG9vZ4Fin6Ly/AvXdpsxzctVcKxiIMPKEQS1TU7b4ElNQFtbeOpNrPB9/6R4+lcGxwo7YwDDCTSZS9f3oqgUWP4NM2svfeBS8WIxSgme2B970A7uMnoD352Z09A71/X3b6iw/l73duy/a6FoFk395wMYfd3wPVNXgxFkam2R6wvxfaw6MnAo1uOxgNrCYaKAFmDmB4JOrq5lsfwGjV6XotMZmqBE+qsL354C7KD0+Eh2Pmg2WOYRYrWSqkCFCI12Dv3A79DZorkwp4KoLCATY+raViV6Got45EtPpiDvuOKMHz/lSuqe1GMZr1149QPvRBSfWunJMq1NM53KyG/clnoU/0/jsYDmrYH3wc+sUHe0DTSuwm+epyVcDNJrAnshTiAx8w/vBjnPyNX8Ot70WNkaHKkD9dYPHBEQBh4VaejfWx9LevhGuivHSoHzU4+bZ4C/f+71yWUkQj3RD39fsYJgWKDx+DfUC2+/UP8Mlv1/jaP43Fg+tbFconqxAjcb7qtJtmoIFRTko0d+uwv/vDL0OA8zl8FlSV4IXPOtQVhr4bvTyAA5XCqan/Axidj27JjTRPzwBrMbx3G+Z8if62x/M/eQrak8i480rTZloLIc3xIdyhj8zPF+D7t69UnXZfu4PscQmzakJ2Yrh/jMX7E4CA2fc4VIgWRHj2a7dBA2P2008AAP3X7koF5/4ezBMAWjW6WAF3bqG7PUP+wCt3qyDPu3ew/Oo0XOOs6zEczWA+A7qv3wMAZD/2sYC6AlZruHfvyM4+ZnL5nduoHnvOhguRLegOK6xuFyifyaT06b9d4N1/fg+2GbDwgjU0MCaPWxT/Oi7RFDlJbkD79TvIH0kmpn1XyFrWxwVmP/APs4/Qr+8UqE5aZGdyL+ffOsTeD6VsvPllmSzm7xbIl4zivMf6VhY4Gx78FuH4e0dwmRDhAIBtgKEA9n86weJ+hrteKoGGAc++c4yLr1t85UyyFu2dPcy/WqG4cGj3DfY+ii9Ve1hg/p7F8fclJjX/qkxux0+f4b2/+WP89B994B8soDkCjn5Y4bO/JmM9+ekErgDIAetflvYPjxa4NV3iw0e3UPzZBL/5O98DAHz0o28JhDszIM/fAWNw8hv7WN0mvMd3UHwqr+0nv13jX/2tf4BfO/9PQ6T+8hsOBz/Yx1ADYGHkAoDm7gCzJhz8xT7Ovxnfg/Ylqk7f3EKy59gVz6Lv5P+0VkJ1F4yNCLrEzEwmBW5bBEWyro2exeMnMHUlsQzvHWgQkMoypOzc5SXMbAbnFb30K2/v3RVeBl+MBUA8EF1vPrsI6VderYC7t4UA92P58tnjI5n8rAU3TShAc/MFzME+YGxIRYaiq71pSMcCgDs9ExLf+QJGPakLr77lPQv1OIanEqDLfulrQWOEu05e9rLwBVvy8Hf3j5A/fCboQ/Us+gG0aiTdq5kN5bYYhpFqW0jvGgKf+VSkTw2HFK3qfB4dgM/O4ZZL2HdkwuNJJZmZrpfCLP8Md/f2kZ8uhRqvUJ3RQf6tGvFkHkkpPgYH3D7CcDSF/ZEnoM8y6ZsWki1iIJCKArxXAz51qt7R8OkDXPx7v46D7z/zDxYwTEtkTy7Rvi8TfHbp+SwcB3LdfmoBAkzLKE8bXHxDznf8B59KCn9D65SP9uGqAuazkxDE5W9/Aw/+zRnu/8FluDfDnuf0sBbEUet0mOQwzYDs2RL9YXxG/uWf/i4uLj/98haSXbHXnPAk6Jmwaz1nv9cylRrYhGv77eR4FHgMhVKbxVmOv9ho0yhonFC8aTA0/fs2KYCUhGhbYVkYx5cECm0LbG/72W1ew7b/5broc/hWCq2/XyY7SeluPpPXtsMb/+szkASK+XlBSIZnKEu2OQBKH6twpM/BKdgFOHe2s53dyN5+zyIFlaSYihcJIyeuMhEJ0pFZkI3hfOMCMmUQpzyLvBHzhfy8kd+nqgzpT01fUVkERii6nAtICAAWS/CkHFMDloUIH6fViPBpTCtBx1GpMSRIqExfgMRTqKokl+/7S0vvnvtllC67gm7IVHQ7AATFd5QF3F4URm6OS9inVorD6iKMVQBlbfsSVmUs2CpySWfWZRR1rpMAJ1EkId6byD6rdRgvN6tg1r0EIqs8fFXXd0rYZvA8mH7pZ4WtOxschmkBm3hCPK3Q7+UojA19GA6mMOsWriokZqT71iX6wwnylfQ3CEI/yjC/bzD91C8vCRgmGcyqwvKu9LeyohRGLLoegLBwu4JQXDDMwFi8K/09KpOUrYlVvv3RBN0sx+SsCiX361sVLr/hcDdBYa5uF6gHFlAWA0Ml52hnBqYHagCrdyLq1v2rm/sLb+dkkWIXNjgdwi7XgLXC3/WGOAZDcugjbk32mIH04RoSbgiKgB3hgNhof7mOeqK6cb2GuRS0JbddILrhvhfuTGb0WrugPA5K/JsCddoOTCZcg8YseL0GXcSbL3yYkhUKKu8pu3XfR8i4kvbMl6FfQZOUWYSHPAS7OlkLj+YwiDapHr9aj8+v/KbMInSk17CKQcYwBkpgwzyOWWh/2AmxDTx4qhddWhpc6Hv9qIQ5X4Z4CACJTWQWtFjBKvcIADgHc7lCDoS22BCsMUDXwzbx/khfHTIgbLOqpt732P94CAFZALCrHOZiielDeSntRQtYCdibzme1SpEyzBYDiqdrzD7yE9ZiJc+GJweSjQbZ2VKQmZ4ICADKJysc/GAf2dkqTJj1wCFuAwBZrhycBah3yJ4tEcO2gOlujrN4OyeL1K6Dc18HA1dLi8R88c2Is8H/ztcV975AN4SsnxSAGKMgM+KEIN8H9nICmvKVQ8hrdSaFZ2l/VR80/ZuyQqfXSKqHunEe5ajYjJ8YE/ulvAjWxqItAC434WVRSQQ45xXcrhaikXMgYyK0ONVsUQh4KKQyUW9lY5/R/47HBViA1xgR7gyVDSBjou5KKp8A8T44twFKH2QdnBvJO0ibJo5Zct1EXrNUdUSIvO6IxeAh1zYzcJnoeAxeQmAoDVwGmM6A8wj9hurM0LjAka0VEl59LgBwZjDU8BqscQxU+wQOsTYkN/K4GAMukuf1JegO3v7JYpu9bDDnGlX2zy1TtBmAI4rBzmQ7qShy6Ms1s/6raK6+jF0JGLrxdk6285b+bmyLjGBj/MVr9Y+ToPCWv5M6lFoZq+O9hfnstbVj01MGHpNx8FQDjOOAI+GK1ikQA9hBr+Y5S4UkuDrqy2te0jZ7OycLMrjCnpJuu8FsORIFMhREd7TIKXgW6X0yJE0YM/Zotnk36RdCd7MmqpClxWihTBnBswhf86AcNi5dp4RpK5RYWxu/9HqN/jzRWxgXkm0qwLNnbgIQQUFZJtsH/5UqE47L4FlwZJ1KJwPvWYxU5xMFMGx4G5z5L32i4hbLrv115pmHhzsZT/+yDKUVtzv5+tIwBOEizm303Jz03RVZLCRT7s5+iCrqyXW4IgsSAFG0SUR7ghIcEVxhYfMMg1cDs2tRSYOL2qN9ZTAUBDNIv4Pwj/XeEY2//pxbSYPa6PG40qLbk2IxnYSGSsYgehQ+dVoa8ECwRRbkAQC8lCLZLhuys53t7Eb2dnoWqV1XYvsiFXX9wjf++Cwbf+2BACjaPC9lWVTdIiM/b7aT+/MlRLfIc4new6/RfR+IRDt0XM4+ZmcefeWskYzCOiHHgWR43KhE3fM7EgVezBHvp9dVSbeLhqmHj/dR61SyDuIx9FOLIs+k31oiziJCNOJ6TONCeTaWKiQSSLW2r8zsZSHt98nvWSbrdt+Wq/NI91fG+9XtWRRlDrYUysdpEElHU+RwVQ4b4gAOXOYY6gyZZh2KXErWfRt2lZRyVwXcJA+l+a6OVAPNkWig6Dj2E4tsnqPx5eimY7hMlhy6rZtAJAXJIFtkaI78+PvnZjyOBDfJJXPj9WQBgXA3dwcMkzwsRdqZQbYo4PIYGwGAbmZBAyNb5GhniWdhv4wxi0349+Y6ON0G7/IPIg8Q0J4p14JOAunvI07JIWHEjm1RVcpDrwGuPBNEoQ+AhXXm4EFeid4nORek9oSiPmZsqHe+Wa3M7ARa7su105J49J7FS7kxAJnk8kyi7trepAbvT2GGIdRQkLWyX5aB2AVqelPX0o8hxig4xAWk38pnQQPkhWaOkGQ/hpwyYKfWD3FZE2QbKaRwuSwAH3B0h3tR1iG3MHUF0zSx/V7GQ1CcsX0aGOgdqI9wL2KWIOgwgDo3LlHvBthmGHFnOJ+KXX5liqm/V9QNcJNilJJla9DvFaiOD2FaxNgJM2xLQO9gep9h6iIPq26zrWiP2pZhWwfbaJ96yYZsDB9nosvKRQ7cvRWu16wJpoljYHoZH52neaCw7+X7FtWpGemyvoy9PZNFMhHciM+iF+0Qbttw7KbosPwQKedHKdFt5xwGyfmn+feuB52dx/Sl9mfdSKlwmkpMUpuubYF11NcwF4vRdWo6VjVQ0omLux7wMncAZJJTxq8EIcqXc6Dt4BaLiDBsW8njK1PWM4F/Bz2R+TIyZSWSiSGlCaA8WYocADDCYPJyHcZ903Q8AITrNucmQJeVh8NWpeAn/L6264Upa7WG8ZBwQwT0g2BkEkxH/aiGPd/gs2AGNQVovoR1jCG5H2a+RMYc2jLnl8iYQW2HvXUL0nviHOyigJlUIK+UZgHYZwbu9Bn2P7o/Sp1ybmHmS0y8fGF2sUbmvQHbyjUMhYErDPLLHvnpErOP8ziGbVrDL5afLGBr4aMIqdNJiYO/2Ef2LLZdA/K7ny2sh71nixzVqUHxaA7qItz7S586TYFW14KvNOBp7RXwEoD45VIsQVUC7EYiPYFNK2mLrAEVRQQzXc5FrMaTyATBmxeApkjBXABomUUwlbrPHuhFeSZ8CHlcLlDu6eyU7q9FAJa52QYoa1KJhqvWpHisAhW5cDLUtR+uc9FR3ZuECUBTnVRXASwFAM2dCSZPa5m49uKDRwBoudzOlJWMR6Ak3JvAKI+H75+Av2wIyLr9CUzTgpomALfcwRTUdKCVCZ4RAKzuVZg04wmemDHUObKuh5tNQI8S9qu9CfrDGtmDIvTBHUxgli36/QqZekDM4KrEcFAFUJY7nAou4yTDxVczlE/9ODDgKovcAUtfZFfnJqRM17ek/b4i9DWhOjWYEoKk4P6k2vq8KiirPl+Gib+5W+P8m4xbfxrvweqdCjUQ0qMazGxnFi4nUDfB6l4iRJXfPGy5C3DubGc7u5G9lZ7FzvBSYJrn2htQdfymGd9wbD+PIrS3yb78k8U1oJ0r2QvFTrxAnSpUgm6eb1OI6JosTYjSb+xz5QHVfmzL6mzJ8Fzbr8H5qtoEELXlGpVSkGm7ghoTxeVJiB7SqN+pItwVS7fpz2k30uB0Sluof/NSf6Evij5N2mdDV3xldhTxLh7BmF7TNpwBMYMGN4qHXM8y7wSLE1C0sR+hviXB2zgfgBaldwTFd9YExTUTFVMc90BvaEjU2dPnyMjvHMYqbg/B9Vf8zrwRfBZEdAJgAeDJz7svP2O7jd01/yLYm3zNX2PmOzfZ8Y2YLACAiP6ImX/j592Pn6XtrvkXw74s17wLcO5sZzu7ke0mi53tbGc3sjdpsvi9n3cHfg62u+ZfDPtSXPMbE7PY2c529mbbm+RZ7GxnO3uDbTdZ7GxnO7uR7SaLne1sZzey3WSxs53t7Ea2myx2trOd3cj+f4vTPoEZtkSgAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.80332660675049 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-08, 'kernel_type': 'size'} is: \n",
+      "[[3.20000e-46 4.80000e-47 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [4.80000e-47 1.36000e-46 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-46 ... 3.20000e-46 3.20000e-46\n",
+      "  3.20000e-46]\n",
+      " ...\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-46 ... 1.40592e-43 1.40492e-43\n",
+      "  1.42048e-43]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-46 ... 1.40492e-43 1.40860e-43\n",
+      "  1.42090e-43]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-46 ... 1.42048e-43 1.42090e-43\n",
+      "  1.45508e-43]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ad7978>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.86416149139404 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-07, 'kernel_type': 'size'} is: \n",
+      "[[3.20000e-40 4.80000e-41 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [4.80000e-41 1.36000e-40 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-40 ... 3.20000e-40 3.20000e-40\n",
+      "  3.20000e-40]\n",
+      " ...\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-40 ... 1.40592e-37 1.40492e-37\n",
+      "  1.42048e-37]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-40 ... 1.40492e-37 1.40860e-37\n",
+      "  1.42090e-37]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-40 ... 1.42048e-37 1.42090e-37\n",
+      "  1.45508e-37]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.74723982810974 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-06, 'kernel_type': 'size'} is: \n",
+      "[[3.20000e-34 4.80000e-35 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [4.80000e-35 1.36000e-34 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-34 ... 3.20000e-34 3.20000e-34\n",
+      "  3.20000e-34]\n",
+      " ...\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-34 ... 1.40592e-31 1.40492e-31\n",
+      "  1.42048e-31]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-34 ... 1.40492e-31 1.40860e-31\n",
+      "  1.42090e-31]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-34 ... 1.42048e-31 1.42090e-31\n",
+      "  1.45508e-31]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98abac50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.93524479866028 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-05, 'kernel_type': 'size'} is: \n",
+      "[[3.20000e-28 4.80000e-29 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [4.80000e-29 1.36000e-28 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-28 ... 3.20000e-28 3.20000e-28\n",
+      "  3.20000e-28]\n",
+      " ...\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-28 ... 1.40592e-25 1.40492e-25\n",
+      "  1.42048e-25]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-28 ... 1.40492e-25 1.40860e-25\n",
+      "  1.42090e-25]\n",
+      " [0.00000e+00 0.00000e+00 3.20000e-28 ... 1.42048e-25 1.42090e-25\n",
+      "  1.45508e-25]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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KjNkuCnE+gHgNORe5GHTeUddA20a7XQlpuWvjHFE9GmR9oqND8GIZGkyaBTkCN634J84v4nN1BzNgMgG9OpFDRNJeeA8ynoi6ljlYLmO/AKA/PQd9/BXQ85fhviQf8HoNOjqKz1c/aL0OVQWuHKjtwMsV8N4jufzf/F7SKs3Y3OExMBqBT07j86nef4L+ax/A/ZunIJ3z6RS8WsXFK87rKPgsVuvUBwD0bPcl4GEuFrvIVVGLrDScj+ofl55mCzMO92PPIMXXM2+yLSGpz1m4qvdAXFRyktbECq5wcM3pGIj1Q9TVDRxA3+cqqfZTx2fOjbkPhRnCTZNCc2oC6VhDnzjE97nvUyKS/m61I2tOGLOMu0520sEM1SZzcKJpourNJfLQ+2AuhP4ultG5l7NnyzjLN4HbTtDkcZwMrNZyTeng5Eba02O6kLAHXSwz8y06QtVxqm1bx+1oJPltzMB6DTpfxv5Gx63JQOXVGlR12XPn1QruZAG0yfRgZlkYo1aTw9fLDQxfCjMkMx+GMg2v0Cwi56XsgOIFp5T91zTBPEg2LzmScwJ3I4DEtVjAdaNG4NLHQ3Wq98DM6WeItxvs00tYVbJza8qzaS/uFvbDD9dYzSL2zbPRmFwai3fpvp3u+uMEByafVOWwmwMSdZD7V5lmga4LL7W2pY9Ich/0Kdg+kmoQhWYBe65nsMmfoPE4LoA0rlO/DuaiUbgKNNK8Dy/jaTtgMkm7dt9LNGQ+AxkNgqYTQDXMAc1Cr4+7c9OCjw9AxmdB41oWkcMDObZu0nsYrmONSIT3gI/lXDo5Tc8Sbfp5OgFGI/F5GC2i++AIo3NDgFPXAC3Tc9d5GI1kHijXLHC+e4xjHw3Zy172spPQTdFgdynH9B7/cfqTg397Y7R6o/pyWr2r5LpOUXWwWs0ASOplqa7fF/T5sn5vy2rVn4Hb0+pdt2+X9ak8xsO0etGcu+mclhwgA87qMru27F/ZryFavQ0hymHptq2hPgyM75/w93DKL3Z6Wd9eM2TXKIeaIUTJqbXNNCmviz/S5vEAwtmw6fWduIKwNyNFvaTtdH4AA0UvfvCWD7FOVRW4GUgHvwPC3o1+Zyng5t7OZQCfaIsHJyGABEYqX2ZH4WPAppf/EsJedUpbD78CtGKfgtMzbjJ9L/6D0GZcjPs++jYUCMfNlg/czkP50fse1eFBvAeACNKLc6m+Hvt8g+kazz0IZsh6HU3U2BPnIjDPhk7dZAI6PBAHaexzcPyqQzUSDcnzejcJe3nLjmr+JpLwEnEH2yW8mDnfYFZi3XEw7IDbUSxRbBT1XTg/vBsA8BoxKLgQMmfmLTH+l8lm/kDiRoghyKqKjtpyzhkAX5TO1Jx5ivhm4cq4IFmMi+0vC+6DfbfhwEYf+mYdvVUljsxtms91+mWiZ9x1mw7VGALPnYtKYKM+D79eyxhcs7lRbLTrQU27qXV4FmctkMK2dwBLf3sXi13lxqCsIuYdd+FL1MVt11/GcZFFUhQcNHA7PWYg4BnOIst83EIyU/Jl2L7tAoEv2yn7pqLApwJYpv23zNoUuCQ3KCi2ZZHuwO6dnULDizJFxqv872RrKLVdxnU5OH879MsvV6YNMzdDYD39rgt2b18+Z+/yhdBybcR7tfCLYuO5bKPUDXjP7r2XvezlPuVhahbbEsmuew8rA6XxNq8xvpArfBbbyGi33X+jArgxWeT8ZDNHXoJ78lkMEdVm41B0INv2TP81UUx3WSrMEK1eHsZTNLbdZzHkByInbdt+uYSIjDiYATo7qgPSU02qsuzfjj4LN5tmEGolxrVh8tim+n2cE19G8LOogzMmEhZaLod52yhfeCBFhjIEZ5EAF+WdL1+4Td0e+nlIrd2WlbpxX3khIyiLNxmWoyMVMC+Vj1mGeRvGVDALTPzoCy7M2JsdODi56yKaNI0z4SfieaiyjzSO04qOg6TPQ76W5NNJGaIJ4VqowMyDZfsiBZ3+HBeSAUcz1blPyTuAYNq0HJypfULoV/BP2PvGLOLWvCMuAJW0v66Ki7Zm/aZ2XJgfM8/kEsbG9rcL8ziQPRrfL3VCBn+Hgum4afL3QccQIn1UIcPccNtlPgsuF1tj3tJ0AhgcDADgGowKb/9icVPZ9rHpsYKsVXdUmwq+/d4ug1/LS5+v0JryntvLBibewtyjNbBr0x9dFHyf9ze81BscwSYFHkAA4TgAfd7fMAbVUrQPYIab1HFnsnDvuGsjT1Hf2Lm2hK3jfCCNO1LTA1nauqAuDVxZnYAhGqKRozL3wc2mm6X89N5NC6oc/Do9DzeuJbJk4fIaAbPRNUj+Baoa0HCmgerTo8eAwsgBibK0bQSvRcQqIKnigDxPR6CuAzct3MFczn3+ctCpTuNaUtSDAxQA3HwOeu8x/LPn6byiLEFMVR+NgEq0mQwU1+zuiXiYi8WQGbJzqFXOi4uCrvRVJWqzRTSWqntQ83NeCn3pi2aqfCeKbZjQnUVV6vGYvaihNYsahW5ylHESRIxD5fLckN7Leew3Q5xhsbHjAJEgFYvthiqXIytn05Q9WdfpxFazNjedbDof8WdAdm8bsg24AZjoQjzHqPCC4GTpj2k/IkuteE5o2HH62LXvNK5jJCLm7vS9fNQmIklVJce0v+NazIO2A44OQJ0JE1fBbAgLAFartBjq86kceFSB1i1AS/BRCJ2+Ohl0UkYEp428zKbwjw9BJ2f5ebSWhQFIGue4BgKak6bTdOOzPYJzL3vZyx3LW4/gvFO5jEnrKkdgeQ8V5rzS1SAlnLn2ruqGDFUOu6xuyFC79hrOzZMNua+6IRvN5A7g6HPZ5mzcoW5IdAwO1A3J0JFb6oZYKTk7AAySSG+tG2KzZNXkCuAs4JK6IYEdrUTN0mSSFzm65PlFE8X0/dfX/ytO/fMHjuC8THYxQ+wLOeD4tAg/AEn9VBt+vR40Q7TYS6RVayR12i8W2YNyk0mofG0ccCaFnJfL9IIYm9XHFHVJe49FYwz9narLpQPOJqoB8uLF+9jyeDovBl6ulcDdwTyaG2yTvIwZQo+OwZrwVJghvmkHX1adDzv3WWp/VYmtX7k8O7OWDE47hmiaFGaIOzyIKeRpEsQM4fUaNK7Rn56n8w/moHENH8ZCk0lIJOuFoi9UKI9Jf44iWpImYhbwxQXoqx+BXp6Y9hx43cA9OpbrLzFD3LqVPj+RFHX3w98b9Je5x48kxd5UTaf5DPzxB3C/+2k6FlL6h8wQnk9BL08yc40+3X0J+HJpFpfJrpqFnquyzV+y7dhdaRZDfQA2d/pS7Ln2fMvZ8To1i20guFLTGRrjPWkWl9Y6LdnAQtjzdWkWQ7VOd9Ys1KFs+nAdzWLvs7gLuQrtee/t75D8pWHK27J+vS4pwqqvvd8FpmOQ3avs49su7nZ9fXBmyL0VGboKFj10X/3dhkcvKzJUwokvw4jcGMZeYoKLWP/GuIO6f1WRofsoX2ijJkNALCtWK7hm+cJ4q4HyhVkzBpaehR81qmU0J/YAiOAmk61Fhgb7YzER9tyCD2XjXn0PoN8oMjQIztsm7Dd5Wvdw773sZS93LQ9Os2DFPww5OONJRkswx+1uHzUA5ZUMHJGKR/DLZYI+F/Z8trqv17K7aJpzaMMdHAgE2God43FklvLLVeZ0dEdHAHv0wdnm5nOxRQOHZgYCGo+lb23OlenGdYaz8MuVAJGaVuqSIDgykez7yM0Zdsfq8aNNFu2qEkdjcHi6R8fiFCwAPtw0G2MGxH53s+mmg7MebdQfoXEtDk0dUwCAcdPAaRp3cEJazlQgOF6NAzD9wQHrNTCuhTsUADzDHR6AJmP0L1/FfllHd1ZjpKqAyUQYxJEclf3JKao/8m8DT23tjkoYwx6LgxOrdTQBeJY4OFE5AYtdLOE/fCzHf+dHycFsdn13fAwaVcIkHrAio699Fe2Pf4jRbxUOzsUqzYuaU/UI6P0mB+dnxkF9hTy4xWJnucKsKAv0RM7MMl15INszQ2Zy4IYs2tGPJnOStV3iXihSmLMoBYyqr9dbx10gbNkYQ+lk037acdnMTfab15g8g8T/GeDxystwsRAAVmFaXMrBGdK2AUTma5vanQhoEh+q9kc5TmNfV4j9iZT8AHB6fikHJwoVnJWiTgmGmjaOwy7GAMCuAyk3hs5JGCO9OstNkcrJebow2TkuihQxs2wWL8MmZefV9nWxCAtYWkj54gKjpxPA8FlwQITGTdKGgj3LmG1/rlF+8d1ZLErt4trX++AFH/Ikl9iKHJk5mHRWLhR6rIeE4DyDiOP1FCpsDd1nqI3BuiQ2H6Ho5yYx7rb7+o37wrtE2gsIia7Cre19PWdzaOHzeT0Tw7cQowvFIhYXSfOzWTgjqtP2XRckZrCNNGn1sg2Oix7scv9I1NZ8SWwbIgl2c9Fr1uuEbnUu1vegRkPQyR9BujAVleOU7zODsdtEMt2Q2Gd9cMs1fDYuzjcinYfeR/6MTK7hs3h3FovbLBSZ1z2yhQyft6tDb5uEjycD9Wyr7WDDlaaeyb2Ko5iXsRGaNKxLqT6Fhl59qnVhs063tQHcnsTHUcrejMdcwsMgaRakzGNx13ZxTDygCV1LyGWRBiIafh/tMVvXw7n0XhCBXdGvy2p/6LhM26zHzUJwF/VR9g7OvexlLzvJw9cstu32VySY2VIAQHC69SbhqiggbO+bFxnyAWWYhyZpPM4K7ugxC76JfWg70HQCAtC357E/3LQpwc1qPFUFN0pgom1FhrD01ygyFByKFmCkO3YVslzD2NzhAfz5BagyDk72Ug7Qc64xBOYsGtcbDk44F9XvjVIApsiQ1PLwqTjReCz+A+bcwXl4KGhIA34j9lKMuO2AegTW7FBHoNkMNBmL8xMAVeKAjkWGbNJZJWUPIoIz9KU/7YH3HsUiP3F8jmKRITKlDWIpgFFInOt60HIFfj84OBfLaC5ZfYIO5kLnf3Ye+Tfc0SH6j9+Da9tUDmEylsQ1Hb+ZV/IevFrliWTr3Qsj32qxIKIfADiD6OwdM3+biN4D8HcAfAPADwD8DDO/vE07mw0PLBCDpCn98LkwDqaQ2UnjMWAgxcPNplobEbbddgX0WuHjdXDAIamYoxGgVbW6Lr5w3PfpASr0OMCcE9zbZrlWeT/1wwp1MKIoHNpz7G9Wp6NPH3t0sM6mMQtT8gicRAkm4+SlPz6UrFPPcjxOUCMLQllyMfQtW0gB+YjDghSzaCcTYO0i2S/NZ2Ee+zSG+Uxg710Hquu4iPGjw/SBWZ9F5cAXC9B0CrJw6elExnuqEPtaoNBdn+ptqNTjGIUBECHTdLFE+5UjjDU1nghcSwEh/15YLC5W0VTwB/KceSIVydyqhTut0HwokZ7xZzV4Fd5jNS+IhJhXM2TV0Xx8iIuvz3H8xSzOrT+cw525mGmr9Ul4WoN6Bp26WKMEAPD89VZR/xPM/C1m/nb4/ecAfI+Zvwnge+H3hynktvsTdpWB66PtP4QA3IYKdLldfF9CuivTju0N2eeOLrez9Zzrypb72lqhsU+vW8p52Pazw/BXR0iqhD7rbb6P8rqy/fL/O5L7MEO+A+Cnw8+/BOAfAfgrd9pCGc4sjwEJG7EN1delUCJ7F0lXy4hEVgk8YC64RYoC+F5U36IdW2lcFxy/XgvZCRBp2eUPHGuHxrZWZncH8rKEbZdfr2Nf+qyal29aaa/v4Zc6bvXQB01smc+bPz3L+gVHEia1VPdPn0t/LMuUDU/anIiw8PnFImkcxiEZTSk1j1brPCKjbfg+JXat1inKURvtJCSyCVFN6gP3oW+2enjv4U/PQE2T5rjthC17IHQKtwItRqmfGunoWox/52lKRiMC6hH8ap3MDyUhYg/3MmhHqrkwg9cNJuF+XkPFLuWBEBH8Fy+E/Ga5iserp1/g6DcZ/Oo0PZuz81j6IHJ5IGmSvmlAlqjHmlpXyG0XCwbwD0higP8zM/8CgI+YWVEinwH46JZtbErGhXkzn0XKmUj2PpuEHvtxlvfNyG+09kMB19VyfWRp34LdqwlBqa1WVFzPqWReXQP9OiT/+M3yhWbXt36XsjQgVS73TZTkN0URJ5pMUj3W8NJCzR699mAuH6FzqXxhGEcWui3MEC4Ic6jx0kYgAAAgAElEQVRy4CXH/sh5QlAT+zmdyDl9n67TkoVKUqP2+uEBcCHZvxbHQJ6lHmg9TmNzUt8kM02CeUm64JmdWUFZQA7KwmoN//go80uQ9vPoUA4o7oE5grK4HsmxrgctVvBPgsny8gRaazWLPs3noFElfQtDoMNDNB8dY2zLF07G4OUKpJEfNVfrEdD1wGp04/KFt10sfoqZf0REXwHwD4no/7V/ZGYm+7UYIaLvAvguAEwxv2U39rKXvdy33GqxYOYfhf+fEtGvAPhjAD4noo+Z+VMi+hjA0y3X/gKAXwAkRf16DXvjwNoCoroOgpNcIky9sm3hmYzIQebA4VCYL+oktLyehelhve28XAkeQM9tGgFv9Ukdl7E5cO8HYdW+aaMDE0DqJ/sI805oTx+vye5hzQU1IwKhbIzeBKi3mAcGyRqAYkRa8HnTrNKxERH8ylSSV1RiUX3e+2VMloqaiY0u2ESql31KwVaNp+3MdQVaVU1FnTNFP8YTzFwqZFz7GZGcHvTsBfgs8WRgXMt41bzhZH7RRfjkQvQNIW3cBc3O65ya6BN5D396KtqgVpUH4F++wpgomMGhjYuFoDiNVgIgIma560AL89l3uwN3brxYENEBAMfMZ+HnPwXgvwbwqwB+FsDPh///7k3b2N54wa1gbMIoluh2wG+huRJaLV1zFyhQsvdtl3g09TutKjEtTIjSXyzgDuaJlCS05Y6OhHDF2Oeq9gKAPzuP6iAvV3DvPQH6Hv2zL+R6LUs3rnLymuUKNJ3AEaUFzoQZbTSET06BWl5cF6IwKRdDFh3tg5LuVE8eg9fGDAGAcS1RBx3Le49AL09lvpRIxXvwei2hySrZ48LZQDIeDZNqRKiqYigzj4aso7+ADg/A5xfwyxVcUOtpOg2+jF6iMRoJeHIMd3Yh9r7yTXY9iFnmbTaFfy6BOfIe7vEj8OEc9Hufxzmh2UzuO6pyIp0QDWElJwrj7r94geYPfx2T3/kiPGQCT8dwpxcx34MW67iB+WO5zk9GYAJc51GdLLH8muSRTH/zh7IoVRWoTSUO3KNjiYY8e57m8esf49W/+wEe/cazOAc8n8CdLmT8nHwWPK1BnYc7vcijIb9V1Na9RG6jWXwE4FeCXTUC8DeZ+e8R0T8F8MtE9BcB/C6An7lFGzcTZuAqR7BF/W1xmG7Ar6+D8NMd3KLoyj5ah99GjkSqWSk1Osxu740P4x4l7myaG2JgxeKETPki8Ib4xp6n47xhWnTRofS/Qp9LGLtnAB6kSkTsH0fIc3Yvb45Vu9vvVqgcm7YzlNBo8z4qAvVyfjTWY/5Kn96dnre+ztQHhKrCyOPciK+G9TW5A5Krt5cpS1m4r1NFXStRX8bLMHSPktsQQXuoqqS+Azmr0lViWbGyvvqN45Z30hmHoeWBtGAqALv347qyrd9ITsg4hqGksYLBHNjiLCY3zPlxmbh8gYy1Owa4L7JErbaLIDSlL5SPUvNRNNfimv3R5upxzmCl2Bhbw2WgqBT3vWhUfR/f3TRWl0w3RzkbVjynghvXaUGWhqLpm+XmAIn7wrz7/8T/bztXUd/Dvfeyl73sJA8T7j3osxhisLoE7l3sfjSeZeq93nODb3ID7t3kYUGFRM/nG7s/jUYphLlax1AgNw3c4YGYHsFOpoN5QnB2XeZjUdj4VXBvXi6vAfeWnat6dGzQqCkMDFNekQ4Pwefn4vNQBCezOBPVdALEyRZCrxlhb0SuTpL9XcC9rR+GV2twl0iNN0KnOr/zudzPlC9Ujkt0nTgVbeW42RRU1/DKZ1FJ1a4I97YFi+pa5lyfT3ge/ek53De/ATwLIGVHct5iCTo2oVNNeJua0CkQnJ5L9D/2vlz+w8/EjCnAZ+7wQAiCT07jPFYffoDux7+C0e8+Te/4ZCycFfo9qDY4kkJLG3wWz74MfBbK+2DZs/UFAa6OhhjPODna+NgBJE+yfXDKq2BwFVpyLrt/SaIKBJZq68k3amYA22TYiyoUsSFK15G8dEPErtwUfBy+j9GCWInL0sKFa6z4i4IdW8lukcwQfvEykcMYfo44Z8bBGe9r52PlAecioziAVKSpiPLwhXJycAKqhWdFRFk0RCNKqOssGuLX4eNxbTJVuQMWS2DUJlNvvc5BSta8adpE/Kv91Dn+9JlEkbRP47G0WbxTlqWdxnUkNfJtB6fzGBezhGtBVUXQl6XR8y9fofJe3h2d67PzlHofaqnG4WiukgFlXcecfbiLxQAr9HX8L9ZPEHdYz2nBUdSfCeNFrgtTX4K7Lq91qhLIRiz/gCZkAfLgErDLA+MqvfxAjiDs+7TT9D2YKSsHaLUs6/jkFvEF19J/ZYKcLTEAhKiE2vKqWSgiUn8PZQJj2jcg/5c+CuPMU9BbPJcIblwnTadKnv+NUgBtB3Cfax/qQDQp6jSdyCKrTuFwPxqP44djEac0HmdOTWVAY43iFAWGaTTaIK/xaw86mMNZR2stlcM06hNzd9gLMAwQgNUszBE1sXoZrwXBSr7NnPA0mWwgOGk2A44PZSHTEwP7Vnxf9PuonKB5DesaANDp6wNlvRkZjF5cF6pR7MoFk9SlrM1ePth4bemRt/czQuizc2PdUYQPzJToi6ZVgUOQ9odrim6QsWo/AzZETlKNqx/s+5AzkoFcNb5YJKcam/O1/wORmowsBjmmIpuLwmGZn6OLp3n+tv8XfUQ/Wp4N+9FHxKnBbUQHp8HPiHZaoFH79PwynM3JaeaM1I9yIyoEJJi4MZO56+D0uSs2wzkTDekjoU2mWSwWcF8ELdZC6Asei3g8wOgzfI+NCl4hb+9iYVS3y/5uk2Y2PvhLxNZ9gBY6ZuOzaI0/ILJK6S56tWahXu7MI61eehdAYBbCPZI6mhp9cWGXhAsLRqTba0Ejd3+axdh49u3uXFVpB5/NBAuBvsh+7VNI1V6v8+qNpgL5cK+jWcQ8hzBX0cdkNJ648xufBdUY5tVU349ec0PNwh0fZdVdI8eoYl66Lu38sRq6gaOv10mzCECxLLQe6oOUmoWbTYH3H4O+SPyfsQj0AK0e9f2tNIt9NGQve9nLTvL24ixUSjDL0N/1b87gAHYd17Y03pCevsldecv7bmlL7p12+ng8Euz2+fGrcCQ3lV0KFiFpLEPmWlmJK2pn5bnXHcNGxGsLHkTxF6EPtp8bVcJsla8bzmmWSGjfm221Z2GiUUVUymoTEcW6Dd/jqqQRxyYueT/1u7ghzuLtNUMukw1AVX+9jxNJVYzOS5vKixBitE7KcA533aYZMlD4KFLKW7nEwSlZpz5GUdQpxyxqOY1Mlms9Any1gxnSXdsMcbPZRop65siEONu4aSQDUmuNBhSqpedX4h9CDxpNUjjUhA13NkO8lAnUeZQGApy5dHBav4maRt7n5mKImtBkbMoDVFeaIbxhhqxRffxj8K+k1qmmqPNqveHgROHg1DFw28YMVf/8ZTA7c46OITOkOj4EPnwfePEqLTLWwWlS1FE5yX3ZMENeE1PWa5FtO3k8bh6o3RmGcBZWS4k7jz78On85fL9Blcd9H1fziE8ILFSlBqI1R+xxN6K0SAUWKgDgpoULEQdvqOf8ei2+ia6NHzt8Ly/1uI6pymD1AYyzlHGPlXyETWMce9aRSIkpK+JN0n0jo3dIRY8fynwmi5pLSEmEj4ybNi1Idj7G4w3aeZpOkh2si3WoT6Ip3zSdgGkN35hzwkIcMR16fD4HfAgLGrYumo4jlb43YcNqOglaGsex02wKUkzG2vg3Khc+9EXsF4gk7+RwBrJI30qcoXQYcjBWpsh2WEC4csCoAq0aEAA+CP6Np18MOsfd0ZH0jznNzWyG9oMjjF6dRYeCzJczxNDhD+Na3rfzBWgeFjEi4OJdWiyGxC4gV+Aptt6i4J+IFc+zSEtxT5a8g4w+Y6jWCJAyTMvaGWX7eo8iCqHU7zHjMsvLCJwGJZ2/rUsCZJTwEcAV1eM+XQNETYOVfAbF/U1Ugc/O05itF15JawaeRZZxq2IjFfY52uNNAmhFL36fSgGwS3Pqzs5yHIv2L9TbiPkk2qeQGRr71ZHU4GDlwLBkOU7O1We4DBuRZ9DL04izACSSgTbVDWHrcGyTZic4GsHe6KLph+YJkErsbZPVa+GLBepPX2ZtS+Zsk1HyAQBWVciGXeWb6jVMr72Dcy972ctO8jA1i7uQoQI9RfGgna8fcBxdWQSIcw2F+4FzbTsb7dGmM4tzgmAtZGQLGsXr1XnKua+He79pUrlwX4t3sIWA7Ji3iJ2PUjMDAK3jwUWtkbz6W3E9+3gdgEg3uNk4D2qAMcwb+8BJayEyPBQm61NxFjDh2dUq0xqjv0NNE0VUal/0HOUradtICzD03gAIEHiDvUB4DsvVhr+Muy71TdvtexlD32fQmOvUbtlrFteVIQ98yBl5K6QsXuRok3S4LKp0GQDtPqXslym0k8nr7J9C/KsqEQFvIxc2xYFeS78ozc/GHO0iiv8I11/3Hg9TsyidlpckjG0vBaB1Q5LX3ZLN8tpEWAoHacbBqVDmwqnnQp2MLHfFJnotfaohohycQEyT1lokqRRAilqQpoEXIDRblwRArE0iTlhTdiCmdlPGJQqIg0wdaDF6UblUzwMQz/3JqexUdXKoKmFu5nQu5gMwoCWbgFc6ONHm53AqW0CjUUoQM9EfIQwqcls8S3RiuQKNa6nzof2dTgQYdpKcuzL+Tkh4VAvQOaiqWFeUJhMJb55fAB+8B/fyxAy2EqDVsfBq8rpJC6EmcTknpQDWktyFx3KuWy4Hw6Q0n4nT+2KRUgKODuG/+mFk2ZL7T8UvUSSS0WgkSXfs87ohi3fdwTlE2FsuCleVGtSXLHrCxzGjE4B4+2PEJI+hU+XSR9+08iAKXoeU1WqhxqauR9tmtTzicWVi0lokGr7V/gbaOK1LErunCMNZehFIw7q9qblhQn/cm35qyHY+k7odQKrdUY9SPQ8AeHQUa4vA8jCsHaj3g9OeEQnrz7OpyfoN/Qv1SXSJpflMFgZTZ0Vre0QS3iD85HiYJMYsTmQS5Wg+k8XhIpHw0mwGHoVnY51/o1EiVdZ5IgJdLNB99Ah1dPiGxclRrBvizlcS/QBS3ZC6gh9XqC4auNMFmo+EKat+9lwKP5fzdzAHT8agtk11RY4Psfj9Bzj6InHY8vGBoDJDaFYZw/xkDFQExwx/ZJiyvnjXF4u95FKowln27a5q8hCJzD2L2O3GxHhdKv02uaT9G6n9dylZ7ZFbmGW3GMfeZ7GXvexlJ3mYmsVQnLiMF28rPqR/jmpj8G4vlyFacUkM2vdgVBLLNlEN4ZYoeCEUaWePmyJAlombu1bIdW3/QuEibpH+N333WGW8neQoK2IUx+g94DnG4i3qkz3nPBOAkKuUOIumTcV/ALjPniXiX8va3fvBbNhsPoBUQrEz0Ysq+Elc7kPxJtNTuTZotU5Zry7p7K5tNtjKLc6i9C3xySn4vIrXOCxC7ZMemEwSJ4n34KoCLhILPBm28/q3Pk0oUEB2/lYKPAFIhY+AZEqRQxVwFr5pMV7I2PqL5XBU6fnLRMijmsXnX+Co7eBfpOqgdH4Bb3AWZP1s8xn47DwvMtRuAui2ycNcLHZxcJIDoCFC69/wYmtqeJGTI4jQ576BAQenOgdt0Z7ohMsYvNxmKLaqUqGczsK9XXIUrlbp3OCMZDb99Qh+kyrZ9cQxM1SL8gJInA1Nk+6voKwIwx7F4+ylH+pcTKzm+XHMponYxTo4oSnemwu0zkf8GcHppqCuus4riakztHJAkxzJ8boBB2dkGrcSfAjg4OQt2a+0fqj+PhmLf+TQ2PXKyEWUoOXjsaAimYUh3H50LhQ91v64aquDk9Yt4Nbg4EegVyeDGxxNpzIXWiUOACYT9E+O4MxCRdOp/H3AwcnHB+JjmxsH56t3ns9iBwTnNnyC/lgiOJU34TIWauYQ3chj/4nsJd3fD9T1kJ0+QcctliKjcIv9uQzBacoZegYF3EW2K3kGmkY0gsDKJQhOjgDOsnydIDgHtDRbUvDsPEZ6sjolqkkNaRZmPmI+DhtNjjlhF0zpPtZxmHnOqAhMWNV7v4ngBIC1pPlbbow4VlOHA6EkY9RGjGaBUM8jq+Oi53/xImpaCGPg3sdq6LGyGwAOGoSGZH3AWVgtZGix4IsLcOC+iAt808L9HjIIO63WGc4itksE1/fwFxfRmR37tqM8zMViV81C64aU7nlmUPCiq1rqxnWWBOVXV4RODZemJBjlmoWbTjYgzm5cp3ojS8R7eFPXow+hUzeuhYWpyA3hthHeBRuK1BKM5v6AkKPEMoi6o2ltU9VclJsz1Hp1B4fxg7N0ejY3xD15DP/ylYQUi/KFwscxEDoN8wGkcZNV9QOuITKaR7V9LOxRTRMp8bLcEKtZPDqOdUgyGY3AiwVoPEZvzD13MAPqcUoCG49lZw7V2VM926CduApQ+rzZFCAndUQ+/grcF69SPyoHXq1Ajx/JgUtyQ9yqEWDV+1JjxJmaKVbo6FDes7PzCMxyhwdov/ERRt834fnAWTqUG8KTseSWmNoyWO6+BOwdnHvZy152koepWexihgw5PjOobE4zp+pfpEsbuqcmknUGEu172R3D3+L9VgNOz9KpaZyNVo1N/Un0eZljrtO+bkKjyajhrHRsfR81iiz9nH1SSX1yIm6YIYUK71++EvXdswCYbHvbzBBLzqsai9G8yJGYHJQ7OLWque2rLR3IlmOj74fNkMA2VpZ89BdLwK3S3C59ojdcLnNHryZ+aUJeUPV906L69OmwGZJxqIZ+agW20gwJcO+h9wYIzljnsoRD3/cY/baUNoxtL0bDcG9lqm+aaAoBSATBO8jDXCyuI9uQnXd5f/v/6xQLBAuAscFzytrUsYK8gXrf9zztIja1Wh3PjsQfczNemmu3L9gPZHR98AbWreQ1wWQit/vHdld9vLHUo8zXdV15dxeLq17+Ap0pjEUuizpcdm2CX6uTbYDPwiRfaRs2AmLvEY+36Vz2SNEc29/4kZsoT+yX1Yx82FWxiVgNDE0bgK7yenPfGB0ZjQJ5T3G+zsfQlOl8hJ9jW4b5HEihPjYfJetYI9tVSKiyHzGCL2RDwwzOygFYvkK4o4/AUeSqJFMNjl3os32nqiqFJ6fTTMOCcyAYCL9NUVcfjz6rgFbV+it2njIJ0SJLykyjkfBvWAen+qyK0CmqSpCsIQKU+rr7JvfuLhZX8VzcJuuUNzktNk55DVmnG+0XOzB7lnAwYKIOsrhF7o4yKvSas05jZCQsBrHyuj33dWWdKv+H5xxLAwg5sWFbZyARHL2urFNTbgHA9bNO2WdQeuhYd5SHuVjsFA0Jv2+pon7jRLKgVVj6PRqPU+gzvMmvN5GM4k6VRUPW68hIHXcTzXkJdnwsuvOGEskUFBaPlWzjIdKkjGTx2H0kkk0mMdJC81m07ZlNiQOtoBZwFtT3ryeR7PBAEsnOztOCc81EMp5NQK9OE/6DGVjunhuyj4bsZS972UnefnZvlaApDJHjbj1fRVfiySSRwd6UHdtVm2qiYduOO/VQ1eu7lKDlbEgBVLKV1wBIPzMuUvlZa5HeW3X2ISnGEJmuDWM1Wx/LVX27rZM2EDFrNftBekH77MnBHczhz8+H2x1iph9yhFvipG39D8z1FqvTn55uas5bqRoIbjaDX60zR/ivt3//HWT3tqS51zg/Y68qEHw364fPH64es228Ltk2lowa3m2eO8SR2Q1zP967lH3d4g/amcHsln1Jfdj03WRh4ciSdc+bgm0b4TndcEGMqNhr+CmsPJzFQqX0Q+jPdse359jcELMCu0AAoklE1eFBxmfRn51FB1bKaZDf3aSOtrq/WMjuEjgRtI3q8aNEfuvS7o3ZVOLzp2dRC/GLBaonguDrPn8q1z86hr9YBt9FY5CfS7jZTBCVWijYVBy36Dw+OQVqOc8dBKp5TcaqHGIJAgA+8GiMfuyj5GwLCUk0GoEmY7DmP3zwHvDFC8EjqA3ODF43ghodoPtzR0epzIFyYIzriLiM9PSTiVQ7U7Tn4QH4/AJ+uUL15Ikcm89EywhIy/jxfPAEdBLyJOxOXTnwxQI0ncJ/8Ty9A08eA7Mp/GdPY79oPpPoxbjO8QijEWg+BZ+exz4AQP/0C/if+hbGP0z35XoEOl/AfyX0dxGSv5jhj8J7Nx6BK0K1bOFOl2i+Ls9//M9/YPxfaWFyH7wHnoyBZy+iX8b9oZ/A2U9+gON/9lls2x/M4M4XCeatvBbTGtQz6HwBPkz8F/Rb/xi7ysNbLIDhHbU8dlXWaRl90BX7ElU3RkwMkxOCh3koD4TV0678kl0HWq/BWthGY96e4wcaQUkFe/YQu3dkvY4gpzYR1IQxSnJXvwHh1p+pyDrkdZOAPwrq0j9qOxfLNL5Gk9ZCdfkstyaZRFkOhjov2W/WW9G503PW6xR90XNXq8H26HwRnHsmpKp/b/IogJQtEBr+OMdNcES2Hdj3eanDMA/xmN6fPUYvl1J2UM9tpW6IO13EttU80Grprh7JB920oMUK9YuwMIWcIJh+AQAvVqCuh9dcHwBuscL06VqcrgoBZxZnblicouM4ZCDzYpUTBPW7a9p7B+de9rKXneRhahZWbuqDKDUBBbvQ1ffbhFkPXGPAM7Et71NxIcudEfAOmS2qPhrDMB3Fs7Bgb4zBp3BquK9aYIP290DfWTMpTdu6q8adbt3EbFi0Zp8a8nlY01DHEG3nlOWb1VQxGoPN1I33bymFTg0LN62bQC1QaBYBGk9dztiNtgO7Kh3rOqBxsTBxpvWwMHzHY03iYK0Wq6IyuVyrXB/ctogV4PSkNlAg9JIpSwuTFey9hFYNJgNtI9pOZ6rKr1YYna7k/oYvFE0L1vFb7hBmMfEsEOudqKK+q1zFtXldsZRlA8jMG4mNWuj9HZlCMFsUvK2s0vcILS+APxmdnOl7KuVoPsqYlaso1XCdLhgRMn1H/Q/5FRvru6MYPQB6eYROUK8JrGTOvaVweQ+3A3N2TCGnnH8imA9Z+cJtNHrKKq/cLfa+23BHt5CHuVjcxQIR4c9KslLJbl08ZKkVmv+csXt3wVlYujo0t6Agv4lcBG2b1eNEKE2HgNyNRLtEG1yakfMhhhUTeMrWsYx1P9kUXO7jYEBuAGY+GiVSHfVRKDO0AW7xep0gxHp+A7Db4q2vKpASx5i6phtALU391+P1aOOcOFdtKDOo7c2maYdVB58ncU42rZyrMGjv5T5KuqN9HNdA77IaqrFf9TjNiTJeLQl8MIU7T2A41AGQF0oS0ipBxVmJZ+oRmAjUdiDP6IPj0z11onHpogHItbWUpqTVOj336QTt4ynGz8fp3JCGHvuvc1aPQF5Qt2RIna/D5/kwF4shKQlnt7F+65/tyo7Nl/XSdhwl5GLTys8xE9IgQpmzojlUVTEHgBVdCVH9qa7zlT8WtK2A3hQwBqC1RzN2b0D6Ydi2abUOfBY+lQLQKIPmehQMXdq/2BYgL1pdJ7q+6QS4GIHIS7/1+DZnGbm80rjO8WgUcypsNCRbridCzc9tF6+jySQ6Xm3pA56HHA1T64NC/guHyA1fmDyKugZPx1kZAppOYzQkM6vqsTBMKcJW6fRPz9E9nmJ8kuadxzWo6yKTN8LiPhgNWXVwzOiO5frxaCTPiwhsNAuaT+W+FxfJjJtPsfxgjPEP07vjD6fiRN0WDWFOdVUBKZi8ozzcxUJVXk24kl/CD/7qaEhBlBNtRVtQt3J5YhQ52YJtHcxt0ZBQuVu6SqlNG30w5DIcqpDHXVe1AQ7JXrrLxehCqgEa294SDQH7LK1b/mb6bvvdtob0xUezhGUg0oV1I8ldnDz3sc4pkMopNI289JYRS8dNTuzna0RD4keiqebetA2AlmvxO4xGyQzxvRQ49vJ84wLddeCul9IFceydLJp9L/4B4/8hALxIi22kP2SP6rxJeSDBfOA2+SFoFaIsnmNEgaZ1shzaDqPzRJkQSYBUS6pcioa0XRYNmbwKPKt67mIt4w3XU6/z4EFdL/ex2vM+GrKXvezlruVBahbiXMt3WjnWFud0yRFXiNLYKWmJOzoUKjRNstG0X5OqrI49N5tGejR6/gL06Bj0/AWAZGu7R8fgi4VgKYJK6A4PwMcCjqKnz0EHAo7hk1PgvUDBphRvh4fgFy/FvrxYpH41bQIPaZVu3YWPDoFHR2mMnz2Tfp6dCwAJQlwDIMLm6Uj6E3fKD95LhXhCAhRNJ+DpJBK0rP6tDzH97WdAPwEfGYDPxVLIfQrfBHkPenSciF/CHPBkDPci9Ceo9Tyfwi1WgpcAgPcew714BX9yJvcA4I8OxNZfN+BZUv8XP/4Y00/PJUJSBS2oZ/DIoXpxDn80EzU+jB8fPkH7eIbRaSjsNJuBHx3KuCdjuJNEhMvTMfyjOarPpb/8KDzH5QrPvnWMD4zt389HqJ9NcPETAWj1qgWPCGBg9b6Ybd2U0I8JkzOP2eczPP8jMv6Pnx2CL5bhXTP8or//K+gPxxj/FoFDf9c/8RX86D8c4/cvnoifAsD6vQmmz1bwtQMY8BN5Bt1BBeqBybMF1h+mZ+af774EPMjFIgsDWvYlQwYToa1bIMyR2ShcZ7P5ojgnH7veN+SV+OUqsltz3wf6/Lwdf3Iq6cCqVkKIVeN1oSSf/MGDXgYKfjUzzs+Fa0Fp7xX96EgATparUe9zcpqYqsMYqWnAXRcXiYz0lj1QlCDAFy/ifTXblddr4GIUOSamv/1MwqerdXRacteJeWAqrSkClJnzOTo9F7X85DSVFND/z0eiauui23VSRsCUS6DVOoaaad2ICQdgvm6BxVIcjGERoaYFAomta02ZhL4HPX+FUdMmwNpqDVouYzarN1BuqkdwJ+expAIFFCU3DT745+eoPnkW3xk3mwAn5zhQf82csRMAACAASURBVIyCsnqP8adhUZzWKepxscKH67CAnl9EU0qBejQawf2bp6jGNfyrk9jfye88w1f/949Qf5b4P6vnFWixQqUO0uCzGNfiH+KLJebPk8/Crb5ETFlcIgaB+BB2vZ6c2HxCQ5d8BhsfI+92TwCCqQjYAuVooMr4RAzHQUzgMtwK3Pto80dcBcJLbmnazBxs6x2bKuDx3Co/nvrNyZ+jWIOqApFHDPn0gRTW0tj5PmFF4kIabGm9p2W77nH9sKXFW/QBm2JDgj6ha3URi30K85n6G3xEa0NvqO+MZ6DM3L4kn4KaLi5YxCz39H1iPrd+AT2vDZG3rgOtW1AbztFaKr3x0RhfSya9R7XuM9Qn6fyYtmRoZp5uGEJ9kIvFRjjT6//GwXlVNGSj1mkNtJR4H0JtEG47RFo6pajbJRoSa52mD5vGY4k2KKW7tuW9mBney66LEJWIIbQmOebaTtiOKrcJqNkSDSETDSETDYnXACkaMp0kCHcbogqjURat4aO5hOFsDYreg10jlPZqfqAN+AZpP76i2kdH14uGZLVO5QOl6SR+jP54LnDnepQiLl0vbTgnJtk65dPQdCpjUe3KkRxz14uGNB/MMVVoN5HwRjCjfyS1QNxiHR2cGg3pp1KHhHqP0ahC86Hs9rNPpwA1EqVQ87mqhqMhR3NcfDxB/XSenL2zMRyRREGMZsGTGtT24qg1uSHXiYbsHZx72ctedpIHqVkMpdhucA3sfjPRGDxHlVmPJ7Zqve/urEJyjyIhKIM+FynjPjgG7TmFuRHF+2vtCNfucwEtj3+yNHNdF0wP01/22biYWTSQAJXemIfrzqfto/atM7u/+ry73gDLglnnpehPHIOGG3ufYNVbDbnLhcrCVOHeZNX+4tUkBhgM6ryMwYaB2YuZFu+7BYDoGdQXc8Ccv1/e9OGW8iAXCytbc/OvzDpNuf3kfOJzuIxgRReOXXAWmmVpSXHbTlRMILP3ubflBJDODedleSR6LfP9ZZ12pm0iQWZaHMXFMtYEZWeqsTVtXCDi/dRn0Rj8RtPKnAyQ7VyKs9AxyI3DPKS23PlCnJRERVlGn7JOrS9jvQbZ6mfeizmmWacWZ+HF8zSEs6hfLLNKY+Q9eLW6POvUmqCLFcYvg2kWuD+JTG5KVQFDOIuLJeZPG8GX6ILX9cByJWa2QXBS28mYb5F1+vYuFoYZC0CR1DMwQPapapdlwtqyotoXgUNSETiVEaRRnaDWNneDOdT8SASsWuMju7/WIQmlBbWd7EO05L02VKtjUF9H4J6I9w7JR+U82LokAFI/2SfPfiRR8fGa7B4DfBRc0N2Tkswyx7J76tBVKDqAFCnhPtbjAJA5QOPiVQCudBPwfhmT1iJfp15vIk1y31YW/dK5rTvtcpmQsc5JtKFpM0d2dIAukc0vBxBZ1k/Ic3I/epr4OgFpo23jgp+S1zzoPHxyxmfmmwZVmCuvZRLNIiYbS5PqfoTj/uUrjL/P8KdnWbiabZ1ew/LNvSSiUYjoAPgS1A3ZoGILP8cEpt3zRrTQsZojNrYt8GAfcy9QSQV1WRisGTG8eGn+RUbDr5qGLbtHI1NOMJDSBhQfN02O5kMVkKVD1cpLlqnQT9vfgWvyX/O/R9p9GKetLbhsxxEcspGAx2ZiMqe5dZIAZRe82G/KzcmynELetyrL4bDlFqMTtevgF4tI5R/zIjSztR6BukCcvFwiq7GSpQ+EerIxcmLUe6v2u4D8bYv3MJwTzSNyycntkrPa5r/YBcAvFoi1bK1504fi1kNZxKZfjM2FWE7Z3TzZOzj3spe97CQPU7MY5Jjka62S6XoG0IuGYfkfA2OSXYnpuunqaobY66Iz1QCwwElzUDVX4+Iln0XJUXkfUu7s+nNQ/5M6nBjDovbhjW8hqMPRt4K0I16Zwj0k6gTULa7vM/+Irb6eOZcNToVK343ia24jbZeNX1nEyPYByI5xMDfQdmLSBSdl9NVYZrBt77UPvramyc7RbOVMrpFduk0e5mIxJLfgSBgs+zf09xuUjsvuba8v7hUTrlQue7j3yWcBZEjY7HDJbcGc+Sc2Fusis3fwPrcVo8LHexsuCA7tb5vf6Je6VR+uGI/toybj2XZdIuuJc2O4Ny4VcsNzoMfuYJFQuXKxIKJfBPAfA3jKzD8Zjr0H4O8A+AaAHwD4GWZ+STK6/w7AnwWwAPCfM/P/faOexWzGK1Z9E2rcQFzuch2MdgJE/wS3wYtvQ7JlzdBLb795bvR9DJ3PAanZh+hCARqLNmmpqdy1bOMyJZfvnhpipbRrClLTRls8tJhRdkvLZHWTvtkqZJYCQJ2sljdU+6XrX+Ec5aq6FJ25k6gvCqL1kM6NunPKMDmSJsbqV1CNJ3J8Gqf2Nic9MyggZzeP+43I1G1lF83irwP4HwD8DXPs5wB8j5l/noh+Lvz+VwD8GQDfDP/+OIC/Fv6/W7HcFRGpWbx82yqV6Z81fyEsMG46EfVNoy+aq1CiRZkkUqIVydZruMkkeuq1LTebbhLKmpoPfrFIfVit4Q4PxDMeWLb1nhFFGslrGtBIKmfZHA4AWU0JIOSGVA6+aeGUxVujPaHSmYbw/EoT6o7SC6vzpqQ96kB8dCy5HswJGQpxoHHTDJqDNJulimbax9k05YYo6nNch/T7Ps6jX64kGhCS6WgyTnBowz9CRyYJSzWL3ot2t14D9TjyWZD3UuXLMH7TeB4rkkXnst47OE1Zc0OUBf7kFPyNr8J9/iKdW9fg5TImvmHdxPcwJr4pYW/bgRYr9B9K0pn7nU8i9aJ9o+n4GDSq4E/PYiSm+vADNN/4EOPfSuzemE7Ai2Uk/4nvTT0Cul5Cy1OD8v3sDhPJmPkfE9E3isPfAfDT4edfAvCPIIvFdwD8DZa35deJ6DERfczMn+7co10kq4GxZeW8Cgdfrsbqn9hoivOf1ca1Gk2MkJjrum6zDXue5+xlLOtPqL0aNSvDs8G9FzCR5fA018R7GFBZqXVplGHjmvU6b9MF3IAdy/lFyKMxO3jItYBPUQ+2s9ka/g0Tbk35D8m+t5gOzUEBJ2yL5mFsRCKAWISYDS8I68JiMmIlOa/JfV0hBB4T6Gx43XWisURYf9L43IszeIOz4K6TfpMs/DZErhoEjap4H143qMLvXvM8zJwTkSxSVZUtpHyxQP35af7utG3i4PRsSJRczI/JwqWvgc/iI7MAfAbgo/Dz1wD80Jz3STi2l73s5YHLrR2czMxE1zDmgxDRdwF8FwCmmF9xdnnxkBlSrHtXmCGWg5OcJJBJ3NuYJ45CbF2bCmaI5eAMpkvphY9clgbBSaNRhlXQJC5Rsadhl9HCuzWwEgdVrOCt7RXUf7F/9v4Q8BRVwtUZuS0tO1ePDdAbTSZp51EEZ1XlHJzHh5Lw1vcJz6C7puHv0KgHUyjYrG2MDRXfkmN/4t/M7knTiZxjMCgYh6S2vs85QA8PgItlKmKsY2CWvo1r8HnALjCDplMpzKR0BSOSZL9ghljTNmE3cjMEqzX8+8cRCUuUkgy1MLJFcKoZwrUkkqHrxQx5PxRGPjnLqqDLQSd9HVXSNy0xczBH89VHGBsEJ8Y1sFxtcnCOKoGFr0aZGYLz+08k+5yIPgaA8P/TcPxHAH6fOe/r4diGMPMvMPO3mfnbNSZDp7wWsdGK0vtsPdPx33Xuvc2bfVl0wLYTwEtvjWR9G+iXZe/O2KnveAzbokrKvUnFv6yPLo8Q3EXfwliz8V6H3Vt/V7ZywyG6a/tbx1u2dwu5qWbxqwB+FsDPh///rjn+l4nob0Mcmye39lds8znocTsHtkCsq5LGEbdeitdGQprIkO1yH4Pv4Zv0M4AI/abKpZ2lCWQvEa0Ydq56tOlvcC6mWQNITtKVIeRtFQo9gV+tpUBva9PZe0FQTie5l93JrqjlEQGAuk60DeZYMrBMUY/jUAftuAbFyIuP98ZolNK7J2MhzXH2pa5iXgMXEHIAkh5eeOZpOk39UeTqJBDoqm0/nQq8XHd7iL3PHTI/DgBJDS99CgjaSZiLjNBGP2pFSs5moIO58GeOx8DCvFyjsCOrdjSfAURwyyX6gzGcJTquR9LWYWBTWyQIvJL4cu3AdQW3aOHaDv1Mnq/r80poAESrev+JpKhbP9d8itV7Y4x/QNAPgWeTjO8kEvZOxkBFcCcO3qaoP9s9mW+X0OnfgjgzPyCiTwD8Vcgi8ctE9BcB/C6Anwmn/xokbPp9iL72F3buyXVkyMF5zfKFMSfCONKEWOYS52kAUpXFaTPWK73/UolfzWK3WicHW9dFFZz7PuWG6D1Xa4B9yDvxWQ6Hb1o4ICfs7RELBEVSnVCyTpOmtC29hn3Kt1DTjs8vktPTFAAiy1714lWKYlgnoCbjDcy5zgdgTA9zzxhS7LrM8ekvFvHjiSxVwXmsjkgVQorqWCGiSHyTJdKdX+Skwet1coiqk1L7VlVyrh7re2ENZ0b9yfPI4qVORd80UW3nQE8IANVZWFSqSpyOTQterTEOoKzezJMVPjmTmq2mVCGev8TRv6rAL0/Siau1RPJMuQUgmah8fgFnHaJ3mRvCzH9+y5/+5MC5DOAv7dz6Xvaylwcj7w6Cs5QdmbI0+zKq5UXRnUGpKmM2BAxEgXrUiusWiGWLAEkBoOSEK52WWrhIyYlje75PCVQxDJti6tbBiSqweOnOCOOjqSoQ+pyBC8iLFJniPvY4TaeJM7Oss9L3g3D0WJEe1pmZiuPEBKrgSI0JV4GxymJgYiGglvJ+zae5KariAi3+uAYtjY+qHonTUivLj+R3Uke3NSPrkZhiqs2NazFJm1aYpxamMLKGRZXU2WTiRpxFVYnTcS3FmdU0oNFoGNA3GUv7gQYAkOfQPplj9MzgJmZTee+q9E7ovPJkLI7Yuakbcg0/3Lu7WAD34uwh65BSuUNI7Y3FOsQKpy0jOVHV7wL7P1DQEr4hsbB6VzgubwC1v5XYDcD54XdmF0fmXctQucZd5ZaESQ9zsciclpdoEMygijZNaOb8xQTCDtzknJRRW+izc0nDiZCPjAYeglYMy7pkODJptc6rhE2KiJDyemoKfbEYaMUzAClJqh7lFcWcC2S7JiU+3EsWEY7j8AprLzkwkXZgPc7zaeJlsJyfEI1pCBZvK6hF1OdknPwFWm0slP6jntLv6uzUc8ZjKRAEALUZ78FMyF+shDKF8L3wZp4men9MJhI6jXykIfRMJLt+fK5SUQ3TSeZ4BREYF+gez1Cfm5KAVQVihj+SHdwRgdWZfSjH1MFZXVQgz+ieyPH6k9GgzwLTCXhcy3up0PCDGVYfjnH0SWqbD2YCNx9wcHJdoZpOouNV+vquaxa7ODiBzVU/8lbQRs4F2qLS2NA92QNUY6PCllUby4ph9h6GyYp7b0h+fYpG2HOVlctU39L2bMUzGWrI7mwH7Kcy0jMgiruAKTFg0Z2EZKq4xUqQhsiDUbG8wMCzyCqo6bhtPdG+j87j7Dodj6OEqKyCI7ftckj0xTLVG7HSWeSl6dt6LTwPWtGs70MGaAci80H1Hkxe6oxGZ2gjZk1VYfRqCS7MEF43cGeh/spqHeHXzkDo1QzBcoXRy2Wcw8EykKu1VE/rTBnHiyWmz5q8bSJhw4pmddjU2g7+sdREoYWJgHypqqhvE5N4NfjnEord+41jW+/r08eXCEl8Woz0/gXRCHqf6PJsbRPPGbRY+2P7OUSHl7FngYVCrxyjRigsqIsplB+0adCaQNcNRkOy/1erwcJN3HWXzzfnY4Kh2pPsUBc1igjKAiKMPLbZuOjHyELri9Vg2JYopIEjfx/iYmPGDpKFCKt1jBRw70PKuFl012tweIbufBFD3tJPyStRv46NhsTEriIa4s4l0tMrhWA5f+smUe7pc8EKo5eLbKPhkAfDRTQEnfiduGlS3ghwrcXiLTC297KXvTwEeZiaxS4+C3LiGc/05JSAROMiCjCdAE1j4N6mElnpszCgLOo6saULB5ybTUMSlDEVppNEOdf3EXbr/VKgygCgWZHTCfiij1mnMYqy7kO172Q/x114PE73B+D7XqIq4W8ABLSkPgsD9/YB10GHB7GqWRYhmUxStbP3HsPpLm99Fut14MzEhsT50LmG2P3+QuHTwY9R1wKK0nvOZ1IGsu1iyUmazcRn0TaZzwIfPslKDobJFZ/F+YXUBLGgrMMDeSamX1qTBOM6ZclWLHVTJmPgNPULzoEXS7Rffx+1bbOqQIsl/FeeyNjPV9Fn0W/4LBq40wWar8m59auTjaRCAKBHRwLKev4yaafvP8H5H3qMIy03CYAP56DzxXafRdvBHxtQ1rtevvBaoKxttyizMAMoK/MNDNyTvRN1UJ2Lylx9T6CsmA1rwU9tB6Z1Dsoit5EezppH4DkDZWVmSIEWfK2grN60H0ylaEaYzEr138Q2tRpZ3yfEJnB7UJY+s95L39ZqWgTzcbXKQVnB5zIEyuJtoKxgbmyAssJ7sRMoS8f1/CUO/7/dQVluNgWfnMGtzTN/pwl7y8Swy1LRifIXN+7+fiMerwS4nC1ExT2ZAUK+qOgHp0lr0cHZbFzPxk8BS1rCnGqvFv2J27Tdri0UPUr4SEsHYXCQJo4KjdDkqeEaOvXL1bDN3CZb2p+cxSLUma+F/fBzKOdDx134YbK8E51f025Wp1XHYsO/bTfodxJOkl40MfPc/XIFWlPmf4nP1vts0WTXQWvdAoiV14gI/vNnm47Zksm9yKmJoWwl3dXFfOC9AQB/fpGu1QjW6bngPJZJs0D5/Ey7br0OY7YIzh38dEEe3mLBLCAbfej6s6syMyP+byMi5kXRXIno4Q9kNVEtXyxAozrbKZUwpiS/ybJOQxvu4GA7+Y0j2TFN1qk7OgSY0Yddwh3MhaikcrHeaDx3MoncBnJQQ5LjLKPTXyyTU0vNhQLebcl4AKB68iR/yRFMFZt1Gshv4DnLdUHTJvg4kC2og+Q3gbU6tgFEsytqMYb8pjoKWZyTicyzljRUkNLxkRC/2IQq1QDXjWSdmkLQdHgAms3gn30R+yPlEIPWYNZvNcVUA4wm5Mkp6Cf/EKrPnqeTA/kNHgv5Da2a5GA25DdcEVzbg86X6D8S8pvq+z+M5Dd2MaWjQ1Bdw798lchvfuwrWP/Br2Dyrz9P7/xkLMWhTckDAFK+sOvhJpPEcA4AP8oMqEtl7+Dcy172spM8PM0CiLwS8ech98SuhZF1tzSAHwDAYrHBZ6H3vTTrVAsjTyeyM9ndwTgg2YCy0LYC8mEGcBLOrUUlrWugT1W0tY6IhSNnfBaz5OCkVdB6WsPToaCiymUOznjNfJaqbbVhdx7XoMkkXuuPDsQp2PepPRZerCwrMlp9TgBYGqZTqPSoikWKooNzPBYcRROcybOZ+A8McI3mU8FOuFZAaGFX9Y8OBMdgQFDUC66GAAE2qW+IWRylhzPgVR37QPO5aEB1vuNSXQt8O2adBifh6TnWX5ljem5MgclYCiM/OQQgDk7d4bvjkHU6dvCVQ7XqMCLCKhRGnv9wIqFRlwh9iUiyYadj0HKZtKXjA5x/dYzxj5Km4I+mcFqXhjliMvysBnUejgg+FGwGAP78HQdlbS1ZeB0p48ta63QHsl+2FP36eykBA2D/Rn2fZ1lmGIwCM2Bo5uL5xf3Ldpk5s0Gzfpa4koI4Nh43plPMQVAQmpo7oRQe+sJHso1OAMjp24IvhjvTr1Dhjbvgy9GFsEs/RzOy602t1TRv1HQyfqJEwx9Ig7n3m+jOrhNTxgLDQklFIsp9KkRyvR4z464WXXL0EoGpDX6IsIGoWcEMtwqLPlcg5+HW0ofRatOPk6aLQyX40Cftb9OiXrD0S7lfV538rhSQOjdEAjrrTL+AvE7rFfIgFwsrgwuHdWxu+fg3PpLwEAbRc3mDOdKT/XCtU0VYGqasstxf9jJ28jHG3JM+sGNxsWiQvHSlk1WvQWs8nz595CVfJ3wAkJUvp60/qmCutkusXwBo3UTHXNQWQltSeSzX2uLP5cJlHIaqxShSNNVvbZLfSJGlro0Lhc4bIL4BbtsAOhqleWt7Ob90Qna9OEV14Wy7hA7lHCgnUPYmR5GG+ayWrSAxgajFcNuClqHOyrqNTlunPoQ+aLKdB7UdRucaBVJWbqRn7iTSRcx5rdOmxfikS6FUQPqxTlXsyGw21IUyiEsLynrHF4sNxm2fvPkAkNCUl5ghRWIVVVXAI9R645QpqbkO5ORnl6jT0LQpjwNIZkjlwH1gaDY1S0mdmnWdmKn7PjBWG6+5OhTV0RV5G9rohY81SE3WaYY7cKuYEBWzVrOIg6Gf03mpa0MqQ5H4xporPJvIgkGUKNo6KVJs81C0nCGjl/HoYjFKuJQIR9a5qMcBVcnp96aVfpucEl0oLAmQn0/hWoFDs51bRWrOpqBgYnHvxdSbT9PYAoEQt63Mg13slLKwVtrDMM/k0B1NUOk8EMn8tB38PB1Tkh095mdhsfCMCkB7LPebjGvpa+ViDW01O3lSyzyp1jUZY/X+CJNPEtaFp7WYbZWTYs6Kz5mMgFb4WqKTNYx5V3mQi8WQNpHV97jxjQvTwJfaye6sQpkUVcVJ2ZmiZmDMhTJ0O2SGeL/xkd+VZDgN3eF057Xwch/CpEOamDXxtv2sC/r1Opf+V5PRpxyZrAJYDHH2ZixGc4ymRyqORBspdLsJ2WejczJQKyQfCwACqA/n6yn6Htv97ZL32vXI3x/zvLa2fUPZR0P2spe97CQPUrNQQhgAsbJ5dkzPCUQxPECIol78WDTm6BBYLEEHwct9chqdUlEcgVDBzabp+lAgSJF12hY9OgZOz/PMzcND8KND2VTaNkG8X/bwT0JBmhDzp/kcvFyJmn3Rp9h4KBJD8zlcKEgUsSKHB2C9DwDXSmEe730seKO1VBXP4EIf/HmASX/wRODCEN8EAGA2FXV9KWNc/PhjzNetqNUKHfaQZCiLkjSlDeno0MzDQVLX9dg8RAkOZqCLZSKT+fAJCOJUVbZs/+gA1HSgVQM/n8ad/fwPPsL8Eynew8pA4Bm+rjD64gz9ozmcpqizh3//GN2TGeoXr+Tcgzn8kyPQsoGfjeFensU+83SC7skco08Dd+sT6QudnuGLn5zhw/ZJPLefjTB+NsLZN2XOJy86+JpADCw/kE+unRH8GBifMg4+G+OLf0dMg6//4AB8huDMTLwj3dfeQ3tYY9Z2AMkYVt94gk//fcL0aXrmqw8nmH0+AdcBXj4RDbQ9rEA9Y/b5DMuPUvSk/70vE9y7dNzpKQPZmtnfM5ixYPy5SbDc6BTcSA3vM8gt9z14udzMYlXuSPU7AFKlSm/VtEDIi+Cugzu7AHwqxscBGs7KjGRgzdy0gL+IocyYUm7uH9sI52vI0BbJ4bZL6D9VxU/OU5q3idxQ28Xfp5+eA4sluPcp5Tr0uURDao1RvlimtrVqWNMmeLZPZgOvUvaoOzmHX61knkMhHxeiPtwK2a3K/JMRqpcXknlpQFkOAF0sUfUe3jiY3ckF6j7NLfOFqNpNC1rVGQSfmhajtovHVCXvuw6PfrvF6FlYWIhQjWu4swscfCJ+iOpsDa4I8MDoQj7UflKBR4Rq2WP0conH82BWLpYyz0XZx+qLM1RnwqGp0P3JZ+d47zefoH6xiM+vWvdwJ4vIUzGq5b7jSQ10HtXJBebrdF/XvMsIzlKGaOGv47uwxDLOCRI0HBetpEMG1d19bpNmEksKpP/Jsj9VVVhQfN5WXedoRGAr2c6dimXSssxg6ggMtTEIbXSgURcWBkMMpOcK23Siyv//23uXGE2W7DzsOxH5/P/669Wv2/feeXAuZwgNR+IQIkyANmBC8JKArZXsjSHAsAXYgjZeWRt5Ye382BgiQMOG4YVsaWPAEGTY4EoQaUEgCJrjoThDzdyZ++pHdVd1Vf2vfMXx4sSJiPzrr+7q7ntnuu/8B2h0VVZmRmRkZuSJc77zfWTN6Jpu3K10HIkk65Fn46yBxxhw6fvVSboQ1oIzG4OZWouS2xcKY7/I2NLo3nJufQqVNv7OwePhjML/nFuwDpnWjKQarM+53y4DODOAhrbIj8/Gs8eWQDcvA9lqb+5kcZ04UPh78lL5Fy+IGr/UC+0fbv8wB/5EIMC4SQFg9HKK21deHkpekkSoCEUuD3KPSFpC5BmeWHge9KbTxoP0eVuqWWEIMFZeSv8zIA8e16VkOzTaDsQXMQgP8YjWL3AsqIDPywbfwoNv/NLDZz3Ui/QvCpcZhj3pg1n1MPMVkFlwkQfKfvb6o66wsK8ZLHZ5MllYAy799YU1FoGNASWavM4SyDGG0sKWViY5wIsB+eyHLhnLcvtzZwxcAXCRsKZZuVdsCTQgMr3Tq4Zvk+Ze8/id7WxnvyD25noWL/rqBHBRTDm+ErLTMUCSxuQ0VYkk7pGmONPjtv2cdpE3UHRpVSbHlB06Rd3FbczskX802h6AVGS2o1BHv7vrPRC3MX6x0wl6lAEMYCdfwRBXGFhKwz0iULYlAK8kLsD+nCOKwYS569p+bftdx9ELQ2uKVNOj5FGL1A0wKx/0bfuQzhzrlDi/bzJGWu26mULXtrcibBm2HadKqRMAWkBHDgziQcZNAVWdC32mboDpEsSpR5IGb6HvQa64ihR2DraJ7QHeMx2ceIPOxYD24L0x5nGq9yXszZ0sXmTpy7OJUWDGjX0udkK1719KJA9T4KlIHnJS3H1KrW/jujeES/RlTnAAKPKw/hzRo3l0HhCDlRgGqWgtCtnXY8BY+RaqImItAoApG2l/QjVKmyTekEgBpLUD8ZjE2dR8f5bJcT47wpkR3gQNfIbd5V5oJWlArzr2QLrk/jBLVifI+Nk4Rv0gVHj+dyIaxxV0qdQNo/ZdbsVV7gdZemhbeQaspJaFlQrAL5GoixB8mtRxPDbHMs/BVQEsk7/78XQ5gsfiqQAAIABJREFUyfLB940GiRU4H1w0lsCZAefAUPlajdzAFYT8UiaRoVD6u14ySmnFcteDjw/gyhwmy+JyLLcYCj9Z6D3IhduTPTiOfR9cYWX51hRB/Uz7f1N7KycLQVXS1W1qN4F7b0J/9UsZMP7makCTjPA4tF2c9QdR+7qSdWmaCH/Wvna9lKYDV6DZvFqHlwqApIMTab3w1faTEC+XV0rUeZMTQ/s5DCFFnHKHgt3VYxbLMQOX8doYiWdhT31KeHAx0+Oc54tINE68oDObOB4A4vn7PuHZ0C+1J9dVOP18ITDrYQhkNAR4OL0wfOsXN3tyKWlXJcMFpI+rBtw0sq/yT/rsiiGCU0Ki5Upe0L4HsmxM/tt2oK6D8xmZ8CIPA+rPVqALnzkhL7K9XCF/IilOWjUhRmPW8ny5IgMMpLjrcoXJgzyMid5nZj+JEYGeXcIWOdxyFfaxp3Ps/3Qi59cxGBxIxaEdh3EwXn+F5ktkKYy9u3mA762cLFK4t2ygMc6CGVu1TtND9IH2Ln1QPdfg3OXl9oBmqDpVyQBfPRqk7nxbenOS1CnyTKpLAQ8T95DhrhccxZAspbIMMF08NpXp2xAZCvR3ypeh++WZPLjbqk6Vrk+vw88lVFWx2rH3GRvV+VRY9ayG6fyLrlR3gxcGWq1GE3lwnfMCI4Ee+ACy9ke3+fEJfagq2ceroAMAqlKWHn0vEG5lmTqYwA4O7IOZAELRGwHggz3QpbzAClV3sxr0JArx0KSKbaX8J6ojq5wcHheCC4vmTgV75n8nAk9KmGFAf+ClAKyV6KADhgPZr68lqG46hyy3aI5L34VMJoM062UteFpLNet8ESZdN6uxuJ9h8lGCm5gWsOwnCeboWVQ5qHOwjuFmkVaPXyKzRlsrJn/Gtk/H/Ju0oYboZ+JQmp16AiZ5cYxnOiISUhh4fME2Zar09KmLmbItqXvphBhmxBxlreS407SnEu9stEdlOV4Lh8u6xu3Lva5GUkcSqPE3WJsozwJn5rhRM0pbct8hyh9ck1ZOrwOAqRINCvWKtE8bSxluu6h9kkCcA4As4DxaOUfKbG1MpDIEEvEmM4o/KeEQ3BD7lk6ceRap/P2LRlnUTxH6wnXMKOmE0/uUeJGDdQLx5f9h+ZR6i8HTHEZ94LZF9u59uIsI4KKyEECdTtyB1TxSDahmCmUZuGlBBwLy0r4gyyLRjqfp04IyHTM7m4FuH4MvLhPPTBi6gmeRjCu37YjgCQD+xfKf4Hx4cqO1yC4bsrOd7exG9lYuQwDE2TqR3HsVLynokSp35pWy6rQQ6iXOn5aPax8TD4M9z4IahcIsjU2QrFl1e+zw1YzB52ycfqUMgpufap9eKenX4i1jEr0N+T0UcW3yY7x6B+OPadGWjk0S3wgB8GHwnBQUjiML6evrjmfKMWGMLwx7frYs6sK4a8v307jYNmNmWeZuillpFgqIUofm9Z+Zt3Ky2FaifqWCMeXm3FYbUsR4AQCYaT1a27ulp1O3NqHEF2CSKfJQou4WS5jpJFDaB3d+bxrh3tpmXUfuxovL8DOv1jCHB7L96ansXFdSq1IUki3RmMNqBeQ5bFXGehR1w1OpAUD4JvNc6lemte+vFwG2xmdVfH98nYk5OoxBxy7JSOS5cEcAUq/x9JnEAnRpwMIgzk175eUgIqkH0QClP4YMRVc7TwBdiSoa7U3B84UQzfo6FqXr534Yc47e2oc5XyCUhPt+iUrXSuQVfG0IWYAOD7xYcB/vz6QOyyuFlwOQuM2kisf7cR4eP0Hzl95D+ZOnerHgMoe5WGBQKYBlIzEIx3D7/j4UAsQyTQ97vsLyl2Tfyf/biQobmZD2hCFZbpQF6OQ0QPTp/Xfw7DvHOPiTkzixTCuYy1WMRQQpgFxStPOlCDmr/SihNHiBvfGTxdZZVXklAFk7Dl5Z/CW+ViEWoiQzXsszvGw+wJkiGkMb1saA3IpG6tw6wQvdmxPknsKcyyIGBNs2vmjDIDfQOUCfuTwHsi6kMkN/SSjqQCZRN/Nf7CKP/BIAeG4Tej7/UJh1HDfm0csGQIJ4erzxyFafNlSMQHdYI2s7UNOBNVimuf22i2lFfVGtTWgDZVILyFsl+FXKvKrU6u24b9OAGorFe3u1BIW7HjypQuC0P6qRDxLUc4XK9jl5SYgkmKmB6L4HlwX623vInp6FMeG6BBkDLvMRWQ4VhQQZdYL2nBBkDRb3C+RP/XNDhGGvRDY4dMdyf7PcSNpycGj9tn4ixW62zVHmFsu7MmaTqhTPSwPugMghTmu4Ooc5zwE/mQ8HNS6+brH302l4Hfq9HDl8CpVZsi6Q4jbbDMiY0R8mHxR789TpmxvgVNtgaR5tAxDFhJKg43Mo6cNh+vJpIC3PJHiorN1tFzIGI3bvvvcQaD85aJBqIxUbApxpcNFE6Dd3fWgrfOF94RjgswOhGG4MFNO+brJfkbWj4JVru0CDT5mm5ro4bpykOZVNezIJLnVKyTYKKlZlSDWHcVRXPxVESlxqsiaeT8+VBm4TAacUwKVjy30fA5waDPYB8HDesohi0qENDkHicP9821QUQJHDaVDRB4810DxiyvL1GpsizW61QvbV96N2hycL4tU68nSmz0aSCQpj0LaxovbJaQx0B51XKRMga4XpXAOcB/vA3VvAk9N4fmNlArae7T6wfEt1duqlAsD/c/6/47w/2QU4d7aznX1+9sYvQ671EML2NLCTLEO2xSxSLyV4If5LQQROURVuALcJbgMasLOCX0g8EyrLBBKefBE3dT1s1PUQvkc/62uqyxo4lS+0xmuS5OC+C54B3AA4vwzywbrAjZnokgCAgdcmSb8mKzdKAwb9FO8FCYt3G/oFQJZd6mVB1va8bsZLNJBHcDq4VPTGGxWTWGbvKy6prsMyJHxp80wwG6ms5CpZOiF6Xezh8FoiRdMJmMfKbjAkcYjlSuj2FJym7SdFeaauAoM3FUUs33eCAqU8j3KLpSBojXOR7VzP64OcNPN8JYlCmC5fOLOyPFsLWMzN/NLgcfQugw0O9tYRkOcwCRKWphO0d/aQP0u0UOoKnFT4hmesyKWQ7vwSSOJaWNy8iO7Nnyy22Q20TlUuYKtUAFGyBPDub1UGYhkAQoe/RetUXf2gHdp4MpogD+h3LYSifuTKFnlYd5NKCMDjFZRS/9l57E/bRS5P7W8nEwnVVXyJFGmpWp3euO0CX2UAO7VtWFaw9tNfBzvjNTz9g6Z0/EUuxyt/5cGeUNIjBit1zLjtYjwpHfIiUvaHNqeTGOTRmEVRiPvtCSiprhGkClUjdTKRicyOXWp3NLvqKvsXHY4FSJVyVExqiVHoMqSupE9tJ9uTOp3AgdnHwKtqnbb3pihVL9XzXpIxGG7J0sJcZCHQGKQAMgNXGGSLAtZaNO8IOVD1abn1A8mzqQQ42zb0gQ/2MP9qhePPYsByOJjCGhM0TrVdV+dwVY6MGe4gAWU9+LJPFjew5xaV8ZiiH5C4ACt/4vNPPKKqB4Armqa6bZMQZ3Ch8IoV3al/67fsixg3uMKNmRYa+XgBdT04S75KWpCU1rxoOlSJfTbh320XA6fav8FEODwgWQ1/PJukvW4ct7luPPS6ueviVzLELjzILilKk/Rokm7turAPd7F9WrUjkiA/OOE8AkdPxrEVJvDAUK51GV0nQcVUtsHXp4T4USdAQDgnUgApvT5LnMQs/YSXsIfZpZ/0cwvqLcyyFWIdZfdOpQkSC5qu6dg0LYoLNxp3s24l+BuuyWfnAMDJebRfTBT3u4G9PZPFS/IfBLbvJEsS0IAU3bQQcbYaRHp+GIeKQvqiEX9rJeU2X4zSrMJX4clzkjaULyNAtvVv2XiGT3kt2P+v/SVPRBOqGpUzoyxHX1qUpXwBrQ2s4rRahb6h70P2x7RtZLzWZZuOt8/+hO3eBYfFKJvCbgCurkBG46E/h7EMIkNFqOkgqiJ8vhC26hFJsScFYuZwXQDg6gK03sjuqGeRZRJcTLEtRS5ZD0WoFoV4FJlF9+4R8gdapzPIfikCtCyETbzv0U4yZKUfX/Us2g7DRO6F6Yfwhddt6lkQM6jp0e/J8VmebRUr5qoElxmMD8oCAJcF2n0zKgZ0VQHbdFs9i+VXpthbt8G7AfBScO+3Z7LYBCZt/rxJqxdYkiPgJf36jxTIAQ89dvEh3XJOqJq5oaiDOQxCoecYSCaGoDGRnCNdi7J+mfS8G+v8oKLuMwPjjIiTr3undHAcrzOJ2wTl9KSIixUw5KtXFUvAgwvUdUGAeEPjJHB9ns8Fbu6vf3RNaZVuej2p5oZe95LGquRkYtWrtt114EZgyqn2aOhP0r45u7yiRg8gFoW5sUfInsJuREvovYL8AUXoNTPQZjJB+aUfO4ZpWvByheLRArj0tIWQmAWvG9inHgKexCyyELdJYhaLFcqHPga2bkZL13BtF3OJg62bkDqlwWHvozoWJwKwTooDN2MWdpVjOjDoYoEs8WKvCC89x3bZkJ3tbGc3srfHs3hFG8USXldXJJxjvGTg67yen5VpHOLKdhehyBvwc9UhHZHq/DwsgZYLJFkyCSGWYXnc/y/SlACJWdb6KQTbL/2ixgi2xqW+MBuRH73aKagbrpYPvIS9nZPFDbIhcddrhJPTKkdAUozcRqWxa7IhIEFkRs6GmPZLVdHIWlEMS2pXRophZj1WCcs3YLeqcmYopjqTvmuWBIiTBFlfTh64Kj35Td/Hda0/lyiwDTHLoufOshh41Rcjz6JSGCBoTp9hSPtNjuVatmVDdDyQgLKyLIlDCKkLZRmYnLCKARKT6HqwiWAvyvPIKZkqpVVlDASGjRzGUuJNyf3wWa0Qp8qzEJPiMgfaSFBMeS7xE4WsF7nEAxYGw6xEfp7cv8wK2EpRnswhNsBekYxzC5dbWCPLCeUMzawF7JbZoCqFb3SV8G1WBdrDAkUSp+K6lBiPXpPyjVQF3KSAXRTgBOX7MsTJb+dkcQOT0vXrMRojlmf4F965EQJy+7EOsPkoqASTMDklqcCREDI0BekfoGUWuTOaZgTT1v6QkZdnhJRsRBkdeXE1+2Dt+DwLEyL2WtYfXgwN8uqEpTiLScJnoefJC9mu5S8HE5hzrZFIgmV6LbzlAfTjoT8DCFBuAPGlr0rQugH3vp9lIRO34zhedRV1O5MXpT+ajIhdpFMsk1vXCYYiDXBOKoFwn6qEogQ8yUPRw7rfB0d5Ul2Be8M5NLdLZM+SlHVuYZjRHsm2zEay4v5QjhsKCXDmpUUOBC2P2V+UW8sWuC7lZb9cBFIeN5tg/p7F9Eex7f5wIi+1nyQU7u0mOZgAM6kCpwYggdab2ts5WdwkwBkCesnAp+nHlA0K8NofbnyjtgU4nRkzZTkGr9ZXeDoDk1Ua4FytY6Cx7RAYZ4YBfBn5EGJ/hijas6kbguVYwBiQQNooNdjGytBl1ChRcWUMQ0LaI+4pX8yvBDjJs3pp4M0+ehap81K2Lx9w3Oaaj5i99Lr7Pglw+nFqu3Hq9AKB9yIEL0PatA/aowCQPaDtAc5lBrdcyYSRBjgv5kIP6PvlFkuQpmqLPAYzmcWjWDchIEyeK4LbDpMPL4DT83Be4wOchRIXJQFOM/eTzEaAUyWYxuMUjU7PYS89KMwHtu3JMxx/Px+1na+aUYBTmcttkUt9ynyJfJUAyF5CN2QX4NzZznZ2I3s7PYubxCxeFMt4VQSnoUBXB0AQdWUJ0q+xVp1+0QjOqgRW3ovR85fjEnVSN32I8oes3J4bCE4sl+J6/ywRnJM6fulTWr2mjTBwvw/1/ReO4KSyEFxK1wNlEYsM/RiIVorfNq0FNXt+8TNBcEIRnE0b7vfLIjjZGlgA7nAa9ueHX/ZlyA1sBPdO19CvW2WbqnWpZUnw8BWUtl6tH5GzIVDfpbJ98IHEwpc0a1WnximMiX/Xvv+sLRU0oth/KnKwzrqeU+SLUo0fmSrDEQngSgl0hgiqStXruCrGILgv0lSwylCgDHxZ6/cK2GcmCBrJnP5lKlFXSzg5N8vBt5oG9JSjE8IvqeCjkWyA7p+Wk1/D4Ul5Md6PlatzBZARYhx4HtDncGQGfkw9h5aQawxAC+AUuToqgiN5SNN0okkmjtTyPJY6I5atS7McMwxFEeMHgYWMwxgGLk/dV4vN0klG9WG3PVM6vskxpsjHZes6+SnSVq93g6lrREWQ8qcW+dVnI+XTVC5L3T/LQ8EeAOFw9eXvZraXANaGwCEaStStCSXuGCKoTnlLU2IhdJF4ecRjqhyrXfQs3eXl1piP2RPPg4gCJwpfzmH2ZxjOniXXlEXvERgRPpvjQ7jTZ6Mg/suUqL+5nsUmvFsDh30PM5kEBKGpSrjVCqauI6qQnVRJNg2QlwEN6BJq9+z+O7Lt4lK+svfvghYr8L64aMMPfgy7NwUPg5D2wlclDgPo4BDwFYX8yQPQu/dgPnkwasP+6q+Anl16gl9/w44P0N0V17T48DHcoVfiPjlF++33QY5h//D70tY3vw48OBFl7/MLGM93MDx6DHv/HfBeDTqTasNAWX/7GP29g3CN+Y8eCKnOk1Pg/l3p14PH0mZVyXG3j+W8P/qJ9P/f+i6yM3nw7XINNgSeVugPK9i5vGgn393H7T+dg9oe7W1xgckx8tMVzKeP430LIkkM/vq7MKcSxHW39gEiDNMC+SfC9qPsTf1hjezZShTZAXTv30L+yVO4Ryeg73wLANDcncAue9hVh34WC76efKfGwY87sPVaHgBs6+ByQv3ZCs2dCtM/+VT6Ngxo/tJ7WNwvcPwHss3NpmjvTWGXAuEuHsUlyzAr0dwuJZgJoL0n97/84x/jz/+rb+G93/c7EtDMDPY/avDor8pLPX3oMHgV9cW70q9unzGUjOLMYPYR4+S35Bn9ld9dIju7FDlLXcIag8u/cg/NgcXxH5/BPBGynpO/8Wt472/+GGf/4NfDym9+32D/40F0SBjoa2mvOSKYFtj/6D4uvhpf++4f/5+4qb25k8VzPB5u2/j1a1uJDSTb0ljBNugsgMDGrC8zPT2Tr24TJxynMOnQlvcW5otY+df3oLPzq1+0x6cycaRfFXYofGm3O78ItPJ8OUf54RMAQK9flZMzuOUSZhDVdvVReBjgnp2D1k3ISATP6ewceSq6czkXrYvVGuaJfH104lN1LqOkLX68i4+fxiyAKpnPCxTnZcic3DYG9pMTsHOoLiLUmJcrr70xLoKDY5hHp0Fzg7oORARTFkL9BwBLaTOfV+DlOnhYOQA+vwD3PexDmViq+UpepKaFTVLFd7ojUTNPafWck3qTiwXsWRVZuJ1D+ZOnyJ/WgbiG1g3KdQNqOqn1uIyTRX5eSHrUZx40RsGrFd77fWD2g7Ow77TMYZ/N8Y6TiTg7byRFyYzZx6qibuByQj7vkJ+ukS/Ec7APn4qXQiZ6GIaw98MCk4nQ6jkfd7n1vUv89B99gHe+fxomzOmnNbKzZUiJqhTAUOcgx8jOliifxhjHh8ubg/F22ZCd7WxnN7I317N4HXuZIGMIWG4gOkd/3xK/uIHWKYC4Ztzo25XYwuayKyUwGUn3mavHXtevz9vSdo3XztwkxvV/AxBZwcMQb7n2a7VYXzC+6j1sjptuS6sp032T/odtI5Z1Dv8/byR1P8c8jhESXfkE87b7pcNGkP3TGIMGe3njmdzmBPjj2VE8n/YjvT/pOL3iI/J2ThbpC6wl6CnMmF2AeV8H9w6BRhNTiUJqE7MDIZia8kP2nh8xfRi3lPlSZgFrRuXllGUC2QUC8xIAAQBVotil/aIsA4pC9kuEYchIeTxZE6T4RnqhI2SpEWavpPQ+DXxJFmWjziXPQF3CT2pIGMK95igADJMMpi6FsDdBMpIvI49pXg/q8qXkYamWS6k45xHuHUr0rfVcEkk5e1KaDkDSmtSJylhdBkDXUGcCPsotuFTCXi9IXOTgSRkzCYMDl7mQ64axNXL9HNOfwTLRDTUKn9bAMBGamcHUl6jDAMNeAbMs0E38Pp0T9ioG+on0q5sYsAXYEmxToJlReBYQxIcii5grMrgqk7So78NQZWiOgGEa4zbDJINdyRjAcSAu7icWtiWBmVeJENXnCfcmov8JwO8AeMzM3/Hb/ksA/zGAE7/b32Xmf+r/9l8A+I8gb/PfYeb/68a9uaFd1fbgKxkOjeRfR4KToh8ZEKaoNIPBLiIJOUbj2TGo62Ku27GUUG+0wx4ZqPwZADwFHCRmkZTC87qBuVh4tKVHeC5XQquXlIbrtfPax1I05qFFV00T0mIAPOOUROY1CBr2hRDPhBiNN5ovo8SAj6pz3wuy0beXn5TA+RzshqjIzSxtdJ0yFY71R1armG3xY0BZBpdkJwCZWLhpQ9aCfMk8+3PoPkp8QwlZTHGSwVxelQKAlwIwSbAazDAXC2RDovfqGcq574WwJu2vczDMYZtOJG5w2P+ogX02D7uaZQG6WKB66PksFmv5oDiGaSXrURYWnBHMSqQA9mv/8ZovRQohJdppO5jzBWjt+6T34ekCRz+skD2JimRmVcFcLAVnwQzrJ7VsngO9g5kvkScfT9PfPGZxE8/ifwbw3wP4Xza2/3fM/F+nG4jo2wD+fQC/CuBdAL9PRN9i3oKKeg2jPIspMCVxSbVOfaEXuyH8f+Ucmn7yUgA0mwHLZdCmwMXcF1thXD8yOCG7mUqQiNcNzMF+fMF8W3S4D1zOR4VNNJvBHfsMSNeBZh7k2/Vwdw7FlT+RQCft7wmoSjMwCrZaN6C6kn4q34I+wPvx/ADEI6lr0DCAvC5J0MhQEJrPssDDzd3dIxgftFReSZ7WcNMKtJTfFx8cYtr1UgB14LU8mOW4ro+MWIE8B6CDfYAuQz8BwO1V0WP398PNapjLFci/wO7uEQz85H64DwAYjvZATQdatXCTGOC8/OY+pp8U8rVU79sxXG6RP5mjP6hhL+JLPdw9QndcofRZJZpNMdyawSxbDJMi8lFAPJj2qA4QbgVc0cUlHv3VKgQzAaCbZKgeFnj2bdmnfjqBywjEjIWn/O9rgiuB4pwxfVDh5LvimXztwxlw4ZegOlkYQvuVW+hmGaaaYQKw+OAIn/01h/rkMLS9vFtg+rDCkBsQA0Ml/W32LUzPmDyosLwfx2z45Ob4lRcGOJn5nwE4fdF+3v5dAP8bMzfM/CGAfw3g37hxb3a2s529sfY6MYu/TUT/IYA/AvCfM/MZgPcA/Itkn0/8ts/XtgW/thR9bd2upq6954II6mFN4hZv8BMK14Ffnii2gb2Lv9nOuvH8kQkrUdeBFmtxkZUT0p+Xlo248rqzFqvp1yVNzXpGr1BwpEuXpoWZRyyJazuJSaQFY2kh25DK/PnA3rKJ/VLF8LUApmgt+xbPOvGYBidqW3p82425PVT/wnlmr8StlrYotK/xEEMk1+a3m/lafh6G0L6Zr4VnsulGgbvytIe9bEQ4R5chA8NYAq0aUTPX++QYZtkgy00c29Ua5kIo8Uw/REJkiJeUWQrbzEUWxmj60CE7914YEahzMIs1ap+izM9bH7DkECPoa4LLCPnSoThvMfFMWbQW4WNWPRw5KbKLNagvgNU63PfyrMXkpxNklzF9XVmCvWhhferUrn0BW8ei2H6xRp0nQLbrKrO32KumTn8XwAcAvgvgAYD/5mVPQET/CRH9ERH9UYfmxQe88ISvlwWmNGpMNHqotu6bBt62QZE3syDpdvKIyHRt7SHb7Hy8JTl+K8rWl1BHqLdE0Nma8I800j+K/JskuOmj7iOujGRfz9+BjX05S/qtx2/GCUK8Ii4N075vnlP7xdaM27IKA796DaN2SYBYOlGwBgINBHOwJUsRzq/mOUDZGoF32/hPxjTZlvl/xmDICZwZaceSxI2sgctkQtAx41ywFS6X7UMh/WVD4AzgDON7ER+A5Pw23HfOCK6AtBfGQPrgMiPnzvx+GWEo5BqGwoR/L4H2fjXPgpkf6c9E9D8A+Cf+108BfCXZ9X2/bds5fg/A7wEC936FTmz87q7/24tMGZISMVrfxyv7vbSl6avRdjd+oa60JcFO2uYxfZGsVumLnkLidXwASb0NWyZThWZvgrLCOTYg9q/bT8cj748YPr3IIFYmcQbnun8M8AISz6Dh9ceSGKNrkn7wKPgL0Cj1SazHxf8BeBZzBxi+0fNGDpG4OelLaDug+V7p0kb2SpMFEd1n5gf+178O4P/zP/8fAP4hEf23kADnNwH8y9fu5aaZjS8bMGLxDl9F4HqPI6kaBSTgx8MAKCJQ6zjIgbUkwRopSsujbogwXxcjwSDAp/TabnQjUZVw0wowgDkrIpPSIhPBXB7vS55Zi9ouMlIpq1ZdxZoPXULo+b0p2Q4vVyGAGKoui1weqnC9Mo5uVsE4zZj4008q2e5/X9/KUTyoAOfgZrE94xxonmh06kTJHMYjjA0AN61gL4vxtr0ahjlgNIa9Gna+lK+z36ffr2DWGYwxowDn6naGbFEJ1kDT1YPDUGUw6x7DQRXSpADg9mu0xxVqZcuuS/T7FezSYJgUkVwXAE9K9Idl4KPQ6tEsy7B4lwIyE5A0pWnrEMxkivDz5V3j9yH0FVCdGpi+wOJ9Cn0gzWLpfSBCd1Ch27fIH5ZhCbw+LrD+5TXaw3QMLExXYSg0wCnn1QCnbUusbyVjkH++qdP/FcBvA7hNRJ8A+HsAfpuIvguZr34C4G8BADN/n4j+MYA/A9AD+M8+70zIzna2s5+PvXCyYOb/YMvm//E5+/99AH//dTr1IgtIQf1Z13BpNaLZ8Dw2LQjG+vWsB2VxCmrSfYKwsfHqX/aFoCwFJ7G1oQ+cJWChzMa2sgyuFM4Fo2Axz5lBmZXrU1CVIdlmTehXCrTSWgDZHuMTvAnKoiRukZgrMhjtl8oV5AIKokq+wH1F4CoHdQOGygfmWKpIZU3tgUv2uSDxAAAfp0lEQVSK02AWbyyL1waSNfxm3Cds2/idfD8AgAsDZgseMrg6Cy52VxOGUvALzquDm87B5QauyNDXFrkHZfHg4AqLfmIiZWFmJTaQy/9ItFw4l7W+bgt0dIZ8UZh6sgK4Kgsbirg0mCmgLNnW7QFDyWg7Qjcx6GZ+6VbkAtazJtL0E8EVBn3p2/fj21eEw6MF+mksHuwmhKE0GEpB2PY+ddpNANtK3KKv4juxjQHxOns7EZzX2Uus5QOprSpmW3M11qPM2CHY6ULQUMlFJNBk4/n02HQCScSAeBOGDAiakCDBsQ0dDqoxjqPoubIEKamTkTUBsQcA1poYINzgYxAEKF0RmWGbTCB6TeQDh34YpKKRR0HNFByd6o2ErebqdXOeTLphIvGBQ722ZB/2E4CzBmTSAIBvroAEXzFex7vCBzcTugIdtxHVibUi/NPL/5wErl0+3uaKuMwdSh6582ylH07BrT6YSQz0frUylIyhZrgFgS3gKt9fgxjDSmIeQ0kYSuHyNH48hoJwa7pEQ3GycIUGUGVghoLCdrbSb53EQns3tDd3stjE/CfGzNtjEalnoQ/LixCcKmff9ZEGXk+3AfeGkUpA6qNcnWOGaTqpEUgtTSPqC9oPMOskzqBfDmtgegcaOMK1nZTZBwSixiV8Co7WbUhtatDONB3sIuXE7EBNBzc4kbWDIA4BCNJycDCJ7B4A2FUX+T4H8dCo62HX8SUrL11I/2qAkHoXKPsDZF4rf5nlZx2PfgAMwSyTtnyq1C6s/Oy320UbxtJ0XgJw3cM0Pah3Pkgp5y0uGHY1gDPxMACZNPLLAdQ7mC4SMsu197BtHoKktG6QLQqRFGQeiR1bA+SlDduyhfdQ+h7FmUHu5QeZZFIzqx7FufQrXzpkDQEsMQp5PAhuQSgugWzNKJ56z2/wk3BmY3rfGBQXfeijPrvlpcOHj27h/ZbDV6q4YGSLAaYzAAMmZF8NbMvIL/vQB7lvuLG9uZPF8yLmqjaG+KIoBiIc+yKcRULYG5SmlDnbH8eKkwhtiaKVUMd5BbFhEBjyBmEJLVbgxqtLaQ3Hag1z4b+gTQvyZdncC+QXg4NT9ONiBdf1AIkaVxBediyTABBxFjpprJuAvgQUZ+HhwYoZ0H39z5HwxsOFL1axX16KgBxL0NE/vPWjGrRYSym3eiz9AFquBb6tXoSW5zsHWq4jpsKf33SRsFe/deRYsATKV3KxDPB2msuYZ0SCs+h6UXDxz8D0YYHsbAXOLexGbYi5XCHLbcSVDAPs+QplHglxCEJwS20HanrQIqrE0eCQ+/sCRCJc7jrMPmLkp358DWCbAvZ8hekDcSOK8zbUhpheJhmtDcnWjOJZj9mHnmpwvgSv12OSJ2uFK2RdyHPhr6F+1KD4swnK0wRqPjCKp2uwIjj9OGSLDLZ1yE+XmKaORXfzNMmbO1l4zyJ8CTYo9QOkuMjBfSfq5p4qnrUQx1Poj1iX9Bweak2+WhLHB6B5JL8xT09B0ymoaeC8d2LKEty2MNMJ2JPf0HwBHB3I/0Boy905hDnLBAyly4Rbh2jvTAECyraDO/IcjX2P1Xv7IAaKTx8CAIZ3bkl2YTqBsSbAy2m1Bs32wNM6eJDhBTicob23H66xWK7As6nUddwSSHDQvSgLOc4T8OCJwMzb9w+Rn/oajKVwbwyzCv1+GcR7n/5qhTvNHqhzaO94GLpjFGclbJo69R4E2g7DnUNY1fu8NZPz1jkK7105Jb85qpGdRfKb9r0jFE5qWIZ7cg3rOzWy9YBs3qHbL8JX9clfLnE4sbIMMBqzYAwFYfIgR3NcYu/JLDwLy186wvJuhtufefj5rEbzzh6yeYd+Lw+SggAw7JVY3asCC3fgzHz8FCe/1Qc+ChChmRH2axsg3JOHmWAoGCHr0c0cXCUexezDAmf/jkw2R39+jOy0lGWx9wbZGsy/sY/1ocHtxWG47yffrvGbv/M9/PmPfzWMweJdg9lHFkMpnkxKfmMbYPZxjsuvxOVV//2bBy1eD8m0s53t7BfG3lwOzud5Flk24ofkvpdSbI2WB4HemOffNFNpIZnySuaj9lzTwJRlZMsCAoejcjde2Q+I7vxsJm6+ei6AqH9rTn/dJHycvXg6wxAqIKmuImYjrTptO8FGJNWo6s2YRMQIANxiJRyTbQfjt2u1q/JcBs5QpQO8dRxjDZ57UpXOAp5jtif6HH0f2L15cAJvT8rpQzakbQXvoUVsRQHlxQzMXVomnmdgz+IFAKau4FZrcNvCHnivqfRCPF7fQ+NSNJsCy1VEWAKyT9IvjfMI43kt2JcnvvTJed7MThTc0qpTValnz06m4+zOL4C//CuBxQvGCOXAfBm8Nlp7uLfjgBXhIgeMxChovkT3rhSi5R8+lGu3Ni4dDQnepsjhnp2H5ad99x7WH9xF9aPHYQy4zGWpFLJMsaSeuh68XI+Eof7ws3+I8+bhjdyLN3cZ8hzbWnZ+BenI4/83d09V1ElSopsTZ0B1bpz3Sjl8319tx08UWnsCQMrN1y6kYGMJtxPq+7StYRyTGcVE/EQRl1cJoW2iNB76qerv6b4DQlxmdHnrJl6Lj8qzc1Jtq1mMRaI+Tm04Lw9xCbJpnAQ400kk1KrotXt191TdPtAQ6GSjLwazxDp030t4iQADKB9GItAUXsLQp06AY7ps0noc50bq6gBEUlDjVdJ4GOPs7DKUz4N8rUnTABcU7wMgY6j1Np4YGETg9RrZaVxCKzo1BLUdZJJqbKQ9AMDzBcqHlzJGOn5tG2JNcByzTdYf27YbdUY3h0G9lZPFVksZpK7TN73muBEztpKxeClDNi1UrzTFd9zYUsar0XYTU6cBVzAgzCyGAMpArpMah3TyewnCktcy7aPWkgRsComnkWpqDgARS18VHasTsdZyJIjEa/EvL+qPtg95iWBNJDLTOhNF1QLBqwj3WQPYzmfUsuz6Op4bGifYB3jJSU7ue8D/mOTeWX9PM4/vSV5qOBZMSvBIs+0vNUlNisnGfw+1IgYjLM7rriHe3Mkimbmv/s0lP8Z0qQuz/g1mioTunthrUToGwadE204COsOQSBPeHMcRa01ceFgICC+NZmF0X+osOCFXgW8bzo08nPS4L8TSL60uobRaUr901oRK0PCVchyzRwl1f6DFx8a9fBVcr35R9XfngmMjf/egOccbUgIM5l76nWR/yBMfpVIJr2I08vJIsmCDS+pn/N8cRwi3qrT7JVcIZq7WHhqQYEKu+/oPDtQNwqgV0vQJc1z6nrzWFfpTfw7n2NnOdvYLYG+uZ/E825g142ZdI77MqWjkQoZliOmvuqevUgafLHPk92TJkxLbGgIGHu9rk3V3UJH6gpcgidcS+qhLkQTtKUFml8QAhlDMp4HbzbjRFeGbl1gvj7voQWqqVrYhXgRrRml0dAnPauKhQaHzoT+vWIFqknvsuVuhcQMAgtTaGAP11Pw1hGWIIVleJUuPkejSqF1/X7Isxrb0eTYky+fNgsvXsDd/srguW6PbA5rHXM2Y+Ac3KllRODY8TE0DsIPZE2q8EOVeLOLyw0X3l3xUOo2Gm8MDOK9RGjIT+/uiiJ32aToJtH3uyalodgJwFxcwB/sgAP1PP5bj96aiLeIj/9pf1zSgsoSZzaK4kAc/0cTT/el1Pj0TMaHFIuBKgk6HVyrT/gynz2Qcbh+Dl3pe7+PnBWhShe3uq3dhPnosBMdJZB1LyVoEhfXEyI8HgJBBoVtH4HNPtadEup7uLwC4Dmbg80u4ebwGmk7E9W/HWqf9e8ewTy7DvQIAcgX4+EAEn6Y1+JMHYX+6fQye1oDXErG3jgSX0nbgqoRRCj5moCqlIlQVy2dTgAjm4Qku/8o97P0w0VwtMpjzBdqv3AIAZBfrUEvSHXj6wMJgKAnFRY/8dIX5NyTTM/vnlzJOaQxiGEBfew+uzmE/exqWUu7r93HyG/u498/iJNcfTUQ3JNTWeHj6JAdnhPxkgf4o6obwn9xcCvHNnyy2WMrYfS2LNxmAE6j25jl0MHVDloFsHwNgSDwVN/6drB3pm1KWJe0oX6cPWqaTXZZJysyfQwuryNqwPd03/C3pbzi2yMPLzIOHrGcZONHBJCveAPu/ARgxgrOJRVRqXBahgCnwiRae3dtvH/YKWE0BJ/2mXjlPr07wYTz0Zz021IZkYRv5dOdoH0OBDZ0rSb0SM7iM7Xd7eSh5D9fDDFfm0t+yGHmLXBZwdR6K95DnYfy4zEZjw3kGNylgL/NwrLJeNQcWk4lv1wGuykDrDt3M38O+iJPFvmfbLmWyAACzLrA+lL/vFznQXCVTcnUuvKBZBhi578OkwOo2wVXxmrtZDrMqpAAPiOzeezmYAFvn6GZxzPglPI63Z7JIcBe8Meum/4+2p4xXQNQTTfL74fjzCwnEJWzT285JFoF1WzY6uMUyIkp9G+7icswWDgiBr8djuNU6nIPbFnTydNzW+UXoZ9rfcCxzhG77CcktliE1ByCk1LjvwZ7cl71IskLXnd9uVCf05DQwbqtXROsGtFgI/BxA8SMKnhQtomqX81/7bS5zGA8gXDe1bQw4qtu+XvtAqQ8EPj2LX1Kv6UkeXu+6PmBrAKDuesF/bJjJMrjlCjRfjLVOT05hzvMoT2lI7n/fw2xqv64y2MsF3MJ7R03rl7CE4z8+A51EmlprJJA61dTrah0myvyhx8FkFmytH9sVbi8EnZriKFKznz2FzTJJ0frJuPjwMd7jOzCfnYT9JmcVeLWOyx3fbqET/sUc9Xn0/Exz8+KQt2eySG2TgWlzm9qGVyHkNT77sQEBV5r/5zJuMYfUViTaudoGgJgPT8/XtjFTMAyAQhSU3j9tyufbVWh4c4Kkbsx3KWzQCY4DCGtpyrLrWb90LV0Uko1ZrcYYFEjGKOAfAHDy4o/d5euFkVN8ANIMho4/s6zV207K2bV/iq3wOIFwjPO4jnRionnQ2hiZZhaGYTyOq5XgEsIHx4ks5TBE9XlAnEWOUgeAX5KWQkJknpwFSUHAe29djFlw28WXV5eOZGCsLJ1d04ZMw5COUzpM60Y8CseB6Z0vLlF8mo3ahsdSXNGUsRa4e0s+TOn9eYk4zS4bsrOd7exG9vZ4Fin6Ly/AvXdpsxzctVcKxiIMPKEQS1TU7b4ElNQFtbeOpNrPB9/6R4+lcGxwo7YwDDCTSZS9f3oqgUWP4NM2svfeBS8WIxSgme2B970A7uMnoD352Z09A71/X3b6iw/l73duy/a6FoFk395wMYfd3wPVNXgxFkam2R6wvxfaw6MnAo1uOxgNrCYaKAFmDmB4JOrq5lsfwGjV6XotMZmqBE+qsL354C7KD0+Eh2Pmg2WOYRYrWSqkCFCI12Dv3A79DZorkwp4KoLCATY+raViV6Got45EtPpiDvuOKMHz/lSuqe1GMZr1149QPvRBSfWunJMq1NM53KyG/clnoU/0/jsYDmrYH3wc+sUHe0DTSuwm+epyVcDNJrAnshTiAx8w/vBjnPyNX8Ot70WNkaHKkD9dYPHBEQBh4VaejfWx9LevhGuivHSoHzU4+bZ4C/f+71yWUkQj3RD39fsYJgWKDx+DfUC2+/UP8Mlv1/jaP43Fg+tbFconqxAjcb7qtJtmoIFRTko0d+uwv/vDL0OA8zl8FlSV4IXPOtQVhr4bvTyAA5XCqan/Axidj27JjTRPzwBrMbx3G+Z8if62x/M/eQrak8i480rTZloLIc3xIdyhj8zPF+D7t69UnXZfu4PscQmzakJ2Yrh/jMX7E4CA2fc4VIgWRHj2a7dBA2P2008AAP3X7koF5/4ezBMAWjW6WAF3bqG7PUP+wCt3qyDPu3ew/Oo0XOOs6zEczWA+A7qv3wMAZD/2sYC6AlZruHfvyM4+ZnL5nduoHnvOhguRLegOK6xuFyifyaT06b9d4N1/fg+2GbDwgjU0MCaPWxT/Oi7RFDlJbkD79TvIH0kmpn1XyFrWxwVmP/APs4/Qr+8UqE5aZGdyL+ffOsTeD6VsvPllmSzm7xbIl4zivMf6VhY4Gx78FuH4e0dwmRDhAIBtgKEA9n86weJ+hrteKoGGAc++c4yLr1t85UyyFu2dPcy/WqG4cGj3DfY+ii9Ve1hg/p7F8fclJjX/qkxux0+f4b2/+WP89B994B8soDkCjn5Y4bO/JmM9+ekErgDIAetflvYPjxa4NV3iw0e3UPzZBL/5O98DAHz0o28JhDszIM/fAWNw8hv7WN0mvMd3UHwqr+0nv13jX/2tf4BfO/9PQ6T+8hsOBz/Yx1ADYGHkAoDm7gCzJhz8xT7Ovxnfg/Ylqk7f3EKy59gVz6Lv5P+0VkJ1F4yNCLrEzEwmBW5bBEWyro2exeMnMHUlsQzvHWgQkMoypOzc5SXMbAbnFb30K2/v3RVeBl+MBUA8EF1vPrsI6VderYC7t4UA92P58tnjI5n8rAU3TShAc/MFzME+YGxIRYaiq71pSMcCgDs9ExLf+QJGPakLr77lPQv1OIanEqDLfulrQWOEu05e9rLwBVvy8Hf3j5A/fCboQ/Us+gG0aiTdq5kN5bYYhpFqW0jvGgKf+VSkTw2HFK3qfB4dgM/O4ZZL2HdkwuNJJZmZrpfCLP8Md/f2kZ8uhRqvUJ3RQf6tGvFkHkkpPgYH3D7CcDSF/ZEnoM8y6ZsWki1iIJCKArxXAz51qt7R8OkDXPx7v46D7z/zDxYwTEtkTy7Rvi8TfHbp+SwcB3LdfmoBAkzLKE8bXHxDznf8B59KCn9D65SP9uGqAuazkxDE5W9/Aw/+zRnu/8FluDfDnuf0sBbEUet0mOQwzYDs2RL9YXxG/uWf/i4uLj/98haSXbHXnPAk6Jmwaz1nv9cylRrYhGv77eR4FHgMhVKbxVmOv9ho0yhonFC8aTA0/fs2KYCUhGhbYVkYx5cECm0LbG/72W1ew7b/5broc/hWCq2/XyY7SeluPpPXtsMb/+szkASK+XlBSIZnKEu2OQBKH6twpM/BKdgFOHe2s53dyN5+zyIFlaSYihcJIyeuMhEJ0pFZkI3hfOMCMmUQpzyLvBHzhfy8kd+nqgzpT01fUVkERii6nAtICAAWS/CkHFMDloUIH6fViPBpTCtBx1GpMSRIqExfgMRTqKokl+/7S0vvnvtllC67gm7IVHQ7AATFd5QF3F4URm6OS9inVorD6iKMVQBlbfsSVmUs2CpySWfWZRR1rpMAJ1EkId6byD6rdRgvN6tg1r0EIqs8fFXXd0rYZvA8mH7pZ4WtOxschmkBm3hCPK3Q7+UojA19GA6mMOsWriokZqT71iX6wwnylfQ3CEI/yjC/bzD91C8vCRgmGcyqwvKu9LeyohRGLLoegLBwu4JQXDDMwFi8K/09KpOUrYlVvv3RBN0sx+SsCiX361sVLr/hcDdBYa5uF6gHFlAWA0Ml52hnBqYHagCrdyLq1v2rm/sLb+dkkWIXNjgdwi7XgLXC3/WGOAZDcugjbk32mIH04RoSbgiKgB3hgNhof7mOeqK6cb2GuRS0JbddILrhvhfuTGb0WrugPA5K/JsCddoOTCZcg8YseL0GXcSbL3yYkhUKKu8pu3XfR8i4kvbMl6FfQZOUWYSHPAS7OlkLj+YwiDapHr9aj8+v/KbMInSk17CKQcYwBkpgwzyOWWh/2AmxDTx4qhddWhpc6Hv9qIQ5X4Z4CACJTWQWtFjBKvcIADgHc7lCDoS22BCsMUDXwzbx/khfHTIgbLOqpt732P94CAFZALCrHOZiielDeSntRQtYCdibzme1SpEyzBYDiqdrzD7yE9ZiJc+GJweSjQbZ2VKQmZ4ICADKJysc/GAf2dkqTJj1wCFuAwBZrhycBah3yJ4tEcO2gOlujrN4OyeL1K6Dc18HA1dLi8R88c2Is8H/ztcV975AN4SsnxSAGKMgM+KEIN8H9nICmvKVQ8hrdSaFZ2l/VR80/ZuyQqfXSKqHunEe5ajYjJ8YE/ulvAjWxqItAC434WVRSQQ45xXcrhaikXMgYyK0ONVsUQh4KKQyUW9lY5/R/47HBViA1xgR7gyVDSBjou5KKp8A8T44twFKH2QdnBvJO0ibJo5Zct1EXrNUdUSIvO6IxeAh1zYzcJnoeAxeQmAoDVwGmM6A8wj9hurM0LjAka0VEl59LgBwZjDU8BqscQxU+wQOsTYkN/K4GAMukuf1JegO3v7JYpu9bDDnGlX2zy1TtBmAI4rBzmQ7qShy6Ms1s/6raK6+jF0JGLrxdk6285b+bmyLjGBj/MVr9Y+ToPCWv5M6lFoZq+O9hfnstbVj01MGHpNx8FQDjOOAI+GK1ikQA9hBr+Y5S4UkuDrqy2te0jZ7OycLMrjCnpJuu8FsORIFMhREd7TIKXgW6X0yJE0YM/Zotnk36RdCd7MmqpClxWihTBnBswhf86AcNi5dp4RpK5RYWxu/9HqN/jzRWxgXkm0qwLNnbgIQQUFZJtsH/5UqE47L4FlwZJ1KJwPvWYxU5xMFMGx4G5z5L32i4hbLrv115pmHhzsZT/+yDKUVtzv5+tIwBOEizm303Jz03RVZLCRT7s5+iCrqyXW4IgsSAFG0SUR7ghIcEVxhYfMMg1cDs2tRSYOL2qN9ZTAUBDNIv4Pwj/XeEY2//pxbSYPa6PG40qLbk2IxnYSGSsYgehQ+dVoa8ECwRRbkAQC8lCLZLhuys53t7Eb2dnoWqV1XYvsiFXX9wjf++Cwbf+2BACjaPC9lWVTdIiM/b7aT+/MlRLfIc4new6/RfR+IRDt0XM4+ZmcefeWskYzCOiHHgWR43KhE3fM7EgVezBHvp9dVSbeLhqmHj/dR61SyDuIx9FOLIs+k31oiziJCNOJ6TONCeTaWKiQSSLW2r8zsZSHt98nvWSbrdt+Wq/NI91fG+9XtWRRlDrYUysdpEElHU+RwVQ4b4gAOXOYY6gyZZh2KXErWfRt2lZRyVwXcJA+l+a6OVAPNkWig6Dj2E4tsnqPx5eimY7hMlhy6rZtAJAXJIFtkaI78+PvnZjyOBDfJJXPj9WQBgXA3dwcMkzwsRdqZQbYo4PIYGwGAbmZBAyNb5GhniWdhv4wxi0349+Y6ON0G7/IPIg8Q0J4p14JOAunvI07JIWHEjm1RVcpDrwGuPBNEoQ+AhXXm4EFeid4nORek9oSiPmZsqHe+Wa3M7ARa7su105J49J7FS7kxAJnk8kyi7trepAbvT2GGIdRQkLWyX5aB2AVqelPX0o8hxig4xAWk38pnQQPkhWaOkGQ/hpwyYKfWD3FZE2QbKaRwuSwAH3B0h3tR1iG3MHUF0zSx/V7GQ1CcsX0aGOgdqI9wL2KWIOgwgDo3LlHvBthmGHFnOJ+KXX5liqm/V9QNcJNilJJla9DvFaiOD2FaxNgJM2xLQO9gep9h6iIPq26zrWiP2pZhWwfbaJ96yYZsDB9nosvKRQ7cvRWu16wJpoljYHoZH52neaCw7+X7FtWpGemyvoy9PZNFMhHciM+iF+0Qbttw7KbosPwQKedHKdFt5xwGyfmn+feuB52dx/Sl9mfdSKlwmkpMUpuubYF11NcwF4vRdWo6VjVQ0omLux7wMncAZJJTxq8EIcqXc6Dt4BaLiDBsW8njK1PWM4F/Bz2R+TIyZSWSiSGlCaA8WYocADDCYPJyHcZ903Q8AITrNucmQJeVh8NWpeAn/L6264Upa7WG8ZBwQwT0g2BkEkxH/aiGPd/gs2AGNQVovoR1jCG5H2a+RMYc2jLnl8iYQW2HvXUL0nviHOyigJlUIK+UZgHYZwbu9Bn2P7o/Sp1ybmHmS0y8fGF2sUbmvQHbyjUMhYErDPLLHvnpErOP8ziGbVrDL5afLGBr4aMIqdNJiYO/2Ef2LLZdA/K7ny2sh71nixzVqUHxaA7qItz7S586TYFW14KvNOBp7RXwEoD45VIsQVUC7EYiPYFNK2mLrAEVRQQzXc5FrMaTyATBmxeApkjBXABomUUwlbrPHuhFeSZ8CHlcLlDu6eyU7q9FAJa52QYoa1KJhqvWpHisAhW5cDLUtR+uc9FR3ZuECUBTnVRXASwFAM2dCSZPa5m49uKDRwBoudzOlJWMR6Ak3JvAKI+H75+Av2wIyLr9CUzTgpomALfcwRTUdKCVCZ4RAKzuVZg04wmemDHUObKuh5tNQI8S9qu9CfrDGtmDIvTBHUxgli36/QqZekDM4KrEcFAFUJY7nAou4yTDxVczlE/9ODDgKovcAUtfZFfnJqRM17ek/b4i9DWhOjWYEoKk4P6k2vq8KiirPl+Gib+5W+P8m4xbfxrvweqdCjUQ0qMazGxnFi4nUDfB6l4iRJXfPGy5C3DubGc7u5G9lZ7FzvBSYJrn2htQdfymGd9wbD+PIrS3yb78k8U1oJ0r2QvFTrxAnSpUgm6eb1OI6JosTYjSb+xz5QHVfmzL6mzJ8Fzbr8H5qtoEELXlGpVSkGm7ghoTxeVJiB7SqN+pItwVS7fpz2k30uB0Sluof/NSf6Evij5N2mdDV3xldhTxLh7BmF7TNpwBMYMGN4qHXM8y7wSLE1C0sR+hviXB2zgfgBaldwTFd9YExTUTFVMc90BvaEjU2dPnyMjvHMYqbg/B9Vf8zrwRfBZEdAJgAeDJz7svP2O7jd01/yLYm3zNX2PmOzfZ8Y2YLACAiP6ImX/j592Pn6XtrvkXw74s17wLcO5sZzu7ke0mi53tbGc3sjdpsvi9n3cHfg62u+ZfDPtSXPMbE7PY2c529mbbm+RZ7GxnO3uDbTdZ7GxnO7uR7SaLne1sZzey3WSxs53t7Ea2myx2trOd3cj+f4vTPoEZtkSgAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acda90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 65.15534853935242 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 0.0001, 'kernel_type': 'size'} is: \n",
+      "[[3.20000003e-22 4.80000000e-23 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e-23 1.36000001e-22 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000003e-22 ... 3.20000003e-22\n",
+      "  3.20000003e-22 3.20000003e-22]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000003e-22 ... 1.40592001e-19\n",
+      "  1.40492001e-19 1.42048001e-19]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000003e-22 ... 1.40492001e-19\n",
+      "  1.40860001e-19 1.42090001e-19]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000003e-22 ... 1.42048001e-19\n",
+      "  1.42090001e-19 1.45508001e-19]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.95050430297852 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 0.001, 'kernel_type': 'size'} is: \n",
+      "[[3.20000256e-16 4.80000000e-17 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e-17 1.36000104e-16 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000256e-16 ... 3.20000256e-16\n",
+      "  3.20000256e-16 3.20000256e-16]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000256e-16 ... 1.40592128e-13\n",
+      "  1.40492131e-13 1.42048104e-13]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000256e-16 ... 1.40492131e-13\n",
+      "  1.40860137e-13 1.42090111e-13]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000256e-16 ... 1.42048104e-13\n",
+      "  1.42090111e-13 1.45508131e-13]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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KjNkuCnE+gHgNORe5GHTeUddA20a7XQlpuWvjHFE9GmR9oqND8GIZGkyaBTkCN634J84v4nN1BzNgMgG9OpFDRNJeeA8ynoi6ljlYLmO/AKA/PQd9/BXQ85fhviQf8HoNOjqKz1c/aL0OVQWuHKjtwMsV8N4jufzf/F7SKs3Y3OExMBqBT07j86nef4L+ax/A/ZunIJ3z6RS8WsXFK87rKPgsVuvUBwD0bPcl4GEuFrvIVVGLrDScj+ofl55mCzMO92PPIMXXM2+yLSGpz1m4qvdAXFRyktbECq5wcM3pGIj1Q9TVDRxA3+cqqfZTx2fOjbkPhRnCTZNCc2oC6VhDnzjE97nvUyKS/m61I2tOGLOMu0520sEM1SZzcKJpourNJfLQ+2AuhP4ultG5l7NnyzjLN4HbTtDkcZwMrNZyTeng5Eba02O6kLAHXSwz8y06QtVxqm1bx+1oJPltzMB6DTpfxv5Gx63JQOXVGlR12XPn1QruZAG0yfRgZlkYo1aTw9fLDQxfCjMkMx+GMg2v0Cwi56XsgOIFp5T91zTBPEg2LzmScwJ3I4DEtVjAdaNG4NLHQ3Wq98DM6WeItxvs00tYVbJza8qzaS/uFvbDD9dYzSL2zbPRmFwai3fpvp3u+uMEByafVOWwmwMSdZD7V5lmga4LL7W2pY9Ich/0Kdg+kmoQhWYBe65nsMmfoPE4LoA0rlO/DuaiUbgKNNK8Dy/jaTtgMkm7dt9LNGQ+AxkNgqYTQDXMAc1Cr4+7c9OCjw9AxmdB41oWkcMDObZu0nsYrmONSIT3gI/lXDo5Tc8Sbfp5OgFGI/F5GC2i++AIo3NDgFPXAC3Tc9d5GI1kHijXLHC+e4xjHw3Zy172spPQTdFgdynH9B7/cfqTg397Y7R6o/pyWr2r5LpOUXWwWs0ASOplqa7fF/T5sn5vy2rVn4Hb0+pdt2+X9ak8xsO0etGcu+mclhwgA87qMru27F/ZryFavQ0hymHptq2hPgyM75/w93DKL3Z6Wd9eM2TXKIeaIUTJqbXNNCmviz/S5vEAwtmw6fWduIKwNyNFvaTtdH4AA0UvfvCWD7FOVRW4GUgHvwPC3o1+Zyng5t7OZQCfaIsHJyGABEYqX2ZH4WPAppf/EsJedUpbD78CtGKfgtMzbjJ9L/6D0GZcjPs++jYUCMfNlg/czkP50fse1eFBvAeACNKLc6m+Hvt8g+kazz0IZsh6HU3U2BPnIjDPhk7dZAI6PBAHaexzcPyqQzUSDcnzejcJe3nLjmr+JpLwEnEH2yW8mDnfYFZi3XEw7IDbUSxRbBT1XTg/vBsA8BoxKLgQMmfmLTH+l8lm/kDiRoghyKqKjtpyzhkAX5TO1Jx5ivhm4cq4IFmMi+0vC+6DfbfhwEYf+mYdvVUljsxtms91+mWiZ9x1mw7VGALPnYtKYKM+D79eyxhcs7lRbLTrQU27qXV4FmctkMK2dwBLf3sXi13lxqCsIuYdd+FL1MVt11/GcZFFUhQcNHA7PWYg4BnOIst83EIyU/Jl2L7tAoEv2yn7pqLApwJYpv23zNoUuCQ3KCi2ZZHuwO6dnULDizJFxqv872RrKLVdxnU5OH879MsvV6YNMzdDYD39rgt2b18+Z+/yhdBybcR7tfCLYuO5bKPUDXjP7r2XvezlPuVhahbbEsmuew8rA6XxNq8xvpArfBbbyGi33X+jArgxWeT8ZDNHXoJ78lkMEdVm41B0INv2TP81UUx3WSrMEK1eHsZTNLbdZzHkByInbdt+uYSIjDiYATo7qgPSU02qsuzfjj4LN5tmEGolxrVh8tim+n2cE19G8LOogzMmEhZaLod52yhfeCBFhjIEZ5EAF+WdL1+4Td0e+nlIrd2WlbpxX3khIyiLNxmWoyMVMC+Vj1mGeRvGVDALTPzoCy7M2JsdODi56yKaNI0z4SfieaiyjzSO04qOg6TPQ76W5NNJGaIJ4VqowMyDZfsiBZ3+HBeSAUcz1blPyTuAYNq0HJypfULoV/BP2PvGLOLWvCMuAJW0v66Ki7Zm/aZ2XJgfM8/kEsbG9rcL8ziQPRrfL3VCBn+Hgum4afL3QccQIn1UIcPccNtlPgsuF1tj3tJ0AhgcDADgGowKb/9icVPZ9rHpsYKsVXdUmwq+/d4ug1/LS5+v0JryntvLBibewtyjNbBr0x9dFHyf9ze81BscwSYFHkAA4TgAfd7fMAbVUrQPYIab1HFnsnDvuGsjT1Hf2Lm2hK3jfCCNO1LTA1nauqAuDVxZnYAhGqKRozL3wc2mm6X89N5NC6oc/Do9DzeuJbJk4fIaAbPRNUj+Baoa0HCmgerTo8eAwsgBibK0bQSvRcQqIKnigDxPR6CuAzct3MFczn3+ctCpTuNaUtSDAxQA3HwOeu8x/LPn6byiLEFMVR+NgEq0mQwU1+zuiXiYi8WQGbJzqFXOi4uCrvRVJWqzRTSWqntQ83NeCn3pi2aqfCeKbZjQnUVV6vGYvaihNYsahW5ylHESRIxD5fLckN7Leew3Q5xhsbHjAJEgFYvthiqXIytn05Q9WdfpxFazNjedbDof8WdAdm8bsg24AZjoQjzHqPCC4GTpj2k/IkuteE5o2HH62LXvNK5jJCLm7vS9fNQmIklVJce0v+NazIO2A44OQJ0JE1fBbAgLAFartBjq86kceFSB1i1AS/BRCJ2+Ohl0UkYEp428zKbwjw9BJ2f5ebSWhQFIGue4BgKak6bTdOOzPYJzL3vZyx3LW4/gvFO5jEnrKkdgeQ8V5rzS1SAlnLn2ruqGDFUOu6xuyFC79hrOzZMNua+6IRvN5A7g6HPZ5mzcoW5IdAwO1A3J0JFb6oZYKTk7AAySSG+tG2KzZNXkCuAs4JK6IYEdrUTN0mSSFzm65PlFE8X0/dfX/ytO/fMHjuC8THYxQ+wLOeD4tAg/AEn9VBt+vR40Q7TYS6RVayR12i8W2YNyk0mofG0ccCaFnJfL9IIYm9XHFHVJe49FYwz9narLpQPOJqoB8uLF+9jyeDovBl6ulcDdwTyaG2yTvIwZQo+OwZrwVJghvmkHX1adDzv3WWp/VYmtX7k8O7OWDE47hmiaFGaIOzyIKeRpEsQM4fUaNK7Rn56n8w/moHENH8ZCk0lIJOuFoi9UKI9Jf44iWpImYhbwxQXoqx+BXp6Y9hx43cA9OpbrLzFD3LqVPj+RFHX3w98b9Je5x48kxd5UTaf5DPzxB3C/+2k6FlL6h8wQnk9BL08yc40+3X0J+HJpFpfJrpqFnquyzV+y7dhdaRZDfQA2d/pS7Ln2fMvZ8To1i20guFLTGRrjPWkWl9Y6LdnAQtjzdWkWQ7VOd9Ys1KFs+nAdzWLvs7gLuQrtee/t75D8pWHK27J+vS4pwqqvvd8FpmOQ3avs49su7nZ9fXBmyL0VGboKFj10X/3dhkcvKzJUwokvw4jcGMZeYoKLWP/GuIO6f1WRofsoX2ijJkNALCtWK7hm+cJ4q4HyhVkzBpaehR81qmU0J/YAiOAmk61Fhgb7YzER9tyCD2XjXn0PoN8oMjQIztsm7Dd5Wvdw773sZS93LQ9Os2DFPww5OONJRkswx+1uHzUA5ZUMHJGKR/DLZYI+F/Z8trqv17K7aJpzaMMdHAgE2God43FklvLLVeZ0dEdHAHv0wdnm5nOxRQOHZgYCGo+lb23OlenGdYaz8MuVAJGaVuqSIDgykez7yM0Zdsfq8aNNFu2qEkdjcHi6R8fiFCwAPtw0G2MGxH53s+mmg7MebdQfoXEtDk0dUwCAcdPAaRp3cEJazlQgOF6NAzD9wQHrNTCuhTsUADzDHR6AJmP0L1/FfllHd1ZjpKqAyUQYxJEclf3JKao/8m8DT23tjkoYwx6LgxOrdTQBeJY4OFE5AYtdLOE/fCzHf+dHycFsdn13fAwaVcIkHrAio699Fe2Pf4jRbxUOzsUqzYuaU/UI6P0mB+dnxkF9hTy4xWJnucKsKAv0RM7MMl15INszQ2Zy4IYs2tGPJnOStV3iXihSmLMoBYyqr9dbx10gbNkYQ+lk037acdnMTfab15g8g8T/GeDxystwsRAAVmFaXMrBGdK2AUTma5vanQhoEh+q9kc5TmNfV4j9iZT8AHB6fikHJwoVnJWiTgmGmjaOwy7GAMCuAyk3hs5JGCO9OstNkcrJebow2TkuihQxs2wWL8MmZefV9nWxCAtYWkj54gKjpxPA8FlwQITGTdKGgj3LmG1/rlF+8d1ZLErt4trX++AFH/Ikl9iKHJk5mHRWLhR6rIeE4DyDiOP1FCpsDd1nqI3BuiQ2H6Ho5yYx7rb7+o37wrtE2gsIia7Cre19PWdzaOHzeT0Tw7cQowvFIhYXSfOzWTgjqtP2XRckZrCNNGn1sg2Oix7scv9I1NZ8SWwbIgl2c9Fr1uuEbnUu1vegRkPQyR9BujAVleOU7zODsdtEMt2Q2Gd9cMs1fDYuzjcinYfeR/6MTK7hs3h3FovbLBSZ1z2yhQyft6tDb5uEjycD9Wyr7WDDlaaeyb2Ko5iXsRGaNKxLqT6Fhl59qnVhs063tQHcnsTHUcrejMdcwsMgaRakzGNx13ZxTDygCV1LyGWRBiIafh/tMVvXw7n0XhCBXdGvy2p/6LhM26zHzUJwF/VR9g7OvexlLzvJw9cstu32VySY2VIAQHC69SbhqiggbO+bFxnyAWWYhyZpPM4K7ugxC76JfWg70HQCAtC357E/3LQpwc1qPFUFN0pgom1FhrD01ygyFByKFmCkO3YVslzD2NzhAfz5BagyDk72Ug7Qc64xBOYsGtcbDk44F9XvjVIApsiQ1PLwqTjReCz+A+bcwXl4KGhIA34j9lKMuO2AegTW7FBHoNkMNBmL8xMAVeKAjkWGbNJZJWUPIoIz9KU/7YH3HsUiP3F8jmKRITKlDWIpgFFInOt60HIFfj84OBfLaC5ZfYIO5kLnf3Ye+Tfc0SH6j9+Da9tUDmEylsQ1Hb+ZV/IevFrliWTr3Qsj32qxIKIfADiD6OwdM3+biN4D8HcAfAPADwD8DDO/vE07mw0PLBCDpCn98LkwDqaQ2UnjMWAgxcPNplobEbbddgX0WuHjdXDAIamYoxGgVbW6Lr5w3PfpASr0OMCcE9zbZrlWeT/1wwp1MKIoHNpz7G9Wp6NPH3t0sM6mMQtT8gicRAkm4+SlPz6UrFPPcjxOUCMLQllyMfQtW0gB+YjDghSzaCcTYO0i2S/NZ2Ee+zSG+Uxg710Hquu4iPGjw/SBWZ9F5cAXC9B0CrJw6elExnuqEPtaoNBdn+ptqNTjGIUBECHTdLFE+5UjjDU1nghcSwEh/15YLC5W0VTwB/KceSIVydyqhTut0HwokZ7xZzV4Fd5jNS+IhJhXM2TV0Xx8iIuvz3H8xSzOrT+cw525mGmr9Ul4WoN6Bp26WKMEAPD89VZR/xPM/C1m/nb4/ecAfI+Zvwnge+H3hynktvsTdpWB66PtP4QA3IYKdLldfF9CuivTju0N2eeOLrez9Zzrypb72lqhsU+vW8p52Pazw/BXR0iqhD7rbb6P8rqy/fL/O5L7MEO+A+Cnw8+/BOAfAfgrd9pCGc4sjwEJG7EN1delUCJ7F0lXy4hEVgk8YC64RYoC+F5U36IdW2lcFxy/XgvZCRBp2eUPHGuHxrZWZncH8rKEbZdfr2Nf+qyal29aaa/v4Zc6bvXQB01smc+bPz3L+gVHEia1VPdPn0t/LMuUDU/anIiw8PnFImkcxiEZTSk1j1brPCKjbfg+JXat1inKURvtJCSyCVFN6gP3oW+2enjv4U/PQE2T5rjthC17IHQKtwItRqmfGunoWox/52lKRiMC6hH8ap3MDyUhYg/3MmhHqrkwg9cNJuF+XkPFLuWBEBH8Fy+E/Ga5iserp1/g6DcZ/Oo0PZuz81j6IHJ5IGmSvmlAlqjHmlpXyG0XCwbwD0higP8zM/8CgI+YWVEinwH46JZtbErGhXkzn0XKmUj2PpuEHvtxlvfNyG+09kMB19VyfWRp34LdqwlBqa1WVFzPqWReXQP9OiT/+M3yhWbXt36XsjQgVS73TZTkN0URJ5pMUj3W8NJCzR699mAuH6FzqXxhGEcWui3MEC4Ic6jx0kYgAAAgAElEQVRy4CXH/sh5QlAT+zmdyDl9n67TkoVKUqP2+uEBcCHZvxbHQJ6lHmg9TmNzUt8kM02CeUm64JmdWUFZQA7KwmoN//go80uQ9vPoUA4o7oE5grK4HsmxrgctVvBPgsny8gRaazWLPs3noFElfQtDoMNDNB8dY2zLF07G4OUKpJEfNVfrEdD1wGp04/KFt10sfoqZf0REXwHwD4no/7V/ZGYm+7UYIaLvAvguAEwxv2U39rKXvdy33GqxYOYfhf+fEtGvAPhjAD4noo+Z+VMi+hjA0y3X/gKAXwAkRf16DXvjwNoCoroOgpNcIky9sm3hmYzIQebA4VCYL+oktLyehelhve28XAkeQM9tGgFv9Ukdl7E5cO8HYdW+aaMDE0DqJ/sI805oTx+vye5hzQU1IwKhbIzeBKi3mAcGyRqAYkRa8HnTrNKxERH8ylSSV1RiUX3e+2VMloqaiY0u2ESql31KwVaNp+3MdQVaVU1FnTNFP8YTzFwqZFz7GZGcHvTsBfgs8WRgXMt41bzhZH7RRfjkQvQNIW3cBc3O65ya6BN5D396KtqgVpUH4F++wpgomMGhjYuFoDiNVgIgIma560AL89l3uwN3brxYENEBAMfMZ+HnPwXgvwbwqwB+FsDPh///7k3b2N54wa1gbMIoluh2wG+huRJaLV1zFyhQsvdtl3g09TutKjEtTIjSXyzgDuaJlCS05Y6OhHDF2Oeq9gKAPzuP6iAvV3DvPQH6Hv2zL+R6LUs3rnLymuUKNJ3AEaUFzoQZbTSET06BWl5cF6IwKRdDFh3tg5LuVE8eg9fGDAGAcS1RBx3Le49AL09lvpRIxXvwei2hySrZ48LZQDIeDZNqRKiqYigzj4aso7+ADg/A5xfwyxVcUOtpOg2+jF6iMRoJeHIMd3Yh9r7yTXY9iFnmbTaFfy6BOfIe7vEj8OEc9Hufxzmh2UzuO6pyIp0QDWElJwrj7r94geYPfx2T3/kiPGQCT8dwpxcx34MW67iB+WO5zk9GYAJc51GdLLH8muSRTH/zh7IoVRWoTSUO3KNjiYY8e57m8esf49W/+wEe/cazOAc8n8CdLmT8nHwWPK1BnYc7vcijIb9V1Na9RG6jWXwE4FeCXTUC8DeZ+e8R0T8F8MtE9BcB/C6An7lFGzcTZuAqR7BF/W1xmG7Ar6+D8NMd3KLoyj5ah99GjkSqWSk1Osxu740P4x4l7myaG2JgxeKETPki8Ib4xp6n47xhWnTRofS/Qp9LGLtnAB6kSkTsH0fIc3Yvb45Vu9vvVqgcm7YzlNBo8z4qAvVyfjTWY/5Kn96dnre+ztQHhKrCyOPciK+G9TW5A5Krt5cpS1m4r1NFXStRX8bLMHSPktsQQXuoqqS+Azmr0lViWbGyvvqN45Z30hmHoeWBtGAqALv347qyrd9ITsg4hqGksYLBHNjiLCY3zPlxmbh8gYy1Owa4L7JErbaLIDSlL5SPUvNRNNfimv3R5upxzmCl2Bhbw2WgqBT3vWhUfR/f3TRWl0w3RzkbVjynghvXaUGWhqLpm+XmAIn7wrz7/8T/bztXUd/Dvfeyl73sJA8T7j3osxhisLoE7l3sfjSeZeq93nODb3ID7t3kYUGFRM/nG7s/jUYphLlax1AgNw3c4YGYHsFOpoN5QnB2XeZjUdj4VXBvXi6vAfeWnat6dGzQqCkMDFNekQ4Pwefn4vNQBCezOBPVdALEyRZCrxlhb0SuTpL9XcC9rR+GV2twl0iNN0KnOr/zudzPlC9Ujkt0nTgVbeW42RRU1/DKZ1FJ1a4I97YFi+pa5lyfT3ge/ek53De/ATwLIGVHct5iCTo2oVNNeJua0CkQnJ5L9D/2vlz+w8/EjCnAZ+7wQAiCT07jPFYffoDux7+C0e8+Te/4ZCycFfo9qDY4kkJLG3wWz74MfBbK+2DZs/UFAa6OhhjPODna+NgBJE+yfXDKq2BwFVpyLrt/SaIKBJZq68k3amYA22TYiyoUsSFK15G8dEPErtwUfBy+j9GCWInL0sKFa6z4i4IdW8lukcwQfvEykcMYfo44Z8bBGe9r52PlAecioziAVKSpiPLwhXJycAKqhWdFRFk0RCNKqOssGuLX4eNxbTJVuQMWS2DUJlNvvc5BSta8adpE/Kv91Dn+9JlEkbRP47G0WbxTlqWdxnUkNfJtB6fzGBezhGtBVUXQl6XR8y9fofJe3h2d67PzlHofaqnG4WiukgFlXcecfbiLxQAr9HX8L9ZPEHdYz2nBUdSfCeNFrgtTX4K7Lq91qhLIRiz/gCZkAfLgErDLA+MqvfxAjiDs+7TT9D2YKSsHaLUs6/jkFvEF19J/ZYKcLTEAhKiE2vKqWSgiUn8PZQJj2jcg/5c+CuPMU9BbPJcIblwnTadKnv+NUgBtB3Cfax/qQDQp6jSdyCKrTuFwPxqP44djEac0HmdOTWVAY43iFAWGaTTaIK/xaw86mMNZR2stlcM06hNzd9gLMAwQgNUszBE1sXoZrwXBSr7NnPA0mWwgOGk2A44PZSHTEwP7Vnxf9PuonKB5DesaANDp6wNlvRkZjF5cF6pR7MoFk9SlrM1ePth4bemRt/czQuizc2PdUYQPzJToi6ZVgUOQ9odrim6QsWo/AzZETlKNqx/s+5AzkoFcNb5YJKcam/O1/wORmowsBjmmIpuLwmGZn6OLp3n+tv8XfUQ/Wp4N+9FHxKnBbUQHp8HPiHZaoFH79PwynM3JaeaM1I9yIyoEJJi4MZO56+D0uSs2wzkTDekjoU2mWSwWcF8ELdZC6Asei3g8wOgzfI+NCl4hb+9iYVS3y/5uk2Y2PvhLxNZ9gBY6ZuOzaI0/ILJK6S56tWahXu7MI61eehdAYBbCPZI6mhp9cWGXhAsLRqTba0Ejd3+axdh49u3uXFVpB5/NBAuBvsh+7VNI1V6v8+qNpgL5cK+jWcQ8hzBX0cdkNJ648xufBdUY5tVU349ec0PNwh0fZdVdI8eoYl66Lu38sRq6gaOv10mzCECxLLQe6oOUmoWbTYH3H4O+SPyfsQj0AK0e9f2tNIt9NGQve9nLTvL24ixUSjDL0N/1b87gAHYd17Y03pCevsldecv7bmlL7p12+ng8Euz2+fGrcCQ3lV0KFiFpLEPmWlmJK2pn5bnXHcNGxGsLHkTxF6EPtp8bVcJsla8bzmmWSGjfm221Z2GiUUVUymoTEcW6Dd/jqqQRxyYueT/1u7ghzuLtNUMukw1AVX+9jxNJVYzOS5vKixBitE7KcA533aYZMlD4KFLKW7nEwSlZpz5GUdQpxyxqOY1Mlms9Any1gxnSXdsMcbPZRop65siEONu4aSQDUmuNBhSqpedX4h9CDxpNUjjUhA13NkO8lAnUeZQGApy5dHBav4maRt7n5mKImtBkbMoDVFeaIbxhhqxRffxj8K+k1qmmqPNqveHgROHg1DFw28YMVf/8ZTA7c46OITOkOj4EPnwfePEqLTLWwWlS1FE5yX3ZMENeE1PWa5FtO3k8bh6o3RmGcBZWS4k7jz78On85fL9Blcd9H1fziE8ILFSlBqI1R+xxN6K0SAUWKgDgpoULEQdvqOf8ei2+ia6NHzt8Ly/1uI6pymD1AYyzlHGPlXyETWMce9aRSIkpK+JN0n0jo3dIRY8fynwmi5pLSEmEj4ybNi1Idj7G4w3aeZpOkh2si3WoT6Ip3zSdgGkN35hzwkIcMR16fD4HfAgLGrYumo4jlb43YcNqOglaGsex02wKUkzG2vg3Khc+9EXsF4gk7+RwBrJI30qcoXQYcjBWpsh2WEC4csCoAq0aEAA+CP6Np18MOsfd0ZH0jznNzWyG9oMjjF6dRYeCzJczxNDhD+Na3rfzBWgeFjEi4OJdWiyGxC4gV+Aptt6i4J+IFc+zSEtxT5a8g4w+Y6jWCJAyTMvaGWX7eo8iCqHU7zHjMsvLCJwGJZ2/rUsCZJTwEcAV1eM+XQNETYOVfAbF/U1Ugc/O05itF15JawaeRZZxq2IjFfY52uNNAmhFL36fSgGwS3Pqzs5yHIv2L9TbiPkk2qeQGRr71ZHU4GDlwLBkOU7O1We4DBuRZ9DL04izACSSgTbVDWHrcGyTZic4GsHe6KLph+YJkErsbZPVa+GLBepPX2ZtS+Zsk1HyAQBWVciGXeWb6jVMr72Dcy972ctO8jA1i7uQoQI9RfGgna8fcBxdWQSIcw2F+4FzbTsb7dGmM4tzgmAtZGQLGsXr1XnKua+He79pUrlwX4t3sIWA7Ji3iJ2PUjMDAK3jwUWtkbz6W3E9+3gdgEg3uNk4D2qAMcwb+8BJayEyPBQm61NxFjDh2dUq0xqjv0NNE0VUal/0HOUradtICzD03gAIEHiDvUB4DsvVhr+Muy71TdvtexlD32fQmOvUbtlrFteVIQ98yBl5K6QsXuRok3S4LKp0GQDtPqXslym0k8nr7J9C/KsqEQFvIxc2xYFeS78ozc/GHO0iiv8I11/3Hg9TsyidlpckjG0vBaB1Q5LX3ZLN8tpEWAoHacbBqVDmwqnnQp2MLHfFJnotfaohohycQEyT1lokqRRAilqQpoEXIDRblwRArE0iTlhTdiCmdlPGJQqIg0wdaDF6UblUzwMQz/3JqexUdXKoKmFu5nQu5gMwoCWbgFc6ONHm53AqW0CjUUoQM9EfIQwqcls8S3RiuQKNa6nzof2dTgQYdpKcuzL+Tkh4VAvQOaiqWFeUJhMJb55fAB+8B/fyxAy2EqDVsfBq8rpJC6EmcTknpQDWktyFx3KuWy4Hw6Q0n4nT+2KRUgKODuG/+mFk2ZL7T8UvUSSS0WgkSXfs87ohi3fdwTlE2FsuCleVGtSXLHrCxzGjE4B4+2PEJI+hU+XSR9+08iAKXoeU1WqhxqauR9tmtTzicWVi0lokGr7V/gbaOK1LErunCMNZehFIw7q9qblhQn/cm35qyHY+k7odQKrdUY9SPQ8AeHQUa4vA8jCsHaj3g9OeEQnrz7OpyfoN/Qv1SXSJpflMFgZTZ0Vre0QS3iD85HiYJMYsTmQS5Wg+k8XhIpHw0mwGHoVnY51/o1EiVdZ5IgJdLNB99Ah1dPiGxclRrBvizlcS/QBS3ZC6gh9XqC4auNMFmo+EKat+9lwKP5fzdzAHT8agtk11RY4Psfj9Bzj6InHY8vGBoDJDaFYZw/xkDFQExwx/ZJiyvnjXF4u95FKowln27a5q8hCJzD2L2O3GxHhdKv02uaT9G6n9dylZ7ZFbmGW3GMfeZ7GXvexlJ3mYmsVQnLiMF28rPqR/jmpj8G4vlyFacUkM2vdgVBLLNlEN4ZYoeCEUaWePmyJAlombu1bIdW3/QuEibpH+N333WGW8neQoK2IUx+g94DnG4i3qkz3nPBOAkKuUOIumTcV/ALjPniXiX8va3fvBbNhsPoBUQrEz0Ysq+Elc7kPxJtNTuTZotU5Zry7p7K5tNtjKLc6i9C3xySn4vIrXOCxC7ZMemEwSJ4n34KoCLhILPBm28/q3Pk0oUEB2/lYKPAFIhY+AZEqRQxVwFr5pMV7I2PqL5XBU6fnLRMijmsXnX+Co7eBfpOqgdH4Bb3AWZP1s8xn47DwvMtRuAui2ycNcLHZxcJIDoCFC69/wYmtqeJGTI4jQ576BAQenOgdt0Z7ohMsYvNxmKLaqUqGczsK9XXIUrlbp3OCMZDb99Qh+kyrZ9cQxM1SL8gJInA1Nk+6voKwIwx7F4+ylH+pcTKzm+XHMponYxTo4oSnemwu0zkf8GcHppqCuus4riakztHJAkxzJ8boBB2dkGrcSfAjg4OQt2a+0fqj+PhmLf+TQ2PXKyEWUoOXjsaAimYUh3H50LhQ91v64aquDk9Yt4Nbg4EegVyeDGxxNpzIXWiUOACYT9E+O4MxCRdOp/H3AwcnHB+JjmxsH56t3ns9iBwTnNnyC/lgiOJU34TIWauYQ3chj/4nsJd3fD9T1kJ0+QcctliKjcIv9uQzBacoZegYF3EW2K3kGmkY0gsDKJQhOjgDOsnydIDgHtDRbUvDsPEZ6sjolqkkNaRZmPmI+DhtNjjlhF0zpPtZxmHnOqAhMWNV7v4ngBIC1pPlbbow4VlOHA6EkY9RGjGaBUM8jq+Oi53/xImpaCGPg3sdq6LGyGwAOGoSGZH3AWVgtZGix4IsLcOC+iAt808L9HjIIO63WGc4itksE1/fwFxfRmR37tqM8zMViV81C64aU7nlmUPCiq1rqxnWWBOVXV4RODZemJBjlmoWbTjYgzm5cp3ojS8R7eFPXow+hUzeuhYWpyA3hthHeBRuK1BKM5v6AkKPEMoi6o2ltU9VclJsz1Hp1B4fxg7N0ejY3xD15DP/ylYQUi/KFwscxEDoN8wGkcZNV9QOuITKaR7V9LOxRTRMp8bLcEKtZPDqOdUgyGY3AiwVoPEZvzD13MAPqcUoCG49lZw7V2VM926CduApQ+rzZFCAndUQ+/grcF69SPyoHXq1Ajx/JgUtyQ9yqEWDV+1JjxJmaKVbo6FDes7PzCMxyhwdov/ERRt834fnAWTqUG8KTseSWmNoyWO6+BOwdnHvZy152koepWexihgw5PjOobE4zp+pfpEsbuqcmknUGEu172R3D3+L9VgNOz9KpaZyNVo1N/Un0eZljrtO+bkKjyajhrHRsfR81iiz9nH1SSX1yIm6YIYUK71++EvXdswCYbHvbzBBLzqsai9G8yJGYHJQ7OLWque2rLR3IlmOj74fNkMA2VpZ89BdLwK3S3C59ojdcLnNHryZ+aUJeUPV906L69OmwGZJxqIZ+agW20gwJcO+h9wYIzljnsoRD3/cY/baUNoxtL0bDcG9lqm+aaAoBSATBO8jDXCyuI9uQnXd5f/v/6xQLBAuAscFzytrUsYK8gXrf9zztIja1Wh3PjsQfczNemmu3L9gPZHR98AbWreQ1wWQit/vHdld9vLHUo8zXdV15dxeLq17+Ap0pjEUuizpcdm2CX6uTbYDPwiRfaRs2AmLvEY+36Vz2SNEc29/4kZsoT+yX1Yx82FWxiVgNDE0bgK7yenPfGB0ZjQJ5T3G+zsfQlOl8hJ9jW4b5HEihPjYfJetYI9tVSKiyHzGCL2RDwwzOygFYvkK4o4/AUeSqJFMNjl3os32nqiqFJ6fTTMOCcyAYCL9NUVcfjz6rgFbV+it2njIJ0SJLykyjkfBvWAen+qyK0CmqSpCsIQKU+rr7JvfuLhZX8VzcJuuUNzktNk55DVmnG+0XOzB7lnAwYKIOsrhF7o4yKvSas05jZCQsBrHyuj33dWWdKv+H5xxLAwg5sWFbZyARHL2urFNTbgHA9bNO2WdQeuhYd5SHuVjsFA0Jv2+pon7jRLKgVVj6PRqPU+gzvMmvN5GM4k6VRUPW68hIHXcTzXkJdnwsuvOGEskUFBaPlWzjIdKkjGTx2H0kkk0mMdJC81m07ZlNiQOtoBZwFtT3ryeR7PBAEsnOztOCc81EMp5NQK9OE/6DGVjunhuyj4bsZS972UnefnZvlaApDJHjbj1fRVfiySSRwd6UHdtVm2qiYduOO/VQ1eu7lKDlbEgBVLKV1wBIPzMuUvlZa5HeW3X2ISnGEJmuDWM1Wx/LVX27rZM2EDFrNftBekH77MnBHczhz8+H2x1iph9yhFvipG39D8z1FqvTn55uas5bqRoIbjaDX60zR/ivt3//HWT3tqS51zg/Y68qEHw364fPH64es228Ltk2lowa3m2eO8SR2Q1zP967lH3d4g/amcHsln1Jfdj03WRh4ciSdc+bgm0b4TndcEGMqNhr+CmsPJzFQqX0Q+jPdse359jcELMCu0AAoklE1eFBxmfRn51FB1bKaZDf3aSOtrq/WMjuEjgRtI3q8aNEfuvS7o3ZVOLzp2dRC/GLBaonguDrPn8q1z86hr9YBt9FY5CfS7jZTBCVWijYVBy36Dw+OQVqOc8dBKp5TcaqHGIJAgA+8GiMfuyj5GwLCUk0GoEmY7DmP3zwHvDFC8EjqA3ODF43ghodoPtzR0epzIFyYIzriLiM9PSTiVQ7U7Tn4QH4/AJ+uUL15Ikcm89EywhIy/jxfPAEdBLyJOxOXTnwxQI0ncJ/8Ty9A08eA7Mp/GdPY79oPpPoxbjO8QijEWg+BZ+exz4AQP/0C/if+hbGP0z35XoEOl/AfyX0dxGSv5jhj8J7Nx6BK0K1bOFOl2i+Ls9//M9/YPxfaWFyH7wHnoyBZy+iX8b9oZ/A2U9+gON/9lls2x/M4M4XCeatvBbTGtQz6HwBPkz8F/Rb/xi7ysNbLIDhHbU8dlXWaRl90BX7ElU3RkwMkxOCh3koD4TV0678kl0HWq/BWthGY96e4wcaQUkFe/YQu3dkvY4gpzYR1IQxSnJXvwHh1p+pyDrkdZOAPwrq0j9qOxfLNL5Gk9ZCdfkstyaZRFkOhjov2W/WW9G503PW6xR90XNXq8H26HwRnHsmpKp/b/IogJQtEBr+OMdNcES2Hdj3eanDMA/xmN6fPUYvl1J2UM9tpW6IO13EttU80Grprh7JB920oMUK9YuwMIWcIJh+AQAvVqCuh9dcHwBuscL06VqcrgoBZxZnblicouM4ZCDzYpUTBPW7a9p7B+de9rKXneRhahZWbuqDKDUBBbvQ1ffbhFkPXGPAM7Et71NxIcudEfAOmS2qPhrDMB3Fs7Bgb4zBp3BquK9aYIP290DfWTMpTdu6q8adbt3EbFi0Zp8a8nlY01DHEG3nlOWb1VQxGoPN1I33bymFTg0LN62bQC1QaBYBGk9dztiNtgO7Kh3rOqBxsTBxpvWwMHzHY03iYK0Wq6IyuVyrXB/ctogV4PSkNlAg9JIpSwuTFey9hFYNJgNtI9pOZ6rKr1YYna7k/oYvFE0L1vFb7hBmMfEsEOudqKK+q1zFtXldsZRlA8jMG4mNWuj9HZlCMFsUvK2s0vcILS+APxmdnOl7KuVoPsqYlaso1XCdLhgRMn1H/Q/5FRvru6MYPQB6eYROUK8JrGTOvaVweQ+3A3N2TCGnnH8imA9Z+cJtNHrKKq/cLfa+23BHt5CHuVjcxQIR4c9KslLJbl08ZKkVmv+csXt3wVlYujo0t6Agv4lcBG2b1eNEKE2HgNyNRLtEG1yakfMhhhUTeMrWsYx1P9kUXO7jYEBuAGY+GiVSHfVRKDO0AW7xep0gxHp+A7Db4q2vKpASx5i6phtALU391+P1aOOcOFdtKDOo7c2maYdVB58ncU42rZyrMGjv5T5KuqN9HNdA77IaqrFf9TjNiTJeLQl8MIU7T2A41AGQF0oS0ipBxVmJZ+oRmAjUdiDP6IPj0z11onHpogHItbWUpqTVOj336QTt4ynGz8fp3JCGHvuvc1aPQF5Qt2RIna/D5/kwF4shKQlnt7F+65/tyo7Nl/XSdhwl5GLTys8xE9IgQpmzojlUVTEHgBVdCVH9qa7zlT8WtK2A3hQwBqC1RzN2b0D6Ydi2abUOfBY+lQLQKIPmehQMXdq/2BYgL1pdJ7q+6QS4GIHIS7/1+DZnGbm80rjO8WgUcypsNCRbridCzc9tF6+jySQ6Xm3pA56HHA1T64NC/guHyA1fmDyKugZPx1kZAppOYzQkM6vqsTBMKcJW6fRPz9E9nmJ8kuadxzWo6yKTN8LiPhgNWXVwzOiO5frxaCTPiwhsNAuaT+W+FxfJjJtPsfxgjPEP07vjD6fiRN0WDWFOdVUBKZi8ozzcxUJVXk24kl/CD/7qaEhBlBNtRVtQt3J5YhQ52YJtHcxt0ZBQuVu6SqlNG30w5DIcqpDHXVe1AQ7JXrrLxehCqgEa294SDQH7LK1b/mb6bvvdtob0xUezhGUg0oV1I8ldnDz3sc4pkMopNI289JYRS8dNTuzna0RD4keiqebetA2AlmvxO4xGyQzxvRQ49vJ84wLddeCul9IFceydLJp9L/4B4/8hALxIi22kP2SP6rxJeSDBfOA2+SFoFaIsnmNEgaZ1shzaDqPzRJkQSYBUS6pcioa0XRYNmbwKPKt67mIt4w3XU6/z4EFdL/ex2vM+GrKXvezlruVBahbiXMt3WjnWFud0yRFXiNLYKWmJOzoUKjRNstG0X5OqrI49N5tGejR6/gL06Bj0/AWAZGu7R8fgi4VgKYJK6A4PwMcCjqKnz0EHAo7hk1PgvUDBphRvh4fgFy/FvrxYpH41bQIPaZVu3YWPDoFHR2mMnz2Tfp6dCwAJQlwDIMLm6Uj6E3fKD95LhXhCAhRNJ+DpJBK0rP6tDzH97WdAPwEfGYDPxVLIfQrfBHkPenSciF/CHPBkDPci9Ceo9Tyfwi1WgpcAgPcew714BX9yJvcA4I8OxNZfN+BZUv8XP/4Y00/PJUJSBS2oZ/DIoXpxDn80EzU+jB8fPkH7eIbRaSjsNJuBHx3KuCdjuJNEhMvTMfyjOarPpb/8KDzH5QrPvnWMD4zt389HqJ9NcPETAWj1qgWPCGBg9b6Ybd2U0I8JkzOP2eczPP8jMv6Pnx2CL5bhXTP8or//K+gPxxj/FoFDf9c/8RX86D8c4/cvnoifAsD6vQmmz1bwtQMY8BN5Bt1BBeqBybMF1h+mZ+af774EPMjFIgsDWvYlQwYToa1bIMyR2ShcZ7P5ojgnH7veN+SV+OUqsltz3wf6/Lwdf3Iq6cCqVkKIVeN1oSSf/MGDXgYKfjUzzs+Fa0Fp7xX96EgATparUe9zcpqYqsMYqWnAXRcXiYz0lj1QlCDAFy/ifTXblddr4GIUOSamv/1MwqerdXRacteJeWAqrSkClJnzOTo9F7X85DSVFND/z0eiauui23VSRsCUS6DVOoaaad2ICQdgvm6BxVIcjGERoaYFAomta02ZhL4HPX+FUdMmwNpqDVouYzarN1BuqkdwJ+expAIFFCU3DT745+eoPnkW3xk3mwAn5zhQf82csRMAACAASURBVIyCsnqP8adhUZzWKepxscKH67CAnl9EU0qBejQawf2bp6jGNfyrk9jfye88w1f/949Qf5b4P6vnFWixQqUO0uCzGNfiH+KLJebPk8/Crb5ETFlcIgaB+BB2vZ6c2HxCQ5d8BhsfI+92TwCCqQjYAuVooMr4RAzHQUzgMtwK3Pto80dcBcJLbmnazBxs6x2bKuDx3Co/nvrNyZ+jWIOqApFHDPn0gRTW0tj5PmFF4kIabGm9p2W77nH9sKXFW/QBm2JDgj6ha3URi30K85n6G3xEa0NvqO+MZ6DM3L4kn4KaLi5YxCz39H1iPrd+AT2vDZG3rgOtW1AbztFaKr3x0RhfSya9R7XuM9Qn6fyYtmRoZp5uGEJ9kIvFRjjT6//GwXlVNGSj1mkNtJR4H0JtEG47RFo6pajbJRoSa52mD5vGY4k2KKW7tuW9mBney66LEJWIIbQmOebaTtiOKrcJqNkSDSETDSETDYnXACkaMp0kCHcbogqjURat4aO5hOFsDYreg10jlPZqfqAN+AZpP76i2kdH14uGZLVO5QOl6SR+jP54LnDnepQiLl0vbTgnJtk65dPQdCpjUe3KkRxz14uGNB/MMVVoN5HwRjCjfyS1QNxiHR2cGg3pp1KHhHqP0ahC86Hs9rNPpwA1EqVQ87mqhqMhR3NcfDxB/XSenL2zMRyRREGMZsGTGtT24qg1uSHXiYbsHZx72ctedpIHqVkMpdhucA3sfjPRGDxHlVmPJ7Zqve/urEJyjyIhKIM+FynjPjgG7TmFuRHF+2vtCNfucwEtj3+yNHNdF0wP01/22biYWTSQAJXemIfrzqfto/atM7u/+ry73gDLglnnpehPHIOGG3ufYNVbDbnLhcrCVOHeZNX+4tUkBhgM6ryMwYaB2YuZFu+7BYDoGdQXc8Ccv1/e9OGW8iAXCytbc/OvzDpNuf3kfOJzuIxgRReOXXAWmmVpSXHbTlRMILP3ubflBJDODedleSR6LfP9ZZ12pm0iQWZaHMXFMtYEZWeqsTVtXCDi/dRn0Rj8RtPKnAyQ7VyKs9AxyI3DPKS23PlCnJRERVlGn7JOrS9jvQbZ6mfeizmmWacWZ+HF8zSEs6hfLLNKY+Q9eLW6POvUmqCLFcYvg2kWuD+JTG5KVQFDOIuLJeZPG8GX6ILX9cByJWa2QXBS28mYb5F1+vYuFoYZC0CR1DMwQPapapdlwtqyotoXgUNSETiVEaRRnaDWNneDOdT8SASsWuMju7/WIQmlBbWd7EO05L02VKtjUF9H4J6I9w7JR+U82LokAFI/2SfPfiRR8fGa7B4DfBRc0N2Tkswyx7J76tBVKDqAFCnhPtbjAJA5QOPiVQCudBPwfhmT1iJfp15vIk1y31YW/dK5rTvtcpmQsc5JtKFpM0d2dIAukc0vBxBZ1k/Ic3I/epr4OgFpo23jgp+S1zzoPHxyxmfmmwZVmCuvZRLNIiYbS5PqfoTj/uUrjL/P8KdnWbiabZ1ew/LNvSSiUYjoAPgS1A3ZoGILP8cEpt3zRrTQsZojNrYt8GAfcy9QSQV1WRisGTG8eGn+RUbDr5qGLbtHI1NOMJDSBhQfN02O5kMVkKVD1cpLlqnQT9vfgWvyX/O/R9p9GKetLbhsxxEcspGAx2ZiMqe5dZIAZRe82G/KzcmynELetyrL4bDlFqMTtevgF4tI5R/zIjSztR6BukCcvFwiq7GSpQ+EerIxcmLUe6v2u4D8bYv3MJwTzSNyycntkrPa5r/YBcAvFoi1bK1504fi1kNZxKZfjM2FWE7Z3TzZOzj3spe97CQPU7MY5Jjka62S6XoG0IuGYfkfA2OSXYnpuunqaobY66Iz1QCwwElzUDVX4+Iln0XJUXkfUu7s+nNQ/5M6nBjDovbhjW8hqMPRt4K0I16Zwj0k6gTULa7vM/+Irb6eOZcNToVK343ia24jbZeNX1nEyPYByI5xMDfQdmLSBSdl9NVYZrBt77UPvramyc7RbOVMrpFduk0e5mIxJLfgSBgs+zf09xuUjsvuba8v7hUTrlQue7j3yWcBZEjY7HDJbcGc+Sc2Fusis3fwPrcVo8LHexsuCA7tb5vf6Je6VR+uGI/toybj2XZdIuuJc2O4Ny4VcsNzoMfuYJFQuXKxIKJfBPAfA3jKzD8Zjr0H4O8A+AaAHwD4GWZ+STK6/w7AnwWwAPCfM/P/faOexWzGK1Z9E2rcQFzuch2MdgJE/wS3wYtvQ7JlzdBLb795bvR9DJ3PAanZh+hCARqLNmmpqdy1bOMyJZfvnhpipbRrClLTRls8tJhRdkvLZHWTvtkqZJYCQJ2sljdU+6XrX+Ec5aq6FJ25k6gvCqL1kM6NunPKMDmSJsbqV1CNJ3J8Gqf2Nic9MyggZzeP+43I1G1lF83irwP4HwD8DXPs5wB8j5l/noh+Lvz+VwD8GQDfDP/+OIC/Fv6/W7HcFRGpWbx82yqV6Z81fyEsMG46EfVNoy+aq1CiRZkkUqIVydZruMkkeuq1LTebbhLKmpoPfrFIfVit4Q4PxDMeWLb1nhFFGslrGtBIKmfZHA4AWU0JIOSGVA6+aeGUxVujPaHSmYbw/EoT6o7SC6vzpqQ96kB8dCy5HswJGQpxoHHTDJqDNJulimbax9k05YYo6nNch/T7Ps6jX64kGhCS6WgyTnBowz9CRyYJSzWL3ot2t14D9TjyWZD3UuXLMH7TeB4rkkXnst47OE1Zc0OUBf7kFPyNr8J9/iKdW9fg5TImvmHdxPcwJr4pYW/bgRYr9B9K0pn7nU8i9aJ9o+n4GDSq4E/PYiSm+vADNN/4EOPfSuzemE7Ai2Uk/4nvTT0Cul5Cy1OD8v3sDhPJmPkfE9E3isPfAfDT4edfAvCPIIvFdwD8DZa35deJ6DERfczMn+7co10kq4GxZeW8Cgdfrsbqn9hoivOf1ca1Gk2MkJjrum6zDXue5+xlLOtPqL0aNSvDs8G9FzCR5fA018R7GFBZqXVplGHjmvU6b9MF3IAdy/lFyKMxO3jItYBPUQ+2s9ka/g0Tbk35D8m+t5gOzUEBJ2yL5mFsRCKAWISYDS8I68JiMmIlOa/JfV0hBB4T6Gx43XWisURYf9L43IszeIOz4K6TfpMs/DZErhoEjap4H143qMLvXvM8zJwTkSxSVZUtpHyxQP35af7utG3i4PRsSJRczI/JwqWvgc/iI7MAfAbgo/Dz1wD80Jz3STi2l73s5YHLrR2czMxE1zDmgxDRdwF8FwCmmF9xdnnxkBlSrHtXmCGWg5OcJJBJ3NuYJ45CbF2bCmaI5eAMpkvphY9clgbBSaNRhlXQJC5Rsadhl9HCuzWwEgdVrOCt7RXUf7F/9v4Q8BRVwtUZuS0tO1ePDdAbTSZp51EEZ1XlHJzHh5Lw1vcJz6C7puHv0KgHUyjYrG2MDRXfkmN/4t/M7knTiZxjMCgYh6S2vs85QA8PgItlKmKsY2CWvo1r8HnALjCDplMpzKR0BSOSZL9ghljTNmE3cjMEqzX8+8cRCUuUkgy1MLJFcKoZwrUkkqHrxQx5PxRGPjnLqqDLQSd9HVXSNy0xczBH89VHGBsEJ8Y1sFxtcnCOKoGFr0aZGYLz+08k+5yIPgaA8P/TcPxHAH6fOe/r4diGMPMvMPO3mfnbNSZDp7wWsdGK0vtsPdPx33Xuvc2bfVl0wLYTwEtvjWR9G+iXZe/O2KnveAzbokrKvUnFv6yPLo8Q3EXfwliz8V6H3Vt/V7ZywyG6a/tbx1u2dwu5qWbxqwB+FsDPh///rjn+l4nob0Mcmye39lds8znocTsHtkCsq5LGEbdeitdGQprIkO1yH4Pv4Zv0M4AI/abKpZ2lCWQvEa0Ydq56tOlvcC6mWQNITtKVIeRtFQo9gV+tpUBva9PZe0FQTie5l93JrqjlEQGAuk60DeZYMrBMUY/jUAftuAbFyIuP98ZolNK7J2MhzXH2pa5iXgMXEHIAkh5eeOZpOk39UeTqJBDoqm0/nQq8XHd7iL3PHTI/DgBJDS99CgjaSZiLjNBGP2pFSs5moIO58GeOx8DCvFyjsCOrdjSfAURwyyX6gzGcJTquR9LWYWBTWyQIvJL4cu3AdQW3aOHaDv1Mnq/r80poAESrev+JpKhbP9d8itV7Y4x/QNAPgWeTjO8kEvZOxkBFcCcO3qaoP9s9mW+X0OnfgjgzPyCiTwD8Vcgi8ctE9BcB/C6Anwmn/xokbPp9iL72F3buyXVkyMF5zfKFMSfCONKEWOYS52kAUpXFaTPWK73/UolfzWK3WicHW9dFFZz7PuWG6D1Xa4B9yDvxWQ6Hb1o4ICfs7RELBEVSnVCyTpOmtC29hn3Kt1DTjs8vktPTFAAiy1714lWKYlgnoCbjDcy5zgdgTA9zzxhS7LrM8ekvFvHjiSxVwXmsjkgVQorqWCGiSHyTJdKdX+Skwet1coiqk1L7VlVyrh7re2ENZ0b9yfPI4qVORd80UW3nQE8IANVZWFSqSpyOTQterTEOoKzezJMVPjmTmq2mVCGev8TRv6rAL0/Siau1RPJMuQUgmah8fgFnHaJ3mRvCzH9+y5/+5MC5DOAv7dz6Xvaylwcj7w6Cs5QdmbI0+zKq5UXRnUGpKmM2BAxEgXrUiusWiGWLAEkBoOSEK52WWrhIyYlje75PCVQxDJti6tbBiSqweOnOCOOjqSoQ+pyBC8iLFJniPvY4TaeJM7Oss9L3g3D0WJEe1pmZiuPEBKrgSI0JV4GxymJgYiGglvJ+zae5KariAi3+uAYtjY+qHonTUivLj+R3Uke3NSPrkZhiqs2NazFJm1aYpxamMLKGRZXU2WTiRpxFVYnTcS3FmdU0oNFoGNA3GUv7gQYAkOfQPplj9MzgJmZTee+q9E7ovPJkLI7Yuakbcg0/3Lu7WAD34uwh65BSuUNI7Y3FOsQKpy0jOVHV7wL7P1DQEr4hsbB6VzgubwC1v5XYDcD54XdmF0fmXctQucZd5ZaESQ9zsciclpdoEMygijZNaOb8xQTCDtzknJRRW+izc0nDiZCPjAYeglYMy7pkODJptc6rhE2KiJDyemoKfbEYaMUzAClJqh7lFcWcC2S7JiU+3EsWEY7j8AprLzkwkXZgPc7zaeJlsJyfEI1pCBZvK6hF1OdknPwFWm0slP6jntLv6uzUc8ZjKRAEALUZ78FMyF+shDKF8L3wZp4men9MJhI6jXykIfRMJLt+fK5SUQ3TSeZ4BREYF+gez1Cfm5KAVQVihj+SHdwRgdWZfSjH1MFZXVQgz+ieyPH6k9GgzwLTCXhcy3up0PCDGVYfjnH0SWqbD2YCNx9wcHJdoZpOouNV+vquaxa7ODiBzVU/8lbQRs4F2qLS2NA92QNUY6PCllUby4ph9h6GyYp7b0h+fYpG2HOVlctU39L2bMUzGWrI7mwH7Kcy0jMgiruAKTFg0Z2EZKq4xUqQhsiDUbG8wMCzyCqo6bhtPdG+j87j7Dodj6OEqKyCI7ftckj0xTLVG7HSWeSl6dt6LTwPWtGs70MGaAci80H1Hkxe6oxGZ2gjZk1VYfRqCS7MEF43cGeh/spqHeHXzkDo1QzBcoXRy2Wcw8EykKu1VE/rTBnHiyWmz5q8bSJhw4pmddjU2g7+sdREoYWJgHypqqhvE5N4NfjnEord+41jW+/r08eXCEl8Woz0/gXRCHqf6PJsbRPPGbRY+2P7OUSHl7FngYVCrxyjRigsqIsplB+0adCaQNcNRkOy/1erwcJN3HWXzzfnY4Kh2pPsUBc1igjKAiKMPLbZuOjHyELri9Vg2JYopIEjfx/iYmPGDpKFCKt1jBRw70PKuFl012tweIbufBFD3tJPyStRv46NhsTEriIa4s4l0tMrhWA5f+smUe7pc8EKo5eLbKPhkAfDRTQEnfiduGlS3ghwrcXiLTC297KXvTwEeZiaxS4+C3LiGc/05JSAROMiCjCdAE1j4N6mElnpszCgLOo6saULB5ybTUMSlDEVppNEOdf3EXbr/VKgygCgWZHTCfiij1mnMYqy7kO172Q/x114PE73B+D7XqIq4W8ABLSkPgsD9/YB10GHB7GqWRYhmUxStbP3HsPpLm99Fut14MzEhsT50LmG2P3+QuHTwY9R1wKK0nvOZ1IGsu1iyUmazcRn0TaZzwIfPslKDobJFZ/F+YXUBLGgrMMDeSamX1qTBOM6ZclWLHVTJmPgNPULzoEXS7Rffx+1bbOqQIsl/FeeyNjPV9Fn0W/4LBq40wWar8m59auTjaRCAKBHRwLKev4yaafvP8H5H3qMIy03CYAP56DzxXafRdvBHxtQ1rtevvBaoKxttyizMAMoK/MNDNyTvRN1UJ2Lylx9T6CsmA1rwU9tB6Z1Dsoit5EezppH4DkDZWVmSIEWfK2grN60H0ylaEaYzEr138Q2tRpZ3yfEJnB7UJY+s95L39ZqWgTzcbXKQVnB5zIEyuJtoKxgbmyAssJ7sRMoS8f1/CUO/7/dQVluNgWfnMGtzTN/pwl7y8Swy1LRifIXN+7+fiMerwS4nC1ExT2ZAUK+qOgHp0lr0cHZbFzPxk8BS1rCnGqvFv2J27Tdri0UPUr4SEsHYXCQJo4KjdDkqeEaOvXL1bDN3CZb2p+cxSLUma+F/fBzKOdDx134YbK8E51f025Wp1XHYsO/bTfodxJOkl40MfPc/XIFWlPmf4nP1vts0WTXQWvdAoiV14gI/vNnm47Zksm9yKmJoWwl3dXFfOC9AQB/fpGu1QjW6bngPJZJs0D5/Ey7br0OY7YIzh38dEEe3mLBLCAbfej6s6syMyP+byMi5kXRXIno4Q9kNVEtXyxAozrbKZUwpiS/ybJOQxvu4GA7+Y0j2TFN1qk7OgSY0Yddwh3MhaikcrHeaDx3MoncBnJQQ5LjLKPTXyyTU0vNhQLebcl4AKB68iR/yRFMFZt1Gshv4DnLdUHTJvg4kC2og+Q3gbU6tgFEsytqMYb8pjoKWZyTicyzljRUkNLxkRC/2IQq1QDXjWSdmkLQdHgAms3gn30R+yPlEIPWYNZvNcVUA4wm5Mkp6Cf/EKrPnqeTA/kNHgv5Da2a5GA25DdcEVzbg86X6D8S8pvq+z+M5Dd2MaWjQ1Bdw798lchvfuwrWP/Br2Dyrz9P7/xkLMWhTckDAFK+sOvhJpPEcA4AP8oMqEtl7+Dcy172spM8PM0CiLwS8ech98SuhZF1tzSAHwDAYrHBZ6H3vTTrVAsjTyeyM9ndwTgg2YCy0LYC8mEGcBLOrUUlrWugT1W0tY6IhSNnfBaz5OCkVdB6WsPToaCiymUOznjNfJaqbbVhdx7XoMkkXuuPDsQp2PepPRZerCwrMlp9TgBYGqZTqPSoikWKooNzPBYcRROcybOZ+A8McI3mU8FOuFZAaGFX9Y8OBMdgQFDUC66GAAE2qW+IWRylhzPgVR37QPO5aEB1vuNSXQt8O2adBifh6TnWX5ljem5MgclYCiM/OQQgDk7d4bvjkHU6dvCVQ7XqMCLCKhRGnv9wIqFRlwh9iUiyYadj0HKZtKXjA5x/dYzxj5Km4I+mcFqXhjliMvysBnUejgg+FGwGAP78HQdlbS1ZeB0p48ta63QHsl+2FP36eykBA2D/Rn2fZ1lmGIwCM2Bo5uL5xf3Ldpk5s0Gzfpa4koI4Nh43plPMQVAQmpo7oRQe+sJHso1OAMjp24IvhjvTr1Dhjbvgy9GFsEs/RzOy602t1TRv1HQyfqJEwx9Ig7n3m+jOrhNTxgLDQklFIsp9KkRyvR4z464WXXL0EoGpDX6IsIGoWcEMtwqLPlcg5+HW0ofRatOPk6aLQyX40Cftb9OiXrD0S7lfV538rhSQOjdEAjrrTL+AvE7rFfIgFwsrgwuHdWxu+fg3PpLwEAbRc3mDOdKT/XCtU0VYGqasstxf9jJ28jHG3JM+sGNxsWiQvHSlk1WvQWs8nz595CVfJ3wAkJUvp60/qmCutkusXwBo3UTHXNQWQltSeSzX2uLP5cJlHIaqxShSNNVvbZLfSJGlro0Lhc4bIL4BbtsAOhqleWt7Ob90Qna9OEV14Wy7hA7lHCgnUPYmR5GG+ayWrSAxgajFcNuClqHOyrqNTlunPoQ+aLKdB7UdRucaBVJWbqRn7iTSRcx5rdOmxfikS6FUQPqxTlXsyGw21IUyiEsLynrHF4sNxm2fvPkAkNCUl5ghRWIVVVXAI9R645QpqbkO5ORnl6jT0LQpjwNIZkjlwH1gaDY1S0mdmnWdmKn7PjBWG6+5OhTV0RV5G9rohY81SE3WaYY7cKuYEBWzVrOIg6Gf03mpa0MqQ5H4xporPJvIgkGUKNo6KVJs81C0nCGjl/HoYjFKuJQIR9a5qMcBVcnp96aVfpucEl0oLAmQn0/hWoFDs51bRWrOpqBgYnHvxdSbT9PYAoEQt63Mg13slLKwVtrDMM/k0B1NUOk8EMn8tB38PB1Tkh095mdhsfCMCkB7LPebjGvpa+ViDW01O3lSyzyp1jUZY/X+CJNPEtaFp7WYbZWTYs6Kz5mMgFb4WqKTNYx5V3mQi8WQNpHV97jxjQvTwJfaye6sQpkUVcVJ2ZmiZmDMhTJ0O2SGeL/xkd+VZDgN3eF057Xwch/CpEOamDXxtv2sC/r1Opf+V5PRpxyZrAJYDHH2ZixGc4ymRyqORBspdLsJ2WejczJQKyQfCwACqA/n6yn6Htv97ZL32vXI3x/zvLa2fUPZR0P2spe97CQPUrNQQhgAsbJ5dkzPCUQxPECIol78WDTm6BBYLEEHwct9chqdUlEcgVDBzabp+lAgSJF12hY9OgZOz/PMzcND8KND2VTaNkG8X/bwT0JBmhDzp/kcvFyJmn3Rp9h4KBJD8zlcKEgUsSKHB2C9DwDXSmEe730seKO1VBXP4EIf/HmASX/wRODCEN8EAGA2FXV9KWNc/PhjzNetqNUKHfaQZCiLkjSlDeno0MzDQVLX9dg8RAkOZqCLZSKT+fAJCOJUVbZs/+gA1HSgVQM/n8ad/fwPPsL8Eynew8pA4Bm+rjD64gz9ozmcpqizh3//GN2TGeoXr+Tcgzn8kyPQsoGfjeFensU+83SC7skco08Dd+sT6QudnuGLn5zhw/ZJPLefjTB+NsLZN2XOJy86+JpADCw/kE+unRH8GBifMg4+G+OLf0dMg6//4AB8huDMTLwj3dfeQ3tYY9Z2AMkYVt94gk//fcL0aXrmqw8nmH0+AdcBXj4RDbQ9rEA9Y/b5DMuPUvSk/70vE9y7dNzpKQPZmtnfM5ixYPy5SbDc6BTcSA3vM8gt9z14udzMYlXuSPU7AFKlSm/VtEDIi+Cugzu7AHwqxscBGs7KjGRgzdy0gL+IocyYUm7uH9sI52vI0BbJ4bZL6D9VxU/OU5q3idxQ28Xfp5+eA4sluPcp5Tr0uURDao1RvlimtrVqWNMmeLZPZgOvUvaoOzmHX61knkMhHxeiPtwK2a3K/JMRqpcXknlpQFkOAF0sUfUe3jiY3ckF6j7NLfOFqNpNC1rVGQSfmhajtovHVCXvuw6PfrvF6FlYWIhQjWu4swscfCJ+iOpsDa4I8MDoQj7UflKBR4Rq2WP0conH82BWLpYyz0XZx+qLM1RnwqGp0P3JZ+d47zefoH6xiM+vWvdwJ4vIUzGq5b7jSQ10HtXJBebrdF/XvMsIzlKGaOGv47uwxDLOCRI0HBetpEMG1d19bpNmEksKpP/Jsj9VVVhQfN5WXedoRGAr2c6dimXSssxg6ggMtTEIbXSgURcWBkMMpOcK23Siyv//23uXGE2W7DzsOxH5/P/669Wv2/feeXAuZwgNR+IQIkyANmBC8JKArZXsjSHAsAXYgjZeWRt5Ye382BgiQMOG4YVsaWPAEGTY4EoQaUEgCJrjoThDzdyZ++pHdVd1Vf2vfMXx4sSJiPzrr+7q7ntnuu/8B2h0VVZmRmRkZuSJc77zfWTN6Jpu3K10HIkk65Fn46yBxxhw6fvVSboQ1oIzG4OZWouS2xcKY7/I2NLo3nJufQqVNv7OwePhjML/nFuwDpnWjKQarM+53y4DODOAhrbIj8/Gs8eWQDcvA9lqb+5kcZ04UPh78lL5Fy+IGr/UC+0fbv8wB/5EIMC4SQFg9HKK21deHkpekkSoCEUuD3KPSFpC5BmeWHge9KbTxoP0eVuqWWEIMFZeSv8zIA8e16VkOzTaDsQXMQgP8YjWL3AsqIDPywbfwoNv/NLDZz3Ui/QvCpcZhj3pg1n1MPMVkFlwkQfKfvb6o66wsK8ZLHZ5MllYAy799YU1FoGNASWavM4SyDGG0sKWViY5wIsB+eyHLhnLcvtzZwxcAXCRsKZZuVdsCTQgMr3Tq4Zvk+Ze8/id7WxnvyD25noWL/rqBHBRTDm+ErLTMUCSxuQ0VYkk7pGmONPjtv2cdpE3UHRpVSbHlB06Rd3FbczskX802h6AVGS2o1BHv7vrPRC3MX6x0wl6lAEMYCdfwRBXGFhKwz0iULYlAK8kLsD+nCOKwYS569p+bftdx9ELQ2uKVNOj5FGL1A0wKx/0bfuQzhzrlDi/bzJGWu26mULXtrcibBm2HadKqRMAWkBHDgziQcZNAVWdC32mboDpEsSpR5IGb6HvQa64ihR2DraJ7QHeMx2ceIPOxYD24L0x5nGq9yXszZ0sXmTpy7OJUWDGjX0udkK1719KJA9T4KlIHnJS3H1KrW/jujeES/RlTnAAKPKw/hzRo3l0HhCDlRgGqWgtCtnXY8BY+RaqImItAoApG2l/QjVKmyTekEgBpLUD8ZjE2dR8f5bJcT47wpkR3gQNfIbd5V5oJWlArzr2QLrk/jBLVifI+Nk4Rv0gVHj+dyIaxxV0qdQNo/ZdbsVV7gdZemhbeQaspJaFlQrAL5GoixB8mtRxPDbHMs/BVQEsk7/78XQ5gsfiqQAAIABJREFUyfLB940GiRU4H1w0lsCZAefAUPlajdzAFYT8UiaRoVD6u14ySmnFcteDjw/gyhwmy+JyLLcYCj9Z6D3IhduTPTiOfR9cYWX51hRB/Uz7f1N7KycLQVXS1W1qN4F7b0J/9UsZMP7makCTjPA4tF2c9QdR+7qSdWmaCH/Wvna9lKYDV6DZvFqHlwqApIMTab3w1faTEC+XV0rUeZMTQ/s5DCFFnHKHgt3VYxbLMQOX8doYiWdhT31KeHAx0+Oc54tINE68oDObOB4A4vn7PuHZ0C+1J9dVOP18ITDrYQhkNAR4OL0wfOsXN3tyKWlXJcMFpI+rBtw0sq/yT/rsiiGCU0Ki5Upe0L4HsmxM/tt2oK6D8xmZ8CIPA+rPVqALnzkhL7K9XCF/IilOWjUhRmPW8ny5IgMMpLjrcoXJgzyMid5nZj+JEYGeXcIWOdxyFfaxp3Ps/3Qi59cxGBxIxaEdh3EwXn+F5ktkKYy9u3mA762cLFK4t2ygMc6CGVu1TtND9IH2Ln1QPdfg3OXl9oBmqDpVyQBfPRqk7nxbenOS1CnyTKpLAQ8T95DhrhccxZAspbIMMF08NpXp2xAZCvR3ypeh++WZPLjbqk6Vrk+vw88lVFWx2rH3GRvV+VRY9ayG6fyLrlR3gxcGWq1GE3lwnfMCI4Ee+ACy9ke3+fEJfagq2ceroAMAqlKWHn0vEG5lmTqYwA4O7IOZAELRGwHggz3QpbzAClV3sxr0JArx0KSKbaX8J6ojq5wcHheCC4vmTgV75n8nAk9KmGFAf+ClAKyV6KADhgPZr68lqG46hyy3aI5L34VMJoM062UteFpLNet8ESZdN6uxuJ9h8lGCm5gWsOwnCeboWVQ5qHOwjuFmkVaPXyKzRlsrJn/Gtk/H/Ju0oYboZ+JQmp16AiZ5cYxnOiISUhh4fME2Zar09KmLmbItqXvphBhmxBxlreS407SnEu9stEdlOV4Lh8u6xu3Lva5GUkcSqPE3WJsozwJn5rhRM0pbct8hyh9ck1ZOrwOAqRINCvWKtE8bSxluu6h9kkCcA4As4DxaOUfKbG1MpDIEEvEmM4o/KeEQ3BD7lk6ceRap/P2LRlnUTxH6wnXMKOmE0/uUeJGDdQLx5f9h+ZR6i8HTHEZ94LZF9u59uIsI4KKyEECdTtyB1TxSDahmCmUZuGlBBwLy0r4gyyLRjqfp04IyHTM7m4FuH4MvLhPPTBi6gmeRjCu37YjgCQD+xfKf4Hx4cqO1yC4bsrOd7exG9lYuQwDE2TqR3HsVLynokSp35pWy6rQQ6iXOn5aPax8TD4M9z4IahcIsjU2QrFl1e+zw1YzB52ycfqUMgpufap9eKenX4i1jEr0N+T0UcW3yY7x6B+OPadGWjk0S3wgB8GHwnBQUjiML6evrjmfKMWGMLwx7frYs6sK4a8v307jYNmNmWeZuillpFgqIUofm9Z+Zt3Ky2FaifqWCMeXm3FYbUsR4AQCYaT1a27ulp1O3NqHEF2CSKfJQou4WS5jpJFDaB3d+bxrh3tpmXUfuxovL8DOv1jCHB7L96ansXFdSq1IUki3RmMNqBeQ5bFXGehR1w1OpAUD4JvNc6lemte+vFwG2xmdVfH98nYk5OoxBxy7JSOS5cEcAUq/x9JnEAnRpwMIgzk175eUgIqkH0QClP4YMRVc7TwBdiSoa7U3B84UQzfo6FqXr534Yc47e2oc5XyCUhPt+iUrXSuQVfG0IWYAOD7xYcB/vz6QOyyuFlwOQuM2kisf7cR4eP0Hzl95D+ZOnerHgMoe5WGBQKYBlIzEIx3D7/j4UAsQyTQ97vsLyl2Tfyf/biQobmZD2hCFZbpQF6OQ0QPTp/Xfw7DvHOPiTkzixTCuYy1WMRQQpgFxStPOlCDmr/SihNHiBvfGTxdZZVXklAFk7Dl5Z/CW+ViEWoiQzXsszvGw+wJkiGkMb1saA3IpG6tw6wQvdmxPknsKcyyIGBNs2vmjDIDfQOUCfuTwHsi6kMkN/SSjqQCZRN/Nf7CKP/BIAeG4Tej7/UJh1HDfm0csGQIJ4erzxyFafNlSMQHdYI2s7UNOBNVimuf22i2lFfVGtTWgDZVILyFsl+FXKvKrU6u24b9OAGorFe3u1BIW7HjypQuC0P6qRDxLUc4XK9jl5SYgkmKmB6L4HlwX623vInp6FMeG6BBkDLvMRWQ4VhQQZdYL2nBBkDRb3C+RP/XNDhGGvRDY4dMdyf7PcSNpycGj9tn4ixW62zVHmFsu7MmaTqhTPSwPugMghTmu4Ooc5zwE/mQ8HNS6+brH302l4Hfq9HDl8CpVZsi6Q4jbbDMiY0R8mHxR789TpmxvgVNtgaR5tAxDFhJKg43Mo6cNh+vJpIC3PJHiorN1tFzIGI3bvvvcQaD85aJBqIxUbApxpcNFE6Dd3fWgrfOF94RjgswOhGG4MFNO+brJfkbWj4JVru0CDT5mm5ro4bpykOZVNezIJLnVKyTYKKlZlSDWHcVRXPxVESlxqsiaeT8+VBm4TAacUwKVjy30fA5waDPYB8HDesohi0qENDkHicP9821QUQJHDaVDRB4810DxiyvL1GpsizW61QvbV96N2hycL4tU68nSmz0aSCQpj0LaxovbJaQx0B51XKRMga4XpXAOcB/vA3VvAk9N4fmNlArae7T6wfEt1duqlAsD/c/6/47w/2QU4d7aznX1+9sYvQ671EML2NLCTLEO2xSxSLyV4If5LQQROURVuALcJbgMasLOCX0g8EyrLBBKefBE3dT1s1PUQvkc/62uqyxo4lS+0xmuS5OC+C54B3AA4vwzywbrAjZnokgCAgdcmSb8mKzdKAwb9FO8FCYt3G/oFQJZd6mVB1va8bsZLNJBHcDq4VPTGGxWTWGbvKy6prsMyJHxp80wwG6ms5CpZOiF6Xezh8FoiRdMJmMfKbjAkcYjlSuj2FJym7SdFeaauAoM3FUUs33eCAqU8j3KLpSBojXOR7VzP64OcNPN8JYlCmC5fOLOyPFsLWMzN/NLgcfQugw0O9tYRkOcwCRKWphO0d/aQP0u0UOoKnFT4hmesyKWQ7vwSSOJaWNy8iO7Nnyy22Q20TlUuYKtUAFGyBPDub1UGYhkAQoe/RetUXf2gHdp4MpogD+h3LYSifuTKFnlYd5NKCMDjFZRS/9l57E/bRS5P7W8nEwnVVXyJFGmpWp3euO0CX2UAO7VtWFaw9tNfBzvjNTz9g6Z0/EUuxyt/5cGeUNIjBit1zLjtYjwpHfIiUvaHNqeTGOTRmEVRiPvtCSiprhGkClUjdTKRicyOXWp3NLvqKvsXHY4FSJVyVExqiVHoMqSupE9tJ9uTOp3AgdnHwKtqnbb3pihVL9XzXpIxGG7J0sJcZCHQGKQAMgNXGGSLAtZaNO8IOVD1abn1A8mzqQQ42zb0gQ/2MP9qhePPYsByOJjCGhM0TrVdV+dwVY6MGe4gAWU9+LJPFjew5xaV8ZiiH5C4ACt/4vNPPKKqB4Armqa6bZMQZ3Ch8IoV3al/67fsixg3uMKNmRYa+XgBdT04S75KWpCU1rxoOlSJfTbh320XA6fav8FEODwgWQ1/PJukvW4ct7luPPS6ueviVzLELjzILilKk/Rokm7turAPd7F9WrUjkiA/OOE8AkdPxrEVJvDAUK51GV0nQcVUtsHXp4T4USdAQDgnUgApvT5LnMQs/YSXsIfZpZ/0cwvqLcyyFWIdZfdOpQkSC5qu6dg0LYoLNxp3s24l+BuuyWfnAMDJebRfTBT3u4G9PZPFS/IfBLbvJEsS0IAU3bQQcbYaRHp+GIeKQvqiEX9rJeU2X4zSrMJX4clzkjaULyNAtvVv2XiGT3kt2P+v/SVPRBOqGpUzoyxHX1qUpXwBrQ2s4rRahb6h70P2x7RtZLzWZZuOt8/+hO3eBYfFKJvCbgCurkBG46E/h7EMIkNFqOkgqiJ8vhC26hFJsScFYuZwXQDg6gK03sjuqGeRZRJcTLEtRS5ZD0WoFoV4FJlF9+4R8gdapzPIfikCtCyETbzv0U4yZKUfX/Us2g7DRO6F6Yfwhddt6lkQM6jp0e/J8VmebRUr5qoElxmMD8oCAJcF2n0zKgZ0VQHbdFs9i+VXpthbt8G7AfBScO+3Z7LYBCZt/rxJqxdYkiPgJf36jxTIAQ89dvEh3XJOqJq5oaiDOQxCoecYSCaGoDGRnCNdi7J+mfS8G+v8oKLuMwPjjIiTr3undHAcrzOJ2wTl9KSIixUw5KtXFUvAgwvUdUGAeEPjJHB9ns8Fbu6vf3RNaZVuej2p5oZe95LGquRkYtWrtt114EZgyqn2aOhP0r45u7yiRg8gFoW5sUfInsJuREvovYL8AUXoNTPQZjJB+aUfO4ZpWvByheLRArj0tIWQmAWvG9inHgKexCyyELdJYhaLFcqHPga2bkZL13BtF3OJg62bkDqlwWHvozoWJwKwTooDN2MWdpVjOjDoYoEs8WKvCC89x3bZkJ3tbGc3srfHs3hFG8USXldXJJxjvGTg67yen5VpHOLKdhehyBvwc9UhHZHq/DwsgZYLJFkyCSGWYXnc/y/SlACJWdb6KQTbL/2ixgi2xqW+MBuRH73aKagbrpYPvIS9nZPFDbIhcddrhJPTKkdAUozcRqWxa7IhIEFkRs6GmPZLVdHIWlEMS2pXRophZj1WCcs3YLeqcmYopjqTvmuWBIiTBFlfTh64Kj35Td/Hda0/lyiwDTHLoufOshh41Rcjz6JSGCBoTp9hSPtNjuVatmVDdDyQgLKyLIlDCKkLZRmYnLCKARKT6HqwiWAvyvPIKZkqpVVlDASGjRzGUuJNyf3wWa0Qp8qzEJPiMgfaSFBMeS7xE4WsF7nEAxYGw6xEfp7cv8wK2EpRnswhNsBekYxzC5dbWCPLCeUMzawF7JbZoCqFb3SV8G1WBdrDAkUSp+K6lBiPXpPyjVQF3KSAXRTgBOX7MsTJb+dkcQOT0vXrMRojlmf4F965EQJy+7EOsPkoqASTMDklqcCREDI0BekfoGUWuTOaZgTT1v6QkZdnhJRsRBkdeXE1+2Dt+DwLEyL2WtYfXgwN8uqEpTiLScJnoefJC9mu5S8HE5hzrZFIgmV6LbzlAfTjoT8DCFBuAPGlr0rQugH3vp9lIRO34zhedRV1O5MXpT+ajIhdpFMsk1vXCYYiDXBOKoFwn6qEogQ8yUPRw7rfB0d5Ul2Be8M5NLdLZM+SlHVuYZjRHsm2zEay4v5QjhsKCXDmpUUOBC2P2V+UW8sWuC7lZb9cBFIeN5tg/p7F9Eex7f5wIi+1nyQU7u0mOZgAM6kCpwYggdab2ts5WdwkwBkCesnAp+nHlA0K8NofbnyjtgU4nRkzZTkGr9ZXeDoDk1Ua4FytY6Cx7RAYZ4YBfBn5EGJ/hijas6kbguVYwBiQQNooNdjGytBl1ChRcWUMQ0LaI+4pX8yvBDjJs3pp4M0+ehap81K2Lx9w3Oaaj5i99Lr7Pglw+nFqu3Hq9AKB9yIEL0PatA/aowCQPaDtAc5lBrdcyYSRBjgv5kIP6PvlFkuQpmqLPAYzmcWjWDchIEyeK4LbDpMPL4DT83Be4wOchRIXJQFOM/eTzEaAUyWYxuMUjU7PYS89KMwHtu3JMxx/Px+1na+aUYBTmcttkUt9ynyJfJUAyF5CN2QX4NzZznZ2I3s7PYubxCxeFMt4VQSnoUBXB0AQdWUJ0q+xVp1+0QjOqgRW3ovR85fjEnVSN32I8oes3J4bCE4sl+J6/ywRnJM6fulTWr2mjTBwvw/1/ReO4KSyEFxK1wNlEYsM/RiIVorfNq0FNXt+8TNBcEIRnE0b7vfLIjjZGlgA7nAa9ueHX/ZlyA1sBPdO19CvW2WbqnWpZUnw8BWUtl6tH5GzIVDfpbJ98IHEwpc0a1WnximMiX/Xvv+sLRU0oth/KnKwzrqeU+SLUo0fmSrDEQngSgl0hgiqStXruCrGILgv0lSwylCgDHxZ6/cK2GcmCBrJnP5lKlFXSzg5N8vBt5oG9JSjE8IvqeCjkWyA7p+Wk1/D4Ul5Md6PlatzBZARYhx4HtDncGQGfkw9h5aQawxAC+AUuToqgiN5SNN0okkmjtTyPJY6I5atS7McMwxFEeMHgYWMwxgGLk/dV4vN0klG9WG3PVM6vskxpsjHZes6+SnSVq93g6lrREWQ8qcW+dVnI+XTVC5L3T/LQ8EeAOFw9eXvZraXANaGwCEaStStCSXuGCKoTnlLU2IhdJF4ecRjqhyrXfQs3eXl1piP2RPPg4gCJwpfzmH2ZxjOniXXlEXvERgRPpvjQ7jTZ6Mg/suUqL+5nsUmvFsDh30PM5kEBKGpSrjVCqauI6qQnVRJNg2QlwEN6BJq9+z+O7Lt4lK+svfvghYr8L64aMMPfgy7NwUPg5D2wlclDgPo4BDwFYX8yQPQu/dgPnkwasP+6q+Anl16gl9/w44P0N0V17T48DHcoVfiPjlF++33QY5h//D70tY3vw48OBFl7/MLGM93MDx6DHv/HfBeDTqTasNAWX/7GP29g3CN+Y8eCKnOk1Pg/l3p14PH0mZVyXG3j+W8P/qJ9P/f+i6yM3nw7XINNgSeVugPK9i5vGgn393H7T+dg9oe7W1xgckx8tMVzKeP430LIkkM/vq7MKcSxHW39gEiDNMC+SfC9qPsTf1hjezZShTZAXTv30L+yVO4Ryeg73wLANDcncAue9hVh34WC76efKfGwY87sPVaHgBs6+ByQv3ZCs2dCtM/+VT6Ngxo/tJ7WNwvcPwHss3NpmjvTWGXAuEuHsUlyzAr0dwuJZgJoL0n97/84x/jz/+rb+G93/c7EtDMDPY/avDor8pLPX3oMHgV9cW70q9unzGUjOLMYPYR4+S35Bn9ld9dIju7FDlLXcIag8u/cg/NgcXxH5/BPBGynpO/8Wt472/+GGf/4NfDym9+32D/40F0SBjoa2mvOSKYFtj/6D4uvhpf++4f/5+4qb25k8VzPB5u2/j1a1uJDSTb0ljBNugsgMDGrC8zPT2Tr24TJxynMOnQlvcW5otY+df3oLPzq1+0x6cycaRfFXYofGm3O78ItPJ8OUf54RMAQK9flZMzuOUSZhDVdvVReBjgnp2D1k3ISATP6ewceSq6czkXrYvVGuaJfH104lN1LqOkLX68i4+fxiyAKpnPCxTnZcic3DYG9pMTsHOoLiLUmJcrr70xLoKDY5hHp0Fzg7oORARTFkL9BwBLaTOfV+DlOnhYOQA+vwD3PexDmViq+UpepKaFTVLFd7ojUTNPafWck3qTiwXsWRVZuJ1D+ZOnyJ/WgbiG1g3KdQNqOqn1uIyTRX5eSHrUZx40RsGrFd77fWD2g7Ow77TMYZ/N8Y6TiTg7byRFyYzZx6qibuByQj7vkJ+ukS/Ec7APn4qXQiZ6GIaw98MCk4nQ6jkfd7n1vUv89B99gHe+fxomzOmnNbKzZUiJqhTAUOcgx8jOliifxhjHh8ubg/F22ZCd7WxnN7I317N4HXuZIGMIWG4gOkd/3xK/uIHWKYC4Ztzo25XYwuayKyUwGUn3mavHXtevz9vSdo3XztwkxvV/AxBZwcMQb7n2a7VYXzC+6j1sjptuS6sp032T/odtI5Z1Dv8/byR1P8c8jhESXfkE87b7pcNGkP3TGIMGe3njmdzmBPjj2VE8n/YjvT/pOL3iI/J2ThbpC6wl6CnMmF2AeV8H9w6BRhNTiUJqE7MDIZia8kP2nh8xfRi3lPlSZgFrRuXllGUC2QUC8xIAAQBVotil/aIsA4pC9kuEYchIeTxZE6T4RnqhI2SpEWavpPQ+DXxJFmWjziXPQF3CT2pIGMK95igADJMMpi6FsDdBMpIvI49pXg/q8qXkYamWS6k45xHuHUr0rfVcEkk5e1KaDkDSmtSJylhdBkDXUGcCPsotuFTCXi9IXOTgSRkzCYMDl7mQ64axNXL9HNOfwTLRDTUKn9bAMBGamcHUl6jDAMNeAbMs0E38Pp0T9ioG+on0q5sYsAXYEmxToJlReBYQxIcii5grMrgqk7So78NQZWiOgGEa4zbDJINdyRjAcSAu7icWtiWBmVeJENXnCfcmov8JwO8AeMzM3/Hb/ksA/zGAE7/b32Xmf+r/9l8A+I8gb/PfYeb/68a9uaFd1fbgKxkOjeRfR4KToh8ZEKaoNIPBLiIJOUbj2TGo62Ku27GUUG+0wx4ZqPwZADwFHCRmkZTC87qBuVh4tKVHeC5XQquXlIbrtfPax1I05qFFV00T0mIAPOOUROY1CBr2hRDPhBiNN5ovo8SAj6pz3wuy0beXn5TA+RzshqjIzSxtdJ0yFY71R1armG3xY0BZBpdkJwCZWLhpQ9aCfMk8+3PoPkp8QwlZTHGSwVxelQKAlwIwSbAazDAXC2RDovfqGcq574WwJu2vczDMYZtOJG5w2P+ogX02D7uaZQG6WKB66PksFmv5oDiGaSXrURYWnBHMSqQA9mv/8ZovRQohJdppO5jzBWjt+6T34ekCRz+skD2JimRmVcFcLAVnwQzrJ7VsngO9g5kvkScfT9PfPGZxE8/ifwbw3wP4Xza2/3fM/F+nG4jo2wD+fQC/CuBdAL9PRN9i3oKKeg2jPIspMCVxSbVOfaEXuyH8f+Ucmn7yUgA0mwHLZdCmwMXcF1thXD8yOCG7mUqQiNcNzMF+fMF8W3S4D1zOR4VNNJvBHfsMSNeBZh7k2/Vwdw7FlT+RQCft7wmoSjMwCrZaN6C6kn4q34I+wPvx/ADEI6lr0DCAvC5J0MhQEJrPssDDzd3dIxgftFReSZ7WcNMKtJTfFx8cYtr1UgB14LU8mOW4ro+MWIE8B6CDfYAuQz8BwO1V0WP398PNapjLFci/wO7uEQz85H64DwAYjvZATQdatXCTGOC8/OY+pp8U8rVU79sxXG6RP5mjP6hhL+JLPdw9QndcofRZJZpNMdyawSxbDJMi8lFAPJj2qA4QbgVc0cUlHv3VKgQzAaCbZKgeFnj2bdmnfjqBywjEjIWn/O9rgiuB4pwxfVDh5LvimXztwxlw4ZegOlkYQvuVW+hmGaaaYQKw+OAIn/01h/rkMLS9vFtg+rDCkBsQA0Ml/W32LUzPmDyosLwfx2z45Ob4lRcGOJn5nwE4fdF+3v5dAP8bMzfM/CGAfw3g37hxb3a2s529sfY6MYu/TUT/IYA/AvCfM/MZgPcA/Itkn0/8ts/XtgW/thR9bd2upq6954II6mFN4hZv8BMK14Ffnii2gb2Lv9nOuvH8kQkrUdeBFmtxkZUT0p+Xlo248rqzFqvp1yVNzXpGr1BwpEuXpoWZRyyJazuJSaQFY2kh25DK/PnA3rKJ/VLF8LUApmgt+xbPOvGYBidqW3p82425PVT/wnlmr8StlrYotK/xEEMk1+a3m/lafh6G0L6Zr4VnsulGgbvytIe9bEQ4R5chA8NYAq0aUTPX++QYZtkgy00c29Ua5kIo8Uw/REJkiJeUWQrbzEUWxmj60CE7914YEahzMIs1ap+izM9bH7DkECPoa4LLCPnSoThvMfFMWbQW4WNWPRw5KbKLNagvgNU63PfyrMXkpxNklzF9XVmCvWhhferUrn0BW8ei2H6xRp0nQLbrKrO32KumTn8XwAcAvgvgAYD/5mVPQET/CRH9ERH9UYfmxQe88ISvlwWmNGpMNHqotu6bBt62QZE3syDpdvKIyHRt7SHb7Hy8JTl+K8rWl1BHqLdE0Nma8I800j+K/JskuOmj7iOujGRfz9+BjX05S/qtx2/GCUK8Ii4N075vnlP7xdaM27IKA796DaN2SYBYOlGwBgINBHOwJUsRzq/mOUDZGoF32/hPxjTZlvl/xmDICZwZaceSxI2sgctkQtAx41ywFS6X7UMh/WVD4AzgDON7ER+A5Pw23HfOCK6AtBfGQPrgMiPnzvx+GWEo5BqGwoR/L4H2fjXPgpkf6c9E9D8A+Cf+108BfCXZ9X2/bds5fg/A7wEC936FTmz87q7/24tMGZISMVrfxyv7vbSl6avRdjd+oa60JcFO2uYxfZGsVumLnkLidXwASb0NWyZThWZvgrLCOTYg9q/bT8cj748YPr3IIFYmcQbnun8M8AISz6Dh9ceSGKNrkn7wKPgL0Cj1SazHxf8BeBZzBxi+0fNGDpG4OelLaDug+V7p0kb2SpMFEd1n5gf+178O4P/zP/8fAP4hEf23kADnNwH8y9fu5aaZjS8bMGLxDl9F4HqPI6kaBSTgx8MAKCJQ6zjIgbUkwRopSsujbogwXxcjwSDAp/TabnQjUZVw0wowgDkrIpPSIhPBXB7vS55Zi9ouMlIpq1ZdxZoPXULo+b0p2Q4vVyGAGKoui1weqnC9Mo5uVsE4zZj4008q2e5/X9/KUTyoAOfgZrE94xxonmh06kTJHMYjjA0AN61gL4vxtr0ahjlgNIa9Gna+lK+z36ffr2DWGYwxowDn6naGbFEJ1kDT1YPDUGUw6x7DQRXSpADg9mu0xxVqZcuuS/T7FezSYJgUkVwXAE9K9Idl4KPQ6tEsy7B4lwIyE5A0pWnrEMxkivDz5V3j9yH0FVCdGpi+wOJ9Cn0gzWLpfSBCd1Ch27fIH5ZhCbw+LrD+5TXaw3QMLExXYSg0wCnn1QCnbUusbyVjkH++qdP/FcBvA7hNRJ8A+HsAfpuIvguZr34C4G8BADN/n4j+MYA/A9AD+M8+70zIzna2s5+PvXCyYOb/YMvm//E5+/99AH//dTr1IgtIQf1Z13BpNaLZ8Dw2LQjG+vWsB2VxCmrSfYKwsfHqX/aFoCwFJ7G1oQ+cJWChzMa2sgyuFM4Fo2Axz5lBmZXrU1CVIdlmTehXCrTSWgDZHuMTvAnKoiRukZgrMhjtl8oV5AIKokq+wH1F4CoHdQOGygfmWKpIZU3tgUv2uSDxAAAfp0lEQVSK02AWbyyL1waSNfxm3Cds2/idfD8AgAsDZgseMrg6Cy52VxOGUvALzquDm87B5QauyNDXFrkHZfHg4AqLfmIiZWFmJTaQy/9ItFw4l7W+bgt0dIZ8UZh6sgK4Kgsbirg0mCmgLNnW7QFDyWg7Qjcx6GZ+6VbkAtazJtL0E8EVBn3p2/fj21eEw6MF+mksHuwmhKE0GEpB2PY+ddpNANtK3KKv4juxjQHxOns7EZzX2Uus5QOprSpmW3M11qPM2CHY6ULQUMlFJNBk4/n02HQCScSAeBOGDAiakCDBsQ0dDqoxjqPoubIEKamTkTUBsQcA1poYINzgYxAEKF0RmWGbTCB6TeQDh34YpKKRR0HNFByd6o2ErebqdXOeTLphIvGBQ722ZB/2E4CzBmTSAIBvroAEXzFex7vCBzcTugIdtxHVibUi/NPL/5wErl0+3uaKuMwdSh6582ylH07BrT6YSQz0frUylIyhZrgFgS3gKt9fgxjDSmIeQ0kYSuHyNH48hoJwa7pEQ3GycIUGUGVghoLCdrbSb53EQns3tDd3stjE/CfGzNtjEalnoQ/LixCcKmff9ZEGXk+3AfeGkUpA6qNcnWOGaTqpEUgtTSPqC9oPMOskzqBfDmtgegcaOMK1nZTZBwSixiV8Co7WbUhtatDONB3sIuXE7EBNBzc4kbWDIA4BCNJycDCJ7B4A2FUX+T4H8dCo62HX8SUrL11I/2qAkHoXKPsDZF4rf5nlZx2PfgAMwSyTtnyq1C6s/Oy320UbxtJ0XgJw3cM0Pah3Pkgp5y0uGHY1gDPxMACZNPLLAdQ7mC4SMsu197BtHoKktG6QLQqRFGQeiR1bA+SlDduyhfdQ+h7FmUHu5QeZZFIzqx7FufQrXzpkDQEsMQp5PAhuQSgugWzNKJ56z2/wk3BmY3rfGBQXfeijPrvlpcOHj27h/ZbDV6q4YGSLAaYzAAMmZF8NbMvIL/vQB7lvuLG9uZPF8yLmqjaG+KIoBiIc+yKcRULYG5SmlDnbH8eKkwhtiaKVUMd5BbFhEBjyBmEJLVbgxqtLaQ3Hag1z4b+gTQvyZdncC+QXg4NT9ONiBdf1AIkaVxBediyTABBxFjpprJuAvgQUZ+HhwYoZ0H39z5HwxsOFL1axX16KgBxL0NE/vPWjGrRYSym3eiz9AFquBb6tXoSW5zsHWq4jpsKf33SRsFe/deRYsATKV3KxDPB2msuYZ0SCs+h6UXDxz8D0YYHsbAXOLexGbYi5XCHLbcSVDAPs+QplHglxCEJwS20HanrQIqrE0eCQ+/sCRCJc7jrMPmLkp358DWCbAvZ8hekDcSOK8zbUhpheJhmtDcnWjOJZj9mHnmpwvgSv12OSJ2uFK2RdyHPhr6F+1KD4swnK0wRqPjCKp2uwIjj9OGSLDLZ1yE+XmKaORXfzNMmbO1l4zyJ8CTYo9QOkuMjBfSfq5p4qnrUQx1Poj1iX9Bweak2+WhLHB6B5JL8xT09B0ymoaeC8d2LKEty2MNMJ2JPf0HwBHB3I/0Boy905hDnLBAyly4Rbh2jvTAECyraDO/IcjX2P1Xv7IAaKTx8CAIZ3bkl2YTqBsSbAy2m1Bs32wNM6eJDhBTicob23H66xWK7As6nUddwSSHDQvSgLOc4T8OCJwMzb9w+Rn/oajKVwbwyzCv1+GcR7n/5qhTvNHqhzaO94GLpjFGclbJo69R4E2g7DnUNY1fu8NZPz1jkK7105Jb85qpGdRfKb9r0jFE5qWIZ7cg3rOzWy9YBs3qHbL8JX9clfLnE4sbIMMBqzYAwFYfIgR3NcYu/JLDwLy186wvJuhtufefj5rEbzzh6yeYd+Lw+SggAw7JVY3asCC3fgzHz8FCe/1Qc+ChChmRH2axsg3JOHmWAoGCHr0c0cXCUexezDAmf/jkw2R39+jOy0lGWx9wbZGsy/sY/1ocHtxWG47yffrvGbv/M9/PmPfzWMweJdg9lHFkMpnkxKfmMbYPZxjsuvxOVV//2bBy1eD8m0s53t7BfG3lwOzud5Flk24ofkvpdSbI2WB4HemOffNFNpIZnySuaj9lzTwJRlZMsCAoejcjde2Q+I7vxsJm6+ei6AqH9rTn/dJHycvXg6wxAqIKmuImYjrTptO8FGJNWo6s2YRMQIANxiJRyTbQfjt2u1q/JcBs5QpQO8dRxjDZ57UpXOAp5jtif6HH0f2L15cAJvT8rpQzakbQXvoUVsRQHlxQzMXVomnmdgz+IFAKau4FZrcNvCHnivqfRCPF7fQ+NSNJsCy1VEWAKyT9IvjfMI43kt2JcnvvTJed7MThTc0qpTValnz06m4+zOL4C//CuBxQvGCOXAfBm8Nlp7uLfjgBXhIgeMxChovkT3rhSi5R8+lGu3Ni4dDQnepsjhnp2H5ad99x7WH9xF9aPHYQy4zGWpFLJMsaSeuh68XI+Eof7ws3+I8+bhjdyLN3cZ8hzbWnZ+BenI4/83d09V1ElSopsTZ0B1bpz3Sjl8319tx08UWnsCQMrN1y6kYGMJtxPq+7StYRyTGcVE/EQRl1cJoW2iNB76qerv6b4DQlxmdHnrJl6Lj8qzc1Jtq1mMRaI+Tm04Lw9xCbJpnAQ400kk1KrotXt191TdPtAQ6GSjLwazxDp030t4iQADKB9GItAUXsLQp06AY7ps0noc50bq6gBEUlDjVdJ4GOPs7DKUz4N8rUnTABcU7wMgY6j1Np4YGETg9RrZaVxCKzo1BLUdZJJqbKQ9AMDzBcqHlzJGOn5tG2JNcByzTdYf27YbdUY3h0G9lZPFVksZpK7TN73muBEztpKxeClDNi1UrzTFd9zYUsar0XYTU6cBVzAgzCyGAMpArpMah3TyewnCktcy7aPWkgRsComnkWpqDgARS18VHasTsdZyJIjEa/EvL+qPtg95iWBNJDLTOhNF1QLBqwj3WQPYzmfUsuz6Op4bGifYB3jJSU7ue8D/mOTeWX9PM4/vSV5qOBZMSvBIs+0vNUlNisnGfw+1IgYjLM7rriHe3Mkimbmv/s0lP8Z0qQuz/g1mioTunthrUToGwadE204COsOQSBPeHMcRa01ceFgICC+NZmF0X+osOCFXgW8bzo08nPS4L8TSL60uobRaUr901oRK0PCVchyzRwl1f6DFx8a9fBVcr35R9XfngmMjf/egOccbUgIM5l76nWR/yBMfpVIJr2I08vJIsmCDS+pn/N8cRwi3qrT7JVcIZq7WHhqQYEKu+/oPDtQNwqgV0vQJc1z6nrzWFfpTfw7n2NnOdvYLYG+uZ/E825g142ZdI77MqWjkQoZliOmvuqevUgafLHPk92TJkxLbGgIGHu9rk3V3UJH6gpcgidcS+qhLkQTtKUFml8QAhlDMp4HbzbjRFeGbl1gvj7voQWqqVrYhXgRrRml0dAnPauKhQaHzoT+vWIFqknvsuVuhcQMAgtTaGAP11Pw1hGWIIVleJUuPkejSqF1/X7Isxrb0eTYky+fNgsvXsDd/srguW6PbA5rHXM2Y+Ac3KllRODY8TE0DsIPZE2q8EOVeLOLyw0X3l3xUOo2Gm8MDOK9RGjIT+/uiiJ32aToJtH3uyalodgJwFxcwB/sgAP1PP5bj96aiLeIj/9pf1zSgsoSZzaK4kAc/0cTT/el1Pj0TMaHFIuBKgk6HVyrT/gynz2Qcbh+Dl3pe7+PnBWhShe3uq3dhPnosBMdJZB1LyVoEhfXEyI8HgJBBoVtH4HNPtadEup7uLwC4Dmbg80u4ebwGmk7E9W/HWqf9e8ewTy7DvQIAcgX4+EAEn6Y1+JMHYX+6fQye1oDXErG3jgSX0nbgqoRRCj5moCqlIlQVy2dTgAjm4Qku/8o97P0w0VwtMpjzBdqv3AIAZBfrUEvSHXj6wMJgKAnFRY/8dIX5NyTTM/vnlzJOaQxiGEBfew+uzmE/exqWUu7r93HyG/u498/iJNcfTUQ3JNTWeHj6JAdnhPxkgf4o6obwn9xcCvHNnyy2WMrYfS2LNxmAE6j25jl0MHVDloFsHwNgSDwVN/6drB3pm1KWJe0oX6cPWqaTXZZJysyfQwuryNqwPd03/C3pbzi2yMPLzIOHrGcZONHBJCveAPu/ARgxgrOJRVRqXBahgCnwiRae3dtvH/YKWE0BJ/2mXjlPr07wYTz0Zz021IZkYRv5dOdoH0OBDZ0rSb0SM7iM7Xd7eSh5D9fDDFfm0t+yGHmLXBZwdR6K95DnYfy4zEZjw3kGNylgL/NwrLJeNQcWk4lv1wGuykDrDt3M38O+iJPFvmfbLmWyAACzLrA+lL/vFznQXCVTcnUuvKBZBhi578OkwOo2wVXxmrtZDrMqpAAPiOzeezmYAFvn6GZxzPglPI63Z7JIcBe8Meum/4+2p4xXQNQTTfL74fjzCwnEJWzT285JFoF1WzY6uMUyIkp9G+7icswWDgiBr8djuNU6nIPbFnTydNzW+UXoZ9rfcCxzhG77CcktliE1ByCk1LjvwZ7cl71IskLXnd9uVCf05DQwbqtXROsGtFgI/BxA8SMKnhQtomqX81/7bS5zGA8gXDe1bQw4qtu+XvtAqQ8EPj2LX1Kv6UkeXu+6PmBrAKDuesF/bJjJMrjlCjRfjLVOT05hzvMoT2lI7n/fw2xqv64y2MsF3MJ7R03rl7CE4z8+A51EmlprJJA61dTrah0myvyhx8FkFmytH9sVbi8EnZriKFKznz2FzTJJ0frJuPjwMd7jOzCfnYT9JmcVeLWOyx3fbqET/sUc9Xn0/Exz8+KQt2eySG2TgWlzm9qGVyHkNT77sQEBV5r/5zJuMYfUViTaudoGgJgPT8/XtjFTMAyAQhSU3j9tyufbVWh4c4Kkbsx3KWzQCY4DCGtpyrLrWb90LV0Uko1ZrcYYFEjGKOAfAHDy4o/d5euFkVN8ANIMho4/s6zV207K2bV/iq3wOIFwjPO4jnRionnQ2hiZZhaGYTyOq5XgEsIHx4ks5TBE9XlAnEWOUgeAX5KWQkJknpwFSUHAe29djFlw28WXV5eOZGCsLJ1d04ZMw5COUzpM60Y8CseB6Z0vLlF8mo3ahsdSXNGUsRa4e0s+TOn9eYk4zS4bsrOd7exG9vZ4Fin6Ly/AvXdpsxzctVcKxiIMPKEQS1TU7b4ElNQFtbeOpNrPB9/6R4+lcGxwo7YwDDCTSZS9f3oqgUWP4NM2svfeBS8WIxSgme2B970A7uMnoD352Z09A71/X3b6iw/l73duy/a6FoFk395wMYfd3wPVNXgxFkam2R6wvxfaw6MnAo1uOxgNrCYaKAFmDmB4JOrq5lsfwGjV6XotMZmqBE+qsL354C7KD0+Eh2Pmg2WOYRYrWSqkCFCI12Dv3A79DZorkwp4KoLCATY+raViV6Got45EtPpiDvuOKMHz/lSuqe1GMZr1149QPvRBSfWunJMq1NM53KyG/clnoU/0/jsYDmrYH3wc+sUHe0DTSuwm+epyVcDNJrAnshTiAx8w/vBjnPyNX8Ot70WNkaHKkD9dYPHBEQBh4VaejfWx9LevhGuivHSoHzU4+bZ4C/f+71yWUkQj3RD39fsYJgWKDx+DfUC2+/UP8Mlv1/jaP43Fg+tbFconqxAjcb7qtJtmoIFRTko0d+uwv/vDL0OA8zl8FlSV4IXPOtQVhr4bvTyAA5XCqan/Axidj27JjTRPzwBrMbx3G+Z8if62x/M/eQrak8i480rTZloLIc3xIdyhj8zPF+D7t69UnXZfu4PscQmzakJ2Yrh/jMX7E4CA2fc4VIgWRHj2a7dBA2P2008AAP3X7koF5/4ezBMAWjW6WAF3bqG7PUP+wCt3qyDPu3ew/Oo0XOOs6zEczWA+A7qv3wMAZD/2sYC6AlZruHfvyM4+ZnL5nduoHnvOhguRLegOK6xuFyifyaT06b9d4N1/fg+2GbDwgjU0MCaPWxT/Oi7RFDlJbkD79TvIH0kmpn1XyFrWxwVmP/APs4/Qr+8UqE5aZGdyL+ffOsTeD6VsvPllmSzm7xbIl4zivMf6VhY4Gx78FuH4e0dwmRDhAIBtgKEA9n86weJ+hrteKoGGAc++c4yLr1t85UyyFu2dPcy/WqG4cGj3DfY+ii9Ve1hg/p7F8fclJjX/qkxux0+f4b2/+WP89B994B8soDkCjn5Y4bO/JmM9+ekErgDIAetflvYPjxa4NV3iw0e3UPzZBL/5O98DAHz0o28JhDszIM/fAWNw8hv7WN0mvMd3UHwqr+0nv13jX/2tf4BfO/9PQ6T+8hsOBz/Yx1ADYGHkAoDm7gCzJhz8xT7Ovxnfg/Ylqk7f3EKy59gVz6Lv5P+0VkJ1F4yNCLrEzEwmBW5bBEWyro2exeMnMHUlsQzvHWgQkMoypOzc5SXMbAbnFb30K2/v3RVeBl+MBUA8EF1vPrsI6VderYC7t4UA92P58tnjI5n8rAU3TShAc/MFzME+YGxIRYaiq71pSMcCgDs9ExLf+QJGPakLr77lPQv1OIanEqDLfulrQWOEu05e9rLwBVvy8Hf3j5A/fCboQ/Us+gG0aiTdq5kN5bYYhpFqW0jvGgKf+VSkTw2HFK3qfB4dgM/O4ZZL2HdkwuNJJZmZrpfCLP8Md/f2kZ8uhRqvUJ3RQf6tGvFkHkkpPgYH3D7CcDSF/ZEnoM8y6ZsWki1iIJCKArxXAz51qt7R8OkDXPx7v46D7z/zDxYwTEtkTy7Rvi8TfHbp+SwcB3LdfmoBAkzLKE8bXHxDznf8B59KCn9D65SP9uGqAuazkxDE5W9/Aw/+zRnu/8FluDfDnuf0sBbEUet0mOQwzYDs2RL9YXxG/uWf/i4uLj/98haSXbHXnPAk6Jmwaz1nv9cylRrYhGv77eR4FHgMhVKbxVmOv9ho0yhonFC8aTA0/fs2KYCUhGhbYVkYx5cECm0LbG/72W1ew7b/5broc/hWCq2/XyY7SeluPpPXtsMb/+szkASK+XlBSIZnKEu2OQBKH6twpM/BKdgFOHe2s53dyN5+zyIFlaSYihcJIyeuMhEJ0pFZkI3hfOMCMmUQpzyLvBHzhfy8kd+nqgzpT01fUVkERii6nAtICAAWS/CkHFMDloUIH6fViPBpTCtBx1GpMSRIqExfgMRTqKokl+/7S0vvnvtllC67gm7IVHQ7AATFd5QF3F4URm6OS9inVorD6iKMVQBlbfsSVmUs2CpySWfWZRR1rpMAJ1EkId6byD6rdRgvN6tg1r0EIqs8fFXXd0rYZvA8mH7pZ4WtOxschmkBm3hCPK3Q7+UojA19GA6mMOsWriokZqT71iX6wwnylfQ3CEI/yjC/bzD91C8vCRgmGcyqwvKu9LeyohRGLLoegLBwu4JQXDDMwFi8K/09KpOUrYlVvv3RBN0sx+SsCiX361sVLr/hcDdBYa5uF6gHFlAWA0Ml52hnBqYHagCrdyLq1v2rm/sLb+dkkWIXNjgdwi7XgLXC3/WGOAZDcugjbk32mIH04RoSbgiKgB3hgNhof7mOeqK6cb2GuRS0JbddILrhvhfuTGb0WrugPA5K/JsCddoOTCZcg8YseL0GXcSbL3yYkhUKKu8pu3XfR8i4kvbMl6FfQZOUWYSHPAS7OlkLj+YwiDapHr9aj8+v/KbMInSk17CKQcYwBkpgwzyOWWh/2AmxDTx4qhddWhpc6Hv9qIQ5X4Z4CACJTWQWtFjBKvcIADgHc7lCDoS22BCsMUDXwzbx/khfHTIgbLOqpt732P94CAFZALCrHOZiielDeSntRQtYCdibzme1SpEyzBYDiqdrzD7yE9ZiJc+GJweSjQbZ2VKQmZ4ICADKJysc/GAf2dkqTJj1wCFuAwBZrhycBah3yJ4tEcO2gOlujrN4OyeL1K6Dc18HA1dLi8R88c2Is8H/ztcV975AN4SsnxSAGKMgM+KEIN8H9nICmvKVQ8hrdSaFZ2l/VR80/ZuyQqfXSKqHunEe5ajYjJ8YE/ulvAjWxqItAC434WVRSQQ45xXcrhaikXMgYyK0ONVsUQh4KKQyUW9lY5/R/47HBViA1xgR7gyVDSBjou5KKp8A8T44twFKH2QdnBvJO0ibJo5Zct1EXrNUdUSIvO6IxeAh1zYzcJnoeAxeQmAoDVwGmM6A8wj9hurM0LjAka0VEl59LgBwZjDU8BqscQxU+wQOsTYkN/K4GAMukuf1JegO3v7JYpu9bDDnGlX2zy1TtBmAI4rBzmQ7qShy6Ms1s/6raK6+jF0JGLrxdk6285b+bmyLjGBj/MVr9Y+ToPCWv5M6lFoZq+O9hfnstbVj01MGHpNx8FQDjOOAI+GK1ikQA9hBr+Y5S4UkuDrqy2te0jZ7OycLMrjCnpJuu8FsORIFMhREd7TIKXgW6X0yJE0YM/Zotnk36RdCd7MmqpClxWihTBnBswhf86AcNi5dp4RpK5RYWxu/9HqN/jzRWxgXkm0qwLNnbgIQQUFZJtsH/5UqE47L4FlwZJ1KJwPvWYxU5xMFMGx4G5z5L32i4hbLrv115pmHhzsZT/+yDKUVtzv5+tIwBOEizm303Jz03RVZLCRT7s5+iCrqyXW4IgsSAFG0SUR7ghIcEVxhYfMMg1cDs2tRSYOL2qN9ZTAUBDNIv4Pwj/XeEY2//pxbSYPa6PG40qLbk2IxnYSGSsYgehQ+dVoa8ECwRRbkAQC8lCLZLhuys53t7Eb2dnoWqV1XYvsiFXX9wjf++Cwbf+2BACjaPC9lWVTdIiM/b7aT+/MlRLfIc4new6/RfR+IRDt0XM4+ZmcefeWskYzCOiHHgWR43KhE3fM7EgVezBHvp9dVSbeLhqmHj/dR61SyDuIx9FOLIs+k31oiziJCNOJ6TONCeTaWKiQSSLW2r8zsZSHt98nvWSbrdt+Wq/NI91fG+9XtWRRlDrYUysdpEElHU+RwVQ4b4gAOXOYY6gyZZh2KXErWfRt2lZRyVwXcJA+l+a6OVAPNkWig6Dj2E4tsnqPx5eimY7hMlhy6rZtAJAXJIFtkaI78+PvnZjyOBDfJJXPj9WQBgXA3dwcMkzwsRdqZQbYo4PIYGwGAbmZBAyNb5GhniWdhv4wxi0349+Y6ON0G7/IPIg8Q0J4p14JOAunvI07JIWHEjm1RVcpDrwGuPBNEoQ+AhXXm4EFeid4nORek9oSiPmZsqHe+Wa3M7ARa7su105J49J7FS7kxAJnk8kyi7trepAbvT2GGIdRQkLWyX5aB2AVqelPX0o8hxig4xAWk38pnQQPkhWaOkGQ/hpwyYKfWD3FZE2QbKaRwuSwAH3B0h3tR1iG3MHUF0zSx/V7GQ1CcsX0aGOgdqI9wL2KWIOgwgDo3LlHvBthmGHFnOJ+KXX5liqm/V9QNcJNilJJla9DvFaiOD2FaxNgJM2xLQO9gep9h6iIPq26zrWiP2pZhWwfbaJ96yYZsDB9nosvKRQ7cvRWu16wJpoljYHoZH52neaCw7+X7FtWpGemyvoy9PZNFMhHciM+iF+0Qbttw7KbosPwQKedHKdFt5xwGyfmn+feuB52dx/Sl9mfdSKlwmkpMUpuubYF11NcwF4vRdWo6VjVQ0omLux7wMncAZJJTxq8EIcqXc6Dt4BaLiDBsW8njK1PWM4F/Bz2R+TIyZSWSiSGlCaA8WYocADDCYPJyHcZ903Q8AITrNucmQJeVh8NWpeAn/L6264Upa7WG8ZBwQwT0g2BkEkxH/aiGPd/gs2AGNQVovoR1jCG5H2a+RMYc2jLnl8iYQW2HvXUL0nviHOyigJlUIK+UZgHYZwbu9Bn2P7o/Sp1ybmHmS0y8fGF2sUbmvQHbyjUMhYErDPLLHvnpErOP8ziGbVrDL5afLGBr4aMIqdNJiYO/2Ef2LLZdA/K7ny2sh71nixzVqUHxaA7qItz7S586TYFW14KvNOBp7RXwEoD45VIsQVUC7EYiPYFNK2mLrAEVRQQzXc5FrMaTyATBmxeApkjBXABomUUwlbrPHuhFeSZ8CHlcLlDu6eyU7q9FAJa52QYoa1KJhqvWpHisAhW5cDLUtR+uc9FR3ZuECUBTnVRXASwFAM2dCSZPa5m49uKDRwBoudzOlJWMR6Ak3JvAKI+H75+Av2wIyLr9CUzTgpomALfcwRTUdKCVCZ4RAKzuVZg04wmemDHUObKuh5tNQI8S9qu9CfrDGtmDIvTBHUxgli36/QqZekDM4KrEcFAFUJY7nAou4yTDxVczlE/9ODDgKovcAUtfZFfnJqRM17ek/b4i9DWhOjWYEoKk4P6k2vq8KiirPl+Gib+5W+P8m4xbfxrvweqdCjUQ0qMazGxnFi4nUDfB6l4iRJXfPGy5C3DubGc7u5G9lZ7FzvBSYJrn2htQdfymGd9wbD+PIrS3yb78k8U1oJ0r2QvFTrxAnSpUgm6eb1OI6JosTYjSb+xz5QHVfmzL6mzJ8Fzbr8H5qtoEELXlGpVSkGm7ghoTxeVJiB7SqN+pItwVS7fpz2k30uB0Sluof/NSf6Evij5N2mdDV3xldhTxLh7BmF7TNpwBMYMGN4qHXM8y7wSLE1C0sR+hviXB2zgfgBaldwTFd9YExTUTFVMc90BvaEjU2dPnyMjvHMYqbg/B9Vf8zrwRfBZEdAJgAeDJz7svP2O7jd01/yLYm3zNX2PmOzfZ8Y2YLACAiP6ImX/j592Pn6XtrvkXw74s17wLcO5sZzu7ke0mi53tbGc3sjdpsvi9n3cHfg62u+ZfDPtSXPMbE7PY2c529mbbm+RZ7GxnO3uDbTdZ7GxnO7uR7SaLne1sZzey3WSxs53t7Ea2myx2trOd3cj+f4vTPoEZtkSgAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.82555866241455 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 0.01, 'kernel_type': 'size'} is: \n",
+      "[[3.20025601e-10 4.80000000e-11 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e-11 1.36010401e-10 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20025601e-10 ... 3.20025601e-10\n",
+      "  3.20025601e-10 3.20025601e-10]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.20025601e-10 ... 1.40604841e-07\n",
+      "  1.40505123e-07 1.42058441e-07]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20025601e-10 ... 1.40505123e-07\n",
+      "  1.40873724e-07 1.42101053e-07]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20025601e-10 ... 1.42058441e-07\n",
+      "  1.42101053e-07 1.45521071e-07]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 65.13387775421143 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 0.1, 'kernel_type': 'size'} is: \n",
+      "[[3.22567448e-04 4.80000000e-05 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e-05 1.37053176e-04 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.22567448e-04 ... 3.22567448e-04\n",
+      "  3.22567448e-04 3.22567448e-04]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.22567448e-04 ... 1.41899267e-01\n",
+      "  1.41827517e-01 1.43112898e-01]\n",
+      " [0.00000000e+00 0.00000000e+00 3.22567448e-04 ... 1.41827517e-01\n",
+      "  1.42258067e-01 1.43220593e-01]\n",
+      " [0.00000000e+00 0.00000000e+00 3.22567448e-04 ... 1.43112898e-01\n",
+      "  1.43220593e-01 1.46862771e-01]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 64.90783715248108 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1.0, 'kernel_type': 'size'} is: \n",
+      "[[1.66464000e+06 4.80000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e+01 2.09238950e+10 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.66464000e+06 ... 1.66464000e+06\n",
+      "  1.66464000e+06 1.66464000e+06]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.66464000e+06 ... 5.47003717e+50\n",
+      "  1.02330397e+37 2.54020150e+28]\n",
+      " [0.00000000e+00 0.00000000e+00 1.66464000e+06 ... 1.02330397e+37\n",
+      "  1.18524950e+54 1.47231108e+34]\n",
+      " [0.00000000e+00 0.00000000e+00 1.66464000e+06 ... 2.54020150e+28\n",
+      "  1.47231108e+34 5.89323965e+44]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98abac50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 65.19227027893066 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 10.0, 'kernel_type': 'size'} is: \n",
+      "[[1.63905546e+054 4.80000000e+007 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [4.80000000e+007 4.54297144e+104 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63905546e+054 ... 1.63905546e+054\n",
+      "  1.63905546e+054 1.63905546e+054]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.63905546e+054 ...             inf\n",
+      "  2.22208084e+245 7.43749028e+196]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63905546e+054 ... 2.22208084e+245\n",
+      "              inf 4.88881601e+221]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63905546e+054 ... 7.43749028e+196\n",
+      "  4.88881601e+221 2.88079794e+274]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 65.39738392829895 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 100.0, 'kernel_type': 'size'} is: \n",
+      "[[1.63840007e+104 4.80000000e+013 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [4.80000000e+013 4.19766072e+202 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840007e+104 ... 1.63840007e+104\n",
+      "  1.63840007e+104 1.63840007e+104]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840007e+104 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840007e+104 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.63840007e+104 ...             nan\n",
+      "              nan             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 65.86875534057617 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1000.0, 'kernel_type': 'size'} is: \n",
+      "[[1.6384e+154 4.8000e+019 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [4.8000e+019         inf 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+154 ... 1.6384e+154 1.6384e+154\n",
+      "  1.6384e+154]\n",
+      " ...\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+154 ...         nan         nan\n",
+      "          nan]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+154 ...         nan         nan\n",
+      "          nan]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+154 ...         nan         nan\n",
+      "          nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 65.93991565704346 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 10000.0, 'kernel_type': 'size'} is: \n",
+      "[[1.6384e+204 4.8000e+025 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [4.8000e+025         inf 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+204 ... 1.6384e+204 1.6384e+204\n",
+      "  1.6384e+204]\n",
+      " ...\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+204 ...         nan         nan\n",
+      "          nan]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+204 ...         nan         nan\n",
+      "          nan]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+204 ...         nan         nan\n",
+      "          nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 65.93483567237854 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 100000.0, 'kernel_type': 'size'} is: \n",
+      "[[1.6384e+254 4.8000e+031 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [4.8000e+031         nan 0.0000e+000 ... 0.0000e+000 0.0000e+000\n",
+      "  0.0000e+000]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+254 ... 1.6384e+254 1.6384e+254\n",
+      "  1.6384e+254]\n",
+      " ...\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+254 ...         nan         nan\n",
+      "          nan]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+254 ...         nan         nan\n",
+      "          nan]\n",
+      " [0.0000e+000 0.0000e+000 1.6384e+254 ...         nan         nan\n",
+      "          nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 66.15934181213379 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 4.8e+37 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [4.8e+37     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     inf     inf     inf]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f548227f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 66.47152590751648 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 10000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 4.8e+43 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [4.8e+43     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     inf     inf     inf]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 67.11745500564575 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 100000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 4.8e+49 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [4.8e+49     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     inf     inf     inf]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 67.05007791519165 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 4.8e+55 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [4.8e+55     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     inf     inf     inf]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 66.85740780830383 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 10000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 4.8e+61 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [4.8e+61     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     inf     inf     inf]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483ec88>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.0395495891571 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-10, 'kernel_type': 'branching'} is: \n",
+      "[[3.20000001e+02 4.80000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e+01 1.36000000e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000001e+02 ... 3.20000001e+02\n",
+      "  3.20000001e+02 3.20000001e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000001e+02 ... 1.40592003e+05\n",
+      "  1.40492004e+05 1.42048004e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000001e+02 ... 1.40492004e+05\n",
+      "  1.40860004e+05 1.42090005e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000001e+02 ... 1.42048004e+05\n",
+      "  1.42090005e+05 1.45508010e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 71.89617776870728 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-09, 'kernel_type': 'branching'} is: \n",
+      "[[3.20000007e+02 4.80000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e+01 1.36000002e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000007e+02 ... 3.20000007e+02\n",
+      "  3.20000007e+02 3.20000007e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000007e+02 ... 1.40592035e+05\n",
+      "  1.40492035e+05 1.42048044e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000007e+02 ... 1.40492035e+05\n",
+      "  1.40860039e+05 1.42090049e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000007e+02 ... 1.42048044e+05\n",
+      "  1.42090049e+05 1.45508097e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.25595951080322 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-08, 'kernel_type': 'branching'} is: \n",
+      "[[3.20000067e+02 4.80000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e+01 1.36000023e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000067e+02 ... 3.20000067e+02\n",
+      "  3.20000067e+02 3.20000067e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000067e+02 ... 1.40592346e+05\n",
+      "  1.40492353e+05 1.42048442e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000067e+02 ... 1.40492353e+05\n",
+      "  1.40860390e+05 1.42090494e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000067e+02 ... 1.42048442e+05\n",
+      "  1.42090494e+05 1.45508968e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 71.75882720947266 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-07, 'kernel_type': 'branching'} is: \n",
+      "[[3.20000672e+02 4.80000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e+01 1.36000230e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000672e+02 ... 3.20000672e+02\n",
+      "  3.20000672e+02 3.20000672e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000672e+02 ... 1.40595456e+05\n",
+      "  1.40495534e+05 1.42052418e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000672e+02 ... 1.40495534e+05\n",
+      "  1.40863900e+05 1.42094938e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20000672e+02 ... 1.42052418e+05\n",
+      "  1.42094938e+05 1.45517684e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.39056992530823 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-06, 'kernel_type': 'branching'} is: \n",
+      "[[3.20006720e+02 4.80000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e+01 1.36002304e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20006720e+02 ... 3.20006720e+02\n",
+      "  3.20006720e+02 3.20006720e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.20006720e+02 ... 1.40626565e+05\n",
+      "  1.40527341e+05 1.42092181e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20006720e+02 ... 1.40527341e+05\n",
+      "  1.40899007e+05 1.42139386e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20006720e+02 ... 1.42092181e+05\n",
+      "  1.42139386e+05 1.45604870e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 71.62871217727661 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1e-05, 'kernel_type': 'branching'} is: \n",
+      "[[3.20067205e+02 4.80000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e+01 1.36023043e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20067205e+02 ... 3.20067205e+02\n",
+      "  3.20067205e+02 3.20067205e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.20067205e+02 ... 1.40938206e+05\n",
+      "  1.40845927e+05 1.42490258e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20067205e+02 ... 1.40845927e+05\n",
+      "  1.41250741e+05 1.42584658e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20067205e+02 ... 1.42490258e+05\n",
+      "  1.42584658e+05 1.46479518e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.4380407333374 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 0.0001, 'kernel_type': 'branching'} is: \n",
+      "[[3.20672538e+02 4.80000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e+01 1.36230659e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20672538e+02 ... 3.20672538e+02\n",
+      "  3.20672538e+02 3.20672538e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.20672538e+02 ... 1.44110815e+05\n",
+      "  1.44083170e+05 1.46516035e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20672538e+02 ... 1.44083170e+05\n",
+      "  1.44835013e+05 1.47117221e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.20672538e+02 ... 1.46516035e+05\n",
+      "  1.47117221e+05 1.55510707e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.19223999977112 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 0.001, 'kernel_type': 'branching'} is: \n",
+      "[[3.26773972e+02 4.80000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e+01 1.38330072e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.26773972e+02 ... 3.26773972e+02\n",
+      "  3.26773972e+02 3.26773972e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.26773972e+02 ... 1.82263456e+05\n",
+      "  1.82155788e+05 1.91537294e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.26773972e+02 ... 1.82155788e+05\n",
+      "  1.88403606e+05 2.01426343e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 3.26773972e+02 ... 1.91537294e+05\n",
+      "  2.01426343e+05 2.80271281e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7fd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.22099876403809 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 0.01, 'kernel_type': 'branching'} is: \n",
+      "[[3.92791759e+02 4.80000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e+01 1.61854595e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 3.92791759e+02 ... 3.92791759e+02\n",
+      "  3.92791759e+02 3.92791759e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 3.92791759e+02 ... 4.12634977e+06\n",
+      "  2.40213267e+06 1.48611620e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 3.92791759e+02 ... 2.40213267e+06\n",
+      "  6.40670947e+06 3.82640335e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 3.92791759e+02 ... 1.48611620e+06\n",
+      "  3.82640335e+06 2.98210874e+07]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.36246752738953 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 0.1, 'kernel_type': 'branching'} is: \n",
+      "[[1.79151667e+03 4.80000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e+01 1.09408881e+03 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.79151667e+03 ... 1.79151667e+03\n",
+      "  1.79151667e+03 1.79151667e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.79151667e+03 ... 2.29077996e+16\n",
+      "  2.15123319e+13 2.77853029e+10]\n",
+      " [0.00000000e+00 0.00000000e+00 1.79151667e+03 ... 2.15123319e+13\n",
+      "  6.14165450e+17 7.56027226e+12]\n",
+      " [0.00000000e+00 0.00000000e+00 1.79151667e+03 ... 2.77853029e+10\n",
+      "  7.56027226e+12 4.03693276e+16]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.35695004463196 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.66464000e+06 4.80000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [4.80000000e+01 2.09238950e+10 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.66464000e+06 ... 1.66464000e+06\n",
+      "  1.66464000e+06 1.66464000e+06]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.66464000e+06 ... 5.47003717e+50\n",
+      "  1.02330397e+37 2.54020150e+28]\n",
+      " [0.00000000e+00 0.00000000e+00 1.66464000e+06 ... 1.02330397e+37\n",
+      "  1.18524950e+54 1.47231108e+34]\n",
+      " [0.00000000e+00 0.00000000e+00 1.66464000e+06 ... 2.54020150e+28\n",
+      "  1.47231108e+34 5.89323965e+44]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.12744283676147 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 10.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.20485024e+012 4.80000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [4.80000000e+001 1.16851740e+027 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.20485024e+012 ... 1.20485024e+012\n",
+      "  1.20485024e+012 1.20485024e+012]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.20485024e+012 ... 5.07648502e+118\n",
+      "  3.16357486e+081 6.35807353e+062]\n",
+      " [0.00000000e+000 0.00000000e+000 1.20485024e+012 ... 3.16357486e+081\n",
+      "  6.82885314e+121 1.28006941e+074]\n",
+      " [0.00000000e+000 0.00000000e+000 1.20485024e+012 ... 6.35807353e+062\n",
+      "  1.28006941e+074 4.26463177e+096]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.53422570228577 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 100.0, 'kernel_type': 'branching'} is: \n",
+      "[[8.52505007e+018 4.80000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [4.80000000e+001 4.65743928e+046 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 8.52505007e+018 ... 8.52505007e+018\n",
+      "  8.52505007e+018 8.52505007e+018]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 8.52505007e+018 ... 2.94113691e+196\n",
+      "  2.04794609e+133 7.58744168e+102]\n",
+      " [0.00000000e+000 0.00000000e+000 8.52505007e+018 ... 2.04794609e+133\n",
+      "  3.10261971e+199 1.58976521e+120]\n",
+      " [0.00000000e+000 0.00000000e+000 8.52505007e+018 ... 7.58744168e+102\n",
+      "  1.58976521e+120 2.87326489e+156]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 71.98276162147522 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1000.0, 'kernel_type': 'branching'} is: \n",
+      "[[8.22482129e+025 4.80000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [4.80000000e+001 4.23856509e+066 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 8.22482129e+025 ... 8.22482129e+025\n",
+      "  8.22482129e+025 8.22482129e+025]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 8.22482129e+025 ... 2.20584974e+275\n",
+      "  1.53579627e+186 6.06655206e+143]\n",
+      " [0.00000000e+000 0.00000000e+000 8.22482129e+025 ... 1.53579627e+186\n",
+      "  2.26557067e+278 1.28192081e+167]\n",
+      " [0.00000000e+000 0.00000000e+000 8.22482129e+025 ... 6.06655206e+143\n",
+      "  1.28192081e+167 2.17582983e+217]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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TsxjBehaTsZ5FbB/R9SzGfdU9dpuYwZmBnC6VjhpX86wvXfdPLclePP3W9R53f2DpT/Y/lOul/k0Zbes0mMGJJKZ5ojbxwrUX3w6JclBMc7wu9OhyQVgACOE0BOgxTkMANI6wABBCWAAIISwAhBAWAEIIC6AHtuy4qfY+CIsG5DyxJ/V07CrqTH+epxqatPb6b2q3hXkWQI8xzwJA4wgLACGEBYAQwgJASBYDnGb2a0m/k/R66lpmbIdocx/k3Oa/cve/iNwxi7CQJDM75e7LqeuYJdrcD/PSZk5DAIQQFgBCcgqLQ6kLSIA298NctDmbMQsAecupZwEgY4QFgBDCAkAIYQEghLAAEPL/wbEblFKvk2IAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acda90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.18881678581238 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 10000.0, 'kernel_type': 'branching'} is: \n",
+      "[[8.19527733e+032 4.80000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [4.80000000e+001 4.19871022e+086 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19527733e+032 ... 8.19527733e+032\n",
+      "  8.19527733e+032 8.19527733e+032]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 8.19527733e+032 ...             inf\n",
+      "  1.49199814e+239 5.93162265e+184]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19527733e+032 ... 1.49199814e+239\n",
+      "              inf 1.25453797e+214]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19527733e+032 ... 5.93162265e+184\n",
+      "  1.25453797e+214 2.11598322e+278]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.04139447212219 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 100000.0, 'kernel_type': 'branching'} is: \n",
+      "[[8.19232769e+039 4.80000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [4.80000000e+001 4.19474442e+106 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19232769e+039 ... 8.19232769e+039\n",
+      "  8.19232769e+039 8.19232769e+039]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 8.19232769e+039 ...             nan\n",
+      "  1.48768531e+292 5.91828858e+225]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19232769e+039 ... 1.48768531e+292\n",
+      "              inf 1.25183119e+261]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19232769e+039 ... 5.91828858e+225\n",
+      "  1.25183119e+261             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.43812608718872 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[8.19203277e+046 4.80000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [4.80000000e+001 4.19434804e+126 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19203277e+046 ... 8.19203277e+046\n",
+      "  8.19203277e+046 8.19203277e+046]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 8.19203277e+046 ...             nan\n",
+      "              inf 5.91695675e+266]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19203277e+046 ...             inf\n",
+      "              inf             inf]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19203277e+046 ... 5.91695675e+266\n",
+      "              inf             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.06367921829224 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 10000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[8.19200328e+053 4.80000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [4.80000000e+001 4.19430840e+146 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19200328e+053 ... 8.19200328e+053\n",
+      "  8.19200328e+053 8.19200328e+053]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 8.19200328e+053 ...             nan\n",
+      "              nan             inf]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19200328e+053 ...             nan\n",
+      "              nan             inf]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19200328e+053 ...             inf\n",
+      "              inf             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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xl98YhtGFTURDJnqsg0dYa9cwSvr32ujdb9qvHyiJhmxKWUzYgxHG+mV7WOg0Q48t5qn3VpRsCPJfDd/yLdOxvSWxOkvk0MjvyJVR8p6LUHk5WaTllCJ9V0fo3OmYRIZQufY+iwJaz6apN2/PLaMXU/2Sl7nkdr3GztWQz/3bly+2W7iEXlZX6XtJ5owPe5+FYRjqmLIwDEPE6pchGssI3y8A9H2VmuR9mqORe5nt0mgs/4xfZPWWRe3DG3ppTO5FLCV1pV7i4q6rYy9c8d8eLXlBjAbSslPnhdrjZ5O2ctCG6kgd15Ajda9jdfmfW7+ESKOdmwydAu1fl1/6urjcW7/9c2Myz22Xtmdfeq57Tcyaay1b7TjoYa1oRWF8C3pTr9WrvVGuZnc95q6G98vWel9kTiG4x0tnwZilIkVDcYZmyVqLRXPm9+9v75yS1L1pZW35deTkSLF6ZWEYRh9W7+DUmnlCpn2rWU6y5EgtNUbIskwlAuWWDa3kD/VtznksTWiS1usfn+ry5fG/a72UMZ8F1hENCWVfSh6k0ozEFqT6JkRKGbplpr6vkSklW+yYW9YcYsqgJGEt5uDOyZjLuM35sCzdW0BrTR4qv6bO2rV/LRK5pe3Q7uNQpqakztADnMr6nCtbTg5pObnzc32g3f+b9Vm0diilyq5xlErl9Z14pbRcIkiY41TO1d1b8cbkCNE6dDrV4dZVWt9mlYVhGGWYstgxWmbfaPLsAyM4htfMZn0WPj080lM9gCxhqTbpZs20iECNRCwKopV4Jqm7tk9XHw1pRc+Ig18vcK5Hey0PjWZmZAtaZ+7Opbd8m4qGpGLYpWWEnGvaoVP/WO6amFe9d+jUlWWuFaaVQVkaOo3ltWiGTt3PIcUfOifXnyWh01i4VWPMmM/CMAwRq7csNGeF3MxfY7HE6oqVJ5mxe+daxNpRkm8hSdYqlcunxgegIVfOKg3N6tIweOn3sTwNjTFjloVhGCKylgURnQDwWgCnmfkVu2NHAHwcwIsAPATg9cz8BBERgL8D8BoAPwbwJ8zc7teIPTRnXM104Jp6XXIWykhI/TJLtaH3ngwpPaIhc5EsQ24H8D4AH3KO3QTgJDPfQkQ37T6/HcCrAVyy+3cFgFt3/w+H1PScazLHcv6l5q+WCS8lt9cg9F2MmOLQfiBy5n7quAaS1POarN2S8yVLlrljJ6ssmPkLRPQi7/C1AK7c/f1BAJ/HgbK4FsCH+CAe+0Uiei4RHWPmR2dJ2ZDWM1zJHobSMnoRisxIUqh7yZ3a5+HKvoRsNZT6y3q1pdZncdRRAN8HcHT39wsAfM857+HdMcMwVs5sB+fOiijO7CKi64noFBGd+imeqq5/rlb1dyK6G2w0NjXloh+hev36lvZPlJrwU1um5dYSPp/YRilXtlGIWWe9+y5HrbJ4jIiOAcDu/9O7448AeKFz3kW7Y+fAzLcx83FmPv4MnF8pRntGNlfXgvVhHTGFtxSidO+dz+JTTjTkbwD8t+PgPMLMf0FEfwDgRhxEQ64A8F5mvjxX/ojp3ilGmJliMfS5svXODp3IZSi2aFMuqzJ3PCdnLuO1pE0xf5FUnlj0h4juZ+bjEhmyyoKIPooDZ+aFAB4D8A4A/wTgDgC/BuC7OAidPr4Lnb4PwDU4CJ2+hZlP5YRYs7JYSnGkZpylZZNSOmv2jARpPOCatEgSBMqUhSQa8sbIV+c83Tv/xQ2Sig3DWBeWwVnBNOssuZ6MzSojyCZlZKsnxNKh1xYOT/thZAftm5rLxx8NN9IyspyjUbLvZSusfiNZDm1NXJrF6JPK7CwtK1V+jWy5cnOp6Etsm88dz/ltUpmpEkXgOz5jTs2SjW0lxJyx7ueackPs/ctvtJ18LW9GjSwhUgOzlZKqpWUadCmlD3LPvosppNIyfDb184XGLyIdQO6AW5vvYBS21m+mLAzDEGE+i4ry/KXIEj6Lkg1qc/0sU7naPota52APn4X03J4+i5hzfY7P4kk8cX9SIAfzWVSUB5x783ubpNKkrNh3IzByUpZUhl6Jb6tIylo7o0VDNOWQDKCRlIOPNOKwBCHZlr73UuukhJI8i723LGK0DvnlZn5p/aEB23I2kw5EibJqESaUEnqwcrLV9unch1fSZ7klYGk9EyU/BWAOTsMwROz9MmREUlmgmklZLU3kVsuHnMOupJy10EvW0M7TC+iI+HqzLHYsPbhi0ZGacnrkTrQqX8vnsqb8kV5yTvXUjpHVWxYa6/eQxg35BrR8BX5dsfXz0gosRUq2EeQuCS0vTSj0OiJmWRibYeQHcQ1sVln4Zpj2QMptIc/h+zB6mdW9lhc9cfswdLy3HKHPa9gVvFllYRhGGZtVFpMmj806GuX75Zb4Idw17HSd1CKZM0tpJnq5jrTa90No5BLU+IRazPLStrWyJqf6asfIZpOyJtyHsZXCcHEHaSp1OPZ3D6RpzyVJWal2a8kVqiN2fzW2fOdki93LmHy5tknqLLkeKEvKsmgIflHjTrSKhuSiIP65sUGydFhwzqzcaj9Nrm+lx+bUm5Inpkh7+Co0xsxmlyETrZYhU5n+MkRaV+i6XvhxeI1liPt5rlwpGUpkC5U7UbP80bhnJf2V64Ncm0rbuHllYRiGjNUvQ+bS0gSMafLSOktMSI1079wMVOOsLAkZ53wLKRlKZEv5LEr7bu6sHbpOupyLHddOTNusg7PVujlXfqljzXeAtXLGuvX5xOqsVWJ+2XNkc8so9fH45eVkkZZTisQvFhor/pgoqWfiPv5HvV8k68EcZTH3wYl1uIaDM+chDxGqr4WjNcWcwZ+KkpQ+nFpyuX2YsnZaRWlC5YcmgVRZGkoqVEZJNGT1ygLQtRJaWxypepeOcOQIWTdL9ZcrU86Rl7I8tCJcpcpcq//myr/Z0Gltx4dmnZjZV3NjUiZk6LwQPS0Ll1Rd0vV17GFuFfKOnSs117WQLh1T1thUTm6pmrvGQqeGYXRj9ZaFpgmZm/k1POQ5j3uto0oTSTSkZJbWNLlTlPgAUteUEuoL3+KtyVWpiYbErD2NMbN6ZVFLboDMNVlz0ZDSQTpiNGT6LldGbIkXu76U3EMpXUrlKI2GlIRBQ8QiH6HzJIoldG3JTwGsXlnELIOaMnJrPy2fRWrmnhMaS5WlQUieVISj1sNf4yxMfY7JmerTWmughphs0ntZa+EBwAV0xN7unaPlQ+WX71MSsosNpJ6WRYicU05SVsvQaUhRaS8za+QKIemzEUKn5uA0DEPEZi2LOWgsTTRkiLG0bFI0ZkZNfCtE0/qYSwuHO1D2i2RmWVQQWlMuIUPs+NKySRlZkYUoWWK1ql+7z0p+kcyURQUjPIgSD/zorElWYHl5W0wC9sPIDtqmeKi8Ecx919OdikK0yqbUIJW/IQ0vl2bzloRDY30XqyckQyo0LZHXL7dk7EWiIdvaG5KitbJY8mGriUaM5s+oiXC0oiZ606sfaxRhqAyfEmVhyxDDMESYsqhg6bVrSoYRZJOyJlmB5eVd2mdhyqKCESIOFg3pz9ajIXvvs2jBCOv9VGbiHNl6tk2SxarhE0o5MUN9Jz2ekzOXrl/SptxWhJw8MedxSZ7FJpTF2asuAwAc/txXm9UxUlQhRUk6sXEuqb0wa8TSvQ3DUGcTyuK+D5/AfR8+oVrmiH4BdyfoaLLlmGReWu6YDEvL1YLSNq1+i7qEQ89/YPeXnsm4tLMrRGir/gj+FQmjyBzzB6yhD3PMbdPeKwuNZJZYeS6adWjJ5VoaEymH2NIPROxejbJZLxSN6C2b5F62YvUOztqbFRqMoV2HtTNeyBOee+HKdI6kjJwX3C9LSi4dOfQ5dm7N+yNSfS6x4CR9HDtv7r3WIpS2L01Jl5Y9YeneAlpr6NSNDD180nJaz7TSASgJB0ofWm3Z3HJTIeZSWTQf2li9NZNJTT0TJT8ytAkHp2EY89l7n8WIpLztcy2GXmtaDdO7dBlSQgun85LWnEbdoeV2yTs4V29ZaAwKP+QYcgxq1ZWqX3p8dEYIgYYYJTy7VrKWBRGdAPBaAKeZ+RW7Y+8E8KcAfrA77S+Z+e7ddzcDeCuAswD+jJk/3UDun6GhcUMhR8nnOfVJLACps86/pgc5JydQ74BLfS4tp8RnsRS95IqNcykSy+J2ANcEjr+HmS/d/ZsUxcsAvAHAy3fXvJ+IDldJJkTDudTSsgjFtUPlhma8mqVJi9kz9ACnyp/qn0KNkshN7FitskwlV0mWNj0Ts/x75j7UufaU1uPXp7rrlJm/AOBxYXnXAvgYMz/FzN8B8CCAy6XCGIYxLnMcnDcS0ZsAnALw58z8BIAXAPiic87Du2PN0HAIxsKRGiaxOxtIchNCci1tMpfO9tJlSO+QtVtnjWy9lnghy7ZV3T1e2HsrgBcDuBTAowDeXVoAEV1PRKeI6NRP8VSlGHrLEPfBbL0MiWVahuQKnZ+rL2X611CqNOcsQ+Yq6BLZSmntT/DHh/YyxC/36kPXtf/5QmZ+bPqbiD4A4FO7j48AeKFz6kW7Y6EybgNwG3CQlFUjB7AOB2dslsopgxoHZ0t8xRd76HrNwH59sf505ewtm4RcH+bGQa9xUqUsiOgYMz+6+/g6AF/f/X0XgI8Q0d8C+FUAlwD48mwpO9AyK9KtI1aXP9A1Zj+t9sSWSC3qq8mzkCz15srRkl4TQijPgkiU6Q1AFjr9KIArAVxIRA8DeAeAK4noUgAM4CEAbwMAZv4GEd0B4JsAzgC4gZnPiqUxDGNYJNGQNzLzMWZ+BjNfxMz/wMx/zMy/wcy/ycx/6FgZYOa/ZuYXM/NLmflf2oqvl5TVymcxXReaMVPljrQE8dfNMdn80NwSpPwja0rKKrGWerVn9ene++KzGF1hSCj1C2gmuQH5zXta9fQg5BhPnVs7TkqiIatXFnPXlrEHNuTAq6krdhMlM0fMwumN1MJKWR0tKenLNSCJEuXOb8HqlcWcEGPpORrll1gQS3juJXJLvPMpage37/yV9mVqjGhFdEIRmZQcuXKkdebGjaYiWb2yAPKhMwmxCIXmAyuJHKQSt3LXtiIVqQm1KfSQpD7XyhSqL9d/0odH+95Ly6qJLkmUg4bFt/pdp4Zh9GGv3pRVYlnkNPgcK8Uv3yfkH5Fc517byrqQzj4aM5WW/ydVtubySUOuWL01y5PSekNl2O+GCHBTaVuVnzteIoN77hJya5bbqu8lfV7ynUa97j0L/euFRl2r91lozLJSL35LH0bpdUs4P30Z5l6r3YaaTE6tPB2JPHMja3PQqG/1ykLD8Zeasd1O1r65NU6vUZjjiW8VXg1FPWLOVs0wb64vQg9q7HOre60xdje7DDEMo4zVWxatliGh2aLHMmRJU7WE1Ay4VHryUslZW1mG7FU0pBd+jH+JB1ri1a/NOO3VHg1vvrSe3BLTl6c0US7kh0klaKXKSpVfK0/seiIS/27I6i2LpRlh5k8N+LVQ8hC2liOWhDaK76jWvzG3DZtTFq1nzt6DW4upX9Ymt4SakKqUVL+1yrqVjLEWWbN7ryxiacEa5bll9n7I3FmiJMFrJGUQa0OIXsujmDwj+I/mWgaha3u8g9MwjI2xWQdn67V9bbp3rpzR071LUtf987Vkc8vVtLpSjtI5lPRZaf/Grp0o+WHk1S9DWodOW4S7QiauW2/svNKye/hmSr9zkUYoatoRkqGkPyWJVFpoK9VUPf4439RvndbS2pkn2S9QUo70urn7Dlr1ibTcFg9oLAO3xEGogX9vfAdoa5+IP5ZK61u9ZVFL6zBYKlGnxvTu5UjtkTDVm54JWiVyjBKKlbJZy8IwjDJWb1n0NFO1ZvWY0zIkV+nsM0JS1pxQdeu0aM0wuiY95In4LMTXr15ZrJGQEtB6IJbIdNQuN/W5tJzRlEKIuU7t0npq+3T1yxCtRKvp/+lfqOyW63m33tb1aZCLhkhkb9m+mAxS2WJlLsUcuVM0/63TkVjjMiRWf+j4qAojJdsIs3pMhhFkWyurVxZrJJUDoJEzMrFUnoWU3nkWc7E8C8MwDAGrVxYaqbYtfRahnYf+LJHLAyhN4tJO8Cldjk19mJNFknJd2o4S2Upp7Xz0x4d7TMNnEUrKKvFZ7P1XsPRYAAABQElEQVTeEO3Q29xdp7HzaxTDHOXlm6Qa+yJaP4C+7CkZS/beSP0YKSXvl+Gb+7V1pOSc6kgt22LyTFxAR8Q/BbD3yqIF/o1bIp8hNeiWlk1KqbLrmb2ayn1ZAg1ZQmWUvClr9cuQtdEipJcqS7PMVF09owsl6ds5uTRSwd1z/b73+8Y9FvpXSm6prHlvTFkYhiHCQqeVrCVOP/IypCWt78/oS7wWmM+ighEGSsyBN1e2nm2TOCE18k8kDlH3s/R4Ts6cc7HWmS3xSfnyhHIsgDKfxRDKgoh+AOBHAH64tCyduRDW5i0wcpt/nZl/WXLiEMoCAIjolFTD7QvW5m2wL202B6dhGCJMWRiGIWIkZXHb0gIsgLV5G+xFm4fxWRiGMTYjWRaGYQyMKQvDMESYsjAMQ4QpC8MwRJiyMAxDxP8DJCmBPaFGSEUAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.30604934692383 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 100000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[8.19200033e+060 4.80000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [4.80000000e+001 4.19430444e+166 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19200033e+060 ... 8.19200033e+060\n",
+      "  8.19200033e+060 8.19200033e+060]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 8.19200033e+060 ...             nan\n",
+      "              nan             inf]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19200033e+060 ...             nan\n",
+      "              nan             inf]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19200033e+060 ...             inf\n",
+      "              inf             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.38939309120178 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 1000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[8.19200003e+067 4.80000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [4.80000000e+001 4.19430404e+186 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19200003e+067 ... 8.19200003e+067\n",
+      "  8.19200003e+067 8.19200003e+067]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 8.19200003e+067 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19200003e+067 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 8.19200003e+067 ...             nan\n",
+      "              nan             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.6570520401001 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 7.0, 'lmda': 10000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[8.192000e+074 4.800000e+001 0.000000e+000 ... 0.000000e+000\n",
+      "  0.000000e+000 0.000000e+000]\n",
+      " [4.800000e+001 4.194304e+206 0.000000e+000 ... 0.000000e+000\n",
+      "  0.000000e+000 0.000000e+000]\n",
+      " [0.000000e+000 0.000000e+000 8.192000e+074 ... 8.192000e+074\n",
+      "  8.192000e+074 8.192000e+074]\n",
+      " ...\n",
+      " [0.000000e+000 0.000000e+000 8.192000e+074 ...           nan\n",
+      "            nan           nan]\n",
+      " [0.000000e+000 0.000000e+000 8.192000e+074 ...           nan\n",
+      "            nan           nan]\n",
+      " [0.000000e+000 0.000000e+000 8.192000e+074 ...           nan\n",
+      "            nan           inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.41722226142883 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-10, 'kernel_type': 'untiln'} is: \n",
+      "[[1.10500001e+03 2.10000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.10000000e+02 5.64000004e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.10500001e+03 ... 1.12100001e+03\n",
+      "  1.12100001e+03 1.12100001e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.12100001e+03 ... 6.44397081e+05\n",
+      "  6.26337082e+05 6.76883105e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 1.12100001e+03 ... 6.26337082e+05\n",
+      "  6.10895092e+05 6.57917123e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 1.12100001e+03 ... 6.76883105e+05\n",
+      "  6.57917123e+05 7.23339242e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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1t6S1g7gNz5t99HneQxYC63t5AGKzA+YHkMKI/eZv3PdAl4dx4zg34us+HVOMsXRwcg9BOutCGNReZgaZ45l5g1xF4cfc+9QeJ+dhdGQGngfWMejcRVJaTv2HuWJmEHOcN16t5Vii5OTsw+8D6jZ3nYxV57EP/Q84OON4ejNOlcUye7mQZ6Bt4zZetyDq8uP0YfYMtB1ovgz9+NS/Mal43QJ9WCB1+2oFd74At126XwBZTHRhjiTLPjk4FwYXMsR8vkXu/2KhPJn7ahaROzLcVFUFIk7ELV1om4x/wuRZxDd9iDTE5By9oTVKYB/oqkpvYuYs+49GjVw4JTypqnhjESzZTJ/faKYPqqrM060ZhtwljSk+AGWURKM5TQOCLgYpmxNVBdIHbjyW8fd9IuvRhdC87XXc5Lx46aMWZ247HY/VLJAWj+jFZ4pjpbqWhcJLu/GtOhmn/k2UBr0PWppLCwsTaNTIm948PJlmkVqImkV5Drxeg0+PQaqxOALqGgQkLYIoRlloEuarCf2w+LD45Ei2n53L/NvrTzJW1CEao9d9PIZ/eAy6mEd6UarDda4CvUKI+tGoSQuF0Sww3/25OfgsDnKQg+wkxKX6/BbkAT3hn6Q/OfjblVXUjf/ixrR6Wb/NzWj1ruk4VR8CgGFaPQB3Cn3eddxb4NA6b1Z2otW77bFlA0haX9SEgBj5iCbGdee05OXYiYMjp9VTn1L82dDqbR3bkLP7sn4H7t1/wt/BGb/YaWLfXTPkMrDVBoZfU4xpc9s22UIrHyc/pPRmACFHe+Sl7ODNtvuGhSGCqtTuNqE0uz9vsDMhHadyjbByRoyiY9Ob2voiQsgv49sMIKnoTO066dczYJx1yelYAN6slA5sOzY7twaUFcORwWwCIL6NdRvn14XFIvpqnJNQMICNokAbkzNM2FudHEfHJ5yYS2IC5lykOj8AksO4acDrNdzpiey7WsfzInPefiB0SqMR3NFRntYefDkbQyeK4fn3j7C3iK0P/RZ2SB9VC9gHZ2E39Qg+CggGoO+z/vfKoM4IbsOHQa4JAJzQnFq+boOdOlss7k4b3CC6jX31IE6LMXM/iLOw+IJBBKo0da3QaVq0jTZg+zcM1rD8EuoQBtJDbRbAm0K2uetyJ6lqLBvOcZ/8QH0vC1vbijM8LBIarWGYe3/b+DzLAjBUN8Qu8gB4n4yxLfLuLhZ3LVsXlAJkdBvt61uzpHTLFhTjeAx9byMywTatoux3l+2lbKi7A4seLllAi7fvIKhMj9uFz4OLxavoM++/T//t4uSTA5wiyp9lPxtVupKLZPih9QGkFoV0ER3YX6MpurDpfC2GEtfC+Xq3pXxhC54NR7myuYi/cb4LgAO790EOcpBbl/uvWexDllvuM7g9hTwHcRb7jKuUAT9J6lZDubl9HlXujcI6d+Oz2GWMMOp+WUjHjpWceTMOtJPhU3YqMjSA/rSajPoBCv8K+mJ/HVtIkEuOxOv5LNxknDvCdRxDIe4tcG8NqbINwVpfGUzyoPos6kaS+konvE1EMz64SOH33vksVK5UDXdQZVXsjbd1gUkq6TAacQtEdycOTp//Zh7gmBsRcyUuMzWCWj3EjZl9x6YpYzEpdgx6cw2RuUZgj7abfBUbhXSYMUhJZ+aeje8jx7BsLpp6HnZsWsRHpC92M+ZFNq7w4Hibw0FStsBwcJbZr6VY/1OslVogdeHFh0FqUtoKYRrdAgd/ScjUVQDXQCSPPWJUkKoqf3H0fcb/ma53wIM4zWVxEglarTLUawbiu0Le/cXiprJtgSjftCWx7WUqhcktiE48vXfjql9vOs5MCjmv1xnkPEYQFP5swWbFwgKiLOU7grIC3bui9nKK+AQis+ebwd41tFiiK0O7JQQbQH7jqUN4yBtvWJoycJUuyLpYhFR4vcl1H+6L4xQRahZIdzxNDkztN0SVJG2bJAKjv41GMdKg49LoigXFKaKS6tqA5hS818E9eAyezWynsj2An2LKOJDg+Br27Dq5F44ElOVfvhx0uNJ4LGNdrZLGMZ3CPXoIPH+R9tM51fvFpXmNWo2hMaB2d0/E+7tYXGWexJssoR/tDXkZYWuewNQPv4WUF6Hgs4i4kbbLUJU2ZySOx5ocdhELarZGJzIUquUqcKEPb8J4fXqDs3cbyE5FUAKIKEptN24fjeJDniFGtZ0h7UvnQz/rf5svAkQEadQ+dB/i7DhyRaVyABiPQRv1O8LD4cUEyGDZdS35OusUrkTTCDLUtktyLDV1us6KxO096HgKKI2iT+NMCM51RJRGnIdzsk1DpceSG4Szs0EItvBZOFDXgVVrGI/Ap0eg12dpx+lEUJqGM0TmoIn3KdkSjntEpQ4OzoMc5CA7yTuP4LxVuQroVar72/azovj7faqf62+X1Q25ykm7T90Qq65fVjdk6PtQX5chFK+aX9uebeeyFPGNZLot6FGt7r6tjRL5OlA3xFZAt+ZA5pQNY7D+jcG6IZrRa30WZUq9YlOuUzcEonF4k0k7VLUsjrdywURJY/j19u/hzD+/5wjOm4renPZBLrcDyd5XGjs1Q7axc+tNEvfr4EYN/Cq/eWk0SjBn3WZSyP1imd0gTm3WYPvGtPehh91VWcq3jQZY2LD6RbjtYl8W9JUVt2k7AF4QgepH6AszJGx3R0fw83kYpzFDgv09OG06H0g2M41GcX+ypommnwMR4ZglqIVkr9IModMT8IXxHej2ppYoQ1XFcet5UFPDh2NoNEpJauNRBEpBzRJLwdcIyzYvV5Ki/iqkqAczZAOVeYkZwssV6OGpTPkPPhsohQi401NJJDPjp+kE+PgDVN//NO04DYlxQ2bIdAJ+dZaS2ZhBz3ZPUf9yaRaXya6ahd1f99s1fHvbmsVQ+6VmcVX7Q9vtGMttwN1oFtvajlGagchN2cVNNQszf7vUOtVQpl0IbX+3qVkM8a5SeDnsqlko56ldYA+axZdF9l3Yyu9vkiVsH9klEetNym2yaF17CJtYkb3bUFata8q9Wyz2KjIEZG+0S4sMbcNfXNJe/G5/vqzI0LY+r/rtKsm0gR0esiGbuBltz9bdGNs1kGqD57od4rzxPWNQH+7/yvtiqITjxrYhLEdxTGiLPfIwcrlra7kurxjaVeULDaObLTJ0VfnCHNqt4fxNCPgu8vaXzIMc5CD3Qu6dZhEBJ9tsb2CrH8Gu9Bn3BUIc26QQ+9Uqt5e1LwQHm+HqtI66yGV5dCR0Z8ZepbqODsgNB6fWjQgxczedSpsx3Tk5XqkZJc82kMBTTR1TsAHhh9TjY10SBRWVDs7wdqwePYxZjBZERaMmbncPTqVOBnPG+cltl71lre3sJqnSuB5DVZU4LdUBGOZSnbduOoFfLMFdC3d8nK5VAIBlDs6HD8Dn55t+ASLwai3Q7lmqEeJOjoFRA//iVZy/6OAsODhRVeL0nC/itQSA/mKG6sf/IPD5Cz1paWO5BD16KJsWS9nfe7DiKQKbFy3X4Nkc/NET2f69T5KTWOfPEdzpCahp4F+fxd/rr38N3Tc+RPVbP0hzMBmLEzamC4S5GI+ArgcvFpHvFQDoM8OfcoXcu8Viq2wL+21Rswa5J3fJMg1eeEsFL1GPcmHqNun8uzxtWh8e9oHO3XJwFunJKWRHcmy3mabNbZcp9uw5Qo/jjV+o2aVjjperTQ5OzxlPAs8XqT1beWAo98DMR4KId/F/iUJl5uxa+EDWCzaU92zGY6/jxUz2GfLF9H0EpGl/vFoJn6f2vV6ncg0DRYbQ9+mlYMZNL15nUZYI/gqFh7IxtW3cJy5I6xbupbwkfEhZzzg4vZM5r9ZpjAD4/AL1Z40QGnO6x4QgOJyr9qvlG9ZtOi/PERS3i9zPxeI2IjhlyvSWVOqdjh/kxjAPgUk714sjD1WxOGT5BdvPcWOs1gdgb3DzO/ty8VSNqUwdtzkYCvfOuRkiDyT7PMN5G+8Ce4CTlz6SIpf5HgAIBU+GJaiNKepprtghzVV4kBTiLacZFpVA+muvFQe0aRY9UHu+R77dycJaEgyDWRbY7EUQCIo1StH3YK0Qpv6zysW2uOuAUFzZEuXY+eO2A/milkjXAXbhBsDeZxXQOBIX94mM2ZIX7/Es3c/F4g1JzDq9RtQghrC2MGYNkr+UNSa2hQi38VzcsmyMUb87F97uqfYFs55r4pIos05vUiskNLC5iUgWjGycLl0zZRsrQ5fRcWryfK47p46QlR/QqIM+qJc9kHFchaO8cilJ75LoBxEJm3mxLZYvvEU5ODgPcpCD7CT3U7O4CvC0SxM221KzQS0HgWWuMnDgjVIA24oM1XWseWFhwVTXkgW5XKXkqa6DG4/B6v8ACmiuLTIU+m/I+BsSCjVzONoiQ9GZWmSdFkWGaDKOdrXltkTTpGSzoykwXwBVcvQRkNPLlfOtmaJAzjM6UGQIRZEhBL9FRH5qRi8LWlKvvDs5Bs/mGxoaARHNqoWn4Z04g8emyHNDWSkA62PaVmSI+x54/FBqhajUNbBcwj0QVCars1znF5AiQwDQ9YApMkSL5UYmLhxJBmtdg0yRITo+hn/6BNQlnxk1jSBGoxao81qBvQetVlLKARBTp3tDWadE9F0A55DAbcfM3ySiJwD+DoAfBvBdAD/DzC9v0s9mxyF9u/ycDy5d9CE1sCAmobqWfUM24daKZEhecyAsFiOzWOg+Crs2DiSqa0lFdiRVtpXwZOYlWxAAQkUyNA2gtS7YEON2iKS4sWV9sEZNTHUGANKK2exjlMTbOh19HxeXuFgcTYFVuIGCY46qSmDEmhH74DQ+SDaDkVarQagyOZJz1YcyVhYbpWtjMzWXS7MwHUW/QIyiTCZhQfHyYKov48nDSHKbmSF1BVzMBPK8SuQydDSVeT8/T9dsGtqu67wYTyPXzumiENLPabVC+9VHGOl5e5aaII7gP3ggXZ0vwKFOSP8gVJ5rKvjaoZq1qF5VWH9V9m2+eJEefDuHp6fgyQhu3abr/vgBZj9yitNXqYI7H09B5/O4GLFG9yZjqfNyPgefHqWxnu++BNyGGfInmPknmPmb4fvPAfgOM/8YgO+E73cve6LaiAo7802IKxicivFsfCeX7N63IXvMz15zSW7v61V0dnl7arMPzN3Gdb9k353FHuqKtrfMCxdjYPU9DPkwrhpbeT7lb0S38qTfhRnyLQA/HT7/EoB/BOCv3GoPQ5GIAbqz7H8hkRgmRCsiPmADreg3QrK8Xps6oyyqaXGcbPOZGcLLVVLxuw68SFEBxS3oTa/qcvTAW49378Hz+WbodLEUlVT3a7sYstTQHtuwGXtwQRbDr882PPLsusj5AAB49iKGPTP+CI1cRFNOhxfmSPsOyViZ2RXLA6zz8gvKBOX7ZALYMHNVpTfxp73kSTiXTDyfykvycpWdmz+/AK3SteT1WjSPgfKFICcmgs6DXp++x+g3P4M/O0+7VlJuUK+FEu/AM9xL0Y4q1UyZwasVxmEMfrGMEZ0Uwmb45y9iIlu8hp8/w2nXpyQ2ALiYSe1c0rIISn4jmqRftyDVXk0FvF3kposFA/gHJLGw/4WZfwHAU2ZWlMinAJ7esI/ryRVmSPJZhO/Bpo7b445lYhNldSl4HUrzrdOFBcRU4bbLwqNUuWR6LDhPO1azRVX1uo71Logp96U4AlEdF5AYbShBWcEHw22X9SWnJeQ3CZQV1P7JONHo26zTxvgcjo+kMDJRssE9hwfdb4R9KbBMxa3B1HNE8JFzNAdlqfnmxmN4z+AAdtJ9oFT6pkwhnRynB91wiRIQ6eSyYsejkYxfM2ir0ZWgrHisgrLaDv7xg1j/VX4T6jsKPgubBcrTcP2bYPauW5Bz8E9kX3p9JguhRpwQtKGjqYCyDAUfHR+j/cpDNPNF8i9NxsB8GcxX3gBloQBlYfHmmLJ+ipk/IaKPAfxDIvo39kdmZqLhIhdE9G0A3waACY6GdjnIQQ7yDsmNFgtm/iT8/5yIfgXAHwPwGRF9lZl/QERfBfD5lmN/AcAvAJKifpNxhAY3zIXsf7l7AZryQ+oYOYDLAi5BrY3H82BaMa/Xm3H7rhNnZujXmhG8kLdDVMe7LlOFuVD3vQUuKbJy7ZMDU88xqOCRpzZVa89yAAAgAElEQVREdpgpjD033/xsUWhSLhUWVm7P8PYTAJeq9QJ+slEL9HK8ENK2yVxarmJxn4hGVLq/WDVd9vXzlPgXYejFGz8WO+5fiZlXVYZzlBNnhvFXMFhg0Qbg5dsVyAWEJoAclEUB3apEuArJ7kGffpHxaHDg4IgmoTVnziwnh957a1AX5mG9lvsAyIBn/Po8MZHr3Lx8hcZ7+FlCj/J8IRXcg0YRz6CqZHvvQWZ/dLsnBV57sSCiYwCOmc/D5z8F4L8B8KsAfhbAz4f/f/e6fWzvPPBSAiE02A3Um7zcDNFcicglOZ1m0YH+dZtK0cUbhCDVt0dRDfXzeUYGo325k2Pwus1g5W48Fu87kdjLStK7WMB98ATwHv0Xz2TfoyO5mcdj8LqFmyTyGhqP4WwY0IQZbTTEn52JWr1aJXIdHadGQzRKEkh3qg8ep+pYhmeTxol3E48fAq/OQb5PKi0zeLmEv5htmHKEKsyHCc8GB24kujXRELbRkONj8GwGv1zBPThJ+4TwKjVNnHP/8WO452cpAgJIdESjKU0D/zLkgTgH9/gR+OQI9H2xml01yaIhGIiGsPJdhmiIf/4Cq3//hzH57S/irjxq4M5n8E8l34MuFtG34h/KdejGFUAEt+pQvZpj9Q0JnY7/xb+T8KZLzlGqKsl7mYxQffYsXnf6xtfw+o98gAf//Iv0wpiM4S7m4LoCeQZrVGQ6Aq07uDIa8r28xuplchPN4imAXwkrdQ3gbzLz3yOifwrgl4noLwL4HoCfuUEf20Un54ZIxgwH4Qt7+6YoSW1PtYXwxuBwA8cxhFyHHJYtb2oqIMpZYtsdCNv+ou2seRhGk/HhjWzfmvomtE7UvPG03SGPDe4i2p7OKzPYohQ9kuPTRnBVQzN+AGmjgD5fU8jn1xN6fdWP4Blcmd90mwvHep9W1kihkMbKfT88VcwgDykXaTVp5jSmKzTsvc7zXWfKGqyiPsSDCcS35Fa2oazhgkyk4IKk4NSzLEQAsHOl7bL9ONZNCK+FGzsDqlKHXFlRe68CzftKybZlfzLjVI2rrMlKTW0wJka1Hkgw2/scthWzNv0DwXlt6nRw10YWLaXnH0pGu+6cUjPaYLAartGb8oRKrs9sXIBce1NwaJAzwwXGcZsvYrXgcrEeuHf3qaJ+gHsf5CAH2UneXbj3ZRyUpSagxXh0Jd2G6rRNFPyIVI+hxWWA4FAkylZoW8vjKri3m043MkljXQoi+NUq05rc0ZGooBo6nYzFGRXChNbHIjUkDKO0IR22cG9v4d7qH1GcQJjDEu5dnZ6mN6zBMsi5h3M7mgKKB1AtgoPDs3yjBk3FTRNcXOeA+36jWFFkQjN+GA5wb3376tt0I3R6fCwOPhs6VbPNYB3kMjHo+BiursRhq+dp4N5ZmHUL3NvP53A/+vuAZ6bQT9MIn8VJIuyNxZOOAuK1qaMJwrMF+KsfyLGffJ7KDzaJlkDh3t7AvauPPoD/2kdwv5f8JcqlEX14sbBQA25b8cOoFuMZ9HL3JeDdXSwuk21p5Kp67mAplGpi5FiwbbmkMqYdGeAebCIRgyXnLIhJU9S7TiIi+l1NC0cpGhJzDnwE9+h3O/bBCEzX5rBzFnxCjNjo+KWReIyVjJdBx957MNoEOX/dJsxCEQ0homQOqs/DUTpXQIoIIQDP9HhjsthxWtq4K6MhwaGsxYN03jQPh5mjoxddJw9V5VJERsF2toSCTiUQOSEAZKA8fPZFVglNsSIRe+EllZ+ZQZG9vYYPcHxer5NPQu9LR9li3Z9dJMJedei+eg3X9+KQ1jnQiJSCskyqejQHzTXmNxENuXO5ji9lD04Ka3/HAr/2OOO8s7wO8sHY9VohrNRkbJUyywhduaycHgDZbzwGcaqvKjdcutlUZKxb7GJTHhEID95QmcLimHge2m/poAxRIR2HFOMVlGAEixEJkQzMA683dniAo38slvIbbSA4dd4s+5ciOKMWoahNH9C12t50Ig+0cynnhwiYSElGsmPjwPJlmbYUbLcNwdnU6XgLyjs5ESej7lpLUiIdhUiRgusAyYcBQHUl1zs4velEFjF+LihTCpoTAFDfw03G0qdBcLrpRIBfL17GUgOoKgF6UeivSGLkLgH0AIAu3hwo6+3LBgHMjocVN0J0DKlaYglrYlfWs3wF+c1AQlVgVIltaflBILw1DUoxsRkNwNn7bTVFfa7R6DgVGxK35cdk4y7wIeRIhq2qMSAQccVC2AhHUHuHvGU5QUvQFIxGFssVFuPkdeoj1TNJpDnINK5ZetCNgzlm77JPdTugmkpijopm44BmAeica6Qo3Qv+5atMc0LV5ixgKp5BVYCJK99EeHG4V2dpDPF3g7NYrjY1i8US7tmL7Jor0Q+ryZVVk1cmM0skvHs06J1fLAa9ykC6SbObIvcbXCqWBIVNbctoMrTxt41jdtAsht78WngXgMTybaEig6MAMFxEKH6u7k6zqGsTIjXe+6DGA4IXEfAQpcXNgNU2clZClMSq2ELQsp9mEe3voOVEH5NqPNNpSAc3xDO6f98DzjDDe9EsYvsAqMK1NAv36CG8yc+QaIwTTQfI/SWaOWvNzdUKdBw0C03Ht9E0z8OaxXgM+uAx8Pxl1rel1YvtNDXQdjfSLA7RkIMc5CA7yTuPs9i5kA6w6QHfVYYYwrHFL7Bvuzvv6/I3eUn1ti2r9rblsjFbbawsq2i2Ry3NcmYOtbUrZuWysW3BsGT4CzWhTPTHZgTHOd53PDoEJeOxY7rKb6bjCfiPcs6sabx1bJrUiNxcHjajMHjP7IOzeOfNkEG5qhTALmIXFnKSKWhCTRI6dQBxdgFjmLaoPVpezFjQyIKRKKVOc+8zByeNx7BRC3U0UoWgDiczguoGEemXdbrFDOEdzBCfVNsN0liXbkoZW5PYyEMGqdYn1SiO9BX2t+o9kJy8mn6OHR2cI3UO1snBaVPUp5OQdzKcog4yuTZMcNORhEPPLuJ57m+GrFF95WkKv4bx8Wq14eCE58hSJfdbcGKuVqCHQn7jn71IjG1dgHsTAW68kaJePXwAfPgEeP4q3aNVlZzPek463kEzZPdap+/+YrHPG3SoAPLQwgLz5u4hE+3qPOTq8/Bo2Cired0kCPfaDxdGNoSr6canhHeYzyXNHID3DBduPpu7EQsb96Y+RoBj02gUU8kTVsSgJ0O7Ss8X+1UchyIHtZ7ISrQxGo1M6nt4kIliiA+A3PD6UFK6GTkke5XhWABwdQ2Ofh1x7rnpBB5aNyT4I3QhMh5/jyW4NfuYdPnMN3F0lNLr7UI3mkSKwd6EON045KgoTmU8TohItf3j9ayiv0HHqXPMp0egpckjISesVOqHoKUsDkDEOHAl+Su0WElE7ighODXErsIA3OPHoLqC9z6xlE2n6J6coHr5Gvoyibk6Sqeni+Z4JOd6MXtrKepvR0ocfrltlyZKr7vG1/1A2/Z7ABNlkQzF5hce+IzSPvSh3zJCG/YpKczsG52GNpqhY29zb3tJkKPtch9+KwBcukiWMHq/Wm2EjFNuSOjvYpZwKfbtq9GCgWsR5wNI41xisy9L3Y+wuJUh2ZjxmptBfH6+MY/yVm6FCMjlHKF+tUpZrkDIjE0aSzY36ryNi5FPC9WL17H4kM4jdx3cmdYNWccs0EgiFMLOvG7lpfAikf8MmW2sBaPMmPzFDPUP6gzjIbVNUp2S2O9yCTQjiWTZWiF71A05ODgPcpCD7CT3U7PYRfZ1AG6j59uyr7JT5ccm7SJqFdk4DBzatmHf2mWb24Zg91dqQM857sCbQkYbzq7cRIoyGPp0qfgPEFnLAYNLiec8PO9Wy4rn3SdOj1hjpI8HxO96bDzOlG3MCjUZLSRuk8aTNmjH1xcFjZgi1oIMzkHa4WgCxnHq98Uyx9UEfwcb6r2IpFRcQzDhIj1h0A62ZVFHCLz9vW2FXtH2rVpXyfUa8C8byXJ7PCcHzeKeSgZBLyIo2T7biHHNMZfud8cS+zdjilT+9rzexPg2SH/JUOpvcaC/oXmzuAuqjAN3H6mqG5FUv7+axWWJaIC5yCkJyzoSbRHl8jhSrzkQixeXb7QE9rEw4JToxVlh5IQsTIQzITlNiX4KEFisrwF9w1JWlwRAqk1ikKElB2cqiRD6HY+TT0HPSdsN293JMfxFynGI0nUbzFub84FU/8MUlE7gIUk4Y/T5Pr7LjlMfQhalOT0BDGOVDFYeLF4GDk6bSh4cmv7Cx3FpGNQ6isGc4NKBbDhLCPzgMVwg1QmTK8WuT1MimcKxI4I0EPTQciXX6ZFEQ7aWU5hOhZBnNksgtJNj4OmHcPbeG4+FPMcuvICQBDWNaE2GSzSWfdhB7udisS10aheHGOYczkC1FcyB4N3uEiKR23VyWJZoUX14II5Im+Ogaqobj2WZsDenqetBobAQAPi+TwxXmmgUapFouM4S62acEUA0PbK6JIBQzDUN0PtIrEtxMZKHP56HzsPRkdxsMCprVaV6HgDowSlIw3MGPk2rFbw1Y4zE+QifAUhkQGH2uuhofZI23ORH0xiW1ePoaApuW2EWN6FifPBoA2oeCySRA0ZNPLd4rpNxZMSiURNrklDT5A1VTqIbarKMx9L2aoX2a4/RaEIWs7B0zRbwHz6W872YC0EvgP5E64Y4cFOhuljBvZ6h/ZrsWz9/iaHllh6cgEeNOGT1HB4/xOxHH+LktakbcnqU1Q3RF4cP0RYX9oljffW+Z52+ZXnj9UZ2lUvqkmRiVee3WZcEyCJIO439TUk5L9sIgd7GvXDdPvUUrnn8wWdxkIMcZCd59+He15VtoCwgx0TEtOkqj9tvg/4q2CWCuvrM9o7dBxhvmYgWzYm222gDQFIxFRVaIlTDZ0VxAsZnQbnjizVZTRGBgEkuS+PUMUSw10ZqPmV+GSWkAZCleG/PhhUzI2tPt0VwFaXxKNYCiMV2LIVfPK7AWbjjaY45gOIsEiVABrQajaT+aax1Wqf08pCGDyBhKijxclDlIu7BPXoIPr+wnSZCI53zmJbfxH00nZzXa/E/APDPXwziLNzJicyFaQtVJUlszw3xjoLaIoIzJQLSZAI/m6cxeMb/8fpX8Lr74j2Ge+8qCsserIVaODirSlwcEWs/vFhksGQgpB1X2Hg8qio6DeOxha/DFg6K21cGYRkfhgEHZ+USnNr5uA3W1g5kOgzkPpawsIhDN+V7sHdZMaAYFlXnnm6fjDPm79hdOJdBNdfOh5530wC8jueruQ7MHLkxqK6lqI6tdNY0INfnyFZA/Ailc1Ch3wq0sotFIMlRoJR+Z+ekLcuqVYXoTJ8crwo1l/qwBgymURzrSNzi4IwPs0LDX1V5eFSbHDXyArHnPGrAD45jrdY4B2YM1sHJJ0egto31aeE9cL67SfJ+LxYl70T2Ww7lVoiyQrS3NhmRhsmhqWjLDMGpiFDzlo1p7/a4MIaSkDVxPfjN8wjIy9yRGNCTfbEfsIGd4B7QnJcs7s5eUqTL5LVABKTb/cUsjb1EkW7DWeh86Gdtt8B7sOsiyxOAiHtgz2nOreZj38KvzwZJd1kXRtfl12O1yss1BJh5rEgWFhFW5K7Bw2Q5MM9f5hpNwFl4cw4RZ6H7FTgLjWjYecrOYTaP+TTxHNZrELPUeglCy9UgzoKqCtR78Gyec2/sgeC8n4vFLtGQuG+hWah6WyRWRfVbtysvgjkmq+Og1anXIWJR5EO4UbPxQNvygn4+TzyOa0SVtT87i+MZyg3hrgt8kKMNCDfVdSoniMDBGdT/GLJVdZ4cYPgolD3cHR0lKHfkeXB5mPPhA6mf4VyuWXSdqPQDN7vOh44TCBrKsuDgHEl9kqhZjBrZR00k3dZ72cdoFu7Rw1TXI24koK5TbogJrbqjI2DURC4KiYZItXE0oxRZCZoFNSOBXYdxwpE8xF9/CvdFMgVATpLDHj+Uw+fbc0PcYgWeLYAPpW6I+94nGyYtANDpaUh6O4+hU/f4EbpvfITqtz5J+02nEt4dyA3hUSOsXJqHAgDLN1tF/SAHOciXQN5fB+dVsg1DoXIpoOvqFPXoMM2wH5RrNKaNjfoopcZUOmeH+Aou4XHIuCiKY+J5IHdE2tT8jOXcAqzKuh2XOYbL2iwDtS2UCzUHj3F2Dln9EtN/ZAYvJZohBWN3XctvnTotqzRfA0C7bBu56DCtTk8HzZDotLbMV6oJlWZI0Dj7i9mgZkajUdo/zI0bNaDjo5RiD0QW8SEzxGYyq/z64n/D6/7ZwcF5J3IpOcwVqNE3JZH+L5C79OYB680+7M2D9xbGaWQQqi4fsBNd++0ORh7Mkuyn3M3u8walnKudjyPadMTvIe//YrHrA7zxBr7kBjVvcOZQW4Q3b3ZJfMpDp1kUxbQRt0fNYksUR5sK0RtpwMcxZT4E1SyIzc1uNBqTfxGlqmIURBO3IpQcSfuwUPA4JvTgMllrYz7SzW4h5FFrqJy0oT6LAFe3C56GTjUKFPuYjMGLQlOxfJwloU1VcJkqwY36QuJ5VJHJPNWQ0WvZSv3aItWfYSIfl4ROad3K71oTZT4fDt7VdRirTyt7I4hgysoQNOKoHQidoq6FZ8PUesHyEA1Jsuubftes0xCZsBmjMQpAhUp+11mnBZEve7fBaRH3s4uZpV0rFrk3mnWaOYD7qAVZM8RmppZ8GHeSdRqiETEMrO2Qw2DWKfBms07tNd8z6xS9z2u9AFuv15C8v4vFLlESAPsnklGqLwFIElhTbyRQ3XUimY0ubEskgxbXsTkgBsBloyEaknvTiWSIzF1hzCGRLMMzhOI/d55INhqlRDIbqRlIJFOchb+YvZFEMnd0FBPJYgRv30Sy8Qh8dpHjP9a7m1GHaMhBDnKQneTeRUO2erw3drRqd1CZx2NoVe1rOyKtVz/25VI0IVSc2qqZ3JaUjtahaIf1rWxjsA7tuPFYsBbXZLi+ltiokt08VBn9LivHq5gq7bbOSWQBt4CoMHY3nQhv6q7307ao21Us9uG+o9Eo+hz8+fleTnU3mUQ8DSBz+uvt339/2b23Fh3a2HFzAreh4/YbwBDHpLGbB8hq70RKRvOh81I/xmXnHM7Fr9ubz811ZAitOMBCdkWd69sfS4l69cWipr6r9Zu63gb9usWvcWUTRT7NNv/INrl3iwWYc1yDfrZv/BKfwJtvVRfw8RG5qNwKIbfCX1ykZDDbF4t/IauifXSUWLlDX9Wjh2CF3gahyTjmAPDrs4i29LMFqg8eg5nRfy4VsavTU0F5KpJT+1utpBLVaJTIaU2CV+TFAODPziItvSJELXt4LEEAwAcejerpxzHPISE4q8QzAQj9fKgaHvMMAPBymUGP7cPnTo6zCvHKL6EJWNH3MR4Dq1Xy3Rwfg2cz+OUKldr1k7FUBO+92PHa3dMP4J69zBfR4BvgixmoadAb30L1+BEwncB/JnNOo0b67zpp10Lwqwp0cpwQojpvz1/A//GfwOh7z8MgxL+B+QL+6RMZwvlC+CyY4R/I9fdNBa4dqvka1csZVr9P9h39899J0H9TWtA9/Qg8HgGfP4uYjuoP/H6c//iHePD//iDed3xyBLqYJwKkgBzl6QjUedD5POOzoN8xaM4r5P4tFsBGFGBj2y5NlCX6+lDzAju8Kfo+i1cP5iOs2zzMBQgZTWAmYuYMrs2rdb7qG/bsDW5NZrmhS2bsrsvIXXSc7DlzhgJI0Y1y7CFfQvuO1biN483NFvA6djJ1M20FcjsXnoVdWxdtXYRKtmwgFi/W6xP75aKOa8hwJcPI7s5nMo9FrVOsQzV6+yb1DF5J9fKUG4JYkJhCjY0olQdMXgWZCE39fCGQ7SBUV+DlEu4sLMwBag4ATqHaVSVOz3ULzBdoXsi+3HWwFdHjHM7moHUrLzd9OcwWmH62TPkmOn/zZSw3SRo6bTug68HLJaiICO0qBwfnQQ5ykJ3kfmoWu8hV9URKjELQAkpw1YbGEnAVEV+gGImiH8U3WEgyMyfATJExad8oANLnofKFnsHeYBT0t77fqFZOIRu1pP2LvowSl2DrkXgGg+Vt1RpNZr2G1tfYqK2xTSwzdd9LBmVnMlH10K7LNLK4j834jEzXPkckzpcSJlayXTNfURu0jN2dKVgMRN5PeA92eflA8h5aMyafMC+0ecahzb6SUK9iJ1Tb0XaAZD55D25buAvZ15usV1soCUFTZeNL4eUS9auFaIcWi9KuwV3QUHUetGLcymhnpj7LLvL+Lhb7yGUM2CSOrNvra8DxHGPiw1RuObv13Xv6IoAInD90dnwBGRn3Zc6RkjpUchlwaqOd6w8y0AhaikBK/w1SVlCroXK7LR8JiB/qpnR+G5Ep2hxXGbXQPsuXk47Tubj/Vuo+ovSn3W05l5tCvYH3ebHYFZRFCb6bkd8Aw34QosQcBaS09t5oGkAqeGseFLKJZM6S3wT2bdtfQNwJGrAYgws3VImINGAxOUWKtTtT/VGbxGXg511yZkaWKjMWWzKQGlPrVFPLAUEnblt4LXzaLDQ2DT725X3SNDS5i9KcK9w8ktLo+Y5Gqa6ohkHJC9nuGjmrl5Z7rM18ESVQVmDsysZfEOWEiZTSg+fpO9WVzKeSJOs5AylFvQ5kP20H6rpIqGvnP5OmBjUNaLHIgFbd6Rj18zpds1AjN86VLlqjJiTpcQKGBW1pV7mfi4XNm8hYvHfXANLDY1CK4X/Wz9Cb3DJehUjFBq3eqAnQW7OxaVIOgGXs7jrQeBQueIgOVBUYreGzUMcnIuNWeqhTzkYWndAoiskHiDkMIdejZOjCdJLYvS3icjyWPAYEj3tQZzM0IApnr83bCNEAmZtwTF1n4wEkusIAyPXxe3Rm6jmEaAiV0ZAHx6C2zd/sQZtgzHMq/9AOppNUQ7WuU55HXedM4U2d11I1uRzth0cYXaQoFDe1kNI8FKo851yMSmTRkIpQLVpUANoP5fjRDxK+I0OnHh2BJyPQfJGIgU6PMf/qFA8+Hcex8vFUXhJD0ZA2OKxP01jx8n0qjLxNNsAtfvtvA5KFNBXLz5xsSkDePkxmXQqfd42GsLE5IcfZcFx8U4ccAfQ+829EOjhyqS2NlqzXg9EQLIu6l+H3yPq0SzTEsmA5SXkmg8Og2SIxcOk8+j76JSKkXdv2IW1a57bvZU5MXzrvDEjOg7a7XKZoiLa3NglhBvdCF3MJqYakqzgHS6nvyUjaHPW9LKam2DGvU3SEqm4j+hLnHUnrYs+oXy3Bc2XAIomorNYpGrJcyXj6PkVDRk3yGaxbNK/C8Z4TRF0xHFUlhbTbFt5cd5otMP18BXR9PgfLlWgUzGkhbDupj2ujId7LsTvKIRpykIMcZCe5l5pFfMPrZ4881ViBW5cVGVL6OQUKnRzL21PtOQUvWVMkODwpgKIAoG+FxbmP0QbZ1z04Bc8XObPz0RT04FT2e/ZCitYA8K/PgMcPJdISQD/uaAp+3Ya062UiR9G34XickqZMgldsH4D//BloMpZkp4cB0KQUciExzAVW6d4ArlzADMS3qJK9hu3dNz5C/clzMbNOj+Oc03wpKryxuYkI7AIoaxYo6UKCFcYjuBcv5XOAydPJEfhiDgrRBXr8CPzyFfyFhwvnFs2gtgOMZrD80Q8x/t1XErWwLOdNBffqQkBNP/g8bscHj9E/PIILc06TCXA0jcWLyFZGbxr4xydwn4fxBnAdrVZ48R88wpO0J/pxjerlCPMfla3j50v4sZhhqw/kOnZTB18DozOP6WcLvPhxmZOPnr0GZnPRUNTCIwf++sfojsdofgfwAcjW/vDH+L2fOsIPzR/FvtvHE4yezeBHAQQ2kke8O21QrXo0z+ZYB5MHHvDnRTGlS+ReLhYWppqlL9tM0ivAWimjMKi/+uAZdV8ASZa/M4RXDcIQ7ENuQN6PP78I4VCTtj1fpPTqrkt9eg+8OhfGLFWfF8vAbCRgoqgSU1BPl6sNoJW/mEW/AoA4Tm67uAhZE4M9x+zRKM9eJMCVEtWuW9BqHU2v+pPn4uNQJ6e2p+nW6pMwYUZ/MUvfA1oU5xcRjUhV8JMsl5kZQr0PSNg+0e2vVim8uh7FuZ/8FkekZlxEeg+s1mDfA/NlHr158QqVAp0g9wTNF9HBmZkhVQWaz+F1wQsLCbcdnvyL16BPn8dd68kYfDHDkar46xYVielUfx5YvMejBES7WOBJIIrmxSLMU5UhaOmTz9E0wheq17357uf4qnuK6sVZBO1VLyt5uQQzpAo+naapJfy6XGL0KrF7u+XucPV7uVhk+RlktsXfi7yJS5tKnn9LQa/Yi6GFabeGDQYiRivMz5bjoPcgL/a+akccHj6NekT8B/tUx2JAbJgtG+11wpXaj/U16PbgkyGjzYlfwixsAaehY46aX7+9QG8Z4rPfo0NXeSWGfC7M4K7PIxlm7Jaxm5jFZjccE4P/9XMZEjV9ZtIZTAmQokbahh7jnGhH3ic/gmJlTJo+c/ADlf1rpM/mp9SFw7KgdYx/QIg0bZ7ONrmfi4VyPCCZIXnI7uqoiK2XAXLCOmRyJbBYZCxNckwlpQJ2jYas5YHVB8NGK6jtkinELIVv+x4U6jjQaISYZ8Cc1xsJRXkjr4FlsDK1R7FapWiIMmq7MM4t0RCaTKAQ7rhYVZVEa8Lbi0+P5Qbvexl3OAcQCaTdhpUBYRObjIHgw6PxKF6vMhqC8VjON0RDMB5Lfc++j85Imk4jeEujTgDgHxzBdb3kgoSHhryAx7CUawyjWdFkAn5wDKgZQpRHQyyvZlNLv/pgmmjI6qMjTF8HbYlIohbeo38kpoW7qOQh7j38w8DiPpF5d22Pigirj2X75AfjGJWzBY1oOpV2Z/P0QjmeYv61CZovThJEfDqCI5Lz1/snbKdVKy9FGw15tns05ODgPMhBDrKT3E/NwkhmGpRZp7s3kj5bCHapXl4zhaamcpgAACAASURBVNuCnCKUF0iqqh9Ie1dzQ2G/PKDWvgFh5qSpeuNAVoi7UZ/BnNR7mPnzBaw4pHdvBXBdPShpewCuLmPzuXYdTCSqfO4EB3Iz5JpzSva24JT0F02LAVg1eQY7AvUctLRyrtK4GNutBQpQ9pTYhnhdpI8r0h72kPu5WFzls9ilCVWp1WfRBlyEXWS0ElYpu+AsNMei7xM2ImSFRoyCsZ95ucz6494nnwDbm9xHTMhdZJ3ycrmJsyh8FhRyMLg3CEDNovWcnh7LB2GzZNdt8tcUOAs1ZYazTm0lreDjMQ+iO5vLPLoqQ3Zy7yVfwt433gvmwJhzzAxaLIezTpkBWqTUecOZOXo+zzM/ux68XGVZp2pOutC/a+pwrh1ovkTzIhzfrkNekctfXIuFID3NPNJsgemnK9BiFRcW571QNl6Gs7AXfI+s03d+sdiopxF/MA4/QCZGWaosE9aWFTV7+Milegx6IeomQMDNwx7e8HERCO3HxCrbvi0DiNRXltClC1bfJ07LgOpEX9Sa0P5IAE5syWr0Tb728PYG03Eyx+K/qh0oC3fJmelni82FN8yPPpTqQ4Bn8VEA6aE16MG4jnc+VhWLcxbOMTl0kw/Dkuj6uY8MVRrBsg5UrNKtT+t19LOwdQTaQstGe+Clli8M12HdRp+OLrJpCihGZeS7jqEHff+zGBYGAK6kYHL0x9iENIWFu6Rd+q5DFfbxWgpTiXd1vl6fgyqXkRT5Fy/RtK3cOxZK3/dy/tYRXlVxESYbAdsDlPXuLhZX0YVZFZZDopDNf9iVWslQz2U5HxAnI1lOCnISgtvRzMlrXxRSpQK41NQJ1j1K8GkajxOqMFLQI5DwDlMD5mYZby6q9rftA0+fbREfDUcyp3KG+ubioFE4l4r82jAuMzQcpIlS8cEAoE7pmA2rC6A1wTYK57g850RNvCYRI6Pv4WcLWYS9BwXHZHR0VhVQaZ3bNvVfpA/Y+rBxnCqq4YRzo7BYbGT02kVj1Ehm6miUaXcWCg+exTH6WQjPF9oRPIdz440+Mglo2+x3TovoLnJwcB7kIAfZSd5dzeIqGeKZuKYTJ1M31WQIb4fsbVCmWu/a5tBxff6ZgU2OC28ceOVb7q6knFftS02RuL3PxqtmCAFRo+Cuk1BiUalbsBfXuFbGFBtqh0JfhDb5Wdi8cb3BJFgw2R6VxIfEmmjskPglgu8mc/TqtqBVCStY4iGJPhFjolGJGdF+mcVss74cNbkipiW0sY/Df4vc38VC5YrKXfs1RbkKHtLR9yU2vUbHA9tyToO3JlvK9gHhYb302C036HX5I8qxhFT97CWhPhO11YsHLY1d93c35rMQH8n2NmKfDjngKziQybCcx/PZxiNSSsmVEdqNdIi3sEioXLlYENEvAvhPAHzOzH84bHsC4O8A+GEA3wXwM8z8kmRk/z2APwtgDuC/YOb/51oj4ytssMLWBbDBBnV5+wNOPMM/wS1niEo55BpWW8EMPVTUl/seBC1alGDdttyeZcWiO46abtWKvLIvxR0TsjQ4JbmzGlBy4GaFlZmGF8irB6aDgiJj2SF/q3sGozfhXh/3BZBIjoMzlqzz+JpiIzIyPvVzGb5V7VMjRUQxNC7Rl+BYXa9lfzOurS8r1eyCQ9Ruj3MRM/XfjGbx1wH8jwD+htn2cwC+w8w/T0Q/F77/FQB/BsCPhb+fBPDXwv+7k8hnkchgomPP/i8Pq0MadbggbtSICqscE4sFAFNVOx5YViRbJ2ef9g3ATcZB1TQOwrpOjN6LZSJQWbcpoUsTyaZCMKN1UlL1MnEqOlM/xVY3dwbB6edzMafaTlKigZgHoQ9vbDc8RO7kOA+dAhvkN7EimfcJhRrCs7xcbZiD5CirdKZOPEdkckNc/M0S9rrpBH6xBHdtRNfSZCxhQC7Ibx4+AJ9dbBD2EjmhBqiqyGehyW00mcA/fxH7Vp6QSBugoijWkBOi166/mAE/8nW4H6TcECHsTVXGYugUAE/DfJnQqbuYRyZw+u3vyzxZsh8iuIenoKaBf30W77Xq4w/R/nsfofntT9M4x6NI2Kvjjv11vYRgFXULgD7b3bi4ck9m/sdE9MPF5m8B+Onw+ZcA/CPIYvEtAH+D5W75dSJ6RERfZeYf7DyifaUoqiPbUn7/zqFT5eAs7OLNAznZv/o98+qHzYoNyDQIH7NcM6yGMldz2jfzBZjvAIL3faAmadtlQHcpY1BwQRQcnGWpvOxhN+do3148m6ewp0FEp1qcueoT8RzaXgi3eub8Ouj59unc/GqVQqd6DgszFm+iIRezmOWb5cjo21fxKTqHmqSnPgsTEuayiLIywCs2xozbvTiHtzwiykVxdh7O13B9Ggi3ni+vVnAvZV/f9yYnx2hM8wW4Wkcfh1yHGZpPR4ItUWlb6VvPX++noKmwYQcXzWR3f811oyFPzQLwKYCn4fPXAfyu2e/7YdtBDnKQey43dnAyMxPR3l44Ivo2gG8DwARHV+xdHpwSyQYdnBZVuM0MUbUwJok5SXiyCVsF/yU5kn0uK4ys8fZQuNhODTV1yB50wGIRCxrxciWqtc3YbBqpYeLEl2LZtuSt5Ew1cRfbz8yQvo9miC2MHM/FO2OGBK95UPG1L82UjMWIAeGjmM0ke1Rp9Ti8qY1TTQl/icPxQaOI9HgAfMSP5GaIvvHceAzvGRxK9+ncxmiMwRhEngyD4OQAe0YbMCELBS950HgEmk6F1xIAXH2lGRKvpZohbQf/wQOh84vXuQFm88ghYhGcHLg22SI4ZzX6J7KvO7tI2pGtuH40FTOk7wHlGTk5wfprjzBarZPPYjySOiXqHFczZBSS6AozBIvd9YXrahafEdFXASD8V0aRTwB8w+z3Q2HbhjDzLzDzN5n5mw3GQ7u8MbGchYO/3bWojW0BUIVDipT1mdzWsd6KZICsMmV7YIzkoIS6ccwajbgMlHaTeTXRg41x6TyGVOw4JiX9jWzY9pxuOKdDzsOrohlkxqvs3C7tHxm+bVr7tr5pyzmUKek3lOtqFr8K4GcB/Hz4/3fN9r9MRH8b4th8fWN/xZDPIas3ar3ARg0YYsrKQkxhAjsf/KPFhPp+Q1tQ6DfVddIsAgov2f4hp0FRfCU3qELSmeEin0UYJ6U4O/c9/GolbXct4EZpXH0v5RbVVNU8itEopk4DECbqphH8gzJNq5MxMGXp2zpqNKMmclTEmD9RXs5vPAKUiCZ2Fm7Uvk/kOUYcEbxqXYBoA9NJ7IuqQMk/HssCbYhxNT8mah91DeYWJY0+H0/lLQ5EnAURgY4m4visqkRMjKSJRCf30ZFoD10n2sHS5NnUNehokpy0SjWwWqE7GWFkHL2oK6Ct4U/lDe6YRZMA4E9Vs6jga4f6Yg1at+inomW64Bcp73p3cgweNSAzJj6aYPVBg9F304LAR5NAZBzuT9WwjmR87rUDn6TyhfukqO8SOv1bEGfmh0T0fQB/FbJI/DIR/UUA3wPwM2H3X4OETX8TEjr9CzuPZB+xC8g2R+ZVTFmWDQpIuRwZHLZskwFoUlRqX5yTRY7FYgmODr8gq1Xqr+2iCs59D57ljFUc9o3gHfMAiiNzmYXWyFEi8TWkOmAZW8yrMEln7Dk9ECHqw+cXmwWJAl19LF/44mWKYnT5uLJK40PzAWN6qMMNAKow76GYEWdOyxbsOfUZGLpKHAF99ixGK+KYIIuLX61AK0O9CAjz1iIlzvFikWDaIwN20izf1SqGXqntohNy9N0vwMGZaU2YmAkaIjEAUJ2FRb+SUgDctuDFEqMwht4SJtvzePU6LXZqcnzxAif/GvCBKhEAaLGAX63zvCIA9FpMYJ7NgLl1iG72tU12iYb8+S0//cmBfRnAX9q594Mc5CD3Ru4ngtOaE1fgKbYdmyj30wpM6POiO9ZRqscGG90mrUmNj6IbZdmyQC7jGCVXJL6VXApa5VydqhHMpcdWxllpVG5bR8N1ab/YfmuQqqYeScy2rVNY0jh/tfgPAKAZRc7MLPHO+5A9uqnN6XzEzwimh2oUOi9NDXYumSdNHUOylnGM+172sf2PxznFnEoj9UmorjNfB9W1/GbCi7KPmItRM1A8h6lzQk1oq2rFaRmcpCQXAgRE04/Zp+ui5kqoJUIryWxWx+dG6UWVuk7FnXQexiP0pxO454l0lwLTGErNQnlJV6uEjQH28h3dz8ViH7lFOPg7LVsyRS9zbr0R5+1lUvavqe0FD+cbFUfiC7FO0563O2nv0tlsZcjxvKdIFbTrj/f9XSyuWiQKnkiq62jfAsgcYXmzQSMIYU+s21RiD0hvz5FUGCMTe7UcnIr8BMTuj5XEzs/TeDQFvC80nqrKuCfjaZqKZ4DY9lRVomFoXwYUxD3y8wDEwagN2OploVIYAKHrD8QxGecnUeCjGMgnGY2iHyKmYY9TmFZDuDSZSPFe1eZ0H+OMpaOphGEDZb8KPzzZIPPRlHV4FuftPPFOYDyWt6xyiYxGwaHcy1vclHSEom+tg5MIvFii++gUzULZ4sXBybMF/OPAwVm55OAMFcm4cuCmQnWxgiNC+5GUOag/TfOUncfRBDweCWeHJuqdHmPxtWOcfJZCoXx6FBzS4X4JC4s/mgC1g1tNkoMTAL74MlQk20W2vVWpQOcB0bG1yxtNMxujaP6BWbXV2Zjh+m3FMIsG9Jyj8HQ8Yb/sfzy2zW8qRRzaRc44ATcQnBzg8ZHMJdQ+Xa0MSjEsfFqtXIluLuaCFJSGUn9tmxHXZOdjK6gpTsDmvmjt01XhLA7YDSmBYCqVK7GPmRf3+iJjrALEwYmmBa9W4lC112O1En4SG/3RamfjUcb0BQA865PzkdZSZJkI9RfnYLsIEQmE/6VEjHixiC+hSo+PZsgaPJuj/qLZmKfsPOZL0LoVZ7OaceczTH9vmpdk5HAvFWaIW7fghyeC6bENv09MWYOyTzRky/EJKp3g1OxzTWAoGqLJZmzDdoNp5H7zwTE3N1uo7RCXpEKclZ3L3OQxamNvZu/A6IHWwJxZaPksZX+En+uDM7Bocp9HkiQCnVK5qU25G5GFGxp98ZvzZucDSOcd8juAEBkJc2znlIG4GMc577q0ENrohq3nYoSQfDLZNeq6nFiol/ljZmBlFrc+cFzaxa3rQCzAJ5qbiIpdnDXSZNi44tWpKtBaoiFYt6AQofDFtY7SrsG+SpR7ALBaw50v8xR1ooy2EJXC4hm0WGU+j40EuCvkQH5zkIMcZCe5n5rFLtEQcgLSKi0RfZPFLM6w4oesyIzzcygaAmyAstA0yeZnky25WuX8i+OxVOKGvMUUmu3nHnQcygAGdZbGY3mjBSi5hWVTU8NNJwk7oVGL0ShR2gHA67MUOdCaG+t1iub0CUKttG10fJyqqBc+CzWh6PEjUO83fBa0Wgln5sDbKs4HkCDp00nyF6jvIUQ0on/kaAq+8FJqUbNOj6ZSRb3wWeDjD0DPX2X9qs/CXczEZ2FMGTo+Bk3G8XxpPE6grFEjJgqMz+JoAsCUOgTAy5Vkfv67cG8EnwVmC/BXP5DzPZtHn0U/5LN4PUP7dck6rc/OB6ve0MMH4rP44kUyxz58jNkf/AAnBjfBp0dw5/NBnwVXJKAvC8p6fYtZp++k3ASUFRaVa4OyFGX5roKyfG4KYb2WnJMMlCXjYs8xzyAeM5tt8oJoxqWq2i9fSXYqcHugLJ13Q1gLAHyRMmYjIMqaIfbh//z5fqCs2Syr5B5BWaE0QypxyWL6FKAszS9qvrcFlBWwyxko6zzxalpQVhOIc7eCsl6fbSBQ8ewljn+DpFauzsFyOQzKOp9J3dzz8xyZepugrHdOdsVTDB4bYv1EOTQcSGnQXKoihWiFMps7Zx8QFzSOAUJd7vt0A/oebPg3/HK1sa/ul/3XYy2cQPEcPieJVZ9J5jsxfggAiYo/FJv2BQu3/EjZwucvUip/SQC7lRLAzAebsZRp9oJvcfl3PZc+OF7N77Y3Kglpo8g5yXHpCJnzVZxb7kheAuE8soe27cB2vH0v7TlC/8WzbN/IFTJExnRhclKASBqkjukhpngAwrqu7Wtk5fxctDlz71BgIN8Ii5OL3CAZZPy9dnCWJoergrlB+T5DYh64WDbAkt9wqrPgF4sEaCoYmkrym4yqP/Thjo8TXb9SpmnWKXLyG163cA9OAM+G/GYijqoqcF8WZDu2cO/WrNNAfgNvckC0avwW8pvq0YOk5lrym9EovuHdg1OBhTMnFu1wHrxcZRmycc7G4xSK1BBo5RKEW008Jb8Ji7Ybj4M5t4Y7OQn7NJE704LQ6KGMazDRbLEEmjpS9jPzBvkNnBPzo095KFE0fDzTMKucd392AfdH/gDcp5b8pgbPF6DHD2XDFeQ3NFvAfySV0N1vfz+ZwNaEPT0FjRr4l68S+c1XnmL9wx9h9Fufpnt+Ms7qhmRZp10PN2py8ptPd6+ifnBwHuQgB9lJ7p9mAQwDrkr6u6uaMDBncpQKI5s3ldQUMYWRlQOizDqta2PnB6dYKGycsYMrKItIAFP6tldQlvdAyAmipk4aRe8T/4a20yRYtqWrsw7OmHVaOjhDG1nWaSyMnDSTqAkoIGkdQm4nRwIbZs4LIwN5gWh9u5OT4xcKypKK4FTXCSSmhZt1/Nr30VSAXuSywsjcthvXyz86gdMEryJFnD0LLZ5qMt5LO0cT4FWV5k8dnAU0HJUDHU/TuAK3Bc0WWD09xvR8EeeBRw0IQP8kgLLOquhw7B4GB+fIwVcO9bxFBWD5VJyO009CYegCxUonR1IYeb5IJuCDY8x+aILmUwPKOpmmwshA7NcfjUBtD1c5+AfBwekBfLG7vnA/F4tbkA2UnPeJRt3uV3r2WSpFkUJu1U7foNAP9GgWH9H3CWFoaf6BjE5efjeOW617mgYfCsZs9smGhEXG2cfP2Wno9xJn0RraNc1g1XYVwLVaJ0yF+hR4E7ORGvWhtKHpk5ykmUcUqjo420BtpxmvbQK96UOiY+k9OJLjArQIFck2uB364OfJ80YkolLHay6Ls5AKsX4PQuyA1dpEiNL1r8/bLCeFEEzL+TrOFzohv6nq8JJqa1REUtl83aK5CO2q89YyuxMBS1mcva0Mt1xj9LpPvhEAWKzFtIkvkmAWA3INVmvQ3KA298BZ3M/FQp2U5bZ9pJwkBS9tqdFQ9pV51YcQdzbNOm40QCwUC1YRRUhckX5z31gTIwFutI3sxgnjZJ+DsgCIxjQAyoJ1EgYuSAE/mXkJ/KIZf2X4Dp9IdJUpC94V49eITKLxj+CqIkWdDHArApvCQiFMXiZFfS0LDcNEzNnUQx0CvtnCyEDg4fQgFM5iQPbVbcbxWi3auBCRks34Pi0gXQDQMYOWYb+ewURyvboebpmH3kvhrge5zvCcAli3aOYhMqfztZaxENcptV7H1Xby28o89nsEC+7nYmFMDjENkKuMg5HqognzZpDswUrUahO3j5mjes+ETE3BKRizYDDrNBCkOuRhLFWbK1O8t6okF8H7VEpRS/MR5WZIGKswKAXHpmadVlWOO9BxmtwSW1KRXG7eABA8gY00OBczLuNNOmqAdcIjAEgP+IqSU03VaSfnw94wTesQixAfQpZpXDyaWvIhYEyVuhaNwgldnxLd8GQEWjYy1tqMoQsL5qgROLn2XdficNS+XcgsRSdtmAWSKies3bqvjsWRkN+YspM8GUlIWmn4eg+unFQ1nwZcyzgc31dwfY/+KDCea7aruae0bzR1lofEkxHWDxo0E5MhO25AXS/nzxw1LJ6MZL66Djw2Ts09WLTu52JhJK/taUJ+V0xC9qbT40qzYR8I+TaxtRu0jSKEp3H9zWN9UqcLM+ROZZtqum3OyuNKDancbjlFrytRqyquiWI0vAlN6v6+MOfK8V9TiJGdM/U+f3kMJYYxwCQaBhX3MDPLgu3Toj00W+Q5/sXzCBpM/LtFOURDDnKQg+wk91KzEH7LpHqz7yOoKN+nS1yYhbiQyu1nC8AR3OkJeLVO0YDzc1Gh1fQAAkEO4I6nEeZM6zXo9CRGGWIE4eEDgTKb6IA7OQY/kdg7fdqDQmEh7l/Bf/wY8AB/IfF6CjgNmk7A/SxFHVYr0HQCOjoSNB6QsBOnJ8AHj1J/fS/jfH0G90j69WpbT8aSgaiM2AFmzk8/gFOU4XyZVP0Hx6AL2Wf5ox9i8lvy1oqedQismQyoyJbti/Oh4wTAx1PQZ89kW5hPfngi2aOKVPz4A9DnzwVe/lDSuP2jE9BCuCt5ktT/sz/0BKf/Vkw0juYNwY8q1F+cwx+NQQZn4Z8+Qft4itFLCUHRybFEetYtMGrgLlImKY8atB+eovk9wWQoZJrmC3z6k0f4Cj4KOzL6SY3R5xO8/sNyLY4+PUY3rUAMzJ7KI9dNgX5MmLxgnH5/gs//qNyP3/jkFHh9hljMKkj7I0/RnjY4+jcMDuOd/cGP8Lv/UYUfff0oYgQXH48x/XQJPw5RkJHoA6tHNaqVx/SzJRZPA9FOD/TP3nO4t4UUc+G4y/Yx/zfaiFBeL87yUDgnc2qVUY7gLPSLZXQksmfwxWyz//NzASll8OK55A4goAdN0R33/AzwPnpbWENkYT8L8+XlCmi7VIpP+7iYZeqqjpO7TuDCSIsZL4LD7yKHmbtnL6NdHxfZdQtqkxNv/LuvwBczgBmuUyiopEZL+QPDARqK67BS3KuQAKUiPDs6AzvwYpkW3eev4lxwIAl2ek59Lz6KMKen/7aSeXQuRSsgJY94sYRbrIRKP4zXPXuN0WKd7gWd7+DjyaDVdY1m3cZ5VMg0r9f46J+v0Pzey7RrU4POZ3jwGyE9/GKBUV0JX+cLWfT9qAIqglt0qF7N8WETfAvnswTGM+nszScvUI9H4Ndn8bofffcVvvK/P0Hz2Vmcg5PzseSiqM8mLDjjzyV0SmcznJwfxzmolu8zglNFEX/q4JQv4cMOdqgNrVHgUjAl49Q5GHMpYvs7Tq6lx7e08zp2iwVQhyWQ3iYuUOTpfpbS/k5LASSGqEjxpv2rc5YokMP0yZHYe8BViWwGSHVP0OesUq66ns/ClBog58QvYGgAIx1+XcXELXVwUlhAImK1DSjJps7e4NcRX5vrA8icOJeM/IzuPyykGkKtw3itY7uuZaz6MrlkfL6m4BQu5kBDr9pfoPq7idzLxSIzOWJE4JrVzsk8tMUbCVUloTwyD/vuC3Fqs6xdoRGGkEciWY0V0MGMpQrAK06LSzhPqtxe8fG9JT6UYfF0VRizoZcPTF36BiOEiIdL4CkODloKbUZIdyCN2XBOXjkucx203bqKzkxZ7IWViidhwepZQpcK0dcohmegcvCjGi5Gb67n7OTKcIg4AjeVLE7RFHKRV1TNI65IoiONA9cOrOtBVYVFrUlh6dEWSDYRfC39xagHhYruIas4LtDVTZeKg4PzIAc5yI5yLzWLOxFHQsxqZcubb6fy9TGr0KzugAmF5uFFsmFFABEpOtRXCD2mMoGp7ayOxpAJZH5THEU+7uK7Z4B8RHJGiZR7AxqO8QsMhSuFm9SMYWhcW74XDYU+VF1P/COk19KHseu+BZKVFB0KJHNU+y3JbU2CWl7pDNGMsEmO2TYH8fRGswByDT2LY7tIhGQ7rr5PWq+lbnROwvLm/uHKmqyU2iUSbaZySRPy+2kb93KxUKo5oHBwWpzFUEUyK5HYxifTwvuCpyJkjWq2am9sZrWJF5DPOY1CbN/CoKPaHMatlyqmJTuSVO5wDrxcSRZhl7gTuO8Dmc0EcGFfvYEtkbCOs3Jy00d/g4u/2ZIGUeoKWNsFrZebtHKRJ5SbSmjndM50vL0sDDadWueSyKVyA57BYNDRJOV26Hw2DdC0yb5umrCPyWZ14jvi4I9Q8aMKFSDbdDuRAJUWSxmj5askAnUJNk+TETAeyUIwanJQVl0JgEvPTQFXjtCPXTIVYjY0wU/lnNy8BY8EVt5NQ5Ri7NCPHEavO8BJZAQQpzKvA3xc57btgI+ewB+N4OrkY+FJjW4KUJvPgXNOwGMVgOAb6Sc1qHagZYv+OETyep+ZUFfJvVwsAFyNPLuqIpmB6wpxTKhyZcOs6qPIVn0vzjEDuWbLAaG7KYejASDxep2iD8wZuS4HL3x0tikxq6Z598bJyiwRA43I6IK5/P/be7eQy5IsPexbEft6zvnv+VdmZVVX93TTNdJMtTUaNSMZjBkYrAdjELZeJBB+8OAxSMYverJfJBB6k20ZjITH2BgLLGMw2EZjbPCDbSTPWAg03T2Xnu4adXVVVuXtz/92LvvsW4QeVqyI2Pucv/LPyqruzOqzIDl/7rPP3hGx9469Yq1vfV89fPO4dtq+9wVUY5i6HfNoOAUwAL42hBrAYuUfHnW5gCe6XUtBnmGeyAgFG2DjakD8g5bZuuz1YkhoA/jMj6cOWCx5H2siaULLE7ixg5dE8nQeyrNjFGm1DsRAEau7XVbsQcj4rVYM4+57YK2H2RuteSyFmFfun7bD5MEKdOGyJO5FYpcrpA8dq1ZVM4+FtSgqR3qcJQ7u3UPNl5h+nA2OO/ColAJdXEMvUpjVyl93fXaNw/dzPr67NknXgxYrnmCt9S+ndFVzZmxVIY2In+KJ5nn2+k4WvsjGfSiC7W4f9AsivkO4cYCBW2wNIkpANMqaDKUAen8c2w+RmuRg3YB7sCPcPqWpr46Udom7DmsAJdF943PwVrkbKxJKGgTDXDtJBc/Ew72duvk40k5Cmw94d1zEdyzcA5JnQQJPMh/aBFKbGE0oFnN+CIxda1Dt2iUeRqS16v9fa/aORC4gz3wxWSyJYCY5VFU7TyhMFrIcoknp068AGP7tKmC574nzKAT+H70ApPJWJnipgFWEZj9DElfrZimobtBPGc+g5KE1Fv3MUSnmCaAAVfcga9HO+Hh6y0uQ6QszptWTamQAQw+Y2gAAIABJREFUtsyxPklRfBjSx3aSM7xd4N6eRyMD2oS/c4JGMRz8NkbbNAp+0rZPx/bP0q8NN7q134ATU0yNUkmO/MZzWjYtxkxYYxuXovs/pQjKWiZeqdaDNa1tm5GnYQfrVH8cR64Tk9/EKcl43OWBjGHqQrBjR2AvKdQyskSSNvCBBmlAG8cOZMxMcM8HsHgBUsU6IFFRGIBBDQURDbRPYuwLlaKNwizTpq4HfSahlIs8iI2sllcv0/7YSrRV1KhNZrgvpUlYdvWGlx5ufKVtaDu+HknCmBHwfRMzTMXZNXITb8wsJtcluXcXxtHqgRyIra5DVqgPk6hfvqZcWyOC03Swz/uuVjzJJkmgWnT3ARENrruazaAOD8JvuNHcRqUG8TLSinE/bTeof/qd6rdw1Z/dai2yy4bsbGc7u5W9nsuQ2D2M1+gv4CUN3xpx2Xj0ZnHlwGNN0Rdup3fPlV9eDLIhsLzOjt4E1lp+82zLkjyPJ/RlbcDBYYJHNEK3DjgsJPMBBBJYESeSYjo5LpkXcn/jc/LPb4hDuSWHbbvNLE1cAu/2JQP2PF7Sux5whciYxEWJURA4bAs0jKxLEmU+xr+7ySTTNCbdja+FfL5AdelN9lpOFt41hbit4EkjrjCM3ewtN4MS0Vrn5qvJhLMOwpEpUe8YtSmozCzzyxizWkFNJsx3Cfhzqdl06GYDUHnumaDMfBFc+KqCOjrkTMIFU9nTdMoSgRmL4cbcnarMAjclELItkdQAAJhrJwVQ11Buu2+nCC/L0s25vProcAPuLUxZPuB3cgScX3JJfxHkEu16vREw5Y4Tj4ewYgnL1N7MxxD8sjDnuIA/93QKu1zCrGsoV0sjTFkYM2XdPYY6u3LxkGhpScTBzCwNHJoGoKMD2CIHfeK4RcuCzx8tD7xpzbUjAveWcXt2jvpb76D40VkYhzSBmi/R33NSAIsqxCwOtsC9L5ZYfYP3nXznIxfPCpktIoI6PYHNM+gnZ4G39J37uHzvGAf//ImfHM2s2Ar3tmUGajqo+Qp2L5IC+FGorXmevbqTxSg1eqNFa90Nj+PTUqcDWDenvkhRuPkXywC1lrnCBS05UBlSkV5RmxvMnxKoi7EOec5aGUSguGitd1oOxsCec42BSnQUqGuDFmhNgZYuZr4GB+hiWjxaaqc70obAZxVg5TFhr7eyCGlLRYwkTTRvF5Lagwl00wJdD7vv6gy63sUx2qGOrEN+Mm2gxDTKEFgWuUGvdZpzYaD0wQcV66DVMSlAbcLnL3P/9myPSmRVA6QJTCZITQPqGK9inYo4t83AFjm6kymSMzc2Sjs9U+bDGHifWcqBQRfY9eOsNZb3U2RngdrOTDJoY9Aec3tTTTCpBvUG9Qlv66Z8HfQ6RYFQYDbJM45txDE1rWEnBadOLzJPRdgflJi/o7H3wcw/L90sQwqX3jaAdTUn3SyDrjokvfHUfmTtC6VOX90Ap9goADfYJiYeRCxO/Jx++cBpH5HZ2JBas04XYqD9IcJFSg8CXJQkG5WtlGZ+CTMgnNGM27cSYAM4kCjBMEklZlmYKCV96torbR3T6Mes474PisJvgGFA0UbkN8LcPZlEKc+Q9o0Dp+LtwJiA63A0gTEztl/COA/A4xlkDPp+I2AoHk88AXIKuA8BTgkGx6lQIFTSxuPgwG0xRSDgliFZxozZks52AV2v/REvL1ytjveOXB9NXSN5+y2Yy6vQDufNDfhEhbDJBb4pIuex6zVIqoKfPvP3s43SqEyWpAf6K3p/BpyeAGehiA0OBuBLAmRcHedq7KUCwG9f/6+46p7uApw729nOPj97dZchYjd5CFG60FucLpVYheiKxNs2juVwDPFqZSQC5DayVxFR4jFdW7axXGL3P6ik8zYKcYqmAWlHsdbWUNrxa0SSgbyPSwfKC9RwBSc5mT8+GPnlUPzWMHDaJPHbRNxwUoCN2uPSlZSlgAtNWDcgRPJWdQS0hZNOjOHlWnPQs2kDCjUejywLZMUOM6Imk4CoFByI0yehKA7DSmFRMV2kYRIHSmk2jQKuEYS7yGBXK1CaoI9U1lVZuPvDXZ8iB8nyMc2CjKOk8LM0cHJkTFOnANi9SRDucd4pWRP4SmKNGKcbYl11LFVOeS7CPgzAYAAsAHWwD0pTjhNJqng6RXcyg76IvJqyBKiKaBRlCZzBpgnoehHSx9YCy9tX3L76k8VntU+DeUdgFX+jJMmA53HAZTA4LA1g1TSmjZclgWiMRjMQJQnHLADOrXsexyZsv74Ov2+dFICJ2uvkAShNNuI6XmpAzic59b73a2zvRjv3PqyNXX/zfCOTIO320/KkBAkPRRmdr1qDVAMRPRofI24nwIHOOIgqRDtoyKvB+316E6QA8syzcCNa29vZZCjNB3hAE7rOxaUi/o485wnCkQhRlvJE2HVMOiTHsC6GUIQJmgrm7rTrGu3JFJkExA0DsCwAc8CThSLyJfNGtE4TBZNqJPMECkBzwvumn6Rb43Q0KRnstV4H9Oi0RHWvwN7HkRTA/nRYViAvtUkOm6fQbTcgLMLj2y8uvryTxfNsLJsnaa1bxHBiFnBr7NbU21Y5e0mHuvMPfjdm8xLiHRN9xm0f8y4CQ6kBwBEGCzt39MaVOo0RS7m0Y4NZvO+Z6FUedtE0VWqodWpHY3rDePj9BFoNuEmcmCMjZkb32qOR9EHXDVm4xZpIxkDOCzdh9D0jM0d9RRekAKjv3cTUczoy7hs6UBtQqFZYwS2ze8dSAHKdhckbbecLvVTlXkaJ4sBr3QJtx8eAi/NsQw63HUsMuH4DgGo7JIvRNa+bQcqdZOJ2sHx0PaiOdH5fIGb5pZ0sSBGsJU+75zaGtGoUdORPt+15+Wgty5DARUF5BnLutJcSFF6B+N6NCWTGVaPJ6FJIwFZFn2ICN49dTUnpOtg4AL5p8twR0rgUmV77gJlFiOqTPCRJEljAYkKeJAFpd5PFhDGxfGDLehtDpnXpDgWCFw+vToFMjunYp9OUPQGXvqUs9Te1LP28F4ihZ4Es3YSvS1HYWm98JyzgfimVZuyitx3MyT5UPI6ZG9cIcg4no9iVKbQs85xngTbi1Gja4FmULpDtPAvqDGidoHfbU61CtWpsWcqs3HkOJd5vmqCb6eEY5BlQt5ueRZFi/eYM5aqGmbhrHiN4b2Ff2snCxm/bsDH8PVrbyhvlufPsaB/b97B1s5GZ8MczQ++BZM0sbzFpa7SW9r8XYZ1IYMf/tmkGEPBtzFO2abnCs2nCEqLvg0BwXEgmbY0wDrF+CAEhZrGq+G+lQn9cmwfVv+P++Leya/e6Dssi1wcvtuSribmNA5FiUuF4UcZCLVYby0dLTAJjmwYUZ5AA7mukfUJ17fRBOq7cFEyKsUDbujhS5EG0LWzdIH22hJVaGcmo1TXUFS954piFili9tItZ2FWF9NnSX7OtYk2riiedOhozAOWj9bCSFgjwdoSYBXU9CgC0WEHHbOtjoapPsV02ZGc729mt7EvrWXwqRdrLYkuEEMb/3/hYwE/NtsVbnByjHa9NrQGTHSAESW/wCL5wixXXehswJBIfEUzFT8C8XgfgYiXuvH0/JDMCgvfzPNDg59k2Oe8LczuyUes4QGzkWbyAfXkni+cJJfsHO9yU1thNha5tFpWo+/Lv8UThtsX1JAPFMClthwMkjZCUXuUsUkGL2+6VxoAgE+j4G2OCG+G7DJKC7vfCBBW1wRr3fy0sWCb0xWVVAHAmSEiG43ZbuyHJMB4P/zfgiGkjaoCIpMdnZByYCJIZApij0iqnBhfVBmXpZuwHDgAlcZd4uaY1x0QklpIkoRQ/S3npAfjqVEqjmEiWMmkwrRmxKSAruGrhruNSfiAohAGeNMcmCjbVUNaC2s4rkm29lyDxHXf+SBmunaVIIsIjViQbjpWMjSky6NSV5Yu9AHHy6zlZxGnRT4N1W4sNSmOJEo8IWnxaTgZyhSgdOiqjFhVzuBTrOHAGFwCLEIpybKndoGrtayTsug41Hc/OQzvWNac4pewagG2biHchKuKSdk1DWsyuVry+tzaUzGu3tpaSbalxkXGYTQGnreGDX2kyrDk5moFWK56EypC2A1WOgGdzqpXx8H8DoEkRcB8ySRQ57DK8yWUfa41PC9O0dFH/PiAhAdb1aEYYDyIPCaciB2I+i9mUoeOCvsxSoMg56xET6IAfVrs3CYFXSRn3PVZvTzBb7rnB4QAnaYXmDd6WnmuYgvvXHvLv+kzB5ITsMkOmFFZv8/jOPsi2eit2fwpTplDLlZdPMMczXH09Q/Hh1O/XncyQRJO4TbkP3SwDWUBNS3QuTUvGwj74sqdOY4/hJkasbdsjt8sDX9z3plo7uPINAVH3f9tjkKJjFqpqmIIFWOuiaQYBNVOtoSTwGgFvbN+HAqVoX6b2a8LnqO1+IpKgatwORMGyvg/BuhENoQ+OSbuvrn0AzU+kDStz+6K7Jxess6LUIGUoWh5bA5wSFI2t6zaZsrqO++WvA+tkWGMDv0PXhQBy9ECnn5xvjCNIAcuK+18PA6X26hpYrUPQcrEM1zYN0G4PK6+bIVOWC8jOfnAJnF2Ga6FZcyT7yGW7qjW0BDivXE1JBMqyqwqz0X0zNnp6Ae2g6RIg1o8ucOe7Gji/DGNQ1YMAp2R0ssuMJ87FCmmERaHm9kuaXYBzZzvb2a3s9fQsbmO3rTp9QQSnLwaTdWLT8t8eeh1Qil8ogjOik/PdS1NfOg0AtK4dFN1EMPNQCGV7+O2eI/MnieAsCo/p8FW1RQFQSAv7fYRCD/gCEZwZL4O63i+VAPD4ZykvPXy7cvYOFsufDIJzWjKt3qoKXuALIjihFJQxMHtuGWLtUCfnOfblnSy+IKNRQEjg374K9SeZUBDQkMQsIiEfAI7h2dWxxNybMY1fzCV6GyW3z9ukDx6ARj6AKUZab9LyfyFtoUDTFwc4+z7UWMQM41n60mpmt7aIM5a2BHFvY32ZQl0pL5nwokmmV79EXSzi5NwmdLxhMU+nQ3CqooDtzXBdva0gLd4+boYrPY9rQShJwtpb3uCtA1WNSusHpeJyDBNIXHzfxuQ9cak+ESiJItrSnhFC0lqX3YkYl0w9ZAD3SFQpO99S+s5ZnaD45svGMZw8Pev2NlN6cDw5jvfsXNn6oO/AILXqzxmV6MfnpyzbXO+7cfHl+tG9Qy4b42MxeR4Cv5PSkwDF5e3+94LkFcSneKICkOv7AT9pXHDHJ1OeWdx2neeP7RfLrW8cVZYQbhQpfbdX16DZFOZqHvok12Z0L0ApqKNDmMurAYfJb1/9L7fm4Hx9PAtxvboOqij8xRHGKJXnTGYK8AOcOk6BPIet+QY264A2TO7d5W2OaFXde4OFep2L1r//AfRsCtt1LGIMZteyfQ+1f8QReQD9w8dQ996AffiYT+3apX/x50HnV646012LowO0bx4CCsjefwxzxCSt9Ogp6n/layBjkfyT3+Nzff0d4PFT0GwGc3HpVdD7x0+g793lyPy5i+ILc9LJEdr7R6GP73/CN/2zC+At7q/+mNuJsgCqNeiE9+8++JDH41//JSTP2KVWC8542EmB9s4EySWf5/xPHeL4u1eAtahPXXbHANmzFejB41AD4kSSrbXAz70Fdc5jbU72ASJ0swzZB095X1d12Z3uIXk6BzlEZPvVU6Q/for+6RnUt94FANR3p0jmLXTV+ig/ADz6sxOcfqdmST8hdSGgzxUmD1Zo9jOUv/eAz9cb1N96B8v7KU7+H7dtb4L2ZMrHLVOPqgSY0Gb19oSDmQBaWTZ854/xh3/3Xbz1W27StUAzVdh7UOPhn+M+7f/YoJ0SYID51/h43Z6FKQzyxwkO3rd4+ms8Mb37X6yhz67cMivUzVx/+y2sDxVO//9nwFPmr3j6V/40fuHXfx/v/91f9mOwuK+w/+MeXUmABbqCx2F9SkiWwP6HHa7fCenp5n/+P3Fbe30mi8iY4TjckLB2g+3aa2qM+QnlGC6F5jMLF1cMCY5KjT2zt2QbXHbDLpesfeGOby+vNs/z5Jw1HiJVcTIWmdvPXM8945FdLFH8i6eAtehkvXp2ziroPYsdCbmK7XuYq2vQOiiQy7nVxSXSWHRnvgDqmrMwTzkl6ynZXNZBXUgUn8cz+/Ez2KUc171Z5wmyxcRDmo8B0KNnAIDyKjxQtlrDLldRIZrlOgdjoR4+85M1Ofc+K3JYYcV2WZm0qmEjbYz0Q4K9nnNb5ZzzCmhY1T3LMt/2ezhlNfN4Kaa4NoQurpEUeWDhBlD86AzZWenHltY1xx6aFjpLA4QbgE40p0dd1kNiFH1d463f0tj/wws/jjZLoK6WeNPe4T6cr2Adc9f+R1HqNCVk1zWyp0ukFb8M9MOzcF0jr3Tv+yWmkwx4euGzQnd+d47v/YP38Ob3AqXf9EGJ5GIVMWXxJNbPMlBnkJwvkZ+FmMW/WO7g3jvb2c4+Z3stPYsvxMQrGVd33pSGHpeM33S8bb97AdTcC9vLxqC2/X6kezL8bpP20MdMnvcqisr0/ZHFY5TtdgsFQBTQvantG9qjcTxktG/4UczIPYa/6+G2aD+y248X9Fbd9yZsI+PYxeVn459H2rtE7J1RP2qTtVB9FNeS4zj9VAADaDc5eUmSwjm75byfYq/lZCHl5+4/YZtP2d3CtRpH4ZOEU4aRJqhAwP2CUGvAdBA1LW/bEJwCZY6Dk0kSSpy18uhDKxBcG+DmlKaBRVy3IepOKpDtjFXVSAVYMYCNMvfBvjTcHvXFt8toF0zVzLLkHpA+T1iBq+thC5di7A2rXUXl+55ngYyDXEtg0wVn4/JwP0bunNH/iYizThIEzlKeXIhgi8zf/H2RIEkd2W46rH2hNOHfSaq472HTxEG1k3AdRclLIOLRuAy2yTgrQjNVfpkBcBk6rRL0TtdUVwmzeVt4rdOudELFBkgWKdppYLTy6XGJwWnFbc00dNQmkyVoDghmkvlAsCk0bJ5we6wNy5DCtcUdB3C39ecJ9yai/xbAvwXgibX2PbftbwL49wE8dbv9J9ba/9199x8D+HXwO/k/stbePoJyS7uVMLJMGDe94duAUiRLHPluI0FeUXaKYhZSLj7IxkQoy0Eb16yvGetuYL32f9um9Q+qbRqo+ZIvrvTH/d5H4FXIvti6DkQt0i53HESixIPvR7IB1v29kT1YVUEAWZStOiZvkeyAvshYxcvYgYaHXXN5+6B0XtoclaNjueJxaENmS8bdupiBP8ay8qXvspYnGT/TA03jX47ZkwI0Z1Z2n+oEOBuyXIHqJspaGKj5EtqYQJJsjS9RRzuUAmBxauX39S/kvsfeg1CODgC0SkDzJfInDp6+qKDci0N17qHONKwi6KqFulxi9sBlTpYr1qVVakAMpOZLUM3s5HKPJOdLHPxxAf1sHibFmrVTPfG0m9RUlYHaHjRfwefRrAV1t49Z3Maz+O8A/JcA/vvR9v/cWvt34g1E9AsA/hKAXwRwH8D/RUTvWru1tOgzG2nt+TGF3Ia0ho06Tq6YRz43juFqGsg9zKxr0QRauvncA5f8WkRrECmosgi09E0LtTcLEGkXFKTDA65DcFyVAKD293wmgLoOtM+1A9R1MHeP+YI/4WAVzWagpuVsRt+HWoSqAk1K0HQCde2CtJIZ2pvB3AnZENV1oDyDsRZ0dODPBcBliWqovRkAeN0Qc/cY6pohzZ6roshhDqZ+++rrx5i4QGp/yL8na6GuV4FEB0CozFWgw33ABRdFqs/sld5bERIeczSDulh4cJV98wT0EEwR6PrQH8+gVg0D4SLw1NV7h9j/I82ROL8UYjXz9OE1+mkBVQXwVH/vBO1xgfzSAeFmU5iDKWjdwhbpYAKweYbmjT0P4RbAFc0XePjnCh/MpN6iLzXyJwXOv8XtnT4svZexeDN4FiYHirMCew8KPP4z3I+vfrjvvCY14I5t3rmD5iDFrO18oHH57jE+/vMGxbNjv9xY3c0xeViizxXIciYIANZHGkltMXk4werN3F+e7tHtcSLPDXBaa/9fAOe3PN5fAPA/Wmtra+2PALwP4Fdu3Zqd7Wxnr6y9TMziPySifxfAPwPw1621FwDeAvA70T4P3LbP125RSOaZsrYFHxG56NYARvGSoWmHabcNfggbtC7IpU6FKWvM/VitQyGXLJnqGmoepTsj1ixaVCBjfbTF1g2vQ8V1j1OzTQtL65D2laVF3TA2QpobfS9pQN/OpvFtj03NK98uWzeMGIQrSHJv+/zZmttlDNQiig24Yrx4/DzOolqHPjg3W1kb3HoR+9WKC6Fcv9W1Y7+yxrdLXWuQqzpFH4Bvk0dTVv+KFcmIoFYtqKr5fJFIsVpUSDUFAtxqDUXEfJdNy8sBZ9T1SM+136bcfdL3PfZ/bJCeC6sWxyhoUWH6kL3X7GINs0wcMze/1btCwSSEbN4jO19j7yMXy1rL0tUOxjK5qKDqLtxXAPKzGns/mCK9XPoxKImQXFTQLlaROJEhXWdQdY/kYoVSwkQW0O3tI5yfdbL4+wD+Fnjp9rcA/KcA/r0XOQAR/QaA3wCAApPn7P3iJrKGXt5w8/wAEGDESoOo2xqsHB+Xy5dDYBVb4N4chCTPY+l29jUCMScGAEYSxrFJzXwNMUzbm3JBR6FM8+jA6PiAbye5IOVgX6HxH9UG2JhfU+DXRLBJCFyaPIGWIK8E+uL6lW2mdeiDrKfTiM8i4pWMBYnifQbBxY6zEzZqf1dqZC5A6sddgYN9i1Hw1x3HpBoqoh6wKT/U0o7BvkXig6EyzkSEdkohwGktTKahtPZLD7NMYAoOcLYTPldXKPQZoDoFk2m0k1GgNzZSsLmGKRMkSeIrbU2u0e45LIWbLPpCI8k1TMb9MFKiXmpoTUgWCfqJa6to0N7SPtNkYa197PtB9F8D+Efuvx8D+Eq069tu27Zj/CaA3wQY7v0ZGvHCP9l+nJFnMk6JbvNibmNjYVp/jCg1t227AMCcYK9nR3peqvbzshvSlACG/BmO3XvA4TgKOm8IIsfcj59HO60dFL2RpA0VIjZzFZjCYkZ093/qzYtd121mRn+PUqlk7UaKkowFWc6G+DSq75fhMJnv26eE/AyG95ikaEdsWPQ5jPlnmiyI6E1r7UP3338bwO+5v/83AP8DEf1n4ADnNwH805du5UYDorShZ+d2jFLxPvHn2NIoXQawXgQw1ArVilO0fQhwitSgCAqDFP89Oo+dlpxxiW+aIkfvqg7VReoFZ3CtYQ4mLs3q3nKTArRcMuO0roNWKeA1U8mLGLlgb56jn4UKROXaaat1VNUa1YIYE/XDBe72S08q6zMdZTHYXp/kSJ5wrYI5CF6hshY0j24pUUsnw32VILCDdpu9AvraBSglwLlfQjvaewDo90vo+RJYKD9e3UEJnSgORJYhwLm8myA7Zx1VG6WVu1KjqFr0sxz6cXir9gcl6pMCE0cMZMuc+1klTDQTP4R5hvaw8HwUUj1KWmP+tYDMpN6iKzVUZ3wwk0zuPYrFffemnwB94d74TY75z/Fp3pgUTLCjovuOFJqjAs1hgvTj3Ff8Vqcp+j+5RPM7pZ9YVndTqM76wKZ8VscKSW2h2gKrNwTuDZj0802d/kMAvwrgDhE9APA3APwqEf0SeL78AMB/AADW2t8nov8JwB8A6AD8tc87E7Kzne3sp2PPnSystX95y+b/5lP2/9sA/vbLNOq5FlcaauWk7WKA0W1AWdEa3rEWea5JAMKRSUKd7/a1cCCrQR5/i/cSl4eLObCQJYJ262OA18pdrkHGQknsw62ZJTZBMVgs0bxWj+IP8imq2a7B/J1SYW0fIxmV2mi7SXm9ze1llTAra3vn3XSl4pSlteiLUJSkUlEVc9oYgtMgclojyvcNRLzWjqowAXA7I0o7K0ryEU+pzRRsm4B6C5MnHjPXlQ6/kChfSGYJMDmDpkyeQAu9oOlhMo1uGoHjlOLfun/x2NhEoc/CNptIzEqh27P8nRuHriQ+toskdoVCVyj+zjli3dSiz4FuSmgnCu2eW35mKY+zixXJvWQyhT6Ta+aCqznh9GiOrrzjlzFdyd5EXyjEhWS9a0ufKXQ5/616Hp/b2muJ4IxtwFwdg7K2BQZjk4fSOmDRGAbstDqsrCHlXDIp+YfPBQnH53GBxXE2xiSjh1nORQSrQvaGjIVxYKjhmtRF/yM0YYx29MhFwAcgicgH9+JS6Xi7P3yiNoKeIFfF6cbGJOA2xQ9TJNAU6P5cbCMe36jfJgkTnoCHbKo5mNqQ/39YcrrfaQVNYakhN3yfk+dq8LEMRegzxfsqDNW79OiauUmROgOT6oiEl9th8jBeEjjURDCF8e48GcBqFlRyiQ+YhNBnAFlCL9SdOdDPevSXCawi2Cy6xpHSO8Bt7nP3kCfav+i6nHCvXOKc7vjgeJ8RTEroUwLZsMzoCh4okyn0bgIxP4kA5ytnDjs/8CxkvXcTVXssZw9wWi+m0ycFpCmobYeeRW/4t5JyNJb/HrNLrSMRIJlIuh566dbt1oa0KCmouuMb3DN4MU+GdXUNXghHswAxVQER6VGQ6xp6ETFFNS3/tuugKt4uwsvkUJKhypbbrwXs5NoASyCR13N9zK6NHzPVOvar3voxjMWfvWfRRrKILUPmk0UD65C0VLsU36IG1WG7XtT8t7E+9ZqsWlDdMlCr177eoji3UFXnmLPDmz676kBtD1X3Ac5veqiqg16nIQhY1UjmCR+7Myxa7ExZi+wy89uSeSB8zh8nyK5lHHnC0FWL4oxnhmzeQ3WKQVAC954S+ssE+QWQLg3yJ24yF+4MrT3KmJRCftGCTMLX3QH/yguD7310H++sw31bXBik8x6q4ZoVLZOu0kgqi+yyRTkJY6NuQQ0j9npOFiN1Lm9xifrzcBaelDYiuxX5PXcs2zSDjIgQ52yQ7a4bIBYqAAAc70lEQVTrTZzFcjWELQNAVUFfutReXXtIsmka6MsVYAx6eassK68kZtsuKHqLapixmziL9RB2PMBZSNn5GGcxoqHTF0vAl767m7XrWGXEjVn5uAItKsAYTqECPLmt1jwZRYpmgrOI1cJoycuQGMsg7VJEfuwAQF0teR9rQK4PGjzZoeuh+t57EXsPCh7HRPtlAgwABYZLW+sh3LbvoS+WKAAPb4e1jFJsO9A68fByAKC2Q6aU3yavpb7rcPC+RfY0jHuySKEul9h74CaL8zVMxstM3bC70U5YpjBdGuQXDQ5+6AKm81XgQJHrqjXSsxX0KnWEvu46PFxj8p0p8rPrMNk3OdJnUYl6zpNQOk+h6h7p+QpTnyEBdPPF4yy+eIuYsQAMGY6yzN/klGWwVeWYlgJLFZPf9P5zbGrGcF0jLv7xIWi1Zh5HAHR9zTDuugEq91YvcqBpQJOJJ7+h1Qp0sMfU+IA/lz09hrq45noQeaCOD9G8uQ9LhLztYI4F7t2j/sohYIHs4RP+/ZsnIAA0m0BdXnuKf6rWoIN9prA/J78NAOhwf0h+U61BkxKq74E7h9xvqXcoCz7WIUOvcck8DfU7xx5gpBZ8XOPIb1Ihv/nFGY47A7IW9RuuXb1Fer6GjkFZXccxlrZhGPkFw737431AMc2b8HtIhqQ93UPyNA3kN28dM0dHXcOcch/WdydIFx3UuvV6GwDw5JcL3En5IRS33BKhzwnTjzO0sxTltSMcMgarb5xgeTfB6ZMD34bGkd/0I/KbXshv3IPmOTOfXeDprzWejwIWaKcKsweZh3DvfZSgnXCaVLIe7Z6BzdijOPhhiYt/k8f88Icn0GcZ42DEeyXC/JsHTH6zqP3keP7eBL/yF7+LP3jwno9ZLO8r7H2Yoit4GSIxi+qUkC6A/Q+zAflN+8PbBy12fBY729nObmWvLgfnp3gWMZ+jLxRTOhLiifgv41r/+PCCL3BcmMwHaTxrt22a4MFE3JG2c+XiEq2X/bwOCZ9L7e2xcG6Ms0gSXs8rGojl2qYB7e3x0kcqK8vCBQddJaoAnpqG226jZUjEjakidm+zWjEytO2gBMcgHpnj1ByIJQHQR0fDalXhDY35MqcTXrb1fWATNxZoG/bqJGYhtHoyRl7QKZSJe+5SYRNzYynjJrSJtmmg95yQT57zUscaVl+Xe2F/D3a+ZC8zQpNaWRrF90LfczFhnsE8feavHWUps6FrNRRB1hqUZ+H6uIxPf70A/ak/Af0wsFUhz3gp5bw2Wjf+3OJBiSoY9VwJ2r19wqf50SOnSaL98ogZynNQomGurv1112/eQ/P1U2SOZQ0AX6dqvZFlQprwMruqgjCUtfj/Hv9DXNWPb+VevLrLkFvaBrms/+I5aMFRrMO6B5PQbt8/Oq7s6//fdhvn8fGOeFsX9rOSJYDLyNSjuMcoIj7+zgv6xMdvu0HS2LczFiny8Zfwm8Ex6nrYLqntEMQmwCXmrg3+LhtNamG4HHlN14XjusCnbZpw/ig7FavPG2mjtVE9T8gQUUSgAxFISpKQ0bF28ND7FLSx/CIwobbEujiOpwOMx5fUoKTfj7010GdXg/gGOq7h8GX3gnK1xgfGlSjKEcGua156uN96Ld0oZoHlEtaRC/sY1XyO9JPMiUu5MViTC2yPQItahRhaPAm+gIr66ztZDEhv3CZJpb3A7wdM3bGGad+H+gyxF2W4cvyTtCUV6fEdAN9UijDIYznSGjKWcRZxLYvWwxTgF2RxGwGEfigCoPlm9m/wnttvTJAi7PswpvGxhNn6xRvk2+VrP7QOYsbkNF218gQ71hXjhfRydMtrxq94tOdntfj6Sn+Viu4r8WYQPcRRnYyKx0YDZFguUTu6g0hzZWDEuA+fNQPgmdhEC3c8abyEvbqTxbY3qv8uIlyJBG1idu/nH9+95ZwqNcHRy8vXrSN8iWUDXqQmI86idGEZM3jbxBdY3FR506bseVipafC/64HuJW/uT223Gd54EjnXOggUZfASgwOJv753/VqGtgJhUvEYEjMssLutxcQ9cn/IuaWNLaegB29zE64rRAIxXnK+7MTb9WHMesuZmr4PfBRRrUxMaGOt5fRo3/tgplk7GU3dBG/wpvS/NaC2C6llgJe4vYlqZj4/APUuwLmzne3sVvbqehafwXyZ+AtOphS5avFShpwrJ97LTeXuW00RYNTmMgdgl9PFAwD23klrfhPHbqrAzePKTeCzufCfxdRQ4SxWL/PgMIFwyz42AMvIoTytcbEPeTUJUOtlTJYkG0tFt0yTwru+ZzCXLH3scBw9kjXuw2dsSzim698AteoKHSksn9B1IKU4JhEvsbTm2EpcwHiDd8HweF66DNqgRkDFlx1vvA6TxbYA5YByLGzbyJg4pa+Bypc7po/YrxngpPdL2Kb1UW6s1z5zIOey4ItIee5/b+ZzqL099FfXPJkIuGhvxgCaKICoyoKzHgDMs/NIWWoOOmA6te6jB37f/nrBwkbr2mczbNsAKoc6OvKK3pJ1oLIE7c/8+cz5JUf3l6tw3lhLteugJoyT6K+uAWug7p5yJB8IgbA0AU0m4XxvvQH6+AlX3wo9IQBbVbBXc1ZYH5k62PNgL+m3mk1hnWYHHAkxTQom6hF6woN92KtrmGXl+0BO09R2PSjR/hZof+4u0o9HpG5KAafHoItrznw8ehK+Oj3h7MRi6dq4z21rWRcVkX4HpSnriDqBH5q6qtvHT3H97bew932XYTDMhaHmSzTvMNVeclF5cFRz5CpuM4U+Z2RmerbC/JuM09j7xxUHM0cBbfra20wu/OCpD6aab7yNp9/ex93/O+L0OJ4iOV8GrVPhs5ixinp6tkB35ApULGC/G2m6Psde/cliiw2CmjeQ3NzoBcjkI28/eZMnCUeGowDYBqGNSMJpPQxqJcmmBqoLUMWEtkiSwIattQ/CkVZh+/iYWvtPb8LALdvkxkoSn5ID5A3DwTYvKkxRH/oI/izxlTwL4kcCMU9TZtF2iM5umiNNudgpbjc5UtttAz8I2EmsIEvDdZBt7vzWaP9/v48UqBUZs06pLhT+AWj3UiT5aBy14odskfKxYya0PIOZZL5wjhzLOgGweerHgQAgS2HKFDoL7XQDivWhYgEgMDjNZBpUp2gOeF9VdzAlt7M55M8+I3Q5gUwCvUqxPuT7aT/RntwmNjPJ0M0cE7kUks0yVKc0KNPv9lLoKvMM3jJZtPspYAG9yNDuuXvBIii33cJeu8liHBn2aaRxGtEFDWO4t+iD2q7ldFP0OzNfbLBdbxyzZ2JgU9ee+JZZp1eRQjifQ/Lhg/PPF1DyIFYVjJy7aaEfn8Wngpkv+JhV5T99O6oKxkQs43KO5dK3C0BgB+97r8RlPRTbkb64gB9lGXtBT858oNj3qapAq8rDx9MfgVW8lAJFXoTpuqEyXNyfCB8g/aZ1HWj15MF06VR/7qfnfh/j1NNoVTGsfJCNASbft7BX18MTk4JKEpjVCpQmIQgOQD85g7rIgkqbtaz01nWAIzT246s11HIF47wQWlU+ixFLCsIapuuva8wEnVqtkbhJOf3Y4VJcpTNVNeyqwqmr6YnHKTb94ClXKkf3Qfb+Y3ylvsOSkc7KZyVsVXnJACkpSPOMq32vF5hcBpyFqm4f3H19JosYUBMvTT4NT+EFfd1/tSvIIhXlyV1UXYBcZsux4/+TYlfTRZkHHgWpsIZvtvByRjgI2zONPf/HBIr6aF+P6ZDP+LejCD5pTlvaug7LLaWciHDAJXgxYY+3iIBSxvKDIxNwHGEXrAXcRBbVf3iTzNGWazEYj/hhEM/LpVZt0zrvJIwjAIbtxxgHyTZFKUF7cbUxjjw2nCWxAuSSU1dr9mJkDAwXCdreQCVJhM/gftlVNcB6UJLwsiWSFPRt6XufPbBN670FIa7hiUbDtsz9KtmLbfcNAF56iGc7daUK13MkDwgmxniM6pEkLUxpApye+LqiMAi3D/DtsiE729nObmWvj2chHkDXDYKW8vdgeWL57ckw8EgpKlJR1/tOu2K1Ylf18IArEh18uT87829b2zkXOUk5t12WILdmNZdXoLLwVaFyjuSt+7DRGxhwbwSnnI4nZ+ENcXEJ+sp9wFr073/A7Ts9gbm8gioLFjaWds3n0Af7oLL0LrEvZZ5NAaetAQD20VMO1DUN1BEXYfn4RpqyqJIrqOvPGPKs3/2Gr+60rgiO0hR2b+q3t197A+kHT3iZNw00frSsYM4vBghQ7qCFfuOOf/vSjIOwdlIATrBZxtPuTVkoSIqo7hwBZxcw8zn0PVaCt/tThlA3Lccv3Jty+fOnmHzghJ59pknBFgn02TVsmcM+eOTaZEDv3Ed/UEJ//8f++thpCdV2TD6EyLIU5ngG/YiXG9Jv++HHePpX/jTu/K4TXLYWJkuQnC+xfPcYALNwGxfgrE4dTDznmEV5YVA+XOP8PQ463v0/PoKdz9ljir2gb7yNfpYhe/+xX1K2f+ab+PhXC3z1H4XiwfWdEvnTlY9VCO9Gc5BCNwb5tPDFfzAW5p+G8oDn2as7WdxQ0wG49bUAfPKcYwlRJSpg/OQxnkT8MY754SGBNL95AjWvvHgMnp1DTSYMq146N7XIgb6HOjyA3XPVlqsKeOPEu5dyru4rd5A85oi6BNXM3WMsf44j+ntdj/YeP9ipMbj61gnIANMfczbE3D/l8uv9Paizc9DJkTvfCrhzjO54huShq+twWQrcvYPl18NkMVs3/GBZi+4rpwAALW69ZDfu3vH9BYD5L95B+dhNeJdMq9/t5Vi9WaJ8wuP7yb82wZvqLmAtVvcd96SxKB/VSCOAEHWdL7Vuv3qK9BFPCM39Q4AI9UmK2R/w6fs9Pk51f4rykxJqzm1Y/vwJpn9EoLpG8zXuw/LtAtlVj3TVodlP/WTx0b+hce+fHMMkBJOEtHRXAofv51ifpDhaiMiQweV7x5i/o/H2M67L6E5mqO4VSBY9uplG+Si8XNpZiquvZ7jzXffQ3+P2zs4v8Qu//vv43j94DwCgeovmgHDwxwU+/vP8sO/9YIp2D0yz8id5wjw9muNeucT3PrqPyXem+JW/+F0AwIc/+CbST1zVqcQ8tMLTb++jOiV8pb6D5AH37eNfLfCHv/H38EvP/qrPnF5/w+Dwj/bRTl3VqZvLV293SOYpDn5wgKt3eRv1QPP92wc4X91Csk+xeAKgJIVtG94W14lIetWlUMem3FvdOhy9mk05ZSZv8GfnUGXB6005V5r4oiypMegXS+jZFL285d259Okprw+lgAlgD2Q64Tfy5ZVXNTPLFejeKag36D/6hNt3fAi74tJ7u65Dqna14iI1V4wGwKdn1bT0b20AMOcXoCyFWVZQLqVqnIqZ74t7Q/YuhZl87Z2gl+HaTknChLqiQnZ6CH1+zW92SdX2Paiq2dOS4jTRYbEWan8vFEZNpx6HYNx5fbam5ACdxAvUwT7M1TXMcoXkLk8Wdlryg9SbgWfR3D9E+vgaSJOB1im13DabpcAzF4hsO+CNE1ZAe58naGjFqeCu48xSFEwU7wrnl76dANA/eoLrf+eXcfg9l7Il1h7Vz+ao32HPIr1cO34Jg+aEf9eVCiBAry3yswpX3+RxPP7HD7jYK0k8nwiUBo4PYMsM9OCxT53aX/g6Hv2r+7j329deRLmfpkgvKn8+kSjopymT/Vws0R85NTUL/M7v/1e4Xnz8s1FI9rmZK0gajNpLTqQ3qX/7JdU4UDve35hNXQ8PI7+97NwLWdwGR6vvxyX+LhLrAdiz8EVZ4yDxWA5BKPleFCi0ZTz9eYGgZt4Hyj9Pgd9vto3MljH/DEbxIWwYhwEdfwyhBxz9XvhuKAVghzB/2swuhT6AIebjMRgH/m9fL3aj7QKcO9vZzm5lr6dnMdYIkW1WCsksSD9HkSx2lRECbML0LAVI/m9/GueWOx0OWq2YdUrQjZIJLJhzwUZvVUpTDowRAYul1yixqwq2yAcpUl9J6GHVI1BWWUYFSu4cee5jKQBAiwXzIKzrgLR0uAjKUv5dPgxw2dkkFLu5CkbKMnb9nTRie1RAXzAZsACCrAHrbFBAsQ5IffPMB2JFzNhOCpBz9YVfxO5N+I0sAcq9CWi9Zq5QGa9ZCVQNpz3z1L+BqzdyzOY5p2Dl95qZtpOuh53koUIVgJkV6GYZMklJliXs/pSDq3k28DJtnqI7mSF1HJx237nyzxIs7itMHwh2ATCFBtU9Vne5vSUR+oJT2Ku7wpDOwKziwkA3OZb3eZyO0oTLzKV61Fl3PEW3l6J8Vnpk7fpOietvGNz5Tuq9m/VphsJYWMc23jsu0vooQbJOUQBY33X3grEwP7y9v/BaThYD3oQRXsDv8zwOTs9AbTiNvl5vcjtYO5gohGfBdp2nsrPGAtV64zy87m48FBsAbN2A5vzAmaYFHHUc2pY1SiOX2K7XDovBAcOYj8Lzh46RlnXtjy/nIPd9AKG5/jQtVyeOcAm0WHldVIFc277nSdcFkLOz5YbmJ6zlbTEeRLAZxsKugkanaJZSb2DqIWkQEXHfJWYxX8E4LdnBOV21JXXhXigfrVnpXTG1njsglFKgxQrU9TAR87i6XiGNxhFU8QTRdUDdDmMWXYdEKb9NHmPTdtj/MWuI8gYLmzPce+K0TpOLCknOnJiqc7GFXMGkhHTeI322wt6HaRgbF0fz15UIyfkSumLuCsmw5U9XOPyjfaQXgc+iMBbJ+dLLMCbCQr7OoJrAOwrwkkU1X3I+C1IEOxI84LqMFzjISIOUi3U2YwQDL8YXA23CrzfMcRoMOCEUDSj5PYBLKaa/F8AUwMxfjvfCxnwHUuymIor8mLMgpvYngvBiCH38oFBtoLUSxsW3q4uKnpQKBMNZwkLJgKfw53S1GpaeC2GvcqAxCfTKPkko4vJ9cVqlsbwBEbFHF52TjAHZhPd3D4rJWUYg1qIF4Auz/HcAB/+cdILSUT/leDGcXr6LdVeTMJ5dSSGgasBBRa29GphOg/aoVworFPqUoBoLm2rPlen5LbQeyBkg0TCZ9shMALCpZp3VSOvUZqx3K9sE9i2fOk3832TxQhwtr+VkAeDlA1NjLY6bjvtZtU5vOpc/zTC4JsG2OKMz0Dp92Ta8gN2YIdsWsBOPQIKFo76O+Tj8bz5LFeS2APC2wLAEOQE3sUdt3gi24sV4Sra2C8MAooxJdNgNrVHL35P7LY2bEHvKn9I+/r0ZbbNb2/Cy9vpOFi9bchu9qeV4/o09OM/QsyDl1uGyzlX8ht4sOuM36eBNq4KSGOnwprZwb+j4hpLSaTl+3F/Fv98gkIk9EOmjL37b9CD8byKziQ7tUsETGKioZ05NPCpHt8rFVW7wLDZU1ImC2phsk3ZpDWgz/H+8T6I5jTs6n8nUBvOUJQISFTyFyLOA1qwvEvdTK5Bxn3FftGIvJFZOA3uIXRE8C1ZgZw9HvIgkVQyOijyLrmAxIN0QbB55FsKwpQjxfWdT9oIoiseYVKMrnSfj7p0+VUhS9kLIBo9CzmsTFTwLY19IkWyXDdnZznZ2K3s9PYuNOMJoG0IW5MZsiDBrgwVdKHWszqMSbxtTojhCG4o4HpkZPN1c++cZsK4H7iQlGqbIAUd2I1kBaJdViJclacqeg7xNo1JsuN+SwNejEmszKcIxXDvjc4l3IAzYvh/ObJl55CCMYY8mSwfbu70UqWSTpDzaWv4+Imrx5fBEw/W+lHlPctBV4tsOAGZSQDVtIOydFAz/JuV/ZyYZlFyfqES+PkyQP8n4zSul10ToiwTpquY+iIdFXNrty77dNbOTHFgr2CLl4KmMS5Zy5uRSMjmhenR9SuhnYRz6QkNVGdZHLk5QZ+hKDbIW1bGLWZSErgCs0kjnKapTCtdZq+H9RIRulqHdT5Hmmc/kNQcpVm936KepXwbVRwn0OtvwKOpDDd0o6HWO+iioqNvkyxizGFSdmuHf422A53wcoD2FjQoID7FkQ4RDMqoqHLBJu99QnnvRYz6m4jSqLBWsG9LOVWDG2QFjmMS2d+eXm7FtQY08oK7is22ZQl8Yk2L9UCf/ByfyS9JfefDleSgKToX2JvBceI1Tx9/hJhFVFDxZdia0q+89Yxi1oQ26dlkaIlAdMUW3HcsfbGOM7vowFlHWyU/OWcpLsUTBHsy8TKDVBCpyqLLw7fJtabvBMkrXhtGa0WmtJlDioNNtXEkKUNNBV5GCWppwKhbA+s1ZyBq0PUyR8fo/qujtyxTp0SGSJXjcwBke+U1S832j6h7aTV6yjU9ISCrLSmGLaAxj9m3fWAIstxGnTjagMUjmKVSUtUnWKVSzGenXjcLyTY3ySRCNZkKLzVPdZK/PZBGnFc3m3xupy7YDTM8K6xIpjmpEfIm1/K5aD1KiW4/ppAMBhDLuroO9vHaK4QFjIJDl+MGJU5umaT1Hhe0N1HzELuXSsbbr/KdvR9cBi5C+9OlZYwfrSrNcsVbrchWwE03DE4DICTj4t/BQsHyeO26U1pSUJgCkZ6tQZBaPz3rtJR7HFkO4pd/qSoXS7roGa74WzF4mqdO+h53PuZjOTSxKK8Dpocb8HeXjNeh6WCpOWoHWLUPn49QpOC2b9CEVTdcL6LYDuh7lqva4EmstdJpCTUtYt00ZA3WlYC6vsP9hx+xUAGAMdJqA5itMHjLmJblYIVnwo6ZanoL6TMFkCtlli/R8hf0PszBOWwiE07MF9CIDrhf+HsynBQ5+cMCSk84KsASlFs/PyTjqdY7yiUL6ZI6pTGzWQrU/C6nT5zFlaQ074jsYHEPo6pV7IJycn4CtcH29nSlLs5iR1HVgWYGKHLSIKPGBAJqKI9URaIoWiwFQKgZT+fasVsyZoJqgd+HazscfRcHzjI8j7v9qxd5F04Lc8oQishtY68ForoMBFDU4bj7Y3tyZILss2JWPQWAAaDF8WP13EYhM+m1nE4818QA1AYUJNsVR6MXAMrM/Aa00qA6eAABUdwvM5tPBea0m9NMcadsxCOxZGEe7N0F3UHLBHwAqCz523cFMcmiBZlvLy5CTKVKHNTF7U0AT6CLB9TsJ8jMH0uoNTKaRAli9KaAsoJ/weVdv8GeXE/qCUE4UptZ6ScHZ75ZbPYvuaIJ2L8XksvQvsfqNCa7eBU6+F/q8vluiADZSpvVRAqsJ085g7cBisID5/u3DlrsA5852trNb2WvpWXwhJkuOW+bcN4rAPu2Y8f9vOs/z/n9bGxeCbcF48H4jr8TJGW5lIZNj+E/41ONtjj1oz01tHR9iXAg1OM7231C/ZX9DHEe4AY9B2/or27dhSeRc1vqvyYTjeOxEVBzGWAg5Bm9TPWCMdb+Njn0jxiUcN/TNgvoRnkOOF7XNn5ekX/F4bT/dNvtyTxafBtwaKTUxboE28Qhjc/TqA9zDNsyHVhjjHkgrmFSWPxRQhopRd7GRjvLtPu8etX0b8s7RyPv/+jabzTaOKOKlmtWmOlIeC/gGq2OchWAh1PB8WgWcwE3jIX+D19NjomOrR3GQhIWZuE5GkJ8qoDSj8e0L8mt0b8rhCpTa+M6mGiZR0BSuwwaFv4yRIpgkoFDlWLY36CbuOwCkLEzG4yLYCePiE0BQNe9zoJsQuoK/6ybR2Gy5tjZheDiIfBDc5ArdzMCkoV9doWDScL5ePnMC9RZWu+MAII0XWlu8EnwWRPQUwBLA2fP2/ZLZHez6/LNgr3Kfv2qtPb3Njq/EZAEARPTPrLXf/mm34ydpuz7/bNiXpc+7AOfOdrazW9lustjZznZ2K3uVJovf/Gk34Kdguz7/bNiXos+vTMxiZzvb2attr5JnsbOd7ewVtt1ksbOd7exWtpssdraznd3KdpPFzna2s1vZbrLY2c52div7l2rRvx1AsB4bAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.49383592605591 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-09, 'kernel_type': 'untiln'} is: \n",
+      "[[1.10500009e+03 2.10000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.10000000e+02 5.64000035e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.10500009e+03 ... 1.12100009e+03\n",
+      "  1.12100009e+03 1.12100009e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.12100009e+03 ... 6.44397806e+05\n",
+      "  6.26337824e+05 6.76884046e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 1.12100009e+03 ... 6.26337824e+05\n",
+      "  6.10895915e+05 6.57918225e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 1.12100009e+03 ... 6.76884046e+05\n",
+      "  6.57918225e+05 7.23341419e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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1t6S1g7gNz5t99HneQxYC63t5AGKzA+YHkMKI/eZv3PdAl4dx4zg34us+HVOMsXRwcg9BOutCGNReZgaZ45l5g1xF4cfc+9QeJ+dhdGQGngfWMejcRVJaTv2HuWJmEHOcN16t5Vii5OTsw+8D6jZ3nYxV57EP/Q84OON4ejNOlcUye7mQZ6Bt4zZetyDq8uP0YfYMtB1ovgz9+NS/Mal43QJ9WCB1+2oFd74At126XwBZTHRhjiTLPjk4FwYXMsR8vkXu/2KhPJn7ahaROzLcVFUFIk7ELV1om4x/wuRZxDd9iDTE5By9oTVKYB/oqkpvYuYs+49GjVw4JTypqnhjESzZTJ/faKYPqqrM060ZhtwljSk+AGWURKM5TQOCLgYpmxNVBdIHbjyW8fd9IuvRhdC87XXc5Lx46aMWZ247HY/VLJAWj+jFZ4pjpbqWhcJLu/GtOhmn/k2UBr0PWppLCwsTaNTIm948PJlmkVqImkV5Drxeg0+PQaqxOALqGgQkLYIoRlloEuarCf2w+LD45Ei2n53L/NvrTzJW1CEao9d9PIZ/eAy6mEd6UarDda4CvUKI+tGoSQuF0Sww3/25OfgsDnKQg+wkxKX6/BbkAT3hn6Q/OfjblVXUjf/ixrR6Wb/NzWj1ruk4VR8CgGFaPQB3Cn3eddxb4NA6b1Z2otW77bFlA0haX9SEgBj5iCbGdee05OXYiYMjp9VTn1L82dDqbR3bkLP7sn4H7t1/wt/BGb/YaWLfXTPkMrDVBoZfU4xpc9s22UIrHyc/pPRmACFHe+Sl7ODNtvuGhSGCqtTuNqE0uz9vsDMhHadyjbByRoyiY9Ob2voiQsgv49sMIKnoTO066dczYJx1yelYAN6slA5sOzY7twaUFcORwWwCIL6NdRvn14XFIvpqnJNQMICNokAbkzNM2FudHEfHJ5yYS2IC5lykOj8AksO4acDrNdzpiey7WsfzInPefiB0SqMR3NFRntYefDkbQyeK4fn3j7C3iK0P/RZ2SB9VC9gHZ2E39Qg+CggGoO+z/vfKoM4IbsOHQa4JAJzQnFq+boOdOlss7k4b3CC6jX31IE6LMXM/iLOw+IJBBKo0da3QaVq0jTZg+zcM1rD8EuoQBtJDbRbAm0K2uetyJ6lqLBvOcZ/8QH0vC1vbijM8LBIarWGYe3/b+DzLAjBUN8Qu8gB4n4yxLfLuLhZ3LVsXlAJkdBvt61uzpHTLFhTjeAx9byMywTatoux3l+2lbKi7A4seLllAi7fvIKhMj9uFz4OLxavoM++/T//t4uSTA5wiyp9lPxtVupKLZPih9QGkFoV0ER3YX6MpurDpfC2GEtfC+Xq3pXxhC54NR7myuYi/cb4LgAO790EOcpBbl/uvWexDllvuM7g9hTwHcRb7jKuUAT9J6lZDubl9HlXujcI6d+Oz2GWMMOp+WUjHjpWceTMOtJPhU3YqMjSA/rSajPoBCv8K+mJ/HVtIkEuOxOv5LNxknDvCdRxDIe4tcG8NqbINwVpfGUzyoPos6kaS+konvE1EMz64SOH33vksVK5UDXdQZVXsjbd1gUkq6TAacQtEdycOTp//Zh7gmBsRcyUuMzWCWj3EjZl9x6YpYzEpdgx6cw2RuUZgj7abfBUbhXSYMUhJZ+aeje8jx7BsLpp6HnZsWsRHpC92M+ZFNq7w4Hibw0FStsBwcJbZr6VY/1OslVogdeHFh0FqUtoKYRrdAgd/ScjUVQDXQCSPPWJUkKoqf3H0fcb/ma53wIM4zWVxEglarTLUawbiu0Le/cXiprJtgSjftCWx7WUqhcktiE48vXfjql9vOs5MCjmv1xnkPEYQFP5swWbFwgKiLOU7grIC3bui9nKK+AQis+ebwd41tFiiK0O7JQQbQH7jqUN4yBtvWJoycJUuyLpYhFR4vcl1H+6L4xQRahZIdzxNDkztN0SVJG2bJAKjv41GMdKg49LoigXFKaKS6tqA5hS818E9eAyezWynsj2An2LKOJDg+Br27Dq5F44ElOVfvhx0uNJ4LGNdrZLGMZ3CPXoIPH+R9tM51fvFpXmNWo2hMaB2d0/E+7tYXGWexJssoR/tDXkZYWuewNQPv4WUF6Hgs4i4kbbLUJU2ZySOx5ocdhELarZGJzIUquUqcKEPb8J4fXqDs3cbyE5FUAKIKEptN24fjeJDniFGtZ0h7UvnQz/rf5svAkQEadQ+dB/i7DhyRaVyABiPQRv1O8LD4cUEyGDZdS35OusUrkTTCDLUtktyLDV1us6KxO096HgKKI2iT+NMCM51RJRGnIdzsk1DpceSG4Szs0EItvBZOFDXgVVrGI/Ap0eg12dpx+lEUJqGM0TmoIn3KdkSjntEpQ4OzoMc5CA7yTuP4LxVuQroVar72/azovj7faqf62+X1Q25ykm7T90Qq65fVjdk6PtQX5chFK+aX9uebeeyFPGNZLot6FGt7r6tjRL5OlA3xFZAt+ZA5pQNY7D+jcG6IZrRa30WZUq9YlOuUzcEonF4k0k7VLUsjrdywURJY/j19u/hzD+/5wjOm4renPZBLrcDyd5XGjs1Q7axc+tNEvfr4EYN/Cq/eWk0SjBn3WZSyP1imd0gTm3WYPvGtPehh91VWcq3jQZY2LD6RbjtYl8W9JUVt2k7AF4QgepH6AszJGx3R0fw83kYpzFDgv09OG06H0g2M41GcX+ypommnwMR4ZglqIVkr9IModMT8IXxHej2ppYoQ1XFcet5UFPDh2NoNEpJauNRBEpBzRJLwdcIyzYvV5Ki/iqkqAczZAOVeYkZwssV6OGpTPkPPhsohQi401NJJDPjp+kE+PgDVN//NO04DYlxQ2bIdAJ+dZaS2ZhBz3ZPUf9yaRaXya6ahd1f99s1fHvbmsVQ+6VmcVX7Q9vtGMttwN1oFtvajlGagchN2cVNNQszf7vUOtVQpl0IbX+3qVkM8a5SeDnsqlko56ldYA+axZdF9l3Yyu9vkiVsH9klEetNym2yaF17CJtYkb3bUFata8q9Wyz2KjIEZG+0S4sMbcNfXNJe/G5/vqzI0LY+r/rtKsm0gR0esiGbuBltz9bdGNs1kGqD57od4rzxPWNQH+7/yvtiqITjxrYhLEdxTGiLPfIwcrlra7kurxjaVeULDaObLTJ0VfnCHNqt4fxNCPgu8vaXzIMc5CD3Qu6dZhEBJ9tsb2CrH8Gu9Bn3BUIc26QQ+9Uqt5e1LwQHm+HqtI66yGV5dCR0Z8ZepbqODsgNB6fWjQgxczedSpsx3Tk5XqkZJc82kMBTTR1TsAHhh9TjY10SBRWVDs7wdqwePYxZjBZERaMmbncPTqVOBnPG+cltl71lre3sJqnSuB5DVZU4LdUBGOZSnbduOoFfLMFdC3d8nK5VAIBlDs6HD8Dn55t+ASLwai3Q7lmqEeJOjoFRA//iVZy/6OAsODhRVeL0nC/itQSA/mKG6sf/IPD5Cz1paWO5BD16KJsWS9nfe7DiKQKbFy3X4Nkc/NET2f69T5KTWOfPEdzpCahp4F+fxd/rr38N3Tc+RPVbP0hzMBmLEzamC4S5GI+ArgcvFpHvFQDoM8OfcoXcu8Viq2wL+21Rswa5J3fJMg1eeEsFL1GPcmHqNun8uzxtWh8e9oHO3XJwFunJKWRHcmy3mabNbZcp9uw5Qo/jjV+o2aVjjperTQ5OzxlPAs8XqT1beWAo98DMR4KId/F/iUJl5uxa+EDWCzaU92zGY6/jxUz2GfLF9H0EpGl/vFoJn6f2vV6ncg0DRYbQ9+mlYMZNL15nUZYI/gqFh7IxtW3cJy5I6xbupbwkfEhZzzg4vZM5r9ZpjAD4/AL1Z40QGnO6x4QgOJyr9qvlG9ZtOi/PERS3i9zPxeI2IjhlyvSWVOqdjh/kxjAPgUk714sjD1WxOGT5BdvPcWOs1gdgb3DzO/ty8VSNqUwdtzkYCvfOuRkiDyT7PMN5G+8Ce4CTlz6SIpf5HgAIBU+GJaiNKepprtghzVV4kBTiLacZFpVA+muvFQe0aRY9UHu+R77dycJaEgyDWRbY7EUQCIo1StH3YK0Qpv6zysW2uOuAUFzZEuXY+eO2A/milkjXAXbhBsDeZxXQOBIX94mM2ZIX7/Es3c/F4g1JzDq9RtQghrC2MGYNkr+UNSa2hQi38VzcsmyMUb87F97uqfYFs55r4pIos05vUiskNLC5iUgWjGycLl0zZRsrQ5fRcWryfK47p46QlR/QqIM+qJc9kHFchaO8cilJ75LoBxEJm3mxLZYvvEU5ODgPcpCD7CT3U7O4CvC0SxM221KzQS0HgWWuMnDgjVIA24oM1XWseWFhwVTXkgW5XKXkqa6DG4/B6v8ACmiuLTIU+m/I+BsSCjVzONoiQ9GZWmSdFkWGaDKOdrXltkTTpGSzoykwXwBVcvQRkNPLlfOtmaJAzjM6UGQIRZEhBL9FRH5qRi8LWlKvvDs5Bs/mGxoaARHNqoWn4Z04g8emyHNDWSkA62PaVmSI+x54/FBqhajUNbBcwj0QVCars1znF5AiQwDQ9YApMkSL5UYmLhxJBmtdg0yRITo+hn/6BNQlnxk1jSBGoxao81qBvQetVlLKARBTp3tDWadE9F0A55DAbcfM3ySiJwD+DoAfBvBdAD/DzC9v0s9mxyF9u/ycDy5d9CE1sCAmobqWfUM24daKZEhecyAsFiOzWOg+Crs2DiSqa0lFdiRVtpXwZOYlWxAAQkUyNA2gtS7YEON2iKS4sWV9sEZNTHUGANKK2exjlMTbOh19HxeXuFgcTYFVuIGCY46qSmDEmhH74DQ+SDaDkVarQagyOZJz1YcyVhYbpWtjMzWXS7MwHUW/QIyiTCZhQfHyYKov48nDSHKbmSF1BVzMBPK8SuQydDSVeT8/T9dsGtqu67wYTyPXzumiENLPabVC+9VHGOl5e5aaII7gP3ggXZ0vwKFOSP8gVJ5rKvjaoZq1qF5VWH9V9m2+eJEefDuHp6fgyQhu3abr/vgBZj9yitNXqYI7H09B5/O4GLFG9yZjqfNyPgefHqWxnu++BNyGGfInmPknmPmb4fvPAfgOM/8YgO+E73cve6LaiAo7802IKxicivFsfCeX7N63IXvMz15zSW7v61V0dnl7arMPzN3Gdb9k353FHuqKtrfMCxdjYPU9DPkwrhpbeT7lb0S38qTfhRnyLQA/HT7/EoB/BOCv3GoPQ5GIAbqz7H8hkRgmRCsiPmADreg3QrK8Xps6oyyqaXGcbPOZGcLLVVLxuw68SFEBxS3oTa/qcvTAW49378Hz+WbodLEUlVT3a7sYstTQHtuwGXtwQRbDr882PPLsusj5AAB49iKGPTP+CI1cRFNOhxfmSPsOyViZ2RXLA6zz8gvKBOX7ZALYMHNVpTfxp73kSTiXTDyfykvycpWdmz+/AK3SteT1WjSPgfKFICcmgs6DXp++x+g3P4M/O0+7VlJuUK+FEu/AM9xL0Y4q1UyZwasVxmEMfrGMEZ0Uwmb45y9iIlu8hp8/w2nXpyQ2ALiYSe1c0rIISn4jmqRftyDVXk0FvF3kposFA/gHJLGw/4WZfwHAU2ZWlMinAJ7esI/ryRVmSPJZhO/Bpo7b445lYhNldSl4HUrzrdOFBcRU4bbLwqNUuWR6LDhPO1azRVX1uo71Logp96U4AlEdF5AYbShBWcEHw22X9SWnJeQ3CZQV1P7JONHo26zTxvgcjo+kMDJRssE9hwfdb4R9KbBMxa3B1HNE8JFzNAdlqfnmxmN4z+AAdtJ9oFT6pkwhnRynB91wiRIQ6eSyYsejkYxfM2ir0ZWgrHisgrLaDv7xg1j/VX4T6jsKPgubBcrTcP2bYPauW5Bz8E9kX3p9JguhRpwQtKGjqYCyDAUfHR+j/cpDNPNF8i9NxsB8GcxX3gBloQBlYfHmmLJ+ipk/IaKPAfxDIvo39kdmZqLhIhdE9G0A3waACY6GdjnIQQ7yDsmNFgtm/iT8/5yIfgXAHwPwGRF9lZl/QERfBfD5lmN/AcAvAJKifpNxhAY3zIXsf7l7AZryQ+oYOYDLAi5BrY3H82BaMa/Xm3H7rhNnZujXmhG8kLdDVMe7LlOFuVD3vQUuKbJy7ZMDU88xqOCRpzZVa89yAAAgAElEQVREdpgpjD033/xsUWhSLhUWVm7P8PYTAJeq9QJ+slEL9HK8ENK2yVxarmJxn4hGVLq/WDVd9vXzlPgXYejFGz8WO+5fiZlXVYZzlBNnhvFXMFhg0Qbg5dsVyAWEJoAclEUB3apEuArJ7kGffpHxaHDg4IgmoTVnziwnh957a1AX5mG9lvsAyIBn/Po8MZHr3Lx8hcZ7+FlCj/J8IRXcg0YRz6CqZHvvQWZ/dLsnBV57sSCiYwCOmc/D5z8F4L8B8KsAfhbAz4f/f/e6fWzvPPBSAiE02A3Um7zcDNFcicglOZ1m0YH+dZtK0cUbhCDVt0dRDfXzeUYGo325k2Pwus1g5W48Fu87kdjLStK7WMB98ATwHv0Xz2TfoyO5mcdj8LqFmyTyGhqP4WwY0IQZbTTEn52JWr1aJXIdHadGQzRKEkh3qg8ep+pYhmeTxol3E48fAq/OQb5PKi0zeLmEv5htmHKEKsyHCc8GB24kujXRELbRkONj8GwGv1zBPThJ+4TwKjVNnHP/8WO452cpAgJIdESjKU0D/zLkgTgH9/gR+OQI9H2xml01yaIhGIiGsPJdhmiIf/4Cq3//hzH57S/irjxq4M5n8E8l34MuFtG34h/KdejGFUAEt+pQvZpj9Q0JnY7/xb+T8KZLzlGqKsl7mYxQffYsXnf6xtfw+o98gAf//Iv0wpiM4S7m4LoCeQZrVGQ6Aq07uDIa8r28xuplchPN4imAXwkrdQ3gbzLz3yOifwrgl4noLwL4HoCfuUEf20Un54ZIxgwH4Qt7+6YoSW1PtYXwxuBwA8cxhFyHHJYtb2oqIMpZYtsdCNv+ou2seRhGk/HhjWzfmvomtE7UvPG03SGPDe4i2p7OKzPYohQ9kuPTRnBVQzN+AGmjgD5fU8jn1xN6fdWP4Blcmd90mwvHep9W1kihkMbKfT88VcwgDykXaTVp5jSmKzTsvc7zXWfKGqyiPsSDCcS35Fa2oazhgkyk4IKk4NSzLEQAsHOl7bL9ONZNCK+FGzsDqlKHXFlRe68CzftKybZlfzLjVI2rrMlKTW0wJka1Hkgw2/scthWzNv0DwXlt6nRw10YWLaXnH0pGu+6cUjPaYLAartGb8oRKrs9sXIBce1NwaJAzwwXGcZsvYrXgcrEeuHf3qaJ+gHsf5CAH2UneXbj3ZRyUpSagxXh0Jd2G6rRNFPyIVI+hxWWA4FAkylZoW8vjKri3m043MkljXQoi+NUq05rc0ZGooBo6nYzFGRXChNbHIjUkDKO0IR22cG9v4d7qH1GcQJjDEu5dnZ6mN6zBMsi5h3M7mgKKB1AtgoPDs3yjBk3FTRNcXOeA+36jWFFkQjN+GA5wb3376tt0I3R6fCwOPhs6VbPNYB3kMjHo+BiursRhq+dp4N5ZmHUL3NvP53A/+vuAZ6bQT9MIn8VJIuyNxZOOAuK1qaMJwrMF+KsfyLGffJ7KDzaJlkDh3t7AvauPPoD/2kdwv5f8JcqlEX14sbBQA25b8cOoFuMZ9HL3JeDdXSwuk21p5Kp67mAplGpi5FiwbbmkMqYdGeAebCIRgyXnLIhJU9S7TiIi+l1NC0cpGhJzDnwE9+h3O/bBCEzX5rBzFnxCjNjo+KWReIyVjJdBx957MNoEOX/dJsxCEQ0homQOqs/DUTpXQIoIIQDP9HhjsthxWtq4K6MhwaGsxYN03jQPh5mjoxddJw9V5VJERsF2toSCTiUQOSEAZKA8fPZFVglNsSIRe+EllZ+ZQZG9vYYPcHxer5NPQu9LR9li3Z9dJMJedei+eg3X9+KQ1jnQiJSCskyqejQHzTXmNxENuXO5ji9lD04Ka3/HAr/2OOO8s7wO8sHY9VohrNRkbJUyywhduaycHgDZbzwGcaqvKjdcutlUZKxb7GJTHhEID95QmcLimHge2m/poAxRIR2HFOMVlGAEixEJkQzMA683dniAo38slvIbbSA4dd4s+5ciOKMWoahNH9C12t50Ig+0cynnhwiYSElGsmPjwPJlmbYUbLcNwdnU6XgLyjs5ESej7lpLUiIdhUiRgusAyYcBQHUl1zs4velEFjF+LihTCpoTAFDfw03G0qdBcLrpRIBfL17GUgOoKgF6UeivSGLkLgH0AIAu3hwo6+3LBgHMjocVN0J0DKlaYglrYlfWs3wF+c1AQlVgVIltaflBILw1DUoxsRkNwNn7bTVFfa7R6DgVGxK35cdk4y7wIeRIhq2qMSAQccVC2AhHUHuHvGU5QUvQFIxGFssVFuPkdeoj1TNJpDnINK5ZetCNgzlm77JPdTugmkpijopm44BmAeica6Qo3Qv+5atMc0LV5ixgKp5BVYCJK99EeHG4V2dpDPF3g7NYrjY1i8US7tmL7Jor0Q+ryZVVk1cmM0skvHs06J1fLAa9ykC6SbObIvcbXCqWBIVNbctoMrTxt41jdtAsht78WngXgMTybaEig6MAMFxEKH6u7k6zqGsTIjXe+6DGA4IXEfAQpcXNgNU2clZClMSq2ELQsp9mEe3voOVEH5NqPNNpSAc3xDO6f98DzjDDe9EsYvsAqMK1NAv36CG8yc+QaIwTTQfI/SWaOWvNzdUKdBw0C03Ht9E0z8OaxXgM+uAx8Pxl1rel1YvtNDXQdjfSLA7RkIMc5CA7yTuPs9i5kA6w6QHfVYYYwrHFL7Bvuzvv6/I3eUn1ti2r9rblsjFbbawsq2i2Ry3NcmYOtbUrZuWysW3BsGT4CzWhTPTHZgTHOd53PDoEJeOxY7rKb6bjCfiPcs6sabx1bJrUiNxcHjajMHjP7IOzeOfNkEG5qhTALmIXFnKSKWhCTRI6dQBxdgFjmLaoPVpezFjQyIKRKKVOc+8zByeNx7BRC3U0UoWgDiczguoGEemXdbrFDOEdzBCfVNsN0liXbkoZW5PYyEMGqdYn1SiO9BX2t+o9kJy8mn6OHR2cI3UO1snBaVPUp5OQdzKcog4yuTZMcNORhEPPLuJ57m+GrFF95WkKv4bx8Wq14eCE58hSJfdbcGKuVqCHQn7jn71IjG1dgHsTAW68kaJePXwAfPgEeP4q3aNVlZzPek463kEzZPdap+/+YrHPG3SoAPLQwgLz5u4hE+3qPOTq8/Bo2Cired0kCPfaDxdGNoSr6canhHeYzyXNHID3DBduPpu7EQsb96Y+RoBj02gUU8kTVsSgJ0O7Ss8X+1UchyIHtZ7ISrQxGo1M6nt4kIliiA+A3PD6UFK6GTkke5XhWABwdQ2Ofh1x7rnpBB5aNyT4I3QhMh5/jyW4NfuYdPnMN3F0lNLr7UI3mkSKwd6EON045KgoTmU8TohItf3j9ayiv0HHqXPMp0egpckjISesVOqHoKUsDkDEOHAl+Su0WElE7ighODXErsIA3OPHoLqC9z6xlE2n6J6coHr5Gvoyibk6Sqeni+Z4JOd6MXtrKepvR0ocfrltlyZKr7vG1/1A2/Z7ABNlkQzF5hce+IzSPvSh3zJCG/YpKczsG52GNpqhY29zb3tJkKPtch9+KwBcukiWMHq/Wm2EjFNuSOjvYpZwKfbtq9GCgWsR5wNI41xisy9L3Y+wuJUh2ZjxmptBfH6+MY/yVm6FCMjlHKF+tUpZrkDIjE0aSzY36ryNi5FPC9WL17H4kM4jdx3cmdYNWccs0EgiFMLOvG7lpfAikf8MmW2sBaPMmPzFDPUP6gzjIbVNUp2S2O9yCTQjiWTZWiF71A05ODgPcpCD7CT3U7PYRfZ1AG6j59uyr7JT5ccm7SJqFdk4DBzatmHf2mWb24Zg91dqQM857sCbQkYbzq7cRIoyGPp0qfgPEFnLAYNLiec8PO9Wy4rn3SdOj1hjpI8HxO96bDzOlG3MCjUZLSRuk8aTNmjH1xcFjZgi1oIMzkHa4WgCxnHq98Uyx9UEfwcb6r2IpFRcQzDhIj1h0A62ZVFHCLz9vW2FXtH2rVpXyfUa8C8byXJ7PCcHzeKeSgZBLyIo2T7biHHNMZfud8cS+zdjilT+9rzexPg2SH/JUOpvcaC/oXmzuAuqjAN3H6mqG5FUv7+axWWJaIC5yCkJyzoSbRHl8jhSrzkQixeXb7QE9rEw4JToxVlh5IQsTIQzITlNiX4KEFisrwF9w1JWlwRAqk1ikKElB2cqiRD6HY+TT0HPSdsN293JMfxFynGI0nUbzFub84FU/8MUlE7gIUk4Y/T5Pr7LjlMfQhalOT0BDGOVDFYeLF4GDk6bSh4cmv7Cx3FpGNQ6isGc4NKBbDhLCPzgMVwg1QmTK8WuT1MimcKxI4I0EPTQciXX6ZFEQ7aWU5hOhZBnNksgtJNj4OmHcPbeG4+FPMcuvICQBDWNaE2GSzSWfdhB7udisS10aheHGOYczkC1FcyB4N3uEiKR23VyWJZoUX14II5Im+Ogaqobj2WZsDenqetBobAQAPi+TwxXmmgUapFouM4S62acEUA0PbK6JIBQzDUN0PtIrEtxMZKHP56HzsPRkdxsMCprVaV6HgDowSlIw3MGPk2rFbw1Y4zE+QifAUhkQGH2uuhofZI23ORH0xiW1ePoaApuW2EWN6FifPBoA2oeCySRA0ZNPLd4rpNxZMSiURNrklDT5A1VTqIbarKMx9L2aoX2a4/RaEIWs7B0zRbwHz6W872YC0EvgP5E64Y4cFOhuljBvZ6h/ZrsWz9/iaHllh6cgEeNOGT1HB4/xOxHH+LktakbcnqU1Q3RF4cP0RYX9oljffW+Z52+ZXnj9UZ2lUvqkmRiVee3WZcEyCJIO439TUk5L9sIgd7GvXDdPvUUrnn8wWdxkIMcZCd59+He15VtoCwgx0TEtOkqj9tvg/4q2CWCuvrM9o7dBxhvmYgWzYm222gDQFIxFRVaIlTDZ0VxAsZnQbnjizVZTRGBgEkuS+PUMUSw10ZqPmV+GSWkAZCleG/PhhUzI2tPt0VwFaXxKNYCiMV2LIVfPK7AWbjjaY45gOIsEiVABrQajaT+aax1Wqf08pCGDyBhKijxclDlIu7BPXoIPr+wnSZCI53zmJbfxH00nZzXa/E/APDPXwziLNzJicyFaQtVJUlszw3xjoLaIoIzJQLSZAI/m6cxeMb/8fpX8Lr74j2Ge+8qCsserIVaODirSlwcEWs/vFhksGQgpB1X2Hg8qio6DeOxha/DFg6K21cGYRkfhgEHZ+USnNr5uA3W1g5kOgzkPpawsIhDN+V7sHdZMaAYFlXnnm6fjDPm79hdOJdBNdfOh5530wC8jueruQ7MHLkxqK6lqI6tdNY0INfnyFZA/Ailc1Ch3wq0sotFIMlRoJR+Z+ekLcuqVYXoTJ8crwo1l/qwBgymURzrSNzi4IwPs0LDX1V5eFSbHDXyArHnPGrAD45jrdY4B2YM1sHJJ0egto31aeE9cL67SfJ+LxYl70T2Ww7lVoiyQrS3NhmRhsmhqWjLDMGpiFDzlo1p7/a4MIaSkDVxPfjN8wjIy9yRGNCTfbEfsIGd4B7QnJcs7s5eUqTL5LVABKTb/cUsjb1EkW7DWeh86Gdtt8B7sOsiyxOAiHtgz2nOreZj38KvzwZJd1kXRtfl12O1yss1BJh5rEgWFhFW5K7Bw2Q5MM9f5hpNwFl4cw4RZ6H7FTgLjWjYecrOYTaP+TTxHNZrELPUeglCy9UgzoKqCtR78Gyec2/sgeC8n4vFLtGQuG+hWah6WyRWRfVbtysvgjkmq+Og1anXIWJR5EO4UbPxQNvygn4+TzyOa0SVtT87i+MZyg3hrgt8kKMNCDfVdSoniMDBGdT/GLJVdZ4cYPgolD3cHR0lKHfkeXB5mPPhA6mf4VyuWXSdqPQDN7vOh44TCBrKsuDgHEl9kqhZjBrZR00k3dZ72cdoFu7Rw1TXI24koK5TbogJrbqjI2DURC4KiYZItXE0oxRZCZoFNSOBXYdxwpE8xF9/CvdFMgVATpLDHj+Uw+fbc0PcYgWeLYAPpW6I+94nGyYtANDpaUh6O4+hU/f4EbpvfITqtz5J+02nEt4dyA3hUSOsXJqHAgDLN1tF/SAHOciXQN5fB+dVsg1DoXIpoOvqFPXoMM2wH5RrNKaNjfoopcZUOmeH+Aou4XHIuCiKY+J5IHdE2tT8jOXcAqzKuh2XOYbL2iwDtS2UCzUHj3F2Dln9EtN/ZAYvJZohBWN3XctvnTotqzRfA0C7bBu56DCtTk8HzZDotLbMV6oJlWZI0Dj7i9mgZkajUdo/zI0bNaDjo5RiD0QW8SEzxGYyq/z64n/D6/7ZwcF5J3IpOcwVqNE3JZH+L5C79OYB680+7M2D9xbGaWQQqi4fsBNd++0ORh7Mkuyn3M3u8walnKudjyPadMTvIe//YrHrA7zxBr7kBjVvcOZQW4Q3b3ZJfMpDp1kUxbQRt0fNYksUR5sK0RtpwMcxZT4E1SyIzc1uNBqTfxGlqmIURBO3IpQcSfuwUPA4JvTgMllrYz7SzW4h5FFrqJy0oT6LAFe3C56GTjUKFPuYjMGLQlOxfJwloU1VcJkqwY36QuJ5VJHJPNWQ0WvZSv3aItWfYSIfl4ROad3K71oTZT4fDt7VdRirTyt7I4hgysoQNOKoHQidoq6FZ8PUesHyEA1Jsuubftes0xCZsBmjMQpAhUp+11mnBZEve7fBaRH3s4uZpV0rFrk3mnWaOYD7qAVZM8RmppZ8GHeSdRqiETEMrO2Qw2DWKfBms07tNd8z6xS9z2u9AFuv15C8v4vFLlESAPsnklGqLwFIElhTbyRQ3XUimY0ubEskgxbXsTkgBsBloyEaknvTiWSIzF1hzCGRLMMzhOI/d55INhqlRDIbqRlIJFOchb+YvZFEMnd0FBPJYgRv30Sy8Qh8dpHjP9a7m1GHaMhBDnKQneTeRUO2erw3drRqd1CZx2NoVe1rOyKtVz/25VI0IVSc2qqZ3JaUjtahaIf1rWxjsA7tuPFYsBbXZLi+ltiokt08VBn9LivHq5gq7bbOSWQBt4CoMHY3nQhv6q7307ao21Us9uG+o9Eo+hz8+fleTnU3mUQ8DSBz+uvt339/2b23Fh3a2HFzAreh4/YbwBDHpLGbB8hq70RKRvOh81I/xmXnHM7Fr9ubz811ZAitOMBCdkWd69sfS4l69cWipr6r9Zu63gb9usWvcWUTRT7NNv/INrl3iwWYc1yDfrZv/BKfwJtvVRfw8RG5qNwKIbfCX1ykZDDbF4t/IauifXSUWLlDX9Wjh2CF3gahyTjmAPDrs4i29LMFqg8eg5nRfy4VsavTU0F5KpJT+1utpBLVaJTIaU2CV+TFAODPziItvSJELXt4LEEAwAcejerpxzHPISE4q8QzAQj9fKgaHvMMAPBymUGP7cPnTo6zCvHKL6EJWNH3MR4Dq1Xy3Rwfg2cz+OUKldr1k7FUBO+92PHa3dMP4J69zBfR4BvgixmoadAb30L1+BEwncB/JnNOo0b67zpp10Lwqwp0cpwQojpvz1/A//GfwOh7z8MgxL+B+QL+6RMZwvlC+CyY4R/I9fdNBa4dqvka1csZVr9P9h39899J0H9TWtA9/Qg8HgGfP4uYjuoP/H6c//iHePD//iDed3xyBLqYJwKkgBzl6QjUedD5POOzoN8xaM4r5P4tFsBGFGBj2y5NlCX6+lDzAju8Kfo+i1cP5iOs2zzMBQgZTWAmYuYMrs2rdb7qG/bsDW5NZrmhS2bsrsvIXXSc7DlzhgJI0Y1y7CFfQvuO1biN483NFvA6djJ1M20FcjsXnoVdWxdtXYRKtmwgFi/W6xP75aKOa8hwJcPI7s5nMo9FrVOsQzV6+yb1DF5J9fKUG4JYkJhCjY0olQdMXgWZCE39fCGQ7SBUV+DlEu4sLMwBag4ATqHaVSVOz3ULzBdoXsi+3HWwFdHjHM7moHUrLzd9OcwWmH62TPkmOn/zZSw3SRo6bTug68HLJaiICO0qBwfnQQ5ykJ3kfmoWu8hV9URKjELQAkpw1YbGEnAVEV+gGImiH8U3WEgyMyfATJExad8oANLnofKFnsHeYBT0t77fqFZOIRu1pP2LvowSl2DrkXgGg+Vt1RpNZr2G1tfYqK2xTSwzdd9LBmVnMlH10K7LNLK4j834jEzXPkckzpcSJlayXTNfURu0jN2dKVgMRN5PeA92eflA8h5aMyafMC+0ecahzb6SUK9iJ1Tb0XaAZD55D25buAvZ15usV1soCUFTZeNL4eUS9auFaIcWi9KuwV3QUHUetGLcymhnpj7LLvL+Lhb7yGUM2CSOrNvra8DxHGPiw1RuObv13Xv6IoAInD90dnwBGRn3Zc6RkjpUchlwaqOd6w8y0AhaikBK/w1SVlCroXK7LR8JiB/qpnR+G5Ep2hxXGbXQPsuXk47Tubj/Vuo+ovSn3W05l5tCvYH3ebHYFZRFCb6bkd8Aw34QosQcBaS09t5oGkAqeGseFLKJZM6S3wT2bdtfQNwJGrAYgws3VImINGAxOUWKtTtT/VGbxGXg511yZkaWKjMWWzKQGlPrVFPLAUEnblt4LXzaLDQ2DT725X3SNDS5i9KcK9w8ktLo+Y5Gqa6ohkHJC9nuGjmrl5Z7rM18ESVQVmDsysZfEOWEiZTSg+fpO9WVzKeSJOs5AylFvQ5kP20H6rpIqGvnP5OmBjUNaLHIgFbd6Rj18zpds1AjN86VLlqjJiTpcQKGBW1pV7mfi4XNm8hYvHfXANLDY1CK4X/Wz9Cb3DJehUjFBq3eqAnQW7OxaVIOgGXs7jrQeBQueIgOVBUYreGzUMcnIuNWeqhTzkYWndAoiskHiDkMIdejZOjCdJLYvS3icjyWPAYEj3tQZzM0IApnr83bCNEAmZtwTF1n4wEkusIAyPXxe3Rm6jmEaAiV0ZAHx6C2zd/sQZtgzHMq/9AOppNUQ7WuU55HXedM4U2d11I1uRzth0cYXaQoFDe1kNI8FKo851yMSmTRkIpQLVpUANoP5fjRDxK+I0OnHh2BJyPQfJGIgU6PMf/qFA8+Hcex8vFUXhJD0ZA2OKxP01jx8n0qjLxNNsAtfvtvA5KFNBXLz5xsSkDePkxmXQqfd42GsLE5IcfZcFx8U4ccAfQ+829EOjhyqS2NlqzXg9EQLIu6l+H3yPq0SzTEsmA5SXkmg8Og2SIxcOk8+j76JSKkXdv2IW1a57bvZU5MXzrvDEjOg7a7XKZoiLa3NglhBvdCF3MJqYakqzgHS6nvyUjaHPW9LKam2DGvU3SEqm4j+hLnHUnrYs+oXy3Bc2XAIomorNYpGrJcyXj6PkVDRk3yGaxbNK/C8Z4TRF0xHFUlhbTbFt5cd5otMP18BXR9PgfLlWgUzGkhbDupj2ujId7LsTvKIRpykIMcZCe5l5pFfMPrZ4881ViBW5cVGVL6OQUKnRzL21PtOQUvWVMkODwpgKIAoG+FxbmP0QbZ1z04Bc8XObPz0RT04FT2e/ZCitYA8K/PgMcPJdISQD/uaAp+3Ya062UiR9G34XickqZMgldsH4D//BloMpZkp4cB0KQUciExzAVW6d4ArlzADMS3qJK9hu3dNz5C/clzMbNOj+Oc03wpKryxuYkI7AIoaxYo6UKCFcYjuBcv5XOAydPJEfhiDgrRBXr8CPzyFfyFhwvnFs2gtgOMZrD80Q8x/t1XErWwLOdNBffqQkBNP/g8bscHj9E/PIILc06TCXA0jcWLyFZGbxr4xydwn4fxBnAdrVZ48R88wpO0J/pxjerlCPMfla3j50v4sZhhqw/kOnZTB18DozOP6WcLvPhxmZOPnr0GZnPRUNTCIwf++sfojsdofgfwAcjW/vDH+L2fOsIPzR/FvtvHE4yezeBHAQQ2kke8O21QrXo0z+ZYB5MHHvDnRTGlS+ReLhYWppqlL9tM0ivAWimjMKi/+uAZdV8ASZa/M4RXDcIQ7ENuQN6PP78I4VCTtj1fpPTqrkt9eg+8OhfGLFWfF8vAbCRgoqgSU1BPl6sNoJW/mEW/AoA4Tm67uAhZE4M9x+zRKM9eJMCVEtWuW9BqHU2v+pPn4uNQJ6e2p+nW6pMwYUZ/MUvfA1oU5xcRjUhV8JMsl5kZQr0PSNg+0e2vVim8uh7FuZ/8FkekZlxEeg+s1mDfA/NlHr158QqVAp0g9wTNF9HBmZkhVQWaz+F1wQsLCbcdnvyL16BPn8dd68kYfDHDkar46xYVielUfx5YvMejBES7WOBJIIrmxSLMU5UhaOmTz9E0wheq17357uf4qnuK6sVZBO1VLyt5uQQzpAo+naapJfy6XGL0KrF7u+XucPV7uVhk+RlktsXfi7yJS5tKnn9LQa/Yi6GFabeGDQYiRivMz5bjoPcgL/a+akccHj6NekT8B/tUx2JAbJgtG+11wpXaj/U16PbgkyGjzYlfwixsAaehY46aX7+9QG8Z4rPfo0NXeSWGfC7M4K7PIxlm7Jaxm5jFZjccE4P/9XMZEjV9ZtIZTAmQokbahh7jnGhH3ic/gmJlTJo+c/ADlf1rpM/mp9SFw7KgdYx/QIg0bZ7ONrmfi4VyPCCZIXnI7uqoiK2XAXLCOmRyJbBYZCxNckwlpQJ2jYas5YHVB8NGK6jtkinELIVv+x4U6jjQaISYZ8Cc1xsJRXkjr4FlsDK1R7FapWiIMmq7MM4t0RCaTKAQ7rhYVZVEa8Lbi0+P5Qbvexl3OAcQCaTdhpUBYRObjIHgw6PxKF6vMhqC8VjON0RDMB5Lfc++j85Imk4jeEujTgDgHxzBdb3kgoSHhryAx7CUawyjWdFkAn5wDKgZQpRHQyyvZlNLv/pgmmjI6qMjTF8HbYlIohbeo38kpoW7qOQh7j38w8DiPpF5d22Pigirj2X75AfjGJWzBY1oOpV2Z/P0QjmeYv61CZovThJEfDqCI5Lz1/snbKdVKy9FGw15tns05ODgPMhBDrKT3E/NwkhmGpRZp7s3kj5bCHapXl4zhaamcpgAACAASURBVNuCnCKUF0iqqh9Ie1dzQ2G/PKDWvgFh5qSpeuNAVoi7UZ/BnNR7mPnzBaw4pHdvBXBdPShpewCuLmPzuXYdTCSqfO4EB3Iz5JpzSva24JT0F02LAVg1eQY7AvUctLRyrtK4GNutBQpQ9pTYhnhdpI8r0h72kPu5WFzls9ilCVWp1WfRBlyEXWS0ElYpu+AsNMei7xM2ImSFRoyCsZ95ucz6494nnwDbm9xHTMhdZJ3ycrmJsyh8FhRyMLg3CEDNovWcnh7LB2GzZNdt8tcUOAs1ZYazTm0lreDjMQ+iO5vLPLoqQ3Zy7yVfwt433gvmwJhzzAxaLIezTpkBWqTUecOZOXo+zzM/ux68XGVZp2pOutC/a+pwrh1ovkTzIhzfrkNekctfXIuFID3NPNJsgemnK9BiFRcW571QNl6Gs7AXfI+s03d+sdiopxF/MA4/QCZGWaosE9aWFTV7+Milegx6IeomQMDNwx7e8HERCO3HxCrbvi0DiNRXltClC1bfJ07LgOpEX9Sa0P5IAE5syWr0Tb728PYG03Eyx+K/qh0oC3fJmelni82FN8yPPpTqQ4Bn8VEA6aE16MG4jnc+VhWLcxbOMTl0kw/Dkuj6uY8MVRrBsg5UrNKtT+t19LOwdQTaQstGe+Clli8M12HdRp+OLrJpCihGZeS7jqEHff+zGBYGAK6kYHL0x9iENIWFu6Rd+q5DFfbxWgpTiXd1vl6fgyqXkRT5Fy/RtK3cOxZK3/dy/tYRXlVxESYbAdsDlPXuLhZX0YVZFZZDopDNf9iVWslQz2U5HxAnI1lOCnISgtvRzMlrXxRSpQK41NQJ1j1K8GkajxOqMFLQI5DwDlMD5mYZby6q9rftA0+fbREfDUcyp3KG+ubioFE4l4r82jAuMzQcpIlS8cEAoE7pmA2rC6A1wTYK57g850RNvCYRI6Pv4WcLWYS9BwXHZHR0VhVQaZ3bNvVfpA/Y+rBxnCqq4YRzo7BYbGT02kVj1Ehm6miUaXcWCg+exTH6WQjPF9oRPIdz440+Mglo2+x3TovoLnJwcB7kIAfZSd5dzeIqGeKZuKYTJ1M31WQIb4fsbVCmWu/a5tBxff6ZgU2OC28ceOVb7q6knFftS02RuL3PxqtmCAFRo+Cuk1BiUalbsBfXuFbGFBtqh0JfhDb5Wdi8cb3BJFgw2R6VxIfEmmjskPglgu8mc/TqtqBVCStY4iGJPhFjolGJGdF+mcVss74cNbkipiW0sY/Df4vc38VC5YrKXfs1RbkKHtLR9yU2vUbHA9tyToO3JlvK9gHhYb302C036HX5I8qxhFT97CWhPhO11YsHLY1d93c35rMQH8n2NmKfDjngKziQybCcx/PZxiNSSsmVEdqNdIi3sEioXLlYENEvAvhPAHzOzH84bHsC4O8A+GEA3wXwM8z8kmRk/z2APwtgDuC/YOb/51oj4ytssMLWBbDBBnV5+wNOPMM/wS1niEo55BpWW8EMPVTUl/seBC1alGDdttyeZcWiO46abtWKvLIvxR0TsjQ4JbmzGlBy4GaFlZmGF8irB6aDgiJj2SF/q3sGozfhXh/3BZBIjoMzlqzz+JpiIzIyPvVzGb5V7VMjRUQxNC7Rl+BYXa9lfzOurS8r1eyCQ9Ruj3MRM/XfjGbx1wH8jwD+htn2cwC+w8w/T0Q/F77/FQB/BsCPhb+fBPDXwv+7k8hnkchgomPP/i8Pq0MadbggbtSICqscE4sFAFNVOx5YViRbJ2ef9g3ATcZB1TQOwrpOjN6LZSJQWbcpoUsTyaZCMKN1UlL1MnEqOlM/xVY3dwbB6edzMafaTlKigZgHoQ9vbDc8RO7kOA+dAhvkN7EimfcJhRrCs7xcbZiD5CirdKZOPEdkckNc/M0S9rrpBH6xBHdtRNfSZCxhQC7Ibx4+AJ9dbBD2EjmhBqiqyGehyW00mcA/fxH7Vp6QSBugoijWkBOi166/mAE/8nW4H6TcECHsTVXGYugUAE/DfJnQqbuYRyZw+u3vyzxZsh8iuIenoKaBf30W77Xq4w/R/nsfofntT9M4x6NI2Kvjjv11vYRgFXULgD7b3bi4ck9m/sdE9MPF5m8B+Onw+ZcA/CPIYvEtAH+D5W75dSJ6RERfZeYf7DyifaUoqiPbUn7/zqFT5eAs7OLNAznZv/o98+qHzYoNyDQIH7NcM6yGMldz2jfzBZjvAIL3faAmadtlQHcpY1BwQRQcnGWpvOxhN+do3148m6ewp0FEp1qcueoT8RzaXgi3eub8Ouj59unc/GqVQqd6DgszFm+iIRezmOWb5cjo21fxKTqHmqSnPgsTEuayiLIywCs2xozbvTiHtzwiykVxdh7O13B9Ggi3ni+vVnAvZV/f9yYnx2hM8wW4Wkcfh1yHGZpPR4ItUWlb6VvPX++noKmwYQcXzWR3f811oyFPzQLwKYCn4fPXAfyu2e/7YdtBDnKQey43dnAyMxPR3l44Ivo2gG8DwARHV+xdHpwSyQYdnBZVuM0MUbUwJok5SXiyCVsF/yU5kn0uK4ys8fZQuNhODTV1yB50wGIRCxrxciWqtc3YbBqpYeLEl2LZtuSt5Ew1cRfbz8yQvo9miC2MHM/FO2OGBK95UPG1L82UjMWIAeGjmM0ke1Rp9Ti8qY1TTQl/icPxQaOI9HgAfMSP5GaIvvHceAzvGRxK9+ncxmiMwRhEngyD4OQAe0YbMCELBS950HgEmk6F1xIAXH2lGRKvpZohbQf/wQOh84vXuQFm88ghYhGcHLg22SI4ZzX6J7KvO7tI2pGtuH40FTOk7wHlGTk5wfprjzBarZPPYjySOiXqHFczZBSS6AozBIvd9YXrahafEdFXASD8V0aRTwB8w+z3Q2HbhjDzLzDzN5n5mw3GQ7u8MbGchYO/3bWojW0BUIVDipT1mdzWsd6KZICsMmV7YIzkoIS6ccwajbgMlHaTeTXRg41x6TyGVOw4JiX9jWzY9pxuOKdDzsOrohlkxqvs3C7tHxm+bVr7tr5pyzmUKek3lOtqFr8K4GcB/Hz4/3fN9r9MRH8b4th8fWN/xZDPIas3ar3ARg0YYsrKQkxhAjsf/KPFhPp+Q1tQ6DfVddIsAgov2f4hp0FRfCU3qELSmeEin0UYJ6U4O/c9/GolbXct4EZpXH0v5RbVVNU8itEopk4DECbqphH8gzJNq5MxMGXp2zpqNKMmclTEmD9RXs5vPAKUiCZ2Fm7Uvk/kOUYcEbxqXYBoA9NJ7IuqQMk/HssCbYhxNT8mah91DeYWJY0+H0/lLQ5EnAURgY4m4visqkRMjKSJRCf30ZFoD10n2sHS5NnUNehokpy0SjWwWqE7GWFkHL2oK6Ct4U/lDe6YRZMA4E9Vs6jga4f6Yg1at+inomW64Bcp73p3cgweNSAzJj6aYPVBg9F304LAR5NAZBzuT9WwjmR87rUDn6TyhfukqO8SOv1bEGfmh0T0fQB/FbJI/DIR/UUA3wPwM2H3X4OETX8TEjr9CzuPZB+xC8g2R+ZVTFmWDQpIuRwZHLZskwFoUlRqX5yTRY7FYgmODr8gq1Xqr+2iCs59D57ljFUc9o3gHfMAiiNzmYXWyFEi8TWkOmAZW8yrMEln7Dk9ECHqw+cXmwWJAl19LF/44mWKYnT5uLJK40PzAWN6qMMNAKow76GYEWdOyxbsOfUZGLpKHAF99ixGK+KYIIuLX61AK0O9CAjz1iIlzvFikWDaIwN20izf1SqGXqntohNy9N0vwMGZaU2YmAkaIjEAUJ2FRb+SUgDctuDFEqMwht4SJtvzePU6LXZqcnzxAif/GvCBKhEAaLGAX63zvCIA9FpMYJ7NgLl1iG72tU12iYb8+S0//cmBfRnAX9q594Mc5CD3Ru4ngtOaE1fgKbYdmyj30wpM6POiO9ZRqscGG90mrUmNj6IbZdmyQC7jGCVXJL6VXApa5VydqhHMpcdWxllpVG5bR8N1ab/YfmuQqqYeScy2rVNY0jh/tfgPAKAZRc7MLPHO+5A9uqnN6XzEzwimh2oUOi9NDXYumSdNHUOylnGM+172sf2PxznFnEoj9UmorjNfB9W1/GbCi7KPmItRM1A8h6lzQk1oq2rFaRmcpCQXAgRE04/Zp+ui5kqoJUIryWxWx+dG6UWVuk7FnXQexiP0pxO454l0lwLTGErNQnlJV6uEjQH28h3dz8ViH7lFOPg7LVsyRS9zbr0R5+1lUvavqe0FD+cbFUfiC7FO0563O2nv0tlsZcjxvKdIFbTrj/f9XSyuWiQKnkiq62jfAsgcYXmzQSMIYU+s21RiD0hvz5FUGCMTe7UcnIr8BMTuj5XEzs/TeDQFvC80nqrKuCfjaZqKZ4DY9lRVomFoXwYUxD3y8wDEwagN2OploVIYAKHrD8QxGecnUeCjGMgnGY2iHyKmYY9TmFZDuDSZSPFe1eZ0H+OMpaOphGEDZb8KPzzZIPPRlHV4FuftPPFOYDyWt6xyiYxGwaHcy1vclHSEom+tg5MIvFii++gUzULZ4sXBybMF/OPAwVm55OAMFcm4cuCmQnWxgiNC+5GUOag/TfOUncfRBDweCWeHJuqdHmPxtWOcfJZCoXx6FBzS4X4JC4s/mgC1g1tNkoMTAL74MlQk20W2vVWpQOcB0bG1yxtNMxujaP6BWbXV2Zjh+m3FMIsG9Jyj8HQ8Yb/sfzy2zW8qRRzaRc44ATcQnBzg8ZHMJdQ+Xa0MSjEsfFqtXIluLuaCFJSGUn9tmxHXZOdjK6gpTsDmvmjt01XhLA7YDSmBYCqVK7GPmRf3+iJjrALEwYmmBa9W4lC112O1En4SG/3RamfjUcb0BQA865PzkdZSZJkI9RfnYLsIEQmE/6VEjHixiC+hSo+PZsgaPJuj/qLZmKfsPOZL0LoVZ7OaceczTH9vmpdk5HAvFWaIW7fghyeC6bENv09MWYOyTzRky/EJKp3g1OxzTWAoGqLJZmzDdoNp5H7zwTE3N1uo7RCXpEKclZ3L3OQxamNvZu/A6IHWwJxZaPksZX+En+uDM7Bocp9HkiQCnVK5qU25G5GFGxp98ZvzZucDSOcd8juAEBkJc2znlIG4GMc577q0ENrohq3nYoSQfDLZNeq6nFiol/ljZmBlFrc+cFzaxa3rQCzAJ5qbiIpdnDXSZNi44tWpKtBaoiFYt6AQofDFtY7SrsG+SpR7ALBaw50v8xR1ooy2EJXC4hm0WGU+j40EuCvkQH5zkIMcZCe5n5rFLtEQcgLSKi0RfZPFLM6w4oesyIzzcygaAmyAstA0yeZnky25WuX8i+OxVOKGvMUUmu3nHnQcygAGdZbGY3mjBSi5hWVTU8NNJwk7oVGL0ShR2gHA67MUOdCaG+t1iub0CUKttG10fJyqqBc+CzWh6PEjUO83fBa0Wgln5sDbKs4HkCDp00nyF6jvIUQ0on/kaAq+8FJqUbNOj6ZSRb3wWeDjD0DPX2X9qs/CXczEZ2FMGTo+Bk3G8XxpPE6grFEjJgqMz+JoAsCUOgTAy5Vkfv67cG8EnwVmC/BXP5DzPZtHn0U/5LN4PUP7dck6rc/OB6ve0MMH4rP44kUyxz58jNkf/AAnBjfBp0dw5/NBnwVXJKAvC8p6fYtZp++k3ASUFRaVa4OyFGX5roKyfG4KYb2WnJMMlCXjYs8xzyAeM5tt8oJoxqWq2i9fSXYqcHugLJ13Q1gLAHyRMmYjIMqaIfbh//z5fqCs2Syr5B5BWaE0QypxyWL6FKAszS9qvrcFlBWwyxko6zzxalpQVhOIc7eCsl6fbSBQ8ewljn+DpFauzsFyOQzKOp9J3dzz8xyZepugrHdOdsVTDB4bYv1EOTQcSGnQXKoihWiFMps7Zx8QFzSOAUJd7vt0A/oebPg3/HK1sa/ul/3XYy2cQPEcPieJVZ9J5jsxfggAiYo/FJv2BQu3/EjZwucvUip/SQC7lRLAzAebsZRp9oJvcfl3PZc+OF7N77Y3Kglpo8g5yXHpCJnzVZxb7kheAuE8soe27cB2vH0v7TlC/8WzbN/IFTJExnRhclKASBqkjukhpngAwrqu7Wtk5fxctDlz71BgIN8Ii5OL3CAZZPy9dnCWJoergrlB+T5DYh64WDbAkt9wqrPgF4sEaCoYmkrym4yqP/Thjo8TXb9SpmnWKXLyG163cA9OAM+G/GYijqoqcF8WZDu2cO/WrNNAfgNvckC0avwW8pvq0YOk5lrym9EovuHdg1OBhTMnFu1wHrxcZRmycc7G4xSK1BBo5RKEW008Jb8Ji7Ybj4M5t4Y7OQn7NJE704LQ6KGMazDRbLEEmjpS9jPzBvkNnBPzo095KFE0fDzTMKucd392AfdH/gDcp5b8pgbPF6DHD2XDFeQ3NFvAfySV0N1vfz+ZwNaEPT0FjRr4l68S+c1XnmL9wx9h9Fufpnt+Ms7qhmRZp10PN2py8ptPd6+ifnBwHuQgB9lJ7p9mAQwDrkr6u6uaMDBncpQKI5s3ldQUMYWRlQOizDqta2PnB6dYKGycsYMrKItIAFP6tldQlvdAyAmipk4aRe8T/4a20yRYtqWrsw7OmHVaOjhDG1nWaSyMnDSTqAkoIGkdQm4nRwIbZs4LIwN5gWh9u5OT4xcKypKK4FTXCSSmhZt1/Nr30VSAXuSywsjcthvXyz86gdMEryJFnD0LLZ5qMt5LO0cT4FWV5k8dnAU0HJUDHU/TuAK3Bc0WWD09xvR8EeeBRw0IQP8kgLLOquhw7B4GB+fIwVcO9bxFBWD5VJyO009CYegCxUonR1IYeb5IJuCDY8x+aILmUwPKOpmmwshA7NcfjUBtD1c5+AfBwekBfLG7vnA/F4tbkA2UnPeJRt3uV3r2WSpFkUJu1U7foNAP9GgWH9H3CWFoaf6BjE5efjeOW617mgYfCsZs9smGhEXG2cfP2Wno9xJn0RraNc1g1XYVwLVaJ0yF+hR4E7ORGvWhtKHpk5ykmUcUqjo420BtpxmvbQK96UOiY+k9OJLjArQIFck2uB364OfJ80YkolLHay6Ls5AKsX4PQuyA1dpEiNL1r8/bLCeFEEzL+TrOFzohv6nq8JJqa1REUtl83aK5CO2q89YyuxMBS1mcva0Mt1xj9LpPvhEAWKzFtIkvkmAWA3INVmvQ3KA298BZ3M/FQp2U5bZ9pJwkBS9tqdFQ9pV51YcQdzbNOm40QCwUC1YRRUhckX5z31gTIwFutI3sxgnjZJ+DsgCIxjQAyoJ1EgYuSAE/mXkJ/KIZf2X4Dp9IdJUpC94V49eITKLxj+CqIkWdDHArApvCQiFMXiZFfS0LDcNEzNnUQx0CvtnCyEDg4fQgFM5iQPbVbcbxWi3auBCRks34Pi0gXQDQMYOWYb+ewURyvboebpmH3kvhrge5zvCcAli3aOYhMqfztZaxENcptV7H1Xby28o89nsEC+7nYmFMDjENkKuMg5HqognzZpDswUrUahO3j5mjes+ETE3BKRizYDDrNBCkOuRhLFWbK1O8t6okF8H7VEpRS/MR5WZIGKswKAXHpmadVlWOO9BxmtwSW1KRXG7eABA8gY00OBczLuNNOmqAdcIjAEgP+IqSU03VaSfnw94wTesQixAfQpZpXDyaWvIhYEyVuhaNwgldnxLd8GQEWjYy1tqMoQsL5qgROLn2XdficNS+XcgsRSdtmAWSKies3bqvjsWRkN+YspM8GUlIWmn4eg+unFQ1nwZcyzgc31dwfY/+KDCea7aruae0bzR1lofEkxHWDxo0E5MhO25AXS/nzxw1LJ6MZL66Djw2Ts09WLTu52JhJK/taUJ+V0xC9qbT40qzYR8I+TaxtRu0jSKEp3H9zWN9UqcLM+ROZZtqum3OyuNKDancbjlFrytRqyquiWI0vAlN6v6+MOfK8V9TiJGdM/U+f3kMJYYxwCQaBhX3MDPLgu3Toj00W+Q5/sXzCBpM/LtFOURDDnKQg+wk91KzEH7LpHqz7yOoKN+nS1yYhbiQyu1nC8AR3OkJeLVO0YDzc1Gh1fQAAkEO4I6nEeZM6zXo9CRGGWIE4eEDgTKb6IA7OQY/kdg7fdqDQmEh7l/Bf/wY8AB/IfF6CjgNmk7A/SxFHVYr0HQCOjoSNB6QsBOnJ8AHj1J/fS/jfH0G90j69WpbT8aSgaiM2AFmzk8/gFOU4XyZVP0Hx6AL2Wf5ox9i8lvy1oqedQismQyoyJbti/Oh4wTAx1PQZ89kW5hPfngi2aOKVPz4A9DnzwVe/lDSuP2jE9BCuCt5ktT/sz/0BKf/Vkw0juYNwY8q1F+cwx+NQQZn4Z8+Qft4itFLCUHRybFEetYtMGrgLlImKY8atB+eovk9wWQoZJrmC3z6k0f4Cj4KOzL6SY3R5xO8/sNyLY4+PUY3rUAMzJ7KI9dNgX5MmLxgnH5/gs//qNyP3/jkFHh9hljMKkj7I0/RnjY4+jcMDuOd/cGP8Lv/UYUfff0oYgQXH48x/XQJPw5RkJHoA6tHNaqVx/SzJRZPA9FOD/TP3nO4t4UUc+G4y/Yx/zfaiFBeL87yUDgnc2qVUY7gLPSLZXQksmfwxWyz//NzASll8OK55A4goAdN0R33/AzwPnpbWENkYT8L8+XlCmi7VIpP+7iYZeqqjpO7TuDCSIsZL4LD7yKHmbtnL6NdHxfZdQtqkxNv/LuvwBczgBmuUyiopEZL+QPDARqK67BS3KuQAKUiPDs6AzvwYpkW3eev4lxwIAl2ek59Lz6KMKen/7aSeXQuRSsgJY94sYRbrIRKP4zXPXuN0WKd7gWd7+DjyaDVdY1m3cZ5VMg0r9f46J+v0Pzey7RrU4POZ3jwGyE9/GKBUV0JX+cLWfT9qAIqglt0qF7N8WETfAvnswTGM+nszScvUI9H4Ndn8bofffcVvvK/P0Hz2Vmcg5PzseSiqM8mLDjjzyV0SmcznJwfxzmolu8zglNFEX/q4JQv4cMOdqgNrVHgUjAl49Q5GHMpYvs7Tq6lx7e08zp2iwVQhyWQ3iYuUOTpfpbS/k5LASSGqEjxpv2rc5YokMP0yZHYe8BViWwGSHVP0OesUq66ns/ClBog58QvYGgAIx1+XcXELXVwUlhAImK1DSjJps7e4NcRX5vrA8icOJeM/IzuPyykGkKtw3itY7uuZaz6MrlkfL6m4BQu5kBDr9pfoPq7idzLxSIzOWJE4JrVzsk8tMUbCVUloTwyD/vuC3Fqs6xdoRGGkEciWY0V0MGMpQrAK06LSzhPqtxe8fG9JT6UYfF0VRizoZcPTF36BiOEiIdL4CkODloKbUZIdyCN2XBOXjkucx203bqKzkxZ7IWViidhwepZQpcK0dcohmegcvCjGi5Gb67n7OTKcIg4AjeVLE7RFHKRV1TNI65IoiONA9cOrOtBVYVFrUlh6dEWSDYRfC39xagHhYruIas4LtDVTZeKg4PzIAc5yI5yLzWLOxFHQsxqZcubb6fy9TGr0KzugAmF5uFFsmFFABEpOtRXCD2mMoGp7ayOxpAJZH5THEU+7uK7Z4B8RHJGiZR7AxqO8QsMhSuFm9SMYWhcW74XDYU+VF1P/COk19KHseu+BZKVFB0KJHNU+y3JbU2CWl7pDNGMsEmO2TYH8fRGswByDT2LY7tIhGQ7rr5PWq+lbnROwvLm/uHKmqyU2iUSbaZySRPy+2kb93KxUKo5oHBwWpzFUEUyK5HYxifTwvuCpyJkjWq2am9sZrWJF5DPOY1CbN/CoKPaHMatlyqmJTuSVO5wDrxcSRZhl7gTuO8Dmc0EcGFfvYEtkbCOs3Jy00d/g4u/2ZIGUeoKWNsFrZebtHKRJ5SbSmjndM50vL0sDDadWueSyKVyA57BYNDRJOV26Hw2DdC0yb5umrCPyWZ14jvi4I9Q8aMKFSDbdDuRAJUWSxmj5askAnUJNk+TETAeyUIwanJQVl0JgEvPTQFXjtCPXTIVYjY0wU/lnNy8BY8EVt5NQ5Ri7NCPHEavO8BJZAQQpzKvA3xc57btgI+ewB+N4OrkY+FJjW4KUJvPgXNOwGMVgOAb6Sc1qHagZYv+OETyep+ZUFfJvVwsAFyNPLuqIpmB6wpxTKhyZcOs6qPIVn0vzjEDuWbLAaG7KYejASDxep2iD8wZuS4HL3x0tikxq6Z598bJyiwRA43I6IK5/P/be7eQy5IsPexbEft6zvnv+VdmZVVX93TTNdJMtTUaNSMZjBkYrAdjELZeJBB+8OAxSMYverJfJBB6k20ZjITH2BgLLGMw2EZjbPCDbSTPWAg03T2Xnu4adXVVVuXtz/92LvvsW4QeVqyI2Pucv/LPyqruzOqzIDl/7rPP3hGx9469Yq1vfV89fPO4dtq+9wVUY5i6HfNoOAUwAL42hBrAYuUfHnW5gCe6XUtBnmGeyAgFG2DjakD8g5bZuuz1YkhoA/jMj6cOWCx5H2siaULLE7ixg5dE8nQeyrNjFGm1DsRAEau7XVbsQcj4rVYM4+57YK2H2RuteSyFmFfun7bD5MEKdOGyJO5FYpcrpA8dq1ZVM4+FtSgqR3qcJQ7u3UPNl5h+nA2OO/ColAJdXEMvUpjVyl93fXaNw/dzPr67NknXgxYrnmCt9S+ndFVzZmxVIY2In+KJ5nn2+k4WvsjGfSiC7W4f9AsivkO4cYCBW2wNIkpANMqaDKUAen8c2w+RmuRg3YB7sCPcPqWpr46Udom7DmsAJdF943PwVrkbKxJKGgTDXDtJBc/Ew72duvk40k5Cmw94d1zEdyzcA5JnQQJPMh/aBFKbGE0oFnN+CIxda1Dt2iUeRqS16v9fa/aORC4gz3wxWSyJYCY5VFU7TyhMFrIcoknp068AGP7tKmC574nzKAT+H70ApPJWJnipgFWEZj9DElfrZimobtBPGc+g5KE1Fv3MUSnmCaAAVfcga9HO+Hh6y0uQ6QszptWTamQAQw+Y2gAAIABJREFUtsyxPklRfBjSx3aSM7xd4N6eRyMD2oS/c4JGMRz8NkbbNAp+0rZPx/bP0q8NN7q134ATU0yNUkmO/MZzWjYtxkxYYxuXovs/pQjKWiZeqdaDNa1tm5GnYQfrVH8cR64Tk9/EKcl43OWBjGHqQrBjR2AvKdQyskSSNvCBBmlAG8cOZMxMcM8HsHgBUsU6IFFRGIBBDQURDbRPYuwLlaKNwizTpq4HfSahlIs8iI2sllcv0/7YSrRV1KhNZrgvpUlYdvWGlx5ufKVtaDu+HknCmBHwfRMzTMXZNXITb8wsJtcluXcXxtHqgRyIra5DVqgPk6hfvqZcWyOC03Swz/uuVjzJJkmgWnT3ARENrruazaAOD8JvuNHcRqUG8TLSinE/bTeof/qd6rdw1Z/dai2yy4bsbGc7u5W9nsuQ2D2M1+gv4CUN3xpx2Xj0ZnHlwGNN0Rdup3fPlV9eDLIhsLzOjt4E1lp+82zLkjyPJ/RlbcDBYYJHNEK3DjgsJPMBBBJYESeSYjo5LpkXcn/jc/LPb4hDuSWHbbvNLE1cAu/2JQP2PF7Sux5whciYxEWJURA4bAs0jKxLEmU+xr+7ySTTNCbdja+FfL5AdelN9lpOFt41hbit4EkjrjCM3ewtN4MS0Vrn5qvJhLMOwpEpUe8YtSmozCzzyxizWkFNJsx3Cfhzqdl06GYDUHnumaDMfBFc+KqCOjrkTMIFU9nTdMoSgRmL4cbcnarMAjclELItkdQAAJhrJwVQ11Buu2+nCC/L0s25vProcAPuLUxZPuB3cgScX3JJfxHkEu16vREw5Y4Tj4ewYgnL1N7MxxD8sjDnuIA/93QKu1zCrGsoV0sjTFkYM2XdPYY6u3LxkGhpScTBzCwNHJoGoKMD2CIHfeK4RcuCzx8tD7xpzbUjAveWcXt2jvpb76D40VkYhzSBmi/R33NSAIsqxCwOtsC9L5ZYfYP3nXznIxfPCpktIoI6PYHNM+gnZ4G39J37uHzvGAf//ImfHM2s2Ar3tmUGajqo+Qp2L5IC+FGorXmevbqTxSg1eqNFa90Nj+PTUqcDWDenvkhRuPkXywC1lrnCBS05UBlSkV5RmxvMnxKoi7EOec5aGUSguGitd1oOxsCec42BSnQUqGuDFmhNgZYuZr4GB+hiWjxaaqc70obAZxVg5TFhr7eyCGlLRYwkTTRvF5Lagwl00wJdD7vv6gy63sUx2qGOrEN+Mm2gxDTKEFgWuUGvdZpzYaD0wQcV66DVMSlAbcLnL3P/9myPSmRVA6QJTCZITQPqGK9inYo4t83AFjm6kymSMzc2Sjs9U+bDGHifWcqBQRfY9eOsNZb3U2RngdrOTDJoY9Aec3tTTTCpBvUG9Qlv66Z8HfQ6RYFQYDbJM45txDE1rWEnBadOLzJPRdgflJi/o7H3wcw/L90sQwqX3jaAdTUn3SyDrjokvfHUfmTtC6VOX90Ap9goADfYJiYeRCxO/Jx++cBpH5HZ2JBas04XYqD9IcJFSg8CXJQkG5WtlGZ+CTMgnNGM27cSYAM4kCjBMEklZlmYKCV96torbR3T6Mes474PisJvgGFA0UbkN8LcPZlEKc+Q9o0Dp+LtwJiA63A0gTEztl/COA/A4xlkDPp+I2AoHk88AXIKuA8BTgkGx6lQIFTSxuPgwG0xRSDgliFZxozZks52AV2v/REvL1ytjveOXB9NXSN5+y2Yy6vQDufNDfhEhbDJBb4pIuex6zVIqoKfPvP3s43SqEyWpAf6K3p/BpyeAGehiA0OBuBLAmRcHedq7KUCwG9f/6+46p7uApw729nOPj97dZchYjd5CFG60FucLpVYheiKxNs2juVwDPFqZSQC5DayVxFR4jFdW7axXGL3P6ik8zYKcYqmAWlHsdbWUNrxa0SSgbyPSwfKC9RwBSc5mT8+GPnlUPzWMHDaJPHbRNxwUoCN2uPSlZSlgAtNWDcgRPJWdQS0hZNOjOHlWnPQs2kDCjUejywLZMUOM6Imk4CoFByI0yehKA7DSmFRMV2kYRIHSmk2jQKuEYS7yGBXK1CaoI9U1lVZuPvDXZ8iB8nyMc2CjKOk8LM0cHJkTFOnANi9SRDucd4pWRP4SmKNGKcbYl11LFVOeS7CPgzAYAAsAHWwD0pTjhNJqng6RXcyg76IvJqyBKiKaBRlCZzBpgnoehHSx9YCy9tX3L76k8VntU+DeUdgFX+jJMmA53HAZTA4LA1g1TSmjZclgWiMRjMQJQnHLADOrXsexyZsv74Ov2+dFICJ2uvkAShNNuI6XmpAzic59b73a2zvRjv3PqyNXX/zfCOTIO320/KkBAkPRRmdr1qDVAMRPRofI24nwIHOOIgqRDtoyKvB+316E6QA8syzcCNa29vZZCjNB3hAE7rOxaUi/o485wnCkQhRlvJE2HVMOiTHsC6GUIQJmgrm7rTrGu3JFJkExA0DsCwAc8CThSLyJfNGtE4TBZNqJPMECkBzwvumn6Rb43Q0KRnstV4H9Oi0RHWvwN7HkRTA/nRYViAvtUkOm6fQbTcgLMLj2y8uvryTxfNsLJsnaa1bxHBiFnBr7NbU21Y5e0mHuvMPfjdm8xLiHRN9xm0f8y4CQ6kBwBEGCzt39MaVOo0RS7m0Y4NZvO+Z6FUedtE0VWqodWpHY3rDePj9BFoNuEmcmCMjZkb32qOR9EHXDVm4xZpIxkDOCzdh9D0jM0d9RRekAKjv3cTUczoy7hs6UBtQqFZYwS2ze8dSAHKdhckbbecLvVTlXkaJ4sBr3QJtx8eAi/NsQw63HUsMuH4DgGo7JIvRNa+bQcqdZOJ2sHx0PaiOdH5fIGb5pZ0sSBGsJU+75zaGtGoUdORPt+15+Wgty5DARUF5BnLutJcSFF6B+N6NCWTGVaPJ6FJIwFZFn2ICN49dTUnpOtg4AL5p8twR0rgUmV77gJlFiOqTPCRJEljAYkKeJAFpd5PFhDGxfGDLehtDpnXpDgWCFw+vToFMjunYp9OUPQGXvqUs9Te1LP28F4ihZ4Es3YSvS1HYWm98JyzgfimVZuyitx3MyT5UPI6ZG9cIcg4no9iVKbQs85xngTbi1Gja4FmULpDtPAvqDGidoHfbU61CtWpsWcqs3HkOJd5vmqCb6eEY5BlQt5ueRZFi/eYM5aqGmbhrHiN4b2Ff2snCxm/bsDH8PVrbyhvlufPsaB/b97B1s5GZ8MczQ++BZM0sbzFpa7SW9r8XYZ1IYMf/tmkGEPBtzFO2abnCs2nCEqLvg0BwXEgmbY0wDrF+CAEhZrGq+G+lQn9cmwfVv+P++Leya/e6Dssi1wcvtuSribmNA5FiUuF4UcZCLVYby0dLTAJjmwYUZ5AA7mukfUJ17fRBOq7cFEyKsUDbujhS5EG0LWzdIH22hJVaGcmo1TXUFS954piFili9tItZ2FWF9NnSX7OtYk2riiedOhozAOWj9bCSFgjwdoSYBXU9CgC0WEHHbOtjoapPsV02ZGc729mt7EvrWXwqRdrLYkuEEMb/3/hYwE/NtsVbnByjHa9NrQGTHSAESW/wCL5wixXXehswJBIfEUzFT8C8XgfgYiXuvH0/JDMCgvfzPNDg59k2Oe8LczuyUes4QGzkWbyAfXkni+cJJfsHO9yU1thNha5tFpWo+/Lv8UThtsX1JAPFMClthwMkjZCUXuUsUkGL2+6VxoAgE+j4G2OCG+G7DJKC7vfCBBW1wRr3fy0sWCb0xWVVAHAmSEiG43ZbuyHJMB4P/zfgiGkjaoCIpMdnZByYCJIZApij0iqnBhfVBmXpZuwHDgAlcZd4uaY1x0QklpIkoRQ/S3npAfjqVEqjmEiWMmkwrRmxKSAruGrhruNSfiAohAGeNMcmCjbVUNaC2s4rkm29lyDxHXf+SBmunaVIIsIjViQbjpWMjSky6NSV5Yu9AHHy6zlZxGnRT4N1W4sNSmOJEo8IWnxaTgZyhSgdOiqjFhVzuBTrOHAGFwCLEIpybKndoGrtayTsug41Hc/OQzvWNac4pewagG2biHchKuKSdk1DWsyuVry+tzaUzGu3tpaSbalxkXGYTQGnreGDX2kyrDk5moFWK56EypC2A1WOgGdzqpXx8H8DoEkRcB8ySRQ57DK8yWUfa41PC9O0dFH/PiAhAdb1aEYYDyIPCaciB2I+i9mUoeOCvsxSoMg56xET6IAfVrs3CYFXSRn3PVZvTzBb7rnB4QAnaYXmDd6WnmuYgvvXHvLv+kzB5ITsMkOmFFZv8/jOPsi2eit2fwpTplDLlZdPMMczXH09Q/Hh1O/XncyQRJO4TbkP3SwDWUBNS3QuTUvGwj74sqdOY4/hJkasbdsjt8sDX9z3plo7uPINAVH3f9tjkKJjFqpqmIIFWOuiaQYBNVOtoSTwGgFvbN+HAqVoX6b2a8LnqO1+IpKgatwORMGyvg/BuhENoQ+OSbuvrn0AzU+kDStz+6K7Jxess6LUIGUoWh5bA5wSFI2t6zaZsrqO++WvA+tkWGMDv0PXhQBy9ECnn5xvjCNIAcuK+18PA6X26hpYrUPQcrEM1zYN0G4PK6+bIVOWC8jOfnAJnF2Ga6FZcyT7yGW7qjW0BDivXE1JBMqyqwqz0X0zNnp6Ae2g6RIg1o8ucOe7Gji/DGNQ1YMAp2R0ssuMJ87FCmmERaHm9kuaXYBzZzvb2a3s9fQsbmO3rTp9QQSnLwaTdWLT8t8eeh1Qil8ogjOik/PdS1NfOg0AtK4dFN1EMPNQCGV7+O2eI/MnieAsCo/p8FW1RQFQSAv7fYRCD/gCEZwZL4O63i+VAPD4ZykvPXy7cvYOFsufDIJzWjKt3qoKXuALIjihFJQxMHtuGWLtUCfnOfblnSy+IKNRQEjg374K9SeZUBDQkMQsIiEfAI7h2dWxxNybMY1fzCV6GyW3z9ukDx6ARj6AKUZab9LyfyFtoUDTFwc4+z7UWMQM41n60mpmt7aIM5a2BHFvY32ZQl0pL5nwokmmV79EXSzi5NwmdLxhMU+nQ3CqooDtzXBdva0gLd4+boYrPY9rQShJwtpb3uCtA1WNSusHpeJyDBNIXHzfxuQ9cak+ESiJItrSnhFC0lqX3YkYl0w9ZAD3SFQpO99S+s5ZnaD45svGMZw8Pev2NlN6cDw5jvfsXNn6oO/AILXqzxmV6MfnpyzbXO+7cfHl+tG9Qy4b42MxeR4Cv5PSkwDF5e3+94LkFcSneKICkOv7AT9pXHDHJ1OeWdx2neeP7RfLrW8cVZYQbhQpfbdX16DZFOZqHvok12Z0L0ApqKNDmMurAYfJb1/9L7fm4Hx9PAtxvboOqij8xRHGKJXnTGYK8AOcOk6BPIet+QY264A2TO7d5W2OaFXde4OFep2L1r//AfRsCtt1LGIMZteyfQ+1f8QReQD9w8dQ996AffiYT+3apX/x50HnV646012LowO0bx4CCsjefwxzxCSt9Ogp6n/layBjkfyT3+Nzff0d4PFT0GwGc3HpVdD7x0+g793lyPy5i+ILc9LJEdr7R6GP73/CN/2zC+At7q/+mNuJsgCqNeiE9+8++JDH41//JSTP2KVWC8542EmB9s4EySWf5/xPHeL4u1eAtahPXXbHANmzFejB41AD4kSSrbXAz70Fdc5jbU72ASJ0swzZB095X1d12Z3uIXk6BzlEZPvVU6Q/for+6RnUt94FANR3p0jmLXTV+ig/ADz6sxOcfqdmST8hdSGgzxUmD1Zo9jOUv/eAz9cb1N96B8v7KU7+H7dtb4L2ZMrHLVOPqgSY0Gb19oSDmQBaWTZ854/xh3/3Xbz1W27StUAzVdh7UOPhn+M+7f/YoJ0SYID51/h43Z6FKQzyxwkO3rd4+ms8Mb37X6yhz67cMivUzVx/+y2sDxVO//9nwFPmr3j6V/40fuHXfx/v/91f9mOwuK+w/+MeXUmABbqCx2F9SkiWwP6HHa7fCenp5n/+P3Fbe30mi8iY4TjckLB2g+3aa2qM+QnlGC6F5jMLF1cMCY5KjT2zt2QbXHbDLpesfeGOby+vNs/z5Jw1HiJVcTIWmdvPXM8945FdLFH8i6eAtehkvXp2ziroPYsdCbmK7XuYq2vQOiiQy7nVxSXSWHRnvgDqmrMwTzkl6ynZXNZBXUgUn8cz+/Ez2KUc171Z5wmyxcRDmo8B0KNnAIDyKjxQtlrDLldRIZrlOgdjoR4+85M1Ofc+K3JYYcV2WZm0qmEjbYz0Q4K9nnNb5ZzzCmhY1T3LMt/2ezhlNfN4Kaa4NoQurpEUeWDhBlD86AzZWenHltY1xx6aFjpLA4QbgE40p0dd1kNiFH1d463f0tj/wws/jjZLoK6WeNPe4T6cr2Adc9f+R1HqNCVk1zWyp0ukFb8M9MOzcF0jr3Tv+yWmkwx4euGzQnd+d47v/YP38Ob3AqXf9EGJ5GIVMWXxJNbPMlBnkJwvkZ+FmMW/WO7g3jvb2c4+Z3stPYsvxMQrGVd33pSGHpeM33S8bb97AdTcC9vLxqC2/X6kezL8bpP20MdMnvcqisr0/ZHFY5TtdgsFQBTQvantG9qjcTxktG/4UczIPYa/6+G2aD+y248X9Fbd9yZsI+PYxeVn459H2rtE7J1RP2qTtVB9FNeS4zj9VAADaDc5eUmSwjm75byfYq/lZCHl5+4/YZtP2d3CtRpH4ZOEU4aRJqhAwP2CUGvAdBA1LW/bEJwCZY6Dk0kSSpy18uhDKxBcG+DmlKaBRVy3IepOKpDtjFXVSAVYMYCNMvfBvjTcHvXFt8toF0zVzLLkHpA+T1iBq+thC5di7A2rXUXl+55ngYyDXEtg0wVn4/JwP0bunNH/iYizThIEzlKeXIhgi8zf/H2RIEkd2W46rH2hNOHfSaq472HTxEG1k3AdRclLIOLRuAy2yTgrQjNVfpkBcBk6rRL0TtdUVwmzeVt4rdOudELFBkgWKdppYLTy6XGJwWnFbc00dNQmkyVoDghmkvlAsCk0bJ5we6wNy5DCtcUdB3C39ecJ9yai/xbAvwXgibX2PbftbwL49wE8dbv9J9ba/9199x8D+HXwO/k/stbePoJyS7uVMLJMGDe94duAUiRLHPluI0FeUXaKYhZSLj7IxkQoy0Eb16yvGetuYL32f9um9Q+qbRqo+ZIvrvTH/d5H4FXIvti6DkQt0i53HESixIPvR7IB1v29kT1YVUEAWZStOiZvkeyAvshYxcvYgYaHXXN5+6B0XtoclaNjueJxaENmS8bdupiBP8ay8qXvspYnGT/TA03jX47ZkwI0Z1Z2n+oEOBuyXIHqJspaGKj5EtqYQJJsjS9RRzuUAmBxauX39S/kvsfeg1CODgC0SkDzJfInDp6+qKDci0N17qHONKwi6KqFulxi9sBlTpYr1qVVakAMpOZLUM3s5HKPJOdLHPxxAf1sHibFmrVTPfG0m9RUlYHaHjRfwefRrAV1t49Z3Maz+O8A/JcA/vvR9v/cWvt34g1E9AsA/hKAXwRwH8D/RUTvWru1tOgzG2nt+TGF3Ia0ho06Tq6YRz43juFqGsg9zKxr0QRauvncA5f8WkRrECmosgi09E0LtTcLEGkXFKTDA65DcFyVAKD293wmgLoOtM+1A9R1MHeP+YI/4WAVzWagpuVsRt+HWoSqAk1K0HQCde2CtJIZ2pvB3AnZENV1oDyDsRZ0dODPBcBliWqovRkAeN0Qc/cY6pohzZ6roshhDqZ+++rrx5i4QGp/yL8na6GuV4FEB0CozFWgw33ABRdFqs/sld5bERIeczSDulh4cJV98wT0EEwR6PrQH8+gVg0D4SLw1NV7h9j/I82ROL8UYjXz9OE1+mkBVQXwVH/vBO1xgfzSAeFmU5iDKWjdwhbpYAKweYbmjT0P4RbAFc0XePjnCh/MpN6iLzXyJwXOv8XtnT4svZexeDN4FiYHirMCew8KPP4z3I+vfrjvvCY14I5t3rmD5iDFrO18oHH57jE+/vMGxbNjv9xY3c0xeViizxXIciYIANZHGkltMXk4werN3F+e7tHtcSLPDXBaa/9fAOe3PN5fAPA/Wmtra+2PALwP4Fdu3Zqd7Wxnr6y9TMziPySifxfAPwPw1621FwDeAvA70T4P3LbP125RSOaZsrYFHxG56NYARvGSoWmHabcNfggbtC7IpU6FKWvM/VitQyGXLJnqGmoepTsj1ixaVCBjfbTF1g2vQ8V1j1OzTQtL65D2laVF3TA2QpobfS9pQN/OpvFtj03NK98uWzeMGIQrSHJv+/zZmttlDNQiig24Yrx4/DzOolqHPjg3W1kb3HoR+9WKC6Fcv9W1Y7+yxrdLXWuQqzpFH4Bvk0dTVv+KFcmIoFYtqKr5fJFIsVpUSDUFAtxqDUXEfJdNy8sBZ9T1SM+136bcfdL3PfZ/bJCeC6sWxyhoUWH6kL3X7GINs0wcMze/1btCwSSEbN4jO19j7yMXy1rL0tUOxjK5qKDqLtxXAPKzGns/mCK9XPoxKImQXFTQLlaROJEhXWdQdY/kYoVSwkQW0O3tI5yfdbL4+wD+Fnjp9rcA/KcA/r0XOQAR/QaA3wCAApPn7P3iJrKGXt5w8/wAEGDESoOo2xqsHB+Xy5dDYBVb4N4chCTPY+l29jUCMScGAEYSxrFJzXwNMUzbm3JBR6FM8+jA6PiAbye5IOVgX6HxH9UG2JhfU+DXRLBJCFyaPIGWIK8E+uL6lW2mdeiDrKfTiM8i4pWMBYnifQbBxY6zEzZqf1dqZC5A6sddgYN9i1Hw1x3HpBoqoh6wKT/U0o7BvkXig6EyzkSEdkohwGktTKahtPZLD7NMYAoOcLYTPldXKPQZoDoFk2m0k1GgNzZSsLmGKRMkSeIrbU2u0e45LIWbLPpCI8k1TMb9MFKiXmpoTUgWCfqJa6to0N7SPtNkYa197PtB9F8D+Efuvx8D+Eq069tu27Zj/CaA3wQY7v0ZGvHCP9l+nJFnMk6JbvNibmNjYVp/jCg1t227AMCcYK9nR3peqvbzshvSlACG/BmO3XvA4TgKOm8IIsfcj59HO60dFL2RpA0VIjZzFZjCYkZ093/qzYtd121mRn+PUqlk7UaKkowFWc6G+DSq75fhMJnv26eE/AyG95ikaEdsWPQ5jPlnmiyI6E1r7UP3338bwO+5v/83AP8DEf1n4ADnNwH805du5UYDorShZ+d2jFLxPvHn2NIoXQawXgQw1ArVilO0fQhwitSgCAqDFP89Oo+dlpxxiW+aIkfvqg7VReoFZ3CtYQ4mLs3q3nKTArRcMuO0roNWKeA1U8mLGLlgb56jn4UKROXaaat1VNUa1YIYE/XDBe72S08q6zMdZTHYXp/kSJ5wrYI5CF6hshY0j24pUUsnw32VILCDdpu9AvraBSglwLlfQjvaewDo90vo+RJYKD9e3UEJnSgORJYhwLm8myA7Zx1VG6WVu1KjqFr0sxz6cXir9gcl6pMCE0cMZMuc+1klTDQTP4R5hvaw8HwUUj1KWmP+tYDMpN6iKzVUZ3wwk0zuPYrFffemnwB94d74TY75z/Fp3pgUTLCjovuOFJqjAs1hgvTj3Ff8Vqcp+j+5RPM7pZ9YVndTqM76wKZ8VscKSW2h2gKrNwTuDZj0802d/kMAvwrgDhE9APA3APwqEf0SeL78AMB/AADW2t8nov8JwB8A6AD8tc87E7Kzne3sp2PPnSystX95y+b/5lP2/9sA/vbLNOq5FlcaauWk7WKA0W1AWdEa3rEWea5JAMKRSUKd7/a1cCCrQR5/i/cSl4eLObCQJYJ262OA18pdrkHGQknsw62ZJTZBMVgs0bxWj+IP8imq2a7B/J1SYW0fIxmV2mi7SXm9ze1llTAra3vn3XSl4pSlteiLUJSkUlEVc9oYgtMgclojyvcNRLzWjqowAXA7I0o7K0ryEU+pzRRsm4B6C5MnHjPXlQ6/kChfSGYJMDmDpkyeQAu9oOlhMo1uGoHjlOLfun/x2NhEoc/CNptIzEqh27P8nRuHriQ+toskdoVCVyj+zjli3dSiz4FuSmgnCu2eW35mKY+zixXJvWQyhT6Ta+aCqznh9GiOrrzjlzFdyd5EXyjEhWS9a0ufKXQ5/616Hp/b2muJ4IxtwFwdg7K2BQZjk4fSOmDRGAbstDqsrCHlXDIp+YfPBQnH53GBxXE2xiSjh1nORQSrQvaGjIVxYKjhmtRF/yM0YYx29MhFwAcgicgH9+JS6Xi7P3yiNoKeIFfF6cbGJOA2xQ9TJNAU6P5cbCMe36jfJgkTnoCHbKo5mNqQ/39YcrrfaQVNYakhN3yfk+dq8LEMRegzxfsqDNW79OiauUmROgOT6oiEl9th8jBeEjjURDCF8e48GcBqFlRyiQ+YhNBnAFlCL9SdOdDPevSXCawi2Cy6xpHSO8Bt7nP3kCfav+i6nHCvXOKc7vjgeJ8RTEroUwLZsMzoCh4okyn0bgIxP4kA5ytnDjs/8CxkvXcTVXssZw9wWi+m0ycFpCmobYeeRW/4t5JyNJb/HrNLrSMRIJlIuh566dbt1oa0KCmouuMb3DN4MU+GdXUNXghHswAxVQER6VGQ6xp6ETFFNS3/tuugKt4uwsvkUJKhypbbrwXs5NoASyCR13N9zK6NHzPVOvar3voxjMWfvWfRRrKILUPmk0UD65C0VLsU36IG1WG7XtT8t7E+9ZqsWlDdMlCr177eoji3UFXnmLPDmz676kBtD1X3Ac5veqiqg16nIQhY1UjmCR+7Myxa7ExZi+wy89uSeSB8zh8nyK5lHHnC0FWL4oxnhmzeQ3WKQVAC954S+ssE+QWQLg3yJ24yF+4MrT3KmJRCftGCTMLX3QH/yguD7310H++sw31bXBik8x6q4ZoVLZOu0kgqi+yyRTkJY6NuQQ0j9npOFiN1Lm9xifrzcBaelDYiuxX5PXcs2zSDjIgQ52yQ7a4bIBYqAAAc70lEQVTrTZzFcjWELQNAVUFfutReXXtIsmka6MsVYAx6eassK68kZtsuKHqLapixmziL9RB2PMBZSNn5GGcxoqHTF0vAl767m7XrWGXEjVn5uAItKsAYTqECPLmt1jwZRYpmgrOI1cJoycuQGMsg7VJEfuwAQF0teR9rQK4PGjzZoeuh+t57EXsPCh7HRPtlAgwABYZLW+sh3LbvoS+WKAAPb4e1jFJsO9A68fByAKC2Q6aU3yavpb7rcPC+RfY0jHuySKEul9h74CaL8zVMxstM3bC70U5YpjBdGuQXDQ5+6AKm81XgQJHrqjXSsxX0KnWEvu46PFxj8p0p8rPrMNk3OdJnUYl6zpNQOk+h6h7p+QpTnyEBdPPF4yy+eIuYsQAMGY6yzN/klGWwVeWYlgJLFZPf9P5zbGrGcF0jLv7xIWi1Zh5HAHR9zTDuugEq91YvcqBpQJOJJ7+h1Qp0sMfU+IA/lz09hrq45noQeaCOD9G8uQ9LhLztYI4F7t2j/sohYIHs4RP+/ZsnIAA0m0BdXnuKf6rWoIN9prA/J78NAOhwf0h+U61BkxKq74E7h9xvqXcoCz7WIUOvcck8DfU7xx5gpBZ8XOPIb1Ihv/nFGY47A7IW9RuuXb1Fer6GjkFZXccxlrZhGPkFw737431AMc2b8HtIhqQ93UPyNA3kN28dM0dHXcOcch/WdydIFx3UuvV6GwDw5JcL3En5IRS33BKhzwnTjzO0sxTltSMcMgarb5xgeTfB6ZMD34bGkd/0I/KbXshv3IPmOTOfXeDprzWejwIWaKcKsweZh3DvfZSgnXCaVLIe7Z6BzdijOPhhiYt/k8f88Icn0GcZ42DEeyXC/JsHTH6zqP3keP7eBL/yF7+LP3jwno9ZLO8r7H2Yoit4GSIxi+qUkC6A/Q+zAflN+8PbBy12fBY729nObmWvLgfnp3gWMZ+jLxRTOhLiifgv41r/+PCCL3BcmMwHaTxrt22a4MFE3JG2c+XiEq2X/bwOCZ9L7e2xcG6Ms0gSXs8rGojl2qYB7e3x0kcqK8vCBQddJaoAnpqG226jZUjEjakidm+zWjEytO2gBMcgHpnj1ByIJQHQR0fDalXhDY35MqcTXrb1fWATNxZoG/bqJGYhtHoyRl7QKZSJe+5SYRNzYynjJrSJtmmg95yQT57zUscaVl+Xe2F/D3a+ZC8zQpNaWRrF90LfczFhnsE8feavHWUps6FrNRRB1hqUZ+H6uIxPf70A/ak/Af0wsFUhz3gp5bw2Wjf+3OJBiSoY9VwJ2r19wqf50SOnSaL98ogZynNQomGurv1112/eQ/P1U2SOZQ0AX6dqvZFlQprwMruqgjCUtfj/Hv9DXNWPb+VevLrLkFvaBrms/+I5aMFRrMO6B5PQbt8/Oq7s6//fdhvn8fGOeFsX9rOSJYDLyNSjuMcoIj7+zgv6xMdvu0HS2LczFiny8Zfwm8Ex6nrYLqntEMQmwCXmrg3+LhtNamG4HHlN14XjusCnbZpw/ig7FavPG2mjtVE9T8gQUUSgAxFISpKQ0bF28ND7FLSx/CIwobbEujiOpwOMx5fUoKTfj7010GdXg/gGOq7h8GX3gnK1xgfGlSjKEcGua156uN96Ld0oZoHlEtaRC/sY1XyO9JPMiUu5MViTC2yPQItahRhaPAm+gIr66ztZDEhv3CZJpb3A7wdM3bGGad+H+gyxF2W4cvyTtCUV6fEdAN9UijDIYznSGjKWcRZxLYvWwxTgF2RxGwGEfigCoPlm9m/wnttvTJAi7PswpvGxhNn6xRvk2+VrP7QOYsbkNF218gQ71hXjhfRydMtrxq94tOdntfj6Sn+Viu4r8WYQPcRRnYyKx0YDZFguUTu6g0hzZWDEuA+fNQPgmdhEC3c8abyEvbqTxbY3qv8uIlyJBG1idu/nH9+95ZwqNcHRy8vXrSN8iWUDXqQmI86idGEZM3jbxBdY3FR506bseVipafC/64HuJW/uT223Gd54EjnXOggUZfASgwOJv753/VqGtgJhUvEYEjMssLutxcQ9cn/IuaWNLaegB29zE64rRAIxXnK+7MTb9WHMesuZmr4PfBRRrUxMaGOt5fRo3/tgplk7GU3dBG/wpvS/NaC2C6llgJe4vYlqZj4/APUuwLmzne3sVvbqehafwXyZ+AtOphS5avFShpwrJ97LTeXuW00RYNTmMgdgl9PFAwD23klrfhPHbqrAzePKTeCzufCfxdRQ4SxWL/PgMIFwyz42AMvIoTytcbEPeTUJUOtlTJYkG0tFt0yTwru+ZzCXLH3scBw9kjXuw2dsSzim698AteoKHSksn9B1IKU4JhEvsbTm2EpcwHiDd8HweF66DNqgRkDFlx1vvA6TxbYA5YByLGzbyJg4pa+Bypc7po/YrxngpPdL2Kb1UW6s1z5zIOey4ItIee5/b+ZzqL099FfXPJkIuGhvxgCaKICoyoKzHgDMs/NIWWoOOmA6te6jB37f/nrBwkbr2mczbNsAKoc6OvKK3pJ1oLIE7c/8+cz5JUf3l6tw3lhLteugJoyT6K+uAWug7p5yJB8IgbA0AU0m4XxvvQH6+AlX3wo9IQBbVbBXc1ZYH5k62PNgL+m3mk1hnWYHHAkxTQom6hF6woN92KtrmGXl+0BO09R2PSjR/hZof+4u0o9HpG5KAafHoItrznw8ehK+Oj3h7MRi6dq4z21rWRcVkX4HpSnriDqBH5q6qtvHT3H97bew932XYTDMhaHmSzTvMNVeclF5cFRz5CpuM4U+Z2RmerbC/JuM09j7xxUHM0cBbfra20wu/OCpD6aab7yNp9/ex93/O+L0OJ4iOV8GrVPhs5ixinp6tkB35ApULGC/G2m6Psde/cliiw2CmjeQ3NzoBcjkI28/eZMnCUeGowDYBqGNSMJpPQxqJcmmBqoLUMWEtkiSwIattQ/CkVZh+/iYWvtPb8LALdvkxkoSn5ID5A3DwTYvKkxRH/oI/izxlTwL4kcCMU9TZtF2iM5umiNNudgpbjc5UtttAz8I2EmsIEvDdZBt7vzWaP9/v48UqBUZs06pLhT+AWj3UiT5aBy14odskfKxYya0PIOZZL5wjhzLOgGweerHgQAgS2HKFDoL7XQDivWhYgEgMDjNZBpUp2gOeF9VdzAlt7M55M8+I3Q5gUwCvUqxPuT7aT/RntwmNjPJ0M0cE7kUks0yVKc0KNPv9lLoKvMM3jJZtPspYAG9yNDuuXvBIii33cJeu8liHBn2aaRxGtEFDWO4t+iD2q7ldFP0OzNfbLBdbxyzZ2JgU9ee+JZZp1eRQjifQ/Lhg/PPF1DyIFYVjJy7aaEfn8Wngpkv+JhV5T99O6oKxkQs43KO5dK3C0BgB+97r8RlPRTbkb64gB9lGXtBT858oNj3qapAq8rDx9MfgVW8lAJFXoTpuqEyXNyfCB8g/aZ1HWj15MF06VR/7qfnfh/j1NNoVTGsfJCNASbft7BX18MTk4JKEpjVCpQmIQgOQD85g7rIgkqbtaz01nWAIzT246s11HIF47wQWlU+ixFLCsIapuuva8wEnVqtkbhJOf3Y4VJcpTNVNeyqwqmr6YnHKTb94ClXKkf3Qfb+Y3ylvsOSkc7KZyVsVXnJACkpSPOMq32vF5hcBpyFqm4f3H19JosYUBMvTT4NT+EFfd1/tSvIIhXlyV1UXYBcZsux4/+TYlfTRZkHHgWpsIZvtvByRjgI2zONPf/HBIr6aF+P6ZDP+LejCD5pTlvaug7LLaWciHDAJXgxYY+3iIBSxvKDIxNwHGEXrAXcRBbVf3iTzNGWazEYj/hhEM/LpVZt0zrvJIwjAIbtxxgHyTZFKUF7cbUxjjw2nCWxAuSSU1dr9mJkDAwXCdreQCVJhM/gftlVNcB6UJLwsiWSFPRt6XufPbBN670FIa7hiUbDtsz9KtmLbfcNAF56iGc7daUK13MkDwgmxniM6pEkLUxpApye+LqiMAi3D/DtsiE729nObmWvj2chHkDXDYKW8vdgeWL57ckw8EgpKlJR1/tOu2K1Ylf18IArEh18uT87829b2zkXOUk5t12WILdmNZdXoLLwVaFyjuSt+7DRGxhwbwSnnI4nZ+ENcXEJ+sp9wFr073/A7Ts9gbm8gioLFjaWds3n0Af7oLL0LrEvZZ5NAaetAQD20VMO1DUN1BEXYfn4RpqyqJIrqOvPGPKs3/2Gr+60rgiO0hR2b+q3t197A+kHT3iZNw00frSsYM4vBghQ7qCFfuOOf/vSjIOwdlIATrBZxtPuTVkoSIqo7hwBZxcw8zn0PVaCt/tThlA3Lccv3Jty+fOnmHzghJ59pknBFgn02TVsmcM+eOTaZEDv3Ed/UEJ//8f++thpCdV2TD6EyLIU5ngG/YiXG9Jv++HHePpX/jTu/K4TXLYWJkuQnC+xfPcYALNwGxfgrE4dTDznmEV5YVA+XOP8PQ463v0/PoKdz9ljir2gb7yNfpYhe/+xX1K2f+ab+PhXC3z1H4XiwfWdEvnTlY9VCO9Gc5BCNwb5tPDFfzAW5p+G8oDn2as7WdxQ0wG49bUAfPKcYwlRJSpg/OQxnkT8MY754SGBNL95AjWvvHgMnp1DTSYMq146N7XIgb6HOjyA3XPVlqsKeOPEu5dyru4rd5A85oi6BNXM3WMsf44j+ntdj/YeP9ipMbj61gnIANMfczbE3D/l8uv9Paizc9DJkTvfCrhzjO54huShq+twWQrcvYPl18NkMVs3/GBZi+4rpwAALW69ZDfu3vH9BYD5L95B+dhNeJdMq9/t5Vi9WaJ8wuP7yb82wZvqLmAtVvcd96SxKB/VSCOAEHWdL7Vuv3qK9BFPCM39Q4AI9UmK2R/w6fs9Pk51f4rykxJqzm1Y/vwJpn9EoLpG8zXuw/LtAtlVj3TVodlP/WTx0b+hce+fHMMkBJOEtHRXAofv51ifpDhaiMiQweV7x5i/o/H2M67L6E5mqO4VSBY9uplG+Si8XNpZiquvZ7jzXffQ3+P2zs4v8Qu//vv43j94DwCgeovmgHDwxwU+/vP8sO/9YIp2D0yz8id5wjw9muNeucT3PrqPyXem+JW/+F0AwIc/+CbST1zVqcQ8tMLTb++jOiV8pb6D5AH37eNfLfCHv/H38EvP/qrPnF5/w+Dwj/bRTl3VqZvLV293SOYpDn5wgKt3eRv1QPP92wc4X91Csk+xeAKgJIVtG94W14lIetWlUMem3FvdOhy9mk05ZSZv8GfnUGXB6005V5r4oiypMegXS+jZFL285d259Okprw+lgAlgD2Q64Tfy5ZVXNTPLFejeKag36D/6hNt3fAi74tJ7u65Dqna14iI1V4wGwKdn1bT0b20AMOcXoCyFWVZQLqVqnIqZ74t7Q/YuhZl87Z2gl+HaTknChLqiQnZ6CH1+zW92SdX2Paiq2dOS4jTRYbEWan8vFEZNpx6HYNx5fbam5ACdxAvUwT7M1TXMcoXkLk8Wdlryg9SbgWfR3D9E+vgaSJOB1im13DabpcAzF4hsO+CNE1ZAe58naGjFqeCu48xSFEwU7wrnl76dANA/eoLrf+eXcfg9l7Il1h7Vz+ao32HPIr1cO34Jg+aEf9eVCiBAry3yswpX3+RxPP7HD7jYK0k8nwiUBo4PYMsM9OCxT53aX/g6Hv2r+7j329deRLmfpkgvKn8+kSjopymT/Vws0R85NTUL/M7v/1e4Xnz8s1FI9rmZK0gajNpLTqQ3qX/7JdU4UDve35hNXQ8PI7+97NwLWdwGR6vvxyX+LhLrAdiz8EVZ4yDxWA5BKPleFCi0ZTz9eYGgZt4Hyj9Pgd9vto3MljH/DEbxIWwYhwEdfwyhBxz9XvhuKAVghzB/2swuhT6AIebjMRgH/m9fL3aj7QKcO9vZzm5lr6dnMdYIkW1WCsksSD9HkSx2lRECbML0LAVI/m9/GueWOx0OWq2YdUrQjZIJLJhzwUZvVUpTDowRAYul1yixqwq2yAcpUl9J6GHVI1BWWUYFSu4cee5jKQBAiwXzIKzrgLR0uAjKUv5dPgxw2dkkFLu5CkbKMnb9nTRie1RAXzAZsACCrAHrbFBAsQ5IffPMB2JFzNhOCpBz9YVfxO5N+I0sAcq9CWi9Zq5QGa9ZCVQNpz3z1L+BqzdyzOY5p2Dl95qZtpOuh53koUIVgJkV6GYZMklJliXs/pSDq3k28DJtnqI7mSF1HJx237nyzxIs7itMHwh2ATCFBtU9Vne5vSUR+oJT2Ku7wpDOwKziwkA3OZb3eZyO0oTLzKV61Fl3PEW3l6J8Vnpk7fpOietvGNz5Tuq9m/VphsJYWMc23jsu0vooQbJOUQBY33X3grEwP7y9v/BaThYD3oQRXsDv8zwOTs9AbTiNvl5vcjtYO5gohGfBdp2nsrPGAtV64zy87m48FBsAbN2A5vzAmaYFHHUc2pY1SiOX2K7XDovBAcOYj8Lzh46RlnXtjy/nIPd9AKG5/jQtVyeOcAm0WHldVIFc277nSdcFkLOz5YbmJ6zlbTEeRLAZxsKugkanaJZSb2DqIWkQEXHfJWYxX8E4LdnBOV21JXXhXigfrVnpXTG1njsglFKgxQrU9TAR87i6XiGNxhFU8QTRdUDdDmMWXYdEKb9NHmPTdtj/MWuI8gYLmzPce+K0TpOLCknOnJiqc7GFXMGkhHTeI322wt6HaRgbF0fz15UIyfkSumLuCsmw5U9XOPyjfaQXgc+iMBbJ+dLLMCbCQr7OoJrAOwrwkkU1X3I+C1IEOxI84LqMFzjISIOUi3U2YwQDL8YXA23CrzfMcRoMOCEUDSj5PYBLKaa/F8AUwMxfjvfCxnwHUuymIor8mLMgpvYngvBiCH38oFBtoLUSxsW3q4uKnpQKBMNZwkLJgKfw53S1GpaeC2GvcqAxCfTKPkko4vJ9cVqlsbwBEbFHF52TjAHZhPd3D4rJWUYg1qIF4Auz/HcAB/+cdILSUT/leDGcXr6LdVeTMJ5dSSGgasBBRa29GphOg/aoVworFPqUoBoLm2rPlen5LbQeyBkg0TCZ9shMALCpZp3VSOvUZqx3K9sE9i2fOk3832TxQhwtr+VkAeDlA1NjLY6bjvtZtU5vOpc/zTC4JsG2OKMz0Dp92Ta8gN2YIdsWsBOPQIKFo76O+Tj8bz5LFeS2APC2wLAEOQE3sUdt3gi24sV4Sra2C8MAooxJdNgNrVHL35P7LY2bEHvKn9I+/r0ZbbNb2/Cy9vpOFi9bchu9qeV4/o09OM/QsyDl1uGyzlX8ht4sOuM36eBNq4KSGOnwprZwb+j4hpLSaTl+3F/Fv98gkIk9EOmjL37b9CD8byKziQ7tUsETGKioZ05NPCpHt8rFVW7wLDZU1ImC2phsk3ZpDWgz/H+8T6I5jTs6n8nUBvOUJQISFTyFyLOA1qwvEvdTK5Bxn3FftGIvJFZOA3uIXRE8C1ZgZw9HvIgkVQyOijyLrmAxIN0QbB55FsKwpQjxfWdT9oIoiseYVKMrnSfj7p0+VUhS9kLIBo9CzmsTFTwLY19IkWyXDdnZznZ2K3s9PYuNOMJoG0IW5MZsiDBrgwVdKHWszqMSbxtTojhCG4o4HpkZPN1c++cZsK4H7iQlGqbIAUd2I1kBaJdViJclacqeg7xNo1JsuN+SwNejEmszKcIxXDvjc4l3IAzYvh/ObJl55CCMYY8mSwfbu70UqWSTpDzaWv4+Imrx5fBEw/W+lHlPctBV4tsOAGZSQDVtIOydFAz/JuV/ZyYZlFyfqES+PkyQP8n4zSul10ToiwTpquY+iIdFXNrty77dNbOTHFgr2CLl4KmMS5Zy5uRSMjmhenR9SuhnYRz6QkNVGdZHLk5QZ+hKDbIW1bGLWZSErgCs0kjnKapTCtdZq+H9RIRulqHdT5Hmmc/kNQcpVm936KepXwbVRwn0OtvwKOpDDd0o6HWO+iioqNvkyxizGFSdmuHf422A53wcoD2FjQoID7FkQ4RDMqoqHLBJu99QnnvRYz6m4jSqLBWsG9LOVWDG2QFjmMS2d+eXm7FtQY08oK7is22ZQl8Yk2L9UCf/ByfyS9JfefDleSgKToX2JvBceI1Tx9/hJhFVFDxZdia0q+89Yxi1oQ26dlkaIlAdMUW3HcsfbGOM7vowFlHWyU/OWcpLsUTBHsy8TKDVBCpyqLLw7fJtabvBMkrXhtGa0WmtJlDioNNtXEkKUNNBV5GCWppwKhbA+s1ZyBq0PUyR8fo/qujtyxTp0SGSJXjcwBke+U1S832j6h7aTV6yjU9ISCrLSmGLaAxj9m3fWAIstxGnTjagMUjmKVSUtUnWKVSzGenXjcLyTY3ySRCNZkKLzVPdZK/PZBGnFc3m3xupy7YDTM8K6xIpjmpEfIm1/K5aD1KiW4/ppAMBhDLuroO9vHaK4QFjIJDl+MGJU5umaT1Hhe0N1HzELuXSsbbr/KdvR9cBi5C+9OlZYwfrSrNcsVbrchWwE03DE4DICTj4t/BQsHyeO26U1pSUJgCkZ6tQZBaPz3rtJR7HFkO4pd/qSoXS7roGa74WzF4mqdO+h53PuZjOTSxKK8Dpocb8HeXjNeh6WCpOWoHWLUPn49QpOC2b9CEVTdcL6LYDuh7lqva4EmstdJpCTUtYt00ZA3WlYC6vsP9hx+xUAGAMdJqA5itMHjLmJblYIVnwo6ZanoL6TMFkCtlli/R8hf0PszBOWwiE07MF9CIDrhf+HsynBQ5+cMCSk84KsASlFs/PyTjqdY7yiUL6ZI6pTGzWQrU/C6nT5zFlaQ074jsYHEPo6pV7IJycn4CtcH29nSlLs5iR1HVgWYGKHLSIKPGBAJqKI9URaIoWiwFQKgZT+fasVsyZoJqgd+HazscfRcHzjI8j7v9qxd5F04Lc8oQishtY68ForoMBFDU4bj7Y3tyZILss2JWPQWAAaDF8WP13EYhM+m1nE4818QA1AYUJNsVR6MXAMrM/Aa00qA6eAABUdwvM5tPBea0m9NMcadsxCOxZGEe7N0F3UHLBHwAqCz523cFMcmiBZlvLy5CTKVKHNTF7U0AT6CLB9TsJ8jMH0uoNTKaRAli9KaAsoJ/weVdv8GeXE/qCUE4UptZ6ScHZ75ZbPYvuaIJ2L8XksvQvsfqNCa7eBU6+F/q8vluiADZSpvVRAqsJ085g7cBisID5/u3DlrsA5852trNb2WvpWXwhJkuOW+bcN4rAPu2Y8f9vOs/z/n9bGxeCbcF48H4jr8TJGW5lIZNj+E/41ONtjj1oz01tHR9iXAg1OM7231C/ZX9DHEe4AY9B2/or27dhSeRc1vqvyYTjeOxEVBzGWAg5Bm9TPWCMdb+Njn0jxiUcN/TNgvoRnkOOF7XNn5ekX/F4bT/dNvtyTxafBtwaKTUxboE28Qhjc/TqA9zDNsyHVhjjHkgrmFSWPxRQhopRd7GRjvLtPu8etX0b8s7RyPv/+jabzTaOKOKlmtWmOlIeC/gGq2OchWAh1PB8WgWcwE3jIX+D19NjomOrR3GQhIWZuE5GkJ8qoDSj8e0L8mt0b8rhCpTa+M6mGiZR0BSuwwaFv4yRIpgkoFDlWLY36CbuOwCkLEzG4yLYCePiE0BQNe9zoJsQuoK/6ybR2Gy5tjZheDiIfBDc5ArdzMCkoV9doWDScL5ePnMC9RZWu+MAII0XWlu8EnwWRPQUwBLA2fP2/ZLZHez6/LNgr3Kfv2qtPb3Njq/EZAEARPTPrLXf/mm34ydpuz7/bNiXpc+7AOfOdrazW9lustjZznZ2K3uVJovf/Gk34Kdguz7/bNiXos+vTMxiZzvb2attr5JnsbOd7ewVtt1ksbOd7exWtpssdraznd3KdpPFzna2s1vZbrLY2c52div7l2rRvx1AsB4bAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.15848588943481 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-08, 'kernel_type': 'untiln'} is: \n",
+      "[[1.10500094e+03 2.10000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.10000000e+02 5.64000351e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.10500094e+03 ... 1.12100094e+03\n",
+      "  1.12100094e+03 1.12100094e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.12100094e+03 ... 6.44405064e+05\n",
+      "  6.26345244e+05 6.76893463e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 1.12100094e+03 ... 6.26345244e+05\n",
+      "  6.10904152e+05 6.57929252e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 1.12100094e+03 ... 6.76893463e+05\n",
+      "  6.57929252e+05 7.23363194e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.2879912853241 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-07, 'kernel_type': 'untiln'} is: \n",
+      "[[1.10500940e+03 2.10000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.10000000e+02 5.64003511e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.10500940e+03 ... 1.12100940e+03\n",
+      "  1.12100940e+03 1.12100940e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.12100940e+03 ... 6.44477646e+05\n",
+      "  6.26419449e+05 6.76987636e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 1.12100940e+03 ... 6.26419449e+05\n",
+      "  6.10986530e+05 6.58039529e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 1.12100940e+03 ... 6.76987636e+05\n",
+      "  6.58039529e+05 7.23580978e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.41571521759033 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-06, 'kernel_type': 'untiln'} is: \n",
+      "[[1.10509397e+03 2.10000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.10000000e+02 5.64035113e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.10509397e+03 ... 1.12109397e+03\n",
+      "  1.12109397e+03 1.12109397e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.12109397e+03 ... 6.45204387e+05\n",
+      "  6.27162377e+05 6.77929851e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 1.12109397e+03 ... 6.27162377e+05\n",
+      "  6.11811391e+05 6.59143187e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 1.12109397e+03 ... 6.77929851e+05\n",
