diff --git a/docs/guide/20_betweenness_centrality.myst b/docs/guide/20_betweenness_centrality.myst
index 40d97f9..5a6ade4 100644
--- a/docs/guide/20_betweenness_centrality.myst
+++ b/docs/guide/20_betweenness_centrality.myst
@@ -63,7 +63,7 @@ import numpy as np
 import pandas as pd
 from networkx.algorithms.centrality.betweenness import \
     _single_source_dijkstra_path_basic, \
-    _rescale, _rescale_e
+    _rescale
 from scipy.sparse.csgraph import dijkstra
 
 from superblockify.metrics.distances import shortest_paths_restricted
@@ -305,12 +305,12 @@ def calculate_betweenness_with(method, *args, show_tree=True):
         del betweenness_edge[n]
         del betweenness_edge_len[n]
         del betweenness_edge_lin[n]
-    betweenness_edge = _rescale_e(betweenness_edge, len(G), normalized=True,
-                                  directed=True)
-    betweenness_edge_len = _rescale_e(betweenness_edge_len, len(G), normalized=True,
-                                      directed=True)
-    betweenness_edge_lin = _rescale_e(betweenness_edge_lin, len(G), normalized=True,
-                                      directed=True)
+    betweenness_edge = _rescale(betweenness_edge, len(G), normalized=True,
+                                directed=True, endpoints=True)
+    betweenness_edge_len = _rescale(betweenness_edge_len, len(G), normalized=True,
+                                    directed=True, endpoints=True)
+    betweenness_edge_lin = _rescale(betweenness_edge_lin, len(G), normalized=True,
+                                    directed=True, endpoints=True)
     return {
         "Node": betweenness,
         "Edge": betweenness_edge,
diff --git a/examples/05-betweenness-centrality.ipynb b/examples/05-betweenness-centrality.ipynb
index 0c6e1a0..42bc195 100644
--- a/examples/05-betweenness-centrality.ipynb
+++ b/examples/05-betweenness-centrality.ipynb
@@ -60,14 +60,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T09:45:20.590663Z",
      "start_time": "2024-04-18T09:45:20.581492Z"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-03-23 10:55:29,468 |     INFO | __init__.py:11 | superblockify version 1.0.2\n"
+     ]
+    }
+   ],
    "source": [
     "import matplotlib.pyplot as plt\n",
     "import networkx as nx\n",
@@ -75,7 +83,7 @@
     "import pandas as pd\n",
     "from networkx.algorithms.centrality.betweenness import \\\n",
     "    _single_source_dijkstra_path_basic, \\\n",
-    "    _rescale, _rescale_e\n",
+    "    _rescale\n",
     "from scipy.sparse.csgraph import dijkstra\n",
     "\n",
     "from superblockify.metrics.distances import shortest_paths_restricted"
@@ -96,14 +104,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T09:45:47.814566Z",
      "start_time": "2024-04-18T09:45:47.257378Z"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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VcpYyp/suH4+6jij+1vMH5SFRAagoiuJTbD9/yKT7Eto5SJdvr/JtZPS2P0wDgSsQE8EFs5gdv9XoYUWHqG/Lnz+/eBOIVoQsoo5GFlKeltCjhtEyDqajE3GHmLOEXqlSpYzwdQSPOaJ9iCIEMvVhpH1btWoVdft58+aZ56B7mu1GitASUHD9s2ny4eLv5ftdro2h4xP54/0aVL2bVMxeTNwFEb6WLVuaxYJ1R8DYd8hyMIDZtPW6aIpACJI6tp/KwSl1dP5SY/jjjz8aq5mnnnrK1ARaUUI8LEsGVZKALfuS3PmbM10WebZsK9l2/qAxgbcgrbz1/AHxJTQCqCiKcnv+a1BAgNyKx3xVe16r2N4UmpM+jg12IHsuRkbAgKgOwobFkyD6FtekEBaiWfY1jMyQRdxRw0hkhvOkObNkyRLr8zFFY+7cufLFF1/In3/+aR7nySeflOeee850OzujWbNmZiydMzBnrlmmpuRJn01Gbp5mjIBjM/B2Jv5ypcsi7979uFRyo/hzBX6C+OOxPPzww1HXI/52794dJQqJqG7bts1MHEF4WyCMEUOOwpCFLmU+Z97k9xgbiGIaqDDibtGihfmMcIoApoGDOj3L+DkxZAoOlaE1njaiEiNoRzF5/sZl8SVUACqKopC2jAhLcOyAYnG85p5f9rlkTBPd/iM4IMhcdy38ZpQAuXDlkomO2c+IxTYkqfYtCDEEg6uFaJx1Hv+12ITd+fPnYwgU++kgtWvXdjkSLiH1a3T5skP//PPPTcNHlSpVTAoXP0S84WJj6NCh8vjjj8e4HtFD3SDQ9XlPztLy6eZpsuzkltszX50LQWutmeHMHNgeZZonKu3rTtjudHyztG/fPtrf6B7HMsVxKgcRWAQw4tweRDjRR8Sgtdhftj9PGtpZdNYToESAzxifdw4aOGCgnpIRfHXfjKwRTCwZg9PLpzWflZzpMhsfUBwBHHGPq6Dn4JnvsqIoSgrDzj+hFMuUz5gJf12vT4y/tSlS2yz9V481NhSwc/sOKduibIzbIgIRg/bCEAEQm6izF3fWGK6EgMiyF29E7JyJuuzZs7u1MYHU92effWYsPmiU6Nixo0nt1apVK97P06VLF3nnnXeM6LFnyJDoNZh5Q7PLkBpPmTnORGj/O71Ldl88Kjcj7sy1zZgmvZTLWkhq5y4vzQvdI5nspn14Knw+rKihM2icoS6SxZrta7/QnMIpkUTqNZ19Hvl82C8Yjbu6js8t7519Q47jecfLfGZp/rHmOVuLs+ushXW2os7WZx4j9F9++UXytakqERkjEi3+RtTsKflCc0ifFaNlz6U7kXp7MgfHNHP3ZlQAKoqiiEiB0JwufeZcMfvQKll3ZrdTM+hFxzfJpH2LZN/FyFQl6al7K9aUzxf1jLGTs79snUfcIQKJxnAa3yWu27PTRtjRpJCSUOc2bNgwGTdunEnZPfPMM9KnT5+oWq6EPE69evVMChghZHkpEgmyOkUdwcCXui4gGnvuxiUJiwiXdEHBxtbD1zpvEWXUDLLEBp93IrEIK0so0qmNgGThb9Z5azl79qyJPtpfx2fW+u5YU1rszzv7G1Fvx4Me+4VIJM0/9n9ftmyZMUy3xB/vG1Ffygfy1iglq5Z/mWjxlz80hxn/uOti9HnZFnx/y2dL2GfV01EBqCiKIiJlshaMMfrNfpQYFM2Yx6R9rVFix6+dM4szTl2/YCZK2NtI1C5WWeoXjzlL1Zch2kRkbvLkyWan/tZbb0mvXr1MZDGhkCLmvtQNYgHzv//9z4hZRMnrr7+eoPF8SqSA4kCApUSJEh6/SUaNGiXz5883BxAczLz//vvmIAJPQOZ3OzZxxfX9tYnIsJrPSqksBeSzLTMkKCBIymctEnX/8zcvm+ix9f0tm8W3Rv+pAFQURRGR8lkLm5FP9unBVyu2jzZK7L78VcxijRJzJf6cwY7p7tv2Er4OUR521Ai/v//+23SvsvPGADsxU0xIc+MNSAMEYoX6L2oRYd26dSYC1Ldv32R4JYonQbSPz9aDDz4oI0aMiDaLOUNwOqmTp7ysOLktquY2ru+v9b2HPhUeEmcR/g83/GrOEyO27usr6CQQRVGU2wzdOFFmHVqVoK7R+HaWlslaSL5xUivoS5CamzJlihF+RP6qVq1qhBndrYltLKDzFS89UpTUCSIsSQcq/gfij7pGhKAzVp3aIa+u/NrtzxsUECj18lQwtkC+hO9ODlcURUkgDxetb1I97obUcqfijXxa+GHETFMCTR2kd//66y9jeMzlxIo/OoSxkqEuDeuP5cuXq/jzY6yaP1fQ9V0lewkj2NzNU2Wai6+hAlBRFOU2xTPnky4l7jW1RO6CnVGNXGXl3nyVfW47U4vHxA46iDFmZnIFs1oRf40bN050cwUj37g/4/FI+fKYTAJRlNjg89a/SmfznXNnW0+PMi2kWKa8PrfxVQAqiqLY8WTpZlIkY263RBHYDaUPCpE3Kz3iU52mpOJmzJhhUrxE+IjKMNWEqR3VqlVL0mMz5QPfQVK9mErTmXr33Xe7bd0V34aav/9VfcxU7SX1GxcgAVI3z10+G71XAagoimJH2qBg+bRWTzMIPikiMFACJV1QiIyo9ZzkSn9nqLy3C785c+ZIjRo1pG3btmZE2dKlS40hb/Xq1ZP8+IMHDzai8sKFC/LJJ5+YqQ90eCpKQmiQr5K8f/cTxvw7Kd/hennukgF3dzVen76INoEoiqI44eyNS/Lu2u9lw9m9iYoc4Cv2QfVuUiKzd834dQX+a6Rh8WKrU6eOqcm777773PLYRPnuv/9+2bx5s6kfRPhR+6coSQHT70HrfjLGzkQD41PdG3RbND5fvo20LVLHiEhfRQWgoiiKCxgdNuPAchm97Q8z0s3RZyzGD6oESGBAgHQs3lC6l25uooneDhE+pm4gAEnvDho0yMzidVdKe/To0abWD6uXDh06yM8//+yxo8gU7+NWRLjMPLRSJu9bJAcunxRbhE2CAgOjPD/5FCPy6PwnYt+yUA3z/eUAztdRAagoihIH127dkL+PrpMfN86Rw2HnJDA4KEatX+GMuaV5werSslBNyZY2o9dv061btxpzZdK7NHkQ8cOLz13Cj5nDCMlVq1aZ6SRTp06VJk2auOWxFcVZ+cKoKeNk8IRR8mS/3nI+4qoRfaGBIVI2W2Epk6WgVM9VRkJTeQZ0SqKHWYqiKHGQPk1aaV24luyYuERmDRwm6w9ul/M3r8jqtWtkyd8LZeyQUZI2yDdq1bBcYcLG119/LUWKFJFff/3VROYY3eUufvrpJ3nqqafMHNrmzZubhhKt9VOSEw5czm87IjeXHZJBtbqb67p27Srf/vSTmYnMlBp/w3eT24qiKG5m+/btUrZUGSmZpYBUz1VahvV+V34e9q2sXLrC67c1YoxZvSVLlpQff/zRNGQQBaTL113ij7m91A0+9thj5jEZD8d0DxV/SkqAqXi5cuWiPu9TpkwxHpaUNfgjKgAVRVHiyY4dO4zZMdCwsGdP5Kxf5pHiieetqbFp06YZD7833nhDunTpIrt375bXXntN0qZ1Xzrs999/l1y5cplawvr165vGDyaEKEpqCMCff/5Zrly5Ys4zpnDv3oQ3e3k7KgAVRVESEAEsU6aMOT98+PCoyBjzaEmVehusNxG5du3amcgfHnxffvmlEWruAlPn1q1bm/mtNHqMHz9eFi1aZOr+FCWl4ADNOoDjoGfIkCFR9axcfvPNN/3uzVABqCiKEs/aOBZ2INQMMfrMivqxI6Fh4tq1a16xLY8dOybdu3c3Xb28Fho98PcjCuhOiCziFThz5kzzXDwvdVeKktIwQ5jvJxHAuXPnGjGI8APSwJMmTTINSf6ECkBFUZR4wA4DEIBEyexTvuxIjh49Kp999plHb0t2gNQ7lSpVyqRkmbW7YcMGadGihVufB6Fcq1YtE1mk1ortwjg3PP4UJbXSv4AA/Pjjj53epm/fvuJPqABUFEWJpwAk0od4GjNmjNOavx9++MFjt6UV4RswYIA8++yzsmvXLnn++eclONi9XoU8fr58+WTlypXG3PnUqVPywgsvuPU5FCWh7N+/3/hLFipUyJQi5MiRQ7Jly2b+xvQZxg7WrVvXrzas2sAoiqLEg+PHj5t0Zrp06UxE6/Dhw6aGjpq2P/74w9S0WfWBngRp15dffll+++03U+9H121yrOd///1n6vzYLkT6qIlUXz/FUyAqzfeXul1qUOG7776Tp59+2kSn3Wlz5C2oAFQURYkHZ86ciUphktqEr776ytQCtmrVym0Gye6CCCVefv369TNRPqKT2K+4ez1p8uBxqaHisXv16mVSy/64Q1U8XwDac+7cOcmSJYvfflZVACqKosRTADqaxVrXeZr4o5uXNO+KFSukR48epuMxOerviCpi6IydBrWRNJMUK1bM7c+jKMkhAE87uc6f8E/ZqyiK4iYB6EmNDQgxvPzuvvtuuXjxokl1ffvtt25fR9Lh1atXl06dOpl6KiKhFNmr+FM8FRWAMVEBqCiKEg/Onj0bQ0g5E4WpBVYrNHmQfqURg/pEDJfdnVamcaRgwYKydu1aM8aN7UK0UVE8GRWAMVEBqCiKksQUcGpy5MgRad++vTFbJg3LhJL+/fu7fbzaN998I5kzZzYWOLlz55Z///3XNJSEhoa69XkUJTlQARgTFYCKoijxwJnYI/qVWgIQ78Hvv/9eypcvL0uWLJFffvnFCLISJUq49XmWLl0qRYoUMVE+IoCffvqp8TzENkNRvAUVgDHRJhBFUZQ4QPg4E3upFQGkBg9BhpkzkzUQZZanmTufg8giApAuySeffNLU+rk7sqgoyc3Vq1eNCbo2gURHBaCiKEoc0FCBCHRWA5jSTSCTJ0+Wnj17SlBQkBm11rZtW7fbuiAusY3hNderV89YvOTNm9etz6MoKRn9A3sBeOvWLWMDo13AiqIoiksQemAf7UMcsQNJqQggEcguXbpIhw4dpGHDhqbWz93ib8SIEZI1a1Zjbs3EhGXLlsnixYtV/Ck+JwDPnTtnyij8WQBqBFBRFCURAvD8+fNGBKaEAMRfDz8/0lg//fSTdO7c2a3eg3/99ZdJJTM1hIkmWMfwfIriqwLwtJPr/A1tAlEURYmnALRP9xKRg+QUgJcuXTKjqpg0UrlyZRP1IwroLvFH80jp0qWladOmcvLkSTOz98KFCyr+FJ9CBaBzNAKoKIqSiAigM1HoThYuXGgaL06dOmVGuiEE3SX8mH3arVs32bJli2nweOihh2Ts2LEm/asovigAmeFtb1l0WiOAGgFUFEWJC6J9jjsQZ6LQHdy4cUNeeeUVuffee6Vw4cJmrNszzzzjFvFHBJEpIffcc49s3bpVWrRoYdK+U6dOVfGn+CzU+9Elb/8dOn36tLns7u55b0IjgIqiKPHoAsYE2Z7kEIC7d++Wjh07GqE2bNgw6dOnj1sG1e/atUsef/xxWblypbl83333GQ9BJnooii+yY8cOefPNN02t7s6dO00kvWjRohIWFibfffeduYz4o5veX1EBqCiK4gQiZNitEP1j2ga1cRkyZDA2KVikEEEgIkhk0B1MnDjR1N4xZWP58uUmUpdUDh48aIQfM4Ghbt26MmHCBJ3Zq/g81LROnz492nUHDhwwp+nTp5c9e/YYQejPaBOIoiiKExB6WKBQJ0cUAcsIDGXxD8MihWidO6Zu0NmL0CTy17JlS/nvv/+SLP4wcW7WrJnZwSH+qlevbgQtTR/FihVL8joriqfDHOz7778/WoSPaDrNVNgobd++XcqVKyf+jApARVEUJ1SpUkU6deoUYwdStWpVE0ljB1KmTJkkp6lq1apl0rHM2mWcm2OqOSEgVtnx5c+fX+bNmycVK1aUdevWyerVq/1+Z6f4H8OHDzdWTRac79u3rzm/bds2v/9OqABUFEVxwUcffRStBo8dyBtvvGGKxxGAZcuWTfS2IxVbrVo1E2lctWpVkrp86RhG7FWoUMFE+RCvK1askA0bNpjziuKPVKpUSZ544omo7zAHRow3JD187tw5FYCp/QYpiqJ4KqRQacSwhFm+fPnk4YcfNk0hR48ejZcAvHLlSozL2LuwY+KxiM4h3hIDEUM6hekYJvpHyovUNGnkmjVrJuoxFcWXGDRoUNT399VXX5Xg4GAT/QNNASuKoigueeutt0zROGDPwg6E1C3ElQL+448/TKfhzJkzzWVEWo0aNUzDB+PWSP0yeSMhEIX8+OOPTfcxptDYuFA/SFPK33//7Za6REXxFeh0f/DBB00U0JpugwBMkyaNlCxZUvyZABuVzYqiKIpLiByMHDnSiCzMkn/88UfTXUskMFOmTE7vw08rYg/TZbqF3377bRk4cKARaAjAhEYfrl+/buqXGNNG4wiilLTxkCFD3NaJrCi+xKHLp2Tj2b2y/fwhOXjxhASmCZLQNGll59INsnPxOln2y1zJEOy/3x0VgIqiKC6ggWLBggWydu1aEzXApBkxh5cYlhLU7jFKzRlLly6VevXqRf7QBgQYQfjYY4+ZZg8rohgfSDUTeZwyZYrpQGbyyOuvv25qEd3hEagovgTfs0XHN8nEfYuM+IM0AYFyyxbZDGKSwTYRW4BISGAaaVGohjxSrIEUzphb/A31AVQUJfm4eVnkwj6RiJsiadKLZCkhkiatx+9Afv31V/nkk09MLR0iCwEXHh4edRuuIxVLCpj6OyJz2K7YQ2SODmLux2NyH8xnQ0JC4rUev//+u4kabtq0yVzGeubDDz80IlJRlJicvHZeBm/4VVaf3imBkVLPYIk/8/3mv9t/uhlxS2YeXCGzDq6UHmWaS8fijSRNoP8YQ2sEUFEU93Jyg8jGb0T2zxW5wBG4XZVJQBqRHOVESrQWqfSMSOYiHrX1MU5+6qmnTC2dJfLiwhJ5CLPPPvvM1PxRI+iqQWTUqFHy/PPPO/0bPoPvvPOOmcuL9yDrUKdOHSNGtalDUVyz6ew+eW3VN3IjPEzC7QRfQqiao6QMvucpkyb2B1QAKoriHs5sF/nrGZEjiyOFnu1WLL88QSL8SJd5ROS+z0RCUz/9QjdukyZNTJcuqdaEghDEZgJLForN//nnn2h/p4OYlDDjqRyNntevXy8vv/yyMW1GdOIF2LVrVxPxS2iTiKL4G1vPHZAXl38pYRG3JML+gDOBBEqAVMhWVIbXelbSBsUvUu/NqABUFCVp0Ef230iRRW9Eno9N+MX4BQoSCcks0nycSMkHU+2dwC8PcUZzhX2qN6HQWcgoN+r0mBXcuXNnYxqN2TPi0B6E3ueff26ie4cPHzbX0RgyYMAA41WmKErcXA67Jo8uHCznb1w2oq1b6SZSMnMBKZ25gGRNm1HG7pwr43bOjXafitmKSctC90ipzAWkWKZ8EhKURjrMHyjHr52TAAmQ9sXqyYt3PeTzm18riBVFSTwIvn9fF1n4skhEWMLEn7l/uMiN8yIzHhLZNDZV3glEX7t27VyKP+b/fvrpp2YeMLehMQTbFWcQOcRkFgGIqBs2bJh5bHvxx/VMGKGZBI9Bbo8fIE0ljGtT8aco8WfU1hlG/BH5yxISKq0L1zbNHYtPbHZ5n2o5S0m1nKXlxPXzsvnc/mh/s4lNJu1bLBvORDaQ+DLaBKIoSuJZPVRk7bAkbsHbKZt5PUQy5BEp3ipF35F3331X9u/f77Leb+rUqXLPPfeY1O3OnTuN9x5NItTnYcTsTASSyv3666/lueeei7qO2j8ifnv3Ru5YEIV095L61W5eRUk4By+flFmHVkVdJoLXcu5b5nyW4AzSunAtp/f7ftdfMn7XPHO+U/FGcnfOkjFSwV9u+12+rtfHp98WFYBeAt2DWFFQXE4UIm3atMbEklFSjqklRUmZD+VGkSWRP7YSnFGk9jsiuaqI5K4qEppLZNl7Isvfj3m/ij1EKvcUyVoqMmp4erPI6o9F9s0Wmd1VpPsOkfQ5nD4l3bRWR607IPo2YsQIl+KvRYsW0rRpU5PKRfQBNX5FihSRoUOHym+//ebyvghLJny899578u+//xoRiIk0j/fBBx9I9erV3fIaFMVfmX5gmQQFBCa46YMoX2wQTdx6/qDsvnjEpJN9FU0BezAUo3/33XdmniF1ReyMiBjQJfjaa69JmzZtpECBAkYIshNjtqGipFjqd063O5cRbBWfEQlKK7J7uuv71XlfpOm3IsdWifzxcORjhN8QaTdLpGTbyHTwv685veuff/4pefPmlf/9739uexljxoyJtdP3oYcekkuXLsmkSZOiXT9u3Djz3YutMxfT6Pr168v8+fPNSDmif5g5z507V8WfoiQRDgRnH1qd6I7fuEBYzj28VnwZFYAeyqxZs6R48eLG6Z/xURbsrIgk2O+0SCkhDIlK/PDDD+aLoSjJypElIifX3an5u3hA5ItsIhMbiSzp5/p+FbqLHF4sMr+XyIG/RfbOFJneRuT6eZG7ukbWBG79UeTKiai7IMD4HrRq1cpE7JYvX+62lzFhwoRYBWCFChWMAbRjbeDGjRuj/u4KvAPx7qN2cNeuXdK7d+9okUssZ+JjM6MoSkyOXTsrl29dS7ZNE26LMN3FvoymgD0MxB0eYUwLsHYWce0kLMF3+fJlYx1BzdLPP/9siswVJVlY/2XcVi/OIOV740L064gAhl+PXCJvJLJ5jEjN/qaWDn89RJTF5s2bTUr15s2bZjIHi3Xe1XV8lxjZxoKtCqd07G7fvj3W1WXerlWzZ8/Zs2ej/h7b95Lnti/R4LvMXOCPPvpIVqxYIbNnz5bmzZvHd+spinKbXRfu/CYkFzsvJv9zpCYqAD0Iogx0ByLgIKHRAUsIMoCeqQTz5s1L0MgpRYnnB01k/+yEiz/ALqbhJ5GRwF1TRdKkE6n+ukhIFpH/Prv9+BEi++ZIuyFrZNq0aTEe4sSJE9KoUSOXUTfqY5m2YX/Kd4tIIgdJiLKEEFtEPa5oO+tKKhhfv59++skIP6KB1sEd9byKosSE7yyzth2XCxcumNONAcdE8t6Z6pEcXA+/Kbciwn12OogKQA+ConHEX1JTuAjHZcuWybPPPmtSworiVi4djBnFS4gAJG1z/xcizcZEXnftjMj01iJHl9253cn/ZPeuoi4f5q+//pJSpUrFEHtE9RCBFnjxMc6NWrx06SKHviMAEYJE4oiYxwb3dxblw+bFPhIYGx9//LHpALYXe9bBHalkHsuKTloL0Xv716EovgD7NhoaDx06ZBbKIKzzLHzfLKFHDbwr+G4UaVNdCvaInLWtJA4VgB4CUwiIDrgSf5UrVzadg3QV5sqVy+xM6Aj+4osvTGTBEXYw1Dd16NBBWrdunQKvQPEbzu5I/H3v6iZy70iR9aMiu34DQ0TuekKk7QyRGe1EDkRaM0jYFdm4/C85dklk8uTJ5jO+cuXKaNEBal7j4vvvv5dXX33VePnR0IF/H124iC4aSuKCObx0AFvj3iz4Hlrp6LhgJ+cq0keHsDMQtAULFjQ1hCzWeftThKmKRMWTIDrnStxZC2UZ9p9z6zNOM2Pt2rVNtNx+yZIlS4zr+D7j8/f22vHJ+nrSBYX4bPQPVAB6AIg+onWkhVxNIciaNav58uA7Rj0UX4BHH31UfvzxR9NhiDh0hMfjcakxwn7CEYxn9+3b5zKdpihOuWXV6iWQtFkjI3+bvos0j7bYP0fkkX9Emnwl8l3xO9eHX5d8+YrJCy+8YBY+/3Tj0lVbrFixeD2lJfKIJmDjwveF6FqNGjWMQXNckIJ+5plnjFHzxIkTo64ncsj30F6UuoJ6XqZ79OvXz0T47cXk9OnTzfQP0tP2C1ESDKN5zdQgUvPI89n/PhDRjEskInRVJCrugIMY6zPpTOBxmc+u/f6HTnnr84llWeHChaMusxDMSOzns3SWgk6vr5mrrKRPEyKhOBKISNGMeaRRvkrm/PIT2+RGRJhkDckgVXKUMNcVz5TPnNbKXU7O37ws529ckfVn95jryrh4Dl9BR8F5AKtWrUr0oHc6Iikyjy0aMmXKlGg7O3YiDK3v37+/Oc8Xm52S4n0gbJYsWSJr1qwxUyS4jNjnoIAfXMabIQTcyv65IlNiaVzAEqbX6Zg+gPlqinRZEen1t9WhNKHhUJHqr4l8ltFE/6Dr8iZyK22uqKYN6xTi0/jBKV3DbBtnlC9f3tTjhYWFxfpyLduWvn37yu7du01EEFHIARjNVrGBULVvIuG7joXT4sWLzWW8PR3nAruC7yo1hdZO2H5nbJ0/evRoNJFIDbAzkVi6dGmpWrWqObBUFEewFKN0wn7BBN0erMnsxZyjuGP2NSUZSW2KJANAeQefXZY8efKY/RWBk1bz3pZLYdGj6xPve1vyhUaWaDhijXtD/H1e+3mnt1l3ZreZK4wNTMfiDeW5cr6bQdMIoAeA1x9flMQMoKfAnC+iK/iiMJHAEoDUHHXr1s2Ms7JgJ8mX1YIvFkKCH4Hz5887PWUh3G/tbJ0t7FidXc8OiteLULFOrcX+suPf2JmRDmCnxWls51l8WdQiKkaOHGl87HivrNfKtuWImm3H9uc8/pGMHGvSpEmsj0ldHNMusBTCgsgRPhd0zS79c5H0SMxKXz4aeZqvVkwByHXXzkaJvxsRQXL+Zlq5eOaoWS+rgYNTXpNjk4erUyIQ9gKQqASvg057avOIflN+EVvdLd8dIuxE8YiosQ1o1sIEOjZ4rjJlypjHtqIcRB6J5iEqiQYS/YsvvMcc7LHwOM7g/T9+/HgMkcgpO3Cip4hEqwaR9xkhiAi1lth+TxTfg99/R7FHZgjINPH5IIvEbwMHltaBhFVTm9zrxgGX4/eK9eI7/vTPA2RZwF6JsPMCfGTBoDgfd/2ZPVJ/5itx2sA0LVBNfBmNAHoAFLMTWYgP7Ej4AmTLls3U9yEC8BcjzeQKvizsFN544w0jBh07jKm7QHxaAo/FlRglfYbQ4vkRWYgyvojWglCzv+xsYf15fBZEirXEdfnq1atGdLKwjpxirOsKIkasKzs0a8fpbCEN4S2juKzoLT/GlidkXFgHF4888oipGc2ZM2eM2/BYpDlJSVqlBdb1RJlJn9I0wci0dOnSypn3wiU0jcNzF20uEpxBJCSTSPNxIjsmRi6w78/I5o/WkyMNn9d9HnkdaRr8/0q3F1nytsjK26UMBeqJdIqMkiUFxBdRQ0SylZKinpCmEPj2229NNC85YadJ7SGikVre1E7J8lkg8um406fwHthGjqKQHX5qr7eS9O8C4t/xfefgAPg9t95vsgecUpeX2gfSfGeoxXU8SON3bday+TLwRCzG84kkUAKkXNbC8lW9l8SXUQGYyrBjYgcV387f0aNHS8+ePc15om9Edr766qs470cKy1UqjGgC00YsYWed2p/nlIWoiifBNrBEob0wtBZELUeR/PBZC2k0ewHMDxy1YvaikJ0g0RHEOT+CnpAqIwJGI8Pff/+dqPvzOnkvuT8/qvYQ3bImbHA7pm4QLUL4UdvD9mjbtq20bNnSRM1C/+4qsme6SISdCOyxTySLi87db4tGmkUj+Kr2Fin3uEiWYpG+gOd2iqwbJbL9djo1IFCk9nuRo+XcAJ9tdiCYSQ8bNiwqjWx9/3jv2bbuBLFJ+pcDMyKFpLHoGCYiiBBEECYk+pfc8H0g6kNmwF4cUIsINJzYC0IEYokSJbzmwMnfYH9Cjbej2OO3z3o/LZFnCT4+r54k8skWESmnUYp1d7R6wiOUGd0fb5wosw6uNOPb3MkXdV6QStnjV2vsragATGU4EqceJ74QfieixUJ3L9ELapPYscUGo6uwzsAbkLSxfcqZqFCvXr3EX+B1O4pC++XYsWNRlgQWRM0QgpYgtD9NCXFIpJPuVex9XDUKxQfEHZFR6gatKRYzZsww4s4RdhL33XefEZ0NGjQw9yMCbBqKDv4jMuk+SRYCgkSeOSiS0T0zrpcuXWp2Jvfee6/Tv/P5J4rubhDRpN+BCLYlqGksIdqGMLXEoLOUuyeICBpPHEWhFTFCSNtHCjlftmzZJNd9KQmH3/R//vnHHORb75NlUUR5j714R+x5akSX3zaEHc2OHDRxAM9nCscLq5SCzxf7Mat58UrYdXls4WA5e+OSW0RggATII8UbSO/yD4qvowIwlWHMFMXoieXLL7+UHj16mKgVPwKu4AtDDRhfsAULFhhBSHMIO0YiP67sKPwZool79uwxIp0UPafWeSsyYgklSxAS4WHHToSNomh3/ci+9NJLxkvOHaPDEIGsGxYmvD6iw47myNT3vPXWW2butCO8pvTp08nlL0pIwNltkePb3Cn+ynQUaRXT2ii5YJsiDhGKSRHX9tv3iSeekLFjxzr9uzUPGDH4+++/m9IGIhmk6ImwEhn0xJ2zBZ99R1HI58j63PDZZ+eMGX3dunVN2YfiXvic0lA0Z84cs1h1rHyv7cUei319tydCXS/ildfBwSgH4ZRNUPvHguXSgw8+aL4rRJwpU3G0Nttx/pD0Xj5KbobfSpIIDJQAqZSjuHxS4xlJGxTTOcPXUAGYynA0TVQvsdDQgZiji5gfBFdQx1WrVq1o15EiZeZwnTp1zBdOiT9sO0sU2p8i6DlqBSKDlhi0lrvuuivB01noGCUC5wrEC+PSeB/5LCFciQSQ1rVPndjDDymikgYky7qB6xAelgiiZpRGCWfwXEunfibyU43IyR1uISDSKqb7dpHQlG1EIDVGLSyR38Q0Y9mLP8QcaXZqb+OCFDS1laSJiRhS0kB0hqJ7BFTjxo09ovwgPt+H9evXm88bYoRoJ1F2osZ8Pq3XQ9pYSRwIIw4cEEpkc/idoaSDzADbl1P7sYOeCkKVkgxLvJKNIELOATQHQIg+9mf2B0GMTHzggQeMrye/dc7Ycu6AvLrya7kWfjNaU0hCqJ6ztHxY/UlJn8azSp2SCxWAHvBloPjW3j8pIfCFoGifOqbYIoDUInFUzpfMk6ML3o6VNtuwYUO0hQ5M/mZ1htqLQhaO0l29LwgKIi6uolP40xGFxCMPKxiaWjA/JrLHTpeja2fwfPhEEoFCZBCZ4jwLIhLxyiQZ+2kXrD/rSyradAEuHyiy7F03bT0RaTNVpNRDkhqQ+kdwIeITO40HsUMUw77OML6w3Ul/WTt5uo3Z3hy48T6ykyd9l9pF+fGNqiIIrdfC5wVhjQC0xCDbCoGoOIeoPNuN7YcAwsGB7yy/B2xDygs47w2fB8QqB0WW6EPMUk5CiYn1eWDfFNdBBvvK2Dh9/YIM2TBRVpzaJoEBARIRj+9xUABxvwB5tlwr6VCsgbnsL6gA9ADuv/9+s5OObadD9y51Q0T5iFZQk0YXMDVERGmoA3QFNVuW1xk2FjR9sHCUxQ8IgkFJXti5k3J1FIaW8Kemk/fDWnhf+LHDJw4hFxu8f/YpaSD6RESS53Rl/8KOA3PigQMHRkWj2NFQf0NkmGgU6ReO1gExwueHHTtNIQY+s/OfF9kwOglbB+FrizSJrpK6taiI4Pfff1+GDBlitk98ooHcjrok7oNhtbsaIyjiR0CxsPPk+8/25/30pogPsO5Wmo/XQ8MJv0v4VFrilgOOlDw4JV24/ORW2Xxuv2y/cEhOXTtvBEOm4PRSJmshKZulkNTLW0Gyp024mE8sdNlbIokoKs1J/DawfVh475118XviAQC/XdZrWbFihbmODIj1WujET46mQvajS09skUn7Fst/Z3aZ69IEBMmt26UqRu6R6bBFmEkfrQrVMMKvQAbP367uRgWgB0AdH0XosQlAUr1PPvmkqQ8iWsMPAwKCFJ6zUXD2OydSeZjPkpphcoG1WE0ORJ8cI1I0pmgxd/LC+80PPu8jKVveEwQ+O0t+oCh+BqKHialNYweCULMexxnsXBCBCL+FCxeaqANRJtIwNCdwf0Tgli1bzOeBCBWpUocXIrJqiMjS2/WCtlsJq/lLEyrS9FuRsh3FU+D10hwyfvx4Y5RuFZ9bhegIQ87zXSSK+txzz8VrNF1i4QCOz4clCPm88PyIJgQUC2LK07r0ncF6c3BiiUGEIQdIZDGsdGZyCp3LYdfkpz0LZMaBZcZEmIgPYsAe6zpOG+WrLF1LNZFimeIeHZhQ+GzhC2kJJZod+M2mxMKK8vF77A3d1qT8qTW33lcyUoxtsw5Y+IwmpdwpMRy9ckY2ntsnOy8ckmNXz8mtiFsSmiadeS/LZCkolXOUkFA/Sfc6QwWgB8AOnx8/V/NCkwI7K462HXdO/AhjJsxRmn1EyurwI73H0ZqjMPSGeiRvhqNkBJ8l0knxs3NMKPzwEkGi4Qd/v9ggEkM6jp1Nq1atTEOLPUy7oMyApgYOQlxyaqPI3KdETqwRCUgTuxBE+HFEXqKNSOPRbuv4dTdEaPlusn2ozUMgkx5v2LChiaJTZJ8aooudK3VgliDE55OUmn29nbeUexBppg7Mei1WqpMDEeu1kAZ3xwHpipPb5MP1v8qFm5fj3SxgpQS7l24uXUrcG+tsWEQQBweuIrP87vL9tgQfB11Enfls8f3j9ZIRiivV6QnwOonsWa+FfQnwnbCifLxvzsaQKp6BCkAP4e2335YPP/ww0bVHzuBIkh03IiK+EBXkB9heFBINsbpE6TKzmhksGxQWdpLesLPxRMHHzttZDSB/Y6duPzw9vkyYMMFE8PgBdtUIYsFECqxeYoODiHjN3+Xze3yVyIavRA78JXL5iMMNAkSylhAp0VqkUk+R7PG3QEoNKLfgs21tI+ryiMJTekGq3BPgN4PvrBV5sYrqeb8sAUWtVWLqElMD6sOIJPFaOKUGlQMa6jN5LQilxESSft6zQEZvm2nqvWyJ7BStkauMfFD9SZM6dIQDar5vRNUpm7C+z7w/iCMOpLAAIupPZzSNXVaUz9M7v+0zFhxUWo0o1OVRf2yl8YngMqpN8Q5UAHoI7OQRVqRG3GFFQcqALyYpBTrFkgI7Ex7HXhSyI6Rj0hKs1JwhCJ155cXW4ODvkP5i50yaFjsfq6EHSPMnZqdN9y/2LZQVkMaMCxo9Hn/8cUkWrp0ROb9HJPymSHCoSLbSIiHeU/iPmKJWiR06vonU+GHHQzQKUez2OctugM8NnysrosZvCutr79fHKa8nJcZ5JQV+CxFPVjOJVUtGihQRTh209X2JjYl7/5XPt85I8vpQP1Y9V2kZck+PaJFARCvijwwKv4kcdLFtOUhg4T1AGBKNJ8pOQ158usRTC7Yx6+xoJE0zB/sW6pStKJ+3NCYpMVEB6EEgrPDNIhWcFL83xBZfSH4wSSckF6QuOOp1ZofC9AhLHBLFsgQhR+7WtA2EoXUeoeOPIhHvOWq3wKrz4WiaVCs7iYTOZX333XdNE0P//v3lo48+itd9qHPr2rVrItbe98Fi6amnnjINMkTB+czy/eS9ok7SGpnnyeDRh4CipICdOJ3i/L4gConk25s5cxDqyZ25pN8t2xxeE2lIvieIQWY2O6sb3Hb+oDy7ZKSJ2nUr3URKZi4gpTMXkKxpM8rYnXNl3M65Me7D358r11rKZytiagH/O71Lvtj2uxy7GtkR/3SZlvJEqcbmPBFKBCnbmfWxmqWsGjjWq0uXLiY974l11awzB/j2Qg/XAatBjfIhe19BhC6vT/F+VAB6GLT9ExFiZ5OYdDDCDyGFyXObNm0ktUAcEiFxFIZYpHC0TOrAHo6G7Uex2YtDzluj6KiN4UfV24442eHyg8oRtDVzmVPqgWjCcNXdy3ZyNGmOS/xh7E0UML788ccfxmPLgs8dlih0ECMO/LlLnPeG1B31lJ9++qmx17H/XtK0Q8e2N4GAJaJpv8PnMp8zfjuwKXKc8JHULEJywPeHlCqG2jQ8IbxIEyMGmWzDbwWdvk8u+kQOXzktudNnkbENXpM9F4/KoSunpHXhWk4FYOEMueWben1k18UjplkkJDCNPFW6uWQKCZXuiz6R8zevmLrAsfVfldyBmcwBHNvP/qCdujcODvgN9qQoK+8xBwDW+27VgFv15xyoOxpJk0lSfBMVgB4GX0rC6xzJUhuWEPgB5AvMD4+n75SIqCAyXI1i4xSxyO2cQcSQH3hLFNqft06JZPBDzMKRd3zPs4Pnh5KF9Ld13nGx/5s1k9gSdtapdZ6/xTeqy06Y1/fJJ5+YOc9x1fBZNaTYubAgBBMCNT1EL6woAEf/lpk1qeSEiElfo3379ub9I9pETR1lD46mzxy0eXv0ms8w/of2ohC7H6sBCaN4x1nA8Um9phQ0XzA6jMggxul8j6mtq/pYY/k73d4Yt88SnEFmNhvoVAC+f/cTcneOktLxnw/k6q3I+ts86bPJL/f2k4l7F8lX22caAdgwXyX5pdMgc3DrDCZWMMEiNQ/CLaGP0HMU+pSd2L+nVapU0SY/P0MFoAfBjy1fRKJh1B59++23xuMPIWTv5WePNdOXozQmO7z++usedcSZVIiaIQgtEWWJrLjOs1ALxTZzZ2ONPbwnFHOzcN4Sn0RLWKzzsZ2ykOZFcCEoEInPP/+8aQhCBFJzhgiMzY/ulVdeMbOgsXIhAugIqT9X8NzsKCzrGcdtRbqNmiV/BZsVy6vOfl4y24qF9wuPvuQstUjN+jvEjWNqkO+Z44xZBCHzjKmJJD2YmoKYOjxM0RGD1x8pLplK5Y20moyHAETYzWn+ocw5vEaGbZoc7T7Dajwj+UKzS5eFg6NuW+iPs7J+6Wrz/aRhyDpwAr67n332WbK+Vp6Xg2VKbjg4YbGEPM17vIf8rpDqtxd7np7qV1IGzytI8GNIL/FF5svLuLAXX3zRFNki7IjskW7iy80RHIKD64gWkjJm5+SLMzcRQUntXuRHECHIjyWnjucdLxNJtRd21nn7hevdtZPDa48dB1MSqMez99mjKYSmg9iw5mIS8WBxxNV6smPAXxJLEyJdjjZEViOR5X3nj3DwgajhM2gdnCGoiZ5Q94WQp5nCF+HzwetkoYbNvhPUXhRiUk8EzoLfLmp92W6uTtlu7vhM0eREExOzzPmt5DF5/Jdfflm69Owm7edHmpzHl/yhOUytIGliR/ZcOmYaQEgJ34y4ZcaNPdyvh0wocmfmM5kAPjOIUERXUuDgAoN3RJ29wLO/zHPZZxYoj7H2C3hT8pnFxzOh4ycV/0AFoIdAHRaRntGjR0cZ9xL5o+AWcUD9nM7RTPyOzJNrBjHpJt3PTstRxPNDbhkxu0ohU1yeGHg8TIyJ3JAi4kCCHY7Vhc7OFDFKEfgjjzxiGkWSulPzJhA71rxVto3lc4bNBYKZ9Li/wWeCVDiL5S/JdiL6RZ2kJVAQQJxS40p9HlEq+88vjWGWIHQlEomOxyUSOShmYYYs3dqUTeDPCNvP30nXx5csIZGduZfCYnpvXrx5VQIDAs2kkDM3Lpnz5jnsLFbxhCRdHtdsdbYZWQpHYWcv7tiG9vW/PLa1vajTpN7Rumwt3uAfqHgOKgA9AHb+3bt3N5EcdsjAjwA+UVZKgR9XFYC+SWwduOwASe/ir+VuLHEH+JCxI0Xo0LzDzpryA6Jb1DKNGTNGhg4daiwfWF86YL1hJFVSoIQAMWzfAMGOmxSoGqJH/4xSD8jCAYsziLDzO2cJQ3uRiKUUnnKO0SyirZYgJErONidtaWUFWHAhsEoXqMXk+WloYizf7qCjTqd8xIfYqkasP/G4W8/uN6+BEgoWRJ113n6xruezw4E99+HzZcEBKg1vlpBDxNoLO/xX+b75ayReSR5UAKYy/HBh+UG6jbFufMFJsXA0yw+iBT907JwV/4NRSngEYkniDo9IdjakhKwdJik8hB07muXLl5t6N1J7HJBg3YP4pAOW+cCYilNzSLkCtYGIQaIvvlh+YB182Ys96iWJynhiV6wnQ60yYo6FrIYrkWilT+0FIgsNSggoaoIRTpw61sVa3w3qVln6/T3amD4nhAs3I5vOMoeExvgb15H2ZZScxbZ9u6TwfYWdPhYClZSs/UKErnz58jHEHeLZEy1iFN9GP3GpDPVd+PX9+eefpiCfbkzEHzU11g8a9WYIQMV/QYDRlUkRflJEIOKPVBJGwTzOM888Y6INFKzTQUyUgdmkTJawHwnHffAzYyFNjDUKYpDpGNyHiCBikJojX4lSWM0O9mLPEoUqAN0PAsgSRTHmTTs5cKbejoMPPstgRQKJHNJ9azw0D+5J0DocvXpGrofflBKZ8sX4W/FM+eTIldOm/s8id65c5vfbUegRqfTkshNFAc+fMO3DIPbeeOMN0/VpFe8PGjTIHAXb7+Q5T1pO8V/YoZAmS0oZADtYdo7UZFWvXt1E/9asWWPSZXScE5kg3ctz0eDgCnwBaUwiSohQRPhNnDjRPCb1iqSK7aPX3oozsecsKqikPIg93A7so4AIxy+//NIcoPz000+SK31WE7FLCKR1l57YIg3yVZL0QXdmPOdOl1Wq5igp/x7fFO32RbLnMxFzBCv1sVYdnoo/xRtQAZhKcKRKlxYF5YMHR9oKADvP4cOHm8J88wYFBpq6GFIgin/Dzg4BQpMQO5j4poysnRFWJTST2KfgiC7ThML1WEMQ0SN6Qg1qfEDwUXhPuo4UMTtBmiOs4faY9Dp2F3uzAHQWFVRSD2pX8a/jc8YBNb+pVsdrmSwFJcJh5m/NXGWlUb5KUjdPeXO5aMY85jJL2sBgc93YHXMlXVCwfFyjh7l9/bwV5eMaT8uFsCvy296FUY9FfWG5rHYdIIriZagATCVIoRHR4YjV3o+JdBrdoOyMKcAnLccOX0fvKH369DEikJQX6eDHHnssqvbOUQzaXyY6gUkuPoGuZtfStUgnOrdbvXq16TJkCobjxBZX8Hyk4/BeI/rH55r7khrGL65v376mE9SbsMSefbRPU8CeBfWrlEV07NgxxncAARjoUI7wasX2MrBaN+lXpbO5fF/+KuYyS7a0kb/DB6+clBeWfym3IsJlYLWu0r9yJzly9bT0XjbKTAGxjxbelU0FoOK9qBF0KsDsSEQd9h3sMB05c+aM2WkSWcELUFGIrtHdaM3tJYLMyCuMet98801jUcLoNorjqdcjgkxjB53klq1QfOEx6ACm+5iUMaPl6E4nWphQsAEhvfzNN9+YSCCilYgj6WZvqLskmmnfrcmUnccff9yYtqu3WupDeQxzr3k/rIlAVh0en7ddd0XI8tPbE9UJHBcZ0qSTGU3el7RBCf9eKIonoAIwFWC4PLN6sT9wNk4J93i6LLELMIXMil9DJI3UKulWmoXY6dEVTBMGYo/O1OSAzx9j5eg+xlyWUgVSxIlp8uA1IAJHjBhhIoGIWepfmbLhqU0j1mu3H//2+eefm2k7ybXNlYTB+0B2hFMigJTL2NdP9/zwddlc0fUUncRCZPGRYg3l+fKpN29dUZKKpoBTGDosx44dawrvnYk/fsDoDMZkVcWfAgglBBTpLiIdDJhn+gFgSeIOaxhn4L2G/x/pZiKKfCbpUF+xYkWCH4vIDMKJZiZEFV3tRCdJT0+dOjXZXkNSIN3r2OxhGUMrngGNIETEqZVmio/954gSmk9fHiD181Qwps3uAmuZTMGh8nhJ3xv/p/gXKgBTEI5SSaXVrVtXnn76aae3oU6LtB5dloqyYMECEzkjJcv0BMa2zZ07N2pmL6eUFCT3PFysLubNm2fSoYg2JoNQdJ9QqFlk/BxD6fFqI4KJsKSYH4HrSQ0j1AA6ij01gfYcsIGh+5zPkr3wo+mJSSUcbCMQX6vUQUKDQiQwgZ6ArrCJTd6s1FEy354aoijeigrAFOSjjz4ykQ92dByxOoMU2T333OPSLFXxH2j46N27t4m6YRaO8KLWz3EkHGO4UsqQmuenDhHDaEQbjSnUrCYUPv8YSbOTJqKIyKSDk2aUDz74INlFbXxwFu3TCGDqQ0Sa2mgmZ9D8wUEQn0WEH58r6lY5SLIa57KnzSRDavSQoMAgt4jAHmVaSL28vjn/WfEvVACmENu2bTMCkHSeq3mqWHH8/fffZqfqqXVRSspBjR+fG5oRoHTp0ubU8bORUgIQ2MmScqO54/333zflDHgTYl+U2Lo4/AjpPsbqCKNpOt+ZjsD3gBGIqYWmgD0HDjKov6xatapZJk2aZOpg+X4sXbrURMiJAvLdmDFjRjQTc6iUvbiMqNVT0qdJm6h0MDV//OtZ9gHpWqqJG1+ZoqQe2gSSAhCxadSokZmFiXEuaQlnkB7GioNRcL44WkuJP9T6sROjTu6XX36Jup4IHIKJz9CVK5GWFJjedunSJVU2LxNrBgwYYKLa1AwSvcP6xVWEO76PSR0sC+O/nnjiCfMcrixs3Akigu8pz9u2bVsjupnTTQc0voZ4KfI62eZK8r8XWGVRM4pBOb+jjCfk/WjevHk02xf+1qFDB3MA8eijj7p8zDPXL8rQTZOM2XN85gQj+kj5FgjNIW9XfVQqZCvq1teoKKmJCsAUgBm/1PwxgcHVPF+OcNnBvfXWW/L222+nxGopHgwdt3ShEuGwn/7x3nvvmQYiDhJWrVol06ZNM359jhGPlIaIIHY0rA/pXBo+SM8lxjrGAoGLhQyikvPMICaCjsVHcsFIPISnMzC7Zi4yIpBOfSV5IBI8YcIEEwFnm5MxQfRhIeSOxjhSxv+d2S1T9y+RJcc3G7NoInyBtxNiCD5LGJbKXEAeLlZfGuevqnYviu9hU5KV48eP27JmzWrr2rVrrLf76KOPbGnTprWdPHlS3xE/5/Tp07YsWbLYXnjhhWjXnzhxwpYxY0bbq6++avNUlixZYmvZsiUdKrZChQrZhg8fbrt48WKSHvP8+fO2fv362dKlS2fLlSuX7YsvvrDdvHnTlhxMnDjRrLv9EhgYaKtVq5YtPDzcrMOIESOS5bn9mZ07d9oGDRpkq1SpktnmmTNntvXs2dO2atUqW0RERLI974Ubl20rT263/bDrL9uITVNtwzdOtn29bZZtwZF1tiNXTifb8yqKJ6ACMJnp3LmzLUeOHLZTp065vA07swIFCti6d++e3KujeAGvvPKKEXoIPnt69+5thOGZM2dsns7GjRttTzzxhC1NmjTmAKh///62Y8eOJekxDx48aA6kAgICbGXKlLFNnz7d7eKAx6tdu7YtKCgomgicNGmS7cCBA+b8rFmz3Pqc/squXbtsH374oa1KlSpmu2bIkMHWqVMn29SpU21Xr15N7dVTFJ9HBWAyMnv2bPPD9v3338d6u19//dXcbsOGDcm5OooXsG/fPltISIhtwIAB0a7fvXu3EVODBw+2eROINiKWCFpe19NPP23bvn17kh5z3bp1tsaNG5vvTP369W0rV660uZPVq1dHE3/58+e3hYWF2f766y9zGeGiJI49e/aYz/Ddd99ttmVoaKitY8eOtilTptiuXLmim1VRUhAVgMkEP2bFihWz3X///XFGKYg43Hvvvcm1KooX8fjjj9vy5Mlju3TpUrTr2UkSJfbWyMi5c+dMmUPevHlNBO/BBx+0LV26NNGPx3eKA6wKFSoYIUHkaO/evW59H1hPHvvjjz8213355ZdGhCMGlfiDYGYbVq9e3WzP9OnT2zp06GCiqir6FCX1UAGYTPTt29fU9FHbEhtEL/hRJJ2l+Dfr1683omP06NFOI1JjxoyxeTvXr183r6Ns2bLmNdWtW9d89qmvSwy3bt0yj0eUjggj6XN3pMgPHz5sav9Yzp49a67r06ePrXTp0kl+bF+H93jevHlme5UqVcq8z9ROPvzww7bffvvNdvny5dReRUVRbDabdgEnA3iXYR9BRy+dnLGBZQGmukz/wGNN8V+wGcEofPPmzVHdsxykNW7c2Hj9bdiwwWc+I9h2MAkE/8AlS5ZImTJl5LXXXjOdnq5skmKDLuHhw4cbPzjsQeikx0SbSSOJBR/CY8eOme9wxowZpVevXsZnjvVWokO3LnOqWfAy5f3A1aBly5bG8Bv3A7ahoigehMpg99OtWzenaTxnUQZSSp9++qm+DX7O/PnzTaRk8uTJ0a6fM2eOuf7333+3+Sqkgtu2bWuin7lz5zY1gzSRJLbrnu5RmjiKFi1q0ozxbRThdkTke/ToYStRokRUCti+G5g0/MiRI01K258hDb548WLbm2++GdW5yzanJpNUP+9fcnbvKoqSdFQAupktW7aYHcXnn38e523feustUxyPzYXiv5D+rFatmq1mzZrRdppcX7lyZbNT9YedKc0hWN/QNY+gqFq1qrFcSYw10tatW20PPPCAeRxsaWiuiQ3sRng+bs9BmaMVjLUgCllIaVLm4a01mQmFzyKijt+19u3b27Jly2a2R86cOU29JI1sVqpcURTvQAWgm3nooYdM5OHGjRux3o4dBz+ejl5viv9hdYEvXLgw2vUTJkww1y9btszmT/DdmTZtmokKIsZYaBrBHiSu75UjPE7BggVN4wGNCI7+gdQQYlGDqHO0folr4UCPSOGaNWtsvij46LZGgPM+WKI8ODjY1G2+8847thUrVpjtpyiKd6IC0I3wg8iP5A8//BDnbb/77juz04mrSUTxzfQZqUrrPCKiVatW0W5z7do1W5EiRWzt2rWz+TP4Z3722WcmQsp3CyGCHyKNMfGNimJE/fLLLxvBVrFixShBzbanu9ox1ZuQBdGIuHQU794GQg4hO2zYMFvr1q2NdyOvj8aaBg0aGMFHmYJ27SqK76BNIO6rpTQjok6dOiXr16+PtVg/LCzMjDcqW7as/P777+5aBcVLGDt2rDz11FNSp04dqV69uhkrtmbNGqlWrVrUbT799FMzTm3Lli2mQUIRsy0YD/bjjz+a5ozy5ctL165dTeNI/vz5o20iZvmyjWnkqFu3rrnuv//+k2eeecac9uzZU65fvy7jx483392kwNxjmk1Wr15tvtfeAPOO+cyxMFJw6dKlZpvRgFO7dm1p2LChmV9uzZ1WFMUHSW0F6itge8DmnDFjRpy3/eabb8xtSbEo/se4ceOiUojW6fPPP2/btGmT+TsNBtmzZ7c9++yzqb2qHgmROzwA8f6jFo/t16xZM9vPP/8cVZP3yy+/mG2LFdPMmTOjRbqIKHK/2CJ71OYOGTLENnfu3KgaxP/9738ub0+amhpCT/QIZLQgr4NRa6RzSYlb600ZSvPmzW0DBw40TR1YuCiK4h9oBNA9IlruueceCQkJMUfSWEW44tq1a1KyZElp0KCB/PLLL+54esXLwCoDawxHsMk4d+6cvPPOOyYquHv3bsmXL1+qrKO3cP78eZk0aZKJDPLdy5AhgzRt2tTY5qxcudLYzfB95O9ECq3vYJEiReT06dMuo3/8nUg+1js7d+6Up59+Wt577z15//33Xa4Lz4MNDXY2qcWZM2dk48aNUdE9opL79u0zf8uSJYuJOFsLv1mFCxeO9fdKURTfJU1qr4AvMGXKFFm7dq0sXLgwzh/TL774Qk6ePCkDBw5MsfVTPIs8efJEu8xnhgXRt2PHDhk2bJj0799fxV88yJo1qxFnLAjmyZMny/Tp0434s0DkPf7440YcvfTSS/Lbb7+ZUo24vDyzZctmzufIkcM8flzwPJ988olJO+NFmFzwPAjcbdu2ydatW6Mt/LYAQvjuu++Wtm3bGqGH4CtRooRJVyuKooBGAJPIrVu3pEKFClKsWDGZPXt2rLe9cOGCFC9eXDp06CBfffWVfgL9lEOHDpnICyD8iBxzENG8eXNTF3jp0iVZt25dkkyM/RkiX4geZ3Tu3NmIbKJ7RAfjAwKQaGFcEUCLqVOnykMPPSRJJTw8XI4cOWKEnqPYI1IMGIZjOk89pLVY9cW+YhquKEryoBHAJEJqiR1KfNK5RAeuXr0a53QQxbfJnTt31PlMmTLJvHnzTLE9kT9SdqQyVfwlLcUORLsQ2AgpQGjT/EATSHJB5I/3Mz4CkGYwJmjs37/fRBwdTzlQ4AATaMQoV66cWZgYY4k9DiitqTGKoigJQQVgEqCLkKhAx44dpWrVqrHelpQNnZ2koBw7FhXf5daJM3LryAmRW+ESkDFUQkoUMuKO6IzVOUoEh1GAjC/j80EXpq9B2pIIOJG0mzdvGvGDuHHXKY8fGhpqFkbp5cqVy9TaWtExovREXYms/vPPP8n2OlkX0s901CI2+d5zykLn8sGDB6NE3tGjR6NFIfPmzWtqD4sWLSo1atSIOk80j/Ma0VMUxZ2oAEwCX375pflRj0893wcffGCiA3379k3KUyoeji0iQq4t/k8u/jBDri1bLxGnz0e/QVCQhJQuIgsee0kK9X5cipUubURAjx49zIHBoEGDxJtA8CBy+B5YIsfZKQsHTEmB7w/RLmenQHTdWhCE1PkxZzulQWTScGEPYp/aT0QoYo4mMMSdJfK4Xu1WFEVJSVQAJhKO8D/88EPjNVaqVKlYb0sXHjV/1A9ZheWK73Ft6To5+fIQubXviBF6cjv1GI3wcLm5ba8U2LFfIuaskZOPPiDTC6aVRYsWyYIFC0zxvidApywpyNhEHaeOnbSkXElxE82ig5no1b333ht1OWfOnEYMuRJyrk6JfsW3W5X1uXHjRjRBaC2UbIwZMyYqLZwckHr+6aefzGu2FgShdtsqiuJJqABMJNRrXblyJV71fKSJs2fPLi+++GJin07xYGxht+T0u6Pk4ndT2PtHXhmXwLid+rv040ypGH5DBrR71AillAYhtHfvXtm0aZOxD+GUhY5ae2GXPn16I+AsIcdBj/1l65TUa3J2wMYHhBbRNBa+d/bQrR/f5o/EQq1hp06dkvU5FEVRkooKwESA1QIC8IUXXpACBQrEelvqkSZMmCCjRo3ymOiO4j5sN8PkeNf+cnX+bduRhIqLiAjJFRgsXZYdlit/LZcMTWon6+fWEniW2GO6BtE+QLxVrFjReBRyim2IJexoVvGWCBbd+NgtYX1CLR0LkUegLjCpkz/igu2mKIri6agATAT4tbEzjE89H4X91PhQ46X4Hif7DI4Uf0kQFWYSbXiEEZIFZ38laSvHHP12+fJl6datm6kZ4+AjNkh1YhXiKPYsjzgiY1iFIPK6dOliTlkc/Qm9FUTtrFmzZM6cOVGpXuorqbNjvFl8wZaHgzbEL9BM8vDDD0d1GlvC2R6in7Vq1XLba1EURUku1AcwgVDIXqhQIbPjHDlyZKy3pQAdXzdmlz766KNJeZ8UD+TyzH/lxJNvO/1brs/7S+ZOLVze93DzZ+XG2q3RrwwKlOBiBaXQwnESkDYk6mq6RREjiDjECB5wVkcoNXjYxuBrZ4k9K33LQQrRKEvgVapUKSqy58sdpaR5if45g+8uE1e2b98eZySQ2l0O3pzB9XTzOoP6P34fFEVRPBkVgAlk7NixJprHeCjSSa5g50JN19mzZ83OWR34fYuIK9fkQNX2EnH+ktPoX5qi+SUoR9YY1+f7cYjYbt6UA1U7OE8XBwRItr7dJfur3aKiWU2aNDEdrZYnHF3n+MfROIJBMJDitASeJfaIWPlD2QHbhZFtixcvjlocJ30ghhs2bCh//PGH/PDDD9K7d+9kSQXT5EVzjPo4Kori6agATADsMCpXrmyO/n///fdYbzt37lwTtWGH88ADDyT1fVI8jIsTfpdTrwxN0H3S1akiBWZ8LmeHjZdzg8e4vF1gtsxSdPN0WbB4kbRp08ZEnR0bFzAErl+/vrET4ZTIlrfU6CUFhJ19s4pVx0jaG9FFvR/bBK8//PisFDAHbaNHjzYpWjr4SaXjS+hOEchBHiUf8ZkWoiiKktqoAEwA7FTuu+8++fvvv+X+++93eTt21oyiotZqyZIlfrFj9jcONegqN7fvS1DtX+5Rb0nGDk3l4D2d5NbBY7He9mivB6XBgNdjXM9nCYHD3Glfhvo66hgdxR6eg4DYs+oYWZikQtrX8tLDo/P5558357FrevPNN6N9D5nc4840LSl1xkGyjurnpyiKN6ACMAE8+OCDxjKDnVJsog6vMQr2//33X7OzVnyL8LMXZH+ZhEV1AzNlkCKbp8v1VZvkWIdXYr9xmiAJeKC+dNvxr0knMjWCNKf1mUP8EL3CbsTb4WDJlQ2NFfVk3Jl9epuF8ovY7Gaoz6MEg3S5s/pbIn+PPPKImdubVFsY3hcEIAd7CFFFURRvQLuA48mePXtMOvebb76JVfxRlP/qq6+a6IKKP9/kxsadCb5PxnaNJTA0nVz6aVbcN74VLsE7DpoaP/N8N26YGrdVq1aZhc+YN9WUIrZoXME8+siRI1Edygg+K30LOXLkMOKO0glL6BHlo2kjoZDiRVi6gu8wUUI6oxFuiRWBvA8skyZNUvGnKIpXoQIwnuDjh6lsXN28iD92Jsz9VXyTsD2HTLNGQtK/mR5tJeFnzsvlPxfF7zn2Ho46b9W2sXgSzOGNawycdZ75v/avhwYVBB5ztC2xh+dgcpdLsM7z5s0z00CmT59uhGLXrl1l3LhxRsglRAgS9aPpg3Ry48aNk3W9FUVR3I0KwHhA0Tg7DDoHmYjgivnz55sOQ27LOCzFN6GLVwIDRMLjJwBDypeQdFXLyfmvJ4rcDIvXfSJuhploX2hoaIwlsZM2EDekkhFBzk4dr8N7MDZRRyTSHmsMHMbRLIg8amUdp4UgulJyWggRSBpCMGT/+eef5fz5O/OZadD6/PPPpUOHDvLMM8+Y7mqEXWyj4vg725KDQQ70HKeNKIqieAMqAOPB+PHjTVF6r169XN6Gvz/77LPGauLJJ59053ukeBgB1N5FJCz6Z419iy83Im65TCkyH9deEBJRi03YWaeJTXNaY+AsEVemTJkYoo5TTxgD54wpU6YYgedM2D399NPmtEWLFqbWEoPnr7/+2qTfL126FO22lq8ij8V3HSGrKIrirWgTSByw0yxdurTp6iXV44q33npLPvnkE1PXxA5S8V2u/rtGjrV/OX43DgmWopumSdi+I3Kk+bPxf5KSheTqN/1MfRwzpzl1tVAjiPBiQRwm9tTxOjwEEXbeNAbOGXhx0hBCvaG9ACxYsKAcPHjQ6Wsjaogg5O+IZ7YBEc3E1CMqiqJ4Ip53uO5hMFKKBhCmecQ27/fjjz82HmAq/nyftJVKx/u2GVrWl6DsWeTMwK/j/wRpgiRT7SpSomLFxK2gEg1StNT7VahQIarhBIHbvn17l8KW67F1YVEURfFFvKeVMJVg3BupOFfzPYkQkg7ClgKvMcX3CcqWWULuKhlZBxgHmbu0kogrV+XytL/j/wS3wiW0gfNRZkriIoDM8CWVfffddxtxR1QPWydFURR/RSOAsUBkj8YOCsddgS3MsmXLjOefjn/yH7L0eFhOvTwkztsde+TVBD92YPYsJnKouEf8MUqPVO6CBQukVKlSRvjx3a5Xr55uYkVR/BatAYwFCsQpCqcWiLooR+iGZCQXReHffvttcr5PigeA+TJ1oN27d5c0tyLkwN3tJeLcxQQ1hMRJQIBk79dDsr38hPse009B9OEpiNcf4g8zaau+j7pKredLHuiyZlTm6tWrZe3ataZbnKgrzULUUpNRadWqVayOCoqiJD8qAF3AjxbzVd955x3p37+/09swSYDI3/bt240fmOLbUOfZt29fadq0qUybNk1m9h0o1X5d4r4nCAqU4JKFpdCCsRIQEvOAQ4k/NGPR2cu0lDlz5mhtbgqwb98++eCDD0y9NI1JHDTTgW6PdV2WLFnMATbfp5w5c6bE6imK4oDWALrgu+++M6d4gzlj5syZxv1/xIgRKv78BBoJgFnQpBI7jhos20rmijSFTirUEwYFSZ7R76r4c8PM7vr160uePHlk+fLlKv6SGeqgv/jiC9MlzRhMxB84ij/764im46FI0xzj+BRFSXk0AugEUkT8MNWuXdv8oDmCQS4jqkj/zp4926stMpT4cebMGeNzx2fDokCBArJu9Rq59cYIuTp3WYImg0SDsW5BgZLvpyESeq9nTfvwNn777Td54oknjB8n/n/YtyjJB4KO7f3rr78m6v78dvKdwkaLuc36W6ooKYdGAG/DZIMZM2aY2iCmBuzatcuMiHLGu+++K6dOnZLRo0frD5aXE376nNzcfVBu7jko4ReiG//ag9C3F3/AXNu7KleSeot/k7CH7xXhOCAogV+pwEAJypdTCkz/TMVfEiGi1KlTJ1OaQYRexV/ywveB30hEd1IeA0gdDxgwwI1rpyhKXKgAvA2zQNu2bWvqURjxxCkRQEcoasYa5r333lOPMC/EdjNMLk+bL8cee1P2lWst+8u1kUO1H5VDtR6V/SVbyv4qD8vxZ9+XqwtWis1ucgY1f87gQGDvgf1yvmsLyf/7FxJcolDkH9IExZ3yTRMkmbs/JIWXTJB0NdTzLykpSGZwv/LKK8aKiXGM1P4pyQsOCDRFYRg+ZMgQmTt3rmm4QdT973//c3qfF154QbZt2ybXr1+Xo0ePypdffilZs2Y1f+M3lWYdRVFSBk0B2wlAujvtoUuQsW5EFhgjhXcYHWycrlmzxmlnsOKZsFO6+MPvcvbDbyXi7IXItKur0WhBQSLh4ZKmUF7J+VEfCb73HjNyzX6KRGBgYNRoNbobiQZa6azryzfIxQm/y7Wl6yX82Knojx0SLGnLl5AMrRtJ5i4tJSinNg8lBerNunXrZqJQn332mZnXrSQ/Bw4cMCUwjMBkJN769etlw4YNsnPnTtPcgZh7//33o92HSUl9+vQxp9TRUjNI1I9sCwfbfJ/y589vBKJ2aCtK8qM+gLcpXry401q/P/74wwhAK03Bjxy+fyr+vIdbx0/LiZ4D5PrSdXeujG0u7m2hd+vICTn+2JuSvt39UjxfAbkeYJNDhw7dvnvk/TkwIOVo1S5xmr5OFbOYhzp7QW4dOSm2W7ckMGOoBBcrIAEeOC/XG6GR4KGHHjLfRxqyMHtWUoahQ4dGNXQgBi0XhBw5ckTNV7YHYffSSy+ZZhHLMB8RSMSQKCIinsY7DqQ4GCdSqChK8qIpYBcCkB07Y6AWL15sztNNyNEqtjA1amihvrcQdvCYHG72jFxfsTHhd77t73dtxj8yv0wT2bb6vxjvPVHB1q1bu3wIxsClrVhK0lUtJyGliqj4cxOkDxs0aCDr1q2Tv/76S8VfCnLp0iUj0siExBcmKTF+D19Ve6jVBHvxTiTXsd5WURT3owLQ7ggVoWc2SmCgEX9LliwxA+MvXrxo6gJJ/9KtpngHNHUcbfuihJ84GxXVS9wDRcjNzbtkV5tesnHdOsmdO3dUxI/6JyxHlJSDFCEpQ6Z88B3V7Z+y4KtozVSOL1ZNpmURY0EUkWi6vUn37t27jY+joijJiwrA2yD+MCe1ooHsWBCF8OKLL5pifwxOOYpVvIPTb38ut46edCn+QiqWkrzffyhFNk2TYgf+kkLLfpRsr3aTgPRpY944PEIy7j0qn97T3EyGeeqpp8zVltmwkjLwvaxbt65kzpzZROWxY1JSFiZ8JLQEZuvWreaU986eOnXqmANuUseOzXaKoiQvfqdmOMJkRBRHmNQQIfzwc6tatarpRiOlR00Rnm9AbRFegOPHj3daJ6h4JlcXrZHLv852+ffg0kWlwKzRErbnoJx++zOJOHNB0tWuLNle6yppK5eW40/EnP4SIAHSZN8lSXP8rOmAJB3suENTkg86sbt06WLSiZy3ukeVlIW0uzOT59jg95apSa+//rrs2LHDpO1pAvnqq69MKtmqqQXEJU0liqIkL34jAGnewLePbkFmVTpCSg/zZzz+rKNbCv6ZBEKRP2anivdw/vOfIz35wp03e2R6uLEEpk8rx598W27tP2quu7bkPwnKk0OydH1QArNklIgLl2PeMcImF8ZOlZwDX3Ba7K4kz0HbqFGjTAdp+/btjc1L2rROorRKipmiJwZmpnMgzUG1lQ6mwa5x48bRxDxi8Ny5c25bX0VR/FQAHjt2THr27GmGk5O+dVW4zE6GI9PXXntN3n77bRk8eLCJMmBHwFGqLzjU8xqp3aGIm4UuZ+u8s8uYYhMR5QfZOrWW2C6TEk2XLl2CFkx7s2fPbhbSQQyKT+w2D9t/VK4tXB37tgiL/BxEXLwS7XpEny08POrvMQgPl4s/zpTs/Z8xAlJJXvhMchBGpyg+f3SfkjJUUo/Ebn/KaFq1amWyK3nz5jXdw9jI9OrVSyZPnhzttlY9tqIoyYdPC0AsXB577