diff --git a/lab3/lab3.ipynb b/lab3/lab3.ipynb
index 42a4922..c2134e2 100644
--- a/lab3/lab3.ipynb
+++ b/lab3/lab3.ipynb
@@ -46,7 +46,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -99,7 +99,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -135,12 +135,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -150,7 +150,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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OJCoqqsh+L/zDGB0dTb169fj66685ceIEnTt3tsZlYc/xeDFLliyhZs2a5OTk8O2337Jo0SJ69OhR7GRri+7du9O4cWNmz55tM58kJCSE5OTkIutb2grHfscdd3DHHXdYv3/vvfd477337IrZ4vTp09bhMYBTp04B5vckJCSE06dPF3nfLH8kL8yjPT744APAXLx/9dVXTJo0iaCgIGsxUfifJzDPHbLM6atatSomk6nE481yPFqcPXuWWbNmMXbsWIdifeaZZ2jevDl5eXn89ttvvPDCC6xYsYL777/fuo7lPc/OzuaHH36wFlZNmza1eS17jn1LQZucnGzzT0tubi6nT5+2if1Sn2UWzz//PMuXL2f8+PG8+uqreHt7O/z5JMXTsJc47YcffiA6OpqBAwda/9CcOHGC/fv3W7u5LcXNV199ZbPtzJkzef755x3aX0JCgvVMGsu+fvrpJ+s8iw4dOnDo0CEaNGhAy5YtrV8fffQRH3zwAd7e3vz444+cO3eOjh07lrifhg0bEhYWxtGjR21eJyIiglmzZll7Qiw/44X/URdmT0wWV155pc06F/4RAPO8lvfff58nn3yy2KKrQ4cOxMfH07RpU+vrtGjRgpUrV/Kf//yn2BgbNGhAzZo1+eSTT2zajxw5ws8//0xMTAxgnkuSm5vLZ599ZrPe+vXrqVq1Km3btrVptxTQlrNexo8fz9mzZ/nll19o3bo1vr6+nDhxwuZn9vHxYfbs2cWehWMZ+tq0aRM33nhjkeX2HI8X06hRI1q2bMk111zD2LFjqV69Otu2bbvoNjVq1GDChAnExsYyadIk63/37du356effuLYsWM262/cuJGaNWtSv359a1t4eLhNDoqb8Hopmzdvtvn+888/58orr6RevXp06NCBvLw8Pv/88yKxwPnf0YKCgosey4VZYu3QoQNTpkyhWrVqNsM6lvfe8lV43lRQUBAtWrTgs88+sxlyOnPmDP/973+L/EO0ZMkSwsLCrBO/7WX5nWvbti1DhgyhSZMmRd5Py3verl07RowYUeSMNAt7jn1LIXLhSQiffvop+fn5Nj/XpT7LLDp16sT8+fPZvn07r7/+OmD/55NcnHp+xGmtWrVi8eLFLF++nDZt2vDnn3+ybNkycnJyrMM5TZo04frrr+eVV14hKyuLpk2bsnXrVr7++msWLlzo0P4sZ62MGzcOb29vFi5cSEhIiPW02vvuu4+PPvqI++67j/vvv5/Q0FA2bdrEe++9x2OPPcbhw4dZsmSJNdY///zT+to5OTmkpKRw+PBh6tWrx7hx43jqqafw9vamZ8+epKens3jxYk6cOEHz5s2tY/wmk+mik3svFZOj9uzZw8CBA0u8yJvl7KARI0Zw11134e/vz9q1a9m8eXOJk6u9vLwYP348jz32GBMmTOCWW27h9OnT1vxaepG6du1K9+7defLJJzlx4gSNGzfmP//5D5s2bWLatGlFrr+SkZHBzz//TH5+PqdOnWLt2rUEBATQrFkzQkNDGT58OPPmzSMjI4OOHTty4sQJ5s2bh8lkKnZeR69evXjzzTfx9vYuMkQF9h2PFxMXF8fJkyfJzs5m165dpKamEh0dfcntwDxkecMNNzB37lyefPJJhg4dysaNG7nvvvsYPXo01atXZ8OGDWzbto0ZM2bYNdnZEStWrMDf3582bdrw5Zdf8vXXX1snr3fr1o2OHTsydepUTpw4QZMmTdixYwevvvoq/fv3p169evz000/s3r37onPhCvv5558xDIP09HS+/vpr0tPTad++vd3xTpgwgWHDhvHggw9y9913k5uby/Lly8nJySkyj+2XX37h7bfftrsws4iPj8ff35/c3Fx+//139u/fX2TYy/KeZ2RksHPnTvbv31/smXj2HPvR0dH079+f+fPnk5mZSfv27YmLi2PhwoV07NiRrl27Wl/vUp9lhTVp0oR77rmHxYsX069fP2rXrn3Jzye5NBU/4jTLKdGrVq1i0aJF1KpVi1tvvRWTycSyZctIT0+nWrVqvPLKKyxcuJA333yT06dPc9VVVzF//nx69+7t0P5q167N/fffz4wZM8jMzOTaa69lyZIl1h6SiIgI1qxZw6xZs3j66afJzs4mKiqK559/nttuu40pU6bwf//3fwD861//KvL633zzDTVq1ODFF1/k9ttvp0qVKrz22musXbuWoKAgYmJimDlzJnXr1uWGG27Ax8eHBx988KLFz6ViclTVqlWZMGFCicubNGnC6tWrmTNnDpMmTcIwDBo1asSiRYvo1atXidsNGDCAKlWqsGzZMkaNGkVwcDBdu3Zl/PjxNnMY5s6dy5w5c1i1ahUpKSnUrl2b6dOn2wzbWOzdu9ea56pVq9K4cWOWLVtmHRJ45JFHqFmzJu+88w6vvfYaISEhdO7cmfHjxxf7RzgmJobq1avTtm3bYnNu7/FYEsslCry9valZsyb333+/3b0NERERPPzww7z00ksMHDjQehX0WbNm8dxzz5Gbm0uTJk1YvHjxRd8HZz3++ON8+OGHLFu2jIYNGzJ//nzrcJ3l558/fz4rV64kJSWFOnXqMH78eIYOHUpycjJ33XUXwcHBjBs3zq79Wd7XgIAA6tatyzPPPHPR4cELde7cmRUrVjB//nzGjx+Pn58f7dq146WXXrI58wzME4YdKawsLKfom0wmrrjiCm655ZYihZXlPffz86N27dqMGTOG++67r8jEY7Dv2H/++eepX78+69at49VXXyU8PJx77rmHhx56yKbgvdRn2YVGjx7NZ599xowZM1i4cOElP5/k0nR7C7ksTJkyhR07dhQZPnP0NQBefPFFp5aLuJvt27dzzz33sGrVqosO5Yr7KIvPMik9zfkRERERj6JhL/EYl+oOVnexiIhn0LCXiIiIeBQNe4mIiIhHUfEjIiIiHkXFj4iIiHgUTXi+wE8//YRhGPj6+ro6FBEREbFTbm4uJpOpyNXmi6OenwsYhnHRu2k783o5OTll+pqVnXLmOOXMMcqX45QzxylnjitNzhz5+62enwtYenwudVNPe507d464uDiio6MJCgoqk9es7JQzxylnjlG+HKecOU45c1xpcvbrr7/ava56fkRERMSjqPgRERERj6LiR0RERDyKih8RERHxKCp+RERExKOo+BERERGPouJHREREPIqKHxEREfEoKn5ERETEo6j4EREREY+i4kdEREQ8ioofERER8SgqfkRERMSjqPgRERERj6LiR0RERDyKj6sDEGDFCkhLg5AQGDrU1dGIiIhUaip+3EFaGqSmujoKERERj6BhLxEREfEoKn5ERETEo7hV8bNs2TKGDBli05aUlMT48eNp164dHTt2ZMKECaSkpNiss3r1anr16kWrVq24++672bt3b0WGLSIiIpcRtyl+Vq9ezdy5c23acnJyuP/++/nrr79YtWoVy5cvZ9++fUyePNm6zocffsjLL7/Mww8/zPr166lTpw5Dhw4tUiCJiIiIgBsUPydOnGDkyJHMnDmTqKgom2WffPIJx44dY+HChTRr1ozWrVszZcoUDh06REZGBgBLly5l8ODB3HLLLURHRzNjxgwCAwN5//33XfDTiIiIiLtzefGzZ88efH192bhxI61bt7ZZ9n//93906tSJK664wtrWtWtXNm/eTHBwMKdOnSIhIYHOnTtbl/v4+NCuXTt27txZYT+DiIiIXD5cfqp7bGwssbGxxS47dOgQ7dq1Y9GiRWzYsIG8vDy6dOnCo48+SrVq1UhMTASgVq1aNtuFh4ezb98+p2MyDINz5845vX1hmZmZNo8XMplM+OTlQW4u5OWRl5mJYRhlsu/L1aVyJkUpZ45RvhynnDlOOXNcaXJmGAYmk8mudV1e/FxMRkYGGzZsoHPnzsyaNYu0tDReeOEFHnroId566y1rcvz8/Gy