+      "  6.59143187e+05 7.25762294e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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v3Pf5G8TqOQBHHtS975Nexm2goBMAUDB7mRlk9mfmDXIVhR9z79PxOAUPYyAz8Dyw6qBzF0lpOY0f5oqZQcxx3ni1ln2JUpCzD7/7Yh51TjrjdvVh/IEAZ9SnN3qqLJZZUJE8A20bF2ZetyDq8v10kfMMtB1osQrjDHB1kJPFrg8LpH6/buFmC3DbJZcGwZXUhbkPi2XYl7suYxdEeY9eIHd/sVCezH0ti8gdGW6qqgIRJ+KWTkEsQPTr41jO4P77kEnJH7qYJbAPdFWlN3HvMyuAmlounBKeVFW8sQgmG4I+v9HMGFRVWUUhBz25SxZTfADKLInqX9cg6GKQqjlRVfI2B4CmBsJCEaP7PizW5m2vepOTc01WnLntVB9rWSAtHjGKzxR1pdFIFgrvs/OlyTiNb7I06CUmRJVLCwsTqKnlTb9IoKrMskhHiJZFeQ68XoPvHYMsCU1Tg4BkRRDFNz1Nwlu9DuN4DwbAJ0fy/emZzL+9/iS6YhSyMXrdx2P4B8eg83kqXxmF+agCvULI+lFTy6IV9osy3/25OcQsDnKQg+wkxLtkDm5Z7tMb/FP0lwd/u7SLuolfXJtWLxu3vh6t3hUDpxpDADBMqwfgVqHPu+q9BQ6t8wYgmvM70erdtG5WTOaL7Fs1ZG+ii3HVOS15OXbi4HBpTtjHmFL82dDqbdVtKNh90bgD9+6f8Ndxyk92mthX1w25CGy1geHXEmPa/G6bDNDKA8gAQ9EEtoSvO9el7BDNttuGhSG6Jup3ayyDq2x73mBnQtpP5Qpp5YwYRXXTm9rGIojAvc/5NgNIKgZTu07G9QyYYF0KOhaANysDaM6oW0Y8k0BZEfhkwG/wXvz9ML8uLBYxVuMcEFyIjaZAG5MzTNhbnRzHwCecuEsCusu5SHV+AKSAcV2D12u4eyey7Wodz4vMefuB1Ck1DdzRkbzQ4hgeQwaAAtJeT8LeIrc+9FvYIH1UK2AfnEX5tcUA9H02/l4V1ENEskC60TP2pTY+CF6RkSU7dfbmuj1rcIPoNo7Vgzgtxsz9hl4SyOxBBiW5gUCVQ10pdZoWbWMN2PENgzUsilEDwkB6qM0CeF3INpdBUs9b7luf4kB9Lwtb20owPCwSmq1hmHt/m34hYHlh35CIs7j+PfPqLha3LVsXlAJkdBPHH6KcK4qj2AYeYR60LX06t/NZ7Pl9KRvm7tCid8ECWpjFg6Ay3W8XPg8uFq9izHz8Pv1v9fApAE4R5c+ync0qXcpFMvzQ+uVqczHfxu6t2RRd2NRaWQwVroXz9W64fWHfg2fzwX3MgOY33txkj1v8EOA8yEEOspPcfctiH7LccpvB75ObICb0NfQqZUucRIbVVG7un0eTe8N9uZ2YxS46wpj7ZSMdqys582YcOE7GK7JTk6EB9KeNI2yJr6AvtlfdQoFcCiReLWbhJuM8EK7xiKEUt15Xja9o7CekVCNozAS3yREYpnhQYxajWor6yiC8un3W1Q24kdczZqFyqWm4gymrYm+8rWavMbEH0YhbYMw7cXAWRKnmAY61EdFUvGCVUlzJNqhw/BubrozFpFgd9OYaInMlirvK3ylWsWFqMw/rbuaeTewjw7Bgc9HU87C6aRMfkTQWVerO5dWiYafwv+1JStK2wHBwxm5i9WgwVmAbGdlFL9PXSwyD1KXU/qtAym4hZIq0NkUBXAOZPPYpK0hVlZ9T3+eAsHi9tWI1xVJoPBYEZ7aI7R47evUXi+vKtgWifNNGevuC2HbwmPmNIhcI2fFoNNoMcpkScl6vM8h5zCAo/FnL3ks4e/hsS74jKCvQvatkN5GOlRVaFaXrmlos0ZV63AKCDSAbLwaEh6LxhqUpWiPmmHGxCKXwepMr/Jt75KAsRYSaBdJNJxvt/yhklRRCbd/C1DQx06B6UQAzWVCcpoCpqmLgNIH3Orj798GzmR1Uvp9O0nXQUnEFsWnas+vkXjgSUJZ/+nQwOErjsZyHAWXRdAr38AHw2JSoK1xe7xeX5jVaNRYMeLp7JOL1XSwuc0/i6pxuYHtDXvRmzwuY+vymV1FsfsFnEY9PLkNVxu/NtuzVnOxzfYOZrdmJDIVaoiOrCvAmjdenNzh7l58HEBGUACKKUo8bv2+aaHXZ8VjHHLK+dD70s45V9PpUBGm0PqpKoMvEab6qCuSKTuUAMJ1k8HMVqkeSfq6qfLEYjeQ3y80R6k6y45LsG48T9JRp86DjKaC1QT7pmRCc61SjoTgP5+Q7TZUeS20QTk8HIdhUjwBN5eu1Gjfge0eg56dpw/FYbAUDAZD963ifkm3huEdW6hDgPMhBDrKTvPIIzhuVm2gyNBSI27VvSPnbi+obMuReDVXrDv09NNZt9A25qER8o5huC3p0iJB2I2ZRuKI23mRjFsWxsqBsOK6Nb5TtB2Erem3Mwp5nCGJy32fu6aAbN9Q3BGLleVOXMtS1zB5DXJSkwx+3f4hT//iOIzivK3pz2ge5/B5IdHKBBs+Wng8f12WxAW47uKaGX+U3LzXNBpGMLSH3y1V2g7hQou7n86RPu076W31dlZV8xzGqKoMNcxiD2y4bV07DBPKg8Q0viEAN7PaFGxK+d0dHSU/rhgT/e3DadD6QfGZqmkQGY+MYWn4ORIRjVqAWir1KN4TunYDPTexAv69HkmWoqqi3ngfVI/SnQgvgJuNUpDZuIlAK6pYEWjvViyoHXq6kRP3Z87AtR3cnQ2Ve4IbwcgV6cE+m/IOPNhceAO7ePSkkM/rTdAK88yaq736YNiyDmNYNmU7Az05TMRsz6NPdafU+W5bFTUppFeySvr1py2Lo+KVlse34Q4HTIR3L74DbsSy2HTtmaQYyN+UQ17UszPzt0utUU5l2IUzzcLOWxRDvKoWXw66WxVCv030si0PM4i7LUPp023ZDf79IlrB95LaZwPaVV1GfK+p0HYayO+eG7NVkCMjeaDfaZMj+bX++qMlQOeY+GJHLdIrHuQRYtGUsqpvt1bobel8BqTZ4rtshzht/Zwzqw+MP3hcX6Wrh98V4OZaj2Ccclz3yNHK5qbkHLrssvLpkTgORUdlk6LL2hZmRBo25bELAd5FXbMk8yEEO8qrKnbMsIuBkm+8NbI0j2JU+476ABNtsCbFfrXJ/WcdCCLAZrk4bqItclkdHQndm/FUajWIA0i+WeYBT+0aEnLmbTuWYhZ+pnJ9UuawHhpzTKJZgAyFYGvaPfUmUiasMcIa3Y/XwQaxitCCqLMB5/x786VmYt8S/wW2XvWWt7+wm4xTgDPtQVSVOSw0AhrnU4K2bTuAXS3DXwh0fp226LgUe9Zo+uA8+O9uMCxCBV2uBds8WqpwEDZsa/smzOH8xwFlwcKKqJOg5X8RrCQD9+QzVj/07wMdP4nFpNAIvl6CHwqvJi6Vs7z2gQK2RsHnRqgXP5uC335D9v/XnaVw7fw/ugeoa/vlpvNdGn3sP3Q++g+rffJDmYDKWIGwsFwhz0dTCGLZYRL5XMIM+Nvwpl8idWyy2yra03xYza5B7cpcq0xCFT3h/DlmPcmHqNun8u7xsWh8e9oHO3XJwtnlGIqXspFqVu80ybW67zLBnzxF6HG/AwswuA3O8XG1ycHrOeBJ4nhrdwHYeGKo9sOcTIeJd/L9EoTJzdi18IOsFG8p7NvrY63g+S9sU7iF3XY42hSyQZFsUrNfx2vJAkyH0fXopGL3pyfMsyxLBX6HxEK/bpE/bxm3icdYt3FN5SXi9tyz/KjmZ82qddATAszlGHz3Pe61qRkoXCR13KQhl4fLUen2OXJ27yN1cLG4ig1OWTG8ppd5p/4F9sofAlJ3rxZGHqihR37EkfkNXGwOwN7j5nX25eKrFVJaO2xoMhXsXBMUKOWafVzhv411gD3CK0kdO0bLeI/yW8WRYglqzKMZDO6R5Cw+SQrzlNMOi4lmQjyUtABXZA/Xn+9wyIicLa0kwDJaeHpkVwoGgWLMUfQ92LpAYGcRqZEHrgPDAW6IcO3/cdiDvM514vQbmi4JY2McOaDI/Ls2jkjFnpMCHmMWNSEp37Zh1GNx3D8assofFtn4TN9ADYlfJxoq9KVzUNet9YfUm0z/EpCO39vrYRwrGrqxfBiD66TXTh2VbnxN3QZ+Tq+pDA/pctm9xj9m2kFvnK7RTgP2nOlw05hXlsFgc5CAH2UnuphtyGeBpl0NYn1GrQS0HQWbOm8pUKA+CNv1ppQK0a7NtaTSKPS9s018ajSLvY3x7dB3ceAzW+AeQApjkANgmQ2H8mow5rhWadR5wXCxTk6EYTC2qTosmQzQZJ7+691KwRiSFUxrwPJqK+VulQB8BOb1cOd9aKQrkPKMDTYZQNBlCiFtocDhW9LKgJfXKu+MjCUAW1gsBsco3VqV6J8HgsWnyXFPWCsDGmLY1GeK+Bx49gLNuQ0BmuvuCymQNluv86jZEQNcDiwXwxkP5fbFMLo3honDTCTAagUyTITo+hn/3DaExjPCAWhCjseOazmsF9h60WMYgKzwD3QuqOiWibwM4gyRuO2b+ChG9AeDvAfgigG8D+DlmfrrtGFcbOFRilp9z5dJFH/LLCmISGo1k21BNmHfuyo9P9ShfLOrRRm/TCLs2ASQajWIpMto2EZ7MJEpOABA6kqGuAe11wYYYt0MkxY1H1gerqdPxAZB2zGYfsyTe9ukwfT/iYnE0BVbhBgqBOaoqucG0w/v9e/FBshWMtFoNQpXJkZyrPpSxs1iTro2t1FwuzcJ0JDGAxSJlUSYTGb/rpBIzCL/5MLEz2JfHaATMSSDPq0QuQ0dTmfczzew0ApfWTvUWP1HLtYuLQphPWq3Qfu4hmtZkMEYVUC3g37wvQ50twKFPSH8/dJ6rK3Dl4OYtqmcV1p+TbetPnqQH387hvXvgSQO3btN1f3gPsy/dw71nqYM7H09BZ3PRgVmyLgD8ZCx9Xs5q8L2jpOvpi+2i/peY+cvM/JXw9y8D+Doz/zCAr4e/b19eNZTdkJT+s5Gy5yUp9PgWfM+d5TYRnte5XjZGYv+VvwMpvnKRuBue5x3mjYmgVfggCn+b/cpzuGicrUWFN3v9bsMN+SqAnwmffxPAPwDwt250hKFMxADdWfZ/eQjbJ5RcwgeUqST2+aQzS/oq1gpwIGzNx/GLpUSxrXm6XEUTn7sOvEhZDX92Hiwhg/MIerLnzCTm3oPn883U6WIZmbXjviFlqak9tmkz9mDTjQsA+Plp3lYRALsOZAvEPn0S054U55FDtN8bV07VY5kPTfktONLKRZM6tgdY5+0XlAmKObkANs1cVelN/L1O5k1JbMJ5smYCbOrUM/zZOWi1Tins9Vosj4H2hSAnLoLOg16fvkfzzY/gtZDMCVUfr9vEch6Id+AZ7qlYR5W6Mczg1QrjkPLVVLHS7enc+sdPYiFbvIYff4p7XZ+K2ADg9Bw+ZEOkLYKS34gl6dctSK3XkgX9ErnuYsEA/oikQej/wsy/BuBdZlaUyIcA3r3mGFeTS9yQFLMIfwefOvr26lZsFDZR1peC16E13zpdWACp2tOkR6lyyfVYcF523AgUHYa1iX2XSG4sSY0jEI3iAhLTjiUoK8RguO2yseS0hPwmgbKC2T8ZpxvIVp3WJuZwfCSNkYmSD+45POh+mLzFkueEuI0jgi/IbyLATUFZ4zG8Z3AAO+k2UCp9kzWg+yfAKUJ2JHGDEqVKzKzZcdOI/lpBWzWXgrLs+QBA33bwj+7H/q/ym1DfUYhZYKGNij34WN2Q4PauW5Bz8G/ItnR6Jguhc+leInGZqK7lmmql7vEx2vceoJ4vYspVzmeZGL/UKhk3MT5iQVlYvKCYBYCfZub3iegdAH+fiP6l/ZGZmbZ0GiairwH4GgBMcDS0yUEOcpBXSK61WDDz++H/j4nodwH8JICPiOhzzPwBEX0OwMdb9v01AL8GSIn6dfQIB9xwF7L/y80L0JQvG7UAwaooG7gkszb+PVBWzOv1JiK06ySYGca1bgQv0tsh6mdM4Qxx2vfyRi5AWbz2KYCp+4SsgVcvIhRjMVPQPXc5/Gyx6dL1OdDHPz+Vt2RvoPAB/GTLrdEjZnN43SZ3Sdsa9qmJU6T7i13TZVs/T4V/EYZevPFjs+P2ScxoJc5RTpwP6F6qAAAgAElEQVQZBhPCkKApzLX0bQdyAaGpegYhRwHdGiwwp1wXPejDTzIeDQ4cHNEljK6fB8J2GniWe28tzYYQ7htmCW4qaMsB/PwsMZHr3Dx9htp7eNM7hOcL6eAeQGARlFVV8n3vQbbXSLd7UeCVFwsiOgbgmPksfP4rAP4bAL8P4OcB/Er4//euOsb2wSXtBwRzvesG+k1e7IZorUTkkpxOs+xA/7xNrejiDUKQ7ttN6iC2WMBNp/BKihLGcifH4HWbPeRuPJboO5H4y0rSu1jAvfkG4D36Tz6VbY+O5GYej8HrFm5iSHPGYzibBjRpRpsN8aenYlavVnBKCKuwZM2GaJYkEM66Nx7GTu6WZ5PGiXcTjx4Az85Avk8mbYBC+/PZJp8oqjAfJj0bAriR6NZkQ9hmQ46PwbOZzPP9k7RNSK9SXcc59289Eti0c5INAKQFIDN4vpTUZ/DvyTm4Rw/BJ0eg74rX7Koqy4ZgIBvCynep8/b0KVY//kVMvvlJ3JSbGu5sBv+u1HvQ+SLGVnzIhvTjEZgAt+5RPZ1h9QOP5LD/5N9KFsYZkFVVSd3LpEH10afxutMXPofnP/4W7v/ZJ+mFMRnDnc/BowrkUzaEpw1o3cGdzfNsyLdfTG3IuwB+N6zUIwB/h5n/kIj+FMDvENEvAPgOgJ+7xhjbRSfnOl3Dwv6Jpr3wt6957Hg8Dd6FNwaHGzirhwhQ4MzaYA43exHQvQm4+0Wi40XfWeswjCXjAzzdWjz6JrRBVHs8C2V2wB4s9PnxdF6Zwb6wgvRvG7fTOgufW0KRkeua80lBl0wHTt+RZ7Arxggvsriv/hwpFFLMgvt+61SRB8haeGHcdNyLLey9zvNVZ8oa7KI+xIMJxLfkVrah7MA2TbXJBUkhqGdZiABg507b5fGjrn7zO2jAkaPFAyAG5MqO2ns1aN5XSratQkcgLLDB4ip7slKdKmvRtpG+fqjAbO9zGGiAtNETFiF4bfp0cNeGgDFHev6hYrSrzqlSMsa/hxi7RMF0fxVcn5legFx703BokDPDKeN44b6a42cycO/u00X9DoATDnKQg7wK8urCvS9i4t5oWRd6VezhNpT8iDQah1RcIuIFUbZCx14ezgTQAr9EyYzlptMNNGPsS0EEv1plkHN3dCQmqKZOA/+DpgktH4XyaWRYkXBOtoGMX64S3FvjIxkydRPu7U5O8oAcEAOGaoW6oyl4vpD+GmpFcAh42jdqLOhycNMEF9c54L7faFYUeTNMHIYD9kDfvvo23UidHh8nuLdJnUL1Mi0BmRl0NIULHBHxPA3cO0uzboF7+/kc7i/8APCpafRT18JncWIIe8PYdDTJzhfeg2cL8OfelH3f/zi1H6wTLYHCvb2Be1dvvwn/fW/Dfe+ThERuZOwYw7Pzum4lDmPS6/R09yXg1V0sLpJtZeRZL86L3YXSTPTrVhYGeyyXTMZ84x62CdEQhV7Gcq0l6gGirIAu9l0cS7Mh0e0KjNyJiMZHXWKEv8zAdG0OO2fBJ8SMTfguHDDukx1DA7VW996D0SbI+fM2YRaKbAgRJXdQYx6OEs+ETA4QFsy4v7oChZ6WNu7SbEgIKMfmQWHeONThMHMM9KLr5CE2nBq8Xm9lJ2dAMDCG+yLq+dEncREB0oIXsReqH3MGLecAx+f1OsUklKqgpmyx7k/PE2GvBnSfPYfruowLhWecQF3hegAAW3fQcG/s43q9uovFVWIpe3BSWP87Nvi1+5ngneV1kA/Gr9fIeekP2i5llhG6EmhxRPUBst14DGJOGYimSQ+YJcXxDKq2+MWmPSIQbuihNoXFPuEH+TOAkuIcADErpHpIM95WbkR9QxLFbmDxQdIbOzzAETikbzvbHsAU22UITu3J4ftkRShq0wd0rS7q04k80C5xRRCRsERpcNk85NTUGSFOBNttQ3DWo7S/ZUo7PpYgo24arBM6CpmidciseU41JZWLwW4CQCeyiPHjlXzXdmm++h5uMpYxDYLTTSegB/eBJ09jqwFUlQC9iGQBKooYdYGKup7vXhvy6i4Wu8oQxfsuuxU3QgwMKUaZQp7aBo8sgYy1XAYCR0MFVTDkK+w5th8EEHEI8UKWroBdyPptPUV9/mZkhpLcJFzJ5j6Z3l2HEl+AHrE6F4BAxBULYReWYPZmdpi+8SwMPZK+JILg2K6w0JPXaYzUzySR5lh4Pvez9KCbAHOs3mWf+nZALZXEHJXhZzZE59yQ8gQ9/bPnueVUtTkLWJwLjrD5SIYTXhzu2WnSgVmg6RZnsVxtWhazBZzn7JpHoh91uaxV3CuTmSUSfgE4ixclg1FlIN2k2U2Rl4lfKLYPBBsux+gytACX2A1DVXaJZTH05o+NdwGBapsu2xZHAWC4iVD8XN2qZQE7rm1YrDGL8TiAh8g0B0oP20bNinJ96tha9u72syyi/63QaY0xqcUznYZy8Jz8Resi4EbZQ01NnXUTowpXsiwsJ2kczzmxdIC8/kKzXabqmVYr0HGwLLQ2xOdW7lbL4s1HwONU1E1K6afWlj4f9Qhou2tZFodsyEEOcpCd5JXHWWx0zLpIbAR8n/MaYgjHlrjAvsfdeVuXvcnlK9p4S19Jj33kIp2tNVbqm8Vlquy7QevQdgK7jm5bMCwZ/kJdKJP9Ubh91uXrinMayXisTpfFzVQfxasYvfT37JhDc0XJssswFfb6WBk4v31wFq+8GzIol7UC2EXswkJOKgVNqklSpw4gzi5gTNNe5oZoQyMLRtIAJyAuhglw0ngMm7WI1Y8Vgjmc3Aga1YhIv2zQLW4I7+CGBP2VsUu+KwKcuktTpwh8IAtSNCT3hqhHwz/WvAdSkFfLz7FjgNMwZcUApy1Rn04k9ezSPMcSdb1HND7BBDdtJB0aep3G67+nG1K9925Kv+q1W61yN0RjCBrgVHIaZmC1kkAlAP9pqm9BF+DeRIAbb5SoVw/uA2+9ATx+lu7RqkrB53Dtor7XdENe/cVin9V+qAHy0MICkw3pIRPtRlmjJvhe0o6ZDhJ9p1GdINxrP9wYuXJCgQeYG58S3mE+lzJzAN6z1CUgr91QKrisAXCAf1PTRF84YUUMejIcV+n54ri2BN7iN1ZijVHTmNL38CATxRQfALnh9aGkdDNyKPYq07EA4EYjcAwKS3DPTSfw0L4hmiGpM7p6Nx7DA+DWbGPK5bPYxHSa4gN2oWsmkWKwNylONw41KopTGY/jsbPzVf0MulZriLxn8L0jkNLxMwsOp+9BoRcMz5eyOACpb0gl9Su0WElG7ighODXFrsIA3KNHoFEF731iKZtO0T86gXv6HPoyibU6Sqeni+a4kXM9n720EvWXI3YBuSL2vTQ9Y18LP3Bs+3cAE2WZDMXmFxH4jNI+jKF/ZYQ27FNRmNk2ZjFsNkN1b/Noe0mQo8flPvxWALh0kSxh9H612kgZp9qQMN75LPX+sG9fzRYMXIssy6JjLrE5lqHuB5A6qOtn3UYzIsYN4ep8Yx7lrdwKEZDLOUL9apWqXAFJcSoM3Bdzo8HbuBj5tFA9eR6bD+k8ctfBnWrfkHWs/owkQiHtzOtWXgpPEvnPkNvG2jDK6OTPZ6g+HGUYDynoS31K4rjLpXRhXyzzAPYefUMOAc6DHOQgO8ndtCx2kX2DVdvo+bZsq+xU+b7JuohWRaaHgUPbY9i3dnnMbSrY7ZUa0HOOO/CmkdFGsCt3kaIMpj5dav4DRNZywOBS4jkPz7u1suJ59wnHonpGT8VYQLpv3M+0bcwaNS1XG/PIcvBkDVr9+qKhEYdgpw8MUxZjA96w8NQl5Pkix9WEeAcb6r2IpNSUqGn+w30vbOkYuB46lELg7e9tK/SKdmy1ukrUccC/bCA293hODpbFHZUMgm4qGQc23HaAuM+NNP65CTHU95aE96XoVzYv0n61ZUOilzBvVJkA7j5SVRvE0PvI62tZXFSIBpiLnIqwbCBxqN5D9yNHWTQ8g3brZhHsY2HAqa8HZ42RE7IwEc6EXiRK9GPBU+RSfw3oG5byviRA6k1ikKElB2cCB4Vxx+MUU9Bz0uNqY+SjoxiItZF16bM5bBFl4KfacGnGgGvQOfQn4WCxRE5O3+X7hRhClqW5dxKZqKIoge4ycHDaUvIQ0PTnPh5X06A2UAzmBJfW2hlTEOjefJRIcz3H4LS7ZwrJlGNUEaTOxf4ivFyBHoQeI+v1IPrXHR1JS4PZLIHQTo6Bd9+Cs9tPJ9IbROdFF7m6lrn1nHGJxrYPO8jdXCy2pU7t4hDTnMNFZbaDefzbpAi5XaeAZYkW1YcHiJWhZQWoRvHtImL7elBoLAQAvu8Tw1VgjtJeJJqus8S6GWcEEF2PrC8JIHwStXTPVmLdSPVWVSD06Tx0Ho6OYr8MtttqPw8A9PC+9CQhyisYVyv4vh8M0MX5CJ8BSGZAYfa66Gh/kjbc5EfTmJbN9us6YRY3qWK8+VDqL7KBUwYKdZP1AqGjI5kXrSRt6tiThGrDK8JeGvxMp8llGY/l/FcrtJ9/A7UlBhpVwGwB/5awX7nzuRD0AuhPQiZi5OCbCtX5Cu75DO3nhVVr9OQZhpZbun8CbmoJyOo5PHqA2Zce4OS56Rty7wh0VkemMH1x8HQMJoIL20Rdn73uVacHGZYL+pJkEnqUvnw4HnJ8zAvs4bqXqEv0quh3VVeiNCL2PM4r4Kge5CAHuQvy6sO9ryrbQFlAjonQ35QspEA0boiCXSKoq897nerwgcatLESL7kTb5cdQ0FRsrxdQoSVCNXxWFCdg4hC2UA3BjdB4io2xGIi2JQGKYK+N0nzK4jJKSAMgK/HeXg0bUI32ePpdBFdRPIeItQBisx1L4Rf3K3AW7niaYw6gOItECZABrQLxso+9TkdxfC3DB5AwFZR4OahyEffgHj4An53bQeX74BJmhV0K7NLyfsVZBACXf/xk2I07OtooEkNVwT18IA2I4jnVGc4ijls50GQCP5tncab/8/nv4nn3yWsM995VFJY92Au1CHBWlYQ4ItZ+eLHIYMmABIwGep0KbLhkyspjHbYJc/x+ZRCW8WEYCHBWLsGpnY/fIfO1OTb3ieelAVpy4XzTwsHe5c2AkAc44/dNYwKxBl4ezmXQvLXzoedd1wCv4/lqrQMzR24MGo2kqY7tdFbXINfnyFZA4ghlcFCh3wEani0WgSSHDMQ+okPH4xj/iIxc5Exf2SZCzcn0gdUAJ4A8kLgtwGm5OOI8DSy2k7G8QPo+7TNuwPePQQZqHvUeCHDyyRGobWN/WngPnO3uirzei4XyOQz+lkO59WFXiPbWQ0akYQpoKtoyQ3AqItS8ZaXs3ef7BR1KQtbE9eA3zyMgL/OcfEBP9sV2wAZ2gntAa17YZFTAXkqky+K1QASk33ub2y9RpNtwFjof+lmPW1hH7FLrPQB52bvPx+SSXfz56SDzEyvOwnX59Vit8nYNAWYeO5Ip94Qidw0extbA+MdPE7kuEHEW3pxDxFmo5VPgLLJWhwMYG55p+0nTNe98BmLOWbrW60GcBVUVqPfg2Ty3mPZAcN7NxWKXbEjctrAsCrYmtm8Ka64rL4LZJ+vjoDfKeriLumvqTSIZ017Qz5M56NeIJmt/ehr1GaoN4a4LfJDNBoSbRqPUThCAD/UQ0h4x5xyVeSGTDRH93dFRWkAiz4NLKUxAelg8l/4cmWXRdaHv6+YNqPOhegLytowPWVH3ES2LppZtTH0LBa4PMtcLANyD+2DDKyFfUoQ5U1WhN6lVd3QE2F4iTQ2aBOtkPE4kPsGyoLoR2HXQE1UFns1BX3gP9MmTuK32HKFHD+Sry2pDZgvgrYei03feH6T2o3v3QtHbWUydukcP0X/hbbhvvp+2m04lvTtQG8JNLaxcWocCAN878Fkc5CAHuWF5fQOcl8k2DIXKhYCuy0vUY8A0w35QbtGYY2z0RyktpjI4O8RXcAGPwwbvhNknngfyQKQtzc9Yzi3AquzbcVFguOzNMtDbwnKjZtsUPTd0Gzt+ZAYvJbohBWP3aCS/mSbYkYt1AGiXfRdSqbxew52cDLohMWht3JAUSyjckLCtn80HLTNqmtisWefGNTXo+CiV2AMhljXshmjg1cZ5/njxv+F5/+lOgYuDZbGvXEgO86rk4V38FzMIW2DKG9+/JClh5y8Dhp7xjuiCHKkUN/UgerH6xXGveM2yYPAV5G7GLPaRy2DfcbvyDXwBi5N5CJlDbxEuVnKFU9vAJLk8i2KOEb+PlsWWLI4eKmRv5AA+6WTw/9GyIDY3dZ8/AOXNHpCdcljzJjffC09nypREndCDy2KtjflID6WFkMdFonJyDI1ZBLi6JIHy1KlmgeIYkzF4UVgqlo+zJLSpCi5TzTIFeHc6jyoymac0tV7LVlCmGVGOAN5i5uOS1CnW68gETovFcPJuNAq6+mR51IIIJhvgbGo55kDqFKOR8GyYXi9YHrIhSXZ1s3atOg2ZCVsxGrMANhvyIqpOCyLfWB1qv1NyH7uYGdq1jRvzRVadZgHg4CYoz8bAWCUfxu1UnSLLIsXjkINWmQJhHddsx4usOjVzQ3tWnaL3ea8XYOv1GpLXd7HYJUsCYP9CshB3UGZu9qF+o2DKuuVCMptd2CgkU1m3iSnLFJJZnMUGU9aLLCQbjWLH9rKQLMMzhOKqWy8kC0xj3Pd5pkYLyfQ4qkNVwZ/PXlwhWeXk/DSjt28h2bgBn57n+I/17m7UIWZxkIMcZCe5c9mQrRHvjQ2t2R1W4vEY2lX7yuzYNqofx3Ipm1CHCPg2y+SmpAymDmU7iiwGgM1sRTiOG4+lU/u+jNvXkS0BwsHO6EUm41bEdGm3fU4yFnCbPSMnPKLz+f7307Zs3LbjhPuOmiZlTs7Odo/JAXCTiVxjI3/S/9Hry+69tenQxoabE7gNHbefAkMck8ZvHiCrvRUpGc2HzkvjIhedczgXv26vPzdXkSG04gAL2SWta29elxL16otFTWNX6xd1vQ36dUtc49JDDNTT7CN3brGICDl9A9qCK7vNUMzC5/4qgOgfOuVWCLUV/vw8FYPZsVjiC1kXbePD61jVwwfg5SoVSkGi9Rr15uenEW3pZwu4NwTB13/8iQx1cgJeLDb6U/rVCm48BjVNIqc1BV6Wz8KfnkZaekWIWvbw2IIAgA88GtW778Q6h4TgrBLPBCD086FruNYZKKW9nxniWvPwuZPjrEM8AGA8jgVYMfYxHgOrVYrdHB+DZzP45QrVA4kB0HQKbluBKo9G6UF67224T5/m94ITpCSfz0B1jf7ps/hT9eghMJ3Af/BR0ktjNqNROt8wX3RyLMhV1RNS+OX/4pfRfPvTbFuezcHvSWd0d5r4LPx9uf6+rsAjh+p8jer5DKsfED6L5s++laD/piuZe/dt8LgBPv40wrurH/khnP3YW7j/jz5IwdaTI9D5PPFYBOQoTxtQ50Fn84zPgr5l0JyXyN1bLICNLMCVxEb8Q4EQ9x6EHd4UfZ9xQQzWI6zbPM0FCBlNYCbi3udwbX2zU4qSA/IQbnBrMssNXTJjd11G7qJ6sue8BgRI2Y1S91AvITqabtyrVVpYz+fwqjuZvplquRVvLvYs7Nq6aOsiFL4HkNifEIJ8Suij49paGlolMJNhZHdnMwkmFr1OsXahz4l1xxi8WsfmxLJdKzpxaEycdWv3gKmrIJOhGT1egOe2i7rAvd1pWJgXS9BaHlqnUO2qkoDlugXmC9RPQu1H18W5sCECns1B61YsQH05zBaYfrhM9SY6f/NlTAGTpk7bDuh68HIJKjJCu8ohwHmQgxxkJ7mblsUuclk/kRKjEKyAEly1YbmEN33EFyhGohiHi5w4ALEOLGDG5vHNGwVA+jzUvtAz2BuMgv7W9xvdyilUo5a0fzGWUeISbD8Sz5HVGm0CNPFqjdhfo+ytsU0sM7WxmjZiEl2XWWSCC/BpnvW7vpfx7RjzpbhsSrZr5itag5axuzOdwoDI+wnvwS5vH0hhrM12ll5o80xAm30l8629RNZtSmHqdVW3y3tw28KdybbeVL3aRkkIliqbWAovlxg9X8T0s4zNQLsGd8GC1XnQjnErE3g3/Vl2kdd3sdhHLmLAJglkXe/wiqYrzONSXKHHILv17Uf6IoAIjNjx3OpnziNuy7xJ69cjZGSK+SvP82pKynHssew8G6SsoFbDedj2kfE414S7b2SmRLc4Nzpf9oWii5Tua/6PqFNDAHTh2FXa9jap/17fxWJXUBYl+G5GfgMMx0OIEnMUkMrae2NpAKk03DwoZAvJnCW/CezbdryAuBM0YKGDPsAlIrKqcvi16hnaGAIA97aIy8DPuxTMZGOV6Y1rWwZSXacsgJaWA4JO3LbwWvi0eZhsGbxuR94gSxUAR2nOFW4eSWn0fJsmvcVj4ZY8TLRGbLEY53A0yoh5Y5tGBXv5/HpQU0vcSXWQiZTWg2emf2hdy3wq+MnEDmKJ+iiQ/bQdqOvgQ9n4YDNuAKhFV1oskpXSNOjujTF6PErMYgFUFudKx21qoBMLOALDvL/45VXI3VwsbN1ExuK9uwWQHh6DUgz/Z+MMvckt49V6vdEXEwg3ky/g1HUdbxayjN1dJ6xHzABCdqCqwGgNn0XQt0Nk3Io3iKnZiCxIRjdbAbmV3VsDo9NJCpIqw3Y9En4H/f5oClqtQ2bIoAFRBHtt3YbBLcTahNEo0weQ7AoDINfHv8vKTJqMwW0L0myIjn3/GNS2yeoA4puXeZYeNoglRONGztcuQtOJ6DQaIXuM6sCcru6cXsf5HO1bR2jODat6VQkpzUPJ3rhTJ9kQ5pQNaUbgilAtWlQA2rdk/+YDM0924T86Ak8a0HyRiIHuHWP+uSnuf5i4N/h4Kp81C2KzIW0IWGs2xDPw9HVqjLxNNkrK/fbfBiRLaSqWnzn5lIC8fbReIGzHPXbLhnRd9hYDZD+bjotv6lA6jN6b4jJOdHDk0rEUZm57gNqaiWXR9zL8HlmfdsmGWBYsJyXPWZZFo++e0zz6PsYl4iIYYwAum+9ohfWmi7pmAADptKXbL5cpG6K6rinFQIwJTudzSamORumN2ksGAJoR0oWh72XBaZNlweuQHel7UNXlLwCdayUA0n08Y/RsmbIhjsTyWq1TNmS5AoWu81U4LzdpQhxG4lj100Wc0whRN9Ybz+egtoU3151mC0w/XkWLIc7BchW7tMeFsO2kP67Nhngv++4oh2zIQQ5ykJ3kTloW8Q2vn33h6ylw66ImQwoMWiwkCHdyLKu/lhAreMm6IiHgSQEUBQB9KyzOfcw2yLbu/j2pRrTlyUdT0H0pGMKnT0DHASj1/BR49EAyLQH0446m4OdtKLteRjq+fr0W33k8TkVTpsCLHt6P5+g//lTAW/M56IF8T0ohFwrDIp2fAVy585DzD5gFqmvgaBotiu7738bo/cfiZt07jnNO82VyK3SeicAugLICjySFAiuMG7gnT+VzgMnTyRH4fA4K2QV69BD89Bn8uYcLDNh8L1yrtkvXC8DyS29h/N1nAFHKAhCB6wru2bmAmj74OCn3xkP0D4/hzoSKjyYTcbFC8yKyndHrGv7BiYC+AJkPCA7kyY8/xBu6HTP8uIZ72mD+QwLKGj9ewo/FDVm9KdexmxB8TWhOPaYfLfDkR2VO3n58CszmMu+2Kdrn30F3PEb9LcAHIFv7g2/jg//wCJ+fP4zWQvtogvrxHL4O7kf4v73foFr1qD+dY/2WuiGAPzMEz5fInVwsbDoyK1+2laSXlJwrmlCDkKwPnjH3BZBk+TtDetUgDME+1Abk4/jTs9hkNx5zvkjl1V2XxvQeeHYmjFkaAJ0vQvWigImiSUzBPF2uNoBWfj7PHlbVk9suLkLWxWDPCdGp8umTBLhSotp1KzGKIKP3H0uMI5jW8Xhdl7f+M4E6fz6LwUGcnYtrdnYe0YhUheuxXGZuCPU+IGH7uNhgvU6l5esmImwn32RBao5GKbjYe6ns1DiEzd48fY6q7WK9BC9XEhMIAc7MDakq0HwuTFZAXEi47fDGP30O+l5AcDqCm4zB5zMc/Wt1pVaoQhB89HHoSDZuEhDtfIE32+DmLBZh3qoMQUvvf4y6Fr5Qve71dz7Be5VD9eQ0gvbGz87l5aLZlHA/jepRdEOaZ4nd2y13h6vfycUiq88g8138vaibuPRwHJF8FK0TwV4MLUx76xqzFeZry3HQe5DvQwwg+KMBw6BZj4j/YJ/6WAyITbNl2l4lXWnjNwYpCS9+dj5fIX5hF7aI0xCdbZYFPQ+mBMtOafbvFNBFvD5Em13BNzgbov59xthNzOKzlxwT5f/62QZOy3myKcvOYEqs6DF0DojS+KqvYmVMmT5zIFweGJ88ZzgLjEIrASrGJ8r/ASHTtKnmNrmbi4VyPCC5IVk2ZIeFwvbLADlhHer7xGS0WGQsTbJPJa0CdsmGNDWwlgdWHwqbraC2S64Qs/TR7HvQWUqLxTeDCVSx6kqUFhbLYGV6j2K1StkQZdR2Qc8t2RCaTKAQ7rhYVZVka8Lbi+8dA17YtWka3pSahmvbPK0MCJvYZAyEGCCNm2gFltkQjMch1djHvylaLHJttDaElLU8POz+/hFc10stSMgCkAKylsGdMpYVTSaSGQhWFxHl2RDbsKgOvU71wTTZkPXbx5hoMJNIshbewz84Dtelkoe49/APgts3kXl3bY+KCKu35fuJZjbUqoTcqzSdynFn83jd+eQIs89P8OCT47jY8LSRfqbKJl6ZbMiqlZeizYbsQbV3CHAe5CAH2UnupmVhZNA12NMNKaHU6TADpuwVxJrPmSluzfohWj19W3tOLox+f03y1ct0tX/HmfQmgKwQ9whLF1M6mvf2WL6AFTNLINhd8RziHBbz5lU3n/X8iDow50FwQHx9PYcrzimV51Y27rHXWu8Fz2ACqJc5jF5DSEcTkArKsB1KqicAACAASURBVN1biPvH2F2uE7t83OvI3VwsLotZ7HIINaktn2G5yHgeXox2wVlojYWS5obtyJQfW/+Z1+tsPO59igmwz1F9ARNya1WnJc7CBDEBgEINBvcGAcicKjtps64l+uGABEyJAHQbOAt1ZQarTq1vHoLHbB5Edz6XAKkrer72Xuol7H3jvWAOjDvHzKDFcrjqlBmgRSqdDy4Ke0b9ZJFXfnY9eLmCex4C2IHSD8xwYXwXsCjoetB8ieZxyLy061TzYuNBi4UgPc080myB6Ucr0GIVFxbnvVA2hgDnIM7CXu89qk5f+cVio59G/MEE/ACZGGWpskxYW1bU9IYJoCclhtULMaoDBNw87PbtZC/ker0xTtYGEGmsrKBLF6y+l2wBEAFN6IteEzoeCcCJLVmNvsnXHt4Wp6mezLH5r1oHysJdcmb62WJz4Q3zow+lxhDgOWY44kPrUhAuruOdZDSsvvowxAe1TzEMS6Lr5z4yVMUMlgmgYpVufVqvY5yFbSDQNlo21gMvtX1huA7rNsZ0dJFNU0AxKyN/qw496LsfpUwNAK6kYXKMx9gH8rToFOYZfr2GC9t4bYWpxLuAEO0+PwNVLiMp8k+eom5buXcslL7v5fxtILyq4iJMlqd0D1DWq7tYXEYXZmsQOBQK2fqHXamVit4aWW1F0+S4AXJg3+/s5tg+FBtiGuBq9+4s7QhIt3JFFeq2FQIJ7zA1YGaBWD0HqmcvUDx9tk186nS7xHaG+ubiYFE4lwh+Vus8VRl8Ka03iQ8GAA1Yx2pYXQBt6nmjcY7La060lqVOxMjoe/jZQnT3PjUgbk1gtdI+t20avygfsP1ho54qauGEc6OwWOQuks9duko6u1PTZBkOC4UHz6KOsflQYR1FxGy0SLfc95ratmzmGHC1L5BDgPMgBznITvLqWhaXyRDPxBWDOJm5adCaG42Ny1LrXY85tF+ff2YgM+tjrMC6S3rs26xSL+dVxyKXaj2AVJthuSkUr6IALo2ZFAG/yJGxrxhXbOg4En8QtrMYZ1ELRS0J20Fcddyjk/iQWBeNHSQOZGI3WaBXvwtWlbCCSZ1KPBYgtSsGczM4LrO4bTaWoy6Xqb8BcvzNVeXuLhYql3Tu2u9QhjcilDkP9eO8ccnMflMtqSi8LTfLC5FtbfsQHtahXeLvGHbXrsq5UOoSSvWzl4TGTHQeI+BKskqZbkDY9noPEll4+ZbfgbCQ2HFDAFncMnXRQgHirjoNcWWoTjwMfLuqXLpYENGvA/hPAHzMzP9e+O4NAH8PwBcBfBvAzzHzUxLN/nsAfw3AHMB/wcz/75U040t8sMLXBbDBBnXx8QeCeIZ/glvOEJWyyxW8toIZumz8K9KDUIWIf4J123Z7lhWLbidralTeYhV5ZV+KGyZkafCFubMWUArgZo2VmQYXoR0UU6VCgFiCidlb3TMYvUn3Bj8/6B5JjkMwloYaIO+rlk2NAmI9sId6+ZllUel8pdS4ZF9CYHW9Tlk5vfbb5kotu/KF4jnNxQ0GGnaxLH4DwP8I4LfMd78M4OvM/CtE9Mvh778F4GcB/HD491MAfjX8f3sS+SwSGUwM7Nn/y91GoTNYuCCuqcWE1fLqxQJAtRHoih3JFBm3Xqdgn44NSH1A28G2DRQEZ2CFXiwNCrSNRVK9FpJNhWAmsnvXCTGKqoIz/VNsd3NnEJx+PhckYNulzmOKCgwPbzxueIjcyXGeOgUEwWnIb9zJsUTgvU8o1JCe5eVqwx0kR1mnMw3iOSJTG+Lib5aw100n8IsluGsjaYt2JNsgv3lwH3x6vsFIRuSEGqCqwnVFLG6jyQT9p49lrKaJPCGRNkBFUayhJkSvXX8+A37w83AfPTbXuZI6Ey3qMx3CeBrmqx6JjusWbraAf+eR7Put92WezH1LRHAP7oHqGv75abzXqnfeQvuDb6P+5ocpwDoZR8LesLP8P26EsHexSKhbZtDHuzsXl27JzP+QiL5YfP1VAD8TPv8mgH8AWSy+CuC3WDT/YyJ6SESfY+YPdtZoXyma6sh3qb5/59SpcnAWfvHmjpzShvp3FtUPXys2wJsGyL2XnDuQYzXUouC0bRYLMH8DCNH3gZ6kbZcRAEobg4ILouDgLFvlZQ+7BRJZC2s2lzQcc4RwRx3ZIyuCUT2MX69xGZ+BpIx/36dz86tVSp3Gc0hvUvYmG3I+i1W+WY2Mvn0Vn6JzuFxlgDHu1/HactlEWRngFRtj9HZPT+Etj4hyUZyehfM1XJ9Fu0ZmllYNT0KrAOVidS63mOYLcLWOMQ65DjPUHzaRrwOQmAdnjZHD/4EHgw07uFgmu7u4VzVS3jULwIcA3g2fPw/gz8123w3fHeQgB7njcu0AJzMzUVnidrkQ0dcAfA0AJji6ZOty51RINhjgLCv7htwQNQtjkZiTgid1DfRtkL1cSLbJ3JCiMbKag6FxMSGBuqgemcbInDcrnozzis26BnidGh0Zi0PeSs50E0/Hz9yQvo9uiB0rnot3xg0JUfPJOCu20krJ2IwYED6Ks3OxhAzPpADFbBCRI9sYNU3ir1R6PAA+4kdyN0TfeG48hvcMDq37dG5jNsZgDCJPhkFwCvsZCzKyqoCFgpcEc0HTaaTagxtd6obEe0HdkLaDf+tBhsehugZm88RdYhCcHLg22SI4ZyP0bz0QFc7Owr3nUhYkYFeoruWaKlvX8THW3/cQzWqdYhbjRvqUFCXqaEIRXeGGYLG7vXBVy+IjIvocAIT/lVHkfQDfb7b7QvhuQ5j515j5K8z8lRrjoU1emJBBHQ7+dr2DD34XGZw1Gl+wTBNRZkrHv8lt1fXWZGg8CzjTxdCygNssw9Ac3BYLtc5jKMXOsgFliXbU5Zpzui3jMzTWNl3C+q/XN7s/LjqG/r/tHC7SYU+5qmXx+wB+HsCvhP9/z3z/S0T025DA5vNrxyuGYg5Zv1EbBTZmwBBTlrUy9GbtfIiPFhPq+w1rIUK/bYl6QOEl3z/UNCiKr+QGVUg6M1zkswjHJaSgZd/Dr1Zy7K4FXJP06ntpt6hustZRNE0snQYAWq/FQlHLBYhvQGXKsqX2AKQkXP1fE2DDKBHJYtwAZ+f5nLkKgKAWfREHkekmeD0eINbAdBL5MCIMezqRBdoQ42p9TLQ+6jrEe3o9uOh7nNi8FGdBRKCjCfhU+DfZ1M5QVQEu1Ya46URK9LtOrIOlbV/ohNlM50+pBlYrdCcNGhPoReWA0Qj+RLZx3oM1wHxPLYsKfuQwOl+DVmv0U/ndhbhIede74yPwuAEZnfhogtWbDZrvpAWBjyZCZKyWlRL2TsaAA9xzBz5J7Qvx+AYJe4no70KCmW8R0XcB/G3IIvE7RPQLAL4D4OfC5n8ASZt+A5I6/Zs7a7KP2AVkWyDzMqYsywYFpFqOEi69Ma7PAnApOFnUWCyWsdFQlNUqjdd20QQXFqhZtj+HbSN4xzyAEshcbqZVl6tQuGYCqiy6WWYwANLMxxKnhKwPn51vNiQKdPWxfeGTpymL0eV6ZZ3Gh+YDxvXQgBsAdoE7I9SzxEDk+UzqNzynMQNDV4kjoI8+jdmKqBMQuCHWoFVOs89n58BiGc+LKfSm7XugMWAnrfJdtzH1SsFVgGc03/4EHIKZ1oWJi27IxABAdRoW/cATwm0LXizRhBqN3sxTdh7PT9Nipy7HJ09wwgwfqBIBgBYLeAOzj20D6kZc49kMMK0WMbCwb5NdsiF/Y8tPf3lgWwbwizuPfpCDHOTOyN1EcFp34hI8xdZDRMr9sAIH5qis6Y4NlOpYwUe3RWvS46M4vrJsWSCXCYySKwrfSi4F7XKuQdUI5tJ9KxOsVNfHpeY3CG9r3S4evzVIVdOPJFbbjlJa0gR/tfkPAKBuImdmVnjnfage3bTmdD7iZwRXzSWeSRBJsNi55J5ovxH2GeMY971sY8cfj3OKOZXasIXZXiajkTBgOXMPjAL+YTRKacUqBExNnxOq5Vjs1hK0DEFSAuQ8gOj6Mft0XdRdcQ48qkArqWzm2GSowPWohIZIFtpN4wb9/SncE9MoKTCNZdR5CEHXphb2NMPQtk/s6G4uFvtImS3Zc1G5M7KlUvSi4Na1g7c3IGSDdOa7l3aFNANWVUXF7PC2VC7ytyVUvHSuIFy5/Dh7Bj5f38XispqRgieSRiNhJCo7dG0cNlgE2vZu3aYWe0B6ezZNKElOOlgOTkV+AuL3x05iSkuvvJ4KR7YWj7bSKywA2/EMEN9e396aIqUVRcuIe+TnAUiAUw9gu5eFTmEAhK4/EMdknJ9EgY9ioJ6kaVLAVMuwp5M0/5pKVOtAH9BxSOV2XZqvo6mkYQNlvwo/ONkg89GSdXgGmhpk2czHY3nLKpdI04ierpK3uFoRnuXNfjTJA5xE4Nkc3dv3UC/C/cIsHKCzBfyD0JGscjFV6k9C+X7twHWF6nwFR4T2bUmzjj5sBhcnOprEAGcMgt87xuL7jnHy0TTNwb2jEJAO90vIkPijCTBycOs2D3B+8lnoSLaLXJRyKoJIyj+wyxtNKxujaP2BWbW1Y1hWA2I7hlk0oGdB4ZX6hO2y/+O+7WYBVd9nHc9sEDCrrNSaDkNLF3ufrlYGpRgWPmVu0srI84DgBHIrrW03+BLK+Yifw5jxO00XWlIfIAWFyWWkyJHYx8yLe36eMVYBIcBZt+DVSgKq9nqsVsJPojp0Xep21tQJcdr3kjWZzVPwl9aScagqjD45A9tFSGHcz6W/By8W8SVU6f7RDVmDZ3OMPqk35ik7j/kStG6zVpZ0NsP0e9MIYQcA4nAvFW6IW7fg+8dyHHvgPepi7uZisU82ZMv+KZuRbghpCXBxNiT2GTE1H8Nl5H7zwTE3N1uobcklqduqnlbfuK+FnEuhFKOP/UlFXaHls5T9EX6uD87AoslWLyBkoFMpN7WpdiOycEOzL35z3ux8AOm829TikXShLuDtDMTFOM55gERnrQiAvJ9LNvgmrFzPlXQ+gw5oQxWrgUVzHwrT7OLWdSAW4BPNTUbFAro0zWnYuOLVUZKctgXWLShkKHzRfiJKuwb7KmvBiNUa7nSRl6gTGdpCAC7VD9Ei1BOtEp3jYMuCLXIgvznIQQ6yk9xNy2KXbAg5AWmVnoi+yWIVZ1jxQ1Vkxvk5lA1BiGso3LvtxCfW1Z1NteRqlb25aTyWTtyQt5hCs/3cg45DG8BgztJ4LG+0ACW3sGyFdSd3IRy/aSKlHQDg+WnKHGjPjfU6ZXNMHEBp2+j4OJL+chGzUBeKHj0E9X4jZkGrlXBmDryt4nwACZI+naR4gY1ZrFYpPnI0BZ97abWoVadHoW9IEbPAO2+CHj/LxtWYBZ/PJGZhXBk6PgZNUnd4Go8F0t11gknwBjCmMQucRj2JhJez/cG3Uf/bcG+EmAVmC/C70r7Qnc9jzKIfilk8n6H9vDRAHJ2epTJ6ex4P7oObGvTp0+SOvfUIs3/3LZwsDFDr3hHc2XwwZsEVwXU9+H5qOYnnN1h1+krKdUBZYVG5MihLUZbGVH85oCxkLg05CgzhBZ+Exk4yUJboJaCsvDkSz2abvCBacamm9tNnUp0K3BgoK867IawFAD5PFbMREGXdEPvwf/x4P1DWbJaxmfMisHdrW4OlCVp2HbBa5aCs8MKov7MFlPVR2N2Css7CdS5AWfU+oCyVT5/i+F9CeuXqHCyXw6Css0bK18/O0jX3fLOgrFdOrpP6VG4KohwaDqQyaC5NkUK0Q5mtnbMPSGA8GiLU5b5PwSiW4ij97BeLjW0BJD2tvr4HWziB4jl8ThKrMZOM8t/EIQAkKv7QbNoXLNzyI2ULnz9Ppfw5QfBwvKKcDzYLeVlmL/gWl/+t59IHS8r8bkej3g8+aHEscpl+wni+inPLHclLIJxHtmiSA1t9+16O5wj9J59mi3nkChkiYzo3TGxAJA1CtOaGiZj9zAQxNbNydibWnIGA02KR0SKYHyI3SAYZf60DnKXL4argblC+zZCYBy62DdC6gKaWt0J4A/jFIgGaCoamkvwmo+oPY7jj45yuH5qaCzUCJfnN/RPAsyG/mUigqnJZUEtTrrZx79aq00B+A5/cDX1bbiO/qR6cDJPfNE18w2tH9NiDU6d93crxLSeHztl4nFKRmgKtXIJwq4un5Ddh0XbjcXDn1nAnJ2GbOnJn0mgU55gePhAIt4LnrKxWQD2KlP3MHMlv/OMnso1z4n70qQ4liqaPZ5pmlfPuT8/h/v0fgfvQkt+MwPMF6JFUkkbyG1N1aslv6HwO/664Ie6b303un7ES6d49UFPDP32WyG/eexfrL76N5t98mO75yTjrG5JVnXY9XFPn5Dcf7d5F/RDgPMhBDrKT3D3LAhgGXJX0d5cdwsCcyVFqjGzg0tJTxDRGVg6IIsBJo5ExWUNQLDQ2jrwYMKAsIgFM6dteQVneA6EmiOpRsih6n/g39Dh1gmVndHVDVadlgDMcwwY4Y2Pk6RSgPMAZ6QDXAdF47xgI/UwybgQgbxCtb3dyqdEz0luZ6lqKwlQfIAVodeyjqQC9yG02Ri6ul394AqcFXtYMd07mrakjDoO8F0vheAo8q+L8xQBnAQ2XqtNp0itwW9BsgdXbR5ieGfeyHoG8R/9IAomucmJJMKN7KAFubhx85TCat9IY+Z3QGPm7NZQTxLoIdDwFT8eg+SK5gPePMfvCBPWHBpR1PIEjSo2Rw/9+0oDaHs4R/L3QsJkZ+HR3e+FuLhY3IBbQxJ6l7sF0rrK/FV+ImarcAeqnFwtVDJQBhratT7GDor+ppZO3+8RjW0JWln6YGxT29vhA0LOPnzP9YrerInbTGto1rWDt++x7WifwlVLYDx0rHTSca9EGMWIodG6A0DUrbcttm0Bvul/bRpo+juS4AC1SR7IcEt1LnKfL/XjuOmlTqAtd1wnQquukhYEltGEHrNYmQ5Su/2jWZTUpBIC7Hm7RxvmSWAijmqk7WaFyTjqbr1s5BgDtvcrOxFeIgJUszt52hluu0TzvJTai94tz4tqEBkS6WDhAgpnrNsYsyFAK7iJ3c7EYsiD27HVqJymClJi39mgox8qi6kMPycDCE6Pq2vfC/l5kERJXpN/cNvbEUB7KFHQjG90OerLPQVlyzn4QlAUbJAxckAJ+8oZDs0uLZgYMk5svWm2BKQt9qb9+TqXoEVzVdlmJevYwK7BJAWkBWamiCEe2RW9s+qEOAd+6Pl+IAyiNUASLAdlWvzOB12rRZosmhQA6LYOV1QV9mUHLsID0nH7rerh5nnovhbse5DrDcwpg3aI+7+JCFOer67Lzjzq1nVhkq1H6bY9kwd1cLAytnrgGyN2QHQpkyLwZIqGNCXDGbTi5IVqpKTgF4xYMVp1K0JNdCt4h5OvjeKpDFWoRvE+tFLU1H1HuhoR9hUEpBDZj1WmV4w5UT1NbYlsqksvdGwCCJ7CZBudixWV8mzY1sG5A1GVtAplZeo/qHKo5Hc6VffjetkEsYMmxQlQfynokPUxhXJXRSCwKRzJvuphMGtBiJLrW6YGgLiyYowpcmVTraASeNGlsFypL0eVVp+F6yP5q3o/ifHYnDRqtsSGSY67XkcmbmMGVk87p04BrGYf9Ww/X9+hPAuP5aCQLsLmniAg0CtfW1iE1NdYPatSTRhZznYOul2tlApw8aWS+ug48Du6c552eFZW7uVgYGYTG8uWTkL3pdJEprIpNy2BP6wWA7d2QaVRaCkMrvG1sW7ghtybst5ummc7G+ojfbWJeMkhxtJbUZN6z6tXOv2UD98VxDU5D3+jiLrqNa3wTc5kx0AYrjO2x7f/6plcPQ622Ys7IuJ7s3Aa2MI1d7O/51u6PQzbkIAc5yE5yJy0L4bdMpjf7PoKK8m26xIVZiAtZAwW7uHsn0vVbiUHOzsSEVtcDCGZ92DfsT+s16N5JzDLEDMKD+wJlNtkBd3wEfvOh/P69DnRfcAPcPoF/S5rM8CeSr6eA06DpBNzPUtZhtYqs1FyFqkYNWN07AcLxAeFzxHgMPD+FeyANb7wybE/G0ghHGbEDzJzfextOUYbzpZiuTQO+fww6l22WX3oLk2/K28vfD+XOXmDNFPqfAMnFYGfmQ/UEwMdT0EefyncBH8IPTqR6VJGK77wJ+vixwMsfCm7BPzwBLdYSo5g00aI4+7E3cfKNkcRZDBGuH48w+uQM/kiyCYC8vf07j9C+cYTmqaSg6OhIoNDrFmhquNOEquVJg/ate6i/K9dHIdM0X+CjnzzCu3g7zAPDTyrUn0zw/MfkWhx9tEY3rUAMzN6VR66bAr4hTJ54nLw/wcc/IffT979/AvCZZMxMK832i++ivV/j6F94QXMCmP/I2/jz/6jCX3j+KFoqi3fGmH64hB+LW92PxQ1ZPahQrRnTDxZYfE7uJeqB/slrDve2kGIuAnfZNub/jWNEKG9AJc7mGyXPXGY5QsDQh3JnPT6fzzbG4bMzASnZ480X0Zz0q1UsM0Dfwz09BbyPHFOsKbLQCMfCfHm5Atou1RDoGOezFHBEAH6FgFeEI2tgbhECfuc5zNx9+jQ2No6L7LoFtSmIN/7uM6m1YIbrFAoqpdExG4EQkAzNdfj0vEirkvBfKjxbswldB14s06L7+FmcCz6TxdHpOfW9xCiCnHxjBPf4dCN1WhGBZwu4+VKo9IO+7vEpmmWb7oW+j/D4DWj1YoR63QpcGogvAV6v8dafrVC//yRdn6YGnc1w/1+HTMT5As1I2iyOH8uD2o8roCK4RYfq2RxvhbaGfD6PVaPx3nEO9feeYPS4AZ+l2pHpt57ivf/jTdQfncbn4eRsDHc6j6nTOsQsxtMGtO5AZ3OcnCcYe7V8nRGcKor40wCn/BE+7BBbsLTpgZqfbcotBAdjLUU8/o6Ta+nxXXpDRN0DszSAFLAEUoDVhR4mtlWAHvc2WwGYlgSkn3V8xTQQxbaKsWCp99KvQ8lmAOH8cKF03rZbcBX2jleobkCkymcNGEc0b5ibUZX6crDArmlUAaMqIVbbUChYj67NduVre30C8YxzycmPdPyculnq4jBy0sFspNc/BZNJ19Zt+jmCH4XxfDEHmnpVOsZA9XcduZOLReZyxIzAFbudk3kLOZci/oBcpDalOve+wXWhsA+6LnKVi3UkUtVYAZ0Zw4UbWyPWLp0nVW6v/PjeYouQNCPjXMSWsCNpB8Ac32AUzoldAk9xCNBSOCbZcycC75KmzvQy10HTowacxmFx43oEnoQFq/OSnlSIvmYxAmU/11VaLK4SwAbAVVos2JEc0173cL5x4QXgQ3YEtQNXVWpgXFWyUNR1wsKMtjymJIsF11V8PzKFju6VCwu4ztmVTi2TQ4DzIAc5yE5yJy2LTK74NtgQR0BfvK2H3nzaTcz8nf2vJk+sKjSrexzLpWpDaKqsTP8F0NNQCji0M0xtAs1xi65mGy6Q+U1xFBu6lWPpm1N96ID9AGBAWQXATL/zfmMehZvU6DCk15a/iwOFMdQET99TZ0BJWnjIHPVWHTL0rbqjOm5ZjGYK1CizFoO1pdtoPM3MOQfLSr9jJ9tSV2yr5fGKWgUQK6ULwl12To7jEe8ftirbe8cFq8+RoEOR9tlV7uRiwSaXrK5HVh3KjMGOZMMHS2EI7wueilA1qpiC3vjM6hMvIJ/zCvNklnJCDhIgJmXogkUUMgCaQXAkJcqAICmXK0B7psberH0gs5kAzjQIQgAONakfJwdAFZMz8QZdPBxsS4MoowpYK7YjxGuq4FcH8huuq0jNlgWEA1TZllPrXBK51G7AMxgsZDIWjAVIvKM2Zdp1vemzO4kdcQBc6bZ+PEJFJCjWLi1sPK4lC8KjjK9SHtYEm6dJA4wbWQiaOgdljSoBWem5ad9TR+jHLulvMCR+Kt+5eQUeV2BU6I5CeXnj0I8dxs/kGvbjcL/4cN+FRkoAxBV++w34o0ZAW3ovjCt0U2TUgr4ZwVUBPFYBCLGQflzBVVKT5E+0ux2LC7Wj3MnFAsDlyLPLOpJtEMeELlc2zaq08Fn5u5fgmIFcs+WA0M20jsCbINN6DcxN+bbNcMyXiOXv4XdSFF4gn5Hzlu/YdtLSc7Ht9oCop/BoLLNt9fPGPqEDWNSRCLTG/9/em8RakmTZYeea+fSmP8SPHxGZkZ1ZrGQnycruFrurRTUgQCRAiAABAYLEjQgQXKghEiAJbrSSNhJAcCeRBEFIQAsShF6IghYCKKg1QQtCUJPNYdFd1YMqK9lVWRGZMfz5v8GfT2ZaXLtm5v7ej/iRmZUVkfUuEIj3/flzNzN3N79277nnwNqlfxDU5cJLM9q1vBEt80Ra2w8iKgIcEbCfABqXSbhuQ4bEQ8w58+P7tFgGciHhfAB4Aje295JITuawy5KDmTGKdFVyJicu2e463jcev9WKYdxdB6x1P3ujNY+lEPNKVqlpMXm0Al3O/a6UZ7DLFdInnO6isvKIysLVi9hMhJEN1HyJyadZ77hEFECBWgPnV9CLDGYVSIP12RwHHxfM3+muTdK0oKUjCLbWx+DSVcap5nKNJK5jaX4asiG+yMb9pwi2vb1bNWQS8nBoDwOP3NuhSeBPbEu0WuDaNpYCcLBuAG7m174tQu1vozdTcJUNoCS6zy5pT6AnEkoSLVU+BvMokAqeiYd7O3XzYdspDazW4o57OLo8IHnGnorpfH+4BmMLEtZEN3zEjyEZIapcu8TzydLemxJZygxXFN7erFDPyyJKtPe9zTiHWq3ZO4omC1h+cGg88ulXPqfmvkjgNU2cRyHw/6gfUnkrE7xUwCpCs5dBF4FHxGYp65dOnNaptT5j0U0dlWKeAApQVQeyFs2Uj6d7S9yQlaIiZykAqUZ216G6k6LIsxDkHecMb5cslXgho4yzQZ0JnBrWvlJmjW4UUPkKbY/u2H+DBmqIbu3X48QUU4OH05HfeE7LusGQCWtoCffP1wAAIABJREFU/rjCKhS58gAvH1SeMzlLtKa1TT3wNKI1cXx8eWhjiYAbsim+SjKCqQvBjie4id8GWnEftzBaxWlAG8cOZMxMFHeIYfECpIp1QFxRmNcUjWooiKinfRJjX2gk2iiMFzBV1XtTivpY7EFsZLW8epn2x1airRLf4O6NH+9LaRKWXZ3hpYcbX2kbxOtJEsaMgO+bmGEqzq6Re0HEzGIA35fJg/swDscCciC2qgpZoS5Mon75mnIpPJIEdr2GcoAzu1q5atEkUC0KLSBR77qr6RTqYD/8hhvtPDrVi5cJ1Z9tgoYMjMFvVf87rrrTW61FdtmQne1sZ7eyN3MZEruHcXT4FbykbTwVfIzozeLKgYeaoq/cRu+eR9mKWAcElvPy0ZvASjn7lmK2l/KEflGL2+ZQmBsaHVL6Pcx8AIEEVsSJpJhOjkufE88gnskN+AzrMh62iRTMZfziEni3nQwYMfoFveu+gJMN3B2+wC3yAP22iIYxzhhJ+X38u5tMfhfrr4jHKMWJcowvQWbxjZwsvGsKcVvBk0bMrRC72VtuBiUuogSURqMeo5SP6A9qQ8TNlGWMWa2gxmPmuwT8udRs1nezAag890xQZr4ILnxZQh0ecCbhgqnsaTziWpWMxXBj7k41ygI3JRCyLZHUAACYaycFUFVQbrtvp4shyLLDOJdXHx5swL0pSThoJ5wNdw6AiyuueCwCM5ddrzcCptxxYt5OqWGRuhqtfQzBxyxECkDOPZnALpcw6wpq6uoxisIryPWYsu4dMtxb0oyAB4RJ4FOyIWQAOtznOMCT59zMUcHnd8uDnrqb1qDpxNdliASCOTtH9fPvovjBqRsEC5ulUPMlugdOCmC+cuAxi27fXf+M4d561UJdLLB6n/cdf+cxj1MkkUlEUMdHsHkG/fw08Ja++zauPryDvd9+DuXufTMtenDvOGZBdQs1X8HOIvnCH0QxrpfY6ztZDGo/brRorbvhcbwodSqBOffm9HRqcvMvlgG3IHOFVl413a/7SHlFbddg/l8CdTHWIc9DAVpctNZ1rD/ZdbDnFwAAlaZe1xRoelqllKUu7RcxX4MDdBQF2mipne5I4wNyKAOsPCbs9TYqAizYwbzJaahS40hqDyYsw9d24cZzmBAr2q+uX8yH4XRHpJ1SFKeIyWyBELwsci4MlD74oGIVdGInI58etUWg62vujJGtGybmTaNsSGs465FnXoIRbQubZ2jvTpGcXbj2aEcfqDhlHccsEs2BQacc5sdZayzfTpE9lz4BZpxBG4PmDrc3VS6l2RpUR7ytnfB10OsUBQGr+zy2YxespBjGniSw44JTpxeZpyLsZgWu39OYfjL1+7bTDKkBbK5BneVJyW3XZYukM2jdhMU8G7f3Ul/fAKfYIADX2yYmHkQsTvySfvkAZxeR2VjT59b0wbUQ4ITp+gFW+XsQUKU080uYHuGMZtx+zM3p3/DWBh3QLAsTpbBkA7BtA0rS3vIoDgbG7qZtWgeN73o4Dd+XKFXrmbuLIrjlUdq3RwrkvB0YEyZdRxMYM2P7QjIh35HJQsag6zYChuLxxBMgp4C7EOCUYLAxvf76Stp4HBy4LaYIBNwyxLGtGymmi/rr/xZTIjfY+r8BwNY1kodv97U7nDfX4xMVciYX+OYsjnshrtdclQvAnJ77+9lGaVQmS9Ksv+KwOHp/Dzg+Ak4vwj2qtWeF7/XHca7GXioA/NPrf4Sr9mQX4NzZznb25dnruwwRu8lDiNKF3uK3u8Qq4rf+DfELj2OInQPTwQ5Tk3CVlRElnqkBVeQbIkHs/geVdN5GIU5R1yDtKNaaFsq9CeOYAu/j0oHyAnXwZMrzSDLRvf0jXRJurdMmid4mrCnhvDBLvRQyrHFuuAMOuQEhqTIVr6conD5IBH3XmoOedRNQqJGpLIN1IkGCGVGjAtYxiXvMidMnoSgOw0phUTFdpGESp1FpPI4CrhGEu8hgVytQmqCLVNbVqHD3h7s+Re41SZBmAQRmHa9omgV5yYxp6uySmOtDEK3OOyVrQC7GYmONGEe1Z111LJVOeW7ivJAT2weDAbAA1P4ex46sBRkXy5hM0B5NoS+uIO99ZmcvIxpFWQJnzDp+vQjpY2uB5e0Dn6//ZPF57aZYhUwY8boaznVEtDzZojfJh3VVnxJ8GtLGy5JANEZjUFaSBG3QqgqckqruaYb638cCRtJeF8egNKxpbdSHOOBItYt1dJ1fY3vqfa04pCPwcJl48rzHieHbHccyxiNPItOTHijXIFVDRI82+hO1E3CTThfGS4h2UJNXg6c883KRXgogzzwLd1yRycQ1/QeN9VgdpiFLQSri78hzHpdrh7TMUh88pSIPHJjWxRCKPCAsi5yXUuuKYyUSEHeM2haA2XdSAES+ZN7MXNwl1TCJQrJIoADUdzj2k36Wbo3T0ajgYOx6HZZSkxHKBwVmn0ZSALOxKytwy0tZEo5z2DyFbtoeYRGGcP8X2Nd3sniZbaROXVrrJbEOqUuR9J01dmvqbaucvbVRymzwuyGIbFhYNpAJkDqM+Lue1ADgoN5OE3RDis9iyFIOoJ9KjGj6yZHNAGBCHQlextID8rstEPt4PPx+Aq0GXDwBsEr32L3htUcj6YO27bNwi9WRjIGcF27C6DpGZg766utgAD6vOzbapC+rgBbUBBSqbTtAcWxMr/tSAHBpb2HyRtP6oi21FpChAaUaVDVA0/Ix4OI825DDbQcix17uxkHVDdL54JrXTS/lTjJxrxVPDk3ULmnrLe1rO1mQIlhLnnbPbQxp1Q0tSPLR/xce15GlePi01qA8A7lliJcSlArD+N4lCsHRYdXoEJU6hKP3RHPcskCQiypK6aZhGYIi92rfPY/GBcwsQlSf5MFNEj+x+OpExwNB2t2UMWFM9GanhvU2NqQD4/Fwn3ksUyBrw3EEDp8FVXrKUkjFqCz9vBeIvmeBbLPozBeFrfXGd0iSkCUCgJTFg9EmMEd7UOLCO68Eqg85R54BXYe2SKDlOKLV0UScGnUTPIvCTRbOs6DWgNYJOrc91apXrRr3zeYpkOdQ4v1mKZqZRjEcg6rZ9CyKFNWDKYp1BeNg6BQjeG9hX9vJwsZv27AxfB6+gdzD8tJ5drCP7TouGhtkJvzx4rdE24IibITH+Bvbz+nL7+N2xu3tOtYD9YJFdnPyAzjybXgNTPFvRSA4LiSTtkYYh1g/hIAQs1iV/FkpUBQDsG3br/4d9se/lV2711VUtGY8JDnW+LCG2xgLD4NUOF4EiFLXy43loyUmgbF1DYozSAD31UQeYFU5fZAWSqlQNNZ1nHJ1mQZvdQNb1UjPV1wIyA3mSamqoK54yRPHLJR4g0pBu5iFXZVIz6UCedM7AgCsSp50qjBmBGD0dN2rpCUgwNsRYhbUdsgB0GIFHdMKDIWqXmC7bMjOdrazW9nX1rPwWIttXtYXxZYYix5kWYhKtrjfX5nF+hjSDqeKJjBob9aAyQ4QgqQ3eAQ/dovgyAzBdh6PxEcEU/EVtM3rdQD9eEocy4rjRGS2ewE/rra581rrgqyveAxqHAeIjTyLV7Cv72QRqZbd/D0gQQWPaBSQ0ouOHZWo+/Lv4UThtsX1JD3FMFEWgwMkDZCUXuUsUkGL2+6VxoAgEygckxHBjfBdBklB93thgoraYI37WwsLVlRX4LIqAAIhTbSG54PbDUmG4Xj4z4Aj1RlQA0hWRH7nwETxeEErkHVix1E03xYZUG7e0p7fIkl6VaXQmr+LVOA4HuJiFIL2dCn4WBCbYzgsOWDGGbTAq+GqhR1CFOAlgCc2dttswvyfygWfu7Hbd9u9BBffcYpkfkJLE7STFEkUp7J5yvGneIzB8Q1TZNBpChvHaV6BV/bNnCzitOiLYN3bPAuJEgtBi7zBJC0nA7lClA4dlFFHcG9bVdv5LFzwK15rU5b62g0q116J266rUNNxdh7asa4YryFl1wBsU0e8C1ERF1zqdDQK6MLVymc+fMm8dmtrKdkWvIiMw3QCLJ2GyJZ2A4DZn4JWK56ERiFtByo5BkKbU62Mh/8MgCbjkEXwKuoF7HIVHuBxwbEEa3xamCYjZupqHZ+Fs+buDGk9wHgQMbbBOAxJzGcxncCOC5CgL9MMKHLOeijVu66UJEFTRNpFBFxeYfXOGNPljHfsDAeAiVDf423pufaBzeaA+9BlCiYnZJcZMqWweofHd/rDbKu3YmdjhnuvSi+fYI5muHw/w/1HE79fd2cCHU3iwhreznKQBdRkhPZOUFG3j7/uqdNtFZ1DN3Xb9sjt8sAX0Q0p1z3396Zj2g5cuRilFW1ZRudzbr0LAsYBNVOufcFPDLyxXRcKlKJ9mdqvDv8P2h4zZZGifjsQBcu6rh+sQ1h2BP0U166rax9Ai5XN0QRWK3V6wTorTrHbn0/Sq9sCnBIUja0N2ic+Bes4F8IDcw3jApGe36FtQwA5eqDTx2dB10OMFLAsuf9VP1Bqr66BVWAcQ8yUJTU1QICV102fKUtxQHb60SVweukOarzmSPbIvdXLNbQEOK9cVioCZdlViengvhkanV5CO2i6BIj10wvc/Y4Gzi/9fklZ9QKcktHJrpjkxy5WSOWaGwuqb7+M2gU4d7aznd3K3kzP4jb2sqrTz4ng9MVgsk6sG/7sodfR8X6cCE5Hw9ezNO0dh9aVK0gLDE32JgSncGR+xQhOwXT4qtqiAChKC+c57xPRB/z4EJyMs7Bt14PNC3MVjYsNBCcWy68GwTkZMV3fqgxe4CsiOKEUlDEws7AMwcnXfRnyEzQaBIQE/u1p1r7KhIKAhiLik1g6QHg+KQokejCYZBlk+8sCwj8ukz6I2JPjoiAbwG3QepOW/8fSFld/ogxPMPICIOMDxT1Bqiz9wmpmtzYif/6Yw+NVzBQJFJFfT1jzavmU179EXSzi5NwmdLxhwzJyuPLrzvTX1dsK0uLtw2YMKPVt10FlaVh7S6FY04b0bdSHXqm4T3EGEhfftyF5T1yqT8Rl6r6tJjxsw/ZGHJUAuJ3Rg+eRqFJ2vqX0nbM6QfHNl42jP3kywOmGNbDSvePJcWLqfN9WmciAEBtyDFi+zcPyf/DYb6z33bj4cv3o3pHsho/F5HkI/DryIQC98nb/e4fipVHR150VgFzX9fhJ44I7PpnLSLljCn9st1hufeOo0QjCjSKl7/bqGjQZw1xHQVu5NgO0LJSCOjyAubyKODgt/un8H92ag/PN8SzE9WpbqKLwF0cYo1SeM5kpAOFp4MxB5uHeZh3QhsmD+7zNEa2qB/dYqNe5aN3HP4SeTmDbFsYFhFSR8+Swt8cReQDdk2dQD+7BPnnGp3bt0h/+MdD5lavOdNficB/NW6ysnf3hM5hD5jCgpyeofuEbIGOR/Obv8rm++S7w7AQ0mcBcXkHtcWS9OzmFfnCfSWfOWf1bouPq6BDNwzuhjx9/BhoVMGcXoHce8D6Pn/I5xyPYVQl1xOrt7SePeDz+rT+J5Mwdb8EZDzsu0NwdI7nk8Tv/hQPc+e4VYAzqY+fSGov0vAQ9fhZqQJxIsrUWeO8hiz8DMHf3ASK00wzZD094X8c43R7PkJzMmd4eQPPeMdJPTtCdnEL9/AcAgOp4jGTZQpcN2mnmky/P/tQYd3+ngkkpkLoQ0OUKk0crNHsZit97zOfrDKqffxfLt1Mc/WPuu92boLkzhl63aIsE6fnKj6UZZ5z1+IiDiY0sG77zh/iDv/cBHv6Gm3QtUE8UZo8qPP0V7tPsRwbNhAADzL/Bx2tnFqYwyJ8lOPi+wbM/y/fuH/v7a+jTK7fMCnUz82+/jfJQ4/ifnQHPWcn95C/9Ir71q7+Hj//eL/ml4+Khxt4nHdqCQBZoCx6H8h4hWQJ7n7S4fs8t+TqL+n/+v3Bbe3Mmi8iY4TjckLB2g+36ZSrqxqXQfGbh/ILfPpG6umf2Fgi3y27Y5TJoXzQt7OVVH44MAM/PWeMhepMpY5G5/czlla8AtYslij88AaxFK+09PWcV9I5FZ2RSs10Hc3UNWgcFcp8VubxCGsF3zXzBGYB1BTrhlGwP3u3aLmMGANkPTz102bo+Yp4gW4z99jsA6LNTQBGK6/BA2XINu1z1yHOsU1FXz878ZC2Zj6zIvbo7HGQ5LSvYSBsj/RHBXs9hmxbqKT8ko3nJmYmmQRZhDO7jmNXMxWUH+PxpArqcQxd5YOEGUPzgFNnzkSeuoarm2EPdQGdpgHAD0Inm9KjLekiMoqsqPPwNjb0/uPDjaFMNdb3CW5ap8pKLknVCrMXeI0erlxK6TCG7qpCdLpGsmd1bPzmFWa76uiEApt8bYTzOgJMLf93v/vYcv/vrH+LBd8/8fpNPR0guVj5LJIxh3TQDtQbJ2QL52ZT72xn84XIH997Zznb2Jdsb6Vl8ZTasGo1tUDK+YdG6s6dX6tfoX3Ce3hZT2VZiv02LdNv3tzEVxU1ibc/B8X017cu6GJXp+xESj1G22y0UAEOKxWE5f1ThCqJ+H+P2Wtt/XdqYkXsIMdcMuPJM7WE/sthsg7UhXmzC3yR6ugn1s069JrpAahcC1zCWfzvADZEZjIF1bdAu2xFBu6kz4X847NwrXP43crKQ8nP3R9jmU3a3cK2GUXit+eJJysxBqq2xAZGoNWBaiJqWt20IToEGx8FJzUAcgV8L+tAKBNcETkxKU0ZkJgmgmxB1J+WIYnQ4bsxfGSEafTtVvzTefzdUVnPH8O0yrq0O3i3l7yZPoYo8EOYCXDXaMkjKt9UHa42DXEtgM/XjEQSGhSvSnTP6m4g46yRB4DQJwspF5m9+U2gex0T3CHsBTrfaLA2p4q5jCPQ484ApP37W9lXN5Ls0hnuH8awnKpwPHN+gskY34m26TGAyvr+6gsegGXMpOhkgWaRoJoHRyqfHJQbn7huTaeioTSZLUO8RzCj1/TSFhs0T2CzhoLAsQwrXljTxJL5k8eXCvYnovwPw7wB4bq39ObftPwfwHwE4cbv9p9ba/819958A+FXwO/lvWmv/z1u35pbWE0YeIBL5Dws/YdyUy2wCSpGsY6VumugNx8pOvcyJ6IjE2ZgIZdlr43rNMQ4hrQUYoqxdnKFuQkalrqHmy36sZb328RjbtlGa1DAZbByZl9/UdRDuBfrfD2QDrPu8QeG2XAU6OVG2apm8RbID6iJjFS9jexoeds3l7b3SeWlzXI4ucO4osyXjbl3MwB9jWfrSd1mrkzFMPmM6oK79yzE9KUBzZmWn2HNTBLtcgao6ylqwxqg2xgelyRpfoo6mLwXgg7Wx3qobw9mjCuo6SEFQWYPmS+TPnXzh9QrKMZsVTt09yzSsVtBlA3W5xPRx5sfflmse94gYSC1W0HXDMSi3PTlf4uBfFdDnizApVh3fSxKzcJOaKjNQ04HmK/goj43U5m9ht/Es/nsA/wDArw+2/11r7X8RbyCibwH4DwB8COBtAP83EX1g7YtkzF/dSGvPjynkNqQ1bNRxcsU88v/GMVxNA7mHWU0nzHkgtHTzeSi+kuNqDSIFNSoCLX3dQM2mASLtgoJ0sM91CJGOhtqbwRy5DEjbglyGg9oW5v4dvuDPWX+CplOmxRuPeEIT8FNZgkYFaDqBcikzuYHVbApz9zCcr21BeQZjLehw358LAHNbVhXUjINdohtiHxyFG39VelCTOZj67av3jzD+yL3N90NdgrpaBhIdAKEyV4EO9gAXXKS9GUAEMy28Ky4kPGZ/CnUVxs3ePwI9A6hpfR+6wwlU2YDWNdd9uAfl6sMD7H2keWkRBTjNKEH65BrdpIAqA3iqe3CE5k6B/NIFOKcTmP0JaN3AFqnnowAAm2eo7808hFv6TfMFnv5K4YOZMEA30sifFzj/eW7v5MmIvQwLLN/ih7cdEboCKE4LzH6U49m/zv1/70d7TutE9bhj63fvotlLMGlav3JafnAHj/+cxfvnd3wl6ep+jvFnBUzuPIqc914faiSVxfjJGKu3cn952qe3x4m8dOFsrf1/AJzf8nj/LoD/0VpbWWt/AOBjAH/q1q3Z2c529traF4lZ/A0i+ssA/iWA/9haewHgIYDfivZ57LZ9uXaLQjLPlHVDAM97G9YARvGSoW564KyNwJqxQeuCXOpUmLKGzFvlOhRyiSRhVUHNo3SnsEx1HWhRgoz10RZb1QxIEtc9Ts02LexqHdK+srSoasZGSHOj7306VNpZ177tsanrVWhX3XCg0Fqoa+Xf9vnZ2n/2VZ/W8rZoHERQ2VrLx5Q+CG4lWgKIp6i04kIo12+1WPE+1vh2Ka14Pd92vSDe+FkNtSg9CtT3acUFW8rankixmq+QKvjYii3XjHBsWmaliljAqO2Qnmu/Tbn7pOs6zH5kkFyIx8IxCnW9wuQJe6/ZxRpmKczcDnxVKJiEkM47ZBdrzB45KHtZuaWrDeOlCOn5CqrKwn0FoDhZY/bRFOllWIaMASSXax+rSFIeB73OoOoOycUKIwkTWUA3t49wft7J4r8G8LfAS7e/BeC/BPAfvsoBiOivAPgrAFBg/JK9X91E1tDLG26eHwACjFhpELVbg5XD43L5cgisYgvcmxm/yfNYup19jcBGcFFrWBVduG3cm9F3lOjAkRkFUG3ML+HayVT+ur+v0PgP2J1tmoDqKBhKBFLKbeeb1ORJCLTJZGEi6Pg2jU4JtMpngIOREtCNg5dJ4h9qGwcV5f804cyEsb72AQDakUbmAqR+GUIEm+sQXI4tTVgpTILkScLnt9a3w1vCZeY6aqeMZzMhxlEAgGUVMJUmPsBplolfFkggs8sJXUZQrYLJEjTjCEYuFolTmSKBGSVIksRjKLoiQbPnsBRusmhHCXQeArzG/d+ONXRCSBYJunEAZb00YxXZ55osrLXP5DMR/TcA/lf356cAfiba9R23bdsxfg3ArwEM9/4cjXjlnwzO7z4MPJNhSnSbF3MbM6b/fzhxOHa8z7A9Lq1IMUdk3K6vymJWpVjgVzymoSgworEdCiK/LI37Km0REt8o2E2SNhQyILiMCdzDZAZ9MBaqNa92XbeZpEbdZ98myeRGaWBP9RH9T5IC9X0znB7w1/kFIT+D/j3WS9nGY/PF75nPNVkQ0VvW2ifuz38PwO+6z/8LgP+BiP4OOMD5swD++Rdu5UYDVFguiGcQCxhvbN9yCBHdiYVzgL5WqFacohXXWmvOAGSpFxQGKf48PM+o4IxLjD8ocnR77JqqizQIyyyWMG67TwWPC9B8zpWRdd1noXaaqeRFjFywN8/RTUMFonLttOU6VIdeR7UgxoR+ODN7I08q6zMdowJmbwTtJobqKEfynGsVzH4Q2VXWAtc6ZJTkCdCOgEaCwA7abWYF9LVLZUqAczqCblp/jG46gp4vgYUKkPCDMfRScyByFLROl/cT5Gcj1lxSIcDZjhMUZYNumkM/C3UR3f4I1VGB8Q9dJmKUw8wKqHXCRVfxQ5hnaA4Kz0ch1aOkNebfgEdmUsfp0aI1PphJJkczUSALzB86r2AEdAXQFhq6zj0M/N644KwZX1h/+vqwQL2fIP009xW/5XGK7k8sUf+TUPm7updCNSFFKwHO8o5CsrZQTYHVceIvj0m+3NTpPwTwZwDcJaLHAP4zAH+GiP4keH78IYC/CgDW2t8jov8JwO8DaAH89S87E7Kzne3sJ2MvnSystX9xy+b/9gX7/20Af/uLNOqlFlcaauWk7aIZ8jZaCGqwhhcQzoAjk4Q6H+LSOpBVb2256b3YJCoPF9MM3rFE0G59DPBaucs5D6+idT1lGfcvpngjBnNZHXlXcn6lgCSOkUjJtQprew9GC9/FY2ZS7aUUhQ/TJprX9g6A1RaOI8Jar3dBxkKliSuHdwFdwWkYRzUn21MXz0n1Rh9s6tokMYc0Kg0XTo5MwdZOJTxPvGvfjoAu14AmGDmXAkymYLOEYy1CL2g6mEyjnUTgOOWuT2u4bdF1tYlCl6mone7+UYqLwlK5jwjNWCHLNFoXSewKhS4nwLJHAQDN1MJkQDsltCOFZuaWcFkKlaXc56jC1aQKXSbXzB03JxwdLNBOjrwTx2Og2LOwvA8AdCMuLDOp8tvI4Mcfs3idbIO5mje+/IfiprqI/QZs2ZqgjCWFZAJzpvBAwAU4NwKR8v0Aamy1EmnS6JyGtxH1sje2de64GcRNtiEM3TkFnQeAH3pPhLuJ1Oy1Uw6fqP42Y127A6TYpMRtijNHUfd9UZ3ENgb7+kMnYRK0Hs2qYZOAArVp1E+Z0LRinsnh8TICtDwI1v9GXHFEmQ/u++CaJ074xxHT6GjMbKphcvLjaNykrIlgCsMTiTuvVXydu0L6ycFMAGFbBrTTDuYygdEEm0fXOFJ6B7jNJieepJMwwXYZ4eF4gXMc+YfeZASbkF9edKlMLAAsF6/JJPaVBDh/4jYM8An+38cNoqDVTcGrIVCrafsBMFJAmoKapu9ZdIZ/K+tKY/nzkF2qakKaUiaStoNauXW7tRG5ioKqO77Bo4wCJYmboJQ/PgllfhkL9LjzVDX0ImL4qhuPBKTSpSh96tSldf36mI+vF3Vol3vIqeFycAlmZtfyGuugGsd+1VkuqTa2J/7svYS6iW5+5odIFjWsQ9JS5R6+RQWqwna9qPizCeOVrBqW/Ws7UGN88K44N1BlyxOeSxlSa5FfNkBroKouMGuZDnrVQq9DLIjKCskiAVUNK4WVEaDOWmSXmd+WLALhc/4sQXYV9iUD6LJBccozQzrvoFp+07cOdt1OCeYyQXYJpEuD/LnzVIQ7Q2uPMialkF22HAwtgwhUcWnw3Udv490qvDDzC4N00YJazalR50VYrZGUFtlVg9FpmNjUpob1jfZmThY3KYvFJeovw1n4B8LCwnJuX+T33LFsXfcyIkKcs0G2u642cRbLVR+2DABlCX3JbwZbVR6SbOoa+oLh3p28VZalVxJyrio9AAAcvElEQVSzTVAysw66bY3dxFmsqx7qsIezcDDwDZxFhDAFAH21BHzpu7tZ25ZVRtyYjZ6VoEUJGAMtHoMxoNWazymuuiN9sdZCLcsAq166pUtVe9yCtEsR+bEDGBVqHVUAOQyJJvI4C9V1vjZk+mkBfbni5d7A61LzJadEhdPEGKiLBQpC2GYtoxSbFrROPLwcYARpplTgDnHbu7bFwfcNstMw7skihbpcYvYjDoZmF2uYjFOyuuZt7UjBaOKJ4rzC/vcd6/t8FThQ5LpqjexkCb3KHKGvuw5P1hj/zgT56bUvOtNVjvR8hSTV/M50k2a6yKCqDun5CpMoe/RV4Cx+/BYxYwHYYDjyrE1ZBluWvB5WgaWqBwPfwt6kpgzXNeJJHO7zrD11F+36mmHcVQ2ULjtQ5EBdg8ZjT35DqxVof8bU+ABs5S7w8R0me1mvgwt+5wD1W3uwRMjrBuaOg3s3Dap3DwELZE+e8+/fOuJiqekY6pIZkQAwz+X+HlPYn7vjSs3E/qxPflOuGRretsBdJt0h4ZQYjxjOve8o7C+Zp6F6944nfVFzBjgZR36TOuDR+bemOGo6wFpUx65dFsjOSqgYlNU0jF9paph7h1DnfC27u/uAArpRiswRvEimozmeITlJA/nNwztIW54gzX3uW3WPyW/UqkE3DdmQ579U4K4m1uSQUhpF6HLC5NMMzTTF6Joh2DAGq/ePsLqf4u4zhuDbyQi1I7/pisRLCgJAJ+Q37lyeM/PsAs/+bOP5KGAZSzF9nHkI9+xRimbMRWOS9WhmFjZnj2L/+2Oc/3ke24PvH0GfZoyDEa+PCPOf3WfymwXXBQHA+c+N8ct/4bv43qMPfcxi8VBh75OUlywWfslRHhPSBbD3SdYjv2m+f/tsyI7PYmc729mt7PXl4HyBZxHzOfpCMaLt/JdxrX98eMEXOC5M5oM0nrXb1jV7LesqLG9IwbauXFwCcLJf3V/7q8kkBEjlnEkS2hixe9u6Bs1mvPQRL2FUuOCgq0QVwFNdc9tttAyJuDFVhJswqxUjQ5uWS8oBTxEonJo9sSQA+vCwX60qvKERXyZNxrxs67rAJm4s0NTs1UkfpVJTxkiK2LKUY0Jdx2xkQFBId2MpCE41KmDKNWzbQM+cF5SlgVsiVnGfTWEXqz5BsTGMQ3H3iL8Xuo6LCfMM5uTMXzvKUmZD16ovgqw1l7nL9XG4l+56AfrX/jj0k9Owb57xUurAFQ2WFS/NrPUelKiCUceVoO07XIimf/DUaZJovzwSJXhKU5ira3/d9VsPUH/zGJljWQPA16lc97g+/famZS9chKGsxT959g9xVT27lXvx+i5Dbmk3xSR6aL9tNoh1eDJYvCTiI2XkERqRJ6f+ebwa+HBbXFofkdFSNYh7yEThsj3D77ygT3z8pu0xefh2xiJFPv4SftM7RlX12+VIZeMaFyxXvg2+tLwzfSSqHy7XhzYSZnIpVVtHNTVxxqkL6vNGxkVK9d2YwwPHInIcO+cHPElCRsfa3kPvIdzG8osgarNvj9ABxuPrJrdhnAjWQJ9esegS3IPdtqycHo+N9FHK/EVRjgh2XfHSA3DjZBHrqFqtgVUJq+vemNn5HOlnmROXcmOwJhfYHoAWtQoxtHgSfAUV9Td3suiR3rhNkpt/hd9vMGPrEJUmrfrHegWiEL+/sX2sBTfUsSG5Psi+cR6LFJByJsJq7dGUXp/0NgznX9DiNgLh7c/joHt6JgQ37ia87anrfH1JD5sizNZfoF2+5ibW/pRx1coT7FhXjBfwNNEtL9qmt8HlvMhiEh+p+VEq3GNS8xPP7THbt4rHRgNkQGkKqx26WKvtXLLEuA+fNQPg2cVFb2Y4aXwBe30niwG5Tf+7iHAlErSJ2b1fevjecTsQeGnjIfuNI3yJyW9epSYjzqK0YRnTe9vEF9i5yP5Nn7LnYaWmIW53+wVv7he22/RvPImcax0EijJ4icGexF/XuX4tQ1sBRxoU+kHG9AvsXqFt/rhyf0TbifihonrwNpc+EQEigShLzthj+bzWRsvNznKmpusCH4VQ88e1Rm3Lv2l4XwlmmrWT0XReBICbixu7jl8mkloGGETXmYiy78sDUO8CnDvb2c5uZa+vZ/E5zJeJ32IyDSXlkVANqd5ShpwrJ97LTeXuLzhJWOYAUdk5B7tiYlvSmt+YMUemwM3jyk3gC7nwr2Sqr3DWUxUXcJjAqgF+23cmLE2ipRMvHeS4EVT98xpFVaUqGl+Bxstywxp+s2u9Qa9PRCxL+CrL1xe0xR9ToPjx0mRY6OiWkqQcJiTuz1BFTpYUQ3NIUVm69NognowvqPzi3ujrP1lsC1D2KMfCto2MiVP66ql8uWP6iP2aAU56bwRbN0Hjcr32mQM5l4XmjEae+yyCWSyhZjN0ooIuJC77MwbQRAFENSo46wHAnJ1HylJz0D7TqbWPHvt9u+sFCxutK5/NsE0NqBzq8NArekv/1HgM2pv685nTc9buXK7CeUXX042LGjNeoLu6BqyBun/MkXwgBMLSBDQeh/M9vAf69DlX3wo9IQBblrBXcx/si03tzwIexPVbTcZBPT5JeLIeF0zUI/SE+3uwV9cwy9L3gSYjoKpZkzQJVa7NN+4j/WxA6kYEHN8Bzq9ARQ7z9Hlo0/ERZycWS9fGPc5CtR1nXAScZi3HEGZjkNMNoYmrun12gvm338b0ey7D4LRO1WKF+t27PHznKxhXQ1MfuorbVMHkhOyyRXayxPxnGacx/X8ZFDcMaNM33oEZpVCPTzwJkHn/HZx8ew/3/3GYCNqjKZKzRaijET6LKauop6cLtIdSKQzY72Qb1+ome/0niy3WC2reQHJzoxcgk4+8/eRNnjhClTgVNyS0iT2DHjFKsuHVSIAqJrRFkgQ27Igtm7QK24fH1Nr/700YuAfizkgSn5Lj4+pQMCepOnmDecHlKNALwOZZED8Syvg0ZRZth+hsJznSlIud4nZT2/IbccvA9wJ2EnzMs3Adom1UN8wsDvQJcoRWYJQzYE21ofAPQLOXIjkbjKNWzOC9yPjYcT1LnsGMM184R0ni9mlg89SPAwFMlDPOoKUNUuxFhPJQswAQwMVtmYauGzR73DZVZTAjN1nsO2BaRh44pVcZykNuwywap9jMKEU3zaDT1Ke5u2mG8h6x6LGzdpZCl7mvEZLJotlLGYa+yNDMJG1rg3LbLeyNmyxiNW4gBNE20ohSABW7704f1LYNp5ui35n5YoPteuOYnUOE1nVIaxnLClqdKIQ7unyXD++df76AkgexLGHk3HUD/ew0PhXMfMHHLEv/v29HWcKYiGVczrFcekJeAL6dtjNB0Uwo5ASn4N6qlGXsBT0/9YFi36eyBK1KDx9PfwCYyyuOxEdehGnbvjJc3J8IHyD9pnUVaPXkwXTQeY/JOL3w+5gL91ZflTBCDBxNouPfN7DzoDjGOyuoJIFZrUBpEoLgAPTzU6iLLGA9rGWlN4cfsbF+qdZQqxJGxmtV+mXP8T87A05Ekcwwi1hVYSJKceUaiXu5pJ+6B1spljkoK9hViWNX0xOPU2zq8QlPFNF9kH38DD9T3WXJSGejsxFsWXomMykpSPOMq32vFxhfBpyFKm8f3H1zJosYUBMvTV6Ep/CCvu5PrfghoSgVJVF1AXKZLceO/ybl6kncDd8rjVdhDV9v4eWMcBC2Yxp7/sMEivpoX4+vGOAsOCPSv8ikuRTcVlW0VnapNQGcIYrRiACyZDuyDDCWH5xoIuTjkMc/AG4i85POABsyFIOWNsfjET8MseflGdmjalQhJ0qTPsZBMgtRStBeXW+MI48NA9MY5xLOZ8o1ezGtm6hM6idXlSSBsd22LBOwKntYD0oSXlI9P+vVkUgbpWW2bnytihDXSErZti0vf2XMt9w3AFiHV2prJq5U4XqO5DHBxOce1CNJWpjSBLh7x9cVhUG4fbZklw3Z2c52dit7czwL8QDathe0lM+95YnltyeL84Quxirqeo+huGa1Yld1f8YBPQdf7k5P+W3bdf0lhjWg0QiU8xrVXF5xsZa4yu4cyVsPWDAmqsKkyQQ4YM0MPD8Nb4iLS9A7b/F5P/4ht+/4iNXTRwXMsoRytHjdfA69vwcajbxL7EuZpxPAaWsAgH16whDlxRLqkAvJfHzDld+TK6jrThnyrD94HyQVqgI3zjLY2cRvF2VzAL7wDgBoWcKcX/QQoNxBC33vLgtKyzgQq7PDCTbLeNrZhIWCpIjq7iFwegEzn0M/uM/77E1Aa1dKH8VoVh8cY/SDiwAEA5jQJtfQZ3PYPIP9zLnsxoDefRvdrID+6Ee+XXYygqobVi+TfgEcsziaQT/l5YZQItoffYqTv/SLuPvbbvljLUyWIDlfYvkBF74VJ2tPElQeO5i4I+wtLg1GT9Y4/zkex/v/xyNeSjnEKABAEcz776CbZsg+fuaXlM23fxaf/ukC7/3GoX8+1ndHyJ+XTFKMwLvR7DPdXj4dobrniv86C/Mv+rSKL7LXd7K4oaYDcDevAHzynGMJUscBADB+8hhOIv4YIrojkOYHx1DLMojmnJ1DjcfsJgqUt8iBroM62IeduQFflcC9I+9eyrna9+4heXYVhHoAmPt3sPwjHNGftR2aB9yG1Bhc/cJdkAEmn3A2xLx9zCJB+3tQxoKODt35VsDdO+gOp9BPXcTbZSlw/y6WfyRMFtN1zQ+WtejeOQYAKHHrJbtx/67vLwDMP7yL0VM34V1x1Wk7y7F6a4TRcx7fJ//mGA+0AhmL5UPHRdlZjJ5VSCOAELWtL7Vu3jtG+pQnhPptnriqo8xXcQo3afn2BKPPRlDXPJ7LP34Xk/8PoKpC/Q3uw/KdAtlVh3TRot5PPZ/Fo39b48FvHsFE5C9WMXvUwccFqjspDlahRP3qwzu4fk/jnQuuy2iPpigfFEjnHZqZ9uMAAO0kxeX7Ge5+hx/C8gH3e3p2gW/96u/hd3/9Q+6zAeo9wsG/KvD4z3G7Zh9N0ewBMED3J3jCPDpY4OF4ge8+ehvj35ngl//CdwEAjz/6o0g/c1WnEvPQCiff3kN5j/Az1V0kj7lvn/7pAn/wV/8r/OLZX/N53/k3Dfa/t4d24qpO3Vy+eqdFcp3g4KN9XH6A0Nbv3T7A+foWkr3A4gmAkhS2qXtl634tazqfQh2acm9163D0ajrhfLx4FmfnUKOC15tyrjTxRVlSY9AtltDTCTp5y7tz6eNjfjMLmQnAHshkzG/VyyuvamaWK9CDY1Bn0D36jNt35wB2xaX3dl35VK9ZraBmM44jCBeEu6nUqPAqZwBgzi9ASQJTrqFcStU4FTPfF/FYXEo1+ca7QS+jbjwkGk7bFAC64wPo82teH8/c5GqYLMZcXoXiNNFhsRZqbxY8FedZgIgDpYiyNSMO0Em8QO3vwVxdwyxXSO7zZGEnI36QOtPTOq0fHiJ9dt3XOjVg6P5qzdmXMxeIbFrg3hHM4RTqY56goRWngtuWM0tRMJFTpxPg/NK3EwC6p89x/e//Eg6+61K2xNqj+nyB6l32LFLR8TDGp07bidMerSzy0xLXf5Svz+FvPuZiryTxfCJQGjjcgx3noMfPfHzEfuubePYre7j/W9dehrCbZEguVl4ewGudjjPodQt1uYQ5cNfMWvzW7/8arhef/nQUkn1pJtT78bYveyIdBGPtMFAb/y2sXUPaOw8Zvr3s3OdqY/S3HxdPmmJDAZJsk/YO4OlS9NWDrRvz+YBZw/GxQRmc24Vwfglqx9B1EwLY1looT9kvQc/PF8KjYX/dP4qv92BcPf+ltQwRN/3f98aLNrNLYV/wRPEVvPR3Ac6d7Wxnt7I307MYQmfFIlo90i9RJItdZYQAW5DjMyGtFx2AFLFb7pYrtFqxtoegG+WNVuRcLBSlBimNtEKuF16jxK5K2CLvpUgpS2GXnN9nWPUAlDUahQBYpO8hsRQAoMXC6454pKXEX7KUf+f1RHgZYqfjUOzmKhgpy9j1d7R2zWGB/HLB7v4o8/1WjrPTDtvlxsOn9CSYOS5AztUXfhE7G/MbWQKUszFoveb9ZLwmhV/T2yLzb+DyXo7pPOfy9whKb7IESdOyG38qRWcszNxOM2SS1hyNePxc4DT2e2yeorszQSJcphKzOkuweKgx+VSwC4ApNKjqsLrP7R2DlcJgLVb3eLnVjgCTEfILA13lWDzk9/ZBmnCZuVSPOmuPpmhnKUZnI4+sXd8dYf5Ng+PfDkC09XGGwljYTHGMxJEV1wcJ9DrFCEB5390L1sJ8//b+whs5WcRVhx55OOSOeBkHp2egNkDHkf8NboeeiwrPs9DjcTB2M3cNuHV37QlgAMBWNWjOD5xpW0CCbU3DGqWRK2kFHFRzwDDmo/D5/yHSslyD5iE7YOqG+R46E4HQXH/qhqsTIz1PAKDFyuuiCuTadh3DuV0AOT1bcVzD2J5raiOMhh8/gNu/ChqdAlemzsAMCIOJiPsuMYv5CqZicFtPZ9ThCagN98Lo6Zq1WpViPgpnSmvQsgS1HUzEPK6uV0hNGEdQyde1bYGq6ccs2hZaKb9Njm6aFnufsIao72ueQM2XGH/GE3FyuYbOmRNTOc7LLlewCSFdtEjPV9j7JA1j4+Jo/roSITlbQJc531du0s2fl9j/3l44N4DCWCTnSy/DmIjmaclap+pyCS9DZS1U8zXnsyBFsJY2t33ealzhiOg2YwQb+yFiXxbbVkLsOA16nBCKPJU8EQUAl1JMfx8XtSkufOJCqegYUuymYs2NiBshpvyXdirysO9eodoQRg5wm6VdbeCMQKK912VSDaUUQNZT+HPbVb/0XAh7lQONSaDXc1FEPBCeb4L7Feu5EBF7dEIEnDC/Bw1iOiZnGYFYixYAF2YlSfgO4DhKomFzDaX7/YS1m1ILwhY21HhVDNv2BMEarHuqtdc3tWkIuHqlMCeMTK1GkmqGfst5BOYfgeJYl1UHjVkANtdoJxSCuQBrqqTJZoAz17AE1mDNwzV7FY6WN3KyAPDlBnRi5OaLjvt5NTGHWpRS/ejfvMbrY8YZHR9Y7AXQPmcbXsFuzJBtQ84Ovx9ouw75OG787e0aFj5vuV69gKJ4UEQcC47GOv4ddVva94pGNv5sbx6/3nWMfmvC395iFOeL2idBXb8vesryX6a9uZPFFy25jd7UAPgt10VvYH+eKD5CCqRcJF+EdxW/oTeLzvhN2nvTKh3exFqFN6XzLHoX2JVUQ44f91dRUCrr9SnyQKSP0s6hxxR7O5HZREftCp7AjcI/sk25uMoNnoX3ZOQ3RO5NT73j+BJz1W70ofdWl/GK3rRdrpEOmacAVmkTCHnkWUBrflvH/dQKZNz/8TG0gk0Ue1SAV3gjcp6FvN3d29wm2scLklSxmrm1fluXE7qUoHOCTYPwj2fYUoT4vhPvhKJ4jEkU2jF6nkWXKyRprKLO5zOZ4oksUV4ewFrAvsJjtMuG7GxnO7uVvZmexeBtv7ENIQtyYzZEmLXBgi6UOlbnuMSbnLapmCIOWUQcjwB6n71lKbDuk5ZQomFcRJ+09lkBaN1TA5f29TROo1JsuN+KBkhc5m1HfRV4StPeucQ7kGKtYdvtKPPIQe+yZ2lve7OXIRG9UpcNgbX8fUTU0vOG8iwUkEmZd5GDnPaotMOMC4ZbC2HvuADNM4BK/ztTZFDu+HGJfLWvkY8yfvNGRDtdrpGuMu5DxH1pRxnaaQYtdAN5xuXeawVbpBw8lXHJUrSzHNmVZHJC9Wh5j1i/xI1DV2ioMsPalZ3rdYZ2rEHWorzjPIsRocs5npIuMpTHrl2pIxuOOTOJ0E4zNHsp0jzzmbxmP8XqnRbdOIxBfZAgKTMflzBOVnF9qJFUCqrKUR06AJz5upao96pOTf/zcBvAN62xfbSnsFEB4SGWbEjb9Tkl7YBN2v2G8pyPHXEgYFT0iGt5X1cCHmcHjPHVheg6j4hE04BqeUCl+rBhCv0k4X1j/dDG0doLMa70N017D4oqCk6FdibwXAi1v/B3uElEFQVPlq0J7ZK2th2oCW3QVefbQFXEFN20QNNs57R04+v3AwAVkJvIUnbtE8UQ9dJN5ppARc5IU9cu3xbhtnSmawuq237KUyko7RTMEt0Xq6pb6LL1Fbw2TWDzFDBA9WAKmXap6WCKjOMLUUWvKRIkhwdIlvAISkGTUtMhqfi+UXUH7eDnyToGkBGS0rJS2CIaw5h92zeWRYqsVI+CMyvJdQK9DlkbvU6h6s4vLySOk1QKi7c1ihMFRxXSn8xvYW/OZBGnFc3m543UZdMCpmOFdUFMRjUivsRafldVvZTo1mO6NCmAUMbdtrCX10zwqwLGQCDLNqJaj1Obpm48R4XtDNR8wC4lEoVt6//37WhbYLEMcG9Jzw5SmWa5Yq3W5Sqkelsu1SaRE3Dwb+GhYPk8d9worSkpTQBIT90+RP3xWq85TbslIBdDuKXf6kr54jJUFVjzteE0q7B/tR3sfM6QdTexKOVSp03T4+8YPSl9atqPueKJwpZrTtXGzGXzFZIupKLpegHtJqFiXXlcibUWOk2hJiNYt00ZA+Xg6nuftMxO5cZKpwlovsL4CWMxkouV10ZVTWDK6jKF7KpxqdMsjNOWyTY9XUAvMuB64e/BfDrCwUf7UJdBOnEEQF0uoQRH5ArJVJWjOFFIn88xaRnuTZ35KUmdvowpS2vYAd9B7xjyVlbugciZfQmRSM9WpiytQWni6zqwLEFFDlpIkMm9/QQ0FWcHItAULRY9oFQMpvLtWa2YM0HVQe/CtZ2P37/QlGcDUNYSVHB9CzlxG1oGshtY68ForoMBFNU7bt7bXt8dI7sseBkSn8+dcytTVgQik37b6dhjTTxATUBhbqKyexOWjFxX/ndmNuG/K+cJOCvfGmG6GPCCKAUzzZDUDYPAzsI42tkY7f4IyTOpSylg9sagdQMzKaClIM5aXobcmSB1WBMzm7BndHmF6/cS5Gdc20Gdgck0UgCrt7hPIwK6MZ93dexqinJCOyKMThUm1npJwenvjLZ6Fu3hGM0sxfhy5Cfj6t4Ylx8AR9+dhDG4P8II8MsQCWZWhymMBibtBGsHFqMOMB/dPmy5C3DubGc7u5W9kZ7FT9SiQiRvN2IOBttNXEw1yIW/aq5/iC6Nt8drUWMwxD7wfi8oThp+lgIsOY6BTz3eut3xeAwK6nrtHhbZbfkdWetxKXERF3XYuBY0/P0A80LDNsQFaHbzvIi9DcNLP+psiFVY+II28sdyeA4gbDO8jYztfX8jPkL2iYPgUoA2xJpE4yJfkeGlJHWGx8kd81Uozb/ek8WLgCkDfAHjFmgTj3CD9YJD2wJFyWa+n7TyOIsYzSl8jMP29NoZt1dRP2IuDxpFSEIALwxfbVueWRNo6IGAOdGa4cM6irBrzdiDKEvDSvZq+7FjTIXrq02C6FJMVjMMUJLQ+snvUg00jOK00bh1RR/NyH1QTF6rGKsQXw+rNUyioGO6fE2b1zPCNQgy1Lr9rLVox+QJcslYmJTp/dvc/S5VHl8hSM2uYIXzbkEwqUI7liyN2rg3ZaxM5lCwLgje5Qrt1PhzyzaTab9NsiFtzvwjNtXoMocrMXiltcVrwWdBRCcAlgBOX7bv18zuYtfnnwZ7nfv8nrX2+DY7vhaTBQAQ0b+01v7yT7odX6Xt+vzTYV+XPu8CnDvb2c5uZbvJYmc729mt7HWaLH7tJ92An4Dt+vzTYV+LPr82MYud7Wxnr7e9Tp7Fzna2s9fYdpPFzna2s1vZbrLY2c52divbTRY729nObmW7yWJnO9vZrez/B+qwtZPb5d1oAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.56851196289062 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-05, 'kernel_type': 'untiln'} is: \n",
+      "[[1.10594004e+03 2.10000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.10000000e+02 5.64351260e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.10594004e+03 ... 1.12194004e+03\n",
+      "  1.12194004e+03 1.12194004e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.12194004e+03 ... 6.52564140e+05\n",
+      "  6.34680592e+05 6.87400683e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 1.12194004e+03 ... 6.34680592e+05\n",
+      "  6.20169286e+05 6.70268990e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 1.12194004e+03 ... 6.87400683e+05\n",
+      "  6.70268990e+05 7.47926368e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.6423282623291 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 0.0001, 'kernel_type': 'untiln'} is: \n",
+      "[[1.11443304e+03 2.10000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.10000000e+02 5.67525248e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.11443304e+03 ... 1.13043304e+03\n",
+      "  1.13043304e+03 1.13043304e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.13043304e+03 ... 7.36259862e+05\n",
+      "  7.19574373e+05 7.87103075e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 1.13043304e+03 ... 7.19574373e+05\n",
+      "  7.15845481e+05 7.90880330e+05]\n",
+      " [2.00000000e+01 2.00000000e+01 1.13043304e+03 ... 7.87103075e+05\n",
+      "  7.90880330e+05 1.00811186e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ad7978>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.55571222305298 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 0.001, 'kernel_type': 'untiln'} is: \n",
+      "[[1.20266442e+03 2.10000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.10000000e+02 6.00553482e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 1.20266442e+03 ... 1.21866442e+03\n",
+      "  1.21866442e+03 1.21866442e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 1.21866442e+03 ... 4.27708301e+06\n",
+      "  4.13809272e+06 2.42881323e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 1.21866442e+03 ... 4.13809272e+06\n",
+      "  5.61898311e+06 3.51080329e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 1.21866442e+03 ... 2.42881323e+06\n",
+      "  3.51080329e+06 1.41627688e+07]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.49629402160645 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 0.01, 'kernel_type': 'untiln'} is: \n",
+      "[[2.49708473e+03 2.10000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.10000000e+02 1.10519195e+03 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.49708473e+03 ... 2.51308473e+03\n",
+      "  2.51308473e+03 2.51308473e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.51308473e+03 ... 1.29478524e+13\n",
+      "  4.60827617e+12 8.35220270e+08]\n",
+      " [2.00000000e+01 2.00000000e+01 2.51308473e+03 ... 4.60827617e+12\n",
+      "  1.18843721e+14 1.50955429e+10]\n",
+      " [2.00000000e+01 2.00000000e+01 2.51308473e+03 ... 8.35220270e+08\n",
+      "  1.50955429e+10 1.54483315e+13]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.399498462677 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 0.1, 'kernel_type': 'untiln'} is: \n",
+      "[[3.84519933e+05 2.10000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [2.10000000e+02 1.17152601e+06 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 3.84519933e+05 ... 3.84535933e+05\n",
+      "  3.84535933e+05 3.84535933e+05]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 3.84535933e+05 ... 4.92112617e+37\n",
+      "  8.37618404e+32 2.26451167e+20]\n",
+      " [2.00000000e+01 2.00000000e+01 3.84535933e+05 ... 8.37618404e+32\n",
+      "  2.18232106e+40 2.59595332e+25]\n",
+      " [2.00000000e+01 2.00000000e+01 3.84535933e+05 ... 2.26451167e+20\n",
+      "  2.59595332e+25 5.23864564e+33]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.5908842086792 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1.0, 'kernel_type': 'untiln'} is: \n",
+      "[[2.45390138e+012 2.10000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [2.10000000e+002 9.35285850e+019 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 2.45390138e+012 ... 2.45390138e+012\n",
+      "  2.45390138e+012 2.45390138e+012]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 2.45390138e+012 ... 1.08411366e+109\n",
+      "  9.26210691e+086 8.40458492e+053]\n",
+      " [2.00000000e+001 2.00000000e+001 2.45390138e+012 ... 9.26210691e+086\n",
+      "  5.41627730e+114 4.18357802e+069]\n",
+      " [2.00000000e+001 2.00000000e+001 2.45390138e+012 ... 8.40458492e+053\n",
+      "  4.18357802e+069 7.47982938e+090]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.56008577346802 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 10.0, 'kernel_type': 'untiln'} is: \n",
+      "[[3.31357611e+024 2.10000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [2.10000000e+002 8.48576888e+046 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 3.31357611e+024 ... 3.31357611e+024\n",
+      "  3.31357611e+024 3.31357611e+024]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 3.31357611e+024 ... 1.49160895e+247\n",
+      "  1.94859563e+186 2.37080912e+114]\n",
+      " [2.00000000e+001 2.00000000e+001 3.31357611e+024 ... 1.94859563e+186\n",
+      "  1.42724125e+253 6.32431006e+148]\n",
+      " [2.00000000e+001 2.00000000e+001 3.31357611e+024 ... 2.37080912e+114\n",
+      "  6.32431006e+148 2.28033684e+193]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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svcyzADqMeRYAKkdYAAghLACEEBYAQrIY4DSzf0p6W9K/UtfSsI1in7sg533+jLt/IvLALMJCkszskLsvpq6jSexzN8zLPtMNARBCWAAIySks9qQuIAH2uRvmYp+zGbMAkLecWhYAMkZYAAghLACEEBYAQggLACH/A5iUgQPanlS2AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.38389587402344 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 100.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.20968152e+039 2.10000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [2.10000000e+002 1.11658436e+079 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.20968152e+039 ... 1.20968152e+039\n",
+      "  1.20968152e+039 1.20968152e+039]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.20968152e+039 ...             inf\n",
+      "  3.71749323e+299 1.83695983e+186]\n",
+      " [2.00000000e+001 2.00000000e+001 1.20968152e+039 ... 3.71749323e+299\n",
+      "              inf 3.78335134e+241]\n",
+      " [2.00000000e+001 2.00000000e+001 1.20968152e+039 ... 1.83695983e+186\n",
+      "  3.78335134e+241             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.72504329681396 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.08669566e+054 2.10000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [2.10000000e+002 9.00962128e+111 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.08669566e+054 ... 1.08669566e+054\n",
+      "  1.08669566e+054 1.08669566e+054]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.08669566e+054 ...             nan\n",
+      "              inf 1.08780878e+260]\n",
+      " [2.00000000e+001 2.00000000e+001 1.08669566e+054 ...             inf\n",
+      "              nan             inf]\n",
+      " [2.00000000e+001 2.00000000e+001 1.08669566e+054 ... 1.08780878e+260\n",
+      "              inf             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.86174750328064 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 10000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.07503100e+069 2.10000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [2.10000000e+002 8.81722771e+144 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.07503100e+069 ... 1.07503100e+069\n",
+      "  1.07503100e+069 1.07503100e+069]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.07503100e+069 ...             nan\n",
+      "              nan             inf]\n",
+      " [2.00000000e+001 2.00000000e+001 1.07503100e+069 ...             nan\n",
+      "              nan             inf]\n",
+      " [2.00000000e+001 2.00000000e+001 1.07503100e+069 ...             inf\n",
+      "              inf             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.79325127601624 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 100000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.07387068e+084 2.10000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [2.10000000e+002 8.79820433e+177 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.07387068e+084 ... 1.07387068e+084\n",
+      "  1.07387068e+084 1.07387068e+084]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.07387068e+084 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 1.07387068e+084 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 1.07387068e+084 ...             nan\n",
+      "              nan             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 81.15413236618042 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.07375471e+099 2.10000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [2.10000000e+002 8.79630413e+210 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.07375471e+099 ... 1.07375471e+099\n",
+      "  1.07375471e+099 1.07375471e+099]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.07375471e+099 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 1.07375471e+099 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 1.07375471e+099 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 81.09764790534973 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 10000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.07374311e+114 2.10000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [2.10000000e+002 8.79611413e+243 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.07374311e+114 ... 1.07374311e+114\n",
+      "  1.07374311e+114 1.07374311e+114]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.07374311e+114 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 1.07374311e+114 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 1.07374311e+114 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.93342137336731 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 100000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.07374195e+129 2.10000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [2.10000000e+002 8.79609513e+276 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.07374195e+129 ... 1.07374195e+129\n",
+      "  1.07374195e+129 1.07374195e+129]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.07374195e+129 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 1.07374195e+129 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 1.07374195e+129 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 81.38548040390015 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.07374184e+144 2.10000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [2.10000000e+002             inf 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.07374184e+144 ... 1.07374184e+144\n",
+      "  1.07374184e+144 1.07374184e+144]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.07374184e+144 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 1.07374184e+144 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 1.07374184e+144 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 81.17287921905518 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 10000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.07374183e+159 2.10000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [2.10000000e+002             inf 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.07374183e+159 ... 1.07374183e+159\n",
+      "  1.07374183e+159 1.07374183e+159]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.07374183e+159 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 1.07374183e+159 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 1.07374183e+159 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54822470>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.61680316925049 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-10, 'kernel_type': 'size'} is: \n",
+      "[[5.12000e-68 6.40000e-69 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [6.40000e-69 2.20000e-68 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-68 ... 5.12000e-68 5.12000e-68\n",
+      "  5.12000e-68]\n",
+      " ...\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-68 ... 4.48896e-65 4.32544e-65\n",
+      "  4.79584e-65]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-68 ... 4.32544e-65 4.18176e-65\n",
+      "  4.62256e-65]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-68 ... 4.79584e-65 4.62256e-65\n",
+      "  5.21632e-65]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.43043065071106 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-09, 'kernel_type': 'size'} is: \n",
+      "[[5.12000e-61 6.40000e-62 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [6.40000e-62 2.20000e-61 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-61 ... 5.12000e-61 5.12000e-61\n",
+      "  5.12000e-61]\n",
+      " ...\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-61 ... 4.48896e-58 4.32544e-58\n",
+      "  4.79584e-58]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-61 ... 4.32544e-58 4.18176e-58\n",
+      "  4.62256e-58]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-61 ... 4.79584e-58 4.62256e-58\n",
+      "  5.21632e-58]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.47289609909058 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-08, 'kernel_type': 'size'} is: \n",
+      "[[5.12000e-54 6.40000e-55 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [6.40000e-55 2.20000e-54 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-54 ... 5.12000e-54 5.12000e-54\n",
+      "  5.12000e-54]\n",
+      " ...\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-54 ... 4.48896e-51 4.32544e-51\n",
+      "  4.79584e-51]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-54 ... 4.32544e-51 4.18176e-51\n",
+      "  4.62256e-51]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-54 ... 4.79584e-51 4.62256e-51\n",
+      "  5.21632e-51]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.56435132026672 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-07, 'kernel_type': 'size'} is: \n",
+      "[[5.12000e-47 6.40000e-48 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [6.40000e-48 2.20000e-47 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-47 ... 5.12000e-47 5.12000e-47\n",
+      "  5.12000e-47]\n",
+      " ...\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-47 ... 4.48896e-44 4.32544e-44\n",
+      "  4.79584e-44]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-47 ... 4.32544e-44 4.18176e-44\n",
+      "  4.62256e-44]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-47 ... 4.79584e-44 4.62256e-44\n",
+      "  5.21632e-44]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.49120211601257 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-06, 'kernel_type': 'size'} is: \n",
+      "[[5.12000e-40 6.40000e-41 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [6.40000e-41 2.20000e-40 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-40 ... 5.12000e-40 5.12000e-40\n",
+      "  5.12000e-40]\n",
+      " ...\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-40 ... 4.48896e-37 4.32544e-37\n",
+      "  4.79584e-37]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-40 ... 4.32544e-37 4.18176e-37\n",
+      "  4.62256e-37]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-40 ... 4.79584e-37 4.62256e-37\n",
+      "  5.21632e-37]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7fd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.39314007759094 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-05, 'kernel_type': 'size'} is: \n",
+      "[[5.12000e-33 6.40000e-34 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [6.40000e-34 2.20000e-33 0.00000e+00 ... 0.00000e+00 0.00000e+00\n",
+      "  0.00000e+00]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-33 ... 5.12000e-33 5.12000e-33\n",
+      "  5.12000e-33]\n",
+      " ...\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-33 ... 4.48896e-30 4.32544e-30\n",
+      "  4.79584e-30]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-33 ... 4.32544e-30 4.18176e-30\n",
+      "  4.62256e-30]\n",
+      " [0.00000e+00 0.00000e+00 5.12000e-33 ... 4.79584e-30 4.62256e-30\n",
+      "  5.21632e-30]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.39752626419067 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 0.0001, 'kernel_type': 'size'} is: \n",
+      "[[5.12000003e-26 6.40000000e-27 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [6.40000000e-27 2.20000002e-26 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000003e-26 ... 5.12000003e-26\n",
+      "  5.12000003e-26 5.12000003e-26]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000003e-26 ... 4.48896003e-23\n",
+      "  4.32544003e-23 4.79584003e-23]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000003e-26 ... 4.32544003e-23\n",
+      "  4.18176003e-23 4.62256003e-23]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000003e-26 ... 4.79584003e-23\n",
+      "  4.62256003e-23 5.21632005e-23]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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Mx8AigZvOsyxoNEpvfbUQNy346ABkAVJ1DXif3uCARD+Yk2Wh4+w8gDn46EDaPTkFA3n/oW8hY2rjdafxCP7hIWg2T+Oqa7G0Ct8INY1YfuF34aIB8300ZC972csNC/FVTPYblgf0hH+c/szgd2+UVk//BpJfYFc6u4vaL3+/xRJS3wKAq9Hq3aRcwaFLVZWss226q9xElurWcw3Ww2QGD9LqXcQfepN6DcmAXnCU+3OGEs0s/8aO/ZTyW/xtnPCLnQZwf7chVnQSzBbiUm0UdPJ6jEZNDhBytDuCdCil2DNAhZdaJQCNoqntnBxrlaY+pTuLibollfm6hL1Gb6t71BFI25Ou6y0M6ggEzAI/RCKjD8M5eTbl5141r9BOCdCiyiW9mLNwdXQAK8BsMgYvxenJ7Xr7/J1D2OuOjsCLRdSJqlA5zOqrPhDdogWnONW1+B6ODqW5dStbmKqCjyA2J8WEeqUAGrjDafyNqMPp+hRh5Og4flcJewcfzi0PQVyJd3lIytRmpTeL16JLbx11IPIl3iDbSFTVWVk+QPZNhwEnoXn78SWcUleSId3JAX4TdeM23MjRL5GwDL4rjpWISOIe5mEntUzUInZmia9QpWumDsWIBQknhoc6YhCGrMfLStv2HLWZA9ter8JJzJvgUNUFK0Rr2ES7tkLKg0PWRo80SkZ6r9rrd02584vFG5PrktFc1F48vsWc1EXJFYQp24hfLtvvrrKNV2FoQWUeXEBtpGi43fO4OcuoD/f/tjR49tSNTzrZB9VsQxgF1LzMs9iVb8R89qtV9lmBZD2AnBWbOjAQlSJnol36+6G6Ib0XT5fmwAICLchsz+69l73s5Tbli2tZnEfNBsj+VsOO12m/d9w43mxfRQXwtA3R9bygc9uGS78Jn8WQjyH7mLZIQ2UCB3EWtl0yY7qEz6L0p9i+tN1ISBv7MIlpPX9RFajm1LfSbZ+/83wW0yl82EZkxLjRbzJAxVe5iA9Bl+qZsK2inlk9Qz6LOiX1WRkkLXZpi/au+iwuJRc9HNvQnqX/Qv8c8pcMsWUPcVJu1cWY4LavIoP0XLdEeVNn+tkH2/gKbNZqOZ7YLmc+ml5/qhvSeLPF9Dzdh0oOugq9RRCIzuZsHFZ3M8e2fwq4DWneOjOSvyTLqaHgBPRWH20rLW75FqHAhVR5Jmvc2rAHuL9oKujP5sewT/ia8zg4yZHwbirqtutAXTfI/9lf4L2gc9XZWwxnF3m3FouL5KIU9fMeKtuGzRthTSfO+6C67odwTQo5b9ocwq1wbL1ZdAEaWpyI+oSyABSuHFW1cHEL6rJSpJNH2DuKm9zCvSfjCCXPbjz2W6NFcT5gohrmrR7f+CEVPlopBv6dpagPOP3cwUGEY6eDBAop4yCXPYxUNynSoDqYqFR0jQR1M3JcA9WvnhyDz2amT0mJjynqBlEZozGO5NhmA163oIMpAMC/ej3o0HSTsfS5XMXr46YTuEcPAZOijqaRCJorFou6zgF2erzb3RPx7i4WhQOp/3162OUjZWjLrW/2sFDEB31gFY/tE8Mu3RZhmdXkJHM83MxxATKo0agvhdCgz7kVqMr5LKB9EPfDyr3ckIRMTA/w8CJEowak5xSL07nzrWa10dfmiwCICFKNJOg5EWkbjjHQCw1i1IAGFiuq65hHYt/C1NTy4KgZX1Ux7wRNA0J422sOSrngkYSPaTpNlgFzShILiwUtliY3JOApQuIYr9cgz9IGALw+xRC5DdW1oD7bNi1io5EgP09O03njUZg/hXuH/5WOz7OgVoFBC+Q82Ts497KXvewkdx7BeWflLtQNUTnHSduT83JqzrXECkfjHawbUrJsZW0OoTS31Q2BWnZDod0hZ6Xp12BKdqqizrvXDelxVHiWKuqWMHirz4Lits86eX9z8/dx4t9lBOcuMrQNGfKsK51coMHLaPWGRNPTNZV908Y06qz7usmhxECWQu6Xq8x/4YIZGlPUNe1dH0yrrwup7jaDVfklRgkuzus2ogl1n+pXKzlPbzzjLAM83HQ6WHfTbk/c4RR+JuCmchuyjSGcmlHPZ0GjJnnyg29BMis5nRvmgdsNqK5in0K1l29D3PEReL7o913XQrdXVfCL9L2bTkF1jS74G9yokT1/iE5kIL/gJ9IHU3wAso2oPvwA/PoknMrRRxJT1C/YhmCxBD18AADoPvlscMGrHhzJw258Mm48Bj58D86kqNN4JGnoQ9uQyRh8epq2IZ5BL3ZfAvaWxU3I27IstlkAKnax3LXfN21Z7AI2O0/nm7Yshn6z7Vj4rV0Ib9OyiO2b/i9lWVC/1ullLIu9z+JdkusmNN1VeZPj2tXhV6b8fwHk3m1D7mSRoaE+tum4K5z4ItnFMoncFRe/tS8sMmSP32T5wl0fth0wMtvn/JwweK9c4jnAg2zcYZs0VGToNsoX2tC24dX0y1L/Lv/f/jzAA7Kv9nDvvexlLzct986y6NXzuAhPUf42SGZlAIkjUveOq1UCahV9UV0nB2e7Fmdm2GsmLstJSvTRPpsaNBqBiITDUp2O6xZVSFHuTiVm7sbjwD5dZftM4aIcpTRoO4a6SQ40QNKmQ1alpo1HB522W4DBqgcPomMvskJVLnPi0vGxOMqcywA+vNlE2HM+8bnjNDFlVTHbMgKGtB8FZYUUct60wkOJ4BhtN3JdqiqmZ7vHj8CKObC+AUfCc1lV0YEMQNLCmxH8q9dxnOrgzOgBABnrdAKehd+H2hv+7AzVv/t14LPn5twKWCVeTZ4vE/WAArXqStpcrcGzBfDBYzn+ne8NOpjdgyNQ08C/eh2ZxOsvPUX3Ax/C/ZvvJwtxMgEvl+nejc7kkQDAlqvsHqHPDX/KBXLvFgsAw2boJc3hHvek3sg75E6X2YpDTrXBjMBA287av+Fl5PUa1tnMJsUaJedniLL0IOJdJwi/Uk9mwy1hzjVRBxW/WvWiLLwJPJc6Z/O56Ge4H63OQ7kh3G7689R1hhxYFSh0Wq6SrvoQeaOPLTFwdpYiGAWCseQWZc+yUHU+d07qvNu0bxkU4OdpHrvkMKWXJzlytKqkcJBGSNoNWLkwdQGK2cUdeLmCeymfvcnfSLk2Hjybg6sqprQDgJ/NUX32Ku+73QxycGK1Shycdnt00fbHyP1cLG5CrHc87vfzh3L7b3Nk5tBGdIizgj1ni5G9SbkrU5ILyHXZ1pDfpbcfTXr2HlQebtdCrW3/md7mhs370zH0E76G6mFwOzBHXa6T/TxYU8MuoutW5lGJeVS0xklJgtv5iNKM7Vv0ZLZYcL5A25fFfJHlh1DgJ9WwMHedhFOZ0+KqD7EXiHwkzxnAdrBnYLNJi7su+Ou1WDpKYAyEBdj3SxxopKi8by5Rq/X+LxZD4bfLWBlFuMzmUPQIe29YssxSR3Ljm5swAoPK5LA3LGW4j4jkwWNzU+pNp/UrANhkrh7IiVz2/aX0sGKZsuy5kcHLg2HmMIKugu5VBeCa5DdWL0eyEFwQVYmLh3OCibDnh60TXZDxHH/nXCQtzkiJ9Zwbkr2Dcy972ctOcj8ti8uAoLa2UWRbakqyeSsOwn2BfpEh3Uva5gPCsszcpKYW/U3hGfiNOKC8B881qUkcrn0HJ4MqAqjJ99ra/jWLDNF4LCYvkHFbxgQrQJKeFgsALiuyi7ZNfAzlXIfSCEByLmdZnKYUwLYiQ5mzruvEpA+ITwCCmDybpbe1dq/jI8q4H2g0kqS4eKy6UpEhevwovXU9S8IXrWKxY16tgcqB2JQCqENxpE0nqNP3Hkm7q1WvOBXISQZr4OWMDu3DA+DDJ6Dvm/PrGqT3lnFwoq4lnb0oMoRNf8u4Ta61WBDRdwCcQuzJDTN/k4ieAPjbAL4G4DsAfoaZX16nnx2VyReQC6IkWWUwMpWoNErSruUus0QzWmvDVhbrulBPInc26k1u9/rU1JKKTBLJiBGKrks3kYV7d11IlU5RGoSHhkaj6My0WYia6gwA1EoVL+sB51mCXHOHVL1dF4uDA7nZdG4CcXD0sgOgh8fJJxC8+1Lwh3pZn7r9cONxisTogqb1R4C0EEwnAo/WB+JgKoto18X5wnQiWZ5dl+pvAMB7j0CWvBfBDK9rYDYH6hq8fh2vJR1MQdOJ1N0AJNN0PJIx1DWwMunslQMdHYH0+uoDt1xh/ZXHGG3M9a8rwFXw70uEw53OwEHP7lgiOtw4cO1QzdZwryqsvyyLRfPsRSLfNRnE9OA4ZdWqE/vxQ8z+2EMcvU4V3PlwCjqbiw5A9I3wwQRoN6LL8WHS9Wz3xeImtiF/mpm/wczfDJ9/AcC3mfnrAL4dPt9dOWdvubX+6C7NDiZJ0fb+yr7cOXq9KdRgyYlAIX9jqP8Sxoz+/MXf30SN0fPaCHkmg7reQn3TnWRIDzL/HLY+jeddb3Yo2inGvO16XUGulRsSLItvMvMzc+x3AfwEM39MRF8G8I+Y+UfOa+dauSFXdXCWtU4DmUxJTpNFHay1YklybK6EqhUS07Jj0aGGxDUBsU7cZAx4H2PoZaJYFLt1KKwZS66jY4j5CyWyVMdSJtSNx2n7YRPJDA0cjUay5WDO++s6SfiyTE42YY1zKwLAYD3YrPyCfg45GHLM6GJwFpHWv6ryhU63LEjhXYSyADRq4C1xTUHmY49bbIvF2dRf/hK85ZQIoVPlqODNJjo0Y6KfqUzHyyXcg2P5+PxFP6IT+tYaqpGE6OgI7v0n4OcvzXwI8U4s4aghW0U+t222dfzN2a/j9ebZG8k6ZQD/gISp5H9n5l8G8JSZPw7ffwLg6TX76MvQ1uKSq2dWvhAIxXpT3Q4eQg6HLYkWIAIkTi4LTX+x0Bi+ZYGKW4/FMivVF2+iAjSlJDcZSQ3l5QBtNqcF3GAR4vWGZcqea3kiVX83HvfBXkQR1API1oDPvOzBLZFKW4Qs7XxYUh19UJzLa34gLEQFKAvLlYxBCyOPmojxoKpKD8rxcbpOGTdnyMSsnACgwjk0amT7pxm0O4CyUICyeNOCnzxM+Akg+GcAehCyTudLUF3JFiZsE7muxI+xagFH8I8l6xQnpwCvU8QpzA0dHggoy/jB3NEhNk8fojqbp+LQ45H4k8JLIN4n4xFIizBn98gb8lkA+FPM/BERfQjgHxLR/2e/ZGYmGqD9AUBE3wLwLQCY4OCaauxlL3u5bbmxFHUi+isAzgD817gP25DSEjGkJwCSR3wbmOki8hu7zRnYx5fM2Mr92OOpjEVyED/3tkd2TBkZa5dvnaz+5Tzo29nCt62O5m2dAEbGEgufueuSxVQiQb3ZOgA9vo/YT4mcDJD7qJsdo5nDaC0R5Vsdw5kRJVgPNBpFQFRGdSiKZ3poZCnTwXeoHj/OYORaZSxaizoPZgziUPeJ+yI4iv3ZLHGA2i1PiGzYKm5uMgE9fCD8nxn6N4HAEq+FS6AsMze/tfq7eO2f3+42hIgOAThmPg1//1kA/z2AXwfwswB+Mfz/a1ftY6tkfAohWlFS2F8UDdEoQGAOovFYQpXheHd6Gh/gzK8RwpA2dOam00SqEvqqjg4l5GfQdDQaidnrCHx6Fm8mv1iievIYYMbmM3H/uMOpbFUqMcsteQ2NRqJLjIaELcRknEVD/OtTUFPDL1dwh2K9+WBG61hcMEn1ZnePHwOa56LbhqpKEQgA9PihkL14Tv15qarlz2bxBmUFFxGnMnsIfpHgiItEtyYawjYacnQIPpvBr1axxB9Np+A2ZMjWdary9fQ9VM9e5j6LANrixUJIcNS3QCS5JMeHwPc+juOkcdhu1bWEPPV+CdEQHyDcGg3pXrzC+hs/hPEffB7mgcHjBnQ6Az99IiqcLsBNDWKGfyDz1Y0lhO5WG1QvzrD82nsAgPE//w54sZQ51zEEXTFq4D9/Hq87/cC/hdMf+wAPfvvTeN/xdAx3GqIhzLLdAcCTMdy6Fb1sNOS7ptL7BXKdbchTAH8n3Bg1gL/BzH+PiP4JgF8lor8E4A8B/Mw1+hiWQbq4qyMbBYYd/h6CwuqFuAQ0NrbFPkGSNUzoDexXPzP3+/Y8hJy+fbHj1jeTha+zyckYgnFbKLk3loL3+fHqil56lvmKc6SLeZhDynSi+MKwcGsObdCmu0z6FG10AAAgAElEQVSW9qCQ6mE+Z22qvllOEwAC0AU9YvlHsaLYOGXPjYzpvWRzpExf2u5N7B/uPFPWVn6IAYYm9Zafy8sw9PvsuGXKdjE6EWXXxJuLODGtuW1MXxesjchGrSZsCdS5RALQpWRoe2aBa8i3FWXSmADDCvO7yL6VZi9RZHpIt3O4MssSBTEqxD5mrsZ8Cpu4dsU5tazf2XalDJMXFIt2q6u0inaskSejKGFgz7GlG6SLc+77gfFdpor6Hu69l73sZSe5v3Dv+HfwWVw2dFrwI1JT5w67TmLUmWNOa3mUcO8B9i43HvczSatRRvSaeBc3cIdTwHNEOcrvO1PHok7njhpwVzBKQ9/q14N7u4ODzCEn000SKlTeiOBXIIsb0Dd01yWzOTqDHdzE1NwIc0AhZT/qA5wL99a3b1m/Q/V0hwcCnXa5gzNmYhbiJuPIEQEA3F0N7u1+6N8GnhmQcl0LdiL4WAQJKz61iNRt6rCd8+Jgffq+HP/+Z2EOTRjaGbj32SyOvXryCPyVD0Hff5bmS30t0TEd/GVNA27bHtybXu2+BNzdxeKy+R/Ml0LmlV7tnplf3nBWfJdnkw+Y03b7EiMKlr+h0MEvlrJYWRi55pw4J9iD0BZ3ftAs5U3BGcGc3Azl+Vuo33oUceTA3AGWIfz0LD1M1gcQFtu44FquC1viT3EcxrOfvsu3kGVKdtZWeKB0sfCtpKhL8SCOv2fNlfDiaFXdeLkS/odOU+bXcTHlMH9pHghdu4mmfFx0mYFPnyVOCUdxbnybCg+JggyyDt2uA5pGuC+0H3NPxMUaiAzkdivhT8/gvuuzeWTvk1PdsJ8TkdyT7IGZ2aL53beCd3ex2HWhsE/tZRyQ1o9gUtOztto246WIXBe7IDgDYpE95/v5CPraZGhOqkZAhezty5tNInqJw2VQVeyTbxLBWdc58U6YKwsCUwSnXVCJGYzw4OpCaR2aGlkCUjivbvLFDUAZrrYIzthXQG3GFG9FcE6nAmrT0C4g34dIF2xdUg1j2vwLZUAzDN2ZbnUN3uSwdm7XApgqdIb3qcqYRXDqWz0mEYY5CVaIf/4yOSyjc7ITX1aJ4ByPQY8eAM+NVVNV8mJR5KbOdVXBaWlDg+Ck2e6eiLu7WNy2FEQzqTxegXMY/C3HNzOAQcdRhiEwsO7s4bCrelFDU815jm+MHGsx6Bz0HTgbV9Kzd3582+W69xy6YT4yJKpZTIbqrZYRHCX9Kc8dwoqwpTEsPscH3VpndjE/m6UHvcRUhHPdxJDOxLog4feWYQqFbhS2owNlA/zrk6xuDAergRV7odERTn1aHARvNuBXLh+bN1tY7+C7DYA2tywWS9CzF3nNGp2PsNhZwp94T5prbK2/i+TOLxaDD0WZXRrPbfvfb5OBFPW8yFALcMHBGSto72BZhNqpmQfcvIl7ORSGjxOA7GnV7C4WCqC6PcuiSbiFbAEwJDOk1bi9qYEazF+7SMb5ZA9Qg1g7VS2EUMcim7fzckOiZeGybY8We3bTiWwtnMt9WBpxqK1lEXJDjL/pqpaFe3Cc5YYoVDzmhtg3vfp4XEhRZw+s1qDD4N9YmtyQeCH9oGVBkzHce4+TNRKuH6/bNH7tt3KRVu+qlsU+GrKXvexlJ7nzOItLyVVo9ba1AcS38hCm49p6XYDzkD+pZ7pfS4+ryHl6bgHC9SpxbQPMXXYMO9cYMfSIunXQqECpm9XvqnPaQw9vmRsLcissmN62N7Cyx3OHMCBE0SLujWVIBsZ3GZzFnd+GDMpQKYDLykCKuvyhDsiQot67CbrdtiG2pJ0eqyhktwZAktkK2RqoAEJ41IMq1dFuWZrgZ3kDKeqUzNgowVFmcx0i6tDkHhAEmMQdspT7OAeWWTvO0TnbkNEoHlMHZ5aiPp1K5CM8RKIWpxR1l7Y9RBL2pdEopajb7cfWbchQivrTGH4FkAiHhlLUhxycq1WsdSop6l2+eDgCUX8bUh0fg957DLYOTkdZinpsRyNrXzgHZwab3fL3RbkhhqYuHCicnjwcbtQbUW/GtQ/7xPztRJXLH2hA9u2Kg9hs4gPoV60hmFWHYhVqktRZYWMECHmZ8CXNp7okAODnIfmoRVosMsyICdWuQ7KWRjpgfLiOYogPANx4BL8OxXcNFJm8Fyr7bAFIae56FVQ/N50k3EKle/pRVhZBsQ3MPv4uzkkBh6aDaQrLWoyI5ptUVWLRhuz5oT6V0HdkKNO9fzyZ5HzLqkUEzx58dAAKLGIC0XdA42OEAyEvhYBUNyTwU1BIv+epFiv2UjrAhvI7wD1+KJgQZilTEMbbvXcM9+okHxOtRAe50PLfWO4Lns8T1gMAlm8uRf3uisXKD31dvNGiY244oz4/13MeyRjy6ivmocQMFMlfqiMXxXkizLv4PztWmvldqkui31OMZuTh0Oh8Ledhve6T7nTIYNGR+t5RVvskdwbn0sOAQB7oDFhGTiwDE+Hwq1XS2S4E1uuv7Z2e9efREUg5PMnl1yOMNerQmlC11U3xCoui/opuKV68TsWHALFg2o0UYgKkRIEudJqc5ghw8kLgdQuKFm1Rr0R1XSylHbOI+NMzVJ/UWWX4aD2YJDQAElJualk0s4Vo92jI3sG5l73sZSd5dy2Li6R8A8a34g4rrX2jcQJdZacM8U0onkN/N4TmtH1YPYvt1i5FjPRY2a9szfyg7hZqnY8n6aTnCDZlN+dahsRUv0Gpu/OxlIgtbqR/29/F8Zv+vdnPqxBTqgBXzk27iRm/tn2wF+ssw8Q4sN/keqk1MJ/nIf4QEk4UAiYUWm6VFYoeMBmD943qGq3fZIXw2Vnet/poyiS2qgtb64S6lXG9QziLa8tNOEMvaD/mjGgfd0gU75GiA/bLMotz9xvnpqVXyMi9eV0sijeLMpwXYbigmNCtyBUJh6lyYJf7mS4j7+5icdHCUEYBeqCsczDz5HqcmLFPPUWhzEVaso16WHLgkoQm5YVUKeKi+rpqkNA3q0sCpNokPjlIt3JwhpwMNx0PFua1HJrucAofAggRlAV5+22jByAD7Y7gqlGT0IQuOS/lbYvsHO7M73TsJvcBANyDB+CZId+NfddCGlRV2f7eTcagukZnozS1JHhZB7JGUrSdOAaSOiTu/SfglyEZzaAyKdQNoeBcBZD4L50DaiEwosUyRkOkBGM/TOoOp+Kgnc2T8/fgAPjwPZDxO9A48I1GUFb4vxFyYucZGBsOztW77uAcshZ2sRrM9ym0ljzhCHU2AOTQX9tXeHAyFvBR00OPRqJZGwwxdT2o3WS1PCLjlC4WoRaJhm8tsa4uOhE6rBEHU5dEx6APXww76iKopLJxvIHF6mCa6mUoCW1VpXoeAOjhA1AIz8VQIACs1qEuSf9NrPMR/wbEK98F5GMI52l9EnJhTAcHAEumpf0dtesQWjZvyfcfgQZo+mg8gjuB1CkxDlA6mEpbYVxuPJYHabORGh2aVBcKB9F0Ku0gtEUOvH6N9itP0GhR6JCvgsUCCHVD6GQWs4b9g1A3pHbwowrVyQru9RnarwpTVvXqdaZj1PX4WBi42k1KKnz8ELN/5zEOT0zdkONDuNNZYg/XXKSDSeTb4aPA6cEMnLzri8VdkrdhhiIPRZqDb02fK8uASTw4tjcpoe4Im889Mczbb1Su05+tLQJcetd5z+6svexlL29L3i2495Bsc3CWWwyF7Fpk5rb2LJw4ICojgMvAinuebYOwVISo/L1JlIDajvoqhti5h2C+QJaoBiB6xXu+CTkZyLY3AeyldUT1mLZtkJVuMo7EOiUb9jZfT0lYAyBxOqg+QJYkFj8HWj5bf2UIZ2FBXukgZYhZC7Sj8TjzY1DdxP4zcFrwQyhpkeqgKFT36GHEVEifLhEaAVliVwTlBZwFFGcREsn8y5fDPouDg0SaZNPOHz+Cf/Y8nahp6AXOQkmX+WyW+Zn+z5Nfw+vN5+8w3HsXuciHEUOf4QY+L2pQ/C5/SEI90g31zpOwXp51asltrGM0Hm8NyY0P7XCX60suKzQcHyR10AWxCM2sXzNeW5wZyKMAMSJBLrvBaBT2zqZd0X2zfd7jfCAtDKZqG1UOsa6q9xk0HMwROh51RAf4IhV9PO7VWo39BGh4XCxDOzHTNOigiyWNRwlxqg7OysDF6+C3Wq9BB5NYHCqj3w+ORPJ8joOTQJ7TcTtPdgxNLX6IzuS5jEbgwynw2sC3g96DDs4D4ftQBCfbl9AO8u4uFhdZTIXloFaApjtvb7ePLxDUXW6xDEUFbOw9455gjjkhmT5WT6uv78CWdoK9PPh+0+d60O9L7gaFFBQMYX65Glgpuyyy42fJQsmRqOchONN8pHEXfBjkBF1o0uERqAnF8mnz3xWWhT856ZdDdCSoVh8wBkY/iUhZ9ivKrJpoJYWoC1ty366LhYv9sxcZwxgHa87Zkoka7bFMZAZnoeQ526JJ0WIy1I9+Pof71GcQ9ohKLXxXVK0A3wkHhoWxD1gx2+TdXSwusCzKxKrIkmwShIZ/6HJeilDTozQdtQxglhRVNykCEvIFAAETxboewZzVrU2ZG6J/W0YrMTZIjlsOzlAikdfrVCdlmUJ/tiBQzPs4PDC5IZp7QVn0xR0fCbWecnOqtG0MLZZiyyLGQjujUR6KhFgtEYBkz/Gp6jyNRpFFzDpI3eNHOa8EwhtWYc5VBX+WIgfu8EBqnWotkFD7lDsvUR6NCmlC1qgRjk8dgyOZ469+GfTsRThXckN4tYZ79FDm0VzrwdyQ2Rx4IlXU3Xc/GiAgkjmnuoY/PYv3dfXgGN1XP4D7/Y/SeGO9135uCEYNHFGeG9LuvgTsHZx72ctedpJ338G5qww5Es87V2UbxmPbMetAtX0VILGdQGUlJNykZgPGL1I6bs/rt+RmiLqnrFyqm9xRGjvcvg0Zci5n6ehlHRDLYKaOYvu7gW2IBY4ltQ2vhR1nGKuQ6yansq36nlmFwU9lfT7KOeEODnKiY92GaA0Yuw2xDmi7DdHqdPP54BxSM0rp5wYb5KaTvAq8Oo172xAXHa8Wm/Kby9+4/fKFezGiTsi31v8lYu8ZxPtuQdNVovM1O/jmdCUnWATiYqEp5U1jLFSuiqW55hx+cReLHjoz5EYUUZLtv0/nZbkh+vVQ6NTCxDmv2WERmrF9JdoZCp3aB8oS+Ng3l1YOM1Bp3hheTfa96M8QjDyNJ50TCXwzy2J7lTH7ps5Cp4Zfwx7L+Do1rGt+R8SQ0oTGZzEew5cPdgidQkOnxrJQJG5Er6ovSi2LGKlBpPiPE6WhU3KCMrU+K+XX0AjHBaFTrFtpA+IAHQqdUlPnoWaEiMzREcg6x88LnTYDUPb1u05+cxNynaxTPT/++ZazTsMCwl2XZXLGKIlt32adDuj+xrNOLb8GkLOAh88xQ/a2s04t/4eZB/Ys7diyDpp1yv6NZp1m1+uyWaddt886PVe27f2vmkimoKwCXMXFw/1WE8lU1uvAlGVyXqKroWDKWiXA1RtLJDMM5hGHUNdSqUxzLTSRbNPGqmq3lUgmxYnS2zdGb4YSyQLOws/9m0kkm06Aphb/hL96IhmfnuWJZO3uuSH7aMhe9rKXneTeRUOG6opuPzk3/agZBfN52NS7VJvZscS+3INt35aUegwxSpeRCmDruN1kIvH926rOPiRbxtDjkgjYlktXXb+KPgYl2tuqldEeIriDA/gBa+ZWdAMCFiRYp6enF0fNbBPjcS9a9FvdP3h32b0vdcP0eDEvUYRoxzZFjP9i0wfU3Ir09BgKW+6+H411MN+klPv3iC7t+2/eWLApLqo0oMeAL2ELCO1WJDJdXfH+LbbFl5V7t1gA6Mfsh7AOQ8ctn0XYt/F6DZCTvXpnKoPNZlsxCFQ3eRXt6TTthSO67oHsb633ejyOXm9/chIRiX4+h3ss3Afds2fSVYjdU13Dr1vjW1hJOwZRGX0J03HixQBiAWO/NAjRQCyrPojSV1J98EHKc7DcF4FnAoDs0ZV+PiASldJe2wFy52l1dJhViAcAjMcpAUv39MrErX6Eo0Pw2Qx+tUL14EHqc7MRaLj10XzpA+CzF5kfQ1GmfCYcD5ay3z15BJpO4D/5TA40jSAdOx9RmLGdugYdHiS0Z+Dx6F68gv+P/wOMvvN5GDSLL2K2AH9ZOCrcyRwc+SxCcllTwdcO9dka7tUZ1j8o5za/8wfJMWru1+rDD8DjBvzps/h99fU/hrMffR/H//T7yUl7fAA6nQN1uHdDVMQfTIRD5Wye8VnQHxr/xQVyPxeLbWK3HUNRBCtFToPWvOidnZUHCG9v9lmB3TLnAEDC6Bfea0uokllJ7Tp/Y0RWbx/PjxKKNscx2CiFucFj/+wTkY1hAs/GobJaJRbtkKdB3kfPPQBh91bnn82JOMfqE3h2kXPBbFjHw/hW6+xcrNYJ1m765M73WNXdyUze9Caky4BEDdbrrHgx2MtYkeaY0CbuzapKc4Zg7ThKUHjTTvN8lvIzmCXha7WCez0L87UE1ZIQV+lY6gpV5UDLNXi2QPNsHufcVl2P3cznoLYBt8kBSqczTL9/KIuHhs8B0UVfdGHhdMpcPl+kiJn3e3bvvexlLzcv745lccl02x42wtaIAM5tKzJRpwP9czrf78NzKpJrChANZUTGt4vJ0LT9cTcwBmtBFHpy8QbZRkbLm00eOvUODJa3s77RVqtUX6NN88TBkqEBZGNWMLnrZHvg0xwoWlItphgO1jepxaW0AZ/AnDOELxaJDtEycG0Qz890ajdSr8Nk4hJCpbVQ6DmdzIEmMVkhKjRbwNstS9eJHvOQKbpagTd5ke0IjOo6oF2DzgzOQkPCJnTNy1XCZKi+qzWqV/PMKmXmUIckXEPDu4LOZB8DQZ89zuLqYve7Af14Vclqlcb2B2jkIrN1gYg0nBnpWHHObUikXcup48guoM5F/IGc6xMVXcHQ3SPpuSHoNilNXOmrCtwTKgKKcsgp5czYbnA+aej6lD4U1XPofyeFkBQdWv5+oEPpL3KPGHyF56TLDbC3vzuLxSVvwMR0FQ4Y6PE5P0o/GHyozaHKRWh1XAwskxW5eOMwElAp7j2JwJb0plw4HJWARCgpTpJQ6xTd9huuh/SrYllABie4tG23GQXeCfNQUqjluaWfLByqDy4AcsmJGv/nhKREVYHcRiKo6gStKlmUlBxX+xiPBVptFwBHIHLgkGZuSxJGQhkVJRAacJhHkuRNoS8AnoxjIhh88FlsNtEJyuzT+UpRUAs7OLUbYNOBDyZxHgfnbzSSdt0yjW3UwB+N4V7U6b5pmuigDRMc5mYk1dnYC9mwytnuz839Xyy2JXFdxPodGaIS+pFhCgiruVa2HzI7LSs2NXWf3Xs0CmZygeVXLoG2TRwTnRcPv2fg1LBdh3qo0bmm7VROvo/Fd8LxphYWbj0vRFHYsHvrFkNzPXoMXZNJumGLaIhGSejoIP5t0YC0WvUdpmbssYCx3qx1QqHaaAgWy7SYTCexxKDlhKBN4LwIiEsA4IdHcbHI3uB1DZwhOh4ByNyNJXpEIcIRoyGbTTjXbC0qBzo8iExckdV8sUT74TFGuuUI0RAA8I+OAQDurJJoCDO648DuPa7AlUM1W8MBWL8ntHrNx4HWMFgYMgQCHR6AJyOpqaqL7vEh5l89xPFn6Rrw0RR0WokOzIl3ZToW9vpZLexaquurPbv35aIhMHtFe36ouVGmpPfqlG6LhkT/h4t98nIJragdH0ZHcpPbZCmfih+TZY4y7Wd1QhEWAsNBmVXYGmLKGoiG8HJpIjFdeuhs1GO+iOnSMcLQpT1+WoBCNAWyh48+A/UFtMu8digALMIxbVc/29yQUA9VoNVp300nM1n06mQxsA95FwXUnNHJnBvyHrlmwa/QbvLoTlUBs3maR82pYI/mxRysIWMiebu3a7jXZ7FdWso1rzZhbkcNYtRuuUL9MkRTdKEwFp7WC8FqnV13Optj+ulS7iNdWE45i4bEgtOtRIR4tUr3nfa3o+yjIXvZy152kvtpWZitQU5saxw4NgFrAMKsoCx9Y7qDA0n+URN5schSvGNfqCQBKZzXnXRwh1N0JxpNCXodHwMhG5GiST0FPTyWt8+zFwlA9foE9PihvD1DwRg3nQioaiQgoUjHdyZvQzceRYo3m+ClCUkAgM+fC23cTGjZAMC/DrR9CsoKJmn3KlDmvf8kUcepNdGMQEcH8bj/6geoPnoGmiACfMgzaL6Ab9t+JiM5SaoKv1eAGCZj+ADu0vlUEJb6FtyTR/AvXoFnc9CRmOo4PgQt17IlGI+i1bX64Q8x/m4DdhSrlmvCFr0+E1q8TwU8RVUFevwQ3cNDuEDFJ6C5iVgcowY8T1Ya1RX48QO4z4O+wcfA32/x4huP8fh3wjVmRjeqUb06w/KPvQ8AGD1foJvUgGesPpDfbSYOviaMTjpMPpnj1Y/KluW956+A2VwsN4Q5IQK+/AH84RjuO4hAts3XnuLjP3mEr8zX0Xe5eTwV3MdItj2+EQujfTBGtdygfj7DJmx5wADPTJGoC+R+Lhbs49Zgaz3KIaJb20S4GTXUF5GH9kZ3BG7L8GcnGaNqvvsOfrboEwCfnsYwV/RqLxbJ7Gtb8FnYEjCDX58Iq7Q6XhdLMZkVBGR9KG0Lv173skP9DEkvIOrJm1a4G4GcaJd9zB6Nej9/aYhqQxSh3ciiGnSrPnoGDuApzXhk34WMycT6lIWCz2Zx7H42l63Y6VmES8fqastVtg3xz7yc4ztpA+KLYTOPuliMf/+ziNRMDkefTPeM68ODX75G1W7gFQm7WoGUqYryXBQKfJkxK1hTyjctHv/OK9Ann8dzq/EYPJth8nthbpYr1E6crIefBwTnqEk+nLM5HuvWb7EIXCEmq7iqQB9/DlfXGSlx/Z1P8SUiuOcnsa3Rq1PZ6gaHvQvbkKppZI5XK9SvTqKutNw9h+l+LhaAuRGvGA7KGKadEJx4zvdwlgMCaWHa5vHPxLm0N48LmQnnMYvXHaFfX/ShvhCNtxuim1THoojoaL9BaCBkx+a7i8LCijfQNqNzdIJEmBsXZQ77fVM7xOBIiOvosyDvwS5Q//fCjEX0R88pogTCwu1zf06cqw68MiQ/ob4HARljNwGCHzGORLlu4jfohXit4/S84sKRKjD/PbliHHUlC7FdVAMyla2PxksEgyqXwtO2fYMhyYhtSt3rWjAYeo73AHa4l1Xdnc+8S2JjxrauhrUuLoiGxKhHsCx6BXFDUWFCBy0PQI7kb1NHY2s0JHj/uYPhFGhiLgVtNmkr5L1sSboOpG9PffMoz4btr67zxSgQwFBTZ7VHebmK0ZDoyFtHQguAuBcNwXSSth+twSyMx4mu/uhALArfgaZhKxUiNhkTebwULGPVaMpknG50U08VCFEGUzeExlLshzdI9VonY2BTS/9NEx8Uf3wIt26Dg1ND0SzzRA5UV4n7oZPaqfzgCKSM4Fq7NURD7F1DlQNNp9EijfM8c1h/eIjJaTLReDwCAfAPD0OzTkKlzPAPQ47OuAYT4NYdKgDrD+Tc8cehJmnlIuCNqkr6noyA2TxZc8eHmH9lggfPDtOx6TgxfjFLvwB4OgItW1kwbTTkxe5uy72Dcy972ctOcj8tCyBZC2pFXTL1dpDHQyHM8XOiUbuWlElgkWIt+Sx0z5lYqDltVdjnvpTb5CDpQdS9MXfDHtsz2Hf5to05badK6HwJK/YMgBNwaFexnBzs4xzBbN2gc1nCPdgD7IxuPp17zfmk8vrqfTQUvjfHCKEamedkhvkuzbluf0u6RNMWeYA2Xd6XZ8BxCs0C1wVvArivi0WZCTp4zgU4C1utyzsxPT2D3PaNPCsOY5es080mw/EDEJNbfQddl/IqPGeZg/F7z4IHALI8Be462ccWeSO9rFPVcyjrlCkfh4rNOg04C2ZOmZ4AaL4Qc9x7A58OWbTs47ZNiWtUt+iU1PyYjRnXLlmnqiutU26IpS08m0tauZLhmnlAcL7GRZlZ6OeqCt74BhiQBaUr8mw6Jw7qoazTF3PBQagemw14tYI7CU7QxTJuS10Yp9PU+k0HzBcYPQ+/V67NMP+A+FJ4sZB2bdbp2RzTT5bAcpW2v12oUKbbOiUPVqToNbJO7/xiUVYO2yrMiaVqCw9kdrolqcke/vBAVNUwpFp1MY6qIcKbWI7QPjDrVsJ9Wn/COAC19kMEZXVdKhJs6lXod36A7Ys3LXhmzjOFlWOlMH1b6YJQ6F7yUTCCr8ZGWdo2RXpsiT9ltdIFUQFQLeegLp/emL1EtoIwmGfhHGYTOTFlDG3dkHWbgGD2+liOSpszslpFKgGZri75dEL76YcOZIFw6+Sjou9+nBVk1oLJsUygLkIAoGHaqkq+lvUarkjDF19LuD/ISbSsqkRf/d3LV6jbNq8b4vJ7xTpk4z1nrjEueq6M3N3F4iK6sAjnNXBsN3Bs6+/zqIEtLqzixmP4rkNknraU/0OmZa8LAlClvowlYIvNUEPpDa4OVnUsrlugMr9F1aOEz/XwA8fOkXO+L6n+Izmvl/CodWbKm54iNBlA/uBZUz1WNh9a1MttgflsE6u8QJklROijXur1T7qycEFoceTgkCW1TEKVdh3Ddks1MaXr51xtE5FpGqBb9fAmGpEBINEghfybhS2DwhsEp18socWrY3thm6qpBQCi5RNRwlE/H7N5bQoC9xlctsrewbmXvexlJ7m7lsWuTqee4wzb3w5bfhdra9hVl+SNYx2cl3V2pvNzK0AwDsZUZIo1KCzbF3uzxy5radyS9NLJDW9H5t8IZnI8O2xDuKqSRaHFbkorSDkyLq+c/K/NlZweweLIqtrbSuZDGBCzHbyqZFsnLxZD5rux91D0LYT+g29LE9QilsUPsIiV4llyWAxHhTp8dX7jPN9A9bS7u1i8o6JAqR6wy1ECXp3zO4jjtPcAACAASURBVI4cBbe3YGyVi264bQCrq7R1UT/qCxpIsos8FxfpICcbva84p0Pgsuz7/qKR8Vg4w7MxxHdigVhDbTvXh9jrvNxgicULFwsi+hUA/xmAz5j53wvHngD42wC+BuA7AH6GmV+SeFP+JwA/BWAO4L9i5n92HQUHHZs8MOlADxi1eyd9KwMc2K6vyoY89DtyW60TKcfn8/KCoZ2s+hgudsfcpAxaNGQsMcqtuQwebxy4Vsj5Kz2XCUFrokDe5W/1wCIWfQNc6Kdv4U6AfJEC4Dri8/skWhTxe6tDAovF0LjnlH6g2cpVzuC1vW8TqtXPdl7OeQFdVnaxLP4qgP8FwF83x34BwLeZ+ReJ6BfC5/8WwE8C+Hr49+MAfin8f7My5Py8LPmNeuo1DDWShCT1lsfogakJIuzegVchhgTXoGbUqxPiptMYLrR1PCOj92KZ0JPrdUro0kSySagAFlCkoFCROyBGtepVNoa6SRWvAAmhaaVv7VdRlKH2qFb5Uv2ro8N+u1WVV+g6PgKfzUBcJxSqRpRC+ngpttJZTBpzLjJVRzYuZS3XhWEyBi9XWdU2GjUxDJo5ih8+kCQrtTgQFg2iECZ1KWpBDu7oUEhhXr6SQ6TOya5H2AvnhHlcQ6QBEevPzkBf+yro02fp3KoCFktJDgQESav8FAfK7l0LcnjVgmdz8NMnosO/+Sj1axy61YOHoKaBf/VayjYAqN5/gs0Pfojq9z+OiyONR4Mp6hiPJHy8XGX3CH1uiHAukAsXC2b+x0T0teLwTwP4ifD3XwPwjyCLxU8D+Ossy9xvEtEjIvoyM3+8s0ZXFYV273r6AAfn4Ft/ANPBXQdbY3PozWRxBbY+pl+t5KY04VrWN4v3/TYDMCzj/Czi8Ba8A1MkN+rJnIfk9LuSmwNhMSl8P1y+veaLlI+wKvrbIlntUGMtxt/oT32h03KVdI3Je0YXe+7ZTBafqsrN+U6ATlxEuHkVsC16nQDDtVHUfCUHeFPT1PgT6MXrPHSqIc4TTd6TUDszg3QhUEhA14FXa7gXElL1bZtyf4zFxLM5WEta6jzO5qg/fS0h4BgNCQmGYWvCirNQ/Erb5tb6JYpKXdVGeWoWgE8APA1/fwXAH5nzvheO7WUve7nncm0HJzMzEQ28ks8XIvoWgG8BwAQH11XjGtuQcKCqJOHJJGxpslWZtEZVwk6w7wK/ZBHx0Di/RRjWtWx3HIEXBlOxhpjzAWmo50YuDMvhGEzkHHRktgvGxMRCnIDMiXXLnstdl+Yh6O/G4x6CE87J1iG8Td3hgaSZ+8SzAc/Aei1WSEGKSy7hMgDEhLD4OyDbhqDYhmC5kjHo9mU0ynAScX4fHKW2BhCcsj0IHCAOoOlE6AKDVbDLNgTFNoQ3LfwHj5LFAAhTliPhLgFkS1LXghDVJC69P9oN3Nkc/n3ZstDJqQClzFZbsSvUNAH3E44fHqD98iM0i2U6dzSSMRYITowaAa0V2xAsbr8w8qdE9OUwkC8DCCWd8BGAHzDnfTUc6wkz/zIzf5OZv9lg96pIPSmJc6/I1GxTvqPclCd5F70CAIociY/jHC/+TbFjXyQ9JuryO025LiIPRDaVe1jXGxvD0LzaCEPvmrp8boOu19ZHrzG53rU7t+0wfxz+2ahI1Ou8iE74fTmGXp83MN9XtSx+HcDPAvjF8P+vmeM/T0R/C+LYfH3r/ooMZ2He7hcR9pa/V5IXXWiZDW9lzPKRN5YiBxEcjqOmH4kJKEuJDoS3eVPnzMrKE9EFWHaVnJbUddJ/3YQ3vIvtc+fhppMUs9chj5pECAxxnErqvU/p3ZaEV3UK4wCzEPAWGAUAssduw758MgafnuU3caW5Ht0g/J2KG56ZRdeSsFf1Vwtokgh7Yd6SWCNBldXKO5ymN79plyYTmdfKJRg+INfSIB3deCzj910g7A39eQaaWkpPqt8kOHZpuUJ3PEHzMtENoK6kVGJgEXPMqXyhEvY2DtxUqE6XoHULfxCspi74siympfNw7yXCXp1JPpxi9WSE5jsGwn4wkbyhWq5vvMcOJsDhFPT6DBx0gOdLpajvEjr9mxBn5vtE9D0AfxmySPwqEf0lAH8I4GfC6b8BCZv+HiR0+hd31uQysiWL70IpMvns71hN6MyhWbQZ4NTcbjLHGq8NbFnzIqJjzjgtlRAWyAvcso8sUNm56oAsHJHcdfCLZd+huG6B7jQ9VMFkZZ9yQ6zjVMzzPIoTGb7MueRCclN4OP3zl+IcDKxdSa8QQhy4FnE+tG/VzzKAOUoLg54zmyVHsD7owQkIz2CX9HefPssSumLfoQQAmXBkHOt8Htv3CIup97LN0KQxZkniCmY8AJAmwwFovvNZVkMVCuX+JAw3RGIARBJfqpzkeqxW8Ks1mkDk24XITyn+1es8mgOAnr3A0b/krG+aL4T5y1h5AICTWrYxszlISy0CN5sbwsx/YctXf2bgXAbwczv3vpe97OXeyB7BqaKoyB18HlnCWWCI6u0JLywC1Ob76arqn3ueDha0o0lwmsRk2tDz4rYpVgsjAaDZcWgxId3eKLioqvLjoyZZBFbv86w7Ox8GdxKL4FSy108sW2Z70nXyW8M4Rl0ndV6yhLwmZrqmfkObJQdnaFscgsHBqXiSTrA0rByZHJLW6hqo2qQDSTYuT8egeXDaBmQpe58wKJ2PodLoXKyEPYv0e2Xe2lIhjUaNcIvaEHszgj+egl6Yx3jUSNq+tqGlAJoGGI9Aq3XuYL6Ej2+/WFxWhi7keXDc25SiTOCgXARFtm1dFa16HRmCORtnnc7tTrynN6UPO3nIitKMQ+fSZQl8ritldbjLiHMJHg70IeIXyP1cLKzT8iJH5pZ09fimjWXf6ux/btfJWij8EfEtA0SUZa/9gAjNipmZimG0NhXJ2k2qJDabxXN50wbeA5+FOGMpPQVEdTLOrOIZIHvuSkhhY9jRWAQ0UIGNppNEoGP4MWOlMAB0dAharhJnpcpKGcf7N6HOR/wbyBycMYw8HoPadVp8x2PxF3Rd/rt2DXRVzk/x+EFy4MaOg45dJ45Ru+cPoVNl6qZRE/uLZQBl0uWtPp0mX9V4HELgS3QfPkCzNM5w54CFA4eKZOQceBwQn0eK4KzgG4fqZAXnHNovSei0+vz5IAKWDg7A4yav+vbwCIuvHuHw2WGag8MpaFanBaFKDk6uHdy6vT0H552Uqzo4bROlg9MyOQ31o58Jebbllr4j/bx1qJmKYdx1ybnIHmxu4njuOQ7OrOKZSpcqnolays5NGVpUGbHZc8x+VNwFL5a9zEwwp8pggNT1sOUCVC9FF543H0DmVM3mnAjUFuNaJV6IrAK4OkIt/8jLk8wBKAedMHgryY29HoulVFLTuak3si3wLNu5iNj1IGzEGaqLKhCjYvVnJ8mxqtuQ9RrulaAyeb4AlvKouZUuwA6urkCLFXi+QPOJfN/ZebLzN58Da0kBiFuv12eYfm8CnhnneGDp6m1DVmvgwZEwbsVG+d1iyrq27GpaFxR155+aJ1ANwpy3Qcftufac3kJ1vh7MKXKjcHAhOS/SxjWyEB/8UPrApQdB24h6lGUJEPwZCotetzERa+t4Sil5Ksu+0OXbOe0rJFxlv7PREEvk0rb9eew6sPcZ8Uz2XbkAaUp92+bUiYGCLuqiafDegxarWHsEQEzLj8xem02k/9PxUeVkgQ40hqTWXBmRU9HomXlRUbuGO13AmzArkUtwbwDUmRfHUqySGEG6ZKLknvxmL3vZy05yPy2L2/BZjEayt48gJcOzWfgsqKmzrFUp3pLjFSJM2VrZo1EsWUivT1NJwlmXSvMtl/FchWMP+SzceJwySBX0NWoEOKRyehqiCdtAWV30ZfA8wMyPDqPPgrb4LNyTR/DP/LDPYtZh0GcR5iP+jeB7UBNaIeyhvkgEnB0eArMZfLuBO0y/o1aIfDMH44fvgT4vkYuiI5+cBjCXgWUfHQbA1rM45wrKIoV9q1SV+A204rpm8a7XaH/wAzT2XnFOMj+fSvlCdzKLPgsOPgtvfRavz9D+wHvSzckpUOykAEhG7bgBPfOJg/T9J5j9yPs4NCTNfDiFmy0GfRbeObjO5z6L092XgPu5WFzGZ7HFzLoxUJayLxVZrxeCsmyG6BVBWVlWKBAqsZtiN6oX+3NAWSYdOuhxISjrxavrgbJ03F2XTP1gXisoKpr7F4Ky0py7z54Pg7LmAZS1XufX42wmPhoLylLmrMk4PZShKlsGyjIvk+YPPx8GZYWPFpRFr2VxdZVDZUFZ4b64CJTFFoH67AUO/Y6grNMabjKBPzkFhRcSmC8FyqLB+hlvWB7QE/5x6mG8bkZKKwS4tDO0117vmOG8sN8PWjpGh21/X0eP3iHKU++V8bvoVx2cmZQkQ/pZi00P6bBN/6HrUOg7FB7NdL9gfz04Bu0n+qSKMRV8JZHJrK4Nrd0AdUDI40GoKdqfO2sNpj6pjJwFciObPjA0h7Ysof7t1y3cqIn8FqJWcb3NcZpOI8eJym+2fw8n/vlOcen7aVls24aoDFkexd9ZFqaWIyzIb+LNVzwkPfKb2mSdap7BwcHlyG/CNqQLZq6bTsW6qKrMAy65KKNh8psi6zTeGGzJb3w8d5D85sGD7eQ3+jlUOgdSGFT5OTJPvLF8hshvsAP5jTs05DfKzH0J8psIvy/JbzxH8ptuC/kNQR9Cdy75jfvRH4EzhZGprqU+x5NH4TosU25MCJFzUwtOY4D8htfrWE5A58YdHfbIb+qnH6D92lPUf/BxThakWafmfsZ4JHVD6jpuheE96NnuS8DewbmXvexlJ7mnloVxWm6rEXKR41PfSLoiKyRY4dKWVi/zUlI/63SoMLIWNrYqjUapMPJ6nZyL7UYAP8xAsCyoNjH1rotvCN6YN32ZddrU/azTqsJOWafbCiMjmM72+PFhLKATLRlmgNayz9e3uoLFAp+Fzke0RkYpWUvnPeqv9S8mE1MYOZwzncr3BkYNAP7xEZxWfdPrS5SwBnUtYDJA+CwmYwExaeGfuk5ZpyEjNUpTi/O3zDpdLLB+eojJmeIsJMOUAHSPBZRVORezTruHwcE5qsC1Qz1r4RylwsgfNRF6H3t3Tqy58Qg0X6QiyA+OMPvqBI8+mcb7zh8dwJl0BNb75nACWgs/Cj84TNfs5e5o0Pu5WAxQ3V1ahgBNnEBK50oBytpKq2ewEPo7hIeJC0AMt2Gvqtub6IgMN4Zd8LzPSvxZjARZLtCAQ2CfaPUidoJCHddSdy27qPoCxvEYfrsU4BAzSzVzabhf41SPQ5yfJQ0+1ugfa1NpQgAS9YiZwkp518Zyk5bdm+ah9CK5tDARAW0YVzGP3Lagtok5ILzZhDINHlQlh264ABLdUgoBw7benKwT6pWldim3LdwsbHnWbSg3yag0+3RUg4ngVi1ouUY9a7M5h8GXkPdCWuMZ3tDq0XKF8cuQzq7b3/lSdCnJbwBQu5Ht2NxUmL8E5Pt+Lha7yCWRnbHArl1oY3LZgD/Em/Y99/vR41ZCVSjEehL+/POdqSpV1J4YqnUKW2tCj0eW5+LcUOu016eJ9CQuSM4fYIve9GmBiItjTE5Dci5apKcFNhlQlvymylLUxTehc6CLmI/9kYlgURsWugrQC8lsgWkpxyMu1psufyg7n14G5YOk6euqV5hPWrXgTVp0iWQOY/lCA+BShixiFsthI9EXt9DIS+EEtn0TyYvCRL/qRYje6Jy2m6xuSqp1GvhaNoYr45JFoe/vYmE96lfZhhhTmRwFqjyfwYfLzFFyhEjzbh1oNutU+9JsSW+cbVWVbha7lXGbUK6Okzdef+9c8Jbn25A4dgCRPLhIbGJ19Fn2JjL/E/eZpJo63WhxfE5yIyg8IOORhAYdCR4BYWEJtUezKECohxLHA4iOakEFNKH+JvI8IJ3Ldk4AmSsnFcgRyH0AgMcj0TOQz0TZBCuvriPUnDRXZDzKnaSVE0uqcuDOkvuENvXhq9I8dodjNHVow7m4veKAQaEuEOL4lF3qJ+E+aGVR6Q7leB3mX7KFOe+7aWRLotdsPEJ73KAZj+K5PGpkMa/DdQx68aiR61nXidKvDAxcIPd3sYjRkCv+3r6pvazy8Y09cM7l2x9op9xKZJ/lDRmLBjNnFkRWiyLE/d+IWAvNWDD6b8jy6Y19aKto06ivItquxXXY/4esttICHLIIryBUXNeeRcID/XhIeEFP1a+VST0795ytgrZd3mOXtKx3kX00ZC972ctOci8tC9L6CVAQSsINpJPC9mTLNsWFqISfz8Vjf3gIatfRG+/nczF1UWVVwqgSDIVyafpXr+GOjyKKTvVyjx+Bz84SChAAHR8B70nsnb7/KehYvOX++Qvw0/fkDfVCYv7u8AC+bQVIczaL+nbrNWg6BR1MhQcTiOhM9+AB8P6jNMaPPgXGY/iTE7jHIeb/7Ll8F+Di7sEDaffzgBP40gdwJ4Kh4EC/RuMx+OERKBxf/fCHGP/+Z4Aj+GPxrBMz6Gyek7MYlm96+ABQbEZg4ebDKVwozhO3M48fwL08EYcvAHz4Htxnz+Ffd9IGJOpB85X4KIwJfvpjH+D4dxt4ovga5KqCn9RoPn0Nno6B72qRIQI/fQ/te1M0r0IE6vBAdGo34KYW2LTKqMHmwweov/c86g4AbrnCR3/yCF/SrZJn+HGF5vMZXv2YYCcOv7/C5lC2BbMvyTg3U6AbE6bPPI6/N8Wn35T2fuDjY+D1adgCp3d590NfQvtghOm/YviAC5n/yIf47k/W+OHTJ9EyWX44xvTjBfw4ALdG0sbySY16wZh+MsfiSwdR1+71DRYZuosyVKx4CEGX/V9IhD97BtBJCnDX5Q5CzxkoS+HbfrFMhWy7Djxf9Prnk9OQlm3aO5vJPhvIYLvcdaievcw99fOF/DYUwsnOD5mKeiwWM5rNYnYjgKgntxv4EB6M0OYwtiy9GQA+e5FlS4JIIjjrNoZXx99tBJTFHm6dQsasfBZlbU/2wndpocoAMJtHkJMyXNFmI8Ap9W98TgJa6joBXAFwoVAOF6HT499tgGcv4ZzLfE8VkVzfWZ3xalbPXqJZrvLs0GVIxa9reJNzQZVDvW7hNbQdINN+3eLpP12g+aPnaVxNDZ7N8fD/DZGPkzma4IsYP5MH1Y9qgAC32KB6dYYPneSG8OmZgNKKgtL1956jHjXwr0/iC2j6By/wlX/0PpqPX8V7tH41Bp3Oo69Ct6ujTyfCoXI6w+FJCp1Wixvk4Lyz0qM6vxzT0yBVvXN5HYpASaf+AgmrXVLPov14zFLKKXbDoj0dCQaCBhyUt1kKwNLnq3NTjynqVf9WFmwg+FHkvIiODXVPWKMi+gAP0RDuItE5G+akgjgzFWNAJAtF6cTbdMHxWYMVz6E0gjrH1xBfuew6cy1JcWxLJJRlFTT02gi9XsxxccHxXVWJ1u8cZixfE9jMAZxh+WKOOIubcDjc38UiiG5DwofwxyWxF/oweuN005u78ynacJnq5Upf1iWeSK1NQkTCm2CjJGW0oqpAdXAgmodLIze3mtMTa2y6GLkgMosFkUCuVz69wTaQG53IFFjiBC6ydG6ugjJ5X0rsfHkPIEQJ4rYHMeKkWZ7ovBRDCvVCEsennMuNiUpdcU59Uyx+dQB0aZi2cr2oHNcEdAzUopevNeLjxMoaNQl70mx5TInkd00dMTtc6f1FII/+InUN2Ts497KXvewk996yuDXRkFzGJmTM6IvEhgVN6ItoiwnuCOD8eFZYJ6rFESwV8Qf2d7ZfZ6wRY5nod8R9PQbJh4Nlw/ENbqywobexBVE5J/r2zyowLcaysvv1rOJcekuSKQ6kEpm9C3RsDqrT8O8A50bc3lTJmrK6VuaYZUmvKH+Dh+0b12abWVeAJ/hGdPSVAzkGWtm+cVXMUMlApmzg9vrUFXz5BOuWxzkwceKzqJ1s2aoqWYNfNJxFL/1a5aJJ0EpNwcHp9OazcNvIcWEcnOEmiinDgSg3ZVpqunNy8jEMyEl/13UABcLedSs3BFHKMQm0bDQe5zT2PiD2ppNIvqszQHWdkdGonrxe90zZyJpdF7dA0ySOgw0E+kzBDxCIbVGHKuFE+UPJgoDkeZ9TwtLyCTQcQjyjWzSlyh+PBESl+/XxCDyv8kWjcgLh7rqEjoQAnSoiYNMlvAyRREwWSxCQc3RWDrTxKbI2nUh/bStlBez9VNfSTmP0BASUNXZgzaRVVCQRugC8cvNKHJoAuoPw/8jBjwmjV+JE7sYK8/chc9dsWzYbYPwEfDCWLd5K7i0/btAeyHhV/KgKoLSwtQoLlp8IoMutW/jDlM/Du7z4dAp2PvMuyVaQT4GiPK+JNvcC8zrkIGRviCG4t9xc8a2mxDKFThn5jaIVN5tUXs97sGU4WiyQ54b4hAKFifYo5NcS6IYF069WcCdGh6Ane46EwHFx3WxgK5XF35zNEutXRJB64AwpQvH6TKITnfHxFEWd4xh0zlaJ+EfP41DlK/YV/rdRJIkqtakNlQAVjzB9QMKj87k4M61FtlhKNMf4jyQSNBcwnkK4F0uBSzMDtMxzQ6pKcj50sWlTNOzwj2ag16fp3KYBLxZoPpFwOi1WqILD0c0Du3cIbdLGg05mOPxeeIA1tycQ6MS/X57AzZosUlQ9e43H/3oMmqfCyHW7kfT44MuJ/rL5SmDpiwWqVYpgUbu73+h+LhZDYklMdhGbGQnEaEQ0hy1isUSLWkgzxFtdLk8Kb+bSjLYkJmoihghCL/HMs9Q/9QwXHGAMBI+3fdsm3omsluoikMIOlSsIC6EdBwB50ExuCChA4a0FMmpS1mo0aV16wM1CasfKCjlRXSoTfdJjI8m6jMvzqAGt1wHmnrJHGUhZpxqOno6BmUQ97PaNIA81TSY5I1lVBV4Jo0MJlzb603gEVpYpM8+boxEqW9ypqcUSOQiZqZ2PEQt/FHhFRgJZd8sWbjPB5lB+P9Jr6vNtFI1Hcd7jC2UywupRg7GB6PN0DGo3xrII/0/G4uDdSFGkcKF221KrGneWKSuYYTYMl30X/06LhFaAkjqiFywczuQDbKkMRqMReLFImZouEc702KaKeczM+xLWbDIl9TOphz+GF114wEJJgMg0Leco7V7eKeV9KZuVtZiGfmOOUzPKv1ddVUfzG95sUrp516VMz0BSEy2fkp807Kn9sm+R9ULg+pk5Xl/1V2jIOcuhaFupFqbzr7iYML9WNwqhUx8WENlamfkr9BAwoKEhDHNcffBBxIBoxEW2fmZronOkodtRI9ZJU4OXK7hHUjck4l7qOi1sVRVT/+11dwcHAv6bzdKCqVvp8ro7l8ohmHv8t1Z/F693ZMraR0P2spe97CR3dxuyq8VTmu3lsZ2aSJZDWctjiM/w8u0Wb0pNgtK3U3gTlHwarM4yk46e1Sy5LcnmVN+gbDJBgxVk+TD8AF+F/d+8sdmZ7y4j+vaMO8WCf8TMYZwhS5AMJOet92DnxGS/TsIgkFux3keuj+hkHbqX7dzovzBGiR5t+vM5IBHJmiXv+RSxumKpwiG5u4vFeWJN1ZgDUiI6jRk2cLGc5nasQ6p1iDqoWa1ec0FtRseG7B/rJgKP/GIBN53Caxl7NRGPDoOT06cQpikFwKdnkfnJL5aSu8Ec+SDdRLgn1aSNpQ6XK6H8n4yjea9bFDcZJ35FAP70DFRV8MsV3GGAGQcHKzXCxOUC05UPEQz35FFkCYucmU1gkFIH5uOH4JevxWdhmLJ4tRYoem+r42Q+tHSBlmp0VTLf1RE3nYRKYTnfp1+tIk8pTcahoJCXfbwuIk/fQ/XsJTKmLEDCjrO5HFNHr3Nwjx6CJyPQ9z+N7UqpQy+/sXDvugYdHiS4d4iGdC9eYf3vfw3jP0gcnNzUoNMZ+EsC4XYn88iU5R/I9elGFbhyqBYtquenWHz9AwDA5He+K4xkxi8GIlQfvA8eN+BPnyWG8a9+GSc/9j4e/rNPks/icCo5PKXPYjqCW21AZ3Pw0UG8ZvjDYtt5jtz5xSLzVQSxsGuqqlhL4zKJZPHmrORhplGoh6l+j7OZPAjK+6C/CdwSF4ZOG7npCG3qa9SkB2W1iklr1Hnw8SFo0wHPX8qxJuxpi9Di/9/et8VakmRXrR2Rj/O699a9dauqn9PtebhtZsY29hiELST7C1kCAX9GsvgA2YBA/PAFPyBZ/jP4xwLJPIz4AOQvZCMQAgkLYY+FzGg89oynmRlPP6q663HrPs77nMyMzceOHRGZ59yqW9U9PVU9Z0uleypPPiIiT0bu2HvttYCVtDVFQCbUgCmtHvmoONlE63Sp/fZ96aROqd+LqVjlw1CSV7/ebg6GsJ5IhX1RmEbehcpPMzqeHs4HBwNJTa8HxSNw0BlN9U9dlAns+clDNUvhH4gql5RhUkhWXe8jX64kDpAnsada1Mg4z4JnQVUN7hWoj/eQnciYw5Bcf1uAM8/lulpcp/fOWkxfKlDcj3otblDANg6r67KtIJKUpmOsjmWyqIYyRtkiQ48Zs1sytv1eGbRoglkjuh+DEuYsUhG6gwEmn7AYvTUCNdLWelQgZwYX0n4dh3pUwM4rWOcCtR85DqnVq9izG+B8lKXeQvczcLUljAY49QfcIZThugJleVvDQYOpaSBR+Ro7AVXKi43iMiG8SdKoSdoxeDT+rWGUwTppI4DIyJ3KJoa6gAhd1j5omzcCxTpuOg6+/abXa19XwUdpzYxn4OYkAA32RXdpAM0vP7hpxDvR9npBIU4Dt2Hcsta28H/XxACnXwYxc6u/VJYBo9AehzoCxJIJloocVBQhwLnBsdENcOaJmFTyO8leerGt3eGDluS9OV5XMSirhDia/XIsLw6tqH14Gtuq46DBZWsl4K6p07090PER+PQsLqU0+N3VDdFKbR8AVvu92W/ioj7ZBTh3bzXhXAAAIABJREFUtrOdfXj2zC9DtlrqOVz2eVvMIvkcCFfrpEiso0bGVTvlBxYvIojLAOC1E6GXVTuAFCpWW96FjbN6XScaJVV8EzoFYVmvSZJJmi95gwdPJAEGaZtUHwQA3ELawTXFmEeaBnacaJf49ud50MsIqzdDAjTSpYF/g2sKNPTZObg0WAcgYEASmLK+7UxZhpI/SpZqnEUeUCoKOABcxePCmHTZ04eDmK7V+0wU4yD+zRz275UeZu/CtVSThIq8pUjWxbCQp/ZzCwKPBlHly0OzkbsoJUl+OQhE3RBPH0jLFZgdeOCXjw9cSzRIh9DsjUQ3xLkQ8KRBH83RCObsIlQihJhVQvunfaU8A48nIX0MZmD5cWf33jYBdAOZj4tZpOXOiO5uixq/u6xJXLrg1le1TAAqrsPxoWtVrPprhHX3chUnjnUV4cOTuG9YRnTxExon6T4sSmWv//eBUWaOMQt1o63XOk37wU6AR3q8iuxYK+1THMWgB5rP0dU6Zd+XrdkoHQ/9DABlGXhB9OFDWUp8QSehsoySgulxgYU7ybIM+/GhTceq9BNrkQOzZHIrC4k9jIVEiIo8XC+N/cBzfVIvBnlRykRDyxXqoyFyJcppYtm+Uu4TEGDibt8vTTIDl1vYSQbjGNWR7GvfywPVf6sb/b5onS4WcWwGfSxv9jG8kwhLDfsyierLJdE65SKDWVdBbxUA8ODqi4vnc7K4ij2G/GYDnu2h2Vvl77rWpdBPax662zrXoDRgm+7TCeRy95wd+YNAxd/ah+U86jUpQCdh/WYlBd7GCwrIA50iOAFh8EpqMGRC4Fib8Yg+b/0uxA0ikEvG30TJgXSfbirWNW0Wbm9Gma1TsxbstVGp+13jWu3nxr+169pnW9oBZFQx5kGuAVjiEHZRRWYvx3G8NJuS6MGSQq1rC1s70GoNVBXsIoG9b/vNqkyB5+iU89bI5k2bWXwtTOMhCKGp73UV2hXaAFwtvuft4ztZkAHgWhR8ui1+BlKodEtz8rLTapBSkXh1LYG3LguUtZFyPTm2BZtO03vdrIRCyEN9SsezSCG+2q4sE7iyektFEQNq+ne5CgEzruLyhmwNMMmbSJcESTEWsiz2p8iRsn4H2/JG3DoeKUu3jmOWCfw7z2WbigzlOdArRVk8oFut6HqgHXhlD7NuD6Q/Jy03v7Pt9ktKuicP/tFBoBEMy8DMgpZZaDsVBUzjUPdz5Or1qGdR14HJG6sqeBZBTV09i9qBlms0/dwPTadoTq0spH9FDrLe68kz1AOLMkuCuUUuE1DHs0CRY31rhHKxghtpFo43qpofZc/nZLEtTtGdIT1EeKuw7pa6D3XDW9H5jXOyf6tHF50dewhu50GpvDueZjKq5G3DLr5xukVSoT0c+rHhWfjCKAAt8BitVnGiqyoR1knectw0IPZvKI4Vl8Fb8W862TcZo9U6xgPmy8iCta3P2yz9Tvu9isVSrAAir8TeUldfV/LW12URUchwpHT9ZrZoUeHJrgR2TUtRPgzjat3alha10XgGnselBfsSdd2H/Ljyeo3sdBZjIY4BW4FX6xaXKVW+AlV/b9bAaMxisUB26vetqq3eLc8WoMyKIntS7Ni7v2jRFZLqx9o2LJ0ah4IIPFuENmjfrmq7bMjOdrazK9nz6Vk8iXXfdB8QVyJLlbie/zDO+dTW9ZoUgp3ELEi3pYpg2gcXIckfBNb+1JbojlACa+fGtcc0wN2/w++2MFZe7jGJ3VD3+o4leP00sPUP2MYYgH5C897z08Lbn8/J4irZkLDvJdmQ9FwAgvpYWoF6WTYEMdXHVd3aHswYtNCf/hoBlNUh4U3X3qE9j+JP9HyeAGIQy5gWyU1IbSYVoxtMWZ01K2XZBtgrxGkCmjSCv1oxg8ZspqC746GfAREbToWafWyEEMlvWvykyXGtSlO1It8cR40TaR+SeABlmY9nKPAsxpQoyyIxj6/0TbchzzyXqAH3i5jaVvW4ug7xCUqAUNzz2TBrhX/TOdAqg+sXoY+tKujQVl8+n/Y3z1GPChRpLMbHbajD7s1lDu7lMHke+UmB7b+tS+z5nCyuYtsmiRS+q+ktP8uasmzVYDQdUpjWqfOsDb9Og1JaLt/vAW7eenBMWYJGAo+m5SpAv2m9DtvhkYCmLNH4ACS7dqk+aRpv4de/LqYfQw4dAC+WgrNwHDECi/hgpOcFC/kODQdxEtIahKKQ7Urbf7gfA6XJ9bBYCPeE2/QAwnjoZwA0GMQYgD6k/b6XZXCb++hxo6G0TWHZ3uqb+8i6GAVrRH3cCXqSEi0Q1QlRFXX4mhtURmorwsTjy84P9uTB9+0EEdx4jPlrI4zm/vfCLPR3kwzVLSk7zxIC4fWRqqgbNCWhPBXpw9lrcv9H7/a2xyz2RwL3ns0jkdH1fZx/usTN26OwX3M4gslsqEXRya3ZLwEGaDFAc6haLwC//3HHWVw1wJn+7Z4iVB/KjXGLZXSBt10n/N95JqeY2tzKlDWb+4rAhPJssQxSdylrFjdNKFBK94VrwDXFv2nb/fmlCXLODaYs307VNtFrabtbTFm+Xe5ivBHg5LoW0hSP0TAPzuDmcwkepg/nJcG5dDwARLawKmqfhICcMmXpOF2MA+sYp8clEG617PbDjXFUzgpeLMHLZQu+7y7GgltI+TaUUWuZtfrG1oKqqs2UZQhc1Rh9/TTU9Cgoy63WyN/xy8HFAsZPar2LLaCs2RwjLYabzTcg8ACAh2ewFxncfBG+t3cf4vjLBnh4Hnazi5XcayUK8i+x/EJwITydIVvEe07rq+uG7AKcO9vZzq5kz6dn8SQxi0vP8ZQITs/+3KLVU2akdOnzHUZwIs9jTKFLq6f7rqTEHUkVI5lLEJxaPv5RIzj1rZ5uAyJYyqM8+aNAcHoELHnxpAhsYomv9PsRK6IITrv4aBCcvZ6U088XMVj9hAhOEIHqJkgvSiHhxx1n8ST2uADnU59Xg4+mHbz7iCyVFOB04ksDeL76kq2NcQhfdi6KWW3OhO+KpdWRqnyWUuX5tm0L+n34bfHXZ6mliWA+X52bBpUNgfItAdXvlKWB+C6f6hUtsJ9rm58wi/f8lKgnnJzbOC627g9gg6NT9Uu7HJ2P46rU3TTgqOlJX4wVSqO1YOtxHJla6q7X6pSKP85T2qDw36IXopH5loZqWmLNCfuzLw5TsNbmBWOWo1W63y3pvqzNW6gEKGuL8mpbAxMXsLXtGpztlpSbIt8owiIjYx5L05P77kv6tS9UFKGU3AwGmyznTRMJgXx2hfp9ibGsI8BOr6cESy0CpO7k7FnSAxHSfL51DI3WqlgbAr1uMoXp92KJvf++y0ymY2uuHYjmbTLZ/N70N3HRXK1E/fnxLJLAIJWRJYqKIuhrpIEqynJftSnkOEB0tQHA3rop23xAzLxwE1iuAotQ8623YEYjoKqiSnm/D65q2KO9kAVo7t6HvXkDzd37rWvYH/wM6GwswSb9oRxew/rlQwBA8a274COJluO9+1j/yPeBHMP+zh/Ktb7vE8C9k8DOZPZFcb2+f4LsxVvSzlOv3K4sV8dHqF4+Cn3MvvEeaNCDOzkFvfKi7Hv7fWnLYACez2GOZf/67XcBAO7P/2nkD73auXetuVeiurmH/FSuc/ojhzj8AwmqrW96V9sx8tM56J334y2r6kDvRq+/AvLtdTdE0b3Z6yF/y4+bZ5xubu4juz8G+SBc9doN5G8/QHP/BOazb8g1bw2Rj9egVYVmWIag8Z2fGOHW/13AWSOSggDYiibH8N2ZpBm/Kv2Ea7D+odcxfanA9d9+R/YdDVAfDWEXFep+HlCV0r5Csh5fP5Xx0mXDV76Jr//qD+CV38rCOFQDg9G7K9z5SfmN7H/bYb0ncoLjT8r5qj0Glw69uxmuvelw7y/IZPPGr8xhTi7QkgKwFpMvvILlocXxFx8A90WE+eTnfhSf//k/wjd++cega8fpyxb7b9eoezJZNKWMw/wWIZ8y9t+uMX7Nt7UB1v/pv+Oq9vxMFokFKLR+Tv7Kfzi8LVrkNek5JrJO1TcRnZ4HFe2wjzJ7a6ZAVcuns6h90TQSse9mAe4/hFssW+0yAApf9OPGk5CGc/O50LI5Rq3nOTmT7InPDqgKOtjBnV+I2rdmUzQrcnaBPFnvuskEWIlKOJ3IjzxMmI1AoPkskrYAQPHWgwBdVug0FTmK+TJMSod/QKC7QiPXmyQP1GzuszhJgZt6MPdOIlVhJbGY/KwMpDE0F48sX67lPH7iz4ngzi/kTa3XnM49/LxBntRFvGBI1Mw7GBUuctDFBDbPZUy8lX/yAMX9QWzDcol8tgBXFXKv/aFGWSbpUZ/10BhFs67wym9l2PuqV1FnH98Yz/AihCovfziD86nT/bfFK2hKA1cQioslivszZCuZQOm9E/EuWqpshNEf9zEclMDJaaBAPP7SGF/59c/h1h9GSr/hnQHsw6nEZxKmrINRCbNuYM6m6D0YhbZ+a3p1bs5dNmRnO9vZley59Cw+bLs0eNZRTU/Je9Py8A1xoK4lMYRL1/T6Nt4We3jU/okJLJk3tl22f+v7uKHVRiKK7dZYw7Y+dHRQZNtj3kUpH8e2Ij/9/2aj43ZlsYYsATbMK7jFtmnMaMv90tL49G/6ndLgAS1aAkrva/I3tEfvS7KNHEA14rF6qcvuucLhkzaRc6Am+R6QSlLdFxCldm2/823V8Wq2jNcj7PmdLPSHa2j7c/pY8pt4vKZDwbxdMSxlEidJN6UCuZQGLoPWqfWSdwlwKM8C67JyKgI+aFrmgjLUH0uW+SCaz2YkHKGUSzl3S0wYmlFIJxsTsh5d5iTN4FA3C5IlkGcNlGl5thL2FhmsZ0NnTZ06J+X6RDHFqeAupla6mfLcl7fbjT6EzFIK8daMiaYk80zGinw61P/4XWkFgJVofYbAap7L8iBIKzbgPIMbFDB5kmbMMnmwsywCxeCDrymqMyFsrgZtmL3rZbDzDE0pbbBlLoS9DNQ9j6jsGzgLkMtgx16zVMemKOQ66xizQGbBuQ+qahasyLDeJ3A/khY3pRX+1g5hr+tZkEeX6ja2jCcpMHnsZEFE/wbAXwRwn5k/57f9EwA/D0AXS/+Imf+L/+4fAvibkFfy32fm/3b15lzRkqg7p+vj7j7btuvXLfSjiBBzoqql+2wII2+Usfsy7+51VquoABVSm6uQ9eD1OtwnXldCHa/XAARtWHmUYtO0y9mXKyCP7QjH1DWQrLPT7zkpUQ/f+7hFa1xmiygFEASS/V9PM2jPp0E5K/SB2Y+hAxpFCCZjsljGAHQyIbZK1AFgkShnQeJGWt6uKFQCIjlNQiyTP5iJfmmSVlZVcV4sROVL5ROYQZMZbONCLAq5i/2t6w1tVZpkGyXw3DQYvbsK3Bdghp1n4OkcxX3ZZqbzwD/Sq32Wp7RgQ7DzCuZ8ir3bPos2m0dhZL1XxsBM5rCrCm4VdWDN2RTXvtWHOYtxmHxdgyZzqQ1hDi8ZsyiBqpY+h8YzqL56zOIqnsW/BfCrAP5dZ/uvMPMvpxuI6E8B+FkAnwXwEoD/QUTfz/zhAh1SQhv1LLpSALpPi/wmMaPpJ+d/gHsjUAKOcvO5L27i4FmQtQCTHJvWdeyNoqK5tuvwAOZi3IIMm70R3LFkQ6iuQZ5Gn5oGfMtnMR5IoMyMhnBVFWolQg3GagXq90VPwwfrgo7E3gjw5wcAU9dAWcI4F+TxAqmM6pLs+WCXD5rxi9dhLvwPf+4DkmUBd20P5kKCwstPHqP3TQcQwR1IVgDMMOM5aF0lac+k8O7wIIKfDiSz40YD0F3/vUowXNuDOZ/EQOytY9EnqWvQkc+iHO7BzJbCCpWAws4/f4SDPzbgFIOSGTS9DPndC9Ee1QnHOfAL17G6PkDpg8c0GAiQarUGyiLwUQAAlzmqWwcRwu0BV2Y6w52f7IdgJjlGU1oU92c4+xFp7+jOANVQPJbpS/LI1X1C0wP69xl77/Rx989K/19/Zx84H6Ml9UAG69dvoNrPMazqEJCdv3GMd38G+PTD6wH7N3+hxOD9gXhZELV2AFgeZciWjMH7Q8xfjFIAzcnVFxePDXAy8/8CcHrF8/1lAP+RmVfM/G0A3wTwZ67cmp3tbGfPrH2QmMXfI6K/DuD3AfwDZj4D8DKA30v2ue23fai2jXuhu03/fxlPQ0toGJBlw7YCni5Dlec6IK38cywudvf6c1lGtNz+1RrGpxpdXYc3N5oGZiJVn3q1UEzlOSlTDIkuNzikb73ns1hGdxiSFibPv6lpwFAop+xTizY82oznYG3XSipLmR3M1IY2FA8jO5NJVOd5sWwHDpVbw7EUg6mHt1iCiGCYo1uvfTAGPF+Efc14Jq6341DEZY1fz9e1QKP9MnH43gpmLGlHtjGOY+YWtFiBGgeXSAqa8VzYo9T7o4Usq6oKWFXt1GlVSfXoIi6FAMA1DvvfdgGbAmbYMoeZzjG6I5id/OEc2VRSmdR4fE6P4DJCMW5QPJxj/y0f51muPA8nJUWNcn67KOKyDEDv/hIHX9tDdj4OQecBgOxsHuISmV+G2FUJu6xhT2cIckiOYdYf7jJkm/0LAL8IieH+IoB/CuBvPMkJiOgXAPwCAPRi8z8662LirQ2ydcEuI7XdkMfbhN+SNaKlmQYQrZHSYRK4tXIOMCRo17qOj20E6rqUcp9IgqIpBFjbkQTaQjsNRcRngH0n0OrEOI9cCFzbcF7OM9BSjm16GTLlSUhwDpRll3OX+tiB7heu1QkYcpkDy8yTzcj/dR/Sa+aZBI6ZJZDpx60eZsj9+IaYRWbhigzWmFZb9TyusAKB1nbp+OVZoMKT/wsPhFaPhv0MYb1HAUdBzBLMzDNUQ9knm+ZoBhnggGokfahLQlMQqAHyMkM1Su5hd+yIwGWOpp/DZllg9256GVbXAM5tGPe6b2GLTAKcAFzurzeQGImZ56gHvq2OwU8Ao3+qyYKZ7yUd+ZcA/rP/7x0Arya7vuK3bTvHrwH4NUDg3k/TDqDjOXwY0PVW+fvVZ93LT5ekupK0WprmDJ/TtKFnNNpIy+qxH7hlj2x0bEPnugCkXc7Jw9tltELivfh9Ax+qpvc+BJHemErspFm7KUxH7e+6KnEpW9dTNoXS7jBL/CBNYzMjuoz+GP3rfDrVxeOFlT2mOB/1qybXHk+9driuHvwhPBpPNVkQ0YvMrLjevwrgj/zn3wTw74non0ECnJ8B8H8+cCu717cRwh20Tg3FgBpzDHxekloNb7cgwtJr/QUQtE3jQQZkROBHBYFpQiLgMtFaEb9vvydIxfRG9npo9sSLMmc54AVhaDINgrnpvjSdSRXoeh1qB0AkQdh+T1icfX/lmDJUNQIAnUk7abWKAdmxivlIui0IG3tz+33YhKiXiIBeiWZvAOvRp6sbPQwfePKXgyiya5iB8aSVIfEDCQz6AbGqVY9ubxCCptoON+rDrKr4Gx/1QReFBJd9H5qDPqz16cokwDl7IUd5MoheBQCXWzSDDGbehxuVoHuxHsXt97E67qP/VhHumdsfgFaVeBFpXUqvwPqoH/godJzprsX4kxGZSY5R9yx6tQvBTGr64lEwMHnFa48OgKYH1P0MZt3HxMPAbw56bcEiADCE1VEfq8MMxZ2eVJ4CWNwqUH92hvXvxns+ezEHNQM0mqL1cO/FdYtsyTBNH/MXvGfRIMDir2JXSZ3+BwA/BeCYiG4D+McAfoqIfgQyX70F4G8BADN/lYh+A8DXANQA/u6HnQnZ2c529t2xx04WzPzXtmz+14/Y/5cA/NIHadSVrLte76AtH2u6Vvbl2gL+aa/5Q4WrrmmtEcyVScBPl5Soc2YDRyMl62fOpUQcWRbW0JRnaMoMYMCkHI8ejCXtS4SbrZUAXne9aUxLFZuSdnK3lDqUWnfandvYrkzW/5xZwQV476bumfDZlVFW0eQCJNM1NXkVdQEHJZoeyhmSJ9yjCoDLBfgUpB1zC2NjrAIAXGFhCklFul4WXPi6D7hClM04k/45a9AUBlxmcEWGTD20pkFTWFRDg4F6mdaPX23BmWmNGVsLV8RtOs5EhGqP0ZT+/04AV1xa1H2N8RDqkgSU5Z2AeshoSqAeEpqeQbWnXB+eQ9OYIB5E1sAVUhyX3ve6JNw4nKAeHAdkaN2TwrmmRwAjtKvuSyGbywyawv+eRdfpyvb8IjgfA2OOQKhLRiPZzsxbYbZRUyPGFuTYTaTkhpnO+eHBRFkM9IUHpHE+KIc2WW7KLh1OlhLZdsqdMwtXxACZMR7JmAZkwyTrt3eCfi4z4uKnRv5HqgV1mYdQZxa68iPfQmZuAaVC+7eNbx6RqTpBudzAJITALjcivAOEe8SZYCnCGX1zm5Ji4MFDmckwXJm8WJKMV3jw9b5aG4R/ZJJKRaCEMxOhXT7LAIBLB6cPYA04C7ARHIWOlz6guq0pgWbUwJ1lYAtwkfyOVQdGg7y1Q1MS6p6/vv/tNgXhpcEED3EcApVNIROl85Nlo3Njz09kpUHtV7zfO5PFo8haiNqBwm3WBWqtK+E6SIJzXc8inC/hoxTBn02RIVqtJa6Swr3rBnbmGbgcRxk5IphVLT9w/YE2TiDKzscNUsi5Y+FurBK+BQC8XMGOE6Lhag1eCriHtGJWJ6NKUJLcUVLLpmvQMjkvEaiqpd3+oSrGeo4aZq1yfgzom1A5PfzYEUtf47Vlu50sI0OXv74dr0CLVSz1H/vP7MJ4ZbMKZlUBdQOqmuBZ9E8czKIW7009rMqhOK9BtYNZRmUwNA3sokK2yMILh5Yr2EkGWq29UlgyNs6hPC3DNjuJ5+ndzVBcLMM4kMtg5xX69+N4UePjGX0PyhoS3FmG8pSRTx1KjaXUjXiTxoCr+GIoTys5x3IlaXcA/bMGX37rVby+bELAtH9qkE9rmMqnTpNS/XzuUJyvMRio5weY7UXZW+25nCwEdt2J2HeIVx6Ls1hvPmjiSXhSWGbJv6fn9TM+e/xCOP82nMVsEc4ZsPzzBcy5vNHdchnflHUNezoFOJaoc0IkmyqKgZ1gQrwqmYxHxFlowBDo4CwCOfBjcBbnU4F8AwHejbqRl7d/UHp356CpkLTou5ccA/OFlJZrf5X0xbGHMXvC3+lcJpF1tYGzMF2cxcU04ix8H4whmdCaRhCj3vZu9wWKntac+HJ1Gs9g6l6cHJsG9uEEPeYIb2cH48QzouW6jbNYZcgzG9vg73fTOFx70wVoN5hhx7lAuN+RV3jxcI68lHoWs1achQFbIJ86FKdLHL7pl36TmZALm4izICLkJ1PYeSHX957b4M4Ce1/aQ/ngLPxGzaqH/OEMWac2JJtFnMXQRa/cfgQ4i++8JcxYAFqQbWFE8rvp2z/lxazqmCVJMiepGQ9zdp4FiQ4PQItlIL+h6QxmNJQHXt88paho06Af4Ne0WIIO9hOQlr/WjUOYMys/OF3yXL+G9YvXAAMUVQ13uC/nqGssX78uBDL3fLnNrWMYQGDd5wY0FHgxLxagg31wvwzMzQrVpoN9VK9cD33MlivJhjQN4KHS2k4aDID5HHQgbcBYSIDWr11HfuLP5x9qHvSwvj5EdiYPz/ln93DoJ7X1DYV7y0NhUs/MizTzugLfOoI5FVi1Oz4AE8ENcuQq6uuzGtULB8jvZiHTU716HbmTehiFxK9vDMW7WFRohkVIC977Qh83zXWwiW54IL+5XaIe5igTrszFZ25gdivH8X0ZAx70UHnym6ZDfuP6BWavjQILd+DMPD3Dvb9QBT4KMFANCHu3iwDh3n8rFxyFQ8h6VHsOXDDKezkO37R4+JekXQffuAF7MhZ5Q2XhNgaT7z8U8pvpKnB0PvjhEb7ws1/B19/7XHh5TV+y2H+nEPIblhgGACxuEfIxY//tMpDfmAao3rr6OmTHZ7Gzne3sSvbMc3Bu8yxgbGcN79fWj+K/7J439/s2gtGgLJNAnF5vXUmxlbJlwWM6qrXPEvjgWLUG5UWMH2gTBwNfxZqAsvIs4CVSdm9er8XTaVzCsu1LwDXQqQCdupZ+uihqrLEAyvIWbkK9Gq4rGF+opRSBWninPJjafnvtoCVKrFWbVBRhyUbDgYxL4yIuxTVBzyP00dPqBfEmLWIrCvE4GheXBUo9WAiuJMQRfMEb15XQHAJyfh3bPIk5HOwJA5qxHaU0J0uqVC3NsWBVeiWcL96D83GipvGq78mC3hhQvxe1S/y9c9MpzA/9AOi9k9APynOpfr3mvbblKlAg8CAqoAOQuMtkhuYVKUQzb92VeJo1UZjZWlF4z3O484vA7pa9eAvr77uJ4tv3I56nyMHz5UbVKYpclp7zBcjje+AcfvfkN3CxunclsMWzuwx5lH0YyMoOko9VvTvd2EUaanS6aZBS/G9VkFJdSSCZWOo2ypH9BKN1D+kEFwhmN1GRgTi2qwTfNCGu0GoncySybZXb8+Y4LFdtwpwkXhPiALO5HNc0cby0lH6b+ThAOK9OclW9SfyrhMratyVkH+aNOFPoj96ni4lMTMoBorsk3KthImMWxflkInbryteaCB1gq4rZEx8Fwt4EuGZOLgLVHQDA88LifNxqLzNHwJWXaIC14MUS9kT2DXQHnJD2EMFNZyBr5T7q73AyRXEnBy+XcUyWnhrBWrleyLxJbQ/XdZRfAEJQ+ir27E4Wj2K3fhzt/hXo/1upvCTNGvVAfLzDozavdN3L2rkNf6/4DgCwtFFiDyXl0YchYZ8SD+fqSlJPbWkbjYlvKUMg4z2xQKrja1gSAqHAFJUUdem+Qkj7ZH1oHc8sHo81ccJSXInqpwAhoxMYtbRtqOV+J7UWT20JQQ8A6W8qG6D55YSZiozxLPFGgpkp3oQp6LMCuJRmAfDpX02DAzIuqm/rkOBpPniBwLM7WegbcNsgpRmKZJDCA7QloLl5iiSbQgm1vxLG1BXvfggpAAAW8klEQVRc9y1Hl0xe2y8Qly8Jr0N44zVN1PtgF37Mob+6BOlQ818mD/hhWbim9iG0MVFcR+4p7BugSsbfexsb3lBC3BvO9RQ6JSE7oO305wrWGJ+xchLUjZ2KJDueNj9IDgAffOJVIh61tf+/ehQ6DgktHtdKpCSSmRrMdCoiZG3MdplLJgpmmKqWJWSajfNj4A8GgA+llmgX4NzZznZ2JXt2PYvHWSoixIlgj3531cBtd2mRwMcF3v2Ub3K/fGnhLxKuTCbTWloEVznhoiTIcggueSvrcR9FxU3SRkpQoEQkQsEuihRx0yR8n9578h5EgMi7ZDliTAsAdyVLIOqh0jIRJArNTkv1HUuMJCmRBxCh6Cls/mnH1Nr278/aTgmAS6gGktKB2iVwftM6l8Dmo6DRpb9DXXZR6inHZdfTeHCX2fM7WYTJIC2HbqtNwTXxL9CaRFQtSgN/qkClGZVmtYJbtQOIgAOMhemVIWvSTGew+yM0njJOH2qzP5LIeYoP6fdAXizInTwEDQXT4S7GMIeSp69v3wn7NtOZYEqaOqpbLZcgymEODwIZjLrRZtgH7e3F4Tg9A+UZ3GIZcSUXnkLOa7sqvWDjKfrszRtBHyTQ9RWFZEA0E/DiDdD7D4Aij3gTSPaFL8ZBHwQIEAjY/YNwvPbbXE80O3z/VPxI4xl0sC+6IYsFzMgLGnn8C+q6RbDcfN8LyG4/RMusAcoj4GwMKgs096LGhr1xDB7EKk6zN5L+1DVQFhGcBohY1f4o6IZQT7RD3YMTTL7wCkZ/nOiHZhZmMsf69agbwp7vYnXkK24LgY+XpxXykykm3y90iKP/PYebzlrLb24amNdfhRuUsLfvS0ATAD71Ku79+AFu/s+7YV93OII5m8b6Gz9xN/uSDcseTNBcVzpHBn+tXXX8KHs+J4s0gPk4Fu/UUm8jRMsTBuWURVvPDbSuRUoYk6vQMLWP0UPzXG5U95oaeLORLbu1vds+a6WNHbIdyvPI8KRvHWvDjxKAvF00oNclv1GZu5Qsh1nIZqokOAhI0VuvCChSNyxhMiGu4V4sEScPjoPbXGOH8fCfAYjQ7zbym3VMhyr5DafHlYUET1MmcQDVfhELxbRLmQUPSphZLmOcBPq4zOEGZYt1nMtcMh8JCRAAoJB97UUW2q62PLQiAARI3Cm3sKsK1b60xS4KNH0/WRwqKY3UelAD2HmB5aFcay/Po8RhYm5QohkVsFlCdDMqML9Jwi2qY7BXoFiVgfxGC96qfRkzOy1QDz9C8pvvpm1onarX0A1qqjuWHpsXElRqmphO88e56Uy+S7Uyu+d0DRhW0pOBlVrTnj745nEL7vxC2MET99E5lgcKks5zGgBbr2OuX/edzuR6q1X8q11breDSgK6m0mZzUFVHGLmyZDuG8wpsKYaCHQedTCoKSWXeOxHmbCSBObMUBTSfcjNvAW48Fhd3FlOGXFUt+r9Wf/x4yDB6vMZyGVXK1pW430pvqPucRCxGVC9bSH1EWncDoP81hvNylGpEFLwrTR+G9t47gTnL4VSBzTmQ4mqKPELR/XLLzOYSgPRtUKax4y8+ALzim+rLutUaQw2WLxawfjIs7ognx1aWD7RcgWdzHE9jH7t6rQBgb9+XiWKxCEuL4pvv4xPLG6B3AxcVeg/7gqXoSD8MeqXIJIwn6J2pF8xSL3NFe34miyeJQwAxPpCQ34QSc9qCL9Csx2MyHsLw7RJno1sm7kuju3Uleo2koCtmZHijoCvQ+3f+hs9pBN/HFpgZSPVePb0cJRWjXTHhFPwUuDITAZ1wfhfHjCcTmViQ4A20XZfcoxY+wF+zFS3SDIBC9fWcKi+ZZVFqUjExrl3N6s7O25M9/DJoRVGSIb0fftIPoLamkTSqcyDbizU9un8qR+nbS/2eSFUmOAuJ07gwuaGqYtm+Aq18atzVtdSiNBHrsQ1HxMuljDdRa/lqbwNNem3FUnRelLxcwhwfSX1OiqN5grjRLhuys53t7Er2/HgWKe4iCVqGZUkKAQ8zp182eHOJ6LHxgUCtLDQH+wLx9gVNzcNTWVJwxD5Qlkmwqd+LgdCLsUCp1WPwy4XshVtws7kETZU8ZzgADkW/g++dhICdOzsHvfqSnO+b3wYA2KNrcJMpTFmKQLLSzk2nsHt7oEE/Li20QnMwEH0O7e+9B6CigJvPYX1gNULDM6CuYQZeNf5MAnf2M58EeQbyILJT5MDeUArLANSv30L21j0BYu1F3RCazuXtvoVrxB4fbQQ4edgPgs3w8HscjICLKUjh88dHwMkpmvEU2S0JGPL+SErF11WLVm/+xk30/8SfL+X4KHPYkwtwrwDficFAeuVFuIMB7Jtvy/8HfaE6rGqJ5eh9A4Sw9/o+7F2/XPSQ6ebO+zj5uR/F8Zdk+UPOgYsM5myK+RvHAISFu+nJo7a4Je1Vwt7+WYPBnQUe/LAEHW/917eDaHerFONTr4oK/DffD0ut+sfewO2f7uP13zwPu62O+ygfzDcIe9fXCtilQ7HXx+rYB4qZ4X7/Yx7gNEUeMhVUFPIAF3my1nMS7V814e/GObzojtMU2q1jmNkiiuacnsMM++JuJ1Wn1DQw1w5CdapZLICb1+UvALeUazWv3oS9fy4PiLr9N48w++QB2AB7jUN9S9pgncPk8zdAjjF46zYAgF++CfOOA13bB52cwlyXaDkvFqDrh2iu78He9UGsqV+D3ryO2aejyNBwXYGHfZh7LtYe+AmTRiM57qavUj2XH9z0s8fov+crKs+l6tSNSsxfGaJ/T459/ydGeME/SPOXlXsS6N9dIquqSFSr8RPHqF+7ieyeuOXVi9cAIqyOCoy+6gl19uThW7wyQv92T6QRAMzeOMbQMcxyher1W7LtlR7KsxrZokG1l4eXwzs/k+Hl3z6GS8hfXCZVoIffKLG6lmPfyxxwXWP8+WNMPmHxykOpZm2ORlje7CObN6gHFr37MRtSjwqcf7rE8ZflXi5vSnsHp2f4/M//Eb7y65+TcWiA9T7h2rf6ePdn5NiDr+1hdU3GqP6sTMQ3Did4aTDBl996FXtf2sMXfvYr0oevf1og3NbA6JLHGNz78QPMbxI+sbwBKz8R3P7pPv74b/9z/OiDvxNIg8efAg7eLFCNPDOXT9LMP9Egu8hw7c0C52/409bA+htXD3A+84VkWy3xIgIUNvUs1DwkeNs6Wt+ovJYCIzPsS2FU4lmYfr9Vv0BZHouy0kKi0QhuGoNGAGCPr0vgM6mpoLKUtyoR+GIMqArXfA5z6wbgHJrb70n7Dg9FicxauNUqeDJuNocdDX1NgdcCUc+n3w/eCiAeC/Jc0o7ek3I+RaoemaY+dXv26isxfqLFV1kmno0GKG9cg3k4liCp9yyolniMOztvF/RpDGBvL/BG0KAfsAAhaKnZpeEQPJvFdPC1Awn6LZawN67H4zUIWkadz+rlI+TvnwufRZrlqRvQfCkBvjOZFLlxMMdHaI5GMN/yTx8ZKVyrG0mVpnGkLBOv56Ecr55e8+AE07/yY9j/wxig5n4BczbB+lVpb3a+FJ1S57C+Lr+7euCZtpYNygdzjN+QF8e133lHUqPGRj4Ra4HDA/CgBL17L8RH6Ac/hXt/7gC3vngR61sGBezZXLI5zCEb0oxKmHkFez5Fc82nTpnxxf/3rzCe3vkYF5I9znSSeFJz7YCk/P8pi9YSKr5t1PdtqjyO/8K2LW35KIwTeLljwCRjEJYX0h5mbhVUbdAPItkv3Z72/Uks1XFJ/4XtyXfdwF13X3+vqUm2bWYsr2bpuygZh0D3z7zBxK9pyyAbkLZLvV0XTnDppcnfC0rV0jmRlkjb9QFtF+Dc2c52diV7Lj0LMgSueXNb09qAR4G1Im+Fd/XyQt52CSKQmbHBGk4GyPOwXMHMyOdZG8BFvV50lU0EHvGwLxWBk0k4B89m4H4pKVSNj2SZFAN57RJ10zGXClRxl9uEwlQWMeAIAKnuiPJczBM+BubYDy/EzXuDtu4HeX6GUR80kevUh30U5xNpY78MbaDG4x4Up5EEOqksglsdlikJelJBaTwUBKWygPGwD5ovQKtVoi0ygJkvhT+jiDGL5c0S2XkpHBo2QsNdYZFVNbhfgh8mqdNhH/WoQK6grEFfrreuwEUeFNBkvDI0hyNYX/Cl2ic4PcP0ZYuhlyqkRoSR83WN+QvS3gFEKYxYdD0Az8JdEPqnBmbVw/QlacNBkUuwvONlusMRqr0CvYf9UGK+Ou5j/Cng+A+K4IWsbvTQcxxY1zXAuTrMYZcOPQDLF3xbHcN9+2MMygJinj79vMG1+RjC3kAc41hK0FeeLzPdKVSdJhgFdpI3T64juev2dXi59KCsuJyg1SpQ1blK9EoByVCYybyNAVit5VhPBpziB7iqAYrAsFDdmGipyn6+nSkxbyDNlcrIkPHwRpN5jIUEhKgDTWKMJH84C5DjgHNw7Alxkok1rV5dLCJGQfVCnRPOTiDIFdIsAye6s2YmvJ7szw8IBydWHk+QAPT67y9Ak7lICSTl7JRZASql2rPOgcYz5ClPhm8T140QLndiFsafR/fT8dx/u4Z9mACdihw0mWPwvjyU2dkc1nNiUuOzT6UBZ4R8WiN/OMP+O34CnS9jrCeoqBPM2VSQmQk/aflgjoM3JUahv52eY5jzGYwnBVL5BLMqYZY17PkUKqNFzDDV1Zcnz+VkkdplimNXhYGHH7sndm0BlgyBOFE60/OmWiDkP3eh4coxkIK2rI3U+6pTAg+eSjQ7Q3uUn4HaRVBSPJRwKCQFaqlnpO2U4q72vnrejUIj1TsBQOSzGda0tnORRUhy4LjgVqEZADA4FpCZhERXi6dSYt1OuyLhrmkdF/4qlD6LGrGuzMI5A4zZSNspy6IsQrKdiyw5vw/mAp5PIk7QlIneKzrwdJARvkuFmfvUKWUWrvTjlduQygxKYV4Y2VQWWZHJOfx1VJ82lJkbI8HZQiD2YXwL0UjVYKaOgcmzQNSrEHtti8kz0VqBB7c9QfDouZ8sLmPvfpLjt2laAGgH1J78xI/elgQsuRuM2rh+51wfVbCz1YZOsKy7PfWKWgHONGDa7vMTBzm33ett48YcUomswUHXDdJ2iwQ/oHXH55J2xc+d7Rw/c9L+Vlu3GDE2g5lbxok+hH4+95PFpZ7FYw+kcLz/EBiGgmkp+LbMSne/rtn41kypzUKptImqW+RVvyi9yd4rieXs0eMhFZrptku9gM45Qv+29H+bqlmLXYn8m95GXsuWSph6SiysT6mnknoWqiovTUnK8DuCS7DiBVETtwdQm17TGrmW9w6CZ1EYH69IxsarjJH1SmuJZ8GZBecWJqU7sEY8IWvaY2aMlOVT0k5vTUnhTY6Gg3hSU8g+mbUSO+CoPdqUBk0uuh6c28DCHUvWCYG4xlMCiEBVvK7LRTAoVaFzuQHnWfAo2McsmtLCOog3pfsbAj9B1nCXDdnZznZ2JXsuPYtt3kQ3G/JYFXWt91+tZLYuchC7WDYeT4SQDVEV9SwL8GQyJJkUrfTU2quiEBBSSwIvC+zOlCUK4MaAe2XLM6U8bxPOpB6DtZJd0EpU69uXF5E9Gt4DyQuQXYWsR/BmrJXj8giXBgA36AXkIPviKyoL0Snx26v9EjaXcm/u++MdfMWriW5z6rWURVR9L3KoHgnGWegv4DMkq3VYyvCgB0wyGV/NHg39GFZRcxUAlkcZins9eQXquj4zcL0cNF+Be2X00JwD9wuBUOsY90q53rqS30NaJFfmaPZL5BdlbJcfz/ktwsFIS9QZrmdhFiWWR9I3uyoFhMWiZg6I9mjTA9gSslmJxS2KY+NjFuk7v9kvUe0XGPTKEFxeXysw/0SDZlQG72p1mMOsSrjSglgyMwCwPMyQDQzMqsTqui9RrxE0Ya9iz+VkcWk2JF2XkQ+qWRsJaBKUp5Zfy/Geqbpxcd9WCbi/RtPA9Eq5kcFttpLSCwE6Pzn4TEiLITqpFhWW5SqeVzMPvuaFqwpuXcHkuVSoJuCnUFWo6VSWsmgqcplw1LXs9wTt6JoYgNNlUC7s0oF0xksPUMJALsAmJ8HCKko22qV8piwDpSXOdRN5OLu2riLSVPs67MfJuSwQhJ219gOAMwam15NjVB5xXUs7q3b2KltwS6EM8AFDY0T60JiQfQEAs6ph50m7NIjIjPWtEQodx6oG93KJK4RlHcH1MthrB8inHGQc4ZzEB6oa2ZLjePnjdBs5+ZfPHeyyRj7mOE6XlPmTlz4wx0f+vA7ZRQYzj322SwezjBki629lNjCYvmDRu58Ef7MkVnIFey4ni5arcEmKVCjeG3DVOS7ULVSt43i1bqdEt5wz6JoCkZylqqVku1PWreXP6YOTpja5qlrpTEpSnqE9Pk0b/qpVFXg+bzFlsSEY54OG/kfupjNgtRKmLH3TVu3JkFOeC3ag6TykBzlJa2pKEwCyh3JeXleth5Xniyjq2zFOOUCUgetiCqfFZas1YAhmXbXSrKZxcOOJbFMiHyIZnw5TVv/ufGMcYW04J9V1637QdA7rXOTvGE9k0q5rlItVZMpiB5PnoMUgEP5S3cASwY0n2H+7FnYqyAPNmQVNZhi8r6plM5h57vvj4fWZQVMaFOdr2NMZ9t9W6P8C20iqswcT2GkBHk9CurvY6+PamwXseZSs7AGw51NJnQIh+2ZWJXr3DbL7Ywx1YmOGqa4e8Hs+J4srMGU9bhkSGJaUI6EshC8gBSltYcpS+nit66D5HChLkJm1d1XQVOLttEBT01kLKBW2vx/3xUwAYFhXsb3LpYDCFPQFRBKYspQCN+V5nE5B/q2sYkCkP/Ysk+N8P6Cs16PBZpaiyANYCgDq60Nk52MBZSk4CT4LN5+DtpBZpiAy7TfvDUCKuSi8Z+FBYWzWcZ/lErxcBXEc3h+C5jZWh3pbvDDAcJyA0gCpOh2WsKtKAGSnZ+ErHg3QHPRh7nrvqt8X8Nmqghv1YBJQGZc5msMhshSUZQ1wMcb4tQy9B6NwLzi3sADmL/piMwD1QK4xf0H+NgWh7gODgcHQcZAUHH6l39b18NZcH6Ee5kJco0uO4yHO3wCOvjIK+y1fGKAHhPSoBjNX13OwIQzXDZa3VGQIcN/cBTh3trOdfcj2fHoW3wnbghd49P4pZuKqx1ySf9923afNizMj5TB+4qpi5gSD4Nrbw2f/d1vh3ZNYd9xUV6NbzLYNG6HtTD23btwq3Xfb2KcFXJ0+UrM5blr01TovAGqQfGaw5fa5XfxM6nk28R8cw6gzdskYUsOxf0GPhmHqNoaCnBSRheCsepk1fIwi/j5k362X22rP5WTRosp73HIjtXRQuzgLYz1iMWYvNjIchuJ/0izHJTgLpbWL+yVEvx1q/VZJtbbH4yz0b6vtXUyIqpZ1z6PfbcNkpH+1X3lUwgrtM5K7V3yEK618Tin3kz5v/f3peCTn3UBU6rbU0n20nieX61ICZwaAum82+s+Z1IZYX7beQqzmGVyZIesopbHHH4Q9PbrXFRY2bScR4ByqkXwHAJQZuNzC5pm0B4KqVORmNVCcBVAPCPWU4EpBYoY+blFIc4VF3bMorQn3qu5ZrA84XBsAmr70N9SGeKxHPTAwtWBAnMd6UENPRNj7TPBZENEDADMAJ9/ttnzEdoxdn78X7Fnu82vMfOMqOz4TkwUAENHvM/MXvtvt+Cht1+fvDfu49HkX4NzZznZ2JdtNFjvb2c6uZM/SZPFr3+0GfBds1+fvDftY9PmZiVnsbGc7e7btWfIsdraznT3DtpssdraznV3JdpPFzna2syvZbrLY2c52diXbTRY729nOrmT/H7bPZjCguBGRAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.5098705291748 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 0.001, 'kernel_type': 'size'} is: \n",
+      "[[5.12000256e-19 6.40000000e-20 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [6.40000000e-20 2.20000168e-19 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000256e-19 ... 5.12000256e-19\n",
+      "  5.12000256e-19 5.12000256e-19]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000256e-19 ... 4.48896334e-16\n",
+      "  4.32544301e-16 4.79584333e-16]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000256e-19 ... 4.32544301e-16\n",
+      "  4.18176282e-16 4.62256310e-16]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000256e-19 ... 4.79584333e-16\n",
+      "  4.62256310e-16 5.21632465e-16]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f548227f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.27455854415894 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 0.01, 'kernel_type': 'size'} is: \n",
+      "[[5.12025603e-12 6.40000000e-13 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [6.40000000e-13 2.20016802e-12 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12025603e-12 ... 5.12025603e-12\n",
+      "  5.12025603e-12 5.12025603e-12]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 5.12025603e-12 ... 4.48929383e-09\n",
+      "  4.32574106e-09 4.79617316e-09]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12025603e-12 ... 4.32574106e-09\n",
+      "  4.18204217e-09 4.62287036e-09]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12025603e-12 ... 4.79617316e-09\n",
+      "  4.62287036e-09 5.21678563e-09]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.56928086280823 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 0.1, 'kernel_type': 'size'} is: \n",
+      "[[5.14586655e-05 6.40000000e-06 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [6.40000000e-06 2.21701405e-05 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 5.14586655e-05 ... 5.14586655e-05\n",
+      "  5.14586655e-05 5.14586655e-05]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 5.14586655e-05 ... 4.52306126e-02\n",
+      "  4.35624025e-02 4.82987231e-02]\n",
+      " [0.00000000e+00 0.00000000e+00 5.14586655e-05 ... 4.35624025e-02\n",
+      "  4.21071151e-02 4.65447745e-02]\n",
+      " [0.00000000e+00 0.00000000e+00 5.14586655e-05 ... 4.82987231e-02\n",
+      "  4.65447745e-02 5.26460986e-02]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483ee48>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.25135636329651 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1.0, 'kernel_type': 'size'} is: \n",
+      "[[4.43366876e+011 6.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [6.40000000e+001 3.33543843e+016 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 4.43366876e+011 ... 4.43366876e+011\n",
+      "  4.43366876e+011 4.43366876e+011]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 4.43366876e+011 ... 9.10740306e+105\n",
+      "  4.00003678e+084 3.69541495e+050]\n",
+      " [0.00000000e+000 0.00000000e+000 4.43366876e+011 ... 4.00003678e+084\n",
+      "  6.46259407e+112 2.00383323e+067]\n",
+      " [0.00000000e+000 0.00000000e+000 4.43366876e+011 ... 3.69541495e+050\n",
+      "  2.00383323e+067 5.92939736e+087]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 72.52125263214111 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 10.0, 'kernel_type': 'size'} is: \n",
+      "[[1.16270855e+090 6.40000000e+008 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [6.40000000e+008 3.91203099e+175 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.16270855e+090 ... 1.16270855e+090\n",
+      "  1.16270855e+090 1.16270855e+090]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.16270855e+090 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.16270855e+090 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.16270855e+090 ...             nan\n",
+      "              nan             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 73.16563081741333 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 100.0, 'kernel_type': 'size'} is: \n",
+      "[[1.07460112e+171 6.40000000e+015 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [6.40000000e+015             inf 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07460112e+171 ... 1.07460112e+171\n",
+      "  1.07460112e+171 1.07460112e+171]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.07460112e+171 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07460112e+171 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07460112e+171 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAHQVJREFUeJztnV+sH0d1x7/n3sSXOnJKTForglACch5Cq1qJSVoJoaDKDgkPhgeu7KYUEJJ5SJ7b0BdQpUhRK0SFWiIFNUookNQ8RERVAF/5hQcEJEEIAmrAgqDESuIWIxLF1E7unT78du313NndM7vzb/f3/UhX9/fbPzNn5jd79syZMzNijAEhhPSxklsAQsg0oLIghKigsiCEqKCyIISooLIghKigsiCEqMiuLETkAyLyrIicFJF7cssTCxF5TkR+IiI/EpGnqmO7RWRDRH5R/b8qt5xjEJEHReS0iDzTOOYsoyz4QvW7/1hEbswn+XBayvxZETlV/dY/EpE7Guc+XZX5WRG5LY/Uw8iqLERkFcC/AbgdwA0AjojIDTllisz7jTH7jDH7q+/3ADhhjNkL4ET1fco8BOAD1rG2Mt4OYG/1dxTA/YlkDM1D2F5mAPh89VvvM8Y8AQBV2z4M4N3VPV+snoFJkNuyuBnASWPML40x5wE8CuBQZplScgjAw9XnhwF8KKMsozHGfAfAGetwWxkPAfiyWfA9AG8WkWvSSBqOljK3cQjAo8aYc8aYXwE4icUzMAlyK4u3Ani+8f2F6tgcMQCOi8jTInK0OrbHGPNi9fklAHvyiBaVtjLO/be/u+pePdjoXk66zLmVxTLxXmPMjViY33eJyPuaJ80i7n7WsffLUMaK+wG8C8A+AC8C+FxeccKQW1mcAnBt4/vbqmOzwxhzqvp/GsBjWJifL9emd/X/dD4Jo9FWxtn+9saYl40xm8aYLQBfwsWuxqTLnFtZPAlgr4hcJyI7sHD+PJ5ZpuCIyBUisqv+DOAggGewKOvHqss+BuAbeSSMSlsZHwfwt9WoyF8A+F2juzJpLN/Lh7H4rYFFmQ+LyJqIXIeFc/cHqeUbymU5MzfGvCEidwP4NoBVAA8aY36aU6ZI7AHwmIgAizr/mjHmWyLyJIBjIvJJAL8GsJ5RxtGIyCMAbgVwtYi8AOAzAO6Du4xPALgDCyffWQCfSC5wAFrKfKuI7MOiy/UcgE8BgDHmpyJyDMDPALwB4C5jzGYOuYcgnKJOCNGQuxtCCJkIVBaEEBVUFoQQFVQWhBAVVBaEEBXRlIXvbNJGCPTSwDIvB3MpcxRlMXA26Swq1BOWeTmYRZljWRbLPpuUkNkRK4LTNbvulraLd8iaefvb344rZfclEWLX3/RO/PzpX/Zmdv1N7wQA1bUl8Sbs3FbmuZOzzNr2FJq+MueSCwD+D6/hvDknmmuzhXtX/bijwKIyr3/+ZsAW+YfALXJdf2I/XPxTXUuWF217Sk1Gub5vTqivjdUN6Z1dZ4x5wBiz3xiz/3KsRRKDEBKKWJbFhdmkWCiJwwD+WnvzxtbXcWDlI+rjmvQADLq3pDxCUMtpU7rcpWDX3zLVW7SJZNUipf+Ci7NJ72279krZbW6Rv7rkWJdiaPvBmsf7fsS2h6YPbeMYmn5oOXyJLXcT3zKMle3Aykc60xhap7Hlqq8Zm68rje+bE3jFnFH5LIqYdXql7DavmDPbCqO1JKbyVid5GWqZxianXJNUFrZlUeOjCEIqjVwKaOrdBJf8JcleajciV735KAuGexNCVBRvWdT4mmou/4WPT0OTbhM7j9hvhdA+lxyWVIg+d0g08gztKo8lhOXhSkNEnm7sY9NJkcqCoyHxmHo3JzeldmOGMiufhc0YTU6l0U6pzr/SSV1vIazjJrNQFhw6DSOHLxw69SdFnZUwdEoHJyGZmYpFR2VBCFExG2WR0nwm06TUNlKqXDbF+CwYwUliU6oTdyoRnFl3JAtBCK1c/1i2g9T+EUMO3WqGMEMPIQ+hmVezHF3y9ynvUMq9LfbA5QCvj9l5h6jLtnZi11fXNV1pDnX2h2i7TYqxLNpGQzQPGkdDwsHREH+WZSLZbHwWhJC4FN8NKbGPScgyUmw3xKb0uSF1mqXPDQHccnJuyDB5lmluSPGWxVSYigVUyzkVeUtjmeuNyiIgUxkvn4qcpbNs9VhkN4SzTuPBWafjWOZZpxwNIYSoKLIb0mVV+EZ1NtPj4jdc/KaLZV38Rns/LQtCiIrJKYup9xEJmSpFOjiBshe/0ZieucKm++qmb75BLg+/LVfX/I4xeWjCqvvmbTTlrWVOiau9D8UnzmJylgUhJA9FOjhLp4SuUJsM2uOlliFn0Jiddwl1VBNCFlcau3DVTdr7Z2NZLFuADPGHbWQcs7EsQvRpfehaqyAXbf38LtlKCSbTrsuQUo6u9SCy1JsIMMLH6PLFXLmyW33/bJRFakXRbCQ5HjRXo7YbQtvCNc1zOZVEWyxMVzliy9Pl4AwRpzNGthB522V61fxWHWcxG2WRkr5VkFLJYNNlWbT5LHJaFm0jCtpVomLI01xRqyTL4sDKR0ZbFnU6zbreJUvosyCExKV4y0KrwVP7LHJ3Q1x0jS743JMD39GdoXkMWb7OdTy1XACCWBXN/4s09ffPxrKgp5v0UWobKVUum+KVhdYJV8obkpQL28g4ilcWhMydqSgxKgtCiIrZKIup9PtIPkptI6XKZVPsrFOb0lf3tj3aJSzU4sJnNmVspr74TcpYixJW915aZWGf0+ah3QrAlX6XDG0Nz44mDD1VWzPduS3wzKcBp3p7dsmokd83rxjlSrl0ALcCUKB5KEOmX+fRdd4lj2tsPGQj1SxA24xqtK/VlinEA+CKOu0KyXbd56rHoetDdL2QttXN6vri/OaxzjR92t2B1XVsbB5TRZoe3HEEx88/ok7bxWx8FoSQuCytZWGTYg0Dnzdv0jkH6O+GDDkXi6HRs0MiXPvS65pUGDq/bRjT225C5kdlUTG2G6LpGmj6z7EnULlmdPZRilPXlkfbHeuqU996bqblmnSWshsCEa9uyFiKdHC2/YA+P2zX9OyxdPXdUz8wfWj74zkshJJHQ3wVUWxKGA2ZrWUx1GnVh3ZUIDaaN2Tz7VcifU7m+ppU09Rdb2T7vMuhWoJsQ9IB/JbVK9KycNFsSJofJ0ecRfN8CTEBLvqGNhln4SdDKmVRgmXB0RBCiIpiLYsujd0WG+AbxzAErXWT0vzvMlHbLJ4uv1AObLn6YjqG5qHx3bTJ4JK3ljklIbvYtCwIIcGZrYMzJjlGDrQyaI+XWoYU8S5t2HmXUEc1IWRxpcF9QwhxwDYyjtkoC0JIXGbTDQk5uUqDHalXgsna5hTski3HkGmXHDWxI1k1cmgiI5PW25Q3GRKR5wC8CmATwBvGmP0ishvAfwJ4B4DnAKwbY347Jp/SKMGc1Yz8uMK6cz2ELrrq0ZY9RyyDZkZrKkKF1dtl8NlkKEQ35P3GmH2N4Zd7AJwwxuwFcKL6TgiZODF8FocAPFx9fhjAhyLksY0cY92lec2HzHJsliMnpdSnVoZS6i0lY5WFAXBcRJ4WkaPVsT3GmBerzy8B2DMyD0JIAYx1cL7XGHNKRP4YwIaI/HfzpDHGiIjTI1Mpl6MA8CbsHCkGISQ2o5SFMeZU9f+0iDwG4GYAL4vINcaYF0XkGgCnW+59AMADwCLce4wcqSnB/GRQVngYlNXNYGUhIlcAWDHGvFp9PgjgHwE8DuBjAO6r/n9jaB6lkmsKdZcM9rEmrvU2xi72EwIfP1OumZ195FjPIuSMaRFRj4aMsSz2AHhMROp0vmaM+ZaIPAngmIh8EsCvAayPyIMQUgiDlYUx5pcA/txx/DcAuhen8ED75ksZlFWCSe878tEmcwkjDynzG7rWaEy0s2FD5GOzlHNDCCFxmU24d2oY7h2WFOHevosTpwr3VlvEUw73LolcC5DYn3MyNCirBHxHd3LLkaXeRi5U5ex6eiQ5G2WR0mdRgiXR9QZs4rtSVkraRnTaVsoaS18bsdd5Lcm/MfXRkKUl90PWJUPRb0YLxlnoKcHBWbyyKOkHqyn1rWwfb56jZaGTh5ZFOxwNIYSoKN6yKJHcb+QuGdgNGU6ubshU4ixmoyxSr5KV+2FjN2Rcfm3nc3RDxgzpjs3HpxtS7L4hNr6NWzt3omssvS9dV1p9jbxNhrZxe9ccjpD7Z/TNK2leX18rl++Aef18b33a5UhBV31rfgvfvGKUy1WHseqP+4aQqJjXz+cWgWSAyoIQomI2PgtfhkQ7jk1/zHE7YjSWWeojn099hTCth/w+XfeE6pbknIDmw9g2s7TKIgYlrPqtwbXqN/Fn2eqOyqIixGIwmnDi5rWucylGK3wtE82iOvX3FPg6e7vqNEQ9N9Nok+3A6mJZl43NYypZVYhgY/NYp5O+luHgjiP6dFtYWmXhUgoh3xR9Skf7kMUYDelijBLpevBCyOzKb8h99vEUsvUpieZ9WoVRp6mpl+PnH1Gl2QUdnIQQFVQWhBAVS9sNsbEDj4agCdnVmrwx+/9DRiHa+vul4ROURfxYWmWhiZT0Ta+vYfo03Fqe0EOnQ8KY2/r2Pg7OkEOnXf6brqhSW+HZStDXWeojWwwH54HVdS8H51i/xdIqC5sUk4d8HqaS3oK+SiA29gM/5L4h99v3uV4sfbIFrS9jettNyPw4NyTg3BAXJc4N8YVzQ9LCuSGEkElTpGXR9ob3GoNuCZQJQVffPXVgUh/a/niO7kSKcG8fbCvEx4cRGx8rzicNH8titj4LH6eVD6WMCmgiETe2vl6sqQ30d7nqa2JGs7bJ09ddbF5XgmxD0gGWdPEbm74fsS2CU/PDa36sLh+ETSifRYxIxGae2rKMka1tdGPokHNIn0XMem+i9VkMyde+Z/KL34TshoQeZy/FnE/RQGNTcjfEhxR1x25IRIZUpNb3MHR0QvOWa4sJcMnQlnZo2tIeq4x9TGvXtb5+hTbrqDls3heD0vaGjx1ncWB1HZAVYGvzYroDJpLZcu2S3dzrlBASliK7IS6ab35fv4LL2TnUdOx6yzbPT81kTj2a08xTSwl1qnEsx6CEbsjkLIuSIhsJWSaKtSy6NHZfXH7zWBtj3swxIj3H0NX3b7N4upzIObDl6oplGZOHxjfSJoNL3lrmlIQMC5i1ZUEIyQOVBSFEBZUFIUTFbJRFyWHNpAzYRsYxm6CslFO3XUFZqUdpNM7Jpmxt6xzkGDK1ZWjKUX/WBqeFlqcZXq4JdkopG0SAkQMS24OyODckKiW8oTQjP/YD2Lw2h4Kz6arHNuWRUp6+7ykJNW3BLsOr5rfquSGzURaphypzKwxNg+kKX8+tKGwZuoZ8c1gWLvmyD5dmtixm47MghMRlNsqihDdlSuTyHd7X+94Tm5WdO3OL4MW529+TNe/n/+EvR6ezcsUVl3y//s/Oqu9lN2SimNfPR70+BVtn9Q21BNa++WTWvK/9loxOZ+u11y75/vOf6BX2bJRFSuz+a+61INqmWLdNnW6ey2mRtU326ypHbHm6wr1Dr43iK1uIvMc4OGfTDUnNxtbFJetKsWqGrKbULEdOSqlPrQyl1FtKqCwIISqoLAghKqgsBtLs75cyEuOSo0+23H4Llxw55dHKUEq9paR4B6c2rDZ1uHduWtdqVB4vtQwxFYZ2jYoSlJZNCFlcafhsBTAby2LZnE3EH7aRccxGWRBC4jIbZVGSyUjKhG1kHLNRFoSQuPQqCxF5UEROi8gzjWO7RWRDRH5R/b+qOi4i8gUROSkiPxaRG8cKuIxeZ0JKRDMa8hCAfwXw5caxewCcMMbcJyL3VN//HsDtAPZWf7cAuL/6PytKWwsi5OreKdGGezfPx5ZnyOreKYi1543PXqe9loUx5jsAzliHDwF4uPr8MIAPNY5/2Sz4HoA3i8g1WmEIIeUy1GexxxjzYvX5JQB7qs9vBfB847oXqmOEkIkz2sFpFrsUeS/fIyJHReQpEXnqdZwbKwbH0EkvbCPjGKosXq67F9X/09XxUwCubVz3turYNowxDxhj9htj9l+OtYFiEEJSodq+UETeAeC/jDF/Wn3/ZwC/aTg4dxtj/k5EPgjgbgB3YOHY/IIx5ua+9H02RtbStzGyfU6bR5/Tq88x1yZDW1i77WwLvY2fZis8ewXzlZ07sXX2rNdmvblC8bscgym2Qxyark2s+vPZvrB3NEREHgFwK4CrReQFAJ8BcB+AYyLySQC/BrBeXf4EForiJICzAD7hLT0pnqmtcEXC0KssjDFHWk5tMwUq/8VdY4UihJRH8bNOY6Ex90OmX+fRdd4lj2sGZEjzVxPP0LZ6VNfS+TYhTGtXzIhmb4+22BK7e+UrT1dXd1vdrC6M743NY51p+rS7A6vr2Ng8ptqy4OCOIzh+/hF12i4Y7h2QqXjbpyInKQuVgzM2JTg4tRGDYxycbfe2ORxd0YShHZyhye3g7CPnRkFaJuvgnCttC6+M+VF8uhlaxRejG+IbxqxRcm33Dkm3Lw1fxdn1QhjTDfGRbQ7dEFoWAYdOXZQ4dOqL/VA1ZXNd62KOQ6exKNWyoM+CEKJiabshNrbHf8hoSN9b3+ftEHNWqK91UsJ+Hlr66j/3TNspQ2VR0WZq+9D3MPk8pDEb9ZCulLYbkhufbgjxY2l9FiHXBGimGSpOY4wcfXSFe6d8oMb6f0ITSonGwMc/5JOGj8+iWGXR9SO0DU/6Bj0NQdtAUr51u4YD25RBWxlyWQuuIWP7fIohY9dwdZe8tcwpCTF6U0MHJyEkOFQWA9nYKmMj3yYuOfpka5YjJynqU5OuVoZS6i0lVBaEEBWzURY5+o2u6MqctEWl9t1Tgvyl1KdWhlLqLSWzURapYTckLKXUJ7sh7VBZEEJUUFkQQlRQWRBCVMwm3DvlbMwcMz9dMmiuaYvMLME5pw0mSyVr15T7ja2vL6aZV0GMyR3qq+uArABbm+PSscp4pey+SXvvbCyL3A8vIXNnNsqCEBIXKgtCiIrZ+CxSUkKXRzNprnmNdiJZSrRrf+Sa2bnte8+SeDFp5h1yGYVXzJlwu6hPhdQNv5SIwyaM4OzJY3VdfU3ftQdW11XpzYnZWBYlvO1J2agsg3rJhr6lGwpY2iE1xaxn8Yo507pYbRexFrRxrVvhWglas76FjyLTLEajXYvCR7ZQC+1qFgBynfcZOvWWqVoFW5O+79DphTq+7PDi+BuPXnK8ycG1O3H83Fe7ZXXIdSFva+hU1tZw/PdfcaZRy1TLY5+r+cOVt+B3W7+RTqHq/EpRFm2L32gbVltja2PM4jcaYls6sUz1XIv2aCi1TlPUWYiFilxpfN+cwCvmjEpZzMZnQQiJy2yURQlOOlI2bCPjmI2DMyWlDTuGXIMzJW2LKg/pVoaSZ8ganCmI5ZsTkfkMnWqH9lKPhpSy/kITrmfRn4f2mqnUW0qKVxZaGGfBOAtNHtprplJvKZmNsiCExKXYoVMb3z52W3/Ypi2OQpOuK62+vnZXTEfb9fb5seavKz9NubRlcZFy+YC2fMfGa7jyilGuEMOkWnz2DVlaB6fmoQyZfp1H13mXPC6zOGQj1TgS2/rxXes/2ISME+hSnE4FVgVT2QrPVoK+8lxS9ir0uw7+2lY3VtBWGz7trg66cr7wRC6R57adH8W3z/6HOm0XS6ssNMFeodN3ne+6pr4utGXRhU/argc1pmWhUQzO+1rCvEM6VO08tsnaoySa96kD/6o0NfUyVlEAS6ws2pyBYyI7fSwHbYMIbVkMGRJsu75Ey8J5X8OysNPztSzarl0Gy4I+i4A+Cxcl+ix8oc8iLaX6LDgaQghRQWVBCFGxtD4LG9vZFSPgxtd5WErQT2mRql10yVhSnU4RWhYVTUfi0AYVyqnpe60vtrNUK3d97fs++E/FPnT1ClaulaxCr2y1bCtlFaks+pyAWurGXcfx19/HNPSukGo7NqIEXPI069GuGw1r33wyqIxBMebSP/ucEk1dbGweK+q3jk2RyoIQUh5L67MIGcGpHULMEcHp209nBOdA2ZYgzmK2lsXQEN4+XA0uB80uVejYkFT4dAtT1HOv78bho0gWP3LZYRxcu3N0Pdj3X7nyFvX2hZMLytK+KfuCsoZWeohoxhCkjOCMxdgAt9D4RHA2r09RZz4BcD5p+ARlFassfOYZuB6AWG9bl1LQRjfGos+KcnWv2rpdJVshJcqWK6IWCPNbLWUEZ+ruQJs/ISddIzVd95Qgf4r6rP0Gnddwk6FWZqMsCCFxobIYSB2fUH8uAZccfbI1y5GTFPWpmSZejx707V62sXks696nOZiNsiihwRMyZ3qVhYg8KCKnReSZxrHPisgpEflR9XdH49ynReSkiDwrIrfFEtyGPgv6LDR5aK+ZSr2lRGNZPATgA47jnzfG7Kv+ngAAEbkBwGEA767u+aKIrIYStovUlgW7IWFJ0g1RpKuVoZR6S0mvsjDGfAfAGWV6hwA8aow5Z4z5FYCTAG4eIR8hpBDG+CzuFpEfV92Uq6pjbwXwfOOaF6pj0Vk2k5CQ1AxVFvcDeBeAfQBeBPA53wRE5KiIPCUiT72OcwPFuEjywJjGOHsp4+0uOaYSL1BKfdaxGH0xGQcuO6yK25gTg5SFMeZlY8ymMWYLwJdwsatxCsC1jUvfVh1zpfGAMWa/MWb/5VgbIsYl0LIgfRxcuzO3CJNmkLIQkWsaXz8MoB4peRzAYRFZE5HrAOwF8INxIpZJc5y9lPF2lxxTiRdIUZ/Hz321X456ef2emIyNNx5VL+8/F3qnqIvIIwBuBXC1iLwA4DMAbhWRfQAMgOcAfAoAjDE/FZFjAH4G4A0AdxljNuOITghJSa+yMMYccRz+947r7wVw7xihhrBsw1iEpGY2EZz0WRASl9koC1oWhMSlGGWhWaPCPu9aZi1UGK7vCtih6MuLFhTJRTFrcPquiRlrJSxX+imtFk2YMSE5KMayIISUDZXFQDjrNCycdVo+xXRDpkQJjaRNBu3xUsuQUwHbeZdQRzWh/XA1u3CVenXv2VgW7MuTPthGxlG8sihpXwkybdhGxlG8siCElMFslAVNTNIH28g4it1kyMZ3z86+OAz7nDaPvkCxvs2O+naI18SbjG30l6Rn7dHZdX0t27nb34O1bz7ptUtWsm3+rLUwmuWq9zwNJVO912hoXHUYq/6WcpOh0VQbyULk4udYeYS+dgyysvjTyFLVzekbL08nny91eVzl6iunb1arSZaXLYbJKYtob6j6jWPMJW+fKHmEvnYMW5uLP40sVd1ce+9308nnS10eV7n6yumJef180PRKZ3LdkFI3RrYpYRPfIXBjZH+WZWPkyVkWhJA8FGtZ+O6ibh+PvYv6BUeaMYv+u1WPOXZRh8g2R2Xt1GvbRf2C76GSP9eIQdPRemB1fXs5Ajh2D/7B3+D477/SLUfltOxzXl5YrHdrk7uoT43kmwxxDc6gJFmDs0dRAFyDs4vZKIvUcCJZWEqpT04ka4fKghCigsqCEKJiNsoitUnIjZHDUkp9cmPkdmajLFJTSh+7CX0W/Xlor5lKvaVkNspi2bQ88UfVRpqh7X3XlRryHonZKItl0/LEn2XbyDg0s1EWqSmlj92EPouePBRxEdpYj1LiU1JCZUEIUTEbZZH67XhwxxEc3HHkwucScMnRJ1uzHDkppT5v2/nRS/53Xdd3zdwodm6ITezFb/oWrXGlq8FeXKftmra5GzEWv4lJ7sVv+tD8Hrnh4jeF0xwyG+os1Qy3hUprDL5bM9p1c9uujxfrUK5ldJUrtMyl1kEsuG9Ihe1ci9EQfN4OvpbUUDQylebI7aJLxtB1OoX6CAktC0KICioLQogKKouKpic+ljfeJ91UIwIH1+7EwbU7VbLUdbP10t4iRlBc1KMUrtGK0KMXt+36eND0SqeI0RAR+R8ArwH439yyJOZqsMzLQMll/hNjzB9pLixCWQCAiDylHcKZCyzzcjCXMrMbQghRQWVBCFFRkrJ4ILcAGWCZl4NZlLkYnwUhpGxKsiwIIQVDZUEIUUFlQQhRQWVBCFFBZUEIUfH/mAax2C+VgtgAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 73.09059238433838 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1000.0, 'kernel_type': 'size'} is: \n",
+      "[[1.07375041e+252 6.40000000e+022 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [6.40000000e+022             nan 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07375041e+252 ... 1.07375041e+252\n",
+      "  1.07375041e+252 1.07375041e+252]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.07375041e+252 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07375041e+252 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07375041e+252 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 73.92352509498596 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 10000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 6.4e+29 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [6.4e+29     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     inf     inf     inf]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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VdpEoZ+GsZuzJP1q+IuLCyaupPQtFiReds1AUJRCJjLMYHd5VtQPVHWfhDuHW8oWtRcsXhkfLFyqKorhIRM8iSN0QpydQOHsueN2Qrfeye/8XS99ITvk7iK6uh6Mr7Ldmu9lxw30APPHLT7fZEiVOlkQEZyXu7nxgnG5vxe7MSHF0pozsyequr6K4SY+zaCB/puMcSm0MOThjcUgRYFq4kqQsTXTOQlGUQKizUBQlEKkZhmTsTEqFEJmonCxQThtHkSFHV+q4ZFW7LVASTlPOQkQOAxeAApA3xoyIyArg/wFXAIeB9xljmp49kwFrzZoQWb6dmAanjcMzutPapYmpK4fabYKScFoxDPkDY8w1ruWXTwJPGWM2A0/Z/1cUJeVE8WV7G3CTffwd4F+Be5sVWjwXvnOSPXi8rC1OR19a0NGVNvr3pdNuJT6adRYGeEJEDPCwMeYRYI0x5oR9/SSwpkkdgJWNGoDpEDU57bBip5U4AtAcnSmjcIkOQ5T6NOssbjTGHBOR1cAeEfmt+6IxxtiOpAoRuQu4C2DDhg0McWWTpiiKEiVNOQtjzDG7PSUiPwKuB8ZEZK0x5oSIrAVO1Xj2EeARsMK98ame10gRIqdGRqn12ODUahxdaSNz4Gi7TVASTsPOQkT6gIwx5oJ9vAO4D/gJ8EHgC3b7T60w1ElAkw9Rk9PZyem0ueO1a6m2itLu0ZQxdePmdpugJJxmehZrgB+JiCPn+8aY3SLyK+CHIvIh4HXgfc2bqShKu2nYWRhjDgL/2eP8WeDmsPL8qqiH6VGAXX9jdrbUArRiZ8gtvXeSWbWylGXbHDqCbFy/mMEqpjKAO264r7T5q7Sv45JVZfES/fuOY/p74OQZileuAxaHG9LfZz1nB2N1//ZALHa7ufH2++l/0S772G/lEZm6vJ++1yeRSWvlavLqYfpfOo05eiLyeinbt93H7JoeclMF8n1ZuscWV8/y/Z2Mb+ks5cuYXWPZ2/eL10KXEWyEa/78QWbWCBsev0DuiPWZPX7sr0PJ2PTlB1n+Wzj/Vuv/UoDODZdp+UJFUVpLYvJZrHr9urKeRVU+i+UfAqwEvkHzWdy64W4ef+Mhbt1wN1Ae7r37/N81a3ZNnQCPv/FQJPKjYvTq/wnA7pf+d5stUeJkSeazaCQZbymRr1PhvBCuEnsjxJnct5VoImDFj9Q4C79yhp7POGUN7dZMhQjoapA4Sx22Ei2LqPiRGmdRbCBGwonNcNo4ehaNxIMkgeKZs+02QUk4iXEWfn9k2rOIFu1ZKH7oaoiiKIFITM/Cj2LI+IVbeu+kaMdZhH3WT269OItW6qpHq+MsCsfi33WqcRbBSUKcRWKWTle8sLVukaBbeu8ErD/GwKUA7FKHThkB9zAkql88R1dUpQaiIq1LvkpzhFk6TYSzqKxItj23k6y91duJvaiKu3DV5yjVB7H/UKH5P1ZHZqWuqPGr37Hjhvu0tofSMpZEnIVvSn13fY4o6oJ4yI8Dv/odWt9DaRc6wakoSiCS27PwKQjk7kVEUUTIS34c+BX70WJASrvQnoWiKIFIbM/Cr06Iuz5HqT6Ik6ezFfo95MeCX/0Ore+htInEOgu/OiHu+hzOcemZFuAlPw786ndofQ+lXegwRFGUQKizUBQlEIkdhvgVFXIX8ykVEWqgEFEY+XHgV+xHiwEp7SKxzkJy9U2T7u6qY79nQun3kB8Hzh6JRq8rSlQk1lkUfWIbiuPnq479ngml30N+LJw809x1RYmIxDoLJy9ErYzfcumaquNW5pLwkh8Hzu7QRq8rSlToBKeiKIFIVM9ie24nAHvyj7Kj6w7Pe5xt5+4ygc5xK1PaecmPA78yglpmUGkX2rNQFCUQiepZuJEOyzRTI9xbXKHdzrHzTEv0e8iPA+nva+q6okRFYp2F7jpt7LqiREVinYVuJGvwuqJEhM5ZKIoSiETm4Bwd3lUVX+HOwenO2J3p7qY4O1tqve73wklQ6xTXkY3rkQvTpazdhVdeI2NHbrp1BU3062TfLhs2uLJv9+87TuES6zhz4ChTN24GoPuxXwGQfeuVmENHyKxaSfHM2VJdj/yx4+QuuzSyxLo33n4/PcetrNbZc3Zxpv6eUtZtgGN/uJzL/vk8xc4sM2sXI0p7TsyQfe0oZmamSq55++ZSSkDnvcPmEt2+zcpPOrWhl65zeXKT8+T7O0vXD93Wwfoni2XPFLqE6VUZVr44w/xQJ32/eK10bfL3NzO5Nsvax6zM7I+//pVQ9jh84JkP8/J33wZAZgHyvcLg4Txv/JH1tzX4Qgdz9sZlc7VVb3do2TSbBs/yb/s3Mbi3i6t2vgLA2XvWlbJ3u/HK5L31vq/wyl1f4x1/+Welc+ffCst/Cwv9AkDe/vFMXZ7n9f/2F1UywuTgTGTPIq1VvRRlKZOInsXIyIgZ2nclFBerjVX2DG69/B4A8keOBi4FsP2dn2PPv/8V29/5OQByxxZ7K41+iwTRCbDn3/8qEvlRcePt9wPwi3+s/vZRli5LIrt3JWY6fOnB7NnJsrYRGY3qTBvO0ENRapHIYYiiKMkjPT2L2bnQz8iFqbK22ICMRnWmDWcyU1FqoT0LRVECkZqehXTaS2RTIb65nSAtJxx8zjvAq6XEGBreSjSpjuJHepxFnxX/wHjw1Hn54YGyNtfCcHA/nWlj6vLW5QJRliapcRbuCuhByZ2eKGsbkdGozrThBFwpSi10zkJRlECkpmfBpautNsQwZOKaS8raZa9GP5/g6Eobx/4wxs1ySipJj7M4fir0IwP7Tpa15nz0QwRHV9q47J9jTEqspJL0OIuMhH7E5LJlbSMyGtWZNoqd6bRbiY/UOAvpCb+0VxjqK2tzM9EHZTm60oZ796iieKETnIqiBEKdhaIogUjNMMQroYof2fGpsrYRGY3qTBs9J3TXqVKfxDiL7NBgzepj0FhCHKfeR6mdX2jMuAZ0po3sa1qPRKlPYpyFH6ZQ8L+p8hnbOZTaBmQ0qjNtxNHrUtKNzlkoihIIdRaKogRCnYWiKIHwdRYi8i0ROSUiL7rOrRCRPSLymt0O2edFRL4qIgdE5Dcicm1QQzSjt6IkmyA9i28DoxXnPgk8ZYzZDDxl/x/gVmCz/e8u4OutMdNaLckODYZ6JnPFulKbuWJdSUZYOWF1OnrThHn7ZszbN7fbDCXB+K6GGGOeFpErKk7fBtxkH38H+FfgXvv8d41VX+AZEVkuImuNMSeaNbSheqPjb5a1sdQsdXSmDKcAkKLUotE5izUuB3ASWGMfXwYccd131D6nKErKaTrOwhhjRCR0pSIRuQtrqMKGDRtYwdb69zu5LcPU/nCGG3YrcRRUinCIEyVOSUFFqUWjPYsxEVkLYLdOsoljwHrXfevsc1UYYx4xxowYY0aGh4cbNENRlLgIVL7QnrN4zBjzn+z/3w+cNcZ8QUQ+CawwxnxCRP4L8FHg3cANwFeNMdf7ya8sjLw9t5PcZWsBq1whVJczdJcJdMoUOiUOofnyhI7MSl1R41dG8Mbb79cSg0rLaGn5QhH5AdZk5ioROQp8BvgC8EMR+RDwOvA++/afYjmKA8A08Kehrbcpnqs/4ZY7PFZ17PdMGLzkx0H/i9UVtMNcV5SoCLIa8v4al272uNcAH2nWKEVRkkdiN5L5FhVyF/Nxigg5z7QCD/lx4FfsR4sBKe1Cw70VRQlEcnsWPhXI3JW/nOPSMy3AS34c+FUG08phSrtIrLPwqx7mrvwVRcUxL/lx4FcZTCuHKe0iuc5i3qeIsTt02z72fSYMHvLjQCbrJ6Hxu64oUaFzFoqiBCKxPYvMkFVOr1hjNSS/YXXVsfNMK/CSHweTV9ePZvW7rihRkVhnURyvX04v98apqmO/Z8LgJT8O+l/yCcryua4oUZFIZyHZLEWfeYLC2fGqY79nwuAlPw7M0fq7+f2uK0pUBNobEjUjIyNmaN+VUFzMvl25F2R0eBcAhbPnqq7VYnTrveze/0VGt95rnTi32PPYffrhJq2urRNg9/4vRiI/KrZvuw+APc98us2WKHESZm+ITnAqihKIRA5DvJB+u+BwnUJEleRXD5S1HTHU9HB0pY2pDa0LaFOWJqlxFsyFj6HIXpgtaxuR0ajOtNF1Lt9uE5SEkxpnYRbC9wpkZr6sbURGozrTRm4ynXYr8ZEaZyEdHaGfMT2dZW2mARmN6kwb+f502q3Eh05wKooSCHUWiqIEIjXDkIWNlwAgJ4OnuDv1e0Nl7crfdLXesBo608ah26IfoinpJjXOouPIGQDCzNkP750sa7Mngi+7NoqjK22sf7JoHfz39tqhJBcdhiiKEgh1FoqiBEKdhaIogUjNnAXZ8H6t2Jkta7MNyGhUZ9oodEm7TVASTmqchekOv5IxP9hR1ubORL8a4uhKG9OrtJOp1Cc1zoJzb4Z+pPfwm2VtIzIa1Zk2Vr6ouT2V+iTCWbz6/EEmzHNsz7y36pqTx0J6whfXKfZ1lbXZiehDmh1daWN+SMO9lfokwllsue4tJadQiZOkZkfXHaHlyssHy9pCDFvUHV1po+8Xr7XbBCXh6EBVUZRAqLNQFCUQiRiGBCF7iZWOP3/kaOBnim/fVNbmjkUf7u3oShuTv7+53SYoCScxzqI4UX9PhekNX8l8bmVXWZsdj74auqMrbUyuTWd8iBIfiXEWfpgjx0M/0/vLg2WtmY5+edDRlTbWPnbEOvjb9tqhJBeds1AUJRCJqBsyICvMDXJzqR7I9txOskODgFUnBDzqiLjqc5Tqg7iWX5utC+LIrNQVNX71O7Zvu09reygtI0zdkMQOQ/yCsIrL+6qOGwncCiM/DmbX1H8Hv+uKEhWJdRbk66e5kbmF6mOfZ8LgKT8GclOFpq4rSlQk11nk6ptmujqqj32eCYOn/BjI99VflfC7rihRkVhnYWbqr1xkzk9VHfs9EwYv+XHQPVb/HfyuK0pU6GqIoiiBUGehKEogEjsM8atA5q785Rw3UrUsjPw48KsMppXDlHaRWGdhBpdZBzXqhMysW1Z1XHqmBXjJj4PxLfWdgd91RYmKRDmL7bmdAOzJP1ozv8Xo8C52n36Y3tfOls6Vjs+0bqOYp/wY8Ks7kta6JEr60TkLRVECkaiehRuN4GzsuqJEhfYsFEUJRKJ6FnvyjwLWvESt/BbOBjF3rstSjs2x0y2zxUt+HPjlwtRcmUq7SMSu05GRETO070ooLu57qNxleuPt9wPQ8+Nnq67VYuNDD3Do7o+z8aEHALjs6WLp2i/+8S+aNbumToBDd388EvlR8YFnPgzA97d9s82WKHGyJHadVtL/irXSEWYb1fonC3C33QK9vxuPwDIPnQB3R66qpbz83bdZB9vaa4eSXHTOQlGUQKSmZ0Gx6H9PBVIwZW0jMhrVmTYy8e3CV1JKepxFLvzW7GJnpqxtREajOtNGvlcLIyv18f3NFpFvicgpEXnRde6zInJMRPbZ/97tuvYpETkgIvtF5JZWGSoXppEL06GecbZzd4/N0D02U5IRVk5YnWncRj54OM/g4dYlD1KWHkF6Ft8G/gb4bsX5rxhjvuw+ISJXATuBq4FLgSdFZIsxpun0TvNXDAOQOXos8DNj25aVtcN7o+9ZOLrSxht/lM7hkxIfvj0LY8zTQNBNF7cBjxpj5owxh4ADwPVN2KcoSkJoZs7ioyLyJ8BzwMeNMePAZcAzrnuO2ueapuOsla0qTBdl8FC+rHVkRImjK20MvhBf6kAlnTQ6G/d1YBNwDXACeCCsABG5S0SeE5HnTp/2j7wsdndS7A63PXtuIFNq5wYyJRlh5YTV6ehNE3MrrH+KUouGfquNMWPGmIIxpgh8k8WhxjFgvevWdfY5LxmPGGNGjDEjw8PDjZihKEqMNDQMEZG1xpgT9n//GHBWSn4CfF9EHsSa4NwMPNu0lcDCCqtOaRiDL2zIlLV9J6OvderoShvm6gvtNkFJOL5/eyLyA+AmYJWIHAU+A9wkItcABjgM7AIwxrwkIj8EXgbywEdasRKiKEr78XUWxpj3e5z+uzr3fx74fDNGeVGwg53C9CwKPaa8jSFgytGVNoaWRRd7oiwNUhPBWewKH2G40G/K2kZkNKozbWwajC8xt+otAAAEFElEQVR1oJJOUuMsusbDb17oP5Ipa7vG51pqUz2daePf9m+yDnTXqVKDRDiLV58/yIR5ju2Z91ZdcxL3dqxeCYSLs1h+IF/WdpyKPtmtoyttDO7tsg4+2F47lOSSCGex5bq31Mzm7WTGKiW/eSW43GM3ZcraS7NDTVgZTmfauGpniA9WuShJ52+2oiixk4ieRRD6f34ACDcM2fKNU3CP3QKcO996w7x0AtwTuaqWcvaeddbBM/XvUy5eUuMszFQDS3tnxsvaVlZZ99WZMnJHWpfsWFma6DBEUZRAJMZZ1Er9ryhKMkiMs1AUJdmos1AUJRCJKDI0ICvMDXJzqXjQ9txOsps3AlDYb62CVBYWetd7vgTA0499gne950s8/dgnGH3bp0rXd7/yf5qyyZFZqStqrvnzBwHY97WP1bxe65qihGVJFBkq9nbVvT47lK069nsmDF7y42BmTf39K37XFSUqEuksskOD8IaVLqNWXMWKZ09VHWfeOFHj7vB4yY+DDY/beSU+U+d6jWuKEiWJdBYQIK7CHc/gxFE0EosRQn4c+MU7aDyE0i50glNRlEAkYoIzSBX1Hdd9FgDz65cCV1G//s4HePZ7H+f6O618wstfXkwd98Tzn23O6Do6AZ79XrqqqG+97ysA7P90yuLUlaZYEhOclZx+xwAAq34d4qE7zpS1p38cQ2JgR2fKeOWur9lH6iwUb1LjLNb8yxgQbiNZ70PLYdRuge5DYxFY5qETYDRyVS3lHX/5ZwA8/3/bbIiSWHTOQlGUQKizUBQlEKkZhhSG+kI/M7G+o6ztOB9eRqM608b5t7bbAiXppMZZZMfD1zodOLJQ1joyosTRlTaW/7bdFihJJzXOgo7wpuZ7MmVtIzIa1Zk2Fvo1jFypTzp/sxVFiZ3U9CxMLrxfK3RKWduIjEZ1po18T7stUJKO9iwURQlEanoWhWVWBfQw39vTq7Nlbd/x6KuoO7rSxtTl6SyOpMRHIvaGeCW/YeQq6+KzLwDVe0Wu/bCVJGbvNz/GtR9+kL3f/Bjbt91Xur7nmU83ZZMjs1JX1Gz6sqXrd//DW9emLz9Y85qihGVJ7A3xWyp1L1FGsTTqJT8O/JYwdYlTaReJdRZ+QVju4CfnuJHArTDy48AvOEqDp5R2oROciqIEIrE9Cylacym1ZlQyhepj55lW4CU/DsRHl991RYmKxDqLYpdlWq3Vj4U+qTp2nmkFXvLjYGGwvjfwu64oUZGI1RAROQ1MAenMHNM4q9B3vhhI8jtfbowJlBUqEc4CQESeC7qEs1TQd744WCrvrBOciqIEQp2FoiiBSJKzeKTdBrQBfeeLgyXxzomZs1AUJdkkqWehKEqCUWehKEog1FkoihIIdRaKogRCnYWiKIH4/2MO/D9kRvutAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98abac50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 73.89270353317261 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 100000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 6.4e+36 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [6.4e+36     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     inf     inf     inf]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ad76d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 74.37439894676208 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 6.4e+43 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [6.4e+43     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     inf     inf     inf]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 75.28355646133423 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 10000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 6.4e+50 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [6.4e+50     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 74.68241906166077 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 100000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 6.4e+57 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [6.4e+57     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 74.76623010635376 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 6.4e+64 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [6.4e+64     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 74.58583784103394 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 10000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 6.4e+71 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [6.4e+71     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.40253257751465 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-10, 'kernel_type': 'branching'} is: \n",
+      "[[5.12000003e+02 6.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [6.40000000e+01 2.20000001e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000003e+02 ... 5.12000003e+02\n",
+      "  5.12000003e+02 5.12000003e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000003e+02 ... 4.48896042e+05\n",
+      "  4.32544044e+05 4.79584054e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000003e+02 ... 4.32544044e+05\n",
+      "  4.18176050e+05 4.62256065e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000003e+02 ... 4.79584054e+05\n",
+      "  4.62256065e+05 5.21632127e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.86074638366699 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-09, 'kernel_type': 'branching'} is: \n",
+      "[[5.12000027e+02 6.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [6.40000000e+01 2.20000006e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000027e+02 ... 5.12000027e+02\n",
+      "  5.12000027e+02 5.12000027e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000027e+02 ... 4.48896420e+05\n",
+      "  4.32544437e+05 4.79584541e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000027e+02 ... 4.32544437e+05\n",
+      "  4.18176498e+05 4.62256653e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000027e+02 ... 4.79584541e+05\n",
+      "  4.62256653e+05 5.21633269e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.4874358177185 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-08, 'kernel_type': 'branching'} is: \n",
+      "[[5.12000271e+02 6.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [6.40000000e+01 2.20000062e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000271e+02 ... 5.12000271e+02\n",
+      "  5.12000271e+02 5.12000271e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000271e+02 ... 4.48900197e+05\n",
+      "  4.32548366e+05 4.79589413e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000271e+02 ... 4.32548366e+05\n",
+      "  4.18180979e+05 4.62262531e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12000271e+02 ... 4.79589413e+05\n",
+      "  4.62262531e+05 5.21644686e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.9153413772583 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-07, 'kernel_type': 'branching'} is: \n",
+      "[[5.12002714e+02 6.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [6.40000000e+01 2.20000617e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12002714e+02 ... 5.12002714e+02\n",
+      "  5.12002714e+02 5.12002714e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 5.12002714e+02 ... 4.48937978e+05\n",
+      "  4.32587669e+05 4.79638129e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12002714e+02 ... 4.32587669e+05\n",
+      "  4.18225791e+05 4.62321311e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12002714e+02 ... 4.79638129e+05\n",
+      "  4.62321311e+05 5.21758875e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.85707259178162 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-06, 'kernel_type': 'branching'} is: \n",
+      "[[5.12027137e+02 6.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [6.40000000e+01 2.20006168e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12027137e+02 ... 5.12027137e+02\n",
+      "  5.12027137e+02 5.12027137e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 5.12027137e+02 ... 4.49316183e+05\n",
+      "  4.32981091e+05 4.80125472e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12027137e+02 ... 4.32981091e+05\n",
+      "  4.18674428e+05 4.62909460e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12027137e+02 ... 4.80125472e+05\n",
+      "  4.62909460e+05 5.22902089e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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HYokKDIfALIGbRLOgoFmkJuBIzte3fhgLrwh8dACyAKm6lsjHaBQaXUr0gzkda8J6hvb46EBOPT0DI0SBdOMPfUuko43XnYYD+PuHoMk0PQ91LZuUzl+vX9OI5hd+Fy4aMN1HQ/ayl73csBBfRWW/YblHj/iH6K/3fvdSafX0byD5Bbals7us/fL3GzQh9S2UciPj2FWugJqkqtpMq1fKTWSpbjzXOFdNZnAvrd5l/KE3Oa4+6RkXHOX+nL5EM5Mlu20/pfwefw2n/GyrCdxdM8SKLoIxIXZqo6CT12M0aHKAkKPtEaQmpTjvt/BSqwSgUVS1nZNjrdLUp3RnUVE3pDJfl7C3GHc2VrsJaMiv2BjgCC7c+HGt+qIh+jBckGdTfrZgLttOCdCiyqVxMQdyGBfNPQAJYDZoYjiT2+Xm9buAsNcdHYFnszgmqkLlsHJtrIkWHMZqWrgAyuJlKyZMVcFHEJuTYkJrpQAauMNx/I0Mh9P1sT4jBaS9yYS9vQ/nhocg7sTbPCRlarPSm8Vr0aW3jjoQeYc3yKbdntw6shPI33TocRKatx/v4JTaWYq243qQA/wqjo3bcCNHv0TCMviuOFYiIomvFMVjE7WIndnINqp0zdShGBzX8cTwUEcMQp/2uKu07ZqjNnNg2zXV64xOnL4reYA1yqLRGjbRro2QcvYSfTLRo9h3ea/663scXvvN4qXJdcloLmsvHt+gTuqm5ArClE3EL7v2u61cNO5yQ2Xu3UC578bM1OiLuDnLqA+v/60DKNaCVz6NyT6oxgxhFFDzEsuwLd+I+ewXi+yzAsnWAHJWbOpAT1SKnIl26e/76ob0vXh0DSwg0ILM9uzee9nLXm5TPr2axUXUbAAUibiT6dHX/tpx43izfVkaN1gzxCBKbRubcOk34bO4BHFZluWL3V2Es7DtWpTsDj6LPj9QiVKMhLSxD5OYtuYvqgLVnPpWus3rd5HPYjiMcO+MGDf6TXqo+AL4C4CEoNXPY6uoZ1pPn8+iTkl9VnpJi10y0d5Un8VOctnDsQntWfov9M8+f0kfW3YfJ+XGsRgV3PZVZJBe6JYob+psfPbBNr4Cm7Vazie2y5mPZq0/HRvSfLPN9KKx95UcdBXWNkEgOpuzedixmzW2/VPAbUjz1pmR/CVZTg0FJ6Bt16Bt42988dCasVKVIz2jacMe4PVNU0F/yZQLPhXrZO0TzTRGyizmrgN1XS//Zx8E3I2GydlbTGcbebM2i8vkshT1ix4q24bF47OmE+d9UF2vh3BNCjmv2hzCrXBsvVl0A+rbnIjWCWUB8cRbUJaFi1tQl5UiVyXC3lHc5BbuPRpGKHl247HfGC2K6wET1TBv9fjGD6nwUUsx8O8sRb3H6ecODmK6eToYAFarlbxdzcNIdZMiDTouE5WKrpEw3Iwc10D1q0fH4POJ6VNS4mOKukFUxmiMIzm2WoGXLehgDADwL056HZpuNJTzTQUyNx7BPbgPmBR1NI1E0FyxWSi83KTJC6p1e0/Em79ZbGSrTg+7fMwToza+2cNGER/0Pmiutk8Mu3VbhGXG+0DmeLiZ4wZkUKNxvBRCg97W6JQxZeFF7YN4Pay8lhuSEJPpAe7fhGjQgPScYnO6cL1VrbZvb5MvoscYiJEEPScibc05FmEKABg0oDJrVkPQmu+xMppIU8tDpGp8VcW8EzQNCOFtrzko5YZHEj6m8Ri8MJsQyUOJYFqQnZ+iJ6sq5saQZ9BYNgucnKEvgYzqWlCfuhaQjYePDoDTs3TecBDWT+He4X+l4/OcxsV+j+Dcy172cvPy2iM4X1t5HeqGqJRO2ovkopyai+ZyB+qGlCxbWZt9KE01J/t8FpsoA3qdlaZfgynZqoo6b183ZI2jwrNUUbeEwZfWDUkMbQDwu6t/jFP/JiM4t5Eijp0dA9bp5AINXkar1yeanq6p7Ks2plFn3ddNDiUGshRyP19k/gsX1NCYoq5p7/pg2vG6kOpuM1jDmGiQ4OK8bCOaUO19H5KM4o1nnGWAhxuPe+tuWvPEHY7hJwJuKs2QTQzh1AzWfBYWPam+BTUZ4rlhHbhdgeoq9hlrqpob3x0f5b4DIJohvFyCiLIHy4W07y78xg2akCzWhSiDAfkFP1Gk7avraEZU774D/+IkzTWkxNPxsRywKeo9Zghmc9D9ewCA7sOPeze86t6RzMP4ZNxwCLz7FpxJUafhQNLQ+8yQ0RB8dhbNEHgGPdt+C9hrFjchr0qz2KQBqNjNctt+X7ZmsQ3Y7KIx37Rm0febTceU39RshLepWcT2Tf87aRa0Xut0F81i77N4k+S6CU2vq7zMeW3L4lWm/H8K5M6ZIa9lkaG+PjaNcVs48WWyjWYSuSsuf2tfWmTIHr/J8oXbPmxbYGQ2r/kFYfC1cokXAA+yeQczqa/I0G2UL7ShbcOr6efl+Lv8f/vzAA/IvtrDvfeyl73ctNw5zWKtnkefI/Oi3wbJtAwgcUSq7bhYJKBW0RfVdXJwtktxZgZbM3FZjlKij/bZ1AkQM5slp+OyRRVSlLsziZkrhDimMlvOzxAz176SM7ARFiud72wGzarUtPHooIsp0jkYrLp3Lzr22LBCWScuHR+Lo8wZ5q8wNj/vKeXHHm44jONNtTOqmG0ZGZ20HwVljYbg+ULmEFimaDBI2mGoxwEA7uEDsGIOitR6Dg5ldSADkLTwZhCdk1S56ODM6AEAmet4BJ6E34faG/78HNVf+RLw8VNzbgUsFtFpaa81FKhVi4OTFkvwZAa881COf/M7vQ5md+8IqOuMSbx+7zG6L7wL9433k4Y4GoHn86SxWe7P1UrWwdwj9Ek/f0qf3LnNAkC/GrqjOrzGPakgoy1yp8tsxT6nWm9GoKFtZ88ZLyMvl7DOZjYp1ig5P0OUZQ0i3nWAeVgT9JgNt4Q510QdVPxisRZl4VXgudQ1m05lfIb70Y65LzeEO58+68OgRYmAhM72xZjmCzPW0JeulecMycnn5/CLBZQMOEkL7rrsZcGeZaPq7Dqa1PYi7VucmdPURpccpvT8NEeOhuiLCxs/tyuwcmHqBhSzizvwfAH3LBAAm/yNlGvjZZOqqpjSDgB+MkX18Yu873bVy8GJxSJxcFrz6DLzx8jd3CxuQqx3XFPEgf706rXf5sjMPkO0L3WYPWebkb1JuStTkgvI9RrPRI/fZc0eTeNc29C4v10Ltbb9Z+M2N2zen85hPeGrrx4Gtz1r1OVjsp97a2p4k/cxX8hmAy58LBwfwLwvH1GasX2Lnsw2C843aPuymM6yui/kfXgxtLFdIpINrkCswgtEnpXDswfbwZ6B1Spt7rrhL5cSKlYCYyBswH69xIFGisr7ZodarXd/s+gLv+2iZVAeytqYQ3ELkmWWOpIb39yEERhUJoe9ZCnDfUSU2K/1O1u7w5LTmDYybe4KdSx6GcZ03QB5i4YHhezDCLOG8TqHdawqANckv8nqfwStZlNURXNEdPNwTjQhe74ygEVkfv+9KL+T/iJpsSEljufckOwdnHvZy162krupWewCgtrYRpFtqSnJPW/FNSmLDKktaZvXpJ8ic5OaWsZvUH3woYCO9+CpJjWJw3XdwcmgigBqcltb279mkaGsGJDhtowJVoAkPc1mAFwqsmtV7z4wUyiNACTncpbFuUWRoeis07IE3kfEJwAp6nM+SW9r7V7nR5RxP9BoKElxGvqkJqJDMyr+sAZuOExFlANy1YcCQc5qTU0N0AIuFBnihZQCIDalAOpQHGnVgacz0MP70u5isZ6JS04yWAMvZ3RoHx6EIkMfpzVvBjIfvZ/1HqtrSWcvigxhtYErtkeutVkQ0TcBnEGerBUzf4WIHgH4BwC+COCbAH6SmZ9fp58tB5NvIJdESbLKYApntnUw2qXcZZZoRmtt2MpiXZe880C6ccNNbm19auqYisyrVYpQdF26iSzcu+tCqnSK0iA8NDQYRGemzULU9gGA2pXMy3jAeZIg19ylyETcLA4PU3EcrcZdVcnLDoDuH6cNZZg861gsQOWmGcwPNxymSIxuaIMmOUh1IxiPpI6HPhAHY9lEuy6uF8YjyRTtOnkwVd56ALLkvQhqeF0Dk6lEE5YnOjDQwRg0HkndDUAyTYcDmUNdAzaTtHKgoyOQXl994OYLLD/3EAO7sdQV4Cr4tyXC4c4m4DDO7ljqg3DjwLVDNVnCvaiw/KxUJGuePU8+DpNBTPeOJat2tUpO7If3Mfne+zg6SRXc+XAMOp/KGIDo4OSDEdCuZCzHh+FkBs633yxuwgz5a8z8ZWb+Svj8cwC+xsxfAvC18PlOyiZb8eoNFlBfK2VfbvOluUk79EIpORGI1vsu64WauZXrl/3+umt70e9Dnkm06S8a701JX1+7/tb4M/KvL2n3Jd0P18oNCZrFV5j5iTn2pwB+hJk/IKLPAPinzPyXL2rnWrkhV3VwlrVOA5lMSU6TRR2stmJJcmyuhA4rJKZlx0LmH4DENQHRTtxoCHif6NmKRLEo1nQotBlLrqNziPkLJbJU51Im1A2HOXW9DDyjgaPBQEJwzHl/XScJX5bJySasca5FAFirHl/md8TPIQdDjpmxGJyFYjI0SStK1yWqfBOSpsEANGjgbfJZQeZjj1tsi8XZ1J95D/7kNK4raeLaOGmR6tCMiX51HaM0vFjC3ZOkM//0WYpmGO4RLW/Ai0UiITo6gnvrIfjZC7MeTkwtXRcN2SryuW2T6Qjgdye/hZPVk5eSdcoAfoeEqeR/ZeZfBPCYmT8I338I4PE1+1iXPtNix901K18IhGK9qW4H9yGHg0miBYgAiZPLRrO+WWgM37JARdNjNs9K9dGgkZunAE0pyU1GUkN5OUCbzWkBN5iFeL1hmbLnWp5IHb8FT8VziSKoBxDTgM+92OBqGrAHlthYsyUj1VGAknN5zQ+EjagAZWG+kDmE9aJBEzEeVFXpQdEsT40mRGlSBu7E1PcYNGL+aQbtFqAsFKAsXrXgR/cTfgII/hmA7oXCyNM5qK7EhFEztBbyHGpXwGQK/1AAXDg9A3iZIk5hbejwQDYY4wdzhwdYvfcA1WSWikMPB+JPckom5OJ4qQeUhdlL8lkA+GFm/i4RvQvgnxDRn9gvmZmJ+uvGE9FXAXwVAEY4uOYw9rKXvdy23FiKOhH9XQDnAP5L3AUzpNRESpyFiURksomApezTmjk9dnxJYkJNnaEXLTN0nxnSC8oq4/WbODz71kHfzha+bdm7zds6YgRMBTX9zF2XNKYSCeqN6QCs8X3EfkrkZIDcx7HZORoNQiMYaxXJbIFhlaA90GAQq4llVIcy8GwcGlnKxuA7VA8fZjByrTIW18FUC4uRoKARKT8oBRi4P58kDlBr8oTIhq3i5kYjgd5Pp9l1tSCw5CNyCZRlzMDfW/xDnPint2uGENEhAMfMZ+HvvwHgvwXwWwB+CsDPh/9/86p9bJSMTyFEK0oK+8uiIRoFCMxBNBxKqDIc787OInlr5tcIYUgbOnPjMbyWrwt9VUeHEvIzaDoaDETtdQQ+O4/2q5/NUT16CDBj9bG4f9x4JNDlStRyS15Dg4GMJUZDggkxGmbREH9yBmpq+PkC7lC0Nx/UaJ2LCyqp3uzu4UNA81zUbKiqFIEAQA/vg09O5abW/kJYzp9P4g3KYYMhdHBHhzFsScNhJKyNZDUmGsI2GnJ0CD6fwC8WscQfjcfgthVTRM03AHj3EdzTF7nPIpTx0/wMr7kjRJJLcnQAfPfDOE8aBnOrrnNezRANUd+ERkO6Zy+w/PL3YPj1j+O5PGxAZxPw40cyhLMZuKlB3sPfl+vQDSWE7hYrVM/OMf/iWwCA4R99Ezyby5rrHMJYMWjgP3karzt94bM4+8F3cO8PP4r3HY+HcGchGsIs5g4AHg3hlq2My0ZDvp1C7ZfJdcyQxwB+I9wYNYC/x8z/iIh+H8CvE9FPA/gWgJ+8Rh/90pfneyF3/mXNcbT5Mk0rOvo4nrdTuxw2GkUYapjQB4yAtudD/ka5qXnuQ04nfMFtSTHveMxC5GNOR9AeOH0f52HnruO2x6srevE5wLnZ5+MKfVMGC6f4wmDFZsTxMqjzu2Rp9wplml9oszi2Ds0HQAC6MI5Y/lGBB4COAAAgAElEQVS0KDZO2QsjY3ov2Rwp05+2exP2w2vPlLWRH6KHoUm95RfyMvT9PjueeBWpcjE6EWXbxJuSdQnoV6/t9wjUbkCMNMR6l0XUYJcEoJ2kzzyzwDXkZkWZNCbAsOBt17EX2bfS7A5FpvvGdgFXZlmiIEaF2MMdHMSxWdMJwJXX1LJ+Z+ZKGSIvKBatqau0inaukSejKGFgz7GlG6SLC+77nvntUkV9D/fey172spXcXbh3/Dv4LHYNnRb8iOpgjA67TmLUmWNOa3mUcO8e9i43HK5nklaDjOg18S6mgjSKcpTfd6aORZ3OHTTgrmCUhr7Vrwf3dgcHuWkBcWiiSWhLF/wKZHED+obuuqQ269/k4Eam5kZYAzIp+9vAvfXtW9bv0HG6wwPwdCZ+CmumaSZmIW40BDVN5LPgrooYDqK80hichI+jvyDcJ36xgPuevwQ8MSDlugbP59HHIkhY8alFpG4TIOudFwfle+/I8fc/DutmcBbOCTS9ruHPJ3Hu1aMH4M++A/rgaVov9bVEx3TwlzUNuG3X4N70Yvst4G5uFn3CvBMyr/Rqr6n5wGa/gO/ybPIeddqaLzGiYPkbijH4haRXZzByzTlxTrAHoS3ufK9ayqtVkcbNyc1Qnr+B+m2NIo4cmDvAMoSfnafcCesDCJtt3HB9P/gq4jiMZz99l5uQZUp22RaqlJ7t21bSzpsaVHP8PWuuhGe4w4Bz8F4e/HYVNwVul7EIEYf1S+tAYb66biaK9NGTxCkRMl65XcG3qUiRDJBB1qHbdUDTCPfFR+keSeseNmskx7Q1JfzJGVzns3Vk75NT3bCfE5Hck+yBiTHR/Pam4N3fLOxTu4sD0voRKFUiy6RtM16KyHWxDYIzIBbZc27PR9DXKkNzUjUAKmRvX17Jw5iR4ngGVYWdfJMIzrrOiXfCWlkQmCI47RucmMEID65ulNahqZElIIXz6ibf3ACU4WqL4LRVy+K6mPRsGo8F1KahXUC+D5EuVJQ2Go182fwLZUAzDN3Z2Oo6bRKWKe3wIHOq6vhilTGL4LSlAIC0JhqtWrxIDsvonOzEl1UiOMcj0IN7wNPnBl3bCHGPIjcNY5bT0oYGwUmT7T0Rd3+zuKoURDMRyWnL5m38LQOW9aXHcZRhCAysO3s47K5e1NBUFZ7jGyPHWvQ6B30HzuaVxrl2fnzb5WNfc+iGRLgMiWo2k756q2UER0l/ynP7sCJsaQyLz/ZBt23H9s4n6UEvMRXhXDcyb9VYFyT83jJMoRgbBXO0p2yAPznN6sZw0BpsDRPW9VIN0eAgeLUCnxjTDQgbRiL48d0KQJtrFrM56MmzvG9L9MM+oUBh7klzjdnnG+JF8tpvFr0PRZldGs9t17/fJD0p6nmRoRbggoMzVtDeQrMItVMzD7h5E6/lUBg+TgBi01oKvjhJYaK6Nc0i+G7s2sSHz/JiLpeAdxnwiJWizrB8kaNw8zYF4QxAoY5Ftm4X5YZEzcJlZo8SFbnxSEwL53IflkYcaqNZaG6I8TddVbNw944TfkPn17YpN0Szd4Hk43EhRZ09sFiCDoN/Y25yQ+KF9L2aBY2GcI8ewD97kfJjGgGElbR6kr3sr6VZ7KMhe9nLXraS1x5nsZNchVZvUxtAfCv3YTquPa5LcB7yJ62p7tcax1XkonFuAMKtVeLaBJjbdQ5b1xgp3oHmGvZVCcvAZleRNfTwhrWxsPtCg1kzewMrezy3DwOiGa59c+mTnvntgrN47c2QXukrBbCr9KSoyx/qgAwp6ms3QbedGWJL2umxikJ2awAkGVNImbLUDJHwqAdVOkZrsjTBz/ISUtQpqbFRgqPM5jpE1KHJPSAIMIk7ZCn3cQ0ss3ZcowvMkBD+FVPJpxR54+Dk4OCMm4KiTUO6dsqklbAvDQYpRd2aHxvNkL4U9cd5rdNdUtQBIQ3SFHUlv7GbhyMQ9Tg4j47g3n4Efvo8O5fVwenNJqSRtU+dg9NuDpv+viw3xNDUhQOF05P7w416I+rNuPTBTszfTlS5/IEGxG5XHMRqZWL1bWozsFFxV4WaJHVW2FhhzmXClzRfZzgLzELyUYu0WWSYEROqXYZkLY10IPpGxX4OIT4AcMMBfCg0bKHI5L1Q2WcbQEpz16ugHno3HiWaukpt+kFWFkGp7Jh9OkfXpIBD08E4hWUtRkTzTaoqJo0BYvNDfSqhXWU9i7Z/PJnkfMuqRQTPXtipLDt35WQtA84Cs1lKW++rG8JemKwA4ImX0gE2PNwB7uF9wYQwx1IK7vAA3aMjuBen+ZxoIWOQCy3/DQdyDabThPXwHpi/vBT111csVr7v6+KNFh1z/Rn1+bme80hGn1dfMQ8lZqBI/tIxclGcJ8K8i/+zY6Wab0FO4XuK0Yw8HBqdr+U6LJfrpDsdMlh0pL53lNU+yZ3BuaxhQCAPdAYsIyeagYlw+MUijdluBD30/nx2vr6OjkDK4Ukuvx7LpWhIFtugOBObrQrIXGd5/ZXY0rMXqfgQIBpMu5JCTEDucDRV46GRkGWbcpNMmYVsHrM5eNlmY/Jn56g+qlMSo/6+bbMkNAASUm5q2TSzjWj7aMjewbmXvexlK3lzNYvLZC0LUN+KW+y0pbnSVximj2/C4jmYe7WFtT76NCTts3gDlUWM9FjZr5hmvnfsFmqdzyeNSc/hDthYlGft9waJqX6DcuzOR1J1W9xI/7a/S3iC1L839rwKsZg/0kaxNqodmXERApiunE+HHGCHlCjGs3ke4g8h4UQhYEKhpamsUPSZmp89942ONWq/CdjH5+d53+qjKZ28VZe0JYuteJNwFteWm3CG9rarF8OnnBHt4zUSxXuk7FD7ZZnFuf2Nc9OyVsjIvfyxWBRvFmUozJ3iRy9hZIVckXCYKgd2uZ9pF3lzN4vLNoYyCrAGyroAM09ujRMz9qmnKJS5SEtWB6QPhXqljXaNhCblhVQp4qLjdVUvoW9WlwRItUl8Di2P7Ruvu+ZkuPGwtzCv5dB0h2P4EEAgQ8XP7WojPQAZaHcEVzV1sp81h0F5JtWNMGiAZSu+Zfu7rstyHwDAHR9JItla33UgEqoy+96F5KzO5GtoTRLrQNZIirYT5xDqkLhHD4UMCMhQmRTqhlBwrgJI/JfOpYTC2TwVUV6261omxBmMpgZPpsn5e3AAvPsWyPgdaDiQZLGSRb0RcmLnuSjf8KY7OPu0hW20BvN9Cq2l7EaEOhsAcuiv7Ss8OBkL+KBZQ49GolkbDDF1PahdZbU8IuOUbhbqlQ/hW0usq5tOhA5rxMHUJdE56MNna5QASN75ON/AYnUwTvUylIS2qlI9DwB0/54QzTqXch0AYLEMdUnWtQJdj/g3IF754ATUcJ7WJyEX5nRwALBkWtrfUbsMoWXzlnzrIdbeuSRjdKcQVi3jAKWDsbQV5uWGQ3mQViup0WELDjc1aDwGnYTrOxyIubE8Qfv5t9DodQ/5KpjNgFA3hE4nMWvY3wt1Q2oH31SozhZwJ+doPy9MWdWLk2yMcaz3jsGjgay7XveH9zH5voc4PDV1Q44P4c4mEpoFYlSED0aRb4ePAqcHM3D6pm8We+kXylX5OyE9KrENs74SCXVHuKzjihT2tee+FLmJeivXNJHv0F21l73s5VXKmwX37pNNDs7SxFDIrkVmbmrPpLQrojICuAyseM2zbRCWihCVv1eJElDbUV9FHzt3H8wXyBLVAESv+JpvQk4GMvMmgL1MrdOyTqslBlZinZINe5OvpySsAZA4HXQ8QJYkFj8HWj5bf6UPZ2FBXukgZYhZC7Sj4VCAVeqHqJtEfmPBacEPoT4GHYOiUN394yzDVHEWkTvD4CwiaC7gLKA4i2A++hcnG3wW48junaWdP3wA/+RpOlHT0AuchZIuW6JoAPjnp7+Jk9UnbzDcexu5zIcRodbhBr4oalD8Ln9IQj3SFa2dJ2G9POvUkttYx2g83hqSGx/a4S4fL7ms0HB8kNRBF8QiNLN+zXxtcWYgjwLEiAS5zJFJg0ZsZ9OujH21ed3jeiBtDKZqG1Xi8ENVCTLT+FbAnIUqqarA6IT016rlWgu07LquIzQ8bpahHarrxFoeigyR9+Io1PMChD3WnQ1tUlUJ8/p4HNvI6PeDn4g8X+zg9Jy4L07O0AcMpJB1Ki+AtPHw4Rg4MfDtMO5eB+eB8H0ogpPtS2gLeXM3i8s0pkJzUC1A0503t7uOLxDUXa6x9EUFbOw9455ght+A4IzjtOP1HdjSTrCXB9+v1rke4twKBKfiGQqGMD9f9OyUXdaGnyQNJUeiXoTgTOvBZixr4UnFPmRs1+E8nXT8nGsW/ux8vRyiI4GP+4AxMOMT7WiZs1+ZyELUkjzHSmBxvl0XCxf7Z88zhjEO2pyzJRM12mOZyAzOQslzNkWTosZkqB/9dAr3kc8g7IrA5cJvRdUC8J1wYFgYe48Ws0ne3M3iEs2iTKyKLMkmQaj/hy7npQg1PUrVUcsAZklRdZMiIKGOBRB4HJUpKUQH1LQpc0P0b8toJcoGZeURAaQSiWpeAIlDci03JOR9HB6Y3BDNvaAs+uKOj4RaT7k5Vdo2qvSl2LKIsdDOYJCHImHMFX2D6zk+VZ2nwSCyiFkHqXv4IOeVQHjDKsy5quDPU+TAHR5IrVOtBRJqn3InmkWMCmlC1qCJoVnhESVZ48+9B9JkrpAbwosl3IP7so4hNwRAf27IZAo8kirq7tvf7SEgkjWnuoY/O4/3dXXvGN3n3ob78/fTfGO91/XcEAwaOKKUGwIA7fZbwN7BuZe97GUrefMdnNtKnyPxonNVNmE8Nh2zDlTbVwES2wpUVkLCTWo2YPwipeP2on5LboY49pSVS3WTO0pjh5vNkD7ncpaOXtYBsQxm6ii2v+sxQyxwLA1bfVCczzPMNatfop99XrMltmOYveLnVQt3cJATHasZojVgrBliHdDWDNHqdEUpwjS3QUo/N9ggNx7lVeCjX6M0Q1x0vNqSky+lfOFejKgT8pX1v0P8PIN4v17Q9ExKrMhLHCs5EtOLi42mlJeFsSjlqjiaYg3XMCOXyKd3s1hDZ4bciCJKsvn36bwsN0S/7gudWpg45zU7LEIztq9EO32hU41myI9in1noVCuHqU/DTktDp0X0pw9GnuaTzokEvplmsbnKmH1TZ6FTw6+hx4hMkpwJk9rfyTl5/244hC8f7BA6hYZOjWZBTR3Cn0ZbCP1lUaEKkeLfjouIwOTED2F9VsqvoZGPS0KnWLbRl0E9yXA61izUjBCROToCWef4RaHTpgfKvnzTyW9uQq6Tdarnxz9fcdZp2EAka7LoL2woKepgsk57xv7Ss04tvwaQs4CHzzFD9razTjexkHuWdoqsU1YG7ZeYdZpdr12zTrtun3V6oWyy/a+aSKagrAJcxcXD/UoTyVSWy8CUZXJeoquhiIYsEuDqpSaSFSUQqK6lUlmX2KoR2s1o9W4hkUyKE9VSac2yfvclkgWchZ/6l5pI5s8nURu7SiIZn53niWTt9rkh+2jIXvayl63kzkVD+uqKbj45V/2oGQT1uV/V26nN7FhiX16Dbd+WlOPoY5QuIxXAxnm70Uji+7dVnb1PNsyhj0viSlXXrzIegxJdM9XKaA8R3MEB/GRStnQ7YwMCFiRop2dnmzXnviaGw7Vo0e91v/PmsnvvdMOs8WLuUIRoyzZFLOpvHVBzK7I2jr6w5fb2aKyD+TKltN8junTdf/PSgk0W4bpF+YW12rC3KZHp6or3b2EW7yp3brMAsB6z78M69B23fBbBbuPlEiAntnpnKoNNJglzUCSbUd1EW93PZnDjcbKFI7runti31ns9GMTKU/70NHFMTKdwD4X7oHvyRLoKsXuqa/hla3wLC0mAMojK6EsYDzM+Cy1g7OcGIRqIZdUHUfpKqnfeEdIcXRvN1wg8EwDg3noIfvZCOhkrUzQDi0VsB8idp9XRYVYhHgAwHEZSW4tw5Nk8ITiPDsHnE/jFAtW9e6nP1Uqg4dZH8/ht4JOApDQFgdE0kuhV1xllv3v0ADQewX/4sRxoGkE6dj6iMOO1q2vQ4UFCewYej+7ZC/j/8N/B4JufhEkzUFfgyQz8GeGocCcT8KABmOHvBz6LpgJXDtVkCffiHMsvyLnNv/hzQYWSqdcKoHrnbfBoAP7oSXScVl/6Xpx//9s4/oP3k5P2+AB0NgVqyanRdfUHI+FQOZ9mfBb0LeO/uETu5maxjfRFEawUOQ0KMb5wz9aNg71xAq7nHABIGH37Fui6lBvgOdeS2mX+xois3j6eH8WzhMcsMzbCpmFu8Ng/+0RkY5jAs3moLBZpE+pCeQDvo+ceQOb93zifQgSezelvIEQ4CvNosczOxWKZYO2mz7jmZt3d2VTe9Caky4AweC+XWfFisJe5Iq0xoZXzQ+JYXDMEbcdRgsKbdpqnk5SfwSzEM4sF3ImYJzwN+RjMqHQNamHaomULnszQPJNNVq+HzbyVNZ+BViuwYSOnswnGHxzm5Q3CudEhHjZN164kejJfpBIKwJ7dey972cvNy5ujWWwL1dbTS7svZnnmkORNv80IZXtxCX69D89JtTcFiPoyIqMKWmSL6t/c9czBahDFOLl4g2wqLcjLJbIaIx0ET2CS4mixiBXB0KY156DJUA+yMSuY3HViHvi0BoqWVI0phoP1TWpxKUukimS2j9ks0SGWDFxdh9KZz+0KZBzD3AXtImhT2ZoxB5rEpIWo0NkU3posXSfjmIZM0cUCvMpN2giM6jqgXYLOp2mdNCRsQtc8XyRMho53sUT1YiommWoszMKPQTm3qWjOPqsrI+PZ4yyuLpbhOaAfrypZrdLYfg+NnH24bATDcGakYwVq8qbFmUI8XRiDtf/teV2X5uN9osMrGLrXSHquC90mM54+X5VzGTengKJc+C70rejXEoV6FSk3x7I9e09F6sMCmRtxEaGaWUCH9raf9RXGH7lHDL7CcxrLDbC3vzmbxY434Br8uYDSbvhR+kHvQ20OVU6Yv01fsExW5OKNw0hAJXBIgSYCW9KbcuNwVAISoaQ4SUKtU3Sbb7g1pF8VbVoOGwUR5e02gdw4EMKEAcsbeUM/+c1vSH9cXjtUroNPmltVgdxKIqjqBK2qUNeDs82XhkOBVtsNwBGIHDikmduShFRVidg2nIuqimQ3mUM8EBRFf4tN2BsNE/uUDz6L1So6QZl9gq3rMSUlWnXAqgOPh3FNetevqWXd3TzNbdDAHw3hntVRQ6CmiQ5au640aKQ6G3shLlY53/65ufubxaYkrstYvyNDVEI/MpJ6GNW1sv2Q2WlZseUmKti9B4OgJhdYfuUSaNvEMdF58fB7ztmuQz3U6FzTdgKjU1Q9Tc6G5hgAAIUoCndd6ksZrkKuxxpD12iUbljzYNBoFKMkdDiOf1s0YHQ89ggNBomV2hYHtoxYQBq/mich78JGqjAeCSNW10kbGgm4fxQ3i+wNrtc6OB4ByNqNR6DxKG14Gg1ZrcK5xrSonORhqBmirOazOdp3jjBQkyNEQwDAP5Bix+7MxWhIdxyiIcMK7AjVtIUDsHxb0J7Nh4Oksem9RAQ6OhImsPk8mcrHh5h+/hDHH6drwEdj0FmVNgtFCY+HssGfOfDxYRrriz27927REBhb0Z6vNTeKlPS1OqWboiHR/+Finzw3YbGVsSsDziFqGD4VPybLHGXaz+qEImwEhoPSfh83vwJHUD7cPJ+bSEyXHjrLBDWbx3TpSGPnU2QjbUCSe0EQGz76DNQX0JqcCstQZTEfGnmxuSEL4zugZHfT6UQ2vbqOGgN7L5tUATVndLLmhrxHrlmg9KtWRb4HpXOAlFPBHs3zGVhDxkTydl8Ixb/+RgogM6pVWNuweagvpH4eIhq6URgND86Bz8+BZpBddzqfYvzBTO4j3VjOuDcaQu1Kfhv8TVF2YMraR0P2spe9bCV3U7MwpkFObGt2TJuA1QNhVlCWvjHdwYG8ATTRZzbLUrxjX6gkASmo0t1pB3c4Rneq0ZQwruNjYDqVhCJ1yI3HoPuimtLT5wlAdXIKenhf3p6hYIwbjwRUNRCQUKTjO5e3oRsOYtKUTfDShCQAwCdPhTZuIklWAOBPAm2fgrICA3X3IlDmvfVQNAcYDEUzAB2O43H/2Xfg3v9E1jCotOQZNJ3Bt+16JiM5SaoK41WAGEZD+EBHp+upICz1LbhHD+BDlXI6Curz8SHcfClv1OEgal2L73sXw2/V4MqBrcOwrkAvzoQW72MBvVFVgR7eR3f/EC5Q8dGgAR0eiMYxaLLK6NQ04If34D4WJm0Kc+D3Wzz/tx/igV5j79ENG1Qvhph/79sAgMGTKbqxmI2Lt8XM6kYOXUMYnnQYfTjB8x+Q6/bW0xfAZCqaG4xv4bOP4Q+HcN/wkUl89ZfexQc/fIzP/e9t9F2uHo4F99EEDSr8vzoewC061E8nWL2lZgjAE1Mk6hK5m5sF+6QWbggB9hLd2iaUjTlsCBF5aJnkHYHbMvzZScaoqu++g5/M1gmAz85imCs69mazpPa1Lfg8mATMkrWoHBEQVZ8MMCjzobQt/HK5lh3qJ0jjAuI4edUKdyOQE+2yj9mjcdzPXhii2hBFaFeyqSrA5/1PpKTgapWIZkPIzrI+ZaHg80ls1yM4PM/OI1w6coPOF5kZ4p/4oDp38SEhm5nZtnGzGP7ZxxGpmRyOPqnuU6NIew9+foKqXcErCG2xkAzR4OC0ZggRgWazSJyr1cp41eLBH70AffhJPLcaDsGTCUZf93FutRMn6+EnoTzAoImbKp1P8VCdyrNZ4Aop/DnvfwTXDDJS4vrbH+O9f+7gnp7GtgYvzsTUDQ5VF3wXVdPIPbRYoH5xmuY13z6H6W5uFoC5Ea8YDsoYpp0QnAQW5yjR5k98BwA2evwzcS7Z4XEjM+E8Zil1h9CvL/pQX4jG2w3RTapjUUR0tN8gWaFfE3nR7y4LC3PgRoh2vjpHlXzX+xwB6MPmGP0QCUdCnNcOZR1rGR50IVQbQ5vhnMJRLQhHv+7PYS8by8KMK9T3oAoZYzcBgh8xjsToWHQpWhXHEQhv4udNEqkCe5ip7LG6ko3YzqvzERMSfRPeA4MDcbJqeNq2bzAkGbGNFUcg54SsJxv7mx4NsTFjW1eD8xtk22gIOVoviBuKChM6aHkAciR/mzoaG6MhdR1ARzCcAo1EDxyBVqtkCnkvJknXgfTtqW8e5dmw/dV1vhkFAhhq6qz2KM8XMRoSHXkaOgx1PMpoCMajZH60BrMwHCZn5vGhaBSdj+o4QsQmY/2Kl4JlrhpNGZkwoamnCoQog6kbQkMp9sOrZDrSaAisasB3Yh6ENff3j+BWoQh0bYsthczVukqaF7MwYd87AikjuNZuDdEQe9dQ5UDjcdRI4zpPHJbvHmJ0llQ0HjQgAP7+YWjWCbzb5Ib4YQ0moFp0Eg15R84dvh/qflQuAt6oqqSuyKABJtMYkeGjA0w/N8K9Tw6kNgkk6kFAZMXiWqMhA9C8FTi4jYY8295tuXdw7mUve9lK7qZmASRtQbWom0ivVghz/Jxo1K7XrpobRVIYJ59FVD19Mk2iqcI+dxreJgeJMYkQVP2o7qqJFMYGIDfV9LfUM097ffR4tSOS03JysI9rBGO6xXBkmSDFHmCDTvUBen0dbpMgZNcMAHXhPirD98UxgkDeyXPUDHTN2fxujS7R9t1Jfxv7ivO91hQB3NXNosiT6D9nS5yF8lQGfD25zYY8Kw5jm6zT1SrD8cc+1aHXdZLjAMhNv1hm5yrug7VEYZd/R960vSnrVMfZl3XKlM9DZbGIdr3iLJg5xzZMZ6KOe2/g0yHvhX0025S4RseWcjtCfszKzGubrFMdKy3j5kqWtvB8KuvoKOEMdBzB+aqbLrOsOVUVvPENsF6nrsiz6Zw4qPuyTp9M88zPVcBZnIZ8j9k8mqWadeqGwSxsV8B0hubZLH02OBcgOIND1ils1un5FOOP5oJFUfO383lRI43StEIMzPNFvvHskHX62m8WZeWwjWL8DdswYZVl98rIAlVVP6Rax2IcVX2EN7EcoX1glq1ccK0/YRyAWvshgrK6LhUJNvUq9DvfM0deteCJOc8UVo6VwvRtpRtCMfaSj4IRfDU2ytK2KdJjS/wpq5U6U6NjlHNQl09vzLVEtoIwmCfhHOYUOVmmjc+W6aNlm4Bg9vpYjkqbM7JYSJthbX3XJZ9OaD/90IEsEG6ZfFT0nQ+ygsxaMDmWCdRNCABODWRdfS3LJVyRhh+1HkDKIZ6cxsLIeg398xeo2zarG8Iuv1esQzbec+Ya47Lnysjru1lcRhcW4bwGjm0h3NtS+UOxGqm4sIobDuG7DpF52lL+27FtGKdEI6rUl9EEbLEZaii9wdXBqo7FZQtU5reoNuexMGNN37xMxb7g+5LqP5LzegmPWmcmSDQKIkpOT/vgWXMuVjbvI/f1xTHzuS+PpaqMeSeaDtW1GSuDp9NY7jEWIFZuDFPs+EImKcOUrp/zYXOcG5oG6HKkpJpL0Wp2LkH+zcaWQeH191Ulm5Ev0LbBTNXUAgBR8ynJc9RprAzmsY2LGVwy2Ts497KXvWwlr69msa3Tqc9xto2z06q6prZG3HXJid/BshXt6OxM5+dagGAcjKrIFGtQZLFzn96aa7U0bknW0skNb0fm31CnrH4OZghXVdIotNhNqQV5t9MbzQwu/1xyegTMRVbV3lYyz3JkjCm0Q35E77Cs6eRFY8h8N/Yeir6FYGIE35aGpeMad37dn1OKZymTsFyuO+bD+sZ1voHqaa/vZvGGigKl1oBdFogErIF+spqdmnb+suWyG26Nx+ECxfU6N6+t39qTZJeBn8ox6GcLnOrjDdlFLLis9/v1TWOdx8KM13KDADkQq69t5xKtAJvNoaircl25dLMgol8C8J8A+JiZfyAce3WHh5QAACAASURBVATgHwD4IoBvAvhJZn5O4k35HwD8OIApgP+Cmf/gOgPsdWxyz6IDa8Co7TtZ1zLAAXJ81ZBs3+/IbdROVFtQDgzr58iqj+Fyd8xNSq9GQ0YTo1yby+DxxoFrhZy/0nOZELQmCuRd/lYPLGLRNxDC0ZGIRzWLToB8mc/iquLz+yRqFPF7u0bKW2JC40hO25itXCX/ycbrHcLHWchf7xVdF39znoZtNItfBvA/AfhVc+znAHyNmX+eiH4ufP6vAfwYgC+Ffz8E4BfC/zcrfc7PXclv1FOvYaiBJCSptzxGD0xNEGH3DrwKMSS4BDWDtTohbjgUaj2T74GqSozes3lCTy6XcCFJqtNEslGoABZQpKBQkTsgRrXqVTaHuknoSEBCaFrpW/tVFGWoPapVvnT81dHhertE4kRTp+DxEfh8AuI6oVA1orRYrL3pZT6pZkVMGnMu5oTEVGplLdeNYTQEzxdZ1TYaNDEMaqMK7sF9YQu37F4ygRAmdSlqQQ7u6FAqeD1/EecpzslujbAXTmqaxuSygIj15+egL34e9NGTdG5VAbO5JAcCQtirbNsheZBrgY5TuwJPpuDHj2QM3/hu6tdA4at79wVVenIqZRsgjN+rf+NdVH/2QdwcaTjIUtRj9Gc4SKFTc4/QJyZZ7RK5dLNg5n9GRF8sDv8EgB8Jf/8KgH8K2Sx+AsCvsly93yWiB0T0GWb+YOsRXVUU2r3t6T0cnL1v/R5MB3cdbI3NvjeT9XfY+ph+sZCb0oRr2XPCLZRt+vzNGMdqz7H2tymSG8fJnIfk9LuSmwNhMylBY+QAaxdPZ6m9RdHfBrF2vdUWUyRCB1CMab5IY43Je+ZNas7l84lsPlWVmx9dJ79pkfsPFgsZk2pAgOHaKGq+kgP8dJ1/gxn07CQPnWqI81ST9yTUzswg3QhMmJ8XS7hnAjn3bZtyf4zGxJNpSm7TJLvzCeoPX0gIOEZDQoJhMGdYizQrfqVtc219h6JSV9VRHpsN4EMAj8PfnwPwF+a874Rje9nLXu64XNvBycxMRD2v5IuFiL4K4KsAMMLBdYdxdTNkFRxlVSUJTyZhS5OtyqQ1qhJ2gn0Xyu0VEY/BYO3tRHWd6O0spmIJUecD0lDPjVwYyuEIRBU5Bx0lFiirYmImc2P2OWANxgzRdQjjd5pRGs7VTEwaNPFt6g4PZEV84tmAZ9E+rFMt4lMSLiOujYrFJ+h3hRmC+ULmoObLYCAM2hzMRj333lFqqwfBKebBLK3/eCR0gZp2voUZgsIM4VUL/9aDpDEAwpTlKHKXICA4yftYlIkNgtOdT+HfEj4LOj0TDIgxtSN2JdAQqqbqjg7RfvYhmvkinTsYyBwLBCeGAwGtFWYIZrdfGPkjIvpMGMxnAISSTvgugC+Y8z4fjq0JM/8iM3+Fmb/SYPuqSGtSEufuytSshKaW+VnlpjzJ5bj62g0AKHIkPo4LIgnXZsfeUi7qp/c7l9ZyrYr3Dm3vJOqfyBjSKR1bu6YuX9sw1muNxyFd4z7yZruxOwKXY7X/TFQkjuuiqNJlc7BtX1Ouqln8FoCfAvDz4f/fNMd/loh+DeLYPLl1f0WGszBv98tS1MvfK8mLbrTMazF5wMsbS5GDCA7HQbMeiQkoS4kOhLd5U+fMyuEmEN8CAVVyWlLXSf91E97wLrbPnYcbj1LMXqfcGEJgiONUUu99fJvHNPOqAumYwjzALCn0BUYBRPJWa4NdPhqCz84R6fUBSQpbBRu8B/5OxQ3PzDJWfSOHN3Ucv2pAo0TYGx+aQSN5NToX1fIOzJvfEMfQaCTrWrkEwwfkWhqkoxsOZf6+C4S9oT/PQFODDg7kHgEiUTHNF+iOR2ieDeL1EXauGj6UCXSdj5qED4S9qB38oEJ1NgfNl+gO5PuqC74si2npPNxbB+BhA1os4hueD8dYPBqi+ZaBsB+MRIPRFH1n1uZwDDo5B+sYPO+Uor5N6PTvQ5yZbxPRdwD8Hcgm8etE9NMAvgXgJ8Ppvw0Jm34dEjr921uPZBfpg1pvEy41G8eac1BV6MyhWbQZ4NRskn3ktwa2rHkR0TFnnJZKCAvkBW45UaVl56oDsnBEctfBz+brDsV2JezgBkvAwUHqbQIbkEJsyzyKExm+zLnkZL6R6erpc3EOBtauNK4QQuy5FnE9tG8gd7Z1ISlNNwY9ZzJJ5RT1QQ9OQHgGuzR+9+GTLKEr9h1KAFCVc57w2Rl4Oo2OU4+wmXovm5cmjTFL6cCgxgMAaTIcgObPP4RXTgwgvHha0Aea+9HGqISS+FLlUBGB2xZ+sUQT1qELkZ9S/IuTPJoDgJ48w9Efc1a/laYzYf4yWh4A4LQGNQ38ZAqya3STuSHM/Lc2fPXXe85lAD+zde972cte7ozsEZwqiorcwueRJZwFhqg1m/DSIkBtbk9X1fq5F43BvCVjEpwmMZk29LxoNsVqYSQANDsPrbGh5o2Ci3TcmqI+aOQNWyTeXajd2fWwzGHapqlzQUBMzUdVpZIM5nfUtmCX+wNomCrLp37DGqjT0kpVBYdgcHBWVUg4EywNK0cms5xb10CVzCaikI07HuVvay1qNDIV5rWsgzoXK/GdkDKeab2UDRXSaNAArpJMVjUPmwH80Qj0zDzGg0bS9gu6QhoMxMm5WOYO5h18fPvNYlfZ4MC6QqbD9aUoE9grl0GRbVs3QSC0q9gNMzj1uMdZtxXv6Y2NycWHGUCEX6+fR1nK++2PK4H7rvZ7dQanee0id3OzsE7LyxyZGyqWxTdtLPtWZ/9zu0zaQuGPyBycayUDw6kBEZoVMzMVw2hpKpK1q1SJazKJ5/KqDQhFn4U4KbwRld9Ba5JmFc8AsbkrIYVNBYuWaQ7o1iqw0XiUCHQMP2ZW6ezoEDRfJM5KlYUyjq/fhLoe8W8k52Xsg0i4PheLlBdhHJzZ7yp5I2f8FA/vJQdu7DiM0bM4Rq3NH0Knkfe0rmO1MzJaD9gLY/h4nMYbuFR5Nkf73n00ht8CzgEzBw4Vycg54cQE4O+FEgLq4DxdwDmH9rGgPatPnvYiYOkgOTgjEvb4ENMvHOPwkxdpDY4PQWculWWskoOTawe3bG/PwflaylUdnLaJ0sFpmZz6+tHPhDzbckPfkX7eOtRMxTBhykpVwng2z3/fmipcPQ7OrOKZSpcqnsmwpBo4TJZrRJNSQIYWuAue2Sphiq7UvIrg8NO6Ho5y1KmiCy9aDyBzqkYnKiAaRUHSA1NBKzMx1Mlp3vju+WnmAJSDTlCNWpXMXo/ZPGR3JmYqZQQjxVvoOmIlzlDdVIH40mg+PJGKYSrkBML/QpyePJ3Fh9dplKNyqJyTDXY6Q/ORfN/ZdbLrN50CS0kBiC+OswnGfzHKnbreJ+czkMyQxRI4PhTGrdgov1lMWdeWbVXrgqLu4lPzBKpemPMm6Lg9156ztlFdPA7mFLlROLiQnBdp4xpZiJujz0yOGPnQsZhIRJa4ZR60WNfDu83zKcV+19cXumTOMacNwpY9tFGUGA0xa7JYrq9jSPXnzq/zWOqmaz+HlHo29HVgFv9FZ2DmmgbvvdDa2VCntjHX2iKrSP8XNaZKws4cIkJahyRGqUrR6Jl5UVG7hDufw5u+iVyCeyP5dBgALRp5Kbr0ktrF9HyJBtde9rKXuyx3U7O4DZ9FgGcnkJLh2Sx8FtTUWdYq1fWaFz7ClK3PYjCIJQvp5CyVJJx0qTRfeBvRYBDh2H0+CzccpgxSBX0NGgEOqZydxShGPyiry0FZEH+E+iyo9FmEt5979AD+ie/3WUw69PoswnrEvxF8D8FHE+HJoVp7BKcdHgKTCXy7gjtMv6N2GQoHmffde2+DPnlWdCxj5NOzAOYysOyjQwFsLT+Ja66gLGuGpDUYSzuAtEUOfrlE+z2P0Xw7pZ7DOTENHkv5Qnc6WfNZeOuzODlH+/m3pJvzSV4VT8d6/574LJ74VLvk0UNM/so7OLTFsI8P4c4mvT4L75wAxKzP4mz7LeBubha7+Cw2qFk3BspS0trCfr4UlGUzRK8IyrJmCIBQid2Qt+q42G8GZUXGbBfHcSko69mL64GydN7WDLAhXJtVOpmk7NxeUJbxWWwCZU0DKGtZMKifT8RHE8blF4tQPKkTlKoh3IVzOSjLvEyab3zUD8qKhLwJlEWhGJG7IiiLbVbxs+c4/P+Q9U3zRT8o66yGG43gT89A4YUE5jeEsPe6smnzUA2krE2qyVPbmHCBYCV+NGUBIoKzh4xWKNSMHRz9JIZ9uxhPb81W36Xf2t90WPOfEELikS/GqIzZqlFUFbhDPg7dSD0yxnSeTKHM4VzeaxvW3a4Hc74ZyZxWa3SDADJ7PNZp3XB/e0V/lqIb4Sofn9cNL6wtt0gvgXny52Sbshm74m26J896nOOGKs8SCOnmVpAb6SbQT2IMqYGqbQStoTs9h5svIr8FAHHQ9kVTHEki2WyWbzhvvINzkxmi0qd5FH+vZWH2kN9ohCD+LlRkXyO/qU3WqeYZjEZXI785kaK1bjyWt25V5R7wVSskN5VbJ6kpsk6V/AZsyW98PLeX/Obevf52A1gJQKx0DuY18pvME28esj7yG2xBfuMODflNYOYuyW/iNb1/b438Jm7eJfmNZ6k6Pxqh20B+Q9CHUDAXbgP5TfX9/yZgyG+orsHTGejRg3Ad5hI+teQ3TS04jUUr5DfvBPKbb31XcnpCOQFdG3d0KHDtFydxc6gfv4P2i49R//kHKSw9HIhjNRRGzshvVh24rqMpDO9Bn2y/BewdnHvZy162krupWVjZ4MC81PFpa4wgaBpdl+DSllYv81LSetZpX2Fk5WWwQwqgHwCg5TK+YQWUNZbfBs2CahNT77r4huBVcLDW9XZZp1WFrbJO+wojL2W+VFX58ePDWEAnajLMAC2TnR8n7SKfhfprItx40GzOOtX6FyEzlVdJI6HxWL7vfHLkAfAPj+DaVq6RohSJopOP6lrAZIBAxcdj8OE4FkamuhYHZyiMnGmrVSXO3zLrdDbD4vERRpNZXAcORYn9A+HXcM7FY92D4OAcVODaoZ60qAAsHofCyB80EXofe3dOtLnhADSdpcLI944w+fwIDz4cx/vOHx3AnbkI24+FkQ+GoDaEp++ZwsjPt0eD3v3N4qoQ5T5AEyeQ0oVSgLJ6QTShvTWHaQAzcQGI4TbYqmreREdkuDHshud9VuLPYiTIcoGG8ofs2fhkclDWGi5htcro6wBIjF7LMQJw82Wa3yrcQiWGJE4s4TlKGnws07xS5MUlByYES6B/R7W8bWO5ScvuTdMQRSEHBAg8kaTOY7USKkKzjty2oEXKAeGV+k08yFZbkwsg0S2N0hi29eZsmdEZUlhvmoZji2UoN8mozuXhdIMaTAS3aIFli/rMEAmrQ1XXwHshrfEMb2j1aL7A8HlIZ1fzdzqXaJZGl1bpmlC7EnNsaiI3O0C+7/5msUl2RHbGArt2o43JZT3+EG/a97zejx63EqpCJb5Jy6vZD5BZAySFY321TgVebjenAJxin/qKvwlOznKM5sZLXJDFprIym0l0wHLaHGNkA9G5uFadS9vRDU8NYt1UvNkgdIzaRjhWbu7Uhg2tAvRCxgiNl83ZolsR/B7ZQ9n59DIoHyRNX9d2w3rSIue1JJJUe9W+eLUSLcH7GEIlDtXJVh2wWsEtTBlIyxNi+yZBzNroVz0NkTld03aV1U1RHhFaUuwL9mWwQy2cu7tZ9JUvLL+/yAxRB1gXPMVVBZC50fUca4E4QqR5tw40m3WqfWmJQW+cbVWVbhZT+o/dSlRyzR6FOBVRCeELG0cVr2BKBqqqrQ7YPLGJ1dFHJimKzP/E60xSQV0GEJmxlcyFtDr6cCChQUeCR0DYWFhqjyZMiL75XTSnZG4puU3RhLGAryIbdZiVi+HROO86OAe7DmgGSXsZDmScdZXMk7DRMXMkLgKCdlPXkolpnaSVE02qcuDOuPSq0KY+fFVax+5wiMZm+46Goh0FDAp1XshovJe1A+BH4T5oZVPpDuV4HdZfsoU577tpQqYqxevQ3hugGQ7SBj9oxNSsw3XU+2Y4AFEb2jFrs0OC3t3dLGI05Iq/t29qL7t8fGP3nLN7++ZNHmuRFKZE9lneypERnDnTILJaFEFNfSliNTSjwei/Ps0H5Rpyz1ydSaO+ilgG8nKM7PIxqKbigLUXx46Zl31Cl7XJPZqnL/7Xr7UOiG3nIko8bdtquvb/G5R9NGQve9nLVnInNQvS+gkIpoFPuIF0UjBPNpgpLkQl/HQqHvvDQ3EOKm5gOhVVF1VWJYwqwB0cRC5N/+IE7vgoUpvpuNzDB+Dz80ASE1TX4yPgLYm90/sfgY4lhdk/fQa8K3F2PJOYvzs8gG9b8difT+J4u+USNB6DDsbCg4kEpHLHR8BbD9McP/gYGDTwZ+dwD0PM/8lT+S7Axd2xeOw7jXQ8fhvuTLAEioak4RB8/wh0KujDxfe9i+GfCUezvy+/J2bQ+TQnZzEs3+7B/YhSVRZuPhjBffgk9BHS9R/eg3t+KklhAPDe23AfPoHvOtB9YcD2D49A04X4KIwKfvaD7+D4T2p45+JrkKsKflSj+egEPB4C39YiQwR+/Bbat8ZoTkI05PAAfDiWNO5BAzcxaNCmxurxfdTfkfXjQ8EquPkC7/8HR3isZlTn4cc1mk8mOPkBuaYHHyywOhBTZ/Ke3DfdCOiGhNFTj+Nvj/HRvyvtfeGDYyCMB8ak7L7nPbT3Bhj/McMHXMj0L7+Lb/9oje87fRTPm787xPiDGfwwRGQG0u/iUY165jH6aIb5Y8VZAN2LGywy9DpKBn2OjrANWZsboiUR/uwZQCcpwF2Xp+x6zkBZCt/2s7lAh8MxgUgXiNDTs1SwR9s8n4B0vBZF167gnr7IPfXTmTjRQiGc7PyQOxFRf5pKPZ1lVpmfzSWK0a4iJDjyTYa58bSAR3/yPPJkxPyYpXjsNbw6/FYdQFkezhQvYuWzKGt7she+y3mOUsVkGjekmPq9WglwSv0bnzwT1GHXCeAKgAuZmqyh03CNj/+kBp6+gLMM3kSoEDa+SZ3xalZPnqOZL7L5UugLVZUjIyuHetnGdVRmLL9s8e4fzNCETQTMwKABn01w748D7+b5FE3wRQw/DqHTUQ0Q4GYrVC/O8W4luSF8di5r4QyU3jnUf/EE9XAAf3Iaw9PjP3uKz/0f76D54Hm8R+sXI9DZdI2wd/jRUHKfziY4OE2h02r+psO9yQFlstIVmZ4yBialYNPvAiWd+gskrLZD20RSxdoWvQUSHR0ZZ1lVgSza05FgIKjHQXnbpQAy562yK1GqolUFchVvqOrUWeYooWND3RPWqIie20dDuI1Q2gCkPYSygAF165xsFHWdHhZAogB1LeUSFc9haQSvuZ6+Mk5skJQmrBy4MtddHe16e2notXHgujLnBgxPVSVav03MWETwNUUMR9ZXQIyyOjgrAq2nnOwkd3OzMKJmSPgQ/rh807B5/vFh9MbpZnknNdqwS/Vyly6YXmytTUJEwptgoyRltKKqQHVwIBYPl63veeNiOSB18yShu4ubBZFArhc+PZSdlxudKAK9NBpFdj0AiUoEJu+dxxbGJTiKECWIZk/4rq7Ao0EcF606CSHWddrIQjs8NBnEV1xTrovNrw4bkN5jev3ssZqAjoFa7j1fp2gQV5Vwaer6NBseUyL4iuR7BWoRxQgSeZio4fVfMHsH5172spet5M5rFrcmGpLL2ISMGm1Dl5eFMU0ojfqqQ6n2wPnxrLBOdjoH7SS8jezveiqfkUsEuJmZw+tvm17y4fBm5PgGd+vhQSsWRBWQiL3vtQzTYjSrwDS1Nh/zloyJVtbPY00K63uqnKA4ARP+9XKuOU00vyqEWSsQGXueRGNJldaCtujC2718gzsHroOZqQTAAHyj2Jpg2rVeEL2VWaE+RrW6ipXX44wrB1/6J+tkhjAZnEXtxGSrqqQNlgmYl8jd3Sxi+rSN3xc5HBeJVmoKDk6nlalsCnnkuDAOTlXJLTDK+B+iU6OqALQBcm1ATgoW6joAKTcEXi5czDHpOvBiIVmdnfEN+MC3MB4lJ6tOua4zMhoiSsQ8hSqrNx3VxS1giuvIdDxI56i5LnWoEk6UP5QsCEieTrMmOcwto/brIMQzaqJp/sZwIJyZvoqfeVrlm4Y+/PpQaV7EqJbtfNUlmHPlwIGol5hzjs7KCWpTI2vjkZhXwe+S1a+ta4m8KKhOM2fJwQ9J+gAybEQXgFduWsEPGxAzuoOQXj5w8APC4EScyN1QYf6B3CaLKjlg+EjyO5oaWFCY7wDtQUBmBvGDKoDSwqYUNiw/EkCXW7bwh1qf1uelFC+Ru7lZ9Dky2acNYgvbM+NMhHjjMwJYdaKtwb19BqcF+0BUk48pI79RtOJqlcrreZ8lXfFshjw3xCcUKEy0RyG/hlhXN0y/WMCdmjEE/kr2HAmB4+a6WsFWKou/OU8VwNApgtSnzwDoxZlEJzrj4ymKOsc5AMIPukjEPzAw6LgGhpRHyH2DDX56Fjk/Yzg1jD+CwsKcmo9OZB2DM1POgzB8LRaReUzXkydTAeMphHs2F7h02Jyz3BAiyfnQzUYJeboOB38xAV6khafBADyboflQwuk0Wwg5LzOGs7DBDw2C82yKw++EB7g1ZEBWe3t+CjdpskhR9eQED//1EDSdp2hIu5KoWPDl6HzdeZjbbIZqkZIeqd3eb3Q3N4s+MSQmW4mBewOI0YioDlvEYokWVe0C8lbvU90jFqRUo82bPEK49U1WJp55lvqnnuFq45B1hTajtHrBMRZlJjBrblcbihiZh0eP13V0rOnmSQo3Vhk0wFQwJxRVWmcYttbD1lQ5IZcB0lgqE33SYwPJuozb86ABLZcB5h60j7qW8QanasRUjIfApI7OzNg3S5iYRqOckayqAq+EGUNTpyJS5qVDlQvFlcI4jaa2Oh5iaAv3NLVoIkofuOpSJupB4BXR0OliBdd5rA7lug30mvrMPhJNZjjIrjsPGyweNBiaaAiPBqB2tV7rdDwUM2q1kr+BZP5uKXRrXvUd5B494h+iohpiCDXZMFz2Xfw7bRJKxCJq/SUbhzP5ABsqg+kbIrFcp8LFmRbTk3+SqfclrNlkSupn0jdJlS6yPGChJEBk45JzlHYv75TyvgKbVWab9v3GHKdmkH+vY9Uxmt/wKtUjsRmMFEhqFC8QNRVdx1DAx88X61piGQLXz5yIdiiYjNEctDkUbSvVwuK4Ai4mrG8cWwjroqoEmKfjtetXjENeAG0aV1jj6p13IgYEzhnTrzBNDAUCDRrRTpoaPF/APZC6IaycpHWdNraqiqUX7HV3Bwdw9++JNmXSBGJ1OXvd9TpYkxbA7y3+IU780612jH00ZC972ctW8vqaIdtqPKXaXh7b4vfs054Z64EA0CrkV5Ws7kbswMXkqvh2Cm+CMuWaNaU9jFPbzMZ4G5Ktqb5BOdYfjVqQTc23iXEG1QklwDVv7MyRvIsU6exr/CNmDeMKWYJkOzbvwc7J76+TMAhAOFHDtfY+cn3EpMS+e1nHo+sTfVNBO0Oql3IRxwprWn2WvOdTxOqKpQr75PXdLC4Sq6rGHJBCk7okRd1pbscypFpr1EFTrpXFOSORldAc1U0EHvnZDG48hp8lpiQAcEeHwclp7PbRMPIf8tl59Kj72VxyN5gjH6QbCfekclLGUofzhVD+j4ZRvVcTxZn2AcCfnYOqCn6+gDsMMOPgYKVGmLhcsKtVFXePHkSWsMiZGZiyogPz4X3w8xNh2jJMWbxYppKK2bVwsh5auiAWAa6S+q5RkfEoVArL+T79YgEX8jFoPBayoIIpix+/herJ8xg6lJNJIiKTqfShjl7nRIUfD0Hvf5Suz3Ag7VYuc6hSXYMOD+CVySxEnbpnL7D8wS9i+I1P0nyrSng13xMItzudJp/FfbkO3aACO0I1a1E9O8fsS+8AAEb/77dl/U2qP4hQvf0WeDQAf/Qk3Zuf/wzOfuBt3Pt/Pkw+i8Ox5PBoNCSWAhjCLVag8yn46CBeM3yrMDsvkNd+s8h8FUEs7JoqIctdSyS7TGLITuLcNBjIDarEtpOpPMzK+6C/CdwS0SYONUbXQqeN3HSENvU1aNKDslhECjnqPPjoQHgPnj6XY02wafW38aGQDURi9Jo7QPEcS6tH5xM55hKFH83CuYomLUKnNB6lUKzyYdShRmvYSLv7h6jalURUQlIYQqSBF4vkuFV6uCrUF1GGp9EIimbUMGte/9SnXJFR2DzIxbnx4Ri0qBM/RHhrtm+N///2vi3WkiS7au2IfJznfVTdqlvd1eWeBzNjj2dsMx5AlkGaP2MJBPwZyeIDZCMLxA9f8AMS8p/BPxZI5mHEByD/MSAEgg+DwLaQGZkZuz1t97i7p6u663Hrvs4zT2ZE8LFjR0TmObfurerqnqqes6XSPZUnMyMyMk/kjr3XXgv5suIfq882wPLbngD+wcqEZwxcv0RzMEZ2dBLGkXo9ZtDK8/ZLJsvgBlEtPdw7rTG9XaB4FPVa7KCAdg6razy55USc0rQO1QFvawYKjoBskaMHYHbIY9sXvZj0vmgFN+zD9QvQSR7Gxu4OcP66xvDdEchwX5tRgdw5uNzT6hVZ2J7NaihjYHf8CyWBg1/FXtwA55Ms9Ra6n4GrLWEkwCkPcIdQRli0WxoOEkxNA4nWQFi/W13Mi3Va/k7dRJp2lB+L9W8NJQzWSR8BREbuVDYx1AVEblC5BunzWqA41Cok+A0gsJKHdtP6FbkO7+24JAANn3FoBdD88sMZL2Yk/dU6BCm7KezupB/+b00McPplkEug9AAHuJldnDrj0ESAWJKipSIHFQWsBBLTpWFn3EGKvTEJ1ibs7tntV0PVMeC9tmUF8t6cW9UxKCuEOJL9so5fHFJRF/twLQAAIABJREFU+/g4ikvJ2ARyJuIiQkmdjseg6/twJ6dxKSXB765uiGTnfABY7LdnX8dZc7QNcG5ta1t7fvbCL0M2Wuo5XPR5U8wi+RwIV5ukSKxDrutS8lsgxEakKhAA3MpCFXnQ4wjNS8VqKwCXx1m9aRKNkjq+CUXwxmivSZKtpyidbWuXJII3og8CAHYBry9CMeaRpoGtS7RLfP/zPOhlhApbRUAe3V8uIqv8UibxOKyFTYJ1bD72kGBR5G2nyjKgrSlZbrnkHFQUsFUFV8fjwph0gnY0HESgmtxnohgH0bqlWEa90sPsbWhLNEmoyFuKZF0MC3lqP7sgXkIuE2FjrYDcRilJYpAUAYHd3Uml8bKCcxZu4JePj7z+SupxGUCNR6Asg0UMeNKgD3N9DHV6HioRQswqof0DOMZCecaxsmSpimX0wC6zl3Oy2DQBXBDIvJijMwmAwf+oTHS3XR2/a7Xloc/Bra8bngBEXMfFH12rYhXsngaSl2UVJ45VHWHaPt4nP/JQkt4CdyleCgSt0ySukUwWJLl+//CHbUDUOk2vw1mGV8vxIrKjNfdPcBTDAat+d7ROnb+WjdkoGQ/5DABlGaQJwmToJQecTEJlGSUF0+OEhTvlHB32Q0whmNItTEM6jlQW/MM5ZxIhBj5xe5SMo0wA1ItBXpQ80dCyQnNtiHwakbnCfymaogRErdOxiAxp2FxDTzIo61BfY44J/X4eqP5To36ftU6Xyzg2gz6WN/sY3kuEpYZ9nkS7Wqf9Eq7MoeqmrXX6FPSML+dk8TR2URq1C8/2b2y3obhqzboU+p30Zmtb2oYxUbeju08nkBtiSZtIfLoeS4o0bSL5TJq+C+hKIQW2DANf4480MV3bSt01ib7rqo41GRddT9c2jZc17dSmUlFyIN0nTTMCHFhNWbi9qVW9HuT2eqgtZbjkWl23DsZfq0ug9iEekMhPUtNw4NE56EXC7i1jakycWJI2aOUnx8byv2oF1DX0IoG9b3pmPUGysxH8hrpBPmvgUrr/VQ3XmHhfpcYmwN8bUAL3fhquzk/uZOEJclIKvhZpThcqTcTM1CnPxabTaiY2CUi8puG3UJcFSutIuZ4c24JNpxDsblZC3PZQn9LxLFKIr/QryxgeLd5SUcSAmvxdVi00przRSTfsgHn3GEB086Xf2l9PkUcOjrTfT9LNTMcjZemWccwyfnvnOSjPw4+Y8pzZspft48jZwMIt5qRfqSk/LsnSMfZJBXZyHq+cg6RaA9d2QaeeXcz6ZZ9SkavDB0eVsWj6OXIZB3mr13VctuR58CwkOxE8i8aCliuYfu6HplM0J9YrOZtT5CDtlxF5hnqYoUiIflyR8wTU9SzKHKtbY5SLCtYveej7oup0U5yiO0OK8G8KuGkxQbcBM6Iv0VqxrJ3ThX3Cut4XPq29DWrvjqeZjLphARhpX9443SKp0B8X+9z1LFZ1CwIeYhGLZawkrGsW1mliu84YkPNvqFRIx/fV+Tdd6INcd7WK8YDZPLJgbbrmTZZ+J9ddqdiWAIjEY0i8Cbeq+a0vyyKikOFI6frVbNGiwuNdGzhrWoryYRirVWtbWtRGpwkNoDE8gWgV9iE/rq6qkB3PWF8U8EuWGm5Vt7hMqfYVqPK8aQUlMYvFAtkxZ2RcvcE7AuBmC1CmYatVzHAQofewLXRMoh+r27B0agwKpeBmi9AHpF7KFWybDdna1rZ2JXs5PYunsWeVN7zwdA6kk5gC8FTrvo/MUtWvpKgowJlTRTC5BpvEND4s5PlZLNEdISlEE42RdEyD+tpH/G4TCLt1Lai9CCi12reOg9fPAUZ9JXMWgMeX+E1PTZTng9hrGiNXtJdzsnge2ZD0XACC+lgaBNuUDZGvJHVaN5vXfUqhhf70bYRsS4eEl7pIupR3c9P5PQITQJQJVKpVOk2rVeDECDGKLlNWJxoeUpfJdZNHYYbMUZ6HtGkrZmDUegq6Ox7yGeBy8FSo2ZfwE5rIoZHyk6al5GmlqVierY8jqSBynCqhybUiSUGTX2qEcZAx85W+6TbkmS+PV4ysDDELrybWNHClj8ckQKjADaoUoyytBVUZbD9uXwvE+jHneEV6vTnMMIdK40a+PH5T6b/r5VB5HvslpERXtJdzsriKbZokUn4CSRnKWr8oWui2jTUOcmyeoQW/ToNSUi7f7wF23vrhqLIEjbzOxrIK0G9arcJ2eCQgFQWrqGcZewApY3aWMUZg4drXkGWhBBsA3GLJKVjrYrBtEX8Y6XnhmHyHhoM4CUkNQp7F/gFw+zucotS61R4WC+aesOseQBgP+QyABoMYA5BAa7/vZRliubtb1czpIceNhtw3kenz1hzuIuuquGeapfsEsZlogdBwwBBur7+CIuf0aNN4zhC5Dl92vjMKAs5y3fb8HPPXRxiJCLK1cHkGmmSoD7nsPMuz8AMVCLjNCaanUB6XyDON+R0e3+F7vc0xi50RT0qzeZBvcNd3cPK5Hm7ei/fG7I+gMs/TAYTJzeyUgANoMYDZ5zQtWQd3/5OOs7hqgDP92z1FSHV5V1O4FVo0cRsCnLCeySmmS221zssgQcD0xltP7Rba90VdzphQoBSOX1ZczdhQ/Jv23Z+fu8DntFUFOnMxo+P7meqDpP1uMWX5ftmz87UAp2sarl/xGA318DFfC1GL7QsXBOfS8QAQ2cLqqH0SAnLGRNYygJmy/L1x6XEJhFssu/s46HqIERFzRiyWcMuEj8JfKy0WEcINsD6Kh6e3mMy0BtV1mylLEVzdYPTt41DTI5gMW62Qf9ffh8UivP17ZxtAWbM5hrJ0nM3XIPAAgMcnUFkGO1+E7/X9xzj4XQU8Pg276UXF91o8JP8Sy08LSC1ONo/UgrSprQtsG+Dc2ta2diV7OT2Lp4lZXHiOD4ngTOjoAjNSuvT5iBGcSKoiKeGZSBGVqDzGIKliJHUBglPQoB83glPe6uk2IIK9vCq4+zgQnB4BSw2r2gdfzjqOh/T7ESsiCE69+HgQnL0e92m+iEHVp0RwQnmC4rREfYvgTOyyAOczn1eCj6odvPuYrIVx6Cp1JfuQ1rxuVWl/KYLQOlR5H7ul1ZFCj58GMP1kuSno9/z7Iu17OH0A8yXVuS3FuHw9oPpRGVGUD+iCy65otpdBp4Hxp0zkvDwl6gkn5yaOi437A1jj6BT90i5H52VclbKbBBwFUu2LsUJptBRsXcaRKaXu0lanVPwyT2mNwn+DXohE5lsaqmmJtYvsz1LeLWCt9QZjlqNVut8t6b6ozxuoBChri15IXwMTF7Cx7xKc7ZaUqyJfB2V5hbVYmp7cd1/SLwWDVJahlFwNBjHInZS3p4RApJUPwK5ifMP3yRkTCJacsZFzJP2he3kEl9Tu2Pl84xgqKf7SOgSI7WQK1e/FEnv/fZeZTMZW7e1yTCfpw29Pv44zc7US9ZfHs0gCg1SWSQVkEfQ10kAVZbmv2mRyHKCd4dCHN3mbDyyqWzeBZRVcNPOdd6BGI6Cuo0p5WcIZC31tHKLh5v5D6Js3YO4/bLWhf+hzoJNzDjbJg7K/h9VtVjkvvnMf7hpHy/H+Q6x+7NMg66D/97e4rU//APDgKLAzqR1WXG8eHiF75ZBVvL3iugTd1LV91K9dD9eY/dFdUL8Pe3wCun2L9713n/viKzHVNe5P895dAID9c38S+WOvdj5hJXnXK1HfGCE/YRf/5Ef3sfdNbnt1M0bW86M56O4H8ZbVTaB3o0+9BjrmTI+9vgcowIx7yP+Y+yPVmPWtXabQ99dUf/oQ+dsPYI6Oob/4eQBAdThCPlmBqhpmWIag8fs/McLNbyxgtWJ5QABWE2xJGLw3QzMuUfz+e9yeNVh9+VOY3i5w/Te+y/0dDdBcG0IvajT9PKAqAcD1C856fPuYx0uWDd98C9/+lR/Ea1/PwjjUQ4XRexXu/SQ/IztvW6xGBHLA+af5fM3YwfYsevcz7L1p8eCneLL5wi/PoY7O0BJG1hqTr76G5b7GwW89Ah6yCPPRz34FX/6538Mf/dKPs1QhgMltjd13GtQDBXJA0+NxmB8S8onDzrsNzl/3aFIDrP7Df8NV7eWZLBITxuvwOfnL/3Hhzdcir0nP4dNl8iai41OeiJYxUhyYvSVTIHoX01mAZztjYE/P1rMAPmOQ9ktZh8LjMuzZeUjD2fkc5Vs82TRynqMTzjj47ECI8jsLe3rG1YeSTZGsyNk58uStZKczju5XFchH68OEaRgC7TpZmOKdR6GM21axJL2YLwOr1R4R6D7TyPUm/gdlHdxiwboWKReqeDAPjoLAD9VMypMfF2uq5PmqhptOw7jl39Ww56xTggdH3OZswRN70yBPajsOiVjNvINRcUUOnJ6jLApYT+PnnEP59iMUjwaBuIaWS+RTztrkWRYh3GBPbjSvQtZDYhRmVeO1r2cYv5GoqOcZ6HyGV9wB73s8h/Wp0513eVI0pRcZOl2ieDhFVvGkTe8fBYrD1MMY/UEfw0EJHB2H7w++cY5v/tqXcPitR2Hfwd0B9Mks1qJ4kaHdcQ9qZaBOpugdjcL58+kW7r21rW3tOdtL6Vk8b7sweNZRTW+T93q7BM8BoI0KBdqxkbXtG2IPm2wDPJthyW5t20X7t75P+9DdJt6VxBougziHmMkl76JN8Y2N2JYrHAdwFsE5IAVCewW32DcfUN10DQKLT/9u+g6I53SWkZAp3sf/owRWLe3JNrKAquP9ou79aem9+nhPp09kLagbenNo30O5TN9/SqD/wtt5VXt5Jwt5cBVt/p0G1u+LyG/i8ZIOhXObFcNSJnHidBMlAVRKA5fSluKSaEqBQ3kWWJdTti3KGOFHxsaJK8t8EM1nMxKO0ABLTsWEIRmFdLJRIevRZU6SDA51J60sltGTBMoy7reUc5syh/Zs6KLxScaCGg8Dl6WBgLsctdLNoSxcrV9DyCylEG/5gUuaN88YkUnE5ev+4bd9LuF2idZnuJcF65RGaUXmCrWDAipP0oxZxj/gLItAMfjga57FcUwIm+thArN3DrafQy+yoHWqiwy25D43PY+o7CuWNLAZdJljNfTXWORAU3A7qxizQKbhch9UFdBdkaEeE1y/CJODKTXztwphrxditqVmZTZ/HgBw2uFpCkwunSyI6F8B+AsAHjrnvuS3/UMAPwdA+M//vnPuP/vv/h6AvwF+Jf8d59x/vXp3rmhJ1N2l6+PuPpu2y9ct9KOJRKhpwZXXA41l7ExMwopn8fwbS9SrKipAhdRmFbIebrUK98mtatBkxuXuUry0XMZ2jGmXs/tMS4jXyDFNAyQ4g/T7NMYSvvdxi9a4zBZRCkC+k78SvD0tg3JWuAbnvJ6oBYygQpMxWSxjADqZEFsl6gCwSJSzwHEjKW8XFCrHpJr2uADIH83gJrNWHQtPPhQ0UIN8gnNwszm0c4EkGbl/rvx5W+jUpgFNshDHSZ+J0XsV0+/77XqRwU3nKB7yNjWdB/6Rnn+bu9JLAcxrqNMpxnd9Fm2+CJm1lDBITebQVQ1bRR1YdTLF7h/3oU4mwePIVw1oMmdZSefCS0YtG6BuQJMZwjTqHKi5esziKp7FvwbwKwD+TWf7LzvnfindQERfBPAzAH4YwKsA/jsRfd655wt0SAltxLPYyArdNG3ym8SkzsBaT+0+HoESen47n/viJhc8C9IacMTHCtN004DG41AQFfq1uwM1mbQeODUewR7sx+M8jT41DdzhNd7pMUfb1WgIW9ecmpvOYg1GVYH6fdbTkGCd1HCMR4A/PwCopgHKEsraII8nPy4SXZKxD3aJhN8r16HO/IPvYcFUFrB7Y6gzDgovP3OA3luWA7W7nBWAc1Dnc1Ci/p2yjtH+bgQ/7XJmx44GoA+8Gy40/3tjqNNJDC4eHoCc4/G6tsfH7Y1A84pZoRJQ2NmXrmHnDQWnY4DTZQqmlyG/f8bao37CIWvhbl3H6lofhQRZBwMGUq2YuEb4KADAlTnqw90I4faAKzWb495P9kMwk6yD6WUoHs5w8qPc39H7AzQD/olOX/HU/H2C6QH9Rw477/Zw/8/w9b/+3R0WWVbJZEEK9es3sNrNMaybEJCdf+EA7/008CceXw/Yv/mtEoMPBrCl92AKflEtr2XIlg6DD4aYv9KPfX109cXFpQFO59z/BHB8xfP9JQD/3jlXOefeBvAWgD995d5sbWtbe2Htw8Qs/jYR/TUAvwPg7zrnTgDcBvDbyT53/bbnain3gnzu8jFctD18n4JoAHah6wagpKioC1DyxVeuaaL77XUf1tpfcMFPy+2vVlA+1WibJry5YS3UhKs+pbVQTCUeS4IhkeWGXEOQvFssozsMTvWSdXDGhnRoYL8S9qlFTA8CgDqbwUm/Kqbgc85CTaLAcXE0D96MSlTn3WLZDiZ6QWVYBzdfRg/PF6EpYyOIKrCOK3bF/b7qfAbrq04DnkSpwNwVg5rA4IMKajpnAJVgW5SCmmvQogI1BjaRFFTnc+RpMRwt+L766uMWE3hdc/WoiAzJJRqLnbct8uOY7tRFBjWdY/Q+ex/54zmyKcPzyXh8TkmwGaGYGOTHC+y8U4SxYR5OSnRDFLLjGdSyiMsyAL0HC+y+sYPs9DwESgcAspO5L38HMh+fyJYFVGWgj2cIckjWQdXPdxmyyf4ZgH8EwPm//xjAX3+aExDRzwP4eQDoxe4/tV0Y4LzM1vgYdZCtW7NNSMz0+A3wW8oy1tJMA4gSJAMHI0kk5oAgbxfMxzYCrDul3Jf2Uy4O6UfCZxH6mUKEA+x7M3TYFTkvJQC4RofzBm5HAKafI/P9cUkgkbKMr2VDtoKy2N8QZCwTuLQEDIWPIbCkR24GIZ3lACerjEHW5gCagUaeM3dFGButYMscWsWxD9eaZ7CFZgi09CuP/RAqPP4/80CotJ9+PFcjCjgKspaDmXkWlh7ZNA/BznrE19CUBFMQlHEoigyrURLHEUug8K7MYfo5tH+u5D5Ue4DLdYD+N30NXWSB69PmvG89zKC1gprmaAaRz8I9KePWsWeaLJxzD+QzEf1zAP/J//cegDvJrq/5bZvO8asAfhVguPez9APoeA5PA12/KP3XKn//8CxI6Q8nTWumac62iG7yV5ikunomzj09S9LVO5ykARPmLRdZrYRJilIIt6T2ZH8x8c6S4y9NvT6pb2kfrV2/j/JdSlSUpDNbLOM+vRn69Wy9QlenupVKXeu37CNpTumH39eLKsPE8XzSU022PZ5rqVM5+Jl/YdGeabIgolecc4Lr/SsAfs9//jqAf0tE/wQc4PwcgP/zoXvZbT/xJoLWqaIYUHMuBj4v8DxiDUfd+n9LgMVrmyYNg5Rts2Yr4urFUCvi9+33GKloYg0I9XowEhg7yQEvCEOTaRDMDU31eqxVWoowsk83EkXN1LCUkiBhCbsTz0MnBYv9VgnRzkQ0MjjdFoSNvdndAXSKDyACygJmPID2lPPVQQ/DR30f4IwVjNo64Fy3MyQ8kMCgHxCr6PfgFMGOByFoKv2wOwPWtpD+7AxAkxmPrx8vszeAnnovKglwzm7lKB8OOBLnx9zmGmaQoVysYAdli83b7g5QHfTRlyVAvwc77oNWDVyRRWJbAK5XYHWtH/gopHqUtMb5pyMyU9KjPeNCMJNMnz0KB0xek9Qp0PS9J1D1cf4ZbufGsB8rcZNnr7rWx2ovQ3Gvx5WnABY3CzQ/PMPqNwfhxTO7lYPMAManaG3u4d43NLKFg6r7mB+KZxG/v4pdJXX67wB8DcABEd0F8A8AfI2Ifgw8X70D4G8CgHPu94no1wG8AaAB8LeedyZka1vb2vfGLp0snHN/dcPmf/mE/X8RwC9+mE5dapTm0ZPqUjzFvCRr5TTn35g2h6XWcEg8A8950VrrC6CrU+XnMh2BWdLXTMPlcY3uEoCWKTPAASrleNTJ8SppT47trjeVCrUAvGsEabkOSCmWWnf6nevYL89d6fKMcQHeuzE9FT5bUSt3DqpkjkhZU5N4VR4MhCRWwWOQcHgKAC5jAFmQdswUlOfOlJiDLTRUweAp28sCStH0uAwbikIhmVMEUyi4MoPtZcjEQzMGptBoBirGUDTzYlJjeRzS+JVSsDmFbQJsInBRmCkFGeoBV6VG0+c+mJLQlOS/49PVQwfTA+oRoekr1GPvRRQ5x2yUiuJBimALBVP49lU87/W9KUz/WlhmND2CKRVMjwCH0K+mx+3bQsGU/nk2YGDYFe3lRXBeAmOOQKgLRiOUirvIY5CeF/AgrQSUlZZYd5CSa5ZsS9fE4ceckKU6WWMT2mS5Kbt0OJmH/KpkwkwASDaPk4KSfqb9TY/pXgf4B9OCosu1qxifMLmHUGcasvIjJNdSt4v3nItUf6mlwUXphy00dHJt7X0idsIRrcUYTEkx8CBQZkWwRehkS/jJKYKj5L5qJqShxsLmOk7c4MnB9FR4Scg4ayLYng1tqNrBKT9J+RWtzTiYSY6XHgBPbGZkYI8zOA24MlkrG9OmCjB+wulR68XUlITbgylO6DqE3cSUBKc50wIAJo/tkWXcReP7pb5vJosnkbUQtQOFm0zSeDJJrGrmOkhYigJ3RuvHY5m5WdaVFyA4qVpxaXwK924M9CweF/gPiaCqhh9weUCNZdi0wJpTyLmcX65BJpXVCnqSEA1LP40JmYwwGXkEZIt/EoCerUI2ROIt1BjoeR0mi/LMn6NuoCvhibDhhxjiQX7syDlQmkb2lbd6sozKY36M9HnFaVG/XZ9X/NnZILuXzWqoqgYaA6pN8Cx6jy3UomHvTSbl2qI4a0C14TEWz9EY6EWNbJHHtO2ygp5koGrllcKSsbQW5XEZtulJPE/vfobi1APYnGMI97xG/xGft5gYKMPBzabP97ceEexxhvKEKz9790Uwm2HopBScpDW1Rnlcgwz30fr73j82+Oa7t/GppQlB1v6xRT5poBqOt2Xes3CKkM8tirMVBo+iF6Q2F2VvtJdysnCiswm0J4XUK7gUZ+F/JAms2HXIep1QxMl5/YzvPH4hnH+xXMdZzFgpSpS7AMDNF1CnnEK01SoS9jYN9PEUcC6UqLv5PEKTE0UxOMu4Dq9KxuMRcRYSMAQ6OItADnwJzuJ0ypBvABAV+cYwes//UHr3Z6Apk7TIi4msA+YL2NUqekzJeLrZPEDO1XTOk8hyFeHTAmHu4izOpgxxti5cg/b9R9PEiQ3A+Lt96NOpX6Ily0wi0GQOZWxLZUwfT9EDIrzdWSjLnhEtV22cRZUhz3Tog/L32xiLvTctiodx3HWZQ51OQ9AzP16gKDg1rit2LZq+gtNAPrUoHy+x96Zf1kxmTC7saQMBTp3mR1PoecHt+4l08P4C42+MUT46Cc+oXvaQHc+Q+fZkuZTNSuhlA308C+TAsA569dHjLD56S5ixALQg28yI5HeTt3/Ki1k3MUuiI/lN6/QjD1MWQd79PWZa9uQ3NJ1BjYb8g5c3T1kyX+agH+DXtFiCdnfCjy60dWMf6lgxbFm8gf1drF7dA4hQ1A3s/g5vbxosP3WdCWQe+HKbWzegHhDT1Z8p0JD76xYL0M6YKezlYoQnYnenTX6zWDA03BjAQ6Wln9TvMThql/uAc+a1WN25HgBG5H/Url9idTBCJuQ3X9rBvk/XrW4k5DfHC6jUM/MizW5Vwx1egzpmWLW9vgMQwQxy5HJfhfzmcBf5gyz0s37tOvKGWcDdDYbEV4dDZJMVVNXADIuwXn/wp/q4qa+33HCneQ0/vFuiGeYoZSI0BovP3cDsMMfBQx4DN+ih9uQ3pkN+Y/sF5ndG4YcWODOPT/Dgp+rIR2EdVkOF8d0iQLh33imY/MYiZD3qsYMr2aPYe1Pj6C/y9e6+dQP6EZPfiDcIpTD5/D6WexoH0ypwdD76kRG+8jPfwh/e+2JIvU5va+y8W6Dpc/ZFyG8WN4X8pmyR39RvX30dsuWz2NrWtnYle+E5ODd5FlC6vYb3fJZP5L/snjf3+xrGaFCWcSBO2lvVXGwlbFlA4GukRMXK1StQXgQex9DFwSAGSEObWcBLpOzebrWCGo8AYxOW7TIB6MRqWNc0fJ02ihpLLICyvIWbcIsFZxGaGsoXvglFoBTeCQ+m9F/v7UaYsfe6wthKO8NBWLYFdm/ngp5HuEZPq8c4kSIWsRUFexzpskDg2QXjSkIcwRe8uaZmmkOAzy9jm2dx390xM6Ap3VFKs7ykSnhEnbHsIRYFrC/eg/VxIl++3grUKsVUhKJd4u+dnU6hfuQHQe8fxftc5HDzBWjPe22LJWeCjGE6RCCKPjUGNJnBvHaDm3nnPseTtIpVtpoZyinPYU/PAkQ+e+UQq0/fRPH2wwhOK3K4+XJdkSzP+P7MFyCPV4G1+M1Hv46z1YMrgS1e3GXIk+x5ICs7JDZBRT3duIYOlAfNIIXtbVSQEl1JIJlYOMhH5NejLoJv3GLZnuBMEjiU/iXttc6fltAnQbnQT+diDUar3N6t9d2mMYwUiSgTB8ACR8bww5+O1SaBISFsqeuYdZBJrm7WiX+lTF+ubQnex7l2nEkCxyly9GzCE5NwgAA+AJ3wUhQRlAVPSxBK/GupNbFokfwCgfgoEPYmCvPq6CxS4QFAw7ywOD2P/YXPCsk1+MkDWsMtlrz0gH8pOgu4hLSHCHY6A2nN99GPjT2foLib8aQi4yU1SSlrOsDtrHw9TRrUvkAUapO9uJPFk9itL6PdvwL9f4sdK0mzRj0QH+/wqM0rtXtRP5O2KEkDxhtJayX2EFIe+TEk7FPs4VxdSeqpuuzZrdf6qGLaEIpAyntigjuQE6QEQsZDwrUJ5/YfPCHt013D2vHE+qWtp0T6meApsKo9GtdGYh80fL89yRCAZx/Tbhpd0s8hHe//JsxUpJRnifdFb0HHVfH+WRbJkS6gWSCiiF8JaVaeREmrCAt4TvbiThbyBtwDqgnAAAAXAUlEQVRE+59mKBI6/XCzNwQ010+RZFMoofYXwpimhu2+5bpFAE9uILYRaAkovvGMYQYr6YNnwU7Toc65tcrXi+QBn5eFNuUaQh8TxXXknsLeAHUy/t7bSL0hJ9eXCiZfgLu4tG+SHZB++nOFN7BW7MFYy0FdsaSGxHna/CA5gA8xSYjVMa0cJicZCzm/v79B4b4RIiXLSyJJbYuIkNYx26U29885x9D4Oi7bpA+BTMgDKejZpEZatg1wbm1rW7uSvbiexWXWfTOl/79EoKd9XGe+TODjDO9+xje5X76kgkQpV6Yj1VpaRNdali6K36Aw/H0a/1D0VMj2Z7akj2v8np5fNLydJRZDyXLFexABIm9V+1wbZPqeaAlEPVRapqX68l1aqi9oV244XppA0RP49DOPaVc4KC0FkD4J1UB6LQYJnD8JSJJflqooaHThcyjLLko9ZQqezLN4cBfZyztZdJchALpqU7Am/pV9/XGiFhV0Q/r9QHoCAK6qYKt2ABGwgNJQvTJkTcx0Br0zgvGUcfKjVjsjjpyn+JB+D+TFguzRY9CQMR327Bxqn3EQzV2u6KdeCTubM6bENFHdarkEUQ61vxvIYMSNDucXqPTjY1CRwy6WnG0BYM88hVyewdVNoBc0nqJP3ziIRDlC15dnoNEIbuqv8dVD4P0HQDGIeBNw9sWdnbeCpKHudGc3ZBLkutX1RLNDiH8HA9YnkUDi7g7rsiwWUB4bQx7/gqZp8T+YT99C9l7MSgBgvovyGnByDipymIfxe31wnbVBfdZBjUfxOeiVEZzmLCjP4XZGQTeEej0OPD46wuSrr2H0Bz7D4ByQaajJHPXrnOHIjmehHqa6xvtJjUZ5XCM/mmLyecZpjP7XHHY6ay2/nTFQn7oDOyih7z6MlIOfvYMHX93Fzd+4H/a1+yOok2nUDfETl9nhbFj2aAKz78fRAe6NdtXxk+zlnCzSAOZlLN6ppd5GeBv4ySLLeK2bko90GbtJeTZwCjeDLtKelABVt00JvOlYWNXaLk2n36FeI9uhPI9Rfnnr5Blcr2jtlzKIA2gT5Zh24Rycg+sVgU80nrfg/vl0sx2WUHnBQbSk3+TBcbAb1thJwC4tKAspPsWFca7MgVVMh8o+Dgjl5a4sGDGaMokDqHcKZKkwNMBs1oMSapZzOXsS8HO9gpmxE/IbV+YcW8qzQE4E8P1x/SKS3xR5II5Z7msWAAI47pRr6KrGapf7ppYFTJ8/r/b8S6bgWg8ygJ4XWO5xW+M8b0scerODEmaYQ2cJ0c2owOImK8aFMRgXKBYlnOfgFARnvcNjpqcFmrGnV/g4yG++l7amdSpeQzeoKe5YemxecFDJmETHko+z09lamm3tnNbAQccAFhDp3hIdUABwZ+fMDp64j9a6SOxbVa2aDvvocbup6Yzbq6r4Vy6tqmDTgK6kdGdzrjeRYK2wZFsH63ksUgyFsy7oZFJRcMrtwVGoywjpWrVkBTSfclNvW9jJlF3cWZIyrOu1WpPQZz8e0jYAUFVFlTLx8ITeUPY5iliM4IXMF1wfkdbdAOi/4WA7CmtEBMozbsenD0OfHhyBTvKAPbEAX6d1QJFHKLpfbtFsDiuEvyJLqb2k4JFgNThDZKsVhhIsXyyg/SRT3PPExJqXD7Ss4GZzHEzjNXb1WgFA333IE8ViEZYWxVsf4M7yBuhe4KJC76TPWIqO9MOgZCkEN5midyJesINaXr045OWZLJ4mDgHE+ECLKMeXmNM6viBkPS7JeDDDt02cjW6ZuF8CdOtKpA3/4DupLAT4jZ4WLcm+G/6Gz2kE38cWnHNAqvfqK0tJq9iPjphwCn6C5X7EytcU+JbIFExnPLEgwRtIvy64Ryk+QK67FS2SDIBA9eWcq+j5hSWjYGLSeBAAe3Lanuzhl0EVRUmG9H4sWa4hgNqMYXyCtSDdizU9sv98kWTcbBQpfvi4hbMQHI1MbqjriHsQoJVPjdum4VoUP47pOLWuY7nk8SYKoCp7PoG+C5i0bcFSdF6UbplDHVzj+py0Yvsp4kbbbMjWtra1K9nL41mkuIskaBmWJSkEPMycftngzSZCt2rMgUYJ5qndHYZ4+zWveXzMSwoXsQ+UZRxs6vcCtNycnTOUWjwG79Jmtw5hZ1w5KrM8DQfAPut3uAdHUBLgPD0D3XmVz/fW2wAAfW0P9mwC1e+xQLLQzk2nUKMR1HAQlxZSoTkYsD6HXO+DRwxnns+hfWA1QsMzoGmgBl41/oQDd/pznwF5BnKpEkWRA+MhF5YBaH7gJrLvPgSIQuEdANB0zm/3LteIs9A3DsKSRwKVbtgHifvu4yE0HrJQkIef07V9uOMTmPMpskMOGLqdEZeKr+oWrd78CzfR/85jrBH29groozO4Mod7P7rs9NorTCP45rv8/0GfqftqX8ou9w1gwt7rO9D3/XJRKP7ufYCjn/0KDr7Byx+ylin5TqaYf4G1RHoPFiFmsbjpnxtPiNM/Nhi8v8CjH+EA9OF/eRf2fNIGxwHAZ++gGRUo3vogiEk3P/4F3PtaH6//x9Ow2+p6n9nXfdWp8G6s9groyqIY91EdxOI/+38/4QFOVeQhU0FFwT/gIk/Wepaj/ZUJf9fO4UV3rKTQDg+gZosomnN8CjXss7udVJ2SMVB7u+FHohYL4OZ1/gvALrktc+cm9MNTBgHJg3t4gNlnuN1RY9Dc4gyI/o7F5Ms3QNZh8M5dAIB79QaUsaC9HdDRMZSvGnWLBdTBNZhrI+gHPlAoWYqb1zH7bBQZGq5quGEf6oGFuc0PrvITZshu3PRVqqf8wE2/eID+B76i8pSrTu2oxPy1Ifof8DV+8GfHuPVb7JTOb3vuSQP0HyyR1XUkJpb4iXVoXr+J7D63Ub/KfayulRi9wfvaEZ9nfmeM/ns9qCn3c/ZDNzD8A0AtK9SfOuRtr/VQnjTI5g3qnSjd990/n+H2/7gBmxGs9svBHKgHhP0/KlHt5djxGQ5nLSZfOsD56xqvHXF/zPUxljf7yGcN6mGG3sNYom6GOU4+18PB7/J1L2/yZDE4PsGXf+738M1f+1IYh3pM2P3jPt77aT52940dVHsAWaD5YZ4wr+9NcXswxTffvY3xN8b4ys98CwBw983PMoQ701CJFMCDr+5icZNwZ3kDmh8R3PtaH2/8wj/FV45+IVSdnn8W2Pt2gXpEgAMaP5fP7xjkZxn23ixw+gXeRg1h9dbVA5wvfCHZRku8iACFTT0LMWGg2nCN8kZ1Ky4wUsN+qzDKPD6G6vdb9QuU5bEoKy0kGo1gpzFoBPi0nGhAyHq1LNm7III7Ow+qZm4+hzq8AVgLc/d97t/+Ptx8zvUAVRU8GTubQ4+GvqbAP/ji+fT74a0N8Bpe9C/Ek7I+RSoemaQ+ZXt257XI49AwJBpZxp6Nb8fe2IN6fM5BUinpNxZYLNlLSgv6JAYwHgfeCBr0AxYgBC0lu9TvB80VAFA7Y9jzCexiCX3jejxegqBlnCzqV68h/+CE6ffSLE9jQPMlB/hOeMJyxoZJV33H//pIceFaY0CZbseRsgzYHQGP+Xjx9MyjI0z/8o9j51sxQO36BdTJBKs73N/sdMl0fdZidd17cn1m+9JLg/LRHOef56Kzvd98j1GcWRb5RLQG9nfheiXo3oMQH6Ef+iwe/MQuDn/rDPAyhHZUQB/P+PoTPgszLKAWDfTpFGbPF+Q5h9/6w3+B8+m9T3Ah2WXWoYK/stl2QJL//4xFawkV3zrNf4fOP6WqD9ts2C/05eOw1vU7QFmsL++4P861lcJdcs3yl2S/ZDvcM0oZJG21/nXlINyGwF13X3+vySTbnhESTRade8fnlFg5OReCpMHrcgDBBer+IAUgz5zQJ/JBT267sfG8XbKn5+gMbAOcW9va1q5kL6VnQYrgGre+zbQ24Elgrchb4V293AN9ElDWxiUaKSDPI4/DTPHnWRvARb1edJUFC5AXgc+AptNwDjebwfVLfjtLfERAYkXOKUJxq+dcgcrusuAsJKZSwI3jMgSp7ogAd+YJH4Nz8Tom/lTjQVv3g4gBYKM+aMLtNPt9FKcT7mO/DH0gYzlFmPBASGEalUVwq8MyZRA1MATc5cZDD1NW4f+0rFj7xPfVjgZQ8yXzMxR5uP7lzRLZaY85NAKjuoItNLK6YRBWmjod9tGMCuQCXBv0Oei6qlmBLYW35xnM/gh6UYVjAQDHJ5jc1hjc9csxB5hSI181mN/isRmAuTfJsa4HICzchP6xhV72ML3NfdgtcmCxaHtGzsLuj1CPC/ROoq7I6nof558FDv5fETyK6kYPPeuYdd052ILPW+3n0EuLHoDlLR9vMw727U8wKAuIefr08xrX5iWEvYHf0jouQa88X2aVkrT6H2+KUXCW8+ZJO5y7brfjlksPyopLG6qqkFGwq5ofCnCGQk3mbQxAtfKkLcxvkOIHWJO1ij9KwT8kWqq8n++nMS3uSQB8rDEx4+GNJvMYCwkIUQuaxBhJ/ngWIMfpo8aEOGm1Z1K9msQh5LrJWubsBIJcIU0UnACzAKjJDHblOTh9m2qiotZpAtDrf7AATeYRWwLw50wzUCklDbYWdD5DnvJk+D65hgmOuzEL5c8j+8l47r7TQJ/4cXcOqshBkzkGH/CPMjuZQ/vsBBkfsyhZ7T2fNMiOZ9h510+g82WsUg0q6gR1MmVkZsJPWhzNsfdtH6Pw1rMO6nQGJaRAHoWqlyWoMtCnnncUvCRS9dWXKS/lZHEluwwGriJoi//v020pYEkRyCVKZ3LeVMOU/Oc1aLg/Xwra0jrcPNYgjXqmqWZn6I/wHKQ6KdJ3rZICqaRAq6OVGYu72vvKedcKjbK0Xz6boaW9CCEOkGTxeJyL0PIAZnKxgEwlJLoB9q3XrgHCQqaS/3ePExi7cGf4cbNlFs7pkqIzZJo9yURvVba7PO2XD+bKeXVCmiM6tV1tVlKoB6o1Di7XoEzDJpBrSWWKUpjpMU+oajSyImPOTGnH81GEMnPF53clM4CF8S0yznokwVxbZlB5FgKboTakl0ERQeWsnwL4oPRTBI8+uZPFFa2LAmxZGlB7Po0l506Qj93g5lr7He/oowx2dvtxkS5Ld2xSr6gbJA2aqR+y35vux6bPScDQSXDQdoO03SLBZ7e1+GP3fm66bPlaPNfuOVp6sReMmxy3Ibga2pUC2OdwnS/9ZPHMKuoCuEnLx5XCRmahTZmVdL9Nx+j4xkqpzSJFfVTdEsYjSh8Q75XEcvbo8ZAIzXT7JV5A5xzh+jZdU7fvorou35H3bJLtLtesEgZEpTNfjp56KqlnIW/MMB4+dUrdfviS8ThmcR9K2qTGcEwhuV5beK8iFUrSrNJGMvaJZ+G0YgBV4iVCK8Bqz3bVLsl3WodYStpu06NEPIrHB1rDFLwtyzWrmTsEbVFTKpgcyEpWQRMW7liyTgjENcSkSS5vK9/ZXKMZ+PbEuyrYe3VaAxpBAc/kCtqCv5O+KoqxnSvYNhuyta1t7Ur2UnoWm7yJbjbkUhV1qfevKp6tixzkeQuCBcKWtETdl7ELPFkRZ1I6KupUFAxCSsuNswxu4BGPWRbLq5WC65UtT5Ty3PNXCg9jh3imLALISTgukRfh/HyM5r7pmEkI3ozWfFzeLum2g15ADjpffEVFDtcvg4JaMy6g85zfTH1/vIWveFXRbU69lrKIOhgll4W7QQ84z+J4wWdIqlUs3hr0gEnG4yvZI18OTiuCS+De1bUM5YMSTke4t8sUbC+Hmi45cyMemrVwg5Ih1DLGZcHXqRSXqjfJA1XkMDsl8lPfB58FIq0wPyTsjkWr0MGWGmrZYHmNry1bFqiHrGU7v8FtNT2WN3SKkM1KLG76sRKNW6BFhWd2StQ7BQZlAbeUcvcC8zuGtVNkDPZz6GUJ0+PYi/GexfJ6jmxpoaoS1TXPHWIQNGGvYi/lZHFhNiRdl5EPqmmdSBVGlKeUX/Pxnqna2LhvqwTct2EMVK9kNzmhWqdemQQO/R32mZAWQ3RSLZpG8p0xUJJ5sMLbWMOuaqg89wzUCaBLqgqToBpp/6MGoqvd7zHa0ZrIOyGueM7s0oF0xksPUN3EMTAWgOVgYR0lG1XFsoekFCgtcV7VkYeza6s6Ik3lWof9ODmXBYKw83gIqjxCVimoXo+P8T9eqqWfBkSx/WzB2aNkE3NSCDlw1i5RV1WDbJb0K88CSc3q1hiFTCx1A9fL4cs+wzjaXga9t4t84qBWSZbFOaBukC1dGC/tn5ds4TNjlv/lcwu9bJD7tHQ6zl0jL32gDlhsSVcW+VkGtYgZIb20oMqEpZX2j022tJi+otF7mAR/sSFW8gR7KSeLlqtwQYqUNTsMXN05LtQt1K3jXLVqp0Q3nDPomqbEq3UDN5mslXW7ZRXSk+HwJLXp6rqVzqQk5Rn649O04a9YXbO8YcKU5RRB2TYy0k6mgOeMkIcnnQC57wnPhbOg6Tz0yyVpTUlpAkD2eMapZlLt1OmyiqK+HQvjIZ8B0NkUVtizqhWgCGpVt+HexsKeT3ibMHMT8fh0mLJ6DxZr4witwzmpaVr3g6ZzKGMif8dkyl5V06BcVC2mLJXnoIVn8QKnTjUR7PkEO+82zE4F/kG7TIMmMwykxuZ4BjX1RDh1wpRVKBRnK+jjGXbeFej/YiNJdfZoAj0t4CbTkO4uxn3svVlAn0bpxB4AfTrl1CkQsm+qKtF7qJA9OsewlmfVQdVXD/i9nJPFFZiyLluGhCWAcCSUBb84UpDSBqYsdsuLUNdB8zlQliA1a+8qoKnE22mBpqazFlAqbP8g7osZA8CwinR/WC4ZFCagLyCSwJRluwp0NgP5tzL1/PJHyG6yjI/z1wFhvR4NIoZArMgDWAoAmutDZKfn7K4nIDDy10IbyCxTEJlctxsPQIK5KLxn4UFhTq3iPssl3LIKPA5uZwia61gd6m152MfgPAGlAUCmYYcldFXz0uH4JHzlRgPYnT7ogfeuej1ur6p5OZZAqF2Zw+wPkc2X4VgoAs7Ocf56ht7RKNwLl2toAPNXfLEZgGbAbcwP+S+rogODRwpD64Kk4PCb/bauhzezP0QzLpi4xverOhji9AvA/rdGcQxuDdADQnpUgpnVNWb2GtYGy0MRGQLsUxSSbQOcW9va1q5kL6dn8VHYBrzAxbu6gDgEcDEWYVMbF52/u/2yfjwp99767/r/n8j43C1m27j9Kfr5JOuOmyzvXIrNSMYsxUY4t6Hwb0N/0v02fbcJV+Icxx0SXAdZ105tOxfwE8rEdsk4OO3CMXJO+Sz4DzJ8HFn+XokzdsF9JedjFkm/yDpQQy0MhTLc98BgJuzsBuAYRew3JcVuV7GXcrJoUeVdttxILV0SdHEWSnvEYgxBr2U4FPG6fgPSc80kX95CXkaK+lamIw1WJvuSxxuQauMXAlIzbVdUyzKNNbORj3QN1xBUs/xFJtH40D/F6EWplbCl9hgH3e63v+aNz5+MR3LeNUSlbEst3UdkBwRBqm0r22T6au14l2vYMoPOGH/QmijzjOtGUqUz7XEa6dhYwGmuMdHdfhqDekShBoMUf9Z5hqbnx6vQAbnZ9AVnATQDQj7j/evhBixOYrbQMKXHf/h7ZXoa9a4NbfP5FfKCrxkA4zt8u8rIeMgEQk9F2PtC8FkQ0SMAMwBHl+37CbMDbK/5+8Fe5Gt+3Tl34yo7vhCTBQAQ0e845776ve7Hx2nba/7+sE/KNW8DnFvb2tauZNvJYmtb29qV7EWaLH71e92B74Ftr/n7wz4R1/zCxCy2trWtvdj2InkWW9va1l5g204WW9va1q5k28lia1vb2pVsO1lsbWtbu5JtJ4utbW1rV7L/D1Uapf9IZqnlAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6518>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.7711296081543 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1e-05, 'kernel_type': 'branching'} is: \n",
+      "[[5.12271437e+02 6.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [6.40000000e+01 2.20061692e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12271437e+02 ... 5.12271437e+02\n",
+      "  5.12271437e+02 5.12271437e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 5.12271437e+02 ... 4.53138195e+05\n",
+      "  4.36955701e+05 4.85017170e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12271437e+02 ... 4.36955701e+05\n",
+      "  4.23212532e+05 4.68825926e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 5.12271437e+02 ... 4.85017170e+05\n",
+      "  4.68825926e+05 5.34467888e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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0V/r/eBu0ekkjMS59I7R6+lgPl0OgVRN7P6jjA9GMm5ahDM+h0/26aekn9MGV79HOojJOE9pCTk2eGx/P0Brm4wL6afX6+j0v07av/0z+gL+KV/x8pwncXTNES3jp5CHdAVWX5wGEH6P6pp16sa8dEXsDKcWdfvQY2EYzwpRujG2b+APk2sHck6sS9mbjHvTKCz+o5tv0ZlwwTQQc1EciA/TnopxD2Kudt0EEoJWNKZh71npQlF9fUcH9fSWikGOhwVPuwDkgPvW7WSxinoY4SZumw0WqzdzgwC4K5+A+dM5QDcqzal68tZ1Ng8oKZj5LnLb5sxJEAGlvNWFv34468BKEL9guL0me2hyQfnKwjc6+Hg3g4vbV16rnus6eI04/9dB12vLtMd9gnkTu+JVxkoE8WWQIXLvNgcJl4vDcRkfkkNP4knDlsHHrtbEK38AUHMeJI1AcwgDgo03BeZs5Mi81LhW9Ecdzx4EtfQbnrnMYs3UvcNiw/IvPQ/NNG3R9N12MTqdOyTWg0t/8zeK2ZBcymsvyVux0nU03lswM2bnvq5on53FMyIbaRLU+edH8+PtJY3S758zpPM6JDMAFINmIpXRfZzNVZggjak6BZ/W8/ncYF2+36e/s++rj78nh9jKu86IS8sHKvjDcNP0bnXxQBsYwsnuPMsooNyqjZgH0+y906b08TLtvm52/de34hMYNfViFHZ1YV/VZnEd1Jz8WMjYV0rUcfDK9OAvNpUBqTnv4LMLYhkoWFpSYFyJRnUcyXgmxRhBaO7x+5/ksptO0krnyR/jO0j4B51+xHPwseSKhM4/0wvT5LMpYOlE9T71miD/+dvss9pGLXo6hlz33X/T9nJ93EQfn0FiIUj9I6CoFTV3o4N7Ff9LnLR8yt/Tfescex8yIWbaJyn/e2PvWNYfBB5h0T9/JuHQuh34ZPEZDcln6htFk5oKOnCno9CBjd1J/1Hj+TZtM2hX0sQCrjTQO0v0vqFwBq/kN60IOTo0etuyu19EmSnEqeeaqoHr7pnORvF2bxUWyb4r6kGg8PksaeXa+tKf7VCnkIX3c9xXg2AIzl7T3HHTmf+59mDXoC0jg4jo1Pr/G/UGlhGcwcmk3wL0nFax8ALP+BtetR7PQbYYHuChStGdRxJfPxEhCcCKqB5/m85jkpqco0QkycX39XKkwIa09gLn8F5843chCOzIHH2EoHh6Cz3zSmIKKhxR1Be0PKer+etQNeLsFHSwAAO2L497dVlLUNTuWmc9g7h2hff5CzcnB5SPc24R1JSLnd6iqeP7Z7p6It3+zGOSkUC87RJ1NkZmD7WkEp0dHcvaShIdcbd0aYcmt4rZQIVOu47lsETeifHMiE6MK8qIbig+jHJfzNHJU5s8KwSmHEwRoNm7FZ0EhfyHDVAxkxMb1iBsMVWX/BgKESIKcozc8CWkTcUQqAqBJ5cK1WozxG5D1L7s6vzDuxRETQkKu5EKcehZEDkUpcPqwzm3rNinJcbHW56PUwEQwMxzXSVCdflxsnHOU5oLgPE0yk4NUVcxBko20KsGHC9CryKVBs6lDj/pNImwafrMBc8xPYQaWI4JzlFFGuWZ58xGcb6q8jXVDzpvLbdUN6avPkbd/mbohfWO8trohRa/f4Nwq6uq83mznXPpAfsBw3ZC+tPWeuiFfa/4BXtm3GcG5i2Rx7OQY0KWTK8vUu38eQlLT4zW180hvNsmDO5ii7lGIdlsnbRivntr1Oo6naeKLqcdrCqcGZ+AnKorEDOHtNtqw0q8nUemkrrctAAsznYbUbO1P0Gn4ZrFwxC6ZGcKtHWQIp2oS29PmhEQijE/e8qqyPpfrxo81NUNCNMGLOTwIvoN40Kv7603inwDg1ryqYP01QrPnVHXF2u0T1qgoUv8GOSRt8eQd2ONX8VxjgLoGCSpzsx02QzZb8HoNc/8eAKD9+JNeeHxxeODO96AywJscTx6D//zj5BivN71mCM1m4FcnYQxgC3qx+xYwaha3LTepWeh2pK0+B+l5/d62ZrELOva8MV+3ZnFeW33Vvmwbyyhk592IZpH1v5dmkYVT2TL+wP7ezprF6LO4DrksC9Z1y5syjuuWN3leb/LYculhDdtH7p4Z8rqLDO3ax2Cx3B3hxBfJRWAmOab/P6edC4sM6eM3Xb4wP0fwGH04kCGMzGX6z+H2uXR4TL1WkWsDQyUQB5p1xy8Yu48y5UWGBssX9qwF+3aSP+1x+0bNYpRRRtlJ7p5mkdfz2CMSoXf6RMuAc0jqFGLebLrAKulLg6vqrXNmago1AGY2y7IRvQPSp0jzapU4O40H5djTU3euh/GKp11zZcrXJefKpGrisAayVKt1vL4HTgy2HTCYOToKWIXAQen5J+U4HR6AT8/c3xTAB3WdwJ7jwnvHqV8bXf8jOBEVCxY3TUwh945GbhqY2SyuTdN0mLLMg/uwHnOQcFCScf0oByFbdk7DSQX78jiMIbBwUUoDQEUBmk4DY3e4d8slih/4PuCT53G+hQFvtsFpyatVYMYiD9SCMeDCgNZb9/fHD9253/rzLgeq3JeyTJjEi/fehf2OJzB/9mHEXgQHp8zfr+ukcmC39Rrk15GZQc/U/btA7t5mAQyrofs0oeHVRHHT2AUsn6lyfbDgsFHkMGB/I1mo3qS9jM49RDrydG/52ap8AIFZty2gm5FxMqsHUEGm86xR+M0kj7KwJ2KRMazWAeIsBk7gURhwriUbp2xCrU3p/f3/SRRpG3kv5eVNOBt0tufJqYsAEUUOSiBycA7MNcwTbZo/kdy71m1OnfR7Bl686kROuGnAfuPnbR3NmwAAE3Ceu/f08lXsR+WSAN4xuVoFdGv4++kZik8q2PUmrkPbunllHJzYFGB2ZQOEGlDPZxe5m5vFTUhOHBuOD+WSpMS43ea49zjYuryAjPQXQ+cP9dGHlOzYo2qcneu5/7h6eeSlybkZHAGtZ5lqY/udNGu1caQkvNEzn88vQLvlcIeXItvQ9aYtLz+ZzMfCYd2TTbe1SRpKWhowDXuDjGPiDghY1f5mk9Z9YZ+z0UPC2xd54aYBCYdn34dHPiyyucrHoWnAZ8vUNxI2xqgVSrss45IPk2XsEw19u3wWeWLSVdvS/1+36K+vrjORnNLNsrxV7/t5NTUE8i7/KK150VuT47w6GpcdV14fxOdcEMV/ed9J/+b6X4EkL2OofTke/o/rGMYr7Z23Xn1z1e1do7xdm8Uoo4xyY3I3zZAhB+c+/gvNqYCIKgxqc92imyrtJS8y5G3UpHmVOKWPBYRlVmSIJpXzITQxqSmUI9CgnaZxfBLUzQ7tFhlCF6l5QZGhpBiQ0PqbNMvVzGfg9cYl0an+dJJTLhpxKhmQBOxeZIjbsHZUlkGt1lmvdHAAeAdkgmBkds5Z5VAlQ6BJ5ZLigtO3urDIEDpFhizo0QOY51lx4s0GdHTozpUiQ1YlcZWeY7VpwCsDevjAnbveuOdGZ72SAc2mvshQvIdmsfBFhtSDVpaARozKc16WoN4iQ7eUdUpE3wBwAmc5Nsz8JSJ6BODvAvgigG8A+ClmfjHUxrXJEGnKQLQkviQxk1ITlgwi6Xx6eMwebdOK6YJbmE3dg6Xh3lUZvOG6crrLXPRecqlIVpawdeNeEKvIXz0RLJVlcGaGbM6yDKnOAEDtqXv4LYcoSQKjbru4EFrMgY1vuFbZmLNpcM7R0VGw98PDD7jr+hxmZJLK6zSZ+CzOEsRnYTyAjxas1jEacrAA8Rl4G2uU0GwG1FuXSapJfB/dB+UEO4ZgyhJ8dgaUZcgOBVvQYuHmpSIcNJuC6sbX/tD1RArQwQLW1/kIL9y2Rv3+Q1Tis7DWvbCGgEeuyhidLF17AOyRyy7lqgAXBmZZwxyXqD/nNovy2YsuD6shR+g7nbixycfhwT2cffEBDl6dhXHyYgZzuozPizynixlQNzCnS/Che0bIMrDcfQu4DjPkLzPzDzPzl/zvPw/gq8z8/QC+6n9/O+Q8G75PhmzGHf0ON1Gv8tKS28PhePQXdArzoH8OfeftPx4z3M4u90m9iDci4j/T//LjyToi0WRJ/n7R+Ib+nPd3DXKl3BCvWXyJmT9Vx/4YwI8x84dE9D6Af8TM//p57VwpN6Qvv2CXOQ3VOg38Dm1UvXOTR5PfSJJXzmfhE9N0RIAMpbwSFLUT47/8IVFJcB9AJ2oQMiJzMl+F/wAQCXbyRDQ9lzyhbjrtagdC1KLn5k2OYFZ5L3yineVmlP7qe1q5xCyS+6DCg1RWAVkqtTXEVIBVPBFAmkSlSgFIiDgxLdgGWjrBToRx9IROk3mr8XK9Rfm59wK+A4Azd7bbSH5TN6ECW9AmyzJEtHhbh1IA9sVLN0Ypa+D7osIEMyqYg4eHMI8ewOo6q4IPychvXGU3H6aVMViLry3/Ho7bT3faTa7qs2AAv0eO3/x/YeZfAvAeM3/o//4RgPeu2EdXhqDNe2x8OemLlBtM1P3hi1WSUNtPflOWzh7V4VFVU0OyIH0j8QZuok3MjWw02jxymwxVpMJ1ymehQFlhw2MbXmreajXdJvMAkICv5KGNxC/+nMUCODsDCsT+JLzHGcVcyIiNnJJhgykpnqtAWWjii+J8OY7yPvdZgDkBZdHBQcxE1dqFIWC9cWuhygzSZAKI2ePPuwiUxRkoi5sa/PAeSJPuCBDq6Mj97gF4zBzN0NJlrVLdAGcr8AN/7qsT9XFSG+F87swoTX6zmKN9ch9GZdrSdAosV7GWqmzCU0dYxIVJQFnY3F5h5B9l5g+I6F0A/5CI/kj/kZmZqL9IBBF9BcBXAGCGRd8po4wyyhsk15aiTkR/C8ApgP8Cd8EMye04bSrgAjMk76tPq+lls1btZ6nCzpGpeBzk65iDnbSK3KddJQV4Bjg8+9ZBHLNiPmXjTeahgD5JYWIP6Oo1QzQLty7us0sauE6i0seUOQMgkrsUygzR6FUtHtpPZRkL/CjTMJyjxiGRpWQtbIviwX3Ys1VYG+HgCNqcmEAqehOc4sJ94Wn1rBQ5zsyQAJBTyX40ncIcHYKXkeMizEOGrcwRbttOFbmv1b+LV/bZzZohRHQAwDDzif/5xwH8NwB+G8BPA/gF//9vXbaPczpPVbWcwl2fMxQNEXOgllyOqbNvfa4Dn566timiIAPFuyd6BZyPwUynkVTF92UOFilEGk6lDmro6VkYg91sUDx8AG4t2mcux8AsFrCbDaiYAJ7EJvQ3mzo1eSvmQiTS1dEQ+8pFQ+y2Dvaz9Sq3zCX4SjzpjnlwP0Q9xPalonCEKRIxuX8EPj5x5pN/yNlaYLOBPVt1eDnJWFfiT6Ihs2l40e1pNxrCq7Wyyw9gT8+cD2Dh5zafeURjC1ST+FI/eQR6fhyIZYIwg9drp8afnIY1Mw/uA0cHgCePISI3Nh8N4b5oiOSe+GhI++IY9Q99LyZ/+jT2V5Xg0yXw7iM3h9MluCphLMPe88S8k8JtLJsWxctTbL/LnVt9/ZvR79JG/5K5dwRMJ7CfPAubW/H593HyQ+/i6J9+FJ47nk1dNKQUNnDvW5lPQdsalEVD6IOsxuo5chUz5D0Av+l3rhLA32bm3yWiPwTwG0T0MwC+CeCnrtDHrQozO8LVcCDLvTivatRgo5qSbeB6y4njTcYCywCp38P5aQLVdUsOT2ZmF5JMqo9ZX35P8gxivkY+l45YBowFcIU5aEi6jNePgWFBWgM0Jv4tc95S08Y5XHJNyXJ6b5k74wrniFbAzuFH1vocjZjbIXBx2IH1U2IaD7nPsUayPpQdv4K8+UxZQ1XUexiaxFt+Li9D3/XJ8eiVz2nYQmRhF9knXKX4HYOj04/BedKzitrApTk9Lh5Lj3k2YE51igz5Mefqd28mKrD/HAZMx85p2sHJNpoXbGG8JgRrw4Yck9kuz5OSqP5ivg6ZNDJ2iWy1baBVDKIzcrMSBrENSqJmrpssES43SzPZp4r6CPceZZRRdpK7C/cOPw/4LC5qIuNHDDazIN6aBjBl8mUNtTxyuLeOv0v7GjYtouDYvK2TvsxiEVKI9fWhRoYi1nXOUFVkaBDuXe8N9zaLhUqPV6FTT6QLeL/CegNSTkfWqrO/F+RNAPJQ6YSwl5wDb2eeN1lWAAAgAElEQVS4t1Vf36oK+IkkdLqYg5feZ6K/qG0bnYmi2hvj2tN8Fra4EO7NHbj3BsV3fQGsCv2gLMGrNYyHe/Nm60KZzCFsGXwKrXUkw597x/3+4VOHjiUCyzNJBJodebj3KtzD4tFD4HNPgI8/jZq0KRy6NXdGSyi/A/e+vdDp6xftV9gDjZd7tXsrdemMRS22TbTKXvo05YEnFT2wioo9FJMhb+5okJN4revae9JVlMRyr1raqarNsYr2rtRvdrVOozRMjnmtiZBzPj2LL5PNfCyGYCq1gfgIjebrYH+erj4explRHtpNtMfDWNVLTGJOANGhLMWDAGduqNwMo+D2vNm4eYmvpd6GIkTs1y92lI1XihUxO6ejdob6qEz7QuWLAO6eikNXsa5z08A8febHlaWWyzqIw12ZEvbVKUzb+lqn4i9qYzQlYz8PNVEV1qS/RGO/3P3NQsseE9c2bW/atHbo5VwXuyA4VeKVDhkmm4H2VRQTgGzYZKgqIzhKE7y0Lag0aWj2OhGcPoTrxhs3s4CaBGKeh6GIELQWLNNRURqXyGUjcQsQtRVBZ6r7cR6CM55jkjWR8GCC4FTOwZj3o8oP+sgXFSbSUMr6SZhS+yE8YCtoQiqHyBwsYPWzVxQgayMrmiA4gQhiM4VDavuXl3ykh7fHPgRt4yZmfNmConDRLFmb2RR0/x5YITjNpErJdjSCs2ySshAAQMtbSiR7baJxA1qCBrDDppGoBoo0huKLzeLV7utfp5T2OI461PDwm4bVX3J1nXx5NUbBx+bDtb6twZqitgUn81Lj7JDNcu/xXkwC2oCZAJBQ0+moRKxMrrvhzrwJLRiZFiGaToYf0c5qbXYF7IYe+5mNTj3Z/L0DkwzBWnZhZ5G6duUiZc2S9Us1HGZKiWfUOtuXx6mG5u8R9USFtBkTzJ2mAUvdEUGCGuVYtga22XY0C16tYD+1CaqTs/7CuQrXou8x7xBxEXnzN4shD3Uv41Cd/u080ZqF+l2DsrrUbXLujpqFeKaVTyFJS9cbg4cDB59FWQXTIwnZWn8ublCzUBpRUrBYNA7/9aIi2u6AUUxOWU6L5/rMTT8qzX65Idqv1KOuC95FfCVu3OrFLJCYQ1SWzlyRF/2SmgXdvwd4/EZY24bOzw0pjNcs2EHRFx6U5c1RbWqBbb9mMZ3CPHoIqwsjC11CBsaTdb2KZjFGQ0YZZZSd5M3HWewj+8C9L2oD6Kh9+yarnTuuPui49Bl+pBivzyuA3dZ9GxrneZfklbiGwFmXncMu4+iDvfeNTY/vsuPR/iPpe8h81U5zhYfoROdyaHmfhp3D+/Vc+qRnfvvgLN58M6RPhpiy9pGhFPUQSvRhR+7zjeyRoq6PFeekqHu4eVBzvaORShPMFDn3xlPU85c8T1H3manc2jRFXcKnYi5AzBmTpqir3IQrpagjOjcB5eAsipT7UqEh43Uu8kSTKkDOk1T6PcyQ8t13khR1Kl1JwY6Dsy9FHXBlA+65rFP77HnwZajOnWM0M0MkRZ1fHMd5FWbYwVl/Vh2cF/18QW5I5xqfCq6P91YVk1wJedF9+ndI/Zb2igIJXT8AUBVzPOoGVPkb2nhsQlEA1oe1bOHCnX4jYvEaeoehmVSRGl+jJ7UDb2V9fREovowsz0UeepWsFUOUvp2sMDJNKliJhshDWRSR/bpv3aoSXMs4/XLMpoBE8QRnMZmA/Eakz+GmjhtWVYE0dkKWdz6PzjuFp6DpNFDps+KuoEmVfJnNpAqp+PLCB/H0AuFsCc2yBR8uQMIuJtpCUbiUecCljEvdkEW3bghaC577jcUnvqVPbOv4LiaVC5WGtZnBPjwCHb8CgcKxcD+AqFFNpyDA4VDkGbnlFPU3V3KsfOfvqboWPMW7BFLaFgnmPsMGAIgx7SzsGep6aK80c6R70+fqcebRG12HQ9PoqwIzgcLfn9/XfrduSN3tO8ur4NVavZTZ/AbWmxUdXOKNF6CW1+ACVkLO3W7jeKR/RVeox+8Sznqg5UXtCxdl92NbR8BWOBgjPAkoy9/nBOshm9eL46S6uVwbktYU3ypqBds3jpOEt1vQC5XJ2xfN2GyA7TYZEy+XMB8/R6s5OoTgJtMseOOSEXm1iuvIvBfEfXRwjjLKKDvJ26tZXCT5FzBoATvGnXvYoPrbS48FzSXrq4Oky/0ReSboRUWMpD+rMB66nWCe9WtYvePWmoHWZvIx90myHv68JMzqbevg5+Dk9zA2QGl1WaKU1kI641faYD5XhWUJ/efr0MJhFTRgrXXX8Grd1dwsxyTEtlVV2ASYJj4vr/V57WBIO5OEwuS529YOKq7mHAotyQFZHw3h1+bVHpnUn63N4rLO0H37eFNECFtsRKiyRX/0he3rGftAMZ3XRlYs0QkiV9kM6G5K6tyAcr1N2Zc4Wi4j2qdoekfe3s2iz8GpN4o8CpAT9l7EwZkzamUFm6madL5OOtHLbpFEXiIJjRpP08RIix6vj3qcW5cEcF8QcdzqKIyfAzQHZ+O+sGZaBbtYs3ZpB6eZz2CXHiaviG64tYP0ABqUFcBVVdlBroZoiGK/Qt2Am1jEWZLr8twHc3jgvrRahAjHc56KgxeIDk25hqoy8ntWFQgCt6cIqBMEZuXqfvBm44BRgsC01jlV6zpwcPJ6HdfJJ8MJQQ9vtsB6HYsof9yk6F8Z63zmoiHKQWvmM+DJY5An7wGQQt6hokUT51wn5rR8Q/22Ozj7Qqf7EvbqKADgHxKbZp3mmAYVqw+cDauVe3izG0yTCtimarqu60HtaVLLIzBcecYq4UgIhLsZQXCoS+IOumtUXZLQrg8F5sxgoW6IzMOPnw4Wsd1GzVcR29K9I5CwaOnoy1qYp7tfW1mP8DPg2syIZ2g+c/VHpGL7fAbYJbg1yXXkHbE6VIzHD7vM+ESgqoINY4j3iQ4WoNksQrAnE/ciNY1j4FL3n8oStJiHmblIimMra77jEcrgFGa3CazXwDuuFoh5dRbrhnimLFsU4MqgON3AHJ+ifd8xZdGLl73mHB0dhmhIYIB/+ADL732ExYmqG3K48ExZQkHoP2qLGRiAIQpMWWAGTt72zWIUJyGbNTuemBlddf6NqkeiRWMj8irgtymZmn8tdU6uUS49nive9zEaMsooo+wkbxfcu0+G0J65iWEicg/AcPzZozc7PotQfCaD82Z+Eu2n0H0FSkCJw4uvoo+d2wPDEpyFjClj2w4ZkLpfNT6dzAakvgWN4Exqnc6msCF7UiFGh7Jh9fpK30Ba/zQna5G5eZbrJKltAE5N83nCKxGOS2p6Rk9H1SShThQiZmZOyi2GYkZG8XIUReD0MPcOO74Sbm1MJFM4i+BTElSs4Cy8GWqPX/VGdMx8HsyeAGArS5h7R2h1Ipkfd46zcCUoZ+CzswTB+X+c/haOm9spMvTmykU+jODpjk68TtRg4LqE4xFZrVM5LTgglYPTUPSJtCbxm4TjdTzXRS6ECUyNVxCCGk7txxRYqOBDgUWE+wIAN3EObBWjFLHfPLTDMhu38u+Q2XYcnDKXXgencsjG7FG14eWMXBR9GQy4uapNps/BSZMqpniLiIPT+6MCaY2sSRX9GPI7ta1rS/wpeoPWTtqiAMHR+AcwmDg4UQdnpsuYHXBwGkeoIyzpeHWKPooFKsvICaI2Hj5cgDTUXMbd5+BczFwRK833efa2w713kYs0ppzHwce3e3NBkhM95kDF7LmJTEXhRe2JCrD/Qkr/gROBuUNq2yGR1eO1bcrDAMEptNkxQSKq4x5bIS9uHlFxFctz7AUSXIcNVP0tuFUP28BGka9HnHesiRIYuXIOCA1p57T0QR7StKdnvXwckpTFrUnGZ7e1c9T6teWGPMrThZEjUY4fNxS6VeX22OcvUmi4Hy+9ehXOlTAsec2HM5yFkOcMRZPsah20LHlC7baGsZ9GYl/4Z1HjLmR9NhuY1roUfk0A9JllytJykWaRh069+n1hFXXErwrgVMxezWIyScBL0od49O1qrUoKxrqY9uwsnKtzQ/LQaZ4bIiaIZgeXcGESDdFZjYrGTx52M58pSLOfkw/5htCpr+XhxhkfIW6ahHqudz0QVXGaTGIo0qv5gYNTvuBiDtgmVlH3/KR5NMTcv5fWHAVimz43JA890mQCe3IS2g1RKJ234iMcNIlhVlSVYy5frUHf8R7omWerkiS07dbVJQFcEaBzckP4bAk8dpET+taf92545t5hrHviNR7z4D74809gvvFBXOfZzEVienJDUJUwhmL+iLXAJ7dbRX2UUUb5DMjb7+DcVS4q85efKzKE8Rg6ph2ouq+hFPJdx5C3D6Smx1D7Q47eTn/aZ9Hlzgz9DY25z7mcOyr7xq4dxTmBcmaGCFFud+g9vCB+rmSUuSG/Z+UWk3Z0CUY4k8jM5/1mSA/favBdZGZIqE63WvVrZmUZnNX6PjiAnHKuaq5TvVbeJ8SKeBkAvrb5+zuXLxw1i+uQS8Jvr3cMKVQ6iRx0ivNQ/J/MGzL+lNZQxvU6Yd96HXvHcZvrpvu67D1T1AqXkbfXZ3GRdNCZDv6cR0mGr4/nhchF5+/Zl5bSCEjShkJohuulHspQ6LRVWkLWvvvdfyFb9SXk9KueR38SGHkndOp/rco0KiCnt+esm6yHWrukTcX1SVCO4MD9GcO8USNJ0Yc0mfQmRoWvOZm4vr5/KiLJTfD7EPvjcpmCtosWEkKnJkWiirQ21Dm5KHQKICBvaSAZLhR73iinsNS2VQ7Oc0OnCsoezq9334w/u5vFdWadDmQ63mjWac7BAEBHOUJ/fVmnQs8v2av6klvMOk3aVFmnOvKieUFuK+s0iSJ5IWPBjXpR4SMcbG8n67S1jiRH84fsm3UqfBya02PMOlUyZPtfNpGsD5SlbXhJJBNw040mkslDIl++NJGMfSJZkgOyjQCuhEbQr4OZ3G4iWVLD1fiErSyRTAhwbiWRrPA1PxQoyzGD+wiYsK/L7yt7+4lkUq3tYL5fIlnlKAR1Ihk1u+eGvAHG6iijjHIX5O5FQ3rIcQcl80tQNYkq6WXnPVTcKNTdyGDbNyW7JhPl9VEG5k3TqVP5b6o6e2+nuePVdE2LXSD41zke8eVo2LseS8bzaubzNBpxk2MDUqzO2dl5V3SbmE6DtinyB+3vvcXs3vs8MDmCcp8iRDu26QfV7eOmZddQ7Xl+BN1cBiC7FemsZYbeDOfc0rhUX/2+mx5fwvaGPwpZ/87Mu+R65Dk/e8rd2ywAdGL2fViHC8hvggbgX24znyeIQLtcRsxBzmfhE44AwG42oRKW7sMcHQVnU+hzMomVp05OI6pytQpov/bZc3f9YhFQnlw30eew2Tim5rJMaooCgJlWkRcDgH116uz0bR0RosJJ4X0e0VfijhfvPHZ2NBDzLDyfhRw3jx7A+vqa2v7lzTYhrtXOM3OwiChRyU2YVLCe1FZ8OWJz52hR3m5hvA+AZjMXlVB5EgCAdx8Dz3xSlcYXlCX47AwoS9jjExkczMOHoNkU7dNP4v2ZVKFdTf5LhQEdHASEqHzd2xfH4H//30L1zU/8oltfRX3lxgOATpaRz+LI3X+uCnBpYE63MMenqL/TnVt+/U/js6TyZop3Hrv1+vR5WOPye7+Is7/wBAf/NCI4+WAOOjmLfBaSEzSfAk0LOjkDH3nWcWbQt1SeyAVyNzeLXWRfdm//Zb1Q5+iJRHDGGg3AvWg6FwRwD6G8iG0bCx9bBrY1EpOw9bVF5Xrdp+W0YnqITNhIXAMkfw8OWx3FYJsyWMO98GFcQjmfHxcPvM2o+PLs0Hw9JMoQxsKRG1LOWyPJb+D1JrKny+ZFqu4oc4Q/ny5hNz5sqKuHb2t3f7O5YrNx/cq4tlvXFjNATerkLgqAVioTNWpB5bMzB7GWtsrW1QJ55euRrNfA1m1qRuqXlC7hj7Y1eLVC+WIZ10Yct4Fd3TjI+LZ2zl4Z79kSs4+XsW/AFaheb4Aiq8fStK5Uw3odcktcnZfdtYzRwTnKKKPsJHdTs+jTFvb0Q3Tiyz4DkmiHdjjFM/TF9lli4tpBp7QJOSf83KnrIZXCBYegcRbWZTF3skPbQIXXGecAjqMzdlXgR2shhKj5kK4tosbdi3EI47DdPpXmFdLts+NQ9VHCuJoGUgGNFBiK12uf4UkAq++gbaJ2wumak/6Ct4iahs/wjFPwJm2uCQGgs1Xg9wAA8vdZvvi82Tqz1UZcC5USsrbAtgadruLvMga9ftuta1f7UjYbmOOl48SQ59/64tpZ6JStx1nkdVXeqirqfTKEnbhiHdBEfSYK6McrSQ7T1SJQYiblY1G2tkqX7yAwb0t07oWGlBO5B7RvzTXXh/BmGEpoGsL1+0ifeWP6lWM91qSXnM38OiDbRBklYPp7RFPufu8c90aKeB3umwL9h/Qd1vca4fJ3c7Pokz15CSOoKhxwD9Aui0spSU4v3Nu/7IlGoJmsWht3fXiHo/ryBdr2nrKKASqcVSQjATXJqQK+atHP7t0D93ZwayRrE6DG8nJPKqBpHHgpwNfZXdcXRZD5KJi3HMuZsiI4zsZz29a/2xESDiKQTx2Xr6MDUtWpz0LWAHAvsEo0o6JwjkC9QRcFQA5YlWgPRJ6YORIeA+7e8WwSU/XZOTjRWpcW7tdGnOWB4Fh8FrXzPUn5wmSdsyQ5lKUrNyj3vZqAD2agF2W4hqrooCU38HCcmxZk2ZERi+yxmbw9mwVwcTREi/r6gUxABeqHP5zH+oG2IacAAKRocXQmCm7fY/TVix5YuSX7TzD6TQNMpyC2wKk/uXC1Q0PugrzsTRM8/LHMnm+/TNm9qfbXW46FlXN2bznexBwFiXoIFX4eDaGDRWTJFkQi2+CAi0lhatOoKoC3YZzuWPflc+Nfh/Wk+cz9rHIakmhIpdbh3iGoruNmCkT2LR8NiQ5K49Z8MQM8SQ2Vpbs/st7atKhK0HwOkvWTl369QfPkCNVSHJzWbaYA+P6hXwfjxskc2L1DNGS5hQFQv+POLZ8qqkHNAjafA7MpaLUOf6fDBZbfcYCDT2fhueODuZtzXzSkbkCnJrB7k2Xg1WeJ3Tt5mZVKvGs0hOJLD8sxNymoqCqV3LeXM0/leHsAifc/XNq2CRV98lWVhz+oye6rycxpVCQwcfVEQ1SOQeiPna9gMBqS+0p01IN9NW/mGE4FwMuYx0CCe2ljzdC4kcr0UkamUNBYIh3QPpl1mnsiL4eKnGCzcZu5tcna0OnS2eRVCRipOm+BjasRSmiURtC6uqNbXXW+AVYcINuJDyYwWfn1WkWtrnyxdNEKwGuULrpFeTTEcoyGVKV7Wdn5GMqXqzhegagraDmvVs4Pon04p0vMnq6cX0c+UidnMRqiqAmoblxUaLMJERDxD+0qYzRklFFG2UnupmahtYnkmFJ7dQJWD+ozAKLWG5AhRydXRxISeOCLI0fxu3ZBYDhKOzmvPT2DWSzQepq5APs+PACybEQzn7nkIkOwnz4HLbxK+uoV6L4DHEHo6uYz8OmZM2dWq1iQqKkDeIglU7GOCV507yhO8vkLUFnCrtYwhw6IY1+pBK26CWCt1qvi5tGDmFglWpBPhQ4axeefgD74BASnCruDHObbcVySAzTBw6LJj4UmE1jPTB0o8w4PwB6E5cbz0HFcWnZt+D5p676ypNKtt198gsm3S68Veg2sMEBZwLw8AaYT8NNPXRtEoIcPYO8tQLLmk8qp+00TgVUyhaoC3z+C+fS5vz8eXPVxg+Mfeoz7cqJl2GkJczzB5nueAACqT5fgmTNDNu+469qZgS0Jk+MG06dnePmDjlbv0fNj2LNlakoYA7z3BHYxhfmzD8P9sd/9Hj78D+7h8/9bTN6rH8wd7kMSCkunD9RHU5hNg+LFGdqHfh0Z4GVcv4vkbm4W4snOj2npI7rVp2cwXbtaO3VWP+iGwDWnfdnWZYwG0tPWZwKm/fDpWQwXiqmz3sSMzqZxdrScf3ySOhzXG+cUlMxHbb7UNex2G1mhhEh3aeO4ANj1BmRcxqZwZgpiVUwUu0zXzT5/qYrotu6hbZq0ktcHnwD1NoWItzaAqSLfZxMcsXx2FtX60zOn5p+eBbJZmR9tNkm79tlzD5ZqHQoTcH1LGLWM8OfJn3JAaoZNxIcmuW2d2aOjJC9ewtQNrDe77HbrfAI9ZggRgdbriICVjbqpcf/rz4Gnz8K5ZjIBny0xlXu92QZzafGpLw8wqUDy97MlHvrIBy9Xrv+c8erjT2DKMiElLr71FO//7wR6fhye2+r41AGvBH3sza7JJx7xu9mgeKnYwDe7pyfczc0CUC/1FfMGPOcDiemq4849fAdBzguJJm0rrARTLK+n/SPSj47DCzI0pJKrZtuBqE0vK1YWTem7JheNXVBYhuCTgNdmNAKQbbgu2cRat26kHJEBdZmHG4EQCgxDPi/K5dmpg71O3n/RWjCrj4HXDkn4HADA+uhNrglJGDTv12TsVOeMK2Al8lCzSY9xWTiHqeaoUD6wiHdxdUzyexWiaU3qRO8VcuUcWJejYAa6BR8H5W5uFnmEog8McVE0RBbVw5OFRSiYIZtNCD9pXgcpkhvrcFBaj0L6qiofSowvNpWly6Ug4/tStU7nc7C1IFHVyzK+UKr+BzcIRXk70ZDCJLVHaVv7aIoZjobk9Uqmqsan1DMtChc5CCbWwm8ENuS6OOfs1oUuK9WXIcc8NVHsTNNpWBPW/BDwUYYVh7AlzaZKY8mjIS7yQCEacgDUtZtrqYstOU2UytIBm/x4aTYDHx3EuhtEWTQkNkGVi5SQjFfWebVG/eQAk1dKS5w5xi7royGmMG5jsDEaYmclmAhm26AgwuZdd+7k4yrcyyASRZtN3fMhmt/hAsvPz3H07CBu1POpN2GK4CSX49hs3fOsoyEvd3dbjg7OUUYZZSe5m5rFNadSs2Wn9nPms7Ap7dw+FGQAIsjKZnuyqOxJ26kZwn48ZAUmreHLNs22vEmRcbAKf4r5oY5pQFkSchTIu40JXwGuvu8c1NoE6HZOL2g5PSaapdxfNV5mBrU7JA9eJK2GZsc26bzwvWVnNbY+BCxt+PE72Pn5zzlZBrWIyW9yfUiwY8BcACHYQ+7mZqFlaOO4CGehMQpCsW45LX+XE8YQsFfWqX/5g8+iaZwqSK5GZsiraFtn9uQZqpbBxm9SOo+E2dnaN5V1qhycMm3ofBCJ8lgL0Db2ERyTRdpXyJL1fYlPo1WbjQxgvYkgLCDJOg0Aro13FFsbTBAAoJMluN6CGxPASH7BnHmk/Buw7NY8x1Osgd6sU4+cDcdCASKL6vkyjZz4+xlxFptQQ9UEpKVPyW9a8GqN6rnOOhUflz9XMkmbNsFZYLnC7OOVi4qJr6tpHa4jc3BSE/NVLpt1+uZvFnm9iyFhhVLcgQkrfeFtsOXzWpZot11nli49CPQS3ugygMGlor4aCSmtZdizVewX8P4KCsdygFDfHLmps6+6H6cH/riTZBNtwzVJG6tVV4Nq2yR6lKSQb7PNlUx0vIW5NElqNTZqgw7RFN9eRsLDq3VcJ4kMadCWhkRvt/3OX7/WDMRnxLix87ZONsek7ogeB5mEeTs6cRn49kchSgLA+4liZEqiSswM8vwdAlNnv55G+VL0ugNuI+WTE79ZxTBp++IlitqR9monb98ahGeobSNwzzJyUN558uZuFrsW2dEOTuW0vDADTD9kqrBMclzK5CUl//wf9diGxpnXwtB/KmIxn0hJbxVVPMFUPtxVQD24RYCCd4QZnejQhUjW7vE0oS5S3WkvupQjDM7MtgXg6PFDkV/JfpT1E6sjFLzpI/fNtbQerU3GJbkcWl33x6Lz2IbShbCqALH/gicbcdMgWb9sHGyNOjbwRZb8n9YijyrBMnTB55yWH0AChQ/XF4XfjHo+gpadM92qTVfWNzGpleaXfAx2N09GB+coo4yyk7y5msWuDhnts8iyMHe9zn0xPN5Ckp/IOBsvMRcusbeyHbiu7f4sZMJA+DIEtVfb5ufhJq4oXSeuhI0zDg/bJOabP+hMj61iA+vLQm1T82HfsYV71PaMV9jO1qndH82mbfq7zjm5pDhchBqTjEPoBNRzKceorr2D1fvKxGRRLGKxQPXA8yxmRK1Y1sTkysiP+epu3FGzCNL38Apo6Col/nquS8oLIlX7icinWDtgEJ0D/rkNyccaRI4Z6voIjIlr18c3ccm17IxFZZeGsZDq10T/SZdLxPSDry41sHRMO92zfF3kGfNQddKlJc9JI5e+4nOj1kDP+Rp4LS7ULIjolwH8xwCeMvO/6Y89AvB3AXwRwDcA/BQzvyA38v8ewE8CWAL4z5n5H19phH2OzRxxJ4cvy96daxkAwN5Bedkw7dB1ZDpfQx0xsQJ7lpvONtFukjHetGRaUaJ1SaRHVQdjy46VKtPw+rSVy9Qw7RYqtqmC5jVEWOOyStV1ISIlDlnlh9k3JN4dmPZfOe0hX5s4Roms+WMS+RDNQkiYTYx20RDhEdsQAk7a73v2ruGZ2cUM+RUA/yOAX1PHfh7AV5n5F4jo5/3v/xWAnwDw/f7fjwD4Rf//9coQ7f0+TQiyTW6Id2YGxJvOHZG+TOEcp74iGABwvQVVk06dEDOdpmEueBSgTmALqMwGxieVtSGpaRJrZNomVOPipnZ964rh4ihVNSUAl+/iKpvVsV9dAYxtbNeP3xwsUsJe7yyDkKoAoIMD8NmZn4/kYPjw6AA1vplNI3pUwoZEITckhPik8pn0NZ2CN47t23jUZOAPUQhFADD3jsAnp+nXFXBw7/UGFByFbv7mYO6QqZ6pHFXpHIwe+asjBVQUoOk01AgJleWWS9B3fx6kckNgCvB6HRjbebVyY2YOfCNcemdw3YDPVsCTh+7ab37gEuSEh8NLcf/AsZO/ehUTBx8/gv3Od2G+8WEc53Tq8vGpcz0AACAASURBVEskdByqv1WRsHfmx8AMenaNiWTM/PtE9MXs8JcB/Jj/+VcB/CO4zeLLAH6N3Vb3NSJ6QETvM/OHuE7p0xwE2r1rE33hwYs4OAPuYgcOTtkoMg7OGMKMbbDlzkvGWSitG+pVXxDJXWlbQDcjfTCnoT4AEmXIx+6SttQXUfwLOtdiuYy4FBFrI29oD9YqrY8qSX6c/Jwck7kpfEeYg+ffhHWgNfmy8tlZ5J/s4yDJ13Bbe06JzAci90xrc20bclHc5THKRC9eJaFTV0Zg68KdftxsTEhqA+AySkUzWG9gXqiPl8fXhP7JxIiOWhterlB8cgy72cbIic/GDfMPhZEdNsVxeSqt5hb4LN5TG8BHAN7zP38ewLfUed/2x0YZZZQ7LleOhjAz006U2KkQ0VcAfAUAZlhccHbn4qubIZqDkxwzEVGasOUcTAq7IJgOX4QYANi2njcy3aHJ8zC60yN3JE0mIKJQQMg34hKFLIcvj3BRwpCLfohXu3GoPCrUlxYKr6HMEKEJZI74Dd6qucAm8wCi+STXh3YVdSAdHrg0c+bAMwm2Dpm5UYAgWVu0sZgxogofrvNrE/7WRG5OmlQQBGowXyZVwDGQ4gylw8M4twzBCZ9UJwhXZnLFmmZTh+TU9+0cM4QzM4SbGvzovqPzEylLZ2L4okhQCE5JvBO+Caodd4Z97PgscHrm6AwVB2jAroiJ5rUac7BA894DFOuI/qVJBfQhOCcTF4EpTGKGYHPzhZE/JqL3/UTeB/DUH/8AwHeq877gj3WEmX+Jmb/EzF+qsHtVpGuXIS/5tTXfE+kAUu90n9dbWJtfdzRE959HOcT7ns2FtDcf/aC0a1vjoUhNiC6Y7jyuexyU3rfkHuvU+/OuNe6fjoTtJEZFQQxlYzHpM3dFuaxm8dsAfhrAL/j/f0sd/zki+nU4x+bxtfsrzpM8SnJeinrguvRfciIXi7bRD9CNrvhU56KIX+qm9qzP2bkexZfiIxDK2GG1BkrRblr/UClWL/Fv+AK9VJrYvuUkFT18hauMsLdpAlI0ODjzFHU1DzA7slmFTQg8nFUZvso0mYA9gU0QmW/b9sLfA9eEiLVurGIza8JexQMq57BVzsyyBKGJyAHREhezwHAW1pHIpaLXpw4JqeHpon3IV3k2dSn6rXV9KI0DRQFazAOEmyaVa3tboz2aonw5C/OCOKAPnBZBrXXOUyAS9pYGXBUoTjaujYW7P4Z7/FcAzGIOTCcwm03Ejs5n2DycovxG3Ax5PnVjzAl7FzPAztxzrsoX7pOivkvo9O/AOTPfIaJvA/ibcJvEbxDRzwD4JoCf8qf/DlzY9E/gQqd/Y+eR7CN9UOt8Q7goNyR7uSWXg9tMfc3bJEodcEAkgtGnbjYd56Hd1iBWjFXKYSpMVvrcsGHpjUuuXStHoTjktsrRBYSXjC3HBLM8kSxnDDs57TrxhDTGH7fPXyiGK3V9RhY0uB4qH6QDPJJkL+n79CyAnkKylhRCEvCRF/PJ805FcyICr9aeJYqS+2ZPTkGrdVzbtZ+DtUBVJXMT1rIQeq2dqQC2KL/xcajZqk0YY+XZ2ka+DqntKmHbuoZdb1D6dWhXq16HuX157KI5agPjZy9w8P9xqL8KwLF5beuOg5Nela5W6ukZSCUb9qYNDMgu0ZC/PvCnv9JzLgP42Z17H2WUUe6MvLlw76vKkBM0pJuLWi9wZvJwb6/OnYPFShPO2q6tCITEJd2QLgLE3qnqmlD1StS5bJE4VcN4JYmKZawqpq45IgQnwdRx3IZKYXoe8BgGGYMAm7xDN8CtfTEfqPmEsQ+F4mQ95Gf5X4ovi0lQVS6VHG16DnFynWMLyOzxSQXKHXYUiwNRUaSFg8rSs46ZOAYpYFSYdC1VO2FcQrU3n4F0YWRD3vnrWdfYBrMgOISNATzWAm0LiPmo10mPdTIBCuNMDNEeJ5WrE6IdxtXEhYNVkSXX78RhZapNGFdSUW4HeXs3i5uSPvg20TUg768miRMxK53H+thACUWJjrxW6S35Z1JOzhuWsF5FAZDCpmS1Q8O511gecGe5rFO2SNMW9nV83s3NItEQLnBkDjURKo8J+tGXnFOoyrDr6r4AH7pUIJoexiepGKbBW7piGNVNwosZHJMqNJeEPrNQbUB4ImoA5CuHiQQEaGvV18eVPnBfZ6XRaG5J/5EMGkZo1zNbHx44559wVoqsPTN3z6ajK6jJWBIHp1Qbm04isEh+9zwTyXVN4ypsVeoRvn+UsJu7kwlUVc5/oJy0MleazUDCJTKZOO2kLWIZQMCngZfOUSqakHCpbjZontxDGXxCXgMq1uCH99y5r4pQpcwe+dBpUYArg+J0AzIGzRN3rnn6aa92Rou5a0OvzdEhll84wuLZy3AeHy5Ap6br4JxNnSaz2aYOzhdve0WyXRycIgOEvnm5wQRx2deP/E6ItGdD50l7uSNUVQxLKp6zDTVAknMFeZghLbltXVw/zzFpWxdJ6BmbxgywZRB8hKGNpgbYMTJFp6N2dK4jQZDQ0RuKlbmk/yEHp2b2knlvtpG0Rf62VRmUgGPu8pXHYjWwdXSEqnWh45POOsKXMrCbjdtI9P3wLFwBIdo03rzxUaFAiNy643YVofBwZgsVBYpPXkXnqzcBeFvDvHjl+1kDG/eqGXGQejME6w14tUL5idtM2ixFIIx1uYpoVtngT04x//YsVkMDXERqs+maIX6T4PUm5fPeA8F5NzeLfWSQds9mv7qNYpckLXnZpJ0+73Vfanbycmb8kR3YdZ5un2xiNtYkkfFIGT/x0gORbEWPUWgENTem7lezYKmUcL3x8XaLAAXP5zwkPaxYusQjw7NJBap+DbXOrhM2qCwaQtu6s47BrLCcJJeFucqawN8D0VB1W/JxEApFAIQabD3xzmqdwul9xExKPnLdRAbyMLAYDeG6CXVIhgpLc9OkPKiAA5qdrWA1eEw21RzuDYCqyp27TaHwu8qYoj7KKKPsJHdTs7isz0L9XWdxAoCZVI7Wztt4dt0O+iwSUNZqlXrZRa2eTtOvk++DDnzdiFexlgar8oKtj6ObSQW7cVmh3NRJdiiVlaunkfssBJQlAJ2T01iNXYGyxGeR0OJ5PIc5dKoqgBCDF5+FqPjm0UPYZ887Pgteb/w5PT4Lvx4AYv2P+SyUa5ToAk0nSRFmWsyB0zPYbRtKLdJ8BmqaZPwAgCePYJ5lTjvvs+CzJVCVaF+ocpKHB84PEcY1iaCsSRVNIx9losU8zExAWfbkFM13vYvyW+pZKVzWKd597Pp5dXauz8Icn6L5vD/35DSBn4ex3jtybTx7EX0Wjx9i+QNPsNAkzYcLmNNlr8+CCwPTNKnP4nT3LeBubhb7+Cy0qA3l0qAsSCZnDyiLYgj1VkFZInUDWAVKUr6VTrarmF06ZR1+HH2gLJW1aZ+/iOS52qF4VVCWoQCKCqaHlIH0bcTxeDNEITIHQVlF0Q/K8gClsLbb2D+pDGFmdh+EPlCWZZR/9vTqoCy/Nm3PcwMA9tUJqDDO9yLP2LMXWPzxjqAsX+DKni1DoSTN0LWL3M3NYhcZdHj6DaNDfCoP8g4On6EUdRW37mVN5jYmcnHKrNzhgbCqTf1/uLYLqeYm2+yA6Mi0F6SoS6LadttZG7YIdPzud05g6XpcQ5LMVRLVtEOZ2PlARPORUW7b7nU96w0A9uSk6/uRuWXp/DJXjb7luolUBZnzlAVyHvwbJuBt2mcvumhatrD5pgsV4g64GespCurOOiXzWK3ixu83Hnt65soi6GdnvYljUEKGQFvPDdJXLmIHuZubxZAZItKneWQ/J2UDgC75zWaTkqzovnLym1JlnfpzzWx2MflNyATdRvIbz4EQsj89ZX5OthO+wnoOGfkNbzb+wdXkNzFD1eWcZOQ3R0c7k9+4dRsmvxHHK1vuJb9BUcQowgD5jZnPIvmNX6NB8pv798CvTjJ6PYrrrclv2DrTbzp1xaD9uVSWbqPIsDNUFDAD5DfFX/jXksLIMIWrG3LfhUN7yW98CUra1gn5DSvym6BdGXJzn1SwL49jYeQnj2G/6z0U3/gobGI0nToTSIX53Zp78hsfAg7z+nR38pvRwTnKKKPsJHdTs9ByDYWRAQQnZdA4Evo5rarbnbJOaTJxXxLFRUGl2tWlgC+8+itgKq9ZuC+5d7iyBot5KHJVRXXS04nkWadSpJjbtpN1KlwdsYixgLKigzTYs0XhjnufAR0uAH0+vF2/2UCzfQfOTllXHw4N2khZxgpwOut0Fb+MIeu0bSMoazF317VtdOQB4PuHbl2V7yhJqy9L5Tz0c5rPQMevwpoHB2dhEswKlSXoYBGzTgXKvVqjfvcQk1OvIbEDcDEA+1AVRq4cT0Z73zu4JyW4IBRndVoY+cNJfIYQhQ4W4NkEtFzFcPe9Q5x9YYF7T9U9X7jM0lAY2s/dLmYOCFgUoTCyA2VdY9bpGy+XJdTVOAbylGe2x5cx0GcOkuqcokhKEnxBvXWmhbaJ2fqiN6pvVcKur3wh9eE42haUVQjL6fn033rHrsFTgnXwwKYAoNrWUUXW1PWC/eiBxLOAqICYD4JY0jC8GN4ECcdV2cMwrroG6sanz0e8CS1dWUUmbYb4cdaZL8Ay2G/YCTBsKxT9lPosALd5KPCYSPFqm2aosnMc0tJvTBtPZccME8yC1vFXbBpgW6M8VSUKrHXkNzIuIvBm6+rxqvtOqw2mL2o3Fn1uXaeRHHgTom6cea3h4nuQFd/9zWJILoqS5C+anHdBMVpwzmrN/ZtMTztSW5Iou4ZMiqTMxt1HHpNzcro+u5yaIeqRRyLgmZR6uEiDw08eQNnYMiZqx+GoQGMy54wpi4yN66TWhtV4Qo0NvwmE48LdqZ3SIY3dpnPwDkqX15HOJ2yw+VzzTd9roixUBF4ISDfSEFa3MNsmjSr45DDaiNOyDYW3aSvsaH5tff1Ss6qTNe9I04ANRUerP1Ysa7B61qhp/bmqDCbcJoK69jB5/UH5LG0WlzVDQm0F54RzSUFI8zw8s3ZQiQ25TMecAUlnnUpfReF+bmNfQk/nfk6zTlFN0g2sKEJJOgYSRihhU8ojGb1ZoN7Zl2S76jXINyIZN+D6NyaQucimRVUFlN4MEJOibUGWXU3QkMfCMQlMzYeKIjoeMyYrqkq3GchxKeGo2a7LMmoUQoMHgGcTYO0Zusv4UnLjEZRFHBvIXzudJGvmcnE84Y9+borC9SuaQWjHwC4mKHQZwunEcW7MJnEdy8Ktjz/GEz++xoLqBs2BO16UJdjaZEwgcn1L/yqfpr43QTmJpgsmlTOVCo8uFVN3WoUNLymZOGad7icOvt0jPfU9bkQkJJeHLOWhvW3JtSIx0fT8PTM19a2Jvl79PWgqcvwqGZuiUSiNhaz7enNrQdRndpnEvCP3g9KILunv72iVfWuSaZ/6Q8aMwGLrnwPecVxkkWpdosEMje0KMkZDRhlllJ3kTmoWrnCO90p7kpikGrb7AwJRTI+ZItDhEDc/PHDOQSEnWS4DcQw3EjHxBDnzefDoty8amMODCCP2fZkH98Enp6nj6+AAeOQKz9DHn7jfAQfeefLIfX1eHLu/L+auxsNsCj6zMH5crT9G83lEffo+zOEB8Phh7O/DpyBPpWYk5t++cH+bTIDttgMzx7uPHVwYcPF6fy7fOwT549svPsHkT53Ww/cidJhOFDowLDQB1rgCQILN8CzcvJjBfPLcnSfmzP0j0PFJdNQ+eeSQmScncQ73D0HLtfNvzCZBuzn9wXdx8C9KoDDOyQmACwJPKxSfHIOnk5D1S8zAu49RP1yg9NEQms8dXLp2eARZBwDAdIL2nXsoPvjUtesjCrTZ4KN/7x7e+wNvRlmGnZYoPz3FyQ86CPf8wzXaRQkwcPa+m2czI9gJMHvOOPzWHE//bbeOn//oyEXEpJShF/vd76E5mmD6RzYgNtc/8B7+7Mcn+L6TR+G89ZMZZh8vYaeuP544fWDzsEKxZsw+OsPqcwdxrMdvOdw7iUSoNOL0pJ5sTSXCZRiuXzruw8QJpp1Jcq5P4w5OIrYu7yDrx746cRtFG0OnWC5d5iDg2pC+6wb0/DhV2X2IjD0iL+Fe9LwRAfUn4KyzZWJOyTi5bsIDFgv1OGcon6XwaDx74YrW+PkDcCHYug79Tb5duhdfslylvXobgFyyNlJSMN84AQCrVdysPcMVNY3jzBRQ1jOC9UWNWGDNdR2BW+sYzTj4FyXw/Nj5g4KfycT1LMs4J2bQs5eoVhtYKQ9QNw7+7Z2kVm/0RYFisw3rSOqad//xEuUHEZRVVCX49AxHf+T9LmcrVN4XNHnmCXsnJZgAs2lgXp7iifhwTs+ij0aeRWNQfPApiunEPVf+WZj9q0/x+d9/F8XTl+HZWRxPQWcrFKG4kPu/ejp1/B+nS8x9mJcsw6zfegRnD6tTVkFqv+acg5IodRAKQUyofG1oJzR4aJfIOepy25xMZICCc3aSMWDY6EQsjLvRnrot5AP4cd2khL7khZNQpCAvvcMtIdVpW3BjEidr2Pqsn6tm67qMv8LE8bB3eDo0p7/vhcu3QFlGnAEz0LThbwKVptanxFflldeTS0q0AC6LVDPwjFrURqQxF/7/0jmQuVQvd1G4sYZ5D3gLiGAr7/g1CmVM5NphVmt+dd/X3dwslASuSveL/2H3TSPh0xTPv/ytz7TZkd/NRVfcDUso4qSvokh/LgoPM1YvVFX5mHv+ohlcGOK9rOgXmf0mJdEfEzcLqiowb+NLCYSvWABdrT1eQIBpAYLs16Gv6PVFY/P9u/bgIyNeW5AXpSycyQH4pDC/qWkwnbRTlYr/43JrapUmA2EhKwys1m782KJ5ZDwDVwEuTKTn89cGLk1/rE/YEGzpNzwbN8wkofGiuiV7yOjgHGWUUXaSO69ZJKIzCy/YSRO1HnBflxwVed6XRquGfWpij5odvtJ520miWk//loH849Lbp+nOW1cQ65P8eJ954M2ggKQsejQbrYa3Kjx53hqSYufW/2fHI+mwhnDbBEDmxkXuK67DjuzwFVxzDNnquXP2e6g+btK1Eeb0zBcAeDOk6Flfb1qw1wy5c4yAxjqNo8zW3UbEK/kyhFwWqXZqDGx2HRvP3F4Yz/Lt+ysNqCkSBng2jH7MQL/c3c1Cp0u7Hy4VU3bXt/5BUmhAD+ZhFR+PtT9Tc6VXTVQQckZs0whIhiPOIKRJa6BV2zpo7mTis05FVXaoQ5pOgSI6WWUcpAA3Mk7y2ZRuWMonomphhmvKMnI2WFf1S8hyQq5EWTiIsSGF4IyYh5BJCrcZB3CWRtVy64hnJDohtT8lO1LGU1XOz0A9mzNnaf5TP/emjZXCCwOeVMDS9aMdxc6JaGM27XTq+qMWVMYyBW7OpYu8nKlx+rVpJybWLm3jvWjn7pxyuQFP3d+bA0+CUxLsxGBy7JyZrY9auEp0NYA6YkJqAO88Ai+m7v4Yz7Mxq1DPM1j6tACWbkPgAmETs/MKZAyKbQ27cJE1YnYb/45yNzeLIUemRlFeAPfmNmtDqlzJwxfyC1rkX2vniVe5Gusus5Eje8lyJeo6hA+5bROmaV6v3UYlvBLeI89t65GjSvuwrjpXh99hvUm8NTJObtvwAndyWrKx89lZjJhI5AAAziIJjXnpeCO44WTN2RMIJchUD/fmtSJ12dY+h+G0w+NgLLsXWiJFZ8vQbrLOkhuiOCaKT45d1KMwKkmP3UZRb8G2jRolu02NgACXDmtqrfM3aVh0UYBUVTTNybH49inw8iSsFU0q8HKF6iOf+r5ag5YOaTpZ+Q1X/Dp1Azo5w/yDaVgbAOkzZwzw8hXMWQW7WsUU9Wev8OBP5qDVJmwsRd2Al+v4cfH3olxtXN7Leo1C5bVQnjNzjtzNzaJPcofZRXBvnb8ARJU02XAywhS5f57lCAC4cV9pztdcYLltdky+8KSjBrU7rslgPAsTFQbWMihXXlSBnpB1WpiUz0Kqd7dKE9IOVF01Xp4fH+VI5m1MqC8KwMGZ1xsXUVCaEgkzV4b0dGOLMOXkQd5Q/DvgYOVNE8l1q7J7jqxh2/ovp5/DdOIh2XG+csvYOk0mYFMsO94JtV4SXZH8kiTnwmttIZqisl2bwwkmup1JBWw24Ln/gkv9U2aw/6qH0OnWwbJbr3EYQyGRTAtVlVv3ogCZJvSzvV9hUhYu4uTXgJq2Yy7xzBcpals1LuVQ30FoMHHlFuUePeIfoU41RCchISbbCMLPcZOQak99bE+D7SKq5gCS1HWaTd3XJrBcK/Zpvan0bEjhJRLmbT3eHgmp5OGlpgR8lmAUPMVbZ4462xJw65KTA/Vdo45TNYl/01pRlnci1HFJ6NRHfmg+T8asqe+AuFkIlWH6xywELr8zx7HpPBnJgfDrIi96INjxmgqR084EjBeyWssyYD14u03XLxsHGZVcJufZFsU7j12haBFfJzWsjU5SFPPFk/xQWYI3mwg4W/kU9KqMGBhjwthCAWsAZrFwYLflKk2EbNsYMVOh04BNUffxa5u/j1c2Jy7tlzEaMsooo+wkd98MSaIHl9CSslohur5nL4Jz52a715Gh+LXu4aIAkCQPsUoL122F9PibkPxLH9LfTTANQqRC1UGRyudsEP0+8oXL5hzS0S89NlUPlGySSp+YQ/pSGZ+uQSJf26smCLZxDG5IWep/klin+pf/rY1+k9al+hOi9jOoJXti44T6EUijUFdNklNyNzcL/bKFHJAcJXm+zyIyRDmCWJpOfaq40PN7SKxSPV36MjmuS1GlNxvHzShedt9XcXjgCGGVI5QmFcjzSPLJSWCvspsNzAOXM2JfutwQM3XkqqiqlFXLs1/RpOrAvXWpAQCwr06dz2Nbx1wYiT5456kRinqfB2IePgxsUlKshorC5cwIO9bDB+AXL0FAwpSFzcaNqRNWNTAH80i5L/k3hQms2CFaM5smVdHM4QHs6ZnjKfV5LDSbgRVTVrjz7z4GPXvZZcoicvfTFCHfBURuzacT2I+ehr5pUkWfhXYEFgZ0cBDh3iE36Bj1D343Jt/8NN7/qgSfLsHvCb3/WYiW2CPPlFUZcGFQrGqYFyfYfO8TAMDk699y628omlJEMO88dhycnz6Pz+YX3sfZv/EEh//sw+gQXsxgzlYuYqUQnLyYgbY16OQsKQVA31Jm5wXy5m8WPSg/DbvW1cb3YSrWtjbIOJ+Br1sBwFGm64gIEGxiobUD4G5sVXVrPfiHjoBww2gycXU2DLnzpQ5G2wJHB84xJeSxExdCdHTxiP1ta1+zwqRMW3DnJGSsZ0t3TNUNIaHGk9CptCtJY7NpUskd5J2bixmw9azS91yyFVQNCmo9WnNbqzqy7DcbA0ynAZHo1sCvSR46nan6p/53khqqssnMZ9EROY1cDvXDBarVxr2YlfIXtO5LLWsK+I1wOkH7+Ajm+QuZsAtVNz50qrWDsgTPp47Wzt9LWaOzz89QfeLX3RDsbILCWtQPne+mhAtpUsvYPnbnNQdujYp1hRmAs8+59qb/cuLIn00RN8GiAC9m4PkE9LKM7N5HCxx/scTizw7DGrQHU9df5YiHuXLnNocTFKsSRWth7839PdsvdPrmOzj7RGsL+c/Axc5NIDo4lbeeLccHvan74d7iNFQOLpiis6lRWXbMloBXANIEM7bu4bPWOf3gX56clg9Imb7DZiFRiyJxQnJThzEHzUQ7aJk7DmSaTrv9ZrkcNPHkLsxpf8I8pecIxHVVeBDXpyppoAiCEuo4X2RJOzipUJRzysEpWkkCnpJxKB4L6Vs0tKRmC3XNpvAnYR5X4+V6i/L9z8EKj6ect91GR68uLyhRE/X88WbriggBsC9euntMlPQlER5df8UcHsI8fgh+/lKth4mJaEDclAvjtNy6jh8Ia/G11d/DcfPp6OAcZZRRrk/efDOkT3LGob6f+3wWff6L8LcsSSxDB7pjbbTh5eu+tZ76LXNGScZqoplUab0SQXBuPVioKADrbWpbOMZt0VrCl8hxgBqNpxD1XtUlAQCs/RelocjurcPAVrF7b314cjKJYdqAQaHkq0qTKqZv54C1tu2vclWVnRw8mk0BcSEU0VTTFdcd7wbFqu2AM61atbby9ZzPVQp+dOzR1IXAURRgVbGMZtMkVEqTSahJkqwDs7ufkwqQcGZVgYhgAfDhIqSsB1Ba20b/0WoVsSFS7tEYcFk4QBUzeOF9P5+2jn4gWakW5t5hoBAM9ISLOeyDQ9DLY5A3WoIZqkLwADw6tQSfnMZzrAU2u2fc3s3Nom8DOI9rsyevPNrVYoaY5H+u0TVrxPwoVJEhMkHtDOdAmSEqckGFCQ/L/9/e18RYlmRnfRFx/95PZmVWZlZ1d3XX/PcMM4xAY2MZkCwvLOSFJYsd9oIFyEYI5A0r2IBkeYfNAgSSkTFiARbssLGEgAVe+E+WxaCZYdwznu7qn+qqyqz8fX/33RtxWJw4EXHve1mVWd09U1XzziYzb94XETfufXFPnPOd76NlVwogPERCECNfcmNAFDkZyfltSJ5HbISv6hSJumDicial5MpDhWUx63JzOv5CpNyffq5UVQJz399gwLEG1dU6xQL+y7qKsE23ZWEsZRHjE8bwgll4rsjwkBeBWLfzOe9qd7ZB6ZdWzGgGUwkmRESGwIueKoqgt6qyzMdWbHfR9QtARxe1LHjOl0u4nRGMEOX4hQWOQCMfG/BBTwBwQsOfaVBuoDOuNrY7PvZzP+vEbMJYq4pjLgnXhxpUWNwaYvAgkQIYD3n+ZF4kwDkoQVXOxD5+XCACjl92uPd17DJo+Dp2b3JXS+s5ApMf+nbWLVIpAjTpI8Br+5/rwW7D3nodiQ954E0fKSlvddlPU5QMoCR+AABKeZZy12s/TcMl6cl03w8PiQ7Fd+k1X2brELE+TegH8ItlzQAAIABJREFUxFBpa/y96J4TJAX9MTknjbnppl0b5CZlI1gpNWtBbYyPkLVQzjKUXEfEqXBaChQ8jEv7VO284XZkHolTyiqBsgfwr2RYrGay3pqJfNS8qzuzcg2iUpbOTdMim7bdmIhvL7xIxOtqTGwnBcltpAAAIchJUZAd0pzgfkbsAPVJZtY1K8zUCcuzKstYY0Hx4e9vbZTwJ0j/qQufd29FqLQM9SnJG0DpDtxYAmLIc2YJl9OKIqh9iwegvKRh6vYDgJJ8vTGA8vOVVnmmQcMsixWuHVTnE+oM0qCwXHeWRUSjFL3lOb9B5YH2auYiKQjAw5aZGyIlNF5LZGM0y0v2uEr4f4azHirOhSoKXihu3oA688xc1vF5yfYTGQdHtbVwgxw6kO34QKQxXMAGv0DIdi8ILLFnQdZC1RmcLzq7jKBZFQVD4Ysc0N6TyDO0owx5+iyUOVTTrHoWeYbm1W0U8zpseZAUM17FXszFYl2cYiUW4cL+vn8MWM0kBHDLZf34v8la5uUMTRLjIfpeRCt6F2kmw3UWlbCI9Yuk5FwSUZmuHghZ28VwkOOFDk1nAaLlkt/KbRtiAww/Z2FnaSfMh1clpxRUBb9wJoVgNJ8nxWvrrnl1qQ3/k9+BrqivLFLeYwqutowxBVp5sZ8+GElPZh0qPD6o2QtovL5Gej+WTaceJ8ZqLNTZRcBkkCiUJS8e8TRo2UCfTuP9k3Ly5ZLxDgC30/JXTSf1NhKzoMUC+pS3Qq6njxvGOp9DNVnQbAUA0grlo1nEjsi4FovVmIVzyB8w3kSl96dfUPkE22RDNraxjV3JXkzP4jr2rPKG12n/k6K4u+Y4iDjI24Fje5hzBw7svQsAeB5wNsECJNt2Ap/ftzGGuBX50v4EMq0UExB1SIvYG31G8Pq1x0Y9r/ja/fY8sSvhkRJ7MReLjyMbImlLCWh62v/OHm5dNsS3GUlt1+yFgQgu6pC2dMlsOxmVfhtCIpyqoAEeL6RCyTOAKBMoJdZhDElcJOUWFZUynWRZfIA1Le+OwVAVlMIAQPm0IbSOkGQ/T5TGhdbNR3LdIQMic6s178uRxIx85ikFo6mMhYc7UX9gRV0sXLfwb/ZIdAK5b3quYeQkxyiSGEvSTjzXM4iVRVJh6jMnpo1xqCaLmS/JVnnyYCVbpFIAZ2Z9NiTPGUWagM1UlqEdFcjSa/DkQSGmJucXvsQ9y7rxsZc+ZnEVW7dIpMU+Kd4BCKjEUBvSh2+nTadwb4E3p4hOwCMhXQdzoIoi5N7VchlqJNRyGXPy5+fhXClzThXEJQWoiph2DJKExrDCuFxuXXt1+CYgB9VcuCE0qE2IaqQMfDQClGe6kv1ungU0IgDQjS2oxYIXnDR16lOJaWFe+JfMh/wOBG0U6QPgFCG5eYzm+3PIUdBOUaMhxy3atvNlt/vbMHUvZmEMM1yR40UuxVmMRgzhvoj1HqqqOC6RBjMNuJ/tccgkCGTdXUywuLuFoY9ZKEcci9Aa7W2u9zHHGVzl9UI8BNxlGrbUKE5LZEcG87uM4Bx+UK7P6GyNGO49nwd2Mbe3jdPPD3BwfxznYGcMc2pCLQr5wKsdl1AEmNEQdtfXhjiAHr7sOIurBjjTnz0TWHUIcPoAnkoDPmsBXK7LlCWaHn3dkNksBuHEFjVcIi4sACGyNhQoha4WDNZxXiHbJekut2ygEQOFISDWZ8paLjmIaaM+SCqqS46CQJFca9A7AeJi1LZQTUzR6aPjWJCWBBQDmGqNhyfzASBct2oT7RNJDcqb1s+vAwJTlks+J3ObehLmg6OVeYTWUNOMg7I9+L47v4CaRcYxCCuXJ6vpCEAbw+rxCVMWs321GH7nMfD41E8jn+sWNbL3vYc2n4fFvjhbBWXRfI6hzP9sFoFlqR2f8otjOov34eEx9r6uQSencQ7mi7UBzuys5PT0dAYjWBMiqOXVmbI2Ac6NbWxjV7IX07O4TszisiaeFcEJQKpUAcSCs3773w8Ep7A9+WClFEaJ0XIZ98CCZ5C3ZR/BKWP8fiI4izzyXMoeuyx8PKLpnENWf+IITuS5R4y6bum7zFdVxtSpIDhns+8rgpNmyRbtmgjOQKsnYyACTjYIzmiXBDg/Unt9mrwUcPRx9vU0S3lEwziS6lAJzPXBZkLtnwZnLwEDfaImQU2Atwt+HpXRIGc656hrBOKefTj+PmpivpAEByPSACp9YRT5emb3T3qM2bN9banIouDRs/T9PKTOrlWivqYcfK0lN7UTdFwD5gnnpyjBS+ZF3pAxO8HFWFTX/KbLfIA04Urs9JEGQtO++lyjT/GUOgjOlOezx/EZSpPl3LQkPPFYJKBKCUip21As2Q5l4/3+niTHsIZKQGV57CtZhNOyc2G4Whm79JdmN/Js7X5fiuYAdJ8dbTq8qiovQvm7HsQ6kFAyThSzRj4jpQcVF371AuJpkV5KRxDIiuVLay17PT5462aztXOopfhLayghMjqfQA+qEMsBEHlI+1yvmsl+6Oy8y8E5+x2c2auVqL94noWzUHkRHhxVFBz1T47B8yxQ23rlc384uaHmgJmJ3Pk5lFLQtw8YHeezCe0770IPhx6l51XKyxJkHczuOGQH7MNDmIN92IeH3IdnkzJvfg44Oe+Q4qibO2heZZXz/O0HoF0macWHj9B89bMsVPtH3+DP330d7vAx9GgId3oG5Qld7eFjZLf22ZX0iusSHdc3d9G+FhW1zZ9/wGrrxydQr93mc+8/5LEMWLND3+TxtO9/wP//a38J2WO/FZrOOShWFWgPtpCd8EN59tU93PgGq583Bz6ybgn58Qx4/0HoX5i2QAT1qTtQJ5zpoZs3AKVgt0pk7/B4hAioPdiGOTwP24X27i1k7z6CfXwC86XPc5+3xjDnS+hlCzeM5DcP/uo2bv3pDJQplhQEQBlrcgzfn6AdF8i//Z4fr0PzlU9heqfC7u+9w+eOh3A7I6h5wxBuj6pU4JTn4u4WBzMBOL9toG99D9/+tS/j7m8LUpLQjA1G78/x4Y/zOdv3LJZjDeWA88/wee2YYAcO1QOD3bcs7v8UP6Rf+pcX0EcnXbSoUph+7S4WuwY3//gRcMhjOPm5H8Ebv/AdPPrVL8ErOOLijsH2vRbtUEMR0Jbc3+yWRj4hbN9b4vxTnKbVFmj+2//CVe3FWyyAjmcgK/0KD6FE3i9hz6KLqCpOADNUWdvZ01JdIxUZEjbqoGUBftu5s/O4UIkdHvPnkzedPj5F7v925xeM4QfgpnMUbz8CiNDKuI9PQIsazr954OnnQI4/Wy9XNCzc2TmyNNrvx0nLJZRE6yV74WHgKWkLAOT3DgN82C1qfpNlGfLZgvfLAG4AwCN+YIvzSBxD83nIkshYxdSjxzGD4q87O60irZ7vM1twdkDmLXtPwV1M+D5Kn5M5X0fbwiSiSrf/SLGaebodM14A6PQCRUJ0Q0Qo7h0hP6zCHKhFDTOZgVoLnZkOBF9lGadH/TxKjMLWNe7+tsLoz7q0eup8ilf845gdT0EVVwlvvedp9QoNlyvkZzXywwmyBS/y6sEh3GwevA4AIK0xfOsIg2EJHJ2Eebz59VPc+80v4OCbD8MzOrg/hDmJNH6iRbu9VULVFuZ0guIxp1oVEbLpBu69sY1t7GO2F9KzuNSuQ6t3pfZ6hDiQ5nsanpfBvdcdX3fsWYJ36+IKbk3MoF+C/rTx9Jmp5bOi5g6sL2tO++0HXtfGQFR3vIlsZAeeLiXZnRL9S+JJbs0YAK6oXfeBftWlxFzIAdQbNzkGXPXL7KVfyVC4WLwYMDtEgOUSe9VK9k2xA0RJG+nc9HRYlSPWRU3HZClsP4I5xDlLxqmsf2bTZzc97wr24i4WEiTT6tLvwRNN6vwF+mw0VyUmUFghtRVIOMOOEaDOvoGuWK1kQwQ2ndZqCGRYftexzB15FmItADh1JyXXaTm7lKevEytaV4adjvMJ8xAsy4AsVnxC++h7kYdqRVdm0EUBco6VrsBfDCVkximkXTFcHbpX3h0yNRFuH+cl3UaYGBiWILAno4VSDGF2cVwmzxi12JsHVfjSd0kh+3vtqiLozwbUpqQ/0zaM6bab/K8Zm1iC7oiRlosazuub6iIHlYYpRyqPqBywFqmiDGaSo/EEviqBa5PwKRkGcFHe41jNDZotxf1ZPwdVxv31CHttaWCIGAyWR9a162RGnrpYKKX+HYCfAfCIiP6iP/bPAPwCgEN/2j8hot/1//vHAP4u+L3yS0T03688mqva2lLz660YIdbhhZFp2Xjtz+ScdcLIxAVGggMAMeJwpUS9XgYFqFhaXYcvQqowRk0LmszQIamZLxh/4fyxVoX+aLnkh0nUyuVN1jSdcmUZJzmKpejyBrOeUKbpxlpoPgcJZLppYok3EDgm9FkR1bIkU+Gvj6zroFvJ90mLRYR2C1dHnhDgyhvOLOK9APhzUt4uEgUAf6Gs7eiRZkcTVgZL+Dq4TcPxlrQk3hFoMoNxLpa1C6GQtYz2TO6RMi2U1hzHSa/bEUbvz6GS2I1a1KDpDLkEii9m4WVQynUVGUgr6EUDfTLB6P0izr+PFUX1MwV9MYVaNty/P25OJ7jxvSH0cUStZl47NWBS/DzkdckES7M5SySCvRXxdK5iV/Es/j2AfwXgP/SO/wsi+ufpAaXUlwH8LQBfAfAagP+plHqT6OMFH6SENjHrsYaJm2z82bOgozGb8cM1GkE1y0g3P5tFHk3J7hkDkOLPFhHkpMajAHYKUNwb26DJJNx4AFBbY8BnAnTbQm15RufHx8Ctm/yF8VIAemsMe3LKWhbWhfHa5ZKPjUYgHxwUzRK1tQXs78Rr9PT56vw86JKE8XmtExmDSAHg1h60f/Bl4VFlCboxDl+I+jMHKC1XYrobMVimzqc8DyHt6R9KRZy2kxqMrS1AK9BoAC0LnS+kot1t6JPzuGDd2mOxZGtDRsjtjqFmNbNCVZHs5+Ire9j6NnthLhDsaNhBjvzBKdeBpAHs23todgfIz32QdTQEjQYM6y7ywEcBgIlmbt+IEG4BXM1m+PDHRyGYqayDKzPkj6c4/SoHLUcfDNGOOcA5fdXXiFSArRQGhw5b7w7w8Me4vTc+2AZwzs9k4BhVaD59G+1WjkFr4Ty8e/bmAd79aY3Pn+wHr29+u8LgwyF7NURwBY93sZchmxMGD2aYv+LrkxzBHl99c/HUACcR/R6A4yu297MAfouIaiJ6G8B3AfzYlUezsY1t7Lm1jxKz+IdKqb8N4E8A/CMiOgFwB8AfJue87499rLZOGnCFXegphWRpEZbS7OKmXIkA1gb6gktPsV+qlyv903zO7jRRLO2ua3ZJlYJrWmZ9Bm9v9GTW6U/erNSwC56mYMm7kysFX4tF8AoAsHvt+5e0ZzhX2KeSbQvALnNgiKqXAYyktA7H86NZGJ8Wd58oFOOtzB+5TjpU2MKUTbYAAvg6Z9UwOVefT+E8WExSxdpooF6yGFASoB18uAjYECnNJq2QzWpgvuAtXQioOuiLKQvyyFbIs0gJT2VnbpoM5jiLamCBHsBi+55FdjwN86CLHOpihtEH/AbPj2cwU4756Nbjc0qfOr2wyI9n2L7nPasFb+WUStjRSCN7PIGZFTyPfrzlozl2vrWN7DQ+OwNHMCdTmFB1yvNg6gq6bmGOJwj1w0TQy493G7LO/g2AXwZvH38ZwK8C+DvXaUAp9YsAfhEAKgyfcvYT2rkswPmUbUgaIAXQDWw9zYzp7Ik7+2OxLFsNHkkgUyDMsq9UigNSKXoyRfqlP+X3lFtBakSM7nIV+HGSSngbknJ2WLc69jwLymMRbWg6x6nKWPJRqVACLecHUtmeqYSLIfBs5FknoAuAt3d1FrMDRd7hsQDAc2Udf2ET5TA7zJAbA0oDpFqDygxqtsrPSXnGSmFywHM9KJmHNgl2Z1xmHpCzCZfqcqwZRwEAlkAlz1c75mNmmsMNeRvSbPEY2lLD5YCyQF5lWI4k4K7XZm6oymGHzF0hAXM7yFDvKlCRhZeXHebQs4LH4ADKud12lMFoBV0VsJ7vE0Q8V1e0Z1osiOih/K6U+rcAfsf/+QGAN5JTX/fH1rXx6wB+HWC497OMA+h5FM+QMu18Pk0bCmvSMwojr7VOejC+5YiI9+790vvOW9p1Pvt9MedTixJQ7qU3SXdTfiRsTuuU1JJxC0P1dRPGkfGcP88p7DRNyP9TNkb5KX547dxJFuGjmJJ0JdjjoF76UlFvjJB5UxxktBTI4sOzgdjmk+63cghpWekrjAExNfuRxZ/xjIuFUupVIvrQ//k3AXzD//5fAfxHpdSvgQOcXwDwxx95lP3+E29Cfu97GJcdD/8XshV5iwpTkVRR+tQeU+YnDE/EokISCFV6ykFE7YOCMq5BxdmDNFdeFnBbA3aTT4uA8VcXE7jtYffcqgImUy5oWtRRx2I2YxKdYRWEisOiUpbcjrRxesZjW9R8PhCJXoT5qkyqRgG4rQG0fKkTbVK3PQzH6/0BhkcVb6eS/jQR1MUE8uQHFjJHcT6AAKl320M+H4i1EVsD6GUTvuRuawB1MWFPRoK8N4bQxkAts06Ac/pqjuLxkLNNSYCzHeUo5kvQsASOonSf2xpiuVehei+P1zkexgBnigguC7S7g8BHIdWjymicf0YFZKZqHWxlUFobgpm6HbBHQcDFHX7u7ICDnO1AQS8HOP8sj3d/OICqu1szAGh2B1hu58jvl6AZt7u4VWL25QXa34/ERLPbJYaWYCsDRYAt2LOY72fIFg4j6zB7JcK9Xf7xpk7/E4CfBLCvlHofwD8F8JNKqb8MXiffAfD3AICIvqmU+s8AvgWgBfAPPu5MyMY2trEfjD11sSCin1tz+DeecP6vAPiVjzKop1oPpLRy7CrbkXT/KpyWPU5G5qlIqkO1inyXKRdiH9gEeICUDvEJAMyhmDPISGVZ2O+rLIMt+E0QrifzfJrax0dMcp1Bt6Mbz1Baw6Vcm36cpPVq7MODyfpjp9wk45J4AgOCpN7AVjroX7jKz5dUWSZgJiU4DeW4zSTmAHDwTfWugYzpXBsZw+coHT7nigwq9xIJyX69rXj/TkYFdXDSCi5TzAVRZBGAZS1crlnNXMBeWgOZZgGgTHfjREbDpceyOO52THCFxGMUA66KDK0vFLWlRltqTlV6J6AZAbYiNCMFWxk0Y4pzk2WezyTq3TANn+qUydtC48bODO1wHLYbbaXgCgNXaoC4b75ngHIKlGvYwm/RLK5V8PHiIjjXLQjXiVmkwUe3HslGAtJJIclSSh14IHREWaafTQOHqeqW0TEOIPtqj5TkfWpaTs7ZGUr3916LJLSTmjEhoAWgM07qBzLTwG467mwN34FS/MUWpGSmGEKdmeDuh8tPlL86mSClVjJTjEiMiyMf07xQypc9TwBWMl9GdR9yf9wVQBCUkz26VuGLTCrJfKyZE0FJonWdRZPPNbClDscEBamUgh244M4rBZDhRcpWfly5gssBQMUFpCK0I4LLFSgDXJWWD1iGlYc4h/ULjg8oa1ksgP3xFK3aAvmNmy3AVbd57BvgRQQOsLnm38HbEHrpF4vki7b22FUWjVS8VyuPCHSdYJIyBuTanmch8nZxX0n1cuWLoBaJCJC8jdoWepaU0QuKVGuomtOAlGQ4VJZxjKTDBaFj+z0RYKqXMJOEV0HG6RzUQhCcLvwPzkXwk0zFZBll94Rgt2mhZzFdXJy18bjncFSWoFqPVhVItcRSnGMOTwnCNTyn5qIGeQSmvC3NpGZBI3/cTPzv5MK4zLSBqluo1vp6CW63OibouuUFTyDNrUNx1gBNC71M2M+thZk3MIvIqaHmNTNX1YwgVfOk6tQ6FKdlOCYKZGQtqgcG+ZlPBxOgKINeNBgccrv5hYWyHNRsB3ydzYi/0OUJIZtYVA/KMK7geQo6VRsUp0soV0DNazj/XFUnFt995zY+V9uwkFenBtmkgWoZ7i0xC2cy5DOH/HyJ4ZFf6Cyge8XST7IXcrFYgWD3jnWOX1aivkzg2had3D4fp4BxCO1aux5nsVhcgrNYdt9kcw195l3pZQMIQrBpYE4ngHOxRF2IWece7pwqmdVLhmsLhFv6WCygzyahP8FZUNtGwt50PG0bkZve9NkkYAmQkL9oIPRXPppye45ggkaJY4h6uginmZLpPJZ8S8pY4Mt+bgGfOkwwGfpsArdgqgDy82WUArxymmqiruf4vQH06cTLBybeiFJQF1O/OApc20GfXKAC4oIpmYS2haqzHs6iQXZkVnAWrm2x+5ZFfhjn3Uxy6JMJtt7lPUd+PENeZVCWoJceZ1EZUAZkE4viZIHdt/xX8WLK40kg78oYZEcTmGkRnisAqO7PsPOnN5AfHge8ia4tzPEUWQ9nkU/KgLMYJlmt7wfO4pM3eZv2GaTAkXzyF6mLHG7huSTF5RZeTIGBpw+wtDESOnTH+8CdG8zf6CP1ajKFHo8ipwXg5QJaqNEwkN/QomZot3/oJXOCvV2o03OGFwsWf3cHzSs7gALytgXtMNRatS2Wd28ClpB5Eh28sg/96DHUcAg6Ow8ZBKpr6O0thi6f+C+qkN/c2IZ9NZLf6MWCyW+sBfYYBq4EGj6ogPkCWiDUPkvSvLEXSG7UxIPGBiWa/TGyU/779Cs72PU1BfUtD/f25Dc6XZy9SDO1LXCwC33C98ft7QAajBuQe5OQ32SHeYBlt3f2kFmu3cHBbugzmyyh5w3aURH2649+ZIQDzVsmwQ8I+c3ggxJ2lKMQSUHnUH/2ANNXCtw85PtAwwp2DfkNwNmQ+d2twMIdODNPz3D/p1zko3CEZmQwer8IEO7tewWWI09+47MezZjgKofqQYndtzI8+FleALa+ewBzfM7PpCykWmP6+ZtMfjOrwxw//uo2vvjz38YH978QPIvJqwbb75ZoBz5WkZDfFOeErXdLXNz1mT8HtPeuvg/Z8FlsbGMbu5I9/xycazwLaJMAGnTgs3wi/2XPlFcbJ2s5h59lHEgU76RpGeOQehbC16hNct6SKf2a3t5/OIwyfAn/ouAlpHKUx9tCj0cefu3f/FUZYx5NEwFcTcslyEnwMLirWd5l9/aK6dQ23X6BqPIlcyZ0gNvbXb0MgPEmeRbGo0dD0GzO8yX9OQpVtqkgElfYepEj8Tq8ohlRhHCHDEqWhXYAxl+Qh+Jr7w2KwBIRhbgOAKitLa46TcrkAXBby6YTECbroKqKsS/HJ/FZyHx2RamOR6qMgSrLqF3ir9HNZtBf+SLUg8N4bp6zVoj32mhRc9aJKHiugcnKWuBiCvca0zzq9x7EEnUpelOKr7nI4U7PIovY7QM0n76N/J3IlIUs6+iGBHqEsmCI/GLBGB5vv3/0X3C2fPiScnACK8FEPna9Ra+jSu4oBDyv1Ao5VvOSP/uUekCMd/jzuU8ke+ZulkVEheL4/GdDkLCHlOy0T3EcHdV2Cw7IRKLZbrk9rYzd1fWamhi/MPlArZvOAi1fMGufiDSktg3tKjQgrYMIUuf6fFwoXEedqLen5ewBOJbElC4ueLvSg+OH+JRzEdzmfD2Qi0JQ1MRFittO5kHEmmQeQ90GQR+dMBUewNvntvWLvuccFfId5yLgKsvCS47qJW890nlSCdpUa7jZDGquOvfdTabI7x9zX0mFKjUt3yvnIsR+EUv/JVDcuY4r2PO7WFxTB4TxDAn24ilYsA47tyfA4Wb8cS04i86Hrj6edZ+T2IVS3ZSV9lgMa7tvBK34y5BwSoSajGcbydUsYcTq80KEsQmxj6Q408/LW9MT/5Buu9f8jHT0Kv1MqDNJhJM91oZrZGRRsACaiHcR5K5cp456q888px0SH+/VJFgR5YMqafvMIu4zXssmZsyM4YVCsDRy7LIvteB5eixmPN9d6YKPas/vYhHeupdMUlhI4tuVelJ8T2w+rYi0gDLdNwm1DZyjrgdyHSxqp67Eu9TEixJpdOnayYU3c6iGFTe6R81/WXbnY7N+f62L2JJl8la0tiMxEGpdEg+D2hakPImLiVvHZ/1SSn+CPUn75n+oQDYkAb+0JgVAzApZhu0rYG0A/FrjSrZN/Bz6LU0/I0dxbpnQh0CNf9tLgHy+CEH3FS+mb85xCnwZt6mSZg+eo+BgPtIVsm0CnBvb2MauZM+vZ/E0W4MyTGCE19zCCFy6t5WR7ckzkXwiiNuofptJn+H3nruYbofgkjEocW8/IQ9DK+4PAPoiPj1JvH5Jv5JqybR0Xiv2qGTswLO7/SkJb5ivBE4vY0u4SBU5lqLsQ/J9ELOLvn22ORWXP/wdYP4CEvT/S2M6slWWYHmA4as4/gRncalH6YO5Sp6PgFzVwUPhvz+6b/HiLhZhn5rCtnsZE2dxmYKZltoGr4CuBmPmc/ToQ6rrgOXobHm04c/689x0BjMewYpepr9pemuLI/1pRL0qOesBwJ2cBqyGu7iA3uZcf/vhA3/uFtxkwvR37RLaV2XSYgFV5AEDAiACmAYVU/fJaE9YedvNF9DbfNydeco2r1QW6Po8zsLs7wWinJA5yTOowSBmLm4fAA8Pufo10TqlRQ26uOhqhwh/8Y1RBDT569bDAdwpCyVJ4FENB5xpEfq/7S1Wdp/PoYe+snM0ZOBS23ZqedynbsN8cISOGQPs3wROz6HyHPYw/l/v74GGFZTfmujtMVRVMT6nKOL1EnGGY2sUaA8lo+AeH2P6tbsYvsXtKkegzEBfTNF8moWdsseTwHfR7Pp7nmnYUqM4XSI7mmD6ecZpDP9g3lGcB3gbo+/eAQ0KmA8eRXDb597A4dd2cfC/78fp3hnDnE5WdEPsmO9TdnQBuysYI4D+rFt1/CR7MReLNID5NJKbyyyt7QCCvmYnoNdn7E6IY1L5wE6aLklhCcFMaM5oTmHJZ1JCmjKWWodz07qTHtM0ijzGENI6jyR1Gt5/AJmWAAATQklEQVScwtDduwZYtzr2Io+l5PLAZhlQlYEc1w1LLshSmo+LtRKHWXMfUrIeGUtZRG9F5t33H96URc73Rv4HgKqCkZY+5R263ypgevNImQENS+hpznOcenRFDhoU3XEVnNZFnkE1PgVMHHCkQRH7S+Z5sWtYAAgIdSVq2aDd8uQ3swJ2yONabvMxWyq0pYJyBcy0wGKXxzAscqj5mjqlQQE7LpHneVgs7KjE/ECx6LE3Oy6g65IL7ICA4Gy2C2hLMNMSdizBX1yL/Ob5x1n07Tpap4IAFT4Kyf+nwUX5X15woCnBT1zWv+hc8nmMewikuSlVvLUd9zHFQVBdxzaWy/DWdKKiLtiN1EOS8XrvhhIWbelTJ/wUbr4I1Yvy5hZ4ddgiyRvIcRpVj8crdH2yOIa3/XgUlL06mqsi9biOKcvrzIa5AQJpcDpvKssiPgXscbi67maKBGeR3C+AEazuPDJd80FmJKP5HDCmowuqx2P2vITjoygi3qaIX8rQTpFHVnPBirQt1J1XgKOTeC8Mq5npXUbN0nweIe6yuGouSlNzVmDDTT7XvfvBWr1Ws3uDvRuPbwG8F/bqPtQ7kV9KVVUHZxEY4cqS2dQvJl2cxcPfeglxFtdNpcpnUjMm5rD7FZCtyBE+OT6heimqFUsWkU5difQRMBe2wzy1IqzbJrUr6U//eycTwQPjYdV13M/7RU0BCdMWxyGiULBA2bmgiubzTqYonCP4B3BGYV2kvl+f07meFBci1avpCZIB8ICkOA8+7WpMUjhHMduUyjWeX6zMI2efuOhO6bZ7P+ZzblcWJpFdIAJ0FV8cqTxDivXIMobNHz7ubr38vAgLt1wDgEBcI6lx52t8BMLdmad0/hZ1YIoP0P+zcyhHnb5VUlMS+vFj1/s3uY30/l7lxettkw3Z2MY2diV7cTyLFHeRbkVSNz1FNAYYeNJE8tYR6LCbL6C04oCk1+QAAHt8wlBoitgHlWUgRxxIFCKY8wl/Rio0fR/m9i3QZNrJ4evhEGrHF24dHUd6udMzmDuvAgDat+/x52/uwvm2aT6PtHOzGbvPVQXyLrUgFPWggtqNuiHu0RFUnsEtm6AbIpJ6qshBywba619YH2jMPvvp6GrLfOUF1HjIQkjwgcT3HvEbfxw1KDCbw/q3KZ8Y32B672YInOqRp+IbVKDH3n0XHZatMeuhSNxkbxf0+ARuMoU52ONzt8dcKt62IdAMAIs3b6P63hGgVNyLaybTNY/PGS4thXrOQb3+KtzWEPq773JfwwF7Ck3LLruA6Py9d3vb0A9ZFSNQ/H3wACc/9yO4+XV/3ZZVwMzpBLM3GcJdPprDDvh5Wdzyz1ehYQsuM6/uz/D4q/xc7P+Pt8MWr5M9+dwbsKMS2fc+BHkhZ/u1L+L+T4zwxu8eBzet2R+iOJzC+ZiF8/wmzU4JU1vko0FH+d79n7gleZq9OItFYhwj8FmHivH6adwASnEtQ23Dz5U2/JcnpNBu7UHPFqBtP5EnZ9ADjoxTsn+GtVz1KV+S+QI42AtVktKXe+0A5tDvceXBvbWH6ae56nT0TQd7wGPQ1uLiq7egW0L1no9sv3IA7YV13JGDvskVl26+gL65A7e7FR7c8OU+2MPss7HqdLioQeMhtDsC3fG1BxIjGA35c/IF9IvF9EsHqB767MAZyxbQqMLstRGqR/xl//Cvb+PV3/fVjHd8la4FqodzmKYJi0TYQhDBvXEL5pD7aG/vAFqh3i0x+n/+XL9ozV7fwuD9iin9wUI6wz8jqLqGu8vZhenrQ5QnDcysQbNdBLLbd/9GgTu/d4vJZjJP/pIpNAOFne8OsLyRYyz3yTpM/8IBzj6d4c6Jn9udMRa3hsimLdpRhvJRjG+0owKnnx9g7+v85Vvc4vtfHZ/ijV/4Du795hfCPDRbCje+N8S7P83n7nxrG/WugnLA7Mvc/42dGfbHU3z3ndvY+dMb+OLPfxsAcPydN5DfP+aUp2y7jMbh13YxP1B4fb4fAGf3f2KEb/zSv8aPHv79UHl7/hlg560SzRgAAdbzZ0xfd8jPC+y8VeL0TR/Ub4Hl917mACfQ8SJCCfqKZ6G6P/tN+IAiLZeA0rwwWNvxLHRZdheLLA9FWZ1CouEwBs58X2aP94fpflWUxADeXwcVrtkc+tY+YB2sT53qnRuM5vM1FKG/+QJmPOL9ruxVk6IrnaROrU+dUl3HlK28tXwANngsPrCa3Xkt8jg0bcikqKqK9TN7O1DHZ6zbsRVL/Wm+4LeevO199oSIoLfGgTdCDQdhTiQgGWQRLkmduvkcZn/fn8PkvyS1HlI2/upNmEennjEseQ8KkU1mQCe8YJG10Ps34XbGUG/7AKFWMXWa9fgssoy9npNu6tQePcbsZ76G8TdjSpYGBfTxBZo3eLzZ6YyzE5bQ+tRpO2SIuKkt8sMZJl/gF8f2H97juILRwbuCMVA725z1uP8w3Hf1xc/g8K/s4uCPTgKfhRsWXFqfZxy0FirCYc5SiWdTuBsxdfoHf/4bOJ/ef8kCnJ+kpQGlJ1GmXwec9YRg3/q2e+enf/eJdYigPhYA79OGRJHmnmiFip/HlizQTuj5Xfx8BwcTA5yk0f3flQaUBnnXjMW3Dd2FeIe+ne5eg+te17POqbLojEHkBVR6/yjS9fP/AAJLGSjnoqRCKNqL+ivqsufOcTsqLabrPTPqOs/gU2wT4NzYxjZ2JXshPQvmlXjKivk0sFZfeazIoZboIALXbtEU5+1Dvny+4N9lS+D7UlW5WradZaBh1AqRLQDN5qCq5LdcgOtySk8XORdGyXiJVcRUVYVgZUBaVmWIpQCAms44kNm2MbcuLmxRdAK68NsQGg2iJKAXGVJ5zscv+JxmZ4D8bMJbQAEEOebgVL6YS44xXJ34WiVoWeQcCxmUUOLqC7/IeMj8o1IVPB7yOYs6ztewglKKOTiLPLxNFwcVhmelB6P5alitQaWBaVpQWQDHSVHZsOKgoT9XVRX3VzegMu/6GXnO6EiJecg8n5zi4o7B4L7/2wGuypA1Lea3ec4HjmCHLF84u83X0FaKA5ynBrq2mLzK93cryzzkPvHKHMHujGHHBYrjKpSYN/tDnH8G2Pu/cStW7w9QWWLWdReFkZc7BcyiQAmgvuV5QRxA717dX3ghF4srqYQ9Res07KclGFcvgaZZ0Trt8H1Kfr9tAdnOkvNcFD3cxqL2fA3J8XrJmqYAXMt6pQCi1mk63mbJ/S+bTkYGiNmPVa3TOrYDMAenZ9sO++8VrdMuLkFdTCNF4HIZSueVUuF49ngaFdYTkmRaLPh6Q02EC3UtaRxCeD9V2zIXKRDccDXRgewGAPRkxueQ6/RJTQO0LVQbiYCrh7OgddqRp5wZ0GzBhMIJ87iezlnrNOF3kCpU1fS0TtsW5tTEMchxa7F9r4U56WudTjH4kBcQczKFnjHqdOi3KK4woEwhmzQwx1Nsvxvh/H3uEQAwpxNGZi4W4RqKwyl23io79H+VJeizKcs1EsF4uLdZtFDLFvpsigDbc4BqXgYOzk/aOrofKhYD9eCvSiuIshajHj1HQE9/YwUaHjgq4pdHCYOTPMwptFw0O1MdlFSzM93fB7W0XkGWaKCG05Jx9jypwInRL7DKMsAIq7SO3BXJccozKEGUCl2+oGX9XAJgjVUxKa4CIho11YOVeZc3q1Ldc9Jiu8xAWQvSJoLOALgyg0n1WgAm7hUynEQ/RTnn9VCSMQiPqxTI9SD2JLoo6XwqjXYYNU1AHFRUWQZX8jHjNVXJMVEvj5WFkVWbIcuzwJkpXBhKqQiu0tw+FVkHseqKjLMePpgJsFejZqzZymPxtSFVBqOU13eNqmzX4RX54V0sEnuShumKZ/GxdHjFIOpH1HH9OKyrWZKOp1dkl/BgxCBit2q189mPgYyF+02DnqvjVI5A5rLzPZv3RxyCov7fvWAjEHAQ4VzqnZuaMFz1g8jrjNB9TuR57Y2hP8ZnsZd3sbiuirq8zXoP8aquKsU3bmhqzeqsvQeReioqeet1mJTk78SzkHL5tHQ5tJ20Ie1KO73zlFL8hu8zJvn+V8Zu+uNKvKDgEejVN6ym1ThQx7MwHS9HhTa71xD618nffe9ISridY89DFvNCh/NTUFbg5EzbEnh5vloersQDSe+xr+XoMGJ5a0vV8bBEPEniBZRpFkuiqD1qvWdhCw0StTE/5xTuW9JXZryCW/TcXK5hB+wtBGmCwsCIWFLiWbhCA46gtVdWAzwZE65sm2zIxja2sSvZC+lZXKqifo0K9VAkJAfygoNsaYm3aJv2rV8Knv4u7Rc5UPe4E9NsiNERlDXVnFVIXVIBKRkNUrqzV+XPllEcR/oo8tA+AODUj7OOmQToSbwGa1fGToOSswxA0EBRec7HfeCt2SpRHGYho8En+2yIvPHBOAIh01F5DhiPHhWm8WEFde6vU+aiKiOprfydZRxXEg6RYQUN/xYu4/jr3Rz5o7IT4KRMww1yZPOaFdeTtzUNK7TjArlkQ8rSXyfHJ1Tq/hc57LhE5lXUw3Vrhdktje0t/ltZgi0N8rrEYs/HLOoK7YjjCvN90Yv1uqQmQz4pMbvFY7hZFpz9UTq+9LWCHZdotgsMyjKwfjc7JaavO7hhnAPOerSwVcacv96TWdzMkc0N9LLCcjfqhoiXcRV7IReLddmQfsUjE7m6Ltw7QXl2lMwAwLM8q6SqsF8qTM5HuiXoBzAxTFUF0t8wAk9VT539sw0QXrIu9NVhXJaal7YFNS0oYwRpyuNITRvqFULbyssZADGgWlVQwwraukhUK8FRz6MpX8BQQt7aSNgTWLV53KEGpebfldFAKn/o+SQ78yZrZdtGDk2R5XNVXKzynLcJmQFtjcK4yC+qalmGcamm5XnsZa/MgiJEWualNbytWDZAKjYMQC0bmHmUOFB5FklqXt1G/kDFeSi9mFEIhmoWWt65gXxCUHWsXDXE48jmFObL+HuSLXxfTgEOyGcOum5RnPvnpF52sjOpaUtAnkHvM6Tf1Bb5eQG9iOebRQG1bBOlOG43mxtMXstQHSZbNNC1QFsv5GLRL9deOQZEwtKOJGFEusVSY794eGg20krjftqVHBdlAbGdpgWdX/hFxybtLUJ6Mnw8SW265TJK7FkLlaQ85dyQMu2nTtuWU5FzSb0ynZ0igk722W46Beoarq6hBbcgmq7Wgto2wL8DVuMipkUpSWtKShPgVCDqmslnOmNe8PWuLbFeRLlFeZMrFeHnOWucqHoJWtScWgag2xZuOuN0qix4xvBY2rbDRFY9mK7MI4yBWXIaVCU8GXKtxjo4SaNfTKCbFtS2KIRnAoCUoxuppwGgrGXV+rNzbN9bsvyknKs1MJtj8IDPNccT6Irf5iPBxuQaNtfIz5cwxxNspanTNRR62dEFzLQEXUxCCjsfDTh1ehZTpyUAfTYNc6V9bEUvK1SHGuboHMMmvnhe/tTpFZiyOtuTNfMRiHD8YqKqEligC1Jaw5SltGLiE+82q/kcKEsoqQCVUz1oKmAhfB+hAG066wClUjBVGM984QVy2zjeuo6gMHmo5IteFiugLJQlVArKCl9OBjPJdWDq8RBbo9WYV14EsBQA2N0RzOkFb5HS/vy1rIPMpyAyGQttjQKrddiGSP9LFf9e8gISPjcesreQ0CACwPyVEQZecjGYMXDDkheMQQkkVbG0NYLbHkAd5mFcNBowJ8Sw6r5184yvOwVlKQWcGpx/qkDx2Ms4OmbK0lph/grPzQCAHXAfs1f4Om2h0FYKwyODoaMgKTj4RtXV9fBmd0cMyjqtwvw2ByOcvqmx881ROK++NUIJhO2ZbDOWuwVIKwwbi8Vt/wxaAr199W3IJsC5sY1t7Er2YnoWn4T1mKOeaj3MQYfFG4h6Fb0ceNCzEJ2N3vGV8Tyh/7Vw9Evy9k/M1V+hXeUiHkFy9lw0lsSPpDhrbbOxuKtTzJX8XzQvVq5nnULaGlNr5pF03JevzDERF30FePuagqz0d4e1/9e2h60g6o4lwT1o2QFY/zlfhKaednscIrWYuMqWoNrkODhoyed6L04AhQ4AKF6zHLsG/uKHa7FIH4A+clFy8ObpztYKnkG2J+k5WbaKCDUJ0s9zQ/LvqltSLeNJx9mnu1+H4OwT+6bWu96A4EyFjogDaGHLIzELP24hM3aFgfHYhXTcyqMvA/X/uvmQ8wDGLSQqbVAJXiEdt1YQbksAHKxtWo+ziOfb0mMhUsszuMJAZ2b9/6oMJsWMrFNL82OjMkF1moiraMYqYCqUVXBFBp2ZgMp0RRaQm82Q27aFQjtUyGeakZijBEW6BrdDpYEt/dj8ImQrg2abeFwyBxXXwgh6lDz5TTvQ0A3jLlwpWBO8eIS9SqlDAFMAR0879yWzfWyu+YfBnudr/hQRHVzlxOdisQAApdSfENGP/qDH8f20zTX/cNjLcs2bAOfGNraxK9lmsdjYxjZ2JXueFotf/0EP4Adgm2v+4bCX4pqfm5jFxja2sefbnifPYmMb29hzbJvFYmMb29iVbLNYbGxjG7uSbRaLjW1sY1eyzWKxsY1t7Er2/wFAf0XQZID5lQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.53318977355957 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 0.0001, 'kernel_type': 'branching'} is: \n",
+      "[[5.14721355e+02 6.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [6.40000000e+01 2.20617972e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 5.14721355e+02 ... 5.14721355e+02\n",
+      "  5.14721355e+02 5.14721355e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 5.14721355e+02 ... 4.95651160e+05\n",
+      "  4.81050041e+05 5.35794609e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 5.14721355e+02 ... 4.81050041e+05\n",
+      "  4.74233708e+05 5.31609019e+05]\n",
+      " [0.00000000e+00 0.00000000e+00 5.14721355e+02 ... 5.35794609e+05\n",
+      "  5.31609019e+05 6.64438594e+05]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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dgM8C+ASAX7P/f3/bMa4UNW9IGrsx5Ap055fauRiL5Isve0NMAhWwDnv0NEbjurwhsiK4UPWlB4LmM6Dvs/gH1lxOmMscz2dbb4h1H8oK6VKlpqMjY08hFRsdBaU6bJ/MtaLZLE8e4y9gwRvibAfid9K9+AD60ZPQVpGJ97DeEO57HwfiPBHye9KLBdSZ0a77h48Q3JvCGzWbW2/IMnxXR0foXnoR/XeCs9F4WLSRQbOo1t4BWu/kDdlFs3gFwO/ZvdcMwG8z878goj8B8Bki+nkAXwXw0zuMcf3gwpNy5z43uGeZUdzv70DNvWpkC0q14dUojSXXqfgQ0Co5xPk+HtMMfFXUjNMOmsGJM4KZg+vUCJg0GJdJl9e9jzcBAHTkx9w3aC8Xa0c8Ty/xj9HHDi1Gjm2JUbuOWcIN+J5GoST/TZK9Zkg9NA503f6YP49H/J1RT6RG925oaBiFRvd2uC7XaQliPx7t66M98wYbSWmMXenetSbbuk5L2IbuXXOdVpidkWyJK5U6ig22W9C9i/ks+j6ie2c5LlTYLnDfQ50cm7fS0JkwSM0hYc+ZzbydxtuTkmuQM2wTuveEuiG3a7HY5UZPvQ+luIFt+tt0zH+WGEOFpXzjuWPH2PX8Td4Q304Sogr9Dn1PQ2S51BviPBwQhwe9IYwoFoJtgZ+RhLea90YvV9Ei4r0hEVkKZQ+J84YsK1m9/SD575DX6ywfRnQNap6PaB7Dw0rcrsVin3u82o2wKzYFkkUy1FJBX+FedgzZy7v9atpCaQHZg/1nCmmqpJUli8vGMPHS+IU5ZJXQnBwpIYzicxy4l7L04kEhH1yFBVZ1UZxOgIgtqcW6+MErcy3gdi0WzwI2cQ8O7f0YxXcY0LbGbDe2XTSm8CA2MVmB0R6HTePnFHld0ETi7UvK78i8ImO8crqPg+BKbbfVjAtoi8UQruIJPpLvcBBPzNC4JdtBkTw0QuZd7UK18Su5OTfaIcbeUDXNoliQiHLNQtgLJFckCmdf63xecg6J/FlhZMlnic6vXJsJX0HzhjQ0NIxC0yyuG2Pp2Ify/0+hXQ+132aMbc4fuz2q9TPlnNo2ZEwltCSLb8bByqqajfg9MFeroQ3KsiXaYnHdmLINKbW7akwxcJZQcz/XtjHbylg8XnapDrJj0/IAm8YtbUPmR/FWIK03OrANMR+LWqeyn5Ida4yBs2bE3XEb0haLbbGJ9zDG5jDFhVg6tzRm5EMX8S2jFynpUSgbXQ2PYEC2sYtAqcByqfjwpjauadeZPT8QLxrVwsjJLtzbMHR5jDRE3cpGnQL3+Y4+xAG5xaHL64b0Jt8GdeZ8XiO/fpaHUwxRn8WLhQuPl++D7F3E/zBu5euJDbnb2KSKX7U6Xx2zYh0fvf0p5IBM3tcS5AyiONeSxT8df0ybIbkGeCrFWi1isck0I3FMuGHTuiGuL+nh8IurJI05ApUMIKx+T5W6ITLhD/Ldhn/vMkVMrpUixB3dsqGh4U6jaRa3Dfs0Hl7VGEP9jDTslfur2Ca2GX9TwFn6hB/SXCqaUqhYxrnrtSRXQaZs7Or2V8qyHdmwaRYNDc8aJKNz0nlqJ9Jf0yz2gSkEqrGGxm3HTC3nUwPkxpCySobJKbKX+qw9yYcC8pKnbZEcBQwYOCvBYe6crDZKuTByVJBZGEeLdUMig6NpH3lDUleogws0lDKpDupoDr1IvR9JsJgbt5Sfs3lDtsCUm2rMDVL5kUf1QcRYWd2QTQtQxWsRZcpKM06bg3H/yXxrN5w8TvOZpxln4425HnbM0lihPkmSHFjIGrWRUacyy5efdrhJovk72UmB/WIRMoKlXgU/7jqeN6/XUKcn0BeXtn9xUw7VDfH9rYHVOtQNWa+K19DXDVkFYyrNZ6Dn7oFkLZTZzP62UtlV+XWrot7wTGJqYNch8CzIeEW4uzNvaGiYhKZZOGziI5Ta1t4PHIuowdKiXisOVMOmIkZpH2n7ynyrRYaEfDJpbJXqXJAtfZ2NxT18qHepTfGYKPazRDZP019lTn0Pn/Ua5lw3vslzEdsnfJCX79eedn6eZ9hmDolsJA8iI1AZnoU+H85bEjE73bHlEvrh47zIkJMhmmuoOyIJZNdZZKgBuDkGzpKleyqDc8x4teJAu7hUa1GW6djpMWngTPNKhA9QJWelc3HGyRJLtcTgdHYTQXpyx0NkaY1RCZCyCXg2bW9KCYVIGfboOmmXZsOCYHumiYvvbKasQ2HKTTKWSblNP0PHRjM4R7TTFe1lKmoM1k2Lb+W8Ot+hFlzF8WfifWQodYtSps05BmdilHR9RBnF3Et3o8bjFmuMRLIWykLo3mhTKY8jnZccN2NwDg8r0RaLbbFtbEgtU9a+NItdY0PSeiWyjTul5qIckr/kJq3FX8gsXO69nEMtNiTN7eDaAvmcgOCO1LlmkcnuMl0Vcnmq4+MoB6c7TrO5edn34WleiA3hvoc6Mm31YlG8hlG9GT/fGej4OHhiILY24r2X19YSkR4srMZ7Q5qBs6GhYRSaZrEtair00LGh8/a1DckiiSZuQyqG0+jtWKNmrY+CcTJ8VouE2nAeCtuBgbYAykbfJO/EGLlq2oCsfO6VFWmMFON6YlXVwLnOtEmfsFfMgzlp48YVGmS05Znwu2uaRUNDCWNo0YfOl3rNaJrFbcOu3omxeTh2MWwO9ZMem2QPKuTTHLIFbUrSM9R2E82cWdiPyslogn1B5wze2vjJMeq63DhabCtk2ZJY1haL24Zdb+JteCb7HGtbDgtQNHqO9qqkxzbJMcoLc7uiTttisQ/cFJ6F7Mf1NTlTVgsky86pHXOZsq47kEx8D9MDyXpsG0jWbBYNDQ2j0DSLfeCmkLJKx8d6Q9wT/CaQsmptNpw3Kst22k+lJOFoTw1RNcN2SZ5qnuNNSYOl9iP4Ifqy4qVJSVka/juOZGikrIbJ2Jcd4q7huq9byT0+5dwdcHcXiwHrdnR8zPmlfbVjQiZ75IiJJypjuzwHWT6Lks0hZRqKORTzWTCX2YoFW0aUE0I8gkIOCUTp57Mq3bUnpGSGinT4xXwWkqUo81nYOdSqpauT43KBYbFX5yT3A7ouPqeWOp+UzT+xitvpHt3zz0csSneuy2fBq3XIIeGrqCvD4FyvwTKfxZOnRfWDZnOTz0IE8amTE9Bz96AfPhbXS5mM4Zat6fNodB2gNbjXIZM4M2g53hJxdxeLmno71ne+kZRVyUDtb8TYKl368Ud9Z+OVs3BXo06Lmaxz2aOq3OJ6RMf73r+OEsQMxTdE10OcmyzWaTxFHGEqz8vH4tW6ch17a0iMbwzWDJIRqURD+4QkpkJ8d8ulkI3DYuYiTFmLEgV2wSUCw9ywcXbvMmGK+x6UBMnxeg0slrEsfdLW213tOGnV9UbKamho2DfurmaRYpMhcNv+smP1J9fO/e+jfaoRJdqAaTKgsUySqfAUHeOGrozJQuMpbicy7SrRNlLNMuMvJHVD/Lg6zinhNB8WWpnrxj7q2cnonvarJM9Jti3WsSbm+l0uE22qrEWZUHguz3kkmmaRgujO0XgzpNfgGbkeEX+g2uiGfL9DLMqh3B5Z0+ubS9MsHPZFYR7qb+iLTRPqbtP/pvbA9DkWZI4Sw2yqpXkVqNValUloSu3TuqY+Qa97v+EmLWX8hjMqJjTuHuLaCCKUO+YXtg6Uli8swckqAsVIEdB1IBVsNUPlC12inZb8ZipqcQHbnF9cGOwPKzle9IZw+DFl90DNG1KRKfKGFCIVB+eB2Oshf0nR8a7zZfhib0ghNsN3IG60bb0h8jydP5lpPqsuIi4Fvkzb5242GQm62RuS5rPoQSfHoF6m6CeQk0ccAxCyeztvSN8bo+jJsTkuyxEm7FQoimXtOtDZGXi5AnWunQISWfz5WgPrdfC8Mbfs3qMwxhsydKPt6g1xbew4RSv+VCp1KcZg4/5/wBuSHneQ1GZ0+XmlhTSyT2jvzszGT45VvSGiH9/WekMctdm1cdckmoO95pRqIlt5Q1bxAocu84Z4r4QfnkSIuganyXMS7ankDUHfA4s4z6f3hrhFvOQNkflUJ7Cyms2ioaFhFO6uZpGRspIAHN5QMEeQcqLAKtekFNREyqumvFxGWxJ/fNHH57uw6+hprWIVXgQWSdWXl0u/T68WMUrIWjSfec1B7oOluq5eeAD9/kMAnScZUQeg76vRk1GRIrdVonlGcvKEL1dI5+jIE5H8eW4bxBRpFureqSdHBcOfAill+nSkJifTfGZIaE4up5GIYLBoDq6Aj5CXV0uoF18A3nvfXkdt5FsC6rl74XtQdn7HR34ONJuBFwvg4hL4q3/FfP5nbxS3WOpobvpdLIK8p6dY/fUfxOz//vNYRjGe+93QfAZoNr87RxZjBj3tMBZ3d7HICE0F91ptG5JSbgusxXLYso5SwUc3lt27Zp8Vw66tSpz2r3tfKSyVs7o9SVPnixs1yAJvowBgFwq7yHmRhOvZ58qU7kXpWnRtRWYrJ+cy3r5FZQdcH1EUp/b96acXganpFhbNQcVPL8EqJkIZEVyjwncabdFEpqz3H/q0/6QIsK5U/eRp1L+fD+JtCPca9MZX4zESb4lerowhU/yu+OIC8y/9BbT8Ta3WeWQpzFbJbUNkBbONMSkCd3exKGHIz37F4xZtFgU69kHhf/RBSxjkXFTtPcJIWCopMIFrUXoKe2am665ED2cGCNHCszU4pNc3NhM7P2k3qHhwOLXnhEmMG7rXyQNuqmWhGTg3o+YNkduQoR/tFG+ItGq7H1XkWrO5D1gLN15ao2LEorEPb4j0NIib2sgdtgEEe2NEsSioyyxvFunVSIx2YftF8fvEGwJrRHTXDRDeEFtPwwzNJqO1skZV780gkCKz7ZEZwbfxhpyehFiZznok1uuw9YPVJJi8J8JtCwh2S3psvCG0XJavf8Ubop67h15urdw1V/l1LXtDMBrNwNnQ0DAKbbEYwj6p31tSmG8SWIftUq7WFzJRjZn3DrJE46af9ybCElLeUlu9h+ue2INGBWc5uZij9kU5B34bPCT/PrZYAnd3GzI1dmPo/F15FiWbxdj9f9LmSngWPi5BRJ264xXuQT6Ozl7vFHUq5XLwUae5gc/PLX3fj7wxN/AsovN617c9oe/BLg7Et7E2Hzbt2PElKnJUeRYXl3F5AReOPxR1GvEsxuPuLhYpSoFku1DAx3hRJEp5IGtyDMk0hkQ2hJp1XMgde3oSjaIUU1LTMGpZqqI2hXlH5wm53AJNSZ3SGkvXhY6PDrIrXxt9uSgu7pFnCmHhAOAXDw9nd6iEqIP7fIi+L+S/cN6vVMqwCEd2ogm/79u1WOzDc5Albd0yK9G2Y0bHazEQe45jGYuh4LKUmgz5JNflG3bbOaQU+JIckaGyrxx3LsrCFmoqSotlqU0p3qTgzcio8ING6srvpCbjlvNsNouGhoZRuF2axT4QrbrXZHQcUJM3tr9OlLZohfSEmfExI8DtKH/tCRmlIqzZfAo2ip3lSbYOY1I0ShKgtFkN2HPyPixXZIx9aw+h7G2xuCk41NZiCvaZO2Ff850qU1pV/TpwCGLd0FZtS2zchhDRp4nobSL6kjj2EhH9IRG9Yf+/aI8TEf0zIvoyEf17IvqRvUk6Bvt21V3nlyuflqW/m4CSTKl8jpHonti7Gly3lanafoRs+8ZY17nUxGqGzjFjpf/3NNcxNovfAPATybFfBvB5Zn4NwOftewD4SQCv2b9PAvj1nSW8Lsh4hn2sxjXjm+pC8JYcSx5P5Sn1M5DTovj52HmpLu7D/YnjNJvFx93fkPcjNY66c0ty1wypBVnk+DQ/ErKo8OfaqyRoSnXGGFua74ZrIOVUp6egmQlK832qDjSb279Z+Ds6Ah0dQR0fQx0fm/ezGdTpKdTpaT5n91514bq7w7MZ1L0zUNeFP3sNojFnM9D8KMgnjk/5rW/chjDzHxHR9yeHPw7go/b1bwL4NwD+gT3+W2xYJl8goheI6FVmfnO0RIfCjpbian/ZsZprbIJ94ipdp9U9fJxbIWo/qt+BffuQfEWXcc7ZMHJtkKfKHxn7nVe4M8tlMQdnqGUqolidbUImDer7OAdnNoD53aTBg1EOTk8o74qcAAAgAElEQVQN53hsBwptqm7lDdjWG/KKWAC+BeAV+/p7AHxdtPuGPdbQ0PCMY2cDJzMzZemGNoOIPgmzVcEJznYVY3fUrPu79pceE8FjHsyQgUlRe/955XVpXNlvqa9Buct5JqUv36fYS0OpS5mySnJFfVbIaNITkHoFpJFSjG+CzlyTuL/MQ2O/C+o6Q+Yag9K1YTb5IZLiRqxD7hL4vCQU8n84xipzlIIvzlAec34898JeD1Jkxu57+CA/kUIwk51tdrCoMPL4bci2msVbRPQqANj/b9vj3wTwfaLd99pjGZj5U8z8OjO/PsfxlmLsGQNEowYEG8CkcwYIZw0hSnQbWxkplLJ7F7Ocj8l8vgHbfmOfBfAJ+/oTAH5fHP856xX5GwAePhP2CoexfIDUEFd7ala+yCjTs2DsZV9yzevgNJGCMVAau2IZkxu98iP12aKSm5kUBYu9yCbl5I7zXhY8E9HYItQ8Hb/rorn5eaSyFOBLBAJR0Fus/QTvQOnp68YPcoQ/ecxfY8AaCpO2isT3oMzN2gXjIuZzoxWovL+SN4y6TozjDK4EHM0TGWM50JlsZu586hLj5z4NnET0OzDGzJeJ6BsAfgXArwH4DBH9PICvAvhp2/xzAH4KwJcBnAP4u6MlOTSmGDjHLCqlGAsWgV7MyOItNvU5pf+0jxpxJxmnnOErPs7rlZd/dJxBVHndBVElWzXKUwXGgWTimH8f5qXTgC4/lMuHkWxN+j58ZnrwX0mpRKKMI5Hz1ufnxXSCfCmS6boFSxpCAb+d0+d2rEpsDq9XptyANOiu1tCPn0T5ONI2If3f2m9jZNmCwajVBGO8IT9b+ehjhbYM4BdHj97Q0PDMoDE4t0VqcCwZMzcaE3cwptbGHNNukwyb5EqTCI8Zq2SoLMnhtziUn7vBphQVP0rlrVH302DBoaCsLHuZPVfUUfFgLVLticI+ckukCERshndbkIpmFwyc8pDZ6rA08tZqqvjtZbL9mkBkbVam24htDJGHwibD3oHmUfQmFBs+Q0bwHY2cTbNwmOI63fYHQiFHJq9jEk41VX+1r3JodZQTU9oTUtdspf+ohEFiePQp6Oczn6shzsE5LZw/HkuEZgt7QUlbqLluaTbLEty4J2ogSPVRPyAFn+HaPb3dkzk18hZcs9wD6vgYWrpmnfvSptyHLUPgZAQQKpLZ71vZHJx94oKNZFVkSyDY773rQGenIJmDczYzyW0y2ZUxpmqODMGtItk2mGrg3GbBSA2Q8qPJGa5GZOJyIKobOIfkkGxBaeBcrf01mLpAVGWtZOsuzafGIOV1pYyBYC9m/VAsQ7xQiHIM5Cqo5XJqUcvDwLRzaf9Zs89cFZV7sDc/9z10mimrICsxZcZSPr+Ir9E6ZAuLO9CmBkuaAnBw1BhtsdgWG2/mLbwqu6JEJ6/t94dkGLNQyf7HnFejbad2jKH8k1nbePziQun6qF2D2nicLLBZuL1Mo9fn/Uh5xCLkywQAIf0ea5GqsH4Ni2HsydiZF8d5Q2SaP38+D39nCZ6RjW1DQ8Oh0TQLh21tFmOs/+JYZJsQY+3FZkFUtyHUbBbJfItlF5PjvqQgCjaLCd6QbCxvMwjbhpINJVR0j20W6mhuuBZyWG+zcE/Vgs1itczHl9esdA28zaKHOjvzZRPllkXZyuhcslm4/tZr8GoNdXoCAOgfP67akqAoLu04n0Hdf85XiHP980ibBQGgy2azmI5dSFlj2wyQpq6MlFVV73cgZZVKCm6SubANicaydpXUmHktpCx/YF+kLPNab0PKqtmS1qvMretJWWlpSNZhXm4b0vd2cVrFpKwJ25C2WOwDU2wPtbb7sl/U2KVj+x8jX+31VGzbT1WWDcbWTczb6P2GdHtikUs9W0V5HGu1lomg1occLw26c7Vth65BKfv5lkmo22LhcN1Rp7qPx0qqmUfyFEk6A8cdphCtHFRX/kWnUaeJy9P0PXCD1UhZNaJWpHEkbQqlEDO5UsiYFte/6jwFuipz9L5A2GKGOjmJtj9uKxNiPcQ5hahT9L13s+qLi/I1KEWdzmag01OwPMfVDSlGneo86nSC67QZOBsaGkbh7moWY3MuDJ3rzi9qEdYAmRz3hjGWUZrhSeAfQhkNOXEXTjFwMo83cA4URvbHBb1ZPqXMPr+vXFshb602BoR2kBpBxRykLHJ8XxhZjBGuhRsvXE+ykaAQWpLXCgqV14ukrPUadHoKkpXNFIHQg47moY27JvO5Hd5GjfY6KowMWbAojcb1pCxrZJ3NQGenxobkvg9HuKoVRu51TMrqm4FzM3bda29aWCqb02L5whGfFfvfRMoaY+AsnV9LP+cQ+fvTgkKVvod4CAPHNhG3os/7PqjZI8ZjzaASKYuTco3+cyrLsFzGbbVCVCZQM9jSnwhmu8LKhpr3vfl8o81CA4lM3GvQYhGxOtnJ6No6Ayd63y4uBNcMnNthCjNzjHFuwhdRZV5O6SslZY05b5JhURCW/KHCArfJPjJItCqQn4b6oXwRS/flVbLWkGybFpuh/KHus0LxZudFIe1ubnujb2DCmjkVFvFeJwsVx229LNJmMSF6TODuLha1bYhU1zdFUbrzNxkhawuQSLFX3oZIJt5I/kdkcNwwh7H9pvKSAinz9JVGPL8NSft3W4jiFiH54aZRp3I7F21D2G8b/KmdeJq64/bm8FuLLGpTgeVDXST2SReMeBsjtpCzmeedALDbtLVX97mH30L47YgzdMIuQmL7GMkhxo4o6LYNHc2jbQgUGVp4gWdhtmI6+2ws7u5iMeWpt6+xnqUIxQ3IcloeEEEWIVMhTLt47h6+46yPkiZTpaLvOL7met/RMLvPs3lDGhoaRuHuahYJr8FRiKWVu6rCW/+8a+douxI0m1tLv1AlXR5FGLZhoHhr72d3/XiV1yeakdsjFXMKBP9B0on1MngcaOYs85YPYNXclGauTo4NpRgI/noymardcXXvFPqp8e37DNYAsFqDS1snd3378Nr8V56f4K6noys7bcFTuLkP581n3jBoth627QsPwA8fGVqzlEEpYLk0IeHCNmAK/szR23mZPJgKzGzbJh6OoyPjrUDwOuiFBr3yMvDWO2JIAi+XUC88MNfx/AKYz4y8Z7aQ0MzkxsRiCX78BPiuD5hzv/rNfKsDGI/LbAb95Kn/DtVz96C//0OgL39NzGkOvlyE7aHbjh0fm4jUywXoJCTIpveT7c8A7u5ikdGCLcNObrlrqpuOc08W8y+6aMAapVtapZnjPS+sai0NlkkEpKQey/4jI5yTkzksEl5V7/05UR+uaI2U0RWuscf1xWW2UEUyF+wgUXh3P3As8cZICrccs7QN4oePRGxN6jrtM3eiLw7k+l9rT4XmpG+Qsl4L681wlGlm4O13Q75NwISe9z30o8fm/WoNLOxi6L5nt6BpDV6vod75TnZNIlkvF2C1DPlPYWjm6uvfCrRyAFitwL0GW6+Lj0m5XHgCWPRgm5BioG1DUsgsU/uyMWzMBpUbpPY6/p4gM5BnGcpL12zTvHeUxY/v4G5Am+XaBE8JeVNZgYiXsjWSPrKM2YUMVURkuRaJIbKUXX3IIGm1ISiKx0nHVLvf6m2xAGJ1uZSSv9Bum76rPwBnvU9/FLVF67pSzZV+tGRrVXSd9yb4KMZCiQPzPiEIDV3jsXK58dKbyy0Utqao3JZlN5BLlb9rGsJ0jMKNmS0goowAFWSQi8bQtaL53GfdyhYfReH4HtAWi4aGhlG4uzYLCRfIJffCtXbAflRrSSiqhiIOuCVrOTglGWmLHJwbZQYAqECA2sElV8yvWeBCDAZJyu8rCc6ybyytGhWXZmyXiOnepa1hrEWFS1L4TTjKuvyfPPmLrxOYoDQxvqN717Z5FVmICOw0w0TGMWiLxRAGyUyxd6L6i45IX+K8KI9CxVcuCV8Rm7NCrMnU6Q2ypfPw7xPjpe03JH5R4OXK3DBZCnwuj1f6TcqxxDYiypmZEpHkUCkb0RsNGbwMBj4iCrkm0wU4qi3q1H6djesJXJVo2yiKVGs4jxVgjZayepmVC2ST62odvHO2vzxJ8RzoOmMslcQuO55btClZoNw1oa6zRtuEADbhuXd3F4saRXcMySilVZfOqRyLvS2CHp1qNZLFWJShQIPO+q94U/xn+fGiNT6NJ3CuVXGzcuEJH1PiE68JgLQamBk/nluc/Cb2nGTjWu9GtMfvEZLMJItOnnBIh/GTJL/Bc1WQ4eIy8jCwXVh9Et6+B5wb1o0pvSG9Bs7P8/lI0dZr04e8NssV+MmTyMVr2vWmloiMDXExKPZ/mHKLDdmMGs05fdJu3X8hEAlCfXUcCsC3M6qvaDwlVmVPGI46DZRif995tXzDFq5yPepU+ERVLtG9EW+7fCRnQvc2cJmiwtaNugLdW8wpO1bRckxpBJHOz1KuvWahOcjj+Q+2FAAzCKvAVxGpKbLxMw8HGf7ExWWIOrVbjfQcIgIrGCq4vGaV4Uq4XYvFlDiHapYk8bQnVa09uTGQrJb2Tvq4hf0gq9VBCjZwoGxfKEZ2FrYA/qk8jm6cRT8S5bwSwQnxN59sL2Je/CKR8ETqc6hneio+1aPX7hpyfE8LHkXY7pibOLrJa1soOxAX6rUCMESpNN8p6zgpjTttGfJ9SvmiEHcSiW5ck9Uy+x3wcgn97neiRVrWPY3GlXOU/U6wOTVvSENDwyjcLs1iH4hW2msKkiptN4ZsJ/sKcBsDqZmUUt+NyeuRbfW23FqN9UZVvUsc9G5p1Nzxembbr22C64Zym0w896pwuxaLKV96umWJQqJR336Uzi9tE1wuyyQEPrKQC5tFdNzJIUOlS5myUnV+KFPWUI5P0UdUArBis/BxIhTbDDxVu/Tjlbk9ne2hG8iUlb4Xc6jaLESJgtTuYLJbx9mvaDY36fWXCa07TCg67rJjR+10j+7553ysjJkrRXk1ue/LmbLsZ7xeQ52dme4ePy4uFDQ/srKGzOrq+Bh0/z70o0dRpizudTVTFotMWcwMWo7fXNyuxWJbiH125j9P28mbFUDNdRoCwRKug7uZZdBab29SZp9dyfywC4xPGVSWybcH12nXgeyGP0pd13U+q5R3/2kOhjmbsi2yCwhvT5QKL6JHj3edkjASells4BcAE0RlU96H6xwSy1Cngo3CGv/U6YkPJPOy2UW6mPuij+fAugfdvw+Sto+ui1PlLRY2x4X2qfZoPrfGTQDnFyHA7MlTAH18vezY3nXqNN6uA156ALKeFC/Xcimo79bA6RZ44TolACibOIqgfcS574rn6SX+MfrYocW4HlS9MAVN5xDfzVAiH/+64tkAitpK1u/UDGAlGYqfq0x7MWOU3Nhi0d+kRcrxC/LS/Cg2LCZuyxIvJtXIQvRvYnB146bHABP9LKKBRYexLKXjFn+s/xUe8XdG7QubgbOhoWEU2jZkW2yyWYzRDIZcvWPOLY0pnySuNkntaV+ToWbPcR9vomCP1RYkZV0eS5+Mme2nwmGJeBQxK3PQXes7oFgrKD6hE82FdbQ9SeUB3M4x4VkAImdGH+wI64KM1l6TulNJkdm+ym1UQlOPgvuUaRttA1eN7j0dm26qtO22Y9RIX1NjN8bGhjibxdj+I1W+svUo0bSByVb5Uk5L/2OXRLVS/EiSvRpA8aYNtU6djEkOy64L/AkKJQ9ksp5SPxG5bj4PPAlh75Ap9z05yt2oNk6ElO3QGj6xELkp5DyiUgDBZkEnxybDt4OzOaXbnkKtUwCgCTaLtlhsgwMwK3MZyjdm1Y1Xo3vvcezp3eR08DR4q1ouoDCvkv3NU9Jr8TRpUqGUvVrqJ5Uzpci7NpKm7tqTbMeBXr8pCY3sw0EzkNorKrlRmclkFGcdE+yGR43QFoupKCwSpbR6Vy9HQQNIch+wTmjaAHzGbwCSQj2J3j4Q3DUFgyozx/OI0hPWNAsZMCb7dB6WshDRa+cNKVVGN22Ey9Z5J1w+iqhtcJeypGpLL4VS9ezeJTktzT5KmTdPbmFHxU81CyKoFx6gf/e9cL7Wd5juvQs20aLTdmLRqNbKLJ5b8yJMfPKXyE5IigEVohezvgtBY1k7G+hWbrO9lpGm0AvxMkkkqJuru/lqmkVaQwNuoSmnqsuuj3gfpQ4E4NyZkWah1+b9apW1NX05enpvYjIQP8mdzYL7HrTasB9gbRYBof0QepNuT3JH4FIrxu5m7mHS/LGObBxTNIvmDWloaBiFtljcBdwALs0kXBN9ebQMXpu4IdexxpLdBL0hMngD2jbEYYo3ZJcx9uUNcW2Ace326Q0pyQ3sfpNLFuc2fZXymEJ4VFI2q/d+pO85bIeEXNUsXirPk8k62ClkhbAoS5UycSkmbHzEczu1vVgbSzQ22eQ9KRQFObfMf3p3F4uMS2CNaGMMfiPo3r4/zr9cM2w8lqQP+/Nl+cGh2JBC/wAC9Vr3qFqykvlGLkMZGyLrfoj4kTgWBfXrJl29PjZE8CLksTQ2pNAGHNLf+bZHR8WMY95VSAoyzNzXCenTBSS4bc1l4MBpyObdG6q2qF1KRECvoSzdm5fLQLG28SIAgE6BlitDDXd078sFSnYtms1snREdMpYdnYCevx+5W13dlSxTlgsnSGrLUONZjED6VHU/ojFegbGZsgpj+CI8SR9ZHgIvT8Hw6s4tZcqKYjPEGDUDamoQLNGNoaO8FbxeB9U8zWdRQ3Q9nOEPlWOhbTVTViG3BS4X+XUkJbJ/JZmy1ivDy5DzHMiUJQ2rUc2XJ099sSQAvuaIvnDn9iBls4sJr5k0cKonTwvXKUAvVyC1jq4HLxbQ770f071t7RjXg1/wROGoKJ/FhG1Js1k0NDSMwt3VLFI8awxOKYdkcMptwTbZva+bwcmUHxO8Ct8mYaleOYOzkN072orJ6OTrZnCKqNNJDE4rn9uGMDNoAj2oaRb7QC1k/CaMSSpf3NJF4BDyp7gpcjikVcaK6fUL1/YmYz6PF9eJst8tzWLoaT2WlFVqEwUcbQgOi5JGijZpmPQmOcbk+DQNcxlL47prU805muSDLBwfRGZzQZ6PlPI4kCg3ae08N5VFvt8fVHZ0mlczkLJM7oeEMCaykbOG1xT1kydlO8NC2KccoawkBxdq0aZNhC3GG8OXS/TvrePvTNp4ovMJtF7bZDty6PE2i2dzsUhzI9QiP1NIVdapYt6yfGSyG7kq55eXBY+JGYNmM79C82ppKqa7G8hlMTo5iaqBAwDNZ8ZCrgj6yVNvGdeXC3QvPgD6Hv37D/352tbm8AldYG4Umh/ZrNTCaAWAZnOo0xM/nj4/NyrxeuUt8y49vfM6+OrqVv7u+ed9tinHQKROgU6OfeIY9eIL0O8/NNfCjdf34OUqLtIrbjZ1eur7dfOm2czICPgnuTo+NjLaOamzM+jzc5NN6sSMRa4v+1345DevvAy8/a7pS5YUZA2+uATNTRVyc4jRPf8c6P599N96288T87kZu+sAyapUCnR2CnaGSLtt0E+eYPWxH8HJv/uaH4vmc/DTc+CVl82xR09MmUFm8IPnzHmnc/C8A616dH/5LlY/8Iq5DH/6hplbsu1TD+6D5nPo9973xtTZh17FOx/7MD7wf3zZi0lnJ0ZGO3+vPZyemCr3T89B985C+7eEd2YDns3FovCUmsqLiFLOITxJ4jiKQqiwO1f4u0t0b1/9W/TBK0Br0YdLAcca+tGT/HxZBV1asL0VP4465b4P8QxSTuZgrU+8DKns+uJSWPxtxqxegfrgssN770NfLsxCJi3xjixUerK5iuWAnzev1uGYq9CuRXAVYtq1mwMJWndUff6td6Jq5gBCkaH12tTZEPPVTy+M61JURvd9U+xSNQWVdCyDvZ4n/+5r4Me2Yrp1nXKvod56J8zduU7PjYtEKTIPn/Ua+nKB2drN0V2nmD7OT56Cuy6qKq/ff4iX//XXoO3YAMB2YfUPFyf/+YVP4UfymvXjjRY3aJPY0NBwk/FsahY3AVOCqSqGpI0+7qnGM9ZA4l3YKFvh841yae2ZjlQKlizYbUb784cC26YgyusxQeushfSn/aSh7SVtqqgB2/O0ih/VG+bJzKCSpus0RbcVc59pnTRlFLXwCZemLRYJIpfYkB1kA4OzmLA3OT9KoJJmY5YU5VI2qZpM0WcVdmltHmJsAIgS9ioCwa4MXQf0GqTiTNFZ1LqYe7XQcFGevvjeeyQUmZuNtU2Ea28UIrDddkT0aa1DmLgMJbdh5tE1k5mykglFIfDSqzCfx54Fd33ctemF18Sd52wqREC3DqxKS+lOUwsUiyATAUdzH+puro2K5+8S9hKBvQxXRPcmok8D+K8AvM3M/7k99o8A/D0A37bN/ltm/pz97B8C+HmYK/33mflfbiXZdSPZp5s3Q56TYc0ipNOXfYgnf5RohbPkJ4GpF4dnR+OVGJxRyPV0BmdktxFsRZ93AQCW4jrJGp+aq9csYj/6RagQrCXYmeZ9zjYMYdgwYeLu8+XSGFrTwa39gTgJte97ayhNvR5AGtbOWoVao1E7gJ+eQ9Ybde2cQZhX6zwew123vje2G2vLcPaa3CtkfweS3bpegx89jtPqudqpTh43bt/DVZePrs+evSG/AeB/APBbyfF/ysz/WB4goh8G8DMA/hqADwH4V0T0nzHvWjj0ClCKiZDp+dfrumahuqhdKflNIPDo6JivJXG5iOJE/HFfCsDGSJTS4vlYDWek1Vn/AIIRUno9ZN0L1pGXBbCeCvfj4/A0pPnMH1fP3TNeBRXXKTE3X1mdjghNNmELdZ03SLrr6Wp/uMVAnRwbD4uIn6Gjua0+HqeIUy88MDkbooGNjHphrrcsKUhHR6DjY18KwMeKCCNl6JyMp+bCzceMqxcaeOXlYMxk9iUH1IPnzbGn50YDYAbZ+iDoFHjWgS6X4CdPgA9+wPS7WOTZugHj5ZrPoB8FN6u6/xz0h78b6o2vh23I8RGwWEbxMO44r9fgxdK0ceg3JN2RMmxqwMx/BOA7I/v7OIDfZeYFM/8FgC8D+NHR0jQ0NNxY7GKz+CUi+jkAXwTw3zDzewC+B8AXRJtv2GM3D1lGJY63BsDANiRuVzTeFXIOsMyZmBgjue+jiMmsKlhqUJPquicKcZyT0ckpXaQycIs5k12SkcJnsQbjVfc+sY+lLmTJf5HXw7lkC1sTrNbxcUmO8sFra5+4NtoOnF9kKr/REHofYBWJ1/eGXp0FhxkbR+Q6ZYrdv3KOj57ExaJ7ZbYWT8+DvImLGJ2yHBjj0iXnOo+2wWIb5LZYclt2cYnunUfQcmzAZu5K9AB7rrl2yZZpJLZ1nf46gB8C8BEAbwL4J1M7IKJPEtEXieiLK5T58NcOa3QsUnv3BZdPoJAjMfqRq8QgJo2XlOdPyPovGEzHzCuKZ5CyyHOVkIPI/22ka7s5uD+fH1Ncd/c/bSO7iXJCiNfzWYjBcDIBwYiZXhMSBk4SuR5sWxJ/IGXiLoScsFwJms9NP11nro37Lo/m5o8INJ+Z7Zc9RrOZ2U51yvdBCR07um5dl+WuoPkMfCTGttsoKBUdQ9cB85ndZsV/U3JbbLVYMPNbzNyzibf+5whbjW8C+D7R9HvtsVIfn2Lm15n59TmOtxFj/7DGvWvJiJRqHRlNOTEWyifzTcgkBcC5DN1fpOkU3XQ6/tsH5HclNTMn08bz9yDHkCF8rAExumbJ9Rm6Vu68KWNtia22IUT0KjO/ad/+HQBfsq8/C+C3iei/hzFwvgbg3+4s5VWgkvQlSkIzEJkpXaxRtiUH59ITH5BIPOKzQgMRzZwlHVtGf6auWuEylBGaMrEJr9YhalOMFeavY1exk9v77EU05mwW2IDHoQBxNJ7rv+Sak/I6Q+VslsgDn2DGJ6CxbViH8zCfg7ACM0VaBp2dxuxEwLgS3Ti2BqnHfG6e7o716p62pAGlsuS6dHQUGaDdnPnBc56ZGdyuCMZMzUajADzVmjsFzDrQxczUiH3hvmn7zrtF7YKOjkwfi0W4jsfHWL/yALN3hEnx+BikOcv6Taen4NkKdHFpqN8O5+P1hTGu098B8FEALxPRNwD8CoCPEtFHYK7VVwD8AgAw858R0WcA/AcAawC/eCM9IQ0NDZOxcbFg5p8tHP5fBtr/KoBf3UWoSRgTQLbpfPeylJ+wFLRmGos25dU5JlZZuDRnKjwV2blC5Tzc3tv2kWoylQErx0aQsoR8Xi73ucvfKGwA7nWoom59+JX8FtImk6Z8S8eviioJRkqZojnSdTvrgpzyuJXf2BPiEG2az+PrOZa4JD7Xp3MT6wEYsthsZly7zv7TiWvqjs1n4JkC+jkwm4HnXZhj6fstHCMirJ6bYSZLIioFdnEn5oCXNyKt+ROGpynx7DM4t1woAk+Ch38Yhf5HGQol28/dNGoW34jJ51PyC8gfVZTPJfrhxF4BOW6tXmmVpSiOyy1JlvNygi0iGkvJhYBCbp2uy0lW8maQSDgfoW0SgSnFlZHIjvnIHC+OgDUaquJCx/MuyCPXyplLdKOCbPYYzxT0yRydTUuoT2b+dMf3iWxnRCArkz/adehP7YCurYuIdt+d+w10CmD7mYzInbBaPPuLxZbwX4T4QRRjHQqai9xT2wN5/wW3JHQSPZpoKZFbzmeYTuR17/tCWnfWETlMysmJiyxzzbrj63WQKxgyYrmtXYWZ/U8tMihKSnU6V3eeiwT1VO3ASoQwMss2vo9ee0YimQ/M8cXSULudncLBugszI3LfR7cK9xqken88umbMJkLVhe0r4VZd9RGTFUTGDnW5FNfUnndh5ertQrE2jE31JNhS0ocRKQKWK3ONJYt0sUB3oSPbmHOxeri+Fkvw2rpOFzIfyfjF/c4uFhlHoVRzshKiPopnkda/dGMsw2v/k2Dt80xEbT2fIqaX+4pT18Sz8PRqN97Fpf/R+twXkrJeouLk6E8AABBTSURBVKMLjgBBbHFK9Glx7SKeheNnLJeBZyE9II+fhMUyWngNBZoQwrsBuzCdXxT5JJws7EM8i+4v343zeHRrw7N48sTKuwoPJbcAucWMtWFVftsYKbXMgSI4KDWexdkb78S/nV6bPBxJbAhWLvHN9jyLZ3OxqCW/cRixNfHWbPcDns9ir4SnWutsLBLBR6z7OI+j69/1kya/sZZo/TTs9/lyAXV2BrBGb28+dXLsk6BEyW9Wy0BLTpPfdF2S/MZY5pk1lLXGu+xNPvlNUoJAnZ6EG87ToOPkN/irfwX0xlfNZzapDsFqHJIgJH70kkZO8xk8Dfvc/lhryW9OT6DPjcbkk+YcHweik9x6fNcHoJxnQKrhqgPOzw3XQeTKVGdnJqGNo5wnyW+okPxGJclveL3C6gde8fkowCbHJZ9fBAq3TH5jvR4876BPZlBPzELxn/7+DwEAfvDXLsI1lL+d5+6ZPvre59RQLzzAn//Cq3jtHz8NW9l7Z9XkN1RIfoPl+CWg5bNoaGgYBZoU639FeJ5e4h+jj+3e0ZjM3JvOdZBU5X3JEvElEvUvPV7Lmi21qCIHpKJhjb02qivvY6WxUxjfZCEeL2ttjoW+ohygEkUPVGLhT7t12lLBAF3aKvrM32mtkRpkqjshpzo7i/kbTht0niKnpQK5RwhmO0SnpsgQX1wEA2dW/IhENDJA8yOjeYnsZkUZARs23/u+Hb6w/gM80u+OsnI+m9uQq0D2g5zgUxrqLzsm9vPRDVy5sarh6AOswSnHa+NlMibh2mlMxyaW4aYQ+ylyV8Zy8TJZ3gzZPjMaj0hJ4KGLbTJbhi1QFEeP9vFC6pIHuYXX2X6cMbdkvPb2K3tovYK+QGJHEePI8bSwRWVpDMahbUOGsK/U9C5xSeTfTl4PJbSRfVwnsmQrcXxK9pl/mcR3XKXcMtYkOiziOgrH5fu9yJCMMe60AndC8Gtq/UfHh2J+9lxa4XZpFvvYUkVPuz2RT0dtB9KnbUWjqB3bJ2rbm9ITvaCW556XQl+7yFXSUoBo+1PLypV6M5y3aCeUoosHPs/asfbGzJAkGflvoTRuLZapts3dAU2zaGhoGIW2WKSQ6v5Vq/1jthalz69zO7JJxsIWoHjuPmQeuxWbkGqAHBt0F/nGPLUHQgKqNP0xcm2a49D3MxG3axsyBel2wHkBZHTnkBrtDUe9OTet5OX6i+I9OpHGbhWNlRb7ASnTZ3qzpfImx6Jap26MQvo872VQXZgHYAompeSqJI2fOpqH+hl+PPt57brZKNfwGqBZF6f5A6Jx/Pv1yhpJQxtHnIrsD6enWd0Q6gDq5jZNooqqqfliTZ4a3vm+S14Fms2yefN6BfXgvi8+FNUNsZwXXi5DpK1Le+gWqeUKvFyCnrsHAOi/87793cRjq+NjEzW7WITv4ewM6sUX0H/7nUhGXq8zWrorxsTLZcRupYs9Rp02bIda7EUpwQ1rbH5CDPVfSwZTPLFiZBXnEzu5QtCbPG6SwKyz8YgLofoFeb0RTxQylpm7TT/s38PmIU2ze5MSizvsDaGSEHUrL3qdx5QoikhdPpBQ2+A5+f355DeFec/noYiQdLkL16lfVC05znSpPPOVLMmr+rvpOpPsRrA1qevAJ0dxPJBLMZDGsMxnIEc2k+Hrly02ZDPSp5/TDMYYNVNXZyk2pFRzUouEtpzEiaR5GHRiJEzcjMX+kbrr4LWbutFR5MywTx45jvlHMX1aPN2yVHoVSHm9EU/GNLhukhwgEf1cpqbzbcL4+snTnDNBKknNJ1yPy6X9TMjlFimZthAAiIGFjmVw44qSgqFzDf0o9OsXOnmzWw3Epf1Lr1PU3WJh/kTMkD4/B73ZR1RzUsvI4OkfSJcL465drUHiN5LGDA3hbi0Wu4azS2yy9I/hDYzhGYwdv8CHyD4b6kd19S1EIQBrJ3mHrPzpFoDjxcwKUB7CbVdiYevfe4nf4mjTXZdxSOJ5h3aypKDsWy5c0WLojom+0/KSmagiSVC0lRU5RKNxsve92QJxUmag8SwaGhr2jbulWQzxHVIDZ2qwlEgNnHZPLfuj2SyPUHT1NwCf8g6waqqrG+LS6llDlTeeSnlt3ZJoa+GOi/2or8atRYDcBgOnq/4OIKZ0W7owYA2Jrv5GWjekErXr0uX5/iyhyG2bvJruacnWljGfmTZiDuba6vj7gq1n4qqyu3FtIhxersx4YpvljIaumLSfp2ZjO/FbHBM4SEcnwWbgnu7LJWYfetVUlXdztuH36r6pmO4quAMAXOCdk2uxAF9cQr3wwFzCt9+JDNNe1rMzG3h37jWW7sHzwAc/AP7mt8J8j+ZmrvJ7scfR9+CuM68BU3fl6fi6Ic/mYlGLOk0Xg4H4jrTojjo5Njewi858+jT3aLhMTbN5VGRGHc19NKdfLE5PgctFtF+loyPQPWP11o8eBcv4xQW6l14Er3v03/62b8uazc2y1JG3hOYzc+O4ilfCS+Gs6gCgHz4GdQp6CR8d6m9Y63Xw0aiXdiF47l7Id7Bc+h81nZ35/fbqr/8g5l/6C2Pxt+Ox1sDFJXoXlQlAJoug01NPaaajI9Pv0Rz68RMvDwATBXp+EaJO7z8H/fiJuQY2foLOTk0xnl6b78tVYP/+D0F9/VvWiDcP3xmzCRc/PoZ+N+SrpPv3gZcegL7ydfu9zkAnxyY6dj6LPCvUdaDn70O/9755f2KuZ//eGu987MN4+V9/LXz/R3Pwo8fQH/5uAED3ziOThZsZ61fMorB6bob+VKG70Dh74x38+S+8CgB47VefmEJGisKWRRHUiy8YY+abfbB7fPAD+Nz/+b/hb//o3w52l+fvQb3/OBhSrYFT3z8FLdZQDx+DH9wPX8xXxi8BtyuQbArGaBa1vW4arFVqVwrIkvtNsYh4zUKzd+15zSR14UltIDXaUVwhLNI8Eg0iC+0XwUkh7iPRBNw03NOedVmzKASSuYpvvj97PTLXqYuVkLYDayvwLj+ZDFkkAqaTY1vpTSGrdWq9ISzqttDRkXGHuoS9UjYxf3+86zJNiNdrdB/8IPixqISmjFE1c50yh6e6u26awYtFeIi8/9D/NtL0BtR1tjqbuTbq9BTqpRfNAiZ+A65KHrQO18FpbNIzA+ALF/87HvbvjHKJPJuaxR3AtZQjGAmfQWxsVqVaO5F5aydIb0jhOjGzyc8p3hfbXsE1TrOHDULOI/k/vuo8lx9o+yhxkKAZOBsaGkbh7moWad0QRWAd1wMZfb40cLqPXSFgqYor8raOSF1Hb20DBF6FtqGcntx69PnnIs9DVMfDjyHqg7A0JFB+HToVuduk3J5UNbPbEIqT2nItk7hjX5JTlR0TMydlkc2M7Q2czjAqikOb4sXkDZF+Okdzk1IOiLYhLt+n+R/cmdSpmNBUNXCKa+u2drLmy9kJ2BpWyY5NWvsCxGzHAhAMnMokzjXp8nTIXvXwcfEa0sxWFFPL8D0czcHP3wOccRUQDFHl5w7AEMT0DFgsvP0KrIFFI2VtRilSMI1WHFIjIztCjZSlI7sAaw45DxN/dzGhbpT/Ih6vLGecsNefxyIyMTUMJzwDTxISY7JWphCOyIGZeXrcnKMDHH8mCFh+sUvzYqyTWqfrAinLXwMOrFIAfLkI19H9d4tJWqbAzhWubquVwS8QfWqz0HGCYZ+vk8FPnkbX3Vdgd4ZiUXuUXHSpswP1vfncGYYLVO9wHeIIU16uoN5/DJ1855Lu7Vtbpqiv7+owYSt2dxeLMRgicW3SLHzNkPrKHQyciK3fcvxJ8qZBQ2XZsnO8ECjSvVN5oUSt1ZTunQ7l8pYW6N51efri+410764DY5VR3okoWyh8P2mdkihpTPKdyjT8sj/71AcQjIq9FlqkEtXUZq6z0IfVMuI5I9ZKS0FlXWfqpjpjpu3LlzSQsncqVIyTsk74iTWbxRCu01NUzElwACPntka/2nlXNYehfeKY/A43GVNlvQJjZglNs7hu1J6qhYxOzFTWDHw+xvHDjrbFpAFU7lx5vBKAVix8NqSd1cKzzaDx68I1yCbj5ASQFQiyJLCifMJtGw+RtJcaVdQFxYWQiIbn5uR38lJaJayg7diKatn37iqtDcmSyBqdO0G1aJpFQ0PDKNxdzWKMN6RKyhpRRd1Z/1NviN1PcmRfEPU7RsobeRdkFfUurP/cq1hDASLPSamKekyeSvJZuOPzma8hEpHA0gS46dNSekOUIZClJCfqlDdeuvcyiMrLiN7YLToV+AzHx6DLRbxft0Q17vvsqUsuXPsiyOg8LcZIKRorCl4gJycAXpOpyWGrqLt8Fuh77w1B33tbhWOhgsiUFFwsDWPU1XvpOpNcV8wXsF4izyq1v9mjOfT9U+AdwVuZz4yNqIv1ADo5MYZUrQMxDADOmzckoBpxuKU3JEtia91t63U8VsGqzdoSdrT9TLoxdUmeujckIzbVktY6w9mmpK5Odh3kjhYNcTwmRRW8QrXr7T+3WxYS2ay8Wq6M+88npHFFo3U8pvu+5A3tSi/K5DlugdAMTvVorePwdTXzbk/1wgPoR4/DeEosSg7zOWi99tW+3NyZyCSaEUWgPFFrtvJygWempGDfh7DxQiU70y2bfBSKgnu070GLdewl0sa9m30DqxXw3R8EvvaX4TfMjIHHU4bbv1iMNbClTLrB/sSiwiwoxMKtlboqAaSuTdmm6PIcEkP+qJxMWXiyKDuYyVPOcxHVUJVuTVlzdClyJqTzqYVY68K1kW5aYrOAJGUDodmHnsvzvOtU1JzlywXS/BpMys+TOH5wmGA08X619otQ/+570aLp6d7SrWzl56fn+ffX9+BFqHXq6fSWWu5cp7xem7+n59l1iuZhKeNRfo+ug3r4GLqUa8QF/Xm3vQa+9pe29KP43TTX6RZI6yxscDdu2oYUXaeCNBXFhjAVokKHXZ6e9AVg4zakD9sFV6C3vg1RiBYJCA3FykZHR+aJCmQFiJnLmtzYTFlefh8bYtuITFmOIJa5Tk+Os5vWBcJ5AleUsk/ZiNSlv6Z+GyK3SB38NsTfhP77AujeGchFs7qoUyBsQ3RIa+i2G0Rk3KW2mLMjZdHjx8WvnWYzEx+yWsekrAf3QY9CXAodHxseRSnqlMiM5TQTYBIpqxk4GxoaRqFpFteMWnDR5OjfK+INjJGv9nqvcnim5NVBBn1l2MBd8IbMQ2KITyJIWuGz+jZxDO7uYrFrbMiY/mveECD3hiT0XL+1cduRlDFai8PYVWzh9ZD9S0+CZwOOjQ2xbdPYkIw9uVE4cR5zSKzroLr8BnYGUrUue0O6Luc11IbvOs8EjcaZiaztfe9ZlH6rolTwhniDswI6BVor8/msE3MsxIZ0Xba1wHxmzpOydB1A67DtcdfHbaG6LjF2j1/wbkQ+CyL6NoCnAN7Z1PaW4WW0Od8F3OQ5f5iZPzim4Y1YLACAiL7IzK8fWo7rRJvz3cBtmXMzcDY0NIxCWywaGhpG4SYtFp86tAAHQJvz3cCtmPONsVk0NDTcbNwkzaKhoeEGoy0WDQ0No9AWi4aGhlFoi0VDQ8MotMWioaFhFP5/19avW8bLbZEAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54822470>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.04246377944946 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 0.001, 'kernel_type': 'branching'} is: \n",