DEjZCCurjWr84wfJSwLgDmVlsWBJ4KgY4rJiRMnzOLqPD++7EztUy3OoKkBMcbCeUQzP/gs/Cg7nne8jttzZE96HbNXVwvbOLZOPyI8liC0F4b2lzHrxoOPWk1OrajQ1X9XR07liKWR8NJvcyTLs49IrqGvypkBoyX89HlJX6eqZO7aRi6MnSa2q9dd3td2+arc+G+rpK9bNT5vkZJItmzZYiJ+hw8fNqPGOnbsqNvSAzAjENeti/O3xBX8FrEAdi/8zhDhteC3hDnOiqIkLz4rACdOnCidO3c2IiOxlgL8EPXt29fUedH5mdLwA4sv1t69e6MtHDlb4g5RZw8ijCNsfkA5yi5ZsqRZf66jcN4Sd0Q2rfP2gi+loiu8JwhySwzSaU1Xp/1Cqsn+MoLAOk+KyHEHhChEDL4WlkPqBgRKgM31DurWoeNypEVPyfv9B1JkzcSo689/M0nOvPVZ7CsfGCA3Nu5QAZiMTJgwwUTuqbvFdJ3yDMUzqF69usyaNSvadc2bN486eATq+yxrF6xf+I736NHDXN6zZ49J+dJARTNV//79jaC0oL6wWrVqKfqaFMUf8clJICtWrJB69eoZgZDUl4egqly5spkP7KoDmNQxgisxRemkWh0FnrXQbXrz5s1oR94lSpQwzvuIO0vkcWqdJ0rmDykyq06IFD+ecCzW+bZ/bpaiF2OP9jLlI9/k4RJ+6pxc+GqihJ85L+nuLi9ZX3lCrvyxUE71GRLLnYMkU6cWkvvTvu5/YX6OFX3/9ttvjTkwxsFMYVE8Bxo4mjZtGu26ffv2SdGiRZ3enus5aKVmljpOfr/4/iL6hg0bZspzHOG3j9spipJ8+JwAZAdSsWJF8wNiP7rLFRyB4kBPJM3V8Hhq0ZgC0q9fv2jXs+mYC8wc0meffdbMtXQFaVH8yzZt2mSWzZs3m1PSWxYcQRPxcLbwI0qtnBI3hxo9KTe37I71Nrm/ec9E8A7e0zFaujdT55aS+7N+cuTBF+T6MhediEGBkrFdY8nz5Tv6drgR/N9oFNi+fbsRfo6jGRXPgN/VwoULm4Mtd8MBNwfvCxcudPtjK4ri4ylg5kxyNBqf+hTShdyeNKvlAegMhB7dwZhB88NnCU2K0/EGBOsHi+fl+S2hZ4k9ZmRagpQj2woVKpj6RHzMSNMi8kjT+kKzSUrw9ddfm4jsvffea0y77bdbQNq4PcrSVigpYTv3x6j1u7FumzkNKVvMtQAMCJAAnQPtVqi1Ze42kWwi+ETdFc8Ekfb888+bqUiJrQN0Bb+ROgZOUVIGnxKA1I4wRii+P0p09y5atMjUlFFsHhuIQLzfBg0aZOxh2rRpE82tnugetTFEL6ymE2rSiEbef//9Jq3FeYQftXhK0njjjTdM3SDQANKsWTMjBhs1aiRpSxaRGxt3itxyHQEOP35aQsoWl4AM6cV25VrU9WmrVzCnt46eiu3DIMHFC+pb6AYocaDOdsSIEeY7OGbMGP1+eAGY4/P7SRQwPpmW+MABHR6PzHdWFCX58akUMFGE+A6EJ5pHypZiZUQdOx9XKWALBB33oTaJ5gVHmjRpYoQIIg+xhzDRiF7ycN9998k///wTdZntbH2UZz7xkpSd81/ULF9nhDarK3l/+FBurN0q57+eaIyg01a/S7K99JjcOnxCDt3XXcSVFQyic9JwCW10jznPAQcNK9Qg0pxz9913mw5lJXY4kMJjk6kP1IL17t1bvy9eBMbOHHC5A76/dPGTLaHOWVGU5CeNr/0gYeIcl0s9qVYiDm+++aZJ/8YXIoUIQEv80WxhRRv5ASMCRT2g4n4w77bqJllIqdtjiT9S6jV6dZOLf8Y+Surq3KVytF0fI/hyfvCSBGbKYMbGXfx+hpwb+WOs4k9CgqXDe31l3c7tppOZz4V9FIRpBx9//HFSX7LPz5OlBIK618WLF5s524p30bBhQ5NxIRqYFPjt5LcUL0AVf4qScviUAFy1alW8RhQh4ujcZTJIQqFpBFNaav7mz59vOuKIZCBA7K0MlMRhNcvYiz37ZhnSRFiCsKOwxLsV/cNOYuDAgWZncqNaebmxbjvhOZfPdX3pOjm2NIHvGR3AjzSTA39NMBE/Z2CJoTgHofzee++ZpipsQJjq4TgHVvEeqNfjO2lFbxOaDua+HLQzHQSTaEVRUo40vtZFGBft2rWT1q1bm9m/CYUfKxo8aB5hJikLMFsYQUg6WYkbxBopU8vuZteuXVGCz75ZhoYbUulEijhlQfwxaQQjWbwZrdQRvnH2dZxZn+8sJ7onQ5dueIRk6fGwrP7wRZP+wqPOvuYU0/DatWvrx8AJpMf5zhCpRwBS++cPlkW+znPPPWciuHxPOXizz4zE1kjC9xyPUsbDubKQURQl+fApARjXpA/STdhLfP7556Z42er8RVAAl4kgMl3DGYgNZxFGhIrOCo4ZycP7y5XHIf6H9rWV1E1S12c1y5DKja0zmzQ+YpBu7JkzZ5r7RHuvH2gooU1qy9UFq8z4NnfALu1IgwpSvHwJ81mYO3eu2YEhWq3PHt6EdHXzOrAGiu01+BO8R9bs5AULFpj0oeI7UPe6fv16Y8BPWnj16shRjNZcdXvzd747zP+lk5ionx4EKErq4FNNIBglx+ZNhf0K/oCxMX36dJddaPxwYddSp06dqPFjnFrnSWXR4evLjR8I4JMnT7ocO8f2J0pKytb6aBE55Qjfmb8hFi6JMdAG1gNRz+KMW8dPy6H6T0jEpSsmcpckgoLkdPpAabB/oTRr/YDpCMd4mzQw0Q8rRT1v3jxTIoA9EJFJRCBisGBB/+waJlLL62ebkPIdO3as2W6Kb8PvLNFxymKokUXkEbFnwgduCfoZUJTUx6cEIDsYojKuXhI7ZGwGHKEZhIgE9z99+rQZOeYKIj4IPGv6hGM3MKkN0oDOZtc6XmZhJBsGz/YL65lcR8WkZjC9ZiEKZy3OLjPP11Hokbp1hNdrP5nEUeQhzF1NUUlusIM50vaFSL+/xIpAZhznzyUFZn0ps1YtM/6PRDKIJjOfltFWiEB2bghA4LNBJASrDCLKpD7feustKVWqlPgDfAd//vnnqJnaNF3Ree/LB0eKoijehE8JQMyaP/roozhTwY6MGzcuXjYwQMOHFc1h0yGSrDFkrmbY2l/mfHwaVUhLOwpDa0FkIuRYqKNxPO/sOp4TYWd5FLqCHbQ1K5hoprNxc/bnOaq3Uuieys3t++R4t7ckbO9h4+GXUNLVqiR5vhsgafJENitwkED6inQXBw0MsieKyfvimPLFq5BJM8OHDzdCmjQon1Mixr4K3xHm+DIDtlOnTmZaTmrM0lYURVH8RAAyr9dZhM8dAhBhRJMHjQpJiWKwuRFhliAkOkQUMSELAhexQZSQJa7znBKBs4Qdp9Zif5nzzF31xSiN7cZNOTt0nJz/8tfImsBYPAIlMMD8HZPoHO/0lMxPtpUAJxFZZpjSBUkq+u2335bXXnvNRG+dQa0iEcMPP/zQ1Ee+/PLLxi7Gl2oEOdBgQgvNHXye6LLHMF1RFEXxPHxKAPJSqlSpYkSau18WoojRR6Q0qfmjuJnIl7VQ46YTPjyf8DPn5eIvf8ql3+ZI2K4DMdPCwWkkbaXSkvnRB8y838AM6WN9PMT8gAEDTIQPaxpED36QsfkZDhkyxETFENtY1/Tq1cvr5zzTCNOjRw/j6UfdI6/Rl8StoiiKr+FTAhDwk2K6gDshikbXKbVujHpzRv369c1YOcV7iLh+w6SHI85fMvN9g3JmlZDSRSUgOOH1itjYYIexZMkSY4fBjGnS5K7Aw/D99983TRHUSCIiH3/8ca/riKS0gCkeePtRGkG6213TIRRFUZRkxOZjRERE2Nq0aWMLCgpC2Lpt+fPPP20bNmywpUmTxunfP/nkk9R+6UoqEx4ebhszZowtR44ctqxZs9pGjRplu3nzZqz32bZtm61du3bmM1SrVi3b+vXrbd7Cf//9Z6tataotMDDQ9vrrr9uuXLmS2qukKIqixBPvCjfEM1WLRQdF59S+uQMK9yn2r1SpkqlxcoRUF9Efxb8hete9e3cTJcZwnPpA6kZpFnFljFu2bFmZMmWKMUemYYRO4ldeeSWaT6KnQR0qqet77rnH1KNSe8voO1LaiqIoinfgcylg+5okrF3o2ExoV7A91PphSoy9DKKSzUXDyIwZM6KNPWrQoIGx/ChXrpybXoHi7WzcuFH69etnumERdtTF3X///S5vf/PmTVNLSDoYiyDqBBGS8W3KIaV9ffVmubFhh9zctk9sV66Z0XXBhfJI2kplJF3NipImf9K6canxo9YPnzdqYt944w2P7wJXFEVRnGDzYQ4dOmS79957E5zuJX1Mqnfw4MG2devW2fLmzWsrVaqUbd++feZxz549a67jtsWLF7fNmTPHVrJkSVtwcLDtnXfesV27di21X7riQSxcuNBWs2ZN83lp0qSJbe3atbHens/ZAw88YG7fsmVL2969e2O9fdjh47bT731h21u8uW13znq23bkb2HbnaWjbnau+bXfu+rbdeRtGXp+rnu1ox1dtV+avMKUSCeHixYu2Xr16mXWqXbu2bcuWLQm6v6IoiuJZ+LQABHZ033zzjS1//vxm5+Wqhs/+b40bN462g9uzZ48RegUKFIi6np162rRpbVOnTjWXEX2IP0QgYnH+/Pmp9poVz/wc8lkpU6aM+Yx16tTJtmPHjlhvP23aNFuhQoVs6dKls3344Ye2sLCwGLc5P366bU+h+2278zSIFHlxLbdvd6xrf1vYybPxqmscP368LV++fLYMGTLYPvvsM9utW7fcsk0URVGU1MNnU8COkK4lFUeX8IoVK8z0Bqsui9olZlnWq1fP1HA5m9aA0XOzZs1M9yaPw+QHvN3Sp49uE8IwdGwwSJUxH5huUDqIFQUoRxg/frzpmsVAnLGD+AHa+1fyuRw0aJBJ/2IvRLcwqWE+o99//72pKyTde+KZ9+Tq7CWJ27BBgRKYKYPkmzRc0lUp6/QmdDT36dNH1q5dayaekMJmnKKiKIri/fiNAHQEM15MmGkUwQA5PvYb586dk9atW5v5lhMmTDA7aGewA2cnz44dEIHdunXzSYNlJfGNFHyG+GxQr4qNEJ+XVq1amYaQ++67T3LmzGkaLPCeXLVqlXTt2tXMWR703vvSZd0pubZwVeyG1nERFCgBaUOkwB9fGO9DiwMHDpjaPppXqF1kjBsHR4qiKIrv4LcCMLEgGhFzRBKZ6sAcYVfC7tSpU/Lqq6+aHT1NInQQ0/WpKPaRaSaKDB06VJYvX26aiOgqX716tfk73npErBm7R8SZiSPy1RR5LrSQuOVwIihQgnLnkMLLfpSrEiGDBw82opQmFMYqeqM3oaIoihI3KgATARE+OjVJzbGD/Pbbb12OAIP58+eb2ahEVugKxUIjttsr/snSpUvlgw8+kNmzZ0ddR4QaUUg6FmF4ff12Odz0Gb64Th8jbdVykr1fD0l3TwVBId5Yt13OfvSdXF+1yfUTBwbKsRql5ZG1s8x4QkbacWBDZFxRFEXxTVQAJoFff/3VRANJk02bNi3Wgfek/IiosFSsWFF++eUXKV36TtpNUQArIUbD2QfmrTnUpIHPdXlTrq/YEHOEHeKvSlnJ/8coubFum5wfPZHhJpK1dxcJqVhKjj70ktxYsyXWjTysVm7pO2q41vkpiqL4ASoAkwg1Wg8++KCZ5frHH38YcRcb//33n3Tq1Mk0AHz55Zcmgqi1gYoFjR7UmIJlZG75TfZu/bD0WX7C5cbK99snElKhpBys3lFs125EfsEzpJciaybKzb2H5GirXq43dFCgZHmmg+Qc0FvfDEVRFD9ABaAbOHTokGkOobOYyN4DDzwQ6+0vX75spkTQKPLoo48aIZg5c2Z3rIri5VArSqc5tX8s+fLlM/V/dA93vhgit8b+jiJ0et9i++bKlb+Wy8ln3ot2fZ5xAyXjA41kf4W2En7ijMvnDsySUYru+lMPSBRFUfyAhE+9V2JQqFAhU6NFNK9NmzamiP7ll192uSOltmrcuHHSpEkTUxtI8T/CsUaNGrp1/ZxFixa5/NuRdn3kVoRz8QcBwWkYJxLjetuNMHMaUq64XItFAEZcuCy3Dh6T4CL5E7zeiqIoineh7X1uAlHHTNe+ffuazl/mBzPaKza6dOki69evN3YfdevWNfNUXc2MVZQb67dHWpa74ObO/ZK22l0UDd65MihI0t1dPvJstrijzDc27tQNrSiK4gdoBNCNYJdBkwdWLwjA3bt3m0YRUniuwOON6CFzVRGPf//9tzH7JfWn+A80fWAxdPHiRbNcunQp+umFi9Ls0pVYH+PCd1Mk98h+knPwy3Lu0x9Md2/215+UNIXyRD1HrASIhJ85786XpSiKongoWgOYTCDq2rdvbyJ6CLoWLVrEeZ+//vrLTA+h6D++91E8FwQXtirUiB4+fNic2p8/efJklMhjiS36G5wmjWzLemdaiCuyvtBFsr3SVQIzhprL2L9cW7FBsr34mBx5oJdcXxmLHUxAgBGPWbo/lLgXrCiKongNKgCTEXbwTG+YM2eOvPLKK8Y4Oi7/P+6DtQxecKSSMeZNk0YDtZ4o7pgM40zY2Z9i3mzB+1igQAHT3EHdaJ48eYy3X6ZMmUwTUGynfG72FWsmtit3Hs8lIcESUrygRFy+KrcOn5Ccn7wmmdo3kf1lW4vteuxlCXm+eU8yPnS/OzaRoiiK4sGoAExmiOqMHDnSpHfj6//HfRi/xTiupk2bmvsgFJSU48KFC3Lw4EGnAs86T8rWAsuW/PnzG2FnCTz785wi+Cxrl8RwpE1vub58Q4Luk6ZAbin473i59MtsOfPO53HevtCKnyWkRKFEr6OiKIriHagATCES4/83b948eeSRR0zUCI9B6gUV90fyjh07Zt4f/Pc4ZUH82dd2UpPpTNRZ11HnmRRxZ7F27VrZvn17lA0M7z0ek3BmwGg5P/o3kVvOO4FDyhaTDA80lBsbdojtxk0JuaukSf2GHTpmjKDjih4GZAyVYntmS4COflMURfF5VACmIPj/9e7d29T3xdf/DzGAryARqalTp0r9+vVTbH19Uezt27cvmtjj9MSJSHPlbNmyGSNmlsqVK0uxYsWMuEP8pVQavlmzZkb4O3aYh4SEyLP3tZCnFh5wed/g4oUk16dvGCEYmCG9hB05IZenzZfzn/0ktqvXY3/ioCDJ/EQbyfXxK+56KYqiKIoHowIwFfjpp5/kueeek1y5csXL/+/MmTOmoYRZsd98842pEVRih0aaHTt2xBB7CGkgXVu1alUj9qzTwoULp7oJ8hdffGEOEpxBPemg42nNfF9JBruggou+l7TlNMqsKIriD2h3QSpA9K9WrVrSuXNn4//3wQcfyGuvvWZSjc7IkSOHzJ07V55//nl58sknZdu2baahxB0pR1/gxo0bsmXLlmhib8OGDVENGKTOEXnUVHLKEps1T2qxdetW2bt3r9O/vfTSS/Lpp5+aGsCjD77g3icOCpSMbe9T8acoiuJHaAQwFcEo+t1335UhQ4ZIo0aN5Ouvv461QYQUJs0hiEXSwkQSSQ/6E2wD0uILFiyIqtdD/IWFhRkBjQejFdFjqVKlimTNmlU8FVLSeEWybNy40TT7sNBkQjMQEUlE/3fffRcVnTzdb4RcGDvNPVHAwEAJzJpJCq/4OV5G0YqiKIpvoALQA5g/f74xjqZB5K233jKRqtjsYmbNmmWih9So0RxC6tKXIW3LNiIKiqUODRrBwcGmq9o+hVupUiUJDY30v/NUEHWIVl7HzJkzZeXKlWadGSHIe0oNIH9r27atEXzt2rWT3377LVq0N+LqdTn6cB+5sW6bSHgSRGBggKn9yz9lhKSvXdk9L1BRFEXxClQAeghYigwaNEiGDh0qJUuWNNHABg0auLz95s2bpXXr1ibNOX36dJNS9hUskWQJPmYlU9NXpkwZad68uRFJDRs29HixZ3H8+HHT2MHr4fT06dOm+adx48amthPxlyFDhmiR4SJFihiBi0ikAcSRiEtX5FiXNyKNneOa8OGMoCAJCEkj+X7+WNLXuzupL1FRFEXxMlQAehgIu2effVaWLVsm3bt3N/OBqQF0ZRpNhGjNmjUmSvTggw+Kt0Inrr1IOnXqlDFARiQh+FiKFi0q3gACjvfPErDMe4Zq1apFCVgEO1HM2KKevH5XdaFgC7tlOnzPDh0nNluEBETY4hf1i7BJupqVJPeotyS4aP7EvUhFURTFq1EB6KERMGq+MI/GfmT48OHy2GOPRetQpRaOyzRA0FRCFHDs2LFmlJwzaIrARmb16tUmunblyhUjLuiGrV27ttSpU8d4DsZlS+MuqNmzF0k0bwCpXEQSS1wiyZOgecN6LdQnYvmTO3fuKPHapEkTczk5uLxpp3zd6CFpHZxDgsJtImmConsFcplUsc0maauUlSzPdpCM7Rqr35+iKIofowLQw1OHjJDDKua+++6T0aNHRzWJEB08f/68TJ482YjBnj17GtFIp2ifPn2iHgNR8t5778mKFStMHRniktvbg8gkxYrhMA0H3B6LmuRoeLAXScy/5XkskcTUk+QSSe4GAb1w4ULzWnhNu3btMtsRIW0JWLwEY4vguQvE/0MPPSRbVqySwscuyfUN2+XKhh0SdOOmBKRJI8FF8hvhl65mRUl7V8lkXx9FURTFC7ApHs/cuXNtxYsXt6VNm9Y2YMAA2+LFi1FwZhk+fLi5TUREhK1v377murffftt27tw525NPPmkuBwYGRt0+riUoKMiWLVs22+TJk+Ncr2XLltmuX7/u8u9XrlyxzZo1y/biiy/aSpcubR4/TZo0tgYNGtg++OAD29q1a23h4eE2b4Dtu3HjRtvQoUNt999/vy0kJMS8nqJFi9p69uxpmzZtmu3ChQupsm4dOnSwVa5cOepymzZtzHt+6dKlVFkfRVEUxfNRAeglXL161davXz8joNKlSxcl6ri8bt26qNt9/PHH5vrs2bMbMRdf4We/BAQEmNNBgwa5XJ8RI0aY27z//vvRrkcEff/997YWLVoYwcptihQpYnv22WdTVSQlhuPHj9t+++03I6Tz589vXkv69OltLVu2tI0cOdK2Y8cOIwxTE7Ynnwfed1i0aFHU+8i6K4qiKIozNAXsZYwZM0Z69OgRdZkUY4kSJUyjAV2xNA+UK1fOpI8dU72JYdiwYSYNbc/48eNNqhjoVsXA+M8//zRedljUXL9+3Yyso0GlRYsWJm2d2hM2YoPthLWM/SxgzmPLAxUqVDApatK69erVi5rN6wkwVpDJMKw//oF33XWX8RC0LGQoEVAURVEUR1QAehEIFZokMAymls+eLl26GGNoagN/+OEHU9PnCNYp1K05g4YLPOkcQWDSOMLzAo0kWJfYi8v06dMbOxpug5ddx44dzQxdT4TtRr2e44i4s2fPmr9Tg2iZSOMvyHYpWLCgeCoIUwT3v//+G+O9x0uSMYL2FjOKoiiKAioAvQiEH40FrsBH8O2333b5d0sA9uvXT/75558Y9jM0NjhC4wgRPLqIMWNmAomjuEQs0agS2xST1IBOY6KTjiPi6NC1opf2U0M4ny9fPo+OVjpa59DFTXMQwpVGEEcmTpwoHTp0SJX1UxRFUTwXnQXsRWAMjAij+xevORZEDoKG8WgzZswwETvH6KAjRMCcRfucgdhj9vCoUaPk1VdfdZpW3rlzZ6pH/DDS3rRpUzSxx2W2EYIOcYrAwyvRmgfsyl/RW6D7mPca4WeZhiPYLYHO61YBqCiKojhDBaAXwQ4dO5jERAeTAqJi0qRJcu+99xpxcfHiRVNnxkQLBCECFLFVo0YNSU7wPOR5WQ4dOmQWxClij1PEEFYs1MEh8Lp27WpO2S6YKvsaf//9t3l9WOmQ+iW6S83f2rVrjbjFKJwIqKIoiqI4ogLQR5g2bVq06E9sfPHFF6Zhg6gZY9YGDhwoS5cudXl7HpPbUU+WPXv2qOuJPtJsgiAsX758ktafSN2RI0eiiTvH8wgae7JlyyalSpUyDScvvfSSSeMi/jypSSO5QHgjADEIh3vuuccsvE+8fmoCeX8VRVEUxRkqAH2EVatWxZn6pUN4xIgRJlKEmGPm8Ouvv24ut2rVyoxgiw0ibYxms2BKR3xSvwhFOmqdiTrrPPVs9tDRymOzMEKtbdu2phnDuo7z/tzcQMTz2LFj0d4PhDoG21bXtrfMSlYURVFSHm0C8RFoBkAQJBSEFulbumCrVKni8nbUFr755pumA5iIH1M8mOxBTeKiRYtMEwI2KVxv/Z3HROQ5WtIwbs4Scfan1nkWX0zZupPPPvvMiPdz585FCT0OAmrWrGmiuUwkURRFURRXqAD0ERBViK7E8OWXX8pzzz1n7FywFHFVfxibryCWI0QUEW6sC6dZs2aNEnT2Ai+l5g37Mm3atDG1l0T8LD788EMZPHiwie56ywxlRVEUJXXQFLCPQP1fYrFsT2ITeDx+o0aNjOAg1WwvCIkOYg9Dx2lKzL71d0ipW3Y+9lATyHuk4k9RFEWJCxWAPkKBAgWMPUxCIUqHeMM6hS5bV9y6dct0IDNxxOr+tUAQTpkyxUQQifIVLlzYeOxhvVKpUiWzEPnzFn89TwdjbqK99vV/NHyQ+h06dGiqrpuiKIriHagA9BGYWLFjxw4j1FzBpBBGhq1Zs8aIODpo8fbLkyePGScWFwjFN954w3QRUw9IJIrnI+rHaDgsSQ4cOGCeA19COpNpPLE6di0xaC107PpzI0diIdKHcLems8CSJUtMJ7W9KFQURVEUV2gNoI8wbtw4eeqpp2JN4/bt29eMaStWrJhkzJjRNGkgHD766CMjCmODmj5uj88e0Lnbq1cvmTlzprmMrQyPbQ/rwu3wKLRfEKpWGpm6QUsQ4tfHKdFDTSW7BtNnvP+IulogzBH41hxgRVEURYkNFYA+Ag0BRPKSw/sNQYHP3/jx46V69erRBB5RvmHDhsnPP/9shFt8YG4wBsX2opARbTQvWGKTqSf20UIua/OImNQvXox0AdO4Y0E0kG30/fffu/39VxRFUXwPFYA+xIsvvmg6euNjBp0Ymxm8/DAbJvJHtI+aP3eBmMTGxjFaiN+dldYmconNyf33329SnUWLFhV/Y9asWSYVz/g9Uvhw6tQpY8PDNJDHH388tVdRURRF8QJUAPoQRNBovMAbLrZUcEIgFfvyyy/LkCFDZPbs2UZgzpkzx9Sgde/eXXr27GnSuMkFdW3UExIhZFm8eLFJV5NCLl68uBGCCEIaVHLmzCm+Du/F1KlTZf/+/VGp3t9++006depkJqkg1BVFURQlLlQA+hjTp0+Xhx56yC2PRb0faV2Mou2jfXv27JGvv/5axowZY+oCmzZtaqKCTBOxagSTE7qdsUHBhJqGCAQiYGRtRQcZD+crDSZsf1K/RPx4bUxGGTt2bNTfn376aVm2bJls2bIlVddTURRF8R5UAPogmAE7esQlFIQcnbvMli1RooTLWr5JkyaZqODKlSuNBQzdxJ07d5Zy5cpJSkHkCzFoCUJS1Xjh1a5dO0oQkrr2Vn88Ip1MXbG3/KERpGXLlvLoo4+a1PiDDz4oI0eOTNX1VBRFUbwHFYA+CmIAixdIaE0gaV9Exdy5c12KP2dzgkePHm0EIdYvROMQgqQm8QVMKUh902WMEEQQ/vPPP2Z96Hpu2LBhVMq4QoUKXtMti8UO9X2Os54RuDR9kPb//fffpXXr1qm2joqiKIp3oQLQh8G0+bHHHjOpQSZ5xCUEuQ0iA+E4YMCARDV5MEqOWsFffvlF/vjjD3O5bt260qVLF+nQoYOxL0lJaCBBnFrRQcySMbymacKKDtJUwWVPhe1JtM8xQkstJDY82PicOHHCZ1LeiqIoSvKjAtDHQQAhxD7//HMTDbMifIg9omVWhy0WKz169DBNHVZ3aVKhbm3GjBnGImbevHnmOgQXkUHqFFPD1oW0NSLQEoRr16412yO11yuuRhgaXOxnPdOU8/rrrxszbSxgfvzxx1RdR0VRFMW7UAHoR9A8wcg3umkvXrxookiMaKOpoGzZskmaJxwXTB6ZPHmyiQwuWrRI0qZNa5pGiAwS3XKnpUxCwEIFQ2VPWy9HqK0kDWylfllXmkOYvvLnn39KixYtUnsVFUVRFC9CBaCS4jAdBOsSRBfpWYyfibwRgSMSlxKdxAldL9LFqdlEgsizuqzxAKRGk+kfTICxml4URVEUJb6oAFRSFRo2EFwsCBtqBKkVRHTVqVMn1UbCsV6MtyN9zXqRgn3kkUdSbb2sNDBm34MGDTK1mlj0tGnTxsxmVhRFUZSEoAJQ8QioRyQ9bYlBrF2wlUF0NW/e3DSSpEY61n69EITM2mW96G5GDNLt7O5u4itXrphuakyvV6xYYSKTNPCEhoaaeclY2tBZjfci9YwIUkVRFEVJCCoAFY+D6NaSJUuM6GLqxcmTJ01tHiLQ6tylbjE5axZdrReCi/WaOHGimbxC7SRCkCWpzTPUaNJ9/c033xgRSLrXatKxQGzyurmetC8Ryvbt2yfxlSmKoij+hgpAxaMhArd58+aort1///1XLl++LFmyZJF77703ShCWKVMmRX39wsLCzPogBqdNm2bWCVFqeR9i1pzQGj/8/hCV8fVt5PWyfdq1aydfffVVilvsKIqiKN6LCkDFq0B4rVq1KmryB5NKuI4ZuJbJM0tCBVhSrWVmzZplonEIOaJz1OaRomVGcVz1glj0UNvH7RzNnuMDEUFeL+K4aNGiSXgliqIoir+gAlDxakiVUitnTf7A/BpIzVqCsFGjRpI1a9YUWR+mjiAEGY9H5JIpHc8995x07drVjNZzhHnK+C8mFdLFiGDEcZ48eZL8eIqiKIpvowJQ8Snw9cPw2koZ792710TWqlevHpUupmkiXbp0yboepGapY0QI4jOIQMNbkKggxs1Wp3GlSpVMh68rqHvs37+/8f5jnWlCwQ+QTmBnkUCsYqZPn+41Y+4URVGU1EEFoOLT7N+/P0oMcopARChRM0hHLQLMWkijJodwYkwbkT7q9OjorVmzpokKjho1ykQsHRs9LKgnnDBhgmk4IapInSGzmYn0DRw40OXzUZdIHaKiKIqiuEIFoOI3UF9HWpa6QaZoMBFl48aNZioKkKK1F4QsjFpL7Izd1atXm0kdlrE1Qo8aQaKCc+fOjfW+iDwihET7nn/++Xg/JwKWtPO2bds0CqgoiqK4RAWg4teQqj148KARgvYL5s8IRgQV9i6OwhAT5tiaO/AOJNVbsWJFGTt2rElB29O0aVMTkXTV9PHuu+/K+++/b56H9UsoCxculIYNGyb4foqiKIp/oAJQUZxw9epV2bp1azRRSMTw7Nmz5u+MiUPcWYKwfPnyRqyRRsafD2sY7FlINyPyrAkeGTNmlBs3bphTV6lfIGWNyTR1g0OGDJEKFSqY58YXkRFwly5dcnlfIo7UGo4cOVLfW0VRFMUpKgAVJQHRwmPHjkWljq1l+/btUWKOqCDp25CQENOAEvVFCwgwo9yo+6OOzzEi6AgpXAQlFjcfffSRSVszAYSoIHOK69evH+v9a9WqZe6jKIqiKM5QAagoSYSIHmKPVC3LgQMHZMaMGbJlyxYjGh15+OGHTWdwbFD/Ry3fm2++aSKAFkQSiezRzUwK2RWMjcMiR1EURVGckbIT7RXFB2FMXbly5aRZs2by9NNPm1Qv0TqrRtBqAqHJhLQwqd24zKGZCAKOzSKzZ882p5aVTGwpbGfiU1EURVFABaCiJAPHjx83I90Qfw8++KARbljQEPlDCMYlzkgtO8OyqYlrYggCU70AFUVRFFeoAFSUZOCll14yI96oGZw8ebI0b97cNIRAwYIF4xSAVoq4RYsW0a5v2bKlOV2xYkWs98+XL18SX4GiKIriy2gNoKKkMEzzKFSoUJy3o44QuxhSygg+Gkf+97//mQ5hZg27AqFJ1NGxzhDRSRSSLmVnY+kURVEU/0EFoKKkMAgxooBHjx6N9XaMfkPwYQVDRI/b//TTT6YTOLbxcaR/e/bsaaKP1vg4JqKQlqarGPGZGG9BRVEUxXdQAagoqQCj3N577704a/kSA3WHdBr/9ttvMf5GXeBDDz0UZxeyoiiK4ttoDaCipAJNmjRJli5dxF/Hjh3N7GDSwI7wnIhDRVEUxb9RAagoKQgC7KuvvjI+flmyZHHrYxPdI+WLbyBpYJpPEIGOljNPPvmkPProo7JgwYJkiUAqiqIono8KQEVJIQ4dOmS8Ap977jkjwDCPxs/P8gl0h7ik85hxdMDjkgZu1KiRaQxheeqpp+SDDz6QtWvXyv3332/mHHOZekFFURTFf9AaQEVJZhBm48aNk5dfftnMEB4zZowRgkBjR506deTIkSOxzgaOD0wNYWycI0wEQeytXLlSVq9ebbqJWaelS5eadUEk8tyPP/64vPbaa8bUWlEURfFtVAAqSjKCwHvmmWdk1qxZ0rVrVxkxYoRkzZrVmEQvXLjQdPlevHjRpG83bdqU4LpAonqkcWkq6d+/v0vzZ55j2bJlxo/QkQsXLsi3334rn376qVlfLGbeeOMNqVu3bqJft6IoiuLZqABUlGRi3rx5xsKFVOw333wjrVu3lv/++89Yufz444/Gkw8KFy4su3fvNtG7AQMGmOsQiHEJP25TsmRJmTBhgtSqVSvJ64u1DM0jQ4cOla1bt5rIJEKQ9Y5rdJ2iKIriXeivuqK4GSJy1NURbSPdunnzZqlcubKUKVPGXKZOzxJ/8Oqrrxpz5nfffdfUBZLKzZEjR9TfEZAs9iIMwUfqdsuWLW4RfxASEiLdunUzkcg//vjDiMy2bdtK+fLlTar4xo0bbnkeRVEUJfXRCKCiuBHSqaR6meLxzjvvmBQvQoomi4oVK8rZs2djpHkPHDhgooCOIpKoIM0a/J0avYwZM5rHoHEkpSZ5LF++3EQEp0+fLnny5JE+ffrIs88+a9LYiqIoiveiAlBR3ASRvnbt2snJkydNWpbUqT07duyQatWqmaYMi0qVKsmGDRs8/j1g3T/55BP54YcfJG3atEYEIgatjmNFURTFu9AUsKK4AdKxNWvWNOJozZo1McQf9Xo0WSD+8P+zbFk6dOjgFduf9DWNIoyUe/755835YsWKGU9B6gUVRVEU70IFoKIkAWbrvvLKK9KpUydTL7dixQrTmGEPtXNM50A0jR071tTYkfJFFHIfb4KZxDSrMEuY07/++kvuuusuI3gXL16cLNNNFEVRFPejKWBFSSTHjx83wg57lWHDhskLL7wQw4YF+xVm73IbooRYrMCJEydk0aJF0r59e5fWLd4AncO//PKLfPzxxyYSWLt2bdM5zOvUzmFFURTPRQWgoiSyOQLxRrPGpEmTpF69ejFuQ+PHAw88IHv27JHff/9dGjRo4LPbmu0we/ZsIwQRtqVLlzZCkIYYd006URRFUdyHpoAVJYHQEXvvvfeaGjh8/ZyJP6Zs0PCBCPz33399WvwB0b5WrVqZ14o4rlChgjz99NOmyQVhqKlhRVEUz0IFoKIkAPzwHn74YZPinD9/vqmJczaPl/m71AIiEPEA9CfwJZwyZYpphsE6pmXLlsYTkdpHRVEUxTNQAagoLnjuueeMlx+ijmXw4MHSo0cPY4FC3Rsdv/ZcvXrVzNN98cUXpXfv3kYg5s2b12+3L36FCxYsMBFTDK6rVKlith31j4qiKErqojWAiuIEJnUQvUL4IVrSp09v5vhi7Mzi2LhBnR8egJg3f/fdd9K5c2fdrg7NIqNHj5b333/fmFoztxgfwXTp0ul2UhRFSQVUACqKE8aNGyfdu3ePdt1nn31mOn0dmTlzpjz22GOSK1cumTp1qpnWoTiHSSjMO/7iiy+MiTRRVTqpvbkTWlEUxRvRFLCiOIEaNoya7VmyZInx/bPvfCUaiAdew4YNTc2bir/YyZ49u4mkMsOYlDCR0jp16pjGEUVRFCXl0Aig4tOcvSYyZ7fIhhORy7nrIsSacoaKVM4jUjWvSLMSIpnsyvkuX75shIq92LMYOXKkqfEjkkXUb86cOTJw4EDp16+f+t4lgn/++ccYaa9fv95EAokIFi1aNEnvuaIoihI3KgAVn2TfOZGRq0T+2CkSHiESFChyKyL6bdLcvi5dGpH25URerCGSJ2PkWDcmewBRQCZ20O1Lg8drr71m6vweffRRuXDhgvz888/SrFmz1HmRPgLblxnDb731lhHW1AZSI5g5c+bUXjVFURSfRQWg4lMg9satFxm8VCTCJhIez8lkQQGRQnDgvSKDu9aQNatXS2hoqBF6RPrw+qORgZTvJ598IjVq1DCdwBqtch9EXocOHWqWjBkzmsjqU089pUbSiqIoyYAKQMVnuBku8tIckT93J+7+pIbRi/dlPyjVLvwhTz/dI8rqhfo+ploQ/aOJgUigY42g4h4OHz5sooFEBZkzzJg9jbIqiqK4F20CUXwCm03k5bkis3cn4TFuny44W1jOV37eiD+ifngBYm6MZcnatWulb9++Kv6SkYIFC8r3338vq1evNrWYmEi3aNHCzBpWFEVR3INGABWf4KdNIv0XiGQIjqzlK59L5K5cIjlCRT5dITJiZfTbf9JEpEP5mI+z+6zI/RMiz79TYa+MerWd6VhFBNLoERwcnDIvSDHgwzht2jQzV3j//v3GYPuDDz6QDBky6BZSFEVJAjqlXfF6Dl8UGbAo8ny2dCKdK4psOyUyb69I5wqu73ctTKTz1OjXXb8VeRogNnlvRUbJliaDrFq1SqpWrZqMr0BxBf6AGGwzZxgfxnfffVdmzZol48ePl7p16+qGUxRFSSSaAla8nm/+EwkLjzx/+JJIpa9EOk4RGbI09vvRJLLuePRl2+nIv9kkQNJkzCXPjvpXxZ8HQDr+9ddflw0bNhjD7fr165s6zGvXrqX2qimKonglKgAVr+bKTZGJW+Lf7ZsQEIE/bkljOosVz6B06dKyePFi+fjjj2XUqFFGnK9c6ZDfVxRFUeJEBaDi1Sw6KHLtdto2oWD7srqHyN4XRFZ0FxnQSCSLnSE0HLsssumkW1ZVcRN0XxP9W7dunfEKZJLIm2++KdevX9dtrCiKEk9UACpezaYTkYbOCYVU7wdLRF6eJ/LEDJHJ2yKbQqY+IhIaHN0aZuMJt66y4ibKlSsny5Ytk0GDBsnw4cOlWrVqxq5HURRFiRsVgIpXs+VUpPlzQhmzLnJZcjBy+WS5yCvzREpmj944wgQRqy5Q8TzSpEljurOx58GmB7seOrax71EURVFcowJQ8Wou3Ljj35dUmBlMTSHzge0bRS6plvB4KlasKCtWrDBdwswTvueee8x8YUVRFMU5KgAVryYgwP2Ph+izJ9DNz6EkD3g0IgAxkAZEIFNbwsLCdJMriqI4oAJQ8WryZ4yc4+sOWpaKrP/DDsZe/OUKdc/jKylDlSpVjAgkNYwArFmzpmzatEk3v6Ioih0qABWvpmLumCngRkVEWpYUaVw88nKp7JGXWej8LZBJZEoHkW6VI2/bsIjIG3VEhjcV2XFa5NfNdx7rVoRIpTwp+pIUNxASEmLEH2nhGzdumAaRjz76SG7dSmTLuKIoio+ho+AUr2bVEZEOk6Nft+RJkUKZnd++7liRizdFhjaOHBWXMzQyynfkksjcPSJfrI5Z87e4m0jhLMn3GpTkBQH43nvvGe9AhCBzhukgVhRF8WdUACpeDfV6DcZHjoNztxc0qeXq+UQmdnDzAyupAobRXbt2NTOFBw4cKK+88orxFFQURfFHNAWseDVE756skjyPzXSRrsn02ErKQy0g5tG9e/eWvn37mnFyu3fv1rdCURS/RAWg4vU8WlGkaFb3NYMAj1Ujv0iLku57TCX1SZ8+vXzyySdmnNzJkydNSnjKlCmpvVqKoigpjgpAxeuhsWNkM/elgNGRTBc59eMTkid3Lnn66aflu+++k//++8/UkyneT926dc372axZM2nfvr306dNHzaMVRfErtAZQ8RkmbRV57a+kHxHhBTimjcg3/TrLr7/+GmPyBA0E/fv3l06dOiXtyZRUx2azyahRo+TVV1810cDffvtNChcuHI/73ZkTvfOMyLWwyIOGApkjO9PpPA/W8kJFUTwYFYCKTzF1m8gbf0c2h1DDlxACbOESEHFTxrQNkfuKB8mZM2ekQIECTqN+zJ9966233LfiSqo3iDzyyCNy+fJl+fHHH6VFixZOb3c1TGT6dpFx60V2nr1TLkAtqu22bRBkCokcKfh4Je0gVxTFM9EUsOJTtCsnMvtRkfK5Ii/Hpy7Quk25jOflyAdlZf6Yd83lHDlyyAsvvBCtUzQwMNA0D9BEoPheg0jt2rWlZcuWRtw7egYuOiDS8HuRfgtEdt0Wf8CBRljEHfEHWAkxa5rbf7pC5GZ4Cr4YRVGUeKACUPE5SL/N6CjyVSuRmgWiC73gwMjFGu/GyX3FRCa0FfnzqRwy8I1e8uGHH8q0adPM30kNIvrMbQMCJCIiQipVqhR1neI7ZM+eXX7//XdjGM084SZNmsjx48dNNHnAvyKPTxc5fTXytvEJLiMMue/IlSKtfxE5cTm5X4GiKEr80RSw4vOcuhJZq7XllMi565HiL0f6yFqtCrlFsqaLXhNGKnDOnDmyatUqU++HbcgXX3xhRF+vXr1Mzdhjjz0mY8aMMRMnFN/j33//lc6dOxvB32Tof7LobP4kPR4HH3kzikzrKJIng9tWU1EUJdGoAFQUBy5duiS1atWS8PBwWb58ublM1O/999+Xl156yTQKPPHEE9KgQQNjIZI5s4uxI4pXc+LECWn59hQ5XaGXWx4PEXhXbpHpj4gEaQBZUZRURgWgojhh165dRgQi/IgGEv0LDg6O+vvChQulbdu2UrRoUfnzzz8lf/6kRYgUz2PvOZGmP9okLCJAMgSLvFgjsraUEYI5QiNr+0asjH6fAy+5frzdZ0XunyDSv57Is9WSffUVRVFiRY9DFcUJpUqVkunTp8uyZcukR48exv7FnkaNGsmSJUtMpzCNA1u3btXt6GMMXEQNX2SxaLZ0Ip0rioQEiczb6/o+bX+Lubz3b+TfmDUNQ5eJnLldS6goipJaqABUFBfQ7fvDDz8YW5D//e9/Mf5eoUIFkyLOkiWLMRZmuoTiGxy6KPLP/jtWQocviVT6SqTjFJEhS13fb93xmAtRQ5pBftsSeZvwiEjPSkVRlNREBaCixELHjh1NR+jAgQNl3LhxMf5esGBBI/yqVq1qukbpIlW8nylb73SKJwVSx61Kiqw8LHLgQuR1uMX8tCnpj60oipIUVAAqShy88cYb8swzz5jl77//jvF3IoCzZ8+WBx54wIwVmzlzpm5TL2f10cioXVJpXVokQ4jIr7ejfxYHL4qcu5b0x1cURUksKgAVJQ7w/8MGhgjfww8/LJs2xQzfpE2bVn755RcjArkNglDxThjztuGEe2ZLd7xL5MJ1kdm7Y/5t80k3PIGiKEoiUQGoKPGAJhDsX0qUKGEmRRw9ejTGbegSZnYwY8QeeughmTt3rm5bL4SpHUzycIch+d35RKbvELnhZBLI8StJfw5FUZTEogJQUeJJpkyZotK7rVq1kvPnz8e4DcbQEydONNFCbGKcpYwVzwLz75MnT8qaNWtk6tSp8tmoUW553E53RZ7+utn532kGURRFSS2ie1soihIr+P3h+9ewYUNp3ry5zJs3L4YRNCJw8uTJ0q5dO2ndurXMmjVL7rvvPt2yqcjly5eNVQ/LgQMH5ODBg2bh/KFDh+T69etRt00fGiq5BvUUCUz8zyPjBh8qK7LxhMjW085vkyltoh9eURQlyagAVJQEUrFiRRPZu//++40IJNVLdNCxJpApIaSCqQukJhDRqCQvt27dkp07d8rmzZtNraa17N17x7wvb968UrhwYbNg9F2kSJGoyyw5cuSQ5j8FyPYziV+PJsUjzaKHr3B9m3I5E//4iqIoSUUFoKIkgrvvvlv++usvady4san5Q+A5isB06dLJtGnTpE2bNqZukNswPk5xT9r28OHDMYTetm3b5ObNm1FCD7FOKp5TfBvLly8voaGhcb+/+UR2nxO5ZZembVREJDQ4sqvXqvFrWTLy/IL9ItdvRW/+uBYmMmOH88cPTSNSNGtStoCiKErS0FFwipIEVq1aZer9KleubFLDGTNmjHGba9eumVTw6tWrzfQQxIgSf6i1RNzZiz3OWzWYbHPEHdvVWricM2fsITbSvhs2bDDCnTQ+dj4ZMmQwY/8WHRB5fHr02y95UqSQi7HPdcdGmkVDvowiS58UmbZd5NW/nM8EJj08rKl+ChRFST1UACpKEmEaSNOmTaVatWqm3g8R4cilS5dMCvj06dOyYsUKnR0cS2SPdO0///xjFky2qdGzOrHLlCkTTeixkLZFtCUUzL3ffffdGJY/QUFBkj17Din50fEoUedufu8oUjlv8jy2oihKfFABqChuYOnSpdKsWTOpUaOG6RR2lmbEOqZmzZomMrVo0aIYKWN/hWYMS/CxcBlBh6BGNDNlBaGH+KPBxl3Q9XvPPfc4/RvznV8bs0xeniduhehfvcIiP7R17+MqiqIkFBWAiuImiFZRD4h4YCRc+vTpY9yG9GW9evXMMmPGDBPV8jeOHz9uhN6CBQvM6Z49e8z1pNHplr733ntNrSQp2eSENDKNPFjAWCA8EYX//vuvhISklSd/F5MOtmYCJxVqCP95QiRvzEoBRVGUFEUFoKK4EYQDDR/Vq1eX6dOnS7Zs2WLchg5ihOJTTz0lo0ePNmlHX4a098KFC6NE3/bt2831NGQg9hB9RProvk1uqPujO/urr74y9ZiIzAsXIof0kvrF5mft2rWSK1cuc93JKyJtfo08TaoI5F0e3Uqkxe3GEUVRlNREBaCiuJlly5aZpg+6UOn8pUbNkXHjxkn37t1l8ODB0rdvX596D2jOIMVtRfg2btxori9VqpQRfCyNGjUy2ycloCsY0c2UFqKuFy9eNKLzueeeM2K9ePHicuLECVO7SVMPwtSegxdEOk4ROXE5cSKQtC93G940svlDURTFE1ABqCjJwI4dO4xHIOIDEYjfnCM0INCIgDDp2LGjV78Px44dk0mTJpkpKDTFREREGH89K8LHacGCBVPUDxDxyfg+pnucO3dOypYta7Zzly5dpHTp0lG3HTJkiLz11lumgYc6TmecvSbyzj8iM3eJBAaIRMRTCHLbAplEPm0mck9+d706RVGUpKMCUFGSsdaNCBM1bvgBOk4DoeP1iSeeMKJp/vz5pi7Qmzh16pRJpyJgifhRz0g3NL571NYVK1YsRdcnPDzc1GEi+lgv1o/ZzYg+FhpJnKXbEatHjhyRQoUKxfkc8/aIfL46csJH0G0h6KgF0wRG+gdmTyfStbLIs9VE0ge78YUqiqK4ARWAipKMYP/SoUMHkw4dP368iT7ByJEjpUqVKqZhhKgTzSHUnhE182TOnj1rxCwii9cEiD0EFlNPnNU8JieIN2x1WB8ikEQiSblbog/D7uSosdx0UmT+XpGNJ0W2nhK5GhYp/ApnEamSV6RGfpHGxUVCgtz+1IqiKG5BBaCiJDNhYWHy9NNPy/fff2/SjdjA0ACC2Nu9e7dpQqBpJHv27KYxwVn3sM0mcvqqyPVwkZBAkZyhIkEJt75LFKwftXOILKafkF6laaNTp05m3rHVMJFSEDnFwoX1IXqKTyDNGwhtRF+tWrV8vrFGURQlqagAVJQUEi3U/A0aNMhYjRC5gp9++slEBdetWyd16tQxAoYGEQQMdWcTt4os3B+ZcrwSdufx0gaJ3JVLpH5hkU4VRPK72VLwypUr8scffxiRRQ3jjRs3pG7dumb92rdvL/ny5ZOU3n40k7A+LJhFIzwt0Uf6PDFm0IqiKP6KCkBFScHuWGrSSKMCgqVkyZJmfi3nf/zxR3n88cflk8+/kTPln5bftpDiFLEbR+u0yYDoYMtSIv9rIJInDn85GjSINGKq7GxkHePsEFiYWXMZTzwifQit+NTIuRO6danpo5mDBg3sY1h3oo6IPjqJ/dFHUVEUxR2oAFSUFICI34MPPmiiaTQr2EOXKvVz0PnNL2RxhoclOEseibDFP41JQ0K6NCIf3S/yYExtZ0BM0YhSrlw5MwOXKCPrhUXKDz/8YNK8ly9fNrWJCKxHHnnEWKSkFFevXjUTVSz7GNK8bCu6hxs3bmzWh9PgYO2oUBRFSSoqABUlBbCaE6ifI2rFqQXX79+/X/7YGSAvzbWZdKdNEp7ORC7Skdq/XmTnqT10IlNnSD0fj096l8jj119/bf6GKCTSh/BzFh1MLlNmGjisEXCcp14yd+7cUdYxLERJtaZPURTFvagAVJQUghm3GA3T7Ut0i/OkOWHk9HXy6YEq8faXi4uPG4t0vOtO6pkZxdTNEVGzxBSRNFK7GCJTf5jcIgtxt3r16qiJIBhmIwJJ65LOtUQfYlQFn6IoSvKiAlBRUgkicYjC2QuWyddhneTctQAzK/bFGiLlc0U2eeQIFfl0hciIlTHvj+1It8oiHcqLFM0qciNcZPcZkQ+WiGw+KfL34yL5M9wyNi2kf3k+CwQWjSfM300uEJs8h5XSZR1oLsmcObPpIrYifJhkawOHoihKyqIV1IqSSiDCsILZW6iInN8amb7Nlk6kc0WRbadE5u0V6VzBdfPHNw+IVM8v8vVakbVHxYjHCrkjTYcxIu77t8iFMW2MSbMjiEGaPdwlAJl4QpMGfoYsdOwS4SPlzIg1unTpgkbwVa1aVZs3FEVRUhkVgIqSiuDtN3nrndFihy+JVPoq8rwRgy4EIJG/RkVEHp4ksu74nesX7L9zftlhkXvvaiil9+yRTJkymegbKWcWGi5ICScUmkYOHDgQJfRYNm/ebEbfWXWN1DQydeO1114zaV06ibVxQ1EUxbNQAagoqQhWL4kp++teRWTVkejiz1lncL7mfWXH0L4x/mafDnbF6dOnYwg9FjqFIWvWrEbokc7t3bu3OV+hQgXJkiVLIl6RoiiKkpKoAFSUVGT+vjvRv/iSL6NIoSwif+8Teb1OZLMH0cK950S+WisyZVvk7cJtkbf5yMljWE0WRPROnjxponpbt26NJvaYZQxp06Y1jRkIPDz4OGVh+oY2ayiKongnKgAVJZVA+G05lfD75b1t9vxwOZHjl0Xe/Ufk0s3IdPHwpiLBgSK/bom8zckrIqs27ZYLx/eZhhNrQfBxyhg16vcAMYfvH+KO0XWW0MOGRQ2XFUVRfAsVgIqSShy7JHL9jh1gvKEBxBoH122GyJFLkZcXHxSZ2UnkpZp3BCA0aNtdbuxdbAQeI9yo0WPBF9A6z1KqVCnTsKEoiqL4PioAFSWVuJYI8QfnrkWe7jl3R/xZ/HtQpPc9IjnSi5y5fbuhI0bJAxUySYECBSQkJCSJa60oiqL4AioAFSWVCAlK3P0OXBC5Gub8b5aVs31dYbUqlaRYyo7xVRRFUTychM+bUhTFLVDLh5lzQqG546+9IiWzixTMFP1vWMPsPy9y7vqd6zCJVhRFURR7NAKoKKkYASydXWTr6ZgiDlPnDLeztaWyi7Qsecfnj7rBT5ZH3u77tpFTQi7fFOl0l0i5XCLP/3nnsbKkjewaVhRFURR7dBScoqQiHy4R+e6/yKiexZInRQpldn77umMjzaKhdA6RN+uK1MgvEhwksvWUyOerRRbsu+MD2KyEyOhWKfBCFEVRFK9CBaCipCL7zok0+iH5Hv/ndiJ1tf5PURRFcUBrABUlFSmWTeTeopHROnfC45XMJlKnoHsfV1EURfENVAAqSiozoFHimkFigy7gT5pi7uzex1UURVF8AxWAipLKFM4i8n4j9z5mr3tEquZ172MqiqIovoMKQEXxABjj9mIN9zwWI+Jeq+2ex1IURVF8E20CURQPYtx6kUGLRWy26J3B8RkPx32eqy7yep074+IURVEUxRkqABXFw9h1VuS1eSLrT0Q2c8QmBK2/F8sqMqypSLV8KbmmiqIoireiAlBRPBCief8dF/lhg8g/+0Uu3Ih5G8yisXh5opJIvcIa9VMURVHijwpARfECMXjsssjusyI3wkWCAyMjfjSPaJevoiiKkhhUACqKoiiKovgZ2gWsKIqiKIriZ6gAVBRFURRF8TNUACqKoiiKovgZKgAVRVEURVH8DBWAiqIoiqIofoYKQEVRFEVRFD9DBaCiKIqiKIqfoQJQURRFURTFz1ABqCiKoiiK4meoAFQURVEURfEzVAAqiqIoiqL4GSoAFUVRFEVR/AwVgIqiKIqiKH6GCkBFURRFURQ/QwWgoiiKoiiKn6ECUFEURVEUxc9QAagoiqIoiuJnqABUFEVRFEXxM1QAKoqiKIqi+BkqABVFURRFUfwMFYCKoiiKoih+hgpARVEURVEUP0MFoKIoiqIoip+hAlBRFEVRFMXPUAGoKIqiKIriZ6gAVBRFURRF8TNUACqKoiiKovgZKgAVRVEURVH8DBWAiqIoiqIo4l/8HzHrL7Uo83CUAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Create planar graph, similar to a street network\n",
     "G = nx.MultiDiGraph(nx.Graph(\n",
@@ -183,7 +202,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T09:46:19.934335Z",
@@ -216,7 +235,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T09:46:40.943464Z",
@@ -262,7 +281,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T09:47:17.588377Z",
@@ -345,14 +364,45 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T09:47:41.937097Z",
      "start_time": "2024-04-18T09:47:40.740062Z"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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sHmXXkbVP2r9/dr0dPHjwkm5Hdx5P9jgsguts/3pMpOM5whprNHPmTLNu7IKzX1ees6688spLPiu+b8d9ILvHEPdBnlvs3XLLLeYzZpKf/XHG7lp2uTMjleeiESNG4NixYzh8+LDTr+f4WlxvstbdmfOrKxzPS3xvZH9e4j7N9WJXqPXe+FmwG3zr1q05Wi9ee2rVqmW2nTs5nsd4vli6dKk5D9oni/D93Hbbbaab2nGf5/XbHo9VYre24/3O7ls831SqVCn1d+7DfP/2z+e+xK5aDl2wx/MHu+eZSGV9RvXr1zfX3/Q+QwuPLw4DuuOOO9IcP9yH2X3MIUeuDntxBl+D3dZcR2soXF7KlwDwyy+/NBuUB82BAwewdu1a09duj/3vjplQ0dHRZiwEL2Y8wOxvHHNw9OhR8zieUMgxm4YBCA9Qx2UyY8dxefxAyFomx2oxSMysn5/LYuDFC7Hj8nhxt5bFEyAvCtzRhw0bZl6Ly37++edTAwCOJ2FSjHVS5/hEnuy/++671Nfj+0wvW5DLst8OFmczC/k8bivHDFnHAD2rZfMg++CDD8zAVl6gOAaTnzvH0XBciqP0sp94n+P7cPwMiWNY0lumM7h8vo5jMMBgitshu9vRGRyzxZMOx+pw7Ba3OT9vZ0oBZLUdTpw4kbo/Osrss7Tfn3lsOu7LvOBzudb+nBVuVwZwDBw5Lopje7gPDBkyJHUsjrWNM9qfHT8DVzgu0xovzGMqs/dOHLvk+P4ZOJKz7z87x5NjAMLP1Rq/xcCBxxEDQ8f1ZVDouL7cxxzXledXXljt8TWYCOCq9N6HdSxbnxuPfY7npo8//hiLFi0y74Fj+ciVY9dxv7cS2axlOHN+dVZ61wzH98Zx2ByPzC/pHF/L8ZB8bxwX6I714v6a2b7qruPCOl+4ck1x3KetL5rp3e/svuXM+d3Za591bnfkeF/0heOHwa/j8fPGG2+Y7cIA0d3++OMPc67P6+QPS76kwvHbgJUFnJH0vplzACd3Dg4QTY/VGmLtQNywHJBsYTDluANzmfwG+corr6S7TGuH4gWLg2P5jSCjIJDL4nrzBJBedq39fRwk/P3335sdixdZntyZYMJBr0OHDjWP4QBX3jgwmwEkB6gzqOJAWQYLfJ9siXDEoNpaH3vODPonLpfbiju8/YGcWVDiuOxTp06ZFiSe3Kz3Q3wvGR1I6S2f9/Gbc27i++U3X34W9u+DrRLcDtndjs7gslk/ijdeSH799VezvfjaGe3nzuK3e66rdXKz50yAyXXj/pjeAGzr785iSy4HOhNbRNiqzeQHJnWxNcQ6Zrk/O17suD/bvxYDl/SSFRjkpLdOjp+XlWWbWUKAtZxnnnnG1PZKT+3atZFbx5Pj58jzAL84s6WYrX/cBvYtiNb6skYet3Veymz/sj5Xnut4MeU5wT7w5Jfc3ODM+dUZ1jXDPihxfG98D2wdmjJlSpptb5/glJP14v6aneSVrDgeF9zPeG1z5ZqSX5y99vFxGV1X7FmPZ7mcjFrinP3C5gqeExkcs4U1P3hEFrCz2NzMg5HN6gwgHW/WCdnKBPzmm2/SPJ8XHcfMXi7TKg2S3jKtAJBdwvwGk16BUvtl8cDmN8H0lsWDP72DkM3T7733nuneZjZteoEju3H4TYSsrD42gbM1wPE5vFBwuewizA6+FrHlwB5PXM7i63NbOAbCbOlyzA60OH5ebJZns39GBTXdhduR3dWOFyNuR+vveYHdHszM69SpU7r7gavYrc39ju+LgZaF7zW9bOH09uft27ebk2h6+3N2i1OzO+fZZ581x4P1PtkdRV9//XWax7IlhcMF7D8Dvi4vnvYYVDrbJcuhBWyNYeBpn4Fqj+eSmjVrYs2aNem+d97su99z+3hiax8vbmwx4Da64YYbzPnCwtZVtlbx88pofXMLW3H5xcXet99+a4IJ9mSQVXqH3YkWtugwQ9udrfnZOb9mxfG8xPdG1nnJCqTsz3Xcr9jS6Y714rWH+7fjkB534/mCWdoMZO23Pxs9uM/xixmPXU/A8wG3hxXw2Z+z2bptBXG8BjKLm8dxep+hhT2Q/Bx4Pc3o+LEfRuMODEJ5PHOITnqtnnnBM4thZYBlJHgwcgwOC+NyfBC/VfLbEfv6+S2ZJ0a2MHIcHltV+HeOnWCQ9/bbb1/SrcxvXyw/wosCu6R44megxzIM/HB4keCOz2/b/ObNFHJeaLhj8cBgyxFfj+vGnYglPXiy5tgrnvx4UPGbClsPecG7//77zcWXpWL4wTOtnycLHnTs3ubFnzg2hu+LOzpfn39j9wLfj3VBefTRR80Oz/EWfB/89sl0fS6br5Pdg5VjHvheWHaAY6VYnJJjKqyAyJl0d25nvn+O++K3K1602f3Bbzz2Fy573GZsCu/Tpw/27t1ruofYgmt1ueUWdrmyu4Zdsfzc+Tnx83r11VfNvubusTf2raTcj9iqy1IHDCgY8LDlL6NWJ1dxv+D+wQCBxwyDb34mHOOTVZcGS5D89NNP5nPkvsaWcu7zbKmcNWuW2T94wcgKgzUGtvxcGVTxRMqTN++3Wj143PHY4Tdw7l+86PGzYDkRjvPh61v4bZnHN/cLju/jlwR2LTtbP4/vnaWSuK/xs2UZC36757g/Xig4bIFYQJfrwW3HsUXcF7nNGJDygs0yTXl1PLH7lOcBvmdeOOy7f4nHFz9rHjMsL8PXZIsOW+fY/crzEMuw5AZevHi+4X7Bcw7Pmwx+eJ81lov7IMd/cl/n58wv8jwfp9dTYrWSMWDm+ZEthul9ec6IM+dXZ3Ff5b7CL03sXueXUrbCcr9gaTHiMvk4XiNYeozXDxZgZpeqO9aLxyG3Ba9vPF543WOAxvMpv6Rl94t+etjLxHXhMjn8ge+L68zrJ4cfubP3IyfYs2SN3+e1ki3rjA14/eO5gF/wrG3HHgzuf/zceJzzcY7lc6Kiosy5h9cAHuPsCuYQIHa/85zA//mZZobXL6t8E49zfr7WrDXcdxxb5jn2jw1S+dX9a3hCGRhnM5eI2VXMkGVmDrOFmEXJbD1mCP3333+pj2PWI9PTmdHExzG7iVk26WUQssQESxcwpZ0p8MwGYhr88OHDTdaqfTYSs11ZcoDlAZi9xnIYLNlij9nLLLXB98DsX2bf3n777SYLzEphZ8o67+ffmY3FLKPPP/88dRnMjmZGE9PX+Vp8H8x+W7BgQZrXYrbULbfcYtaF684svrfeeitNhqKVBcz7ncXsMJYwKFKkiMmqYtYUs7cds+KsLGD7Mh2Wffv22Xr16mUrWrSoyfJmCR+WGnD8DKz9gtm2LHPD1+R24fu1/0wzyuLNKFM2PRk9n6VBWI6B2Z3MpuSynnnmGVM+xl565S2yi8vma7IUA7NS+Z75+XGbMists/eW0Xqkt3+z/EvDhg1TS1qwFAn3d34uWT2X+/+zzz5r1ovP577KZTHD3sraz0p0dLQpAcLjlMcEj1m+Z5bKsEp3EPdZZl7XqlXL7Msso9G/f3+TRW+PmYhvvvmmKRfCY5tlNVjGIqMsYJa+SQ+zmPl4rhP3cWaS25eQsMqwMIOWxx/XiRm1POaZOe4KZ4+n9LKALcyEtsolZZSBzAxTlnri/sQsSX6mLIFjX8Yio/OrdSy7wjqeWD6EnwNfk8cQ19Uxe5rnRe5HfAw/O2ZBsyyM4/vdtWuXKT3Cc4ZVYiqzz9M6v1mleZw5vzrD2k5r16415YK4LF4bWGXB/rpALBliXZN4zmb5MZZgss80dXa90jsOWfaHZV94/HI/5P7YtWtXs0xn3oOjzM5jvMZwH7euX7x28v05cy3P6HqQ2TXd8b3zfTlyPLaJGfDM2uV25LmJ2z+98kwsscPjjZ8NP7+7777bZK3DoQwMsdQMX5+P43bmZ8nfMzqHOL5HLjO9W3rrxfMcSxq5Uk7L3QL4T/6Fn+JN2GzOAekcwM0WU3dhtzpbNNj6lZtdVZKCA845EJ0tWmzJE986nvISu0E59pItRCLiXbyqC1jyDpv7OZaRXS/somISCrsO2R3orRcrf8UZKNitw6w5dh9yWAO7MTmkQPKGjicR8TQKACVdHI/GcTgcN8EMNwYPHAfF3yVrHCuX2dR05uDLo/loOUif43k4joVjSFmGheO03DG20ZPeZ35wTCpzxC9PvHnb8cSxopl1DnEsmH1Chzfx931WxKIuYJFcwBInWQ2637lzZ7YzaT0Fg5is5kL25VEmWQ2K56DyzCoHeHLXrlXAOj0c0G4NePc2/r7PilgUAIrkApYncCxR4IhZte4uLZDXGARkVRDZl8d1MvMvM1YGvLdhpQOrSHd6mL3rSmauJ/H3fVbEogBQRERExM94VSFoEREREck5p0a6csAsu7M4kNlTCkGKiIiISNrxqxy+wVnMsioy71QAyOCP1fhFRERExLNxNi3HedWzFQBac15ygY5TqYmIiIhI/uM0dGywc2aucqcCQKvbl8GfAkARERERz+XMcD0lgYiIiIj4GQWAIiIiIn5GAaCIiIiIn1EAKCIiIuJnFACKiIiI+BkFgCIiIiJ+RgGgiIiIiJ9RACgiIiLiZxQAioiIiPgZBYAiIiIifkYBoIiIiIifUQAoIiIi4mcUAIqIiIj4GQWAIiIiIn5GAaCIiIiIn1EAKCIiIuJnFACKiIiI+Jng/F4BERGRvJBsS8bes0dwMPY4EpOTEBYUgipRpVEivDACAgL0IYhfUQAoIiI+K8mWjCWHN+HnXYuw5vh2nE9KuOQxhUIicUXpBrixSlvULlIxX9ZTJK8pABQREZ/079H/8Pqa73Ho3AkEBgSaFsD0xCTEYub+Ffhj3zI0KVYdzzS+CeUKFM/z9RXJSxoDKCIiPoXdu++vn4JHlozH4XMnzX0ZBX/2LYW07sRO3DbvDfy+Z2merKtIflELoIiI+FTwN+LfL7Awer35PRk2l57PQJC319f+gNMJ53BT9Q65tKYi+UstgCIi4jNGb/jFBH+uhX3pG7vpV8w+sMoNSxLxPGoBFBERn7DiyFb8vHuR+TkiKAwDanVCjULlUatQeRQJi8LErTPx2daZaZ7Tq0o7dCrfDOULFEdkUDhOxJ/G+uO78Pl/s7D7TDTeWjvZjAssHl4on96VSO5QC6CIiPhE1+9ra75HIFLKuRQOjUT3Sq0RGhiMBRe6g9PDxzFL+M01k/D40gmYuGUGahYujwlXPIIKBUriXFI8Ptg4NQ/fiUjeUAugiIh4vUXRG3D4fErCBzHzt8vM4ebnwiEF0L3S5ek+j62C9lYf344NJ3fj6w5DcW355vh06wzMObAag+v9DyXUCig+RC2AIiLi9dj1a7X+5dTJuLNpMoPpj73KChbfogBQRES8vvt37fGdLmf82mPwGBIYhEoFSuHpxn1xPO40/ti7zPyNy2VNQRFfoi5gEREXnUk4hxNxZ2CDDYVCI1EkNErbMJclJSUhPj4eERERl/yNyRoJyYk5Wv6s6183U8PRnjOHMWTx2DRdyptP7YXNZtOUcV5s/9mjWH9iF7ac2oej50+Z2pAFQiJQvWBZ1C5cEfWLVkZwYBD8hQJAEZEs8ELBFqDpe5dj7fEdiLYLDIgBIC8e15RrhivLNkRIoE6t7jZ06FCMHj0avXv3xl133YWOHTsiMDAw9cKeUw8sGo3gwGCTDdy36pUYdfkDppD0rjPR5u+xiXE4nRCLQqEFcvxakncYtP99cC1+3LXAHLsUZGaFsfGvF2aI4Vc5G4qGRuGGKm3Rs3JbFA3z/S91OkuJiGTin+iNGLXhZxyIPWYuHPbjwiwn489gcfRGk4hQeH0kBtbpgh6VLjcXF3HfhTwhIQGTJk3Ct99+i/Lly2PgwIEYMGAAEkKTcrz8rTH7zf8bT+7GwkMb8P1VwzCoTlcMWzEx9TEJyTl/Hck7B2OP49U132H1se1pxofaH8NJdj+fiD+Dz7fOwqSd8/Fkwz64qlwTn/64dHYSEUnHucQ4vLL6Wzy9/BNzIaH0gj+LNf7sVEIs3ln3Ix5ePB5HLkxDJtnv9j148CD+/fdfnDyZsi0TE1O6evfv348XX3wRVatWxZeffu7WTXwuKc50A1csUDLN/VYXsXhHTcjb/n4D647vNL87Oz40GTacTTiH51d+iTfXTsr0mPd2agEUEXFwNuE8Hl36Ibac3Gt+Z/eQqzin7L2LRuGDNg+iXGRxbWOHwO7IkSM4cOCAuTHIS+/n6OhoJCdnfgEuXbo0bryyC96OSVvOJSdYNqZawbLmM7Tv5o8KuXT8oXgeDtd4ctnHJnjLzrFru/D/b3uWmLGlzzS+ySdb8xUAiojY4UVj6PJPTfCXk6xSLoeZpEMWj8Nn7R5HwdBIvwnsMgrorJ8Z2PGxFo7lYyBXrlw5lC1bFs2bN0f37t3Nz7yPt127dqFXr17m8cHBweb2yiuvYMiQIQgKCsLYGXNN0WZ7rUrWQURwKCKDwszvVaJKo0PZRubnxdGbzID/dy+/D3/tX4l9Z48gLinBtPr1rtreZARbs4YEIAD1ilTKwy0p2XX0fIzpts9u8Odoxr4VqFukEm6scgV8jQJAERE7k3fMN8WAnZ1KzNGY1oPRpHh1/LRrId5fP8V0A4/e+AuGN7nFa7czW+GsFrvMgrtDhw5dEtiVKlUqNYhr2rQpunbtmhroWffzMQziMlOwYMHUn6+66ipMmDABVapUSb3v8lL1MP/Q2jRddo837I2ykcUuPq9ck9RxXX1mj8SxuBhsjzlgxmuWiiiC0MAQcx/HjD337+epCSBsE7q8VF23bEvJ3XGib62dZAL58KDQLI/fQASgT9X2aFmyNqoWLGMy+g/FnjBzSX+zbTbOJJ43jxu78Vfz+ftaS74CQBGRCzjWb8Lm39NMJcYAgVOJZTSThD22ElQoUCLNfWyHYCsCZ5XghcYTA7v0gjrHrlhr7B0FBASkabGzAjv7oI4/M7BjS507MNi7/fbb0aVLF/Tt2/eSciw3VmmLuQdXp7mv75yXs1wux3llhYHhdRWaZ2OtJS+xFuQ/hzc6ffyGBYXgzlrX4a8DqzBt7xKcjD+L2oUq4PaandC2dH0MXPAe4pMTzJeKT7fMwHNNb/WpD1QBoIjIBVN2LUzt9nV2KjFLmYiiuLdOF7y8+ju82uLONH8LDAjAt9vn5lkAyMDu6NGjTrXYOQZ2VosdA7jGjRvj+uuvT7fFzl2BnbNCQkLwxRdfZPj3xsWqoVahCth2+oAp2+Mu7P5laZDI4HC3LVNyx5TdC1Mz9Z05fuOSEsyXhJiE2NT72Pobff4ERjYfYIYLzNr/r1ne7AOr8FD9//lUzU8FgCIiFy4GHPSd3eDhyUZ9sfzIViw4tO6Sv7HO2IqjW804swoOmaXZCeyyGmOXUWBnBXEM7Dp37pymtY7/s1UvrwM7d+F7HN7kZty14B23LZNdhOwavqvWdW5bpuRe1v68g2mHAGQlGbY0wZ9l44k95v9S4UUuPtZmw9wDa8yXAV/hnUe6iIibbTm1F2cvjPlxVbeKrcxAcZadyAg7LBkgphcAMrA7duxYpkEd/+fNPrAj+xa7hg0b4rrrrrukK5aBHVvQfF21QmXxQN3uGLNxao6Xxc+LmZ8jmvZHRHBKEol4rv9iDritZEvzEjXN/zvPHErTir/x5B7cAAWAIiI+ZfPJvaa7z9XMwRLhhfFAvR4Yv+k3k0CQkUAE4rfls7Hxm7/TDe4cA7uSJUumBnENGjTAtddee0lXrL8Edq7oW+1K06rzxX9/5qjlj8Hfyy0GoGGxqm5dP8kdW09l7/hN73i+t05XbDq5xxSBtzC4ZJFwX6IWQBGRC/O/BgUEINFMEeW8Jxr2NgPN2X2cmSQkY+XezZg26q/UIK5+/fq45ppr0u2KDQ0N1eeSTQNrX4/SEUUxav3PSLQludQyxOCvZHhhjGh2Gxop+PMaTODg+D9+3tlVMCQSb112jxlOwELQjsHkybgz8CUKAEVEOAYwOcHltgMOEmetucH/jEGUQ5JASECQuY+16awApGGzxlh9+Ftt7zzAQf8tS9TCe+t/xj+HN1yY8zX9QNDKJ+YczpwHdmDtzur29TNRIRF4r9W9KBFeCI8sHp86+4+9nFcV9CwKAEVELlz8XVW1YFlTTHjCFY9c8rcelVub27DlE00ZCtJUYnmrTGQxvHHZ3WYeZ7bQrjz6H7bFHEB88sXu9qjgCNQtUhGtS9VD54otUVCzfXgltt5lN4ErKiQC77e6D2Uji+ORJeOx/fTBdB9XKMS3irkrABQRAVA+soQpJOuK6XuXYdWxbekWg55/aB0m75yPnTEpA8nZPVU5qrS2dT5gAV+O6yK2xp6IO42E5CSEB4WYsh6ONQXF+9QqXD5bM/dEXQj+uI9w+sf/Yvan+zgev/WK+tZsMAoARUQA1C5S4ZILSFZTibHWGG/pOXL+lKkpZl9GonbhCtrW+YwXcg70F9/CGpCOSSBZHb82AO+0uhc1C5fH6A1TERQQhHpFKqc+/2T8GdN6bB2/dQpXhC9RACgiApi5XkMDg9N0D2Y1lVhGwV96eGFqdqG8hIi4V4GQcLQpXQ9LDm9KHXOb1fFL1hzPjzS4Aem18L+65nvzM9uIref6igCbE30eMTExKFy4ME6dOoVChQrlzZqJiOQxziP6+95lbqsnZp9ZWrtIRXyUzlhBEXGPZUe24PGlE3Kl1fiK0g1MWSBP50q8FphnayUi4uF6VWlnunrcjV3LN1Xr4PblishFzPpuUqy6Cdjc7e7anX1uUysAFBGxm0niluodzVgid+HF6LKSddCxbGNtZ5FcxGSeYU1uNsdcgJvrSlYtWAa+RgGgiIidO2tdh8pRpdzSisDLUERQKIY26qtMU5E8wDF/zzftb0bt5TQIDEAA2pau77Ot9woARUTssFbfe5ffZyaCz0kQyKnfwoNC8f7l96NkxMVJ5UUkd7Uv2wgvNrvdFP/OyTF8Ren6eKnZHabWpy9SACgi4oBlQj684mE0KFol2y0HbIkY1/Yhk/whInmrY7nG+KTdY6b0S8ox6ZyggEBTDeDRBjeapI/QIN8tlqIsYBGRDHBmgam7F2P8pt/MlG5ZTTbPvwcGBKBftStxV63OmvlDJJ8lJidh2t6l+HHnfOw+c9gcoxwrmHwh05+BIVsKmfnPFvsuFS8zxy8LQ3sjV7KAFQCKiGThXGIc/jqwCtP2LMXWU/sumXCeY/0qRZVC5wot0KViKxQNi9I2FfEgrHi36eQerD+xC1tO7cPBs8dM9MeZQGoWKm+KtLcoWRuRwSlFo72VAkARkVxsUfjqj8lYuGoZ7r3vXjN3bLWCZRAWFKptLuIFevTogRkzZuD06dMIC/PugM+R6gCKiOQSW1IyHrvtfkwc8R7KxRVA3SKVFPyJeInNmzdj2rRpSEhIwJQpU+DPlAQiIuKCDz74ACdPnjQ/T5jg/lkHRCT3uoEHDx6c+vuYMWP8elNrDKCIiJOio6NRvXp1nD171vxevHhxHDhwAKGh6v4V8XQ///wzbrzxxjT3rV27Fg0bNoSvUBewiEguGDp0KM6fP5/6+7Fjx/DTTz9pW4t4uNjYWDz00EMIDLzY8RkcHIxx48bBX6kLWETECcuWLcPnn3+OpKSLGcC8mIwaNUrbT8TDjR8/Hvv370dyckr5F0pMTMQXX3xhWs38kQJAEREn/Pjjj+mOKVq6dCm2bdumbSjiwVq0aIF+/frh6quvNi1/BQsWRGRkpPnbwYMH4Y80BlBExAnx8fFYt24dTpw4gW7duqF79+5o3ry5aVEYMmQIoqJU+0/E0/FLW3h4ON59912TEMLfWRjaH8cA+u4cJyIibsREDwZ8LB8RFxeHLl264M4779Q2FvEiTODil7lixYqZ330p+HOVuoBFRFzAFkCyLiAi4j2OHz+emsHv7xQAiohkIwAsWrSotpuIl2HmPhXTFzgFgCIirlAAKOK91AJ4kVoARUSycQFRC6CI9x6/xdQCqABQRMQVagEU8e4u4KCgoCwzZP2BWgBFRFwMAJkRbNUQExHvagFk61+AH2f/WhQAioi4GACy+1cXEBHvbAFUBnAKBYAiItkIAEXEe1sARQGgiIjLFxAFgCLe2wKoADCFWgBFRFxsAdQFRMR7v8CpCziFAkAREReoC1jEe6kF8CIFgCIiLlAAKOK91AJ4kQJAEREXaAygiHey2WxKArGjAFBExAUaAyjinU6fPo3ExESNAbxAAaCIiJPOnz+Pc+fOKQtYxAtpGri0FACKiDhJ08CJeHcCCCmLP4UCQBERJykAFPH+FkCVgUmhAFBExMUAUC0IIt5HLYBpKQAUEXGSWgBFvLsFMCQkBFFRUfm9Kh4hOL9XQETE27qQNBWciOfbe+YI1h7fgS2n9uFg7DH8V3QX6j/7P3y6dQZqF66IZsVroEBIOPyVAkARkQysWrUKc+bMwb///otNmzbh4MGDCAgIwP3334/mzZvj2muvRa1atbT9RDyo1t/8Q+swaed8E/xRcEAgEm3JQEEgqmlFfL1tNpJsyQgNDMb1FS9D36rtUSmqFPxNgI1bKwsxMTEoXLgwTp06hUKFCuXNmomI94s/A5zaCSTHA8ERQOHqQHAYPBlPid9//z3efvttrFy5EoGBgSboS0pKSn1McHCw+Z2P7dixI55++mlcd911+breIv7u8LmTeH3N91h+dCsCEYBkZBneICiAjwzAwNqd0a9aBwQHBsGbuRKvKQAUEfc6vAZY+xGwayZwit/A7U7CAcFA8bpA9e5Ao0FAocoetfX37NmDu+++G3/99ZcJ/JKTk7N8TlBQkAkG+/fvj9GjR6t7WCQfrDu+E08s+whxSQmmdS87mhavgddb3o1ID/+SmhkFgCKS945tBv4cBOxfkBLo2RIzfmxAEMCTdO2+wFWjgcj8735Zvnw5OnXqhLNnz5rZAlzFQLBcuXL4+++/Ua1atVxZRxG51MYTuzFk8TgkJCc61eqXkUAEoEHRKnj38nsRFhTq8wGgsoBFJGc4iuTf94EvGwEHFl+4L4sAysbuVBuw9UdgYh1g29R8/RTWrFmDq666CmfOnMlW8EdsBeQYwXbt2mHfvn1uX0cRudSZhHN4ZsXEHAd/xOevO7ELEzb/Dn+gJBARyVnwN+9J4N93svn8JCDuJDD1BuDaT4CGd+X5p8Gp3W688Ubzv/04v+xg8Hj48GHceuutmDt3rulGFpHc88HGqTgZd8YEbxFBYRhQqxNqFCqPWoXKo0hYFCZunYnPts5M85yGRauiS8WWqFmoPKoWLIvQoGD0mT0Sh86dgA02TN65AFeWaYzGxX27JV9nJxHJvuVvZT/4S8Vv7TZg1kBgR95/8x4xYgR27dqVYfBXoEABvPfee9i/f78JEpkZ3K9fv0yDwPnz52PChAm5uNYisufMYfy+d1lqy1/h0Eh0r9TaZPcuiF6f4QZqXqImmpeohejzJ7H+xK50u4LHbfrV5zewWgC9xJEjR0wpii1btpiLUFhYGGrUqGFKUXDckUje75RrgYXDU34OiQJaPweUbAKUagpElgT+eQFY/OKlz2s4EGh8H1CkJpCcABxdDyx/E9g5HZh+B3DXFiCieJ68BbbWvf/++5kme0yZMgUtW7bE0KFDsXXrVtxyyy0mS5ite999912mgSUTSkJDvXMskYin+2X3PyaL10r6YAtel5kp56TCIQXQvdLl6T7vi//+xOf/zTI/31StA5qVqJHm7wwoN57cg20x+01roq9SAOjBOBidFxhmFq5bt87cx4uOlZ1oXbSqV6+OBx98EHfccYcyECXvun5nDLj4OwO2hoOAI2uAbb8Aje5J/3ltXgRajwBWjwcWDAWCwoGmDwE3/g5MvRHY/isw7wmg82d58jY+/fTTTIO/66+/3tT6u/nmm03QR0zyqFy5Mt566y388MMPGT7/6NGj+OWXX9C3b99cW38Rf8USTNP3Ls9Wxi+7ebPCwHLmvn9Ro57vBoDqAvZQv//+u8kkvOeee7Bhw4bU+3mxYReT/UVnx44deOyxx8xF6csvvzQHhkiu2r8QOLzqYrJHzG5gbFFgUgdg4TMZP6/BXcC+BcDsB4DdfwE7pgG/9ADOnwTq35EyJnDj18DZ6Dz5AL/66qtMA8AbbrgBp0+fxuTJk9Pc/9lnn6F8+fJo1apVhs/lF7Vvv/3WresrIikOnjuOM4nncm1zJNmSTXaxL1MA6GEY3N17773o1q2baUGgrGqRMeDjjRmMbAXkRSs2NjaP1lj80upxKaVeXMUu37hTae9LigOSzqfcUh4ErP8UuY3HCIdUZKZBgwZmBhDH8YFr165N/XtGeNwuWbLETWsrIvb+O7U/1zfI1pjcf438pADQg/Aic9NNN+Hjjz82vztThNae1fL322+/mVkJOFZQxO24n+2annWpl/SsHAVU7ZzSEhhWBChQBrjyHSC0MLBy9IXlJwM7ZyC3rV+/PstjrHjx4qnz/9qz7uPfMxMdHZ36RU5E3OdU/Nlc35znk+KRmJyzygCeTAGgB+GgcQ44z2kXLi9q//zzj2lJFHG703subcVzJQCcPRi4eizw4AngvoMpXb+/dAcO/HPxcYdXpgSCuejEiRNOPS6z49GZY9XZ1xGRtH7++WcMHjzYjKVlYWNxLwWAHoKzELz22msZXlAaN26MadOmYffu3abr6tixYybIY72xjIJAjm9ia6CIWx3PvNs0U/UHAB1HAas/ACZfDfx0PbB7FtBzKlD52ouPSzib6+MAOb9vVnicpdfKV6xYMfN/eq2DjlQLUCR7/vjjD4wbN84Ma+Ixd/nll+Oll14y176CnFs8l4UHhXr93MCZUQDoARj0sbUuswtFkSJFsHfvXgwbNgxdunTB7bffbmqXff311xg+/EIpDgdcHpebkJCQi2svfifRGqvnInb5suVv3ScpxaP3zAF2zQB+vwU4tBzo9GHax6eOCcwdZcqUyfIxzL6vW7eumebNXsOGDVO7kbNSsmTJHKyliP9q1qxZ6hc1NmosXboUzz//PNq2bYvnBj2W669fu3AF+DKVgfGQ1j8Wl83MvHnzzM0xU7hq1aoYNGgQXnnllUuewwOGU1OxFZAzHYhvlgpauHAhVqxYgY0bN5rfQ0JCUKVKFVMj8oorrkCFCm4+iWV3ovRitYGQyJRgz1H0CqBiByCkQErrH7FETC5iYMdtldkXJHZB8fjq1asXJk2alHo/k61YGJoXpMzw+MxqPk4RScFjkVUvWPOWN17zHHvFGBAWLVoUrzz1PN44PwunE9KOdW9Vsg4igkMRGZRynqoSVRodyjYyPy+O3oS45AQUCS2AJsWrm/uqFSxr/r+8VF2cjD+Dk3Fnsfr4dlMGpn7Ryj790SgA9ACffPIJgoODszUHKQeYlypVKsO/s+WCMxIoAPQtLP0zatQoU8eOQZ/VQsVEIp4guT/xZMqfWcvukUceQadOndzz4kVrZe95Zw6k/F/2cmDjl2n/xvvOHb8Y/AVHAgVKIzcx+GvatKn5ApbR0IsZM2Zg1qxZGD9+vAnktm3bZmoCcpty+EVmSST8DBiAi8il4uPjTQu6FeytXLnSZNfHxcWZ81adOnXM0Cdm4dsfn//73//wxRdfmONx3caTZtq2ZLvxwo837I2ykSlDNOiqck3Mjazp3qoULIORze3qmF54Hq06tg1DFo8zZWCuLd/cpz86BYAegHOGOhv88cBg1y6/AfXp08dk+7IIdEYYECxatMhcqDQWyfvx82RhcM5KYdWEtO638GRptWrxZwYwHEvDgsRjx45FiRIlnHod7pecBo31Jdldmrr/FKoChBYE4k+nfVKVziktePwbFa8H1OyV8vPOP4DTe4GtPwGNBqWUfuF9/JbOJJDyVwALn724rNLNgIDcH6EycOBALFu2LNPH8MsTW9g59ojjkDZv3myy9VkEOjP8bAYMSHuREfFHDOrsgz3eOLyCQSDPK2yNZ49F//79TbdvkyZNEBUVZZ67Zs0aEwTycW+++aapeWt1C/+vUhv8sCNtz1jfOS9nuT6rj21Hu2kZdyFzKri6RSqheiHfnmUrwOZEGltMTAwKFy5ssnDUneFebL0pWLCg05m/bIm47777Ug8qtux8+KHD2Kl0cAqrmjVr5nh9Jf+wziMHQ//111/Zej5bCfnFgc/nN+vMsKXLfn9haxaDQCZE8Oe/Hy+JqEN/Acl2X1wG7gQKV0l/gR9XSSkWzYCv6YNA3duAwlVT6gKe2Aqs+gDYfKFoMgO/1i+kTC2XB8cf3xe3rTvxYsVC7jzunEk2EfEV58+fN8GdfbDH4I9fSnkOqlevngnyGPDxxnMRv2hmhNe4b775Bj/++COuvPLKS/7+5tpJ+H3P0tT5gN1lbJuH0KhYVXgbV+I1BYD57L///kOtWs53qVWsWNF0+fLWvXt3Mz7p6aefxjvvvJPp8+bMmYOOHTu6YY0lv06qnJKM2W+ORYldwRMwv1lz3GBmRYz5haRSpUrYt29fun9fP30M6m94CLkiIAgYtAeIyptv32wVzawVPbvY6squYhFfxVqz7La1unCtYI+t3zzX1K9fPzXQ461Ro0aIjIx06TWs3gwO2UjP2YTz6P/36zged9otQWAAAtC3Wns8WO9/8EauBIDqAs5nro77YyYwbzR9+nTzP8vHcExEZgVnszO+UDwHg3yrKz8nGDyytatHjx7mRJ3RyfjAgQOoXbv2JQEgT+pMPqp/7bVA9ATg2KaU6dvcGfzV7pdnwR/df//9JsGD2zcnwbX9NmKWvoI/8SUsP2YFe9aNCRs8ZtgrwC+UDPLYKMEWPgZ7ERE5L9WSUeBnKRASjtdb3o0HF3+A+KTEHAWBgQhAo+LVcE/tLvAHagHMZ7zAslUvuzjGiPOSck7SzMYyLV682NRQEu+zYMECtG/fPsO/s2WXY2fatGlj9qWTJ0+arGCOWeO38oy6KB9++GG8++67qffxGyMLkbO0EMf/WYkk9oENs2LZ8mxE/wt8c5kbCzYHpJSKuWszEJlxYlNu4IwdrVu3Nl+ucvJliduoZcuWpps9s24tEU8P9lavXp0m2LOmRGRAxjJI9t24/D08PHez9rOy4cRuPL50As4lxadJCnFFixK18GqLOxGR3UoHHkBdwF6EXW1sruWE89nBlj9mI3IcU0YtgByDxIs7xxqK92FAwTJBGbVOsfWKY/MmT55sSsGw7tzjjz+OFi1amCQhBnMZ7RccgsBv8Qz6fv31VzMo2woomfzAMTcchM3Hfvfdd+jXr1/ahSweCfwzwn1vtscUoOYNyA8smXTNNddcknXoCm67qVOn6lgTr8EeASvYs7pxeQywtyE0NNQEd/bduGzpCwvzzADp6PlTeGPNJCw5sgmBAQFIduI4Dgpgu18A7q3bFX2qtje/ezMFgF7m6quvNhfpzC46LOXCD5atfGytYCYns4CZjcjMKHYRZoSD0bdv355Lay+5iSdjBnKZYcB35MiRNPex9YmJHOzmzaj8C1sBeYLn+EJm3fGLBEuclC9fPvUxY8aMwZAhQ0wrc7oZrdxnObXbmvE5a/ljtw2LRDd5APmJ2+LFF1/EG2+8YVrznGkN5OPYWsrnPPTQQ8q29xLsLlx8eCPWn9iFzaf24si5kyZgKBgSgdpFKqJO4Yq4okwDFAvznS/ObGhwbNljVjuvPQzq2G1rBXps4WOwx3OEN+F7WRS9wZSHWXnsP3NfcEAQEi8MVTHhXkCAKfPCmT66VrzMBH7lC2RdHcEbKAD0MpzqhoPQMwsAefG98847Tbo8ZwXhtza2zLCGIDOkMrs4PfXUU3j11Vdzae0lNzEDjkkK2emWnD17tgnmWE8rI0wI4fCAjBJC2ArAmoM1atTI+IW43y57A1h0IWvXlujamD/W/Lv2Y6COQ+tiPmKrKLf7559/bga6M1jmscRjlBcPfh78mcciZ9vhOEKWyxHPdybhHL7ZPgdTd/9jigizxYfBgD3rPv7foWxj3FGzE6oWzHrmGE8LBNhzYB/sMSvdCvaYfWvfsseEjazG23mbA2ePYe2Jndh6ai8Oxp5AYnIiIoPDzWdZu3AFNC5eHZFe3N2bHgWAXviBsQuXFxp348Vq586dujh5qcsuu8wUKnYVs784bzSzvzmLRWYOHTqE0qXdUHT5yFpg5t0ps3oEBGceCDLw4zfy6j2Aa8bnadKHK/hFi+MpefFkoMxhFEycseqWsZXEU7vD5FJLDm/Cq6u/x6n4M04nC1hdgnfV6oxbqnf0yLlhOcTH6r61/mewRxybxxZ++2DPmgVHfI8CQC/07LPPmla67I49Sg9bLNitx3GC4n3Y+sZgg/UeXfXVV1+Z8XpM/MkoESRXypVw/z20DFjzIbD7T+DMfocHBABFqgPVuwON7gOKZXNWkTzGKak6dOiAJ554Am+99VZ+r45kw7fb52D8pmlmvJctm5mil5WsjVda3Gm6DvMLk7ysIM+6cbgH8XxhH+zxCwqDPQ5REP8QozqA3ocXeTbJ80B2RykKdlkxMWDLli2m+K94H7Y+ZSdxh9m/zz33nBlWwG7MrHz55Ze47bbbkCvOHQNObgeS4lPmAeY0cqEpFf69Bb+Ucco4DrngvMp79uxRcWcvM2nHPIzZODXHy+H4sRYla+GNlgPzpCXw+PHjlwR7HJJhjfN1bNnjcA9rWkjxTzGqA+h92I3EqaXatm1ruoJzUu/Nmi6OWZsK/rxXdlqDR4wYYYK/YcOGORX8UU5rC2YqonjKzYt9//33JvizyjYxYeuqq67K79USJ206uQcfbPzVLduL3cbLjmzBt9vn4vaa17j1Mzh27FiaLlzeOHzHGqvLLyGs32kFe5xAQMGe5ITahT0IWwA5bytLdzAbMTsD/3lCYAD4008/mexi8V7szmEGHkuzOBv8MYP1+eefN8XBncWWYsm4Hpo19ygDch5f77//vgJAL8r0fXnVt6bbl922A2p1Qo1C5VGrUHkUCYvCxK0z8dnWmZc8j3+/v2531Cta2SSDrDz6H8Zu+hUHY4+bv0/cOgNXlK6PaoXKZmu9WLLLvlWPN47ZJbb6s+uW0z5a3bgM9jSXu7ibAkAPw2K+HHTOLjlXB//zBFG9enVT042148S7Mdhgdm5WY/isMaQM/kaOHGm6gF3BC4ykjyWWDh8+nNoay+EZ06ZNMy0zVat63zyh/mbOwdXYc/aw+blwaCS6V2qN7TEHsCB6PbpXSr8wfqUCpTC69WD8F7Mfz6/8EqGBwbi7VmczN+xd89/Gyfiz5nFfbPsTLza7Pct14P7jGOxZszkxWYvHX+/evVNb9phxr2BP8oICQA/EKbg+/vhjvPLKK2bu1/3795uMLftZGSwc3MuWQrbicGaHJ598Mt8rsot7vxBw+qXMWoPZQsXAj1MDcpo2zgpjb+nSpRk+l3NKlyvnmRm4+e3s2bN4/fXXU0u/WEEg/2f3+ttvv53fqyhZ+GnnAjNuj123h86dQJeZw839hUMKZBgA3l27MxKSE/H08k8Qm5iSgLXl1D581/EZ3FStIz7cPM20Cs47uNbMP2tfJ5AZ9Y5j9qzpFFkyiMEea7dawR5rtCrYk/yiANADcWYHZu/yQsPkkBkzZmDmzJnmQs4K7ewSZEDIb4q82HM8Us+ePb2uYKdkjfvBBx98kOljrKnZmMmbXjYvg5eMWhjvuOMOk1XIcaeOt0qVKvl1+SCOy2WrKlv72BrPmmosyn3ixAkze494tuhzJ0yBZ1ew5Eub0vUwY9+K1ODPWtaqo9vQvkwDEwASpxsb++e3SP73UGqwxzm0iWOvGeDx+LWmTGOwl9GxKJIfFAB6WNYnZxJg8VlrDBgv0l27djU38T8M8DkVEwsTZ5SswenHsoPL4zzDGSUK1atXz7yuv2LrujXDzssvv2xacjKbb1s8y+aTrgV/VC6yuBkryG5iR9tPHzQZwOwSjk9OhC3Zhi//+hHHv1lpArzbb789tWWvSpUqCvbE4ykA9BAc99e3b9/UgcCkyeSFLQbvvPMOrr32WrduDHY73XPPPSbhiIWiHTOO+boclyQXC+2q1c+7bIs5kO4sH5kpHFrA/H86IfaSv8XExyIwINBMFXcs7jQQGIDLenTE16NmKdgTr+Tdsx77CM7WwIK9DP7sW3lUqV2Ic/kOHDjQbSUfuJyyZcuagsbMNOR4U0cMAK+5xr1lLryZAkDvnPKN2b/ZkVkFJvs/nUeigj/xWgoAPQAH4TN717GLTwGgWN577z1TByynQSCfz7Ftv/zyS2qR6bvvvhsPPPBA6oWMrYNMJGrfvj26deuGv//+260z1HgjBYDeJzvj7U5dyPAtFBp5yd94H8f9MbB0nCZOxBtp7/UArN6+ceNGPProo2nuVwAoFhaC/fPPP015n+wOJOeYNg4rmD17tklmsMfadixCTgz2mHDEsahsleYYQ85JzELl2alN6QsUAHomFjznONnHH38cP/74o6mYYCkeVsgEbK44EHsM55PiUb3gpfX9qhUsi/1nj5rxf5YS4YVy+A5E8o8CQA/BizovzFdccYXJ+ixRooTKc0gaLCPBOWlZ8Jktec7O72m1GrIwOJM6ONzAEb9sTJkyxUx1xjGBrD/IDGGWoGF5GY5/Y/mKmjVrYvTo0SZhyZ8oAPRM/ILCxBzuk3369DH7L8+dbC3fs3yTKf/iCo4XXBS9Ae3LNkJEUFjq/aXCi6Bp8RqYd2hdmta/ukX8N0tevJ8CQA8q/cKLLeuODR482GQc/vHHH/m9WuJhWOrnhRdewOrVq9G/f//U0j+OwaD9761btzatIwzkeIHMSMmSJc3c0d98802aLyadO3fGX3/9ZcpcsC4h6w6yRMzw4cNN3TN/oADQM1155ZXmf/uWaU6pxuPj39/nI9ChtbxVyTroULYR2pauZ36vElXa/M5bWGCIuW/ilpkIDwrBm5cNNI9vV6Yh3rzsHpxKOIsfdvydJlisX1QBoHivAJsTg3tcmVxYXMcCzyy5wQLQnGVAxJXJ4q3gbP369Th9+rQZ48eaYyxHwXF8HGLg7laXUaNGmeQR1qTkrDXsgqtbt67PfnDly5c3WdMMviX/cCYWzsvMcam8cV7m9FqjORsOZ8d57t8vsDB6fWom8KSrnkXZyGLpLrvP7JGmWDTVKlwB99fpZgI8MxXcsW0Yu/FX00VsKRAcjqmdXkRYUErgKOIJXInXFAB6AF5IBw0aZL61cj5gEW/AgsgTJkww3W8HDx40BamfeOIJtGvXzucyIzl2krUAHcfpSt4GfPPnzzcXNiYpccwqv+Bw/Cr3RSYvcbgDp8JkSS1i8eYhS8a5fb3Ysti36pUYXK+H25ctklcBoLqA8xlnXOBsAxxfpeBPvAkLSA8dOtTMlDFx4kRs377ddMlxjOHkyZPNxdtXWuhjY2PNGEzJXdxn2JrN2pf8QsEpLtmSzeEG/Az4BYPFyzl7DVu+OR7Wmv2GFz2OkbWCP2pSvDralW5g6ve5C0vLFAyJxG01rnbbMkXygwpB57Px48ebcVTsshDxRuxyvvPOOzFgwAAzzpBz5PIizG5otpjxb95c1JzfqEmFoHMn4GPPh30LH7d3RESEGW/KgK9Dhw4m+537WXq433EKtk8//dTsc/bYEv1Eoz5YNfc1M7Wbq0kh6bHBhqGN+qHQhaLRIt5KXcD5iCc6nrBuvPFGfPTRR/m5KiJun9mGrThMbmLLGesMPvjggyhdurTXbekdO3aYOp1scWImtWQfkzWsgI+tdfYBH7t02YKcVcCXHWuP78AjSz5EUnJSjoPAgbWvxx01O7lt3UTcSWMAvQS7fl977TVs27Yt0+xMEW+1a9cuM0brk08+MRd/lpZhFjETnrzFqlWr0KxZMyxfvvyS+onifMDHG7tv7QM+BntWwGdltOcWBoFPLfsE55LiXa4PyDF/TJe8t05X3FrjqlxbR5GcUgDoBY4ePWpa/5hZyJYSEV/PVrYSRqKjo9GjRw/TvccgwNMTRhi4sBj21q1bTR1E8Y6ALz3HzsfgrXWTTa0/Z+YJ5ng/dvmWjyyOZ5veigZFq+TZuopkhwJAL8CLHy+IHEDPwqUi/iAuLs5kaXKc4ObNm03CCI+Fnj17um2uY3ebOnWqWT8GrqVKlcrv1fG4gI8tpFaXrhXwRUZGpgn42HKaHwFfelj5jGVdpuxaiIWH1psuYbbwBV7IiWTAZwWGNQuVR6+q7XBNuaYq9yJeQQGgh2OR5xo1apgMStUVE3/Eea9Z6JyBIAMHjrFj1zAH9DN48CRffvml6bo+f/68W8eleXvAZ7XwsfakJwd8mYmJP4vNp/Zhy6m9OH7+tOkaLhASgZqFyqF2kYooF1k8v1dRxCUKAD3cvffei59++skMLldhbfF3HFvHQJCzlRQrVszMhMMbZybxBGPGjMGTTz5pAkB/42sBn4ivi3GhDqDKwOQxJnywXMEbb7yh4E8EMOPBfvjhB/OFiAkjb731ljk+2BrIVsH8HnfHmnP+UgKGAd/KlSvTdOlaAR/nKX/mmWdMwMfafAr4RLybysDksVtuucWUPvjvv//MwGgRSYtzuX744YcmYeTIkSNm/B1b4DincX7gGMVff/3VJIH4csDH28KFC9MEfFYLnwI+Ee+gFkAPxSmNvvvuO5P8oeBPJH2c/YEzP3B+YSthhEWBeWMgyBki8jJhhF0pvjILiGPAxxY+zqXr2MLHLt2QEM1xK+LL1AKYh3jhYubjxo0bdXIVcSFhZNq0aSYQZMDCLmEGh7fffnuufpFiYLR//34MGTIEZ8+eNS33nG/W2wI+Tq1m38LH98WZWRxb+BTwiXg/JYF4oH/++ccMmv72229x88035/fqiHilpUuXmkBwypQppqWQs4twlhF3lFJieRAmpHz88ceYO3euGZPI+yxRUVGmIHSvXr1M8OmJrYKct9ixS1cBn4j/iHEhCUQtgHmAFxEWkj1x4oTJqPO2VgQRT7N9+3a89957mDhxovmd8w0zYYTlZLKDgR+z83l8BgcHm5az9FhFq1kO5uGHH8bzzz+fr8M5FPCJiD0FgB5m1qxZuO666/Dbb7+hW7du+b06Ij41o864cePwwQcfmJ85rzbHCbZq1cqp5yclJWHEiBFmSkZ+MePvzuLjq1atajKY2YWaVwGfY5cuu6fZpduuXbvULl22VKpLV8T/xKgF0LNa/6xpjxYtWuTx016JeKNz586Zgs2cVpEZ9gyGmL3LL1wZtbizla9///6YNGlSmq5eVzAZhcf29OnTceWVVyKvAj52R9uP4VPAJyKkANCDsOBz7969zck7Ny4QIpI2YYQlWzhOkF+4ateubRJGbrvtNoSHh6fZVPfff7/JyM9u8GdhgMkuYXYj169fP0fLUsAnIjmhANBDsDupQYMGqFSpEmbOnJnfqyPiVxYvXmwCwZ9//tnMKvLQQw+ZoI/JI5yGrmvXrhk+ly1szz33HJo0aYKmTZua53PaxhdffDHdx3PcYMOGDbFs2TLzsysB34oVK1Jb+Bi0Wi18jl26rixXRPxTjLqAPcPnn39uBqfzBJ9XY4REJC12Cb/77rvmeGRrHTN4Oe3c8ePHTYtheipXrozVq1eb2p0sAH3PPfdkGgASh3e8+eabpus5Iwr4RCQ3KQD0AHFxcab7iQVVebERkfzFWUWYMMJWQZZGcRZbDJlgklUASKVLl8a+fftSW+scAz6O4YuNjVULn4jkCs0E4gE++ugj7N271wwOF5H8x25clm355ZdfTMteTsf+pSc6OtrMZcxlW126DPgKFixounQZRLJLl93K6tIVkfykQSW5gGN4Xn75ZdPVVLdu3dx4CRHJBtbiZNdubmE38LBhwxTwiYjHUwCYC0aNGmUuNGxtEP+WGH0MifujgcQkBERFIrR6RQSEheb3avktllTJTWz549CP9evXq4VPRDyaAkA3Y+DHgeD33XcfqlSp4u7Fi4ezJSfj3IKViPlyKs79sxrJR0+mfQDrxtWqjAI9OqBQ/+4ILpPzKczEeVu2bDGtdLnR/Wvh0A9174qIp1MA6GYM/jjwe/jw4e5etHi4c4tW4fCjbyBx534T6CG9WSWSkhC/aQfit+zCibc/R8Fbu6HECw8gsGCB/FhlvywY7eqMH9lJABMR8XSalNaNDh06ZLp/H3nkEZMNKP7BlpCII8+8jwM9hyBx98GUO7MKMFh+JCkZp7+ehj2tbzWthZL7WLA5o9Iv7qIp2ETEGygAdCMmfvACk1kdMPEttvgEHLr9GcR8OiXlDleDi+RkJB05jgO9H8XZPxfnyjrKRTVq1MjV7l+qXr26NrmIeDx1AbvJzp07TemXl156CUWLFnXXYsXDHX7kdcTOXsrR/9lfSLINsCXh0B3DUGH6hwhrXNudqyh2XCnI3rlzZxQoUMBk9FK9evXQq1cv8zNnEmF3siOO/bv88su1zUXE4wXYnPg67EphQX81YMAAzJgxA9u3bzcXDfF9Z6bNQ/Sdz6b7t5JjhqHQTddn+Nx9ne9F3L8b094ZFIiQqhVQ8e/PlCmcixjIbd68OcuWQH6pyyiRi/fv3r073b998803uOWWW9yyriIirtBMIHls48aNZh7Q0aNHY/DgwXn98pIPks+ew+6mvZF88nS6rX/BVcohqHiRS+4v+/UbsMXHY3fTPul3FwcEoOjTd6HY4wNya9X9HmcDefDBB3OlK5it/wcPHjRDQUREPDkA1BhAN+Ck8ZUqVTLzhYp/ODPlTySfiMmw6zdx1wHTwmd/Y/2/oBJFEPPdHxmPFbTZcGrCZDO2UHJH//79zQmS5WDcidnFDz30kII/EfEKCgBzaPny5ZgyZYqZIzQ0VAV+/cWpj38yrXWuKHRLV1Mn8PS3f2T6OAaWZ3+fn8M1lAw/h0KFTCugO1sAg4KCUK1aNTzzzDPa8CLiFZQEkkOs98cxRbfeeqt7PhHxeEnHT5lafq5gnb8C3Tvg3Px/kbjnQqmYjAQHIXb+CkTdcHXOVlQMBno7duzAqlWrsHLlSpPAsW3bNnTr1s38nNOyMGxJ5O3rr79GeHi4trqIeAUFgDkwd+5c/Pnnn6YFkC0A4h/i1m51+TlRN16DwMhwnP7m96wfnJh0aYKIuIxj8fjFbNmyZWZ+bqublgEfx+gxYLvhhhswb968bAeBXB5vkydPRqtWrfQpiYjXUBdwDloVOOl7y5Yt0bNnT/d+KuLRErbvdbn7t+CtXZF07CTO/OFc127Cjn3ZXDuxP0aXLFmSGvyRFei98cYbZhwgWwDvuOMOcx8DOVfwS1+xYsUwffp0nQNExOsoAMym3377zVxcXn31VbcPJhfPxixeBDr/mYfWq47wpnVx+sdZgJPJHZxdRHKmXLly+Pzzzy+5n0HboEGDzM/ssp04caIJBPl4yqo1n3/nMc/WRc4tfM011+ijEhGvowAwG9iKwLF/HTt2xNVXa5yWvwlgsg+LN7vQ+kec9s3519DoDHccpwzQ0mzXgAAMHToUERERae6//vrrsWvXLvz666+mALRV/NnxuZxJ5KmnnjI1Ar/44gsTTIqIeCNdZbLhu+++w/r167F48WK1/vmhkBqVnJ/5IzQEBXtfi/P/bkT85p3Ov0a1itlfQcGxY8dMuZeZM2fi2WefNUXaV6xYYTKA77///gxb9rp3725u7D5mQLhnzx4kJiaagJDJXlFRUdq6IuITFAC6KCEhASNGjECPHj005ZOfCmtUy+nHFujSDkHFCuPYyAnOv0BwEMKa18veygmWLl2KPn36IDY21ozPu+6660yXL5M02HrnTBDH1r6qVauam4iIL1IA6KJPP/3UdP/88ssvufOJiMcLKloIofVrIH7T9iy7gln7L/lsLM78/JfzL5CYhMj2LXK+on6GrXZjx47FY489Zub8nTRpEipWTGlJ5f9szeNcvSIiojGALuHk7y+99JKZ55NTv4n/Kjywl1PjAA/2fRw7q1wH29lzTi87sFhh03Iozjt9+rQ5LjkTxwMPPGBKu1jBn0XBn4jIRUoCccEHH3yAI0eOmFk/xL+Zun7FC7uUDeyUgAAUua8vAkJD3LtcH7ZhwwZcdtllmDZtmmn1e//99zUrj4hIFhQAOokTK7/++usYOHAgqlev7uzTxEexqHOp94e6lA2cpaBAhNSqjCKDb3bfMn0cizkz+GPrHpM8OPZPRESypgDQSe+8844ZVP7cc885+xTxcQU6X4GCt3RxuSh0utiSGBSE0uNHqPXPCefPn8d9992H2267Db179zaJH7Vr18755yAi4icUADrh8OHDePfdd834IqtYrPivM2fO4Oeff0anTp3Q4Ou3Ed7p8pwFgZyBIigIZb9+HWENa7pzVX0Sk7CuuOIKU+T5o48+Mv9HRkbm92qJiHgVpcQ54bXXXjM1wp5++unc/0QkTyUdPYGkk6cBNsCVKIqgwpcWAKb9+/eb2V+Y/T1nzhxTDohCQ0NReuJInHzlY5z68IeUYC7JhXllAwMRVLYEynz0AsIvU2JRVvgZ3H777ShatCj++ecfNGvWzPltLSIiqRQAZoGlI8aNG2eKyRYvXjyrh4uHs8Un4Ozv83H6pz9x/t8NSD56Ms3fg8qXQnirRijUrzMiOrREQGAgDh48aOrBsSAw68NZ88ny5wcffBDBYWEo8dKDKNClPY48/iYStu42tfxYziXTLt/AQBQa0BPFhw9CYJRasDLDbc/hFxyHyxqcbPVjECgiItkTYGPxrCzExMSYidOZCMFK+v6ESR+cHmr79u3pTg8l3oG7ecyXv+L4qx8j+fiplJa6C4HcJTgXbFISgiuWQYnXHkFEp9bo168fpkyZkhr8WdasWYNGjRqleZ3zi9cg5qtfcW7RaiQdPJJ22aEhCKtXHQW6d0ChW7qYVkfJ3KFDh3DzzTdjwYIFpjX+iSee0Aw8IiI5jNcUAGaC84jWr18fb7/9Nh555JFMN6R4rsRDRxF930s4v2iVa09kK12yDVG9r0XhV4eg8eWXYevWral/5tRgLEGSmaTjp5C4/zBsiYmmlS+kankEqBix0+bPn2+Cb/rhhx/Qvn171z5DERE/EuNCAKgu4ExwyjcmfTDbULxTwp6D2N99MJKij7v+5AslXjiLx655i3Hgv+2oXLky9u3bZ1r67rzzziwXwWngeBPXcPu+9dZbGDZsGNq1a2fm3y5Tpow2o4iImygLOAOrVq0yRWWff/55hIeHu2t7Sx5KOnUaB3oOSQn+kpJysKBkFD0Sg9mNu2HtqtVo0qSJuZszT4j7nThxAj179jRJV5y7988//1TwJyLiZmoBzMDw4cNRq1Yt3HHHHe7e5pJHjj47BokHDmeYlRvasCaKPXEnwprVRWChKCTuj8aZn/7CyXHfwXYuLs1jgxCA4vuOIenr3zF37lxs27ZNJYFywcqVK01dPwaBzPjt1q1bbryMiIjfC/bHriVm9q5du9b0kbO8S/ny5dG0adPUJA8ONp8+fboZc6T5Q71T7PwVOPP99Az/HlKrCsr/Ph4J2/fg6LOjkXzsFMJbN0bRJ+5AWONaOHT7sHSfd/y1T1CpWwezv4h7j8uPP/4YQ4YMQYMGDTB79myTeS0iIrnDbwJAZmuOHz/eBHUnT6Yt/WGV9Khbty4GDRqE77//3nTzsSVCvNPJMd+aqdUyav0r2OsaBEaE4dCdzyJx1wFz37mFKxFUujgK3/E/BBaOQvKpM5c+MdmGUxOnoMTIh3L7LfiNs2fP4v7778dXX31l/n/vvfcQFhaW36slIuLTfD4AZA03JnGwlAtb81hPLKMWiE2bNuHRRx81Pyvxw3sl7DqAc38vz/QxtoSU/SA55mya+xn02ZKSUv9+iaQkxHw9DcWGDTIBpOQ8055ftHbs2GHm9b311lu1SUVE8oBPJ4FwDFGdOnXw+++/m98zCv4sDPyssogffvghrrzyShw54lDHTTxe7LzlZmaPzJz+YYaZAaTkW48juHJZBBSIQGSnNih0Rw+cmvgzbLHnM3yu7Uws4lZudP+K+5nJkyejRYsW5rhcvny5gj8RkTzkswEgM3iZSXj69GkkZTMDdPHixWjbtq2ZC1i8R9zqzSnFnDORuPcQ9l9/H0LrVEXlFZNQbdcslP32DRMYHhs2KvMXCAxA3Not7l1pPxIfH4+HH34Yffv2RdeuXbFs2TJTU1FERPKOT3YBL1myxJTosG/Ryw4Gjuyauv7667F06VIlhHiJ+C27Mp+GjTt+xTIo883rSDpywowDTDp2EuHN6qHIY7cjsEAEjjzyRsZPDgxEPKd7E5ft3bvXBH7//vsvPvjgAzzwwAOa1UNEJB/4XAvguXPn0L9/f/OzM8Hf3XffbR7HlsKMgkDWBGRRWvEOmXXfWoo9dx8CowrgYN/HcXbaPDN928mx3+HYs2NQ6NZuCG/TJJMXsMEWF+/elfYDM2fONNnTBw4cwMKFCzF48GAFfyIi+cTnAkBO27Zz506nun05ywcfv3///kwfxwCRs4KwfIx4voCwkCwfE9agBhK27rokWIxbtcn8z67hjF8gAAEhWb+GpOCx+MILL5iW9Msuu8zU+uP/IiKSf3wqAExISMDo0aORnJx+6Q9HTPTgXKOcaSArDAI/+ugjN6yl5LaQGpWB4MzHACYdOorQ2lVN8oe9sBYNzP+JBzJJ/rHZEFKtgntW1scxiYqB30svvWRu06ZNQ/HixfN7tURE/F6gr2X9Hj161KnHstwEs3w5BsnZVgzWEcxuQonknbDGtYEsvgScnDAZgcULo9zkd1Hgfx0RcUUzFHnkNpQY+SDiN+9E7OwlGT85KTnlNSRT//zzj+nyXb16NWbNmoVnn30WgYE+dcoREfFaPnU2njdvHkKc6JorWbIk3n//fQwdOjTL7l97x48fN3XLxLNFtGtmCjZnJnbmIhy48REkn4lFiVceRplv3kDBfp0R88VU7O/xIJBRHUAKDUF4c2WtZtZazuOLX7CqVKlixtBec801OflIRUTEzXwqC5jlJNgNnJVx48aZQI4teq5asWKFSlZ4uLC61RDWvB7iVm3OtCXw/KJVOLholWsLDw5Cwb7XIbBggZyvqA+KiYkxiVU//vgjHn/8cbz22mtOfSkTEZG85VMB4LZt27J8zI033oju3btnay5XziTCBBPxfEUG34zou55z/4KTkvHyliWYXLasmas2KioK4eHhCA0NNbfOnTvj9ttvhz9at24devXqhejoaPz000/mWBMREc/kUwFgVjN9FChQAGPHjsWYMWNMKYrChQub+3nhJv7OFsTY2Nh0n8/5gp1pYZT8V6DblYjs1Bqxc5aZ6dvcIiAARQbfhOiN83Do0CFzu/inANP1yQQkfwwAv/jiCzOPb61atUyNvxo1auT3KomIiL+MAYyMjMz07yVKlECZMmXwxBNP4OTJk6k3Fo1mSw5//uabbzJ8Pi/wWb2GeAYGZCXffQqBBSOBIDfs5kFBCKlRCUWfvtvMWdukSZM0Ney4b/B3Jjr4k/Pnz+Oee+7BgAEDcPPNN5vZcxT8iYh4Pp9qAWzUqBEOHjyYYQFotth06NDhkvuZDMIB6yxXkVkWMVsY69ev79Z1ltwTXKYEyv30Pvb3fCil3l+Sc+WBLhEUhOByJVHup/cQGB5mvjVxjFvDhg1N4XELu4I5Cw3nn+ZwAV+3fft29OnTB5s2bcKnn36Ku+66K79XSURE/LEFsGXLlgjKZA7YuLg4kynseGNgyPIu/HnDhg2Zvkbz5s1zYc0lt4Q1qoUKf3yIkCrlTRdudoS3rI/y0z9EcNmSqfdVr149TRIR97urr77atIY1aNDABIg5mYbQ0/3yyy/mWOAMOgx6FfyJiHgXnwoAObF8VuMAs4vde2z9K1++fK4sX3IPZ/WoOO9zFBlyKxASDARmEQhe+DuLRJd4/VGUmzoGwaUvLV7MsX5sASOOf2MdSs5yweQQ3s8vJKx/50uBIMfAPvnkk7jhhhtMwMus+MaNG+f3aomIiIsCbE5cnVjagQkSp06dQqFCheCp+FY4NovZiO6+6DIA5MwhgwYNcutyJW8lHTuJmO/+wOkfZiDhv92XdguHBJtWQ84HHHXjNQh0mCnEEceNvvHGG2Zcqf0MF2xNfuaZZ8yYuI4dO5pyKK1atYI3Y+LUTTfdZAo8v/nmm3j00Uc1l6+IiAdxJV7zqQCQJk+ejL59+7p1mZy9gMWjWWaGySLiG5LPx5lZP5JPnjbdw0EliiC0VhUEsJXQDXhosVVw+PDhWL9+PXr27ImXX37ZK8eRzp071wR/HNv4ww8/4IorrsjvVRIRkRzEaz7VBUy9e/dGjx49Mh0L6CqW9rjjjjtMbTPWAXR2rmHxbEzoCG9SB5EdWiLyyhYIq1/DbcGf1WrMfZFToX355ZfmfyYqMWN29+7d8Abc11999VUzkweTXjirh4I/ERHv53MtgMRCtCz0fPjw4RzP3cuLOOcL/vbbb3HixAlzX1hYGGrWrGnGPtWtWxf9+/dH5cqV3bT24qvi4+Px0UcfYeTIkabrmOMGhw0bhlKlSsETcepDjnP8/fffTXmbF154wa1frERExL38ugvYsnXrVlPahWVdcpIYwgvgxIkTTQuOY6Yju4bZQsKLIy/qIs44c+YMRo0aZcbRcf957LHHzLRpOT222KV9fvl6xK3ZgvhNO2E7e85MXRdSsTTCGtVGeKuGCC7nXLDJ5A62pjPLl3UPWSJJREQ8mwLAC/bt22cCOI5fcgVbOdjyx/FazHi0Aj12323cuDE1wYT3ly1b1ozvKlKkiPs/SfFpx44dMwkknJmGs9SwNZCtzawn6IrE/dE49clPiPnyNyTHnOGOmVLyhkMVmNDM3xOTzM+RV7VC4UF9ENHxsnQTOLhvM9npkUceMQlVkyZNUuu2iIiX8OsxgPYqVKiA2bNnm263cuXKmfsyK9Br/Y1Zm2vWrMHTTz9tgjzi/7xY2zeYMijkGC9vaRUVz8KsYbYCMrmIc+g+9dRTZmgBiyo702rNffHUF1Oxp/WtODn+h5Tgjxj4cegD99VkW0rwZ54AxP69HAf7PYHoO59F4pGUIQ32LZMczsAglNnu8+fPV/AnIuKjfLYL2BHHAv7xxx8mS5iFazmLgZXMwendmjVrZga3s5uXF+H0cFO1bt0ay5cvNz+3adMGixYtMgPk2UXM1kCRnAxbeO6550yrW+3atU0LNAPD9Frq2N0bPegFxE5fmL0XCwpEYMECKDv5XZMIw9k8+Fp79uzBJ598YjJ+RUTEu6gL2AmcFSQ2NtZ097K0i9XSlxXWd+N0cgwE2ULy999/m25mFsjlWMHu3bvn9PMTP8di0uwOnjlzJlq0aGFqCPJLhsWWkIhDtw1F7NxlKS182RUUiICwUKwb3B23vjTMtPZxBhMmNomIiPdRF7ATmMlbtGhR06LpbPBHTCxhK+LPP/9suox5YWZ3MQNCdgc/9NBDaeaHFXEVW6NnzJhhxq5yH+vUqZOZdWPZsmXm78ffnIjYOTkM/igp2bQklnj9a/Tt1sMsX8GfiIh/8Jsu4NzGzThu3DiTzcku5O+//94rC/6KZ7GKSbNFkPNUP3RNNzy89lSGwV9Y07oo9sxAhLdsYJI+4lZtxvHXPsH5Zesyfo2AABS6vTtKvf1kLr4TERHJbWoBzAccpzV48ODU8YHsuhs/frxPzQMrec8qJs1WZo4zvXLtISRlsE+FNamDcr+OQUB4KKIfeBmHH3jZdPGW/ek9hLXI+MtIgM2G01/8ivjte3PxnYiIiCfx6Szg/MDZEhgEMpmE2ZQ33HCDqUUokhMcq9rv8vZokhyOoAy+U7Dlj5nAzPKNnb4AZ/9YgAN9HoPtzDkUf3FwFi8QiJgvpupDEhHxEwoAc0FERATGjh2LX375BQsWLDAzhsyZMyc3Xkr8yOnJsxgJZvj38Msa4tyi1bCdi0u9j8Wgzy1ZjYjLGiKodPGMF56UjNPf/q4WaxERP6EAMBf973//w9q1a1GnTh2TLPLMM8+YbGGR7Di/YgOQnPHUhmYe4/j4S+63xaXsc6F1q2W6/ORTZ5C456A+HBERP6AAMJeVL18es2bNwquvvoq3334bbdu2NTUIRVwVt3qzKeackfituxDWvH7KLCCWoCCEN6uX8mPRrBO44tZu1QcjIuIHFADm0fitoUOHmqLRnP6LU2x99dVXefHS4iNsycmwnT6b6WM4HVxojUoo8fqjCCpTAkHlSqHk208guGLplGVklZAUACQdO+nO1RYREQ+lADAPXXbZZVi1apVJDGHxaE67xZRtEXc4/e0fOPbSeBTsex2qrPsZVdb8hNBalXFy3Pfm70kHj2SxBM4frKx1ERF/oAAwj7GOIst5fP311/j1119NayCnphPJTEBgIAIKRGS5kU6O+RY7a3fD3na3Y3fT3tjf9QEEFi6I5LOxiFuzJfMn22xOdROLiIj3UwCYT2699VasXr0apUqVMnMQv/LKK2a+YpGMhDWq5dzGiU9A/OadSNwXjeDypRDV8yrEfDUNtvOXJog4CnX2NURExKspAMxH1apVM2ViOD7wueeeM5nC+/bty89VEg8WzmLOwRmXgQmtUxVFnxiAyE6tEdG+OQrf3w8V/voUCTv24fjrn2S5/ICoSIRULe/mtRYREU+kADCfhYSE4OWXXzZ1Av/77z80atTIzDMs4ijqxk5AYsatxLb4RES0a45SHwxH2W/fRKEB/8OpL37BgZ5DTD3ATAUFoWCf60xXs4iI+D7NBexBmCE8cOBAU0D63nvvxbvvvovIyMj8Xi3xIPs632vm90VystuXXWH+FwjLolagiIh4Ls0F7KWKFy+OKVOm4MMPPzSJIpxPmHPAiqTuIyPud3/wFxSIqF7XKPgTEfEj6u/xMAEBAab1b8WKFaZ7mKVjRo8erSm6xIho0wSFB/YC3NVVGxhosoRLvPaotrCIiB9RAOih6tWrh6VLl+K+++7Dww8/jG7duuHw4cP5vVriAYo9dx/CmtU1LXc5EhhgllHm81dU/kVExM8oAPRg4eHhGDVqFKZNm4bly5ebBBFOKyf+LTAyHOUmvYPwlg3STvvmiqAgBISFmuVEtG7s7lUUEREPpwDQC3Tt2tWMBWQAeN111+GJJ55AfHzWNd3EdwUWLIByU0ah2NN3m2DO3Jx6YkBqSZmK879ExBXNcndFRUTEIykL2IskJyfjvffewzPPPIOGDRvi22+/Re3atZ16LgNIJpiwJXHlypU4e/YsAgMDUa5cObRu3Rpt2rRB3759zUwl4l3it+zEyfE/4PTkWaYItKkVaF8uhr8nJZuZPsKa1EHhe/sg6sZrVPJFRMSPs4AVAHqhf//9FzfffDP279+PMWPG4M477zTJI+mZOXMmXnjhBTPdXFBQkAkibba0870GBwebWUjY5cxl8fElS5bMo3cj7rJ+8VIsevcj9G7YAnEbtyP59FkEBAcjpHI5E/iFt2qIsPo1tMFFRHyUAkA/cObMGZMcMnHiRNNyN2HCBBQpUiT174z+H330UXz22WempY+BnzMYJPJbw8cff4xevXrl4jsQdzpx4gSqV69u/j969KgpKSQiIv4lxoUWQI0B9FJRUVH49NNP8cMPP5hWvsaNG2PhwoXmb9HR0aZbl7UEydngj9gSePLkSfTu3dvMTyyeLy4uDt27dzfBH7GbX0REJDMKAL0cW/84vq9ixYq48sorzbzCHTt2NNPKMZjLDquL+NlnnzWzkYjnYnB/xx13YPHixeZ3tvayfJCIiEhmFAD6gMqVK+Pvv//GiBEj8MYbb2Dz5s1ITEx0y7KffPJJkzQinmn48OGmFdhq5WXwzvGeIiIimVEA6COYyMFuX3JM8rCwhZB/S+/WqlWrdJ/D5JL+/fsjISEhV9dfXDd9+nS8/vrrae7jZ8nWwIz2AREREVIA6EOYvcsuwKywjMzll1+e5rZ+/fp0H8tu5E2bNmHq1Km5sMaSEywB1KdPnzTJPwzYOfh3586d2rgiIpKh4Iz/JN5k7dq1qePAssLxga6ME2NmMMvNMDFEPEe1atUwadIkHDlyBKVKlTKlgZgBtm7dOpcSf0RExP8oAPQRP//8swnUspv4kRkuc/78+Th+/DiKFSvm9uVLzvCzIY7/ZDKQiIhIVtQF7COWLVvmdKvP2LFjzZg+dhXOmDEDbdu2dep5SgbxTLNnz0bNmjUV/ImIiNMUAPqIVatWZTnwnwHf+++/j3vvvdeUimEhabYYMYP42muvzfS5HFvIrkXxPHPmzMFVV12V36shIiJeRF3APjQzSFZWr15tbhYWjmbXMQO7N998E7Nmzcrwuexe5vgy8SycDnDLli0YOXJkfq+KiIh4EbUA+ggGaNnBVsFp06aZmUQ4F3BG2LrIUjPiea1/1KFDh/xeFRER8SK6ovuI8uXLmyncsoOlQyizLmQWluZrWDjtGKcc49hDZhRz3uABAwZk6/UlZwEgg/eSJUtqM4qIiNMUAPoI1vJjV6CrM4Cwhly3bt3MGELOKZuZ7du3o02bNti3bx/27t1r7rMyj1mSRAFg3mLAzgQQlecRERFXKQD0EczknThxYqaP+eabb7Bnzx6sWLECR48eNZmjjz/+OEqXLp1l8FawYEEz88S///6b5n6r7MzVV1/thnchrmBAzkBc215ERFylMYA+gjNCREREZFks+rrrrsMnn3yCv/76C6+88go2btxoWvXYkpQRtvINHDgQ//zzD/r165fhnLRPPPEE/vjjD6cSUsQ93b/8bNq1a6fNKSIiLgmwOTFpKLM/CxcubBIGChUq5NorSJ4ZMmQIxo0b5/Zi0BwjuHnzZtSqVct0O7744ovmZqlcubKZZ5hBJLNSmSzCuYVZmoStU+yeDgsLc+s6CUwwzhZdZ2eAERER3xbjQrymFkAf8vzzz5sP3krqcAfW/3vsscdM8EdcNucc/uyzz1Izj2+55RZ88cUXpjuS4xBHjx6NsmXLmoLTzE4tWrSoqTPImSrY/Zwbs5X4Gxb9njt3rrp/RUQkW9QC6GN++eUX3HDDDW5ZFlvy2LrHOoHpdS+zG5lFpSdPnoxmzZqlG6SsWbPGdFWydZBTlp09e9YknjAwZOsgWwnr1q3r1qDVH7A7n9m/3K4qAi0iIq62ACoA9EGvv/46nnnmmRwHf2y5Y/di9erV3bJe8fHxpnQMgxbeuGxOScfWQgYxVpcxg07JHGd0GTp0qCnHk9XYTxER8Q8xCgBl1KhRJsOXXO1yZbdv1apVMXPmTLcFf+mJjY01s5EwGGQrITOMOcaQr2kFg5yyrlSpUrm2Dt6qR48epjU1s+QdERHxLzEKAIU47Vv//v2xYcOG1Hp9meFj2G3LwPGll17K85YltmZxXmKry3jTpk3m/oYNG6Z2FzPZxN8TkVjrsXjx4njqqadM9rWIiAgpAJQ0wcJvv/2GMWPGmKQBq4WPwR5b26zC0QyqWOrlvvvuM/UBPcGBAwdMMGgFhMx45Xq3bNkytYWQJWwym8LOF3HmFWZWsyxP69at83t1RETEQygAlHRxqjjO+MHEDO4kHOdXoUIFNG/eHHXq1Mn2fMJ5gcHqjh07UscPMihkMWuWl2ERbAaDvPG9+Pqcxa+99pq5HT9+3Offq4iIOE8BoPg8dlWvX78+NRicN28eTp8+bVoy2U1sdRk3aNDA5zKMr7nmGtPqOW3atPxeFRER8SAKAMXvMJuYNQatgJDdo5zbmAkk9hnGnLPYm50/f95kZ7/66qt49NFH83t1RETESwNA9R+JTwgJCTHj4Xh79tlnce7cORMEWl3GkyZNMq2GVapUSQ0G+X+ZMmXgaZjdy9qKCxYswJIlS0yBbSbwREZGolKlSiYILFmypOkW97XWTRERyRuqAyh+gd+G2E1stRCy+5jq1auXOn6QXccsUp2fYzSZff3RRx+ZIJDj+6wkHYsV8DH4a9SoEUaMGIFevXrl0xqLiIgnURewSBaio6PTZBjv3LnTZEczicRqHWRyCVvd8sIff/yBO++8E8eOHXO6biODQQaCN954Iz788EPTKigiIv4rRnUARVzDANAKBvk/A8TQ0FBTZsbqMmb5GXY1uxtL9AwZMsQEoOymdhWzt8uXL29aONnFLSIi/ilGAaBI9rFVbePGjanjB1mcmgdVVFQU2rdvn9plzALVDNpy4tNPPzX1F3OK3cXlypXDsmXLULp06RwvT0REvI8CQBE34ji8lStXprYOcvo6JmKUKFHCTFVndRnXqFHDpaSMLVu2mHF8nCPZHdgS2LVrV/zyyy9KDhER8UMxagEUyT0M/hYvXpzaZcxWN47bq1ixYmowyP/ZIpdZKyNn82Bg6ZjoYY/jEIcNG2aym1n7b9++ffjyyy/x8ssvZ/ic7777DjfddFOO36eIiHgXBYAieXzAsWSL1WW8du1acz9nV7GCwQ4dOqBYsWKpz+HjWNA5MzfffDO++uorU8Lm22+/xZkzZ1C9enUTWI4cOTLd57AFslatWmYeZZWIERHxLzFqARTJP0eOHDHzLltdxtu2bTPBWNOmTVPHD44dOxbTp0/PsPWPQR67iNnaN3jwYJfXgeMWWdZGRET8R4wCQBHPsXv37jQlZw4ePJjlc1jf78UXX0TlypWxZ88elxNCHnjgAYwaNSoHay0iIr4cAOYshVFEssQgjjX+2J27f/9+M8tHVphtzJqA7EZetWqVmeqOpWnGjx+PggULZvpctipyXKKIiEhGFACK5CF2BZ8+fTrLx7GuH4tQM1j84YcfzHjBt956C7fffrspGp0VaxyiiIhIejQXsEgeYwCYVdFn/j0iIsJ0A7/xxhvmPhZ6ZskYdu1yHCG7kzMSGxuruYJFRCRDagEUyWOs18cyMJlh9y/NnDkzzf1MHKFmzZpl+nwGkMoCFhGRjCgAFMljFSpUyDIAzKgL1wrqspoyrmzZsjlYQxER8XUKAEXyWPPmzbN8zE8//WT+v/7669Pc36VLF/P/kiVLMm1hbNWqVY7XU0REfJfGAIrkMSZ4sM7fgQMHMnzMn3/+iV9//dWUg2F3LgO+Fi1a4Pnnn8dvv/2GRYsWZfhcti5yBhEREZGMqAVQJI+xG/e+++4zgV1m+vXrh/fffx+DBg0yY//uv/9+vPfee+jdu3emz+Ny+/fv7+a1FhERXxJgy2owkouFBUUkaywGzfqArO/nTiwC3aNHD3PjtHFRUVFpbiwtk1XgKSIi3smVeE1dwCL5gEkaL7zwAoYPH+7WlsXw8HDExcVhwIAB6T6GQSGnphMREf+mpgCRfFKrVi23lmthY/6YMWPw2WefZThbSP369d3yWiIi4t0UAIrkMZZweemll9CnTx+T1VuxYkXTdZtTQ4cONS1/JUuWNLOHOGKw+frrr+f4dURExPspABTJQ2fOnEHfvn1NNu/IkSNNpu/ixYtRr169bLUEsuQLn/fyyy/j1VdfTb2f5WMGDhyYOt6Pj2HgycSSWbNmufU9iYiI91EAKJJHdu3aZcqzcHaPn3/+Gc8++6wJzFgSZsWKFWZMIAM63rJiPaZq1ar4559/zFhCxwDy3XffNcsmJoCwtAwHB1933XWm5XHDhg259E5FRMTTKQAUyQOcx7dly5ZmHmC2+PXs2TPN30NCQkzNvx07dpiu3OLFi6f+jd3DvNln715++eWmm5dBHH9OD8cBfvXVVyYwZJfzNddcg/nz55si01u3bkWjRo1MOZro6OhcfOciIuKJVAZGJJd9+OGHeOihh9C+fXtMmjQpTXCXEXbXMlv333//xe7du5GYmGha8Ro2bGjmAS5atKjTr8+C08w6tm8hjI+Px7hx40xgyGU/88wzeOSRRxAREZHt9ykiIt5TBkYBoEguYY2/hx9+GOPHjzcB4DvvvGNa+jzJ8ePHzVjEDz74wHQXcxzhzTffrFqBIiI+HgCqC1gkFxw5cgSdOnXCJ598go8//hijR4/2uOCPihUrZmYX2bhxo5mjmDOIsEt5wYIF+b1qIiKSixQAirjZ2rVrzXi/TZs2Yc6cOSYb19PVrFkTU6ZMMWMVWU+Q3dW9evVS0WgRER+lAFDEjZhg0bp1a9Oytnz5clxxxRVetX0Z+C1dutQkj3D9WZ7m0UcfNV3FIiLiOxQAirgBkzZYxqV3797o1q0bFi5ciEqVKnnltmW2MbuCt2zZYt4Tu7Fr1KiB999/3ySPiIiI91MAKOKG4s4M/F588UVTkPn7779HZGSk129XZgQPGzbMdANz1pLHH3/cTCXHGobsJhYREe+lAFAkB3bu3Ik2bdqYIstTp05NtyCztytdujQmTJiANWvWmJbAG2+8EVdeeaUpXi0iIt5JAaBINv39998m2SM2NhZLlixBjx49fHpbNmjQANOnT8eMGTNw4sQJ897ZVbxnz578XjUREXGRAkARJ+r5cYyfPdb2Y5mXJk2aYNmyZaZr1F9wKrlVq1bho48+Mi2ftWvXNi2fnOVERES8gwJAkSywy7NFixampY9JEJw+7YEHHjA3toYx49ffcGq6e+65x4wP5NhAzjvM7mEGhZxZREREPJtmAhHJoqZf48aNzc/s4mU5FJZJ4fRud911l7bdBXv37jWtgCwfw9bQt99+G507d9b2ERHJQ5oKTuSC4+eAGduANdEptxPnAaZolIgEGpcGmpYBrqsOFAxLf5MNGDAA33zzTWqrVoECBTBz5ky0bdtW2zgdTAxhi+D8+fNx7bXXmkCQ8xeLiEjuUwAofm/nCWDUMuC3rUBSMhAUCCSmHcaH4Av3hQcDvesCQy4DSkdd/PvBgwdNLT/7Lk1m+DLbt3v37n6/jTPCEjHcRk899RS2b9+Ou+++Gy+99BLKlCmjbSYikos0F7D4LQZ7n6wEOn0N/LolJcBjxTrH4A92951PBL5bD3T8EvhpEwOYlPvHjBmDpKSkS4Kbm266yWTBSvoYJPfs2RPr1683YwN//PFHM9XcK6+8YsZRiohI/lMSiPiM+CTgwenAyAVAQjKQ5EKtYj42NgF4bBbwwjzg5KkYvPXWWybg48wYVmBTt25dDBo0yBRJlsyFhobi4YcfNq2A3GYslM2MYY4TdMyqFhGRvKUkEPEJbLVj8Pf7fyktfjl1Q6WjGH9TeRPw3XDDDabYc6tWrVCoUCE3LN0/MRB8+umnzXzJzZs3xzvvvGMKSouIiHtoDKD4nW/WAcPmuHeZE7sDV1dz7zIFZp7kxx57DMuXLzddxW+++abpIhYRkZxRACh+ZV8McPVXKWP5CoSkJHPUKwnULwkUjwTeWwK8vzTtc97uBPSpd+myth1PWRY7fYtGAHPvAApnkCEs2ccuYM6Z/Mwzz+DAgQOmpuKIESNQvHhxbVYRkWxSEoj4lY9WAgkXcjWKhgM3NwRCg4BZOzJ/3rkEoOcPaW/sRiaOUDtxDvhuXe6vvz/iuMpbbrkFmzdvxsiRI/HZZ5+ZQtJMGomLi8vv1RMR8XlKAhGvdjYemLThYsLHvtNAow+Bfj8BbyzK/LnJNmDVobS3TUft/g7g8zUpmcWSO5hMM3ToUDOjCLOrn3zySdSrV89kDjMBR0REcocCQPFq8/cA53Jx5rGDZ4B1h3Nv+ZKiVKlSZn7ldevWoU6dOujTpw/atWtn5lkWERH3UwAoXm1ddEpB5+xgAejlA4EdDwFL7gJe6nDpeD/OGrI22i2rKk5g69/vv/+OWbNmmbEszLxmV/Hu3bu1/URE3EgBoHi1DUey10XLrt5XFgKPzgJunwr8uCklKWRKXyAy5OLjOIOIfbew5I1OnTph1apV+OSTTzB37lxTP5AJIwwKRUQk5xQAilc7FZe9un+frkq5LdyTcnt7cUoR6BrFgJsbpB0neDrenWsszgoKCjLTyP33339mWrlRo0aZRBF2FdtPzyciIq5TACheLYB9tG4yY1tKUklThylrA934GuK6qKgoM5fw1q1b0aVLFwwePBiNGjXCH3/8oUQREZFsUgAoXq1cFBAU4N6Akq1+9sFfyUj3LV+yr0KFCvj888+xYsUKlC5dGl27dsW1116LNWvWaLOKiLhIAaB4tYal3DP1G3WpmTL+j+VgLInJQKPSbnoBcYtmzZphzpw5mDp1Kvbs2YOmTZuaruKDBw9qC4uIOEkBoHi1ZmXTtthRh8pAlxrANRemcatZLOV33pj5W74g8FMfYEDjlMdeWRl4qg3w7rXAlqPA9+vTLs+xS1jyX0BAAHr06IH169dj9OjRJhjkdHLsKj579mx+r56IiMcLsDlRbdWVqUVE8hKDv/afp0wHZ+3IC+8EKmawm7adCMTEA29dkzJVXInIlG7e/aeBmduBscsvJn2wa7lFWWBSnzx7O5JNJ0+exCuvvGKCwRIlSuDVV1/FbbfdZmYcERHxFzEuxGsKAMXrMZt35Hz3dQXbG9cF6FozFxYsuWLHjh1mZpHJkyebruF33nkHHTt21NYWEb8Q40IAqK/H4vVubQhUKeLeZBAu67JywPU13LdMyX3VqlXDpEmTsGjRIoSGhuKqq64yXcVbtmzR5hcRsaMAULwex/WNus59LYCMIzm7yDvXqgSMt2rTpg0WL16M7777DmvXrkWDBg3w0EMP4ehRVfUWESEFgOITGpcB3rzGPQcExwRO6AZUKuyONZP8TBS56aabsHnzZjM+8MsvvzSFpN966y3ExcXlbOEcOn0+Hjh6Ath9ANixD9i1Hzh4FDgTCyRnY3oaEZE8pDGA4lOmbAKe+islOSTJ5nq3b1gwML4L0KFKbq2h5JcjR47ghRdewIQJE1CpUiW8/vrr6NOnjwkUnZaUBEQfB/ZHA7HnL95vlmG72AwdFASULQGUKwVEOEwwLSKSSzQGUPzWjXWB6bcC9Uqm/O7MuEDrMa0rArNvU/Dnq0qWLImxY8di3bp1qF+/Pvr164e2bduarmKnHD8FLFsP/Lc7bfBntQjaHALFfdHAsnUpLYNqERQRD6MuYPE5rPs3tR/wYVegVfm0gV5IYMrNmt6N/11VFfiqJ/B1T6BcwXxbbckjdevWxW+//Ya//voLsbGxZrwgu4p37tyZ/hMY3G3bA6z7D4hPcP0Fdx8EVm4C4jSptIh4DnUBi887chZYdxjYcAQ4cT4l+CsekTKLSINSQJHw/F5DyS9JSUlmbODw4cNx7NgxPPzwwxg2bBiKFClyMfjbuhs4lMPkEX7TCA0FmtYBwkLdsu4iIo5UB1BExAWcPeTtt9/Gm2++iYiICLz44osYNGgQQqKPAdv3uW9bFowEmta9MGZQRMS9FACKiGTDgQMH8Oyzz+Lzzz/HtVe0xx8vvYVABmtBgUDlckCBCCAqEggNAXYdSMkAtndli4wXHnsOWL4BqFYBqKj5BUUkfwPA4Fx4fRERr1SuXDlMnDgRQ4YMwfkV62BmymQAGBycktV75hxw7CRQ9kKWkSOO9XNUqABQoxJw9GTK7zv3A6WLpwSRIiL5RAGgiIiDJnXqAqcSL97BBI5Fqy+cNYMzDgBPn730vnIlU8YSskYg8WeOKaxUVttdRPKNsoBFRBwdOuaebcKu45JFgVOngfN2xacPHtE2F5F8pQBQRMQRAzZ3KFkspSi01fpn4SwiCXYtjCIieUwBoIiIPXbRpteVmx0cN8hA78iJS//mrtcQEckGBYAiIo4BYJIb5vKNDAcKRQGHj6cs01F2ikqLiLiJAkAREXvpBWvZbf3LbLyfu15HRCQbFACKiKQ5KwamzNyREywdU6p4Sjfv2XPpPyY4SNtdRPKNAkARETu79+zB8fMZBG3OKl4kpc6fY/KHvQKR2u4ikm8UAIqIX4uOjsZ3332He+65B9WrV0eVKlXw46zpSEp2GAdYrBBQoihQvPDFMX78nTe2Gjp2/yYlpYz/Sw8fHxGWS+9IRCRrKgQtIn7lxIkTmDdvHubMmWNuGzZsMPfXq1cPXbt2xVVXXYWrm7VE0M6DaZ9YszIQbhe0lSqWcqMla1OKRVNYCFC0EMB5hBkEOmL3MmsDaj5gEclHCgBFxKedPXsWCxcuNMHe7NmzsXLlSjPFW7Vq1UywN3z4cHTs2BFlypRJm6Bx4NjFoI6WrnPuBeMSgPn/Zvx35n6UK5WDdyQiknMKAEXEp8TFxWHp0qUm2GPQx58TEhJQtmxZE/A98MAD5n929WaIrXNVywObd7p/Bdk6yPmBRUTykQJAEfFqiYmJplXP6tJla9+5c+dQtGhR07L33nvv4eqrr0bt2rUR4Eq3K7t3Dx8Djse4b2U59q92JoGniEgeUQAoIl4lOTnZjNuzAr6///4bMTExKFCgANq3b4+RI0eaFr7GjRsj0DE5wxUMFmtXBVZuTOnWdYc6VYGwUPcsS0QkBxQAiohH43i97du3p3bpzp07F0eOHEFoaCjatm2LJ5980gR8LVu2REhIiHtfnKVcGtcB1mxJOx4wu8Efkz9ERDyAAkAR8Tj79u1LbeHjbe/evQgKCjJBHsu1MOBr06YNIiIicn9lWK6leV3gvz3pz+mblfDQlOCvcMHcWDsRkWxRACgi+Y4teuzKtTJ1//vvP3M/u3F79+5tAj527xYqVCh/VpAti/WqA0dPAHsOAqdjM35swIVM35DglGzfiqWBIM36ISKeRQGgiOQ5jtmbP39+arfu2rVrzf21atUyCRuvvvoqOnTogBIlLsyn6ymsws+c4u3YqQtTvcUCSckpYwZZJ5AZvmztY8HonIxBFBHJRQoARbwAy9IdjQXOJwGhgUCJSCDIi2KL2NhY/PPPP6lduitWrEBSUhIqVqxoAr4nnnjCZOxWqFABXqFggZSbiIiXUgAo4qGOnwMmbQT+3gWsjQbO2iWihgUB9UsC7SoBNzUAynnY8DLW3Vu2bFlqwMfgLz4+HiVLljTduXfddZf5n1OvuVSaRURE3CLAxhQ7J7prChcujFOnTuXfGBwRP3EqDnhjEfDDBpY8ARxmpE0jMCCldbBLTeD59kDpKOQLtuatWbMmdQzfggULzAwcPF+wK9dMr3b11ahfv74CPhGRXOJKvKYAUMSDLNwDPDwzpfUvOcuvZhcFcfhZMPDa1cD/aiPX8Xvj5s2bU8fwMYGDc+wyK7ddu3Ym4OOtadOmCA5WR4OIiKcFgDozi3iIX7ekBH/kSvBHSTYgNgEYMgM4dAa4t7n712/nzp1pSrMcOnTI1N27/PLLMWTIEBPwtWrVCmFhYe5/cRERcSsFgCIeYP7ulODP1cDPnvXUVxcCRcKBfvXTf9yuXbswdepUPPTQQ5nOlHHw4EFTdNkK+BgA8vHNmjXDHXfcYQI+FmLmDBwiIuJdFACK5LNT54FHZqaM5SsQAgy5DKhXMiXJo3gk8N4S4P2llz4vOBAY0BjoUw+oUgSISwK2HQNeWQg8NxdoXQGoVDjtc5YvX47OnTvj+PHjpuWOLXYW3jdv3rzUcXybNm0y9zdo0ADdu3dPrcXHOXZFRMS7KQAUyWcM2E6cT2nBKxoO3NwQ2HQEmLUDuLlBxskfH3UDWpQDJvwL/HsAiAwBGpQCIkKAxGTg6b+A73pdfM6vv/6Kfv36mQxdzqoxffp0M27PGse3atUqM7aPmbkM9kaMGGFKs5QuXTrPtoWIiOQNBYAi+Yi1/X7ceLHrd99poNGHKT+bYDCDAJAtfx0qA70mA6sOXbx/zq6LP/+zD9h4JKU1cezYsabL1z7p/8UXXzT/lytXzgR8/DsDvsqVK+fGWxUREQ+iAFAkH7HUS3aG/d3VBFi2P23wl15m8FdrgY2j/2da/y75e1CQafVjF69q8YmI+BcFgCL5aPZO1xM/ykYBFQsDf+0EnmyTkuzB1sIdJ4AP/wV+2nQxM5iP2bt0aZqgLzk52bQEsnbfsWPHFPyJiPghBYAi+YSB34Yjrj+vzIViz73qppR8GTEXOB2f0l387rVASCDw/YaUxxw+C2zceQi22GNmZg7eFi9ejCVLlpg6Udu3bzeFmkVExL8oABTJJwdPA+cTXX8eE0Cs6eAGTAX2n075fcEeYNpNwMOtLgaA9N9xoFX54rj++uvNjdgCeODAAZQtW9Yt70VERLyLF00nL+JbzmUj+KMT51L+337iYvBnmbcnZV7g4hEX70svyOSYv/Lly2daB1BERHyXzv4i+SQ0KHvP230qZdaP9FxoHEwzrpBdwiIiIvZ0aRDJJxzLx2LOrmJyx587gBrFgAoF0/6NpWF2nUypK2hhkWgRERF7GgMoko8tgLWKARuPXhrEsahzgdCU32sWA7rUuFjnj126by9OedwXPVNmCTkTD9xUH6hbEhj8x8VlFQ5LyRoWERGxpwBQJB+1qwxsOZbSqmd5+SqgYqGLv3erlXKjthNTikXvOQX0/hEY2hZ47SogJCil6PPdvwFzdl6sA9i2Isf75fGbEhERj6cAUCQf3Vw/ZSo3e1d85txztx4D7rq0vnMqBpX9G+Vs/URExDdpDKBIPqpaFOhYJaW1zp24vBpFgTYV3LtcERHxDQoARfLZSx2ylwySGWYBv32tun9FRCR9CgBF8lmlwsCLbp6M44GWQNMy7l2miIj4DgWAIh6A07gNucw9y+IUcU+0ds+yRETENykAFPEQj7cGXrgypTvY1TGBnB6OT3mgBfB2p4vTxYmIiKRHAaCIB7mzCTDjVqBhqZTfswoErb9XLgz81Bd4uq2CPxERyZrKwIh4GBZ+/qUfsPIQ8OUaYO4u4FTcpY9jsWjW+bu9EXBFJQV+IiLiPAWAIh6IxZubl0252WzAwTPAtuNAXFLK3L5Vi6Qkj6jIs4iIZIcCQBEPxyCvXMGUm4iIiDtoDKCIiIiIn1EAKCIiIuJnFACKiIiI+BkFgCIiIiJ+RgGgiIiIiJ9RACgiIiLiZxQAioiIiPgZBYAiIiIifkYBoIiIiIifUQAoIiIi4mcUAIqIiIj4GQWAIiIiIn5GAaCIiIiIn1EAKCIiIuJnFACKiIiI+BkFgCIiIiJ+RgGgiIiIiJ9RACgiIiLiZ4KdeZDNZjP/x8TE5Pb6iIiIiEg2WHGaFbflOAA8ffq0+b9ixYrZWR8RERERySOM2woXLpzpYwJsToSJycnJOHDgAAoWLIiAgAB3rqOIiIiIuAFDOgZ/5cqVQ2BgYM4DQBERERHxHUoCEREREfEzCgBFRERE/IwCQBERERE/owBQRERExM8oABQRERHxMwoARURERPyMAkARERER+Jf/A56hhpHUXAHLAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "t = 17\n",
