Seabones.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "30bdee9c-f3de-468c-972e-8ef82882f931",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "/home/x38fed/.local/lib/python3.11/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f48bd4da090>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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vHEZ+DQHRTuuiVD8FFSIiIiIiIuI8/pFw+SvQ6MKS7W6ecNMCCG/pnH6J0yioEBEREREREefKTYfkXSXbrPmQvKdkgU2pExRUiIiIiIiIiPMUFs5MO1iy3W6DL0bArl8UVtQxCipERERERETEOXIzYMOskjUp7l5esmbFoscgK8lpXZTq5+bsDoiIiIiIiEgd5ekH3e6CzETY/j2MPlGT4vKXjfsPrYMbVUyzrlFQISIiIiIiIs7jFwb9noDeD0JII6PNP9IIKwpyILiRM3snTqCgQkRERERERJzLLwwIK9nmH+mUrojzqUaFiIiIiIiIiLgMBRUiIiIiIiIi4jIUVIiIiIiIiIiIy1BQISIiIiIiIiIuQ0GFiIiIiIiIiLgMBRUiIiIiIiIi4jIUVIiIiIiIiIiIy1BQISIiIiIiIiIuQ0GFiIiIiIiIiLgMBRUiIiIiIiIi4jIUVIiIiIiIiIiIy1BQISIiIiIiIiIuQ0GFiIiIiIiIiLgMBRUiIiIiIiIi4jIUVIiIiIiIiIiIy1BQISIiIiIiIiIuQ0GFiIiIiIiIiLgMBRUiIiIiIiIi4jIUVIiIiIiIiIiIy1BQISIiIiIiIiIuQ0GFiIiIiIiIiLgMBRUiIiIiIiIi4jIUVIiIiIiIiIiIy1BQISIiIiIiIiIuQ0GFiIiIiIiIiLgMBRUiIiIiIiIi4jIUVIiIiIiIiIiIy1BQISIiIiIiIiIuQ0GFiIiIiIiIiLgMBRUiIiIiIiIi4jIUVIiIiIiIiIiIy3DpoMJqtfLGG2/Qr18/2rVrxyWXXMK7776L3W53dtdERERERERExAHcnN2BikydOpVZs2bx8ssv06xZMzZv3sxjjz2Gv78/o0ePdnb3RERERERERKSKuXRQ8ffff3PxxRdz0UUXARAbG8vChQvZuHGjczsmIiIiIiIiIg7h0kFFx44dmT17Nnv27KFx48Zs3bqVtWvXMmHChEo/l9VqdUAPa7/CcdP4VT2NrWNoXB1HY+sYzhhXi8VyTo/Xz8DZ0f8hx9HYOobG1XE0to5RE6+pUjaT3YULPthsNl5//XU+/PBDLBYLVquVBx98kDvvvPOMn8NqtbJ+/XrHdVJERKSG6dy581k9TtdUERGRks72mioVc+kZFT/88AMLFizgtddeo1mzZmzZsoUXX3yR8PBwrr766ko9V9u2bZV2nQWr1cqmTZs0fg6gsXUMjavjaGwdoyaOa03qqyupif/WNYXG1jE0ro6jsXUMjWvt4dJBxSuvvMIdd9zBwIEDAYiLi+PQoUO8//77lQ4qLBaLfljPgcbPcTS2jqFxdRyNrWPUpHGtSX11RRo/x9HYOobG1XE0to6hca35XHp70pycHEwmU4k2i8Wi7UlFREREREREaimXnlHRt29f3nvvPaKjo4uWfnz88ccMGzbM2V0TEREREREREQdw6aDiiSee4M033+Tpp58mKSmJ8PBwhg8fzj333OPsromIiIiIiIiIA7h0UOHn58fEiROZOHGis7siIiIiIiIiItXApWtUiIiIiIiIiEjdoqBCRERERERERFyGggoRERERERERcRkKKkRERERERETEZSioEBERERERERGXoaBCRERERESkKmWnQOqBkm2ZiaXbRKRMCipERERERESqSnYKrJsBX4yAlHijLSsJ/noH5t4JqQed2j2RmkBBhYiIiIiISFXITYcNX8BPT8LhDfDljZB2EP58G/6cBPuWwdw7MGUcdnZPRco1YcIExo4d69Q+uDn17CIiIiIiIrWFhx/UP9/4Oy/DCCveaAe2guJj2gwFdz/gqNO6KeLqNKNCRERERESkKphMEN0JbppvhBVQMqQY+Dq0vRa7p79z+ifiBHl5eZV+jIIKERERERGRqmIyQUgTaNSrZLuHH7QYAF4BzumX1FiLFi1i8ODBtGvXjm7dunHzzTeTlZVVtETjvffeo2fPnnTp0oV33nmHgoICXn75Zbp27cqFF17I119/XeL5tm3bxujRo4ue78knnyQzM7Pc82/cuJHu3bvzwQcfAJCWlsbEiRPp3r07nTp1YvTo0WzdurXo+LfffpshQ4bw1Vdf0a9fP9q1a1fp71lBhYiIiIiISFXJSoJlb8L2xSXb8zJKFtgUOQPHjh3joYceYtiwYXz//ffMmDGD/v37Y7fbAVixYgXHjh3j008/ZcKECbz99tvceeedBAYGMnv2bK6//nr++9//cuTIEQCysrIYM2YMgYGBzJkzhzfeeIO//vqLZ599tszzL1++nFtvvZUHH3yQO+64A4D777+fpKQkpk6dyty5cznvvPO46aabSElJKXpcfHw8ixcv5p133mHevHmV/r4VVIiIiIiIiFSFnHRY87FROLNQx1HFy0BOFNg0ZRxxTv+kxklISKCgoID+/fsTGxtLXFwcI0eOxNfXF4CgoCCeeOIJmjRpwjXXXEPjxo3JycnhrrvuolGjRtx55524u7uzdu1aAL777jvy8vJ4+eWXadGiBT169OCpp57i22+/JTExscS5f/rpJ8aOHcszzzzD8OHDAVizZg0bN27krbfeom3btjRq1IhHH32UgIAAFi8uDufy8/N55ZVXaN26NS1btqz0961imiIiIiIiIlXByx9aXAbL34Hs40ZNinbDofMtMONKY1ZFz/uwewYACivk9Fq2bEmPHj0YPHgwvXv3pnfv3gwYMIDAwEAAmjVrhtlcPP+gXr16NG/evOi2xWIhKCiIpKQkAHbt2kVcXBw+Pj5Fx3Tq1AmbzcaePXuoV68eYCz3+O2333jrrbe45JJLio7dtm0bWVlZdOvWrUQ/c3JyiI8vni0UHR1NSEjIWX/fCipERERERESqSmQbuOk7OLQeWl8Jnn4Q0wlGz4eUvdDicrB4OruXUkNYLBY+/vhj1q1bx59//snMmTOZNGkSs2fPBsDNreRbepPJVGabzWar1Hnr169PUFAQc+bMoU+fPri7uwOQmZlJWFgYM2fOLPUYf//iIrHe3t6VOt+ptPRDRERERESkKkW2gTbDigtnmkxGWBF3BXj4VPxYkVOYTCY6d+7MuHHjmDdvHu7u7ixZsuSsnqtp06ZFsyIKrVu3DrPZTOPGjYvagoODmT59OvHx8TzwwAPk5+cDcN5555GYmIjFYqFhw4Yl/pzLDIpTKagQERERERGpah6nfKJsMoH7uX3KLHXPhg0beO+999i0aROHDh3ixx9/JDk5mSZNmpzV8w0ePBgPDw8mTJjA9u3bWbFiBc8++yxDhgwpWvZRKDQ0lOnTp7N7924eeughCgoK6NmzJx06dOCee+5h2bJlHDhwgHXr1jFp0iQ2bdpUFd8yoKBCRERERERExCX5+fmxevVq7rjjDgYMGMAbb7zBhAkT6NOnz1k9n7e3N9OmTSMlJYVrrrmG+++/nx49evDkk0+WeXxYWBjTp09n27ZtPPzww9hsNj744APOP/98HnvsMS677DLGjx/PwYMHSwUd58JkL9zXpJayWq2sX7+eDh06YLFYnN2dGkfj5zgaW8fQuDqOxtYxatK41qS+uiKNn+NobB1D4+o4GlvH0LjWHppRISIiIiIiIiIuQ0GFiIiIiIiIiLgMBRUiIiIiIiIi4jIUVIiIiIiIiIiIy1BQISIiIiIiIiIuQ0GFiIiIiIiIiLgMBRUiIiIiIiIi4jIUVIiIiIiIiIiIy1BQISIiIiIiIiIuQ0GFiIiIiIiIiLgMBRUiIiIiIiIidZzdbufmm29mzJgxpe777LPP6NKlC0eOHKmWviioEBEREREREXFBVpud5buS+Hb9QZbvSsJqszvsXCaTiRdffJENGzbwxRdfFLXv37+f//u//+OJJ54gMjLSYec/mVu1nEVEREREREREztiizYd5esG/HE7NKWqLCvTiv4Nbc1mbKIecMyoqiokTJ/LMM8/Qq1cvYmNjmThxIr169aJ169bcdtttrF27Fm9vb3r16sVjjz1GSEiI0d9Fi3j33XfZt28f3t7etGrVismTJ+Pj41PpfmhGhYiIiIiIiIgLWbT5MHd/uq5ESAFwJDWHuz9dx6LNhx127quvvpoePXrw+OOP8+mnn7Jjxw6eeeYZbrrpJlq3bs2cOXP48MMPSUpK4oEHHgDg2LFjPPTQQwwbNozvv/+eGTNm0L9/f+z2s5sBohkVIiIiIiIiIi7CarPz9IJ/Kestvh0wAU8v+Jf+rSOxmE0O6cOzzz7LwIEDWbNmDW+//TZffPEFrVu3Zvz48UXHvPDCC/Tp04c9e/aQlZVFQUEB/fv3JyYmBoC4uLizPr+CChEREREREREXsWpPcqmZFCezA4dTc1i1J5keTUMd0ofQ0FCGDx/Ozz//zCWXXML8+fNZuXIlHTt2LHVsfHw8vXv3pkePHgwePJjevXvTu3dvBgwYQGBg4FmdX0GFiIiIiIiIiIs4ll5+SHE2x50tNzc3LBYLAFlZWfTt25eHH3641HFhYWFYLBY+/vhj1q1bx59//snMmTOZNGkSs2fPpn79+pU+t2pUiIiIiIiIiLiIcH+vKj2uKpx33nns2LGDmJgYGjZsWOJPYbFMk8lE586dGTduHPPmzcPd3Z0lS5ac1fkUVIiIiIiIiIi4iK6NQ4gK9KK86hMmjN0/ujYOqbY+jRgxgtTUVMaPH8/GjRuJj49n6dKlPPbYY1itVjZs2MB7773Hpk2bOHToED/++CPJyck0adLkrM6npR8iIiIiIiIiLsJiNvHfwa25+9N1mKBEUc3C8OK/g1s7rJBmWSIiIpg1axb/93//x5gxY8jLyyM6OpoLLrgAs9mMn58fq1evZvr06WRkZBAdHc2ECRPo06fPWZ1PQYWIiIiIiIiIC7msTRRTbuzE0wv+LVFYMzLQi/8Obs1lbaIc3of77ruP++67r+h2o0aNeOedd8o8tmnTpkybNq3Kzq2gQkTEUbKSwaeMKXnltYuIiIjUVakHwDsEPHxOajsIvvXAzdN5/XKiy9pE0b91JKv2JHMsPYdwf2O5R3XOpHAW1agQEXGE4/vgm7sgaVfJ9sTt8O1YSIl3Tr9EREREXE3CNvjwEti6EPKyjLYjm+GDC2HXr1CQ69z+OZHFbKJH01CGdIihR9PQOhFSgIIKEZGqd3wffD4cdiyGmVcVhxWJ22HGENj2A3w5SmGFiIiIyPG9MONKSD8Mc28zwoqj/8D0QZCZCF/cAPv+Arv9tE8ltYeCChGRqpSZBAvGQcIW43ZKvBFWxK8wQoq0Q0b74fWw6HFjGYiIiIhIXeXuCy0uL7499zZ4rxdkHzduBzeG4EZgqhszCcSgoEJEpCr5hsLlr4B/ZHFbSjx8NKA4pAAIagD9n1atChEREanb/MKg70TofEtxW+HsiZCmcOPXENLYOX0Tp1FQISJS1cLiYPT8kmHFyYIawKh5ENq0WrslIiIi4pL8wqDLraXbO98EfhHV3x9xOgUVIiKOEBYHw8rZoumajxRSiIiIiBQ6stmoU3Gqn54qWWBT6gwFFSIijpC4HebeXvZ9c8aU3g1EREREpC46vs8onFlYkyKkKbQaUnz/3Ntg7zIV06xjFFSIiFS1wt09Tq5JcbKUfTDzaoUVIiIiIh5+xfUpCmtSDHq9uC2qPYS3VDHNOsbN2R0QEalVMpPg+0dKhhSB9WHoBzDnFkg/YrSl7DOmMw55B7yDndNXERGptOTMXKw2CPByw9Pd4uzuiNR8vqHQ417wC4cWlxUXzuw70djto81Qo76X1CmaUSEiUpV8Q2HQm1AvzrgdWB9Gz4OGPUsW2IxoC5e9qJBCRKSG2JuYyfS/9nDd+yu4evKfTPxmExsPpJCZW+DsrpUpOTOPzQdTWbE7iW1H0knPyXd2l0TK5xsKnW8tubuHXxh0u1shRTWbMGECcXFxfPDBByXalyxZQlxcXLX1QzMqRESqWkgjGDkbFj4El78Moc2M9sLdQH58Aga+pguviEgNse1IGiOmriQpM6+obc7xg8xZd5AXr27LkI7R+Hi4zsvq7UfTeeCLv/n3cHpRW7+W4Twz5Dxig32c2DORCrh7nllbXVKQC/tXQqMLjKUvdjvsXQr1u4Gb48bG09OTqVOnMnz4cAIDAx12nopoRoWIiCMEN4KhU4tDikJhcXD1ewopRERqiKSMXMbNWl8ipDjZY99sYk9iZjX3qnz7k7MYOXVliZAC4Jetx3jwy/UkZeQ6qWciUikFuTBrBEwfDIseA5sNFk0wbs8aYdzvID179qRevXq8//775R6zePFiBg4cSJs2bejXrx8fffRRlfZBQYWIiKP4hJTTHlq9/RARkbN2MCWbbUfTKzxmzpoDWK22aupRxTYeSCGhnDBi9d7jHEzJruYeiUilFYYUu38xbq+cAu9fACvfM27v/sWhYYXZbGb8+PF8+umnHDlypNT9mzdv5oEHHuCKK65gwYIF3Hvvvbz55pvMnTu36vpQZc8kIiIiIlLLHE3LOe0xa/YdJzPfWg29Ob2l2xMrvH9vUlY19UREztr+lbBrCdhPCkCPbi7+2m4z7t+/ymFd6N+/P61ateKtt94qdd/HH39Mjx49uOeee2jcuDFDhw5l5MiRTJs2rcrOr6BCRERERKQc3u6nrz3h5+WGu9k1tk4MD6h43XqAl+vU0hCRcjS6ALrdVfEx3e6GRr0d2o2HH36YefPmsWvXrhLtu3fvplOnTiXaOnXqxL59+7Baqya0VVAhIiIiIlKO+iHeeJ9mG9KbezbC20WKaV56XmS593m7W2hcz7caeyMiZ8VkggEvQkSbsu+PaAMDXjCOc6Dzzz+f3r1789prrzn0PGVRUCEiIiIiUo7oQG8eHlD+lnzNw/1oG+OcqvhlaRDqw0OXtijVbjbBm9d3IDrI2wm9EpFKsdth8WMll3uc7OhmWPy4cZyDPfTQQ/z666/8/fffRW1NmjRh3bp1JY5bt24djRo1wmKpONg9U64R/YqIiIiIuCB3NzNXd4zBw83Mq4u2kpZTABgfZF7SKoInB7Z2qTf/AV7ujO7RiB5NQpm+fC/xSVl0qB/E8PPr0yzcD3eLPqcUcXl7lxYXzizPyinQciA0vsChXYmLi2Pw4MHMnDmzqO3WW2/lmmuu4d133+WKK65g/fr1fPbZZ/z3v/+tsvMqqBARERERqUCIrwcjujbgohZhHE7NocBmo56fJ9FB3vh5ut7L6UBvd7o0CqFdbCC5BTZ83C1YFFCI1Bz1u0HTS4zdPQoLaka0KZ5hYTJDk35Qv2u1dGfcuHF8//33RbfPO+883njjDd566y2mTJlCWFgY48aNY+jQoVV2Ttf7zSoiIiIi4mIsZhP1Q3yoH+Lj7K6cMQ83Cx5uVTMNW0SqkZsn3PC5sQXpriVG4cwBLxjLQVa+Z4QUN3xuHFfFXnrppVJtsbGxbN5cchnKgAEDGDBgQJWfv5CCChERERERERFXUhhW7F9l7O5hMsFlL0HLQcZMCgeEFK5EQYWIiIiIiIiIq3HzLFmDwmRyeE0KV6HFaiIiIiIiIiLiMhRUiIiIiIiIiIjLUFAhIiIiIiIiIi5DQYWIiIiIiIiIuAwFFSIiIiIiIiLiMhRUiIiIiIiIiIjLUFAhIiIiIiIiIi5DQYWIiIiIiDiO3Q5ph4y/C1kLIO2g8/okUgtMmDCBsWPHOrsbDuHyQcXRo0d5+OGH6datG+3atWPw4MFs2rTJ2d0SEREREZHTsdvh0Dr4oA8cXGvcthbAgVXwQV84otf1Imdr4sSJvPTSS87uhkO4ObsDFUlNTeWGG26gW7duTJ06leDgYPbt20dgYKCzuyYiIiIiIqdzZBNMvxLyMmDGlTB6PljzYOZVUJAL0wfDLT9AeCtn91SkxvH393d2FxzGpYOKqVOnEhkZyYsvvljUVr9+fSf2SEREREREzph3MNRrDof+hrxM+GgAYAeb1bg//DzwDHBqF0Vc3aJFi3j33XfZt28f3t7etGrVismTJ/PMM8+QlpbG5MmTOXDgABdffHGpx3bt2pWZM2cCsGbNGl5//XU2b95McHAw/fv3Z/z48fj4+FT3t3RaLh1U/PLLL/Tu3Ztx48axevVqIiIiGDFiBNddd12ln8tqtTqgh7Vf4bhp/KqextYxNK6Oo7F1DGeMq8ViOafH62fg7Oj/kONobCvBbseccQi7ZwB2D+PTWFP6YbDbsAfElDi0SsbVPxrTtTMwfTUa06G/wVZQ3JWGvbFf/T52v0ioY/92+pl1jJp4TT2dY8eO8dBDD/HII49wySWXkJmZyZo1a7CfXPMFiIqKYtmyZUW3ExMTufnmm+nSpQsA8fHx3H777dx///288MILJCcn8+yzz/Lss8+WmBjgKkz2U79DF9K2bVsAbrnlFi677DI2bdrE888/z9NPP83VV199Rs9htVpZv369A3spIiJSs3Tu3PmsHqdrqkjN5unhQTPfDLy+uIb8Cx/jcERfAjxNBPz8H8jPIuPyd9iZkFPqDdC58vH2omnBdjzm3lyiPe+Gr9mRH0FObl6Vnk+kOp3tNfVM/fPPPwwdOpRffvmFmJiSYeKECROKZlScLDc3l1GjRhESEsLkyZMxm81MnDgRi8XCM888U3TcmjVrGDVqFOvXr8fT09Oh30dlufSMCrvdTps2bRg/fjwArVu3ZseOHXzxxRdnHFQUatu2rcPTrtrIarWyadMmjZ8DaGwdQ+PqOBpbx6iJ41qT+upKauK/dU2hsT0zpsxjmGeOgbwM3JdMpH7fibDnD0z7lgLgv3sh7bvfA27GG5YqGVebFfPBVZg+vbPUXR5fj6b1qG+xRXUAk8vX+K9S+pl1jNo4ri1btqRHjx4MHjyY3r1707t3bwYMGFBh3cbHH3+czMxMPvroI8xm4//W1q1b2