assignment_exs.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Usage examples for `assignment` module\n",
    "\n",
    "This module provides a lightweight implementation of the Gale-Shapley stable assignment (proposal) algorithm and a few tools for exploring the stable assignment polytope, including a modified implementation of the optimal stable marriage algorithm described in the following reference:\n",
    "\n",
    "- Irving, Robert W., Paul Leather, and Dan Gusfield. 1987. &ldquo;An Efficient Algorithm for the &lsquo;Optimal&rsquo; Stable Marriage.&rdquo; *Journal of the Association for Computing Machinery* 34, no. 3 (July): 532&ndash;43."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "from assignment import *\n",
    "from matplotlib.lines import Line2D\n",
    "from matplotlib import rc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## One-to-one assignment examples\n",
    "\n",
    "### Small example\n",
    "\n",
    "This is the example used in the discussion notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Rotation flow graph')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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3fH9yP2G9x+Ds6ISzo5NVCxegimslFj4WTAUnZ55f9QZXE+KsenwhCkJKVxhu11+HeP/HVbzX72WquFYq0XO5ODnzVsBIOjRoxbDlU/nr6oUSPZ8Q2UnpCkOdvnqeVza+y6xeo2joVccm51RKMerBQTzl04unV4Ry8Nxxm5xXCJDSFQaKS7rB6IgwXnygP/feZvs3pnm8TTdCewxndEQYW4/vsvn5RfkkpSsMkZqexqQN8+nYyJv+bboZluPBO9qx8PFgZm0N5/O9XxmWQ5QfUrrCEGHbl+KgHJjg96TRUWhZ63bCB4eyav83zNn+qUwpEyVKSlfY3Bf7vmbX6d+Y3XsMTtk+7dco9Txq8smQaRy5eJJJ6+eTlJJsdCRRRknpCpvaeTqaxT+v5t1+k6hcoXgfPGltVVwrsfDxyTg7OjF81ZsypUyUCCldYTOnrpwjeNMCwnqPpYFnbaPjWOTi5MxbPUdyd/2WDFs+lTOxMqVMWJeUrrCJa4nXGRUxm1EPDqR9g5ZGx8mTg3JgzEODGebTi6DloRw8L1PKhPVI6YoSl5KWysQNb+PXuD39WncxOk6B9W/TjZDuzzN6TRjbT8ivwwvrkNIVJUprzaxt4VRwcmHsQ0ONjlNoDzW+m/cfe4UZ3y6RKWXCKqR0RYlavm8L+8/+zqyeo3B0KJ3/3FrVbswng6excv/XzN0hU8pE8ZTOR4EoFX78cz9LflnLu4GTqGRnMxUKq55HTZYOmc6hCyd5ZcO7GW+0LkRhSemKEnHy8lle2/wBYb3HUs+jptFxrKKKayUWPT4ZBwcHnl81g9jEeKMjiVJISldYXWxiPKMjZjPedyh3129hdByrcnFyZmbPkbSr15xhn0/l79iLRkcSpYyUrrCqlLRUJqybR7dm9/LoXb5GxykRDsqBsQ8N4Yn2/gQtDyX6/AmjI4lSREpXWI3WmhnfLqGya0VGPzjI6DglbkDb7kzp/h9GrZnNDplSJgpISldYzWd7NnP4wkneChiJgyof/7R8G7fn/cde4c1vl7Bi3xaj44hSoHw8MkSJ++6PvXzy60beCZyEu4ur0XFsqlXtxoQPmsbyfVuYt+MzmVIm8iSlK4rteMwZpn61iLl9xlnl03tLo/qeNVk6eDoHzx/nlY0ypUzkTkpXFMuVhDjGrA1jUudhtKnbzOg4hvJwq8Ti/q+hUAxfNYNrideNjiTskJSuKLLk1BTGr5tLQMsH6HlnJ6Pj2IUKTi7M6jWKNnWbMWy5TCkTOUnpiiLRWvPGNx9R1d2DFx/ob3Qcu+KgHBjnO5TB7XoQtDyU387/YXQkYUekdEWRfPLrRo7FnOZN/xfLzUyFwhrUrgevP/wsI9f8V6aUiQxORgcQpc+OE7tZtjeSz4a+Ue5mKhSWXxMfFlT0YuzaOVyMv8LAdt2NjiQMJpcoolCOxZwmdMv/mNdnPLUqVzM6TqlwV53GhA8OZdneSN6OWiZTyso5KV1RYJdvxDImIoxXuwbRuk4To+OUKvU9a7F0yHQOnDvGqxvfkyll5ZiUriiQm6nJjFs3l0db+fJIi45GxymVPN0qs7j/a2g0L3z5lkwpK6ekdEW+tNZM+/p/1KpcjeEdHzM6TqlWwcmF//YaTevaTcxTyv4xOpKwMSldka+Pd63j1OVzTH9khMxUsAIH5cB4vycY1LY7QctDOHRBppSVJ/IIEnn69tguvtj/NfMDJ+LmXMHoOGXK4Lsf4bWHn+Wl1bOI+mOP0XGEjciUMZGrIxf/5M1vPuSDx4KpWamq0XHKpM5NfKhW0YNxa+cy/P4rDGj7sNGRRAmTK11hUcz1q4xdO4fXuj3LnbXvMDpOmeZdpynhg0P5bM9m5n/3uUwpK+OkdEUOSSnJjF07h8e8u/Jw8/uMjlMuNPCszdIh09n391GCNy0gOTXF6EiihEjpiiy01oRsWUQDz1o8d1+g0XHKFdOUstdJS0/jhS/fIi5JppSVRVK6Iov/7VzD2Wv/ENrjBZRSRscpd1ydXZjdewytat/BU5+HcPaaTCkra6R0RYavf99JxMHtzO87EVdnF6PjlFsOyoEJfk/Sv+3DPLU8hMMXThodSViRlK4A4NCFP3jr2yXMD5xI9YqeRscRwJC7H2Fy12d4cfVMvvtjr9FxhJXIlDHBxfgrjFs3l6ndn6dFzUZGxxGZdGnageoVPRm3bi4vdHyc/m26GR1JFJNc6ZZziSk3Gbt2DgPb9qBL0w5GxxEWeNc1TSlbunsj73y3XKaUlXJSuuVYuk5nSuQH3FGtHs/c86jRcUQeGnjWZung6ez5+zCTZUpZqSalW44t+mk1MdevEtL9eZmpUAp4uVfhf/2nkJKWygiZUlZqSemWU5FHfmTDoSjm9ZmAi5Oz0XFEAbk6uxD26Fha1Lqdpz4P4dy1GKMjiUKS0i2HDp4/zn+3fcI7gZOoVtHD6DiikByUA5M6D+PxNl0ZtnyqTCkrZaR0y5kLcZcYv24eoY8Mp1mNhkbHEcUwtH0AwV2f5sXVM/n+5D6j44gCkilj5UhCchKjI8J4sn0Afo3bGx1HWEHXpvdQo6IX49bNZUTHx3lcppTZPbnSLSfSdTqTN79Pi1q3M8ynl9FxhBV5123K/w0K5ZNfN/Le9yvQWhsdSeRBSrecWPDDF1xLiuf1bs/KTIUy6Dav2nwyZDq7/jrE5M0ypcyeSemWAxsOfcdXR39m7qPjZaZCGVbVvQofDphCUmoyI1bPJC7phtGRhAVSumXc/rO/M3fHZ7wbOImq7lWMjiNKmKuzC3N6j6N5jYY8tVymlNkjKd0y7Ny1GCaun8+b/iNoUr2B0XGEjTg6OPByl6d4zLsLTy0P4cjFP42OJDKR0i2jbiQnMjoijKB7etPpjnZGxxEGeKJ9AK90eYoRX87kB5lSZjdkylgZlJaezqsb38O7bhOG3u1vdBxhoG7N7qV6RU/Gr5vHS50G8Jh3V6MjlXtypVsGvfv9chJSkgju+ozMVBC0rdec/xscyv/tWs+CH76QKWUGk9ItY9ZG72Dr8V3MfXQczo7yREaYNPSqw9Ihb7DzdDSvRb5PSlqq0ZHKLSndMmTv30eY/93nvBf4Mp5ulY2OI+zMrSlliSk3GfGlTCkzipRuGfF37EUmrp/PWz1f4vZq9YyOI+yUm3MF5vQeR9MaDQhaHsL5uEtGRyp3pHTLgOs3ExgVEcZz9wXSsVEbo+MIO+fo4MArXYIIbN2ZYZ9P5eg/p4yOVK5I6ZZyaenpvLLxXXzqt2RQux5GxxGlyJM+PXm58zBeWPUWP/653+g45YaUbik3L+ozUtJSebnLUzJTQRTaw83vY37fCUyJXMia6G1GxykXpHRLsdUHt/L9yX3MeXSszFQQRda2XnM+HhTCx7+skyllNiClW0r9+tchFvywkncDJ1HFtZLRcUQp16hqXT4ZPJ2dp6N5PfIDmVJWgqR0S6G/rl7g5Y3vMqvnSBpVrWt0HFFGVKvowYcDpnAjOZEXV88k/maC0ZHKJCndUiYu6QajI2YzouPj3NuwtdFxRBnj5lyBuY+O545q9QlaHsIFmVJmdVK6pUhqehovb3yH+xp6M6Dtw0bHEWWUo4MDr3YJos9dfgxbLlPKrE1KtxSZs/1TACZ2ftLgJKKsU0oxzKcnE/1uTSk7YHSkMkNKt5RYuf9rdp4+yOxeY3BycDQ6jignuje/j3l9xjMl8gMiorcbHadMkNItBXaejmbRT6t5N/BlqrhWNDqOKGfurt+CjweF8NHOCN7/YaVMKSsmKV07d+rKOYI3LWB27zHc5lXb6DiinGpUtS5Lh7zBj6cOMCVyoUwpKwYpXTsWl3SdURGzGdVpID4N7jQ6jijnqlX04KMBU4i/eYOXVs+SKWVFJKVrp1LSUpm4fj6+d7Snn3cXo+MIAYC7iyvz+kygUdW6MqWsiKR07ZDWmv9uC8fF0ZlxvkONjiNEFo4ODgR3fZpHW/kybPlUfv/ntNGRShUpXTu0Yt8W9v59lFm9RuHoID8iYX+UUjzVoRcTfJ9k+KoZ/HRKppQVlDyi7cxPpw7w0S9reTfwZSpVcDc6jhB56tHifub1Gcfrmz9gbfQOo+OUClK6duTk5bNM3vQ+Yb3HUt+zptFxhCiQu+u35ONBIfxv5xoW/rhKppTlQ0rXTsQmxjM6YjbjfIdwd/0WRscRolAaVa3Lp0Om8/3JfUz9apFMKcuDlK4dSElLZcK6eXRteg997vIzOo4QRVKtoicfDZzKtaTrjFzzX67LlDKLpHQNprVm5taPqVTBndEPDjY6jhDF4u7iytt9JtDQqw5PrwjlYvxloyPZHSldgy3bG0n0+RO81XOkzFQQZcKtKWU9Wz7IsM+ncixGppRlJo9yA31/ch/huzbwTt9JVHRxMzqOEFajlCLont6M8x3K8ytn8POpg0ZHshtSugY5cekMUyIXMrfPOOp61DA6jhAl4pEWHZnXZxyTN7/Put92GB3HLkjpGuBKQhyjI8KY2PlJ2tRtZnQcIUrU3fVbsmTgVBb9tJpFP60u91PKpHRtLDk1hfHr5uLfoiO97nzQ6DhC2MQd1erx6dA3iPpjDyFbFpfrKWVSujaktebNb5fg5V6FlzoNMDqOEDZVvaInSwZO5WpCXLmeUiala0NLd2/k6D+nmOH/Eg5K7npR/ri7uPJ23wk08KxlnlJ2pVjHCw4OZv78+UXa9+DBg3Ts2LFY5y8KeeTbyI4/9vDpns2823ci7i6uRscRwjBODo681u1ZAlp2YtjnUzge81eRjhMTE8PSpUsZPnx4rtssWLAAHx8fKlSoQFBQUJZ13t7eeHp6smHDhiKdv6ikdG3gWMxpQr9azNt9JlC7SnWj4whhOKUUT9/zKGMfGsJzK9/kl9PRhT5GeHg4AQEBuLnlPt2ybt26vP766zzzzDMW1w8dOpTFixcX+tzFIaVbwi7fiGVMRBivdA2idZ0mRscRwq74t3yAOY+O5dVNC9hw6LtC7RsZGYmvr2+e2/Tr14++fftSrVo1i+v9/PzYunUrN2/eLNS5i0NKtwTdTE1m/Lp59G7li38L248dCVEa+DS4kyUDp/LBj6tY/HPBp5RFR0fTvHnzYp27Xr16ODs78/vvvxfrOIUhpVtCtNZM//pDalaqygsdHzM6jhB27daUsu0ndhNawCllsbGxVK5cudjnrly5MrGxscU+TkFJ6ZaQj3et5+Tls0z3HyEzFYQogOoVPfl4YAiXE64xKmJ2vlPKvLy8iI+Pz7jt7+9PpUqVqFSpEsuWLSvweePj4/H09Cxq7EKTNigBW4/v4ov9W5jfdyJuzhWMjiNEqeHu4sr8vhOp51GTZ1ZM45/ruU8p8/b25tixYxm3IyMjuX79OtevX2fo0IJ9tuC5c+dITk4u9jBFYUjpWtmRi3/yxtcf8nafCdSqXNXoOEKUOk4Ojrze7Vl6tOjIsGVTOR5zxuJ2AQEBREVF5Xms1NRUkpKSSEtLIy0tjaSkJFJT/x262LFjB126dKFCBRteHGmtc/1q3769FgUXc/2q7rHoJb3l6M9GRxGiTNh0+Hvtu+A5vfN0dI51MTExul69ejohISHX/UNCQjSQ5SskJCRjfUBAgF63bp3VcwO7dS69qnQerxT6+Pjo3bt326b9S7mklGT+s3I6D97RjuH3ywtnQljL7jOHmbThHcb7DqV3q4eyrJs8eTI1a9Zk7NixhT5udHQ0zz//PD///LOVkv5LKbVHa+1jcZ2UbvFprQne9B4amNVzFEopoyMJUab8celvRq6ZRWDrLjx3X6DdP8byKl0Z07WCD3dGcCb2ItN6vGD3/xiEKI0aV6/P0iFvsO3Er0z/+kNu3EwkaHkIX+z/2uhohSalW0zf/L6T1Qe3Mr/vRFydXYyOI0SZVaOSFx8PDOGf+Cv0+mgM0edP8NHOiFL3/rxORgcozQ5fOMmMb5ew8PHJ1KjkZXQcIco8dxdXbq9Wl59PHyRNpxOflMCuM4e497a7smz3zz//EB4ezsGDB7l27RoeHh54e3vz9NNPU6OGsZ/UImO6RfTP9Ss8sex1XukSRNem9xgdR4hy4WL8ZXosfokKTi4kpSYD0K5ec8IHTwPg119/ZebMmURGRgKQlJSUsa+bmxtaa/z9/QkODqZDhw4lllPGdK0sMeUmYyPmMLBtdylcIWyoVuVqbB2xiNAew/Fv0ZGKLq7sO/s7SanJLFy4ED8/P9auXUtSUlKWwgVITEwkKSmJtWvX4ufnx8KFCw35HmR4oZDSdTpTIxfSqFpdnrmnj9FxhCh3qlX0xL/lA/i3fACAS9dj+b8PlzBx4kQSEvL/NAqtNQkJCUycOBGAESNGlGje7ORKt5AW/7Sai9cvE9L9eZmpIIQd+PPI8RyF6+LiwkcffcSpU6eIi4tj7969PPLII1n2u1W8th5CldIthMijP7H+UBRv95lABSeZqSCEPZg5cyaJiYlZljk5OXHmzBl8fX3x8PBgypQprFy5koYNG2bZLjExkZkzZ9oyrpRuQUWfP8F/t4bzTuAkqlX0NDqOEALTLIXIyMgc08YSEhKYNm0ap0+fRmvNpk2b+PPPP2nfvn2W7bTWbN68mZiYGJtlltItgIvxlxm/bh6hPZ6nWY2G+e8ghLCJ8PDwAm1Xs2ZNmjVrxqFDh3KsU0oV+DjWIKWbj4TkJEZHhDH0bn/8mlicASKEMMjBgwdzzFLIzsnJiWXLlvHJJ59Y/ISIxMREoqML/xltRSWlm4d0nc7rkR/QrEZDnurQy+g4Qohsrl27lud6pRSffvopycnJjBw5Mtftrl69au1ouZIpY3n44MdVXEm4Jm9iI4Sd8vDwyHP9kiVLqFWrFgEBAVneRzc7Ly/b/UapXOnmYtPhH9h85Efm9ZmAi5Oz0XGEEBZ4e3vj6upqcd3ChQtp2bIlvXv3znMIws3NjdatW5dUxBykdC04cO4YYduX8k7fSVR1r2J0HCFELoKCgiwuv+2223jhhRdo27YtFy5cID4+nvj4eIYMGZJjW611rscpCTK8kM25azFMWPc2b/iPoGmNBkbHEULkoWbNmvj7+7N27dos08b++uuvAg0JKqUICAiw6ZvgyJVuJgnJSYxZG8ZTHXrx4B3tjI4jhCiA4OBg3NzcirSvm5sbwcHBVk6UNylds3SdTvCm97irdhOeaB9gdBwhRAF16NCBOXPm4O7uXqj93N3dmTNnDj4+tp0KKqVr9u73K7h+M4HJ3Z6RmQpClDIjRozIKN78Hr9KqYzCtfWb3YCULgDrf4vi22O/MLfPeJwdZZhbiNJoxIgRREVFERgYiKura44hBzc3N1xdXQkMDCQqKsqQwgV5IY29fx9lXtQyPh4UgqdbZaPjCCGKwcfHh9WrVxMTE0N4eDjR0dFcvXoVLy8vWrduTVBQkOGfHFGuS/fstX+YtGE+MwJe4o5q9YyOI4Swkho1ajBp0iSjY1hUbocXrt9MYHREGM/e25cHbm9jdBwhRDlRLks3LT2dVze9R7t6zRncrofRcYQQ5Ui5LN353y3jZmoyr3QJkpkKQgibKneluyZ6Gzv+2MOc3uNkpoIQwubKVenuPnOY977/gvcCX8bDrZLRcYQQ5VC5Kd0zsRd4ecM7zOw5kkZV6xodRwhRTpWL0o2/mcCoNbN5oeNj3NfQdm/hJoQQ2ZX50k1NT+PlDe9wb8PWDGjb3eg4QohyrsyX7twdn6LRTOo8zOgoQghRtkt35f5v+OnUQWb3GoOTg6PRcYQQouyW7i9//cbCn77kvcCXqeJa0eg4QggBGFi6wcHBzJ8/v0Dbjh8/nkWLFhX42KeunOPVje/x316juc2rdhETCiGE9RlSujExMSxdupThw4cDkJyczOOPP06jRo1QSrFjx44s20+aNIkZM2aQnJyc77Hjkq4zOiKMkZ0GcM9trUoivhBCFJkhpRseHk5AQECW97vs1KkTn332GbVr57wyrVOnDi1atGD9+vV5HjclLZWJ6+fz4B1tecy7q9VzCyFEcRlSupGRkfj6+mbcdnFxYezYsXTq1AlHR8svePn5+bFp06Y8jxu2fSnOjk6M833CqnmFEMJaDCnd6OhomjdvXqh9WrZsyYEDB3Jdv2LfFn49c5hZvUbLTAUhhN0ypHRjY2OpXLlwn9JQuXJlYmNjLa776dQB/vfzGt4LnETlCoX7cDohhLAlQ0rXy8uL+Pj4Qu0THx+Pp6dnjuV/Xj7L5E3vE9Z7LPU9a1kpoRBClAxDStfb25tjx44Vap8jR47Qpk3WT3iITYxndEQYYx4aTPsGLa0ZUQghSoQhpRsQEEBUVFSWZTdv3iQpKQkwTSFLSkpCa52xPioqCn9//4zbKWmpTFj/Np2b+BDYurNtggshRDEZUrrDhg1j8+bNJCYmZixr3rw5bm5unD17lh49euDm5sbp06cBOH/+PIcPH6Zv374AaK2ZufVj3J1dGfPQECO+BSGEKBJDSrd69eoMGzaMxYsXZyw7deoUWussX40aNQJgzpw5TJ48GRcXFwA+3xvJgXPHmdVrFI4OZfY3mYUQZZDK/BQ+Ox8fH717924bxsnfDyf3EbJlMUuHTKeeR02j4wghRA5KqT1aax9L60rVZeKJS2d4PXIhcx4dJ4UrhCiV7OKTGY/+FUPoqkOciHUiSTvjqlJo4pnK9AF30axBdQCuJsQxJiKMCX5P0K5e4X6xQggh7IWhpbt822FmbYvjqmdbtL4Hh+qmX2yIBy4mJ9DtC4VX7E4m+bmz9dIauje/n96tHjIyshBCFIthpfvcgii2JPpANVeUgyMq23oHF1MBX63WgeB9SdS8XIclAwfaPqgQQliRIWO6twpXuVRE5fM+CcrBEQeXisRUe4Lh739vo4RCCFEybF66y7cdzijcwlAuFdmS6MOK7YdLKJkQQpQ8m5furG1x4OSaY7lHBVjcE468CD8+DX0svVbm5MrMrddKPqQQQpQQm5bu0b9iuOrZ1uKQwhudISUd2n8IY7bAm52hadWs2ygHR656tuXYmUs2SiyEENZl09INXXUITXqO5W5O4N8E5v4MCSmw+xx8exL6WXgPG601ISt/s0FaIYSwPpuW7olYJxycc77f7R1ekK7hz9h/lx25BM2q5tgUBxd3Tlyzi+nFQghRaDYt3STtbHG5uzPE3cy6LO4mVHSxfJzEdMvHEUIIe2fT0nVVKRaXJ6RA5WwFW9kFbuTy4b9uDpaPI4QQ9s6mpdvEM5X0lIQcy09eBUcHaOT577KWNeDYlZzHSE9OoIlHasmFFEKIEmTbF9L6t0JZOGViKnx1AsbfZ3pRzacOPHwHrDmS8xhKKaYNuMsGaYUQwvpsWrotbquBV+x+dHpajnWvbwdXJ9j7PLzrb7p9PNuVrk5Pwyt2f8ab4AghRGlj82kAr3apwit7kiDbb6RduwnPb8xn59Qkgrt6lFw4IYQoYTb/jbTBXe6kh9tudPKNQu2nk2/Qw203gzrfWULJhBCi5BnyhjcfjvTNKF5LQw2Z6fS0jML9cKSvjRIKIUTJMOyTIz4c6ctsn9N4Xd6FTkkkPTnrrIb05AR0SiJel3cx2+e0FK4Qokww9Fe7BnW+k0Gd4diZS4Ss/I0Tl51ITHfGzSGFJh6pTBtwF80a3G9kRCGEsCq7+H3aZg2qs3yCn9ExhBCixJWqD6YUQojSTkpXCCFsSEpXCCFsSEpXCCFsSEpXCCFsSEpXCCFsSEpXCCFsSGmtc1+pVAxw2nZxhBCiTGiota5haUWepSuEEMK6ZHhBCCFsSEpXCCFsSEpXCCFsSEpXCCFsSEpXCCFs6P8BWRqJ+YDM8aEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "candidates = [[1, 3, 0, 2], [1, 2, 3, 0], [0, 2, 3, 1], [0, 3, 1, 2]]\n",