     "\n",
@@ -406,12 +456,12 @@
     "        del betweenness_edge[n]\n",
     "        del betweenness_edge_len[n]\n",
     "        del betweenness_edge_lin[n]\n",
-    "    betweenness_edge = _rescale_e(betweenness_edge, len(G), normalized=True,\n",
-    "                                  directed=True)\n",
-    "    betweenness_edge_len = _rescale_e(betweenness_edge_len, len(G), normalized=True,\n",
-    "                                      directed=True)\n",
-    "    betweenness_edge_lin = _rescale_e(betweenness_edge_lin, len(G), normalized=True,\n",
-    "                                      directed=True)\n",
+    "    betweenness_edge = _rescale(betweenness_edge, len(G), normalized=True,\n",
+    "                                  directed=True, endpoints=True)\n",
+    "    betweenness_edge_len = _rescale(betweenness_edge_len, len(G), normalized=True,\n",
+    "                                      directed=True, endpoints=True)\n",
+    "    betweenness_edge_lin = _rescale(betweenness_edge_lin, len(G), normalized=True,\n",
+    "                                      directed=True, endpoints=True)\n",
     "    return {\n",
     "        \"Node\": betweenness,\n",
     "        \"Edge\": betweenness_edge,\n",
@@ -447,14 +497,587 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T09:49:15.417307Z",
      "start_time": "2024-04-18T09:49:15.370684Z"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
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+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_f2fab_row4_col2, #T_f2fab_row4_col5, #T_f2fab_row4_col8, #T_f2fab_row17_col0, #T_f2fab_row17_col3, #T_f2fab_row17_col6, #T_f2fab_row18_col0, #T_f2fab_row18_col1, #T_f2fab_row18_col2, #T_f2fab_row18_col3, #T_f2fab_row18_col4, #T_f2fab_row18_col5, #T_f2fab_row18_col6, #T_f2fab_row18_col7, #T_f2fab_row18_col8, #T_f2fab_row19_col0, #T_f2fab_row19_col1, #T_f2fab_row19_col2, #T_f2fab_row19_col3, #T_f2fab_row19_col4, #T_f2fab_row19_col5, #T_f2fab_row19_col6, #T_f2fab_row19_col7, #T_f2fab_row19_col8 {\n",
+       "  background-color: #f7fbff;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row4_col3, #T_f2fab_row4_col4 {\n",
+       "  background-color: #c7dbef;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row4_col6, #T_f2fab_row4_col7 {\n",
+       "  background-color: #94c4df;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row5_col1, #T_f2fab_row6_col0 {\n",
+       "  background-color: #c7dcef;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row5_col2 {\n",
+       "  background-color: #e7f1fa;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row5_col3 {\n",
+       "  background-color: #caddf0;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row5_col4, #T_f2fab_row9_col8 {\n",
+       "  background-color: #cbdef1;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row5_col6 {\n",
+       "  background-color: #6dafd7;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_f2fab_row5_col7 {\n",
+       "  background-color: #77b5d9;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row5_col8, #T_f2fab_row8_col3, #T_f2fab_row8_col4, #T_f2fab_row8_col5 {\n",
+       "  background-color: #e3eef8;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row6_col2 {\n",
+       "  background-color: #e8f1fa;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row6_col3 {\n",
+       "  background-color: #d0e1f2;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row6_col4 {\n",
+       "  background-color: #cfe1f2;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row6_col5, #T_f2fab_row11_col6, #T_f2fab_row11_col7, #T_f2fab_row11_col8, #T_f2fab_row17_col8 {\n",
+       "  background-color: #eff6fc;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row6_col6, #T_f2fab_row6_col7 {\n",
+       "  background-color: #74b3d8;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row6_col8, #T_f2fab_row10_col6, #T_f2fab_row10_col8, #T_f2fab_row17_col7 {\n",
+       "  background-color: #edf4fc;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row7_col0, #T_f2fab_row7_col1 {\n",
+       "  background-color: #d5e5f4;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row7_col2 {\n",
+       "  background-color: #92c4de;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row7_col3, #T_f2fab_row7_col4 {\n",
+       "  background-color: #ddeaf7;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row7_col5 {\n",
+       "  background-color: #add0e6;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row7_col8 {\n",
+       "  background-color: #084285;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_f2fab_row8_col0, #T_f2fab_row8_col1, #T_f2fab_row8_col2 {\n",
+       "  background-color: #dbe9f6;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row8_col6, #T_f2fab_row8_col7 {\n",
+       "  background-color: #bdd7ec;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row8_col8 {\n",
+       "  background-color: #a9cfe5;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row9_col0, #T_f2fab_row9_col1 {\n",
+       "  background-color: #e0ecf8;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row9_col2 {\n",
+       "  background-color: #dfecf7;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row9_col3, #T_f2fab_row9_col4 {\n",
+       "  background-color: #e7f0fa;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row9_col5 {\n",
+       "  background-color: #e6f0f9;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row9_col6, #T_f2fab_row9_col7 {\n",
+       "  background-color: #d8e7f5;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row10_col0, #T_f2fab_row10_col1, #T_f2fab_row12_col6, #T_f2fab_row12_col7 {\n",
+       "  background-color: #eaf3fb;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row10_col7, #T_f2fab_row17_col1 {\n",
+       "  background-color: #ecf4fb;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row11_col3, #T_f2fab_row11_col4, #T_f2fab_row11_col5, #T_f2fab_row13_col3, #T_f2fab_row13_col4, #T_f2fab_row15_col3, #T_f2fab_row16_col0, #T_f2fab_row16_col5, #T_f2fab_row16_col7, #T_f2fab_row16_col8 {\n",
+       "  background-color: #f5fafe;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row12_col3, #T_f2fab_row12_col4, #T_f2fab_row13_col0, #T_f2fab_row13_col1, #T_f2fab_row14_col1, #T_f2fab_row14_col7 {\n",
+       "  background-color: #f0f6fd;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row12_col8 {\n",
+       "  background-color: #1e6db2;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_f2fab_row13_col5, #T_f2fab_row15_col7, #T_f2fab_row16_col1, #T_f2fab_row16_col2, #T_f2fab_row17_col5 {\n",
+       "  background-color: #f5f9fe;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row13_col6, #T_f2fab_row13_col7, #T_f2fab_row15_col1, #T_f2fab_row17_col4 {\n",
+       "  background-color: #f2f8fd;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row13_col8, #T_f2fab_row14_col0, #T_f2fab_row14_col6 {\n",
+       "  background-color: #f1f7fd;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row14_col3, #T_f2fab_row14_col4 {\n",
+       "  background-color: #f3f8fe;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row14_col5 {\n",
+       "  background-color: #c1d9ed;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row14_col8 {\n",
+       "  background-color: #08458a;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_f2fab_row15_col0, #T_f2fab_row15_col6 {\n",
+       "  background-color: #f4f9fe;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row15_col2 {\n",
+       "  background-color: #afd1e7;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row15_col4, #T_f2fab_row16_col3, #T_f2fab_row16_col4, #T_f2fab_row16_col6 {\n",
+       "  background-color: #f6faff;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row15_col5 {\n",
+       "  background-color: #bad6eb;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_f2fab_row15_col8 {\n",
+       "  background-color: #08306b;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_f2fab_level0_row0, #T_f2fab_level0_row5, #T_f2fab_level0_row6 {\n",
+       "  color: crimson;\n",
+       "}\n",
+       "#T_f2fab_level0_row1, #T_f2fab_level0_row2, #T_f2fab_level0_row3, #T_f2fab_level0_row7, #T_f2fab_level0_row12, #T_f2fab_level0_row14, #T_f2fab_level0_row15, #T_f2fab_level0_row19 {\n",
+       "  color: black;\n",
+       "}\n",
+       "#T_f2fab_level0_row4 {\n",
+       "  color: darkorange;\n",
+       "}\n",
+       "#T_f2fab_level0_row8, #T_f2fab_level0_row11, #T_f2fab_level0_row18 {\n",
+       "  color: dodgerblue;\n",
+       "}\n",
+       "#T_f2fab_level0_row9, #T_f2fab_level0_row10, #T_f2fab_level0_row13, #T_f2fab_level0_row16, #T_f2fab_level0_row17 {\n",
+       "  color: mediumseagreen;\n",
+       "}\n",
+       "</style>\n",
+       "<table id=\"T_f2fab\" style=\"font-size: 12px\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th class=\"blank level0\" >&nbsp;</th>\n",
+       "      <th id=\"T_f2fab_level0_col0\" class=\"col_heading level0 col0\" colspan=\"3\"></th>\n",
+       "      <th id=\"T_f2fab_level0_col3\" class=\"col_heading level0 col3\" colspan=\"3\">Len scales</th>\n",
+       "      <th id=\"T_f2fab_level0_col6\" class=\"col_heading level0 col6\" colspan=\"3\">Lin scales</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th class=\"blank level1\" >&nbsp;</th>\n",
+       "      <th id=\"T_f2fab_level1_col0\" class=\"col_heading level1 col0\" >C_B</th>\n",
+       "      <th id=\"T_f2fab_level1_col1\" class=\"col_heading level1 col1\" >C_B_paths</th>\n",
+       "      <th id=\"T_f2fab_level1_col2\" class=\"col_heading level1 col2\" >C_B_restr</th>\n",
+       "      <th id=\"T_f2fab_level1_col3\" class=\"col_heading level1 col3\" >C_B</th>\n",
+       "      <th id=\"T_f2fab_level1_col4\" class=\"col_heading level1 col4\" >C_B_paths</th>\n",
+       "      <th id=\"T_f2fab_level1_col5\" class=\"col_heading level1 col5\" >C_B_restr</th>\n",
+       "      <th id=\"T_f2fab_level1_col6\" class=\"col_heading level1 col6\" >C_B</th>\n",
+       "      <th id=\"T_f2fab_level1_col7\" class=\"col_heading level1 col7\" >C_B_paths</th>\n",
+       "      <th id=\"T_f2fab_level1_col8\" class=\"col_heading level1 col8\" >C_B_restr</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row0\" class=\"row_heading level0 row0\" >9</th>\n",
+       "      <td id=\"T_f2fab_row0_col0\" class=\"data row0 col0\" >0.289</td>\n",
+       "      <td id=\"T_f2fab_row0_col1\" class=\"data row0 col1\" >0.289</td>\n",
+       "      <td id=\"T_f2fab_row0_col2\" class=\"data row0 col2\" >0.053</td>\n",
+       "      <td id=\"T_f2fab_row0_col3\" class=\"data row0 col3\" >0.233</td>\n",
+       "      <td id=\"T_f2fab_row0_col4\" class=\"data row0 col4\" >0.233</td>\n",
+       "      <td id=\"T_f2fab_row0_col5\" class=\"data row0 col5\" >0.040</td>\n",
+       "      <td id=\"T_f2fab_row0_col6\" class=\"data row0 col6\" >0.538</td>\n",
+       "      <td id=\"T_f2fab_row0_col7\" class=\"data row0 col7\" >0.538</td>\n",
+       "      <td id=\"T_f2fab_row0_col8\" class=\"data row0 col8\" >0.052</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row1\" class=\"row_heading level0 row1\" >0</th>\n",
+       "      <td id=\"T_f2fab_row1_col0\" class=\"data row1 col0\" >0.287</td>\n",
+       "      <td id=\"T_f2fab_row1_col1\" class=\"data row1 col1\" >0.274</td>\n",
+       "      <td id=\"T_f2fab_row1_col2\" class=\"data row1 col2\" >0.255</td>\n",
+       "      <td id=\"T_f2fab_row1_col3\" class=\"data row1 col3\" >0.209</td>\n",
+       "      <td id=\"T_f2fab_row1_col4\" class=\"data row1 col4\" >0.229</td>\n",
+       "      <td id=\"T_f2fab_row1_col5\" class=\"data row1 col5\" >0.212</td>\n",
+       "      <td id=\"T_f2fab_row1_col6\" class=\"data row1 col6\" >0.327</td>\n",
+       "      <td id=\"T_f2fab_row1_col7\" class=\"data row1 col7\" >0.383</td>\n",
+       "      <td id=\"T_f2fab_row1_col8\" class=\"data row1 col8\" >0.420</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "      <td id=\"T_f2fab_row2_col0\" class=\"data row2 col0\" >0.262</td>\n",
+       "      <td id=\"T_f2fab_row2_col1\" class=\"data row2 col1\" >0.268</td>\n",
+       "      <td id=\"T_f2fab_row2_col2\" class=\"data row2 col2\" >0.324</td>\n",
+       "      <td id=\"T_f2fab_row2_col3\" class=\"data row2 col3\" >0.221</td>\n",
+       "      <td id=\"T_f2fab_row2_col4\" class=\"data row2 col4\" >0.222</td>\n",
+       "      <td id=\"T_f2fab_row2_col5\" class=\"data row2 col5\" >0.272</td>\n",
+       "      <td id=\"T_f2fab_row2_col6\" class=\"data row2 col6\" >0.382</td>\n",
+       "      <td id=\"T_f2fab_row2_col7\" class=\"data row2 col7\" >0.387</td>\n",
+       "      <td id=\"T_f2fab_row2_col8\" class=\"data row2 col8\" >0.850</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row3\" class=\"row_heading level0 row3\" >6</th>\n",
+       "      <td id=\"T_f2fab_row3_col0\" class=\"data row3 col0\" >0.239</td>\n",
+       "      <td id=\"T_f2fab_row3_col1\" class=\"data row3 col1\" >0.239</td>\n",
+       "      <td id=\"T_f2fab_row3_col2\" class=\"data row3 col2\" >0.239</td>\n",
+       "      <td id=\"T_f2fab_row3_col3\" class=\"data row3 col3\" >0.201</td>\n",
+       "      <td id=\"T_f2fab_row3_col4\" class=\"data row3 col4\" >0.201</td>\n",
+       "      <td id=\"T_f2fab_row3_col5\" class=\"data row3 col5\" >0.200</td>\n",
+       "      <td id=\"T_f2fab_row3_col6\" class=\"data row3 col6\" >0.445</td>\n",
+       "      <td id=\"T_f2fab_row3_col7\" class=\"data row3 col7\" >0.445</td>\n",
+       "      <td id=\"T_f2fab_row3_col8\" class=\"data row3 col8\" >0.551</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row4\" class=\"row_heading level0 row4\" >18</th>\n",
+       "      <td id=\"T_f2fab_row4_col0\" class=\"data row4 col0\" >0.229</td>\n",
+       "      <td id=\"T_f2fab_row4_col1\" class=\"data row4 col1\" >0.229</td>\n",
+       "      <td id=\"T_f2fab_row4_col2\" class=\"data row4 col2\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row4_col3\" class=\"data row4 col3\" >0.217</td>\n",
+       "      <td id=\"T_f2fab_row4_col4\" class=\"data row4 col4\" >0.217</td>\n",
+       "      <td id=\"T_f2fab_row4_col5\" class=\"data row4 col5\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row4_col6\" class=\"data row4 col6\" >0.352</td>\n",
+       "      <td id=\"T_f2fab_row4_col7\" class=\"data row4 col7\" >0.352</td>\n",
+       "      <td id=\"T_f2fab_row4_col8\" class=\"data row4 col8\" >0.000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row5\" class=\"row_heading level0 row5\" >7</th>\n",
+       "      <td id=\"T_f2fab_row5_col0\" class=\"data row5 col0\" >0.224</td>\n",
+       "      <td id=\"T_f2fab_row5_col1\" class=\"data row5 col1\" >0.216</td>\n",
+       "      <td id=\"T_f2fab_row5_col2\" class=\"data row5 col2\" >0.071</td>\n",
+       "      <td id=\"T_f2fab_row5_col3\" class=\"data row5 col3\" >0.205</td>\n",
+       "      <td id=\"T_f2fab_row5_col4\" class=\"data row5 col4\" >0.197</td>\n",
+       "      <td id=\"T_f2fab_row5_col5\" class=\"data row5 col5\" >0.055</td>\n",
+       "      <td id=\"T_f2fab_row5_col6\" class=\"data row5 col6\" >0.437</td>\n",
+       "      <td id=\"T_f2fab_row5_col7\" class=\"data row5 col7\" >0.414</td>\n",
+       "      <td id=\"T_f2fab_row5_col8\" class=\"data row5 col8\" >0.092</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row6\" class=\"row_heading level0 row6\" >8</th>\n",
+       "      <td id=\"T_f2fab_row6_col0\" class=\"data row6 col0\" >0.217</td>\n",
+       "      <td id=\"T_f2fab_row6_col1\" class=\"data row6 col1\" >0.213</td>\n",
+       "      <td id=\"T_f2fab_row6_col2\" class=\"data row6 col2\" >0.068</td>\n",
+       "      <td id=\"T_f2fab_row6_col3\" class=\"data row6 col3\" >0.176</td>\n",
+       "      <td id=\"T_f2fab_row6_col4\" class=\"data row6 col4\" >0.180</td>\n",
+       "      <td id=\"T_f2fab_row6_col5\" class=\"data row6 col5\" >0.037</td>\n",
+       "      <td id=\"T_f2fab_row6_col6\" class=\"data row6 col6\" >0.424</td>\n",
+       "      <td id=\"T_f2fab_row6_col7\" class=\"data row6 col7\" >0.423</td>\n",
+       "      <td id=\"T_f2fab_row6_col8\" class=\"data row6 col8\" >0.046</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row7\" class=\"row_heading level0 row7\" >1</th>\n",
+       "      <td id=\"T_f2fab_row7_col0\" class=\"data row7 col0\" >0.153</td>\n",
+       "      <td id=\"T_f2fab_row7_col1\" class=\"data row7 col1\" >0.153</td>\n",
+       "      <td id=\"T_f2fab_row7_col2\" class=\"data row7 col2\" >0.355</td>\n",
+       "      <td id=\"T_f2fab_row7_col3\" class=\"data row7 col3\" >0.115</td>\n",
+       "      <td id=\"T_f2fab_row7_col4\" class=\"data row7 col4\" >0.115</td>\n",
+       "      <td id=\"T_f2fab_row7_col5\" class=\"data row7 col5\" >0.291</td>\n",
+       "      <td id=\"T_f2fab_row7_col6\" class=\"data row7 col6\" >0.258</td>\n",
+       "      <td id=\"T_f2fab_row7_col7\" class=\"data row7 col7\" >0.258</td>\n",
+       "      <td id=\"T_f2fab_row7_col8\" class=\"data row7 col8\" >0.823</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row8\" class=\"row_heading level0 row8\" >15</th>\n",
+       "      <td id=\"T_f2fab_row8_col0\" class=\"data row8 col0\" >0.126</td>\n",
+       "      <td id=\"T_f2fab_row8_col1\" class=\"data row8 col1\" >0.126</td>\n",
+       "      <td id=\"T_f2fab_row8_col2\" class=\"data row8 col2\" >0.126</td>\n",
+       "      <td id=\"T_f2fab_row8_col3\" class=\"data row8 col3\" >0.093</td>\n",
+       "      <td id=\"T_f2fab_row8_col4\" class=\"data row8 col4\" >0.093</td>\n",
+       "      <td id=\"T_f2fab_row8_col5\" class=\"data row8 col5\" >0.092</td>\n",
+       "      <td id=\"T_f2fab_row8_col6\" class=\"data row8 col6\" >0.248</td>\n",
+       "      <td id=\"T_f2fab_row8_col7\" class=\"data row8 col7\" >0.248</td>\n",
+       "      <td id=\"T_f2fab_row8_col8\" class=\"data row8 col8\" >0.301</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row9\" class=\"row_heading level0 row9\" >10</th>\n",
+       "      <td id=\"T_f2fab_row9_col0\" class=\"data row9 col0\" >0.103</td>\n",
+       "      <td id=\"T_f2fab_row9_col1\" class=\"data row9 col1\" >0.100</td>\n",
+       "      <td id=\"T_f2fab_row9_col2\" class=\"data row9 col2\" >0.105</td>\n",
+       "      <td id=\"T_f2fab_row9_col3\" class=\"data row9 col3\" >0.075</td>\n",
+       "      <td id=\"T_f2fab_row9_col4\" class=\"data row9 col4\" >0.073</td>\n",
+       "      <td id=\"T_f2fab_row9_col5\" class=\"data row9 col5\" >0.077</td>\n",
+       "      <td id=\"T_f2fab_row9_col6\" class=\"data row9 col6\" >0.141</td>\n",
+       "      <td id=\"T_f2fab_row9_col7\" class=\"data row9 col7\" >0.139</td>\n",
+       "      <td id=\"T_f2fab_row9_col8\" class=\"data row9 col8\" >0.200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row10\" class=\"row_heading level0 row10\" >13</th>\n",
+       "      <td id=\"T_f2fab_row10_col0\" class=\"data row10 col0\" >0.055</td>\n",
+       "      <td id=\"T_f2fab_row10_col1\" class=\"data row10 col1\" >0.058</td>\n",
+       "      <td id=\"T_f2fab_row10_col2\" class=\"data row10 col2\" >0.053</td>\n",
+       "      <td id=\"T_f2fab_row10_col3\" class=\"data row10 col3\" >0.043</td>\n",
+       "      <td id=\"T_f2fab_row10_col4\" class=\"data row10 col4\" >0.044</td>\n",
+       "      <td id=\"T_f2fab_row10_col5\" class=\"data row10 col5\" >0.043</td>\n",
+       "      <td id=\"T_f2fab_row10_col6\" class=\"data row10 col6\" >0.047</td>\n",
+       "      <td id=\"T_f2fab_row10_col7\" class=\"data row10 col7\" >0.050</td>\n",
+       "      <td id=\"T_f2fab_row10_col8\" class=\"data row10 col8\" >0.046</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row11\" class=\"row_heading level0 row11\" >16</th>\n",
+       "      <td id=\"T_f2fab_row11_col0\" class=\"data row11 col0\" >0.045</td>\n",
+       "      <td id=\"T_f2fab_row11_col1\" class=\"data row11 col1\" >0.045</td>\n",
+       "      <td id=\"T_f2fab_row11_col2\" class=\"data row11 col2\" >0.045</td>\n",
+       "      <td id=\"T_f2fab_row11_col3\" class=\"data row11 col3\" >0.009</td>\n",
+       "      <td id=\"T_f2fab_row11_col4\" class=\"data row11 col4\" >0.009</td>\n",
+       "      <td id=\"T_f2fab_row11_col5\" class=\"data row11 col5\" >0.008</td>\n",
+       "      <td id=\"T_f2fab_row11_col6\" class=\"data row11 col6\" >0.036</td>\n",
+       "      <td id=\"T_f2fab_row11_col7\" class=\"data row11 col7\" >0.036</td>\n",
+       "      <td id=\"T_f2fab_row11_col8\" class=\"data row11 col8\" >0.037</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row12\" class=\"row_heading level0 row12\" >5</th>\n",
+       "      <td id=\"T_f2fab_row12_col0\" class=\"data row12 col0\" >0.042</td>\n",
+       "      <td id=\"T_f2fab_row12_col1\" class=\"data row12 col1\" >0.042</td>\n",
+       "      <td id=\"T_f2fab_row12_col2\" class=\"data row12 col2\" >0.232</td>\n",
+       "      <td id=\"T_f2fab_row12_col3\" class=\"data row12 col3\" >0.032</td>\n",
+       "      <td id=\"T_f2fab_row12_col4\" class=\"data row12 col4\" >0.032</td>\n",
+       "      <td id=\"T_f2fab_row12_col5\" class=\"data row12 col5\" >0.202</td>\n",
+       "      <td id=\"T_f2fab_row12_col6\" class=\"data row12 col6\" >0.058</td>\n",
+       "      <td id=\"T_f2fab_row12_col7\" class=\"data row12 col7\" >0.058</td>\n",
+       "      <td id=\"T_f2fab_row12_col8\" class=\"data row12 col8\" >0.675</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row13\" class=\"row_heading level0 row13\" >11</th>\n",
+       "      <td id=\"T_f2fab_row13_col0\" class=\"data row13 col0\" >0.032</td>\n",
+       "      <td id=\"T_f2fab_row13_col1\" class=\"data row13 col1\" >0.032</td>\n",
+       "      <td id=\"T_f2fab_row13_col2\" class=\"data row13 col2\" >0.039</td>\n",
+       "      <td id=\"T_f2fab_row13_col3\" class=\"data row13 col3\" >0.008</td>\n",
+       "      <td id=\"T_f2fab_row13_col4\" class=\"data row13 col4\" >0.008</td>\n",
+       "      <td id=\"T_f2fab_row13_col5\" class=\"data row13 col5\" >0.011</td>\n",
+       "      <td id=\"T_f2fab_row13_col6\" class=\"data row13 col6\" >0.023</td>\n",
+       "      <td id=\"T_f2fab_row13_col7\" class=\"data row13 col7\" >0.023</td>\n",
+       "      <td id=\"T_f2fab_row13_col8\" class=\"data row13 col8\" >0.031</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row14\" class=\"row_heading level0 row14\" >4</th>\n",
+       "      <td id=\"T_f2fab_row14_col0\" class=\"data row14 col0\" >0.030</td>\n",
+       "      <td id=\"T_f2fab_row14_col1\" class=\"data row14 col1\" >0.034</td>\n",
+       "      <td id=\"T_f2fab_row14_col2\" class=\"data row14 col2\" >0.271</td>\n",
+       "      <td id=\"T_f2fab_row14_col3\" class=\"data row14 col3\" >0.017</td>\n",
+       "      <td id=\"T_f2fab_row14_col4\" class=\"data row14 col4\" >0.020</td>\n",
+       "      <td id=\"T_f2fab_row14_col5\" class=\"data row14 col5\" >0.237</td>\n",
+       "      <td id=\"T_f2fab_row14_col6\" class=\"data row14 col6\" >0.029</td>\n",
+       "      <td id=\"T_f2fab_row14_col7\" class=\"data row14 col7\" >0.032</td>\n",
+       "      <td id=\"T_f2fab_row14_col8\" class=\"data row14 col8\" >0.812</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row15\" class=\"row_heading level0 row15\" >3</th>\n",
+       "      <td id=\"T_f2fab_row15_col0\" class=\"data row15 col0\" >0.017</td>\n",
+       "      <td id=\"T_f2fab_row15_col1\" class=\"data row15 col1\" >0.021</td>\n",
+       "      <td id=\"T_f2fab_row15_col2\" class=\"data row15 col2\" >0.284</td>\n",
+       "      <td id=\"T_f2fab_row15_col3\" class=\"data row15 col3\" >0.009</td>\n",
+       "      <td id=\"T_f2fab_row15_col4\" class=\"data row15 col4\" >0.005</td>\n",
+       "      <td id=\"T_f2fab_row15_col5\" class=\"data row15 col5\" >0.254</td>\n",
+       "      <td id=\"T_f2fab_row15_col6\" class=\"data row15 col6\" >0.015</td>\n",
+       "      <td id=\"T_f2fab_row15_col7\" class=\"data row15 col7\" >0.013</td>\n",
+       "      <td id=\"T_f2fab_row15_col8\" class=\"data row15 col8\" >0.882</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row16\" class=\"row_heading level0 row16\" >12</th>\n",
+       "      <td id=\"T_f2fab_row16_col0\" class=\"data row16 col0\" >0.008</td>\n",
+       "      <td id=\"T_f2fab_row16_col1\" class=\"data row16 col1\" >0.011</td>\n",
+       "      <td id=\"T_f2fab_row16_col2\" class=\"data row16 col2\" >0.013</td>\n",
+       "      <td id=\"T_f2fab_row16_col3\" class=\"data row16 col3\" >0.004</td>\n",
+       "      <td id=\"T_f2fab_row16_col4\" class=\"data row16 col4\" >0.006</td>\n",
+       "      <td id=\"T_f2fab_row16_col5\" class=\"data row16 col5\" >0.007</td>\n",
+       "      <td id=\"T_f2fab_row16_col6\" class=\"data row16 col6\" >0.005</td>\n",
+       "      <td id=\"T_f2fab_row16_col7\" class=\"data row16 col7\" >0.007</td>\n",
+       "      <td id=\"T_f2fab_row16_col8\" class=\"data row16 col8\" >0.009</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row17\" class=\"row_heading level0 row17\" >14</th>\n",
+       "      <td id=\"T_f2fab_row17_col0\" class=\"data row17 col0\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row17_col1\" class=\"data row17 col1\" >0.050</td>\n",
+       "      <td id=\"T_f2fab_row17_col2\" class=\"data row17 col2\" >0.042</td>\n",
+       "      <td id=\"T_f2fab_row17_col3\" class=\"data row17 col3\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row17_col4\" class=\"data row17 col4\" >0.021</td>\n",
+       "      <td id=\"T_f2fab_row17_col5\" class=\"data row17 col5\" >0.014</td>\n",
+       "      <td id=\"T_f2fab_row17_col6\" class=\"data row17 col6\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row17_col7\" class=\"data row17 col7\" >0.047</td>\n",
+       "      <td id=\"T_f2fab_row17_col8\" class=\"data row17 col8\" >0.035</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row18\" class=\"row_heading level0 row18\" >17</th>\n",
+       "      <td id=\"T_f2fab_row18_col0\" class=\"data row18 col0\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row18_col1\" class=\"data row18 col1\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row18_col2\" class=\"data row18 col2\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row18_col3\" class=\"data row18 col3\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row18_col4\" class=\"data row18 col4\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row18_col5\" class=\"data row18 col5\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row18_col6\" class=\"data row18 col6\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row18_col7\" class=\"data row18 col7\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row18_col8\" class=\"data row18 col8\" >0.000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_f2fab_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
+       "      <td id=\"T_f2fab_row19_col0\" class=\"data row19 col0\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row19_col1\" class=\"data row19 col1\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row19_col2\" class=\"data row19 col2\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row19_col3\" class=\"data row19 col3\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row19_col4\" class=\"data row19 col4\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row19_col5\" class=\"data row19 col5\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row19_col6\" class=\"data row19 col6\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row19_col7\" class=\"data row19 col7\" >0.000</td>\n",
+       "      <td id=\"T_f2fab_row19_col8\" class=\"data row19 col8\" >0.000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x76f82b44a270>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "display(pd.DataFrame({\n",
     "    (\"\", \"C_B\"): cb[\"Node\"], (\"\", \"C_B_paths\"): cb_paths[\"Node\"],\n",
@@ -490,14 +1113,1139 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T09:49:46.517845Z",
      "start_time": "2024-04-18T09:49:46.440574Z"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style type=\"text/css\">\n",
+       "#T_8473d_row0_col0, #T_8473d_row4_col0, #T_8473d_row4_col1, #T_8473d_row4_col3, #T_8473d_row4_col4, #T_8473d_row9_col4, #T_8473d_row14_col0, #T_8473d_row14_col1, #T_8473d_row14_col3, #T_8473d_row14_col4, #T_8473d_row23_col4, #T_8473d_row25_col3, #T_8473d_row25_col4, #T_8473d_row25_col5, #T_8473d_row26_col2, #T_8473d_row26_col5, #T_8473d_row29_col2, #T_8473d_row29_col5, #T_8473d_row32_col0, #T_8473d_row32_col1, #T_8473d_row32_col3, #T_8473d_row32_col4, #T_8473d_row36_col2, #T_8473d_row36_col8, #T_8473d_row40_col0, #T_8473d_row40_col6, #T_8473d_row41_col0, #T_8473d_row44_col2, #T_8473d_row47_col0, #T_8473d_row47_col1, #T_8473d_row47_col3, #T_8473d_row47_col4, #T_8473d_row47_col6, #T_8473d_row47_col7, #T_8473d_row50_col0, #T_8473d_row50_col1, #T_8473d_row50_col6, #T_8473d_row50_col7 {\n",
+       "  background-color: #eef5fc;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row0_col1, #T_8473d_row1_col6, #T_8473d_row2_col6, #T_8473d_row2_col7, #T_8473d_row9_col1, #T_8473d_row16_col3, #T_8473d_row16_col4, #T_8473d_row33_col0, #T_8473d_row33_col1, #T_8473d_row33_col2, #T_8473d_row33_col3, #T_8473d_row33_col6, #T_8473d_row33_col7, #T_8473d_row33_col8, #T_8473d_row43_col1 {\n",
+       "  background-color: #eaf2fb;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row0_col2 {\n",
+       "  background-color: #c3daee;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row0_col3, #T_8473d_row9_col3, #T_8473d_row23_col5, #T_8473d_row38_col8, #T_8473d_row39_col0, #T_8473d_row39_col1, #T_8473d_row39_col6, #T_8473d_row41_col3, #T_8473d_row41_col4, #T_8473d_row49_col5 {\n",
+       "  background-color: #f1f7fd;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row0_col4, #T_8473d_row1_col1, #T_8473d_row1_col4, #T_8473d_row1_col7, #T_8473d_row2_col0, #T_8473d_row2_col1, #T_8473d_row2_col3, #T_8473d_row2_col4, #T_8473d_row5_col6, #T_8473d_row10_col0, #T_8473d_row10_col1, #T_8473d_row37_col2, #T_8473d_row37_col5, #T_8473d_row37_col8, #T_8473d_row40_col3, #T_8473d_row41_col1 {\n",
+       "  background-color: #eff6fc;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row0_col5, #T_8473d_row2_col2, #T_8473d_row10_col2, #T_8473d_row37_col0, #T_8473d_row37_col1 {\n",
+       "  background-color: #cadef0;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row0_col6, #T_8473d_row1_col0, #T_8473d_row1_col3, #T_8473d_row27_col0, #T_8473d_row27_col1, #T_8473d_row27_col6, #T_8473d_row27_col7, #T_8473d_row32_col2, #T_8473d_row32_col5, #T_8473d_row40_col1, #T_8473d_row40_col4, #T_8473d_row41_col6, #T_8473d_row43_col0, #T_8473d_row43_col3, #T_8473d_row44_col5 {\n",