28/f3Jzs72+n95ubmEhcXV6rYL5SQkFBsu5+fH+GnTpF/6hTeBQUkxceTk5NTpvu+XJWUMymZcuYY5ctxypnjlDPHOZuzC+uBkrh18ePj40NQUBCzZs3C19cXgJCQEG6//XZ+/fVXAgICAIoUC9nZ2QQGBjq9X19fX6Kjo50PvJDMzEwSEhKIiooqNiaTyYRPWBh4eUFoKNWio9Xzc4mcSVHKmWOUL8cpZ45TzhxXmpzFx8fbva5bFz+RkZEYhmEtfACuvvpqAI4ePUrHjh0B8+nwV111lXWdpKQkIiIinN6vyWQiKCjI6e2LExgYWPJr+viAry/4+OCrXxCri+ZMiqWcOUb5cpxy5jjlzHHO5MzeIS9wgwnPF9O+fXv27dtHVlaWtW3//v0A1K9fn7CwMBo0aMD27duty/Py8ti1axft27ev8HhFRETE/bl18XPnnXfi7e3NhAkT+OOPP/jhhx+YOnUqHTt2pHnz5gDcf//9rFixgg8//JD4+Hgef/xxsrKyuO2221wcvYiIiLgjtx72qlGjBqtXr+aFF17g9ttvx8/Pj969ezNlyhTrOnfccQdnzpxh7ty5pKam0qJFC1asWEGNGjVcGLmIiIi4K7cqfl588cUibVFRUSxbtuyi2w0bNoxhw4aVV1giIiJSibj1sJfHcWCyloiIiDhHxY87qVoVVqwwf4mIiEi5cKthLwHS0lwdgYiISKWmnh8RERHxKCp+RERExKOo+BERERGPouJHREREPIqKHxEREfEoKn5ERETEo6j4EREREY+i4kdEREQ8ioofERER8SgqfkRERMSjqPgRERERj6LiR0RERDyKih8RERHxKCp+RERExKOo+BERERGPouJHREREPIqKHxEREfEoKn5ERETEo6j4EREREY+i4scdmUyujkBERKTS8nF1AFKMqlVhxQpIS4OQEBg61NURiYiIVBoqftxVWhqkpro6ChERkUpHw14iIiLiUVT8iIiIiEdR8SMiIiIeRcWPiIiIeBQVPyIiIuJRVPyIiIiIR3Gr4mfZsmUMGTKkxOVTp04lNjbWpq2goID58+fTtWtX2rRpwwMPPMCRI0fKO1QRERG5TLlN8bN69Wrmzp1b4vLNmzfz/vvvF2lfvHgx77zzDtOnT2fNmjUUFBQwfPhwcnJyyjFaERERuVy5vPg5ceIEI0eOZObMmURFRRW7TlJSEk8++SQdOnSwac/JyeGNN95g7Nix9OjRgyZNmjBnzhwSExP58ssvKyB6ERERudy4vPjZs2cPvr6+bNy4kdatWxdZbhgGU6ZM4dZbby1S/Ozbt4+zZ8/SuXNna1u1atVo1qwZO3fuLPfYRURE5PLj8ttbxMbGFpnHU9jKlStJTk5m6dKlLFu2zGZZYmIiALVq1bJpDw8Pty5zhmEYnDt3zuntC8vMzLR5vJDJZMInLw9ycyE/H/Lyzj/m5kJeHnmZmRiGUSbxXA4ulTMpSjlzjPLlOOXMccqZ40qTM8MwMNl5Y3CXFz8Xs2/fPhYuXMjq1avx8/MrstySnAuX+fv7k5aW5vR+c3NziYuLc3r74iQkJBTb7ufnR/ipU+SfOoVvSAikp0NBAaSnk5ucjHdBAUnx8R45h6mknEnJlDPHKF+OU84cp5w5ztmcFVcrFMdti5/s7GwmTpzIv//9b5o0aVLsOgEBAYB57o/luWXbwMBAp/ft6+tLdHS009sXlpmZSUJCAlFRUcXGZDKZ8AkLAy8vCA01P4aEmB8NA0JDqRYd7XE9PxfLmRSlnDlG+XKccuY45cxxpclZfHy83eu6bfGze/du/vjjDxYuXMiiRYsAc49MXl4ebdu25dVXX7UOdyUlJVGvXj3rtklJSTRu3NjpfZtMJoKCgkr3A1wgMDCw5Nf08QFfX/D2Nj+3PPr6go8Pvh76S3PRnEmxlDPHKF+OU84cp5w5zpmc2TvkBW5c/LRq1arIGVtvvfUWX375JW+99RYRERF4eXkRHBzM9u3brcVPeno6e/fuZfDgwa4IW0RERNyc2xY/AQEB1K9f36YtJCQEHx8fm/bBgwczc+ZMatSowZVXXskrr7xCZGQkffv2reiQRURE5DLgtsWPvcaOHUteXh5Tp04lKyuL9u3b8/rrr+Pr6+vq0ERERMQNuVXx8+KLL150+ZgxYxgzZoxNm7e3N48++iiPPvpoeYYmIiIilYTLL3IoIiIiUpFU/IiIiIhHUfEjIiIiHkXFj4iIiHgUFT8iIiLiUVT8iIiIiEdR8SMiIiIeRcWPiIiIeBQVPyIiIuJRVPyIiIiIR1HxIyIiIh5FxY+IiIh4FBU/7urcOUhMdHUUIiIilY6KH3f1xhuwbBkcPuzqSERERCoVFT/u6NgxOHDA/PzgQdfGIiIiUsmo+HFH3313/vlff7kuDhERkUpIxY+7yc+H778//72KHxERkTKl4sfd7NsHaWng62v+PjER8vJcG5OIiEglouLH3ezcaX7s1An8/Mw9Qfv3uzYmERGRSkTFjzvJzYXffjM/79gRwsPNz3/5xXUxiYiIVDIqftxJWpq5p8fHB2rXhogIc7uKHxERkTKj4sednD1rfgwOBpPpfPHz66+ui0lERKSSUfHjTjIyzI/BweZH9fyIiIiUORU/7sRS/FSpYn60zPk5fBhSU10SkoiISGWj4sedXNjzExAAoaHm5xr6EhERKRMqftzJhcUPmCc+g4a+REREyoiKH3dSeMKzRWSk+XHfvoqPR0REpBJS8eNOLpzzA1C9uvlRt7kQEREpEyp+3ElxPT/Vqpkfjx+v+HhEREQqIRU/7uTMGfOjih8REZFyo+LHnVh6fgoPe1mKn7/+AsOo+JhEREQqGbcqfpYtW8aQIUNs2r766isGDhxI27ZtiY2N5aWXXiIrK8u6PDs7m2eeeYbOnTvTtm1bJkyYQEpKSkWHXjaKO9vryivNjzk5cPp0xcckIiJSybhN8bN69Wrmzp1r07Zr1y5Gjx5Nnz59+PDDD5k2bRqbNm3imWeesa7z9NNP83//938sWLCAN998k4MHDzJ27NgKjr4M5OeDpagrXPz4+kJQkPm5hr5ERERKzeXFz4kTJxg5ciQzZ84kKirKZtmaNWvo2LEjI0eOJCoqiu7duzNu3Dg+/vhjcnJyOHHiBBs2bGDq1Km0a9eOVq1aMXv2bHbu3MlPP/3kmh/IWZmZ5keT6XyxY6F5PyIiImXG5cXPnj178PX1ZePGjbRu3dpm2f3338/kyZNt2ry8vMjNzSUjI4MffvgBgE6dOlmXN2jQgIiICHbu3Fn+wZelc+fMj0FB4HXB21J43o+IiIiUio+rA4iNjSU2NrbYZc2aNbP5Pjc3l5UrV9KiRQtq1KjBiRMnCA0Nxd/f32a98PBwEhMTnY7JMAzOWYqRUsr8u0fH8nghk8mET14epvR0fAAjKIi8/HzIy4PcXMjPx7tqVbyA3MOHyS2juNzZpXImRSlnjlG+HKecOU45c1xpcmYYBiaTya51XV782CsvL49Jkybxxx9/sHr1asCcHD8/vyLr+vv7k52d7fS+cnNziYuLc3r74iQkJBTb7ufnR/ipU/ieOEENIM/Pj9TTpyE9ndzkZHxDQqji50cQkLZvH3+WcVzurKScScmUM8coX45TzhynnDnO2ZwVVxMU57IofjIyMnjkkUfYsWMHCxcupFWrVgAEBASQk5NTZP3s7GwCAwOd3p+vry/R0dFOb19YZmYmCQkJREVFFRuTyWTCJywMk68vAN4hIVQPDTUPfRkGhIbiVbMmANUzMwlq2rRM4nJnl8qZFKWcOUb5cpxy5jjlzHGlyVl8fLzd67p98ZOUlMQDDzzAsWPHeP3112nfvr11WWRkJKmpqeTk5NhUe0lJSURERDi9T5PJRNCFk45LKTAwsOTX9PExn8oOeAUH4+XtbW7z9QVvb+ud3X2SkvAp47jc2UVzJsVSzhyjfDlOOXOccuY4Z3Jm75AXuMGE54tJS0vj3nvvJSUlhdWrV9sUPgDXXHMNBQUF1onPAIcOHeLEiRNF1nV7hSc8X0hne4mIiJQZt+75eeGFFzhy5AivvfYaNWrUIDk52bqsRo0aREREcNNNNzF16lRmzJhBYGAg06ZNo0OHDrRp08Z1gTvDMrmr8NWdLS68yrMD1a2IiIjYctviJz8/n02bNpGbm8u9995bZPmWLVuoU6cO06dPZ8aMGYwePRqAbt26MXXq1IoOt/Ts6fnJzIT0dAgJqbi4REREKhm3Kn5efPFF63Nvb29++eWXS24TFBTEc889x3PPPVeeoZW/i/X8+PlBQID5CtDHj6v4ERERKQW3nvPjUSw9P8UVP6ALHYqIiJQRFT/u4mI9P3C+t0eTnkVEREpFxY87KCg4