    "reviewers = [[1, 0, 3, 2], [3, 1, 0, 2], [0, 1, 2, 3], [2, 3, 1, 0]]\n",
    "\n",
    "assn_inst = assignment(candidates, reviewers)\n",
    "\n",
    "viz_prefs(candidates, reviewers)\n",
    "\n",
    "assn_inst.draw_rotation_digraph(method='maxflow')\n",
    "plt.title(\"Rotation flow graph\", size=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([(0, 0), (1, 2), (2, 3), (3, 1)], array([ True,  True, False]))"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The optimal stable assignment and verbose solution\n",
    "assn_inst.osa(method='maxflow')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 6min 3s\n"
     ]
    },
    {
     "data": {
      "image/png": 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3B+IRkBKQrJtEiWkKf/69ZSjNyxYdjzTO421BuaVw1tctyViMZYuLccx9Ft9e/koEkpEaTU5P4ZP6s/i/3/mxrOvqdDrYTRZ0DHqRnjz730ciIrXhzhSRynz0eT1W/smXeP3ni3Au+Bx82RswbH4evuwNOBd8Dt/6WSpW/smX+OjzetFRScPc3haUz2FnCgi1ST90+QQkSVI4FanVueZrsJssKMjMlX1tmzFUTBERaRGLKSIV+eFf1uKPLy9Bf9Y66BKSoU9MeeTr+sQU6BIM6M9ahz++vAQ//MtaQUlJyyRJgsfbijJLwZxe/8KS5ZiWgrh4lwV8rAo1ntiiyNo2Y2hwLxGRFrGYIlKJH/5lLU7610KXmAqdPu6Zr9Xp46BLTMVJ/1oWVDRv3cO9SIiLR3aqaU6v1+l02F25DYfYJj0m9Y4O4tLdOmwtW6/I+nbuTBGRhrGYIlKBjz6vf1BIzcdMQfXTL7hjQHPn9ragzDy3I34z3nRsxLUODwesxqBjDWexqbgSaUkps784DHaTle3RiUizWEwRqcC/+nwIiH98zs+cxCdj/2eD8gaiqOb2tqLcWjCv9xgSkrBr2RZ8dPWkMqFIlSRJQrWCR/yA+8f82B6diDSKxRSRYO42H/pNq2Y92vc0On0c+k2r0Hi3R+ZkFK1CO1MF837fO6u34mjdaYxO+OUPRark9rZgdMKPdXkOxZ6Rm25G11AvpoNBxZ5BRKQUFlNEgv3kF3WQsLAPEZIk4cc/d8mUiKKdx9sy750pAFicno3n8p044uI9vVhx2FWDnc5N0OuU+7iQnJAIoyENvpE+xZ5BRKQUFlNEgt0eiIc+YWF3EfSJKbg9yLFxNLuhwAgGAyPIM1nDev/uyiocunoCQYm7CNFuYmoSJ9znscO5WfFn2Y0W3psiIk1iMUUkWEBKkGUdf1CedSi6ebytWGrOD3unYbWtDKmJBpxrvi5zMlKbmqbLWJqdD7vJoviz2B6diLSKxRSRYMm6SVnWMejlWYeiWzid/B6m0+nwXmUVPmSb9KhX7arBrmXK70oBMztTbEJBRNrDYopIsBLTFIKTYwtaIzgxhhLjlEyJKJp5vK0on+Ow3qfZWrYet3xtaOpplycUqU73cB+ud97Cq0ufi8jz7CYrOgZ9EXkWEZGcWEwRCfaT7zqhW+B/ijqdDn/2vWUyJaJo5va2LLiYSoxPwO+seBWHrp6QJxSpzsf1Z/Ct0ueQkhjmyIZ5shnN6ODOFBFpEIspIsHK883IGLgGKTgd1vul4DQyBq6hNC9b5mQUbcanJtA2cA/F2fYFr/XdVa/hpPsCBv0jMiQjNQnNlqpRdLbUN9mMVt6ZIiJNYjFFpAL/9JV0YCoQ3punAtj3qlHeQBSV7vR2IN+0GEnxiQteKzvVhM3Flfj1zc9lSEZqcr2zEQCwKrc0Ys80p5kwMjGGsYkwfw4SEQnCYopIBd59xYGthkuQJkbn9T5pYhRbDZfwzsvKDdSk6NHgbUaZJfzmE9/0XmUVfnb1FKbC3FUldap21WLXss3Q6XQRe6Zep0duuhmdQ7w3RUTawmKKSCX++g83PyioZjvyJwWnHxRSf/2Hkem2RdonR/OJhzlyimBNz8IXty7KtiaJ5Z8cx28av8Kbjk0Rf7aNs6aISINYTBGpyF//4Wb8bfsXSO46A2nSj+DEo13+ghNjkCb9yOj9Gn+xtpWFFM2L29uCMhmLKQBskx5lPrv1NVYsLoF1UWbEn20zWtAxwCYURKQtLKaIVORc83Uc7fgQyys+waffH8UG/dew9J5FmvcrTN75NdbrvsTypP8D//EHSTzaR/MSlIK45WtDuYzH/ADglaXrcG+oBw3dzbKuS2JEuvHEw9genYi0iMUUkUqccJ/HP67+ABIkAEBpXjY++qMtuPjnG1D3L5/HprUX8Se78/AHL2/lTgDN292BbhiTU5GenCbruvH6OHx/1ev48DL/Tmpdx6AXjb42bClZI+T5dh7zIyINYjFFpAJHXLX4Z8f+CuNTkwCAAf/wY69xWAtR19WEbeUvcmAqzZvH24oyS6Eia39nxauoabqM3tEBRdanyDhadxpby9bL0u0xHDajBe085kdEGsNiikgFjIY02NLN0EEHPXQY9I9AkqRHXuOwFqG++05oYOrKb3FgKs2L29ss+xG/GUZDGl4vewG/uP6pIuuT8oJSENWuWrwl6IgfMDO41/fYzz4iIjVjMUWkApuL1+DfvfVHMBnS8J2Vr8JusiL4jQ8Uzpxi1N+/l/I9DkyleQrtTBUotv7uym34xfVPMXF/d5W05dLdBqQmGlBhVWb3ci7SklJgSEhE39igsAxERPPFYopIJY64avHW8pfxJ6/9XRz+O/8GcfpH//Msyc5D+0A3xiYCHJhK8+b2tsjaFv2bSrLzUJKdh5OeC4o9g5RT7arBzgjPlnqSXN6bIiKNYTFFpAKT01P4pOHsM4/YJMTFozjLDo+vFQAHptLc9YwOYGJ6EjmLshR9zu7KbTh05QSPaWnMyPgYapsu442KDaKjhJpQDLCYIiLtYDFFpALnWq7DZjSjIDP3ma9z5ITuTc383xyYSnMxM6xX6V2HjUWrMTI+hmudjYo+h+R1yvMl1uY5kJVqFB0FdpMF7YNsQkFE2sFiikgF5jrbxZFThPquOw/+fw5Mpblwe1tQZi5Q/Dl6nR7vVG7FIbZJ1xSRs6W+yW7krCki0hYWU0SC9Y0N4WJbHbaWrZ/1tU5r8SPFFAem0lx4vC0otxZE5Fm7nJvxZdtNdA31ROR5tDAtfZ1oG+jGhsJVoqMAuN/Rj+3RiUhDWEwRCXas4Sw2FVciLSll1tcWZdnQOdSD0Qk/AA5MpbmJ1M4UEOrItsOxCT+9dioiz6OFOVJXizcqNiAhLl50FACAzWhlAwoi0hQWU0QCSZIUOmLj3Dyn1yfExWOpOQ8eb8uDP+PAVHqWsYkAuof7UJj17Pt4cnq3cisO3/wC/snxiD2T5m86GMTRujOqOeIHADnpWegdG8Tk9JToKEREc8Jiikggt7cFI+NjWJfvnPN7HNYi1D101I8DU+lZGn2tKM6yIV4fF7Fn5plysCK3FJ/Un4nYM2n+vmy9AXOqCUvNeaKjPBCvj4M1LROdQ7w3RUTawGKKSKDDrhrscG6GXjf3/xSdD3X0m8GBqfQ0Hm9rxO5LPew9tklXvcMqajzxMBvboxORhrCYIhJkYmoSJ9znsXOOR/xmfHNnCuDAVHq6SN6Xethz+cug0+nwVZsr4s+m2Q36R3Ch5QaqKl4UHeUxdpMFHWyPTkQawWKKSJDapssoyc6D3WSZ1/sKs2zwjvRhZHzskT/nwFR6Eo+3BWWWJRF/rk6nw+7KbWyOolLH3efwYsFKpCeniY7yGBvboxORhrCYIhKk2lWLt8I4YhOvj0OZeclj7dA5MJW+aXJ6Ck297Sg1R76YAoDtFRtw894ttPV3CXk+PV21qxa7ls1vVzxS7EYL2tkenYg0gsUUkQDekT5c62zEq0ufC+v9FdbH701xYCp9U0vfPVgXZSElMVnI8w0JSXh7+Sv46OoJIc+nJ7vla0PP6ABeWLJCdJQnshktbI9ORJrBYopIgI/rzuBbpc+F/SHXmfP4vSmAA1PpUW5vM8otBUIzfH/Va/i4/sxjx1JJnFDjm42I06vzI0DozhSLKSLSBnX+JCWKYpIkobqudkFdtBzWoseO+QEcmEqP8nhbUSa4mMpJz8YLS5aj2lUjNAeFTE5P4VjDuXk3vokkY3IaJEnCUGBEdBQiolmxmCKKsBv3bkGSJKzKLQ17jYLMXPSMDjzxwwYHptIMj69F+M4UALxXWYWPrp7EdDAoOkrMO9t8DfkZOSjIjNwQ5/nS6XRsj05EmsFiiijCql012LVsM3Q6XdhrxOn1KLM83oQC4MBUCpEkCW5vC8oFdPL7ppW5pUhPSsWZ5quio8S8mZ8/amcz8d4UEWkDiymiCPJPjuOU5yu86di04LWedm8K4MBUArqGe5EUl4isVJPoKKE26Wuq2BxFsN7RQVy6W4+tZetFR5kVO/oRkVawmCKKoM9ufY3li0tgXZS54LUc1uIn7kwBHJhK94f1qmBXasbWsvW409uBW767oqPErE8azmJL8VqkJhpER5mV3WhFxxBnTRGR+rGYIoogOY/YOHOKUNf95J0pDkwlUcN6nyYhLh6/s/Jb+Ogq/06KIEmSZo74AYDNaObOFBFpAospogjpGPTC423FyyVrZVkvPyMHA/5hDPiHn/h1DkyNbaH7UoWiYzziuytfxSnPV0/9O0vKqe++A//kONbkVYiOMid2k5Xt0YlIE1hMEUXI0boz2Fb+IpLiE2VZT6/To8JS8Njw3hkcmBrb1LYzBQBZqSa8XLIGv7rxuegoMafaVYudzs3Q67Txa39xeja6hnvZAZKIVE8bP1WJNC4oBXGkrlb2IzaOnCfPm5rBgamxadA/gsHAKPJMVtFRHrO7sgo/u3YSk9NToqPEjPGpCZxwn8cO50bRUeYsKT4RmSnp6B7uFR2FiOiZWEwRRcDluw0wJCTBYS2SdV1HTvFTO/oBHJgaqzy+Viw156tyF6LCWgib0YLPb10UHSVmfHH7EsosS2AzWkRHmRebke3RiUj91PebligKVbtqsWvZlgXNlnoSh7UQ9c8opgAOTI1FoftSBaJjPNV7lVU4dIWNKCJl5ueP1tiNFrQPsgkFEakbiykihY1O+FHTdAlvVGyQfe08kxUjE2PoGxt66ms4MDX2qPG+1MO2lKxF93Af6rqaREeJet3DvXB13carS58THWXebEYrOgfZHp2I1I3FFJHCTnouYG2eA1mpRtnX1uv0qLAWouEpTSgADkyNRR5vKypU1snvYfH6OLyzeis+5O6U4j6uP4PXSp+HISFJdJR5Y3t0ItICFlNEClP6iI3DWvTMe1MAB6bGkvGpCdwd6EJxll10lGf69oqXcbrpKnwj/aKjRC1JknDYVaPJI35AqD0670wRkdqxmCJSUEtfJ9r6u7ChcJViz3BYi57aHn0GB6bGjqaeduRn5CAxPkF0lGdKT07DtvL1+MX1T0VHiVrXOhuh1+mxYvFS0VHCYjda0D7AYoqI1I3FFJGCjtTVYnvFS0iIi1fsGc6c2YspgANTY4Xb24Iyc4HoGHOyu7IKv7z+KSamJkVHiUrVrhrscm6WvfFNpGSnmuCfDGBsIiA6ChHRU7GYIlLIdDCIo3Vn8JbCR2xsRgv8k+PoGR145us4MDU2uFXefOJhRVk2lFqW4IT7vOgoUWdsIoBPG7/GmxqaLfVNOp0OuelmdPCoHxGpGIspIoV82XoD2akmLDXnK/ocnU4XOuo3y70pgANTY4FH5W3Rv+m9yip8eOU4JEkSHSWqfHbra6zKLYUlLVN0lAWxmThriojUjcUUkUJCF783R+RZc7k3BXBgarQLSkE0+to0szMFAC8VroR/chxXO9yio0SVSP78UZLdaOXOFBGpGospIgUMBUZwvvk6qspfisjzQvemmuf0Wg5MjV5t/V0wGRYhPTlNdJQ50+v0eHf1VnzI1v2yaR/oxu2eu9hcvEZ0lAWzm9iEgojUjcUUkQKON5zHi4UrYTRE5kPtXI/5ARyYGs083laUaeiI34ydyzbj4t16DmiVyZG609hW/qLqOzrOhc1oQfsgZ00RkXqxmCJSQLWrRvHGEw9bnJ6NyeAUvCN9s76WA1Ojl1tj96VmpCYasMO5CT+7dkp0FM0LSkEcrauN6M8fJdmNFnRwZ4qIVIzFFJHMbvnuwjc6gBeWrIjYM+fThALgwNRoFWo+oZ37Ug97d/VWHHbVsA32Al1sq0NaUoomi+onsRkt6BzysUEJEakWiykimVW7arDDuRFx+sj+5zWfe1McmBqdPL5WzX6ItpusWG0rw8f1Z0RH0bTqulrsWrZFs7OlviklMRkpiYZZRz8QEYnCYopIRpPTU/ik4Sx2OiPfRWs+O1MAB6ZGm57RAUxOT8G6KEt0lLDtrqzCR1dOcBciTMPjYzjddAXbKzaIjiIrm9HM9uhEpFospohkdLb5GvIzclCQmRvxZzushajrvjPnD6IcmBpdZuZLaXlHYl2eA/FxcbjQekN0FE065bmAdflOZKaki44iK7vRgvYBNqEgInViMUUko2pXDXYJ2JUC8GBHonu4d87v4cDU6OH2tmhqvtST6HQ6vFu5DYcunxAdRZOqXTXYFSWNJx5mN1nRwU6PRKRSLKaIZNI7OohLd+vxetkLQp6v0+ngtM793hTAganRJFRMFYiOsWDbyzfA1dWElr5O0VE0pbm3Ax2DPmwoXCU6iuxyjWZ0sD06EakUiykimXzScBabi9cgLSlFWAZHThHqu+d+b4oDU6OHVtuif1NyQiK+s+IVfHT1pOgomlJdV4s3KjYgXh8nOors7EYr70wRkWqxmCKSgSRJqjhi47AWom4eTSgADkyNBqMTfniH+4Xc1VPC91a9jmMNZzE8PiY6iiZMBafxcd0Z7Fwm5oix0kJ3plhMEZE6sZgikkFDdzPGJgJYm1chNIcjpwgN82hCAXBgajRo9LWhONseNbsS1kWZeLFgJQ7f/EJ0FE240HIDlkWZKMnOEx1FEdZFWRjwD2N8akJ0FCKix7CYIpLBYVcNdi3bDL1O7H9SlrRMxOvjcW+oZ17v48BUbdPysN6nea+yCh9dPYnpYFB0FNWrdtXgrSjdlQKAOL0e1kWZ8/65RkQUCSymiBZofGoCJz0XsMO5SXQUAPO/NwVwYKrWRct9qYetyF2KDMMinL5zRXQUVRvwD+NCyw1sK39RdBRF2dgenYhUisUU0QLV3L6MUnM+bEaL6CgAwrs3BXBgqpZ5vK1R0cnvm95bU8XmKLM43nAOG4pWIz05TXQURbE9OhGpFYspogVSQ+OJhzms89+ZAjgwVasmp6dwp7cdS7PzRUeR3WulL6ClvxONvlbRUVSruq4Wu6L4iN8Mu9GCdrZHJyIVYjFFtADdw3242XUbry59TnSUB2aO+c13h4kDU7Wppa8TOenZSElMFh1Fdglx8fjeytdw6Ar/Tj5Jo68VfWODeD5/uegoirMZLWyPTkSqxGKKaAE+rj+N10qfhyEhSXSUB7JTTUiOT0JHGB88ODBVe9zeFpSZo6v5xMN+Z+W38Gnj1+gfGxIdRXWqXTXY6dyMOH30/yq3Gy3oYHt0IlKh6P8JTKQQSZJw+P6HGbVx5hSFdW+KA1O1JxqbTzwsMyUdryxdh1/d+Ex0FFWZnJ7CJ/XnVPnzRwl2kwUdg17e6SQi1WExRRSma52N0Ov0WJlbKjrKY8K9NwVwYKrWRGvziYe9V1mFn137DSanp0RHUY3Td66gMCsX+Rk5oqNERHpyGnQ6PQYDI6KjEBE9gsUUUZhmjtjodDrRUR7jDKM9+gwOTNUOSZLg8UXfjKlvKrMsQb7Jik9vfS06impUu2qxy7lFdIyIshnNaOdRPyJSGRZTRGEYmwjg08avscO5UXSUJ6qwFqGhuxlBKbyBp+9VVuHQlRMcmKpy94Z6kBSXiKxUk+goitu9pgqH2CYdANAzOoAr7W68XvaC6CgRxY5+RKRGLKaIwvDZra+xMncpLGmZoqM8UWZKOtISU3A3zCGXK3KXIjMlHbVNl2VORnKK9vtSD9tSvBY9owO4ee+26CjCfVJ/Bi+XrI3KDo7PwllTRKRGLKaIwlDtqlXVbKknCbVIbw77/e+tqcKHV7gToGYebwvKovyI34w4vR7vrN6KQzH+dzLU+CY2Zkt9k81oRgd3pohIZVhMEc1T+4AXt3rasKV4jegoz+TMKUJ9V1PY73+t9AW09t/jwFQVi6WdKQB4e/nLOHPnGrwjfaKjCFPXdQcTUxNYY68QHSXibEYr70wRkeqwmCKap6N1tdhW/iIS4xNER3mmCmsh6sNojz5jZmDqh7ynolqx0MnvYenJqdhe8RJ+fu03oqMIU+2qwc5l6mx8ozS7iYN7iUh9WEwRzUNQCuJIXS3eUvkRPyDUHr3B2xJ2EwogNDD1s1sX0ceBqaoz6B/B0Pgo7CaL6CgRtbtyG355/TOMT02IjhJx41MTOOm5EDOzpb4pN90M70gfpoLToqMQET3AYopoHi7erUdaUoomjlaZDItgMixCW39X2GtwYKp6uX0tKDXnQ6+LrR/jBZm5cFgLcazhnOgoEff57UuosBZicXq26ChCJMTFIyvFiK6hXtFRiIgeiK3fwkQLVO2qwa5lWzRzxMZpLULdAo76ATMDU09xYKrKxNoRv4e9t6YKh64chyRJoqNEVOjnT2zuSs2wGy1sQkFEqsJiimiOhsfHcLrpCrZXbBAdZc4qrIWo7w6/CQUQGpi6xJSDTxu/kikVycHtbdbEDqkS1heswMT0FC7drRcdJWK6hnpQ19WEV0qeEx1FKBvboxORyrCYIpqjU54LWJvnRGZKuugoc+bMWfjOFBAamMo26eri8bbGbDGl1+mxe/U2fHjlhOgoEXO0/gxeL1uP5IRE0VGE4uBeIlIbFlNEc1TtqsFbGjtiU2EthMfbiulg+E0ogNDA1N7RQdy4d0umZLQQgckJ3B3oQnGWXXQUYXY4N+FKe0NMtMqWJAlHYnS21DfZjJaY+J4TkXawmCKag+beDrQPePFS4SrRUeYlPTkN2akmtPR1LmidBwNT2SZdFZp672JJxmLVt+dXUkpiMnYt24yfXj0pOorirna4Ea+Pw/KcEtFRhGN7dCJSGxZTRHNwpO403nBsQEJcvOgo8xa6N7Xwo35vL38ZZ5uvo3s4dgemqkWsDet9mndWb8WRulqMTQRER1HUYVetphrfKMlutKCTxRQRqQiLKaJZTAeDOFp/Grs0MFvqSZw5RbIUUzMDU39xPXYHpqpFLHfye5jNaMGavAocqasVHUUxYxMBfH7rIt5waKfxjZIyU4zwT05gZHxMdBQiIgAspohmdaHlOixpmSjJzhMdJSwOaxHqZWhCAcT2wFQ1ieVOft/0XmUVDl05saDh1Gr2aeNXWGUrhTktQ3QUVdDpdLAZzezoR0SqwWKKaBbVrlrNNZ54WLm1EB5fK6aC0wteqyAzF86copgcmKoW08EgbvnuotS8RHQUVVhjr0ByfCLON18XHUURocY3W0THUBW7ycqOfkSkGiymiJ5h0D+CC603sK38RdFRwrYoKQWWtEw093bIst7uytgcmKoWdwe6kJGSjvTkVNFRVEGn02F3ZVVUtklvH+hGU287NhevER1FVUKDe7kzRUTqwGKK6BmONZzFS4WrkJ6cJjrKgsh1bwoAXixYgckYG5iqJm5vC8os3JV6WFXFi3B7W2T7BwO1qHbVoqriJU02vlGSzWhG+wB3pohIHVhMET1DdV10zHZxWOUZ3gvM7ATE1sBUNfF4W1FmLhAdQ1WS4hPxnRWv4FAU/Z0MSkEcrdNu4xsl2UxWdLCjHxGpBIspoqdo9LWib2wQz+cvFx1lwRxW+XamAOBNxyZc7XBzeKYAbm8Lyq0FomOozvdWvYbj7vMYCoyIjiKLr9vqkG5IY6ORJwgd8+PPHiJSBxZTRE9R7arBDscmxOm1/59JubUAt3x3MTk9Jct6KYnJ2OWMjYGpauPxtqCczSceY0nLxMaiVfifN78QHUUW1a6aqNgVV4LNaEHnkC9qOzgSkbZo/1MikQImp6fwSf057IySDzOpiQbkpmfjjox3SmJlYKqa+Eb6MS0FYV2UJTqKKu2urMJPr56UpXOlSEOBUZy5cxXby18SHUWVDAlJSEtMgW9kQHQUIiIWU0RPcvrOFRRkLsaSjMWio8jGkVOEuu4m2dbLNZqxNs8R1QNT1cbjbUGZeQl0Op3oKKq0fHEJzGkZqLl9WXSUBTnpuYDn85chIyVddBTVspss6GB7dCJSARZTRE9wxFUbdRe/HdZC2Yb3zoj2galq4/a28A7NLGZa92tZ6IjfFtExVM1mtLI9OhGpAospom/oHR3A5fYGvF72gugosnLkFMteTFXay5GckBS1A1PVxuNtRRmLqWd6delzaB/shtvbIjpKWO70duDeUA9eLFwpOoqq2Y0WtkcnIlVgMUX0DR/Xn8XLJWuRmmgQHUVWZeYlaOptl60JBRBqk/4e26RHDHemZpcQF4/vr3odH17W5u5UtasGbzo2Il4fJzqKqtmMFrSzox8RqQCLKaKHSJIUtUdsUhKTYTdZcbvnrqzrbit/EZ4oHJiqNqMTfnhH+rEkM3ru8SnlOytexRe3L6F3dFB0lHmZCk7jk/qzUfnzR252E4spIlIHFlNED6nruoPxqQmssVeIjqIIh7UQdV3yNaEAZgamvhpVA1PVqNHXhuJsO3cs5sBkWITXSp/HL298KjrKvJxvvo6c9CwUZdlER1E9zpoiIrVgMUX0kGpXDXYu2xy13dLkHt47I9oGpqqRu7uZR/zmYXflNvzi2qeyHmtVWrTuiivBnJaJQf8IApMToqMQUYxjMUV03/jUBE56LmCnMzpmSz2JM6cY9d3Nsq9rTsvAxqLVUTMwVY08vlaUWzisd66WmvNRmJWLU54vRUeZk/6xIXzV5sK28hdFR9GEOL0eOelZ6BxiRz8iEovFFNF9n9++hHJLARanZ4uOophS8xI093ZgfEr+f819L0oGpqpVqPlEoegYmvJeZRU+vHIckiSJjjKrY+5z2Fi0GouSUkRH0Qy70cqOfkQkHIspovti4YhNckIi8jNycMsnbxMKAFi2uDgqBqaq0eT0FJp7O1CSnSc6iqZsLKrEoH8YN+7dEh1lVtVRONtOabw3RURqwGKKCEDXUA/quprwytJ1oqMoTql7U0B0DExVo+a+DixOz0ZKYrLoKJoSp9fj3cptqm+T7va2YMg/gufynaKjaArboxORGrCYIgJwtP4MXit9AYaEJNFRFOfMUa6Y0vrAVLXisN7w7Vq2BRdab6B7uFd0lKeqdtVgh3MT9Dr+Sp4Pu4k7U0QkHn9yU8yTJAlHXLV4K0aO2FRYi1DfpUwxpfWBqWrl9rKTX7gWJaXgjYqN+Nm1U6KjPNHk9BSON5zHrmXR2/hGKTYe8yMiFWAxRTHvaocHcXo9li8uER0lIkrN+Wjtv6dYS2GtDkxVM7e3FWXs5Be2dyu34tc3vlBlG+3apisozrLBbrKKjqI5dpMV7QNeTTQYIaLoxWKKYt5M44lonS31TUnxiSjIzEVjT6si62t1YKpaSZIUOuZnLhAdRbOWZCzGssXFONZwVnSUx8zMtqP5W5SUgvi4OPT7h0VHIaIYxmKKYtrYRACf3bqINx0bRUeJKGeOckf9AG0OTFWrziEfkhMSkZVqFB1F09TYJr1ndABXOzx4rfQF0VE0y260on2Q7dGJSBwWUxTTPm38CqtspTCnZYiOElEV1iLUKVhMaW1gqpp5vK0o567Ugr2wZDmCkoSv79aJjvLAx3Vn8MrSdezSuACh9ugc3EtE4rCYophW7aqJmcYTD3Mq2B59hhp3ArTI7W1BubVAdAzN0+l02F25DYdU0hxFkqT7P394xG8hco1mdHBwLxEJxGKKYlb7QDeaetuxuXiN6CgRV5Kdh/aBbvgnxxV7hpYGpqqZx9uCMjObT8jhTcdGXO9sxN2BLtFRcLPrNqaC01htKxcdRdPsJitnTRGRUCymKGZVu2qxrfwlJMTFi44ScYnxCSjOssOj4DworQxMVTvuTMnHkJCEXcu24KdXT4qOgmpXLXYu2xwzjW+UYjda0D7AYoqIxGExRTEpKAVxtO50TM92qcgpQp3CR/20MDBVzQb8wxgZH4PNaBEdJWq8s3orjtadweiEX1iGwOQETnkuYEeMNb5RAgf3EpFoLKYoJn3dVof05FRUWAtFRxHGqeDw3hlqH5iqdh5vC0otS6DX8Ue1XBanZ+O5fCeqXbXCMnx++2s4c4qRk54tLEO0yFmUDd9oPzuHEpEw/A1NMSk0Wyp2d6UAwJFThPruZsWfo+aBqWrn5nwpReyurMJHV08gKAWFPL/aVYtdMdj4RgkJcfEwp5rQNdwjOgoRxSgWUxRzhsfHcLrpCrZXbBAdRajiLDs6B30Ymwgo+hw1D0xVO7e3BeWWAtExos5qWxlSEw04e+daxJ99b6gHDd3NeKVkbcSfHa1sRivvTRGRMCymKOacdJ/H80uWIyMlXXQUoRLi4lGSbYfbq/zuFNukh8fjbUGZhZ385KbT6R78nYy0o3WnsbVsPZLiEyP+7GjFe1NEJBKLKYo5oSM2sX3Eb4Yzp1jR4b0z1DgwVe0CkxPoGPSiJDtPdJSotLVsPW733EVTT3vEnilJEo7U8Yif3GxGC9ujE5EwsdcTmmLand4OdA758FLhKtFRVMFhLcJXbS7Fn/PwwNTn85cp/rxocLvnLpZkLI7J1v2RkBifgN9Z8SoOXT2B//21vxuRZ15pdyMhLgHOnKKIPC9W2I0WfH7rougYRJrj9Xpx8OBB3LhxA4ODgzAajVixYgV+8IMfwGw2i46nGdyZophS7arBm46NiNfHiY6iCs6cItQr3B59hpoGpmqB29vMI34K++6q13DSfQGD/pGIPO+wqwZvcbaU7Gw85kc0LxcvXsS3v/1tLFmyBD/+8Y/x4Ycf4uOPP8aHH36In/zkJ8jPz8e3v/1tXLzIf6SYCxZTFDOmgtP4pP4sj9g8pDDLhq6hXoyMjyn+LDUNTNUCj7eVzScUlp1qwubiSvz65ueKP2tsIoAvbl/CG5wtJTu70cpjfkRzdODAAWzZsgWHDx9GIBBAIPBoEyq/349AIIDDhw9jy5YtOHDggKCk2sFiimLG+ebryEnPQlGWTXQU1YjXx6HMko+GCLRIB9QxMFUrPL4WlLGYUtx7lVX42dVTmApOK/qcU54vUWkvR3aqSdHnxKIMwyJMTE9iKDAqOgqRqh04cAB79+7F2NjYrA2hJEnC2NgY9u7dy4JqFiymKGaEZkttER1DdRzW4ojMmwLUMTBVC6aDQTT62lhMRYAjpwjW9Cx8ofCdm+o6zrZTik6ng91o5VE/ome4ePHig0JqPmYKqkuXLimUTPtYTFFM6B8bwpetN7G1bL3oKKrjsBZG7N4UIH5gqhbcHehCZooRi5JSREeJCUq3SW/r70Jzbyc2FVUq9oxYF2qP7hMdg0i19u/fD78/vFMhfr8f+/fvlzlR9GAxRTHhmPscNhatRnpyqugoquPIKUJ9BNqjzxA5MFUrGjisN6JeWbruwTBdJRypq8UbjpfYmVFBNqMZHYPdomMQqZLX68Xx4+HPepQkCceOHYPPx3+weBIWUxQTQrOltoiOoUqFmTb0jA5E7L6ByIGpWsFhvZEVr4/D91e9jg8vy/93cjoYxNG60/z5ozCb0Yr2AR7zI3qSgwcPLngNnU4nyzrRiMUURT23twWD/mE8x/lGTxSn16PMsgQN3sjcmwLEDEzVEjd3piLuOyteRU3TZfSODsi67tdtLmSkpKPUzOJYSXYO7iV6qhs3bjzWtW++/H4/bt68KVOi6MJiiqLeEVctdjg3IU7Pv+5P47BG9qjfwwNT6VGSJMHdzWIq0oyGNLxe9gJ+cf1TWdetdtVgl5ONJ5RmN7EBBdHTDA4OyrJOf3+/LOtEG366pKg2OT2FYw3n2EVrFpG+NwVEfmCqVvhG+yFBgiUtU3SUmLO7cht+cf1TTExNyrLeUGAUZ5uvoariJVnWo6fLTTfj3lAPpoNsbEP0TUajUZZ1MjIyZFkn2rCYoqhW23QFRVk25JlyREdRNae1KKId/YDIDkzVkplhvTqdTnSUmFOSnYeS7Dyc9FyQZb0T7vN4YclymAyLZFmPni45IRHG5DT4RvpERyFSnRUrViA5OXlBaxgMBixfvlymRNGFxRRFtdBsKe5KzWZJ5mL0+4cjvksUqYGpWuL2tqCM92uE2V25DYeunAi769XDONsusmxsj070RO+///6C15AkSZZ1ohGLKYpaPaMDuNrhwWulL4iOonp6nR7lloKI705FamCqlni8LSi3FoiOEbM2Fq3GyPgYrnU2Lmidpp52dI/0YX3BCpmS0WxCTSjYHp3omywWC6qqqsI+8aDT6bB9+3aYzWaZk0UHFlMUtT6uO4NXlq5DSuLCtrZjhUPAUT9A+YGpWuPxtqLMXCA6RszS6/R4p3IrDi2wTXq1qwZvOjYiXh8nUzKajc1oYXt0oqfYt28fDAZDWO81GAzYt2+fzImiB4spikqSJKHaVYO3eMRvzpwCmlAAyg9M1ZKR8TF4R/pRkJkrOkpM2+XcjC/bbqJrqCes909OT+GThrN4i0f8Iort0Ymebt26dfjggw+QkpIyr/elpKTggw8+wNq1axVKpn0spigq3ey6jcngFFbbykVH0QxHjpidKSUHpmpNo68NJdl2tvEXLC0pBTscm/DTa6fCev/5luuwGc0siiPMbrKgk8UU0VPt2bPnQUE125E/nU73oJDas2dPhBJqE39jU1SqdtVip3MzO6LNQ57JiuHxMfSNDUX82UoNTNUat7cF5dZC0TEIwLuVW3H45hfwT47P+73Vrlo2nhDAZrRyZ4poFnv27EFtbS3efvttJCcnP3b0z2AwIDk5GW+//TZqa2tZSM1BvOgARHILTE7glOcCfvG3/rXoKJoSakJRiIbuO3ipcFVEn/3wwNS//+LvRPTZauLxtsCZUyw6BgHIM+VgRW4pPqk/g99Z+a05v69/bAhft7nw59v+voLp6EnMaSYMBUbhnxyHISFJdBwiVZIkCb/sOo+831uPtv/8n3Hw4EHcvHkT/f39yMjIwPLly/H++++z2cQ8sJiiqPP57a/hsBYhJz1bdBTNceYUob67OeLFFBBqSf0Hv/iX+DvP7UJifELEn68Gbm8LvrPyVdEx6L73KrfhX3/+3/CdFa/OeZf7WMNZbCquRFrS/O4l0MLpdXrkGs3oGPSiJDtPdBwi1QlKQfzL3/xfOO4+j6IsG8xmM370ox+JjqV5POZHUafaVcuL32FyWItQJ6AJBSD/wFStmZyeQktfJ5Zm54uOQvc9l78MOp0OX7W55vweHvETy260oINH/YgeMzk9hb1H/j2O1p8O/f9TU4ITRQ8WUxRVZrrCvVyyTnQUTXLkFKK+u0nY8+UcmKo1d3o7sDg9m8eTVESn02F35Tb8j0vHcK75Ov5d7YfPfH1DdzOGx0exLs8RoYT0TTZ29CN6or8693N8fvsixqcmAQD9gWHBiaIHiymKKkfrTuP1sheQnJAoOoom2Y1WjE2MC2sEIdfAVC3yeFtQbikQHYMeMjYRwNhEAGebr+EfV38w6zy0alctdjg3Q6/jr1ZRbEYLOjhriugxf2vtm/j/vPg96HU6JMUlYHTcj6ngtOhYUYE/8SlqSJKEI3U8YrMQOp3uwb0pEeQamKpFbm8LylhMqcp/Ovdz/Jua/wEJEsanJpEc//R/pJmYmsQJ9znsdHK2nUh2E3emiJ4kMyUdjpwilJqX4G++/6f4By99F3p2PJYFiymKGlfa3UiIS8AydkNbEJH3poCFD0zVKu5Mqc8fbngHG4tWI+l+EZUc//QjmLVNl1GcnQe7yRKpePQEdqOVd6aInqLaVYO3lm3Bityl+Hvrv81ddJnwf0WKGoddNXhrGWdLLZTDWihkeO+MhQ5M1SJJkuDxtXJnSmWSExLxf779I/xuZRV0AKalpx+JYeMbdbAZzWgf8MbkvUuiZxkKjOBc8zVsr9ggOkrUYWt0igpjEwF8cfsi/tGmd0VH0TxHThH+9Rf/TWiGdyu34vc+/N/xB+u/ExMNGToGfTAkJCMzJV10FPoGnU6H/2XTu0hJTMaFlhvwer04ePAgbty4gcHBQRiNRhSXL8VFvQd/seMfiY4b89KSUpCckIi+sUFkpZpExyFSjRPu83ixYCWMhjTRUaIOiymKCqc8X2K1rRzZ/OW5YLnpZkxOT8E70gdLWqaQDOEOTNUqj68FZZYlomPQM6yMs+PYz/87lvwg9H0KBAIPvpacnIzpYBC/eymAffv2Yd06dhMVyWa0oGPQx2KK6CGHXbX4By/+jugYUYnH/CgqVNfVsPGETHQ6HSqshcKaUMx4L4bapLu7eV9KzQ4cOIAtW7bg8OHDCAQCjxRSQKiwmpyYwOHDh7FlyxYcOHBAUFICQrOm2ge7RccgUo3bPXfhHenD+oKVoqNEJRZTpHlt/V1o7u3E5uJK0VGihtNahHqBTSiA8AamapXH18piSqUOHDiAvXv3YmxsbNbCXpIkjI2NYe/evSyoBLIZLWhne3SiB6pdNdjh2IQ4PT/2K4H/q5LmHamrxfaKl5AQx1OrcnHkFAltQgE8NDD18jGhOSLB7W3mMT8Vunjx4oNCaj5mCqpLly4plIyehe3RiX5rcnoKn9Sfxa5lHNugFBZTpGnTwSCO1p3mET+ZzexMiT5it71iA1z3bqO1/57QHErqHxvC6LgfNiNbaqvN/v374ff7w3qv3+/H/v37ZU5Ec2E3Wtgenei+c83XkGeyoiAzV3SUqMViijTt6zYXTIZF/Fd9mVkXZSEoSfCO9AnNYUhIwtvLX8FHV04KzaEkj68VpZYlnPehMl6vF8ePHw/7HxQkScKxY8fg8/lkTkazsRkt6OAxPyIAocYTO7krpSj+9iZNq3ax8YQSdDodnDlih/fO+P6q1/BJwxkMj8/vqJVWcFivOh08eHDBa+h0OlnWofmxLspCz9gAJqenREchEqp3dBCX7tZha9l60VGiGosp0qyhwCjONl/D9oqXREeJSg6r+HtTAJCTno0XlixHtatGdBRFuL0tKDMXiI5B33Djxo3HuvbNl9/vx82bN2VKRHOVEBcPS1omOoe4K0ix7VjDWWwqrkRaUoroKFGNxRRp1gn3ebywZDlMhkWio0QlZ474jn4z3quswkdXTmA6GBQdRXZubyvKrQWiY9A3DA4OyrJOf3+/LOvQ/PDeFMU6SZJQ7arl6Z0IYDFFmsUjfsqquL8zJboJBQCszC2FMTkNZ+5cER1FVoHJCXQOelGcZRcdhb7BaDTKsk5GRoYs69D8sD06xTq3twWjE36sy3OIjhL1WEyRJjX1tKN7pA/rC1aIjhK1LGkZiNPH4d5Qj+gooTbpa6rw4ZXjoqPI6lZPG5Zk5rKtvwqtWLECycnJC1rDYDBg+fLlMiWi+bCbuDNFse2wqwY7nZvY3CgC+L8waVK1qwZvOjYiXh8nOkrU0ul09+9NNYuOAgDYWrYed3o7cMvXJjqKbDzeFpSZ2YlSjd5///0FryFJkizr0PzZeMyPYtjE1CROuM9jh5Nd/CKBxRRpzuT0FD6uP4Nd/CGhOGdOEeq7m0THABC6VP7dla/h0JUToqPIxu1t4X0plbJYLKiqqoJOpwvr/TqdDtu3b4fZbJY5Gc2F3Wjl4F6KWTVNl7E0Ox92E+cXRgKLKdKccy3XYTNaUJhlEx0l6lVYC1XRHn3Gd1e+it80foX+sSHRUWTh8bainJ38VGvfvn0wGAxhvddgMGDfvn0yJ6K5shnNvDNFMSt0p5z/4BwpLKZIc/hDInIcKmpCAQBZqSa8XLIGv775uegoCzYdDOJWTxtKOXBatdatW4cPPvgAKSnzayuckpKCDz74AGvXrlUoGc3GZFiEoBTEUGBEdBSiiOoe7sP1zlv4VunzoqPEDBZTpCl9Y0P4utWFreUvio4SE8xpGUiOT0LHoHrmteyurMJPr57S/EDOtv57yEoxYhHnf6janj17HhRUsx350+l0DwqpPXv2RCghPYlOp7vfHl09P7uIIuHj+jN4rfR5GBKSREeJGSymSFOON5zFpuI1/AAaQaF7U+o56ldhLYTdZMFnt74WHWVB3N4WlFkKRMegOdizZw9qa2ux661dSE5Ofuzon8FgQHJyMt5++23U1taykFIJm8mC9oFu0TGIIiY0W6oGO3l6J6LYj5c0pdpViz/a8ruiY8SU0L2pJrxe9oLoKA+8V1mF//fSx9im4R1Kt7cF5SymNEOfk4bmF5Px/+z9Jf7r3/wN7FOL0N/fj4yMDCxfvhzvv/8+m02ojC3dwiYUFFOudzYCAFbllgpOEltYTJFmNHQ3Y3h8FOvynaKjxBSntQj/7dLHomM8YkvJWnzwxX+H614Tli0uFh0nLG5vC3ZXbhMdg+bgzJ2r+CfV/wYSJPyXa9XodyThk3/01zxGo3J2kwW3eu6KjkEUMdWuWuxatjnsLqQUHh7zI82odtVih3MzB9BFWIW1CA3dLappQgEA8fo4vLN6q2aH+EqSFOrkZykUHYVm8Un9WfzRkX+Hiekp6KDDgH8Y8fp4XLpbLzoazcLOWVMUQ8YmAvhN41d407FJdJSYw0+lpAmhAXTnsJOzpSIuK9WI1MRk3FXZ3YNvr3gZp5uu4MPLx/De//jnuNPbITrSnPlG+wFIsKRliI5CzzAxNYk/P/VfEZSCAAAJEoKShMngFD6/dVFwOpqNzWhBB9ujU4z4/PZFrFhcAuuiTNFRYg6LKdKE2qbLKM7O4wA6QRw5RahTUROK0Qk//tvFjzE+NY5/W/shGn1tGBkfEx1rztzdoeYTPIqhbonxCTj1B/8JLxevhf6h75UOOtQ2XRaYjOYi12jGveEeTAeDoqMQKS40NmaL6BgxicUUaUK1qxZv8YeEME5rERpUNLy3qacd//fX1ZgMTmMqOI14fRxSE8MbriqCx9fK5hMaYTSkoWPQi//49v+G/9+b/ysS4xLw+8/vwobCVao6+kqPS4pPRIYhHd3DvaKjECmqY9CLRl8btpSsER0lJrGYItXzjvThWmcjXl36nOgoMUttO1Mrcpfib773pw8KqMnpKaRpqF2+u7uZxZRG3PLdhW90AOsLVsJoSMWyxcX4hxvfwZ9X7eHOogbYTbw3RdHvaN1pbC1bj6T4RNFRYhKLKVK9j+vO4NWl65CSmCw6SsxyWIvg7m5+cHdEDdbkVeBnf2s/MgzpmAxOIS1JWztTnDGlDdWuGuxwbkScXh+aDWYuEB2J5oHt0SnaBaUgT+8IxtbopGqSJKG6rhY/fv3viY4S00yGRUhPTkNbfxcKMnNFx3kgz5SD6t//t/jT4wfQdm8Yf/bLr3B7IB4BKQHJukmUmKbw599bhtK8bNFRHxgeH4NvZABLMhaLjkKzmJyewicNZ/H/vPNjAIDb24rn85cJTkXzwZ0pinaX7jYgNdGACiu7w4rCYopU7ca9WwhKQay2lYmOEvOcOUWo776jqmIKAI6db0PN5Y34n03pkKTnoM8OHfcbBtA9MYZv/UyHjIEv8U9fSce7rzjEhgVwy9eKpeY8xOl5MEDtzjZfQ77J+uDvvNvbgr+19g3BqWg+bEYLzrdcFx2DSDGhxhOcLSUSf5uTqlW7arHLyR8SauCwFqFORU0oAOCHf1mLP768BP1Z66BLSIY+8dF7U/rEFOgSDOjPWoc/vrwEP/zLWkFJf6vB28IjfhrxcHeswOQEOga7UZKdJzYUzYvdZEU726NTlBoZH0Nt02Vsr9ggOkpMYzFFquWfHMdvGr/EDicH0KmB4/7OlFr88C9rcdK/FrrEVOj0cc98rU4fB11iKk761wovqELDeguEZqDZ9Y4O4tLderxe9gIA4FZPGwoycpEQxwMdWmIzmnlniqLWKc+XWJvnQFaqUXSUmMZiilTr81sXsSynBNZFWaKjEACHtRDu7hZVzGz56PP6B4XUfMwUVD/9ol6hZLNze1tQZlki7Pk0N8cazmJz8ZoHXSI93FHUpOxUE0YnxjA2ERAdhUh2nC2lDiymSLVmzgGTOqQnpyEr1YjW/nuio+BffT4ExIfZ3TE+Gfs/G5Q30BxNTk+hpa8DS7PzhTyf5kaSpNAR44c+pIR2FFkEa41ep4ct3YKOQZ/oKESyaunrRNtANzYUrhIdJeaxmCJV6hz0weNrxcsla0VHoYeE7k01Cc3gbvOh37Rq1qN9T6PTx6HftAqNd3tkTja7O70dsKVbYEhIivizae4aupsxOuHH2ryKB3/m9rag3MJuWVpkM1nQMdgtOgaRrI7U1eKNig08eqwCLKZIlY5wAJ0qOazi70395Bd1kLCwo4aSJOHHP3fJlGju3N5mlFsLIv5cmp/D93fF9brQr8jpYBC3etpQyp0pTbIZOWuKost0MIijdWd4xE8lWEyR6gSlII7U1fKInwo5copQL7ij3+2BeOgTUmZ/4TPoE1NwezDy/5rn8bZy6KvKjU9N4KTnwiONb9r67yEzxYhFSQv7e0di2I0WdvSjqPJl6w2YU01YamZ3UTVgMUWqc/luAwwJSXBYi0RHoW+osBbC42vFVHBaWIaAlCDLOv6gPOvMB5tPqF/N7csoNefDZrQ8+DO3jx0YtcxusnJwL0WVw2w8oSospkh1ql212MnZUqq0KCkFlrRMNPd2CsuQrJuUZR2DXp515kqSJDT6WtkRTuWe1B3L3d3MIljD2B6dosmgfwQXWm6gquJF0VHoPhZTpCqjE37UNF3Cmw4OoFMrh7UQ9d3imlCUmKYQnBxb0BrBiTGUGKdkSjQ3HYNeGBKSkZmSHtHn0tx1D/fhxr3beHXpc4/8uYc7U5pmM1rQOeiFJEmioxAt2HH3ObxYsBLpyWmio9B9LKZIVU56LmCNvQJZqSbRUegpHDnFqBN4b+on33VCt8AfXTqdDn/2vWUyJZobN4f1qt7H9afxWunzj3RblCQJ7u4Wfu80LDXRAENCMnpGB0RHIVqwb45tIPFYTJGq8IeE+jmtRWjobhb2/PJ8MzIGrkEK896WFJxGxsA1lOZly5zs2dxeHhVTM0mSHnTxe5hvtB+ABEtapphgJAu7ycJ7U6R5t3xt6BkdwAtLlouOQg9hMUWq0dp/D239XdhYtFp0FHqGcmsBGn1tmJyO7DG5h/3TV9KBqUB4b54KYN+rRnkDzUFo6CvnFKnVtc5G6HV6rMwtfeTP3d0tKLMU8A6nxrE9OkWDw64a7HBuRJyeH9/VhN8NUo0jrlpsr3iJA