+       "  background-color: #ecf4fb;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row0_col7, #T_8473d_row6_col1, #T_8473d_row14_col6, #T_8473d_row14_col7, #T_8473d_row16_col5, #T_8473d_row23_col2, #T_8473d_row24_col2, #T_8473d_row24_col7, #T_8473d_row25_col6, #T_8473d_row25_col7, #T_8473d_row25_col8, #T_8473d_row26_col8, #T_8473d_row43_col6, #T_8473d_row52_col0 {\n",
+       "  background-color: #e7f1fa;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row0_col8 {\n",
+       "  background-color: #08306b;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row1_col2 {\n",
+       "  background-color: #c1d9ed;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row1_col5 {\n",
+       "  background-color: #c7dbef;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row1_col8, #T_8473d_row2_col8 {\n",
+       "  background-color: #083370;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row2_col5 {\n",
+       "  background-color: #d0e2f2;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row3_col0, #T_8473d_row3_col4, #T_8473d_row3_col6, #T_8473d_row5_col4, #T_8473d_row23_col0, #T_8473d_row23_col3, #T_8473d_row23_col6, #T_8473d_row45_col3, #T_8473d_row48_col0, #T_8473d_row48_col6, #T_8473d_row50_col5 {\n",
+       "  background-color: #f5fafe;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row3_col1, #T_8473d_row3_col7, #T_8473d_row8_col3, #T_8473d_row8_col4, #T_8473d_row45_col0, #T_8473d_row45_col4, #T_8473d_row45_col5, #T_8473d_row45_col6, #T_8473d_row46_col4, #T_8473d_row46_col5, #T_8473d_row47_col2, #T_8473d_row47_col5, #T_8473d_row47_col8, #T_8473d_row48_col1, #T_8473d_row48_col2, #T_8473d_row48_col7, #T_8473d_row48_col8, #T_8473d_row49_col8, #T_8473d_row50_col2, #T_8473d_row50_col8 {\n",
+       "  background-color: #f5f9fe;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row3_col2, #T_8473d_row5_col5 {\n",
+       "  background-color: #c9ddf0;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row3_col3, #T_8473d_row48_col3, #T_8473d_row48_col4, #T_8473d_row48_col5, #T_8473d_row51_col0, #T_8473d_row51_col1, #T_8473d_row51_col2, #T_8473d_row51_col3, #T_8473d_row51_col4, #T_8473d_row51_col5, #T_8473d_row51_col6, #T_8473d_row51_col7, #T_8473d_row51_col8 {\n",
+       "  background-color: #f6faff;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row3_col5 {\n",
+       "  background-color: #cde0f1;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row3_col8 {\n",
+       "  background-color: #083c7d;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row4_col2, #T_8473d_row14_col2, #T_8473d_row26_col0, #T_8473d_row26_col1, #T_8473d_row29_col0, #T_8473d_row29_col1 {\n",
+       "  background-color: #d0e1f2;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row4_col5 {\n",
+       "  background-color: #d7e6f5;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row4_col6, #T_8473d_row4_col7, #T_8473d_row22_col2, #T_8473d_row22_col8, #T_8473d_row35_col4, #T_8473d_row35_col6 {\n",
+       "  background-color: #e4eff9;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row4_col8 {\n",
+       "  background-color: #084990;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row5_col0, #T_8473d_row6_col3, #T_8473d_row18_col0, #T_8473d_row18_col1, #T_8473d_row18_col3, #T_8473d_row18_col4, #T_8473d_row18_col6, #T_8473d_row18_col7, #T_8473d_row39_col7, #T_8473d_row46_col0, #T_8473d_row46_col6, #T_8473d_row52_col3 {\n",
+       "  background-color: #f0f6fd;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row5_col1, #T_8473d_row5_col7, #T_8473d_row10_col3, #T_8473d_row10_col4, #T_8473d_row27_col5, #T_8473d_row36_col5, #T_8473d_row38_col2, #T_8473d_row39_col8 {\n",
+       "  background-color: #f2f7fd;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row5_col2, #T_8473d_row13_col6 {\n",
+       "  background-color: #c4daee;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row5_col3, #T_8473d_row27_col3, #T_8473d_row27_col4, #T_8473d_row40_col2, #T_8473d_row42_col5, #T_8473d_row43_col2, #T_8473d_row43_col8, #T_8473d_row44_col8, #T_8473d_row46_col1, #T_8473d_row46_col7 {\n",
+       "  background-color: #f3f8fe;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row5_col8 {\n",
+       "  background-color: #0f5aa3;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row6_col0, #T_8473d_row15_col0, #T_8473d_row15_col6, #T_8473d_row22_col5, #T_8473d_row33_col4, #T_8473d_row33_col5, #T_8473d_row34_col0, #T_8473d_row34_col1, #T_8473d_row34_col2, #T_8473d_row34_col3, #T_8473d_row34_col4, #T_8473d_row34_col5, #T_8473d_row34_col6, #T_8473d_row34_col7, #T_8473d_row34_col8, #T_8473d_row40_col7, #T_8473d_row43_col4 {\n",
+       "  background-color: #eaf3fb;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row6_col2, #T_8473d_row38_col1, #T_8473d_row38_col3 {\n",
+       "  background-color: #bfd8ed;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row6_col4, #T_8473d_row9_col0, #T_8473d_row25_col0, #T_8473d_row25_col1, #T_8473d_row25_col2, #T_8473d_row35_col8, #T_8473d_row41_col7 {\n",
+       "  background-color: #edf4fc;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row6_col5 {\n",
+       "  background-color: #c7dcef;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row6_col6, #T_8473d_row11_col3, #T_8473d_row11_col4, #T_8473d_row23_col1 {\n",
+       "  background-color: #e5eff9;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row6_col7, #T_8473d_row21_col0, #T_8473d_row21_col1, #T_8473d_row21_col2 {\n",
+       "  background-color: #dceaf6;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row6_col8 {\n",
+       "  background-color: #1562a9;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row7_col0, #T_8473d_row7_col1, #T_8473d_row7_col2, #T_8473d_row18_col8 {\n",
+       "  background-color: #cfe1f2;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row7_col3, #T_8473d_row7_col4, #T_8473d_row36_col6 {\n",
+       "  background-color: #d8e7f5;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row7_col5 {\n",
+       "  background-color: #d9e7f5;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row7_col6, #T_8473d_row7_col7 {\n",
+       "  background-color: #4292c6;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row7_col8 {\n",
+       "  background-color: #1967ad;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row8_col0, #T_8473d_row8_col1, #T_8473d_row8_col6, #T_8473d_row8_col7, #T_8473d_row15_col3, #T_8473d_row38_col5, #T_8473d_row39_col2, #T_8473d_row40_col8, #T_8473d_row41_col2, #T_8473d_row41_col8, #T_8473d_row42_col2, #T_8473d_row42_col8, #T_8473d_row49_col2 {\n",
+       "  background-color: #f2f8fd;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row8_col2, #T_8473d_row20_col1, #T_8473d_row42_col1 {\n",
+       "  background-color: #b7d4ea;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row8_col5, #T_8473d_row12_col6, #T_8473d_row12_col7 {\n",
+       "  background-color: #bad6eb;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row8_col8, #T_8473d_row9_col8 {\n",
+       "  background-color: #3787c0;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row9_col2, #T_8473d_row22_col3, #T_8473d_row22_col4, #T_8473d_row38_col4 {\n",
+       "  background-color: #c6dbef;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row9_col5, #T_8473d_row16_col6, #T_8473d_row16_col7, #T_8473d_row17_col6, #T_8473d_row17_col7, #T_8473d_row17_col8 {\n",
+       "  background-color: #caddf0;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row9_col6, #T_8473d_row11_col5, #T_8473d_row13_col1, #T_8473d_row15_col5, #T_8473d_row18_col2, #T_8473d_row20_col5, #T_8473d_row23_col8, #T_8473d_row35_col3 {\n",
+       "  background-color: #e6f0f9;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row9_col7, #T_8473d_row15_col2, #T_8473d_row21_col3, #T_8473d_row21_col4, #T_8473d_row21_col5 {\n",
+       "  background-color: #ddeaf7;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row10_col5, #T_8473d_row37_col3, #T_8473d_row37_col4 {\n",
+       "  background-color: #cddff1;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row10_col6, #T_8473d_row10_col7, #T_8473d_row13_col4, #T_8473d_row18_col5, #T_8473d_row24_col0, #T_8473d_row24_col3, #T_8473d_row24_col4, #T_8473d_row27_col2, #T_8473d_row29_col8, #T_8473d_row30_col0, #T_8473d_row30_col1, #T_8473d_row30_col2, #T_8473d_row30_col3, #T_8473d_row30_col4, #T_8473d_row30_col5, #T_8473d_row30_col6, #T_8473d_row30_col7, #T_8473d_row30_col8, #T_8473d_row31_col0, #T_8473d_row31_col1, #T_8473d_row31_col2, #T_8473d_row31_col3, #T_8473d_row31_col4, #T_8473d_row31_col5, #T_8473d_row31_col6, #T_8473d_row31_col7, #T_8473d_row31_col8, #T_8473d_row32_col8, #T_8473d_row35_col2 {\n",
+       "  background-color: #e9f2fa;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row10_col8 {\n",
+       "  background-color: #5ca4d0;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row11_col0, #T_8473d_row11_col1, #T_8473d_row11_col2, #T_8473d_row15_col1 {\n",
+       "  background-color: #dbe9f6;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row11_col6, #T_8473d_row11_col7 {\n",
+       "  background-color: #8dc1dd;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row11_col8, #T_8473d_row42_col7 {\n",
+       "  background-color: #6aaed6;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row12_col0, #T_8473d_row12_col1, #T_8473d_row19_col0, #T_8473d_row19_col1, #T_8473d_row19_col3 {\n",
+       "  background-color: #deebf7;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row12_col2, #T_8473d_row13_col2, #T_8473d_row49_col6, #T_8473d_row49_col7 {\n",
+       "  background-color: #d9e8f5;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row12_col3, #T_8473d_row12_col4, #T_8473d_row35_col0, #T_8473d_row43_col7, #T_8473d_row52_col6 {\n",
+       "  background-color: #e3eef9;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row12_col5, #T_8473d_row13_col5, #T_8473d_row16_col2, #T_8473d_row17_col0, #T_8473d_row17_col1, #T_8473d_row17_col2, #T_8473d_row19_col2, #T_8473d_row19_col5, #T_8473d_row23_col7, #T_8473d_row36_col4 {\n",
+       "  background-color: #dfecf7;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row12_col8, #T_8473d_row13_col8 {\n",
+       "  background-color: #72b2d8;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row13_col0, #T_8473d_row15_col4 {\n",
+       "  background-color: #e3eef8;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row13_col3, #T_8473d_row24_col8 {\n",
+       "  background-color: #e7f0fa;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row13_col7 {\n",
+       "  background-color: #cee0f2;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row14_col5, #T_8473d_row26_col3, #T_8473d_row26_col4 {\n",
+       "  background-color: #d1e2f3;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row14_col8, #T_8473d_row26_col6, #T_8473d_row26_col7 {\n",
+       "  background-color: #a1cbe2;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row15_col7, #T_8473d_row38_col0 {\n",
+       "  background-color: #b9d6ea;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row15_col8 {\n",
+       "  background-color: #a6cee4;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row16_col0, #T_8473d_row36_col3, #T_8473d_row49_col1, #T_8473d_row49_col3, #T_8473d_row49_col4 {\n",
+       "  background-color: #e1edf8;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row16_col1, #T_8473d_row20_col2, #T_8473d_row35_col1, #T_8473d_row35_col7 {\n",
+       "  background-color: #e2edf8;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row16_col8 {\n",
+       "  background-color: #aacfe5;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row17_col3, #T_8473d_row17_col4, #T_8473d_row17_col5, #T_8473d_row49_col0 {\n",
+       "  background-color: #e0ecf8;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row19_col4, #T_8473d_row36_col0 {\n",
+       "  background-color: #dfebf7;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row19_col6 {\n",
+       "  background-color: #d3e4f3;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row19_col7 {\n",
+       "  background-color: #d4e4f4;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row19_col8, #T_8473d_row20_col8, #T_8473d_row36_col7 {\n",
+       "  background-color: #d5e5f4;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row20_col0, #T_8473d_row44_col0, #T_8473d_row44_col4 {\n",
+       "  background-color: #afd1e7;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row20_col3, #T_8473d_row42_col3 {\n",
+       "  background-color: #b5d4e9;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row20_col4, #T_8473d_row22_col0, #T_8473d_row22_col1 {\n",
+       "  background-color: #bcd7eb;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row20_col6 {\n",
+       "  background-color: #1966ad;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row20_col7 {\n",
+       "  background-color: #2676b8;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row21_col6, #T_8473d_row21_col7, #T_8473d_row21_col8 {\n",
+       "  background-color: #d6e5f4;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row22_col6, #T_8473d_row22_col7 {\n",
+       "  background-color: #1a68ae;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row24_col1, #T_8473d_row24_col5, #T_8473d_row24_col6, #T_8473d_row27_col8, #T_8473d_row28_col0, #T_8473d_row28_col1, #T_8473d_row28_col2, #T_8473d_row28_col6, #T_8473d_row28_col7, #T_8473d_row28_col8, #T_8473d_row32_col6, #T_8473d_row32_col7 {\n",
+       "  background-color: #e8f1fa;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row28_col3, #T_8473d_row28_col4, #T_8473d_row28_col5, #T_8473d_row39_col3, #T_8473d_row39_col4, #T_8473d_row39_col5, #T_8473d_row40_col5, #T_8473d_row41_col5, #T_8473d_row43_col5, #T_8473d_row45_col1, #T_8473d_row45_col2, #T_8473d_row45_col7, #T_8473d_row45_col8, #T_8473d_row46_col2, #T_8473d_row46_col3, #T_8473d_row46_col8, #T_8473d_row50_col3, #T_8473d_row50_col4 {\n",
+       "  background-color: #f4f9fe;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row29_col3, #T_8473d_row29_col4 {\n",
+       "  background-color: #d6e6f4;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row29_col6, #T_8473d_row29_col7 {\n",
+       "  background-color: #3f8fc5;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row35_col5 {\n",
+       "  background-color: #ebf3fb;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row36_col1 {\n",
+       "  background-color: #dce9f6;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row37_col6, #T_8473d_row37_col7, #T_8473d_row42_col6 {\n",
+       "  background-color: #65aad4;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row38_col6 {\n",
+       "  background-color: #2c7cba;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row38_col7 {\n",
+       "  background-color: #3a8ac2;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row42_col0 {\n",
+       "  background-color: #b2d2e8;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row42_col4 {\n",
+       "  background-color: #b8d5ea;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row44_col1 {\n",
+       "  background-color: #aed1e7;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row44_col3 {\n",
+       "  background-color: #b0d2e7;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_row44_col6, #T_8473d_row44_col7 {\n",
+       "  background-color: #519ccc;\n",
+       "  color: #f1f1f1;\n",
+       "}\n",
+       "#T_8473d_row52_col1, #T_8473d_row52_col2, #T_8473d_row52_col4, #T_8473d_row52_col5, #T_8473d_row52_col7, #T_8473d_row52_col8 {\n",
+       "  background-color: #f7fbff;\n",
+       "  color: #000000;\n",
+       "}\n",
+       "#T_8473d_level0_row0, #T_8473d_level1_row0, #T_8473d_level1_row1, #T_8473d_level0_row2, #T_8473d_level1_row2, #T_8473d_level0_row3, #T_8473d_level1_row3, #T_8473d_level0_row4, #T_8473d_level1_row4, #T_8473d_level0_row5, #T_8473d_level1_row5, #T_8473d_level0_row6, #T_8473d_level1_row6, #T_8473d_level0_row7, #T_8473d_level0_row8, #T_8473d_level1_row8, #T_8473d_level0_row9, #T_8473d_level1_row9, #T_8473d_level0_row10, #T_8473d_level1_row10, #T_8473d_level0_row12, #T_8473d_level1_row13, #T_8473d_level0_row14, #T_8473d_level1_row14, #T_8473d_level0_row15, #T_8473d_level1_row17, #T_8473d_level0_row18, #T_8473d_level1_row19, #T_8473d_level1_row21, #T_8473d_level0_row26, #T_8473d_level1_row29, #T_8473d_level1_row31, #T_8473d_level1_row32, #T_8473d_level1_row34, #T_8473d_level0_row36, #T_8473d_level1_row37, #T_8473d_level0_row38, #T_8473d_level0_row40, #T_8473d_level0_row41, #T_8473d_level1_row43, #T_8473d_level1_row44, #T_8473d_level1_row46, #T_8473d_level0_row47, #T_8473d_level1_row49, #T_8473d_level1_row50, #T_8473d_level0_row52 {\n",
+       "  color: black;\n",
+       "}\n",
+       "#T_8473d_level1_row7, #T_8473d_level0_row11, #T_8473d_level1_row11, #T_8473d_level0_row21, #T_8473d_level0_row28, #T_8473d_level1_row28, #T_8473d_level0_row30, #T_8473d_level1_row30, #T_8473d_level0_row31, #T_8473d_level0_row51, #T_8473d_level1_row51 {\n",
+       "  color: dodgerblue;\n",
+       "}\n",
+       "#T_8473d_level1_row12, #T_8473d_level1_row15, #T_8473d_level0_row16, #T_8473d_level1_row16, #T_8473d_level0_row17, #T_8473d_level0_row19, #T_8473d_level0_row23, #T_8473d_level1_row23, #T_8473d_level0_row24, #T_8473d_level1_row24, #T_8473d_level0_row27, #T_8473d_level1_row27, #T_8473d_level0_row33, #T_8473d_level1_row33, #T_8473d_level0_row34, #T_8473d_level0_row39, #T_8473d_level1_row39, #T_8473d_level1_row41, #T_8473d_level0_row45, #T_8473d_level1_row45, #T_8473d_level0_row48, #T_8473d_level1_row48, #T_8473d_level1_row52 {\n",
+       "  color: mediumseagreen;\n",
+       "}\n",
+       "#T_8473d_level1_row18, #T_8473d_level0_row20, #T_8473d_level1_row20, #T_8473d_level0_row22, #T_8473d_level1_row22, #T_8473d_level0_row25, #T_8473d_level1_row25, #T_8473d_level1_row26, #T_8473d_level0_row29, #T_8473d_level0_row32, #T_8473d_level0_row35, #T_8473d_level1_row35, #T_8473d_level0_row37, #T_8473d_level1_row38, #T_8473d_level1_row40, #T_8473d_level0_row43, #T_8473d_level0_row46, #T_8473d_level1_row47, #T_8473d_level0_row50 {\n",
+       "  color: crimson;\n",
+       "}\n",
+       "#T_8473d_level1_row36, #T_8473d_level1_row42, #T_8473d_level0_row44, #T_8473d_level0_row49 {\n",
+       "  color: darkorange;\n",
+       "}\n",
+       "</style>\n",
+       "<table id=\"T_8473d\" style=\"font-size: 12px\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th class=\"blank\" >&nbsp;</th>\n",
+       "      <th class=\"blank level0\" >&nbsp;</th>\n",
+       "      <th id=\"T_8473d_level0_col0\" class=\"col_heading level0 col0\" colspan=\"3\"></th>\n",
+       "      <th id=\"T_8473d_level0_col3\" class=\"col_heading level0 col3\" colspan=\"3\">Len scales</th>\n",
+       "      <th id=\"T_8473d_level0_col6\" class=\"col_heading level0 col6\" colspan=\"3\">Lin scales</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th class=\"blank\" >&nbsp;</th>\n",
+       "      <th class=\"blank level1\" >&nbsp;</th>\n",
+       "      <th id=\"T_8473d_level1_col0\" class=\"col_heading level1 col0\" >C_B_e</th>\n",
+       "      <th id=\"T_8473d_level1_col1\" class=\"col_heading level1 col1\" >C_B_e_paths</th>\n",
+       "      <th id=\"T_8473d_level1_col2\" class=\"col_heading level1 col2\" >C_B_e_restr</th>\n",
+       "      <th id=\"T_8473d_level1_col3\" class=\"col_heading level1 col3\" >C_B_e</th>\n",
+       "      <th id=\"T_8473d_level1_col4\" class=\"col_heading level1 col4\" >C_B_e_paths</th>\n",
+       "      <th id=\"T_8473d_level1_col5\" class=\"col_heading level1 col5\" >C_B_e_restr</th>\n",
+       "      <th id=\"T_8473d_level1_col6\" class=\"col_heading level1 col6\" >C_B_e</th>\n",
+       "      <th id=\"T_8473d_level1_col7\" class=\"col_heading level1 col7\" >C_B_e_paths</th>\n",
+       "      <th id=\"T_8473d_level1_col8\" class=\"col_heading level1 col8\" >C_B_e_restr</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row0\" class=\"row_heading level0 row0\" rowspan=\"2\">3</th>\n",
+       "      <th id=\"T_8473d_level1_row0\" class=\"row_heading level1 row0\" >4</th>\n",
+       "      <td id=\"T_8473d_row0_col0\" class=\"data row0 col0\" >0.029</td>\n",
+       "      <td id=\"T_8473d_row0_col1\" class=\"data row0 col1\" >0.042</td>\n",
+       "      <td id=\"T_8473d_row0_col2\" class=\"data row0 col2\" >0.163</td>\n",
+       "      <td id=\"T_8473d_row0_col3\" class=\"data row0 col3\" >0.020</td>\n",
+       "      <td id=\"T_8473d_row0_col4\" class=\"data row0 col4\" >0.026</td>\n",
+       "      <td id=\"T_8473d_row0_col5\" class=\"data row0 col5\" >0.144</td>\n",
+       "      <td id=\"T_8473d_row0_col6\" class=\"data row0 col6\" >0.037</td>\n",
+       "      <td id=\"T_8473d_row0_col7\" class=\"data row0 col7\" >0.051</td>\n",
+       "      <td id=\"T_8473d_row0_col8\" class=\"data row0 col8\" >0.632</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level1_row1\" class=\"row_heading level1 row1\" >2</th>\n",
+       "      <td id=\"T_8473d_row1_col0\" class=\"data row1 col0\" >0.036</td>\n",
+       "      <td id=\"T_8473d_row1_col1\" class=\"data row1 col1\" >0.026</td>\n",
+       "      <td id=\"T_8473d_row1_col2\" class=\"data row1 col2\" >0.168</td>\n",
+       "      <td id=\"T_8473d_row1_col3\" class=\"data row1 col3\" >0.035</td>\n",
+       "      <td id=\"T_8473d_row1_col4\" class=\"data row1 col4\" >0.026</td>\n",
+       "      <td id=\"T_8473d_row1_col5\" class=\"data row1 col5\" >0.156</td>\n",
+       "      <td id=\"T_8473d_row1_col6\" class=\"data row1 col6\" >0.043</td>\n",
+       "      <td id=\"T_8473d_row1_col7\" class=\"data row1 col7\" >0.026</td>\n",
+       "      <td id=\"T_8473d_row1_col8\" class=\"data row1 col8\" >0.623</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row2\" class=\"row_heading level0 row2\" >4</th>\n",
+       "      <th id=\"T_8473d_level1_row2\" class=\"row_heading level1 row2\" >5</th>\n",
+       "      <td id=\"T_8473d_row2_col0\" class=\"data row2 col0\" >0.026</td>\n",
+       "      <td id=\"T_8473d_row2_col1\" class=\"data row2 col1\" >0.026</td>\n",
+       "      <td id=\"T_8473d_row2_col2\" class=\"data row2 col2\" >0.145</td>\n",
+       "      <td id=\"T_8473d_row2_col3\" class=\"data row2 col3\" >0.025</td>\n",
+       "      <td id=\"T_8473d_row2_col4\" class=\"data row2 col4\" >0.025</td>\n",
+       "      <td id=\"T_8473d_row2_col5\" class=\"data row2 col5\" >0.124</td>\n",
+       "      <td id=\"T_8473d_row2_col6\" class=\"data row2 col6\" >0.042</td>\n",
+       "      <td id=\"T_8473d_row2_col7\" class=\"data row2 col7\" >0.042</td>\n",
+       "      <td id=\"T_8473d_row2_col8\" class=\"data row2 col8\" >0.623</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row3\" class=\"row_heading level0 row3\" >2</th>\n",
+       "      <th id=\"T_8473d_level1_row3\" class=\"row_heading level1 row3\" >1</th>\n",
+       "      <td id=\"T_8473d_row3_col0\" class=\"data row3 col0\" >0.007</td>\n",
+       "      <td id=\"T_8473d_row3_col1\" class=\"data row3 col1\" >0.008</td>\n",
+       "      <td id=\"T_8473d_row3_col2\" class=\"data row3 col2\" >0.150</td>\n",
+       "      <td id=\"T_8473d_row3_col3\" class=\"data row3 col3\" >0.005</td>\n",
+       "      <td id=\"T_8473d_row3_col4\" class=\"data row3 col4\" >0.006</td>\n",
+       "      <td id=\"T_8473d_row3_col5\" class=\"data row3 col5\" >0.135</td>\n",
+       "      <td id=\"T_8473d_row3_col6\" class=\"data row3 col6\" >0.007</td>\n",
+       "      <td id=\"T_8473d_row3_col7\" class=\"data row3 col7\" >0.008</td>\n",
+       "      <td id=\"T_8473d_row3_col8\" class=\"data row3 col8\" >0.602</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
+       "      <th id=\"T_8473d_level1_row4\" class=\"row_heading level1 row4\" >6</th>\n",
+       "      <td id=\"T_8473d_row4_col0\" class=\"data row4 col0\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row4_col1\" class=\"data row4 col1\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row4_col2\" class=\"data row4 col2\" >0.126</td>\n",
+       "      <td id=\"T_8473d_row4_col3\" class=\"data row4 col3\" >0.028</td>\n",
+       "      <td id=\"T_8473d_row4_col4\" class=\"data row4 col4\" >0.028</td>\n",
+       "      <td id=\"T_8473d_row4_col5\" class=\"data row4 col5\" >0.103</td>\n",
+       "      <td id=\"T_8473d_row4_col6\" class=\"data row4 col6\" >0.059</td>\n",
+       "      <td id=\"T_8473d_row4_col7\" class=\"data row4 col7\" >0.059</td>\n",
+       "      <td id=\"T_8473d_row4_col8\" class=\"data row4 col8\" >0.572</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row5\" class=\"row_heading level0 row5\" >4</th>\n",
+       "      <th id=\"T_8473d_level1_row5\" class=\"row_heading level1 row5\" >3</th>\n",
+       "      <td id=\"T_8473d_row5_col0\" class=\"data row5 col0\" >0.024</td>\n",
+       "      <td id=\"T_8473d_row5_col1\" class=\"data row5 col1\" >0.018</td>\n",
+       "      <td id=\"T_8473d_row5_col2\" class=\"data row5 col2\" >0.161</td>\n",
+       "      <td id=\"T_8473d_row5_col3\" class=\"data row5 col3\" >0.012</td>\n",
+       "      <td id=\"T_8473d_row5_col4\" class=\"data row5 col4\" >0.006</td>\n",
+       "      <td id=\"T_8473d_row5_col5\" class=\"data row5 col5\" >0.148</td>\n",
+       "      <td id=\"T_8473d_row5_col6\" class=\"data row5 col6\" >0.027</td>\n",
+       "      <td id=\"T_8473d_row5_col7\" class=\"data row5 col7\" >0.018</td>\n",
+       "      <td id=\"T_8473d_row5_col8\" class=\"data row5 col8\" >0.530</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row6\" class=\"row_heading level0 row6\" >2</th>\n",
+       "      <th id=\"T_8473d_level1_row6\" class=\"row_heading level1 row6\" >3</th>\n",
+       "      <td id=\"T_8473d_row6_col0\" class=\"data row6 col0\" >0.041</td>\n",
+       "      <td id=\"T_8473d_row6_col1\" class=\"data row6 col1\" >0.050</td>\n",
+       "      <td id=\"T_8473d_row6_col2\" class=\"data row6 col2\" >0.171</td>\n",
+       "      <td id=\"T_8473d_row6_col3\" class=\"data row6 col3\" >0.025</td>\n",
+       "      <td id=\"T_8473d_row6_col4\" class=\"data row6 col4\" >0.035</td>\n",
+       "      <td id=\"T_8473d_row6_col5\" class=\"data row6 col5\" >0.154</td>\n",
+       "      <td id=\"T_8473d_row6_col6\" class=\"data row6 col6\" >0.058</td>\n",
+       "      <td id=\"T_8473d_row6_col7\" class=\"data row6 col7\" >0.085</td>\n",
+       "      <td id=\"T_8473d_row6_col8\" class=\"data row6 col8\" >0.509</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row7\" class=\"row_heading level0 row7\" >6</th>\n",
+       "      <th id=\"T_8473d_level1_row7\" class=\"row_heading level1 row7\" >15</th>\n",
+       "      <td id=\"T_8473d_row7_col0\" class=\"data row7 col0\" >0.129</td>\n",
+       "      <td id=\"T_8473d_row7_col1\" class=\"data row7 col1\" >0.129</td>\n",
+       "      <td id=\"T_8473d_row7_col2\" class=\"data row7 col2\" >0.129</td>\n",
+       "      <td id=\"T_8473d_row7_col3\" class=\"data row7 col3\" >0.100</td>\n",
+       "      <td id=\"T_8473d_row7_col4\" class=\"data row7 col4\" >0.100</td>\n",
+       "      <td id=\"T_8473d_row7_col5\" class=\"data row7 col5\" >0.099</td>\n",
+       "      <td id=\"T_8473d_row7_col6\" class=\"data row7 col6\" >0.393</td>\n",
+       "      <td id=\"T_8473d_row7_col7\" class=\"data row7 col7\" >0.393</td>\n",
+       "      <td id=\"T_8473d_row7_col8\" class=\"data row7 col8\" >0.498</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row8\" class=\"row_heading level0 row8\" >0</th>\n",
+       "      <th id=\"T_8473d_level1_row8\" class=\"row_heading level1 row8\" >1</th>\n",
+       "      <td id=\"T_8473d_row8_col0\" class=\"data row8 col0\" >0.017</td>\n",
+       "      <td id=\"T_8473d_row8_col1\" class=\"data row8 col1\" >0.016</td>\n",
+       "      <td id=\"T_8473d_row8_col2\" class=\"data row8 col2\" >0.189</td>\n",
+       "      <td id=\"T_8473d_row8_col3\" class=\"data row8 col3\" >0.009</td>\n",
+       "      <td id=\"T_8473d_row8_col4\" class=\"data row8 col4\" >0.008</td>\n",
+       "      <td id=\"T_8473d_row8_col5\" class=\"data row8 col5\" >0.182</td>\n",
+       "      <td id=\"T_8473d_row8_col6\" class=\"data row8 col6\" >0.017</td>\n",
+       "      <td id=\"T_8473d_row8_col7\" class=\"data row8 col7\" >0.016</td>\n",
+       "      <td id=\"T_8473d_row8_col8\" class=\"data row8 col8\" >0.421</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row9\" class=\"row_heading level0 row9\" >1</th>\n",
+       "      <th id=\"T_8473d_level1_row9\" class=\"row_heading level1 row9\" >2</th>\n",
+       "      <td id=\"T_8473d_row9_col0\" class=\"data row9 col0\" >0.033</td>\n",
+       "      <td id=\"T_8473d_row9_col1\" class=\"data row9 col1\" >0.042</td>\n",
+       "      <td id=\"T_8473d_row9_col2\" class=\"data row9 col2\" >0.158</td>\n",
+       "      <td id=\"T_8473d_row9_col3\" class=\"data row9 col3\" >0.022</td>\n",
+       "      <td id=\"T_8473d_row9_col4\" class=\"data row9 col4\" >0.031</td>\n",
+       "      <td id=\"T_8473d_row9_col5\" class=\"data row9 col5\" >0.146</td>\n",
+       "      <td id=\"T_8473d_row9_col6\" class=\"data row9 col6\" >0.055</td>\n",
+       "      <td id=\"T_8473d_row9_col7\" class=\"data row9 col7\" >0.083</td>\n",
+       "      <td id=\"T_8473d_row9_col8\" class=\"data row9 col8\" >0.421</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row10\" class=\"row_heading level0 row10\" >5</th>\n",
+       "      <th id=\"T_8473d_level1_row10\" class=\"row_heading level1 row10\" >4</th>\n",
+       "      <td id=\"T_8473d_row10_col0\" class=\"data row10 col0\" >0.026</td>\n",
+       "      <td id=\"T_8473d_row10_col1\" class=\"data row10 col1\" >0.026</td>\n",
+       "      <td id=\"T_8473d_row10_col2\" class=\"data row10 col2\" >0.145</td>\n",
+       "      <td id=\"T_8473d_row10_col3\" class=\"data row10 col3\" >0.020</td>\n",
+       "      <td id=\"T_8473d_row10_col4\" class=\"data row10 col4\" >0.020</td>\n",
+       "      <td id=\"T_8473d_row10_col5\" class=\"data row10 col5\" >0.138</td>\n",
+       "      <td id=\"T_8473d_row10_col6\" class=\"data row10 col6\" >0.046</td>\n",
+       "      <td id=\"T_8473d_row10_col7\" class=\"data row10 col7\" >0.046</td>\n",
+       "      <td id=\"T_8473d_row10_col8\" class=\"data row10 col8\" >0.345</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row11\" class=\"row_heading level0 row11\" >15</th>\n",
+       "      <th id=\"T_8473d_level1_row11\" class=\"row_heading level1 row11\" >16</th>\n",
+       "      <td id=\"T_8473d_row11_col0\" class=\"data row11 col0\" >0.089</td>\n",
+       "      <td id=\"T_8473d_row11_col1\" class=\"data row11 col1\" >0.089</td>\n",
+       "      <td id=\"T_8473d_row11_col2\" class=\"data row11 col2\" >0.089</td>\n",
+       "      <td id=\"T_8473d_row11_col3\" class=\"data row11 col3\" >0.057</td>\n",
+       "      <td id=\"T_8473d_row11_col4\" class=\"data row11 col4\" >0.057</td>\n",
+       "      <td id=\"T_8473d_row11_col5\" class=\"data row11 col5\" >0.056</td>\n",
+       "      <td id=\"T_8473d_row11_col6\" class=\"data row11 col6\" >0.264</td>\n",
+       "      <td id=\"T_8473d_row11_col7\" class=\"data row11 col7\" >0.264</td>\n",
+       "      <td id=\"T_8473d_row11_col8\" class=\"data row11 col8\" >0.316</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row12\" class=\"row_heading level0 row12\" rowspan=\"2\">1</th>\n",
+       "      <th id=\"T_8473d_level1_row12\" class=\"row_heading level1 row12\" >10</th>\n",
+       "      <td id=\"T_8473d_row12_col0\" class=\"data row12 col0\" >0.079</td>\n",
+       "      <td id=\"T_8473d_row12_col1\" class=\"data row12 col1\" >0.079</td>\n",
+       "      <td id=\"T_8473d_row12_col2\" class=\"data row12 col2\" >0.095</td>\n",
+       "      <td id=\"T_8473d_row12_col3\" class=\"data row12 col3\" >0.063</td>\n",
+       "      <td id=\"T_8473d_row12_col4\" class=\"data row12 col4\" >0.063</td>\n",
+       "      <td id=\"T_8473d_row12_col5\" class=\"data row12 col5\" >0.074</td>\n",
+       "      <td id=\"T_8473d_row12_col6\" class=\"data row12 col6\" >0.182</td>\n",
+       "      <td id=\"T_8473d_row12_col7\" class=\"data row12 col7\" >0.182</td>\n",
+       "      <td id=\"T_8473d_row12_col8\" class=\"data row12 col8\" >0.306</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level1_row13\" class=\"row_heading level1 row13\" >0</th>\n",
+       "      <td id=\"T_8473d_row13_col0\" class=\"data row13 col0\" >0.064</td>\n",
+       "      <td id=\"T_8473d_row13_col1\" class=\"data row13 col1\" >0.055</td>\n",
+       "      <td id=\"T_8473d_row13_col2\" class=\"data row13 col2\" >0.095</td>\n",
+       "      <td id=\"T_8473d_row13_col3\" class=\"data row13 col3\" >0.054</td>\n",
+       "      <td id=\"T_8473d_row13_col4\" class=\"data row13 col4\" >0.044</td>\n",