+      "[[5.39923351e+02 6.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [6.40000000e+01 2.26286719e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 5.39923351e+02 ... 5.39923351e+02\n",
+      "  5.39923351e+02 5.39923351e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 5.39923351e+02 ... 1.84754980e+06\n",
+      "  1.88625904e+06 1.26776199e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 5.39923351e+02 ... 1.88625904e+06\n",
+      "  2.47509642e+06 1.67138523e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 5.39923351e+02 ... 1.26776199e+06\n",
+      "  1.67138523e+06 4.92046399e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.48682022094727 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 0.01, 'kernel_type': 'branching'} is: \n",
+      "[[8.75323400e+02 6.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [6.40000000e+01 2.95268475e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 8.75323400e+02 ... 8.75323400e+02\n",
+      "  8.75323400e+02 8.75323400e+02]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 8.75323400e+02 ... 5.57450768e+11\n",
+      "  3.80123538e+11 1.52414569e+08]\n",
+      " [0.00000000e+00 0.00000000e+00 8.75323400e+02 ... 3.80123538e+11\n",
+      "  6.89086075e+12 1.66210825e+09]\n",
+      " [0.00000000e+00 0.00000000e+00 8.75323400e+02 ... 1.52414569e+08\n",
+      "  1.66210825e+09 5.32022402e+11]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.08420324325562 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 0.1, 'kernel_type': 'branching'} is: \n",
+      "[[5.42189385e+04 6.40000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [6.40000000e+01 1.07245729e+04 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 5.42189385e+04 ... 5.42189385e+04\n",
+      "  5.42189385e+04 5.42189385e+04]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 5.42189385e+04 ... 8.25017677e+33\n",
+      "  2.94209901e+30 3.83463881e+17]\n",
+      " [0.00000000e+00 0.00000000e+00 5.42189385e+04 ... 2.94209901e+30\n",
+      "  2.31563720e+37 7.07724521e+22]\n",
+      " [0.00000000e+00 0.00000000e+00 5.42189385e+04 ... 3.83463881e+17\n",
+      "  7.07724521e+22 1.63659022e+30]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.54347920417786 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.43366876e+011 6.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [6.40000000e+001 3.33543843e+016 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 4.43366876e+011 ... 4.43366876e+011\n",
+      "  4.43366876e+011 4.43366876e+011]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 4.43366876e+011 ... 9.10740306e+105\n",
+      "  4.00003678e+084 3.69541495e+050]\n",
+      " [0.00000000e+000 0.00000000e+000 4.43366876e+011 ... 4.00003678e+084\n",
+      "  6.46259407e+112 2.00383323e+067]\n",
+      " [0.00000000e+000 0.00000000e+000 4.43366876e+011 ... 3.69541495e+050\n",
+      "  2.00383323e+067 5.92939736e+087]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "../pygraph/kernels/treePatternKernel.py:187: RuntimeWarning: overflow encountered in double_scalars\n",
+      "  kh += 1 / lmda * kh_tmp\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.68400287628174 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 10.0, 'kernel_type': 'branching'} is: \n",
+      "[[2.32266257e+024 6.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [6.40000000e+001 1.80503662e+044 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 2.32266257e+024 ... 2.32266257e+024\n",
+      "  2.32266257e+024 2.32266257e+024]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 2.32266257e+024 ... 4.18098008e+246\n",
+      "  8.24830217e+183 2.19043622e+112]\n",
+      " [0.00000000e+000 0.00000000e+000 2.32266257e+024 ... 8.24830217e+183\n",
+      "  7.37111057e+252 2.16185748e+148]\n",
+      " [0.00000000e+000 0.00000000e+000 2.32266257e+024 ... 2.19043622e+112\n",
+      "  2.16185748e+148 5.42577611e+192]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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BIISwABBCWFQg56nag2pLPV27l1ymkQ+qIbf9NkjZeplnATQY8ywAVI6wABBCWAAIISwAhGQxwGlmb0v6p6R3UtdSs+Vim5sg522+zN0/Glkxi7CQJDM75O5zqeuoE9vcDNOyzXRDAIQQFgBCcgqL7akLSIBtboap2OZsxiwA5C2nlgWAjBEWAEIICwAhhAWAEMICQMj/AAhJrhJBNDbbAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.61891841888428 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 100.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.16282366e+039 6.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [6.40000000e+001 4.07095168e+076 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.16282366e+039 ... 1.16282366e+039\n",
+      "  1.16282366e+039 1.16282366e+039]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.16282366e+039 ...             inf\n",
+      "  1.30640754e+297 4.22243461e+184]\n",
+      " [0.00000000e+000 0.00000000e+000 1.16282366e+039 ... 1.30640754e+297\n",
+      "              inf 3.36117839e+241]\n",
+      " [0.00000000e+000 0.00000000e+000 1.16282366e+039 ... 4.22243461e+184\n",
+      "  3.36117839e+241             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acda90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.80231475830078 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.08236296e+054 6.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [6.40000000e+001 3.49486987e+109 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.08236296e+054 ... 1.08236296e+054\n",
+      "  1.08236296e+054 1.08236296e+054]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.08236296e+054 ...             nan\n",
+      "              inf 2.78569458e+258]\n",
+      " [0.00000000e+000 0.00000000e+000 1.08236296e+054 ...             inf\n",
+      "              nan             inf]\n",
+      " [0.00000000e+000 0.00000000e+000 1.08236296e+054 ... 2.78569458e+258\n",
+      "              inf             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54822470>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.93578004837036 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 10000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.07460113e+069 6.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [6.40000000e+001 3.44181981e+142 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07460113e+069 ... 1.07460113e+069\n",
+      "  1.07460113e+069 1.07460113e+069]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.07460113e+069 ...             nan\n",
+      "              nan             inf]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07460113e+069 ...             nan\n",
+      "              nan             inf]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07460113e+069 ...             inf\n",
+      "              inf             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.89046478271484 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 100000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.07382773e+084 6.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [6.40000000e+001 3.43655800e+175 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07382773e+084 ... 1.07382773e+084\n",
+      "  1.07382773e+084 1.07382773e+084]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.07382773e+084 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07382773e+084 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07382773e+084 ...             nan\n",
+      "              nan             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.41592359542847 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.07375041e+099 6.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [6.40000000e+001 3.43603225e+208 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07375041e+099 ... 1.07375041e+099\n",
+      "  1.07375041e+099 1.07375041e+099]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.07375041e+099 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07375041e+099 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07375041e+099 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.1308228969574 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 10000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.07374268e+114 6.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [6.40000000e+001 3.43597968e+241 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374268e+114 ... 1.07374268e+114\n",
+      "  1.07374268e+114 1.07374268e+114]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374268e+114 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374268e+114 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374268e+114 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.62979054450989 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 100000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.07374191e+129 6.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [6.40000000e+001 3.43597442e+274 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374191e+129 ... 1.07374191e+129\n",
+      "  1.07374191e+129 1.07374191e+129]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374191e+129 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374191e+129 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374191e+129 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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6n8fWp6n9rMv1pb5tOnB0jdHDF2QuGYtadcyixs27BMvBhKOzVDby0OeaAMu8H1JZvWUhCFsHDmDvAv/3MXy4LITQb4rU+M0PX5umPg/98PFseau2LARBKMfq6yyAsqZiyH9v7bfHElNsVJsl1lnUigeEGKHOYrVuSGwlW0yAM3VOQckAZ635FTZqBThz+7F1gNMVGG4V4LS1kRvgbPJTAGtj7szYGyel6o/zXerbKjbTEdtmzHe10GXGyLftm9PPtgcxpFvp/grdNyXlrXawMC2F0m1z5XPaKTk3JLcMfOS5ISFy54bktq+3VXpuiNmm7W+OLJOYny+UAKcgCCwWFeDMLaCpaTL3mIiVgi/+IIThzDheEqtfsDeG0iavK0jWm1H1isHmOvYqo+dmH3rqllvtGYu4IYKwCWxt27ezbIqpiTKaCIIwNK5ZpxFRiNW7IVxiJ5KlmIK1J5LVzDLYKDmRbG6HE/GvWWeRWvexpIlkug4xv6IuloUgCCwWlQ0B4t64NabrtpwSzNHFxPUGqVnzkUOporYSpLz1WwU4XcHf2DZMYn7rdHGWRc6Fmadh18wSyFRvoSY9763FWRZAmdHcVWHn82ljrRouNvmuCtSYuIpNH66FEaOz7TtuW6kxH267rjcxJzXKjSPlvnxiXmAlyvn189mIiWQlzeZQp9euVzAnBvnkjlI74dNjBB1Ll8MLC3RDBEHow2Iti00n1qIaMY4yok46NWdwxlJCtu18YqaoL96ycOXnc9or3aYwBqNez1H1Mlm8ZRG7DkVs2yHft9fcBRuuYKhPt1EmwLkmaLXuW19AtFeKvBS2oLkUZQmCUJzFDxY1XYalmIeC0ILFDxaCILRh8YNF7ZiFIAj7LHKwsAWaYl0GTll2jhtSaqDRB8MWg1eujBEHWJdOrXUdsW9iWGy5t05KRoIzaYi7WlJK+yXoWe5dilrl3in0KveOQcq9F0jv1CnnptV1c+nXMwXou/EldXo5JS1V/Rw3qihLEIQ2yGAhCAILcUMS0c3CHia8zTy36WFb7i10TCv0cxgxCKn3melu9lokqMTSDPo9EfMjQ8MPFtybPHWdB9exKesnphK7nkGKH1/65i6xiFDNB+7Y9nEAwO6lU5fJy1mZq5a+HL1GmEg2/GBhw+zclBtXHwD0mvlSa0iEsimhdSs4x9WA25ejV7faBoneOtsCpiPoxUViFoIgsFikZWFzEWKtC3NfnxuSqyNne2p7pVnKWy4GM83dWw/z7956cRHLQhAEFkHLgojuBfA2AOeVUq+Zth0E8M8AXgHgSQDHlVI/IyIC8A8A3grgAoA/UUr9R46CMYGdkgGoVjECQVgKHMviPgC3GNvuAnBaKXUDgNPT3wDwFgA3TP9OALi7jJpX0mquxGiyUgexEQNpo+ljYvZZbxemhGtsnk/R1KlS6hEieoWx+VYAN0+fPwXgSwD+atr+abU/4eTLRPRiIjqslDrHVYhLy3LbljcJd6Xx3qnTEoyok85INSkjpE5TYxaHtAHgRwAOTZ9fBuAH2n5PTdsEQVg42QHOyYqInrpKRCeI6AwRnfk/PBstV6+qA+ou2CtuSB1a65PbZ7X05da1DO+GOHh6di+I6DCA89P2swBeru133bTtCpRS9wC4B9ifoh6rwEiuQUtZoz3wwubAWs9iiln8q5YN+VsAP1VKfZiI7gJwUCn1l0T0RwDuxH425PUAPqaUuinUfux6FhxqTm12TaeOlZ8Td4kpD4+R5Zqi7drXN43btW/uOgxcffTttuNDJf4+PV3T61PbCvV77HQALjHrWQQHCyL6HPaDmdcCeBrA+wH8C4BTAH4bwPexnzp9Zkqdfhz72ZMLAN6tlDoTUqLWYAGUD0r5SrhbUvqB67GuRWqJfi1S5o20Wm8j+77b2sbuxZNXbC66+I1S6nbHV1c83VP84g6OYEEQlsUiy71roE/sAeKXe+Ps7zM1bSbxKGlh1z4c87kGsWXSvj6N7WfXRECbu5cyczm2D0OuYEmLcfXl3iMFJ0dhjoovRV9hDFZvWbT0wUcvMppxBefWytaBA9i7cKG6DB/bN15fXKavTVOfh374eLa81Q8Wrcz51rJy2IQBQqf2QMGRcenb3y0u09emqc+bX3oEu3t58lY/WHBpsVwap9iKs29rYvRugS4zd6Jhqv6u+FZItxorlrH+3trOlrX6mIUgCGVYvWXBHclzsiFcWaNkQ2JjFpINuVK2q401Z0MW+YtkHGrdxKEHp/UDE0tMZWJtll6U1Xvm83BFWUunxYVsEe8oSU458aZjxiQW0297l7KbWKRlUcJq8FkIvv1i3JqatJr3UpMUkztXXg2rqrZe8z65cm1tPIp/x8/3fkqc4yXAKQgCi9W7IbHEzs5sHavwYbOCQrr1mEDm02OmRqA3NpjbKnDYypozg/gAcDUdZB8vloUgCCwWb1noo2WL6egzqYVBNUkpAhpZd9/23nqM0m8xWAPxxApXAFjBYNELcUPK0sINidWjlRvSCnFDBEFoggwWgiCwWOxgcWxrnBW3W8rilg2bjLh+xWj6mJh91lPfUtfPbKPF6t7dMX3GGg/z7N+NtIBOqq88om89ok46IwU1S8k2YxYtfmRoGOYTr/FAj/7mE4SWLHKwKDHK1nYtSr4J5v9bznNJPn77eCFNyjF6WnYpLHKwEAShPYuMWdQI9JSmVPs13SyfvOTjL50qpEk5XOfU2s1culu72FmnuSadWXzjChyaC5vUmHVqk28roAnpOjMv1qqvwxg75yVGZ9t33LZMfXyL68b2qXlMaNGf1AWJWsw6temYs6bJfPxGrGdhe9hLTDG2rXTU0goJpeo4urRYoNanR05/ldI9te96MKpeJkNbFpwBoNbaFrYByLd8GqekmoOtfVt7nDdciXLvlDUTuG363pK+t3mOTqH2U8q9ffdFSA+brqY83zUM3bshHa6mg/i5eoY1QWTowQJw38wuN8K2rw/fxbWR0rbt+JQbXj+uZmS91Zsu9hxyzO7S11Yn1YVIdT9i5fraeFSdZg8Wkg0RBIHFImMWNisiZpQ229D/Tn3zh9oPbU9trzRL8Z9jiLUea+th/t1bLy6LtSxKFilx1nwYpYBrlLkhJfqj5gNS4pqZfdZ7oCnxAjPPZ1VzQziBnR7ZkJgAZ4z8nH1rBDhT9EghJsCZ0p5rG3efkCWaQ+tBKFXe8AFOG7UyILb2XDdxavulqGXptLxxWw9QIXO/doDTJ5ebJcmRKwFOQRCasEjLgkOtFKMvHdqS3Oo9V3stz6XEm7EkqfUwLfos976jnR08/KvPXLl9Eyo4S2PmvWPrKTj7+9wnWzam103I3SenviWH1NoYV4FXboCZU5TFDUynuGbc4rFcZLAQhAiWkOK0srWd30QBNYakVL2Er22TkYODOnMKrfeN38N9y2FOx/bS+9jWO3DL4TvSDnb81mnMSlmrj1kAZW/KkEke40bkmIi1S5/nfUM6+Exg176l4y0h+aEpAyl6ufrR1hYnCxO6X2OuWcx5xMQsVmtZCIJQFolZVIJjLYxohqcE+zjH6t/VchFd8mO3l5Ab0zepusSclysbEoMMFhM52ZAYGTOjZEM4SDbErYPZxrDZkKtui2rXxqpjFq2qHF0+pkv+vBpUi5iF7SbmtrvJMYuYas/QoLCWmMWiBovct0CpwcP1hiopg6PDDPeBNY/T6V1YNkKxmG5dxlottcm14EoUZUmAUxAEFhKzmIiJWZj7cc2+kjELn6lq6pb79qsVs3CZ8uZ3vr4qGbPQ23O5WDZ5LWIWHPfO9bd+vKlXTJ3F6geL0hH3kQKPOq6b2PXd6LgCiL10yNmnNK1d3plFxSyAuBvHFcDK6WTfyN06M+ArCvJ9zw3ctSC2EKomsW/9XvEUlz6cNkxWtWCvDVulZOzbh3Nj+FyDkKmfG/HnmP4hmbZgXUxGoAUuub4+r6lLaIANuRu1Cb0MYtmIWac2X6wEpq+8u2efQ+HzqXMI3QAcq2D+kSF9W+iY3ui6678dUlI/zoPtS4nWshx7DTixMiUbIggCi8VaFrWILV4qlXGIhVO4o+s2Qh2DCScbUrJvYwOWMVmG2nqVtJwvy4YQPxuyeMuiZsR/iVkEQYgiImQZDHAS0b0A3gbgvFLqNdO2DwD4MwA/nnb7a6XUg9N37wPwHgCXAPy5UuqhkBKyYG8aKQFdrsXUipJBaY6smEwQt/altl4uHUsE0UsHOO8D8HEAnza2f1Qp9Xf6BiJ6FYDbALwawEsB/BsR3aiUsq+8kUFuNsSFLcptCwjVckNisiEu3c19fbr1dENsesyM4Ib4trd2Q0qSKi/ohiilHgHwDLO9WwGcVEo9q5T6HoAnANyUpJkgCEORE+C8k4jeCeAMgL9QSv0MwMsAfFnb56lpW3FqpU51fKnTWnBTpzml1aMwok46pn499a0W4GxQ7n03gA9iPzzyQQAfAfCnMQ0Q0QkAJwDgBTgQ2PtKarkhOj43pFadBdcNsZ3v/Pf2jdc72xvpAdDPQdf90re/+5t9emaZ9D4z77Fela65cs0it5ifL0zKhiilnlZKXVJK7QH4JJ5zNc4CeLm263XTNlsb9yiljiqljj4POylqAChjWZgPfusbwiVn5DevTzdfqrYVNh3mbb11MxlNHxdJlgURHVZKnZv+fDuAr0+fHwDwWSL6e+wHOG8A8JVsLRuylDoLGy0DnKVds9IBTpt+nLYkwOkmOFgQ0ecA3AzgWiJ6CsD7AdxMREew74Y8CeC9AKCU+gYRnQLwTQAXAdxRIxMiCEJ7goOFUup2y+Z/8uz/IQAfylEqhhIxC+7bpBa95ZdmZL1H1m10Fl/BWTpmwdlemt7ySzNiXGBmZN1GZ7FzQ2wzAmtZFrXfRrZiL5fcJbwZR9ZxZN1GZ+jBwjUAmOmtlBuAWzabWl6be5wvgJYyMHL3D5W7c44PBf9ya0VydLK1xbXsQhkgXTeXTO4UeTPF6XoObO3pL8+QDqv6+ULbjRWq0efchDbLxIXrAurH5jxkx7aPY/fSKd6+nofRlw0JHZP6IObikuvr85q6+B4+Uy/fMTV1nCkhV1b3FgShOEO7IT5q5bltbzHX28b2OUk+06pw6eLTI6TbKMG+FkHeGDcAkJWyTBY7WGw6tWIWLRlRJ52RSuNLyLadT0zMYvFuSOmMReuJY0I7Rr2uo+plMrxlwTWjS436udkAYVxam/tcRtXLZPGWhSAIbVj8YFHTDVnCaC/wGfV6jqqXyfB1FqmUzJbY2tWJLZyafxsjR8fUGyxUKMXZVz+GU/9iflda95D8GjUmnPoQfVsoixXKtHB1i3VppM5iokb0ukSbdN3hAprw4M6FkDkTl5Na8bpmhg9wmpSYA1LzAnNkzCtBjXSjzf0ao1NKObT+ubT5HVur4dN3+9BLWDI5UxJCsjjfxxxj2047O3j4V5+JlqGzuMEihhqDg29RlRF9z5jJaDkD8dr44rlPWLeXLrduhXr22ew2Vu2GCIJQjkUGOEuU3breCpzJWTntl8Sly7xgr77wLdfK6jWRbMZcsFcnVzfuhEFTXmj2Z229XDrmBop398r/yNDQ6C5AyXkioQsYmnXaA9+s09AxvfVPmUKeKyNmH3N7rblJLUiVt/jBohclJ5KVQiaSldWj1USy1qQGmCVmIQgCCxksBEFgsXg3pPREMrPtkA/bK2bBCbTpuoUqN3uY1b5gXY2YBQeXq2GrVjX3qUnJiZL6Oa5qWT0bkg3ZJ+bcl5IN8SHZkL7ZkMW7ITKR7Eq2DhzA1oH4348dgZp6j3o9R9XLZPGDRY31LGq6NkI/Rr2eo+plsviYRWlizXWpsyiD1Fm0I1Xe4i0LQRDasFjLwnzz1Hi7O9c72NquVpQVKpi5LBi2tb3//96ly4596IePT9+/zq3b1jawd6m7RTGfg677m1965PLtk661oZ2dy+TN/Uw7Ozh21W3YvXgStLNzmb6toZ2d7Elhx7aPA4hbVR5YaDaEQ2zGxJw5Gko1mpgDlm3wclUE2uRy3YdYUiLvKYvCmJRc/IZbkh/SL2fxm5rUyLi42Ki5ISG4b4CcoCb3WN/35nc131yxNyNnAAi1URKXVRdKbbawAG3bOSnbUn0y23+0AAABQUlEQVRXsi2T1Q8WXLiWhe9YndADaRZKxVoWpeDUkbBcIsextu9y3+Q+y8LWpqtPcx6s0CChtx2yqlLrhmzut7N4LOInMl1IgFMQBBZiWVSCYxmMkrbUiXnL2d7qNWMWqXDToSVlcCweVzuxVcIcWblWBbDywcLb6bZMgpHlcLXJLgE3oviXZSu2Li/Jd7oxcxu6vvNnBq4HlK66CuriRX95u5GpMImOWUTobeOyTMTW9m+yFL+Rf/FkWszColdMabi+35uefzvUxYv9YhYF3A0XQ2RDiOjHAH4J4Ce9dWnMtZBz3gRGPuffUUr9FmfHIQYLACCiM9wUzlqQc94M1nLOEuAUBIGFDBaCILAYabC4p7cCHZBz3gxWcc7DxCwEQRibkSwLQRAGRgYLQRBYyGAhCAILGSwEQWAhg4UgCCz+H4np5DKVnXp1AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.40047526359558 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 1000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.07374183e+144 6.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [6.40000000e+001             inf 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374183e+144 ... 1.07374183e+144\n",
+      "  1.07374183e+144 1.07374183e+144]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374183e+144 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374183e+144 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374183e+144 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acda90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.65202522277832 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 8.0, 'lmda': 10000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.07374182e+159 6.40000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [6.40000000e+001             inf 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374182e+159 ... 1.07374182e+159\n",
+      "  1.07374182e+159 1.07374182e+159]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374182e+159 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374182e+159 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374182e+159 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.33117890357971 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-10, 'kernel_type': 'untiln'} is: \n",
+      "[[2.38500004e+03 3.06000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [3.06000000e+02 9.20000010e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.38500004e+03 ... 2.40100004e+03\n",
+      "  2.40100004e+03 2.40100004e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.40100004e+03 ... 2.29095793e+06\n",
+      "  2.27925797e+06 2.42308430e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 2.40100004e+03 ... 2.27925797e+06\n",
+      "  2.27915210e+06 2.41500853e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 2.40100004e+03 ... 2.42308430e+06\n",
+      "  2.41500853e+06 2.61114616e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.07141184806824 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-09, 'kernel_type': 'untiln'} is: \n",
+      "[[2.38500038e+03 3.06000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [3.06000000e+02 9.20000099e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.38500038e+03 ... 2.40100038e+03\n",
+      "  2.40100038e+03 2.40100038e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.40100038e+03 ... 2.29096628e+06\n",
+      "  2.27926667e+06 2.42309596e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 2.40100038e+03 ... 2.27926667e+06\n",
+      "  2.27916199e+06 2.41502233e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 2.40100038e+03 ... 2.42309596e+06\n",
+      "  2.41502233e+06 2.61117458e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.92679452896118 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-08, 'kernel_type': 'untiln'} is: \n",
+      "[[2.38500385e+03 3.06000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [3.06000000e+02 9.20000988e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.38500385e+03 ... 2.40100385e+03\n",
+      "  2.40100385e+03 2.40100385e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.40100385e+03 ... 2.29104976e+06\n",
+      "  2.27935373e+06 2.42321257e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 2.40100385e+03 ... 2.27935373e+06\n",
+      "  2.27926094e+06 2.41516032e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 2.40100385e+03 ... 2.42321257e+06\n",
+      "  2.41516032e+06 2.61145885e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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a2tl1DF266AQ12V4kTtYO3SRBrs0f0NV/yzmdhX5y5GQeRg+HOYDp0lKEG6wNU8SkvgT4Ydt1eOmLDF23bJODkcu2L+9aercGYuh87WxyrHZlncrfttmGaOzJhkrha9vR87aN3jnepdFXJKRNzHzdf7aFSpzhSoc8+7VVdyA4elNdvR6kfs+Ho0F3Gky3iYMzwfjYhr8kaTPrOyxq54R/94uFyC7Eto2vb0t0ooPmPgFHqb464dhdkqewZ+0DiHBxgaS7g+3ta9h7y0uiXx6dCt7ob12IL3spkxcyL+vHtuUcdV2oJqYg0YOq3cmtIjf671SW7m/LmNYe+icDnYwm4LQwBxqqf3DQSBrjunYQbSBBVIb5InKAqboGL1cwHsBVn5x0Wi8aHg+4+2DuHKQp6mXpn60s2laYFPotx3dIUX91F4sGn4VHa+aIxq7L1UvvHrDm35tl7RTCss5QlQoRGM4VR12+iBFFZKcai849AQBICI1jUlVSOClfvICAoATi1y8gT+UylT+i+yPdTst8aXRquLYNwUkcxxbOscl1RAwwJS8FjYbgacuLJsjNoojzK+1ojgoJ+9Y2eaHkWo0A1Uhcs78HGywDhZocDpO+3Nx5xCu5vni5BDAD7bs8EsozWGUMguC0nCzadHgHJBmr/hiAoEN4NqoyLsiiA9AjOHvppZfLlxcfwXkb5EVAVIq0OSi33V7t0sdlt7POZ9HmZ9nkA9HH2troukYzpm1bN6TtXJ3R2+b8Tc61TQuvTc+2wxesG/J79e+8QgjOTbLuwQLi38QHsE2xF+1tr2t3w7L6DWHvn3mvg9d7sUi3Mt5klUzFkPbetQ1RKd9JBMCbx4ADIAU0YejLP1j+AU+S0pidHl0p6mL+jscxSzJLXOvchihfiN5OhBT1JEmM4/akMC4rU40hJpdlPov9cUpvJ30LdV5RxPmF2yZQUcD6sVBZhf7NcAgr51oOe/7gqynL8Hvx8DXY4xN/rg0p8cYnh/F8vnYbwtMZzN1DN4UfPW7dhpi9PdeuSsGn0RDmY6/BfueDeEz8SW3bkOEQfHIat0dsQcfbp6j3lsXLJp1gpEvu47ra7rIWrtKy0BZZVzv6966KZFdhWWQ6XbTW6S6WRe+z6OXmpDM/Z3sP/ZWIhCcvyqD1gkkrc9gOcvu2IRf5ql1HJulNZauKXGRuttX5sqyKVih5B84jwVZ0QZu3aG/b/jSWZM15IVTZJq08rO1zvDGvSW2XNZvbTuULZVvcly/spZderlJun2Vxka+aXulz7sk2Ds41e+PEOam/LtJeNWgwLVNRBPCVOB9dG0vHegTAzmbxekHb5Y5X/3Vp4/jUvAh2Pm86ONt4QRG/bGY0CtR02iGp61GYg/3ARh04P62NHJwtQmXVcHBqTkyZd5nLRo0SW4OqQegzMHMr09oc7INbHJzwXJdUFLAKPGXGY1BZopaxeJwFMwd+zCB+bjVHqsxx+clPwD59lswpLxaR/WqxjHr6+0zGeAfvEpjOQA88B+d7H7Q7OMcjUFXCnkYaveLeXeDtN8DffC/2PRo6J6hgPWQbNaiA2oLn8wT/sYuD8/YtFpclmUOKQwRgOw7OBv16foosFCqSwZYjKCjjhGymOYcc46a+HdmSbTybYnp25T/k1+gXNUmRFs5NwEVC1O9Bp66yekGPLOWabfNYphOvdKp2OifClRnOnc4iSXFG29emnyMCburAfhFK5sZyAohKxnZy4khy5ZBxfJnwdHeag1Po91iKDLEj0TVHJ8nY8p95sQxRIbmHdjqDefI8XdTOavcsyUfPH6bVKnJwat7NOnPMrpFXeLHoerC3nLxNOSSaHUrtg5PFqG1xuIhw+8O86Zrk17yqmDuInFw4EBzX6Xnd/WQvgUCns+hCvqgl5yj+zDa9sFx569ACevEJi0S9cc7DRyP/U2NxVwvaYpkS7LCHjC/Vh0HOlXOIAmEv6jqEZLsWXK7rZGF0w6nBk2lC0swCbc/OjYTUnKBYeYdMst5nkctl1rxIkn/We6KDp1qfexW1Ny5JApGvr88hv/s/prqvYd+6oBLdHn6BvudMX0o3klodl6JKyzxscx1RU0f1v/9l8/X5uK5AXtynsZdeenmh5NXdhmQgF10QF1DWag5JFh/EpiJDAWGZOji7igxRWYKAgBpMoLkJb0Qdvqg7FRnqKgWQO3qrsongFOp+cTruj2HPpqACacJVbSMtYD7dLQ5OzX+5c5EhQXkaAklze3vOn2KUTkVsgwoTfQtk3JwPBqi1DucoMmTu34N99lz1WQC6yNBqFX0WeZGh2gKzGcy9u24KP3jktlG+TxEpMgRVZIjGY+CNhyBdZKgq24sM+VIAN1ZkiIjeAXACt0NcMfMXiOgBgP8NwHcBeAfAjzPzs642ztlx8wXetYk8OlAUjhcxz/7sujY8LLW7QfNssShLYLVK99RFEaMetaoSZtnV4rAMSDSkcBycun6IOzd67UXCw1OVoX3pw1XHsrGvpC5JHeHnXn8zHMYXopY0ceNgxH5OaH8ftFgC1jq9Aaf7YgGu241VKmL+RFjQNITc6xfgyhKdGQ5ha8dPEc4ZDZ0/oK6BKmZQ0uFBXOW16V4YYDJ1UGtNrDsYAOMRaDIJOtBgEKJHuro6isLfIxuvBVAvFrCvHYIEGs4MiJ5377hjZ1NQ6euh7DtiXlQlbFGA5gvQMaF+6BYLevI0LPJh0QBA4xGoqmCXyxgpOtjH/BP3MHj6XJ03BqbT+BGQbc1o6O7n2SRkuIIZmF5v1unfYubPMfMX/O8/C+CrzPxZAF/1v1+9XBLSjojQWT/yuuWqaoZeVLKvlvuZ0t/DuaZ57mWIMbu1SdEXEKwYc0n3uqUNEt8TbekXMYhv4w73nHN/WKbLZT7PF8oN8ZbFF5j5sTr2dQA/zMzvE9FbAP4VM3/vunZuJDckS8zqwjN01uvIr8/nsS1fIEtA04xHVLovZOBWyBPFRHQuwhpyHdeWwop05Ujk2zGPNwn9tjjNaDCI7NPSX4iOpOPSY9eENkHHFtxHElnQvCCmiNe3WBBhy5ItAiEsnbFaUeG2bRp7obejeWX0hPtCbeuK+/djFXTfd5IcqLchYnXoOVgswtfeHh3H/lVkRLaCrnSktyxGI5h7dxPyG0liCxaFXth96FRbpV+bfQVH9sm1ZJ0ygN8hV+/uf2HmXwTwBjO/7//+AYA3LtjH1UhGctNavhBoXwhyUFZRNOC6oVyfBmWp7UNr+ULExcLpV0eSm1zfFtq3HJQVzOkdQFlC/uIOxqhMUr5wPALXZ4A1SR0Orut0n982H0DMwKT4QmhQlsyP/M55+cJQ6jElqaG9scM2UGrlUIWQ5ZssFlXpXuhZ9BNRWQIelJVI+JtN9axr0OFBUgKRCuPKF3qfBc3noRwijUZxDoxx2y1DIJ91GsoX6rkzBBpUbmFT1P80GsI+vA+aTOO9GVQAeTAec5wfua8ZKAvL7a2Yiy4WP8TM7xHR6wB+l4j+vf4jMzMRtZouRPQlAF8CgBH2LqhGL730ctVyaSnqRPRzAE4B/EPchm2IlpzIBNi8DdmlzeR4OzN2wiupz5Nzw89rthR5v+tSrLsk3z61VSTzxxKOCY5ArcSK0du7fGx6K5XPV5sDu60iWb4lEW4PqUjGnESeQvOqeppVHBdrpYPkxuzvJzwZwtMRofBqW1eorZTivhBHMU+nwepsWIGyNVJbRnOw7zg8cgJgrbM6nlcp+9rqt3Fsr5j8hoj2ARhmPvE//x0A/z2A3wTwkwB+3v//G+ftY03n7eHMHRa+JDpAxpG91jbcYDuZQPgrY1+OF5PKMgmd0XCYPizwUQVfOk+b2PJQ2LNpQoRj7h4CllE/d55tMxoGrzjXaruwdKEvnbugORmTaMhk4qMhixiFyUKz4tUX/YuD/Wa7RQHy8wMA5t5d8NGxu15FQ3ixcO0EcBaH7Z0usxcIYIwJJDp5NCTkquztwU4m4NUqEOAKQU+I5siW5cE98NGJi37ISym+lPkCNKhiTgtqmDt3QPt74I+cy42INkZD+GwS9AQcwS7/te+CeVcR0AjJzMMH7sBkGqqa84G3ogcVuCDQsoY5PsPq46+58f67d4DFIt0GGYI52HfRkOdHIZ+m+NhDTP+DT2D8R+/GbYjoKOOX7dhwAKxqcBYNoUeKj3ODXGQb8gaAX/eDKgH8C2b+LSL6fQC/RkQ/BeCbAH78An1cj7B1k802wc03oLfbQsGz88P+G0i/ALqfFpi1+8K0tGsZKK4hYqMTtSzHuVE5J8lXkznCrSGHO9LGL+ihd/eLW+czyXeQvqx15+ZlDSUhDTj3nFL+kcoh68x5qVevOzld69otakDQk7UroSvnBgDVHBbxcK6el3YvwLnkxWfK2oU78rxcEm1Rjsz7HeQ889W2NejiVNQ0dcrs3Tnn4zJk3QvdwVGZMIxL4lkXk9OuY9h2gcmLDCl6wuDc07kSeUmFXaVt69bF39kGfVfRsNhmSvvf+kxnUHHXx7r8nOb4dqmi/gIG8XvppZcXUW4n3PsSEJw5P2Lgs8hDjI3yeHW6onfBvYXPQh/zvBAAkkIwSUEaIYQdyPWFJ4xFOJfKCgHTACQOwE64d1cRo8wa03wWYdwCTZb4vodVa9xA2Jq0mcweKq1rjYT07F3g3v7rG0KnzNFRCDj/w3SWhE7d1s9vNzzWAADYADQYw5Ql7MlJ1PUccO/y7TcTuDdVJXg2j74BbSEIn0UpIXoLTGfA685nwe8/UroqnIWHe7OCexd37gBvvQ68/yj6LMoyIewNvo+qdFm5F4B73/5tiFosEqflpnFtiFa0esqlutc20hZhAdIoSNItJYuVy3mI7Neay6EN13FpsiZDVEc+gse/SBddAAkYCUBWvzMuDDuPIYuGhAzPNvBbFZ8FHQ0JDl1x3hIFh+HGe9vxYTKjUUriI3PTEYEBEBYlYS+nsYeBL5fh78FpTiZu5VT/VDqcSDKPfqFtyzxtS8n/Pft/vpqlACLy8Dx+hRSpyJabxCDJvnQDglM/xMoyIZ82raMkUi6PCt1HXCjaHJ+bwGIAzofg1MjRMJT0pRQEZ5LibZV/RR5ehebMEYmSyLULgjMJ3baEBzWCM1gbREm5gtC20PsXBQABwsUSC7sgOGk8Tpyc0meI+sjCBIRclhz0RXtuseCjpbMSFAkRGRvLFyoEJ5Vlo3whdLU43Y8xoBYE56tVvvC8llGOQcgZmzbh87chv2k55tpvEqyEEqQtDE+N9tqg3l6Pxte6QcDTvCb5tZUQxuss2yZd1zOL7ycOWnU8Gat16NS2L3muv/49bg01HiXt3y3ySPIxNN5DOxK5tu6DoBycwRrKbx/XYDXvWi9NdQcgsmxl0TAAAenJChPCdQ1zchp1Qqa/ZYCbloVdLIHnR+kc5WxgyS9NZ/kuO4sXf7HYZTHYJQqiv6g630L5Irjrpcyv32RZqGOduSGKjxMAqNCWUkso8DosC20R6dyQwJNp0v5qpH4LtgiUVdoyCYlcu1kWwYIoCsCzUeU5K8E/oI+HF7NqtO22Aen87WpZSMp+bNdEfQAXGu3IDWFmh6vwhZF54XNDmNL5b7MsqhJ09xCsLAszKJLcED3WttyQXSyLPhrSSy+9bCUvvoPzJuW8kZaL9tkmL8B9arWmcotFR4ouil/YVqcua0lE/72tSthF9ct12Oa5yZHHuV65ZbrJwt10XofsgrN48bchu8guAK6OFPVGXoMuNnOZKer5Xn8wcMg9MXMlPBpqeqr+ritFPaidmbTrUtQTtjExXG2yvaHcn6DbvqwU9aCXTRGOivSXqtJFvKR8wHlT1O/dc9B6rfNy1XBwAogOziKGRnmxAN1xRDn2+ZHyZUjX/vlsS1HPWbpMloa/IUX91XJwarmAs5MKypiqGcgpnjWeQYX/WlPUDTUuT1LUfU0PAB66QUBB4GXc77e+7P5vmqYu+ALyFHX10Od8GY3FUaeoBydfGqYL5wyqiAcRvQpylHpswasuZ2qM9IQ2NXUf/Euk/RvhHBvDn4VxOTt1nfomxiPA+pdWwfadvktXp2SumLIEjxH6qgIehIoixUdk7GShULJl0P4eSOeRGOPaED/EfBFTxQVnQQRI3LsuAAAgAElEQVSUJXjuXv6QYxPwM8oJWQNmb+hS1FU5AhoNwffuAEfHUa/hENCFmDXOgsjVKBndTIr67ZW2KAC3UOm3Xpt795svRxvWI2mb01oejShADrjKoi9JASO/mOQ07+5Lb9rbQ8zlSPqV2hSJLqlOdjrriJp041v039J5yKJQYk2JSN2Q7N4Ei0udy2eTduyGT+jLrTFerXw0ROkl+mR6Cr1/skBLdOg4rRsibbHUDVmuwLLQ+fNYnKmrlfu7f+G75jCpG+LFTmcwHz1NE96kNojoFvr1VeQXy9TS2aFuSO/g7KWXXraSV9eyyGUTHiE/N9sWbNtHl+Wye3GgzGfBzlRvVFRrw2no9nPAV2b9AHBWS/I1qtvP31Fyv437z7T/3qmjynBtsYoABFxGY1dZ1y04DYGJ1y3H60wv97udz1vun00KB0nRHz1mNqtQ5WwTp0ZnkaHprGGJud+9PqKWZ+pqWI1re02ltywuQ26KVFeTtW4i29mmrZuWpDBRRlZ83frl2b8tsmtBoYtIgifRpMO7iFlTlGkLeXUtizw60ALKWndtAvc11Ax8aC++iEr0Ek7I0EZGQhOS09qiGQo85JUNfSbQZg/J5hpNB6fSE4hfHFJw4SR6UUTafiGkAZC+VHXdme+hoxwhUqFyX7SDM6n7KudodKgke2V5NmZ/HCMbed+yZ1dfcBoMQEUBKwQ83kEcE9T0vaOUEEeS4RZLFPfvwR77ZDTFfmV8YWTWDsdA/OMBYcsleDpz5EcA6o8et1pHNBi4Nmbz6JAdj2E+9hrwnQ+S83QimTw3VJVNHQDQce/gbMax8z/nUQDJigzZhB2LhSwU8uDKNZkDMa/TIX201g2p63C8FiYrX4tEnGA5QXAatfA3vCgadUNiNq1ku8bxsxovQqRjEJOZVIQkPIQA6M5B8P7rDEZeLDoddEkkQbFi2RANUahH7/QDfN0Qy+CVTa4L5MBqsaI7d2Dasl79Ak1liVo5A2kwAA0HcSzCZLZcJeOCtUBVuQJBum6IIWCxdKS5S7UImwKYzVTdkDLOvzBlGQM7qGAmM8AUsK/fd+0+e97qMKe9cawb4h8ps7+H+aceYPAsIjhpfw84mzi2MEAtEIPI+C1JawBw1i8W1ypS5PaFFpOZ+L10S16PZE19kquqK9opxuwUwWiVc27p+qeml1562Up6uLfIJqSjPg9IfRst5DebEr0C4Mr31UlO0yUbEKIAIvGsTloTP4iMUcOMvR6te2btc9Bbkjz9ewvekbCP1mhN0d0DsrS/JKG+k+vafBaDqt1noigB9N+pLN3fln5rYoqADtUgNGkjjBHRucl1jUIYtpUkhEa66I/MV4azMB7AVZ+ctG/jqkGTkKcoGinqQe9QCc7368mI7XSWECR9bfq/46h+/ArCvduk66Vr5DR4aHdWzKe9TQXbZnE2dsCWk5wBk/g6koUj8x0krFxtDk7Pmu2O2aCT9g0A8DVcER/2BCatEZw2PR9NB6ccl/qjcn4YHrCzgzM8pR7O7BCH0dSmwoSasZo4hogBTqMRNBqCpx3+KYGma/2KogHhpsotlqFmKOAcng20p3cYLrw/Qdr1Dk4AaTGfDgen8w/NAqsWTSYdDs7KOU5n87gADAagwzsgqYYG5UNqcXDS/j6orlN/zCsL926TLXkcgmWwbpFQ5zLHl3drNKOtwQvbel2Cwkv0WYPgTDp0OIJGzonoQnk7HhWZRUcSPQTZyOkXzeoHekucRSuCM6mTwg62AGVN6HM1TiLpU+l1atvvhcDHc4zBYuH/liI42bKjr9Ow98zCcVB69/f62fMGGxjYBrq+JF9mpvAUvjI91zW4ftaYp6Q57/hmyyAPl+fpFPbDjyLTFwBSpDlaaE6g2oLn8wRtynZ7/8fLv1hsaVmI+Z1HSVpF54aIqd9lWWTH5Mtvk9yQGA2xUkU9mJMdlkVbbkhZhZwF15av4UGsQraZZZGFVI2iadOWhTbLzcF+rL+hc1EEFNURfcoti8TUF8vCnyegqFBHpM6uY25EQ8zBfqjrkYiHObvckPiymuEQqCrY09N4f6oS5KMfkePDm/FVFV528rkWPJ+j+NjDZjLXYgFz58DNy4bcEJ7NYO65Kur1+x+0WxbjsdNfFRQyB/vAW6/DfPO9eJ7UsGnJDaGqgrU2yQ2h59u7LXsHZy+99LKV9A7O88pGpqwtLJqun7ftfxsehx1T1FMYe8sxtFtNjWvW6buuj44SgW16NLro0ivhQ9U+JO/z0EWw28ottrWjHMY0HLZuQ2KR7Yw/VERtQzRYr3UOvTXbYPoaDhPnaoPrVB3PuV+B3coX9pbFyygClV73cr0I8G4ACWQ9HMth39eva4jMhFKM7YzsL8w8biFhKxSej91e/5ffZ7GtbBs6lXOT3812jtE8dKr/lB/fFDqV6E2ma86J2Rrl0fpn0Z80nKnyEfRxhVhthE53kDx06v5Lv4ytvCAdodNGJEiNkWs0Q6eFZ1q3UQf31S18u82wboOQBnVAmWrhWkUmNoROAUQEb+7o1rp6S0RD4Wk8AmkIuyB7W0KnLvpj46IBgJZ9NGR3ue1Zp23t+EzU8H9b2zeZdZo4Q1U2p84k7eIKiSfEHy8r65Qt0rIMaM06JePm9lqzTvX92jHrtMGDAoB3wB6/uovFeRPJKP1CdDJlXWcimWLKaiSSeRxBJ1OWHF+qXI+bSCTzX2rHgsVJ9TJ3zjUnkg0GLmkrNJ4mkgnOgi1fSyKZ8RXJBPsBYPdEsmoAPjvLEsm2r0jW+yx66aWXreT2RUMuwrh93irrm/rXxy6jj/PqBTS9/bl0zF2AeV/387CLg/Cqdevy0azpP+Aarlr8MxaQo8DO/bZB+V/u8oUXeWAu4wVu618fu+5Fok2Hdce6Lr+JhQLoDi/fsC6tvpu2S/KQ6VWJRpm2peFv04TlC83r7VssgGbM/hwTkPNNhL26XrXbMAgtq3vb18WMRr5ql/Lsaz6LySSiORdLFH5/Wx8fh+sF5ZkjS6ksE/SjHkPCLzGdevTiIvYrfBnSbuYrKQ4Po2NO5Wfo5DHz2gPYJ0/jvEl/i0UCPdaONI0MDVGLqnI6ZsewXMZzx+MAvTYjl2xFI49rqGt3vocsmwf3HfFtnjZeFODpzPFZqDyK4mAfGI/iWIS3Q1C5OjJRFK5fjxCVcdcnJzA/8H2gDz7yY2aHzJxMYV5zHBV8NnVV05kjn0VRAGUBzBfA0Sn44x9zx//8nSb0H4C5e+gQmM+PwhyXb76B+fd9HIM/fiecR+Ox07EsEfJh/Jxh5UiEpa4qANCjCtvK7VwsGtyT52hCF1EmitWnaXN7Do6spDU3RNX8UOdpD3ngJRDa/+x6rWfiRfcs3g0zua4jcU2mZyd7eFu+hPQtmZo1AH18MnVOyIxNPDBctcTvw3wAMUkMy3hMFgeva3CuLuM5of7HYhm+sAQ1XpXPkWxv6o6ckdUKNJ83dBAHazJnzMCsOY8AYE7OYOf+BbcWVKzcgiclDedz8DL98FBZOifkcgmez2GO3CJW60iTvuezedRJIjKzGQYfnTWZxReLOJ8U0xLgc0MS2SE3pHdw9tJLL1vJ7bQsLkOy0nBiBTSwVR1WTONLn1+WxbPDecqagGJrDnvRsPXJIc8tbWV6NeqGyDHm1JICwpaqUTck+wo7qLKfF/miLRaxAlkH5qEhyXz7dlaRazOk24tVEc6JX9JwTOYqv1/zRdySKcuCVx7PgMyKqmtAgZLC/WELJpNuIVG7WiKZdQRmV68ky9bl2gI+KRDLZUxbFytJQFZiLfgaI7CcwsP1GLz1G44tljBHp+BlmkXKq1W0KCSEKtZS7mPZwf/x6i4WWrQXPJTeQ0Q/XtA/0t5nC81dvte+Ifq71hKL7g/Nc+Wh7MwJacmxWHd8VxFUY66TpsLT+RRdY7uIkEkWp4BtyF9Y0Vf/3wkjjwjStdR9+VjXUABeVF7dxSLcJL9/FjKZLV9Qvah0s3sjeSGoKCJxq2avgnJgyslFAdjIzq1h2TE9XhqmoFOSMi4+B47U8czpQ50sjoBn15YxxqSpAJaCdzCuVoCNZD7EHgvY9RJq+HRIn1blCwWW7OHKoX6HlC/kOF8Opm3duIiAwl879E7q7AUiogieyxOxqhI01yFTE9vVN1XoBQKwTAiQCbQ3AosVYW0kf5Z0dCAuDnKs9OUEvcUg5Dd4fqRQ5kqvsnT6rlbx/gwq8OE+6Og43ptBlRLwyCI2qKKvSJPyzNcsRJnczsWiLRqy41e/8cIVBQh1fAiWHRcCKVJSWK4aCE6hh0u/KuJFp9UqWTjcTVZmr5AA+5es8VJni0IYg4pOkOhW183ozzp27xANiWMR1m3AedxpOnMpFIqiDQukZm5WtDhBmoq+WYQk6K/0cYQu8QWlQQWuLSjjs6D9vTQvQqQwrsZnVUYEpiHQoAKNRsCZIDhNiIrpnJeg62gYFwvRcz6HvXcAEh4NHw0hyyAf+WBDIJOye3NZgIsC5Gud1vddNIw+KFqtHhoNQVUFWiziAjseY/bGAYYfVsGRHZi7QxFp4dEYxMVCFiYAOH3Z2b0vYSvQuCGyl9RJWS1JTMCO0ZCsD+1ND18DQ26PqzzToXZFHl0Q07YjGqL3zheNhkjfzFnUYzoF5Gtt1SJk08UgWDY2rewdxmnVHOn2VTSE1csR7o2ETYEEhs6TWYC4C/0/LIfiw1zHUGLYv5cquuCpBXeOhhxPYjQEMaKDU7+ALBeBrYtkDJV/wdk9E+bInctAoBcMz54hFw1ZrtJoyHSKwZNJwvbN06kn+nF+Hal1Cl/XtY+G9NJLL1cut9Oy0GzaXenhG7YnxifTCMDFjEcuuWuUFvtJ2hcqOgV+4tNTB4Tx1GzSlznYd6u8WvXN/hi0vw8QwT59BvKMzvb41NGqMYcELbO3B3ty4kBCs3nC/u36r2LSlErwIk/lBgD8+IlLn55MQlKT0OHJF9nsOZM0gMFeexCrf4vJPhoGcBQA2M+8DfPO+yBmkL+eAPBkAqpP4y0w0Zfi5sNTBo5Hzl9SVYCvHi7JTbS/Dz6L2AFz/x7w7DnsdBp0pcMDF/lYLt198HO+/MybqL79xPkHApkOOfDT8xPQaIj60Udh/Ob+PfDdA5AfLw0q1/9i6bY6ZxHAhWoA3D0APX4a9AQA/vARjv7mmzj8Q2FJZ2BQwTw7xuK733SXPp2AKwfKmj/04LuRQT00GByvMHz/BM8+9wAAcP93jkNkJFivxoDeeh28N4T51vuwftvEn34b3/7b9/HJ35iHObD3D1A8OQGLZVU6vVaHI5jFCsWTE9Sv3YnPyL9T5L0b5PblhgDdPguRbcakKfDJJBTwgOfILCuXpanzPnwmaI6obGSdVgPvs0hZkkLWqeI4gGW3WNV1WADMoArAJ81uxHXtMkXzsCWQcHyGMeQI0JZrZByAR57KeGWL4DMugyN1PHKm/XIZFleuLbBcwi6W0Y+hsleD0w+IgCRrw2KtHZx6G2IGlTvHM1KF65mdM1GqkwGgvT23YFVlcCRitXILj/fbaHQqDSrQwT7s0+fhWQhZp5RyX4iDU8x4/ZwU3/1d4A8fu+NEwKBySElZuOeeC5Wt85EAzocg26vpFLjvODj5vQ8igjSUdjSBiVyTJRf37oE//Rbo3Zh16nhBPeen5bjtEsexRxyL/JvjX8fR8qOXNDcEaF8MLrLoecxDioNoZ9DerVlOnJxUIHqq2bpoAtwLHHIzOO6bpVZp4ihV51yZZKnvLuoRFxRidshDZuc/8HqFRSZLcXdjVfgA7xNIwo076eUWiuBLscrHAr8Q5Knq1i2umoyYuAQWywvPJ63qEMViZpD4n9aFZ2sboyGrlbsGAFsb8RTKlxLIb7Sw70c7lSX9PL+Hl/DM3M7FYhP/5BYLRxINIePDYjaYw7xcxHAqp1ueraIhYkHU6qtZGPUljhEKLJypD8uBr4DK0v3ucQTBAvB4/wR0dNnREJVzEhiWqjI4M2lvz0PLV2ErBWb34qk2haGbrbOowpdSLAvREdguGiI1S4c+KiG5LRJluXPg9DCFy8UQvYQlXRUhImLQcAg62Af81k8K8ewaDalfuwNzpngmhk4nuuO2HJj4ELO1YH+MBxVgAFpZkDFYPXRbA/PREx9qjU5hIorRkFmEp9P+PqZv38HeR3vxmR8Ownwyc4jCYDgAVr69c0ZDegdnL730spXcTsuiS867Fcmg391/28GUs7b9fGUtRCo/m3Irih5qq5IctxyASFctzBzCfeFLB++jYDUGyyokGuHnnehDBRw6r16+k2x7wgDqUC1eb+vc9kBdx9l24bxzapHeuwBH794uOxAbue2ItSm7H7OrXSLzaIBWzawFrazbuoi10QIBuCy5nYvFJfgsNuVEtJ0Tz90t6zT4G2rrAE/eZ8Fqb59TwCcFhPIcCLbgVUsm5VXgLAC3H18gLAY8mUSfhWQ8+pwEySWJqnIcq873gAee7YKzEF0XCzdWzl7I07NAKUeFP9d6X8py6V4qzT+5XLn8jQviLIrnpwnOArVt4CyQ4yzK0m3xrAXP5jDPTr1OS4+PiPMPazqyTucYPjpzDtSwSFjn4AxQc/8ELJcXxlm8+NGQXepp7MJS1VUvQ6MOpU7DeXJDupx3Abad3iTh1EzqS+gHW7/U8rcu4phwETePb9K/o+ByQ1exMnQhZtE/G2OAtuc1N/QY2mqeyHEdjVojAcSW94G48AdfhIDdDEXU6SbLsaOmidnbSxPJpD5H3pfml8gS3SQsrDlEG5Gr7HmksnQh9uksHfeaXJzc2tulbsjttCyA1pciyX/Y5aVWhWVyPL57yPSNOAcTVlu+SbYoub5tCl8uI2FMAgU3BF51jK9r3Lt8FDryY7TTL4RC5ZhYFBSduAm3huXQbqDVX27BRtVyPNnaCHmvFh1CZoadzaOTWaIF3jIhjQBdKVxO64ehe3FLSj0Wpmn1yYsq+43CoXZdGcQMFi/jEsJgQ6GEY66TG4OJOT8yFy2LRrBkEysVW0vv4Oyll162kttrWaz7Um7zFU3M3LhHTxK/6nSPe+5Y9YbrXPjWf5mUp0s4DPI2OHd6XqZ06Uom3XrUftuB6Hdxf7PBosjZvuKWQGWgnkM3PX5CnXzVRaeGTyr3jQQnbHvV8Z3UytmtVum2Jq9s765xP/NyFXE2qi2y0SdF3L5LYMuguo4MZVoH5FuYi+Msbr9l0eYb2Abs01Y2L5d1PAIXkdzMz7Y/jXNviNci758Mdeq5lnOho62L6JL33WjPUOv9I/Lp5zmvxAWkAS7LfTxd+knleONT6i/CS5HNjYban2uuW2SjRkT0ZSJ6RER/oo49IKLfJaK/8P/f98eJiP4pEX2DiP6IiD5/YQ1zj3fb3+VHjYTctt28fQmp+VW/87yL6N7CghU8/qul++ezIh3qUJPgcvP6qxQ9HzYya8VID8fjHFGSkhUboiDZv3N9zTva0XoFsRzD0fqrK7r5uW07Z2e12sLt2Ze+VT8f9mXrojUuYuHv+2Kx3VzZbE5Un7rvyyD72WYb8ksA/hmAX1HHfhbAV5n554noZ/3v/w2AHwXwWf/vBwH8gv//emSXl1nnhkBFIwQpuVy44HZHHsrG3JCyalDrUVk5zL4xzumm8jWMdwqG6lge8dhKfrMmz+PCuSHDYSN0Kjktcq052HcJaZLzAVHNP+htfAwyH4hOPKJqt9wQXz2NqtLDt7O6nQf7LglOk99Yh5CUCnA6amFGQ1eF/ORE6XmO3JA3X4/5JYBzOM7moDs+YUsqkunckKJwOq5W4OkU9MAxgdvvfBA5OWRragg03ANVJezpWcwNOTwAPv4m6N33E/Ib9s+WOD8BuNwQHzrVuSG7VCTbuFgw878mou/KDn8RwA/7n38ZwL+CWyy+COBX2Gn+NSK6R0RvMfP7W2t0EdklzBr8FNmXcputdJY30socnS0UjWO6L7FitLTlV4TT5WuYY0VyDzwHSyviNtZfk5cv8Mqk/U9nUT+tt3zddNiSFDNYPjY1Lj3vydxqXIFuo+U6TKYhQS+h+8usoNDEMuaJJG164FzKwcEhqS8RZvDxqcNBACHj1fFqTsIYgj4hOUyVmVwsAF/+sLFQiz6LZeQwkWd2Nod58hx2sUjycni5cnVUgfhOmGXAwiTYinp7i+q8m+E31ALwAYA3/M8fB/CuOu/b/lgvvfRyy+XC0RBmZtqm2EYmRPQlAF8CgBH2Npy9tqHdfQmAcgapbUiNNGFrTZ/bFUZG8nUVzkcADoUYtjwrF/9njv4JT/MHAK5id2TIcj83y+vl25CQ6rzDNkQS6nzHURefCAXAJY/5rM+kP8+iHSkAM/yATniTL62KZIT+9XHFwRm2L54LM+AkpI99nxRmIoEuAQHBiaIA5mpbOKhcglbYmhQh/b3htJS5lW2rSsyje4chIS78bT6PXB8awSnbEOHgtBY4Owsp6nR65p4bQ+H+g4zTtSphVeSExmPY1++DZrMA88agAhSCMzhw5b5m2xAsrz6R7EMiegsA/P+P/PH3AHxSnfcJf6whzPyLzPwFZv5ChWHbKd2ya2rzts2KB115ki+h0R3OVYCwFkTpjUgroEz5BHIvvlyTAbDSyy/x/nW11RENaURUruhZWqtD3q/W57z5Muv6yvs4p5zXsvhNAD8J4Of9/7+hjv8MEf0qnGPz6Er8FUn0ouPnDUxZ8UstUGJKQ9PMDWshcW4qLseQoq76CoS9+ktuyhShGfbVKqlK9qO+f5eqXrtrtf76ix4SoTpS1C1vnaLuuCE9TsLX9SAqQ4o1AFBVge1Z+tL7rzmzTZCZwUdKVQMsSINB4HGIZLxefznuz2G20VooCjDgCHtd4+6/0dA5E4EU8TqognVlV5N4PHsxpXwham/FaEqMrhT1xRK8N4rIUMuBaCbQEVjlaPSlA7l0PKE0nbs2xr49wVckBmANM77j9JvF3A4aDrC8P0b1rrLghkM3d9KfwMsHA8B/lK+MsJeI/iWcM/MhEX0bwD+GWyR+jYh+CsA3Afy4P/0rAH4MwDcATAD8g601uWwJWYntW5SGY2+5CqGsTe0mxWk9SU3elxVSFR3aVUSzXCvgEHOgrEvOVXrmDtVGaUR/jdUOPEkkY1Ue0S94wfG5VI4wr0ebw4+04/PoOEYxdAJYV6alng85D3CLQAY6E4CRnGOns3BO6FOdQyb2b58+a5TyAwDMyRP5rtL7MZ16GLWaW3GI5olkPjksOChrG7/k33kU6BDj+TXsU9/mIm4LhMJPcBZ25cKkxucz1R1kPPbktLHdtc+PMPhzSuq30nyesLCFD5LfAtvpTG27EDgutpFtoiF/r+NPjcwvHwX56a1776WXXm6N3F649yWL4Bny+hzNEyXpKyatOYxGW4YgUj+EKgKU8GqyOi6OxpbCRUn74kBVyuoiRq4PE+P1smdNfCE26iAWvTehXbMKuamO06AKXye9HcJq1ZnEp8sqaOYwjeUAEPAc4tyL27n0OmbvANTbOrVNSES2YoUBr9JEQakyLzpIASNUVTIOYQwLvBEeL4O6Bu2N49eaObRJw0F6PRCLDHleTUnxD87Qo+PW8D0NBk5/FaqmwQB8eADypMcAovMyODhle1e5tPhl3B4BAGbb+2xe/sXiMksOvsjSVQZPfDHr4OQAzpWrcdmiTGcOJR2v2cGrSw9qrEauhzFX6xztkgs43cmYXZJMG/LyLhYbFok8ZOhClWg6/NquNZQ4OJMvluIaADLfiHJAkjgv/TnBYSZl8LzTVPapeahWf5UjIbBJHJxc21DZLFyvohRsjSrD5y+qYnUrqHBq4jjd3w+ONn28MV49Z8oC0XybAkIKYdFB5fwOah7d17ROrgtlCrVlsbeXkteKVD4c6kOa8XgFGg5AgsosPFLVGHeNjB9w907KI3o9AYDnc9j7h6CZ8oZKNTBffgGk5lkqkhUFuCphJu46+8ChPemjx+0I2OHAVyRbRif13hjztw4xePQknifOyzYHZ1mAFotgxQAAji/RwXlrZYM10coylTNgdV2reQmAyNiUEZqsY7JqOFi108mfq89rIEazKt/uuE0XObYATCRNkWNyLds0r4HIMUopBmwAcVsi/5+dtTJGtR3Tf2tdSBQ6k4gaDsrQJplmNbcsD4gnk+Y8ArH6WM4K5dmzNOFxqHYm0Q0gMoTNFYvYwuM2igLm2TGsRCnUNoS945Hni/hsqOiPg58vwbMZzFOH4Kx11Xg9D/OF2+bVkRWdJ1MM3j9usF/xfN7YhmC1cqUSFkuAlDN9B6asl3ex2FGSBKnNJ6f7Ss0BmbXXOJZHD/w5Ddq7jVGZLHVemJCWWfue3o/0NkNfm0CoOYV7a8slobpbNhaS0F9X9Mm2zI0q8UiofYk//zfpS6Dmmj5AR0PUuHg2B7fBlzvg7g5KrvT11grXFrRUi5sfl04bBxB4MnkyzSIntVugPNUeL+JiIZ8TFgIgHw1hgYZ33ffl0vmghHIPABYLmONT2Myaao2GWOssnuUy3YrskGB2+1PUe+mll2uRl9ey2NFnkdPE8bzb4adBWS6bsemzML5GRfIlqkoY7622k4nKXLSNMoJUleB53e2zaIlaoChC+6EPT/EWyi1OpyGaw5ZTcBngKqQLeU3msxAT39y/BzzxZfy0j2SxgJ03E9z0fEh7cq1wTkp0IWSdeovBDIf+nDqUnJQqZHkVdfPgPlhFBoJUJXg6A5UlapXuT+MxaDiAfX4UxzkSUFOhqr0j+CyM31rQYOCSzU7PwB9/A+b9R7E/U7itxWsuk5TPpg2fBZTPgk/OwG8/dJeeTQKeRAsd7IOqCvboOFiP5rV7mH/v2xhooNb+Hvhs0u6zKIzL3tU+i9klZp3eWrkqUJZcm28hsn66QFm2A5SVg3ouBZSltj2sQ3uI26g823UrUNaz51cHysrIc68dlKJiaeIAACAASURBVDX1oKyqTnUhl+beBsqi9z5sB2V5v2MXKIt2AGXx6RnYp9pLBMs+P8Lw6zuAsgYD9wHRc3SZoKyXSrS1kT/UgpPYlKMerlMpxHrhEcdSG8O4rdPnQPXVcA7abI/dgLVnX3BPDyh09uFUG3EKzTGk42jVw+up9bbTaWhja84YPR9eGZ2sF/Wrg/8l/J61wWoRTl03zQU0/pEbyYGBtlDa0mQ4QLqQEQMr1a9fQMgQ7MlJe+r62SRcH2ZcvajBumMLeyT+kfbnzybX+YV0vgQ/fpqQIyVESUDsl4xb8BWK2KnWOzjbRb8kumwACbAqI78RWvxN5Dcahishv2rQJL9RWaF2sVxPfuPJYkIkQ3AHtnbl+XK+hax9wJPfCNhsW/Kb0aid/KYwIXJi9vbcl7SD/CYeiI7XdvIbWkN+48abkN9Ug3j9tuQ3QOBx0OQ3bNmR3wwq1MenQQdNfhPvXbGW/Kb81Cci+Y11jN08m8fQ6WIZ8RG6uLOvdcqTKchvWervfOAdrSnnKQ2HzcLIdw+Bj78JtJDfBDCWfLwG1YXJb3oHZy+99LKV3E7LooPqbhekZlJjBIiFkcUR1bL1lf5as06z0BxVJZJwH5QDDW7PG4sn13G117R6YlGQsnhs3QLrVjwRFy2MPBoGU1mfS4MqAJ7o8MDBm5lTbgS/p+/ks1DzENrdJes0L4ysgG0AXGFk8SXkKeAz5+AUyyJ8rffGIF/UOBSuXq7as06lILTME+AKIz88DOAqNz4/p/cO3e+nE5eJyhwcnLYqgdKA5ksQEVYfc+eaRx6UZQiEFHAmMPvg8zk4wOSThxg/fhb4LGh/7J7RvDDyaOj8E4ZSB+fpq+jg3BHS3QpoYhsWj3X9JKCsQNuWt9fcezoSllUoX5jSm9UpQMqqrQBbQOvl9Wwjgc1p6UXPnFQ2XJvPQ44vAAByJn9YEOe+1KKNxwJIqkt06cA2Wj0Zn8yD9hvIVtDG651/IcM9+BJ/YMWhofvMCwOtVm5h1Dr4PT1nc0Z1DSwVfZ3abpnTeUL/z+xQp2a2iP3I4ifI1+UKXBj3/3IJM/Ffp8Q3pfJmlguX/q8dtPMFqiMH1gr3ajb3OTr+vmsSIGsBIQPO+9hCbudicRW5HuJd34b0q+XlbYhivI7+Bs4capmTVD8InJaZaywMmT8k6JGArJSeDQdck+sxnJdHQ5gidwTg63HaxgKxrhRmMlaxvlREKLJCkXtZbfOc0IbnkdRFm0UvN48GJB9M62udZgtLHGud/k7k2vXAqtC2RneKnl5ovoDVTFlkE1BWQHuyBfvELRJYvbeQAuy7w+HIy5WzHvR9Xy5QnMyTe8bLZTwXCL4SBkKafRIN2eFdup2LRduWo6vGZ1cTOtuSTKCxC1uD5SLJlPQXwac/xgVAjudiCMQ+/0LXqKiqcE3inKvKlLDFO1zdL5xum3y9ifyllnEkepEBdHZmeNhNupCJaPIbn4AWMi51zH65ctsA2Tb4rz8vV/E8TQtYmJh1WhThfoXQZ8A0FG57I4tHUYDMyqkqW5XSZ6Yye2Ib/9UejdxCUhTO7AecE3a1Alvr8BmqyFDIeQlJa26cAb+RZZ1SpVjcNeHu/hh0pBjCh66fQH4jbVt2lIQAOJDluGLJ9kCxfnu6wFif1eWsoCyBuSrXWA2wujdC9aHaeg4q9/fCo2ElT8XjXCiHsu+QDHc7F4suOa/FkcQF15hlO5hs6WVy09e029hS2PaX+aozaPPxWwaKzDoJBEBqa6H1V9D5TmrCLJfmvJLAu2VLSIzch+QValpNO4QOu5XItnJ5uJstIP6HAGe3DoRW23aIuk0tsa6Zopzp3UoE7/IzYvtoSC+99LKV3E7LQlcz11sDvWfYxMEp8GfvcDLjEXixjN59STnO+4KF8azQAFAfLWH2x6iPUgeVOdh39TW0I2xvD3R4AACwHz0BCR/j0QnowT13ki94Q/t74KPjEFUJ+q6cp57GowD6CRiJ/XEsbAMAHz0GjYawpxbGx/wF/CN4BrPvdKifeyj3g/uR4s/vuWk4cPr4ffXyM2+i/MZ3nF53DuK4T89AmpxFl9A72Ac8epH2nS40GsI+fRZ+BpzXnyeTeF8e3HfITMsBt0B3DkCzOXi5dFsPP+eL73kDg286/AKrLR6qEubZMTAeAVOJWhSgB/dg7+6DBMI9Gro+5gtgOAhZo4DzMfDdOzCPPczd68LvzfH0bzzAA5UAx6MK5ukJZp91FTIGj8/AAxcNmb3uYf1jg9WQMDyqMX7vFI8/7+7/x95/4ti+iVKO0Dc+BnswhHnnfVfgCYD99Bt49z/bx2ee3A+nLV/bR/n41KXYA+DKWTTLu0PQwqL86DhEXgCAT9WWZIPczsUiz7jMjwHKBGw32yP82ZujkrGozb8cESj78tXKwYJ9+3Y6a5qi05mDB2v49XQa+1uuwssDtmC155Xr5TxX3k7BqpcrwE5iyrjAoaczGN2f15PrOi4sGWzcTnV8EOCj40a74oQTwFX17ScR3qxfEim5p+dPfpYCQEAovoP5PMKzpS/vrQ9FlY+OPb+FdYArwEUWJCKiIgGDb5ZuHltCp3Y2A80XyTaEj05glisHsRYdfDSIJmn1Mi4K5/sQVKaC49/7sxPgcaxIZsoCPJ1i9I5/vSbT4OPYO/HzXZXg0oBmS9DxKR78qX+5Z7OYri/bE0OgJ89QHFewZ5Mwj+X7T/HW10bA8+Mwrmo297khrj/jF5zB8wGwcs9BNYvjokU3rUAut3Ox6JJdKpIl16kVXJOphNofmRWzQ7tJ9eqk8K16oMk4h1StfBSkHJmJk5WurmCz6JV0R0GXkFhlvLOvthEJizqOL3NwNvQ+L/uVroXBBLB36EoES/ooy4i/sBa88hwQZRlxNN55i7K4+HyW2XgE06LzM7SlC4DFD1Q6x7FYQuFc5WDVtVFysaWnPJSPnNyrnM/iEvxDt3+x2PUF1tcBSaQBJsK4HfjKQ26D5349L2ZD5EXPIxTwD4VAcoWPEVC6mABrzmtC6II/VyKaWk7XBRFgFREwHIKmswBA4hVAheOkSAoFSdRGF/6Rl3oHLgUA6YNPPjxaxuJFXDiqOypL8J6LLtByBaymHq5dgH00irB025VBFe/5OefUVgZGLwxV6SNR/p5J9EeHeYvCRUEGJYqqjPfXR53Is3uFY21CBFv5/oIVYkJUB9aqD9LFF4vewdlLL71sJbffsrgEcYxL/me9+mchLbYt4b585U5QmBlKsuMDwcw+BBYL9xKQUKglcpVWxTqxytzPEudCWDJLyw/HbEQfkm7rvCL9taXFWxsdrR7i7C5JEafE7EKXej7XERxTto0MumTn5fdHth/ZFpKJPNuWjZFO8Ytp/1nYkmbfdk3Vt2HrzYKXyf05WxFJOrn9i0XigFQTtm3OCCvzTSP0BEuQPPw6C9Ob30CokJVIoDNjiNOBqjKQknBtQd4RHbg0iCKi0NoAcHKLRqxYxrV14BtZzEjtbVUOhujJGqwVtl9ZzolcUxShXUnhdqAsExGJZREdkzkvJhD5KNUckzERf6EyJDFX5jfgTWqFZq3KeI6N8y/taD4NMf95VbutB+C2lqUjv4EtU6gzkXdoSh6Kp8sH3PamUJGdqnTAJtFTfCJkwAUlPpKQnyLgp9kikAbz0B8rDeygQHHmnK5cxeeCl6uUeLi2MPcq154Hqcl9qIcmvQflKPV7lHFemQi0XIJHimR5B3/N7V8sumRTNKSD/KaLnVq3m6Ses0QBsmhIC/FqiIAI94RKauL5It1j1rGuSMrv4NtSLM8hwpKR1cbFzsaXO+RcINEhXKPIZsLLvVq5kKOM8fmJhxhHfaX4sAZiRQSqSSMly5ioFiIkmkxI5afwdObvjeIpnc1C/9oqcMS5s4g41WMSgiKVM+KIdFVCnmcVDwWldQRqtXJWyCLL4WCL6sNj8MlpnESfJm6euAgJzxcBUWnk+qpEQeTGMJlg8MFJvGdAw6djj098Ily873x8gjt/ecfNbbBirVsYPbw8zMPUzZmdztIFtie/2SyN4joejtz40nZdq7M1PW1/ck6A68aX3lH1ewr5jM8iwHTPfGxfm5xsEcyQ0L5JX3wgVvoOei5i1mlG+R+g7HnWqa6hGgr9FDH6AYSaoqygw9Gcb0/XTeDr4swtCsdeJeOR/tUCQGUJKlYu61Su81wQgS5QFqHxyIVHyzI6Xq0FrC8FsDcO+A3pUxfcocKEthtOZCkF4Be6hDfk7h7Mc9XOcODm0+NogqXCDPa4Fh5UQEGgpWOUX91xDlmjnMAsT6GhWApgOnXEvQBoNMLsY2Psf1s9G6Ohm5e2rNOlS2gLldx929sKrUv+uS45pAf8g9SohuikKxzakguSpGFvGleewhx+VFGHskzo4ECmk8moIRJSbIFsB4Yk3aekucsL4SMRwt6UZFca6h5jV47MtmFlkzpWEri2DisTua91iCRwGGtYEFereB6ipSGV1XkV64M0fEE5BQHSFzTRSSdNWV+EWHJw6jqhogsFjFVavxDabLQqWyw8MKM4PEzwKlS57U54HhUWhTQ3JnMoGyCgOcHXoCgiOM5bOfl9p2oAc3jgt1g29pVEodS8+qQ8fU+/tvptHNunW60YfTSkl1562Upu7zak64t0rrY06lCb/y0IznO0mVgmABpcGrr+hfgJDNJ0cdVWouMVS2IN6K9xnaX0aySt8nmwaY43Of+8uogkKFufBl4jZs5ypp/m3wCSFPjzSk6fyFkf+h6GfjU/h0R1gJh6rztYZ/EIkjVRyALyjGSp6heR27lYdKSotxX26WxCc1KScVT1iinL8T5yanp6AJgU1AUQOA3zqlBmPA6OOs0vKRTy9mwa0+EXC5g7dwC2AfdPg3EsM1DH/TqvHGNUYt4Le9NgkFLzT6fRzJUSBKFUXxH3/H4cAFAc7Dfb9UxZgYL+/j3YZ89BXMZcGnZefF4sMxIfnyszGkZmbPFzGBNM7bDFqKqkKhqNx46Fe7UKPKU0HMZIjfbRPLjXgHuTj4jx3M+l8lmYg32Xti75KUSxzECRwr1RFKDRMMC9Zd7qkxPgez4F814sBUBlmfBq8mQafDGhFIAvk0iLJczxKVafet118++/6fwdEi4FAEMo7vpSAM+PAm9p8fABZt//cQz/6Fux79HQFSwqy3Tb430WPJmGnCQAoEcvU25I6768K5FMfa02hU7VXps8zwRhmdClwZSOkyJ0RYFPItYO9WS/mU8gcdTJYjEYOCccEUgnrVnralTWNdiTx5qydM40H8rUDkoqS+cAbQmd6srdPJvH0Kns4cUb3xU6HY9C7U8svd5V6ZxipV9E7h642iKLZSSltRaYzdIaJ3YV6OESktjRMEZR5IUUX81w4JySMo9DX69EnMCAe9iFxHcwCBERe3cfZrlyoV3leMVy5e6ZXrD8QskP7oKOVV7OcOiiBQoZKveOxspBKuM5PcP07QPsP4/REB4NAWbU91ySnSmMC7lai/q+m696rwIbglnUqIgwfdu9wAd/6aq3k/BR+Lmh8diFPE9OQ+iU7+zj6DMDvP7Ng0B2Y/dGzrcgoVpx9O4NXR6KXrAA4PH2VuqL7+DcRXbJDdHnyiquPO6B/7KN3bvt+rxPYQZP+oxEOInpK1mllgOVexI9yLEkOeu4GpPOI2D5QmnuiC5HsVrkcrNcHJKiBw0GERuSOThbQ6d+Xtu2EW1s44kzV37XRC6FmlvtnJaiyhq2bzO+iMBj4ZjJqSyjc1Lp2WBPF8yKuj8yx8VrD4JFGHRerprOVCAs2uGL7xPwJFvYPj8KjmLN7i15QjpMb0ajYOUFMSadP50jIiznyhr72uwrOLJPegdnL730cnny4m9DdpFzM2UxqMgo9JiBPEFNWSHh67lauZoYyxTc1KDk88dCOG0+V1aM/wIUBF7q/X7dtAwA9wVUdTjCFz/DWUgdFNmDO33VNiS3pJizsogqvFuYUMDIfcE9oCwkS5H7O1vwquM+aEckslCohDYlqU6+qiocrvEqzN7hqkPdo6Fyriqshrc4qDCwc1WsJ1hVflxl5awNa50FIFsk2fsnGckRfk2jUSDilXAo6jpS6M1jRbJQN8S3J0CwsP0NwEBNJQCYg7HTX9+TwQB8eACoko00dBgYaIvCzwHK0nGOKGwJltvbCy/XYqFlE/mNMiMBeA5ONEBKrU3rl94DnvJapzn1fujDO8ZImYPa0RhIdzzQq7PWqSfFARCiI7rUAIBYboDTsgMyBramoad2kAZG6sKkJQb29yNLtT5f2mmJUCWOSFXrNEQHfGYmVaX3MfiFYTQMJQXDdQIwypCadLCfwqSBkLIeFkLliKbBwPkoxOlblbHMwKBKF5yicC96fRJ1IONKRr52GP08erskxEA0iSAx7y9gY8DDEjSZgwDY13zZgI8et0ZnaDTypQCWQS/a38P87UMMHj2J5+17f4TMt1HzWJXOV7OvfBY7FBl6eReLDdJKo78luzdbjs5F+HBY9vVnlRSW9CFhtSwBqhH+UjyWub4sLM+5Xsyx1IA7EVIXlXRpAQAhzJjD1GtVkkBT5KvjScSjjd27ZXFO5kNfGyDhvi9jfDhQQp0xQS2h4ff6aNZxzBfNeawRkvLyRYzrOqnhSjaS6lCtCHutKz9IuhRAbd2zwhY0XcSPi2Wg8PdH5c9I6UQS4pnC+RBotnAfgMncX97x/K1WzgmtEvJ4uUR5ukzvwTL9PVhecwJZD5mfKyv4pS8FsIskkROFBgxOOH+eZ+PeFI92X8DIzM21gRkOUQeUoH8ofIZfshVRjjeSLEAgJKMloijpnL8r6ku+HXmsyLN3U5EWGUJZhtCjjoaIw4wKZRnIS6K2AKy4N/RxGlSRm0LrXbt6G62Whcq4DNdWKuJQVZELYlDFrNGiAKq6cR0DjSrqGA5Ak5Z5LEsPLc/QqYVjAQ8O18ola1FdAA/vg6QkYV27LzWZQKMvVhwxg8eDaDmJZbFaxUSyxTJaFpLE5S0LMLtFbm8Yxti6XAwq53yuKhcpA0BVhdVBhYG2rirv5M0sCwwHWL1xD8ViEWDoSa7MFvLyLxYdWaltNSS4rjcm7LovVBrJsPO5bztGKHi1au9Dam3miWxZQld4YbP/w8/LrH2rCs3IeasV4DEKOvHJbVs8kGiWQp15sWjAs4OFIcfPzloLKOf1XvO/NeZjll2jUt+TymkyVrmXM2/FZJB3Pj1rziMAFJ4SMEsdl5Bs0Gvhk/mYQU+fR+i1tS4D1ZhGchkvFiieHKuICgdsiySXuYQ1/2StZFw+urJYgmczmCfO71C3JCACcJSChU/IW0YawMF3jhsYH57Po79FrMzVCqVl2Mk0tTy2TV9AHw3ppZdetpSXd7G4avyIT/0GkKRX34isqXvS6jvp2qfeMOaGlY8ggUDrub5KUZDrkIIvPoK2uVFkOtcpzNzwNW0lvpIbZDw7tvHybkM2kd4EXgOFBKXt9nBJinpHNCRkQyao0oyERrXR4FnUJDWCUBV9PUCHWPwYERYcfBP+WvEVaP+IhH7ZmqaPpoiOPV0VLKnQVQ2AQkVtRGRr0CY6O1SuUUQ7ge9T/qbnUe6Nuo7q2vFYKv8IVYqcRk+lVBLL/yY+Hr+FCFsDICG/Ib+1oLIEm4g4pcK4bcTeCCTUAlaFTgXlWdtAehSiVYVx0Qm/9eLxMLTbxiJGpatIRppYaFDBHo6DD0OOJb4c8RNVFTAagqbT1K+1Q27V7VwsciTlOlh3VxMSihQvtVToVuULG6jHQKGXMmW1sVWTx+YnpUwqVUV9sYxhy2UsdSd8Fu4Bd5wXmsshVFFPkJYqhyODe8MYj1ZsgXtD4S9kgRgNQ/Xw4ECVkKxkYd89AHk6/yRmP4Pf0zetAJmP8LO/Ni8HSMOBwyVIeFDg3isbr9vbA5aLWO1cxnv3Tkrs4sdJg8qFkYcDVTfE9U/jcagbAh8epaV3Vqv7SmXpKq4LvmToyx7yGVavH6KaaP+Gn9N7DpUZHLdwkHQA4NLADksUp3MYAIu3XOi0fK9sXXBpb+xJdWaxpsqdA5x+eg933425HnxnH8Jk7sbkHfF7Ixd+Ho3Ad/Zjw09f9tCpXhS6wnVrwngAIjgphAMXjezBrja3YsoSchh9TBxo0r/K1Az1KPS5zIHzIeirdG9lytJ1T0RPtjGnYRNT1tmk6eCsa+cIlOSux0+jU007XsU51+bg1POhMkAbTFk+bCrnmtOzyJSl+hQHp3a0msdPG/MIACzgp6WacxnrbJ7MLeoTF5JdLFNnplmAFou0zomHVlfvPHIwbSBxcJoPH7uhKVAWnTr9TGFQeL3sbIbBX7q/1y3PDeBg4FSVvr6Nd0Y/eYbDP65gVW4LzRfO4Z6Dsk4rgMgxZenQ6Ro8US4vr8+il156uVS5nZbFNnJVCE6ips/CV/V2DV4TglPT6onPIsNZSB+SNKX1aSA4xWq4ZgQnqT5gPMvWQkGy/TnM9uoRnEKzV9tEXwCRVk/mzyM4MZtfD4JzPHK0erN5uO+7IjjlXaA9heA87XEWVy6Jw/C8FbYuIsYoZ2wdQV7aYemdqGRWyQscQFnGNp1+1y26SpkqykM6vV+yLq9cF+Odwpz6U6ynCNB+DDLOmXhd8yd9G9NcyLYUHg+B07Pgx3Aftu0dnLcvRX0XR2ZX+nXHvnorkfRwxRItX3/pAxB/QUsfeWp728/b6iGS8XzqFPEknRuIaevSl3wFqzKmnYeTM8eutJ+lkSfSpX9ben8H92kSEWhhoOqSTr0014nWT6gJrEpakwS78Tj6cxRdQWjfO7lpUDlwVm7R+GQ/0TthagfiIulTAIxHe0aAXzaEahCuC0RGkwloOEz5PzN+V33c3LnjUuk1B+f8/8Dxlinqt8+y8OakfjklRz/ZCpjCPQSmgIQktDOsOHRmn51MADIoHj4AT6egA2c6rt77Dsxw6JxtwmHgMz3NwQGMN/dWjx6jePgaVo8eJ32Un/wE+OQkOsTgGaZeO3RbmW99ECuqP34K/mvf5crZ/dHX3fVvvwn7+AloPIY9PYvVzo+OUdy756qae8eWsF8V9+/BPowVtc23vgPaG6N+9hzFxx666z9yeprhEHY+R3HfVe9effChO/4D3wdz4qIDfObmhvZGsPcOYI6dc+7ob76Jwz94BFrVqF/zVdstUDw/hf3wo3iral/glxnFm68HYh+65+ae90bAdxzDlLA32fuHMM+OQxFk/vgboPc+hD05QfmpT7gxPDyEOZ2D5gvHlu1frqd/44ErUlwa2EoWc4ALQvXhsWPh/vNvBd3wPZ/C9O0D7P3b/8/pMBq5LcV0AR4PUDyJ2Zy8N3JRj3ecvrJt4K//Ff7qv/s8PvVbPvxqGcs7FcbvHuPxf/gAAHDw7QXqcQGyjKNPu0VhdQCsxsDwKXD/L5Z492+7Rft7//kH4GdH7usvzysZrL7/01jcrbD/h+8FZ+r0Rz6P1c88xt7/cDcEoCZvDbH/7hT1uAQxox66dqevFShnjINvTXD6KffsEgP2//q/sa3cvsUC6RcmgUMnUZI8cSoVWY0lHdgeHbsQpnwhmCOzd4Bw+yjEbA6rPPv2+KTRj336LNR4kK+KffY87G3t6VkI8/F8DvPuB4m+9tlz2MXS5R7UNeyZVFxn90VRnvlQRf34xDFYqTGS/+oJQYp8Aa3/omlPOgDQBx/Bem85L5wXn2cz0NkkHD/8wwL84WMwAHMWK8Hb+aJZOT7Mx/MQkaHgH6lCNfYQkpzNYGfzsOia9x/BTiZOV5+rYSYzYLWCXa1Aqvr8A+ZQzdyoryeVJfjkFOb5MCG6Me89wv7zU9RCZTibu/vjPz7JF/vsDNVkFl7UcB+XK3zqt2YY/OWHfqAW1aACn57h4e/7a4/PAnPV+D0XtrSDwhcZWqJ4eoxPLxytHj9+GhZ/jbeo3nmEauBo9SQqdPBnj/D8y29i8OfvxPM+3Acdn6KqHOOWFBkaj4fAqgadnOHweQydFpM+GtJLL71cstxKy+LGhW0Kq96l9qhYP1uwLdMW5yTSpscm3drqcubHbObjYQ7bizZppQ4EmmO2aZutP3fp2mYxamIY7WfZ9v4IBFroA7QeltN5UH8j2zJn2Tk5xJosg2pXbzW0oSQvMpTAtNW4yHKgzEv6zP+XWrp5Gzu47m7/YpGnoAPbOQlzh5P3wAdEoBDx1lDtm+hM1BGQNgRnUYDNykGyVR8S0nJp3x5dVxSRdEXSwj1EOcC1A2GvTxdvi8AY0ygSFM7ritjkx30FMNeZc7xSVcYaoIBLvdaoSMADtyxYpe87lmph5IrRjuDN1179AE8uEqYsPZ6Asi0LMJcgcv0HfodRBVP6OZb7KLVHB5Wv6qXC1WUJHg1jRKMofP8c9dD6FUWqp5flnQrVIMLseThwIVVf17SYleDKETjboUdyjkvYwsP2JwMsD0o/taXbphVFKGcgzw1XZaITDyrM7hrcHQ7iVnk4cJwZEqoNqfEVaEGOUV3Xw73MWqdE9GUA/wWAR8z8A/7YzwH4hwDEm/XfMvNX/N/+EYCfgsMg/9fM/Ntba3Me6UJcbkBwQvkcAIR05QBp5qymqZzLaXUwMAeEYaKWpD+rwshQVHS8WkVY9XIVa2WKPrN5Uhi50Z9OrZZrlquI0wCSvwfPfo7gzLz4PJmqWqQRaRmIU+Brik6m/msXk+kkDT2NSLg5ZOWHCFiHVSxErZGk4V4AYKlrypzQ+Ic50AjOpyexildW8ZxnzheR9DOZxvn04wz/Z+e26SnzOX73GKwIezGbgydTFE+PfT8zTwXIKKXodFkAZeHIb07OsPdtF+EItV11ZKq2rv1F6hOi41Pc//ND5+j2z59ZLEM6O4CwuJiZI+jh6TQNll5yrdNfAvDPAPxKdvyfMPP/qA8Q0fcD+AkAfx3A28D/3963xFqWZFetHXE+9/d+YAzvmQAAIABJREFU+V7lt1zVTclut2WQZbU9QcgeYKlnyEMmWGJgD+wZUyQGlocwNFIjGCFADEBCwMiSJRDYctsgYXebKjdNdVVWZ+X/vfu/5xPbgx07Is6592W+/FR3ZtfdUirfO+989ol7bpwde6+9Fv6AiH6Guc9G+Yp2qRRA2ojxHFCW6mUozn40El5Mz5uI9To2W3WazUQDQ5uE2osWZjJGe6Hcj74MNxmLCHLyZTSjEejoQN7WbRvAMTSdgs6uiZ8zT9s2HoGaqYCUlP0bkGijyEHDQawY+AfYTMZyfjXfzORmMxgPEAoJuqLoyOa1T/05Tk/AmrRUkeGyBE1GgIcqVx/cRP5X0hlK2mfADMyXMUEMJBOtFfZqTWaORvJGHZRwT/zQ+giFJmPhpdhEf9xjgBfLKDtwfAizrqSHxNPuA8D6p29g8HEGTnRDAABFLiLFo2EAkzEz6PQE7fEk9IbQcCBAqqqWPoxE7JjKEnx8ECDcCrji9QaPfulaSGaCGa7MYZ9MsfzZGwCAwf0l2oH0xqxvSNWnGRo0A0J50WL0yQIPf1mqKzfuTYDZfPu5vX0d7biAbVs471fzlRv45JsDfPD4NOxWnY6RP5iBB5Lg5Fwmi/poILIDD2aorsdnhGdX1w15boKTmf8bgCdXPN/fA/DvmHnDzP8fwPcA/PKVvdnb3vb2xtqr5Cx+h4j+AYA/BfCPmPkpgDsA/jjZ567f9nptlzTgC/IddEJ4MrGRLMFFXHZt7r09ebPZvr4vm24BohYrCYubJkKEHQPLVTdhmITGW5ybbQveVMGPwNO52QCLpAsz+bu+qUPSsW789h7L0mIVlwl1LapZgLytPYN5/mQZ91km75u66t6v6m84FtV1LZnW0ZetsJ6M3Jsyii1WvqnOhc+G5r7ZraolP+evWTxaAMuVZ0pPWt01CgESzgwGL1ciAKRLjE0F0FKWR1UdxkzG3IGIQvkYJFESty0mdyspj3qz6wy8XGNw3zeNXSxASymdqn65lk6zZQ17scDBpx6CrYS8if4HEYGmC1j1yW+3j+c4+mgMWqxCcjcnAi1WoVlMcxZF3Ypi+2yB3MbPjJovnoPznwP4XUgu9XcB/FMA//BFTkBEvwngNwFggNFz9v4CjWICkIi6WfTLLO0NAXZDpj38Ol0AEVHoEdiCZmtvymVupvByQNbAivvnBCZtu2t1gXvHBGmosCgfRp+XMrPgutuxCOMTY6rVmlsQddfE/uRdtGRqKfdEQvsfujEDp6dPhCa/h3FU37PMc0RYv80n8QqfAEyOh7aHW9NNqMLjL9LeEv/5SB+K7S5lrAGUf8KPk45nO7QxocosPBXWyNIDkIlCW9R9grMtDVxpYFoLzjM0wx6ys2+ZDdfXzwFFjnrieUAUg5ZbuQeP69DrcpHJ8rfI5WdvfIXHPbhw9V2jMfN9/ZmI/gWA/+x//QzATyW7vuu37TrHtwB8CxC498v48VosfRP2ykoBGr5j3yudup/05Ch42xG/TUuxveun+/9I7FnXSSHTIbHZTwA7bDGRp8f2f34VH9ntLr+mn6Ou/dOyqJpzVy+rPsMoZWr3pWdOr7XDr0Dj2rIvgapPHNrv421d/pl0rh0PiNteUfQ5tZeaLIjoFjPf87/+OoC/8D//JwD/hoj+GSTB+dMA/uSVvdxy4CoJzku2658T4hnAJ9hcUgqcYXeCEwg9AbqNijxGKLpvWYLqphtZlIXAkwHQdCb6oQCwWkf9yUSMhpZLYb1OO1Q3G2HDKsvANB2y40Xe0bGk6Uy2rTdRm9MnL4NMX9FNcPFkFB9ox/KmK0vwZBQwAZuzMQYPvIBOkuAkZmC1xpayOgRKHcZa73s0BPkkrfrHk5GE/Ik/tFxJeJ7sQ+sNeE2SkNYE5/URRrN1NyIwBC5zqRKMh7EEzQyejNCejGE+z4MPcu5KWLiTSgENSrijceCjCOP8yODi/TwgMyXBmSFrXUhmDuAjCmYsb8u9NwNCPQKGY4tJ1WL6FYlUDgdlQLOmE547GqOZFMgfxr/X10Y4/7rDjf8RP/PN2RBl48A+qnE+wVkdF7CVQ9k4VGdxf/7+a+w6JaJ/C+BXAZwR0V0A/wTArxLRL0Ci4o8B/JbcG3+HiP49gO8CaAD89muvhOxtb3v7sdhzJwtm/vs7Nv/LZ+z/ewB+71WcehFLdTVeKLo1vTW86m7outYnyQhtOG9I1qVrYt13yy8jycHOujeubSkB+JC1AnRKUYGZDet8Tmj84MFcsr13XdMDaxHFrtL+voFJaQcvpUYxPidAWSaJMk/N1w4MUBZS/1e1cmYBbnkZRsAHWYYCL2W4h0zWz5zZsEbvANSSfEzMS8Ro0OUZqG6EczNRDmuHkldgS10uzsxvL/I45n49345yWBtzKGyM5CeM6eZ/rAFnBkb9TPI5zUQSloBEY24o46V5CFdYtKUBsUQUAFCPgWZIqDYC0Kon6msWno2QECaCyyUhGnwE4AoDOqngBnlY1rQDCy5t8Ef/b70vnBm0RbwvfoGGj7cSwblrYtjVlvvMc/QThn1xl966sWM9ToGd/AL6Re9d0+nD6s8DQNa4lgB3CRy6DzxzHB8qAGz8Q2UNXLKsCCQ5SgADJF9OjzC1vacls53EpndcvsR+l7Y04gNRTKwhIQVWMBc7wPmEZ38SA2Ti7CVKJTlow3YhtfXasnpcZsDWxJyPP3dTEjjzX3xFNBJJw5ZOYmEt74SAppdk5lKQllzG8VU/XJnBqp9l/MybYTJZtCzIzMyGicEVFq4Uv+qRHkNoxkC+AJw1aMYR2s3MHfIlZpYJZ2BiAhcyaR8eLgBThOesHRDYGplYmOGKZGzIgIsMzUjHCK8Xwfkm2qUTwwvAvbf4MZumm+DU8tsu5qe2FZk4PbbeLrdyLRJ/7Pso5JpuN/+hMaBa4NLhS6KEK4CUE3tcELypEnIWDtc0y4jgdE0jaMykdBr2bUSUaMv3TVfEBiSt0rSJPKPFtAn+h9JbG5OFkfS48ZGF6Tz8Yb/VRnwEQlnULNfSrato0eUaTiUG9U27qQX85en6lW2rvGhB6xrILJzP+JNzsAvhJqW67VY/qhqmauOYVLUwV609/2nK2EUEO9+EbSo3yI5RPgHswm9nyfPQukLpgXrZsoZpLdAyhmOfQ9jIRFHMGHbTonxEYRy19BsiC2tg5xsU3kd9ieXTBuefHeJGvQgt6sW0hVnXMhEwg2o/NhnBrh3MYoPyacqmdvWX7Fs5WfRr+fEX3t7nkrVJn5SWV+vYi6HnUoyDvqVUc7NuELHaTpSr+tdZrSPkW9+e6zVo6r/sVRVmda4bmOnCw5pdPD5V50qSXoHMt07+7u8hXVaon9y2AptO9tWfOWnDBgBczAP2IkxGCrf2v5f3PKy6aUBpdKSQbp3w2hbEsnTj1SpiKhYL2aeqdyqI8XodcRazRcBZKGKViGSSaxrfwi9jNvxsDprOAWth094Qx+DlUujrEmV0M50jJ0qg8FJ9Uj1QTqDzaBoYAM5vCwnYtsXJX9UB2g0AtCwEwv2JYC/sxSL0hkwqTyfge0PspkX2ZIHTv/REOYulfzZicxi3BubJDLTcyNj4zyG/P8Xpn12HfTIPz2hZtzDns9ASb/w42EUJqhrQ+Qxl8j0x9RePs/jR2Y5ogbI8EtJYC3aeM8IkLFXPqYYYD7VW5iBzcuzJbySrTcslaDj0ePzkjdm2MMNB4DrkqoI5OowPt74Nrh3DXMw6XwZzfIT27AgwgGka0JHnXWwdmjun0on4+KnsfP0UdJ9BoyHMbB5g6G3dgA4OhPbtQh5Q5T8wR4dw1xPym81GSHLapzDHR8FfIJLfmKOEBAgA33kH5sIDjPTLOfZVgwvZ5+kvXMPJtxvx+8zT3TNgns5h+lwjxoDqGnTtBFDujBPvy7CAUXi8fh7XDqTHQ/25fQbjWriLFnQq99a8cwizlCjKTQbheo9+8RjXvpOBdekFgAng3KD4fIbmYAA7j/oezXvXsbo9xOSJh8APSiG/WW7AozJICoqvJapbh4GFW8lvzGyGT3/NBj4Kcox6kmF0twwQ7oNPR2iGBuQQqh71BGjGjPIR4fQvc/zg1+X5/vr3TkHnU8l56bNDhM0H11EdZThYV3B+Epn9/Bne+43v4eLj90LX6vxOgYMfDNGMNGchE/fyzCJfMiafjDB/L0oHNPevTgu457PY2972diV78zk4d+UhdokMAc/nv0xNw3UP9w5clQlrN6zt8lIqXyNFNfRA6ddjA6e8gAKUUv7FsJ6vqi5D+HAoobyuiYs8EUeO3Z3SWi3NZf28S6eaA4k4lJcy+LvjGL0PwDfU6T66xEvU3wGARkNZEjjXVUCra8nL9JjEIwN6l8kbzgkbGWJVSsdSl4emyGUfFxW+yLN1p4I+4tdIWL06cG8n19XcU5LgpKIQVS9l2/IM4ppn6nymKuykTOBamdlskH31ffCjpH0qz8CrdWT3rupQFQqiTFkm21qvGXNdmsH4h/fjs6ddtr4iRXkGN1+EcbXHx+D3boI++Tw+o1km0PYk3xWu1zTSLFlGYag/mv5HXNQPr5TlfPOXIV+U9RCFAXeF7SXL9rG8tfbf2iX9u4KmjG8VJ68S5q/Fjr2CdzLB6USR5ks6/m5PiBxa4nt+pv7uOKbze9rCrRNd66+vk95yJce1bRdhekniOU1OyjUhX5IkR6Pj30fNBmrDdEwuy1MtFlGKIOkNSXt5wkSmFYcEjZqOH8uF4rl9fw73fWAGP72IVHhAoDKEdq1q7oE50gdaGyelqgKdTzv32CVXkh4eDv1GmmdbgT5/3BW50n08OVHIwWmvSY9CIFSurmBv72TxAhqNzz+X2f5ZWbv7rM0vdfoUk2G2tpGWWdNFoVLjN03s4wAEUeqlB79oU8mA8Dt1fWZlaYJUHdggYCp0G4zpsGPLvWnm/4Ud6h7v/QhfLO3tsTaJbpw05RnqRByk+9vY8/LSY2p7Y2Rt1DUBYtm4pyED1V81JiSK2d8P5VmMMq0BX9LwJfqrBrtg60E/1t/rq9qbP1nsWk5cssS47O35/PO78DCHXKhK/nVkA16wj6D31gxaHei9HbEjStHKy05K/Bdz40Wt71ugyQvRV1wa7fRXOSM6nb1Jgvolv5ShCxNR3iD1lYzxfqW9EQk5DxhoVkgO2IoSX8p8GRoAGCwMVynRc4+8CIjLPvbK5iFBrmOnEYLc5M7LspZ3++Vvx/HFk3SuvqrtE5x729vermRvfmTxPHsR0aHLjg8/m85blAy9nrf4JWpaHWJbhUX3jiPj39bp8uh1+XUF6yyhEvUwwSO4CDgzEPAV2ogSTZZOHfGblwz7dy7nbAJY8z6mUHoQBRnGtJ1dhI0ptPADrxCx9Sj8BMyXNNHpGClzm9/GzOJ/G/lJQyI0kae8tO1f79/a7ncghRmkS6FXjKDezsli1wTR3/Y8Wj1Vi/J4DTMoRTdE17peq2LXtSnLw35utYIZjQJOIXAhDgfdUNJfQ/ESbjoPHZ+8Wkd6u8eSVadBCbda+cpHHf2tZf1vRmVHN4QMiS7oKNbQ3YXvOt1spNoCwHmVca2SGJ+ddyvhozRHhzEUToScaFBG3Y9b18H3HkiuxR9PkBCaV+1OoBWVo0he4+/bDA8CRVzQgC0LQZv60Fpp9lxVx2rIaATUVfi8whRy452IUwkXNjDHojROZYHWa48AgD0ag4ZDtEqtOBlKR2zTCK3eMi5ZKMtAo2GkJRwOADJw5xdofu79ID4E56QiMV8Atz32YroIBLruyOuG+F4PO9/APJlh84Hsm3/7Q0lmpjkKdrA3rkvl5tGTML729k2cf+Mmjv/7x3HXg7GIRGlVTHtZRgMQAHo6BR9Owv70g65W7bPs7ZwsXof1MfEK7b6KdmWf/GYXu7eyc6fsItaCtNRoKLJVbyhuT/1J/ey94fX8ALrkN+l5TExwPZf8RsvPeSzZhvWunlcRoyPPiG16frctaLM76un4G1i6Y/9F8C/PpcTXxt853IPft8iFoMb3yKi5SQk77Y2jMcLsnWUiLJwmR/NcWtGTZjYqcrD3LU1cIsvkPOp7noexrY4Sdm9PfoOqQjuWL6Kt6tBA2Exkm/Z6FABouUF1FNm9U5h5sCIHD0uJJPwmHpZYnRocl/ELzyOhLggM3tp0NioAB9iyAI9i6ZT734Nn2JuPs+jbVZcduyILxVa4pN8jwWh08AjPUFEPuAxIZEJZDvZUcaHL09AzcRCKgQAkMgj6lQonVuxGeh/qr49udp5fMQxALNO2bRffIQ6Gio+a+tGHwpN2nioWYzIW5Kv3Mxzv2b13R3JRXjJ86VN8CpmwhOA29mtIVaDq4FUUC9Gf3M1kLJiFvlkrfR/WdEqcpiwBa6MqmkaMHj+SRkhEJNs0uvLjzG0Le3YaIg4w++tVgSSZN1VcDmh0ZE3wi9frgLBt732+M6I1k4lMFAnDORUFcOs6+NMfxm1lKViQXiWGijxEPAHrAeCPzv/DHmcBYKtc1Gkx34U3uEpmPOl72P1nin9/Fg6ih31wvbfJVmWntybdmigMxWpOWjs3JNWDfj6kvwa2sk8H1xB8QQf/4BarbbyBnvNZlapd1YEd+6VlZK6bmLvZwjh0mbLcfLGz1E1GJQpMxz9X1SDTk3HwLFcmy6Ikgvq93nQqFJRlAptPJAXjUHBYYqX9QYqzYC2NezkDF/pAdk+2XFUS8RDFJeV8AfPgcRcb47EUyc2H483xUUeCQny7eoVvXw3Z2972diV7+yKL/tLiWYnMNHxHd2mhyTIN1c14JLOv6oFMp91lCyC/ew0PTci5+VySfyqa7K9hj49EWDeZ5Wk4DIlM9/Q8hINuvggq56pmbg8ORAA5y+QNqMuIzQZmMPAJUP+K0PB+OAzq7gDQPj0XfZDVKl537t8kPkcT3lJeryS7eSN2qCYJSRoOg4APv38bxkOMaezp5HzXqZ4H6EYd9nASQ3h/TSqLjo4JgAgl14a302O48wu4TQ2rjXeTiU+CVkAe1+vu/RvI7qkQCcX/Mwv2NIatV7sHAHt2DXwwBn/yWfCBxiNwXXdyNwSI9sjBBOwTqNpI2D58hNU3fxGT78YEJxc5aDpH8xXRDbGP50JuBKHCA6TBqx0Y5NMG+f0pZj8vn//BH34Uxzl5nu3tm+BhCdz9PCwBzc98Ffd+5RS3/+vdOAbHE5ins5iz8Ms0dzAA1y3soIQ7jglO/iguSZ5nb99kAXS7TotCsv3JNjCHPEInn5CYOfTdltOphHY3zkCzBXAs2zGbSYWkbUPXqSlycOtgDiagQ+m25PUG5p3TWEHQa92+AfP4HKzU9ABw4wybd4/BRBh8l+HOpIvS3L2H1d98F9Qysvte5O3WddDde7LuPb8IHartg4fSIXt8APNQvhjaZm7eOcXmvWvhHou/aECHB3D3HwK3fGb+E1nf0nAgVZh3pCdBv+Sbn72D4qF/GC9E7IYPx1jfmKB4LGv7u792gnf/gADnsLrtu04bh/LBAubjNjzklEKX79wUoR8gdMbWJ0MUH/llm8/Qb24dorg3hZlKCL/52m2UH5L0Xty5CQBY/tQh8osKdrZBczwIHZef/t0xbv3xAC4juDy+JNrS4OD7B1i/M8ToT+IEu/65O7j4aoEb/2URfNjcPkQ2r9FMchQ/jF2n7nCI+fsjHP65fOk3t+XzyKczNL/zCOf/Snwjx1gfGZx8dIhPvimVr6OPxqgnBHKM86/7/piTCoeHC5x/dojTP7uO937jewCA1f+7Cfr8seRlEgTn+TduYnVqcPMPHcyDxwCAe79yiv/9j38ff/vhbwXM2/kHFtc+nKCaGICFZAcAFrcJ+QI4+fAAT78Wv/bVC3Sdvn0JTmA7aZkmLIFupHFZ6dS/kXQNqhNDJ2LQJGKv3t1PVGq7d7g2ADMeS5ShUGf4N/SglC/gfBGvtdnAnhyDWxdKp3YyliSoNjRpMlSjn6SFOW260rc2IBOARiahRKpvd5+/Mf6Np4lVe3otZuPrOrKCFXlc356dAE/OgbqJrfrOAZsN3GIVKfISxiwzGgV/Q4KNTEyUapXBJ+g096DJVG5q2AOvpDUcROlD37AHADg9Ac6n4q++WVsXpAgplxKqfu7m8BA4moDveu5pY6LmrLWdPEQonfrjoyLdFO7v/C0UH8VzoCxEUtA3h9FiJduZ4Q59ZDHIJZ9Ut7BP5lj/DYksyv/1/chnochMa+WlURZwD2OOwr57G+e/dAvH374X80FlIS89bbZTrdOykCrJfCnqct7+52f/Ghfrz/cJztdmYcnzes/XEbzpJ0PfgElcrSNbIBu2f3YcId9aylURaX+OEHGkTWkv6Ec4Xv/1/VFF8zBRJf4BWz0U5PhFhMR3W3rKnWrnvJUdJIZc14mPlCZttaNW7RnPgjJidcYivf5rfI72Cc697W1vV7K3M7LYxX6lXBNXPYXtlkCpyIEqwQ0krctbx2ZZWEJgs5Gfe6UzGpTAIqHUg4TaNBzKMmS1jgjO9Ub2T8qTlGWS6CoKv1zw4SRzDJf17aNgJ5+gC9dbrWRb00T0oy4FPL9BuA/FdyTLGPZdo/0EpzuZwJxPZWmigsaOweyAlemWafV+En4OTfZRWQYJx+DfuKtOR+MRaLMRPIseNx6KUnnttznPPnU6Rr72GIMEKMfZQMZqUHYiNhqUcKNBxCKUZTfBmVqRgw/GgUNV/aTZDMtbJfL7UTeEywKmqlGdyracKAgUb85kfNuBRTsgFNMWZd1ifkfG8dqfZzslNPlgLICr6Tw8s+54gvMPLA7/TxEiiPZkDMsclcj8ddtJCVM7WADt2WH09QVyFm/nZPFatE67x3FVb9XoL1Mk6wO2dvNIbsCesyFgL6oa0Ex33QCkeQ5PgJI8yApEChwOiW/cth3t0MDBUFVAAkpK/x54NfWL7Alm+r4HDsj0Pl0cIwCwj2dR8zM9drOtddoZD70HPbZ1O3ERac6CF8v4swKSfOs+101ngs0ezWUcyXSWOeQn5xTsJZyeSxgArU5iOuG3rTwPac7C4z/cDjzF+NOVcH/qvusKvFwhf+DzG4uVSDswo/Qwbi4t2BqYdQ1zPsPBD4ZhDLfIh5hhZgtQVcv1Nc/2dIZrH04kR+GfHcsMzBbhpaet77QWkmOeL5FOD9Rc/QX7dk4Wr9vIA2R6MO6thi1t6CHTeXPtgnuL/iR14d6JjkfKPsVAAEWlx+9s4lJL6PJDQ5ZqXqT+qm99GLtyYvR99xGHuJugAI0FWT9xeS1POI7sZErkEs4tfmkiVaUHOudNuDKRbtPPor+PPvjKZuVY/q5jnGdRU7WjwUpRD0XP5Yzca55199PIMssiSbKOn9c7CX/XuxxmyPMI90ZmRWdk4COhTRW0R4NSmBdGJha/lTMz1/sHuvwmWSbnSKEAeSZVD01m+jGgLAuJzZAYL3II8tcGrZfOuF/B9pMF0I0e3O4349Z+r+Oyb1ASM9iz7rGjE9pL0l5yDn7Wfi9pnXNddt40QegpE7fYvHbphL6EUT+hucu3XRW5fjIy7JowXD3PNMF56d85XusV7cs7WfTbnYOwTpJj2KV1GsqovYihZ1uiRXpuz9hEFJXNmTxTUkoQ44/fdR49PjQBBXKdfoMbBd+2Hj5Pl7fle6J2Hhq4lFEqqJjb8AWkNDewo8IRI4teG3bvWp0IKFVyS8SagoK5MaLGZpJIDbI+N8ZEljE1VXczSZTifeKs54Oh5F+/9Tx9TlIch41vcmZRWrM25AvYK6DDcdAelcjCgGoHk2eBhRtkIsNVSlyj1zbKlCZj0wwFdBYqbLm/T9+2zlo6zb1IlE18lZNvfWaX2b4asre97e1K9nZGFldRUX/eKXQtl5CopDqfzz42snQD6PwcrBD18w7tm+eFACBviPRaZY9XoNdi3MlvGCNrU11TazdmnlRp4COCPANtKGqsmiTSSNrkwzEenCYX43AvKIuQy2gOB8geZBJlpX7XdZKvQKAQBODZrOv4MxlB3yZt5/J/4ZOvLvzOmp/RtfagFP6M5DgAqI9KFOeFvC1DdOTvfbUGkm5LGJLqyKjsdGbSoAQ21LlfGdtcOCHmeRgnHc/VqcVw6M/tGDzIYdYV6iNBcBZ1C/YKadWxjFc7NGhKEqWwRYnlmYzDOMtCZNQh2x0N4EYFzOPYDesOBljcJnDyGbSTErSuBXLOHKKb5qgEVQ5ZVaM5jForbH/ScxZXqYaQAeBJd0MbdILmdL3jApjnGazd7ISEJgkFyVppO/YsW5H+3sv5pX61bQQLdYBDDmh6X9BaOiVJz+F6eZU++ayGnmkVoChA4zGodbEUSCZMjGAOvRWUZZ6FO/ExvZc2+muqJn6R0mx6n5cztUTeUM7jAJRxssoyCZ8zK+Q2urywJpR/g19NK5NJ67r9PpXr+gO/jPPdnVDJQ7W6kS+W+uWTiOQYzY1jZEnlCFraTnpOeFjCHBwgW3Pn86NKqjXGq49RHRHGtkryOWRg1w5UNciXSZWqP37Kou7ExyAYVbfIFwAlpVZTO5F21CVbMjbLOwMcPlmECYJeMI3xdk4WVzGPhNtFlgrsLn9eymGR7tdst5LzbI7QHq5rR1/a7JQPk9KmSOTFcmafh6Ffvkx946bx8ohdpqy+udUa1LbgzabTAi28HfKl5sUibAczeLmKZdZ+Kdlvl9Jpt4QY7vkyOYCk1JtiUrQZjupGIoWq6pLQuhZuKeXTUMo0JJNp08T+EwDZw+k2n4UhUF37pj7X/TyWK5BzUW91vpDxahrYqoJTpiznBLMyGMTmPWZgvoCbLzD5ZCnlS/jkpDHgVVI6nS1CBBRKp5mIFJvFBnQ+w+STURzjHZMtPZ3CloWHvvtmxUGJkw8PwPN4zxYQSHevGpJVNQ6fLIDzKfK0ubHel06fuzzpCBIBseuxB1LadV5lVJL9vGiLYgD8tQJoKn3JPD5iAAACWElEQVTzJaApWq06QKkARnr6NPqx2URSHvXXixrRoNx6qBQ8Fd4qq7WE8VUdw+bNJkYX7OJ9ePxHSssXzuvBSmrt6QGMF+bZAlFV1W6mrARElgKwqNcvQqMRQKuobj8ayZuzbTu0elxVsj1ZhjTvHCJf9/AfROCBB6YNBqCkK5ZGQ/BkBHp6Hnyg8UhwIKNhHF9mGccUlDUaSdJxNsf8vREOzxNQlqf6q65LL0tuTVyGnPlu1cKgGRmUTwuUzEFS8Pj/ljsjMz6cCChrvgh8FO54gqdfyzD5TvLZnB3KhKHj4ieN5nAAtoS8bdFeS7pOf7iXL9zb3vb2mu0nN7L4UdqL4C8uq3e/iZiLL7Nd5fMIGIaXu8TLHvdMe17T2SvYfrJQ20WM+zrO19/Wr92Hn832vi9j9pJgsdPC77AVVIaW/x2oSsVrKGx9F/Iy9XmX9MEuNOquGr/pUQoY4c3oyCdaE3AmKX6ELW3fvye/AZntv/mE6tb+l/G8dtCkfj/HaAuK52kd2FpJrOceR2MtOPPEuX6bKwhtIbwbbC3a8jnPnzVgS5Kw1BaAzKAZIGAp5PwWxiNIdR/9n3yCVrfJ/e6+3C57I/gsiOghgAWAR8/b9yfMzrC/5y+Dvcn3/D4zv3OVHd+IyQIAiOhPmfkbP24/fpS2v+cvh/2k3PM+wbm3ve3tSrafLPa2t71dyd6kyeJbP24Hfgy2v+cvh/1E3PMbk7PY29729mbbmxRZ7G1ve3uDbT9Z7G1ve7uS7SeLve1tb1ey/WSxt73t7Uq2nyz2tre9Xcn+GucO/HK7PrHAAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.02746081352234 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-07, 'kernel_type': 'untiln'} is: \n",
+      "[[2.38503845e+03 3.06000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [3.06000000e+02 9.20009875e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.38503845e+03 ... 2.40103845e+03\n",
+      "  2.40103845e+03 2.40103845e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.40103845e+03 ... 2.29188484e+06\n",
+      "  2.28022452e+06 2.42437889e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 2.40103845e+03 ... 2.28022452e+06\n",
+      "  2.28025072e+06 2.41654064e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 2.40103845e+03 ... 2.42437889e+06\n",
+      "  2.41654064e+06 2.61430321e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acda90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.0060384273529 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-06, 'kernel_type': 'untiln'} is: \n",
+      "[[2.38538455e+03 3.06000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [3.06000000e+02 9.20098759e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.38538455e+03 ... 2.40138455e+03\n",
+      "  2.40138455e+03 2.40138455e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.40138455e+03 ... 2.30026206e+06\n",
+      "  2.28895754e+06 2.43606401e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 2.40138455e+03 ... 2.28895754e+06\n",
+      "  2.29018211e+06 2.43038688e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 2.40138455e+03 ... 2.43606401e+06\n",
+      "  2.43038688e+06 2.64291272e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ad7ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.40988802909851 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-05, 'kernel_type': 'untiln'} is: \n",
+      "[[2.38884775e+03 3.06000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [3.06000000e+02 9.20988217e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.38884775e+03 ... 2.40484775e+03\n",
+      "  2.40484775e+03 2.40484775e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.40484775e+03 ... 2.38673927e+06\n",
+      "  2.37884735e+06 2.55512766e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 2.40484775e+03 ... 2.37884735e+06\n",
+      "  2.39293586e+06 2.57324308e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 2.40484775e+03 ... 2.55512766e+06\n",
+      "  2.57324308e+06 2.94617734e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98abac50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.33179807662964 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 0.0001, 'kernel_type': 'untiln'} is: \n",
+      "[[2.42370016e+03 3.06000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [3.06000000e+02 9.29945244e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.42370016e+03 ... 2.43970016e+03\n",
+      "  2.43970016e+03 2.43970016e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.43970016e+03 ... 3.59458919e+06\n",
+      "  3.59137109e+06 3.98872127e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 2.43970016e+03 ... 3.59137109e+06\n",
+      "  3.86923540e+06 4.53760238e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 2.43970016e+03 ... 3.98872127e+06\n",
+      "  4.53760238e+06 8.41969524e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.86571621894836 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 0.001, 'kernel_type': 'untiln'} is: \n",
+      "[[2.79503622e+03 3.06000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [3.06000000e+02 1.02609523e+03 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 2.79503622e+03 ... 2.81103622e+03\n",
+      "  2.81103622e+03 2.81103622e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 2.81103622e+03 ... 7.37965672e+08\n",
+      "  3.83878317e+08 8.03079422e+07]\n",
+      " [2.00000000e+01 2.00000000e+01 2.81103622e+03 ... 3.83878317e+08\n",
+      "  1.85069895e+09 4.44534717e+08]\n",
+      " [2.00000000e+01 2.00000000e+01 2.81103622e+03 ... 8.03079422e+07\n",
+      "  4.44534717e+08 1.21033787e+10]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.99593138694763 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 0.01, 'kernel_type': 'untiln'} is: \n",
+      "[[9.73413510e+03 3.06000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [3.06000000e+02 3.17093132e+03 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 9.73413510e+03 ... 9.75013510e+03\n",
+      "  9.75013510e+03 9.75013510e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 9.75013510e+03 ... 7.07909124e+21\n",
+      "  7.11182390e+18 3.46732242e+13]\n",
+      " [2.00000000e+01 2.00000000e+01 9.75013510e+03 ... 7.11182390e+18\n",
+      "  5.61784162e+23 6.04409684e+16]\n",
+      " [2.00000000e+01 2.00000000e+01 9.75013510e+03 ... 3.46732242e+13\n",
+      "  6.04409684e+16 8.57222431e+22]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAACjpJREFUeJzt3M+P3HUdx/HnS8ASjQYatEEgSkgvcHBDNuiBmBIS+XEpXghcaAxJPcAfACc8ejEmJkpSk4Z6AOyF0EMjkl44qdSkwWIkNlBCa2lVDBoMVcrbw34bJrXrvtnZme/+eD6Szcx89zs770+nfeb7nZ1pqgpJWslnxh5A0sZgLCS1GAtJLcZCUouxkNRiLCS1jB6LJPcmeSPJiSRPjD3PrCQ5meT3SY4lOTps257k5SR/Gi6vHXvOaSTZn+RckuMT2y67xiz58fC8v5bk9vEmX71l1vz9JKeH5/pYkvsnvvfksOY3ktwzztSrM2osklwB/AS4D7gVeDjJrWPONGN3VdVCVS0Ot58AjlTVTuDIcHsjewa495Jty63xPmDn8LUXeHpOM661Z/jfNQP8aHiuF6rqMMDwd/sh4LbhPj8d/g1sCGMfWdwBnKiqN6vq38DzwO6RZ5qn3cCB4foB4IERZ5laVb0CvHfJ5uXWuBv4eS35NXBNkuvnM+naWWbNy9kNPF9V56vqLeAES/8GNoSxY3ED8M7E7VPDts2ogF8l+V2SvcO2HVV1Zrj+LrBjnNFmark1bvbn/vHh9Gr/xOnlhl7z2LHYSu6sqttZOvx+LMm3Jr9ZS++739Tvvd8Kaxw8DdwCLABngB+OO87aGDsWp4GbJm7fOGzbdKrq9HB5DniBpcPPsxcPvYfLc+NNODPLrXHTPvdVdbaqLlTVx8DP+ORUY0OveexYvArsTHJzks+y9OLPoZFnWnNJPp/kCxevA98GjrO01j3DbnuAF8eZcKaWW+Mh4JHhtyLfBN6fOF3Z0C557eU7LD3XsLTmh5JsS3IzSy/u/nbe863WlWM+eFV9lORx4CXgCmB/Vb0+5kwzsgN4IQks/Zk/W1W/TPIqcDDJo8DbwIMjzji1JM8Bu4DrkpwCngJ+wOXXeBi4n6UX+f4FfHfuA6+BZda8K8kCS6dcJ4HvAVTV60kOAn8APgIeq6oLY8y9GvEj6pI6xj4NkbRBGAtJLcZCUouxkNRiLCS1zCwWn/bTpBNvgd4yXPPWsFnWPJNYrPLTpJviD/RTcs1bw6ZY86yOLLb6p0mlTWdW7+C83KfrvrHczp/Ntrqaz/HFbN9S7xBzzVvDel7zh3zAv+t8OvuO9nbv4TxuLyz9Yd75yX8mJGlOflNH2vvO6jRkxU/XVdW+qlqsqsWr2DajMSStlVnFYkt8mlTaSmZyGrKFPk0qbRkze81i+E9KD8/q50uaL9/BKanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpJYrp7lzkpPAP4ELwEdVtZhkO/AL4GvASeDBqvr7dGNKGttaHFncVVULVbU43H4COFJVO4Ejw21JG9wsTkN2AweG6weAB2bwGJLmbNpYFPCrJL9LsnfYtqOqzgzX3wV2TPkYktaBqV6zAO6sqtNJvgy8nOSPk9+sqkpSl7vjEJe9AFfzuSnHkDRrUx1ZVNXp4fIc8AJwB3A2yfUAw+W5Ze67r6oWq2rxKrZNM4akOVh1LJJ8PskXLl4Hvg0cBw4Be4bd9gAvTjukpPFNcxqyA3ghycWf82xV/TLJq8DBJI8CbwMPTj+mpLGtOhZV9Sbw9cts/xtw9zRDSVp/fAenpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWoyFpBZjIanFWEhqMRaSWlaMRZL9Sc4lOT6xbXuSl5P8abi8dtieJD9OciLJa0lun+Xwkuanc2TxDHDvJdueAI5U1U7gyHAb4D5g5/C1F3h6bcaUNLYVY1FVrwDvXbJ5N3BguH4AeGBi+89rya+Ba5Jcv1bDShrPal+z2FFVZ4br7wI7hus3AO9M7Hdq2CZpg5v6Bc6qKqA+7f2S7E1yNMnR/3B+2jEkzdhqY3H24unFcHlu2H4auGlivxuHbf+jqvZV1WJVLV7FtlWOIWleVhuLQ8Ce4foe4MWJ7Y8MvxX5JvD+xOmKpA3sypV2SPIcsAu4Lskp4CngB8DBJI8CbwMPDrsfBu4HTgD/Ar47g5kljWDFWFTVw8t86+7L7FvAY9MOJWn98R2cklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIajEWklqMhaQWYyGpxVhIalkxFkn2JzmX5PjEtu8nOZ3k2PB1/8T3nkxyIskbSe6Z1eCS5qtzZPEMcO9ltv+oqhaGr8MASW4FHgJuG+7z0yRXrNWwksazYiyq6hXgvebP2w08X1Xnq+ot4ARwxxTzSVonpnnN4vEkrw2nKdcO224A3pnY59SwTdIGt9pYPA3cAiwAZ4AfftofkGRvkqNJjv6H86scQ9K8rCoWVXW2qi5U1cfAz/jkVOM0cNPErjcO2y73M/ZV1WJVLV7FttWMIWmOVhWLJNdP3PwOcPE3JYeAh5JsS3IzsBP47XQjSloPrlxphyTPAbuA65KcAp4CdiVZAAo4CXwPoKpeT3IQ+APwEfBYVV2YzeiS5ilVNfYMfDHb6xu5e+wxpC3nN3WEf9R76ezrOzgltRgLSS3GQlKLsZDWgZf+fIyX/nxs7DH+L2MhqWXFX51Kmr17vrIw9ggr8shCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtJLcZCUouxkNRiLCS1GAtpA/vM1VfP77Hm9kiS1tzHH344t8cyFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqcVYSGoxFpJajIWkFmMhqSVVNfYMJPkL8AHw17FnmbPrcM1bwXpe81er6kudHddFLACSHK2qxbHnmCfXvDVsljV7GiKpxVhIallPsdg39gAjcM1bw6ZY87p5zULS+raejiwkrWPGQlKLsZDUYiwktRgLSS3/BUqWaM3yM3YpAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483ee48>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.31685066223145 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 0.1, 'kernel_type': 'untiln'} is: \n",
+      "[[9.91315274e+06 3.06000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [3.06000000e+02 1.01175323e+09 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 9.91315274e+06 ... 9.91316874e+06\n",
+      "  9.91316874e+06 9.91316874e+06]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 9.91316874e+06 ... 1.06059200e+70\n",
+      "  1.60486479e+51 7.66096322e+35]\n",
+      " [2.00000000e+01 2.00000000e+01 9.91316874e+06 ... 1.60486479e+51\n",
+      "  1.00211498e+75 4.83058176e+44]\n",
+      " [2.00000000e+01 2.00000000e+01 9.91316874e+06 ... 7.66096322e+35\n",
+      "  4.83058176e+44 6.05094380e+64]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "../pygraph/kernels/treePatternKernel.py:151: RuntimeWarning: overflow encountered in double_scalars\n",
+      "  kh += 1 / lmda * kh_tmp\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.0759916305542 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.00295360e+015 3.06000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [3.06000000e+002 1.33918859e+032 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.00295360e+015 ... 4.00295360e+015\n",
+      "  4.00295360e+015 4.00295360e+015]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.00295360e+015 ... 3.07118661e+209\n",
+      "  2.15063276e+137 9.56402573e+097]\n",
+      " [2.00000000e+001 2.00000000e+001 4.00295360e+015 ... 2.15063276e+137\n",
+      "  1.44360504e+221 1.99679666e+120]\n",
+      " [2.00000000e+001 2.00000000e+001 4.00295360e+015 ... 9.56402573e+097\n",
+      "  1.99679666e+120 6.14171855e+174]]\n"
+     ]
+    },
+    {
+     "data": {
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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.22481536865234 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 10.0, 'kernel_type': 'untiln'} is: \n",
+      "[[1.14574033e+029 3.06000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [3.06000000e+002 2.29492402e+076 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 1.14574033e+029 ... 1.14574033e+029\n",
+      "  1.14574033e+029 1.14574033e+029]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 1.14574033e+029 ...             nan\n",
+      "  3.59857942e+294 6.23192224e+208]\n",
+      " [2.00000000e+001 2.00000000e+001 1.14574033e+029 ... 3.59857942e+294\n",
+      "              inf 1.08311694e+256]\n",
+      " [2.00000000e+001 2.00000000e+001 1.14574033e+029 ... 6.23192224e+208\n",
+      "  1.08311694e+256             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.58561062812805 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 100.0, 'kernel_type': 'untiln'} is: \n",
+      "[[7.39717938e+043 3.06000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [3.06000000e+002 8.67654501e+128 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 7.39717938e+043 ... 7.39717938e+043\n",
+      "  7.39717938e+043 7.39717938e+043]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 7.39717938e+043 ...             nan\n",
+      "              nan             inf]\n",
+      " [2.00000000e+001 2.00000000e+001 7.39717938e+043 ...             nan\n",
+      "              nan             inf]\n",
+      " [2.00000000e+001 2.00000000e+001 7.39717938e+043 ...             inf\n",
+      "              inf             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.77159595489502 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[7.07257230e+058 3.06000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [3.06000000e+002 6.13604312e+182 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 7.07257230e+058 ... 7.07257230e+058\n",
+      "  7.07257230e+058 7.07257230e+058]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 7.07257230e+058 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 7.07257230e+058 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 7.07257230e+058 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acda90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.9607002735138 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 10000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[7.04082365e+073 3.06000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [3.06000000e+002 5.92587505e+236 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 7.04082365e+073 ... 7.04082365e+073\n",
+      "  7.04082365e+073 7.04082365e+073]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 7.04082365e+073 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 7.04082365e+073 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 7.04082365e+073 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.60243105888367 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 100000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[7.03765582e+088 3.06000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [3.06000000e+002 5.90524593e+290 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 7.03765582e+088 ... 7.03765582e+088\n",
+      "  7.03765582e+088 7.03765582e+088]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 7.03765582e+088 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 7.03765582e+088 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 7.03765582e+088 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 89.22527742385864 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[7.0373391e+103 3.0600000e+002 4.0000000e+000 ... 2.0000000e+001\n",
+      "  2.0000000e+001 2.0000000e+001]\n",
+      " [3.0600000e+002            inf 4.0000000e+000 ... 2.0000000e+001\n",
+      "  2.0000000e+001 2.0000000e+001]\n",
+      " [4.0000000e+000 4.0000000e+000 7.0373391e+103 ... 7.0373391e+103\n",
+      "  7.0373391e+103 7.0373391e+103]\n",
+      " ...\n",
+      " [2.0000000e+001 2.0000000e+001 7.0373391e+103 ...            nan\n",
+      "             nan            nan]\n",
+      " [2.0000000e+001 2.0000000e+001 7.0373391e+103 ...            nan\n",
+      "             nan            nan]\n",
+      " [2.0000000e+001 2.0000000e+001 7.0373391e+103 ...            nan\n",
+      "             nan            nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 89.36353826522827 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 10000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[7.03730743e+118 3.06000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [3.06000000e+002             inf 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 7.03730743e+118 ... 7.03730743e+118\n",
+      "  7.03730743e+118 7.03730743e+118]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 7.03730743e+118 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 7.03730743e+118 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 7.03730743e+118 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 89.13758397102356 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 100000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[7.03730427e+133 3.06000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [3.06000000e+002             inf 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 7.03730427e+133 ... 7.03730427e+133\n",
+      "  7.03730427e+133 7.03730427e+133]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 7.03730427e+133 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 7.03730427e+133 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 7.03730427e+133 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7fd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 89.54426693916321 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[7.03730395e+148 3.06000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [3.06000000e+002             nan 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 7.03730395e+148 ... 7.03730395e+148\n",
+      "  7.03730395e+148 7.03730395e+148]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 7.03730395e+148 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 7.03730395e+148 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 7.03730395e+148 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7fd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 89.27618861198425 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 10000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[7.03730392e+163 3.06000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [3.06000000e+002             nan 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 7.03730392e+163 ... 7.03730392e+163\n",
+      "  7.03730392e+163 7.03730392e+163]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 7.03730392e+163 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 7.03730392e+163 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 7.03730392e+163 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.04616212844849 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-10, 'kernel_type': 'size'} is: \n",
+      "[[1.280000e-77 9.600000e-79 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [9.600000e-79 3.560000e-78 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-77 ... 1.280000e-77 1.280000e-77\n",
+      "  1.280000e-77]\n",
+      " ...\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-77 ... 1.646560e-74 1.652920e-74\n",
+      "  1.746200e-74]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-77 ... 1.652920e-74 1.668256e-74\n",
+      "  1.757090e-74]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-77 ... 1.746200e-74 1.757090e-74\n",
+      "  1.887804e-74]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.73524403572083 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-09, 'kernel_type': 'size'} is: \n",
+      "[[1.280000e-69 9.600000e-71 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [9.600000e-71 3.560000e-70 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-69 ... 1.280000e-69 1.280000e-69\n",
+      "  1.280000e-69]\n",
+      " ...\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-69 ... 1.646560e-66 1.652920e-66\n",
+      "  1.746200e-66]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-69 ... 1.652920e-66 1.668256e-66\n",
+      "  1.757090e-66]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-69 ... 1.746200e-66 1.757090e-66\n",
+      "  1.887804e-66]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.7938003540039 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-08, 'kernel_type': 'size'} is: \n",
+      "[[1.280000e-61 9.600000e-63 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [9.600000e-63 3.560000e-62 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-61 ... 1.280000e-61 1.280000e-61\n",
+      "  1.280000e-61]\n",
+      " ...\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-61 ... 1.646560e-58 1.652920e-58\n",
+      "  1.746200e-58]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-61 ... 1.652920e-58 1.668256e-58\n",
+      "  1.757090e-58]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-61 ... 1.746200e-58 1.757090e-58\n",
+      "  1.887804e-58]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.67548942565918 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-07, 'kernel_type': 'size'} is: \n",
+      "[[1.280000e-53 9.600000e-55 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [9.600000e-55 3.560000e-54 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-53 ... 1.280000e-53 1.280000e-53\n",
+      "  1.280000e-53]\n",
+      " ...\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-53 ... 1.646560e-50 1.652920e-50\n",
+      "  1.746200e-50]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-53 ... 1.652920e-50 1.668256e-50\n",
+      "  1.757090e-50]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-53 ... 1.746200e-50 1.757090e-50\n",
+      "  1.887804e-50]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.68517899513245 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-06, 'kernel_type': 'size'} is: \n",
+      "[[1.280000e-45 9.600000e-47 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [9.600000e-47 3.560000e-46 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-45 ... 1.280000e-45 1.280000e-45\n",
+      "  1.280000e-45]\n",
+      " ...\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-45 ... 1.646560e-42 1.652920e-42\n",
+      "  1.746200e-42]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-45 ... 1.652920e-42 1.668256e-42\n",
+      "  1.757090e-42]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-45 ... 1.746200e-42 1.757090e-42\n",
+      "  1.887804e-42]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.75953102111816 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-05, 'kernel_type': 'size'} is: \n",
+      "[[1.280000e-37 9.600000e-39 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [9.600000e-39 3.560000e-38 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-37 ... 1.280000e-37 1.280000e-37\n",
+      "  1.280000e-37]\n",
+      " ...\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-37 ... 1.646560e-34 1.652920e-34\n",
+      "  1.746200e-34]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-37 ... 1.652920e-34 1.668256e-34\n",
+      "  1.757090e-34]\n",
+      " [0.000000e+00 0.000000e+00 1.280000e-37 ... 1.746200e-34 1.757090e-34\n",
+      "  1.887804e-34]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.84523892402649 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 0.0001, 'kernel_type': 'size'} is: \n",
+      "[[1.28000001e-29 9.60000000e-31 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [9.60000000e-31 3.56000003e-30 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000001e-29 ... 1.28000001e-29\n",
+      "  1.28000001e-29 1.28000001e-29]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000001e-29 ... 1.64656002e-26\n",
+      "  1.65292002e-26 1.74620001e-26]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000001e-29 ... 1.65292002e-26\n",
+      "  1.66825602e-26 1.75709001e-26]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000001e-29 ... 1.74620001e-26\n",
+      "  1.75709001e-26 1.88780402e-26]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.6217794418335 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 0.001, 'kernel_type': 'size'} is: \n",
+      "[[1.28000102e-21 9.60000000e-23 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [9.60000000e-23 3.56000272e-22 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000102e-21 ... 1.28000102e-21\n",
+      "  1.28000102e-21 1.28000102e-21]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000102e-21 ... 1.64656150e-18\n",
+      "  1.65292153e-18 1.74620128e-18]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000102e-21 ... 1.65292153e-18\n",
+      "  1.66825762e-18 1.75709137e-18]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000102e-21 ... 1.74620128e-18\n",
+      "  1.75709137e-18 1.88780570e-18]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.48925709724426 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 0.01, 'kernel_type': 'size'} is: \n",
+      "[[1.28010240e-13 9.60000000e-15 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [9.60000000e-15 3.56027203e-14 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28010240e-13 ... 1.28010240e-13\n",
+      "  1.28010240e-13 1.28010240e-13]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28010240e-13 ... 1.64671026e-10\n",
+      "  1.65307329e-10 1.74632829e-10]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28010240e-13 ... 1.65307329e-10\n",
+      "  1.66841810e-10 1.75722737e-10]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28010240e-13 ... 1.74632829e-10\n",
+      "  1.75722737e-10 1.88797415e-10]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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E+fXtUBFzQARhS8TxGqU/FSYiONVCQDs7KsTN7qWsLczYh0NXq4jqFPSkIbcwbzbAfA6zuwMAsEcztFkkguAU6LprqwLdvgUcHsXz/EIecmMEyenHigVc/oicvx4QnIMMMsg5y/VHcA5y/eQiQ7pncX6eRq8Wp2HTCdixPdXboutWN6SVGqC57fuS/b2XFMG5jZyUon7STVPnUVk2Y+3SXoa40ynqSRuVT1GXuPkJtHpt2xCdqOba2sRtiCStCRJQXwMEkBVVI+Vsy7ch7rjZ3fHmcr4NqbvnTftC8nR0IKbBh+xMf25RBAq/5jaE023Izo5L4c6ECuPHbRJcAlUjh5RUtAAusuESviRr1DXu9vzhPhdFSNoy9+6BDw7cHPhtCNc2UOWdtA3h+Rzm7h0AwObho1bHqhmP3Vwsl3EeRhXMR15FrVLUj92GTCbgg4NTp6gPlsUg28t1AotpOQ/L4rjjXVbIedY67WNZqGNbWxbasY7tLIvBZzHIIC+TnIEh7OZtQ87yVbsMgNN1AVFtKy1sX51yXcd2Gr22wb204T3a5q0Lnp2ck19zwtzr7bKIrbvLF7b2fbYM28GyGGSQQXrJzbMszvJVa/NkC8uSh+wmeITj9rNdHJxZe8llmilrtTqeg1Ouz/eZbQ5O9dUJ8X/fh1wv/JUNnEXOwTkeR8xAzpQlDs69XVgf2w/tMjc5OBWCtJWDU3Fi6mO6nQAA48jBKU7IBgfn3m5avyP8wXhnb3RmSts0GjkglL4/lhN6AD8JDvQlYDS5d8slyrfehH36TJ3rHKFmZyfeB+9opPEoXE/GgDc1eDaDuX8PAFC//7DpYAZgplM3X4pJ3Ny6BXrzAfjt99SYKueY1cArP1ah1EsdnP3LL968xeK8JFsEGrDbE6/twcHZ1ofmotQv+5YcnG3t61TnXM+2VPK29kPkIekLid52voj65VwKHc413X+41m6CHuHvWbEipw93t6E5QOdztRimDsTWNO6cj1Lfnxrp+eSuT/SU+dg/SFPffQq/LFwJR2ZAgJJLy2BXZChEU4QDNefg9At/wkm6WIIeP03uOdd1oBFMrpd5qWvooAbb/qntL+9i0SYnebDzc9t+PvE6BaVWfTUe5pNIdzr31F3EvD335nndCsUdEUSR+iZ1N09KLgt9HZdzke2rj+WCQIId4M0mIfJ1l8dFMa8R2iDxbXwE0nwPhyRtjoFXq5T8xzirR17QVkIaCRH78fAqS1FvI1LOapy4BWmBBNXJQgaUWbVynG2y0G3z7A4+i6uSPCMTSL8mfetGXKS0MFMFvY5LRgo1LPLr6XzGkved1csImA1ScHCtd9c8n1adHmPSeJAghhx+o+1vffWS7U1XO+cow2IxyCCD9JKXdxvSkUjWSLjqurbLwSmnHJfoZajp4PSOSV5GRCPXiGZ24uA08MUz0jGcR5Ghskr3+WhxcApSkqm9yFAjkzR1yJ66yJB2gh5TZCj90hs3Vb52h97fU1WmjmjC6YoM3b0D5MWJV+tGkSEC0iJDhUdwLpYBwckPHzWjqGRckeW8yNB0AnrwKvDeB67kAQBUFUgXGfJz4fhkr7DIEBF9HcAB3AZpw8yfIqL7AP5PAN8O4OsAfoKZn56lnwuRrmxLeSDbFguVqZnUjSiKJJsRQPpAy+VFEepG8HoT+2qJhsjLmSwaXl95eeODH2ts0ChmFEp0h9nGxUj4MfPFURYLRQAb9vNF4fRb+xfF18lgpuTB00V+GlIUkFc4qSymYN3hb5sYiaBRFff/GjLtFya9ONLtW6Dn3NwWFAUwnwNVFeeMjIuGjEcgNefStnvhFTS8KEDjMUiiXXK/Nmvw/TugpdR/taEmCN265Y7N5+F5oD0fISkLoCxAixVABPuqWyzo8ZMAz9c+FppOgbIEbTYx43dvF+u37qJ69CQ5j6U/IC4W4zGorsFEoJ1pnJt5/2jIeWxD/iozfy8zf8r//nMAvsDMnwTwBf/79ZZjYbnnuA9Ue8pt95eXsSftLbJPJgr/5Pfz8AGcJJT7e5QvpLFQ6DnvgkCfXaF+7bX6Jij+L2PY9j5fwpwDOFtuiLcsPsXMj9SxPwPwI8z8LSJ6A8C/Zua/dFw7V5Ib0tiGNBPEjkWLnsRG1ZElmJCoqPBeY/ujE6+0HEfQk7+sXYloXXpKv6EvlUimXzqfOMdWbQ1YsUx30cm1Ud7pbZE+T+sj53jdNP1/m14hIU2kriOhjYqOSOKYxl4kumX65+Q3on9x+3ZSL1W2O8Zbebp8YcDBqIppGpNhDw6aYXOZ/0B+48c+HsPcvg27vx8iHDppTgsVJmBh9Nbxi8vfwb59fClZpwzg8+Rqyf0fzPxLAB4w87f8398H8OCMfVyKaIYk4IQoYA/ym5PKF0L3VaMBmnIJQja+PFl/yYOr/C4pKMsG3XqT31SlAmVFT7suX0iTMfjIggookhgTyxe2TVlb+UJDYVvUCcqqSncOx/misnS6C3hK+phOnckvLFQyN0UBeFCWDlFSWbrthPgh9Dg7QFlogLJqt/3Jap0CbrsGAFitXSYqcwBlUVkCRA7nMJuDbrvyhY7IpmUbMhr57VTEetBoBLx6Ny1fWJXASo1frMCydNuQ3GexviSfBYAfZuZ3iegjAH6XiP5U/5GZmaQoZSZE9BkAnwGACXbOqMYggwxy0XJuKepE9PMADgH8XdyEbUgu225D+rSXb3GOO91bNg1TvQ2c1Wd7JOduK1265jgGIHEwJqZzl+55e22cnV1p4Fq3TBddrDhwdygLTnNm5HomEO420huthz6mfjc7O7CK+yKnMtTRJTkm2wLhvhCLUNppbHlkXjUtYFk2OTwUz0fO99FWof1L9ecvnvyGiHYBGGY+8D//dQD/M4DPAfgpAL/g//+t0/ZxTOfpTTvpBWprQsx+bdLVMYfCLsSnYJt9aRKb9coRxmTFXoLHPivrF7zo83my9TB7u4Bl1B72G8rSkQsd6m0ElVUaBlRhRh0NsfOF386sY7+aaNczPss4AMDs7YWoh8CUqTCOt9GH58zdO7DPnoOYXS6J14FXa9jFUm3l4qJhxuO4xRIzmCiN/kD5HeS+jMfg5dLNke+LRqNI1iPV571efHDgxiYRF7ZJ9XDJaQETzM4OaHcHtUQTDCXREG6JhohvQsZgDw+B7/w2FO8+VPe5gj2awdy/67qaLeLi4LcmXJVuXtcb0P4h7Edfcyr8x6+5+2ooRI9ABmbvNlCWsPv74b6bV+5j+T0fw/iPvx77Ho/Bs7kLzcp9Btz2Z7MBz+ZJNIQexeflJDnLNuQBgN/0HuYSwK8x878koj8A8BtE9NMAvgHgJ87QR7v0SR8+qYmOmpDnTgbUgvNv1SV88Tg5LrDlRpvoH/LaVsIc5LrnEHdr0329bUKsW8cumIBiuzGIXuElstYdk/aCH8M2Q9/i3MswJGytsoBOOacWWc6PdTppqDlnlon+33KKgGcL9ITRk+TjJBBuC0h/5xhAu/5MWdvwQ+TAo9OIMnUTmnj520XMlxpjwCB4HWLiUt0491Jky+2UxqCEF1OSn/LrzzqGtvbaoPNqSyn0hTqfogFuO40eXVuntt/1MZWVm/49A6z1oSsU2cLS3qaK+gD3HmSQQXrJzYd7n/Zrb9KvXwidagJbSYY6Ds/QBfcuy4ZDSTvehExX+goxednXC3GskNMi6ttwhp4n3Dvjs0iIdGXqphPnVNO4AWsjx4ScK8hTYlCZEfZ63MFWcG9vFQTMgOX4s9eLF8s0dOrnh+s6hC+dvgZmWoGqMvgxwv3fEu5dvvlGymchRL45n4W1AcEbfCqWHZ/FR151v37wYdAVrNCpo0kT7r23B3r9NfD7H4atWODklPurHarKdxPavSy4942WzKyPfBbqnJCx2GLu6hNbTMSUBEbMcSR7/IBJINMAObmFwsRtkDI1nY+jxSy1dRN2ztk2Ro+h5XjCywDvpOT0BbGHR/FlaskjaURIgLRKOLFLmdZbPJYFKtNHOY6lDa7T/bz0Y+ujMIeC/5B8CJABA3FRBoNX6yStvXX+YjeJvvq8+tHjNOfEL3hWOCq0k1scuhLh8LgS+/CRH5sA0Ewyp3axaHy47NEM5t33Uz4LXrb640J0ReYjjONl4rM4yz5TrhdLoYUcJemjLa28E8HZ0p5CQuYITlAFMgpwo1ibk5vP7JxWJ1k8wKkQnMFqEb0yvQEVsZBxAk53y+7aLEqTOzpDW9oi64Pg1BaampcErOUjONoXlyTH1UqnonDWRtf89URwmukE1iqGLkMgnTejLRQNPgOcRQaApGzAwaGzNmxKKuRAXBmCsypBu7vg/Vi+kCjOgejijlNMBtSO5WV/D+jNXyxOK7lnP1gKLZDkPtfnklPDA+4rqD9c2lrIzPH8i5323YJPED0aRLDNKEvr3+XXBqOWsorCIeXlr9PzOudNjzVc0zKHuf426bhFF5POleAnmNJjXqhU+tW1Z6tS27ku4lyu07VfnWcPj1oJeZK6I74fVguerqLOEtLNsRX+5zaaR16tklAqgDieDPkbjktUKFzQ/2N7/ReLbSyHbaIgPXJDmKn9gc6vPyk3RPfRMzeE0ZEbotu/iNyQYywiWSTMqHJ798TiiH6UBuRbfCP5gkI4tWWRWhUZRkOfWwBg9WKq7VCA3yuqu1NZFjs7MTcECBnBx+aGEIG8HwOrdSiMzCE3JF0kWy2LsnK5ITo9XmDqZKBDwV25IdtYFkM0ZJBBBukl19+yuCjJv7BdZnCf6/uCxLyZGz5Yqq8kwQtITeM+bav2W8/tuQ1ptc4yE9wulN5txk8bHiPZTrT10WMbYsUJqi7TP+eYmKxttunxQG6b3MvttyH1wUHahtdDz1O4LEP6iuVXP1s3zk22HC38KrxeoX70qHFuq/q6+cSx/CJtQy5KeqWoN7NJW68/bhuSHOt2cIoTLnFwWu/MTN4IZdJfxDbkvFPUBTKf7cHDVuKUKequeW7VKw/1aj8AZ85GqkpYXT7gNCnqd27DHqUOTp06EMO1LSnqcL4Hs7frTnm+n/gydN+Nbch4HKD3QU2fa5LoIsfPuA15eReLXNr26sfUnUxyNYqisfJHvID2cyBlxwrFitnf1CKs+uFFyl9298d+hZFX8byuFPX8eJKiHp5VSvb2NBq5cXvCWScFCLUbCzetCCoobc/3xev0WEhRF5+EnGPr9ByBwusoy2QMnreEDaX2iCFgrXSr0sc/KYysw9ZOwUaKOhHBLi1oOgVJ6rt1URa2HPwQaKsbQgZUFuD12uMvXDQEz/fR5gin0TSmqMvcjEbAnVug5yoaMhol/QVCnaoEkXE5SYL1AC41Rf3mSmMbIl+zHnFn5uRFbas1cmJdj7yNdZ7LkG1Dsm1Pn7okrhnnYG1EVcQ0z+uV6Loh+hwVVbDLpYKha7265y6pd5HXCAEidaBNw65an0afbAHFgGDni+Y8ApEfI5+b9SbZhgSsTcgb0efXieWnuTQadUO81RWcntqK9El6MAZMzgLhzQZ2X9cNaS54ASuisStSN0TjP/Joh0RD1EdNL6jb4CwGB+cggwzSS15eyyKXkxyBp22vccy2n9OWDHSqfvP2bfP4Sde3On/jcV0lrHM8jXbbHMJ5+n9Xhm3LdVov+XNLNTXAWy1tViO3Fx6CZG1mbTlMR9RBruXVuhVnkZaBFIBfFj4WX4/m1GiR0EaGV+H5Iu07L1Ylllcd20kKK6H/czYsFi+yaDLY6yq5bn2Icy5DfE5L0IVSH0By3mXLKftM0KqnkJd3sWiLAuiH4jiAV8bB2ebgbI1YaNIcSfLyfeUkNCEK0BbNIGp1cIJiXRIAoTbJcQ5OPQ7AAX0ahXl9u6Eg7+4O7JEngdEO1brul0qdJ42hzcHpz6lK74ewyXXyRdbRkAZrlEyLIrHVoUsqK18sOSZhBedpoR3ehZ8DExPJpLTCehNJd+B8BhKRMALhXq3SMgaAr0bm64bM56FuyObho9aFUuqG8DLmfpjpBOYjr4Lfez+OyTtzA5O5ODq989YAjsgIbvEYEsn6SP6SFK5uSF5Ho+va5LyiaJCtJA+5HFN1PZLCQisbj69jVXHW4VutL5mEQFceLl2XxLW1aeYDJKE/VU9Eihupy8D0AAAgAElEQVSNKle3Q5/rHzQ5bvZ2Y/VzzcOwoUCu25iyMB/xRaOyBPyLmrxM63WYz1gjRF0nbFZ53ZBbe6GuR9J3WYJnMx/FUQjOUeXmSyIZqm6IZuAKc9tWN2S9caS5oq8kh80XoNuqboiEfaXwUFkAVQmaLwFDsK+6Kur09Fmrk1bqhvBmE7YRtLOD1Vv3UD2OZXloZ+ocpyEHRaIwkdEsRGkAYNaf8OflXSxOK9fZpM/qTSQYBMmuvVSFbp5oUz3MWR66zv5+aXLWujFn1HeIhgwyyCC95PrT6l2WnIR0zM8VEURlvm3pQ5qj++oip+mrQ0YHCCCiRNt8MR3kN4lvIUuAC9sdATn5/qIeHdmw+XhytKZqpy39vM03E/rToCy11UlPV4l7+j6ZAgl1ovwuSMucBAgRi6E5O8x0EomHw1QotKbCWYQ6K0LQ43EWsjWwh4ft2zhJJFNgPpCBub0Hq0BZSWKcnitPRqyJogHg3y5++9KKDN1cacu2VE60k2DeDQRnY7HImMH9sXAdp301fCXBV3GMgzMAdDIHnYiHYye+mCSsFksiSoZtqPmq2o0OTv/raBT9D4mD87h5M0l7QObHyBi5kjqrUAuf9OnDnomDczyGbSN+UUzX+j4JSY52skoBo8AGBoDIAbCSbUfhndWrFWhnJy4s3sGJ2gY28pMcnJjPYTzrt3McNx2cNBq5Z2CFOEdl6fwikt6O4x2cZncHdr1OmbJWA9z7ZOlKoDopkawF+diG4OxksurgTkiYpBJ9eiI4iWJilFa3BpK08TbUp/5d5R7oRlhZDfZoFpO6WnEQLdKSSBaKNMsh4iQz212nsBN5n8wIrNkA6sOj1kgCb5AuuGqsXJvkngbWLWRo0Bop94WUC7AM++x5cv/YW0x2pjlJfBRFM2X59tgyWGj5OhzroS6JojOw6w3wwYcp85XHmoQ7keQKWdjVOqme9nIxZZ1Wzhg6TSwLQ41n1OUYZC+0KVQEZJW2kVdR7xM6bYmGSM4CAPdgFK4MYgjNZotSIzdEIg3ITG5l3ib8DdqS8SZ165TJfKg+dSX4pPiOcHnqc4TTQfpsKZhjdqcdodMifN31doFGI1BRhESykBvCnplKWymeLjCPAvFqjeLV+3ErILkhq3VIDuMTckN4vgih0/qDh60fHzMZu3YXyzA3ZncH9MZHYL75bjIm7sgNQVnCMCe1ZWi/fzRkcHAOMsggvWRwcF629E0VP2v70tbWTFkdjlV9vI078zS6tzk987ZOYiFLeFFbMod1e3lb4rhto0Dsait3+traVaRLCIlNsl1ICHuVc9L/MXGG5o7SY3U1Bcxk3Eyxz1Lrdd8JNQKAL9nPY99ecPnCQZScFLkYZHu5CjyL6tO9WPnflZP2sqULbr6N+K2kdgpvM5xhsRDZJnQq5x933kmhU4l0SBt5FKZP6PQk8pvjnoROC0K9EPlXVKIuVRmdk3l/24ZOcx3z3BAdVcoJipD6LHqFTvUKEEh41KFAOtTMDdELSLQa4HwAbUln4ofB8aFTaJ/VatU6h5H8JkMETycgnR5/XOhUfE/az7Tpv/gMi4XItlmnJ5130Vmnfdvv+hJ1tX+VWafSf9c5l5F1qol/Mv6+lNMnLgCXmnWa6bpV1qmvKJ/FhFr7a5OXd7E4r0Qye80SyRT7E6834auaVFrTl+TRkOuQSGYjMVCwFlRVtUtJJBtVYMkZEctCs2d5nIX1SWA3IpFsPAIfHp26ItkQDRlkkEF6yc2LhpzFmdhFdHtWySMFwHY1TC5SevpgWnEhly2tfKNb+JHOU4eu6uT56dWoydh9kaKxOl2Rkw6JhMZxfr9kf693FfWbtw05ywNzUS+w1um6LBIiPefryhcKoNtvdJl6BR36fVQayNuLFlsnyNdtJG4vTzefN2+xOC/Jq4dXo3Rvv151WzHa97BetX5daDxuONyorAJ6zs4XCZrT7O25437vS+NxQl6T+FL814WzmqK6/dBHUYA369TbDkQsQOYrMbu7cV+e8VnI8eL+PdRPHIeC3v/yatUorBzGrvNJFJ9F+DrKnl76EZ/FeOz26ZtN4GSIHBcpn4W5dzcQ3yZ5HIYc8rGqgq8FbF0V8vEI9RMHtQ58IwLlXunqZQY0GQfK/3AfZzMUf+WTwPuPQrsoCofKvO84KriLz6IoQMsV+OAQ/NZH3PV//nWHvFVV1wCguL0HVKMEWl689hrWf+ktVF/+WtRzMgHP5u18FnUNns1BO5HPgh71XwJe3sWiYWJ6iDH3sMjaPOO51HVrH4kjVF+3XiPZEmZM0422dPs6X0WHwkRP5maRZx9laOaGbBp9E3xNUGG9ns+j132tvqxt8yB96r/5xY83m+jIlFP934Ne6pzQxnodIOF6KefZPOjDJo9yWBAyK2C9TmMBcn88I3rOd4nVOhyL1e0ZtH8Eq7cEhfWRCrew8GLpFm3dZlGAjAFvagcNf37kh6jySZRDmFdrV/BY67RYoPrwMFnUgNShGhyctYvONBbztlq6HTI4OAcZZJBe8vJaFpm014roOjnHM7TE9q3afwvjkmZWzmL8nH81uiwKuTZgB9LjzQrZ/kuVf/W522LJ+2ZrEkZo9l9Ytuy+WLnOLaK/lG7cdah0rvUjZLrq7F5pX6yKjKmal8tYjSvxI7GaM20teGtD1S4h3w9xxqNBynoDEqwCz+YJGIys/4r7TFGx1hKaPiKwL5bMqxVYbY9aJi/UOEl8S+s1aP8QVuu5kmcpuxd1DVjbDPEPdUOukWwDzyWP6hOeCTIZQvIKpKt/hQwM/Ao670Ffl80BGUrwEeeun+eeaKW9y3Uz5zC/PceS+1Faj8sx3eZxz4Axx9L7dc7DKWSwLLw4h5JimTpuwW3AtjMYsbTXwExR3Esm7EsRBsxrQTQagBVwK+svYZDSBD5Zyrjo1pfd25HNiM9Ckc34ryDgnHu8dqQ/4UEM5Qnb/RYyv8lYfE3Q0EfoX1kXCr4cyh4WBswUSGkA7zwcj92XUqDUgCPYLeD1VbVOPchKGKiCFEVsVyeAFd6prPUCHFR7OgVpMFhROF+GkCev3AvNzCFF3fVL4I2zFMins+P5QZzDDMoeU/r9w1lV4L0d4NnzYOkEUF4GyqIyMn9ppzRWA7v3yZLnaJAzjfVD4M7Lchr8C6aZrVqZsjTngjoWbpRm3LYc6Nmx8A+d+lq79SEuYmHRaWHK0pRp8kKzME5Lv2H8NhkH4KMRMkXy0HpKNnEe0nQK8iZ2iLIwg+DJZNpELUIhP0LnMehoCKKZLw85bzYpCnKzAaNOxku7Oy5qQpR+7ckA1vo6oMoZWFXAeAxS3ByBz0MvujK34zEoe+F4tQLf2QPJNgJwEQhrHYMWANA8LIISieCyAMoCtHTbIHvHLRb0fjPblQy5hbAsQatVjCrtTLF+/Raqh4/jubJAif6yaPpoiFwXZPYyLRZnzfjMcxL0vrszTblnNES3I8d09ED3ZbNkKSCFUuf+gIuMhuR9WU705sXS1erUzFzMwdsfwrHSNFu3N9d+HCCJdPSKhohfSR9jDvtuns/dtUUBorg48mYZ5ieBvWfw9OB3sG6+kqQ06btRk5ZBhzNYFWUIoV2/CPFqHSwLbZ0Ff8FmA7PvzrUAhF6QlIXBy6WbCx2Ony9QPp6nfp3F0vmUCusWrDDermjI4LMYZJBBzllupmXRlZ6dE5u0EZ7InxUgCmRcEtJyGUhW67UGL2Wm+2gUzFB7eOgSqw4P3Tm+L7O365Ka1KpvdnZAuzuAMbCPnwST0R4ehUQiITIx0wns4ZEzyy27RCIAduFMbxqNQmxfvnZmdydQuQFA/eSpO+9oBuNN4tqTuwqoKxDFejBYcf9exAdI9a1RBZpOg3fffsebMH/xnjOr/fVgBs/mzjPf4Bg0MLvxemGyprEDGbk+/F5+dwd8NAtfQHPvLuzTZ+7eeEAT7e2BlytgvQLGsahS/fEHKN974u65SS003j8ATSaoP/gwHDP37oJv74YthBmNXP/rNaiqYoQCAEaVK2LkC/rIuDcffIj9H3gTt/+oiPMwqmCeH2D9idcBAOWTI3BVgpixes3dn3psUE8MRvsbjN7bx5PvfxUAcO/zB4DvlzXg7MFr4OkYxTvvx2S5j72Bd3/0Pj72f0Xym/ruHoon+2AB55Wer3NvAlrXMI/3YV+5Hc7nP4sgvpPk5uWG5HLabYggOBV/Zc5Y1MiX0AtQhqjMYd7ykutMVmGTBhCyIEUHGo8B5sgHORrFkF+yXYn79IaDU+UNAHEhTK7JfTE5knU8RlLpTPMwBB5Jhy7lzSYyWHu/Aq83SWm/QK1fqFwLvb0STkvl4NTbkMApyQyq/IJSlS4MyBzYuAGAphPwfOGOySKy2TgT3lrnEBQzvK7dor8zDQtWuP/WOTiTcKh3cApxrn5Oym//NtgPU78BH82i03K1jg5TQaGOR3H7OJuD7vmPxXvvu5BuS4YrisIhUP08Frdugb/9TdDbH8S5JZNyfsq2tiqB9cahgpWD898efg7PNx++oLkhuZx2sdP7fR1aUi/mueVLhL7Ie/HlBYr9kNp7ix5JqrjyjOep2ecuAQ/BAJrp7YTo2wgPtLVxcVMw9OjbiQTDJBwL244h+JVs3P8r/AJZjlgCuW/iz2AGZX4IstYtJqpGiZa2OW6d9xzXsN64/mQxYAZZcQJ78Qld7DEZWk94NnaNoA3O3SzKRhtBnUZiosSPI4vGFkjNLrmZi0VrhGI7C6PB7+C99fGrqPIyGluek6MhrjboJgFeibediED+6+EaKaK3eqm+XH6RaERDslDmuUZDVNQDtY2YBcX6Tbs7MLUUx5nEdj0JTJxbKMsiCwPKAr1FNETGRpNxgC+7XA4//r1dSG4GVeJkdQsC/BeV1EJGoxFodxfk8z1C1CfkhiinpY+GaIsHcJaRvX8rRlT830iHQ2cLX2iZw/aFx5Wbg00NIkL9qtsa0IeP3fh97ZGgl4+G8GoV7/t0gsWbtzD5UNU6HY/cNkZHnLL7etpoyODgHGSQQXrJzbQs2mTL7UInNFltBXpBvzvVOQb6HBKKTOwndwpaYYISGLiK++e/X6RYdoAr5jjHEnIVE1rOS/STH9XY1DZCA6dOpZN1oUFWcHPI1oQYvG5JHZdkQS2JQ/aUc1pzun1tCUeymrswhoLiGGr1d8tgAzVf3d90U/v51e3Ls6VCteexnb6Zi4Ue+Hn5LCQnom7e6LZr++AsGouAj3OLzyLJq1it04VKZx+q/+VnwgXhLFarRo1PlzMRs2J5No94DAVyCtWwbHTcBp7KWjlqaxu2ONvgLMLCsFoFn4XOJOX5PGbNCozbqnFyOofOERhTwQl1NPM1hkTPv+iiODPN88MUZ+HvM/vIUyvOoiycjnUNXi5RPDv0zfv7ao3ypdiAs0gWt/kCow8OXWRIxLJ7lmS7JfMg+SlnwFlc/2jINixJZ2Gpyr9ybVyc2/hFjqt30Qb2yvD/eYHgxuLWpcdZ6njk1+f6ZZGj3PEqv3fqrtuS431D4Fq3loLK7kf14itHZGvdDqVLILDJnd25HvqY+t1MJrCa+yLjPdV6hGNaPxXCZlUDpLUgtK7VWpaB7yPvp228bffsS/XnX2CmrFzUw9Qrr6Pt+uT3jFr+lKxESds5vX3+kkE7AuPDREURvhCBAl7Ctl01Wc978dfz4ZGZYBtwGkFfjoWKSYUtAXTT829adD2OJStJTlN5Kzk8ulAhZOu+yqQdffAvone8Bog6HxP9Om4hySWB4vvTGwunr+FRlikmRJdoVHVRXQ3adJzOwsz6kwU9I88Jf8szpreQwcE5yCCD9JKbb1lk+9BTXU/pPh+AN/ky59A2Drnky9OeX5L+6k1r4XioM+fgMddeqORsUSK+unlyTPwVOS1fK9/HKb5Tbe20GFjcgiINc5lREfKmxem5rVoZF4n4FRpjVMdCZq/35VDul2GVS9ORyRv60hwkup82Hc4gg2XRRzzHxKmu2ZbPou3n4867Ignp4pqbok2vvsdOp0S3bl1cIMK/IX8/77ns215+3mmesaS5lvtwzmM7sTUi+iwRPSSiL6tj94nod4noK/7/e/44EdE/IaKvEtEfE9H3n1lDHbI7SWx9Ouem9JGwK9V+n8jtf9+mzT7X+rAe+0hA/i9t64Itiy6dVehRR2nCV1vGsHawbwcB7xnCPJWeygekftb6NFi/RLfNutUCOQ+d+rGtKT0BB5X3kR8WpKma0842vAUS7oM/3vh3DtJnG/LLAP4pgF9Vx34OwBeY+ReI6Of87/8TgL8B4JP+3w8B+EX///WTzLstuRzBSZrTj8k12+SGZN7sUPEKCHkTgDObJcfCej4LKotYtYxtGukhAypayG/OIzdEITWTyIJyopndqWe5LhJkJte2kxpfVzrTTtytckM0ylPCwTrZamfHM2krp6zo5slvQtSCDMyoAo1GMbmuUONUxDxyvnN4r6KegAt7PngN9klEUQr6U5L6dOiUJhPfl8OZsLXg2RzmFccEXr/7voukaLIgAGYy9qzh8zA3Zm8P9NHXwd98Lz7HUkmtg/wmzw2hw/7YkhMXC2b+fSL69uzwpwH8iP/5VwD8a7jF4tMAfpVdPPaLRHSXiN5g5m/11uiKJMTyj9vjJcAaDQZq20urF5niokDqmoSDU7/EbW1y2l8XB2cSeVB69uXgTK8XK8JxcAZrYrFsfkFP+KLqr3jwM6gxJJwVKqSq66qG9nU+h+bgFJyF54PQ7TX8P6z4KLVeAU+RzQ1xsPxCu9LU/kE6b+JHkOzR2ga+zbAQB+Ijpwc/P0h10fpKchiZBC/CqxXo0bOUg0RyY/ItSLEOC6yGS7QByLrktJuaB2oBeB/AA//zWwDeVue9448NMsggN1zOHA1hZqaQRthfiOgzAD4DABPsnFWNs4kUGlY4B/bmPvJK3/k2pIuDU4BLygLRiV5JXxtP+WbVl4sMQBFB2ZeDM92G2KBbXw5Oqkq1DTHBWSiJUAAct8VsBiJO8AyobT4NYRvlkvLiPMiXX3AsndsQwbrobYjokieo7e4A84UbW4bghICk/DaCrfG8JFVAoSbbrY5tCBrbkBp053aIZshY7HIZuT78NgRATFHXCM7ZHHTXc0zMZs5a8gmEoheNRq7PeXxGzHgMvHYPtFjErNPRyOEzWrYh1LYNWV98ItkHRPQGAPj/H/rj7wL4mDrvo/5YQ5j5l5j5U8z8qQrjtlMuVq4Dc7ZIF0N1Rwr3haaniz69vfqUvpxQnvmuNs6q/zaM3Ced6xfe857TrRm1dTREAGd99NKLgh6r4rO4anbvzwH4KQC/4P//LXX8Z4no1+Ecm89vgr8ifmGzz2IeWdFf8F6EvZmTNGHfXseXZmPdTfes0K5vzxVh/LEECqJIWtzJrvm2FHX5Mm9D2Outj1DXQ764cnw8AmazjBTXhyQ3th2ZaagxvZpxWqdS82rVTFHXX/miAFkLTuuJuWs9OU3IeTDGOf3mtXMoJtZCCkunqgwOXirLpMqYlDZspKivN+CdCehAvUp+roQRzOnhx7czCedwVTri4/UaPI0fzDYnsVEp6mHWx2Ns7k5Rvq0QoOOMcFhC3NqaSFLU+y8kJy4WRPQv4JyZrxLROwD+Adwi8RtE9NMAvgHgJ/zpvw3gxwF8FcAMwN/prcllS/ZyS5iU+4SZeiSSiQe/2YdkEqoCt8xNfL88MKKn1tfW4DViW35rxHUNLDMn3jqDXJ+USLZcNscjDjt/3D57njBOJfPQESLW8xHGrReBPFFLfhd9mOOczKPDMmETf/qsNYrFpMiFtXNv6clt/dzyGtEhmhHlCIFvUkpRIlXfehip7vRc+AgJrzfxpRXeC1/vw9a+fKFOUGuZQ3t41GDvsvv7KL9KsJpLwzOYBatO+qWZYwpbLEFJCc3+Ds4+0ZC/1fGnRuaXj4L8TO/eBxlkkBsjNx/ufVppZBF6Z2ZedKfr8qyORyOxso1lS29D6szp2KhX4p2m2qkq+vqKZUFFqQ2hixgBkEJGroiR7ysJB1IyDgChvoWbAoWLUMdpNIpfJ9UfyVja5kvmA0idmbIFUM5Lrq3j8UjOUfemcIWA9LgAOO7LefOrHJLN1FYqtFMUwWIhQ7GAUam3eYiJfRz1IiJwbUA70zgfwtUBxIQ6NU+hyr3xGJW1s2hp19cNOTxqtVSlyJCuRUOjEXB7D/R8P54n2w3xX8izUZWA39IFHQBg0X8bck08fDdIukriXYX0cUT2dVaekxPsXOSE0n6Xo4NJSjPmQt6pe+HO5tbOT+mcP+Nz+uJbFl3cD3nI0If2codfe5uphdD6QOkvolymQ6frTWplyHHh4BSnabAwslBt7kD1x5LSdKJbDcUqrs5n27Bo0opkcSzJ8d2dyBWqHarSZ9t86zRqnS4erA0/vqoCrddgUr9vNm7YPkwbrpOvfdBrF9SyB3dWgk3Zvf1xmowBcYoWsSKZICzdcQp/C1/9qnI+h8USfO82SAhowpwuYujUUHRw7saKZFyVoLkvr3DPh04fPW6ktwPeShlVzhkqnKOTCdYPbqP64FE8T5yXwXpTVo4xwHqVOl4P+y8gL/5i0SU5clEyBfumlmhTsQ25KIhF7VDTTFZs02pemfmeMHvn+upr8z7b6OSAlH5Oi+juF9XANKV0IKiFAHDIRPm5MeYOyI3Ow8jZpkQ/Q6Bc/3XGxKX0Fk6K8PejoyYTlO8vMH7r+7HZAHOFlPQRKK7rZNENzODLZZz39dpVPisK0NP9GDnx2xBebyKCc7lUpSr99X4bwus1eL6AebrvVW3PV+HVyrOG2YhRWSxQfbDfGLMuBRAWvM0GtLvroeBqgdgCwfniLxbHkZkkv29BDJJQx7UndrVGBvIFQr/wDTi2inTk+rJK3sp1UotOoN/L2yMK422LfDQiJB6mzuolz+nwoP7eJglMWS9CijoONaJFoSDYDeIYScnOo1KLZesiKklWlMduQzsZ5JytH6NKTiPjQGcKci73nmfzLHLioym6CFSI+sSQrkSw3MJy1JinZAxSw5Vt4OTk1Qq0f9j80LREQwJjeV1HUh2g+/1okcFnMcggg/SSF9+y6JI829JnRQafxbrFnBXJQFkNLzs8QEgXsfV9iCc6qX62WgXPeQBElZXTQTJatb4+u5QzIpcAKhKZz6NvowuUVWW+kvG4SV4jvhZ/3Ny7C/YYAu2zwGbTiRMI8wHleyjL+JXz0QVUsi/3103GwHzufBZS4nA0ctuCOuW5NPfuwu4fNPsuS5eNWlVgKTPpx0qTMeqnz9P5q+sU9u6jIzQaBUyD1H+pD4+Atx7AvP8o3ouicFuL+y6T1GXCNn0WqEqY+RJ8cAh+4yPu7/NFKw2h2dkBRhX42fOgl7l9D+tPvolKYTxoZwqezdt9FkQwdZ36LFbnmHX6wsppQVl+q5KYvy0391JBWVqPDCRFcOd1grLkuPgs+oCynj67EFAWAyEEGcz9+Txmu6o+wzZE778fPzkWlEW6UhlwLCgrZG+KLh48pUFZoe93Pzg3UJY9BpTlfByR2sDu76P6Sk9Q1uGRW+zmC5AiF271fXXIy7tY5NLmGzju3GS1aKO+a2knd2TmzraTrtfSGq1pOmgbjtK8fWlHoM8dOAl93C6X8cXvOL/ZADd+TheXLH096N9sI53DeIJd2vZ5k4UwnwJfQjAesJEYGUgWTdeN8rswud/JOOui4ROKdWuTPmXBy3wz9X70ZbUJb9YxkuXrm/BqBZstkGFOs5AzAyDPN5KMa3Bw9pA28pscKNUZds3Ib9qyTk9BfsPKwqBqlJLfZGQ7/bJOT1kYOYNcd5LfsE1Dp0J+k7OZQ0LBKQDL6RPJaNy4y2T7lpDflHH7Engv9TZkOom5IVkCWYP8hq3Lt6gqV2xY9FSFkXWkRYpay/VJYeS33oR9+ix2JuQ3vnJ9Uqh4PArnOFCXBS8WMHddYeT6/YeK/Cb2b0aVK4w8X6TkN298BPzu+/E5HjlId8gz0qAsy+CVychvLj7rdJBBBnnJ5OZbFlsWRA6XyRdeO/H8/wAU7Fq1rzggehVGlvY1TNk7xqwGYll2xwHUAZTl6lkEuHYGL09rU6isU40POI/CyF4XGo2i83Vvz+17rXUOSMDpslqliV35fMj1hU+n9vwMMjehf6WnOBwbhZHFP1NVkcvh1q1oFWhfhiEAC9CoUj4R/4WdTkCyXVCgrAQ2L3M7nYD4KNGTVyvYV247TgkR0fPOLff70TyC4vZ2Ql+2KkHLFWifUH/EWRb0+EmwJAPkHR4IV5YOoOb9TGZ3B4uP3cX4sSqMPJ16gF585oK+1gJHRwFaDgCYvUwOzlMsFIByoImpJrH4vjw+OUgq/7OOySvQD+oaLP3ngC19fe4czYFfbUCwNrCW7vukcQDe6ZgCwZgpLSO4XDkHIHPMWpTf9ZYpG08y53Xt0sxlayLz7oFW4bg4M4Gol18oBCwV+hD8B5v0PtZev/Ummcfg9BSR+yOOYX0uakeSk2XHAgDNlrHEgGonIEM3G7D12wGP2ERZuAV34x2cMyHlUdgOtQ3k1RpkOckN4fUa1f4qzBkAsHEOTmJ/D6QMpteZ15tT4yxu/mJxWjmO41KkrcygPzfhz+x6cduu60J+MruVX3wpij272YwumIzodFMcj4meGjiWR0PyylkKQahfZNaApnWsNZqAjdrmQeawZdwM9eDLn8UXE44rRKMGZUn/ZMPCSqt1QJFqjksX5WIQK0Jm0V0tRkAdfBWMFJxGKHxIVxCY0edFixWsWnQEwCY1SBOHrPgQam9Veqe3mS381ET/U0IAsl6Dbfr88GoNc7hwi6hYV+uVH5MCf3mdQv1WHQ3Zgvn75i8Wp9yGxK+fDb+TsdFcXCPN7MyuPSnrNNzsrBYIFQWkEHMIa/k4PjPHnIvCqJe22Z/Q7ukxUJYrwUK/xyOWvWMAACAASURBVMosT9iYbCPrlIpC5YZ4/Y3PwpR5Ho9B/usecCO1dcWTa7VFk7mTvBX/8KeM4Cb0G/63DE3Bx+JAlrFVlbMoyOV7kLwoY7dVosIAld/O2Dp89amM2BQy7lqMxyBzlNwfRh30CGLI9xu3fG6OCbw7BWl8x3gM2mziFm0Bty3gyO6NqgSIQEKi6/EXkd5RfajIuL7LErRah4gNjSps7u6gfFhFXUeVs0B0pi0AqqoI5ddZp1skl938xeIcpbE16FP/4eRGT7whbNl/KVXYzn/1yXiIL/rvLc9VdN86zOa/1q3kKX2strOIle0Ru4Ui/1hYjj4nTudUW01kO3JsTqlP/L2lzQb0X7a/mf5qbH2EaptsTWDFikq3n+dRAH2IhgwyyCC95GZaFm1bj/yYJo1pgx8rqDXIuBj9ahVMx1pVsI42cYRIS1Gg+uAAZmcH9YHUffBYhL3dWMfCi5lOQLedh9w+ehxgt/bwyMXZmWF9QpGZTmDro1j8SOEkJLVaUIPBO76zA7q1F/rjR49hxmPUh0cw3swV8I/gGQQLUO+7rEdz766DCwMJBJx2fQEfAPXHH6D4TxuQZZAvpANm8HwO2kQiljjZJhYAAkLqNo1GgMcnyLzT7q7LHvXOQXPvLvD4CezSwkx9gZ5bt9y9Wq0jbgHA+jteR/X2Yx8NiaAkrkrQ0+eg6RT1QrZ5fqx39kCHMcJBt2+Blyu3pcm2FrizB3r42J3r7yO/v8Lz7/sI7vx76YyBUQXzdB+r73wDAFA9OgSP3DZu+Zqbr820QD0hjPZrTN7Zx+MfeAUA8MoHjwDJVpUtBBHowavgnTHM19+D9cEb/ugDvPPXbuHjT+66rQeA+pVbKB7tg0eV08U/55vbE5jVBsXjA9Sv+CgNEXimtiQnyM1cLNqkzcxrOy6SOQKtpB8vsvPyqIeHSFvl2bfzRaMfWSj0VsYul6Dn7MA4m43L3YB3hh0ceIedpB8vvRPOOTITlN5mA55zIzfEzhduDyzniZ5sIxw5eNI36XHRcf8ghE5ZRzpU6nr53hN3nVVOVknv7nD2JgunLHKLZYRUzyX64TI+pS+7fxDSyyMZLwdOTT0v1duP3TzmRYYMuWs3aa4O7x+ANpvgnGRm0HPvQ1gsUu6LzcadKwvo84hCvf2nz4AnCpRVlrCzOUbfdPkiPFvAFAbMjMmhH3tVAmXhnI3PDnDvP/pQ7HzRjEaRAT1+BjqoYBUc37z/GK9/aQd4th+2GcVy5XND0tBptT9yUZmjGYqlGteqJwIXL9JicVpHZy4ZpX1vfotjJBQR1rTsFKnbg8NSxdVhoqOw4fO4TGYuQyGPIUQYiCILeDgWIyMawxLK8BnF7nRW9itDAHuHYWGic0/msTDREmPvvxBcR05aVJZnnk9WlIMAQMY4J3Gg6XeWDgGuMhkQX+aycDVEwnNBgdQnfAyOYeviMsPc6OfrnH1FN3+xSLYJGa/mFm0QkfO6azBO4DxU25BtVg8B1nTUBYlMTIV7aHUCEAkfJDtKfv2iXSCVGxGBZcFkZwWFB5gUvfx47P5e+WjIeh1o5gLkPAcXid66ANA2EghdHI6Ci8JFPTSATiI3njGK1psYISnLuJD5dlCVZ5/P0qQv6aiK8wYECr4k6a40LohV+RIDhTvXeJi2ThdIMnu1EMFW5O6BPPOFogO0BiRzdg7PzODgHGSQQXrJzbcsEp/COWxD9NcuZ6PaVjwKL8J2s1U+ZH629yP7UBd3P70aZxEBMwFI/TybjfNl6NCpten/QJwDIJrKwoC9TWWxNrHWhSk5vWfM7HAgoqdH6Lp/GaJ1G+um6+ucZNTa42txBNAdAANQnYafJYTeYFHr7BspnWGZPSg6VSGQEJ9u3m/+YnEeohGC2lTMK0NJJqSnjAfgwFuFcVwIWtQNiRW/ke6ZdX5KcCbGTFJerUBl5R2raoGp64TsNgKYTGKyBmr7DVLzG9Efo8fh9FYPZSDYBUAGvFFkwssIZY4DddiQnJsjn784hipwQgRQllQgkzkrS3eO9nNIdTPmBGbNsqXYbNLs2qIA1wuQrWPWqcimjr6WsgzExFSWKZ+p3yqKzynJti3V9lWwOoZcRAJwVcdkcRRAVGlgRwXMbA1ihq3c9UacydqhLbr5vKKwNJUl6okBbxTS1BiXlUwUiIadjv7YskxBWVtsT27mYtHBFbFVEznMWTz5+qvQ4SRq5HG0Ea5IHoICZXFtYwTEZg+6kJ5INEQS0DLotT4/T1HnzQasiFD034NnP+OSaPA3LpZNb/x6kwLG9g9iLkhCups5OFVuTJKXIYvcXEGqOVolOqrC83nUNczXIvavhJ4+d1EPYyJK1DK4XvgIxzKBe/NymbwsEqHi2gLFOp0bD6mOER2JXzLKD57DzhR3xWbj+nriGLh0P0JITGUJ40FZfHSE6v3nyRzmzx4fHgHFwkeG/H05OMDef9oH1iuVHlCHFHUWBzDgKrttNo7sR9emeSnJb7aMhkQuCX/Aw5ED/uIEWr0cxt04xcN1dQ5JgAwTuVCc3Ei20VKQPAf9BdH6WsTQYJZ1CjKNrFPIV7kj67She1WBIKHTOBZNg0+TicMi1IoFW4WVowIqa1LBl0lFVfJap/DOukCuK6UAbLSCaFS5jFpxBMqcTafuRRCHMQBYBvkXiKaTxOpxeJUJsH+Y3h9Tp3Vnvc468xbesYvlEvbObgL3lvMChZ4fPzMHxyuPK2dpbFzSWn3bO2TbtghyX0eVSwcQq2syweLBLibvjeLcTibu74VJLFkaeUew5ZRW76D/loTOAwZ6VrlN9/mHqFEN0clJEQ69SGRELsdKR/hOfxVdUeFs0eg7X7r9HqG5UO1K0aEJOQqQbYk8oc2J/Z7m3hq1582g6jrvROpuhmN6YVBFg/P6nE59ZT31Bdcp3YQYJoScdQ6Fz4cIelkLu1rH8LXopqwgG/Abdff8NSrYxd/N7m669fJhz2S+ZI40yY8nW+L1JoDmWNUwYQUMDKRC6r5TWcLs7aZYGW3NZvcvJOWpY1+yn8e+fdJrLzJEQwYZZJBecvO3IWe1jJSfAMh8A+eRSOYajT+3UM653+VrKXt3k6RwX5q0JYEFn4vySbRwe8rXPvFDWJN+6YB0a3YK3eR6ma9I1+fP85whAJqp/oogGECaen9aUan+lNHxab0T0ZEjtmnCl48eJTVVukSiPEl36jnSVtcZ5WYuFm3sVds2kTFl5QxJ6d47Mz1NNHN5vXJ8mZmPIzA8aR5HRdXP83nwqNvVOuZoHEpuSOWcUf7FTFCRhaORb5QCUKUGAA//LlzhX83s5E52Ly+VAqpyx83eXgPu7VK+q0hBf+8u7NNnIGtTH4kwS+cvCxmYURWZtuQaomhqq2iIhpbTeOxYuDebkI8T/CeeKUtS1M29u875mjNlwTkZqSxj5TA4LlGMx7AC1S4cQCoU5FGREyqMy8c58vktfp7tbAb6xMdQvPcwdlaW4NksLQXgAX7kmbLYIzdpuQbvH8B+/HXX7p9/M9yjUEeVDIo7u0A1gn32PGxJzSv3sf7Lb6H68jeUH2Mc+wPi1m3s4d6zeSxxCIAe9V8Crv9icdJCkFQb11/w4xPJIiJSheiAmCC2WgGmjO2Ha2waOt1IeDLd0wrRLClOCypLd9PIAOv4AhOzS9SyFpCkpqoMVagYSOuiCkIyEOtK+NFEDgUAtFxGer7AvxAh5mxj1EBCpzQeKT4Lj8osS4fYFMr827ug5TKUxAu6GAIfKU4Q4V0wlJLEjqporQgBriwWkzEwV1/qydiX3KPoVJxOHMNVXTu9ZB7u7LnjZRkSqGCtC48aAk0mkVYP/tq7t2MVcmMiZV9VJs8NlSVoOg00+mGe5wss3tjD9Jl3cBKBJyMQW9h7LqnPFMYtDrVFfd8ds5MKbAi0sSgNYfG6W0R2/qIMi1Wwd41xTsnxCHQUmcRpdwfPPzHBa9/YC7ryzsRdN/IcFx53wdOxy0OpbaT2A4An/QE819/BeVHS5bDKWLRPdCR2LUgd1dYT557akgieQpv6DVo+3Z/WXfeZ1LGskSyaXdfo47mDM9MbiF9/BxaLDs48VNzYfmXtsWXkpQjCeVofVR/UnRLDn216JYlkQBIBStivhLFbOyf1/GX6J1ss9ZwUd+8Ei8Pp6aI8SX6K6hNAklbAqxWMz961z/eb2zmZf3F0ygdpPIa5ewf22fPYvnKKB13kuMe36L6/uPwd7NvHg4NzkEEGOT+5/tuQy5I2ANYxVoWuL+L8All4sCiaoUFCup2QL+SG/RcglkEMX93cMsjbz44lX6xADdhSD0VfI8fl95wXEwjhQAAwo1EMR4YvuMOp8IazC6UfUrs5/7Wryrj9CdmYQqtXp+foexOyLFPaQhqNWhmhgsVhCFjXaTs6y7goQk2SRnlICceKz8fX/bAruO3NQlknxjjrQLYqso2C2r5I5u56HRG5IpwVi2ILGk1TNnQ/LtzajdsoPwdoqaJOhS95eTRLt6rrgVavv8+Cldlfq5fnpIVCv/TyMGoJD7QGJhUpBkG3IceXClKtCxhpfSmFdYftShFLDQAI5QYS8hy9zdEmqV/YSDsi1VgSn8PujvNZAA0HJ/IFsjEfyOjpJZJhwjE9l3IOb2Jd1uCMzjhH6fatwDOhhcrSIS6rKuWoGFXuxRFCHE8qhLXwZ3r8grXOkTqqIpfEeOz632zA9++AhCNCeC9p6UoTAMBsFssD7MRap1yVge3bvnbXnfvkaWsUjqYT18Z6HR3Pe7tYv3UXlSfkARCIhYLPRhaL8dgdsxwdnETAFkWGXtzF4iTym8b5Wajp2FNVyQDmdI8o0sX43cXuncNuT9DjpFIDomdwfOXkPCGRKpsnTSuv2L2T4+t2SvxjQ81tIWnN4i25L3WdMnrrn9V17PXRoU9erprzCLjSC7V1yEwtdZ1C7msb65GsN6l/o66BdQyLioXGlkHzZcruLfdBFqa1ihAJh0lROMfrwpURoJlbNILfJ5d1JOgJslqj2F+lFqZnII/OUW+9knGlFzabjN27v8/yxV0sdHk+7UTrRIIaNNi4O85rREMm44iwDI45QiOEn/NlaCdcjvY7QQ/NkA3Pd9FIJKtqR8+HRbQspGwiGWekBHbuOn4VxYEmL7AUNQpbgyrqrvU+Ls9Az4dsQ3LOBp/TEUoWAr7sXsaH4SMFgYVbxjsegRc51Zlvu1g359iHoON8Kcvi1fswUti49mUaDYFWEXKO8RiGGTwdx3mXOdTWokRoAMBvAaSKOgGuONPOOI6x7d6PPLt3UYDGZThW3x6h0nNQVW4xyC2LUYX69XswX1+BdjzDuGW8+IlkfYSzr64+lh9HfFlO5LZpOYcXy+YiJC+fprmr67jn1VaGTvTS52o9M3q/hMKOLUDui8RCWON1sPOFTwSL53KNeL6q/en0iJXedYVzAGEPz0ezsOgkendtQfR8yM9wNIPBLyAPbkiki+eyFDjKrJP8GO8fNOH5gPvaSgV1fT9WPrKgE+bgaomaJ08D9JqZHfbEmLhFWsBZH+sNzJPnaRFk46qds+dlZeWz0EQ94rPg+QLmw2d+uDXaLAuezcHebxQW2LpG9e6z5rOzWqWEQICzQqynUUws2v6gvyEaMsggg/SSF9eyELloHMk1wKkA8F8j75zVpDld5Ri38NFcmlgGCo8HUL6Mc6nf0kfYhi0P1yoF3jLYIOHZDKRAVzF/p5yPwHtxSp1f/MWibzREEI1Zha72NlWKehcnZqgYpqIhynvPWRut5DSSjt4SDQk+lkynUPEMiAxLNZo6NrISJUpiVCUxiVQUaYWuUZVWEPPCwk7eNd+ycGnCG9nqaH9EXUekqZDhqEhVqBqGIh2XrwTWkKIAauurm+mwsffxyBwURah2pslv2KiwqqpuFsKT00mg7wfgtoHWOoQoECuEQUWPvL+EiNx2xmed4lF2X6VNj0pNozkj2Fs7aXarh6uHYzI/1cj51haLWK0tK5lwkry4i8UJOSONsn2eMFfX5zju2ujghCf7zeDeVdnwbzi4t3+AVqvInbFZh+Pw5DUSjpVFIy9fKO27YwruPY4xdF4uA1w8J6ptMmVFeDUyNimqyqRdurUH8mQv+riMpe0B1PrGEGgVXz71MvFyGfbSztm5BlDH8Op04nRcryMEHHB1PfL7JgzekseifAs0GTsIt8y55IasKaGfI38/Aszc6wVDsEczbF67jULIbyw7tm4A8FXUyZjg4OTbDqnJpYEdlyiOViAA6weuinrx3gcN/AwA1/doBJrHEgW0t4vZx3ex9/YkjsnXjQkOV7nv07HTbTIJ+Snu70PoVDk42xeM/IZY79g70eRl51jTFcGD80yfFip6x+N2tQ58lqmzk2EVw1XQR+mZFMT11yZMWURJ+8k1bDOmrLiI5YuiPZo3HJxc1+5rLy/246ewnnWqwRXZNd9aX68L102mrFAPxM+vnc3CPMqcEB8FBycpBx09fJxCt+W4r9OS3yd7NHe1Q5Ve4jSllUnmhteubggr3cnnI5XffAirgFHsHZzmoasbYjUoSxYmIpTewWnnC1R/4adwtWp3cB4cOgenmkf75Cn2vlw5Fi2R1dqdk4OyDgqw1E/Rc7RpWZg6ZHBwDjLIIL3kxbUsTpLTIjj9tWELsfQoyEtGcCaISETzPoENC0JTJzV1ITiDeX3JCE75qnv4NKrKbS+0uV/XYKYLR3CiKGDGY7f9G1UBwMmevk9TC0p2Mlbry0FwjsfAqPKZzP7YtghO+Vlo9YwBZsM2JMp5VSpT7elMR3FO5j6LixZSjtWcTEZwFsFXoR1gGXdo7li9dBFHpqeqD5XPNBdp7sy9KFVkTomcc1K2XcyBRp+0P2ZUpc/CRYrOHs3BZT2Fp2PniD3l9TcvRX3bl/+0HJ3HtZcf0olkJ/XRN1V8Wz06EJ8hFVwk1ytQ21dNFGp+Xlva+Fk4P01MWtNp60kyW5vuOT2AqNiSXJfo1sbvqXktTRF0MJNxg1wogWILknc0ckCpnCOVbZPlHNFRrdP4he8VQGcZheCwJBOJd+YLmMk4BYTlCZGKv8Ts7DjfmHpWvrj+nd4cnDfPssgg3DGjMOOekN81eY36u/EmolT2Nq/cB+aLYMZtvvW+M93qWHxXkrLMdAISZqvHT2Du3UP9+EnSR/nWm66o72oVvkbm7h3w/TvuIX37W7Gi+pOnwHd+G2AB+yd/5q5/8w3Ujx47uPbhUWTSOjhAcec2aDp1RYyBgMI0d+8Ar96NU/XN90A7O7DPnqN49b67/pHTk0aOicvcdV74+sMPAQDFX/kkaN85zHg2d1/T6dRXG3fOuf0feBO3/99vAbWFve9N7Zphnh/Cfvgo9q+cj8WD10JVcrpz2/19ZwJ8yzFMBfP83m3Q0/1QyR1vPQDe/QD14RHKt9508/XKbdBsCVqsXMjRYyOef99HcPtPn7kvbykvI4NL4+j67+wCX/lGOE6f+BgWb+xh8odfdTpMJm5LMV+Cp2OYJ5EnAtMJNq/dRvlNpy/fd/Nmv/J1fOPvfwof+7wnLaotNnsjjN99jiefehUAsPfuCvWkAFnG/re5F329R9hMgfFTxr0/X+GbP+q2c9/1z94BP33uiIQkIkSE+i9/HOvbI0y//E7gr1j9V9+Hw/9+H/f+l2lwbM9fn2Dn7SPU08qVnx27BWvxSolyzth55xCzj+6FYdl/8/voKzdvsQCSlbMBixaxzQUiaUJVMAcAfr7v9qq6DkYbBJt9vYk6tu8qoGfRlacOhsuWo4n/7HnY29rZLITh7GKJ4t2HCAVq5Pr1Bta6uhkhWsIcvfjKMw8AfHCQhA5FT96sg7c+Wg+OaEcgyUHefxQiCiH6MV+Ajmawvr/bf1TAfvjYvXCil2XY1Sot4qPuiX3yNLYnfpODMjBTh5DkcpXAwM37j3yVegv71EGiabEA1q76uabgv/PvATx55vb02uIpCtjZHLR/EMdmGcV7DzF9doBaqPIWS9e/D6EnX+yjGYrZPMyj3EferPGxzx+h+tr7/vawi3IcHeH+H7pL6XDmGKssY/KuJ7kZleDKwMzWME/38e3rB+74oyfuvmnOUgDFNz5AOXK0ejLHO//hfWw++xbKv/ha8HPc+mAHfDhD4cO3kjcyno5Bmxp8cIi95zF6Uszz6ljdMkRDBhlkkF5yMy2LixSTOgC7oJza17OV30dQk2dlW26p0ekgyLZxrOv85O9av5NkK59R9xwmIvopyHWiT58+E3+EovZriy4E30G2XT8OBq/b0XVSMmh4+F8zeFsDnchG1gKWIi6mTXf9u7I6ow7saqVmx1xSYNyGiY6OSZyz+W0Os0te3MWiL/mNpKUbH47UoTgT2Z3iNXEfCQBM1IrgFOdZQuNeFDFVWdK+4UOqVeX2qNKOQKwlZVmHOOVaXYZOdMo83SGaIMfzaIiKnAQdCz9GeaiKwlW4kvCuhBzXm3jMWgeTVuNKCIV1insLD2VYpIW9qrbpOXpspSdxARIiYYwqV49U1xSt/Quy8bpKG5YdC/dkFCHR/hkI8GzNokUEKosIdlLzudkboVTUABiPgEUJHntCZmFpZ4Yde+fktAQXBmwI5XyEzZ47XlWesNdEvlDpG6XTKSx0owrLOwVu6fD1eOS2SKUnHBbC3snIoV7L0tWEDfN+jnBvIvosgP8awENm/s/9sZ8H8HcBfOhP+/vM/Nv+b38PwE/Dxbr+B2b+V7216StJqnkHUrMvglMQjRnZSXJOOODTuC3Hh1nIb3IEp6RV6y+U2s/rUgNc17BHs7jyAwGpR+xQgklpAo9wzMlvXC3VyOcQ9MxT0eFfYM6qoAPg+SKOW8+RjSn15vkB7NEsJlPJtQoBqfuSv+nUdCJy1PSN6MUiuRdBnzyN36M/tY/GPN2Hnc1dyFhbDB65yJtNOu+zmbPEwqLGAHl/lEKsOqV1GjvceX6M43efg4+8H8CyWyjmC5in3k80mwdYdeERk0VZOMbv1Rp8eITp257nwusZ9BH9j2YOYarnZv8Ad75yJ/U7rVbg+UKVAvDRLl/DlhcLtxiqeewrfSyLXwbwTwH8anb8HzPz/6oPENF3A/hJAN8D4E0Av0dE38V8IkvEdtJWN6Sr7F2HZWEk/LR02wKzO3X1MD05SS1OJiBGU6QUQFXGkgGbNcx0gjoLO5qdHVfUVz/Mu9MI1PnwUYi82P1DmPt3nZPQP3RmZwf24MCF5hbLqO+iDrT0wekpL/F0EiIsAMAfPoIZj2FnNrJHy4Plv/Rm6vIKaqkbcv9edP4K3dxkDNrZCUWX1594HeVXfK1R3y4A8OER7HMFS1f4D7O36x54ROAQTacOhATEnJndHceX4R2R5v494MlT2Pk8RITozi1gsXT1VhWf5Oo738Dom4+8VRcXCx5VoCfPQf4eB53u34O9tweS8guTMejWLRfBGo3Sl3A8Bu7cChBuuY+8XOLJp14NzkxYCx6PYJ7uY/ldrhbI6OER7Mi9assHPqo1IaynBuNnNaZvH+DRD7oaI6998CiUg9BYE7z+GuzuBOZr78DKuvSx1/HNH9vFdzx6JahZv7KH4tGBs6yYwb46+/r2BGZVo3x0gM2r6hmZqdyaE+TEjTMz/z6AJz3b+zSAX2fmJTN/DcBXAfxgb20GGWSQaytn8Vn8LBH9bQB/COB/ZOanAN4C8EV1zjv+2LWTxPz2ZnrgYExObHG2aX5FNEOscizhyQTcViCEbG3clrAFzxbe+Unxes/lmOvLzC4ZS5vPoocO93k92UYTPvBqok6Oh7bn88gQJVbRygA0D1uZ8smRgzkzAzO17Vl1h+HC/AKd2zEAzuRWoVOez+PPouvR3G1hNpsAyQaA6tGhm8cMaUmLpWszUciC53OYwqAWy3O1dtDstWs7qUhmGWRMDA17K4stY+/dVcCgwFq3tZjNMXroLZb9oxDKnEhofFJiXBoU8zXMwRFuvbMXdMidpQyGOThCsVqHhEcAKJ4d4u6f3wLNFmGbVBD5UK2Hl/vtT7Wu3biOZih0rZVNf26L0y4WvwjgH8L5xf4hgH8E4L/dpgEi+gyAzwDABDsnnH0JIlDftpL3jXMzLs02+Kx2jmnPu9pLprBs40hrA0oy0yN3RBkdUYn5FUmRoKDnutmeQKhz3VVpRigHW8jdAFxOgyGQjQ+j0PkxgLbMXSICK8iy9NXg8jRF4gxNzglktwZs5ToT/TyjEqYw/l6q8QpUO0/HLpzfQCkZnKcoywZWIzmmHJr1pAiORIgztzBh61H4PBDALRIAYMcF6nEBqhlFUWAz9bq1ORx9mj1XqU5clVjv+rHK8ar0unrHpvw/ctwZZAxYlbi8cD4LZv4g9kX/HMD/7X99F8DH1Kkf9cfa2vglAL8EOLj3afQ4d9HhLqA9fHYKiV9zRK5JywmjVSOEmevRxo59QRL0kgWAfaHeQOTLUf8shJwsFJxZQxehd+bsFl0Tx52JC1pyTy0nKe6nFbJqbNmcdIr1/fvzSdS1LfN0zLyRRfascPb3eC/PKqdaLIjoDWb+lv/1bwL4sv/5cwB+jYj+NzgH5ycB/Lsza9lQQEG49c/bNCFYfPl6jkbuponD7Oio3cHJNjBQAwBmM/dzxkdB41HD00yjUSAeoYNDdw48cnB3J7nRNBn7WqWFo3EXfdcrT0YzCkxOgVRmNALtqqK33kFKy2Xsy29TqPBjkXF4xyrtThuLJI1HDo7tH7zVa7sYPRw7UhjJcvSLAS2WacQljGcS50OcmTuTyO/gv3a0O3WhUP8C0K4jp+HVKoyB93Zctia5+qUiy9d2MTn8/9u7lh5Lkqv8nYjMvHkf9equru7pnmHwSBhbWAiwF6ywJYTMmh1rS7BA/AaLhX8DEhJsLdjBxgtWlgDL2BICYQ8e22PPTLfdPV09VXVfdW8+IlicOPHIe6uraro9093OI7W6KitvZRyiOgAAHDVJREFU5InIvJER53zn+1Z+BcMNEBd81TUwGgIiggyAJiO0NyagRzqM+WjIk0s5SCqJqShY41X8dfB0UoTpb+QemSnpUd20PphZWutXFOd32N+mVKhHhPIkw3jd4uwz/PfxdweMIlYqmQTs7hjtuID+aOC3h+2NMU4/b3H07yHIXN8aI28NrGMA9wHO/RKqMsibFvXNcL55/zlWnRLRNwF8BcAhEd0H8HUAXyGi3wOvoH8O4C95nOwPiOifAPwQQAPgr557JqS33nr7VOzSycJa++dbDv/9U87/BoBvPItTH8u6K4yYB2LbfBUHwBTx3lf2rHK8U8UoPJ2yB/bXibUebBQ/6PJzOjVt+TtFQSgrqt3xntjFHKjLlag1PJBMfAA4OBjvwVXkG3XPVcH3yGwWgGlSsk1ZxpgA9/ZvB4rf8k0D60BGnk5OZBiBoCDvVmNSWk3RGPg+qGiPrcJx64BISZzI7cmpzRK182boYgNawUohmQGQMdemHeRBgd4Y2EzDlDl0BPyyGcdsbKY3xtxmEYhN+kAK9YR8fIKMgRlm0JlGW/K5psxgBhowvKIAgGpMaIeEuiKYYYbaxTcp07AOkOefPcX9MYXmAKbzoc012oPoHoALx7I8g3X+mIL9bN11kWmYIgbm4cr26iI4r2EMxlHYCAJ2odOydyRKA4nxz85IKY6+x0IuUeDJtwMXG5Dgm93c81sXiU/az1LyWe9HjM6L/KSs42McZIxNa38tGwdmM+2XxW2pwsTmEadRUDHefglVYQKScu0LYS2iQGme8c9RwM6f4/43ecaoSPFNvjwlRYFGuRZ/YZQLeiaTf6aTLQtJELFp+boxKjPPYAaZR2rGKMhmCNhcJidiZGamUbug5SBTXP1pLOqR83VIqHaAbMnnN+MosO2oG/2z0LYwgwxtqVFkmc/qtEON8f558hy0AwWbaz9JyP9NqWCJUBQZmmG453ZbQPUCe3Uni8uo7uP4gKKwT46DSR3SFc852bZhP2sN/9ydWJotjFFNA1pV/AYzBlb25Y7hOVlZCOTYGOef8Ci4CcYJ6iZ9bBrPvAS4eIzzzXbiG170pyvovK4CZbyX6mtB65BGLKaCMDSBwzFCeAZWLtc/5fpqomuDYzVG+uD8o/M1C+8I0OzcnROhTWldAU0bEKSu3WLaOkizBtxenVoLtaz5nCZivTYGtK6T1KGtax6/1ZoDunWUOiWCXlT+mB9nazA4cdcAB3+tIlBVY3Dq0JrnNahlX8sTHpu6ImRLQjG3UOsG5TGFsRFCpWhloReV91GCldmsxvLBBNSGUvp83kCtKh84VTVfr8gIetWClmsUp4V0arO25Cn2ck4W27AP18xcxMQm1iiGFdcNoCLcQAeu7WG2TZPgGWyMbZBjy6WH5ooMoF2tw5e9aYBlwFzQdJ4UC9nl0uuWMkFvQIjaquJldAcWbM/Pk22F+GmNZQhwdC6colnXdzube3yB5+KQLIK7XvELxzchpLWuDx4f4Rm8okzJMqBZPVdFXUcw9OhcuRddf5w0IU2JcRtNk9D4lfenwOkMFG2Z0Br+Ai8WIAAmvu/TGTJFvvTeT751E2DTYnXDnz9P5RGtYT4KgXYDQHZeOAg3I0DVbMFbHWsxXjvIu6sNUesG+mSBG28P0nFq24BLUQT10RmyRcHXd37mD09x63t3oU7mfgyKdQM6m7GMYVQbUi4cI/psgTwKnKpYVf4Se/Eniy0MUjEzlfzMnJVRTcIlMQuBORv33KqDfX6gJrx5NIulZ0sSDgjKWEWbhkMogWp/eAy1vwfjYMByLXXjAHY2S4A9an8P5pDJb9R7BrTrrvX4CczrtwAD0AnDn9XRIcyHx6BhCTtfeN7E9rSGmoxBZenJb4Qtm9s/CONU1VDjEezJqSe58eNWFEBV+ePmoZtM7h1BOb4DD8+ejGH2xlBT/v2jPzjEje82gDFoD5nIBq2FPp1DxffJvSVt00DdPIA9c+Q3+7t8fDiAklXG2MHRD3ahTqa+1sK+dgTVtminbSDqOdqDWlZQy1XQ2wDw5Is3cfB2wW3rMGmaXCN/eIZ2dwgV1XCYN+9gdWeE0cmZHxNzax+0XMOOBl5SEADseIj69p5n4RbOTJov8P5XC89HAWvRTHIMPxh4CPfO/QmaoQK18FmPegI0Y4vymHDj7QF+/mfs7+ffPYQ6OQNIgRwEH6RQv3UH1V6O8brynBrzL9zGa197F4uf3fXfj8W9EpP3x2iHGchaNKWQ32hk5xaT9xaYvxmyIc2Tq08BPZ9Fb731diV78Tk4t3FTbiskA67HsSnnCkbBrUw8b2LbgjoKUN4P4W6Ua3Up/QBQXqBbUcnKXi6Q1zS+Ddu2UKKuLQIyEZN0HDC0kdpUWjnLfaIo8GarCsIxuSGeJOPWGTNVlmH5G/NNRuhHX+xlbaQebn08pxuz8D5Le7GKmfQ3znREeiJeUd1akFPSEmV1DgyHwCuNR7x1oEjhLa6YjbAL1lrGoGRZKK6T60tQOr5/Duvinwdpf71G9uYbMMehfIryjIsSpciuqj0Qz2NMJMvTtrwtu80UfPYXj0KJelUl14bWDH93fumdHeCN14APfhkAc5nzUdCuMbKzbnyRnNh35v+Cs+bxlaKcL/42ZJs9jwluW6bDGsBG43YRcs6VtV/UFrAZ7+Bj7ovjSXSjSaBOg6QbCubx/t/72vGvW8oe+blZbr9ZRg4gpcXz1oatHQAslq4s34R6i5jMdoslWQiXUrVNHWI0cX+jvlkJ/MbnxOMU3yPxS0UvkCi2A4TgK6Qupm3T7atcf4O0p03vaXw/Ts4C0S6pwNvqqkfjWg+hbfQM5rJNc1uhrSXj1qSiTlJfcr6CenTM9T8RtUHim8Sw1mtsE2ay5uJ71rWXc7K4wLzEX1xjcbUPpv/LYa1gm85518GYbeiJBh+7P/ObJyVbgVKwRlYg3azM1d24jnXZwDd8lONawTYmBDgVHBuUCSsHn/rrtPsxWcISZmw3rlxT04E4RxgWnxGK9UyBVBNFnpuPO6YxzgZ4en2Rr2/RYcXVtuHzXXId+dlskdMUoiGtA6+IMbAIJQViXLfzbC/ZF3+yuOxLH0fRn6JP+tTP2zZkKUzYXpiqe/1rZFy2ZWzi9l0WRn6Whze8PTsB28jfC+nun4PZzgrBtvAPMrkJy8pWISEBMuGzESlu+Ft4U9u2MwldxzdIKtatzGJf3VZnG5GRv3bkGyniFOkzjqesssLvbmw61aP8c7TSc/fStsYHM5NqZk/Rd8FzbWyovo2IcniFpML/gGfZexbrA5y99dbblezVmiw6DEnX+pz8qMjDqzdg1s/sn7r453grFAnDbJy77ffnbVvg4dSFjcvyXf6RSv3d5qM7/jxUvMJ9UqFdCTw7iDplAf2Z+CU+CGr3GQmUu9cg9+xQBM3eSjEg/3f6AWCDC/ZCU0wdQDoNQosvz9Ne/G3IdewatHo+Wu6UtVVZMl4jyhpsbGtce/Ge2KzXTF0nAS6h1RsOU+VwMJWf4CWEMg8AU8ZNGK/QOpwFFSXMauVFlGK/WAlruEFoE7cfX8Os1j7bYs7P/ZfFGhvR9THOQu9OAghKdD7yDDQYBKq727dgHj3mCWMQaO3seu2oBDeDpKocJJkeADxuQmknOqYDPk/GXo1GMPMFbFN7X2k8Yh/rmrVR5Z7ePgQ9CdgIbsDVtswXoKJAexr+rvfGLKBUOaq8YggalgzKKvIAHoMLjA5L2Nnc+wlFMGdTtJ97E/o9x9rgamTsYgncucUuzBa+5sjucobEZgpmkEEvKqiPzlC/xRR8+r/egVmtk62HNRbZ0SGQ5zBPPvL3Rd85wuyLdzH5t5+G7u5MYGfzEMiV53zo7tPZ3Fc+gwh0/+q0ei/nZHEVDs5L25A3Z1S30Zo0sLSNsVs+exn5jRR7kU2PRTJ0CeN2lm35vLxxOgE0+ew28pssS4vc4v4l/XZB067veRHiEG2nXUFgDgcp07aYBBK3ZUVif+PPdslvipxh6+J3kYdAc/Q5MhbWmKR+w44GoNnmw8+s3ituOx7HvGAm7tgvKe7LslRT1IlO29hPZ/VugUzSkYKarCqYMQP/dFX7WpJ27F4QhWbSHADZokC1x+0No4BrYnkexl3QrWWB5U2NnWjCtMMB0wSIfzJZjAaAYfi8nzi6JEGX2IuPs+jadSeF2ERbM67BiDEacebiEq3SeGXiJRSlHUjGolMfEuEgbFWlbbg3tE/BeflF2vRXagc6AdCuCLKtHbK1qUFZ7o5V6bZLfDCW8Rh5EQUiA48H5Vl4o03GaOcLJLT/QCL1uDFsWZYouHNDOqxeJEuhVRowlHOie8M4C5tgTgBG5ZotWqHk0pPQOtESpbwA5UF5TFaMgt9I0tBOsT3GWRCxxKC+eeAlBflcBVs3UA5daqs6PDdl+KJSlnGtx/kKykk6to+PtwZc1XDI/scq8FkGeu0I9v4vwzHBpaj0ZUiaiwzt+SpA4QF8Z/rPrzjO4joWTS6+xBzbMQob+Imt7akQ+Zf2t+wNNyYKd41Qk5JmNTa4KLviOl1GqC4GhBRH+DspVnnIL8JA+AxDnsFWJt1C+GuaBAcicoK2RRrpvwxn0cFLJE+omww8TkIyRaJFglBYFftio0Iwc749s2Gl/c6YMc4jfRZ8sdogTG4e6xJtKwmcfaEiTyQFgfCiEBbuJFMicHuhILSWq0pFXnLbcyN9dnU3wixvlkvQh0/Sa7dmg1YBACwpqGKH24lJda6Bs3i1Apy99dbbr8xevpVFNz5xmW5I/NEYyeegw/ImVSMOmnk5+8Ui3bb4Ng0oy8N5yyUrkssbWWDTOzssGBMHOIelhwCb07Og5nV+ziruANpHrNKtJhOYxdJDjONtBA0GXk8EgAcTxeru/hpZBlM3vvDNF4c5UJAvqHMFVvrWLV/d6Wn78pxp5KTi0kGMAQDDQGuH8xXMcrm56rEGajLxS2h5M2IwgJk6oWE3FlSWsKtVOHf3AGY6ha0qKFfkp8YjXr5H9wsA7Ou3oR4+cVmRaN2SZSwaXZZoj5+E+3HzBmg8QvuA+0JZxvenqjlWEr+hi4IL6kTnxN3H9vETVH/y+xj98KFzwnJwdDqDecMFLU/nIWZxw30u12iHGtmsRv7wFPMvcCHa+Nv/xyu3DqhK3zmCLQvYXzzyejHqrTfx4ZePcPtb74cx2JuATmeB18RtR8ykBBoDneewB7uhX++GAPVl9vJNFgBXfzoQi/wcHwOQVqNu2UerPRZaMWczXtrdvgU7WwD7ToDlJz+DKlhS0F+rYF5NtTvxYj72gwdQR4ewHzAvsV9m3r0NenLCtQqC2rt9iPoeVyvmP7TAoatcfPAI6995A2Qs9GN+mOnOLagHD0HjMcx0CrXr9rTHXOWKvR3QE35wpZRaHR2iuheqTvO3W/bz0WPQa0d8jtvf0rDkvfIR1ySYn/FkUf/2PeSPXcR/Ouf992SE+s4Osie8t3/w1Ru4968EagxWd3kcVGtRPJqD3nsQtheybbAW9Pod0LHLRNw6AIjQ7A+R/cSd7Spw69u7yB9N+doA6t+6i/zHBPPkI9+H1Rv7yKcV1HyFZn/k4cv3/3gHd747gs0IJpcYD5P1TH46xer2GOV/ugnPWNSfu4ezz5Q4/JbjT90Zo763Dz2t0O4WyB+EzInZGWH55hiT/+XJSe5jNptj/tdTNP/AihfUWqz3NPZ+vIf3/5Qnhv13dlCPmQ399PM8AbQHDcb751g+mODW9+7ita9xOWv17mtQj45TeUqlMfviXSxvahx924I+5Gfkwy8f4ft/87f4o8d/AQFnnr2V4eBHu6h2NMgCjWPrmt8j5Avg4J09nHw2TLDVP24Jzl9gL1+AE3gu2ZAEDkzKTwzxyoKyzAf+APigI2VZUkgUpxXF1Gi0Ue9BRcHtk+IVifhQ1Tx5WYvWvbnUZMIrB0U+UAnwSoiKIgTtpA+ufRWlMs1y6YNifp/r/PRwY1nduON6fy+kToWvQms/UQIA3TyAPZ3yZCyEudbArivmx+hICVhjoYZlWh4P3rfLW9JTDLoAXZI6XS65fsKVsVM58HwPVOThDXxzHzidsr+SIWhbJvOpKyAv/EoGxvKkvzNB+8tH3h8p4KNOMBFae7qAuA/tbAb7h7+L7N1OkHE2A26xUhgtV76IzadOBznr5LYt1Mkc1W9ymjX/75/ydWMaBiLQZAzKc5iTUx+jyO7ewexL97DzvfshDlEOYOfLgLmQezEouJBsvkhU5P7j4Tdxtn7YBzifiz2jHIDAigGEG3qBsvc2WPBmg5/s5O6p9Tf+YHAhBX1U/Ob77ti/+e/mWim7C68hzGaSDRJ5ghhqHUOuu/cyPu8ZjOK+bTNj0m1R12zww1obMYC5NvXTPuvaj/trDX4V4cg+wNlbb71dyV7dlcVl25POUhl5DtgqydtvU9ZCvCwHgoiuLFklTVvkCaWeXEMQlrRaB8yF28oAABzCkLSGtWsQOYLWuOJTlsudQiUqCq9nAQBYr/m8ugkcBpJmc7wN3W1IrMMBoVPIM1A58AHVdn8CdToN+iXSb2NDmrIzhrxdMN5PAKxH0kF1Jv6730kU5QXBORzCqoqLr6JtSHtzB3rtcCSyDM+YgNialvt2FrgrqBzAjspACFwUrINS12EbI1bkoJ2JHz+vlzJf4PxOiZ1HQT/FDpiFrL3JcRhN5FnI61suwDnQaAcK+bxBsW6wuMfjvv+DzNMmenpCaxmZORyAFksfo7F7E5y9lWHnfwb+uTP7EyhrA6Gwe57NTgmqWygA5kYkjHx89fXCqzNZbGAatuATYuswUMMR4G7TLU3Oc3nxeHIQcpbk1NU65UoAQHUdFMqbhjVEwV8ouzxPMi/WcWRCAEoJAY5JtE495qCqUsZv8dOayN+UsHdD63R5HmDkHbUuiWXoj6bMW2kt4LIrEL3YLu5CcCnCmQn4qtSLQFxxzMJzUlobFNBJeZ5Kv/UAoI+nAaKdlNZr/my0FRH+UQJgvAar9Js5T5OxkfjLBhmSweiDBew8jAOtmb9THzsawfnSf2lzd60sz2BzzeS6ZzNM3h+H9o3lcvJ40p3NmeA4xnqcznDwo12+tjtXWctxFYkBue2ermomOZ4vku3EJ6F1+uLZsyA7gVBQdNleukNLb12xkP+Sig8CH49AUlAdiLe0JbolNkr5bSuA6vq74VoHUYkA/rmoX7Heqve7y0ch7Wr3RSvywDrli5eUhyF7IFDEz5GA1wRmHEPAYx6HWMfVw+ajvmkFsooBRVqDbOSXlvuYrsREfzQUxjlof6z7qRTDugFeCcSpdkF3ip8RI1k7zL3wMayD7sdtZ1nQHhWlsCKDKZiHgvIc7dDpovoCsw6/SZZxe/F9zDNUOxpjrSARBZtnDIfP0tSpl13Iso5cBK5sr85k8RJb+jbehtg0EOGeT9WehvaLUZBd4uTrtnWFa0QX2/x7xOMAANBBr3VrkPMZjbpNXLaq7Z4rAc2uXxGt4ZWv/Su0V3eyuCxm0S3Cij93adudFchVI/tdsJDgL3yJcnSuvEW7LEz+WPymlvoWFb3pIz/jgrKkFN5u+q7TvgljV8xriczVRcQrJcNtxUVQycqiM16idhaK3qSgzPmqot83znGrNrm+fOHzkNL2okzW8upDd1Yy1nAq3KuoIdwfP77xvaJQ3Bf7QiwglMerMdem6IySEx0iY/0xU7AQkKp51SEs3AUFtfl0wtP++n6MlWIcRaeokVR0D6PYjY188XYNCoY+G9Jbb71dyV7dlcVllihtsxYmjEnYsTdMyq+71ZZbStSpKBi0FGVDKOJ/IL0IoCwgZBX8ucoTqMgbAQBs7bIheVTpKoujDr8E1Dy8aaVfQtGgiD/XjXEMBhsl6pQ5Pgt33ExKqJzLxCkuzW6a7SyPMr669u3JGBEtE/9o4NTL5dqDAWi+4DHIw+cseCFGee4DnM1uiXxahP4BADn9V5cZSnwaFJxhiCozaTBg1foiD5kjAMjduTMd/ASvClc3Mwxc2Te1BrYsQKs16l3OcOR1C1twNWu9z8faUqEpFYqMUC5KrG5yu6M8Y1+JEio8OxxwCf6xhqUA4Z7fIxxGz47ZKZOSeImVtLucDdFVDbMTMl62S5jzFHt1JwtHrpvAvS/akljjwTCIMwDd/a3UhThmIrkOlWXICiD9oiWs3Nb6eoPkZ8elmFxKqgeFV9J22iGVpHnJlTz7foK/VGo84viAj4671K+kTt2DRudZkGb01ZZRX6LjVLc+mIlI4s9nf7YB2drW9yGuufDkNSIErRQLDvlAMKeJqY2AbELt38mmqKrZGEfZ8tiG/5ZUpTYNZz3Er5yDf2QM2jsH0MKX2bSMGjU20X+1wwHUaITs3IJiGceqhm0NVBUUzmRCUlWU4SCWFERVIzu3/lyfDemaAZBnUIVLfTYG+QLhXsDdmyZSiouOn98dY3KySLeE14h5vJyTRadce+MYEFJkSYo0OqejueFp4ePU2JZ0LJc1a0BU7KxhaG/MPRG1l6S/4tRmkn41CSuT/7xL0/r/I9+ZkSrIF1q4PWV8vfNzmLqGqWqvFOYnBAf3FvhykqqUFGJ3ApPirifTIPm34fOW8v94PKJ2AIR0qPSvrjjN6n5XbQtzvoJtaliXasZiwVD6eGIDoJ/MfKGcN0XAOuO0b5eMeHnOLwfxa7HkL2rTQP28SqQK7WrlitwiWP9iCbNcYnR/7hm0OGaRwa5WyFzq1C6WPoaSy6SSaRRFBlqugdkCk/cWfmy2EgifzVn3NZJ21HmOg3f2/D0E+BlIUqc6pE4nJwvYsyl0XCDXbLnWBfZyThbPgymrA8oSYFUCUtrGlCUsVfJGlOVtpzbEg6ZinEUMmoqXxVUdjkdVmFIjIF9uAPw21JoBRe5t5Dks8pRWj1Z8DWqaUJ3p9CegNS/jxYf1mqPyHVDUht8AzM1dkONf2Di/qrGNEyQGkcUALPL1IgFwBVJ+PGk4BLnJw39uPOa/u+pQMQ/Kik2pwL41HHotD7m+nYzCmJcD7k9Vg0ZluHfWAHnBdHSRX9AamC+wfH2CyZnIIhpOUxqL5pBXAFoRp3UB1Ddd1XGh0Aw1itMCuTFeUnD3nSLR9fC+TkYOlLUIDOEHuzj5bI7RD0Kth7mxwy8NAfxlAZQFpaDbFubAFUESwX549W1IH+DsrbfermQv58qit61G10iDvZL2tP5flela2ujiLy5i535Wu+o966Zyn8Hsx2ynnyyua1LheNmAX0TfHmcf4nO2kf5+HIse4qRitCsv0LV4q7XxxXDZH0FmZhGe4qL+bPhFmz9vG8Pul1BFuAixBGMS9TfbgsAl4oi/og0cyKWEtV35yW2YD2tgCvJZBQI8rkMwFdCafQNgcv6/LRRMQfy71mgLwU5sH0OrWBmegBDszhTaEgm2xmaMtfFZDsmi5RrUuu267ozBFe2F4LMgoscAFgCOP21fPmE7RN/nXwd7kfv8prX21lVOfCEmCwAgou9ba7/0afvxSVrf518Pe1X63Ac4e+uttytZP1n01ltvV7IXabL4u0/bgU/B+j7/etgr0ecXJmbRW2+9vdj2Iq0seuuttxfY+smit956u5L1k0VvvfV2Jesni9566+1K1k8WvfXW25Xs/wFPfz8y3hvV8AAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7c18>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.61717343330383 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 0.1, 'kernel_type': 'size'} is: \n",
+      "[[1.29026979e-05 9.60000000e-07 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [9.60000000e-07 3.58754580e-06 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.29026979e-05 ... 1.29026979e-05\n",
+      "  1.29026979e-05 1.29026979e-05]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.29026979e-05 ... 1.66185888e-02\n",
+      "  1.66852278e-02 1.75928608e-02]\n",
+      " [0.00000000e+00 0.00000000e+00 1.29026979e-05 ... 1.66852278e-02\n",
+      "  1.68477548e-02 1.77115120e-02]\n",
+      " [0.00000000e+00 0.00000000e+00 1.29026979e-05 ... 1.75928608e-02\n",
+      "  1.77115120e-02 1.90544641e-02]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 79.3991768360138 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1.0, 'kernel_type': 'size'} is: \n",
+      "[[2.21682772e+012 9.60000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [9.60000000e+001 3.48898422e+026 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 2.21682772e+012 ... 2.21682772e+012\n",
+      "  2.21682772e+012 2.21682772e+012]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 2.21682772e+012 ... 5.59506848e+202\n",
+      "  1.29639183e+131 1.49801341e+092]\n",
+      " [0.00000000e+000 0.00000000e+000 2.21682772e+012 ... 1.29639183e+131\n",
+      "  1.15004882e+217 2.78311843e+116]\n",
+      " [0.00000000e+000 0.00000000e+000 2.21682772e+012 ... 1.49801341e+092\n",
+      "  2.78311843e+116 6.74779575e+168]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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CWAAIISwAhBAWAEL+B44uIWF7AHb6AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.42908596992493 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 10.0, 'kernel_type': 'size'} is: \n",
+      "[[1.07460112e+121 9.60000000e+009 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [9.60000000e+009 8.88612252e+290 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07460112e+121 ... 1.07460112e+121\n",
+      "  1.07460112e+121 1.07460112e+121]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.07460112e+121 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07460112e+121 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07460112e+121 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 80.75117325782776 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 100.0, 'kernel_type': 'size'} is: \n",
+      "[[1.07374191e+233 9.60000000e+017 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [9.60000000e+017             nan 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374191e+233 ... 1.07374191e+233\n",
+      "  1.07374191e+233 1.07374191e+233]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374191e+233 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374191e+233 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 1.07374191e+233 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 81.19135761260986 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 9.6e+25 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [9.6e+25     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     inf     inf     inf]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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e7r19/Zfw0sDfYPv6L+ltxxdGK359MytZXr81w6b/pkcAAPvf/+8hayIEyaLYwVlMNfk9lXEoPp3pJ1aDFCuujDg/Iyxp4mMsbObBjm0M42CWVfRRrcy4wTOzYasgRBzxWQiC4AoxFoIguCI205CEsUTmJXCvigJlRoMKIMmQkhU3EqtXha2CEHFqMhZE9AGACQB5ADlm7iWiTgD/F8B1AD4AsIOZr9amJkAtetg1eInyrULMGSXVqoQXmTEjuz6eegvBUY9pyO8y82bL8svDAF5l5hsAvGr8LAhCzPFjGnI3gC3G9XMA/gXAQ7V2qo2U7mpzgs9eKCwDWKlQsuJG+vCZsFUQIk6txoIBvExEDOD7zPwMgG5mvmjUXwLQXaMMAHo0asBb+kK1rViV/icvXJAVO1Z2hq2BEHFqNRa3M/N5IloF4CARHbFWMjMbhqQEItoNYDcA9PT0oAMbalRFEAQ/qclYMPN5o7xMRD8GcCuAQSJaw8wXiWgNANu8eMYo5BlA3+4Nh5PX1SQhUjkyVBnEpiwlK27wQDynT0JwVG0siKgZQIKZJ4zrOwH8BYAXAXwOwBNG+U/1UFQFoPGSk1Od5FQlrtS8KONaZtzI/famsFUQIk4tI4tuAD8mItXPD5l5PxG9BWAfEX0ewBkA9lFsBEGIFVUbC2Y+BeA/2NwfBrDVa39OWdS9Zvm+M3MvOJczy3pxZ+ZeJNrbzCjb+bPnkOxZZ0awCioNYP9Nj5iHv9S5jsTqVQX7JdKHz4Da26Bdugxaf43+rDHdoMZl4JlZczNW4tQHgehtZesd30DmuLFS1aan1Jtf04b0xXHQuB5TI7vpGmSOXkB++Cpenvt7X/Xp3/QQsuuWIzU+h1xbAzLnFlbgtLZGTF7XgrZfDel6rdM336XfPOI5jWA1/M49T2JmZQLd/zwIGJHb9o/8L0993PzgU+g8Mo+RGxei4C9bLekLBUGoM5GJZ7Hi+G8WjCxK4lm0/hcA+nZvt/Es+tfcj/0Xv4f+NfcDKNzufWDi2dqUriATAPZf/J4v/fvF9g//VwDASye+FbImQpAsyngW1QTjVYF2zYC77P9OiyCD+9YTCQQsOBEbY+GUztAOFbdSlUHs4Awy1WE9kbSIghOxMRacm/fcRu3NMPdoBDCyqGY/SBTQxsbDVkGIOJExFk7/yWRk4S8yshCckNUQQRBcEZmRhRNeRhSA7LMAvO2zyA8HH7BX9lm4Jwr7LCKzdNrx7ocrJgm6s+EPAOhGw+3SqUp1qNIIWKchfv3hKVl+pRrwi/6u+wAA+4e+H7ImQpB4WTqNhLEozkjWl9yBRIv+TaP2XhQbCGt+DpUfRP1HBWr/z6r6LJblN075O/pvekRyewh1Y1Hss3ByRlrzc/iRF8Su/0Bwyt8h+T2EkBAHpyAIrojuyMIh9oR1FOFHEiG7/oPAKdmPJAMSwkJGFoIguCKyIwunPCHW/BxmfhCjTV3k2/QfBE75OyS/hxAWkTUWjnlCrPk5VF4Q1aYe2PQfBE75OyS/hxAWMg0RBMEVYiwEQXBFZKchTkmFrMl81HU1iYi89B8ETsl+JBmQEBaRNRaUqXzKlJoaS65Vm7rIt+k/CMjh9KdTvSD4RWSNheawn8A6ilDXTm08ybfpPwi0S5UDEzvVC4JfRNZYqLgQ5SJ+J1etLLmuZywJu/6DQJ0OrbZeEPxCHJyCILgiUiOLvqSej+hgfh/6Ujttn1HHzq1pAtV1PUPa2fUfBE5pBCXNoBAWMrIQBMEVkRpZWKFkEgDAmv3hMFrWUHKt2tRFvk3/QUAOW9ad6gXBLyJrLOTUaXX1guAXkTUWcpCsunpB8AvxWQiC4IpIxuDc1r6rZH+FNQanNWI3pVLgXM4s7Z63QwWoVcl1kj3rwGPj5g7J3KkPQCl94GWV9XL2eVfvpKJvW6cN1ujb6cNngJWdev8DF5D77U36M6+9AwBIbbgO+bPnkGhvgzY2bub1yA+PILmi07fAulvv+AbSl/XPnsaMcIVtLWbUbQAY+Ew31r84CBBhfnWr2TZ9aQI8cAE8XxrhPLGhZyEkoPHeXmOJ9m96CAAw19OB9OgsEuMz0NoWdtcObGvHml8UTtM4QZhbnkLbkVFkVzUj/eYRsy53yyZMrmtAx8Hjuj6X/6cnfRSbf/Iomp4zRrc5xnxzAm2npnHmLv0UdMcRRraVAACjN+n/37TWHDq6JjB2sgOr3gJW7Na38Wv3NQODQyUy7CJ5/9affhtvP/Y0tvzxn5j3Rm5Mo/PIPLKtuv8u36DLnVxLeP/xL5f04SUGZyRHFnHN6iUIi5lIjCx6e3u5450NgEWX4pFBf/cXAAD5oSH3WdRv/hr2H34c/Td/Tb8xdNWs2z/4tzVqXV4mAOw//Lgv/fvF1ju+AQB49bX/FrImQpAsiujexfCs91UAGpssKLUq+qhWZtxQUw9BKEckpyGCIESP+Iwsst7SFwIAG8uuZllFH9XKjBvKmSkI5ZCRhSAIrojNyIIyGQAAz7nfTUnNzYVlXqu/YmVkxg2VmFgQyhEfY6GiVZWJb2EHL28tKCmADOdKVtyYXyMRuITKxMZY8PSM5zY0OlFQalX0Ua3MuKE2XAlCOcRnIQiCK2IzssC1a/Xy8JHKz1kY+/j6grL16Fjd1SonM24MfKY7bBWEiBMfY3HmvOcm7W8MFJTauP9TBCUrbqx/cVC/+Ga4egjRJT7GQvAXorA1ECJObIyFrIb4i/X0qCDYIQ5OQRBcIcZCEARXxGYaIvss/CV9KZ56C8ERGWORaGkpm30MqC4gjsr3ocp6BvR1khk3JB+J4ERkjIUj7P1chzIOppGooo9qZcYNu1B4gmBFfBaCILhCjIUgCK4QYyEIgiscjQUR7SWiy0R02HKvk4gOEtFxo+ww7hMRfYeIThDRr4joY24VkYjeghBt3IwsngXQX3TvYQCvMvMNAF41fgaA7QBuMP7tBvB0fdTUV0sSLd4CtKTWdJtlak232YfXfrzKVHLjRGJDj57bQxDK4LgawsyvE9F1RbfvBrDFuH4OwL8AeMi4/wPW8wu8QUTLiWgNM1+sVdFq8o2qg2OqDCJnaRCH1XxBJQAShDJU67PothiASwDUV+laANZjl+eMe4IgxJya91kwMxOR50xFRLQb+lQFPT096MCHKz+/rEGXN+8+QneirbWg9H+XxYKs2GGkFBSEclQ7shgkojUAYJSXjfvnAVijv6wz7pXAzM8wcy8z93Z1dVWphiAIQeEqfaHhs/gJM99s/PwtAMPM/AQRPQygk5m/SkSfBvBFAHcBuA3Ad5j5Vqf+ixMj9yV3ILlyJQA9XSFgk87QkibQTFNopDgEak9PqPosluU3TmkEt97xDUkxKNSNuqYvJKLnoTszVxLROQCPAXgCwD4i+jyAMwB2GI//DLqhOAFgGsAfedbeQBt3CCB7YbDk2rGNF2z6D4LM8cpnNJzqBcEv3KyG3FumaqvNswzg/lqVEgQhekT2IJlTUiFrMh8ziZDRpi7ybfoPAqdkP5IMSAgL2e4tCIIrojuycIi5aY11acbYVG3qgF3/QeCUGUwyhwlhEVlj4RQZyxqRSl1XE03LS/9B4JQZTDKHCWERXWORrbz5iqemSq6d2niSb9N/END4ZE31guAX4rMQBMEVkR1ZJJa3AwDyg5ftH1i7uuRatakLNv0HQXbTNTXVC4JfRNZYaKMOeUnPXyq5dmzjBZv+gyBz1GFTlkO9IPhFNI0FJRz9D3nL3F1d19NnYdd/EOSHr9ZULwh+4epsiN/09vZyxzsbAIsuxWdBtrXvAgBoExMldeXYvvYBvHT+u9i+9gG97eSCo/LA2N5a1S4rEwBeOv9dX/r3i/5NDwEA9h/9y5A1EYLEy9kQcXAKguCKaE5DbEg0NwFAxURExWhdywvKRACjKCUrbsz1dIStghBxYmMseM67PyIxOVtQVtNHtTLjRno0nnoLwREfY5GrImPWzGxBWVUf1cqMGYlx//PACvEmNsaCUlWo2risoKQAAvaaMmOG1la/czXC4kQcnIIguEKMhSAIrojNNIR7jC3XV91vSrp66+qCsv19/4faSlbcGNhWx63ywqIkNsaCLg17btN+eLSgpCH/E+koWXFjzS/i6ZgVgkOmIYIguEKMhSAIrhBjIQiCK+LjsyDy3ihRWFbVR7UyYwYnAvhshFgTG2OBBu9h/vMtDQVlYqx+qQKcZMaNueXx+VMQwiE2fyF81Xtgm/TAcEHJY/4Hu1Wy4kbbkXiu4gjBEQljceztUxjnQ+hL3FNSp+JYmGH+PaQo1NpbCkqqY3AcJ5lxI7squERKQjyJhLHYeMsG0ygUo4LU9KV2eu6Xj58uKLV5/w+SKVlxI/3mkbBVECJOTN1xgiAEjRgLQRBcEYlpiBuSKzoBAPmhIddtEh+6tqDEkP/Bbk1ZMSN3y6awVRAiTmSMhTY1XbGeWvSwenBvKzDf1VxQZmb8j2ehZMWNyXXxXPIVgiMyxsKJ/LmLntukfnmioMwHEPxGyYobHQePh62CEHHEZyEIgisikTekjTr5Ntpq5gPpS+5AosXYI2FE8y7OFWLNz6Hyg1iXX2vNC6L6LJblN075O/o3PSS5PYS64SVvSGSnIeYmrDKh/7UVy0uuzTZ1wK7/IMiuqyzLqV4Q/CKyxgLZ+YrVienZ0muHNl6w7T8AUuOV/SpO9YLgF9E1Fpl0xWqtaVnptUMbL9j2HwC5tsqrEk71guAXkTUWPF05j0VieLTk2qmNF+z6D4LMucqynOoFwS9kNUQQBFeIsRAEwRWRnYY4ZiCzZv5SGceqyVrmof8gcMoMJpnDhLCIrrFoM+JClMkTMr+6veTabFMH7PoPgsnrKr+DU70g+EWkjEVfcgcA4GB+X9n4Ftvad+HA2F6kTw+a99S1NlI/559d/0HQ9qvKh1+c6gXBL8RnIQiCKyI1srAiOzirqxcEv5CRhSAIrojUyOJgfh8A3S9RLr6FOiBmjXWprvND9Yusbdd/EDjFwpRYmUJYROLUaW9vL3e8swGw6FJ8yvSO7fpJy8yBQyV15di05ykc3fNlbNrzFABg9ZsL0b1fe+mhWtUuKxMAju75si/9+8XmnzwKAHj3974esiZCkCyKU6fFNB3RVyS8xOde/8oUsMcoAaTP+59FXcnCHt9F1ZWm5wxfyO+Fq4cQXcRnIQiCK2IzskBe89yEclpBWU0f1cqMG4lc+NNRIdrEx1ikvauab0oXlKkq+qhWZtyYb5ZBplAZx78QItpLRJeJ6LDl3h4iOk9E7xr/7rLUPUJEJ4joKBFtq5eiPDEJnpj01CZzYcwsMxfGzD689uNVppIbJ9pOTaPtVOUI68LSxs1X7bMA/geAHxTdf4qZn7TeIKKPANgJ4KMArgHwChFtZOZ8rYpq167WL664Xx4dvm1VQdnxa/8PhClZcePMXfFMYSAEh+PIgplfB+B2GeFuAC8w8xwznwZwAsCtNegnCEJEqGUS/0Ui+kMAhwD8GTNfBbAWwBuWZ84Z92omOaJPHbwsnbYOzBWUqg8/UbLiRscRcXAKlanWq/U0gA8B2AzgIoC/8toBEe0mokNEdGjIRUpCTqfAHh2UucakWeYak2YfXvvxKlPJjRPZVkK2lcJWQ4gwVRkLZh5k5jwzawD+DgtTjfMA1lseXWfcs+vjGWbuZeberq6uatQQBCFAqvqKJaI1zKzyCf4+ALVS8iKAHxLRt6E7OG8A8G81awkgt0IP+uLlu2+iJ1VQZkb9DxyjZMWN0ZtkGiJUxvEvm4ieB7AFwEoiOgfgMQBbiGgzAAbwAYD7AICZ3yOifQB+Dd29cH89VkIEQQgfR2PBzPfa3P7fFZ5/HMDjtShl229KnzF5GVnkGqmgVH34iZIVN7RWL65jYSkSmzFzrkl3GmY8tMm2FZaqDz9RsuJGR5d9kCFBUMTGWGTGss4PFdF0iQvKavqoVmbcGDvZEbYKQsSJhLE49vYpjPMh9CXuKalTgXtTKzsBeNtn0XFsrqBMDfq/DVvJihur3gpbAyHqRMJYbLxlQ9lo3ioy1n/8zLcAAMtOn3Hd75n+hoLymp9316KmJ5lxY8Vu95+rsDSRo4aCILgiEiMLNzS99j4e6X38AAADa0lEQVQAwEu0iI3fPQN81SgBaOP+O/GULHzVd1F1RbvPOEj2frh6CNElNsaCZ7xnSNeujhaUnPXfwalkxY5BSV4kVEamIYIguCIyxqJc6H9BEKJBZIyFIAjRRoyFIAiuiESSoTbq5Ntoq5k8qC+5A6medQCA3JkBAKVJhz51u54M55WfP4pP3f51vPLzR7H9+q+Y9S+d/nZNOqk+i2X5ze/co0cq/H8/erBsfbk6QfDKokgyxA2VT4Fk2zMl105tvGDXfxDMrKw82HOqFwS/iKSxSLS0gC9ervhM87sDJddObbxg138QdP/zYE31guAXkTQWgPO+Cm1svOS6mr0YXvoPBKfkznVM/iwIXpAxrSAIroiEg9NNFvX+Gx8GAOSPnXSdRf2Tn/4mXv/pV/HJT38TANB0ciGjwf4jT9SqdlmZAPD6T+O13/u3/lR3CL/z9FccnhQWE4vCwVnM4BY9ec/KYyddt5l94GpBOfGP/icAUrLixtuPPW1cibEQ7ImNsVj9U/2Alpd4Fsv/vAHoN0oAyUv+H8NWstDvu6i6suWP/wQA8PpPQlZEiCzisxAEwRViLARBcEVspiG8vFW/sE1ZZM9UT0tB2TrrfwRrJStujNyYDlsFIeLExljQqPfANc1nJwvKavqoVmbc6DwyH7YKQsSJjbFAFflJ843pgjLpY47TYplxI9sav/ysQrCIz0IQBFfEZ2SR8G7XtEyyoKymj2plxo18QzwzqQnBISMLQRBcEZuRhdba6LnNTFe6oMwMe++jWplxY3KtjCyEykTibIhd8JvkRzYCAPLvHQVQelbkE5/Vg8T86z88iE989kn86z88iP7fWAhOs//fv16TTqrPYll+c/ODTwEADj/55bL15eoEwSuL4myI0zKndYnSj6VRu/6DwGkJU5Y4hbCIrLFw2oRl3fykrs02dcCu/yBw2hwlm6eEsBAHpyAIrojsyMIRKnMdl/4FIWZE1lhwqvKgJ5+mkmunNl6w6z8I8g5J2J3qBcEvIrEaQkRDAKYAXAlbl4BZCXnnpUCU3/laZu5y82AkjAUAENEht0s4iwV556XBYnlncXAKguAKMRaCILgiSsbimbAVCAF556XBonjnyPgsBEGINlEaWQiCEGHEWAiC4AoxFoIguEKMhSAIrhBjIQiCK/4/Qv/7KPpWQKsAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8908>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 81.78144335746765 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 10000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 9.6e+33 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [9.6e+33     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     inf     inf     inf]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 82.05513429641724 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 100000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 9.6e+41 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [9.6e+41     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     inf     inf     inf]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483efd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 81.75092363357544 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 9.6e+49 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [9.6e+49     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 83.0473530292511 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 10000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 9.6e+57 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [9.6e+57     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483efd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 82.30248141288757 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 100000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 9.6e+65 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [9.6e+65     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acda90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 82.40114164352417 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 9.6e+73 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [9.6e+73     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 82.63600897789001 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 10000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[    inf 9.6e+81 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [9.6e+81     nan 0.0e+00 ... 0.0e+00 0.0e+00 0.0e+00]\n",
+      " [0.0e+00 0.0e+00     inf ...     nan     nan     nan]\n",
+      " ...\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]\n",
+      " [0.0e+00 0.0e+00     nan ...     nan     nan     nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.69701743125916 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-10, 'kernel_type': 'branching'} is: \n",
+      "[[1.28000001e+03 9.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [9.60000000e+01 3.56000002e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000001e+03 ... 1.28000001e+03\n",
+      "  1.28000001e+03 1.28000001e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000001e+03 ... 1.64656048e+06\n",
+      "  1.65292050e+06 1.74620067e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000001e+03 ... 1.65292050e+06\n",
+      "  1.66825659e+06 1.75709081e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000001e+03 ... 1.74620067e+06\n",
+      "  1.75709081e+06 1.88780565e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7c18>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.74796509742737 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-09, 'kernel_type': 'branching'} is: \n",
+      "[[1.28000011e+03 9.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [9.60000000e+01 3.56000016e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000011e+03 ... 1.28000011e+03\n",
+      "  1.28000011e+03 1.28000011e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000011e+03 ... 1.64656476e+06\n",
+      "  1.65292505e+06 1.74620672e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000011e+03 ... 1.65292505e+06\n",
+      "  1.66826188e+06 1.75709806e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000011e+03 ... 1.74620672e+06\n",
+      "  1.75709806e+06 1.88782053e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483ea20>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.58703923225403 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-08, 'kernel_type': 'branching'} is: \n",
+      "[[1.28000109e+03 9.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [9.60000000e+01 3.56000164e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000109e+03 ... 1.28000109e+03\n",
+      "  1.28000109e+03 1.28000109e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000109e+03 ... 1.64660756e+06\n",
+      "  1.65297049e+06 1.74626720e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000109e+03 ... 1.65297049e+06\n",
+      "  1.66831480e+06 1.75717062e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28000109e+03 ... 1.74626720e+06\n",
+      "  1.75717062e+06 1.88796936e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.64756798744202 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-07, 'kernel_type': 'branching'} is: \n",
+      "[[1.28001088e+03 9.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [9.60000000e+01 3.56001637e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28001088e+03 ... 1.28001088e+03\n",
+      "  1.28001088e+03 1.28001088e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28001088e+03 ... 1.64703572e+06\n",
+      "  1.65342499e+06 1.74687209e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28001088e+03 ... 1.65342499e+06\n",
+      "  1.66884411e+06 1.75789639e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28001088e+03 ... 1.74687209e+06\n",
+      "  1.75789639e+06 1.88945819e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.15823364257812 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-06, 'kernel_type': 'branching'} is: \n",
+      "[[1.28010880e+03 9.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [9.60000000e+01 3.56016369e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28010880e+03 ... 1.28010880e+03\n",
+      "  1.28010880e+03 1.28010880e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28010880e+03 ... 1.65132641e+06\n",
+      "  1.65797887e+06 1.75292943e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28010880e+03 ... 1.65797887e+06\n",
+      "  1.67415010e+06 1.76517142e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28010880e+03 ... 1.75292943e+06\n",
+      "  1.76517142e+06 1.90440964e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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qCcwB2nWLBU5OUbJIqK7dNRzh7TSqQQ/ugSS3Rc5rqJMbIosFM0cUKQBaDgjOQQYZ5JLl9iM4B7l9cpUh3Ys4P8+jV2mP33EC9mxP+5ykpTY6/eb5M2cA1XLLUg5XVRq67fNZSB/Z9u037D97TRGc28hZKepn3TR1HtV1N9Yu7WWIO52inrQx8inqEjeXtPeebUhC8SaqVel+lFdNZw8bkID6GiCArGg0Vs62fBvijpu9XdiT0+T60EbfvGlfSJ6ODsTthCSsyblVFSj8cvRjZxuysxMyPdN5MSFrU+MSaDR2SElFCyD903QS22IbzPiQoj6qw9/Vm4/AR0fuVL8N4aaB2d11x87YhvB8AQop6s+K/hgzmbi5UL4RGo9h3nkLrUpRl99icRsyGYOPT9JtyPHmm4vBshhke7lNYDEtl2FZbNOW5gS5TstCHdvKspDr1bFtLIvBZzHIIJvKVbJrXYcIg9c55e5tQy7yVrsuwNVV93EVUmL76pPbOrbz6LUNJL2E9yjNWx88Ozknv+aMudfbZRHbblcY+Sx8zBkyWBaDDDLIRnL3LIuLvNXWQZG9Ay7BI6zbz/ZxcPrzOxBgIMbx4Zxeazk45XrxtK9zcKoxBCCQ70OuF3akDs4i5+CcTCJmIGfKEgfn/h7s8Ym7bh0Hp0KQFjk4FSemPqbbofHYnePbCOeUODj3dmBn8+jcC184TkzBRYTbUeLgVDgLzhi0aFQ7Dkwg3sfFAvX776W1O4jAyxXM/l68D+LgnAgHZwUyBrxagWdzmEdvuCl8/HG3xgkAs7MDVJVzLAsH5717oPffAX/4OHZd12WmLD8uXi4zB+fm5Rfv3mJxWdIx1xRX4UbXrufgTLgjg9jkB5g87H0cnD05GMX2OW1f61lKJS+1HyIPSV9IwE52Nu/n4Oxx7On+w9hsE/QI32fFipw+6Tmk21D929k88mpmDkS2DMpTvUscnDryojk4G+v1slEv6ff4JE199yn8gVdTc2QGABi5vtkVGQrRFB0J0qrJwq/nZr4APX+Z3DNu24gYVYspN00sMqT0Ybs5XcDru1iU5CwPdn5u6fOZ1ykotSZtzX8kZ5Hu9O6p+4h5N9ybl2pKaC4LwP0YsxyHos69fa3Lucj21Wu5IJA+1BmRr7s8Lop5jdBA4pvv66XfzBJNF2j1wCkC49A322DFJYQ0hUQ3Te679uWQ1ThxC9I8ZSGHzIHiywBAgootkjpvJsNicVOSgGV0zsMtoqArMFMln/sWh5xQuK+9c+tVyh/Rf+ocD5s+rKWQ5QWd0iRWwkYnS24IRVg5k9o2KItgE8Z5Y7p5IFckg4NzkEEG2UheX8uiJ5Gsk3DVd22fgzOcsz7Rq1NkKDjMdEJX221Hkr/cxj0dw2UUGapHyT7fqZ1mnZrdXe8UrMoOzlJGqEZrnrPIUOIEXVNkKHVwGjdVre06LUd16oimiA4N1IFy7roiQw8fAC8PYpdVBSxXmxUZsm4rYd546M598rRrXJJxRZbzIkM7U5i334T9+IkreQAAoxFotYqWijRRKjJkzFYIzgstFkT0bQBHcBujhpm/QkSPAPxfAL4A4NsAfoyZX1yknyuRvmxL+UGuXSzUQ29dxihni4VU9NYPDlWVg/sa47I2pa9CNESiAiFVWmeo+uhE/OHbtH3IqW0gHY5RGL1ntsk4AIAUAWxwXlZVjEoAoU5GnsGYFPlJJoOSuiMyblfzw3aPNRTrp4xHcf8v54zHYWHSiyPd2wdJNEovGFUFzGauWpfMGRkXDZmMQTLnZFx/rb832mdZGdB0EpyDMs/crMCPHoAWUv/VupogQKgFgtksVlOTBaSugFENmi8BItg3Hdybnj0P8Pykbsh0AozGoFUTM3V3d7H87BsYPX+hzpuCT2fxt1VJFGYCalvw6SxmuALAbPPF4jK2IX+Cmb/MzF/xf/8UgK8z85cAfN3/fbtlLSy34Fu4iEgI7Zr2mZcpRNQNS2bfr73euGJDZ7VzUbnKtrcSov7fTMcfFM+90G+DyPlD5N8lyoVyQ7xl8RVmfqqO/Q6AH2Hmx0T0PoB/zsw/sK6dW5EbUkgQW4sWPYuNqidLMCFRUc62zvanVCs1b+8s8pu+RLQ+Pfv6zSj3hX6erdoaCM9CiU5Otjslyju9LZLvdCRCb/Hk7ax0SRLJJKFPyigAYbsSKOxUdISqym0tNHHNGgdjgm1Rv5Pq/v0EqyHbHSPWh98CQRPi6EiYSjqzR0fdsDnFerOh7isAGo1hHj6APTyMVpuUj8idvpUJTODaGvvG6h/j0D67lqxTBvBrRMQA/k9m/lkA7zKzoEQ+BvDuBfu4GskeEreViFmMax3RG5DfnFW+ELqvFh3QVCCG6fA5tumCo8agQV+A33J43TYmvxnVvaAsd5vhyW8syNhILAMTyxd2Fpue8oWGwraoF5Q1qt05HOeL6trV8PTZoKGbnR1v8hciHKvGPTDLSCtHde22NPrYGaAs7oCyWrf9yWqdAm67BgCYLzqgLKprgAjctMB8DrrvtyzHJwAK25Dx2G09T1qEbed0Ajx64Mhv5Hc8HiU+El0Ymdq2C8pqr8lnAeCPM/NHRPQOgH9KRP+f/pKZmeQXlgkRfQ3A1wBgit0LqjHIIINctVxaijoR/XUAxwD+Ml6Hbcgm7eWck+tO95ZNx1QvgbM22R7JudvKBmnV0SIqVCTrY7UutVXi7Owjo9G6KRM735IE61BXJEuKTad6OstFnJPcP3+d6Fn82+zuBhg4EK3K3PeQbNvESiICt9EBHeDkOd+nzGvGIVrt7znkqkabqi2X1qFUof032l+7evIbItoDYJj5yH/+UwD+FwC/AuDHAfy0//8fnrePNZ2nN+2sB6gkJu61AQQPu2wH7FyFLfO+NInNaukIY7JiL8Fjn5X1C1GP2SzZepj9PcAyWg/7DWXpaJSGWZvGhTe1mazCjDoaYmdzv51ZxX5VmT14xmcZBwCY/X1g5atiiee/Mr4yuA/ZPXwA+/IA1LaBaFaIZ+18obZyitR2MolbLDGDidLoD5TfQR7wyQS8WLg58pyWNB4HWDONx5AXnnlwH3x45NqS7RFzzIkY1bAnM3+cYHZ3QXu7aJ8+V/ctRkOSLYuPhsj1Ms/29BT44udRfRAJaDAegU9nMI98OPR0HhcHH4ngsbuHaFrQ4THsZ952Y/idb4U8lvAEk4HZ2wdGY9iXByHcXL39JpY/+DmM/90fxG3IdAo+OXERGRUap8kYaJpONISebr4EXGQb8i6AX/ae5xrA32fmf0xE/xLALxHRTwD4AwA/doE+yrJJ+vC5m76cdmKD6UpePsX/oDmD81oOsOVOm9g8AWgrsTbOQa57niSWH7NdiHVx7IIJqLYbg+ilX4PFXB62Ee0cnJWcMHCxzLdVPpYz7lOfUJv9ZqxvN3FUqtAx4L43Faj1ztcc4r4hjJ4kHyfk22TYm9DGxX/Xt58paxsobg48Oo8oUzehiZfvrmK+1BgDYMbrEBOs2s651y6bhCQ1w7hObirl3Vx0DOtYoHqiQkJfGKI3Ss9L2XJu8rc+prJy0+8zwNomdIUiW1ja21RRH+DegwwyyEZy9+He533bZ2+lbuhUYNU9b4Uz4N5U151MUh06FTJdwL15Q0xe9vV17RxfQk6L+LbuOEMvE+6d8VkEqLckPiHyRiS4AesqepcwGiAG1Rnc27e3FdxbkJF17bcQ7MKh4rPYmbrQpg6dAs6fwp5IV+bKGphpnfBZBAfklnDv+r13Uz4Lz9PRIey11oU7/b0STATP5jBvv+nUevLUOUeJAFZh4fG0C/fe3QV95l3wdxVhr3CEVFViaQmiOIF7A6DT6wud3l0ppR9DOeWACOwpmbsaV1EwEUt76cA1IH83ca+cg5zcQmHiNijzdhfNUtt2YOdBzz7qt+x4wssAPx+cPiD2+CQ+TIU8EsFeJMXWVdk8buF8CrpvlvnP9FGOY1aLmFIw/G3bkzCHQQfmwAXBQFyU4XkktBO6NH+xm2RLqs9rn7/oYDK4bWE1R4VvREPLA06kbWE/fZaMEcYkc2rn886Ly87mMB99nHKk8MJfl5UpnMkgOLnHrxefxUX2mXJ9H49FB/RUgH73IjgLKcYU04lzBCdoBDI2efuW+RDYefjOsniAcyE4g9UiekmIsYSUlHECkFRwtuwAU3J9GF+cjzAHqLq+mHUIzjx0m6E4XV6Jn7OwGHJqbWndpEpXPn9bIjjNZAKr75FPOw9vcK2LWGIhtGvBAGhn6k49OnYWl9ULk7eqOgjOGrS3B1YIzgBYU7q4oVERwYnV5pDwu79YnFd6vcU5zqFnMWIufxYpvqFy4hFlLeS1Q7M3dtp3AZ8genSIYDn9v3SN/rNIi5fqnRDK6KiD1r+kc95HaQ5z/RPrw3ZO6ejF1m17mNJjXqhOozusddPzV+AVSZzd6nt7elok5CmR3uSYD8FTsNAU5tgK/7lE88jLJezhYZd9rUQYpBZhLhEcbSC3f7HYxnK4pCiItMU5DVsfSOes3JDkuLYm+nNDGD25Ibr9q8gNSX6khcgC4v43tTiiHyVsr0T6ckMI21kW0r+yfko5K7oPqgBdF1Vvh4IPSVHdncuyCCn7CN9xiyw3pO7khoRf13IVfBn2UPRLF8miZVGPYO7twx4cxXO3zA3ZxrIYoiGDDDLIRnL7LYvrkj4z+Kzz889nHeuxoZMELyA1jTdpu9S+PnfDbUjROsvaFIIerWYiJf9PwZlZ1nPdNsSdkzoa1alzvRXowrbZpseDwzm5l9tvQ9qjo+L8JvrIZRnSVyy/9mDVOTfZchT4VXi1RPvseefckrBqngtzuom8votFH9Y/yQ3pZpMWr1+3DUmO9Ts4haEqcXBa78zM95hXnaIe+spSpOUS7+DcOEVdm/eqvSSqs2WKumuei3qFUK+I2jok4VAfNblwivqD+xFGDoStQIDzl1LUtdN1uQxlA+zBYeLLSOY/34ZMJjD377sUddGRKM6B6CLHBwfnJUkperGu7qRmrsrrTUL9sBI/B1J2rFCsmP1NraI3Xx6k/GHP28/GkKeoh6Sm86Soh98qJXt7Go9dvD4hWKkcs3RTsG4AUEVpexDfR3ospKiLT0LO0fcisG6le3OaTsCz7psysHwZAlaqnVGd0M8lhZF12FrPrYQdZT6XFjSdgiSPxNoQ9gx5M4uFYvnyuTvGLVS8WrnfwtRFQ3BwiNyhDLag8Y5n/IqOUxqPgYf3QEfRZxHybgp1Qwhw5QNuKEX97konGiJvsw3iztl5vZiKQh8x+YuT65J6H6KP1jPb9mxSl0Trca66IWK+t22SV2EXCwVD73r8S6L17dQIASJ1oE1xJak+3WPamWpn1J1HIPJjZJElXjXJNoTbNqlJkkai2sTy03wk9ui4gE/h6PTUVqRP0oMxYKKYgHd41JmnpD3BiiidpG6I1QlvYj3kGa9NE15qOsVjG5zF4OAcZJBBNpLX17LI5SxH4Hnb6xzriXGXkoHO1W+Pf2Ob64sYlHhcVwnrHU+n3ZJDOE//78mw7dwbZfloh2WhmhrgrZaS1Zib+0D0u3BXH4dmjToI2peXq3L2a9jOtYBwQOk2BY/Rto5NKxljQS+kGApuAVblDONY1biCb8VXJJPCSvGKYn8lGSyLV1mC03DLBeM6hairXw7sugn9ycR/JZ30edctWq9tLqsupuvra1n0EdXqaMi6a89wcIb29JtCk+ZIkpfvKyehCVGAUjQj9F+Ak2eJZFs7OOuRQljapF05bvZ2XYFeIINSt5ulUudJYyg5OPPEsjZGQyS5Lo+G7OzEMoB6WsRZSSYJXVI9SqIhuYMzvrErPwcGVriDhINz1cA8fBBrlUrCmiLhTQoji4Ozqtx4Vkvne3jgSgG0nz4rWkdmPHIJaotF8FuY6QTmnbfAj1UimY8IBYZzcXT6yI8BHJGRnH8yODjPlvwh8XVD8joafdcm51VVp85IQDmqB1rX9UgKCy1tPL6KVcVZh29zwt7QPsKPS9clARBrk0gdDCCFE/fUDUFD6bmeBVuOm73dWENE8zA0FMh1O1Om9JVxU10Di5QIRyIXYirTdALMZmCmoCtNJ85R2NrkbWn292Bzh51xDznPfCXJMxRQAAAgAElEQVR3jeAcj1LCXl8fRcKe2hFIVeVqb0jYUpjHVo0jzZX7JmOZzUH377mLC3VDYAx4VIPmC6A6Ad5yVdTp5UHHWQq4hRCyEMjc7O1h9dlHqJ+/jOft7qR1QyTyNB77zFfO6oZsTkD0+i4W55XbbNIDaSjwDtYmAZAmdw1yuWIK275NL71kVQYZZJBXVG4/rd51yVlIx9L5cl6x1ukZiV7ij9BtyPG+60v9y/UZHSAgXniFSCy13+e70ccyBKYuZZg42vqyYfPx5GhN1U7CwC1/57R8JQCd6FXAWSRFnTJ27IQ6Uf72SMuEo0LPqddBzjU700g8HKZCoTUVziJsm4Sgx+MsBMBlj4/L2zhJJNMYCjIw9/fRvoh1VvuYxWUryQogBgDfWPyjaysydHellG0JDVU+A+adOzj7CiMnCE7l62DbaQNQvpLgqyg7OFPosd+X6iJGQOBy6PhiVJREs3WB4/m+gUTvgMBUD2Xq4Fw3b8ohmzg45ZBfkAy5TFHtL4Fa+KRP7lLd03jcAV6582NEQ98ngXtrJ6vwQZjJJHqbfNGhvH4qVRWwXIJ2d2OY1Ds4odjIz3JwYo7oRzg5RcdxDb9YVJXz8cg8jGpX4EjS2+W8hsoOzt2dpK4uANAA995A+hKozkokK+ALijH2PiarEncCkDjeUn02RHAK21emS4i767RxjeDLz1e5B7oRVlaDPTkN+m3MjVBixcrxARl8GwDQKmdf3iczNI1AjjmIY0K64Ibjq/gdkLBm2cUitVJapNwXUi7AckLPD0TkQqDr0wuddl4qnAWJk7LHse5Qmis4OgN/bL4APn6SMl95rEm4E2o+jbWwy1VSPe31Yso6r1wwdJrU8TDU+Y1KiftO6DREQJZpG3kV9TNCp6XckNyyEJ5PblR9kGxRykOqEg0A4kKS8z4k/A3akvEmdXHKZD5Un7oSvFgWwrsQJrQaR7CVRBR8icE8KSpwg+Z9K15KvV2g8RhUVbCzWThPoiBU16mVYii243UnIvByherNNwJcO+SGrJqQHMZn5IbwbA7zhqsx0n7ypPjyMdOJ038WE9bM3i7ovbdhPvhuMiZtyejcENQ1DHNSW4YON4+GDA7OQQYZZCMZHJzXLZumil+0/bytbRy3pXP08YQXs6e/TXUt6ajbOouFLOFFLTs+k3PPmpMznKgdJy27WiSdbSSQ+oMy/lDdB7cFUF6nMSo6aM14VE6x13+Hj5ToAmxXvnCwLC5DbjP24izdSnDrm5AO5PsG9FL99WJUtF7XCfUmta0479yoBUv+YYtmXl+fRS4XCZ2uay8/liAx9Rsyi8JsEjo9i/xmXbp9rwWhohZ56NQfd8WESwS95widFiDrrm+bnlMKneYcH1m4Mzap3qjagU3dqnORdMggSf6SczuhU++H6CSdcfRTqHGVQqcAAgdn0cGM6NPRjmqqKtDebkSgiv5tYbGT6I2UHxBpNl8thsVCZNus07POu+qs003b73sD9bV/k1mn0n/fOVeddcqR90OiSJ1zbyrrVNrIIllbZ516zg495k3l9V0sLiuRzN5gIlknBLNhIpk2t/NoyG1IJLPxoQ3Wgqqqdi2JZONRrKIuloVmz/JvajubXU8i2WRy8USy8cgtLjqRzG6+lRp8FoMMMshGcveiIWft5ddJ6W1/GZJHCoCL1TC5TNnQB1PEhVy3lPhG10VFrlKHvurk+emjcX8E4ypEW6fb9qutVS+/Yf/ZxtGQu7cNucgP5qoeYK3TbVkkRDacrxtfKID1fqPr0o2Vb2GDPksh0ysVjQLeVtaVl9hA7t5icVmSVw8fjdO9/WrZ/zbLVvfS24Umk47DjepR2LPa2TxBc5r9fcBa2JOTeL1HeSaxcb93L/JZqPZDH1XlfBeCENUJYGw7vhKztxf35RmfhRyv3niI9oWDJ4c8A2sdGWyBi0HOK/FZsC4UDERfgYxpMnH79KZxFd6lT0/CmyA4H9x3RZvzvivjfBmjUfC1gK2rQj6dhESswAciUO4kymBA00mg/A/38fQU1Q98Efjk09hhVTlU5iPHUcGaz2J3Gs8Z1aDFEnx0DH7/HXfu732rGNGp7u8DdQ17cBQWqOrtt9H84c+i/vffCmjTdXwWbC0wmwO+rioA0LPNl4DXd7HomJgeYpyXLOy5Nq0V1OMJL/SRVEXX161WSLaE4knXRYr72le5DUkoTHvwg9MyjTJ0c0OaTt8EXxNUWK/n88jM7dmqWfeRi3yn8yoAMOLcSb4DN02MEABA08TP8v9qFSDhqV6LhD3bDdOCWwchp6yyODcNsIxuuzB/lotzAx31aOL2jo5PE4ZtVDZGKpA6OCOMvQIZA25a8HwBc3DshlhiSyfjFq7WJjrxfI766XGyqGE+D9D2ZEvn2c0dsZCSUi3dHhkcnIMMMshG8vpaFplw/iZfe3KOZyjE9q3af/vVPWdWTmpA6OSp5PoMkOSPpTF/pYd+Gyo9N60bogv8yHdsjbMu5A3utwlsGWgLOhckGauyWMIxsTByXdvCfKlCTEkbi4WbRz0+AJBMzBw7YdlZIvqYHz9l7N6davFar9NZyn1h3X2QLRa3rQunMrtEM/iwsfFVwpomJoj1MJzHGicK77Jcwhwew+r5mlv/WypgZazthviHuiHnkJtgaV6jQ+B3APqBVdcsASJ89onpfBb0vxDlX9J24b557gkqzVuum7nC+16CZRuTUh/26NnJISk2T8n/of0rksGy8OKgu4plat2C24FtZzBiaa9FCoCSMoBAUtHKkdN4NOAqnOz+yJmuhLBXQ49DeNF0UsZFt03ZvR3ZjFhZKvmpqqITbTxy6e8mJcx17ZcnTuYXSIFcEPJZlbaeWBcqNT6UPawMmAlEHMs+wjlDJUU89Av3tUvXV7VOPchKGKiCVFVsVzN2BaKcCHICADQNaHcHpJO5vL9Ak8zAGBAAmoxjP95nAWYH2waAg6MwJ8nLY1SrlH4/x6MR+P4+cHikiIS9gzsDZVFl1P1Tei03X1xe38Uiz9EgA6BNfgTuvCynwT9gmnmqyJQlD1cG7w03KmfcFlTd3PMxyINhKF+HOg9vyNkQFm4vgc9C5wOcxe5d14E4JZj4wnrtnYe0swOaLxzxjEYDwpPJlEQtQmGBqRSWQfIofP+yxDrmKs+TIWMYjUBtC4YvPiwPyu5ORC/mb2Zrna7aGTgaAZMJSLg5yIT+0vmN0RBqJfIUI1n8YB90qrYRdQ1YC/J8Fjglf4wDuzePanBdgeZLgC3sw33X7iefdt5UZMgtAqOxm3e/INN0itU79zB6ElGfob6qzJVYH5NJXHQ1u/fp65Qbcl6wTvA0ZzkJet/dm6a8YTREtyPXLZdu/2rZvcHke7/PDfroCuUlucpoiKr1SfKGXSkmqPnCvbFWTdzzModoTrTOVATAV8NKdFDRBdGa/diK0RC5XkeOlB+A53N3bVWBKC6O3CwcDNuqxbFt3ZhUqPnMaMhc1XjV0ZCTWUwTJ3KWUdOAhSlruQKtfI1ReajVIoumgTl057YyLrW49kVDsFhg9Pw09Z/MF+7cyqZWVuv9KHloe4iGDDLIIJctd9Oy6EvPzklMSoQn8nUGUqKdHWC5DCSr7UqDlzLTvR6FlGJ7fOwSq45dnFz6Mvt7juJNrfpmdzfuTV+8VG2cwDx84D5/97E7d28H9vjEmeWKKZoXzvSm8Ti8zcQTb/Z2YaR9AO2Ll+68k9OQ1NR60JKAuuR86xOhqjceujc0EOL3NB4lSVr2+z8D8/vfdcf39kJ/fDpLPfNhsg3MXrxeTGWajGFfHiT3Q0BFcl/MwwewLw9gFwsYb8LT/j54sXRkt5NJeDvaL7yH6vFz36fyFdUV+PAINJ2iffLUHasqmDcegu/vgyQpbjSC2d8Dr1ag0SgBeNFkDLq3Dzx9Hu4vADSffIqjP/o+7v0bsaIYPBnDvDxE+33vuTl9fgKMahAzVm+769pJhXZiMDpqMP7uAV780NsAgIf/5DBERlgDzt59G7wzgfngcUyW+5738eGPvonv+eV5+N3Zh/swL47Awizu27D3pqBVC/P8CPbRvXjPfldZOGfI3csNyeW82xBBcKpqXulDuejmS+gFKENU5jBveci1czKwRwMhC1J0oMkEYI58kMJULSFKEdvGNvKtheL4BPxC6NmVkn71WHIkq3r40qzT6MUXdKnmDpWtA6+apLRfmI+CfwKWAxpROzj1NiRwSrJjpAK8s89aBK5M2f7sTMGzuTsm24vWuhCm91kEM9yzXNPuTliwwv33bN65/q584SrqAPc7qb/wedhPn8Vzx2PwbBZfDL4dZgZNp/6cUeTrPJ2BHrqsU/v4Ewcg0xmuvgIdqsohUP08VvfugT//GdCHjxE7N5HzU227wrwul4mD8/85/hUcNJ++orkhuZx3sdP7fR160vu/y8qXUDUzZXF2/oCIgaD8jazStJNoSLj2CsOpAV8hPgjrnJkC1x6Pom8j+BNsXNwyGLr7HOuBBF/NtmMIfiXrMQuu/+ArsQpLIPdN/BnMzima4yGWq82wNUB/WLLJfidep+CH8WnryRi8f4qbxi26Sk94NvaoV5u8BKDbzcck5+n2gG0IsXrlbi4WxQjFdhZG4ugCgkNJv4FjUd58y7NZNMQBmbKwXMil4CTsSDuupgOEW2FUh0VCMx+x9bonob1LjIaoqIcArqgyLnIggKK9PRcVaNuQrwG2wWEZ51ZNma/HEcYGQDNFbRINkbEFBvLcstjfc3pUlYs++HlG07j6HuMxSC1kNHZbC1KM4GujIeNRuF5HQ+yb98NWBoZAoxGIWUVD5r7QcqwzyuORu4ethSFC+5azLOjpczd+ogh464uG7O5g8Zn7mDx9GS3kyQSgGeD7Czkpk3GI8J03GjI4OAcZZJCN5G5aFpeQwryJ6bmxeXoeYQtZq1mb8yLWxq0KWwjwKF67eb2HrURM/JLkiW5WQdRtDGEWk/T0/xlwalPpmNRhO6K2lJYBBQGP/hfvP8q5MhuVGXxeFG+rfUrs4NayLQPctoJTkJebS/KJbjZmD/gxsIGar369qOXUXyb3ZJOEyC3lbi4WWi7LZyE5Ea1df52/dhOcRXBw6mMKZ5HkVTQKswCEHIeQj5HlVhCuL+sU8IAr6ed05in0OIKc5EfPkZtS+1q4VXvw1rp/CoW6Ec5C9Foug88i0evkNGZ4VmphknEqiAFLBmZSW/V8Wafm5VFCx09+25TgLCQ3JNAJ1M5nYS2wWKB6ceSH6O+rNanPqJR1ejrD+InPOpXfTtu6v0nqt5owjxfFWdz+aMg29TQuwlLVl0dwXjKbdfUuiueb7M+YfOY/+P/P8M9cpI7HWTrKKcKAnTle5e9e3ZNGPOBt0xC41q1QUNl9VE7UHh06QDcykcCmk7CX6aGPqb/NdJqkqAsUP/qDOOgW+hfnrndkG88xoSumdRarUt0QX5RZj7tkEYfj2T3bpm7I3bcs1I9po7yO0vXJ3ykeP1Dei2zzAOb1JQrMzvK582OCdyyKhSE5F4Gsdw13xGVKntwmnz1OI+jrLQoyFJ2ekh3aR8/fbLCdTB7YbgJZEpKVryoVQhZrLpQP9Pgabxkl+R68Jvq1Tq9ccueofoBVZAytwNXjtiw4qKsqOLsj0XDPD1vyWVT7xUUjLM7bPCBRBgfnIIMMspHcfctCrfDnckh2zEpl3nayOrdwGiVvnnJ+if7MVszy2EeHf6F07VVLwrGh3i1WcUSoc9mamISncSKdZs/xniq1kxtYJd4KKJM+w4Bw03V6bq1WzkUi/Bn5GNWxkNnbNM6iFH+M4uOIGbL9v2vxMSW/ff17Ep/RJTjrB8sC6F8ELsJxcZ4yc2fxNNx2Kem86bFL7C9wgZTm0/iMVPn+sudZ+WzOOi/5v++cM/QLnBaaa2STts8hZ7ZGRD9HRE+I6LfVsUdE9E+J6Pf8/2/440REf4uIvklE/5aIfujCGjJvvg+37fkcktKH7se23VJy2/gDdJul9jt7YB9JENh09q/YxlVJX1+F0GPnO4/g5JWLYiRzGNq9+Ns89JnrJfB40SVn/RLdGh/ZuGwrLYfn57rm54le+T0Xsucz5pzZZfPKv9BX/u8SZJNtyM8D+NsAfkEd+ykAX2fmnyain/J//08A/gyAL/l/PwzgZ/z/t08y73ZI2BInaU4/ll+7SW5I5s0OFa8ATx4j5DdtSGCzPomL6ipWLWObRnrIgKoC+c1l5IYIOhLRdM35M8zejmO5ZkoRo60tU+MTxQiKzAPgQqeSyLdJbohGeUo4WCdb7e5GejpxGIpunvwmRC3IwIxHoPE4JNeBsD43ZFTDzhXCFgAvFqjeeQvWs53LGBxju0Nw8nzhkbQcyG9C6LRpwfM5zKOHAID2u5+4SIoiCwIAszPp5IaY/X3QZ94Ff/g4/o6FHT0nvxEkbJYbQseb43XOXCyY+deJ6AvZ4a8C+BH/+e8B+Odwi8VXAfwCu3jsN4joIRG9z8yPccslcnBuYLrlHuXiXlo9yBQXhcCQle1pk4c4ub4AdNL4iaRTm0YelJ6bcnCW6oV2ODjni/hmbLM3ekn82y++Rf1xNYaEs0KFVHVdVc3BWeTxnM1igl7IDeHOWzzo23RzWML4My6T4NtQFkr47ug4LbHgLYPA7t1asElzaZjIPchSQuFQspYVvkb3Lwu/npv5AvT8IGH35raNDGlaKseI7vKQtB9qc6vjvJuad9UC8DGAd/3nzwL4QJ33oT82yCCD3HG5cDSEmZlojbu2R4joawC+BgBT7J5x9hWLMpOTxCqfbLU2Rb2PgzOY3TY55mLiKaaCG+tT0iNCzyWxRYBP3l8fB2e6DbFBt005OGlUd7chPj07poLvgE9PQcRplmNruxycKmEt0IIk25AMLJVvQwTrwnGLGJLHBCeh9MJs5hGcsr3y909AUt4CYOso9Gg6Saj2ztqGcGcb0oIe3AepbSvVNSwQU9QVgjOkqFcGguCk2TykqOP01FlLPoHQTSG530dVgU9ahMTB6QR46yFoPo9JfqO6dxtCpW1Iu7m9cF7L4hMieh8A/P9P/PGPAHyPOu9z/lhHmPlnmfkrzPyVESbnVOMCchWe8PNKD0N1/+lXmJ5+3r4EVuwXsoSdvHj+OcbQc88CQ7bxpv2mbNfmEn8D20a/SszcW3dJ6aJwmeMpyHkti18B8OMAftr//w/V8Z8kol+Ec2we3AV/RXzD5slcPfv8jQl7MyepEMICAFbxgWmsu+lSRQrwiVktGFJZSqmhSVrcya75qyLslfEI8ctkDByf+BCkfjAJaGwZmWkoTq+2EDZNUdc+l9EItFqBkfZD43FkkZK9uHGp5Tzz/BG6nexBpVEdHbwZLFxKGyYp6sY438TORFlY7KzHqgpWhDvm2b2lfKExoXwhFkvwTnxhOh01rwpgJEV9uYwWz3iE5uEO6g/VOMaOzLhUvjCM5aoIe4noH8A5M98iog8B/DW4ReKXiOgnAPwBgB/zp/8qgD8L4JsATgH8pY01uW7JHm4J8W1UdJZTc7uUSCYe/G4fkuDURig5c5ITEM7VeiaZha0rGZDli3DbAouCIxTKIXdWItliURhPCwnrAoB9eRD125AsSM9HGLdeBEKSWQYwEn04smphFh2WrM3oFy+LUSwmEx1/GsS38OS2fm55hehgDbT7MgVtCLm6k5UT9ONPHYWiOs5tC/gICa+a+NDKecaAiGB94pf5ru3MkxZ7MgPMPNHJHh2j/k+PYYWdHHCLiWZhk+Oek4TnC5A4Y01MJ9hENomG/IWerzqZXz4K8lc27n2QQQa5M3L34d7nlU4WoXdm5kV3+i5XDkMXE+9+33nT6iJAbeZ07NQr8U5T7VQVfYmQ1BNRKL7EfJZsx4xpKya4ETrJd2RikWLlbJXiP4AzaYNDTye+yVh65itpT67VWA4yvpqYChuGc9S98YlTrjiT6n86Ac+6b2UiCtYCtH7eIRx4QA3FAkZZMhgMdXhEiQjcGldkSNpVXB0hoU7NUygCZLzTeOUsWiE+puOToqUqHJzakqPxGLi3Bzo4TI8ByodEnetJlT/AfGDKujq5JaUEAWzmpNXQXzL9+t/0uCSL9Kb1EFlXs+Um5SIwdXOxMb3GlkUWMpRQZebw672W1Mqdv7GA9I0olykHJK+a1MqoIyIw6CPhWwnPir5ioeQOVM3x6duVPIhQHlEukf12ZtEEMl4on6rXOzg+d3ciV6h2qEqfJb+FflMrZ2Z4U/r6pBiNHKGN+GG9w1Hfm6Q6muYx3duLHJsixo2dZ46vU5O/kEdwQpyiMn+NQ3tC5ow5lF/QyFIicoQ4D+658KUeK+YxdGoocmH6cgaJgxMAP/T0/E+fdVnT4K0U0V+ssekUzbsPUD9RzOK7WUUy7eCsKmC1jFXLAOB480Xn1V8s+ohiSlmJeRZln+S0ZSXkouQdaIeaZrJim2S15ub7WQjOzg9KkIOeicudxmpL0ePIEt39PEmFdK0DQS0EAPh0Fj93xtwDudF5GOpazfjNcMxXiawydCLgsBK24Jw9OSlvg4QJDUjvx9LnrQSns7sPrup5Fs5vfVX0kL26cpXPqgp0cBRh5ELvrxGcQs0PREe134bwagWezWFeHiVzkwsvFm5B9xgQAOD5HPUnBx32q8AWJmP37dLensdg6OzhS3Rw3nnZmMxkO2KQpBRfH9y71IdeIPQPowPHVpGOXN8MPi3nB1i2bqez6Hj/B5ejITrqocdCMia4H2NOhwf1fUn0fJSu7UDB1d8d4hiJmGSLO88XxYeNyVHUUR4aF3h8Djln68eooOzkIgcaci73nk9nafkDHw1hXQQqRH1iSFciWG5hOenMUz5/JPyaPk2Al0vQUXeBLEVDJBzcISLaIjFx8FkMMsggG8mrb1n0SZ5tWY9S3sTVsu/KDiir5LOg8biTlEX1KHiik+pny2XwnAd/QT1yOkhGq9bXZ5fmxXwcEEiZz7OZ94AvgUpVb/djAGySPQn4vXFOXiO+Fn/cPHwA9hgC7bNA0/TiBMJ8AKFPqutIHZf5I4LPYjoBZjPns6hH4RitXGKU9lmYNx+F6mLxoPNZWF+pTFs/NJm4rNODCC0XH0kCe/fREZpMAqZBfEP25BR4/x2YTz6NfVaV21o8esNdP5v1+izMYgk+Ogbec+ULaTbvkurCZdSirsGHh0Evc/8NNF/8DGpd98SXf+zzWZi2TX0Wy0vMOn1l5bygLL9VSczfAsfkjYGyJEUbcfuQ6JiDsjLdi6AsD2hKQFmqDKDu7zJAWYDaesxmcftzFijr2fPLA2XZmJUqpRqEoyPoKab+4ydlUNbzF75dBcoSAFUOylJbvCIoyyNmNbWBPTxE/U3aGJRF47FbNFUuTJ+PpCSv72KRS8k3sO7cZLUoLDBFp2rmyNQ/3PxHfpYeJSg6t2DteOWsBGKpfWlHHJw9OAl93C4W8cFfx/tR6k99TheXzGchp7bpNZ0+1QV2YdfOW2cKmiYNGa9B5rpulN+Fyf1NxvFh6Pvh59KqhTu0o1PZlVLtYfRlFXVPeEKq0JbNFsgwp1kImhuAPN9IMq7BwbmB5KAs4wA3CVCqL5KSk9+Usk7PQX7DysII12e8CglhTe4ENVUCUgrkOXobw+niUCyMnGed9pLf2Bjy9ZmdaYZsGjbmHIAF9RAotm7NYEX1KIKmNPO1gmWLmJ1pzA3JEsg65Dfsyxf6KvNBT9l+FBi6qa7LhZHffw9WAaMC+Y2vXK+jEwEQVdcO1NU0yZal/fiJIr+J/ZvxyJHfzObhd2X290Hvv+PIb0RPCa8WQFncWmBJaZ7IydVnnQ4yyCCvmdx9y2LLgsjxOlknIw9Akm2Y8z7ozxtmnYZwo4Ypj6OjMbyVLbu3HIBWWxYarp3By9MwWNnBySdtyDqNzlSrxn9GYWS/9w2FkQUItb/v9r3WhvEQ3Bu0jy1LO0iDhTAaATMF65b+l8tg3TgHp00g8WYyiT4IXbD53r2IQ9B7dkMAnIOTgh/COCrDnSlItgtyf/qyTicTUKCv8/VHlkvYtx/G5CzLriiztaD7++6YL4zMzAGoxaMaXFfAYgkig/adB67dZ8+D34OMssx2dlxGadOE+272djH/3ENMnr2IQK3dHeDkJBaGFottOnHXzkzq4Jy9Tg7OixLYyv7OE55uxOOTg7JKPoucQNUfS0z8trw/dmplztH8IcxxFtKPAjElepYKzpR0b9sUwMWuTie1bdCJF0uEOqN6/yuYkwIUWYhl/R8A4CIaCpQFwOmv5k6fI2OQhYI5UugDiPgPNqG9MI+eWCgpA9m2CWmNduSS/C3nAqEEILLv6HQRSgwws7uWGfDoTKyWYOu3NbXnHG1bt1VYNeCmgTl2LwmrsR66yljTRJ0Eg7JYYnQY+3Zz4KNE1v8O5GUwh3eMN0Cl6zhu/vzc/cXivFJ60PLjub8gOZ2Ln3vb98eSRUGf0ypfAhAfjELb7phuR52bITU5r9uZWUl5+9pfkKIrVX+rWGsU6mEsIlllDvW4ZWyIC16ndmw4brv3RhYuywDFQs60XIWIB2dMWbKwJGUN29Y9rFpvWTCQzj2hdSHdLGoDZtBsAZskqHmwlUC5V028LxL1aqrAnsVNAzNPo2EdfpXVCmxTnlNuGpijOXRxaFo5q4xzQmp2tWi5aYClWsy3YP6++4vFJW1DxOzTLNhJZmfn8pitWco6DTc7q10RHJDK1CW0Sd4BAE9jFx+kvD+QSUsaep007oAbr5tkUQJpaLiQdUpVlZLfSCaoUNkBwGTicjD0Vop9keJWbdFkOD6XRRCUiY5tdGzq7yIFny8vyGprMPIEL2TdZ3lQJmN33yoTzXDm8OZ1TmN/rvHO0Z1pDGeq8VOW4Ymqcn3JVkrGSATe2wEdHcdz/XYhwbwYZ72GTFTv6CRxDHv8RXAEGwKJVUhuG0h1DVosVD8HaGoAACAASURBVN7MCO0bu6iejuJCPR4BGn8ivz+vk9s6qqzT0yE35FzC+k0JlC2G7RstmuV5v51th3/rdwr8Xodk1a0gbF0SZhNrhVPLIoyhz2qTP5kvll3q9WBmD4HOtxzKwgpbQBu3SfB+ImArnEGvdGD9G4ThZfvbev21hSZjCOf2v/2p5XRLeoW/kyEaMsggg2wkd9OyKG098mOaNKYEP1ZQa5BxMfrlMpiObYaodBf5CIKPzwMAHx87tutjqfugsAizefLmMjtT0D3nIbfPngevtD06gnng2J2tTygyO1PY9iRERYw3He28DazUduatDjGzd3ZCYRsA4Ocv3Pbm5BTGm7kC/glV0L0OfOSyHs2D+wGroCHgtLsD9mnY9gvvwfz+RyDLIOmPGXxyCuvbyedNFwCinR1nZo/HgXpO5p329lz2qNfBvPkIePYcdmFhdjwz9r177l4tV27r4ee8+f73MfrgqbvneqtTV6CXh6CdHbTCzl152PrDeyBfZIjGY9C9ffBy5VL19dZiMgEe7IN8Oni4j/MFDr78Nh78K+8bsAyejmGeH2D5xfcBAKNnJ+CR27Ys3nbz1U4NmqnB+KDB9LtHeP5DjwAAj548AyRbVTnR6d23wNMJzHfagBblz76DD/7kPXzh2YNwXvtoH9XTQ3DAc7h+2/tT0KJF9fwQ7SPPJG4A/o9qS3KG3M3FoiRbmoJpMR7rUIltW2Ra0ucFiLTy7LuiO+l1slDo7YNdLELojZsmQLPZMvjQP2SSXj5fuGsbX2RXo/SaBjzjTm4IzxewCpEX9GSbwpHlO7YRxCQ6Hp+EiEqIigj02S981ePnrj3JggRcBCMPnSqeylAACAh0/TxfREj1TKIfTdKX4/ts4jxLX+KIVPMy+uBpXLSzrR8vFo5wWG1D+OjY5bM0KpIhPoR5lXJfNA2oadzvBAj3EWxx/z8eAM883yYA1DXsfI7xB25h4dN52E5Oj/w9H9XuQV6ugINjPPQPLc/mSbZrkGcvHShMwfHNJ8/x/jd23W/H61Mtli6DVXxMHnRXHzqeDj6doVqocS03RODiVVostnR0RvRkdlwcV/6cjfgtiupQdBRKXoCif2cyEdUnCEn94zDKGZqHc6+zhIGn1yeiGGGAdxZqOkC0cTzKwZmU4QvFidcwdm2qE7s6JlSZlJMDcOhIcby21qFTqwoQajkgOlvr+uLzWZuktAHVVUoT4Il9WMOwxfKpKlBdxeO+pIGj7FPjLQgRwVYpujagi4Um0qh2Lyh3f7HQUOscwr1NG/K/BuMEWLHK1Nxm9RBgjfoxBseeptGvKvfjabUuFIE8TMnxc9Xc2EYEKqwdkYZAwqRD5LzuzDHqAACVdREZocXX4CJj4n3RYc3z6EUOR8FV5fqXN3HlHhKqa8AzRtFyBZ7N3DjqOnkZwPhxXHA+eVSlDtvxyNcxUVSBEqqWl1RVgZgdW1Zdh+Omcs5kqusE+t8ndmzS70P9FAKsSX9vF5TBwTnIIINsJHffssiTrC4q+m1XQkluIx6FF2G7ms5Mh8v850KIMSBLN0XlrqvAtalov4cgEoE0zNjaFIhlXWg1gJ1CAzaGKcO5NlbQOkv/nvEEIFJp3lob07BzNrI8NLmtdVNWJv27h8JQb00Bh9EgCZuKxeHHVWRRK1kHjDgPwPr7L1bHObckd3+xELnIQsHW7ynbFOLbrDrnASn4iVceOJSdqm9arPiNaIKrH7hUVw8ZokDk0xRfBqstVtvGHAYgATAlBLZCbd+kvhj5zuWcxHFIG4EjQhyoFTwITMziKvJvFFLuS+QtyZjDGEbOdwPlz5EaoCEL1YTPQYyaCw11rmMGLev08NrVKKW2ilmnbhKAJt5z8r4O9p8T6HxVue2Fj0AlRMW6BIOG9AvJz5zidm3ic4Nq47Yvpw5xaWs3RiPOZO3QBgK5cLLgjEawEwI3Csy34/wfRARUUS8euSxXrFZRBz2XG8jdXCwK3AhbN5HDnJumC5fugXt38jhKhCsCI04WBZtEQFJMvyc9IfWGoe6Co8/PIdwSJenoyRwf4IxLosPfOF90vPEuqhJBV3x4FP9W7QpMOzo4Y4o9a1i1PEwzRX4jfc04iSLplOwYwZqnIDBBcL48DOS42ocg3Jy8XCYgty7hUOPJdixQrdK5aVNCnEAyxIz6yYGLIomMXJo4vXBp67xYBASnzJcZjeK8zWYYfewYvgJsPPvt8fEJUM19ZMjP1dER9n7/MELIAbBt3T006SKMhYs88XKVLvDN5j64u7lYaDkDT7GxeDhy/qYt95nVbegpbEysIgH+GPyPhASWDLgHTGqXCpY/M1nTIkEm/vgAJJD1rNZpqBWiYeZB5wK61FPxA6nFksCqp1OHRRALRxRbAp07ECj/jPqsHKWKug+AqnWqohVt63ylfr6E64M83Dypor5cuaiHzEPbgloXBqWdabJAhCrqgg0RSLdp07qzXmcaj+NiIQ/7YgH7YC+Be9No5LZCvq4p+/EnWaeTkRt/45LW2nu7oZ8OUxk5lisIDaHc98kEi3f2MP1uxErQZAKprapDpzQZB3bwUIMV2KoUAOUw45uQ+/SIf5g61RCdnBXh0ItERuSyVnqL7SgzflR3TepN50u3v0FoLmw3QnhRwmf+LdJk5nPfGBPmp3PcW12IJoOqa2KdQPFW2FYFwJqnk8up+zTpz8bgOqWbEMMEEh2OiyU8IQ6piItdrmL4WnSTrUdVwQb8Rts/f50KdvFvs7eXWimePqA0NyFlfFQHzldeNQE0p8l7NKtWQmQkTdU1zP5exNAA/X42ofrL7ulvtL+GQ36+0V5kiIYMMsggG8nd34ac1zIqvTVyyfgXzg1sKbxZuslW8rYUb71JUrivTUpJYEKBp97GnXokQHjbJ34Ia2IbAT15zndUdr3MV3AgV/6Yrp2Sp/pnBMGc1xI5j2RI3U04USJRsUfBij4q9T+22a+jA51l/iyVgHiZcjcXixJ71bZNBISfYohSaeMlxu4giuuSV0vQaNwpHRDK7ukfkVDNAw4o5HWwy5XLnWAOfJBmWscSh22bOA3JoxE7pQBUqQHAOQepqsDNKmF2cie7h1fo9UV/s7sb9+XhIUyZsswbD2EPDkGKKUvaZqmalUyGgdFlEes6FtkR813M8/EoqYpGk4lj4W6a0FfClFXFgs3m4YOYz2HSbSAvFgEuLWL2doDJBPa5g2o7pqxRLMijIidUGZePczILegKAPT0Fff/nUT1WpQDqGnx6mpYC8AA/KQXAIzcHtGrAh0ew3/Oea/d3v+3GqsF3ZGD29h2M/OAobEnNG29g9Z99DqPf/nbUczqJ/QHhBUeTiXfgzoGd6LOgZ5svAbd/sThrIUiqjW/xFg6ISP9AeMea8XwD7XIJoIrth2tsGjptJDyZkY1oRx1FxxxJ2GoVH2ASx5e1IYkoOPHE0anrolYeo1AKnWoy1sVi+9DpdBLJUVYr94Oua5dIJTVP7u+DVitguQoJVYH/48SquVGhZq3XdBKtlYwAl8ZjhPwb/7cruafa2Jk6boZV4374Mg8P77k6pXUddIW1weMv1HJuHlo3pof3YxVy4xYErBrnJNUOzroGTacBvxG4KmZzzD9zDzsH0cHJOxMQW9gHbm6M3C9mtA99AtruCEyAaSwqQ5i/7xycu99249eLoNNrCkzGoNNYGoH2d3Hw/VO8/Z392Pd04q6T3BAfTubdKWjucneCk9UQ8GJzWr3b7+C8KulzWCWs3WusFn19Xxas/t63nTj31JaE6hGgmLQ0G3YHeNbn9NWs4/kY1l2jj+cOzkxvACEvxIHFohMvhIpLW63cEal11HrIeVofVR/UnRLDnyW9QrRIJKG+zyIclUmsjdB/IWyeRCrU76S6fz91MhpKiYFaG8lvBAqvHLDcNIEJ3B4ddbdzMv/i6JQX0mQCc/8+7GFkFhfGcO0oD8eFdUx9943FP8KhfTY4OAcZZJDLk9u/DbkuKQGw1lkV4e3pw185MEu3F6wXqLdql0PTXaOqYJUsA2m+EI/XdUkAt7WQN1SnHorvNzne067oFqye0SjZzwfdpQhPKdmu8O5ynBpyuUqqs6z6qtPqa3JOQUcaR26L5LjOkG3SEKdG2pIv08it7ZaHlHCs+Hw88Msu4bZFOsRufCFm2ar4bRSgti+CffGV3OU4Hxx6C1MNgC1ovOPOn8V5oLoG3dsDlGWB0Si5r8m5oxp8cppuCVeb2wuv7mJxFlhLPeyAPCRqb78Ox0AmpdavCrVOw49N3VxxoME7KlUb4bh3NIbyAsEno/QNnJb+kJjWutQAEExhttx16MqioMFazE4P8b8owJSj8veZkft7wVGa1jolNx89ZEOdWqfjcepE9cf0wivncGPT67yDUz8UdG8/8kzovuvaIS5Ho5SjYjxyD+k8ZneKzyKZR2sDB2bgkvC+LWoa4NGDmIsSCh/NXWkCADg9RV7rlGvnpKbZAjgi2Dcfuu+fvyg610l8Rr7GKwDQ7i6Wn3mI0dPn8bzdHUfWK/Mi8zqZOD9M24L2IkHSwMEJxB9sn3VQChHmFP/rRIdVS7yHfVT9SVhRXZe/KXNG68RvYUOCWfJdlsSl4eu9pQXy8LDkqahziDg97un6O3qv438s8URqFm+Z96ZJ2L2Rf/b/B/IbPSZh986E4fwGZLLvPLt30KG17m9pWxMoS18yB95CY5uxe1sLkqQ6WZhWDVB5TT3xDDWVc7wulsCqgTl1Po+2D1TVtg4hqxPnmgb18TK1BFerBOxG7B3JZEDW+qpkulzE5j7LV3ex0OX5snqe7nNqWThYNKfOt2K73tmkSEVoOokIy+CYy9CF0kcIaWVOuMxsTDg2CpaFThiD57ugKoV708iVRbQ+bAgglk0k45pSlk54K4YfmuJC0MdHigNC673uh6cL/+hrA6t35U19A6JJtFxGdcwMDW9LX8BJrpPxjkfgede7T3UNVKvuHAshjkJVhirqbz2CkcLGrWd9NxQLLdU1sDOFYXbRj8AmHi3NEK5umug49tGwYFkAwHIJ66HhnQJJIr58IS2qyBBe12j2xxjpORiN/OKUWRbjEdr33oD59jJlHd8CO/TqLhaK9qxzLD+O+LCcyW3jz9FTXKLVE9o6fZz92yG0oyqb5z6ATkHjzLIIiW/yHbk3jrYgeNXAii7qXG4Rz9fms9ej07flxI9gj0+i7jYbX8+CwfoNrhPodDurJvy4QzKbp85jZdmE47kldXRcznhdrQI1X3I/vL8g14vbFub5ixjhsOwWG2NSCj5fHYyeH6RZrsa4xDmfc8LKZ5G8uDyWgxcLGE/L16h5SubvdBZg5GEr2bYYf/dlwhdLPmkw91lguUJlbYcXdpsU/SEaMsggg2wkr65lIXLVOJIC+cqNCFs44olM+vwIJYvlFkhee4Q5rSZ+tZ3b8KbNYdQJCZCIJiy+TjnnfPAW6eglefUXiw3h4AHRmFXo6jlZ+RSoHA2pKodgVHvCFPmpIi9su0jKUpWzXAcdfvU6JeZn23qAELokJxp85E72eisOjYAMrVJSnckYFCj1U+OUs61XuEbmA3HcSY6JgIckJT2Q31Te2RjvTagahjb1Q0wmae1SkaryVbqqWNbP655EcyRFXQBVlU/V96FIqlVER/wtTeNS30/9NsR6Pg9rHUIUcA5PGbNEWarKoSsFiStlDtQ8JfNXO7JhNjqaM4a9vwv6RPmpxqPIRAZ1f0ZjVzZhPgdGKtIz+Cxw5iLRwRf4H40uX9h7bf7QCyRb9UmjGhqRKW2H+hhNE0OnzSo6nXxtDsEGCIYjqaJeVaF9ACGxiioTnV+A27t63c6Ge3u9p5PUWy7t6hDjvX1Xa8OYtBTectVlF5M2lL4xBDpKHz740OliEaI4NJn4cyIikiYTtzivVpFXAnB1PUr3zT9ANB5H0ho/VprG8oVhQQACqzng/FPi0BQ8hcyztYz27Qcwyr8RHtAHLnRKFHlM+J5UUa/A4xrmxJWHWL3nan9UHz8p41x2po4pa7GIzt/9PRx/7z72P1S5Hvt7zukeqqhTuN7pPQbt78Z2D4bQqXJw9jjcshtiffLSmSavZ4TSFcEDVZvqy84XHQenXa5AEsps28hdwBwSlBJ9lJ5aX+co7TJl2SUSnIF2VCZMWUS9TFn2ZNZxcHJrQK1a+J4+D/qRdlaucXCG+QDCuF2NEOVglTY0U9bpaWg39Olp+dhysjjQk2cpdFuOzxwEOjg51VhJO3RlTi1Hp6iMbdWAJFEOAJ+eukWALcx3PnFgKjnXOzjNk6euHw3KkoWJfP3Z5Qp2scDoW+77Rs2TFj44BFdVwpBmn7/AvX9Xo9XEO4tl0cFJJ6eOW2S+SF8Ga16KuQwOzkEGGWQjeXUti7PkvAhOf60+j0Y1eJFBr68BwZnT6ukUeNdWTHHvpdWT47Idu04EZx23JsmefrVS+vhUf6YrR3Ciqlz6u89c1WFoqhy+gcUy8OS5WCyuB8G5swNImr+A5bZFcIp140tWOt02zzp99ReLi3JzltoDUlAWUXScXWMWb3TGlg1E51upEgJb51sxkEphuS/jWsVER3FSrU0BwNzBzJl7RRLIbYliGjzgHIaymCk9MR518QxXJbqq3eh8jy3vTBwFwjnLRdy9FPVtH/7zcnSua69zTHEjntXHpqni2+rRgzwVvsoguV7y469HXRRqfl4pbfwinJ+mipZFzvUZnLcF3Uvp/9JGXwiplCckCYHq3sl8mekEOblQztYeSHy170XpEa1PZaGYrr6sUtdzxvFwanBYRqeync1hphNYDQgroYa9VPt7sKenybFvrP4RDu1mHJx3z7LIINwho1D/gIH4tyavUd8bbyIK8s68+QiYzQMxSPP4Y2e6tW0SMWHLrhq65x9onz1H9eYjtM+eJ33U77/nkI4+IgF4JqdHvuL1hx/HStwvXgJf/DyoZbT/4Xfd9e+9i/b5CwfXPj0NfAft0RGqB/dB0ymsd2wJCtM8fAA8ihW1+cPHoN1d2JcHqN58w+vrIMzCSGUeuvPbTx3TU/UDXwQd+yrePhxIuzvgB/sg74Q9+qPv496//hhoWtg3fUXulmFeHsE+fRb7V2UVqnfeCixW5CvG884E+PjT0AcA8IN7oIOjGIp8/x3g8RO0xyeo33dsUvbth6DTBWi2AO/thAXg4MtvuyLFviaHa9CVDKyfHMA+2AO++R2vbwv6/s9j/pl7mP7m77ljO1O3pZgtHIT7+UHQn3amLurxnU/cAT/P9pt/gD/4q1/B53/Nj61lNPsjjD86wIuvvA0A2P9ogWZagVrG4fe6beJqn9DsAtPnjDd+d4Hv/KiLrnzp73zgnKUmkjUTEewPfC9W98eY/PYHwZm6+pN/FAf//SHe+l+nYWsye38Hux+ewE5d9qmduHmYvzlCPbPY+fAYs89Fshz7L34dm8rdWyyAZOXsQJNFbHeBSJqQ+h0SbTg4dHtVtafNocMhguArrkv7fHTU6cceHIaq4uG98vIA5BOJ7OlpMHPtfIHqA/8jlMjGwaGDa3uYtfV7ZYmc0HIV9AtjODoCKXo/0ZObFayv0q6jD9y2AZIc5JNPYyRGfAyLBeh0FiIN9/6Ngf30GcDsvOwy5sUiLeKj7ol98TL6OXwSFo3qAKmWuaD5HHa5Cn2bTz71FdtbWP+Q0NIlX9mmSSj4H/wrdtXMPTN6kKqCPT4BHR2HMbBlVI8/xc7BMVrRYbkELVeu3bpOINx8OoOZzcODKj4Kblb4/K8do/rWx36gjMl4BD45wRu/5Q7R0QnG3jKYPnYZnzyqYMcVqpMl6PkBvnflF8LnL9x905ylAMx3PsF0PIY9OAxzvPMfP8bq5z6L6j/9ftDz3qe74KNjVGKJeOtmvDMBNS34+AR7B7HGSTVbV/MilSEaMsggg2wkd9OyuC5ZswdOEra22auXqOXOI4UEoBIkOa/aVbpmI2GFRtXXyB68D5/SR6cn14RkNaVfDqPuWI1cJrnRVlzez6YikO9OnxmlgPZdtJx+J+cmiYvZfbAEahWIT6uYzxMZSC3ZVFeGabhzzP3n25XCUKGebq4XNpbXd7HQMGfyhKoe7gsAmM8DyjG9Ju4jAbjitqVoiJDkGHWDqypWylL1MamqPMpQOeyEmUlSlvUPSKELkyHpkJk65hCJPQ5QHSURHSv5gamwZl1Hsp3JOKZyCzKxtQ4mbZYJQ7pEXTS7FWkTOaStm3hMRUnCOXpsoouPSIQHZOqqdlFdRcLe1nOIjGqna4hqsGPh3pnEBc//BgI8O2fRqkwoC6ipBpr9ESaaIHg6cYxacsynl4PZVSID0O6MwJW7j9VsgtW+m5PaE9TAKGYy8ohhzwgeZFRj/rDC/nQS52DsSHqEMSsQ9k5GwIoAU4UarJA53FDOXCyI6OcA/DcAnjDzf+GP/XUAfxmA8J//z8z8q/67vwrgJ+BiXf8DM/+TjbXZVEor9pae+BT9aGPqb55ynVzk07gtR+SboCDzFHVBBuo3lNrPc4Z85NMZdDVsQeoREzqp8x69WKrXCkUcq/XMY/dybafWqaotCj1Hqs6neXkIns2cJaPemJ1UcqU3L5dBB5mRMoXfPEnDDvqwqtfq54nbNkFwmucHsPO5g7dnD4GbT5vO++kpSBESuTlxdVTh08+DSIKZrrfqxzj+6AB84v0Avp4pz+Yw3kHK80UoJ2h8MpepK3DlSwEcn2Dng0k4N6BEZR4Nud/HapWm+h8d4+HvnXifmT93tQLP5oDx+sni6GvY8nyeWp8laHmPbGJZ/DyAvw3gF7Ljf5OZ/zd9gIh+EMCfB/BHAHwGwD8joj/MfCZLxHZSqhvSV/auJ9RqJPy0cMlUZm/HVdr2ORrty2V8u+WlAEZ1LBlwdASzu4tWHIW+L7O/5x4o/WPe2wHt7zudPn0aIi/24BDm0UPAMqz/0ZndXdijoxiBEX3nLkeCdnai01Oo3nZ3Qffvhf7406cxmrLvHGtW1/Vs2xhl8TyO5tEbYO+0dI42R8FP+3sBkNR+33uofq9xORO+XVgGn57CHmimrvgWNPt7oV0ZN02nwAvH4yC5FrS3Cz45DSFE8+gN4PkL2Nks6Er394HFErzwRC5+zpdffB/jD3w0RlexH9WgF4eg3WmE2Pu27QOf5wK4XJF791wEazxOnb+TCfDgXoBwC+CKH3+MF195OzgzwQyMRzDPD7D4gc8AAMafnsCOaxAzZu/6+Z4aNDsGk5ctdj44xKd/7BEA4O1PnoZyEGGLQgS89zZ4dwLz7Y9g/brEn3sX3/nRfXzf00dBzfate6ifHAYLhv1i0TyYwixbVE8P0b7lo1EE8InKrTlDztw4M/OvA3h+1nlevgrgF5l5wczfAvBNAH9sY20GGWSQWysX8Vn8JBH9RQC/BeB/ZOYXAD4L4BvqnA/9seuXMxPJMuap5SpyMCYnFhxtbZuEVUvsTMHs1dua5SpkPXJrI8wYAJ/OEyeihF3DtkTpy611MOMsyYyXyySrUvTktg1v6rAP9p874eHZrBOSBQCcUsBzVM9PgFXjnGin0Rzn5Qp9pfPYm8EA4nbMchfabFyVssBaNZvFz6Lr6RxYLTvXjp6duHnMQqc09216PfVYTWXQar1OT93YmiatSGbZs3n7Y97KYsvY/2gBOorhSIxH4PkC40+9xXJ4gqp2PgvJD7XjCjyqYE5XoONT3PvAF2tarpRT2t97MMzhsQvrqsS36uUxHv7u/YB/AYCKyDF4Lz3Lt/dZkOcW5eNTV/RIxlVIh++T87rkfwbAHwLwZQCPAfyNbRsgoq8R0W8R0W+tUEatXUg0dHeb8zc61ztETeac01I6Rs7B5P5R1obiuWROr2frz884McXxKf+MUe1X8ZjkkvReo52nVThG3nkLY5zjUP6WHA3veKPKBEi5ICA5ixwEZ61/kJ0z1sRxiX5G/vfHZa5kTk3sz/1N4R+PqrhQ6H+ePzPn3ui0IfdH9NBtiPObKL2PAJqpd1x7zgn3z8COa9hxDdTOqcijGnbs8BV2UqPZqWCnzmnZ7lRodyrkvpYgo5FzTPo5JkPgUY3Vvpo7zylKtesTdTzOk9p/53lH5d8WNVHPZVkw8yfymYj+LoD/2//5EYDvUad+zh8rtfGzAH4WcHDv8+hx5XKVLEja4siZtoEYvit+dz3TFcJvvs/wN6vQpXoLMncXiaQtXfxX2j2vXqV50d/r/X6mfxCx3C44n9QWwpfa+ZuHK+UY4CgLmF0ERuu1qVh021aO8uS8C8q5Fgsiep+ZH/s//xyA3/affwXA3yei/x3OwfklAL95YS3XKqPg3NtcFohhhf3Y1ZgMWZsnJ2UHp2e1CqQvs5n7PEv5KGgyjjT2FPuQrEM6OQl1T2m+CHBniS/RdOKQk6M6zVBdLX12aSxUHEhlxqPQPgDQ0ZE7tlwGfWkmbFN+LDIO71Oj3Wl8yD3jEk283v746u09jD515wW9vR6keSuUgzPMB7xj0/dFgp4U/fZ2HBpW8AF7O6DTU+90lHN2gXoJLBYJ2c/i7T1Mj2YAkavjCbitx2QMLJfuOimC7NtuH+4HpimaTlz/i6W7RqFyaTwG39uNfBRyH18QDr93HJCZsBY8GcE0bXBmTuG2HYCDYwNAMzVY7RJ2XlTYW7Y4+IIb2+5vTtKCRTK193Zh9yYwzyfBad6+sYeX/znjnX8RyWxWb+5h9P+3dy29kiRX+YuIzKysulV97+3u2297wEYGYyHByBI77IUl79mxtgQLxG9AQvJvQEKCrQU7WIDECiGBQRohhIXHHuPxeKbdM909ffs+qm5VZWZEsDhxIk5k1e1b/Zjpx9TZdHXdfJyMrIw8cc53vq+z8HWe4Gz3KcFZdhbtlaQb4j96geQ3SqkfAPg2gKtKqbsA/hzAt5VSvwu6Fx8A+BMA8N7/r1Lq7wD8GEAH4E9feCVka1vb2kuxUmS3JwAAG1dJREFUCycL7/0frfn6r5+w/fcBfP95nLrQ1kUTTxthSMCNDutnXt/y9z0cQAQYMYCLzyvBReyD4TWvTutCo4nHIKx7lQBoeeZOjC3wJh5b8XqajdfU/bxID0iU+SkFj+X1r9PSkGCx8J1nUBMAOzCoqpISZhyZeJ+0NQJxcFSQ96S7wcA1xWOd5WzYT51fG2+jdLw3viygrAU6k4GybK1pXW90fKMCAAoNXZbwgzJFaNZSDmFUwsR7qeALA9WZdJ/EuPhStPoX6fjtWKXGNadghyV0YWBrugbOUcB7dOG7dkehqxWaRqMelmhDxVsVhnxnbk72K/SSaOGTqwzsfhejCLo3GmVZwFd0PlcVcWxoLEyMcgBsrKkFvMkITkkas1Z7M42Sdz497DLh09cW4bUkJ7jY+g8iAKV1QkXG/XTORSB/jJzMi23gSoTzqzBuZXRCjar0wK2g88KkE5N7kmhY6RXffVlAhQeVQ3mldfZw2IFOE1scLzGhySoKUxXy5CCu25dF4ofgZWFZpMmkv418UEMCVh6vq3VELHK+wCvxIDOdIJvW+cMSEoToCPGZTaQFcWbGCZTHWWl0o7TMUFbBGwVvCEdB12BozAC0I/ZVoZ0AxZy270Z83zUYBJfG0MNXBWxtUAhuElsbjPbm8FrH67U1TWouXLOvdPheAwp0nKHAoHzWCc7Xwi6iupcsSFolRKZMLvVIV1hkmGTvmNPS0ef+xNK2+YMPAM5CLUJZEojU7EopoLOU7JIPXGCJzjkQVDp+v+O2bSLrNhBKn8E338tvxHxKm6+P1bKJfnnrCC7eJb8BoDztEAV3bMpv+NATkZEeB8i771Iewjs6rlo2cHwNrPS1bODbVB7UvI1PCFKW/IsI0uBDddxR+dOkSVN5D3XW0L3oBLOWc1BtB90l+n80LTFXLRsqLcsOWq2hZ4m/Us2ZP9WhPvQwM8FxqgmZOTgK13DWonAeyjoMH9P5m0ajmCtUUweztBg8Evc98HPG6zUGerZEGXzkRG05bTG/O4GyRzGBWU47qHkDw5NlG7pOCw2zsFBnS1RHAS2qAN1Pzj7BXs/JYh32YUVX9AKchSA28U6n2r4WcOkeXDviGbouon0BZKjA+N08wZZZBtDPF+lh77rI5O2tgzqZ5riKoBzl+byCFNg3TcazEf1aLAGT6v3sp7eWjie25c993/3pNH4XFde9p3EI56vuHcOfETqVw2LGfsgxo0iMfVskXpA5QbKxbIQimqgOhbGL/nA7OCdDlU4EvIIkuL53ChxPoQoj5AQ9jdV8DgXAyft+cgqjVdIp9R44VYS1aZqciMZaKO8TIfCpite4/94y474w80GAcId29ukZTIgYdhoajzr0hpilhX48xZV3wwMcxpXkD9LErg+PYc5IipLHprh/jIN3dqAPE9K0alqokynUjPtvKIrQs5qu63iKQr4omxcL9365tqbTUc66kio/lSAtIvlNnxQnmA7U6O4swL13L9EPahwIaWZnkS2JOSBUUdLDPxyK6sUjInN5GGDGYcmjL+/Dn57SgxfCb72/R2QxSkF/6Ai2DMA9fAR364Dego+JnEYfXIF7+Ig0KaazBEM/bqHHO0R+EzgqIkX/7iXg6n4ap6aFGg2hDo+g94njMXJUBO5JJqKJE9fNa9DHgVQnVHjUzghubwx9QpWAx28fYP8/OyjnInQYDjCPT6FDExQAyiuAJiV9eQ/+JBDE7CXyG32Pqx6B52FvAn10mnotbhxAWwt7Ygn6DcBe24WeLqEXOfnN4duXsfdumVVDoBVcoVF+cgw7GUGLHg73pRtY3BxhFKQDVT2Au7IHfbaAG9VRUhAAMKzR3tiNLNyRM3M6w4ffHUQ+CuWBdlxg+NEgQrgnH40JQ+F8rHq0E6AbeQweKVx5d4Bf/CGN2dffvwJ9dEIRGUd9SqP9yg00uxV2lg0AmoSm37iOg+99gOUvrseu1dntGuMPd2CHBeARlz/zqwXKucfOhzuYfTlVQ+yjzaeAZwVlbW1rW/uC2avPwbmOQ2FdIxmQknWbcGzytoxRCJFJ5E0MzNErojncnMaJwnOiF24Ay3AWJil78Xqez6VD5BDZpKoq6/6UIsjSx2xstInZ/niswDG5Ip7E49YbMzUYZF2j9CUlSPm3okej1HUqwn3O58RzCY0UyaspE4fxekXlhUJwm8ahoZyDCkpajD2J+0VMxigu9ZLaW+qYlduy76qqYnNd5MJ0nipUAk7Owk6OozjBmVl86Q5cUFyP/i2WsWHON21KxnLDnFAj82dz4NoV2vbjB6lFvUmRhQoJVzc7i+NoJhPgzg3g7icJ6FYUtHzqEQyjLCjPE5rk2H44/Qccdw83ynK++suQdfYiJrh1lY5NVNTj+Z9AziKOJ//ubXhwIomuyB/01LPjRLAOocjHXkEFurzXQ/i52m7fmxCkHyvWy93M5zQReJdXfJ6AeM1K0EjLk9T7sqYtHogTRbaN9EWOz+yM/NLiBSJa672YyOAStYCciON96BEf+c7l+RjZ6n58kvIbSqd8Enfv+kDK43wEXEUGc0UCSProJF7/ComRd3CLJSW6xX138wX0g0fU/yPHixXpgXR/lmqtMJN/ChX113OyOMc20il98gHEMUiGznf5358FLZoxV4vKRlbl0AqQiMdQavSOI5B+Vebp3XgWy3yUGh1Gw3culTM1yP+om4H0wFrkLOM9fdWn9kXqtGq1MqEqgWHx1lJitk+y430kC4r3/FnHVKvsHm9Eta+p/Bz1XoV/CsjLtsYAbs0kzj01vA9AkyN8GhchIfC8r9hXf7K4KIqQWfSnkGJbPW4PouwsXNPf7ilmoXNo4eLxQxWGP/PNTm9Pk73xpN9rtTBfpGURDtIyiiMCXiq4VLaMeAofOmIRriXS3ac39bM+lDweSnM3b6o0AYAXREErlPp8bn6zhwdJAc89nhxlpf/brLK1ttdDVNa8dTGZmXUzx4T9Ob/rQG6UEQ5x9MHj7Rgz8xwXGGyb4Nza1ra2kb1ZkwW3Dz/ttufsswKzfl6ToWr/c0RWps9Z2H3ecT4L6/vDvqz5PrV369zfPm9odni1lvPi6VxUyae+aVqGqCKhP9f6JVv4n2NM++fgVv3Yir9+J/q3z7MquUfFtT7h5GHJKtG0yZcXaa/+MuRp7Clo9WK2PCS5dF1HjUuA6OtWljXheMok0I9bLom6jsNerhgMh5niNQBo1tYESMciZKXdfA69Q5gLe0TgHlXVcItFFFGS1QylFVQ1zENqPr7QsWRaPte0sdri5vP4YHtrIz2gCzgLc2mcQFBCm5RFiQBAXz+Au/8wdb/y8DRtIKtZ7ZrUw0FW6WF/WT0+6pgOBgSQE1SBbjqD79pILaiGQ7o3bZsIlgGo61dJN6RnqioJq1JVsEfp73pnDFXXwq9hFJZCVSahI1CVAcM66YYMh4ThOD6B+823kvgQ57rO5sANEhnSJ9Pop5+ECklJ8HE9W0IfHqP9CuE0zH//jCouTiYhPczBFarcPDqM98XcuIbTt29h/G8/j8tYNd6ha40KZuEvw5qwJ0cnUdwKANSvNqfVez0ni004OC88Rt6nEN8wMjnVL9vKXox+AqpvkWhG+KQ1EMp/UPO8Ga2s8v116I9Q4l/pu2xe40ShZA/P/Gzzc/G/yq/6XhQpD2HFccsqfu+Hg7Sf9NtymXhNbkf6K/ftEcuiKICuS8zisTlNbFOVlGtwLhNm9vUgF2oGKMqoKsAs6FhyHIuCWtGlX1UJNMga6vhvqqpSg5qYJNtLFWouRzoXypQt/CiUSZs2ws/dTpicKwNbG5QAzNkAzS7tPxQJV2mqqoi93JhU6agrzK8YTMSE6YcDErJi/8Lv2Y1qAv2VJd2/OD6bRx+vPs6ib087KUhjbU2eXIB0LP6bxE+cd37kkUmUUOTjsPXLm9qI/drsXIwhiG/lKL+oVv3l3oFeAlT1fuCRil+ojUcIdzhWjFicj36slCiVzjpw9c6I6v1iHICQKDxv3NbommbK6hyKcxZfYDKycmbYL5YBxYOlR6MU4QlToTwJY7LEpyqroIo2j9fC6umKzxsPHsacE5ChoctbR+jUEHHQthq+7aBZMb1p0+8mRHiRfatp4ZdL6ICk7e4/XFvO08Mh+S9V4IsC+voB7K8+Tt8FXEpfsJnkAQqi3OOJTSv88OTv33CcxdOYmFxiiznWYxRW8BNrj8fZ/V600bfzcBDMedg71yr4S26H/Fh9RqrgF3Wn5iVWetDPv5xYYTAG3rvcj3hO4TdAEHauLmzK4ZiNxypWIRqX+7hSFHApQJqsMjp8MTc5KWMgT83nX5FOaDOsBx2PKhtqMFjBumTLSueJpq4q4YWkoLzeyMIdryGv2CmlCIPRdmAI99rfDV9z2wFapaXj2Rn8p4f5OLJMhJyEw/66mtD1ZRWXz56Dc2tb29oXzF6/yKKfnzgvZ7FmuZLN6hz2hzepHo0Ilsv6HLNZvmyJx3RQRSJRcfN5Ds0OYbieTAKjtUhwCvV1d3Sckp2zM5gDgvva+w+iP26+oFC9aaCKkCBrG6jBgM7J3aHhFLoexIaseI4AUdYMPRbLBwkzZw0Sc3AAz01lrABflkSFxyH8l24CH31M4bqg1fNn87g8yQfeQY/H0V9VD+i4VRmV4Dk0VnVNHarh7acv7cOdkMi0Dk1+emcEv2xoCSgTrLevQd8/XK1AlCVpgAwGcI+SqoXe34caj2DvkaixKgq6P11HBMUSdRq0UxjWzffRPjpE+53fw/DdIIzsKeLwp1P4O9dpTI+mMWdh94N+C+cspi2K+8eYfoO23fnXn5AQdA9sZm5cg68r+Hv3473Sv/5lPPjWdVz/p1+mMdgdQx1PI68HL0vduAZaC1OW8HtJW0b9QuQvLrDXb7IAqPszrO35s/wOQN6Nugaspbnj82RKod21q/CnU2B/lzb42fvQVRlUrEQW31rq+twNIjN379G+d+/R/7kb9uY1qMOjoA4Vuk4PrqC5TZ2T5U8AXKZzmY8foPntO1DOQ4fuVXXrOvSvPoHa2YE7OYEOGWz76BD60iVgbwIV+CR5AtDXrqK9nQRnip9Yynx/8gCKM/MfkZ8s5qOvXaVx+OBDAED3tdsoPqUHWIcuUX9pjPbaBOUhnefud6/g9j8rKGuxvEVrbWU9qgdT6F8mfmbfdTHUVreupzbuq3uAUuj2hih+HtbbE3qIuuu7KO4fR2r97jduofg/BffoEOrmNQDA4s4eypMl9OkCdn8UCXM/+s4EN/9jBGcUXMWAN8ANFHbeP8Hy2g7qd3iCdWh/6w6Ov1Lj6j+GCXSyg+bWHoppg25cobqXKifu0gjTt8aY/IgemeYWdZ0W/zXD8Z+doP0bUrzQncdiz2DvZzN8+F26Z3vvXSIWbgccfZ18tfsdRntzzO9OcPDODg6+9wGd5/0b0A8e0UMu+nhO376F+RWDa//i4D+lCe/Bt67jnb/4S/zBwz+GCquJo68W2P/pLtoJwcmZmWt2S6GcAfvv7eLx18KLUgHN3z5hjdqz1y/BCbyQakgGB1Y6TgwyslBFka9pRdu7bCTicp80PRolPguG3FZVOv58kXxoWujdCeA9bHhzcaTDDU0yMaqqCpmGRSTsreJ6FgDsdBYjk7jOlT0M3sU3Ovtv9nZT6dTaBImuBOHulX34x0fkV3jDwtlYOo1JViELqId1PC5HVEqp+JbkseAEXZRKHI1obd51SZFsWCfyG9aIBaD2d+FPTsnf2AMSiHeWyyySgfM06V8aw37yIN23kKtQxmTJUlKBq+P+UpEOv/87MD8XScZ6QJHMVZq41WyetE7HIcKrS2K4shb68BTNr9FkXv7P+xRV9bVOxztQZQl7+DjxWdy8jtNv3sHknbuJwGdQxdJp1uhXlTRms7PY4AYA/37/Bzhe3t8mOF+6rVPijp8FHJiXOutgwf3vPuvJvZ8EZDaqHuQ8fZbXRIlfFcrFWbVC7hNYw5/bx6hW3vMtkyP4HF6G6+7RBnT+yvuY4+YKu/c+NZJxYpUY8dYfwwFrqf+jb8/aKLVq2wTn1ra2tY3szY0sLlqeyFDZuyBRn9enV8qT4bgSwUnJxyLVvyWvgLVZKTMmCpUC5ou4JPFNQ9+LtwCVMpdpKSS7VVUQK7Z5+ZASdEI3JCx1fNul2jovBYwhPuMiLacA0P4hwYkFRQAqIEM5Qen2xlDHp4Tg5GWPc1TmXKrsTR9Ls1WZwuoygKOCpgn9vUrnl8M9GkKxojwvVUZDSka3AXwUzmEvj2GWDTIov9ZQQwPvLPl6nCjoVD0gIFfkfCjp/G0LVZZJJCj4r8Y7BHiSfk5nmN8cYvIwhPbeE+N528JepbyWUSoS/LJmhx3okODsUDUtZreJuW33x+G35Fx+z8c7BLiaztLybneMo68WGP8oAePc3hjaknaJcj4SLbtJDdVaaADushDPfrR5zuLNmSxWMA1r8AnSevX4yGu5RuAlbUThHrU9p/CaIeNrjycmHNW2BAPWgVuAcwPOJxo5wUsQuzq9y/ztc28mzEOXQZSjn5LnQuITJAku73MmtU5dQnMCCe79+FTkPubxuKx1mo0X41KaRDAccxd2DaSer52vkTkpmXsUAGaz4JvN/DOfntA4SvkFAFCKJjqxZPHOJ15OwcHpmQE8EMVEC2zmcWwisM1hdHdGyXE+XVHAzxcoHhB2ws/OaKJzDmUgQy7LgqQF5g3UyRTjDwOt4JL89MiXV346I4Jj/l0AUMdT7P90F36aeFe1daR2vzDwQCRbMk0LdJaS2mKsVfcmcXBuas+D7EQAyPTh3udtK4R3Pe/b34jh4zKyYB2P2Dik4vFQFCkSAhJMO500/6wF90aUl1ArDUjRt951MSeGvI543j4fBR/XhAeNafKdi4Sw8ApQPSCQkz4LyLq8xj7PBGtmSAg2jxVvUxRQroVXuX6pr8oE6e5FYl7r5Cv7yPB4wWQW9WaNyVGQWlPkZvKSJAC4uoThCM17ilL1An4QelmakkqZ3ielsKqAKw2M91CzgjgzAWiGc/f5TYqCIjGJLC0M2onJIO5+UAILExK/LmmtVCXd64DkTPdk84a+N2eyeBVtQxaejPvgoojo87BNkmX8eR3aUMLQP+sO2ZWTB2SsnKjMmiRrtv2LOOcF/79wm94xZeL2SWPocw1X5ZiV6/z786z25k4WF+Us+k1YWodGqAtmWtl4xv/XKUrI3sb9yALI3m6RBZsFhtaeZ40//dZ5+Xbubx9bsNe0u6+LpNa15evemz28db33ud/9Y53HHiWV4+O24nrl+ddtww1y3ufnKAxYdT0DZrEwz7oxLkx+DqOhfB6FAMiEj3g79sUNUjSmnIvq5dx0por0d/7OVQV8pUnXw+jIwl3FSDCPLOT4xwqTMehqHZc4AEhRzegUqTI4q+D7pTLBqKeJLLbVkK1tbWsb2ZsbWVxkvTdwrF6sazePG1Gybl378sqmZeChELRvqkjVA2US54AHSGVchpNlAcxTLiWygrehGlKKTlfmPmDwlPSL3268Tp2Lv7luxXcJvoqVHaMDzwO9vdykhn5goNhvtsC1wSY5N1VRAIb1VxIAi68r8lnw+QW7N3Ohxm3qAfwCUN5lreL2Uo3ipApvYeFHWQTFddGODhCYblTHKITvj1dUAYJsDisrYFhDMVxegN8WV0pUoe1bOU+ViMUS3W5Qi287+EEBOFIzB0hO0NYaVaGhZzXmV+nahmUBLEOuSb7KhzW1mRepU9eNa8xuKVwVY+AmNUzTJg3aEEXYSzXU0sI0LexYQPTN5vHCmztZBHLdDO4tlyR98FHgMcy6FldUzkJfiGRAUpp+hNNwTkbZOALmyOqAt1YI77j0OXApZqcKnZWRRVtWJSxxdiYpPiJcUSZfVnApVYtEV+pENbRf5D2gPhiWIKTjimuRD3CbPmd+R+7JNbkaobAley4ieY0JSwhjqL9FJBK5TBz37zpCjFqXMVWrpV0ZR2aS8l2X+Cp5HLsOatHA8XFLSv4p52Bv7MNwaN/ZNClGNjAFPxzAjHdQzF2qKngPtKF1ndW+rIVqaT8tFcAUYBZUeSnnYczbLirRSfNaUSm3LKCrUPpsLcoZIr8FEO5NZ1Pimif8pcX89g7GR9OUw2F/N7TXc7LotWuvfAeIEqFd3VZ+z6VK/iF1TxhI76nxzJuUVPKOSlecWJOlT0EdH88RSptelmm9y0qevG0s0/p8EmPZwVheDJOcBjJGZ79cAtYSUxb7ZS2Y2t9bG/tKIg/FPDVxrZRVubnr8BRuTYmZaPvPabEW7d0ZKS3LJ/L1tSRpyG9PbS21nnct0ITrmuugFNdlSVdzeLIyjtCKiGiadhXtOV9kk5ufncVJTX/QUENX9HMBNahyucfZGdzZGYZ3p6l8GfI4frGA+TSUTqdnlLcAYuk0Ci2fLYHjKXa4dCpKo5kdnUCVJRzLHQAwZYn993bTPQTlFfzsLJEghd+CaVqMj6Yk2cg+aAW1KcUAXtfJ4kX0hkQRmvBWKUhcJgMpnceUJcL9KNrS6w1Jb0PxnQBNqfkiA0pFkM/JSdyWSUy8FBZyFC2pqkpvDU6iMqiI/QznULI7k/UnDC0j4pt9uaTrHNariu1VlYGl3OUJFNPL9UBUFLqv/gAliEwCsBIoK1HmZUuF4ZCYpqxN+w2HgGmARmddp/byJQJlZSdWxIbVdQR8E5gEDGvqk4hUhhVFNU1L/StZBFRBjUcJ1DYcUhQ3nWF+Z4yd4zRZ+LKAAqK0ozY6dp0yKMtVBnaoUR0NUHgfJQUn71VZtBQvYzImUNbsLPJR+L0JHn+twq0fp14Pd3lCLw3uXeJlyHgIGAXTWZLQDOYfbL4M2SY4t7a1rW1kr2dk8bra8zRPvan2IsfkGQ7l17FivyDzGxx2k20y6/l67v7nlUSf41q/uJPFOjyCVi/ux8s/wj6aVuIJ1mEIpD/Sz7562TpS1x6C8yLzzkP3llpK66RALs8nKgy+kLT/52Ai+iZ9Xrdv3E7neYWoIJbUzzgZqlSXYSe80avXH3Ewq3+ja5X4jycn/nwfIxPIkGwlEsvex9+SLxL+hfEVvgwEupWGrTSKkva1lcSZrP4GvSFfFVLSEsbA1sgwId4QbiP6WqTzKkfLdW+e8Lt7gr0SfBZKqYcAZgA+fdm+fM52Fdtr/iLYq3zNb3nvDzbZ8JWYLABAKfWO9/6bL9uPz9O21/zFsDflmreL6K1tbWsb2Xay2NrWtraRvUqTxV+9bAdegm2v+Ythb8Q1vzI5i61tbWuvtr1KkcXWtra1V9i2k8XWtra1jWw7WWxta1vbyLaTxda2trWNbDtZbG1rW9vI/h84Sb5H4RZmVwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.3496720790863 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1e-05, 'kernel_type': 'branching'} is: \n",
+      "[[1.28108837e+03 9.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [9.60000000e+01 3.56163732e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28108837e+03 ... 1.28108837e+03\n",
+      "  1.28108837e+03 1.28108837e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.28108837e+03 ... 1.69515441e+06\n",
+      "  1.70441574e+06 1.81435152e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28108837e+03 ... 1.70441574e+06\n",
+      "  1.72852267e+06 1.83967993e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.28108837e+03 ... 1.81435152e+06\n",
+      "  1.83967993e+06 2.06039156e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 86.84979367256165 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 0.0001, 'kernel_type': 'branching'} is: \n",
+      "[[1.29091662e+03 9.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [9.60000000e+01 3.57641967e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.29091662e+03 ... 1.29091662e+03\n",
+      "  1.29091662e+03 1.29091662e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.29091662e+03 ... 2.24159016e+06\n",
+      "  2.27107602e+06 2.51960599e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.29091662e+03 ... 2.27107602e+06\n",
+      "  2.43129540e+06 2.79013419e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 1.29091662e+03 ... 2.51960599e+06\n",
+      "  2.79013419e+06 4.45397864e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f548227f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.17020153999329 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 0.001, 'kernel_type': 'branching'} is: \n",
+      "[[1.39252087e+03 9.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [9.60000000e+01 3.72896146e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.39252087e+03 ... 1.39252087e+03\n",
+      "  1.39252087e+03 1.39252087e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.39252087e+03 ... 9.69101197e+07\n",
+      "  5.36681399e+07 2.79451798e+07]\n",
+      " [0.00000000e+00 0.00000000e+00 1.39252087e+03 ... 5.36681399e+07\n",
+      "  2.69417050e+08 1.16029109e+08]\n",
+      " [0.00000000e+00 0.00000000e+00 1.39252087e+03 ... 2.79451798e+07\n",
+      "  1.16029109e+08 1.44975529e+09]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.36908531188965 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 0.01, 'kernel_type': 'branching'} is: \n",
+      "[[2.80544997e+03 9.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [9.60000000e+01 5.86481341e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.80544997e+03 ... 2.80544997e+03\n",
+      "  2.80544997e+03 2.80544997e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.80544997e+03 ... 1.20399658e+19\n",
+      "  4.61493764e+15 9.27665568e+11]\n",
+      " [0.00000000e+00 0.00000000e+00 2.80544997e+03 ... 4.61493764e+15\n",
+      "  2.21222907e+21 1.61244377e+15]\n",
+      " [0.00000000e+00 0.00000000e+00 2.80544997e+03 ... 9.27665568e+11\n",
+      "  1.61244377e+15 1.39477775e+20]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.50898051261902 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 0.1, 'kernel_type': 'branching'} is: \n",
+      "[[2.63928626e+05 9.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [9.60000000e+01 4.62700516e+05 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.63928626e+05 ... 2.63928626e+05\n",
+      "  2.63928626e+05 2.63928626e+05]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.63928626e+05 ... 1.59580515e+62\n",
+      "  2.88491682e+43 6.71218865e+30]\n",
+      " [0.00000000e+00 0.00000000e+00 2.63928626e+05 ... 2.88491682e+43\n",
+      "  1.07078764e+69 2.79494631e+40]\n",
+      " [0.00000000e+00 0.00000000e+00 2.63928626e+05 ... 6.71218865e+30\n",
+      "  2.79494631e+40 1.41114644e+58]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.26246118545532 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1.0, 'kernel_type': 'branching'} is: \n",
+      "[[2.21682772e+012 9.60000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [9.60000000e+001 3.48898422e+026 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 2.21682772e+012 ... 2.21682772e+012\n",
+      "  2.21682772e+012 2.21682772e+012]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 2.21682772e+012 ... 5.59506848e+202\n",
+      "  1.29639183e+131 1.49801341e+092]\n",
+      " [0.00000000e+000 0.00000000e+000 2.21682772e+012 ... 1.29639183e+131\n",
+      "  1.15004882e+217 2.78311843e+116]\n",
+      " [0.00000000e+000 0.00000000e+000 2.21682772e+012 ... 1.49801341e+092\n",
+      "  2.78311843e+116 6.74779575e+168]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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CWAAIISwAhBAWAEL+B44uIWF7AHb6AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.63899779319763 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 10.0, 'kernel_type': 'branching'} is: \n",
+      "[[1.16133129e+025 9.60000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [9.60000000e+001 1.05460835e+072 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.16133129e+025 ... 1.16133129e+025\n",
+      "  1.16133129e+025 1.16133129e+025]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.16133129e+025 ...             nan\n",
+      "  2.98498320e+291 3.24981756e+205]\n",
+      " [0.00000000e+000 0.00000000e+000 1.16133129e+025 ... 2.98498320e+291\n",
+      "              inf 1.81116484e+255]\n",
+      " [0.00000000e+000 0.00000000e+000 1.16133129e+025 ... 3.24981756e+205\n",
+      "  1.81116484e+255             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.59246325492859 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 100.0, 'kernel_type': 'branching'} is: \n",
+      "[[5.81411829e+039 9.60000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [9.60000000e+001 9.48010514e+124 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 5.81411829e+039 ... 5.81411829e+039\n",
+      "  5.81411829e+039 5.81411829e+039]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 5.81411829e+039 ...             nan\n",
+      "              nan             inf]\n",
+      " [0.00000000e+000 0.00000000e+000 5.81411829e+039 ...             nan\n",
+      "              nan             inf]\n",
+      " [0.00000000e+000 0.00000000e+000 5.81411829e+039 ...             inf\n",
+      "              inf             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.74905443191528 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1000.0, 'kernel_type': 'branching'} is: \n",
+      "[[5.41181482e+054 9.60000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [9.60000000e+001 7.40661671e+178 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 5.41181482e+054 ... 5.41181482e+054\n",
+      "  5.41181482e+054 5.41181482e+054]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 5.41181482e+054 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.41181482e+054 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.41181482e+054 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acda90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.49205732345581 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 10000.0, 'kernel_type': 'branching'} is: \n",
+      "[[5.37300564e+069 9.60000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [9.60000000e+001 7.22560202e+232 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 5.37300564e+069 ... 5.37300564e+069\n",
+      "  5.37300564e+069 5.37300564e+069]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 5.37300564e+069 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.37300564e+069 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.37300564e+069 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.21039605140686 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 100000.0, 'kernel_type': 'branching'} is: \n",
+      "[[5.36913863e+084 9.60000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [9.60000000e+001 7.20774126e+286 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 5.36913863e+084 ... 5.36913863e+084\n",
+      "  5.36913863e+084 5.36913863e+084]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 5.36913863e+084 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.36913863e+084 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.36913863e+084 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.77909111976624 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[5.36875207e+99 9.60000000e+01 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [9.60000000e+01            inf 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 5.36875207e+99 ... 5.36875207e+99\n",
+      "  5.36875207e+99 5.36875207e+99]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 5.36875207e+99 ...            nan\n",
+      "             nan            nan]\n",
+      " [0.00000000e+00 0.00000000e+00 5.36875207e+99 ...            nan\n",
+      "             nan            nan]\n",
+      " [0.00000000e+00 0.00000000e+00 5.36875207e+99 ...            nan\n",
+      "             nan            nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.21444892883301 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 10000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[5.36871341e+114 9.60000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [9.60000000e+001             inf 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 5.36871341e+114 ... 5.36871341e+114\n",
+      "  5.36871341e+114 5.36871341e+114]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 5.36871341e+114 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.36871341e+114 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.36871341e+114 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ad7978>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.06056046485901 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 100000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[5.36870955e+129 9.60000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [9.60000000e+001             inf 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 5.36870955e+129 ... 5.36870955e+129\n",
+      "  5.36870955e+129 5.36870955e+129]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 5.36870955e+129 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.36870955e+129 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.36870955e+129 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQsAAAECCAYAAADpWvKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAHIRJREFUeJztnV2sHkd5x//POY4NQUmJSWusACUg5wJa1SJWwgWqgiqffLSS4SJHdgNFCGQukt624QpUCSlShahQS6TQRgkVJD1cRERVBD7yDTflI0EIEtSABUGJ5Y82RiQiqoPPmV68u/ZmzuzuM7vztfv+f9LR+579mHlm3tlnn3nmmRkxxoAQQvpYyS0AIWQaUFkQQlRQWRBCVFBZEEJUUFkQQlRQWRBCVGRXFiJyh4g8LyKnROT+3PLEQkReEJGfisiPReTp6theEdkUkV9Un9fllnMMIvKwiJwXkWcbx5xllAVfrn73n4jIB/JJPpyWMn9eRE5Xv/WPReSuxrnPVmV+XkRuzyP1MLIqCxFZBfAvAO4E8D4Ax0TkfTllisyHjTEHjTGHqv/vB3DSGHMAwMnq/ynzCIA7rGNtZbwTwIHq7ziABxPJGJpHsLPMAPCl6rc+aIx5CgCqtn0UwPure75SPQOTILdlcQuAU8aYXxpjXgfwOIAjmWVKyREAj1bfHwXwkYyyjMYY810AF6zDbWU8AuBrZsH3ALxVRPankTQcLWVu4wiAx40xF40xvwJwCotnYBLkVhY3AHix8f9L1bE5YgCcEJFnROR4dWyfMeZM9f0sgH15RItKWxnn/tvfV3WvHm50Lydd5tzKYpn4kDHmA1iY3/eKyJ83T5pF3P2sY++XoYwVDwJ4L4CDAM4A+GJeccKQW1mcBvDOxv/vqI7NDmPM6erzPIAnsDA/z9Wmd/V5Pp+E0Wgr42x/e2PMOWPMljFmG8BXcaWrMeky51YWPwRwQERuFJHdWDh/nswsU3BE5C0ick39HcAagGexKOsnqss+AeBbeSSMSlsZnwTwN9WoyAcB/LbRXZk0lu/lo1j81sCizEdFZI+I3IiFc/cHqeUbyq6cmRtjLonIfQC+A2AVwMPGmOdyyhSJfQCeEBFgUeffMMZ8W0R+CGBDRD4F4NcA1jPKOBoReQzAbQCuF5GXAHwOwANwl/EpAHdh4eR7DcAnkwscgJYy3yYiB7Hocr0A4DMAYIx5TkQ2APwMwCUA9xpjtnLIPQThFHVCiIbc3RBCyESgsiCEqKCyIISooLIghKigsiCEqIimLHxnkzZCoJcGlnk5mEuZoyiLgbNJZ1GhnrDMy8EsyhzLslj22aSEzI5YEZyu2XW3tl28W/aYd73rXbhW9r4hQuymm9+Dnz/zy97Mbrr5PQCgurYk3oSrd5R57uQss7Y9haavzLnkAoD/w+/wurkommuzhXtX/bjjwKIyb3rxFsAW+UfArXJjf2I/WnyoriXLi7Y9pSajXN83J9XXxuqG9M6uM8Y8ZIw5ZIw5dBX2RBKDEBKKWJbF5dmkWCiJowD+Wnvz5vY3cXjlbvVxTXoABt1bUh4hqOW0KV3uUrDrb5nqLdpEsmqR0n/CldmkX2i79lrZa26Vv3jDsS7F0PaDNY/3/YhtD00f2sYxNP3QcvgSW+4mvmUYK9vhlbs70xhap7Hlqq8Zm68rje+bk3jFXFD5LIqYdXqt7DWvmAs7CqO1JKbyVid5GWqZxianXJNUFrZlUeOjCEIqjVwKaOrdBJf8JcleajciV735KAuGexNCVBRvWdT4mmou/4WPT0OTbhM7j9hvhdA+lxyWVIg+d0g08gztKo8lhOXhSkNEnmnsY9NJkcqCoyHxmHo3JzeldmOGMiufhc0YTU6l0U6pzr/SSV1vIazjJrNQFhw6DSOHLxw69SdFnZUwdEoHJyGZmYpFR2VBCFExG2WR0nwm06TUNlKqXDbF+CwYwUliU6oTdyoRnFl3JAtBCK1c/1i2g9T+EUMO3WqGMEMPIQ+hmVezHF3y9ynvUMq9LfbA5QCvj9l5h6jLtnZi11fXNV1pDnX2h2i7TYqxLNpGQzQPGkdDwsHREH+WZSLZbHwWhJC4FN8NKbGPScgyUmw3xKb0uSF1mqXPDQHccnJuyDB5lmluSPGWxVSYigVUyzkVeUtjmeuNyiIgUxkvn4qcpbNs9VhkN4SzTuPBWafjWOZZpxwNIYSoKLIb0mVV+EZ1NtPj4jdc/KaLZV38Rns/LQtCiIrJKYup9xEJmSpFOjiBshe/0ZieucKm++qmb75BLg+/LVfX/I4xeWjCqvvmbTTlrWVOiau9D8UnzmJylgUhJA9FOjhLp4SuUJsM2uOlliFn0Jiddwl1VBNCFlca1+C6m7X3z8ayWLYAGeIP28g4ZmNZhOjT+tC1VkEu2vr5XbKVEkymXZchpRxd60FkqTcRYISP0eWLuXZlr/r+2SiL1Iqi2UhyPGiuRm03hLaFa5rnciqJtliYrnLElqfLwRkiTmeMbCHytsv0qvmNOs5iNsoiJX2rIKWSwabLsmjzWeS0LNpGFLSrRMWQp7miVkmWxeGVu0dbFnU6zbq+RpbQZ0EIiUvxloVWg6f2WeTuhrjoGl3wuScHvqM7Q/MYsnyd63hquQAEsSqan4s09ffPxrKgp5v0UWobKVUum+KVhdYJV8obkpQL28g4ilcWhMydqSgxKgtCiIrZKIup9PtIPkptI6XKZVPsrFOb0lf3tj3aJSzU4sJnNmVspr74TcpYixJW915aZWGf0+ah3QrAlX6XDG0Nz44mDD1VWzPduS3wzKcBp3p7dsmokd83rxjlSrl0ALcCUKB5KEOmX+fRdd4lj2tsPGQj1SxA24xqtK/VlinEA+CKOu0KyXbd56rHoetDdL2QdtTN6vri/NZGZ5o+7e7w6jo2tzZUkaZru4/hxOuPqdN2MRufBSEkLktrWdikWMPA582bdM4B+rshQ87FYmj07JAI1770uiYVhs5vB8b0tpuQ+VFZVIzthmi6Bpr+c+wJVK4ZnX2U4tS15dF2x7rq1Leem2m5Jp2l7IZAxKsbMpYiHZxtP6DPD9s1PXssXX331A9MH9r+eA4LoeTREF9FFJsSRkNma1kMdVr1oR0ViI3mDdl8+5VIn5O5vibVNHXXG9k+73KoliDbkHQAv2X1irQsXDQbkubHyRFn0TxfQkyAi76hTcZZ+MmQSlmUYFlwNIQQoqJYy6JLY7fFBvjGMQxBa92kNP+7TNQ2i6fLL5QDW66+mI6heWh8N20yuOStZU5JyC42LQtCSHBm6+CMSY6RA60M2uOlliFFvEsbdt4l1FFNCFlcaXDfEEIcsI2MYzbKghASl9l0Q0JOrtJgR+qVYLK2OQW7ZMsxZNolR03sSFaNHJrIyKT1NuVNhkTkBQCvAtgCcMkYc0hE9gL4DwDvBvACgHVjzG/G5FMaJZizmpEfV1h3rofQRVc92rLniGXQzGhNRaiwersMPpsMheiGfNgYc7Ax/HI/gJPGmAMATlb/E0ImTgyfxREAj1bfHwXwkQh57CDHWHdpXvMhsxyb5chJKfWplaGUekvJWGVhAJwQkWdE5Hh1bJ8x5kz1/SyAfSPzIIQUwFgH54eMMadF5I8AbIrIfzdPGmOMiDg9MpVyOQ4Ab8LVI8UghMRmlLIwxpyuPs+LyBMAbgFwTkT2G2POiMh+AOdb7n0IwEPAItx7jBypKcH8ZFBWeBiU1c1gZSEibwGwYox5tfq+BuAfADwJ4BMAHqg+vzU0j1LJNYW6Swb7WBPXehtjF/sJgY+fKdfMzj5yrGcRcsa0iKhHQ8ZYFvsAPCEidTrfMMZ8W0R+CGBDRD4F4NcA1kfkQQgphMHKwhjzSwB/5jj+MoDuxSk80L75UgZllWDS+458tMlcwshDyvyGrjUaE+1s2BD52Czl3BBCSFxmE+6dGoZ7hyVFuLfv4sSpwr3VFvGUw71LItcCJPb3nAwNyioB39Gd3HJkqbeRC1U5u54eSc5GWaT0WZRgSXS9AZv4rpSVkrYRnbaVssbS10bsdV5L8m9MfTRkacn9kHXJUPSb0YJxFnpKcHAWryxK+sFqSn0r28eb52hZ6OShZdEOR0MIISqKtyxKJPcbuUsGdkOGk6sbMpU4i9koi9SrZOV+2NgNGZdf2/kc3ZAxQ7pj8/HphhS7b4iNb+PWzp3oGkvvS9eVVl8jb5OhbdzeNYcj5P4ZffNKmtdry+IiV3Rt10OWYh+SoenaxKo/7htCCAkOlQUhRMVsfBa+DIl2HJv+mON2xGgss9RHPp/6CmFaD/l9uu4J1S3JOQHNh7FtZmmVRQxKWPVbg2vVb+LPstUdlUVFiMVgNOHEzWtd51KMVvhaJppFder/U+Dr7O2q0xD13EyjTbbDq4tlXTa3NlSyqhDB5tZGp5O+lmFt9zF9ui0srbJwKYWQb4o+paN9yGKMhnQxRol0PXghZHblN+Q++3gK2fqURPM+rcKo09TUy4nXH1Ol2QUdnIQQFVQWhBAVS9sNsWkLPPJBE7KrNXlj9v+HjEJog7Jy4xOURfxYWmWhiZT0Ta+vYfo03Fqe0EOnQ8KY2/r2Pg7OkEOnXf6brqhSW+HZStDXWeojWwwH5+HVdS8H51i/xdIqC5sUk4d8HqaS3oK+SiA29gM/5L4h99v3uV4sfbIFrS9jettNyPw4NyTg3BAXJc4N8YVzQ9LCuSGEkElTpGXR9ob3GoNuCZQJQVffPXVgUh/a/niO7kSKcG8fbCvEx4cRGx8rzicNH8titj4LH6eVD6WMCmgiETe3v1msqQ30d7nqa2JGs7bJ09ddbF5XgmxD0gGWdPEbm74fsS2CU/PDa36sLh+ETSifRYxIxGaeKXwWbaMbQ4ecQ/osYtZ7E63PYki+9j2TX/wmZDck9Dh7KeZ8igYam5K7IT6kqDt2QyIypCK1voehoxOat1xbTIBLhra0Q9OW9lhl7GNau6719Su0WUfNYfO+GJS2N3zsOIvDK3cDK6vA9taVdAdMJLPlukb2cq9TQkhYiuyGuGi++X39Ci5n51DTsest2zw/NZM59WhOM08tJdSpxrEcgxK6IZOzLEqKbCRkmSjWsujS2H1x+c1jbYx5M8eI9BxDV9+/zeLpciLnwJarK5ZlTB4a30ibDC55a5lTEjIsYNaWBSEkD1QWhBAVVBaEEBWzURYlhzWTMmAbGcdsgrJSTt12BWWlHqXROCebsrWtc5BjyNSWoSlH/V0bnBZanmZ4uSbYKaVsEAFGDkjsDMri3JColPCG0oz82A9g89ocCs6mqx7blEdKefr+T0moaQt2GV41v1HPDZmNskg9VJlbYWgaTFf4em5FYcvQNeSbw7JwyZd9uDSzZTEbnwUhJC6zURYlvCmJJyuruSXwYtf+t2fN++VPfzB4ujf96Wt6GYLnnonc3QIygO2t3BJ4cenM2ax5v+1fzwVP9+c/vVp97WyURUrs/mvutSDapli3TZ1unstpkbVN9usqR2x5usK9Q6+N4itbiLzHODhn0w1Jzeb2lSXrSrFqhqym1CxHTkqpT60MpdRbSqgsCCEqqCwIISqoLAbS7O+XMhLjkqNPttx+C5ccOeXRylBKvaWkeAenNqw2dbh3bjrXalQcL7UMMRWGdo2KEpSWTQhZXGn4bAUwG8ti2ZxNxB+2kXHMRlkQQuIyG2VRkslIyoRtZByzURaEkLj0KgsReVhEzovIs41je0VkU0R+UX1eVx0XEfmyiJwSkZ+IyAfGCriMXmdCSkQzGvIIgH8G8LXGsfsBnDTGPCAi91f//z2AOwEcqP5uBfBg9TkrSlsLIuTq3inRhns3z8eWZ8jq3imIteeNz16nvZaFMea7AC5Yh48AeLT6/iiAjzSOf80s+B6At4rIfq0whJByGeqz2GeMOVN9PwtgX/X9BgAvNq57qTpGCJk4ox2cZrFLkffyPSJyXESeFpGnf4+LY8XgGDrphW1kHEOVxbm6e1F9nq+OnwbwzsZ176iO7cAY85Ax5pAx5tBV2DNQDEJIKlTbF4rIuwH8pzHmT6r//xHAyw0H515jzN+JyF8CuA/AXVg4Nr9sjLmlL32fjZG19G2MbJ/T5tHn9OpzzLXJ0BbWbjvbQm/jp9kKb8cK5iurwPaW12a9uULxuxyDKbZDHJquTaz689m+sHc0REQeA3AbgOtF5CUAnwPwAIANEfkUgF8DWK8ufwoLRXEKwGsAPuktPSmfia1wRcLQqyyMMcdaTu0wBSr/xb1jhSKElEfxs05joTH3Q6Zf59F13iWPawZkSPNXE8/QtnpU19L5NiFMa1fMiGZvj7bYErt75StPV1d3R92sLozvza2NzjR92t3h1XVsbm2otixY230MJ15/TJ22C4Z7B2Qq3vapyEnKQuXgjE0JDk5txOAYB2fbvW0OR1c0YWgHZ2hyOzj7yLlRkJbJOjjnStvCK2N+FJ9uhlbxxeiG+IYxa5Rc271D0u1Lw1dxdr0QxnRDfGSbQzeElkXAoVMXJQ6d+rJj6LQhm+taF3McOo1FqZYFfRaEEBVL2w2xsT3+Q0ZD+t76Pm+HmLNCfa2TEvbz0NJX/7ln2k4ZKouKNlPbh76Hyechjdmoh3SltN2Q3Ph0Q4gfS+uzCLkmQDPNUHEaY+TooyvcO+UDNdb/E5pQSjQGPv4hnzR8fBbFKouuH6FteNI36GkI2gaS8q3bNRzYpgzaypDLWnANGdvnUwwZu4aru+StZU5JiNGbGjo4CSHBobIYyOZ2GRv5NnHJ0Sdbsxw5SVGfmnS1MpRSbymhsiCEqJiNssjRb3RFV+akLSq1754S5C+lPrUylFJvKZmNskgNuyFhKaU+2Q1ph8qCEKKCyoIQooLKghCiYjbh3ilnY+aY+emSQXNNW2RmCc45bTBZKlm7pty3Tf1OxeGVuy8vlDw2nabs18rem7X3zsayyP3wEjJ3ZqMsCCFxobIghKiYjc8iJSV0eTST5prXaCeSpUS79keumZ19/6ck1FR7uwyvmAvhdlGfCqkbfikRh00YwdmTx+p6/zWM4GxlNsqihLc9KZu+xXJJN8WsZ/GKudC6WG0XsRa0ca1b4VoJWrO+hY8i0yxGo12Lwke2UAvtahYAcp33GTr1lqlaBVuTvu/Q6eU6tlbvdg2vr+25Bycufr1bVodcl79bQ6dy1W5nepdl2nUUm5ced56r+YOVt+G32y9Lp1B1fqUoi7bFb7QNq62xtTFm8RsNsS2dWCZwrkV7NJRapynqLMRCRa40vm9O4hVzQaUsZtMNIYTEZTbKYtmcTcQftpFxcOh0AKUNO4ZcgzMlbYsqD+lWhpJnyBqcKYjlmxOR+QydaoeoUo+GlLL+QhOuZ9Gfh/aaqdRbSopXFloYZ8E4C00e2mumUm8pmY2yIITEpdihUxvfPnZbf9imayy9L11XWn197a6Yjrbr7fNjzV9XfppyacviIuXyAW35jo3XcOUVo1whhkm1+OwbsrQOTs1DGTL9Oo+u8y55XGZxyEaqcSS29eO71n+wCRkn0KU4uxSYrfBsJegrT9cLaUfd7Dq6OG8FSbXJqqEOutIEj91+9cfxndf+XZ22i6VVFppgr9Dpu853XVNfF9qy6MInbdeDGtOyGDqxq+26kA7VPtn6lETzPnXgX5Wmpl7GKgpgiZVFmzNwTGSnj+WgbRChLYshQ4Jt15doWWjuax73tSy60uqSbQ6WBX0WAX0WLkr0WfhCn0VaSvVZcDSEEKKCyoIQomJpfRY2trMrRsCNr/OwlKCf0iJVu+iSsaQ6nSK0LCqajsShDSqUU9P3Wl9sZ6lW7vraO2/422IfulpGV7lCy6xZeWtOFKks+pyAWuoGU8fxtzUi3zTbjtmxESXgkqdZj3bdaLh05mxQGUtEUxebWxtF/daxKVJZEELKY2l9FiEjOLVDiDkiOH376YzgjCPbHOIsZmtZDA3h7cPV4HLQ1Te3KdUx6dMtTFHPvb4bh48iWfzI6jrW9twzuh7s+69dvV69feHkgrK0b8q+oKyhlR4imjEEKSM4YzE2wC00PhGczetT1JlPAJxPGj5BWcUqC595Bq4HINbb1qUUtNGNseizolzdq7ZuV8lWSImy5YqoBcL8VksZwZm6O9DmT8hJ10hN1z0lyJ+iPrnJ0DhmoywIIXGhshhIHZ9Qfy8Blxx9sjXLkZMU9anZkUwrQyn1lpLZKItl++EISU2vshCRh0XkvIg82zj2eRE5LSI/rv7uapz7rIicEpHnReT2WILb0GdBn4UmD+01U6m3lGgsi0cA3OE4/iVjzMHq7ykAEJH3ATgK4P3VPV8RkdVQwnaR2rJgNyQsSbohinTZDWmnV1kYY74L4IIyvSMAHjfGXDTG/ArAKQC3jJCPEFIIY3wW94nIT6puynXVsRsAvNi45qXqWHSWzSQkJDVDlcWDAN4L4CCAMwC+6JuAiBwXkadF5Onf4+JAMa6QPDBmdf3yuH0pU5VdcvTJ1ixHTkqpz3oOR/3ZdV3fNXNjkLIwxpwzxmwZY7YBfBVXuhqnAbyzcek7qmOuNB4yxhwyxhy6CnuGiPEGaFmQPtb23JNbhEkzSFmIyP7Gvx8FUI+UPAngqIjsEZEbARwA8INxIpbJ5tbG5XF7zfh9Clxy9MnWLEdOUtTniYtf75ejXl6/Z3bo5qXH1cv7z4XeKeoi8hiA2wBcLyIvAfgcgNtE5CAAA+AFAJ8BAGPMcyKyAeBnAC4BuNcYsxVHdEJISnqVhTHmmOPwv3Vc/wUAXxgj1BCWbRiLkNTMJoKTPgtC4jIbZUHLgpC4FKMsNGtU2OddS5mFCsO1V8NKZbn05UULiuSimDU4fdfEjLUSliv9lFaLJsyYkBwUY1kQQsqGymIgnHUaFs46LZ9iuiFTooRG0iaD9nipZcipgO28S6ijmtB+uJprcJ16de/ZWBbsy5M+2EbGUbyyKGlfCTJt2EbGUbyyIISUwWyUBU1M0gfbyDiK3WTIxnfPzr44DPucNo++QLG+zY76dojXxJuMbfS+mwvZGynt2v92XDpz1muXrGTb/CnicULJdHh1PcoMWVcdxqq/pdxkaDQiVz7r77HyCH3tGFZWF38aWaq6OfdXN6aTz5e6PK5y9ZXTE9l1VdD0SmdyyiLaG6q2sIy58j1WHqGvHcP21uJPI0tVN2/76n+lk8+XujyucvWV0xPz+9eDplc6k+uGlLoxsk0Jm/gOgRsj+7MsGyNPzrIghOShWMvCdxd1+3jsXdQvLyprzKL/btVjjl3UIbLD4XZ4dR0wpnUX9cu+h0r+XCMGdX1ubm04HYchHLtre+7pXVrv8K6j2Lz0+OXPrusAANtb3EV9aiTfZIhrcAaFa3CWz2yURWo4kSwspdQnJ5K1Q2VBCFFBZUEIUTEbZZHaJOTGyGEppT65MXI7s1EWqSmlj92EPov+PLTXTKXeUjIbZbFsWp74wzYyjtkoi2XT8sSfZdvIODSzURapKaWP3YQ+i548FHER9Fm0Q2VBCFExG2WRWsuv7T6Gtd3HLn8vAZccfbI1y5GTUurz9qs//obPruv6rpkbxc4NsYm9+E3fojWudDXYi+u0XdM2dyPG4jcxyb34TR+a3yM3XPymcJpDZkOdpZrhtlBpjaGZtqa8dt2UPGzYJWNomUutg1hw35AK27EVoyH4vB18LamhaGQqzZHbRZeMoet0CvUREloWhBAVVBaEEBVUFhVNT3wsb7xPuqlGBNbe/DGsvfljKlnqutk+e6CIERQX9SiFa7Qi9OjFHXs/HTS90iliNERE/gfA7wD8b25ZEnM9WOZloOQy/7Ex5g81FxahLABARJ7WDuHMBZZ5OZhLmdkNIYSooLIghKgoSVk8lFuADLDMy8EsylyMz4IQUjYlWRaEkIKhsiCEqKCyIISooLIghKigsiCEqPh/oh2C713mmF0AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ad76d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.40348625183105 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 1000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[5.36870916e+144 9.60000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [9.60000000e+001             nan 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 5.36870916e+144 ... 5.36870916e+144\n",
+      "  5.36870916e+144 5.36870916e+144]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 5.36870916e+144 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.36870916e+144 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.36870916e+144 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483e898>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.10579776763916 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 9.0, 'lmda': 10000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[5.36870912e+159 9.60000000e+001 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [9.60000000e+001             nan 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 5.36870912e+159 ... 5.36870912e+159\n",
+      "  5.36870912e+159 5.36870912e+159]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 5.36870912e+159 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.36870912e+159 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.36870912e+159 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483e898>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.52840256690979 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-10, 'kernel_type': 'untiln'} is: \n",
+      "[[4.43300016e+03 4.34000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.34000000e+02 1.49600003e+03 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 4.43300016e+03 ... 4.44900016e+03\n",
+      "  4.44900016e+03 4.44900016e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 4.44900016e+03 ... 7.55791212e+06\n",
+      "  7.40712488e+06 8.33548293e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 4.44900016e+03 ... 7.40712488e+06\n",
+      "  7.29048702e+06 8.18277500e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 4.44900016e+03 ... 8.33548293e+06\n",
+      "  8.18277500e+06 9.40670436e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 96.2308714389801 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-09, 'kernel_type': 'untiln'} is: \n",
+      "[[4.43300156e+03 4.34000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.34000000e+02 1.49600027e+03 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 4.43300156e+03 ... 4.44900156e+03\n",
+      "  4.44900156e+03 4.44900156e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 4.44900156e+03 ... 7.55801217e+06\n",
+      "  7.40723176e+06 8.33562627e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 4.44900156e+03 ... 7.40723176e+06\n",
+      "  7.29061325e+06 8.18295504e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 4.44900156e+03 ... 8.33562627e+06\n",
+      "  8.18295504e+06 9.40707656e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 96.07406401634216 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-08, 'kernel_type': 'untiln'} is: \n",
+      "[[4.43301564e+03 4.34000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.34000000e+02 1.49600271e+03 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 4.43301564e+03 ... 4.44901564e+03\n",
+      "  4.44901564e+03 4.44901564e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 4.44901564e+03 ... 7.55901290e+06\n",
+      "  7.40830079e+06 8.33705978e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 4.44901564e+03 ... 7.40830079e+06\n",
+      "  7.29187568e+06 8.18475564e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 4.44901564e+03 ... 8.33705978e+06\n",
+      "  8.18475564e+06 9.41079939e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.66453838348389 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-07, 'kernel_type': 'untiln'} is: \n",
+      "[[4.43315642e+03 4.34000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.34000000e+02 1.49602714e+03 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 4.43315642e+03 ... 4.44915642e+03\n",
+      "  4.44915642e+03 4.44915642e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 4.44915642e+03 ... 7.56903504e+06\n",
+      "  7.41900657e+06 8.35140408e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 4.44915642e+03 ... 7.41900657e+06\n",
+      "  7.30452159e+06 8.20278100e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 4.44915642e+03 ... 8.35140408e+06\n",
+      "  8.20278100e+06 9.44810627e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.60571956634521 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-06, 'kernel_type': 'untiln'} is: \n",
+      "[[4.43456444e+03 4.34000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.34000000e+02 1.49627145e+03 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 4.43456444e+03 ... 4.45056444e+03\n",
+      "  4.45056444e+03 4.45056444e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 4.45056444e+03 ... 7.67076473e+06\n",
+      "  7.52763684e+06 8.49576472e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 4.45056444e+03 ... 7.52763684e+06\n",
+      "  7.43316711e+06 8.38498713e+06]\n",
+      " [2.00000000e+01 2.00000000e+01 4.45056444e+03 ... 8.49576472e+06\n",
+      "  8.38498713e+06 9.82912968e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f548227f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.66885256767273 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-05, 'kernel_type': 'untiln'} is: \n",
+      "[[4.44866796e+03 4.34000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.34000000e+02 1.49871746e+03 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 4.44866796e+03 ... 4.46466796e+03\n",
+      "  4.46466796e+03 4.46466796e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 4.46466796e+03 ... 8.85572561e+06\n",
+      "  8.78972183e+06 1.00340683e+07]\n",
+      " [2.00000000e+01 2.00000000e+01 4.46466796e+03 ... 8.78972183e+06\n",
+      "  8.97078684e+06 1.04148679e+07]\n",
+      " [2.00000000e+01 2.00000000e+01 4.46466796e+03 ... 1.00340683e+07\n",
+      "  1.04148679e+07 1.45406449e+07]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7fd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 96.03934526443481 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 0.0001, 'kernel_type': 'untiln'} is: \n",
+      "[[4.59206097e+03 4.34000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.34000000e+02 1.52347414e+03 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 4.59206097e+03 ... 4.60806097e+03\n",
+      "  4.60806097e+03 4.60806097e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 4.60806097e+03 ... 7.54566122e+07\n",
+      "  8.31927197e+07 3.83904662e+07]\n",
+      " [2.00000000e+01 2.00000000e+01 4.60806097e+03 ... 8.31927197e+07\n",
+      "  1.58255030e+08 6.99957142e+07]\n",
+      " [2.00000000e+01 2.00000000e+01 4.60806097e+03 ... 3.83904662e+07\n",
+      "  6.99957142e+07 4.13582764e+08]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.91062760353088 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 0.001, 'kernel_type': 'untiln'} is: \n",
+      "[[6.28684631e+03 4.34000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.34000000e+02 1.80358053e+03 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 6.28684631e+03 ... 6.30284631e+03\n",
+      "  6.30284631e+03 6.30284631e+03]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 6.30284631e+03 ... 1.51100557e+15\n",
+      "  8.26093187e+14 2.59261319e+10]\n",
+      " [2.00000000e+01 2.00000000e+01 6.30284631e+03 ... 8.26093187e+14\n",
+      "  9.82185590e+16 1.19559024e+12]\n",
+      " [2.00000000e+01 2.00000000e+01 6.30284631e+03 ... 2.59261319e+10\n",
+      "  1.19559024e+12 6.81603314e+15]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 96.1321713924408 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 0.01, 'kernel_type': 'untiln'} is: \n",
+      "[[9.97247956e+04 4.34000000e+02 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.34000000e+02 1.48684597e+04 4.00000000e+00 ... 2.00000000e+01\n",
+      "  2.00000000e+01 2.00000000e+01]\n",
+      " [4.00000000e+00 4.00000000e+00 9.97247956e+04 ... 9.97407956e+04\n",
+      "  9.97407956e+04 9.97407956e+04]\n",
+      " ...\n",
+      " [2.00000000e+01 2.00000000e+01 9.97407956e+04 ... 6.61843723e+43\n",
+      "  4.44154416e+38 1.64684854e+22]\n",
+      " [2.00000000e+01 2.00000000e+01 9.97407956e+04 ... 4.44154416e+38\n",
+      "  7.74179077e+48 3.90269171e+28]\n",
+      " [2.00000000e+01 2.00000000e+01 9.97407956e+04 ... 1.64684854e+22\n",
+      "  3.90269171e+28 9.10260081e+40]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.8234338760376 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 0.1, 'kernel_type': 'untiln'} is: \n",
+      "[[5.36638593e+010 4.34000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.34000000e+002 5.83154191e+013 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 5.36638593e+010 ... 5.36638593e+010\n",
+      "  5.36638593e+010 5.36638593e+010]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 5.36638593e+010 ... 1.60491429e+143\n",
+      "  1.41720737e+110 3.10972499e+063]\n",
+      " [2.00000000e+001 2.00000000e+001 5.36638593e+010 ... 1.41720737e+110\n",
+      "  4.76403109e+154 4.94338199e+085]\n",
+      " [2.00000000e+001 2.00000000e+001 5.36638593e+010 ... 3.10972499e+063\n",
+      "  4.94338199e+085 5.14115463e+123]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 96.14166498184204 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1.0, 'kernel_type': 'untiln'} is: \n",
+      "[[2.40840470e+025 4.34000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.34000000e+002 6.26262051e+051 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 2.40840470e+025 ... 2.40840470e+025\n",
+      "  2.40840470e+025 2.40840470e+025]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 2.40840470e+025 ...             inf\n",
+      "  1.08069071e+297 2.27351202e+175]\n",
+      " [2.00000000e+001 2.00000000e+001 2.40840470e+025 ... 1.08069071e+297\n",
+      "              inf 5.19806675e+238]\n",
+      " [2.00000000e+001 2.00000000e+001 2.40840470e+025 ... 2.27351202e+175\n",
+      "  5.19806675e+238             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 96.44252038002014 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 10.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.39191466e+050 4.34000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.34000000e+002 9.73709741e+123 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.39191466e+050 ... 4.39191466e+050\n",
+      "  4.39191466e+050 4.39191466e+050]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.39191466e+050 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.39191466e+050 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.39191466e+050 ...             nan\n",
+      "              nan             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 96.55717945098877 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 100.0, 'kernel_type': 'untiln'} is: \n",
+      "[[5.85331757e+080 4.34000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.34000000e+002 4.84404724e+209 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 5.85331757e+080 ... 5.85331757e+080\n",
+      "  5.85331757e+080 5.85331757e+080]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 5.85331757e+080 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 5.85331757e+080 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 5.85331757e+080 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 97.04473066329956 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.72362983e+111 4.34000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.34000000e+002 2.76417123e+297 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.72362983e+111 ... 4.72362983e+111\n",
+      "  4.72362983e+111 4.72362983e+111]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.72362983e+111 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.72362983e+111 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.72362983e+111 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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C2kBlQQhRQWVBCFGxGmVhPbSZtIdtZB6rCcqqOXXbF5RVe5RG45zsyza8vvZQrw9NoFHNuu0/19Rgpxqy5UpnalDWapRFTSy8oTQjP8MfYP/aFgpuSKweY1GKteQZ+16TXNMWhmV4C2+q54asRlnUHqpsrTA0DSYWvt5aUQxliA35trAsfPJZGC7NkQ7DvQkhRVmNsrDwpiRkzaxGWbTuFhCydlbjs6jJsP/aei2I0PTj0NTp/rmWFllosl+sHKXliYV7514bJVW2HHnPcXCuxrKozdFT7y39ZsWqmbKaUr8cLbFSn1oZrNRbTagsCCEqqCwIISqoLCbS7+9bGYnxyTEmW2u/hU+OlvJoZbBSbzUx7+DUhtXWDvdujWatxthxq2UoqTC0a1TUVlradTZy5DNkk0FZW3M2kXSsthGrcg1ZjbIghJRlNcrCgllNbMM2Mo/VKAtCSFlGlYWIPCAiJ0Xkxd6xfSJyVER+3v0/pzsuInKPiBwXkRdE5KK5Am7R60yIRTSjIQ8C+GcA3+0dux3AMefcnSJye/f9nwBcDeBA93cpgPu6/6vC2loQOVf3rok23Lt/vrQ8U1b3rkGpPW9S9jodtSycc08CeGNw+DCAh7rPDwH4fO/4d90eTwH4iIicpxWGEGKXqT6L/c65V7vPrwHY330+H8DLvete6Y4RQhbObAen29ulKHmnIhE5IiLPisizf8Tbc8VYzFg1aQfbyDymKovXd92L7v/J7vgJAB/rXffR7thpOOfud84dcs4dOhNnTRSDEFIL1faFInIBgH9zzv1l9/2bAH7Tc3Duc879o4j8LYBbAVyDPcfmPc65S8bST9kYWcvYxsjDc9o8xpxeY465kAyhsPahsy33Nn6arfBCK5inbNbbKhQ/5hissR3i1HSHlKq/lO0LR0dDRORhAFcAOFdEXgFwB4A7ATwiIjcB+BWA67rLH8eeojgO4PcAvpgsPSHEJKPKwjl3Q+DUaaZA57+4Za5QhBB7mJ91WgqNuZ8z/V0esfM+eXwzIHOYv6deO4Az/vznqniG0OpRsaXzh+QwrX0xI5q9PUKxJcPuVao8sa5uqG5yzi71dQ9jmyHNbTObVRYlWIq3fSlyEluoHJylseDg1EYMznFwhu4NORx90YS5HZy5ae3gHKPlRkFaFuvgXCuhhVfmPJSUboZW8ZXohqSGMWuUXOjeKemOpZGqOGMvhDndkBTZ1tANoWWRaeg09DCsDZ1OuZ9Dp/58alpnFiwLTlEnhKjYbDdkyNDjnzoaopmpmPJ2KDUrVCOn757+f8uM1X+uOl1CXeSGyqIjZGqnoOmPahtZySnQJbshrUnphpA0NuuzyLkmQD/NXHEac+QYIxbuXfMHNdXBWYpcSrQEKf6hlDRSfBZmlUXsIYSGJ1ODnqagbSA137qx4cCQMgiVoZW14BsyHp6vMWTsG66OybuTuSY5Rm920MFJCMkOlcVEjp6ysZFvH58cY7L1y9GSGvWpSVcrg5V6qwmVBSFExWqURYt+oy+6siWhqNSxeyzIb6U+tTJYqbearEZZ1IbdkLxYqU92Q8JQWRBCVFBZEEJUUFkQQlSsJty75CzAlnnFZNBcE4rMtOCc0waT1ZI1NuU+NPW7FrnqYFjGD+Oci7X3rsayaP3jJWTtrEZZEELKQmVBCFGxGp9FTSx0eTST5vrXaCeS1US79kermZ1j32uSa6r9sAxv4c18u6gvhdoN30rEYR9GcI7nob1mKfVWk9UoCwtve2IbtpF5mF3PAkhfQDfngjZjKycPF9CN5Z3SSDWL0WjXokiRLddCu5oFgHznU4ZO58g0ln7q0OmwjofHx+TwyTrML2Vtl6FMYzKcLfvwW/eGRIXqMKsshoUda1ihxhBizuI3Gkq/xUqZwK0W7dFgtU5r1FmOhYp8aTztjqmVxWq6IYSQsqxGWWzN2UTSYRuZB4dOJ2Bt2DHnGpw18ZUh1teuIc+UNThrUMo3JyLrGTrVDlHV9nRbWX+hD9ezGM9De81S6q0m5pWFFsZZMM5Ck4f2mqXUW01WoywIIWUxO3Q6JLWPHeoPD4mNpY+l60trrK8dGxcPXT88P9f89eWnKZe2LD5qLh8QynduvIYvrxLlyjFMqiVl35DNOjg1P8qc6e/yiJ33yeMzi3M00isv/TqeePqrKkdiqB8/lCNWppxxAjHFGVNgQ4UXCqjSEnshhepGG5SlYSxwMCbPFDarLDTBXrnT952PXbO7LrdlAQBPPP3VUbnG8P1QS1oWGsWQkndOh+qYbCmypgb+afLKUcbNKouQM3BOZGeK5aBtELktiylDgqHrLVoWmvv6x1Mti1haMdnWYFnQZ5HJZ3Hw5rvx/L23RdOPyVDLZ/Gp//gHPPmZbybdQ5/F6Vx809147junP+8cWPVZcDSEEKKCyiITPqvCIqlWBfFTyqqwzGZ9FkOGzqISATepzkMrQT/WIlVjxGS0VKdLhJZFR9+ROLVB5XJqpl6bytBZqpV7d63l6MWYjLlltloHpViMspji2Ns1mF0cf46GHhpFAU6PjbCAT55+PQ7rhuyhqYutWSqLURaEkLZs1meRM4JTO4RYO4IzNOQ5do9Plv7/kBw54yx8w901IziPnvoBLr7pbgA6Z+YW4ixWqyymhvCOUSqiMhVNzIB1x2QsejYU9FRann6+QyWhVU6lZMuR57AMKdsXLi4oS/umHNPqUxtfjmjGHNSM4CzF1AjOUqREcPavr1FnKQFwKWmkBGWZVRYp8wx8P4CpkZhj+JSCNrqxFGNWlK97Fep2WbZCLMrWQq6cz2qTEZy1vdIhf0JLYiM1sXssyF+jPjXpamWwUm81WY2yIISUhcpiIrv4hN1nC0yZmtwvR0tq1KcmXa0MVuqtJqtRFlt7cITUZlRZiMgDInJSRF7sHfuaiJwQkee7v2t6574iIsdF5Gci8rlSgg+hz4I+C00e2muWUm810VgWDwK4ynP8W865g93f4wAgIhcCuB7AJ7t77hWR9+USNkZty4LdkLywG2KfUWXhnHsSwBvK9A4D+L5z7m3n3C8BHAdwyQz5CCFGmOOzuFVEXui6Ked0x84H8HLvmle6Y8XZmklISG2mKov7AHwCwEEArwK4KzUBETkiIs+KyLN/xNsTxXiPFoEx9Fnkw0p90mcRZpKycM697px71zl3CsC38V5X4wSAj/Uu/Wh3zJfG/c65Q865Q2firCli/D+29uBIOmwj85ikLETkvN7XLwDYjZQ8BuB6ETlLRD4O4ACAH88T0SZ0cOaFDk77jM46FZGHAVwB4FwReQXAHQCuEJGDAByAlwB8CQCccz8RkUcA/BTAOwBucc69W0Z0QkhNRpWFc+4Gz+HvRK7/BoBvzBFqClvT8oTUZjURnOyPElKW1SgLWhaElMWssoitE7AbtvItZZY6pHXZDf5R3+Hya7Usl7G8rFtQ1uUj0zG7rF5sTczQQjdTVqp66uEvB/MP5VcSjRfeMtblI9Mxa1kQQmxBZTERKxGHfRjBOZ6H9pql1FtNzHZDLGOhkYRk0B63WoaWCniYt4U62pFDFl8aKat7r8ayYF+ZjME2Mg/zykJr7ll6CxCbsI3Mw7yyIITYYDXKgiYmGYNtZB5mNxkakrpnp3afyWH8xpzNiTSbHYVkCO1uVWK7xNTNhVI2UtJuDFWKmIy5N4IqtcGQrw5L1d8mNxkihJRlccqCpiQhbVhcN8TqxshDSnveSynNmiMGS9wY2UeNOrOwMfLiLAtCSBvMWhapu6gPj89xVMbQWjctdlH35eubmbv7XtORNsZQLl85ajgk+893zOm7g7uoLwxuMsQ1ODV5aK9ZSr3VZDXKojacSJYXK/XJiWRhqCwIISqoLAghKlajLGqbhPRZ5MVKfdJnEWY1yqI2VvrYfeizGM9De81S6q0mq1EWW9PyJB22kXmsRllsTcuTdNhG5rEaZVEbK33sPvRZjOehvWYp9VYTKgtCiIrVKIsWIbd0cObDSn3SwRnG7NyQIaUXvxlbtMaXrgbNHILQYjS+eQqlFlzJRevFb8ZoOadDCxe/MU7/jTL1jaF5G+VKaw79tDXlHdaN5bdqTMbcMlutg1Jw35COoWOrRENIeTukWlJTyen0s0BMxtx1uoT6yAktC0KICioLQogKdkM6Upbsm5uH9toa5F7duzUpq3vnyMtiHZTCxGiIiPwawO8A/HdrWSpzLljmLWC5zH/hnPtTzYUmlAUAiMiz2iGctcAyb4O1lJk+C0KICioLQogKS8ri/tYCNIBl3garKLMZnwUhxDaWLAtCiGGoLAghKqgsCCEqqCwIISqoLAghKv4PXLND1X1cV0cAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 96.8442587852478 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 10000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.62276662e+142 4.34000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.34000000e+002             inf 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.62276662e+142 ... 4.62276662e+142\n",
+      "  4.62276662e+142 4.62276662e+142]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.62276662e+142 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.62276662e+142 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.62276662e+142 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 97.09547424316406 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 100000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.61279295e+173 4.34000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.34000000e+002             inf 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.61279295e+173 ... 4.61279295e+173\n",
+      "  4.61279295e+173 4.61279295e+173]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.61279295e+173 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.61279295e+173 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.61279295e+173 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 96.98517060279846 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.6117967e+204 4.3400000e+002 4.0000000e+000 ... 2.0000000e+001\n",
+      "  2.0000000e+001 2.0000000e+001]\n",
+      " [4.3400000e+002            nan 4.0000000e+000 ... 2.0000000e+001\n",
+      "  2.0000000e+001 2.0000000e+001]\n",
+      " [4.0000000e+000 4.0000000e+000 4.6117967e+204 ... 4.6117967e+204\n",
+      "  4.6117967e+204 4.6117967e+204]\n",
+      " ...\n",
+      " [2.0000000e+001 2.0000000e+001 4.6117967e+204 ...            nan\n",
+      "             nan            nan]\n",
+      " [2.0000000e+001 2.0000000e+001 4.6117967e+204 ...            nan\n",
+      "             nan            nan]\n",
+      " [2.0000000e+001 2.0000000e+001 4.6117967e+204 ...            nan\n",
+      "             nan            nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 97.23360395431519 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 10000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.61169709e+235 4.34000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.34000000e+002             nan 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.61169709e+235 ... 4.61169709e+235\n",
+      "  4.61169709e+235 4.61169709e+235]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.61169709e+235 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.61169709e+235 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.61169709e+235 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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mvJlLRHrOYajvH7N4hpzILfDlGoplmZOHxmcQkyEk707mmuQMC1i1ZUEIaQOVBSFEBZUFIUTFapSF5bBmYgO2kXmsJiir5tTtUFBW7VEajXOyL5t/fe2h3hCaQKOaddu/r6nBTjVky5XO1KCs1SiLmlh4Q2lGfvwHsH9tCwXnM1SPQ1GKteQZ+16TXNMW/DK8ipfVc0NWoyxqD1W2VhiaBjMUvt5aUfgyDA35trAsQvJZGC7NkQ7DvQkhRVmNsrDwpiTr5m3vP9A07ws+9qfZ073yY6/pZcieeyNadwvI+jl36nTbvAvk/4un3qW+djXKoiZ+/7X1WhCx6cexqdP9cy0tsthkv6FylJZnKNw799ooqbLlyHuOg3M13ZDaHDv/5pJ1VqyaKasp9cvREiv1qZXBSr3VhMqCEKKCyoIQooLKYiL9/r6VkZiQHGOytfZbhORoKY9WBiv1VhPzDk5tWG3tcO/WaNZqHDputQwlFYZ2jQoLSssnhyyhNDYZlLU1ZxNJh21kHqtRFoSQsqxGWVgyGYlN2EbmsRplQQgpy6iyEJH7ROSMiDzdO7ZfRI6JyC+7//u64yIiXxeREyLylIh8fK6AW/Q6E2IRzWjI/QD+GcCDvWN3ADjunLtbRO7ovv89gBsAHOz+rgVwT/d/VVhbCyLn6t410YZ798+XlmfK6t41KLXnTcpep6OWhXPu+wDOeoePAHig+/wAgM/2jj/o9vgBgPeKyKVaYQghdpnqszjgnHup+3wKwG7u7gcAvNC77sXuGCFk4cx2cLq9XYqSdyoSkaMi8oSIPPF7vD5XDI6hk1HYRuYxVVmc3nUvuv9nuuMnAXywd91l3bG34Jy71zl32Dl3+O24aKIYhJBaqLYvFJEPAfh359yfdd//EcBveg7O/c65vxORvwZwO4AbsefY/Lpz7pqx9FM2Rtai3e5+aJ3FsXRDaY055mIyxMLafWdb7m38NFvhxVYwT9mst1Uo/pBjsMZ2iFPT9SlVfynbF46OhojIQwCuA3CJiLwI4E4AdwN4RERuBfA8gJu6yx/HnqI4AeA1AF9Mlp4QYpJRZeGc+0Lk1FtMgc5/cdtcoQgh9jA/67QUGnM/Z/q7PIbOh+QJzYDMaf5q4hliq0cNLZ3vk8O0DsWMaPb2iMWW+N2rVHmGurqxuhnLI6XdhbqHQ5shzW0zDPfOyFK87UuRk9hC5eAsjQUHpzZicI6DM/bbmMMxFE2Y28GZm9YOzjFabhSkZbEOzrUSW3hlzk1J6WZoFV+JbkhqGLNGycV+OyXdsTRSFefQC2FONyRFtjV0Q2hZZBw6DWFx6DQVDp3WxaplQZ8FIUTFZrshPr7Hf8poyNhbP+XtUHJWaKp1ot1LwwJj9d96pu2SobLoiJnaKWj6o9oHrmSjntKV0nZDWpPSDSFpbNZnkXNNgH6aueI05sgxxlC4d80Haq7/Jze5lGgJUvxDKWmk+CzMKouhmxAbnkwNepqCtoHUfOsODQfGlEGsDK2shdCQsX++xpBxaLh6SN6dzDXJMXqzgw5OQkh2qCwmcuy8jY18+4TkGJOtX46W1KhPTbpaGazUW02oLAghKlajLFr0G0PRlS2JRaWO/caC/FbqUyuDlXqryWqURW3YDcmLlfpkNyQOlQUhRAWVBSFEBZUFIUTFasK9a87GbDHzMySD5ppYZKYF55w2mKyWrENT7mNTv2uRqw78Mr4H+67W/nY1lkXrh5eQtbMaZUEIKQuVBSFExWp8FjWx0OXRTJrrX6OdSFYT7dofrWZ2jn2vSa6p9n4ZXsXL+XZRXwq1G76ViMM+jOAcz0N7zVLqrSarURYW3vbENmwj8zCznsUr7mx0sdohSi1oM7Zysr+A7lDeKY1UsxiNdi2KFNlyLbSrWQAodD5l6HSOTGPppw6d+nXsHx+TIySrn1/K2i6+TGMyXCz78Yo7K4NCdZhRFrHFb7QNK9YYYsxZ/EZD6bdYKRO41aI9GqzWaY06y7FQUSiNH7rjamWxmm4IIaQsq1EWW3M2kXTYRubBodMJWBt2zLkGZ01CZRjqa9eQZ8oanDUo5ZsTkfUMnWqHqGp7uq2sv9CH61mM56G9Zin1VhPzykIL4ywYZ6HJQ3vNUuqtJqtRFoSQspgdOvVJ7WPH+sM+Q2PpY+mG0hrraw+Ni8eu98/PNX9D+WnKpS1LiJrLB8TynRuvEcqrRLlyDJNqSdk3ZLMOTs1DmTP9XR5D50PyhMzinI1U40iM9eN9OYbKlDNOYEhxDikwX+HFAqq0DL2QYnWjDcrSMBY4OCTPFDarLDTBXrnTD50fumZ3XW7LYoiUtEMPaknLQqMYUvLO6VAdky1F1tTAP01eOcq4WWURcwbOiexMsRy0DSK3ZTFlSDB2vUXLQvO7/vFUy2IorSHZ1mBZ0GeR0WcRwqLPIhX6LOpi1WfB0RBCiAoqC0KIis36LHx8Z1GJgJtU56GVoB9rkapDDMloqU6XCC2Ljr4jcWqDyuXUTL02Fd9ZqpV7d+0Nf3y72YduJ2OoXLlltloHpTCpLMacgFp2DWYXxx9rRKlpxo75sREWCMnTr0e/bjScO3U6q4wW0dTF1iwVk8qCEGKPzfosckZwaocQW0Rwpr79GMFZRrY1xFms1rKYGsI7RqjBtWCob+5j1TGZ0i2sUc9TfE4140dydHH936dsX7i4oCztm3JMq0+t9BzRjDmoGcFZirkBbrlJieDsX1+jzlIC4FLSSAnKMqssUuYZhB6AUm/bkFLQRjeWYsyKCnWvYt0uy1aIRdlaRdQCee7VJiM4a3cHYv6ElgyN1Az9xoL8NeozpbuzlHqryWqUBSGkLFQWE9nFJ+w+W2DK1OR+OVpSoz416WplsFJvNVmNstjajSOkNqPKQkTuE5EzIvJ079hXROSkiPy0+7uxd+7LInJCRJ4Vkc+UEtyHPgv6LDR5aK9ZSr3VRGNZ3A/g+sDxrznnDnV/jwOAiFwF4GYAH+1+8w0RuTCXsEPUtizYDckLuyH2GVUWzrnvAzirTO8IgIedc687534N4ASAa2bIRwgxwhyfxe0i8lTXTdnXHfsAgBd617zYHSvO1kxCQmozVVncA+AjAA4BeAnAV1MTEJGjIvKEiDzxe7w+UYw3aREYQ59FPqzUJ30WcSYpC+fcaefcG8658wC+iTe7GicBfLB36WXdsVAa9zrnDjvnDr8dF00R4w/Y2o0j6bCNzGOSshCRS3tfPwdgN1LyGICbReQiEbkCwEEAP5onok3o4MwLHZz2GZ2iLiIPAbgOwCUi8iKAOwFcJyKHADgAzwH4EgA4554RkUcA/AzAOQC3OefeKCM6IaQmo8rCOfeFwOF/Hbj+LgB3zRFqClvT8oTUZjURnOyPElKW1SgLWhaElMWMstCsUeGfDy1llmtIy18Nq5blMpYXLSjSCjNrcIYWjwktztI/7/8250pVc9ZjzJXvlPOElMKMZUEIsQ2VxUSsRBz2YQTneB7aa5ZSbzUx0w1ZEhYaSUwG7XGrZWipgP28LdTRjtx+uB0pq3uvxrJgX56MwTYyD/PKQmvuWXoLEJuwjczDvLIghNhgNcqCJiYZg21kHmY3GfJJ3bNTu8+kv8PUnM2JNJsdxWQYiifxz89t9KmbC/kbKb3t/Qdw7tTppF2yam7zF8s390ZQpTYYCtVhqfrb5CZDpB7n37dv/CKyOhanLGhKtuf8Uz9vLQJpwOK6IVY3RvYp7XkvpTRrjhgscWPkEDXqzMLGyIuzLAghbTBrWaTuou4fn+OoHEJr3bTYRT2Ub2hm7u57TUfaGL5cqbOQtXmMpdG/v2NO3x3cRX1hcJMhrsGpyUN7zVLqrSarURa14USyvFipT04ki0NlQQhRQWVBCFGxGmVR2ySkzyIvVuqTPos4q1EWtbHSx+5Dn8V4HtprllJvNVmNstialifpsI3MYzXKYmtanqTDNjKP1SiL2ljpY/ehz2I8D+01S6m3mlBZEEJUrEZZtAi5pYMzH1bqkw7OOGbnhviUXvxmbNGaULoaNHMIYovRhOYplFpwJRetF78Zo+WcDi1c/MY4/TfK1DeG5m2UK6059NPWlNevG8tv1SEZc8tstQ5KwX1DOnzHVomGkPJ2SLWkppLT6WeBIRlz1+kS6iMntCwIISqoLAghKqgsOnL4LLR55L52DlN8FudPHTTbX6fPohwmRkNE5L8A/BbAf7eWpTKXgGXeApbL/CfOuT/SXGhCWQCAiDyhHcJZCyzzNlhLmdkNIYSooLIghKiwpCzubS1AA1jmbbCKMpvxWRBCbGPJsiCEGIbKghCigsqCEKKCyoIQooLKghCi4v8AXB0tpCxfAPsAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 97.30274987220764 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 100000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.61168713e+266 4.34000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.34000000e+002             nan 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.61168713e+266 ... 4.61168713e+266\n",
+      "  4.61168713e+266 4.61168713e+266]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.61168713e+266 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.61168713e+266 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.61168713e+266 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 97.33426523208618 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[4.61168613e+297 4.34000000e+002 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.34000000e+002             nan 4.00000000e+000 ... 2.00000000e+001\n",
+      "  2.00000000e+001 2.00000000e+001]\n",
+      " [4.00000000e+000 4.00000000e+000 4.61168613e+297 ... 4.61168613e+297\n",
+      "  4.61168613e+297 4.61168613e+297]\n",
+      " ...\n",
+      " [2.00000000e+001 2.00000000e+001 4.61168613e+297 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.61168613e+297 ...             nan\n",
+      "              nan             nan]\n",
+      " [2.00000000e+001 2.00000000e+001 4.61168613e+297 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 97.55917716026306 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 10000000000.0, 'kernel_type': 'untiln'} is: \n",
+      "[[ inf 434.   4. ...  20.  20.  20.]\n",
+      " [434.  nan   4. ...  20.  20.  20.]\n",
+      " [  4.   4.  inf ...  inf  inf  inf]\n",
+      " ...\n",
+      " [ 20.  20.  inf ...  nan  nan  nan]\n",
+      " [ 20.  20.  inf ...  nan  nan  nan]\n",
+      " [ 20.  20.  inf ...  nan  nan  nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ad7ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.3909502029419 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-10, 'kernel_type': 'size'} is: \n",
+      "[[2.048000e-87 1.280000e-88 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [1.280000e-88 5.760000e-88 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-87 ... 2.048000e-87 2.048000e-87\n",
+      "  2.048000e-87]\n",
+      " ...\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-87 ... 5.266944e-84 5.127856e-84\n",
+      "  5.912384e-84]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-87 ... 5.127856e-84 5.011322e-84\n",
+      "  5.767748e-84]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-87 ... 5.912384e-84 5.767748e-84\n",
+      "  6.795520e-84]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98abac50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.74970293045044 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-09, 'kernel_type': 'size'} is: \n",
+      "[[2.048000e-78 1.280000e-79 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [1.280000e-79 5.760000e-79 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-78 ... 2.048000e-78 2.048000e-78\n",
+      "  2.048000e-78]\n",
+      " ...\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-78 ... 5.266944e-75 5.127856e-75\n",
+      "  5.912384e-75]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-78 ... 5.127856e-75 5.011322e-75\n",
+      "  5.767748e-75]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-78 ... 5.912384e-75 5.767748e-75\n",
+      "  6.795520e-75]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.20982718467712 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-08, 'kernel_type': 'size'} is: \n",
+      "[[2.048000e-69 1.280000e-70 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [1.280000e-70 5.760000e-70 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-69 ... 2.048000e-69 2.048000e-69\n",
+      "  2.048000e-69]\n",
+      " ...\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-69 ... 5.266944e-66 5.127856e-66\n",
+      "  5.912384e-66]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-69 ... 5.127856e-66 5.011322e-66\n",
+      "  5.767748e-66]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-69 ... 5.912384e-66 5.767748e-66\n",
+      "  6.795520e-66]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e9ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 86.77457761764526 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-07, 'kernel_type': 'size'} is: \n",
+      "[[2.048000e-60 1.280000e-61 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [1.280000e-61 5.760000e-61 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-60 ... 2.048000e-60 2.048000e-60\n",
+      "  2.048000e-60]\n",
+      " ...\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-60 ... 5.266944e-57 5.127856e-57\n",
+      "  5.912384e-57]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-60 ... 5.127856e-57 5.011322e-57\n",
+      "  5.767748e-57]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-60 ... 5.912384e-57 5.767748e-57\n",
+      "  6.795520e-57]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7c18>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.03894019126892 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-06, 'kernel_type': 'size'} is: \n",
+      "[[2.048000e-51 1.280000e-52 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [1.280000e-52 5.760000e-52 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-51 ... 2.048000e-51 2.048000e-51\n",
+      "  2.048000e-51]\n",
+      " ...\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-51 ... 5.266944e-48 5.127856e-48\n",
+      "  5.912384e-48]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-51 ... 5.127856e-48 5.011322e-48\n",
+      "  5.767748e-48]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-51 ... 5.912384e-48 5.767748e-48\n",
+      "  6.795520e-48]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.49170255661011 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-05, 'kernel_type': 'size'} is: \n",
+      "[[2.048000e-42 1.280000e-43 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [1.280000e-43 5.760000e-43 0.000000e+00 ... 0.000000e+00 0.000000e+00\n",
+      "  0.000000e+00]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-42 ... 2.048000e-42 2.048000e-42\n",
+      "  2.048000e-42]\n",
+      " ...\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-42 ... 5.266944e-39 5.127856e-39\n",
+      "  5.912384e-39]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-42 ... 5.127856e-39 5.011322e-39\n",
+      "  5.767748e-39]\n",
+      " [0.000000e+00 0.000000e+00 2.048000e-42 ... 5.912384e-39 5.767748e-39\n",
+      "  6.795520e-39]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ad7ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.31858253479004 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 0.0001, 'kernel_type': 'size'} is: \n",
+      "[[2.04800001e-33 1.28000000e-34 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.28000000e-34 5.76000004e-34 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800001e-33 ... 2.04800001e-33\n",
+      "  2.04800001e-33 2.04800001e-33]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800001e-33 ... 5.26694404e-30\n",
+      "  5.12785604e-30 5.91238404e-30]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800001e-33 ... 5.12785604e-30\n",
+      "  5.01132203e-30 5.76774804e-30]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800001e-33 ... 5.91238404e-30\n",
+      "  5.76774804e-30 6.79552006e-30]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f5483e898>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.20457577705383 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 0.001, 'kernel_type': 'size'} is: \n",
+      "[[2.04800102e-24 1.28000000e-25 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.28000000e-25 5.76000440e-25 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800102e-24 ... 2.04800102e-24\n",
+      "  2.04800102e-24 2.04800102e-24]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800102e-24 ... 5.26694793e-21\n",
+      "  5.12785958e-21 5.91238812e-21]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800102e-24 ... 5.12785958e-21\n",
+      "  5.01132543e-21 5.76775193e-21]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800102e-24 ... 5.91238812e-21\n",
+      "  5.76775193e-21 6.79552609e-21]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.34181046485901 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 0.01, 'kernel_type': 'size'} is: \n",
+      "[[2.04810241e-15 1.28000000e-16 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.28000000e-16 5.76044005e-16 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04810241e-15 ... 2.04810241e-15\n",
+      "  2.04810241e-15 2.04810241e-15]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.04810241e-15 ... 5.26733741e-12\n",
+      "  5.12821456e-12 5.91279561e-12]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04810241e-15 ... 5.12821456e-12\n",
+      "  5.01166497e-12 5.76814063e-12]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04810241e-15 ... 5.91279561e-12\n",
+      "  5.76814063e-12 6.79612891e-12]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.23769950866699 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 0.1, 'kernel_type': 'size'} is: \n",
+      "[[2.05834662e-06 1.28000000e-07 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.28000000e-07 5.80455985e-07 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.05834662e-06 ... 2.05834662e-06\n",
+      "  2.05834662e-06 2.05834662e-06]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.05834662e-06 ... 5.30712868e-03\n",
+      "  5.16453637e-03 5.95442905e-03]\n",
+      " [0.00000000e+00 0.00000000e+00 2.05834662e-06 ... 5.16453637e-03\n",
+      "  5.04651314e-03 5.80813565e-03]\n",
+      " [0.00000000e+00 0.00000000e+00 2.05834662e-06 ... 5.95442905e-03\n",
+      "  5.80813565e-03 6.85868022e-03]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 87.413241147995 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1.0, 'kernel_type': 'size'} is: \n",
+      "[[7.86292024e+023 1.28000000e+002 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [1.28000000e+002 5.81864238e+042 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 7.86292024e+023 ... 7.86292024e+023\n",
+      "  7.86292024e+023 7.86292024e+023]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 7.86292024e+023 ...             inf\n",
+      "  8.57709940e+288 4.14238452e+164]\n",
+      " [0.00000000e+000 0.00000000e+000 7.86292024e+023 ... 8.57709940e+288\n",
+      "              inf 6.09633722e+230]\n",
+      " [0.00000000e+000 0.00000000e+000 7.86292024e+023 ... 4.14238452e+164\n",
+      "  6.09633722e+230             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c3193c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.2377827167511 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 10.0, 'kernel_type': 'size'} is: \n",
+      "[[5.40756465e+193 1.28000000e+011 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [1.28000000e+011             inf 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 5.40756465e+193 ... 5.40756465e+193\n",
+      "  5.40756465e+193 5.40756465e+193]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 5.40756465e+193 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.40756465e+193 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.40756465e+193 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8160>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.82736778259277 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 100.0, 'kernel_type': 'size'} is: \n",
+      "[[     inf 1.28e+20 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [1.28e+20      nan 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00      inf ...      inf      inf      inf]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00      inf ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      inf ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      inf ...      nan      nan      nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdf28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 88.88064861297607 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1000.0, 'kernel_type': 'size'} is: \n",
+      "[[     inf 1.28e+29 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [1.28e+29      nan 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00      inf ...      inf      inf      inf]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00      inf ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      inf ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      inf ...      nan      nan      nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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q9KkgPwuvVBQoVcaRZMiMPJUx8p0dSasgpJyqjAURnQYwBaAIYJGZ+4ioHcA/APgYgNMA7mXmqpdAUos+Nw8/qzRViDmjpJF8tWp4l5kxFq7vTFoFIeWEMQz5HWbebJl+eQLAa8y8EcBrxt+CIGScKIYh2wHcYRy/AOCnAL5UbaPamP/OCZ85Zy9jmKlQsrJG4egHSasgpJxqjQUDOEBEDOB7zLwbQBczXzDqPwIQyjZJMnwWftIXqmXFqrQuyooKJStzdLQnrYGQcqo1Fr/NzOeIaC2Ag0T0rrWSmdkwJMsgoocAPAQA69evRxs2OF0mCEJKqMpYMPM5o7xIRD8CcAuAISLqZuYLRNQN4GKZe3cD2A3oy71x1umqJYIkIVI5MlQZx6IsJStraGfPJ62CkHICGwsiagKQY+Yp4/huAH8J4BUADwB42ih/HIai+Q59aq84POz5HrWTU5Vq12SUmLIyhtZ3Y9IqCCmnmp5FF4Afkb6NuwDgB8y8j4jeAPASET0I4AyAe6tXUxCEpAlsLJj5FIBPOZy/BOBOv+25ZVH306MAjPwbWtEsw2Jr4T7kW5vNKNuLF4ZQ6O5aimAVUxrAgU2Pm5u/1L6OfGeHbb1E4egHoOZmFIdHkLvuGv1aY7iRa6iHdnnOXIxFg/HP4ty1ZRcK7+njT2rS4zks9KxBzeAlcwHd4sevQ+G9syiOjkeeL2Vb72ModrQiNzsPrbEW+ZFJs44b6zH18Ta0HtF998UOY/Hdr0/4TiMYhNv+4K8w25HDugPnoF0cAeA//san/vSbaHv3CsZuMGKAaED9OklfKAhCyKQmnsWa9z5p61ksi2fR+J8B6Mu9vcazGOh8GPuGv4eBzocB2Jd775/9X9WqXVYmAOwb/l4k7UfFtuv+CwBg79n/kbAmQpysyHgWQYLxqkC7cWY4jzO4b5hIIGDBjcwYC7cMZU6ouJWqjGMFZ5ypDsNE0iIKbmTGWPgxEgoVjFeVcfQsTFkZozgZ/epWIdukxli4LbqSnkW0SM9CcENmQwRB8ERqehZu+B2GyDoLf+ssiuMTsehtRdZZeCcN6yxSM3XadqS3YpKgu2vvB6AbDa9Tp/3ND2D/9AtmQiHrMOTA/IvVql1WJhA8YU1SDLT/EQBg3+jfJ6yJECd+pk5TYSxKM5Jtze1AzvjlVmsvSg2ENT+Hyg+icosA1ecFUW2Wyooat/wdA5sel9weQmisiHUWbnlCrPk5zLwgAXKL+Gk/Ftzyd0h+DyEhxMEpCIIn0tuzcIk9YfU/RJFEyKn9OHBL9iPJgISkkJ6FIAieSG3Pwi1PiDU/h5kfxLgnFPkO7ceBW/4Oye8hJEVqjYVrnhBrfg6VF6QlxGC5Du3HgVv+DsnvISSFDEMEQfCEGAtBEDyR2mGIW1IhazIfdRwkEZGf9uPALdmPJAMSkiK1xsJtlyk11C87VveEIt+h/Tig5sq7P93qBSEqUmssNLcVnBOTy47d7vEl36H9OCgOj1RVLwhRkVpjkWvUdyGWi/id71iz7FjdEwZO7ceB2h0atF4QokIcnIIgeCJVPYutuR0A9B2mW/POuYn6W3Zi/9QeW5pAdRwkxWE5nNqPA7c0gpJmUEgK6VkIguCJVPUsrFA+D6DCbEht7bJjdU8o8h3aj4Ocy8yLW70gREVqjYXsOg1WLwhRkVpjIRvJgtULQlSIz0IQBE+kMgZnf8vOZesrrDE4bRG7c3n9WJUO1zuhAtSq5DqF7i7wzMxS1O5z5/U2AZssrxGmVfRt67DBGn27cPQDoKNdb/7seWh9NwIA6Odv6fXXXoPFC0PItzajODlt5vUojk8gv3pVZIF179qyC4UhI9L3uL4YjZoazajbADB0dw+6DgyCawpY7Fpl3lsYmoB29jx4YbmfKd+7fikkoPHcfmOJbut9DAAwf/0a1AzPgGbnwI1LPpzTv9+B9XvtC+iKTTWYa69Fy7FL0FrqgV+fMOu0vhsxc209Vh14R9cn4Dv9rQNfQm63/rnmL2soNuTQdGYaH3xW75GuPaJhtkP/XR7drH+Xci0LWNc5gaG316L7F4yWL+hRzvHHdeDzy1NJOgWA/s0/eRaHv/ocfvdzD5rnxm6oQ9u7VzC/Wh80FGsIADC5IYd3vvbFZW34icGZyp5FmFOggiCEQyp6Fn19fdz25gbbudKewUDXIwCA4vCw9yzqNz2JfUe/joGbntRPjIybdfuGvluFxpVlAsC+o1+PpP2ouGvLLgDAT372VMKaCHGyIqJ7l8IBehs0Nmkr4+ixKFlZwxx6CEIZUjkMEQQhfWSnZzG/4PsezUiBp8ogbQSVmTnGs9kjEuJDehaCIHgiMz0LqjGC4Sx4X01J9fW2EiGu8HSTmTVUYmJBKEd2jIWx/gF+nJQdq20lhaxTRZkZY6EnvpgdQjbJjLHgMkFwKqKmSo0yUBtBZWYMteBKEMohPgtBEDyRmZ4F9XTrB8ff93zP5Zs/ZisbTkWfgVzJyhpDd/ckrYKQcjJjLHjwgu97Gg6ftpVxDEOUrKzRdWAwaRWElJMZYwHy756kfM5WcoA2gsrMGlyTna+CkAyZ+YaQitzto3fAba22kopa6HqVk5k1rLtHBcGJbP4MCoIQO2IsBEHwRGaGIbLrNFpk16ngRmqMRa6pqWz2MSDYf3SV70OVYQb0dZOZNSQfieBGaoyFKwGC9CjjYBqJGAL9xGGQosApFJ4gWBGfhSAInhBjIQiCJ8RYCILgCVdjQUTPE9FFInrbcq6diA4S0QmjbDPOExF9m4hOEtG/E9GnvSoiEb0FId146VnsATBQcu4JAK8x80YArxl/A8A2ABuNfw8BeC4cNfXZkpyKaeGRQtdasyx0rTXb8NuOX5lKbpbI967Xc3sIQhlcZ0OY+XUi+ljJ6e0A7jCOXwDwUwBfMs5/n/X8Ar8kotVE1M3M/neBlepx5Yrve7TJKVsZR85SJStzjES/I1fINkF9Fl0WA/ARgC7j+FoAZy3XDRrnBEHIOFWvs2BmJiLfCxiI6CHoQxWsX78ebeitfL2R9JgXva8HyLW22Eptatqvmr5RsjKHkVJQEMoRtGcxRETdAGCUF43z5wBcZ7muxzi3DGbezcx9zNzX2dkZUA1BEOLCU/pCw2fxf5j5k8bf3wBwiZmfJqInALQz8+NEdA+ARwF8BsCtAL7NzLe4tV+aGHlrbgfyhgEpDg8DcEhnaEkTaKYpNFIcAtWnJ1RtlsqKGrc0gndt2SUpBoXQCDV9IRG9CN2Z2UFEgwC+AuBpAC8R0YMAzgC417j8VeiG4iSAWQB/6Ft7A2288sYmHvxo2bHbPX5waj8OCu+drapeEKLCy2zI/WWq7nS4lgF8vlqlBEFIH6ndSOaWVMiazMdMJhRiaDin9uPALdmPJAMSkkKWewuC4In09izcMpBZM3+pjGNhrsx0aD8O3DKDSeYwISlSayxcw/ZbM39FkXHMof04cMsMJpnDhKRIr7FwCcbCc3PLjsMM4OLUfhzwTOUNdW71ghAV4rMQBMETqe1Z5FbreSzUoqxSqGfdsmN1Txg4tR8Hix+/rqp6QYiK1BoLWZQVrF4QoiKdxoKo7PoKhTY9vezY7R4/OLUfB8XRys5Ut3pBiApPe0Oipq+vj9ve3GA7V7oXpL/5AQB6RK3SunIMdD2CfUPfNfeMWGdL9k+/UI3KFWUC1e9NiZttvY8BAPae+uuENRHixM/eEHFwCoLgiXQOQxyglmb9wE+szrXttpJGos+ibsrMGPPXy2IvoTKZMRa47H+tA03O2EoO0EZQmVmjZjibegvxkRlj4SdClnnP3BV7GaCNoDKzBs3Gt/BMyCaZMRZU8K8q1dfZSgQI+htUZtbgxvh21grZRBycgiB4QoyFIAieyMwwhHt79IO3jnm+Z3RLj61cfWwydL3Kycwap3+/I2kVhJSTGWNBZ/0vuW771ZCtxFh4y8HdZGaN9XsNQ/rfktVDSC8yDBEEwRNiLARB8IQYC0EQPJEZnwUCrLNAXa29DNJGUJkZo9hUk7QKQsrJjLGgWv//CRdb621lzWT0/5GVrKwx155NIyfER2aMRZDANjUfDttKbXIqVJ0qycwaLcckELBQmVQYi+OHT2GSD2Frbseyuv6WnQCCLaPmhjpbSTEE3lWysobWks0ekRAfqTAWm27uNY1CKfun9gAAtubvdayvhHb6rK3kYjGQfkFkZo5fn0haAyHlyGyIIAieEGMhCIInUjEM8UK+Q9+7UC41gBO5jRtsZRyZxUxZGUPruzFpFYSUkxpjobmEy6OmBv3Ax2TDwpomW1l7Ofp4FkpW1pi5VhycQmVSYyzcKA6e931P4c3jtrI4H16qADeZWWPVgXeSVkFIOeKzEATBE6nIG9JK7Xwr3WnmA9ma24FcYyOApeFJaa4Qa34OlR9E5RYBqs8LotoslRU1bvk7tvU+Jrk9hNDwkzcktcMQajDG0OV8Gaualx2b94SBQ/txUOxorapeEKIitcYCC5UjcdOVheXHLvf4wbH9GMjNVvaruNULQlSk11jUVFaN62qWH7vc4wfH9mNAa6y8ocutXhCiIrXGwjUh0MT0suNQkwg5tB8H+ZHKcULd6gUhKmQ2RBAET4ixEATBE6kdhrhlILNuWTczj4UYCcup/ThwywwmmcOEpEivsVhlTBFOOo/RF3rWLDs27wkBp/bjYOrjbVXVC0JUpMpYqOA3B7WXbQusrPS37MT+qT0onFxa/q2OtUujoeni1H4ctB65UFW9IESF+CwEQfBEqnoWVmQFZ7B6QYgK6VkIguCJVPUs1Gax/padZeNbqJic1liX6rg4OhaaLk7tx4JbLEyJlSkkRCp2nfb19XHbm/YIU6W7TG+/5xkAQN3eN5bVlWPjrmdx4qk/w8ZdzwIAun+xtHfk9X9+vBqVK8oEgBNP/Vkk7UfFbx34EgDg3+7+7wlrIsTJith1WkrT2/osgJ+tYte/Ogs8ZZQAagajz42hZOGpyEWFSm53p35wd7J6COlFfBaCIHgiMz0LaJrvW3Lzi7YySBtBZWaN/OXo342QbbJjLHL+O0FabcFW5gO0EVRm1ig2SCdTqIzrN4SInieii0T0tuXcV4noHBG9Zfz7jKXuy0R0kojeI6L+sBTl6Rnw9Iyve2qGJsyyZmjCbMNvO35lKrlZounMNJrOxLcVX8geXn4G9wD4DoDvl5z/JjP/lfUEEX0CwH0AbgJwDYCfENEmZq46b6DWe41+cNj79OjIbd22su1Y9GH6lays8cFnZbGXUBnXngUzvw7A66aL7QB+yMxXmPkDACcB3FKFfoIgpIRqBtiPEtHnABwC8BgzjwG4FsAvLdcMGueqJn9R79r7cR+uOjlrK1UbUaJkZY21R8TBKVQmqFfrOQC/AWAzgAsAfMemJ6KHiOgQER0a9pCSkBvqwA3+4krMr641y/nVtWYbftvxK1PJzRKzHTnMdoiTUyhPoG8HMw8xc5GZNQB/h6WhxjkA11ku7THOObWxm5n7mLmvs7MziBqCIMRIoGEIEXUzswqs8HsA1EzJKwB+QETPQndwbgTwq6q1BLDY2aLL9pEdcKK3xlbWTraEoYonmVljdHPVPmhhheNqLIjoRQB3AOggokEAXwFwBxFtBsAATgN4GACY+SgRvQTgGHT3wufDmAkRBCF5XI0FM9/vcPp/Vrh+F4Bd1SjlhFajj5jyPu5ZbLCXqo0oUbKyRq4lvkRKQjbJzHLDxQbdTPgxFvOr2FaqNqJEycoa6zqzt5BMiJfMGIu6S/4TCLWcsZdB2ggqM2sMvb1WP5Bdp0IZUmEsjh8+hUk+ZAbstdLfshMAUGjXo1r7WWfRfnTWVhYuhBccx01m1uj+hdEjylYYDiFGUmEsNt3caxqFUlRkrC3/8RsAgPqzg57bPb290VZ2/2v0+T+UrKzR8oUYo4EJmURW4QiC4IlU9Cy80PgvRwEAfhYlb/zWKeBxowSgTUW/q1LJQjRR+6Ljj41el491LMLVRWaMhRYgQ3pxbNxW8kL0gWmUrKzB54eSVkFIOTIMEQTBE6kxFuVC/wuCkA5SYywEQUg3YiwEQfBEKpIMtVI730p3msmDtuZ2oHBdDwBg0VhXUZpY6K7bvgYA+MmVH0ORAAAC+UlEQVTP/wJ33fY1/OTnf4Ft13/RrN975ptV6aTaLJUVNbf9gR6p8Of/+F/L1perEwS/rIgkQ24BaqwBZtRxmEFtnNqPA7cANBKgRkiKVBqLXFMTePBCxWsaD51edux2jx+c2o+DdQccYwV5rheEqEilsQAAbe5K5frJyWXHbvf4ku/QfhxoF0eqqheEqJA+rSAInkiFg9NLFvWBG54AABSPv+85i/rt9zyD1//5cTMDe+P7SxkN9r37dDUqV5QJRJelPSp+80/07O9H/la2nV5NrAgHZylDd+jxFjqOv+/5nrkvjNnKqX9aG75iZWRmjcNffc44EmMhOJMZY7HuFX2Dlp/dHW1frgEGjBJAbujUUuXfhqhcqUwAGIim/aj43c89CAD46YGEFRFSi/gsBEHwhBgLQRA8kZlhCLcZiXs/8r6VenZ9i61smo9+i7qSlTXGbog+ipiQbTJjLGjM/1qHxg+nbGWQNoLKzBpt74a3RkVYmWTGWKDO/5LrYnOdrcyNR79sW8nKGvOrs/NVEJJBfBaCIHgiOz8nOf92jQtkK4O0EVRm1ijWZFNvIT6kZyEIgicy07PQWv3n45jprrOVhfHoc3ooWVljcoP8bgiVScXeEKfgN/kbNwIAiu+cALB8r8iW7XrSoZ/9+M+xZfs38LMf/zkGbnrSrN939OtV6aTaLJUVNZ/6Uz1oz//79hfL1perEwS/rIi9IW7TnNYpyiimRp3ajwO3KUyZ4hSSIrXGwm0RlnXxkzo27wkBp/bjwG1xlCyeEpJCBqqCIHgitT0LaJV9KWSpN49d7vGDY/tx4Jaf0U/+RkEIkdQaC66vqVg/35Jfdux2jx+c2o+D+dXV1QtCVKRiNoSIhgHMALjaAkx2QJ75aiDNz3w9M3d6uTAVxgIAiOiQ1ymclYI889XBSnlmcXAKguAJMRaCIHgiTcZid9IKJIA889XBinjm1PgsBEFIN2nqWQiCkGLEWAiC4AkxFoIgeEKMhSAInhBjIQiCJ/4/6gm2Ob0CmiIAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ab2f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 89.42226576805115 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 10000.0, 'kernel_type': 'size'} is: \n",
+      "[[     inf 1.28e+38 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [1.28e+38      nan 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00      inf ...      nan      nan      nan]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f552006d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 89.76648592948914 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 100000.0, 'kernel_type': 'size'} is: \n",
+      "[[     inf 1.28e+47 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [1.28e+47      nan 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00      inf ...      nan      nan      nan]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8908>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 89.66677856445312 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1000000.0, 'kernel_type': 'size'} is: \n",
+      "[[     inf 1.28e+56 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [1.28e+56      nan 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00      inf ...      nan      nan      nan]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 90.64025664329529 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 10000000.0, 'kernel_type': 'size'} is: \n",
+      "[[     inf 1.28e+65 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [1.28e+65      nan 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00      inf ...      nan      nan      nan]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 90.03168940544128 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 100000000.0, 'kernel_type': 'size'} is: \n",
+      "[[     inf 1.28e+74 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [1.28e+74      nan 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00      inf ...      nan      nan      nan]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8160>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 90.24439430236816 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[     inf 1.28e+83 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [1.28e+83      nan 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00      inf ...      nan      nan      nan]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 90.1073067188263 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 10000000000.0, 'kernel_type': 'size'} is: \n",
+      "[[     inf 1.28e+92 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [1.28e+92      nan 0.00e+00 ... 0.00e+00 0.00e+00 0.00e+00]\n",
+      " [0.00e+00 0.00e+00      inf ...      nan      nan      nan]\n",
+      " ...\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]\n",
+      " [0.00e+00 0.00e+00      nan ...      nan      nan      nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9c319390>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 94.79279446601868 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-10, 'kernel_type': 'branching'} is: \n",
+      "[[2.04800004e+03 1.28000000e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.28000000e+02 5.76000004e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800004e+03 ... 2.04800004e+03\n",
+      "  2.04800004e+03 2.04800004e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800004e+03 ... 5.26694979e+06\n",
+      "  5.12786230e+06 5.91239224e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800004e+03 ... 5.12786230e+06\n",
+      "  5.01132965e+06 5.76775867e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800004e+03 ... 5.91239224e+06\n",
+      "  5.76775867e+06 6.79554167e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418ccc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.0595772266388 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-09, 'kernel_type': 'branching'} is: \n",
+      "[[2.04800044e+03 1.28000000e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.28000000e+02 5.76000043e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800044e+03 ... 2.04800044e+03\n",
+      "  2.04800044e+03 2.04800044e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800044e+03 ... 5.26700194e+06\n",
+      "  5.12791898e+06 5.91246637e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800044e+03 ... 5.12791898e+06\n",
+      "  5.01139851e+06 5.76785465e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800044e+03 ... 5.91246637e+06\n",
+      "  5.76785465e+06 6.79573675e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 94.92164874076843 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-08, 'kernel_type': 'branching'} is: \n",
+      "[[2.04800436e+03 1.28000000e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.28000000e+02 5.76000432e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800436e+03 ... 2.04800436e+03\n",
+      "  2.04800436e+03 2.04800436e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800436e+03 ... 5.26752348e+06\n",
+      "  5.12848590e+06 5.91320777e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800436e+03 ... 5.12848590e+06\n",
+      "  5.01208725e+06 5.76881460e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04800436e+03 ... 5.91320777e+06\n",
+      "  5.76881460e+06 6.79768781e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.2647225856781 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-07, 'kernel_type': 'branching'} is: \n",
+      "[[2.04804362e+03 1.28000000e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.28000000e+02 5.76004321e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04804362e+03 ... 2.04804362e+03\n",
+      "  2.04804362e+03 2.04804362e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.04804362e+03 ... 5.27274533e+06\n",
+      "  5.13416212e+06 5.92062511e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04804362e+03 ... 5.13416212e+06\n",
+      "  5.01898476e+06 5.77842170e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04804362e+03 ... 5.92062511e+06\n",
+      "  5.77842170e+06 6.81722821e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 94.93681693077087 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-06, 'kernel_type': 'branching'} is: \n",
+      "[[2.04843627e+03 1.28000000e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.28000000e+02 5.76043210e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04843627e+03 ... 2.04843627e+03\n",
+      "  2.04843627e+03 2.04843627e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.04843627e+03 ... 5.32561698e+06\n",
+      "  5.19163716e+06 5.99514138e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04843627e+03 ... 5.19163716e+06\n",
+      "  5.08899175e+06 5.87525549e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 2.04843627e+03 ... 5.99514138e+06\n",