bZtGwsWLCg6zm63Y7PZOHDgAE2bNnX491IZLh1UhIWFlRqwJk2asHjx4ko/l8ViqTU/rM6g8XMclxzbvEzw8D3pdhZ4uN7atYq45LjWEhpbx6hJ41qT+uqKNH6Oo7E9jYAoGP4ZzBgCaQcx/fp88X3thmPqNBqLZ+nr/TmN69GN8OlQo3AmQMz5YM0ximzmZWKaOQTLbUsgvPXZPX8Np59Zx6hN42qxWPj4449Zt24df/75JzNnzmTSpEnMnj27zOMnT57MsmXL+Oqrr/Dz8ytqz8rK4vrrr2fUqFGlHhMVFeWw/p8tl44uO3XqxJ49e0q07d27t9SUFxGpQplJsOpDSNxu3E7ZD3+8AmmHndsvEREROXf1msONX5dsC4iBS58D/4iqP59vONTvZnzd6AK4bjpcPwuiOxptjfsaBTdFpFwmk4nOnTszbtw45s2bh7u7O0uWLCl13OLFi5k8eTJvvPEGDRo0KHFf69at2blzJw0bNiz1x8PDo7q+lTPm0kHFTTfdxIYNG3jvvffYt28fCxYsYPbs2YwYMcLZXROpnawFsG0hLHnK2Ers8Eb46mZYNgl+fwVy0pzdQxERETkXqQfhh/+UbEs7CP9845jrfGAMXPUe9H4Qrn7PuB1UH66bCb3Hw6D/A3/X+zRXxFUUvh/etGkThw4d4scffyQ5OZkmTZqUOG779u08+uij3HbbbTRr1oyEhAQSEhJISUkB4Pbbb+fvv//mmWeeYcuWLezdu5clS5aUqFnhSlx66Ue7du145513eP3113n33XeJjY3l8ccf58orr3R210RqJ4sbNO0HDXpC/F/w/gVGe2B96HkPeGn7MBERkRor7TB8Oxb2/GHcbnoxJGw1goof/gPu3tD2WuPvqhQYAxf+p+Qy0qD6cOEjNW5pqUh18/PzY/Xq1UyfPp2MjAyio6OZMGECffr04Ycffig6bvPmzWRnZzNlyhSmTJlS1F64PWnLli2ZOXMmb7zxRtEH//Xr1+eKK66o9u/pTLh0UAHQt29f+vbt6+xuiNQdgbHGJx5vtituGzoVQps5r08iIiJy7ryCoPPNsOd3aHudsdwjJ9WoWWHNg9jzqz6kKFRWIKGQQuS0mjZtyrRp08q876WXXir6eujQoQwdOrTC52rXrh0fffRRlfbPUVw+qBCRapayH+bcWrJtzi1w03yo18I5fRIREZFz5+ENzS+DW3+CoAbgF278GT0fbAUQ3tLZPRQRAVy8RoWIVDNrgfEpy8E1xnKPsSuMZSDph2HlB6pRISIiUtN5eEP980sWzqzXTCGFiLgUzagQkWIWN4gbCJdnQrOLjeUew6bC+s+h02jVqBAREREREYdTUCEiJfkEQ6ebwN3LuB0YC73GgZuXc/slIiIiIiJ1goIKESnN/ZRQQiGFiIgIAPuSMlm6I5Hftx+jff0gLjsviqZhvphMJmd3zSEsFotRv8JiKXlHQT64uTunUyJS6ymoEBERERE5A3sTMxn+wXKOpuUC8NO/x5jy6y7m3N2TVlG1c3lki1Az5q3fQYtLwdPfaDy2BZL3QNO+jtslRETqNBXTFBERERE5jQKrja/W7C8KKQpl5ll5ZfE2MnILnNQzxzEf343PnBGYvr4V/vkWcjONkGL6IPhyBOz4CfKznd1NEamFznpGxaZNm9i1axdg7O3atm3bKuuUiIiIiIgrSc8pYPG/R8u8b9mOBFKz8/HzrEWTlfOy4N9vIXW/cXv+PZC4DTZ8DpmJRttPT0JMZwiMcV4/RaRWqvRv0yNHjjB+/HjWrVtHQIAxxS0tLY2OHTsyadIkIiMjq7yTIiIiIiLO5OlmJirQi53HMkrdF+7vhbu5ltWo8PDB3nE01rRjuK1532j7663i+4MawI1zFVKIiENUeunHxIkTKSgo4Pvvv2fVqlWsWrWK77//HrvdzsSJEx3RRxERERERp/LxdOOevs3KvO/B/s0JD6h9haftPqEktx2DveWgkne4ecLo+RDa1DkdE5Far9JBxerVq/nf//5HkyZNitqaNGnCE088wZo1a6q0cyIiIiIirqJNdADvjOhImL8nAP6ebjw5sBV948Kd3DPH8TdlYdq/omRjQS7s/RNy053TKRFxqNWrV3PXXXfRu3dv4uLiWLJkSbX3odJLP6KioigoKF0syGazER5ee39Ji4iIiEjd5uflzqB20XRuEEx6TgHenhaiA72x1LZlHyeYE7fh/eU1xTUpTjb/HuPv84YU7wYiIrVCVlYWcXFxDBs2jHvvvdcpfaj0jIpHHnmEZ599lk2bNhW1bdq0ieeff55HH320SjsnIiIiIuJqooK8aRHpT/1gn1obUpCXCbt/Kw4pghrAuPXQfWzxMcvfgZw0Z/ROpE7Jycnh4MGD5OTkVMv5+vTpw4MPPkj//v2r5XxlqfSMiscee4zs7Gyuu+46LBYLAFarFYvFwuOPP87jjz9edOyqVauqrqciIiIiIlI9PHyxtxuONSsFt02zYNQ8CGkMFzxk3L/rVxjxpYppijiQ1Wrl/fff5/PPPycnJwcvLy9GjBjBnXfeWfRevLaqdFBxchAhIiIiIiK1k90riCMNrySm00hMwQ2NRt96RljR/W5jloWIOMz777/PRx99VHQ7Jyen6PbYsWPLe1itUOmg4uqrr3ZEP0RERERExMUcTc0lqnErSnx261vPWd0RqTNycnL4/PPPy7xv1qxZ3HrrrXh51b7dhgqdUVCRkZGBn59f0dcVKTxORERERERERCovKSmp3JoU2dnZJCUlERNTe5denVFQcf7557Ns2TJCQ0Pp0qULJlPpokF2ux2TycSWLVuqvJMiIiIiIiIidUVoaCheXl5lhhXe3t6EhoY6oVfV54yCiunTpxMYGAjAiy++SGRkZKniHTabjcOHD1d9D0VERERERETqkMLCmSfXqCh0ww03OHTZR2ZmJvHx8UW3Dxw4wJYtWwgMDCQ6Otph5z3ZGQUVXbt2Lfr68ccfL5pdcbLjx49zyy23qIaFiIiIiIiIyDm68847AaMmRXZ2Nt7e3txwww1F7Y6yefNmRo8eXXT7xRdfBIx6lS+99JJDz12o0sU0C5d4nCorKwtPT88q6ZSIiIiIiIhIXWaxWBg7diy33norSUlJRctBHK1bt25s27bN4eepyBkHFYUpislk4o033sDb27voPqvVysaNG2nZsmXV91BERERERORkuRmQkwKBscVt2amQm6ptU6XW8fLyqtWFM8tyxkHFv//+CxgzKrZv3467u3vRfR4eHrRs2ZJbb7216nsoIlKbZBwDv/DTt4mISJ2UV2DFzWzGbC49g1lOyM2ALfPhx4lw03cQcZ4RUqz/HP56E26aD/VaOLuXInIOzjiomDlzJgCPPfYYEydO1DakIiKVlbwX5t4OA1+DqHZGW+JO+OZ2GDIFwjUrTUSkLsrOs7I/OYsfNh9m1d5kQnw8GdGtPk3D/AgPcPw07yKZSZCXAcENi5o8PDwwpx8E72Dw9K++vpTHWgC7foZ5dxu3pw8ywordf8DiCSfaroRbF5f4PkSkZql0jYrCJSAiIlIJyXvh8+sgcRtMHww3LQAPH5h5FaTuhxmDYfQChRUiTnQ4JZv03AK8PSxEB3pj0SfaUg2y8gr4YdNhHp6zEbu9uH3BxkN0axzCpOEdiA7yLv8JqkpmEix/BzbNhlHzoF5zAJr7ZWGacgUMeBHOG+L8sMLiBpFtIaQJJO+GrGSY0rPkMZ1ucn4/ReScmJ3dARGROicnBT65AqZdaoQUIuJUmbn5LNx4mCvf/ZNLJ/3BFW8s5ZM/95CUkevsrkkdsPNYBg99VTKkKLRyTzLv/LKD3HyrYzuRmWiEFMteh9QDRoieuAPz0Y14fXEN5KbB/Hvgn3mQk+7YvpyJkCZw49fG36fqMwG63Qk+IdXfLxGpMgoqRESqQ0gjGDG7eM1sbjpkJRlf+4VrNoWIE/1zKJ17Pl9HQroRTKTnFvDswi38vPWYk3smtV1OvpWP/9xb4TFfrT3AwZRsx3bEZAa3k3bvSz0A0/pj+mSgEVIUcvMEs4u8ffCpBy0Hl25vNVghhUgt4CK/aURE6oCQRjD0g9LtAycppBBxkqy8Aqb8trPM+yb9tJ1jaTnV3COpS1Kz81m2M7HCY/KtdhIcPbvHJwS63gkXPVbcln0c8jKLbw96E5r0BQ9fx/blTGSnwt+fGYUzTzVjMBz9p/r7JCJVSkGFiDhWZiLkl/FJUEaCURCrLkncCV+OKt3+7T1weFP190dEyM23lftp9bH0XPKttmrukdQlJsDDcvqX4xZTNdRL8fSH1kOgxWWl7+txD8T/CZvmGCGBM1kLYMePxYUzATrdXLwMJCvZKLCZEu+U7slZsNuN14WnsuaX3S51goIKEXGczERY+n+wc0nJsCL9CCyaAPtX1J2wImlXceFMAJ9QCKxvfJ2TYryoOlKDw4r0I3BgDeSf9OlzQT4cXAtph874aQqsNuKTsthyOI3dCRlk5daRnw9xmgBvdy5tHVnmfb2b1iPA273M+8SFJe2EY1tKtmUlw/5Vzn+TfYpQP0+GdYqp8JhAb3ciA6th54+CHGO77H1/lb7v328h7go4vB4Kshzfl4pY3KBBV4hoa9y+8FG45H8wck5xWHHho+AVCHnZxvckrstuN36u5o01lhwVsuZD/HJY/LjxGkPqHAUVIuIYmYnwx6uwYgrMHlUcVqQfgYUPw+Y58OnQGhVWpGTlcSglm7Ts/Mo/2OIBvuHG137hcPNCuPm74poVXgHg7lN1na1O6Udg0WMwrb+xZVx+jhFSxP8JHw2Ab+89o7DiwPEsXlm8jcve/IPL31zKJa//zgNfrmfr4TRstjKqzIlUAYvZxDWdY4kI8CzR7uNh4dHLW+LvpaCiprBYLJiP74EZVxm7KxWGFVnJsOI943fU+k8rDityM4q/zsty6PXpeGYeR9NyGNQ+Gl8PS7nHPXRpC6IDq2HXj6Sd8OWNJWtSFEo9AD8+Ab0fAP+okvcl7zHC+EKZSXD035LBdVULagg3fAaD3oDudxnLUVLi4fJXYci70OEGMHsYMy9+egrSjzquL3L2CkOK6YNh54/w9e3Gz5q1wAgpPh1m7ELzw6MKK+ogBRUiUvXsdti7DFa+V3x79ijjE5mFD8PWBUZ7QS58PhwyXPsFRHaelVV7krj541X0f/13bpu+hrX7jpNbUIkq7EH14brpxpTa0fMhvBUEN4KRX0GzS4yt4EKbOupbcJzMJFjyDPwzF+w240XuziWwbxl8do3xiciun2HBAxW+UDxwPItbPl7NB3/sJivPGFebHX789yhXT/6LrUfKeOEsUkUa1fPlqzt78NxVbbikVTgPXdqC+ff2plWUtjesSZqHe2MqnLmWmVAcVqx4D/542Tho8eOwZT4U5JV+gsMb4e+ZkJ1ihBTbvndImJ6ZW8CfOxMY9dFKLp30B+/9tpOPb+lKZEDJWRPuFhMPX9qCQW2jMDt6q9z0I8YyxJNDin5PQNfbi2+nHoDfXzZqVxRK3mO8mZx5lRFWZCUbu4e81+vEBxQODis63ggefrD3D+OaM+dmSNxhnHfHjzDnJtgw60RYoTe6Lif9MMy63igwDhD/lxFWbF9s/FxZT/w//XeesezIehYfFEmlvf/++wwbNoyOHTvSo0cPxo4dy+7du6u9H27VfkYRqf1MJmjY01gzuu4To81uh2/uLHmcxR2u/6x4poGL2nQwheEfrCjaOm7V3mSufe8vvhnbi/b1g878iYLqw5DJ4Bta3BbcCIZOrbkVyr2DocvN8O9cY8aM3QZfjix5jMXdWN/sE1rmUwD8suUYO45llHlfdr6VZ777lw9GddE0fHGYBqG+3Bjqy43dGzq7K3KWEjPy8OlxL6ZFjxoNmQkwuXvJg4IaGNcnN4+S7akHYeYQ4412XqYxa+DbscZsuPvWGb+/q8jafccZ/dGqottz/z7Eyj3JfHLr+aRm5bM3KYtAbzdaRPgTHeSNl3v5sy2qjH8kXDfDCBxS4uHS52DvUmOJYre7jA8eYs6Hi/9r/N4H403kvj8h+cRsiplXQcNeRjAA8NuLENMJ3KMd12+L+4nQ6cRnr7np8OcbRnieup+iC7fJhFERRFyKXyQM/wxmXFlcuDX+L+PPyVpcDm2GGf/e4nCrVq1i5MiRtG3bFqvVyuuvv86YMWNYuHAhPj7VN/tXMypExDH8wqHfRCOsKIvF3VhP2qAXuLnuhSc1O5+XF20ttb+9zQ5vLNlBZmVrKPiW8Wa9poYUYGxTF9PFmCXiXsbUZIs7jPzaePFqKTsbP5aWw/t/VJzUr9idzOFUB2/PJyI1WmJ6HvZ218Plr5R9QFCD8mev+daDq94DswV+edYIKQAGvgbeQVXWx+TMPJ5b+G+p9oMpOUz5dRcd6gcx/Pz6XNYmiiZhftUTUhQKjIXrZsKgSUZIsX0xbFkAtgIY8AJ0uQk2fFm8tbbFw9ge9NLnjNsp8cUhRXhruP5zCHBgSFHIzQMa9YYRX4HZrbgvhRfu9jdA/6fBP8LxfZHKMZshupPxGqK83WRaXG78TAZElX1/LVdQUMCcOXMYMWIE/fr1Y8SIEcyZM4eCAsctS5s2bRpDhw6lefPmtGzZkpdeeolDhw7xzz/Vu5uOggoRcRy/cOj7eNlvYDuOhtiuLh1SgLF1YXmf9G89klb5oKI2MpshqgP0erD0fR1vgtjzyw0pAPKtNo6ewRaQhUtCRETKY/f0hzbXQFgZWz4Pebf8JXZunkaget7Q4rbojtBykLEbRhXJzitgV0Jmmff9czjNub/nbAXG8o11M42QotWV2O/8g/zAxrB1IXz3IKQfLLkUxjvQCAJCm5V8rqvfh+BqnJ3k5gENukP7ESXbLR5GoU0/hRQuy2yGqPZwwUNl3z/o9TodUjz44IO89NJL7Nixg7S0NHbs2MFLL73Egw8+6NCw4mTp6cbSnMDAwGo5XyEFFSLiOOlHYOFDZW9PuvajE4UXXftTcj9PN9rGlP2LuUP9IPy8tILOKJz5Fyx9tfR9az+C3b9WuE7Zw81MTHDFheJMJvD11FiLSMVMOSmw8n1I2Fr6zjm3lt4NpFBeFmz7ATZ9Vdx26G9Y+4lRs6KK+Hi40bqc2iedGwTh61mNMyhO5eELLQZAtzuNbUqveBWbTxiHwvtgb3WlEUj0e7LkzITMJFj+rlGI82RfjixZYNPR8rJhx0+wfmbJdmsezL8f0g5XX1+kcgp39/jtpbLvnzOm5G4gdci8efNYvnw5APYTM4QK/16+fDnz5s1zeB9sNhsvvPACnTp1okWLFg4/38kUVIiIYxTu7lFYOPNUhQU2T9261MX4e7nzyIA4LKcUMvOwmLm3XzN8POr4m+fC3T0KC2eCkSqYTlxeCgtsFu4GUoYwfy/u6duszPsK9WkRRnR1bM8nIjVWVJAXppUnFc4EYylHoZMLbJ4qOxl+nGh8PegNY9mC2QJLX4OcqtvSNNjXgycHtTZKJpzEy93Mrb2b4OHmxKACwNPPmEVy+StG3QoKl9QMN0IKv5NqSlnz4N9vYNnrxu2wVtDrfuPrlHjjulAdAUF+trFjxJybipd7RLYrXgayY5FR0Dn1zLfKlmpSGFKcXDjzVIUFNutgWDF37lxMp/6yOMFkMjF37lyH9+Hpp59mx44dTJo0yeHnOpWCChGpenY7xK8sGVJY3OGGL6HT6JLHzRtbvN7VRbWOCmDe2J70bx1BbLA3V7SN5Jt7etIiQjsCkJtmfApZGFJY3I014LcuLl7yY7fBP9+UveXdCb2b1aNTg6Ay7wv0dufxK1rhp20iRaQC/p5mY0ePQkEN4N61JWtWZCbA0X+MXadOFhgLN82HoR9A22uM3Zhu+MJoC2pQpf1sFxvEN3f3pG9cOLHB3lzVIYZ59/SiebhflZ7nrHn6FYUUheyeASVDCjCWVTS/1Ji2H9YKRnxpTN+/9DnjWjBoEvjUc3x/C7f/tpzYYrj9DTDqGxgxuzisqNe0dAFVcb7MBJh7R8mQosXlxhbuJ2/ZHv+X8X+7ju36ceTIkaIZFKey2+0cPerYXfOeeeYZfvvtN6ZPn05kZOTpH1DF6vhHgSLiECYTNL4QLnocfnvBeMEy4ito2NuoAA6wboaxpdjoeRAQ49Tuno6Hm4W2sUG8eX0HMnOt+Hla8K7rMykK+YbCBQ8ba5vXTTcKpDbsbcyoGD3fqOQdN9B44Xrqi9yTRAd5886ITny/6TBTfttFUmYenm5mrusSy829GtM0zEVewIuIy9qZkEOHG76EWcMhP8sITUMaQ/vrjQN++A9cNcXYJtrNs/QThLWE4MbF9zW+yLh+lfOJ5tnycrfQoUEw747oSGaeFX8vt+otmlmVghoYuzbYbcU1KTqONmZlBMRWTx0qswXqdzX+vTd+YdTG8q0HjS4wwordv0OvcUabuJaAaLhxLkwfZHxoVVg40y8CblpgzIDKz4LOt0Cba+vcrh+RkZGkp6eXGVaYTCYiIhxTe8Vut/Pss8/y008/MXPmTOrXr7pdjypDr7RFxDF8gqHrHcYLiJjOxptXN/cTu4E8Ce6+0O5ao9pzFb8IdBQfDzct9SiLXxj0mQDn3wahzYsLZ8Z0gdt/Nbay8z99Eh8d5M1tFzRhYNsosvOtuFvMRAR4On8qtIjUCDabDVtgfSwjvgSbtbhwplegEVY07mPMnPCsIPg8OcBw8CfwPp5u+NSG2junbt3qHWj8qU6FYUVYi+KtsN08jLAiqkPZO26Ja4hoDTd9B8vfhn5PFRfOjO5khBWbv4be443XGnXM0KFDeemlsmt32O12hg4dWuZ95+rpp5/mu+++Y/Lkyfj6+pKQkACAv78/Xl7Vtwy3Fvx2FBGX5RMMXcYYMydO/lTFLxz6PGps+VZDQgo5Db+w0i8izGYIb1Xpp4oKqriwpohIhYIblW7zCjT+SO1lthSHFIXcPMDNNUOK7HwrXqExHEjJIcDLnWDfOrw0JaI1XPqC8bqxUOHWpSFNS7bXIVdddRW///47y5cvx2QyYbfbi/7u2bMnV111lUPOO2uWsc3wqFGjSrS/+OKLDgtHyqKgQkQcq7yLSx296IiISB2XlWwslzt5OVxGwontjbQ8obbLK7Cy42gG7/y6k8X/HMFmhzYxAYzv34JODYIJ8qmjgUVZrwvN5jr9etHNzY1JkyYxb9485s6dy9GjR4mIiGDo0KFcddVVuLk55q38