ArtStudies/M2/Clustering In Practice/VAT.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0537d051",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyclustertend import hopkins, vat\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "from sklearn.datasets import load_iris\n",
    "\n",
    "rng = np.random.default_rng(42)\n",
    "\n",
    "iris = load_iris(as_frame=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "0e5dc717",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hopkins statistic: 0.8337\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/arthurdanjou/Workspace/studies/.venv/lib/python3.13/site-packages/pyclustertend/hopkins.py:53: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  uniformly_selected_values_0 = np.random.uniform(min_data_frame[0], max_data_frame[0], sampling_size)\n",
      "/Users/arthurdanjou/Workspace/studies/.venv/lib/python3.13/site-packages/pyclustertend/hopkins.py:54: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  uniformly_selected_values_1 = np.random.uniform(min_data_frame[1], max_data_frame[1], sampling_size)\n",
      "/Users/arthurdanjou/Workspace/studies/.venv/lib/python3.13/site-packages/pyclustertend/hopkins.py:59: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  uniformly_selected_values_i = np.random.uniform(min_data_frame[i], max_data_frame[i], sampling_size)\n"
     ]
    }
   ],
   "source": [
    "hopkins_val = hopkins(iris.data, len(iris.data))\n",
    "print(f\"Hopkins statistic: {1 - hopkins_val:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "b2f0c0a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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v3GeqvUL1g8oXpT9pvvvcGF2zqJQ+c/aflDnGNzoAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAEBxcNABAAAAAIDi6GgzgloENV6Yp0RRSly6efPm8HlOeZUvEnW3eqtxym3nrhBetdsV+KXcvOuKKlU/KuOBkZERK19ktuCKm9U4KMGbexOwMhOIUOUjYf5EZsyYYfWF2w8p81TVndPmgYGBtt/w7N5inpMvyuuubbUW1Bi645IiMnfns6rbNTiJYsy5VVvNCfU8FWMUj9vnbj4Vj7uuo75Vz3TbrdLcm+Sjd4DbP6q8u67dtZXynnLjcftbEb1fcww33Hk2Ge8At40pa86N0Z2nOXuXa8AQjb+qW9Wj3pvuO0DVkfIe3s1cm+7nCrdsivGR04/uGmzUYecEAAAAAADoEDjoAAAAAABAcXDQAQAAAACA4uCgAwAAAAAAxdHRZgStkiLIU+TcYOwK8tx8KaIs9wbaFMGziyqvbs9VbXENCnp6emTdOaJTN+7cPlOCRyXoc/MpVDzRLcmuUNNtt7s+InJEp64hgJum6k2p2xUYu+SUTSnf7nyT8Ux3rKO51+75kxNP1OZ2P9Mtm2J64dajaHfZ3HravX9Ez2z3Z5WcuCNy2j2dY9jueFL2j3avuencKxQ57+EIJ56UecI3OgAAAAAAUBwcdAAAAAAAoDg46AAAAAAAQHFw0AEAAAAAgOLoaDOC+obp8UKozZs3ZwmgckRaSjSYa3qgcNujROazZs1qStu0aZOVpvo2Eq0rwbwSrCoR2+joqFWHMh4YHByUMc6bN88W4TtjrfpHGRSkPFOhDBfUrepRux1Th2g+qTFU7Vb9qEwdVD41p7q6umQ8Kk4VjyveVAYOar2quCMzAvcWa/VMtx/dW9GjNafG1d27VIyusUK0F6p43BvvVfuGh4eteKIxVPG4fe7evq76Qq0F1b5oX1Bjo+JR+6u736t6U/Z71xRGjY07T6J55prPqLjVXqH6UY2Bijv1feGgxlqNlxrXKBb1THcPUGOYa2ik4lRprjhejaFC5YvKqrWk8rprWOVTdURrU/XPiMjrGiyputWe67Y5JcaJadHzFHyjAwAAAAAAxcFBBwAAAAAAioODDgAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAUBwd7bo2MDCwjZOH68wSOW4p9wfX7Um5YSkHF9fdInLcidyCnHzKHUW1TzkFqbSoPcrdzY3RdXVRjjnKXa1m48aNTWnz58+3nqn6R421yhc57rjOYKpvlQOQQrVFlY3GVaWrcVVjOGfOnJbdjNatWyfj6e/vb0rba6+9rLhdN0XVFtdJLcrr5nNd19y4U5zTVDxqbNR8VnMixXVNtVG1x93Puru7LSe/qM/U2m6365qKR7lhKZfEyOVIxa3GRqWpPlPPU/miOeXuNe47yZ0nKu6onsitsNU9ZTJc19z+UeOq5o9qcxSL+9lJxZji8Ok8L8VNzV2baj67z4s+46hnumtO9a2azyot2itUn/UIx1rVRrVPqXrU81RZlS9qj/oMMXEduu61NXyjAwAAAAAAxcFBBwAAAAAAioODDgAAAAAAFAcHHQAAAAAAKI6ONiOohVHjBW5K0KkES5GIKTIAcMRTkcFBq2LiSLin0lXcbprqM7cfcuOJRIcOrtA6Mh7YsGFDy0JkV2g5Ojoq43HFkkrQWxtwOKi+SDG9UAwODloxqjRlCLHHHntYZSNBp4pHtds18HCFqNHz3Lyqz10zAhVjFI+qR4mjXTMC9Tw1x909IarHFaOrPUCtD9XmqM9Ue1TeHDMCNdZKEK725siYQ/Wjeqbqn76+PqsOlS9lTrlmBK4piOrvqTIjGBoassY1mvfuZxVV3n0nqTFUcyIyI1D1qLyqb1X7cs0IXLMoN031j0KZT0XvYfWec9ecGms1z9TzonjUOPSLdqu1oOazKuumRWvT3WsmjoN6/0fwjQ4AAAAAABQHBx0AAAAAACgODjoAAAAAAFAcHHQAAAAAAKA4OtqMoBZQjRcuRrcQuzeYu+VdlKjOFV9GhgmusNq9iT63H5TIzxVVqnFQdbvi5AiVVwnjlOhQiTxd84honrlCZte4wr2t2hVVR3lTbiJ2yqaIiV2hpWqPK5ZWqHmbIv5XeVU8rpDZnSfRHFB1u4YUbj4VY4rxiGvgoJ6p1rCaE64wOuozd59y16ErTo/yKlS7VdmctMmYU6p/VD+mGA2p8m6Mqqwr6k8xI3Drdg1J3DGMTHxUPe4+5ZpH5JoRuH2h1qa75lQ+tc9EeVWaaotaR7lr0zU5eUqModo/1PNUX7htTsk7MZ+7hmr4RgcAAAAAAIqDgw4AAAAAABQHBx0AAAAAACgODjoAAAAAAFAcHW1G4KBEaCniO1dY75oEuDHmmhG4onU3npS8rgmDK+h180V95uZVxgMjIyNNaV1dXS0LViNcwwXXoMC9kT3qM1eA7dbjismjOar6QtWt8qn+cU0PUoTsrtlDrpmFG48rZFYmJe64ujFGAmO3f1Q+9Ux3TkR95rZH9ZkrjFZ1uG1J6TNVXsXt9neKAYyqR5V336XumolizHlnu/GkGB7kmDW0e57lmoq47yT3c0UUoyuYV/W4c0W12d1Tona7+6u7N7tjHbFrxrtU5XPTovXW6jsgZT/iGx0AAAAAACgODjoAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAEBxdLQZQS3U2p6gUP17dKuta0agRNmuyM8VIUbtckV1Sjicc1N2FLfbv66pgyLnht5IeK6MB1RblPHAunXrsgTvo6OjlYMahzlz5jSlDQ4OWnNUEQlE3bni3lat0jZu3NiUNmvWLBmPGoeenh4rn6q7u7u7ZbFrZODgCkdVP7qC5xSRr9seFbdKU3uKmuOuiDmKx93jVPvctqTMe9WeHKOQnLSoblf8q8ZLlVXrQ/Vj1G7XjEDNC1fQ7Yq3c80I1DPdfS96x7lGIW4+Na7u2ozWgmt6oNqo9vEcw6YU8blbT87z1HsmZRzcGN3PLtFnjZw9abcMkwG3bPQeV8+cOB+j97CCb3QAAAAAAKA4OOgAAAAAAEBxcNABAAAAAIDi4KADAAAAAADF0dFmBLXQarzYKkfYGonqVHnXeCDlFmKn3hQBlns7sBKtp4gGXbGbW9YVjap+UALRqB43zRXLpvSjO4Y5AlqFK2yN8qo01W73Nu+U9qmxcU0P3DS3zbl95pbNrSNn/5mK50XPzElTcyq3z1JuvG91j3OfF8WTky+33ukaw9wYXdrdvuncF3L2qMl6Zk7dU5FvMtbrVPVjzpr7o2lolPNZIcLZA1L6hm90AAAAAACgODjoAAAAAABAcXDQAQAAAACA4uCgAwAAAAAAxdHRZgT1DePjxcvujeObNm0Kn+eUVzeEu6LlXMMDV9yqyo+OjlptUWkRKm+OQF0ZRajxiswaFCoe1Rfq5l5lcODedDwwMCDjcW8XVreTqznqGkKosYr6Ud0GrsqrW5rVGKp+nDdvnjUuUXl37romHLkCUXdt5+Cuo4h2i2Bzn5djruHe8u6aUaTkdc1M3NvlU/ohx5DGHVe1PnL7zDUAmQxS1kirz8udZzujUUgKOftrznil7OHuOLif49zPkBFue56ZsSe5+17Uj2qvcfbXlHHhGx0AAAAAACgODjoAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAEBxcNABAAAAAIDi6GjXtdrZYby7g3KJSHF/cJ10XDebHKePyPHCbY9y5nCddFLcetw+V/na7VIVOdmoZypnMJWmUM5gqm7lrhY5iLm4fes6HEWxqGe2210nxT1GxaPGS+VzXWbceqM56jrXuH2Wu5/lrPdcJ50cF8mcPTfneVF6Tp/luMBFczSnbjctZd6n9G87606Zj+5ccWPMdefKeY+3ux+juHNc8nLmRERue9qZL6XPcvbxHNe0FEezXaZgj8vdc3PgGx0AAAAAACgODjoAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAEBxFGVGkFIuJb2dIj1FTtkU2i3wisgRKLtiPiWyS4nHFQTnCChdwXtkCuCKU935qMT7OcYIEW48KSJE95mueFfNn5znpZR363aFpJPRRpWW0z/RHpdjXNFuc4zJeKaatzlticq3ewzdtJS8OWL73Oe57xq37px+zK1HMRnjmjN33fdUCil96dSdM/dS5lm712vKfpRT91NTsM9Eedv9mZhvdAAAAAAAoDg46AAAAAAAQHFw0AEAAAAAgOLgoAMAAAAAAMXR0WYEtdh7vOA7R3AYlXdv5FZCb5XvySeftGKJhFuuwF2VnzVrlvW80dHRLPG/K/TfbbfdmtI2bdrUlDZz5symtBkzZjSljYyMyHiU4F6VV2OtxnXz5s1Wf3d3d1cuqu41a9Y0pe23335WPhW3GoM5c+bYMar5o+aFmlPz5s2zxiuKx61HzSmFyufWERkCqD5394+c50XxqNjVPFV9odLU/FHrKGXPdQ1AVF+4AnX3ZvIoPefWcHf+pBihqL5wx8sdQ5Wm6o1Q7XbfkW5Z1T/R+ldrW+V13+1uW6J5puJx143bbtWPKi3aj9x5qsqr+ZNizuPi7mcKN56Ueea22607d8/N2bueYe7D7r4X7R/q853TZynziW90AAAAAACgODjoAAAAAABAcXDQAQAAAACA4uCgAwAAAAAAxdHRZgTDw8PbCKGUkD1F6K/Ku+LEOpZWRVqKSOzm3mSvTA+UyYAShLtC/QglLlOovu3p6bHKKjFnVK9qz8DAQMvCYSWYV2WVaUHKLc3KeOChhx5qSttrr72seTJ37lzbHKOrq6spbXBw0Orb3t5eK+5ly5Y1pfX398t41Ppat25dU9rQ0JA1hmot5IgvU9aNGuscI4QoHrce14xAofpREQme1ZrNMSNQ88QVvEd51Xp1xeSuSYBar5HAWO3ZrsmNWsMqbf369dbaivpCtccV8KvxdwXY7rsnitHNp+aZ+7wob8pt8s7z1Liqd1JK3GqsVYxqPrqfIaK9QsWeI6x3P7OpPS56T6nPFSqvWsOqb9UY9vX12WtTje2oaI9am2qPVHWrz80qnuiznTJTUs+cOP7R5ysF3+gAAAAAAEBxcNABAAAAAIDi4KADAAAAAADFwUEHAAAAAACKo6PNCGrh4XjBlHtzcyTwc2/QVqIxJfR2xcDuDdYpolyVpm62V89TQrBIsOiK8N3bk5VA0L25Wwn3UlACStU+t56UG+vVeCuRnjIeeOSRRywzATX3Zs+eLWNUbVQCw0gE6cwzZSagxjUSdav53N3dbfWt6h/3lu1oXN28ahxynhfFo9aca0agRN1qD0i5pVuRc6u2Gi/3JvAoxkgI7ZDSbqfe3NvOFa7oWK2tFNML9zZ41yjCNeaITCZUjKq8Ow7uOow+a7S7HrWG3X6MYnTnlBtPiqFRDu7nQHdfUGlRHSrd7Qt3HaX0bU4bFeq94K7hqA71LlZMrCdlr+YbHQAAAAAAKA4OOgAAAAAAUBwcdAAAAAAAoDg46AAAAAAAQHF0tBlBLXgaL3pyb4dOEXm6Ai9VtyuWcm+HTonHfaZ783Ju3a4AzhXfpaAEgu54qbpdMXkkjFXtVnWruJUgXIn5lKmDMsyI5qi7FlwhouozNXcikadrCuKafbhlc8dV5VVzz607RYCtnunuC26MKl+KKN8VqLtpKp6UW9pdEW2OIYAbY/Q+c01T1F7hjqs71ql5Wx3XHPF2lDfnven2Y/R+dfepHJMRd05Fe487L9x1GI2Ni1u3+/nD3XNz+0yVV2tzMsYwZV9pZ9zu3hOVd+J221HDNzoAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAEBxTPpB59Of/nTj9yPf9773bU0bHR2t3vWud1ULFy6senp6qte//vXV448/PtmhAAAAAADATsKkmhHccsst1T/90z9Vz33uc7dJf//731/9+7//e3XZZZdVvb291bnnnludeuqp1U033ZT0/FooPl7g5oqBN23aZNehym/evNm6STpHhJhy060S36l4lDBSCdlV+yJRpRKP1wdZJ0aFitsViM6ePVs+07293RWOK1xBZpRX9aOKURkKqDml8q1ataopbd68eVnzVMW9YcMGK19fX59VR83SpUub0uoflDjzWc2V+gcszni54xLlVWYWan2pul0TjhQzArWO1W3Xas3k7HsR7o33qm/VOnJjjPrM7XPVP65RhNqn1DspujFcGY2oMVTlFyxY0JTW3d1t9eOcOXNkPGruqnhU36r56K4jtQ7VuERrITI+abXuFJG4+0xXWK/mVP3ZyplnSjie0kY1hmpOuf0d4X5uc+tR7wB3rFTfRu1W71j1flZ9q95xah2qz1zR2PaIdqs2um1R+VT/RPuZm3fi/ppipDVp3+gMDg5Wp59+evW1r32tmj9//jYfbr7+9a9Xn//856s/+7M/q44++ujqG9/4RvXzn/+8+sUvfjFZ4QAAAAAAwE7EpB106l9Ne/WrX12deOKJ26TfdtttjVPm+PSDDjqo2meffarly5eHJ/n+/v5t/gAAAAAAAEzpr6595zvfqX71q181fnVN/fpM/fXyxK/AFi9eLH+1puaCCy6o/uZv/mYyQgUAAAAAgAJp+zc6K1eurN773vdWl1xySfbvb2/h/PPPb/zK25Y/dR0AAAAAAABT9o1O/atpq1evro466qhtBHk33HBD9aUvfam6+uqrG0LHjRs3bvOtTu26tmTJEvnMWtioxI0OKbd0u+Tc0uzGk2JG4N7c7ZoMpJgjqDa67c4RiKbcdp4jgnX7IqXPlEBQpSnRoWq3EqIqEasSEtbrUKEEi2pcXfG2GuuUH4SoenJusc+57T5awznxRHOl1XwpuHuS2xbXeCS3btekJGUMc8Yhp263bEqMOfM5ZY7mzGeX3LXp9q8r/nfriNaCu1e4guucOZUyVu3eX906cuduSj3trGMy1qtrepJiKrRLxt6e895LzbvDHHROOOGE6je/+c02aWeeeWZDh/OhD32oWrZsWeNDy7XXXtuwla5ZsWJF9fDDD1fHHXdcu8MBAAAAAICdkLYfdOqfQh922GFN9nO1Td6W9LPPPrs677zzGlaXtc3eu9/97sYh54UvfGG7wwEAAAAAgJ2QSb1HJ+ILX/hC4+u3+hud2lHtpJNOqv7xH/9xOkIBAAAAAIACmZKDzn/+5382/W7+l7/85cYfAAAAAACAjrlHBwAAAAAAYKf61bV2UbtNjXfKSnHiUijXLeUooRyyFK7TmBtLSntUPa5rlmpf5P6i4nRdl1zXJNWPKu6ob11nMNU/rjOcakt9X5Rbj0tXV1dT2uDgYMtzT7mrRc+cP39+U5pac8rdr7e3tylNXfyrnOFqlOuiGgfV56ovorHJGSuV13XIUesr10HMRT1T9W3u/tpu56McN6OInL3LzafS1PhHdaS42rXaZzl71GQ4Wk2Ge6o7Nu0e65T1nsNk9G27HSzdOnLrbvfaTFkfrhtfzuehlD4by5j3Kh7X2S3lM6TKOzHNdSSs4RsdAAAAAAAoDg46AAAAAABQHBx0AAAAAACgODjoAAAAAABAcXS0GUEteh4vSFIieiWKUmLpKN0VX7kmA0rgpWKMxG6u0E4Jh1Xdqs2qbCT8UqLu+m4kp+4cEaPKp+rdYmfeTgG/6jPVPtWPUd6cuIeGhqznpcwzZTywYcOGprT6MmAnra+vz8oXMTw8bPWvmgOq3WqvUGlKKBmtQWV64ZqZqLa4dUciX3efUvNMmT+ovo3W3FQYOCjUPHP39RSTCpXPNY9Q469ijPbcgYEBKx5VfuPGjU1p9aXdTj7VtymGJK7oWOVTayvFZMStR+3Nqm53P4rGUPWPKxx39zM1Xmq9Rp+HFGr/UG109zNFtL+6e7vaK1Q/qnXk1qvWR/RMlVe9x1XfqrIpa1PFPijqdtemqkc9TxkNRXu4+lyhPtOMjIxsdw1G8I0OAAAAAAAUBwcdAAAAAAAoDg46AAAAAABQHBx0AAAAAACgODrajKAWHm5P4DYZN3fn3HbuCtEj4ZbbHlW3ElUqXFF+FKcrOnSNHtzb7iPxv4rRFR2rPlPCTxX37Nmz5TPdOeD2hRLuqTpckW/Ul8o8QNXd09PTlNbV1WXVoUTwKaL1dt+qnnMLfcoz1XpV4+8KbXPJuSE+tx731nhV1hVLR22J9hAnHve9oGJU9UZ7riv0dsXx7g3oUZ+5Y5iT5s693Bjdee/GHY2hypuzT7l1pPRtu+OZDFT/uqYObl+4RlMp9bjr3a07ZZ49Kep2P/O5/ZPSllYNv1LGhW90AAAAAACgODjoAAAAAABAcXDQAQAAAACA4uCgAwAAAAAAxdHRZgS1wHm8mFoJmZUYdHR0VD5PicxTRO8O7k3HkemAa0agYlRpSoyecsOzKh/1r4MrgFT9EJkgzJkzp2UzAle45968HeV1b3ju7e192nifrqy6gThC3ZatzAiU8cDjjz/elLbffvtZt0hH5gjz58+3xlCZHqi5ouJW89Y11ohiV+Og+lbtPZEhiZvPFebPmjWrKU3tpRNvpo76O8W0wDWPcI1U1E3gqn3RPqPqUe1Rc8+dK8qkRI2h6tto7qp41HpdsGCBFY/qnygeNXfddaj6Vo2BSkuZJ2otuO9S9UzXeCASTKs9IMUAwpnj6r3nmutEuG1U4+++c6NxcfcA17BFzXuVTz1P9W30TPXOVmtT9aN676n1r+ZTlD5bxKjGRuVT7Vb5VPsio6G5c+daYz2xf6I2K/hGBwAAAAAAioODDgAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAUBwdbUawdu3abYRiSoiqiMwElLjJvWXXNTJQqHyRsNWNxzUUUH2WIiZ2zQzcZ7oCbLfNUbs3btzYssmAK6BOEXmq9sybN68p7aGHHrLmihI2uvkiAWVfX58lOlXGAyruAw44oCmtv79fxvPYY4+1LOB2zQhUX6g6UsSyqryap2rvcQXYUTyuYFqJRJU4Vc3n4eFhWbcTS1SPazSi1oyao2qPi/aZSDDb6n7vxp3y/hgcHGxZ6L1mzRprzdTv1onsu+++WcY3qi/UvFBj486TSLCu6nHF7e68TzEjcMfbvf1d5VPvONcIJUKNq6pbPdPt7wi1jtUcUGmqb5W5ilvvunXrZF5lsLN+/fqW548qq8ZV5YvGYVSY7rhmHcrQSPVPyh61atWqluZZ9E5R8I0OAAAAAAAUBwcdAAAAAAAoDg46AAAAAABQHBx0AAAAAACgODrajKC+pXW8wNEVVKXcIquEka64VYlOXXFhJER1xfpuPUr0pcRqkZmAEpiq8q4xg3szccq4KhHcHnvsYcWo4lFiQCWMU2YCUV7VHiWWXLZsmSWMVM9TQm11o3ZkCqBuO1bzRwkylfHA/fff35T23Oc+1zZHULdGK2G1Glf3dmk1v6O5rMS2qrzaP1zxriu0jeaZSlMCfJWm1rXq7xRcYw9X1K/Kqpu7oz6LTGCc/nGF0WrNqTmh5mi05tQep+pZvHhxU9qiRYusPlu4cKEdjyrvviPVGLhrIRK8u+YsKh71TNU+V6gf7TWRqYgzd9VYu+/IyIzANUdQe4p6V7hrK1qbKnYVjxovFaN6f6jxV2tzzz33lDGqtaTeh6puNX923333prQlS5Zk9dk88blE9ZkaQ7V/zJ071+qz6PPQPvvsY73vh4aGWjbN4hsdAAAAAAAoDg46AAAAAABQHBx0AAAAAACgODjoAAAAAABAcXS0GcGKFSu2EdwpQZYSWU0UNaWWV0IrJQZU4kv3NtdIXOYKsFTcSkSvRLUpt6+7pgduWRWPEvMpImG0Eusr8a6qWwkE3bFW4u0I1ee12YZjEqDakiKiV0TCQafP1NxTcSvjgTvuuEPWo+afEmu7RiFKgKv6TKVFa8EVTCshs2tkoMYwMihRe40r3nXjiW67dmKJ5o9qjytkdw0Toj5z90PVP66JgopHiYYjoxDXuEKJiVX7lJhY3Wwe7QlqTrl7kms+4/a3al9UjyuOV/ncd0U079V4q/a4nxfUnqLqyDUjUHldMwLXbCFFZO7uzyotMtdo9fNetJZUXlW3Wkdqr1Bjrfo7xYhpN7G+VN2qHmXAoOaZMlaI5o8yPZi4t6vPFBF8owMAAAAAAMXBQQcAAAAAAIqDgw4AAAAAABQHBx0AAAAAACgODjoAAAAAAFAcHe26VjtujHfTUK4VyoVHuVlFKEcI1ylIxRO5/Thlc11KlixZ0rJDSYTrSqZQ9ah2q/alxK3cOdwYXdckVXfkZqPmgHK4UX0xPDzcsiPR0qVLrbLRHFd1q7bMnz+/Ke2xxx5rSuvt7bXH8Pbbb7ecWZTLjOoLNSeUo4zrxPZ0fdnqXuG6uLl7Ssoe6TpfKXcdFWO0R6l4VP+6fabmqOuGFqHao/Y9hdpn3H0vwnXsGhkZsea9aovKF7lIqrF1XeRUWXe8VD+6LmXRXqHiUc90Hc2ieZ+St1XnRXeso7msnunO+5yxidaCSnfnikpT81nFrdaR2mcih7YNGzZYdau+Xbt2reVCu379+qz9/gnTTU/VrdqsXBsXLFggY1RuwKruFDe+ifCNDgAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAUBwcdAAAAAAAoDg62ozg+c9//jYCWVfgpUSIkSDLLa/EaUo8pQR+KeJ/Vxir2qLE1qpsSjyuMFKJy5RAUMWjnqfSlCiuZq+99rLEckogqgTYPT09Vj9Ewk3VbneurFu3zhL5KhHiwoULrTqiGN25otaHa1qg+jYyHrj66qtbNhpR+dx5FgnZXZMJt2+VIYQiRViv6skR9LptjoSkaq6oNNfgQIl31b4XGUfMnj27ZbMHtccp4xJVR4rQVu0BamzUvvCzn/2sKW3NmjVNaffee6+9n7mxu2YECtU+Nc9U30ZEnwOcutX7PjKfUai8OUY8qt0rV67MMiPIMeFQe5c71lEdrrmTa6Ty6KOPtmxacM0118gYly1b1pT261//uuVxuP766609btWqVfaetEzEqPpMrVfVbmW28Lvf/a4pbZ999pExqmceccQR210zkSGEgm90AAAAAACgODjoAAAAAABAcXDQAQAAAACA4uCgAwAAAAAAxdHRZgS14G28yEyJ1VyxdJRXibSU0M69ydUV76q0KEb3dnElLlOiSDfGKF2Vd/vCFRyqeiMTBSVEVMI/V4CtBMYpZgSuWYOKe2hoyBJbq350447WiDJ7UOVVPW5aZCih4lGGAurmZtWPagxUPCkicTeva/YR3RDujqH7TPc2eNdEQcUT3YquxsbdS92b1nNu1E4xV8itZ7Kfl2Lq4N6UHqWrZ6q5knXbeYJYXuV1549aM6qsu15T5k9OjCpN9U8Ut4rHbaOaP5NhRqBQfebuSW4/Rnu4il2ZHKl8OevINYlI6UeVT7XFjTGay8rsQeWdmOaujRq+0QEAAAAAgOLgoAMAAAAAAMXBQQcAAAAAAIqDgw4AAAAAABRHR5sR1AKz8aKwHBF8iujMNS1Qz0sR0Stc4wLXJCBFaNduwasrEHX7LIo7py9yzCOieHL6V5XNiSfFZCKnHrfuaG26gnslbndvIXdFmpGoNkcsmyNuj/KlmBS0M8YUc5V2t9sVdEdj5Yhgc+vOFaLnlE8R8OaUdWN0x9p9L0TPm4z15eRLmfdu/7Y7X26fuftMu/s7aqP7+cMtm7NmovK5+5TzvOiZT2WYNeSkpeDMvZR5wjc6AAAAAABQHBx0AAAAAACgODjoAAAAAABAcXDQAQAAAACA4uhoM4LZs2dvc2O6ElQpIfKsWbPs29dV+ZkzZ7Ys5nLF7RGuAFPdMN/d3d3yrfEp8agb1F1TCHWjrnqeqleNX4r4X/WFGmvVjyqeSEjoGiGoeNQtwl1dXdbzenp67LnnrgWFqsdNi+ro7+9vSpszZ07LfTswMGCNa+7t9K6YNEXA7+Zz17F7i7k7x9V6nQxx6lQZl6i8qt2TIbbOmSuqHjU2ap64gu6obtU/7Ta4yFlvUT05Qu2UcW23wYGKx72dPlqb7nvTnXvu2ET5cvrMnY+uIUD0WUOV37x5c8tj4+Zz380p46DqVmnqee47JSqPGQEAAAAAAMB24KADAAAAAADFwUEHAAAAAACKg4MOAAAAAAAUR0ebEdRCcSUW357QMhKSuUI7JRJXgrOc2+Aj8aV7c68rElb5UswRXMHidIlv22EAMdk320d51djkjL8SEqb0gyt4VIYJKh61ZtQcjYwC1Li6xgzqeatWrbLWehSju68MDQ1Z+VT7VFoUjztX1LiqZyqDE/W8lP1VxajqVvnUfFamFbVpjTOukVGNao+aU64BiIonZa/YsGFDy/N07dq1TWlr1qxpShseHm5KW7dunR2jGpvIBMhBtU/NCdW3ESoe1zRH9U+uINwViat4VFs2btzYssA8mj8qrxoHNV7uHE8xI1B53T1SzWdVdmRkxCob9XlfX19T2vr16622qHxqj1P1pjzzGWIM3Tml+kLlU3tPFKPKO/HzgvqcEcE3OgAAAAAAUBwcdAAAAAAAoDg46AAAAAAAQHFw0AEAAAAAgOLoaDOCWjg2Xjzm3gQeiXddsZwqrwSrSqjrGhTkmhGoGKfKjMC9Vds1CVBxq3yRqNIV6ub0Y4oZgWq3qtsVVUbCaqdsZCbh1p1z+7rbtynPzLk9W/WjEhhH6yNFjNxOw40oHvfm92jdOPncPS7C3Q/duF2Rd0qfuc/MiVER3Vifs2erNePG6M6TqLzbbncNq7ZEa9A1s3CNZiajf9zy7rtC9UVu3K4ZgZqPufO+3SZAqi2qbMq+rvK6BhCqf9x4ojF0x/uZYv64Zd20qB/d9kyMx51PNXyjAwAAAAAAxcFBBwAAAAAAioODDgAAAAAAFAcHHQAAAAAAKI6ONiOoxcPjBcSuqC4SPLtiNyXcyjEZcMtGdStRlis