+      "  5.87525549e+06 7.01564500e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+PR+n+5k5nWrLC5qktPOqe5bI7V0s2uS89u1d9qbR5w6cBGfp9yzXty0oyYJ3LjkZbYt49Dmp3NbQq4UQuGE96oDSXKfbirHKxdPogeTFIBYqZ7XJELEg922VlsVOz+fNvnOXuwU2faH0cO9rLl2cYtfNUdrF4uqKVTmPsa3TJ8V/eIzGBcxrasnk8kqyl1nrIn3A07FtMlZgtYV3BukdnL300ksn6S0LJ+fl4JTfZ461OjiFw8ycK5Klcg7OnI4yrGbbXfu2X4XglKeJEgHeiUbh7QjApkt3d3CCcLYiQ2kX41FcMMj3VWT5QKkobOEeHZ+/YZEhtbMNLYoTO4fq2iJDymSdYjaPiwyl9VciXUWRoeEwFBny56l8kaFBGXwnV1FkiIheB3AIY4NVzPxJIroP4H8C8FEArwP4XmZ+2tbGlUkaBXDEqelD23ZtlD2qGg9J5MUXx3zGn+yLtSFs1dr3azz3NgLQqMWh4h++yBh1qc4AoOfa69ZcjNwiEme7quHAn+MXB0VGb3tcbW1BHx76CIGXZdXqMDPkx9p/Nv8qaI8aDw8T+0I5Rh+9QLSg0nAILE22JooiRAJ2d4D9g7hjpcw5s7l5kOqw8FBZgsYj1Msw5749l+Ep53w8Aly0xc3nvAYe7IWsU21IeLXTBwBOpmGR2DIREpTm4af5wmxY7u+Z7w+O/DxF8zeZgMoSuq79GNTWFupXXwAdihT18QiYzgK83P3ORyNQVYHnc9BoFBquREX1NXIe25C/wcyfYOZP2r8/C+DzzPxxAJ+3f99uIcrsQzNTr5JjKb9C7pqLkC59nUaXixqDorioEGDmUqnmvKfnXAMh9/to8Gmcsc1zljPlhljL4pPM/IE49ucAPsXM7xDRhwD8c2b+D1a1cy1yQ9rM/bOgRdtMfoeRWJdI5qTLFiftI3ddV73l9ZnkrbZao42wX4pryYWn142tjQcj3dI4vQT+IqgldOV4y2EsnlDtvFW3FNsixqi2t6GngbTGWX25sgONNz6Mtefe9no6C+cniXwNnEhZNrdAtnyET4hT8ZxJixYAvlD9Ng705WSdMoDPERED+B+Y+WcBPGTmd+z37wJ4eMY+LkbaftApCU2X67MLQ1KGzx6TW4+IQMUd12JPHP2wM76FiwBltZUvLIrAyzMcmtqcYjx2GO3zlpQvDJGADUBZDsxVFAAnDwMQtglJ+UIq4DMxpYlPRRGXL7TztxqUFW+luKpAO9sR+Y1bCJQtSciLhbdiPCirKMzcVxUwA5TdsvB8HpVY9G0OSpOlKpmyhkPQ3l2z7XDnlSWwMFs8MDdAWUhBWfXlgbK+k5nfIqKXAPwOEf2Z/JKZ2S4kDSGizwD4DACMsXVGNXrppZeLlnNLUSeinwBwBODv4yZuQ5yc1zakS/urjp91O3Heku6nG/RywnTuEily359Vl+h4iGREFclW4A42qjrX8nugwXBFcWU0tj7mn3ib5N72EU/Iui0pUZ7DIzdeGWUS7V0K+Q0RbQNQzHxoP/9NAP8VgN8A8IMAfsr+++un7eNCJTHLXU6ENy+Xi+Y10q8hM/8yWwIaDBvQWioKX6ZOz+bClF1CbRnrSh8fW31kWTrd6C8bDVFFEg2Z+x+dj8Kk0ZBkHtR4bMJ5QCCadSa488KLfbIvu2cjObxYCD9CCAHK8bgHg4j8D311NGQZ5c94XTRHRC5q7y70wWFzO8bs8zNcTosZ6wi0NUH95FnQYU00hBvRkDnUxz4CfvtROLUswdOpz/fgkykwKI2+29aKHpTmHiwr8OEh8IrZreuvvhHyWBDGoLa3TDTk8NDPY7G3h/rjr6H4szeCnsMBeDoL43eL0mgELJaNaAgddF8CzrINeQjg1+yeqATwS8z8W0T0BwB+lYh+CMAbAL73DH1cnLS9bS6wViQAQOt2L3wD6uyccgycv3O7k5j9u50TiW1wn7WwKNIENN9IMi73MG6uTP6wy9dg9vPrF1I511o326jPAe2o0/Fm2kxxIdLq0tzQI7KIVkRGSDPk7qB1VjO4lE3l+jNlbWKynieUty2z86JFhbdJRDF32XqskzawlwSeXZXuKwB23sKSC9tZfy+rIjhdr1Ux3iGKfHSNfgEbj6Vnyuqll17OXW4v3LvNoSicUubNnlyTnt/mxJN8FqLtKGQo+xIFaQAXHtTBukgxGbk34jnAvVfxWfhLhF9B+gZ8enQqTi+B0zCn82Zwb8dnIZyXkV6jEdj5aeQ2J+PkdP4JKgpoWXfjFHDv4v496ANZ6EdF2AmuKhP2ZPY+Hu9r0Qw9n6O4ZxCc9eOnoX/5uymoCfcejVC88AD1B4/FVFsIebLN87pfFdz72klXjASQ8Q8k2ALZ3rrrc6ZfzvRmbSDc/gFN+CxYh4fP/mCyhYLaTGfO5Ga481amXos/08gAEXx6tJ0P/0DKtGm5v3bAI0huiGSs6RbP65noH52T4bDQ4aFmB2giBiHMY4TbkECpuo4XNzl/md9QNDfie71/EPNb1HZuBOO360WS50g8h362H9pOFzvXd1rIaLEwC4UYRxvcnt34gKidTdwQz9dicZbU3Ew4rlPB2VXtpQ8qUdibtoS3ZD5Gp4piuX5Po6+TlkSyCCkpIxv+Le8sAh2IXrQYfw7K3CUBrw3wlgtHCuBY7nt5PLVKov78ud0QnDQamYXKd2eqmUULvxOB4JS9O4vDLzApqZCLgEnwV1FATcbQR8cCqTmIyyXKOcggONExagw8b4vFWaTNPD+v9tyxVqtHR46uhjm/zpLp8l0XaWXUCvB0j4LklEiF2+ct0r/OLwLpeY3rctaHsFiqsO2LGbzEVlGFn7yZ47rb3Kb3Tpynp7NoEfHkN7lF1y2kyXbHwcXlyyISXTeDTHUNfXScvFRq23d6H8I4YwspP9ycXP/FYpMf/3lFQVxbXbYzq9rZJDeEFLIp2+77Tfo9zXWrrk8WgKgeabRVS5iY1uZ4bGhZ5HJD5KURNkV+Abh0/0g3V2QoqnW6uWUhOUmNenFuSPSmT3JDmNnwdVp8DJ8s7TVJ/22WxdYW9MlJbJEmRZrknJ3FsuijIb300ksnuf6WxWXLeeFOVpnYnHnzpub/afU4q/4dtgZtjr7O7W6yjVq7DRFf51C3qUjLQdexVbFKt1XbkEbpwqY+3hByXCFp8w1ukg7bkKpCfRDzdzTOydGRPrfbkMuSXIjxLLkhbSZ2Ll8gA7vO1hxd1bb8TrZ7Gr2zxzOp4CJ64xGHqenu9EjbTUOk8ppNtiEZvdL9fhzxECxUCb1/Q8+u25BciroMK+ccnEXhkZ9cVb5sgD4+Cb6MJDK3aYp6JL2D84Kl6wPZ6rFvvgF99KASCwSHm+t/V6uQhRJrIfVMcyKS/TmAtYWRoxR1mdciojNUDEzilHxQbQQAXOf1lg9apv6HTLCSUOcs45jvK8FBDAfAPOPLsDSAnn3MHS8S7IksjJykyod2gg6Ae9DHgimLAUUg1CZlHjB5KXae3TG4uiGLpcFfjGyOzfFJ1l9GwzLmEYFZLGh3FzgOOBGffp7iLFxB5sXyylLUnx9Zh0fInbtKsjiLJHogztk4TJtbTFZFJ9ryNdItRp1/2OVxrir/g4687qt01s1xM8tFNsFQuL6iuiHimP9bREPm87yD0z5g2bohidURwSySOeNlFevujh/FdUNcnZKobohbXI5tm4o8gIrrGuysg5ZoFC8rE0mReJWqgn62H2e8OlxJihFyfB6NuiHdrc/ewdlLL710kt6yOA85j/Dupv6Fru1sYjF1bDdftewUknNeplu6dQ7XVK+sPisQr2nhIN9/7njmGGBS6FM+D+bojR/Yr6weNYJvkXWTk6Khqw7hVBd2dVXPsnOQWEU1DGNYamH1lsUtF6IYy3DTJEJ7XoH+KX5klQ43aX49claF/zaQ3rJwsi7hKne+O68LuMgdkyQ2aXKYO952fYf2sw5OoDMHZ5vjNEoEGw5jRiff4QqnbEdwVXCwZhyca0BZWdYoCOdsmo/iQFkuxEkJB2dS2jAi9xXlGIqd7Th8an0Dq+qGQCnjs6gqU2Nk20RD6v2D7BxSOTB1RkRdFBoOoe7cgX4qKm0UhfdPxLpbtnPWQQcANLutiWSbSCPr1IaquiSjSc6GqspSs+W8+BB1PfRcR2344zMRHZCw6GRxirz1IpIhfwguTBbVKEkWo7SeyKq6If6cyRjaRUZkf1XVSlEXMW+78GFZZpmyUFX+QfVZsILUmMrSZFYm7OK0uwtKcAdEZMhqZ3PzsM3DfVXDATAY+AXAz1+tzcMlx+LrhthFqijgCHTpwT2Qu8+O3GixWF03RCmgLEDTGfTxCej+PfN9A75tux+PsnVD+NUXQcchdOozbzN1Q/xib4mEAQDL7nVDbu9i8bxJzhy+rDojz6MoYaZzM+X7SuW09/WMv4f+19RLL710kutPq3dd5bRIz44kNJ3aaWsj9Yus8sU0tmMtYxHH5ZbkTIjRLn6MHNKzBRmaA1I12lyHyrTnNtpqY+pm3cqwnU0kc+0kOIuwDZ0hK5KkWQDYaDKBPpLEOwVyOAu3ldSLZYQs/UL1ORzox53Mpn4b4mQTB2cWupxxHK6Ee2eyTt3xtuvb9BB6x6zWrr+ML6Z1URAw49TBibBf98zXmazTVl2ThaENwQkUiHk9kvH69O4mSjHH1OXbSO+TK54kCjt5LooyTmV3LOc+PV+eOxxGRYaMgxNxHdgWB6fzi3hk53yenUNXSBmSh6MoQOMxSDJ9FYXhycg4OGk8Ajl/jFEC1MO9TyFnQXBms3Va4votyUgbJ5K14CmaGAgd/s1dn7bTgjyVektqt7MkkjUS0lIeCtd8qmtLn7rlQfNI0QwLV8Q5oQMilasqYb8CIu4LgV6tj45jy8UujBFdn2tnmXk6WaM+yCQXylMkZsNFaeqFRXBK9GgSOfLXA2SxHywg3reXKessclrLwlkF6Q9xTXlBrqoonNla16NNciFOGwr0qvn8jRWWRUv9FHOuyA0RVoAajXxNkkZN0TbynBYuzYZlYblHvWXhwpWJ9ZSrtaomYxMJSKUoRG5InIiFogjXuPljHd7QEJaFbcfpbiyNJYr7e9CukrmoOeKSw9blhuj53JcvrJ88y84hDYfNuiejEdSLL6B+971wns2DyeWG+OruMnR60t1t2Ts4e+mll07SOzh72VzOkrp/kdLBOXuma9rS51MrL7VSozYy72dpIbVZZjmLl2ylN8njsa5vCQbEZuULe8uil15uk5wBnt77LM5DrkvoVLbj2rqI0KlErJ536DRta1WIeJPQaRrhce1If1OUk5KQz+SO2Wt9PVYAgbJ7k9ApmgjezBi8j0cidsejyPm5KnTqozTSn7HBLesXi/OQTR6StnM3fdC6trMuytN2/orzLjTrdNU5a647l6zTldekx8y1l5516tvcLOsUxKEd/8XqbqX0i4WT5zmRbFX71zWRLMeUdZmJZDmmrFwiWVXdnEQyG/k5bSJZ77PopZdeOsnNi4acxRO/qV/guvZxEZLDhdxm6fg7i6DvlyEpVmfDa9MxbVJF/eZtQ85rj3xRctMWCSf9QhFLx/t4qhKTZxHmy+/Tys1bLM5LWvbqnVbt1PeQeSsbzoXE4aYKwWcxj/ksxoZjwCUS+TeWa7sDn4Vs3/Xh9umtCNHEl6HG4/V8Fru70IeHXk8nXOuAtkynzM0H4KMEVCijIxBzVQiotUeLMgdOiBY+C7V3F/rgIHA4ACbVvCjAjs9C7PnVaAQaDlG7sRSF2fMLFGYYgAINBwHt6e7dfI7yYx+Fft9WMrd8FrxYQO3dNees4LPAbG5qlT58wVz+xlsxAa/TdWsLNCijcoXFvXvQH30F9BevhwjJZGzqrub4LKrK+CxsdXcAoIOez2JzEQVz15+betGbzrZsO6zNA+eqkYtzuE681xnIdeP7TI5KnG8R9GytnZoyWFdVo2/WCqgDBJvn83CO0LvhiJRe+misbpHTzWPpZ1nxW/QZCjOLNmYzU1FcOvdqWy29rkFJ/U+uNSAWD65rW+mQQZwUpiYGKlEOQbZzeBw7HsksNHxickN4sQgLjxtzUZh5qioDBz88bow90rWq/Dh8bs18juLJAWp5z6ezwARulLGNDC8tAAAgAElEQVQNsLk+zU3p8nu30js4e+mll05yey2LLnH3rtdn28qHEePK3fk3q79+lb4tma5dLYi2dmXYMoSFXYzfWhrLKnyOYvYr5i6aD3Fttn/O/y37lFaPk8XCz28EPLLnR+dypoAzBcuhkdjKOnorR9bPyUm0ZWGnt7M26jrMq3Z1Q9w2VkdWSNyn0CuTHMbLCnxwFPetObKiWLal07oyeqOs096yWCVngMZu2naj3NxF999FcrwdkiEa1p+xinIuQkVSjJU4k27t1+fnMjnf6aEo1us0otK2W3TLHbfXElHsayHVTS9FZ5/LjnJ7LYuWxJxOhL3p9VmAlIUGJ8d92TtHxuL+IAVSOrycG4xR3VLn45RxdAN3iXYjVmtRT9SXFYRxTHqQk08td2/8Fl6OTH3SHGycFEFWKjP9Ir7O6ZKkyBuy3QSQZAljnLURc99YyHU0HwnITBw3+iY1Vrk2jk+ROg5FIKbgVEZwNNJwGPQiFfwQzuko65ZKtRz5jbAMDKHN2F4jaqi69tPryTiFI/KbuvsieXsXi0TSorqrLOom41WTzyLH8CTZt2XhXGbtWZXcw9PK7mS+jLkgxAOZsnu76xtRHo/gjBdHx24tDvloiGd1mkxA9pyIDcqOpTFX7BCR8PNg/lVRxMX3j+DM9PwaOtwbGg4BtxUSiFXa2Q4Pk3vbE5nPs3lY5Nz5w6GpjyoZxldFQxJ2bwCGLfzeXZBDjmoTUdPzudEHyLN7lzbyMl8Y8/7eHfP9s/2wIMlpzLB702SC+uV7oGf70XnAzMwbcyMagiQagmV3q6RfLKz4veoFRkNYc6CXTzD6jbqbgDD5m6t/Ng9iVTSkrZbqumgIqVhvIIQPOUQlIH0d/u3s/nYJUM4XYhfkSudrh0Z1VSmc4/QSPhM5Z3wyNREORSFawWze+m6+BZcmLyvzwEpfiI+4JHNDDMzm8Xid7B9F0RAfeXB+iOXS3l8dFqBB6dvgxQK0f+j1Ci8D17cCz+ZgtYjnZjpF8cEBNHOoyG6jIYFUyM5EXRudqir4TYD48xrpfRa99NJLJ7m1lkVklhMZ07YO4KVQ7CdJgHLgIAHKoeGwQeemxiPwYhGbvYMSamvLtH946PevejaHsiZr/fiJObcsbdLPAFzFYDEqClAhigE5s3Q4hBIFZPTRsQEkLRZQ1vSUICiua6+D01/t7vrPnkKuUKDJJJzz8EXoR++b70R/PJubyEBG3HwA8GawAxkB8POpJmPo6cy/gdXOtgEiiUJMtL0FXizNOXIb8trLoHfeM9aD27OrAqpQ0IdHoEGJ+sDS35GC2tkG7WyDLVcmlaW5l644k7QWisKcu3/g5xoA6sNDLL7lwxj92Vv2Xmjjwzg8Al572Zz79AAYDQFm1PfNdoNHBfSgQHk4h3r/GU6+9RUAwPhfHBvSXquj+Yeg7u+BxiPoR+/7ZDn18EV88F2v4cHn5t5Kod1t8MEhaGDBeXY7xtsT0GIJPjwKxY8A4O3uS8DNyw05L0kdlIICHkCMnuxyfTqPMnvTX6MEr0AcwqLh0IS2RHWsLDDLoS5zodk069QuhCuzaVMHZ8rBKbkx3SUDi8YUiys701tWP0up9EUmaaSj0COt5BblXijhxJPgJvegjEdg65vwi4gLkTaAZuz5IPTxSWO88lynf5p1CgDQNYqHL0FLv4Fb6C0HJ5ZL89BqHRycbhuiCDydQd3ZBQDUj5+G7Z8HnpFfACVZshqPoV5+Cfq9D4SeBF4sjX9G+ixsNipXVeTX+sL8n2G//uA5zQ25CGlDOq70cm7SthVCtGfOU6xx0CPFO0i9co7PVdI1ytPQR8c6O/HYATs+/zBmcheYgbafY1toMA25tmBWiLhxnwwU3C4gfjGMH0AjhdmzS2JiG2lJIycAogjDSkd40rfXXAmLhwgoyDiTpd/A+YHEuLgGaFg0IzcSq+GHVIR0+BT27hzaaai3o9zexSKp3yF5DACAdSbKId/S66Ih3vsf/xB91CN6A1uzVuvYsqhdVKSO+gtRlMRaWBUNSX/cHaMh7q3mrQnYrYc2D6R/U2rtIcmRZWFDyDIaIvMWOkdDZK1TW4+VCmtl2IdFbW+ZGqxFIcKDMONxb3dpWQwHoK0tkNxCFoVZgKST1M2t3arKMaCqgL07UNOZvRV2m6q1yAMJURbaNttQuBwe51i/b/JIfGTDslq5uaHh0GyTRN4MjUaoXt5DIawalCUwnZnfmYvqACYa4qI+Mhoy79m9e+mll3OW22tZpH6AdeesOu88dLFv6hhGnkCU/WFRleqCxVhb9g8ZprTw4Vzobe1WTr7xTqWU2PqQgMy7EGJqrtvvXJKY14sNfiO1bk6jD/OKMWt2mClxzGSnwmXPuu2nhexHCXKa23dxtYVxex+P6POc5fYuFok4H0GnLX0XnIXDFQh/A2s2GAF7TYSzqKr4Bnt/hc72x1o1F6/zyDoVGZ2N/A/392wezOe0GlamTe/HkDiL2u7lMzkmjaxTf07sFPbXOcfpdOb9FXK/7p2vyRzwsgJoHvsGYB/OXNapiG5FD+/+YSNywlUVZ50KfA0As10ATAbtbA717DCaw8hnRSbl3eM1ZNbpBwfQMnNWbAcjcdm3jazT7n656x8N2YR56jxZqpxf4rxJYdZFJfzfiVPxsu5TF9ZwJ6nj1Z+bOHEzldn89afVMdd/CzdnVjcpXe9xy9xIro5sX0lUxfwTg9B8CFs+zJIv1Z8sHeYU86G69nNz4I4nc7ZJ3ZDny7I4rcc/DS+6w0Vh4MsJzmJzvTokiSWhWwBRAeJWBOZ5S9sC4HT0Hyl20opygg4P4bg7GhBw19Zp7lP6d+bh9yQ2QAhHu/l18HShL3ddkNu+JwUD+Qz9t4WNo+a8Q72OQ5yAIQbynMhx2cXseEWbrX16a/J0v53ewdlLL710kufLsjgtLiK34vp8Bm6ed9r2V0rTt0AQ++w0O/YipVVf4XRz7okMD0dMy5ckuwFwHBmn1ktagm3+Ip3eN2shNnKAzr7NTOegrXaH7dj+oyK/lWdKc99XAf+x0gCTXBmZflr/PoX0lkUqgkPgsiIOV85bsUo8/8SKrYncCri/0725m9fzGuuqdlr5JJqgqvO4x402HBfFJqIojhB15aiQ/CIXzGuxtnUi+jkieo+I/kQcu09Ev0NEX7b/3rPHiYj+CRF9hYj+DRF925k1TMOJ53XuujZySMSLEmnZ6Nr855B87u/c+ZetW+47FghIF4qslpa4V4e3bPrfWXVqa4eTt2wSImcLSXfRGY9CPYNOURt+Tlp0axOXFer+c8THa/0oOv5P9nPOv5Mu25CfB/DTAH5RHPssgM8z808R0Wft3/8FgO8B8HH733cA+Bn77/WT1COfMjit85B3zQ2Rx20FLADB6Wb78nUxl6LSF+um81UiSDNRhtbckLQiWcs8NHJDrC7SaafGI+jZHKDEuVYnC5vUW+bKCNKabNWvOuMsFGNwuSEp3oQmE5MUFpHfuBBl01FM5cAks00DpZ1H8qo0dGpRrC4ZTuQQFQ/uQx8ciCk1DkmXNMiLRWDEcshNSdg7m3sm8PqDx830cgA0GoGIPNM5AKjJBOrFB6jffU+MqcznhgwGPnQqOUhoeo58Fsz8e0T00eTwpwF8yn7+BQD/HGax+DSAX2QTj/0CEe0R0YeY+Z3OGl2WtK78Hfd263wZubcLa7MXJdXoa2MOztxi1paX0XZ+pt1GHdMcB+dikd9Pr9oXR/MhMCa5/sWx6O8MtsLt/QEYvomUg7N2b/5mLk5uriIOzkg3y3/hMA4SC3J8HIc87UKjLQRczovHaUgcSFX5ZDZu+Fpg/GeOg1POzWJhsmAzHJzeavLzoIWlJ4FsF89n8VAsAO8CeGg/vwrg6+K8N+2xXnrp5YbLmaMhzMxElHm1rhYi+gyAzwDAGFtnVWNzaWxDLGfmRXBwii2OpNKTjFIu8YetBeDNb4dHSPXNpc+fyzZkIN6a8TbEMVzRaBQ4FwSeAQ3UY+qwy6Sob7INkenyTAGnYPXyXBhya+LGb+dSUtbRoLQp8C7tnDpsQ+IxcFWBdndAic5YLDy3SLQNcUlcLtGt1sB06vlMeDoVEP9E1yRCR8Mh6N4eaBYnwqEy3KKRi9VuQ5BuQ+qLTyR7REQfAgD7r9s0vQXgw+K81+yxhjDzzzLzJ5n5kwOMcqc899Jgxs551YGmZ/2S2Jw36iv15EcRkjUM4KeUEGlpRgIabNltup0yXTvtK9tPfFL+YkU2dd3+l0F4rr0Hq8bg2j0HOW0rvwHgB+3nHwTw6+L4D9ioyF8HsH8t/RVdpRWxR3F4UKIu3SnyZguvNhUqTp+236c/bkdS2+b7oByFvU1Rd/9JS6OxMFH+QaNCxefavqTO0ZvJ6k3SQvERndWRBqOj8paLIzQ2TNTKj0c+QF6X3AM0GvlFi1kmV9k2FEW6pQ+5Q35KPaL/hkP/Ge4/ImAyDvPujitzHJMxMDCOVBoODPHueAQaj41FMhiY80dDy6YlfAvyfg+HhijZ9UkEGg6g71ir3C4KTkcMBuY/N6bREDQZGz0mY/OfmK8usjY3hIh+GcaZ+QKARwB+HMD/CuBXAXwEwBsAvpeZn5CZ/Z8G8N0ATgD8PWb+w3VKXAlT1lll7TakBRoutwOyjbZtwqr+c33Kh8j1kUZT2sYh/07PFdsez16V9tcWMkz1lQtVmv+QwpRzOQ0t8GlDQZjUCV2VY+O2HZKtS8DuG9sQuTUR7arJxESHpLCO8j384itrkCpDxsPLCmpsaQ+n0+wcep6PZLujdrYDVSAy2zhhfRkI+TJ6uX1h+Vs40I/PJzeEmb+/5avG022jID/cpeNeeunlZsnzBfc+i6x7A6fnRn93TIoSe/cmPWdyfF3SmnAYyvOibEamoFvquG3LoEzfqEJvz8wlEtzi7Ml2dfNDEG2KrYYMh+bo7aJzKN4eNRymjvPUh6wTR2SCPvVtkwKIG+04eLgsFkXDAUhQD8CyXPk3uAhhOmvDWBYELMkwaDnH5zRTxtDpJuqsADDbi/EYJAoTUdGcFzc3KApQLZPpNKjqvg3pF4vbINcZTp6RqCraFfXvqooBCfbhBksrh2dHub2LxRlDp1HoTJbYE983EtEER2aU3i0Yl8P+WYRMMwjOdRXPAIgQoNA38YmklcrS640qFB1Xk7HhukzOj/TPzJcHJLl9u0CLympjBuBUx+dIDk7HE+osJ9fH9nYUwjRTQ8bRN4MBS80lgrMEBsHP4cbJzBG7OhXmWhoOfUWy6D7e2/MV2jwD1mIRKPdzFcmUAsoCNJ0ZQNaDPfP94WE2zcBVJCNRBEptbUG//AB0cBjOc2Ft6RsBvPOX6tpWLbOyAQfn7V0sMhGGTRCcnKDmst9nEZzOXI3Rlo2HbBXOn5Nq6XYBSSuHmTYK8TkzjpQ9ShDCerSie8Pa43o6y/6gV+XSRAxPOcYrbbcAstoYEDkfG3POOtoqNJCUgC1DqGN4vWxbMIGz5kBzJ8sNAIC2VcHcfFmuDpACP30Wap0KFnE+NI5HXlZgZWHiblG22xBeVgae/fhZY54iXR1TloC465MTFO8+Ri3JbxxTlh2ra4mqCjQZm3orsv0NmLJu72KRyibJN/JNv2EfbSZtK+1da1tJ5MEudKn57trtTqvXAiOXtP8eJEWt4+kiKVen0b1unpOjJ5S0g+7cZKExX4s2M2OlIjo5WGsNGj4LIY8WNwd/XybzJhIBXT9uwXUPtoyG1HWjSFVD6hrso0BFODabxXrW2kPeAeFbWVZAsYz0AoBNmPL6FPVeeumlk9xeyyIHn5Ze5FV4BwF22shnoQpPOafncfUzf9yVTXS4hjafhYxaiGPSh6AXy3afhW039Vmo0SghrxF7ees5dyUFgcTHUVUb+yy0rGBuj8nizGo4MOckPgt22wWxtVB7d6PsTzNM47Pg2dz6LMIbXI1G5rujI6+Xa5tEpTO3LTE+CxutKGzRn/kc6uGLwAdP7KQbnwUvFj6TlFf4LGB9FvTwBfP961/P+ywmEzNfh4d+boq7d8Df8CGov3g9nDcamTHmfBaAqesiSk5S1QQUtsntXSzasji7xP9Sf0Pb/j3Th+NVTNtwD01TnxafRYbFi1PT2WeLchOslPMfINRCjc7RCIhSwNcebWxDVmQw5nwWcjvhGaOS9HizUOjW6+S2RT/bb4yTSZniOhnd9HxufAhCL9l/pItmzzdhLmbvD9CP3s+CslxJwwiUZWvBNkBZbz9qzFPU3HQKtr4Qt0Dqw0Oo1zVq0TfJCuoQoW1beEjP5iHMi+b9XyW3d7E4q6xNUW/ZC6Z8D7njm/Yvj7Utdm36NJyw6/WWTtrO4IrcfOWulRGg9JxV1wGBCyRtb4VOjdIJ9nyGcHA6f1AlxxAstDbUpbRiwtrm2o/18JwaLfMf6UnhWH1wFN+b5HcUrZGsDTlRQgjUVW7vYtGF/GYVMOo05Ddy+yLeENA1aGDyAqIiwPLHmvYndc+0D+B8CiPbOXE1QAGxNQDi/hz5Ta6vhPzG/EONN1vItqX4bwGJl7pE5DfOBI8SxQzoieu60R+VAwOBltZULufEwsCpbCmM/MIDaBv58ACsuvZAK64qvx3w5R6L4KTU8znUHVNdvX78JGsFRbraBUGNx1AvPED9fiiMTEURuC+i68sApBNbR+rLF/bSSy/nLbfXskhE8hgAK7ff/k1jTqwDgCptrwYiTgLnJAPAs3nEbeELJrs4vANd5eDaaVKTAJa1FkZOHJnB4ohBaGlhZKcLDYe+mhptb4Fq6xR0NHEekyGTwIKFIQsje0elgC93KowsIdOOwVu8QdXujgGLSWSi9Q1gsQh8EO6rQWne/tLJ6hyb1joIJysDZrKgLGcZ8LwG7u9B2TYMoMtgMpQFZfHJFBg4B6fNEi0LcKFAswXUAYAXLCjr4CBgRaRlJ0FZzkLY3kL1yn2ofUHpNxoa/4SzXGRh5Koy3wkHJ5Y9KGtj8eULu8KM20hh3SFHX5biA+QPgSk+f1U/SX9ZPVnDU8on17fiIRrYg6R8Iamgt6fVE07HBghMNia3P5JQNuRVSNwCgIAT8E5N3RyDJbcFAIh54Fm+fKEnw83R6snyiFqBnMO0jueMlPagKADhPAB0PI1LCNbKzONsFuaIOQZAlaXn6uSqgjo8Cbqmwq5vQTAM88Ipnh7b7Z8dg+xPCAEGAFbXgHTGbkCr1y8WTjaYtFODspJ+ogc4RVKuAzu1Mkgnziv5sEbndVs8fHhSHhdRiUbR5CiVXCyGsqiys+ByCy63HJcigGZUhHM8KEsroJAJdW1OW44fznQRju6VCuhO97f7brGM+iDtOClCFIcA80C7l4VmsLNetAYvk2hVIlxr00ZyH2i2MIuI8zlZi4sdKMu9qJZVWGQjGoKV3UbSLxZOEoYi1shuL8xJ6xeKsI1IzhWZiFHmoiWX4aW4PkOvJnXNZZ3GWZTUPL4m69RsceIHIjLP3RiKAkQBpwHSYbwph4TLZXHtRWRBfq8T/iURGs1kehqnpfI5Gw7RSMOhcSZG5Qs1yFkViqL5oUKZbZQMPcosWrEgONIdrpu/ExqPQMdp2UkdtoQuX4QIsNs2v90qS0N15/I17HjTZDoqlCXbEb/JwQC8MwGeDcwC5ebW9WfnHjBbLgbMPZfzv8E7r18spEgorf/7tE2teJu1sBM13oCZVONrI26roNdYAVKk9XAe43L3K43edMl3YPM2pvPIKE23GOkLYlV4clX/SfSoea021o5usTLPWa7pL7GXXnq5bnIzLYuUoq0N67CqCVfUx8bN1XgUFWBpRA3EZwmr1rMZ1GgEbZ1ZTtT2lslSFHtiNR75tGX95Jk3Pfn4BGrvLpgZ9SPDfUyjEdh6tbnSUREiE1UZeNCPL/4zGoF2d31/+ulTAxGezz3TtHYIQotfUBYL4PRXe3e9Yw6uoE5Zgna2jVcfAL32MvDmu36cgLGKaDpDLYhYovmeTLy573TBaORRjm7eaXs7yh5Ve3cNMnO58LgFtbtjnJnLykRGHNrzmz4M9fo75k3syxMqYDgw9TXKMqAqtTJw7Ds7IFvfw/FTYlkBgxI8DfeUyhJ07y7w/mM7HjOG+slTHH7yVez+6+CgxaAEHxxCf8xUwSje3wdPRoBmLF8y96eeFKhHCsOnCwzffIL9T34IAHDnc/vmHpGKktzUwxfB4xHU19/2aFF67UN467tfwmv/yyw4Pfd2oZ7sGz5PwG9H6rvbUPMl1JN98H0DQwcz8LVh9n7l5GYuFlk04GZmmAfX2Ou0TDFe01cKq25AtQEDz00827xYADbMxXUd8gxYQx8cRqYsz+fWSWb6bcDL5zJqwV4PErkRXk/mgCaUkGvmhu764CByYAIQpfXsvvid93xKtvZRCR1FLuKBs6W4t3q6h3A+9/fBhwMt/NkvAAcH4Zx56NP1JaMx6vV3wG6xsg8JOwefq9Il4dz7B6B5WNC5rg0UWqSZOyG1AFVVeFCXAcW6+8ePoF1uCHNYoF83C6qezYzPQTOG+5Z7whIqo6qgj45x548KPzc+a1RsQ/T7j027swDKwjvv4ZX/q4TeP/C/HTqZGuBW4rtQthiRns1B7mWg2YeNu8jNXCzOW7wDjuP9Yerg3NB6aUQRct8DxqHn8AAR63aCLvWXXRzzFRGJEGMt6OQQfC2O4q3WwVkm5qaJUnW+lzpuZ2PlnB7K+glUcOjJ74sCKbKUCst+7R2TyiZznf0RYMnWbnkqZOjWf3aM7ECoG1IUXjd3DlmfjsS5ZEURuCigCvG7kX0oFfo+B7a0m79YbPoA++taIg0SPuw4Ik/dfuLp930oT90GAMRJFqnVg2x+wqbcluclcU0TFRznLjpiAUiAicB52jbJPWkaarRHRBtxKTR0IzLhUenZtzU4qCh81AFsw6NuIfa6aPN3UYgF5JT6FEUMBEsBUW7BlS8Opcwi58oaFCFSZELC4vxMqQkvpYuSxC+WaIEyAz7d2IT0Ds5eeumlk9x8y+IC5dyJWknFW420n5RA9RSh26hQ0cZXWx1SFKgzbSPuj2aRHi8NVi4NqDIYWuLtx4nV4enmHCbDncO1eEuKfoWfh5TyPgppDUa1QbxKDEI8X97a0yoi7LVfRlZItJUqi3gu7JbSYykWS2M5cMBZcFkAMGzbUAQexNZDZHVpBoaF71+yrNejIn7jOyvH0QL6QlgKrMV3gEEJbLA9ufmLxVnjyyxN5Tr+oadp4zIHQ4JyMuQ3JrfAXee+DGChCP3IAYHn+3DVsMnuzyXoTrOvjWpPtmqRIad14shvWJjrUZEc3cyFETT/Xn/NhnvBRTMKFRybYmFxY0idx1Jvedw8TEkW52Bg2wzAI++Ek4tqXZsIjNy6uQdRwMFNda7SRHaKIua7UBaW7Yl5ra+DjGMwgntbAJebA++XIfOge3p9yUfhjgnCY3bbo0FpFohjCwkfhPtj9Ie4KTXU0FYvOxIgtcEA9bjAIHLEKu83AYqwGAwGZkFzESR3HzbwH938xeK0kuOeTPI1Wv0hiR8hS37jvOoyN0Ti8llHUGNeJFwMaUJWqq/km5QRjgT376MpwntvRDeiLADicC8Lx+RsHiIUh0cBlLUMCVTxQmT7cOLm130G4hwQV7B4huiBZtGv12uxCG2IvTjvH/ioh4+GVBWwWPicEYkuTefc/QY8K7qEqNc1iI/jubHzqR49MQzdTmyaOLsw7WIZFhkH61bWSqlr8HSG4pEh7K1FYl1gb1fQR8cN9jV9eITx60+M5eL1NOOiqoqRnJYnlBfLsMAyA1V3h9jtXSxysokTaF3WaQbuLWuGcq1Ef7X36mftpEwuSq74jsQXRMdExmbDAkph4FG9jLBFMNEPe8mgND9QCg8lwVkOdfQgxTgVFf+rEjPfHZPOwMThDCQRm2g7UIaFQs6Xc8aWZbRAEMUlDpwexvkpHNR+Doqw6MrfyngUOSGpKMCqAgb2DV5rHzolZ/mJ0CmGFXgc4x3SLXDA9syjY7w9DmFSIPBWuJqobrEYlH5xCkWGNstxWlvr9DJkZa3TNtKWnGxaL1T2kXsgy0HMvnTqyEuHG2IfkChvQjw0Devlou7bKl1lXoVNkSexrfLfSZMcecsLpE53n9bp5HJupMXhygBwqD8qraC2bVO2/8w5NBoJ1m5BH5C+fOT9dffW4jlcrVO3GLm6pPLaho6qMGBCmfHqSyRkXnyJpQsAX9S/iwN+0mnF6KMhvfTSSyd5vrYhp038ks7FKH23Y1p31/aBtVZGRAYTkcZ2b+PcpG0+KDj/chR8UQp5mwPtDEl6bW25+qdRTY9Uv4aFdg56ZOuftKnq7q/250cJed6S7KCbvW4lV8k5JiI+X4vFJpJsWRwjU0gbz6Ryy+2K5Op0tP1CaDAMTlN3zO07lTKwW89etfRmqIed26iEd7RJfUmBigxTlig1AFimbmvuN8sj2rEk86BGo4iHAbD7dV9WUJYCKCKmLE+ukuHsoHIQ2nN5IESe/zKi+RdsUGo0Mucw+/wYXwDZgpfcVlrt3TU5IMJnQYCn5ndkM/5+jEag4RC1heCTA3m1MWWJfJzAlDWH+oZXwY8sD6Y2W420FICn5nelAEobxlwsTeWyVx+a41/7eiAwkmUOJmPDzn0UnKzF3h70x16B+ou/DGraiE2DKWswBKoKPJ+HIswA6OB5KgWQ5VzIPMBt57aIXxREzJqIQyLZyUnbpfZhDXU4DOouWSwK1XzLFIVPHiORtAbW5kdUa58vImttegeo6086qMwHf00jdFoUhuquLXSa1BOh4dAnkAHw0GUaDsIPfmfbe9s9TZyuAZqDp3KvHngZvM6AXzAB+HJ+aejUh5UHA0MlV1XeOUyOIq6uTQVzNw93dkDzuXEeiroZPqelLEPuiPVf0N3dUIXchTitg1D+mogINA41VQKGYoHlyx8T734AACAASURBVHcx2D8K7Y5GwOEReHfbnAsYnZjBeyaRTI+Ng5MWFZTWmD80xwdvDgBexLgNZfo2dUtmISy8NcHRR3dw962tQH7jeDFcnRLn4JyMgfki/NacHHW3PK6/g/OyJMeCfVqHpmwvPZYSw7i+UudsZP5n2mnTa9V1XfWW18tcFQ6LknOkRQ7OjAOt0U4q68aWvhgSXSIHpyxkFJHYxNuEcIGygC3h4GybP3fv0vvDDLW9HZLjIJy/pbO6RJ9p8R8Ya48m5gHWxydh+5DqqhLLqCyjgk/uPBYWqZ8H2550SgPAF6rfxoHuHZy99NLLOcr134ZcpXR9e2d8Fm3itz9V/BbL4iBaeTK5WVfE6tWo4+HehjnLJbWkEL+dU/08zqIsG4V8I9zHKr1Fu3FfAdMhwVq5MpCeci5xAHpfBmJHcaPUozu/sEhH4fPxb+Qksc+FY1noBZg5puEQlKZ6E3t/jgeKAX6bSDaJzVVy976fI2udpbidoSX4lSHqsjQWibAsfAIaSdpBBKrB2TzeEtbd7YXbu1ik+I0olRqNm9W8PpzXudYpqch3ENHzu+NyDy+rcyXboxjhF34QUSkAh0RkavgmpJ5eB8D4Vdz18kEWHJzGr2Gg5BEYSbaTTpfcIvjcBNGmLAVQ63hhsqUA/JwXBQi1jXqIBW0yjkrzATD7fZEnEY3fzpfDKZD3WejogYL1+VBZhgWqKPzDSzvbxleSjtmR/FhAGADjO4D1JZSlQcbWNWjH+jf2D7JzSGVp7q+oA0vDIfjeHdDTZ+G88QiYoZGpSsOh6a+uIwcn5j3ce3Pxb+nNQ2m50FU2nMU6CrOtYvdep0e8DzcLCGuOk8Ckg7WlvYaemvO6J9Bndy1Ry3hW9ON/7IKY1z34zBzp2ihtkOgSiYTA+3MVQA7CnX7HUcTDz58LZcq27LlSd4bRlReLQMXvEuxYh4VfB6Ii59BlInONg2XPF415iqSuG+hermuo2QJavpCWVTNnxl7vroFcjDbwaz3/i0VXJ6VA1AFotyyso0tGU2hQmmIzUXPr4djR1qMFpt2qblGIr7XXKSJSYe1DkWujIc45KeHesnuRGOfDnIKTAwCIMwl1mfnwVkShABaIRmcFiGQ2ZxWwJFKWSXpSBmXk8PTnOv6Q3HcJTNsk6Gnzprc0gpKdm1RAWHpn5XAIFrB3Px5nTahlsKZklMJZTUp5GrxsUiJgokKFAi+WUOPS68vjYZw5OxBwbylFATzYAy0WphARYO73SW9ZBFm3f/Z/24clJcPJXiff2CJJS56WbkFcH2LvHMGg28BCubCwu5YzVkRV+YcioouL9AcaiWTueF3Hekm9nRWwWFjPOiIm+VUVuXNV1KPPxHaxsW9r94Z1lo4cq6cLjEPTPJ01dHBt+rwVKe5tnerFGjiZxpXB7GLm9bK+Bq5r8NFx4zfANkEMgPlOJ/dT+Cx4WfmQbtsc8mJhrEd537WGenoALS2FGbwfBEBYzJlBT/fNdy5yw7yaXTyRPhrSSy+9dJLn37K4KDlPuPJZZQVMvQHLvsYScXyEg8HquwyYu3hrB3+K83eICJTbFl3B7yCUUNxQLOr1tNih27tY5LJZN/kxromG+OhKA3Tk0rQpaqMVw98GFsuNxbXvTE8XDalbQrNt43JOSwl8kseLQoxD6E3NkF/ULkR7SV9ptTG/ZfAREx1dR8rlgIj9elmCVMIL4smFM/eJlE13p6CDh3sHCgGXsh6lxrt5JgUMB4F6QDg4o+xb79+wIVLH/wkAxTKkrrf4qlyo1flM/NxMxrF/wqXjNzKoS5/CH6Xlb/CTv8WLRezIbFRRbwkBumujUGTmQadBafexSW6IrxUSYNu80OG4TYn3VHA+hBovLKF9+Idatm/acv6Ler2D08O9B0BF4XrZriNw2dk2uAKbM+JlsQAvMgtkNB8IuSHDYSiH4B7M4dDkNjgnqK2YzhWDSvvAjUeGdMfxRLg+7t0N8HEnhclfIT5GAzsxHJi2FoGty8O9PdsUAJgwaa56PC8W4If3fb/kFobpDGRzQ3B45BcDBwFHWYAHBdTRDFAE/fIDc/3TZ2YO0/nb3jLMWNbHAQDF7g5m3/gAI1eGwJ7HxyeBpcsthJOJsZYWS5Ct9QIAmD5PuSEXJQnewDngmDsstbr24BwAMVWbO7ZYNB6aqFaIrsOPgk1djca5Uk+pr65NTdR0DNUSmCZOz0rHTtjUwZnozvN5w8nGlQamIfzH+6GWB1JnZYuJK+fDjztyptp/p3EVdYj6K75PcQ5LUNH7j0MinhVS5Nm/DLuYCOHO52ZBtvPIdstjXhoBzwDWYFKg+khAw8O9o68/iiHXbi5sQaIIlGUZtcgC6HRVgWdzqK/bGiOZ3w0A6IMjGw0J3+tn+xh/iVCLPCZaLMJLBgigLBvZ4WUFkrk/GzBl9Q7OXnrppZPcXsviLAjOnL8hhedeBoKTM2OQ+9c66NaZVu86IDirKoRE3TmXgeC0GA9THV4J8JLx0dBwECZQ3sfLQHAOBwHB6eZxUwSnIkCfRFtVLHucxaVKK5Dm0hQIDroom9FlKsqq5TJzM8fufR2EAnmNL1x0WV0TGWRmUcRo2AyJT8rpeWlySkIbGgwMeOy019+4FPWzpI275KuzjLkt9TxNo77seW2L5KSpzi16UVmu9Dk0+jqP8a3S2UkH3dfqtS6lX947x9UpyHo8KEv+dtwC7UiBciTFazhDozFKMqU2Pe31juBIz+ftPLGZvj2RkNDhi/XnOnNw3jzLIuWZcBmfbTwI8ri4EWpsq4pbT3hxZ8c4olx17MdPQhKTu84uNmo89lGA+vAQxe4u6sPDoB+A4sUXTTXwxcLfHLWzDTzYM6e98543PfWTZ1Af+wigNeqvfM1cf/8e9P4BaDSCns4Ck9bJCdT2Nmgy9qg/P4adbdCDe36M+p1Hhgnq6BjFfdNv/cSYrGo4gF4sUVgdaltQufzYR8GHFk14cmKg0sMBcO8uYAleFt/yYQz/7Zumk707Ydz7h9CPn/jxSl6F4sF98LFpl3Z3jAU0GUM/et8csw8A3dsDP33m6e3VwxehH70PPZ2ieMFEDHB/D3Q8NfdrPPJzfvjJV7H7x49M7VEPr7ZRh0dPgPEI9dvv2slhqG94FcuX76L811+2OgxNtfjFwiwC0mk5HJiox9cfmXPtvFVvvYM3P/sd+Mhv2q1ApcGTAYr3nuHgr70CANh+4wj1zhDQwME3mt/XYodQbQGT9xn3v3SEN/6OIb/52H//VVPpXUDeoRTwTR9BdWeMwZ++4Z2p+js/gTd/tMJHf3Lpg26Lh9sYvX0AvWV+n64O6+ylCQZHFYZv72PxionSEDP4X/0LdJWbZ1mcl6S0epYGz/sRlov2N5Kr+QCzR/f5F0JoNIrfOACoHPj9oj4+EaHTBdTOjjluFx0aDAMrdZpiror20OkksCDp4xN4Iha7uEkWakjyGqu/2t0N5wifBQkW6eLeHmq7T1Y2g5GZTRgxZ5Yzh/mACJ2WpSeN8fkm41FUu0RtbxlCGB2yJZVl02bmqDCyevhiqGbucjWITEGf4xOgKKBF5EDt7IDGY9SPn4T5s7khUCqCcFOhQNtb0AdH0Rj0dAr1H/5VkI1moK5Nzsd0BvWiWdw4Fzq1RYboeAY83Yf+6IdMu3/61UZlezPnd03o9PFTH5EpH76E6be+hvEffiXoOZm0h06rCnx8EkKnzPh/Hv/P2J8/6slveumll/OTm7cNuSg5bw9fG7xan6Kf3N43TVFf1b5MGPJ7buStpjb9xHHOlCw8lUTJcU2YdUMfB11v69NXHUvmKyHe9f2lfXm1uAFszKZ9uzFUIkHQwalZ0AVoDjygFtfARKbWqi2fSFVIcc+PrQarOMLBtUaxTPT3W263TbfHtQZrWyZTB71uV4r6WZ1twnFESmeqZCVOra592VRvU5UsAGRkereLXLBDDrIOZmOhwLUrWIMoauFTwxPyGwNBToxFMqnV2aLCMgTs9VZBL9+mCz+60OnA6itCgpYghhG2FKHQjgYJHaLQqdTT9u9Rp+5vMafR3GgdKm8BpupWWcap5+6eFaaOaZhHg8Kl0SgKv5pLMpEPokY40rXPk4GYB1N1jBdLw+ANGJh1aebP1TrlkSUtZgaGA+iJOa6cr0L6LGzoWqJVAYDKAsvtEoPBMCx6jqzY/Z6czoPSzBcRPImvQruTOSNrFwsi+jkA/zGA95j5W+2xnwDw9wG8b0/7L5n5N+13Pwbgh2Du9o8y82931uY0ctqFIkkBd6m/lJ7DmTd4mhqdsyIcOlGkvfOy8uDvCCXJOiA4nT5VFfpJ0tlNBfA6PwbpM+BQ61SmxhvRjXYB69OIqOlqEFvKfnf88CjQ6kmLwxG7RH05pGjAB8A5fWXau1NjsYjSsF06vJtTANanYa0CaeUcHJoIQcSMbZ2tywqsqngeFwvDwi3S5N28wRLfyrlEJgUezCjeexYIe5lNbdPFwlD8AyZV3T20dv6VLV/IyyX46BjlI1MXtXblFKK0fJvu7kst2Pt9fIKtNw684xiA8UvM5qE/tzBUlbk+9SnlyIVapItl8fMAfhrALybH/zEz/9fyABF9M4DvA/AtAF4B8LtE9O8zr+Oo21BypQA2tDAc87JzFqmxccB5p2NaX0N8pnIQHFwnJ1DjUeQ4A6xDaRZDp9V4BNq1jswnz6Bc5OXo2NeY0O9ah99oBD458VT+Xt/lopGrIcfg2nd90KCEnk6945OPjvz4o3olVn+1d9fUuQD8wkNlaaIE7vhrL4O+/o6BLAtaeT6Zoo5gzy5xjKC2tvwD5caNydh4/iEcnLs7ZjFyDs69u9DP9qN6F2p3BzybgWsdJUXpj70K9bp1NEqQ16A0RYoHQ+/M9GPd3QY5J+twYKJhVeWdlP5+DkqT62Eh3DJqdvDXXsGdf2UXqFqbCMzhEepvehUAUD7aB0+M7ouH5v7UowL1mDB6usTwL5/g6bcbB+fe46fQJy5UGxY99dIL4MkI6i/fDgvTay/jzb/1AB/+1aMwB3u7UE8PQkV5a43ovW2o6RLqyT74/t1wz/6dKB2xRtY6OJn59wA8WXeelU8D+BVmnjPz1wB8BcC3d9aml156ubZyFp/FjxDRDwD4QwD/OTM/BfAqgC+Ic960x85XsluDzbYjKUOUr6aVIvUyfTWqbmXChZyY064PT9XmuBvd55MkkayKw6KNbYtrX14j20+uSXX0yVkpw9PJtBE6ZcC0uzQWDD09MOYzEKXD+y1DBngktxNh3CLBzW3lLEOV108wVvltzsk0bGt02CoW7+9Dz2aRf4Rtdiwvlg2Tm0+mZtvp9VqatrQG1DKem7o2W5ZFs4jy9htHfssBzd4qcVsLPjwCzUxVtaFL3HKh05M5+OgEu1879nPj+DMi3lLbhl4svb70ZB8PvnTXbGHtuYrZbEvmLnRq7kWxrEz1s+OTaKtNGySSnXax+BkAPwnzO/pJAP8IwH+2SQNE9BkAnwGAMbbWnH3+EsGc7Y+LmGLnXuMiuw2RDjSX15HiLKyDKuWx9JWsgNh5NyijCEcKc05h2dED4foQ7ftrnDmejMtzYqbOPZeijeCLIaKA8AQMX6TT3TsrEeYgF1mKHJWWz7IQuR1i28Bq4XlADUcFWd9vcGTCRSxEuzwZBSegzyMxzmNT0i9ZxJwj0I3dnevwNjISUxSgQeCtkPNc7wxROBxFrY0zsyj81oNmc8+xqbfN9oUHCnpYoGSGOixQ7ZrvhylnBawzfDAARkPv3AUAjEeY3SswUUXYI4yGwHwe+DGcz2Y8Mo7NxQJwuSHM2YW9TU61WDDzIz8Qon8K4H+3f74F4MPi1NfssVwbPwvgZwEDyjqNHucmMm15lYVykQC2xEl6HcByDStB8kg6EtsuDFy5sZx1fNqGPqUzU9sQsS0qbfpJvk8XsvOY53RtTNsU1i/5z+I75lCCkZvs6qtYzkgjHlPbeM5hnKdaLIjoQ8z8jv3z7wL4E/v5NwD8EhH9NzAOzo8D+P0za9lUYL2Dc53jMyGDobI0YT+HdHTe/lzeBwW2IV4s4oQiEV70Xm2nUlkGh+DJSWBNms0Dqu7pU3v90LQpQ2mAt2RoPAIfOzODm+0DwNGx0W1ZhUxDQfQCCqFPN17amoQfn10caDi0tVjNXNX370A93TeWjCRSYe2drv5vO29+PgDvqKTxyJPHunmnrYnJrHTO1a0JcHJi65q6c2yfy8o78gBg+dIuhvuH8QIyHICHA9DSsFGRdeSyZtDWxNQe/cA4LTEYAJOxIbKxoWEnNBwY9KXlo3DZozg6xsE3jvHgXZs1WtUmPMrsnZnDqobeHoOYMX3VwsTHCtWEMPlggMlsiWcfM3Py0h+NQuasYCrj3W3w9hh48swT7ei9HTz+VsK939/xutYPdlFoDXb321pCy/tbKKZLFFqjvm+d4Brg98/RsiCiXwbwKQAvENGbAH4cwKeI6BMw6+PrAP4BADDznxLRrwL4EoAKwA+feySkl156uRJZu1gw8/dnDv+PK87/hwD+4VmUugpxPoZoX5spTgvWvhaFlxQIZc+VfgXfh6OGEyAfUuT34eFcCxqyvI/S50COA9O17X0WCShL6pmrmVFndFeqGaNXZPR2YeWR/UwU3uxaG/BRVJBYtG3HYj6rxjH/nQOFJX+zPR+A0aU0Pp7IdzCxx0XtFHZ6K/ud5NUsC+hxGelAShl0pfWreCEzB/5cMW+LHQpzQwQelVBliXoUAFE8UAAbiwIAllsK9RiothR4PMByR8yNBexFrG0uIU74svSwwHJPe0vGHVODEjwoTaJYqcLxyua8DFyeUQbtukJuPoLzlLLSkemksb8NHAtRYZfchDsCV1nJOiGLaaIp43YM+Cqjh9bGcZc6Le0PWurVeEDFd5zTvSyaP6CE/EYPChSagaIJfnJ6I9U7N0eDMl6QXP9ykSuLxoLGduycOGfrkXjAvXPSPGSmyBDFOqULgnN42oUvJcLlQdEoFgQA1Rb8A0ii3Xps78+ggB6a76uJOVaPgcUuYXhoxlq53RwZPxArRFtYHhSoR4VBeFJYAGjPJQaadvXIzlepwIBfLOqxAukSxaBE7YoUMaMLi6STW7tYpA5ErmuD/5c+hoTgNZyro+hHlh2qqjJ9aNB8EZ3jxfFD+h+7WGRINR2ei2WjtB9XlQcYNfRMMhndtQ3dZ/Oo7B6URVoKvcvDubVMRE5EHdCUAe4dz4eX2lpnEhFpGZtoOotCp9E5zucxszyTdQ0uQxRp+HQRolMualFr4HhmrpXclKwN29ciuY92/Kw5mhsCoI5moaCP8M1M3meTPer6YwYvlxg9taHmkzlK68icfGAssWpLYXhIGO7XoOkCW49cTkcdLAv3GlAEdTRDqeGRvQBQHsxQvn4PqJ/53215MA+/MQ4kx8NnBYrjBehkhsHTQLJM9fOeG9IFZ7EGfxER2JKNw7M2sGZ3TraqWFINjB2+ID5P2x+9h1wDwGwOE6kl+8O0TWgGHx5GiT1aEufKSmYwPxiWUG2HE1hWJp1b6m+/9+OS8GrWDZyFPjpu4izqGgrwx9X7Ft4sQ4usRWp5ZoGdzcPDN50ac3ixbOAs9PGJOW771scnnmjXjUEd2IdGa7PIWhm++QT66NhsJRPCWp7OgGEVzQkfHkFpjdrp5Ra/TIo6CovXcIuEaOf+l46ApxZToU2uBx8dY/iXBsvIRydQhyY3ZDIzCwiPB2aLNV2ADo5w/0vGtGA3XlH9jJjA+wdQJ1PUAhVcvP8MH/p/d4FnB/5lUiyWBqXrLB+7cA9OZh5noSTDeaaaXptc/8UixzzlCG/kZ2lOyihISzTEw5ztzVd3dkws3sF4HQHKMrA/O0tDDQMvRb1/ALWzjXr/INJT7d01sGVxM9SdHeD+nokOvPUulIVm89NnwCsPzY/VwqWLe3vQz/ZBwyH0dBao5+saNJmARsMG+Y3anoDuB/IbLA05TH1Q+75S8hu1baIn9TMbfXj4AsiT30zNNmU0Au7dAe0bro2Tb30FW39sFxIHHWaGenYIfvI0bI+cBVHXBrZtFzK1sw1f3zOJkODBHujxsxCdefgC1NuPDG/EHUu088Ie1OEJ2I7Pyf4nP4Q7f2TNcLcNHJjtQ/HoGXg8hHIWltbAqw8xf7iLgZ1HGg4Mqc18AYxi8hsaDKBffuBZuD1x0dffxht/Zxff8L9ZPopKQ08GKB/tewj37teOUe0OQZp91GNpyW+2HjHuf2kLX/5PzX34q28+APYPwgsFMC+zD7+M5d0RBn+y9Jwa87/yCqoffQz9Yy+bJDEA05e3MXnzEPX2EMSAHph5mD4cY7hfYfTWPmavBri3/sNzhHv30ksvvQC4AUxZm3BanvZcyb0o0qsbDN05zEWb9eL4PqM+Vdy+R2AKJitR2MccSOpoMDdYvuSYSDjlTP0IWnuNbxfwjGGN6SrCeGg08ts2j9Owma2mBGFc2s/PpWTytvPdKGScFgKS98COwVcKt3PqRE3GZnukknlI8C5ON5NkNghbN3v/nVM60s0VdpJM4HaOy5cf+oQ4x97Fy8onzHm8DHOwoNxWSddma2ApA/UHj71FFjF1DUpTZ2Q6Ddbr1panHfRbQlucSkaX3HHY2im+UhqAL0z/D+zXH3Ryc17/bchFScPvkcnBSM9beX36fcKDYY9xJUlkxOnp3rElx6LRdqJTq/5tRLCpEzZTMMkcF/rYLUKaNr9K4nMtX0VmHKmfKPpb+GaChHb1yYl50JkifdLFJxzXAIsUeA5OzQZineuo2pp0fupn+zEVnqUn0CdWX1G0yPsIFHm0KS8rwG5jI6e1BGUtFqZ0opgbPZsDHzyJ6RudczZR33Ghpgs0b0DG9HxtQ0i1P2Arr5MhTJX8t0FsKddu7vpURwo5EqQovHnFsbjNS7xtYi68bslxqT/gMCIt+A7f7BnmNWknmjPbp9chmUN/3OEt3HyeZU5TUhwX3szMjdfb5SMReSIkj8txltGK6/3Y3TXyfsjxpnNzBrn+lsUm26S2t+dGfYi3TBv5zcZtWhEWRhwmrcG2QjdXiTWySseLFmFxAcISomAZROFROy69EH+jzmzVkus21kvopANwjgoEnTh+Q7v+vAUgLbezUiqm1pyLllkQQ2R1OeuIjWXB4ChM6yNoAhDYNlesrSVpt3+AXSQEOVM4fvbfzPNlWfTSSy8XJtffsrhKyZQl7H5txhmafp9+dpyf/jPO/tY7i+SQnAgmbswNyl5/+X3UTrrdO+3YcjB88TmiELDUgK1m+Hlsh3K8pwnWxPsMMrB7YmrMjacQcO21zZVyW5WW+ThHub2LRVo3xBYUkvVAWrc1KsB+ebkwEYRlTC7TqFQFRHU9GnVDbPamrxtS2Di7w5FIfUmBhpm6IaIuie+jKMDVsr1uiKDrA4yHPTKJnd62ngcAqPt7hrJvWIRMUNs2uyreiWTrhgyHgXvULUSuPonDX0wm4OnU1mcZ+HOwNAhWmcujHr4IbWnvvAwLqOGOBWvZaII7fzI2OJSnVq9hGfg8BoOIMIiI4rohrirYyQnwTR9B8dZ75kSbIczTGdRLL5h5zNUNcbkeRzNTlf7DL5t2/+1XLbGRGANrFPfvmbohT5/5eSxfegGzb3kNoz/4ctBze6u9bggz+OAwyhSmD7rjLG7tYtGo8WmL7TYKFLddK99IKxxY0U23hXhdG1FyWJncCkuo44lfEnZvl/gGiDf4KvIbt7iJ77LkNzIsKXJaHCkNYB9W55STejv2rIxE7N7uB2xpAYx+glRmuTR7dneO+yzOYW3JlWV0YzzKzqMhrSka39GgNOn3Qi/yDOXNvJGI/Eb0W90ZY/ieXQyUZeFeVlnyG/bkNybXo9SAOpliedecWxaFH2+sqyW/kaRIoyFmDwYYiVAoxiNgsQjkN+6+T0aGFWs4COQ3wEZWyPXHWaSyITFv41qg3fkonY6r+kjRohJRmn6XXBdVABN9ebxCjig4JxLHIbY7DXyBM2HTWprpeIUebTgLT6LramYCzf7adM5syyJMhdjiSFxJhLOQ17lzJM5iPPKIXN+tjQT4foS1SDZZzHOXiEpz0TWunaJo4iw0o7h7x5cUlHMRcBbLYAHZh9hlHbNl41Z3HML2aXYOaTSKUZ1Wf3VvD/X7H0THWObAyJdFURiUco+z6CCr9n5rcklCG5mHLO0DyG9hUhxEiifI6dMmLRmdoVYHwt5XZ94eSfvuoWx74OVx7bgqU71X6ZyJKmWT9PxWMDyMJiQIP6cx9kLgLGbzxrybNO8VY0p5TB2X5bgM0QhX3Mgl+yHMsxoOTD5Nik9hFuUBtKfCc8Q1DPjfI9e1396symViWKvSArv0dAY8fdbEu7golLyeFIqdbeh0vBv4jfpoSC+99NJJbp5lcZZtU2qCIpj9NBpF9HU8n+e3Am7LIM6jQQmex2au2tpqMHDTcAi1FRyZzjmop1MUe7bKuaPVs8V/3Rtfbl+oLKNizJ6uTrTv+jAw34UvYKznsXmf0ggW9+75z8HBqbyjEUCAGCsV4Mu2DelAlKImk2DCO6eofSubjgs/b9rS6AEwJv7hIbiqoMbGrKftLeNstY5IT//32oeAd96L/TDW16APj0BFEeqasEaxtwfamqB+ZJyTVBofRkrY63wjxe5OqHNix1AfHkJ/5ycw/PLb9l4Ywl4+PgFes07LJ/veT6D3bN2YoeG4KA9mKN5/hvlfMRXXB1/8M+jZPGzHrJQvvQCMhraivLFYyo+8iqff8Qr2/s+vhm2brbvSIOzdnoCWFYpBCbqza+eAQW8L/8UauXmLBZDPOpXHVh13X9uHqj46BilCcW/PZFlaT3H1zrumEE9dNyMmkwloHIrMqDt3QvEat1g8uA/eP4hS3ot7e6hfNR5y9dU3TdEaAHj3PdQff81wEvxLkxVavPAA9QePIHHw3AAADFhJREFUTb7D0XHQ98BkudLurv/hwmfO3gG/+qLvj75agcamkI960Xrm37UPhi1S5DI56/dNcTn90VdQPLHQ44Mj48gcj1G/fA/FB+b4B9/1Gl74v80DWb1sFjmqGcUHB+C33/3/27uWHTmSKnoi8llV/XR7XtYwM54V0iBWSPwAEnwDS3Zs5lfYAh/BDyDEAonZILFBIyFbgw0zHgR+dFd3V1e+4rKIuBE3MrPc5bYHd9t5N5ajMzMemRWPe8+5Jwyy8Jnod45ADtKsDu09Zm8O/fCRa48dT/P+EZJ/PwGt7Q+CPv4A+oFBtzzz/In2zi0kz85tXoudmc+j8c3P3sWdP6agJAE46UuRoCsTlA+eghYl9L2H7j0ZmE/v4OyTHez9wbFOZzPQ4R70urYM1WfL0JdZifXdI5RfOkfzoR03dW+Nrz9v8cFvPrTvrTFoFinmD5f4+qe2vUdf7mN9mEAZ4MkP7P3NgYE6qJE+OMQHX+yi/dxGcYpfvgM8fmr9E97RrLH+7EOsjzIc/KkBnIL9sx/fwZ9/9Wv85Oe/8HkplndL7N9fodlzC1Fq61t+lKI8Ntj7ah/LT1lFHWh+v/0UcPMcnH27qsOTQ5Ei7AihDUlVFZyIfSJZz1EpV3nfLA4VCiecSpJANa+CxBw1LZKdBYgIhhXD8hwyn0S/PigdzslMAnMrI5u5uHCh0xYqY6KayKw04ljVi0XoC//YOcrC9bjVC8aEUK3TDTFVFTn/eIxlf6weqcv25CY6H5FwiYqD76Dwvgif6JefZUy0s9CHBzAnS+tMlBDsrrPEtyTxuyMyBL2YQy/m6B6HcKtKU0sG6zkTkSTWsesS/vK4mfUa+offh/rnt+HaLAedn0O7dAF0ceG/JVaMY81TdB1wvITh0Onf/+HzWUiynJ6VQJbCnCxDPovbt1F/9j3kf3sY3k2WWQ0alpbgcS1LUFWBLtY+DQMAfHH8O5zU/3lLHJwvO9l5KLJTsx7Rvr2SbZMi/xKLcB+v4HnbVTpkZ7KzMVLfHty2gUy3KTTHWbiuak4RXAmRIRAFeQA10p4R0tQrWSwHpLN+GkQK3kHZVqWgDIV+cBvJAEZfDtUmY3cURP6d+P7039ELEMY22eTgnGyyybaym7+zuOIxxK/YQvkKIg8AARvDrByzBrBZkSxL0SdaqUT7bTvVTTgCOP0LBQCnbjVRyoa1VAZA5L4wsCHRTIT2eLuaJJHDUQndkSD43Pg+UF+PBLBbVOdA8ysbIzhZ42N3AVqtIkUvlcLSnZXGGHGK/T3cTsAeJ5RwogLO0WxEPs/C6miQCUcxVeQ2jCiOZwBAB7tQqwvHwlRhTLT2IspGih1zxjMB+rLoUJfzIVxqn7OY2zEFwvGrqlC/t0D5xOm1ENkxaVuYA+tI1EQWlEWE7siWmTyBKRKkywpJ3eDifYvsLO+Hbyli8i7mQFlAna/Ce9ndwfJuidv3srCj2Nux+VvznoNzdw61dm1nBycAnG6/lb75k8UVt5HhPB3yE5ChoQT9BnxAdMgbwws0bXRm5zr8D7HrAMHOlIrd9u9iIqBYpYqELyNqY9cFgJFsJwlNUYkTcAlrono5d6h8PgBAlC9PvYYoZIJgkUw2fihFeTXRBjBaP48oqiq8C1jfzkCX9WLt4PgUba/10xPrUJYYGJdp20PIJWN13cvLQQZYIyTykQsAkc2P6RP2hvLi0dJGP9gc+IkdpFZ71EWb2L/iMpurqgadnWH2tYX5G9930Val7fMZSs/f0+kZ9u+vYp1cQ9Y53AhYPyy+g5pm8J2Nfbub7OZPFq/KRsg/z722R14aGOty9O9zWhlK1341pRbRCunvh11dqJev3cO4fb2CfBZJDYicHB6Z2COt9dsuYOSsN+rh3lwuYc+MBjTuBybHQyqSJYJKLlb9qK1cJt+FvEaiEYlA6GK/R5GHXYusQysLhhJp9P1zpNYJvx/ecYmFQynltFJEO13fzDy3P34eBw6t8+pepYEbwjvLLPURG6QpukXuuqg8+CoC02XuGWJsVJah2cuRCp1clWd2omBoO7e3yO3CUTchrOrav61Nk8VrMOKdwjWIRG1rA1kDFzEYdeSO6ImS2B29Ap7nZus7TtlB29dFjXJi8HHrFbVhC1SkIpfNiqMYA7/yC3wbV9WbfUGbJgthA4LYyzxLEn565VxX5B+5pN4B8e059b6MSTUw2lDuVcOA7cZLZoFi0zHdXdZDopwzSUX9loS0/pGD2xZl9FL+b6EiFxLWQyX3fj2yH2P9JUk603C7GW3LfV28I3G7yVSDUu0V1zkLdyLGJZowHJekP4YmHRlXmTGL28BKc5K+T4QXmbqnaMhkk022ld38ncVVoyEMHPLsRm2TufSo3AO2JJGjiLsVonH39vPcZhlU14uGZKnV4ACsY5DPjnVjy/tqaEA4o/YTvHDeBcDXoRIdng9ArVa2bS0i1Xf7COX6G/oBwN7fI9WpJLHlXN9iBhw7fQ5RHzoTK5/J7UCWBR8AMy+L3DsZve+jKJwzrg3t4ShMKq4BBpmqu/0F9MkSMk+pSrStr26sz0GSQ7PcqqFHoLk8wP7Fd6XS1CJ3nTPRg99WK6zfnWHnWxcNMcbW07YwBzbCkTSt9VUQobnl4P55gq7UyI8TZKs1Lt6zQKmdhKUW44Q2ajazNPNngcJOixmWH6XY+WvpHb20O7f+GRd98eC3/QVU1dix3XUITkPAk+33Czd/sriMEr1pMunRu4kI/czHY7wQ6CTeViplPxyv+BUiExb9KXNYdp51CKkyRmZEXtBFKxhB2sspaevmjxyhTRIxmqZQZQFFIj2/YKRCUeSoA2DDdp7OzZOkicoVRzaI4nb7Po+Mt4xEiCiO3yY7xy+0suHbJDzXh4l9NMVNJuxQdaarZoRFmnjoNOen9Na2VlCIy0QoGEcHUE5lDF0XNFB9ZQoqy6CLAtlZ68OdZIwFWDUt9IXrQ92AhZQTV6ZbY7VHz2ugbpCfBNSsj4ZEHSGotgMlCRIncKSaFuWxiSJgal1b8SUuYIdv1aB+bxfF8engudvazZ8sNtkllPMBPdrRsy89wZkuxmAwFbnvAGS9TlkuQpvUdUF6jyh64XytbGdEQ+46p3Uqw45xWBCwVHLVGVDbBJChU2/z8oW9SY6qahg6JeNDmoAN2UU5E0Sfn0ux5uf5VP5rn0BXdcZjJ1iThMdhQD1n/dPe+OqnJ4N8FtAuEU3dDK6nqooXCEdOo66Dkhm/jJvUIrnFFUhrmKpC/ujEh07JLVBU19BPnZaIC3sCIXQKrS2pa7UGna9QfGOvNc14+JmWp1YWcV15mnmSpdj7an8Ydr9Yh0mc/Ttti+L41GYMa8VYTqFTYRt2FlESGsBlysLlmbI4dTtv67tu9BgSQFniZQjQlKrrCCjlwVSOe+AzZTG3Q3JDkqQHyoI/mkjcv2pad7zSm48hY+zbwVjpAJYCoHZ3oM5XA9Yp92V0vEV7fVq9WRlAWVzmtus+TOuuISFopGal/WErFYVW6dY+1LqHI3BHC8XANLkKFwXUfAbF8oVZavvTtlBFHjAkjkMzAGUpDawr1Hf2UTjJRxjjdxEs7agAzzrtbjluSJagK1Nkz3LorvOSgvm/NiQfYlCWwFSovV0sP53j8H4Zldm+9DJluaOHajvgILBOsdw+BDQ5OCebbLKt7M3fWXxHWIbrwNa91MjgpdYDvx3+jtYUGRp8WWIZAEmo8pa48rG/XfasLd+xktdK0lj/eUAgnRmy972MEWFj0tNBvUMksnpBcuKbP1lsaT6+P4Ix2HQ98JxJYwTvoJQKDrT+Nf1kshtwGtG93mcg/BVabCslknLbH6LEDPg8jtq2j7fXDqqMfn/qGhttTPpAZOb27dO9bbH8v7hGJQlYV5SNimwECZvYaIjk88i+pkPkrMeQ9N+hGAP5rGaeIve5NVuP4DSlHZskTT0l3czdv7lGWybQFyl0mqJd2Oflm3AyaWrHXQUnLeUZ6r04aTIVmf0/o0f5Oy0zqMYdmfn4a2j0O91k1yKfhVLqv7BBrceXXfuG2W1MfX4b7Dr3+WMieufyy67JZAEASqm/ENGPXnc7/p829fntsDelz5ODc7LJJtvKpslisskm28qu02Tx29fdgNdgU5/fDnsj+nxtfBaTTTbZ9bbrtLOYbLLJrrFNk8Vkk022lU2TxWSTTbaVTZPFZJNNtpVNk8Vkk022lf0PoRBktp0hu08AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.19529509544373 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1e-05, 'kernel_type': 'branching'} is: \n",
+      "[[2.05236728e+03 1.28000000e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.28000000e+02 5.76432304e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.05236728e+03 ... 2.05236728e+03\n",
+      "  2.05236728e+03 2.05236728e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.05236728e+03 ... 5.92543017e+06\n",
+      "  5.84461806e+06 6.77537887e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 2.05236728e+03 ... 5.84461806e+06\n",
+      "  5.90507818e+06 6.92338123e+06]\n",
+      " [0.00000000e+00 0.00000000e+00 2.05236728e+03 ... 6.77537887e+06\n",
+      "  6.92338123e+06 9.32957663e+06]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea63c8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 94.81863570213318 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 0.0001, 'kernel_type': 'branching'} is: \n",
+      "[[2.09213005e+03 1.28000000e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.28000000e+02 5.80343257e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.09213005e+03 ... 2.09213005e+03\n",
+      "  2.09213005e+03 2.09213005e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.09213005e+03 ... 2.97826328e+07\n",
+      "  3.40288680e+07 1.89877067e+07]\n",
+      " [0.00000000e+00 0.00000000e+00 2.09213005e+03 ... 3.40288680e+07\n",
+      "  5.92507869e+07 3.00120948e+07]\n",
+      " [0.00000000e+00 0.00000000e+00 2.09213005e+03 ... 1.89877067e+07\n",
+      "  3.00120948e+07 1.19534827e+08]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.58856081962585 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 0.001, 'kernel_type': 'branching'} is: \n",
+      "[[2.53829169e+03 1.28000000e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.28000000e+02 6.21536789e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 2.53829169e+03 ... 2.53829169e+03\n",
+      "  2.53829169e+03 2.53829169e+03]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 2.53829169e+03 ... 4.44140645e+13\n",
+      "  4.45652338e+13 4.21954983e+09]\n",
+      " [0.00000000e+00 0.00000000e+00 2.53829169e+03 ... 4.45652338e+13\n",
+      "  3.12277825e+15 9.62423362e+10]\n",
+      " [0.00000000e+00 0.00000000e+00 2.53829169e+03 ... 4.21954983e+09\n",
+      "  9.62423362e+10 1.12322503e+14]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f9418cd30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 94.8605318069458 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 0.01, 'kernel_type': 'branching'} is: \n",
+      "[[1.70815992e+04 1.28000000e+02 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [1.28000000e+02 1.35966636e+03 0.00000000e+00 ... 0.00000000e+00\n",
+      "  0.00000000e+00 0.00000000e+00]\n",
+      " [0.00000000e+00 0.00000000e+00 1.70815992e+04 ... 1.70815992e+04\n",
+      "  1.70815992e+04 1.70815992e+04]\n",
+      " ...\n",
+      " [0.00000000e+00 0.00000000e+00 1.70815992e+04 ... 2.27763626e+38\n",
+      "  8.91514027e+34 6.72817008e+18]\n",
+      " [0.00000000e+00 0.00000000e+00 1.70815992e+04 ... 8.91514027e+34\n",
+      "  1.03384035e+44 1.37631692e+25]\n",
+      " [0.00000000e+00 0.00000000e+00 1.70815992e+04 ... 6.72817008e+18\n",
+      "  1.37631692e+25 3.17110846e+35]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551fc828>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.3538761138916 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 0.1, 'kernel_type': 'branching'} is: \n",
+      "[[1.11495540e+009 1.28000000e+002 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [1.28000000e+002 2.23378944e+008 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 1.11495540e+009 ... 1.11495540e+009\n",
+      "  1.11495540e+009 1.11495540e+009]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 1.11495540e+009 ... 6.78790002e+127\n",
+      "  5.80638111e+101 4.86670797e+054]\n",
+      " [0.00000000e+000 0.00000000e+000 1.11495540e+009 ... 5.80638111e+101\n",
+      "  5.73285007e+142 9.51779041e+076]\n",
+      " [0.00000000e+000 0.00000000e+000 1.11495540e+009 ... 4.86670797e+054\n",
+      "  9.51779041e+076 2.64101291e+110]]\n"
+     ]
+    },
+    {
+     "data": {
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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.12283635139465 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1.0, 'kernel_type': 'branching'} is: \n",
+      "[[7.86292024e+023 1.28000000e+002 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [1.28000000e+002 5.81864238e+042 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 7.86292024e+023 ... 7.86292024e+023\n",
+      "  7.86292024e+023 7.86292024e+023]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 7.86292024e+023 ...             inf\n",
+      "  8.57709940e+288 4.14238452e+164]\n",
+      " [0.00000000e+000 0.00000000e+000 7.86292024e+023 ... 8.57709940e+288\n",
+      "              inf 6.09633722e+230]\n",
+      " [0.00000000e+000 0.00000000e+000 7.86292024e+023 ... 4.14238452e+164\n",
+      "  6.09633722e+230             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7c18>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.5284788608551 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 10.0, 'kernel_type': 'branching'} is: \n",
+      "[[2.15790457e+050 1.28000000e+002 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [1.28000000e+002 9.51803346e+116 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 2.15790457e+050 ... 2.15790457e+050\n",
+      "  2.15790457e+050 2.15790457e+050]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 2.15790457e+050 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 2.15790457e+050 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 2.15790457e+050 ...             nan\n",
+      "              nan             inf]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f95ea6550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.42967677116394 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 100.0, 'kernel_type': 'branching'} is: \n",
+      "[[5.40863544e+080 1.28000000e+002 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [1.28000000e+002 1.92965250e+203 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 5.40863544e+080 ... 5.40863544e+080\n",
+      "  5.40863544e+080 5.40863544e+080]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 5.40863544e+080 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.40863544e+080 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 5.40863544e+080 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.95684504508972 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1000.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.68603835e+111 1.28000000e+002 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [1.28000000e+002 1.29425808e+291 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 4.68603835e+111 ... 4.68603835e+111\n",
+      "  4.68603835e+111 4.68603835e+111]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 4.68603835e+111 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 4.68603835e+111 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 4.68603835e+111 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98acdef0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.72212481498718 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 10000.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.61907035e+142 1.28000000e+002 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [1.28000000e+002             inf 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 4.61907035e+142 ... 4.61907035e+142\n",
+      "  4.61907035e+142 4.61907035e+142]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 4.61907035e+142 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 4.61907035e+142 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 4.61907035e+142 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f941e0f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 95.91179156303406 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 100000.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.61242394e+173 1.28000000e+002 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [1.28000000e+002             inf 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 4.61242394e+173 ... 4.61242394e+173\n",
+      "  4.61242394e+173 4.61242394e+173]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 4.61242394e+173 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 4.61242394e+173 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 4.61242394e+173 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 96.60271716117859 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.61175981e+204 1.28000000e+002 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [1.28000000e+002             nan 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 4.61175981e+204 ... 4.61175981e+204\n",
+      "  4.61175981e+204 4.61175981e+204]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 4.61175981e+204 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 4.61175981e+204 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 4.61175981e+204 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f551e96a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 96.4047601222992 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 10000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.6116934e+235 1.2800000e+002 0.0000000e+000 ... 0.0000000e+000\n",
+      "  0.0000000e+000 0.0000000e+000]\n",
+      " [1.2800000e+002            nan 0.0000000e+000 ... 0.0000000e+000\n",
+      "  0.0000000e+000 0.0000000e+000]\n",
+      " [0.0000000e+000 0.0000000e+000 4.6116934e+235 ... 4.6116934e+235\n",
+      "  4.6116934e+235 4.6116934e+235]\n",
+      " ...\n",
+      " [0.0000000e+000 0.0000000e+000 4.6116934e+235 ...            nan\n",
+      "             nan            nan]\n",
+      " [0.0000000e+000 0.0000000e+000 4.6116934e+235 ...            nan\n",
+      "             nan            nan]\n",
+      " [0.0000000e+000 0.0000000e+000 4.6116934e+235 ...            nan\n",
+      "             nan            nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f98ac4198>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 96.75548815727234 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 100000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.61168676e+266 1.28000000e+002 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [1.28000000e+002             nan 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 4.61168676e+266 ... 4.61168676e+266\n",
+      "  4.61168676e+266 4.61168676e+266]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 4.61168676e+266 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 4.61168676e+266 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 4.61168676e+266 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558f8128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 96.8838255405426 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 1000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[4.61168609e+297 1.28000000e+002 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [1.28000000e+002             nan 0.00000000e+000 ... 0.00000000e+000\n",
+      "  0.00000000e+000 0.00000000e+000]\n",
+      " [0.00000000e+000 0.00000000e+000 4.61168609e+297 ... 4.61168609e+297\n",
+      "  4.61168609e+297 4.61168609e+297]\n",
+      " ...\n",
+      " [0.00000000e+000 0.00000000e+000 4.61168609e+297 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 4.61168609e+297 ...             nan\n",
+      "              nan             nan]\n",
+      " [0.00000000e+000 0.00000000e+000 4.61168609e+297 ...             nan\n",
+      "              nan             nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f558e7f60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      " --- kernel matrix of tree pattern kernel of size 183 built in 97.23178291320801 seconds ---\n",
+      "\n",
+      "gram matrix with parameters {'h': 10.0, 'lmda': 10000000000.0, 'kernel_type': 'branching'} is: \n",
+      "[[ inf 128.   0. ...   0.   0.   0.]\n",
+      " [128.  nan   0. ...   0.   0.   0.]\n",
+      " [  0.   0.  inf ...  inf  inf  inf]\n",
+      " ...\n",
+      " [  0.   0.  inf ...  nan  nan  nan]\n",
+      " [  0.   0.  inf ...  nan  nan  nan]\n",
+      " [  0.   0.  inf ...  nan  nan  nan]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2f54894e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "3. Fitting and predicting using nested cross validation. This could really take a while...\n",
+      "calculate performance:   0%|          | 3/774900 [00:00<8:40:16, 24.82it/s]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/ljia/.local/lib/python3.5/site-packages/sklearn/linear_model/ridge.py:154: UserWarning: Singular matrix in solving dual problem. Using least-squares solution instead.\n",
+      "  warnings.warn(\"Singular matrix in solving dual problem. Using \"\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "calculate performance:   1%|          | 9224/774900 [04:52<7:27:00, 28.55it/s] "
+     ]
+    },
+    {
+     "ename": "ValueError",
+     "evalue": "Input contains NaN, infinity or a value too large for dtype('float64').",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-1-a014d0395ba2>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m model_selection_for_precomputed_kernel(datafile, estimator, param_grid_precomputed, param_grid, \n\u001b[0;32m---> 17\u001b[0;31m                                        'regression', NUM_TRIALS=30)\n\u001b[0m",
+      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/utils/model_selection_precomputed.py\u001b[0m in \u001b[0;36mmodel_selection_for_precomputed_kernel\u001b[0;34m(datafile, estimator, param_grid_precomputed, param_grid, model_type, NUM_TRIALS, datafile_y)\u001b[0m\n\u001b[1;32m    115\u001b[0m                     \u001b[0;31m# loop for each split on validation set level\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    116\u001b[0m                     \u001b[0;32mfor\u001b[0m \u001b[0mtrain_index\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalid_index\u001b[0m \u001b[0;32min\u001b[0m \u001b[0minner_cv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_app\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# validation set level\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 117\u001b[0;31m                         \u001b[0mKR\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_app\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mtrain_index\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtrain_index\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_app\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mtrain_index\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    118\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    119\u001b[0m                         \u001b[0;31m# predict on the train, validation and test set\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.local/lib/python3.5/site-packages/sklearn/kernel_ridge.py\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, X, y, sample_weight)\u001b[0m\n\u001b[1;32m    145\u001b[0m         \u001b[0;31m# Convert data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    146\u001b[0m         X, y = check_X_y(X, y, accept_sparse=(\"csr\", \"csc\"), multi_output=True,\n\u001b[0;32m--> 147\u001b[0;31m                          y_numeric=True)\n\u001b[0m\u001b[1;32m    148\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0msample_weight\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msample_weight\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    149\u001b[0m             \u001b[0msample_weight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msample_weight\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mensure_2d\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.local/lib/python3.5/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_X_y\u001b[0;34m(X, y, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, warn_on_dtype, estimator)\u001b[0m\n\u001b[1;32m    571\u001b[0m     X = check_array(X, accept_sparse, dtype, order, copy, force_all_finite,\n\u001b[1;32m    572\u001b[0m                     \u001b[0mensure_2d\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mallow_nd\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mensure_min_samples\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 573\u001b[0;31m                     ensure_min_features, warn_on_dtype, estimator)\n\u001b[0m\u001b[1;32m    574\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mmulti_output\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    575\u001b[0m         y = check_array(y, 'csr', force_all_finite=True, ensure_2d=False,\n",
+      "\u001b[0;32m~/.local/lib/python3.5/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_array\u001b[0;34m(array, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)\u001b[0m\n\u001b[1;32m    451\u001b[0m                              % (array.ndim, estimator_name))\n\u001b[1;32m    452\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mforce_all_finite\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 453\u001b[0;31m             \u001b[0m_assert_all_finite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    454\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    455\u001b[0m     \u001b[0mshape_repr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_shape_repr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.local/lib/python3.5/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36m_assert_all_finite\u001b[0;34m(X)\u001b[0m\n\u001b[1;32m     42\u001b[0m             and not np.isfinite(X).all()):\n\u001b[1;32m     43\u001b[0m         raise ValueError(\"Input contains NaN, infinity\"\n\u001b[0;32m---> 44\u001b[0;31m                          \" or a value too large for %r.\" % X.dtype)\n\u001b[0m\u001b[1;32m     45\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     46\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mValueError\u001b[0m: Input contains NaN, infinity or a value too large for dtype('float64')."
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "calculate performance:   1%|          | 9225/774900 [05:10<7:27:00, 28.55it/s]"
+     ]
     }
    ],
    "source": [
diff --git a/notebooks/run_untilnwalkkernel.ipynb b/notebooks/run_untilnwalkkernel.ipynb
index b1b65eb..4eba502 100644
--- a/notebooks/run_untilnwalkkernel.ipynb
+++ b/notebooks/run_untilnwalkkernel.ipynb
@@ -3,7 +3,9 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {},
+   "metadata": {
+    "scrolled": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -16,7 +18,7 @@
       "\n",
       "2. Calculating gram matrices. This could take a while...\n",
       "\n",
-      " --- kernel matrix of walk kernel up to 0 of size 183 built in 0.217087984085083 seconds ---\n",
+      " --- kernel matrix of walk kernel up to 0 of size 183 built in 0.2203214168548584 seconds ---\n",
       "\n",
       "gram matrix with parameters {'n': 0.0} is: \n",
       "[[  5.   6.   4. ...  20.  20.  20.]\n",
@@ -30,9 +32,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f24bed1bf98>"
+       "<matplotlib.figure.Figure at 0x7f3789aed9e8>"
       ]
      },
      "metadata": {},
@@ -43,7 +45,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- kernel matrix of walk kernel up to 1 of size 183 built in 0.31014084815979004 seconds ---\n",
+      " --- kernel matrix of walk kernel up to 1 of size 183 built in 0.321882963180542 seconds ---\n",
       "\n",
       "gram matrix with parameters {'n': 1.0} is: \n",
       "[[ 13.  14.   4. ...  20.  20.  20.]\n",
@@ -57,9 +59,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2502f81978>"
+       "<matplotlib.figure.Figure at 0x7f3787a59da0>"
       ]
      },
      "metadata": {},
@@ -70,7 +72,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- kernel matrix of walk kernel up to 2 of size 183 built in 0.6249465942382812 seconds ---\n",
+      " --- kernel matrix of walk kernel up to 2 of size 183 built in 0.5602786540985107 seconds ---\n",
       "\n",
       "gram matrix with parameters {'n': 2.0} is: \n",
       "[[  33.   26.    4. ...   20.   20.   20.]\n",
@@ -84,9 +86,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f24bcc05eb8>"
+       "<matplotlib.figure.Figure at 0x7f37879ea630>"
       ]
      },
      "metadata": {},
@@ -97,7 +99,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- kernel matrix of walk kernel up to 3 of size 183 built in 1.1889216899871826 seconds ---\n",
+      " --- kernel matrix of walk kernel up to 3 of size 183 built in 1.1601207256317139 seconds ---\n",
       "\n",
       "gram matrix with parameters {'n': 3.0} is: \n",
       "[[6.500e+01 4.200e+01 4.000e+00 ... 2.000e+01 2.000e+01 2.000e+01]\n",
@@ -111,9 +113,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f24bcc21780>"
+       "<matplotlib.figure.Figure at 0x7f37879faf60>"
       ]
      },
      "metadata": {},
@@ -124,7 +126,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- kernel matrix of walk kernel up to 4 of size 183 built in 3.3105242252349854 seconds ---\n",
+      " --- kernel matrix of walk kernel up to 4 of size 183 built in 3.2611255645751953 seconds ---\n",
       "\n",
       "gram matrix with parameters {'n': 4.0} is: \n",
       "[[1.4500e+02 6.6000e+01 4.0000e+00 ... 2.0000e+01 2.0000e+01 2.0000e+01]\n",
@@ -138,9 +140,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f24bcb5d208>"
+       "<matplotlib.figure.Figure at 0x7f37879faac8>"
       ]
      },
      "metadata": {},
@@ -151,7 +153,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- kernel matrix of walk kernel up to 5 of size 183 built in 8.728955268859863 seconds ---\n",
+      " --- kernel matrix of walk kernel up to 5 of size 183 built in 8.812129020690918 seconds ---\n",
       "\n",
       "gram matrix with parameters {'n': 5.0} is: \n",
       "[[2.7300e+02 9.8000e+01 4.0000e+00 ... 2.0000e+01 2.0000e+01 2.0000e+01]\n",
@@ -165,9 +167,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2502f6eda0>"
+       "<matplotlib.figure.Figure at 0x7f378792e8d0>"
       ]
      },
      "metadata": {},
@@ -178,7 +180,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- kernel matrix of walk kernel up to 6 of size 183 built in 25.120248317718506 seconds ---\n",
+      " --- kernel matrix of walk kernel up to 6 of size 183 built in 25.35515284538269 seconds ---\n",
       "\n",
       "gram matrix with parameters {'n': 6.0} is: \n",
       "[[5.93000e+02 1.46000e+02 4.00000e+00 ... 2.00000e+01 2.00000e+01\n",
@@ -198,9 +200,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f24bcb67e80>"
+       "<matplotlib.figure.Figure at 0x7f3787a4ec50>"
       ]
      },
      "metadata": {},
@@ -211,7 +213,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- kernel matrix of walk kernel up to 7 of size 183 built in 72.31423902511597 seconds ---\n",
+      " --- kernel matrix of walk kernel up to 7 of size 183 built in 74.0282814502716 seconds ---\n",
       "\n",
       "gram matrix with parameters {'n': 7.0} is: \n",
       "[[1.10500e+03 2.10000e+02 4.00000e+00 ... 2.00000e+01 2.00000e+01\n",
@@ -231,608 +233,31 @@
     },
     {
      "data": {
-      "image/png": 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1t6S1g7gNz5t99HneQxYC63t5AGKzA+YHkMKI/eZv3PdAl4dx4zg34us+HVOMsXRwcg9BOutCGNReZgaZ45l5g1xF4cfc+9QeJ+dhdGQGngfWMejcRVJaTv2HuWJmEHOcN16t5Vii5OTsw+8D6jZ3nYxV57EP/Q84OON4ejNOlcUye7mQZ6Bt4zZetyDq8uP0YfYMtB1ovgz9+NS/Mal43QJ9WCB1+2oFd74At126XwBZTHRhjiTLPjk4FwYXMsR8vkXu/2KhPJn7ahaROzLcVFUFIk7ELV1om4x/wuRZxDd9iDTE5By9oTVKYB/oqkpvYuYs+49GjVw4JTypqnhjESzZTJ/faKYPqqrM060ZhtwljSk+AGWURKM5TQOCLgYpmxNVBdIHbjyW8fd9IuvRhdC87XXc5Lx46aMWZ247HY/VLJAWj+jFZ4pjpbqWhcJLu/GtOhmn/k2UBr0PWppLCwsTaNTIm948PJlmkVqImkV5Drxeg0+PQaqxOALqGgQkLYIoRlloEuarCf2w+LD45Ei2n53L/NvrTzJW1CEao9d9PIZ/eAy6mEd6UarDda4CvUKI+tGoSQuF0Sww3/25OfgsDnKQg+wkxKX6/BbkAT3hn6Q/OfjblVXUjf/ixrR6Wb/NzWj1ruk4VR8CgGFaPQB3Cn3eddxb4NA6b1Z2otW77bFlA0haX9SEgBj5iCbGdee05OXYiYMjp9VTn1L82dDqbR3bkLP7sn4H7t1/wt/BGb/YaWLfXTPkMrDVBoZfU4xpc9s22UIrHyc/pPRmACFHe+Sl7ODNtvuGhSGCqtTuNqE0uz9vsDMhHadyjbByRoyiY9Ob2voiQsgv49sMIKnoTO066dczYJx1yelYAN6slA5sOzY7twaUFcORwWwCIL6NdRvn14XFIvpqnJNQMICNokAbkzNM2FudHEfHJ5yYS2IC5lykOj8AksO4acDrNdzpiey7WsfzInPefiB0SqMR3NFRntYefDkbQyeK4fn3j7C3iK0P/RZ2SB9VC9gHZ2E39Qg+CggGoO+z/vfKoM4IbsOHQa4JAJzQnFq+boOdOlss7k4b3CC6jX31IE6LMXM/iLOw+IJBBKo0da3QaVq0jTZg+zcM1rD8EuoQBtJDbRbAm0K2uetyJ6lqLBvOcZ/8QH0vC1vbijM8LBIarWGYe3/b+DzLAjBUN8Qu8gB4n4yxLfLuLhZ3LVsXlAJkdBvt61uzpHTLFhTjeAx9byMywTatoux3l+2lbKi7A4seLllAi7fvIKhMj9uFz4OLxavoM++/T//t4uSTA5wiyp9lPxtVupKLZPih9QGkFoV0ER3YX6MpurDpfC2GEtfC+Xq3pXxhC54NR7myuYi/cb4LgAO790EOcpBbl/uvWexDllvuM7g9hTwHcRb7jKuUAT9J6lZDubl9HlXujcI6d+Oz2GWMMOp+WUjHjpWceTMOtJPhU3YqMjSA/rSajPoBCv8K+mJ/HVtIkEuOxOv5LNxknDvCdRxDIe4tcG8NqbINwVpfGUzyoPos6kaS+konvE1EMz64SOH33vksVK5UDXdQZVXsjbd1gUkq6TAacQtEdycOTp//Zh7gmBsRcyUuMzWCWj3EjZl9x6YpYzEpdgx6cw2RuUZgj7abfBUbhXSYMUhJZ+aeje8jx7BsLpp6HnZsWsRHpC92M+ZFNq7w4Hibw0FStsBwcJbZr6VY/1OslVogdeHFh0FqUtoKYRrdAgd/ScjUVQDXQCSPPWJUkKoqf3H0fcb/ma53wIM4zWVxEglarTLUawbiu0Le/cXiprJtgSjftCWx7WUqhcktiE48vXfjql9vOs5MCjmv1xnkPEYQFP5swWbFwgKiLOU7grIC3bui9nKK+AQis+ebwd41tFiiK0O7JQQbQH7jqUN4yBtvWJoycJUuyLpYhFR4vcl1H+6L4xQRahZIdzxNDkztN0SVJG2bJAKjv41GMdKg49LoigXFKaKS6tqA5hS818E9eAyezWynsj2An2LKOJDg+Br27Dq5F44ElOVfvhx0uNJ4LGNdrZLGMZ3CPXoIPH+R9tM51fvFpXmNWo2hMaB2d0/E+7tYXGWexJssoR/tDXkZYWuewNQPv4WUF6Hgs4i4kbbLUJU2ZySOx5ocdhELarZGJzIUquUqcKEPb8J4fXqDs3cbyE5FUAKIKEptN24fjeJDniFGtZ0h7UvnQz/rf5svAkQEadQ+dB/i7DhyRaVyABiPQRv1O8LD4cUEyGDZdS35OusUrkTTCDLUtktyLDV1us6KxO096HgKKI2iT+NMCM51RJRGnIdzsk1DpceSG4Szs0EItvBZOFDXgVVrGI/Ap0eg12dpx+lEUJqGM0TmoIn3KdkSjntEpQ4OzoMc5CA7yTuP4LxVuQroVar72/azovj7faqf62+X1Q25ykm7T90Qq65fVjdk6PtQX5chFK+aX9uebeeyFPGNZLot6FGt7r6tjRL5OlA3xFZAt+ZA5pQNY7D+jcG6IZrRa30WZUq9YlOuUzcEonF4k0k7VLUsjrdywURJY/j19u/hzD+/5wjOm4renPZBLrcDyd5XGjs1Q7axc+tNEvfr4EYN/Cq/eWk0SjBn3WZSyP1imd0gTm3WYPvGtPehh91VWcq3jQZY2LD6RbjtYl8W9JUVt2k7AF4QgepH6AszJGx3R0fw83kYpzFDgv09OG06H0g2M41GcX+ypommnwMR4ZglqIVkr9IModMT8IXxHej2ppYoQ1XFcet5UFPDh2NoNEpJauNRBEpBzRJLwdcIyzYvV5Ki/iqkqAczZAOVeYkZwssV6OGpTPkPPhsohQi401NJJDPjp+kE+PgDVN//NO04DYlxQ2bIdAJ+dZaS2ZhBz3ZPUf9yaRaXya6ahd1f99s1fHvbmsVQ+6VmcVX7Q9vtGMttwN1oFtvajlGagchN2cVNNQszf7vUOtVQpl0IbX+3qVkM8a5SeDnsqlko56ldYA+axZdF9l3Yyu9vkiVsH9klEetNym2yaF17CJtYkb3bUFata8q9Wyz2KjIEZG+0S4sMbcNfXNJe/G5/vqzI0LY+r/rtKsm0gR0esiGbuBltz9bdGNs1kGqD57od4rzxPWNQH+7/yvtiqITjxrYhLEdxTGiLPfIwcrlra7kurxjaVeULDaObLTJ0VfnCHNqt4fxNCPgu8vaXzIMc5CD3Qu6dZhEBJ9tsb2CrH8Gu9Bn3BUIc26QQ+9Uqt5e1LwQHm+HqtI66yGV5dCR0Z8ZepbqODsgNB6fWjQgxczedSpsx3Tk5XqkZJc82kMBTTR1TsAHhh9TjY10SBRWVDs7wdqwePYxZjBZERaMmbncPTqVOBnPG+cltl71lre3sJqnSuB5DVZU4LdUBGOZSnbduOoFfLMFdC3d8nK5VAIBlDs6HD8Dn55t+ASLwai3Q7lmqEeJOjoFRA//iVZy/6OAsODhRVeL0nC/itQSA/mKG6sf/IPD5Cz1paWO5BD16KJsWS9nfe7DiKQKbFy3X4Nkc/NET2f69T5KTWOfPEdzpCahp4F+fxd/rr38N3Tc+RPVbP0hzMBmLEzamC4S5GI+ArgcvFpHvFQDoM8OfcoXcu8Viq2wL+21Rswa5J3fJMg1eeEsFL1GPcmHqNun8uzxtWh8e9oHO3XJwFunJKWRHcmy3mabNbZcp9uw5Qo/jjV+o2aVjjperTQ5OzxlPAs8XqT1beWAo98DMR4KId/F/iUJl5uxa+EDWCzaU92zGY6/jxUz2GfLF9H0EpGl/vFoJn6f2vV6ncg0DRYbQ9+mlYMZNL15nUZYI/gqFh7IxtW3cJy5I6xbupbwkfEhZzzg4vZM5r9ZpjAD4/AL1Z40QGnO6x4QgOJyr9qvlG9ZtOi/PERS3i9zPxeI2IjhlyvSWVOqdjh/kxjAPgUk714sjD1WxOGT5BdvPcWOs1gdgb3DzO/ty8VSNqUwdtzkYCvfOuRkiDyT7PMN5G+8Ce4CTlz6SIpf5HgAIBU+GJaiNKepprtghzVV4kBTiLacZFpVA+muvFQe0aRY9UHu+R77dycJaEgyDWRbY7EUQCIo1StH3YK0Qpv6zysW2uOuAUFzZEuXY+eO2A/milkjXAXbhBsDeZxXQOBIX94mM2ZIX7/Es3c/F4g1JzDq9RtQghrC2MGYNkr+UNSa2hQi38VzcsmyMUb87F97uqfYFs55r4pIos05vUiskNLC5iUgWjGycLl0zZRsrQ5fRcWryfK47p46QlR/QqIM+qJc9kHFchaO8cilJ75LoBxEJm3mxLZYvvEU5ODgPcpCD7CT3U7O4CvC0SxM221KzQS0HgWWuMnDgjVIA24oM1XWseWFhwVTXkgW5XKXkqa6DG4/B6v8ACmiuLTIU+m/I+BsSCjVzONoiQ9GZWmSdFkWGaDKOdrXltkTTpGSzoykwXwBVcvQRkNPLlfOtmaJAzjM6UGQIRZEhBL9FRH5qRi8LWlKvvDs5Bs/mGxoaARHNqoWn4Z04g8emyHNDWSkA62PaVmSI+x54/FBqhajUNbBcwj0QVCars1znF5AiQwDQ9YApMkSL5UYmLhxJBmtdg0yRITo+hn/6BNQlnxk1jSBGoxao81qBvQetVlLKARBTp3tDWadE9F0A55DAbcfM3ySiJwD+DoAfBvBdAD/DzC9v0s9mxyF9u/ycDy5d9CE1sCAmobqWfUM24daKZEhecyAsFiOzWOg+Crs2DiSqa0lFdiRVtpXwZOYlWxAAQkUyNA2gtS7YEON2iKS4sWV9sEZNTHUGANKK2exjlMTbOh19HxeXuFgcTYFVuIGCY46qSmDEmhH74DQ+SDaDkVarQagyOZJz1YcyVhYbpWtjMzWXS7MwHUW/QIyiTCZhQfHyYKov48nDSHKbmSF1BVzMBPK8SuQydDSVeT8/T9dsGtqu67wYTyPXzumiENLPabVC+9VHGOl5e5aaII7gP3ggXZ0vwKFOSP8gVJ5rKvjaoZq1qF5VWH9V9m2+eJEefDuHp6fgyQhu3abr/vgBZj9yitNXqYI7H09B5/O4GLFG9yZjqfNyPgefHqWxnu++BNyGGfInmPknmPmb4fvPAfgOM/8YgO+E73cve6LaiAo7802IKxicivFsfCeX7N63IXvMz15zSW7v61V0dnl7arMPzN3Gdb9k353FHuqKtrfMCxdjYPU9DPkwrhpbeT7lb0S38qTfhRnyLQA/HT7/EoB/BOCv3GoPQ5GIAbqz7H8hkRgmRCsiPmADreg3QrK8Xps6oyyqaXGcbPOZGcLLVVLxuw68SFEBxS3oTa/qcvTAW49378Hz+WbodLEUlVT3a7sYstTQHtuwGXtwQRbDr882PPLsusj5AAB49iKGPTP+CI1cRFNOhxfmSPsOyViZ2RXLA6zz8gvKBOX7ZALYMHNVpTfxp73kSTiXTDyfykvycpWdmz+/AK3SteT1WjSPgfKFICcmgs6DXp++x+g3P4M/O0+7VlJuUK+FEu/AM9xL0Y4q1UyZwasVxmEMfrGMEZ0Uwmb45y9iIlu8hp8/w2nXpyQ2ALiYSe1c0rIISn4jmqRftyDVXk0FvF3kposFA/gHJLGw/4WZfwHAU2ZWlMinAJ7esI/ryRVmSPJZhO/Bpo7b445lYhNldSl4HUrzrdOFBcRU4bbLwqNUuWR6LDhPO1azRVX1uo71Logp96U4AlEdF5AYbShBWcEHw22X9SWnJeQ3CZQV1P7JONHo26zTxvgcjo+kMDJRssE9hwfdb4R9KbBMxa3B1HNE8JFzNAdlqfnmxmN4z+AAdtJ9oFT6pkwhnRynB91wiRIQ6eSyYsejkYxfM2ir0ZWgrHisgrLaDv7xg1j/VX4T6jsKPgubBcrTcP2bYPauW5Bz8E9kX3p9JguhRpwQtKGjqYCyDAUfHR+j/cpDNPNF8i9NxsB8GcxX3gBloQBlYfHmmLJ+ipk/IaKPAfxDIvo39kdmZqLhIhdE9G0A3waACY6GdjnIQQ7yDsmNFgtm/iT8/5yIfgXAHwPwGRF9lZl/QERfBfD5lmN/AcAvAJKifpNxhAY3zIXsf7l7AZryQ+oYOYDLAi5BrY3H82BaMa/Xm3H7rhNnZujXmhG8kLdDVMe7LlOFuVD3vQUuKbJy7ZMDU88xqOCRpzZVa89yAAAgAElEQVREdpgpjD033/xsUWhSLhUWVm7P8PYTAJeq9QJ+slEL9HK8ENK2yVxarmJxn4hGVLq/WDVd9vXzlPgXYejFGz8WO+5fiZlXVYZzlBNnhvFXMFhg0Qbg5dsVyAWEJoAclEUB3apEuArJ7kGffpHxaHDg4IgmoTVnziwnh957a1AX5mG9lvsAyIBn/Po8MZHr3Lx8hcZ7+FlCj/J8IRXcg0YRz6CqZHvvQWZ/dLsnBV57sSCiYwCOmc/D5z8F4L8B8KsAfhbAz4f/f/e6fWzvPPBSAiE02A3Um7zcDNFcicglOZ1m0YH+dZtK0cUbhCDVt0dRDfXzeUYGo325k2Pwus1g5W48Fu87kdjLStK7WMB98ATwHv0Xz2TfoyO5mcdj8LqFmyTyGhqP4WwY0IQZbTTEn52JWr1aJXIdHadGQzRKEkh3qg8ep+pYhmeTxol3E48fAq/OQb5PKi0zeLmEv5htmHKEKsyHCc8GB24kujXRELbRkONj8GwGv1zBPThJ+4TwKjVNnHP/8WO452cpAgJIdESjKU0D/zLkgTgH9/gR+OQI9H2xml01yaIhGIiGsPJdhmiIf/4Cq3//hzH57S/irjxq4M5n8E8l34MuFtG34h/KdejGFUAEt+pQvZpj9Q0JnY7/xb+T8KZLzlGqKsl7mYxQffYsXnf6xtfw+o98gAf//Iv0wpiM4S7m4LoCeQZrVGQ6Aq07uDIa8r28xuplchPN4imAXwkrdQ3gbzLz3yOifwrgl4noLwL4HoCfuUEf20Un54ZIxgwH4Qt7+6YoSW1PtYXwxuBwA8cxhFyHHJYtb2oqIMpZYtsdCNv+ou2seRhGk/HhjWzfmvomtE7UvPG03SGPDe4i2p7OKzPYohQ9kuPTRnBVQzN+AGmjgD5fU8jn1xN6fdWP4Blcmd90mwvHep9W1kihkMbKfT88VcwgDykXaTVp5jSmKzTsvc7zXWfKGqyiPsSDCcS35Fa2oazhgkyk4IKk4NSzLEQAsHOl7bL9ONZNCK+FGzsDqlKHXFlRe68CzftKybZlfzLjVI2rrMlKTW0wJka1Hkgw2/scthWzNv0DwXlt6nRw10YWLaXnH0pGu+6cUjPaYLAartGb8oRKrs9sXIBce1NwaJAzwwXGcZsvYrXgcrEeuHf3qaJ+gHsf5CAH2UneXbj3ZRyUpSagxXh0Jd2G6rRNFPyIVI+hxWWA4FAkylZoW8vjKri3m043MkljXQoi+NUq05rc0ZGooBo6nYzFGRXChNbHIjUkDKO0IR22cG9v4d7qH1GcQJjDEu5dnZ6mN6zBMsi5h3M7mgKKB1AtgoPDs3yjBk3FTRNcXOeA+36jWFFkQjN+GA5wb3376tt0I3R6fCwOPhs6VbPNYB3kMjHo+BiursRhq+dp4N5ZmHUL3NvP53A/+vuAZ6bQT9MIn8VJIuyNxZOOAuK1qaMJwrMF+KsfyLGffJ7KDzaJlkDh3t7AvauPPoD/2kdwv5f8JcqlEX14sbBQA25b8cOoFuMZ9HL3JeDdXSwuk21p5Kp67mAplGpi5FiwbbmkMqYdGeAebCIRgyXnLIhJU9S7TiIi+l1NC0cpGhJzDnwE9+h3O/bBCEzX5rBzFnxCjNjo+KWReIyVjJdBx957MNoEOX/dJsxCEQ0homQOqs/DUTpXQIoIIQDP9HhjsthxWtq4K6MhwaGsxYN03jQPh5mjoxddJw9V5VJERsF2toSCTiUQOSEAZKA8fPZFVglNsSIRe+EllZ+ZQZG9vYYPcHxer5NPQu9LR9li3Z9dJMJedei+eg3X9+KQ1jnQiJSCskyqejQHzTXmNxENuXO5ji9lD04Ka3/HAr/2OOO8s7wO8sHY9VohrNRkbJUyywhduaycHgDZbzwGcaqvKjdcutlUZKxb7GJTHhEID95QmcLimHge2m/poAxRIR2HFOMVlGAEixEJkQzMA683dniAo38slvIbbSA4dd4s+5ciOKMWoahNH9C12t50Ig+0cynnhwiYSElGsmPjwPJlmbYUbLcNwdnU6XgLyjs5ESej7lpLUiIdhUiRgusAyYcBQHUl1zs4velEFjF+LihTCpoTAFDfw03G0qdBcLrpRIBfL17GUgOoKgF6UeivSGLkLgH0AIAu3hwo6+3LBgHMjocVN0J0DKlaYglrYlfWs3wF+c1AQlVgVIltaflBILw1DUoxsRkNwNn7bTVFfa7R6DgVGxK35cdk4y7wIeRIhq2qMSAQccVC2AhHUHuHvGU5QUvQFIxGFssVFuPkdeoj1TNJpDnINK5ZetCNgzlm77JPdTugmkpijopm44BmAeica6Qo3Qv+5atMc0LV5ixgKp5BVYCJK99EeHG4V2dpDPF3g7NYrjY1i8US7tmL7Jor0Q+ryZVVk1cmM0skvHs06J1fLAa9ykC6SbObIvcbXCqWBIVNbctoMrTxt41jdtAsht78WngXgMTybaEig6MAMFxEKH6u7k6zqGsTIjXe+6DGA4IXEfAQpcXNgNU2clZClMSq2ELQsp9mEe3voOVEH5NqPNNpSAc3xDO6f98DzjDDe9EsYvsAqMK1NAv36CG8yc+QaIwTTQfI/SWaOWvNzdUKdBw0C03Ht9E0z8OaxXgM+uAx8Pxl1rel1YvtNDXQdjfSLA7RkIMc5CA7yTuPs9i5kA6w6QHfVYYYwrHFL7Bvuzvv6/I3eUn1ti2r9rblsjFbbawsq2i2Ry3NcmYOtbUrZuWysW3BsGT4CzWhTPTHZgTHOd53PDoEJeOxY7rKb6bjCfiPcs6sabx1bJrUiNxcHjajMHjP7IOzeOfNkEG5qhTALmIXFnKSKWhCTRI6dQBxdgFjmLaoPVpezFjQyIKRKKVOc+8zByeNx7BRC3U0UoWgDiczguoGEemXdbrFDOEdzBCfVNsN0liXbkoZW5PYyEMGqdYn1SiO9BX2t+o9kJy8mn6OHR2cI3UO1snBaVPUp5OQdzKcog4yuTZMcNORhEPPLuJ57m+GrFF95WkKv4bx8Wq14eCE58hSJfdbcGKuVqCHQn7jn71IjG1dgHsTAW68kaJePXwAfPgEeP4q3aNVlZzPek463kEzZPdap+/+YrHPG3SoAPLQwgLz5u4hE+3qPOTq8/Bo2Cired0kCPfaDxdGNoSr6canhHeYzyXNHID3DBduPpu7EQsb96Y+RoBj02gUU8kTVsSgJ0O7Ss8X+1UchyIHtZ7ISrQxGo1M6nt4kIliiA+A3PD6UFK6GTkke5XhWABwdQ2Ofh1x7rnpBB5aNyT4I3QhMh5/jyW4NfuYdPnMN3F0lNLr7UI3mkSKwd6EON045KgoTmU8TohItf3j9ayiv0HHqXPMp0egpckjISesVOqHoKUsDkDEOHAl+Su0WElE7ighODXErsIA3OPHoLqC9z6xlE2n6J6coHr5Gvoyibk6Sqeni+Z4JOd6MXtrKepvR0ocfrltlyZKr7vG1/1A2/Z7ABNlkQzF5hce+IzSPvSh3zJCG/YpKczsG52GNpqhY29zb3tJkKPtch9+KwBcukiWMHq/Wm2EjFNuSOjvYpZwKfbtq9GCgWsR5wNI41xisy9L3Y+wuJUh2ZjxmptBfH6+MY/yVm6FCMjlHKF+tUpZrkDIjE0aSzY36ryNi5FPC9WL17H4kM4jdx3cmdYNWccs0EgiFMLOvG7lpfAikf8MmW2sBaPMmPzFDPUP6gzjIbVNUp2S2O9yCTQjiWTZWiF71A05ODgPcpCD7CT3U7PYRfZ1AG6j59uyr7JT5ccm7SJqFdk4DBzatmHf2mWb24Zg91dqQM857sCbQkYbzq7cRIoyGPp0qfgPEFnLAYNLiec8PO9Wy4rn3SdOj1hjpI8HxO96bDzOlG3MCjUZLSRuk8aTNmjH1xcFjZgi1oIMzkHa4WgCxnHq98Uyx9UEfwcb6r2IpFRcQzDhIj1h0A62ZVFHCLz9vW2FXtH2rVpXyfUa8C8byXJ7PCcHzeKeSgZBLyIo2T7biHHNMZfud8cS+zdjilT+9rzexPg2SH/JUOpvcaC/oXmzuAuqjAN3H6mqG5FUv7+axWWJaIC5yCkJyzoSbRHl8jhSrzkQixeXb7QE9rEw4JToxVlh5IQsTIQzITlNiX4KEFisrwF9w1JWlwRAqk1ikKElB2cqiRD6HY+TT0HPSdsN293JMfxFynGI0nUbzFub84FU/8MUlE7gIUk4Y/T5Pr7LjlMfQhalOT0BDGOVDFYeLF4GDk6bSh4cmv7Cx3FpGNQ6isGc4NKBbDhLCPzgMVwg1QmTK8WuT1MimcKxI4I0EPTQciXX6ZFEQ7aWU5hOhZBnNksgtJNj4OmHcPbeG4+FPMcuvICQBDWNaE2GSzSWfdhB7udisS10aheHGOYczkC1FcyB4N3uEiKR23VyWJZoUX14II5Im+Ogaqobj2WZsDenqetBobAQAPi+TwxXmmgUapFouM4S62acEUA0PbK6JIBQzDUN0PtIrEtxMZKHP56HzsPRkdxsMCprVaV6HgDowSlIw3MGPk2rFbw1Y4zE+QifAUhkQGH2uuhofZI23ORH0xiW1ePoaApuW2EWN6FifPBoA2oeCySRA0ZNPLd4rpNxZMSiURNrklDT5A1VTqIbarKMx9L2aoX2a4/RaEIWs7B0zRbwHz6W872YC0EvgP5E64Y4cFOhuljBvZ6h/ZrsWz9/iaHllh6cgEeNOGT1HB4/xOxHH+LktakbcnqU1Q3RF4cP0RYX9oljffW+Z52+ZXnj9UZ2lUvqkmRiVee3WZcEyCJIO439TUk5L9sIgd7GvXDdPvUUrnn8wWdxkIMcZCd59+He15VtoCwgx0TEtOkqj9tvg/4q2CWCuvrM9o7dBxhvmYgWzYm222gDQFIxFRVaIlTDZ0VxAsZnQbnjizVZTRGBgEkuS+PUMUSw10ZqPmV+GSWkAZCleG/PhhUzI2tPt0VwFaXxKNYCiMV2LIVfPK7AWbjjaY45gOIsEiVABrQajaT+aax1Wqf08pCGDyBhKijxclDlIu7BPXoIPr+wnSZCI53zmJbfxH00nZzXa/E/APDPXwziLNzJicyFaQtVJUlszw3xjoLaIoIzJQLSZAI/m6cxeMb/8fpX8Lr74j2Ge+8qCsserIVaODirSlwcEWs/vFhksGQgpB1X2Hg8qio6DeOxha/DFg6K21cGYRkfhgEHZ+USnNr5uA3W1g5kOgzkPpawsIhDN+V7sHdZMaAYFlXnnm6fjDPm79hdOJdBNdfOh5530wC8jueruQ7MHLkxqK6lqI6tdNY0INfnyFZA/Ailc1Ch3wq0sotFIMlRoJR+Z+ekLcuqVYXoTJ8crwo1l/qwBgymURzrSNzi4IwPs0LDX1V5eFSbHDXyArHnPGrAD45jrdY4B2YM1sHJJ0egto31aeE9cL67SfJ+LxYl70T2Ww7lVoiyQrS3NhmRhsmhqWjLDMGpiFDzlo1p7/a4MIaSkDVxPfjN8wjIy9yRGNCTfbEfsIGd4B7QnJcs7s5eUqTL5LVABKTb/cUsjb1EkW7DWeh86Gdtt8B7sOsiyxOAiHtgz2nOreZj38KvzwZJd1kXRtfl12O1yss1BJh5rEgWFhFW5K7Bw2Q5MM9f5hpNwFl4cw4RZ6H7FTgLjWjYecrOYTaP+TTxHNZrELPUeglCy9UgzoKqCtR78Gyec2/sgeC8n4vFLtGQuG+hWah6WyRWRfVbtysvgjkmq+Og1anXIWJR5EO4UbPxQNvygn4+TzyOa0SVtT87i+MZyg3hrgt8kKMNCDfVdSoniMDBGdT/GLJVdZ4cYPgolD3cHR0lKHfkeXB5mPPhA6mf4VyuWXSdqPQDN7vOh44TCBrKsuDgHEl9kqhZjBrZR00k3dZ72cdoFu7Rw1TXI24koK5TbogJrbqjI2DURC4KiYZItXE0oxRZCZoFNSOBXYdxwpE8xF9/CvdFMgVATpLDHj+Uw+fbc0PcYgWeLYAPpW6I+94nGyYtANDpaUh6O4+hU/f4EbpvfITqtz5J+02nEt4dyA3hUSOsXJqHAgDLN1tF/SAHOciXQN5fB+dVsg1DoXIpoOvqFPXoMM2wH5RrNKaNjfoopcZUOmeH+Aou4XHIuCiKY+J5IHdE2tT8jOXcAqzKuh2XOYbL2iwDtS2UCzUHj3F2Dln9EtN/ZAYvJZohBWN3XctvnTotqzRfA0C7bBu56DCtTk8HzZDotLbMV6oJlWZI0Dj7i9mgZkajUdo/zI0bNaDjo5RiD0QW8SEzxGYyq/z64n/D6/7ZwcF5J3IpOcwVqNE3JZH+L5C79OYB680+7M2D9xbGaWQQqi4fsBNd++0ORh7Mkuyn3M3u8walnKudjyPadMTvIe//YrHrA7zxBr7kBjVvcOZQW4Q3b3ZJfMpDp1kUxbQRt0fNYksUR5sK0RtpwMcxZT4E1SyIzc1uNBqTfxGlqmIURBO3IpQcSfuwUPA4JvTgMllrYz7SzW4h5FFrqJy0oT6LAFe3C56GTjUKFPuYjMGLQlOxfJwloU1VcJkqwY36QuJ5VJHJPNWQ0WvZSv3aItWfYSIfl4ROad3K71oTZT4fDt7VdRirTyt7I4hgysoQNOKoHQidoq6FZ8PUesHyEA1Jsuubftes0xCZsBmjMQpAhUp+11mnBZEve7fBaRH3s4uZpV0rFrk3mnWaOYD7qAVZM8RmppZ8GHeSdRqiETEMrO2Qw2DWKfBms07tNd8z6xS9z2u9AFuv15C8v4vFLlESAPsnklGqLwFIElhTbyRQ3XUimY0ubEskgxbXsTkgBsBloyEaknvTiWSIzF1hzCGRLMMzhOI/d55INhqlRDIbqRlIJFOchb+YvZFEMnd0FBPJYgRv30Sy8Qh8dpHjP9a7m1GHaMhBDnKQneTeRUO2erw3drRqd1CZx2NoVe1rOyKtVz/25VI0IVSc2qqZ3JaUjtahaIf1rWxjsA7tuPFYsBbXZLi+ltiokt08VBn9LivHq5gq7bbOSWQBt4CoMHY3nQhv6q7307ao21Us9uG+o9Eo+hz8+fleTnU3mUQ8DSBz+uvt339/2b23Fh3a2HFzAreh4/YbwBDHpLGbB8hq70RKRvOh81I/xmXnHM7Fr9ubz811ZAitOMBCdkWd69sfS4l69cWipr6r9Zu63gb9usWvcWUTRT7NNv/INrl3iwWYc1yDfrZv/BKfwJtvVRfw8RG5qNwKIbfCX1ykZDDbF4t/IauifXSUWLlDX9Wjh2CF3gahyTjmAPDrs4i29LMFqg8eg5nRfy4VsavTU0F5KpJT+1utpBLVaJTIaU2CV+TFAODPziItvSJELXt4LEEAwAcejerpxzHPISE4q8QzAQj9fKgaHvMMAPBymUGP7cPnTo6zCvHKL6EJWNH3MR4Dq1Xy3Rwfg2cz+OUKldr1k7FUBO+92PHa3dMP4J69zBfR4BvgixmoadAb30L1+BEwncB/JnNOo0b67zpp10Lwqwp0cpwQojpvz1/A//GfwOh7z8MgxL+B+QL+6RMZwvlC+CyY4R/I9fdNBa4dqvka1csZVr9P9h39899J0H9TWtA9/Qg8HgGfP4uYjuoP/H6c//iHePD//iDed3xyBLqYJwKkgBzl6QjUedD5POOzoN8xaM4r5P4tFsBGFGBj2y5NlCX6+lDzAju8Kfo+i1cP5iOs2zzMBQgZTWAmYuYMrs2rdb7qG/bsDW5NZrmhS2bsrsvIXXSc7DlzhgJI0Y1y7CFfQvuO1biN483NFvA6djJ1M20FcjsXnoVdWxdtXYRKtmwgFi/W6xP75aKOa8hwJcPI7s5nMo9FrVOsQzV6+yb1DF5J9fKUG4JYkJhCjY0olQdMXgWZCE39fCGQ7SBUV+DlEu4sLMwBag4ATqHaVSVOz3ULzBdoXsi+3HWwFdHjHM7moHUrLzd9OcwWmH62TPkmOn/zZSw3SRo6bTug68HLJaiICO0qBwfnQQ5ykJ3kfmoWu8hV9URKjELQAkpw1YbGEnAVEV+gGImiH8U3WEgyMyfATJExad8oANLnofKFnsHeYBT0t77fqFZOIRu1pP2LvowSl2DrkXgGg+Vt1RpNZr2G1tfYqK2xTSwzdd9LBmVnMlH10K7LNLK4j834jEzXPkckzpcSJlayXTNfURu0jN2dKVgMRN5PeA92eflA8h5aMyafMC+0ecahzb6SUK9iJ1Tb0XaAZD55D25buAvZ15usV1soCUFTZeNL4eUS9auFaIcWi9KuwV3QUHUetGLcymhnpj7LLvL+Lhb7yGUM2CSOrNvra8DxHGPiw1RuObv13Xv6IoAInD90dnwBGRn3Zc6RkjpUchlwaqOd6w8y0AhaikBK/w1SVlCroXK7LR8JiB/qpnR+G5Ep2hxXGbXQPsuXk47Tubj/Vuo+ovSn3W05l5tCvYH3ebHYFZRFCb6bkd8Aw34QosQcBaS09t5oGkAqeGseFLKJZM6S3wT2bdtfQNwJGrAYgws3VImINGAxOUWKtTtT/VGbxGXg511yZkaWKjMWWzKQGlPrVFPLAUEnblt4LXzaLDQ2DT725X3SNDS5i9KcK9w8ktLo+Y5Gqa6ohkHJC9nuGjmrl5Z7rM18ESVQVmDsysZfEOWEiZTSg+fpO9WVzKeSJOs5AylFvQ5kP20H6rpIqGvnP5OmBjUNaLHIgFbd6Rj18zpds1AjN86VLlqjJiTpcQKGBW1pV7mfi4XNm8hYvHfXANLDY1CK4X/Wz9Cb3DJehUjFBq3eqAnQW7OxaVIOgGXs7jrQeBQueIgOVBUYreGzUMcnIuNWeqhTzkYWndAoiskHiDkMIdejZOjCdJLYvS3icjyWPAYEj3tQZzM0IApnr83bCNEAmZtwTF1n4wEkusIAyPXxe3Rm6jmEaAiV0ZAHx6C2zd/sQZtgzHMq/9AOppNUQ7WuU55HXedM4U2d11I1uRzth0cYXaQoFDe1kNI8FKo851yMSmTRkIpQLVpUANoP5fjRDxK+I0OnHh2BJyPQfJGIgU6PMf/qFA8+Hcex8vFUXhJD0ZA2OKxP01jx8n0qjLxNNsAtfvtvA5KFNBXLz5xsSkDePkxmXQqfd42GsLE5IcfZcFx8U4ccAfQ+829EOjhyqS2NlqzXg9EQLIu6l+H3yPq0SzTEsmA5SXkmg8Og2SIxcOk8+j76JSKkXdv2IW1a57bvZU5MXzrvDEjOg7a7XKZoiLa3NglhBvdCF3MJqYakqzgHS6nvyUjaHPW9LKam2DGvU3SEqm4j+hLnHUnrYs+oXy3Bc2XAIomorNYpGrJcyXj6PkVDRk3yGaxbNK/C8Z4TRF0xHFUlhbTbFt5cd5otMP18BXR9PgfLlWgUzGkhbDupj2ujId7LsTvKIRpykIMcZCe5l5pFfMPrZ4881ViBW5cVGVL6OQUKnRzL21PtOQUvWVMkODwpgKIAoG+FxbmP0QbZ1z04Bc8XObPz0RT04FT2e/ZCitYA8K/PgMcPJdISQD/uaAp+3Ya062UiR9G34XickqZMgldsH4D//BloMpZkp4cB0KQUciExzAVW6d4ArlzADMS3qJK9hu3dNz5C/clzMbNOj+Oc03wpKryxuYkI7AIoaxYo6UKCFcYjuBcv5XOAydPJEfhiDgrRBXr8CPzyFfyFhwvnFs2gtgOMZrD80Q8x/t1XErWwLOdNBffqQkBNP/g8bscHj9E/PIILc06TCXA0jcWLyFZGbxr4xydwn4fxBnAdrVZ48R88wpO0J/pxjerlCPMfla3j50v4sZhhqw/kOnZTB18DozOP6WcLvPhxmZOPnr0GZnPRUNTCIwf++sfojsdofgfwAcjW/vDH+L2fOsIPzR/FvtvHE4yezeBHAQQ2kke8O21QrXo0z+ZYB5MHHvDnRTGlS+ReLhYWppqlL9tM0ivAWimjMKi/+uAZdV8ASZa/M4RXDcIQ7ENuQN6PP78I4VCTtj1fpPTqrkt9eg+8OhfGLFWfF8vAbCRgoqgSU1BPl6sNoJW/mEW/AoA4Tm67uAhZE4M9x+zRKM9eJMCVEtWuW9BqHU2v+pPn4uNQJ6e2p+nW6pMwYUZ/MUvfA1oU5xcRjUhV8JMsl5kZQr0PSNg+0e2vVim8uh7FuZ/8FkekZlxEeg+s1mDfA/NlHr158QqVAp0g9wTNF9HBmZkhVQWaz+F1wQsLCbcdnvyL16BPn8dd68kYfDHDkar46xYVielUfx5YvMejBES7WOBJIIrmxSLMU5UhaOmTz9E0wheq17357uf4qnuK6sVZBO1VLyt5uQQzpAo+naapJfy6XGL0KrF7u+XucPV7uVhk+RlktsXfi7yJS5tKnn9LQa/Yi6GFabeGDQYiRivMz5bjoPcgL/a+akccHj6NekT8B/tUx2JAbJgtG+11wpXaj/U16PbgkyGjzYlfwixsAaehY46aX7+9QG8Z4rPfo0NXeSWGfC7M4K7PIxlm7Jaxm5jFZjccE4P/9XMZEjV9ZtIZTAmQokbahh7jnGhH3ic/gmJlTJo+c/ADlf1rpM/mp9SFw7KgdYx/QIg0bZ7ONrmfi4VyPCCZIXnI7uqoiK2XAXLCOmRyJbBYZCxNckwlpQJ2jYas5YHVB8NGK6jtkinELIVv+x4U6jjQaISYZ8Cc1xsJRXkjr4FlsDK1R7FapWiIMmq7MM4t0RCaTKAQ7rhYVZVEa8Lbi0+P5Qbvexl3OAcQCaTdhpUBYRObjIHgw6PxKF6vMhqC8VjON0RDMB5Lfc++j85Imk4jeEujTgDgHxzBdb3kgoSHhryAx7CUawyjWdFkAn5wDKgZQpRHQyyvZlNLv/pgmmjI6qMjTF8HbYlIohbeo38kpoW7qOQh7j38w8DiPpF5d22Pigirj2X75AfjGJWzBY1oOpV2Z/P0QjmeYv61CZovThJEfDqCI5Lz1/snbKdVKy9FGw15tns05ODgPMhBDrKT3E/NwkhmGpRZp7s3kj5bCHapXl4zhaamcpgAACAASURBVNuCnCKUF0iqqh9Ie1dzQ2G/PKDWvgFh5qSpeuNAVoi7UZ/BnNR7mPnzBaw4pHdvBXBdPShpewCuLmPzuXYdTCSqfO4EB3Iz5JpzSva24JT0F02LAVg1eQY7AvUctLRyrtK4GNutBQpQ9pTYhnhdpI8r0h72kPu5WFzls9ilCVWp1WfRBlyEXWS0ElYpu+AsNMei7xM2ImSFRoyCsZ95ucz6494nnwDbm9xHTMhdZJ3ycrmJsyh8FhRyMLg3CEDNovWcnh7LB2GzZNdt8tcUOAs1ZYazTm0lreDjMQ+iO5vLPLoqQ3Zy7yVfwt433gvmwJhzzAxaLIezTpkBWqTUecOZOXo+zzM/ux68XGVZp2pOutC/a+pwrh1ovkTzIhzfrkNekctfXIuFID3NPNJsgemnK9BiFRcW571QNl6Gs7AXfI+s03d+sdiopxF/MA4/QCZGWaosE9aWFTV7+Milegx6IeomQMDNwx7e8HERCO3HxCrbvi0DiNRXltClC1bfJ07LgOpEX9Sa0P5IAE5syWr0Tb728PYG03Eyx+K/qh0oC3fJmelni82FN8yPPpTqQ4Bn8VEA6aE16MG4jnc+VhWLcxbOMTl0kw/Dkuj6uY8MVRrBsg5UrNKtT+t19LOwdQTaQstGe+Clli8M12HdRp+OLrJpCihGZeS7jqEHff+zGBYGAK6kYHL0x9iENIWFu6Rd+q5DFfbxWgpTiXd1vl6fgyqXkRT5Fy/RtK3cOxZK3/dy/tYRXlVxESYbAdsDlPXuLhZX0YVZFZZDopDNf9iVWslQz2U5HxAnI1lOCnISgtvRzMlrXxRSpQK41NQJ1j1K8GkajxOqMFLQI5DwDlMD5mYZby6q9rftA0+fbREfDUcyp3KG+ubioFE4l4r82jAuMzQcpIlS8cEAoE7pmA2rC6A1wTYK57g850RNvCYRI6Pv4WcLWYS9BwXHZHR0VhVQaZ3bNvVfpA/Y+rBxnCqq4YRzo7BYbGT02kVj1Ehm6miUaXcWCg+exTH6WQjPF9oRPIdz440+Mglo2+x3TovoLnJwcB7kIAfZSd5dzeIqGeKZuKYTJ1M31WQIb4fsbVCmWu/a5tBxff6ZgU2OC28ceOVb7q6knFftS02RuL3PxqtmCAFRo+Cuk1BiUalbsBfXuFbGFBtqh0JfhDb5Wdi8cb3BJFgw2R6VxIfEmmjskPglgu8mc/TqtqBVCStY4iGJPhFjolGJGdF+mcVss74cNbkipiW0sY/Df4vc38VC5YrKXfs1RbkKHtLR9yU2vUbHA9tyToO3JlvK9gHhYb302C036HX5I8qxhFT97CWhPhO11YsHLY1d93c35rMQH8n2NmKfDjngKziQybCcx/PZxiNSSsmVEdqNdIi3sEioXLlYENEvAvhPAHzOzH84bHsC4O8A+GEA3wXwM8z8kmRk/z2APwtgDuC/YOb/51oj4ytssMLWBbDBBnV5+wNOPMM/wS1niEo55BpWW8EMPVTUl/seBC1alGDdttyeZcWiO46abtWKvLIvxR0TsjQ4JbmzGlBy4GaFlZmGF8irB6aDgiJj2SF/q3sGozfhXh/3BZBIjoMzlqzz+JpiIzIyPvVzGb5V7VMjRUQxNC7Rl+BYXa9lfzOurS8r1eyCQ9Ruj3MRM/XfjGbx1wH8jwD+htn2cwC+w8w/T0Q/F77/FQB/BsCPhb+fBPDXwv+7k8hnkchgomPP/i8Pq0MadbggbtSICqscE4sFAFNVOx5YViRbJ2ef9g3ATcZB1TQOwrpOjN6LZSJQWbcpoUsTyaZCMKN1UlL1MnEqOlM/xVY3dwbB6edzMafaTlKigZgHoQ9vbDc8RO7kOA+dAhvkN7EimfcJhRrCs7xcbZiD5CirdKZOPEdkckNc/M0S9rrpBH6xBHdtRNfSZCxhQC7Ibx4+AJ9dbBD2EjmhBqiqyGehyW00mcA/fxH7Vp6QSBugoijWkBOi166/mAE/8nW4H6TcECHsTVXGYugUAE/DfJnQqbuYRyZw+u3vyzxZsh8iuIenoKaBf30W77Xq4w/R/nsfofntT9M4x6NI2Kvjjv11vYRgFXULgD7b3bi4ck9m/sdE9MPF5m8B+Onw+ZcA/CPIYvEtAH+D5W75dSJ6RERfZeYf7DyifaUoqiPbUn7/zqFT5eAs7OLNAznZv/o98+qHzYoNyDQIH7NcM6yGMldz2jfzBZjvAIL3faAmadtlQHcpY1BwQRQcnGWpvOxhN+do3148m6ewp0FEp1qcueoT8RzaXgi3eub8Ouj59unc/GqVQqd6DgszFm+iIRezmOWb5cjo21fxKTqHmqSnPgsTEuayiLIywCs2xozbvTiHtzwiykVxdh7O13B9Ggi3ni+vVnAvZV/f9yYnx2hM8wW4Wkcfh1yHGZpPR4ItUWlb6VvPX++noKmwYQcXzWR3f811oyFPzQLwKYCn4fPXAfyu2e/7YdtBDnKQey43dnAyMxPR3l44Ivo2gG8DwARHV+xdHpwSyQYdnBZVuM0MUbUwJok5SXiyCVsF/yU5kn0uK4ys8fZQuNhODTV1yB50wGIRCxrxciWqtc3YbBqpYeLEl2LZtuSt5Ew1cRfbz8yQvo9miC2MHM/FO2OGBK95UPG1L82UjMWIAeGjmM0ke1Rp9Ti8qY1TTQl/icPxQaOI9HgAfMSP5GaIvvHceAzvGRxK9+ncxmiMwRhEngyD4OQAe0YbMCELBS950HgEmk6F1xIAXH2lGRKvpZohbQf/wQOh84vXuQFm88ghYhGcHLg22SI4ZzX6J7KvO7tI2pGtuH40FTOk7wHlGTk5wfprjzBarZPPYjySOiXqHFczZBSS6AozBIvd9YXrahafEdFXASD8V0aRTwB8w+z3Q2HbhjDzLzDzN5n5mw3GQ7u8MbGchYO/3bWojW0BUIVDipT1mdzWsd6KZICsMmV7YIzkoIS6ccwajbgMlHaTeTXRg41x6TyGVOw4JiX9jWzY9pxuOKdDzsOrohlkxqvs3C7tHxm+bVr7tr5pyzmUKek3lOtqFr8K4GcB/Hz4/3fN9r9MRH8b4th8fWN/xZDPIas3ar3ARg0YYsrKQkxhAjsf/KPFhPp+Q1tQ6DfVddIsAgov2f4hp0FRfCU3qELSmeEin0UYJ6U4O/c9/GolbXct4EZpXH0v5RbVVNU8itEopk4DECbqphH8gzJNq5MxMGXp2zpqNKMmclTEmD9RXs5vPAKUiCZ2Fm7Uvk/kOUYcEbxqXYBoA9NJ7IuqQMk/HssCbYhxNT8mah91DeYWJY0+H0/lLQ5EnAURgY4m4visqkRMjKSJRCf30ZFoD10n2sHS5NnUNehokpy0SjWwWqE7GWFkHL2oK6Ct4U/lDe6YRZMA4E9Vs6jga4f6Yg1at+inomW64Bcp73p3cgweNSAzJj6aYPVBg9F304LAR5NAZBzuT9WwjmR87rUDn6TyhfukqO8SOv1bEGfmh0T0fQB/FbJI/DIR/UUA3wPwM2H3X4OETX8TEjr9CzuPZB+xC8g2R+ZVTFmWDQpIuRwZHLZskwFoUlRqX5yTRY7FYgmODr8gq1Xqr+2iCs59D57ljFUc9o3gHfMAiiNzmYXWyFEi8TWkOmAZW8yrMEln7Dk9ECHqw+cXmwWJAl19LF/44mWKYnT5uLJK40PzAWN6qMMNAKow76GYEWdOyxbsOfUZGLpKHAF99ixGK+KYIIuLX61AK0O9CAjz1iIlzvFikWDaIwN20izf1SqGXqntohNy9N0vwMGZaU2YmAkaIjEAUJ2FRb+SUgDctuDFEqMwht4SJtvzePU6LXZqcnzxAif/GvCBKhEAaLGAX63zvCIA9FpMYJ7NgLl1iG72tU12iYb8+S0//cmBfRnAX9q594Mc5CD3Ru4ngtOaE1fgKbYdmyj30wpM6POiO9ZRqscGG90mrUmNj6IbZdmyQC7jGCVXJL6VXApa5VydqhHMpcdWxllpVG5bR8N1ab/YfmuQqqYeScy2rVNY0jh/tfgPAKAZRc7MLPHO+5A9uqnN6XzEzwimh2oUOi9NDXYumSdNHUOylnGM+172sf2PxznFnEoj9UmorjNfB9W1/GbCi7KPmItRM1A8h6lzQk1oq2rFaRmcpCQXAgRE04/Zp+ui5kqoJUIryWxWx+dG6UWVuk7FnXQexiP0pxO454l0lwLTGErNQnlJV6uEjQH28h3dz8ViH7lFOPg7LVsyRS9zbr0R5+1lUvavqe0FD+cbFUfiC7FO0563O2nv0tlsZcjxvKdIFbTrj/f9XSyuWiQKnkiq62jfAsgcYXmzQSMIYU+s21RiD0hvz5FUGCMTe7UcnIr8BMTuj5XEzs/TeDQFvC80nqrKuCfjaZqKZ4DY9lRVomFoXwYUxD3y8wDEwagN2OploVIYAKHrD8QxGecnUeCjGMgnGY2iHyKmYY9TmFZDuDSZSPFe1eZ0H+OMpaOphGEDZb8KPzzZIPPRlHV4FuftPPFOYDyWt6xyiYxGwaHcy1vclHSEom+tg5MIvFii++gUzULZ4sXBybMF/OPAwVm55OAMFcm4cuCmQnWxgiNC+5GUOag/TfOUncfRBDweCWeHJuqdHmPxtWOcfJZCoXx6FBzS4X4JC4s/mgC1g1tNkoMTAL74MlQk20W2vVWpQOcB0bG1yxtNMxujaP6BWbXV2Zjh+m3FMIsG9Jyj8HQ8Yb/sfzy2zW8qRRzaRc44ATcQnBzg8ZHMJdQ+Xa0MSjEsfFqtXIluLuaCFJSGUn9tmxHXZOdjK6gpTsDmvmjt01XhLA7YDSmBYCqVK7GPmRf3+iJjrALEwYmmBa9W4lC112O1En4SG/3RamfjUcb0BQA865PzkdZSZJkI9RfnYLsIEQmE/6VEjHixiC+hSo+PZsgaPJuj/qLZmKfsPOZL0LoVZ7OaceczTH9vmpdk5HAvFWaIW7fghyeC6bENv09MWYOyTzRky/EJKp3g1OxzTWAoGqLJZmzDdoNp5H7zwTE3N1uo7RCXpEKclZ3L3OQxamNvZu/A6IHWwJxZaPksZX+En+uDM7Bocp9HkiQCnVK5qU25G5GFGxp98ZvzZucDSOcd8juAEBkJc2znlIG4GMc577q0ENrohq3nYoSQfDLZNeq6nFiol/ljZmBlFrc+cFzaxa3rQCzAJ5qbiIpdnDXSZNi44tWpKtBaoiFYt6AQofDFtY7SrsG+SpR7ALBaw50v8xR1ooy2EJXC4hm0WGU+j40EuCvkQH5zkIMcZCe5n5rFLtEQcgLSKi0RfZPFLM6w4oesyIzzcygaAmyAstA0yeZnky25WuX8i+OxVOKGvMUUmu3nHnQcygAGdZbGY3mjBSi5hWVTU8NNJwk7oVGL0ShR2gHA67MUOdCaG+t1iub0CUKttG10fJyqqBc+CzWh6PEjUO83fBa0Wgln5sDbKs4HkCDp00nyF6jvIUQ0on/kaAq+8FJqUbNOj6ZSRb3wWeDjD0DPX2X9qs/CXczEZ2FMGTo+Bk3G8XxpPE6grFEjJgqMz+JoAsCUOgTAy5Vkfv67cG8EnwVmC/BXP5DzPZtHn0U/5LN4PUP7dck6rc/OB6ve0MMH4rP44kUyxz58jNkf/AAnBjfBp0dw5/NBnwVXJKAvC8p6fYtZp++k3ASUFRaVa4OyFGX5roKyfG4KYb2WnJMMlCXjYs8xzyAeM5tt8oJoxqWq2i9fSXYqcHugLJ13Q1gLAHyRMmYjIMqaIfbh//z5fqCs2Syr5B5BWaE0QypxyWL6FKAszS9qvrcFlBWwyxko6zzxalpQVhOIc7eCsl6fbSBQ8ewljn+DpFauzsFyOQzKOp9J3dzz8xyZepugrHdOdsVTDB4bYv1EOTQcSGnQXKoihWiFMps7Zx8QFzSOAUJd7vt0A/oebPg3/HK1sa/ul/3XYy2cQPEcPieJVZ9J5jsxfggAiYo/FJv2BQu3/EjZwucvUip/SQC7lRLAzAebsZRp9oJvcfl3PZc+OF7N77Y3Kglpo8g5yXHpCJnzVZxb7kheAuE8soe27cB2vH0v7TlC/8WzbN/IFTJExnRhclKASBqkjukhpngAwrqu7Wtk5fxctDlz71BgIN8Ii5OL3CAZZPy9dnCWJoergrlB+T5DYh64WDbAkt9wqrPgF4sEaCoYmkrym4yqP/Thjo8TXb9SpmnWKXLyG163cA9OAM+G/GYijqoqcF8WZDu2cO/WrNNAfgNvckC0avwW8pvq0YOk5lrym9EovuHdg1OBhTMnFu1wHrxcZRmycc7G4xSK1BBo5RKEW008Jb8Ji7Ybj4M5t4Y7OQn7NJE704LQ6KGMazDRbLEEmjpS9jPzBvkNnBPzo095KFE0fDzTMKucd392AfdH/gDcp5b8pgbPF6DHD2XDFeQ3NFvAfySV0N1vfz+ZwNaEPT0FjRr4l68S+c1XnmL9wx9h9Fufpnt+Ms7qhmRZp10PN2py8ptPd6+ifnBwHuQgB9lJ7p9mAQwDrkr6u6uaMDBncpQKI5s3ldQUMYWRlQOizDqta2PnB6dYKGycsYMrKItIAFP6tldQlvdAyAmipk4aRe8T/4a20yRYtqWrsw7OmHVaOjhDG1nWaSyMnDSTqAkoIGkdQm4nRwIbZs4LIwN5gWh9u5OT4xcKypKK4FTXCSSmhZt1/Nr30VSAXuSywsjcthvXyz86gdMEryJFnD0LLZ5qMt5LO0cT4FWV5k8dnAU0HJUDHU/TuAK3Bc0WWD09xvR8EeeBRw0IQP8kgLLOquhw7B4GB+fIwVcO9bxFBWD5VJyO009CYegCxUonR1IYeb5IJuCDY8x+aILmUwPKOpmmwshA7NcfjUBtD1c5+AfBwekBfLG7vnA/F4tbkA2UnPeJRt3uV3r2WSpFkUJu1U7foNAP9GgWH9H3CWFoaf6BjE5efjeOW617mgYfCsZs9smGhEXG2cfP2Wno9xJn0RraNc1g1XYVwLVaJ0yF+hR4E7ORGvWhtKHpk5ykmUcUqjo420BtpxmvbQK96UOiY+k9OJLjArQIFck2uB364OfJ80YkolLHay6Ls5AKsX4PQuyA1dpEiNL1r8/bLCeFEEzL+TrOFzohv6nq8JJqa1REUtl83aK5CO2q89YyuxMBS1mcva0Mt1xj9LpPvhEAWKzFtIkvkmAWA3INVmvQ3KA298BZ3M/FQp2U5bZ9pJwkBS9tqdFQ9pV51YcQdzbNOm40QCwUC1YRRUhckX5z31gTIwFutI3sxgnjZJ+DsgCIxjQAyoJ1EgYuSAE/mXkJ/KIZf2X4Dp9IdJUpC94V49eITKLxj+CqIkWdDHArApvCQiFMXiZFfS0LDcNEzNnUQx0CvtnCyEDg4fQgFM5iQPbVbcbxWi3auBCRks34Pi0gXQDQMYOWYb+ewURyvboebpmH3kvhrge5zvCcAli3aOYhMqfztZaxENcptV7H1Xby28o89nsEC+7nYmFMDjENkKuMg5HqognzZpDswUrUahO3j5mjes+ETE3BKRizYDDrNBCkOuRhLFWbK1O8t6okF8H7VEpRS/MR5WZIGKswKAXHpmadVlWOO9BxmtwSW1KRXG7eABA8gY00OBczLuNNOmqAdcIjAEgP+IqSU03VaSfnw94wTesQixAfQpZpXDyaWvIhYEyVuhaNwgldnxLd8GQEWjYy1tqMoQsL5qgROLn2XdficNS+XcgsRSdtmAWSKies3bqvjsWRkN+YspM8GUlIWmn4eg+unFQ1nwZcyzgc31dwfY/+KDCea7aruae0bzR1lofEkxHWDxo0E5MhO25AXS/nzxw1LJ6MZL66Djw2Ts09WLTu52JhJK/taUJ+V0xC9qbT40qzYR8I+TaxtRu0jSKEp3H9zWN9UqcLM+ROZZtqum3OyuNKDancbjlFrytRqyquiWI0vAlN6v6+MOfK8V9TiJGdM/U+f3kMJYYxwCQaBhX3MDPLgu3Toj00W+Q5/sXzCBpM/LtFOURDDnKQg+wk91KzEH7LpHqz7yOoKN+nS1yYhbiQyu1nC8AR3OkJeLVO0YDzc1Gh1fQAAkEO4I6nEeZM6zXo9CRGGWIE4eEDgTKb6IA7OQY/kdg7fdqDQmEh7l/Bf/wY8AB/IfF6CjgNmk7A/SxFHVYr0HQCOjoSNB6QsBOnJ8AHj1J/fS/jfH0G90j69WpbT8aSgaiM2AFmzk8/gFOU4XyZVP0Hx6AL2Wf5ox9i8lvy1oqedQismQyoyJbti/Oh4wTAx1PQZ89kW5hPfngi2aOKVPz4A9DnzwVe/lDSuP2jE9BCuCt5ktT/sz/0BKf/Vkw0juYNwY8q1F+cwx+NQQZn4Z8+Qft4itFLCUHRybFEetYtMGrgLlImKY8atB+eovk9wWQoZJrmC3z6k0f4Cj4KOzL6SY3R5xO8/sNyLY4+PUY3rUAMzJ7KI9dNgX5MmLxgnH5/gs//qNyP3/jkFHh9hljMKkj7I0/RnjY4+jcMDuOd/cGP8Lv/UYUfff0oYgQXH48x/XQJPw5RkJHoA6tHNaqVx/SzJRZPA9FOD/TP3nO4t4UUc+G4y/Yx/zfaiFBeL87yUDgnc2qVUY7gLPSLZXQksmfwxWyz//NzASll8OK55A4goAdN0R33/AzwPnpbWENkYT8L8+XlCmi7VIpP+7iYZeqqjpO7TuDCSIsZL4LD7yKHmbtnL6NdHxfZdQtqkxNv/LuvwBczgBmuUyiopEZL+QPDARqK67BS3KuQAKUiPDs6AzvwYpkW3eev4lxwIAl2ek59Lz6KMKen/7aSeXQuRSsgJY94sYRbrIRKP4zXPXuN0WKd7gWd7+DjyaDVdY1m3cZ5VMg0r9f46J+v0Pzey7RrU4POZ3jwGyE9/GKBUV0JX+cLWfT9qAIqglt0qF7N8WETfAvnswTGM+nszScvUI9H4Ndn8bofffcVvvK/P0Hz2Vmcg5PzseSiqM8mLDjjzyV0SmcznJwfxzmolu8zglNFEX/q4JQv4cMOdqgNrVHgUjAl49Q5GHMpYvs7Tq6lx7e08zp2iwVQhyWQ3iYuUOTpfpbS/k5LASSGqEjxpv2rc5YokMP0yZHYe8BViWwGSHVP0OesUq66ns/ClBog58QvYGgAIx1+XcXELXVwUlhAImK1DSjJps7e4NcRX5vrA8icOJeM/IzuPyykGkKtw3itY7uuZaz6MrlkfL6m4BQu5kBDr9pfoPq7idzLxSIzOWJE4JrVzsk8tMUbCVUloTwyD/vuC3Fqs6xdoRGGkEciWY0V0MGMpQrAK06LSzhPqtxe8fG9JT6UYfF0VRizoZcPTF36BiOEiIdL4CkODloKbUZIdyCN2XBOXjkucx203bqKzkxZ7IWViidhwepZQpcK0dcohmegcvCjGi5Gb67n7OTKcIg4AjeVLE7RFHKRV1TNI65IoiONA9cOrOtBVYVFrUlh6dEWSDYRfC39xagHhYruIas4LtDVTZeKg4PzIAc5yI5yLzWLOxFHQsxqZcubb6fy9TGr0KzugAmF5uFFsmFFABEpOtRXCD2mMoGp7ayOxpAJZH5THEU+7uK7Z4B8RHJGiZR7AxqO8QsMhSuFm9SMYWhcW74XDYU+VF1P/COk19KHseu+BZKVFB0KJHNU+y3JbU2CWl7pDNGMsEmO2TYH8fRGswByDT2LY7tIhGQ7rr5PWq+lbnROwvLm/uHKmqyU2iUSbaZySRPy+2kb93KxUKo5oHBwWpzFUEUyK5HYxifTwvuCpyJkjWq2am9sZrWJF5DPOY1CbN/CoKPaHMatlyqmJTuSVO5wDrxcSRZhl7gTuO8Dmc0EcGFfvYEtkbCOs3Jy00d/g4u/2ZIGUeoKWNsFrZebtHKRJ5SbSmjndM50vL0sDDadWueSyKVyA57BYNDRJOV26Hw2DdC0yb5umrCPyWZ14jvi4I9Q8aMKFSDbdDuRAJUWSxmj5askAnUJNk+TETAeyUIwanJQVl0JgEvPTQFXjtCPXTIVYjY0wU/lnNy8BY8EVt5NQ5Ri7NCPHEavO8BJZAQQpzKvA3xc57btgI+ewB+N4OrkY+FJjW4KUJvPgXNOwGMVgOAb6Sc1qHagZYv+OETyep+ZUFfJvVwsAFyNPLuqIpmB6wpxTKhyZcOs6qPIVn0vzjEDuWbLAaG7KYejASDxep2iD8wZuS4HL3x0tikxq6Z598bJyiwRA43I6IK5/P/be7eQy5IsPexbEft6zvnv+VdmZVVX93TTNdJMtTUaNSMZjBkYrAdjELZeJBB+8OAxSMYverJfJBB6k20ZjITH2BgLLGMw2EZjbPCDbSTPWAg03T2Xnu4adXVVVuXtz/92LvvsW4QeVqyI2Pucv/LPyqruzOqzIDl/7rPP3hGx9469Yq1vfV89fPO4dtq+9wVUY5i6HfNoOAUwAL42hBrAYuUfHnW5gCe6XUtBnmGeyAgFG2DjakD8g5bZuuz1YkhoA/jMj6cOWCx5H2siaULLE7ixg5dE8nQeyrNjFGm1DsRAEau7XVbsQcj4rVYM4+57YK2H2RuteSyFmFfun7bD5MEKdOGyJO5FYpcrpA8dq1ZVM4+FtSgqR3qcJQ7u3UPNl5h+nA2OO/ColAJdXEMvUpjVyl93fXaNw/dzPr67NknXgxYrnmCt9S+ndFVzZmxVIY2In+KJ5nn2+k4WvsjGfSiC7W4f9AsivkO4cYCBW2wNIkpANMqaDKUAen8c2w+RmuRg3YB7sCPcPqWpr46Udom7DmsAJdF943PwVrkbKxJKGgTDXDtJBc/Ew72duvk40k5Cmw94d1zEdyzcA5JnQQJPMh/aBFKbGE0oFnN+CIxda1Dt2iUeRqS16v9fa/aORC4gz3wxWSyJYCY5VFU7TyhMFrIcoknp068AGP7tKmC574nzKAT+H70ApPJWJnipgFWEZj9DElfrZimobtBPGc+g5KE1Fv3MUSnmCaAAVfcga9HO+Hh6y0uQ6QszptWTamQAQw+Y2gAAIABJREFUtsyxPklRfBjSx3aSM7xd4N6eRyMD2oS/c4JGMRz8NkbbNAp+0rZPx/bP0q8NN7q134ATU0yNUkmO/MZzWjYtxkxYYxuXovs/pQjKWiZeqdaDNa1tm5GnYQfrVH8cR64Tk9/EKcl43OWBjGHqQrBjR2AvKdQyskSSNvCBBmlAG8cOZMxMcM8HsHgBUsU6IFFRGIBBDQURDbRPYuwLlaKNwizTpq4HfSahlIs8iI2sllcv0/7YSrRV1KhNZrgvpUlYdvWGlx5ufKVtaDu+HknCmBHwfRMzTMXZNXITb8wsJtcluXcXxtHqgRyIra5DVqgPk6hfvqZcWyOC03Swz/uuVjzJJkmgWnT3ARENrruazaAOD8JvuNHcRqUG8TLSinE/bTeof/qd6rdw1Z/dai2yy4bsbGc7u5W9nsuQ2D2M1+gv4CUN3xpx2Xj0ZnHlwGNN0Rdup3fPlV9eDLIhsLzOjt4E1lp+82zLkjyPJ/RlbcDBYYJHNEK3DjgsJPMBBBJYESeSYjo5LpkXcn/jc/LPb4hDuSWHbbvNLE1cAu/2JQP2PF7Sux5whciYxEWJURA4bAs0jKxLEmU+xr+7ySTTNCbdja+FfL5AdelN9lpOFt41hbit4EkjrjCM3ewtN4MS0Vrn5qvJhLMOwpEpUe8YtSmozCzzyxizWkFNJsx3Cfhzqdl06GYDUHnumaDMfBFc+KqCOjrkTMIFU9nTdMoSgRmL4cbcnarMAjclELItkdQAAJhrJwVQ11Buu2+nCC/L0s25vProcAPuLUxZPuB3cgScX3JJfxHkEu16vREw5Y4Tj4ewYgnL1N7MxxD8sjDnuIA/93QKu1zCrGsoV0sjTFkYM2XdPYY6u3LxkGhpScTBzCwNHJoGoKMD2CIHfeK4RcuCzx8tD7xpzbUjAveWcXt2jvpb76D40VkYhzSBmi/R33NSAIsqxCwOtsC9L5ZYfYP3nXznIxfPCpktIoI6PYHNM+gnZ4G39J37uHzvGAf//ImfHM2s2Ar3tmUGajqo+Qp2L5IC+FGorXmevbqTxSg1eqNFa90Nj+PTUqcDWDenvkhRuPkXywC1lrnCBS05UBlSkV5RmxvMnxKoi7EOec5aGUSguGitd1oOxsCec42BSnQUqGuDFmhNgZYuZr4GB+hiWjxaaqc70obAZxVg5TFhr7eyCGlLRYwkTTRvF5Lagwl00wJdD7vv6gy63sUx2qGOrEN+Mm2gxDTKEFgWuUGvdZpzYaD0wQcV66DVMSlAbcLnL3P/9myPSmRVA6QJTCZITQPqGK9inYo4t83AFjm6kymSMzc2Sjs9U+bDGHifWcqBQRfY9eOsNZb3U2RngdrOTDJoY9Aec3tTTTCpBvUG9Qlv66Z8HfQ6RYFQYDbJM45txDE1rWEnBadOLzJPRdgflJi/o7H3wcw/L90sQwqX3jaAdTUn3SyDrjokvfHUfmTtC6VOX90Ap9goADfYJiYeRCxO/Jx++cBpH5HZ2JBas04XYqD9IcJFSg8CXJQkG5WtlGZ+CTMgnNGM27cSYAM4kCjBMEklZlmYKCV96torbR3T6Mes474PisJvgGFA0UbkN8LcPZlEKc+Q9o0Dp+LtwJiA63A0gTEztl/COA/A4xlkDPp+I2AoHk88AXIKuA8BTgkGx6lQIFTSxuPgwG0xRSDgliFZxozZks52AV2v/REvL1ytjveOXB9NXSN5+y2Yy6vQDufNDfhEhbDJBb4pIuex6zVIqoKfPvP3s43SqEyWpAf6K3p/BpyeAGehiA0OBuBLAmRcHedq7KUCwG9f/6+46p7uApw729nOPj97dZchYjd5CFG60FucLpVYheiKxNs2juVwDPFqZSQC5DayVxFR4jFdW7axXGL3P6ik8zYKcYqmAWlHsdbWUNrxa0SSgbyPSwfKC9RwBSc5mT8+GPnlUPzWMHDaJPHbRNxwUoCN2uPSlZSlgAtNWDcgRPJWdQS0hZNOjOHlWnPQs2kDCjUejywLZMUOM6Imk4CoFByI0yehKA7DSmFRMV2kYRIHSmk2jQKuEYS7yGBXK1CaoI9U1lVZuPvDXZ8iB8nyMc2CjKOk8LM0cHJkTFOnANi9SRDucd4pWRP4SmKNGKcbYl11LFVOeS7CPgzAYAAsAHWwD0pTjhNJqng6RXcyg76IvJqyBKiKaBRlCZzBpgnoehHSx9YCy9tX3L76k8VntU+DeUdgFX+jJMmA53HAZTA4LA1g1TSmjZclgWiMRjMQJQnHLADOrXsexyZsv74Ov2+dFICJ2uvkAShNNuI6XmpAzic59b73a2zvRjv3PqyNXX/zfCOTIO320/KkBAkPRRmdr1qDVAMRPRofI24nwIHOOIgqRDtoyKvB+316E6QA8syzcCNa29vZZCjNB3hAE7rOxaUi/o485wnCkQhRlvJE2HVMOiTHsC6GUIQJmgrm7rTrGu3JFJkExA0DsCwAc8CThSLyJfNGtE4TBZNqJPMECkBzwvumn6Rb43Q0KRnstV4H9Oi0RHWvwN7HkRTA/nRYViAvtUkOm6fQbTcgLMLj2y8uvryTxfNsLJsnaa1bxHBiFnBr7NbU21Y5e0mHuvMPfjdm8xLiHRN9xm0f8y4CQ6kBwBEGCzt39MaVOo0RS7m0Y4NZvO+Z6FUedtE0VWqodWpHY3rDePj9BFoNuEmcmCMjZkb32qOR9EHXDVm4xZpIxkDOCzdh9D0jM0d9RRekAKjv3cTUczoy7hs6UBtQqFZYwS2ze8dSAHKdhckbbecLvVTlXkaJ4sBr3QJtx8eAi/NsQw63HUsMuH4DgGo7JIvRNa+bQcqdZOJ2sHx0PaiOdH5fIGb5pZ0sSBGsJU+75zaGtGoUdORPt+15+Wgty5DARUF5BnLutJcSFF6B+N6NCWTGVaPJ6FJIwFZFn2ICN49dTUnpOtg4AL5p8twR0rgUmV77gJlFiOqTPCRJEljAYkKeJAFpd5PFhDGxfGDLehtDpnXpDgWCFw+vToFMjunYp9OUPQGXvqUs9Te1LP28F4ihZ4Es3YSvS1HYWm98JyzgfimVZuyitx3MyT5UPI6ZG9cIcg4no9iVKbQs85xngTbi1Gja4FmULpDtPAvqDGidoHfbU61CtWpsWcqs3HkOJd5vmqCb6eEY5BlQt5ueRZFi/eYM5aqGmbhrHiN4b2Ff2snCxm/bsDH8PVrbyhvlufPsaB/b97B1s5GZ8MczQ++BZM0sbzFpa7SW9r8XYZ1IYMf/tmkGEPBtzFO2abnCs2nCEqLvg0BwXEgmbY0wDrF+CAEhZrGq+G+lQn9cmwfVv+P++Leya/e6Dssi1wcvtuSribmNA5FiUuF4UcZCLVYby0dLTAJjmwYUZ5AA7mukfUJ17fRBOq7cFEyKsUDbujhS5EG0LWzdIH22hJVaGcmo1TXUFS954piFili9tItZ2FWF9NnSX7OtYk2riiedOhozAOWj9bCSFgjwdoSYBXU9CgC0WEHHbOtjoapPsV02ZGc729mt7EvrWXwqRdrLYkuEEMb/3/hYwE/NtsVbnByjHa9NrQGTHSAESW/wCL5wixXXehswJBIfEUzFT8C8XgfgYiXuvH0/JDMCgvfzPNDg59k2Oe8LczuyUes4QGzkWbyAfXkni+cJJfsHO9yU1thNha5tFpWo+/Lv8UThtsX1JAPFMClthwMkjZCUXuUsUkGL2+6VxoAgE+j4G2OCG+G7DJKC7vfCBBW1wRr3fy0sWCb0xWVVAHAmSEiG43ZbuyHJMB4P/zfgiGkjaoCIpMdnZByYCJIZApij0iqnBhfVBmXpZuwHDgAlcZd4uaY1x0QklpIkoRQ/S3npAfjqVEqjmEiWMmkwrRmxKSAruGrhruNSfiAohAGeNMcmCjbVUNaC2s4rkm29lyDxHXf+SBmunaVIIsIjViQbjpWMjSky6NSV5Yu9AHHy6zlZxGnRT4N1W4sNSmOJEo8IWnxaTgZyhSgdOiqjFhVzuBTrOHAGFwCLEIpybKndoGrtayTsug41Hc/OQzvWNac4pewagG2biHchKuKSdk1DWsyuVry+tzaUzGu3tpaSbalxkXGYTQGnreGDX2kyrDk5moFWK56EypC2A1WOgGdzqpXx8H8DoEkRcB8ySRQ57DK8yWUfa41PC9O0dFH/PiAhAdb1aEYYDyIPCaciB2I+i9mUoeOCvsxSoMg56xET6IAfVrs3CYFXSRn3PVZvTzBb7rnB4QAnaYXmDd6WnmuYgvvXHvLv+kzB5ITsMkOmFFZv8/jOPsi2eit2fwpTplDLlZdPMMczXH09Q/Hh1O/XncyQRJO4TbkP3SwDWUBNS3QuTUvGwj74sqdOY4/hJkasbdsjt8sDX9z3plo7uPINAVH3f9tjkKJjFqpqmIIFWOuiaQYBNVOtoSTwGgFvbN+HAqVoX6b2a8LnqO1+IpKgatwORMGyvg/BuhENoQ+OSbuvrn0AzU+kDStz+6K7Jxess6LUIGUoWh5bA5wSFI2t6zaZsrqO++WvA+tkWGMDv0PXhQBy9ECnn5xvjCNIAcuK+18PA6X26hpYrUPQcrEM1zYN0G4PK6+bIVOWC8jOfnAJnF2Ga6FZcyT7yGW7qjW0BDivXE1JBMqyqwqz0X0zNnp6Ae2g6RIg1o8ucOe7Gji/DGNQ1YMAp2R0ssuMJ87FCmmERaHm9kuaXYBzZzvb2a3s9fQsbmO3rTp9QQSnLwaTdWLT8t8eeh1Qil8ogjOik/PdS1NfOg0AtK4dFN1EMPNQCGV7+O2eI/MnieAsCo/p8FW1RQFQSAv7fYRCD/gCEZwZL4O63i+VAPD4ZykvPXy7cvYOFsufDIJzWjKt3qoKXuALIjihFJQxMHtuGWLtUCfnOfblnSy+IKNRQEjg374K9SeZUBDQkMQsIiEfAI7h2dWxxNybMY1fzCV6GyW3z9ukDx6ARj6AKUZab9LyfyFtoUDTFwc4+z7UWMQM41n60mpmt7aIM5a2BHFvY32ZQl0pL5nwokmmV79EXSzi5NwmdLxhMU+nQ3CqooDtzXBdva0gLd4+boYrPY9rQShJwtpb3uCtA1WNSusHpeJyDBNIXHzfxuQ9cak+ESiJItrSnhFC0lqX3YkYl0w9ZAD3SFQpO99S+s5ZnaD45svGMZw8Pev2NlN6cDw5jvfsXNn6oO/AILXqzxmV6MfnpyzbXO+7cfHl+tG9Qy4b42MxeR4Cv5PSkwDF5e3+94LkFcSneKICkOv7AT9pXHDHJ1OeWdx2neeP7RfLrW8cVZYQbhQpfbdX16DZFOZqHvok12Z0L0ApqKNDmMurAYfJb1/9L7fm4Hx9PAtxvboOqij8xRHGKJXnTGYK8AOcOk6BPIet+QY264A2TO7d5W2OaFXde4OFep2L1r//AfRsCtt1LGIMZteyfQ+1f8QReQD9w8dQ996AffiYT+3apX/x50HnV646012LowO0bx4CCsjefwxzxCSt9Ogp6n/layBjkfyT3+Nzff0d4PFT0GwGc3HpVdD7x0+g793lyPy5i+ILc9LJEdr7R6GP73/CN/2zC+At7q/+mNuJsgCqNeiE9+8++JDH41//JSTP2KVWC8542EmB9s4EySWf5/xPHeL4u1eAtahPXXbHANmzFejB41AD4kSSrbXAz70Fdc5jbU72ASJ0swzZB095X1d12Z3uIXk6BzlEZPvVU6Q/for+6RnUt94FANR3p0jmLXTV+ig/ADz6sxOcfqdmST8hdSGgzxUmD1Zo9jOUv/eAz9cb1N96B8v7KU7+H7dtb4L2ZMrHLVOPqgSY0Gb19oSDmQBaWTZ854/xh3/3Xbz1W27StUAzVdh7UOPhn+M+7f/YoJ0SYID51/h43Z6FKQzyxwkO3rd4+ms8Mb37X6yhz67cMivUzVx/+y2sDxVO//9nwFPmr3j6V/40fuHXfx/v/91f9mOwuK+w/+MeXUmABbqCx2F9SkiWwP6HHa7fCenp5n/+P3Fbe30mi8iY4TjckLB2g+3aa2qM+QnlGC6F5jMLF1cMCY5KjT2zt2QbXHbDLpesfeGOby+vNs/z5Jw1HiJVcTIWmdvPXM8945FdLFH8i6eAtehkvXp2ziroPYsdCbmK7XuYq2vQOiiQy7nVxSXSWHRnvgDqmrMwTzkl6ynZXNZBXUgUn8cz+/Ez2KUc171Z5wmyxcRDmo8B0KNnAIDyKjxQtlrDLldRIZrlOgdjoR4+85M1Ofc+K3JYYcV2WZm0qmEjbYz0Q4K9nnNb5ZzzCmhY1T3LMt/2ezhlNfN4Kaa4NoQurpEUeWDhBlD86AzZWenHltY1xx6aFjpLA4QbgE40p0dd1kNiFH1d463f0tj/wws/jjZLoK6WeNPe4T6cr2Adc9f+R1HqNCVk1zWyp0ukFb8M9MOzcF0jr3Tv+yWmkwx4euGzQnd+d47v/YP38Ob3AqXf9EGJ5GIVMWXxJNbPMlBnkJwvkZ+FmMW/WO7g3jvb2c4+Z3stPYsvxMQrGVd33pSGHpeM33S8bb97AdTcC9vLxqC2/X6kezL8bpP20MdMnvcqisr0/ZHFY5TtdgsFQBTQvantG9qjcTxktG/4UczIPYa/6+G2aD+y248X9Fbd9yZsI+PYxeVn459H2rtE7J1RP2qTtVB9FNeS4zj9VAADaDc5eUmSwjm75byfYq/lZCHl5+4/YZtP2d3CtRpH4ZOEU4aRJqhAwP2CUGvAdBA1LW/bEJwCZY6Dk0kSSpy18uhDKxBcG+DmlKaBRVy3IepOKpDtjFXVSAVYMYCNMvfBvjTcHvXFt8toF0zVzLLkHpA+T1iBq+thC5di7A2rXUXl+55ngYyDXEtg0wVn4/JwP0bunNH/iYizThIEzlKeXIhgi8zf/H2RIEkd2W46rH2hNOHfSaq472HTxEG1k3AdRclLIOLRuAy2yTgrQjNVfpkBcBk6rRL0TtdUVwmzeVt4rdOudELFBkgWKdppYLTy6XGJwWnFbc00dNQmkyVoDghmkvlAsCk0bJ5we6wNy5DCtcUdB3C39ecJ9yai/xbAvwXgibX2PbftbwL49wE8dbv9J9ba/9199x8D+HXwO/k/stbePoJyS7uVMLJMGDe94duAUiRLHPluI0FeUXaKYhZSLj7IxkQoy0Eb16yvGetuYL32f9um9Q+qbRqo+ZIvrvTH/d5H4FXIvti6DkQt0i53HESixIPvR7IB1v29kT1YVUEAWZStOiZvkeyAvshYxcvYgYaHXXN5+6B0XtoclaNjueJxaENmS8bdupiBP8ay8qXvspYnGT/TA03jX47ZkwI0Z1Z2n+oEOBuyXIHqJspaGKj5EtqYQJJsjS9RRzuUAmBxauX39S/kvsfeg1CODgC0SkDzJfInDp6+qKDci0N17qHONKwi6KqFulxi9sBlTpYr1qVVakAMpOZLUM3s5HKPJOdLHPxxAf1sHibFmrVTPfG0m9RUlYHaHjRfwefRrAV1t49Z3Maz+O8A/JcA/vvR9v/cWvt34g1E9AsA/hKAXwRwH8D/RUTvWru1tOgzG2nt+TGF3Ia0ho06Tq6YRz43juFqGsg9zKxr0QRauvncA5f8WkRrECmosgi09E0LtTcLEGkXFKTDA65DcFyVAKD293wmgLoOtM+1A9R1MHeP+YI/4WAVzWagpuVsRt+HWoSqAk1K0HQCde2CtJIZ2pvB3AnZENV1oDyDsRZ0dODPBcBliWqovRkAeN0Qc/cY6pohzZ6roshhDqZ+++rrx5i4QGp/yL8na6GuV4FEB0CozFWgw33ABRdFqs/sld5bERIeczSDulh4cJV98wT0EEwR6PrQH8+gVg0D4SLw1NV7h9j/I82ROL8UYjXz9OE1+mkBVQXwVH/vBO1xgfzSAeFmU5iDKWjdwhbpYAKweYbmjT0P4RbAFc0XePjnCh/MpN6iLzXyJwXOv8XtnT4svZexeDN4FiYHirMCew8KPP4z3I+vfrjvvCY14I5t3rmD5iDFrO18oHH57jE+/vMGxbNjv9xY3c0xeViizxXIciYIANZHGkltMXk4werN3F+e7tHtcSLPDXBaa/9fAOe3PN5fAPA/Wmtra+2PALwP4Fdu3Zqd7Wxnr6y9TMziPySifxfAPwPw1621FwDeAvA70T4P3LbP125RSOaZsrYFHxG56NYARvGSoWmHabcNfggbtC7IpU6FKWvM/VitQyGXLJnqGmoepTsj1ixaVCBjfbTF1g2vQ8V1j1OzTQtL65D2laVF3TA2QpobfS9pQN/OpvFtj03NK98uWzeMGIQrSHJv+/zZmttlDNQiig24Yrx4/DzOolqHPjg3W1kb3HoR+9WKC6Fcv9W1Y7+yxrdLXWuQqzpFH4Bvk0dTVv+KFcmIoFYtqKr5fJFIsVpUSDUFAtxqDUXEfJdNy8sBZ9T1SM+136bcfdL3PfZ/bJCeC6sWxyhoUWH6kL3X7GINs0wcMze/1btCwSSEbN4jO19j7yMXy1rL0tUOxjK5qKDqLtxXAPKzGns/mCK9XPoxKImQXFTQLlaROJEhXWdQdY/kYoVSwkQW0O3tI5yfdbL4+wD+Fnjp9rcA/KcA/r0XOQAR/QaA3wCAApPn7P3iJrKGXt5w8/wAEGDESoOo2xqsHB+Xy5dDYBVb4N4chCTPY+l29jUCMScGAEYSxrFJzXwNMUzbm3JBR6FM8+jA6PiAbye5IOVgX6HxH9UG2JhfU+DXRLBJCFyaPIGWIK8E+uL6lW2mdeiDrKfTiM8i4pWMBYnifQbBxY6zEzZqf1dqZC5A6sddgYN9i1Hw1x3HpBoqoh6wKT/U0o7BvkXig6EyzkSEdkohwGktTKahtPZLD7NMYAoOcLYTPldXKPQZoDoFk2m0k1GgNzZSsLmGKRMkSeIrbU2u0e45LIWbLPpCI8k1TMb9MFKiXmpoTUgWCfqJa6to0N7SPtNkYa197PtB9F8D+Efuvx8D+Eq069tu27Zj/CaA3wQY7v0ZGvHCP9l+nJFnMk6JbvNibmNjYVp/jCg1t227AMCcYK9nR3peqvbzshvSlACG/BmO3XvA4TgKOm8IIsfcj59HO60dFL2RpA0VIjZzFZjCYkZ093/qzYtd121mRn+PUqlk7UaKkowFWc6G+DSq75fhMJnv26eE/AyG95ikaEdsWPQ5jPlnmiyI6E1r7UP3338bwO+5v/83AP8DEf1n4ADnNwH805du5UYDorShZ+d2jFLxPvHn2NIoXQawXgQw1ArVilO0fQhwitSgCAqDFP89Oo+dlpxxiW+aIkfvqg7VReoFZ3CtYQ4mLs3q3nKTArRcMuO0roNWKeA1U8mLGLlgb56jn4UKROXaaat1VNUa1YIYE/XDBe72S08q6zMdZTHYXp/kSJ5wrYI5CF6hshY0j24pUUsnw32VILCDdpu9AvraBSglwLlfQjvaewDo90vo+RJYKD9e3UEJnSgORJYhwLm8myA7Zx1VG6WVu1KjqFr0sxz6cXir9gcl6pMCE0cMZMuc+1klTDQTP4R5hvaw8HwUUj1KWmP+tYDMpN6iKzVUZ3wwk0zuPYrFffemnwB94d74TY75z/Fp3pgUTLCjovuOFJqjAs1hgvTj3Ff8Vqcp+j+5RPM7pZ9YVndTqM76wKZ8VscKSW2h2gKrNwTuDZj0802d/kMAvwrgDhE9APA3APwqEf0SeL78AMB/AADW2t8nov8JwB8A6AD8tc87E7Kzne3sp2PPnSystX95y+b/5lP2/9sA/vbLNOq5FlcaauWk7WKA0W1AWdEa3rEWea5JAMKRSUKd7/a1cCCrQR5/i/cSl4eLObCQJYJ262OA18pdrkHGQknsw62ZJTZBMVgs0bxWj+IP8imq2a7B/J1SYW0fIxmV2mi7SXm9ze1llTAra3vn3XSl4pSlteiLUJSkUlEVc9oYgtMgclojyvcNRLzWjqowAXA7I0o7K0ryEU+pzRRsm4B6C5MnHjPXlQ6/kChfSGYJMDmDpkyeQAu9oOlhMo1uGoHjlOLfun/x2NhEoc/CNptIzEqh27P8nRuHriQ+toskdoVCVyj+zjli3dSiz4FuSmgnCu2eW35mKY+zixXJvWQyhT6Ta+aCqznh9GiOrrzjlzFdyd5EXyjEhWS9a0ufKXQ5/616Hp/b2muJ4IxtwFwdg7K2BQZjk4fSOmDRGAbstDqsrCHlXDIp+YfPBQnH53GBxXE2xiSjh1nORQSrQvaGjIVxYKjhmtRF/yM0YYx29MhFwAcgicgH9+JS6Xi7P3yiNoKeIFfF6cbGJOA2xQ9TJNAU6P5cbCMe36jfJgkTnoCHbKo5mNqQ/39YcrrfaQVNYakhN3yfk+dq8LEMRegzxfsqDNW79OiauUmROgOT6oiEl9th8jBeEjjURDCF8e48GcBqFlRyiQ+YhNBnAFlCL9SdOdDPevSXCawi2Cy6xpHSO8Bt7nP3kCfav+i6nHCvXOKc7vjgeJ8RTEroUwLZsMzoCh4okyn0bgIxP4kA5ytnDjs/8CxkvXcTVXssZw9wWi+m0ycFpCmobYeeRW/4t5JyNJb/HrNLrSMRIJlIuh566dbt1oa0KCmouuMb3DN4MU+GdXUNXghHswAxVQER6VGQ6xp6ETFFNS3/tuugKt4uwsvkUJKhypbbrwXs5NoASyCR13N9zK6NHzPVOvar3voxjMWfvWfRRrKILUPmk0UD65C0VLsU36IG1WG7XtT8t7E+9ZqsWlDdMlCr177eoji3UFXnmLPDmz676kBtD1X3Ac5veqiqg16nIQhY1UjmCR+7Myxa7ExZi+wy89uSeSB8zh8nyK5lHHnC0FWL4oxnhmzeQ3WKQVAC954S+ssE+QWQLg3yJ24yF+4MrT3KmJRCftGCTMLX3QH/yguD7310H++sw31bXBik8x6q4ZoVLZOu0kgqi+yyRTkJY6NuQQ0j9npOFiN1Lm9xifrzcBaelDYiuxX5PXcs2zSDjIgQ52yQ7a4bIBYqAAAc70lEQVTrTZzFcjWELQNAVUFfutReXXtIsmka6MsVYAx6eassK68kZtsuKHqLapixmziL9RB2PMBZSNn5GGcxoqHTF0vAl767m7XrWGXEjVn5uAItKsAYTqECPLmt1jwZRYpmgrOI1cJoycuQGMsg7VJEfuwAQF0teR9rQK4PGjzZoeuh+t57EXsPCh7HRPtlAgwABYZLW+sh3LbvoS+WKAAPb4e1jFJsO9A68fByAKC2Q6aU3yavpb7rcPC+RfY0jHuySKEul9h74CaL8zVMxstM3bC70U5YpjBdGuQXDQ5+6AKm81XgQJHrqjXSsxX0KnWEvu46PFxj8p0p8rPrMNk3OdJnUYl6zpNQOk+h6h7p+QpTnyEBdPPF4yy+eIuYsQAMGY6yzN/klGWwVeWYlgJLFZPf9P5zbGrGcF0jLv7xIWi1Zh5HAHR9zTDuugEq91YvcqBpQJOJJ7+h1Qp0sMfU+IA/lz09hrq45noQeaCOD9G8uQ9LhLztYI4F7t2j/sohYIHs4RP+/ZsnIAA0m0BdXnuKf6rWoIN9prA/J78NAOhwf0h+U61BkxKq74E7h9xvqXcoCz7WIUOvcck8DfU7xx5gpBZ8XOPIb1Ihv/nFGY47A7IW9RuuXb1Fer6GjkFZXccxlrZhGPkFw737431AMc2b8HtIhqQ93UPyNA3kN28dM0dHXcOcch/WdydIFx3UuvV6GwDw5JcL3En5IRS33BKhzwnTjzO0sxTltSMcMgarb5xgeTfB6ZMD34bGkd/0I/KbXshv3IPmOTOfXeDprzWejwIWaKcKsweZh3DvfZSgnXCaVLIe7Z6BzdijOPhhiYt/k8f88Icn0GcZ42DEeyXC/JsHTH6zqP3keP7eBL/yF7+LP3jwno9ZLO8r7H2Yoit4GSIxi+qUkC6A/Q+zAflN+8PbBy12fBY729nObmWvLgfnp3gWMZ+jLxRTOhLiifgv41r/+PCCL3BcmMwHaTxrt22a4MFE3JG2c+XiEq2X/bwOCZ9L7e2xcG6Ms0gSXs8rGojl2qYB7e3x0kcqK8vCBQddJaoAnpqG226jZUjEjakidm+zWjEytO2gBMcgHpnj1ByIJQHQR0fDalXhDY35MqcTXrb1fWATNxZoG/bqJGYhtHoyRl7QKZSJe+5SYRNzYynjJrSJtmmg95yQT57zUscaVl+Xe2F/D3a+ZC8zQpNaWRrF90LfczFhnsE8feavHWUps6FrNRRB1hqUZ+H6uIxPf70A/ak/Af0wsFUhz3gp5bw2Wjf+3OJBiSoY9VwJ2r19wqf50SOnSaL98ogZynNQomGurv1112/eQ/P1U2SOZQ0AX6dqvZFlQprwMruqgjCUtfj/Hv9DXNWPb+VevLrLkFvaBrms/+I5aMFRrMO6B5PQbt8/Oq7s6//fdhvn8fGOeFsX9rOSJYDLyNSjuMcoIj7+zgv6xMdvu0HS2LczFiny8Zfwm8Ex6nrYLqntEMQmwCXmrg3+LhtNamG4HHlN14XjusCnbZpw/ig7FavPG2mjtVE9T8gQUUSgAxFISpKQ0bF28ND7FLSx/CIwobbEujiOpwOMx5fUoKTfj7010GdXg/gGOq7h8GX3gnK1xgfGlSjKEcGua156uN96Ld0oZoHlEtaRC/sY1XyO9JPMiUu5MViTC2yPQItahRhaPAm+gIr66ztZDEhv3CZJpb3A7wdM3bGGad+H+gyxF2W4cvyTtCUV6fEdAN9UijDIYznSGjKWcRZxLYvWwxTgF2RxGwGEfigCoPlm9m/wnttvTJAi7PswpvGxhNn6xRvk2+VrP7QOYsbkNF218gQ71hXjhfRydMtrxq94tOdntfj6Sn+Viu4r8WYQPcRRnYyKx0YDZFguUTu6g0hzZWDEuA+fNQPgmdhEC3c8abyEvbqTxbY3qv8uIlyJBG1idu/nH9+95ZwqNcHRy8vXrSN8iWUDXqQmI86idGEZM3jbxBdY3FR506bseVipafC/64HuJW/uT223Gd54EjnXOggUZfASgwOJv753/VqGtgJhUvEYEjMssLutxcQ9cn/IuaWNLaegB29zE64rRAIxXnK+7MTb9WHMesuZmr4PfBRRrUxMaGOt5fRo3/tgplk7GU3dBG/wpvS/NaC2C6llgJe4vYlqZj4/APUuwLmzne3sVvbqehafwXyZ+AtOphS5avFShpwrJ97LTeXuW00RYNTmMgdgl9PFAwD23klrfhPHbqrAzePKTeCzufCfxdRQ4SxWL/PgMIFwyz42AMvIoTytcbEPeTUJUOtlTJYkG0tFt0yTwru+ZzCXLH3scBw9kjXuw2dsSzim698AteoKHSksn9B1IKU4JhEvsbTm2EpcwHiDd8HweF66DNqgRkDFlx1vvA6TxbYA5YByLGzbyJg4pa+Bypc7po/YrxngpPdL2Kb1UW6s1z5zIOey4ItIee5/b+ZzqL099FfXPJkIuGhvxgCaKICoyoKzHgDMs/NIWWoOOmA6te6jB37f/nrBwkbr2mczbNsAKoc6OvKK3pJ1oLIE7c/8+cz5JUf3l6tw3lhLteugJoyT6K+uAWug7p5yJB8IgbA0AU0m4XxvvQH6+AlX3wo9IQBbVbBXc1ZYH5k62PNgL+m3mk1hnWYHHAkxTQom6hF6woN92KtrmGXl+0BO09R2PSjR/hZof+4u0o9HpG5KAafHoItrznw8ehK+Oj3h7MRi6dq4z21rWRcVkX4HpSnriDqBH5q6qtvHT3H97bew932XYTDMhaHmSzTvMNVeclF5cFRz5CpuM4U+Z2RmerbC/JuM09j7xxUHM0cBbfra20wu/OCpD6aab7yNp9/ex93/O+L0OJ4iOV8GrVPhs5ixinp6tkB35ApULGC/G2m6Psde/cliiw2CmjeQ3NzoBcjkI28/eZMnCUeGowDYBqGNSMJpPQxqJcmmBqoLUMWEtkiSwIattQ/CkVZh+/iYWvtPb8LALdvkxkoSn5ID5A3DwTYvKkxRH/oI/izxlTwL4kcCMU9TZtF2iM5umiNNudgpbjc5UtttAz8I2EmsIEvDdZBt7vzWaP9/v48UqBUZs06pLhT+AWj3UiT5aBy14odskfKxYya0PIOZZL5wjhzLOgGweerHgQAgS2HKFDoL7XQDivWhYgEgMDjNZBpUp2gOeF9VdzAlt7M55M8+I3Q5gUwCvUqxPuT7aT/RntwmNjPJ0M0cE7kUks0yVKc0KNPv9lLoKvMM3jJZtPspYAG9yNDuuXvBIii33cJeu8liHBn2aaRxGtEFDWO4t+iD2q7ldFP0OzNfbLBdbxyzZ2JgU9ee+JZZp1eRQjifQ/Lhg/PPF1DyIFYVjJy7aaEfn8Wngpkv+JhV5T99O6oKxkQs43KO5dK3C0BgB+97r8RlPRTbkb64gB9lGXtBT858oNj3qapAq8rDx9MfgVW8lAJFXoTpuqEyXNyfCB8g/aZ1HWj15MF06VR/7qfnfh/j1NNoVTGsfJCNASbft7BX18MTk4JKEpjVCpQmIQgOQD85g7rIgkqbtaz01nWAIzT246s11HIF47wQWlU+ixFLCsIapuuva8wEnVqtkbhJOf3Y4VJcpTNVNeyqwqmr6YnHKTb94ClXKkf3Qfb+Y3ylvsOSkc7KZyVsVXnJACkpSPOMq32vF5hcBpyFqm4f3H19JosYUBMvTT4NT+EFfd1/tSvIIhXlyV1UXYBcZsux4/+TYlfTRZkHHgWpsIZvtvByRjgI2zONPf/HBIr6aF+P6ZDP+LejCD5pTlvaug7LLaWciHDAJXgxYY+3iIBSxvKDIxNwHGEXrAXcRBbVf3iTzNGWazEYj/hhEM/LpVZt0zrvJIwjAIbtxxgHyTZFKUF7cbUxjjw2nCWxAuSSU1dr9mJkDAwXCdreQCVJhM/gftlVNcB6UJLwsiWSFPRt6XufPbBN670FIa7hiUbDtsz9KtmLbfcNAF56iGc7daUK13MkDwgmxniM6pEkLUxpApye+LqiMAi3D/DtsiE729nObmWvj2chHkDXDYKW8vdgeWL57ckw8EgpKlJR1/tOu2K1Ylf18IArEh18uT87829b2zkXOUk5t12WILdmNZdXoLLwVaFyjuSt+7DRGxhwbwSnnI4nZ+ENcXEJ+sp9wFr073/A7Ts9gbm8gioLFjaWds3n0Af7oLL0LrEvZZ5NAaetAQD20VMO1DUN1BEXYfn4RpqyqJIrqOvPGPKs3/2Gr+60rgiO0hR2b+q3t197A+kHT3iZNw00frSsYM4vBghQ7qCFfuOOf/vSjIOwdlIATrBZxtPuTVkoSIqo7hwBZxcw8zn0PVaCt/tThlA3Lccv3Jty+fOnmHzghJ59pknBFgn02TVsmcM+eOTaZEDv3Ed/UEJ//8f++thpCdV2TD6EyLIU5ngG/YiXG9Jv++HHePpX/jTu/K4TXLYWJkuQnC+xfPcYALNwGxfgrE4dTDznmEV5YVA+XOP8PQ463v0/PoKdz9ljir2gb7yNfpYhe/+xX1K2f+ab+PhXC3z1H4XiwfWdEvnTlY9VCO9Gc5BCNwb5tPDFfzAW5p+G8oDn2as7WdxQ0wG49bUAfPKcYwlRJSpg/OQxnkT8MY754SGBNL95AjWvvHgMnp1DTSYMq146N7XIgb6HOjyA3XPVlqsKeOPEu5dyru4rd5A85oi6BNXM3WMsf44j+ntdj/YeP9ipMbj61gnIANMfczbE3D/l8uv9Paizc9DJkTvfCrhzjO54huShq+twWQrcvYPl18NkMVs3/GBZi+4rpwAALW69ZDfu3vH9BYD5L95B+dhNeJdMq9/t5Vi9WaJ8wuP7yb82wZvqLmAtVvcd96SxKB/VSCOAEHWdL7Vuv3qK9BFPCM39Q4AI9UmK2R/w6fs9Pk51f4rykxJqzm1Y/vwJpn9EoLpG8zXuw/LtAtlVj3TVodlP/WTx0b+hce+fHMMkBJOEtHRXAofv51ifpDhaiMiQweV7x5i/o/H2M67L6E5mqO4VSBY9uplG+Si8XNpZiquvZ7jzXffQ3+P2zs4v8Qu//vv43j94DwCgeovmgHDwxwU+/vP8sO/9YIp2D0yz8id5wjw9muNeucT3PrqPyXem+JW/+F0AwIc/+CbST1zVqcQ8tMLTb++jOiV8pb6D5AH37eNfLfCHv/H38EvP/qrPnF5/w+Dwj/bRTl3VqZvLV293SOYpDn5wgKt3eRv1QPP92wc4X91Csk+xeAKgJIVtG94W14lIetWlUMem3FvdOhy9mk05ZSZv8GfnUGXB6005V5r4oiypMegXS+jZFL285d259Okprw+lgAlgD2Q64Tfy5ZVXNTPLFejeKag36D/6hNt3fAi74tJ7u65Dqna14iI1V4wGwKdn1bT0b20AMOcXoCyFWVZQLqVqnIqZ74t7Q/YuhZl87Z2gl+HaTknChLqiQnZ6CH1+zW92SdX2Paiq2dOS4jTRYbEWan8vFEZNpx6HYNx5fbam5ACdxAvUwT7M1TXMcoXkLk8Wdlryg9SbgWfR3D9E+vgaSJOB1im13DabpcAzF4hsO+CNE1ZAe58naGjFqeCu48xSFEwU7wrnl76dANA/eoLrf+eXcfg9l7Il1h7Vz+ao32HPIr1cO34Jg+aEf9eVCiBAry3yswpX3+RxPP7HD7jYK0k8nwiUBo4PYMsM9OCxT53aX/g6Hv2r+7j329deRLmfpkgvKn8+kSjopymT/Vws0R85NTUL/M7v/1e4Xnz8s1FI9rmZK0gajNpLTqQ3qX/7JdU4UDve35hNXQ8PI7+97NwLWdwGR6vvxyX+LhLrAdiz8EVZ4yDxWA5BKPleFCi0ZTz9eYGgZt4Hyj9Pgd9vto3MljH/DEbxIWwYhwEdfwyhBxz9XvhuKAVghzB/2swuhT6AIebjMRgH/m9fL3aj7QKcO9vZzm5lr6dnMdYIkW1WCsksSD9HkSx2lRECbML0LAVI/m9/GueWOx0OWq2YdUrQjZIJLJhzwUZvVUpTDowRAYul1yixqwq2yAcpUl9J6GHVI1BWWUYFSu4cee5jKQBAiwXzIKzrgLR0uAjKUv5dPgxw2dkkFLu5CkbKMnb9nTRie1RAXzAZsACCrAHrbFBAsQ5IffPMB2JFzNhOCpBz9YVfxO5N+I0sAcq9CWi9Zq5QGa9ZCVQNpz3z1L+BqzdyzOY5p2Dl95qZtpOuh53koUIVgJkV6GYZMklJliXs/pSDq3k28DJtnqI7mSF1HJx237nyzxIs7itMHwh2ATCFBtU9Vne5vSUR+oJT2Ku7wpDOwKziwkA3OZb3eZyO0oTLzKV61Fl3PEW3l6J8Vnpk7fpOietvGNz5Tuq9m/VphsJYWMc23jsu0vooQbJOUQBY33X3grEwP7y9v/BaThYD3oQRXsDv8zwOTs9AbTiNvl5vcjtYO5gohGfBdp2nsrPGAtV64zy87m48FBsAbN2A5vzAmaYFHHUc2pY1SiOX2K7XDovBAcOYj8Lzh46RlnXtjy/nIPd9AKG5/jQtVyeOcAm0WHldVIFc277nSdcFkLOz5YbmJ6zlbTEeRLAZxsKugkanaJZSb2DqIWkQEXHfJWYxX8E4LdnBOV21JXXhXigfrVnpXTG1njsglFKgxQrU9TAR87i6XiGNxhFU8QTRdUDdDmMWXYdEKb9NHmPTdtj/MWuI8gYLmzPce+K0TpOLCknOnJiqc7GFXMGkhHTeI322wt6HaRgbF0fz15UIyfkSumLuCsmw5U9XOPyjfaQXgc+iMBbJ+dLLMCbCQr7OoJrAOwrwkkU1X3I+C1IEOxI84LqMFzjISIOUi3U2YwQDL8YXA23CrzfMcRoMOCEUDSj5PYBLKaa/F8AUwMxfjvfCxnwHUuymIor8mLMgpvYngvBiCH38oFBtoLUSxsW3q4uKnpQKBMNZwkLJgKfw53S1GpaeC2GvcqAxCfTKPkko4vJ9cVqlsbwBEbFHF52TjAHZhPd3D4rJWUYg1qIF4Auz/HcAB/+cdILSUT/leDGcXr6LdVeTMJ5dSSGgasBBRa29GphOg/aoVworFPqUoBoLm2rPlen5LbQeyBkg0TCZ9shMALCpZp3VSOvUZqx3K9sE9i2fOk3832TxQhwtr+VkAeDlA1NjLY6bjvtZtU5vOpc/zTC4JsG2OKMz0Dp92Ta8gN2YIdsWsBOPQIKFo76O+Tj8bz5LFeS2APC2wLAEOQE3sUdt3gi24sV4Sra2C8MAooxJdNgNrVHL35P7LY2bEHvKn9I+/r0ZbbNb2/Cy9vpOFi9bchu9qeV4/o09OM/QsyDl1uGyzlX8ht4sOuM36eBNq4KSGOnwprZwb+j4hpLSaTl+3F/Fv98gkIk9EOmjL37b9CD8byKziQ7tUsETGKioZ05NPCpHt8rFVW7wLDZU1ImC2phsk3ZpDWgz/H+8T6I5jTs6n8nUBvOUJQISFTyFyLOA1qwvEvdTK5Bxn3FftGIvJFZOA3uIXRE8C1ZgZw9HvIgkVQyOijyLrmAxIN0QbB55FsKwpQjxfWdT9oIoiseYVKMrnSfj7p0+VUhS9kLIBo9CzmsTFTwLY19IkWyXDdnZznZ2K3s9PYuNOMJoG0IW5MZsiDBrgwVdKHWszqMSbxtTojhCG4o4HpkZPN1c++cZsK4H7iQlGqbIAUd2I1kBaJdViJclacqeg7xNo1JsuN+SwNejEmszKcIxXDvjc4l3IAzYvh/ObJl55CCMYY8mSwfbu70UqWSTpDzaWv4+Imrx5fBEw/W+lHlPctBV4tsOAGZSQDVtIOydFAz/JuV/ZyYZlFyfqES+PkyQP8n4zSul10ToiwTpquY+iIdFXNrty77dNbOTHFgr2CLl4KmMS5Zy5uRSMjmhenR9SuhnYRz6QkNVGdZHLk5QZ+hKDbIW1bGLWZSErgCs0kjnKapTCtdZq+H9RIRulqHdT5Hmmc/kNQcpVm936KepXwbVRwn0OtvwKOpDDd0o6HWO+iioqNvkyxizGFSdmuHf422A53wcoD2FjQoID7FkQ4RDMqoqHLBJu99QnnvRYz6m4jSqLBWsG9LOVWDG2QFjmMS2d+eXm7FtQY08oK7is22ZQl8Yk2L9UCf/ByfyS9JfefDleSgKToX2JvBceI1Tx9/hJhFVFDxZdia0q+89Yxi1oQ26dlkaIlAdMUW3HcsfbGOM7vowFlHWyU/OWcpLsUTBHsy8TKDVBCpyqLLw7fJtabvBMkrXhtGa0WmtJlDioNNtXEkKUNNBV5GCWppwKhbA+s1ZyBq0PUyR8fo/qujtyxTp0SGSJXjcwBke+U1S832j6h7aTV6yjU9ISCrLSmGLaAxj9m3fWAIstxGnTjagMUjmKVSUtUnWKVSzGenXjcLyTY3ySRCNZkKLzVPdZK/PZBGnFc3m3xupy7YDTM8K6xIpjmpEfIm1/K5aD1KiW4/ppAMBhDLuroO9vHaK4QFjIJDl+MGJU5umaT1Hhe0N1HzELuXSsbbr/KdvR9cBi5C+9OlZYwfrSrNcsVbrchWwE03DE4DICTj4t/BQsHyeO26U1pSUJgCkZ6tQZBaPz3rtJR7HFkO4pd/qSoXS7roGa74WzF4mqdO+h53PuZjOTSxKK8Dpocb8HeXjNeh6WCpOWoHWLUPn49QpOC2b9CEVTdcL6LYDuh7lqva4EmstdJpCTUtYt00ZA3WlYC6vsP9hx+xUAGAMdJqA5itMHjLmJblYIVnwo6ZanoL6TMFkCtlli/R8hf0PszBOWwiE07MF9CIDrhf+HsynBQ5+cMCSk84KsASlFs/PyTjqdY7yiUL6ZI6pTGzWQrU/C6nT5zFlaQ074jsYHEPo6pV7IJycn4CtcH29nSlLs5iR1HVgWYGKHLSIKPGBAJqKI9URaIoWiwFQKgZT+fasVsyZoJqgd+HazscfRcHzjI8j7v9qxd5F04Lc8oQishtY68ForoMBFDU4bj7Y3tyZILss2JWPQWAAaDF8WP13EYhM+m1nE4818QA1AYUJNsVR6MXAMrM/Aa00qA6eAABUdwvM5tPBea0m9NMcadsxCOxZGEe7N0F3UHLBHwAqCz523cFMcmiBZlvLy5CTKVKHNTF7U0AT6CLB9TsJ8jMH0uoNTKaRAli9KaAsoJ/weVdv8GeXE/qCUE4UptZ6ScHZ75ZbPYvuaIJ2L8XksvQvsfqNCa7eBU6+F/q8vluiADZSpvVRAqsJ085g7cBisID5/u3DlrsA5852trNb2WvpWXwhJkuOW+bcN4rAPu2Y8f9vOs/z/n9bGxeCbcF48H4jr8TJGW5lIZNj+E/41ONtjj1oz01tHR9iXAg1OM7231C/ZX9DHEe4AY9B2/or27dhSeRc1vqvyYTjeOxEVBzGWAg5Bm9TPWCMdb+Njn0jxiUcN/TNgvoRnkOOF7XNn5ekX/F4bT/dNvtyTxafBtwaKTUxboE28Qhjc/TqA9zDNsyHVhjjHkgrmFSWPxRQhopRd7GRjvLtPu8etX0b8s7RyPv/+jabzTaOKOKlmtWmOlIeC/gGq2OchWAh1PB8WgWcwE3jIX+D19NjomOrR3GQhIWZuE5GkJ8qoDSj8e0L8mt0b8rhCpTa+M6mGiZR0BSuwwaFv4yRIpgkoFDlWLY36CbuOwCkLEzG4yLYCePiE0BQNe9zoJsQuoK/6ybR2Gy5tjZheDiIfBDc5ArdzMCkoV9doWDScL5ePnMC9RZWu+MAII0XWlu8EnwWRPQUwBLA2fP2/ZLZHez6/LNgr3Kfv2qtPb3Njq/EZAEARPTPrLXf/mm34ydpuz7/bNiXpc+7AOfOdrazW9lustjZznZ2K3uVJovf/Gk34Kdguz7/bNiXos+vTMxiZzvb2attr5JnsbOd7ewVtt1ksbOd7exWtpssdraznd3KdpPFzna2s1vZbrLY2c52div7l2rRvx1AsB4bAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f24bcb940b8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of walk kernel up to 8 of size 183 built in 232.24490237236023 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'n': 8.0} is: \n",
-      "[[2.385000e+03 3.060000e+02 4.000000e+00 ... 2.000000e+01 2.000000e+01\n",
-      "  2.000000e+01]\n",
-      " [3.060000e+02 9.200000e+02 4.000000e+00 ... 2.000000e+01 2.000000e+01\n",
-      "  2.000000e+01]\n",
-      " [4.000000e+00 4.000000e+00 2.385000e+03 ... 2.401000e+03 2.401000e+03\n",
-      "  2.401000e+03]\n",
-      " ...\n",
-      " [2.000000e+01 2.000000e+01 2.401000e+03 ... 2.290957e+06 2.279257e+06\n",
-      "  2.423083e+06]\n",
-      " [2.000000e+01 2.000000e+01 2.401000e+03 ... 2.279257e+06 2.279151e+06\n",
-      "  2.415007e+06]\n",
-      " [2.000000e+01 2.000000e+01 2.401000e+03 ... 2.423083e+06 2.415007e+06\n",
-      "  2.611143e+06]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f24bcb3f358>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of walk kernel up to 9 of size 183 built in 725.239883184433 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'n': 9.0} is: \n",
-      "[[4.433000e+03 4.340000e+02 4.000000e+00 ... 2.000000e+01 2.000000e+01\n",
-      "  2.000000e+01]\n",
-      " [4.340000e+02 1.496000e+03 4.000000e+00 ... 2.000000e+01 2.000000e+01\n",
-      "  2.000000e+01]\n",
-      " [4.000000e+00 4.000000e+00 4.433000e+03 ... 4.449000e+03 4.449000e+03\n",
-      "  4.449000e+03]\n",
-      " ...\n",
-      " [2.000000e+01 2.000000e+01 4.449000e+03 ... 7.557901e+06 7.407113e+06\n",
-      "  8.335467e+06]\n",
-      " [2.000000e+01 2.000000e+01 4.449000e+03 ... 7.407113e+06 7.290473e+06\n",
-      "  8.182755e+06]\n",
-      " [2.000000e+01 2.000000e+01 4.449000e+03 ... 8.335467e+06 8.182755e+06\n",
-      "  9.406663e+06]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2502f6eda0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " --- kernel matrix of walk kernel up to 10 of size 183 built in 2509.266710996628 seconds ---\n",
-      "\n",
-      "gram matrix with parameters {'n': 10.0} is: \n",
-      "[[9.5530000e+03 6.2600000e+02 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [6.2600000e+02 2.4280000e+03 4.0000000e+00 ... 2.0000000e+01\n",
-      "  2.0000000e+01 2.0000000e+01]\n",
-      " [4.0000000e+00 4.0000000e+00 9.5530000e+03 ... 9.5690000e+03\n",
-      "  9.5690000e+03 9.5690000e+03]\n",
-      " ...\n",
-      " [2.0000000e+01 2.0000000e+01 9.5690000e+03 ... 2.6862605e+07\n",
-      "  2.6989945e+07 2.9874139e+07]\n",
-      " [2.0000000e+01 2.0000000e+01 9.5690000e+03 ... 2.6989945e+07\n",
-      "  2.7302473e+07 3.0127539e+07]\n",
-      " [2.0000000e+01 2.0000000e+01 9.5690000e+03 ... 2.9874139e+07\n",
-      "  3.0127539e+07 3.4034389e+07]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
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6U1yOFsiGjFfCrsiLBNNU14KzSq7Nj6fLAXFbR4JqNsUb1puuLSlsDS8BHy1Yf3i0jKRWxcx2vr4smFn+rz289831AGCrbdN77ScTEHOoZeOle+zAiPeWXFzHprIFRjbl1XE3NgX7rT2uW/49wdJYScJS1ofoTF/eU9eRZqEcdR+jvy/tT47p3Hfi9NQopEV6vY7C3+l9sN8pc+e/Fza/67ivzkWLqbno5ppa+4gorr39+emc5xUrHVnn5zQhotcT0W8R0SeJ6BNE9AO6/SYRfZiIPqX/39DtREQ/q63u/4iIvjoZ6216/KeI6G3J9q8hoj/Wc36W9MaeZY5VcrUspDZgcQ1F0+DmyYvw5uyMwaiioCwDV6W4MWYVMYtpr24LIKZ8SBnP5yFVTMOhbDs+BuVSlR4q4LNMzfwMcHks29D1Ua+An87iGlo1VcG90gC7Gw5kTbW5kS64V7S7Az4eS9i0EDeSyrKjHMfB9Qpx8zIXHmKez4ObFJIKdS0B9fk8uqc6nx3r9nbhx5OoCKyebVHKvVc30o1GQK8AHRyFVHuwZnWNlGXxnui99pMJ3Be9Bnz/QO5dnoPnC7jdHblX6orTYADkmXyuZSWu4c3r4M9JRy7SrrHZ/hDIc/ijY3BZwV2/Bn7mCbgXbokr2u+BZ7NwfSACFQXYe2A6A4aD4LLixVO/kg25QD6kCsAPMvPvE9EegI8T0YcB/EMAv8nM7yKiHwbwwwB+CMC3AXiT/rwZwM8BeDMR3QTwowC+FuJVfpyIPsDM9/WY7wPwuxC+/LcA+A865tpznHQRV0shtWUNpdTAj5iJTRGR28hGq6tkrtSSu+S5OV7dLLUwpYC6llgDgEB90VXvVje3c10DFTVdpwZnUFKjlqwhjSFxrbAdZpC5HMwgcx2ZG1gdw9jYGMwxfsOeQeqPsc3lWeIxntWlk7GZGcQMeA+eL+RYIom71LLd7km4nEpjVHovWO9xGkMK97uumwms6SwoavIMlCV4sQAvShAl5SGmRDwDZQWazOIc6h7yogRqL3OyB+ZzuKMpuKzQqPczpa/uX4ghTSXjxxtaTcxA6S9GITHzi1B1yMxHRPSnkA7SzwL4Rj3sFwH8NkRZPAvgfSwX+BEiuk5Ez+ixH2bmewCgSu0tRPTbAPaZ+SO6/X0AvgOikDaaQ9faKVdTIRmP0ToWUsp7k2Ug0uBrpeOQxmsSICJlGdgCygmYzwLDQYlkWbA8ZL9aE71CvvQW6La1WLEn6uaDkgTJKc9DOQJXPlof4boNAKjbigKEMsR6QqDde6Dfl3WpVRMUqFozth5yXgK3dd3sSJJYPZTnYL2GENBlasxHRS6WwqAfz7V7Vnu1FCUwzEygXiFWjD7QDQvJ7plaSOnaeLEA7+2AZnNRLHkOAmQsohAcp0FfAtusyhMA745Ad8WKZIhyoV4hVtZiIZ9Hvw9/bQd0PJFxc/2sMq19dLomU0aphbSBiMu29jlPEtHHkr/frd2fl4SI3gDgr0EsmacTBfASgKf196529687ZfvnO7bjDHNcTYW0hD1qWxtr4I1S6ll7o3Kl7psjCd7amArUC3w+LdzREm1FXTdcP1tBfaAI37zQ7IxkoWBkZEAnhojLRZgzrCGdk5fX5Y+Pm2Okf0wmMUBsmSxdF4CYtSpZ3BlyEf1sazOwYbKO9DPxybhBjo50omWmATCLcoQGv4/HYgX5urscBAAmWFpD/dzzzcA5+zhvKq1qfzo8lM11LRYQALQwTfWdO8Dde8trX1qc3m0d8yyyAVL7DjN/7WkHEdEugF8D8I+Z+TCNnzEzk7kHD0nOO8flVEirMmeNsgara6Lm321JShLkVArB1vCmT6EAJ67rhKBxeoylwYtc1uxckqWKDxE3KtaTa9wgi9go7EwfPnPJ1L0IdCP6JqdeLyprzwBiuh9AzKSdwodEWRYDxDpHyGyp9QTvxS3S++L6/eh2OgfM5uBVD316Xckast0d+OlMPsdQ5JqwQ5rFYhZmUYAXC7i9XfB8IfdA1+hbWTbq9eBGo5jx9D6OGz6WCF84Ox/Sxab9iaiAKKN/zcz/Vje/bG6SumS3dPuqdvcvILpftv23dfsXdxx/ljlWyuXMsqUp5fZ25maZwWJxCpeOb/xwLWlkXixCYNa2n76u1jgaU5IYjP5dlSEW4WdzmWM6BS8W8rfNv858a0hjfltDXWsci0OhqAWkua7hFyX8dBbXV5Xx/LJqxq3Wmd/ODXNofKWswLN5TJvbfZnOZN6Fxn3OcC+4qsKYlhjgWqEB6gYzs7qWEmOCZ/B8AZ7N4ccaI+pKbth9W5RyjMWXPMf7Wp+gQNcWcdnW+Tl1JDGFfgHAnzLzTye7PgDAMmVvA/Dvku3fo5mwrwdwoG7XhwB8CxHd0GzZtwD4kO47JKKv17m+pzXWJnOslMtpIV2kdFoXCSbnrGMRNRVhQsyWMiIG66uj60Z3LVv7uFPW2FDGaYAciAChlgGZWBxL+Cg79qS6vEa9XHvOdN46WpUJeyZlNm8dA/snYsmWFZY3sn5A4oDskV6vTF8HTFLAJk1TS8tLfHGJ5L8Ej5eTCY3rAuKL8xy66QJLR/46gO8G8MdE9Ie67UcAvAvArxDR2wF8FsB36b4PAvh2AM9BnOLvBQBmvkdEPwHgo3rcj1uAG8D/DOC9AIaQYPZ/0O0bzXGSXE2FtIlbc0JF/VKWbZ15U2m5g3F4dXt8Euh2CsRrV/Of02U7cQ0pzWpC72rrIGd/L7uiIcN4KoVtgmlKAIkwVLrtq5u1auQsgeC0FGQzl80N+tG6SWEHqYLtAEYG9Lq51Y7AyJouW17Ican1ZNeTusSJux9kE5eNcWF92Zj5vwArtds3dxzPAN65Yqz3AHhPx/aPAfjKju13N51jlVxuhbTqQTyp2t3EHprOh1tRyKvoccPfLeqPpfmaD4mNH9DNzN1xIgAhS9guKgXQ6BKSHpvOYw9HF6WHnhItBzTpXZmxVFHfXntKf4KmkrU1RvfVBqmTXYkFFObV8bzhqkhqx5JSGgDNzGJyu4LyU2R2WIsXl43a3NeewZAUfyiZWSwaSQH2CNm7EA9LXUGkn4Ven/OAdxKcT7Ba2NDiZhAq3/1CebXK5VZIZ5G2Imq9zcNDtso0Sgjf5Yuo25ljt9j02CKmogP4sdeTbfN5nKsD1Gn1YyHt32IqBNCEHuj6A9jTMlYpWFOZDFMAI4D40Fj8qh2kTYCbQJLhTAPWtReIgO7juvUQ67FuZygB5/CRSGDfMo68iDVkIaicZTEoblAJxQtRniuEQuvxqgpu/wZ4PA6fMVeV1NBZzRkg6XxT3pXEi2g0kixaeu39vqxjPheraTiEu34tZNrivTCgp4sBcyB8B0AOuIeNZFvt35THRyGtcnVMCcEeOjRxPO1hQvlBvfymNpeghRsCIA+CKYIUvW0Kpa0MLdPHTZwUsgzkdCyvmaM6WinsXWNdKT7IxgjbLJOGaAUYwHHJGrRrM8WVZYAht4Em3kn3geT4tjJDvw8qm9anYJSaKHnKc0G7LyTrhaIQPFNARKvbVeQhUwZA1rUzBMpFY82CQ1oE7BP1+6KcMgfMdc6dIXC3GSSW4loHqiowakFm741AB5rOHw4Eb5QUHlMREeqkTQs6S1ROkIvOsj0O8vgopFVB2DQjp3ilk1LMYgGJBSHZm2hpxcLXOF5aWmKpcj+ZLM25RLjm62AphGMXi1hKoorPL8pwDaFDa3JemMvWlWCj6qQs5bTuKnZtNnbMXOnDm1ht3BrXRgtgxsViOYg/RbSidH5vOCmvsRhLozdacVcxG6pdQgCgfvHlJcZIXpRNly2trdNsIE0mS1lZr/gliwf5BwegyTS03KbJpHE9oU4xE7pbjDuwWGvKlsK2KY+PQjKLKKUMAZr0IwnFRifZmsUoFNfiegX8PD781Ot11p4BkForpclwo5FsG49jPVzq1mjMxOrHUuS31a4FbE2RxwfD+o8FgnsveJkqSdWbhVRVcKNRUFjBQqq6U912beZ+pOuwceF9A9MTEN9td29vF3w8bo5f5BJMzrKwJjcayfUdj8V9y3OxNPo9KT8xa8koSgohUOPZXGrZHhwECynFGK2ykHg2B13bQ/W5JhTG7e0JUtvu1XAAvOYJZJ9/SQ4YKpq8bSENB+AHh4IIN3f8C8tfq5WyZuHsq0keH4UUAHF1999Yw0Ky9K/RUMybAemLtpDa4zcwNTZmgkJvWEiplZFe70VbSHZAmukyXJHhfGwMO/QsFpJlsQDQdIrOriPWR62uwRdoIdUHhzHLBoDm87UspMAZdXy2wLSkV7YKKZXHRyFdVVkXstBuZfQopIta9mHP94pM05HpXOc8oyg5h2wtpKZcGYW0Fqc2EB7wzhq3k8B+ybnh93RXF6f2KhDjOrCE9rzh+FPqptL1dNXwNebeAGS1tPbWOho4IP297R7b7pM+p3bTgsbfCS6qfR9CnSGa2cP0kFAHeML0XST/CT2NcWqfRPIfM695jDmeQRhAdUHV/o+LXBmFFNKurdS57OQlS8O+nOHBhWZTtMbJh5R8s2aL8jzEJFIuIi4lNiSlBHVI0VuKvxFD2t0BIK6AGw4D/Wqo4i8XsZ11wi5JRS496yeTZhyr3cM+aeWTXb8WXBUAsTp+UcLt7wnNK3OIdXFZhXNTN8QNpGmAHUdZprxMlkLvaZmHhxsOpPyjKuF2dpZjSNf2wUdHTZeJKNSQeQ0Cu90doFfA33sQuKUCiNGUWpZJTGkyDXGw+niM7Cv+EnDrHsAKQ5jNQNevgY03yXvwzjAwDtBsAR5PwE/dBH/qMzK2wgrc3i6oKOAPDoUe93WvRfX6J5H9mVQ50KAvMawAcnVAvwdUNXg6DfxXyBzw/HrfZwCBoG0rUa6MQuqUtlJK/7dD2txBJ4HXWOvAjOsnzbIBQRkB+jBXrRhGKcqFF2XkQ7L57TxLubP0om/Qy5YVvI2tYL9Qs4VoOaSxE57Nm3xInkMxKE+m8cFexPuxhC5GEjOy6v7QLFHHtXiRZ/hQA6jXmtVhPwCp4F+Uy+5lXcesHXuBRVgtodW0eRZeoZRyxWoPkwJluncQ42cGJTg6bs5blhGtXVXAooS7f4g65UPyTu5Ttghz8NEx8pcLye4xBwxT4AgnivTAizLWuZ3BfdvGkJpytRTSOu7P0jlJrVVH3daJ57SOSx8Iq1Mz0i55yBMlFFDE3WturCV1kxIlIIhqbu43pHlYk6KlAzAyIqcDv08anO4qZGUPsFpflK7LB4wUoY7Ks7HGZD6n16sPtgEiQ7W8XUta80dJC2tzfWo0r0cVPSU1ZDybR2XLWuw6m4vyMjJ+Vu4r486uqkg1ktx/LiuQ983jEmXO3jeaB7CxN1ghsRHPuQ3dL97GkNpytRTSBUuoZVszUBxKCDr4mJfoSFJ+545gcGfB7Tmkc36nGS3vQk1XAH121LJtyqWtJ8VfidCA1TiHBv1Ku+ZNjznTvXAUgYiB/9ph5UvLJccC6i57rApiE5EwXiZ/h64jFyRbYOSynEshEdHzAI4gUb2Kmb9WOXl/GcAbIB71dykf7/mlC4192ikGsrMyDyvCTF2C0MrZCj5XcGrneaBvNbwS5bmURczmEm+pKuH7UZcvgOdUEQQmSHKgggKeCIi4Jk45tYs8AiGtdCTh1KZBX+hb9b4QkSCa6xo0GgKTKZBJbIyAhgvYuE95LqUhoQyCGnVadu1WkgJ12wLnEytqGxIb4vGkoZQJCLgmKdFwcP0+0JdiVyqowRhp7nAXpzbXNXDjmlDXAkCeA7MZ3P5eLNexe2Nsj1UtJHU3rwPWPklT9244ENZJ5dSmnR34p2+CKnHZqSgE32RKzWWgPAN7D5rPhZnT+Jea8KtTZauQmnIRFtI3MXNaHLSK8Pv8kpZdtDNI7YC3SVIBTrk+PAbs65rCgqtVqTSlSV2ZBrADt3Keg0Yj+aKWpQQ/x15KDQDg+FiUg1G3sg/0uUaS5oFYBtIrQKMRyHp9sZcgdwJ6RF3LukwhjYbA3Ak2iJRSdjgA5nPQ/l58sK28YT5v4ncglhEN+sBsHoLaKHpBydj5mM1U0Y2C22T0r6i9/M8efPOa8Gvb5+KcKIbjsQAK51JtT6Oh3KvYAPPwAAAgAElEQVSjI7m3w4GsN88DTzUKucfOs+yH4ITKZ66jV1by2RY54Aj+iX3hwlba2np/CC4y+NwhG5fIHmRYPLOP/PN6TXb9e3vgQQ9uUcrncWMf4zfuYe+BKC7eGYKOJkG5cebgB32hBj6agPdGgGf4It+I5J9BqLdZtoY8jLvxLIToG/r/dzyEOUTWwIxsWl+0kTjXGciktqlPbvP4wqayjrW4zr0gdz78T6PdEnVed2MdK445VewU1xqrJdyai1M3Dzh57lXYL6ILe3I8aK2fV4uc10JiAP9JOXT/LyUdX0X4fX5pB5tbHDmN/1VCI0VyEbvSwOr4RqYu1pOxVKwnx8rfPrhsPJtLJgealZpq/Zmm2kEu8HBbYDZwVNcebAhgC/JOZ1LPVVYh6+UnkxhMtwB1UknPB4cxYAyAXQUy6+/OvZAtC8WuFpDOssgz5vVa6zpwbweXM1DaLiL/jyHKfS2ulN2/LBMX56VaUM5WFW8slhaM1vX6o2PQfBGZG7XafqlzrXUYsXtZ1+g99zL8odSgUSadQ+zeBarc+wUyc/OYwfM5+mWFWgPukhBg+Lv3Gp1rcesO9qpaSlMA4Hgs7a0CNa+49VD2TTo+DtxKmwhvg9pLcl6F9A3M/AIRvQbAh4nov6U7TyL8JqJ3AHgHAAwwOucysNJlswp/IImTJJ1AGgFWil00eOGb8RuONWQWDKbMiasDgKdKT+I5unYz6dVmfNIUKuVrDcpaTEpjHoZD0jgXl1UYU5Yq1f6CQ1I3b9AHUtpZrY7n2oN2RtKXjdQl86yKxTeyf4apYiBU1Dsi+KSTRsBk1epGeinBoTxXRoPk2N2dqFhc4h5pTCowEPR6sq7JBJT1TsQh2ecHSEmMv7Ef2jxRLhQotL/XqDnjYV/cNyItO3HwN/dAt++EADiRuI5UFHLfFwvQzg7KL7qGYjKV9Qz6wEQxWcwNHBLaOKQNo6W8VUgNOZdCYuYX9P9bRPTrAL4Oqwm/2+e+G8C7AWCfbp4t3bQuDkktpJRnCIAqo2Sb4ZACxqZVu9au0aoqiRkBMfXOXt60nDQOSPuMJZaKN+vIEMELD298RVZPt8DJ1f7tttV1TFH7g0NJuaslEPBJFoxW0jOrpAf7wKYYub9VyYRebB5+4hs4JHZRech8DyIGSJVVoBwhyY4xtNOJQiR8OYe1pGagqYSVizy0rPY16KXboYCXNSZIaZExABxmIRYnn/8CVNXwzKIgPYMdwAdHkbmSPfz9Byi8hx8LzoknU0kcqHvHdq1lKYpfj9vc9dwCI9tyZoVERDsAnDal24GQgf84IuH3u9Ak/D6/pARlVdWo5F9lITntnwVA3mQaFK4PytixwsjYmELVuZ9MGtXyYNbOqBEV7fp9CcoSifvR64GnU7gnbgLeo759R9Dd06lkkxYl3ECq96nfh7OMkwW1+33QaAR/eCjWwnzeXENCvOaVnCx74oYQ1ye8R9RXHqQb14AHRyBfy7Uzg2czqa5PrERCFrq+0qAPIzXj8bgR1GYLau/sgMdj+Nkcbn9Xg9q1BKyZ4V9zA+7uYQhmE3MMghcF/P0HIOfgblyXPmmffxEuGzSC2mgFtfngMAS1/d17mP/VN2Dw6dvy0fQKuKOxZMaOp8F19NdGqPrSudbNK2QPJpi//jr6H/1UQI9TlgmyfNBD9vId+Pkc9PrX4uCvPIH9/3pb1j3owx1PwHkG8gzOM/CwB1pUcElQm4sc+OPNvtJbC6kp57GQngbw6xo/yAH8EjP/RyL6KLoJvy9GDCy4ySmpf+8Td+UsOCA732k8ARKfCFaOWiIR1ChWCSWAwCYY8nzCNq736oZYtw2zihSkmcahgCZ4Mw6m1wasHUcNXT4YbBgdj4jXsYSeWYkBG+XR1c12XaEUMGr3n1kUhhXf299Oj/ceYLOaXbCIly6VGeQBsnuYjJ3+fV7Z4pCWhdr9ph6F7NNNfjMtcYQvF9Q2ilDVpO/3l1yr5iAdYDzFGqVcQwA6C0U7x7LxgKa7BMQgsGfpew+EuAkRNevS1ikWPk0si9febHVviQVo66JCa/DMjVRXNA3Krr22pMlAm3ebsixSf1Taxdez4H4SF9JaUm902UWvUb+33DJLsV6t+xDmzrLonrYLdV0WuvACSMjiWgDOju/Lb/Cvfnydho4AsPOmZ/gv/+z/tNb1/v63/29rj3uV5XIitVdRcjS6kGpNmCGnV1S2B1I2R6C8j8DZXEqxbuMLa1/iFcBINxw2LItAu0okpn5CjGbxGBr0Jc6gCsBcSKFNzToJ33wKjEwKfO36U2BktrcnD7NZGkncxo2GwHQWeb5Z40npw6sKzQ2LQL4mGSjtJNvm2K4jV7c94EtB7Z0dibtYUNsswiQDxsygnR24PJNYl4FM1e0OLmgHMNJPJnBf+iXAHeW8Lgoprt2NTSC59qDRAFzkwTri8RT8zBOgz70o97KQ75ABI70CI7OnnoB/7VNwX7gdr302i9eSZTJnWYprmbbS3giHtHXZ2nI5FdIq6apBc3Qi+0P65gy1SXaea1o1YorXsE4hbXqPBpiSFIFdVdLzCwjZtBDUDlk9SUvLemId10rCN47dShrHWCvtBKyZksGFoDaEEJ8PypjVSiwSIhKlYm6eo7A+QimuxHwu5yRWlN2jBjVHV1DbiNKUM5trH5DsoihHct9mMyBz4V4E5Zz2jQNiIaslBJiBl2+HRgKB3VKLmuVBZ9B4LPFABZryYhHdM0cwju/68DgStDHDPziAq+vAWhkSAZb2JwI7Fy1L+ww2xm9tg9ptuZwKaRM3MsHxdIlZQO3eZGlcJS2MjS2GOhDhaclJsKZco6MG6lpI7pmDJWQPe2AA8AzKOlwNLW/hxaIZwG+7I8m6qNdrxoM0UA+vPcgUP4NMgruUKhhTLKo8mDnp2NFr4JDs2hsUur4O1w/vA8iRhgNRIk4wSEQEDKQ7ipWQgJUSxSywzNpud+CQ7J5YOn/hQbu7EuMBQkt0Gg0lW+hIFE/RA2lQ3eJ9tDuCvzOT2BILpsoN+jK24pDccCAQgnv3JZWfZQIbIB03KRtiQ9Xb9u4CgJVyCSIml0oup0I6TZJq+FMPTb7YIRaQdFQNFd6h+psRqunb1f5lO86R0HN4FpwREFpH24MCILpUNqal9xvX4BOLyC9ZI+lxYU0JFIHUWrTaPZ7OosK2gLW5HO37FCrb9X4ES43Ceu3+pBS6jdhPsP7GUbFYhbzV87GXWji7TyjjvbD1NYqR7T4lyQhm+PsPoqLPykiXEm4Rg7J5rPzXl4Z7oFAIVZbsINZbaiFNZ3B37kUuLL13rO5mbH5pVC6JS72hbF22plxqhdTZ8z3FHgFLbtWSJA0VY3sdp+dFHqFYmb/aQmpbK9ZLDICkq41UbaCxjtk8EvkDiSL1ALKLsZCsjizhnw6ukQb8mWPhqmGcGghxtXoiYJMAt56F1OgOa5bZcKhFrolbHAChGovyYiEFsGmGjSwkd/0avCKpJXiullkSp0KvSApypRCWdgRGEdDlnpctpH4f9MQN4O79+LknfEhSwJwDZXUuC0mSdVuFlMqlVkhL0gV+tH5nq5RS0nk2NvtbwQlkYydE/I1DykVLGXpwajTpQxT6zlucCakFlnABtdfMdaRYDfGijuxToiR9I0Nk5wAgh9oUWyP+Yq5m89pDjKiuJSZmYEwzVJJ1pDSwjTZIptRtTdbFxa43CcqDvQSq55q58nWT8C5dnlEHJ/vrl281rF+wD2UvDbE5NcNHVv6TWMxtauL66CjEhRqfW5tG5gL8rW0MqSlXSyGtorA9SSwzQk5KDNRlkSybQ2g3nWbuUkqSRClRoZkqS5FbDAnyBrY3O/X7sIC0xXgogyosTcPrQ3mihcQnWEg+gjPTWrYQQwIClS28l5IQbWMUAu32PCfWSYiJab3aqTEk7T5rAWIwg4YDTakv17KB5B4xE9ywJxm0w+MQl1nPQlog+6KnJTsHBBBpGkOCZ4nl5Zm6niwMCNf24V++LWNVZg32G7Vs2bV94MmbwN0H8ftisTi9x4LU7rCQNiwd8X6rkFK53AppnTdQYgEtKSsr36ghXyyXR+PIazYtzCNBWcoLWLvnpb5sRuoFc3Mots2eTECUw3uG0wcncGOnbbb1oQUrFKCDo9tqyEJQ3NrxGJbG1sVaN1dVYK9pcqKQUUK/H4LLFthmK/eommU0Ls/BXAOQmIsbDuAxW1ZuGvT1mIHLJBgNRJdmNBLXCQgKhnqDwPNUa3bM9RUVrnGlgP0xF0mvGcbzbT3wPEtnWWN/JCdUIDsjMM1ECQHSNy1TtPh0LsmN0SBkRwGAAbgbN0B5Bu+9UMUMh6hu7iK7fwAgi7VqVpeXaS0bkVCqhP2bKSQGbV22llxuhdSWtsu2blDbArBpV9j2+YZ/qesYnDakbhKY7eLABtS0V/Kz1I0y5oBQ+2VuQl0HZdQ4X/4A17ot7a2mijW4cYp/anCFcwQb4ngcXUazOCxA3Lp34dps7Bma4yY0tDyL5S6pNRcSBUdHjXsgVkgpVf0uXo+fz2ON3EJjgdZu29ZhMa+yimh0ALh3IFgnvQ9cVXCHx+JCmmJcqIutFg4vFqB7tGRxsr04dE5/PEb+Yh5gBcLpHbm62TlRhkVPEge1x1llm2RrytVSSCfJOtbUCq7s9jFWfd+IKxn3cxcHdnpegt05ba5VHN0NGEIjZhGtsyBLAWoX+a/TjiZIFF/HvQplLnbtrXWEsFWqLPV4cq1jE4UF6EOnMRviBPSarp0pZNpIM2ByLgeLUhSyHj+dxbiYungG1gzc16rAjD2A6zoSv6XXbkW5dl/LUqhhgpXno0tuopnKc6Htt0HtJdnS1T1CaXdYtb9DZ9TlE07e/5DX16Ckveg1LBG7JfGak469iKlTQr1sg7E1w3gu4TV/XiXy+FhIJ5WbJJzVFsdZavqoxxpXdgiipml+C+a2OLABSHxE+ZMCzqaqYvmJrSOBFHRydGvMKFDedvAhSfBXY0b9fuC6BhBLMKoKbncHXik6QuC1qhr0Je1rM07tgH62B055uhl1LGfxcryl9EO8aW8XOE7IpTW4zTPlQzI8mMaN/LGP1MFW5gLAas4oz4UxIS3TeeIG3P0H4XPjxQJuT0pHYCUs/X5kHJjN5b5e32+uDZAYUJ4D47HAFnZ3gKefhLN72u8Ld3aimKkoNFHAga9JYkrLX6uTZGshNeVqKaQVgWvZtwI7ZBkaaFC00qBvmsJP4kShUWRZBbSyHKPEZMASBzYAkJL7+7oO2zAeB15uW4eRq4UCVyBydPd6kikqS1UAgrYmBRVaE4G0vo1GI+HJTgnNlP+a9vdAlh1SJUnzuXAutSr97dqcHif1WT4WyCqxP0rlwtaMnev3hSKkrASbAwBPXG8AL0PjAXKCDdL4Eo1GQncyncm9HAj9iCl0AMKvPRqIm9bvS9B+sUD52hsoKo0P5hkwnsI/eUNoQnQd9e4QXDhwkSE7nsMdjFG+9gbcF15qfq32d8G9QuJZiwVw4xrGX3oNuwfKqb03anBqwzn40QBw4mLw/o7EB50DvoCNZIvUbsrVUkgnBbVXxIfSWrBAQZvWRKVjE4SSVAOvcm4cz6+gnAU0wK2IY394GM9RGlxbR0D/LhaBoK1NiRtqzxSrIxieGBDHLHbd9YeHjeAzOQplIf7WHYmrABEb1IkQj9dmDQVIu9RanVqoE2MGDg5ln2fJJLaC2q6uY0AYFtSO5TV2Hf7wEDTONDkwE6VW12rFlRFhPZlI2n02B2umMH/uC0IVLBNIULuq4BMAo+sVIaiNRQm/WCCfzgSflV77vQcSZ9Jz+aXb2J0t4O8pMPL4WFgaEh5uYQsdwI8nglnyvDHztXzEF+N+EtF7APxtALeY+St1248B+D4At/WwH2HmD+q+fwLg7ZC88//CzB/S7W8B8M8BZAD+b2Z+l25/I4D3A3gCwMcBfDczL4ioD+B9AL4GwF0Af4+Znz9pjpPkaimk0yRFWYdticumdLYCklsGRzYwN8YAkB6QuEo2XkACl1UkULNt83mDRWDJZVMsELmkLk5JzoxSVqy5KsRsxOV0MaBsx6HpsjEgtWwJcRug4Yi6jg9X+9oshV8UAAtcwYjMrPaL8hwwZZ1lTUgDIJZMWmYT8Ei+mdLX4ltaLGIhrnNyvtWaZU7umblyhnUaDRsATADRdepw2SIkYbgUg6JeISl9u4ZeAd7fAR0dxetJ5jGXjXdHoLIUy+6MvE4XaCG9F8C/gCiHVH6Gmf/3dAMRfTmAtwL4CgCvBfAbRPRluvtfAvhbAD4P4KNE9AFm/iSAf6pjvZ+I/k+Iovk5/f8+M/9FInqrHvf3Vs3BvIKWQ+XxUkhpHVrYltZdGSF/95cnpriraEmlaX9LwafjJZZZSPGnaf9Q2uKb69P0fXSdNB1vnWiBRhZKGlpyOC+MMZ83rDYrGmbP8MfjBmVuuMauLFuZXLONw0k3V1eFEpHQ8tqz3Ctbp1lwB4dL2SdDRov1qWPO55GBUzFOoZp+sRBrTOdMAZ0AwHfvRytMs2w+qcoHxIJtZ9mcwR7StY0nAQwKZuHVZhZ6YEAss1aWjbIMVHvweLJUPL2RXJBCYubfIaI3rHn4swDez8xzAJ8houcg9NMA8BwzfxoAiOj9AJ4loj8F8DcB/AM95hcB/BhEIT2rvwPArwL4FyQfwKo5/t+TFna1FNJJMaRwzOr6s0BKlmWx1gpoxpC0Ps0vNO6TAAiNyyi4R0rKD4jLQ3kOv4DQawCoDw9jcDixIriqlOen18AZUZ6DBv3A/cNa7xUI1sgBWpdmRG9uNJI1lcYf5OKc1/aF+tW5aCFVVSxtSSTwNOlxNOiHILTdO64qsZB6hewzcGeWCYuAHuuuX5N5w+AE5HkERmpQ2Y1GQK+Af3CgMSTpdYaiJxaJWkhU9AR42uuJyzeeAK97Gu72vfiZz+egG9fAk25gpJvOweMp8OR10KcSyhYAtLeniPEjAYXeuI7q9U8h+7MXZP9wKEH1FjCSe4UwCIwG8fu5UVD7FQFGfj8RfQ+AjwH4QW3a+joAH0mO+bxuA4A/b21/M8RNe8AcCqXS419n5zBzRUQHevxJc6yUq6WQTowhmXVTN/5ucvfEeq3O85ULiWspzZAHNx4TWiqF8XyIubBZCb5ucBSF2FEHMJJbioE9S2DVgIBWWmIWUool0utcimvVLoAN6cFBVFRGoJ+cm4pdW1C2QfEqT1Kyn4xhwEjojOROLQhvcbBUgoVEjbVjqpaJWkviBs6iRQeEvwPf1GKB7IWXlywku3chM3iYBQvJm4WkWKXGtR8eRitKLb1ssZCSFgA0nnRaSAGFP96wXW0q61tITxLRx5K/362NMk6SnwPwEzrLTwD4ZwDWo6h8RHK1FNLDllWYklWQgoeyBqmvs5KXUPpi+9irAnillkPLf5PDiax455tQlEMrUB52276HJJv0VpPuKeeQzYCRdzalsGXml+13Ivp5AP9e/3wBwOuTQ79Yt2HF9rsArhNRrlZSeryN9XkiygFc0+NPmmOlPH7AyJOAaoFi5ITLNiyS0tum44WHkSgG0K2WKzkvbDtlLtLz0nkDMI9c/GmvPR0zy5J1RRxVqI1zFLbFY5fvUSgW1uPt3DCuEZVB3cIWiLNxrNF52JwWvA73Kt4nKvJ4nrbEhkEN1H2WFujNNWA4kDEVvyT92/ryu2KEaNCXQPdwEPdp55LGtWsNYbivhbY0t/EH/TCPHUu9ItCbUL8vLmcKV1hXHiIwUtuQmfwdAH+iv38AwFuJqK/ZszcB+D0AHwXwJiJ6IxH1IEHpD7AQ7/8WgO/U89+G2E3IugxB9/9nPX7VHCfK42chnWTJnFY6okFnKwEJAeBQimBlDjbHBZSOpEFx75LOtlZzRmF/SK+nb9WHVToSzq0bBcppeYudd2GlI+am6j4AaiklgX0792GUjthnsWbpiPXAO5f1fEExJCL6NwC+EeLafR7AjwL4RiL6KshH8DyAfwQAzPwJIvoVAJ+E9IV5p2W/iOj7AXwIkvZ/DzN/Qqf4IQDvJ6KfBPAHAH5Bt/8CgH+lQet7ECV24hwnyeOjkFYFujdCap/QuRa4cKR2GiRPkdow/ukqdq5tB7UtJvUwkdq2DgABqR3S78qBfWFIbe2Hx3UdA+otpLYF0P3x+EKR2m40Ckhtruv1kdr9HvjwuInU3jScdHFZtr/fsfkXOrbZ8T8F4Kc6tn8QwAc7tn8aMROXbp8B+LubzHGSXBmFtNQSqfOgxL2y9khJANeUUBcGSU5ygVFRjo9vPyp6S+1yuFw0FJsRl/kkyBn228shIX9LqU3YO8BXzep5aLDZ1w1Dy1gN/aJszAVAFI6us07hB+1WPy2x/XYNto4QAF6UMWitnVpJWwjZMxWerUkzi7VKGvfJMwBFcFcRSkCOJHGgfEYgBzccoHr+c0uWydK96GibhQcPls6rDw5hGUPq9VDfuQvcvXeq5eMGg2ZbK7+hdmFcmIX0uMiVUUiddLaNA5pfhmX+63UmadNyJAqjxR90IZKSzLWq+sX9W+1ahozfw5Q2XqfFgnC6AX7GuVL8VYpkNpe63RL9guYWipP1lQon1MENLNgmU79CuZKrIldGIYE5Mjim/5sSabtsxqiYvMXccBB6j/nj40Brmo5lwc+uVtrZ9WvaZ15dtkFfkL8A+OBQMETjqbS3ZkZ96zayvT3BKBk2KM/h53Phbe71zt9K++nXSMo84JAyCdzO58J6aL3LBhLM5dksAP7SB8jt7oQ+clZzxkfH0dXTWjauqkYr7ez6vrhItRe3BwA//QTcnftR2arbxMdjUFGgVlcru3EdGA7gX74trq+5n3keUdhZBtrdEVyTYb7u3oP/G1+F3mfvBrcOkyn80zfhjqZSy8YMvz+ELzJw7pBNFsjujzH/kpsofu+/ydgKZHRPPwXu94Bbd+CnM2Rf9hdw9BVPYv8PXpRY4u4IdDwJaO/QSrvyIGulzQwuMuC/bvq93vD4x1yujkICGgHgxv8nnZIS4BvaFye8Yes6uiBttPGijOMBUgQ71y8pcwA58nwR35xJkNoCwuH4xDUBIIWlRrgGcWO4FZhukKgBAb/T6BumCsqNp/BmKZK6q2nvs3BbWcjT7BoAUEqKBoT2RUaWHwLQKehTye/c0VjuQZrRW2hvuoCGZ2nqqPcGC8RyEaWGBQBkHlA0NCWB9PzuVICOACjPwLMZ3OFECnUNoOm9sHdmTpDgkymKe5NwTda1mccT0KKUF1ddg8ZTDF+eCdLbrn0yC80TyDkpjalqaVBpbv0m1CXh5m9dtlSulkI6SVaxSKZZLCvLSL8EDVdJ+7dBYxatItQAUrRiWGb5olsHXYs9pZ1kw//cnM8z2DcZKK2ldFyDjwoEiG5cmsEy1knPYEiBJ2uRaigs9km5ySrX1wjK6lrKKCoDZur+qor3r0pKaLTcwxo0AgAms9A6PGSmrKQluRdcJZ1sDdekLYpC4Fv7vTVcdvZS1R9igsrOMJ1FRWjnmoXnPbgs4Y5nqLU8JfB364vGXho8myF/MBXFbyUy5QJc6cvHmkzW2kxSvztpW/G1hAF6hfBkV0UeH4V0mqwiPCOJS5x93NYbLmRi3NK2hwUqFIAeN9PSNr81b7SaMBczRaihGCK/fN5mC5Dz0rHtfyPuhxT0Cre3C24vXNZNwrbOnO35bc400xq6EicJDzveFFPX2Pbj0Lm+c4MiZZSthdSSx0chnZT2p2hSh2p/YNnlowREaLVZSZlJaKWjDzBR7PDBrgrYFOmBpmPrtqWW39b/LA3cpuDFpAsI11GhBYK2KsaMrCurjWHtq6lIuo4Y5apfRj+Hue3+mQIrq+iGZBnIq8VkgE4DN9oaLN3e68XuHy4TMyBz4jWGhgAKvtS6s9CcwOADPrl/CSOAfaY8GgBHCpjM9X4MrCpf78ZwAM6VraCsQFWlPEat6y9yUFGAptOQ0q/2+sjvSjff0B3YYA1OeZ2MeaDfj11XNpVtDKkhV0shtUnY2n2yuk7JktS1PpRNFHXLWjHciz4AnHDnUK9QkJxuKIqA/CUjX6sqUL+n8QkNnKNMimsduEKgLhFlou5JnoMGgzC3YX4oxFMyEOoQ8AYgKOQ0qF3kgptZlBKMVZciYGWQxMYSxUQaCA6kcXku89pDOBgIpYmrJUCuvEqCDXLS1tqC2vs7oLKMlotZRZhE9kdIUgDDQaRxGQ5kzjyPCrbIYxcTu9eTCconR+gdSxEzF7lU51/bgXNOlBAQg9oZIZuWyACUT45QfCYWUgMAjUbgQQ80mQqbwd4OJs8Msf+SKDjeGcpLoh3ULjVut6fryLJmaeo6slVIDblaCgloYUv88raWhIyYoXmZJbYAyNuQWzVjpwW1U1dAi0LTuQwVjNqHOFPgAiKnlBr6xVYitTSojdmsGdROW2WvCmobsZkTV8gKYWk8jTQmtZdsosaKSEGZAACvLpTGReAojGv3igFBMNcemM1iULuqQJzAAZhBxxNwWYpiUSuTZ9Kdg1EFdgDpW1eEe2EBbsqqpUJo2w+9L/mDGXgyk89QA+TucKJgTpnTeWllJXE0ifcVD2YRqLkoBag5mYBKIXALQe1bc0AZKel4okXELljKVFbSNcaC2sauualsFVJDrpRCahScekRqEQsodlHYDrQ3GQDa3ZGHtd+P4D2zkqyoVdPxdVnBjUaoA7tkDbe/B55MA7MgjYag/T3Zf+eetGk+OARuXJMA+cEh3GgIPigFfTydwfX7qO1B7PcFNayKwe3ugPb34G/dEQjB8Rh0bR9kLaMTBHYAPT55E248jaRnRhw2nqJ6/VPIX7grVt2e0KzSRFkuLTNEBHaa9h9PBGUNAP0e3L37QNHTezcCH09A5QJ04zr4/gP4Yw+3vxfaSlv/tNmXPon+nz+QYLTxFxUZ3INjSa+/eMFfQeAAACAASURBVEvmeOIG6msjuINDsbpGw0CFS9biqCjgb+zC3boPKMSC5nPc+x+v46Z+xnU/R3a/h8mX3kT/7gy+L9be/Ik+qqGDz4Heocfw5SnufcUunvzsi9orTj5/ft1rUO30UXwG8EfHKN/wGnzhG0b44sl1AEB5Y4DenTF8T+EEvRzVXoFsXqO4M8HiyRHgAd9zm1lIW2DkklwphZTWT4X/rSRjFYVtQvHBVjKgVooEemMtGozwzPqrTSaN8fzRcehLD2ZgMo21Z1Ul43sPPDgCvMZCprPQFwxq8UipQwnM5o20vj8ei6ula+CyAh8cNkjWjHgtyJ17kto3MrNFCZpLe+v8hbvi2lkcybJ45molmSt/PJa/De18dCy8TJkiuGezYCFR7RWPVYOPjjX+5IGFdPYd/BkHzBF6wg2O+UIQ8pNZDLDfe4BM0+08m4vLZKU9ZiFlGWgyUapYUVJcVrj5Rwegl+4CAPJBH3w8xqgSoreMxHrNbw2loaNBF46nuFlZllIzc1kGeuEWikJ4mbiqUDx/C8+4p5HdOwRqj+x+Ji8TtZCyPEdR5JKdm83QezA4cwyJthZSQ66UQoogyORvIAZjV55mLo9gTyhwDPklJXfy/Enq3jspP7RdhgOqPchrGl7jLCEFbpAD9oEvui1L2Zt1s142nrmjdS2/q5tJgY/JR8WoUAFbj5TNdLf2SdeV/s7MAX/UcCWZwVXdZFFM3C85j8UtSu9F1/9pFi0ZP0hVJ/gmVQx2nmUWFVNFzLGY1lx4495OM5MG6QAiuX977jQbZ3inTWWrkBpytRSSWkOBDygEZVcHto1/GuSEVkKRzphOIze1Zd4qf3pQeyHfIcsKGQKaykrcQ2Zpq1PXoCNttW1oYubAkW0tfbiuG0FtQ0SHoHaew8jVuoLaNBgAtIhKL8skqF6rm+a9XPNwGBV3WTYyiMykrq0Gvw2mkAS10ddrc7UEzYOlVYibWPsQ9Pf7I7iqFnR2ngmg0XtgJp8BNOZFg4F07DgQgrRGUNuq8otc1r4oG0Ht+VMjDA/GYhUOeiDvUV/fhTvORIHUHv7aCPVAvuKurJERYf6aEQbPF8FqpcwJI+Sgp0RsNXhniMlrByhu74qiHvbgiCRYrp8lD3ugeSkvuTSovelXequQGnK1FJJKw5pJS0dOPin+Hh5E7t6/zho01W4c0ADkLe1b9XBmDRkQj1tv8guURvrft8Cdye9mnYTr95wANxWXtQEJGis9SJN2RVDplPwtnNg+xv2AaCFteC8CoJAj+p3sOpPvB3kGOwLVGniubX8dwJxd3xxSICd5lq+Gji3jcfMzPo9sY0gNuVoKaZXLdtIpiVtGpWbJEgWy5KqdlGUzVHQtQXDWUo+QyVJXhGezMDbXvuUm1uHhDeT15ygdYct4WZYtcdlIEdNc++iGWAEp+QZ63NwYtj5uer0hI6mW1XLpSCnXpmUf8Ax3OJF74LJIyl97QTvbZ+i9ZKjUSmRmQVq3S0eYAZrKvVariT2jd3cSSzsqoQO20hGzRh0zXJHr2ivQZIbinraVYhdfTNOpYJT0HtB4iuFLc9B0DngP573Qy6zKsulnsXHpCGPrsrXkUiukTsoRjcUAkC9H0Us6e2DpzRUUgCoQ40ymvIgYpVCtzVHhcOylFsayDh8AkJZ2AKpkROEEDqJC3S5TgOYmkaTZA4e01VQpR3e6Bj+bh0JhVnKzlM/Ij6dNxWz1cwk/NzyLMjHrQTE1Qa9XPgb/mROoQB1BmVUsc/GTaOXwbK6lFAzMFd+ziC4kW1zGeroh4n94ZnV4qtiM9xtJ3E/71Qkft7quvgZ9/mUh+4e4SlxVgbYk3IqjvFG64qsKWS3dSQLpGjP44Cg0dgB7+Hv3UZSlfI72AqtruRaLd2VZVNCWZDgLyn2rkBpyORXSSRzW5kqwliIYkvkkLgxqUa4mnTSoQSFRn+r+LfW7NzFktRKWpS2hjZtJkNIMyhSwmSpSlTZLZbvW7sR7kpLQK/4mdLnNMnFpyAfIQgjawtzXLJRVhMwdWnV0nDBpJnMGellzbYgkTtYTYjc/noqC9h40HIQiXgkGl+CqjHMkgNdG+6eUisQKcRUtzy1lFDvNFKELcUC39/sC4uSxEL6NNZuaWG/2WVpyYkkU2xX2dfB/ryPbGFJTLqdCOknaxbBr+vKpa0aQMgBLgQNo1nOtM0b7+Dr+z0Cz2NYAh8n6L4xLqBEbC4trFtNaYataSARI9q2qJChcxzEk67bBU2IWX3JeyDailGs3C9DWYjAEPT+df+3LtsJXh1AEC4pWWPjbeuUtFiHjae2cuK6jS5qOzWpdJv3WzL22NXfWwJ1FtgqpIaeqdCJ6DxHdIqI/SbbdJKIPE9Gn9P8bup2I6GeJ6Dki+iMi+uqHsupzdJ2IBa5AqF27SGmvLS08PYtJv+ncaTmIFbOuPL5j36b3I6V1TcdzyXW35mke585UXNtgEmhtD/saBb+CO1uyJld9Jil1inW91b8vShmRGqzr/LxaZJ0n5L0A3tLa9sMAfpOZ3wTgN/VvAPg2SHeBNwF4B6Qv1OaSvlG79iVWQUrP0T2Wjz9AiINwWcWuqeyxFg4pGZNbAfGAZzIrAJC38qLU/xehDKRB7n8BEtaSXqu6NJYBC/EjDWDHtSX3wGJXG96LdL7G/zaeXa8BQI3DKcEDbXzNdj0hs+nD9rjPN36E72kRrh113c0satYtp2O0ru+ihGm9n1eJnOqyrWjR+yykwwEgbXV/G9KV4FkA79M2KB8houtE9Awzv3hRCwaAWFxL0e9fUe1vxP6Admetlbx/OgWQNeIVTZL/RYy/yI2AG/RVAeqbUjvNAgjdZrEo4XZ3AAhXsxtKxb0F6KURgMR0nG5rd8L1k4msoazgesUSbzMVEYfkdndilg1oVPsHkn/vZZ2WtZvNGw8VOQrNAizu5YgUqR0r+I2gzQ0H8NMZuCql1KZd7X9tH3x43LAySLvLIsvA02koV6HBAP7uvUjyr3GhSNCmuKrJNFT718dj4I2vg3vxrn4OWSTwtywbAB72paxFs2zueAL/9E3Q//c8AlMBEdy1PVBRwB8cShPK1zyJ8n94CsWnX5I19HuBoM3WhCIXgrbpVHBSgAAjn9/gewxsXbaWnDWG9HSiZF4C8LT+Htrqqlj73CWFRETvgFhRGGC02eytrBI4wbWclGUzgjGNeyyPG/vWg7lB8g9EaywQtNU+1MkFuICyKAqIkJYxT6Y4PIO51cKorOCh1paPxavRunPBugtrMuWS4ogsizSehGwZrPtPsM4i7idACTQbJ8trWnIpRMFb99cU9QyAvQa1j8ex3s8gBGZxJLGsUE5TeyWAU/hAct8C06fGgOzzd/eO4Gd6UVYoe3gkwXLL+inw0dbP8znc/SP4gGrXGNRkCs4WMc40HqN4qSfQBUCyaUbEB0SeJ4VJBKvyLK7nViE15NxBbWZmos1vq7YBfjcA7NPN9c5vtxIK2y0j1WEhZVk4VChIKaKlE44iqcw/oQ0Sxwp5u1wqci07cMB0ChRF5KW28oyiEMpcp9ACa/ucOQBO+5+5MJ7r96XLhlpI1gYprNE7tZA0GD/oB+SzxWusTo32dqU2rRYrQ4K7ZciCGakbsZ5TljEzCMB7XrKQUHtZo2cwa6eOTB5uaFYqFOgqDokVUIhSLENMJXhC/R5oOFQeovxECwlAtJDKCv6JfaE4AaRmbjwBXdtv4JB4NBB+bcMhjXPUN/dBd+6JsrS+baOhWEh1DSwWoN1dLF57Hb35Qty1fk+ocRWHhCyTGr2yEsR/aiHdX+ubHGWrkBpy1ijry9YVU//X8u2ztc99JSTls1nafpFiboqlw7sCunSBAe42Q2WbtTGdMw1yp8HktrV41sB2eq7dg3TOtOtvus6zslR2rbk9FiXrCQyQLrJGrgpQt9fZ3n4RwhrYXuPn1SJntZCsfe67sNxW9/uJ6P0A3gzg4Fzxo3bwMIAIE5fNeqy16UdCYSUBldarpV8kXzesH3PjrC2zYVeie+Qj3iXlYVJ6DmaWeidzBwkBVuDncxmrKgHXk7nrWrqgzBBLH3ra9lktK3iWziaGn1H6kUZsqyf1eWZREFHs2tHvAUfH8ZpNcdR1JP9XcUTwVnriWdZRK2OBI6lfcxSI0gx5TpkqtiTwyjtDsVQgkAciAo0GElfKsliHp5YU1zXcaCSWUFWJxWOucJ6DRgPZbnWD8zmq3R56aokiz4Ayh98bwjGLVQTA7w3ARQafO+THC9CiRD0skC0WDcPE7e6AewVI5+TRAPMnCvSeF+XDo4ES0GlsKnPgkcQO3YED72rXkXwLjDyvnKqQVrTofReAXyGitwP4LIDv0sM/CODbATwHYALgey90te04UaqwVtGPJHGggLQOsYj0fFF0Rq4WY0EJKno6a8RVMJ/HsctK3BiNQYRh9ZiAh1FFIPGiWYjLkCOtwDcEsczNswQdbgHw2TwE4/nouNkIQKlauazg7t2HD+UVcd5GLVnr2ry5hxYfyfReWeOAECMqJZ40jXQiIS3+8h2w8RlBnjlr/0Tz2LmWj45DS2yeTmM8qlc1qHcxn8u5ZRViP73nb4MPjxounhC1zUNQOzvsKd0ugcsSPJ2hV1aoWsqYHxxERek9cPsedj8JeOOhmk7h54sG4p4OxF3n8RiY6D0+SwzpVZTSX0fWybJ1tegFgG/uOJYBvPO8i1op7UzaSYhuO0VjQwBCtXzgpG7HnhTHY+jvwL1tYxk7QIsD2+YJqPG0UNR6qVmMysjlHK3k6GZXxZ5xWQagbDQISGl5Kc+R0uoaYpq8B4pe4DMK6/Rey0GaT4JdW4gZZZkoIzuvyMHOidWkJTFgHxkG6uTYfr+BAgcgVfvaGjywCeS5bLc24nkerM7QEilzgU6XCj03K4VTezoNHNoEiacx+8i9PZBW2pxnoLncMx4NlhVHnkf+cSJQv4d6bwB3t4jXk6LnsyxyPc3nIdO6lfPL1UNqnybtgPdVkTZgb0Wc4sJjXquko4PJxXTaOGVONlAjATV3x7cuGmDaiIFtwHKQZ93Z2k1k67I15PFRSKsUUcL7Q3ke3IeuXvdm5aAo5A2fJV84zSh1kfIDCLglSmIdODqKnEppJxPlGepsGqAE/cFS6vWEdhcIXVPC+gA5HogMAFkWCfl3R6Gi3rq+gkgLZZsPUrg2I/nvS/aONB5Dg4E2wOSwL+CWjMJWj+Vruw1GAqtrg2eJeRl9cL8v1sXxWK6z1wNXtVgrlViJMKyX3Vci8HSG6qk9FFN1mfMMPJ4K1W3mYgxpfyjxniJDdjyHI0L51B7cZ5tUJzQagPs9KQpelOC9HUxfu4Pdl7Ur8d5IY3PWMcVJ95Lcwc0HEkMCwBkBn1v6Wq2WV1nAeh15fBQSsGxVUIJnASLFxglDNDrbGgL4NFJ+IGJlPEf8is2p+9v/r2waoKjikP4OWCAFgpoL6J12rl3EZgbWsLEswccT+V9OlnnKsoF9Cuu0azNubmuKYC2R5kk8TaEDQsW7iGhrA6AeHAdqEECNgEKoeSm9f/O5FDRbUH6h96DfC6hyAOCxIqppIal1IuS3j8CBF50EkHr/WICK6rJlGnMSl20BHk+Q39b0fnrtk5lQB2vbJzoaY/iFYeyOwvqZJi6bW5Tga7sC89BxzmS7bhVSQ66WQlonqN06vlGZbgFkdAe1LZ4TYk5LBbG++TAnD2Fok90mKjMAoYEtrazEgus2nnfSvbXUALEGkO0BDgoiDcrDMnlJ6UQNkNOW4WWiqFwdriFmK5PLt2uzQldtrU0B8JncQyAoa2ZqrBVA5CVPhIBmZbyunfReUB2vHfNFAHRSgt0KHU5YmhVY+++guGfz0IXW5kSWgRYS1MailPPapTHlAuytYYQD5gu4o1ksriVq8EQhU3DsdB7iTmcuJ9kqpIZcLYV0UlCbnEAA2kZSAm4M5RHGs9QOagONtH/DNWItmVACNRuPRmKuU11r2YcH7UjpCCYToR7RQHAAW87lbzccKNePrrXXE1qQg8PYNLFXCAxAg+2oxXU0ygza2RHCtJbLhtkMdOM6SFszmctG87nwGbUeSrs2Z67dcCCulLo/0EA1A6DREHws6GrXl/IMSlw2vOYJ0N0HyccmLps7HovLZlbYzo7AGuZzuZeW9u8VYGuSYGl/HEb3eDaX0o7PkVCq5BkwnoKfeULI4XQdddtlOxijfN1NuNt3mt+Ra/vist2+Jxbfkzcw/ktPYFezZ7w3gjuaLLlsnBFcXTfT/i91fXG7hbB12dpytRTSw077Ey5P2t9I+EPaPykCTni+eTxuFhhbqUVZge8/kPNxjrS/3Su7j96Dj31QgH4+l9gLc1Q0t+6ul/Yfj0P/t5D2V7oSIYxjcYuTtL+RuxWf7Uj7v4hm2v9ovJT2L6p6Oe1/cNjAR+HOfez8d5KWVgBoNltO+x+NJat3dBTbbGFD4W3avy1XRyGtkeJvHq+pbZ+4N+Y+raqeVsL/8NpKH1yXLRGqcS3UqQAE7KiukJ/NG8fY/vb/bJlxgxL4KrplnLiHLQ4lLqvQo84nTI92n0xp+uNIINZwlzruo10bJ4q94Z5WVcA+hdZPnoE6ggztf0qJy4LIOplcmF/ukzBickXR5U0Ut7iOPrxImASIWd++E7v1WtFxm/nhOEGj27XM543vBKCsm7b2Ioc/OhJL0hRNYKxMvjfkQpFxAFSexW3bWkgNuToKKXXRXKbuWeJytUW/dFT0mtX+LJzIfjqNWJ+EpTCt9k8zdPA13M5OpJ0lF2vZEKv9eVHC7e8CnrXafxC6W7Bm10JGTn9fqmXTan94RWXbg9FR7Z9d34+BZUCzdz1wVUljy6NjhFY/gATSZ/MYRLfr7vfFyrBatswF0COAWO3PJGucz4F6Abe7q9m/iP+hazJvwHYBMt90BhQ5eDwRZHtS7Q/nxFWrIxYqXM9gAB6PwzXUh8dwf+XL4F6yav9c2ABuXDux2p/GU/inrsdqf3O99/ZAvQL+/gOp9v+ip7F4w1Po/dlL8t3SJp9LtWxVDdcrmrVsn9ngOw1cmEIiovcA+NsAbjHzV+q2mwB+GcAbIDwE38XM90k+1H8OATFPAPxDZv59PedtAP5XHfYnmfkXdfvXQKiIhhAA9A9oHevGc5wkD5kx7IJlifxsjeW3qGsNyNc+P6WmDT3fW50wKFPS+oTgDXkucQ6jLnFxWxgjwc6EB9xAlUqva0BJKPiPsiyuWfeHYxvAS12v8jyT9gcT+EKu25wA+fI8lnq0r1/vDWWxfCbcK1uXbSvy5DoUuGjXnDnpTqtgQ+rpj4IgkeexlizP5cE2jmpbn84f1p5nYT9yAVLWo56MbwDFPAcPevJ7rxDFN+zBj+SHB7Kt3ukh1KjZPcvj9YEc0CtQ7uk4/Z7El4r4N3oFeNAD97UFVF9/VGFuIhdYy/ZenJO3TJXLj0LKvr4OwI8a+aIe833JeW85yxynydVSSOybqf11SM7S4G2gvjiZ0G3JzbFddn7YoFmpOqHo0HkiMb9u83757zrGhQJxm1GcJBm1lIAtHBeuSddrsRdbExDGChQfltXzSesmVXQN6lfNHgbaVluXbdPsltwTvX67ZmbBTdU12MjNLK3fyhCirmMbpLpWChJ1CW0NtZeGk7rfymeyaSmZs6rSMWpJQFS61rICzUq4aQmalqC5HOdmLQQ5IOMbYwJ7YFGimGgssaoVEqBjL0oZe16C5rLdfqc2On0d4TV/ThuG+XcA3GttfhbCVwb9/zuS7e9jkY8AuK5F8t8K4MPMfI+Z7wP4MIC36L59Zv6IVmO8rzXWJnOcKFfHZQOie3HWRpFKdB/AfkmjSCvLMOuEgY7SEeXAcYjWg5UpmPWkZQXsfQRaamAVtRbo6lqk2tzF0pGWhWRAyob15nxzXXkOYsUeORctDPbyRl/EzFVQKHOKjSuJ5HoyB/ZZzJQBTWvSOqjUtVhIWqAaLCMnFCbsvTRdnBVq0eg8lQbve4VgmvRcHvbjvchzEKRRZCg4VguJk3tNjqS4Vt1LHvQk0N/viYLOnJSeDHvwfT2nzuDqGvWoh8Lc8mT81ELiQQ+L/QLFQEtY+gXo/2/vTWMlS7LzsO9E3LhLLm+t11W9TM8GDk2yxxxxGpyBIRgECI0F/pENAYINCEMbBGiAku0f/iETsGFDsgzBmyjbsGEaHlgUINvSD8EEJZKmII0EEByKI5M9Qw5n6SF7qZra3prbzbtEHP84EXFvZr2qfu91DetVdx7gIV/evEvEzcyTJ875zvd54UtJGcg+UB5kmvnI6LII8gs6m/dhl+Ute9L22+dsv8o1nths/3w5JG+XEYqMv/whmnIdleqVhSI9sReF43qJ2keEIsO2nhyQv/jFr3eB8Txi5827vy/37kF/21WIxiKBXO8ehkjUUe/8gQ62z9ZwtTITcTcHsq77Xq/dV2KACSDrOZkgcyY/Fsaj1TFyHP/i54V7f0/RLlFlu0FEX+09/0XPKXYhuypv2WXsaVzjuXJIQe5aktE2Vpq619qOIsSbKnKpoiiCGo/AVS2tCNOpRAchMtIaBEANC9++UYPGo1jK5rYVArDZPJbd1WgI3tuW69+zoNEQbE/hXtgFHMAPj0A+EU5FDrZzSYBWFajIQYMBeDrtktbjEbC/A2Wt4H7OJlA723CBiCzPBBk8HgEepcw396GmvuM8RClbQ9BsgeUnbiD/rq9obQleSk0WMqdedz4rxLlFSpBhAbp/KNgtALw9EgR2VQnO6MGRYJy2x77topGoAcDkh/cw/o5EPUwEaIJLNZKHU7hBJpLVzHA399DsFkhPzuTejQayJEoN1MzPLzVoboxhvnccWzRoUeLe5wa4hQOAGTZPkD7IcfbaDgb3hmgLDWJgfjNBWwA2I+THjPHtHA9+LMcr3zCIdMUAmo/fRDM2GHyTwSdnmP/gAd79MxqfONsBMVC+kKG4t4TLZH+XKlQ7CXTlUNxforyZgyxgcwK+dcnP9MW/vofM/Prlzi68Zcx894K8ZXfQUVOH7V/22185Z/+rXOOJ9lw5pFi276Oj+6/1HuP2UBa3EDBhH13NvbK2z9W4cinKqY7Bs/nqNabTjhQfAM8XAsyDL2F7Clh1NAGcEzraRekpZOX1UB3jZQU07QrQErO5MDWGMbQt+GwSHSyXPgcz63BO6vAEXNWdE64bUehtGmTvnoK92KFq/b1bLjsRR+si3StPZh3HEklFjBdlBwxtW3Dpjz06jfMSChEP4lyKFtz4O1rugVJSeYIQ5nK5hCorad1ghjo8Q1rWci/CPfLL1IgJShKYuhGsUCiv1zUO3qhgvif0jIlJQNM5tr6loWYl0kQ08tLjAi7VgCaosoU+XeCGUV3V07eWmDvHSLIUfDaBqyoM3jrFrd/cg7k/AZgxmmYCuAzASK2RPUhBjQVN5hhNh4jAyMva93fJdineMiL6dQD/VS+R/QUAP8/Mx0Q0IaLPA/htAF8E8D9e5RrvNeDnyiEBkF+2kEMCOrzR4ywslcj3ZIW8SMgVBdBhiJSeeO0e6+IK42LveciHoKuwka8sRTbJp8oYKZ3xnfQPddU/It+o6vMf1gmtrEdOR2pd2K4SqPTllmxEIKXke+WpUGIFK9GCmvY5JPIOioynEA4Vu7Vq5kXMJdQt0xN/z5W/H5EZkqKT4MSPJ7wfPs+Ex1zbJeTzZr35hLK/ks/R++ZdeIo5pKfBW+Ydz18D8Dt+v7/KzCFR/nPoyv6/6v9w2Wu8lz1XDiku0QKfjsflXODAVYrTvnpE03avX5S1JFCfBkrWkExWvuyeaKCF/5LrqIAa9w3J7ouM/SIWnJHW3qF4Z6ulhA3npMEUPnkdMD+BU9qfI5T9QbSaD3ritVV3jkQDLjh96brn3IAsS4UqQAiSxDsDBZcmUFpfLocHSGc9AFYENlqcXbiu521iIrAmSUwbBU4UWMM7RcE84bxSPRFcIucNy05Wcu7ooPT7dkfyfrzvs4g9Ld4yZv4SgC+ds/2rAF47Z/vRZa/xJHu+yv7v19Z/+c/50j1RBDCifnuJ65is7iWJ+yV0ducrs/rk8bpoIvUjsLUxr/Bh945ZOWeARkRWgcACsOb8Agp9Lckcxn8uF/g5//cO7JLi4cvKLM7I+TGFfXr3g3qMCitCjH3RS/883ptAERyiwZCgj3zmiBEph/0Ayev5/Tlc19ruRyqwOiglaiTMsiTXvWgsRNne2UErsCbwVYVAn1LZ/4Niz1WEFDvm+zmkUGVb59QORhRzSAA85iX0qnnUtbOA7b7sZBKgRHxcORcQ8TkxKoDkrgiIEkhQ1LVjLCtB+4ake+hkT3NANV3EF7iYfMTF5Ev4fSL/0GQbLNFAHaItK18srSRXZLR0zod5s8cjObfSLgF2IFKxu57BoEHegRkBGZdpZM7GAx1RRYfJflkGAC7V0IA8bwVRz5kBlUsZQ6D1IAK14rApT4EsFYeTms6RJlqgAfNSyvqAtI5kPvqLPwwEVyRQiwacinpJW2i4TMGmCulZCyhJcHPddHLeTQsc7MENUqhElo+cSzKcmm4+SimBHmgAiYLNE1CiQMsGdpiBrJN81SVt01y7as+VQwLw2PL+Y5trPZBOmlflQxgTwGGZFltQvOZZoNYICfFwLk+LEaIbrusuwcwsfVJATNKSXxJKl753lrFdgyVJHJpdw3Gk4hjYWtmnTzfS758DJPEemmCJQDXAWADWQZ3OEPiGsPS6dI1vhDVJr89OdY3CjTAL8GQmDa3hXvmEPFsLNZtLMp6dJL/9kjT8QCQPp12rRcA7lcvYPBw1zealT65b4TYKgMil7hLsWsu9CK8D4KbF4PYCdDKJPyA8X8DcnYDKSnrYmJGX3jkRgRoLNZ1jeMe3xgT2S6VAJxPomYFbLMBNC304wc6bmZzLOiStBc0W4oQ9u4BZSLMvL0qY9dxXGwAAIABJREFU0Hh8lQhp01y7Ys+fQ/Jd+YDPIbVP/olZ0YCPLSGqW16s7NxLTAfwYmSMDFzWHeaIArcyvDMJ7Rc+ygk6bMIyCfkCqyQuqyIrZI/zW1opQstI27WQAAgaav1ELHkmRg5z9dzUjFZaODyFBowBadc1z/bwWPHavsKFcJ5Kd/zUXt0k/l95gGdoB/FUKXAObpBBlZWP1nRvOeeEusQroVDq2y2IJBpNDWADgNWPMzBGVlXM95Ai1FspEs9lzakBVTXsMIcKdCSOYUeZACMVoCoLYkYzMugzYAs1S2gP8UrCRYblvkH+jkRgPMgE2BmAkVqDixRoEtk+yK9WZeNNhLRu19Mh+XV+5C3qm+q+jGwtVJ6L1HTo4F4DrsXjSfU686WZVGWZl4uW1+FqcN0pz7rFYuV8cZnjcx6uqgRT5Am6QjndnZxKWbvIAcdQg4E01IYG1kRQ07ZcdktOPx/yUUgYg53Nu7mtwR4AwJ543iGfJAYgSyKtgbsPZGx1Le0e/njSGlTkAhEgEiXaspSlaCnJ9xANxeXkYhEjIAoqssyijusjA/bCijRfwHkOqIC6DmPi6Uyu3bSRfiTcC1I92paeOCa8skp4ndsWxe/fhptMxZmlqXA5lWWXr3MO+n4CbQSpHqShiskWOKDL53PBQ92T++T8Ep5v38PurJSozAmI0kXFE9ctqesGrmlBR+/ja7RxSCt2PR3S46zP+RM2vQdytvtg9xO3Pu/R6yXrv36hMXiWxxABxaQ2WJYq/oPLzPKFWE90P44C5SoWrh1wRUDH3hj723pJbEByJ4Hu1iPPpRLoLrX0EFVa98g2eAqRlWR6j1tJjoM4qyugn6PjCXMLEV8fCe8YK3Qv1spY41L1Me95SPT3eZP69y4k6Z+CbSKkVXuuHFJICK/0svUrS6GFpPcBV3kW8xFqMPAUG6aLdno9bOHXlpIEbrGAGgwkSgIk4hkNu8gBgMoyYXgE4KYzQUmXJdTujixdTk4Fqb1cyvKkbuTa5RKqSHs0Hp4GwzNQuskkChGsjMEvqyjL4DwJnN7dWQFGkl/icF0D+7vA8an070W2xeVKDkomQjK3uulkq8cjiWbCki2TZRO3rcxpPodbVlCjYbdk8/u6m3tQh2exDA/4nM28jFpm5ADa3QbnGeh7rUSTntEzCl36OdNoKMBIjxp3R8eoPv0q8j8W5kc2CdR0DntrH2pWdku27TVg5Mkci0/uo/jtN2VcxoCIoA72wVkK/eBQIuZXX8Lpa3vY/t0HIMdwo/wRYCQXKahuoaYL8NgzRhoNvHHJD/XGIa3Y9XRIvSXMudbDIa1ETedV2SIIUqoypEi+nLN5B1a0WNFiC/pfUQdMBtPlUUJZPsuE6pUIFFpSrKc0dQ58fAKV6C6XgkY4lCqSfAsFBRAfxRlxJjTXnvJW2ihQdkDLwIcUrcglPxUwT4mWbamB3R5A+w543hpK5zr55H7IGXnMEuWyvKSi6HJunr8IgDg5Z6P+mTiMSo7z3EBcZIBz0g5S1oBJ4NIE5ByoFSpd9lpmsA6cZ2j3h0gOjYw9z4BWGnLjPUmN5GgWy07/TGvMXzJID/2PwSCFdg7NXg6jCc5okHWo9nO0Q48UXxrkkHaSItCh+HPxIJcq24m0wNjtAtNXNcZvjQBmtKMUBhCH4wA2Cu0ohS5bJNah3S5AzHBXQGpvIqRVu54O6TEWq1Ft0z0PDmOdkTEcU/oWB6tAZ9OuMuQY8EyAYBfzUG4plKxwFq6fvwHgjk97SzySvrLpVJZmTSv9ZY5Btz1C3lq4s0nnWK2nlnUMN5nFcwWn6mYuKrmGPI07PVtti/FMkHFM9x96+hHulms+6a3OJn5eDjibdJU760RsMSzxrIU7Opbye1nKfPxYY0J9Nu/odj3tLJyN5GqxegYgPTmTe6N1BD1yoEnxGClmBn2vRXJo/H1m0LRHSRuWZIpAp2cSvU2nch/qGvv/7HZUltU+msxOJ8Lz7VkhBiYVBw0gtM0cPNiGm84E7OhzfpjNobSONL76m2/jlaN94FBaU1JfoVUBzKoI2suac90guS/Jdn1ZjbYPGcboIna9HdJ5uYX1zv7gMM5jk1zv5ldJD49ku4oTMwAXkdZCxSEaZf0oTaIW32zrGGQoMixyXYN0CtdUUFqWR67PEBmWm9qPWVGn8MoUIzJKDRyEfRJ+iReXL6QADjQfPsGcGqCGtH/AY3u8FhzluWeHVLECx8zSj9eucvdQ6pO/Sj4SajDokuP+dW5bUa7NMs+B7SPFUPULLTOjYY+33IMe8xS8WIBMIsl8QJZpSpZXlGdC5GatKNdWlTinQOLmtdugCAoQrbQAy/BVORoNBW7gox8uMgEsJlpK+MzgQd5BCiD+QG1vCdmbz4fRcIh2fwR94qW0iwKg3r1QSipzJgFNfJI+lP3XGYmeYARsOLXX7Ho7pMvYk4QiQ/h/CaHIddlneIlmAUDaeD4UXhSyqiR/o+puW8gFNW03Dq07oUjf59WXxaY8FzL7wD+UZ1GOJ/SARVAiIMwEvcRxGBMBwKAABbJ9PyYqlyDV0eb2j+NeHogy74B6XEeoCWgoviYKKJ73KOR+AFmy9vJUobSOtvXL5nk39jwDTafijPJcrll4ocsgi52L46ZcuJN4WaHZHyKdl3JPE+E2cttDKKJVochEwRmNZJpAAaj3h9DrTKCDQqADy6VEPcMC5a0c4zteKHJruAqC1Qo8yMCZgW7ayKRwpUT3JkJasQ+OQ3qc9YnqQ+XlCVWdUDVix49Uf1a4g8L5+sDBsH+7Vp1h140jHO9CFajHzxRYEa0INEatMx9lxKpgP7fWevbGwEhpreSlrBXgXsgTBVBhGOM6gNTPbWUOYYnFFFkbY9UwgEetA6GNjwAk6uuDOeGdkrWCM+qNHW0S5xmEPIMqrhzbghoPpAzskiyMkZ1ElYyJlp7N0c9BlQk4UZK/quQ1XTaP4s8arw/nGStV0yKZ2e59rOqVSik5BSz9PForbJTrkfsFjZ7wWfww2gfGIZEiMFPkSoosAJ6iVXbqdcOfZzos2fxflkpOBQA7zxbQb8INXfVA7EtjoNsW9gmAy5UmX+p4o1WvwhcqTVnmu/JTQC+7JRckqUzhy5uIJhr3GQaSBKTb1U76EPk0rYxxLd8R5hb7yYwB0laurzzYM0uBqpaoKPS8BU5tdBESUrMK3gztIEu92l3vGSXDPAM+ye1vQSkVIyooAWCS57OGtWgLA52aGCGh8Y28ddNFSIWJERK1DrRMYAsDvd7TmAonNrIMKknAJkE76rGBZilQNasRUm6wfHGEYlEJx9NVHMsmh/SIfWAcEvejDNkgjyHCAN5bSrv3Glsr5fQe22E83nVRBJU9Ke1QMSvXpLRDE2df1daDHyPXdO9LwnUjPWV1LUsFazv5oNA6EsbhS/FdG4iLPXW0KCVfolQcZxzjOS02kfsakIS/H4f05XWc2OxkDFGqKHBq+0S0mi1WlsRM0iXPdS10u+H+eZ08tk5yRv6eKqUiKBFN4/NwPhpqGnBVwxzNwYtlzCGhEiHIfg5JeSyY9jkkXpQwR/NHpLSxKMWRVX7OAIp7y67nDljNpykFai1yADRbQL9H1P0k21TZVu2D0+1/Hn3FVT4kfXBd6Aj/k7D+h9q5CGg8d4nFfK5Tefpj8uOIIETXVfSe8lJjhSyvLwjQuyd9AYKnfm2gO/8FjRrbsTtc9X7wBf8+JPaBiZCCAMC520MSOuB41sj7V2ytj2xlaRMwTeuk/OE6oe+sT5QfrtUHYPrnUTQA3C3hgkyQ5yUireLxkXLXX4edr3Bp16Glw5islQ79QBgXxsS8Qv27Pjf0l3hBuCCwDgASMYUktk/WhzEGFgIOie7+29CTMopQAq1l+edJ00IPHlIjkZGXlKIwj9QIGRwtBXuUaACesL+V3r1Ixg9IJSwRKW3FIiRpB+mjy9UgcRR4mVKDZmSQhD7FTIoc8d5oBU4NXJ5Cm5780WW5yLGJkNbt+XJI6+DH9cpar/E2HtLrag9Cg5Qa4bDrgx4D2DJJOiHG9WpMlkYsUTgPDTzPc7mU6tOyittwdCzXWlZxHFIpq3vNpF0UQF7HnhcLBGki8jkkAF3nfJLEZQeNhsB80eXFTBKv73ZHoIW8FsUMqfSsAqvfhDC3iNQe5AI3CI4oz8BzD1fwrzE7qQomWpK73hE0N8YwfUkgogiaFD7zWRw7D3LQ6ZncizyTBHYPSkDGCBK6qiXHBADWYvHKAKP5OOaQSCvUL4xhjjVcLmNudnLYVMFlhPQ0RaoUFq8MMPzG6seet4ZwhYGaL8CLEm5vhLNPpMjfGQIA2v0Rkp5TZ6PRjlIQA2pYoN0fCqL7Ks21m7L/ij1fDmmdYmRlGbP+ms8p1XXc5sql1/qy5x7PFrFCJNQf5cr52OdkQg7ElUso17sOfO7Ja8LHa7KL44j7hcee/HO4XqQTCbQcARgZ+uDKspvf2WSF55tCI21dQz04ER5xpWJFKuab1nNIId8UrG1X6UfaVsZqLQDhnmbH4PlceIKslUdACPl79wCkgLlvVq263BOfTYDFUuY7m3fVuYBSD2DLqu7oR3w+a/TtU+DwNOaQuKqQvkvgcimgRQDqLAN6OCRelBgxw/XnCYAenkCnAtDktoW+d4IbX9PAsTQum7JaySEppZCeiuAkzxYwAeKwKfu/b3u+HNKT7EmtIxfEIcUWE2PkyxEeAYDt08chBXrZMFwjlR5aVh6U6byEtcchaSVTTNOOv+j7hUPq46H8c5Ak4cNrkXLkqeCQUonC2i5Kg2PZv8ilgJB7BzObP10c0rCQ5d5CHP1FcUhQCso5uPEQdAX6EcJmybZuHxyH9BSMejmAAJIM275v+eNAHA9EilYOcIAgex3K8YFbKOa2vs/xvmeojFAJrUDc66u7bKvEE69FkYwt5pCsFwYIryvfj3gFUYAnWqQGpq7H7QJmCwN1pgBNV8/xb3BIK3b9HdJ53Eix8rT2Zva4kgJPUqSUBWLXfFyarLSWsORtPAIZgJS2e534djbHefxF4X/b7+/yFjiVuHbdox+D6wsoen4lquuucgOA5wtZJpICIJGSm82hilz4eI6OVytupCJ3EfWWRxTm3qfk6FmYmw37V17WSXtlknIZ34vIFqAIdjKLYgvBedP68s87tdAbF95Hd3QcW2uUv98R2uDZOZmWHRxhNo9cTuaN78KGMfp+PJrOYK3tsFQe46U9K6VtW5ijE9i1JZu7/xBRgGFQgN+5g9HxKeyZ9M7RUeL5kHqc30rB7O7AnZ6BTnxkeB53+nvYJkJatevvkMIXs23FyVRVpO1QWRZJtUIimrIMXFm4pSSCk1s3hcgLgLr1gjSvjoewb74FPRqC21ZoNPJMCN+2dkHDAvbufahbL4Dv3pfrVxX0j/wg6PjM94cRsLuN5sUdQAHpm/fhdrdA9x6i+lc/BnKM5Dd/H+oTrwL3H4JGI7iTU6idbdj7D6Bv3ZRk7fFZxC3R/i6al3aRvPk9+WIcnQAv34S+I2NAkQPlErS/i/atdwAA7l//DJKjUoQVicCDHM2NAZLTJY5/dAd7XzsDmFEdDEAOSI8WoNv3BZUd9NmYgY+/DHU8hdvfAshLVb/1UDrtAbQHYyQPp6DFEs1HD2Defgj78BDq05+CHaTQZRMTvfc+N8DBG5Uod2gCCLCZwuD2AvVWiuL3b4OtQ/XpVzF/yWD/n90Gjwdo9odynsLAHMmyzg1SSWB/+xTNviSZzRvfxR/+wqfw8j8UQch6qDC+XeHu53Nsve3QDAlwwPRjQDtmuNwhu59g+03Gw5+s8UP/2X1hYPB835PXX8ZyR+Hgt4+Ahyd4+Bf/FH74Z/4Ab/7Cj4EYmL2ksPW2RVsQwECbE5YHhGQObL3TYvKqqKi0AwL+28t8trHJIa3Z9XdIPRPnwx5syNEZBTIwAB1YLxwz7QQQ+eRMwHm+KdNFxkYXk9U8nwvvdNOCT89Wz/fgWHiX/ReZHCP1r7vJVMB1sznyP3oIMKO1Fjg8Fo4dK8nq0L3vziagpYgxhmuok1OY1sJNZ0BVSdL8oRwPQFpCmhbKM1ICQPr2EXheghv/qz9NkM4G4MUSewDo3hEAoDjzbIvlUqKu0CrihSLV3SO45RLkVXLTPANPpoAHB5qyAnvOafMOgSdTGcu9IxhjwE2DNE0BZtzCgYg4BlEEJUhtOpkgybP4A5H/8SHSw0KijGUlOaG6gU6NgB4B6ERLNe3wVF4HYKsKL/9Dja0/PJH3Pk2gzuZ4kW/AHC/AqXyst971VTZDSCcV0odzmHI7JtwD/mj8zQLDQQo8PAHP57jxe1N8/e+8hhe/LnxLw9sFkpNFj35Ew45SUOuQHM+RHQ4j/cgfXPIzvamyrdpz5ZDet4VlTb994zwcXL/f7Lzj1/e9Av7ksXbZnML6/tTLuaxsX2U/kFaRJ5zX97XFs4RIlUUaaL3Pb0UaqffailRRFO2kR8e93ucX77U+tw+Q+NG5i+SS3+7kOTnPTBkh+P5REWC93JPzck29iqqy3I2T/ZjCqji0zXgFF7IOxACpy4c7G4e0au+ZlSSiLxHRAyL6/d62/4KI7hDR7/m/n+q99vNE9CYRfYuI/o2nOVjqK7/G5+rJ5daQmI09XjpKC0XgYx8QGJLHwKM4JH886Q7kB9MBCCnRgAfKsU++kjGRhZJ0d83IJBD668JcEt3Nsd//FjXHer15fowroEOvFktpCpd5wrckAeepjMmDDClNe317MnbyAopkTNdjFv78uMj/TyQKwlEqyRhwLr1mNk+8SGQKHubgIpXowiQyBn8/2CRwg9QryWq5Rv9R60e3JxpQhHqoRFEkTaRnzSSwhUgYuSyByxO0hUYzVGgLhXao4XKDZiiJcWRZpDZhk3hmSXm/XZqg3ia4QQpXGLhcg7MEnCfgTHBONtdyjD/WpRouu2SyPTjVi/x9SOwiEdL/AeB/AvBLa9v/JjOvrJiJ6IcB/NsAfgTASwD+MRF9ivk8XpDL2xN12cLP13oU0whGh5gkUdo0UQEkYoB6vWZd4tytYJgACP1rXXfEZstljES4Fn01rmuo6TyOMxwTE7NKEOVcVasd7vDJ9nnZjcHaSIIP+B933wMXbVHKNQIJfSvd7lzV0CcpOJCfBTaApe99C+0ZYa6+dw3zhcypkSJCcPXsl1PctnGM7ASbhSCyUNdgAOmDHDQVRs5+lYznC1BVC22vc1DTObTz94Jd7GVD01HYipadkj6zMGdrMb4tvWsAQIsENJ0je5CDZqUnhWOoVrTSWBF02UCdzjG6nUqCXqnIZqCmc1AlvFNsLZLjOba/m0MfTSUSqkRCKTgsTjRUmYIaC5ouYAB5v69Q/dsktVftPR0SM/9zIvrYBc/35wD8X8xcAfhjInoTwI8D+K0rj7BnpLWgg31HP2kNbrs2jijE2KP/oKKQ0DryRgtxGabTiOsRgUUNIgVV5MLLUzdQ41HEAHFTg3a2BWXsSc/U1jgmgaltQVtjUNvC3dwTJ/ngEDQagepGktTWCqamLEGDAjQcQE1mEROlxiO4G7tQbQvKUjhm0O52BCdKwr6S/Tyntru5BzVZdE2+eSZ4nMkCi0/sYeDFG+3OCMQs+0ZqkeBsFWhnC5hMQdtbct5xIcsdTxvrdkdQJzJ3fnEfdBeCU9rdlsiobqKQ49lrO9j6lpb427MIuCKBuTsRqaJS8EP21j6avRzZ6QQ0GsJtD0HLBpyb6Gw4S1G/MEb6LsFtS1KbpjPc/XyOF/kGyDJsoZE9yHH86W0M7xawhTiG2YsabUFwGZAf5hjfznH/syk++rVcokxP5Fe/egP1tsGoaaEAzD+1hztfcMiP9kDMWNzMMLhbwGYKxJKgX+5qJBVjcHeAxYsZyEmyG1+/5Id645BW7P3kkP4yEX0RwFcB/MfMfALgZQBf6e1z2297xIjoZwH8LADkGFzsik9Aasdu/7W8T+y2dxK9SCTjo5p+KOw40raC6q7bv8/rUy47FDWLcKKaenqSppVqmbWgWSmtBECUBooAy5AkrxswhYjLR0BVDTVbRCSxCCj2hCLrblzB1LSUymFVC44GgiTGskJ2tIwKrWrmMUx+jGH+scpWLmVsPnpQfn6BVVNpJWjluhHC+55QJFkrFSsr0erg3lDI9gPJPxHUogGVlZzX517UrITRJCjwcglFJNxEdSNRDABqLcyx7l4HYK3F1tsO5ngBOECXCWhWYni3QHqyhJsnnv0xQ5sruISQTi3S4yXG74osExTH+5CclFBVG9/f7LDC+NtDmFOJdAsiJCcltBFHlxgFXaVQlUVyskBBEum4dAOMfL92VWTb/wLgkwA+A+AugP/usidg5l9k5teZ+fVV6b6rWcTArCVzqZdzgtIdwPBx5/A676QoPsZzJ0nEoPgDJFdikg7YBwi2JiCc9VqSuS/6mOhIL0v+yyvn8mMg2Se+Hqlou7eNfQ4r5piIRB1DaxFJDPPt52XOs3AOLbmicN7Y9GqSmOuJ1wzH+QZe1gqcaLRFl+9hraXBNU9k3Env+omGM11OjY0n+PfXIs+X5PJuDGzkPWiGJDmkTMf8jy00XJrA5Ro2T9AMFJqBQj0itIWCSzWawXqyX8k5im5+LtNoxlJNY6Nhcx1zR5zJfW0LDTuQHJYdyPO2uGwO6YL5o00O6cnGzPfD/0T0vwH4Ff/0DoCP9HZ9xW97enYlIqy1iOq8as5FoNh9WpL18awzSfpzstcdo7DP4yp4V7V1cGew0LTrGSPR1zEDIo1I1GMLY7rS/fVVp9CiE6pSCp7xUnVgz0Dv4v8ne0WKF9d77FXcKFTFvJFjEJPILsWKm5PqqmOcX2b1513ReENHwuYrjU/DNlW2VbuSQyKiF5nZS2vg3wIQKnC/DODvEtF/D0lq/wCAf/G+RxkvrFaqbH1qkdVtPev9mlOeR8ZFQKIXZuokpB1LB3+Wya+2fwzGw0JaGsKHP89gt6TfSZ0Y6WifaLht0ekCKdAgB83nwoioOznoIKFEdQ32H3zKMthRAeXHwOVSwJCTQLRvwF51Nyw73VYB5Xr0I0Uet1X7GZIHBUAkYwKEhmMaKFOcr0I6GXvdRCCkG+fQk1T4rP11tKd6tVsF9HQOzJQQ6Rep5H4KySHNbyZIj0VOiX1lsC008rKBHWXQ9xME3bRqP8fApOAik3GXUjVTYT5ZimYnhzqT1+V905h+THBGZBltoaFah9mLGuQyNAN5z2YvabQDwOZAW2joOsP048ALngVT8mgK9W6OeieBuZOBFiXKAwP7Q3PUXykAx1jcNFAtw2ZyXpsplHsKScVQTY7FC0mXQ7qkbZZsq/aeDomI/k8APwHgBhHdBvCfA/gJIvoM5LfoLQD/PgAw8x8Q0d8D8A0ALYC/9LQqbAA66L5WXvEiOKcn/MyEZZrv+o58QYFXyLMxCv0sxxYCOXbNufV7zAC/vNBgElmcsNRoMw1yDKWot/zQYNWV+ynRYK0euR6b3ja/DFrB7yi1Mi5nvNSQJ+NnvwxSqUFbKEk0M8PmgiZWJpD2m64yR+Tpbv2SkUjK9IFLCejGof24wxLPyLKFLAvMgIG2gFS3EgXWBCbAZVKmd5mXt3YWLtVohyreG066v3jdRMGm/l4kAe6h0I4ZNlWCkC5IzlUQ2lyhzf32AdAOGTYD2iHJEm7soiZeWM66VMGm4d4SbEY42J2iLW6IoynECdlcISC1beHzWalCmxGUBexlMw8hktxYtItU2f6dczb/70/Y/68D+OvvZ1DvZf1er1j2X8/RBPNS19SXP2aOpf7AVMjhHCT5G/gc0sr5fF6nnzhf4cAhkvN60CE7WcY4X4rvlgB+zN5BRlChd3Ah59PH/Mj1u23xXiRqJacE8u0azHAJECS9AXQgRfgkfFjS9e9NiLwS1eWj4PMpiQbV3ln19ycfCQFgAmxGgPY/Hh44alPloyV05Pm6d2+9I6XWwRntydfkui6jLt8EQBPB5Q7OyFKMta/kZYBLCDYFiAk2FydhRxb2NAErAqduJamPtoXNxKkIxkmjzQi3ijmO6QZYAzYlOEOwhiR5bQhtLpN1qYLNCS60jlzWNv5oxZ5fpLZH2MYIqcdVvWJBDBDwevYcl1MwBtQ0XYRknXxZqlr2C4/hkstOshqKgNZCzz0sgFkqWqSgKq9p77vXKUm8w1NCKaJFH43Kymuk+bL+soKeVXIeJY2+qqxE3w2Q6lPb+tYXGZde1LGSBiZQT1kjnbg4b9VYQSP7eyC0JnUXITVevaRpASIksxrcNKBKnJmeVaBKtulZBW68ekfTihJv04KsBllGfsxQZevZGiVaSc9aUGOhKhEmgLMib70UwQAqKyTTBFQ1QshfeigEM9LTNL4OSP4ru58gnVQIJGe6bJAf5kinFqpVPrLRaIcEe5ogOwHM3CF7oLtEf9OAlEJ20oBcIu9HU6M4cfj6uy/h1aV8VvITBzO1ULUgxHVNYKWRlIz0tEEx8BFZfvka0WbJtmrPl0M6z+mEXrbHlf3rJnZhc1nKF88fx3UdE9tBWXWFaK3X7Q8APF904EAAKEvoU1+VqiqQUnB1DX26AJyDtVb6zDxZPzetdOAHcn5P5B/L/ksB+62U/eflo2X/HteQPpkLONL3oFHbQgNA3aC4X4JmJeAcNJE4x8VSHFyQSvJl/0DMT3NZsoXSe7i2IorzD2T6YAeaC0E+WgtlLcgxxrdzuQeJLNvgACgIAJE5AhD1yRw5AF4uBcgIiINbJgK4hGCdUqXAizKWhG3bYvtNRvpQsErJzECdzjG+nSM9XsKlsmTWteSTWJE4o5Ma298puuZoTypnDhfQC+NJ6hoUd5cYvDFEdjgBWM5jjnq9bJmGmRqoysIcLzBkvlLZX97kjUfq2/V0SOdRjgDyqx7Iy8rS8wWl8kU3Cbiy8TGYGg3hwlJpbwf1D1UiAAAceElEQVS0WIJHA9BkIsDHqgZKT61a16DBADQsQIsFaHvc0XZUFnywB3UyEYQ2EbC3g/rFLTARsqaF2xuDWovqIzsAA+ndBwIiBECjAdTpBDQcCEna9pbQtx5TBDXSzpZ0+5dL0KCAsha4sQMVyOSKXI7d2QJOhc2wenUP5ngBNZNzON/tb06XOP6REfZaB2JG9cIAZBnmeAkdHGDbSj6rqQVgeTKF3dsClHD9pE0bk9zNwRjJQyPd/i/vwbSCIncHO7DDFGrZCF81gAc/luOGEUfAGmCSvMzwTopmZFBMtkDOYfHJfcxvJjh4sA0e5EKeVjawvW5/G7r9mVGHbv+jEzz8yRqm3AYYaIYKo9sp7n82xfjdBM1AlnLTjwPN2IFTiYy2v1Pg5KcW2P+tHYFQVDVAhOkPbEu3/6wCOcbxawP8+J//Gr5x+zWQA+YvKYzfMWhzWbK1OaE8IJgZsPVOutrt/08u+VF/iv6IiN4CMIVUelpmfp2I9gD83wA+Bsn3/gVmPiFZNvwtAD8FIXT+d5n5//Pn+WkA/6k/7X/JzH/bb/8spHOjAPCPAPxHzMyPu8aV5rDeJPksbIv2+HP0k92GxzgkKCFhj2hspaOaa8zLrDeRZlmsppBJZGljjEQt3sFFIca2iX1q8fUed5Iaj6UVJVTZkiTKOwf5Ha5r0HgsUdeiFGR2KLEHQGVdy7j8/yGqI5MIpcpiIWNoWqg8g/MRUeQdCpzfAPTubtd+QtQJDzgGDb0ctrVS1XMcmQyiNDZRN1drozQ4rBV+psAt5O8FM0f6F65r6PG4I8c3qbw/W2PwdC4/GKHdwkdl8f2xVni+sxTu4ZG836nxS1rVyR5p0cfjRRk50e1kBvrRfwX6rnTjI0sletvZAi3reA0e5JGAn6y0ebSv7EN/5zagNHjp9e6yDJRouLOJzOnFW6g/cYDUszbAJAIYDdirwK/dtPLDWBSyn1b4tbf+5r9k5tcv9LnfeoVf/9xfvsiu+Kf/+Off87zeIb3OzIe9bf81gGNm/htE9J8A2GXmv+L7T/8DiEP6HIC/xcyf887lqwBeh2S4/iWAz3on9i8A/IcAfhvikP4HZv7Vx13jQhNbs+sZIT3J+mV9dojijD2MyIr1lnCRbM3JcVHRA5AQPvTJhZ65kPgNxwfn5LxAorXiGPxyKPaqNb7frU9b68JrTZxDf7kGyJLOhXGGpWSvny7UK/uUKOz7wmQOKjonMok4IyfziAonAY+UJIIR8mDQ6Cy9k3KB3C306nknwgGB7u9NOA4AiOSHgSdTr6ib+CKAd84hl+edI/sczsq9CJQo4b6Q6jTselzo+mQqy7rwvlU16GwGdr1lfdNAGRPpdbksoY/n4rg97S20jrzg4Ro8m8Pcy7sfn6oGmlrexwARUTpq4kUU/lVYH77/OKQ/B6mSA8DfBvBlAH/Fb/8lll/XrxDRDhG96Pf9DWY+BgAi+g0Af5aIvgxgi5m/4rf/EoB/E8CvPuEal7br6ZD64L2V7f6L2eODjpxIjz1XECa0IMgvOcPnc+IXyuFC5dcekJJbiapi86ntwH7xF7ppASNVrL4Mt0hmX+HDe+6YeucOjkGLsCKliMT8kTQ/OCWed/e3j8NyLqrgXsh6Don9eMhHd+R8mwhLq0i8w/N5jFQBrEbBF7XWV0gtSw7LWulNC3MKGmuhNSZQ4lY13KIE6zo2PT9i7EThNyTulRQ8Ou7yp4dkuQTA8gYRfbX3/BeZ+RfX9mEA/y8RMYD/1b9+s4cZvAfgpv//ZQDv9o4NbV5P2n77nO14wjUubdfTIV3CztUYe8x+/p8YVcWowSm/HHqPkygCnIpLvA5qoGTJ4cv9pLV82SMXtcc79VDRMbJ7WtaTwQbQaciFil4/GmSJ2shDAth1Y49Vt8tYWNatRJwqaqlJtNLG1pe45A335ir3Ilyz1y/XQRE8YDbQyrSt6LnprsJGSdI54nOckuCuNAKUmgL1S6jsXvYenWeMy5T9Dy+wFPzTzHyHiF4A8BtE9M2Vy0m+5/uao3m/17jeDmn91yN2aHfPuzK8Bpzt8k4hD+XzROwYeqvwkYMBlsuYm4GzYPi+rSwTLqHpFGo8hj2beKdnJQneZ3gscskXAXBHx9LRfyYd8wSgffc2VJHDTmZCkRuocpsaUBnU7q6wMAYGyqIAbY3gjk8lnzJfgMZjuIkwHIa5qcEA9mwCsIO6eRCrXwCiLhsvFuCXXwDdeSDo86KIktB8NhV5pJ6p7bFISg888nw0BJ+eddxRg1xYHJtaEvJnE7h5CRqPZfnjddkIQPPxmzB3jnsnV8DBHuhkIjmjew9k88G+JM1nc6jtLbl244UiF6U4UmNE9ePhCWjoUef3H2Ly+ssYf1OQ1GwSqOkc9as3kJyUYM9LVO/mghPKpLRvDheY/sA2Rr9+uBId0sdeEeHJ2w9Fl+2Tr+Dh61u4+WWJFNu9IZLjeac64nXZQARzOEO7OwDYY8L++aU+4E+1ysbMd/zjAyL6BxCmjfuhs8IvyR743R/X5nUH3fIrbP+y3/7KOfvjCde4tF21ufaZ2HoD7bpKyLmmddcgG4nAknjMI+fUugMa9lVWgY7cTHu5pEB8lqey3RiJEsK2/jn8OPpNqUKK1gdGegIzInGwSokz8c21cd8k6ZaOWdopu/oxcC7b7DCLhGthTGGMYe7xL8wt7J/2nidaruOBnJylXTtOaoAsjY/IUjRjA87S7i9P4QapFBOyNM6HM9keiOw4NYL8zkynWJsauMKIg86EZA5EWO4ouEEKLlK4gRxbbxu4gYEdpbCjFPVOgmpHY7mjUG8ncAOD5Y5aJX/TGm6QioPxaHc7SlEekBDLFSnasQEXKeyw+2u2DJpRApfLfNuxQbN1+d934ov9ved5iIZENA7/A/gCpKXrlwH8tN/tpwH8P/7/XwbwRRL7PIAzv+z6dQBfIKJdItr15/l1/9qEiD7vK3RfXDvXede4tF3vCKlnQTcMwCOPgMcf9VDUlBhw20hE4Pdz09kKwdnK8Vb4lYI4opCPLbpEeGJiFSZeYzqDCnxJZQlnLVzdQN+PRQ7h9LYWCOPwHNVclnAhER5yE/O5XDsQulkLN5nGKDDmY+ZzifyaFnhwKOoqYZxlCVqUcHUN88eAOz0Tx+YjIte25+bdwtyiIu6yEvqRoAlXe55xa0EPj2OVz52criZ7AQy+yY8IRaokgVssQCaR6wPQDw6hTlLhHGcWjvG2BTzvUygIqPkCbjYX3TSfhA+E/GAnOmtVhVEjFCKJ/8Exdx4VijyYVXD+PQimbz+U1h+/PX3zPj5S3RAxBADFUSEJ8eCElYLJUmmzmcwwOC26Cu9l7elFSDcB/AP/45YA+LvM/GtE9DsA/h4R/QyAtwH8Bb//P4JU2N6ElP3/PRkOHxPRXwPwO36/vxoS3AB+Dl3Z/1f9HwD8jcdc49J2/R1Sv4z/uMe4b5cLEvI1tVIFivAAd87xAb3tGAy7GnF5AcnHVcUA79x8Rcz1RCjXq1ErzrSPsdJKEr8ePU2e9RDOdRJDsdrmy/OOOzXeMCffKgMrYgGdM+slsHtSTnGcYW59NsrQUqKkDE9aAayiQycjMAcR53Rd9fDkbOUeyPwk0R35qQBxRN6ZknMerOmgEq9cCxvhE0HYQeTGi0jIH8dvrUgp1U1kbuwcmAY3woVFjrFeLInVOgA0HMJNpkhuE1wQ2eyDYQEwkUBIDvYjwFUmdMlkN0PQ80/BmPmPAPzoOduPAPzkOdsZwF96zLm+BOBL52z/KoDXLnqNq9j1d0jBmbRtzKGsPPovetT7Ul611Msg6a0twfWQgtrZFmrULIM9PIxfam4bUGKkulIUwtZ4egYq8qi75pZLJC+/BO59yWk4BHaFYREPDuXDfHIK+shLALNILR3sw52eQRW5qIhkGex0Cr29BSoKuNlcKkAAaDQEdrfB9x5KHqWuoXZ3uqSrEQFFGg1hD0VNRH/qk6C50NiCZOnF4yFoXqL52Aswbz2QyHHoO+XnJdzxSVedAwDH0C/cAM/noNFI7vcgBx4eRxVZHg+FlraqgRu7wOEJ3HQKfeumH2sjS0LHmP/gAQZvCXBT+vqED0kfToQd4PY9qca9+hLsdgH9zbdBwyF4WEA1rTQkh/c/NXB7I+h7J3EO/M4dPPyLfwo3fk8oZl2aIDmeY/6pPWSHVeS2Lg8MbEZoM0Jx4lDcXeL4tQFe+Ps9JwrAffIV2FEqUlaTKZrP/gDu/ESOj/7KLgBgeaNA9tAjtSENzfW2ga4dsmGO6oWB/DhkqiPiufDn+5L7f8DtejqkNXBj3JymEi1kWYwSpI3CrUhBr2Bj9nZkOUAEfnEfaloKFerRMdRgINzQcytIbWuhdrbB44H8ur6wH6Wo2Vq0H7mB5L4kXIkI7uYe5h+XpPa4tWhubcM4h7NP74McMHz7NtxLB9JSsTWGOjwG7e8K+vvGHtq9EZK7iejWA8DNG5h/YhujZS2JXGa0HzmADhGJT1bj5g3Ai1FOf+QGivtLJKfC0NiOMyxeLFA8qPC9Pz3Ai+omwIzFSznIMYp7FYwvZ1PbxhaK5qMHMPdS1C/tAESo9g1G3wDsWJDa5UtDFN8roKZLzH9wH8NvEaiqUH/sAM3YwCxa1FsG5Bjv/hmNW7+5B5eQaLMp6ZjfeTPDct9g17eznL62h+mrGq8c7aPdH6G8lSOZWbQjjeKe/KA0I4OzT6S48TWN8paMZXR8ih/+mT/A1//Oa1CWUW8Ttr+b484XHMbfHqIZQ9obf2iOg90pbhVzfP3dlzB4Y4gf//Nfw90vvyBRaNOCtcLD17dQHhA+Ut1Acptw5ydy/OHP/s/4zNHPgRww+aTDzre20AwpshksXmmRTA22v72Ns08BZIF25C7tkJ4Wr9IHxa6nQ3rMmxRAghz02XrLi6DZFh7j9odHEsYrgrrzQPAxs07BNnJm+xwJjo5BZxO4ZQV9+15XiWOG/u5dyau0rYTtbYvx6UyigNMzmEUJN19g642HIOtgHUN976G0pxyfyHiPPKL+6BT65AyuXHZVO2sxOpvBHZ+AplO4eQn93TtwkxkAgPy+qudwt373rvSV+cpicpRg614GtBavLHagjydA3cA8HElFqawkH2OSjs6XGeaP7oGXS6S+nSJ9iySyOxKs0Oi+5FG4bjBaLOH8PUq/ew9pagDrYHyE9ImzHZj7E0lQG1l6UiPXzt8x4lSbFtu/+wDjt0bA4Qn0yRnGd4oVECMAJMYgf2cIHJ/K6wDs2RRv/sKPiW4aiTqIPpoiP9qDOZ37njOH+isF2uIGjukGXl0yssMJvnH7NeyefEd+uJoGUBo3v6yE0+n2fbhFiY/+yi4+c/RzuPVbE8AybrxhYE7KeF5OE9ihgSpL6JM59r8+9CwACm8/pc/6h9Wup0P6ftljtMYuY7yed+o9cv95fz/nVmlnI8Dy8ioV5wzIX4MBhW5+YXtAZjsP7OuxNcbj+wyYga7kogna3pzD+aNmmpVzUX8svWvTVRkq0as8cTenoJfWvydCT4K4XRgjuQOTPoaykRwEdNmfT//9fRoIa8afBFL7ubLnyyH1GSLDc5aIiLRPZq8BHGMkAMR8CCW+96rPTwR0OmNFLsuq8Oh3oTyTxGtgeDRG8hpEojufZ5KAzbOYwI7UIxGg2Cv7F0XHRwRIdWk8AM1m0l+1rCSn5StklBrZN+uYwHg0EHyRRxRTmoKHBWi2QLObQ594busiBTsIEyORb9PouJKQpZLLCjmjQS4VO38tHg/kC08k/y+XQoOSZ1LKrxsp1ztG+UKG0VQqXOz5mVyqkbQWPMhAIXczykWyWwkGi7eGkqPK0g4Bnxm0+yNRzt3yqiNHCWYvKQxvFwADLtegymJxM0NBBJtLVLa4aYRcLSXkJw66zjB/SWEnUNf4RHa7N0Q7NiiOCqBusLxRYPJJhxtvGBADy4MUuWOw7+a3RqHaTZAsDXIAy5vFlehHCE+PCveDYs+VQ4q5oV61Kb72OPqRUFmz6PTLwmu9c4VKFbetLI0ci5pHvxeuFCqR2JRa1aCpL6fXDbBYSv/UbNFFTUtP4VFL3mZl2Qms0KNQVYGmC7hatOPYOg9b8GP0+1KvgkWzRQQshntCisDLCunhPKp3qNDOsqY6Eht/F15RJTAPWAdX1V0ujshrzDVQ0wWcV2ThcglqrfSltfL+FPeWUJOFOCSPVldKgWYLUGvhfOVRTUTTTJaOpTihtgWqJi7ZqG2RKFE8CU7KNS223hbFDzgGZwKMHNwtkJyUSDKhCQm0s84QzNTCHC0wfsd4vinfDkKE5HgOXQqDBLctsocL7HxrC+akBJiRO0ZyPJdkOzMSo6GXKVTdUaiEJdulbeOQVuy5ckikCMyrYMj3bBvpKYQIXmZ1+bTSZgAbWwsAPKrQoTuVkEB3GtC7sVlXifIGhVK96lRDOKiaUDiHb2XotbU8olyrdO916tH2dvMTSl+1Okal4NJEJJEAYX5klhaKcE8CH5LysAOiTtixr1zrn4POUa4NCiksCiFghsuEXTKopwAA+3aNuN05sGfIVIEVwB8fqYbDfAIvemDKVIS2oI6fKJXXbaagjSiPEHOknbWGoGoWhHXu76HWkc0SiSiXBJwRGy2qJj7/xWlQl/Hz80q1AKC9cu2V+JAYwFMq+39Q7LlySAAu/4uytix75ByXUR0577zxlF2OIeRGQq5oRXXkKtd6DzuXQmY9nxJyPGs5o37TbzzuMgC/mK9xj+bOQh6JSNJl/Oj1Rd3jCl/Kfv4l3Hd/mpVlEPfQzq6Xe+o34Z5jsr/rPedHrvM0bLNkW7XnzyFdFg3rI5JwbIxM4vm6CImUi5GPRDdda4nkp1TE1ci5O6J+aceQ5tIQjQDoeLDD+cL4VRdRdWMNkVfXuEt6NRqK+3njRPuoJ7TA+AhNS6SgkwShmZaVz2GdEyE9ossWopY+B5DWgHbd/0CMyPqCAC7tiQD4PBIS1UU+PkISjbdwv0XQgJx/DGPUSqKoIHgAiUbbXCIYYo583zZTSIwS7m0fIbW58GHrmsCZj5BiY7S870F/jfxYndFoCx95McMahcToXiSkowIJJyoyVNoNY+T7tufLIa0sr3rP0SWzH0lqJwkYQllKxhOABdIu8kojQOzkJ62kh4q6x2hZKjLasZ1Ew+UZ4Dv84Xu8uEi7X1NjxOmEL7AXkITfn5Yd8RcZAzfI4xjCOUMiPBCekaftACDl6qaV6hYRkJq4rR0bGH+9MCZq2tjqEcnXiLplkb83PMhAZ0m8lhvkUHUjfEiDXECSpOR6ufSnhf69aidB9iAVR6Rl2WfzBGZRydi8E+dCesh0kgjJ2iADlgqcG8lHAeDUSOL71L8OAEpheSA9Z2CGzTVUmWK5q6GrFG0hjqrcU7CFEPKzEtrZ8iCwA3Q/Uu1IetNMloJMgnrbYPFKCzs0gAOq3QR6mcZlms0Uqh0NXSvoZYZqV2SQbHbZ1pGrVxk/qHb9HdJK60hYFqypdwAdn08ASAYKkNAqYSHVMWtjG0JsB/DJXcqyVamjIu+iGk5ELpp7qhXOCcmZhWxrhRSMan9eJ8leruuO7iKQvnkyfRhfUdJakNgKoh83GoCs65pcQ1OtdUCWQuW5ONfWeRlrGylVqJHr6Mon04lAVU/Ku+kS6dH8OdBL+lMqza2caCBR4O2R9IRpAuUZVJH7ObeeXkS+kLpygjvy52FNoESAiGh6Vc+6hS49v3doqgWwfHEkieLGwuWpLJF83s4WBmZ3B8kcIgYQCgKNFZ20ykJ7NZOkCp8bQlLKa2aGjhlh5TMG6U072IeuHZKp4IwAIFkaqHo1WalrhfmLGsUDkXoC8eXbQAKcYGPRrr9D6r1h65W0lQpY04oDaCmW3IPTifuVy1hFe+R4T7wPIDotPp1E1kSpKJXnVsUAX2XzFTE17VF7+EpdGEfsLWtbYCZVsFC1gxOiezdfiBrKfCHVtroWZxPGNZnFBlmaLqT6VXVUu6EiZg4XXUtJmOdyGQUNVm6zn1to/lVnSnrFqgqipJILjUvdQFkLnk6lFSY10hDcNIL8BlDcX4ImXZ8ZaSVCkouyq7IBUNMFEisVR5rMoJsWaC2KRSXVQ2ZoY6CGBXi2gHIO6kzBnZ5h651WKEGcgzYJaLrA4O4AyckCyUw+1qrJYVMFlyqkpw3M8QJb76SPEMKZwxn0LAUmM6CqkA1zbH97WwQUAOQQMQUdos1EIqPigYJ5MMXQ85azvsKSbYNDWrHr75B6tr4s6y/PhIisa/CMxyQJSPkvqyfJFzXYyVp+yFdeTALKc2BegvIMNAv5JvtY3BAA0GwWMUNhW7zmYhHHQYH6JEn8+XqJ0yyVlpHFQqKkuumUbwHpvWOOeCqQ6vBB8RxZ3FbfGCA9zSN2CIAIDsw6ZxGP83OjwveLjQbAYhlVfgPeCUTy2rKKOCnODKjqIpzyZo7RdBjPzZpghxmMFw2gI//FHg/QbhdI7htQkcNtDUBVCzfIoJ1gdDg1aPeHMMsKbjwENIFOEkxeTZAdDgWekGoYAIsXMxQE2IGcf/FCgjYj2JxQDBSGzJi8mmCYrH7s290BmrHB4LQAOxFEOPsUsP91mcPyZoEciEs2l2pUuwlYE4atw/JmJngoc/lu/01Se9WeK4f0vi12ZT/5Q7CCuH7cOcL/553zcf9fxELVy53z09lLjgXC/3W0eDzOOUR9+nX4wtq5zh3r49p31itp5xjZteMdydLqnCocrY//HMR1oI4l5rgbeYcVK2gehS3VsXAcoCzgHPv90aOh7U+qO0e4D2R7VTvXu0547iDLNGY53gJ0WeA9Y+UHaWMfNId03helh9uRqhatVq765ulJYyVsvaIXlGxVdz5nOrI3eLlpNt1tpZBADePoK+yuk8r5Cl7c2leUlYt0+wVIgfH5LtVVvViHKluojKmOkiNIYq9FkitqvZBlSZ+ChXVv2ZfIGAWBrjq8kb8vNqcoey1zlUpUXw4bELyPSxQ0hTHR2nzlHnUqun5s1qEdyHZSDJfK/NpclGQDHqjNSWS0ByKx7VIlUkVr950TAU+KWIOFyxTakYtAxzZXcKY7r00VbEYgK8s0ZwikBRF+OdsktdftWsggEdFDAHMAh++17zW2G3i+xw9s5vA07KPMfHCRHbfzW/yvfeSLFzrpr73531xYXul5tmsRITHzARF99Xm+4c/7+IHNHJ6JXYOA4DrZtXBIG9vYh9J6+a6NiW0c0sY29syMzy8ufIjtOjmkddG7582e9/EDmzn8ydqmyvaIXRuHdI4K53Nlz/v4gc0cnoltckgrdm0c0sY29qG0jUNasY1D2tjGnpltcEjrtnFIG9vYs7I1zqWNbRzSxjb2bG0TIa3YxiFtbGPP0jYOacU2DmljG3tWxo/Ken/YbeOQNraxZ2kbpPaKbRzSxjb2LG2zZFuxjUPa2Maela0rsGxs45A2trFnapsIacU2DmljG3uGxpsIacU2DmljG3tmtkFqr9vGIW1sY8/KGJ2C7sYAbBzSxjb2zIyxKsW1sY1D2tjGnp3xhqBt3TYOaWMbe4a2iZBW7VqojmxsYx9GI6Jfg6ikXMQOmfnPfj/Hcx1s45A2trGNXRu7ghj5xja2sY19f2zjkDa2sY1dG9s4pI1tbGPXxjYOaWMb29i1sY1D2tjGNnZtbOOQNraxjV0b2zikjW1sY9fGNg5pYxvb2LWxjUPa2MY2dm3s/wejNsNtfPCAdwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f24bcc236d8>"
+       "<matplotlib.figure.Figure at 0x7f3787830f28>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     },
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "3. Fitting and predicting using nested cross validation. This could really take a while...\n",
-      "calculate performance:   0%|          | 3/13530 [00:00<09:07, 24.72it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ljia/.local/lib/python3.5/site-packages/sklearn/linear_model/ridge.py:154: UserWarning: Singular matrix in solving dual problem. Using least-squares solution instead.\n",
-      "  warnings.warn(\"Singular matrix in solving dual problem. Using \"\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "                                                                            \n",
-      "4. Getting final performances...\n",
-      "\n",
-      "best_params_out:  [{'n': 3.0}]\n",
-      "best_params_in:  [{'alpha': 1e-10}]\n",
-      "best_val_perf:  6.946023550705546\n",
-      "best_val_std:  0.20182277907868265\n",
-      "final_performance:  7.141429610058318\n",
-      "final_confidence:  1.3483608876145277\n",
-      "train_performance:  6.191789462423358\n",
-      "train_std:  0.14585718770710454\n",
-      "time to calculate gram matrix:  1.1889216899871826 s\n",
-      "\n",
-      "params                            train_perf      valid_perf                test_perf                  gram_matrix_time\n",
-      "--------------------------------  --------------  ------------------------  -----------------------  ------------------\n",
-      "{'n': 0.0, 'alpha': '1.00e-10'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e-10'}   12.25±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e-10'}   6.68±0.16       7.21±0.23                 7.05±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e-10'}   6.19±0.15       6.95±0.20                 7.14±1.35                              1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e-10'}   5.53±0.15       7.43±0.46                 7.23±1.47                              3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e-10'}   4.96±0.23       8.81±0.61                 8.30±2.14                              8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e-10'}   4.04±0.36       2567844.05±4070423.07     2581997.51±4519539.01                 25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e-10'}   3.63±0.31       8069849.38±28067311.92    5318954.85±17398318.11                72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e-10'}   2.80±0.29       1464987.94±4163934.76     2521345.32±12466807.11               232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e-10'}   1.99±0.20       766662.08±1486487.92      1286808.44±2752787.35                725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e-10'}  1.55±0.24       2198.49±4736.63           6574.95±26416.57                    2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e-10'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e-10'}   12.24±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e-10'}   6.67±0.16       7.18±0.24                 7.04±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e-10'}   6.17±0.16       7.03±0.20                 7.15±1.29                              1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e-10'}   5.91±0.15       7.72±0.54                 7.38±1.52                              3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e-10'}   4.96±0.22       8.77±0.62                 8.33±2.15                              8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e-10'}   4.06±0.36       3692957.64±6509964.41     3604469.46±9070829.76                 25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e-10'}   3.62±0.30       1129446.93±3365012.92     2113955.05±7535540.34                 72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e-10'}   2.79±0.29       1842715.22±3976666.34     1956254.28±8522500.15                232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e-10'}   1.99±0.20       371490.35±615155.53       803333.16±2063629.43                 725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e-10'}  1.55±0.24       2324.28±4851.59           5430.76±19385.84                    2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e-09'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e-09'}   12.24±0.21      12.69±0.29                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e-09'}   6.68±0.16       7.19±0.24                 7.05±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e-09'}   6.16±0.17       6.96±0.23                 7.17±1.24                              1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e-09'}   6.07±0.28       8.16±0.67                 7.99±2.06                              3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e-09'}   5.52±0.35       9.05±0.71                 8.88±2.32                              8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e-09'}   4.07±0.35       5154566.89±8158319.53     4515957.33±8176130.34                 25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e-09'}   3.61±0.26       1471436.20±3466483.80     2472808.44±9348602.59                 72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e-09'}   2.79±0.28       1452703.20±3551176.02     1549007.28±7127159.09                232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e-09'}   1.99±0.21       407806.22±573221.94       1072897.65±2409907.96                725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e-09'}  1.55±0.24       2467.68±5206.32           10579.74±48145.73                   2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e-09'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e-09'}   12.24±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e-09'}   6.68±0.16       7.19±0.24                 7.05±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e-09'}   6.19±0.18       7.05±0.24                 7.20±1.26                              1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e-09'}   6.10±0.31       8.17±0.52                 8.02±2.10                              3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e-09'}   6.03±0.37       10.01±1.15                9.51±2.60                              8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e-09'}   4.63±0.71       56922134.64±82649956.88   50097943.03±65187825.03               25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e-09'}   3.62±0.24       9474871.15±35602864.59    10546109.01±35335925.81               72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e-09'}   2.83±0.33       1280982.17±3061321.95     3519493.82±12799812.69               232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e-09'}   1.99±0.20       396615.26±531602.15       1116923.24±2723209.84                725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e-09'}  1.55±0.24       2245.86±4963.70           6087.88±23096.06                    2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e-08'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e-08'}   12.24±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e-08'}   6.68±0.16       7.19±0.24                 7.05±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e-08'}   6.20±0.18       7.08±0.24                 7.22±1.26                              1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e-08'}   6.12±0.35       8.16±0.51                 8.12±2.13                              3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e-08'}   6.94±1.54       13.20±3.41                14.43±10.96                            8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e-08'}   5.86±0.85       32469294.88±34920948.81   26445229.81±34706437.37               25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e-08'}   4.20±0.89       40311551.57±101806904.68  39928665.42±97725519.27               72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e-08'}   2.81±0.27       1455403.06±4061170.99     3679066.78±15900582.39               232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e-08'}   1.99±0.20       359312.75±460207.85       941434.83±2072005.49                 725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e-08'}  1.55±0.24       2348.25±5032.83           9284.74±41196.30                    2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e-08'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e-08'}   12.24±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e-08'}   6.68±0.16       7.19±0.24                 7.05±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e-08'}   6.20±0.18       7.08±0.24                 7.22±1.26                              1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e-08'}   6.15±0.36       8.26±0.56                 8.16±2.23                              3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e-08'}   7.52±2.31       15.20±6.41                17.19±16.45                            8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e-08'}   7.14±1.48       19610001.29±35284721.61   14033350.33±19189415.36               25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e-08'}   5.75±1.57       16120242.26±27211266.71   17713715.81±40423107.95               72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e-08'}   3.51±1.62       55673723.33±112086928.79  21599279.38±40886690.56              232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e-08'}   1.99±0.20       317045.50±462342.86       836555.67±2258169.18                 725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e-08'}  1.55±0.24       2147.85±4716.71           6064.36±23689.20                    2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e-07'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e-07'}   12.24±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e-07'}   6.68±0.16       7.19±0.24                 7.05±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e-07'}   6.20±0.18       7.09±0.24                 7.22±1.26                              1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e-07'}   6.15±0.37       8.29±0.57                 8.16±2.23                              3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e-07'}   7.19±1.94       14.37±4.62                16.26±14.26                            8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e-07'}   8.71±2.67       8126474.26±13375691.81    5844044.96±8207812.09                 25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e-07'}   7.79±2.01       13779602.21±25967474.18   15487819.83±40160990.87               72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e-07'}   4.86±1.05       24311134.42±47979248.63   12392167.57±25549926.69              232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e-07'}   2.40±0.54       13172755.44±19236720.25   16012091.98±34104863.98              725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e-07'}  1.55±0.24       2213.94±4939.54           5403.59±19368.08                    2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e-07'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e-07'}   12.24±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e-07'}   6.68±0.16       7.19±0.24                 7.05±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e-07'}   6.20±0.18       7.09±0.24                 7.22±1.26                              1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e-07'}   6.15±0.37       8.29±0.57                 8.17±2.23                              3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e-07'}   7.56±2.73       15.76±7.21                18.71±19.48                            8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e-07'}   10.42±4.88      2454228.83±4037913.18     1809324.85±2623549.84                 25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e-07'}   11.24±3.78      7304580.20±14785530.27    6129209.12±12842103.05                72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e-07'}   8.55±1.70       18181871.06±41643454.67   7061824.29±16202683.68               232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e-07'}   3.45±0.56       6451009.03±9202208.83     8336353.58±17441402.03               725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e-07'}  1.84±0.68       69359.56±344326.80        45326.53±181760.04                  2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e-06'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e-06'}   12.24±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e-06'}   6.68±0.16       7.19±0.24                 7.05±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e-06'}   6.20±0.18       7.09±0.24                 7.22±1.26                              1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e-06'}   6.15±0.37       8.29±0.57                 8.17±2.23                              3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e-06'}   7.79±3.07       16.76±9.43                20.23±23.27                            8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e-06'}   9.78±3.35       1303488.00±1754632.95     1122573.40±1610500.39                 25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e-06'}   17.06±6.30      3823132.66±7536231.22     3014498.76±5562911.01                 72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e-06'}   16.54±4.00      12059177.16±35832719.14   3233779.44±8141360.84                232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e-06'}   5.95±1.02       3093703.54±4232353.14     5573538.57±13402082.07               725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e-06'}  4.23±2.29       28767.63±97942.81         31377.52±80266.69                   2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e-06'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e-06'}   12.24±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e-06'}   6.68±0.16       7.19±0.24                 7.05±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e-06'}   6.20±0.18       7.09±0.24                 7.22±1.26                              1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e-06'}   6.15±0.37       8.29±0.57                 8.17±2.23                              3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e-06'}   7.79±3.07       16.76±9.43                20.23±23.26                            8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e-06'}   14.56±8.20      666294.76±1085454.30      680327.87±1406415.19                  25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e-06'}   16.49±6.61      1457113.05±2628533.63     1599570.70±4195521.58                 72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e-06'}   29.33±7.13      6041315.56±17574316.89    1655315.13±3849004.44                232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e-06'}   11.00±2.32      1285492.67±1382227.34     2739226.17±6246609.04                725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e-06'}  6.16±1.78       9101.38±27905.46          18973.50±68577.72                   2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e-05'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e-05'}   12.24±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e-05'}   6.68±0.16       7.19±0.24                 7.05±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e-05'}   6.20±0.18       7.09±0.24                 7.22±1.26                              1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e-05'}   6.15±0.37       8.29±0.57                 8.17±2.23                              3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e-05'}   7.79±3.07       16.76±9.43                20.23±23.25                            8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e-05'}   24.00±21.96     396580.77±935624.27       436681.02±1305422.44                  25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e-05'}   26.93±10.50     719184.19±1255055.43      757386.18±1938474.06                  72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e-05'}   49.15±16.97     2056244.87±5452106.50     622762.23±1425880.40                 232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e-05'}   20.07±6.46      509216.38±591028.11       1177808.88±2574864.71                725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e-05'}  10.96±2.26      5223.19±10767.41          10426.05±34723.16                   2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e-05'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e-05'}   12.24±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e-05'}   6.68±0.16       7.19±0.24                 7.05±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e-05'}   6.20±0.18       7.09±0.24                 7.22±1.26                              1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e-05'}   6.15±0.37       8.29±0.57                 8.17±2.23                              3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e-05'}   7.79±3.07       16.76±9.42                20.22±23.23                            8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e-05'}   49.97±67.08     162824.63±442483.47       193334.69±682253.16                   25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e-05'}   50.67±21.36     268320.35±507272.71       306573.08±774306.83                   72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e-05'}   68.32±48.95     607369.04±1351612.21      208831.17±449390.81                  232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e-05'}   38.37±14.69     190031.76±204700.51       446898.47±1131185.33                 725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e-05'}  21.67±6.28      7477.69±18764.36          8093.20±16724.47                    2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e-04'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e-04'}   12.24±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e-04'}   6.68±0.16       7.19±0.24                 7.05±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e-04'}   6.20±0.18       7.09±0.24                 7.22±1.26                              1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e-04'}   6.15±0.37       8.29±0.57                 8.17±2.23                              3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e-04'}   7.79±3.06       16.75±9.40                20.20±23.16                            8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e-04'}   120.60±204.01   52249.37±140086.43        61960.47±215015.22                    25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e-04'}   102.40±56.35    83768.34±158650.57        98807.95±245560.62                    72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e-04'}   98.31±52.27     294555.23±597227.83       98642.94±195947.83                   232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e-04'}   57.37±30.22     106433.92±180480.28       151201.59±324276.36                  725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e-04'}  42.51±15.38     10945.45±25172.70         12691.29±27081.34                   2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e-04'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e-04'}   12.24±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e-04'}   6.68±0.16       7.19±0.24                 7.05±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e-04'}   6.20±0.18       7.09±0.24                 7.22±1.26                              1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e-04'}   6.15±0.37       8.29±0.57                 8.17±2.23                              3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e-04'}   7.78±3.05       16.72±9.33                20.14±22.96                            8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e-04'}   160.89±295.38   17165.24±44149.78         20451.68±67083.67                     25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e-04'}   232.43±206.39   44774.41±98654.90         34688.16±76919.83                     72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e-04'}   182.11±91.65    110779.47±220165.49       39011.44±69382.34                    232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e-04'}   79.10±45.60     36947.73±56989.06         61635.99±144492.07                   725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e-04'}  79.94±26.56     11686.93±19794.74         23831.30±60759.82                   2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e-03'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e-03'}   12.24±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e-03'}   6.68±0.16       7.19±0.24                 7.05±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e-03'}   6.20±0.18       7.09±0.24                 7.22±1.26                              1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e-03'}   6.15±0.37       8.29±0.57                 8.17±2.23                              3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e-03'}   7.76±3.00       16.65±9.14                19.95±22.41                            8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e-03'}   69.36±110.67    5435.24±13652.03          6411.24±20375.79                      25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e-03'}   338.37±336.39   64646.91±223551.84        45531.12±167398.80                    72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e-03'}   343.69±232.05   48959.49±120090.59        14998.04±21814.87                    232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e-03'}   147.85±95.87    16983.59±22186.43         26384.78±53057.64                    725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e-03'}  177.51±74.16    8176.40±10135.99          16036.39±31549.18                   2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e-03'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e-03'}   12.24±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e-03'}   6.68±0.16       7.19±0.23                 7.05±1.42                              0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e-03'}   6.20±0.18       7.08±0.24                 7.22±1.26                              1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e-03'}   6.15±0.37       8.28±0.57                 8.16±2.23                              3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e-03'}   7.72±2.90       16.48±8.71                19.53±21.22                            8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e-03'}   36.55±37.73     1783.74±4000.27           2043.99±5784.29                       25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e-03'}   189.96±221.88   6336.93±8205.70           5975.96±15103.53                      72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e-03'}   479.36±476.63   14627.41±19259.61         8409.14±12854.97                     232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e-03'}   275.00±232.55   7829.82±6735.56           15264.85±24500.36                    725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e-03'}  374.29±203.96   7580.40±7542.70           14049.99±27759.82                   2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e-02'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e-02'}   12.24±0.21      12.69±0.28                12.54±2.02                             0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e-02'}   6.68±0.16       7.19±0.23                 7.04±1.41                              0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e-02'}   6.20±0.18       7.08±0.24                 7.21±1.26                              1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e-02'}   6.15±0.37       8.27±0.57                 8.15±2.22                              3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e-02'}   7.63±2.75       16.15±8.03                18.82±19.60                            8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e-02'}   22.92±15.11     540.81±1033.67            549.20±1382.11                        25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e-02'}   139.07±285.28   2916.68±3776.93           2263.99±4236.43                       72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e-02'}   423.20±586.91   7064.28±9142.59           6929.34±15611.24                     232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e-02'}   353.38±333.85   8271.14±19256.89          14166.97±34076.96                    725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e-02'}  481.26±365.02   7481.36±7238.15           17187.15±36691.34                   2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e-02'}   16.84±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e-02'}   12.24±0.21      12.68±0.28                12.54±2.01                             0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e-02'}   6.67±0.16       7.18±0.23                 7.03±1.40                              0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e-02'}   6.19±0.18       7.06±0.24                 7.19±1.25                              1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e-02'}   6.15±0.37       8.25±0.56                 8.12±2.20                              3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e-02'}   7.50±2.54       15.59±7.14                17.98±18.06                            8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e-02'}   19.34±24.58     160.15±279.64             166.65±328.59                         25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e-02'}   78.69±68.64     1055.53±1340.59           888.14±1447.35                        72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e-02'}   282.60±291.26   5461.80±11425.77          2130.88±3538.98                      232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e-02'}   313.54±408.56   3480.58±6091.76           6355.53±9879.24                      725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e-02'}  601.28±405.37   13155.09±25170.58         22935.78±49873.61                   2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e-01'}   16.85±0.30      16.95±0.31                16.82±2.76                             0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e-01'}   12.24±0.21      12.68±0.28                12.53±2.00                             0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e-01'}   6.67±0.15       7.16±0.23                 6.99±1.36                              0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e-01'}   6.20±0.18       7.05±0.24                 7.15±1.26                              1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e-01'}   6.17±0.38       8.22±0.54                 8.08±2.14                              3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e-01'}   7.35±2.21       14.65±5.81                17.02±16.25                            8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e-01'}   43.54±166.01    166.38±635.47             173.68±622.42                         25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e-01'}   72.32±136.77    364.63±333.14             779.68±2476.74                        72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e-01'}   568.78±985.16   9043.26±20642.81          4589.91±10961.21                     232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e-01'}   286.28±271.36   2604.98±3242.36           3347.26±4490.46                      725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e-01'}  651.29±473.94   9181.48±13991.09          13481.27±35395.02                   2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e-01'}   16.85±0.30      16.95±0.31                16.83±2.75                             0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e-01'}   12.27±0.21      12.68±0.28                12.54±1.97                             0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e-01'}   6.75±0.14       7.22±0.21                 7.01±1.27                              0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e-01'}   6.39±0.18       7.18±0.23                 7.23±1.37                              1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e-01'}   6.38±0.40       8.37±0.53                 8.18±2.06                              3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e-01'}   7.38±1.74       13.58±4.23                16.08±13.76                            8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e-01'}   11.97±6.68      30.97±23.56               38.14±40.28                           25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e-01'}   54.34±107.42    262.85±335.92             365.88±1033.05                        72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e-01'}   121.02±187.90   11348.15±53810.92         2557.30±9692.98                      232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e-01'}   316.30±416.63   2450.80±4898.55           2875.65±3958.27                      725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e-01'}  877.24±937.15   6191.43±7843.00           6849.66±7863.58                     2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e+00'}   16.87±0.29      16.97±0.30                16.84±2.74                             0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e+00'}   12.46±0.19      12.83±0.27                12.71±1.97                             0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e+00'}   7.49±0.13       7.91±0.20                 7.60±1.36                              0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e+00'}   7.30±0.18       8.03±0.23                 7.98±1.73                              1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e+00'}   7.30±0.40       9.31±0.58                 8.98±2.18                              3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e+00'}   7.89±1.17       13.12±2.77                15.43±10.52                            8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e+00'}   9.87±2.18       20.00±6.99                22.90±14.04                           25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e+00'}   25.73±20.58     133.19±175.11             119.57±232.04                         72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e+00'}   132.06±160.66   1623.97±3850.35           570.90±896.48                        232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e+00'}   127.83±80.85    745.14±592.64             2531.26±6398.94                      725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e+00'}  463.51±514.05   3194.71±2356.43           5798.82±10386.42                    2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e+00'}   16.96±0.29      17.05±0.30                16.92±2.70                             0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e+00'}   13.24±0.18      13.53±0.25                13.44±2.17                             0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e+00'}   9.55±0.14       9.95±0.22                 9.47±2.02                              0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e+00'}   8.96±0.18       9.68±0.28                 9.66±2.06                              1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e+00'}   8.84±0.32       10.86±0.60                10.43±2.64                             3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e+00'}   8.55±0.56       12.85±1.36                14.45±6.71                             8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e+00'}   10.61±5.29      21.38±23.08               22.26±24.78                           25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e+00'}   17.05±8.33      81.38±164.25              102.04±254.60                         72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e+00'}   41.41±26.79     243.60±340.78             154.75±219.17                        232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e+00'}   109.66±146.58   660.20±1093.73            946.81±1994.40                       725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e+00'}  343.52±311.85   2332.92±3349.07           3939.52±6284.43                     2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e+01'}   17.41±0.28      17.49±0.30                17.38±2.57                             0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e+01'}   14.60±0.21      14.82±0.27                14.76±2.50                             0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e+01'}   11.79±0.22      12.17±0.29                11.50±2.58                             0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e+01'}   10.54±0.21      11.27±0.29                11.50±2.30                             1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e+01'}   9.99±0.23       11.79±0.58                11.46±2.91                             3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e+01'}   9.04±0.28       12.19±0.59                12.92±3.83                             8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e+01'}   10.01±1.39      17.81±7.34                20.15±12.47                           25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e+01'}   13.57±7.66      38.42±63.94               37.22±35.28                           72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e+01'}   27.69±17.53     103.83±89.94              66.13±50.04                          232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e+01'}   107.14±295.36   786.00±2866.23            3201.68±15465.75                     725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e+01'}  301.39±389.25   1469.99±1537.15           3179.14±6952.33                     2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e+01'}   19.16±0.26      19.20±0.30                19.23±2.42                             0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e+01'}   16.06±0.26      16.30±0.31                16.31±2.76                             0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e+01'}   13.45±0.27      13.82±0.32                12.90±2.63                             0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e+01'}   12.18±0.26      12.92±0.30                13.40±2.59                             1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e+01'}   10.75±0.23      12.31±0.54                12.26±3.06                             3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e+01'}   9.56±0.31       11.75±0.51                11.85±3.10                             8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e+01'}   10.01±1.30      16.24±7.50                17.97±12.48                           25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e+01'}   16.72±16.47     40.19±61.00               52.22±80.99                           72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e+01'}   15.74±5.23      38.61±14.46               32.24±16.53                          232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e+01'}   481.31±2376.04  817.63±3659.76            7088.62±37580.45                     725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e+01'}  122.57±105.60   656.91±607.70             1205.11±2471.42                     2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e+02'}   23.39±0.22      23.25±0.31                23.62±3.28                             0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e+02'}   18.17±0.26      18.42±0.32                18.70±3.22                             0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e+02'}   15.77±0.26      16.23±0.28                14.89±2.61                             0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e+02'}   14.33±0.32      15.08±0.35                15.60±2.84                             1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e+02'}   11.98±0.22      13.38±0.45                13.63±3.23                             3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e+02'}   10.42±0.33      12.25±0.45                11.99±3.00                             8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e+02'}   10.22±0.55      14.04±0.67                14.94±4.36                            25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e+02'}   10.85±0.94      18.45±2.09                21.64±7.28                            72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e+02'}   14.00±5.86      32.52±16.62               26.35±14.64                          232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e+02'}   32.00±35.41     85.63±87.93               136.98±240.96                        725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e+02'}  77.63±80.65     363.89±565.04             466.71±564.45                       2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e+02'}   40.16±24.57     39.75±24.61               40.78±26.73                            0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e+02'}   22.57±0.25      22.66±0.33                23.31±4.72                             0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e+02'}   19.66±0.24      20.07±0.25                18.41±3.40                             0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e+02'}   17.80±0.35      18.48±0.40                18.81±3.30                             1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e+02'}   14.31±0.23      15.41±0.41                15.68±3.44                             3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e+02'}   12.74±0.29      14.72±0.38                14.32±3.16                             8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e+02'}   11.39±0.30      14.77±0.60                15.85±3.59                            25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e+02'}   10.83±0.54      15.61±0.99                17.57±4.63                            72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e+02'}   12.59±2.05      27.03±8.01                23.32±12.29                          232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e+02'}   93.78±350.44    553.59±2477.53            965.81±4718.07                       725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e+02'}  39.89±34.23     138.20±147.36             246.54±486.03                       2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e+03'}   37.10±0.48      36.48±0.49                37.03±8.04                             0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e+03'}   42.85±25.58     41.52±22.68               43.20±27.02                            0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e+03'}   25.78±0.32      25.91±0.37                24.39±4.48                             0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e+03'}   23.09±0.37      23.54±0.45                23.67±4.40                             1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e+03'}   18.89±0.33      19.80±0.40                19.72±3.40                             3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e+03'}   17.51±0.25      19.37±0.39                19.17±4.34                             8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e+03'}   14.53±0.24      17.72±0.74                19.35±3.81                            25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e+03'}   12.49±0.32      16.39±0.80                17.45±3.73                            72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e+03'}   12.74±1.07      21.54±1.61                20.78±9.38                           232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e+03'}   17.17±8.35      39.19±21.94               44.33±32.57                          725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e+03'}  22.19±17.09     70.48±60.81               76.03±82.98                         2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e+03'}   54.50±0.54      53.97±0.54                54.52±9.90                             0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e+03'}   39.61±0.75      38.89±0.85                39.85±9.57                             0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e+03'}   40.59±26.30     40.22±25.78               39.52±29.03                            0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e+03'}   30.19±0.48      30.35±0.53                30.63±5.57                             1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e+03'}   26.51±0.39      27.13±0.37                26.51±4.77                             3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e+03'}   24.41±0.43      25.94±0.54                26.39±6.15                             8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e+03'}   19.95±0.32      22.36±0.78                23.92±5.05                            25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e+03'}   17.48±0.24      21.38±0.89                21.44±5.35                            72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e+03'}   15.32±0.56      22.86±1.29                22.45±9.68                           232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e+03'}   15.05±1.42      27.31±2.33                28.34±11.00                          725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e+03'}  26.10±24.09     67.76±64.00               64.98±74.96                         2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e+04'}   87.09±0.68      86.71±0.71                87.72±9.99                             0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e+04'}   57.96±0.77      57.30±0.80                58.17±10.08                            0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e+04'}   46.01±0.67      45.34±0.68                44.45±8.59                             0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e+04'}   41.34±3.78      41.30±3.76                42.04±6.66                             1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e+04'}   35.62±0.43      35.79±0.51                34.79±6.64                             3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e+04'}   32.85±0.58      33.85±0.70                35.44±8.03                             8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e+04'}   27.13±0.46      29.07±0.70                30.02±7.79                            25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e+04'}   25.53±0.43      28.99±1.07                28.37±6.46                            72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e+04'}   21.20±0.39      27.40±0.90                27.07±11.82                          232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e+04'}   18.26±0.58      27.73±1.89                27.52±7.82                           725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e+04'}  19.34±3.68      41.36±7.53                32.23±21.61                         2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e+04'}   116.85±0.89     116.48±0.94               117.92±10.01                           0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e+04'}   89.90±0.74      89.49±0.76                90.04±9.50                             0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e+04'}   63.28±0.75      62.64±0.72                62.08±9.70                             0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e+04'}   52.47±0.75      52.07±0.78                53.20±7.83                             1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e+04'}   47.16±0.56      47.09±0.67                46.37±6.91                             3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e+04'}   41.66±0.73      42.06±0.80                45.07±9.28                             8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e+04'}   36.51±0.81      38.21±1.14                39.61±10.98                           25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e+04'}   34.47±0.74      37.52±1.09                37.30±8.51                            72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e+04'}   29.21±0.66      33.61±0.96                33.28±12.66                          232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e+04'}   25.78±0.33      32.77±1.67                32.45±9.72                           725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e+04'}  22.15±0.67      37.90±2.93                33.87±17.37                         2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e+05'}   132.27±1.04     131.89±1.11               133.54±10.08                           0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e+05'}   118.42±0.90     118.05±0.91               118.34±9.54                            0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e+05'}   92.89±0.79      92.50±0.75                92.28±10.21                            0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e+05'}   69.75±0.68      69.33±0.71                70.58±7.77                             1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e+05'}   59.73±1.00      59.40±1.05                59.06±7.19                             3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e+05'}   52.84±0.83      52.86±0.75                56.91±10.25                            8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e+05'}   46.90±1.09      47.96±1.40                50.09±12.17                           25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e+05'}   44.08±0.78      46.48±0.96                47.50±11.95                           72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e+05'}   37.16±0.92      40.41±1.09                40.07±12.79                          232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e+05'}   35.19±0.65      40.62±1.55                40.32±10.48                          725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e+05'}  29.75±0.52      40.74±2.88                39.86±15.61                         2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e+05'}   138.16±1.11     137.77±1.19               139.51±10.12                           0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e+05'}   133.00±1.07     132.62±1.09               132.78±9.72                            0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e+05'}   119.69±0.99     119.33±0.94               119.24±10.89                           0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e+05'}   97.68±0.65      97.45±0.66                98.23±7.95                             1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e+05'}   75.33±0.81      74.86±0.87                74.79±7.64                             3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e+05'}   66.37±1.26      66.07±1.09                70.25±10.78                            8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e+05'}   59.09±1.13      59.61±1.26                61.93±12.39                           25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e+05'}   53.62±0.97      54.87±1.08                56.75±12.78                           72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e+05'}   46.45±1.05      49.56±1.20                48.69±14.31                          232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e+05'}   43.89±0.90      48.94±1.24                48.87±11.85                          725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e+05'}  38.76±0.76      47.14±2.34                45.06±13.10                         2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e+06'}   140.15±1.14     139.76±1.21               141.52±10.13                           0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e+06'}   138.53±1.15     138.15±1.17               138.26±9.81                            0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e+06'}   133.45±1.21     133.07±1.15               133.01±11.32                           0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e+06'}   122.12±0.80     121.89±0.81               122.21±9.24                            1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e+06'}   100.17±0.74     99.83±0.75                100.28±7.41                            3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e+06'}   80.54±1.12      80.04±1.06                83.74±10.45                            8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e+06'}   73.84±4.14      73.82±4.28                75.70±13.00                           25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e+06'}   64.89±1.15      65.36±1.18                67.38±12.86                           72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e+06'}   57.58±1.06      59.92±1.53                58.25±13.56                          232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e+06'}   53.38±0.81      58.11±1.19                58.86±13.97                          725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e+06'}  46.49±0.87      53.14±1.64                49.92±12.33                         2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e+06'}   140.79±1.15     140.40±1.22               142.17±10.14                           0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e+06'}   140.39±1.18     140.01±1.19               140.11±9.84                            0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e+06'}   138.68±1.31     138.29±1.26               138.23±11.50                           0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e+06'}   134.39±1.02     134.11±1.03               134.22±10.04                           1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e+06'}   122.85±0.76     122.52±0.76               123.51±7.92                            3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e+06'}   103.22±1.03     102.84±1.03               105.59±8.75                            8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e+06'}   85.30±1.32      84.93±1.36                86.31±10.88                           25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e+06'}   80.95±8.87      80.58±8.35                80.54±15.76                           72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e+06'}   70.30±1.08      71.66±1.46                69.60±11.34                          232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e+06'}   63.72±0.93      66.98±1.47                68.08±12.42                          725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e+06'}  54.77±1.00      60.83±1.41                57.15±13.84                         2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e+07'}   141.00±1.15     140.60±1.23               142.38±10.14                           0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e+07'}   140.99±1.19     140.61±1.20               140.70±9.85                            0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e+07'}   140.44±1.35     140.04±1.29               139.99±11.56                           0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e+07'}   138.99±1.13     138.70±1.14               138.72±10.35                           1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e+07'}   134.52±0.90     134.15±0.90               135.43±8.44                            3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e+07'}   124.13±0.84     123.78±0.84               125.87±7.88                            8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e+07'}   104.77±1.12     104.41±1.13               104.76±10.08                          25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e+07'}   89.93±1.36      89.59±1.37                88.34±13.30                           72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e+07'}   278.92±548.83   237.23±401.14             239.65±386.45                        232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e+07'}   75.29±0.91      77.15±1.06                77.56±9.52                           725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e+07'}  66.13±0.92      71.09±1.41                66.98±15.32                         2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e+07'}   141.06±1.15     140.67±1.23               142.44±10.14                           0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e+07'}   141.18±1.19     140.80±1.21               140.89±9.85                            0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e+07'}   141.01±1.36     140.60±1.31               140.55±11.58                           0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e+07'}   140.54±1.17     140.24±1.18               140.23±10.45                           1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e+07'}   138.94±0.99     138.55±0.99               139.94±8.67                            3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e+07'}   134.96±0.85     134.57±0.85               136.38±7.86                            8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e+07'}   124.28±1.01     123.97±1.02               123.73±9.60                           25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e+07'}   107.38±1.36     107.03±1.36               104.90±13.10                          72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e+07'}   94.55±1.13      94.65±1.17                93.93±9.63                           232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e+07'}   134.82±93.62    143.96±114.55             134.30±103.35                        725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e+07'}  79.38±1.10      82.14±1.35                79.65±14.95                         2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e+08'}   141.08±1.15     140.69±1.23               142.46±10.14                           0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e+08'}   141.24±1.19     140.86±1.21               140.95±9.85                            0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e+08'}   141.19±1.37     140.78±1.31               140.73±11.58                           0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e+08'}   141.04±1.18     140.73±1.19               140.72±10.49                           1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e+08'}   140.43±1.02     140.03±1.02               141.46±8.75                            3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e+08'}   139.08±0.89     138.66±0.90               140.38±7.92                            8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e+08'}   135.03±1.03     134.69±1.03               134.24±9.63                           25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e+08'}   125.26±1.32     124.93±1.35               123.78±11.80                          72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e+08'}   108.45±0.94     108.18±0.95               107.99±9.05                          232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e+08'}   98.28±1.31      98.55±1.23                99.08±7.90                           725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e+08'}  124.85±101.48   124.61±89.46              120.91±95.24                        2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e+08'}   141.09±1.15     140.69±1.23               142.47±10.14                           0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e+08'}   141.26±1.19     140.88±1.21               140.97±9.85                            0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e+08'}   141.24±1.37     140.84±1.31               140.79±11.58                           0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e+08'}   141.19±1.18     140.89±1.20               140.88±10.50                           1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e+08'}   140.91±1.04     140.51±1.03               141.95±8.77                            3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e+08'}   140.47±0.91     140.04±0.92               141.73±7.95                            8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e+08'}   139.23±1.08     138.86±1.06               138.34±9.70                           25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e+08'}   135.31±1.27     134.91±1.31               134.58±11.31                          72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e+08'}   124.71±0.92     124.45±0.96               123.84±9.70                          232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e+08'}   110.33±0.95     110.04±0.93               111.18±8.72                          725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e+08'}  102.64±1.65     103.29±1.87               103.52±9.08                         2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e+09'}   141.09±1.15     140.69±1.23               142.47±10.14                           0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e+09'}   141.27±1.19     140.88±1.21               140.98±9.85                            0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e+09'}   141.26±1.37     140.86±1.31               140.81±11.58                           0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e+09'}   141.24±1.18     140.94±1.20               140.92±10.50                           1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e+09'}   141.07±1.04     140.66±1.03               142.11±8.78                            3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e+09'}   140.91±0.92     140.49±0.93               142.16±7.96                            8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e+09'}   140.66±1.10     140.28±1.08               139.74±9.73                           25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e+09'}   139.26±1.28     138.83±1.32               138.84±11.21                          72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e+09'}   134.95±1.09     134.66±1.09               133.60±10.59                         232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e+09'}   125.03±0.98     124.73±1.01               126.10±8.79                          725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e+09'}  112.01±1.07     111.91±1.13               113.34±9.47                         2509.27\n",
-      "{'n': 0.0, 'alpha': '3.16e+09'}   141.09±1.15     140.69±1.23               142.47±10.14                           0.22\n",
-      "{'n': 1.0, 'alpha': '3.16e+09'}   141.27±1.19     140.88±1.21               140.98±9.85                            0.31\n",
-      "{'n': 2.0, 'alpha': '3.16e+09'}   141.27±1.37     140.87±1.31               140.81±11.58                           0.62\n",
-      "{'n': 3.0, 'alpha': '3.16e+09'}   141.26±1.18     140.95±1.20               140.94±10.50                           1.19\n",
-      "{'n': 4.0, 'alpha': '3.16e+09'}   141.12±1.04     140.71±1.03               142.16±8.78                            3.31\n",
-      "{'n': 5.0, 'alpha': '3.16e+09'}   141.06±0.92     140.63±0.93               142.30±7.96                            8.73\n",
-      "{'n': 6.0, 'alpha': '3.16e+09'}   141.12±1.11     140.73±1.09               140.19±9.74                           25.12\n",
-      "{'n': 7.0, 'alpha': '3.16e+09'}   140.61±1.29     140.16±1.33               140.30±11.18                          72.31\n",
-      "{'n': 8.0, 'alpha': '3.16e+09'}   139.21±1.22     138.88±1.20               137.62±11.04                         232.24\n",
-      "{'n': 9.0, 'alpha': '3.16e+09'}   134.80±0.97     134.48±1.01               135.82±8.65                          725.24\n",
-      "{'n': 10.0, 'alpha': '3.16e+09'}  124.58±1.11     124.34±1.13               126.43±10.46                        2509.27\n",
-      "{'n': 0.0, 'alpha': '1.00e+10'}   141.09±1.15     140.70±1.23               142.47±10.14                           0.22\n",
-      "{'n': 1.0, 'alpha': '1.00e+10'}   141.27±1.19     140.88±1.21               140.98±9.85                            0.31\n",
-      "{'n': 2.0, 'alpha': '1.00e+10'}   141.27±1.37     140.87±1.31               140.82±11.58                           0.62\n",
-      "{'n': 3.0, 'alpha': '1.00e+10'}   141.27±1.18     140.96±1.20               140.94±10.50                           1.19\n",
-      "{'n': 4.0, 'alpha': '1.00e+10'}   141.13±1.04     140.72±1.03               142.17±8.79                            3.31\n",
-      "{'n': 5.0, 'alpha': '1.00e+10'}   141.10±0.92     140.67±0.94               142.35±7.96                            8.73\n",
-      "{'n': 6.0, 'alpha': '1.00e+10'}   141.27±1.11     140.88±1.09               140.33±9.74                           25.12\n",
-      "{'n': 7.0, 'alpha': '1.00e+10'}   141.05±1.29     140.59±1.33               140.77±11.17                          72.31\n",
-      "{'n': 8.0, 'alpha': '1.00e+10'}   140.70±1.27     140.35±1.25               139.02±11.20                         232.24\n",
-      "{'n': 9.0, 'alpha': '1.00e+10'}   138.98±0.99     138.62±1.05               139.92±8.67                          725.24\n",
-      "{'n': 10.0, 'alpha': '1.00e+10'}  134.19±1.18     133.93±1.23               136.11±10.94                        2509.27\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "calculate performance: 100%|██████████| 13530/13530 [10:30<00:00, 12.45it/s]"
+     "ename": "KeyboardInterrupt",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-1-2b1121e86472>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m model_selection_for_precomputed_kernel(datafile, estimator, param_grid_precomputed, param_grid, \n\u001b[0;32m---> 15\u001b[0;31m                                        'regression', NUM_TRIALS=30)\n\u001b[0m",
+      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/utils/model_selection_precomputed.py\u001b[0m in \u001b[0;36mmodel_selection_for_precomputed_kernel\u001b[0;34m(datafile, estimator, param_grid_precomputed, param_grid, model_type, NUM_TRIALS, datafile_y)\u001b[0m\n\u001b[1;32m     76\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'2. Calculating gram matrices. This could take a while...'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     77\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mparams_out\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mparam_list_precomputed\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 78\u001b[0;31m         \u001b[0mKmatrix\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcurrent_run_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mestimator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdataset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mparams_out\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     79\u001b[0m         \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     80\u001b[0m         \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'gram matrix with parameters'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams_out\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'is: '\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/untilnWalkKernel.py\u001b[0m in \u001b[0;36muntilnwalkkernel\u001b[0;34m(node_label, edge_label, labeled, n, *args)\u001b[0m\n\u001b[1;32m     45\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     46\u001b[0m     \u001b[0;31m# get all paths of all graphs before calculating kernels to save time, but this may cost a lot of memory for large dataset.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 47\u001b[0;31m     \u001b[0mall_walks\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m \u001b[0mfind_all_walks_until_length\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGn\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnode_label\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnode_label\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge_label\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0medge_label\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabeled\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlabeled\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     48\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     49\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/untilnWalkKernel.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m     45\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     46\u001b[0m     \u001b[0;31m# get all paths of all graphs before calculating kernels to save time, but this may cost a lot of memory for large dataset.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 47\u001b[0;31m     \u001b[0mall_walks\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m \u001b[0mfind_all_walks_until_length\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGn\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnode_label\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnode_label\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge_label\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0medge_label\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabeled\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlabeled\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     48\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     49\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/untilnWalkKernel.py\u001b[0m in \u001b[0;36mfind_all_walks_until_length\u001b[0;34m(G, length, node_label, edge_label, labeled)\u001b[0m\n\u001b[1;32m    119\u001b[0m         \u001b[0mwalk_strs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    120\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mwalk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mall_walks\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 121\u001b[0;31m             \u001b[0mstrlist\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m \u001b[0mG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnode_label\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mG\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mwalk\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mwalk\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0medge_label\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mnode\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mwalk\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    122\u001b[0m             \u001b[0mwalk_strs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m''\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstrlist\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mwalk\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnode_label\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    123\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/untilnWalkKernel.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m    119\u001b[0m         \u001b[0mwalk_strs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    120\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mwalk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mall_walks\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 121\u001b[0;31m             \u001b[0mstrlist\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m \u001b[0mG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnode_label\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mG\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mwalk\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mwalk\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0medge_label\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mnode\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mwalk\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    122\u001b[0m             \u001b[0mwalk_strs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m''\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstrlist\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnode\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mwalk\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnode_label\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    123\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/networkx/classes/graph.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, n)\u001b[0m\n\u001b[1;32m    438\u001b[0m         \u001b[0mAtlasView\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    439\u001b[0m         \"\"\"\n\u001b[0;32m--> 440\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madj\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    441\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    442\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0madd_node\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnode_for_adding\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mattr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/networkx/classes/coreviews.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m     80\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     81\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__getitem__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 82\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mAtlasView\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_atlas\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     83\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     84\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/networkx/classes/coreviews.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, d)\u001b[0m\n\u001b[1;32m     43\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_atlas\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'_atlas'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     44\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 45\u001b[0;31m     \u001b[0;32mdef\u001b[0m \u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0md\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     46\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_atlas\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0md\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     47\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
      ]
     }
    ],
diff --git a/notebooks/run_weisfeilerLehmankernel_acyclic.ipynb b/notebooks/run_weisfeilerLehmankernel_acyclic.ipynb
index c318d29..baa12fb 100644
--- a/notebooks/run_weisfeilerLehmankernel_acyclic.ipynb
+++ b/notebooks/run_weisfeilerLehmankernel_acyclic.ipynb
@@ -16,7 +16,7 @@
       "\n",
       "2. Calculating gram matrices. This could take a while...\n",
       "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 0.3643152713775635 seconds ---\n",
+      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 0.34269118309020996 seconds ---\n",
       "\n",
       "gram matrix with parameters {'height': 0.0} is: \n",
       "[[  5.   6.   4. ...  20.  20.  20.]\n",
@@ -30,9 +30,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9d47a3b0f0>"
+       "<matplotlib.figure.Figure at 0x7f5d85ce3160>"
       ]
      },
      "metadata": {},
@@ -43,7 +43,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 0.8394806385040283 seconds ---\n",
+      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 0.7666378021240234 seconds ---\n",
       "\n",
       "gram matrix with parameters {'height': 1.0} is: \n",
       "[[ 10.  10.   4. ...  20.  20.  20.]\n",
@@ -57,9 +57,9 @@
     },
     {
      "data": {