+       "      <td id=\"T_8473d_row13_col5\" class=\"data row13 col5\" >0.074</td>\n",
+       "      <td id=\"T_8473d_row13_col6\" class=\"data row13 col6\" >0.161</td>\n",
+       "      <td id=\"T_8473d_row13_col7\" class=\"data row13 col7\" >0.132</td>\n",
+       "      <td id=\"T_8473d_row13_col8\" class=\"data row13 col8\" >0.306</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row14\" class=\"row_heading level0 row14\" >6</th>\n",
+       "      <th id=\"T_8473d_level1_row14\" class=\"row_heading level1 row14\" >5</th>\n",
+       "      <td id=\"T_8473d_row14_col0\" class=\"data row14 col0\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row14_col1\" class=\"data row14 col1\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row14_col2\" class=\"data row14 col2\" >0.126</td>\n",
+       "      <td id=\"T_8473d_row14_col3\" class=\"data row14 col3\" >0.027</td>\n",
+       "      <td id=\"T_8473d_row14_col4\" class=\"data row14 col4\" >0.027</td>\n",
+       "      <td id=\"T_8473d_row14_col5\" class=\"data row14 col5\" >0.122</td>\n",
+       "      <td id=\"T_8473d_row14_col6\" class=\"data row14 col6\" >0.051</td>\n",
+       "      <td id=\"T_8473d_row14_col7\" class=\"data row14 col7\" >0.051</td>\n",
+       "      <td id=\"T_8473d_row14_col8\" class=\"data row14 col8\" >0.231</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row15\" class=\"row_heading level0 row15\" >0</th>\n",
+       "      <th id=\"T_8473d_level1_row15\" class=\"row_heading level1 row15\" >14</th>\n",
+       "      <td id=\"T_8473d_row15_col0\" class=\"data row15 col0\" >0.041</td>\n",
+       "      <td id=\"T_8473d_row15_col1\" class=\"data row15 col1\" >0.089</td>\n",
+       "      <td id=\"T_8473d_row15_col2\" class=\"data row15 col2\" >0.082</td>\n",
+       "      <td id=\"T_8473d_row15_col3\" class=\"data row15 col3\" >0.016</td>\n",
+       "      <td id=\"T_8473d_row15_col4\" class=\"data row15 col4\" >0.066</td>\n",
+       "      <td id=\"T_8473d_row15_col5\" class=\"data row15 col5\" >0.055</td>\n",
+       "      <td id=\"T_8473d_row15_col6\" class=\"data row15 col6\" >0.041</td>\n",
+       "      <td id=\"T_8473d_row15_col7\" class=\"data row15 col7\" >0.184</td>\n",
+       "      <td id=\"T_8473d_row15_col8\" class=\"data row15 col8\" >0.221</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row16\" class=\"row_heading level0 row16\" >10</th>\n",
+       "      <th id=\"T_8473d_level1_row16\" class=\"row_heading level1 row16\" >11</th>\n",
+       "      <td id=\"T_8473d_row16_col0\" class=\"data row16 col0\" >0.070</td>\n",
+       "      <td id=\"T_8473d_row16_col1\" class=\"data row16 col1\" >0.068</td>\n",
+       "      <td id=\"T_8473d_row16_col2\" class=\"data row16 col2\" >0.076</td>\n",
+       "      <td id=\"T_8473d_row16_col3\" class=\"data row16 col3\" >0.043</td>\n",
+       "      <td id=\"T_8473d_row16_col4\" class=\"data row16 col4\" >0.043</td>\n",
+       "      <td id=\"T_8473d_row16_col5\" class=\"data row16 col5\" >0.049</td>\n",
+       "      <td id=\"T_8473d_row16_col6\" class=\"data row16 col6\" >0.148</td>\n",
+       "      <td id=\"T_8473d_row16_col7\" class=\"data row16 col7\" >0.146</td>\n",
+       "      <td id=\"T_8473d_row16_col8\" class=\"data row16 col8\" >0.213</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row17\" class=\"row_heading level0 row17\" >13</th>\n",
+       "      <th id=\"T_8473d_level1_row17\" class=\"row_heading level1 row17\" >0</th>\n",
+       "      <td id=\"T_8473d_row17_col0\" class=\"data row17 col0\" >0.076</td>\n",
+       "      <td id=\"T_8473d_row17_col1\" class=\"data row17 col1\" >0.076</td>\n",
+       "      <td id=\"T_8473d_row17_col2\" class=\"data row17 col2\" >0.076</td>\n",
+       "      <td id=\"T_8473d_row17_col3\" class=\"data row17 col3\" >0.074</td>\n",
+       "      <td id=\"T_8473d_row17_col4\" class=\"data row17 col4\" >0.074</td>\n",
+       "      <td id=\"T_8473d_row17_col5\" class=\"data row17 col5\" >0.074</td>\n",
+       "      <td id=\"T_8473d_row17_col6\" class=\"data row17 col6\" >0.146</td>\n",
+       "      <td id=\"T_8473d_row17_col7\" class=\"data row17 col7\" >0.146</td>\n",
+       "      <td id=\"T_8473d_row17_col8\" class=\"data row17 col8\" >0.146</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row18\" class=\"row_heading level0 row18\" >1</th>\n",
+       "      <th id=\"T_8473d_level1_row18\" class=\"row_heading level1 row18\" >7</th>\n",
+       "      <td id=\"T_8473d_row18_col0\" class=\"data row18 col0\" >0.024</td>\n",
+       "      <td id=\"T_8473d_row18_col1\" class=\"data row18 col1\" >0.024</td>\n",
+       "      <td id=\"T_8473d_row18_col2\" class=\"data row18 col2\" >0.055</td>\n",
+       "      <td id=\"T_8473d_row18_col3\" class=\"data row18 col3\" >0.024</td>\n",
+       "      <td id=\"T_8473d_row18_col4\" class=\"data row18 col4\" >0.024</td>\n",
+       "      <td id=\"T_8473d_row18_col5\" class=\"data row18 col5\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row18_col6\" class=\"data row18 col6\" >0.024</td>\n",
+       "      <td id=\"T_8473d_row18_col7\" class=\"data row18 col7\" >0.024</td>\n",
+       "      <td id=\"T_8473d_row18_col8\" class=\"data row18 col8\" >0.129</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row19\" class=\"row_heading level0 row19\" >10</th>\n",
+       "      <th id=\"T_8473d_level1_row19\" class=\"row_heading level1 row19\" >0</th>\n",
+       "      <td id=\"T_8473d_row19_col0\" class=\"data row19 col0\" >0.080</td>\n",
+       "      <td id=\"T_8473d_row19_col1\" class=\"data row19 col1\" >0.079</td>\n",
+       "      <td id=\"T_8473d_row19_col2\" class=\"data row19 col2\" >0.076</td>\n",
+       "      <td id=\"T_8473d_row19_col3\" class=\"data row19 col3\" >0.079</td>\n",
+       "      <td id=\"T_8473d_row19_col4\" class=\"data row19 col4\" >0.078</td>\n",
+       "      <td id=\"T_8473d_row19_col5\" class=\"data row19 col5\" >0.075</td>\n",
+       "      <td id=\"T_8473d_row19_col6\" class=\"data row19 col6\" >0.116</td>\n",
+       "      <td id=\"T_8473d_row19_col7\" class=\"data row19 col7\" >0.113</td>\n",
+       "      <td id=\"T_8473d_row19_col8\" class=\"data row19 col8\" >0.111</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row20\" class=\"row_heading level0 row20\" >7</th>\n",
+       "      <th id=\"T_8473d_level1_row20\" class=\"row_heading level1 row20\" >8</th>\n",
+       "      <td id=\"T_8473d_row20_col0\" class=\"data row20 col0\" >0.203</td>\n",
+       "      <td id=\"T_8473d_row20_col1\" class=\"data row20 col1\" >0.189</td>\n",
+       "      <td id=\"T_8473d_row20_col2\" class=\"data row20 col2\" >0.068</td>\n",
+       "      <td id=\"T_8473d_row20_col3\" class=\"data row20 col3\" >0.190</td>\n",
+       "      <td id=\"T_8473d_row20_col4\" class=\"data row20 col4\" >0.178</td>\n",
+       "      <td id=\"T_8473d_row20_col5\" class=\"data row20 col5\" >0.057</td>\n",
+       "      <td id=\"T_8473d_row20_col6\" class=\"data row20 col6\" >0.499</td>\n",
+       "      <td id=\"T_8473d_row20_col7\" class=\"data row20 col7\" >0.461</td>\n",
+       "      <td id=\"T_8473d_row20_col8\" class=\"data row20 col8\" >0.109</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row21\" class=\"row_heading level0 row21\" >15</th>\n",
+       "      <th id=\"T_8473d_level1_row21\" class=\"row_heading level1 row21\" >6</th>\n",
+       "      <td id=\"T_8473d_row21_col0\" class=\"data row21 col0\" >0.084</td>\n",
+       "      <td id=\"T_8473d_row21_col1\" class=\"data row21 col1\" >0.084</td>\n",
+       "      <td id=\"T_8473d_row21_col2\" class=\"data row21 col2\" >0.084</td>\n",
+       "      <td id=\"T_8473d_row21_col3\" class=\"data row21 col3\" >0.084</td>\n",
+       "      <td id=\"T_8473d_row21_col4\" class=\"data row21 col4\" >0.084</td>\n",
+       "      <td id=\"T_8473d_row21_col5\" class=\"data row21 col5\" >0.084</td>\n",
+       "      <td id=\"T_8473d_row21_col6\" class=\"data row21 col6\" >0.108</td>\n",
+       "      <td id=\"T_8473d_row21_col7\" class=\"data row21 col7\" >0.108</td>\n",
+       "      <td id=\"T_8473d_row21_col8\" class=\"data row21 col8\" >0.108</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row22\" class=\"row_heading level0 row22\" >8</th>\n",
+       "      <th id=\"T_8473d_level1_row22\" class=\"row_heading level1 row22\" >9</th>\n",
+       "      <td id=\"T_8473d_row22_col0\" class=\"data row22 col0\" >0.179</td>\n",
+       "      <td id=\"T_8473d_row22_col1\" class=\"data row22 col1\" >0.179</td>\n",
+       "      <td id=\"T_8473d_row22_col2\" class=\"data row22 col2\" >0.061</td>\n",
+       "      <td id=\"T_8473d_row22_col3\" class=\"data row22 col3\" >0.160</td>\n",
+       "      <td id=\"T_8473d_row22_col4\" class=\"data row22 col4\" >0.160</td>\n",
+       "      <td id=\"T_8473d_row22_col5\" class=\"data row22 col5\" >0.042</td>\n",
+       "      <td id=\"T_8473d_row22_col6\" class=\"data row22 col6\" >0.493</td>\n",
+       "      <td id=\"T_8473d_row22_col7\" class=\"data row22 col7\" >0.493</td>\n",
+       "      <td id=\"T_8473d_row22_col8\" class=\"data row22 col8\" >0.059</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row23\" class=\"row_heading level0 row23\" >14</th>\n",
+       "      <th id=\"T_8473d_level1_row23\" class=\"row_heading level1 row23\" >13</th>\n",
+       "      <td id=\"T_8473d_row23_col0\" class=\"data row23 col0\" >0.007</td>\n",
+       "      <td id=\"T_8473d_row23_col1\" class=\"data row23 col1\" >0.058</td>\n",
+       "      <td id=\"T_8473d_row23_col2\" class=\"data row23 col2\" >0.050</td>\n",
+       "      <td id=\"T_8473d_row23_col3\" class=\"data row23 col3\" >0.007</td>\n",
+       "      <td id=\"T_8473d_row23_col4\" class=\"data row23 col4\" >0.029</td>\n",
+       "      <td id=\"T_8473d_row23_col5\" class=\"data row23 col5\" >0.021</td>\n",
+       "      <td id=\"T_8473d_row23_col6\" class=\"data row23 col6\" >0.007</td>\n",
+       "      <td id=\"T_8473d_row23_col7\" class=\"data row23 col7\" >0.076</td>\n",
+       "      <td id=\"T_8473d_row23_col8\" class=\"data row23 col8\" >0.056</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row24\" class=\"row_heading level0 row24\" >12</th>\n",
+       "      <th id=\"T_8473d_level1_row24\" class=\"row_heading level1 row24\" >13</th>\n",
+       "      <td id=\"T_8473d_row24_col0\" class=\"data row24 col0\" >0.046</td>\n",
+       "      <td id=\"T_8473d_row24_col1\" class=\"data row24 col1\" >0.047</td>\n",
+       "      <td id=\"T_8473d_row24_col2\" class=\"data row24 col2\" >0.050</td>\n",
+       "      <td id=\"T_8473d_row24_col3\" class=\"data row24 col3\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row24_col4\" class=\"data row24 col4\" >0.046</td>\n",
+       "      <td id=\"T_8473d_row24_col5\" class=\"data row24 col5\" >0.047</td>\n",
+       "      <td id=\"T_8473d_row24_col6\" class=\"data row24 col6\" >0.047</td>\n",
+       "      <td id=\"T_8473d_row24_col7\" class=\"data row24 col7\" >0.050</td>\n",
+       "      <td id=\"T_8473d_row24_col8\" class=\"data row24 col8\" >0.053</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row25\" class=\"row_heading level0 row25\" >9</th>\n",
+       "      <th id=\"T_8473d_level1_row25\" class=\"row_heading level1 row25\" >8</th>\n",
+       "      <td id=\"T_8473d_row25_col0\" class=\"data row25 col0\" >0.034</td>\n",
+       "      <td id=\"T_8473d_row25_col1\" class=\"data row25 col1\" >0.034</td>\n",
+       "      <td id=\"T_8473d_row25_col2\" class=\"data row25 col2\" >0.034</td>\n",
+       "      <td id=\"T_8473d_row25_col3\" class=\"data row25 col3\" >0.028</td>\n",
+       "      <td id=\"T_8473d_row25_col4\" class=\"data row25 col4\" >0.028</td>\n",
+       "      <td id=\"T_8473d_row25_col5\" class=\"data row25 col5\" >0.028</td>\n",
+       "      <td id=\"T_8473d_row25_col6\" class=\"data row25 col6\" >0.051</td>\n",
+       "      <td id=\"T_8473d_row25_col7\" class=\"data row25 col7\" >0.051</td>\n",
+       "      <td id=\"T_8473d_row25_col8\" class=\"data row25 col8\" >0.051</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row26\" class=\"row_heading level0 row26\" >6</th>\n",
+       "      <th id=\"T_8473d_level1_row26\" class=\"row_heading level1 row26\" >9</th>\n",
+       "      <td id=\"T_8473d_row26_col0\" class=\"data row26 col0\" >0.126</td>\n",
+       "      <td id=\"T_8473d_row26_col1\" class=\"data row26 col1\" >0.126</td>\n",
+       "      <td id=\"T_8473d_row26_col2\" class=\"data row26 col2\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row26_col3\" class=\"data row26 col3\" >0.122</td>\n",
+       "      <td id=\"T_8473d_row26_col4\" class=\"data row26 col4\" >0.122</td>\n",
+       "      <td id=\"T_8473d_row26_col5\" class=\"data row26 col5\" >0.027</td>\n",
+       "      <td id=\"T_8473d_row26_col6\" class=\"data row26 col6\" >0.231</td>\n",
+       "      <td id=\"T_8473d_row26_col7\" class=\"data row26 col7\" >0.231</td>\n",
+       "      <td id=\"T_8473d_row26_col8\" class=\"data row26 col8\" >0.051</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row27\" class=\"row_heading level0 row27\" >11</th>\n",
+       "      <th id=\"T_8473d_level1_row27\" class=\"row_heading level1 row27\" >12</th>\n",
+       "      <td id=\"T_8473d_row27_col0\" class=\"data row27 col0\" >0.036</td>\n",
+       "      <td id=\"T_8473d_row27_col1\" class=\"data row27 col1\" >0.037</td>\n",
+       "      <td id=\"T_8473d_row27_col2\" class=\"data row27 col2\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row27_col3\" class=\"data row27 col3\" >0.013</td>\n",
+       "      <td id=\"T_8473d_row27_col4\" class=\"data row27 col4\" >0.015</td>\n",
+       "      <td id=\"T_8473d_row27_col5\" class=\"data row27 col5\" >0.018</td>\n",
+       "      <td id=\"T_8473d_row27_col6\" class=\"data row27 col6\" >0.036</td>\n",
+       "      <td id=\"T_8473d_row27_col7\" class=\"data row27 col7\" >0.037</td>\n",
+       "      <td id=\"T_8473d_row27_col8\" class=\"data row27 col8\" >0.047</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row28\" class=\"row_heading level0 row28\" >16</th>\n",
+       "      <th id=\"T_8473d_level1_row28\" class=\"row_heading level1 row28\" >17</th>\n",
+       "      <td id=\"T_8473d_row28_col0\" class=\"data row28 col0\" >0.047</td>\n",
+       "      <td id=\"T_8473d_row28_col1\" class=\"data row28 col1\" >0.047</td>\n",
+       "      <td id=\"T_8473d_row28_col2\" class=\"data row28 col2\" >0.047</td>\n",
+       "      <td id=\"T_8473d_row28_col3\" class=\"data row28 col3\" >0.012</td>\n",
+       "      <td id=\"T_8473d_row28_col4\" class=\"data row28 col4\" >0.012</td>\n",
+       "      <td id=\"T_8473d_row28_col5\" class=\"data row28 col5\" >0.011</td>\n",
+       "      <td id=\"T_8473d_row28_col6\" class=\"data row28 col6\" >0.047</td>\n",
+       "      <td id=\"T_8473d_row28_col7\" class=\"data row28 col7\" >0.047</td>\n",
+       "      <td id=\"T_8473d_row28_col8\" class=\"data row28 col8\" >0.047</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row29\" class=\"row_heading level0 row29\" >9</th>\n",
+       "      <th id=\"T_8473d_level1_row29\" class=\"row_heading level1 row29\" >6</th>\n",
+       "      <td id=\"T_8473d_row29_col0\" class=\"data row29 col0\" >0.126</td>\n",
+       "      <td id=\"T_8473d_row29_col1\" class=\"data row29 col1\" >0.126</td>\n",
+       "      <td id=\"T_8473d_row29_col2\" class=\"data row29 col2\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row29_col3\" class=\"data row29 col3\" >0.106</td>\n",
+       "      <td id=\"T_8473d_row29_col4\" class=\"data row29 col4\" >0.106</td>\n",
+       "      <td id=\"T_8473d_row29_col5\" class=\"data row29 col5\" >0.029</td>\n",
+       "      <td id=\"T_8473d_row29_col6\" class=\"data row29 col6\" >0.402</td>\n",
+       "      <td id=\"T_8473d_row29_col7\" class=\"data row29 col7\" >0.402</td>\n",
+       "      <td id=\"T_8473d_row29_col8\" class=\"data row29 col8\" >0.047</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row30\" class=\"row_heading level0 row30\" >16</th>\n",
+       "      <th id=\"T_8473d_level1_row30\" class=\"row_heading level1 row30\" >15</th>\n",
+       "      <td id=\"T_8473d_row30_col0\" class=\"data row30 col0\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row30_col1\" class=\"data row30 col1\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row30_col2\" class=\"data row30 col2\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row30_col3\" class=\"data row30 col3\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row30_col4\" class=\"data row30 col4\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row30_col5\" class=\"data row30 col5\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row30_col6\" class=\"data row30 col6\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row30_col7\" class=\"data row30 col7\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row30_col8\" class=\"data row30 col8\" >0.045</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row31\" class=\"row_heading level0 row31\" >17</th>\n",
+       "      <th id=\"T_8473d_level1_row31\" class=\"row_heading level1 row31\" >6</th>\n",
+       "      <td id=\"T_8473d_row31_col0\" class=\"data row31 col0\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row31_col1\" class=\"data row31 col1\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row31_col2\" class=\"data row31 col2\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row31_col3\" class=\"data row31 col3\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row31_col4\" class=\"data row31 col4\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row31_col5\" class=\"data row31 col5\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row31_col6\" class=\"data row31 col6\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row31_col7\" class=\"data row31 col7\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row31_col8\" class=\"data row31 col8\" >0.045</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row32\" class=\"row_heading level0 row32\" >7</th>\n",
+       "      <th id=\"T_8473d_level1_row32\" class=\"row_heading level1 row32\" >1</th>\n",
+       "      <td id=\"T_8473d_row32_col0\" class=\"data row32 col0\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row32_col1\" class=\"data row32 col1\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row32_col2\" class=\"data row32 col2\" >0.037</td>\n",
+       "      <td id=\"T_8473d_row32_col3\" class=\"data row32 col3\" >0.029</td>\n",
+       "      <td id=\"T_8473d_row32_col4\" class=\"data row32 col4\" >0.029</td>\n",
+       "      <td id=\"T_8473d_row32_col5\" class=\"data row32 col5\" >0.036</td>\n",
+       "      <td id=\"T_8473d_row32_col6\" class=\"data row32 col6\" >0.047</td>\n",
+       "      <td id=\"T_8473d_row32_col7\" class=\"data row32 col7\" >0.047</td>\n",
+       "      <td id=\"T_8473d_row32_col8\" class=\"data row32 col8\" >0.045</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row33\" class=\"row_heading level0 row33\" >11</th>\n",
+       "      <th id=\"T_8473d_level1_row33\" class=\"row_heading level1 row33\" >10</th>\n",
+       "      <td id=\"T_8473d_row33_col0\" class=\"data row33 col0\" >0.043</td>\n",
+       "      <td id=\"T_8473d_row33_col1\" class=\"data row33 col1\" >0.042</td>\n",
+       "      <td id=\"T_8473d_row33_col2\" class=\"data row33 col2\" >0.042</td>\n",
+       "      <td id=\"T_8473d_row33_col3\" class=\"data row33 col3\" >0.042</td>\n",
+       "      <td id=\"T_8473d_row33_col4\" class=\"data row33 col4\" >0.041</td>\n",
+       "      <td id=\"T_8473d_row33_col5\" class=\"data row33 col5\" >0.041</td>\n",
+       "      <td id=\"T_8473d_row33_col6\" class=\"data row33 col6\" >0.043</td>\n",
+       "      <td id=\"T_8473d_row33_col7\" class=\"data row33 col7\" >0.042</td>\n",
+       "      <td id=\"T_8473d_row33_col8\" class=\"data row33 col8\" >0.042</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row34\" class=\"row_heading level0 row34\" >14</th>\n",
+       "      <th id=\"T_8473d_level1_row34\" class=\"row_heading level1 row34\" >0</th>\n",
+       "      <td id=\"T_8473d_row34_col0\" class=\"data row34 col0\" >0.041</td>\n",
+       "      <td id=\"T_8473d_row34_col1\" class=\"data row34 col1\" >0.039</td>\n",
+       "      <td id=\"T_8473d_row34_col2\" class=\"data row34 col2\" >0.039</td>\n",
+       "      <td id=\"T_8473d_row34_col3\" class=\"data row34 col3\" >0.041</td>\n",
+       "      <td id=\"T_8473d_row34_col4\" class=\"data row34 col4\" >0.039</td>\n",
+       "      <td id=\"T_8473d_row34_col5\" class=\"data row34 col5\" >0.039</td>\n",
+       "      <td id=\"T_8473d_row34_col6\" class=\"data row34 col6\" >0.041</td>\n",
+       "      <td id=\"T_8473d_row34_col7\" class=\"data row34 col7\" >0.039</td>\n",
+       "      <td id=\"T_8473d_row34_col8\" class=\"data row34 col8\" >0.039</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row35\" class=\"row_heading level0 row35\" >8</th>\n",
+       "      <th id=\"T_8473d_level1_row35\" class=\"row_heading level1 row35\" >7</th>\n",
+       "      <td id=\"T_8473d_row35_col0\" class=\"data row35 col0\" >0.063</td>\n",
+       "      <td id=\"T_8473d_row35_col1\" class=\"data row35 col1\" >0.068</td>\n",
+       "      <td id=\"T_8473d_row35_col2\" class=\"data row35 col2\" >0.045</td>\n",
+       "      <td id=\"T_8473d_row35_col3\" class=\"data row35 col3\" >0.056</td>\n",
+       "      <td id=\"T_8473d_row35_col4\" class=\"data row35 col4\" >0.061</td>\n",
+       "      <td id=\"T_8473d_row35_col5\" class=\"data row35 col5\" >0.038</td>\n",
+       "      <td id=\"T_8473d_row35_col6\" class=\"data row35 col6\" >0.059</td>\n",
+       "      <td id=\"T_8473d_row35_col7\" class=\"data row35 col7\" >0.068</td>\n",
+       "      <td id=\"T_8473d_row35_col8\" class=\"data row35 col8\" >0.033</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row36\" class=\"row_heading level0 row36\" >2</th>\n",
+       "      <th id=\"T_8473d_level1_row36\" class=\"row_heading level1 row36\" >18</th>\n",
+       "      <td id=\"T_8473d_row36_col0\" class=\"data row36 col0\" >0.078</td>\n",
+       "      <td id=\"T_8473d_row36_col1\" class=\"data row36 col1\" >0.087</td>\n",
+       "      <td id=\"T_8473d_row36_col2\" class=\"data row36 col2\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row36_col3\" class=\"data row36 col3\" >0.071</td>\n",
+       "      <td id=\"T_8473d_row36_col4\" class=\"data row36 col4\" >0.074</td>\n",
+       "      <td id=\"T_8473d_row36_col5\" class=\"data row36 col5\" >0.018</td>\n",
+       "      <td id=\"T_8473d_row36_col6\" class=\"data row36 col6\" >0.100</td>\n",
+       "      <td id=\"T_8473d_row36_col7\" class=\"data row36 col7\" >0.109</td>\n",
+       "      <td id=\"T_8473d_row36_col8\" class=\"data row36 col8\" >0.032</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row37\" class=\"row_heading level0 row37\" >9</th>\n",
+       "      <th id=\"T_8473d_level1_row37\" class=\"row_heading level1 row37\" >1</th>\n",
+       "      <td id=\"T_8473d_row37_col0\" class=\"data row37 col0\" >0.145</td>\n",
+       "      <td id=\"T_8473d_row37_col1\" class=\"data row37 col1\" >0.145</td>\n",
+       "      <td id=\"T_8473d_row37_col2\" class=\"data row37 col2\" >0.026</td>\n",
+       "      <td id=\"T_8473d_row37_col3\" class=\"data row37 col3\" >0.137</td>\n",
+       "      <td id=\"T_8473d_row37_col4\" class=\"data row37 col4\" >0.137</td>\n",
+       "      <td id=\"T_8473d_row37_col5\" class=\"data row37 col5\" >0.026</td>\n",
+       "      <td id=\"T_8473d_row37_col6\" class=\"data row37 col6\" >0.326</td>\n",
+       "      <td id=\"T_8473d_row37_col7\" class=\"data row37 col7\" >0.326</td>\n",
+       "      <td id=\"T_8473d_row37_col8\" class=\"data row37 col8\" >0.026</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row38\" class=\"row_heading level0 row38\" >2</th>\n",
+       "      <th id=\"T_8473d_level1_row38\" class=\"row_heading level1 row38\" >7</th>\n",
+       "      <td id=\"T_8473d_row38_col0\" class=\"data row38 col0\" >0.184</td>\n",
+       "      <td id=\"T_8473d_row38_col1\" class=\"data row38 col1\" >0.171</td>\n",
+       "      <td id=\"T_8473d_row38_col2\" class=\"data row38 col2\" >0.018</td>\n",
+       "      <td id=\"T_8473d_row38_col3\" class=\"data row38 col3\" >0.172</td>\n",
+       "      <td id=\"T_8473d_row38_col4\" class=\"data row38 col4\" >0.159</td>\n",
+       "      <td id=\"T_8473d_row38_col5\" class=\"data row38 col5\" >0.016</td>\n",
+       "      <td id=\"T_8473d_row38_col6\" class=\"data row38 col6\" >0.447</td>\n",
+       "      <td id=\"T_8473d_row38_col7\" class=\"data row38 col7\" >0.414</td>\n",
+       "      <td id=\"T_8473d_row38_col8\" class=\"data row38 col8\" >0.021</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row39\" class=\"row_heading level0 row39\" >13</th>\n",
+       "      <th id=\"T_8473d_level1_row39\" class=\"row_heading level1 row39\" >12</th>\n",
+       "      <td id=\"T_8473d_row39_col0\" class=\"data row39 col0\" >0.020</td>\n",
+       "      <td id=\"T_8473d_row39_col1\" class=\"data row39 col1\" >0.021</td>\n",
+       "      <td id=\"T_8473d_row39_col2\" class=\"data row39 col2\" >0.016</td>\n",
+       "      <td id=\"T_8473d_row39_col3\" class=\"data row39 col3\" >0.011</td>\n",
+       "      <td id=\"T_8473d_row39_col4\" class=\"data row39 col4\" >0.012</td>\n",
+       "      <td id=\"T_8473d_row39_col5\" class=\"data row39 col5\" >0.011</td>\n",
+       "      <td id=\"T_8473d_row39_col6\" class=\"data row39 col6\" >0.021</td>\n",
+       "      <td id=\"T_8473d_row39_col7\" class=\"data row39 col7\" >0.024</td>\n",
+       "      <td id=\"T_8473d_row39_col8\" class=\"data row39 col8\" >0.018</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row40\" class=\"row_heading level0 row40\" >4</th>\n",
+       "      <th id=\"T_8473d_level1_row40\" class=\"row_heading level1 row40\" >8</th>\n",
+       "      <td id=\"T_8473d_row40_col0\" class=\"data row40 col0\" >0.028</td>\n",
+       "      <td id=\"T_8473d_row40_col1\" class=\"data row40 col1\" >0.037</td>\n",
+       "      <td id=\"T_8473d_row40_col2\" class=\"data row40 col2\" >0.013</td>\n",
+       "      <td id=\"T_8473d_row40_col3\" class=\"data row40 col3\" >0.027</td>\n",
+       "      <td id=\"T_8473d_row40_col4\" class=\"data row40 col4\" >0.035</td>\n",
+       "      <td id=\"T_8473d_row40_col5\" class=\"data row40 col5\" >0.012</td>\n",
+       "      <td id=\"T_8473d_row40_col6\" class=\"data row40 col6\" >0.030</td>\n",
+       "      <td id=\"T_8473d_row40_col7\" class=\"data row40 col7\" >0.041</td>\n",
+       "      <td id=\"T_8473d_row40_col8\" class=\"data row40 col8\" >0.017</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row41\" class=\"row_heading level0 row41\" rowspan=\"2\">0</th>\n",
+       "      <th id=\"T_8473d_level1_row41\" class=\"row_heading level1 row41\" >10</th>\n",
+       "      <td id=\"T_8473d_row41_col0\" class=\"data row41 col0\" >0.028</td>\n",
+       "      <td id=\"T_8473d_row41_col1\" class=\"data row41 col1\" >0.026</td>\n",
+       "      <td id=\"T_8473d_row41_col2\" class=\"data row41 col2\" >0.016</td>\n",
+       "      <td id=\"T_8473d_row41_col3\" class=\"data row41 col3\" >0.021</td>\n",
+       "      <td id=\"T_8473d_row41_col4\" class=\"data row41 col4\" >0.020</td>\n",
+       "      <td id=\"T_8473d_row41_col5\" class=\"data row41 col5\" >0.012</td>\n",
+       "      <td id=\"T_8473d_row41_col6\" class=\"data row41 col6\" >0.037</td>\n",
+       "      <td id=\"T_8473d_row41_col7\" class=\"data row41 col7\" >0.034</td>\n",
+       "      <td id=\"T_8473d_row41_col8\" class=\"data row41 col8\" >0.017</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level1_row42\" class=\"row_heading level1 row42\" >18</th>\n",
+       "      <td id=\"T_8473d_row42_col0\" class=\"data row42 col0\" >0.199</td>\n",
+       "      <td id=\"T_8473d_row42_col1\" class=\"data row42 col1\" >0.189</td>\n",
+       "      <td id=\"T_8473d_row42_col2\" class=\"data row42 col2\" >0.016</td>\n",
+       "      <td id=\"T_8473d_row42_col3\" class=\"data row42 col3\" >0.191</td>\n",
+       "      <td id=\"T_8473d_row42_col4\" class=\"data row42 col4\" >0.187</td>\n",
+       "      <td id=\"T_8473d_row42_col5\" class=\"data row42 col5\" >0.014</td>\n",
+       "      <td id=\"T_8473d_row42_col6\" class=\"data row42 col6\" >0.326</td>\n",
+       "      <td id=\"T_8473d_row42_col7\" class=\"data row42 col7\" >0.317</td>\n",
+       "      <td id=\"T_8473d_row42_col8\" class=\"data row42 col8\" >0.016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row43\" class=\"row_heading level0 row43\" >7</th>\n",
+       "      <th id=\"T_8473d_level1_row43\" class=\"row_heading level1 row43\" >2</th>\n",
+       "      <td id=\"T_8473d_row43_col0\" class=\"data row43 col0\" >0.037</td>\n",
+       "      <td id=\"T_8473d_row43_col1\" class=\"data row43 col1\" >0.042</td>\n",
+       "      <td id=\"T_8473d_row43_col2\" class=\"data row43 col2\" >0.013</td>\n",
+       "      <td id=\"T_8473d_row43_col3\" class=\"data row43 col3\" >0.035</td>\n",
+       "      <td id=\"T_8473d_row43_col4\" class=\"data row43 col4\" >0.040</td>\n",
+       "      <td id=\"T_8473d_row43_col5\" class=\"data row43 col5\" >0.012</td>\n",
+       "      <td id=\"T_8473d_row43_col6\" class=\"data row43 col6\" >0.051</td>\n",
+       "      <td id=\"T_8473d_row43_col7\" class=\"data row43 col7\" >0.063</td>\n",
+       "      <td id=\"T_8473d_row43_col8\" class=\"data row43 col8\" >0.014</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row44\" class=\"row_heading level0 row44\" >18</th>\n",
+       "      <th id=\"T_8473d_level1_row44\" class=\"row_heading level1 row44\" >2</th>\n",
+       "      <td id=\"T_8473d_row44_col0\" class=\"data row44 col0\" >0.204</td>\n",
+       "      <td id=\"T_8473d_row44_col1\" class=\"data row44 col1\" >0.205</td>\n",
+       "      <td id=\"T_8473d_row44_col2\" class=\"data row44 col2\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row44_col3\" class=\"data row44 col3\" >0.201</td>\n",
+       "      <td id=\"T_8473d_row44_col4\" class=\"data row44 col4\" >0.203</td>\n",
+       "      <td id=\"T_8473d_row44_col5\" class=\"data row44 col5\" >0.036</td>\n",
+       "      <td id=\"T_8473d_row44_col6\" class=\"data row44 col6\" >0.366</td>\n",
+       "      <td id=\"T_8473d_row44_col7\" class=\"data row44 col7\" >0.367</td>\n",
+       "      <td id=\"T_8473d_row44_col8\" class=\"data row44 col8\" >0.014</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row45\" class=\"row_heading level0 row45\" >12</th>\n",
+       "      <th id=\"T_8473d_level1_row45\" class=\"row_heading level1 row45\" >11</th>\n",
+       "      <td id=\"T_8473d_row45_col0\" class=\"data row45 col0\" >0.009</td>\n",
+       "      <td id=\"T_8473d_row45_col1\" class=\"data row45 col1\" >0.011</td>\n",
+       "      <td id=\"T_8473d_row45_col2\" class=\"data row45 col2\" >0.011</td>\n",
+       "      <td id=\"T_8473d_row45_col3\" class=\"data row45 col3\" >0.007</td>\n",
+       "      <td id=\"T_8473d_row45_col4\" class=\"data row45 col4\" >0.007</td>\n",
+       "      <td id=\"T_8473d_row45_col5\" class=\"data row45 col5\" >0.007</td>\n",
+       "      <td id=\"T_8473d_row45_col6\" class=\"data row45 col6\" >0.009</td>\n",
+       "      <td id=\"T_8473d_row45_col7\" class=\"data row45 col7\" >0.011</td>\n",
+       "      <td id=\"T_8473d_row45_col8\" class=\"data row45 col8\" >0.011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row46\" class=\"row_heading level0 row46\" >8</th>\n",
+       "      <th id=\"T_8473d_level1_row46\" class=\"row_heading level1 row46\" >4</th>\n",
+       "      <td id=\"T_8473d_row46_col0\" class=\"data row46 col0\" >0.022</td>\n",
+       "      <td id=\"T_8473d_row46_col1\" class=\"data row46 col1\" >0.013</td>\n",
+       "      <td id=\"T_8473d_row46_col2\" class=\"data row46 col2\" >0.011</td>\n",
+       "      <td id=\"T_8473d_row46_col3\" class=\"data row46 col3\" >0.011</td>\n",
+       "      <td id=\"T_8473d_row46_col4\" class=\"data row46 col4\" >0.010</td>\n",
+       "      <td id=\"T_8473d_row46_col5\" class=\"data row46 col5\" >0.009</td>\n",
+       "      <td id=\"T_8473d_row46_col6\" class=\"data row46 col6\" >0.022</td>\n",
+       "      <td id=\"T_8473d_row46_col7\" class=\"data row46 col7\" >0.013</td>\n",
+       "      <td id=\"T_8473d_row46_col8\" class=\"data row46 col8\" >0.011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row47\" class=\"row_heading level0 row47\" >5</th>\n",
+       "      <th id=\"T_8473d_level1_row47\" class=\"row_heading level1 row47\" >9</th>\n",
+       "      <td id=\"T_8473d_row47_col0\" class=\"data row47 col0\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row47_col1\" class=\"data row47 col1\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row47_col2\" class=\"data row47 col2\" >0.008</td>\n",