tm3bHPK8laWgQkRERESkOmQdh1VTIeMoXPSYMRMtM9HYXcTDF7qP1TKFWsxut7NqTzI3f7yaAltx3YHNB9O49ZM13H9xc8b0bkyAd92qxSDlc3Nz45prruGaa65xdleqnYIKERERERFHy0qG1R8aRaYLXTQBlr4OK6cUtymsqFo5qSWX/WSngGeA8Wl9NTuYks19s/4uEVKc7M2fd9C/dQRtYrRMSUTbk4qIiIiIOJqbZ8n6GWumweTuJUOK4MbaRrMqJe+GHyZA6gHjdlYSrJgCB9eCzVbt3dmXlMXxrIq32Px67YFyt6QUqUsUVIiIiIiIOJqHL7QcCEOnFrdlJRV/feW7cN4Q8PSv/r7VRsf3wafDYMPn8PXtkHYY/nwbfn/J2Dr7yIZq79Lh1OzTHrP1SDp51uoPUURcjZZ+iIiIiIhUBw9faNoPwlvDsX+L20ObQdwAhRRVyd0bGvQ0ZlXE/wVvdYCCHOO+4MbgHVLtXQr19TztMTHB3nhY9FmyiP4XiIiIiIhUh8xE+OPVkiEFQNJO+OV5Y/cPqRp+4XDJf6Hd9cbtwpCiXhzcMAuCG1Z7l5qE+eLjYanwmBFd62PS1u0iCipERERERByucHePle8VtzW7pPjrtR/Dby8ax0nVMFvA55TCpB6+RrsTxAR589xVbcq9/8r2UTQM9a3GHom4LgUVIiIiIiKO5ukPjS4A04mX30PehWs+Kq5ZYTJBk4uMN9Jy7rKSjJoUK94t2X5onVGzorDAZjVys5i5tHUE0285n2bhfkXtwT7uPDGwFU8Mak2o3+mXh4jUBapRISIiIiLiaG6e0OxiGP4ZZCdD66vA06+4wKabFzTvb9RWqKnyMiFlP/hHgfeJLTZz0iDtEATGGt9vdcnNgI2zjK/Dz4ORs+HXF2H9p3BwNaQfNvpUzfy83OkTF07r6AD2HT2Ot7c3QT4eRAd5a8mHyEk0o0JEREREpDoUhhWthxS/aS/cDaQ2hBRbvoPJ3WD955CdaoQUG2YZbVvmG+FBdQluCKPnQ5N+Rk2KwFijZkWnm2HkHIjqWH19KUOIjzum1EO0jPQnJthHIYW4jM8//5zBgwfTqVMnOnXqxPDhw/n999+rvR+aUSEiIiIiUl3cPI0/J6sNyz2Sd8M3dxhfL54AtgIwm2Hx40bbvLuNmQ3R7auvT2FxMGwq+NYzbvuFw8VPglcQWPQ2SKQskZGRPPzwwzRs2BC73c68efO45557+Oabb2jevHm19UP/Q0VERERE5NwExECfCfD7S8btn54oef8FD0NQ9S+1KAopyrst4uKOHj3KokWLSE5OJiQkhMsuu4yIiAiHna9fv34lbj/44IPMmjWL9evXK6gQEREREZEaxCcEut0JdquxBevJej8IPcaW3oFDRMpVUFDApEmT+OqrrwAwm83YbDbeffddrr32Wh588EHc3Bz7dt5qtbJo0SKysrLo2LF6l0spqBARERERkXNndjOWVZzKKwhMetshUhmTJk1i9uzZ2O12AGw2W9F9s2fPBuCRRx5xyLm3bdvG9ddfT25uLj4+Prz77rs0a9bMIecqj4ppioiIiIg4Q07ambXVBDlpsOEL+HFi6fuW/Le4wKaInNbRo0dLhBSnstvtfPXVVxw9etQh52/cuDHz5s1j9uzZ3HDDDTz66KPs3LnTIecqj4IKEREREZHqlrTLeAOfdri47dhW+O1FyHDMmw+HStkHP5z06W6vB+CCh4pvL54Ax/dWd69EaqRFixad0U4wixcvdsj5PTw8aNiwIW3atOGhhx6iZcuWzJgxwyHnKo/mYImIiIiIVKekXTDzKkiJN4KKwW9AdgrMGAwZxyD7OPR/GvwcVzCvygU1gMtfgR/+YxTO7DEWMIHZ3SiweenzENzI2b0UqRGSk5OLalKUx2w2k5SUVC39sdls5OXlVcu5CimoEBEREZGzlpqVx7H0XDBBhL8XAd7uzu7Smck4ZmxXCWC3Q2ZC8W1HOnGu/OjzsYS2wLxrCXx5ozHbIDPBOGbvMsjPdnxfqpJXILS/HqI7QmjT4sKZ3e6EZhdDvTjwDnRuH0VqiJCQkApDCjDCg9DQqi9Q+9prr3HhhRcSFRVFZmYm3333HatWrWLatGlVfq6KKKgQERERkbOy42g6E+ZuYu2+4wB0bxLCC1e3pUmYn5N7dhrH98HcO+HylyCyHRz+G356Cq6aYswMcKDDaTmsSa7PnIy7qOcFNw5+nBZbJ+N7YLVxQGB9GD2vZs4+8AqE+l1LtvmEgE/Xso8XkTJddtllvPvuu6c9bsCAAVV+7qSkJB599FGOHTuGv78/cXFxTJs2jV69elX5uSqioEJEarb0I+AbDubikjtubm6YMhMgINKJHRMRqd0OpWQzatoqjqTlFLWt2J3MzR+vZvadPYgM9HJi7yqQlwXrpsP+5TB9MFz6HCx+HPIyYONs6HEvuDum70fTcnjwy/Ws2J1c1Pb1Rnjtinu4KnUXlsN/w6i5EFq91fVFxLVERERw7bXXlltQ02Qyce211xIRUfXLw1544YUqf86zoWKaIlJzJe+Bz66Dg2vgpOlxLYLtmD+9Co5udl7fRERqufjkrBIhxcntB1OynNCjM+ThA13vgPOGQW4aLBhnhBQdRkKnUQ4LKQC2H00vEVIU+t/PCRzsON648eNTJQtsikid9OCDD3LddddhNpsxm824ubkVfX3dddfx4IMPOruLDqUZFSJSMyXvgc+uhaQdMONKGD0fYrpgTtqB9+zrjIrpnwyCm7+DiDbO7q2ISK2Tlp1f7n2ZudZq7MlZ8IuAbrfDP18Xt50/xuHFK1fsLrvwXXpuAcmmIBoAbP8BvgMGTYKAKIf2R0Rcl5ubG4888gijR49m8eLFJCUlERoayoABAxwyk8LVKKgQqSb5Vht7EjP5Y3sCh1Nz6BsXRnBwNRTtqo1y0mDZJCOkAKPg2IwrYfCbmH58snhbt+zj8O29MGJ29RRIExGpQxqE+JTZbjZBlKsu+wCjmOXBdfDpNcZtd2/jOjLzaiP0ju7gsFM3CvUts91kAp/wpmB2A1sBJO8Ga/VW2BcR1xQREcHo0aOd3Y1qp6UfItVkzd5kBr61lOcWbmHasj3cOG0Vk34/TGKGXohUmlcA9PkPNLqguC0/G+beUXLv+eBGMGyaQgoREQeICfZm7EVNS7WP79+C6CBvJ/ToDOVnQ+I2Y7lH+xtg3AZjGUhOqhEQ5JdezlJVujQKxs+z9OeEA9tGER0WagTrEW1g5GwIbuiwfoiIuDrNqBCpBkdSs3n4q43kW0sWw1myLYFRR9OJCHThF3SuKjAWrn4PvrkL9i4tfX9wI7hxrrFFmoiIVDl/L3duv6AJF7YIY+66A1hMJoZ2iqV5hB++ZbwZdxkePtBqMAQ1NIpW+kfAZS9A19sgqr1Da1Q0CvXlizu688S8Tazfn4qnm5nh59fn7j5N8fPxMgL4kXO05ENE6jwXvoqI1B5JmXkcTCl7P/Qf/zlKnxb6xP+sBMbCZS/Ce71L3WW/5GlMwY2d0CkRkboj2NeD7k1C6d4k1NldqRxPf2h00lZ7/pHGHwczmUy0iQnkk1u6kpyZh5vZRGSgFx5uFuMANw+FFCIiaOmHSLXwdLNgMpV9X0SAC6/jdXUJ2+DTYWXeZZp3FxxYXWI3EBERcRFZxyEvs/h2ZqKDzpNUcimHo85TSUE+HjQJ86NBqG9xSCEiIkUUVIhUg6hALy5tXbo6r8Vs4tLWmk1xVhK2wfTBJWtSnCw/G2YOUVghIuJqslNg3QzYssAIK1IPwoIH4dD6Knn6o2k5bNifwvp9iRzZvwv2/WmEFSn7Yd7dcGxLlZxHREQcR0s/RKqBr6cbTw5qjc0OS7YcxW6HMD9Pnh/SkkYnqqYfSc2mwGrHw81MeG2cZZGTZhTBPF3bmT7Xmo9KF84c8RX2heMxFdasyM+Gn/8H13xirEEWERHnSz0AS54yvs5Jg60LYc9vkPAv3LzwrJdguLu7s+VIBnd9upYDx43lllGBXky5IoT2W3/AtPxtOLQWshLhhi9VaFlExIXVqBkVH3zwAXFxcTz//PPO7orUIrn5VtJy8rHZ7Kc/+GS24j3ikzNy2HQwhR82HWbZjkTikzKxnvJ8scE+TLquPT8+cCEL7u3FvHt6EmtJIyEjjw+X7ubKd/6k9yu/MnTKX8xaGc+hcmpa1EjpR2DJ/yBxe3Fb6kFYPBGS91T++bwCoPd4aHtia7nCwplhLbBf9R62hidqVkR3hKvfV0ghIk6TkZNPdl6Bs7tRLqvNTlp2PnkF1tMfXAkVXluDG8KV7xpf//CIEVL4hcPwz86pToTFP4ybP15VFFIAHE7NYfQ3xziQ426EFEENYOiHZxVSHEvLYV38cb7fdJiVu5M4dLyKrtMp8cY1sVBOmtF2Bux2O2k5+eTmV+2/n5Tj+L6Sy4cyjsHxvU7rjkhtVmNmVGzcuJEvvviCuLg4Z3dFaonsPCvbjqYzdeku9idnc2nrCAa1jy53j/MSErZD6n5o1JsDaQU8/NUGVuw5XnS3n6cbb4/oSK+moSXWnvp5udPcyx0Aq9VKWno9bvpkNbsTitfpHjiezWPfbKJ9bCCTb+xETFDZ+9TXGOlHYOHDsHUBbP8BRn8LHn4w7y7Y84cxJffGryGkkoUv/SPg0hfALwq63FK0u4fdP4qMi18lYPMnmHrea7woFRGpZodTslm2M5FZq+Lxdrdw2wVNaBd7FjPIHGh3QgZz1h5g6Y5E4iL8uaV3I5qF++F5DjUTsvIK2HYknal/7OZASjYDzotkULsoGp58bfX0h2YXg28YZCYYbZ1uguBz+32dnGsvc8vvtJwC9hFFfZMZut8DAbGVfu7dCRncPmMtuxIyitrC/Dz58KYutIsNxFReIarTSYmH2TeDdxBc+bYxNus/h1+fh5sWQHSHch8an5TJwk2H+WHzEWKCvLn9gibERfq79o4rNVnCdphxJZx3NVzwENht8MvzsPsXGDVPu4xJrfXBBx/w2muvMXr0aCZOnFht560Rv8kyMzN55JFHeO6555gyZYqzuyO1xPLdSYyZvhr7iQ97Nh5I5dMV8Xx5Z/eSL6hOlRJvXKgyj5F28x889XNmiZACICO3gNumr2Hhfb1pGVX2C9MCq50v1h0tEVKcbMOBVL7fdITbL2hyVt+fy8jLgoNrjK/TDhl1JXwj4MiGE20HjE8kKhtUgBFWXDQBPP1KNO9MyKZjvycxefmfY+dFRCovIT2Hh77awF+7kora/tyVxAOXNKd/rGv8XtqdkMHQKX+RkpUPwKaDqXyz/iBf3tGdLo1Czvp5/9qZxG0z1hTd3ngglc9W7OOLO3vQ4MRSR1IPwryxRkhhMhtv+P541dgqtNVg8DiDDwzKkGctf2ZkjhUwu8HixyCoPjS9+Iy3IT2alsOY6WvYk1jyep2QkcvID1fy3X29aVTvLPqcnw1/f2rM9ACYfx806G6EFGAE+qPmlTnLZH9yFiM+XFk0e2TjgVR+2HyE90d1ZsB5jt+9pM7JSoKfnoT0w7BiMhTkQUEOrP/UuP/X52Hg60bgJOIAmZmZZGRk4Ofnh6/v2f2OPBvOnCxQI5Z+PPPMM/Tp04eePXs6uytSSxxNy+GpbzcXhRSFjqTl8OvWYxU/2MMfut4BNiuHklL4ZVvZFcStNjtfrztYaglIocNpOXy59kCFp3rvt10crulLQEKbwOj54H9iu7X0I8UhhZunsWQjpvPZP/8pIUUhu3sNn4kiIjXWnsSsEiFFoXd+2UmBZ6ATelRSgdXGV2v2F4UUhaw2O88s+IfjWaVnJZyJI6nZPPXt5lLth1Jz+GN7QnFDTorx5twvHMauLF4GsnE25Kad1bkBwnzdcLeUntlgNkGjBo3g4v8aocjmuZU6z/7krFIhRaGM3ALWxh8v877TcveGLrfCeUON27t+Lg4pAmPhuk/LXQrz587EEktcCv332384klrDXze4Ip9QuOJViGpv3F7zYXFIUb8b9H9GIYU4xJo1a3jggQe46KKLGDhwIBdddBEPPvgga9asOf2Dz9HJkwUCA6v/2uXyMyoWLlzIv//+y5w5c87peaxWrd07G4XjVtvGLy07v8wLPMCv2xIY0bU+FnM50zg9AzB1vgXT3qUcz3ev8Dxr9yWTlZuPj0fpabSZuQXk5Fe8G0VSZh7Z+daaP/4hTTGPnIPpvV4lmu0DJ2GL7QqYoIq+x9r6M+sKNLaO4YxxtVjObTtE/QxUbMvhst8EF9jspOQUOH380nMK+GNH2SH7xoNppGfnE+BZ+Z+R9Ox8DqXmlHnfz1uOcX2XWGOr7tA4zKPng7s3tpCm4BeJ2T8Se3gr7D7hZ3U9sFqtmLKO8/KwtoyfvbHEfc8ObkVUiD+2oJGY6jXHHtEGU14W9uxU7B5+mLKPY8pLwxZQ35jhcYr45KwKz712bzJXtY+qdJ8B8AnDfNlLmOKXG5/Wn2C/8WtswY3LHYuft5a949WRtBxSs/IJ8/M4u/6cQr/3T+Ifg/n6WZgmtS5us7hjv/YTbL4Rlf651dg6Rk28ppZn1qxZvPbaa1gsFuwnPl212+389ddfLF26lIcffpjrr7/eIeeGkpMFnLGqwaWDisOHD/P888/z0Ucf4enpeU7PtWnTpirqVd1U28bPKySaAC830nJKFzhrEe7L7l07ycws+9MTP28PGnMAjz1/4Hvefyo8T2yQNwf37yMzvfSLVreQGMwmqKiGp5e7mezMdNbHb6v4G3JxTcO8Cfh5AqdGP6ZfnyO3Xhu2J9mr/IJS235mXYnG1jGqc1w7dz6HWUzoZ6AiZrOZcN965d7v72Fx+vj5+AfQrJ4v/xwqfW2KCfImI+046/eWs/VzBTxDovD3dCM9t/S1tWWEDzt2bCcry3jT7+7ujs2Wi3X/egC8vKLI2XkEOFLp856suY+Jb+7swrr9adhs0KVhIB75aWz9xxjzkMDGxBzciMecGyno/wKZDS/Bd/MM3Fd/QMH1c9iR5U9uXvFME5PJRIBHxYU36wd5snXrVnJyyg5pKhIW4EnU0V9xPymkALD98BhpFz3P7oTSH6p4e3vTMsKPn/4tPQPU18NCfk4m69fvqHRfKuLsn1lXUD/Ei5ANU0q+ebLmY/3jDRJb38TB45X/9weNraPUpGtqWdasWcNrr70GlA5dCm//3//9H82aNaNLly5Vfv6qmixwLlw6qPjnn39ISkpi6NChRW1Wq5XVq1fz2WefsWnTpjNOsNq2beuwtKs2s1qtbNq0qdaNn91uZ9zFzXluYcm91D3dzFzbpT5Nw8pf+2XOOIzpnUvBVkC0j41m4X7sPJZR5rGjezaief2yp0pl5uZzccswftqSUOb9ADec34Bm0WG41a+5W6iZ0g9j+vZuTPtObBlqcQc3L8hNh7RD+Hx1Pe1HfWt8qlYFauvPrCvQ2DpGTRzXmtRXZwhLzSEywIsjaSXfuFzSKhxvew5NXWD8bvNJ57vNR0otT3z0sjjiGkRCg8rPELDZ7dzbrxkv/rC1RLunm5mhnRvQpJ7jluQV/j+Ka9oYi8VCuwYnh0WhxV8WZGPesRnsVtwX/4eg8FZwbAtY3PEwFdCqZZxRy+IkB1NyCPB2Iy27dABjMkG/1lE0q+B1Q7nyszFv/grTkieM2wEx2EObY9rzG5bdvxBkfoqOV76N3bf0awD30CymLttbambm2L5NaREbhqVB1bxuqIm/nxzBlH0c0+8vY1o/EwB7dEew5mE6+g9ua94nwtOH8J73YfcKOuPn1Ng6Rm0Z108//RSLxVLhB3kWi4XPPvusyoOKqpwscC5cOqjo3r07CxYsKNH22GOP0aRJE26//fZK/fBZLJYa/cPqbLVx/K7uGIO3u4VJS7aTmJFHl4bBPDmoNU3D/ctf9gHgFwkjZsOB1dRr0Jq3h8PIj9aQnFlyTe/4/i1oHuFf7rj5esK9fRrz565ksvJK/xIK8fVgVI+GeHq49H/T07PlQ+qJWhyFNSn8wmH6lcY015xUTHnpVf7zVRt/Zl2FxtYxatK41qS+OkNsiC+f396N13/azg+bj+BhMTO6R0Nu6tmQw7u2YLHUd/r4tYj0Z9bt3fjfgn/591Aa0YFePHp5Sy5sEXbWfbMAwzrH4uvpxhsnrq3nNzKurU3C/Cq+tlaR0/5sWvygxWVw1XvwzZ1GSAFww5eYGvbCYil9za0f4sOHo89n9EcrSwQDJhO8MbwDDUN9z27MLH5GfQOfUKNexahvMXn6w6IJ8O83mDqOwuQVBGU8d9MwP766syfPLfyXlXuSCfX1YNzFzRnYNgoP96p/3VDn/897B8F5Q+Dv6RDVAdM1Hxnb1M8eBYnbMcVdjsk7GMyVL/9X58fWQWryuGZmZvLnn38WLfcoj9VqZdmyZWRlZeHjU3VBcFVOFjgXLv0OyM/PjxYtWpRo8/HxISgoqFS7SGWF+nkysntDLm4VQb7VRoCXG4E+Z7Cm0+IGDXpAZDvwDqSVD3xzV1fW7U/njx0JRAZ4cUW7KBqG+BLgXXENC3P6Eebc1YMXvt/Csp1G4TWzCfq3juCRAS1pElZ2ocgaJaSxsf3orBEw8P+gfndjDEfPhy9ugKvfh+hOzu6liEiVahLmxyvXtGPC5S0xYSIiwBMTdg6f/qHVwtPNQtfGoXw2pisZuVY83cyEB5zZLhgVqefnyY3dG3JJq3DyrXYCvN0I9K6aeglVpiAbEreXbDu+F2K7gqX0riwmk4nODYNZOO4C/tqZyNp9x2kW7sclrSNoGOKLl/s5vGCPaA03fQcWD6jXzGi77EXodpfxOsPDu8yHmc0m2sYG8sHoLqRl5+NuMRER4HX226RKxSxuxuuXW34Avwij2CnAdTONHUGiOpxVSCFSloyMjNOGFIXsdjvp6elVGlRU5WSBc+HSQYVIdYgMPIsXZhY38C5e0tEwLJCGYYFc3alye7Pn5eXRIcKPKTd25nBqDtl5Vnw9LUQHeuNTm/ZBD2kCo74B3zBj7ADCWsDNC40Lvl5YiUgt5OPhhs9Js+JcsWhesK8nwQ7Y6S4ysOw32OVJysgtmpkY4utBqJ+DphvnZsDa6bD0NWMpYrsbYP1MWDgePPzgvKvBrXSwYjGbaBrmR9MwP0b1aFS1fYpoXfK2f2S5u32cKtDbncDTfCgiVcTiVnqXsuCGxh+RKuTn54fJZDqjsMJkMuHvX7XbXrvKZIEa905o5syZzu6CSJXz