8dw0BUoT1rhmBm0/F494an5K33eMa9Zkr1naNHnLGNcV4IiVvq/0Y9U2KcUE7TUZUjBNvaE4dB1XenePumknJ64ptVT61Z+bOM9fgQO17KkbXpKZm06ZNVj0qRpWmDC6i+eM8LyrvznH3eYoUUbZ7Y31O3K4oP2X/cQ08VF+ouRPtZ65ZgxuPazLhpkX15BhhRPPZnRPuOnTzqfFS7wDXtCJaS64w350TKYYSKu9mEaNr9uO2JcUwQaFinPhMd9+q4RsdAAAAAAAoDg46AAAAAABQHBx0AAAAAACgODjoAAAAAABAcXDQAQAAAACA4uho17XaFWK8M4TrmhS5NbkOMMpJR6W5TmMpLkWuE5Ny21Axug5Hua5rrlOMKuuOq2pflK6e6cY4Y8aMlt1xomeq8ipGVbdqnzvvU5zqov518uWkReluP6q1oFB9q9xjIiel0dHRprSZM2e27IiY6wDkrkP1TDV/XIejFHcu1caUtZTjYOmWT9kPW8Xt7yjd3e/VfFTPc92jIlTeHJdEdwyjOtxxdeeZuw6jeaLKu65rKp9qS67rmqpb5XVdRN01E+3X7meVnM80rptiNB/deZHj2ug6Q0Y8Ze4f7t7uPi+aZ+q96fSPu1Zr+EYHAAAAAACKg4MOAAAAAAAUBwcdAAAAAAAoDg46AAAAAABQHEWZEeQI0yKBmStuza07J0aFK/R30yLc8iruSAjfah3u86K8Ks0V8LvGE1F5d67k9IVrWpDyzHb3bcrcSxGZ54g33X5QQm8lHJ01a5b1zByzjijdFcGqetz5o0wdIlLa06qBh5s2GfG445piRuC2x90rcgxOome6xi6qz1zRurs+ovScd2RK3Qq3L9o9R1Pew249OUYqKbj9646N+znOXTNR3SlmBk7ZlHmm2CXB/MqpO+czaVTeWXMpn/f4RgcAAAAAAIqDgw4AAAAAABQHBx0AAAAAACgODjoAAAAAAFAcHW1GUIuYxguZXFFTah3txL31OeW2c7ceN1/KDc/uM93y6uZd1T/urc2RsNa9zVcJ3tSt4Sm4t127Y+PeQqzijua3arcaGxWje6u6EurPnj3bjscVxro3KA8NDVn5ovFX8Sjjgb6+PmuOuqL1SIjsijXVuCpjBdU/uUJUdSu2K4RX46r6Vo2BqiOap66wOvfmdzff4OCgJY5W46rS1PNU/6Tse+5e6r4PFa7hQe57Uz1TzVu1n0W4+3iO2F7NUTctZd7nGCukjJXqMzUn1dxVfavGULV5ZGTEHmu1vhSqvCrr7jPR3HHfu88wTRjcflRtUfmi/Vn1+cRnpqw3vtEBAAAAAIDi4KADAAAAAADFwUEHAAAAAACKY1IOOo888kj1lre8pVq4cGHjd+4PP/zw6tZbb93mdww/9rGPVXvuuWfj30888cTqvvvum4xQAAAAAABgJ6TtZgQbNmyoXvziF1fHH3989aMf/ajaY489GoeY+fPnb83z2c9+tvriF79Yfetb36r233//6qMf/Wh10kknVXfffbcUJkXUQqvxQjhXlB3hlldiSZXPFWSmmCioepRIL0eI6Ir/o3S3fI6w3h2DKN1Nc2/FThFf5pg95AiZ3fZFMbpzTwkRlWhU5YtE4jlrO0fwnHKLtDtXVBvdvsg1BcmJ272lO7fP3P0wZZ9y43FR/aPmqNsXrgg+BVWPu3/krJkUoxCXnHkSpbvGJW7dKeOl+tftH7ctOXM0Ss9Jc9vnmsdE88w1a8jJF717VHl3Lah8Ki137j3DrFs90+2zlPXvPnNiu5P2o6rNfOYzn6mWLVtWfeMb39iaVh9mxi/wCy+8sPrIRz5Svfa1r22kffvb364WL15cXXHFFdVpp53W7pAAAAAAAGAno+2/uvbDH/6wOuaYY6o3vOEN1aJFi6rnPe951de+9rWt//7ggw9Wq1atavy62hZ6e3urY489tlq+fLl8Zm0j19/fv80fAAAAAACAKTvo/O53v6u+8pWvVAceeGB19dVXV3/5l39Zvec972n8mlpNfcipqb/BGU/99y3/NpELLrigcRja8qf+xggAAAAAAGDKDjr171ceddRR1d/93d81vs0555xzqre//e3VxRdf3PIzzz///MZFcFv+rFy5sq0xAwAAAABAWbRdo1M7qR1yyCHbpB188MHVv/7rvzb+/5IlSxr/ffzxxxt5t1D//cgjj5TPrG/pVjd114Kn8aKn6IZwV/DsClld0ZgrGswVVSrxnhujK3aL+sY1V3DFtqp90XhNJBp/t92qH90b61NwRaKuQNDtHzdfisDQNdxQdau0aAxVXrUnqHhcYbU7l6PxzxF0qvYNDw83pXV3d1cuKTfHO2Jb96Z0lS/FzMQdw5y6U+JJuYncyafGJUWArXCfOWPGjLbvFTl9lrM21R4VjatrAOOa5uTMiRTcGN24c+t2801GPAq3z9VcydlnItOsHGMod69IMfVwDZ8UKp8yFcoxLkoxTZmYlrLe2v6NTu24tmLFim3S7r333mrffffdakxQH3auvfbarf9ea25uvvnm6rjjjmt3OAAAAAAAsBPS9m903v/+91cvetGLGr+69sY3vrH65S9/WX31q19t/Nlyenvf+95XffKTn2zoeLbYSy9durR63ete1+5wAAAAAABgJ6TtB53nP//51eWXX97Q1XziE59oHGRqO+nTTz99a54PfvCD1dDQUEO/s3HjxuolL3lJddVVVyXdoQMAAAAAADBlB52a//bf/lvjT0T9rU59CKr/AAAAAAAAdMRBZ6qoRVnjhVk5N2qnlG/3bd5uHU+X3qqw2o0nEpLl3FjuiklzbrFPidGtR/VtivgyZw7kpClS5lnOjcy5azPnVnUXd1yjWJQAM2d9KOOB+ptwVziu2vPEE0+0LHgdHR212qLyRX2m2q3a4+4LrnB8MnDF1m6+KO7oVnbHrEPNCSUwru+uc+bO08XZzjXs7j1RjDl1uwL1FHF0jkmFu6e4Ivioz9zyahxyRfRuPAp3HHLWa9Rnai3loNawMqnJfae1u39cg4LofeHs4yn7+uR/egAAAAAAAJhiOOgAAAAAAEBxcNABAAAAAIDi4KADAAAAAADF0fFmBOPFVq4wOhLFucIt97ZzV8jsCrWjvDk3SbumBSl9pnDFxDnmD+pW9ChGt3/ctBQThRyjADfNbXOEOzbu+sg1N1Dparxdob87f9znRQJK9cxonjoooX4kjFWkrG1H5Ov2T9TmHJMShVs2el5OG10BrtuWSFTt1qPKq3FwTTSieHKMIlzBs7t3pfRZzjxLufndjcc1KFD5IkOSVp+XYkrkvgPcvo3emyn9207TArd9uYYJ7npNEeG7JhW7mOvV3WdSzAhaNcJIeR7f6AAAAAAAQHFw0AEAAAAAgOLgoAMAAAAAAMXBQQcAAAAAAIqDgw4AAAAAABRHR7uu1e4T4x0oXHedFMcd113HzRc5irgx5jgAuY4rKY4prguc2xc5zjxRvpwxzCmb67iixsGt260jBbe868KSM9Yp5LgSuq5gUbpyzXHXl+qLFOc85cY2Y8YM65muk5/CddiL8ircfdOtOzeedpedDNy+cOd41D7X0cwdwxxHzJRxzVnvKXPKjSfHlSxnj0txgcxZr7muuG7/uC6AKePlls3ZN11HTNeBNHdt7pIxp1LWZo4LqcuOtTMDAAAAAAC0AQ46AAAAAABQHBx0AAAAAACgODjoAAAAAABAcXS0GUEten7yySe3+ftExv/79nDF+kpo5QqwXSIBmys8b7f4O8WMIKV8O2OMxPJqDrhifdU+Vzw3GYYSbtzu8ybDjMCN280Xpbvj6uLOvWhc222uoPYAZTAQrUFlPLB58+amtN12281+phOjIuozV1ir8qkYVf+o50VrOEesrcY6pe4cwbNbjytOHh0dtfLlCplzBNgpgvcUcwXnmSmGPS6uYY/bZ27/pOxRqh437skw61BzXL0D3PXhti/6XOnOXbXnup81FSkmNbuafZGzN7v5or5U5Seur5R3Pd/oAAAAAABAcXDQAQAAAACA4uCgAwAAAAAAxcFBBwAAAAAAiqOjzQhqcdN40ZIryEq5RVaJ6pSQTIlgc25ZzhV+KqFWjgAuRUzsiu1VWVdI6NYRtVulqfFXgm6VpojicQWPbtwqTdUxc+bMLMHzrFmzZF4nn6pbpam2ROLolDngrFeVpoSSKl+UV42rKu+KTl0xeYoIdmhoyKpHjZdqS4q5QY5JyWTgiondsc65ST7CFfq6RhpqvEZGRqyyEa0KjFMMV3JvWXfnVM7aTBlXF/eZOSY8UT2qje7nrmjfdJkK8xk3XzTP1HweHh5u2ZxHvfdUWZVvMkyONm3aZNWRMtZu3onzMWVt8Y0OAAAAAAAUBwcdAAAAAAAoDg46AAAAAABQHBx0AAAAAACgODrajKAWhI0Xhbki2EjwrERVbnlX3O7e0BwJIFW6K2xr9228U2VGkHv7eo6hgOqzHc2MQInElXDTjTsSW6p6VBtVPlV3ihmBe/uy6kdXlJ0iZFa4piKq3a7gPWVtusYnqn+UGL23t7etxgpRu3PE365hRjTW7q3h7j6Vc2N9dPu6e6O7O/dUPtcAJgW15lyxdI7RQ8radPcKt44Us5cUE6B2khuj+77PMQ7InVNuWYWaE7Nnz7af6RqX5M5xhbvf72LmU21x13A0zyZjXkyEb3QAAAAAAKA4OOgAAAAAAEBxcNABAAAAAIDi4KADAAAAAADF0dFmBLVQa7xYyxV5RqKoHMGi+7zJwK0nR3wXlW133UqY5oo8I/Gua9bgiu9cQV6EK950+1YJwlWbN2/ebNeh2ujeiqyE7CpGdZtzJBJXJgWucNztW9U+1Q/RTc6uocTQ0JBVVrXFvSk7xcRDCdSV8cCqVaua0ubNm2fFExlhDA4OtjzWqn2qb13DjNQ56bRbzZVon3LzrV+/3uqLuXPnWvNePa+7u9saq1xjD3dtuiL4FFxzFdUWddt9ym3wOQJ1NdYqn4pH7XFR3O47VuVTYn1XWB/tWyp295kqbrXWVd0qn3qXRjEqgxRVXu0fao6q8YrWgpoXm0SM7v6q8qk9V7Ul2j/UPqWeObHdqh0RfKMDAAAAAADFwUEHAAAAAACKg4MOAAAAAAAUBwcdAAAAAAAojo42I6iFUePFUUrEqkRokVDSFZQrgZgSX6nnuaLKSFymBGKu+FelubfxRn3j3p7siipVW9S4KqIYlRhQCQwVqu5IyOzG4/aPGi8Vt8qn5r3qh5RbsV3xX1dXlyXeVfki0boSb7q3ybu3dLti4MiMJMdIQ/W3K/xNEWWrPlPiVpWmjAc2btxojWvKWlC4piBKBK3yRfPM3TcjMbKzf7gGOSn7mTsvVN3qee67K0KtBVdEr8jtsxRTonYS9Zn6DOKaVLhj7X4mySXHtECRYirkpql1qPrCTYs+A6i6lTmPOzbueyoypHGf+QwxT922qLIphgnuZ7GJ5VPWL9/oAAAAAABAcXDQAQAAAACA4uCgAwAAAAAAxcFBBwAAAAAAiqOjzQhqMdL2BEkpAkq3fI4gOEc0GsXj3i7txpOSL+fGaleU7ZaN6m33TdtuvlzhZ7vnlGIyxKmT8cycdajSlBhYic5T5okSYEai91ZjVMLNXKG/Euq64lTXeCIS76p01+DEvbnb7dsoXdXtislz9vtIlK3GWwmUVYyqrDJWUAYFkXGA+/5R5d2y7p4SxdhuwbxropDSZyrNNShQ8yfnHZci9M+JMWXfUvura3zi1q3I7TO1v7rPVOtQ9bdrkJT7LnX70TWaitLb/RmCb3QAAAAAAKA4OOgAAAAAAEBxcNABAAAAAIDi4KADAAAAAADF0dFmBLXQb7zYz70xNhKCuSJPN80VWrq3Gke4dbtxpxg45JR3Y8x5Xko9OTcl58aT+8wdnakS76ryrjDaJfdG9Zxb3l1hfMoz3fYoYwX31vBNmzbJZ86dO7dlQwHVj25aZBKhYlfxuGYE6nlKYOyazETPVHlVPcrMQvWFev9EfeauJVXeLZszJ6LyrvGESlNjnWt8lGMgo9qtRPAp5JhMuOOlSDEVUm1U8ah87pxQRGPtGqS4a0GVdfNF7Gb2hWtSo9riPi8ymXDqTnmH840OAAAAAAAUBwcdAAAAAAAoDg46AAAAAABQHBx0AAAAAACgODjoAAAAAABAcXS061rtPjPeWUa5hCj3mMiZxXVxUY4Qqh63buVkETmPqPKqHtcNySVyAHLdPlynGNdVKsWpznU9ccuqNLd9URtdtzA1hup5rvtUisONKu8686j+dtuX4gKl1qbrVOc6LkW4Lk7K+cp13Upx7HPnhTt3BwcHrTrUGCp3tZo1a9ZY5V3HJVVW9XfkAOQ6Eqn5qNyDZs+ebaWpfty8ebOMsb+/3+of5QzW09Nj9c+CBQuselP2gBxHK9W3uW6lrnudWgsjIyNWjBEqTtcV1d3H1Xgp98Mobrd/3XGN3ofu89S82Lhxo/VMNcdV/6i6VZ9F7wW1ZtVc6evrs8ZalVUxDgwMyHjUfO4Tdat9T7VF9aMaAxWPen/UzJs3zyo/cZ5G+6OCb3QAAAAAAKA4OOgAAAAAAEBxcNABAAAAAIDi4KADAAAAAADF0dFmBLW4bbzALVfspsRgUb1OmhLzuYLnFDOCnBjduiPBsytuVmmuANttcyQQdNud02eu4P3p4nTy5QjMU4T17TZRcOdZNNauoYSKxx0b1/Qi2idUPeqZSvjpCn9V2VzDBIV6ZiTgd8pG9SpBuBL/uu1294poTqg+V2OjBNxqXqh87jxTZgLRM1VfqPKqf1Tcam0NDw9X7d4rXLG9O6eitemuL3evUH2bYoSg6nH3Ltf4KPoM0Wq+1Lyt7lPuGk4xgFB96xpCuGs4Ku+ubdfowf2cEsXzZLCvOHuu+7yU9aH2GtXnE80HMCMAAAAAAICdGg46AAAAAABQHBx0AAAAAACgODjoAAAAAABAcRRlRpB7Q2+OmYEroMwV5LmibiUGU3G7fZZiRqBQIrac8Uq5eVuVd4Wsbp/lmhHk1O3G44qgo3R3jru3y7vrKKVudxxcswY1LtEads1MXLMG19QjarM7hm7carzUPpNirqLS1fxR4tQck5FoDHP2bDUOrrFLyri4+6Y7d12jh5Q9zhXHu89U/eOaLUR1q37MidtdRxGu8YA7/q4gPBKJ54yXemaOCU+usN4t686JFPG/2rtcIwR3nkVj6JZ/ynym6jO3b1NMfFL2Gge+0QEAAAAAgOLgoAMAAAAAAMXBQQcAAAAAAIqDgw4AAAAAABRHR5sR1OKm8QInV2QViaJyyufcyO7e2hzhCtvctBQRYo4A0+0ztx9zxW5umht3JMDOqSdn7qX0bY4A282XEo97i3mOoDP3hmeFW7drKJJzM3lKeffGelcQHol3XSG8Kj86Olq1G9eMwDV6yDGpUX2TawChxlXdTK6I4lF154jo3bpdI4toHFS7XeG5GoOUd4C73lV73La4hjspBg4Kd1xz8+UYV6TMlVbfhdE4uMY3CjUnenp6rDpSTCF2Ef3jjr+770X93appjmuEVcM3OgAAAAAAUBwcdAAAAAAAoDg46AAAAAAAQHFw0AEAAAAAgOLoaDOCdevWVbNmzdr695GRkaybzd0bbJVYTtXtChvdm9KjdNVGJdR10xSR2M1tj4rRvWld5VP9MDw8LGPs7u5uShsYGGhK27RpkyWgU4LDlHnm3jruttEVtm7evNmOUdHX12fNcdWPqqyKO5qPqt1r166tHFyRcH9/v9U+tU9EfanmruoLFaMrJk6ZZ1HsExm/r25haGioKW327NlW3JFwdObMmVZed54+9thj1vqPUGtbzRXVbjWGqh9zykZjqOJWaWrNqPEaHBxsStt9992z1pcaa4UrHFdzwjVWiOJxxfpqbFLMMdx1qFB9oeJR+5l6B6h3Rcp7So2Xisddw5EIXu3FOSYDCxYssGJU4/rAAw/IZx566KFNafPmzbPWkhoH9d5btGhRloHDwoULrfJqn1qyZEnL7VP5oj5XYzNx7qrPGRF8owMAAAAAAMXBQQcAAAAAAIqDgw4AAAAAABQHBx0AAAAAACiOjjYjqEWm40Vvrgh+MswIVN2ucC/FjEAJI93bb7u6uux6XDMC1RfujfeusYJ7K3YkYlTtdsdVpbm3H0fxuO1WY+32oxI2pghEVexKyKriVvUo4aASO6qxiuJRInPVP+4eoOJxDUWiGNX8iUTmra6jaG268bioetQ8c2+6ThFwu7dgqzmhTBRcYXy0/6g55c4994b3CCVQVvNUjY1aX8qYRQmHI7MXd++KRO/O2nTfAaofIlRelabqVn2h9seUG+vdd4jqR1VWrS21D0fj4txOH+VzzVXceqM+U21U+VTcal9wDXLUuyJlXqi6Vdzqs4b6nKraF6UPibrV2Kh4VPtUmqpDpUV9rvJOnLuqXyP4RgcAAAAAAIqDgw4AAAAAABQHBx0AAAAAACgODjoAAAAAAFAcHW1GUIvWxgvXlGgwRUzsikTdm79TBOpujCrdFf+6aYpI7OaaGajyqh+VMFLVodJS+sy9fd1NyzUjULjj6ppZuGUjctqdM2+jueLegO2adbiC5xTcuF0zE8VkmBGofErAr8SyroFH1Beu4YaLiju6Vds1CnFRwmHX3CBaC248qu6enh6rHtVnKeLfFNOMdhLV4caj+rbdaSl5c8xDXFLeU1PxWSNqs7sHuGvYfS+4JgERroGU+9knxYhJ8aRpCuLuM645RvQ8tdeoZ05Mc9tRwzc6AAAAAABQHBx0AAAAAACgODjoAAAAAABAcXDQAQAAAACA4uCgAwAAAAAAxdHRrmu1W8OsWbOeNk+K65rrUqTSXBeVXBcN18FDuV4odwvXCSdyzFB94TrcuM4srkuV6oeo3aOjozKvU7fb5hQ3G7d8Tt+qtkRONuqZymlGOZ+oetQYuM5eEbNnz2557qq+VXuJ6ocUxy6V5rrFuGszmvc5LoJqbNSacV3XonF1nTLduF03pGjej4yMWDG6e5fqMzX31ByNXAVV/7hpXV1dTWkDAwPWWhgeHpbxpMTeqluU+46MxrXdDlLKgU7tC9HadPckdw9QDnspzleKdrvkuWOd47AY1aParcZLlVX5os+dahzcfUHNle19vt2eU50aw1FRt7vHKdTz1DqKPnO5n88mjkOKCyTf6AAAAAAAQHFw0AEAAAAAgOLgoAMAAAAAAMXR9oNO/XuGH/3oR6v999+/8Tv0z3rWs6q//du/3eZ3Bev//7GPfazac889G3lOPPHE6r777mt3KAAAAAAAsJPSdjOCz3zmM9VXvvKV6lvf+lZ16KGHVrfeemt15plnVr29vdV73vOeRp7Pfvaz1Re/+MVGnvpAVB+MTjrppOruu++2xVdbRGvjhWuuyDsSu+WUdwV0uaJKt54cIXKKsN5tj2vM4Io0XVOHKN01dXCfl9tnbvkc8e5UkSNiTTFwUGOYM/eUkN0VeUfPdM1McvoxZaxV3aof3bhVn7n9EKW7693dA5TQNhJlq7xKYOyaMChRrqrbNfXI3QPcPnPnaErdU2U84OIaCOWK+t26XfG3i2uYEe0z7lxRz0zZA9x8ao24+5S7DnM/Qypy9vuc/TqFMfNdo+p2P7OlGFqpd+zEMXQ/rzXqqNrMz3/+8+q1r31t9epXv7rx9/3226/6l3/5l+qXv/zl1g698MILq4985CONfDXf/va3q8WLF1dXXHFFddppp7U7JAAAAAAA2Mlo+6+uvehFL6quvfba6t577238/b/+67+qG2+8sTr55JMbf3/wwQerVatWNX5dbQv1tz3HHntstXz5cvnM2lauv79/mz8AAAAAAABT9o3Ohz/84cZB5KCDDmp8zVV/vfSpT32qOv300xv/Xh9yaupvcMZT/33Lv03kggsuqP7mb/6m3aECAAAAAEChtP0bne9973vVJZdcUl166aXVr371q4YO53Of+1zjv61y/vnnV319fVv/rFy5sq0xAwAAAABAWbT9G50PfOADjW91tmhtDj/88Or3v/9941uZM844o1qyZEkj/fHHH2+4rm2h/vuRRx4Z3pyqbk+tvzEaL45yBYuR6M8VA7oiP0WOqDaqxxUIusI2RYp4VwnbVJpbt6ojRUDrChaVuM0VHbvCxijdLZ9jmOAKx6PxcsurfErQrdZ0JMBWYlKFO/dybpeP1oIr6FRtyTHHyL3BXMXj1q1up04xYFD1qLnizvHaxTNHOK7GQc3noaGhpjRlpOOKv1PG330HqBvdc/Yjdw1G88J997n7cK4ZgcLdK9x80dxzRe/qme67S41/ym3yrslAu81wUkTmIyMjLedzzShUn0WfXVT54eFha49zBPhRvmhcVT1PmutYlVX7nmrz6Oio/Z5y9/sc2r5T1IM6cTHUk2JLZ9Qua/Vhp9bxbKH+Vbebb765Ou6449odDgAAAAAA7IS0/RudU045paHJ2WeffRr20r/+9a+rz3/+89VZZ5219aT/vve9r/rkJz9ZHXjggVvtpZcuXVq97nWva3c4AAAAAACwE9L2g85FF13UOLi8853vrFavXt04wPzFX/xF44LQLXzwgx9sfAV2zjnnVBs3bqxe8pKXVFdddVXSHToAAAAAAABTdtCZM2dO456c+k9E/a3OJz7xicYfAAAAAACAHf6gM524Ar+Iqbi52S0bxZJbvtV8kQjRrdsV209nn7l1u4LMFDMCN19OW9y0lHjcG7Bz+jvCvcU8x6DAFaxG5NStSInHFZm7t7S7MSqxaySAVUJUd1xdoX/KO8A1cVG/faAEuPUP/pw61FiliP9zbm93jQdSROKuoYC7llQ8k7GfqbjdtZAyXu46dA2EXDMKlRatDzVersmNeqY71in7q2uG4u7t7tqM1oKaA67Y3t271D4TmRGkrNl2vl/dsin9M3Eckta6nRMAAAAAAKBD4KADAAAAAADFwUEHAAAAAACKg4MOAAAAAAAUR0ebEdQiuPFCOCWAcsWFUXlXnOqK3XLE5FE8rrBR3TqfI4KOnukK1qJxcPpb9Y+KJUp341YxuoLFSFjv5lX1RG1s903Xrri53WOo8kXi766urraKW3t6eixxacoYuP2jxj9H/J87DipNiUZVX6i2zJw5U8Yze/Zsqx53fah5osY/EsAqoa/qX1W3Mh4YGBiwxjXH9CSKUa1h9wqH7u5uez6q/lXjrWJU7VZz1H2XRjG6fe4Ko5X4W7Uv2ntccx537qWsOVcknmNoo2JUpgWKKG41hmqeup9z1Bi6pg5qrUfzR8Wo8qmxVu8k1RaVL5pnm0W7XSMMlab6x91bo/f4yMjIdutx12oN3+gAAAAAAEBxcNABAAAAAIDi4KADAAAAAADFwUEHAAAAAACKo6PNCGoh63ghU85Nx1G6Kh8JplutO0WI6t52rp6pRF/u8yJUX+SYESiBmRInqvZFokrVblfkqYSNriFENM9U7K44NTI4cNqnhN/R81RfqrFRc1zV4wqjI4MB1ReqHoU7H9XzXBFrhLunuHMi5cZphbt3qXhyhNGRCF71ubunuHNClY0MJdxxcPczNdbDw8Mtz+VIeKziHhwctITRamzcfoxwb0tXY+iu15Rb3913sbu2VT53f0x5f7mGFO58VGsrxTTHfaYiN59Kd+NRbYnE8U6+JUuWyLxKRK/iUfncd7YS/6cYOAyL/cedF2qeqbao9RGZFsyfP9965sTyKSY8fKMDAAAAAADFwUEHAAAAAACKg4MOAAAAAAAUBwcdAAAAAAAojo42I6jFSOMFSUoM6Ap6o/JKzKUEWe6tyOp5KaJzV/Cq2uKmuULSlLyuWNIVmKk+i4SkrnBU5XPjzjUjUPW4N3e781GJASOxq3ujsitQV3GreKIxdNehot35ItR4ueYRKWuu3agYo7nbatkUc5WcZ7pjmHJjvTvH3bYogbES3+6+++6Vi6pbCYxzTE8iwwS1NpXBgWsIoIwiXIF5NM/UGM6YMcNqt8rn7veRGYGap6qNqi9UPCqf2l/d/SjKq9roroXIkMRpX9TnKq8S5qvxV/G4nxej/UPVrd5pKm53P1NxR+9NVX6miFHNPVWPSlNtUaZCkQGMazIxcQxT3o98owMAAAAAAMXBQQcAAAAAAIqDgw4AAAAAABQHBx0AAAAAACiOjjYjqEVQ44VQSvjnCiAjVHlX5Jkj/IxElSmCR0eEliveVQIz92Zr14xA1eHeYB6JaJV4Tz1T1Z0yfxSqvHsrtit4V/2oBILRPHPF8WruqXpUjOqGd1ewOlWi/hQhqps3Z0/KvSHeFSOr+aPSXCOMaJ9xDS5UP6q16c6fqL/VM1Wa6nMVt3uzvTIeWLt2rcy7ePHilk1KVDwqbvW8KB5333TjcfdcVTYaVzV/1PtQtVvFMzo6aqVFe4UrPFd1q7hVvr6+Pmu9pZjmqM8+Kk21RRluKCLRumJwcNCqR6W5hgCR0F+xYcMGq253H1fvUrUOU4x0RkQ87mcsNadUP27cuNHKF80f9Zlt4lrCjAAAAAAAAHZqOOgAAAAAAEBxcNABAAAAAIDi4KADAAAAAADFwUEHAAAAAACKo6Nd19asWbONO4Nyk0hxONq0aZNVXjlUqLqn03VNOcAMDQ1Z+RSRq4fruOI67qg+U3WospGry/DwcFNaf3+/5a6S4zITOVzltFu10XVdU/2Q4ro2MDBg1aPc1JQ7juv2FI3NunXrKgd3bJRjjlpbkQuPO4aqL1xcR7IINd7uHF+/fr3lcqb6WzlFRetQzQEVjzt/1LyP+kyNt5orOc6Lan247mo1jz/+uOVSNHfuXGvNqHGdP39+U9qCBQtkPGoc1Lxw9z3lzuS6Qql5EuHu46pudz+L3pspTolO3K6DnOqzlFhUG1V5Nf7umonyuY6sap6peBYtWmSVVZ8L68+eij322MN6X6i61Vp47LHHrPWh9riozxaJutUzlePbAw880JS2ZMkSa94vXLhQxqic3Pbee+/t9mP0WUHBNzoAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAEBxcNABAAAAAIDi6GgzglqINl6MpoRXStiWIsBWQjtXGOsK8CfDjMAVebpC5skwI3DboupwBfiRUFP1hULFqASQKbiiXFWPaqN6noo7EoS7qD5TY6PyuWlR3+YIj10zAlfwnCIwdvtH4a7NaN4rVDzuHqnyqf5RcUd9lrL3OflU36aIrd287rxQY+O2ORLbKuMBZVKiDAXc/lFjHZlwuOYROXNc5VMxRvNMpatnqjTXkMR9XpSe8/kjp31RjO7cdffXyJzHXf9uPKrPVJq7b6qy0R4eGSK1GqOqRxlhROtNrZEnzc8Qal2rsm5aiomPU3fKe49vdAAAAAAAoDg46AAAAAAAQHFw0AEAAAAAgOLgoAMAAAAAAMXR0WYEtShz/O2trjAtEm6p9BxxvBJZuSK9XDMCRXd3t12PK1jMEYSrulVb3NuPI7GjuhXZFdCqul0RbNS3rhmBK95UqPapm45T6lAxKkGgmmfuuERllchTlc8R/qbcqq5w56l7Y7mKWxlKROtf1a3aqOpRZefOnduySUQ0Vq6Q1V0fSryrnhcJ/VVfqnrUbemqz9Q8c8XEkbBejYMyHnj00Ueb0g488MCmtD333NNah9GN9e57052POaTsZ6ruSDDttEWVTTHhUGlqz3aNXdSN84pIWK/qdg1A1Hp1xzoyzVF7yCOPPGLFrdbr6Oio1b7h4eGmtN13313GqNq4du3aprShoaGWxf89PT1WHdE6HBbtUf3jGnOotqi0BQsWyBjnzJnTkplBtIcr+EYHAAAAAACKg4MOAAAAAAAUBwcdAAAAAAAoDg46AAAAAABQHB1tRnDTTTdtI4RT4jJX3B4JstzySiztCmhThPWukF31hRKxqjYrIlGle1u6W1aJ0Nwb61WbIxHjwMCAJSZVQstILOn2mStaVm10hcyqH5UYMMUwYePGjdbcU/WsWbOmKW3x4sV23/b39zel/exnP2t5fbii0UiArVCxu2YE7q3YKp5I5OsaHKi5p9qinucac0RrUwlr1TPdcVVjqMTJqt4or2vYkmO44RpC1Kxbt86aK8p44Kc//WlT2jHHHNOUdu+99zalHX300Un7nDOn3H3PNfpwDUqiPnNNStT73n2XphhuKNT6cOeZ2meiG+ZzTHMig4McVOxqvarxUm057LDDrL5VY/29731Pxvi2t73N2u9f+tKXWu3753/+Z2u9RiYaKv1lL3uZ1e7a7MsxGTjqqKOa0h588MGmtH333VfG+B//8R9Naa95zWu225b6nXLllVdWDnyjAwAAAAAAxcFBBwAAAAAAioODDgAAAAAAFAcHHQAAAAAAKI6ONiN4znOes41gSgleU0SeSrilBGKuOFEJG1XdU2VG4N4YnCI4VSJRlVfFqARwbj73tvJIlKlujVbjr+qOzCxc3DFUgk5lRqBiVPNW9UPKTeLKzEKNtRIxqrm3aNEiq45IMKsMDlxhtOoz9TznhuZ2jKGLqjsSE7v7jyv0Xr9+vSWCdk09UvZsFaN6ptqblfFIZDKh8roGMq6YXPWZel40rmoc1Hrfc889LSHzrbfeagm17777bhmPilOtd9WP7vtVjbXqs8iYQ+G+V1Q+JcpW6y3aj1S7Vd5or3H6e3h42PqcEt0wr9LVHFfjr8w+XKOI6P2q9grXiEfhmhaofliyZIl85h133GHt9ytWrLDGf+nSpU1pDzzwQJap0D333GOtL/Uef/jhh63PFY888ohlZhS1W/XjxHF110YN3+