+       "      <td id=\"T_8473d_row47_col3\" class=\"data row47 col3\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row47_col4\" class=\"data row47 col4\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row47_col5\" class=\"data row47 col5\" >0.008</td>\n",
+       "      <td id=\"T_8473d_row47_col6\" class=\"data row47 col6\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row47_col7\" class=\"data row47 col7\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row47_col8\" class=\"data row47 col8\" >0.008</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row48\" class=\"row_heading level0 row48\" >13</th>\n",
+       "      <th id=\"T_8473d_level1_row48\" class=\"row_heading level1 row48\" >14</th>\n",
+       "      <td id=\"T_8473d_row48_col0\" class=\"data row48 col0\" >0.007</td>\n",
+       "      <td id=\"T_8473d_row48_col1\" class=\"data row48 col1\" >0.008</td>\n",
+       "      <td id=\"T_8473d_row48_col2\" class=\"data row48 col2\" >0.008</td>\n",
+       "      <td id=\"T_8473d_row48_col3\" class=\"data row48 col3\" >0.004</td>\n",
+       "      <td id=\"T_8473d_row48_col4\" class=\"data row48 col4\" >0.005</td>\n",
+       "      <td id=\"T_8473d_row48_col5\" class=\"data row48 col5\" >0.005</td>\n",
+       "      <td id=\"T_8473d_row48_col6\" class=\"data row48 col6\" >0.007</td>\n",
+       "      <td id=\"T_8473d_row48_col7\" class=\"data row48 col7\" >0.008</td>\n",
+       "      <td id=\"T_8473d_row48_col8\" class=\"data row48 col8\" >0.008</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row49\" class=\"row_heading level0 row49\" >18</th>\n",
+       "      <th id=\"T_8473d_level1_row49\" class=\"row_heading level1 row49\" >0</th>\n",
+       "      <td id=\"T_8473d_row49_col0\" class=\"data row49 col0\" >0.072</td>\n",
+       "      <td id=\"T_8473d_row49_col1\" class=\"data row49 col1\" >0.071</td>\n",
+       "      <td id=\"T_8473d_row49_col2\" class=\"data row49 col2\" >0.016</td>\n",
+       "      <td id=\"T_8473d_row49_col3\" class=\"data row49 col3\" >0.071</td>\n",
+       "      <td id=\"T_8473d_row49_col4\" class=\"data row49 col4\" >0.070</td>\n",
+       "      <td id=\"T_8473d_row49_col5\" class=\"data row49 col5\" >0.020</td>\n",
+       "      <td id=\"T_8473d_row49_col6\" class=\"data row49 col6\" >0.095</td>\n",
+       "      <td id=\"T_8473d_row49_col7\" class=\"data row49 col7\" >0.094</td>\n",
+       "      <td id=\"T_8473d_row49_col8\" class=\"data row49 col8\" >0.008</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row50\" class=\"row_heading level0 row50\" >9</th>\n",
+       "      <th id=\"T_8473d_level1_row50\" class=\"row_heading level1 row50\" >5</th>\n",
+       "      <td id=\"T_8473d_row50_col0\" class=\"data row50 col0\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row50_col1\" class=\"data row50 col1\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row50_col2\" class=\"data row50 col2\" >0.008</td>\n",
+       "      <td id=\"T_8473d_row50_col3\" class=\"data row50 col3\" >0.011</td>\n",
+       "      <td id=\"T_8473d_row50_col4\" class=\"data row50 col4\" >0.011</td>\n",
+       "      <td id=\"T_8473d_row50_col5\" class=\"data row50 col5\" >0.005</td>\n",
+       "      <td id=\"T_8473d_row50_col6\" class=\"data row50 col6\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row50_col7\" class=\"data row50 col7\" >0.032</td>\n",
+       "      <td id=\"T_8473d_row50_col8\" class=\"data row50 col8\" >0.008</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row51\" class=\"row_heading level0 row51\" >17</th>\n",
+       "      <th id=\"T_8473d_level1_row51\" class=\"row_heading level1 row51\" >16</th>\n",
+       "      <td id=\"T_8473d_row51_col0\" class=\"data row51 col0\" >0.003</td>\n",
+       "      <td id=\"T_8473d_row51_col1\" class=\"data row51 col1\" >0.003</td>\n",
+       "      <td id=\"T_8473d_row51_col2\" class=\"data row51 col2\" >0.003</td>\n",
+       "      <td id=\"T_8473d_row51_col3\" class=\"data row51 col3\" >0.003</td>\n",
+       "      <td id=\"T_8473d_row51_col4\" class=\"data row51 col4\" >0.003</td>\n",
+       "      <td id=\"T_8473d_row51_col5\" class=\"data row51 col5\" >0.003</td>\n",
+       "      <td id=\"T_8473d_row51_col6\" class=\"data row51 col6\" >0.003</td>\n",
+       "      <td id=\"T_8473d_row51_col7\" class=\"data row51 col7\" >0.003</td>\n",
+       "      <td id=\"T_8473d_row51_col8\" class=\"data row51 col8\" >0.003</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th id=\"T_8473d_level0_row52\" class=\"row_heading level0 row52\" >0</th>\n",
+       "      <th id=\"T_8473d_level1_row52\" class=\"row_heading level1 row52\" >13</th>\n",
+       "      <td id=\"T_8473d_row52_col0\" class=\"data row52 col0\" >0.050</td>\n",
+       "      <td id=\"T_8473d_row52_col1\" class=\"data row52 col1\" >0.000</td>\n",
+       "      <td id=\"T_8473d_row52_col2\" class=\"data row52 col2\" >0.000</td>\n",
+       "      <td id=\"T_8473d_row52_col3\" class=\"data row52 col3\" >0.023</td>\n",
+       "      <td id=\"T_8473d_row52_col4\" class=\"data row52 col4\" >0.000</td>\n",
+       "      <td id=\"T_8473d_row52_col5\" class=\"data row52 col5\" >0.000</td>\n",
+       "      <td id=\"T_8473d_row52_col6\" class=\"data row52 col6\" >0.063</td>\n",
+       "      <td id=\"T_8473d_row52_col7\" class=\"data row52 col7\" >0.000</td>\n",
+       "      <td id=\"T_8473d_row52_col8\" class=\"data row52 col8\" >0.000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x76f82bc1a850>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "display(pd.DataFrame({\n",
     "    (\"\", \"C_B_e\"): cb[\"Edge\"], (\"\", \"C_B_e_paths\"): cb_paths[\"Edge\"],\n",
@@ -534,14 +2282,45 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T09:50:34.670455Z",
      "start_time": "2024-04-18T09:50:33.125241Z"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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KGL4w4zBcudsZw1peLBZDNAaEo4DFCBiNFJKEZAt0ARNCSJbwTt0qJf4EEX/Cfza/iQ3tO4cs/ILhGLwhwBcCQhEgrC2OEJIlUAASQkiWUOdrQSobXZ2vdVDfD0dj8AZj8ASBYESEYNdntP0Rkl3QBUwIIVnCbFd13O7XhbiCZ+RXDur7gRB6fV9HrICRaAxGcQUbtEFEIeMLCZmY0AJICCFZwuKSWbh4znHdxN9Ve5yD6rySQX3faQWspr4/l3jAYBjwhwBvEMpSKBZDf0hzGYsFMRqLKRcyISSzoQWQEEKyiK/NOwHHTtpbuYOn5pejwlE06O+KNc9qBsymGAJhsfh1feawaJ+LuBN9F+0xSKIIIl3zGw2xhKWwy2pIRzIhmQIFICGEZBki/GQYDCLoxL1rios0EXki1ETwhSOaEEy258nnouN6uo8GIwwNhhhMBm1dMtCFTMj4QQFICCE5TiiqJX2IsLMYYzCbNGud2WSAyRhTAnCgWL9+haFowCgQjQIREYXh+HcgQjCmCUIlPhlTSMhYQQFICCE5jAg3pyWmCbOIJgRlMBk0IWg2jsx1q4ShuIQlttDUJQpFEMo6ZawLQuiC0NDdIkkIST8UgIQQkuOIyDIbNLEn4kzctuIWFvdvQG4UYhXU3bZpEGRqfSIukSQI42JQhmCS21iEqKxXt0oSQtIDBSAhhJBu4sxighoko1cr/wL4w10WOhGDMqTLOpcsQJM7kCQEYdwqKYkluhCldZCQkUEBSAghJCVicbPF7xLRqGYZlEG3DOpuYk2Qpc86J4JQdwMLulVSF4NiHZTV6ZZJikFChg4FICGETHD0unujGS8nfYCtRsCq6gHGBVncTaw+j1vnRsNVm2yV1OMHdTe1DLI2EYMmEaOMGyRkUFAAEkLIBKe2LagsdJOL7WOyPhF4qmB0XJDplsGxcNUm4gfj69ZLzUgCi2QzYxRiFgnJRigACSFkAiMiqNUbQnGeZVzW35d1TnfVjmZmb7Kr2GpKEoNJmcUiBmXb6CYmpDsUgIQQMoHxBCJKdLkc2s95IBTBliY/ZpQ6YNWzKsaIntY5PbM32kdmbzoFYbIYtCXFLIqLWMayBoupq8bhYAlFw2gPemExmlBgcdKiSLIGCkBCCJnAtPsjqmCzw6KJvR0tAdWXt8kTQpVbpND40G9mb6y7hdCYJAjTFcOnxyyK6JP1hvqocdjXuja01+CxLW/jhR1LEYxq5sRqZwnOnn4ITp6yP/IsQ3O3y/43dYbQ4glhVrlTbR8h4wkFICGETFBEVLT7wnDZzUrItPnC8CpTG9T0Spc1YyxWqTJ7kwWhiuFLFoTdeggPXRRKGztJjdFiAaWjSVK8Yjx5xaD6Hvf+7lNb38Mtyx9RlsJIrKshcq23CbetehKPbH4Ltx74TSUIB0MgHMW2Rh86/NoO+kNROG0pVjwA+jGTJByxqqpx3O0+0LSuNn+aBVQ7tlrbP9XBRR1v7X1iHv07bNuXlVAAEkLIBEWERCgSg9thQiQaw84WKc6iIVZA+dyhsjUyj1SCUJKZE91BYkAsqUOIAZqI0YSKVgZGFyqpEEufsvwZAJtZLIyGXvGKqXhz13L8dvl/1OtIj3n0d/X+Vnz3vTvw98Ou7tcSqFv9djT71bbo+FTfPSAU1s6fGsJRtb4uESfHQRNzydMGQ2+RJ9ui92fuEpF9HIKBlyvCUIlF7b3FZFDhBlazJAfJ2AiL2QBz/JiTzIQCkBBCJihi5ZObcJ7NpMSfCIZkmj0hTMpQAdhfL2ERaMkWL10Y6uNQuLssSxaG+mtd3Mj3fSEtGURqGuqCJJUwkfXdufppFS/YnzYSq+AuXzOe2/EhzplxWMp5AqEo1td5lBDvydYmf7f34sIXESUiVfVglrFujYuLOM0iOvC0oVhLddHdJQzjx1sJz+5isc/pKs4yijZvGMFItJuolM3QBKEmELuEYpdYpCt8/KAAJISQCRz/J8kf4vZt8XZTRYpWbxhVhSKQJqYVRrcS9rxZdRcuXUNyT+GeKNdvUMsWFvGRis+aN2K7p2HQ2yeu4LOnH5pScLV4QynFn+BymFR8piUuisbLSpYsurU0mZGhudjFmhlDMBxVgjAYf+0LRtEe0SyeyYjo7bIcxoWiCMS4WBzP45PtUAASQsgERKx94uItybeo1yKUetxblSjyBiLIt2fXT3134dJFshtZL1DdE/G+Wvs4HKtatiqxLJatgZA5dnqb4An7kW9x9Pq80m1TpXkk6UPcwHKuksnLsnMiaC52zc3eV4yjai8oolCJw2iSWIypGMlgONTN1S0WTbvFBIfVqA0WE+xWEYZjm+GejWTfFUgIITmAiiMD4LSaYLcYsXBSvioBs67OhwqXVVlTJJYuU2MAR1MYpgpuEyEhwqS/yjihaASGAR3Avb/TF2LBqnDb1CDnSxeDphy2aKn2ghYZ+j4R8kCjRGE4qoSzWA+9wQiaO0OJMyNuck0UmlQGvD0+HoxL2Rv24+1dK5V436tkNqYXVCAXoQAkhJAJiCcY1WreJbkz/SHt9liUZ85tC0mSfutK+gDa/CE0eYJo8YUwvciJ8oLuZXIqHEXdsn4Hwmq0oCCF9S8VSqhYTaguGptuLRMZcQvrx8vdw8IrsZU+JQojatzmDaE+7mqX7+0xJb/fkIeljevwo6V/hzfclTB12tQDcdUeZ8NoyK3/GQpAQiY6/lag/hOgY4dEaQPOMqB8LyC/ery3jIwi4toV619yfJRYSTQXXG7dyHoiLkRxJTZ6g2j2BhOiT6bL0ZKyOdWu3kLs8Ko98LvljyAQDQ24DpPBiBOnLIHZ2N3CKiKlsTOs9Sc2SWFsLalDzgu7kYwMudbF0idDUVLnGz0cQop/9yf+xPIn4s8nwaBJPLXtPexWNA0nTdkPuQQFICETkZAPWPsQ8OmfgPpPU89TMAVY9E1gj68BzvKx3kIyiojIELFXVmDtNt0T1ERhriGuwrrOAHa1+9W4NUnsuR0WlDgtmFmShxKnFUVOS58C2Wm247RpB6rkDq2KYP/n4KxpB6f8LN9mUjFtUotQLFb6kpJFoXhA9dcTNUlnrBFXsIg9iQEUUa0jlj/JhB8IcfsmW/50xO3/zPYPKAAJIRnOtteA5y8COrZLMa6+55PP3/kx8P6NwJG3AntcqtVlIBMeZe2IdQ+0l+B6fzCKwsLsf66XsiP1Ivg6NNHX7NViw/KsJlQU2DC7NC72HBaYh2gN/cb8k7G2dTtWtGxBl3TrQo8Q/P6eX8BMV1Xvzw3ivjRAdwzrpWxCcUGoZclG4UvyNIuW0UrAdBWtVuNEmZf09U+eyEi2uxzHzkBUufUl9nWwcX+CxPylIoYYOoI+5BrZ/0tBSLYgQUwf3gy8/aMu4TdQvJJ8HvYCL/0PsOV54KR/Aebxaw9G0oPe7cOZFEgv1hFdBGUb4WgUDZ3BhOAT1678O8jNv7LAjrll+ah02ZHfwyU+HGwmC35/wGW4e82zeGrbu/BHJGnDqAk5xDA1vwKXzT8Zh1TuPsSC15KF0jW9qyuJJgrFfallL4uVq/dytDZ5mjgUwaMLRCUc4zUAsx3Zd71bjIzlQaDDH1UCudBpGrD3tSR8pMJoMGK/8nnINSgACZkofPgrTfwJQwhUT7DhCeDpc4HTHgN6xC2RiYW4f3taPmSaVjJj4sf/iZuv0RNEXYcftR0BNHQGlBXNZhbBZ8N+JUVqrLfA64uPt7SlFFOCJM8smupK/ZnJgit2Ox1fm3eC6gxS72tRsX67F03HHkUz0mKN6+pKkrogdVdXFGnr1tXaTURjJKxZgLsvT+ujrFkQNVGoC0aVHa1m0iyYhsR4fESj2r/4M60akva5a7omiHVhLGPZ91SoGpBRoHtARG8k21cSPiTmz6B6y0jMoBGF1jycN/MI5BoUgIRMBHa83SX+houIxo1PAZ/+Edjne+naMjJOCSAFDnOvaZI1ORFdhSJsmj2ahU8XfGIVE3EkLt19JhcqwVfosAxp//or51ecn2SO6wOn2YYTJu+L8e2Kknp/uwkkEYVJQkliImXaYIrZdBeE2p+e03Sx2DVP17RUwi2VuFOdRAY4Jz1Jdo2Ldc8UjSHQo7i29HIudJhVLOVgkGxfSfh4ZvsHyu0rlj8Rf6X25Hzj3IACkJBMJxIEnvuK5vaN9V1zbNC8+QNg1ulA4cx0bB0ZY8TtJQkGTmuXpU9usFIWpjjPPKFEX31HAFtavNjW4oM/HFWB/eX5NuxZ7VKu3WKnZUSuzUlFVmxv7p7xKbgdZkwpHlz5lkxFxJeqANRP/Jveqi2lhS0+TehTwMWfG7X30V7CTm1HT7GYJBRVz2b12tjnPN0EZlz06qe8p9gX93gg3PUbWGA3qv+DoTwUiMVPsn1PyrGM31RMnF8LQnKV9Y8B7ZvTtzwRkWIFlMQQMmHj/5Jj/aTdlliABpMJOZ6IuKjvDMZFn1fVcZP9kAzdqYUOlOZZ09IbVmIGtzb6VdHlnoihaE7FxBZ/g0X1Bk5cEoZROZ9jaXHWM3+HavUjqaEAJCTT+ez2uPVvGHF/fQnA5X8FDv0VYO5dC62904/b//02OrwB3PTtk9OzTpI2xNWrav0lBbxL/J+QiSVgRCQ0eILY2uzFlhYffKEInBYTphc7VTFmEX3pEhH+YARbm/xo82l94KSfbGGeGfXtXUJwfnUejGKaIiNmrMMNxB1cWmBWIn4ihjpkGhSAhGQyUrOq5r30iT+dUKdWP7D6wMSkTm8Ad/znHdxy32to9/hR4LRRAGYgIvZ6Cj2ZJgkSKtM0Q0SfFF8WS5+IPj1pZVqRJvrK8tMn+oTmziB2tPgTnVCkDd7UEjuK87S0gJbONkgr3uoiG/JsvO1NZJLr/5GRwf8EQjKZxuVArI+u9iPCANR9rASg1x/EXY+8i9/c+6qy/knckDBQIVwydrR6tcLGYvQTF3CFy9TN/eYJRJFnG1+rlmyP1OPboix9XlWU2m6Oi75iB8rybWktVRKNRrGjOYCGjqBKfhAK7CZMK7XDae1+a5tfnY8WT1gJQEKIBgUgIZmMp3Z0lms0A5016qY95fifw+vvHSvl8QWx4MybVSFdGUxJ48ICB4pdTpQU5qHE7USxOy/ptROl7jw1znfa6KpJAztbtDIoOnXtIeXWLHSaUVVoU8HxZQUDZ7WmG7l+pMWaiL6tLT50BMLKEjmtyKGEn2Twprs+nS8YVvF97X7N7S0GoQqXBZOK7TD34drV+8oSQrqgACQkkxlKzYShL1yJs/85+yD89fH3VcxfMiajEeccswiRaBThiDZEIlGEwhG0dvjR0NKJNVvq0NTmRXObF4Fgb0ul1WLSxGFcGJa4kwWj9r7n9MICO2O0euBymNHq7X58Y3Hx4wnE4//GMAFEEk42N3uwpr5TWf2sJiOmFjmw/9QiVLrSL/qExo4gdrb4E2VAbBYDJhXaUdqjHR4hqdAznhk72AUFICGZzGj18JVEEGeFennzlafg55edgH88sxS//OtLqGloV9MtZhNuuPykwfem9YfQ2OpBc5sMXu11u4hDjxKJTeozL7bVtqApPk3iDnsiVsZZU0oxb3o55k0rx7zpZZgr42nlcOX3TlrJBYrzLL0EoMRCVbhtqG0NqKLGYnkbbToDYaxr6MT6Ro+yOk5y2XHUbDeqXSLa0y/6JJt3R7MfjR2aC1wXw9NK7LTokSEheVLSRi7fxhhCHQpAQjKZsj3TmwGsI8ur2Cfx1mY142tnHoCvnLoE/3r2Y9x0z0vK4jdY5Kk6z2FVw7SqokF/T6yGmkjUBKIIw7qmDqzf1oh1W+vx4POfYEdda2L+qjKXJgqnlWHejAo1FnE4qdyd1U/2UutMMn/lBqYzuUgsbUC7P6wE4mgh4r6uM6CsfdtbfKr0xuySPMwrz4fLPjrr9QbCKpu3I+7mlW4WlS6rts/M4CXDQFruMX+kO4aYbhfth/b2drjdbrS1tcHlSt06hxAySvxjCVD/SVpFYNhShKWnrkGh04Fqt73XjTwcjiiLXiZY3MRKuH5bA9ZubcDazXVqLOJQpgXjjUEl1nCuiEJlMYwP08oxa0oJrJbseM6taw+ivl0raux2mDC1xIHOQASbG3yYVe5IewkYeQDY1OxVwq/VF4Lbblaib1ZJHiyiyNKMJHXsaguiviOo6hoK0tZucrEtkc1LyHAQmdMRiMFuNqgMcQll2djgR0m+RQ3ZxFD0Wnb8MhKShdQ3d+CPD7yKitDZuMKwNH0LNpiBBV9CBCasqG3Hspp2FNjMSgjKIHXZzGYTXPmZETQv4m6v+ZPV0FOkbq1twdqt9VizuV6JQnn9/Lur0dLuU/NIwsqM6mLMn16OuXFRuPvsKuw5p0rt40SiyCn17IKqnG91oSbM231hZZGTEivpQhI51tZ3YkOjB8FIFJPdduw7uRBVrvQn9Ijok4QWyeT1S52WeLli6dQxrcQBe1K3E0KGi95DWI+SaOjUQgokrCLbBOBQoAAkJMNoaO7ArQ+8gjsfelMJmN9891SgoQLwNaTJChiDea9v4uDSEhVjVdcRQE2bXxXqlRu/FM+tctkxye1QAf2jYe1JByLgJFZQhpMOWdi98HCLRxOEW+qxZosmDh99eZkSjLqoPGCPaTh48QwcstdM7LtwCuy2zL0RhMNheDs7YZMMbKdNiT7ZTxGALrt5xMJMliV9eFfXd2BHq19dA7NL85XFTx4O0i366uOiTzqB6ORZjSqmUdrZ0c1L0on0ldZa0xkQCEXR6tU8BxJSIe9taXyAmkjQBUxIBgo/+aG6/EtH4IovH4mSwnxg83PAY4NLyOgfA3DAT4CDr++zjpuIwZ1tPrT5wypmRuq3Keugy67adk3kWDupebhsXQ3e+Wwz3vl0E977fAvaOv0qW3nfhVPjgnAGDthj+ri6v+VcvP7663jwwQfx7rvvYs2aNYhEtJuW3W7H4sWLccrpZ+G0C76J6aV2FNj7F2lSiHltfQd2r3J1E/TSV3hTk7h5O9T5LnRYML88HzOKnWkV/iL6GjpCyr3ri7ey02MbK1xWZYWh6COjRWcgquJIxQW8rTnQ7RosdJpQ6bblpAuYApCQccbjC+AP972MW+9/RYmrb51/OK684ChN+CXz+tXAx78b/ooMJqD6IOALLwOmgWOqPIEwatpFDPrR0KnVoXNYTKqLg4jCsjxrWqxP44nEAq3YWIu3P92sROG7n21CXXOnEuCL5lTjoLiFUIRhWVGP8zFKPPbYY7j22muxYcMGmM1mZf1LxRHHnoRrfvYr/OqHV+D3v/8d9tmnK6knGSns/dLaBpXIsdckN/aocsEfimBlXYfK6JXg+CmFDiX8pG5fus6niL7GTqlXGEz0L9ZFX5lLriGKPjL6RKMxdAZjcFgM8AUjqGnV4mh15HKfU+4YlSz28YACkJAJgNwg//X0h/jpbf9VGbBi8fvfi45BaZLQENfF9havqvk2s9gBvPZd4NM/xSOlhlIj0ABMPhQ482nAWjDkbRVLUX1nAA2dQSUGW7whtXap/6YJQitK82woclpGpQbcWFreNmxvVGLw7U83qUF3G0tiySGLZygxePBeMzG1cvDZzoOhpaUF3/zmN/Hwww8rETaI/DxlNdPnve666/Dzn/9cicZklte249OdbYnSMZLEsbHJo+1TeT7mleUjP01uXrmmmzpDKmElWfRJjGK5iL4Cij4ytgQjMdUiUPKINjX4kaq4QaXbqoqqZwMUgIRkOG8tXY9rf/8YPl29HWcftzduvPI0TJ9Uqqw14oatbfejps2HXZ0BVQvaZjLg/L2naF9e+x/gpW8AAbmpRwdO+BAO+jmw5BrAlJ44NxGE0uu10aMJQnktFUpEYJTkaYKwLE/L3pzovTu317UmrINiKVy9uU5Nn1JZiEMWa9ZBsRJKFvJwrWf19fU44ogjsG7duoSrd6jIuk8//XT8+9//hsWinWc5N8+tqe82nzh2d6tyYUFFPuxpSIQJhcW9G0SLJwRPD9EnRZqlSwfdu2S8kOQiSQJxWgzY3hJAKBxTD9bJSAvBSVnSJpACkJAMZeO2Bvzw/57AU68uw767T8NvrjobBy6eqT6TuLvXNzaqwOSe9r19Jovrzt01wdcELL8H+PQ2oHNHl4tXL/IsWPKBPS4FFn8LKJoz6p0hWrxBNMQFoQhD2Q/RfsXOLkFYkm9VVsOJjBS4fneZ5jIWC6HEFIoruawoDwctmoFj9p+LEw9ZqGoTDgafz4f9998fq1ev7tPdOxQR+KUvfQkPPPAAQtEYnlxR2y3RQpBzcvae1cqdPxwkcaixPYRmT0i51JJKE8JuMaA034ZKN0UfyQykT7Y8l0nogY7UmDQZxPJnU2JQamyaJviDqg4FICEZRku7F7/6y/O446E3UFHqwg1XnoZzj9+nm2VEhNOzq+t6OXbld+m8xZNhTdXpQbKCWzcBdUuBjh3ae0cpULE3ULJb2ix+Q0UsmW2+UJcg7AzCH47GS3xYusUR2ocpRDKFDo8fHyzfqgThm59swgcrtipBuPf8yTj50IU46dCFWDS3uk/r4FVXXYVbb71VuU/TxUMPPYSCPQ5Ho7d3j2dh98oC7D25cNCCT9y6LZ1i4Yt0c6HJjTPfZkJJgQWFDmbvksys/6d1yjEkpq2v82VlDUCBApCQDCEUiuCeR9/GTXc9C38ghO9fcpxK8HDYUydhrG/oxDtbmhPv5SdrdmkeDp5RgomM/OhKGzFdEEosoYgJQcqMiCAsclrhsplVYom0NZuoySXS1eTF99fimTdX4sX31qLd41fWQBGDMhy296xEyZmPPvpIWf8GE+83WOS4SRbgA2+tgD+iCTRxw8t0k0HGwIziPNW7NxUiRJs9YSX6pM9wsrtMliPLK863sFwLmTAJIOL+ldJJQjAcVbGAk4tsyLdP7IfPVLAQNCEZwCvvr8ZVv3kE67bU46LTD8BPv3UKqsr6dguKxUwyM8Xip99zY/FA/YmOiI8Cu0UNM0vyEqVJlBiMi8LNTVqyi25Zku4kIgilxImIQpfNgjybKeOTTIrdTpx3/F5qCIbCyjL49Jur8MxbK3H3o++pdnlH7z8Xpxy6EI/8/XcwmUwjdv0mo+oDtrdj7QsPKeviQIjga/WF0dQRQocIviSfrrjFXA4TSvI0awlj+chEQr+Uk7sH6gXH7Tla+y8ZloEhJM20dnjxg989jvuefA+H7TsHv736bOw5r3sXi55sbvIoy5/U2Tt8VokqyLy2wYMihwWn716VE+dI4gg9wbDqbasNIki017oVSsSxZKzqglAXh2JFzNSC1cnCbNWmOiUEn3lrFT5auQ3RSBiBz+4Gwt60r2/atGnYtGlTN9EmYk+ycyWLu8MXUW757oJPYqVMqrewuHXN7LtLJjAi9qRbZIE9KdSmPYg2XwSzK1JbwCc6dAETMk4888ZyXHHTQ6q236++dxYuPvPAfl2ZIno+2t6i+q1K8d2DphcrISMxdB9vb8XkQofqypHLiHCSRIaOQCghDjtkHAh1S3BwWkxJ1kKxHFrUa/s4upO3tXhhM5tQnm/ttQ233/13XPH9nyPavm3U1r9y7Ubkl1Sh0x+JZ0N2dzWLS1csIUV5EpdpgTlVnCkhExTJSpf/uuQEkO3NfjWeUpydv6t0ARMyxjS2dOLq3z6Ch59bihMO2Q1/+vF5mFzRf504sW69vqERLb4gDphWpOqx6SJB3JxLpqa3ztxERY6JWKVkqCjoXY5GCUJlKdQEorS229Dg6eZOFguhlDyRRBqJL5SWavpryUpW4/j7dLqYP9rWqkSXlMaRxIvkQsvrVi2DyVc7UCGfYfPs++vQaS5BZ1uwW/yelLwozLOo1mt06ZJsfnCUvKqeOWbyIJQtNf9GCo8CISPk0Zc+wfdu/jfCkSj+duNXcN5JSwa0OG1v9eKtTU1KdJy0oBKlUqWUDBmxloq4kiGZaDzpRLMUauNAWKyIYTR5ogiEI6pAbMplGg3qvChBmCwOU4hG/bO+XKV6bkezJ4g3Njah2GlR7dgqC2xYuXIlQqHUWbrp4P47/4CTTz0VZ5x0rLKAUOyRXCIWH5LLu0i4g2Sxi1eAUAASMmx2Nbbje7/6N5545TOcftQi3HrdF1FZ2n/vRREmn+xoxYpdHar91iEzSpSIIOlFrHgqicRuwaR+zoVYECUrUMRhIOl1MBIfh6PwhiJo8YXUa5new4saX59mqZQzaYi/lttOJK4A9a9Ike83NzapG5DHo3XjGC0e/ec9mFTixAVnnTiq6yEkE9HLFcWTf7slgNiYAKKgBZCQYbgWHnr2I+XyNRmN+Odvvoazjt1rwO95g2FlBZKWavtOLsRulQUTttRJtohEic+ToWAI515cuskiUQYRkqL1RFQqy0MsnvRR15FSMLolNtE++jFIVqu1z9hTIVuK3xLSE/3/ztBDAMolL2EhhAKQkCFR39yBb17/Tzz75grl6pUM3+TevX2xtdmL97Y2K9FxwvxyVBRkZwBytiOCXW4eg804luQeEYX67WZGiRMLKwuQZzXjwTlz8NZbb6W1BEwy4l6eNWuWqoUmFswGj1ZyRx5AJAtYCnGfvlvlqKybkPFGHnLk3zT5IVuy3iXpiQ/eGrQAEjJI3vl0Iy689m+qy8N//vA/OOWIPQf8ji8UwQdbW7ClxatcvpLlO9wWXGTiIRY2sRhOL3Yqi2+eresnd99998Xdd989qusvXXQI/vpRV5ax3Av1uMQCG69Dkl1IVQBx/WrhF1pohrL6GQ0Qr28gFFVJUESDApCQARBX3q0PvIKf/PEpHLDnDNz/q6+iurxwwO9sbvbig20t6v1hM0tUmRc+eeYWh87UYjyldmFPjjzyyFFdd1FRERZOqUTDltZEDGJyw5GKfNuorp+QMUeFYXS9ldeq4ZD0JbdI1YAY4/+SoAAkZIAevv/zs3/g6dc/x1UXH4ufX34KzGbTgLF+721twfZWH6YXObH/tCJa/XKUntnJycyePVuJwDfffBORiNYWL11Id5FvfvObmFPhRkmBA8+uqVOWkORwxHe3tmBDk1c9mMwqcSq3NCETGavZgFCwd9Ct9AEWb4zgYAJIAv7HE9IHn6zahi9f81e0dfjwyK3fwMmH7zGg1W9Dowcfbm9RPVePnFWKacVOHl/SJ9KqzVVUik8//gjbtm5Jy5FavM9+KCoqxv984xvqfbHTijN2q8Jza+rR5g8pEZhvNWHvSYXY2urF0u0tylJd5bJhdkmeEoSSGEPIRAy5MBpi3ayAEvZgNQEtnmg8fpcJIDoUgISkEHJ/+c/b+P4tj2L3OdV4/u4rMa26pN/jJDXn3t3SjJp2P2aV5GG/qYW8iZJ+keSMg488HksOOw6XfPnctAnAo449AVdcdZ0KdpfsZElYERe0JHy8sK4euzoCmFbkVD2mZZAsZolR3djowdubm1VLQolXlet4WqED5gxvsUdIMlaTAf5wlwJ0mA0q9MYbiKhe4gzD6YK9gElO89GKLfjF7c/gL7+4UNXw6/QG8O0bH1QdPb7xxcPw6/89EzarpV+xuLahE0u3t6riwJLkIe3bCOkPVZTaH9FKxvg7sPvC+Whubh6xK1hcv/vvvz+ef/l1tPoiKiDe7TDB7TSrDHTJjPy8tl25fKVGYqrwhU3Nmhis9wRVUWwRi7NL8zDJZVfB9IRkMvKb3BHQBKCUWJUi6FLDc1ODH5MKrShwZLfdq729HW63G21tbXC5+q9LSwFIcpqzrrwTz721AnvOnYQ//+RLuPSn92NnXStu/+mX8IXj9+n3u42dAXy4vVWV1Zhblq9q+0lXCEL6uzl5AlJcOqosFS67SYkq6Qpy6KGHqh/v4YpAEX8LFy7EG2+8oRJApPxMmzesGt+LEa84z6JuhoO1gIi7eGOTR4nBVn9YFa+eKfGCpXkqgYSWFJKpyP+YZAHn28QlbECrN4xdbUHMqXBkfe3LdgpAQgZmR10L5p74U3VTVv1fDcD8GRV48JavY+70ij6/5wmE8fHOVmxq8qLIYcF+U4tQ5WJdP9I/Yn0TMSZlYfJtRhWMrouoYDiCj9ftwGXnn4bly5era3KwyDJk/tNOOw3333+/evpPRtzAzZ4wfEGtBlpxnnlIDyqybOlgskHEYJMHnmBExRCKi3h+eX5KSyIh40k0GlU9tvUWjTtbAqoN3LTS7P+dbh+CAMxuWyjJGQKBAFasWIG6ujp1wyotLcWee+4Jh6Nvd+y9j7+r6kTJk6JYS8Qft8/CaZgzrTzl/HIjXbGrXbVxE9eYuHvFNabEIyH9IC6oNn9E1ScrcpoShaTlYWJzkxdbm/0SrYSX33oPd9x6C26++WZ1TQt9iUGx+Im1sLi4GH/84x9x/vnnp7TKyboqXFZ4gxE0d4ZR0xpEvs2EQqcZ5kEExMsy9X7L+00pVDGEIgbXNHRiWW27ihPcvdKlkkhoFSSZgPS9Tn7EkWu/yMkHlZ7QBUwmLF6vFw899BDuvPNOfPrpp706KsiPwO67746vf/3ruPDCC7tZRsLhCGYe9yM0tHT2Wu6t152Lb5x7WOK9iENxg32ys1XFbu1W6cIeVS4V80dIf4h4k+K0nQEtA9FtlyB0oMkTwqZGLxo6g4l5RYqdsFuZeqCQp3ex5j3wwANYtmwZgsGu+YSCggIV63fppZfizDPP7LPlW6rtkdhDcYlJpqQUxRUhOBy3WDgaVVnv8kAknUaKnRYlBMUyaM5yNxuZWHT4w3BaTVnv/hXoAiZZjdzEHnzwQXz7299GS0uLEnpi8k+FbpEQS+Bvf/tbXHbZZWr+B5/9CJf86D71mdxwlQUQwJTKItz0ndPxhRP2Ve9r2/34aHuLcoFJeYx9JhemLOpLSF9iSzISxd0rbl+5Hj/b0YadrQEl+JJteyV5Fhwwo6jXcuTBZu3atYlrvaKiAjNnzhyRtU2u93ZfBG2+sNoIl8MEl2N4QlD2U7LfRQhua/WpWMGFFQVYUF6gbrqEkLGDApBkLT6fDxdccAEee+yxROzTUJDCu/LdY77+Z6zcUIt8pw0nHro7jtp/Ho7cf16i3IsEwEtmrxRzLsuzYsnUIpSzcwIZRryfWNmSi8/uaPFh2c6ObvOL7Jpd5sTcioH7Sqd7O9t9YSUGRU+6HWYUOEzDDmto9YWwsq4D6xq0HsgzS/KwR2UBSvPYdYSQsYACkGQlfr8fJ5xwAt56660+LX6DzZT8+z8fgy8Yw0F7zVJWleRYkeW1bSq+yWkxKYsfW7iR4cb7iaBKVXg2lQjcf3ohSvMH58pNNyJUJWNYLJYS2aCEoHJXD08ISqiElEdauasdncEIKgts2L2yQJWUYcwsIaMHBSDJSr72ta/h3nvvHbb4SxaBxx13HJ555pnEDU6EnyR4rK3vhOjBPSpdWFhZkMgiI2Q48X6p6ub5ghG8t7ml631Iu56PX1A67kWXJdFJ4gOljIbE8Ul8YF7cdT0cxAq4tcWr3MOSPCLZwxJDO68sX/VIJoSkFwpAknU899xzOOmkk9K6TBGTXzj/gm7Cb7cKFxZUFPDmRIZRfDYCf6h7vF9P/KEI3t/cqoTRgTOLlMj6bHu7er9/ivi/8bRiihD0BjUxW+Q0wzGEGoKpaPAElBDc1ORRrRIlkUoetFg7k6SbcDQCk2Fk1+tEhQKQZN3Ndc6cOdi8efOIrX868sNwxOlfxFd/9GtlpaHwIyNNqAhGesf79RRV729uUfMdOKMQeRMgmSgQiqLFG4ZfClebDco1PJRi0qmQbiPSjWRVXYeyeC6udmNhRT6t7WREdIZ8eHzrO3h8yzto8LfBbDDh0Mrd8cWZh2O3ouk5c3TbWQeQZBOvvvoqNm7cmHZRuWvHNqBhM8459lBa/Miw+/lqLddiKHSY+rRmiWv1w61aGSHJ9J0I4k+wWYyodFuV21osgg0dIWW1FKGbbx9eWQ2n1YwDphWrkjGf7mzDh9tasKK2HXtPdmNuaT7bzZEh0xLowOXv3oYdnkbE4rn14VgEb+5ajtdrP8e1i76Ik6fsxyPbAwZhkIxHaqGZzem/Ya795H3849Zf9in+RCTKjZ2QVMi10eILIxKLqVi5vsSfJFh8tLUNnkAE+00vRIF9Yoi/ZBxWE6oKbagqtMJmMSir4I7mAJo6Q0rcDgcpp3TozBKcs2c1Kl02vLW5Gf9ZXqO6jQw1u5/kNr/87EHUeJsS4k8nEouqab9Z9jA2d+wat+3LVCbeLxHJOd55551eRZ7TgbiT33//fXWzSXZpaSU8wmjxhFR9jlllzrSvm0xspK1Uq9TQU509zH0WPpZr6eOtrWj3h1WWr9sxsbsRyMNSWYEVRXkxdPi0rGEZxO0ttQSl1dxQ3cOFDguOml2GRVVBfLSjFa9uaMQypwX7TinCFLc9J+O4xgP5HZSHlVBEe/BVzZFimqSS19Ee79VrrYGSeq19Lu/178anJ8+feC31VyUUR6vDqo+1afGx0aAsVBKbLZ8V5VlSWpx3eBrwfsOafvdNlimu4f/d4+xRPIITDwpAkvF1/9Lt/u0ZL7Fjxw5MmTJFWTJaPGEl/vTnSJrISepM2Yi6MRX2UzxZYgM/3d6miojvN60wq1pRieCVG7LbaVaWTYmBrGsPqYQREYJ5tqHXEpRWcyfMK8euDim+3ooX1tajosCGJZML2Wt7hETiwk6uXRmHZRzuPk2GwaDEWlxUqRbqqo160msRcOh6LaXADUZd2MmcWuFLTVRqYlHEo1jSw1F5HU18lhCdMaiHi/wU1vOljesH3v9YFO/VrwJAAZgMBSDJaNrau9dKGw2kw0LUWYpAuPcPoEzp9IfVTV4GSRiRsm60SuQmEsMnBZ5VmZd+CibLzWvZjnbUdwax71Q3Ssapvt9oI/svLm3pLSyJIu3+CJo6xXoeVnGC8tlg+g0nU1lgxykLKrCjTevC8/TqOmUJFItgaV52HsfhIuJIF28i5ML663C02/SekSxySixmozo3EueZbzeqa1r6RsvYZOou4jSRl5m/e5LxK7Kyp/u3J6FoZMy2aaJAAUjGBblBhlP8cOkuCPWEGpEnQCd+dNPvceMPvzdq2yJ1Aft6+pUnz5q27n1YBTH66KJQfkyNidcy1j4TK4n8wMo4E384ydDQBY41Lv76OqfK7butDY2eIPaa7EJ5QfZ3wZBjIXGCMsj/c4cvoo6ViGWpIyhC0GYe/P+BzDel0IHJbjs2NXvx8Y5WPL6iFjOLnVgypRAue/ZYUweDHFNfMKrKCMlYHkTEgie/l8nI0RUBZzZrQs5ulbElLu66BF6q+pQTlVmuqgHFn5SEmeeePGbbNFGgACSj/nQqN075wQro43AUPePG5b5giQsm+ZGyW7QOCiZDDH/78+9H9SxVV1ejsNChYpkaO0PdflRlG6YU2ZV7Qm7skvUpWlFeJ4aYFhMm+6e/74mIQPXDHP8h1sShMfE6F5qUT2SkULgUeLabtQzYvoSMlHpZuq1NxfwtmVaIsiy1/PWH/P8W5xtVYkxn3D3sCQTVdS5iUNzDg639J8d5Vkme6sYj7eU+2dGGRz6vwZ7Vbiyuco174ezR+M2U30cReVIg3B/UBJ/+myQ/E0poW6R3c3dRp34vJ+jDphgEnl/doK6RYqdFhUtIbKgMA/02Li6ehcl5pajxNEFSPvpyAZ8x7aBR2vqJCwUgScs/r9z4AqEY/MlCL9T17yj/wxJALu4GsQboP1i6CNKDf1MxqboSNTu3j8qZkti/oiKtAK/LYValLaQlVpMnpNwmsknKiqdFrgwKPSBaWTWjXdZM+RGXack/6Dqy/7r4tZkM6gYpddesJmNWPa1PROR8ifjrr8CzINaZD7bES71ML0RhFsX8DQe5buV/SgSzPARKdxF5yNJd6OI2FjE4GBexuJrnlxcoMfhZTRuW1bRhfUOnKiczvcgxIUWPPCzKcZESO/pYRJ+eAC3HSIpvl+RblCVPRJ/8JkzEfR0I2aNQNApvSAqqh7GlxZf4TEThAdOLVDvBlN81GHDdovPx3fduB2LRXiJQln109d44oHzBqO/HRIMCkAzpB6ubJU+eUMNRBJNi5+SBXISe/HBJdqQIPnkvP2bD/eE6+uij8cknnyASSW8MR3lFBf736mu6ZQHr2WZy45Is4OFY5lTgc9xFrP1kSRh06oy7LpHY5Q5v94tADHf7AdTFoBqLODQZ1bHOxptBJiE3ZunwMZD46wyE8eGWVnXrOWhmkSpxQnq7h2Mxc1xQa3UFpZyMuIZFCMow0P+bPCAtmVKEuWX5eG9LM15e36DcxAdOK1bWosHQM+t/uL+FzZ0hJc4GekDT/9eVVS8u8sSylxxzLAkO8pspDw262Btq7ORERkRvkcOiYmZ72vDE+yJhF/2xZ/EM/Omgb+O2VU9iRcuWxPR8swPnzjwMX5lzLH8rU2CIDaLg0lAqS5Ms6Wkad0EkC77kODkRdLpFT8b2+Hg4P1oifmpaA+pJLZFoocSNlGoB2hq2Y+7s2WneS+DIo4/Bk0+/oH4YxCMlQ6aIKnE1ByOauE6MRWwnnQO57+iWQnv8HMj7oWZfkv5j/uwWAwpsfbt9W30hfLSlVR17qfMnN28yuGtcWs1JFrHeD1mEtghBp633ddzsCSEYiqLMZVW/E/I7ta3Vh/e2tsATDKu2clJMOlX/7o3tNXh867t4reYz1THCaDCizO7GKVP3xylTD0CxrWDQp0wSLDbWe5WAm1piVw+Mycj/qdqnhNhL5cIVwWdSYk/+b3Ptf1bOfbMvhIbOIBo6A2jyBFOGzjgtJhw+q3hIhdO3dtapgtB2kxV7FM2A1ZRbD2PtQ9BrFIBEuXC9gQg88R9jiXfSHwt0caELPX2czpg1EYAb6rtM/j2ZVGjFl849E88//3za6gFK4seiRYvw4UdLVTyiVn5AcxeYTZoY7M8tPd5xlboYVK53NXT9eopFxW4xJQnz7HQbjUW2rxw7Vz8xf42dQRXzJwJRYv7Y13b4FjX57ZFBrmU52mIREzexjIXtzQH1PyoW8Qq3JDZo08PRKD6vacdnNe04dEYx5pTlJ5bbEujE9Z88gI+b1qtEAIkFS8aoypcYcPb0Q/DNBafCbOxfvIubf2OdLyHoJM6xutCmLJqdfokTDSc8IpoLVxd7muAbiSdkIp9biYlt84fUw5LUz2zxhdR0OZeS2S2xsm67BW9vbk58TyyCh8wsZpemIUIBSPpF/vFE5Ok/uGLtk58sETy6KyYv/nQ6Vk+mO5r9Ks6qJ5JtKR0Itm7digULFqi6gOkSgOJWrpg2Lx6UrtWoisQMCEe08i8q/s+YuWKwp4hPuOV7uOZlq61xMdgl5nPvRjRYRFRLe7eBsn1r2vz4bEe7uoHtPVUsTzye6UDCICReUH6b5GFHDr/ExfqTHnLkUFe4rd3EgXxPeRDi56vJ347L3vkj6v2tqrZcf8g3DqnYHTfse7ESiqmQclCbG3y9SqroyP+X/JZIHLEI12xLUBn0/05c6Ek9VRmL+NMPmRyXQruW5CGiT9z2yfeYF9bUq5ALifc7YFphTh7DkcJewKSXha2b4Iu7W+SGJa6WykKrJviGUcV/pIhYkVgg+cHvicRcSR9SYdq0abjjjjtw8cUXp2W9N910E2bOXaisCs0ezaoouy6xdSKOrCrmy4xQxIBQRLcMxjJWDMqPqLgek92PShTGxaCMxSUlP8qCbmFR38lRN1QqREQk1/lLdZ7FCrulyYdVuzpR7bZh0WQXj10aEcteoVPLIhZBIW7iDn93y7+IsNrWIMoLLHDatGtetwhqn0dxzYf3oGEQ4k+dUwBv163AXaufwbcWntrr84aOIGpaAim/K+3xxA2cvP5sR/4HPOr3JIRWvyb0ZNDvLRIJJF1vip1WzCxxKqHnVjUh+z9GCyoKlKVwt8oC/k+NAbnlHM+pJ2gRe9pYLEOC3NTkCbU4z5Kweo2HkBELpGQDivATAah1FTChw98VZyhxV9VFtm7bd9FFF6G+vh7XXHONmj6cfqGmyQfg4jMPTyzDZg4m3KeyOM2dKso0om5AdqMEIYuIluOKCSEGu4nCePB9T1EoP9Ri+W3xhtDk0fZJD0TXhGT2Zx/LsZASJU6rFjsp1550+JA41sI+xJ9cuytqOrCj1Y8ZJQ4sqMzP2POfDWgxrkb1OxGRgOAe1HeEUIZYrxixDxvWYl37jiGtS34FHtnyFi6cfTQKrN3bPzZ39q4F2oWWvZ/tLlxd5LXFX+tucLHCisCbWujQhJ7D0m/MbH9MLXLIo+ko7AVJBQXgBEePCdOte/JUprv+ROCJ0Csr0AXf+P1I6aJPnuR1a5+4AyYVWdVYfiwsppBqJyWCcHKRPeUT4Pe//31MnjwZl112Gbxe76BjAs1msxqmH34+Xm3Jw5Zd7ZhR5Vbu5S2N/l7zlxZ0PdGb465gOdYTVQymFIV52j7J9eKNF5iVEjjNMe2YKkEYD1aXcbbVKtQSbGIIigi0xOALay7Evix/YkH9eHubuobF6je50D4u251ryDUqArAnWv1MzWrfk0c3v60SPQZj/evZVeK5HR/h3JmHd5s+ryo/UYxZvCkSMy2WSb0ywkRHK0mjeYd8oYj6PdCFnlzv+qO2CDsReZWufOXKlVaIEm9MJiZMApmoWboh7Wbd7gsnMkNVDIpVi+ET1+54P5XKE2JnD9EnFiatRZSp1/ZJZlhde1BZKCVOrT9qa2uVGHz44YcRjVsG9LGO0ai5tGX6aaedht/97nfIK6rEsdc+qn7MX/7N2ZhcWqDiD0WcJr5nAGaVO/p1VySLQUkiUTGD6MokzpRs4qGiBKGqVajdDPSbnP6krwr5jlO4QLqRc667rHRK8qQUSe/zLlmKn2xrUwJxn6luZeUgY3dNNnSElEXaliiD1Lf3oiPoxckv/niA3hCpkSXOKqjG3w+/elDz94w7zNjC0iLswpFuIk9lKKtxpFt1AV1cu+zmeDFms0rQGIwLl4w/TALJQuQfWW7GIvgkjkusfvK/6FaFVs0qDiYTgtAl3lCr/h9W2yuIi224fUEHoq6uDv/4xz/wzjvv4IMPPkBjY6M6VlLceb/99sOBBx6ICy+8UBV81tlW34FjrnkEDpsZL/36bLjz7NjUoCWXqH6X4i43GzClxD4oEa2LQSlTKMYA/adUqwWoZRVn6g1isBZmTQxqVmbRgyphKPGwkRnX3lCRsiI9jTc9e/zK/m9t9mFVbaeK89p7iptZiRnOlo46XPjGr4f9fbc1D08fdwMyHSkwL1ZrTczFi0knCTz1PtxV0UFHEsH0MA8Z25Ne62O2r5y4UABmmegTwSeCSm7E6snMYVLCT26+mWCFEdEnVj6xqIyF6EsHG2talQgsL3Ti+ZvPguRGSPC/lHQQ69a2Zs0tPLXYPqA1suc5kx9cERZiGdQfrPWMYmUdnACu4oHccRJqIFZd3f2VsA7aTOoGk+n7p6xKnanDB+S6lRthz3i/+ZX5E1bI5xKbO3bhK2/8Ztjfd1mceOb4GxPv19Z3orY9kOj73dUDPF6zVPX/jvcAj7/Wa5hKnKk8MGnj5Neax6PXNBmr6f1/V67Nnt2EpJWmJui6i7nkaRPhf5OMDGYBT/jsqi73rvyTi+gTwed2mpWwyoR/YNXwXbl3tdgxIS+etauVQBj/beyPWdWFePrGM3HcDx7FGT9/Ck/+4jQUOGxKsArTS+3Y3uTHlkafsgQ6kxIp+kPOjcomNiZZB+N1BvXYQcFk1Cy4WuxgZh+rvro6lOZr4t8Tj4mSpB7JqJZTL1ZB3UKYibGDyUXNdeRcyDZL7Gy3eL9JBZisgtPJeFq7VIedQVxLhdauOoDDocjW/fu6mNKFV0gSUuK9wRPjuNiT18lXlmytbLIxLhYTrxPj+Ou4G1lrCWns9rkeTqJP04SnWPKSxJ4qwk/3LBkajAHMFNEX0Ep0SFaiiD5xRUk7MhF+GSf6fF2xUyL6RDSJ1SQTb/QD8cn6epz8o8cxraIAT1x/OiqL8xKfyY+5xAeKwJ1U3CUOh4veIzjS0zoYb6GXiB2MC62JbR3sanUl16+U1JH6aJniKpb/NX37JK5MBL78zwnNniA+3tambsr7Mt4vI3j4s50qMUGKA5fn21TtRRl61pHTufzd27CieXOvvrADYYABX5t3Ai6ac+ywtzUa9wJMhKQwkn3QBTxBbpYSK6e7d0UQaPFHmuiTZInx/vHQ4790S5/c3GWLxKojgi9/goq+nqzc0oTTfvoErGYT/nvDGZg9qbDbj7nU/5L9F+tmz7ZPI0G3Dqr4wXgnkl6CUN1EJuaNRKw2co1LYVfdSqySgFSxXPO4ikHV5jAU7fbgIudjQ4MX6+s9jPfLMJ5eVYe6Tq0On5ytZFm39yQ39prk7ja/tHz76Sf3D3k90hnksWN+hhI7W56SiQldwOOIiCS58ckNriciJjz+JNEXkxIGBlUVXdy74mYYzxt9oiSIZICqcgdaD0td9EnBU3HvZoPoS2a36SV47ZZzcdpPnsCRV/8bj19/OvadW6E+E+vCpCIbdrUF1SBWQWkAn47zpHoQS9u5PgRhcoUb5TKOJ5VMFMuCOVHQ15LICJdWWVK7TQa53tWDhG3kcaJy7CQR6Pbbb8f777+v+mDabDZUVFTg/PPPxyWXXILS0tLE/Fp8VJfLTILmpauHJIbMLnNiTnnehHLNZzPSC1seGuo6tffJ4k/coVUuW6/vHFq5B6ocxaoLSM/2b/2JvxOmLKH4IzkDXcBpRKrWb6j3quDfBdV5CaEkqfYSG9XqCWmiz9xl6RvPchpaiQBN8HkDWuaYCA9Btktcd2KxkbiobC8KLDS1+3D29f/Fii1NePCHJ+HYfaZ1O1aNnSE0doRQ5DSrNlSjfd4S2cVxl3FyzLfoJYkD0scTyW0c0csDBboyxUciBv/5z3+qzi6rV69WtR571oaUckDS+u+8887DDTfcoLrKJLOrPYDPd7YrMbF4sgsl+Vr3GTL2yDUv14VY++o7gmosfWN7IleIlCk5YV65umZSsb2zAd945//gDfsHFIEi/uYXTsUfD/wmbCaefzJxoQt4nG5qIv70IswVLqu6kYlFQaxpWreL8RV9eoyW3HR1K5+ICtUFwqoJPomFyoUuEH3h9Ydw4a+fw4sfb8Pd3z0G5x81v9vnLZ6QsgSKWJFOJWNpJeoWQ6iyCHtaQyaeKFRiUNzE/u5iUOJfB7I2S33Hq6++Gn/4wx8G1RlGxKHb7caLL76IvffeW00Td++6eg8qCqzYc5JrXIul5yLhaBSNniDqO4Oo6wigvjOgWhcKEt9Xnm9FRb4N5XlWPLWqDqH4U5BMP25u+YAleXZ4GlRLuO2ehpSFoaXvr4jDwyr3wI8XfwkOc29rIiETCQrAMUZuPNIkXLJ3eyI3MSlsXJBUW2ysEJeziDy9er2MVcFiydIUF5jUcGMf2F6IC//bf3oV9720Cr+85BB872xNLOh0+MLY2RJQ1tHJxfZxdYlrZSM06+BEF4U9xaAeeiBiMC9FTOy1116L3/xmaOU+xBKYn5+vakbOmzcPmxq96uFsSpE9Y49LtvWPbfB0ib0mb1Bdu3IORNRJgoc+9BR3r6xvwJYWH6YXOXD4rNJBx5CKwPuwfg0e3fI2PmxYk/j/sBotOHHyvjhj+kGY7Zo0CntMyNhDATjGP2qSKdrq6+okoSOxYyL+xvIGmiz29Exd+Z1Ulr24lS8bujiMxXm9/oH38euHP8KVZ+6Fmy85JGEVbfcGYDaZsb3Zr46llInJpHgxXRQqQZhCFGrlJLQHAf11psUV6hnn0oNUrOoiYAscZpTma1mfTz/9NE499dRhLVtE4KxZs5TLWNzDJP1IzKe0EWv2BtHs7RoH4jEmBTZzQvCJhU/ioAf6H5JuLLs6AlhYMfz+y4FICB0hn7L8FVgcMBvZxoxkF0wCGUNq24IpxZ8gtfxGQwDKDT4U1lr8BBNjKcqr3eYlUUAEX4XDouq1SZmLTLq5TwTkeP38KweiosiJq+56A3UtXuUS/nh9vaod+MfLj8AXj1igCkbvbA5gcrEtY46xqh/WI7lErgxdDMpYvKV6CzsdA2LKSthdFI6d1VCua31d0oGlOM+o4i3lutasghKjaobRZFBt/UTIRaT9yhCR76xbtw4vv/wyjjvuuFHZl5wqVh+KoMUbQpMu9HwhtPlCiWvLZTOj2GnBbpUFalyWZxt0Xc1kSvKsahgJNpNFDYQQJoGMGInxa+oMKQuFPNtqRUE1C4zEE82tdA572bKcYDeRp42Ti9iqZuhmo3KX6IkbUk4mU8RINvDoW+txyS0v4MCFVVi3oxW1zR6Uuh1Y+7eLIY7KHc0BVRJHLL4T7bjrcYXdhh7CUFDWwvhYtxx2nzby/e4M6HX5tKLMfS1zzZo1WLBgwYjWJfGAJ554Ip566qkRLSdXkN8iSc5ol8EfUoK81S+CL5SI2ZNOFMVOqxJ52mBVdfvGuyc5IblEe3u7inWWSgguV//ljEZW2TaLeOaZZ1Qw+eeff67KRVx88cW4/PLLkZfXVRg4FWLh68vKN1BQuj6PWGI0C153sZfc6kcSSsSSJ0JDxJ5kEovwy5TCutnM2YfOQanLjlN/+iRC8ZudZAzf/t9luPoL+6K6CComsLY1qErl6MIlFgjC8+xb8L3/OQKfrkakoVmpJfPkStj3WQDH4UvgOGwfGMbRDam6K0h5mT6EoVzCsscx/bWMUwhEmdLNYqgWHh8n1W7Txl3fVq/iy9U/DYSBIMQKqHVL0S9x/bjec889w7b+6UimsLiRa2pqUF1dPezlZFvsqxJ4AWnrqIs9TfBJ7F5Xj2uDKorutpuxoKIAxQ5N7Emplon2AERILkMBCODGG2/ET37yk8RNpaGhAddddx0efPBBvPnmmygoKBjWwU0IgfjNVASduG57ir3k8h5SF1CEndshIs+o+tDKtFzNys0UdrV4E+JPEDEk8YFfO2F3FBXY1fuaVokNNKDMbkDLn/6JtjseRrStU9S71gcuTnj7Lvg/Wo7W2x6EeUoliq65BAVfPCGjbp6q9RRiSvwZknqXaq2vknuWaq3vNOHX1e5KXvdlGVRiMiEq40ITMdjkOMUloyw/GDEgEpK4Vq0losT/iZV71apVIxJ/XdsRw/r167NeAOoF3cVVqwaJEU56LWMRejLWUT3H7Wblvp1ZkqfG6r3dDKeFQo+QbCDnBaC4k0T8Cck3FSkxsXz5ctxyyy24/vrr+zyAcqOSfqhqiHYfh5LeJxsD5RYnFjyx5OXZLInXMs4kEUA0Gtq8uPxPr/Q6HJ2+EG5+6EP85uuHqULeImI669uw/cvfRWj9Nk3hCEniL0F8mojBhit+ic7HX0b5bT+GuaxoTA67bnkORaOQy16EnSbwNHef/ronWpcSrRepWILUw0lcAOqfa69jaizr0a2BCXtg3DKoLV4XfN2ve/3/QNYlRdUlPlHWJTQ3N6ftOLS2tqqx/I/Kfkv4RCYl9KQ+byKOZZBwkGi318nCTpLAdNEn30lG3LVaySeTEnSVBba4yLMokWc3M1GMkGwn5wXgfffdl7J4rC4Ixd3UnwDc0uBXP8A6cu+QH1exBMlYapqZ4+/1aTKm0Js4SEzc3nMq8PmmRrR5tHZUOrc98RmuOH0xppS7YF+3Ec1nfgcxn79L/A0S3xsfY+dJ38Skp/8Mc0VJn/PJA4UE3EtplIFqoAm6hU0sQCIQZKweTiLdm9ZrZWKk8Xxc1FmMSuApF6yxqwH9aIkjeZDyBntPt5i0/6fkbF0p45Iu9BCPZ1bXqXp0gvy/ihC0miSe1qjWL8dFCd+4y1yzdHYdFzWOD5rbWvtM7Zs8Gig3d9dYc6/HLau9Ptfq42miLknoifcgGu330rKZpHi7JurEJVteYFWv1RCfLqKPcXmEkJwXgHV1df1eBeIO7g+J+VJ1rETg6e6vDLYgkKEjmcAv/ups9bqxzYd1O1uwdnszPli9C++vrlHnO7yrEbXnfE8Tf3o7laEQiShrYO0Xr8bkl/4Cg6X3v6aEC0g3EhEAnkCklwAUK0+XwIsqC7QSekk9htVDiMmgSgJpDyRGJVjG+5oVMdTcGVTbIaEPWlFyEVO9Re6UKVP6fGgbKpMmafXfjphZorJXNYuaJrx065qMNdd3DCEl2uKJXvFOLZorXC/SrU/X3gtaskyXpVTEYWKsZ23Hfzf0sfyWiACV+odFJktCjKoQEf21WcuWlvfatMy2XhJCMoucF4Bz585V7t5UyA+x1AvrD3naJrmDZP/KcNDCanz1+N0T4mXXBTci2ukbnvjTiUQQXLURLf/3AIqv/mq3j8SlJ+0EdQKqo0tEWYV0y16yl0/EgIgIu00TBiIUMkHo9YVslWaV1OJiO/zd96O8wAJLXPBeeOGFuPfee0e0PrEo7rHHHpg/X+v04nZY1JBO9CSwTD3mhJDcJufz8yXbV6wJff1IX3HFFWN+UsjEwvf2J/C++K4ScCMmFkPL7+5DuKEl/jaGdl+4m/gTxPIk0yTmS6w+WscZMypcFkwqtKpWhCX5FuUqloeUTA87EEEmCR49EVEosWx6qRHhyCOPxOzZs0e0P/LQd+WVV47qMZFlZ/IxJ4TkNjkvACsrK/HQQw8pEShZwIK8Fr785S/jsssuG+dTRDKd9r8+Ju0l0rfAaBQd/3pGvWzySBmO1MKy0GFClduWEHoS4yWWvkwXHSJqJRNe2r41x3srb2n0JzrXJCN7UuW2qLIjiWkGgxJvw0W+L/WxzjvvvGEvgxBCJjqG2CCK1Q2lsOBEZcuWLfjLX/6CFStWoLi4GBdccAGOOuqojL+ZkvEl6gtg84zjRub6TYFl/gxMfet+VY9NhFKq4swSJzeWrQaHivy0SHatSl6Ilz2S+DoZ6/siMW8S8ydZp+KiFsGrI++rC3v3hBWCwSCOP/54vPXWW0MuCSP/048//jhOP/30Ee8jIYRkEiwEPQymT5+Om266Kf1ng2Q1wVUb0i7+hND6rYj6Ayiw25T1q6eYkvZo8aoo445eUkbVttSzVdXrpAQUg5ahKmKuwB4vZN4jLlElgnjCShzK59Vum3Jdp8JqteKJJ55QrdyWLl3aZxxvMvp65EGP4o8QkuvkfBIIISMhuG7r6BxASezYvBO2BTPVW60/rgxAns00psJOMlv1Onn6WKYnT0vONNa71OTbNZEn7yWRYyBrunLNOkwqq7bMZR0wo1W8Eq+//rrq2HP//fdrZVVSCEG9wHtVVRXuvvtunHzyySM7MIQQkgVQABIyAqTd22ghnUdC/khXpw2920bSa1VsWW2I1k1D77KhvddEXLf3KeaVcS+BF0ldCFrWbY7XxFNZxuK6NWFIQq8/ygqsQ5rf4XDgb3/7m7LeS83O22+/Hbt27Up8LttyzDHH4Nvf/rbq/avH+RJCSK5DAUjICDA67aN2/NoLi+FtHz2BqWNIEnXikrVKEWhbl8jrGmduSROx7klHnx/+8Ieqdqd0+LDZbKqv93BbORJCSDZDAUjICLDO11y0acdiRmV5PmIWS9xS19UlQrfq6RY8XZJpVsEukaa/73qtWQx7f5aZom44iIVPMvtlIIQQ0jcUgISMAOv8GTBYLYgFQ+k7jpIZu3AWjLZkd2j2iLR088C7W3HI3FLMKNXauhFCCBmYnK8DKEihXclaJGSoiPjLO/No6bGWxoNngOu8E3kyBkBiFX/6+Er89vn1uO3ljTxehBAyBHJeAIo7rbEzDH+KIrSEDKqo8RdOAMJp6AISx2C3Iv/c43nw+8EbCOPKf36GJz6tVe+L84eWPEIIIblOzgtAaTUlSAcFIRKNYldbQNU0I6Q/ahracO5V92D+VfcjfPbx0s8sLQes5GffgsmVz4PfB3Xtflx4z1K8s6Ep4Rz3BdMnwAkhJBfI+RhAKVorSAkLodMfhWi/Nm8Y5S5aFUhqq9/9T76Pa3//BOw2M/7560swe9+Z2P7eJ4jUNQ+/J7DJCPtBi+H66hk87H2wsb4Tl/79E7T6QiohRp0PFcaRxhhMQgjJAXLeAiiWPjH+SakLubF74pYE6WLAuEDSk601zTj18ttx2S8exGlH7olPHvkhzjh6EUzuAkx6/I8wlRYOry+w0QjbnvNQdd8vYUiTJTEbeXt9E5o8QS0FOolWLwUgIYQMhZy/04jQk64FgjcYTVgVhFZfV19SQh5+/mPsd96vsG5LPZ667Zu4+/ovo9itZZ5KBwrzjEmY/OLdyoqnGEx5lbjYK7jgFFQ//n8wFjCTtT++ctBU3Pe1fbHnFHe3QywWQUIIIYOHLuBwFPk2k7L+dfgjvdzDkhxit+S8Ts5p2jt9+N6vH8G/nvkI5524L279wRfgLnCoa0YeErY1+1DbFkBpvgX7TitH9aN/QMfDz6P1//6B0IZtXbGBepsyyRiWXmqxGOz774Giqy+G87B9x3UfJwpSs3CvaYXKYr9bdQEOm1eGhz7YDntas7AJIST7yWkBqPc0lQb1IvSkDVZPWr1hVLgsWVUslwyeD5dvwcU/ug+NLZ342w0X4vyTl8AbjGBDvQc7Wv3dsseLndaunrbnnYiCL56AwNKV8L2/DIFlaxGpb1Zi0DK5ArbF8+E4bB9Y507n6Rgiy7a3YemWVvzui3vg2N0qcOlh01X/YEIIIYMnpwVgcgJIZw/rn46IQrm3mKj/copIJIpb/v4SbrjrOeyzcCqeuf1yzJhciu0tPqys6Uz5nUlF3dvCiRC0L9ldDSR9/PmVjZhdnoejF5R3ZfDTAEgIIUMipwVgOO6Ss5gMcDvNcEZiypLQ7A2j0GGGzWKA0aD1QiW5w7baZnztJw/g3c824dqvHYfrLj0BFoumMNx2i7oexHqcjMtuVpZkMros3dyC9zc14/fn7Qkj/y8JIWTY5LQAFPev3EPEUiMWPrmxh+N1Ac0mQ6I2IMkdHnv5U1x+w0PIz7PjhbuuwCH7zO72ucthxt5TXPhoa1u36RUsGTTqSMzlba9uxPyqAhy9oGz0V0gIIVlMTgtAce/2tO5F4uUlqP1yz+X709v+