93LH36uWv9AIKGO98xm+EBMRkdopLTuf+KNJPPX9LtbFp+BhMXNXr2jaNY7k/EYhVf8m3NMPmveHlVNg6FRjFkXTvvDTU8ab0DJCiiqRddzYkjWyPfiFGW2ZiXB4vTGr0CfEMecVkRrH19eXXr16sXz58tPWqOjZs2eVzqZwJZqjJCIiIiLVLjvPyp74eBrs+pTnLvAizM+T6cOiuMs0l5zkg8xevZ+svNIFLM9ZZFu4/Tdo2Bs8fIyaFbcuLl56UdWyjsOqD+DTYfD7S5CRYIQUf7xqtK14D7KSHXNuEamRbrzxxtPOwrNarYwcObJa+jNz5kwmTpxYLecqpKBCRERERCovP8eo7ZB70s5Xybsh7dAZPTw5PYtGCT8TsPRZWv80ivnXBtJl1QP4rHyDixNnknw8iYPHS2/PWSUCY4qXInr4GLcdJe0g/PaC8fXqD+GX5+DXF2Dle0bbHy9Dyn7Hnb8Wy8ot4HhmHjn5rresSuRcdOnShYcffhigVE2IwtsPP/ywQ7YmdRU1bumHiIiIiDhZfg7s+hm+vBGumgKtBkP6EZh5FYQ0hasmQ0B0hU/x+85kGnidT9forngcWkXUrEuMO4IasKvJaD77+hhRYUk0j6ja9dfVLriRUTj6mzuN2+s+KXn/kMkQWjVbdNcVR9Ny+PdQGh8u3c2x9Fyahftxc69GNA/3J8TXxYq3ipyl66+/nmbNmvHZZ5+xbNky7HY7JpOJXr16MWLEiFodUoCCChERERGprKwk+O4BsNuMN+Ap8fD3TOPvlHjYvwpaXVnhTgi7EzN5buVRltz6NtGfdCtqP9r/He5eeJy0nAJ2J2ZWwzfjYJ5+0HIQDH4DFjxQ8r6Br0HrIcYxckYOp2YzfvYGlu9KKmrbcSyDHzYfYWS3BjzYvwX1HFWMVaSadenShS5dupCVlUV6ejr+/v61tibFqbT0Q0REREQqJzDG2Gbat55x+9fnjYACoP8z0OSi027X2DzMj2lXRRK26K4S7RGL7+b9ywMJ9HanaZgDtiSpLgU5xp/Cr49uKX3M0S3GdqlyRqw2O5+vjC8RUpzss5XxrN6jeh9S+/j4+BAREVFnQgpQUCEiIiIiZyO8FVzzScm2+t2g42jwDjrtw3s3DaZ11hrcj/wNQQ04PPI38qK7QtpBGu+ZxQ3tgujRNNQhXXeInPTirwtyIX4V7F8D6UeNwpmr3i/9mDUfwm8vQ2ZC9fWzBjuYks3Hf+6t8JjXf9pOUkZu9XRIRBxGQYWIiIiIVF7SLvj2npJt+1fCjkUlC2yWI8Tfhz3h/Ujt8yybL57BwC8SWdXpFTJ7/odFQTcQER5GdJC3gzpfxTKOGWHEsa1GSLF/FaTsg2P/GMU0V31QfGzfiTDw9eLbaz484wKkdV1qdj4ZuRXvBLPjWAaZpzlGRFyfggoRERERqZzUAzDzauPNOECnm4qXgXxzF+z9A2y2Cp/C28NCk/r1Odj0ep75M5vkzDxu+eYwUwoGExpZn2GdYvHxqAHl1DKOwS/Pwl9vwozBkLQTMo4aNTx++A8k7jAKjprMcPF/4fAGY2yummy0XTsD6rVw9ndRI7ibTac9xsNixnIGx4mIa6sBv/1FRERExKV4BcKFD8P8+6D/s9D5Zuh+N0wfBAExENHmtDUqAAK83WndIJz3RwWRnJkHQLCvR83aucHdG2K7wroZRmjx4cVgzQObFdx9wGSCnUvglh/gr7fBNwzOu8p4XMNe4BdhfC2nFR7gRevoAP49lFbuMVd3jCbMX8U0RWo6BRUiIiIiUjme/nDe1RDdCQLrg1eA8eemheDhA36RJY8vyAO3ssOHPKsVq91OqJ8HQT5VH1Bk5eSQlW/Cy8OCny0DclIhuOFJByQZS1VObqsMT38jeLDbYME4yD9RHNPNE4a8C7+9YMyq+OcbCGsFg98snn2i3T4qJcTXg6cGteaGqSuw20vf7+VuZkzvJni4Waq/c3WA1WYnJSsPs8lEcE0KE6VGUlAhUp6cdMjLgIAo43b6YXD3NV6IiYiI1HWe/hDZpmRbeEtjWciq96HdcPALN24f3gT1mkJIM8g8Cv5RWG12dh7L4POV+/htewJ+nm6M6d2YHk1DiQosY4ZBdiok74KQJkaxzrRDRhHK8POA0lP9M3Ly2XboOO8v3cvWo5nEBnlxV49w2h6eS3Cb/hDdwQgp/nwbNn0Jo781lmDY7cbSDf8TYUtuBuSlg39U+WNh8YKA6OLbJhP0HAcevpB93Ghr0BM8/ODAGmja1wgypNLiIvx4dVg7Xl60jYSTimY2CvXh5Wva0Sxc4Y8j7DqWwbz1B/lu42HcLSZGdW/IRXHh1A+pO7tQSPVSUCEupcBq42BKNgeOG59GxAZ7ExPkjZulmsup5KTD5jmwYwkM+j/ABAv/A00vgrbXKqwQEREpS+oBmDMG9q+A4/HQ7Q746mboMRZWLIE2Q43aDTfMZn1GICOmriS3oLiWxfjZGzi/UQhvXd+BqJMLaWanwoZZsOhRo85DhxEwfxzs+R1GfQOx3Up0IzffyoL1B3hs3r9FbfHJWfy1O5m7uvZm7LqvCDCZYPM38Ock44AZQ+DWH8nIyedQYjKHLVZ8vbyobzpGxMoX4PKXS4YRhQryYe9SmHW9cdtkgsteMgpqRrWHK9+FzV9DTCfITYONXxrHKaw4K0mZ+bz72y7u7NOEQG938q02PN0sHDiexardSXRrXIN2iqkhth1J49r3l5OWXVyk9Mlv/6FJ2F6m39JVYUUt8/bbb/POO++UaGvcuDGLFi2q1n4oqBCXUWC1sXxXEnfMXEt2vhUAb3cLU0d3pnuT0OoNK3JS4OenjU9BbPnGi47ti2DfUmjeX0GFiIhIWex24MSc/JS98O+3cHQzLLgfut0Nn10D+VkkHDvEIwv3lQgpCq3em8yqvckM6RBT3OjuBSGNwWwxrs9/vWVco31CwTvEKEp5kgMp2Tw5f0uZXXxvVTKDrr+SNh/0ocT6gQseJtPmwZTVCUz+6yh2+1HA+KT+48vG0jhxe9lBRXYyLH8bbAVGTYpbFxvFNXf8CLt/hes+hRaXwdwxxvkueRrSj0BepoKKs1BgtbEnMZPnFpb+973h/PpO6FHtlp6Tz/MLt5QIKQrtTsjk2/WHGHtRU8wqYOoQdrudDRs28Ouvv5Keno6/vz99+/alffv2mEyOG/PmzZvz8ccfF922WKp/OZV2/RCXcSAlm9tnrikKKQCy863cNmNN0QyLahNUH25aAN7BsGOxEVJ4BxttQQ2qty8iIiI1RVB9uOYjqN/NeKOelQhdxoA13wgX8rOg8y0c9W3J7sTMcp9m2rI9pGXnFze4eUKTi+DqqcbtwuUUNy+EiNalHr/jaDoFtjKKGJzw8wEg/KTHDXwd2l7LhuMW3v3zcIn8Ym9SFk+vMpEe3qXsJ/OPgCvfhuaXwuj5xtKUNsOM+7KSjZ1Avr7VCCm8g40lJ62HgE9Iuf071aGUbLYcSmPnsQwycvJP/4BarJ6/J03Dyl7eMah9GUGSnJNjabn8sSOx3PunL9/LsZOW4EjV2b59O8OHD+e2227jiy++YOHChXzxxRfcdtttDB8+nO3btzvs3BaLhbCwsKI/ISFn/vuqqiioEJexPzmLnPzSn6zk5NscF1Tk50DmSb98MxONNgDfcGMtbaGQJsZaWxERESmfZyC0GGB8vfNnaNC95P0tryDPXvEngZm5BRRYT3lNkJVkLP842bYfIDul1OMzckt/+nuytBw7uHkVNzTsCV4BfLl6f5nH/7YjiYSKXooExhqFM2M6GwUyW10JQyYb99lOfADj4WcsU4lsDz7BFfavUHJmHl+siufKd5Zx+VtL6T/pd+79/G92HE0/o8fXRvX8PHn9uvb4epT8hHdopxjiIv2d1KvaK/802wxn5hZgqyAUlLOzfft2xowZw969ewGwWq1FfwD27t3LmDFjHBZW7Nu3j969e3PxxRfz0EMPcejQIYecpyIKKqRGsOOAX4D5ObDrF1j6f0ZAkZkIS1+HXT8ba2wXPgQHVxuFsDz84OBaWDAe0g5XfV9EREROlXEMdv9u1E0CSN5jXItO88bBqXLSYdNs+PkZCG0Kff5jLPuA4rD/ixHUs2SVeqN5sktaRRDg7V7ckJ0CPz8HO38ylnv0f6Z4GcjOnzl1C4gWERW/Ye0dazF24ij0yRVw9B8CvCpYFZ2fVeFz4hd+0pasptLLOkwmsHiccUiRX2Dj67UHmDB3E4kZxtatdjv8tj2B6z9Ywd4KZqTUdu1iA/lu3AW8dX1HnhjYirlje/LEwFbU89NSmqoW5O1OdKBXuff3blaPoJP/r8o5s9vtPPHEE+Tm5mIr5/e9zWYjNzeXJ554AntZW+Ccg3bt2vHiiy/y4Ycf8r///Y+DBw8ycuRIMjIyqvQ8p6OgQlxG/WAfPN1K/0h6upmpH+yAIj1ZifD1GFgxBX59AX59EVa8C1/fdmKmxTFjiuati+HWE0s/Mo8Za1BFREQcKSPBeLM/40rY+AUc32fUd/hkIBxe7+zelS8nBX6caHwdUB88/MGaB22vgSvfgV4PgK2A6Lw9jLu4WZlP4e1u4ZrOsSVrU3kHQe9xxnKNm74z6l1cP8tYDtKgmxECFErdT6wlhV5Nyy6q2CjUi5a2XXD+GGO2JBhLNKYP5rFeZQccFzQNIsztDGd35mXDjkUw9zbjdmHfctNh+iA4+s8ZPc3BlGxe/6nsT0uTMvP4eevRM+tPLWQymWhcz5crO0Rz2wVN6NQgmBBfhRSOEBnozeMDW5V5n8Vs4r5+zfHxVNnDqrRhwwZ2795dbkhRyGazsXv3bjZu3Fil5+/Tpw+XX345LVu25IILLuCDDz4gLS2NH374oUrPczoKKsRlxAR78/6oziXCCk83Mx+M7kJMcBnblJ0r/yi4ca4x9XPNNFjzofHpx41fGwW7rvkIbvkBItsaf275Aa752Fh/KyIi4kgeftCsv/Em9/uH4d3zIWknBDcxZhS4qoCY4joNV7wCTfvB7b8YW3PmpEH3u+GuZbjFdmFY5/pMHNgKv5Pe5LSM9OeLO7qXXYMgrCWMmmfUpHDzOFGz4n1j2QXGm1dT+iGYfQshH3bllYGxXNspGrcTRf5MJujbPJhPBngQ5ZYBPe8/cc0/EVZc/gpWr2DuuKBRidPGBnvz9KCW+IedYY2q3FRY/3lxTYo7l8GwD437spKN7UnzTjM7AziWnluibtep5q8/RHodr1ch1ePC5vV47dp2hPh6FLU1CPFh5q1daRGp7WCr2q+//nrGxSstFgu//PKLQ/sTEBBAo0aNiI+Pd+h5TqX4S1yGu8VMr2b1WPTAhcQnZ2HC+CUYE+yNuyN2/DBbICwOYrvC3j+MtpguRpvZUvTCp0h42WmyiIhIlfPwhhaXwqUvwuIJUJBr7Cgxcnbp65MrMZuNa+nN30NAlNEW1R58w8ArCDx8wD8SgHoecGuvxgxoHUlSZi4ebmYiA70IreiTcf+I4q/dPIueC4wX7KasJDj2D1hziZnWkWf6PMVdw1qTZvPA18ON6NgG+B1eZWyT6hNs/Lnxazi2BZr0xd/Dh/su9mFop/ocSMkm0Mud2BBvogLL+cAkJR48A4wZHwW5kJkAfpEw+E348Uno/QBEtjHCkKEfGjuEnHe1MQ6n4XaaXRQ83MxYHFj1X6RQgLcHQzvF0r1JKAkZeVhMEBHgRXhA+UtC5Oylp1euBk1lj6+szMxM9u/fT1hYmEPPcyoFFeJS3C1mGtfzpXE9X8efLDMRlr5mhBSF25rt+xN+fwUufAR86zm+DyIiIuVJP2LM9iuUn2UUj2x3PXi5cNFAs7k4pCh08raednvRcgiL2USDEG8ahJ77Es+CggJs4e2wjP4WZgyB/Cy8f3mCpnBipse3EBoDwVcaH0gUCmkCQQ2L2vy93GkZ5U7LqNNsRZ6wDaYPhh73QqfRcGAVzL7JCD5iuxozSgpnv3j4QMsrwFpwxlucRwZ6EebnSUI5Oyrc1KORptxLtTGZTMQE+xDjiOXYUoK/f+V+v1f2+NN5+eWX6du3L9HR0Rw7doy3334bs9nMoEGDqvQ8p6OlH1J35WVizckkp/1N2G//zfj0x83L2E4t7zQFqgpyoOCk6ZanO15ERKQyMo7B3NuN5R7h58EVrxYvAzlSteuRq1VeFuz4CVJO7K6RcRS2zC+5A9e5MJmNGZCtrizZfuHDENzI+NpcxpTqstqg9PW9cMmGtcCYTZGZAD89CXNuhVnXG2HSgTXG36cu0fHwBe/AM/5WooO8eXlYW8qaNNE+NpBODc+sKKeI1Cx9+/Yt2t3jdKxWK/369avS8x85coTx48dz2WWX8cADDxAUFMTs2bOrfYtSxbBSJ6Vm57MrzZ9Pc2/hYEoO3f7xYlDbxjS+9WfcvXwguGH5D87Pgd2/gJs3NOxtrEVd+4mxJ3q95tX2PYiISC3mFw6D34DvH4WrJhu3fSOMmX9hLRxzzowE8Ao06j+AER5U5exCa4Gx29aXIyG6I1z/OfzyHKz/DC58FHqMNZZQnANT7oldRzZ+UfKO7x+BoEbQ6AJwO8MdCjITYc3HcN5VxvU9ZR+s/sios+EfCY0vhOGfwhcjjB3DAPpOhI6jznjWxOn0bFaPeWN78fYvO1i1J5kAb3du692Y/udFEB3kgPpdIuJ07du3p0mTJuzdu7fCgppms5lGjRrRrl27Kj3/pEmTqvT5zpaCCqlz0rLz+OTPvUxaUrwt2co9ybz3224+ueV8ekSFUuGKz+N74IuRxqcvwz+D3b/BisnGC62T1+SKiIici4g2cN0nRn0HgOaXQqNejlmamH7U2OqzzTXQuLexTfe398HgSVCvioIRi5sx2yGoIRz6G14/UfvJww/iBhghyTnwC4lga0IOmeY2hA2eTfSOz/BocxV8e48xw2HWcLhv3ZkVxbbmw+a58OtzsO4TY4eReWPh6CYoyIN+E8HiDqZTZmKYLZQ5BeIseblbaF8/iDev70hadj5uFhNh/qoLIFKbmUwmnnvuOcaMGVPuFqVmsxlPT0+ee+45TLW0Vo2Wfkidsycpq0RIUSjPamPs5+s4mHKa7cf8wuGCh40XMZ9fZ4QUbp4w5N3iPeJFRESqgu9Jxcs8vB1XP+ngWiNw//xa2DgbPh0G+5bB4ieMnSqqSmhTGD2vZNvwTyG6U+Xf4J/Ur0Mp2fz3p3iumLKWa78+zoBvbMxp+D/SmwwyalN4+MLQD858xxSLO8RdYdSaSD0A719ghBQhTaDb7cZS0b3L4MsRxvGN+xjLTn5+xhjH7NTKfS+n4evpRlSQd40KKQqsNg4cz2JvYiap2XnO7o5IjdKiRQumTZtGo0aNAKNYcOEfgEaNGjFt2jRatHDQDDsXoBkVUud8+/fBcu9Lycrn4PFsYisqFOQTCl1vh/WfQtoho63HfRDTufw1riIiIq6sQXe46DH47UVjBgJARFsY+Cr4FK9LzrNaOXQ8h+NZeQR4uRMd7I23eyWufRlH4Y//K9n289MQ2qxy238f22IUv77kv9js8OHSNFbsPk7jej7MHBbFR2uSefzbLbSMDqZT/S5wzyrwDjmj3TaKBMXC0PfhrY7FbUOnFm9nGhBtPGf3sdDlVohfDnNugch2RjBS1Ww2o1Dp6dpcwNG0bD5bEc+0ZXvIzLNyfqNg/nflebSOCqi1n/6KVLUWLVrw5ZdfsnHjRn755RfS09Px9/enX79+tGvXrtb/X1JQIXXO6WZMZOYVVPwEmYmwbFJxSAHw15vQqLdRs+JM176KiIi4Cp8QaH8D/P6SsSsHQK9x4F+8nPF4Zh5z1h7g/37cRm6BDYvZxI3dGnBP32Zntk2h1QrbFhkzDjz8jDf9iyYYy0B+fR4uf+XMajukH4WvbzPClVUfYv57BjcP/JLdiSE81zWf2Fn9uOf8h6BzD75YHU+nhu3PbkvXlH3w5eiSbV/dBKPmGTUrwlvB7b+Ah79RW6NpP7h3jbE9qaWKX2LnZWM/sJr9vq05kA75Njv1Az2IydiIZ2gDYzmNg7i5Ve57yc638tbPO/lsZXxR2+q9xxn+/grm39uLJmF+Vd1FkVrLZDLRvn172rdv7+yuVDvXi2BFHOyiFhUvz4g43YutzARY9YGx3OOmBXDhf4xlID/8B7KqqGq5iIhIdUreDTOvMkIKy4limvPuhj3LjJoMwN/xx3n++y3kFhjrpa02O9OX7+O7jYexF4YbFbFYoMUAYyvPm+ZD3OUw6htjicVFj515AUr/CLj2Y2h9Fax4B3JSabxwOG/G/UPD766HvExClz/PnecHkpVrPbO+ncqaBzuWFC/3uGdV8TKQddMhN8M4LqgB+JzYfcPN0whEHBFS7FnG2rQABk5ey4gPV3LTR6sY8NafLDnqR+6vrxuhShXLybeyNymLbTkBvP/HHn7YdJi9iZnkW8sv7gdwOCWbL1bvL9WekVvAsp0lXydl51vZnZDBP4dSOXy6pbciUqdoRoXUOd2bhhLg5UZaTumZE72a1iM68DRVtEOawoivwN0L6nczip35hBpFzlRIU0REaqK0w5C631juMeJLWDfDmF2x6xeIak9GQQBTft9V5kOn/L6LK9pGEll4/cxJg4Jc8Dupvkb6USNg8I+ES/4H3iHkWW0kuUXjdtl7hAVXspBmUEM4tN6YhfHDfyAnlZCfHzLuM1s4dPknPPRDIrdd1PLspkdbPIzdPqz50OJSI6y45mNjR5EOI8GzGmcFZCdxMC2b2384Rnpu8WuXfKud+xYcYvHwa2i+9Xtj+YmbZ5WcMjU7n7nrDvD8wi0U2IqDHi93M5Ou68BFceF4e5S95Ccz14rVVnY4tPNYRtHXh1OyeePnHcxZewCrzU6YvycvDW1Lr2b18KrMciIRqZU0o0LqnMb1fPn89u40CCm5TrVvy3BevqYtwb4eFT+Bm4exvVn9bkZNCp8Q6HwzhDZxXKdFRESqQmZC8dc2q7ElKRizBUYvgBs+g8AY6HYn3PgN9H4AfEPJt9pJzc4v8ynTsvMpel+akwYbZsGy142lkgBHNhlFOpNOBB0+oexJyuSpb//hsjeWMmzqOr5cHU9iRu6ZfQ8FucZ2oN/cCYc3QpcxJe5O7f4I/7czimB/P9rGnMNOIj6hxvW9sCZFUCx0v8cIXKpTYCyHg8/neFbp8bfZYUtOKLS9rspCCoDlu5J4esG/JUIKgJx8o/D4liNp5T42