-      "image/png": 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Ft/RqmuKCFBRb8SjYCJtw49BdHIDI1YREgYEY8ytQSDdAoerKGyrL0v9+FwTxj0K6kf0TKMjTlCLycppknfZ5BJvDc3psJqvgmAuCZcbg95MhPZliKQUsDYJuAVN7yVIs5B97HvTpD5QbNgLgvpyPmEC87gWnT9NYx0QqG48UkpmsTD6vswwFe7lZiZHPDTHLpDIyNs9j5QGE3snTXTkTVwyPmCc5LcjKGZnISJy5tB4lr8KEwBHwQ31q9Riirz0LQNbdPBfwMa2c9lnOn0tep3yH0SS60HhK8AedcGrTZfnndeJdCOhs178733sFOFdbbbU72cPwLI7YotTYEIXYU06PahEWjSE/BcOmqYtljpl6Eg2lNGTCLDTddyYFXGFrnhoTC/0b0AdisjB7RaYdA1ikKQF9OqYnmCkUUw9Cy471yZCf2BoLMxeS0mzXty4DbiWizUMcm8rUNCY3hOYqhX4zqvGxEKngCHVKVXGau9pibLPv69PYDVwVs2k6tL0KcJOMZdpQ+r48oQFg870IpJ9XS8rnlvc3ivYCAExbV7n5Lrn/+hsq56LCV1Jo4iblbNTXe3sdM2bhBy5eTgSQ/j88dmgO9TkIPR3dn5uER6L/5+O5RyHZg2iM/Ng95T+5+RnQqREWcZpkTiDgWRJtuUnjESiudYjg87QtJW0BlXbC4iKd13vcoMuY6xn0+/q/vja3OGv2XB87Dvu5btO+NxbOZmjVLb9jpfuQah7mNQGq63CMhDWvK5nzK+yyozf/DWNT6rSO0W53vs/YlvDIutb2vT3WOamqfD5/X8Y2nnoBbn1N9NL3lsCkNy97LIBLHVsmYDFXJLC8by6gp4YNbK4LSz5T3OL1ZLF6krDjiZ4Wx/b//g+/hKvv/v6dQLCH5VkYjEGFazKt25K0Gr8gXAFYYBRK1rKZk4xVKAOz9RWZitVjUXLVbqjA17ht4HZTnhS0/Fk9g0yCuhyqddTU+9HvATVJyq6nACsaB0pCwdy34gG9hvSl+1CiUyGAecCKnzQaw4sn1H96qDyg2BZxGEuWio2AsXMCFQXO3ph6HW6MGTCujtEQwOaf2cmCAktG4aUWVhlmqy8An5CnHGJDVcakezkhbBzGU5efqv4Q4feyfysWM54mYHlDmTUp5w2Z3KXr2bEqgSs2hNAT2quYxxlaQrOvJ0MhdFH2BNqr6vDTNjivS1G8kfGUELqE+VyI9+GHMs7YyHqLQrKRMX4gGEcw5UH3IWU9rMniyASQbc67eJ2ljInyMICUUjUg5JsYRQbFCGat5pNsSn79HMRbdRw2lRs7X2VbdB1MKdtimJzTWVvcbL15Jn6tXsRnbTbzwg1l1SeduAC5qdlRnijepUm2RSaP8bRMOJrFkBtWz5HLN7r/HGrJ/IFBzBU7801Msi0WQL7Hd99u15+xzVW4rVnexV0mjMTFUB4GALTfuxTPwvs7FzDNTVxclz2duBX5teErUgSnT3Z/+W61GV/H48hjTZ6Fei6Hp/JYKZyFclNOpx79p5+f2pjldOjkEPo6DFG8YTj373zCUOq39UqAEmawA/YfyrWnT3flbbxrE16IvOq+redzV5t6qjyL+xSSrdmQ1VZb7U72oDwLq8LN82yGc3CXe8QPz+FeXh3v1WCBNOdyGNJ+T8rHpw9OskBKFpsZQxWaZIDOhioGBHNDqIBHDT+67+4AT6VqNBYehJsDl7os/V/xHsx6jrnajhyElL6roEo+dEfAACzEYEYlMMlzIWMSs+ZKYetB+5gAP8OtsOMy/AeXKkHnnAiKDL8r7+VcLLkSssDIyBEWcTYAkGF75vLu11SourEGHClyDh80RndjLMsVqz5EuElA3tA5k4FgIYIRsHkW8n4Vn1A8AgB8ZBDLcfiofA2qeBIA0OxTSMsEJoKfZV90G7pubMSzsTwJN4lnMweV3QRwlP2x4aQoYctZ8BZ3twc1WdxF5v9eqbaEUSioqRPFW9lcjapxiWmqqc+kL3l17Mufrc3Ty4tsRErfZiVu+x0t/Tdq03FDVQXj52EKkGYQdaYAHlshc4XeVczSdzKWNAHM04lSeZsyD1npapndeJcWG9lXaG2m5/5hiNLR38Qe1mRhu2mNdXFHJWP2Og4FzBMnxiKLp0/RTQP3QlOjQE1IOBIXWy9jVhpeLZsK+6/iQbyOA3ET7yELmFi26Cw7lJcXmrVdRgGzbA1VmQlNo6lc2325D0ftBqB0vt3KK4icOR1kwFaVjRPewlsA04GPcifqMfnsTTQHk1VqqGJUApI69QfJjsxrXaw0v5gFndM/OVN0/FxXyyfGtPGSjk26HDoGN939t2qvhcF6jPF5F3sYk0Xj4Z48rqX0Zn09lO5Nl9ciXJPprFH0IGMsaVEiEanR0EJ1F1Po4V5EHH74g/R9LnRs4zWwFb/J+X0RnYmty0Vg3DgQpKaE4HIdydWPPjJqRcfpyQouaQbATZyp0CpeorRvfZI5c5FVFOiQUn6WP9E5gCXtV6U9W1eArbQJN0T4XcCLP3paPS3dhEWIlAVe2nK+3CTvreiLHqvm+InLeSjHIP/7gUFt4kicAEp5ogDEU0J7HfHsX07ShVpHRzJ+u7/5jcBEGE+FVu0HzjyG0GuaUeo0APm/vY5yzk8L0YpJ6izGLeXxttcR42kDisDFD3lMW01RynFNJ1TUvwMjbCjRzsux2/Ovv7umgf2B8zZ1O+zke3q8r77WoLkq49ffYToBaAK4QSYZspP0bOhr/Yt4j+KyFeBcbbXV7mQPw7NgXjYSnvX10A5g6rJnhavUR8PtpsJy1Di4rVOsOV0aTUzcOZCn7H5zVsry8PsAcKFg+31A6KUvRvY8HOWisdiUCk03CkgGAKQN2w2QFVuhJQNaLCbehTL12quI0ImLG7vSZWo8deguwqKIK7YO5OsQQghV6XQadzVs3IIF6SYJA/yAqpRZgLUZ25OKK6uf6dMtesKUUnN5Hz6VSKenp2pA+rE86WNDiUE6oykTUtrSHmvZvpTJp3VHmIKsso4/yDr2M/byhGVX0rXqpgNKBy/bCK2oX+n50hQmBeRx63aDpwysyvkWgpc9hvl5U49Dn/Shp+IxENBeFC8sS/hNwLSt6duhK96ErZBu9kVFy1apfnFJWbeZjdEtGp4q/rj3JZxQWXY/myzy90Jp2uIpg2fKS8jb9gR3CNllZ0fgzsMfQlVpGDsPN4QMbgIyWbBLF0u3BJSiJzgqE0Czj3LjGOAxNkCjHQtSXFwk1WYanT6N1+yDPfKE5UxVb+hdnrT0c1CEA9LyspVq4shgKHIWIC9r5eZ3oZRml3ADaPYRFDUuSaHLwOXmaA0pq7Xnq9Cq1R23bredLASAVDZqWhaAk+9GDGeE6aSAg801w4+M4awwNd0kE4obpV5EGZQScsmEp2MbTwjjqYyXPeCVwdmSsD0vyu/DTsbh95zHHtJkFFu5+duZwO60LazO8RToRzm/oSWwlr7vgMOHpexdrdmlEvixnoymE6B7JSFS+VFxZ3sYkwURqG3BR9KhSuumWcNh24eS5v1BGgL2sS60Ao4yNykUFqEbI6JqMVCNXeT9DiGnCIHy9MgeRXoNKJNTYy4ktWYf84XRXsVU02CO26PoO1aYRRm3LeJySE+4UC8Dp0nRrCspQo2Zddxle3Yb8iSq8ZLsjYycS3g0ngaVWN3iB8cQeClztzUREo/X5egC6rk0EQHlqeymdHNp2UtIN6U9B5nejTx56/KSitTvMyiI19ReIdOoZZ3kLSj+FGQyoQCM3myHGDiINmfMKU6q9qNj1XH5Q5lYMyYSYa6PdKxRXnVyY0fwO8oPFABJdAfwEQAD5Mr+mutyjvI4cHd7GJPFMdMb+6ZmPupFpCxElaGY4s3fUyPzhHZUZQzychOeAKV+gY1WxTzll4d/pJGLMxx+9rVoi15MFbrtlwVb/iDhR+zqJr/HisAqt3em4nxTc5nQztYz6dgyaYjHUWcz0rpxqaUg5xgmfatZKaoLp2ahkS6LPj2FZ8VYcS5u7oubbUVfrGJUdsEn8fgU5ASQMwX5d1HPQMuStuU3c4ERjOdQjYXVYzB1GafzhsUoSuK+/q4eWzOWh8y0RRHO0WPrdFzl636Q5XN18TH16JpO5tcB7mwPd7KY3+xzfoTJVmg2Iq+qCPAtYYjNenBD2aNQ+rE/pEKuWZ/KeNcwxHR+Khdq6XitgixAHa9bMlFsgHYUdF6fJopvvLMwZOTKC9DtAkbyLcoTrLvkaplKzesyfe+jYDVlu28WhugkFEzGKPQm3Jnkfegpb9cNQP8qYtwSxnOqshHzoqo3DUNiW8LF2Er2qXlefsvYEvyeq7Agpps/bGTi1ZAjp7KbfOjJa1uGIW4AhseM5srgOU3KdnAdhjQ7YHj8dmHImg1ZbbXV7mQP17MwDYOAGWYxE9FVcd0sIHPWwX1vuBWzsFkPQDAKCoUWPDxq0OwiprMWIYGKfs/SiZprcRVgiVmMDVUSc0Bi4aUhseF0qAAKgCweqxqR7EieJqcyzsMj6UHRvpoWmAWA5bJ7YhYiNjsLqebuf6MYQI2ms5MnroKi+tsNZ0D/yi16ZFjMIr8PXG1TvQnJLtVuuMbx+fsB4F7JSmVZbACQgJrq7U1b8QooAIcPUjbkmxF+SDTqGWZBjAqzyNJ5qXGRnjPViwh9Cd9CT2gS+KreRuFgyFM/ixxtyrnQcdljtZjF8Fio7fNsiHpVGo7I+SuYhTM1jl88zIIcsOmB66UkN3fHh5jFcFOzHtXMBO7H9PP7UFBrT6Xp7C5i2jo0u5iRbvY3bub4tg+alanBSfm/DiNK9We5wNiV7Ida/yp+JuKrt5mtZmRfYu184SX8YK7n6CYFcwtBCSiVmTpJvCndWG9eCuYmMp8rZiGCvfV35527RFBXznP36u0Yq5KGteeIKsFeHVPVoSxNKipWo+FQwU+A7lX5/5i5AaAZqcoPsjzrkerD6Z7X7jF7GJPFXWwoPAwLuqk4jNtNmRIeth5t5NKl/IjlG5WRcQkKLKlSiIqTThjKPHQjo7k4iEaGKn47h2Y35le12G0KLVdxCocKudenTHcVhO8RGeOpqpmXi49ikX7TJ4zteSnnh2tFLAAYgEaBWFNH4vdTXq+ZgaKhb+sn+1gAP43L2QH9PmDaODTpkFUNKvalk5d+b9pQPg49dhkT8lzTXMcFDqOm4K16Fpb/YD0R3V97bfApIhweSYZm+73CoxhPBFhsdpzPbXcB9C9FtMaK17CTSTB0pQDPKoLH1jA4J0Z7yUlM1066Ai7q2MXLSV5FEC/BHkP3krNnoXyQKQHhOvnunxK6VzVIKfuRiTr09QTVP5cJUrEYoIC3d7GHMVkwL9S9c/ihRCoFK1NokcOQnbT387sRi8rNue6F3hixVBrGzpkb2JKyBJQiLmQiN7J4OlOs2xc2DcCcX3XdDB4mCx3lp2NONaKAquwoX3TNTsA0P0SEtriaKhE/VyTnxglDfFaRGTUTYyaWsGkKKc0UblHgBcDI3oYV6ftazESGOIRCqJrzLKYtyc1haNX5fCo5qSFApfOW+Ga10HIHopkc/Sgq2ZJSNcDrQUMkVwDGVsbEvrjtbiqqVKqYpdsI6bfQ7M20oZz9qdsXUn6fj/+E0F5yyQqhPDimrRb6zc6x0dUIG8B/ynlf0Xiq0wng9+V06QShIUvhlRRS1jHZvbvYCnCuttpqd7KH4VkcaTKUuQ3bI1qbgeFVk7IRzEJSoIlQdYdKPH2y+n0w1Fvrqpd+EyWMuIfPxkaCTbli+xkPIhOaKIcQ6rpK6kxce6uD0F0w3rrM/hZTrcc8Rlc8AbUmAlp0l7GA9L45GEA0e1myyrzA7L6WvbIZN8PyIuZjzcVlUZ74WSrvkLyKVtiWb2NyjorHqGSvjPEMXIVhuh64XOeZsp4iZ/YSFgG4EaNyg4x/3mRIiWqWsKYl9m9jD2OyCBP42YtKg1OrTP2zlwAAfiSsEhonuOsBMQGflgffXaQrZRgRz7aI26aK47OexRTRXMkVHHoPTjwJAJkr0VzK583FoQJZ91/ZoH01Fk4FFQxFGwIBQHMdqoZBas4QbfT/8VREVykW4VcNB5qEZ+h4VD8znDRVtkXj+cZoPkwbl8ntoR1kAAAgAElEQVRf3UVpmzieOsP3MBMPS8fxaOjpoarJMMtbqngHMuZUjZnqW3QffoxoL8IiOzSduByqhQ6li5YhrClXQys/Zd9lG1XFZeIVhK6M1Y2Mk+9KeDI8KudcK0zHE5e3e3jkcrw/Whp42u7meeGVTCcFhPYHgMxkETYE/5Ize1J5MsqTkO9Trk6NrWAU9bmhPIlNJwV3mU6k3SEAtJeM4clSg8Qf5HexVcxuZOw+JnQvahLXF5aURa355ecdyrIad8p47I+Alxas8wS3m3IJuy7TNoXqRbgpwh9Cwhyc/A8U0lbrq25eOlHYEnUFSNtXY5WSLd5LSl+aEnJvwLzu5ZSeBCaNGBhuSHHxxAajkezNdOIqhL/ZxUUJvC6jWN/Um2fTQrxF0noykcxL1DPNeywTmRTQEfy4LJxTrUwrZDOe+0VGYjgr+/IHRnuV2vxhBloSITa8IHtFT6mnRlm32YvnpdRudjIJuElqRGz6dzxxs+Iw8dxCS9h+r5DI2APtJbB/UgrGugsGLqQQLvSFGelGzsQnnZiaa3k/OjtZyTF2r3iGeaTtv+LsMTTXAnZOp0geazp/j+Tmt2XmbpDlFDU9LMunLaG9AMbzWYn6PWaABzVZVDarMp339JhXlAKoqkq1hwczHXXb7c0eermxRZEpqWopb2I3VvuaszWl5aDPrznkuCq8jyy3b+T/dRIAkOXoVRUKKHRzvws5PSzrNnBjRHNd0Hr5gjzR5mIqUrBklrN6QJw/B4pr313Eyq0VjYoaqZf+EzUrU70CNzKmBNha2nd7ERZy/91l+X5sCVNrXGV1n51OoqJpoesCyL08MwCdWgbMs06bF5IFGW024sDodrHiQ7TXhsFp9CiyZ/Gi9A6dV7dq+jW2mvY0RWPpvQvFs9B0aGxlUtXUq97ckrWovy/8DWTPr3/Owko1z032sjz3Okn7ay9lwuleIHsmQJ0teZ2tAOdqq612J3tQnoXVtKD+uIQPjRN4ewNLxVoiWInehXYxL82BrB4FgCVHQce0qFFBVUgWOwc3ROFJpCY3+btG31L3UbZL1dlfFILlgiKXcJF6u7GlKjWr3a0sSSq2UqhFsK62q2LZoieRvB2ui7usizzvujVv9DsnW+l2pKS9pKjVQueqEnirZaFPvNgA5AjThrDoaOlpMT4XGBGmcMyJCz4fm5KnZPyFeyHnLX1X+1Gl9+OWMC9eK/uol9n3EhKgKiWfj9uOF2lIeRxOMQ7xLCwwzq4OQyggl+LbcDKmdLcWlNlx3NUe1GRRYRY3IP6KWcyLxAAb8wdRxx5javyTXP8+NRmaIrTkKjauKgCz/wMQwpXRBlWNC13PDRHTic+Apu7LEoyqQrK8HUPxTYVdlcYjEhcgT0TpGLYeNKQMDRtiUEdVu7u8PEndKZHHH6IAqgZo1fFK2TxXF180rQBfD3CynHotdNJ+rSykqznA6YeY+RCxpRzKTD1lspCOs7s0E17FAzGZhJGOApz9K0Y0hV8A0F4JqW08cVmFu73mHIYcPiwAo4Yh3SUjpufZeFIK0yiUbIiEIYTuZQlDlNNhAU7uCRw5i9zMszihp0ojQ3gaZTKQ31LCEItBKJt0XpTnRsb+I2D7HarCkC+s+I16FnR+tiRYAYjnG/hnl+CmtBusVzBHbjwLbQDUfXcnnkVTqlQpMtwQRP3KUcYyFLNg56qxKHHLehbNdcDhg1Y6Rmk2w5TzFcZhKXcnSyY6FCAyf2fiSqNCPQvFOe7iWQAp9TsV0s/+Qy/VlW156ssYZiI8ut1oL6iCQWTiz6yBs2yrXiax9us9CxeSMG/g2rOICUNQureCzyQYhO0p6gchZLHKAbBRwroqqV7idEMZUNl6Fu2FAU7TxD5uKTMt9bj8nhcl6pKNqH8DSXHa73JOU1OghffmD5zPlxsZ49nSs5AJpT6nWpcyVxcLPaG5ejvP4uFiFkY16pix94s/OFeAUM1fm1Ly3O8jqXBrdiJ2HjE1Bo6dz+9FLi+WsZAUh1GaWPRGjp2rmJ5AndnQp19sBRi0/TkBuZH0c/3Tdn4UVVdD+puy0UhQdWc31elGtZjClfE03ahUyrCjl7+QnujSMJnhBmGt6p9yE2JTxhd6wpi0HeyySnIuMRC1TiP35zB/fohJSDf9LOmmjl62P27LhOZGzczIJJFDnMSViK0sD51oP4yn4kkIa1FT1PLZtJV13awcX7UwKMrTW2pH0rlsgXbHkgJNHI1pKylWod5bcLJkIeS7lNTCinegKe3QS5m68jPKNUH5PGmJe3Ndty/0B86FZ/Za8wfOBWc62fsDI/aohHKAL7BnkcOQ/QGYYxaN1GPEs01qDPQaz6JxYO/gxim39NOJgAJnFe55taha9b7qH5rwjnSNaYbD78WrmLapEO2qVIXae9guy01zbBWoWc8BC0UsbT4szX9rD2Culymp1HSBpU3oxZ5PmVKKe0L0Dt1FvFGefp5S9eOyQlR0Iji/B457H0CazIyCtk4EVhsjenn6D4+A5tN0vuyYzFBzdajxLNTz8KOoX2WFqjR2PxZvz8rgyXky+wml2jaNGM210Lv15lTz+/q9NCkqHhmgHkVad6wnl/k2tCiNvUwOWYMzqV+5GYuAAuDA+TUvm+lvyge4sz1cz2K11VZ7UPYwPAvnQY/OwTvjIz19AqDM9u5SgjOKEcMPP82An2YxVF1bFkojHW1OrK8Uo3QKY8bVjz6S7SZuQABy7w5A9CgAqR61PR6a64Cw8WiuyqODAsNBQhtd/vJHN/nJWrQP5mXp8trsNCa1fUOEXDR93Kb8vHhaSiKy2gpA0mBIPS+sKSN0PHXVMvVK9PP2WsKE53+krchTtk9FOV7Z//6JL3KAY3LvrbCueg0uAbAGu9Hzqd9v0pM0NuJdWMr41BP6V4wX/2Lq9qZ9NLTMeyzv582CY0O4/EMefi9cA/W8dj9AWaFKQw03CUdBtS60GlUFeS9/0OXx9s9T1ejIuP6YMJ4nAtae4A7AxY8wmmsNGYHxEScvRL7vdzUpbv9Ur7e0nSvC1Q+n6+eaEHsVBi6exLN/LaD71CNszXUwEMYnATQSuGW4fcr6dYz2ucP+Y0b3wjB/Z2HMbfYwJgvwonXhvOo0A3wp1DgmfpN1MfWGnIntas9QCiFfuKFzYGd0NhslzYgMP4UiPSey/Em233T4snoYOcwIJh7u9MekCrjT/xWAiw1ynN5eM0JXiEc68YwndLS/pdyYbrEsNks/02pkFCFgmSi14VE+Zx4IR7QQsuiLphcTNiHhUb2u3sRFkxJpn2asnhDnOpmQkAJUx/NzdW9LwJprTAJJ38HVn8VG5PGBknpUmb35urLPuu5EtTAoAHAlHIqNEMiIzbIe8IeECU2KWtbHMtediL1hV24Z/kDACGkepM/EQNVEIceigCkl1ei0u71kXdyB0hj1QBan60Zbw5DVVlvtTvZAPIs7mCVHGcBR+Q6xK31DNESZ04tzR/BQXHjyUoTV7JdKy1ZgV1ZWZLpkJXLT3PSk1T36AdmjqGXpyjL1hKZNSgs2JaPAKVuh6cKcxzdaBvYJzp4QaZ6FKU95656HvvZw9Nhkvfr8shln5XH04iHkJ36jAJ7pG5LFf8R9prYGOt1oQhVfvC2bTvXJK5AGTWldV17ZlfX9oCAvwHpcUao3p63QnJW/odmL0Be3PsvhJRKVlc4TUV42niflBj/sS1gBB8SW4XeFK8JOQMzmYH7fVrfLiB45ZCl9QwrAGjqguSr6FNkTunIIpxE0ld+FgiznhuEOznghQNwwmsv6Gp83gb7NVs9itdVWu5M93MnidTyLRrgIQpKi2RO1JlId3XzKP2e6c1tvw4JzoaOqq5jyMyxFe96zo6ogTfuSoiFkgFLBVUssUk5GXm+GTaj0vR9i5h1kqb05M31RPVpwgppsZdYby2cKos7TtMpFqMZmvJrMqkzcjtiW8WnTJAoC1vqRSxm6oY7b8VFA7h6ucoTKvZgL9sbOeBVpW27gjJNYXUo3cLU95U/kRtihBlD9vqSeqxRkLJ6KHoe+V/Znc43cTIiifIcTFiPp3gIcW5Ur/bzZmW1M8pfHtaP8p82X/Z6q37K9EnzFtg3QY7yrvVUYQkTfAHABgUkmZv5JIvoQwN8E8CMAvgHgZ5n5+Wu2BDQNYPud2hJxYKGnqdwJMMv/tiNZsoVwr51QlCk3zPgVygnIoi5FdEU/16ZEeRk0I4IMcLInA+Ap6Fkubh/LeK3atRXI8Sk7opqbgACfSoayJiSz+QRQcwXydg+me7lWVqZS9NjW25gzS6t9zlmnaULQCkpLJrXbzQzErkzWQplON4qdg2L9CpSbhGL5X22u7SC9auUczj/Lqu1GcMYN6XfY1TeShiwZMBzKDa6kqnwcu5og53dGmlDX4/KZbDAtTyEFzTJQVuTGnkd/NQu1D8ebFoWNSB7Evj6uz5vB+aeZ+SeY+SfT+18E8NvM/GMAfju9X2211b7g9i4Azq8D+On0/68B+J8A/Me3f2WZOlXLGhWz6k8FLy3PIgOc6al9G8BZtiNAYrOPFQ1bGIXFTbXrW+GaDHCmV7vH3GbOAJxatDT1RfkpA5woRVLtjpNIbEqdKqMxVY0y0QLgtABqPra8zt0AzmpZ3u4RgNPPAE4UT2MOcFIEyIjM5G3YY6DbAU6KdSWpHF+9/9sATtGBqAHO9qreRm6oTEuAs0jlFe6FBTjz+UsApzuYc9UwmKnyFrLeRF8DnMqzsMVloUPuD2IBTnY4CnBiInDDoMkUAUIATgXiyxdwZ3vbyYIB/B2SLsL/DTP/MoCPmflb6fNvA/j49ZtZhiE5/r0pDEliMOwd3BAEp8hhiNKMbw5DijvJcFQmBSsSo/z9ectBy6fQLACQbgoj4V/wAUN7TmP0RmJfJPU0Vq3DkNBhFobE2SRQzteSPMXwR2JSmxnRzzUM0f0V44pUpuvqDW1DAi36ymEIyrZtGJLpyjO8Qcfih3o5gFQ8VvM0YpvOcaGxiGy+qUSV+gvkMMSWwEvZeE3yUj7IvIZCwhBbR5L4FCGVo9swJNShgN8RplMGtSXMQMIt/J6kubTTcZVr2I3lIcMNEJqCVwAyCfkrh9jXpKzYpWsrTRiATBTukLgWNtr/HCeLn2LmbxLRDwD4u0T0D+2HzMxEx5MzRPQLAH4BADb+/C2Hsdpqq71re6vJgpm/mV4/IaLfAPAnAHyHiL7KzN8ioq8C+OSG7/4ygF8GgMfdD/DrGJxZ/XsUpqYyOLkh0CTNjRX0VI9C11FTbwQhlJ4dvcN46nJTmcJolFW7q1D19RhPHbqXU16m2/CHmF8Bycnrk0gZk9RSBjNt6LH/wFWai4B4G6GTHiGhl1dA2htq5y/LxJRKzyWfQrM4+n0AGM5dCXs6BfkEDO0uucr8jKeU0Tj7ZJ22oktpu5O7oWgsALbASTQlbBNlQMBaXaaMSNvJCzDl7qHIx1k3PDYl5HBD0rLogdAXoPrs96QV4OHD4s31z6QT2eFJKeLyB8aQhHH3HzHai3RuDsLR2H6XMzV8eCQUb3+QJ7muGztgPGP0zwghCeBMp9K8uNkVarl+dzxjxL6mYAPA+CSi+aac3OFJxMkfOFHz7kRHEwDaC4f9V0fQWL4bO1k+bRnNjvJ5aC4Jw9OA7R80GM+MJ/J5ZEOI6BSAY+aL9P+fAfCfA/hNAD8P4K+k1791h60tsyHJchhyKJOJzUZwTOnTWGjXWgmq5KzyRZsa1Qs3ib6kysCsBJ66oEerGRFZbjIq4QI70aIs6cxEyz4zF7xWQFrNh6FkJFS/0Q9ca0kYDUWdGArWMMv8TCYtZ5ZVKQmz73mmRnt8Duc1ku9MZWlOOU7igrtRVKmAdFOnXelNredCtSCsriZgmhWZscpvUNe8aKo5T6ZcPgsdsqZDHT7pw0ayFVKyTSATNmlDJzWt3aAoKcaq3WTKhpQ2k+k6nHS5WVcJc0o+GwjcpNqZGW6j15wes6ppNReFUNVcSTbFpp4BYDph0OgqfISmMkGEngsxrAHcwSH0daXw56WU9TGA3yC5uBsAf52Z/zYR/Q6AXyeivwjgnwL42bfYx1FTjQcARRxmIUt3O8+i9O8UbYS5ZFy1L2f2lQRsKoDVUzUmAKnGIr0xgrfztCSQYuXB9ggpKUW98HIdSbphJOVrnihUX0jzY6ma5/bL41TTcahVE8e8jD7W51FLtXNvTi7rqcS/tebAGUYK3S2/QeJZlD6gdiKuMRBbvp33ndi5FtzTVG1sy7rqFeXvGgZq6GsWqnpPcl4o15mETo672RdhXPaA25XaEwBgxSY4TfSaMlVGwMb85ltJ5SpnI08i14SwpQrgzMt78Vx04nATYWzFwxkfmXT35+FZMPM/BvCvHln+KYB/8023m7ejvTqUlo1ytcfOYzpJFYj7iPG8gd/H0qejc+ie3X4W9Ik9nhRg1E3FTT08dnLxnJY+lv5Q+nrcxD2w27fiLYBcNPr90FJ186mOw+FJAjIvxeV1IbXKS9vYf+DQv7iN91Dev0kz3NBSVYloKfD2OFSUxRZ1xVYk21R/0mpO9s8Lr8ENR8bPaezzj8x7Le7K4OqM8i6cigTa6SQXyziFUp5u9kcEeiHHdHgqq578AY5wVfRYZu9nl5dODLGVh8R0guxZhBOhf8+zN5wyQKA6CwIIeHn4sPx/LG0xnTBiH+EORhayZ0xK+PJcAbo3jf2u9nAZnKutttqDsodRSOZIFLutnsWsfaG7LJ9RYLQXMlXG1qG9kB4dVpxUBXsrs6nT9G97VfMrMvh2lYC2idHsTDo0KStlqjMjMzctgxPMWSTXKjCptTuTvjRt+dpLk2cf5ElvnwSb56nXBi/DAqEGW7ZpOc4qJXswTxoT/7uJF0xH9rNmvnl5cuMNxdkP8t42JZZxJFxEu6tn7KGUbGf+w7QM1YglvCm9NYwL7+txacdxi4VQZPh9UrxWzGEoT/HuhVk3FRk2OzLgKoDU+Dmnw0NheU7bcs5CJ3yK5hqYNjqm+nwAACKSkDFlbgZQ6NixF1BS/letUSk/z4zTawI7X6VCKRKa61LcqNsFJIUrx3CPfKmxhzFZMETi3y7T6kq94Q0pi30BHikwwtZnurP9/q2krHS+QucKJmDcNuVYAIZarSKvA1X4RGwpq3HnPVKh+EYzWZQWfKYdnxGG0ZjWD6nRzCUqVz83v6Ea5MzS/uaCFFHfdOwVZkHm+HW8yGOs9CJ8AX1tOCLnplb3BgkorKKwWQSnpaw4DZgQzpCyRONT1y+blBuBAJQsSdaAiEsCV0i1IVkXItVJxE5i/wKeSnaCuxI2ZY5GpLSs8Do0hLBVspmU1ZQMUmyBsE0cCQVy+5ogBaTQYhI9CiV8AcicidABOC0Pjs5TAvHLMYeeEc4icOmq7YaEzagUoJwbRtgKZlHpWdzDHsZkQcgS/3lRSpmGUzkzfqxTq9r7k73I5LN3WWo+P9F29XfIaHTmrlaHKBeNkwmi1SxL6lURm1I/Er30HtVOYbIdh2YQAd9miNnjmD5u82SQsyGh3DCSGpWxdBdCtHJTSWWFltBepgtyLCnO/hVj3BKmTd1m0A8x163k42XO5CI7sfQvS9cx/ZyiZDOmE1+V5YvUvd7c6UWLr4wylZZxA4zNp0i/TVlf+17Ycz+clt+qOTBIf4fqSSnnPTMlUStx2RqO2AL9Cy3y0w0AwyP5Tv8pcjev2ADjI8AdCgks9JJODR2w+dROjjLZjeeUPbHulWhwUhQsJqZJnkagfZXeq5d6kZS0qHhFbiQgyroAMuiox9Kagi9/SJmU05TVSeM9fCTqV5Wy+C4J4kQCOgaNZfvdC4fxUVHw0vNwV3sYk8URz0Kb+5R2fzoR1BwKUa2SBsgLYOoOSll68ZQLLoFo+SlY/x87B5pMMyFCaTCUPgOQZe1rK9kO21XbKmVlTka6+dwo+9DxaQs+F+o0a/SpoZBND3sCpwvJehbTxmRd8udFKat6AjqUq2TuvVrcjfW4CDzrAaUFX7bYCkgsVq36TWO1GQ0d91z5ugZVATIpVW2wYzMr6olNJ7NtGzo1IGGOenaTaXVICSR1KW0O1EpZTMgTA/t0TlOYoev6Q33ymABy6rGY3q5aZOfN9dwC3Yv62gFSmnTLVTYkVizR4kG6fcmQVHoWN2TFjtnDmCyOeBZqelNaz8LyLNSroFCyIaF3QGBQuLmRYyFfscjl5fx5iqtP5YyOp3X1aHM5Zhk/oPZsLK8jtF3R4DREqawpOprGyBcR06Zw/61piKJou8rVa+1KPoWBMzdEzYHzOrbBjxLQ9Pir/fXNAt8o+yj/Nweueoe6IK64lGPX2IQVirHbUeVuPUeL7IY5Z2QmXzsmN9TpW63nsbUv+6cScmyf16Sq2CVswTTd6S4MGc54If4g39F9aWNkQLrBqwanPxCaC+DwAWf8wUUJgfRmBQCfvKjmWjCe4YmOV7bTXgiJDADaS8ohkB8KPrL7KqP/1OX0qNp0lqjdfalR4ZbRfyLjVAKZDG55vm+yNRuy2mqr3ckehmcRGbQ71ABnCiEUd1DPg5KHMTwRX7R7MWJ40qJ7MZZMhBJf+lljyiy7FwrT8tTlp7pStgHg8MihfyUCM9qpqrtgTGct/C5UVHLeetDE+RUoT16gAJyhL20EY+9yV3ClcAcvPApAsh7jiaha247eu68QTr4t3pAFWUPvhJdhvILYEMbTdDqNTsbhcVHl1s81G9JeFVXrdHSLKlJ9Ius+xOSpK3TnGv0PW8EL9AnepXPQXpdj0C7nldAxUHqPmBhIAUkFgdXXbq6B/UeSjci41ZRA4k7OXQate8UwkOnPp98UBisFYHjkKjxmOkFFyR/OqYQhrmQYQp/4MVMJG4YnjM33qNK50MrYw6lkhPK5Tcc2njPCaQrBG8LZN5xhFadjOxAOT2POmgDFq6Aon3PyVLoXxauoeqPe7Hwv7GFMFsdSp+nG1tSpf1lcfIqM7oUCnITuxbjIkNhtlO8tA7TuovjWthy7fxUzrpDrKojgUk/SgqUQSAHMwTSscWViUGt3NqVn+lCaH0wJV9HLBDFua+bhybc5VVXWMbCkPXm2rN62mp04qspYVtCw3s5cXh9XyMdYhVhOQpC5yAwn3cc8wbRUvZaxLglvKqhjq0NzfO+AxlZQ+pIGLRsoLM1mKNL3biqt/PpnGm5wonEfqZxV8Zt8TuQ6oyiTo9LIG3X7TeakfWX6i1YVykCjk0xS6W525Zx0zwxDt0UWQrJYylxT076nKFgFAIynjPZKJoqqVP5zont/dhYC8OwFaFtaT/uXckX65+mmPJXP2BOaq3ExEQBA+1yvIsb0eAsKcUHXBiA3/ag5+9LKUIFKAGhfKSZBWScDAMJJg+nEoUlegW1Aa2X0rexc7iw1lL4eVstB+3hUql0JPJw2rgIz1aPYfeirPp3S45MXk4he0JNhk7ZXJo2ZpfBcqT2Yl45rif6svH4yuhh+lCxNMxblr0LD5mpdtd1HLl/4zY5zijIfPwDVudDsi/xmyMcCLjwO9oRmxxXAKSlOmXj9oWSHtPCuvSzewv4poX8hfUNsIWBsheo9PCk3Wp7U0w2sN7vfCQ9ieMxZBcsfgGGrfT/SeTe1POwAp4VoOdVpivwOwO4H5Pta4wLIPrtnDtOpxZgIw1nMDxidLOKGMTEwPgloX5TZhbvZg+AWexiThZqpPOWtTOPqDdgqVO7bRaYDqLMdADIQaXuMlKxKucBUn8L2AMlZjTHCyvWF3qX8dfrBOgdwzP1H8mRxRM+zquUwZ75Uj5bP1eWkWIOZGSCdueuiJF7fkLIPqohOoaVZ4ZPJRvhaS0I/zjwRk0rMPIa2LNNIYerrCcuh6GxWy0dzHtOYbLrV7jP36ED9NGSPXMxWtjPTk0geic1w6P7nlPjpRCbxyfzmKjij/Ud0Pft5JoqhiNWoSVaLct8PewxaNTtvQWh1RWIrmRVtP5jrPQ5H+oY0BdSkqWRkXKqOpUCZWi5fmKe4brYV4FxttdXuZOtksdpqq93JHlYYYs3dPo/NqdzAjM6d/tcmREDBLChEUHB5O6qdad3rvPWBpWt6stARml0sbEZmUY9myc9bFN5SxwFUTYCUOwAUTcy5RxhbwTFita6g4raJEQBT3j4jZTlxaRXUdKHmR1QammFJirJuupKXlKQkEnRlmYJvtncoAHAU0Z85h6JqaER6HlIop2SxrKZuxmrOk7ZN0P2FXrgedlzdK15wPfxBql+jqf7VcneKkv2gqWxD+6JmSnqDXOFKXIOGsS+EL12XpkIwA+S7mGTd2PKizDz20lhIz7vfyTmwwj5uFGEdN5iQyJfwikxZAwUBObUBkdoXj5R1F7My/6/RqsirNQS3K2QtDHrjFiCTvGptLjUpAME25ntTii+AzJrMTERFwK+L3oROAlZvwhYlqb6EBRfzDZBYjoVchaypYe8auYFRKR+pYIz0vigT07xPie4vtsDmBVf1dgEFiziqM2FSgW5M5KxcaJLWY077n2EZpiOZ1quUfqiGaDUywoZyhkKBRzdKciFPIlxPHjpmv0/LtmZ5KAQ3q18RTwp+kPEbRupcVsDyeFK+A8AAp+V91q5oUkcxk1GZl9bPwV+rlakTmD+g6onSXFGqQzGb8rJcv680dHcApjOZcCbLsP3CThaNGc48zTnrI7KoKAXqqlIg9xPJPUaoPKGLl8G57wdQPIrc/8PVzYeafUQl7Iv6NV9MJi2YJ6ZKK8Ei2JyfylmVihkc0/7ZNBU+2pdEtudCfUP7aJYZMR3LxXAzD8P28gDq7WkNlorezPt26LrzFKd6IvM0nRXxnadnizpXoj3vS9Zinq2pJuBhRi2P9Q1sO7lLSrXeb3ONfPNaMNQfSmlAXi9Z6GoKujvU7ykJFtuJLAs0HwAa6chDYuYxdabIMAGYsS/ZFXs+Yg8B2zu7ZFwAACAASURBVI0CV+wp9xSxylorg3O11Vb7zG2dLFZbbbU72cMKQ6zCt9seXUV5Fq8FOCHgpSVluSGkUCQCKsH3WoCzZktOGycAJ3QfJp9uNDSBJcBpAUjbW1UBTitKKwSlFIJ4goOJ4ecNgsy+vWE/Tn1y/akAnAJ43gBwxuMAZ+Zo3AHgBGgBcCJRwY+xBesmQwbg1GrJsRDI5gBnJmopl0Cb8MwBzkT2sgAnDgTHNcCpndwFk6oBTtWcyPySGcBpg+JoMQEUNqcFOLlBDXDO0O3YG0yrK7+D5VkIDb0GOCkCEZywGDbnSujjc4DzPvawJgtrrj558z6mSq6q16lxDG4ImNIrAIyJgBWQLzC5eYRYBaT/gfy+iRL7lf3SAuBU9qYApYm2uy84g735rBaDNtURpt7sB+SUxdgB3BacYTzVeLoGDPXGsQAnu3TRW0BTL1ydVxP9WSs1m0OtiVF17LITY1cmtHJsNQCpx6QAK89+0znAKXF+oiTrhK/ENAcD8ppxmHOr+ETsyg3lD5SFcqfTUvXpxsSS3AAq72oBzvGM0b0ok3xslgDneCbgopvIKGXJvtsL09+0BZoLZCl/QOplaJJ1Y8dVfYccY6kO5VawDQU4rWDv8DTADTbjd1yw1x8IwzbAvXBfEoDzNrtjBkRN2hmmDuvzUu4xVqK09xqG02xEupCQ2gtOnPpevNl272s2mwIkxt9cbJY0lVnUkTS9mOswTEcyf0xI9x0aWVk9Lylol5i06p10rzgrh7+JAPG9xhNKipNi8RAoJbaqugxdp8Uik/FOxqap6Zns4L1solS0Zu6He/zkxPe8Cd+FPW6/wn/qyb9T1YZkuneqMrW1IYtqUjVTVTo92qRUaNGZYO8AloKr6azehk4s9j2wzLqMj1L1q3Xj1TEwDsJ4eiRMWlCxb/58oU0x050YzmulrJyhofqpe0xMxgrv1JkFxnC+HPecer3ol2mWHVOOduH4NTac1bwUTR1b2rc/JJ7BIHoSN42nHB8v6N7HjsWurzadSCMjbX9YhVh6fDre5CXMe6uW1oJ1GKMeheVjqMdk6d7zsFBNJQFtuDJtOW8jH4+trzHbkP2ka9qELb//V38Jh9/7/TtxvleAc7XVVruTPawwJAGcfH66+Ig9IZz1aJ5f3+xZWCNC2Hj4/YTDU/FS+k8PUl3p7zSRHrUcd3NhVPpDxP5DnyoCPx9PjV2R+wMSGWpW2anVl3bZ/gMJlY6xKd/mvLyRUcEf2LPR8SwegFW2eteWBZYb5aOU9/oEHx4XDAAQvoUVDX5nY+v1/Lzd9RX7N//+w5osrJnepsds3scUQNXLlEIEWleFGwqK+v2Usylh46oepSp+o+9t1Sog4cXm2ZTXcxNjPHVZJEcnC9uLVG8I24tU+3oCpffoXC8h9IT+pUjutVcynsNjj2bPqVVBWT9rcxq3OnRSQRl6wiaV7/uDiMAoIJezLxPntoa2ajT0yFdJBSx2QHux7EvqQ7mx88R5IPSvYrUuoBJ2ZT/jOSUdzCVm0VwXzCLMx2fO2XBCC4Dz9JvSw3T/UQE42wvZtvQ2TbIEl6Jx4QdU6/pd6nX6nQIqj+eM6YwxnhGaHaG90HMu4rib7xWAM2xlfxbgHM8FtBwfCcDZf6928nUbum73grJwr4r7tpeE3T8/oXllmgy1snwOcDbXhN0PTdh8q8V4XuIbS6p7nT3cyeI1Hb8WfUyBCgQt6dKifgWWmD62DpbCrD1KtW8pYJiSs7aIqlmhy2KS9B9bqk58jTeUfdkYXU1v0ootOQGgEifPGzbHlupMwJFOWhQk66FsSxmXPA3z8WUueqoloePpVDkXbJYlNaaRF+vpzWeP+xiDM3RUPZU1bteeHHYM9vs2DncTMk6klGgBAksmIzM4Tf9SrfewGEbsigfRXFONL0ySAcsqVRPB71IvDq69C3+oj4tGVL1K9Rh13WOApT+Y4000cXZ1Wjb0DLevT6ocL5cUK5V1aZSGydbuAxqvmMVqq612J3u4nsURngVXfIe78yzyU57eHc9C+Qtz9SvgYfEs5BiKR5Fl5saVZ3EXnoV6LNMJYzqX6uXvF57F6lmsttpqd7KH5VmkqlPaHTKvQo1byWzETSdciddhFo0TMk/qCwIAYevBToR9ncUmKBZgkGrMQhYt4zxbkk5BhF5FbToBaNcxE45sZXbGKqj87wdeyNkpZkGxEJd0ufJH4ix7MW/GAxRmppr0OeVCkU44i4KK3SVXvAge7T7sOVGMxuI5kpVR70m3rdubx+aWTyHHikwky1hC2v10Ip3Y7XbnpsstZqGYhhtrzEL7wErHtXR0ply/2dVYglCt6z6j/uCTjN2M3LajxXlX7y6vd7h5XaAs13W5ATh5IsqXoIngr93ifNAEOKL8qsto59+K2PawJgtr8xJ1Mq7tsabHQFWiLnUeosI9pYZBtI+IGwE4tWx93tB4XqIOqMuvG+ZZOERo9hHjaepKpuERL4lUQL0si64clhdLXo+PfIdL2FHGWJNxAGSWp7eq457gh6LfaTU1phM5vrpxbj1B2HH4sSYJucApfVze230sWLhEOVRTrQ8ldmlII20PGWFLcN89Nqb6HMgNSXC+XuZGaXacb8CR8/JjtTZ+V44j12W45TrOURJLTtsF4NOx5Gsp6jgK81e/45N+5/yG123oumN/5DePSSB41u1MpQOshABFSF3IPJa4R0b6YUwWzoPOz4B94UrHs9SiSS/qy336gLH72gfZM9BCMStcw14k+/tPZXv6SjH1pwyMF39UuBx+QM6A2GbFpddHWyH+7ZVMDNoegFjos80+wg2clz//I+V79klrb+jc6/SSMZzLTWxbJbIrvUdDLz9Ve8WZNWi9EYpJuKarlzUmPZtP94TctVw/7y4ZYMazH/dZ1l7Pz/xClguRsX9anmr+wBjPpMl0mxSebAGY9mydm96o7WVR92ZHphetpFK332Y8//GUBtRO40ngpXTdkhvYWmyAVz8W0Vw5dC+K57X75wR36J47I3rL2H5Heq34QVKWsh/pLnb5h8rEsv0O5SK26x+MCB/KwdFVA3/pcPUvDaCLJBR97TB9ZYTrA+KlXAD+SgaivUj3H6vuRMLKXnlcfU1mC3/hEc4D0EbQlYe/Tmn7P/Uc4zcfYXpcLoR41eD840sMQ4Oum3B9JaDU9uSA6dtn6J/uED4pLdhoe4Rye4M9jMmCGZhmgzZq3gCQZfaiKncrZyIibBz8Pi4xwgUIqnTwkkqUm6soZ5VJgrIojb1wY5LOyy4rUao+pAT6FVAvA6sq8Wdo1lWv0y4BpJ4y4Nhc683AFbg3nopM/TGXPjDq/qcNFqAiYKpRYVLMITW7GVEhWdEAanlZK09v+xm78n6cceq4QSXmMp/kZD+lR2ntMZXKWbt/QCY8bcYs2yKEWbEyO4Y7ODCh+iw2RThG1a79LvE7nHhZdhzaOlCvMQVSSStJo6lx2TAQKXtdccPA4BAjZc8in7dN8SABAFmshoFWTk7ckoRVwcv5UL5JcOCTqXIOqI8IQfYVggOl4o/9rgO6iHFowL7cKHFV915ttdU+a1sni9VWW+1O9jDCkDtYaf5TcAoAWYw3dq50Vteu2jOBHGcANgtqha7URljXUwBSg4U4ILikxG3i8egkNLF8DPlePXaghA+yrIQWGm7k7mmei1KzK7iH5S7MVa4DagSffXHZq3L23rj/6tKPMh5VuD5mVZ9Ow3bUbQL1slzZOhVx3Gp5MNtMY9Wy73weIcfJjgrDM5bvlFAEBsStQyethZm2RYBHuB8SgmgVppsoC9qELVfansJ1oPx4jV0Snhnlt6K9/tgAt/JeGa+yPwLGEppILQyBWwZ7w8TU0GUb8ja5YbhdqjKOpX/pftfBdzGHGoDoPu13HYiA/eQLQxcQzOTgc6hj93cXe7iTBd1+ELkz1xQRWwdnWgyqqvexeL2sVOjcuj3b/i/6ou6koGEGKk35uN4ci1LhCQj55ijUcP2fokmXElc3gIxLxkaBq19JsRQ/8iJ1Oke2qxvXQkIGL5njEZXkPo6vo8c7P+Zccj1PzzmAdmbiMqBozob4Mv5jtHXJJKCsC1TKVfKeFnRmoYDLRKg9T/P6BwK3wJSKs9xB6NQlDUp5/+yR+6ACNe2aImVyEzeccZJcDHcSc/1GUamiNAlKdqtMTOkkxCKkBBZ8RR8Qqp4eDh5+EzDtygWSJwTdS8IneOeBbZD0aWtO8IpZrLbaap+1PVzPYm43eBqFUk0VR4I9VWI2AIDxhm34otCkFZdK8W12M1S8JfDIlUsuIQnnJrk3jXG+zGpwasVo5err05bMk0efrlSHTNob03qYIlGvHphxVXsjEZ/p2ksdSB1HHrM+TaO46c0VFTWpgEybzqQhNqHjEeKR1TxlX0RuqqKsQTkYS0o8ewkjlIClamCx55yCdAeH5lr2Mz0KcIeUdkwhReiNV9fINhzqHqLatMcdKIvcxIYRthIOxz7m7QIAuggcXB3SNnUjofydLoo3MHbpnHDeBu2SN9LGIgzkS3oVkJToNc9EPyEeBQfLBmR0JwMOOw+8oQbn6lmsttpqd7IH61lkQPOGz/Vp7UPSaLTszYRZ3Gb5aUIlv2/LxGMjRVlWZKbR8nKDFxyTpwNmGEE+pvr9XEZvvo7tYKYWOwBXgJ8VZh2VyZuxG6vx3XB65sSxikKu56YzPI98Hstvlb0F9TTaGt+wmIV+K+g+5g89NizM9GQOvoC8VFHhCWGrXJqCN7gBoL4sy+un5RlLGRL4O/Pi3EgIjqsuY1ZHg0bK5Cp2iWNhvdhNwRyCelsjybFGQhwdXMYq0mFHc0ITwO0OBOoZUQWDhgTuG4zC9QEYXB4Hd8nD2nmEcyF0BQu83qOQ7MFOFvNOUZxIWZQ+05tLRV6j6TPaXE1gTwv33/nlzaUKU4BWDMpyf5DwpN+HcrMQIbSUqeRqoZUMib7q9nPIYIVf9Xh8cbenrR4Z8s2iiH6uMFRRHRWtmQGJx8KN2Bb9hWrdrgBpWRsyUtK94Oqm0qwHgOyaU0w9Ng+UCU2A3IwV4Sp95PcyMeTJTQ/VHENsj2dDrP6HzU7oMdn9a7lQ7GNmJobGg2IKCc4mxDGFIftGHgQ90F6ZzFYrYGrcBsRDqlVK3cvs7xFbyViwc+A+ghKrkiIBfQCFBuGk/OCxAZqxhFLcS5hBfUC/HXG40r4R8tKcjuAXwiILJ5OMP50v7nSyJGzaCftteeoo8Yu7CNq5nA3hlrE9OeDKb0AmjLlPQPJgJ4t5HQGF8mi0TYUVvXcjcupU+4X4fT1tksmY2NLqZs85RdpdapZELtBp4wpewoz2OnkyiSIePaG9lidte82ZLr5/Uop2Mj/fMEct9bm9LLUKhS0KIPV/AIsSVj5+V6tZyfq8KEX3Bz5KsW4vluNwo3gr+6duUfZdJmHzFE+iLXYZkJiO17XXFRtRz5qnTtkVJqk/lHqGSgTINPmdTuqCNKY0Dq0BDKmB8ODBRj1qeMxgAvx3ugqDCVtO5eslQ9FeigBQ+6ypvLFmRxjPkAP39pJAsYEbgeEJEFR9igFctPJeJ7eBEE6jlKWnm5cOLq+7v26y16R4xHTRgnSyOXhMJ4ygzFAV3P3KAc9fnlapU54c6MkARwD3oWQ7+oCryw3i+QRYfOUe+MXDnSzmgOaib0gB5pSzULgY6Ya/DeA0qdPoS+GRBTgBRmPccinWIvgx5jBEAU5thmOfhJo6tZRoTZ3qBCfHAsTUiCd36U5aEf7AFcCpsvhuqp/AsQHI1ZNQbG4GOHPj4RnAOU+dVk9TA3DGbglwqrJUzF2+C8DpxnLdFvfe8DwMwDmfrHQMC1VvTp6FSXHGdglwtpcO7Bnj4wJwyrFSnoD0+6HnFM4w/M6A3a1oTijAGfoCcHLLebvcMHgT4C7KQcQ+wl870FQ4ErGX882bANcH8DAT8mwY0N+ShAviJgU40zV08Dj78BrXVyUmoiYiHnwGOHPq9ODQfbDH4aIVADYPbk2drrbaap+xPVzP4har8AyavR5b54gVLUsB4CzRqNoOFxAudyIf6+pQ+5q3b1Sg8lk+QpoClPBT9wmpyFQMozGRwpQjAOdCy+INAE4/U8qqgLyctj2yzCM36Mm7qsIJ4/nFsq8McN6is6DhlZZiB1N8RSMtUpTynYIB+b0Cl+XJTjthhNIGOXB3QyrTN1qgMnZC8DXAOZXCTSmJ16K0jYCTbk9FSZsAN0gp+bQp35EvJIBzBr7yhgto2h8HOLHzmCYPnsoPT03MxCsaBU8BJOwJUwI4jWfxpQA4F9oHVtjGYBYU5TMBFGfrzPUkzDYqObixYBaKOShmUfUvZcEAQueqUnZ16d1YhGOmLRYxusUslMcByEUKThOGYhYDACphiUjvFS7GuDVoedqexvx2mepC2BtKq2n1fxm7TEhaZm4tb1PBW5hsgy4z9HktGbdjmU6WmMV4RtWkqGK7c9EY/d4cs8jnz4r77CiBw+XkDI+lrN/qOTAJSAsu2w9bkaRjQg5BAAlB3EgYHiH74s21PjjkexazoMEtMIvpPGI6LZgFYlmXQ/ktWaX+B5eBTATCeM6gU67CBnoyYBwa+K48CcLgC2aRsi0AgD4gRkJ8MuWwDQDu0/f0YUwWRCL9bxojc6M1H/JLNi/3+TPpOKU3T6F7q4o3e0L3Ylx4F1bxSi+06ElucKoJVeMJiY5mX26e5iAKWEApRQdQHqWhLJeOVjO8gIzHEI/csFN5YsVRvy8eR8YyOqC5FiylOraAI52/jsejPiyXqXDNvCT9mMcCLLEF/W7sUdJ/itk0XBGwFFdpr+xEWu/THhenB8HCc+L6u26SNo2V0lYaB7FMaDn70jEip3TmVjNNqSOZQyaU5X1NELxC9zUADUSNis4JsTMp2yAZCzfo9chyTjzAubYnbT8kj0fTmer5DFJ+DgA4+KJWHsx3HSMMS5fMOUaMJK96DiaHmEheNL4Z+vAwJosjFtNkoTUfOnlQ0r3QnhyAS/8vT0DY1icyC6OMMT+Npl7rLeSGmUwaFZAJQ1Or0RPGE4f+ZZAsie4n1WvYXiC2kU9ppCM3ui7T/8dzyjn+KWkuUBD0ffOpuKF53TMRh20OvOjvEVD3Wg192Xf3qkwktleGfu6TIGx7VetR2PSmPoVya8Hr4moHJI8iAuNj+c1ULwIQJqwem5577RFSxqr9Usr+9XgoWFA2LYt16hQ7YDoT2TnVbHAHh813HMZHjOFpmUGU2TmeGabmIP1A/IFweBqziK4/EKbT1AskjU37hrgDycSwSxNDx+DzCe6F6VezjWg+beBCSZfHE/E8+HwSEPJiJnN2PgKJP0EnE5pPvKSqe8Z4ns7DRYvzjy9x+aLERL4LmC5aoGHEiUqa9LJB8+EB/K0Nwlk5DzQdf6AcsxXgXG211e5kD9azmIvkzjGMTH5ShSdTMZq3cQtmYcuoKYpXQREFs/AljZhdZeYsaa8uPxPVeo6quDVrAKT7wsx1BuSJptqaOQ8f67Luebw/xxVUmLbiKEwoOzSmqde0ZVk3YRYWy7H7k+NPHtKU3PpY0qNI55G98SjMrmOL/GiyxKbM6pzMqxlCaZhsuqhbfHuick5jqt8YKRfJ0FTSu/66rtewdSE6Lp+8I7+jWih5oNzoR84hZQmBsDVYAwAcvJSp67mZJL0azPEiyG/NBw8mLoecxs2jq/6Xc5XS6BqS9BH7fe2RxGi8Cc9lG22UkKWvcY9jIeZNtnoWq6222p3stZ4FEf0KgH8LwCfM/K+kZR8C+JsAfgTANwD8LDM/JyIC8F8C+BkA1wD+A2b+P99kYIpmZ/2HWbpUn6ztFWM8TUK26ePx1KHjpQK49Vas6IplWPo06w5nwsicNoRpW5BvP8YKnBQwLAFPbABOE+vr9uc0Zvt0XzIXE8krpQ1zbL8F+FLIXc48YjkSiOfanEbN2p4/0zLPfq5PcbZe0YT8SNGMB7eSjoxNWZbHcQRdF6Yk5ZRnjpO5JotRSKQ1Ay5qW0krlFPWT6+ZjUqJVGWyNVGeyBRLpkTH5Kb/n713iZEsS8/DvvO498YzMyszu6qrqpvT0+2mSFEaESJhaQyYIGADkgADlDeGvbEty6YXFLzxwrI3MqCNFn5sBAigAUPmwhIEL2xBECDAT8LWSIQty+SMxpz3dHVVd1dVZkZGZDzuvefhxX/+87gRVV095Jg5RB4gEBHnvm/EOff/v//7v1/AO4/+NCi9OwkRwqZ75QtR/j4iAzjlWO7hAF75KMrrRsHCyfAV2cqYiSqMjNaR59DqVkGdEmBjtrpg58ZyBNrBdBo+Y2QK7YiY1UvITLfCOwG/VWSFfwGcIm9v4ob8TQB/HcBvZH1/GcD/5L3/a0KIvxy+/0cA/hyAD8PrTwH4G+H99U0K+HEDkal7M7DJRYnV1abYpLlOUv7NtaW09Kb8N8VCyQcaMzCrDSlzO0VhPKZxN8vwQ+sELgJAtbLo5wrVKuQeNBJ64+J73H+dgZ0hkJPnPYg2hUWbpUc/prAt18YA6LgkhZ/AweaCJiHTpDAvQIAnTzDpHvo4efXT1N8sXWJ29uXgHqpwqxYQARjOB6dqqahwoovTuXopYp1Svj7ViqgqlffztQE02dP5p+gQN1v7Ijyqt8ye9ZSgFVPjgeZSFHkkrgI2jxyqlUBzmQDKDkB34lAtBdQNzSCuBkYv6TrqJb3T8Qn43Z376HaNXmaA8TGiuS+3CvpGoHvLxImzWij0JxYYWYgN/Z8pvCxCLROBNkxYCBEUvZLox+G/v9CwYw9XeaiNjGHbqjbon07hJ2micqsKzdkWnatQ1QbdhhBVfdwBT8Yw5z30y+yp9fsZOvXe/6YQ4r1B968A+OXw+b8B8L+CJotfAfAb3nsP4B8JIU6EEA+99598zkH21L2jZcH5HBw3d4zih5tqLQ1UazPLIUQvBrJ6uZUiAn5hKwHh2MxI2aSmEdBR3TucgqHjEq2YH7fhXMJ7/sSOalpVsjYKiyR8Ng3F2UndOyDwOx9o5InzAVBolQobl7eQLK2y+HAu05c3e0Ddm/kqe3TvA9J8vF+vkvvLkoRepYmNLRI7KvfLJRZzXgiHbIeFkoRDEXIGiPdAB6XPggvpeLK8XEY99zLgGJLOK4agNRKRqmGLJ90bMykLT7sq5cPEexjydiCSNeR1iPB4EW+OHREd3AEpzC5Aoc8mhHs54UuGnKPaQ7C698hDrSSUEZQJHQa4NQpuPGBV1Q7W0A9jTZLQM62CbDzxN/IJ4s0rAfzImMWDbAL4FMCD8PkxgCfZeh+Hvrt21+7aT3j7PUdDvPde5Glvb9iEEL8K4FcBYFQdESkrX866lfUBHrBHLEnoKgnVEjErJU29wfHZ/zM+RklyEV3dkpXBzELgiyHHwiWzO8/wHNai4OXxqdslLgOlRouCZFRv9iMWv99tWNfjUJEhLjeYuya8bm6BAMFfr5JF8aM+oqLL06WnuDAp65TUrIYbpcgNb8PXSEpiZPL/XpqXiJmgsg+/V5eo5bIVsDMHkdUS4VojkS7PZKyeiVxI3ItXPP1tF+qIjDLropOwSsF7Wu7D/kTzBUyIV7Qf9S59JoR4CADh/Xnofwrg3Wy9d0LfXvPe/7r3/he9979Yq8mhVe7aXbtrt6j9qJbF3wXwbwH4a+H9f8j6/5IQ4m+DgM3rz8UrAMBaiKslMErUPXVNKJm6ChbGhIPlAnpjIbv9mbJeJEyiPRtBdhS52BNdyfI5VO8hO8Im7EjEJ3ue5JWDgGYi0c0k6psAwNYSqnPxPSpu+4w7EJ6Iuk3lBX1GL682lJimc2DPEwW9m6JQ8q42BE5uz+UeEDlUueJjC+/RzdI9qFc+5Zow6KiBQzqned1Rvo+UbEbfy/KFAtU6AcLxXHwJZnJrzxBLJVbrxIIFSmwnpbHz7xu+6xCB6tI16G14aic2NeETfShVGfJWCFfxqBcJm2jPHcRzCTOl9HuuYGYbD38jsHtgU9r9cxnPTwR6NwCgJ4DV1B5ynfJ8jPZUYSxkzEkrYhQNAhArTm8I/8utiPdCb4H23Q6ychQZCWzRetKhX1TANMcgBOpJB9Nr6MqgXdMfrh71aMcK8wc3WH02i6vr+s0tjjcJnf4tEJh5LoT4GMBfAU0Sf0cI8RcB/BDAvxZW//ugsOl3QKHTv/DGZwKUIOegXOGwnOF+aUIAWXlCALGsYV7q0OvBnzErO8ifgWyC8CVIaGsCMWOZw5rCdFwG8VByU6R9exTV1+NlB1Atj25SnkNwUURGAuP7kJdHBAiczST++RhO075yYM7WGe2YBZpCLksuLQiEwZrL9dPRo5JXmpxEBG0jvT0SrvxekhuAolQiEZ7EHpgagU+dJoncHqbzTv1MnOLwrxfJrTKTLNQryWUYkttsAEHtGFEA2AsCQWWbiFJ5KUTKuE2/hate8T2UH4z30lIY2mtfyvDxNi59hhNwQfKfJ6a+03AjV2QAeeWpRKET6L2OIGvf6VjaMFfKsu7NnYs3iYb8G69Y9C8dWNcD+LU3Pvpdu2t37Sem3Vq6d16BjD6k+VNYvxcWBVBUHCNwUMJnGapc2YoK/DAtO+hqhv3bAXioN654glP1shJk5M+2TpaD3iXXIRKB6gRo5epXtglh2TpRl30gnjHQmid+SQPorS8Srih0K0qOguAQn08grSq3YyuAw5PVzUBXQ6Xzj9cRLIqcjm6D9B2pTYXfI7OuuPp73qp14j2wHma8pzr1C0e3hSX82GqQQcvCZ0pmbBFEerwFqqUoKogBBDpqJpYx2L2lIkXCUfWyuG5QJauX6XxjMSMPQPoIknpJVohepXR4V9P3PN3e1US7dg0lvmmWyutTOLeoFr/SBJSOXbQs/KIGpqYgZUF6+EVNLpsVRPkG4LeUur5ZjEnUNzT/BQhat3ay+NyKZAdqceSyebEqLKzcNQAAIABJREFUepX/8XkC8hn3QcS6H7kGZq5BgWwfthKo1h4my3y0lYgZq3mOg+M/RvbH50HrdEoVpwHrC+4FnTsRonyVBl4/EdGszwefDVyNvHFqu6sTRiNsynLlY/B1cEm/ktOA5P/XZT9pe6Q+vrZiEgNixugwmpQL7diG0ttlS5MB8zdifk6uvM7zmw+uAq/riMHpNGKuhmwpE9fViDJ4vF/ZA3aEyNpUYTDKHelPIDAw+V4TuY6ZtC7jZyQ8hq7DoVqqeB9cRQOfBnuKdsHRutAe/qa8Ob72EKswWdQeciegdwJeStiAM8hWQJxamC7bVnvIGxHupYALjFDZCujaoFvUQB4Z+UNRvnAofjNoe0lig22i3kWfgWY26CpoUZCRZO8zMDL8yXKMIDuU6ktswOnUpwLuwf3cCjEXt99XJHb5cnksLsNP0zgJlmHYvKRi3gewajfidjkjNY40kQhYe6QoPk8OqfoUKh2GWel6ymvI1bHzZhtRALIc9hQGkAPymquRxHcG2E48vqcBL6yPT8zc0lHbDGR1jCXk50OhWC9JKCcHZKWhicVmE4QKSWy+8oPrkOX3XsREsNziocQ3CW99Cv/yz9El4pzsBNzIwwgUBYZc4+HbAbXABGtFebgGUSfDNYRb+LEtnyny9eMsb7d3sniNZXGw2hhwsOJYaVIny8KzyEwQtaWoyb5lQV+y/SkBNcjkNA1ZFrmqVl4xzEa5/fTbsDgtwKzBMq+DmaN+YEHQMfZ/4FdVPXM1CmUxPl6kQ/O5BRciF6kBSqBtaFnkkxiACI5Gy4JPyYsYQXld8yHXJK83KkyyLCJoGYWQfXF+EsSGZNFeABC9gF7T0z23LIQDvEkW0rCZIxvrk75KAIgrnHmZqo157UO1MVXof0R3SvD985COqpmhdnBbnhnC4B45+FAYOcrzcWPXwgPVuIcRmXaGpXwX6CCzw1mnAGazHVbtFD9q+8nJOvWJPPUmTVgf09b5M4BAlnKfs/VrTkOmpyong/G7lyEh63P0P39fmk8DnMNvbEHEpDSRnqyMPcQnrUjL+TXMyfhxN75vfA99RvSyjY8p5JSz8+M/H44asRoVqYRTGQEiUdE6aT1RPOl/nI21WEmJK7y+YLNWUrq8kfG157u+pv3kTBZ37a7dtT/QdnvdkKEVMYiGvAlm4ZWAapM2pwi0cDtWKTVbAChSxEvMAqkLAKtqJ7N0iFnEsoY+VfY66Nd3ydQ+hFnkArxFmUMW/RUDzKL3RbHlvK9e+gJ8zCX2ovsiiDhFxYrSvc6fJkPMYk8gOFooYdsI9pZEN27E4UifczCzYkp3SKIrOBLxeGLv+BIMVifMgkV61Da5HKLfvwank6s0xCy8p5sRuRcB12DMIokaC8g2JBRGPCUs9wlvkb3IMIsEjDPmJXcy/UeDnB5piGYRPyvQb6uYqZr3++yd+3bbGtAeQuc/xB8GzGLYDoCXn9cY0MwHkHA00bhpSRwSWcZpcdgDWZsQmbp47gPLNMmYLDpRyPqj7Mu/F6K1oQQBp87n15wPsvw8WbGLGxc9cloU98/pTM8iW5/B4OLcshDv8DrYF+c+rwA/IHTxudk6RS3S+WXbu8yvz65PZphFXuQIQBACTiCnZ7dKZhOpCG7YIBU7Lx+Z93HeS0E4C4PcNgmgZLYs34Oo1cH4ziivByvS9yw3JN4Okd0rPk9RTqS+8lSjNC97MLb0DM3LEbYSfmwphOpEOl7toKQHGluUDvgivsXtmiyyZLKhMjfrWkgtIYyLacl5K9S7qySu283Tfm1Q62aVbgb0ZO+LOHgMNToatNy8EOHpQn1mRCUP+0Bn7o5ovWaZnlI+plDnpQBETJPnJ6TIBjRL4sXBwuUaIeKAihwJcBhQALvBoJCl5dIdkVAwA7l8jmYC2LHA+NNyUOdV1HJBGdaMyAc7reOz9VK4lq9j2CJoiTAh1PSud+m8hCEq9uj5ILw4ALTjOZgy6kFK5NQXSxdkOBNv12UWIyXEMc8hTQSRes6WkAIlkeWGqConfgCF4BCtw8JGAr5NQst8TVRLhiNrHnZGauFubGOFbnldUYj4QHSIAPPy/hgAsrGlZfEFYKrbMVkISXkhGd3bHFOAmMFItaZfX1iLzQfHcT12MzgLFUjoPwvk5EI5aucge4fLnx1l+0CMZrBlYGsB1aUcCgBQHdUyNY2Ik42SDMDRgNQXtP3in1PZduEy84LDCuBRKTv+cyAKrrDydSTxZL8Uk6GGlore+MI1oacu9XWT8tg5FRsAmitAvgCufq7898guP06YsAz90c3EZ64UCdzQIMq4BNifJFLZxrS9XofBFKIehjNyg0Uxei6x+VkaUX7LMzoRm2SuFDUYpF4B/qSHb2UUuQEQla3UjYI94ZlUor5QJDQDATMLDxRNqlfm3MQndX2hYiSmf9zh3tkKALDeNug3Ne6drbC4psiDNxLj+Q6jusd6S+ZRvynNGj7t8Zxmye1qhNEJCT6tb0ZoagOlHHbbOlZN/4Vf/Db+35f3cTJOZTLWXYUP7l1g2Y1wVO9wsaNzqKTFs+UR3pqt8fQyjZ+mORAKekW7Azjv2l27a2/UbodlcaDtYQXss1sy123UrhBZslSOTexzD1QB/tG7q9h3FpGNCQQasBXgYrsAuRO2CkDmgNXJ58TPLtWWJivvMz5VZXYONQCfkrzo/ESkVPM7QNmSDMwNsQXblKYu9wHlEzdfj5fTuYRixwOt0NxaAQCrEiAcuSSjkvhFF5m20VsRzXnWoxAW8XHFrE3h948XMYptuUAY4jgwW1P0AnbiynWcAJYaQgF24pJp7gXkNlCyg+muNjIyLO3UJRXtnvQz1VJniWQUVhVBSXy5Kmt3LFeTiA2o2mK7GmErM2pr2I8KLoEJ1kLfh6zUyqHrgustPdpVQzfIIUrhfbS8h0ndY92lH6xSDh8t78E6icUuZbttugqVsvj0eg6l0j3qzJtPAXeWxV27a3ftjdqttSwOsRTzFkNNKgBVqgTZPlfViiOGGf3aVcCQbn1IKcplNVFjstgAcB1iB8AgTFcNwLK8bgYQw5PDqIcK5fUOXd/wPIdamq9aVlxbhaLwMd/ffB8x8iFSKBA+WGN+P0RKQGgC4iKzMWd/9pniVUZB5mLGZS2QkLSlXXGyXvuoms0hRq9CBEEQvpGHHn3tg+BFsCYbwiZYUyKPoIheFHqXai2pBgcAIT10FSrl9QreC1S1gQ/nZo1EPenC8pBm7gnL8F5AKgsRJBckC/9KA8fhX+mgRrR/l5UenNYd1l1dYBaL7aj4vguWw+lki53RqMYtVttMN0YNfqzXtFs7Wey5IYPBmEJryQ1JYbwsryPfZ/49/jE52kDfmaosHJld0nq4LDzqKgIzi7CWSgMor7+ZQofhnKuBG5JpNjD9O15XCO3pbdguUsNBdU4H5rpXZKEOa3zy/oZlDfNjc+OJMXdDfMbn4EHEsvayTfL2uR5Dvh43tUtuSDTvs2ugcyV5/j03iMdHDDtmiRSVgw8GMhUUIvo0Z1a6XkKsNHwNyHkfwUEYQVXGs+JAwqRyjH5sI39BWCoSJNsMcG48/NjCK4lKW5g+/RjNqEPXVjFarbSLGhPcdG1gnEAz6jCqeyxMScNWysGGbEWlLcwuFFAG4rWtuxonoy02fQJLK+Ww7moo6Qqtil2vcTLe4cXNtJgg3B+KRLLXNGEBDPCAvZoSB3ztvOVPS6+wZ2nk++GWIggJ2+DjDI/H8XogxfP3nubxSZvqcAyPJSwgVIpaxAhKT4h9vv6Qq1FU7hqG8l5huJFEfR6CzvYxSGcWHtHfZwvk0PGFo6hGrsIN0AQYJ90su3X4G3A4kKMe+QD3LLJJW6ZcCOYSOAG1lbDKwRtJdUUB+E5SFqhOoV7ZCsIqWA2LQ8A9TRZql8Ry7DQbcFbBholFVg7OSZhWxWMJbeG2NdBLUssC4FTI+3ASndHxfI2gA1RVCxv6dGXhdyrWI2HraLVtMK07dLb8o6+2DWpt0RmFWtMPsusqTOse202D8SQ9OdwXEL+5wyzu2l27a2/UbodlIQBf6VghHUiYBYvcDDU3dSAfOS2CWyAKn5rey8dn/n2II7AbkWqoJj5Cjk/EOh7s6kj2t6kATW6xRA5Cl/bJTXWIT1LZIdHNfbkO4ygc2dEbtobKp/yrap0On9JAKBw0YHDKPlxzhYLMw7VkgUR1lkbAxoSrct/SCICLEsV9i6iXyfeG9of4uBIWkI5wC4n8+IgJZrGPiUuasz0zctpWFZgFELI2fYimiLQPGzAI2ab98WexVYUlJfoQqWJMoRVwUGR1zJOX7I1EBw0hCMsAALOrIBtb4iUegBPoWk0uDGebBmumbXVU5u6kJndLUTSE3RGlHBbbEarMrdh0FZRykNJBKQEbcJPJqMW6q1A3PSWU8XV9AWH+22FZeED0JfHfKwmvJGRPJCq6++nH66cS/VTGz0D68/qQxs35IcMXgJgdahvEF+la0stkguP9RKCfMJsv0KIrkcKsXLimStur1kcXh/v6OYo+2QVCVhZaNVN6QTBmQYxKaTyk8ehO6Dz11sc+KvFHIdi8UA+rTxFGkdaNOpXZcqYuq+3+z2PGHmbsIyjbz13EJbiPQ45Oe5gZvXjf/cxH4hnL9cuWqnzFe6CCOE3ALvg1xIGEBVzj4BqXzPLKwVfh+0kPzAzE2EIE2rO+oZJ9YmzJDagcfOVRLSWEoXCrnTgSyQ2hVz9Os6DsyA2plwJqK+J6fmzhggy/byV8KyG0w2jcwbcSrlVwrcJ4voNf1BCLKq4HIK5bNz18L+F7CSE9hPSQ0kM2FrKxqGoDudLQlxoyCx9vNw1Oxjustk18nYx32G4arLcNtpsEZF5dzFEph81iDKVcfP3hUMoatKhFMehnH9JlTy7ZUU7InhjMAb0L2lZAWfpjRt6B8YEWnkUoEPAHkcBUB1GI9ooDqcMHac5Z/oLLwu8M7rPorJeiwCLySlv59XGeRR4RIZWsdI2xv86iMpnWxsFzz7Utmvxp7SA7VfRFoJejHT3fyxBtGrIrZT5RBlEhWwrJAB5C7uMlQDhO7crvIF5DHZiJO10DLzS89hjPd2h3dMG2p+QM1zgUIrpBoEaPTVKg8iHCkoG9kJ7WkQpVbdCu01Aa1T02QMQsaN++uIaqNug7jVHdE5awpj8BPw/HTR9LD6qxQxciQl77QhbvbLTGYpvYyNwIIM3SJ7TDyWiL5+oYlRoCWG/WfnImi0MJXUiTiFcCPoYfSTdzP9nqFfvOzOKo7s3hWFtmYbqKhGpSWYHQ1/n4vrf/A3fZ63RcUl8SJUlJJjcoj5xEcR05GMhZdCbvY2Wn3G1hRah0bBqM8gAgXOwvJCwJS09pv1RFXyxgzIOEQ52B3DbMGoVAIWjjK1K4yicg4Th358C5KRo4DA565SEA1E2PsxlRpS8AGIzglcfZbIOLsO3mRtO11Q5ipdO1atLEHE9arFhN21LUBXnIOqyzRYO6NshrG03rHpdAmYMxUKSqw2QxrXu8PV3iE31cLJ+PWiwsSfYr5eieSnKv6ppupDUK95sbfFof7d2bYUhUSo/74xW+re8XbssXkLO4JW7IXbtrd+3Wt9trWQz0LIYkrQhWCgEuyCMG2wzLGBZhUA7jBaBOmoQj0P55I1E8zVl4Nk/blj0BaJy5Cgyo5jmY6FNfER5lwlZOEsvKBBb1SERpVcTrcOU1CpcyF/OmsgxIXs5hT6rTMbz34djsa1vAhgzhmMSVZz7yeibd40KDM7xbJLdLWAIN6V6UACdEuF8MYDPfQnkiKWWArG8ldrqOFkTXVhRmF8DFzSTSqeGD5Zm5Bl574lY4wgPyZeglpagzUauT2G4amFahr3ThDq12DVksYfO+VxCNg/MiUrX7nngXq10DKeaRwMWAY2cT6OnDdm5E1gW7F3XT43k7K9yKdVejbno02sI2PVTY32jcYdmNyf3JAM6fPA3OA9EQGaqnczRErZOCjNMC1TqYv7kOQjTrJYT1qK/L2SKfcPrAgVEtMHkR+PmNQLMMx+UqVUcpfVhaj8kLj/ZIYrQI24wFmiVliDbLlB9x81MqTjz1KmzfebiQxVqvEgFs9hGJwXLldD5XtRPojugcd2fUX93QwDNjURCt6qWH2pXK2nWfyFjdUfrjT5+mcgBxHyGSsvzQFVmcqk0Tit6EiaUDhJPojj2qoEqtdkB3TP7+6DPqYyzGS4/NI5ciDeFncDpFiqolXY9tAL1O18CanqoDgZcAsGSmGSBWGmrLxyMwEy80DIIfXwF4dwssa5hvHsUBLE4c3IMW6kWd8kmkx/jjCt2Rh/7WBH7u4n7rC4X+cRfByfHHFfxnGtoBuy8D52/Rj7xYTrD45Ajn7yxwFbJO+8UIp48XmDcdXqyob7Ok81t8coQFjiAm9F+tR/T+2ZN7GJ0SE/Pm5RSz8zVGlcFiOYEJNVC/+uXv4Wvffx8Pz67j/VptG/zCoye4bKc4PVvjo9UpAODR9Br/5Ok7+JkHz/GNpw/j+rNmWBz21e12TBaHoiFRsj2gzVUQT+0MJW2x+pUnRW0KXbKPHJJ9RqWXxWnswvr4J/UK6GYipn33Y/43Iao+5QxCkuJPQKhTAo4jJZNEA1e7tJ0J+TxS5wlc6Ynd3hNBWyGxF9WOxHZVS+eiQ5TC1em88rYnWoMQpRjI8gPlxBFrfPRkGem1LOjeNGky7hFuDWt6ioRP2CaBzP3RvmVSrTKGbRaujcepMzA2I13JAOo5LVIUIQrbePgasOyDe8DMUIZOBYBlDQiP7swWPrpYVcWxRC/Rz8h6aM9Ln99MPHCj4+b9zEcCl6wcbnIK9bwvvouJwXpLEQqme8uKSGJy3kMqC9OVQ7G5t4MNWFk1b7HdNNiiIUZqwImerk9wdnJTWBajusfT9QktNyfoA+nq2foYJ7MtPl3PI/gLADs7qHf5mnY7JgsA7mgCebmK372S6Ocaoxc0u3I1ddUZ0lKY8s+WwpqjK7qJ1drCaRFDqsMmOxeLDPUTATMR0fTu5/wUpe/jlw79JABokgba5IWLxwSAfkq1ROid+qobH7UpOAzrauJJDD+3pz5I2KcB6SUVzGkuaPtxqPm6fUtAdxSaNdk5mDGAcZpUuM+EOpijl2nd3XkqYMPL9VpAbwXqRVmaj0OmAKlZAyFqMjNQn9Xoj1OfWksIAxqUoCxOgCT4m0sRJ01uqkv3xkxIfVttU20N2pbeZY+oRxEtAScg530COLcKmBmM57sEcN5MYL55hO7M4k/80R/i2y/PAQCblxPopUJ/v4cMAKdsBcx5D7FVmL2zxOqCrACxVXBHBqMndSwuZM57zM/WkRHJ9UPl1ODxWws8+cE55JQegONpi83LCeRWkXgNgPmDG6xvRnh0vsBXTp/hH3z7Z+nagovx8OwaTz4+o3XP1lh9MoLaSPiJQ3NGN+Wj56f4Mx9+E799+Sjer2nd46PnpwS+ZmzN7abBV7/8Pfwf3/0Ab52mcWa619CcB+12TBYCENtSvtmHAshRIavPqigNogDVxgfkn/1vWdQCiYc5gFkAyQLIUXfGHPLaFpRi7iPOwY2xihyzyKM3uV+e9xVVt3rmXzBFmCYwV4twbWldO6JJoTgHs38MaZILURDC2kQeG2IWr5P7y90T11N6d6RgB4m7Yb4KvzOXg9flY3OEhMhuIr6nexuuq6i9kmEWGa0agiIX7S5hFn2vyPUQwLdfnmNU0w432hNXRCYcQmwF0EmIXhBmwbkhvYBXhGXE/1CGWXQ6DSPGIYAUBrVWUpQlwwe6LmEWv335CEqX4cxJ1cXrmtQ9bqwAnCDdzSx1/RBmASBiFYyFKG3xfDuHNxKbLk/+wRu3u2jIXbtrd+2N2u2wLN6gCZMl7mScgWpN4GJeS9OMBOreF1J7QMI/gOxJrcjlkAaAQcQ9CEAkbU0GHVVLKtlcgxQIls2aMJNqnTCL7f3E8zjEESCNR/rcXKZ6FX3AEwhTSftgnMFxXdRMf5POLURV8qhRKw4eu1rt4waMWWzfHmSi5pZKFlmRO1opqmhvBVlLtS8sEICYmR2yDFiuaj5GfFxJPtdhRId1Ll2SwitAFSPgcwvAS9heYnOj47rihHa4eTnBhq0I5UkMZ6OBGf0Qrq2gl4qst8umqHamNhL93MfogV4qWNtA9gJ95dDcC+6yE1hvazT3duh29AS3QpH25cjGIB9bB+ttjW1bRfeD3YYnVyeYBVm91baBH1vYxlFUKGTOPn7nAp+uj/YSyR6eXcN6gfmojXTvndZ4sZ5iPN9FUR0AEPrNTYvbMVlICT+uIbYJtePJwU7oFPVyV2xSL+mPw3L/XokEeloGGYeqSRkDMVy53iR5f1tnkY/ex+I8jF94RUK//USi3vK+BWTv4Cp6z6t3sehsHJCdJ1FdENWZffh66WN0QyzC+VXkavRHRI1m8K+5APpZoHDn5fU6X6hzAYD0Ccjtp+mPXy99zIQdyvubCUVh4j76bJLggd0xpuIjK1Z2hH84L2LUhAlf0gh0J1RDlO8NH5S31zskxexBuUdbl2FwGaIfvvYQvYznZ8cO9QXlf+QUeveghVjRRMA0dTtx0Mcd7FUDhInFNR6jhUQ/9WheqohPuJqwlO7cxnDwaCGht6QL0N6TUCHPpNs18BuNyVtryOBGmOsa84crNNpiFSjY3aaG9xQpgfBxsuGB3G1qqFDT1Gw19NhAVxbtuo6KYZOqw3c/fQtnJzfx3ixuxnjv/BI7U2Gke1xsCHd59+ga33j6EA/PrvH0xUn6L+ghU+7V7XZMFgea1+XTqYiGOMSJgQZpYE/mvAXnXx8NYTVlSdEQ5llEPQtLT2+9TSK4rgL6iYRuU/1UL6lPWo9+IqNlUWXhv1ggd0DPjtGQk5RjUgjW1Ij1P3NgFCAAtSwzKCLjNO+zI772zF8+SuULeTlbFvVVec9c7WOV8sj2DDkfJDAc+kYAV0nrZ6GPgxTOo1qW1w4A9SJZTk6HIsVmMOFl+h8McMZ7ZIn1abOno5n5qGlBHQLqRQ1XefT3+8Qq3WjYqwZ+ZCPAqbaCzt0D7bmNk5DsqHp6/VLFez6MhmwuA1IrPdS8x+ZyAsG07JHFzWKCVS/j8dXIwnYSat6jqk2MfEQLY76L4dVq2sFcjGGZ4RvS3H/w8hRnJzcFb0Iphx+8PEVV2YTXAPhuf4bxpMXTFydRYAcA2u4nLRri3D7AGUAuteV/dWkV8GBtrh3aY4nm2sXByE9ROSxElH11cQCIOJDycGR7j4rz9FORBujKRyskDUoBFSwW5VKZRNtk1HGuWJ7xCkiiPyxnEM8CLQHgqBdkeaiOnqwcNehnHs2l2CNlSeMLlyFe/4EHR1GmMANGpQnaknUWuuwETFUOfleR62XzGpweMRls2PpTC3WT8kj0Ssb7wU04xGrmucWUZ8dGFW52D2IhofB7t5TgJayIFG4gRU/kSidS1cwANxpypVE9opndfn8W5f3Vupw05aFJbE3FhPqdwuSUZnNrJfpOY3K6wWZBpqMeG9hOQU/7KDZjdwTMeg+06yReM8sUvd99dAkgkMm0o9Ga1QJ5fHqNxXaEPnND5uM2KmhN511cttiO0HU65qTE+/sFSFl3AOddu2t37Y3aLbEsPOEVWZGh6op8OGHpcWlnZMvLXqJaOzTXaUacPKcnh14zp8Bhdx5CSFn5QsY2ABWf6tXGhbAhuRbsG1dPaZ/1qvSX2yMJ21A2KkA8jWpDQCgRu1Ioko+RlylMSWvJOlAtkY5U6zF5hri93gRXaJOudfqUwqvM6OSWl0PkxlmgwiYrx9aBBZpVT+d1mYClthlmYUR0hTjpK6XVJ3dGdsTP0BsRLalEwpKxeFDecuKT2gqoVhQ4B92nUPdEIoYymb/hQkJcrkdRX6iYgMd9kAnbEOHaXFuR5uZWwH6fOBL2QQd/UVG6+kYmib3KkU7GSTJ5/AWZGfzLsEZEt6nhWwlbmxj6NNc1mrNtrPsR98Hp6tpHa+lmMYnLnrCZ2UmcvkNgVm9VAVCutw1OZolcs7gZY3raoVYsvUfn+daMslM/uHeB716dpfWrN684fTsmi0ONMQvLQGb43rugybBvFClOrOjJBCdSlsz4F5S2Lo2PRYJsQ6QuYUXAHfJoBLk5ZpSRnyZAvfIlKWtAvgKA5ipRqvn4/TwbSCq5A12glPfzNPiYoFUvaT/1Kqw7p3WbRUnKchpwk4Rt5H3C0AQRz3eWuRTZOQPA+DNRsD5dnWjbzAFhzkR1kwa3maSJop8nHgVA7sXopd+L4IjnMhLAzNjDjpP8fhTclczBoMI+QHJ11JoGNEvcyVYQIUz6mIOBTmL8cYV+5mHO+zjh6KUiMHPmEy5yUcGd9cBW0XsAPplMVX9cJ92OM9rIWwGhPPpnoaDQ2ELPe/TPplETQ4bvthXw4VzFzMCDXBSlLdoLuhEMXsp5D7ykG+/mBpfPjuk85gbNnGbv7/3wPh48XGBxk9hudW3wvR/eh2wsXKugxzRDXz4/wrvvXOD//ujdgh6+2R2g+L6i3d7JYlgYOa91Oqhfyq1QwgpgH+tSAAR6xryErO6H7CnvI9eDSIK2ZS0O2ZP+Zl53hFH8vJaHGe/Tm7lIL31JgCcrV+XLhaValTZaBIlc5SXtf09st0OBy3Afp9vT9SSFcAB7VkA/ReGccv1QAFHBigFkL5IFgC7Qv2WWvJbdN2LJomhmmtihwgFyV4LU6ULCPRjgIYfEgtVGkmXBk4UDuiMiXomtSipbEuinHrnwsZ04IAxWv1WR2u0rD2Ek+iOX9D/DesIJ+ImBnyezyXaq+O5aBcxNrK9LOwXgBGynCMfgRWGSdL1MNUyNgJ73sGMLnaW9T0622HRVTFkHyMKZnGwhpYcbp+PVTY/OKpyd3BShVlUdkFJ7Rbu1mIWrVaR4A0CulEU/tNx72UZm4VMClQSCAAAgAElEQVRyCfqpjApZtpbwgkKtnKFpa4H2RMCMRPzcnoiojiUNRVr41c9EKDKUAK/2NFgOM5HUoPqklNVPw2uGpDY1RVy+O/dxeXdELzuiJDKK/JB0oOp8HHSklIX4sqPgWoj0siOiku/O07lIQ8ezo7S8PfVwIVdFlxFq2LGHmdCrO3HoThzaM4f2gSH+ROjrTh0pXWnQ8jMXFbOI2p4KE/FLr8n1UC1dU3/s6P3Eoj9x6E9cEPlBqFMqogK3a6i4kJsbuKPwajzsiYG8v8PsnSVm7yyhzltUa1K6mr2zhHywg3ywgxs76J2AnbmoGaI2ktS0ALz7/gsCQWeGmJdTg2opoTYyrvfu+y8wfvsGzbQji6UjQeB7Z6v4WShPlkAnoZaK3A0j0Ew7iMrh3tkK7719ATEiHoaoHETlcHqeKNnNvR3MqoK4rGG2GnVtUNcGu22Nn3/wFJO6j6/5uKUSh04ULs9uW+NffPu7uFjMUCsbX7Z/8yng1loWOYEKAIQtv+vdvmUxjH4QFpCshHx5tDYsEbtUR7VOq4B7cO6I06UVo1paL4ZeFUVJCKNIIdmc15BrcA51OQFKshoqY5OLIiLuwJYFuy57Jr3Zxy2ECeHJpkxxz2nW9SJYCw7BFSop2xQlGRzLAq7VlNC23aeT65vk9vF5mMm+GJEdJ9eGowuyJxeB8YJotZlUezS6KiGlPKpwG4qCmE5G4RoYEbNHVxfT6IZII2DGviCauSYli338yWk6UenhWwkzy1LUbzQ+/uQ0CtyITIZvuZoU37tNDTG2sFkae99peCuwXE2w66qoq8k4x3I1iWHWblNDTg184yB1qlQ2ne3wg2XCHwDS4JzOdqiULQRwprMdfmfxCEfzTVHBTOo/BJbFXbtrd+12tVtrWexhFoP2JpgFENiZUegmaXMW4jcu+PUio0FnWpdDzKJIOKv2+/Lj03mlbYd9wD7fgpdzUlUufhPFdQYErqEyeH5tuSiO06Uob5Fcp8r08LiPwfnLPtWVzRW8edtDgjuJtZn1NT4yt6XJ+CYBv0gnRucVE74KcRxRfJcdASfeDiwGoMAsgEBN77KEP456VJ6AxrwympEkzhtAL7lVcFsFLxTEyEJyPZBewnaK6ocEE9/3EmpigAqpz8iIWbQ+cScYs7Cdio9y30s00w5+cA8ndY/VrkFTlZjFfEx/qEo5tCElvqkMNj1VL8s1O7V8c8vi9k4Ww3KAWSYiKS/t/yFznUlhAyPQJdBMmmTWM9PSVpxVmliUQPxPQO9SEWZezgI0eR+rQUU3IxOySQSwkpHIn80kAKdNPnjpvPSG9hMLI4d11S6FPwEajMyqTPcMUW6fBWWI0p3CmAn8TThCUeyoKrNHAcBKH+joaYKwiqjbwqS091gAGcRodQOyoL9JepusjE66Hlno06ffgolSObDpq0Fh5KmjSYWBu16ivlAwEw93ZGJUTW0khU2z6mwc9RCGMImon2EkvHbQC53Od2yjrgSkhw2CNKgcCfku63gOorGwq4rUx3nCmxhie9YWurKwIfLC8v9qYuCCCLCfGOxuaqCliYlLIV4sZrh/uoxZrgAxOC8WM+iKqqRxWcWb9Qg/df8Sn17P42QCAF0m6vt57VZNFr7KmGVdGZTPlbO8BPR6X6G4zP0gNa2i/F2wHLwSUeRGtx5VAN/MmDgTtC/axNYSqkuz7+jKY3ciMFrQev1YoL7x6McCo5sUebl5LOPA1VvOVcnEZrJksPELCo+qDFzk86Zwq4+JZBxK7U5SJANgWf2kxMXHkB1dW3ecwOHxZylHRXac90KT6s1P+QJPkW2WL8OKWdtwbrOET+gtAbNeJ+2MvBTk7rzEBwBg98DGpLN6Kej+8EOPb7kMAsMOMOf0n1BBKcuNSX1LZTknzWUQ7+HIe+PRP+6AG43Rkzrut597dOcW9UuVUudPetQf1+iPHKqPa5hAW3cjmijw7hY+6D/UHzNRBejODWYPKDa9vh7DXjaYPV5hfR1CmosKs3dXUekKAKldeQG7bWAFokUhwuB2VzV80MMQK42z968wrTtcbsZY39BN+uPvPsNv//Ax7p8v4z29WMzwc48/wapvMK9aPF2REPDj+9f49stz/MKjJ/i/nr0b1z8eDRDt17RbNVmwWpY7msBLjmoEnoUUMLMK9RX9c73etywSdZlBQAnVOuxO6QceXdpUUoDzFiRZKVxMOcrasUvjfaF9YZrSLXAV4HoajHaUuRTZXMchUlH5GCLL80RIZUrQcqTtnQa5FiKBs1GtypRuCLklA2tMcZg5XW93TDuMpCyTeCURDM49kfwpr9P5ehmWZX2QAGypvRF305chaO5jU5+2eTUpy1VIpnrmHuT1XCFT8l9OyvItBX3NOMkeQvpQd6Q8JzsmS4UiO+E4IkRfOhWf6u1ZEGPaEKmqz2qd+soNvtNy50SqLaqJiu8rX5Cy8n3E2q6Vh/PAqqUfrQqh0lXfoB6VacVKW6z6Br1VWKEBPz9XfYNR3WNnq6jpASAqab1JuwM479pdu2tv1G6VZVG0AwxOfhp/YQZnzazAHzeDU4Afy7eVwalagX6eShJy1qgPaeV3DM7XMzjZomBpu7Zu7hicf9AtqnofEB92WhQDmBvH23PLMv+DJsakQz+lS7e1iBqaVomCH8GtLNAjgFUZMeBBbnONzSwzNtee5MmA+ngS8XsuhN7SOpwfwse0zWH2qjsQbXA1ZakKB6gM9TczHyMiJnAQVKugtsGsz/bFkwlQMijd2EI4vceq1BDR12cTn2VuX1fVHqCohTIC5sim33ItC5YsrwcAaHxRZtBBATUBjLn2pP9Mw05d1MwEAGsb6K2iiWa9/+B55+Fl5Fq4rUpgZtZ+5sFzfFudw1qJlhmdjcPRfIPL6zpuU9UGbVNBWBknwWbSodvUOJpvcDLe4fub8gc8OV7jMoCmzbxFe5UiGMzY7BuNn773HN/C/WLbdWMxGnfYoY7ivM4J/Km3foD//uJPvPoH+Jx2qyYLBjjFtoOYlDcv1+TkUOewDcOAAKJGJxAGWtDCyCnYuXZmUgh/xX4lCgyDtqHoR14yUef7zMVcsr6UYCb2rodTxod6n4w/DKNBOS077+NBlov99DORkak4XdxDSgF4FAlfRTg41xWV8qBepjAJCN3Tzxwy+PMx6tO7bGWsdMZ0bFbLAsrQacwZCv1eSRipsAVNCqZV0A5RV9MElSnZCyD0i3QoyvVwAhc3k0i48iwnLlISW1s3+LYiTc/F9TSVQOwlNruGKrSFyEbfaVoeNDS5j9fl7fLG++B16X75siSikXi+nZeamqG/71V8574fbmjyK5S1DkB/r2q3Y7JQEn4+KZSyzIRugAiCvaycpXYGm4dNArBkihzYhm6CGSfFrLysI7M+VeuweoeFVAjk6hWDnWG/inkHqjgW17bgxoK2vIxdi80DkeLk/Nu4hPZ7lSwOV/sQwsue/mMC5+yI5OpMpjDez0QZ5UEKL+Z8BuFpnzIDQ6nYskh1YcMxZUuu1+axKwV4lI/SebFUYS/gG4fuBClsaQXsGBBzAc9qVFwCYSzRHaeTzPM/8tqhwoRQqPQph6MK+iGdoKhGWBcAhPSotIULf34/p1teBTo0APSVxu7LgKwcxpM2iuv2lUN7T0JWDv0uDR6hPPzElJXGR+TadOcmujdCeVgrsbie4vFbC6zmIStaOsybDtd1D50xKN3xGr1VUUh3Hqqaz5sOs7rFsDrntO5wEUR8R5XBbqphQpiT9/GVL3+MR5Nr3B8navjOVujuadTKoLMaWqYBcFzt8MHbLzBS6WnwzfrAU/cV7XZMFt4DpnwsRtJPmCRkrsGp01NGb31UtBouH1LCc/PdjDOa885HcROW0ufUcDPOq3d5iCDBXy+Drz4OFPCK3tlC6OcpaY2f4nmiGbLwXrUiboPepcxVvSEXyTUAXMIBpBEQfSlpR/eJzr3gfyC5RXlGbLVKkwovZyq6Pe2RV/gSOxXDjbHSWC8gNhJ2ngoSyZ2AnTu42iXZO+ZgzAKOwFW3gkvk61RzVa9ktILyAsLCAXZECV/3zmhQLFd0McwlsKzBKQDfSrRrnWqP1g7nb61ws22iXD9A+RZqTApXhXDNsyn83KC9GEfKtqwc7KrC7MFNfFL3z6ZotwrCCqzmDf74fdIWeLo+wYubKX7+wVN864rcg01X4f17l7jXbPBsTaHM5zd0LpebMS434zgBPJjTNT5bHuGDU9Iof7I8xuPja8yqFp+sj7AMpKo/+9bX8feefwXvTS/jde1shT/71tfxWX+MB9U1vrujc7inN/itq/fwi6cf4WsvvxzXP85rR3xOu4uG3LW7dtfeqN0Oy+JAY19YHPg+pD87nXx5brROadupjLQVEXAV/H+RmISxXyOkuCdCE9c2HTI483cA0DsRowc8JbsmwxVk+pwL00RGZE0MTla35siCbTx0KwqBGm6Hqo/ZyKfY78s/S0OnKdY6VfMCCDMYKEB7GVyTbJmLGpzJDcmb3Kq4brSIcuxBZvyM/HgmWXbrbXmBJjzlmWrtjYyFffLGRCg5NfDsUjmBbtcQNyMXrgnWRJ4I5noJVC6RrEBRD9E4+F5CShergPVWYRKqgrE25qTu8el6jsvdJOIFMtCsm+CqMO6wMwHUDHwJgGjbL9ZTvMAUnUlD9uvrd3BU7bA06b6MVI+vr99B6zRedHO0YaB81s5RK4Nv3dxHlbkm60M8/Fe0WztZDIGXBGRZmgg4QtGEz00KdzJIuReq8yIuj+uoIGrb0p+fMQUayIKEcTPMwo5EDGdyYx1P2wio4PqQuhTTvZOvzoPcVR6KAayZj2SoOAkGPcxqKeArQK/4WPTO2pzcOLwp27KPQ5u5YG5/5IvJBwhKVRJQN5IK8PJ9r7LiOJw16QTQWGBVwY9CaNsJiE6SiC5rOQQwURgBfSPi75GDvHmEwzWuBDeRXB+vgD5EDFj12nuBZtTBBWJRB43RuMOo7jENxKPVrsHikyOoeU/YQgAU19safqOh5n0CEFtJuhGdwr2zVXR3bEchSHvZEFkKgJ73OJpvsNk1VMP0hkKnk7rH29MVvnd1Gov/TOsOn17P0fcKTUP35my6wbqr8fZ0haN6i2+8fJt+m3AtD2YrfLKaAwBOxjs8vTxG32kobXE8I9bld1bn+OrZ9/HdzXm8X420+M7qHLOqxU3f4KimdS92U/zJ0yf4xy/ew9vTxPhs7ZtPAZ+7phDivwbwrwB47r3/Y6HvPwXw7wF4EVb7T7z3fz8s+48B/EUAFsB/4L3/B298NvlxB+HBvCJZXreDBmkpQsuYBRdPPrRP5ihQHc4Ms7ii5TwB9NP0ZJMGUNf7mEV9TZZGfZ0wi9V7r8csZJvYg83lYcxC9gmzaO8lzMJLYmLmmIVs9zELgPAQut7UN3qZRHV4OWMW65/p9jCLWAckxyysJsyCS/8FzMLXHnIRJOd4klQe3VtmD7MwA8yiWhL1WrYZ4BgwC2H3MYuqNujaKkY4hAi1QQBEL752OH9ngZttgyc/yAbVvR0mb61LzKI2EbO4/PikwCzMssbs8arALC6vawgrcF33+PkHTwEQZvG9q9MCs3hxM8WH5y8PYhbfu6IIRQQ+a5rtP1qc4P17dBVPlsd47/xyD7P482//0z3M4nk7w59/+5/uYRY/f/QxfuvqPfzSg+8UmMVpnRFzPqe9ybTyNwH8dQC/Mej/L733/1neIYT4owD+dQA/B+ARgP9RCPHT3vv9RI5yQ9Lf7PdNSC4J4BnwBFOSS94Bh0WBZFm8zg2J+pjOE1kLofhuROp9nDDyjE3xpm7IJkUc/L7HUDQ7BhASvBhMNCOQXxASHbk2KbtgPzY3ZKVj9AMILkem0xm3mzh6HITmGg9YQHZlKBMgroTXPtGX2R1ZfzE3ZBGqksfapl5QohnnVUgfZe6izoRArGYupybmJ3a7ClJ5iMZGFW6h/I/khmjl4sTQW4lK2fid2+Vughfb5EZo5WDCupVy0WXhOh/zURsnkkrZg27IP7z+ACPVR1cDADqr8Q+vP4ASHt/dnMfCx4tq8nt2Qz4X4PTe/yayifpz2q8A+Nve+9Z7/30A3wHwz7/x2dy1u3bXbm37vWAWf0kI8W8C+D8B/Ife+ysAjwH8o2ydj0Pf69uB0GlUyW5TIlneuLK5bn0s/MPWhtOUgm4HxKXEY8jqe4zImpAmFSsC2A2htdllkR0t15uEWTBBirflkK/sE44QK7SPk0XgdVLRNlPSVfAKsIExqTdEpa5WIY2aE8FOCMcYVh9zGvC6tCC8RCwQlGtY2DEBp0BazteiNiVmAaS6G7ExrtOJhC8I+u6Vhx+zeRTwmRFQLRSFQJFIW6rLrLLaw1XkWpVMz8wiCRYFYxbWSCjtIAIfwewqTE7KUGDfK/SLEcTEYDxtI5hphYK5roGRjZRoc11Dznu4lhLGuoCR+F5SwaBFFV0rGYoDMd7BAOWk7jGtE4YBkLL208tjOCciZjGqDLRyOApZn89X5JZMGwLelPCYBNylVhafXBzDGgmpfGSnPt/O8f78As82x+lYoxs8WZ9ASwfjZMQsfndxH+8dXeBbV/fx9jTxMlr74y8y9DcA/FUQ6e2vAvjPAfw7X2QHQohfBfCrADCqjvbcEBnSwtkNUbu0zEugWYaUdQ00y5QaDgTgTInX8iw4RVu1PrIl+2kCKHUw972i6l98LHWAZ0GaE1nNVJQgImML9XUy+70XUfdBrwW8BuS2dC+EoTwO1YpIcBq9FDAToDvEs1jvTyAMjL6SZ7Hie0Mv81bKn6B+Ab0MpCeufr4Lld2nLjIaZSeIOu4AfREAQyZsGYH+JKWj2yCPZ3SJWei1OCjqY0ceaAXGc/rjb1c0W9WTDn2n4YLWpGwstp/MKJrDxK3G4fTxAuttg83LSSRVycZi/nCFm8WEhGZA+R79sykw4FmoiSGexbslZkEUbgF3vI74wqfrOT69nuPD85e43NFNf3p5jK88eoaR6mPUhIsDfXo9h1IOoyBgk0v4VyFSstiO8MHbL/Ywi186/w7+txcf4iv3nsb79TuLR/il8+9g42pMZIfvbwmn+dOPv4/fvPgQ//Kj3x1gFlnpvM9pP9Jk4b3/jD8LIf4rAH8vfH0K4N1s1XdC36F9/DqAXweA4/HD/VjboBUqWNmfiZWwVO9jhIQBziFIeogO7mUWwTC+CKnKoB3J+xGOjtdLSjqjPjq2V/Se8I20nWYdh+x0hAFEGNicB5JbC5GhGTbNoxbx/PNap0FpKn8qk55F+JJNFvKAujeJ33hKQMowC/Tl5AXQpKL7wNjkFPdWwEwBKIBdYptZDRjZKFERMZHKASGUKGwAfaUvfieuwSocYmr1ViZwxjsBsPqU8lHUl5vzAvOmw3rbUPiWJ5GRDeFJCT2l/SrlYFsBNxVQG5k0MwNRbFSZVFGsFUSVdwK9VbjXEFB4uZug7+n7iy1ZF84JjFSPB80Kly31vbD03vcKfa9QTemmcQRlvZ3hS2eEtl+vx5hVLe7VW7zcziKT81F9hZu+xnaAOzyqr/Csu4dH9RWe9xRRmakdVn2DU70uKpjl+MXntR9pshBCPPTefxK+/qsAvh4+/10A/60Q4r8AAZwfAvitH+UYefJW/l0YX/IsghJWrohF/fv74NEqXJnzcAisLCjJ2X5tcDlyF4c/2yrleKg2uT2Rat0MnppGFP3D5UCySthK8QH0VDux53IMt/cSmW5Fdo11Wi8vNiSsgLupYk4C3Suxx7Ogyty+WGZYlQyp6HJxrRsdAdE4WViVcipC6UOvSkBYeEQ3ZJ9nEf4EmZy9Gw/+/NrjxWoK0+timfegIsXSxwlgt61jVmjuermeANrFchLX9VNHk5MVUMLHKEdnKTz6bH0cwcimMXi6PsFlO8WyJauAox/slnD4dxe2qSqLm55upNYWn6yP8HI7w3UmifeNzWPMqm7AszD4xuYx1rbBlZnguieT9J9tHqGSFt9cP4wTEgCsD6Hir2hvEjr9WwB+GcC5EOJjAH8FwC8LIX4eNPp+AODfBwDv/TeEEH8HwD8DSdH82udGQu7aXbtrPxFN+M8Rxv3/ox2PH/qvvv8XikSy3ftvAdjPEVE7g9X7s4OJZHkOB4ACxwDKRLLFB4ELIJMuZ55IRqUICYfIj+UVhVOHfcL6uAx4dSJZDKcqxDApa0oWkvuOMALZUyJZXvWd7svAitBh/67s42MPyVrDcGhMJHv05olkopVFIhncgMHJ5KtW0vHYG3tFIhn/DrlosOxDnZTN4UQylSeShc2KRLJeY3dTQ1YO09kuyuj3nSbGZ+Vgh4lkHmimXSJrGUnnt1VFIhljJjnZKyaSbUdlIpnHaxPJPruZI2/TusPFmnzHUWWw61MiGbtjXzq5wqPJNW5MVh/EVujs4USye/UWT9YnRSLZ//Lv/ndY/e6nb5R7ensZnIOW62vmjTMqSxk7whb26l28Yh+JUZgGBvc7jcQm9SGdfUAr986n9wN2VByYYtAXJ7eMbxA+Cg+KJjjiduTSdsKUkwKAJCnoyj5xoD+fOHj5sG5JOk8Rrz+SszwgtirgCdlF8e0duBvkqog4yGP1c5/WpergwUXMfwNHhz90bt5ImPz4TkBoh77TaaBnkZT1zSh+B2hysaEYEEAMTh/2023qpBDuREqEY9V3BHp4L4s6HACw7mjwmhB50coVOAGtU8V1112NNkwE7CKs2joqbxsrYYyC94R/7LLjPd/NYFzadx0mgm7AzNzZCi92Cr0rz2MoG/C6djsmiwOhU/6DskWR070B0sIEAGkJ2JQ2Cc2SrL94Ld2bbxJXCFMtWRk53VsaBh8Z2EuRkBznOET3ZrVvOsYBunfjo9DsIbq33ohI96ZIC/W3Uw9tSh1Q2l+49t8j3Vv0Av4N6N5iQPfGAbq3z+ne6326t7ApdPt5dO98UlKsMzGke7evpnvLeY9H5yXdu1+MoOZ9tEh8K4nWfYDurWoLu22iJaXHpqB7X24IG2iU26N7H412+3Tv8Q7rrsbj+XVB9+aoyL3RtqR7t4nuPQvq3Dur8dWTJ3t07yfdSaJ7h8lja6pI9z4bpQiI/TzGYNZux2QBwM3GUFeroq+fKzTMs9gDK8N2SoSwoMDoKkU1bL1fAWsoWhP3oZPbEUOK2yxBLYuqcGiPeR/suggrgqLT/jF4Mhe+7JMs0NOQcI40SFZMbk1IH4HAHDT1+WRR0QRY1MWofHRxcoFjV2dRG5bVt4fP3as0scomKE/3Es24x26jiz5vSdwlPqkFu5AyFKUePMZECsd67QHt4a1PkxJAT3cB+AO1SKSyGNV9BBI5sWxa9zH/QYo5FjiCVBZfOX2G3758BADYthUgPKlYrflHD26NEzgZ7+ITvPWC5PoFohuitMXJmEK5s7qNkwUAHNXE9agyN0SpUsR3VrdYdzWO6i3+hePv4rvXNODZTTlt1vhoQWHWSlJ1MSMApTymdZJff1gv8KJLLgyzOetBlKOSFg/ra1TKYqQSuv/mU8UtwSyOpo/8n/6ZXy0mi+1PE12WSVL1Fd0g2Vlc//SsoGCzEnYs8dd51Ddub3JgSX/Ze1z+EfqD5HhHrgpNiloBK8hwhsilyPpy3ISjLDfv7tO9hUXCMUT6DIQJwYg4eHP/nqI36ansKiJrDSMfcuCeFEI4A7WvYePQ6817rjRNRbIE2ELiKIgwIoUieVBLX+oaApGsVbolxK3I3S4v6H3ImWFhoe6n6D/Af1mhPFG8DceBPRGoKldYH44l+rSD0kzoUnFiMLuAX7UUCoWg0GrhhjikEwx9Ymzhe4nzh9fR5bBeoFIWzsmYWdoZTWFXn6IeWjm0RtHgrQxGmiyAGA2RLkY+tHK42TbRDVFhMv4j959jojuY7AdddiOMlIGWFsapuGyiO3RWR+Vvbv/Pr/0GVt96M8ziTs/irt21u/ZG7Va4IcJ5yF13cJnaDZG8wCkIFoduPUwjQhZq5mu/wuWIy9kFqJG0MHx6inINEIp2UB8TmLiqN59L/s7N1T7V+IiAX+JWuLoEYIUTwWqg73pN1bo4YsAmvBuHSmCv+OUOWQ2v6x821zjkdTngRLIIIkAJwlcGIraxBga3sL4fAegkvORoCp2My3UvWEZPoDi+F2TF+D4xONmcl2E9I0LRISsgG1sUsxPCox7RU9tm1bfGkxZdp2GNwuyEAKGbxYQiHpyYxroeii2WjKexLc0nVrjamQq9k5jXbUwKmzYdamVRKRsth87oaFUo4WP/W2PCE1Z9gy+dXMXPjM3niWQfzp/jZTfDNDMbmfy1tTXGqos8it4pXGOEM2VwsUtUdP0FSFl3lsVdu2t37Y3arbAs3qTl0RDK/aBvVPMjvQMoaoLkLY+GMB/CNgJmTCTAXAWbMYv6OtW78AoxGhKJb+JwNIQsA1rFjBl4TaFKsiCovz9x5L+Pkj/vGsIcqrWAVT7qTsSaHAfEb1gyP+/7otEQvVRJah+BEcmRiAA8eiegpz2V4GOAcuSBTlJEZE4nwYrVYqugVzKBrVy0eiuQi9/42lNy2iiLhuwkYSEq5YSwMpaUBko5VBVFB9pWQ0qPcdNjPqK+zip89uQemns7PDy7xqQi8/DJ1Qm6TY3xfBfLAfpWUiJZL/ejIRNDJQX52PMeJ8drbHYNpnWHZ8sjAKRw9WC2wkeLk3gOSnisuwrr7QxVsE7Ophus2hr3RlsCM1eUjs7qWD97/Bm+9umXAAAf3Ls4KH7zO4tH+OrZ93GTsTA/a+f4ncUj3B+voggOABin8OH8Of7xi/dwOkoaFr+v4jd/UC3K6IVIRC5+Y6uUmVivHLq5RL1yMWLSzSXGlxbVepAbckCw11VUJ5TyHRLy394TqJf0zhNIvSKhHK9oG95e7TwgkvAvAKzfTcltQ0IV9zFoqZ+qCFC29J+hGqLTFIZtT8PkNpmK5RIAABrsSURBVHWoL6lwUg5a6nUprgPQ/niSyd2W0csEju6J33zZFvRpscvyKdj0FoBfjCEmLuaniJ7IWH5iokIWuxPqtEU/1hC831API9cg0WsBEUBbn5OkLEerBEbBXWBilXMC1lSwrG/RS8jGotvUWNhZPIfR6Q7WCjz5+Cy6FrOTDVRtsVmO8O6jIDLTnlFhn8bh8uOT5A5JwK011R7lifNlg8sVUeMvtI3iuqu+wSerOd6/dxn1KCZ1j0o5fOnsKlK4L9YTaOnwyWqOjxYnMQrCrsfXPv0S/uR9Sqv63uoMdW0wbnrsugrXYXL7M+98E7+zfASZhdlGqscvnn6Ey36Knzr9CIueJrylafBPLt/F6WiDT9cpetKoOzfkrt21u/b73G6tZTFsjlPVjSMiVgA4Wdein8iYCapCZfBh1TLNBaONT5XOBNBPyVJwVRmOtE2Q5B/xOZAbkutZcDFl1rNg90ZtBBDcj6hWlRk6tk7hzO7EEWlpnLshIpLFEEoFAokvMdSzsHUKI+d9h/Qs+jn29CyY7q1WCm6csRx1srbYBIcELFsQXAukAWAF0CqISSBlBTfEbDXUQiedjPAwy2UAXRVA304UbhBlohLAy+6CjHRvCoXqYNp3UqOqDdTYQakUOr15OUU1bzE/W0eNiNW2gdlqVNMOFzchJbeTcHMDGIHm3q7Qs/ATA7HSkZTFZQT7jsKiT5aUSFYph5PxDk+Wx5GUVSuLxXaE6/UYOqsFYqzEyXiHStoIhrIb8sG9C3xvdQYAOBut8dHz0z09i69fP8J7swuss0Sy1il8/foRJrrDs81xZHQuuxEeTxf41tX9gqfxk+eGOA+xbWNFMgCoF3RDmMFpZvTD2ZGGaj3q1X6UJLosxmN7TpXLGEsAaDA5DZhRlqK78mj6kI4+Tj4/DzovAXWR/rztkQguSpiQJiTq288Ir4jHahIuoIPLkg8O2YtIqpo8k6H4D8AEC2GBWhGeUi/SJDb7AZXz2973xeSjtqHaWoZjeEWTgHCp4I9tPOpFqmfKjE+vgb4B7NwWKd5yKyPTlM+BCWxmQoOb+/o5cS/0c7q/Md3eUkapWpWGbPtu0vuUKw25E3FCidyOJlQ1n3k0Id+jXdHJq5GF2cnktlQO/csGnfZJoVx7zM6pbOHqkxFuOMt1TKI35mKMPnAyTt9Z4PLZMfS8R3s1ikrhzbTD7qbG2ftXMSpx+ew4lhTcTTUeH1P90BfrKZ5ekmbmizVNAJ9cHBd6FACw3I5gjMLT9hhKuci/4P0/vTyO+S0fPT/FV7/8PSjhseobvNySi/XHjp/hf3/+AT48Zilc0gD96jnhGDPV4qPtPQDAT58+x7du7uPffu9r+J8vfyau/1ZTEiFf127HZMFN577qYbyBxXAO1fsc5kuo1kN4X2AGTJ7KyVesQ8HaFPm+jC6xAdUCZprlk/TMfuRBlIF4g4kn15uQBuBJnfUlcnBSOA/vBPwUBbVbGrJgeCLgxsfPM45psqR3FtoRNoWE+XoAwHPVskxjgveRh36BoHQlSZQmXlsrIMIxZEynz6nvVMc0b7JycFsdt9E7gUzMjLY1gJUespPRWsgFhb1N+hVeCbJE+pSH4kYeo8pgi4aEeliPonHEyrQoRoHcKtixJe2LEBr2NYBWYVp3WLV1XI+v0RgVgcQXmKLvNGZVixegycIaWehRAIi5Hn2nYQSgq1J/tu80xqFOqTUSSnic1zdY9U3MPTnV63g+cTurcKrXcF7gVK/xVJzEdZfdCCPZY9lldVNFedzXtds1WWQt168AAFfL2H9YqwJAplfhZVC+alNURBoCR4VPpQCAUoeC+RtxEGSl/4AgsefToLQhg5O+p9wStUuRj6gdkbkNXmaRkTrRxrkJK6IAD5DKHLgweUmTJh6AIh9+8Gt6hSzxjAFdDzNOuSS8jW1C1uc6aUzQBimRLNLWw7pwougDc0XYjch2ozYSw5C+2aYTtmMHL1NeSNK5IEaoG/9/7V3bj2THWf9V1bn0fXru3pld766djUmIA2gNyEQOL4jwAAhFCOK8EIl/APEPROIdHkHiKU9EKA954QXEA2AFC2zntgE7sdeXnezs7sz2TM90n/upKh6+qjp1ZtbOBCEySc4ntbr79Ln2zKn+6vtdPoncOGI5ta5nemOXq1gTL8Mu48aHouLQA9VcmwLRvDncAFJJ6lIeBAr1uAYPvEJvT7Yo3croX2zB1GYMZU2IxYNk4jgRXOgn+lEoxSACCSE0pDkvu40IpKObc0EZxaKKwZnGWp8KvW8mVzCMKpxUzT7t8kIJHJZjHBc0xXqTXcEkyrFfrjqrPQBIVYyLxqUdLPwaBQDXVZ1XZlryhC7qfk0CaOjf9hnQrjepvQlVAGgDfdrXQCNzD9PGgQsgezpRACpqw6n07GUAnhuV8sxgGk1GM1hUY5wz2bHQqChpn647e2SzA+ZgT8CDQD0NhYy1O6a/vJp4pCenZrW1Ft4ahHSgIW3/E3Mjq5g1MGfc1FgAusktvOtctEoSxp010WEZd3J2HWlI460JoRuqtY1AQVmUxdsPj2WTzUkGNa7BY+lSeFkL1IsQLFZkm+d6hAgiVoXKDRZlGSAeU4bQXy8c6gKQhV+y7CE0+43HhTuGYNpZ3QHAyihvve8PCjftsNGLCNkY9QsMoxKPTtoS9ZVR7lCP/qDA42yEpIyw1k+xElMBai+Z4sZk5hy8AWAQlk6Gnnv1iL1kiuen+3gv28BK6A0WP4YHZ4eGdNFFFxeKy5FZcAbdj1sydTkwWHpEo3GQmLRPKuTXIzeP9une1ZB+IYoVGgNtEdRmCZRNaPBa4/Sm7c5OhUXNGVTUULrLFQZeAvl6M0XhJZn3lhOG2ChcNfcIWUXjZ3H0K9KlvCKxWVEzdSDVqMleFhz1QCNIGWrj7q2Nu3exQUXD7EpTD6CCpXa1AbtvnwhG3xX9ogMkg7cRLpusxH7OjOydv3jc6iCeZxGk1/QHAHTJ6do2CydDRybApiXZ1BkeBbNz/kAhjGpHt7YGudY8BgD0PAIvKFPxtY1MMui+BD8JcfuFtwEA906paDeMSiRlhIWx2xNCIUvptT1WFFd48ea7uJ9Mce9gzSEpu1dnGIQl3n+8ht21E3e8dz/YwmCaIVn2MDTkp0FUYTYf4flr+w6tePeDLVQxGeh8+uYP8Tub5Cz5veQq3lls4A+e+jb+/eRZAOTC/dmNd7ATHeO/UjK7f3tBQkn76//c1gEAonADRLj63NU3aZ8nO/jUyj7WggRvJlewZ0x//+bZv8dfz17C7eH7zfkXW3h55Q3sywF2RIo7JR1nN5jj6ye38aXNV/DV2Ytu/Z2oufYfFZdCdWqdsvzBIv04wUYis/9wBllYVpjfGji3aqudsIU7gAYQzc9PVcLU3JyJwvEtI2vuG+TC+ExIy7asyOMyOkXrWPUQiObtqYXsUY1C9jzfiVXt9uVDgXbgkEPlXtfTGqzipDo1N1hwKiBHCuExh+xrRHNat1hXCJYMvGRu/4Dp2mW8OW3UA+3YkOG8ueGrqSRmJOA+FymHyBiqVUXEKnu+nlzcQnYAQX/HJ0O3rK4FOW1X3GktcqPmrMsAbBZB9dv1CFZ5bM1YIogl6kIg7DeV3ioLSeuRBBjtkuzcwp8AMO1lztBlnvUw7edY7yXYipcAqEPXt+5dw/p0iRc293BQUIHxYTLBg9kK1qdL1+AnyWJMRxnSMsQvb9/H+6f0P7jIYwziEg8Opoh6dOzpKMPHVw+cHf+9hAawSZjjudEjvHZ83UnBt3pL3D3dwLKKMDIM0mcnj3GQj/D8ZB9Xojn+5eg5+hoM1HmjP8OdU5LTXx3M8e3ZVSyKCMOowo0JEcC24wW+sPofeC27CT/u5ltYDVIc1wOsmn/I/WKK31/9Jr42+zXc7D926/7lH/4njt86uJDq9NIOFvlNYr/ZAqcNkdeY32qsqp0lnmj4FT5c2trWZBhBrjH7ZJNUad44bPutCoEm07DHOicqO9PQyS5f3lCt7YC2zb9/o+uAsoQWZFm1C54+UuJL6VvHrtrvz7Yy/KggNIWheK7dd4Nz7QqRzruiEK7XhjOwrTkZxJRn9Okw0m8/PGu6J63DPIGaLji9Xwa4eot+da3L1LSfo5LCNRsGiD/hm9+EQqKSovVM+6A/XCW5k2wPogrzZR9RVLcGJID6gvjL5st+a2CZBDRoWvPcSVA4b4nDfIRb4wNkMmqZ656WfUyiDJOgcIOYrSdMwxQfpGutZQBaxczPb34TcznAM9GBW/Z6+gyeiQ8w4AVSFWMu6V7ZCY9xZFit7+Tbbv2/++I/4f3vLTuJehdddPF/F91g0UUXXVwoLkeB8wlhmxqL+snTJMtzsEQkUfifMeee9WHheBVRsz8LU9rloqSU3z8WYGBRz6vCnwq5/ZesZVkHtIuSTMKxHwlGbZifQONG5SszAaAeaQRLBlG0bersFMk3tvUdwM/2SbHTrXM+HEnQmgZINNMPd22mEZGuedOAOFBuCmLbC9opCgsUFT1t/cN2PJOsxYdAoIGanYNNdUG2fHb64Xfq8q3r0jLE+qjdFdwWQO3UxE4/AJpKCKEwNp6WdgpiC7y2JaGURAibzUfOacvCpgCZ4Vr4sicqxFzioBg509zN3hJ35jvmc9t5rEYkasRcolCBI0rZOsejYuxeF0rgfjJtpkum7vFusYW1YInX02fcuawFS7xbNE2Ze+YP/8riOVyJTvButolp2HxHS9nmaHxUXNrBgp8ZJCy/AjD1Ca+YCVjzGwpL6xbFmX14ZDVXtDRoCJN00/p8Bl7SenY7KqK20ZBGK0LP9matpufREJF5A4pnoRcuOGRs0BCrwkwZpKFJs5qhHjVoiBZAOVI/Eg1R0D8GGkIDyHh7eQ4NUWfQEBg0hE1L9xkzaAjnmqTraGoPLCCOg0NDxIegIUuDhngu7BYNAUgvATRoyNSY3vpoyINZ0/cTIDTk9s6eQ0NsXFk/wY2NI7z/eM1pJYZrpUNDDo/GDg0Z9wvM5iP84u6DFhqSxBK65ihXg49EQ/aS6YeiIXslIRt2ENk29Os78x28sHaP9nmygxc33juHhry88saF0ZDfHL6Fr5/cxsvrr7bQkO3wFBeNSztYnA3H6JSA7xHZ6gbmtCGGbHW2q5n/T+i3DggBYSnV3r61MHRuO04xmObHbQjUCtBUyMAti7TyHKZsBuAVMHXQ9B6xfhcy1s6T0hVTrXbCZiTmXM5a42sBYybczjZ84pb7zuLGxct+zhkDr4iY5LcvbLlOWfIT19CRAmfespDeK8XablkgpmWpQncttqZeV0Fj1S80sVCFbm2vAfLW5Nr9+krVDGaCK0Tm155zhTIgc1tLDY8D6VoG9geFk4JLzZDXIcJQumwjEhI8luBco9cvW527glC2/Ct5LNHrl6gqgUjUeFTRIFUoono/qlbcsQKukKoI++Wqc66yfT1GYYGIS5QG0bGtCLf6CxxVdN6DoMRSxlCaoVDCDSz7ktCOgc/7N8sTFWMfwEIR63ShcqwFCWZyhL5oqvaVPl+Q/rD4qRksWloQn0ZcEc9CVO3M4tw2aGtHLM2ZGaNa6Ma0FmiYkjJuZxa81qj7jdEOmekad+6qySx0qFtNdmihdy51c1MFGf3Si6JJy62/BCKiUdvpieVZaNEe8Kw+RXnd5plsxGx+4x6f/Wk/t5mFn4YDQO6xDn0DW5Zx6LgxtWUVh9aEnig7KJpr4eGTeRZBWKNyfHNmeBZo+wVLBm2s/SxNeZ43tGupOEqzXyEYZC1a9nkyrrC2nuB+PXUcDICa/PSCClUlMBw3N48qSHWbZ5EbcEKhUFcC47DAArFbL0dEmYUMsB0aIVk5xrKKsR2eOIv+WnEMeImd6BjHJqXdlzS4LE2mYgcAeyO/s9jA0yaz2E9XMBIF1oIEh+XYcTN2BMGjZynbOyLFvnmeSUK3xjzHUT3E+mDZ6o0aPqkhy4fEpR0snPkNrDCrnVk4D03Tdcs2Q7bxJP3IR2UW7Ix+w7YBaGlDmJWjw0nkaRvmnm1mYR2e6Fq8fetmWdPrlDIKGTeGOSqk16wibYYTZwUaPGfgOWupTsGMPoS3B1XpaiDNYhlrd25nM4s06YF5O9aKtSBOANCRoozA+0zHRJtW8KBP71zKNGo8OY2mo0iiRhQmNFTPnL+fHQFuHd87EmicsG1mITVrcUEAomLfW6yhUhz9QQFtUjepGWbpEIzBZQtJGTpIuNf3ZNxVgCCUuL9YcarQoF8jimmwCbjE3ZzS/UIFmEQ57uZbro4xiXK8l23goBq73qPW+9L29UhNVzGbeYzCwhnXRKLGvWwV99nUaT0A4E5JfAoLjwJUo7hTbmGh+pjJzMGlR3KEAS9xJ7/WyiyWP4Y2pENDuuiiiwvF5RgsGIMO23MnXinwSkEHDDqgXqL+tCJMdcPITO1cGs6ejgRjuv1QbRRAc2P4UhhxmDGP4XVT6ATotX1PJjf0bJWr/rOdPuioeW0f4ZKBS4Cb99SFq5m68JohTOjBFCN0pqcpkwpITRnNOZSg5fYaNAdNowpCUewDmqYZwhjIuGsu6DP/c1ubOfvLDAA6I9GVLjghE4uAvDYBt4xl5n3NgWUALAO3nVqEEBFNWbSkbmYsloiHJdUIYioG85yZnqnNg8lGbh5yiZBLpGWItAwRcoVKcuRliLwMEQqJ5XyAZNlDlsbI0hi14tgZniDkRAWvKoGqEsirALvjEwQBGdNY9qcloDmFK4A4rFFXArvjE0z7uVsvzyLXc2Q1SLEapCiUwCwfYjVIsRLmWAlzPEwm+MTwAT452MdKmGElpKlBLkPM8iFOyx4GQYlBUKJS1GKwVgKndUyPsoen+8d4fnQfm72lO6/dYI79Yoqd8Ng9HpQr2A3m2A2OsRvM3bq/2vsAqYrwfG8PmYzcY8TP/70/LC4Hg7P3lH7x+p+0/CzyazSnC5ZURCin9McTuUKyE3pK0iZ8One2JnC2m7xFUMJUYblr5s9xg4KooGFk2sEhPtat/WTbDOGiqYtoTl4RFomw3309bFocOjjUg0t9GLWeyKZ5sD3XzLQvNEhJNDeoxpjqEPVAt6z0VUyoiY+QyKEiJKFmEEtvHj+Szo7fIg0sExAJRz2RrY5g3FT8AUIvANJd9AdFS4UpawGlGFQSIDCGvbY2oTNxzggYINm5j5iEUY2qDDAc5a5ukmeRY5GO18lFyBYeQ6EwjMrWNCIUCtNehq0+oQqnZR9vPdpq0bMBMqk5XQxcSwAAGPYLDKMKpRR46am7Du5MqwihkHh4MnZNiYdRhV/ffB8fpGtYCXMc5pTuR6LG9cER3l5sOZeqnqhwWvaxqGKEZvpxbTh3zM4r0Qn+bXbLbQ8A1wdH+ObRNQDA7nCOXIY4LXuYRDmuD8gzNOY1Pjt6C/v1qvtOj+oRjuoh1oIER/UQA0MpTlWEP119FV89uY21oBlw/uLz38XD/z76KaJ7P2GwqDboy2fSOmUZOK7WSHbCc7Ao4HtQaKSbgoRURmgG0Gt7ky93DZxZwAnA6kFji+d3Gfc5HOWEoRqTPgQAqhEQLuk58KDR5FoDbdqiqQ9tqqAZTCyUGSRecdJ6chgnbuVEZyR4y3bqlu+ESHhLqAbAGerwmqEaW3m5RvxYNI7j1l7PUMjFzaWDMwEq5FmjXlt8tTJ2Na4dZ0KkHHJatwYmN0jWrLWujfGVRcNpmPfBMuEGL4ccBdrxPG48RdDpQyPnHvcLpGXoCpdRXNF+hHb8jzCq8QvbB3iYjHF4NHYDX3+cY32U4v7h1A14n97ZdzqS2XyEyZh+MaZ96lV6e2fP1SG+de+au45nnzp0MOcPllt4mEzw2e138IMl1THuna7it3a+76BPgODUSokWBR2A60P6MJk4F+6HyRhfuvEqerzCfrmK9zIqnH5p8xV85fAlfGblbbf964ubeHn9VczkCOtiiTs5nefzvT386/ITeHnlDXz15LZb/2tf/Ed857tP6Fv5hLi0g0VxhcxERG66QnuZRbYVPpFw5Ws/bGbhu0dZbwouNfJVa5zSJjOd1X6EiW4dK19nLfKW777lh4rhbnD/BvaP07QFPA+J2t6gwvAqrIem9cGoJu3Mwu7TzyzIBOYsAez8Nq33vnEM0Co2woOAWaxIz+HDpDUjVMR6dTrYlxM/5AykKkftzKJ1HuamZoFy5C97U4szPUTd/gx5KhTSkbUqyXG6GCCKKze4AAQRVyW1DrBQ8XQlcZlFJGSrO3oolCN3AXDak1IKPDVcOP5FyCUmUY5ZPnRZRE/UDna1A8M4LJBLKob2ROVEa/7n1oV7GJVY7yUus7BakZjX2InnSM8IlObVAH1RukZDAEGynxr+EEf16H+dWVyOmkUXXXRx6aMbLLrooosLxaXiWfiICC/bZBFRNL4WKsC5BkIAwLwplRZAfEoISOAZ9gpFKEJletCECRnaMAVUI3LqBpppQd0nGreNeK6RbTL0D2mZ3cY+W03L6a50NO/ASNODhGTwdIENczM+ojYA1gXcHl9zhnydKNvllNbtPWaoB0C1VjvTWNo3g0gZ5KA9LRApkbjyLTvPAXqPuKOPi7SxBwQHgl+at8hLMg3Ak8aclo5F3c/r9RosEW5ZtVFDhwrhEf1bORm+BuSVAjpt/7tt7J5gaaja+eM+xFJAjkzB1XqGcg3Wl1BZgBs7JMX+YGak28MMiyxGltA+4n6F9GBIHBLDFeHDGp959i5+cLyFR3ursBTZ3nqGj105xNt7265w++zqDK99/yamG0s8ejB1BdW1QYb7j6f43K03nZT8te8bDwmuMbxW4re3yajmjZOncfd4HX9041t44+RpAMDbs0184Zk3cDU6wqunHwMAvHmyDak4DpMhOIOjnNuaxd3jddycUiHz7tEG/nj3deyGR/hOeh3fPr0KAPjy1X/Al/d+D7+7+V33nX7j5Bb+bPufcb+eYDc4xTcyopx/pn8XXzn6Dfz5xiv4q8cvufWvhm0tzUfFpahZMMYOASQAHv+odX/GYgPdNf88xGW+5uta682LrHgpBgsAYIy9rrV+4Sd9Hv+f0V3zz0f8rFxzV7PooosuLhTdYNFFF11cKC7TYPG3P+kT+AlEd80/H/Ezcc2XpmbRRRddXO64TJlFF110cYmjGyy66KKLC0U3WHTRRRcXim6w6KKLLi4U3WDRRRddXCj+B0oGGZqm/4jDAAAAAElFTkSuQmCC\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9d47a2efd0>"
+       "<matplotlib.figure.Figure at 0x7f5d83be6f60>"
       ]
      },
      "metadata": {},
@@ -70,7 +70,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 1.3557612895965576 seconds ---\n",
+      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 1.2073416709899902 seconds ---\n",
       "\n",
       "gram matrix with parameters {'height': 2.0} is: \n",
       "[[ 15.   4.   0. ...   0.   0.   0.]\n",
@@ -84,9 +84,9 @@
     },
     {
      "data": {
-      "image/png": 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6A8h0PzwBH47MLu7uHiG9tgHnoJO5bcpVkXGEwuuHAMga8B4Cnrof9jwiTi48BgNc0rtzEABxnFkMrQaZ955ndtR0qwnW65ug5fBjZPVUvnyX5nijhcqf3SF9LzhNRjzPzJn0PcrCDYZgW+uk53AM1m5CdLr578QxWW8ON26Id2cfEsDoczeNXpPP3UZx/3Dxunf34ay3ycVRVgjrDyl7dH0b8v6BmSudpXs3cikWCykEWNHPLRbM4cCLN5F+63v0ux2cSdMMUPPttzD4mx9F/U/egujSzZh3P5aKesh5swH0hpBpmoOXs0bduDba/BWHxznf/3HnNwvYMZmVrFqBtAJk+vxF9ZIhDA1UWuwfgjcbC+kxduMqxO7e+XR4ElF6AzC6syAw0X+AzGPnQMVMLNOe+R5lDeoETWeTENJzAc+F3N3LzeOTiIZE2y4X873MX+/1ARVghir1dg46EDouUwpQ/ZqaO99DenQMHkfAturV/ITzKsMZxS20KHg8dFzJepZ0JsLEIKo+za2Owa23wSYh6anGUv7O0dIKDl6rQgY+MBybTQ7lIrlh6r7pudJgvncjl2KxACM0nbDh3tMQTmcAuSSCq19sgF7k+p+8hegj1+D9lQokRo+3LHSwU3R74O0W7Tw6lw2YhUOMxgZGzivlhaDpO51fdHv0PVWHItUOBwAsTXO+J9s/JoyBesCY71Hg0/dzwUvs7oEVg3ON8UnE1lvrLnVZto4lRDFkqw7WH2aLWFCg9N40zKrsrXiDjKLcPD4J5NvEXeLMspBRDKYWLLIEpyr+oYKWlRLkaQdM3dd0S8UW3toj/79afdeLL3O4mTMN35bjcbbojqcK0j0AUorx8ICCsWwS0uKq5/akAwlAPH8V7Lt36bNb15d2wRXdHrjnAn5mWcjekK7dbkF0zrK5Ki9HkF5ELsViwVxvAebKK2Wkpx0D4bZxF7xSNuAYGcUQ3S68vxpj+jM/DIBW4uTeA1P0o8UGPpk01DTMsiHIAk9IU2C9TalQvWqXikj3H9J5rHPrTIKdDeH1mtExV+ijriPGk+ya9x/Sz2lK2RIA8bU2vAcdpC9cBYtTOB1Vb9Hrg9Vr5A7N66D1tj7TFbbzi4upW7CKpQxwxwII5XSHdY7TMwirWEoqYJptebFqFTKcgUFBq615ZACSu/fMGLSuts7z48rAXgpYNZ6oDEiUzW0cQYoUiFTgdTgyixM7OCIwGwBUq0h3WmDdCdhQ7b7KLZJpCo4sWGzrlnum1Jhtq0KmgixE+16oACmvlDMsi8JLyDAExmPEH6Egq3ZDncMupJ7Lhx0IBepaeKbHUzr/XL2Qvm9mc/LUZjW/yVzA91oFOFeykpWcSy6FZbFMWLWSrx61UrysWsmt2sz3IaMI5e+Q39f79DYqu/ffsfZfl3wjTWnXKRdp5dWbmueDxQmiqy1Ij9ZUrzOBnNHumDu3/tmOuVg6GlPd9zKswnhsArFiNM5WbbUTeAddQAi4hz0gThDd3KDPSwGEywEpl+tgS5Is3Tjs783/PTe3QC6dbI9D9AfLYepBVtmo/XLWqCO62oI7mKsGtsdg6fqozW6+GEvq3X5+fDb8GoQIlsenSIdDcD2GcpnmFjCxAdnrG33SWR7XYHTTNI9JQu2coUr4bRzLNDRupBGVjjXH9PqUnh0MISaTLF2q/i66PRNjkONp7rr6Z6dRhxyPc2PllXIulW9fXwPKnpQT41LhLN6pNsQGaYlpuDR2kKsNsYFbBvuvTH074KS/p8zceXN+/mHklQp4u5lVUAYF8uk9P1/Ors0/BZgCMlfA1KNosepA5j+b56PQokFfAAzwywZ9ARlUWqaCcAYAEBSyQK7nZxwVmmvBziQpUJcpPbcXjWXgKTW/OazJEt31HLCdLcNxwWYRBX89nxbuoaLb4+o6npcFBW2MyByQbkE3XYvhebmaE10DYsdO+NYGZH9g6lOMS6qv3aqDjWiFMPGTORCd1sfm/5CpyPgqtGi3zeEZvkSdj3leDlwmo5ieuVJAuJEabTjO/inFPaqVHOCKlcsL9S1mDhWCmXQV+PLp76I/ffjBqw0xfIxS5jkhAbBSCTxNF3kobLFAV/LgCNGnbxNoyypF5htrOd/NFBjp0nCFGDX+6mSSy8Sw7U2Ig6MsytysgE0mZDX4DSTX6Frsa9+xioVUkMm6DnN49rMGAll8Awa5qIBLeh54qQQZRYTgnANPieev5tKzWGsBrgPe6ZliMqYCuXr30Sm16GoLs7aP0r/5hjW3im/B4VRjooJwzCPiF02Aoz/TwC4TTLNeADE3jzJNKSWr/X3PBatWkW7U4Rz3zYua7qzB2T/F8JPbKP/xa+qeedn5PT9HPKPHZoBbcUJZj0oZrFEnEh7QS6Wh+mbBmEVAqwHECVihZhZjxBREFQdHxnLKWQkK+al1Y+UyRLeXS/FqCyAH6gLpC8+F7Km5UrEvfQ59rKiVgLv74LWqsULFYJgr/ad59M21betCjGPwrQ2w0SQDewHABQLNl2qx0KSyOWo4JTbu4rz1BP5XXjc4DEBFy99tzYaNWASAu/tg5ZLJqmjU51PiaF64tr4Wu76dXyhAWA6kKSYfv47SX6tjuz3g1nWw4y5ZRepB8+7sw4uj90dvS2zshLy2RWPwPCQ3KJ3pvLEHubVOCND3QReeprRb12uQdVrI2GhiSH7ySNgihh/bQuXLd5+yZshwHOPxAqfzRUSP8UnkUi0WmjlZ75622LiLc5F+KCyGxmEAQPVffO2J03ZGD4XJ0PlyXqtCjseIP/MSnGkC91Ct+08TNAUsx0PM4TgAAEEBxa/vGnYtduMq2GCC5MYmnM4I8XNkCXlHA9qNX3/76eo9NwZthTDfAzvpAcqkdt6ihY9VK5DHZ4SFeJr4EqhsSqCoCIUAzpSPD5gqVHbjKgBAFD3waYzq1/ae+iIGKCb0bo8sG+8JX1shzBifSIcnu+pKVrKSHzS5VAHOXIm6dkXmApzOlc08sYwl8+Q3choq34+QneEvfALlb9x/V+Q3vFLJEa/K8Ri8ViXAkePkqmSfNvmNjYcwgbxcNiIjILYJU5YR9mrw1QKx0NMmv9FjUEHJeRJeO1Bs3M+nRX6jSHhNQFKDyrROjgOhqp/1sazVhDg8furkN0AWoH9i8ptmM19VC+Dl4b86N/nNpbIs5Hi8kArSwjyPJr0ULPnmEtGQ8JjiHLxSRvkb95HurOXKeS8qvFyimyDoH69VycctFsF8H+lLzyF96bknPv+5JaVr81rVBCF5rWr0gkjBy6V8sDG2Amy+TxkJ36MXpBRksOf3S1TwV/+D49AYrAWA16r0or4PuukM0Tyk37CC65fbt46ZLMbXnobwWtVk8sx8PYGY6l797wK2wqWKWRj/NYoNBb6RoAAMhpT2mccYLDtXo278d5N1aNThHHbR+w+uo/K71KNEJkkeo7DsvJb1pSPQ5k86RpASK5f2tdM5DMGC2FiHR43FzunPHWuPLxvjOBel1+lhuyAPQC4zoRdm7vnAevMd8RtLMRvLPnvUeOas2NwYdBpT/W/0UmPjk3DpfC5rGrf00rPZAnZCf54TjX3R/CnQO3tMmQczpzHEZAJeivMkNEmSnVPfP/t6c/d04fpL9JJJQguEXTavPn8kydKSudKWyEJ6/JxyKdyQi5LfuDeu5yv4lpDfiOPTR0KcISXYjxI03Nk/zUGvcxPp+ZBX2pSa1Jc67YDXalnRWrGY9eKIoszN+NiL4NMYLIwyPEQY0sucCoJBa8buTpc4LcJwMW/fqIKFESIdiLyzT59NMqyJ7teh2wZk5u9celbPwxJafgNZ/9SH4SjwlA7isf4oZ9Jq/AazoPAyDAneHfiGAo8FBQoUei5mN9fgDhRIK07BUglmP/iq9YK2MMznUWyCe9FnfwgAENztQBYLkJ5D5+oocJXnLWwyzPMQ3boC72SUI7/BWguy4IJ3R0RKo6+nCt4MXgGg3if9AaVVdc3J7l5GftNuIm1nkG/nsIvwpSsI3iIOC8QJRLuGuF0yc+Ac9wnz0Fcw/paVinU5eGdg6liczhCy4JuMDOsTxCC5tgb3wSlkowrpKXdyMEF4sw2vFyItenCmmYvidIZI21Xw+1mhycvDf4n+5OCD54asZCUrubxyKdwQKQSknDNdOQWKDAhL72pJQpBoBUjC3X1Vyt3LgmVWwConFmjL2SdzMrmxCfewlyEG9c6zuQYcHIEfd02+HUcnFCRT1aCkFzdgKht0xQ+7EOsNxK0SvBM1za26ScehUYVUO7BBVzoO5A7Butn9h4o/owfZasC/S7tB9OIOcR7MU/B5PpnsdoDQ8wksNSe2laH/zhSgytk/Q7qhdjnOwcIIYr2hjlGWjFOjHbngA4bNqQzpuUhrAZhCGGrau9l6CaVvPzTn5cddGmsOJZnpuuCPK6vGP6FnIW1XwcezjKavpK6nQFXzTYP8vTOIRgXcctGi9Qr8N8llnNxQpeCv7hN/iLaatMQJAat6w0w3xZRlQF56Z59EkJUS/M40Q1XWK+DdEQqjuSDmLIJsN4AoBhuSRZTstJAWXfjTCOPrhDuqhglRO86xX0nOINYbZF2puRCVAF4vBJ/GSIseWEqeA++NiFqgMwTs+U3Oj7m4FIvFuUS/GAnRpDH9kF7fBnpDKsm1YhS6BZ0txg1JEoNodA97mN7eQPDKNI/vBwgNNxiC6wdaV4x2e7lzG3iwlYmg77nwD2eGS9HtjLNofDkAV7DbwaevofaVB2ClIiTPXnTpuWSGD8cGvOS2a2AORzoIMx0UvBhOkFU8QgXmVE7djm/Y7oPJuYd0XdHrw9GLTUi6ewddWhgUjBxFH7NbG/C6oVlA0nYFznAG98GpQbE6gxDSdxEcDCE6Z7C9YxmGOTfT5P/DWQ5HwFLPjIUdd3M6a500PykHAM4hfc+8vHEzgPe1N8A5h6iV0P8wLXzNrxyaFgPFPeUKjMdmbkStRBR5gCHYEaedTN9GHaJWApslYHGS1ZkAkOUi+GEnW8RSQXqedLJK42qZ3JPABXMYuasAeJjAPR6g++ktNP+S4mqnP7WD9hcOqUVnMTALmXfQRbzdhNuJIItqoZ1G4MddxB/aosVQ3984gXQ5oGpSjK4XqBO5FIvFMqYsABTxX8KUxYIAOD0zv0tVv2BuRLmIdO9gEXxlpSf1sXI4QvDKFPGLO/C+ez/b6U66Crq7Zoq74HlUB6JfTmQIROP7WzECba24b9BNFze2jN/H9k+olBpA7eVd+q7DwU/ooZOtOsUl1HVMULUzIJaluboGgErCGWDqCii2oFOF1rG6rBnIxmZBtY2VpXRPb2yB98ampoCFEQrdEcVd1ALrJClw1ocEshcnTjLa+o38PDLPA/qDbL6qVVMnYgfxdO1NjmS4WoZolMF3D8F8D2mbdmA+mGDwI20UD2fwD0iHQmcAGQSQwzG4EGj+pV4AyFpgcWLGJaIYslYCTwX4YJLj4GSlYm7OpV5M4oT4KI5UrVFLAeXiGHDo2Q2fayD4uiKj0a0XAh+iWQYPE4rdqAVa3//mXx4Yy2Ttz/chrOAvtF4ihXviEhOXjhNf2wA/PYP7xgE9X+p6GI7AB64ZYybnj1le2gAnr1Ypiq9WcsM1kCSEodDm/hISUkM+Oyc2Ya+zTpRnEFnRj7hxxbgnMiSMhulbgSx6b/e1mDeZjV61auYS6J1wODKFUbJVz3AHSUoPrOdmbM/6vHMM1tDMTgdHi8FQuzgJyBPfPk7UnPFmI48FKfjEUp4KQzKDODb9RvSOCACyWjLBt9ycKHfD9KjYaFFm5OjULM52/4qchae+K8aTzI1QFo5Yb4D3RlQ3oeaKH3ZytHoy8MGGE4hmBXwwMcdqYt20WTYBP1NPYd0zAMYymK/A1YS9shTk5kG/+KKhFrGTHjF2d4ZZc2iAFgOHE5uYXVDnuRC1oiFIlrXyUjcEAKTnYna9CWdK7473oEPPUeCTTmqu0vU6uW6TMAcd+PLR59GPjj54hWS2LHS8ttwQuwISenfTXakByBiPdUPsIieAoubO/il6P0UkJPU/eYtuytgCtoQzors/hxuiMxtSWEAcRXADIMswAESqs9WEc9LPXkiH0wM0UeAeq9KSnfU7BtdfAAAgAElEQVSRTp+OGyLH42y8cUyWgap+HXyK4kS1V4/Q/8QGGv/+fhax747B+iNa1BqqpkK/QLqbvJ4Hlb1IL+iGmI7y2to66ZEL96qqLhYCKBXR+9QWOh+h5//6H0zgHhyBC4Gzn76O5qvKlUkFEM6QbjeMtfekboioFcHf7hndep+9ivoXX8+yBwWfKkStZyS6dQX+3hni7SYm2wFqf90xerE0AvetKtuAKprn3RA5HCH66A0Ed7O2EPBcqpyd5Z9J58ExMZC/CzdklQ1ZyUpWci65FJaFlGJhhWONOhGwapmDQ6cvUEGP8717GT+FPsbzgdH4HWMWRjbXyGs76QJxRBYFgLNffB6tP3zLYC0AAA87tMMviRcsxCx8D9hcy5nlol0zDXjQqhuSVuY44LuHkACij1wDAPivPSBuzrOuKmMmlyL8xHMIXrm3VAf7+tmYLxizUHoDWT4fngtRK6H2igKctatofOUAsl4xAU5RCcACH9J3MdsgU9/vTJHUChAeR/DKvfw8AotjUHgR2NmMXN+QstGH/pYYnQAV62hUUX/lGPVX6DMWZ6Q6rS8fkMkPKKLbIfy7x5h+ghC3hS99x8zNfMwCyvU0+o6ntNPGCZzRBFLNGSYh6q8oPlX9/UbVWHza3dLZLT5LUP/aQ+MazG5vwd/rUen4esbILZfFLDbXyP2YWa5gKchid1bRmRyPyQ2zv09/wXnlUiwWzPXA/XwbODme0gOiA3t2Fafnm1JwVi5nZC6KGZvFCdB9DGW/9ucPjjKIr8WD0PrDt3D2i8+j/aUDMAXKko1qxtj8OPF84ODIZFUAUDcx7fOedPMpTAXQMjT6601Mr1ZRmkYUjFN6Ba/co4fvceN7UlF6A1lGCFFMQTgdzDzs0jyddMHnOp0xAF5wxRznHGb+fW4egQuPwZSHW7EY29lm5SKgYz92Zabnkw62ezMJIdfbEEWf5hQXeW3m9CoF2Zxp8p6xhaadhEC5nI95lCi4qrlVRbsGwLr/pYA2MDWupbodHMGJ27mP2CTMeEashk3fN4S9y0RPuJac5bHRAlQfBX2MGI1Nn9Hoagv83oNFyLglepfjx13q8VBeowDkOLNO2l86QOcnttH8VpYWE70+mOtmCxtjwGSS/a+E375BkW3PzbILaQq50QKbziCthrqi2wWv13JFQmwSovwq5cbBOQYfp9qI2jceIl6vgt/PM2uJ6ZSChnaxlv4MyJX1C60vsAjB/qGbJrCmA66mKMsiotXEMcL6TC/YGvKOoEDB0J11DG5VEXSU1RXT7uruZwVtor9Ef62Tag3p7Gyp7yemE5iM4oztSxP2WnBxOA7w0dtwHhwj2b1verpiZwvwXPBRCKEtnjfHSE9OqFhP3Wd9DtkfEN+K0jc9OQEUQNNZX6deKEpkfwBsrgN9q2my5yF9/opBx+KkS9e9uw8xGsG5RbEycA5ZCiAPjpB88hZ99XBIdTOqaEyjh/nN69TpzCq8Y406sL0JNpxArjezYGacIN07oHtmLdLLCjIfJZdjsRACC8VjnCs2JmUyWQ836w0hrFZ4vNmgqk8NPVacmfO8FzbcW0O4Zb1KOAqd4dDgryttsM4AzW/1MLlOq375zilYoUDwbvvcdoWfugY/6VGv0EnW0xSba6bvKW/UDcW+qdtwHMgd1ZhGf78/BDwPlTfpBe59ehv1V46RzlV8zndU1+dbRsvHS6WFqlMN93YOu5AVeqEM/VpQoJ1Q8ztsrYMfnoCVSrkKUXIjEqTXCVjGp7FxS6qv95FWKJjqntC40+k0V4WpF4WFSlaQBWECpg6nhUxlLpgCtck4Bms1KaOg3QWRgh10IFMBp1HPgtCpAIZ9wPMw26Kshf+dyMyNY1VzUrC8SNWrukq3VDJwbwDGkmEz6vmKSWhS2JqN3X0gsvQwVEZmvU1jUGMT7Rr4YAJWLsEZZb1h5XQKoebG3GvOqZGRbe1yTguFYlU3pD29viGOssGKcrzENX+ErAKcK1nJSs4ll8Oy4DzHMwmAGstGcZZbz7cVybXCE4fEsagRc15ncn56uKMTxT7k5VOKDzvGty7foYvPrjfh3d8//7iOTohlSQPAjk4BZQbLcJaHFIcz6qdxSLuErJbBZtFCh2w7XfnU5Ijsa627HI6A4Sjzm1W3KxnOTFMmQzLLHTha3zQFA1A86UG0a8aiELWigSFfREyzIwtfIuPYpMxZvWZwKlqMJaH0NFR5/SFQKkLUSih+m0BzT0Y2p/AZes50p/U4Mq6JHKr4hXUfTexC6aupF7i+//UqxYYA0+FtQY5O6D5YZfVyODYd7eVwmKWr56qUn2iclwGUZbqo265GQeEDVKmus76uOl5NcyQztmgCETmbgVerYNubgOsQoAUKgl2mPpTavOXFIMfEbF5s9Xva6xtdACD66R9B4eU7ObSo8Z+tykHx1r08hkCJfR3zs71IWcexIECqMB26FNlp1Km61Pez/pUKlu12xlntCQC5sw4WpxjebqD6pYwuL33+CpzOyAC+AIKfQwjIO3cXMCRGLKCSLPj0wtngpXCWVdaq3/VY5ucRINfDZh2f3VyDfzAAhEB0lZCQ/sEASbsMZzQDu//wHXVCOCOXqeBDFrRbkEDsPoDTbEBsNMFmqsS/P0Ta7cFpNvL3pF4Fm0UGUAUQhFoWXOJb1dduVCGLPvofbqD5lwfmRdTn0C+y1lH2+gYnAWT3XNarVP16nA/26nOYY6Gqk2vVbPE4OIK8fiXDg+jvqqZZNs5ChiHkjR3ww05W6wTg5df/Cfrp6blAWZdqsThvK4BcAMsS+zu5MvYlrQB0LESGoSkt1+Xm9ndy5wUxZcnb1zPUn8MzAJbqFwHA0LHr8nEAuRJypvthghYx5nt5tiQVA+G1Wg5FaliQPnILXJUf6zJ4uwSexjbLumZZ6EfR7Znit1yqlzu0+OnUpcMJoTge57qNyWloiGoM3f00NKhVm+laX8P27/W8pS89Z1KvzmGXMghBsEBhr6HvhvhIQfFR8Ek/HVjmjgGV5VCsjSqlUK32kbxcIqBVp2uOnf3oLRS+eRfYWgdUTAZQcYTDDqJbV8AT1UNVZeMMdb+2WGYR5HAEubNhFgAZhhTwVPMJgMr4LavMWEsm1ZnVKsnxGOL5q1kaek9RJjBGfXTXm1T3Acq4iesbFC9yeVZs53tg0xnCm+0ciOtLJ/8Mw/7eB3ux0GIaqqyvGx6G+SCNOXYezi3mWvqpPhOsWkG6R6anoUcLAvPS0rnoYZ2nsOdN2s3jFynAqutJDEJRBTM1fR1dQy0g1SplB2IrZw5krQCqVWNqGwi6GqvOvmgyY95sZuMDAO5Q7cnAyqGf9bP+GLoPhc642A8qYB7W9Og4N7fM90xLRWlZPwutAKplyLPu0lYAmihmPuBsj0F8aAfSYXCPB4Qb0ItjtQyoas+F3rGqX4uut8BkaqwHprEHc60A7P4a860AWDHA4GdfQOXehFKamockFWSNvfXQjGnyudumqRU4N82eebtF2YwHB0ZP0awAb96nwHiRXGW+3oZUKF3TM8WS+VYAEKl5tgwPim5tYfOCXGkDb963Wj0oHTpnpi+K+BA9u1GzgFe++A/Qj49XfBYrWclK3ju5VJZFLmYx12TIjlksbTCEvGXhXrtKK7pqzAKo0nJlOttEsPTdfLs3Y1lY6T2AWuEhnJmdOn3hKpw39sDq1JTGxC10oRe38tjzXai0ZWAVgtnXN+SxFlmtJnp11tqGZyKp+MQE5XCT3gSQFXtZQT/ZqpMZHxTILFbzIJoVJLUA3nfvZzuYRXqrC+5yc2WnmrW+y1ClytWbJ/zljboJ1rI4Be8MqGlTKk2KWacSJ7fXTe+TzFJU90uXzuvqY7vJEJRJr3ZjO8ho40YAQF6/Qma75+YL5DyXsB1CZClSm8dVFZoZ0cViVlexBQJdPWdBQRW7WWTEWnfLkktubMI9HkBUAsRtco8Kbx6bojE9Ll2QmNNNX69WppJ45fqxVOLlN/4P9MPDD14hWa7JkF04BhiYNa+Uc4EiW+xCMTkcUqewcsn40JpcF8gWFlYMcgGzhTZzk0m+oC1O8gU6b+yh/3O3Uf+j79JnCnVndLTK2e1Cr1z372qFHgwnf21dtMaKQdaRrFKGnKbkkqlzecv0Bj04VGglMmLZg6MsoBrDNPNx98/gPezkOCZkTOfNOpKpF8VzswCn9RlUjGQ+wAmHQ8xmgB3gTFPI4RDcLg4r+OCdgdKZvqtLtotf3813SwdMgZcBJaUpgfnmA5wPj+A4fCHAKUZjCnDqmNb+sVr0R3jr7zyH539bBVRHE6LWs12FRh1nn9tG89Uu2Hiadx8rpXMFOFmakstScLPFQtMb1qum3IE16tRsKU3Bhj58FYeQw+FigNNzHxngHH5qB9U/f4PGqOUC5DeXy7JQYjcZMi9JtQq2tY70jbczFN6czMcstJ8bf+YlAID7F98in9Fa4S9sWay1TcwBgGKz6mL647cRHAwzsJeu3nxKlgWv1bImy7p/ZSoo2KctA11xau1Qo8/dRPXVQ+KMtLIhTmdIu+ZZ7/2zLMqlLDIvBI2h4EM6PAOEeS6NqxSYPqNPy7LAepssBmte6P6o3+MEs9uKyGgwy/hJlx0PvKeWhawT76oM/KzX6XH/YpaF5hq15uDl3d9Bf3Y+y+Lyxiws4lktmi5N9w+d/2d/x1gT7RacaUIFNxaaUf8D1O5p9aXUvzPfo2yMPq/jQLbqJhsAxwEmU7AgQHAwxOh5K3WqmzfHEWU+VPZDv4DM4WYXYeVi9nf7+kGQWwA1y7MZXzijfyfdHKGrbgUgAx8y8JE+f8V8VvnOKU5/agdp0UPUJNJb6TkUaIsTWpRU2wBpWUFMc0R4Lu3eCuVpf2bGWy5mY1L/5GymSIrUvygi4qCzPgViw4jqI4QASwXSraZxUWQpoCCgahVhJI4zi0dbOEo3UaN/suBDDAam7FxW6J+GrJsALwD01IIZJ+b7mv9ClsjK8/foHwCktQDRrU3ipNC6aWthaEG9gwLkeIy028uO81yal1JgWK7opCm5uQVqWi3DkLqk9YltDL0h+GAKPiBrRlRoo2AxMXZpywLhjP6PYwqqD4eUMTmZq8f5oDFladFxiqWR8zbt4E6jDrGsohTIM2H5HpJra3C+d8+0FJTFAOlLz8F566HBx89Xi2rJV0PmTbVckyEVA+CdAWqdATo/ex0A0Pj88WOrQu0KxhyruP23ucpMXX3IioGJj7D+CBhNqKo11yTXhXQ5MUDrMfSGaP9/w4zoRe24s5trEB6Hv4xhzMyDlfpU7th8hWiuKtLKhuix2MKK2SINhxtyGj6YGECSaNfAOwNMf3gbhS/NIfPmdNLVoSxOwGZZZSrSFDIMDbMVgKzDfBhmhEXlMgHPHEo5GusGABOCCukUZkcDz6TnmqJHc6zjUHWnpWOuahQw95w5DtjMzaycZecYT4H1JlgYEnYmSsy85qpjlSx7pmUU05h8L1+UtqQW51FyeS2LlaxkJZdKLkXM4sJ9Qz50A8IunlnWN6TTXejGvrRvyKGqOlUuQm6F93zInXUTZAOA9LQDZ62N9Ejl1a2Aq3E9AMQ//TEUHg5pp1O+thyPCQIsiKVJZyvk4YlpsLxAlbfeBJuEmN2kUn3/tQfEhQGr0EuIHCbDAJIUUAyAaaIMIA/K0qhX5RKFv/AJ+D1FHhsLomIbTkhnXQQ1oe7sWG8bHfTYZODnSquRUt+Q4Y9soHik3BrVNwRABho6PSNQWzFYiPOwRh2i00X06dsAgMJeH3AdiMAlDku125v+HpawIMDgM9dQebNPCFA9v1vriNdK8O91MlfDc8C+e5ewCxajlC4XT17YBtcB0u/ezWJKW+uYvECVq8FJCOewi8GP7aD6PTUPwwnC25uYbHooP6TxFu6dQRYLGbpYlajLQkYDEF+jc3qHfUTbDYiCA68XmrL2wSevoPbVfaRbTQhVPOl2xjj97DpKxwmSEoc/UFWyPkf5zikmL7SJxVzJl4b/HMPe+UBZl8INuXArgMn0XbcC0OhHsd4AV2XkZILOtQJQ1Z8ATCsAu5+ngZ6r/7XpV3g4xOxKFf7JGCxWx9YrgCKU0bBiAKZqclkrAAwngMONnxy/uEOszbavDQJXmQyRRRWYe/H0seVytqDoYKZyIYp7Q0TriiS5IOEKAY4SNRwaKfh2k6jtRTnIaOVLAYTyvaWqOmWphPQchOsBKm/0EKvz+prQl3MCJlm6UvB3jmWdU9wjqtPj6nd8JBUfTND5HQ2qipOFVgDS4SjfoyCkXYuTBi6VfscJBi/RQlr7Xo8AUOpYmxODBQViZ9dZFqsVgAQgOb1vcc0HH6uqXZV+lbUy/JMx3LEPHlrPeRST6zhLTJYmWi/DmSbgpQBJRS0clQBeVwHEHJbpJZG1bVAiKgUUBgLeIAaQtQIoPhxDFn0UzvK0hTw6dxXV5XVDbIjzwt/aDfDOIMs8LPGxc6XTS4SFEVgYIan4Jupsf8dmiWKTMOe/2rBl8zLOv5SpgH8yRvejDaTtKtK26iLGuQkmUlm8OpfatflgkqXCZkS4ane78s5UKleI7J/n5oPBXGVh7M90EFA/KEsCyAC94F4vhNcLMWt44GGCaLMCPo2RtMtI2mVjDbBpRKm3JKX5TCVGt+omAJdUfPDxjB5QAG5/BrevaQTcfAZB6+I4FLTU/wBznN9P4PcTTK5W4ExjsnzCxMxpjgzXzAUHSyXCrTz5y/D5qjlv6SBE6SAEU1Buo1duvijjwRKRHWddw+9F8HsRwcEZgzuxFyxG2JH54jnOaZFQ54YQ8Hoh+rdKgMNx8jEfJx/zKQAtJVnEiTB6FXoxeJggLbk0F7GAKLjgkQQTEmHLojBQC7fGWDyJXArL4lxi4S7YYJxZD9e3geOzhb4hUE1/bckR9ircgXfiUhHWGwcUdc69YL5h5AbyRWb2uVkQ5FoRAJSbZ7GPxp0xppsURKyc9LPCrWLBsDwNPrWD2isP8/lvz6cA5XhKO7puCVgu0o48meQj+ZyyKdJO13G+NGVo13+YvyvCXjYYg0dkIVTuSoQ7VRQOR0CcGBMcnFPfkM7EvDgaTFU6mJoXzB1RwNHpTsD6w4yMGLRYy3CWfaZ1TUV+R/czOHrhkBZwL3DBpzFEuaD6htA5+JRAZnbfkNlGCcXXj+FW/FzfkPJDYrqWlRItwFBunYZS10rZohAnBMwajrPCtXLREPbC4eYc0uWQnoPgYEguGehFhZSUntbpaLVYyiItBlzdHx4mqOxHOPtkCxvfoIX1+MdquPIH+3QPPdfUyPjHY4iSDxYLpCU15/0ZSpMYk6sV1N+cGEuGxSlEUIDTGeVZxB6xIS+TS2tZrGQlK7lccmktC90oeGl16XAI8TwR9vLdh2DVSp7qXlVwsiUoT3MOHchs1eF2xlSE9XZWgmzIddPUENhK1edCTEM4G+tGFzhE52YjMOV4DNQrcE76ZFEAGHziCqqvnZBPnaQmGFd7FbR7VUoZ4AYgnESnCz7yDHpxdvMa/G/t5oK/gLJuqmXyk7V1EceAU8j00cc26tkxTr5sXA6HQJVQnbw3QrE3wvT2BpxJQpByAGmzBP9oRLu48uHTCvn07mEP0VUqXnIHIUStiKTiwT86MYFZ3ZBHjMbgsRrDepsqI8fTHJRalgLa0dM0SwsHVYRXayi+fgxZ8E2MJeiOcfgfXkF1L0HxgMYb7A0ge334IGuh8dcKZ5CkRFmgrCQA8F85otR6h8ZpXM9wBtluGLoAAEhfeg58omISLjdWiPQciIKbdXED0P/YGupffJ3wQaooTzQrkJ6DpFYgC03FN9JGGYW9PgqHDqRDtufmyTiHANUWqSwFSAuOaagEANNbayi+foxKT90r5cKyByfgzgZw0kH60nPZ/L7xPuEsGGO7AIYg3pBESvkpxlgLwP8L4AaAXQC/KqV8R2bWZR3JpMpNL+1IVq2C71qszqr0OMcxMQ0XYxk2DkMHu87ou9T6LqPF0+S6cqNl6hRQKhGM3HHMyyZTAehaEztnv7VBwUwL3Vd97QSz600U7ncNXR6ArDeIEHAOFPlJpQQ2nIDVCGkprxMJbuH1Q8hWA2weFxJTx3ZZCgAVI4BI8zgEfex4alXkzrF772yZvpu6diTYGyBulUxA1t3PsjBsopvjJJT18Vz4e1m3OKQCjudC3Ngx+ACs0WLCbSStjuEoXISRcpGehVSAqZhEUisg2B+a7xUeqq5wDsf6KyPwSQQ21XMgIDfXgVmUg0VLzyU+EJ4Fj+H59N1UgFmYDACAfhZ51tNU4zaS9jq8Q9oQ4iv0crqei7RJgU53ImhDKwUm3pVWCpi1CiiczcBHoXFZNJKWTWdAUS3kCaFnuSYqtng19QKuZbTtIbjnm+xV1KbNp9itAdMIrFzGrEXn9cYJmPv+cnD+rJTSRsv8BoAvSin/PmPsN9Tv//17cJ1MxOMjuI8lIl3yEi0LipqHzhbHyfgVbUTmY3RkqUDhfhfJehWeFTBFmmZBT31snMUHSI8o/ze7CZOBi8fAWdZSUNpG2Xx3siVZEq3jgqQit3tl58iCkBo9uCCKw4FNo7zFoPQ3cRcd7J07B+sNCSFpfeYfDGCaMNniqSIpGw6gO7rpYrB5/WHNte8B0ygf4FTHsVRAcisOZt0Pt5/dS71wAYDTpcWppIOwqTCWo9ubwpnEYFFiStUBGFCYFNzUbdD9dkzDp/k5ksWCObb9zXypu15UpYV0Le3ax5wflPU03JBfAfAz6uffAfCneMxisTR1CgCOk1kUVoBThqHZnTSGgaWpaXa8QICir2MXmmncfaMKWQ6o9+h6M8uCtOqQJ13IwdAQx0jVkQx2psYjXEOubSBgWJBYnNDNBGiH6A/hTUKEL11B4b5CkZYDcGU2mo7l+yem6zoLCoaUVVy/At4d5V80h+DaiGOCeavnmNlFVvaLouot6Lu6CbL6fxZlTExxAlnziSkqsEheXXq4k4pPQUyQ+Z2WXHgH/az36CSCLHiEq3hwCOgArhBggl6+XApYWTKG5AbKFQgKYHE8F5gTiK414Z1OEK/RDu6dTmhRdZ0cdkJjFpzRLCMN7ocE765XIIoqRdkZmoVjPsAJqA3Bqjo1AU4pTXNmlghyS+AadCSL6Blg4yl4L8t+8cGE3AThGR6SZL0KZxIjWS/DO6XnOdqqwr/XMfdOz4/0XSQVH1HDhzul57FwOKLxl4rGTQIAWfQhSj4hT+1n4fxrxbteLCSAP2KMSQD/WEr5mwA2pZTaRzgEsPm4kyx1Q1S8YpkbAu5A6gY9Vq/TrBoxMm5MTmw3RBdh9Ybgk5CayDKWHXNwZEhcTEWh4jHURDkAWTAyjpS1YbFKr7fJbE9F5mP2B+blKNzvIt5W3bAP1W7EOS0SUFmA0YQg3ZMwI5S5/xByZyt/j4Ug/P8cZJg+E9n5tB7jqUXvn3dDsF3JHiaVdqQitdRkApgClDmeYxY5pAI88Kmj+INT8326xowqa5Ubk263Cexl4yyGY8iQFlx7bDKKwQo+Ae8UjoP3KKLvTOhF9U5UOXu5AOfBsWq8rCgOigWIZgVuP8xD4aMYYr1Bi4ly/XScilXLBKPWi5PnEmO2osADyE3VTYbmOTL5KKR0eYE2OP/eKSY/fAWFE3cBjKbdDlmmZ1dbKc4koUZDANzuFFI/rw4z35VFD97JCEyUMbpOfw/uzhBvKRe75IPN6ByT6zWU7g+Qtiu5ju/L0uePkne7WPyElHKfMbYB4I8ZY9+z/yillGohWRDG2K8D+HUACNi7b4CykpWs5OnKu1ospJT76v9jxtjvAfg0gCPG2BUp5UPG2BUAx4/47m8C+E2AStSXNWhllhuiEZNSuSGa6HXy0iaK4yn1+VCErgb2/IguTDJJDD8nL5eIP+HlXcgkNQzhOuYhut2srwdgWiXmuolVK7RbVyumiEoenhhkZtZQGBTMTFPIcmAsijf+23Xc/scPyazVboHmnDw6AcplAy93NjeA8RSic7bQ0YwFhXxRUVAAtMlqVxuuN6lLFmD+ziYhMJ5CPniYkegCGHz2huGWMO5UuYjTH2uh/c2+2fGSekCEwXFioMsGvCWEaXADAM4J4UfEeJyNoVwkXWyuTSjTXwgKPirma5SKFISMyRpM6opbZBJDthsQJd/gDvo3A7T/+WvA9iaiqy3c+5uk763/8whsdx9SZdUAshb03ERXWzn8hayWIHf3Mn3Xm4haJQKHhUlGuFsqIm1X4Tw4BtsiuLaslVG824U8ODJzK9sNovxTFoh3lIepv/1ftfDC/0bjvftfbOHmP3yDIPXlsmlr6OyfInpxG3yWGli3LBbgvX1I9+3lXfM8l99IEK9X4N3Zp+ZDWmaL2cZHyRPXhjDGygC4lHKofv5jAP8zgJ8D0LECnC0p5X/3TudaWhvSqOc4Jmzmbptf0+a/NF3UVXZiPmZhn8PdsrwjzTXgeaYsmu8eUrnzMIs22+c3MhezMGXd+qGygoC2eW93kQLnGH14A5XXDvOxBJt921oEmE9jXhaz0HT8wEVjFoqZu5qhRXM6pALJjkqJHg8Qb9XhHfYxvUVp5eKbp8RDoQBMgBUsneRrdOB5qqx7mgNqmZiFFR/R/AxyOMqD1kAZjaRdpkVKHx8niLfqmG4qav1YovLaIWQpwOiFhmnWhCQFhMD0+XbGwGXFRJbGLGxQlj5mliDeqsJ/oOJPDke8WaOXXwdgVWbCnpvJ802U3uhgdr2JqO4avdgsAVyiDdDZG+m55NLOgbIQJ5i80EZwEmbsVzrwarGg6d/TWmDSwlpe3v1t9GdHT702ZBPA7zEK4rgA/qmU8g8YY18F8LuMsb8N4B6AX30X11guKkYAgIqxNCOQzcgdRefDWTgOWKlID3oq4ChMhFlCbcKSUpFIYc+Ls9BpQfWQy0qJgntzmQ5RK3TG1voAACAASURBVKHy2iFGH9lC5VUiEpblImViwhmdR5ewez5Q8CFOO08PZ2F3OqvXDF7APc52P2cSA0Kg+CbFJ6a31lD87iEFjnUvU13GrRnO9XyUioS8HAwuhLMwRWI6uD2L4B0mSFXDZJZKJO0yeCxQuZtlJWSvD5YKlO9yY4V4DzpAHCM4DKyy8fET4SycUZTTzZmlwFnPEOMKj8M77EOeZf1tg6MCRK0IbxBR/ZAuUFPXTK61wfZVLOb6BvjRySLOYjhC8SAwQV0AtHjeeUD3rT/I5iqMwF3+bHAWUsq3AXxsyecdkHVxgXMt6aLeagL9QVYcZovjIP4h4o3w7uwD623Ik062K6YCWPa9uXMAgNzZgOScCsYUcxFA3cwLrx+aylMApgEQgDy5ySPOL3c2crl9UStmwbT1RhbMVLtA5dUDHPzHNK7tf03NhPhwDLnRNLiKyY/dQPkb95dekoKEFgfDEqq9x4pVzDavOx+TOxK3SvC6U4hGBSKgR8gbRIpPI8Tow2RtpAUO4QKFXorSV3eXzqOtO4KC6f2R+1z/XFW0i/oDziEDP2uJMJwAoqIK1OiV4mGyNN04u7UB/7UH4IMJxj92AwBQ+vLrFPwLZ3lCGiAfHAXgHvZMxoUPplkB4Cyh7E+1Yjg5WLNCzX+sRZgPpmAqo+POYmNBnv3kVdTenoDPkqzr/CNE7mxgtlFCcDcEVEGYM2Jmnli1YuZKDseAytjkApwXkBXceyUrWcm55FLAvZnrgfulrDM5aCWU0xB8Q+1Sqs8HAIA78F67S98tlyH2D8F8L6v/P+gC3e47pk6NX3//IVkPrTphNpQP77/2gHAXkxBM8VnIapnwDhYJr06hzrMTsbIPdv8hrewKEOVAITPjBGz/JEtnar+8XMT2vyar4fjnr2H9L46QvLBNaT8VSCx9dZfaKp52FsbHqlUwICMltpiscsfazFzzCE6lNwCjO6uWiUNBBcP8/oh26vEUrgaAVUqmG1r11SR3bhnOKABrzyOQGwOrVrNUqx2fCQpECRfFGYGt3RZwFhkKAVkKyNcPE7BxVrYuuQM5HIMLkTP34xe24YxmKH1118yRrJXAU5FnoIojcp0spiupGL0QJ2QlWu004TpUfqC6vkvPAfc9wr/oMZYDCIcRNmQ8Rfg8WV2tv9gzY9HzyctFYs3S11d6sV4fwbSdq4gWtSJd2/NzLRThe2CDCYQaYybnj1leisViWRd1FhToAdY3bJ7te1sFKPsjcNWCznvQMed7bNWpvk6rSQEkPeH6Zl5pY3q1ivKro6yr+CyivqjTMAtkKq5M0nmOnbvVpBdM5/wDP4NSt+qAJsUpBRTdn85MgHX9L47Q/8QGGi/v0fc1WOj6Br24c+NjQbCAtWBBkJn0Fm0fKxczEJb+e5gZmeYBm9Pd/Fz0KaBW8CEKVoVoqw42i3D6U+Srt77ZJTIXIfLd2XUE3h6D5tPU+mnRQDhgIbulmbzN73ECPuVU+amQkjxMAEXYK2qlHOrTe9Ahenzd9f2tPQXzjiGazczsDvnCM8UUBSCbJWBRks0ZCAvBy2VAoX/5kiQCi4gzUzTKYA4zFbXpVpPcmqIPpmI/ouiD9byMe1bPDy8j2qzBO8rOy6eqyZPnAnH++Re1EliPFg1LkwXdHiWXgynL35Q/7v9SzrLQTFnOFVoUknsP6A9Swt3ZznVr0t2/xEdvAVD+5PHpwgJkM2U5L3yIfj7TsYpALVDWrrxOlorxm0tFpPsPwWs1w+GpWx4y3zdtEAGA3/6QYZgyu1FILf7AOQUCTWHVSdb7Uu3GyQvb8B50cPaTV9F4rZdF5g+OgM11soJ0vwsVQLTbIwIUC8l1PdPzoDq7AZZFpMmDP3wLfKSyRjq7oWpJctkgx8laGKjPWLVqshxAlo2RKrVtzlss0Atl12r0+ln2a44Bm9eqdL9vUTyHdwZkiRUIBGY6h2nLz2JVZ75nXkCcdDKgXSlA57ObaH/9zLBVyXoFcnePNh87rasZuFqNbMHc3cuYslRPXQBAFIMNx0h31gxZEM76EDe2CFClshY6ZqF1H32Kgo6lvREFwW14vyqlN4tpP0P7ctV0WpfkO4ddJNfWCD3rOSaekzSK8A66SNtV03oTAF4e/kv0JwcfHKasZZYFoNCR+sGzmbIKeQwFr5TppmliD53qegemLMNi1GqA68VA7R6Aerk0LbxOUcYJsWGFYdaa0OEm68Ispiw2CSldtVE3Dw0feVk9QlDIsA56LI4DuUE7lNsn16TxWg+zrQqCu1ScpVvwLVDweT44kE8Zez7YfE0I8guH/rtmytIvNKAsiFQYaj+NqcgF+zQuRbF/Jxs1OB16rGZXG/CPx3S/ZlnaEFFM6M3hKEv/WrrOW4Q6I2W4M9q1DMXoueQiQKVqG/UcA5eECkCWA/C4boKSo1t1NL89oOpfhcBk/RHdC9UP10icULapl7W3xBxTlum/4bmQ9Sq5Qjob1KiC98YLtSzS4YByyYLTbN4n12so3+1jtkV6FQ5HtKDpzJxOTUcZelQvCrJeoWK4RJBVpyDnbmcMWQrIKrXn9wJ9Qy7HYsE57cy2e1CtECejhrmenJi/iUoAdpaBjHSjZM1NGN3cgHN0vJBhsSV6TnFa3j2mUmXdM9JKUTLPxeDjm1luHoB4sAdeyuIrLCKYOnPzcPX45hr8vR7taHrniqOs65W1y6VHx9T3M45M1kN3Z2eBj+DuGQ5+mfzfnS/sIdpuwDvr5jJFMooyPcyn46zvitVrxWZPn5+j2a21rPEuQLucrpc5PjPjEKOx0VnfA1Yuwwl8M96CqkMQ7RoOf6KFQNVFFHop3GkK/6xv3CYxGhv950VbbaKmwFcaK6DS0KaDeblMVPtW42zm+5j+zA+j/J0jJLv3zTxUk6tUEyIEwueoHic46SI9OaH7e3hkjtX9dZ3NDbMZpCcngHok3Z3tXGc1dtIl+kO90al6m9ELDZT2aGNyDrtk8by1R+f2lKUbJyjdF8D+IdjG8/SZjjcp0J1UVrX46C0437tHLo8SWQoQbzbgdSYENxe6loVRD9SNNWOVAwD4it17JStZyXsslyJmUeMt+Zk5aIbzwoeoKlCBiea7jY0+dxMAUPmzO8D2pvEhAQDbmxCvv73ghix0WQcR4LqDELwzyHUFDz/xHIJX7oGVi+h9ehsA0Pj390337flO4/MduVi5jPjFHXhnExM8nd1cI+wGlCmtsg6snHXynuic/1d3CYzz1l7OJL77X17Fzf9rd2m3cxpjnP9MjScHylJd2wFkpesmG1LOOsQr3UWthLhdMrwP4c0Wiq8fU9MezwJwxSlYIjB6gXbqQidCXPMwvOpi64/2Mb1NgcTitymzZY/B6BpH+XJ623K5QdBs6WZ8pblK1N6Q5mwaZ66oirkYC9UO0t5/CFYu4/A/onjBxv/zatbRvlHPZUPg+SY2pudQW38AWbMAEf6Y+JJuZanuIzw/72J5LpKtBuEe1HnGH9tBcW8INo0Q3iRAld+Zgn33romNaYtU3yf/bhaDSLeaFORUsHk9V+z+w6WlCl8++TwG4uxc5sWlWCyWBTh1EFOnTnMBzg/dgFRuCGs1IQ6PqWGNQkqKSgD5nTcXrrM0wNkbGkZpWS2ZxsIyFUCjimS9CvdE0bXXisBr6rz6XPNVezrA+fwNIrjRUGyAKPRbDUP0ImsKeTie0sNS8HPBOhYnJogXbdML6N89pgfqT7/96PEpeSynx/x305QCs9rt0LD0cDZ3bNYiMIspWdkVG6EqBFDwCXykyHqjdhE8EXC/Yd0jW3dbb+WnyygywW7diNi0bVQLgKiVqL7DnoOgAFkrgw3GBKTbVMAwRR2Q1ANzf3HSyfhbF+gN8uUDdntJ3m7mjtX30oC2TnpIt5q0mOrU7YyIithZn1LdW0qv8ZQWNC8rcZeeQyX+c/NkZ9sygJhaQNXca8h92q6C76pzWJmxl4dfQD8+/uAEOGUcQyQTcIXAlNMpkgNVFLZLuAO7j4g46WQ9QUaZ5aEXkIXeIvoF1jT+jboJLso4QjqgEmw+LCO12wl0u+D3HaRW8JVXKpC3r5uIMvM9Y5HI8TgPMffIJ5ZqERSjMcUkNPGLOkx0zsCKAcSp9aCfUlTfWWtDjsfw1NjS0RjFP+0h+uwPZUQrqjdJri8JYOo9ZCrAVWYHQuR2Fx0z4Kpfh/RdalmgzzuLst6ulpUiQyf3kojBELzdohiFzlTp3iSDIfxZ1g6x8AAAdzD5yZcQnKiS7MMusZApKv4Mju5Q0C6MDKzbOexmzNsFn9CJAHicQMxzmTgE8XaTFBgOM2qDRh2yVoL7nV0zrtmP3kLhm3fpxT08MZtP2ixTL5DPXENwTAuewfn4HnFrqBiYdzICxlPEtzazepEwRFr0IBoBvJ4a72hCC4VmeNMFiOUi8Z6c9U3wGIcDTD7zPGYNB8XTxKRZw60Kit96gHSraSw83hlg8uFNeOOEKPc6dN6oWUAwqOP0s+tYezmL/yVzcP93kkuxWGgRI7WjSbkYgLP6iLBicTHTAeSyHaa3iOorAlBzHV6rGk4KAMj1+9A9QGCDrPINfXm7CTmNTSGbWF8HC0PT29O0FBxmVpKO+Nt9PWxmbt3Hw671mG8+rIOZety6LwmArDeJ1ZcEADUdrpYp26Mj84GfmdCpMPB20awgqQU5RizN4MQ8j1iibBi27ylG8blCMCHMQmRe2DTN9yhVUtwbIm6rHbFaAkOW6WAz+q7mkAxv1FHcy3g/jLXmuXm9yuV8Y2TOTaEZa9SzuhPVLlFaLk9Ud1FoNRA3i/CnNeOyiIILXgpQvjdCUiuYcxnh3PT1IB2KcEYZ4xYLsr4fhsVLZzSCQpYCBrLshKqf0d+XnKH29gTTzQBeST0Dx5MM4KbFc4mqL0zgOMywexeOJ9Q3ZJCxoYNzOHvfB31DVrKSlVwuuVSWxTuJ3XSISsLfOT+sGxEJ5IN+2hQ2jYIskt7cz4+SUDE8qV+Tig8PCp47nmb+vpZlvJS6AdCyJjvz40jF/8/em8VYlpxnYl9EnPXueW/lUksv1exmU60eLiLZlGTNUBpagjU2LNsPwvhBtgcG5sU2DPjF4ye/DuAHY2AbxvjBY2sAe2ZgGLA8mMW2hkON1KQokk1SZLP3qq7Kysqlbt797CfCD39EnDg3s7qrKZKqFuoHEpl5l3PixDkR8cf/f//3Xc6XqUWMAGD26RFGb26oYtbJ5TOXQk23o9wfwDep3H7HtpcvE/iV3GpTg1xELdtl9YB+z9nH+x5trYpmC/FQ4wKsVshHxsPqIVwlYEWFatKFf6xTvmkJMIbwPG8Ch6Zdl7Rh25T+rIqDBjlq2rrFyRks6H+hMQsGaMVLaVnDvOVFTlYleOMxGG9gW8zng2KDggN5cz0qDlrXxcoKwZxEnIJlheVz5I2NfqDV3GO/abM5t7lvTrtU6IMXyqJueV59FLT3YzxZbMO7HbMBtguvN3BuI0RkRIjcY6qibECuftAWB9qCbMs0bW15yucO4L93bAewf7am7yQZbUEMhNvlm7BALEcEyNmXN1uCLbh4RAAw+IHN5PAeZU6MiBEAK2TkihgBhJSE4FhpESOAMhz1J65CzBKowCPKOnO+JKPMgYE0mwmCc4rNGNdZw6xZXrReM+zcFo5sOTPExQwSCrDlBr1b+j5LSZWgh3PwvLI8GdGtc2Q3x4jen7cGO90MAs3ZNuhzqzBo6O9qBTadA5w3nJlwsiROBis8JjZ2npaQgw7qjt4+luS6Gwo8gCYbFQdYvDTC6LUHrXIB1Yla4DaEAb3vkBor3yMS4E4EGfsQ+vuslkBe6VqOjf2+f05yASyPEGtdU76mTJVISzs5Kd8jbA/nLRQozyTKXkgIUWNSgn3sQFmPYK6OyIdxVQCw2iJGVwTQA7jbBbCxRDgcAEQE1u833BStA7WnXm9KZeDyBQ091mXbJhhoBW7fbPgmrJKZyzfh1HEYmLnqdy20nPX7VKOQZoTMbMkk1FaXBIDVJmnpkgCETowDDL53Ykl8WFnBMw+mw0pl9D28V394KU+G+W7LsrzhVujGYNM59bHZz5uJsa6h8q2Miu57rlfP9JN7YLUiz+dsjXhG/VBcGyF+6xT5zSsIXnuXvuzC8KPQIktRVqgORpR1MCt7VaOezamIb8/JWiQp5HIJsTOy2QG2SXH8G9cxvF0iPE0svT+kRPaJXUpj63jM/F97GoM35qRD4gmok4Vtm4x98KMT28560oN44326l4Z17WAXKvAhI81I7mScGCje5HK/AoA6n4HLIUyERp3PgF4EMW/iY9XBCOKN95uFRrdBnc8gBh1wrQMDAPnIA37wMZ0seE8P6jS9sB1wdUTkZZogQDut5GiLWISf7kA2GlqkpNH7YM7fgLN1cUl8AWLbHg0tGzNbaJfeDHyTm3dWUSsb4Op6yOaYtvYiazIGTB+TCUGelAn4GhzHeKcJZuo0matLYtrGNAuYresoymabAIDptol1QgNKizy7/c7Kigaknsjsa7UEMzqxnNutncUnyKZ2hYXhxVTu7sRuk6LDJU24ZaUJiJ2JqZYI3z+3wUgVB83KXTbEtqglQZ3zqvFCamkHKHe0QFQtKbC9JffY0h1xgqHhfZ121Z5j/92VrW2pJ30IU4XcjWCkJKUm4ZUeh6d1P0zQt44863Hy9cb2nZWWSDIo019m63ttH6qs7HaMdbtgrgcDIB+H6BpxZyFQG9GqpAukBVQYYH2NnoXu8UPkGx5ij9Vk8aj2SPiBD9MWcYqtABrQHyambO0ybQ0uWhMAM7oebrzB0fVQ26UwvBEuMu0x7WRbuhkAPlSXBEBbm0RPFkzQpPvQa3WLsGw2Q2r9DmH/b10jQNuPwG+30177JRO7EG2NEo2dqHd0ObweSDY7o48PoKma9J3tEkAs3GnRPq7g1I6onSJkgU+M7lvW0h3ZHkhGhBpNLQZAtSemH/gy0RodvmU+99OgSZXrdKjQnpMSVMfSpHqd2g9/u0bmoiAzoONlemLr3F60xJzNogbOKQZT1VZbxBAEPao9yYY8sSf2xB7JHivPooWzCI0wj+OOmkBZHF+6MrZFhEiIyIgQARo41O0QKClwqh0N0a7jJlpL07Zbfn0XuHfWlGaP+kSQ4/stzgdoXVQXwemKALnl8IhCHRws20rtRtDIDwAYlnMfKGBFjIAGjeiKGAEgIaPjNSEAi4b0RU0GQK0saS0A0q2QEux+Q5JsEZxme2GYwE15uBvg1ME7BjR9YFZCWVOA1uX2FJwEjQz5rM4C8KyiYiitX+qfbaB65NpbjRJzL6KgRWrMyorEi7YDnFluX3MDnNiC6CvtmQCEBk1u0LY4WNH7wXtnDZmwFhkyGq8tL8QQIjvtsu+b/vY9il9FHQpwOqhX5XuAJ1oek+xF5LXogCgAiIyQm0owMAPrTosWgtNtUzWMiEjJkPuW+OAszZY9tp4FE6K13WCuq2bQhFs/re/UNblddW3Rfq7bTJWJzmA14JwobP73A5q49HGZENTRZUEkJHpQLV95yrZTeZp8Jc0aoSOhB10UNq65ZgRXRoHLvO+ePwqbB7mqKMhp9u1ZRg+D2d8XJQ0Qp8/C4zWO//KYAn7nC0IFmj1vUYKVFbKbY2Q3x5CRB+ULp2qzbFTbHOk7wy5tgT3Oa4a7Q3Wi5pr0NkDlOd0L/aOKkhCnWUGDxrjUgmH6hQn8Bwn8Bwmpe6UFlGBUcemyaBkZR9M2wLatGkSoBhFk5EEuV2B5Qf/3Qmq7lBp565D3JJnl3nz7d6hMvHtrAf9oQUI/qxUtDPpzp7+4AyZVw9mxSQkhG/sWVQrQpKY2KeRs3nzO9wDBIWMfdexsN6QOlEceVJbTT6RV4eaLFiuWWm1Q9YiDlFWS7qvvUQlDXtDvkkrl1WqD5XMxwd59YX8+Son6YztZbJvcJJcHNR9iqpZg0zmSzz7deshoMDy6VsK2rT45omCUIYtZbSjbkOWoJz3w6ZLIWX7KpmoJttpQRqAssXp5l4J+7oD0BQ7+1Tne/g/GtL/3aRVdvDyGigNUewNEh0tEh0uI6doSzP6sTGlvCiVNXIuXRuDrDJNvn+P+lye4/2UizFm9vPuzaVtZ6kxKhZu/lyN5ZoDkmQFUN0LdC+3krwoanOPXU9z6d342AllspYOgZdXO9nwE69/NnWusL+rCflgbHodCsgEbqy+xr7RqQ4xZPoZ+n+QMt+DYrrlVpd7BPuQmaViW8JBqS6BVcelWObrHNMZ3dgiia/gsTJahlhTgNMAxU9nnUOJZyPNW9aEtSnIg0RbufUnVKABSaXcBV1I2ZDKmTaYwzvcboaPX7hN5Tq9DK6RbJKarLW0bDHCprHT/6MpNg8VwVmW1SYFRv2HWglMJewnUG37QMIWBVnWjr9EqjDqeUup2vrLiOmZ1NYG9lnTAVtvcKtNWNqQTtdoKANgbEyZDByGzm5R29DalVldXzeA6mxGmw5E4pD6srA6qZQK7ROLQxV3Ygjg0+I0LTFmjPnkCW4FtlhYo9wcWlCWmK9STPlhZt5iylMeJDEd/xtgf3f/fsNzce6RI58fGs3hiT+yJ/fna4xXg1CAU3ulc3CrUNcSVCap7RxBuEc/DLArBagk5m8PwILgcF5fRzT16Q2XDf7l/BTg6wfrLL6L3+gPLEvVTN9kod5X7A0L4GQ9A6MBaQlyZKsstgvPev30D13/vECr0kD1zYFmxiFIuvvxcP8VrsIrroUecIlFAXoAJZpqU56j/kIP8BJsTeRBRSDGCJLNVvSZuAt/D4mXimOi/61OsYLFuyS3+NNtmvIViQvfJVJ8++kEk6tgHj9xn/+PG7n2Judqmxly6/YfpmJrv2DLs55+2eXlzTJkk1qVi3S653sZ1NhOR/l8mSYuSrv7EVfDvv9Oc/2wGNhqi/71jPPgr1zH5p5r7Yjanzzjue4tQxeGCMPqarUpGw0itr8NwfYjdXSLgccrM/fkK9SeuEjLTCdyqyQCskli8PMboj6jU//rvHeL1/2ofz//9EpsDH8FUu6aJp2M7m3bfdmMKDruyeZ2I6hGmq9ZrBi5utguWY9QPLF2dtaIENhuIuUaHdmPknzxAeOsB4HtYfYZoBPvfOyYE5Lv3221Cg0C1GZkkA3Z3UDtBQ5GWYD+6Bb53BcWNcctdl6cPGjpFAPzOqZV/KG6MrV5qeLymeNT338FIX1M96SO7McDmCxNMvjW1RDesGzekuGbbNuwBZ7NW35rz1JM+6thHYFC1ehvjEuuq3R1q22YD3u0iSnfss2cIloypTgR+55S2SA7pDzYpqheva1GuBslquGgfxR7byeJCoZgQYP0ucHbWlvN7yHdMtoKdzlA9S6Qp7P4JMQ15Xru2JMsbhiazhzfHZ6x1XDFdA3FkAVis0wGyHPX1Kxi819RVQEZN9sVqc+jSdk6vuSLIJnVqrSyAjDdAJMNNaaDJpszctGvmlMTbrJECygqDN+aNtkbo4fm/XyKfBNj50bphuuK8mdSCdk2LTQM67FPcXpOTitQ1JHaScFKnLAwvpE5ZFDWcDQCCkzUN/Fqic9SAicQyo3u/tV83n3VfZ0kG7pA3s1qBDfpQYUAsVnmTorSkzMZGfYov+B68ZQYgsp/lWQW+M7Il8wCpsO3McrqXlp6fakvc9rKsALpxO5aiCZBccJf5vvI9Ivy1Mg0F1HgIrr0eyxTW78JbF5Cx39Y6HfWhdOzH+A2s3wWvZGuiAABcwnn6MPv4xCzq+qLA7geZH9AK6/sU6Tckrx9WVfphtsXQbCseOUfd8dop2Z+21SRYrDoRpfy2EX5VTVuxTmBTfvlBD8vnYnSOUqxudsGTgjQ73QrVn6Ep32t+PNKbhScoVSoYbbc8/ufSNl5JGmCymZBsylGb8T5+6uZMiLITQHb+DNvoH9Me28niAs4i8Buij0fAWShNSKOyHOX+AOX+gN53uCp/HJyFwRIw36fMQy3Jc5ES/rIgEpxu/LPBWZi+WawtYKcFKpMS6fNXIJaZzdlHh0vs/HAJJRgGb8xx9JUxjr4yhup3aNL5GeIs5Cah6tl1oingFJTvIT/oQSwzandIdSAGq/Czwlmc/uKObQNfZ2C1glyu7Gt17OOtvxESyc3PAmeRFZAaZ2Em+I+OsyBKAosF8vilVd0Ps8d2snhiT+yJPV72WMUszL5cJkkD9zbvjXegzueUKalrsEeIWRQ3xvDfvAf/REf8J2MKAPkB5FK/pmMDNkZhZPyc47fiJ92opZold3rw7p1b3of8JvEwePdPmjY60oCt85j4Q5JdIMU1MYsL11oWUHVNXKQ7OpOgA7hyEEM48HbVjeAvi5YLzxZriETDgcsK1/85ubf3f/UKhrdLRHfutc/nyho6zeO1bJWo02cp9mNRhlvxn+04FI+jFv0dlIIcxJSFMHKNIyosS16YoPPq9APbZNrTilnkFWRNJeCtmEWWU3tMvAposkGcY/fby/bWRymKgelKXx/Ap/4HjtrwXDj3la8De/9MG5W+b2zrnvN1cKFEHUBzDP1ZudMDSxKr5wrQs+stsxaqE/pc9vlynufhm6uLxXEfQTfksZosWrZdom6qB/V7H1aiDi6QTwL4paPXeTYF+h0K8mj5wW1BY3s+93/3uLLNXFUNIvj3pxaQJH2Hd/JS4Fh58W9X3Gj7va3jKC2QCy5QadEdv5JgSYaq56NVjytp0LAkax5mN0ruBC2Ht0uc/oKPp/+fh/Qt0IqJsLJqCS8DsOA2k0naBrhdiBdxYbMpJj1Z9XoI5hs7AKobI4gzidUND/Gl97x9flPmzvIGJIW6JulIF5SlmdeII0Uf1xmIfJk2g9AA67hoDTa+TAiGvUnbEgxCkJCx00Zz37bvORMCLPda28oLx9ikqG6M4d9vn18VZVvA2Xm91e/2s2lrstFnutinD7HHAsE5FFfUl8SvJmYFcQAAIABJREFUt9KkLps3ANQLDaHWNP7quGEoRl3Taqt5C1i/BzVfQK7byEFXCgC/+GkAgHfvnPaCUXQBRQk/ICFiB2pcP5hCXN23qu58OKB29rp0Pn2O7Dc+R/oPtbKMR2q1AnYnmg2psKg+dfc++GioyXccSULAaoRa5qjX3gd2d6ACr0EISkl74uWS+ss5hrkeI6kAoM3ubXRZdCxh8dtfQPe+XtFKSZoqy6RFq6dWa7rOa/uWmNjQ7KvQs3T8JiOgfA+Lz+2hc6QJhyqKT1Q9H/5Up7XvT21qsUW5X5akMXo2xeZXXgQAdG8toHyBuuNDJKWF16tOBDw4b91z1ung+DefIp6Kt+80tUFPHWDzTA/9Pz21rOF17MP7zltg1w9IM9UQx3Qj8OMpVl96BuGU+sb7zluN1ulTVzH9An128F6K4PAc01+5htGPKI0upivMX7mG9XWO0dv0jHffPic8iW57vUdp87oXALVCcHhuvdTgcI7Vy7uoYobencx6yvd//QDX/skhimcmkDpDEh6vcf/XJgiWCkWPoX+PzpdOBHa/McXss2OMXz2y/fO11T9Ccnb3YyQFICWU2gq0OGzeQMNhoaqKVsqbBF827N1yNm/k/Azk+gO0TsVS58v3hhCC6wHg8DNosJU4Xdi0I07OtJyAbI7NhaXR547WaTAvUOx24c8z8EJ/tu8MrmHPrnK8q48vBNR1YjFid+6DjXcsuYkBT5UvXidRmW34cOA3E4UjCgxcxKNYBmzAvm+0Trv3C+Q79F6wqCj6340hO4FlBVODDvhsjbobNtWOUWCDnkqrkgOUPciuROjdSVB16bjmYfdkTBBqp63bMHIGUBpQCMiAnmnZCUiaDxqs5FSuYjxq8Vko30P/sKLKTAfHUkce4hOCXC9epHTo4L3EShGw0bAtYBSFCKcFZUdMHzpap8o4lB2P+strmLXloINoWoJXnq1gBQBWkLQjKyr72eRGF8FSV9526fx+N0I4L+FvOJ3f4EqkQr3bBijW/RCKA8FaQnEO6VOfdU5ryNiHv5Gt6+LVX4Cq0yf2xJ7Y42WPhWdxmbls3hfe63Ws+7bN3m1NCFzK0KTNcAKAO4pbomGrYos1AVp8rynyscd2AmyCQ5XNb2O8lJChwubpHnq36Jt8vm6+axTat45pthYKsHwPJp0HEOEuOHFMGKVwCN5aTZmD/TCmLgS2Ll8nWCkty3Wy76OX15ChB2+RQXZDfR3a29NyhQABj1g3Qnqti87btA2pJz2IVY6QM7BageeGRZ1Sqga+DBAtn33vIViWdEy/vSQCkwqKM4i8hli208Xb3xW5RDEK4R03L6f7kRUpDudaA8bjFPMx2y3PaJMQJ4nIa+vRtGJDjCFc0HnLnkAoGOoATdEZF+B5DZFtXRdjxDPCmGWtCuclNldDBKcMy2fpnsUn9H1WSkiPg+t2xecKLC9RTRq4uQwFeKHAC4UqAgINL/JSXVhWtj0J9hFgR4/tZHHBHLZvw3sJwLJ388kYUnNtUsUm2ihNoEWOY5BzLCtQPncA7+0jYmF2v+AHrXy5Zd92KN7c11ss4ZscnpQITjfIrpObG8/XDZHMILAu+PKXnsXgeydWAcucG7rqk22hFCE45dHNoNK08SyKGokD8zmHzNaag/y07+sH2VtmdgD38hrJtQjDH5xrQuKGmTx/fg8irSB01sFkZuLDJuIuVjmgFLw5yTNyd3uRFQ1GYqut7sTWMKQLdI/pXNHxBnXHRzEKwKSykxjLS7C8ggp8ew3ZQRfhWQIZUiXr4iUSnBq8uwFPS6h+B9GJg37txlCArXoFoCc1j7Zh0refM2zhSjBEZ3qL5nMoX6B3VJO6m74/TCqSMzCl5R7R9KuAeERM3/K8Rvcww/TzY1z5LrXr5It9HLw61/GfZpqKzwraHpYSxUBD06cV+oc1srHA6L2SZAxAWxbpcfjLsr3Nu4wi8iH22E4Wl/JOGnP5FI/PaJCsnAnEBJ4+gFPTpMDk7gj+0Qz1swcQd0+bScn3qK7DgKUAWwKuNhti3wagslzrmLTPx1YJODoo9nu24Cf95F5DTJs2KcbB93Kt6+BQ5WsAmlptgN2dpr2TAfjpjDhDzUDSbFxGH9VmCFytD3eyMDBp4ILmBl8mli1bhh6GPzjH4uUxencSO7kBBM2GRlsCsOXQ5bijodIgnYqEHmhx3IgYs7X2jla5hTSrfgdgjGpGXDkDU3Mia8T3aeLODrqoYo7eu6STkh1QX8V3cpx8eRf9wwrxEX02OloRqGuPJuLRn1KwOj/oITqaEqBMZ5W84zmxY680CbHRKSkLG+QUur3VwYiQr/o6vTX9Xe5EqHsB4pPUXsfs0yNMXj0mT1AvMjLyIEOPvKO0tCXpnHMUB12Mv7/A6nl6xvb/ZEVeqVPSDgDeMofyBfxlYWUKN8/0EJ9k6BxWKHdIyQygIGk96UFM1yj3m0WJvf0XgPyGRdFDB7vapFSAY3D6lzEUfxis26AJAUIJzjetVdldWSwi0fzvzsaG9HWb/FUj+YKTNU0MaQGRVCjHnYZmzWmDGbxyEJMAMwj5B1m38uhG7o8yQLJBiVp6vLiBJ7uDzqAyzZZt6/2mX6SFE3sLSo327iRYP92xyEELNfYaxiUZkpCvf55Y9CSkRN0Pke7ryacbWi+Azl9b8htLAlzL1o/shc17mrClijniE61WLiXCaYZwSm0d3i4RzB0uiFoBUtqAtrFg2jDIp/sR0v2G9NZuHzQE3jCOG/KZbeh53fFQd3zUHR/5jo9sTNiJuhei7jXXy2piKENRou4FKAcB8gl5mOZ6q16A8IwQrfFZgfisYSlHXTfnLyvSTw0FcW3ovlk851mRIW+ZI9/xkO+QRokh9sn2QmR7Iaqe/1GKTh9fz8II+hqz2RCQCyhOtU6D7+sZNwBDk9d3iWPsMUz+GWjYvXXHsiQDorBNEhP4BBs3yuoAlb6XDRSaRZGm7BPtFZtz8HWOatIl5SdoQSJXKMesqnGIem8A73TZ6JBodWzm+zQBaKGk4FCzXftBU2gkeENUs9o06cFOA3pyt1cuG3Trfe2JmDbIbkiufa0w/OEMR1+h9ODVP5jjwSsTXPmTc+R7NHmFx2sowVANYlvZqXx6kLu3iKHJJV0xGqq2kExKQBHTtRujEbONJqopKSsCID7JIJISMvZx+sUB9v5kafshPE1w+soQixdpFNz4/RrdN3KU4w7OX4px5fvkcZSDAPF0iepghO6tJvUqljTpVOMOhMFc6EwFC3y7aIhlhnJMAj+oFcSa+qx7V+LkS3107zDafgEYvam9RocdXHGG+O4Sm5tDnH1hiL2v08Ql0hLZfgf+skQVG35TCR7RFllFgV1MvHVhvQ+mtxv7f7whLzPkqEOB7qFmiIsCFJMYUVqi986iuQ/s0XEWj61n8cSe2BN7vOyx9SxYtwtkWYtiz5harVG/QIQ23u0Tmu1dBJ1mbP4gghureSoGQBxYpbDB904AaOGY4xm5+we79CW9uqs0a0BNRUlcD/q3PX6SQO304J01Ghj1TgfePX1ej1uBHnRjeKcaRzGmlTpYrGmFPcnANqlFYGY3x4heW12gqrPBQV2JCoDaZVYyF+WnKeWAi1kStVpDGUq7+aZpez/E1T8gr+bo10a4+ocrKMEITg7CPvCkgH+yRHaTCGKCWY5qEKHueIjuHQMTCi5asaLNxgbYDEVdiwkbsIVVqpZgG+o7obdPPK2w/41mlWRZgXoQYfKDBOM3qd0iqaAWS/i+h/HrzWHD4zXUagUxDWx7DeDNeH82CJ5kQCcijpJC41acUm9/ltpsBstL7H5nQwhQG8yOwBYrijNpTo+AMaCq4W8q7LzRbO3qUCA+XEF29HYEOhszX0Fq0JoJFCuPo+xwDB40Adq6H9r7xo1uKgB2voAYd4h/xS1T/wiFZI/tZKE2m63IvpOsqmuqxwBQP7UHcTQlnVGN3pOLJckFbGdDsvYxAIDP1sif30M4W0P1u1h8jgBFo28eERfkegOu0aIsisiddKpXAYp5sLKyv6n9BfiMgpL583TM4MRhNtIBSQB48MUxRm8lEEkJf9aQ47CybmpQNDgtfutUb48utgFAm48yDBraeOezdexbPgrzPjcqY067TduDkzXEMsODV/Q25A9XuPVbPTz3fyxQDui8IqkgagVWVnYCoRgHEBymqLf7sShb/WjaymvZpLV1u+x1GaIWh1dz+tkhhu9Qn3mgGMXpL/Qw/zT1w853Ixy8TUzvp1/sgOs15epXp4AQyJ/eoT4FgMC3fVMOfIi06RsZ+62q5Tr2UQ58QDDUvQDBe3Rtqt/B2We7uPZ/T62UJasV3euzqb2u7Hof0eES+cjH+rqg9gDgetyffqGHa//4kP7+q9exd7e555bY53QBXo1QDSPUesviL4ktPX9+D+E7p01f9bsoBz6CYKvK9SPYYwH3NoS9rondXYpbGM/C7MPzHGJ315K9Wl2QuobcNH9fJpxs9E1VnsN7lrRKVUg0buzeGdV3GEyFZjdCWVzIfEA0MOptMWOL8d+dQHUjqh0wGhZ5ZTMBxTNXIHKj31ATvkJKyBGlINm9M2A8tKucZSe/Omlg3m7qFNDFUU5WZkuF6wMty6nt1/abVGRZE9XcLLFZDwC0inKOzTM9i1UA55A+hzdPUevsAs8qSwcnjmcNEhZoNEdclitz/G2x5j6tiNUL1wAA3oLSu+VOBG9d2lWdZxVlFbyGc0JGng3K8qSwAUeRlBbjUPeb6zXsXwZjYa6NpYUtKQc005ZJnYYeqh0jE0js29UwhEg0QjcpUF7pUDm7OWRWkQ7rTocCnDp1mh/04C8L1LFnFdurQQh/ltnUqUm/FrtEaCM9jtVT1GeT7y5QTGIoQRgUE8uoY8/iXFxmrVdv/T0sN0cfH7j3ZcY0F4Jl+nECnACah7euLe+DlSI0GYYPCnCaLUAnoihx4ANZgfpAM0iXNXjgQ2ZZM/hkTYVYq3VzbBPYtBkOh//SsFzpFJwKPbCErstbF5ZnUnVjpM9fQfzOA8iIbokX+JChR5iSTtwUZfmiYc/eDnACtLUxffWwwfgBAU62ShoIdyUJR6EHnwlm+ssC5SBA53CD2c/T6rnzo7XN6ZtVjtWU2xe1oonIiBTpICzLchvgtG0tKzu50n3wLKuYtzBbRyLF8WeZxVHQ/a2g4gDptS6ysQZPFcDom3MoX2D+8giD9xJ7DL5KUDy3aweRKbSyAU69DeEZtYlPl+BlZPuwGkQQKWU2zETAaoXkRg+dO0t732Xswz8mbgnDm5o+PUR8Z4HF8x0ozjD5NnnFFhdRSpuq9tYl2CYjLVwnwOkvCzz4TA87b2cYvdVsWYIpbYtYrexE6s1TZDdI+sGdCG16+BHsSYDziT2xJ/ZI9vGcLMqL6Ue25XJ/GLWdyjJa7cqKim+0iyxmGytaC6CF17AaISlxQrJ+9+El7psNgbqSzLIS1b2QVi5OKD9Di1cNI8TvPLCVpQAazkzdRhcjwQSnmI5hUtqkjdJ5J7aQ6W09DZdpyjAoXeiX1criQtgqgRIMMiIcQXi8tgAzkRBcfedHa+z8aI3Zz/WaFLTpr7K2tHQqzVrnVEUJuVxBrTYEPAt82v5wblmfWCWh4rAJcC43LUUtVtaIjlaoBiGqQQjlEUBL5BL9uzn6d3N0jjKo+QI8LdG7k6EcEL6BpyXUagX/bNMI7sxXKPZ71mvlaUksVJsUKvRJf2a+aj6njec1+DIlz0QweGkNPltDxj5k7CPf1Rot5zPy3FYJgnmOehAhOq8xeC+1+AuRUpFj3fHIm9hkKHZCCnBOz4H5yraLzzfoH1bwFjl4KcFLiXwSgU+X1PeO2BVbJXTPzmYoJx3781ECnB/LmIV3sG91PnG+oOyHy0tQ12BxdAGY1YpZPEXZFIscPD1vISUvjVkkSTNh6NgE63bpPEJYfgQAYOMdyF7UQj2iqilm4XsonpnAP9KRfK1LybKiCYqZmEWSEWrPZBCuTsBPZ4QvMdsun0A3SFIaVCZeY3L72IJQu3Upbrwjy4D9XVs9aitCt+oXzHvVMLJuM6TE7OcHGH93ZiP7rKS6Ep5XrZgFSzKq9p1trFvOssKKDCmHqp6tiPAF5wvIZ4nx2+zvTVWvCdj5s5Tk+JyYhcF6nH9uBzvfnzcyib4ghXFXjiApCMGqdVFt3UqtqA9qabdIfJk0MYs4QNXTgd6UcCl1x7fbJkBXxzrbAjdmAcCiRvODHpXwlwQRN2ZEjpRgtl3VIASTCodfjnHtj+j7wTRFNWwWTluPA9oemsnI2Nff+3tYJB+nmMVlTS0LwOGocLkp5N5Ow2FQFlQinGbNIImihojFNWfyMA9kPYjg3X1AYK/FuvEUAi3yuztp9vdcWAFle2y/bJjB3XPq469eHFmmau94bmME/tGiWdkNjDfLbXoQoCAgBEe1N4Awg6qS5E1pVKHtPkNGgyauw9B4PC4TuFXtct63bXfiBem1LuLDFcpxRyMz9V75ZAlWVvCchYYlGcbfrXHv18e48U8fAACK/R78aUKI0MmgIZaRmtXaId9BXlgwHXORpwZOXxaEOAQgd0IE0xTehtpuA3bmWIW08Snme5Cxj+icgshm0px/cQ87382J71Lv4UVFvCBM972L2mVJRpOyiT9tUnLLDQ8o9PMU+/CWRETknWndkZgQnbITNLUhBdVobCNLvU2J85e6uPKtGY5/hVK6e99ZNwV7lWriDIMQ3izF9X/FIFJdDh95KLse/GWJ5FpkEaDeModn2MO2mLUe1R4Pz4KP1Zew5Vm88Bwwv4gnkEkCsbuL4mUSIw7fOm68AMcu6F/o19xjAIB8eg/KFzSQy8o+INnNMfxlAfHufUjNzyCOZ5ROdchjALQ0Glw8g3x6j1Yv/YCW4w6CQwpkVQcjeHdpUMnJwNYGrF+irUijQ/IOUdRr8aL1L99E/1uHjS6J0wa6xrT1mn3g3f7RmhUAGmV0o/mh2w3Atl153AbzAKCYxDY9aoKZAOyq9d5fpxTrja/mtsCp9+qtdj8CrWswbTVaIPYaTDu1PCKABjtQbaVZlynqSQ/S41CasUykFWmO7O5YDAu9XpIux+4O1i+MbBvh6IaYScjqk9w+bPpcH0+kZbt6tqyJPe2k2QLUkx4tSI6GjBx0wCqJ5Nkh/GVpz7V+YYTO4YZ0WXR/17EP/817zTOtcRIy9rF5ptdCZMpOQEz2Jlis+4pPlyhu7l3QDfn6j/4uFvWDJ/KFT+yJPbGfnD0e25BLrMUbCbTJePtdS8emTBBxCw9xmRBR6xgmIKpFbKxYjgb+BNOUVsAobIRgjHJ64LcFlk0a1iF/ZaMhWK1Q7g9sRaLnuJw8aUrMWVpQzKGsUIeNsM/4uzOwKER+Y4RQty+c0vdY7BTaGSEjV8RIH8O6nC7uxIgawXFJDdnuuFl1DB+FCmmVM6tnMMuJit4XTVyjrKEEQ7Hfw42vUn+srwcIVhL+urZVtNRnnhX5sffBtLV2tiZAk5KWtU0ZytCDSEqogNtzu/3KOW8QlbUCRn1UoxjeMrM4i+lnBtibbaDKCl7aoEiNQJJ7r5Repfmg32BXkgyex4kA2BOQnUasSeQ15Kjb4v1QnQjodSwHidlKBPOCaod0jYYSDIsX+xi8l2DztC77PyFZC8MiZvYCMvQQzsr29kbfN1bWqHe7NmbB8g4Fm7WQkjUHP/Nh9thOFggDIMtwKYFNkqK6Rq6jf78J3qlthuwPMtkE5mx8wrFqEEIcAyhLy0vw6CU3oGCYL8i9dCpKTbGWUbS+0CznjqiQgpjB6cbe4HLgI7isWvQnZQ5nguGj4ElBMGJdkl0NIvBEl1kbdSzBoDiDP02wuUlB2mAlsbjpYfQO2mQ/H4FDwTUzIIQzMNgjOMeslhCJ4YvQBMW3cjtwq/jP7mCbfvCywmIcmvPrv6VDGQBQhW8obJsAYH1NoHevRh1r2j802IttUz4Vi5l4BdD0EatVCwT2k7APnSwYY/8zgH8LwKlS6mX92hjAPwTwLIDbAH5bKTVjjDEAfwfAXwOQAPiPlFLf+XEa1mLzBtqZDd9HPqG9mGHvVkVpBzMbDYnqX2zNmq1j0KXnux1ERzoQlWX2nNLnlK68vmvBSPHZ3IrwNMeUVjAIgjcBRd9DthshFMxKC1Y9H0KvUqysm8pVLbSsamlZm1SWWyJehIHNkqxueOi+EUAtV+3rMdmYWsJOsK6X4XpZftCU1DvvKx10y65QzCDkVDkpOwGyKxFVj4JKsoPDFCzyIJyBwICWUpa/rjF6Bzh5RaBzOMDqJnkXQ73ioiyg3NJ+Lqgk35FxVGUJFAKqKC2bOUCkv2KVQ0Faen+WZJCDmNKdxlOspa45qSkFakBosU+eDOeYvmTiKk28xwYvgYbKwCmlb33G95B9khavSDB4ixzVMESgg/DVbh/+dEmZN0fuUXUiYtCabezi1btXIzov4B+vcPxrFFfbebuAuEvoXBTNtWWf2kE0LRq1PQDFDb2IzjJUgyYrEk5XEFN5Mbj5EWKWj+JZ/C8A/nsAv+u89rcA/L5S6m8zxv6W/v+/BPCbAF7QP18C8D/q3x9ozPPBg44V/wWoM+VmY1mpq9t37HtyMkDva2/a/9XtQ6iisJ8tbowh7p+0jrdthjm588P7lL/euwJW+zajEL32Plg3xvL5PvpvLex5pVZxrzUrFwtDyDy3v41t/tIeem9T4ZVh9gpOziCfvU7bjrvHYH1yM+vDI4grE6As0PmT2/SdbgxxPIO8OgHLKxsZN2zOQV60gr9yvYHS7bD9UhSkBAa0lOfrszP7OZW3vbH15/bQu6MDe1orVRwn6B3PLOVgdO8Y9XoDUe41GZg0I+LkyQC9V0nEmPVJS7RzOMCdvzbC6B0aEOuXrsBLJSJoNCeAeja/0H5jRIRc2KClrbFhjALD57psv98Df/dQY1L0djCOcf7vvozJH5+hun3HijN7cYD8kwcIjpa4+g2TBo9R3b4DMRqiun1m+4xFEerZHOzFmxZqX92+A2iCee/ZpyFyujaRVODHU+TPPAO/rxGvd6conrmC85dijN+kcwXvTykT9+Zd1OsN2Is3AQC9dxfkUT44x/A2bQnDwwXk3g5xjBzPoeZNQNP/wfvEfq4tOFlj9tkxYp+jGAiEM83u/ck9RN98G/UnboC/e9g8I9HDiy237UMnC6XUHzDGnt16+bcA/Kr++38F8C9Bk8VvAfhdRSmWbzDGRoyxq0qp+/ggk9LeXGtaZNdG903dvVJUb/Es8U6w28TuXT+Y2tiBt8woFbol+upKARjcfb03JD5FTSRj8RxXJ2DTJaJpafe53tkKLAwJy6CPzYQAwtD+NqtQfJKh3O3CWzRsUBgPwQoNTBoOiLMCsOlhYvem1YSdkZgxX1PKLprTw5h+cg/haXJRZ0KzjbuSj9iSgLRd2+k0fB7menU8pnOUWRZuntfgunJVdsOGj2IyAj8+I9yEzlxwXUinfNFi9wbnWN3sYvSORD6ge7jzRkF1C6umWJAFJD9JbXa4Q/U9YUI0jN6xT89HrlOtRp29lsSInhctAFv/bk5cnKOhreWpQx/B6QasrPDgL9Fr19+qbN+I0bBVLsDjCGy2th4A73QsIxsAy0hVdzzwfhesbuJfatCFf55geNuDt2gmZ55VwJUxOBeA9o7Kgz5YKSE6HVQd6gephYz4OrPcLXRgEAu9E4OQ3RBequAvC0jP8SyO11Sxukxb18XSnz5T1r4zARwD2Nd/Xwdw1/ncoX7tiT2xJ/Yxtz9zgFMppRhjHxmswRj7mwD+JgBEog8WBC2RIQPS4cZ9fuB8WUqw2/foOOMdyONTWp07MR7VTCCIn2r8ge8De2OwqXZp70+hRjTLG3CNicY/6vGD43n7xZMHwJWxvYb6GuERxJkulurEYMdUqqz6XVohuzFQlDaWEf/wCNmnriK8i5+K8Uo2GAGTrVknEAunvH61oTJzNNsIgOID3IV868K64XyD9UtXsPMGrbTpQYj4rMCjx+HJTGyJay0V2YvA0tzGn+qdLmEnWl8KqfLSwMw18pcvU8hBjHonxtV/2RYm+qimfA+dO1oOsyIkbnx/g0IH4YP3HyD75H4rUKl8j57jdUKgQo2H8I9XhEAddNF9f33hXK5176wJ4drvWAyJf7JERwdYo7PMol2za310HPj3j2M/rmdxwhi7CgD6t7lD9wA85Xzuhn7tgiml/iel1BeUUl8I+KMPQgBtqnin1sC1y9zv1vu1oj25EBS4okZ96Hfo2C6Fv2j/3vqsMpWorvCNof3f5OAbqu2A4JdyYppycC+t4WmXkVdaQlG77aQgv9WmLXe+pTivr+EyjtMWPF3wNjTcoelXRakRpnQuVUtS1XKJazTlPwB4qSTa/rxGfFYg3W14QVjg27YYCgD7A7QD3U7/bZuhv2tZTbBpQ1LLEq0N6gkq495WIHfOZ9pG0HpxQbG9dZ2XmLfMbArW25QkX+A3UHRjTFCqVwlGZfARkUWbz/K0JBi8Pr9tl7bVp3Za5wKaVLZty7q8vO0fwX7cb/4egP8QwN/Wv/8v5/X/lDH2D0CBzcWHxitAUWZZJeAGJ5GmqI7oa1IHNltyhidnDfzbgYFXt97XBySJQxiJQ0N0o+tF2Gho9ThVltGxFkvwZIDaHK+ugdkM3r0AtcPWxXs91J96hlCBILyGWq3AogjS1KRAQ651MZfJesj1BlzXkSgurFaGNMjSpTPzPyByFoF9qNUageYBrWczeMsVkr/8KaLdB6xEIgcaeURAx0R0XEDzf0BKYLOxe3ez5zaqakXPhydp8ibyHWLhhqybupiN5vkc9S3bl9psbFRfznRg16Ady6IVzBQAgncEzr/8NHp3dMDv8ByYLwgrI3iTNeh0SBQ47aPU2ZDAwLa5Ls3XAWQmJfWlO1EGPrLd0PJsGrlqQkwXAAAgAElEQVQI7nuo97oI3j60fbH+3A10v76Gur4LdvfY1rJUky78u8Dxb1zH8LYO8poAd+CDlRVWL5GX2Ht3AVaWSK920b2luVuzHMnVmOQH9dIpziqKadQ14PsUSwAgR12KxSQZZc4A4GyGB7/5PLIJw/C9ynKIzH+uj8nxDNFpbomcw1sJls914GUKVcTQu0cT0+qpEONZjPu/NsHVrzaTSC4efQp4lNTp/w4KZl5hjB0C+K9Bk8Q/Yoz9xwDeB/Db+uP/BJQ2fQeUOv0bj9wSAHKt3S6lbADRbE2Ir0LQgBsOLkoTAi15QnAOPuhDLlctXU8W+FDzhZWyY75vZQfN3+Z8AAX+XC+FdztQZW1Tj/XBDniSQA37xKBsZvy0oJVAcBvg5CXJCzKfVisL0NHgJMOVYK/X8GH4TZbGXHd0ltkHJB/56N0S4M4gAwjKzTgnslv9Wj3pQcxpy6Z8D9yRPlCdCP40cbwi4upgUUiZEL3NM9epfK/1mooCSgsbCLchJJbtYCZAnl/vTob103TNfbkDv5ZQgy4R1Zj0auCjGkRgPSfLo1dI5QtAemCGE0PwRprRYG/CAJ0jqhrlo2FT9RoFdK1+s0JvDgS64xHyvQ7i5QBSbw3KQQCv38Ho3QJlT3sdTnZJRYHFRIBzoBOTF1jVth/ikwyKMyt/SPwjFeDHUHFovVpW1lChTxOVDuqzKESwkogfSKRXPChBWbTevQKq10HdcegcfQ/hnOj66lBYUFbvXoFqGIFVCuUVExBW8JrEyIfao2RD/v2HvPWV7Rd0FuQ/efTTP7En9sQ+LvZ4FJKZEnU3PbqFAxCjIWlkpCnxa16yb72UNm+1tm6mXK5o1WmBs/R+3/cb2jw0Jej1YtnyYsTVfYJl6+AkK2vwszmt4kZly5zX7HXNPj8K2iJAJlYSkTaGioImYOj7hB7VVa5yRoFY3iMODT4ZE8gHTXVnftCzIkZ0wbLhtdArqtzpEVZAu/A2TsK5VUC33pGOORj2KFvlavhGDTUeAAQ+BRu1hAF1nl5FkwRyvWn1IxMkPlxeIyzB5kaMaFo2/J3aLa93OhBLkk4UZ9qtNxW0hd7Lm8KytCCaOsNPAb1Fm86hhn26vtwBRa02ltwZoAK6s88P0DmT6N1a2WMowShA+NaZxSUsXh5j8Mac2MAiz6aV5aBD8PjpijwGANUwgn80o3ugKQONLg15R7JJS5v74gmwpXkWSE2NbQh0lu3Td7tvnNH5BLNttUVsmvZAdXVqe5mgPBiCSUUaKQDyocBb//C/wSK9//EuJGMPwQgA0Pu84MKP+x01X9AAfOrAOWYTnGsJ7kRh84BHof5fH1cpe1wmBPKbVwjFqQNSfLok2cMksxJ+AIGUrACQ3o4g8JtgmEZ9qlrSYDTv2/N7li4QoK2Vqpocu1qtLJFK+M4pyglxOdpBrZmdVehh9sqBfY1Pl3QNEb2HwKcfQTyTBqGqikYbBYxRDYFx/zuR5bwwr8lOoPEyZSPKZK6bC5r0jahSXdPn5gv4d6fw704RTUvMP0E1DiwvkXxiB8kndsDKGsV+j0SgHPIegAY8UQo2QcM69lD3Ait0JCOPFom8oP97IbVdSoq9OAE/cboAk0CwrFANQ1TDCNWQBlbZ40Res1iDLdaQHg3Msy+NaYDrthGXhdeSvZQhUSHK2RxIUuId8SnAWne8NoGuZjOXkdeQG0UBPWdnU4jpCtFJgugkgVptUPWIyMeSBfkcmNP1Yr6yE6dabaB8Du/eOUSuIHIFL1MXBJM+yB7b2hC1RVzDooikAYBLi8QufMcPUO8NwW/fBzRSUtUS3JDVuObWlJi/zfEZax03OFqCRZGl7pc7PTthGEIUAGCrqInsG+DRJm1xdVrvSBdQsU3abgvQxC0MwMwUqnW7DVFOUSE4nKPcH4CVFeodihnwjHQ4d7553PJuwlsPKF6RSesZyEGMqtdDMF+1PQuAIMaOEDMrK8u6bR42vpQWSGeKsRoPpyZP0Zn8meBg/T7UgNrqLwvsfTO1Jdedd8mTqiZdBEdL5E/vIDLxBh0LMJkmU7MCwW2BoT1PrcAGfagwgLfMrGdhCtlagKadHkbv5hBpReS/Tg1K7/0EbDS05fOD9xLwpMDuH2u+S0MRoBQB8fpd205/1hSCmaApTwpaiBxCHNMuujdVA+bLClTXx/BOPche1JTD97vw1gUxj+u2esscGPVJkMklPOp3wUrKWBmi6Ggq/2IUkm0T9LoKZbRtuBjgdAl5rWqZUSzT3zOMWiZrYSv5DCHMlgvttgWALgYSFn3J4hDLV55C/wdnYECjgs6FZbOy9Qhl1dQZdCJby2IIdFlZNSplmh8DZdlKk8EPqG2GcRqwqmf+2brl0qpOhPPPjjH59nlzrjiwk5UKfOQHNJGG91cI5hvdtyaF2N6qWKUwTSjDgYa5vJJQIgCTsuGjsHUQDZrSmk5FurUkkBK9dxY4+srEapR4iwwq9EjnYzvtZwSQzfYor6k+JW7o7nkl4c0FMXA7nBw85WBJ2hLDVpwTizaAt39ngOf/waa553pLZ4wnBU5/cQdXvr+hSdnVjPHFFjNZ3bCZmb4UHlhaQnVJRpBrRTMIomCUnQBeqjNNMRXxKe1FmW1Eb5YQK1atwA2xUFJYDhKXjFf5Hs5f6uDK99ZNJapU+AupSKaM1uOjfn61BsoS1bP77S1HXV+Eln8EK26M6FimXH25IQX0JKMV/RItzJ+KlYRzYHkB/5jo321sQuM6yt0uJt8+x/0vTyAHHchBB3yZYP3CiABJ/RDh/RXC+yuarH5MBqUf/xoq8PmGfpYp0ht9oKpx9Q/mOP7lEY5/eQQUJbJr/Wb//lM0lmrN0KLCzd/Lcfa5Hs4+10MxiZHvdlo6o6ySGL+e4uSV3ocf+CfRtpwWE56WiE+yJvvyEax/WIEnBURSQiQl4VI+QszyYzNZPLEn9sT+fO2x3YZsxyx4t6O3EEWrHP2h3+EC9fUrEG8f2upOOc3AB31yn125w9oncFWSgNXa5X8I8U5wtKTtjCZzUd0I/Iy4NcV01cQR7txvuDAN32UnArox2HxFhD1OsZOh9DPZEBaFRKK7zSOquUkhhFWR52mJ6NZ5Ay8+IhfeP9tAeRzX/tkRBdYAIArR/95xEy030flRF9WNEYLv3271LfNJDLgexA3ruZSkYJZkpOsBcpXZkhjH7fdNjKE0mBUHoVpLKgAzCl/9ENFJgmrShbfIcPX/PQYALD63h+H3HmD9mWvovUaggPraBHyTU4zH95rtkZQ2G2LQjKyioCtfJqRY5pSzq7IEy0UTRA495Ac9eOsS3iLH/td0hkJwYh53tlEmA3Xt91OUO3FTjj7poY49hMczVNcJ2l8OAsQ/OiZv0HTN/gAYRFA+bX2sVyc4cYBW0t4zBqA8GMI/rtqaH3lB8ZGi8WRXn9rB4Dv3taJdZbNN/tEM4TSDjDzc/yuEEendk4Aj6fhh9rFJnfJ+324hbJXmlrVSpwdU26Ymo0ajVAsGqaIE39FlvSaGkGUtdTGTOpXrTSswJz//KVLH1pyWrN+l+AWnFKNVSNMIwxaE21UMi8JLGbbd87MosjwVcqlRirrSkT11tZEezCpk1/skw+cMSEI+Fli9vIv+D87s6/WkB7EkiQJTZ2HaYZCRAOzgMAxWlq8zL7SMI2+Ct/q1lkq8uZZNSpOcG/vhAurqxHJU+OcJiv0egqMlVOghu0YTYXxrhsVnrmD4g/Pmeg03qCEl0rEbSGnTui2hokraQcYcohnDqG76f/25G+i+fY5q0oVISsuSXXY9RGekCGY4IoLDOVQcYPHSCKM/nTUQbkniQHU/tDwmNoXpPAumhkTFIYHQtHJ9azJIm74s9wfglUS6HxFbGkCBSilRx36rfL8cdyz4ywZpOUfd8VD0fcQnTUbpG6//XSxX9z5G7N7abFCzqi7EJ9jBriWtlWl2eVp1iyBn9QvXiPfiGk0c7OgEuLYPnmSQp7oyTUODVVG2pP9aCE7nFGKdt9TGkk/uIv72bSs1mP48SeyFX3+zTXun26dqSQHYsmzaa8hoXPZxV49EiFacRdU1eFYge5ZWiPA8R/T+HPnNKwjfP3fYyDnkIMbgm3cbD2XUh3j3vo6ONwpZyQsTrG542P9Hr18c1NLILDYeAtNaJo0KnASMgLMJPuvvGX6J7XvG0r5FZspuiOBwjvzpHYTHa3R+SHD69WeuYfiDc7z31yd47r97p/V9brNNtW0D9W0FljeBapUk4L7fsKKbfi0LKOf7wbyA7BG9PttkCLRinN+NLRozMBSLvge+TDD6dkEe1taz503bRYQXEKxGvLusINLcplq5eWZ8H0rzsTDfR/byLvpvzhC6ZMS3ToEwgJg6C1JZIVisLy5UAPiwB8V7liWdlfIjKZI9Xp6FY64n4ZqqKnjPPWuzEXJJdRkuEQxlNYILzODKgYNXX/k8ACA424CfzqzCtb1B5pi7k4aXYKXd0mv7ULfJJeY7I8u67LJoFb/0cyiGHoJFZYV52CZtUpiO+8yPpwS/XiztlknNFzY9yipp9UPFklzWetJvgEcVbQnUfEF4E5M90VkeAC1GZ5zNLrKBa6as5K++DBnQ9JiOObrHNeL7JMRjq1C1lF751MRqY7DlBvXBDqqej+CQBoocxJbt2lDAAU31qMt8FRyeNwzpbiYhyQhSf+cU7/1nzwMArn+tQDbxoTggcoX+W87A1Glee8/jEMufG8FfS3TeOLGvp5/cAy8lwlsPMH+FJniRS8tCLqYru82rBjSRZTfHloKv9+otna2qIHdHePALNHErDux+a4Fb/94QN/9PDSITDOnVLvIRR6h5Sbq3FlYoSQlms0L5OEQdcfTeWeDBF+iejV/fIB+HkD7dF1MbcvKlIQ5enWN9s486pPfisxL3vhxg9JZCss8RLGh8R3OJ+DjH8rkYk281As1/ePS7WJ/f/XiDsp7YE3tij5c9tp6FC++mFxwV9ReeawqCNJxbbTZtHMYl1oppPPcsAKCe9CHOFpQHd1OHBnvhivNoCLeqZQOYKdsBSMtgtb8LFQdIbvQQ33cqYwchgiPNfWD29463YcwKEOVFS1dExQG4YWzaii0Yb8WqrH8UM4pk1w+aVW4SITreIDvoooq5TdeJdU7uq6NSZlbJ/KBnPam6F0Ksc4IgnyeNAvlsQ0VfpYNPMN5QtaUiN4ipqGy+Qv5pgvAvbgYY3iqsyJBhqRLr3AYoDUGvsXKnXSS3uTlE980HYLVE/gwFIoOTNepBRClFN76gId2uBkw9iEglLK+QPTOyQKfFzQjBWsJfS/va8pkQk+/MiC5PH7ccRSh7Arwk3gkTs6gHEZJrMbrvr3H2eQqWj19PSW1Nj1UT1yh2uxBpBeVzq5Z+71e7uPL9CsGqRLobIBvRZ6+8trRaJKtPkMfkJRLf///+24+ZItlHNCPp92cxg9s3N0mOuhCX4QwM4tI9vwuSeph5AlUvQHx/Y6UEshsDRPdWNjBowVofxHbte61AFzVWNgFU87+2VsDyxzDlN/R1TJIMn5kotgegC4gyFkyb4Jll1Db7YgfUZIh0P+w+8k1DbpNNqN+HtwqsngoweJ8GTxVTe+N1jsWzPvqHDLHTVuW3GbABivMQOK2A1DEAM5kpX4DlsvV9ABaMtm3eurRxgGAtEU1poPZv6S2aDKF8oc+j+T02ZdMvaCYA6XGEM2p7/7Cy/Wf62kzKAFCHHEJ3txF7Gr9Ro+pweCmniWhuqlwNHN63KmUAoD4CZf1jO1l8IAiLc5s5YJEuL48iqI2jJdLtXgoJt8c3kNmUovj89jHk9V1KgwItZmcbHDQkLGEAdW6yIX3yLnThlzEZeYSQ4zrtBlC2Qre/eGqHhGpBEWuWEsDKehmrDe3fwyYtCBBCVHWii4OsrNpFaHAK14BLpfjo3O1BVHeawaA4QzEKiKPBUf/iKSldlTuRRTzyrKJVfVPaydHoeohVDjBmWZtkL7L9YCUN55vG03AmY7ZJIUc9cMGh9FzjbUoM3ldYPhOid1SCVzRpyE6A/a+dtbROq14A5XMq43+3sLUeyqf7wjxui9eqQYjw1gPIUc8eD6AB7M9S1IPIDsrw1gML7eelhPRo1HmJhLcuIa8GdhIaf3+B9FoXTMJ6G/4ss9orMvTA4dt2VbGA9GMwPZcUoxBeKuw9MROf0ZiZvRCB69s4eivB8rkY6a4PJqk9AJBcjeFvalQxt9weQDv78mH22E4WTHCo1v8O/FtKOyAMHLodmdd8E1uQ8BYc3MH9QxI/A5uvsXyFiL4Gr923WqH2uGUJ6KBW69i6atT+hq7LMKuAgfiGzeD1HyQNeo4xIlg5brITNhWpB5Ad9Ga7FAaNC2+2JE60nxrBL0CvATRVpGgmEQYAWl9DRnRckdd2wlMecPpFcov3v7HA9LNDjH+4RnZAaezoaAV/rtPNzurLwImuPy2aOhcDY/a9RiiFN9WtLSYpc41CQOTtLXPvqMTp5wLc+Bc6rZyXUHGA01eGWLxIn73+VYn4JAUrpYVnA4CqSQ+lGkZWgFikjXxlNYjsym9WdiNebPrNwMernm9ZzOpQ4PiX+ujfra1nJSMP4XkOxZk9V77XQXiaILnRxWZfYPc1HQSXCiKXdE69vWIlbWlYWdt7AwD+psbmRoz+YWUnK+Vz+BsFL5VQHHbCCeYFac4sq1b/suonKwXw2Bl5EjpmoAcIi8KWghlqRzPjErNcm50YshehnvTAkwKD7520PqeyDKyri8PMip0kYEMaONDixdsCMmy+gtAl1KZCs9jtErQaQHmlA/+MHtxqGMGbbohD0qzKuuAISQrWiRv6990JjKq67QNdf2L4Ou22xmmT60G0StO34jt8ugTrmMwLrb7ZQRfhNMPenzQr0vAdKqAKz8ibKycdsFK2YhM2W5NXwPm8YeE2Xs1iZYlr5KBjFc/drY2KA9qG1bXNelTDCFUswCuFG/9ihQefIU9g/HqC85c66DyQGL+pYzycQZwtUN28gvHrKcoBTcbBNAVbbiB80YCaygrFjZFlfrc8rVlFZebvz+megmD/Jk7ApKLJH0C5E2P8hkJ4vEa1Q9e2uRpi+MaSCg21VyU8jqoXwEsldt6ummI4KcF9gXwcIj6i5yM76JIYdVaARYHlgg2P12B1F/mOB5HRoC/6Pnq3VnTsdWGxIiItSe/lZI3sxsD2L6se4r1fYk+yIU/siT2xR7LHwrNgnIMJr83uDQB1bdGaJpMB6C2KERAaj4i7sdttITABfKDWqd3G5AU4KBYgR71my6AzISyKLFyZDQcEweWigU/rdtrf5pwa9ATOwVOakyOdBYDvwX+Q2FiGcVdZrcBWOu7SiWgL0u8SjZ2hBpyvIK9OwLdiDa0iMjcecUlRWyvrY97XWqdqPGxnAvIS8Z3cKq8BAMsK++CYVdkvaytKdKFtSUY0AdrjqXe6VIItnbL3tABLQXDnvL1FBNpQcbHOEa9z0vjMS4xfpz5LrkXY/VYjwAPQFkB1Y3jLnGJDUge2swpyp4eqFyA4XNs+NxmT1jZVn9ONFZlSeJZXkKFns0IiLSkuwRtcyeDdDYpJjEC3B4DdZgSz3LYTaLwZL61t3wbzXFfYtj+jfNHEW3SQNzzP7TZD+Q2tXr7boVhK7NvvUIMf3V94LDwLJeXFiUIzP8v1hliWXGKbsqRJYjwCW22IZ6AgVimrkFWUH0yOkyT004mgfA+LL1wlcJRhsDYCsmUBNhyADQeEsotCqM2GFKL2dughjkL725xLLZa0NTCQ6Fri+F+/CjnqEky5qiHunkLcPdUEJRXqjg+506OfXkjxi7OpJWpRmw3k03tg96eQs3lDjqKBVdXBCHKnR6XMJs6iiWgMOYvapK1gpyWqMW1/4NDiS5IGPPmVCbJnRlABQayrvQHFY9LCvpZd69u0Zz3poZ70iHwnDlAf7GjAGGU/+J1T4PScULTzFTBfod7poLg2oICbaH5I5Fc/G0UJFCXygx5Of3GH4NSc4/ylDs5f6qD/zgpv/Ocxjn9lpMlrQprAjs/AdQqXSUUs24KB3bkP/2SJetInANbZDMtPjVD3Q/qsJpRhmxTlpAN175hg/vpzhkynjj092RUoJjE2N4jVyluX8NYl3v83+4h+eAh29xhilkDMElRdH/k4xOZGh7gyl6llB2NlDZFWkLHfxH9OzwkIeDaz7eJL2laFx2t0by3QvbXA7FMd8PkG/tkafL5BOQhQDgJ0vkvE1/zOKdZPd+wPLoHnP8weC8/ikewC1b5eabSHwALfwpJVmtnJxjWVXYxhMM3rEB/ngO9j/gVi1hq+dgqroep0KNVEiKYgKfCbQKQTwFRZbduodDtMiTCU0sxT9LrsBJDDiHQldDaEZ1Q0xDQtn8nIWEX3reujc9dUylw3AVWLbXA+W8e+Ja+xGQ4D4XbabdreP6zgrUucvkIoxckPEpz+Qg9Xv1YgvUYej8g1kUohG7Fkcy1peaEft6+BlTWYqzhm7k9ZN/2q2+WtS/QPib3r9JUhOg+a9o6+HWL9lML8ZTrGjX8eoP8e6LNf7ODK92klD7IKEALl/oDEq/W99NcUSCzHIUTq9I1Urfb66xrlwAcEQx1y22feusTJ5wMMvietTsjgPdVky7SnVAw8ROcFls9EWF/v4OpXtaeq+6zq+gjv08JXxj68wIfK6PyGq0NkBdbXA/jLJtgezaR9pllK940a7FOAU1/jj2Mfm8niYUArmGCd7wGF9hpMsdk2PuIhx1C+oEpN38P0ZXInh69pkFPRSOEBVJnIBG8efN/T3I7NbwBA1j4+AMRHG5sJkIMOmAH4dDxk4wC9WyvrzrJNCTWIwbggT8FodzpEPu71qVCL/7YmtoayTTifrR1mpdoJRrLca7XbtN0E2kyGYfwmx/zTFQ5eFcjGdG39uzr7U5S2dsFeS1ld6Mfta2BlDWjAlEsz5y2zdr+Ctm1xQroaixeVDWYCwJU/TTF/2cc//jf+DgDgd777X6Cvr2P12QzD9/Q2Ys7AuEC2FzaiSr4Hf1nSZNET8JdOoLZWrfb6yxLJNSOF2DxXIimRPNOkxAFg8H6DCzKTStll6N3KUXYizF+qsP/19rNa9gRCmwHTeiH6/PaezoB0l2HwfvPd6Lyw942lzRYXvkfM5Poam5vwF5D85ok9sSf2/7P35jGWJOed2C/yfvnu9+rV1dXX9FxsHjPD4ZDDS0uJS0KSJXG1AiQDsmzr4K4hG7Ih/WMvbGiNBRb+Y1fQeiVopTVXhFaWBHkhLbRa6ljJpERyNLyG19zT3dVHVXVVvXr17rwzwn98EZGZVT1kSyblHqMDaHR3vnyZkfEyI7/4vt/x/227dyMLydBUraKFYJg6MZevd2HujajUOC/ZvZnmqeRehfVX8otIux7c0Qyi6ePcH8uQVH3XNDV7knkeGdjaTnFsu6QYHRcJReZ5lDcwDMSrVDL0dmYaEyFsU6NIpxc91I6KMp06vxFltMwBCuNjJb0njw2AoNO5oJxBORGZCy0jV4aSm2GqYc/qc9V35vvFvqaBaL0Ob28Olgts/Tn10QwydL9CYrimeqnn5LbFbEuDhrSDW86riuwKjyKXcOW+slxUkI2aXp7zQtVbtqzh4MwnCzwC9yyYQYatP3HwY1/5WQBA3GNgzQYy30b3sy7mZyUZa88Aq9dgJAXOQPiF7F45VBe2CSPjpBmqysphCnthw15mYNzSv6UwGbb+lIE3vCKZGefIu3WYKJDD9lIAnMObCHSer7q4cdvA9KKFxhW6RyeXXKwekAxjOd/EGx7csUDStDXJrHYQgbd8LM83UL9RQm72mzAyQWppZabpX0OD857ghrTNFfEu80OVJGfFgQwkyQ8AEALmIw9C7JXwEHlOtG1ZOWHNBsR8AT6tejuWXdT5+x4HQGxHPhqDeZ52F9PNdsAvrMPcK1h6+dEIxrkz4NsyYdTtgs9mMFotchST51j+wJOo31jQzS+pzmIyBdYGWkdBq4Fv78LoyyTgCcs+fm4VxixE8BBZD/hfuA6s9jQ2g3biYPMl8vGExkDZ75lGoYNxplA5F7v7MFrED1CfKxf14U88pWHGZsxhTyLtNKYnpyldpzi3UWiOTqbEK/Gswm+009Sw7tG7BuRmDkmN5gLRwIW/R2t189Yh+GxO/Srlp0SSEmP24Aiz73wIANC8MoewTQJDLdKqRcB+oduh7oUbP7KFjc8GsJ/f1sfmD5zB9KE6ul84RN6n3yFtOXA/8yLYhS1AyhkAxNewbh1h+KHzaOzRZOJ+5sXCRf3iGex9F/FLVr4ew9se4faHN9B/nq7N2Zvg9oc3sLgADJ6j5639whjcd3Tfs3XSV0k6LoyUw9seIXh4AIA0PYbvHSBpM/RfSOilA2D7h1fwwG/sIXh4oEFZ/s4CN7+3AysA0gbQuUITw/SigXP/8Rj77+tpYSEA+NTitxDt3h3r9J6YLO6Kol4mkj3yoLas09ECL8Gy8xxGq1mQumQrE8nMR4jurIhXYr6E2OiTUrdsCr1ZPgeTuggKJMU6bSo7KmUrVY05twEY9GZWSSZnR4rw2BayQVPTu5GRTSCbB4WTloJ72xapcU1KUVNJiAaA9sNQY6JFf0tiNAqaDEjIuFsgRQHovvOHzulcQ9JxYc8SQhXOosJ8d7gALBN50y2AS2GK47f34B3n8K/LB6BTgxlQDkBdIwAgzZCutWQ+ohC0UajVsnCNUkw3DscIHicimRlTtSDYqMEbxjpHYs1iEr4twb1z34YwGA7e5ePMfzrWE97iYhP1mwsYi1iD5vKaTS8POVZlCr3qqyqHqv1YnCHv+hrsZaQE9w42a5pKznKBtOtVEJz2ONJcD0XwAoC84WB+1kXzVozlBvWrfjvW+ZxySzoO3OMY136oho3P0Oe1gwjBpgcjFUjrBrzjUoQkh1/ZXgLAM9keVXgAACAASURBVNd+HfPZzhtrsnh3/fvBg4ItaXbaYPU6st09/X8AyCdT+qxsH6ceHBlt3GkfAPoBV58D9LArIVsAOH4PaRv0nqHzZtdv6n0BmgTYzduVY6vvl49Ttkg8+aCWvwMAyVYPcd+pYPbV8dS5Mun5al04V52oSn0oH19tUze8mqjU+ZTsnPrcmkU0iZT6fbLvh08rfYUQh0/52PzzY0zeQm/Exs1IHyPZ6uljqj6dHEfVymOUtTxYs+jUQ3qn6yr3qfdiqPfNWh4On/Ixf5y+1/2si7XffRHi3Ab+6I9/Bx/4qY8CoAeG3byNxd95hGQGT4zN7NEO/L2oclz7+W3d32Srh2DTg73IwW2mj8FbPvY+2MPW7+9UJh1n57gytsfv2UTn+QkOn+7i3R99Dld/8mJlXMKtJuovHuhzlb+vxtfZOcbOD25h9QtVlrGayMrWFMYswOSdm+h8fk9/HwC++MwvYpoN30CsU4bKRAEAME0KSyVEuJKzKIWp88fW0fziDuUuenQzG0r16hvkLMrHmF7uoPssDWz3q0QQU+t2w/cLE+F2EyzOTh1br/dLOYuTxweAztfHelte8u688X01PPhvjzXJSR9Telvwll+Mg20R/X3v4HQfgEqehsWZfmOVt5thqvc/mbM4WaJWsnEANK8CAIyUrqF1TcKcWw6shVHJjeQNF0ZM3JZT4xhE4JNpUd2Rfa30+eR16YqCZJu2Pax8banf6oy7MDKOla/FuuoxP8u0K9wHfuqjmP03NCE7/5sHu16HO0kLsFMQ6T7Yi7wyNmZYvafKOQujBCJjudDlWfUbGxmnib+UU2tdI/BX52qC53/+bfDs6v2/86MZHv7H1K/tj9TwyC8W9115fNrXiKIedylCU8s6dU+rseItn/IwJ75/X937frvf7rdvebs3liFGT7zrhM+y2e8V/hwokpMijmE8frlIGkpzILFcEl0cINu9E5qWwJ1zFumgQRgL5dGpAE0eWRIK3ytASiWIt3Y1Vw5nUstR50lksm9+qQn/gN409v68gFI7NiESVTMMsCBC/OAqAMC9ckjLK84xf+sAzZdlxKNEdqV1H4DCwCYI6e2jAFiuU8ClTwrr3EEsWEQRxIUzOosfrnnw9wgl6IxCXdUhApPQFnwA5Sx43cX0oTrar9CaePRYC+3tGCzlp/ITsEywMC5Ytko41zD0NgBgc0nJP54ieuI8ACB3DAlrNoBSxUc5sMEwCpcveZ3LLR+Nq1P9tr/14Tou/N4xWJwh2SRilT0KdD5HuFYhY5ALgl7nXOdT9DIxzsAbrhbyVRTypOPAv0FRjMrtcNfSOQsjSIqqWMmrNFrzMXzMxuanAwzfTuO98vVIw9CFyXS/kn4NZpAhbRWsV4AAX/YiR7Bm65yFM4mR16hSZc6KXN5fXfv1N5b4DbNsGI5/aikikoSMiAFkN27p7cZkoQV3Wb2O/OAQzHGQS+l1a38CMZmSMnf5eGVBXPmjO1dugy8Dqoa4TqGwPZ9DSIYn5pJv4NeQ796GubEGfkQVEsM0qWrTqNP55DnyFR/2/hztL4eai8Fncxj9Lt3Akzn4gJYn7PousUnTFM7zdJ3pQ5uwb41w9J1n0X1hViAtr+5AnFmHKOU8WJqRl+ZsBqPmaSQrklTrkBqrK/ra+eFRwTVZKso2Ta7B+YZWxPJ3SLjH2xsBeY6aTP6K+ZzQjGsrMBSXZT6HsTZA9yuxVj5fVYpYQYT44XU4h3Qu3qqRz+dqvbAbnC+1likrT8ppCngOkCYaEeltH5MQTZ2cupQBEe82wG7epr6pilC9huP3bKL9CuUobHndF34vxo0f6OH8H060Zmi61oJ15SbYmXXKFQ2oAiXqHtjxFPN3ndfK2taVm2ATqZp26awW5mlsL2AeThGundHLSvvGEKPvPIfUZ2js0W/j3yRDI5VQn77rDO274Nj8dAD7OMD6Z2kSNEdzzJ7YQFZjaNyMNIhs8dYWBp86hLi4orUzvO1jzN+9htw1wC2mx2z4eB3rfznC+PEees8UmqVp/Y1WOnXWxNPOd1cmC2t9DXwZ0MMFIL9NyR4Rx7DObBaVj9UesLtfqYGzOKEH4gTcuyKrd3aLNqYpkbXSjDgC8qF0tg/B+63iLQ7Q//dHNLmUlLuZbZPgr20XEUenXShJS7p5WeFLeI4mkoFzxAMf3v6ySIA2PL3eRFZoYrAgQnp+AOvF6xVNDeUOL0oCPMwriE8VQ2GlyQEUKFAZWbBet6p90fT1ZKfKe+ZooVW40xVVIVlqC8ZT9oVRoolxAJBsdmCGKYzrtwu8iymNl0tO4wAKm4Ug0GLGKlrgDY+k+yRKMWs4sA9mSNdaiFZlviARqL9yBBgGFo/24E4kjmJ/DlFzsP+eDjY/sVP0V0aXykYBKCIx5bquxk1FFul6E84tGfmZBtLNNpxbYyRnu/pc6aBBVSR538wf6aL56gTRmaaOlACQzQTIl8S9QUnpdL0N+9aI4OKmWamELR9ZQe32srAoOFiQB03dA1tGeqzS9SbMRULu7qUo86+2P45pcvDGiSxEloJnJ6IKybbUkv0VxqiFxTvoYVdS//z6Dthc/pAy43zKoKccWTTpJg8utCkzHkQwbh7qJE74xHl4X74BvtHXfqC1F/Yq3iMAwJzSEqmkqiVavs6oK+5B/OAqnJ0JWEokoTJ+w98fQyQplk9doP9/4TqpTO+PIdoNROfpQZ1esLH2yYNTwj5K2v7UtpNjgOrEoT+X6t68W8f0EVrOuZOc3LpbHsI1T1droos91F49RLbe0ck9XrMhWh64ZSDuU9+skCOrGRhdtrDxbISjt9JNvvGpYyJDlX1aSn0t37kiSfVEqFS4a0OSwlNlXc3O3Fkg7zdhHwcFhBuQZLQcza/u6wcl2erA2Zlg8xM7eOlnNwAAb/qF23pZe0rHNE6qeqzLkO6VNIO9x3H4ATpGbZTD31ni+Ol1dL9AeBPFP0kHDV3daT4/hKg5MIMMXqkKNn1iFe4kg7cz08dsb8vlmlQ+U5Pu/ofPoPsasWlVhBZttbBct9G8FSN8uKVVxBpXSO1M+F6VdfxGY53eb/fb/Xbvt3tiGXJHRzJLhs8S1VlxJOt2T3mCAKj4gihvEeUrAtD6XIeRynhoutB+H8oDhI6VnjouAJgrfURv3oL7lW367Mwq2O6h1NWY6+Pn610iZ0lPDwBVXw8ZxgIAuz0iANZkWjqnfKNurlEfVcQiryF+8kEkbZl3kd4kZV8SAIUEX5qSMxtQICw7FD3ot4xtQfhexc2KWwbpM4zm2l4RgL7OfL2radWYzCE2+qT6rdzaSt4klaWPPN/iLetYrtOaeeXLM5iHU0K1lhzihWshONeCM0l0xNJ4bQJes5G1XErYjRb6mBiO9fgChMGJtlowg4ywJqUlZdby4Gwf6n2v/sQZPPBvDzB9YhWdL+5r35DZpTo6Xx9j9qYOwh6N7/qf7upL4S2fTJ1BBDP7YIbpE6tovUy5AWMWYHl5DdxmsEKZd9mZFcvUmlMR1AVQVUMfzXH4XWdgJgLzswYGX5UALs9A8+UxFg91NJmt/fwxRu/ow53myF0D7oTOkTZMeKMEtz7o4cxfyLE1GT7/pV9CMHwjIjhLk4XCFag8htnvkY3fYgnmODpBV27qQedBQPtLvQuNaJQPqwq5AUqQsnqN1p/yoaVj0UOQD4e6LwDAzm4CR8caetz66pAqEZxX1oJid1/3UR0zW+9QQi5MdFISADDoggURsvUOrH1l0CNBNTIZmQ8JxmwOBjRh1DyaoFQzDBz8nQEGX14UcnZhQrJ0aV7ICHouPfSlG1X32TbBXtqujC2r14pcRSmLzms2rX/lBJKsNeBuH9E1SUMjPUkuw1PjCKByDQffuQbGgc7VmLw/VXXgTBPejQl4w9Uw8vwShefW/gTC95Cs0TLRHgWYPdqBvcg1s9IMU7CXtmGsriDZ6unKiTmagx8ewVhdKX6HThMv/aMuen/loPdKpKXykOU4fP8Aq7//is6bXPmpMzj3xyGMjCOvWToxnV/aQNxz4X/huu7n4pyP9ievQiyX2jYzfngd3KYkpD1LK6A5QHI5FGx+IPNIxxOg19HwdPPqbaSPnNHLXACYvqWH9iev0stnGeo+mFdvI728BXtviuH712S/GPb/yT/FNL07UNY9O1mc9Dot+4jcldfpmU2pVbnQkQWfzfX6Vz8Q2kKwqs79el6n5sYaRL2mlZ+NZQw2XVBSrlTOpA+rFnK6xKm2nShfCtuqKnTLhNYdvU7PbSKVGo9mSIra2mpA/abKR6WcsFQl4ZPq4IZBsPGwUBjX18IYHfOEr2nZ6xSWCWRVirw+5+t5nZ4Z6HJsWjfhzDJSB48ynYfIOnSNjBfqVapsqxWjVPk2ynSZsqx0dbdep5P3nkPUYTAToP+VIspLu6T56Q0jJF26L+OOhdbLE+1rqgiAuW/r8mhZBsBaFKVhoCB4CZMRf+ibeJ1GF3uwFinCdU9bBViL9JTXKZ2XF9GhhKebQYbctxCsuTqPEawYuPp//vM3ptdpuWkCmZwsYJrEupOfn4RyA0UCJo9lZt8lhStdSVCTxnSm963AvU33FGxaTKYwS5MT7zRI8ahdiJ5e/Yfncenf7FYy6BiO7gj3Zq8D91aJL21pOAvAu10N9+b7VA2yVs8BkymwP4QTFn3gLVKLVnoZattrP9bCxT+IdbaeBVHlfArCPfjSjJYUpX5X+86Q9YrrSFs2ajvzyjZrFoHFyWm4N4Ds+rAK985zsFv7qM3oGtyWj6xND53qMwBYU0k+W0Z60qMqBP2mZWg4S3Nwy0Dac0m7AcQe9Z95FTi3oaMOoIB78xIZrvPFfSRnu7CmMf7Zv/8Y/of/6qfpGOOI0KHXdlGTkYW51cMrP+dj6/csuKMEluLucF9DtfXY1WwYk0UF7q1+g2iribRhovVyNRF9Eu5du3IEMZ2hOewg2ZKR3nCKyTs34e9FWjwYeH2492v//SYe/Zf7ukrjjYBr0d0rZd2zkcXJZcjJnMWdWnkZol3U203gWL4lZLWAL5Yw1wj8VC4tnsx2AwAfjzU9HADw8AWqjasoRKpTgxOkVxPRbOuUiQ7lDzKdHzhZvixnqSvrfNuq4EqQJmC9bhEdWCapT+9PK7DoxeVV1LenCM63SMkKgHt7rtfwRsaLpUWaaRCaHhP1Ns44eXpKVWkjJC1HluaF74fcZoSnqy8qL3Sy1Csavp4cWZoTk3YagfsOhk/QQ7n2F0MqTd4Y6RyCemOr6E5HHDJHxGt2RUDHPg40Ca4MdS5k7GRUMGhrL4+s7eLWB2ki6r0oYGQCrZcmBe08TJH2fESrxJwtRzJ6TIKksq08XuoYecvT0nhqP9V3q7TsE66trQCUd4kZZshrFpKWpXMhziisXHuZjh5s1OAdJ9qvBgCeff5XMVveXWRxvxpyv91v99tdtXt2GSJOQLVPtTu4jZ1S705TsEWgly4i5ySJ5zgF8CfNKEpIEyB3i4hBHd80K8c1Quk9uit1E2wLbBEArlOxDiwDZyoK2gCtW8vEKJVDiOLSdxIgMihySbOiiiP7lXfr4Ap6nEq9xxPeJc6csAu1vaV+IwrLoLeYzKewchgq6fD6GlReIE20GI/qr5FzoveXtjGnGiHpyCfPTyuvGwayfl2TwLy9OcyFvH7O0b6utEYNpHULdr1WAI8Ol+TkZRkwMq77UO5bWQE7LzFrVc5C1JxT1P/ZpTo6Xw6RrtZhjyP0XqTzZR5DYy9DslpH0qJrarx4BGsWoSZzKXlDLh/jHEaQINpswpORBYsz7SGiqObWLAJyDiNIYBnsVC7DDFO9jYUJwq0mGAeinonakVyO2Q6ccYykZWl3dzfNEW/VYYXkkmYvlXuZCSvkmJ910bpWRBvcuXtZvXt2sqg4kAFVh7I0OQVKAlBxHBNRTCY8plGAfHSSLSUBF8g8hueS2U2c6MqJ5ohMZzBqpeWJa8HYHyFTGfnDmeZgCN8DU8nL4VifXz00ot+pmABp2f+mT6XJfofKnwD1h3OI6QzM8zR03eh2IaII5v4YhpqQpJFRdGmgTYx0f2sOct/WDyILEzJUitRDI69XSBn//VExBoYyL/Igyp6mvkdLjkWsYfN80KZkr1rKAJVSaT6e6DwUfZbCvgVYEhwXnmsjbRho3AjoupX6Vd2FN4yALNewbLUcssehXDJI9apFjOTiCiUY5UNpZBzWrSNdKtU8kjAFO57SZCyTsp2vj3H4/gEae5lksEpA016G2Tkba3+2C0de2/ipVTRuRsh9C6bBYO/RUpd36kj7Pmrb46q51M2xRrICQNavg/mOXlIoISMzyWBYBgnjjGf6N/JvzMDCGF7D03kae7hAut6EO0r0ciNeb6Dx2oTEnjOuJ0p7f47wYhfd52cItmiJl7QMmF88bRXxeu2eylkYiggWhhVVK+CEcpZpnlLBAlD5TkVNS25nNY/ecp128dabzLXClVK9qn6nBr4o3j5Go4HssUuwX6E6u8JHsHodfDzREUB2+QLdAFLFCkBFyYqZBuVTAIhbezBaTeTjArOvyGnGuTNV/MbBIYxGHfPvehT1G9LyTqpxlZW4AAmzns919USNjbi+o0t45SoLDBOL91zU/AczzmkCOJ5WCGp8PKGE89kNqgTJbezsJj3ou6TtoNS4RJpCnFkl93fVTAP7Hz6DzlU6l7c9gjgeUwJQRV5yv7zfhLGINYpVcUPylgdzHoNNpBCS79G5TVPD8VmzieEHz6L3wgLGaze1TAHbXMPi0R4az2zrXNX0HRtoffI18AfOwLi2C6yTUlWyWoe7fYQbP7KF3svUr8ZfvCL7ZwIrPQzfS/v2v76AuTfC+P3n0LoqJ4Bbhzj83geQtBm6r9Bk5b82opeGJDCqSSQd1GEGGcz9MXifkr/G/gg7//klhOsCg+cEGjfpJXP7vQ2c/d2bCN+0XihlvTbC7Q+tw0wEMp+hc4XOd/wmG2f+fIKb39vBuU8U99mnRh9DfOPuxG/uqciCS0k7w/eBEsAKAEQYwVzpI9vdgzkYVJOOqpW+wxYB4HmESbhA0HD+6jUwx4E4PNLbmGMT+UqCoNTbr6y6xUolP+ZJD8xUqSjTAxE/vA5nxyMfDIB0HFyLkoPyTW3UPJooJGhIvZVZvQ54buXNq0FZtqW9XKm/Mmw/jHVYbs1iKrvW68CipLblOWC8TjBqOelO39JDJ4iQ95vk3zmjtwybLgDbqrylctcEuA3TcyucD5bUtSS9kRbb1PXqsnQpSjNmQaWMDNNA+3qqqxauR9gZHZWUllNZy4UTpjrUVm7mOtGnfis5BidBWY29FLlrkiCSqqi4dK1l/lDYM9BuNpB0XdSaDeRy6Za0LDi+h97LGXY+SM/VwztbFJ1MF+Cuhfp+Ee4bvgfGoY2g4bmo72eojZiOVmBbEMgA36uAspALOkbTL5iznovGHkdjD4g6DP6eBGBt5xBNH1nNKBTGbQvOQmhQljpfezsn7syiKDUL24S1vK/ufb/db/fbt7jdU8sQ1cpIP43glDJ52fWbpLr0zRCccn+xDMHPUZmUvbRdeUsDfwME55l1YDhC8J6HAUDXwlVZzxxRZFGmgX9bEJyOXZUWtC1Mn1hF8+q8KF+mGSE4SxBsNRaqleHFACCu7/ztIThL1zB55ya4RQpSRpBQn+VxnZ2JhnID3z4EJ6vXcOWnzmDla6JCAESaYfzUKrqfeAn8EkWku/+zwOBXfDijkCKfbzOCkwWRxmmoe824efjXQ3A+cgbOzjGOvoPo8FGf4ea/+KdvMFm9OzQdHpbJf4ry7NgVTETxeXLqO6xeKx4eteaWk4n6XAOk5L+BUsg1RCVUFTUHDMUkAZCeYvcrxzqZdLKP+phBUtXglPsmPR+WZcAIkgqIhrd8sIk8zrC4njtWgmoOWi9PTmlVKo1KRz64Cump/C6v/Bhd26O/bNB3T4wtb/kaL5CeBGWluU62sZTra0rkfpZyJrvDOJ5srZcnyFoejCCp6Grao0CLKkP2S/VH6XaWAUn+XoS0ZWsDIHthw79qg7d8qZlJfailOdjErvwOAHDuj0NYswiv/JyPS/9aXscsQuNmMX4AMPiVFv7vj/8f+MBPfZSMicp967l038l+KtsBSswrUyUOdxQg3Goi2PRgzaoTabTmoz6iYyY9X/9+QDHBm/Uagk0P5W/6e1FxT5fGitVrJM/3y0DrGo1t6xpw83V/kdPtnposFHmMBwEMs1n9sKTJeSd9TQB31NhUGp0AgF4XCEIYflokuk5oZ95Jy7J83OnlDjq7h5Xzdr86prXroF5UPkp9rECMy9tKeo6VfeR+d9L7RJpV1bDK/SppfAKkAbnytSW2/14dD35M3qTTBZbv6KM7jpH7Fh75tUDvy8LkzvqiakjLgCuT3Vkvs6TxeHIsK78PqpMHywUmD9cw+FyIla8tcfBOihY2/zzE5K1ddL6U6Ejl9fqk+2MWL0p7KcdL6mqqUqIe27Juqm2RP0gusPV7FqJV6cXBBXLfgm2aOqHr1Gyt6bn6v1qV39VeljRZVR/T7JSGp973xDWpfpfvD/qHWYXpp1Wt0PL2ii6s3Lb5GanEXvYNufuUxb2xDHk93xAlxQ8UCUceBMT7KHE6RBTTfqrcupR8DqOqAlRBeF44V3ygpNzSDLwjvTv3RhRiT4pSpE6cRXGB3FR8EGnuUyYlqWNr+TvLQN5wyQKgPO6MIV3xYS4SjSoUdU9LuQGghK1qSv5PTUzKcMgyiVWqmKClc59kfGpOh6oaBFFlCaH6JUxGEvi+pcuR9jhEuuLDGocaP2DEueZ0aOSnMhkq62dA4i8Mg5ZiUkKP12zaFhf4AkAK2oxDsJKyWLxKjuBGypE1ylwMInXlbpHws0IOb28O7jsI1zytAsak63vWdnXZU9QcpH2fTIklhkPtm9ds2MOFTkqnfR8s5TDDFPvvbWP9s3SMaM1H0jLRurpEuCYjS4dplKdKZM4e8GEvOdK6ASMD6js0RkbKwW0DwjZgjeW9YJva2V2YTCNXASDuuWAcWhFrftZB59VA2w5EA0oyu6MEacuGexxj8jDd43bA8cIf/sIbS1ZPcA4hTrxZDcJDnJTGA0DZcFlWwvYujFaTynmyqTLgSRp7mWqu1n3CNilPcHAE5vswrtFxxNoKsHdQgVWLA7kWWBtA3CKrAKPbgZjPKZM/n+tJLXzqAoTB4EySwng34wTJBqk86Us9HMMJY3JePyPzK9d36dw1F8hy5OtSMUx6WyTnV2DLmwlC0MN+MIXpeQVhy7YqeRHdhuNTuRkhmbjH3/Og9pdwpxzeMIa1SMBSQ2M1hMngXBsieWAAc0FjasxCpGstAI5+03GfgFPRwx2YcYGd8G9SeXp+ua8fXntvrCHu5benM5oRCC7PcfR2Wjp2rkbIGja4xWCFuWaHCpPBGs6rxs41F7sf6qP/YlKR/I8vriDq22g/d6BFZur7GfwvXIc4M4A1Weh7JG84mq2pqh7+F65rOP76Z4HtH6T7cfU5jvbLM+x8qIP1z0sDpUWCw6daCNcZ+s/TS67z4kzrhbI41fqk4zc14E5z1LdnWhW+dXWJwycbSJsMvZdSeAd0va/+eAMP/laEcM2DaNCP1roR4/oP+HDGDElXkCk0gNFlH5ufDnDwzgY2PlXkR+Lu3cvq3a+G3G/32/12V+2eiCzu2E4m8dTbUonhKFaoXPdqKznVeH5qXa9BW6Xljib79DpAlBSw5CCCsKuuXULqbSJOwPrSqIUX8nBlSLM3jAjKbDIdlgvbRLrRhHt7rrP9AAC/RkuJlV7hmyo9UJCkhB+Q8GVL/m0PSwAnRX0e9MHrXiXJqSOIch6iXiugxCqZGck307WQlhwgwRRhG0i7HuKujfotRVFPIZo+zCAr+VLUYIZpxaEdhgErSuCZTFOkAehrb1ydFnqaLZ+iihPL4qzf0L+RinimFz04Cw4r4Mhds0LVj9eJyq10OYXJsPL1GIyTz6fqrzAYGtsLCNNAbSTHdJYiv7RBERAvGUPFOXinjv7XF9qRLL+0QVWbOEO05mP1Obqm2XkT3GrBmQpkEgcyueSh/1KE9KalVbij9Toy34CRCHhHhbp3YzdBVjMhXBtcoeV9Syd8y239MwzCYBraDQC77/fQuC5QP8gRtw1Efdq+9qUEwjbQuZJqYygrFLCv3X0a4t6dLE5S0iUYScRxJWfAfJ8g3fU6oKwDwwjMwanyqgpPRRzD3JcCqw2/MNxNM0zeTaWx9pcP6eaVcGsAtLRpN4GjY2CFJgsWRBANv/hbTmrm/hjG0qd1v1yn8pItn5b0By2JcteEGZd0GCySiDcOx2TKI8uGWgjlJEtWQrBJBr8KXgKKkq46n8rqa9XwhQNmmuR8JY/rStn5vOEAAjh4F4Xlg+eWpBb9zERDh60whzMKK45iZkxrbGsaw9gfwWjKUnKkhHBT/Tvm/SYy34I1jSvMzLxmwZzHgG1j8EVaws0fbMIbpbAWKfbf3UTvZaHPl9ZNHDzpIDhPk+PWnzK0vnKAvN/E3gd72gDIDDOYh1MkDwy0zaDylHWPY4RbTS2iawQJ0r4P99V9DbEPHuoDPRf2MkPSMtF+mZZW3Gph/93AQ785QzyQxlAGCRrbe5muyI2e7MFZcMzOWZg+0MDGX9Ly11qmMOIcSdfVVYu8ZsHdn9I95jla/Kb12hzHb22hvV1USszYwuqXFuC2gfoOx+wSjbm3O8fiwTYar02wfJpUyxkn8ODdtm+a4GSM/RsA3wfgUAjxFrntHwP4KHRBD/9ICPEJ+dn/BOAnAeQAfkYI8SffrBN35XUqm8gymA89UJHXZxKpqfvs2MSnmJ3gSZQQntkHnwRAlF5jf0Tq3NJQGUBxzLVBgReQCFNxbgO4Io2R+z3KWTSblZzF4rvfCgCwAkqwARQN6fW4lLIHCA4s+l9BgwAAIABJREFUmnXgeKKVmBSEPF/vwogy/fa0jwOwKEFytqvzBSzNYSwigkt7HpHo5DmEhJqLjX4xPrdHYPLBVZ8r9bDx33+bfkvlDtDYy1E7CHVyja4jpD48MNBJOGO8QHq2j6xhExwbxJMg6rmLuGODyXmwdpvOGW7U9ZvW2x6RenazXslZsCBCdqYH6/oBrv70AwCAjWfoAeUWvR0bV6UEgWGQ7kUpwuQNDwfv6aJxO6/kLJaXSS6/9dUDHD9NptFGBrQ/eRX5pQ1Y+5OKWXFte4zJEytg8tAKy4A0Q77Zx+4HaCJ1pgKDL83w2n/RxKX/q0hajt/UQDhgaOzSAdovzyhxKRO6mSSihesuuMXQfnmGg6cpR7PytQCzB2rIPAZ3VsC9b353A+f/wxSzh5rIPPpt6vsZrv8Q0HrBRrgu4EkIhRkC/ZciDB/3sPnnRc7iL29/HOHBt0hWjzH2HQAWAH7jxGSxEEL8sxP7Xgbw2wDeCWATwJ8BeFgI8Q0ppHeshnTaBeQZJ1Sw1tcKyftehwRblNkPcMoQWbXKMVQ1RErPC9OosBC1nkQU63OxdqswGlIPZFotW+lzb67pN6g2zck58q4PcxwAVhE+WwsCavFWrYh4WnUy4bEtKrcpNa1lCHFmcBo+DdzZRPlumzJGvrRVsDiFgHAsUmNquFqmnkWEBxG2qRWeeM2m791BTZxFCVkKyPFINjvEAM0F2RwApLQFFP+XTY0Xm87B12nCS7serEUKbhswgxRZWxobu6aukmjNC8/SWqLEDpUQ+WmErO1B2EalGsJ955TSFo2tWVRrQFoaahmyfKhHDF9ALz3sWYLh4zQht25mSBsGvONMa0lEAxdGSjoZ7ujE/co5Ab2kz0rWJlNlmExPzgAQbTbhTGJkdRtxl86beQz12ymymgkz4doXJG4baF8JIWwDyw26H81E4Ot/8ouYT++OG/JNE5xCiL8EcPzN9pPtIwB+RwgRCyG2AVwBTRz32/12v73B2/+bnMV/xxj7LwF8EcDPCSHGAM4AeLa0z47c9g3bHUunpgnmQJdOdc5CfS6FXtl8CUhYdzkpKnJ+SkOhTGHXQKF2A8g5ovMd1F7YK3QuOk1AgYCkhJ6YLzXLVKxKE+bDMRGmopj+LtHPRauuNRYBYPrYCqyAw5d4BOcGqV+JVp2UtmwDrCuXIbYJQwhgOIboNHWSVXuJRFH1+lxay3LLgB0qBakCx6DAROqaT0Y9DAByTjBoJQdnmADnGL9NGju/IqObFhkgGUGicx7xwEft1ky/nen8EsswaMK+NaLrBIrrVjICANKzfXDXrIj1AmS4rNS71TJodt4F4y56X5uCexaWG3SM1tUlbvxnTbSuCbRuSMRlnMPZm2i0pybJNV3YN4YQDV+WfEmOTrun12ytVMXiDMmgDu+FHU2Oo/0oYuEO00vCySUPwgBWvhqhdZPusdvvM/Hgx6RJlhJIXnUR9UwwLmCFFpk0gSj53LVgxLn2qzEyTrKIkqGqfh93RJqgzjguELk/3ED7Sgp7lkCYDLNzNOarnx4i2WzB2Zng6K207LICASM6HQm+XrsrUBZj7AKAPywtQ9YAHIGeu38CYEMI8ROMsV8C8KwQ4jflfh8D8EdCiH93h2P+AwD/AAA8Vn/y/db3V5YhRrNJEnqSiakmDZFlsM5ugUvZfKPfrfAwAGi9i9fDWYgsg/G2R+n74wXRqqMI/MIGzF11I0d0TMPQuQrWaWsaeAVnIW33lKUAACTvfhOc4ZImCjXGB0eUkzAMiJqL8CzdpLVtqY+ZZjqHoCnpm30Yk2Uhz7d3AH5pi0BCJ3EWkylNIH8DnIXKWcy+723wRlLzIc7BuCBsCOck0guATecQzTrSzTb5t4JyC/lqu2LJp1mqUUK4EGW2tNGEtUwRbNS+Kc6CRYl2glu8g7xO/Zu03o/WfLjHsV42Jf0aPdB2wTrNu3UcPtVC75UY7vaRftCEbWLypiaa1wsOSHChrXEWxl8DZ5GdXdFLjv5LEezhEqN39GEm9Lt3vnSI7R9dhxED3ddk1eNGQJOpBLEpcFtap4oJS3nhi5pyDJ84jbO49eE2zv3HY8wfbiNYoUXC2rNT7H2gAzBKrLa36Xx738HwwL+LMHy7X8FZ/MXw44h27y5n8TeKLIQQmhjBGPvXAP5Q/ncXwNnSrlty252O8WsAfg2gnMXJz4nwVY4UTriJycmCjyRBajbTqt+KQHYqOVo6RtqXs/MiAh+OwDyPiFGlfIdIqJRmyZIh0gw8jGCYRnHsPAcPI5ieRzkReY5gzYa1dMByoSsRIs/pAco52DKEO5Rgr70DGIM+xPG4QKHKwyvgzuIhers3hmPSYuycUJ5SfbOdqqOXnDBZabIo+6ec9DpdnDFgZJL6HUkDYiUgpPImaQoMRzBbNQ1fFvM5WL9Fa/7b8m3V8GmSafo4vlxD+3qh7MVdE1mNaaAW0qwgyJVL4CkpWIucI+7QA1E7sCkK41QCVaViR/WtlEcyASwutNB9jdFkKhPY+SNnkfqMBGQG9AbnNqPx4H3atyy0HCVI2gy1ESvGLVXw+C7Cddqe3rRg72UIBwwrXy/pfcZA8GCC+m1Z6k9z5L4NexbQ2MoKkkKe+jsTLC6TP23jtQnSZhPRQIBfKcqswdmMSIk54B8phXgTwYaAFTIkbQ53LDMNggyk0zoqZXthf5tLp4yxDSHEbfnfHwTwvPz3HwD4LcbYL4ASnA8B+Pzf5BwkEFPSkVAPUZZVZeYAIDeA/DS8+5TmRdmEaFZI2DHP09UBbUgk+RfmrPCLBKQmRZqBKfUs09SCPEoXAwDqt5NCjaokxCJyDt6qwZhwvTwx6n6hR6FPJL8jbwxV3mOODcQZ7MkJyLhtwWjUCfZeEhG+EzuX1esFoUkxY2Vk0Xkt08k6fX7F1FXfKbFH9TKm2QSXbuA6ajEl3DzN0Hsl0krdAN3Ujd0ST8F1YLSa5AtbStyWJz53wvV1AQaVmrnQaFjuWTBXenTdqkxeczF4TpCVQImly7ggk2LT0MuN3LdgdDvghkGK6iWNCeF76L6San0Io9uR+JcMmW1qZKYV0ng1drlOZoqag+5rOeq3baR+oSXBuICouYVuBQB7mevvOLMi0u5cycBvEKZClZZXnzULweNSPrb9GuDOOFKfwRvTBytfJiHgxq4o7AYMA9biWyirxxj7bQAfALDCGNsB8PMAPsAYexy0DLkO4B8CgBDiBcbY7wJ4EUAG4L/9ZpWQ++1+u9/eGO2NSSSTMv8AXp9IBpw2Dy4TyZSLOkBre8+hUHOTwn1n+/B1iWRiGepIRCWdtMS/0kZoFm90zS1xraIEWQ61LRPB+Ra8g+A0kUyxGctmtqXzVc7h2PR2HculhWnc2WbgdWwIxDIEeif8WCQ5LW84esngHC7JKWx3rvMuziQm8FSSFm87RcQKqqVBNR4szYqxqXuU1A2Syps2a3mELZkuICQ5L15vaDOieNXXb3Aj48jqNpKWhbROx7CXAs1XJ5SjuNxC65q0lpCo0MWlNprPF+LLyVoD1kIqayn2rCy5WsO5Hq9kraGJZNNHmui8KE2j1+sIVi30vjbF4qIkEzKgfiuoEMl2P9BE99UMwcCEHQjdr7IxkcqlKNsFNZ4qqQzDwOxSHfXbRcQ2veih9wKBsoyUazKbexwja9hwRiHGb6bfzEwEXvr3//yNRSS7U2N2VaSmotzt1wq8g1yfijTVISvrtMFHYzC8fs5CJ9/ihNb73TrMeVARIWFpBr7RrzpqRzHA8wIlmaRgeU7Lljwv5PZqPcIclFzJhG0i7rkwg7R6zDSD/9oIvFXT4TOF9BlYziFMQxPJlOAMU14oqq85J+h7acnEoqSYFMpw7yAqJquy8ngq7Q6lG5hyIuOuhaxmoXZL6pNmOXl15hy1m9SPvOURRsK2qlD2nISM85ZX4DdKGqEMMlRX24UAK1OuWx7hNJJUP2hpwyRV7yCBexhoQJMwGDmHHSdobBdK4dx3wOIUnecnBdxbKpc3X50Uk1tI7uyAVAJX15FzMN+hMYZS1jbgjgJJM6/rCS7zDTgLWioYKZ0r6ployByFSlp2X80wO2+hdSODv7PU/VJ9sxaJ1kfRE4V0s9NmWi0PzetB5btxh8l8jgC3DWS+yvNwcp1Pcw0jNxNUl7LfpN0Tk8Xrl05tLcyrcgQijiHmS4gzJJBqjGZAU1ryKbi3tCn8RnBvNpVJx36HaN0RUc3TTVkSjTNKTG7vAgMCA4n5kt68R8dFTkF6hypVa51nmcyJLRln+mbMWi7c4xgsyZD3mzrxmfebSFsO7Fmi3aLsowC8U4d56xBo1mFcJU2O7NHzsK4fyNKwW4yh7xVy/2oi8/y/NtybSZYnAMrUOxaEwZC7DMuLFHXYywxxx4Z/O8T0QcpfeMc5XJCaVnCB9nMmCbhrwohzWK/cKiDyim6f54Atf1fbRO5bZE1YL12XTZUjlmaAfOuqh1DYJgIpew8AzjgGtxlm5z2k8mXgTQS6z+4h7zcxfLKlBYLtWQJjNEP4pnUdmdhhAm4RLT86AffOaxasOAHkcbnFEG41YS8zpHVD3w9GIjA7Z6FxJYWRyYedC7Akgz0LtJp68JY6WjcyDJ+wUB+0NJQ9XvXpPuiSwxwAcmpbxAXcuySytP90A6tfLoBaZiRgBilFmEEKM3b1NRDc+yQA7A02WQAkpack9AAU5cgRvekNs4of0yhFGWqLdgMoy+rVB5UwHYBe0lRakoKZDGwZQtiWVlhqf5Hyt3yxqHxPuBYMSSYDKMEnXAvg9DeL5TmV8Ihp6DeiPQoIlm0aALd1CJ67JpK2BWe4hCURgmwZgpXCcVU6tvYnFEV5ni5lwjR0qGoslnqyKDtzadsAoOJYpf7N0pz6nvNKZCFsCsfrNxIM30GTQPflBIszJuo7Qi9NlIxd+d9GnNGkO14iXyxhGIW9AzMNWkIqKwLOKZFoMmSNkpvYmBzKzDDWb29vKKH+roXlmonua8WLxhvGWJzxMblM2zrPW+jK63z3R5/D8z//NhpHU0HaDXjbSnLfIdWrXMjohcbXUhUb29ITvz1L9b1iZNDITu+IYfoAlccVMtMKLZLmR4EVsQMBf2eJ+qCFB3/8FUy+ekYeNwG3DGQ1A17Z5cy1wFI6v/JaUZNJ3LH1BNp7hcaJWwaYyeANpayAbSJum/BrNtrbxbLljSd+46yJp53vrkwW1voa+DKA0Zc6DrclqEVCtcu6icodPX2EBtzZOaZtJ1oZ7m1eJg1N5d0B0ygePtDbj/dbVJpSACbfo4jELLQyTgK/dHRzboMmi3JmP0qoeiCXJsrQhy0jCv9L+8fnunD3F1hebMM7irT+pVq7s2VYLDnUOaJYGykBKNS176bdAe6tbmwqz3H9YCuocxlwhiQlktQJUR+6vlD6k5YMfkxG+Zk75VTKv0MQUal8OC70JGcRhGVoDQgts6eEf2TuRh9PLjlO2gcuLjbg70WUi4BkzsplXtmgGIZBHrZyUgagwWsszpD161p8hioxAlnDgRnLSGgZIx3UtXgQgIo5krBN3Pgeym+c/bMCG6RNl2QfwHnFEDpvuARai3O9fHL3F1qYR50HALK6DUP2p6zZ+cz2r2O2vLucxX09i/vtfrvf7qrdE8sQkaXgWVDd6NfA0lQbAldaznUUYb8icwrDkTb+EQBVRr6ZBSKA7EwPRpTBGE405Bkg9WX31X1y+yqZvdBJS8OmznPifMK1kQzqsCeRfoPknTq9uQBkgybJ68nGYjImPn4/VWl6n95Bvt6FvyOXWzIRuXzsDOovHhCNXJGuSriCclWomlwtoSLT7HRUooa24SDYolyPOyG6tGEYSBuFAlbumjACqkqoN6oZZsjqNqxlinBNYlVMhsWmicZujsbVKdJ1enva+3Mw09CsVABgkVHocpSXi6ZBdH7TQNyTEnEAuEXSc4yLImGa5rRMMKpRQdJxYYVZlYS15sNecFiTENMnSJ3M34tgAhX9EfW3mWSV6KCM6FGsUoD0KKxlinDdJXc1EIQ7rZPcn8JRmCPqi8pRqIji+veRNkZtSBaIAC1NsoZN2hWLVJ979BYfjb0cwjDBbckubXmYn3VhBxy5w2Avuf4t3LFA3LUrhsvc+f+BUpaYzirVkHLL17twdo515eJkaQ6gaso3PL5FN2FeswohnbKcm7TKEz6JyVSqF+VWopyfbGaYYfzmFuL1Bj1Ys1A7qytxFt0k67J1LSjKe7MQ4BzBVoNC95qD2s6cjlFiZ5JJTen88hzlber7as0tTnyuWy7gzDI4swzLDZdk8dbrMMMU0ZqPaM3XN5s9S0gXIsxgziIYGcfx5Tr8nSX8nSV5hO7m8I4T6QLOKTy2TMqxxFThoD9W0S/521SWAgByz0DuGQg2axC2gaxmyknD1H9ONlVCnJ+tLsmGj9mwFvQbuJMM7uS0rkMucz5c9qXsPn7yHO40hzvNdZ+4xWgSk5wfK8y1k73+TWxT5yhUW32OY+8DBPsePmZj+BiZKZlBpvur+lU75nDmKeJOSf9DCQzlQNQxSEPVZLACTkzU6IRocn73aYh7ImfRMnriXajqWSichX5by7cln88JZyHX40q9O1/vano3H0/Aat6pfILSt+DzOYn+giaDyZOrOmOuy3uKdLY/hFGXfAJpN4jjaYEgtS0I1wGLE/pbZfoNg8qzpoHjt1MVoPflMdHOTQPpZlvffNd+qIFLvzNF7ttajMRYxJTHWEaUC5CWgBj0qTypfDohqx+ODWQ5TZwKm1Kv6bW7FvEFrc3VderPFzH1vWSlB8YwerKH3temkjatEnoch+9ooP9CpNfGuW/RW28RV/bLaxacvRlwdKyRn6JFLmlKMAhAITYcZcibxYOt8hPGeAFeItkBxAUhwRvpFxrmOsJRTmfTixa2/mAPydku0rqFnR+l6774KwL2cUC+JAcFyU4lisOtZsV7RNgmrN1jyp/I/aI1X6tza3Fd10bSdeEeBki7chziHMJgsA9mpcqYB2uRIF4lR7EiEUlG0OnPjND6H+n7r/1YCw9/7FhX3JQlg7VICMvBgERpcF4LYYYpjp5oYeXLs5Lwkomo76BxZVoR/P38c7+MabT/rdGz+Ntod5wsBgNNbgKqJDDxnse0tgL2DghXcXikH2DWaUPMFxDhCTBQ2d7wyTcDAJbnGmh9+TaF+YYBoZzMB11gOEZ6eUszCs39sa7SKIFgo9XUDFARRbq/+eMPIWvYGD7mYPU5OqYmlmU5RRLKkjCISFNjvtQiNez2SCuEx+e6uj7PbQPe7hwsjCtLDOVrCiX9B2jAGoBCbRwg71Q52erP5Vin73pUP3yzCxZWvhIgXHdRGyZaq8EdBjBHc+T9ZknBO0Leb+Dw7Q2sfW6qx7Z2EOHobT7a1zNd86/fWEjrxKhIgs6WBQu1HPEEoRYGGn7kERoDC2juZGCc1LHssUz+JhnpakjpfRp0G+HZFuKOie6zezqC2fuedax/dgpzvNSCvf2vzsjYp9MkjI1m3xrax0ULAN081EQy3m9pcV0ySgpx9DYf65+myDdeb8AMM0QDV0O4nYOFxp6UhYWizSaGj9k4+ycT3PxfaFvvNxuo7wSUUC5pbRw/3kX3pQWigadFhMKBg+W6geatHKM3m6jvKfvCGGaY0eS9U4hbP7P3m5jNd+8nOO+3++1++9a1N0xkoZqCaisCU/BQH/UXD7T9oGqn9B5wAu4tlbJEvYbRkz2s/OUuJQ3LJrtBRGU8lQRU22SpFpAJxZKeRRnuzRsEYT58ihKka8+MKZGZZkjOdnXoev3v93Dxtw/BG6XwW5bmjNGMYM4K7t6qkYfErf1TehbgnPqhml+7ez0LBffuNHVJV9gmDp5qYu0Lcvkmy3OMCxxfrqO9Het1dNJ1taaCWoMzLmCkHGnLgbszrVyfEaZElVfl3RLkXmMvAL1sY/Mlsgtr+vhGxilxuUg1LsOZxPpzIfs6ueRi9dNDSq7mAtsfoaXbhU8QZT3d7IJLEV53+0hD4dO1VkXPApYJNpro5a9aDmiDH5lUzX2lzFUyqbIp36FUxYACDJdL9Km6F/KGi7xm4cb32tj4jESA/uQYqz+TnNKz4L6DpOPCjHPEXWlDuchhBhkO3+Fj9YuBHodyVKE1NQA8+9KvYRofvIGWIUqDU4akEEK7kym+iDkYUJgfhjC63VNaFUB1mWFdOEeDKn1FAMplqGUD1ggByhaB1qFQ2hR0rJILVFhCyG1tUm7jOoG28oe2YL62Q8rc0zmE5FakPZ/0JqTWBICq3oRtFULBh8cFXkRfi5QUXBtUDIZUPiZ416WCq1H2JokKiDtveISRmC8h+jJM9iwKtXttqqLI/Xm3gazlIRq4cCeFnoUZpASAy3khDzghhCwfdCinIreJjX7FV7VQDo/BV7vVJLFh4Oh9G3DmUul7ew5jNKPqlJSrA4CsX4cwGKKBqxOE/g1ai2dtlx7CibwXHJvG8oSL+vDpPjqvhpQQVy7q/RYWl9pofXFXX9fw/WsYfPoA0cUealeOtJ5FNPDg35hh90N9NPaoD53P7xXj3Gng8J30u/deDGEPFzh+agXN6zQ2zt4E+393A2mToXOFzl/fnmkIt3AtPdkorot9HBQaraM5rvzEBoyMoXVNoL5Pv8/hEw7O/eEIiwfbehnTuDLF7Q/0wDKAu0DrOi1Pxg+b2Hg2xI3v8XDuT2R+xGB45pVfRnzz26hn8e1qRkMmsMKwygUBiI+RJFqz4qRWBXAH7sc2lVJVfoHVKK/AOu0CEi31KCD1HBRwSyVWjUYdvHRcPhoju7gCR6IRrcMZRE6JRT6bg0lQFt94sOiYukHvoDcBQOs48HKOJc8h8pyQq3levNGSBKzmIe6YBfkoF/RGPh5DbK7p8q8xCyAmU/CcA1K/kqU5GfTK4ykRIRYEsG+bWJy7BHup6PGUzUeaAXmu+82XS4jIBPqtYrJZLsHynr4eoBDwETnxM5SaOUBJ2ajPUJM6DGwZQcznsA4tiiTkmNn7GbLVFpqvjLWmB0S1XKqjJNuiiT8yNTCNAUjakhY+mRa2lZ0mshojbpFXaFLieAJr0CRVd/kGZ5winHBdoCHnCD2xmyZYvYa0WfyqLIhIQFchcOMEaZORHsUNmaOREwULIrDU0jR79QJgQQShYN1xAiNjiM4maF2zdWI87tnS7a1Evc840jqhSrM6IGShJO4JmEEGwaCjQQAw3btX976nJgv1BhdZdiqyQJ5X9S1OalUAFb0KpBlFEcsloML1NNHCOArjX9GhUNoUQCmxmlbOa7SaOhwH5Nt77lAIXa9rzoo9iSghlQn9llPH1pGFQkhKfQn9OUqRhdxfL28cB8hz1I4yjWdwZhlY7MHg7Yo/iPA9MEhCXInMZtTr+m2qoi7he4BtoXEz0qg/VZbUb2m1ZKnXwRwbuW1Wtqnr1ZwclahMUnJ9K5PZbAvtaxnCFdrHO6jBTNt66aa4K8IyEK55cE+UUYVtQhgM3LPAvBLiU/atHFn0X5Aq6J22noS4ycjs2DT1tvlZA71eB+G6h+awoytFUc+E1/AweE4g6tBv1pHaGEL+jr2XSqRHz4E7EwWuw7bQeykFv8I0j4U6QdEalb7ly0c+yML3CnlB2yKpwGs2Dt+Tw53S9a5/juvKlVJkB4DGroA7zZG7BpxZLvcFsU4nVTg9rt39FHBPLUPKE4Qhy2wKAl7OYdxJ0AWo5iTYk28myfogKm6cZSgVuNJK6VN/VvbhkA8nH48rExO7QKAptbSIL67A2ZlQOfIEfFlhKvR3g6igsr8OTbx8fpVth21pcBqr12kczm3oEtjsAR+1owzu/qLC+OQl3odq8XoD3s4MwjI0bBsoypHla9CepRlFF7wlfU3DVJcY9ffkNuOkSS8kRH25rEgGMMdGvt7F8jxFk2bE4R0EELZZ8SQFihyEEizSyt0lrU/1N8t4hRMDELxZlRvLJsKqnKwmi+XlNbjHMfJa9QHiKueQcZ2PUYZKAJWIy2OsxyRIKttOws2NMEXe8iins7/Q+6njlsFT8XoDZpAh7ju49T207eGPR8hrFpKWVZDpRmHl2ssmyMFmTY81fSbw3DP/ErPZt0jd+3673+63+w2415YhJfEbVq9TfkFGG3w81vtY66uFsfAdjJHNThts9wh8Nkc5bionQPE0sQ+FwWDvjQEu5cykRiOkMbJx8VwBHz4YAnsHwJl1/aZ3cw4xn8OMqiZD8+9+KyAIMq38H8rRhHAsCEVK2j2CaNYJG6KMkSdTwKhTEjHJwN9GORBuGXD2JojWG5p12Hl+UpgMSZFhADCj0yZD7v4CGI5hNOv0HSUQLKO22//14xrTUTsWqA0TWLMYec+HJfEmwjJgHk4RPbymKyBIM2RrDaDl6giAuxaEbSB6VOp/yh+jfpPGePKmJhq79H33xrE2GWqMS/aLcYJ80Ia5fYi9j1wAQMxK5ZRuL/PKW5mFCcwogSkN3HjDw/YPr2D1ixkazxcmQ+HDq1i8tYWVzx5g/8NEHfCPOMyrt8EurMMcTrXJELcd2MMFdr5vVQvgNj+9C7Mk2Pvqj1OEtP4ZhtZrc9z4/jbWn5UI0VGEW3+3ieBshtVnKbLovrTQVHP3MNB+JqO3+KgdczSvzHH8OI1b59UlDp9wEPdsrH+O4+GPU0R042cFzv7vHFnNQNJU7/0atv+eAXtmIu1maL1E99jiPMfFP0iw914P5/6oqIzFhffUN2331DKk3KyzWxBRrCcJldjMJ1NY62vIz9JDZY7mlC9QpT/IhGHN0+5eqqmkVD6ZagQnH3SQ+7ZmHiZbdIOYYQZztIDYH4Kty8rJfAm+2iVHL7VkMQzwhgdjEdHfKuOfc+SrbRhRpsPl3DW1R2k6aBT/Xm8irVuo7S0Rr0p9iO1jpGstUuxqN2iSApC+5SKc7UNKgJbVuOoeCaOpag/eAAAVFElEQVSUkoi85WthGPtgprenay394KvPrVmk+54PaD3O4lT3nbsmwgH9O/UNGJlAYzfG+CG64Zs7meZfLB6k77tjUpyywgz28zdoAkaJ6cu5RnCKmoOs4cBaJNo0CADZGZoM5nipS4a5X4TZy62aViO3ZwnSloPFGQfhgMk+CKx+6jbS9TYO3lVH+xpN1u4ogbNzjMVb1jUK0zlY6HLo/FITtSGNkbVIkfsWnGtDjeBMez6CTQ/2giYPZ6L8WBmmD9bQ+3qBnlTLDBYmumw5vdxB83qA/afpHu29LEvjFoMzTxH1HNR3JAW976F2a0YyCr6HZI2+w1KO6z8NbP1GldrgjiLkvlXxl7WmMSaXW+g8P9Fi1QDwpc/+izcYgvMu7AtV3oAHAawHLlScwUQUUy5C5SwWS5hbm4XMvWzlnIb55keKD7IcbDpH9OYteNsSq6H0KsolWtuhEqfv6fIgBt1C+KY0YfEL5M2Q+5aGRNv7yvnKxfJiW4urMC7Ih0NyQQDoY6qbS8nr04EsXdYDiCtghmmhIq6SXqUcglqzA7SG16I3YYEiFcsQ6eVCbjCrWTBSUlgyggTpCh3DPgqQtT3i1cg1sTWNcf0HOjjz6Qj2SBKo5ESjfD/K/Z8/2oV3GOub2RmFOu9xp3yDs3OM2ROEtPSO6bcZP+ShuUNuXwDgjilvw31HHzdp2jAygVsfMnHx9yONO8hqJqwwhzWLdb5hebFFStpyrOJ+kWNxRwly30JWo++r/cwwRTzw9XYr5LBC4tXUhsUktjjvV0R1veNEP8xxx9bIzqxmIu6YsCKhcwtWmCNpnV4EZDUD7iTHj/zCJ/Crv/QRAMDKCyGmFz0YmQC3GNwpHSOtF0rqykMVAD73/L/C4vjuSqdvzJzFiYx/+e877XOnpolHWa4fyDKQ5k5NlwLLmfk7yNYBlBRTiTFhFyAhAECWwwpzLM7VsDhXQ9xz6Ya1ThOhhG1WZeoAbR2o/ihrvkqf0qyyzQxT/QfAHS36AEgSlKETeUnLKiUQecEFqVmYn3X0NmGb2PxsXBnD1ztH2vPRuDKtjEk5SWlkXP+hMZCAJ5cUu1jKJTCL3sRmJGBGAlntTkQyBm4xDXCKuzYxL0PSgMhaRRSjZPjV+ejBL3QhuMX08qfcjJRDmFSmVFWJzGOIu5a2FQxWDF3GPNmMVOj7hdvEFE0aRD6zQgJcKUJY7hq6X0oe71d/6SNYvC/A4n1SWcsDkoYsF8t+hSsGrEggO/GYiL+G+M0bc7K43+63++1vvd2zyxCz3yOQ1An7wpNwbzZfFjDr9ARQ6xupez9wgf7d8MDirDAlVmVD0yjKrjJhqO0Ll6FOGBqj2R3VvdFrgzfIik7R0eNVH4tNG/2vTOmtG0okXc0FshxZv67VkRTWgE0XlLNQ+ACp5nQnde+830Dcc+Ffl4Ch0j53re692tOsT+6aMIMMwWYN0wcsrH1O/hZy2VQuBcZ9D97+sqJQBVCkkLVc/D/tXVuMHNlZ/k7duvp+75mxx2N7fNusvdpd2CxsCBGBB8giIIsQQnmIEEgkD7xFPPHIG0RCeSICISQQEm8rbUA8kixREsDr9SZr79oee8bjGc+lp2813V1dt1M8/Oecqh6baBYSdna3fqlluae66pxT1afP+f7v/z5rb6wYiZJxmVb3DhYqKj2aXo2ML1ZRfn8ANhpj9gxtQ3Z/LofG+xHyu7St8Mu04sv1PQyeKcAecLVVYQGHPg0QFUgPQtkXyoIq08Bsmej49paD0bUG8l1fKXfLPniLJXKHF+0dXWuQ/oUboP9cBZWHdN+2f9GG7gHtdwK4LRqbg+cZLv3jaC5t2r9aglejVVHjjqe2bmHFVniDlO3LDefT4nIL6TfzpHGRWs0N/2SCwjdrMFwql997ma557ltjsjrsuVh/TfS3x7D5V39xbHXvEztZHMUsZMRhCP3KRUWB5s4hVXymsAUp1pvOkADz2ZDwV34WAJGn9O0D0rWsVhBLgWB5zlMLCpCTNob8wjLYe+vUzk6LaNzC2lBmQ3q/+zxyDofmx0rARhuOE8k4Q0dYpYfBfLBL5e8HfQXKxsMRWLGI8EyL8AIBSll7YyAIMb3UTDCPICK8Q7rJp7QhpJUBX+kkYysqKwEkVgciG7L7By8glh40fozyVgT7QPiPSlHa4QRs5mN2eQGWEHHReg781TaCooHCPcJ9omZJTRaTJQuGS89aYYc+46wWkBsKE6V7PWpLrfwEN8VfbsBa38f9r5B94cJ/RggLGiKLpP5L6wKrMXVqW8pmgVcK2Hy1hvrdSOmqAiRt4FV1NL+/h94ribVE81/XEFw5DWurD3+ZGKle00Lp3hA7v9SCNY7VcZIHE5xtY+M36f6UNoDOW2Pc+SMbq/8kMIdJgN2fL2G6FKN6j67TemesXOBjnantkNTdqN9ysPsLBBS3b0zR/ZkCgiIRriTmsPYlC1f+zkX/akltL8pbEaZfHeLwRhPeUojcjvgxCBmWfuBj+3Mmzr+e4F9v7vwtZlsfQbr3jw3JogxDku8XFGy2cgrY70NrNhR1OfYDMDuady1Dig4eCkcvEMAXrC7CuPeYsipealNnWmRwLIqzZOGW5gq9SRHy/XRhV2E/JPFXHmO6LFSUhmMFYPJCQgBzXjmH8p2BMmCW14ZpUJ1EyNUvjyxuMyfhvLS+ptH1j6hEyaxN+teaFfOIpTq5qt+g/1tODGss9ul+jFlDR2GLtEFjuVfXNHgXO2ofDUBpTZhOyrlMGCObgxnypqbSrHJVYsxilYmQbY21I6I3pgBRNQ21u/RFtQ4DGK4Gt23CcLnK6NBpNMSWqX7FJ2dLMKYCF6gUVCl5vhsgymmIizbKj+j++hUDrJgnfCJlXWi4nNLFPjEj5bhJDc5YY7AGNA7FPcJCKrdMhHlBWXd8gAGGy5BzxP2Xcv02FZ4pEHzKwSLg4MUKyo/oWvsvFaD5ROGW16fzkiI6uaQx0dYIhzea8Bsc1p6B0iYdO14hwNPusaeKBB0nPjqTRbo+o1KAJvkKm4/BbBu8l/L7sEyiSB9V2kqdQyLuUd6EtbaDmFONgRTcZbZNv7btuqqJkCuL2KgnWhSQFa65OT0L0m4wMWvoqK7NF1ABgt0nsgWV728grop6BJnuDXwgoIc+zpmIRGWkKdiUUU6HLmsPdOIXxLMZUdNl3QvnSTo5lT2JJymW5hFjZL/E1EQS2kDtQYCgbhPXQrRB4xy5tX34q+3EgnEwBup5TE/ZqIo0bdQuQh/7CCs5+BUd3KBfTbs7A7cNhDZL+iXbesR3RLIrwTmmCwJ4nFnQglh4nSLhf5jk+s7cEEx0q/gQOHiuhqBImhT1H9C96H/mFLjBwCYzuJeTSZrGo0Zp5EpCpWYhR1hgCQg6cQnwC0KwZhF+XQCoVQ3FLQ53MUbzdiJpF2uAX+XKvlALuFpZMJ0lz6PFMKtpWPiPETa/QCuL09+eYv/TBYRFzIGrQT2EPg3BDRuG2GWGeR3eUghrz0B4dgZvlBd9iKGFMXmdptmmHwC1PLGTBdO1OUJVemWhjRMKN7NMmhwCUxUJAUdqK+R7qZWF2o9GMRVplYt04+XqwDTo1z0Iky+fFJZxfbAmLVERcfqM/FeE5dCvanEnUXGOmmVy+t4WzuNCPl55k7Yaqs+sIfxL3ICqcXlCwdZmnFKNcmUht5LtJiJJO5fnKSYU7fR78ZG/y5VFeTtUeo7WWCD9GsP4fAnFLTHx5C3h88nVyiLqVKF5EfLdhEsg1aQBSmuq63tkCFXa1tUxcdF+4n4BQHCqrtTDrJEo2a5psIccxpSDcShehuZFmJ1vkGKXwIliU0dtjSM3jGglICY3ux+RfqimKf9ScxwhurAEntPpB0lMWuYkRFSxUVtLvE6jC0uqOnbWzqH8QAxjk8G5UITdZQiK9Mw6K0VU1yPkBpryHnUX8ggLGnQvB7vrpa7FYcxixGYiXBObGiobEWKdnit5bOU9E1EhRG7EVaZl72UduR2gtAl4ozyCsrAIuE3/ljdj5UhmTjmM9SeG/H+MLBuSRRZZHCtOxGTBNE3RumXEEVcl6VqpqErIAZAIam9AFoXlEgGZpkVu6BI/0DWyvEu95s4hQhsSYIj+kJiL4ph4SDqbLAgJuByOwMol2qZYJnivr7Y+yitEbENiP0BkaTCHM1g9V/ENtI0d5NcOyA9UZ5iuVDBdqRAQKcuy+yN6eSR2EtZIxVueg23uqBWK4loYGoF63R703QHZAs6E18fEpVdKBDeeuGARn/+7aLvb1BVvITcIwXiM3OYA1Rt70B3yL9H2B7QVyhvQ3ACaG0DfJ7zIcDxoPQdaz4E+mEIbk8hMrDNY3Qms7gSzU2WEQoU6yhuJaPJ+nzJEYaRe5uOB2rrZQw57yNF620FxywU3hdr12Ic+9uHXcsj/8BHMR705keXRebH1c6YKZ7GGHgaXLASLZZTWRiitjRCUdOj3d6hoLKW9EeV06IMp+p8ibU95nOZMwcZT5Ho+Zk2GWZOh9SMftR8NoLu0JfGqGjr/3sXjzzH0n4vhVcnsJ9f3UF6foLQ2gj4NEBZNhEVTievynI7quqfk8AaXdex9WlPaogBRuI2Rh6DIcLis43BZx7lvjcFChvEK4NVj1O7Sq/fqjISLVxjqtxzUbzkorY8Rlj9qgr1PEb/RRQlwJEDLdCpVX+g8VU17js59Zjk5RpZnpypJ9eVEsDc2aD+bNpdR1Oetx4pqDgDxudNzD1Kcz+Hwcg3lOwP60rqpSkNRepyuQmQuqR1FFVtVJYYVW3l3ypCaj6pdG2RfqHVaysA4UerWk/2v6ytyV1i14azmUX7kJcrUnCPKm2op66wSkFe9c6gqTmVqLjZ1pUrFggh+U1QtTkMEFROmEyimpCSfGY43V40JCAanzNTIEOI/MiNE1yOgr/9sAeUtScsm6rLZncyxUAGpSsXU1kD2Magkgr1aGKO0NoK7XEZQ0hU923AjSuemWa7tpH0PvpjDqTdjcSz1w96dzIGp67+Vx6nvRtCCWIn7xqYGv2KQbECQkMpkKlZhEwUDpuPDXbDhVXWV4ZCq5ZGtofBYqGflDTBOehRhyVSqWLlBgMmSBW4wGDNqq1QpT48LQNvJa1//Id750xfnxvDtN78BZ3w8Dc4TO1kc1bNIp1L1hc4TaVFgPjUq06sytQpAicwAlP4ERG2JSHnKNCidS2Aalqm4HgCgt5qYXV1G7iZt9vi5JVLNWmiRTJw4/+T50+RrKtOawFxqU/IiAEC/v0Mpw25KFlBgLvzC8pxPKd8/ACsWcfDrFxWyLtOzc6lZgKTgnAkQBKqWJsrpwmuFMBEltyfK5gcvNJTXhPwSmHsOrbAkS1b00z/fSdythGMYCyJKzQIqPcumM0SL9TksBaaBnV9ukd4HgPbNCYztPqJOlXCElMuYu1SEOQnn0opR3oTXtMi2QKhz87xJQropPQteKWD3sw1UNwIUb+8pfkl4pgVntYDG9x6rfj34vSZW/2EPoxc7qF3fVb6zh2dyqL/rYPPVGkwxXKff2FJdCRdr2HuZ7mVtLUBhY4TtX22hfVMoZW0N8fgLiyr1KfvwtJL6WScHfcaR3zpM0uVbQ6z94QJiBlhDhsYdmvB6z+o4+0Yf/RfqKnXafsvB+msV2D2GoEgYBQAcrjAsXA8w/uMRCt+kjFCsA/914xvwHh6vRP3EThZP6FmkVhZaqfgE4Qo4QroSxC1J2gKQaGcGfqKhKR4sqXd5NEvwhJ7FmVNgQahqM5gXJP6lqZjT0ZCepmnSVBAqpF+SpKJmiURigGRVITQ4lNqX0LPAQltpWkriV5r0BUCRpuYIYPYRoloqTRmbOk2eRzxIgkYBs04OpTVxXvGAa26gPh80C7D2xqqmhd4M1Vgc1bMAAHQaqt7Eq5nQvRi6Fyk5PwB4/Pkalr57SMItYlKQxCmzR/oXcsVjOj7GKwWY4yjxWw05FQTmLYQVWwHbmhsozRF5H2YX2nDOWrTd6flqpcJNMjgqbI0VoDu4WkHlgQst5BheLqJxk2qFhtdqCG2G1vUBhtfoS+m2NCx9uw8WcjVe/Rfqiq5dXfdU3+TfecFSNTVx3kLQLCi9UUlrt/emCCs5tYIBgM1fy+P864667xLMrN9y4LUL4AbD9Kv0LI2vt7Dz518/9sriRGAWWWSRxcmPE5s6/T/HEVu+n3T4dcEZ2H5SC/THhSIh/SRCcjaEobJXM1DcDRO5vqcbuv2vwpj+lMYzkvwEqrS0e1zpaQBAaVtqbSbX/2m1JdYZxivkQG735v/mVzQUkKhgzZoMFZEuNVPtMVzifwBC0xOAMU2t3qXWiB9D/wCPjqwYBTCHRRwNuze/SDCPjFWs04oCAPzaBxvHE7UN0cpCDzIt2CvapzcbtAURTmPRQe+J86Q/o1+9gnhTqKtKtmfeJi3PWlUx9LSeQ+eKIugLneS8UrC3WkHUH6hraKUSvFeuwH77Ib0hsIajRkeTz14hmjfnRFgCEO13oddrxBlJeaji7ga0ZgPRfjfpjPBPZVfOkx2ALDtf34RWr6P7GxdRuytk4XhMehzdHnB6UY2ZEvGNOOJnztF5OQd7bx1ahx4Y3hNK3JYJaDr2XruI4p5w2x5HRIffJ0cyhQPsHxDp7fKKwlP4/gFw+Rwdt0a0QU1yUYIA3qdOkzOZDF3Dxm+30LwlxGRu90hcqN0kNqfcoukagoUKzIGL0VXCECrvD9X2wxp40Lu0PeKVAl1bTwn2Nuq4//tLOP0dH7m31hIuzoUz2H+5isV/eUi1NwD2P9NE5/U7CK6dhfnuQ/BVEsWZnsqjdPsA732thc73aLJovnFb9ENHfGYRD36HAPnlf/Nh3+9i64vLSqOicGsHa185A38pQOc79Hw0bg6IyTohS0spWThZKcFyQtjrPYWZWA+6eP9ry6iuDsD+uYH6PdpS3v8yw7N/1sPwpUW1pam9O8T9L9UBDoQljvZ1Gof9z/u49Dch7n05h0t/n1gSvNP/S3Rv9z46mAVjrAtgAuApLsgf62gh6/MnIU5yn8/Gcdw+zoEnYrIAAMbY9TiOX/qw2/H/GVmfPxnxcelzBnBmkUUWx4psssgiiyyOFSdpsvjrD7sBH0Jkff5kxMeizycGs8giiyxOdpyklUUWWWRxgiObLLLIIotjRTZZZJFFFseKbLLIIossjhXZZJFFFlkcK/4bT6JWTRyLHOQAAAAASUVORK5CYII=\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9d459b9320>"
+       "<matplotlib.figure.Figure at 0x7f5d83be9f60>"
       ]
      },
      "metadata": {},
@@ -97,7 +97,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 2.07392954826355 seconds ---\n",
+      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 1.911818504333496 seconds ---\n",
       "\n",
       "gram matrix with parameters {'height': 3.0} is: \n",
       "[[ 20.   0.   0. ...   0.   0.   0.]\n",
@@ -111,9 +111,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9d45945fd0>"
+       "<matplotlib.figure.Figure at 0x7f5d83b755f8>"
       ]
      },
      "metadata": {},
@@ -124,7 +124,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 2.4412496089935303 seconds ---\n",
+      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 2.1614458560943604 seconds ---\n",
       "\n",
       "gram matrix with parameters {'height': 4.0} is: \n",
       "[[ 25.   0.   0. ...   0.   0.   0.]\n",
@@ -138,9 +138,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9d4595b780>"
+       "<matplotlib.figure.Figure at 0x7f5d83b72978>"
       ]
      },
      "metadata": {},
@@ -151,7 +151,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 2.8024017810821533 seconds ---\n",
+      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 2.8392231464385986 seconds ---\n",
       "\n",
       "gram matrix with parameters {'height': 5.0} is: \n",
       "[[ 30.   0.   0. ...   0.   0.   0.]\n",
@@ -165,9 +165,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9d45921cc0>"
+       "<matplotlib.figure.Figure at 0x7f5d83ae3eb8>"
       ]
      },
      "metadata": {},
@@ -178,7 +178,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 3.4581663608551025 seconds ---\n",
+      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 3.197157859802246 seconds ---\n",
       "\n",
       "gram matrix with parameters {'height': 6.0} is: \n",
       "[[ 35.   0.   0. ...   0.   0.   0.]\n",
@@ -192,9 +192,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9d440d3710>"
+       "<matplotlib.figure.Figure at 0x7f5d83adc320>"
       ]
      },
      "metadata": {},
@@ -205,7 +205,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 3.761540174484253 seconds ---\n",
+      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 3.8528859615325928 seconds ---\n",
       "\n",
       "gram matrix with parameters {'height': 7.0} is: \n",
       "[[ 40.   0.   0. ...   0.   0.   0.]\n",
@@ -219,9 +219,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9d45901f28>"
+       "<matplotlib.figure.Figure at 0x7f5d83ae63c8>"
       ]
      },
      "metadata": {},
@@ -232,7 +232,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 4.494075775146484 seconds ---\n",
+      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 3.7338240146636963 seconds ---\n",
       "\n",
       "gram matrix with parameters {'height': 8.0} is: \n",
       "[[ 45.   0.   0. ...   0.   0.   0.]\n",
@@ -246,9 +246,9 @@
     },
     {
      "data": {
-      "image/png": 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ZHZP0rKR7zaxPkks6KulxSXL398xsWNL7kuYlPeHu56IpHUArmbvHXYO+at2+3jbHXQbQMqcf26juofj3Jpn0ov7XT1uY9zKDE4hB99BE6uZgEBZATNI2rEpYADHqHprQx/+WjntJCAsgZiueG0/FVomEBYBQCAsgAXp3j6t393iiWxeEBZAgvbvHE9uHQVgACbPiuXF9NHxH3GVchrAAEuhrD83oyAsbdeSF5AytEhYAQmH7QiChVu6qTAc//eYadW89HHM1tCyAxOveejgRd6oSFkAKJGE9DMICSInCaDnWDk/CAkiRlbsmYhslISwAhMJoCJAy1VGSs4Pr1TEy2bKfS8sCSKmOkcmWTg0nLIAUW/HcuAbf/6wlP4uwAFJuZO3ylnR6EhYAQqGDE8iAVkwNp2UBZEj31sORXY4QFkDGrNw1oTPbm7/NAGEBZFDXvpLODq5v6vckLICM6hiZ1JntG5rWyiAsAITCaAiQYV37SpKaMzWclgWQAx0jkzr95pqGvgdhAeREo8OqhAWQIyt3Tej0m2vqamUQFgBCISyAnOneeljdWw/rsx8s7ZKEsAByavlLEzp/3bWh32/uHmE5IYsw+0zS3yT9Oe5aWuwGcc55kORz/pq7Lw/zxkSEhSSZ2X5374+7jlbinPMhK+fMZQiAUAgLAKEkKSxejruAGHDO+ZCJc05MnwWAZEtSywJAghEWAEIhLACEQlgACIWwABDK/wOyNv1vJXnNTQAAAABJRU5ErkJggg==\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9d4595ba20>"
+       "<matplotlib.figure.Figure at 0x7f5d83b6ada0>"
       ]
      },
      "metadata": {},
@@ -259,7 +259,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 4.6411638259887695 seconds ---\n",
+      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 4.214876890182495 seconds ---\n",
       "\n",
       "gram matrix with parameters {'height': 9.0} is: \n",
       "[[ 50.   0.   0. ...   0.   0.   0.]\n",
@@ -273,9 +273,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9d440d3278>"
+       "<matplotlib.figure.Figure at 0x7f5d82275470>"
       ]
      },
      "metadata": {},
@@ -286,7 +286,7 @@
      "output_type": "stream",
      "text": [
       "\n",
-      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 5.17179536819458 seconds ---\n",
+      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 4.636343955993652 seconds ---\n",
       "\n",
       "gram matrix with parameters {'height': 10.0} is: \n",
       "[[ 55.   0.   0. ...   0.   0.   0.]\n",
@@ -300,9 +300,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9d4591efd0>"
+       "<matplotlib.figure.Figure at 0x7f5d83b743c8>"
       ]
      },
      "metadata": {},
@@ -314,7 +314,7 @@
      "text": [
       "\n",
       "3. Fitting and predicting using nested cross validation. This could really take a while...\n",
-      "calculate performance:   0%|          | 3/13530 [00:00<09:39, 23.34it/s]"
+      "calculate performance:   0%|          | 3/13530 [00:00<09:29, 23.74it/s]"
      ]
     },
     {
@@ -333,468 +333,471 @@
       "4. Getting final performances...\n",
       "\n",
       "best_params_out:  [{'height': 1.0}]\n",
-      "best_params_in:  [{'alpha': 0.12589254117941676}]\n",
-      "best_val_perf:  7.593412392539851\n",
-      "best_val_std:  0.7111794979520709\n",
-      "final_performance:  7.923917693852004\n",
-      "final_confidence:  2.919445947208125\n",
-      "train_performance:  5.9954331001158705\n",
-      "train_std:  0.26528917359193244\n",
-      "time to calculate gram matrix:  0.8394806385040283 s\n",
-      "\n",
-      "params                                 train_perf         valid_perf               test_perf                gram_matrix_time\n",
-      "-------------------------------------  -----------------  -----------------------  ---------------------  ------------------\n",
-      "{'alpha': '1.00e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
-      "{'alpha': '1.00e-02', 'height': 1.0}   5.93±0.30          7.91±0.84                8.40±3.39                            0.84\n",
-      "{'alpha': '1.00e-02', 'height': 2.0}   451.39±1422.80     2033.21±3426.97          13378.54±63943.34                    1.36\n",
-      "{'alpha': '1.00e-02', 'height': 3.0}   13217.28±19076.04  261279.62±289350.01      437442.31±862782.28                  2.07\n",
-      "{'alpha': '1.00e-02', 'height': 4.0}   10671.89±29293.73  21335653.32±64894754.82  4989479.40±9290521.80                2.44\n",
-      "{'alpha': '1.00e-02', 'height': 5.0}   94.09±3.28         407296.40±47673.76       444502.94±272049.80                  2.8\n",
-      "{'alpha': '1.00e-02', 'height': 6.0}   93.91±3.15         486340.54±58427.24       459992.03±280235.03                  3.46\n",
-      "{'alpha': '1.00e-02', 'height': 7.0}   93.94±2.67         520804.91±75722.08       657807.23±404298.33                  3.76\n",
-      "{'alpha': '1.00e-02', 'height': 8.0}   94.22±2.73         625727.59±61899.85       569481.82±335243.00                  4.49\n",
-      "{'alpha': '1.00e-02', 'height': 9.0}   94.30±3.66         687051.15±78936.05       667719.96±446436.72                  4.64\n",
-      "{'alpha': '1.00e-02', 'height': 10.0}  94.41±2.97         762435.00±95172.47       714393.46±458341.02                  5.17\n",
-      "{'alpha': '1.26e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
-      "{'alpha': '1.26e-02', 'height': 1.0}   5.93±0.30          7.87±0.82                8.36±3.36                            0.84\n",
-      "{'alpha': '1.26e-02', 'height': 2.0}   277.93±758.85      1552.65±2280.09          1514.81±2473.29                      1.36\n",
-      "{'alpha': '1.26e-02', 'height': 3.0}   9437.19±13421.12   174782.35±151622.74      274881.23±586531.17                  2.07\n",
-      "{'alpha': '1.26e-02', 'height': 4.0}   7398.32±18414.83   11840780.80±34685999.57  2942677.48±5100993.34                2.44\n",
-      "{'alpha': '1.26e-02', 'height': 5.0}   94.09±3.28         323521.90±37866.99       353073.83±216091.39                  2.8\n",
-      "{'alpha': '1.26e-02', 'height': 6.0}   93.90±3.15         386307.54±46409.46       365379.51±222589.05                  3.46\n",
-      "{'alpha': '1.26e-02', 'height': 7.0}   93.94±2.67         413684.62±60146.49       522504.97±321142.58                  3.76\n",
-      "{'alpha': '1.26e-02', 'height': 8.0}   94.22±2.73         497027.10±49166.67       452349.10±266285.35                  4.49\n",
-      "{'alpha': '1.26e-02', 'height': 9.0}   94.30±3.66         545738.18±62699.49       530383.11±354608.84                  4.64\n",
-      "{'alpha': '1.26e-02', 'height': 10.0}  94.41±2.97         605616.74±75596.99       567457.60±364065.72                  5.17\n",
-      "{'alpha': '1.58e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
-      "{'alpha': '1.58e-02', 'height': 1.0}   5.92±0.30          7.85±0.81                8.33±3.33                            0.84\n",
-      "{'alpha': '1.58e-02', 'height': 2.0}   176.25±161.40      1390.68±1857.71          1715.33±2996.09                      1.36\n",
-      "{'alpha': '1.58e-02', 'height': 3.0}   6396.84±8263.38    131706.82±101947.90      251319.34±643023.46                  2.07\n",
-      "{'alpha': '1.58e-02', 'height': 4.0}   5360.98±12332.55   6631038.07±18579708.95   1835063.49±3032523.77                2.44\n",
-      "{'alpha': '1.58e-02', 'height': 5.0}   94.08±3.28         256977.44±30077.20       280449.12±171642.05                  2.8\n",
-      "{'alpha': '1.58e-02', 'height': 6.0}   93.90±3.15         306848.51±36863.40       290226.11±176799.23                  3.46\n",
-      "{'alpha': '1.58e-02', 'height': 7.0}   93.94±2.67         328595.95±47774.36       415030.57±255089.63                  3.76\n",
-      "{'alpha': '1.58e-02', 'height': 8.0}   94.21±2.73         394796.67±39052.35       359307.28±211510.34                  4.49\n",
-      "{'alpha': '1.58e-02', 'height': 9.0}   94.30±3.66         433489.29±49802.32       421292.58±281667.36                  4.64\n",
-      "{'alpha': '1.58e-02', 'height': 10.0}  94.40±2.97         481051.56±60047.64       450742.30±289180.18                  5.17\n",
-      "{'alpha': '2.00e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
-      "{'alpha': '2.00e-02', 'height': 1.0}   5.91±0.30          7.82±0.81                8.29±3.30                            0.84\n",
-      "{'alpha': '2.00e-02', 'height': 2.0}   125.97±137.21      1048.44±1112.78          1021.78±1307.63                      1.36\n",
-      "{'alpha': '2.00e-02', 'height': 3.0}   20302.49±82971.88  313670.36±1065466.94     589536.67±1943611.12                 2.07\n",
-      "{'alpha': '2.00e-02', 'height': 4.0}   3955.13±8402.38    3769262.95±9990447.47    1172757.06±1852365.49                2.44\n",
-      "{'alpha': '2.00e-02', 'height': 5.0}   94.08±3.28         204119.31±23889.56       222761.26±136334.68                  2.8\n",
-      "{'alpha': '2.00e-02', 'height': 6.0}   93.90±3.15         243731.97±29280.69       230529.65±140427.07                  3.46\n",
-      "{'alpha': '2.00e-02', 'height': 7.0}   93.93±2.67         261007.62±37946.83       329660.62±202621.89                  3.76\n",
-      "{'alpha': '2.00e-02', 'height': 8.0}   94.21±2.73         313592.16±31018.26       285401.54±168001.01                  4.49\n",
-      "{'alpha': '2.00e-02', 'height': 9.0}   94.30±3.66         344326.84±39557.74       334638.89±223727.89                  4.64\n",
-      "{'alpha': '2.00e-02', 'height': 10.0}  94.40±2.97         382105.92±47696.35       358032.04±229696.49                  5.17\n",
-      "{'alpha': '2.51e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
-      "{'alpha': '2.51e-02', 'height': 1.0}   5.91±0.30          7.78±0.80                8.25±3.27                            0.84\n",
-      "{'alpha': '2.51e-02', 'height': 2.0}   188.37±542.93      1013.54±1474.00          1332.40±3017.49                      1.36\n",
-      "{'alpha': '2.51e-02', 'height': 3.0}   9955.28±26477.71   253161.66±677515.09      1180633.15±5705131.18                2.07\n",
-      "{'alpha': '2.51e-02', 'height': 4.0}   2955.62±5794.80    2156680.75±5406547.12    761733.10±1152104.32                 2.44\n",
-      "{'alpha': '2.51e-02', 'height': 5.0}   94.07±3.28         162132.60±18974.53       176938.16±108289.04                  2.8\n",
-      "{'alpha': '2.51e-02', 'height': 6.0}   93.89±3.15         193596.71±23257.53       183111.07±111535.65                  3.46\n",
-      "{'alpha': '2.51e-02', 'height': 7.0}   93.93±2.67         207320.31±30140.54       261848.86±160945.29                  3.76\n",
-      "{'alpha': '2.51e-02', 'height': 8.0}   94.20±2.73         249089.12±24636.56       226696.12±133440.31                  4.49\n",
-      "{'alpha': '2.51e-02', 'height': 9.0}   94.29±3.66         273502.58±31420.18       265807.42±177704.93                  4.64\n",
-      "{'alpha': '2.51e-02', 'height': 10.0}  94.40±2.97         303510.61±37885.37       284389.67±182446.91                  5.17\n",
-      "{'alpha': '3.16e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
-      "{'alpha': '3.16e-02', 'height': 1.0}   5.90±0.29          7.75±0.80                8.20±3.24                            0.84\n",
-      "{'alpha': '3.16e-02', 'height': 2.0}   142.63±251.72      906.42±815.89            1333.06±1973.95                      1.36\n",
-      "{'alpha': '3.16e-02', 'height': 3.0}   6891.55±8840.69    166321.90±228973.64      279768.30±671954.98                  2.07\n",
-      "{'alpha': '3.16e-02', 'height': 4.0}   2243.88±4055.42    1260772.00±2958901.20    499416.02±727770.64                  2.44\n",
-      "{'alpha': '3.16e-02', 'height': 5.0}   94.06±3.28         128781.38±15070.39       140539.59±86011.60                   2.8\n",
-      "{'alpha': '3.16e-02', 'height': 6.0}   93.88±3.15         153772.87±18473.17       145445.15±88586.37                   3.46\n",
-      "{'alpha': '3.16e-02', 'height': 7.0}   93.92±2.67         164674.96±23939.79       207984.07±127840.39                  3.76\n",
-      "{'alpha': '3.16e-02', 'height': 8.0}   94.20±2.73         197852.54±19567.39       180064.75±105987.78                  4.49\n",
-      "{'alpha': '3.16e-02', 'height': 9.0}   94.29±3.66         217244.88±24956.29       211132.65±141147.59                  4.64\n",
-      "{'alpha': '3.16e-02', 'height': 10.0}  94.39±2.97         241080.14±30092.23       225893.45±144915.23                  5.17\n",
-      "{'alpha': '3.98e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
-      "{'alpha': '3.98e-02', 'height': 1.0}   5.89±0.29          7.72±0.79                8.16±3.20                            0.84\n",
-      "{'alpha': '3.98e-02', 'height': 2.0}   138.31±196.80      1267.62±2668.98          1652.36±2796.92                      1.36\n",
-      "{'alpha': '3.98e-02', 'height': 3.0}   6478.02±11055.70   123471.52±147910.88      298331.38±771669.13                  2.07\n",
-      "{'alpha': '3.98e-02', 'height': 4.0}   1736.58±2903.69    754766.87±1650052.08     334691.85±467002.49                  2.44\n",
-      "{'alpha': '3.98e-02', 'height': 5.0}   94.05±3.28         102289.57±11969.22       111627.19±68316.00                   2.8\n",
-      "{'alpha': '3.98e-02', 'height': 6.0}   93.87±3.15         122139.68±14672.81       115526.06±70357.12                   3.46\n",
-      "{'alpha': '3.98e-02', 'height': 7.0}   93.91±2.67         130800.57±19014.36       165197.76±101544.22                  3.76\n",
-      "{'alpha': '3.98e-02', 'height': 8.0}   94.19±2.73         157153.89±15540.81       143024.15±84181.46                   4.49\n",
-      "{'alpha': '3.98e-02', 'height': 9.0}   94.28±3.66         172557.81±19821.84       167702.93±112109.06                  4.64\n",
-      "{'alpha': '3.98e-02', 'height': 10.0}  94.38±2.97         191489.86±23901.92       179428.26±115102.76                  5.17\n",
-      "{'alpha': '5.01e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
-      "{'alpha': '5.01e-02', 'height': 1.0}   5.89±0.29          7.68±0.78                8.10±3.16                            0.84\n",
-      "{'alpha': '5.01e-02', 'height': 2.0}   113.20±192.15      717.38±715.29            692.81±705.13                        1.36\n",
-      "{'alpha': '5.01e-02', 'height': 3.0}   3320.31±3710.73    55827.61±48994.23        91365.16±124507.92                   2.07\n",
-      "{'alpha': '5.01e-02', 'height': 4.0}   1379.39±2158.81    465219.45±944427.71      229421.22±306945.02                  2.44\n",
-      "{'alpha': '5.01e-02', 'height': 5.0}   94.03±3.28         81246.39±9505.87         88661.26±54259.88                    2.8\n",
-      "{'alpha': '5.01e-02', 'height': 6.0}   93.86±3.15         97012.54±11654.08        91760.49±55877.10                    3.46\n",
-      "{'alpha': '5.01e-02', 'height': 7.0}   93.90±2.67         103893.18±15101.95       131211.38±80656.43                   3.76\n",
-      "{'alpha': '5.01e-02', 'height': 8.0}   94.18±2.73         124825.80±12342.38       113601.75±66860.08                   4.49\n",
-      "{'alpha': '5.01e-02', 'height': 9.0}   94.27±3.66         137061.61±15743.40       133205.49±89042.94                   4.64\n",
-      "{'alpha': '5.01e-02', 'height': 10.0}  94.37±2.97         152098.91±18984.79       142519.65±91421.88                   5.17\n",
-      "{'alpha': '6.31e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
-      "{'alpha': '6.31e-02', 'height': 1.0}   5.90±0.28          7.65±0.77                8.05±3.11                            0.84\n",
-      "{'alpha': '6.31e-02', 'height': 2.0}   495.01±2368.19     701.09±907.85            1074.88±3332.14                      1.36\n",
-      "{'alpha': '6.31e-02', 'height': 3.0}   10680.06±36678.01  84683.10±120163.09       218752.56±487822.52                  2.07\n",
-      "{'alpha': '6.31e-02', 'height': 4.0}   1142.88±1719.11    298125.16±562161.90      162416.05±211678.35                  2.44\n",
-      "{'alpha': '6.31e-02', 'height': 5.0}   94.01±3.28         64531.20±7549.16         70418.78±43094.71                    2.8\n",
-      "{'alpha': '6.31e-02', 'height': 6.0}   93.84±3.15         77053.36±9256.22         72882.83±44375.22                    3.46\n",
-      "{'alpha': '6.31e-02', 'height': 7.0}   93.88±2.67         82519.90±11994.21        104215.06±64064.67                   3.76\n",
-      "{'alpha': '6.31e-02', 'height': 8.0}   94.17±2.73         99146.69±9801.78         90230.72±53101.22                    4.49\n",
-      "{'alpha': '6.31e-02', 'height': 9.0}   94.26±3.66         108865.98±12503.78       105803.20±70720.87                   4.64\n",
-      "{'alpha': '6.31e-02', 'height': 10.0}  94.36±2.97         120809.57±15078.97       113202.11±72611.48                   5.17\n",
-      "{'alpha': '7.94e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
-      "{'alpha': '7.94e-02', 'height': 1.0}   5.91±0.28          7.62±0.76                8.00±3.06                            0.84\n",
-      "{'alpha': '7.94e-02', 'height': 2.0}   306.95±857.73      1151.28±2004.26          1935.36±6798.23                      1.36\n",
-      "{'alpha': '7.94e-02', 'height': 3.0}   4564.02±6486.95    54324.41±56928.97        104940.22±130143.03                  2.07\n",
-      "{'alpha': '7.94e-02', 'height': 4.0}   1041.89±1605.14    203639.32±357797.85      122517.59±167291.18                  2.44\n",
-      "{'alpha': '7.94e-02', 'height': 5.0}   93.99±3.28         51253.87±5994.90         55928.28±34225.89                    2.8\n",
-      "{'alpha': '7.94e-02', 'height': 6.0}   93.82±3.15         61199.23±7351.53         57887.78±35238.96                    3.46\n",
-      "{'alpha': '7.94e-02', 'height': 7.0}   93.87±2.67         65542.51±9525.65         82771.13±50885.35                    3.76\n",
-      "{'alpha': '7.94e-02', 'height': 8.0}   94.15±2.73         78749.07±7783.72         71666.46±42172.18                    4.49\n",
-      "{'alpha': '7.94e-02', 'height': 9.0}   94.24±3.65         86469.40±9930.46         84036.80±56167.13                    4.64\n",
-      "{'alpha': '7.94e-02', 'height': 10.0}  94.35±2.97         95955.57±11976.46        89914.37±57669.85                    5.17\n",
-      "{'alpha': '1.00e-01', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
-      "{'alpha': '1.00e-01', 'height': 1.0}   5.94±0.27          7.60±0.74                7.95±2.99                            0.84\n",
-      "{'alpha': '1.00e-01', 'height': 2.0}   89.35±130.88       702.29±1001.96           491.37±465.29                        1.36\n",
-      "{'alpha': '1.00e-01', 'height': 3.0}   5890.66±16470.70   62994.31±97190.58        129042.83±260862.31                  2.07\n",
-      "{'alpha': '1.00e-01', 'height': 4.0}   1590.22±3690.33    182193.69±313149.59      143780.91±375020.40                  2.44\n",
-      "{'alpha': '1.00e-01', 'height': 5.0}   93.96±3.28         40707.33±4760.30         44418.08±27181.14                    2.8\n",
-      "{'alpha': '1.00e-01', 'height': 6.0}   93.79±3.15         48605.86±5838.58         45976.81±27981.76                    3.46\n",
-      "{'alpha': '1.00e-01', 'height': 7.0}   93.84±2.67         52056.90±7564.80         65737.62±40416.64                    3.76\n",
-      "{'alpha': '1.00e-01', 'height': 8.0}   94.13±2.73         62546.67±6180.71         56920.35±33490.92                    4.49\n",
-      "{'alpha': '1.00e-01', 'height': 9.0}   94.22±3.65         68679.18±7886.40         66747.14±44606.68                    4.64\n",
-      "{'alpha': '1.00e-01', 'height': 10.0}  94.33±2.97         76213.34±9512.06         71416.26±45801.29                    5.17\n",
-      "{'alpha': '1.26e-01', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
-      "{'alpha': '1.26e-01', 'height': 1.0}   6.00±0.27          7.59±0.71                7.92±2.92                            0.84\n",
-      "{'alpha': '1.26e-01', 'height': 2.0}   48.25±40.76        393.24±411.22            336.33±324.83                        1.36\n",
-      "{'alpha': '1.26e-01', 'height': 3.0}   2530.54±3320.80    51756.89±85299.59        67083.99±85132.00                    2.07\n",
-      "{'alpha': '1.26e-01', 'height': 4.0}   2161.16±4321.83    250431.27±513859.25      127397.71±211480.04                  2.44\n",
-      "{'alpha': '1.26e-01', 'height': 5.0}   93.92±3.27         32329.94±3779.63         35275.22±21585.29                    2.8\n",
-      "{'alpha': '1.26e-01', 'height': 6.0}   93.76±3.15         38602.62±4636.80         36515.60±22217.17                    3.46\n",
-      "{'alpha': '1.26e-01', 'height': 7.0}   93.82±2.67         41344.91±6007.24         52207.45±32101.04                    3.76\n",
-      "{'alpha': '1.26e-01', 'height': 8.0}   94.10±2.73         49676.66±4907.40         45207.11±26595.16                    4.49\n",
-      "{'alpha': '1.26e-01', 'height': 9.0}   94.20±3.65         54547.92±6262.74         53013.49±35423.89                    4.64\n",
-      "{'alpha': '1.26e-01', 'height': 10.0}  94.31±2.97         60531.55±7554.51         56722.71±36373.76                    5.17\n",
-      "{'alpha': '1.58e-01', 'height': 0.0}   16.78±0.34         16.85±0.38               17.36±2.96                           0.36\n",
-      "{'alpha': '1.58e-01', 'height': 1.0}   6.08±0.26          7.61±0.68                7.92±2.84                            0.84\n",
-      "{'alpha': '1.58e-01', 'height': 2.0}   45.58±36.64        379.59±394.67            395.44±512.31                        1.36\n",
-      "{'alpha': '1.58e-01', 'height': 3.0}   1514.06±2243.98    28601.81±56482.31        49247.17±86087.19                    2.07\n",
-      "{'alpha': '1.58e-01', 'height': 4.0}   1070.69±1396.30    145407.22±381518.31      118222.29±291447.85                  2.44\n",
-      "{'alpha': '1.58e-01', 'height': 5.0}   93.87±3.27         25675.56±3000.65         28012.82±17140.35                    2.8\n",
-      "{'alpha': '1.58e-01', 'height': 6.0}   93.72±3.14         30656.78±3682.19         29000.32±17638.20                    3.46\n",
-      "{'alpha': '1.58e-01', 'height': 7.0}   93.78±2.67         32836.10±4770.03         41460.07±25495.71                    3.76\n",
-      "{'alpha': '1.58e-01', 'height': 8.0}   94.07±2.73         39453.66±3895.97         35902.98±21117.67                    4.49\n",
-      "{'alpha': '1.58e-01', 'height': 9.0}   94.17±3.65         43323.07±4973.03         42104.49±28129.74                    4.64\n",
-      "{'alpha': '1.58e-01', 'height': 10.0}  94.29±2.97         48075.07±5999.58         45051.22±28885.21                    5.17\n",
-      "{'alpha': '2.00e-01', 'height': 0.0}   16.78±0.34         16.85±0.38               17.36±2.96                           0.36\n",
-      "{'alpha': '2.00e-01', 'height': 1.0}   6.21±0.24          7.67±0.64                7.95±2.74                            0.84\n",
-      "{'alpha': '2.00e-01', 'height': 2.0}   89.06±164.72       957.29±2783.62           870.02±2562.11                       1.36\n",
-      "{'alpha': '2.00e-01', 'height': 3.0}   3623.18±13460.71   28255.58±55476.75        138758.54±431759.63                  2.07\n",
-      "{'alpha': '2.00e-01', 'height': 4.0}   805.96±2638.59     106734.00±393681.69      55498.96±145636.61                   2.44\n",
-      "{'alpha': '2.00e-01', 'height': 5.0}   93.81±3.27         20389.83±2381.89         22244.13±13609.61                    2.8\n",
-      "{'alpha': '2.00e-01', 'height': 6.0}   93.67±3.14         24345.20±2923.92         23030.75±14000.99                    3.46\n",
-      "{'alpha': '2.00e-01', 'height': 7.0}   93.74±2.66         26077.34±3787.28         32923.15±20248.89                    3.76\n",
-      "{'alpha': '2.00e-01', 'height': 8.0}   94.03±2.73         31333.27±3092.57         28512.46±16766.74                    4.49\n",
-      "{'alpha': '2.00e-01', 'height': 9.0}   94.14±3.65         34406.88±3948.58         33439.17±22335.79                    4.64\n",
-      "{'alpha': '2.00e-01', 'height': 10.0}  94.25±2.97         38180.56±4764.45         35780.25±22936.84                    5.17\n",
-      "{'alpha': '2.51e-01', 'height': 0.0}   16.78±0.34         16.85±0.38               17.36±2.96                           0.36\n",
-      "{'alpha': '2.51e-01', 'height': 1.0}   6.39±0.23          7.77±0.60                8.02±2.65                            0.84\n",
-      "{'alpha': '2.51e-01', 'height': 2.0}   54.61±89.25        274.39±293.91            239.06±230.21                        1.36\n",
-      "{'alpha': '2.51e-01', 'height': 3.0}   1091.97±1284.58    15415.44±22101.51        55468.31±140524.95                   2.07\n",
-      "{'alpha': '2.51e-01', 'height': 4.0}   294.90±426.58      26446.23±32961.94        22945.61±24803.83                    2.44\n",
-      "{'alpha': '2.51e-01', 'height': 5.0}   93.74±3.26         16191.28±1890.39         17661.93±10805.03                    2.8\n",
-      "{'alpha': '2.51e-01', 'height': 6.0}   93.61±3.14         19331.78±2321.60         18288.98±11111.86                    3.46\n",
-      "{'alpha': '2.51e-01', 'height': 7.0}   93.68±2.66         20708.70±3006.66         26142.08±16081.17                    3.76\n",
-      "{'alpha': '2.51e-01', 'height': 8.0}   93.98±2.73         24883.05±2454.41         22641.99±13310.68                    4.49\n",
-      "{'alpha': '2.51e-01', 'height': 9.0}   94.09±3.64         27324.53±3134.83         26556.10±17733.49                    4.64\n",
-      "{'alpha': '2.51e-01', 'height': 10.0}  94.21±2.97         30321.10±3783.36         28416.08±18211.88                    5.17\n",
-      "{'alpha': '3.16e-01', 'height': 0.0}   16.78±0.34         16.85±0.38               17.36±2.96                           0.36\n",
-      "{'alpha': '3.16e-01', 'height': 1.0}   6.62±0.22          7.92±0.56                8.16±2.56                            0.84\n",
-      "{'alpha': '3.16e-01', 'height': 2.0}   54.05±109.97       238.59±298.74            188.49±227.69                        1.36\n",
-      "{'alpha': '3.16e-01', 'height': 3.0}   1666.43±3413.96    20243.44±52284.88        32350.13±50420.16                    2.07\n",
-      "{'alpha': '3.16e-01', 'height': 4.0}   192.44±134.92      15596.94±9967.47         14669.65±9654.92                     2.44\n",
-      "{'alpha': '3.16e-01', 'height': 5.0}   93.65±3.26         12856.29±1499.98         14022.21±8577.27                     2.8\n",
-      "{'alpha': '3.16e-01', 'height': 6.0}   93.53±3.14         15349.52±1843.17         14522.51±8816.95                     3.46\n",
-      "{'alpha': '3.16e-01', 'height': 7.0}   93.61±2.66         16444.28±2386.59         20755.73±12770.61                    3.76\n",
-      "{'alpha': '3.16e-01', 'height': 8.0}   93.92±2.73         19759.49±1947.51         17978.94±10565.44                    4.49\n",
-      "{'alpha': '3.16e-01', 'height': 9.0}   94.03±3.64         21698.84±2488.45         21088.71±14077.75                    4.64\n",
-      "{'alpha': '3.16e-01', 'height': 10.0}  94.16±2.96         24078.13±3004.05         22566.54±14458.70                    5.17\n",
-      "{'alpha': '3.98e-01', 'height': 0.0}   16.78±0.34         16.85±0.38               17.36±2.96                           0.36\n",
-      "{'alpha': '3.98e-01', 'height': 1.0}   6.91±0.22          8.12±0.51                8.35±2.47                            0.84\n",
-      "{'alpha': '3.98e-01', 'height': 2.0}   49.86±74.92        423.62±1025.43           217.13±354.00                        1.36\n",
-      "{'alpha': '3.98e-01', 'height': 3.0}   526.15±484.70      5601.31±3973.72          13993.28±18153.44                    2.07\n",
-      "{'alpha': '3.98e-01', 'height': 4.0}   152.41±74.56       10732.48±4799.03         10551.26±5993.01                     2.44\n",
-      "{'alpha': '3.98e-01', 'height': 5.0}   93.53±3.25         10207.29±1189.87         11131.15±6807.69                     2.8\n",
-      "{'alpha': '3.98e-01', 'height': 6.0}   93.42±3.13         12186.37±1463.13         11530.74±6994.05                     3.46\n",
-      "{'alpha': '3.98e-01', 'height': 7.0}   93.52±2.65         13056.99±1894.06         16477.25±10140.90                    3.76\n",
-      "{'alpha': '3.98e-01', 'height': 8.0}   93.84±2.72         15689.75±1544.87         14275.00±8384.82                     4.49\n",
-      "{'alpha': '3.98e-01', 'height': 9.0}   93.96±3.63         17230.25±1975.01         16745.85±11173.89                    4.64\n",
-      "{'alpha': '3.98e-01', 'height': 10.0}  94.09±2.96         19119.21±2385.02         17920.12±11477.45                    5.17\n",
-      "{'alpha': '5.01e-01', 'height': 0.0}   16.79±0.34         16.85±0.38               17.36±2.96                           0.36\n",
-      "{'alpha': '5.01e-01', 'height': 1.0}   7.25±0.21          8.38±0.47                8.60±2.40                            0.84\n",
-      "{'alpha': '5.01e-01', 'height': 2.0}   26.87±20.60        116.90±75.77             121.44±128.40                        1.36\n",
-      "{'alpha': '5.01e-01', 'height': 3.0}   785.86±1508.78     8718.36±16998.65         47199.93±187043.98                   2.07\n",
-      "{'alpha': '5.01e-01', 'height': 4.0}   129.42±49.88       7794.74±2735.41          7879.20±4255.73                      2.44\n",
-      "{'alpha': '5.01e-01', 'height': 5.0}   93.38±3.25         8103.20±943.54           8834.78±5402.05                      2.8\n",
-      "{'alpha': '5.01e-01', 'height': 6.0}   93.30±3.12         9673.86±1161.25          9154.37±5546.07                      3.46\n",
-      "{'alpha': '5.01e-01', 'height': 7.0}   93.41±2.65         10366.44±1502.83         13078.82±8052.01                     3.76\n",
-      "{'alpha': '5.01e-01', 'height': 8.0}   93.74±2.72         12457.10±1225.05         11332.90±6652.70                     4.49\n",
-      "{'alpha': '5.01e-01', 'height': 9.0}   93.87±3.63         13680.77±1567.18         13296.25±8867.27                     4.64\n",
-      "{'alpha': '5.01e-01', 'height': 10.0}  94.01±2.96         15180.25±1893.31         14229.39±9109.36                     5.17\n",
-      "{'alpha': '6.31e-01', 'height': 0.0}   16.79±0.34         16.86±0.38               17.36±2.96                           0.36\n",
-      "{'alpha': '6.31e-01', 'height': 1.0}   7.63±0.21          8.69±0.43                8.90±2.34                            0.84\n",
-      "{'alpha': '6.31e-01', 'height': 2.0}   35.58±63.12        123.47±146.83            176.46±344.92                        1.36\n",
-      "{'alpha': '6.31e-01', 'height': 3.0}   428.18±500.44      4257.16±4435.22          7930.43±12367.72                     2.07\n",
-      "{'alpha': '6.31e-01', 'height': 4.0}   114.75±35.74       5820.70±1661.76          6004.25±3194.91                      2.44\n",
-      "{'alpha': '6.31e-01', 'height': 5.0}   93.20±3.24         6431.96±747.88           7010.82±4285.50                      2.8\n",
-      "{'alpha': '6.31e-01', 'height': 6.0}   93.14±3.12         7678.20±921.47           7266.83±4395.92                      3.46\n",
-      "{'alpha': '6.31e-01', 'height': 7.0}   93.27±2.64         8229.34±1192.06          10379.44±6392.69                     3.76\n",
-      "{'alpha': '6.31e-01', 'height': 8.0}   93.62±2.72         9889.39±971.02           8995.98±5276.84                      4.49\n",
-      "{'alpha': '6.31e-01', 'height': 9.0}   93.76±3.62         10861.38±1243.23         10556.20±7035.04                     4.64\n",
-      "{'alpha': '6.31e-01', 'height': 10.0}  93.90±2.95         12051.48±1502.73         11297.81±7228.31                     5.17\n",
-      "{'alpha': '7.94e-01', 'height': 0.0}   16.79±0.34         16.86±0.38               17.35±2.96                           0.36\n",
-      "{'alpha': '7.94e-01', 'height': 1.0}   8.04±0.22          9.03±0.40                9.24±2.31                            0.84\n",
-      "{'alpha': '7.94e-01', 'height': 2.0}   22.69±28.56        142.73±379.10            386.12±1610.23                       1.36\n",
-      "{'alpha': '7.94e-01', 'height': 3.0}   227.28±170.11      2519.01±1835.87          5056.97±8342.04                      2.07\n",
-      "{'alpha': '7.94e-01', 'height': 4.0}   104.96±26.07       4421.51±1040.23          4634.21±2461.66                      2.44\n",
-      "{'alpha': '7.94e-01', 'height': 5.0}   92.97±3.22         5104.59±592.46           5562.13±3398.57                      2.8\n",
-      "{'alpha': '7.94e-01', 'height': 6.0}   92.94±3.11         6093.11±730.99           5767.62±3482.33                      3.46\n",
-      "{'alpha': '7.94e-01', 'height': 7.0}   93.10±2.64         6531.89±945.22           8235.37±5074.57                      3.76\n",
-      "{'alpha': '7.94e-01', 'height': 8.0}   93.46±2.71         7849.88±769.24           7139.78±4183.96                      4.49\n",
-      "{'alpha': '7.94e-01', 'height': 9.0}   93.61±3.61         8621.95±985.92           8379.79±5579.65                      4.64\n",
-      "{'alpha': '7.94e-01', 'height': 10.0}  93.77±2.94         9566.29±1192.49          8969.24±5734.14                      5.17\n",
-      "{'alpha': '1.00e+00', 'height': 0.0}   16.80±0.34         16.86±0.38               17.35±2.96                           0.36\n",
-      "{'alpha': '1.00e+00', 'height': 1.0}   8.45±0.22          9.39±0.38                9.61±2.31                            0.84\n",
-      "{'alpha': '1.00e+00', 'height': 2.0}   13.42±5.66         48.59±20.64              53.77±66.09                          1.36\n",
-      "{'alpha': '1.00e+00', 'height': 3.0}   197.96±199.80      2051.49±2168.73          3204.98±5011.18                      2.07\n",
-      "{'alpha': '1.00e+00', 'height': 4.0}   98.24±18.96        3398.37±665.20           3607.25±1921.04                      2.44\n",
-      "{'alpha': '1.00e+00', 'height': 5.0}   92.69±3.21         4050.38±469.01           4411.56±2694.04                      2.8\n",
-      "{'alpha': '1.00e+00', 'height': 6.0}   92.70±3.10         4834.19±579.69           4576.90±2756.66                      3.46\n",
-      "{'alpha': '1.00e+00', 'height': 7.0}   92.89±2.63         5183.70±749.16           6532.43±4027.47                      3.76\n",
-      "{'alpha': '1.00e+00', 'height': 8.0}   93.27±2.71         6229.96±608.99           5665.46±3315.87                      4.49\n",
-      "{'alpha': '1.00e+00', 'height': 9.0}   93.44±3.60         6843.20±781.54           6651.11±4423.58                      4.64\n",
-      "{'alpha': '1.00e+00', 'height': 10.0}  93.61±2.94         7592.33±946.06           7119.70±4547.27                      5.17\n",
-      "{'alpha': '1.26e+00', 'height': 0.0}   16.81±0.34         16.87±0.38               17.35±2.97                           0.36\n",
-      "{'alpha': '1.26e+00', 'height': 1.0}   8.87±0.23          9.76±0.37                9.98±2.32                            0.84\n",
-      "{'alpha': '1.26e+00', 'height': 2.0}   13.51±10.10        53.70±85.83              45.77±55.26                          1.36\n",
-      "{'alpha': '1.26e+00', 'height': 3.0}   136.50±104.44      1287.66±1011.68          1825.89±1787.81                      2.07\n",
-      "{'alpha': '1.26e+00', 'height': 4.0}   93.52±13.65        2634.90±433.90           2823.99±1508.58                      2.44\n",
-      "{'alpha': '1.26e+00', 'height': 5.0}   92.34±3.19         3213.22±370.96           3497.85±2134.38                      2.8\n",
-      "{'alpha': '1.26e+00', 'height': 6.0}   92.39±3.08         3834.38±459.50           3631.25±2180.26                      3.46\n",
-      "{'alpha': '1.26e+00', 'height': 7.0}   92.62±2.62         4112.97±593.43           5179.92±3195.62                      3.76\n",
-      "{'alpha': '1.26e+00', 'height': 8.0}   93.02±2.70         4943.36±481.71           4494.50±2626.34                      4.49\n",
-      "{'alpha': '1.26e+00', 'height': 9.0}   93.22±3.58         5430.43±619.21           5278.11±3505.27                      4.64\n",
-      "{'alpha': '1.26e+00', 'height': 10.0}  93.41±2.93         6024.49±750.32           5650.68±3604.50                      5.17\n",
-      "{'alpha': '1.58e+00', 'height': 0.0}   16.82±0.34         16.88±0.38               17.34±2.97                           0.36\n",
-      "{'alpha': '1.58e+00', 'height': 1.0}   9.28±0.24          10.12±0.36               10.35±2.34                           0.84\n",
-      "{'alpha': '1.58e+00', 'height': 2.0}   11.00±3.60         32.59±10.44              33.85±32.34                          1.36\n",
-      "{'alpha': '1.58e+00', 'height': 3.0}   157.26±355.85      1076.17±1289.59          1522.62±2631.35                      2.07\n",
-      "{'alpha': '1.58e+00', 'height': 4.0}   90.10±9.74         2055.20±290.82           2219.31±1188.12                      2.44\n",
-      "{'alpha': '1.58e+00', 'height': 5.0}   91.91±3.17         2548.51±293.07           2772.34±1689.80                      2.8\n",
-      "{'alpha': '1.58e+00', 'height': 6.0}   92.02±3.06         3040.46±364.03           2880.31±1722.43                      3.46\n",
-      "{'alpha': '1.58e+00', 'height': 7.0}   92.29±2.60         3262.68±469.74           4105.83±2534.72                      3.76\n",
-      "{'alpha': '1.58e+00', 'height': 8.0}   92.72±2.69         3921.57±380.64           3564.55±2078.64                      4.49\n",
-      "{'alpha': '1.58e+00', 'height': 9.0}   92.94±3.56         4308.40±490.27           4187.67±2775.82                      4.64\n",
-      "{'alpha': '1.58e+00', 'height': 10.0}  93.16±2.92         4779.27±594.84           4483.95±2855.62                      5.17\n",
-      "{'alpha': '2.00e+00', 'height': 0.0}   16.83±0.34         16.89±0.38               17.34±2.97                           0.36\n",
-      "{'alpha': '2.00e+00', 'height': 1.0}   9.67±0.25          10.47±0.36               10.70±2.38                           0.84\n",
-      "{'alpha': '2.00e+00', 'height': 2.0}   9.85±2.19          27.30±7.33               26.68±19.32                          1.36\n",
-      "{'alpha': '2.00e+00', 'height': 3.0}   76.49±42.38        673.19±559.47            821.58±723.10                        2.07\n",
-      "{'alpha': '2.00e+00', 'height': 4.0}   87.55±6.98         1610.11±201.24           1748.52±936.74                       2.44\n",
-      "{'alpha': '2.00e+00', 'height': 5.0}   91.39±3.14         2020.85±231.21           2196.40±1336.59                      2.8\n",
-      "{'alpha': '2.00e+00', 'height': 6.0}   91.56±3.04         2410.14±288.18           2284.11±1358.80                      3.46\n",
-      "{'alpha': '2.00e+00', 'height': 7.0}   91.88±2.59         2587.56±371.50           3252.97±2009.57                      3.76\n",
-      "{'alpha': '2.00e+00', 'height': 8.0}   92.35±2.68         3110.18±300.38           2826.08±1643.61                      4.49\n",
-      "{'alpha': '2.00e+00', 'height': 9.0}   92.61±3.54         3417.35±387.88           3321.72±2196.37                      4.64\n",
-      "{'alpha': '2.00e+00', 'height': 10.0}  92.84±2.90         3790.35±471.35           3557.39±2260.75                      5.17\n",
-      "{'alpha': '2.51e+00', 'height': 0.0}   16.86±0.34         16.91±0.38               17.34±2.98                           0.36\n",
-      "{'alpha': '2.51e+00', 'height': 1.0}   10.04±0.26         10.81±0.36               11.04±2.42                           0.84\n",
-      "{'alpha': '2.51e+00', 'height': 2.0}   9.53±1.66          24.26±5.57               23.59±14.70                          1.36\n",
-      "{'alpha': '2.51e+00', 'height': 3.0}   64.65±30.33        496.46±371.46            610.18±530.04                        2.07\n",
-      "{'alpha': '2.51e+00', 'height': 4.0}   85.58±5.13         1265.71±143.92           1379.90±738.49                       2.44\n",
-      "{'alpha': '2.51e+00', 'height': 5.0}   90.75±3.10         1602.17±182.08           1739.35±1055.97                      2.8\n",
-      "{'alpha': '2.51e+00', 'height': 6.0}   90.99±3.01         1909.87±227.92           1810.89±1069.99                      3.46\n",
-      "{'alpha': '2.51e+00', 'height': 7.0}   91.39±2.57         2051.64±293.48           2575.90±1592.21                      3.76\n",
-      "{'alpha': '2.51e+00', 'height': 8.0}   91.90±2.67         2465.98±236.67           2239.78±1298.08                      4.49\n",
-      "{'alpha': '2.51e+00', 'height': 9.0}   92.19±3.51         2709.83±306.56           2634.14±1736.07                      4.64\n",
-      "{'alpha': '2.51e+00', 'height': 10.0}  92.46±2.88         3005.09±373.26           2821.66±1788.21                      5.17\n",
-      "{'alpha': '3.16e+00', 'height': 0.0}   16.89±0.34         16.94±0.38               17.35±2.98                           0.36\n",
-      "{'alpha': '3.16e+00', 'height': 1.0}   10.38±0.27         11.12±0.37               11.34±2.46                           0.84\n",
-      "{'alpha': '3.16e+00', 'height': 2.0}   10.36±5.23         23.74±9.36               26.10±33.18                          1.36\n",
-      "{'alpha': '3.16e+00', 'height': 3.0}   56.88±21.97        383.48±263.02            449.98±372.91                        2.07\n",
-      "{'alpha': '3.16e+00', 'height': 4.0}   83.97±3.96         997.84±105.95            1090.21±581.67                       2.44\n",
-      "{'alpha': '3.16e+00', 'height': 5.0}   89.98±3.06         1270.16±143.05           1376.88±832.97                       2.8\n",
-      "{'alpha': '3.16e+00', 'height': 6.0}   90.31±2.98         1512.99±180.04           1435.46±840.63                       3.46\n",
-      "{'alpha': '3.16e+00', 'height': 7.0}   90.78±2.54         1626.41±231.52           2038.59±1260.41                      3.76\n",
-      "{'alpha': '3.16e+00', 'height': 8.0}   91.34±2.65         1954.66±186.11           1774.42±1023.66                      4.49\n",
-      "{'alpha': '3.16e+00', 'height': 9.0}   91.68±3.47         2148.18±241.99           2088.34±1370.41                      4.64\n",
-      "{'alpha': '3.16e+00', 'height': 10.0}  91.98±2.86         2381.65±295.35           2237.57±1412.83                      5.17\n",
-      "{'alpha': '3.98e+00', 'height': 0.0}   16.93±0.34         16.98±0.38               17.36±2.99                           0.36\n",
-      "{'alpha': '3.98e+00', 'height': 1.0}   10.70±0.28         11.41±0.37               11.63±2.50                           0.84\n",
-      "{'alpha': '3.98e+00', 'height': 2.0}   9.48±0.93          20.50±3.00               20.32±8.64                           1.36\n",
-      "{'alpha': '3.98e+00', 'height': 3.0}   51.49±15.77        299.15±180.84            336.42±259.88                        2.07\n",
-      "{'alpha': '3.98e+00', 'height': 4.0}   82.57±3.27         788.88±79.69             862.12±457.37                        2.44\n",
-      "{'alpha': '3.98e+00', 'height': 5.0}   89.07±3.00         1007.14±112.06           1089.69±655.72                       2.8\n",
-      "{'alpha': '3.98e+00', 'height': 6.0}   89.49±2.94         1198.40±141.97           1137.84±658.48                       3.46\n",
-      "{'alpha': '3.98e+00', 'height': 7.0}   90.05±2.51         1289.21±182.33           1612.42±996.51                       3.76\n",
-      "{'alpha': '3.98e+00', 'height': 8.0}   90.67±2.63         1549.00±146.01           1405.22±805.71                       4.49\n",
-      "{'alpha': '3.98e+00', 'height': 9.0}   91.05±3.42         1702.48±190.73           1655.23±1079.91                      4.64\n",
-      "{'alpha': '3.98e+00', 'height': 10.0}  91.40±2.83         1886.86±233.47           1774.02±1114.62                      5.17\n",
-      "{'alpha': '5.01e+00', 'height': 0.0}   16.99±0.34         17.04±0.38               17.38±2.99                           0.36\n",
-      "{'alpha': '5.01e+00', 'height': 1.0}   10.99±0.29         11.69±0.38               11.90±2.53                           0.84\n",
-      "{'alpha': '5.01e+00', 'height': 2.0}   9.70±0.73          19.43±2.10               19.50±6.56                           1.36\n",
-      "{'alpha': '5.01e+00', 'height': 3.0}   47.51±11.06        234.40±120.08            254.16±177.40                        2.07\n",
-      "{'alpha': '5.01e+00', 'height': 4.0}   81.24±2.87         625.67±60.77             682.53±358.65                        2.44\n",
-      "{'alpha': '5.01e+00', 'height': 5.0}   88.01±2.93         799.12±87.44             862.50±514.76                        2.8\n",
-      "{'alpha': '5.01e+00', 'height': 6.0}   88.53±2.89         949.33±111.70            902.18±513.85                        3.46\n",
-      "{'alpha': '5.01e+00', 'height': 7.0}   89.18±2.47         1022.10±143.27           1274.68±786.48                       3.76\n",
-      "{'alpha': '5.01e+00', 'height': 8.0}   89.86±2.60         1227.41±114.22           1112.54±632.63                       4.49\n",
-      "{'alpha': '5.01e+00', 'height': 9.0}   90.30±3.37         1349.01±150.05           1311.77±849.09                       4.64\n",
-      "{'alpha': '5.01e+00', 'height': 10.0}  90.70±2.80         1494.36±184.32           1406.34±877.69                       5.17\n",
-      "{'alpha': '6.31e+00', 'height': 0.0}   17.07±0.34         17.12±0.38               17.41±3.00                           0.36\n",
-      "{'alpha': '6.31e+00', 'height': 1.0}   11.27±0.29         11.95±0.39               12.15±2.55                           0.84\n",
-      "{'alpha': '6.31e+00', 'height': 2.0}   10.05±0.60         18.79±1.46               19.06±5.06                           1.36\n",
-      "{'alpha': '6.31e+00', 'height': 3.0}   44.55±7.52         185.52±76.68             195.09±118.98                        2.07\n",
-      "{'alpha': '6.31e+00', 'height': 4.0}   79.94±2.61         498.27±46.68             541.38±280.04                        2.44\n",
-      "{'alpha': '6.31e+00', 'height': 5.0}   86.79±2.85         635.01±67.88             683.22±402.58                        2.8\n",
-      "{'alpha': '6.31e+00', 'height': 6.0}   87.41±2.82         752.53±87.60             715.94±399.03                        3.46\n",
-      "{'alpha': '6.31e+00', 'height': 7.0}   88.15±2.43         810.85±112.27            1007.40±619.15                       3.76\n",
-      "{'alpha': '6.31e+00', 'height': 8.0}   88.90±2.57         972.76±89.06             880.80±495.21                        4.49\n",
-      "{'alpha': '6.31e+00', 'height': 9.0}   89.41±3.30         1068.94±117.76           1039.67±665.68                       4.64\n",
-      "{'alpha': '6.31e+00', 'height': 10.0}  89.86±2.75         1183.25±145.28           1114.96±689.42                       5.17\n",
-      "{'alpha': '7.94e+00', 'height': 0.0}   17.18±0.33         17.23±0.38               17.47±3.01                           0.36\n",
-      "{'alpha': '7.94e+00', 'height': 1.0}   11.55±0.30         12.21±0.39               12.40±2.57                           0.84\n",
-      "{'alpha': '7.94e+00', 'height': 2.0}   10.53±0.51         18.48±1.04               18.93±4.12                           1.36\n",
-      "{'alpha': '7.94e+00', 'height': 3.0}   42.39±4.96         149.46±47.10             153.16±78.74                         2.07\n",
-      "{'alpha': '7.94e+00', 'height': 4.0}   78.64±2.42         399.16±35.95             430.91±217.30                        2.44\n",
-      "{'alpha': '7.94e+00', 'height': 5.0}   85.43±2.75         506.05±52.35             542.31±313.21                        2.8\n",
-      "{'alpha': '7.94e+00', 'height': 6.0}   86.13±2.75         597.50±68.40             569.22±307.89                        3.46\n",
-      "{'alpha': '7.94e+00', 'height': 7.0}   86.98±2.37         644.20±87.66             796.32±485.66                        3.76\n",
-      "{'alpha': '7.94e+00', 'height': 8.0}   87.79±2.52         771.49±69.17             697.67±386.13                        4.49\n",
-      "{'alpha': '7.94e+00', 'height': 9.0}   88.36±3.21         847.37±92.16             824.42±519.91                        4.64\n",
-      "{'alpha': '7.94e+00', 'height': 10.0}  88.86±2.70         936.99±114.27            884.36±539.77                        5.17\n",
-      "{'alpha': '1.00e+01', 'height': 0.0}   17.33±0.33         17.38±0.38               17.56±3.02                           0.36\n",
-      "{'alpha': '1.00e+01', 'height': 1.0}   11.82±0.31         12.47±0.40               12.66±2.57                           0.84\n",
-      "{'alpha': '1.00e+01', 'height': 2.0}   11.11±0.45         18.44±0.78               19.03±3.63                           1.36\n",
-      "{'alpha': '1.00e+01', 'height': 3.0}   40.93±3.23         123.40±27.88             123.83±51.72                         2.07\n",
-      "{'alpha': '1.00e+01', 'height': 4.0}   77.36±2.25         322.54±27.66             345.07±167.13                        2.44\n",
-      "{'alpha': '1.00e+01', 'height': 5.0}   83.97±2.63         405.32±40.04             432.25±241.90                        2.8\n",
-      "{'alpha': '1.00e+01', 'height': 6.0}   84.73±2.66         475.97±53.08             454.19±235.59                        3.46\n",
-      "{'alpha': '1.00e+01', 'height': 7.0}   85.66±2.31         513.25±68.14             630.15±379.00                        3.76\n",
-      "{'alpha': '1.00e+01', 'height': 8.0}   86.52±2.47         612.86±53.49             553.40±299.57                        4.49\n",
-      "{'alpha': '1.00e+01', 'height': 9.0}   87.15±3.11         672.50±71.85             654.57±404.04                        4.64\n",
-      "{'alpha': '1.00e+01', 'height': 10.0}  87.71±2.64         742.44±89.61             702.26±420.77                        5.17\n",
-      "{'alpha': '1.26e+01', 'height': 0.0}   17.54±0.33         17.58±0.37               17.68±3.03                           0.36\n",
-      "{'alpha': '1.26e+01', 'height': 1.0}   12.11±0.31         12.74±0.41               12.93±2.57                           0.84\n",
-      "{'alpha': '1.26e+01', 'height': 2.0}   11.79±0.41         18.61±0.65               19.33±3.46                           1.36\n",
-      "{'alpha': '1.26e+01', 'height': 3.0}   40.12±2.21         104.95±15.95             103.80±34.12                         2.07\n",
-      "{'alpha': '1.26e+01', 'height': 4.0}   76.19±2.08         263.95±21.20             279.11±126.97                        2.44\n",
-      "{'alpha': '1.26e+01', 'height': 5.0}   82.49±2.50         327.33±30.30             347.09±184.90                        2.8\n",
-      "{'alpha': '1.26e+01', 'height': 6.0}   83.25±2.55         381.38±40.85             364.69±178.29                        3.46\n",
-      "{'alpha': '1.26e+01', 'height': 7.0}   84.23±2.24         410.95±52.65             499.97±293.62                        3.76\n",
-      "{'alpha': '1.26e+01', 'height': 8.0}   85.12±2.41         488.41±41.17             440.33±230.94                        4.49\n",
-      "{'alpha': '1.26e+01', 'height': 9.0}   85.79±2.99         534.99±55.75             521.05±311.93                        4.64\n",
-      "{'alpha': '1.26e+01', 'height': 10.0}  86.40±2.57         589.26±69.99             558.96±326.09                        5.17\n",
-      "{'alpha': '1.58e+01', 'height': 0.0}   17.80±0.33         17.84±0.37               17.85±3.05                           0.36\n",
-      "{'alpha': '1.58e+01', 'height': 1.0}   12.43±0.31         13.05±0.41               13.24±2.56                           0.84\n",
-      "{'alpha': '1.58e+01', 'height': 2.0}   12.55±0.38         18.94±0.58               19.79±3.51                           1.36\n",
-      "{'alpha': '1.58e+01', 'height': 3.0}   39.96±1.74         92.26±8.91               90.66±23.13                          2.07\n",
-      "{'alpha': '1.58e+01', 'height': 4.0}   75.23±1.92         219.83±16.15             229.30±94.91                         2.44\n",
-      "{'alpha': '1.58e+01', 'height': 5.0}   81.10±2.33         267.76±22.63             282.13±139.31                        2.8\n",
-      "{'alpha': '1.58e+01', 'height': 6.0}   81.79±2.43         308.54±31.08             295.85±132.99                        3.46\n",
-      "{'alpha': '1.58e+01', 'height': 7.0}   82.75±2.15         331.73±40.37             398.69±225.15                        3.76\n",
-      "{'alpha': '1.58e+01', 'height': 8.0}   83.63±2.33         391.42±31.52             352.40±176.60                        4.49\n",
-      "{'alpha': '1.58e+01', 'height': 9.0}   84.32±2.84         427.47±42.98             416.70±238.73                        4.64\n",
-      "{'alpha': '1.58e+01', 'height': 10.0}  84.95±2.49         469.25±54.35             446.79±250.71                        5.17\n",
-      "{'alpha': '2.00e+01', 'height': 0.0}   18.14±0.32         18.18±0.36               18.08±3.06                           0.36\n",
-      "{'alpha': '2.00e+01', 'height': 1.0}   12.79±0.31         13.41±0.41               13.59±2.55                           0.84\n",
-      "{'alpha': '2.00e+01', 'height': 2.0}   13.40±0.36         19.40±0.54               20.37±3.67                           1.36\n",
-      "{'alpha': '2.00e+01', 'height': 3.0}   40.46±1.54         83.97±5.08               82.57±16.64                          2.07\n",
-      "{'alpha': '2.00e+01', 'height': 4.0}   74.68±1.74         187.34±12.21             192.64±69.47                         2.44\n",
-      "{'alpha': '2.00e+01', 'height': 5.0}   79.96±2.15         223.11±16.63             233.53±102.90                        2.8\n",
-      "{'alpha': '2.00e+01', 'height': 6.0}   80.46±2.28         253.32±23.30             243.80±97.37                         3.46\n",
-      "{'alpha': '2.00e+01', 'height': 7.0}   81.34±2.05         271.18±30.63             320.72±170.22                        3.76\n",
-      "{'alpha': '2.00e+01', 'height': 8.0}   82.14±2.23         316.59±23.99             284.87±133.67                        4.49\n",
-      "{'alpha': '2.00e+01', 'height': 9.0}   82.80±2.67         344.11±32.84             335.87±180.58                        4.64\n",
-      "{'alpha': '2.00e+01', 'height': 10.0}  83.43±2.39         375.94±41.86             359.68±190.69                        5.17\n",
-      "{'alpha': '2.51e+01', 'height': 0.0}   18.57±0.32         18.60±0.36               18.38±3.07                           0.36\n",
-      "{'alpha': '2.51e+01', 'height': 1.0}   13.22±0.31         13.83±0.40               14.02±2.55                           0.84\n",
-      "{'alpha': '2.51e+01', 'height': 2.0}   14.34±0.33         19.98±0.52               21.06±3.90                           1.36\n",
-      "{'alpha': '2.51e+01', 'height': 3.0}   41.66±1.40         79.04±3.28               78.13±13.05                          2.07\n",
-      "{'alpha': '2.51e+01', 'height': 4.0}   74.71±1.56         164.15±9.12              166.63±49.53                         2.44\n",
-      "{'alpha': '2.51e+01', 'height': 5.0}   79.26±1.94         190.52±11.99             198.13±74.03                         2.8\n",
-      "{'alpha': '2.51e+01', 'height': 6.0}   79.45±2.12         212.35±17.12             205.39±69.66                         3.46\n",
-      "{'alpha': '2.51e+01', 'height': 7.0}   80.13±1.94         225.73±22.93             261.54±126.25                        3.76\n",
-      "{'alpha': '2.51e+01', 'height': 8.0}   80.78±2.12         259.70±18.11             233.98±99.89                         4.49\n",
-      "{'alpha': '2.51e+01', 'height': 9.0}   81.35±2.48         280.29±24.78             274.11±134.48                        4.64\n",
-      "{'alpha': '2.51e+01', 'height': 10.0}  81.92±2.28         304.20±31.87             292.80±142.98                        5.17\n",
-      "{'alpha': '3.16e+01', 'height': 0.0}   19.09±0.32         19.12±0.35               18.76±3.09                           0.36\n",
-      "{'alpha': '3.16e+01', 'height': 1.0}   13.73±0.30         14.34±0.40               14.53±2.58                           0.84\n",
-      "{'alpha': '3.16e+01', 'height': 2.0}   15.38±0.31         20.68±0.50               21.86±4.19                           1.36\n",
-      "{'alpha': '3.16e+01', 'height': 3.0}   43.61±1.24         76.67±2.49               76.31±11.21                          2.07\n",
-      "{'alpha': '3.16e+01', 'height': 4.0}   80.30±14.24        148.43±6.91              149.33±34.31                         2.44\n",
-      "{'alpha': '3.16e+01', 'height': 5.0}   79.23±1.72         167.56±8.45              173.20±51.51                         2.8\n",
-      "{'alpha': '3.16e+01', 'height': 6.0}   78.97±1.94         182.82±12.24             178.00±48.52                         3.46\n",
-      "{'alpha': '3.16e+01', 'height': 7.0}   79.33±1.82         192.49±16.84             217.50±91.31                         3.76\n",
-      "{'alpha': '3.16e+01', 'height': 8.0}   79.71±1.98         217.32±13.52             196.67±73.47                         4.49\n",
-      "{'alpha': '3.16e+01', 'height': 9.0}   80.10±2.27         232.29±18.38             227.84±98.06                         4.64\n",
-      "{'alpha': '3.16e+01', 'height': 10.0}  80.54±2.15         249.95±23.87             242.27±105.24                        5.17\n",
-      "{'alpha': '3.98e+01', 'height': 0.0}   19.72±0.31         19.73±0.34               19.22±3.13                           0.36\n",
-      "{'alpha': '3.98e+01', 'height': 1.0}   14.35±0.29         14.95±0.38               15.15±2.64                           0.84\n",
-      "{'alpha': '3.98e+01', 'height': 2.0}   16.53±0.30         21.49±0.50               22.77±4.51                           1.36\n",
-      "{'alpha': '3.98e+01', 'height': 3.0}   46.33±1.07         76.23±2.02               76.33±10.32                          2.07\n",
-      "{'alpha': '3.98e+01', 'height': 4.0}   80.48±8.03         138.29±5.15              137.97±23.05                         2.44\n",
-      "{'alpha': '3.98e+01', 'height': 5.0}   80.82±2.98         152.15±5.80              156.40±34.49                         2.8\n",
-      "{'alpha': '3.98e+01', 'height': 6.0}   79.61±2.59         162.33±8.45              159.32±32.94                         3.46\n",
-      "{'alpha': '3.98e+01', 'height': 7.0}   79.14±1.69         169.01±12.06             185.60±63.98                         3.76\n",
-      "{'alpha': '3.98e+01', 'height': 8.0}   79.15±1.82         186.61±9.93              170.37±53.04                         4.49\n",
-      "{'alpha': '3.98e+01', 'height': 9.0}   79.26±2.04         197.08±13.33             194.09±69.52                         4.64\n",
-      "{'alpha': '3.98e+01', 'height': 10.0}  79.50±2.02         209.85±17.51             204.94±75.70                         5.17\n",
-      "{'alpha': '5.01e+01', 'height': 0.0}   20.46±0.31         20.46±0.33               19.79±3.18                           0.36\n",
-      "{'alpha': '5.01e+01', 'height': 1.0}   15.09±0.27         15.68±0.36               15.88±2.76                           0.84\n",
-      "{'alpha': '5.01e+01', 'height': 2.0}   17.81±0.28         22.43±0.50               23.80±4.85                           1.36\n",
-      "{'alpha': '5.01e+01', 'height': 3.0}   50.44±1.59         78.25±4.26               78.30±10.37                          2.07\n",
-      "{'alpha': '5.01e+01', 'height': 4.0}   91.96±38.47        135.38±18.53             131.56±15.55                         2.44\n",
-      "{'alpha': '5.01e+01', 'height': 5.0}   90.40±17.17        142.42±3.88              145.68±22.34                         2.8\n",
-      "{'alpha': '5.01e+01', 'height': 6.0}   81.84±4.22         148.80±5.58              147.34±22.09                         3.46\n",
-      "{'alpha': '5.01e+01', 'height': 7.0}   91.10±35.41        153.18±8.34              163.31±43.24                         3.76\n",
-      "{'alpha': '5.01e+01', 'height': 8.0}   79.30±1.63         165.15±7.13              152.74±37.56                         4.49\n",
-      "{'alpha': '5.01e+01', 'height': 9.0}   79.04±1.80         172.09±9.40              170.36±47.55                         4.64\n",
-      "{'alpha': '5.01e+01', 'height': 10.0}  78.98±1.87         181.10±12.50             178.19±53.04                         5.17\n",
-      "{'alpha': '6.31e+01', 'height': 0.0}   21.33±0.30         21.30±0.33               20.46±3.26                           0.36\n",
-      "{'alpha': '6.31e+01', 'height': 1.0}   15.96±0.25         16.52±0.34               16.73±2.94                           0.84\n",
-      "{'alpha': '6.31e+01', 'height': 2.0}   19.24±0.27         23.51±0.50               24.96±5.20                           1.36\n",
-      "{'alpha': '6.31e+01', 'height': 3.0}   78.43±40.71        91.95±17.39              116.54±148.94                        2.07\n",
-      "{'alpha': '6.31e+01', 'height': 4.0}   106.61±35.60       129.17±3.43              130.85±16.10                         2.44\n",
-      "{'alpha': '6.31e+01', 'height': 5.0}   88.50±5.62         136.82±2.60              139.36±14.58                         2.8\n",
-      "{'alpha': '6.31e+01', 'height': 6.0}   220.59±206.13      140.44±3.49              140.26±15.23                         3.46\n",
-      "{'alpha': '6.31e+01', 'height': 7.0}   84.18±7.15         143.15±5.52              148.50±28.28                         3.76\n",
-      "{'alpha': '6.31e+01', 'height': 8.0}   97.51±64.45        150.87±4.97              141.67±26.21                         4.49\n",
-      "{'alpha': '6.31e+01', 'height': 9.0}   81.80±5.96         155.12±6.42              154.41±31.25                         4.64\n",
-      "{'alpha': '6.31e+01', 'height': 10.0}  79.21±1.71         161.29±8.63              159.79±36.26                         5.17\n",
-      "{'alpha': '7.94e+01', 'height': 0.0}   22.30±0.29         22.25±0.32               21.23±3.38                           0.36\n",
-      "{'alpha': '7.94e+01', 'height': 1.0}   16.96±0.23         17.49±0.33               17.70±3.18                           0.84\n",
-      "{'alpha': '7.94e+01', 'height': 2.0}   20.82±0.27         24.75±0.52               26.27±5.56                           1.36\n",
-      "{'alpha': '7.94e+01', 'height': 3.0}   99.59±176.99       95.37±58.38              91.73±43.12                          2.07\n",
-      "{'alpha': '7.94e+01', 'height': 4.0}   90.49±2.54         127.88±1.90              127.56±9.96                          2.44\n",
-      "{'alpha': '7.94e+01', 'height': 5.0}   94.09±5.71         134.04±1.85              136.05±10.60                         2.8\n",
-      "{'alpha': '7.94e+01', 'height': 6.0}   94.02±15.17        135.76±2.11              136.56±11.47                         3.46\n",
-      "{'alpha': '7.94e+01', 'height': 7.0}   87.74±6.40         137.33±3.49              139.36±18.45                         3.76\n",
-      "{'alpha': '7.94e+01', 'height': 8.0}   82.97±1.51         141.96±3.36              135.29±18.38                         4.49\n",
-      "{'alpha': '7.94e+01', 'height': 9.0}   82.47±2.75         144.25±4.26              144.31±20.09                         4.64\n",
-      "{'alpha': '7.94e+01', 'height': 10.0}  84.55±15.38        148.31±5.72              147.78±24.62                         5.17\n",
-      "{'alpha': '1.00e+02', 'height': 0.0}   23.39±0.28         23.30±0.32               22.11±3.53                           0.36\n",
-      "{'alpha': '1.00e+02', 'height': 1.0}   18.09±0.22         18.57±0.31               18.77±3.49                           0.84\n",
-      "{'alpha': '1.00e+02', 'height': 2.0}   22.59±0.29         26.17±0.53               27.75±5.90                           1.36\n",
-      "{'alpha': '1.00e+02', 'height': 3.0}   79.09±42.07        90.37±17.21              95.78±43.47                          2.07\n",
-      "{'alpha': '1.00e+02', 'height': 4.0}   94.07±1.21         128.24±1.51              128.04±9.68                          2.44\n",
-      "{'alpha': '1.00e+02', 'height': 5.0}   94.28±2.04         133.06±1.48              134.71±9.20                          2.8\n",
-      "{'alpha': '1.00e+02', 'height': 6.0}   92.69±3.44         133.56±1.35              135.04±9.73                          3.46\n",
-      "{'alpha': '1.00e+02', 'height': 7.0}   123.03±45.60       134.39±2.15              134.30±13.01                         3.76\n",
-      "{'alpha': '1.00e+02', 'height': 8.0}   86.03±1.21         136.90±2.24              132.06±13.47                         4.49\n",
-      "{'alpha': '1.00e+02', 'height': 9.0}   88.14±6.91         137.84±2.80              138.45±13.68                         4.64\n",
-      "{'alpha': '1.00e+02', 'height': 10.0}  96.95±37.44        140.36±3.63              140.49±17.49                         5.17\n"
+      "best_params_in:  [{'alpha': 0.1}]\n",
+      "\n",
+      "best_val_perf:  7.408897274451954\n",
+      "best_val_std:  0.7280307805221202\n",
+      "final_performance:  7.6770690731806726\n",
+      "final_confidence:  2.3181322643015494\n",
+      "train_performance:  5.909130825932086\n",
+      "train_std:  0.24106718316563544\n",
+      "\n",
+      "time to calculate gram matrix with different hyperpapams: 2.62±1.45\n",
+      "time to calculate best gram matrix:  0.7666378021240234 s\n",
+      "\n",
+      "params                                 train_perf           valid_perf              test_perf                   gram_matrix_time\n",
+      "-------------------------------------  -------------------  ----------------------  ------------------------  ------------------\n",
+      "{'alpha': '1.00e-02', 'height': 0.0}   16.86±0.30           16.98±0.32              16.87±2.47                              0.34\n",
+      "{'alpha': '1.00e-02', 'height': 1.0}   5.89±0.25            7.64±0.81               8.03±2.47                               0.77\n",
+      "{'alpha': '1.00e-02', 'height': 2.0}   1850.53±8495.35      7413.48±27850.20        49953.89±265798.39                      1.21\n",
+      "{'alpha': '1.00e-02', 'height': 3.0}   158730.24±717452.81  1437804.88±4133498.55   7667000.67±30318904.22                  1.91\n",
+      "{'alpha': '1.00e-02', 'height': 4.0}   16653.08±46197.89    7904151.09±13562096.05  12222217.46±42270377.03                 2.16\n",
+      "{'alpha': '1.00e-02', 'height': 5.0}   94.41±3.53           413264.50±53384.79      368929.20±230070.59                     2.84\n",
+      "{'alpha': '1.00e-02', 'height': 6.0}   93.57±3.14           486696.80±61273.57      466831.43±311986.09                     3.2\n",
+      "{'alpha': '1.00e-02', 'height': 7.0}   94.69±3.31           559652.14±70435.33      475694.36±284948.70                     3.85\n",
+      "{'alpha': '1.00e-02', 'height': 8.0}   93.48±4.49           611340.81±68548.76      700494.13±365043.03                     3.73\n",
+      "{'alpha': '1.00e-02', 'height': 9.0}   94.71±3.79           690040.31±78333.14      654124.04±481253.77                     4.21\n",
+      "{'alpha': '1.00e-02', 'height': 10.0}  94.38±3.55           744311.87±94286.93      693669.90±420716.47                     4.64\n",
+      "{'alpha': '1.26e-02', 'height': 0.0}   16.86±0.30           16.98±0.32              16.87±2.47                              0.34\n",
+      "{'alpha': '1.26e-02', 'height': 1.0}   5.88±0.25            7.63±0.81               8.01±2.47                               0.77\n",
+      "{'alpha': '1.26e-02', 'height': 2.0}   457.04±894.89        2764.93±4001.17         3439.97±8149.06                         1.21\n",
+      "{'alpha': '1.26e-02', 'height': 3.0}   16399.32±44893.28    486473.91±878785.82     2532452.26±12164366.72                  1.91\n",
+      "{'alpha': '1.26e-02', 'height': 4.0}   10055.95±20739.19    4953114.74±7792697.43   10859850.17±34085132.33                 2.16\n",
+      "{'alpha': '1.26e-02', 'height': 5.0}   94.41±3.53           328261.40±42402.42      293043.28±182747.20                     2.84\n",
+      "{'alpha': '1.26e-02', 'height': 6.0}   93.57±3.14           386590.29±48669.86      370811.67±247811.84                     3.2\n",
+      "{'alpha': '1.26e-02', 'height': 7.0}   94.69±3.31           444541.08±55947.74      377849.83±226338.89                     3.85\n",
+      "{'alpha': '1.26e-02', 'height': 8.0}   93.47±4.49           485598.83±54448.67      556413.39±289959.99                     3.73\n",
+      "{'alpha': '1.26e-02', 'height': 9.0}   94.71±3.79           548112.48±62221.03      519585.83±382262.80                     4.21\n",
+      "{'alpha': '1.26e-02', 'height': 10.0}  94.38±3.55           591221.82±74893.73      550994.12±334182.43                     4.64\n",
+      "{'alpha': '1.58e-02', 'height': 0.0}   16.86±0.30           16.98±0.32              16.87±2.47                              0.34\n",
+      "{'alpha': '1.58e-02', 'height': 1.0}   5.88±0.25            7.61±0.81               7.99±2.46                               0.77\n",
+      "{'alpha': '1.58e-02', 'height': 2.0}   359.40±684.20        2142.02±3083.64         4610.21±16154.28                        1.21\n",
+      "{'alpha': '1.58e-02', 'height': 3.0}   22326.13±48176.67    437770.33±670209.83     20347881.66±108491010.11                1.91\n",
+      "{'alpha': '1.58e-02', 'height': 4.0}   12497.56±41451.95    3028725.85±4555456.36   54058567.27±275562982.64                2.16\n",
+      "{'alpha': '1.58e-02', 'height': 5.0}   94.40±3.53           260741.05±33678.82      232764.95±145156.90                     2.84\n",
+      "{'alpha': '1.58e-02', 'height': 6.0}   93.56±3.14           307072.88±38658.38      294540.47±196836.41                     3.2\n",
+      "{'alpha': '1.58e-02', 'height': 7.0}   94.68±3.31           353105.11±44439.84      300129.16±179783.46                     3.85\n",
+      "{'alpha': '1.58e-02', 'height': 8.0}   93.47±4.49           385718.42±43248.57      441965.99±230319.41                     3.73\n",
+      "{'alpha': '1.58e-02', 'height': 9.0}   94.71±3.79           435375.20±49422.73      412718.34±303631.48                     4.21\n",
+      "{'alpha': '1.58e-02', 'height': 10.0}  94.38±3.55           469618.08±59489.16      437662.73±265446.00                     4.64\n",
+      "{'alpha': '2.00e-02', 'height': 0.0}   16.86±0.30           16.98±0.32              16.87±2.47                              0.34\n",
+      "{'alpha': '2.00e-02', 'height': 1.0}   5.87±0.25            7.59±0.80               7.96±2.45                               0.77\n",
+      "{'alpha': '2.00e-02', 'height': 2.0}   1180.92±5490.13      2807.18±7564.94         3211.03±8110.46                         1.21\n",
+      "{'alpha': '2.00e-02', 'height': 3.0}   19476.61±42072.93    500334.14±1350251.05    1143078.49±4131816.59                   1.91\n",
+      "{'alpha': '2.00e-02', 'height': 4.0}   4176.04±6369.35      1976787.50±2773660.48   4584635.41±14409870.89                  2.16\n",
+      "{'alpha': '2.00e-02', 'height': 5.0}   94.39±3.53           207107.73±26749.42      184884.17±115297.86                     2.84\n",
+      "{'alpha': '2.00e-02', 'height': 6.0}   93.56±3.14           243909.95±30705.97      233956.10±156345.19                     3.2\n",
+      "{'alpha': '2.00e-02', 'height': 7.0}   94.68±3.31           280474.95±35298.79      238393.44±142803.17                     3.85\n",
+      "{'alpha': '2.00e-02', 'height': 8.0}   93.47±4.49           306380.60±34352.02      351057.19±182945.21                     3.73\n",
+      "{'alpha': '2.00e-02', 'height': 9.0}   94.70±3.79           345824.80±39256.67      327830.47±241172.40                     4.21\n",
+      "{'alpha': '2.00e-02', 'height': 10.0}  94.38±3.55           373024.79±47252.87      347640.41±210846.71                     4.64\n",
+      "{'alpha': '2.51e-02', 'height': 0.0}   16.86±0.30           16.98±0.32              16.87±2.47                              0.34\n",
+      "{'alpha': '2.51e-02', 'height': 1.0}   5.87±0.25            7.57±0.80               7.93±2.44                               0.77\n",
+      "{'alpha': '2.51e-02', 'height': 2.0}   121.83±158.01        858.18±574.96           911.94±1169.07                          1.21\n",
+      "{'alpha': '2.51e-02', 'height': 3.0}   11751.37±18519.69    494373.74±1338223.62    702338.74±2004156.41                    1.91\n",
+      "{'alpha': '2.51e-02', 'height': 4.0}   4819.54±13751.61     1513719.19±2711713.85   1886618.16±5353975.45                   2.16\n",
+      "{'alpha': '2.51e-02', 'height': 5.0}   94.39±3.53           164505.27±21245.20      146851.12±91579.98                      2.84\n",
+      "{'alpha': '2.51e-02', 'height': 6.0}   93.55±3.14           193737.86±24389.15      185832.24±124181.87                     3.2\n",
+      "{'alpha': '2.51e-02', 'height': 7.0}   94.67±3.30           222782.76±28037.79      189355.02±113428.68                     3.85\n",
+      "{'alpha': '2.51e-02', 'height': 8.0}   93.46±4.49           243360.33±27285.24      278845.76±145314.55                     3.73\n",
+      "{'alpha': '2.51e-02', 'height': 9.0}   94.70±3.79           274692.39±31181.49      260401.64±191559.40                     4.21\n",
+      "{'alpha': '2.51e-02', 'height': 10.0}  94.37±3.55           296298.02±37533.24      276133.14±167476.95                     4.64\n",
+      "{'alpha': '3.16e-02', 'height': 0.0}   16.86±0.30           16.98±0.32              16.87±2.47                              0.34\n",
+      "{'alpha': '3.16e-02', 'height': 1.0}   5.86±0.25            7.54±0.79               7.90±2.43                               0.77\n",
+      "{'alpha': '3.16e-02', 'height': 2.0}   119.76±131.64        1144.70±1075.34         1217.35±2791.34                         1.21\n",
+      "{'alpha': '3.16e-02', 'height': 3.0}   23870.45±49916.46    686824.04±1699826.57    1269093.59±4089024.38                   1.91\n",
+      "{'alpha': '3.16e-02', 'height': 4.0}   1928.81±2359.42      727382.03±998246.18     1121543.70±3310129.29                   2.16\n",
+      "{'alpha': '3.16e-02', 'height': 5.0}   94.38±3.53           130664.94±16873.05      116640.41±72740.19                      2.84\n",
+      "{'alpha': '3.16e-02', 'height': 6.0}   93.54±3.14           153884.75±19371.53      147606.09±98633.64                      3.2\n",
+      "{'alpha': '3.16e-02', 'height': 7.0}   94.67±3.30           176956.23±22270.18      150402.42±90095.69                      3.85\n",
+      "{'alpha': '3.16e-02', 'height': 8.0}   93.45±4.49           193301.55±21671.89      221486.20±115423.45                     3.73\n",
+      "{'alpha': '3.16e-02', 'height': 9.0}   94.69±3.79           218189.91±24767.14      206841.02±152150.38                     4.21\n",
+      "{'alpha': '3.16e-02', 'height': 10.0}  94.37±3.55           235351.78±29812.67      219332.90±133027.13                     4.64\n",
+      "{'alpha': '3.98e-02', 'height': 0.0}   16.86±0.30           16.98±0.32              16.87±2.47                              0.34\n",
+      "{'alpha': '3.98e-02', 'height': 1.0}   5.85±0.25            7.51±0.78               7.86±2.42                               0.77\n",
+      "{'alpha': '3.98e-02', 'height': 2.0}   79.49±67.45          803.01±819.16           690.36±815.07                           1.21\n",
+      "{'alpha': '3.98e-02', 'height': 3.0}   74400.21±351437.51   982172.51±3670953.64    677551.00±1839635.51                    1.91\n",
+      "{'alpha': '3.98e-02', 'height': 4.0}   1377.61±1529.42      453881.11±607348.87     708319.75±2069204.34                    2.16\n",
+      "{'alpha': '3.98e-02', 'height': 5.0}   94.36±3.53           103784.62±13400.12      92643.19±57775.22                       2.84\n",
+      "{'alpha': '3.98e-02', 'height': 6.0}   93.53±3.14           122228.31±15385.88      117242.00±78339.96                      3.2\n",
+      "{'alpha': '3.98e-02', 'height': 7.0}   94.66±3.30           140554.93±17688.80      119461.27±71561.64                      3.85\n",
+      "{'alpha': '3.98e-02', 'height': 8.0}   93.45±4.49           153538.46±17213.06      175923.88±91680.10                      3.73\n",
+      "{'alpha': '3.98e-02', 'height': 9.0}   94.68±3.79           173308.40±19672.05      164296.31±120846.69                     4.21\n",
+      "{'alpha': '3.98e-02', 'height': 10.0}  94.36±3.55           186940.47±23680.00      174214.87±105662.66                     4.64\n",
+      "{'alpha': '5.01e-02', 'height': 0.0}   16.86±0.30           16.98±0.32              16.87±2.47                              0.34\n",
+      "{'alpha': '5.01e-02', 'height': 1.0}   5.85±0.25            7.48±0.77               7.81±2.40                               0.77\n",
+      "{'alpha': '5.01e-02', 'height': 2.0}   175.72±407.99        1367.95±2528.49         1554.43±3674.17                         1.21\n",
+      "{'alpha': '5.01e-02', 'height': 3.0}   10213.37±13634.83    184237.07±258652.98     250319.51±461469.15                     1.91\n",
+      "{'alpha': '5.01e-02', 'height': 4.0}   1044.38±1092.46      291295.25±374352.33     453376.67±1297552.43                    2.16\n",
+      "{'alpha': '5.01e-02', 'height': 5.0}   94.35±3.53           82432.83±10641.48       73581.54±45888.11                       2.84\n",
+      "{'alpha': '5.01e-02', 'height': 6.0}   93.52±3.13           97082.71±12219.97       93122.95±62220.11                       3.2\n",
+      "{'alpha': '5.01e-02', 'height': 7.0}   94.65±3.30           111640.35±14049.68      94883.86±56839.51                       3.85\n",
+      "{'alpha': '5.01e-02', 'height': 8.0}   93.44±4.49           121953.52±13671.28      139732.44±72820.09                      3.73\n",
+      "{'alpha': '5.01e-02', 'height': 9.0}   94.68±3.79           137657.75±15624.87      130501.86±95981.29                      4.21\n",
+      "{'alpha': '5.01e-02', 'height': 10.0}  94.35±3.55           148486.00±18808.65      138376.36±83926.29                      4.64\n",
+      "{'alpha': '6.31e-02', 'height': 0.0}   16.86±0.30           16.98±0.33              16.87±2.47                              0.34\n",
+      "{'alpha': '6.31e-02', 'height': 1.0}   5.86±0.25            7.45±0.76               7.76±2.37                               0.77\n",
+      "{'alpha': '6.31e-02', 'height': 2.0}   110.93±213.95        831.64±1083.91          596.38±746.01                           1.21\n",
+      "{'alpha': '6.31e-02', 'height': 3.0}   6282.14±8477.48      116882.78±167776.26     228186.40±612608.49                     1.91\n",
+      "{'alpha': '6.31e-02', 'height': 4.0}   813.63±812.77        190407.96±231916.14     293339.87±814604.18                     2.16\n",
+      "{'alpha': '6.31e-02', 'height': 5.0}   94.33±3.53           65472.51±8450.21        58440.34±36445.85                       2.84\n",
+      "{'alpha': '6.31e-02', 'height': 6.0}   93.51±3.13           77108.86±9705.20        73964.51±49415.66                       3.2\n",
+      "{'alpha': '6.31e-02', 'height': 7.0}   94.63±3.30           88672.70±11159.03       75361.33±45145.31                       3.85\n",
+      "{'alpha': '6.31e-02', 'height': 8.0}   93.42±4.49           96864.71±10857.94       110984.57±57839.05                      3.73\n",
+      "{'alpha': '6.31e-02', 'height': 9.0}   94.66±3.79           109339.44±12410.08      103657.97±76230.00                      4.21\n",
+      "{'alpha': '6.31e-02', 'height': 10.0}  94.34±3.55           117940.54±14939.19      109908.82±66660.47                      4.64\n",
+      "{'alpha': '7.94e-02', 'height': 0.0}   16.86±0.30           16.99±0.33              16.87±2.47                              0.34\n",
+      "{'alpha': '7.94e-02', 'height': 1.0}   5.88±0.24            7.42±0.75               7.72±2.35                               0.77\n",
+      "{'alpha': '7.94e-02', 'height': 2.0}   63.80±83.80          475.48±401.58           427.51±497.69                           1.21\n",
+      "{'alpha': '7.94e-02', 'height': 3.0}   3925.00±3974.10      75713.01±97197.23       122070.67±312003.20                     1.91\n",
+      "{'alpha': '7.94e-02', 'height': 4.0}   646.78±617.83        126949.82±143939.78     192176.69±511584.55                     2.16\n",
+      "{'alpha': '7.94e-02', 'height': 5.0}   94.31±3.53           52000.47±6709.63        46413.27±28945.58                       2.84\n",
+      "{'alpha': '7.94e-02', 'height': 6.0}   93.48±3.13           61243.08±7707.64        58746.44±39244.72                       3.2\n",
+      "{'alpha': '7.94e-02', 'height': 7.0}   94.61±3.30           70428.85±8862.90        59854.05±35856.28                       3.85\n",
+      "{'alpha': '7.94e-02', 'height': 8.0}   93.41±4.49           76935.98±8623.23        88149.34±45939.18                       3.73\n",
+      "{'alpha': '7.94e-02', 'height': 9.0}   94.65±3.79           86845.42±9856.49        82335.12±60540.99                       4.21\n",
+      "{'alpha': '7.94e-02', 'height': 10.0}  94.33±3.55           93677.42±11865.57       87296.25±52945.75                       4.64\n",
+      "{'alpha': '1.00e-01', 'height': 0.0}   16.87±0.30           16.99±0.33              16.87±2.47                              0.34\n",
+      "{'alpha': '1.00e-01', 'height': 1.0}   5.91±0.24            7.41±0.73               7.68±2.32                               0.77\n",
+      "{'alpha': '1.00e-01', 'height': 2.0}   126.94±278.94        693.99±922.66           889.86±1863.54                          1.21\n",
+      "{'alpha': '1.00e-01', 'height': 3.0}   3929.85±4800.81      64825.58±88308.57       191137.08±526650.31                     1.91\n",
+      "{'alpha': '1.00e-01', 'height': 4.0}   567.78±513.52        123813.55±220137.10     132054.41±320465.37                     2.16\n",
+      "{'alpha': '1.00e-01', 'height': 5.0}   94.28±3.53           41299.26±5327.03        36859.86±22987.91                       2.84\n",
+      "{'alpha': '1.00e-01', 'height': 6.0}   93.46±3.13           48640.46±6120.93        46658.31±31165.65                       3.2\n",
+      "{'alpha': '1.00e-01', 'height': 7.0}   94.59±3.30           55937.26±7039.02        47536.19±28477.74                       3.85\n",
+      "{'alpha': '1.00e-01', 'height': 8.0}   93.39±4.49           61106.03±6848.13        70010.68±36486.78                       3.73\n",
+      "{'alpha': '1.00e-01', 'height': 9.0}   94.63±3.79           68977.79±7828.09        65397.79±48078.77                       4.21\n",
+      "{'alpha': '1.00e-01', 'height': 10.0}  94.31±3.55           74404.55±9424.11        69334.47±42051.75                       4.64\n",
+      "{'alpha': '1.26e-01', 'height': 0.0}   16.87±0.30           16.99±0.33              16.87±2.47                              0.34\n",
+      "{'alpha': '1.26e-01', 'height': 1.0}   5.97±0.24            7.41±0.71               7.65±2.28                               0.77\n",
+      "{'alpha': '1.26e-01', 'height': 2.0}   71.34±76.07          654.66±789.97           792.38±1869.37                          1.21\n",
+      "{'alpha': '1.26e-01', 'height': 3.0}   2292.71±3314.04      74814.93±244698.18      52157.76±94110.72                       1.91\n",
+      "{'alpha': '1.26e-01', 'height': 4.0}   464.07±366.36        62269.14±55659.20       92898.49±203852.65                      2.16\n",
+      "{'alpha': '1.26e-01', 'height': 5.0}   94.24±3.52           32799.01±4228.80        29271.34±18255.55                       2.84\n",
+      "{'alpha': '1.26e-01', 'height': 6.0}   93.43±3.13           38629.86±4860.56        37056.39±24748.22                       3.2\n",
+      "{'alpha': '1.26e-01', 'height': 7.0}   94.56±3.30           44426.20±5590.26        37751.79±22616.75                       3.85\n",
+      "{'alpha': '1.26e-01', 'height': 8.0}   93.36±4.49           48531.87±5438.13        55602.64±28978.46                       3.73\n",
+      "{'alpha': '1.26e-01', 'height': 9.0}   94.61±3.79           54785.05±6216.88        51943.99±38179.67                       4.21\n",
+      "{'alpha': '1.26e-01', 'height': 10.0}  94.29±3.54           59095.58±7484.79        55066.93±33398.34                       4.64\n",
+      "{'alpha': '1.58e-01', 'height': 0.0}   16.87±0.30           16.99±0.33              16.87±2.47                              0.34\n",
+      "{'alpha': '1.58e-01', 'height': 1.0}   6.06±0.23            7.44±0.68               7.64±2.25                               0.77\n",
+      "{'alpha': '1.58e-01', 'height': 2.0}   55.82±67.03          548.63±712.40           645.23±1345.78                          1.21\n",
+      "{'alpha': '1.58e-01', 'height': 3.0}   2037.75±3275.77      33900.84±45655.78       35449.52±49521.65                       1.91\n",
+      "{'alpha': '1.58e-01', 'height': 4.0}   407.69±296.93        46011.33±34362.68       81695.67±164955.70                      2.16\n",
+      "{'alpha': '1.58e-01', 'height': 5.0}   94.19±3.52           26047.04±3356.45        23243.60±14496.49                       2.84\n",
+      "{'alpha': '1.58e-01', 'height': 6.0}   93.38±3.13           30678.19±3859.41        29429.34±19650.67                       3.2\n",
+      "{'alpha': '1.58e-01', 'height': 7.0}   94.53±3.30           35282.66±4439.47        29979.79±17961.19                       3.85\n",
+      "{'alpha': '1.58e-01', 'height': 8.0}   93.33±4.48           38543.88±4318.12        44157.95±23014.39                       3.73\n",
+      "{'alpha': '1.58e-01', 'height': 9.0}   94.58±3.79           43511.36±4937.05        41257.28±30316.55                       4.21\n",
+      "{'alpha': '1.58e-01', 'height': 10.0}  94.26±3.54           46935.24±5944.33        43733.84±26524.68                       4.64\n",
+      "{'alpha': '2.00e-01', 'height': 0.0}   16.87±0.30           16.99±0.33              16.87±2.47                              0.34\n",
+      "{'alpha': '2.00e-01', 'height': 1.0}   6.20±0.23            7.51±0.64               7.67±2.21                               0.77\n",
+      "{'alpha': '2.00e-01', 'height': 2.0}   116.25±231.80        1489.13±4978.40         1544.48±4377.89                         1.21\n",
+      "{'alpha': '2.00e-01', 'height': 3.0}   1753.89±1667.24      52871.83±124646.98      32421.86±39697.35                       1.91\n",
+      "{'alpha': '2.00e-01', 'height': 4.0}   304.60±242.60        30353.29±22361.81       39706.86±79913.75                       2.16\n",
+      "{'alpha': '2.00e-01', 'height': 5.0}   94.13±3.52           20683.80±2663.52        18455.64±11510.56                       2.84\n",
+      "{'alpha': '2.00e-01', 'height': 6.0}   93.33±3.13           24361.97±3064.16        23370.99±15601.53                       3.2\n",
+      "{'alpha': '2.00e-01', 'height': 7.0}   94.48±3.30           28019.72±3525.36        23806.30±14263.15                       3.85\n",
+      "{'alpha': '2.00e-01', 'height': 8.0}   93.29±4.48           30610.16±3428.47        35067.13±18276.95                       3.73\n",
+      "{'alpha': '2.00e-01', 'height': 9.0}   94.54±3.78           34556.38±3920.45        32768.54±24070.64                       4.21\n",
+      "{'alpha': '2.00e-01', 'height': 10.0}  94.23±3.54           37275.97±4720.70        34731.66±21064.74                       4.64\n",
+      "{'alpha': '2.51e-01', 'height': 0.0}   16.87±0.30           16.99±0.33              16.88±2.47                              0.34\n",
+      "{'alpha': '2.51e-01', 'height': 1.0}   6.38±0.22            7.63±0.61               7.73±2.17                               0.77\n",
+      "{'alpha': '2.51e-01', 'height': 2.0}   42.27±41.29          261.07±197.87           272.12±363.49                           1.21\n",
+      "{'alpha': '2.51e-01', 'height': 3.0}   1613.98±2137.84      23979.41±35429.79       36075.94±89358.33                       1.91\n",
+      "{'alpha': '2.51e-01', 'height': 4.0}   233.90±175.14        20402.13±13653.33       26084.86±50189.17                       2.16\n",
+      "{'alpha': '2.51e-01', 'height': 5.0}   94.05±3.51           16423.67±2113.11        14652.48±9138.73                        2.84\n",
+      "{'alpha': '2.51e-01', 'height': 6.0}   93.27±3.12           19344.87±2432.48        18558.72±12385.18                       3.2\n",
+      "{'alpha': '2.51e-01', 'height': 7.0}   94.43±3.29           22250.59±2799.26        18902.55±11325.68                       3.85\n",
+      "{'alpha': '2.51e-01', 'height': 8.0}   93.24±4.48           24308.22±2721.79        27846.06±14513.86                       3.73\n",
+      "{'alpha': '2.51e-01', 'height': 9.0}   94.50±3.78           27443.21±3112.93        26025.72±19109.35                       4.21\n",
+      "{'alpha': '2.51e-01', 'height': 10.0}  94.19±3.54           29603.35±3748.73        27581.01±16727.75                       4.64\n",
+      "{'alpha': '3.16e-01', 'height': 0.0}   16.87±0.30           16.99±0.33              16.88±2.47                              0.34\n",
+      "{'alpha': '3.16e-01', 'height': 1.0}   6.62±0.21            7.81±0.57               7.85±2.14                               0.77\n",
+      "{'alpha': '3.16e-01', 'height': 2.0}   30.38±30.44          148.71±90.02            169.66±234.91                           1.21\n",
+      "{'alpha': '3.16e-01', 'height': 3.0}   1100.04±1315.87      14134.02±13044.86       15230.16±19952.37                       1.91\n",
+      "{'alpha': '3.16e-01', 'height': 4.0}   194.97±134.68        14591.59±8534.11        17913.67±31634.69                       2.16\n",
+      "{'alpha': '3.16e-01', 'height': 5.0}   93.96±3.51           13039.79±1675.90        11631.59±7254.70                        2.84\n",
+      "{'alpha': '3.16e-01', 'height': 6.0}   93.19±3.12           15359.68±1930.71        14736.24±9830.34                        3.2\n",
+      "{'alpha': '3.16e-01', 'height': 7.0}   94.35±3.29           17668.05±2222.50        15007.42±8992.36                        3.85\n",
+      "{'alpha': '3.16e-01', 'height': 8.0}   93.18±4.47           19302.44±2160.46        22110.20±11524.72                       3.73\n",
+      "{'alpha': '3.16e-01', 'height': 9.0}   94.44±3.78           21793.05±2471.49        20669.74±15168.46                       4.21\n",
+      "{'alpha': '3.16e-01', 'height': 10.0}  94.14±3.54           23508.81±2976.67        21901.08±13282.74                       4.64\n",
+      "{'alpha': '3.98e-01', 'height': 0.0}   16.87±0.30           16.99±0.33              16.88±2.47                              0.34\n",
+      "{'alpha': '3.98e-01', 'height': 1.0}   6.92±0.21            8.05±0.53               8.03±2.10                               0.77\n",
+      "{'alpha': '3.98e-01', 'height': 2.0}   2747.21±14863.56     16409.93±89139.91       4249.78±22412.36                        1.21\n",
+      "{'alpha': '3.98e-01', 'height': 3.0}   956.79±1100.86       12542.57±12507.92       10824.66±12603.34                       1.91\n",
+      "{'alpha': '3.98e-01', 'height': 4.0}   166.60±102.93        10656.19±5342.84        12581.25±20009.41                       2.16\n",
+      "{'alpha': '3.98e-01', 'height': 5.0}   93.84±3.50           10351.94±1328.63        9232.10±5758.14                         2.84\n",
+      "{'alpha': '3.98e-01', 'height': 6.0}   93.09±3.11           12194.20±1532.14        11700.01±7800.95                        3.2\n",
+      "{'alpha': '3.98e-01', 'height': 7.0}   94.26±3.28           14028.06±1764.36        11913.47±7138.93                        3.85\n",
+      "{'alpha': '3.98e-01', 'height': 8.0}   93.10±4.46           15326.26±1714.58        17554.09±9150.35                        3.73\n",
+      "{'alpha': '3.98e-01', 'height': 9.0}   94.36±3.77           17305.01±1961.98        16415.36±12038.10                       4.21\n",
+      "{'alpha': '3.98e-01', 'height': 10.0}  94.07±3.53           18667.78±2363.40        17389.40±10546.27                       4.64\n",
+      "{'alpha': '5.01e-01', 'height': 0.0}   16.87±0.30           16.99±0.33              16.88±2.47                              0.34\n",
+      "{'alpha': '5.01e-01', 'height': 1.0}   7.27±0.20            8.34±0.48               8.26±2.08                               0.77\n",
+      "{'alpha': '5.01e-01', 'height': 2.0}   36.08±68.23          134.34±173.38           133.99±151.31                           1.21\n",
+      "{'alpha': '5.01e-01', 'height': 3.0}   949.82±1916.17       8193.65±10771.56        10610.38±20976.73                       1.91\n",
+      "{'alpha': '5.01e-01', 'height': 4.0}   145.17±77.80         7900.59±3349.30         9002.25±12733.97                        2.16\n",
+      "{'alpha': '5.01e-01', 'height': 5.0}   93.69±3.49           8217.00±1052.79         7326.23±4569.35                         2.84\n",
+      "{'alpha': '5.01e-01', 'height': 6.0}   92.96±3.11           9679.85±1215.54         9288.33±6188.93                         3.2\n",
+      "{'alpha': '5.01e-01', 'height': 7.0}   94.15±3.28           11136.78±1400.45        9455.93±5666.68                         3.85\n",
+      "{'alpha': '5.01e-01', 'height': 8.0}   93.01±4.46           12167.92±1360.41        13935.10±7264.30                        3.73\n",
+      "{'alpha': '5.01e-01', 'height': 9.0}   94.27±3.77           13740.09±1557.27        13036.04±9551.57                        4.21\n",
+      "{'alpha': '5.01e-01', 'height': 10.0}  93.99±3.53           14822.46±1876.26        13805.70±8372.59                        4.64\n",
+      "{'alpha': '6.31e-01', 'height': 0.0}   16.88±0.30           17.00±0.33              16.88±2.47                              0.34\n",
+      "{'alpha': '6.31e-01', 'height': 1.0}   7.66±0.20            8.68±0.45               8.54±2.07                               0.77\n",
+      "{'alpha': '6.31e-01', 'height': 2.0}   25.91±21.14          126.30±137.50           110.47±107.86                           1.21\n",
+      "{'alpha': '6.31e-01', 'height': 3.0}   1732.59±7101.34      6325.81±7624.71         41977.44±202938.08                      1.91\n",
+      "{'alpha': '6.31e-01', 'height': 4.0}   128.86±58.00         5931.38±2107.79         6551.50±8186.22                         2.16\n",
+      "{'alpha': '6.31e-01', 'height': 5.0}   93.50±3.48           6521.26±833.69          5812.48±3625.02                         2.84\n",
+      "{'alpha': '6.31e-01', 'height': 6.0}   92.80±3.10           7682.72±964.05          7372.77±4908.44                         3.2\n",
+      "{'alpha': '6.31e-01', 'height': 7.0}   94.01±3.27           8840.25±1111.38         7503.93±4497.22                         3.85\n",
+      "{'alpha': '6.31e-01', 'height': 8.0}   92.88±4.45           9659.25±1079.09         11060.50±5766.13                        3.73\n",
+      "{'alpha': '6.31e-01', 'height': 9.0}   94.16±3.76           10908.44±1235.79        10351.80±7576.46                        4.21\n",
+      "{'alpha': '6.31e-01', 'height': 10.0}  93.89±3.52           11768.08±1489.31        10959.13±6645.97                        4.64\n",
+      "{'alpha': '7.94e-01', 'height': 0.0}   16.88±0.30           17.00±0.33              16.89±2.47                              0.34\n",
+      "{'alpha': '7.94e-01', 'height': 1.0}   8.08±0.20            9.05±0.42               8.85±2.06                               0.77\n",
+      "{'alpha': '7.94e-01', 'height': 2.0}   22.52±17.63          87.38±77.96             95.85±131.50                            1.21\n",
+      "{'alpha': '7.94e-01', 'height': 3.0}   416.21±751.07        3714.85±3937.59         5486.40±14095.58                        1.91\n",
+      "{'alpha': '7.94e-01', 'height': 4.0}   116.43±42.54         4500.38±1337.54         4842.28±5344.62                         2.16\n",
+      "{'alpha': '7.94e-01', 'height': 5.0}   93.27±3.47           5174.43±659.66          4610.24±2874.86                         2.84\n",
+      "{'alpha': '7.94e-01', 'height': 6.0}   92.60±3.09           6096.47±764.28          5851.31±3891.29                         3.2\n",
+      "{'alpha': '7.94e-01', 'height': 7.0}   93.84±3.26           7016.15±881.76          5953.53±3568.26                         3.85\n",
+      "{'alpha': '7.94e-01', 'height': 8.0}   92.73±4.43           7666.63±855.63          8777.22±4576.07                         3.73\n",
+      "{'alpha': '7.94e-01', 'height': 9.0}   94.02±3.75           8659.26±980.43          8219.71±6007.58                         4.21\n",
+      "{'alpha': '7.94e-01', 'height': 10.0}  93.76±3.51           9341.97±1181.93         8698.11±5274.44                         4.64\n",
+      "{'alpha': '1.00e+00', 'height': 0.0}   16.89±0.30           17.01±0.33              16.90±2.47                              0.34\n",
+      "{'alpha': '1.00e+00', 'height': 1.0}   8.51±0.21            9.45±0.39               9.19±2.06                               0.77\n",
+      "{'alpha': '1.00e+00', 'height': 2.0}   14.74±7.03           50.36±21.22             55.99±60.86                             1.21\n",
+      "{'alpha': '1.00e+00', 'height': 3.0}   295.46±297.82        2694.14±1517.29         2865.00±3303.75                         1.91\n",
+      "{'alpha': '1.00e+00', 'height': 4.0}   106.99±30.60         3445.19±861.32          3628.78±3565.87                         2.16\n",
+      "{'alpha': '1.00e+00', 'height': 5.0}   92.99±3.45           4104.79±521.44          3655.49±2278.93                         2.84\n",
+      "{'alpha': '1.00e+00', 'height': 6.0}   92.36±3.07           4836.62±605.59          4642.95±3083.31                         3.2\n",
+      "{'alpha': '1.00e+00', 'height': 7.0}   93.62±3.25           5567.36±699.37          4722.15±2830.33                         3.85\n",
+      "{'alpha': '1.00e+00', 'height': 8.0}   92.54±4.42           6083.96±678.13          6963.66±3630.73                         3.73\n",
+      "{'alpha': '1.00e+00', 'height': 9.0}   93.84±3.74           6872.78±777.59          6526.22±4761.39                         4.21\n",
+      "{'alpha': '1.00e+00', 'height': 10.0}  93.59±3.50           7414.94±937.77          6902.24±4184.97                         4.64\n",
+      "{'alpha': '1.26e+00', 'height': 0.0}   16.90±0.30           17.01±0.33              16.90±2.47                              0.34\n",
+      "{'alpha': '1.26e+00', 'height': 1.0}   8.93±0.21            9.84±0.38               9.54±2.07                               0.77\n",
+      "{'alpha': '1.26e+00', 'height': 2.0}   43.65±154.61         109.04±362.54           258.19±1136.96                          1.21\n",
+      "{'alpha': '1.26e+00', 'height': 3.0}   218.99±247.31        2000.75±2238.28         2044.66±2944.52                         1.91\n",
+      "{'alpha': '1.26e+00', 'height': 4.0}   99.85±21.55          2657.28±567.01          2752.63±2444.77                         2.16\n",
+      "{'alpha': '1.26e+00', 'height': 5.0}   92.63±3.43           3255.36±411.67          2897.39±1805.48                         2.84\n",
+      "{'alpha': '1.26e+00', 'height': 6.0}   92.05±3.06           3836.08±479.53          3683.33±2441.48                         3.2\n",
+      "{'alpha': '1.26e+00', 'height': 7.0}   93.35±3.24           4416.71±554.49          3744.23±2244.14                         3.85\n",
+      "{'alpha': '1.26e+00', 'height': 8.0}   92.31±4.40           4826.95±537.14          5523.24±2879.77                         3.73\n",
+      "{'alpha': '1.26e+00', 'height': 9.0}   93.62±3.72           5453.87±616.47          5181.14±3771.51                         4.21\n",
+      "{'alpha': '1.26e+00', 'height': 10.0}  93.39±3.49           5884.37±743.82          5475.86±3319.53                         4.64\n",
+      "{'alpha': '1.58e+00', 'height': 0.0}   16.91±0.30           17.03±0.33              16.91±2.47                              0.34\n",
+      "{'alpha': '1.58e+00', 'height': 1.0}   9.35±0.22            10.23±0.37              9.88±2.08                               0.77\n",
+      "{'alpha': '1.58e+00', 'height': 2.0}   14.03±19.17          68.19±206.18            72.11±211.57                            1.21\n",
+      "{'alpha': '1.58e+00', 'height': 3.0}   154.16±121.08        1421.38±1077.06         1718.64±2580.40                         1.91\n",
+      "{'alpha': '1.58e+00', 'height': 4.0}   94.47±14.87          2062.16±384.28          2109.87±1727.50                         2.16\n",
+      "{'alpha': '1.58e+00', 'height': 5.0}   92.20±3.40           2580.93±324.50          2295.57±1429.31                         2.84\n",
+      "{'alpha': '1.58e+00', 'height': 6.0}   91.67±3.04           3041.58±379.38          2921.34±1931.61                         3.2\n",
+      "{'alpha': '1.58e+00', 'height': 7.0}   93.02±3.22           3502.94±439.40          2967.68±1778.47                         3.85\n",
+      "{'alpha': '1.58e+00', 'height': 8.0}   92.01±4.37           3828.67±425.16          4379.26±2283.20                         3.73\n",
+      "{'alpha': '1.58e+00', 'height': 9.0}   93.34±3.71           4326.96±488.48          4112.86±2985.24                         4.21\n",
+      "{'alpha': '1.58e+00', 'height': 10.0}  93.14±3.48           4668.75±589.75          4343.04±2632.05                         4.64\n",
+      "{'alpha': '2.00e+00', 'height': 0.0}   16.92±0.30           17.04±0.33              16.93±2.47                              0.34\n",
+      "{'alpha': '2.00e+00', 'height': 1.0}   9.74±0.23            10.60±0.36              10.21±2.10                              0.77\n",
+      "{'alpha': '2.00e+00', 'height': 2.0}   10.81±4.32           28.05±7.90              31.82±31.22                             1.21\n",
+      "{'alpha': '2.00e+00', 'height': 3.0}   153.04±299.54        1183.30±1684.97         1967.82±6958.57                         1.91\n",
+      "{'alpha': '2.00e+00', 'height': 4.0}   90.43±10.14          1608.19±269.25          1631.03±1257.11                         2.16\n",
+      "{'alpha': '2.00e+00', 'height': 5.0}   91.66±3.37           2045.57±255.29          1817.98±1130.37                         2.84\n",
+      "{'alpha': '2.00e+00', 'height': 6.0}   91.21±3.01           2410.80±299.81          2316.42±1526.54                         3.2\n",
+      "{'alpha': '2.00e+00', 'height': 7.0}   92.60±3.20           2777.39±347.98          2351.16±1408.51                         3.85\n",
+      "{'alpha': '2.00e+00', 'height': 8.0}   91.65±4.34           3035.95±336.22          3470.79±1809.25                         3.73\n",
+      "{'alpha': '2.00e+00', 'height': 9.0}   93.00±3.68           3432.03±386.81          3264.48±2360.70                         4.21\n",
+      "{'alpha': '2.00e+00', 'height': 10.0}  92.83±3.46           3703.34±467.36          3443.43±2085.91                         4.64\n",
+      "{'alpha': '2.51e+00', 'height': 0.0}   16.95±0.30           17.06±0.33              16.95±2.46                              0.34\n",
+      "{'alpha': '2.51e+00', 'height': 1.0}   10.11±0.24           10.94±0.36              10.51±2.11                              0.77\n",
+      "{'alpha': '2.51e+00', 'height': 2.0}   9.77±1.95            23.68±3.78              25.64±20.79                             1.21\n",
+      "{'alpha': '2.51e+00', 'height': 3.0}   99.68±131.75         675.19±560.35           946.38±2494.04                          1.91\n",
+      "{'alpha': '2.51e+00', 'height': 4.0}   87.37±7.01           1259.25±194.87          1269.72±937.80                          2.16\n",
+      "{'alpha': '2.51e+00', 'height': 5.0}   91.01±3.33           1620.79±200.35          1439.20±892.75                          2.84\n",
+      "{'alpha': '2.51e+00', 'height': 6.0}   90.65±2.98           1910.15±236.58          1836.34±1204.71                         3.2\n",
+      "{'alpha': '2.51e+00', 'height': 7.0}   92.10±3.17           2201.41±275.34          1861.84±1114.57                         3.85\n",
+      "{'alpha': '2.51e+00', 'height': 8.0}   91.21±4.31           2406.59±265.58          2749.47±1432.68                         3.73\n",
+      "{'alpha': '2.51e+00', 'height': 9.0}   92.58±3.66           2721.45±306.05          2590.82±1864.62                         4.21\n",
+      "{'alpha': '2.51e+00', 'height': 10.0}  92.45±3.43           2936.74±370.12          2729.14±1652.02                         4.64\n",
+      "{'alpha': '3.16e+00', 'height': 0.0}   16.98±0.29           17.09±0.33              16.99±2.46                              0.34\n",
+      "{'alpha': '3.16e+00', 'height': 1.0}   10.46±0.24           11.26±0.36              10.80±2.13                              0.77\n",
+      "{'alpha': '3.16e+00', 'height': 2.0}   9.46±1.13            21.12±2.31              22.90±15.77                             1.21\n",
+      "{'alpha': '3.16e+00', 'height': 3.0}   67.90±35.26          462.28±318.98           470.69±599.28                           1.91\n",
+      "{'alpha': '3.16e+00', 'height': 4.0}   85.01±5.13           989.52±144.87           994.20±712.51                           2.16\n",
+      "{'alpha': '3.16e+00', 'height': 5.0}   90.23±3.27           1283.96±156.75          1139.06±703.78                          2.84\n",
+      "{'alpha': '3.16e+00', 'height': 6.0}   89.96±2.94           1512.99±186.33          1455.56±948.97                          3.2\n",
+      "{'alpha': '3.16e+00', 'height': 7.0}   91.48±3.14           1744.35±217.64          1473.67±880.98                          3.85\n",
+      "{'alpha': '3.16e+00', 'height': 8.0}   90.66±4.26           1907.06±209.48          2176.88±1133.44                         3.73\n",
+      "{'alpha': '3.16e+00', 'height': 9.0}   92.06±3.62           2157.36±241.90          2056.01±1470.60                         4.21\n",
+      "{'alpha': '3.16e+00', 'height': 10.0}  91.98±3.40           2328.12±292.87          2162.13±1307.27                         4.64\n",
+      "{'alpha': '3.98e+00', 'height': 0.0}   17.02±0.29           17.13±0.33              17.03±2.45                              0.34\n",
+      "{'alpha': '3.98e+00', 'height': 1.0}   10.78±0.25           11.55±0.37              11.06±2.14                              0.77\n",
+      "{'alpha': '3.98e+00', 'height': 2.0}   9.50±0.81            19.59±1.79              20.98±11.69                             1.21\n",
+      "{'alpha': '3.98e+00', 'height': 3.0}   58.16±24.67          342.02±218.09           341.45±370.57                           1.91\n",
+      "{'alpha': '3.98e+00', 'height': 4.0}   83.11±4.15           780.13±109.73           782.43±547.58                           2.16\n",
+      "{'alpha': '3.98e+00', 'height': 5.0}   89.30±3.21           1017.16±122.18          901.60±553.41                           2.84\n",
+      "{'alpha': '3.98e+00', 'height': 6.0}   89.14±2.90           1198.17±146.36          1153.78±745.72                          3.2\n",
+      "{'alpha': '3.98e+00', 'height': 7.0}   90.74±3.10           1381.86±171.78          1165.99±695.31                          3.85\n",
+      "{'alpha': '3.98e+00', 'height': 8.0}   90.00±4.20           1510.79±164.92          1722.53±895.58                          3.73\n",
+      "{'alpha': '3.98e+00', 'height': 9.0}   91.43±3.58           1709.73±190.92          1631.58±1157.64                         4.21\n",
+      "{'alpha': '3.98e+00', 'height': 10.0}  91.40±3.37           1845.08±231.47          1712.21±1033.31                         4.64\n",
+      "{'alpha': '5.01e+00', 'height': 0.0}   17.08±0.29           17.19±0.33              17.09±2.45                              0.34\n",
+      "{'alpha': '5.01e+00', 'height': 1.0}   11.07±0.26           11.83±0.37              11.30±2.16                              0.77\n",
+      "{'alpha': '5.01e+00', 'height': 2.0}   9.73±0.65            18.68±1.39              19.84±8.73                              1.21\n",
+      "{'alpha': '5.01e+00', 'height': 3.0}   51.88±17.50          258.25±142.92           260.60±244.84                           1.91\n",
+      "{'alpha': '5.01e+00', 'height': 4.0}   81.47±3.68           617.24±83.95            618.83±423.12                           2.16\n",
+      "{'alpha': '5.01e+00', 'height': 5.0}   88.22±3.13           806.19±94.78            714.16±433.64                           2.84\n",
+      "{'alpha': '5.01e+00', 'height': 6.0}   88.18±2.84           948.93±114.56           914.94±584.13                           3.2\n",
+      "{'alpha': '5.01e+00', 'height': 7.0}   89.86±3.05           1094.66±135.32          922.41±547.66                           3.85\n",
+      "{'alpha': '5.01e+00', 'height': 8.0}   89.21±4.13           1196.66±129.55          1362.23±706.43                          3.73\n",
+      "{'alpha': '5.01e+00', 'height': 9.0}   90.68±3.53           1354.74±150.41          1294.92±909.07                          4.21\n",
+      "{'alpha': '5.01e+00', 'height': 10.0}  90.71±3.32           1461.90±182.67          1355.43±815.54                          4.64\n",
+      "{'alpha': '6.31e+00', 'height': 0.0}   17.16±0.29           17.27±0.33              17.18±2.44                              0.34\n",
+      "{'alpha': '6.31e+00', 'height': 1.0}   11.36±0.26           12.08±0.37              11.53±2.17                              0.77\n",
+      "{'alpha': '6.31e+00', 'height': 2.0}   10.10±0.53           18.17±1.07              19.18±6.70                              1.21\n",
+      "{'alpha': '6.31e+00', 'height': 3.0}   47.45±12.16          198.75±90.65            204.70±165.16                           1.91\n",
+      "{'alpha': '6.31e+00', 'height': 4.0}   79.97±3.44           490.55±64.40            492.14±327.07                           2.16\n",
+      "{'alpha': '6.31e+00', 'height': 5.0}   86.97±3.04           639.80±73.10            566.76±338.12                           2.84\n",
+      "{'alpha': '6.31e+00', 'height': 6.0}   87.05±2.77           752.00±89.23            726.30±455.63                           3.2\n",
+      "{'alpha': '6.31e+00', 'height': 7.0}   88.82±2.99           867.44±106.33           730.00±430.17                           3.85\n",
+      "{'alpha': '6.31e+00', 'height': 8.0}   88.28±4.04           947.95±101.46           1076.81±555.93                          3.73\n",
+      "{'alpha': '6.31e+00', 'height': 9.0}   89.77±3.46           1073.47±118.21          1028.13±711.65                          4.21\n",
+      "{'alpha': '6.31e+00', 'height': 10.0}  89.87±3.27           1158.18±143.86          1072.79±642.36                          4.64\n",
+      "{'alpha': '7.94e+00', 'height': 0.0}   17.28±0.29           17.38±0.33              17.29±2.42                              0.34\n",
+      "{'alpha': '7.94e+00', 'height': 1.0}   11.63±0.26           12.34±0.38              11.75±2.18                              0.77\n",
+      "{'alpha': '7.94e+00', 'height': 2.0}   10.58±0.45           17.98±0.83              18.89±5.44                              1.21\n",
+      "{'alpha': '7.94e+00', 'height': 3.0}   44.29±8.20           156.80±56.11            165.02±112.86                           1.91\n",
+      "{'alpha': '7.94e+00', 'height': 4.0}   78.55±3.28           392.30±49.23            394.11±251.78                           2.16\n",
+      "{'alpha': '7.94e+00', 'height': 5.0}   85.59±2.93           509.11±55.99            451.50±261.80                           2.84\n",
+      "{'alpha': '7.94e+00', 'height': 6.0}   85.78±2.69           596.90±69.01            577.79±353.40                           3.2\n",
+      "{'alpha': '7.94e+00', 'height': 7.0}   87.62±2.91           688.11±83.24            578.51±336.57                           3.85\n",
+      "{'alpha': '7.94e+00', 'height': 8.0}   87.19±3.93           751.44±79.15            851.07±436.06                           3.73\n",
+      "{'alpha': '7.94e+00', 'height': 9.0}   88.72±3.38           850.96±92.59            816.99±554.85                           4.21\n",
+      "{'alpha': '7.94e+00', 'height': 10.0}  88.89±3.20           917.75±112.97           849.25±504.54                           4.64\n",
+      "{'alpha': '1.00e+01', 'height': 0.0}   17.43±0.29           17.53±0.33              17.45±2.41                              0.34\n",
+      "{'alpha': '1.00e+01', 'height': 1.0}   11.90±0.26           12.59±0.38              11.98±2.19                              0.77\n",
+      "{'alpha': '1.00e+01', 'height': 2.0}   11.17±0.39           18.02±0.67              18.87±4.76                              1.21\n",
+      "{'alpha': '1.00e+01', 'height': 3.0}   42.13±5.36           127.52±34.14            136.74±77.89                            1.91\n",
+      "{'alpha': '1.00e+01', 'height': 4.0}   77.19±3.11           316.62±37.29            318.65±192.18                           2.16\n",
+      "{'alpha': '1.00e+01', 'height': 5.0}   84.10±2.79           407.11±42.51            362.15±200.74                           2.84\n",
+      "{'alpha': '1.00e+01', 'height': 6.0}   84.37±2.59           475.34±52.86            461.46±272.07                           3.2\n",
+      "{'alpha': '1.00e+01', 'height': 7.0}   86.27±2.82           547.09±64.83            459.88±261.91                           3.85\n",
+      "{'alpha': '1.00e+01', 'height': 8.0}   85.96±3.80           596.64±61.45            672.99±340.46                           3.73\n",
+      "{'alpha': '1.00e+01', 'height': 9.0}   87.50±3.28           675.34±72.19            650.27±430.32                           4.21\n",
+      "{'alpha': '1.00e+01', 'height': 10.0}  87.74±3.11           727.82±88.37            672.92±394.76                           4.64\n",
+      "{'alpha': '1.26e+01', 'height': 0.0}   17.63±0.28           17.73±0.33              17.66±2.39                              0.34\n",
+      "{'alpha': '1.26e+01', 'height': 1.0}   12.19±0.26           12.87±0.37              12.21±2.21                              0.77\n",
+      "{'alpha': '1.26e+01', 'height': 2.0}   11.84±0.35           18.26±0.56              19.07±4.47                              1.21\n",
+      "{'alpha': '1.26e+01', 'height': 3.0}   40.83±3.49           107.38±20.59            116.71±54.13                            1.91\n",
+      "{'alpha': '1.26e+01', 'height': 4.0}   75.97±2.93           258.94±27.83            261.13±144.73                           2.16\n",
+      "{'alpha': '1.26e+01', 'height': 5.0}   82.58±2.63           328.24±31.96            293.75±151.86                           2.84\n",
+      "{'alpha': '1.26e+01', 'height': 6.0}   82.89±2.47           380.76±39.94            371.00±207.38                           3.2\n",
+      "{'alpha': '1.26e+01', 'height': 7.0}   84.81±2.71           436.81±50.12            367.74±202.23                           3.85\n",
+      "{'alpha': '1.26e+01', 'height': 8.0}   84.59±3.65           475.27±47.40            533.07±264.09                           3.73\n",
+      "{'alpha': '1.26e+01', 'height': 9.0}   86.13±3.15           537.26±55.94            519.09±331.42                           4.21\n",
+      "{'alpha': '1.26e+01', 'height': 10.0}  86.44±3.01           578.24±68.76            534.38±307.20                           4.64\n",
+      "{'alpha': '1.58e+01', 'height': 0.0}   17.90±0.28           17.99±0.33              17.93±2.39                              0.34\n",
+      "{'alpha': '1.58e+01', 'height': 1.0}   12.50±0.26           13.17±0.37              12.48±2.23                              0.77\n",
+      "{'alpha': '1.58e+01', 'height': 2.0}   12.61±0.32           18.64±0.50              19.44±4.40                              1.21\n",
+      "{'alpha': '1.58e+01', 'height': 3.0}   40.35±2.40           93.85±12.46             102.75±37.78                            1.91\n",
+      "{'alpha': '1.58e+01', 'height': 4.0}   74.98±2.72           215.71±20.36            217.94±106.92                           2.16\n",
+      "{'alpha': '1.58e+01', 'height': 5.0}   81.15±2.44           268.09±23.74            242.30±112.79                           2.84\n",
+      "{'alpha': '1.58e+01', 'height': 6.0}   81.43±2.34           308.00±29.63            301.44±156.01                           3.2\n",
+      "{'alpha': '1.58e+01', 'height': 7.0}   83.29±2.58           351.31±38.36            297.07±154.48                           3.85\n",
+      "{'alpha': '1.58e+01', 'height': 8.0}   83.15±3.46           380.82±36.26            423.79±202.98                           3.73\n",
+      "{'alpha': '1.58e+01', 'height': 9.0}   84.65±3.01           429.31±42.96            416.43±252.89                           4.21\n",
+      "{'alpha': '1.58e+01', 'height': 10.0}  85.01±2.89           461.04±53.12            426.22±237.23                           4.64\n",
+      "{'alpha': '2.00e+01', 'height': 0.0}   18.23±0.28           18.32±0.33              18.27±2.40                              0.34\n",
+      "{'alpha': '2.00e+01', 'height': 1.0}   12.86±0.26           13.53±0.36              12.79±2.27                              0.77\n",
+      "{'alpha': '2.00e+01', 'height': 2.0}   13.45±0.30           19.15±0.46              19.94±4.45                              1.21\n",
+      "{'alpha': '2.00e+01', 'height': 3.0}   40.65±1.85           85.13±7.73              93.33±26.52                             1.91\n",
+      "{'alpha': '2.00e+01', 'height': 4.0}   74.40±2.48           184.06±14.51            186.21±76.96                            2.16\n",
+      "{'alpha': '2.00e+01', 'height': 5.0}   79.96±2.23           223.10±17.38            204.52±81.76                            2.84\n",
+      "{'alpha': '2.00e+01', 'height': 6.0}   80.10±2.19           252.89±21.47            248.81±115.36                           3.2\n",
+      "{'alpha': '2.00e+01', 'height': 7.0}   81.83±2.43           285.81±28.96            243.84±116.27                           3.85\n",
+      "{'alpha': '2.00e+01', 'height': 8.0}   81.72±3.25           308.10±27.44            339.25±154.00                           3.73\n",
+      "{'alpha': '2.00e+01', 'height': 9.0}   83.12±2.83           345.63±32.60            336.75±190.60                           4.21\n",
+      "{'alpha': '2.00e+01', 'height': 10.0}  83.50±2.74           369.90±40.62            342.55±181.25                           4.64\n",
+      "{'alpha': '2.51e+01', 'height': 0.0}   18.65±0.28           18.73±0.32              18.70±2.46                              0.34\n",
+      "{'alpha': '2.51e+01', 'height': 1.0}   13.28±0.26           13.95±0.36              13.16±2.32                              0.77\n",
+      "{'alpha': '2.51e+01', 'height': 2.0}   14.39±0.28           19.77±0.44              20.57±4.58                              1.21\n",
+      "{'alpha': '2.51e+01', 'height': 3.0}   41.75±1.57           79.91±5.03              87.37±18.91                             1.91\n",
+      "{'alpha': '2.51e+01', 'height': 4.0}   74.41±2.23           161.65±10.04            163.59±53.54                            2.16\n",
+      "{'alpha': '2.51e+01', 'height': 5.0}   79.23±2.01           190.36±12.49            177.62±57.48                            2.84\n",
+      "{'alpha': '2.51e+01', 'height': 6.0}   79.10±2.03           212.05±15.10            209.89±83.43                            3.2\n",
+      "{'alpha': '2.51e+01', 'height': 7.0}   80.56±2.25           236.51±21.47            204.74±85.84                            3.85\n",
+      "{'alpha': '2.51e+01', 'height': 8.0}   80.41±3.00           252.97±20.47            274.72±114.79                           3.73\n",
+      "{'alpha': '2.51e+01', 'height': 9.0}   81.65±2.62           281.59±24.35            275.63±141.30                           4.21\n",
+      "{'alpha': '2.51e+01', 'height': 10.0}  82.00±2.57           299.81±30.65            278.69±136.47                           4.64\n",
+      "{'alpha': '3.16e+01', 'height': 0.0}   19.17±0.27           19.23±0.32              19.21±2.56                              0.34\n",
+      "{'alpha': '3.16e+01', 'height': 1.0}   13.79±0.25           14.46±0.35              13.61±2.41                              0.77\n",
+      "{'alpha': '3.16e+01', 'height': 2.0}   15.43±0.27           20.50±0.42              21.31±4.76                              1.21\n",
+      "{'alpha': '3.16e+01', 'height': 3.0}   43.65±1.38           77.31±3.45              84.07±14.15                             1.91\n",
+      "{'alpha': '3.16e+01', 'height': 4.0}   76.17±3.54           146.54±6.82             151.52±45.55                            2.16\n",
+      "{'alpha': '3.16e+01', 'height': 5.0}   79.16±1.77           167.37±8.78             159.23±38.99                            2.84\n",
+      "{'alpha': '3.16e+01', 'height': 6.0}   78.63±1.86           182.68±10.26            181.97±58.69                            3.2\n",
+      "{'alpha': '3.16e+01', 'height': 7.0}   79.69±2.05           200.26±15.54            176.96±61.89                            3.85\n",
+      "{'alpha': '3.16e+01', 'height': 8.0}   79.41±2.72           212.10±14.99            226.45±83.52                            3.73\n",
+      "{'alpha': '3.16e+01', 'height': 9.0}   80.39±2.38           233.45±17.82            229.54±102.51                           4.21\n",
+      "{'alpha': '3.16e+01', 'height': 10.0}  80.65±2.38           246.77±22.72            230.83±100.77                           4.64\n",
+      "{'alpha': '3.98e+01', 'height': 0.0}   19.79±0.27           19.83±0.31              19.82±2.74                              0.34\n",
+      "{'alpha': '3.98e+01', 'height': 1.0}   14.40±0.24           15.07±0.34              14.16±2.53                              0.77\n",
+      "{'alpha': '3.98e+01', 'height': 2.0}   16.58±0.26           21.35±0.41              22.17±4.97                              1.21\n",
+      "{'alpha': '3.98e+01', 'height': 3.0}   46.79±2.68           76.88±2.73              82.96±11.89                             1.91\n",
+      "{'alpha': '3.98e+01', 'height': 4.0}   78.29±2.73           136.89±4.35             138.18±23.28                            2.16\n",
+      "{'alpha': '3.98e+01', 'height': 5.0}   81.36±4.67           151.98±6.04             147.27±25.64                            2.84\n",
+      "{'alpha': '3.98e+01', 'height': 6.0}   78.89±1.68           162.33±6.73             162.72±39.97                            3.2\n",
+      "{'alpha': '3.98e+01', 'height': 7.0}   79.42±1.83           174.45±10.90            158.04±43.47                            3.85\n",
+      "{'alpha': '3.98e+01', 'height': 8.0}   78.91±2.42           182.70±10.71            191.34±58.90                            3.73\n",
+      "{'alpha': '3.98e+01', 'height': 9.0}   79.54±2.12           198.14±12.72            195.60±72.32                            4.21\n",
+      "{'alpha': '3.98e+01', 'height': 10.0}  79.61±2.17           207.53±16.46            195.86±72.56                            4.64\n",
+      "{'alpha': '5.01e+01', 'height': 0.0}   20.52±0.26           20.54±0.31              20.54±2.98                              0.34\n",
+      "{'alpha': '5.01e+01', 'height': 1.0}   15.14±0.24           15.79±0.32              14.83±2.68                              0.77\n",
+      "{'alpha': '5.01e+01', 'height': 2.0}   17.86±0.26           22.33±0.41              23.15±5.20                              1.21\n",
+      "{'alpha': '5.01e+01', 'height': 3.0}   52.60±8.93           78.05±2.31              83.97±11.44                             1.91\n",
+      "{'alpha': '5.01e+01', 'height': 4.0}   90.36±40.64          131.38±2.68             132.09±14.10                            2.16\n",
+      "{'alpha': '5.01e+01', 'height': 5.0}   86.57±11.43          142.31±4.13             140.01±17.08                            2.84\n",
+      "{'alpha': '5.01e+01', 'height': 6.0}   80.30±1.86           148.92±4.28             150.11±26.43                            3.2\n",
+      "{'alpha': '5.01e+01', 'height': 7.0}   80.66±4.28           156.80±7.34             145.84±29.88                            3.85\n",
+      "{'alpha': '5.01e+01', 'height': 8.0}   102.05±125.25        162.36±7.42             166.75±39.97                            3.73\n",
+      "{'alpha': '5.01e+01', 'height': 9.0}   79.31±1.84           173.06±8.82             171.40±49.30                            4.21\n",
+      "{'alpha': '5.01e+01', 'height': 10.0}  79.11±1.94           179.38±11.59            171.13±50.68                            4.64\n",
+      "{'alpha': '6.31e+01', 'height': 0.0}   21.37±0.25           21.36±0.30              21.36±3.30                              0.34\n",
+      "{'alpha': '6.31e+01', 'height': 1.0}   16.00±0.23           16.64±0.31              15.61±2.88                              0.77\n",
+      "{'alpha': '6.31e+01', 'height': 2.0}   19.28±0.27           23.44±0.40              24.28±5.45                              1.21\n",
+      "{'alpha': '6.31e+01', 'height': 3.0}   67.87±29.82          91.16±26.51             96.98±39.72                             1.91\n",
+      "{'alpha': '6.31e+01', 'height': 4.0}   107.49±25.27         128.93±2.74             128.75±10.99                            2.16\n",
+      "{'alpha': '6.31e+01', 'height': 5.0}   89.83±10.32          136.76±2.90             136.01±12.97                            2.84\n",
+      "{'alpha': '6.31e+01', 'height': 6.0}   161.06±145.43        140.65±2.71             142.38±17.50                            3.2\n",
+      "{'alpha': '6.31e+01', 'height': 7.0}   81.91±2.06           145.37±4.70             138.51±20.55                            3.85\n",
+      "{'alpha': '6.31e+01', 'height': 8.0}   88.96±46.20          148.99±4.98             150.41±26.08                            3.73\n",
+      "{'alpha': '6.31e+01', 'height': 9.0}   81.92±6.57           155.98±5.92             154.85±32.39                            4.21\n",
+      "{'alpha': '6.31e+01', 'height': 10.0}  79.73±2.65           159.98±7.89             154.36±34.30                            4.64\n",
+      "{'alpha': '7.94e+01', 'height': 0.0}   22.33±0.25           22.28±0.29              22.30±3.67                              0.34\n",
+      "{'alpha': '7.94e+01', 'height': 1.0}   17.00±0.22           17.61±0.31              16.51±3.11                              0.77\n",
+      "{'alpha': '7.94e+01', 'height': 2.0}   20.87±0.29           24.71±0.40              25.57±5.70                              1.21\n",
+      "{'alpha': '7.94e+01', 'height': 3.0}   96.00±137.36         88.45±21.19             116.48±122.17                           1.91\n",
+      "{'alpha': '7.94e+01', 'height': 4.0}   90.17±2.70           127.83±1.25             127.78±10.19                            2.16\n",
+      "{'alpha': '7.94e+01', 'height': 5.0}   93.16±5.52           134.03±2.21             134.18±12.01                            2.84\n",
+      "{'alpha': '7.94e+01', 'height': 6.0}   90.97±12.29          136.03±1.86             138.07±12.59                            3.2\n",
+      "{'alpha': '7.94e+01', 'height': 7.0}   86.97±5.50           138.51±2.86             134.56±14.87                            3.85\n",
+      "{'alpha': '7.94e+01', 'height': 8.0}   83.75±2.20           140.78±3.27             140.27±16.82                            3.73\n",
+      "{'alpha': '7.94e+01', 'height': 9.0}   84.03±8.84           144.96±3.86             144.16±20.91                            4.21\n",
+      "{'alpha': '7.94e+01', 'height': 10.0}  86.48±17.93          147.31±5.22             143.58±22.86                            4.64\n",
+      "{'alpha': '1.00e+02', 'height': 0.0}   23.39±0.25           23.31±0.29              23.34±4.08                              0.34\n",
+      "{'alpha': '1.00e+02', 'height': 1.0}   18.14±0.22           18.69±0.30              17.54±3.38                              0.77\n",
+      "{'alpha': '1.00e+02', 'height': 2.0}   22.64±0.31           26.16±0.40              27.03±5.94                              1.21\n",
+      "{'alpha': '1.00e+02', 'height': 3.0}   111.74±210.77        121.27±177.90           113.99±119.23                           1.91\n",
+      "{'alpha': '1.00e+02', 'height': 4.0}   93.79±1.45           128.34±1.05             128.11±10.39                            2.16\n",
+      "{'alpha': '1.00e+02', 'height': 5.0}   94.00±2.46           133.10±1.88             133.70±12.23                            2.84\n",
+      "{'alpha': '1.00e+02', 'height': 6.0}   91.27±2.73           133.86±1.50             136.04±10.62                            3.2\n",
+      "{'alpha': '1.00e+02', 'height': 7.0}   127.20±47.94         134.86±1.73             132.82±11.96                            3.85\n",
+      "{'alpha': '1.00e+02', 'height': 8.0}   87.47±4.62           136.21±2.22             134.58±11.84                            3.73\n",
+      "{'alpha': '1.00e+02', 'height': 9.0}   87.22±6.65           138.38±2.54             137.76±14.40                            4.21\n",
+      "{'alpha': '1.00e+02', 'height': 10.0}  111.65±77.03         139.62±3.43             137.15±16.01                            4.64\n"
      ]
     },
     {
@@ -802,7 +805,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "calculate performance: 100%|██████████| 13530/13530 [14:10<00:00, 15.71it/s]"
+      "calculate performance: 100%|██████████| 13530/13530 [13:10<00:00, 20.24it/s]"
      ]
     }
    ],
diff --git a/pygraph/__pycache__/__init__.cpython-35.pyc b/pygraph/__pycache__/__init__.cpython-35.pyc
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diff --git a/pygraph/utils/model_selection_precomputed.py b/pygraph/utils/model_selection_precomputed.py
index 224223d..7fd304e 100644
--- a/pygraph/utils/model_selection_precomputed.py
+++ b/pygraph/utils/model_selection_precomputed.py
@@ -1,4 +1,9 @@
-def model_selection_for_precomputed_kernel(datafile, estimator, param_grid_precomputed, param_grid, model_type, NUM_TRIALS = 30, datafile_y = ''):
+
+
+def model_selection_for_precomputed_kernel(datafile, estimator,
+                                           param_grid_precomputed, param_grid,
+                                           model_type, NUM_TRIALS=30,
+                                           datafile_y=''):
     """Perform model selection, fitting and testing for precomputed kernels using nested cv. Print out neccessary data during the process then finally the results.
 