X/yUdGqfzvgSEREpEyp+3EFWlvksLtCwl4iISDlT8eMOzp41P/r7my9uWBz1/IiIiJQJFT/uwFL8BAeXvI6KHxERkTKh4scdOFL8lOJu9SIiIqLixz1Y7kB/sZu4WQqjQle5FhEREcep+HEHluInIKDkdSzFT0oK5OaWf0wiIiKVlIofd/D3Hd3x9y95naCg8/f0OnWq/GMSERGppFT8uANL8ePnV/I6Xl4QFmZ+rqEvERERp6n4cQeWYa+L9fwA1KxpflTxIyIi4jQVP+7AnmEvUPEjIiJSBlT8uAN7i5/wcPNjUlL5xiMiIlKJqfhxBxr2EhERqTAqftyBhr1EREQqjIofd6DiR0REpMKo+HEHKn5EREQqjIofd6A5PyIiIhVGxY870NleIiIiFUbFjztwdNgrJQXy88s3JhERkUpKxY87sAx7Xez2FnD+9haGoft7iYiIOEnFj6vl50Nenvn5xe7qDuDjAzVqmJ9r3o+IiIhTVPy42tmz559fatgLNOlZRESklFT8uFpGhvnRZDL37FyKih8REZFSUfHjapaeHz8/cwF0KTrjS0REpFRU/Liapfjx9bVvffX8iIiIlIqKH1cr3PNjD0vxs3UrzJ0LK1aUS1giIiKVlR2TTKRcWeb8ONrzk5ICqanlEpKIiEhlpp4fV3O256fwWWIiIiJiNxU/rmZv8WOZDG0pfs6cKb+YREREKjG3Kn6WLVvGkCFDbNri4uIYPHgwbdq0ITY2llWrVtksLygoYP78+XTt2pU2bdrwwAMPcOTIkYoMu3TsHfaqWtU8v+eLL8zfq+dHRETEKW5T/KxevZq5c+fatJ0+fZqhQ4dSr1491q1bx6hRo5g5cybr1q2zrrN48WLeeecdpk+fzpo1aygoKGD48OHkWO6X5e4cGfZKS4OCgvPbGUb5xSUiIlJJuXzC84kTJ5g2bRrbt28nKirKZtl7772Hr68vzz77LD4+Plx11VX8+eefLF++nIEDB5KTk8Mbb7zBxIkT6dGjBwBz5syha9eufPnll/Tr16/ifyBHOXqqe1CQ+dEwIDMTQkPLJy4REZFKyuU9P3v27MHX15eNGzfSunVrm2W7du2iQ4cO+BS68nGnTp1ISEjg5MmT7Nu3j7Nnz9K5c2fr8mrVqtGsWTN27txZYT9DqViGveyd8OztDYGB5ufnzpVPTCIiIpWYy3t+YmNjiY2NLXZZYmIijRo1smkL//sKx8ePHycxMRGAWrVqFVnHsswZhmFwrowKi8zMTJvHC/mlpeED5Ht7U2C5yanlMTf3/PNCbT7BwZgyM8lLT8fIyyMvMxOjEg2BXSpnUpRy5hjly3HKmeOUM8eVJmeGYWCy504JuEHxczFZWVn4XdAj4v/3zT+zs7OtySlunbS0NKf3m5ubS1xcnNPbFychIaHY9oaJiYQCGTk55Jw+Denp5nk96enkJifjGxJSpK1mQAC+QHpiIrlXXklSfPzlM8fJASXlTEqmnDlG+XKccuY45cxxzubswnqgJG5d/AQEBBT5o56dnQ1AUFAQAQEBAOTk5FifW9YJtAwNOcHX15fo6Ginty8sMzOThIQEoqKiio3J38s88hgcGkpBaCh4eUFIiPnRMMxzei5o8w4JgSNHqObnhxEWRrXo6ErX83OxnElRypljlC/HKWeOU84cV5qcxcfH272u08VPdnY2v//+Ozk5OdY/vAUFBWRmZrJr1y4mTpzo7EtbRUZGknTBDTwt30dERJCXl2dtq1evns06jRs3dnq/JpOJIMvE4jISGBhY/GtmZQHgHRCAt7e3+c7ulkdf3/PPC7dVrQqAT3Y2+PjgW0l/qUrMmZRIOXOM8uU45cxxypnjnMmZvUNe4GTxs337dh5++OESh5aqVKlSJsVP+/btWbNmDfn5+ebCANi2bRsNGjQgLCyMqlWrEhwczPbt263FT3p6Onv37mXw4MGl3n+FcPQKzwDBweZHTXgWERFxmFNne82ZM4fQ0FDmz59P79696du3L0uXLuXuu+/GZDLx6quvlklwAwcOJCMjgyeeeIL4+HjWr1/PypUrGTFiBGAe2xs8eDAzZ85ky5Yt7Nu3j3HjxhEZGUnfvn3LJIZy50zx83fPj4ofERERxznV8/P777/z3HPP0adPH86cOcOaNWvo3r073bt3Jzc3lyVLlrB8+fJSBxcWFsZrr73G888/T//+/alZsyaTJk2if//+1nXGjh1LXl4eU6dOJSsri/bt2/P666/ja+91c1zN0RubAlSpYn7UGQQiIiIOc6r4KSgoICIiAoD69evzxx9/WJddd911TJ482algXnzxxSJtrVq1Yu3atSVu4+3tzaOPPsqjjz7q1D5dTsNeIiIiFcqpYa969erx+++/A9CgQQMyMzM5ePAgAHl5eZzVfafsp+JHRESkQjlV/Nx8883MnDmTt99+mxo1atCiRQumT5/OV199xaJFi8rsNPFKzzCcG/ayFD8a9hIREXGYU8XP8OHDufPOO9m9ezcA06ZNIy4ujoceeoiDBw8yadKkMg2y0srJMV+5GZyb8JyZef5GpyIiImIXp+b8eHl52czradmyJZs3b+bgwYM0bNiQYEvPhFxc4eFBZyY8W25uKiIiInZzquenadOm/PLLLzZtwcHBtGrVSoWPIyxDXt7e5i97+fiA5YrWml8lIiLiEKeKn8p0KwWXshQuf9+vzCGWK1+q+BEREXGI07e32Lt3r/U+W8Vp3769sy/tOZw508siOBhSUlT8iIiIOMjp4ueZZ54ptt1yS/myvit6pVSa4scy70fFj4iIiEOcLn6efPJJndJeWpY5P84UPxr2EhERcYrTxU+LFi1o1apVWcbieUoz50c9PyIiIk5xasKzlBENe4mIiFQ4p3p+9u3bB8CBAwfYsWMHZ86cITQ0lJiYGK666qoyDbBSK82wl6X40S0uREREHOL0sNdTTz3F+++/b3Pau8lkon///syYMaNMgqv0ymLYy1JAiYiIiF2cKn5effVV1q1bx9ixY7nllluoWbMmSUlJfPTRRyxZsoRGjRpx3333lXGolZCGvURERCqcU8XPBx98wPDhw/n3v/9tbatTpw6jRo0iNzeX9957T8WPPTTsJSIiUuGcmvB8/PhxOnXqVOyyjh07cvTo0VIF5TEshUtpe350c1MRERG7OVX8XHnllfz+++/FLtu3bx81atQoVVAeoyyKH8OAtLSyi0lERKSSc6r46devHwsWLOCzzz6zTng2DINNmzaxcOFCbrzxxjINstKyFD+O3NHdwsfnfNF08mTZxSQiIlLJOTXn54EHHmDXrl2MGzeORx99lNDQUE6fPk1+fj4dOnTg4YcfLus4K6fMTPOjMz0/YL7Kc04OnDoFV19ddnGJiIhUYk4VP35+fqxYsYJvvvmGnTt3kpaWRkhICO3bt6d79+5lHWPlVZqeHzAXP6mp6vkRERFxgFPFzz333MO0adPo3r27ip3SKG3xExhoflTxIyIiYjen5vzs2LGDs7q+TOmVxbAXmIe9RERExC66t5crleZsLzhf/KjnR0RExG5O397iX//6V4nLTCYTe/fudfalPYel56e0w17q+REREbGb08XPwIEDiYyMLMtYPE9ZTHgG9fyIiIg4wOni54477qBVq1ZlGYvnUfEjIiJS4TTnx1Xy8iA31/xcE55FREQqjFPFz6pVq7jqqqtISUmxtqWnpxMfH19mgVV6lvk+oFPdRUREKpBTxU/Tpk15+OGHGTRokLXt559/pl+/fowdO5asrKwyC7DSKovip3DPz9+3GREREZGLc6r4mTlzJnFxcYwZM8ba1qlTJxYsWMCPP/7IggULyizASssy3ycwEEwm517DUvzk5+vmpiIiInZyqvj56quvmDx5ss0NTP38/OjTpw/jx49n06ZNZRZgpVW4+HFW4Zubat6PiIiIXZwqfjIyMggJCSl2Wc2aNW3mApWFvLw85s2bR8+ePWnbti2DBg3i559/ti6Pi4tj8ODBtGnThtjYWFatWlWm+y8XlmEvS++Ns6pUMT9q3o+IiIhdnCp+mjRpwrp164pdtmHDBho3blyqoC60ZMkS3n//faZPn86GDRto0KABw4cPJykpidOnTzN06FDq1avHunXrGDVqFDNnziwxPrdh6flR8SMiIlKhnLrOz8iRIxk5ciQDBgygT58+hIWFkZKSwtdff82vv/7KkiVLyjTIzZs3069fP7p06QLAlClTeP/99/n55585dOgQvr6+PPvss/j4+HDVVVfx559/snz5cgYOHFimcZSpshj2gvPFj4a9RERE7OJUz0/37t1ZvHgxAPPnz+epp55i3rx55Obmsnjx4jK/03tYWBhff/01R48eJT8/n7Vr1