yNedQO+yl8H2amYUg80rsPLe77v4cvX+olAjIT2X22esYddJYYaI1F2aUSF1UpuYQObc1YNDqdlk5loJ9fUgOsibgHIurKWcWofCveZU4RYRkToqeY9RKHPQJKN45f5Vxs5Vl79sFIZs2KP4WJ8QaNav6GaQjztXd4zh5UXbSj3tZedFGiG/zQo7lxgzHAq1vx5mDIHs4/DpULj5e/Zbg7n+gxUcTTOCidTsfB79ehP39M1iXL/meBZ+mm7NK16GcrLs47DmYwhuBOcNhdk3Gu3ewRAWR+C6Kbww4jKyQ1sT7OtpLF1xO82HEOU59fruXnVhQKVUEELYPf3Bt+RuJgVWG4dSsjmcmkOBzU6wjwcxQV4E+px+HI6l5/DiD1vKP58d3lqyg3dGdMTPq/TrpphAb/535Xk8+OX6Eu3nRQcUBUeHUnOYtar08hCbHeasPcB55xIwOVhWbgHZ+Va8PSz4eBS/lcrNt5KRW4C7m5mAMsZFRCpHQYXUDWmHja3GCrd1y88m3J5MeP0Y5/ZLRESkOuSkGbttHPobvrwRej8E390Pnv5GLYYOIyHnOORlGAEAQEo8mCwQGIPJZGJoxxjaxwZx4Hg2FrOJ9ftT+HXrMcZd0rx454/YLhDV3rjexnSGjy+HvEwj+Bj+GXgFER+fRU5+6ToHU//Yw7BOsUaxxezj8M88o0Bl8CmFIv0jYfBbkH4Ipg82nt+3HvahH2JK2Aq+4Xh9PgSvO36DjByj/kbTi43tXWuoKH83gn3cS82qMJvgvIiSM0SPpeXwxap43v9jN5l51qL2Tg2CeGZIG1pHBWA2l78cJikjj31JWRX25/cdCSRn5pUZVJjNJi5tHc7Xd/fk4z/3cCw9l6EdY7igeT2ig4x/g/wCG3nl1Lo4kJKF3W53uR0Njqbl8O+hNKYu3c3h1Bwahvhw2wVNaFLPlyNp2Xz8117+OZhGgLc7Y3o3plODYGKCa+7PnIizKaiQ2i/9CCx61Chw1Xu8sWXYziXw45Nw49fGnu4Okpadz66EDBZuOkyB1cbAdtE0D/cj6Aw+0SBpl/FpUngrY43skc3gF25MyS2P3W5MsfUKNF7Y5WZAwlbjRWdhSCMiInWPVwD0nQitr4SCHGPWQ2hTuPR54xqRc9xYrrHxK7j5OyPYWDGZxCZD2B/qjhU3vt90mJTsfLo0DGFPYibbj6Yx7eYuND15F4egBkYgsXWhsdXp4Ldgyf8oGP4luxOz+WlzPLuTcxnfvwVZeQW89uP2ouUFeVYb6RmZYNtv9GfnElg73dgi1JoPkW2McxzZbNSI8I82Aoj4v7CPmI3pyxuNHbn6PQnNLjGugTOvguxksoZ8xOyUVnj6+NKzaSgNQx2wfaij5KYTc2gJU69swi3fHC2qU+FuMTHpiijq//k4XPwohDQhMSOXZ777l+82Hi71NOviU7jmvb+Yc1dPvD3M/LzlGLuOZdK3ZRjtYoOKQoQzqT1qt0NFh/l6utO5YTDtYgMosNrx9ij5liPY14OmYX7sSii9zGNIhxiXCykOp2bz6JyN/LGjuBjonsRMwgO8CPR2Z+rS3SWOv2/W3zQP92PazeeXWmpclj0JmSzdmcDmg2n0bBpKl4bBxJ7B40RqMwUVUrvlZRk7dPz7rXHbDsR0grm3GVfZr26CkV87ZL1pdp6VOWsP8Mx3/xa1ffLXPsb1a8btFzbBx72CEjGF1dfzs42dRTITjSmzDXvBkHfLDysOb4Dpg4wiYyO+gN1/wLdjodtdcOEjCitEROoyay788CjkpsKgN4xrzKzhEHM+DH4TEnbAhQ/DgnFwcB1JI3/k460eNLLn8p+vVxe9gZ277iADzougbWwQd366llm3dScq6KRPjrOTYfEE4zr72wswaBJrj9m48atj5FuNJ/l63UE6Nwzm4UvjeGnRVgA83cw0Mh+B5R/A+k/hyrfBLwK+HAUZR+DmhWByg08GGu03zoGe46D73ca2p4Xbhv/yLHQfCz8/DVlJAHj9/ixt+s3kms82Uc/Pg9l39qg522TmpGL6aSKd3HxYOOhpDnjFke/mQ/3cXcSseRzPA39B424QEMPOYxllhhRFT5Vv47/zN9M+NoiP/twLwJdr9tMuJpApN3YmJtibYF93wv09OZZefs2QTg2Cyq1DcTJ3i4Wy6mLW8/Pk5WFtGfnhyqJdZAA6NwyiU4Pg0z5vdbLb7cz7+1CJkAKMwqJdGgXznzkby3zcjmMZvLp4Ky8Pa1diicjJTCYTOxMyufb95aRlGwHU7DX7aRDiw6djutEgVGGFGPLy8sjKysLHxwcPj7NcylYJR48e5dVXX2Xp0qVkZ2fTsGFDXnjhBdq2bevwcxdSMU2p3Tx8jEJYUSf2Hl7xLnw9xnjx5BVovOl3UFGsgylZPP996TWeb/2yk4PHT7MFl5sXhDQzip5N7WeEFtY8iOpg3FcerwDwDYOjm2FyTyOkAIjuWPpx1nxI2FZc7AyMAmUJ240ptyIiUnvYrEZ4H9QAspKNQpTz7zV+70e2Ae8guPJNsNugXgvAzp7jBUSF+PHMgn9Lfcq++J+jtIz05+DxbHacXPzwyCbY8CV0vdO4nbSLYwf38MiPiUUhRaG1+47j6W4m2Md4wzuuZz18Mg9AeGvjgPn3wde3QeI28IsED3/juu4XYbRN6QUf9Yc5t0CjC7B2vav4yVdMLgopbEGN+afvR9w85yAAiRl5vP/7LnLzrdQIgbEw+lvMBVk0SP6Lnk2C6dMqhiZRoXgmbzVmkJx3NVk2Cx+e8sl+WdbuSylVA2LjwVRW7DbGKyrQm/GXtqjwOcb3b3Fms0Mr0KF+EN/d15tHL4vj+i71mTq6C++M6FQ0s8NVHErJ5v0/Su94M7BtFN+uP1jhY7/fdIRDKTnl3u/tH8Sri7cVhRSF4pOzWLDxELZydk+RusFqtfLbb78xduxYevXqxSWXXEKvXr0YO3Ysv/32G1arY36HpaamcsMNN+Du7s7UqVNZuHAhjz76KIGB1Vs7RkGF1H6F01B9ShaaYvS3xQGGAxxJzSl3e649iZkVPzggGq6eYlQaz88CW4FRMKz3/aUKZpUQ0gRGzQN3b8g9UZH70ueg1eCSW6lZ8yF+BbzXG5aeqMxekAu7foXJ3WD1hworRERqk7xM2PkTdLjBCCLys41rQbP/b+++w6MqsweOf6fPJJn0ThJCSwAhEDqCYkNFikpHBMTeXV13ddW18LOuZXXtq6xSpAmCCipiBxVBpIP0lt57Mpn2++MlZUgCAdI5n+fhIXNn5s47lyHvnXPPe86l0Ps6MPur25vnqy/Gva5jY5oTk17r0RKzut2phcQEerHxcI7a4HKquef391VwvNd1AOR4d+RoTu01DzYezmFkQgRvjQ5nSuhRDEm/qmUfF/5NPcBWoOpoTF0KgbFqWeP1S8Hkq+5zu6HfTbgjepN93o2440d6voDezKGr5jNlWQZF1d7H17vSySkpP5sj2rSC42DmV2oJa0V2ZNh5cMuP0P8msARQbHPwZ1phvXZnq6VGyIotydiPf/G5rFsYNw6JrfEYjQYeH9WdhCj/M30nlfQ6LV3CrNxxUWeeH5/A8O5hRJyqRXwzKCxzkFdLx5VOIT7sTKm7+wmA0+Ump7juz5nb4MX3ezJrve/zrSnkl9XeaUe0fcXFxdxzzz08+OCDbNq0CffxaLHb7WbTpk08+OCD3HPPPRQXn+I7xRl47733CA8P57nnniMhIYHo6GiGDh1KTExMg7/WyUigQrR99lJI3aJSUavb/rFnNkEDM9fRXxw4dXcRpx2y9kF+UtW2w2tVvY2TsRXB4XXqPVfYuqjm+yxMU0tJnOUqy2Tty7D3K1g0RV1N++5ptZ/6LFQVQgjR8pl9oc8M8A6DvCNV21M2q4KZxRmqyGZxJoSeB0kbCPHWoTtJ0cVAbyOFZQ4CK9p6a3UQNRCmf6YC5Id+AMCkcaKvYz/t/fQ8FLKeq36dQuBP/1RtUsN6wq7Pqh5kK4Rjv6lgS3kJHP2tKhgPsH0pmrI8fClGc+xXzxdwlOGb+iuXd/Fc5hHobcKoq/00uMVexQ5oX3MJZ0CM6nYC6LQaTPq6zz2q09by1iP9LOg06o5gHxN/uSyOVfcM5Y4LYxndK5KHR3Rl9V8uZPKA6Pp3SWsD9LraP7tlDifedSzpqM5Yx/MBcDur/v+cIMRqwqSXr2rnIqfTyd/+9jd+//33ytsn3g/w+++/8/e//73BMyu+++47evTowb333svgwYO55pprWLJkSYO+Rn3Ip1+0bfYy2P8tLJmmvnSbfFWGBcCvb3r2eW9gUf5eRAfWvDIQ7GOk/anWHOYnVQUS+t8CHS5SJ4/zroH8k6QZpm2rWu5x6eMqwyJ9Byy/HYoyqh5n8YeRr1TdXv8WLJmughQA3a+BqP7q0okQQoi2wVYAiyarDLq+M6HzcLUMZN41KnOv13Vw7Tuw6gHI2E2fUA1/phYyILZmzQCLQUe4r5mMQhvnd6qW6afTgyVQzbvHa0aEZ/7MuJ6BNfah02oYE23DmrUNfNtBQbLKIvz5VbW0IzgeBt+lHvzJzZC+C7L3qp9BFQcNjlc1NzJ2YV48Tr2fE4R8/yD/iN7F2B7+ldvuu7QzQT5VLT8Ly+z8fjiHvy7Zyh0fbeLb3elkFNadst8SBXgZmdw/+pSP8zHpcZ6wDEejgamDYjy6gfhaDHQN92FMBy2vTkzg9mGdiAuz1llvoa0KsZoZ2KHm5/ebXRmMTIg46XPDfc2E+dW9ZNddksc9F3eu9b47hnU65461UNauXcuGDRtwuWrvjFPB5XLx22+/sW7dugZ9/WPHjrFw4UJiY2OZPXs2U6ZM4emnn2b58uUN+jqnIoEK0bZp9epLudagalLcsBJu+EJdrQGwRqjHNIJwPzMf3DCAxBj/ym3dI32Zf/NAogJUoMJgqOOKhCVQrTkdcj9c/A+1DKTzcFVY7GQFMYM6Qa8pcO27qoDm9ctUXYsrn1MdQyqYrHDeNap42om6jYERL6j2b0IIIdoOiz8M/z8YdJeaY8a8DnFXwZj/qLoPiVMhKE5t73IFsRGhjDgvmLsu7sywuJDK3cQGefHc2J68/eMBHhvZrXJOq6Q3qgsDACNfxnLhfdw3wIdxPQMrMzTCfc38b3I8HR37odsoGPYQxJwPvlFwyWOqttIVz6g6E1e9CH1uUBkF1nYqyDLmdVUwc+oS6DFOBTYqghQBHeC+rVVBDiBgx4eM6+6Dl1HHP0Z0ZWiXqrnU5nCyYksK49/5lWV/JLF6Zzo3zfmdpz7bRXZR3QUlWxqNRsPFXUMxn6xYN3DrBR0psjkqs1yCfYy8c31fuoRaa318ScnJW5W2dX4WAw+P6Foju2hXagFdw611ZkQAPD66+0mXs5SVlXFljzDuvaRzZfaEr0XPv8Yn0KNd09YDEC3HkiVL0Onqmx2lZfHixQ36+m63m/POO48HHniA7t27M2nSJCZOnMiiRYsa9HVORcJ0om3T6SF6EExbrr6cV9SkmLIAjvwKcVeCpfEmgs6hPnxwQ3/SC2yAmxCruXJC0xRn0s1apNrE6bxVpw97qVpzavGDPtPVFa6K2hpXv6lOMvWmOl8PnzAYPgsMXqoNa2BHuG5J7QVDdUbwqiXo4R3SaMEbIYQQzcjsB70mq+WFFfWORr9aNbfoTWqJiE8IRPRCaw0nMQAyc/J4YnQ3Ckq7kFZQRnpBGb8dyuL5sT2JD7fibTphzgiIhesWQ9Im6DIczL5ERmh5euBO7rpkIGVuA4HeBsINZcAIFWDYswoueVQtO3E5YdxsmHc1XPgwxF+hMv0qAu4XPwoGs6q9ZPKB8+/DrdHjtJWg274YzfXL1BiGPgCA+8CPOCbMJ8AeyFf3dSbS34K+2rKPlLwynq7WoavCqu2p3HRBB4/Mi5auY7A3c28cwPT/baCsljoUo3tFMHlANH4WA8O7h1FqdxLgZWxxBSxbmu6Rvsy9cQB/+3grKflVmTYfrT/CBzf0558rtrMtuWo5UoCXgSfHnMcFnU/dbS3I28jdl3ZmbN8oim0O/CwGIv0sHtkt4txRXl7Oxo0bK2tSnIrL5WLjxo3Y7fa6L4CeppCQEDp16uSxrWPHjqxevbpB9l9f8m1EtH06PcQMVmtnK/jHqP7rusb/L+DvZaxZGbswHc03T2DYvhj3+A9V1sP8caqA5cwvVMVzi7/nc+rbnaR65kRdz6sonLlkWs37fp+tiqBd8IC0MxVCiLbGfEJwvrY5Qm/yyKoLCfSnIp+i3OGkpNzJZEMMptr6TlYIiFXZERXzrFcAlg6D6Ogx71oq70N/rcrCqLh44BMMN3yp5kLTCVf6fUI8b1vDcDudpMWMpl3idSrzAtQcNvQBNANvx+wfQ/c6hppZWObRIrO6bcfyWly7zJPRajX0ax/Iqnsv4Ps/M1i08RhldifdI3y5+YIOdAzxIfh44KXVtGdtAUx6HUM6B/PJneeTkldKcbkTq0lPuwAvQqwm5tw4kOS8UvJKyjHqtUT6W2jnb0FTzyW0Rp2O2CDvRn4XojUoKSmpd5Cigtvtpri4GH9//wYZQ58+fTh06JDHtsOHD9OuXbsG2X99SaBCnBu0tZxMNUGQok4GC0T1hW2L0Cy9AQzeUF6klqQYm2CiKsqAxVOr1aS4GtqfD18+pG6vfxNiBqliaFKnQgghxHFGvQ5jPQs21phnTzbv+tdSW6G2bSeRnm8jokM3PEZXj4B7jYyQaiJaYaaBVquhU4gPHYO9GZvYDqcbvE06qXfQAML9LITXspQjwNtIwEmWgAhRX15eXmg0mtMKVmg0Gry9G+77w4wZM5gyZQrvvPMOI0aMYNu2bSxZsoRZs2Y12GvUh9SoEC1D3jEoqtaeKT9JFcJsq8y+uHtOxjHoXlXks7xIVe2eshD82zf+63sFw/gPVBCi+zUw4l/QeyqMeUPd33emykKRIIUQQoizkbkX8o5W3S5Kh/Sd4Ky95ekZc9o5L8q/qltVcbY6t6iHSD9LrcUS/b0MdAuvvW5Da6DRaAj0MRFiNUmQQohWwmg00r9//3rXqNDpdPTv37/Bln0AJCQk8MYbb7Bq1SpGjRrFW2+9xSOPPMKYMWMa7DXqQ35rieaXfww+nqkyDIY9pIIUc8eomgydLlXrUNsgTUkWur0rqzaU5UHyHyqIYGzkKzhGiyrOOXP18eJkx1N8z7sGgrtAYKeaqbVCCCFaj+JMMFqr5tDiTFWDqCll/glzxoB3qKoNpTfDmidgxzK4/hMVEG+I7EZHOdojazEvuxn3tE9Ufab1b8Ke1ep1A05+ASDA28hLE3rxr9V/smpbKi43JMb48+y1PYmRdHwhRBObOHEiGzZsqNdjnU4nkyZNavAxXHzxxVx88cUNvt/TIYEK0fyKMiF9OyRvVAUlj21QX9q3fwxR/Zo+UFGaD8m/Q3gPVZyyIAWy9qp2nQ21LKMwDZZMQ5NzEHdYTzRdr4IfX4ClM+DWH6uKfjYmowViBnpuM1nVkg8hhBCtV1EGfP8MxF0BHS+BwlRYcSeMegVCuzXNGGxFsOszlUFRlA4LpkBgB/jzc3X/2ldUK9T61l86mbJ82PUplOWhmTMGYi+AvV+CzqDe+ykCFQDRgV68MC6Bvw6Pw+FSnTBq1JcSQogmcMEFFzBgwAB+//33k7Yo1Wq19O/fn6FDhzbh6JqOLP0QzS+iF0xboU4o9n2tghRdR8OVz6tAQVOyFcK2RTB/rLrqU5gGn94Nc6+GfWvAUd4wr+MdCqP+jTtqAEz+CM6/B656CQbeoXrJCyGEEGcqfSds+hAWTYUtC+CjCXD0F/jib1Cc1TRjMPlAv5tg8N3qdsaOqiBF+6Fw9RsNE6QA8AnBffFjOM8br5ZS7v0SNFqYugza9a33bryMemKDfegc6iNBCiFEs9HpdLz44ov069cPUAGJ6ipu9+/fnxdffLHey0RaG8moEM1Pq1OZCppq/wm9ApunRabRR2VxGH1g60LYsfR4G7dgCIlXveEbglaLKyKRgivewNc3Sv2CSZikunFIpw0hhBBnI7IPXP40fP0YrLpfbQvpppZUNuUc4x0EQ+6DLR+prlYVrn4D/NqpiwH2MgiMPfvX0upxV7TzBlVjyeQj7baFEK2St7c3r7/+OuvWrWPx4sWVLUs1Gg39+vVj0qRJDB06tM0GKUACFaIlSNsBc0arL+lhPSF7H/wxR3XGuODBpq2VoNGoE7zrlsCHV6kgBcD0zxo+XVaj5WBGEb0jj982+zbs/oUQQpybLH6qm9O3s8B5PBNw4O1Nn6VYlK6yE6sHKQAWT4OJH8IPL8DRX2H6CgjqfOavU5yNZv2b6De+q7IzQ7pD2lZVH+OGlRCZeDbvQgghmoVOp2PYsGEMGzYMu91OcXEx3t7eDVo4syWTpR+i+Rm9wStInVRN+0QtA9GbIbR78xTSLEyFtS97bvvldXXCJYQQQpyFcD8jmupf3AvTwGFv2BfJOQTzxqoghd6ktq26Xy2vLMlp2Neqi60I1r+jshMBogbAeWPVz+nbYfkdEN1fFdRe96qqM3GmDGYI6Qo6I+6py9S5RK8pqpuWsfV27RBCiAoGgwF/f/9zJkgBEqgQLUFgB3VSMeJf4BMK0QPg7t+hx1hV3LEplRfDutfgwLcqPXbc+1XLQLZ9XJVhIYQQQpwmTWkuoQeXotn4nsoyyEuCj2+AI2sbNlhRnAn5R9WSxRkrYfgscLtgzypI+l0VjW5sJh9IvB4CYlVNimvfVksrE6epCxQDb4Pf3lHdvS5+BMx+Z/5aRm9c8SMpv/03XNGD1Pw9/CmVTRF8FpkaQgghmo0s/RAtQ0Bs1c9aHfhHN884jN4w+E7VUm3E8+oKTWBH+OllOO9alVIqGl1eSTlHskvYeDiHAG8jvaP9aR/ohV4nsVUhROulKc3BsP4NcDlUBkHS76rj1cr7YeaX4Bt56p3UR7u+KjuxME21+06cDuP/Bxm7VdHopprLgjrBtOWgM6maFN0tKjtx8gJY9QDkJ8MNX1S1yD4bBgvbj+bSO/B4h4/mKMbtKFd1OUB1NDP7NVxtKyGEOMdIoEI0Lacd3ID++EmSvax5lnecTEB7GD+7quBYZB8Y/VrT1so4h+WWlPPGd/uZve5Q5TaTXsucGwcwqGPQSZ4phBAtm8s/BseEjzB9PBV+e1tt9IuCqUsbLkgBKuDf/nzI2AP2UtjwLuxfowpbdh0BBq+Ge61