+hULjXRgMXpWbjT2yEsw7uvOLDVcAnSxOi83idNjGKr4RLeedmhULKnCw195c6UWh15SuMb3peKDmyPTlo3OT2FYw3nsNPJsTFqw2KKVGE6GMSRutN4i0f8NMGRI35471//4eYHBdVsR/6k4PSDQuqv/zDyv4j6xobgnww80m6b1GNsIoDfNH6FHc6Nj33Nw3b2UcHGY36kcWfuXEV+Rg4KMnNFR6FvYDFFqvBl601kp5qw1JwvOgrNgdMqfngvECqo/mJtKzJ6v4Y06Udw4tEuf8GJMUiTfsR1foG/WNsqpJACgEZfK0rNS3hUTKU+u/U1VuYufeK9qNCOIo9nap3dyFlTpG3VT7jTSerAYopUgT8ktKXCWoQ6wTtTM9552YHr/2I9qt/uQcLd/wvZvtNY5PsKlt6z2KD/Gr/c2Q1b/kfY+rxdWEZ2g1O3pzW+GRkfg29kAEsyFkc+FMkqNGuqW3QMorD0jg7gcnsDtpatFx2FnoCXU0i4ocAIzrdcxz//1u+LjkJzVG4pQFPPXUxOT6nijpskSThw+b9hUb4L/+KNSlRVPP/I11+5sw6/uvEZ/u4LbwvJ5/G1sPuSSrUPeHGrpw1bitc89rVGXytKsu287B0FrIuy0Dc2hImpSSTGJ4iOQzQvnzScw5bitUhNNIiOQk/A3xAk3PGG81hfsAJGAwfQaUVKYjJsRgtu99wVHQUA8D8uH8PVDg8A4NPGrx77+nuVVfjZtd8I60AY2pniUTE1OlpXi23lLz7xA7bb24pyK79v0SBeH4ecRVnoHPKJjkI0L5Ik8fSOyrGYIuGqXTXYxe40muPMKUJdV5PoGLhx7xb+w5mPMDE9CQC40HoTQSn4yGvKLEuQb7Li01tfRzyff3IcHUNeFGXZIv5seragFMSRutqnNr5xe1tQZmbziWhhM7IJBWlPffcd+CfHsSavQnQUegoWUyTULd9deEf7sb5gpegoNE8V1iLUCxzeO6Ol9x7Sk1Khgw5J8QkYmwjA42197HW711Th0OXjEc93q6cNBZk2VRyHpEddvFuP1MSUp95n83hbUG598tdIe2xsj04aVH1/bINex4/sasXvDAlV7arBDscm3knQIKcK2qMDwM5lm/D5P/gvWJKxGP/s1d/HP/vW38Hi9OzHXreleC16Rgdw897tiOYLDestiOgzaW5mjs48qcvi5PQUWvo6sTSbHUajhd1oYRMK0pTxqQmccJ/HTucm0VHoGfgJloSZnJ7CJw1neQ5Yo0rNS9Dc24GJqUnRURCYnEDXcA/ecGzA91a9BpNh0WOvidPr8c7qrTh0JbK7U27OKVKl4fExnG66gjccj8+WAoA7vR3ITTfDkJAU4WSkFLvJio5B3pki7fji9iWUWwqQazSLjkLPwGKKhDnXfA35JisH0GmUISEJ+Rk5uNXTJjrK/aN0ubMepXt7+cs423wN3pG+CCULHRWr4M6U6pzyXMDaPCcyU9Kf+HW3t5lFcJQJtUfnMT/SjmpXLXbyH5xVj4f4KSLcbT785Bd1uD0Qj4CUgGTdJKYnmvD7rz0nOhotQIW1CHVdd+DMKRaaw+NtQdkcCpb05FRUlb+En1/7Df5ww/cVzzUdDOKW7y5K2cRAdY64avGD53Y+9euh45ns5BdN7EYrOga6IUkSB2iT6nUP98LVdRv/dtc/ER2FZsGdKVLUR5/XY+WffInXf74I54LPwZe9AcPm5+HL3oCe7O/iL669ipV/8iU++rxedFQKg9OqjntT8zlKt7tyG35143OMT00onApo7b8Hc5oJaUkpij+L5q6lrxN3B7rxUuGqp76GxzOjT3pyKnQ6HYYCo6KjEM3qaN1pvFb6PI8aawCLKVLMD/+yFn98eQn6s9ZBl5AMfeKjHyj1iSnQJRjQn7UOf3x5CX74l7WCklK4HDnq6Ojn8bbO+ShdQWYuKiwFON5wXtlQuL9jxl0p1al21eINx4anHguVJAmNvtY57XaSduh0ulBHPzahIJULzZaqxa6njG0gdWExRYr44V/W4qR/LXSJqdDp4575Wp0+DrrEVJz0r2VBpTGl5ny09nUiMKn8Ls/TTAeDuNXTNq+jdO+tqcKhK8chSZKCyUK7Gxz6qi7TwSCO1p9+5oeUjkEfDAnJT71PRdrF9uikBdc6G6HX67Fi8VLRUWgOWEyR7D76vP5BITUfMwXVT7/gkT+tSIpPxJLMXDT2PD7XKVLa+u8hO3V+R+nWF6zA+PQkLt1V9u8ah76qz4WW67CkZaIkO++pr+ERv+gVao/OYorUrdpVg13OJ49tIPVhMUWy+1efDwHxyeG9OT4Z+z8blDcQKcppLUJ9l7h7U+EULHqdHrtXb8OHV04olCp0TINDX9Wn2lWLt2bpjuXxtnA2WJSymyzoYDFFKjY2EcCnjV/jTeeTxzaQ+rCYIlm523zoN62a9Wjf0+j0ceg3rULj3R6Zk5FSRN+bCvco3Q7nJlxpb1DsyI93pB+ADubUDEXWp/kb9I/gfMt1bCt/8Zmvc7OYilo2o5XFFKnaZ7e+xqrcUljSMkVHoTliMUWy+skv6iAhuKA1JEnCj3/ukikRKU2LO1MAkJKYjF3LNuOnV08qkOq3c4p4TEM9jjWcxUuFq5CenPbM13l8LKailc1oRvsAG1CQeh121WAXZ0tpCospktXtgXjoExbWBlqfmILbgxyBphUl2Xm4O9AF/+R4xJ8dOkrXGvZRundWb8WRulqMTQTkDYaZOUUFsq9L4auum707Vv/YEEbH/cg1miMTiiIqN92M7pE+TAWnRUchekz7QDeaeu5ic/Ea0VFoHlhMkawCUoIs6/iD8qxDykuMT0BRlh0eb0vEnx06Soewj9LZjBasyavAkTr5u0jyqJi6NPpa0Tc2iBeWLH/m6zz3W6Lrdfz1GI0S4xOQlWJE93Cv6ChEjzlSdxrbyl9CYjw/A2kJf1uQrJJ1k7KsY9DLsw5Fhqh7UzMNHhZylO69yiocunICQWlhx1O/iU0M1KXaVYMdjk2I0z/71567m538op2NHf1IhYJSEEfrannET4NYTJGsSkxTCE6OLWiN4MQYSoxTMiWiSBB1b8rja11w6/E19gokxyfifPN1mVIBw+Nj6B0bRH7GYtnWpPBNTk/hk/pz2DmHDym8LxX9bEYLOjhrilTmYlsd0pJS+PNHg1hMkax+8l0ndAv8a6XT6fBn31smUyKKhAprIeq6I19MububF/yLR6fTYXdllaxt0hu9rVianT/rLghFxpk7V1GQuRhL5lDchnamCpQPRcLYTRa0D7IJBanLYVfoTiebFmkPf9OTrMrzzcgYuAYpzMu9UnAaGQPXUJqXLXMyUlJJdh46B72KNHJ4Fo9PniYPVRUvwu1tQXNvx8JDAXD7eFRMTapdNbM2ngAA/+Q4Ooa8KM6yKx+KhLEbregY9ImOQfTA8PgYTjddxvaKDaKjUBhYTJHs/ukr6cBUmB+qpwLY96pR3kCkuIS4eJRk58EdwSYUw+Nj6BkdkOUoXVJ8Ir6z4hUckml3yt3No2Jq0Ts6gMvtDXi97IVZX3u75y4KMm1IiGM30WjG9uikNqc8F/DckmXITEkXHYXCwGKKZPfuKw5sNVyCNDE6r/dJE6PYariEd152KJSMlOSwFqE+gkf9bvnkPUr3vVWv4bj7PIYCIwtea6YjHIn3cf1ZvFyyFqmJhllfyw6MscFu4uBeUpe57p6TOrGYIkX89R9uflBQzXbkTwpOPyik/voP2cVGqxw5RaiLYBOKBq+8R+ksaZnYWLQK//PmFwtaZ3J6Cq19nVianS9TMgqXJEnz+pDikfnvFKlTVooR/skJjE74RUchQnNvBzoGfdhQuEp0FAoTiylSzF//4Wb849JLSLp3GtKkH8GJR7v8BSfGIE36kdH7Nf5ibSsLKY1z5kR2Z0qJobi7K6vw06snFzTQs6m3HblGC5ITEmVMRuGo67qD8akJVNrL5/R6t7cF5eYCZUORcDqdDjajmbtTpArVdbV4o2ID4vVxoqNQmFhMkWKaetrxUfPfICfvf+DT749ig/5rWHrPYpHvKwSbD6Ny+jQ+/f4orv+L9TzaFwWKsuzoHu7FyPjCWuPPldsrf9e15YtLkJ2agZrbl8Neg/el1KPaVYMdzs1zGsA7HQzilu8uSrkzFRNsRgva2R6dBJsKTuPjujM84qdxLKZIETfv3cbvHfrfMT41iWkpiNK8bHz0R1tw8c83wPUvnsf3X2nGH+xKY9e+KBKvj8PS7PyINKFQ8ijde2uqcOjK8bDfH5pTxA/koo1PTeCk5wJ2OjfN6fWt/feQnWrEoqQUhZORGoTao7OYIrEutNyAdVEmirPZQVTLWEyR7K51ePB3fvpnD86j+ycDCErBR17jsEb2fg1FRqTuTSl5lO7Vpc+hfbA77KJQiR0zmr/Pb19CuaUAuUbznF7vYfOJmGI3WnjMj4Rj44nowGKKZCdJoX/10+v00EEHnU6H/rHhR17jiPD9GooMZ4Q6+oU++Cqz+5MQF4/vr3odH16e/+5UUAqi0duKMjN3pkSb74cUFsGxxWa0oIPH/EigAf8wLrTcwLby9aKj0AKxmCLZrbaX4b/v/j+QHJ+Ib694BebUDExLj17od1gL4e5uwXQw+JRVSIsiVSQr0XziYd9Z8Sq+uH0JvaOD83pfx6AXqUkGZHBWiFDdw72o62rCK0vXzfk9bIseW2xGK9oHOWuKxDnWcA4bilYjPTlNdBRaIBZTpIhTni/x/JLl+NPXf4iTf/BXsKRlPvL19OQ0ZKUa0dp/T1BCUkJhpg2+kX4MBeY3Y2y+lN5FMBkW4bXS5/HLG5/O632hIq9QoVQ0V0frTuO10hdgSEia0+slSbrfFr1A2WCkGjajGZ1DvseOoBNFSmj3nF2MowGLKVJEtasGb83yQyJ0b6opQokoEuL0epRZCtDgbVbsGZIkodGn/FG63ZXb8Itrn2JyemrO73F7W3jET7DQbKlavDWPI37ekX4AOljSMhTLReqSkpiMtMQU9IwOiI5CMcjjbUW/fwjP5y8XHYVkwGKKZNfS14m2gW68NMsAOkeE7tdQZDmtRahXsAlFx6AXKYnJih+lW2rOR2FWLk55vpzze9zeFpRbC5QLRbO62uFBnF6P5YtL5vyemWG9Op1OwWSkNmyPTqIcqavBTudmxOn5MTwa8LtIsqt2hQbQJcTFP/N1jhxlP3STGErfm3JH8Cjde5VV+PDKcUiSNKfXe7ytKOPQV6FmGk/MpzDifanYZDexox9F3uT0FD6pP4edTh7xixYspkhW08EgjtafnlMXrQprITy+VkwFp2d9LWmHQ+GdKbe3OWJH6TYWVWLQP4wb927N+tq+sSH4JwOwzbEVN8lvbCKAz25dxJuOjfN6H9uixyYb26OTAKfvXEFhVi7yM3JERyGZsJgiWV1ouQ5LagaWmvNmfe2ipBRY0jLR3NsZgWQUKUsyFqPfP4xB/4gi63u8rRE7Shen1+Pdym1zapPuuX9fikfFxPm08SusspXCPM+7T2yLHpvsRiuP+VHEVbtqscu5RXQMkhGLKZJVdV3tvGa7OKyFqO9mE4poEqfXo1zBJhShJg8Fiqz9JLuWbcGF1hvoHu595ut4X0q8UOObLfN6z/D4GHpGB7EkY7EyoUi1bEYz26NTRPWMDuBKuxuvl70gOgrJiMUUyWbQP4ILLTdQVfHinN/jyClGHe9NRZ1Qp0b5v68ijtItSkrBGxUb8bNrp575Ok+Eizx6VPtAN5p627GpqHJe72v0tmKpOY8XwWOQ3WRFO4/5UQR9Un8GL5esRUpisugoJCP+9iDZHHefw4sFK+c1gM5pLUJDt3JttEkMR04h6hVoey/qKN27lVvx6xtfIDA58dTX8KiYWNWuWmwrfwmJ8Qnzep/bx/tSscqSlolB/wjGp57+3zWRXCRJwuF5jm0gbWAxRbKpds3viB8AlFsL0Ohrm9csH1I/pdree7ytQgqWJRmLsWxxMY41nH3i18cmArg31IOiLFuEkxEABKUgjtadDmsAprubRXCsitPrkZOehc5Bn+goFANcXU2YmJpApb1cdBSSGYspksUtXxt6xwbwwpL5DaBLTTRgcXoW7vR2KJSMRMjPyMFQYBT9Y0OyrusRuIvwrDbpt3vvoiAzd9ZxAKSMi211SE9ORYV1/i3zPb5W7kzFMJvRwqN+FBHVrhrsXLaZTYqiEIspksVhVw12ODaFde9A6blEFHl6nR4V1iLUy3yEU+QuwgtLliMoSfj6bt1jX3N386iYSIddtWHtSk1OT6G1rxMl2bN3H6XoZDda0D7AJhSkrMDkBE56LnC2VJRiMUULNjk9hWMN57AzjA8zQOjeFIf3Rp9Qp0b5vq/+yXF0DvmEHaXT6XTYXbkNh57QJt3jE3P8kELd+M7cuYLtFRvm/d6m3nbkGi0wJCQpkIy0wG60ooPH/EhhXzRdgsNahMXp2aKjkAJYTNGCnblzFfkZOWG3Fq6wFqGOO1NRx5Ejb0e/Wz1two/SvenYiOudjbg70PXIn7u7m7kzJchJ93k8l78MGSnp835vaFhvZAZAkzqF2qPzmB8pq9pVE9buOWkDiylasIX+kCi3FKCp5y6bUEQZZ04RGmQskj1e8XdbDAlJ2LVsC3569eSDP5sKTuN2TztKzfkCk8Wu6jCP+AH3Z4OxCI5pdpMVHZw1RQrqGupBXVcTXil5TnQUUgiLKVqQ3tEBXG5vwNay9WGvkZKYDJvRgts9d2VMRqLZjVaMTgTQOzogy3pqaT3+zuqtOFp3BqMTfgBAa989WNIykJaUIjhZ7LnT24HOIR9eKlwV1vtFdYck9bAZLWgf8D6xsQyRHI7Wn8HrZeuRnJAoOgophMUULcjH9WexpXgtUhMNC1rHySYUUUen092/NyVPEwqPSnYRFqdn47l8J6pdtQBCHQbLeFRMiGpXDd50bES8Pm7e7w1KwQdzyyh2pSenIj4uDgP+YdFRKApJkoQjC9g9J21gMUVhkyQJR+rk+SFRYZX3fg2pg1z3pqaDQdzy3VXNUbrdlVX46OoJBKUgO/kJMhWcxif1Z8PujtU56ENqkiGsu1YUXdgenZRytcONeH0clueUiI5CCmIxRWGr774D/+Q41uRVLHgt7kxFJ6dVnntTrf33YE4zqeYo3WpbGVITDTh75xo7+Qlyvvk6rIsyUZxtD+v9bm8LyswF8oYiTbKzmCKFhMY2bOFsqSjHYorCVu2qxU7nZuh1C/9rVGpegubeDkxMTcqQjNTCkSNPp0a3V13d8nQ63YMhvmxiIEao8c2WsN/P7xvNsBkt6GQxRTIbmwjg81tf4w3H/Mc2kLawmKKwjE9N4IT7PHY6N8myniEhCfkZObjV0ybLeqQOuelmTExNwjvSt6B11NgoYGvZejT6WiFJErJTTaLjxJT+sSF82XoT28pfDHsNtTQ0IfHsJivaB1hMkbx+0/glVtnKYE7LEB2FFMZiisLyxe1LKLcUINdolm1N3puKPjqdDo6cogU3oVDjLkJifAKey1+G5PhEHuGIsGPuc9hYtBrpyalhr6GGVvukDqFZU2yPTvKqdtXirQXsnpN2sJiisFTfPwcsJ6eV96aikdNahIYFFMmSJIW6rqmwY17Ooiz0+4cx6B8RHSWmHFngz5++sSH4JwOwyfiPQaRddiN3pkhedwe6cKe3HZuL14iOQhHAYormrXu4F66u23hl6TpZ15VjB4PUZ6H3prwj/dDp9DCnqu+oxN2BbjhzivHrm5+LjhIzPN5WDPiH8Vz+sgWsEWqJzh1FAkLjDnyj/RwcT7I54jqNqoqXkBAXLzoKRQCLKZq3o3Wn8Vrp8zAkJMm6bqk5H619nQhMTsi6LonlsBahvutO2EMx3d5mlFnU+cHX7W3B766pws+unsJUcFp0nJhQ7arBDucmxOnD//XF+1L0sIS4eJhTTege7hUdhaJAUAriaN1p2U/vkHqxmKJ5kSRJkSN+AJAUn4glmblo7GmVfW0SJ2dRFoKSFHYTCrXebRkKjKJvbBAvl6yDNT0LX9y6KDpS1JucnsKxhnMLnm2nlgHQpB65bI9OMvm6rQ7phjT+jIkhLKZoXq52eKDX67Fi8VJF1nfe38Wg6KHT6e7PEQvvCKdadxEafa0oNecjTq9/0CadlFXbdAVFWTbkmXIWtI4au0OSWHajBe0DbEJBCxca27Cwf/AhbWExRfNS7arBLudmxY5c8d5UdHJYi1DX1RTWez3eFlSo8IOv56Ghr68sXYd7Qz1o4N9dRcnxIcU/OY7OIR+KsmwypaJoYDdZ0THoEx2DNG4oMIozd65ie/lLoqNQBLGYojkbmwjgs1sX8aZzo2LPcFgLuTMVhRw54e04Do+PoXdscME7EUpwe1tQbi0AAMTr4/D9Va/jw8vcnVJKz+gArna48VrpCwta51ZPGwoyc3kxnB7B9ugkh5OeC3g+fxkyUtJFR6EIYjFFc/bZra+xKrcUlrRMxZ6xNDsfdwe64J8cV+wZFHmO+23v59uEotHbiqXZ+QtqNqAUj7f1wc4UAHxnxauoabqM3tEBYZmi2cd1Z/ByyTqkJCYvaB13tzqPjZJYdqMVHWyPTgsU2j3fIjoGRZj6PqGQah2OwDngxPgEFGXZ4fG2KPociixLWgbi9HHomme3LLe3WZWXeCemJtHafw8l2XkP/sxoSMPrZS/gF9c/FZgsOoUa39TIMgDT41NnQxMSy8YGFLRAd3o70DXUixcLV4qOQhHGYormpH2gG009dyMygI73pqKPTqe7f29qfkf93N5WVQ7rbepth81oQXJC4iN/vrtyG35x/VNMTE0KShadbnbdxmRwCpX28gWv5e5uRrkK/06RWJkp6ZiYnsTw+JjoKKRR1a4avOHYgHh9nOgoFGEspmhOjtSdxrbyl5AYn6D4s3hvKjo5rIWo755fE4pQC+tChRKF72nd4Eqy81CSnYeTnguRDxXFql212ClD45up4DRu97Sj1Mxiih6l0+lgM1rQwd0pCsNUcBof15/hEb8YxWKKZhUaQFcbsVafDmsR6rpZTEUbR878dqYmp6ceO0qnFu5nzCnaXbkNh66cCHtIMT0qMDmBU54L2OnctOC1WvvuwZxmQlpSigzJKNqE2qOzmKL5O998HYvTs9klNEaxmKJZXWyrw6KkVFRYI7NDUJKdh85BH8YmAhF5HkWGw1qEhu7mORcZTztKpwYeX8tTj4ptLFqNkfExXOtsjHCq6PTF7YtwWIuQk5694LVC37eChYeiqGQ3cWeKwsPGE7GNxRTN6rCrFjsjOIAuIS4eJdl2uNmEIqqY0zKQGJ8w51kuau26FpSCaHzG0Fe9To93KrfiENuky+KwTI0nAPX+nSJ1sBmtLKZo3vrHhvBVmwvbyl8UHYUEYTFFzzQ8PobTTZexvWJDRJ8700qbootzHt9Xte4idAx6kZaUApNh0VNfs8u5GV+23UTXUE8Ek0WfmUHIL5esk2U9dvKjZ7EZzWgf4Kwpmp9j7nPYWLQai3h8OGaxmKJnOuk+j+eWLENmhAfQzfd+DWlD6Ps6tyYUoXtJ6msU4O6evchLS0rBDscm/PTaqciEilJH607j9bIXZDnqKUkSPN4WVXaHJHWwG61sj07zVu2q5RG/GMdiip5J1A8JZ04RGrgzFXWc9+9NzWa2o3QieXxzy/Vu5VYcvvkFB1CHSZIkHKmT7+ePd6QPgA7m1AxZ1qPok2s0495QD4JSUHQU0gi3twVD/hE8l+8UHYUEYjFFT9Xc24HOIR82FK6K+LOLsuzoGu7FCGd+RJUKa2iG2GxNKOZylE6UuexMAUCeKQcrckvxSf0Z5UNFoSvtbiTEJWBZTrEs67m9LSi3Fiy4vTpFL0NCEtKTU+Eb6RcdhTSi2lWDHc5N0Ov4cTqW8btPT1VdV4s3KsQMoIvXx2Fpdj6bUESZrFQjUhOTcXeWewlPm+OkBm7f3I+Kvcc26WE77KrBLhlmS81we1tQxvlSNAu2R6e5mpyewvGGcxEbG0PqxWKKnmgqOI2P68QOoOO9qejkyJl9jtiz5jiJ1Ds6iMDkBHLTzXN6/XP5y6DT6fBVm0vhZNFlbCKAL25fxJvOjbKt6fG2ojxC4x1Iu2wmC9oH2YSCZlfbdBnFWXbYTVbRUUgwFlP0RBdabsC6KBPF2XZhGUL3a1hMRRuntQgNsxTJbpU2CvDc35Wa626JTqfD7spt+JBt0ufllOdLrLaVIzvVJNuabm8LyrkzRbOwG61zHt9Ase0wZ0vRfSym6InUMIBuLjsYpD0VVu3uTHm882+tvb1iA27eu4W2/i5lQkUhORtPAMBQYBR9Y4PIz1gs25oUnWxGM3emaFa+kX5c6/DgW6XPi45CKsBiih4z4B/Gl603hQ+gK8y0wTfSj6HAqNAcJC+HtRDu7uandsya71G6SAqnyDMkJOHt5a/go6snlAkVZe4OdOFObwc2F1fKtmajrxVLs/MRp+evPHo2u9GKDt6Zoll8Un8Wryx9DimJyaKjkArwNws95ljDOWwoXIX05FShOeL0epRZCtDgnb2VNmlHRko60pPTnrpT0+hrnddRukgKd07R91e9ho/rz7A75RxUu2qxveIlJMTFy7amR6U7naQ+dpOFx/zomSRJQrWrBm+x8QTdx2KKHlPtqsFOlfyQCN2vYTEVbZw5Rah/ylE/tQ7rHZsI4N5QDwozbfN+b056Nl5YshzVrhr5g0WR6WAQR+tOy37EWK138Eh9zGkZGAyMcD4cPdXNrtuYCk5jta1cdBRSCRZT9AiPtxX9/iE8n79cdBQAQIW1EHXdTaJjkMwqrE/v1BjaRVBf17XbPXdRmGULe8fkvcoqfHT1JKaDHAj6NF+3uWAyLJK98AnddVPf3ylSH71Oj8Xp2ejk7hQ9RbWrFjuXyTe2gbSPxRQ9otpVg53Ozaq5W+DMKUY926NHndl2ptS4i+D2Ni/oqNjK3FKkJ6XiTPNV+UJFGSUa30xOT6GlvxMl2XmyrkvRy25ke3R6ssDkBE55LmCHQ76xDaR96vjETKowOT2FYw3nsNOpjiN+ALAkYzH6/cMY9I+IjkIyclgL4fG2PrZLs5CjdEpze1sXNPRVp9Nh95oqHGKb9CcaCozibPM1bK94SdZ1b/fchc1oRXJCoqzrUvSym9genZ7s89tfw5lTjJz0bNFRSEVYTNEDp+9cQWFWLvIzckRHeSBOr0c5m1BEnfTkNGSmpKO1/94jf77Qo3RKcntbFjz0dWvZejT1tuOWr02mVNHjhPs8XliyHCbDIlnXDaedPcU2m9GMDu5M0RNUu+Qd20DRgcUUPVDtqsUu5xbRMR5TYS186v0a0q7Q9/XR+3Bub8uCdn+UMhWcRlNPO0rN+QtaJyEuHt9d+RoOXWGb9G+aOWIsN7U2NCH1shmtaGd7dPqGe0M9aOhuxisla0VHIZVhMUUAgJ7RAVxpd+P1shdER3mMM6cI9V1sQhFtnNbix+5NqXVYb0tfJyyLMpCaaFjwWt9d+Sp+0/gV+seGZEgWHZp62tE93IcXC1fKvrbHp86/U6RedpMF7YMspuhRR+pqsbVsPZLieWSYHsViigAAn9Sfwcsla1U5gM5hLUJ9N4/5RRtHzuPf19AcpwIxgZ7B421FublAlrWyUk14uWQNfn3zc1nWiwZH6mrxhmMD4vVxsq4blIJo9Laq8u8UqZfNaEHHoBeSJImOQiohSRKO8IgfPQWLKYIkSTjsqsVbKv0hkZ+Rg6HACP8lP8pUWAvh8bZgKjgNIHSU7nZPuyo7+Xm8LSi3Fsi23u7KKvz06ilMTk/JtqZWTQWn8XH9GUV+/nQMepGWlCL7PSyKbouSUpAYl4A+/s6h+660u5EYnwhnTpHoKKRCLKYIrq4mTE5PotKuzgF0ep0e5dZC7k5FmUVJKTCnZaC5txMA0Np3D5Y0eY7SyU3uu1wV1kLYTRZ8dutr2dbUqnPN15CbbkZhlvwdHN3d6tzpJPWz39+dIgKAw64avMXZUvQULKbowcVvNf+QcFqfPpeItCv0fQ3dh1Pr3RZJkuDxyX9U7L3KKhy6wjbpoe5Yyoxj8PjYyY/CYzOxmKKQsYkAvrh9CW9wthQ9BYupGBeYnMBJzwXscG4SHeWZHM8Y8kra5cgpfrDjGNpFUN8Rv+7hXsTp9DCnZci67paStfAO98N1L3abq/SPDeHrNhe2lr+oyPpq/TtF6mc3WtmEggAApzxfotJejuxUk+gopFIspmLcF7cvwmEtwmKVD6ALdfRjMRVtnNbffl+V2P2Rg1uhXPH6OLyzeis+jOHdqWMNZ7GxqBKLklIUWd+t0t1OUj+b0Yz2Ac6aIqC6rkax3XOKDiymYtxhlzZ+SNiNVoxOBNA7OiA6Csmo3FqARl8bJqYmVdsW3d2tXK5vr3gZZ+5chW+kX5H11a7aVYu3FPr50zs6iMDkOHLTzYqsT9HNbuLOFAFt/V1o7u3EpqJK0VFIxVhMxbB7Qz2o776DV0qeEx1lVjqdDg42oYg6qYkGLE7PwqX2euh1elUeo/D4lDsqlp6chm3l6/Hza79RZH01a+huxvD4KNblOxVZ3+MLNQ1R811QUi+70YJOFlMxLzS24SUkxMWLjkIqxmIqhn1cfwavl61HcoI2BtDx3lR0cuQU4XTTVZRbClT5wVfJnSkg1Cb9lzc+w/jUhGLPUKNqVy12ODdDr1Pm15DH2yprO3uKLdZFWfCNDnB8QQybDgZxpI6zpWh2LKZi1G8H0Kn/iN+Mh+/XUPRwWotw494tVTYKGAqMYsA/jPyMHMWeUZRlQ5llCU64zyv2DLWZmJrECfc57FSw8U2onX2BYutTdEuIi4c5NQP3hnpERyFBvmq7icwUI0plHItB0YnFVIy62uFGvD4Oy3NKREeZswprEeq4MxV1KqxFaOvvUuV9KY+3BaXmfMV2T2a8V1mFD6+cgCRJij5HLU7fuYLiLDvsJqtiz5B70DLFHrvJgvZBNqGIVUdctdjl1M4/OJM4LKZi1GFXaOtajceqnsZmNGNiajJmL+tHq3JLAUbGR1GcZRcd5TGR6jD4UuFKBCbHcaXdrfiz1CDU+GaLYuuPTQRwb6gHhZnyDwKm2GE3WtEx6BMdgwQYCozibPM1bK/YIDoKaQCLqRg0NhHA57cu4k2ntgbQ6XQ63puKQlPBaQA6TKjwboInQh0G9To93o2RNum+kX5c62jEt0qfV+wZt3vuojDLxkvjtCBsjx67TrjPY/2SFTAa0kRHIQ1gMRWDftP4JVbbylTZOW02Dmsh701FmUZfK0yGNLi96uvU6PZGbujrzmWbceluPTqivIPYx/Vn8OrSdUhJTFbsGW5vM8p4z4EWyGayRv1/j/Rk1a4a7NTQnXISi8VUDKp2abc7jcNazHtTUcbjbUFBpg11KiuSJ6Ym0dbfhZLsvIg8LzXRgB3OTfjZ1VMReZ4IkiShWuEjfgDg9raq8g4eaYvdaOGsqRjU1NOO7pE+rC9YIToKaQSLqRhzd6ALd3rbsblYmwPonDmhjn6xclE/Fri9LVhlK1Xd8c2m3nbYTVYkxUdudMC7q7ehuq4WYxOBiD0zkm7eu41pKYjVtjJFnxPaUSxQ9BkU/exGC3emYlC1qwZvOjYiXh8nOgppBIupGFPtqkVVhXYH0OUsykJQkuBlE4qo4fG2YmPhajT3dmBialJ0nAciecRvht1kwWpbOT6uPx3R50bKYVcNdjk3K9r4Zio4jaaedlW22idtMRkWYWp6GkOBEdFRKEImp6fwScNZvKXR0zskBoupGDIdDOJo3WnNHvED7jehsBaqbheDwjMxNYnW/ntw5hQjPyMHt3raREd6wO1tQbmlMOLPfa9yGw5dOYGgFIz4s5XknxzHbxq/xA4FZ0sBQEtfJyxpGUhNNCj6HIp+Op0OdpOFHf1iyLmW67AZzSjIzBUdhTSExVQM+brNBaNhkebvEjhyilDX1SQ6BsmgqbcdNqMFyQmJoTliKro35RGwMwUAa/McSIiLx4WWmxF/tpI+v3URy3JKYF2UpehzPN5W7kqRbGxGNqGIJZG400nRh8VUDDlSV4tdUdCdxplTjIZu9XV+o/lzPzRY1WlVT9v7oBREo68N5eaCiD9bp9Nhd2UVDkVZm/TQhxTlf/5Eqp09xQa70YL2ARZTsaBvbAgX2+qwtWy96CikMSymYsRQYBRn7lzF9vKXREdZMMf9HQw2odA+j7cVZfcLltAMMXUUye0DXqQnpQqbMbK94iXUdzejpa9TyPPl1jnog9vbgpdL1ir+LDafIDnZjGa0D3LWVCw41nAWm4orkZaUIjoKaQyLqRhx0nMBz+cvQ0ZKuugoC2ZJy4Bep0PXcK/oKLRAbm/zg52pUnM+Wvs6EZicEBsK93c37ucSISk+Ed9Z8QoOXTkhLIOcjtafxtay9Yp3RpQkCR4f26KTfOwmK9ujx4gjGh4bQ2KxmIoR0XQOWKfT3b83pY4jYRSebx6lS4pPxJLMXDT2tIoNhvu7G4KHvn5v1Ws47j6HocCo0BwLFZSCEfuQ0j3cC71Or8mB5KRObI8eGxq6mzE8PoZ1eQ7RUUiDWEzFgDu9Hega6sWLhStFR5GN01qEBpXcr6HwPOkondMamiMmmsfbinJr5Dv5PcySlomXClbisKtGaI6FutLuRlJ8Ipw5RYo/y31/V0rJ1usUW3KNZnQN9WI6GF3dNelR1a5a7HRugl7Hj8U0f/xbEwOqXTV4w7EhqgbQOXKKUMdiStOe1C1PLfem1LAzBQC711ThoysnNP1BbmZXPBIFjrtbTAdGil5J8YkwGtLgHekTHYUUMjE1iRPuc9jh1H6DLhKDxVSUmwpO4+P6M1FzxG+G4/4OBptQaJf7CV3XHNZC4TtTvaMDGJ+ewOL0bKE5AGDF4qXISjWitumy6ChhGZ3w44vbl/CmY0NEnufxsZMfyS/U0Y9NKKJVbdNlFGfnwW6yiI5CGsViKsqda76GxenZKMqyiY4iK3NaBhLjEzhMUcNC84AKHvmzpdn5uDvQBf/kuJhQANz3Owyq5ajYe5VV+FCjbdJPeb7EGnsFsiJ0h8ndzWKK5Gc3Wvm7JopVu2rxVpT9gzNFFoupKFcdxd1peG9K29y+x49kJcYnoCjLDo+3RUwoiBvW+zTfKn0erf330OgT35hjviLZ+GYoMIp+/xDyTDkReR7FDrZHj17ekT5c62zEq0ufEx2FNIzFVBTrHxvCV603sa38RdFRFMF7U9rVOzqIwOQEctPNj31N9L2pJx0/FCkhLh7fX/U6Prysrd2p1v57aO3vwsai1RF5nsfbglJzPuL0/LVG8rKbrOzoF6U+rjuDb5U+h5TEZNFRSMP4WyeKzQygWxSlA+gcKun8RvPnub8r9aSjdKLvTalxTtF3VryKz25dRN/YkOgoc3bEVYvtFS8hIS4+Is8Lfd/EdmCk6GRje/SoJEkSquui9/QORQ6LqShWXXc6qn9IOKyFqO9uZhMKDXrW3RaHVdyO49hEAF1DPSjIzBXy/KfJTEnHq0vX4Vc3PhMdZU6mg0EcqTsd0XsIajueSdHDbrKgfYDFVLS5ce8WJEnCqtxS0VFI41hMRSm3twVD/hE8l+8UHUUxWakmpCYm8yy7Bj1r96ckOw+dg16MTQQiGwrArZ42FGXZI7abMh/vranCz66dwuT0lOgos/qq7SayU01Yas6P2DND7ewLIvY8ih3ZqSaMTIwJ+ZlEygndKd+smmZDpF0spqJUtasGO2JgAF2FtQh1POqnOc+6l5QQF4+S7Dy4BTSh8KjsvtTDSs1LsCRjMT5t/Ep0lFnNDMCMlImpSbT230NJdl7EnkmxQ6/TIzfdzI5+UcQ/OY7fNH6JNx2R+zlF0Su6P2nHqMnpKRxvOIddy6J/AJ0zh/emtGYuR+kc1iLUCzjq51b5UTEttEkfCozgXPM1bK+IzGwpAGjqbYfdaEVyQmLEnkmxxW60omOIR/2ixee3LmJ5TgmsizJFR6EowGIqCtU2XUZxlh12k1V0FMWJvF9D4ZnLUTpHjpgdR7dXfc0nHra5eA36xoZw494t0VGe6oT7PNYvWQGjIS1iz3R7W1BuLYjY8yj22EwWdHBwb9SI5NgGin4spqLQ4Rj6IeGwFsLd3YygFBQdheZoLo0CnDmR35maCk6jqacdpWb17kzF6fV4Z/VWHFJxm/TD9+8hRBLvS5HSbEYL2tnRLyp0Dvrg8bViS8ka0VEoSrCYijK+kX5c62jEt0qfFx0lIjJS0pGenIq2/i7RUWiOQh98n12wFGXZ0T3ci5HxsQilAlr6OmFdlKn6eSNvLduCcy3X0T3cJzrKY2733IV3pA/rC1ZG9Lke7kyRwuxGdvSLFkfqTmNr2XokxfNYMMmDxVSU+bj+DF5duk71HwjlJOp+DYXH7W1FufXZ84Di9XFYmp0f0SYUar8vNSM9ORVV5S/hF9d/IzrKY6pdNdjh2BTRwblBKYhGXxvKuTNFCrKbOGsqGgSlII7URX73nKIbi6koIknS/XPAsfVDwpFTjPquZtExaA5+e5Ru9pbZkb43Ferkp42hr7srt+FXNz7H+NSE6CgPTE5P4ZP6sxH/+dM+4EV6UmpE72hR7JkZ3Mu5htp2+W4DDAlJcFiLREehKMJiKorcvHcb08EgVtvKRUeJKBH3ayg8LX2dsCzKQGqiYdbXOq1FaIjg9zXUrl39O1MAUJCZC4e1EMcazomO8sC55mvIM1kjPvBYKzuKpG2piQYYEpLQOzYoOgotQGi21BbOliJZsZiKIoddNdgZgwPoKiyFaOhuxnSQTSjUzuNtnfNxLEdO5Do1SpIEj7cVZSru5PdNuyurcOjKcdX8S/nh+x9SIk3Ns8EoutiMFrSzo59mjU74UdN0CW9EcGwDxQYWU1FiZgDdDsdG0VEizmhIQ2ZKOlr774mOQrNwe5vn3CigMNMG30g/hgKjyoYC0DXci4S4eGSnmhR/llxeLFiByekpXLpbLzoK+saGcOluHV4veyHiz9ZaEUzaZTdZObhXw055vsTaPAeyUo2io1CUYTEVJb64fRHOnGLkpGeLjiKEg0f9NMHjbZ21k9+MOL0eZZYCNHiVvw/nmUOHQbXR6XTYXbkNH145IToKjjWcxebiNUhLSon4s3nMjyLFZjSjfZA7U1rF2VKkFBZTUaJa0BEbtXBai1EvYMgrzZ0kSfeHq869yYPTWoSGCDQXCXUYLFD8OXJ707EJVzvcQls2/7bxzZaIP7t3dACBqQnkppsj/myKPXajle3RNaq1/x7a+ruwoXCV6CgUhVhMRYF7Qz1o6G7GKyVrRUcRpiKnMGL3ayg83cO9iNfHzesoXejeVJNyoe7T6tDXlMRk7HJuxk+vnhSWwe1twci4H2vzKgQ8uxVlliUxd0+UxLCZLOhke3RNOuKqxfaKDUiIixcdhaIQi6kocKSuNuYH0FVYCuHxtrAJhYq5w2gU4LAWRWTHUctDX99ZvRVH6moxNhEQ8vzDrhrsdG6CXhf5XydsPkGRZDda0M5iSnOmg0EcqTsd06d3SFkspjQuKAVxJMaP+AGhQabmtAw093WIjkJP4Q6jUcCSjMXo9w9j0D+iTCgAQ4ERDAZGkGeyKvYMJeUazVib58CRutqIP3tiahIn3Oexwylmtl04BTpRuKyLstA7NoiJqUnRUWgevmy9CXOqCUvNeaKjUJRiMaVxV9rdSIpPhDOHA+icEdrFoPCE0yggTq9HucJNKDzeViw15wvZWZHLe5VVOHTlBIJSZHdma5ouY2l2PuwmS0SfO8Pja2UxRRETr4+DNS0TnUPs6Kcl1ffHxhApRbufHgjAb7vT8M4AUGGN3Fwimr9wj2Q5rEWoU7BIdmuwk983VdrLkZyQhPPN1yP63NDPHzEfUsYmAuga6on4kGCKbWyPri1DgRGcb7mOqvKXREehKMZiSsNGJ/z44vYlvOngADoAcOZwZ0qthgKjGPAPIz8jZ97vdeQUor5LuSYUHo128nuYTqfDexFuk9493IfrnbfwrdLnI/bMh93qaUNRlp0XyimibEYzOtgeXTOON5zH+oIVMBrSREehKMbfQhp2yvMlKu0VyNLQoFEllVsK0Ohrw1RwGvH6ONFx6CEebwtKwzxK57AW4T+e+akCqULc3hbsrtym2PqRsq38RfyH0x+hubcDhVk2xZ/3cf0ZvFb6PAwJSYo/60nc3ZwvRZFnY3t01fJ6vTh48CBu3LiBwcFBGI1GDKRO4R//g38oOhpFORZTGlbtqsHvrX1DdAzVSEtKQU56Fu70tqNU48e2oo3HN//mEzPyM3IwFBhF/9gQMlLSZc01PjWBtoF7KM62y7quCEnxifjOildx6MoJ/PPXfl/RZ0mShCN1tfizrX+g6HOexeNj8wmKPLvRgjoFd8pp/i5evIj9+/fj+PHjAIBA4LedTQ0GAz77f6tRVVWFffv2Yd26daJiUhTjMT+Nau2/h5a+e9hUVCk6iqoofb+GwuPuDv+Dr16nR4W1CPXd8jehaOppR75pcdSMFfjeqtdw3H0eQwHluh8CwI17twAAK3NLFX3Os4TTHZJooewmCzrYHl01Dhw4gC1btuDw4cMIBAKPFFIA4Pf7EQgEcPjwYWzZsgUHDhwQlJSiGYspjTpadxpvOF7ifYFv4L0pdfL4FnYky2EtRL0CzUXcC8ylNua0DGwsWo3/efMLRZ9T7arBTudmYY1vpoLTaOppR6k5X8jzKXbZjBa0D3RDkiTRUWLegQMHsHfvXoyNjc36/ZAkCWNjY9i7dy8LKpIdiykNCg2g42ypJ3FYixT50E3hm5iaRGv/PZRkhz/jw5GjzI6jxxt9rbXfq6zCT6+exFRwWpH1/ZPj+E3jV3jTsVGR9eeipa8TlkUZSE00CMtAscmYHGpkMBQYFZwktl28ePFBITUfMwXVpUuXFEpGsYjFlAZ91XYTmSlG3gt6gnJLAW733MXk9JToKHRfU2878kw5CzpK58wpQoMSO1Pelqg7KrZscTHMaRmouX1ZkfU/u/U1lueUwLooU5H158LtbUG5uUDY8yl26XQ62ExWHvUTbP/+/fD7/WG91+/3Y//+/TInoljGYkqDql212OXkALonSUlMRq7Rgts9d0VHofsavM0LPkpnN1oxOhFA7+iAPKEABKUgbvnaUB5Fx/xm7K6swqErxxVZe2a2nUgeb4vm29mTdtmNFrSzmBLG6/Xi+PHjYR+1lCQJx44dg8/HeWEkDxZTGjMUGMG55mvYXsHZUk/jtBahQYFmBRSe0FG6wgWtodPp7t+bku/7enegG8bkVKQnR9/8kVeXPof2wW64vS2yrtsx6EWjrw1bStbIuu58RcOgZdIum9GM9gHOmhLl4MGDC15Dp9PJsg4RwGJKc064z2P9Eg6gexZHThHqeG9KNUJH6Rb+wVfue1MebyvKFljkqVVCXDy+v+p1fHhZ3t2po3WnsbVsvdDuh5Ik3R+0HJ3fO1I/u9HKnSmBbty48VjXvvny+/24efOmTIko1rGY0pjDrlrsWsYjfs/isBayo59KPDhKJ8P9ltCOo3zfV7e3OSqP+M34zopX8cXtS+gdHZRlvaAURLWrFm8JPuLXNdyLeH0csjmsnARhe3SxBgfl+ZnW398vyzpELKY05HbPXXhH+rC+YKXoKKpWZinAnd52TExNio4S89oHvEhPSpVlJ1XuHcdo7OT3MJNhEV4rfR6/vPGpLOtdutuA1EQDKgTvCHm8HNZLYtmMLKZEMhqNsqyTkZEhyzpELKY0pNpVgx2OTYjT89v2LIaEJOSZctiEQgXcMjYKyE03Y2JqEt6RPlnWi8ZOft+0u3IbfnHtU1m6Wx65vysuarbUjFj4vpG65aab0TXcq9j4AXq2FStWIDk5eUFrGAwGLF++XKZEFOv4qVwjJqen8En9WR7xmyPem1IHj4yNAnQ6HRw5RbI0oegZHcDk9BRyFmXJkEy9lprzUZiVi1OeLxe0zuiEHzVNl/GGwNlSM9xRvqNI6pcYn4DMlHR0D/eKjhKT3n///QWvIUmSLOsQASymNONc8zXYTRYUZOaKjqIJvDelDqGdKfmOhTmtRWiQ4fvqud8UQ/QuSyS8V1mFD6+E30YYAE56LmBtngOZKekyJguPR4ZW+0QLZTda0THI1toiWCwWVFVVhf3zW6fTYfv27TCbzTIno1jFYkojqutqhc920RLuTKmDx9sqawtrub6vbm8rymJk6OvGokoM+odx496tsNcINZ4Qvys+FBjBgH8E+Rk5oqNQjLMZzWgfZHt0Ufbt2weDwRDWew0GA/bt2ydzIoplLKY0oG9sCBfb6rC1bL3oKJpRmr0ErX2dGJ+aEB0lZvWODmB8egKL07NlW9NhLUJ9150F7bIAsTX0NU6vx7uV28Juk97S14m7/V14qXCVvMHC4PG2otScD72Ov7pILJvRio4BNqEQZd26dfjggw+QkpIyr/elpKTggw8+wNq1axVKRrGIv5E04FjDWWwqrkRa0vx+aMSy5IRELMnMRaOvTXSUmDWz+yPnUbqcRVkIStKCm1CEhr4WyBNKA3Yt24ILrTfCuuNxpK4Wbzg2ICEuXoFk88PmE6QWdpOFs6YE27Nnz4OCarbfMzqd7kEhtWfPngglpFjBYkrlJElCtauGR/zCwHtTYsk1rPdhOp0OzgU2oRibCKB7uA+FWbFz/3BRUgreqNiIn107Na/3TQeDOFp3BjudW5QJNk/R3s6etMPO9uiqsGfPHvzRf/pz2NeUIjk5+bGjfwaDAcnJyXj77bdRW1vLQooUIf6fGumZ3N4WjIz7sS7PITqK5jisRXB1NYmOEbM83hZsLFot+7oV1kLUdTXh5ZLwjmk0+lpRnGVDvD5O5mTq9m7lVvztQz/G33vhO0hOSJzTe75svQFzqglLzXkKp5sbt7cF71ZuFR2DCDajBe085ifcR1dO4ojvEvJ+bz0uv3sGBw8exM2bN9Hf34+MjAwsX74c77//PptNkKJYTKncYVcNdjo38Y5AGJw5RfjF9d+IjhGz3N4W/PCFt2Vf15lTjF9cC//76vG2xsx9qYctyViMZYuLcazhLL694pU5veewinbFx6cm0DZwDyXZ6ijsKLZlp5rgnwxgbCKAlMSFzTyi+ZMkCQfO/xIHLx6FBAmT01Mwm8340Y9+JDoaxSB+QlexialJnHCfxw6n+C5aWrQ0Ox9t/V3wT46LjhJzQkfpehVp5e+wFqG+O/wmFLF2X+phM23S3d0t+PenDz2zQcugfwQXWm6gquLFCCZ8uqaeduSZcpAUP7ddNSIl6XQ65PKonzBH607jv1z41YOfYVPBaf6uJ2FYTKlYTdNlLM3Oh91kER1FkxLjE1CYZUOjr1V0lJjT6GtFUZZdkaYFlrQMxOnj0BXmwMxY6uT3sOlgEGMTAbT1d+F3D/0JDn59FCPjY099/Qn3ebxYsBLpyWkRTPl0bl8L70uRqtiNbEIhypaStfgnm38XiXEJSIyLhwTAN9IvOhbFKBZTKhZqPMFdqYVwWItQxyYUEadkowCdTnf/3tT8v6+T01No6u3A0ux8BZKp269vfIZ/cuTfYmJ6EpPTU9DrdEhNfHqHULU1vnF3s5MfqUvo3hRnTYmQnpyKV5c+B0NCEv7me3+Kv73uTWSoYKg4xSYWUyrVPdyH65238OrS50RH0TRnThEaOLw34jw++Tv5PcxpLUJ99/ybi7T03UNOelZM3nF4e8UreGvZFiTfPyYXlCQkxSc88bW3fHfRMzaAF5Ysj2TEZ/L42MmP1IXt0cU6WleLqoqXsNJWiv91024s4vgYEoTFlEp9XH8G3yp9LiY/9MmJO1NiuLuVPZLlyAnv++rxtaDMrFyRp2bx+jj82ba/j/9l47vQ6/TQ6/VPnc1S7arBDscmxOnV8SsiKAXR6G2N2e8dqRPbo4sTlII4UleLt1S0e06xi938VGhmttSfbfv7oqNoXkl2HjoGvey4FEFTwWk09bZjqVm5o3QOaxEaupshSdK8hgLzqBjw3poqmAxpOHD+l/B6vTh48CBu3LiBwcFBGI1GOJctw8e6ehz6e/9adNQH7g50w5icBqNBHfe3iIDQMb8OtkcX4uLdeqQlpXC3mlSBxZQK3bh3CwCwKrdUcBLtS4iLR3F2Hjy+Vqy2lYmOExOaezthWZSJ1ETD7C8OkzktA4nxCegY9M2rQYvH14L31+1ULJdWWEaTkXjsLpb8w9BOTyAQePC1ZEMypqan8Y+/GsG+ffuwbt06UTEfiNV29qRuNqMFHUNeBKUgx5dE2Mydzvn8YxqRUvhfvwrNNJ7gDwl5OK1FqOfw3ojxRKjrmvN+i/S5kiQJbm8LyhW8y6UFBw4cwJYtW3D48GEEAoFHCikACPgDmJqYxOHDh7FlyxYcOHBAUNLfcnubecSPVCclMRmpiSnoGR0QHSWmDI+P4XTTFWyv2CA6ChEAFlOq458cx28av8Kbjk2io0SNipxC1LEJRcQofV9qRuje1NyL5K7hXiTFJSIr1aRcKJU7cOAA9u7di7GxsVnndEmShLGxMezdu1d4QRXamSoUmoHoSUL3pnyiY8SUU54LWJvnRCa795FKsJhSmc9ufY3lOSWwLsoUHSVqOK3FqGcTioiJ5M5UQ3fznF/v9irbYVDtLl68+KCQmo+ZgurSpUsKJZtdaNBy7H7vSL1sRjPbo0dYtasGb3FsDKkIiymVUdtsl2hQlGXDvaFejE74RUeJejNH6SLR5KHCWoT6+00o5sLjje2hr/v374ffH95/A36/H/v375c50dz0jA5gYnoSi9OzhTyf6FnsJis7+kVQc28H2ge8eKlwlegoRA+wmFKRjkEvGn1t2FKyRnSUqJIQF49Scz7c3S2io0S9ruFeJMYlIDsCR+myUo1ITUzG3Tn+q3Ckijw18nq9OH78+JwLz2+SJAnHjh2Dzxf540webwvKzAW8Q0qqZGN79Ig6Uncabzg2ICGO/dNIPVhMqcjRutPYWrYeSfeHapJ8Kqy8NxUJkT6O5ciZexOKWN6ZOnjw4ILX0Ol0sqwzX24vh/WSetmNHNwbKdPBII7Wn+bpHVIdFlMqEZSCqHZxAJ1SnDns6BcJHm9LRFtYhzo1zl5MDfpHMBgYnVcb9Why48aNx7r2zZff78fNmzdlSjR3bm9zTN91I3WzGS1o56ypiLjQch2WtEyUZOeJjkL0CBZTKnHpbgNSEw2oYMcqRTisxaifR7MCCo/b24oyc0HEnldhLZrTjqPH14pSc37MzoIZHByUZZ3+/n5Z1pkPD3emSMWsi7LQ7x/C+NSE6ChRL/QPzmw8QeoTm58sVKjaVYOdnC2lmMKsXHhH+jA8Pr9OZjQ/Hm9zRHemHNZCuLubEZSCz3ydJ4bvSwGA0WiUZZ2MjAxZ1pmrsYkAuod7UZCZG9HnEs1VnF6PxYuycW+oR3SUqDboH8GF1hvYVv6i6ChEj2ExpQIj42OobbqMNziATjHx+jiUmZfMq5U2zc9QYAQD/hHkmawRe2ZGSjrSk9PQ1t/1zNe5Y/i+FACsWLECycnJC1rDYDBg+fLlMiWam0ZfK4qy7LxsTqqWy/boijvWcBYvFf7/27vz6KjONE3wzw1tESGh0BYRAoWEFhAiBJhF8m4jvIGwAVNZmem0T8+heipnjqrcp2cm8amip6erqruqqK5humf65By6K6dnONNjO5dytuSFxU7bCgw2aTDGEJIihEC7kCK0Iym0xp0/BHhDUiz33u9GxPP7qwpFfPc5VZYUr77ve9+tyDRmiI5C9D0spnTg/dYLqCp0Ijddmb8e0/0580O7X0OR8fjEHKWrDKEJRaIfFTt06FDUa8iyrMg64Uj0/79RbHBk2dmEQmUNTS4c4BE/0ikWUzrQ4HaxO40GnPbQO79R+EQdpdtoL0XTMkXyzPwsukf7UZbr0DCVvthsNtTW1kZ8jFiSJOzduxdWq1XhZMtL9EHLFBscbEKhqlZ/J4anxvBQkbY740ShYjElWMdwH7pG+vE4B9CpjsWUukQdpVtpZ+rGYA+KsvORmpyiYSr9OXLkCEwmU0TvNZlMOHLkiMKJVpbI7ewpdjgsNvSOs5hSS4O7EfucTyLJwI+spE/8L1Owt5tceH4jB9BpoThnDYYmxzA+PSE6SlwSdSTLaS+B19eJheD9m1B47gx9TXTV1dU4duwYzGZzWO8zm804duwYqqqqVEp2f3ML87gx1INyDeeWEUWiwGJDL3emVDG3MI/3ms9jP4/4kY6xmBJoIRjEO02f8IifRpIMBlTYi9kiXQUz87PoGr2Fsjztj9JlGjOQY85E58it+37do/HsKz2rq6u7V1CtdORPkqR7hVRdXZ1GCb/WMXwL9lW5MKdG1ziDSG2OrMXBvbIsi44Sd87evIzinNVYm71adBSiJbGYEuhC51VY07Ow3soBdFpxhjjklcJzY7AHRVmrkZacKuT5G+0laFpiKLPX14EN3N24p66uDi6XCwcPHoTRaPze0T+TyQSj0YiDBw/C5XIJKaQADuul2JFpzIBBMmCMpx4U9zbvlFMM4NkygerdjfwhoTGnvRQft10UHSPuiG4UUGkvQ/PATeyrfPJb/x6Ug2j1dyX0jKn7qaqqwltvvQW/348TJ07g2rVrGBkZQXZ2NjZv3oxDhw5p3mziuxaPjXKIOcUGR9ZiE4os0yrRUeLG0OQovuhpwd8+/6roKETLYjElyFhgAp91XMX/8uwfi46SUCrzS/Hzc78SHSPuiJ7j5MwvxcfnL33v37tG+pFlWoVMY7qAVPpntVrx2muviY5xXx5fB/7owX2iYxCFpCDTip6xAWxaXSY6Stx4t/kcdq2rQnpqZI1ziLTCY36CnPKcx6PFD3AAncaKsvPvDJe9LTpKXPH6O4Xu/my0l8Dr64BvYhhf9nrv3V3w+jp5XyoGybIMr5+d/Ch2OLLs6OWsKcXIsowGnt6hGMFiShDOlhLDIBlQYS9hi3QFBeUgWn2dwu4lnfF8hp81/DvMzM9izz+8ikNv/gUmZgMAAK+fnfxi0a3xQaQmpSA3PUt0FKKQFFhsLKYU1NR/EzPzs9jh2Cg6CtGKWEwJcN3fhcHJUTy8lgPoRHDaS9iEQkHdowPIMmXAYhKzy9rq78Sl7mYEZRkLwSAcFhtWpS22//YMsJNfLPL6xbTZJ4rU3TtTpIwGdyP2b9oZ8aBxIi2xmBKg3t2IfZVPcACdIM78MjRxZ0oxnoEOoUf8/uSxH2HT6jIY7vzS3Vm2497XvP5OVLCTX8zxCm5oQhSuAstie3SK3sz8LM54P8P+Ss6WotjAT/Mam1uYx8mW8/whIVClvRQt/Zw1pRTRd1uSDAb8Hy++du+S8pNl2wEAg5OjmFuYh31VrrBsFBkOWqZYsybTCt/EMOaDC6KjxLyP2i6hwlaM1Zl5oqMQhYTFlMbOtV9BUXY+inPWiI6SsAqz7JiYDWBockx0lLggemcKALLNmfj3L/4MyYYkbCvYAGBxd6PCVsxjIjHIy0HLFGNSkpKRZ85C//iQ6Cgxj40nKNawNbrGFn9IcFdKJEmSsNFejJaBm3i8dJvoODFPL/db1qZZ8eP5B/DfHvqnGBsbw1gwgJwiO/y7/MJnJlHoxgITGA1MoDDLLjoKUVgKLFb0jg3AkWUTHSVm9Y8Poqn/Bv79gZ+JjkIUMhZTGhqaHMOl7mb8zd4/FR0l4TntpWhiMRW1wclRzC7MIV/gUbqLFy/i6NGjOHXqFABgenr63tdMJhOKTvwWtbW1OHLkCKqrq0XFpBB5/Z0ot62FQeLBCYotBVl29Iz58JDoIDHsneZP8Gz5wzClpImOQhQy/rbS0Hst51BTxgF0elCZX4aWAd6bipboo3THjx9HTU0N6uvrMT09/a1CCgACgQCmp6dRX1+PmpoaHD9+XEhOCt3ifSk2n6DY47Cwo180ZFnG224XXuQRP4oxLKY08vUAOh7x0wOnvRRNbI8eNZGNAo4fP47Dhw9jamrq3pDepciyjKmpKRw+fJgFlc7xvhTFKkcWZ01F48teL5IMBmxevU50FKKwsJjSSPPATQTmZrCjkAPo9KDAYsXM/Cz8EyOio8Q0j6APvhcvXrxXSIXjbkF16dIllZJRtDy+DlSwkx/FILZHj87dxhNsGkSxhsWURhrcLuyv3Ml7ADqx2ISiBM2cNxUVUTtTR48eRSAQiOi9gUAAR48eVTgRKWFmfhbdo/0oy3OIjkIUNoeFO1ORmpqdxofXL+IF5xOioxCFjZ/sNTAzP4vTnk+xv/JJ0VHoGyrzS3lvKgqTswH4bg+jOGe1ps/1+Xw4derUikf7liLLMk6ePAm/369wMopW22A3irJWIy05VXQUorDlmC2YnpvFxEx4O+YE/K7199haUA5rRrboKERhYzGlgY/vDKBbY2F7Zj3hvanoXPd3oSzXgZQkbZuCnjhxIuo1JElSZB1Sltenjzb7RJGQJOnOvSn+oSZcDe5GNp6gmMViSgMNbhf2s/GE7jjtpWgeuBnxDkei8/jEDOu9evXq97r2hSsQCODatWsKJSKlLP43xU5+FLsW700NiI4RU3pGB3BjqAc7y3aIjkIUERZTKhu4PQx3fxueXv+g6Cj0Hasz87AQXICPTSgi4vV1CvngOzY2psg6IyP8/7veeAUV6ERKYXv08DW4XdhT8ZjmpxyIlMJiSmXvNp/Fs+UPcQCdDkmSBKe9FC1sQhERz50ZU1qzWCyKrJOdzbP5ehKUg2j1d6GCO1MUwwrYHj0sQTmId5rOcmwMxTQWUyqSZRn1d1p9kj4583lvKhJzC/O4OdSDcgHDVbds2QKj0RjVGiaTCZs3b1YoESmha6QfWaYMZBozREchilgBO/qF5fOuJmQa07HRXiI6ClHEWEyp6EpfKwySAVtWrxcdhZZw994UhadjuA/2Vbkwp0ZX1ETi0KFDUa8hy7Ii65ByFo+N8gMVxTYHZ02FZXG2FHelKLaxmFJRg7sRByp3cgCdjlXml6J5oJ1NKMIk6ogfANhsNtTW1kb8fSVJEvbu3Qurld019WTxvyke8aPYVmCxoW/Mj6AcFB1F927PTOHsjcvYu/Fx0VGIosJiSiVTs9P4XevneKGSA+j0zJaRAwnAwO0h0VFiiqhOfncdOXIEJpMpoveaTCYcOXJE4UQULa/AAp1IKaaUNGQa0+GfGBUdRffOeD7FQ2s3I9ucKToKUVRYTKnkw+ufY+uactgyckRHoWXcbULRxKN+YRE9D6i6uhrHjh2D2WwO631msxnHjh1DVVWVSskoUqILdCKlFFis6GV79BU1uF084kdxgcWUSup5DjhmOPNL0cwmFCGTZRlev/gjWXV1dfcKqpWO/EmSdK+Qqqur0yghhWpwchTzwQXkr8oVHYUoagUWO9ujr+DmUC/6xv14rGSr6ChEUWMxpYKe0QHcGOzmALoY4bxzb4pCc2t8EKlJKchNzxIdBXV1dXC5XNj9fC3S0tK+d/TPZDIhOTUFFY9uhcvlYiGlU947w3p5v5TigYMd/VbU4G7EC84nkGxIEh2FKGqckKaCt5vOYk/FY0hNThEdhULgtJegeeAmZFnmh7kQeP1ij/h9l2WtHb5dWfjpS/8KRX0puHbtGkZGRpCdnY3Nmzdj3w8P4o/fOYr1lRWio9ISRDY0IVKaI8uGz7uaRMfQrfngAt5rPod/+NG/FB2FSBEsphS2OIDOhX934Geio1CIbBk5SDEko2/cjwKLTXQc3fMMtGODTrqufdXXiv/+N3+D+eACMrMteO2VP73v63aWbcdvr32EP3pwv8YJKRQeXwd38iluFFhs6Bn7WHQM3fq0/SvkZ+aiNLdAdBQiRfCYn8IudjUhI83Mv7LGGN6bCt3izpT4eUDn27/Cf/frv0ZgbgYA4JsYWfK1r2yvxa++fB/zwQWt4lEYuDNF8cRhsaGXd6aW1OBuxP5K3imn+MFiSmENTS4c2FTD42Ixhh39QucZ6NDFztRpz6dY+MYsF98y7e2d+aWwZ+bi4+sXtYhGYZicDcB3exjFOWtERyFShDUjB2PTE5iemxUdRXdGpsZxofMa9lQ8KjoKkWJYTCmIA+hiV2V+KVrYhGJFY4EJjM9MojDLLjoK/k1tHf7XF/450lNNsBgz7u1QLeWV7bV4/fIpjdJRqFr9XSjLdfAiOsWNJIMBqzPz0DfuFx1Fd056zuOJ0m3INKaLjkKkGBZTCnrf+xmqiyqRwwF0McdpL0FT/2ITClqax9+B9dYiGCR9/Oj4rPMa/puq5/Hxn/wD3vgnf7vsa59aX41b44M8zqkzXl8HKuzFomMQKarAYkPPKGdNfdfibKka0TGIFKWPT0RxosHdyB8SMSo3PQvm1DT0cNDiskQP6/2mmflZnPF+hn2VTyLJYEDeCq3akw1J+PHW57g7pTMeXwc2WItFxyBSlMNiQw/bo3+Lx9eBscBtPFi0SXQUIkWxmFJI+1Avesf8eJwD6GKW016G5n4e9VuOx6efTn6NbV+g3FoUVgfGH2x5Gq4blzE4OapeMAqL19fJnSmKO44szpr6rrfdrnt//CKKJ2yNHgFPlx9/+ZsmtI0mY1pOgVGaQ6rcjZ3bHuS5/xhWmV+K5oGb2F3xiOgouuX1deKf7HhedAwAke0EW0wZeG7Dw/jNlQ9Q99gP1QlGIZtbmMfNoR6szysSHYVIUQUWG77s9YqOoRtzC/M42XIe/+WVfy06CpHi+OeBMLz5UTMe+JcX8NyvV+F88EH48x7HbetD8Oc9jm7LAbze/hM88C8v4M2PmkVHpQjcvTdF9zczP4vu0X5dzAYZuD2Mq7fa8PT6B8N+78vb9+A3X/0Os/NzKiSjcHQM9yE/Mw/mVKPoKESKWrwzxZ2pu1w3LqM0twCFWfmioxApjsVUiH76cxf+7Iu1GMmthpRihCHV/K2vG1LNkFJMGMmtxp99sRY//blLUFKK1EZ7KVoGbiL4jXbb9LW2wW4UZa1GWnKq6Ch4t/ksni1/CKaUtLDfuy6vEOutRTjj/UyFZBSOxftS+jg2SqQkR5YdPWMDbGp0x+JJAs6WovjEYioEP/25C2cCVZBS0yGtcIxPMiRBSk3HmUAVC6oYk2PORKYxHd3swHRfemk+Icsy6qP8xfzy9j14/fIpftARjMN6KV6tSjMjNSkFI4HboqMINzg5ii97vXi2/GHRUYhUwWJqBW9+1HyvkArH3YLqlx/zyF8scdpL2Tp7CR6fPob1ftXXCoNkwANryiNe44nSbZicCfBOg2BeXyc2sJiiOFVgsbFDLIB3mz7BU+ureZyX4haLqRX83UfjQHKEPwCSjTj64ZiygUhVzvxS3ptaglcnuwgNbhf2V+6EJEkRr2GQDHhp+268wTbpwsiyDK+/AxU6KNCJ1OCw2NCb4PemZFlePOJXySN+FL9YTC3D0+XHSNbWFY/2LUUyJGEkaytauwcVTkZqcdoXO/rRty0Eg2j1dwnfmZqancYHrb/Hvsonol7rQOVO/L7LjVvj/P4U4db4INKSUpG7wnwwolhVwPbouNbfhrngPLY7KkRHIVINi6ll/OVvmiAjumYEsizjL37tVigRqc1pL4XH18EmFN/RPdqPLNMqZBozhOb48PrneGDNetgycqJeKyPNjH3OJ/HLL88okIzCpZdjo0Rq4eBeZU4SEOkdi6lltI0mw5BiXvmFyzCkmtE2xnFescJiykCWaRU6h2+JjqIrix98i0XHQIPbFfZsqeX8ZPtu1LsbMTU7rdiaFBq9HBslUkuit0efnpvF+97PsL/ySdFRiFTFYmoZ03KKIusEgsqsQ9qotJeiiUf9vkUPnfx6Rn24PtiFmrIdiq1ZmJWPB9aU472Wc4qtSaHRS4FOpBZHlg29CdyA4uO2i3DaS5GfmSc6CpGqWEwtwygpM9TTZOBw0FjizGdHv+9abGEt9kjWO00u7Kl4FKnJyv5x4pXte/DG5dNsk64xPRToRGrKX5UH/+Qo5hbmRUcRot7diBcVPElApFcsppaxLmsewbmpqNYIzk5hnSUxf5DGKmc+m1B8l+gjWUE5iLebXKr8Yn6waBMMkoQLndcUX5vubzRwG+Mzk3Bk2URHIVJNSlIyrOlZ6L+deE1ubo0PomWgHbvWVYuOQqQ6FlPL+MsfVkKK8v9EkiThr360SaFEpIWNthJ4fB1YCLIJBbA4cHE+uAD7qlxhGS52NyM91axKQSdJEl7ZXovX2SZdM15/J8qtRTBI/BVE8a3AYk/Ie1PvNJ3FcxsehjElVXQUItXxN9kyKoqsyB69Ajm4ENH75eACskevoLyQ54VjSaYxHdb0bLQP94qOoguegXZU2IqFdmNqcDfiwCb1OkLt3fg43LduoHOEjUe0wGG9lCgcWYnX0U+WZbzdpGyzICI9YzG1gj9/KhOYj7DT1/w0jjxtUTYQaYL3pr7m9XcKbWF9e2YKZ29cxvPO6GdLLcWYkoo/2LILb15mm3QteHztvC9FCcFhSbxZU5d7PEhJSsGm/DLRUYg0wWJqBT95yondpkuQZyfDep88O4ndpkt4aZdTpWSkpsXhve2iY+iCZ0Bs17UPvBdQVViJHHOmqs/58dbn8F7LJ7g9E909SVoZm09Qoiiw2NCbYMf8FhtPcLYUJQ4WUyH4xas77xVUKx35k4ML9wqpX7y6U6OEpDSnvQTNAzdEx9AFj19s84mGO7+Y1WZflYtH1m5Bg7tR9Wclsum5WXSP9qMs1yE6CpHqChLsmN/U7DQ+bruo6kkCIr1hMRWiX7y6E39f1Ynsoc8hzwUQnP32X6+Ds1OQ5wLIHvocf1/VyUIqxm20l8Dr68J8hPfl4sXkbAC+2yMozlkj5Pkdw33oHh3AYyVbNXneKztq8ebl02w+oqIbQ91Ym71a8Rb3RHrksNgT6pjf+94L2FZQgbz0LNFRiDSTLDpALHlplxMv7QJauwfxF792o20oGYFgCkyGOayzzOOvfrQJ5YWPiI5JCshIMyM/MxftQ71Yby0SHUeYVn8XyvIcSDYkCXl+g9uF552PIyVJmx9VW1avh8W0Cp/cvIyadVWaPDPReAS32SfSUrZpFeYW5jE+PYlMY7roOKpraGrEK9v3io5BpCkWUxEoL8zDmz+rER2DVOa0l6Kp/2ZCF1OLnfzENJ9YCAbxTvNZ/Mc//BeaPfObbdJZTKmDnfwokUiStHhvasyHTGOJ6Diq6hrpR/tQH3aWbRcdhUhTPOZHtITFe1OJ3dHP6xfXKOCzjq9gy8jBurxCTZ/73IaH0T7Uh+v+Lk2fmyg8vnZssIrrDkmkNUdWYnT0e7vJhb0bH9PsJAGRXrCYIlpCZX4pmvoTuwmFxyeuk1+D26VJ44nvSklKxg+3PoM3Lp/W/NnxbiEYRKu/iztTlFAKEqA9+kIwiHeaznK2FCUkFlNES6iwlaBtsAdzC/OiowgxtzC/eGcsT/tjjmOBCXzWeRV7Kh7V/NkA8IdbnsEHrb/HyNS4kOfHq+7RfmSbMhPi7gjRXQ6LDT1x3h798y43skyrhM4kJBKFxRTREsypRqyxWHFjqEd0FCE6hvuQn5kHc6pR82efbDmHx0q2ItOYofmzASA33YJd66rw22sfCXl+vPL4OlBhLxYdg0hTBZb4b4/e4G7krhQlLBZTRMtw2kvQ3J+Y96ZEdl1raHJhf6XY8QKv7KjFr668n7A7k2rw+jqxwVosOgaRphxZdvSMDYiOoZrx6Umca7+CvRsfEx2FSAgWU0TLcOaXoilBm1B4fB1CGgW0+jsxPDWGh9du1vzZ31RhK4bDYseH1z8XmiOecGeKEtGaTCv6x4fidn7dac+neHjtZmSZVomOQiQEiymiZVTaS9GSwDtTIhoFNLhd2Od8EkkG8T+eXt5eizcunxIdI254fR2oYCc/SjDGlFRYjBnwTwyLjqIKHvGjRCf+0wqRjm2wFePGUA9m5+dER9GULMvw+jo1nzE1tzCPky3nsV9AF7/72bWuCv6JEbhvJXZXRyX4J0awIAdhX5UrOgqR5gqy4vPe1I3BHgzcHsYjxVtERyEShsUU0TJMKWlwZNnRNtgtOoqm+sb9MCanIjc9S9PnfnLzS6zNzsfa7NWaPncpSQYDXtq2G69zdypq3jvHRiVJEh2FSHPx2tGvwd2I552PI9mQJDoKkTAspohW4LQn3r2pxV2pYs2fq8fjIgc378InN7+Ef2JEdJSYJrKhCZFojjicNTW3MI93mz/Bizr7mU2kNRZTRCuozC9FS4IVU4v3pbQ94jc0OYovelrw3IaHNX3uSjKNGaiteBS/vvKB6Cgxzevr5LBeSljx2B79fMdXKLDYUJJbIDoKkVAspohW4MwvRVOCNaHwCthFeLf5HHatq0J6qknT54bi5e178I9XP8TM/KzoKDFLRIFOpBeOLBt646w9+ttuFw7o5H4rkUgspohWUJ63Fh3DfQn1QVrrTn6yLOvyiN9dJbkFqLAV47TnU9FRYtLkbAC+iREU56wRHYVIiAKLHb1jftExFDMyNY7Pu9zYXfGo6ChEwrGYIlqBMSUVa7NXo9XfJTqKJkYDt3F7ZgqOLJtmz2zqv4mZ+VnscGzU7JnhemX7Hrx++TRkWRYdJea0+rtQlufgJXVKWNaMLNyemURgbkZ0FEWcbDmHJ0q3Y1WaWXQUIuFYTBGFwJlA96a8/k6UW4tgkLT78dDgbsT+TTt13ent0ZIHMD03g8s9HtFRYo5noJ3NJyihGSQDVmda46YJRYPbhRd5xI8IAIspopA47Ylzb8oz0IEKW4lmz5uZn8UZ72fY53xSs2dGwiAZ8PL2PWyTHgGvX/uZZUR644iTJhQtA+24PTOJ6qJK0VGIdIHFFFEInPZSNCfMzpS2jQI+bruEClsx1lismj0zUvsrd+JSd3Pc/HVZK4tt0bUr0In0qCBO2qM3uF3YV7lT09MLRHrG7wSiEJRbi9A10o/pufhvQrG4M1Ws2fMa3C7dNp74LnOqEfsrd+JXX74vOkrMmFuYR/tQL9blFYqOQiRUgcWG3hgf3Ds7P4fTnvPYX8kjfkR3sZgiCkFqcgpKcgvQ6u8UHUVV03Oz6BkbQFmuQ5PnDdwegru/DU+tr9bkeUp4adtuNDS5MDU7LTpKTGgf7sXqzDyYU42ioxAJ5ciK/WN+rhtfoCyvUNMGRUR6x2KKKESL96ZuiI6hqrbBbqzNXo3U5BRNnvdO01k8W/4wTClpmjxPCY4sG7YVVODd5rOio8QEDuslWuSw2NEzGtuzphrcLhzgrhTRt7CYIgqR014S9/emvH7tjvgtzpZy4cUYOeL3Ta9s34M3Lp9GUA6KjqJ7Hh87+REBQIHFit4xf8yOV/BNDONKXyueKX9IdBQiXWExRRSiyvyyuO/o5xnQbljvl71eJBkM2Lx6nSbPU1JVoRMpScn4rOOa6Ci65/F1atrQhEivMtLMMKakYnhqTHSUiLzb9AmeXl/NI7tE38FiiihE6/IK0Tvmi+u7MlruTDW4G3FgU42uZ0stRZIkvLy9Fm+wTfqyZFlePOZnLRYdhUgXCmK0Pbosy3i7KXaaBRFpicUUUYhSkpJRllcIb5w2oVgIBtHq70K5Vf1dhKnZaXx4/SJecD6h+rPUsnfjY2geaEfHcJ/oKLrVN+6HMSUVuekW0VGIdMERo+3Rr91qw4IcxLaCDaKjEOkOiymiMDjtJWiO0yYU3aP9yDFbkGlMV/1Zv2v9PbYWlMOaka36s9SSlpyKH2x5Cm9cPi06im55fZ2o4K4U0T2OLBt6YrA9er27EQcqd8bkSQIitbGYIgqDM78UTXHahMLj025Yb4O7MSYbT3zXj7Y+i1Oe8xifnhQdRZc8vg5U2ItFxyDSjVg85heYm8EHrRewr/JJ0VGIdInFFFEYKu1laOlvFx1DFR6fNvelekYHcGOoBzvLdqj+LLXZMnLwWPEDqHc3io6iS15fBzZocGyUKFY4LDb0xlh79I+uX8Sm/HWwr8oVHYVIl1hMEYWhNLcAfeODmJwNiI6iOK3mAb3ddBZ7Kh5DSlKy6s/Swss7avHm5dNYCLJN+ndxZ4ro2wosdvSO+UXHCMtisyDOliJaCospojCkJCVjvbUQnoEO0VEUJcsyPL4ObFS5mArKQbzT5IqrX8xbVq9HbroFrhtfiI6iK6OB25iYmUKBxSY6CpFu5GfmYnBqFHML86KjhKRvzA+vvxO71lWJjkKkWyymiMLktMffvanByVEE5SBsGTmqPudiVxNWpaVjo71E1edo7ZXttXidbdK/xevrQLltLQwSf80Q3ZVsSIItIwd947GxO/V201ns3vAI0pJTRUch0i3+liMKU2V+KVrirJjy3Lnbonanpnp3fO1K3fVM+UPoHLmF1jhtmx8JD+dLEd2XwxIbHf2CcvDObKn4+5lNpCQWU0RhctrL0NQfX8WUV4PmE7dnpvDJzcvYu/FxVZ8jQkpSMn689Tm8/gV3p+7SqqEJUaxxZMXGrKkvultgTE6F014qOgqRrrGYIgpTSe4a+CaGcXtmSnQUxSy2RS9W9RlnPJ/iwaJNyDZnqvocUX6w5Wl8eP0ihqfGRUfRBa+GrfaJYklBjAzuXdyVquFsKaIVsJgiClOyIQkbrGvRMhA/LdK9vk7VdxEa4vSI31055kw8vb4ab139UHQU4abnZtE75sO6vELRUYh0p8BiQ4/O26NPzgbwcdslvOCMv5MEREpjMUUUAWcc3ZuanA3ANzGCtTmrVXvGzaFe9I378VjJVtWeoQev7KjFr668HzOdutTSNtiNtdmr46b9PZGSHBY7enXegOJ97wXscGxEbnqW6ChEusdiiigCTntp3Nyb8vo6sS7PgWRDkmrPaHA34gXnE6o+Qw/KrWuxNns1ftf6e9FRhPL6ecSPaCmOLP03oFicLVUjOgZRTGAxRRQBp70UzXGyM+VV+b7UfHAB7zWfS5hfzGyTDngG2HyCaCkWYwaCchDj0xOio9xX58gtdI7044nSbaKjEMUEFlNEESjOWYOhyTHd/jIMh9pd1z7ruIr8zFyU5hao9gw92Vm2A8NT47h667roKMIs7kwVi45BpEuSJOm6Pfrbbhf2bnyMx3SJQsRiiigCSQYDKuzFcdGEwutXt/lEg7sR+yvjt/HEdyUZDHhp2268kaBt0heCQbT6u1hMES2jQKft0ReCQbzddBYvJshJAiIlsJgiipDTXhLz96bmFubRPtSL9dYiVdYfDdzGhc5r2FPxqCrr69WLm2pwvuMrDNweFh1Fc92j/cgxW7AqzSw6CpFuOSw29OiwmLrQeQ156Vmq/U4gikcspogi5LSXxfy9qfbhXqzOzIMpJU2V9U+2nMfjJVuRaUxXZX29yjSmo7biMfzmqw9ER9FcC4f1Eq2oQKfF1GLjicQ5SUCkBBZTRBGqzC9Fc4wf81O7UUAid4R6efsevHX1I8zMz4qOoikO6yVamUOHs6bGpyfwacdXqK14THQUopjCYoooQkXZ+RgL3MZo4LboKBFTs1GA19eJ0cBtPFi0SZX19a44Zw2c9hKcbDkvOoqm1G5oQhQPHFl29I3pa9bUac+neKR4CyymDNFRiGIKiymiCBkkAypsxTF91M8zoN4uQoO7Efsqn0SSIXF/zLy8vRZvXD4FWZZFR9GELMtsi04UgtWZebh1exALwaDoKPfUu104kEDNgoiUkrifcogU4MwvRXOMNqGQZRlefyc2WIsVX3tuYR4nW84n/Nn7R4u3YG5hHpe6m0VH0cTg5CgAGbaMHNFRiHQtLTkV2aZMDNweEh0FANA22A3fxDAeKX5AdBSimMNiiigKzvyymL031TfuhzElDbnpFsXXdt24jNLcAhRm5Su+diyRJAkvb9+D1y+fFh1FE547A6AlSRIdhUj3HFn6aULR4G7EPmdinyQgihS/a4iiUGmP3Z0pNe+2sCPU115wPokvez26u2yuBi/vSxGFzGHRx6ypuYV5vNd8jj+ziSLEYoooCoVZdkzMTmFockx0lLB5feoM6x2cHMWXvV48W/6w4mvHInOqEQcqd+LNL8+IjqI6Dzv5EYWsQCfF1Pn2KyjMsqM4Z43oKEQxicUUURQkScJGewlaYrAJhVo7U+81f4Kn1lfDnGpUfO1Y9dK23Xin6SwmZwOio6jK61PnDh5RPCrQSXv0ercrYUdYECmBxRRRlJz22Jw3pcY8IFmWUe924UUeF/mWNRYrqgqdeNvtEh1FNRMzU/BNjPCv20QhcmTZ0Su4PfrQ5BgudTfhuQ08SUAUKRZTRFGqzC+Lufboo4HbmJiZQoHFpui67v4bmFuYw7aCCkXXjQevbK/FG1+eRlDWTytkJbX6u7Auz8EL7EQhcljEN6A42XIOO8t2ICPNLDQHUSzjbz2iKDntJWiKsSYUXl8Hym1rYZCU/RHQ4G7E/sqd7OZ2H9sdFTCnGHG+/SvRUVTh8XWgwl4iOgZRzMhLz8LUbABTs9NCni/LMhp4xI8oaiymiKJUYLFhen7mzoyd2KDGfanpuVm8772A/ZVPKrpuvPi6Tfop0VFU4fV1YIOVzSeIQiVJEtZkWoU1ofD4OjA5G0BV4UYhzyeKFyymiKIkSdLivakY2p3yqNAo4OO2i9hoL0F+Zp6i68aTPRWPwuvrxM2hXtFRFLe4M1UsOgZRTCnIEtfRr/7OCAulTygQJRp+BxEpoDK/NKbuTanRwrre3YgXeVxkWWnJqfjDLU/jjTjbnZpbmEfHcB/W5xWJjkIUUwoE3ZuanZ/Dac+n2MeTBERRYzFFpACnvTRm7k1Nz82id2wA6/IKFVvz1vggWgbasWtdtWJrxqsfbX0Wpz2fYXx6QnQUxbQP92JNphWmlDTRUYhiisNiQ8+o9sVU440vsD6vSPEmRESJiMUUkQIW26PHRjHVNtiN4uw1SElKVmzNd5rO4rkND8OYkqrYmvHKmpGNJ0q34bdXPxYdRTGeAQ7rJYqEI8uOnjHtZ0013DniR0TRYzFFpIDVmXlYCC7ANzEsOsqKPL52bFCw+YQsy3i7iR2hwvHK9lr88sszmA8uiI6iCK+/AxU2dvIjCpfDYtN81tTA7WF81Xcdz5Q/pOlzieIViykiBcRSEwqvrxMVCu4ifNnrQUpSCjbllym2ZrzbtLoMtlXZaGy7JDqKIrgzRRSZAosNfWM+yLKs2TPfbf4Ez5Y/xGO5RAphMUWkEGd+bNybWmyLrtwuQr3bhRc3cbZUuF7eXhsXbdJlWYbX36nobidRojCnGmFKMWo2WmNxthSP+BEpicUUkUJi4d7UQjCI64NdKFdoF2FqdhofXb+I551PKLJeInl6/YPoHfOhZaBddJSo9I75YUoxIsecKToKUUxyaNge/au+VkiShAfWlGvyPKJEwGKKSCGL7dHbNT2uEa6ukVvINVuwKs2syHoftF7AtoINyEvPUmS9RJKSlIwfb30u5tuke/084kcUDYeG7dEb3C7sr+RJAiIlsZgiUogtIwcSgIHbQ6KjLMmj8HGsBjcbT0TjB1uexsdtX2BIoyM+avAMdKCCR/yIIlagUXv0wNwMfnf999hXyZMEREpiMUWkkLtNKJp0fNTPM9Cu2Aff7tF+3Bzqxc6y7Yqsl4iyTKvw3IaH8JuvPhQdJWJefyeLKaIoFGTZ0KtBe/QPr3+OLavXw5aRo/qziBIJiykiBTnz9d3Rb7FRgDJHshrcLuzd+Jii86oS0U+21eI3X32AuYV50VEi4vEpV6ATJSKHxa5Je/TFxhM1qj+HKNGwmCJSkPPOvSk9kmX5zpGs6Dv5LQSDeKfpLH8xK2C9tRBluQ6c8X4mOkrYRqbGMTkTwBqLVXQUopi1eGdK3Z2p3jEfrvu7UFO2Q9XnECUiFlNECnLaS9A8cFOXTSj8kyMAZNgysqNe6/MuN7JMq9h4QCEv76jFG1+c0uV/N8tpvXMHzyDxVwlRpOyrcjE8NY6Z+VnVnvFO01nsrngUqckpqj2DKFHxNyCRgmwZOUgxJKNvXNuJ9qHw+hY/+CrRxYnHRZT1ZOk2jM9M4qu+VtFRwuLxsZMfUbSSDAbkr8rFrfFBVdYPysHFZkGVnC1FpAYWU0QK0+u9qcVhvcVRrzM+PYlz7Vewd+Nj0YciAIBBMuAn23bH3BBfj4/NJ4iUUGBRb9bUpe4WpKeasNGu3LB2IvoaiykihS0O79XfvSmvQrsIZ7yf4eG1m5FlWqVAKrrrwKYaXOi8hn6V/jqthsWdqWLRMYhinprt0RdPEnC2FJFaWEwRKWxxeK9ed6ai/8skj/ipIyPNjBecT+BXVz4QHSUk03Oz6BvzoSzXIToKUcxTqwnFxMwUXDe+wPNOzpYiUguLKSKFOe0laOrXVxOKiZkpDE6OYm326qjWuTnUi/7bQ3ikeItCyeibfrJtD/7rtY8QmJsRHWVF1we7sDZnDVvjEynAkWVHjwrH/N73XkBVYSVyzJmKr01Ei1hMESksNz0L5tQ01VvdhqPV34l1eYVIMkT3Ld/gbsQLzieQbEhSKBl9U1F2PjavXo+TLedER1mR19eBDVY2nyBSgsNiU2XWVEOTCy9uYuMJIjWxmCJSgdNehuZ+/dyb8tzp5BeN+eAC3m3+hB2hVPbKjlq8HgNt0j2+DlTYi0XHIIoLBRYbekcHFP2+7xjuQ/dIPx4r2arYmkT0fSymiFSgt3tTSnTyO99+BWsyrSjJLVAmFN3XQ0WbACzO8tIzr68TFdZi0TGI4kKmMR2SJGFsekKxNd9ucuF55+M8ikukMhZTRCq4e29KL5To5NfgduEAj4uoTpIkvLx9D16/fFp0lCUtBIO4PtiFcs6YIlKEJEmKtkdfCAbxTtMnbBZEpAEWU0Qq2GgvRcvATQTloOgomFuYR8dwH9bnFUW8xsjUOD7vcmN3xaMKJqOlPO98Alf7WtE92i86yn11jdxCrtmCVWlm0VGI4oZDwfboFzqvwpqRjXV5hYqsR0RLYzFFpIIccyYyjenoHhXfhOLmUC/WZFphSkmLeI2TLefwROl2fnjWiCklDS9u3oU3L58RHeW+PH4O6yVSWoHFplhHv3p3IxtPEGmExRSRSpz2UjTr4KifUkf8+ItZWy9tfQ7vNJ/FxMyU6Cjf4xlo57BeIoU5smzoVaAL7FhgAp91XMUeniQg0gSLKSKVOPNLdXFvKtphvR5fB27PTKK6qFLBVLSS/Mw8PFy0GQ1NLtFRvsfLnSkixRVY7Iq0Rz/lOY9Hix9ApjFDgVREtBIWU0Qqcd65NyVatDtTDe5G7KvcCYPEHxdae3lHLX55+Ywu7t7dJcsyPAMd3JkiUliBxYoeBY6GLzYLqok+EBGFhJ+OiFTitJeixdch9IOwLMvw+iOfMTW3MI9TLeexn7OlhNi6phwZaWZ8cvNL0VHu8U+OAABsGdmCkxDFlzWZVgxMDGM+uBDxGtf9XRiaGsXDazcrmIyIlsNiikglFlMGsk2r0Dl8S1iG3jE/TClG5JgzI3q/68YXKMsrhCPLpnAyCsXdNulv6KhN+uKu1FpIkiQ6ClFcSU1OQa7Zgv7xoYjXqHc3Yp/zSSQZ+PGOSCv8biNSkdNeiiaBR/2iHda72BGqRrE8FL7dGx5B22A32ga7RUcBwPtSRGpyWGzoHY+so9/cwjxOtpzHfjYLItIUiykiFTnzxd6biua+lH9iBFd6W/H0+gcVTkXhSE1OwQ8feEY3u1OegXYWU0QqWWOxoTfCWVPn2q9gbXY+1mavVjgVES2HxRSRikR39Iumk9+7zZ/g6fXVMKcaFU5F4frhA8/gfe8FjAUmREeJ6g4eES3PkWVDT4Tt0RvcjWw8QSQAiykiFW20lcDr68RCUEwTCq+/AxUR7EzJssxfzDqSm56FmrIdeOvqh0JzTMxMYXBylH/5JlKJI8L26EOTY7jU3YLnNjysQioiWg6LKSIVZRrTkZeehfbhXs2fPTI1jqnZaRRYwm8ece1WGxbkILYVbFAhGUXilR21+NWV96Pq9BWtVn8n1uUV8nI7kUocWbaI2qO/13IOu9btQHqqSYVURLQc/kYkUtnival2zZ/r9Xei3BpZ17V6dyMOVO5kxzYd2WgvwerMPHx0/aKwDB4fm08QqanAYkPvWHh3pniSgEgsFlNEKnPaxdyb8kbYyS8wN4MPWi9gX+WTyoeiqLyyvRavXz4l7PkeH4f1Eqkp12xBYG4Wk7OBkN/TPHAT03Mz2OHYqGIyIloKiykilVXml6J54Ibmz/VE2Mnv47aL2JS/DvZVuSqkomjsWl+NgfEhNAtqahJpgU5EoZEkCQUWa1i7Uw1uF/Zv4kkCIlFYTBGprMJWDK+vS/O7Lh5fZF3XGtwuHOCcEl1KNiThx9ueE7I7Nbcwj47hPqzLK9T82USJxJFlR0+I7dFn5mdx2vMp9jl5koBIFBZTRCrLSDMjPzMX7UPaNaEIzM2gb8yHslxHWO+7NT4Ij68Du9ZVqZSMovUHm5+C68ZlDE6Oavrcm0O9WGOxwZSSpulziRJNgcWKnhB3pj5uu4QKWzHWWKwqpyKipbCYItKA1vem2ga7sTZnDVKSksN639tNLuze8AjSklNVSkbRspgysLviEfzmygeaPtfja4+ozT4RhcdhCb2j39tuFxtPEAnGYopIA057CZoHtCumPBHcbQnKwTu/mHnET+9e3rYHv/nqd5idn9PsmV5fJzZYizV7HlGiKsiyoy+EWVMDt4dxrb8NT62v1iAVES2FxRSRBirzS9HUr10TCm8EzScu93hgTEmD016qUipSSlmeA+utRTjj/UyzZ3p8HaiwF2v2PKJEVZBpQ8/YyjtT7zafxbPlD/PoLZFgLKaINFBhK0HbYA/mFuY1eZ7H14GNYe5MNbgbsZ+zpWLG3Tbpsiyr/ixZltHq78QGK4/5EamtwGJF37gfQTm45GtkWUa9uxEv8ogfkXAspog0YE41Yo3FihtDPao/ayEYRNtgN8rD+OA7ORvAx22X8ILzcRWTkZIeL92KydkAvuz1qv6s3jE/zKlGZJszVX8WUaIzpxqRkWqGf2J0yddc6WtFkmTA5tXrtAtGRPfFYopII057iSbzgbpGbiEvPQsZaeaQ3/O+9wJ2ODYiNz1LvWCkKINkwE+27cEbGrRJ9/g6eF+KSEOOLNuys6Ya3I04sKmGJwmIdIDFFJFGnPmlaNKgCcXiB9/wjmPd/cVMseXApp34vKsJt8YHVX0Oh/USaavAsnQxNTU7jd+1fo4XnE9onIqI7ofFFJFGKu2laNFgZ2qxUUBJyK/vHLmFzpF+PFG6TcVUpIb0VBP2VT6BX355RtXneHwdEQ2AJqLwjEyN49dXPkDXSD/+46f/iBd+8c/xbvMn33rNh9c/x9aCclgzsgWlJKJvYjFFpJENtmLcGOpRvZ11uDtT7zSdxd6Nj4U9k4r04Sfb9qDB3Yip2WnVnuH1c2eKSAvXB7vxN7/7z3D330DPmA8DE8Owfuf4NRtPEOkLiykijZhS0uDIsqNtsFu1Z8iyvDgPKMQPvgvBIN5ucvEXcwxzZNnxwJpyvNdyTpX1R6bGMTU7jQKLVZX1iehrDxZV4pnyh5BsSAIApCYlo6qw8t7Xe0YHcGOwGzvLdoiKSETfwWKKSENOu7r3pnwTIwAAW4jHP37fdQ255iystxaplonU9/KOWrxx+bQqbdK9d1qi86I7kTb+4rmf3psdtbviESQZvv6o9k7TWeyp4EkCIj1hMUWkocr8UrSoWEzdHdYb6gffBrcLBzbtVC0PaePBwkoYJAkXOq8pvrZngPeliLSUaczA3+59FQDw/Mavm0wE5cWTBPyZTaQvLKaINOTML0WTik0oPGF0XRufnsD59iuorXhMtTykDUmS7g3xVRrvSxFp78my7fjr2j/BdkfFvX+72N2MVWnp2BhGgyEiUh/3iYk0VJ63Fh3DfZiZn0Vacqri63t9HXim/KGQXnva8ykeKd4CiylD8Rykvb0bH8d/+OSX6By5hbXZqxVb1zPQgUPV+xVbj4hW5vP50PLeBfzq6D9gbGwMFosF8zmpeP4H/F4k0hsWU0QaMqakYm32arT6u1SZXO/xdeDVx38c0mvr3S78yaN/qHgGEsOYkoo/2LILb14+gz9/+pAiawbmZtA37kdpboEi6xHR8i5evIijR4/i1KnFXebp6a+7dJpMJjT84k001NbiyJEjqK6uFhWTiL6Bx/yINOZU6d7U7ZkpDE2NoSiEXYm2wW74JobxSPEDiucgcX689Tm81/IJbs9MKbJe22A3inPW8LI7kQaOHz+Ompoa1NfXY3p6+luFFAAEAgFMT0+jvr4eNTU1OH78uKCkRPRNLKaINOa0q3Nv6rq/E+vzir7V+WkpDe5G7HM+GdJrKXbYV+XikbVb0OBuVGQ9Dusl0sbx48dx+PBhTE1NrdiVU5ZlTE1N4fDhwyyoiHSAn6SINOa0l6JZhZ2pljud/FYytzCP95rPsSNUnHplRy3evHwaC8Fg1Gt5w2hoQkSRuXjx4r1CKhx3C6pLly6plIyIQsFiikhj5dYidI30Y3puVtF1vb7OkD74nu/4CoVZdhTnrFH0+aQPW1avh8W0Cp/cvBz1WovdIVcu0IkockePHkUgEIjovYFAAEePHlU4ERGFg8UUkcZSk1NQkluAVn+nouuGeiSrwd2IA5tqFH026YdSbdIXgkG0DXaj3MpiikgtPp8Pp06dinjgtizLOHnyJPx+v8LJiChULKaIBFi8N3VDsfXmFubROdyH9XlFy75ueGocF7ua8NyGhxV7NunPcxseRvtQH677uyJeo3PkFvLSs5CRZlYwGRF904kTJ6JeQ5IkRdYhosiwmCISwGkvUfTe1I2hHqyx2GBMWX521cmWc9hZtoMfkONcSlIyfrj1Gbxx+XTEa/C+FJH6rl69+r2ufeEKBAK4du2aQomIKFwspogEqMwvU7SjnzeEuy2yLPOIXwL5wy3P4IPW32Nkajyi97OTH5H6xsbGFFlnZGREkXWIKHwspogEWJdXiN4xH6Zmo/uL5F2eEHYRPL4OTMwEUFW4UZFnkr7lpluwa10Vfnvto4jeH8p/U0QUHYvFosg62dnZiqxDROFjMUUkQEpSMsryCuFVqAmF19e54i5CvbsRBzbthEHit32ieGVHLX515X3MLcyH9T5Zlu/8N8XmE0Rq2rJlC4xGY1RrmEwmbN68WaFERBQufqoiEsRpL0GzAk0ognIQXl8HNizTdW12fg6nPZ9iX+WTUT+PYkeFrRgOix0fXv88rPf5JhaPDFnT+dduIjUdOnQo6jVkWVZkHSKKDIspIkGc+aVoUqAJRd+YH+lpJmSbM5d8TeONL7A+rwgFFlvUz6PY8vL2WrwRZpt0r68DFfZiSJKkUioiAgCbzYba2tqIv9ckScLevXthtVoVTkZEoWIxRSRIpb0MLf3tUa/j8XWiwlay7Gsa7hzxo8Sza10V/BMjcN8KfRfUs8JOJxEp58iRIzCZTBG912Qy4ciRIwonIqJwsJgiEqQ0twB944OYnA1EtY7H177sB9+B28P4qu86nil/KKrnUGxKMhjw0rbdYQ3xXdyZWr5AJyJlVFdX49ixYzCbwxtZYTabcezYMVRVVamUjIhCwWKKSJCUpGSstxbCM9AR1TpeXycq7MVLfv295k/wbPlDMKWkRfUcil0HN+/CJze/hH8itPbJHl8HKrgzRaSZurq6ewXVSkf+JEm6V0jV1dVplJCIlsJiikggp7006uG9i0eyiu/7NVmW0dDk4hG/BJdpzEBtxaP49ZUPVnzt7ZkpDE2NoSh7tQbJiOiuuro6uFwuHDx4EEaj8XtH/