gAAAAAAEBxcNABAAAAAIDi4KADAAAAAADFwUEHAAAAAACKo6PNCFauXLnNbctKaOeKHSMRm0pTYrkcIwRXFBmVV21UQi3XjCDlNnjXXCHHjMCtIxKnqRu5+/v7rfJqrijxnUKNS0q7lUDQFYS7cyKaZypGJSZ0jTTUjfVK7BgJ9dV4qdvbI2GtE7cS70ZjqFD9q/YK18BD5VPrNUWIqvYptW+6817F7c7HmgULFrQsPFeo+TNv3jxrT4hiV33hirJVn6l5r9ZMNJfnz59vrVdVt1ozynjgzjvvbEp7xSteIeNxDUBUn7vGNWpOqD6LBO8qbzQHnL7N3StUXjV/VD633Y8++qhVRzTPVD2u0N/d4xRRP6p1qD7TqPmjxvpZz3qWVYfac5VYvuaFL3yhtSepulW71TpURgiR0F+154ADDrDyqT7bY489rOepsd53331ljMoM5eCDD97u3FPvsgi+0QEAAAAAgOLgoAMAAAAAAMXBQQcAAAAAAIqDgw4AAAAAABTHLmOuQmwHohYm9/b2Vpdddtk2YjTXjCAS2ysxsSqvhHaq7hxhfYpIXMWoBHSuGYEimibuTdSuGYFrHqH6TI1BJMrt6+tr2YxACWNV/6QYSqj+UXWrG7ndW9XnzJljlY1QfabareaZEmQuXLjQEo5HwsMf//jHVj+qNBX3unXrssS7Kq+aAymmEE7dkXjX3WvcuavG0J3Las1EJhOqH12zBjV/lHBcxRjV7eZT46DSVFuUQYEy8IgMHNScUvvr8573vKa0u+++uyntT/7kT6z1lmLg4M5xNa7uuzR6H6k+V2Jrdx9W+5F6l6a8A1wjFTVXVIzuXhG9A9w1p+aZWh/uZ4XIJEL1pepz1+hBfS5QdavnKTOBmgceeMDqHzWGau6pd6SqQ73bo7oXiP1Djata17/5zW+a0hYvXtyU9thjj1n1RuYq6jPExHGox/QnP/lJ43PJ3Llzq6eDb3QAAAAAAKA4OOgAAAAAAEBxcNABAAAAAIDi4KADAAAAAADFwUEHAAAAAACKw7PB2EGpXRjGOzEod4zIXSd6XqsuJW7dyskkxbErJ243LcV1TcWp8rp9ofKpOlS+qC05DkmKHOeqqLw7T9155jrPpMwz1w1Luf2osu64RPW480eR0u4cUlztWm1ztDbdtZQTj5svGpcc0093Haa8A1LytvN5at5HY+U6ASqXK9U/7rpWLkyRA9nuu+/esgOdcoBSqP6JHFXd/s1xRXX7O8J9L7jv0px+TBkvd467rmtRPtcRz/1M4pZ13WGjMVTjoOrOcemN+sxtz66ivOs4q+qIXDbb/Y6065j0GgAAAAAAAKYYDjoAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAEBxdLQZQS2WGi+YUuIpJRqLBIs5oroccZkrikwprwSmShTntjkSVboCQ1dI6MbtGhREwji3L1RZlTYZZgRqnirRscqn+nHmzJlWLFHsmzdvtuLu6uqy4pk9e7YtYlR1K1yxvmvWkGJaocq7RhE5QuaUeebuFQp3f00xPHD3PnccXPFt1LfuXqPmo4pHrTlX6B+JyVVed2wUar2m7PXKeGDt2rVNaXPmzLHGZnh42IpHzZPIMMEVVrvmQ27ZaAxVPJs2bbLqdvfxdevWWfmiGF0hvOqLkZERK00RzVvVZ0NDQy3vud3d3Vb71FqPPkOqvaKvr6/lz4tqTqi2qH5IqedJ8Q5Q7VZtUeu/v7/fyhd9pnH2ipT3DN/oAAAAAABAcXDQAQAAAACA4uCgAwAAAAAAxcFBBwAAAAAAiqOjzQhqEd14IZwrWI2EZAqVV4n3XCGyel6uGYF7e7Ibt1tH9ExXEO72hXuDcSSWVTG6t0a7xhMpZgQK97ZjlebOZ7fNETmGG27c0RgqkbFKc295V3Gr56XsH24bVZorwE9Zmzm3YrtGCOp5rqlHVLcq7653JdR250SEuz+rNuYYVEQxujeJu0J21T43XxS7EhMPDAxYe5L7zlXxKGFzhBJbq/FS9YyOjlr9EK1N992nyqs2qrFWY+C+h6O63fFSa9N9/0SGEqp/VHtU/6ixVkJ/15BGrY/omcr0QM0f1RZlFKLq7unpkfGoeTEiTCHU3uXue6rNisiMYu7cuS2ZTLgmOjV8owMAAAAAAMXBQQcAAAAAAIqDgw4AAAAAABQHBx0AAAAAACiOjjYjqMVJ4wVKrig/ElW65d0090b2lJu7XaG/K8BWuG2ZjHjcsm4sufHkxJgiJm53PTnjnyKMdePOHet290WKGD2n7GTM53aP61Ss4ZQYU/afduMaiLhr2BX0ugYVUT0qzTWZSDFCULgCdyVGV8Jxty9cU4aUcVX53LKu8UgUu6rHNVhSY+AafUS480yhYoyMZnLeATnjmjJeOf2oyDGAUflSzKueabbb7YsUUyGFa2g0cQyTzJ7snAAAAAAAAB0CBx0AAAAAACgODjoAAAAAAFAcHHQAAAAAAKA4OtqMoBYsjRctKQFTrnDLLa8EWa4gzxWsPl16qzG6osjcW7rdfnRFg26+yRDkubfBR+SI/Ny2uOLUCPcm+nbfnh31TYrw0KHdhgBR3nYLaFNw5497o/tkxO3OZ5eUvTTnmarPckTHas1EN8mrW8yna11H6cPDwy3vperW+Jw9M6Vu992n2pzbZ+47xF3X7vOi9eoaQLhj495kH+VzP5+5azNnr0jZU1R7Ut7Fre7XKeYaY+a7a/PmzVZfKJORqM2qPWp95OzjfKMDAAAAAADFwUEHAAAAAACKg4MOAAAAAAAUBwcdAAAAAAAojo42I6gFS+NFS0r0pQRMKUIwVyjlCs5cAX6KGYESorlxu6LjSJTtim3d27NzDBwiEaIqr/rCjVGJgVNE6+4YqrhV3a44VbU5EqKqdLfPVD4Vd4oAW/WFu47dOR7V7ZJjHuCKfCfDhMMVt06GEYYSrbr1uPMnZVxd8a6az+odoPrR7Z9oXHOE7O7aVGm5t8G7AmPV7qGhISvfrFmz7HjcsXHLqrkc7QlK1L1p0yYrHtVnau65nyuizxruXuO+X3PNTNzPcu772f3MlvKuUHNAzUk1f1Saa3wUjaFqz5OmKYRqy+zZs618qr9VvihGZ69J+sxl5wQAAAAAAOgQOOgAAAAAAEBxcNABAAAAAIDiSD7o3HDDDdUpp5xSLV26tPG7i1dccUXT78197GMfq/bcc8/G7/OdeOKJ1X333bdNnvXr11enn356NXfu3GrevHnV2WefXQ0ODua3BgAAAAAAoBUzgloUeMQRR1RnnXVWdeqppzb9+2c/+9nqi1/8YvWtb32r2n///auPfvSj1UknnVTdfffdW0VZ9SHnscceq6655pqGQOnMM8+szjnnnOrSSy9NiqU+aI0Xirki7xTRsCtOzanbNSiI8rqCRbctk9E/bl9Mxm3Frqg7d2xcckSiUzH3InLEpDntS8mbM16uMDpFlO2Wd9vi3kI+GX2Rs1ekmF64AtrJWK85c9etW5k/TIZIXNHufSYlb87+45poRAJlV/w9VbiGPTlpuXuuot3jmkK7Py+46zDlM6RrFOD2uWv2krI2XVxzBDeeaL3lfp6alIPOySef3PijqBt84YUXVh/5yEeq1772tY20b3/729XixYsb3/ycdtpp1T333FNdddVV1S233FIdc8wxjTwXXXRR9apXvar63Oc+1/imCAAAAAAAIIe2HrsffPDBatWqVY1fV9tCb29vdeyxx1bLly9v/L3+b/3ralsOOTV1/voEePPNN8vn1raL/f392/wBAAAAAACYkoNOfcipqb/BGU/99y3/Vv930aJFTb+qsGDBgq15JnLBBRc0Dkxb/ixbtqydYQMAAAAAQGF0hOva+eefX/X19W39s3LlyukOCQAAAAAAdmCSNTpPx5IlSxr/ffzxxxuua1uo/37kkUduzbN69eomoWntxLal/ERmzpzZ+KPSx986m3vjtCscVbfiusJIV0gaCbRcUaZC9WEuqn9dsaTbFve24kiIGs0d55k5Ny9HuEI9Nc9U3KofVZqKO0UI6LY758b6aI6q/lG3NCvRuopRzTP31udo/1BzxTUUcE1GVDzR+s+52dxFxeiKWKPY3fJq/qg5miJazxFRq7Lu3pxiPOHuuWr81S3t6nluvihOVT66Gb3V56k2Dw8P28/cvHmz9cycMUyZZ6p/3bmr9r05c+Y8bbxPV2+0Dt09zhX6K9QaTvm84OYbGRmxYlRp0Xuqllk475X6B/YOqqyqW62PaI/csGGD9Uz3eWodqT4bHR2Vz1Sx1+eB7T1Tzfkp+UandlmrDyvXXnvt1rRaT1Nrb4477rjG3+v/bty4sbrtttu25rnuuusai6rW8gAAAAAAAOSS/KO8+r6b+++/fxsDgttvv72hsdlnn32q973vfdUnP/nJ6sADD9xqL107qb3uda9r5D/44IOrV77yldXb3/726uKLL278lOfcc89tOLLhuAYAAAAAANNy0Ln11lur448/fuvfzzvvvMZ/zzjjjOqb3/xm9cEPfrBx1059L079zc1LXvKShp30+K+nLrnkksbh5oQTTmh8HfX617++cfcOAAAAAADAtBx0Xv7ylz+tHqH+veBPfOITjT8R9bc/qZeDAgAAAAAAFOW6BgAAAAAAMG2uazsLKQ5brT4vxQ1rKuqO2uw6rCkHF1WPyuf2d26MbtxujNEYunW7bj9ujDlOONEz3bjdeHLXVorzUavPi/rMzeumqT5z86XUo3D3H9cxMsXZTZV3HeRcojkR9WWrqDmu0pSDUEos7X4npbwDXKdMtx53XFPc/QYGBiy3pxxXVNUPyoUril3NAVWPu8epfCmfK9y6XQc5d1yjuZPTHnc+5+4zrjukaqMaf7e/oxhz9vtniLJqzai4lYtb5Lqo+sf5XOF+PqrhGx0AAAAAACgODjoAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAEBxdLQZQS3oGi/qUqKmFEGuK/51hWSu2C0lRlcYqeJRcas+U0RCVPVMV9Sv2uL2d4rgWaWrNDfGHBF0iqhSjY0S9OUIRKN5psbQ7TP1TFeQGY3hjBkzrDTXMEGluULLSACbIhJ1yroC81xzBHcMlcA0Z++JnumK29X4u89LEe+7pgDuulZzwm1Lyjp0+0zFo+qO4lFtVPVs3rxZlnficQ1XojrU2h4dHW1K6+rqalnor9oc7RVqP1TtdgXXKp9qc8r+4a5jd09xDSqieaZQ/aveka45Qs56TRkH9/2s+kLNnWisU8yGHFQ8rhmBMgSJ2uO8dzEjAAAAAACAnRoOOgAAAAAAUBwcdAAAAAAAoDg46AAAAAAAQHF0tBnBVJBz47RrRuCKpXPjyWGq6nX7QvVju281n27cPk+ZP24+95ntXh/tyOvgmha4+aK8rslASj1uvpw+y4nHNVyJnuncih2lqbjdfJEI1u0LVY8SRivBvCuqjup2hfnuXqqI+kyNreoL19jDfUcqonzqmcp4YHh42BJ65+6FbhtdA6Gc96E7/inlUwyW3HhUeTXH3bmnxlqNgWs0lSLWV3W7e5eaE5EwX8W52TQFUah6lKmHG0uKoc3E8pgRAAAAAADATg0HHQAAAAAAKA4OOgAAAAAAUBwcdAAAAAAAoDg62oygFuWNF+a5YsfotnJXTOze6O7eqJwi3lWxu2JQJWJ0BV2RkMxtt0pz2+LexhzdVqzardLcGFU9KULUnJuklUDZnT+uiDVqj9tnKp+KW+WLbs92+0fNZ1eArcbaFX5HqHFw532OIUBu3a4wOieWKB6FO14qTc2zaAxzzBHctijUnqLizt3H3RviVVo0/q7wvN3GA4qoH9y1rYwHlNi6u7u75b6N6nHH0O0zdz5G+VQ97rvY/SyWsldM1Z7txBOtTfWec2NUqP5O+Uyb84580jRhcD9/5pqZuM+Tddg5AQAAAAAAOgQOOgAAAAAAUBwcdAAAAAAAoDg46AAAAAAAQHF0tBlBfbvseCHTyMhIlmjUvWVXCbxU3a4IOkVc5oqW3dtqN23aZOWLxHOu4NHtC1cErcpGbVZ5h4aGWhYSqnwpN47ntFvdqNxuMWiEe5uzSlNlZ8+ebd0sHa1NNx6FG6N7233U52r+qHnqzglVh0qLnpkjmFf94/ZtFKPaN10RrMqnRN4p80TNM9cUQs0V9Ty3jmg/GxwctJ6p9gXV32ovVH2Wsr8qcwX3nZRiHuHiGraocVXGA6rPUkTVrqGE+/lFrQX33R6J/93PPqpvXfMZRcp7SrVb1Z0Tj+qHaC9UY6PGwTV2UWtGtVmt/5Q9cqZ476p8q1evtta62meid7vqH/XMiXtAyjzhGx0AAAAAACgODjoAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAEBxdLQZQS0wGy/CUoKzlBta3fKu6EvV494YnXKLrMrrCvIikbAbj8K9mVgJ8tx4VJ9FZV0Bd47JQIoZgTuG6pkqRlcEq9ocCVFd8beK2xXVpgjrldjSXa/ubffu+ohEvu56V+WViNXtx2htuvNUlXcFxi7RPMvZs1VblHjXFf+nCLhz5rNrehKJ9911qNqt2ucaK0R9496+7grr3fdZrrBeCZ5dUxhVz8DAgFVHVN6NUYnoU+aPUzYFd/xd8Xg01qq8awKl1oLKlzsflYDfHQfVZ65ZS4o5wi4ZpkTuu0K1ec6cOfKZqj3O2nQ/K9bwjQ4AAAAAABQHBx0AAAAAACgODjoAAAAAAFAcHHQAAAAAAKA4OtqMoFXRsUpLEby6t8G7ZV1xeopxQdRGt57p6jM3TfVDZBzhiptz0lLMCBRuG92yrklANK7uGLqi41xhvTufFTniS0WKgUMnoPrH7bOUvavduDG6cznFfMZtY86aSVkLOe8AN1/U36q8EsyrGJVYWpXNGevISMF9pmsUogTU0Y310S3xTowqTa1Dd22mjGtOnynTArdsVHdO/+S8F6J55rbbrVvlyzUYeIY5V1SaWputmgmkmmFMXHPuXl3DNzoAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAEBxcNABAAAAAIDi4KADAAAAAADF0dGua7WjyXgXiCeeeCLLzSanvCrrOqyluB4pBw/leqHcXpRjhoo7xaWo3a5rqi3qeaofVVuidNU/Ks1tX4pDjeuQouaeO16qrBr/yPFEtdvtH5UvZwxSnpnjvJjjFhfNXdW/OQ5ZKftZ5A7noMqq9qn9KMV9LsUJ0FlHue8Ad59yHa1clyt3j0tpj6pHjaE7x1Pmk5oXai24zk5q/af0meof191t1qxZVllVd+SuNjAwYNWj3KtcVzGXXIdXt2xuPAr385TK193dbY2B+3kvGi9Vd09PT1vXZkqfdXV1WfNZ9YWaz2pdq7UZue6p2GfPnr3d/lH9FcE3OgAAAAAAUBwcdAAAAAAAoDg46AAAAAAAQHFw0AEAAAAAgOLoaDOCdgrjp4oU0bpbvt3kCAmj8u4zc+t2yaknN0ZXyOyKlt3+ThmXHNOMHIFoFI9rHpCz3tXzXIFoSjw5Qm/VliienL5w56hrHhKNqyvgV890xagp/aDidMW2rmmBK9RN2evdPs/p20iArdq4adMmKx43RvW8FMGzaxQyGSYlCiX0Hh0dtUTiromCO9aRIY3CNYBw9wpX0J9irpFTt/tuj/aPFIMdBzWn1DxRxgq5jImxVm1Ra841w4ryqjk1cZ6m7I98owMAAAAAAMXBQQcAAAAAAIqDgw4AAAAAABQHBx0AAAAAACiOjjYjqAVh40VhrkB0MoSxbllXAJkiynbTUoTMLq4gLCduNy2l7pxxzY3HfaZb1hWy5xpz5Iy1O89y43HL55h6RGXbbRSSs8/kim1z+jblxmp3Laj5E4lbnTZHonV3DFU86pmqL9R6dUXnKfGoG9BdMXDKe8Hdk3LeP+6eGz1PzQF3DBWqrBLRR+tN5VXjPTAwYNWtPlcsWLAga6/IEfCrsu58jt5nKnY1Xu6cUmVVP6YYhSijgLlz51rPdAT4kSlING/d9sww56MaV2WE4K6jaP9RcWNGAAAAAAAAMA4OOgAAAAAAUBwcdAAAAAAAoDg46AAAAAAAQHF0tBlBLYIbL4RLufk9el4703Jul0+5sT5HoJ5TR0r/trvPUmj3OOTG4+KOoXv7em7c7W537tp0+8c1JFECyBTxvxLBugJTdwxVvhQBds58VnHnmBtEz3RF4qqsK6DNxY3HvXVeiYFnzpxp1+0KjN141LjOnj1b5lXrQcWuRNSusN5dH9E8c/cKNX/cvcItG6Wr8qp/hoeHm9JmzZpljUGKEY67/7ii8Jz3Wco8c/d7dx2peKIYXZOKds/HyOjBbeOuGWmqbjUu7f4snvI8vtEBAAAAAIDi4KADAAAAAADFwUEHAAAAAACKg4MOAAAAAAAUR0ebEdSCp0iwmSoQTrll170p1xXzpYjdXDGyEkuqvnKF+pHgsN194d5+rIjEaUqoqYS1rphY9WOuMFblVSI/Jeh1RayqzSmCPlW3298qHndconFQed1bsdU8U/GkCMzVuOaIW11DiUiImmPg0G5Th6jP3BvrFUrkq8Yw5QZtd46rGF2jB3etR+Pq7j9u/3R1dVn5on045z3nllWGEqpsZDyh8rpj6NbjmihE6e5aUmMzOjra8nshitEV8Kv+UetIzUdFlM8VwrvmI6rP3D08ek+547Bp0yarH9VaV/FEn4PV/BkWZhZqrF2TKzXW7pyIYh8aGtpu3SkmM3yjAwAAAAAAxcFBBwAAAAAAioODDgAAAAAAFAcHHQAAAAAAKI6ONiNYvXr1NkLKkZGRloX6kVhKCZ6UWE7V7Yp3XWFiyk3iSuzW09Nj5VOkmBG45VVbVH8rMZ/qMzUGkXCwv7+/KW3z5s1W3a4YOEK1W80VlW9wcLDlfuzt7c0Sovb19Vlxz5kzpylt48aNVt1qDKLxWrlypbUWVIyqf1SM7p7wdOlOPndOpAgw1TPVuLrPdG+2V+MaCevVuLoxqr1HPU8JhHP3KbVvqjS1V7jPU+stGgc1V1T57u5uS5z86KOPWvVGY7tu3TprX1BjmPPeVHVEeZWo392H1Xi54vYIVfeCBQusOaXG4K677rLanGJ64fZjynx26og+dw0MDLS87y1btsxqs3onqfVRc8ABBzSl3XvvvU1pz3nOc6w9TpVV6/Duu++2++zwww+31qEqu2HDhqa0RYsWNaU9/vjjVt9s+RzfSv+4xjE1fKMDAAAAAADFwUEHAAAAAACKg4MOAAAAAAAUBwcdAAAAAAAojo42I6jFSOMFSa5YNhKOpwiPHcGae7NsimBRicZUjKotKsZI/O32mXuLucIV0bs3xEdtUX3m9o9bd4oZgRpvVwSrYnT7UQlEU8wIVHkVtxK3unMvGkPVHjdN4Qr91fxOMSNwhfXuOlJlVVuisXXNTBTubd6RkYr7TIVrMqHmj1tH7jp061H7Ucp+5t5i7vajMnHJmaPR3FNzxY07972ZMifbidu+lP5RaWpslEmAMkxIidE1TkoxTXHNolT/qDT3M587J1RZ93NTytx1DWnczw8p5XcRfeGaOqg016QqitEZ66TPXHZOAAAAAACADoGDDgAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAUBwdbUZQC97aaUagBGauAFPVrepxhWCRUM4V36l43LQUsb0rCHOFlm5/qxijm3LddrsCSldom1LeFeS5t6K7cyLFjMA1a8iZe9EYusYD7np3zQhSDA9UumsU4Qpj3T0u5dZ5VT5lfeXg7j8qRrdvc/o7d4/LEUFHomzXmEHdbO4a1+TuFcqQJGqP8zz3vZkigs4RZbti8misXdMLhfu5Qo2Ba+AxVSL6XOMjVbe75tRccffMaC90548am5zPBSn72W6ibtVutX+oGN1+jMbffW9mmWjYOQEAAAAAADoEDjoAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAEBxcNABAAAAAIDi6GjXtdppYrzbhOuGFTlUuOVdNxLlCpHjKJNS3nU4SXF8a7cDmVu3G0/KuObU7cYT9YP7THcMVT7XSSuXnGem9K3rfOQ6X7nuMSluLzn1uE6HyqHGnScRuXtSjtNlztp243bnThSn+0zXpSjXeVOh5kVXV5dVd67zphpv933ounO5fRGtTVXeddl0XQAVufNexeh+ppk5c6ZVR7QWRkdHLccuFzeeqG9UX6g1t2nTJvuZ7XY5UzG67ncK1T5VdtasWbK8uw7bjdof3TUT5Z2YhusaAAAAAADs1HDQAQAAAACA4uCgAwAAAAAAxcFBBwAAAAAAiqOjzQhq4dd48ZcSVSpRUyRiUkIyV7Co6naFrSlCdFfkpeJ286UIUV3jAVck7grWUsSlKl2Nlyv8VGPgti9Kd40r3P7JGeupqlvlU+MSlXef6c7RnDqivMp4IGUcnLLRfpZjmqLyuXthihGGmzdnn3HX1mSYNbhGBiotMsdw50+OIYArqk55z7mi7BxDiajPcsxHVD63bDTPXNF7Tlvc9R991lDjpfZndz67RP2g+kzVo/rcHUN3XJVRQ0p512TAFdynmHDMEHWrsVZprgmL6odo/3D3monz1F0vjbJ2TgAAAAAAgA6Bgw4AAAAAABQHBx0AAAAAACgODjoAAAAAAFAcHW1GUIuRxguSXEF4itgt55kpdbv5cupxxW4pYmD3VvacenJjzOkfV9CbM9aTEWOuKFulu8JI51bj6HmTcWuze+t8zi32KeVdAW2OEUZEjqDXTUsxTHDFu25ZFU+uWNrNq0S5rnA8xYzANdxQ8aSYuDgxRmOr6nb70e2LFBOfnLXt5suZyyn1uO+KWbNmWc/LXQtKmD9nzpyW+ydFtK7a6O6b7jrMZebMmS3PR9dkQvVDSj3PzDBIcY1Hcpk4d1MMZfhGBwAAAAAAioODDgAAAAAAFAcHHQAAAAAAKI7kg84NN9xQnXLKKdXSpUsbvyN3xRVXbHOZ1Ic+9KHq8MMPr7q7uxt53va2t1WPPvroNs9Yv359dfrpp1dz586t5s2bV5199tnV4OBge1oEAAAAAAA7PcnquaGhoeqII46ozjrrrOrUU0/d5t+Gh4erX/3qV9VHP/rRRp4NGzZU733ve6vXvOY11a233ro1X33Ieeyxx6prrrmmcTg688wzq3POOae69NJLk2KpBVizZ89+2jxKuBkJztxbzJXQMufG6BSBoCqv2qjydXV1WfWkCP1dgaErglZtUcK2lD5Tc2Tz5s1WPeqZrgAyxcDBFfS6twirfPUPH3LMCFzRsppn6kZtFY9Ki/pMiTxVPQo1Nu48S0GtD1V3jjFHNO9d8wCFqlutI3dO5Aq11b6gyBEnT4ZI3K3HNRRJEZm7e0pPT0/Le0rEyMiINQfccXVuSn+656m6XWMX1W61z6R81nDHy+1zFc+mTZus56UYwKj2KOOBgYGBrHoUqn9Vu9XcU/NemSi4nwHVO66mv7/fGgdVt0LNR9XmFEOaUVG3a7BUf/534qnPAk6+CKeN7t5Rk/z2Ofnkkxt/FL29vY3Dy3i+9KUvVS94wQuqhx9+uNpnn32qe+65p7rqqquqW265pTrmmGMaeS666KLqVa96VfW5z32u8S0QAAAAAADADq3R6evra/z0ov4VtZrly5c3/v+WQ07NiSee2Di53nzzzfIZ9Ym4PimP/wMAAAAAADAtB536K7Jas/OmN72pocepWbVqVbVo0aKmrwsXLFjQ+DfFBRdc0Pi2aMufZcuWTWbYAAAAAADQ4UzaQaf+Hbs3vvGNjd+r+8pXvpL1rPPPP7/xzdCWPytXrmxbnAAAAAAAUB55CtHtHHJ+//vfV9ddd93Wb3NqlixZUq1evbpJ7FU7sdX/pqhFx0p43KrQNkWAnXOrunsTfcrt6+2OMbpJ2o3HjT3nRuacG6yj9JxnunFH4sscQ4qcm47d28WjZ7qCciX8VGJi95blFLGkm+beLq/yReOqyrtiYnf/SBGtu/PHFVbnzNtonuXMcXf+pNyAnnPjvSv+V89TBgNKVJ3Sv27croFD9DyVrmJ39wC1Ztx3e7R/5Nzyrup2jUtSTDhcoxkVo5pn9Q+Fc/rM+cyVYvSghOy5701XhK9iVGmqH1M+n6lnKjMC16RG9YXaryOhvzsnn9FmwxV3L0yZ9zvUNzpbDjn33Xdf9ZOf/KRauHDhNv9+3HHHVRs3bqxuu+22rWn1YajumGOPPbbd4QAAAAAAwE5I8jc69X03999//9a/P/jgg9Xtt9/e0Njsueee1f/4H/+jYTF95ZVXNn4quEV3U/97faI7+OCDq1e+8pXV29/+9uriiy9uHIzOPffc6rTTTsNxDQAAAAAApuegU9+Hc/zxx2/9+3nnndf47xlnnFH97//9v6sf/vCHjb8feeSR25S7/vrrq5e//OWN/3/JJZc0DjcnnHBC4yuz17/+9dUXv/jF3LYAAAAAAAC0dtCpDytP93uRzu9M1t/upF4OCgAAAAAAsMPcowMAAAAAADDVcNABAAAAAIDi4KADAAAAAADFwUEHAAAAAACKg4MOAAAAAAAUR7Lr2o5Efcno+BtY3VvMo5t3c25fb3fZFNxb3t0Y3Vuoo/JuvpyyuTHmpE0n7Y4n6keVnns7ufO8qH1qjqsblVWaeqZ6nrt/pMTo9k/OHhCNizsOLuoGbNXfuTeJq3rUM1VZVY96XnRjvVuPO1fU7fLujezR7eBu/7g326t6VPui57n9M2vWLGstqTnl7j3R7esqRtUeVY87n9Xt9GqsUm6OV3WrNLesiifaz9z92b3F3t3jRkZGZHp3d7fVHtUXaqxVPjVH1bhu2rRJxqieqfpMxePuKYqU98cMEaNaH2pc3X50xyDqXzUOOe83vtEBAAAAAIDi4KADAAAAAADFwUEHAAAAAACKg4MOAAAAAAAUBwcdAAAAAAAojo52XavdWcY7Nij3BteFKSrvOimpsqoe10UlxUlJxaji2bx5s5Wm6oj6TLmeqNiVK4gq6+ZTqDZH5VVelabiUQ4lKW56brsVarwUak4op5jIuUSNYeQ047i1qLJuW1Jc0tz1muOIGNWh8rbbYU3tZ9HzXIc+9UyFGkN378l1hnPd79w5keLY4/aPQtWt9o+UOeG6DSrnIhXP6OioFWM0hu4e6bp45bwjo3eFO94p72InX4o7qPvedPvbdQCL9jN3r1H5ctacclerGRoaakrbY4892jpX3Hwp7y61Dl3nRNclL3IbdB0ndzVd11yXTHfupbyzc+AbHQAAAAAAKA4OOgAAAAAAUBwcdAAAAAAAoDg46AAAAAAAQHF0tBlBLYIaL4RyBZAqX4rg1RWSqeflCBujdFfkp9qthIS5Ako3Rrcet2xkRpATTzRXHKJxyRFgu2VdIXrKPFNprpDQNdGI+jtFeNyq0FvFk2Iy4Y6NErKqdk+GSNOtxxWJq7JdXV2WsLVm48aNTWmuqYw7T5TYPrfPRkZGrHFVwmpXvDs4OCjjUX2p2v3II49YY6Pap/KpsYrKK+G4mlOuQYH7bo/WjLufqTFU46Xmo5oTKSYc6pmq3TNnzrTmxMDAQMufZ6I5qfIqsb1rzqSI4lHGAw899FBTWm9vr7UHLF682DJcGR4etsYgGge1bvr6+qzxV/kWLVrUlLZmzRp7nvX397c8z9SepGJUbV6yZImMcffdd7fGa2L/pBhC8I0OAAAAAAAUBwcdAAAAAAAoDg46AAAAAABQHBx0AAAAAACgODrajKAWWo0XrinhlSuqjdJzbrB1RfApt3S7hgIqX07ckZDQFesrAbcrJs+5wTiKsd1j7Qoto2e6wkZVVrUvR9AbpeeMg4rbbV/KjcyugYMryk25Sdyd46rd7lpIMShIid0pOxkGDjm4fZtyS3uOIUnO7eJK+KvE7bmmEO77Q41XitBflY/MYpx6lDDe3ZsjVDzufHbF9in7q9vnKp8aQ9UXbvsiYb772SCauw5qrKPxVsYDShyvTEFUP7p7eDSuqt05n3OU0cP69eut9qXUrcgx61BEhjLKeKDd7wu+0QEAAAAAgOLgoAMAAAAAAMXBQQcAAAAAAIqDgw4AAAAAABRHR5sR1CKo8UKoHNFXlO6aGbgCczdfFGOOiF6luTdGR7h53XiUWNKNMUX46caTYhThxpOT140npW4XtRbcNFd8m2JG4N4Q74ryc4w1cud4u+derrDeFZO6xgoqX4oQVaW5c9x9XpSu2q1Ex2pc3bF264gEyqoeJSZ355QyR4jExO76UkJmdwxzzDGienKMGZQZgWpfivFR1L+t9pm7F6a8N11TGGUo4O49au5F8aj9Qwnzh4aGrPFSY6Dq2H333WWMal6ovlDPdOe4ep5qS/TMzSKvu0+5Y6D6MTIj6enpsfauic90zU1q+EYHAAAAAACKg4MOAAAAAAAUBwcdAAAAAAAoDg46AAAAAABQHB1tRnDIIYdsI2RyBaKR0N8VaSlRnarbFf65YvkoXYkllZhLifSUkEwRCeVUX7gCdTUOruDZFcVF7e7v77fGX7XPbXMk8nTHUPXP8PCw9Tw1b5XoL4pRtWdgYMCKe/bs2db6mD9/flPawoULZTxqbB999FErHjdt3bp11nxUaytlDqi2uLeY595Yr+aueqZqS46ANhIiq3Wo2uPuCwsWLLCEyFGfqbHNmVNqT1H9qAwGohviFy1a1LKI+rDDDrPG5lnPelZT2iOPPCLjUeXVnqv61r11XrVPjWFk4OC+f9T+qlBzL+UdEN1k3+r7R431smXL2m5QkhOPW08079V4LV68uOV1eMcddzSlzZkzxxrrl73sZTLGa665pint2c9+dlPaXXfdZc3nU045pSntvvvua0qbO3eujEd9NrjzzjutNqo9aenSpU1pv/nNb6x6f/vb38oYX/GKVzSl3Xbbbdsd12gPV/CNDgAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAUBwcdAAAAAAAoDg62oygFtaNF9cpAVTuTcBuvnaXTRGyT0Y9rujYvX3ZJSfGlGdORd25cSvc24pzccfQNZ7IqSNqtxK3ujc8u+YPKsZIVKue6cbt7l25uPuHwu0fRdRnrjmCK2R210fUD25ed/64a9OdO0+X7uRTMbpzNOXGevVMZSiQE4/KlzKu7X53RSZHCiX0VvGoZ7p9EY2X87yUdejGGJkMOH0T9Y9rHqLmnjIeUIY7ysQnmmeqjUror+Jxx1+Z/ag6omc+ZZrPuHupilHFo+qN8irziIl9Fj1PwTc6AAAAAABQHBx0AAAAAACgODjoAAAAAABAcXDQAQAAAACA4uhoM4L69t3xojd1G68SJ0eiQSVsU+VVmqrbFZimiGVV7KoedUO0e4OxIrqFVqW7AnXVFvcGbPfG+ajdaqyVAE4J5dwxSBETu+VVG92bxFVbIrG0isddH6p/VFk3LZrP7npXbXFvVX/iiSesvk0ZQ1WPuxZcIWmEKu+mqf5OMXtRqPFWfe6aTKgY3XkSxaPaqPYKFY96nvuuUHVEz1TtGR4ebnmOu3VEc1fFnnKTeaui6pT3prvm1DPdfSbCzesaD6h8agzUXI5iyTFmcPtRoeZjNF5qjqt8as2p96EyHhgcHLSeFxlAuHWrcVDtc/NFzBQxuuYRav9Q+dTcmzt3rj3e3d3d282Xsp/wjQ4AAAAAABQHBx0AAAAAACgODjoAAAAAAFAcHHQAAAAAAKA4dhmbjOu3J5n+/v6qt7e3+ou/+ItthFVKKOWKslMElK6o3xVLptx2r4R2KkYlJlUCr0j87eLeBu7eJO72tytEjm5aVjcgq75QdXd1dTWlJd3Sa5oRqHlaz30nRtWP9ZrJmWcbN26sHNSN0+vWrWtK23PPPe1bsZXY8pprrmlZ8KoElCpGRTTWqi9VPWqeqX1K9YUSbkbmKq5JhZo/6vZttT+6t6+nGHO4t68r1q5da7UluqVd9bmK0d271PPUPpyyf6xZs8Zqj9qn7rzzzqa0JUuWWHUcc8wxMh7XkETNFfcd6RqpuPMx6jP1cUjVrfYjtTajj1cqb86N9WqOP/roo9YajsT/7v6hUHPPNSmJ+kzF7n7+UHvKoYce2vLnim984xsyxre//e1NaXfddVdT2ote9CJrHf3gBz9oStt///2tfS965pve9KaW3wFXX311U9qRRx7ZlPbQQw81pe21114yxv/4j/9oSjvrrLO2O0/rcfn4xz9e9fX1hUYHW+AbHQAAAAAAKA4OOgAAAAAAUBwcdAAAAAAAoDg46AAAAAAAQHFw0AEAAAAAgOLoaNe1n//851VPT8/Tuq65jjAprmvKhUXV7TqmTJXrmnLRUPlU3dE0UW4dKq/bFyqf66wSOcgplyPlIOa6urjOPlGfuf2rXIGUW5zruqb6IQVVt4pbzTNVdtGiRU1pkXuKGlvlAOO6AimHIzUnlCORmidR3Wr+qGe6Tnyq7qjN7l7jrlc1Bmqe5e65qt0qTa2P+fPnWw5ZEZEDlROPGgfXXUvtKRs2bJB1qzaq949yfHvuc5/blHbHHXc0pe23335NaTfeeKOMx31/5Th8uv0Y1eG+N9U4uE6Hqr+jea/mrloLyvFLxa3yHXDAAZVD9FnDdWhUqHjcspEjohpv1edqLSjU+lJ1qznxghe8QD7za1/7WlPa8ccf35S2fv16axyOPvroprSbbrrJHmvV548KNz537qo+U3UMDg7a782jjjqqKW3VqlXbraeen/WehOsaAAAAAADslHDQAQAAAACA4uCgAwAAAAAAxcFBBwAAAAAAisNTh+2g3HnnndsIn13hnjITSBH6KsGaEsAp8Zwr3IwEgq6QXYky58yZ03YzAlfwrPpCidhUf6vxUjGq8Y+Edkocr8bfFSemeHookZ/qH5WvNuJw+kf147x586yxitKVWF/FXRuFOOJLNQZqrCIR5K9//euWxe0qXy1qdPoxEv+7InqFuxZSUPNHpSmxvqrbFf6q+RgJkVV5tbaVIFytOTXHXZORKF3FrvpMxagMQNTzVIyRqDoS9U5k7dq1VoxKOKzSoj5T463WkmuG4s49tUcpI5QoRvVM11BEvTdTBPgqdjWuSmSt3kmqfffee69Vb8q4KtT7UPWPa0YRvUvVeKl3kmqP6rNnP/vZVpvVuN51110yRmU8cP311zelnXTSSda7QhkPqP5Zvny5jEe1++Uvf7k1L1TZFStWNKUdd9xxVv8oY4Wae+65pyntZS972XY/y9frJTJImQjf6AAAAAAAQHFw0AEAAAAAgOLgoAMAAAAAAMXBQQcAAAAAAIpjl7EUFfUOQi3IrgXPtRnBeIG9Em/m3tKtyiuBYbvNCCKRuCtkV/EoMwL3FuFomqi+cG9aV21xzR9Un0VtUSJYJZZVQl0lTlRxq/ZFY6hid80IVBtVPaot27s9eHvtUQJlNV6qv5V4W93wvnDhQhmPEoRec801VjyqLSqfMkxwb7uPxtC9IV6NoWtGoPaoCDWfVXnXwEGVVW2Objt3DSBUParPdt9996a0oaEh63lPZ2jizgEnn1rDrsFNzaJFi6z2qHa/9KUvtQTGz3rWs5rSfvKTn2QZaaSI9du5tqJ61PxR+5TaP9y4I1Ohnp4eq7yqx+1v18AhMh1Qfa7mqXpmzlgrc4Pofaj2D4WK57777mvZDOnP//zPZT3qnbRkyZKmtKuvvtoy0njrW9/alPbwww9bZSNuuOEGawzVe1ztr3/4wx+sMYzm2cknn2z148R1WO95999/f2MObO+zDd/oAAAAAABAcXDQAQAAAACA4uCgAwAAAAAAxcFBBwAAAAAAisNTh+2g1GKk8SJMJch0xbK55V1BrxI2qudF4n+Vrupx2+IKmaN8buyu54WqRwkEU8TbKt3ts2iutDouUexRXidGty2qH6L2qfbkzCk3nmieqbzuuLppuWvGHUMlUFdC3clYm+78cfvHXddR37j1uH3rzqlor3Db6OZz563aE1Lmmcqr5llO+1LG0H335c4fF9Xnas3l1JNiCuIajUSGNq3OPSXod+tIMVhyY0zpR/ed75oFue97d72llFfmAa6ZlnpeZI6i+uwZIi1nXrgmThGu2cfEsXY/m9XwjQ4AAAAAABQHBx0AAAAAACgODjoAAAAAAFAcHHQAAAAAAKA4dhlzFWI7EP39/VVvb291/vnnb3P7rxJzuTfdRqIqt7wrJFMCLyWqioRWSjSmxGnqJuC6z9ybpCcSTRMVj2tQoARnrrBN9WN0k7i6pVfdGq5uflc3QavnuSYTUbpbfnBw0BoDNW8XLlxoCw5V+saNG605Pn/+/Ka09evXW7csd3V1yXjWrl3blHb99de3LDpV/aNidJ8XzVO1NnOE0WruRTeOu0JUtVeofKpu1RfqRvYoRrVmVV5XbK1utndvc0+JXdWtYuzp6bHqSHkNqz1AtVHF+PjjjzelLV261LpxftmyZTIe1ZfqvRKtbQe1x6m06Ib4nPmsxl+tGTWXc42PVBvVPqPacu+997ZsHBHNKZVX9U+O4U6UT/WFmqdqfSkOP/xwqw61p9x6663ymccff3xT2k033dSU9qd/+qfW+H/9619vSjvxxBOb0u6++24Zj/o8dfbZZ1vzVK3Xq6++uintmGOOaUq7//77m9IOPPBAGeMNN9zQlPaGN7xhu3tKvQYvuOCCxhyYO3du9XTwjQ4AAAAAABQHBx0AAAAAACgODjoAAAAAAFAcHHQAAAAAAKA4tEK0QzjssMO2EUy5hgCRMDbHjECJE5XA1BUIRyJG9wZtJaxXQk2VL+XGWSXecwWGrrGCe2tvZKyghJoDAwNWX6QIXl1RpYpdzRUlBlXiSzUf1bydM2eOFUs0B5QZgUIJsFXZJUuW2H2rxksZFLg3jquxqU1OWr1dPpp/7lir/lZllTA2xSgk50Z31Reu2UK0FtRe7O4Lap4tWrTIijt3j1N9pt4BKp+aJ0pAreZ3tC8ogwLVP0o4/MADD1hrU+VLeSe5Ji7ubfCqrKojilHtm2o+qrmi5rhKi9agO3/cuesa+7j7UYp5gHqmqlulpaDiVOtdmcqoNXPfffdZ7x/VD/vvv7+MURkPqLgffvhhqx5lPPCTn/ykKe25z32ujEe1+wGxjtX8UetD9a163sqVK635Ha2bFStWVNtDfV6L4BsdAAAAAAAoDg46AAAAAABQHBx0AAAAAACgODjoAAAAAABAcXS0GcHq1au3EY+5ZgRKZBWJm1wzAlW3EpdF4m83nyuMVYJXdXusijvlVmPXKMC9UVkJFpWgTgkyVVsigaFrRuDeQp2CK7ZWbRwaGmpZDKzEgJFYVtWtjBBcIwwlYlR1dHd3y3hU+VWrVrV8Y72aZ8owwRUdp4j63RvQc3GF/pFI1BkvV3QeGcCodejucWpcVT3u2orKqzQ1x1WaMgRQ/aPKRiJxZUihYlRmBqoetX+otaDMTKK61T6l+sJ9V7gmPsrUIZpTKq+7NlU/qnGJ5plqo9r7XJG4mlN33323VW8Uo+ofVV7lc/dcRfRZQ30OWLNmjdWParzU5yHVt2pcI6OQAw44oClt+fLlTWmHHHKI1T+/+tWvLOOBO+64w/7sc/jhh1tz3P2co9a16kdlcBL15YIFC7bbP5H5lIJvdAAAAAAAoDg46AAAAAAAQHFw0AEAAAAAgOLgoAMAAAAAAMXBQQcAAAAAAIqjo13XaheG8a4kyg1JuahELiPK9cIt79atnGLU81LcWlQ9qi0qLXKQch2AXBcXVT7HmUX1Y1TWdc3JqVu1JRpDNV5uP6oYVTxqXN35HdWtXE5U3G7fqnzKWSeKM3LnaTWfqsNNS8FdcypuNZdT9gqFO3fV86J9wUWVd+txndjcfojKK9y15O7XKf2o5o/rVOe6rkUueQo1V1R51znNfZ7KFzmqunW7Tn7uGOSinum6Kaq9NGUtuGPjOslG+5SL6/Cq8qlxdduniN4Bamyid5oTj+tCq9zVIifaZ2b0ozvW7vqP8ubOlaa62/o0AAAAAACAHQAOOgAAAAAAUBwcdAAAAAAAoDiSDzo33HBDdcopp1RLly5t/B7dFVdcEeZ9xzve0chz4YUXNt1yfvrppzdupp03b1519tlnV4ODg621AAAAAAAAINeMYGhoqDriiCOqs846qzr11FPDfJdffnn1i1/8onEgmkh9yHnssceqa665piG2OvPMM6tzzjmnuvTSS5NiefOb39w4LD2d8MoV9EZiayU6U+VHR0dbFvmmCPxU3aqNqi96enqsuBWRiFGJP13jAdUWJfJUdag+U22O2t3f328JdV3hpyt2jNJV/6p8arxccwzVD5HoT7VH/TBC1aOEkSru+occE9ljjz1kPKr8smXL2ioIr38A47RPzZOoHtfUQY21K1qPzA1ckbmKW6W5+6OqNxKJ9/X1We1x18fChQvlO8upI2U/dA0l1FwZHh5uSps5c6a9ny1atMiKR9Xzspe9rCntnnvuaUo74IADmtLq93W730muuYbb3xs2bKhyUOOl5visWbOy3uNdXV1WPGq9qjQ11ocffnjW2lRjqITw7nvKNbiIxPuqvHqPu+N65513Wm1Wa7P+zKr4wQ9+0JT28pe/vCntxz/+sdWP9ZcAE3nggQessY7W1//9v//XemerOXrMMcdYbVHv5htvvFHGWJ8HJvLNb35zu/2TYqyRfNA5+eSTG3+ejkceeaR697vfXV199dXVq1/96qZN9aqrrqpuueWWrZ120UUXVa961auqz33uc/JgBAAAAAAAMK0anfqU9da3vrX6wAc+UB166KFN/758+fLGT3LHnwxPPPHExmnt5ptvls+sf5JYn9zH/wEAAAAAAJiyg85nPvOZxleM73nPe+S/r1q1qumr9zr/ggULGv+muOCCC6re3t6tf9TXYgAAAAAAAJNy0Lntttuqf/iHf2j8fl07L/w5//zzG7/LveXPypUr2/ZsAAAAAAAoj2SNztPxs5/9rFq9enW1zz77bCPk+6u/+quG89pDDz1ULVmypJFnotCwFgLX/6aoxWBKEFZ/EzReoKbEakpIGIni3BvPlXgvR0CbImJ0zQxUG924FZHwS9WTY0bg1uHeIhyVd0XZqs9c8W3UPvfWeVdM7v5QwTV1SLkhXJVXYlK1tlQ8kTBWja07f9z+cW+HTtk/3LWdchO9U0eU7u6RObfdu2WfbrxbNXpw13qEa67iouJ2Y4z6xhWEK/MINZ/V81LiUXnVe0XV4xq7uKjPCTU5P3hV8UT1uO9xd967Y+OuhZS1qch5H0Z94caTs7bd94/73ovqVSYVqt3uu8Ydr+hdqOqZLYwHlFGI6h/1PHc/igw4VHvU+pr4TPfzeqOOqo3U2pxabzOek046qZG+xaXiuOOOqzZu3Nj49ufoo49upF133XWNhXHssce2MxwAAAAAANhJST7o1Baz999//9a/P/jgg9Xtt9/e0NjU3+RMtPesT4X1NzXPec5zGn8/+OCDq1e+8pXV29/+9uriiy9u/KT23HPPrU477TQc1wAAAAAAYHo0Orfeemv1vOc9r/Gn5rzzzmv8/4997GP2My655JLqoIMOqk444YSGrfRLXvKS6qtf/WpqKAAAAAAAAO35Rqe+/Cjld2hrXc5E6m9/Ui8HBQAAAAAAmBaNzlRTi6rGC6vcG5UjIZkSdLlmBjkCc9dgIIrRFeoqMZgr0owOt+02I3BFrCl9ptrtzgtXlKvmSYpA0J0rrgBfta+7uzvLjEDFqNqtxI6qLSqeSLCo6lbCTxWPKqv6x31eNAauONIdV7ctkVGIGtucetyyqt5IfK1uLHfXl6pHzT23fSnrS5ljuMYDKm4191L2Mzce1T8qTYmBVYxRG9W4uvNR7T1u+yJcIbzC3StS6lXlVbvVWnCNdFzzB5Uv14xAtSXHNCdKV/PUNYBxjQNU/6g1k9K/6t3nCvjdfoji6TKfqe6rVH2m6k6ZUyqvqmfivE8xI2j7PToAAAAAAADTDQcdAAAAAAAoDg46AAAAAABQHBx0AAAAAACgOHYZy7mGeJqoRVK9vb3VZZddto2wanR0NMuMQAkeVZoSXw0PDzelqa6dDDMCJcpSt2L39PQ0pak+S7lF2r31N0fc7N4irdocCQeV0E6NtarbjSfC7R81T/v6+qz5qNoyb968prRo+asYVd2q/Jw5c5rSNmzY0JS2ePFiS6RZMzAw0JR2zTXXWCJo14ygvsjYyafSoj5X/egaHKi2KKJ41DPVnFLrxt031Y3aqt5IlK32H3e8FPWdbc7enIJqz9DQUMu3qqt8Snyr1lu0RlT/qHm25T678Tz88MNNaXvssUdT2n333WeLiVXsriGAmvdqD1fjEu3Nroha9ZkaL7Vm1LyN4lF1q3a761D1rdpzXaF+hLunuOtDEQnrVT31vY6tGmGoextVPrWv77fffjLGRx55pClt9erVVt3uvF2/fn3losZ2r732svKpui+//PKmtFe84hVNaXfddVdT2iGHHCJjVPvz3nvvvd35U49LHU+918ydO7d6OvhGBwAAAAAAioODDgAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAUBxald8hHHnkkdsIn5UwNuVmcyViU+VdUa4SJ7piwOk0I1CiwegWaiW2dMurfnTFl6ofItGxarcyI1B9lnMTdCTydM0IVD4Vo6pbzQklYo7WgiqvhJ8qnxIOq7iVgHDRokUyHlVeiW3duafiXrdunTUflTg1qketY7Xm3DnhtiV6pjt3VZoSGLtC5uimbNcAwjUzUYYbal+IzA1ccwSV5orW1btC9U/UZ8pwQbVHjddRRx1l7QsHHHCAtWdGc3z33Xe3+sI1rlBrTvV3ZODhmoq4a1ONjeqHXKMQNTbqnaT6R+2lKsbInEmh2u2OV/SuceqIyivTC5VPjetvfvMbq6yKp/7sqXj88ceb0o477rimtJtuusnqs7e+9a1NaQ888ID1GSfixz/+sdVGZQqhjAfU8w477LCmtN/+9rcynje/+c1Naf/6r/+63bUUfSZV8I0OAAAAAAAUBwcdAAAAAAAoDg46AAAAAABQHBx0AAAAAACgODrajKC+0Xm8CMs1I4jEd+7NxEoM6JoRuOLdSLjnipaV+E7dWK/yKaJbjV0hoyqv2qgEea7wM2pLV1eXJaxV46/G2jVgiAwlVLrbP0pg7PZjb29vVoyqz1zTA2VkoMTJkZhYlf/d737XspBd9Y8rjI/MCCJTAKe8a8zhCuOjvULVo+JxTQ9c0XG0TwwMDLQsHFf1KBF8yi3tqh53r3HFsWqOqz1KzccodteM4MEHH7Ruc1d1PPbYYzIetT9HxgWtzkfX7CV6vyphtUpTqHmv3vdqTkTCetdIQfWPils9Twnj1fOitemuY/U+VAYg7vqI+kylR2vEWR9qrqi2qHF56KGH7PfUXXfdZY2hqvv+++9vSlu5cqVVNhqvZcuWtWy4odqijAfuvPPOprSjjz5axrhixYqmtP3333+786ce0/oM4MA3OgAAAAAAUBwcdAAAAAAAoDg46AAAAAAAQHFw0AEAAAAAgOLoaDOCPffccxuBvWtGEAkWlegs58Z6t6wSu0YxKoGgaqOKx72xXhEJCZUIzr013G2LEtSp/lHjH90arMSArrBatTllnrmGEqrdqi3ujdxK8ByZEbg30at2q75VwkZ1i70Sk9csWLCgKW2fffZpWfCq5uPatWutORHddu4K5t3b11VbXKF+NLbu7eSqrBLaqnxqTkRiWfVMVV71hXqmmlNKlB/NE9dkQM0flaaep/Zc1ZZIlL1w4ULr3aXWzL777msJulW+6GZzhVrH0f7cTsOMyJBGlVdGGGoMVT1qj1NmPykmPtEacdacat8BBxxgPS96T6WsYyeeaD67JhGqL5csWdKygYyaz2qs586d25S21157yRiXL19uifB//etfVw4HHnigNcdVP0Rje+ONN1qfDRSHHHKI1Y+qzbfddpt85ktf+tKmtMsvv3y7895919fwjQ4AAAAAABQHBx0AAAAAACgODjoAAAAAAFAcHHQAAAAAAKA4OOgAAAAAAEBx7DIW2YLswPT391e9vb3VJz7xiWrWrFlP60ahHDgi5xDX0Ui5ggwPDzelqa5VbivKRSVyw1IuGsodRbmMjO+rp3PrUTFGqHhUmuqLnHwK1eZovOo51GpfKOczhRqXlHaruNesWWM5pqi66zXjzjPV7g0bNlhtUS41q1atynJNU85Q11xzje265PSPu44iVN2qf9U6VG5oqqzbvmgMXUci1RdqXFU8Kf2oXNKUO5NaH65bpcoXOTupdNcFTKWptanGX9WhHOki9zK1bpQL2Lp166y+Vev12c9+toxH9bn7/lFxu86b7tqK3vkqzZ1TyjnPdV2M2q3ePyrNnberV6+26o1cGxUpeVstG+0Val4odz+1J6l39sEHH2zNCRXPLbfcImM86KCDLFey448/3lqHysVN9WPKe/zkk0+28ql9+Morr2xKe8lLXtKUtmLFiqa0/fbbT8Z44YUXNqV99rOf3W7/1OP88Y9/vOrr65PvpvHwjQ4AAAAAABQHBx0AAAAAACgODjoAAAAAAFAcHHQAAAAAAKA4OtqMYO3atduIkFyRZiTcUsI/Vxip6nYFtCotEjEqYaRqoxLkKWGsK26OROJKvKfyuiYDqqzqC1VWjUEkyq0FbI7oUNWt0lTckYmCGm/VP6oeJYJVKMGiGv9oLaj2DA0NWetDzQkVjzJHWLx4sR2PMiNw555Kq/cTJ+5IIOzOATVPXZORXDFxitGIM/4K1beRAczAwIC1Dt31sWDBAivuqM9ccwUXNdYqTfVPNM8WLlxo9Zlq40tf+tKmtDvuuMMSaqv1FqHao8bBffdF7x+njmj+uOZDavyVUFulRcyePbtlIw3XpGTvvfdueR2l7O0KNR/dspGhhEK1W80V9d68++67rTXX3d3dlHb66afLeL7//e83pR1xxBFNaddee621N7/lLW+xhP5q34vmyne/+13LzEKNw6GHHtqUdttttzWl7b///k1p9957r4zxXe96V1PaBz/4waa0iYYD9Vyu3x+YEQAAAAAAwE4JBx0AAAAAACgODjoAAAAAAFAcHHQAAAAAAKA4Wlem7gDUArPxIjMlOJsMMwIlWHTrdgWHkZDdFWoqkZ4qm2tG4AqmXTMCVwCp+iwyI1Dl1Xip8Xdv5Hbbl4IaLxWjK7RNiUeNoepfNV5umhIOR/NRtVEJXnPMCNz1H93c7RppqPJqTqm63bGOcA1SFG7cimjuqWe6t8G7t8u7t9in5nXaqJ7n1hHtuaqNrmmGW9YV5Ue476mUd59DVFbF7u7jCnefifpM9a9rfOP2maojxXtKxe5+fpkqjyt3bbrrS+VTe1T0DlCfF3L2cdd8KIpH8QwxhipNtcWNO+Vzt3qmMheoTchahW90AAAAAACgODjoAAAAAABAcXDQAQAAAACA4uhIjc6W3+mbeNmce3lUrkbH1brkXBg6GRodN58i+n1x9/c4czQ6rk4m0uiovIODgzudRse9dC/KOzw8bI2XitH9nfaU38NV8eRodNzLIlMuDHUvfZ0qjY6rVVC4cStS9CauRsftW1eXEuV1tSlqvbsXear+ifrMfabKp+a4arPKlzLP1LxQ5d3542o+ohhztITuZ4gUXZOrn3E/Q7jjr54XzTN3L3X3LpeU96a7V6i+cMda5Ys+N7laOXcfdterq+VJaaOrT3W1TtE8cz87Rzh5dxmbKtVYG/nDH/5QLVu2bLrDAAAAAACAaWDlypXV3nvvXd5Bpz4ZPvroo9WcOXMa3+rUh566scqpAaaH+ifzjMuOCWOz48LY7JgwLjsujM2OC2OzY9JfwLjUR5f68//SpUu3+y1gR/7qWt2oLSe4LV/31YPVqQNWMozLjgtjs+PC2OyYMC47LozNjgtjs2Myt8PHpbe318qHGQEAAAAAABQHBx0AAAAAACiOjj/ozJw5s/r4xz/e+C/sODAuOy6MzY4LY7NjwrjsuDA2Oy6MzY7JzJ1sXDrSjAAAAAAAAKDob3QAAAAAAAAmwkEHAAAAAACKg4MOAAAAAAAUBwcdAAAAAAAoDg46AAAAAABQHB190Pnyl79c7bffftWsWbOqY489tvrlL3853SHtdFxwwQXV85///GrOnDnVokWLqte97nXVihUrtskzOjpavetd76oWLlxY9fT0VK9//eurxx9/fNpi3hn59Kc/Xe2yyy7V+973vq1pjMv08cgjj1RvectbGn0/e/bs6vDDD69uvfXWrf9em2F+7GMfq/bcc8/Gv5944onVfffdN60x7wz88Y9/rD760Y9W+++/f6Pfn/WsZ1V/+7d/2xiPLTA2k88NN9xQnXLKKdXSpUsb+9YVV1yxzb87Y7B+/frq9NNPb9z8Pm/evOrss8+uBgcHp7glO9fYPPHEE9WHPvShxn7W3d3dyPO2t72tevTRR7d5BmMzPetmPO94xzsaeS688MLix6ZjDzrf/e53q/POO6/hBf6rX/2qOuKII6qTTjqpWr169XSHtlPx05/+tPFh+Re/+EV1zTXXNDa6V7ziFdXQ0NDWPO9///urf/u3f6suu+yyRv560zv11FOnNe6diVtuuaX6p3/6p+q5z33uNumMy/SwYcOG6sUvfnG12267VT/60Y+qu+++u/o//+f/VPPnz9+a57Of/Wz1xS9+sbr44ourm2++ufGhod7f6sMpTB6f+cxnqq985SvVl770peqee+5p/L0ei4suumhrHsZm8qnfH/U7vf5hpsIZg/rD2l133dV4L1155ZWND4HnnHPOFLZi5xub4eHhxuex+ocF9X+///3vN37w+ZrXvGabfIzN9KybLVx++eWNz2z1gWgiRY7NWIfyghe8YOxd73rX1r//8Y9/HFu6dOnYBRdcMK1x7eysXr26/tHn2E9/+tPG3zdu3Di22267jV122WVb89xzzz2NPMuXL5/GSHcOBgYGxg488MCxa665ZuxlL3vZ2Hvf+95GOuMyfXzoQx8ae8lLXhL++1NPPTW2ZMmSsb//+7/fmlaP18yZM8f+5V/+ZYqi3Dl59atfPXbWWWdtk3bqqaeOnX766Y3/z9hMPfWedPnll2/9uzMGd999d6PcLbfcsjXPj370o7Fddtll7JFHHpniFuw8Y6P45S9/2cj3+9//vvF3xmZ6x+YPf/jD2F577TV25513ju27775jX/jCF7b+W6lj05Hf6GzevLm67bbbGl9Xb+EZz3hG4+/Lly+f1th2dvr6+hr/XbBgQeO/9TjV3/KMH6uDDjqo2meffRirKaD+tu3Vr371Nv1fw7hMHz/84Q+rY445pnrDG97Q+HXP5z3vedXXvva1rf/+4IMPVqtWrdpmbHp7exu/nsvYTC4vetGLqmuvvba69957G3//r//6r+rGG2+sTj755MbfGZvpxxmD+r/1r93U62wLdf76c0L9DRBM7WeC+lek6vGoYWymj6eeeqp661vfWn3gAx+oDj300KZ/L3Vsdq06kLVr1zZ+l3rx4sXbpNd//+1vfzttce3s1Iuo1oDUv5Zz2GGHNdLqF9KMGTO2bnLjx6r+N5g8vvOd7zR+faD+1bWJMC7Tx+9+97vGr0fVv3r713/9143xec973tMYjzPOOGNr/6v9jbGZXD784Q9X/f39jUP/M5/5zMZ75lOf+lTj1zlqGJvpxxmD+r/1DxHGs+uuuzZ+AMc4TR31rxLWmp03velNDc1HDWMzfXzmM59p9HX9vlGUOjYdedCBHffbgzvvvLPxE1CYXlauXFm9973vbfyebW3WATvWDwTqn5j93d/9XePv9Tc69bqp9Qb1QQemj+9973vVJZdcUl166aWNn3jefvvtjR/e1L/LztgA+NS/MfDGN76xYRxR/2AHppfbbrut+od/+IfGDz/rb9h2JjryV9d23333xk/bJjpE1X9fsmTJtMW1M3Puuec2hGvXX399tffee29Nr8ej/lXDjRs3bpOfsZr8Ta025jjqqKMaP5Gp/9SGA7WAt/7/9U8/GZfpoXaKOuSQQ7ZJO/jgg6uHH3648f+39D/729RT/0pH/a3Oaaed1nCOqn/NozbtqN0laxib6ccZg/q/E42JnnzyyYajFOM0dYec3//+940ftm35NqeGsZkefvaznzX6vf719C2fCerx+au/+quGe3HJY9ORB536VzyOPvroxu9Sj/8paf334447blpj29mof1pTH3JqF4/rrruuYcs6nnqcanep8WNVu7DUH+oYq8njhBNOqH7zm980fiK95U/9LUL9Kzhb/j/jMj3Uv9o50YK91oTsu+++jf9fr6H6pTJ+bOpfp6p/R5qxmVxq16j699HHU/9QrX6/1DA2048zBvV/6x/i1D/w2UL9fqrHsdbywOQfcmq775/85CcNC/3xMDbTw1vf+tbqjjvu2OYzQf1Ndf3DnauvvrrssRnrUL7zne80XFa++c1vNpwizjnnnLF58+aNrVq1arpD26n4y7/8y7He3t6x//zP/xx77LHHtv4ZHh7emucd73jH2D777DN23XXXjd16661jxx13XOMPTC3jXddqGJfpoXYh2nXXXcc+9alPjd13331jl1xyyVhXV9fYP//zP2/N8+lPf7qxn/3gBz8Yu+OOO8Ze+9rXju2///5jIyMj0xp76ZxxxhkNR6Irr7xy7MEHHxz7/ve/P7b77ruPffCDH9yah7GZGrfIX//6140/9ceUz3/+843/v8W5yxmDV77ylWPPe97zxm6++eaxG2+8seE++aY3vWkaW1X+2GzevHnsNa95zdjee+89dvvtt2/zmWDTpk1bn8HYTM+6mchE17VSx6ZjDzo1F110UeOD2owZMxp207/4xS+mO6SdjnoxqT/f+MY3tuapXz7vfOc7x+bPn9/4QPff//t/b2x8ML0HHcZl+vi3f/u3scMOO6zxw5qDDjpo7Ktf/eo2/15b6H70ox8dW7x4cSPPCSecMLZixYppi3dnob+/v7FG6vfKrFmzxv7kT/5k7H/9r/+1zYc0xmbyuf766+V7pT6IumOwbt26xge0np6esblz546deeaZjQ+CMHljU/9wIPpMUJfbAmMzPevGOeiUODa71P8z3d8qAQAAAAAAVDu7RgcAAAAAAODp4KADAAAAAADFwUEHAAAAAACKg4MOAAAAAAAUBwcdAAAAAAAoDg46AAAAAABQHBx0AAAAAACgODjoAAAAAABAcXDQAQAAAACA4uCgAwAAAAAAxcFBBwAAAAAAqtL4/3OTrJjc0kLfAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vat(iris.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb2cc242",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}