TCeyo/s74E354DnatgPVvVWUorvu36gyi1YNvRNXzitIBjcq0bOlshbBzBeQehsF3qSU3X/8Tek1WrVIlWCFaCafLjU6rae5hCAFIoEI0JaddFc1yOVUaqL0Iti+FjhdBcJf67aMkR3UEAVV8s7y46vZpyCq0kVNcjkYDVrOeYB+T59X66lXRNRoJUjShw1nFHkEKAJvDxb0LN/Pp3UOI8LM008iEEOIsaQ3Y/Tpg8gmFghS1rcNF4FWzE0dJuYPMQhtuINTHhJepjlO2ipoTXoFq+YitQN3WmcgsLKVo5GJM5blEbHsTzZ9fQJfL1UWC6nNn9bm1MWTuhR+ehV2fqtvt+qmMkoxdavmHRgMBHVStKms4FGXAd0+D1gAX/aPlz8GluaoGiNOujm1BkgrIHPgGblunskmEaMGO5qgs1lXbUvE165nUP5ouYVaCfUzNPTRxDpNAhWg6uYdh/jjArdI+U7fBd/8H/u3hxq9OfTUp409VwXzEv9RJy4HvIWUzDLxVFeOsB5vdyaYjuTy2YgcHs4rx9zIwfXB7ukb40jcmgDDfFpbdcQ76aV9mrdszCm1kFtgkUCGEaLU0hSl4rbxTBSlMVpXtsGU++LaDQbdVzmVHs4v51+o9fLE9FYDh3cP4x4huxAZ7e+4w+wDkHIQN78GIF6AkG4rSKMtO4veg0Tz2eS6Hs50EeAXxwND/MNL2JYFf/1PVhYjoCeE9PedW/6gzf3NOB+j0VT9rdSoAAWDyVYU0934FUf3VzwaLClLkHFLbvp0FR9fDlc/D90/DH3OPHzQNXPQweJ9GsMJRDqXZYK2WoVFeCmV5nlkbDcUaqbJiPhoP699Q28x+avmNBClEC3cgo4gp760no9BWuW3FlhRG94rgn6O6E2qVc2PRPGTBt2g6XoEw5C/qisNHE1SQQquDkS+dOtBQlAEr7lCFwJbOhJ3LYdEU+PF5daWmnvZlFHH97N84mFUMQF6Jnf98u5996UV88scxbHbnWbxB0RB8zXWvnTbo5VeWEKL10jjK0BalqOUet/4A132sljxk7FJfroGMgjJunfc7K7el4nKDyw2rd6Yz88MNpOWXVu2sOAuO/KKWdexbDQsmQsof8Mlt7PUZwLQ5WzicXQJAbomdf36dytdeI2HgHfDDM6ot+J9fwNzRam797R2VpXgmsg/AruVqCYTTAcfWQ/ImcLvV/b7hEDMYJsxRQYovHlTLUibMUV/wv52lLmbs/AReT/QMUsScf3pLVZx2OPQjLJgCeUfVtvJS2PcVLLtF1cVoaDq96lQWFFe1rcOF4B/T8K8lRAMqKLXz+Kc7PIIUFT7fmsrvh3NreZYQTUPO+kXT8QpSVb4r1qsC9Lvl+PrNU6SW+YTC2P+qk7ukDbD8NlXB/LKnILRbvV7e7nTxwc+HcLlr3jf3l8MYdDpSqp8EimYxpFNwresjE6L8CJeMFyFEK+YK6EjJ+EW4p62AoM5q/rv5WxWwP36lPzmvlD/Timo891BWCcdyqs1R3sEQO1QVygyOg6y98MXfKI+9hPd3OCtjBNW9vC6LNK/OEJGolissmqIuBHS4CAbdoQpKn678ZJg/FpbdrJZzHvlZ3Z47RmVLAJSXwKGf4NO7VJDC7YKtH4GjDCJ7w5XPgeb4KWlFsESjgbGzIX5EvcflZTKgPbIOFk6C1M2w8DrIT1JBiqUzVXeVT25V2xpSYRp8+RBk7FSFSjVa2P05/PKGynIRooVKyy/j5wN1f0bf+fEA+aXlTTgiIapIoEI0ndJc2PShSlOtsGm2SvWsT1s2/xg4/76q20ZvSJgIFv96vXy5w8WhrNqvFmUXl+Nl1FFSLhkVza19sBfvXt8XX0vVyrTuEVZem9SbAG8pSCaEaN32ZLtwBRwP2OsN6ot6ta4XBWWOOp+bW3LCFwa/KPXFeMCtlZtsPhEczq15dRQgs9BGOQa4+B+ed1z62JkvUbAEwCX/VD+v/IsKUDhs0O+mqpajeUfhk5vVl/bhs6DjJaqF6sIpqj5G1ICaFx38Y6HDBWCsfzaFw3V8PPrjSwTTt8M7Q1WQoiJyE9Be1b5oSPZSdRHF7KcCT9OWq3+XA9+rII0QLVSpve7fN6BqutnsriYajRCeJFAhmk5Jtqr4rdXBpI/gwr+rFM3P7oGS2usSVHLY4OAPsPrhqm3lxbBkhupDXw9eRh3Du9feruy8SF/SC2wEeMkX4eZm0uu4pGsoq+65gGW3D2blPUOZd9NAOoT4NPfQhBDirLlcJz/pD/etO8MwKqBajR6HHZL/gLIC+PrRys3eqRu5tEPt2We9o/2wuvJh3jWed3w0AdK2n3LstTJ6qayHvjdUbQuJVx1GKlp1WiPg8qdhzOvQdyZc8yZ0Ha06bGkN8O1TkL7Tc7+5h1SWQmFavYdSbrfjCu8FMz4D4/E5ozS3KkjReypc9gRYG7h1aWAHmPYpzFgJEb1UwfAZq2DinOZrty5EPfhZjJgNdX8dTIwJwGqWkoaieUigQjQdvxi1HnfKIugyXKWZDn8arl926kKaZXmwZYHqGHLZU3DvZnUlKW0rFNXvJEaj0TCiR0SN5QMGnYZbLuhIQpQvkf5SqLEl0Go1RAd60Tc2kB7t/AiSqtNCiHNEpL+Fmy/oUGP7lAHRtPOvll1gy1fLPQ79qIL5A++Em75Gay/i6qhiQq2evzeNOi1PjOpOQNovVcs9/rpHBQxKc+Hwz2CrueTklJwOVdh668KqbZl74M9VqmYFgMUPEqfBedeCvRiy9x8v3tlBdQOpXpOix/iqZSA7P4HVj6nx1pdGo+pF9JtZ876LHwWfBg5SVAjuDBEJ6medHmIGSpBCtHiRAWZmDqn5+wbUf6VbL+yIxSiBCtE85JMnmo7eqNbj4lI1KfQm6H9j/dae+oSpiuYJE6H9ELXcY9oKVUwsone9hxAb7M3i2wbx1Y40ftiTSUygF1f1DCfEaqpZTV0IIYRoYlazgTuGdWJo52DmrT+Cy+Xm+kHt6RXlj59XtSUL3sGq1WhIV4i7Qs2NtkIY/z9iS/NZcmsfVu/O4Ic/M4kP92HKgBg6hviA/QqYslh1/LCGq/oYvaeo55vOIHOtOEMtrXDYYPA9ENpV1aJYdT90GKa6m4Cat4vS4ZunYMtHMPIVFZToNho2zwWXA8a8CfEjof9N8OFI9U0pYYLqEFJfjjLY9zX8+kbN+xZMgikLpMilEMcZdTpuOD+W3OJyFv9+rDL5yGrS88L4BOLDrM07QHFOk0CFaHi2QvWnIkuiIBX0ZvAKUOtxqzudwl3WcIi/qqrdWXAXVYxMU7Pw4sm0D/LmtmGduGFQNGh16LUadG4n6OW/gxBCiOYX5GPiovhQhnQOwu0Go15X+wOtYarYNKi50Du4cplDrEbDbSFWZgyOxajToq0oUqyzqsBGxdx54tx6unwjYeoy1UFkwC0qqKA3qwBF9Vagbjcc/U0FKQBWPQDlReocYfRrUJYP+7+Bdn0gdSvM/FJti+gFG99X2RgBsScdirfZiPbAt7CsWk2KmMFqWUt5kapZsfA6mLJQsh2EOC7M18w/R3bnxqEdSMsvw6jXEulnoV2Apdbi5kI0FflmJhqWrRB2fALblqguHVodfPUQhCeoKySWgLPb/4knUmd6YpWxG1POQVXQy6WBQz+AbxSE9zi78QkhhBANxKCrI0BR3SnmRbOhln001FxaISJBBRHMvup2/AjVdrV6Ry+NBmKHwJD74ed/q21rHld/h/cE71C49J+qXkb+MbjoYeh7I6x9WbVg3bIQpi45abCi3OmG0I5g9lfLWXpPVcU7846qdqzlRdBx2Om1OxXiHOBt1hNnthInGRSiBZFAhWhYpXlqvWlhGiy9SZ207FsNB3+EnhPOPlDREPKOwZxRqrjnuP+pytxLpqtq3bf9JCmhQgghxKmU5qvaExXc1YqE1pUt6RUEQ+4Be4kKPlRI265qWJn8qoIbPzwPf8yDguTj+/QCzckDN3a7HVdIb3QzVqrMjaF/UVkmXkEw43PY8yUMvL2qyKcQQogWS4ppioblHw3TP1M1JY79qoIUZn91ghDQvrlHp5j94MKHVFro0pmw+Hp1gnXBX9VJkhBCCNEKZRSUkZJXSqm9EVtt24pUEc/Vj0B+surAVZQJP72klmycirNcZTicKO8oeIfA1KVqWSdUBSkiE2HivPov1wjvAcMeUp3FnA6VzRHQAXpfJ0EKIYRoJSRQIRqe2R+CulTdtoaDdzAulxunswX0Yjb7QsIkVYSsQuwFqiK5RQIVQgghWpfMwjIW/HaEa9/6hcte+ZF/LNvOgYwz6OBxKtkHVJ2HuVfDlvnw+T2qxsT3T8Ovr6vlFem76n5+YSqsfAD2flnzvi/+CtuXqPoWkYme90UPPL1Cn06HytJ4axAc+03Vutj0gWrLmn2g/vsRQgjRbGTph2hYBamqJsWRdaqHuc5AQcT5/Hk4l/k70yiyOZncP5re0f6E+tbe573ROWxw5GdVtKvCkXVw6CfoPByMrbxFad4xdcUqqJO6XVagqrL7tju9yulCCCFavHKHkw9/Ocyb31d9AV+xJZl1+zNZdsf5tA+qZ9HqwjT15T56EJitkLVPtQaP7AtaLRSmw8czoNdkVXeqIAX2fwvvnK/mVYDgeDD51r5/txuSNsGeL9RtrU5lSRzbAD+/enwMqbD2Fdj+sedzf3tHLR0dcCt4BZ76vdgK1BxvK4T516p6VHu/VK+ZdxQCO559XQ4hhBCNSjIqRANzgb1MZVXM/BLbTT+y1HcaExcc5rOtqXz3Zwa3ztvEE5/tJLvI1jxDLM6ET25Ryz0ufQKueFadQC2/FUqzm2dMDSXvGCyZUXXVqKwQtiyAN/qpkzZ7aXOPUAghRANKzivjvZ8O1dieVVTOxsO59dtJYTp88Xf4aDxsWwTZB9U8MmeMyqAA1WFkzBvwwwvQ4QLodInaXhGkaNcXxn8A/lG1v4ZGA7FD4bJZKmAwZbG6ODDkXlVg0ycUuo6ETbPV4yMT4a7fqpaBrHtFBU7qwysQzr8HBt6hxleRwTF5IbQ/X4IUQgjRCkhGhWhYvu1g9KvqKkZIPMmZRTz/fc000C93pHHzBR0J8jHV3Edjs0bCtOWQvAl6XadOWPRmCO0G1ohTP7+lcjnh6HpI2aRuz7sGuo6B9cd7ya9+BCL7gF+7ZhuiEEKIhlVUZqe8jmWVO5PzGd+3jsBBdSZf6DEO/vwMvnhQBRJcTogaAJZqNR3Cjtd+sBXWLJhp9FGZFydj8Ye+M6DbSPCLAb0R9McLbCZer+anKYtVIc0JH6ji1lOXqlpSV70I/qdR60qjUzWpPMbofcqCnEIIIVoGyagQDc83EkLiAcgqsp30BKpZaLXQrp86KbL4Ha9ZMVGtgdW24hMYrU7V3bj8GXU772hVkMIvCq5fLkEKIYRoY3wtBiy1tSAF+sXWs9OW0QJxV8ClT6rbLqf6kj9xTlWGhNMBx9arjh1Z+2D35577OPQjfP4XtSTkZCz+KktCb6za5hUEwZ3V8sQOw2Dy/KoOXIEd4PplpzdHl+bBHx/Cj8+r50T1V9vnj4WkDSqLUgghRIsmgQrRqLxNdSfthPs1U40KUMEKU7Ve0SZr6w5SVLD4qarmEb09t4//QJ0ECiGEaFPa+Vv42xXxNba3D/Kid7R//XeUfww2vld1uywf+67PycjKpLTcoVp6f/e0WpJx8Hv1mMg+cNMa6Dpa3T78k3rc2dAba2Y3WsNPb442WCCkK+iMarnHdYth8F1qWapXoCz9EEKIVkACFaJRtfO3MKhjzcJXgd5GukVYa3mGOCtlBbBtCaRu8dy+7CapdC6EEG2QXqfl2j7tmD2jH33bB9Ax2Jv7Lu3CvBsH0C7Aq347KUpX7brzk3BHDaDsyldAo8Hw1d/RZu/j32v2kubyg7H/VfUspn0KcVfCNW+BLR9GvAAJk9X20PMa9w3Xh96kamjc+wd0vEhlbAz9qwqqhHRt7tE1j8K0mrdthc0zFiGEqAepUSEalb+XkZcm9OLfa/by6ZYUHC43gzoG8tSYHkQH1rMSuagflxP2rVFdV0At94gfBRveUctA5l0LM7+U5R9CCNHGBHgZubRbGP07BGJ3uPD3MqLTnkbWgE8YXPsOfPt/FF7yPH//MoUnr3gXU/Zu5u/V8t+fD6HTafnr8Dj0vSaBzgBXvwnewRDYGfQGVZjaEnDqOhWNyGistpxEbwK/6Krb3kHqTxOyO53otVo0zZ3BkbEbPr5BZVeGdVfBpq8fU63Ze4z1zDA92W4Ky8gqtOF0ufG1GIj0t2DQyTVPIUTjkECFOCXtWZ50RAV48fS1Pbnn0i64XG6CfUz4WgyAqmHhcrkJ9Daib8DJzu5wkZJfSlp+GWaDjgiLk9DC3aoqudECqdvVyVRYC7jy01C0Oojur5Z9lGSpK1s+oeAfDWseg8ufBks92roJIYRolXzNhjN/clgPXGPe4skvjvHVnjzszkg6+Ufx39/VUo4Pfz7M1IExRFVkaXgHQ1Gm6qBVkgWa40sqCzNAb4H8o6pIZ0Wr7IZUmKrqZLTrW1nUU1OQTFdLDjhtoPNSXa6asCV3Xkk5x3JL+HRzCoezi+kc6kPf9gGk5pXSLzaITqHemOxFKuMxtJuan5tCfhLMGa06ns0ZBdM/Ve1gty9VbWCtYdDlijqXw6QX2tAGxbD5WD5fbE9l/vqjlDtdmA1apvSP4YYhsfVvgSuEEKehRQcq3n33Xb7++msOHjyI2WwmMTGRBx98kI4dOzb30FqW/CR1NT3geDXsnINgtIJPyFnt1u12cyy3lFRNMLs3HqNzmJUSmxNfk4b2VggKrrb/8lIozgDvUBUIKMqE8iJVBAuwlKYTq7FBiLqdkZXJdweKWbQxickDYvAy6sgrtdM51Id2vgYKbS52phYS4GUkPtxKex9U61CfMNDqIfewOjkK7gKl+VCWC75RoNNTUu7gm13p/H3ZNsrsqpBnpxAf3pzck/S9GaQWOekWGkR06W4CdUa1j7bCPwYmzQNneVVLt8RpEHc5+EarfxshhBANI+eQ+jJsDQeHHQpT1DIDk0+9nl5QaudYbgk7kvMr57uYQK/TvwKfc0gFCbyDVSHJ0hww+UN5garT4LCB0QenrYjNeV7sz7ZxRXuw6uy4/TtwNLeEXSkF2BxOrjwvnNxiO9/uyeDbai9RanficFYrQlmYDt88qZZY7FoOjnLofxNsXgAX/lW1NrX4w7QVtQYrMgrKOJRdzMHMYmICvegU4k24Xz3mqMJUWPkg7FkJ174L3UZDcTaa5bdhOLYe96SPVABj8zzoMR4CY0/vWFZ/qTI7ybmlbE/Ox9ukp1uElZhA7xrZKllFNl7/dh9zfj1Sue2b3RkA3HJBR3anHWZUz3CGFHwFn98DfabDJf88q2BFYZmdpNxSdiTn42PS0zXCl5hAr5qZNJYAVWR7+a2qfsg7Q6vu63ARhPWsNUiRW1zOd3+m88JXe8gotKHVwLC4UP49qTePf7qD7OJyPvjlMF/tTGPhrYOIlWCFEKKBtehAxYYNG5g6dSo9e/bE6XTyyiuvcNNNN7Fq1Sq8vOq57rKty0+CZbeoyWfqxyo4MGcUdLsaLn7krCbBbUn5XP/+bxTaHJXbJvWPxqDVkJyVx3NXuwkPDVVBin1fw7KZMO4DiB0C3z8Du1bADSvVVfzP/wKZu2HaCkrcJt74PplFW3J4ZVIvnlm1m9T8ssrXuLBLMOd3Dub5L/8EwGrSs2D6efRcfpnq4R7QAb55XLUXnbYcjvwCXz+qulpED+RwdjH3Ld7iUdT7QGYRf/tkFwM7BvL+WtVv/tqewTxyhT9nF85pgSoqpVew+Kk/QgghGk7WXph7teoiNfJlSNsBCybAVS9Dz3GnTKfPLS7n3Z8O8M6PByu3+Zj0vHFdIt/tTueirqH0aOdHqLVa4enCNBWs9w5WtwtSVGDigyuh9/Uw5C9wdB0suxlG/ludA+z/FsrycEcNRLf6YSJHzqXEEItpzbNonEWsG/A2t8zfgr1aEOKB4XG4cfPDnszKbf3aBxDgdTxjozQX1r4EWxfAtoVwxXNqqcXiqerCiVYD/W+Gda+oJQZXv6mKWB6XnFfKvQv/YNORvMptnUO9+d+MAcQEneT8zumEvV+rIAXA8tugLB92rUBz9BcANMtughtXw3f/pzqTXLdYBZJOU2GZnY9+O1p5LgJg0muZM3MAgzp5LiH5Zne6R5CiuvfWHuTZa3vw/Fd7mN2jhFCAP+ZC/EiIv/K0xwUqwDV3/WFeWr23cpvZoGXujQMZ0OGEzEmjN3QbBfZXYeVfqraH9YBr31ad2k7gcLr4ZHMy/7eyqr28yw3f78lgR0o+D4/oyt+WbgMgNb+MV77ewwvje9XZfUYIIc5Ei15YNnv2bMaOHUuXLl3o2rUrzz//PCkpKezcubO5h9ZyuJwqSJG1Bz4YAR+OhJIcdTLjdJz6+XXILLTxl8VbPIIUAIs3HqN3jD8/Hy7it2Mlx8dgVymFLicsnaFSDDd9AI4yKC8Bl0NlW+QdhQ9GkJx8hPl/ZDGiZzjLNiV7BCkAftqXhVajIczXBEChzcFfVuwnq8+9sGgyLLke9nyh0jpzD8FPL4LTrk5W3E6+/zOz1s5j25PziQurOnFcvj2LHZlnfoyEEEKcwxw2Ncft/kxdIFgwQc13halqTjqFQ1lFHkEKgCKbgyc+20mQ1cyNH/7OP5fvIKvQpu4sTIc1j8Mvb6h5PvugylrIOaiuiq9/E354BnKPqPn483vVl/WN74HRB3dhKrgcRK6azoW/zMRr/0qSe9zB3Yu2ewQpAP79zV6u6V1Vz8jHpOepUXH4eR2vAWEJUC2+zX6q1edXD8PK+9XrGr2h2xh1XMJ6wojnPYIUbrebL7anegQpAPZnFPO/nw9R7nTWfdB0Ooi/SgVBKnz5d3XBAlSwZNS/YcUdYPCCq15UmZ5n4GhOiUeQAsDmcHH3wj9IySut3JaWX8q/1+w98ekePvrtKIM6BpPvo7JKGfYwRA84o3EBHMkp9ghSAJTZXdy9wHNsVQMvgiPrPLcVHg9y1SI5r5SXVu+p9b7MQhvHckvoFFKVQbFqexopubW8rhBCnIUWnVFxosJCVZ3Yz+/0rw47TzbxtWa+UWivW4Lmw6ugIBkAd+yFuEe9gts7TF19OAMZBWUcyiqu9b5NR3LpFmFl/sYULj0vEovBG02PCWjspWjWPAYZKgLvnvYprohE0GjRTJyHZt61aLL3kWvT4HLDwA6BPLZiR62v8e3udM7vFMzyzeo9HcgsJqPdZQS7HoXMP1U9hjGvw+pHoSgd94QPcXW8CDRq6UddnC7Pk7HFvydzYVwTrRM9cSzH/23a7GezmchxbTxybBtHcxxXne7srnzKZwAI6Y52xudo3r8EMtWXOvf59+IecCtuk1+t82/FcXO5XKzZlV7rbo9kl1QG6lfvSmfm0A4EeOnRFmei2bkcnOW4i9Lh6K9ocg/h/ukluOYtNG8Phk0fQtdRuC9/Gs3Xj0G6urBjj7uKRcnBjEwsIXDz22q8OgPHvHtSZNtSYwxuN9jKy7njwvZEWnUMsWbQYc003GPfw1XROjS0h3r/712iAjQVxrwO3z+L2+WAyR/hskZ5HIvcEjuLNx6r9b1/8kcSt17QofL918oSiObCh9DYitBsW+R53+j/wC+vQ/oO3Jc/o85B3O4zOhfacCin1u1ZReWk5ZcSZlVBm5zictILbCfd186UAqYNao/ZVXrKz0h9rD9QewvYjEIb6QVllWMD0BRnoFnzGJrtS9UGnzDV5aUkB+aMwj1jJa5gz/a26QVllNrrHtvavVn0bR/IgUx1nuh0uckqshEbJMtLT4fMqY2jNc6ponatJlDhcrl49tln6dOnD3Fxcaf9/O3btzfCqJqfwWAgzs+O2V5StbEwlZL8XPYdSMflUjUaNBoN5oAwsso0lDpctLMacBdmUF5eXut+Nf51d4Yw6XXYnW78LDqSjh2juCCP6EAzgZl7PD5Q9uwjHC3xptjmJC7AjcWWD0CAwY5WA04XGHRabA5XLa+hxe703K5zVjsRcLugLE+lc+YexpG5nzRjFzIKbAzpEMmb39ccd3Sghawiz5MJL6OOgwcPUlBQUOf7bWxt9bPZ3OS4Nh45to2jKY9r3759z+r58hkAb4uJDpoUTK6qk2FX1n7ys9I5lHX4pM/dt28fhpN05dBWqxmwbm8G1tI0NLjpNHERpiWT0GxdAIA7rCdlo99Gl7SZyq+mQZ1qtKPWFKTQPTgCU1K1cbmc6DU1598Kvs5cHsp8AvYdhdzDlI95h2NpueQdUAEWH4uRTpoU9O4T9lGSDb7t0KTvoLQwh71H83A4qgIZFv9gTPraE3pNeh15eTmkHqw9iFOhc6gFa+5hahzBonTV8Sp9B5rvn8Ee2pv9ZX7YbLWf69TFYDCgo+6aC/ZyG1u2bFE3/GounTiRRgNRfgYifn4fl9lar89IXYxGIzrqDgjYbWVs2VKVqdMx2IRvUTY6wBV7IaVX/htD0q8YV94NDhu24nz2pu/Ebq/KArL7RJx0DAa9FqfL89/dZiurOibitMjv08bRmuZUUbtWE6h46qmn2LdvHwsWLDij5/fs2bNNRru0eUfQzL4USnNxx14Ihalosvfh/elMel2/DLdVTaAZhTbuWrCZP47mASqNc+ntg+keWvtEXFDqoE+Mf+Xjq+sd7c+cXw/zv+sT6NIxEk1pHpq1L6LZMg8MXri7jUGzbRHGz26l05QlEBOH5n9XQFEG7nb9ichYy9TEy/h2dzqjEiJY9kdyjde44rxwXviqKuVyQHs/wg8vB5Mv7k6Xotm1HFY9gHviPDRFmRh+eJqoEX5E9ppCvsPA7cM6eqTUeht1/O3yeJ5etdvjdab0i6RjbPDpHvYG4XQ62b59e5v9bDYXOa6NR45t42iNx7U1jbWxaJM3ovlwKrhduM8bi+bAd+j2fkGAwYz/lc/j9qo5t1T8W3fu3Jkr/Ev5z/cHazymV5Qfe9IKK2/HBHnTtau6eKDN9wajj6oRAdCuD2ZnIZrP7wDAfdXLaLL3otn0gVoG0W0MbP8YfVEyfQ5+h+bgl2D2pzTmIix7VxCd/TOh1mAyCj2D+Eadlnjfcjj0k9pv76nou48i1nC8foTTjvbIT2gWqvePzqi6fjjK1FKMEf8C3FgWTyBhxue4gnp47P/mC3Tcv3hrjfc+c2gscdHhaGLq/qKsKUxFs/w2NMfW17xzzeO4x7wBHS9C89XDmL59lO5TFuP2Pv1qVOasEnTaPTUyMWODvIgN9Se4o8rGzClRhcD3ZxTVua+hnYLoZN+H/uhaAAJ0evxHvKAyX8+AMbMY7Zd7OGFodArxITbMn6COnpmimmvexL3pQ+g7A7NPBPiH4zaZIbAjhrBenHdCMc3UAhuB3kZyimsP8FzWLYz311Z9di0GHTEhfkQHnH4tkHNZa/zd3xrIcW07WkWgYtasWfzwww/Mnz+f8PAz+yWo0+na5ofVZFWFMwvT0Iz6t2rL9dFENP1vRmP2U+s5gQNZxR5BhyKbg7d+OMBLExIw6mselwAfHS9N6MWt8zZVTr4mvZYHhsexclsKd58fTq9wszqmXgGqD/f2JTBlEZrQbhDVDza8hyY4Tp1UJUyGpN/RjP0vPm4X9+zdwLfl3fGx+pGcV8r6gyrFUqfVcOuFHTiYVURBmboCEx/uwwtXd8Fvye0w43P1vvyj4eCPaELPgyufh8/uRtPhAnRmK4HAnRd1YnSvSHYk5+Nv1hHrb+DVHw5XnowZdBr+MbwD8aHezf65aLOfzWYmx7XxyLFtHK3puLamsTYa3yiISITOl6IZdAfkHYP516DpMx2NJbBy/q2NTqejQ7A3r07qzcOfeHaouvXCTvx9qfoSbzHo6BsbqI519kGYP1YFKazhUJKD5o85qk7EhX8H/xg0510LadtU68mx76v6Ve3Ph31rcPe9Ec3Rnzl45Xy+SzMzzr8zYQeX87/pb3HTvM2Vyxd8zXremtiV6B+nV45Xs30JmoSJEDME9AZVuDtzX1VNitH/UUsyP79P1YvKOaQyGw79hOb759CNftWjTsXQzsFMH9yeeeuPVNaUGtUznLGJ7dDrT3Jq6nSo4ElFvQW9CaYsVkUzf5+txrr6H3D7z2ArQpMwAY3vmZ03tg/y4p3r+/CXRVsoLldZM1EBFt6d1o+wat1JQqw6HhvZjRs+2FjrfrQaeOCidkQ4tqtj5HKi2f0ZmsRpEHfqbIzaxAZ58/bUvty/ZAslx8cWE6jGG+pbS7aFXzu44AE0Fe1adT7QdRTozehq6fjRzt/C82N7ctv8TTVqfnWP8EWv1XgEt64f1J52AV7oGrDN/LlEfp82DjmurZ/G7a6t7GDL4Ha7+b//+z/WrFnDvHnziI2NPe19OJ1OtmzZQu/evdvuh7UoQ03eFemH+Umqd7nZt/IhK7elcPeCzR5P6xMTwNybBuBjqvukIKOglMMZ+TjcWvy8TdidLnwMGiLN5Xj5V4vYu1yqgJg1ArRaKCsEW746UQEozlJXWipu5yeByUq2w0xhqY3cUgf5pQ5CfExEeLspcOhJK7BhMeiI9LcQ4qU7ntJ5fElK7hFAAwExqqBZcVbVfbUpTCPbYSSlREexzUGol4ZIXyNmr/q1kGsM58RnsxnIcW08cmwbR2s6rq1prE0iP0kVbaz4Ep6frIo36g21PvzE41fucJKaX0Zafhk6rYZjOSU8+dlO8sscdArx4eUJCSRE+aPVatRyjnnXgMkPpixUbbrnj4X+t8CAm8E7RF28cDpUzSrfSHV+YPRWgQWzP47iHPbb/MkrtRNnteOvt6MNiCY1r5TU/DKcbjfhFjftlo5Cm7kLrn5LFetc+5LqNHLrT1VzbWm+6voR3hPWvaq2XfwPOPA9xF0Ji6aottjj3qt1fi4qc5CSX0pOcTn+FgOR/hZ8LbUfNw8l2bD+HfjlNdX6NGqAyir94Tk02xbjnv4ZmnZ91DmH4exqJjicLlLySkkrsGHQaYj0sxDmZ67xuMIyO6u2p/LEpzs9lrN6G3W8ck0nhsWFYDZb4OAP6rhc8Rz0mqyCTGfIfnxs6fllGPRaIv0thPnWHNuZKi13sju1gFfW7OX3Izn4WQyMTYwiOtDCU5/vqnyf/doH8Pp1iUTUp7Ws8CC/TxuHHNe2o0UHKp588klWrlzJW2+9RYcOHSq3W61WzOb6/TKWD6uyP6OQkf9Z5zGBvj4lkdG9ThLNL8nFnbyRLEMUQcEhaFM3Q2SfqrZoZ6IgRRVy0upUgKEku9bWWOcC+Ww2DjmujUeObeNoTce1NY21JTrV8SuxOUgrKMPudBPsYyTI54SiktkHQGdQbaiddhVE8Ao6u3n5RI5yOLxOZW7EjwBHKWyaC50vhYgEz8faCgENlGSpQgz+7VUnCZ1eBUl0ppNfRDhTJdnqdfzbq9cCXIUZ2Auz0IfGoTtZVkYjsTmcpOSV8WdqAWn5ZUQHWogL1BPpq0fv5a8e5LAdD2YFnVWQoinll9hIyS4AvZHlfyQz++fDOF1uOgZ7c99lXRgQG0iEvwQpzoT8Pm0cclzbjha99GPhwoUATJs2zWP7c889x9ixY5tjSK1WbJA3H98+mJe/3kNWUTk3D+3AkM6nOLEpTEXz0QQCe0xE4xMM69+CmV+e+QlRxm5YMBHGvgcRveHgd7DmCbhuCQR2OOXThRBCiLbMy6SnY8hJMv2COlX9rDNASHzdjz1TeiPEDlWdPIxe6k//m8FsrflY0/FtpmpjtvirvwMbMWPRK0j9qcbtFcTOfUn0Cqu7SGljMunVcp4OwXUX4URvgqCOTTeoBuBj0lOScZTevXtz//A4pp8fi9vtxmLUE3xiIE0IIRpQiw5U7NlTew9ncfr0Oi0JUf68PbUv5U4X/l7GUz8pIBb3mDfQfXa3un3ZUxDW4+TPqYutEHZ8AnlHYe7VMOAW+PVNVYTryM/qiouuHmMSQggh2rBim4NDWcWs2ZWOzeFkePcwOoX41G/ebih6I1Dt9WoLUpyN0jxVU8vneDHJwjS1ZNXodVa7bcFJwm2CxagnytiivzoIIdoQqXpzjvEy6U99spN3TAUWHKXgLIcZn0NgR8jaq9Z8ngmTFQbeCgNuU/v45XUVpBj+f9B1tAQphBBCnBO02rpPvWwOJ6u2pzLq9XW89u0+3vnxIOPe/pX31h6koNRe5/NaldJ82DwPvpmllocUpMCnd8GeL6C85NTPF0IIcU6QQIXwlL4T/nsh7PwUbIVoXA5YNBX36FfhyC81erOfFpMvxAz23Nauj2fKqBBCCNGGdQvRoylKVzfKSyBzr+qUAaTklfLY8h01nvPm9wdIyi1tymE2Hls+/PAcbJkPXz0MK+6E/d+on0tzmnt0QgghWggJVIgqDhtk7oGSHPjsLvjqH/DVQ2ArgKz9cP0yVd37TPd94FtYdqO67d9e/T1/HCRtVC3OQBXIyk+qel5+ktomhBBCtHLazF2Y8/ahydgJhemw50vY8K4qilmSQ1p+GeVOV63P3ZNW0MSjbSR+0TD9M9WNZMcyOPi9qn014/OqzmBCCCHOeRKoEFX0Joi7QrUjA5WG6XZjv2QW7h7jVBGvM81+cLtVC1NQyz1u+VYtA8GtloCACkj8+jZ8PBPyktSfj2eqNmQSrBBCCNHaaXTww3Novvw7JP0GKX+oLljvXwpHf8Wsr/u0zK8+rTtbA41GBST8oqu2hSWo9qpCCCHEcVIRR3jSaGv2HTeYcZ9JTKsgBcz+qjiW3gSRiXDPJrAEgcUPhv1NVRIP6qRO1GxFqid7QTIsuV7tI2UzFKZA4vU1KnwLIYQQrYajHI7+ouo9gep61a6PyioweMM3TxE56Qtig7w4nO1Zq8HXrKdTaPMsk0zOLWXj4Ry+3pVGl1AfRiZE0jHYG73uDK915SfDZ/dA5p9g9FHdRQ5+B988CZc+Dj6hDTp+IYQQrZNkVIgqDhvsr7Y8o/1QAAyr/452z0ooL67/vnKPwPzxsPcrsJdC8ib43+VqH5bjvcO9QyAkTgUpAALaw/RPwRqhAhQpm9XP01ao+4QQQojWSm/E3fFS3Bf+Xd0uSCEjeCC/j17DqotWseWqT9EZTcye0Z/e0X6VT+sY7M1HNw+ifdBJ2l42kuTcEm6as4G/LN7CF9vTeO3b/Yz6zzq2HMs78526HFCYqpZ73LwGblilloHkHVEFvIUQQggko0JUpzepdEyTL1z8KCRMwr33KzQr74fATqC3nHofAE6HCkxk7FRBj4F3wB9zVJBiywIY9lBVn/UTGb3JGvxP0k1qnWp4eRJBxqY/ORNCCCEamibvMJqQeAjqTNLQ57n9JwM7UjOO35vMhV2CeWFcAh/MHEB6fhlOt5tQq4kQq7lZxvvzgWz+TCvy2FbudPHI8u0svGUQQT6m099pQHuYskhdxAjtqpaG3vg1WAJUq3IhhBACCVSIE0X2htvXqSUbZl9c8aNwRPRHHxiD7iQt1Tzo9NB5OIx8BVY9AOuP17zofT0Mvb/uIEV+MrtT87hnfRT7M9SJUefQKF4PyKWb2y0nMEIIIVqn/CTQ6HAHdICjv+G85l3mbNKyIzXV42E/7ctize50pg+OJeBUrcQbmd3pZOXWlFrv25teRF5x+ZkFKsAzS1KjgfAeZ7YfIYQQbZYs/RA1+ceA2Vf9bLCw41ieql1xOkw+EJ7gua39+Wo9ah2S7V5MX5paGaQA2J9RxPRlqSSXe53e6wshhBAtQX4yrLgDvngQTVE6mtCuZCYfZMnWrFofPu/XI+QU25p4kDXptVqiAmrPpLQYdBhdJbXeJ4QQQjQEyag4F5SXqIKWAE47uJ2gP4s00ur7s5eq1qLVu4HYSiFzJ8y7Wt0OiIXcw6rlqcECcVdWPb+aYwUuMotqnpxlFtpIKnTRrrUUBHc61Bpcw/FjXP14CSGEOLeUF0LadijNhaIMyD2IZtA/0WkDan24XqdBq9F4bMssLMPlhiBvlWWRXVyOVqMhxOT0nF/KS8FYz2Wap6DRaLhuYAyLNh7D5VbbLAYdoxIiuKJ7MFavM8ymEKfH4xzuhPMLIYRowySjoq3LPgC/vQ15x8BeBkfXw4HvoTDzzPaXth22LYayAjV5pm5VSzuy96v7847CxvfUROp2Q+I0uOkbtQwE1Dbcte661O6s82VPdl+L4nRA0gbY/40K4pTmwZaPIH1Xc49MCCFEcwjpCjM+B6MPmqQNUJxFcMFOpg9S7TnNBi2h1qov/Xde1An/48s+0gvKmPvrYca+/QujX1/Hi6v3sOFwDuPf/oUVv+zA9ttsHGm71RPzk+Cnf6mOWw2kS6iV/93Qj0g/M72j/XlxQgKp+aX8bdlObl+8m98P51Ba3krm59Yo5yCsfxOKM2ueXwghRBsnGRVtWWEqLJwEWftUoKLL5fDxDBVEmLES7EUQ2KH++8tPgrljoCQH7CUQ2h2SNsL3z8DmeTB5ISy/HdK3qxZjt3wPXoHgEwI9J0KHYeAbWWd2QZS/Ba2Gyis3FbQaiApoJRkJBckw7xpVuXzcbHXcv3lCtVu75QepsyGEEOcKRznoj9eZ0Oo8llDq8g4z8YowdqQUcmdvPaG6YmZ+reOS+BCuCkyDnHIKvaJ4cfWfLN2UXPm8d386yHd/ZnDfpZ251PETpq8eg99ex3Xdx2i/eli1Py1Mgyufq7se1GkwGXRcFJjLJ8MySAm7iImzN+M4PkmvP5jDhHd/Zcltg+kfG3jWryVOUJgKi6ZCxi4oTIeuo2DhRHV+cdtaCO/Z3CMUQohGJRkVbYG9TAURHMeXTRRnqaUW3qEw+j+qm8emD2DRFDXB9b0B9qyCrx9TQYf68gpS+9NoYPUjsGCi6hISkagyKd4ZooIUAR2g+7WqmndFP3SzFYI7n3QJRLsAC4+N7F5j+2OjuhPp30rSHC0BcNkslTmy9EYVpNBo1XHzDm7u0QkhhKinYpudPWkFfLE9lR/3ZnI05zRqMhRlwsb3VX2KzD0wZzTYCnCH9QRLAJp9XxP57X28fVUgietuJ+rT8ay61szfe5agmzsKPpqAvuCYR5Ciwr6MIpxu2KrrgS16KBSlo/3vhSpIYY2AC05StPp0FabB4mn4Jv/E22sPVwYpKrjd8MKXf5Jfam+Y1xNVvENh1KtqyezG99RyWocNBt2p/p2FEKKNk0BFa2cvU2mA/+kNh36E4mz46UWYfblajtGuH5x/X9XjrREqs+LwOnXFxes0roIYLNDxYug+Vt12lsOWhTDuPc/HjZ8NQR1P+614GfVM6BfFZ3cP4b5Lu3DfpV347O4hTOgbhZexlST/mH0hYYLnlY6EydDhQhUwEkII0eIVlNqZ++tRrnh1LXd+9Acz/reBUa+vZXty3qmfbCuCDf+F1f+AZTep4L5/e4gdCqNeoXzKMhXUjh6AwWhCEzsU7KUY541C9+EIlbHYfggFjrrnvZS8Mv75XQ7Zw1/zvOPadyA47uzefHXWcJg4l+K4sexKq325wZ60QoptjoZ7TaFoddCuD1zwYNU27xAY8he58CGEOCdIoKK1s5eqqzVOOyycrLIcfnsHyvKhNAdStsDPr1Y9vjAV/lwJI/4F1sjTe63yEti/BnZ9om7rTZA4FT6e6fm4j29QtTHOgNVsICHKn/uHx3H/8DgSovyxmg1ntK8m46q2Prc0D7Ys8ixWum0hHPhO1pQKIUQrcSi7mBe++tNjW0Gpg7s+2kxGQdnJn2zygYSJ4NsOjv4Kb5+vMhl7TwXvEPYWmHDf+qOq4eQXBRc/ArEXqGWZLgfEDIJLHydPG8AJNTUrRfqbeebSQIJX3+V5xye3QuaftT/pTIV2w7vTQHq286317m4RvviYWsnFhNbE6VDLa3/6V9W24kz48V/qbyGEaOMkUNHaeQVA/xth2EPqC3Py72r7tBXg3wE+u/v4co8b4Zq3VHBh60J1xSZpg5oI66s0B754UOV6XvUSXLdULTmpWO5x53qI7KuWgWz6UF1VauucDlWgNG27ul2WDz7B6iT1hlVwxbPqeK366+ktsxFCCNFsfvgzo9btR3NKSC+sR+vQ4C4w+SP1s9MOn90DUf1x+cVgs9lw+UaBxQ9cLsg+CMmbqp6buhWy9xPlb2JSv+gau+4WYQWgp2MnxuT1YI3AdfsvKnOvKB1+eUMFzRuQl48v91zSBYPOM3Ki1cBDI+LxtbTwCwqtUXEmrHpQLfcYfJeqLWawwO+z1ZIcIYRo4yQE3hY4HVCS7bmtvFAFMaYsgt2fqroVe9fA1KVq7ewPz0PMYFWNvL7LP/yiYPrnkPIHdBsDOoMKfFz2FHQbDUGdYOIcFQjpM8OzZWlb5HTAsfUwfywYvFRVd7OfOklM2wZXvgA9xoPRG6IHSiFNIYRoJfS6uq/jaOvIcvCQewSW36HmSefx+g2f3oVm3