0wmE4xGIw4ePAiXy8VCikgnkkUHIEpklfmluNAZ+eT64alxBOamUWC5/+Xjq7euAwAeWFMe8TMoPry8fQ/+6a/+Nf744ReRlpy65OtafZ1Yn1eEJAP/1kaktaqqKrz11lvw+/04ceIErl27hpGREWRnZ2Pz5s04dOgQm00Q6QyLKSKBnPYy/OffN0T8/rst0Zc6FtLgbsT+yp3sykYoyS1Aha0Ypz2f4sCmmiVf5/FzWC+RaFarFa+99proGEQUAv7pkUigktw18E0M4/bMVETvX25Yb2BuBh+0/h77Kp+IIiHFk1e278Hrl0+jfagX/+nTt+47zNcz0MFhvURERCFiMUUkULIhCRusa+EZiKxFusfXvuQuwofXP8eW1ethy8iJIiHFi6AchAygY6gXP/x//wzHP/1HjE1PfO91Xv/KrfaJiIhoEYspIsGc+ZE3oVhuZ2pxtlRN5MEorrz11Yd49bf/FjMLc5hbmIdBkpCe+u0L7nML8+gc7sO6vEJBKYmIiGILiykiwZz2UjT1h19MBeZm0DfuR2luwfe+1jvmQ6u/CzVlO5SISHHgxc27sKfiURjvNJ8IQr73P991Y6gHBRYbjClLN6ggIiKir7GYIhIs0vbo1we7UJyzBilJ3+8j807TWeze8AhSk1OUiEhxICUpGX/3/D/DTx8+CINkgEEyfK8xidfXseROJxEREX0fu/kRCVacswZDk2MYn55ApjEj5Pd5fZ33vS8VlINocLvwv+3/HxVMSfFAkiT88cMHkW3KxD9c+K/w+Xw4ceIErl69irGxMfRND2NdxXr4H/Sz/TIREVEIWEwRCZZkMKDCXoyWgXY8tHZzyO/zLLGL8EV3C9JTTdhoZxMBur+i2Uykn+nD2v9hsWvf9PT0va81n7+Mt/+vX6G2thZHjhxBdXW1qJhERES6x2N+RDoQyb0pr+/+84Aa3C4c2MTZUnR/x48fR01NDerr6zE9Pf2tQgoApgOL/1ZfX4+amhocP35cUFIiIiL9YzFFpAPh3ptaCAbRNtiNcmvRt/59cjaAxhtf4HknZ0vR9x0/fhyHDx/G1NQUZFle9rWyLGNqagqHDx9mQUVERLQEFlNEOlCZX4rmMGZNdY7cgjU9Gxlp5m/9+xnvZ6gqdCLHnKl0RIpxFy9evFdIheNuQXXp0iWVkhEREcUuFlNEOlCUnY+xwG2MBm6H9HqPrx0bbGu/9+8Nbhde3LRT6XgUB44ePYpAIBDRewOBAI4ePapwIiIiotjHYopIBwySARX2kpCP+t2vk1/HcB+6R/rxWMlW5QNSTPP5fDh16tSKR/uWIssyTp48Cb/fr3AyIiKi2MZiikgnnPYSNIfYhOJ+nfzebnLheefj9507RYntxIkTUa8hSZIi6xAREcUTFlNEOuHMLwvp3pQsy3eGq359zG8hGMQ7TZ/gwKYaFRNSrLp69er3uvaFKxAI4Nq1awolIiIiig8spoh0otJeGtLOlG9iGJJkgDU9+96/Xei8CmtGNtblFaoZkWLU2NiYIuuMjIwosg4REVG8YDFFpBOFWXZMzAYwNLn8B1/PnV2pb86Rqnc3svEELclisSiyTnZ29sovIiIiSiAspoh0QpIkbLQXo2WFJhTfbT4xFpjAZx1XsafiUZUTUqzasmULjEZjVGuYTCZs3rxZoURERETxgcUUkY4sDu9d/t7Ud5tPnPZ8ikeLH0CmMUPldBSrDh06FPUasiwrsg4REVE8YTFFpCOV+WUrtkf3+jqw8RvFVIO7kY0naFk2mw21tbXfOhoaDkmSsHfvXlitVoWTERERxTYWU0Q64rSXoGmZJhS3Z6YwPDWOwqx8AMB1fzcGp0bx8Foev6LlHTlyBCaTKaL3mkwmHDlyROFEREREsY/FFJGOFFhsmJ6fweDk6H2/3urrxHprIZIMi9+6De5G7HM+ee9/J1pKdXU1jh07BrPZHNb7zGYzjh07hqqqKpWSERERxS5+AiPSEUmSFu9NLbE75fG1Y4O1GAAwtzCP91rOYT+7+FGI6urq7hVUKx35kyTpXiFVV1enUUIiIqLYwmKKSGcq80uXvDfl8XWiwl4MADjXfgVrs/OxNnu1huko1tXV1cHlcuHgwYMwGo3fO/pnMplgNBpx8OBBuFwuFlJERETLSBYdgIi+zWkvRYPbdd+veX0d+PHW5wCw8QRFrqqqCm+99Rb8fj9OnDiBa9euYWRkBNnZ2di8eTMOHTrEZhNEREQhYDFFpDNOeymOfvj/fO/f5xbm0TlyC+vyCjE0OYZL3S34m71/KiAhxQur1YrXXntNdAwiIqKYxWN+RDqzOjMPC8EFdI30o7n/JuYW5gEAN4Z6UGCxwZiSivdazmHXuh1IT42sOxsRERERRY/FFJGOXO7x4M/e/Q+Ymp3Ggf/7f8JP/r9/gbbBbgCAZ2BxWK8syzziR0RERKQDPOZHpCNdo/34oPUCgrIMAEhLTsF6axEAwOvvQIWtGM0DNxGYm8F2R4XIqEREREQJjztTRDpyoHInnil/CMmGJADAltXl9/5nj68DFba1aHC7sL9yJwwSv32JiIiIROKnMSIdkSQJ/2bPn8CekQMAeHp9NQAgKAfR6utEcU4Bzng/w/7KJ0XGJCIiIiKwmCLSHWNKKv7TD/9nGCQDdjicAIDeMR8y0sy40uvFButarLGwbTURERGRaLwzRaRDhdn5eP0H/zv+1X9pRttoF27PS5ibfR6Hrzfjnz1fLToeEREREYHFFJHuvPlRM/7uo3GMZG2FLD8IQ5753tdGZ6fw119I+D8/vIA/fyoTP3nKKTApERERUWJjMUWkIz/9uQtnAlVArhGSIQnSd75uSF0srEZyq/FnX0zjo2YXfvHqTu2DEhERERHvTBHpxd1CSkpNh3Sng99SJEMSpNR0nAlU4ac/d2mUkIiIiIi+icUUkQ68+VHzvUIqHHcLql9+3KxSMiIiIiJaCospIh34u4/GgWRjZG9ONuLoh2PKBiIiIiKiFbGYIhLM0+XHSNbWFY/2LUUyJGEkaytauwcVTkZEREREy2ExRSTYX/6mCTKCUa0hyzL+4tduhRIRERERUShYTBEJ1jaaDEOKeeUXLsOQakbbGJtzEhEREWmJxRSRYNNyiiLrBILKrENEREREoWExRSSYUZpTZB2TQZl1iIiIiCg0LKaIBFuXNY/g3FRUawRnp7DOMq9QIiIiIiIKBYspIsH+8oeVkKL8VpQkCX/1o00KJSIiIiKiULCYIhKsosiK7NErkIMLEb1fDi4ge/QKygvzFE5GRERERMthMUWkA3/+VCYwPx3Zm+enceRpi7KBiIiIiGhFLKaIdOAnTzmx23QJ8uxkWO+TZyex23QJL+1yqpSMiIiIiJbCYopIJ37x6s57BdVKR/7k4MK9QuoXr+7UKCERERERfROLKSId+cWrO/H3VZ3IHvoc8lwAwdlvd/kLzk5Bngsge+hz/H1VJwspIiIiIoGSRQcgom97aZcTL+0CWrsH8Re/dqNtKBmBYApMhjmss8zjr360CeWFj4iOSURERJTwWEwR6VR5YR7e/FmN6BhEREREtAQe8yMiIiIiIooAiykiIiIiIqIIsJgiIiIiIiKKAIspIiIiIiKiCLCYIiIiIiIiigCLKSIiIiIiogiwNXoEfD4fTpw4gatXr2JsbAwWiwVbtmzBH/3RH8FqtYqOR0REREREGpBkWV7yi1VVVfKlS5c0jKNvFy9exNGjR3Hq1CkAwPT09L2vmUwmyLKM2tpaHDlyBNXV1aJiEhERERGRQiRJ+kKW5ar7fY3H/EJ0/Phx1NTUoL6+HtPT098qpAAgEAhgenoa9fX1qKmpwfHjxwUlJSIiIiIiLfCYXwiOHz+Ow4cPY2pqasXXyrKMqakpHD58GABQV1endjwiIiIiIhKAO1MruHjxYsiF1DfdLah4TJKIiIiIKD6xmFrB0aNHEQgEInpvIBDA0aNHFU5ERERERER6wGJqGT6fD6dOncJyTTqWI8syTp48Cb/fr3AyIiIiIiISjcXUMk6cOBH1GpIkKbIOERERERHpC4upZVy9evV7XfvCFQgEcO3aNYUSERERERGRXrCYWsbY2Jgi64yMjCiyDhERERER6QeLqWVYLBZF1snOzlZkHSIiIiIi0g8WU8vYsmULjEZjVGuYTCZs3rxZoURERERERKQXLKaWcejQoajXkGVZkXWIiIiIiEhfWEwtw2azoba2FpIkRfR+SZKwd+9eWK1WhZMREREREZFoLKZWcOTIEZhMpojeazKZcOTIEYUTERERERGRHrCYWkF1dTWOHTsGs9kc1vvMZjOOHTuGqqoqlZIREREREZFIyaIDxIK6ujoAwOHDhxEIBCDL8pKvlSQJJpMJx44du/c+IiIiIiKKP9yZClFdXR1cLhcOHjwIo9H4vaN/JpMJRqMRBw8ehMvlYiFFRERERBTnuDMVhqqqKrz11lvw+/04ceIErl27hpGREWRnZ2Pz5s04dOgQm00QERERESUIFlMRsFqteO2110THICIiIiIigXjMj4iIiIiIKAIspoiIiIiIiCLAYoqIiIiIiCgCLKaIiIiIiIgiwGKKiIiIiIgoAiymiIiIiIiIIsBiioiIiIiIKAIspoiIiIiIiCLAYoqIiIiIiCgCLKaIiIiIiIgiwGKKiIiIiIgoAiymiIiIiIiIIsBiioiIiIiIKAIspoiIiIiIiCLAYoqIiIiIiCgCLKaIiIiIiIgiwGKKiIiIiIgoAiymiIiIiIiIIsBiioiIiIiIKAIspoiIiIiIiCLAYoqIiIiIiCgCLKaIiIiIiIgiwGKKiIiIiIgoAiymiIiIiIiIIsBiioiIiIiIKAIspoiIiIiIiCLAYoqIiIiIiCgCLKaIiIiIiIgiwGKKiIiIiIgoAiymiIiIiIiIIiDJsrz0FyXJD6BTuzhERERERES6slaWZev9vrBsMUVERERERET3x2N+REREREREEWAxRUREREREFAEWU0RERERERBFgMUVERERERBQBFlNEREREREQR+P8BTQq0+RIy22oAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%script false --no-raise-error\n",
    "%%time\n",
    "np.random.seed(3454)\n",
    "\n",
    "m = n = 600\n",
    "\n",
    "A = [list(np.random.permutation(range(n))) for _ in range(m)]\n",
    "B = [list(np.random.permutation(range(m))) for _ in range(n)] \n",
    "\n",
    "cost = np.random.randn(m, n)\n",
    "\n",
    "material = assignment(A, B, cost_arr=cost)\n",
    "material.draw_rotation_digraph(method='maxflow', kwargs={'figsize': (15, 15)})\n",
    "plt.gca().texts.clear()\n",
    "\n",
    "# Wall time: 6min 3s"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Multiple assignment examples\n",
    "\n",
    "We can use the proposal algorithm to find stable matchings in many-to-one and one-to-many assignment problems, too. However, the Irving et al. algorithm for rotation through stable matchings cannot be used in this case, as eliminating the rotations may violate the stability conditions (Baïou and Balinski, 2000).\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "([(0, 0), (0, 3), (1, 2), (1, 1), (2, 4), (3, 5)], [[0, 3], [2, 1], [4], [5], []])\n",
      "([(0, 0), (1, 1), (2, 1), (3, 0), (4, 2), (5, 3)], [[0, 1, 4, 3], [1, 4, 3, 0, 2], [1, 4, 3], [0, 1, 3], [2, 1, 3, 4], [3]])\n"
     ]
    }
   ],
   "source": [
    "# Universities with fixed quotas propose to applicants (one-to-many)\n",
    "applicants = [[0,1,4,3],[1,4,3,0,2,],[1,4,3],[0,1,3],[0,2,1,3,4],[0,1,3]]\n",
    "universities = [[0,1,2,3],\n",
    "                [0,2,1],\n",
    "                [0,1,2,3,4,5],\n",
    "                [1,0,3,2,4,5],\n",
    "                [0,1,2,3]]\n",
    "\n",
    "university_capacities = [2, 2, 4, 4, 3]\n",
    "\n",
    "admissions = assignment(applicants, universities, reviewer_capacity=university_capacities)\n",
    "print(admissions.proposal(reverse=True))\n",
    "\n",
    "# Applicants propose to universities with fixed quotas (many-to-one)\n",
    "print(admissions.proposal())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cost function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0.37237552  0.12791554  0.52721226 -0.3707729   1.75044345]\n",
      " [ 0.37902089  0.18706375  0.68037359 -1.22451047  1.23012957]\n",
      " [-0.48360123 -1.11492177  1.42741881 -0.53488605 -0.91212697]\n",
      " [-0.9135388  -1.82906774 -0.99341399 -1.27539239 -1.17459533]\n",
      " [-0.80590751  0.73995612 -0.2997519   0.08830975  0.59831814]\n",
      " [-0.11749066 -0.22978487  1.58119242 -1.33964861 -0.83135589]]\n",
      "-3.108421803000054\n",
      "-4.076997308638162\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(87)\n",
    "\n",
    "# Sum-of-ranks cost of proposal assignment\n",
    "admissions.cost()\n",
    "\n",
    "# Supply an array of arbitrary costs \n",
    "cost = np.random.randn(6, 5)\n",
    "print(cost)\n",
    "\n",
    "# Arbitrary cost of proposal assignment\n",
    "print(admissions.cost(cost_arr=cost))\n",
    "\n",
    "# Arbitrary cost of an arbitrary assignment\n",
    "print(admissions.cost(pairings=[(0, 3), (1, 3), (2, 1), (3, 3), (4, 1), (5, 4)],\n",
    "                cost_arr=cost))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Behavior when no rotations are present"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "([(0, 0), (1, 1), (4, 3)], [[0, 1, 2], [1, 3], [], [], [3]])\n",
      "([(0, 0), (1, 1), (3, 4)], [[0, 1, 2, 4, 3], [1, 4], [], [4]])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[[], [], [], [], []]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Men propose to women (one-to-one)\n",
    "# Contains only one stable matching\n",
    "men = [[0, 1, 2],\n",
    "       [0, 1, 3],\n",
    "       [1, 0, ],\n",
    "       [0, 1],\n",
    "       [1, 0, 3]]\n",
    "women = [[0, 1, 2, 4, 3],\n",
    "         [0, 1, 4,],\n",
    "         [0, 2, 1, 3],\n",
    "         [1, 0, 4]]\n",
    "\n",
    "marriage = assignment(men, women)\n",
    "print(marriage.proposal())\n",
    "print(marriage.proposal(reverse=True))\n",
    "\n",
    "# Empty output expected\n",
    "marriage.rotation_digraph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No rotations to graph\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(None,\n",
       " [(0, 11), (1, 7), (2, 12), (3, 6), (4, 10), (5, 4), (6, 2), (7, 1), (8, 5)])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "applicants = [[11, 12, 10, 8, 9, 7, 6, 5, 4, 3, 2, 1, 0],\n",
    "              [11, 10, 12, 9, 6, 8, 7, 5, 1, 4, 3, 2, 0],\n",
    "              [12, 10, 9, 11, 8, 7, 6, 5, 4, 1, 0, 3, 2],\n",
    "              [11, 12, 9, 10, 8, 6, 7, 5, 2, 4, 3, 1, 0],\n",
    "              [11, 12, 10, 9, 7, 6, 8, 5, 4, 2, 1, 3, 0],\n",
    "              [9, 11, 12, 10, 8, 7, 6, 5, 4, 3, 2, 1, 0],\n",
    "              [12, 9, 10, 11, 7, 8, 6, 5, 2, 1, 0, 4, 3],\n",
    "              [12, 11, 9, 10, 8, 7, 6, 5, 1, 4, 3, 2, 0],\n",
    "              [12, 11, 10, 9, 7, 8, 6, 5, 3, 2, 4, 1, 0]]\n",
    "\n",
    "firms = [[0,2,8,3,4,7,1,6,5],\n",
    "         [2,0,8,4,7,3,6,1,5],\n",
    "         [0,8,2,4,1,3,7,5,6],\n",
    "         [2,3,0,7,8,4,5,6,1],\n",
    "         [0,2,3,8,4,1,7,5],\n",
    "         [0,2,8,4,3,1,5],\n",
    "         [2,0,3,8,1],\n",
    "         [0,2,1,4],\n",
    "         [0,2,4],\n",
    "         [0,2],\n",
    "         [2,4],\n",
    "         [0,2],\n",
    "         [2,0]]\n",
    "\n",
    "hiring = assignment(applicants, firms)\n",
    "\n",
    "# Empty output expected\n",
    "hiring.draw_rotation_digraph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[NbConvertApp] Converting notebook assignment_exs.ipynb to html\n",
      "[NbConvertApp] Writing 699353 bytes to assignment_exs.html\n"
     ]
    }
   ],
   "source": [
    "!jupyter nbconvert --to html assignment_exs.ipynb"
   ]
  }
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