     Parameters
@@ -50,26 +55,30 @@ def model_selection_for_precomputed_kernel(datafile, estimator, param_grid_preco
     # setup the model type
     model_type = model_type.lower()
     if model_type != 'regression' and model_type != 'classification':
-        raise Exception('The model type is incorrect! Please choose from regression or classification.')
+        raise Exception(
+            'The model type is incorrect! Please choose from regression or classification.')
     print()
     print('--- This is a %s problem ---' % model_type)
 
     # Load the dataset
     print()
     print('1. Loading dataset from file...')
-    dataset, y = loadDataset(datafile, filename_y = datafile_y)
+    dataset, y = loadDataset(datafile, filename_y=datafile_y)
 
     # Grid of parameters with a discrete number of values for each.
     param_list_precomputed = list(ParameterGrid(param_grid_precomputed))
     param_list = list(ParameterGrid(param_grid))
 
     # Arrays to store scores
-    train_pref = np.zeros((NUM_TRIALS, len(param_list_precomputed), len(param_list)))
-    val_pref = np.zeros((NUM_TRIALS, len(param_list_precomputed), len(param_list)))
-    test_pref = np.zeros((NUM_TRIALS, len(param_list_precomputed), len(param_list)))
+    train_pref = np.zeros(
+        (NUM_TRIALS, len(param_list_precomputed), len(param_list)))
+    val_pref = np.zeros(
+        (NUM_TRIALS, len(param_list_precomputed), len(param_list)))
+    test_pref = np.zeros(
+        (NUM_TRIALS, len(param_list_precomputed), len(param_list)))
 