Gw01dMkClNUAWZ7icq40Ohg81yYdw3ed2/ggeFx9I725721B7E5XIzrE8XgjkH845Pt5CV044bLX0TXaRj6sHi45h1V2LrPjIarUVFNXJiV5XcO4bVv9rI1KZ+u4VbuHx5H94jaMy3EWfKNUMGu3Z9D7+vUcqFpn6o2tw25vEcIIVooCVS0dsXZ8PNrqmiX3gydLoE9X6hlINcvV1dY+t+srtD4x6hU1OJsVdwyss/p1agACOuuOoUYjvdpj+wF4QlVfdv9o2HIvZ5LH9oql10FgJzl6orHh6PUyWHuYXV/3hFVSDNhsvQ8F0KIVuSi+BBeXL2nxva4MB/CfU/x+9xWpIofOm0wbTlYAuGjCeAThsZWQHigteqxXkFwzdtqeeDFjwAadQEgdghYggg1mpk8IIbh3cNwut0Ee5twA4tvG4ROq8Fk6l41v/i1g6F/abT516DX0qOdH69NTqTQ5sDbpJclH40tsAMMuLXq3ziqn1oeJDWvhBDnAFn60dqZfSHucjD5qhOia96BS/6pCnf5R6siXiarKuLlH6OKM1lDVUHNMy3GVBGkAHVCZLR43n8uBClAHYcuV8D4D9RxLsurClIMuhMu+KtqzSpBCiGEaFVig7x5YVyCx1KHdv4W3pjShyCfU3xJNPnAoHtULagFk2HzfJj5JcQMRvPOUIILd1V16TJYoMtwuORR1SXLJwSGPazmlmpdsoJ8TIRazWi1GnRaDaG+ZjWOE+eXJph/vUx6wnzNEqRoKtX/jbU6CVIIIc4ZMsu0djqDWsJx53pVnVurg/43QcIkFagQjctogaj+KiWzeg2KXpOlKrcQQrRS3iY91yRG0j82gJT8MswGLe38LUT4WU79ZFC1inK8VObd+rdUd668o+rCQXkxuKsVYTZYPC8A+MjcIYQQQkhGRVugM6iUT61O3bYEeAYpHDZI2VxVfKkkG5I3nxvFLhtb3lFYdF3NQplzr64qsCmEEKLVMel1dAzxYWjnYPq1D6x/kALUfBwzCK4/3iUr/xhc/Qbu65aQ4peoMh+SNkHWfnV/eYmal6WbgxBCCAFIoKLtc9jh0Fp4/1JY/aiqCP7z6/DeRbD7M3VlR5yZ8hJVGyR1q7o98A649l21DKQ0Fz69CwrTm3eMQgghmoe9pKpV95jX4acX0SycTJSpFG3yRpgzCpbfBln7YM+X8P7F8MMLquC1EEIIcY6TpR9tnd6gliAYvGHHUjjwrfoSrTOCX7T6W5wZo5cKTmTtU+1ZL3hAHWe9Cb55UtWusIY19yiFEEI0NacD9q2Bz+9Vt40+qph15h70c0eqpR8Om6odtftz+G6WamUddt65U+dJCCGEOAkJVJwLInvD9M9UFkVprto2+SOVlqqT3udnxTcCRr6sAj4VNSm6XAlRA6QdqRBCnKt0ejX3BnaEix5RHbgCOsKymZC+Uz2mw0VqHv7y7+r2Rf+AnhPafmtvIY4rKXeQmldGemEZ3kY97QIsBJ+qWK0Q4pwhgYpzQUk27PrUc9vWxaqtqDW8ecbUlvhGet42WsAoQQohhDinBXaEGStV22q9BcoLIOdQ1f1pW6HfDWoOKUiBXZ9BrykSqBDnhLySchZsOMrLX+/F6XID0CvKj9en9CEmyOsUzxZCnAukRkVb5yyHHcvh53+rq/6XP61ame5YCr/8RwpqCiGEEI3Frx0YvaEgWRVZtpfgPG887i7DVYbjqgdg8iII6gwZO2HZzVLbSJwT/kwr5F9f7akMUgBsTcrnX6v/pKTc0YwjE0K0FJJR0dbpjBB3BWxfApf8U7Uyjb1AFXrsd5NcuRFCCCEam9kPhs/CnbqV7IQ7CPG1AH+D7teqelFTl8KSGXDlc+AdcsYvk5ZfxpHsYtIKymgf6EV0oBdBkkovWhiXy81Hvx2t9b4vtqfy4OXxxAbLVxQhznXyW+Bc4B8NE+eBV2DVutnrl8myDyGEEKIpmH2h50Tc8aM4ti+ZoOh4dCNeUhmO3oHqz9Ql4B0K2jNLdj2aU8JNH25kX0ZVpuTF8SE8NzaBcD8p0ClaDjdQWkfWhMsNLre71vuEEOcWWfpxrrCGeRbOlCCFEEII0XTMvrirZ0sExqoARQVr+BkHKcodTt754YBHkALg+z2Z/Lg344z2KURj0Wk1XDcgptb7hnQOItgqWUBCCAlUCCGEEEK0allF5Sz7I6nW++avP0p+qb2JR4Rqt3qy2+Kc1jPKj3F9ojy2hVpNPDXmPHzN0pFOCCFLP4QQQgjRxhSVOUjNLyWzyIav2UCkv4VAb2NzD6tRlDucFJY5eGrMeei0GrKLy3n3xwPklqjghF6rQatp4kG5nJC0ESwBEBIPpflweC2061OzU5Y4J4VYzTw2shs3nN+evemFhFjNdAzxJipAOn4IIRQJVAghhBCiyWUWlrEjpYAdSfn0iw2ga7gvAQ0QTMgusvHuTwd5b+3Byov453cM4sUJCbQ72Zeg/CSwl0BwHOQdAacDgjqd9XgaU0m5g693pfPQ0m3YHC4AogIsPH1NT/6xfBsFpQ5uHNoBa1NfoU7brrqcmP3ghlWwdzV8/Sh0uQLG/EeWnwoAAryNBHgb6Rnl39xDEUK0QBKoEEIIIUSTKiyz88qavSzccKxy298uj+eWYR0w6nRnte9NR3L5708HPbb9cjCb99Ye4pGRXWvff0kurH4Ujv6i2oV+fh+4ymH6Zy36S/WR7BLuX7zFY1VFUm4pr327l2mDYskvLWdQx8C6d9BYvIMhqr/Konijn9qm0ULfGWD2b/rxCCGEaHWkRoUQQgghmlR6QRmLNh7z2Paf7/aRlm87q/2WlDv44JfDtd63cMNRMgvq2L9XAFzyKKCB9y+BnP1w9VvgE3ZW42lsa/dl1lr6YW96EZd0DeGhK7sSYm2Gjh9+UTDuPc+gxGVPQqfLwCAdSIQQQpyaBCqEEEII0aScLneNL9gOlxv3WRZcdLuh/PgSiBM5anlNDzoTGL3Vz1oDmHxA09TFHU6PrY73CmDUaZt+yUeF0nzYvgzK8qq2/fom5B1unvEIIYRodSRQIYQQQogmFeZr5qL4EI9tk/tHE+p7dlfbvU16rh9Ye9vD0QkRBNXV9rBi6UdROkyYq4IUi6dBYdpZjaexXRgXUuv2qADLWR/Ls5KzX9Wk0Gjhmncg9gJ1bJfeCIXpzTcuIYQQrYbUqBBCCCFEk/L3MvLstT35fk8GP+7JZETPcM7vFIzFcHb1KQAGdwrmsm6hfLM7o3Jb+yAv/jI8ru79ewXA5bOg9AGITISwbmAva9H1KQA6BHnx4OVxvPT13sptPiY9b0xJJKw5AxWBHeHSJ1THj06XQocLYPVjcNFDYG3Zy2mEEEK0DBKoEEIIIUSTi/S3MHVge6YObN+g+w33M/PCuASO5pRwKKuYMF/V9jDCz3LyJwZ2rPo5OK5Bx9RYfC1GZpwfy2XdwvgzrRCrWU+nUB/aBzZzi0dLAPSdCQaLqknhFwWjXgGvZijsKYQQolWSQIUQQggh2pQgHxNBPiYSYwKaeyiNzmo20DXCQNcI3+YeiievE469BCmEEEKcBqlRIYQQQgghhBBCiBZDAhVCCCGEEEIIIYRoMSRQIYQQQgghhBBCiBZDAhVCCCGEEEIIIYRoMSRQIYQQQgghhBBCiBZDAhVCCCGEEEIIIYRoMSRQIYQQQgghhBBCiBZDAhVCCCGEEEIIIYRoMSRQIYQQQgghhBBCiBZDAhVCCCGEEEIIIYRoMSRQIYQQQgghhBBCiBZDAhVCCCGEEEIIIYRoMSRQIYQQQgghhBBCiBZD39wDaGxutxsAp9PZzCNpnSqOmxy/hifHtnHIcW08cmwbR3MdV61Wi0ajOa3nyJx6duT/UOORY9s45Lg2Hjm2jaM1zani5DTuirOONqq8vJzt27c39zCEEEKIFqV3797odLrTeo7MqUIIIURNZzKnipNr84EKl8uFw+GQKJcQQghRzZnMizKnCiGEEDXJvNjw2nygQgghhBBCCCGEEK2HFNMUQgghhBBCCCFEiyGBCiGEEEIIIYQQQrQYEqgQQgghhBBCCCFEiyGBCiGEEEIIIYQQQrQYEqgQQgghhBBCCCFEiyGBCiGEEEIIIYQQQrQYEqgQQgghhBBCCCFEiyGBCgHAxo0buf322xk6dCjx8fF88803Hve73W5ee+01hg4dSkJCAjfccAOHDx9unsG2Iu+++y7jxo0jMTGRwYMHc+edd3Lw4EGPx9hsNp566ikGDhxIYmIi99xzD1lZWc004tZjwYIFjB49mj59+tCnTx8mTZrEjz/+WHm/HNeG8d///pf4+HieeeaZym1ybE/f66+/Tnx8vMefK6+8svJ+OaZti8ypjUPm1MYjc2rTkDm1Ycicem6QQIUAoKSkhPj4eJ544ola73/vvfeYN28eTz75JEuWLMFisXDTTTdhs9maeKSty4YNG5g6dSpLlizhgw8+wOFwcNNNN1FSUlL5mGeffZbvv/+eV199lXnz5pGRkcHdd9/djKNuHcLDw3nwwQf55JNPWLZsGYMGDeKuu+5i3759gBzXhrBt2zYWLVpEfHy8x3Y5tmemS5curFu3rvLPggULKu+TY9q2yJzaOGRObTwypzY+mVMblsyp5wC3ECeIi4tzr1mzpvK2y+VyDxkyxP3+++9XbisoKHD36NHDvXLlyuYYYquVnZ3tjouLc2/YsMHtdqvjeN5557m//PLLysfs37/fHRcX5968eXMzjbL16t+/v3vJkiVyXBtAUVGR+/LLL3f//PPP7uuvv9799NNPu91u+cyeqf/85z/uMWPG1HqfHNO2TebUxiNzauOSObXhyJzasGROPTdIRoU4paSkJDIzMzn//PMrt1mtVnr16sXmzZubcWStT2FhIQB+fn4A7NixA7vd7nFsO3XqRGRkJFu2bGmOIbZKTqeTVatWUVJSQmJiohzXBjBr1iyGDRvmcQxBPrNn48iRIwwdOpRLL72Uv/71r6SkpAByTM81Mqc2HJlTG4fMqQ1P5tSGJ3Nq26dv7gGIli8zMxOAoKAgj+1BQUGy3us0uFwunn32Wfr06UNcXBwAWVlZGAwGfH19PR4bFBRUedxF3fbs2cPkyZOx2Wx4eXnx5ptv0rlzZ3bv3i3H9SysWrWKXbt2sXTp0hr3yWf2zCQkJPDcc8/RoUMHMjMzefPNN5k6dSqff/65HNNzjMypDUPm1IYnc2rjkDm14cmcem6QQIUQTeSpp55i3759HmvoxNnp0KEDK1asoLCwkNWrV/PQQw8xf/785h5Wq5aamsozzzzD//73P0wmU3MPp80YNmxY5c9du3alV69eXHzxxXz55ZeYzeZmHJkQrZPMqQ1P5tSGJ3Nq45A59dwgSz/EKYWEhACQnZ3tsT07O5vg4ODmGFKrM2vWLH744QfmzJlDeHh45fbg4GDsdjsFBQUej8/Ozq487qJuRqOR9u3b06NHD/7617/StWtX5s6dK8f1LOzcuZPs7GzGjh1L9+7d6d69Oxs2bGDevHl0795djm0D8fX1JTY2lqNHj8oxPcfInHr2ZE5tHDKnNjyZU5uGzKltkwQqxClFRUUREhLCr7/+WrmtqKiIrVu3kpiY2Iwja/ncbjezZs1izZo1zJkzh+joaI/7e/TogcFg8Di2Bw8eJCUlhd69ezfxaFs/l8tFeXm5HNezMGjQID7//HNWrFhR+adHjx6MHj268mc5tmevuLiYY8eOERISIsf0HCNz6pmTObVpyZx69mRObRoyp7ZNsvRDAOo/+NGjRytvJyUlsXv3bvz8/IiMjGT69Om8/fbbtG/fnqioKF577TVCQ0O57LLLmnHULd9TTz3FypUreeutt/D29q5cG2e1WjGbzVitVsaNG8fzzz+Pn58fPj4+PP300yQmJsov01N4+eWXufDCC4mIiKC4uJiVK1eyYcMGZs+eLcf1LPj4+FSu967g5eWFv79/5XY5tqfvhRde4OKLLyYyMpKMjAxef/11tFoto0aNks9rGyRzauOQObXxyJzaOGRObRwyp54bJFAhAFUhd/r06ZW3n3vuOQCuvfZann/+eW655RZKS0t5/PHHKSgooG/fvrz//vuy3u4UFi5cCMC0adM8tj/33HOMHTsWgEceeQStVsu9995LeXk5Q4cO5YknnmjysbY22dnZPPTQQ2RkZGC1WomPj2f27NkMGTIEkOPamOTYnr60tDQeeOAB8vLyCAwMpG/fvixZsoTAwEBAjmlbI3Nq45A5tfHInNp85NiePplTzw0at9vtbu5BCCGEEEIIIYQQQoDUqBBCCCGEEEIIIUQLIoEKIYQQQgghhBBCtBgSqBBCCCGEEEIIIUSLIYEKIYQQQgghhBBCtBgSqBBCCCGEEEIIIUSLIYEKIYQQQgghhBBCtBgSqBBCCCGEEEIIIUSLIYEKIYQQQgghhBBCtBgSqBBCNLqHH36YO++8s16PnTZtGs8888xJH3PJJZfw4YcfVt6Oj4/nm2++ASApKYn4+Hh27959xuMVQgghWiqZU4UQ5wIJVAhxjqrPyUtDPKcxLF26lEmTJjX3MIQQQghA5lQhhGho+uYegBBCnK7AwMDmHoIQQgjRJsicKoRoiSSjQohz0MMPP8yGDRuYO3cu8fHxxMfHk5SUxIYNGxg/fjw9evRg6NChvPTSSzgcjpM+x+l08sgjj3DJJZeQkJDAFVdcwZw5c85qfE6nk1mzZtG3b18GDhzIq6++itvtrrz/xDRVIYQQornInCqEEA1PMiqEOAc9+uijHD58mC5dunDvvfcC4HK5uPXWW7n22mt54YUXOHToEI899hgmk4l77rmn1ucEBgbicrkIDw/ntddew9/fn82bN/P4448TEhLCVVdddUbjW758OePHj+fjjz9mx44dPP7440RGRjJx4sQGOwZCCCFEQ5A5VQghGp4EKoQ4B1mtVgwGA2azmZCQEAD+/e9/Ex4ezuOPP45Go6FTp06kp6fz0ksvcdddd9X6HACdTld5kgUQHR3Nli1b+Oqrr874pCoiIoJHHnkEjUZDx44d2bt3Lx9++KGcVAkhhGhxZE4VQoiGJ4EKIQQABw4cIDExEY1GU7mtb9++lJSUkJaWRmRkZJ3P/eijj1i2bBkpKSnYbDbsdjtdu3Y947H06tXLYxy9e/fmgw8+wOl0otPpzni/QgghRFOQOVUIIc6OBCqEEGdl1apVvPDCCzz00EMkJibi7e3N7Nmz2bp1a3MPTQghhGhVZE4VQghFAhVCnKMMBgMul6vydqdOnVi9ejVut7vyysumTZvw9vYmPDy81ucA/PHHHyQmJjJ16tTKbUePHj2rsW3bts3j9tatW2nfvr1c+RFCCNEiyZwqhBANS7p+CHGOateuHVu3biUpKYmcnByuu+460tLS+L//+z8OHDjAN998w+uvv87MmTPRarW1PsflctG+fXt27NjB2rVrOXToEK+++irbt28/q7GlpKTw3HPPcfDgQVauXMn8+fOZPn16Q7xtIYQQosHJnCqEEA1LAhVCnKNuvPFGdDodI0eOZPDgwdjtdv773/+ybds2rr76ap588knGjx/PHXfcUedzUlJSmDx5Mpdffjn3338/EydOJC8vj+uuu+6sxnbNNddQVlbGhAkTmDVrFtOnT2fSpEln+5aFEEKIRiFzqhBCNCyNu3ojZSGEEEIIIYQQQohmJBkVQgghhBBCCCGEaDGkmKYQosmkpKQwcuTIOu9ftWrVSVu2CSGEEEKROVUI0ZbJ0g8hRJNxOBwkJyfXeX+7du3Q6yV+KoQQQpyKzKlCiLZMAhVCCCGEEEIIIYRoMaRGhRBCCCGEEEIIIVoMCVQIIYQQQgghhBCixZBAhRBCCCGEEEIIIVoMCVQIIYQQQgghhBCixZBAhRBCCCGEEEIIIVoMCVQIIYQQQgghhBCixZBAhRBCCCGEEEIIIVoMCVQIIYQQQgghhBCixfh/va5Df4YjnnIAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1073.22x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Script for creating a Seaborn relational plot with the \"tips\" dataset.\n",
    "\"\"\"\n",
    "\n",
    "import seaborn as sns\n",
    "\n",
    "# Set the Seaborn style to \"whitegrid\" for your plots\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "# Load the \"tips\" dataset provided by Seaborn\n",
    "tips = sns.load_dataset(\"tips\")\n",
    "\n",
    "# Create a relational plot (scatter plot) using Seaborn's relplot function\n",
    "sns.relplot(\n",
    "    data=tips,          # The dataset to use\n",
    "    x=\"total_bill\",     # The x-axis data\n",
    "    y=\"tip\",            # The y-axis data\n",
    "    col=\"time\",         # Separate plots into columns based on the \"time\" column\n",
    "    hue=\"smoker\",       # Color the points based on the \"smoker\" column\n",
    "    style=\"smoker\",     # Differentiate the points with different markers based on \"smoker\"\n",
    "    size=\"size\"         # Vary the point sizes based on the \"size\" column\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d10bea7a-694e-406f-b925-a6755f87e360",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}