+Ln50eTJk3YtWsXHTp0wMfnfB3XqVMnEhISOOnOvSEa9hIREXEJp6/w3LNnT3r27El2djapqalUrVqVoNL+IS/BE088wcMPP0yvXr3w9vbGy8uLBQsWUK9ePRITE2nUqJHN+uHh4QAcP36cK664wuH9GYbBOUvPTCll/l3kZBY+tR3wPn0afyA/IIACywUP8/PNFz+0PF6qLTcXr8BAvIHcxERyyyhmVyspZ1Iy5cwxypfjlDPHKWeOK03ODMPAZOfZ004XPwCnTp0iJycHwzBITU0lJSWFzMxMdu3axV133VWal7YRHx9P1apVWbRoEREREbz//vtMnDiRt99+m6ysLPwuuEKyv78/ANnZ2U7tLzc3l7i4uFLHXVhCQoLN9xGHD1MHyD95krTUVHKTk/ENCYH0dCgogPT0S7blJidTzWQiGEiNj+dwGcfsahfmTC5NOXOM8uU45cxxypnjnM3ZhfVASZwqfvbt28fEiRM5cOBAsctNJlOZFT/Hjx9nwoQJrFy5knbt2gHQsmVL4uPjWbBgAQEBAeTk5NhsYyl6nO2J8vX1JTo6unSB/y0zM5OEhASioqIILDS/x+ebb8yP/v5Ur17dfJHC0FDw8oKQEPPjpdoMA6/kZABCCwqo0rRpmcTsaiXlTEqmnDlG+XKccuY45cxxpcmZI3eZcKr4efnll0lLS2Py5Ml8/fXX+Pn50bNnT7Zu3crWrVvL9FTz3bt3k5ubS8uWLW3aW7duzdatW6lduzZJSUk2yyzfR0REOLVPk8lU5kN4gYGBtq/59329vPz88PLxMV/l2dvbfO0ey+Ol2nx9oVo1AHxSU/Epp2FHVymSM7kk5cwxypfjlDPHKWeOcyZn9g55gZMTnnfv3s3DDz/Mfffdx4033khmZiZ33303S5cupXfv3rz11lvOvGyxIiMjAfj9999t2vfv309UVBTt27fnhx9+ID8/37ps27ZtNGjQgLCwsDKLo8xZxjOdvampRXCw+VETnkVEROziVPGTk5NDVFQUAFFRUezbt8+6bMCAATYXICytVq1acc011zB58mS2bdtGQkICc+fO5fvvv+fBBx9k4MCBZGRk8MQTTxAfH8/69etZuXIlI0aMKLMYyoVlcnJpi5+aNc2PR4+W7nVEREQ8hFPFT+3atTly5AhgLn4yMjI4+vcfXz8/P9LK8D5TXl5eLFmyhE6dOvHYY48xYMAAtm3bxsqVK2ndujVhYWG89tprHDp0iP79+7Nw4UImTZpE//79yyyGclHWPT9nzujmpiIiInZwas5P3759mTVrFkFBQVx33XU0bNiQuXPn8sADD/DGG29Qt27dMg0yJCSEadOmMW3atGKXt2rVirVr15bpPstdWfX8WIqfv88Go4TbjoiIiIiZUz0/o0ePJiYmhg8++ACAxx57jP/85z/885//ZNu2bTZ3e5cSlFXx4+enm5uKiIg4wKmeH39/f+bPn0/u32csde3alU8++YTffvuNFi1alHnPT6VUVsNeYL7Kc06OedJzw4alfz0REZFKzO7i55577rH7RU0mE2+++aZTAXmMsur5AfMtMk6fVs+PiIiIHewe9jIMo9ivvXv3cuTIEZu2goKC8oy5crAUP76+pX8t3d9LRETEbnb3/JR07Z4ZM2Zw5MiRMr+Te6VnGfb6+1YcpaI7u4uIiNjNqQnPhfXq1YudO3di6DRrx5TlsJd6fkREROxW6uInKiqKs2fPkvz3PabETpaeHw17iYiIVKhSFz9BQUEYhkF6enpZxOM5yqPnR8NeIiIil1Tq4uebb77Bx8fHeg8usZOGvURERFzC7gnPO3futPn+7Nmz/Prrr7z55ptcd911BFuuNCyXZhhlf50fUM+PiIiIHewufoYMGWJzu3jDMDCZTPTs2ZNnn322XIKrtHJyzLejAHPxk5dXutdTz4+IiIjd7C5+Vq1aZX1uMpkICgqibt26VKtWrVwCq9QsvT5Q9sWPYUChIlVERERs2V38dOjQoTzj8CyW+T5eXuDtXfrXsxQ/ubmQkQFVq5b+NUVERCqpUk94FicUvrpzWfTS+PmdP2VeQ18iIiIXpeLHFcryGj8WmvQsIiJiFxU/rlCWp7lbaNKziIiIXVT8uEJZ3tTUQsWPiIiIXVT8uIKGvURERFxGxY8raNhLRETEZVT8uEJ59PwEBZkf1fMjIiJyUSp+XEE9PyIiIi6j4scVymPCs+Xeaur5ERERuSgVP65QnsNe6vkRERG5KBU/rqBhLxEREZdR8eMK5Xmdn1OnzDc3FRERkWKp+HGF8rzOT3Y2nD1bdq8rIiJSyaj4cYXyGPby84OAAPNzTXoWEREpkYofVyiPnh+TCcLCzM8170dERKREKn5coTx6fgCuuML8qOJHRESkRCp+XKE8JjzD+Z4fDXuJiIiUSMWPK5THsBeo50dERMQOl03xs2HDBm688UZatmzJTTfdxGeffWZddvToUUaMGEFMTAxdunRh7ty55OfnuzDaSyjvYS/1/IiIiJTosih+PvroI5544gkGDRrEp59+Sr9+/Rg/fjw//fQTubm5DBs2DIA1a9bw9NNP8+6777Jo0SIXR30R5dXzownPIiIil+Tj6gAuxTAM5s2bxz333MOgQYMA+Pe//82uXbvYsWMHx44d46+//uK9994jJCSERo0acerUKV5++WVGjhyJX1n3rpQFy3V41PMjIiJS4dy++Dl06BDHjh3j5ptvtml//fXXAXj66adp3rw5ISEh1mWdOnUiIyODuLg4Wrdu7fA+DcPgnGVoqpQy/+7lsTwCBJ49iwnI9fKC/HzIy4Pc3PPP7W0r/BwwwsLwA/JPnCC7jOJ3heJyJhennDlG+XKccuY45cxxpcmZYRiYTCa71r0sih+Ac+fOMWzYMPbu3UudOnX497//TWxsLImJiURGRtpsEx4eDsDx48edKn5yc3OJi4srffCFJCQkWJ+3/bv4ST17Fk6fhvR0cpOT8Q0JgfR0KCiwq63w84L8fM4FB9MAyP7rrzKP3xUK50zso5w5RvlynHLmOOXMcc7mzN7RHrcvfjIyMgCYPHkyo0ePZuLEiXzxxRc89NBDrFixgqysLKpVq2azjb+/PwDZ2dlO7dPX15fo6OjSBf63zMxMEhISiIqKIjAwEHJz8fq7p6Z6RASEhoKXl/l+XJbnISH2tRV+DoS0bAlAQEYGTZs2LZP4XaFIzuSSlDPHKF+OU84cp5w5rjQ5i4+Pt3tdty9+fP+eFDxs2DD69+8PQNOmTdm7dy8rVqwgICCAnJwcm20sRU9QUJBT+zSZTE5vW5LAwEDza6amWtt8g4LA2xt8fMyTny3P7W0r/BzwrVcPAK/kZIICA81Xfb6MWXMmdlPOHKN8OU45c5xy5jhncmbvkBdcBmd7RUREANCoUSOb9ujoaI4ePUpkZCRJSUk2yyzfW7Z1K5bJzt7e5q+y9PdwH7m5NkWWiIiInOf2xU/z5s2pUqUKu3fvtmnfv38/9erVo3379uzdu9c6PAawbds2qlSpQpMmTSo63EuzTESuUqXse2b8/c3DYwAnTpTta4uIiFQSbl/8BAQEMHz4cBYtWsQnn3zC4cOHWbJkCd9++y1Dhw6ld+/e1KxZk0ceeYR9+/axefNmZs+ezf333+/ep7mXVxeopbdLxY+IiEix3H7OD8BDDz1EYGAgc+bM4cSJE1x11VUsWLCAjh07AvDaa6/xzDPPcMcddxASEsLdd9/NQw895OKoS2ApfqpUKdvXtfQiRUTA/v1wwVCgiIiImF0WxQ/A0KFDGTp0aLHL6tevzxtvvFHBETmp8LBXWapaFVasgLQ08/fq+RERESmW2w97VTrlOeyVlnb+qtEqfkRERIql4qeildewl0VwsPlRxY+IiEixVPxUtPIa9rKwvK7m/IiIiBRLxU9FK++zvSzFj3p+REREiqXip6Jp2EtERMSlVPxUtIoa9lLxIyIiUiwVPxWtooa9zp07vy8RERGxUvFT0cp72MvPz3zDU1Dvj4iISDFU/FS08h72MpnMFzwEFT8iIiLFUPFT0cp72AtU/IiIiFyEip+KVt7DXnD+jC9d60dERKQIFT8VrbyHvUA9PyIiIheh4qeiadhLRETEpVT8VLSKHPZS8SMiIlKEip+KVpHDXprzIyIiUoSKn4qmYS8RERGXUvFT0Spi2EvFj4iISIlU/FSk3FzIyzM/r4g5P6mpkJ1dfvsRERG5DKn4qUiF77VVnsNegYHg42N+rnk/IiIiNlT8VCRL8ePtbb4HV3nx8oLISPPz48fLbz8iIiKXIRU/FanwmV4mU/nuq25d8+ORI+W7HxERkcuMip+KVBGTnS3q1DE/Hj1a/vsSERG5jKj4qUgVcZq7hXp