-    gram_matrices = [] # a list to store gram matrices for all param_grid_precomputed
-    gram_matrix_time = [] # a list to store time to calculate gram matrices
+    gram_matrices = []  # a list to store gram matrices for all param_grid_precomputed
+    gram_matrix_time = []  # a list to store time to calculate gram matrices
 
     # calculate all gram matrices
     print()
@@ -80,6 +89,7 @@ def model_selection_for_precomputed_kernel(datafile, estimator, param_grid_preco
         print('gram matrix with parameters', params_out, 'is: ')
         print(Kmatrix)
         plt.matshow(Kmatrix)
+        plt.colorbar()
         plt.show()
 #         plt.savefig('../../notebooks/gram_matrix_figs/{}_{}'.format(estimator.__name__, params_out))
         gram_matrices.append(Kmatrix)
@@ -88,17 +98,18 @@ def model_selection_for_precomputed_kernel(datafile, estimator, param_grid_preco
     print()
     print('3. Fitting and predicting using nested cross validation. This could really take a while...')
     # Loop for each trial
-    pbar = tqdm(total = NUM_TRIALS * len(param_list_precomputed) * len(param_list), 
-                desc = 'calculate performance', file=sys.stdout)
-    for trial in range(NUM_TRIALS): # Test set level
+    pbar = tqdm(total=NUM_TRIALS * len(param_list_precomputed) * len(param_list),
+                desc='calculate performance', file=sys.stdout)
+    for trial in range(NUM_TRIALS):  # Test set level
         # loop for each outer param tuple
         for index_out, params_out in enumerate(param_list_precomputed):
             # split gram matrix and y to app and test sets.
-            X_app, X_test, y_app, y_test = train_test_split(gram_matrices[index_out], y, test_size=0.1)
+            X_app, X_test, y_app, y_test = train_test_split(
+                gram_matrices[index_out], y, test_size=0.1)
             split_index_app = [y.index(y_i) for y_i in y_app if y_i in y]
             split_index_test = [y.index(y_i) for y_i in y_test if y_i in y]
-            X_app = X_app[:,split_index_app]
-            X_test = X_test[:,split_index_app]
+            X_app = X_app[:, split_index_app]
+            X_test = X_test[:, split_index_app]
             y_app = np.array(y_app)
             y_test = np.array(y_test)
 