i9/f9wrOOnYxbvvReShyOXvNJ/F/K2s7ldXYEM8iF8oKbOOw1bnF+xub8cnWVtz25cWMySWEkBGS0wIwkkIA6sHk4voluUFrhxcX//B+vPTeavz6f8/EFV8+IqXA6PSHleVPLpkDZxapEiQfbm5VJekKbAxCG23r359e2Yg9J7tx6NySUV0XIYTkAjkuAHtb+uIGHXWTJ9nPui11+ML//gX1TR148k+X4ZgDF6Scr80XwtKtbSrOb99pbtjjMYEHzypWsaTMEh9d3lzXiBU723H3RXvxWBNCSBrI6SC3viyAelwgyW5eeGcVDvvK75W1960HrupT/EnniQ+3tCHPasL+MwoT4k+PFU1+T9KP/E/++dVN2GdaIfafWcxDTAghaSDnBaC5ZwxgClFIss+dKLF+Z155Fw7eaybeuO9/MXuqVlKkJ3XtAXy8tU1lhe87vZCJQePAK6vrsaa2A5cfPYsPZoQQkibMuSwCVH2/FC5g6r/sxecP4vIbH8KDzy7F9796LH72rZNh6iPjR2r+rarpRIXLhj0nFbDsyDggD2S3v7YJB84qxr7Ti8ZjEwghJCsx53L8n2Dq4eoVd5O49Uj20dTqwZlX3okVG2pw380X4dzj90k5XzQWw5pdndjW7MeUIjsWVuXT8jROvLCiDhvrPbj+9IXjtQmEEJKV5LAA1Mu99C4DYzPktGc8K9lZ34pTv3W7aun20j3fUd09+uoN/dmOdrR4Qkr4TS12jPm2Eo1wJIo7XtuEw+aWYs8pbh4WQghJIzkrAMMpBKByC0txaOq/rGLjtgac/K0/K9H/8l+/g7nTK1LO1+EP45NtberaWDLdjeI8rbcvGR+e+XwXtjZ58Ztz2UqPEELSTc4KwC4LYNe0WHxgEkj2sHzdTpx6+e1w5Tvw9O3fwtSq4j6TPT7f2Q6nxYQl0wvhtDKzdzwJhaO48/XNOHphGRZUucZ1WwghJBvJWVtXchs4nXhrYBaBnqC88v4avLdsU+K9vD7u639EVZlbWf5SiT+x+m6o9+DT7e0ozbdi/5lFFH8ZwL+X7kBNqw/fOnLWeG8KIYRkJTltAWQbuOwhGo3iK9fdi7ZOP+6/+SIUOO047+q/Yu+FU/DIH/4H7oLesXzS93l5TTvq2oOYXebErDInkz0ygIaOAP78ykacs+8kzKnIH+/NIYSQrCR3BWAslrIGYKrMYJL5LF25Dc1tXvX6gmv/rqy4xx20EP/8zVfhsFtTdvZYtqMDgXAUe01xqVIvJDO45fl1sJiN+M4xs8d7UwghJGvJXQEo5V56dQHRxtR/E49n31yh6vlFIlHVm1cE/uFL5vQSf+Ly3dzow/p6DwrsZuwzsxB5tpz9N8g43t/YhOeW1+HGsxbC5bCM9+YQQkjWkrN3PhEJPdu9iWiQEoBsAzfxeOq1z5X4S+YHf3gChQUOXHTGgeq9PxTB5zs70OwJYUapA3PK8ljcOYOQEjw3Pb0We08rxKmLqsZ7cwghJKvJKQHY7gujwx9R4i8UiSEYjsAbjMAAAyYVWdkGboKyrbYZqzftSrw3m4yqhtzkikJUlmn143a1B7CypkO5hqXESwlLvGQc9769BTtbfPjD+XvyIYwQQkaZnBKAEvQfCGtxft2zgWPK7Sui0MouIOOKuGj9734G7yvvw//JaoS31iAmCTslbtj3WgD7AXsi75QjYHR0xezd/tAbiddOhxVfPGEffPmU/XDQ4pmqtd+Kmg7saPGjosCK3aoLYDXnbPJ7xrKj2Yu/vLkFFx40FbPLmfhBCCGjTU4JQLfTjLa4BbDbdIcZ4gwWAZjH+m/jRufTb6D5xrsQ2rhdzHii2BOfRWrqEVy9Ce33PwXDtb9H4TfORdF3L4TBZkVhgRMzJpfiJ5ediDOOWpSI+5NEj893dCjX725V+ZhcZKdlKUNF/83PrEVRngXfOHzGeG8OGeBctbW1we1283+JkAlOTplCpOxLkbO75hXh53KYEp1B2Ad47Il2erHr0p+i7qs/RmjTDm1ikvhLEJ8W6/Ci5Xf3YfvhFyOwaiN+cOnxWPXUT3H+SUuU+JMEn3V1Hry/qVWd8wNnFWFKsYM3rAzl1dUNeGt9E649cR6cTMjJWJ5//nmUlZWhqKgI5eXlePnll8d7kwghIyCnBCDiYi/Zy1tgNymRINY/wUIX8JiLv51nXAnPf+Nu3J7m2b6IxRDashM7T/4WAsvWJia3eEN4d2MLNjd5VV2/A2YUIp+iImPxBsL49XNrVb/foxaUjffmkD7YvHkzzjjjDDQ3N6v3TU1NOPXUU7Ft2zYeM0ImKDknACUJoCivywpYGLcIigCUqjBsAze27qS6b1yP4Ir1XTV4hoKUfPH5UXPO9xCqb8aaXZ34YHOrsuIeNLMIs8uZ5ZvpSLu3Fk8IPzhpLi20Gczbb7+NQCCg/mcTsbp+P957773x3jRCyDDJOQGoW/0k6UPC/XSXrwhAWv/Gls7/vADvi+9qmTjDJRJFtMOLhh/9UZV3mVeRp6x+UuOPZDbr6zrxj/e24euHTcfkYud4bw7pB5fLNaTphJDMJycFoNT5m1ZsRXVhV5HgUCQKiyknD8e4EAuF0fSz29NTdTsSge+JV7B3Sw1mlLKd20RALEg3Pb0Gk4ocuPiQ6eO9OWQATjjhBCxevBgmkwlGo1GNlyxZgqOPPprHjpAJSs6aSeRHrNt7gwF2CwXgWOF5/m1EGlvSt0CzCW1/ewz2fXdL3zLJqPHUZ7X4ZGsr7r5oL5blmQDYbDa88cYb+PWvf41169Zh/vz5uPbaa2G19m6zSAiZGOSsAOxJhcuatZYWSXDWhvjraKx3rkXcENeXPa67oc6Qcl6ZR+IoRUzL2NBPVxXPc29JwOXI3L/JhCPwPPMmYtEoDD3EPcksalv9+M1z63DSnpU4YFbJeG8OGSTi7r3pppt4vAjJEigAJ5yQi6l8iW6Crp9pg8ypHTVE/ilRaDQkBKLdbIR/6cr0ib84Ma8foc07YZ01JeXnInwD4aiy9LLd3/ggJXque3QF8mwm/PDkeeO0FYQQQigAM0zkiSYKRWOqa4ka4q/jVWpSCyxjl9VNxtLoQgRX8jRNhCVb51Jb5vQsv17TU0zoOS3WTYD2EK3qfdfr8LZajAY9BaBsgzcY7WoDCGBGqR1WcxpiD8mQ+etbW/Dptlb89av7wOWw8AgSQsg4QQGYhgb2zZ4wXA4znNaBXY+6KAolibuucdd8Ik8kQ9lsNMBp08aaqEsWe30LueHS1/J6Te1ztYZBHYOGNFv/EoTDauQLRpTga/eHexka5TiSsefz7W2447VNuPTQ6dh3ehFPASGEjCMUgCNALEsi/nTBkSwAxdKlW/E0ix4SQi/ZciZhcBajloCiCz4ZS3WaieqmlGMRjMSUq1csbT33Q94b8hyIeXxpX7fRla8E5rbmQJ/z+IMRlXggx1nENBl9PIEwfvDICiysLsBlR87kISeEkHEmZwVgKBRCfX29ym4rLS0d0ndFYLT7IugIdJmWAuEYOv2a8BGrYLI1TwxOIjasJoMSibrIE1ftRBV5/SGWNxHHguydzSIC1wSb2aAGycC27T4H/g8+T/u6rbvNUse0ym1FfUcwZZjhztZg4rXUfhTxbTMbtbEIcVoI0470+m32BHHXRXux3BIhhGQAOScAW1pa8Ktf/Qp33XWXamou7L333qqkwbnnnjvg9yNRsfpFlOBLRty6rb6IEhQiIgpMBvU6F61MIqZ0AShHyR+KwR/SLKViEawutMG+/x7xRJAUPX+HiWXmZJjcBeq1uOTz7SY0doTQ4tXWLTgsRlQVWhEKx5RYl6SQQCiKzkAokRktAlDOod0cH8dFYTaK9bHgueW7VNmXG85ciCks+EwIIRlBTgnAxsZGHHzwwdi4cSMiScLjs88+wxe/+EWsWLECv/jFL/pdRkNHuJt1L5kip0llN+YaYhEV93YwrAkqcQGnQgxrJXla4H/B+Seh9Y//TN9GGAwInn8aVm9vwYIpWnyZCO9yl1WJwdq2gNo+EeVS8NtiApw99kHiMv2hqNoHGYugj3i6tr2bpbAP9zbpTk2rDzf+dw1O2L0Cpy2u4uEhhJAMIacE4P/+7//2En9CNN6H9oYbbsDxxx+vRGJfSO9gTyCiXItiQUpG3uche5EyKiKStCGqxTfGB/1IiKVMRJZMS0ZEU3mBJZGAYZ09FY6j9oPvjY/TYgU0OGx4uGg6brjyUew/rxzfOGEBzjp4JmwWk1r39BI72nxh5YpO+X2DQQk6iQ3sKWwDYsFMWAojCYui5t7WxKC49p02E93HSYQjUVz3yErk28z48anzKZYJISSDMMT6qvuRRHt7O9xut3KZTtTej2L9q6qqQjieJZoKs9mMc845Bw8++OCglimHTrkRQ5rlS9yL4nacyOiWMJWlnCT2ZCxu7uTkFU3siTXNAIuK7zPCFBd4ta2BhJvcZTehKM/cSwCEttZg+yEXIubviskbLmX/9wM4v3ginl26DXc9twqvLqtBmcuOi4+dh0uPX4CpZflIZy07EYO6KBRrof4wIMcgz2ZEntUEu9WYc+7/ZO56fZPK+pWSL/sw65cQQkadoei1nBGAL730Eo477rgB56uursbOnTuRrcjpjsVFTLIFT38tFi8d0S6ay1QTemb9dbwkTX+0eEJo80VQmm/pVxR3/Pt51F8+gu4CRgPyTjkcFff8opvAXLujFXc9vwr/fG09Ov1hnLTvVFx24gIcueekUSkDIyLZG4jCE5QEGM1CLJsjlkERg2IdlCSgXHEZL9vWiov/9jG+duh0fPvoWeO9OYQQkhO0UwD25uWXX8axxx474MGbNGkSduzYkfIzbyCiSrp0L67cvTbfWN3glZCLAZGk9m4yFmHX7b3qCNI1LVVBaT1ZpafYG0kpGlXUOqZZCQei7b4n0fj9W7RK1UOsD5h38mGouPvnMFhTFxXu9IXw4BsblFVw5bYWzKl24ytHz8W5h85Kq1Ww576L9VNCBUQM+oJRJbq1mo5dgjBbs41FcH/hjg9QnGfBvV/bl1m/hBAyRlAA9pH9Ky7gQCDQrwv4vPPOwwMPPJDy8/r2IHyhaO8+un30w+02vdeL1CWTe9XMS3odjYsqXdD1hS5MTbowjXcAEfesvm3KhRuvO5gJVinf+5+j/vIbEN62SzuI/R1kkxEGsxklP/smXF87a1C9f0WUvbO6Dnc/twr//XCrqgV4yMJKnHf4bJx54HQUF9gxWsh5ExEoglAshJKMIkhJHEkayjZ38Q8fXYFXVzfgP9/an1m/hBAyhlAA9sGll16Ke++9t1cSSDIffPAB9ttvvz4/l4QRqfMnia5BiY0La4WeRZDJDd1pMakbvq5ferVL6/VCXsYGbLMmdBNzydZHJfZ0C+TErS0Y9QXQ+Z8X0Hr3fxBau0WbqHYoXmdHjoE7H66LTof7kjNhnlQxrPV0+IJ46v2teOjNDXj18xoljI/fazK+ePhsnLzvVDhs5lFPjvDEBWFPd3GB3YwCm2nCdit57OOd+PmTq3HjWQtx2uLq8d4cQgjJKdrpAk6NxDAedthhqtyLnvkrmEwmJQp//etf45prrun34G5v9vfZl7fIaYbbkVOJ1aNGeFcjAsvWqp7BsWgMpmIXbHvOhWX2VBhM6Uu02dXixSNvb8LDb23E0vUNKHBYcPoB03HeYbNw+B7VMIupdBTR3cUiBKWQuFiYRfpJ3KTLblYJJRNF0Eurt6/+bSlO36saPz1twXhvDiGE5BztFIB909nZiVtvvRW33347amtr1bQjjzwSV199NU466aQBD25nIIzGztSZxFVuC2zmiZ0FnMtsqGlTQvChNzZgQ207KgodOOeQmTjvsNnYZ3bpmAixUDiK9ngPY3EVi6U3326Gy2FSWeaZKgYbOwI4784PUVVoV1m/yeV0CCGEjA0UgIO0vHR0dMBqtcJuH1r8l5T+2NUe7OWmVW48i9SEMyl3XqberMnA18YnGxvx0Jsb8cjbG7GrxYfZVS4VL/jFQ2dhdrV7TA6hlJfp8IdV20HJzpZ4TRGCYhmU+oOjQWhbLXxvLEXg87UIrtmCmM8Pg90Gy5ypsC2eD8che8M6a0r374SjuPTeT7C92YuHLtsf5S7bqGwbIYSQ/qEATLMYaPKElfUlWdRJHKCIQD0ZI88q9fCkBZrWD1hCuPJtJjXQGjJxkXi9N5bXKDH45Ptb0OELYZ/ZZTj30Jk4fu8pmDvJPepCX65BcQ2r/tP+cCLeVOIFRRDKdTdSvG99jNbb/gXfax9qAahiyQ4nxcrKe4mdjQH2Q/ZG4bfOQ96xB6qPfvn0Gjzy8U787av7YPHUwhFvCyGEkOFBAZjmm29jZ0gF7YsIlFZmkj2r137b1RZUMYGVLqvqOKGLQ+kYIYN+sxYhKBmf2ZLpmYv4AmFVaFrE4IufbFfneVJJHo5ZPAlHL56kagyWukYvm1iQBCNJHunwazGDotXkupR2dwV2U6IQ92CJtHWg8cd/ROdDz2vVvQdThic+X97pR+Ldr3wFP395C35y6nx8Ycnk4e8YIYSQEUMBOArITbfZE4LcHoudZiXoxPIjBZTF6ic3356WIBGP3mAUHYGIcufJpyIC5bsiCukinrh4A2G8vbIWL3+2E698thOrtreoEIC9ZpbiqEWTlCg8YH6FakU3WkjNR3nIaPeF1XWmX19iFdSvz/6QTiw1Z34H4Zr6IddfFJoLXLjs/Ctw8rxiXH/hEl7PhBAyzlAAjuINV/rAyk1XBJx0uRis+02EonyvIxBW91opuKy7iIdqtSGZx84mD15bthMvL9uJVz/biYZ2P5w2Mw7bvSohCOdPLhw1kSTXlx4vKC3qJF6wMJ6Vrlusu81fU48dx38DkYaWYfdi9psteG3BYhxXuxEznr0dlhmT0rAnhBBChgsF4CjjC0XQ1ClCLqZustLrdrA3drEKquB+VQNOs7pIbKEIwUzO8iSDRwp1L9/ajJc/26Gsg++urkMgFEF1iRNHLxJ38WQctWc1ytyOUTmscn21ekNKDCJeUkZKFNnj11csGkXN6VfC/9GKYYu/bphMsC6cickv3q0KdBNCCBkfKADHAInFavWGVckO6fEqba/0GMDBIgJSxXNJi7lITIVW6VbBdAT2k8xxF7+zapcShK8u24kVW1vU9MUzS3DIblXYa2YJFs0owbzJhWmtOyjXV5svrK5Tub7Eal3otAAPP42ma36HdFP8o/9B0XcvTPtyCSGEDA4KwDFESsI0eUIq81cseWJpGap4E6ug1HzriLcKky4iklUs7jtmEGcfNc3iLq5RgvCDtfXYXNehptutJuw2tVgJQxGEi2aWYPdpxcqVPBSWbW5SySiSoKJfX5LEJFZBTyAKtHXAdN63YdixK637ZXDYMH3VUzDmO9O6XEIIIYODAnCM0W+wLZ6Qygh2O0xKvA0n41csixIrKJYbiRUUt7Asa6jWRTJxaPME8fnmJny2uQnLNjVh2eZGrN7eqix40hJu3iR3QhAunlGqxkX5fdfaq77wAeVyvvni/XDpcQu6tZVr+e8baHz5QxiefBkGjze9O2IwoPTX34P7q2emd7mEEEIGBQXgOCHiTYSbxF7JPVfiAweTjdmfqJTlifvObjbC7TSpMeMEsx9/MIyV21rwmQjCTY1KHK7Y0gyfNKEGMLUsPy4INWG4cEoRJpfmIxiOoPT8+xLLOXB+Be6+4rBE8eqaL14N3+sfSaBi+jfaYIBtn4WY/Nyd6V82IYSQAaEAHGckI7NF3G3B6LDjA3uWkhEhKG5mq8RxOcxMGMlBIpEo1tW0aaIwYS1sQktnQH0u2eQVRQ7UNHVZ9uRBRCyA15y9GNeeswg7F56GaKvmch4NDDYrZmx9Ma39mgkhhAwOCsAMQbIxm0cYH9izG4QIwUA4psrIiGtYYgVpEcxd5LrY1tCJ9TVt2LyrA2+sqMGj72xOOe8BM4twz/23jvo2TXnnAVjnTh/19RBCCBm+AGTNhlFErH5VbqsKvBeL4M7W4LDjA0XkaT2GTUpYihCUDiWtRhGCgyv8S7IPOefTygvUIGJQsoh1ASiWPylJI32D95ldjm8fOQMx8xeABx6HIRQetW2KtLSP2rIJIYSkBwrAMbhBSx02p82oRFubT2vhVeS0IM82POudCEu7xYpAWBOC0qu41ReGy661A2O7ueyLLZWwgnC0+zgUH4vIk5aD0hZu9U5NfMlltd+8Cpxx0EwctXgKnFYzDNEIoqbDgH8/A4yiADQYmbBECCGZDgXgGCGiTERfgc2MZm8IjZ4Q2v0jiw+0mY0oL7AiGNGEoHQpkbH0hZXi1BSCmY9Y7STbW0Sd9JZOiLwkoSeZ5clIYw/p7iGDhBZI7J+ca4n3u/DI2Zha6sTJS6ZhUokz/pn2IBJpbMGWL14x6vtkKi0a9XUQQggZGRSAY4zctEW06fGBu9qDIy71YjUZUZZvRaEjqjKQpfCvtAUrdlqUQKBreHwFnmRxh5Itdz2secmI5c5i1MSdCPw8m0G1dVOCLz7uT9jvMa1IDX0JM1N5MSL1zWnfz8T25zlgnl49assnhBCSHigAxzs+MJ7hK0JQdWqIC8HhiDZJMCnJN8LlMKHZE0ZDZ0gtU6yMIibI6KIX9BbXvBpC2utkiZcs5uQ862JPn6Zb60aCiH+xKiaLRlN8ufb99oDnubekTQjSjtEI294L+MBBCCETAArA8Y4PtJlUJq9k+Irlrq4jpErHiEVwuNY7EYIVLquqGdfsDaO2LajWI3UJRRCQ9Ig9ycbWhJ4m+ET86WLPolvw7GY1FiutJICPhTVWkoNS6TtZs/N7lwBPvzE6K45G4fryKaOzbEIIIWmFAjAD0DN8xRXsl8QOb0RZ70Za6sVhNaHaYlQt5kRcSt9ht5PxgcNJwlCWvbjQk3Mk73VEsEumbYHdqCyuIviSu2+MNSL2JdmoJ7LFzlmTEaguQ6S2UVRsWtdrLCxA/imHp3WZhBBCRgcKwAxCRJ7DYoLD3bvUi7h15cY+nPIxkh2cZxVREFZCUMtCHr6FMZuRjFrNhdtl3ZM6jjoi8FRXFhF7FqMqzJ0pyTZ60fBkcZpMpcuqMtJNN1yBuq/9NO3rL/n55aoQNCGEkMyHAjBD0Uu9BOOlXiSmr82rZfgOp9SLZINKLKB8l/GB3QWfNxSFNxBRbnhJ0BDk6Iq4s1uNcJvFsqdZ9zJNMOsFwkXUSw9pySkRi6QYIJPzS8oLLEr8CfmnHYnO04+ER1zB6YgFNBnhOGxfFHzppJEvixBCyJhAAZjhWM1GlBVYUahKvUQSpV5EyIllT4TdUMj1+EA9UcMbjKgEHLG0CuJuF4uoEnpi2TNlntjTkexh2X6x9slYhJ6cOwkXEJEn+yCFx5s6tVp/pfkW9eCQTPkfrsXOjdsRXL1pZCLQZIJlWhUq7vhJxh4vQgghvTHE5I6YxtYiZPRv/u1+KfOixXiJEJRhOC3m5NTr8YFyFWRrfGAk2l0wid6RXXRajFp3FZtx2C36xtLKp2+/7uIVi6Rsf55NRF93wSrlZbY1+ZUoLMm3pFxupLUDteddDe+na7B+2kzM27xBWT4HjcEA64KZqPrP72EuLx7pbhJCCBkh7AWcA4io0YWgWIBEABTYtbi+oQo4WZZ0EpFliSWpOE+Wo7kLJ3KGriS9iGCS14i7dLV2ekaVcJPJFispCq0En+xDKKoEupRycdq07Zf9GMj6K8dhoH2MhcK47/bn8LChCP/3q5/CFAoNvHEmExCLovA7F6L4qosY90cIIRkCewHnAHLzl84iYuERoSDxX5IwIvf7fKtJuQIH68aUZZUkxQfWd4SQZ42omMGhupgzyS0qmy5Cye3QBJPUw8vkTGNffNtlH/RYRIkF1RJ2elv5BmIw8/pjBjyTX4Vjy6wovvh0tP/zacS8fu3gSUs3UZ6yHDmg0SgMdisKzjsR7q+dDev8GSPaZ0IIIeMHYwAnOGLtkxg+GcRqJEJQBnHtSlxbgdQZtA1sLRKkVl1FgUV9X2INd7YGlDAcj2xhic2T7e9ru/tzi6oaijajytbNVCuf3iFE334Rf7IHYoGV412SZ4Ij3uZtNPnvijp4ghFccOQ8lJ62J4xXXYK7XliNr7dsQnTDVsQCQRisFlhmTYFt0TzY914IY75zVLeJEELI6EMBmEVIHFuR06i6iajM0ICW6CGD1BIUkThQlxH5TFzJUkNQWtVJPUJxl4oQHCsLmnSyqGsPId9mRKXb1i1jV/bJk8ItKvs9GLdoRmQci5UvoPX9FeT4FudrpXpE9I6VaJVEoP98WoMTFpShvMCmHiCueWETtrVEcdiJx+HgmYzrI4SQbIUCMIsLS8sg8X26VVC6jIiFSbcY9hR0UvdOEkJ0sSc9i0VsiRDc2RZAsdOsvjeaAkXWJ+JPex1FOCKZupKsElaiKTZCt+h4dgrRYxFF5OXZNMEqVr7xSrp5asUuZf07b59JygV9yysbsa3Fpz7b2eofl20ihBAyNlAAZjliEROXqGT3igARIagKQvvCyvIkgk4XIWJ5E8thbVsAlW6rsiiK+1gEl7iEmzxh5WrtK6s0HRYpKUujI3Jpa1NAjbWexlqZk0zL2NU7hYjbWu8DnKpTiMsuos8ISwb0Zdasf7UJ699f3t2K19Y3qc9Ejq6r7xzvTSSEEDKKUADmCGIls1tkMCohJZY2EYPi4pUbvnwmljZB8g9EiEnnCKlDKCJSasmJWBwt/MEIalq7xJ+O5CFMKrSp7cgEJnKnkJ7WP2/c+vf4slolBnVkb9bUUQASQkg2QwGYgxjjcX4yBKXcSEDiBcPqxq8TTRKBImQEEY99EQqF8Nhjj+HPf/4zli9fDqPRiIMOOgiXX345jjvuOPW+L6LRKHakEH+CXrNvPBD3uW7RC4S01xOtU0hf+/XE57tw7Pwydd7vfHtrr3nqO4PKIizXCCGEkOyDv+45jmT+Wp1GxBBTnUaSEalT2x5Eab7E/vV9qTQ3N+PEE0/Ehx9+qISeCDrh+eefx9NPP40zzzwTDz74IGy2roSOnkhMXCwKSJRfOKKJlFi3jGDjqMXqSTKGlJGRsQg8XfDpSRoi6UQET5ROIQPx/pYWNHlCOHX3ClS67DhzUSU+2NKKnW1a3J/sliTYrG/wYO8p7vHeXEIIIaMABSBRSDmSvhBx1J+AOuOMM/Dxxx+r97r4U98La63InnzySXz729/GX/7yl5TLENFYlZTtqy9X9JcIQUmaGA6yDNl0Je7iAk/GoWg08b5nFzRJIhZ3swhSsXiK4BvLzNyx4JmVdZhXnofZZXnq/WWHTMfxC7z4xkOf4+zFlSrpZ9WuTiVyCSGEZCcUgEQhIkcXP3LjF4ubjI0DlFV588038dZbb/U7j4jCv/71r/jZz36GyZMnD+qIi+AS/dFfWReJx9OtdslWvORxsnSVJUl2s2RCy346jbKfhsQ0GWdivF462dXux8fb2vC9I2d2m/7C6nq47WZ89YCpyipMCCEku6EAJAop+TIcRNiZzeaEta8vxMp377334sc//nGfWbQy1hpOxMdx92wkorU0S/5cpsc9tAlEt1iMRiXkxE2rizoZ6wI3myx5w+G5VfWqxuPhc0oS04LhKF5a04jjF5RR/BFCSI5AAUhGxPr16wcUf4IIr82bN6f8rLEjhHZ/9/jDnkjJGhFwSsiZuyx2yeNcF3cDITUVX1jdgGPmlcJh6crofnNjk6qzePJu5eO6fYQQQsYOCkAyIpzOwbcF6ysJROoKStePjkDvsirqIjUaMKmo7wQSMjje29KCZm8IJ+9W0W36syvrsXiSC5MKHTyUhBCSIzDYh4yIgUq86IiV8Nhjj035mRbnJ4WoI73En7pIDVomsLh+yfB5ZmU9FlbmY0ZJl2jf0uTFitqOXqKQEEJIdkMBSEbEJZdcApOp/wLRIhArKytx6qmn9jmP9POtcFmU2OuJiMIdLQFsavRjS6Mfu9qCqmWdLxRRmb5kYKS12yfb23oJPRGFhQ4LDppZxMNICCE5BAUgGRFlZWW4++67+77AjEY1/Otf/1LJIv0hRYenldiVOziZkjwzJhfZUF5gUa3gJAGkqTOEnS1BbGzwY3uzHw0dWuHiUCRKUZiC51bVocBmwmGzu5I//KEIXl7boJI/Mq29HiGEkNGFMYBkxFx88cXIz8/HVVddhW3btimLoKrjF41iwYIFuPPOO3HIIYek/G67L6wSO6Tmnir9YjSg0m1TYq6+I6QKEkvJFvk8uROJLF/asYlrWAapY6gXshYtY0/6jmQEZ3t5l/4QUfzCGkn+KFN1DXXe3NAETzCCkxYy+YMQQnINCkCSFs455xycddZZePnll7FixQpl9dt///1xwAEH9JmdKyJO4v58oahqo1bolI4jJjW/WAMlU1WEoMNq7Le3sY5YBiWJRBeFzd6wEpCJHr3xws4yzrbizv3xzqZmtPnCKd2/+0xxo8ptH7dtI4QQMj5QAJK0IaJPkkJkGAwiwKoLrcp6JzF9de0hNBnDcDtNqiixlHcpyrMMev2qJIzNhDybKSEwpb6gP5zaSphn1eYVgZnNFkIRertXFWBqcVeW76ZGD1bXdeKnJ8wd120jhBAyPlAAknFFRKCIMBnEetfqC6OpM4wWTxguu1mJweHGp8mybRatKLQ7rn2ktZyIQV8wqtyfUn9QpJ+IQLUdVpMSnhMd2U9xp+9s9WHZznZce8zsXqKw2GnBAdMLx20bCSGEjB8UgCRjEKFWYbGiJC+mhKDEB8pY3MIuh0kVgx6p21ZEkS44S2FRXTBECHoCUTR0hNCAkHIX62LQap54ruKnlu/CHW9vxYKK/EQv4wNndGX5+oIRvLK2EafvWQkzkz8IISQnoQAkGYdY4ErzLSh2mpWFTuLXalojysUrQrDAPnyrYE9U72OzEUVOzWrmjYvBFm8YzZ6wWqfTZlRicKK4iqWXr+yL1PfT+dJ9n+DA6UX4zhEz8PqGJlVCh8kfhBCSu1AAkozFaNQSQ9wOk3LbihjUhZnTalQu4jzbyK2CydZBST4psGvxg5Kc4glogrDdF4GsRtYrYlDqFoo4zETmluf1mibC9sOtLYhEpysL4ZJphahwsbsKIYTkKhSAJOMRgedQFjgTyqIxdAYiSpDtag+qwtFiEXQ5zN1KnKRjnU4RelYTSvNjqhi1iEFvIKrK06AjpErNSF1CWb/WzSQzmFbsVOJUsqJ1xA38y1MX4POaDmxs9OKyQ6aN6zYSQggZXygAyYSzCorYk0Hi90QISqkYye6V2D2ZLjGD6RRkKpnELIMRxXlauRlvIKKEaGNnSBWlzktjnOJIkX2fWeLEugZPfPuBn504V1kGL//PCuxZXYBFk9zjuo2EEELGFwpAMmGR2L3SAiNK8s3wBEUMhlUiR2NHSFnmXHZTosB0OjEniVARgx2SsOKPjFqc4nAQsacLwP89cib2m1aE9zY3Y0ODB789Y8G4bRchhJDMgAKQTHhE4InVT4ZwJIZ2f1gVmJZBXJ/KRRyvK5huRPBJrUKJVfTHLZJ6nKIkjYgI1YtbjyVuh1Y/8fQ9KnD8gnIV0/jAhzto/SOEEKKgACRZhYi84jwLikSQ6YkjHk2QiTUwL17vL92dQFScokVcwElxiv6IKm7dYAiNSpxif5y7V7Uqpi2lXoT3t7RgQ6OX1j9CCCEKCkCS9YkjksShZfNGlBBs8mj9h7VsXmPa4/Z6xSmKNdKXFKdoNysXdTriFOvq6vDSSy9h6dKlWL9+PYLBINxuN/bcc08sWbIEoQVHw2Kx0PpHCCGkG4aY+IYGoL29Xd1U2tra4HK5BpqdkIwlKuVdpAuICMJgBJEoVCaxZPtKSRkZj0ZGr/yb6XGK0pJO1iCu4YJhJo4sX74cN954Ix599FFEIhEl8kKhUKIlnyxPppeUlODib1+Nz8uOUNY/Jn8QQkj2MhS9RgsgySmkkLPeCUREWSAcL+8SFHet9AkOKUGmdQIxwpIml22fcYqtWpyixBCKm3igQtPhcBi//OUv8Ytf/CIh8gRd/AnRaDTxuqmpCbfe+GNMnrs7GubdAkw6Ji37QwghZGJDCyAhcUKRqKrzJ5ZBsRKKaVy5iuNiMN0ZxSJAJU5R2t1JsWkxPLod0v/YnLLIdCAQwDnnnINnnnlGfXcoiFVQvnPPPffgkksuSds+EEIIyRxoASRkGEjZFrdTBjOiUusv3glE4vdavV2uYhGCMkg830gEYXKcosQKSsu7Vq82iDVQrIJS6kYQ8faVr3wFzz777JDFX7JV8NJLL0VhYSHOOuusYW83IYSQiQ8tgIQMQE9XsbxW/zwAbHExKF1BZDzSUjPSw1eEoAwSnyit5ySj+dF/P4gLL7xwxOdKRKfEhaxZswaVlVqGMCGEkNyzAFIAEjJMQSjuW33Q266J61ZZBy3xsdnYb1yfLKu2LaisiVK+RrcoynSJERRroLShO+WIJVi3ZtWwrH89MZlMOPfcc/Gvf/1rxMsihBCSOVAAEjLGSGKHEoNhTRAGQloMoSDiTncbKyuhsct1LBa/zY1+9dpqMqDSbU24fQURfH+79358/WtfTYv4SxaB27ZtQ3V1ddqWSQghZHxhDCAhY4y4fvNNJuTDlNJKKKVfpA6gIB3ixDKoFaPuWoZY+rY1B1Cab4HboXUPkeEPv/tt2rdXtu++++7Dddddl/ZlE0IIyXxYBoaQUUCEmz3uBtYRN7FYBpWFMKyJwlCkt1WvsTOEVm8IVYU2BLydWLly5agIwLfffjvtyyWEEDIxoAAkZKz+2YwGmOM1CHWaOkOqd3BPwlGgzRvGms8+G5VtEQH40UcfjcqyCSGEZD4UgISMI3rySLJIlBIw0pVE3MRvNzaO2rqbm5tHbdmEEEIyGwpAQsYRqS2oiz7pEmLtUVswnYWne63bmJ4uJ4QQQiYeFICEjCNlBVaUFfT9eVVV1eitu6xs1JZNCCEks6EJgJAMZtGiRaNiqZMyMPvvv3/al0sIIWRiQAsgIRmMw+HAvvvui6VLlybauaUDWdaRRx6pxlKuRmIRpZZhKD6EI1FVpqa6yJ62dRJCCMkcaAEkJMO5/PLL0yr+BKvVqlrLbW7wY02tFxvqfNjS6MfOlgAa2oNo9oQTdQsJIYRkHxSAhGQ40rZNYgHT5QqW5Xz9619HYWGhqjUoiSjJ6HnJJfmWtKyPEEJI5kEBSEgGI63i/vVpPQ7+6b/Ro2LMsMWfiMlf/vKX6r3TZsLcSmcvESgEQhFVtJoQQkj2QQFISIbS5Ani+4+vwr+W7sTZS2bg+1dfNWLxZzab8dBDD6GgoCv12GE1YVa5A8kaUPoXS4Hq1TUebKjzqs4k6exFTAghZHxhEgghGcgn29tw0/PrIV7f3525EIsmu/HFvX8Nn8+H2267TdUHHIogE+Enmb9PPvkkDjnkkF6f59vNmFHmwKYGn3o/udiu6hK2esNo7AyqWEGryYAKtxXF+RYYR7E+ISGEkNGHFkBCMohoLIYHPtyhLH8zS524+/xFSvwJIvr++Mc/4h//+Iey4ImgGwg9blDKyXz66ac4/vjj+5zX7TRjWokdbodJFaY2Gg1K7M2tzMO8KqdyF29vDmDlTg/q24PKPU0IIWRiYogNwozQ3t4Ot9uNtrY2uFyusdkyQnIMfyiCX7+0EW9saMJF+0/GBUsmw2TULH1bWrx4fWOTag/3pb0mY9euXfjTn/6EO+64Ay0tLUocipVPJxQKqfHixYvxne98BxdccEG3z4e/jVHUtQVUlrBsW3mBBaUuq+pmQgghZHwZil6jACQkA2joCODHT6/F9lYffnjcHBwyq1hZ2NY2dOLjHa1o9YfVfOX5Vnxx0aTE94LBoKoR+PHHH2PDhg3qvVgHxeK3ZMkSzJ07d1S2NxgWIRhEU2cI4g1WHU1cFlhMdCoQQsh4QQFIyARi9a4O/OTptTCbDLjplPnK9fvpzjZ8srMNvnD3LNxDZxRjcbXmEs4EQuEo6juCaOwIqfIxpfkWlLussJopBAkhJJMFIJNACBlHXlrTgFte2Yh55fm4/uR5KHJa4AmG8e7WlkQ9vmQqC2zIJCxmIyYV2VHhsqGhI6gGEYMSO1jhssJmoRAkhJBMhAKQkHFK9vjru9vw4Mc1OH5BGb535MyE1SzPasbpu1XimTV1qi2bjoTZleVllgDUEeulFJUW619jRxD17SHlHi7KMyshKKVmCCGEZA4UgISMMd5gBDe/uB7vbmrBZYdMwxf2qlJJHMmU5VmRZzGhLaLF/okMLHFaVeJFJiPbV+G2qZhAEYB17UG0eLxwO8yodFtVJjEhhJDxhwKQkDGkviOAHz61BrvaA7jp1Pk4YEZRr3lCkSj+u7oO/nAUX9izCh/vaMPGZi+qXfYJc66khEyZy4qSAgtaPGGVObx2l1eVlxEhKHUHCSGEjB/8FSZkjNjZ6sNVj6+CAQb86dzdMaPE2Wseyfx9dk296gJyxu5VqCiw4cT5Nqxv9EwoAagjBaOlp3BxnlkVld7VFsT6Op8SgpOLbbBbaBEkhJDxgAKQkDFgU6MH1zyxGnk2E245YyHKUiRzSFzgi+sasKPNh9MWViYSPsQ9PLcsf0KfJ9mHojwLCp1mtPnC2NkSwOoaL8oKLKgstLGOICGEjDEUgISMQZmXHzy5Wlnzfn3GQpXp2xMp9iyFnjc2eXDi/HJMKXRk5XkRIVjotMDlMKtuIlJLUFzEVYVWZSnsGQtJCCFkdKAAJGQU+WxHG3703zWYWZqHm0+bj3xb6n+597a2YGVdB46eXYpZJXlZf07ENVzptqEkz4KdrQHVYq6xM4TJRTbGBxJCyBjAIl2EjBLvb25Rlr+FlQX4zRkL+hR/n+xoxcc723DI9GIsrCjIqfMhdQSnlzowt9IJsf1JfODmBp/qNEIIIWT0oAAkZBR4bV0jfvLMWiyZVqiyfR19JDtIx493trZg38lu7DUpczp8jDUSGykicGqJHZ3+CFbVeLCrNYBodMBW5YQQQoYBXcCEpJlnVtTh969uwtHzSnHtsbNT1u6TmL8Pt7eqYe9JbhwwtXc5mFxD4v8kDlASRXa1BVTGsNQSrC6yqWmMDySEkPRBAUhIGnluZT1+9+omnLZHBa48YoaKdUsl/t7e0ozPatpx4LQi7Du5kOcgCRHM0l6uJN+KnS1+bGn0I9+mlY1hRxFCCEkPdAETkibe3NCE3726EafuXoHv9CH+pNTLqxsblfg7fGYJxV8/2C1GzCp3Yma5QxXHXlPrxfYmP8JJ7fEIIYQMD1oACUkDn2xvw03Pr8fhs0uU5S+Vu1KKPL+0vgEbGj04Zk4pFpTnVsLHcJE2cgXVeWjoCKm4wBZvSPUdLmXZGEIIGTYUgISkoc7fj59eg72muPGD41LH/IUjUTy7th7bW32qzl8ulHpJJ2JNrXBZVUeR2tYgdkjZmI6QcgsXsK0cIYQMGbqACRkBm5u8uO6pNZhVmoefnTQXFlPvfykpafLUqjrsbPPj1AUVFH8jQI6vZArPq3RCDvWGOh92NPuZLUwIIUOEApCQQeILRvD5zvbE+13tflzzxCqU5lvxyz5KvXiDETy+shYNngBO360SU4t69/8lQ8dpM2FOhROTimyqgLTEB3oCER5KQggZJBSAhAySf39ag+8+uhK3vrYJ9R0BfP/x1bCZjfjN6QtSuiEbOgN4eNlOdAYiOHP3KlS77DzWaUTiLMtdVsyvcsJoBNbt8qK2NaCyrAkhhPQPYwAJGSTLazTr33+X1+HF1Q1wWI247Qt7oDjP2mveDU0evLSuAUUOC05ZUNFnFxAycuwWk3IJS91AGdp9YUwrtavphBBCUkMLICGDQMq3rN7VqV6LfckfjkIMTR2BcLf5xPr00fYWPLemHtOLnDh7jyqKvzGyBkpmsHQTkWxrcQk3tAdpDSSEkD6gACRkEGxv8cEX6t6fttUXxhX/WaHcwXqm7wvrGvD+tlbsP6UQJ8wrS5kUQka3pdz8qjzVUWRHSwAb69lXmBBCUkG/FCGDYFWtZv3TkUovUprk+AVlKHJa0BkI45k1dWj2hnDivHLMLmWZl/HCaDRgSrFd1Q/c1uTHmhoPJhfbUZTHdnKEEKJDAUjIIHhjQ1PidZ7VhLMWV+KMPauU+KvrCCjxJ9X/xOVbnm/jMc0AXA6zsgZKmZitTX60+cxKGJpNves0EkJIrkEBSMgg2NHqUxm/Xz9oKk7crTxR8mVtfSde2diIUqcVJy8oR56V/1KZhIi96WUOuD0hbG/2Y3WtR9URFOsgIYTkMvwVJGQQ3P+VvZSFT2/xJvF+b25uxsq6Dswry8dRs0tgllokJCMpyrMg32ZSlsBN9T4VIyg1BFN1bSGEkFyAApDkLOEo8NIm4JNaoCMI2EzAJBdw+jygokcIn8T76bT4Qnh+bb0aHzW7FAvL81P2/iWZhcVsxKxyhyocXdMSQIc/jOmlDpU4QgghuQYFIMk5Wv3AfcuA+z8HGr2AOclwF40BN78NnDAL+PrewN5V3b+7vtGDV9Y3KFfvuXtWozRFDUCSuYhQLyuwqsLdWxt9qni09BiuLLR2E/mEEJLtUACSnGJLK/Dlx4GaDk3s6ZbAnrywEXhuA3D9EcBFi7pq/L21uQkzip04clYprMnKkUwo7BajqhlY1x5EbWtQWQNnlDl4TgkhOQMFIMkZajuAs/8jLtwu8dcXkfjnP31dsxB+eQ/NenTRPlMYN5YlyPmsdNuUNXBzgw9ra72YXmpHARNECCE5AE0YJGf49nOa+NPF3WD50avAmkbtNZMGsrV4tFO19ttQ78OuNvYTJoRkPxSAJCdYUQ8srR26+BMkUfT+ZaOxVSRTMJu0BJEKt1W5hDc3+BEeyExMCCETGApAkhP843NguPV/RTQ+shpo1zq+kSx2CVcX2jCzzIFOfxjraj3wBSPjvVmEEDIqUACSrCcWAx5fMzzrn04gAry8KZ1bRTIVt9OMeVV5Kit47S4vmjtD471JhBCSdigASdYjNf78IzTkiPWw3pOuLSKZji2eJVzkNKvi0dJOjhBCsglmAZOsJ1WZl6EiJeKCaVgOmTgYjQbVNi7PFkKLJ6zKALHgNyEkW6AAJFmPyzbyZUSigDsNyyETCxF8pQVWNRBCSDZBFzDJeqSO375VWjbvcJHwwQMnp3OrCCGEkPGDApDkBBcvHrj4c1+IcNyvGphbku6tIoQQQsYHCkCSExw/CyiyA8MxAopw1NvBEUIIIdkAYwBJTmA1Ab88CvjWs0O3/h0yBThxdvfpWxt9aPaEuwlK3cDosBgxvzpvxNtMJgbb2oAfvAKsagCmuIAbjwQWVY73VhFCSP/QAkhyhpPmaDdnEW2GQYq/vSqBO0+WFnDdPyuwmxKiTx90rOYRBBuSCYU3BJz3KPD+DqDFD6xoAM57DNjRPt5bRggh/UMBSHKKC/YE/nIqMKlAe9+zO4guDi1G4II9gH+dBeTFE0BbvCFVCkQozreiyp06M1TaiZHc4LNdwM6OriLjEi7gCwGvbB7vLSOEkP6hC5jkHMfOBI6eAby9DbhvmdYj2BPU3MRVBcD5uwHnLAQK7V3f6QiEcdf727C42oXj5paqGnEi9DzBCNp93atMSy/ZSUUGOGSBJKvpK7N8uG0HCSFkrKAAJDl74z5smjYMhgKbGSfOL8MLaxvQ5g/hjN0rYTMbMa3EgTW1HoTiJqCqQqtqHbam1ouyAgsq3TaYqQayFgkRmF0MbG7RrIByqvOtwLGzxnvLCCGkf+gCJmSQLKp24dxFVahpD+AfH+9Emy+kxN3McodyG+fbTErwSQJIdaENTZ0hrKrpRENHMOE6JpmNnCYp+h2KAP7wwF1kbGbgobO0+NKZhcAhU4FHzwUqmANECMlwDLFB3Jna29vhdrvR1tYGl8s1NltGSIbS6AniP8tqEY7GcM6elahy2eENRmAxGWBJyhYJRaLKHSxC0G4xYlKRDS4Hje6ZhPz6xeKxeyL89B9DQ9xKLEXEpQ0gIYRMBIai12gBJGSIlOZZ8ZV9J8FtN+Ofn9Rg5a4OOK2mbuJPkPfSS3ZepRMmowEb633YVO+DP8Smwplg5QtGgEBEG4ulzxAXfDaTZtmzmCj+CCHZCwUgIcMgz2rG+XtVY155Hv67qh4vrm1ApI9WI06bCXMqHJheqlkK19R4sLPF3+f8ZHRduyL6RIPH4jF7kqsjok/GtPgRQnIF+qMIGSZi4TtlQTkmuex4eX0jdnUEVHKIy97738pgMKAozwK3w4z69iDq2oNo7gxjcrENhU6z+pykFxF4orGVezeuteUoi+gTY60q+ZN02CUaRtz64Yg2+MStbzaq80YIIdkGBSAhI0CE296T3ah02fDE8jr8/aPtOH23CkwvdqacX8rHVBbaUJxvwc6WALY0+pUAFCHY04VMhh/TJ9Y+XfShH9En7GoNYFd7QH2nJ2IRpAAkhGQjvOMQkgaqXXZcvGQyKvJtePizWry3paXfzF+r2YgZZZpbuMMvbmEvWj0hnosRWPpCSTF9kR7uXYnnk6SOVIZWg1ETjKmYUergOSGEZCUUgISkCUkEOXdxFQ6cXoQ3NjXj0eW74BdV0g9iXVpQ7USezYTNjX5safAp9yMZnPALxQXfUEVfMuUFVlhT1GoszbfA5aT7lxCSnVAAEpLOfyiDAYfNLFblYba3+nHv0h2o6wj0+x1x/c4os2NaqR3t/jBW13jQ5g3zvAwig1dEn4g8ad03FNGnEwxHsa3Jj2AP0S3u4klFSa1gCCEky6AAJGQUmF2ah68umQyryYgHPt6J5bUdA8YSFos1sCoPTpsRmxp82NJIa2Cy8AvHhZ+ewWtOEn0qvm8IeTRSo3F7sx8rdnaqHs9Tiu0ozusKiZ5a7GAHF0JIVsMkEEJGiUKHBRfuMwkvrmvEM6vrsbXFi2PmlMIuiqUPJOt0ZpkDzZ4wdjb7scbvwZQSu8oezkX0As26gU4VZzYMzcqXTDgSxa62oOrOIkjnlgqXVdVpDEfMaPN1Kld+UZIYJISQbISdQAgZA5bXtuPldU2wmg04cX45ZpakzhJO5Z6UJJGSfAsmF9lUFnGuJHWI6NNLJUqI3khq9ElcZX17QJXfEcpdVlS4evdpDoWjSgzmwnEmhOR2JxA+5hIyBuxR5cK0IieeW1OPfy+rxaKqAhw1pxQ2UTX9ZArPKneoVnJSMsYTiCjroE0C3rI1vi/u6hVEgsmuDtfaJ0ixba3uYkCJSUn4qHBb+yy5IxZYQgjJBSgACRkjpED0uYuqsKymA69uaMTmZh9OWlDWZ81APTawtMCqZQk3+LC21oNppQ64nebsdvPGhd9wEeEnbl5x90ajMZQVWFEpwo8CjxBCFNlzFyFkAiCCbvEkF2YUO/DsmgY89Fkt9prkwpGzSpTFry8cVhPmVeVha6NfJYhI3FpVoXVCdxCJxq19uptXdl88siPZpWiS8BMRWFJgQZXb1u+xJYSQXIQCkJBxwO2w4LzFVfh0Zzte29CETU1enLSgHNOK+i48LLFpUi5GXJo1rUF4ghFVSHqidRDpafFLl/Br7AxhV1sAoUhMxUyK8MtWdzkhhIwUCkBCxrmN3IxiJ55dU48HP63BPpPdOHxWsSof09d3Ktw2OG0mbGnwY22tV3UUERfxRCnlkk7hFwhFlcWvsVMsflCldMQy2l+mNSGEEGYBE5IRSNu4pTva8MbGZuTbTKpczKwSZ78uXskSllqB3kAUk4psKC2wZKRLON3CT45Vuz+ChvYg2nxhVQOwNN+q4vxo8SOE5DLtzAImZGIhwm3JlEIl+l5Y24hHPt+l4gSPnlOK0jxryu9IXNvsCidqWgLYEc8SlpqB4irORuEnpVyaPEE0tIcQCEfhsBoxrUQKOFtYtoUQQoYI6wASkmGIhWt9o1dlCrf5w9h7khuHzCiCox+3ZosnpGoGiigcy1IxEb0rh6lv4TfSGn6+YETFPTZ7Qip+UIo0SzkXcXtnosWTEELGC1oACZnAiKiZW5anikUv3d6Kd7e0YOWuDhw6sxh7VbtSWruK8iywW4yqVMy6XVpcYL59dOPgRIxJWzbBGNPq9iXX8RuJ8BMR3OoNK+HXGYjAYtJiH8vyLSzlQgghaYAWQEIynM5AGG9uasbntR0ozbOo+MDk2oG17X7UdwaxqNqlWp1tavDDG4hgWqldCcPRQKx80pc3buTrxkiEn3TikGxeSeyQbF6JhyxzWVHkNNPaRwghA0ALICFZRL7NrErESMbwy+saVe3A2aVOHD27FIUOM55aWY8WX0hlDi+oyMfsCodyB29p9KtYOakZmG5XqVj/eoo/1bnDNPQCzqFIFK2eMJq9IXT6I0o4luRZlPCTvryEEELSD8vAEDJBqCyw4ct7V2NNvUfVDvzLB9uUm1jEn/DM6nqU51tRkmdVyRE2cxC1rUFVKmVqiT1tIjCW5PrtNj0uAgeb0NHqDam4Pul1LBTYTWq7C52WXj16CSGEpBcKQEImECLilJWv1IkPtrbg7S2tic+k88Wjn+/CxUsmq2SQqkKb6jUsfYTFnWo1p0dUieu3LyQGsK/VyPZpoi+Mdl9YTZM4xanFdhTmmSdcQWtCCJnIUAASMgERsVTlsveywDX7Qnh6VR3O3KNSicXifIvKmk2nC1h3/Rr0Ib5oGfc03Inoa/OGlaVPRJ98V+L6phTbVVwfe/MSQsj4QAFIyATlnS0tKaeva/QqF/FRc0rV+/7En2Tsrm0CxItcmQ9Mdg28Xrt54LZsUqBZRJ+MxWWcZzWpYtWSlMK+vIQQMv5QABIyQSnPt6mx0WBQ1jdJvhCx1e4PD5g8IYLv7k+A+z8HGr1d0/evBr65BDhy+tBKtkicoYg9sfJ1BCJqO5xWI6oLbShyWtihgxBCMgyWgSEkx+gMAuc/Bqyo17J5kxERKdN+cihw6d59L0Ncux3+sHLviugLRmLKHSwxfW6HGW6nVpeQEELI2MEyMISQPvnJa6nFn6BPu+EtYPdy4IDJveeR4szbm/3qtSSZiNhzO0zIt5szpg0dIYSQ/qELmJAcos4DPLE2tfhLRpI57vk0tQCUFmySuVvgMNPKRwghExQKQEJyiGfXa3GCAyHlXF7epLmL8629BaAMhBBCJi4M0iEkh2jyAYMttyc6sUXz9BJCCMkyKAAJySHEmjeQ+zeZgh7WP0IIIdkBBSAhOcSxMwcnACWXY58qoLB7rWlCCCFZAgUgITnErCLg4Cm9O3b0RETiJYvHaqsIIYSMNRSAhOQYtxwLFDv6F4HnLgROnjOWW0UIIWQsoQAkJMeoLgD+ex5w3CzN1ZtMsR247mDg18d09fglhBCSfbAMDCE5SFUBcOfJwK5O4J3tWmu4qnzg0GnAAF3kCCGEZAEUgITkMJX5wNkLxnsrCCGEjDV0ARNCCCGE5BgUgIQQQgghOQYFICGEEEJIjkEBSAghhBCSY1AAEkIIIYTkGBSAhBBCCCE5BgUgIYQQQkiOQQFICCGEEJJjUAASQgghhOQYFICEEEIIITkGBSAhhBBCSI5BAUgIIYQQkmNQABJCCCGE5BgUgIQQQgghOQYFICGEEEJIjkEBSAghhBCSY1AAEkIIIYTkGBSAhBBCCCE5BgUgIYQQQkiOQQFICCGEEJJjUAASQgghhOQYFICEEEIIITkGBSAhhBBCSI5BAUgIIYQQkmNQABJCCCGE5BjmwcwUi8XUuL29fbS3hxBCCCGEDANdp+m6bcQCsKOjQ42nTJkynO0hhBBCCCFjhOg2t9vd7zyG2CBkYjQaRU1NDQoKCmAwGNK5jYQQQgghJA2IpBPxV11dDaPROHIBSAghhBBCsgcmgRBCCCGE5BgUgIQQQgghOQYFICGEEEJIjkEBSAghhBCSY1AAEkIIIYTkGBSAhBBCCCE5BgUgIYQQQghyi/8HAz/AJ9mXf3YAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "def betweenness_plot(G, cb, cb_e, title):\n",
     "    \"\"\"Plot graph with edge widths proportional to edge betweenness.\"\"\"\n",
@@ -592,7 +2371,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T09:51:07.533970Z",
@@ -651,7 +2430,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T09:51:29.611450Z",
@@ -740,14 +2519,87 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T09:51:44.214518Z",
      "start_time": "2024-04-18T09:51:44.188049Z"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Node: False\n",
+      "keys: True\n",
+      "0.09999999999999999 0.1111111111111111\n",
+      "0.031578947368421054 0.03508771929824561\n",
+      "0.010526315789473684 0.011695906432748537\n",
+      "0.05789473684210526 0.06432748538011696\n",
+      "0.2736842105263158 0.30409356725146197\n",
+      "0.049999999999999996 0.05555555555555555\n",
+      "0.15263157894736842 0.1695906432748538\n",
+      "0.26842105263157895 0.2982456140350877\n",
+      "0.021052631578947368 0.023391812865497075\n",
+      "0.034210526315789476 0.038011695906432746\n",
+      "0.042105263157894736 0.04678362573099415\n",
+      "0.2894736842105263 0.3216374269005848\n",
+      "0.2394736842105263 0.26608187134502925\n",
+      "0.21578947368421053 0.23976608187134502\n",
+      "0.2131578947368421 0.23684210526315788\n",
+      "0.22894736842105262 0.2543859649122807\n",
+      "0.12631578947368421 0.14035087719298245\n",
+      "0.04473684210526316 0.049707602339181284\n",
+      "Edge: True\n",
+      "keys: True\n",
+      "Node_len: False\n",
+      "keys: True\n",
+      "0.07313767820943767 0.0812640868993752\n",
+      "0.008219771107034904 0.00913307900781656\n",
+      "0.0061403508771929825 0.00682261208576998\n",
+      "0.044295461952093856 0.049217179946770946\n",
+      "0.22946370816687553 0.2549596757409728\n",
+      "0.021116233284387647 0.023462481427097386\n",
+      "0.11539523149980213 0.12821692388866904\n",
+      "0.22181564165124942 0.24646182405694375\n",
+      "0.005480001421123074 0.006088890467914524\n",
+      "0.019813615507248455 0.02201512834138717\n",
+      "0.03220881150244031 0.03578756833604479\n",
+      "0.2325841273344125 0.2584268081493472\n",
+      "0.2014165967171499 0.223796218574611\n",
+      "0.19667861852237278 0.218531798358192\n",
+      "0.18006572332036724 0.20007302591151915\n",
+      "0.21724997606004473 0.24138886228893858\n",
+      "0.09276404798359016 0.10307116442621128\n",
+      "0.008966952492744458 0.009963280547493842\n",
+      "Edge_len: True\n",
+      "keys: True\n",
+      "Node_lin: False\n",
+      "keys: True\n",
+      "0.13896758494845704 0.15440842772050783\n",
+      "0.023359176261386148 0.025954640290429053\n",
+      "0.007017543859649122 0.007797270955165692\n",
+      "0.049915064363695624 0.05546118262632846\n",
+      "0.38272005205036447 0.4252445022781828\n",
+      "0.0473048193471913 0.05256091038576811\n",
+      "0.25828897902651365 0.28698775447390407\n",
+      "0.3871473764597995 0.43016375162199955\n",
+      "0.01283262944726276 0.014258477163625289\n",
+      "0.03185852410754838 0.0353983601194982\n",
+      "0.05752803060282284 0.06392003400313649\n",
+      "0.5378626268058401 0.5976251408953779\n",
+      "0.44474809271817645 0.49416454746464056\n",
+      "0.41385367319495386 0.4598374146610599\n",
+      "0.42254482067639965 0.4694942451959995\n",
+      "0.35204737799703467 0.39116375333003855\n",
+      "0.24752834967722848 0.27503149964136503\n",
+      "0.0357698896125187 0.039744321791687444\n",
+      "Edge_lin: True\n",
+      "keys: True\n"
+     ]
+    }
+   ],
    "source": [
     "# Check if results are the same when unsimplified\n",
     "cb_paths[\"Edge\"] == cb_paths_2[\"Edge\"]\n",
@@ -773,14 +2625,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T09:52:23.580242Z",
      "start_time": "2024-04-18T09:52:00.815835Z"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1.06 ms ± 11.8 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)\n",
+      "530 µs ± 4.78 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)\n",
+      "460 µs ± 10.1 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)\n"
+     ]
+    }
+   ],
    "source": [
     "%timeit calculate_betweenness_with(_single_source_dijkstra_path_basic, \"weight\", show_tree=False)\n",
     "%timeit calculate_betweenness_with(_single_source_given_paths_basic, node_order, pred, dist, show_tree=False)\n",
@@ -811,7 +2673,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T09:54:47.350395Z",
@@ -822,21 +2684,101 @@
      "outputs_hidden": false
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "AttributeError",
+     "evalue": "'dict' object has no attribute 'graph'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n",
+      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)\n",
+      "Cell \u001b[0;32mIn[16], line 1\u001b[0m\n",
+      "\u001b[0;32m----> 1\u001b[0m \u001b[43mpart\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgraph\u001b[49m\n",
+      "\n",
+      "\u001b[0;31mAttributeError\u001b[0m: 'dict' object has no attribute 'graph'"
+     ]
+    }
+   ],
    "source": [
     "part.graph"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T10:04:17.300351Z",
      "start_time": "2024-04-18T10:04:16.580503Z"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-03-23 11:00:13,214 |     INFO | tessellation.py:101 | Calculating edge cells for graph with 1256 edges.\n",
+      "2026-03-23 11:00:14,136 |     INFO | tessellation.py:155 | Tessellated 785 edge cells in 0:00:00.\n",
+      "2026-03-23 11:00:14,299 |     INFO | ghsl.py:129 | Using the GHSL raster tiles for the bounding box (10529206.185883993, 3665258.196608499, 10534037.079623077, 3670687.995752596).\n",
+      "2026-03-23 11:00:16,355 |  WARNING | features.py:148 | CPLE_AppDefined in DeprecationWarning: 'Memory' driver is deprecated since GDAL 3.11. Use 'MEM' onwards. Further messages of this type will be suppressed.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Distributing population over road cells:  67%|██████▋   | 1570/2355 [00:04<00:02, 346.34Cells/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-03-23 11:00:21,004 |     INFO | __init__.py:11 | superblockify version 1.0.2\n",
+      "2026-03-23 11:00:21,004 |     INFO | __init__.py:11 | superblockify version 1.0.2\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-03-23 11:00:21,272 |     INFO | utils.py:265 | Highway counts (type, count, proportion): \n",
+      "                             count  proportion\n",
+      "highway                                       \n",
+      "residential                    711    0.572003\n",
+      "tertiary                       184    0.148029\n",
+      "primary                        132    0.106195\n",
+      "secondary                      122    0.098150\n",
+      "unclassified                    45    0.036203\n",
+      "living_street                   18    0.014481\n",
+      "primary_link                    10    0.008045\n",
+      "secondary_link                   9    0.007241\n",
+      "tertiary_link                    8    0.006436\n",
+      "[tertiary, unclassified]         2    0.001609\n",
+      "[residential, unclassified]      1    0.000805\n",
+      "[unclassified, residential]      1    0.000805\n",
+      "2026-03-23 11:00:21,273 |     INFO | utils.py:299 | Graph stats: \n",
+      "                                             0\n",
+      "Number of nodes                            539\n",
+      "Number of edges                           1256\n",
+      "Average degree                        4.660482\n",
+      "Circuity average                      1.099485\n",
+      "Street orientation order              0.306443\n",
+      "Date created               2026-03-23 11:00:12\n",
+      "Projection                          EPSG:32650\n",
+      "Area by OSM boundary (m²)      18634010.566506\n",
+      "2026-03-23 11:00:21,274 |     INFO | base.py:185 | Initialized MissionTown_main(ResidentialPartitioner) with 532 nodes and 1243 edges.\n",
+      "2026-03-23 11:00:21,398 |     INFO | checks.py:86 | The partitioning MissionTown_main is valid.\n"
+     ]
+    }
+   ],
    "source": [
     "from superblockify import ResidentialPartitioner\n",
     "from superblockify.config import Config\n",
@@ -854,14 +2796,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-04-18T10:07:41.749617Z",
      "start_time": "2024-04-18T10:07:11.229057Z"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "36.5 ms ± 2.14 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
+      "722 ms ± 15.2 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
+     ]
+    }
+   ],
    "source": [
     "from superblockify.metrics.measures import betweenness_centrality\n",
     "from superblockify.metrics.distances import calculate_path_distance_matrix\n",
@@ -899,16 +2850,7 @@
    "name": "sb_env"
   },
   "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "name": "python"
   }
  },
  "nbformat": 4,