+REREiqXipyJVxAUOLSw9Pyp+REREbKj4qUgVOexl6fnRsJeIiIgNFT8VqSKHvdTzIyIiUiwVPxWpIoe9LD0/f/0F+fnlvz8REZHLhIqfilSRw16RkebrCeXnQ2Ji+e9PRETkMqHipyJV5LCXtzfUrm1+rnk/IiIiVip+KlJFDnuB5v2IiIgUQ8VPRarIYS/QGV8iIiLFuKyKn0OHDtG2bVvWr19vbYuLi2Pw4MG0adOG2NhYVq1a5cIIL6Eih71APT8iIiLFuGyKn9zcXCZOnMg5y9ARcPr0aYYOHUq9evVYt24do0aNYubMmaxbt86FkV6Een5ERERczsfVAdhrwYIFBAcH27S99957+Pr68uyzz+Lj48NVV13Fn3/+yfLlyxk4cKCLIr0IzfkRERFxucui+Nm5cydr165lw4YN9OjRw9q+a9cuOnTogI/P+R+jU6dOLFu2jJMnT3LFFVc4tT/DMGx6mEojMzPT+uifno43kO3tTUFmJj55eeZT0fPyIDf3/HN720panpdHXmYmppo1CQAKjhwhq4x+nopQOGdiH+XMMcqX45QzxylnjitNzgzDwGQy2bWu2xc/6enpTJo0ialTp1KrVi2bZYmJiTRq1MimLTw8HIDjx487Xfzk5uYSFxfnXMAlSEhIoPGpUwQDR0+f5lx8POGnTuFVUADp6eQmJ+MbEgLp6WBnW0nLvQsKSIqPxzh3jlaA6fhx4n77zXz6+2UkISHB1SFcdpQzxyhfjlPOHKecOc7ZnPn5+dm1ntsXP08//TRt27bl5ptvLrIsKyuryA/q7+8PQHZ2ttP79PX1JTo62untC8vMzCQhIYGoqCiCDAOAKxs1woiOxicsDEJCwMsLDANCQ83P7W27yPJq0dEYUVEYPj6Y8vJoVqMGhuW6P26ucM4CAwNdHc5lQTlzjPLlOOXMccqZ40qTs/j4eLvXdeviZ8OGDezatYuPP/642OUBAQHk5OTYtFmKnqBSnFFlMplKtX1xAgMD8fq7Gy+gRg0IDAQfH3NvjI8P+Pqef25vW0nLfXzwtRw0tWvD4cMEnjwJZVTQVZTAwMAyfx8qO+XMMcqX45QzxylnjnMmZ/YOeYGbFz/r1q3j1KlTNvN8AKZNm8amTZuIjIwkKSnJZpnl+4iIiIoK034VfbYXmCc9Hz6sM75ERET+5tbFz8yZM8nKyrJp69u3L2PHjuWWW27ho48+Ys2aNeTn5+P993yWbdu20aBBA8LCwlwR8sVV9NleAPXqwXffgcacRUREADe/zk9ERAT169e3+QIICwsjIiKCgQMHkpGRwRNPPEF8fDzr169n5cqVjBgxwsWRl6CiL3JYeJ+ffFJx+xQREXFjbl38XEpYWBivvfYahw4don///ixcuJBJkybRv39/V4dWVE6O+VR0qNien2rVzI/HjlXcPkVERNyYWw97Fef333+3+b5Vq1asXbvWRdE4oPB1diqy+KlZ0/yYnFxx+xQREXFjl3XPz+XEZCl+vL3NZ2RVFEvxk5YGGRkVt18RERE3peKnghjh4dC8OfTrBw6cjldqQUHn5xj98UfF7VdERMRNXXbDXpctHx/49deKLXwswsLMw27790PbthW/fxERETeinp+K5IrCB8zFD5iLHxEREQ+n4scTqPgRERGxUvHjCVT8iIiIWKn48QSFi5+/b64qIiLiqVT8eILQUPN8o9RUOHnS1dGIiIi4lIofT+DrC9Wrm59r6EtERDycip/KqLizysLDzY8qfkRExMPpOj+VUdWqsGIFBAefb6tZE37/XcWPiIh4PBU/lVVamu3kZsttLvbudU08IiIibkLDXp7iyivNjz/+6No4REREXEzFj6eoUwe8vODoUUhMdHU0IiIiLqPix1P4+0PTpubnu3a5NhYREREXUvHjSdq1Mz/u3OnaOERERFxIxY8nad/e/KieHxER8WAqfjxJ4Z4f3eZCREQ8lIofT9K6Nfj4QHIyHDni6mhERERcQsWPJwkIgJYtzc8170dERDyUih9PYxn60rwfERHxUCp+PI1l0rN6fkRExEOp+PE0hSc95+W5NhYREREXUPHjaVq1gho1ID0dvv/e1dGIiIhUOBU/nsbbG66/3vz8009dG4uIiIgLqPjxRDfdZH7ctMm1cYiIiLiAih9PYTKdf3799eabnP76Kxw+7LqYREREXEDFj6eoWhVWrIC5c2HLFmjY0NxeuPdnxQrzl4iISCWm4seTpKVBaiqcOQONGpnbChc/aWnmLxERkUpMxY+natbM/LhlC2RluTYWERGRCqTix1PVrg3Vq8O5c/DRR66ORkREpMJcFsVPamoqTz31FN26dSMmJoa77rqLXYVuz/D9998zYMAAWrduzfXXX8+nOoX70kwm6NjR/HzBAtfGIiIiUoEui+Jn/Pjx/PTTT8yePZt169bRtGlThg0bxsGDBzlw4AAjRoyga9eurF+/nttvv51JkybxvS7gd2mdO4OvL3z7Lfzwg6ujERERqRA+rg7gUv7880++/fZb3nnnHa655hoAnnzySf73v//x8ccfc+rUKRo3bsy4ceMAuOqqq9i7dy+vvfYanTt3dmXo7i8kBO64A1avNvf+tGnj6ohERETKndsXP6GhoSxfvpyWLVta20wmEyaTifT0dHbt2kXv3r1ttunUqRPPP/88hmFgKnx9GzsZhsG5c+dKHTtAZmamzaOFyWTCJy8P8vPN99jKzT3/3N620m4D5D/wAAGrV2O8+y55UVEQHExeZiaGYVjjLJyXilBSzqRkypljlC/HKWeOU84cV5qcOfI33+2Ln2rVqtG9e3ebti+++II///yTxx9/nA8//JDIyEib5eHh4WRmZnL69Glq1Kjh8D5zc3OJi4srVdwXSkhIsPnez8+P8FOn8CoogPR0cpOT8Q0JMd9zy8620m5TkJ9PUo0aNGzenCp79pDz5ZdkdO9OUnw8OTk5+Pn5Uevzz8lPScG7Rg2OX389OTk5ZZoXR3Iml6acOUb5cpxy5jjlzHHO5szPz8+u9dy++LnQjz/+yGOPPUbfvn3p0aMHWVlZRX5Yy/fO/qH29fUlOjq61LGCuXpNSEggKiqKwMBAa7vJZMInLMw89OTlBYYBoaHm5/a2lXYboFp0NF5PPQX/+hdBO3fi16MH1aKjrRW0j8lkXtdkosrf7eWtpJxJyZQzxyhfjlPOHKecOa40OYuPj7d73cuq+Nm8eTMTJ04kJiaGmTNnAuDv71+kyLF87+zBZjKZCAoKKl2wFwgMDCz6mj4+5huN+viYJx5bntvbVtptAN/AQLj9dli2DNNXX+G7aRO+M2bYxujrCz4+5nUrULE5k4tSzhyjfDlOOXOccuY4Z3LmyDSXy+JsL4C3336bMWPG0LNnT5YuXYq/vz8AtWrVIikpyWbdpKQkgoKCqFq1qitCvfyYTObbXphMsHs3fPONqyMSEREpN5dF8fPOO+8wffp0Bg0axOzZs22Gudq1a8eOHTts1t+2bRsxMTF4eV0WP557aNkSrr3W/Hz0aPPEaBERkUrI7auDQ4cOMWPGDPr06cOIESM4efIkycnJJCcnc+bMGYYMGcIvv/zCzJkzOXDgAG+88Qaff/45w4cPd3Xol58bboAqVeC338w9QSIiIpWQ28/5+eKLL8jNzeU///kP//nPf2yW9e/fnxdffJHFixfzyiuv8Oabb1KnTh1eeeUVXePHGVWqwC23wLvvwtNPm68BJCIiUsm4ffEzcuRIRo4cedF1unXrRrdu3SoookqufXv46y/zvJ/Ro6FXL1dHJCIiUqbcfthLKpjJBEuWmM/w+uQT2LPH1RGJiIiUKRU/FW3FCvN8mvffd3UkJWvaFP6+XQgbNlivBi0iIlIZqPipaGlpkJoKZ864OpKLmzoVatWCkydh2zZXRyMiIlJmVPxI8apWhZdfNj/futVcsImIiFQCKn6kZIMGQVSU+Zo/H3/s6mhERETKhIofKZnJBAMGmJ//+CP873+ujUdERKQMqPjxZMXdB+XCtrp1ISbG/HzMGMjPL/+4REREypHbX+dHylHVquazz9LS4MorS26LjYW4OPN9v5YsMV//R0RE5DKlnh9PV9zZZxe2VakCN95ofj55Mhw4UNFRioiIlBkVP2Kfa6+F7t3h3DkYOhQKCsztK1aYv0RERC4TKn7EPl5e8MYb5l6g//0P5swxt6elmb9EREQuEyp+xH4NG8KsWebnU6bA11+7Nh4REREnqPgRxzz4INx9t/mWF7fdZr4CtIiIyGVExY84xmSC114z3/09JcX8/OxZV0clIiJiNxU/4rjAQPjoI/Op8CdOqAASEZHLioofsc+FFz+sVQu++AKCgiAhAW6/3XwbDBERETenixyKfSwXPwwOhoyM8xdBfOABWLwYPvvMfAr8qlXmM8NERETclP5Kif3S0swXPix8EcSoKHPR4+MDq1fD+PFgGK6OVEREpEQqfqT0mjaFlSvNz+fNgxkzXBqOiIjIxaj4kbIxaJC58AGYOhWWLXNtPCIiIiVQ8SNlZ+xYc+ED8O9/w6hRro1HRESkGCp+pPQKnwn27LPQubN53s+yZboKtIiIuB2d7SWlZzkTzHIG2G23mSdEx8XBrbfCN99A27aujlJERARQz4+UlcJngHl5wYABEB1t/v6GG2D/fldHKCIiAqj4kfLi4wPDhkGbNuarQMfGwoEDro5KRERExY+Uo/BwuO8+qFMHjh0z3w/spZdcHZWIiHg4FT9SvgzDfOHDmjXh9Gl4/nnYvdvVUYmIiAdT8SPlLyTEfNp7eLh5DlC3brB5s6ujEhERD6XiRypGSIj5NhgNG0J6OvTtC48/rpuhiohIhVPxIxUnIABGjDDfDNUw4IUX4Jpr4IMPoKDA1dGJiIiHqBTFT0FBAfPnz6dr1660adOGBx54gCNHjrg6LCmOvz8sXw7vvQfVq8Ovv8Ltt8PVV8PIkfD223hv20aV5GRMOTmujlZERCqhSnGRw8WLF/POO+/w4osvEhkZySuvvMLw4cP5+OOP8fPzc3V4UpjlgojBwearQX/yCfzvf3DwoPmK0MuW4Q80saxfpQpccQVUqwahodCzJ9Subb6Y4q5d5gJq7Fjbq0yLiIhcxGVf/OTk5PDGG28wceJEevToAcCcOXPo2rUrX375Jf369XNtgFJUWpp52Cs/33wrjJ49zXeG37oVNmzASEmBjAxMeXlw9qz5y2Lr1qKvN2mSeTJ1aKh9X9Wrmx9DQsxDcSqcREQ8ymVf/Ozbt4+zZ8/SuXNna1u1atVo1qwZO3fuVPFzOQgIMN8G49ZboW5d8pKTSa1WjepZWfgmJpqXHz9uLprq1TNfM+jYMYiPh4wMyMmBo0fNX47y8YGgIAgMNBdEbdpARMT5r/Bw8PMzF2sWJpP5bLVz58w9Urfeau6hqlr1/Jevr/P5yMkx/1xnzpi/MjJg3TrIzDTHeMcd5ngt+6xSxfl9iYiUF8OArCzzP7AZGfDWW3DqlPkzdepU8+eni5gMo/Cn+uXnyy+/ZMyYMezevZuAgABr+8MPP0xWVhbLli1z6PV+/PFHDMPAtzR/vAoxDIO8vDx8fHwwmUyYMjLMk3t9fMyPXl7mR2faKss2Xl4YwcEAmDIyMPLzMby9MRkGJsM4vw1Y17Osi8kEeXnmXiTA8PeHggJMBQXmXzrDOL8fwzCvX/j78uLlZd6XV6FpdcX1MBnG+TgssToal8l0/suyv8L7Us9WsQzDwKTcOMQjc1bKzwm3zFl5/9kv/FlW0r4CAzEiI4vZ1PZvpiNyc3MxmUzExMRcct3LvucnMzMToMjcHn9/f9LS0hx+PUuyy+pgNZlMtrFVrVomr1vZWLNdtSqmwt+XtN7f6150uchF6FhxnHLmOOWsZMXlpsjfTEdez2Sy+2/3ZV/8WHp7cnJybHp+srOzCQwMdPj12uru4yIiIpXaZX+qe61atQBISkqyaU9KSiIiIsIVIYmIiIgbu+yLnyZNmhAcHMz27dutbenp6ezdu5f27du7MDIRERFxR5f9sJefnx+DBw9m5syZ1KhRgyuvvJJXXnmFyMhI+vbt6+rwRERExM1c9sUPwNixY8nLy2Pq1KlkZWXRvn17Xn/99TI7Y0tEREQqj8v+VHcRERERR1z2c35EREREHKHiR0RERDyKih8RERHxKCp+RERExKOo+BERERGPouJHREREPIqKHxEREfEoKn5KqaCggPnz59O1a1fatGnDAw88wJEjR0pc//Tp00yYMIH27dvToUMHnnnmGeud6T2FoznbuHEjjRs3LvJ19OjRCozafSxbtowhQ4ZcdB0dZ+fZky8dY5CamspTTz1Ft27diImJ4a677mLXrl0lrn/06FFGjBhBTEwMXbp0Ye7cueTn51dgxK7naM6WLFlS7HHmSU6dOsWjjz5Kp06daNu2LQ8++CAHDhwocf3y+iyrFFd4dqXFixfzzjvv8OKLLxIZGckrr7zC8OHD+fjjj/Hz8yuy/tixY8nMzGTlypWkp6fzxBNPcO7cOV566SUXRO8ajubs999/p0OHDsyePdumvUaNGhUVsttYvXo1c+fOpV27dhddT8eZmb350jEG48ePJzk5mdmzZxMWFsZbb73FsGHD+PDDD2nYsKHNurm5uQwbNoyoqCjWrFnD4cOHeeKJJ/Dy8mLs2LEu+gkqniM5A/Nxduutt/Loo4+6IFr3MGrUKAoKCli+fDlVqlRh3rx53HfffXz55ZcEBgYWWb/cPssMcVp2drbRtm1bY/Xq1da2tLQ0o1WrVsbHH39cZP0ff/zRaNSokREfH29t+9///mc0btzYSExMrJCYXc3RnBmGYQwfPtyYPn16RYXolhITE40RI0YYbdq0Ma6//npj8ODBJa6r48yxfBmGjrGEhASjUaNGxq5du6xtBQUFRu/evY25c+cWWf/jjz82WrRoYaSmplrb1qxZY8TExBjZ2dkVErOrOZozwzCMG264wVixYkUFReh+UlNTjfHjxxu///67tS0uLs5o1KiRsXv37iLrl+dnmYa9SmHfvn2cPXuWzp07W9uqVatGs2bN2LlzZ5H1d+3aRc2aNbnqqqusbR06dMBkMvHDDz9USMyu5mjOwPzfUuGceaI9e/bg6+vLxo0bad269UXX1XHmWL5Ax1hoaCjLly+nZcuW1jaTyYTJZCI9Pb3I+rt27aJ58+aEhIRY2zp16kRGRgZxcXEVErOrOZqznJwcEhISiu0R8hQhISHMmjWLRo0aAZCSksLKlSuJjIwkOjq6yPrl+Vmm4qcUEhMTAahVq5ZNe3h4uHVZYSdOnCiyrp+fH9WrV+f48ePlF6gbcTRnaWlpnDhxgl27dnHzzTfTpUsXHnroIQ4dOlQh8bqL2NhYFixYQN26dS+5ro4zx/KlY8z8D0j37t1thp2/+OIL/vzzT7p27Vpk/cTERCIjI23awsPDATzmGHM0Z/Hx8eTn5/PFF19w3XXX0aNHDx599FGSkpIqMmy38eSTT9K5c2c+/fRTnn/+eYKCgoqsU56fZSp+SsEy6erCeSr+/v5kZ2cXu35xc1pKWr8ycjRnf/zxBwCGYfDCCy8wd+5csrOzufvuuzl58mT5B3wZ0nHmGB1jRf3444889thj9O3blx49ehRZnpWVVezvMOCxx9ilcrZ//34AAgMDmTdvHs8//zwHDx7knnvuISsrq4Kjdb17772XdevW0a9fP0aNGsWePXuKrFOen2Wa8FwKAQEBgLk70/IczL/8xU3cCggIICcnp0h7dnZ2sVVvZeRoztq1a8f3339PaGgoJpMJgIULF9KjRw/Wr1/Pgw8+WDGBX0Z0nDlGx5itzZs3M3HiRGJiYpg5c2ax6xR3jFn+GHniMWZPzv75z3/SrVs3m0n0V199Nd26deOrr77ixhtvrKhw3YJlmOv5559n9+7dvP3227zwwgs265TnZ5l6fkrB0h13YbdlUlISERERRdaPjIwssm5OTg6pqanWLuPKztGcgfmMG8sfJTD/51SnTh1OnDhRfoFexnScOU7HmNnbb7/NmDFj6NmzJ0uXLrX25lyouGPM8n1Jv8eVlb05g6JnD4aHh1O9evVih/wro5SUFD799FPy8vKsbV5eXkRHRxc7/Feen2UqfkqhSZMmBAcHs337dmtbeno6e/fupX379kXWb9++PYmJifz555/Wth07dgBwzTXXlH/AbsDRnK1du5aOHTty7tw5a1tGRgYJCQnFTpATHWeO0jFm9s477zB9+nQGDRrE7Nmzix1usGjfvj179+4lIyPD2rZt2zaqVKlCkyZNKiJct+BIzubMmcN1112HYRjWtqNHj3L69GmPOc5OnjzJ+PHj+f77761tubm57N27t9gTDsrzs0zFTyn4+fkxePBgZs6cyZYtW9i3bx/jxo0jMjKSvn37kp+fT3JysnU8t3Xr1sTExDBu3Dh++eUXtm3bxlNPPcU///lPj/lvydGcdevWjYKCAiZNmsQff/zBr7/+ypgxY6hRowYDBgxw8U/jHnScOUbHWFGHDh1ixowZ9OnThxEjRnDy5EmSk5NJTk7mzJkz5OTkkJycbB2C6N27NzVr1uSRRx5h3759bN68mdmzZ3P//fdftACoTBzNWZ8+fTh27BhPP/00hw4dYufOnYwZM4aYmJhiJ0hXRo0aNaJbt24899xz7Ny5k/379zNlyhTS09O57777KvazrFQnyouRl5dnvPzyy0anTp2MNm3aGA888IBx5MgRwzAM48