@@ -110,43 +121,60 @@ def model_selection_for_precomputed_kernel(datafile, estimator, param_grid_preco
                 current_test_perf = []
 
                 # For regression use the Kernel Ridge method
-                if model_type == 'regression': 
-                    KR = KernelRidge(kernel = 'precomputed', **params_in)
+                if model_type == 'regression':
+                    KR = KernelRidge(kernel='precomputed', **params_in)
                     # loop for each split on validation set level
-                    for train_index, valid_index in inner_cv.split(X_app): # validation set level
-                        KR.fit(X_app[train_index,:][:,train_index], y_app[train_index])
+                    # validation set level
+                    for train_index, valid_index in inner_cv.split(X_app):
+                        KR.fit(X_app[train_index, :]
+                               [:, train_index], y_app[train_index])
 
                         # predict on the train, validation and test set
-                        y_pred_train = KR.predict(X_app[train_index,:][:,train_index])
-                        y_pred_valid = KR.predict(X_app[valid_index,:][:,train_index])
-                        y_pred_test = KR.predict(X_test[:,train_index])
+                        y_pred_train = KR.predict(
+                            X_app[train_index, :][:, train_index])
+                        y_pred_valid = KR.predict(
+                            X_app[valid_index, :][:, train_index])
+                        y_pred_test = KR.predict(X_test[:, train_index])
 
                         # root mean squared errors
-                        current_train_perf.append(np.sqrt(mean_squared_error(y_app[train_index], y_pred_train)))
-                        current_valid_perf.append(np.sqrt(mean_squared_error(y_app[valid_index], y_pred_valid)))
-                        current_test_perf.append(np.sqrt(mean_squared_error(y_test, y_pred_test)))
+                        current_train_perf.append(
+                            np.sqrt(mean_squared_error(y_app[train_index], y_pred_train)))
+                        current_valid_perf.append(
+                            np.sqrt(mean_squared_error(y_app[valid_index], y_pred_valid)))
+                        current_test_perf.append(
+                            np.sqrt(mean_squared_error(y_test, y_pred_test)))
                 # For clcassification use SVM
                 else:
-                    KR = SVC(kernel = 'precomputed', **params_in)
+                    KR = SVC(kernel='precomputed', **params_in)
                     # loop for each split on validation set level
-                    for train_index, valid_index in inner_cv.split(X_app): # validation set level
-                        KR.fit(X_app[train_index,:][:,train_index], y_app[train_index])
+                    # validation set level
+                    for train_index, valid_index in inner_cv.split(X_app):
+                        KR.fit(X_app[train_index, :]
+                               [:, train_index], y_app[train_index])
 
                         # predict on the train, validation and test set
-                        y_pred_train = KR.predict(X_app[train_index,:][:,train_index])
-                        y_pred_valid = KR.predict(X_app[valid_index,:][:,train_index])
-                        y_pred_test = KR.predict(X_test[:,train_index])
+                        y_pred_train = KR.predict(
+                            X_app[train_index, :][:, train_index])
+                        y_pred_valid = KR.predict(
+                            X_app[valid_index, :][:, train_index])
+                        y_pred_test = KR.predict(X_test[:, train_index])
 
                         # root mean squared errors
-                        current_train_perf.append(accuracy_score(y_app[train_index], y_pred_train))
-                        current_valid_perf.append(accuracy_score(y_app[valid_index], y_pred_valid))
-                        current_test_perf.append(accuracy_score(y_test, y_pred_test))
+                        current_train_perf.append(accuracy_score(
+                            y_app[train_index], y_pred_train))
+                        current_valid_perf.append(accuracy_score(
+                            y_app[valid_index], y_pred_valid))
+                        current_test_perf.append(
+                            accuracy_score(y_test, y_pred_test))
 
                 # average performance on inner splits
-                train_pref[trial][index_out][index_in] = np.mean(current_train_perf)
-                val_pref[trial][index_out][index_in] = np.mean(current_valid_perf)
-                test_pref[trial][index_out][index_in] = np.mean(current_test_perf)
-                
+                train_pref[trial][index_out][index_in] = np.mean(
+                    current_train_perf)
+                val_pref[trial][index_out][index_in] = np.mean(
+                    current_valid_perf)
+                test_pref[trial][index_out][index_in] = np.mean(
+                    current_test_perf)
+
                 pbar.update(1)
     pbar.clear()
 
@@ -156,7 +184,8 @@ def model_selection_for_precomputed_kernel(datafile, estimator, param_grid_preco
     average_train_scores = np.mean(train_pref, axis=0)
     average_val_scores = np.mean(val_pref, axis=0)
     average_perf_scores = np.mean(test_pref, axis=0)
-    std_train_scores = np.std(train_pref, axis=0, ddof=1) # sample std is used here
+    # sample std is used here
+    std_train_scores = np.std(train_pref, axis=0, ddof=1)
     std_val_scores = np.std(val_pref, axis=0, ddof=1)
     std_perf_scores = np.std(test_pref, axis=0, ddof=1)
 
@@ -171,23 +200,34 @@ def model_selection_for_precomputed_kernel(datafile, estimator, param_grid_preco
     # print('best_params_index: ', best_params_index)
     print('best_params_out: ', best_params_out)
     print('best_params_in: ', best_params_in)
+    print()
     print('best_val_perf: ', best_val_perf)
 
     # below: only find one performance; muitiple pref might exist
-    best_val_std = std_val_scores[best_params_index[0][0]][best_params_index[1][0]]
+    best_val_std = std_val_scores[best_params_index[0]
+                                  [0]][best_params_index[1][0]]
     print('best_val_std: ', best_val_std)
 
-    final_performance = average_perf_scores[best_params_index[0][0]][best_params_index[1][0]]
-    final_confidence = std_perf_scores[best_params_index[0][0]][best_params_index[1][0]]
+    final_performance = average_perf_scores[best_params_index[0]
+                                            [0]][best_params_index[1][0]]
+    final_confidence = std_perf_scores[best_params_index[0]
+                                       [0]][best_params_index[1][0]]
     print('final_performance: ', final_performance)
     print('final_confidence: ', final_confidence)
-    train_performance = average_train_scores[best_params_index[0][0]][best_params_index[1][0]]
-    train_std = std_train_scores[best_params_index[0][0]][best_params_index[1][0]]
+    train_performance = average_train_scores[best_params_index[0]
+                                             [0]][best_params_index[1][0]]
+    train_std = std_train_scores[best_params_index[0]
+                                 [0]][best_params_index[1][0]]
     print('train_performance: ', train_performance)
     print('train_std: ', train_std)
 
+    print()
+    average_gram_matrix_time = np.mean(gram_matrix_time)
+    std_gram_matrix_time = np.std(gram_matrix_time, ddof=1)
     best_gram_matrix_time = gram_matrix_time[best_params_index[0][0]]
-    print('time to calculate gram matrix: ', best_gram_matrix_time, 's')
+    print('time to calculate gram matrix with different hyperpapams: {:.2f}±{:.2f}'
+          .format(average_gram_matrix_time, std_gram_matrix_time))
+    print('time to calculate best gram matrix: ', best_gram_matrix_time, 's')
 
     # print out as table.
     from collections import OrderedDict
@@ -199,15 +239,18 @@ def model_selection_for_precomputed_kernel(datafile, estimator, param_grid_preco
     else:
         for param_in in param_list:
             param_in['C'] = '{:.2e}'.format(param_in['C'])
-    table_dict['params'] = [ {**param_out, **param_in} for param_in in param_list for param_out in param_list_precomputed ]
-    table_dict['gram_matrix_time'] = [ '{:.2f}'.format(gram_matrix_time[index_out])
-                                       for param_in in param_list for index_out, _ in enumerate(param_list_precomputed) ]
-    table_dict['valid_perf'] = [ '{:.2f}±{:.2f}'.format(average_val_scores[index_out][index_in], std_val_scores[index_out][index_in])
-                                 for index_in, _ in enumerate(param_list) for index_out, _ in enumerate(param_list_precomputed) ]
-    table_dict['test_perf'] = [ '{:.2f}±{:.2f}'.format(average_perf_scores[index_out][index_in], std_perf_scores[index_out][index_in])
-                                 for index_in, _ in enumerate(param_list) for index_out, _ in enumerate(param_list_precomputed) ]
-    table_dict['train_perf'] = [ '{:.2f}±{:.2f}'.format(average_train_scores[index_out][index_in], std_train_scores[index_out][index_in])
-                                 for index_in, _ in enumerate(param_list) for index_out, _ in enumerate(param_list_precomputed) ]
-    keyorder = ['params', 'train_perf', 'valid_perf', 'test_perf', 'gram_matrix_time']
+    table_dict['params'] = [{**param_out, **param_in}
+                            for param_in in param_list for param_out in param_list_precomputed]
+    table_dict['gram_matrix_time'] = ['{:.2f}'.format(gram_matrix_time[index_out])
+                                      for param_in in param_list for index_out, _ in enumerate(param_list_precomputed)]
+    table_dict['valid_perf'] = ['{:.2f}±{:.2f}'.format(average_val_scores[index_out][index_in], std_val_scores[index_out][index_in])
+                                for index_in, _ in enumerate(param_list) for index_out, _ in enumerate(param_list_precomputed)]
+    table_dict['test_perf'] = ['{:.2f}±{:.2f}'.format(average_perf_scores[index_out][index_in], std_perf_scores[index_out][index_in])
+                               for index_in, _ in enumerate(param_list) for index_out, _ in enumerate(param_list_precomputed)]
+    table_dict['train_perf'] = ['{:.2f}±{:.2f}'.format(average_train_scores[index_out][index_in], std_train_scores[index_out][index_in])
+                                for index_in, _ in enumerate(param_list) for index_out, _ in enumerate(param_list_precomputed)]
+    keyorder = ['params', 'train_perf', 'valid_perf',
+                'test_perf', 'gram_matrix_time']
     print()
-    print(tabulate(OrderedDict(sorted(table_dict.items(), key = lambda i:keyorder.index(i[0]))), headers='keys'))
\ No newline at end of file
+    print(tabulate(OrderedDict(sorted(table_dict.items(),
+                                      key=lambda i: keyorder.index(i[0]))), headers='keys'))