iRI0ajRo2MdevWWdc/efKkMWbMGKNNmzZGx44djWnTphlZWVmuCt8lHM3Zb7/9ZgwdOtS45pprjJiYGGPMmDHGX3/95arwXW7y5Mk2163RcXZx9uTL04+xJUuWGI0aNSr2a/Lkyca2bduMRo0aGdu2bbNuk5CQYAwdOtRo2bKl0aVLF2Pu3LlGfn6+C3+KiuVMzr777jvjX//6l9GmTRujQ4cOxmOPPWZzrSRPkJ6ebkybNs34xz/+YbRq1cq4//77jf379xuGUbGfZSbDKNQHJyIiIlLJadhLREREPIqKHxEREfEoKn5ERETEo6j4EREREY+i4kdEREQ8ioofERER8SgqfkRERMQlli1bxpAhQxzaJi8vj3nz5tGzZ0/atm3LoEGD+Pnnnx16DRU/IiIiUuFWr17N3LlzHd5uyZIlvP/++0yfPp0NGzbQoEEDhg8fXuz9wUqi4kdE3NIPP/zAmDFj+Mc//kHLli3p1asXU6dO5cCBA0XW/eyzzxgyZAjt2rWjSZMmNG7cmCZNmvDBBx+4IHIRuZgTJ04wcuRIZs6cSVRUlMPbb968mX79+tGlSxfq16/PlClTOHPmjEO9Pyp+RMTtLF++nEGDBpGZmcnjjz/O66+/zsiRI9m7dy/9+/fn008/ta67cuVKnn76aXr27Mm8efN49913+eCDD/jmm2+47bbbXPhTiEhx9uzZg6+vLxs3bqR169ZFln/99dcMGDCAVq1a0adPH+bOnWu9RxpAWFgYX3/9NUePHiU/P5+1a9fi5+fn0E11dXsLEXErX3/9NSNHjmTMmDGMHj3aZllubi4TJkzg66+/Zv369URFRdGlSxdeeeUVunXr5qKIRcRZU6ZM4dixY7z11lsAbN26lTFjxvDYY49x7bXXcvjwYaZPn06TJk2YN28eAAcOHODhhx/mjz/+wNvbGy8vLxYsWEDPnj3t3q96fkTErSxcuJCGDRsyatSoIst8fX159tln8fb25tVXX+WPP/4gKyuLunXrMmLECNq2bUvHjh157LHHSElJAWDIkCE0btzY+nX06NGL7n///v2MGDGCmJgYYmJiGDVqFEeOHLEu3759u/W1fvjhB5tt3377bRo3bkxsbGwZZELE8yxdupQ77riDO++8k3r16tGlSxeeeeYZPv/8c+vvbnx8PFWrVmXRokWsXbuWAQMGMHHiROLi4uzej095/QAiIo5KSUnht99+Y9iwYZhMpmLXqV69Otdeey1btmyhT58++Pr6cu+99xITE8OcOXNISUlhzpw5/Pbbb7z//vtMmzaNjIwM/vvf/7JkyZKL7v/QoUPceeedNGzYkJdeeom8vDyWLFnCXXfdxUcffURYWJh13SpVqvDVV19xzTXXWNs2bdqEl5f+pxRx1t69e/nll19s5utZBqgOHDiAt7c3EyZMYOXKlbRr1w6Ali1bEh8fz4IFC1i8eLFd+1HxIyJu49ixYwBceeWVF12vfv36bNmyhbNnz3LmzBmaNGlic9ZIo0aNGDhwIOvXr+fuu+8G4ODBg5fc/8KFCwkMDGTlypUEBwcD0LlzZ3r37s1rr73G5MmTret269aNLVu28OijjwKQmJjITz/9RLt27aw/h4g4pqCggOHDh9O/f/8iy2rWrMnWrVvJzc2lZcuWNstat27N1q1b7d6P/kUREbdh+Q/P19f3out5e3sDWHtZbr31VpvlLVq0oF69emzfvr3ItgUFBeTn5xf7utu2baNDhw4EBASQl5dHXl4ewcHBtGvXju+++85m3djYWBISEqxF1eeff07r1q0vWbiJSMmuvvpqDh06RP369a1fiYmJvPzyy5w9e5bIyEgAfv/9d5vt9u/f79CZY+r5ERG3YSkcLtVzcuTIEapUqUKVKlUAiIiIKLJOaGgoGRkZRdr79OkDmAuoOnXq0L9/f0aOHInJZCI1NZVNmzaxadOmItvVqFHD5vuIiAhatGjBli1baNiwIZs2baJfv37s3bvXvh9WRIp44IEHeOSRR1i4cCE33XQTiYmJPPHEE9SpU4eaNWsSFhbGNddcw+TJk5k2bRqRkZFs2LCB77//nnfffdfu/aj4ERG3ERYWRps2bfjiiy94+OGHi50/k5GRwbfffktsbKy1WLJMbi7sr7/+4tprry3SvmTJEmrWrMm5c+f46aefmD9/PkFBQdx7771UrVqVa6+9lqFDhxbZzsen6Mdlr1692LJlCzfccAO//fYbCxcuVPEjUgrXX389c+bMYdmyZSxdupTq1asTGxvLxIkTAXNv75IlS5g7dy6PPfYYaWlpNGrUiJUrVxZ72nxJVPyIiFsZPXo0w4cPZ/bs2dYPPIv8/HymTZtGVlYWw4cP5+qrryYiIoKPP/6Yf/7zn9b1tm7dSnJycrGnvzdq1Ig6deoA0LFjRz7//HO2bdvGvffeS4cOHYiPj6dp06bWYscwDCZOnEj9+vVp2rSpzWv17t2b+fPn8/bbb3PNNdcQHh5extkQqdxefPHFIm033HADN9xwQ4nbhISEMG3aNKZNm+b0flX8iIhb6dq1K1OmTOHll18mLi6OgQMHEh4eztGjR3n33XeJi4vj+eeft17QbMqUKYwbN47x48dz6623cvz4cWbPnk3btm2L/QCNi4vj5MmTnD17lh9++IH9+/dz0003AfDQQw9x5513MmLECO666y78/f1Zu3YtmzdvZv78+UVe6+qrr6Zu3bqsWrWKp556qnwTIyJlRsWPiLidoUOH0rZtW958801eeuklUlJSqFmzJv/4xz94/vnniY6Otq574403AuarQo8dO5bAwEB69erF448/bp0YXZjlwom+vr7Url2b0aNHM2zYMACaNGnC6tWrmTNnDpMmTcIwDBo1asSiRYvo1atXsbH26tWLVatW0bdv37JOg4iUE13hWURERDyKTnUXERERj6LiR0RERDyKih8RERHxKCp+RERExKOo+BERERGPouJHREREPIqKHxEREfEoKn5ERETEo6j4EREREY+i4kdEREQ8ioofERER8Sj/D3Ud0DuEc5TjAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -160,37 +160,468 @@
     },
     {
      "data": {
-      "image/png": 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",
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1lR07djheZ2Rk8Ouvv9KnTx8AevXqxa5du2jZsiWdOnVy/HzwwQe88847mM1mfvnlFwoLC+ndu/dxj9OqVSvi4uLYu3ev034SEhJ46qmnHP86tud47L82j1admOxOO+00p3Wq+tfu1q1befvtt3nggQeqLL569erF9u3bad++vWM/HTt2ZNGiRXzxxRdVxtiyZUvi4+P5+OOPndr37NnDxo0b6datGwB9+/bFarWycuVKp/WWL19OdHQ0Xbt2dWq3F9KdO3fm/PPPZ/z48RQUFPD777/TpUsXLBYLGRkZTjkHBwfz9NNPV1kc2IfEVqxYwT/+8Y9Ky6vzfTyR5ORkOnXqRPfu3Rk7diz169fn559/Pul2VanO59CjRw/27NnDtm3bHNuVlJRw++23OwqC46nuZ3ay3FzdzxNPPMFZZ53Feeed59L7UZ331v4+9erVi3vuuYd69eo5XfVo17dvX/bu3eu4ig4qhl7fe+89kpKSaNasGb169aKsrIxPP/3UaVv7VWlH/+Nrw4YNToXQn3/+yd69ex3nFbtBgwbx2GOP8e677zp6+Nz5HkvNU0+QeETnzp157rnneP755znzzDNJS0tj4cKFlJaWOoZ52rVrx8UXX8yTTz5JcXEx7du359tvv+Wrr75i3rx5Lh3P+P8rPsaNG4fZbGbevHnExMQ4LtG9/vrr+eCDD7j++uv53//+R2xsLCtWrOCtt95i8uTJ7N69m/nz5ztiTUtLc+y7tLSUrKwsdu/eTfPmzRk3bhxTpkzBbDbTv39/8vLyeO6558jIyOCMM87gt99+Y+3atZhMpkpDUkc7WUyu+uuvvxg2bBidO3eucvmtt97KlVdeyahRo7jqqqsIDQ3lzTffZNWqVcyZM6fKbYKCghg/fjyTJ0/mrrvu4t///jfZ2dmO99fem9G3b1/OO+88HnjgATIyMmjbti1ffPEFK1asYOrUqYSFhTntNz8/n40bN2Kz2Th8+DBvvvkmYWFhdOjQgdjYWEaOHMkzzzxDfn4+vXv3JiMjg2eeeQaTyVTlXJyBAweyePFizGZzpeEVqN738URSUlI4dOgQJSUlrF+/npycHEdPiauq8zkMHTqUV199lVtuuYWxY8cSGxvLkiVLsFqtXH311Sfcf3U/s5Pl5s5+jr0isTqq895u3LgRwzDIy8vjq6++Ii8vz3FvsqMNGzaM119/nVtvvZU77riDxo0b8+677/Lbb7+xYMECoGLoqnfv3tx///1kZGTQrl071q5dywsvvMCQIUOcjl1UVMTIkSO55ZZbKCgoYNasWSQnJ1eaJwU4eq8ee+wx+vXr59b3WGqeiiDxCPvltEuWLOHZZ5+lcePGXHrppZhMJhYuXEheXh716tXjySefZN68eSxevJjs7Gxat27NnDlzuOCCC1w6XpMmTfjf//7Ho48+SlFREWeffTbz58939JgkJCTwxhtv8NRTT/Hggw9SUlJCUlISjzzyCJdffjn33HMP33//PVBxWfOxvvnmGxo0aMCMGTP4z3/+Q2RkJC+++CJvvvkmERERdOvWjZkzZ9KsWTMGDx5McHAwN9988wmLoJPF5Kro6Gjuuuuu4y5v164dr732GrNmzWLixIkYhkFycjLPPvssAwcOPO52Q4cOJTIykoULF3LbbbcRFRVF3759GT9+vNPk19mzZzNr1iyWLFlCVlYWTZo04aGHHuK///1vpX1u2rTJ8T5HR0fTtm1bFi5c6JjndOeddxIfH8+yZct48cUXiYmJoU+fPowfP77KievdunWjfv36dO3atcr3vLrfx+Ox39rAbDYTHx/P//73P6688srjrn8i1fkcoqKiWLp0KU888QQPPfQQ5eXlnHnmmSxZssRpou7xVPczO1luruznhhtuoEWLFi6/H9V5b+3flbCwMJo1a8a0adO46KKLKt0/y2Kx8PLLL/Pkk08yd+5cjhw5QsuWLZk3b55jONn+mc+ZM4dFixaRlZVF06ZNGT9+fKXCrkePHpx11lmO+XgDBgxg4sSJxx3uu/feexk8eDBz585l8uTJLn+PpeaZjBNdRiLiB+655x7Wrl1baVjN1X0AzJgxw63lIuJf7L3Ir776qocjkVOhOUEiIiISkDQcJlINJxtiqM4QhIiIeBcNh4mIiEhA0nCYiIiIBCQVQSIiIhKQVASJiIhIQNLE6GP8+uuvGIaBxWLxdCgiIiJSTVarFZPJVOkO9CeinqBjGIZxwidwu7qv0tLSGtuftwqUPEG5+qNAyROUqz8KlDzh5Lm68/tbPUHHsPcAnewBoNVRWFhISkoKbdq0qfJhfv4iUPIE5eqPAiVPUK7+KFDyhJPn+scff7i8T/UEiYiISEBSESQiIiIBSUWQiIiIBCSPF0E5OTlMmTKFfv360a1bN6666irWr1/vWP7TTz8xdOhQunTpwsUXX8wnn3zitH1JSQnTpk2jT58+dO3albvuuousrKy6TkNERER8jMeLoPHjx/Prr7/y9NNP8+6779K+fXtuvPFGdu7cyY4dOxg1ahR9+/Zl+fLl/Oc//2HixIn89NNPju0ffPBBvv/+e+bOncvixYvZuXMnY8eO9WBGIiIi4gs8enVYWloaP/zwA8uWLaN79+4APPDAA3z33Xd89NFHHD58mLZt2zJu3DgAWrduzaZNm3jxxRfp06cPGRkZvP/++yxYsIAePXoA8PTTT3PxxRfz66+/unSvABEREQksHu0Jio2N5fnnn3e6HN1kMmEymcjLy2P9+vX06dPHaZuzzjqLDRs2YBgGGzZscLTZtWzZkoSEBNatW1c3SYiIiIhP8mhPUL169TjvvPOc2j777DPS0tK49957ee+990hMTHRa3qhRI4qKisjOziYjI4PY2FhCQ0MrrZOenu52XIZhUFhY6Pb2dkVFRU5/+qtAyROUqz8KlDxBufqjQMkTTp6rYRiYTCaX9ulVN0v85ZdfmDx5MoMGDeL888+nuLiYkJAQp3Xsr0tLSykqKqq0HCA0NJSSkhK347BaraSkpLi9/bFSU1NrbF/eLFDyBOXqjwIlT1Cu/ihQ8oQT51pVTXAiXlMErVq1igkTJtCtWzdmzpwJVBQzpaWlTuvZX4eHhxMWFlZpOVRcMRYeHu52LBaLhTZt2ri9vV1RURGpqakkJSWdUjzeLlDyBOXqjwIlT1Cu/ihQ8oST57p9+3aX9+kVRdDSpUt55JFHuPjii3n88ccdlVzjxo05ePCg07oHDx4kIiKC6OhoEhMTycnJobS01Kn6O3jwIAkJCW7HYzKZavT24+Hh4X5/O3MInDxBufqjQMkTlKs/CpQ84fi5ujoUBl5wifyyZct46KGHuOaaa3j66aedipkePXqwdu1ap/V//vlnunXrRlBQEN27d6e8vNwxQRpg165dZGRk0LNnzzrLQURERHyPR4ugXbt28eijj3LhhRcyatQoDh06RGZmJpmZmRw5coQRI0bw+++/M3PmTHbs2MHLL7/Mp59+ysiRIwFISEjgn//8J/fffz9r1qzh999/Z/z48fTq1YszzzzTk6mJiIiIl/PocNhnn32G1Wrliy++4IsvvnBaNmTIEGbMmMFzzz3Hk08+yeLFi2natClPPvmk02XzDz30EI8++ihjxowBoF+/ftx///11moeIiIj4Ho8WQaNHj2b06NEnXKdfv37069fvuMsjIiJ4+OGHefjhh2s6PBEREfFjXjExWqpn5baVpOf/ff+jxKhEBp8+2IMRiYiI+C4VQT4kPT+dtNw0T4chIiLiFzx+dZiIiIiIJ6gIEhERkYCkIkhEREQCkoogERERCUgqgkRERCQgqQgSERGRgKQiSERERAKSiiAREREJSCqCREREJCCpCBIREZGApCJIREREApKKIBEREQlIKoJEREQkIKkIEhERkYCkIkhEREQCkoogERERCUgqgkRERCQgqQgSERGRgKQiSERERAKSiiAREREJSCqCREREJCCpCBIREZGApCJIREREApKKIBEREQlIKoJEREQkIKkIEhERkYCkIkhEREQCkoogERERCUgqgkRERCQgqQgSERGRgKQiyIeZTWZPhyAiIuKzgj0dwNEWLlzI999/z6uvvgrAiBEjWLt2bZXrPv7441x22WXYbDa6du1KSUmJ0/IxY8Zw++2313rMntQwsiErt60kPT/d0ZYYlcjg0wd7MCoRERHf4DVF0Guvvcbs2bPp0aOHo23u3LlYrVbHa8MwGDduHLm5uVx44YUApKamUlJSwgcffEBcXJxj3YiIiLoLvhYcW9x0iO9Q5Xrp+emk5abVVVgiIiJ+w+NFUEZGBlOnTmXNmjUkJSU5Latfv77T66VLl/L777/zwQcfEBkZCcCWLVuIioqiXbt2dRRx3Ti2uEmISvBgNCIiIv7H43OC/vrrLywWCx9++CFdunQ57npZWVnMnj2bW265hVatWjnat2zZQuvWresiVBEREfEjHu8JGjBgAAMGDDjpei+88AJhYWHceOONTu1bt26lrKyMG2+8kc2bN5OQkMB1113HpZde6nZMhmFQWFjo9vZ2RUVFTn9WV1BQEGW2MqehQJvNhs1mO2lbma2M4uJiysvLTzH66nM3T1+kXP1PoOQJytUfBUqecPJcDcPAZDK5tE+PF0HVkZ+fz1tvvcWYMWMIDQ11WrZt2zbKy8sZO3YsiYmJfPPNN0yePBmr1crll1/u1vGsVispKSk1ETpQMW/JFVFRUeTm5JKZmeloK4gtID8//6RtsaZY0tLSyM/PP+W4XeVqnr5MufqfQMkTlKs/CpQ84cS5hoSEuLQvnyiCVq1aRWlpKcOGDau07OOPP8ZmsznmCLVr1479+/fz0ksvuV0EWSwW2rRpc0oxQ0W1mpqaSlJSEuHh4dXeLigoiJgjMcQb8Y62yKhIoogiPv7vtp2FO/ki9Qs6x3cmKiQKgJj6MbRo0aLOe4LcydMXKVf/Eyh5gnL1R4GSJ5w81+3bt7u8T58pgs477zzq1atXaVlYWFiltuTkZD788EO3j2cymWr06rLw8HCX9xdsDsZisThem81mzGazo63cKGf2mtlkFmay6dAmrutyHRGWCILNwVW+J3XBnTx9lXL1P4GSJyhXfxQoecLxc3V1KAy8YGJ0daxfv54+ffpUas/Ly6NXr14sX77cqf2PP/7g9NNPr6vwPGJT5iYyCyuGwQ4WHOTV31+luKzYw1GJiIj4Dq/vCTpw4ADZ2dlVXgJfr149zjrrLGbNmkVcXBwtWrTg888/58MPP2ThwoUeiLZuGIbBT3t/AuCcZufwa/qvpOens3rXajo0rPp+QiIiIuLM64sg+6TfY+8ZZPfoo48yd+5cpk6dyuHDh2ndujVz5syhb9++dRhl3dqdu5v9R/YTYg7hPx3+Q7N6zXjjrzfYcmgLcRFxuou0iIhINXhVETRjxoxKbZ07d2bLli3H3SYqKorJkyczefLk2gzNq/y490cABrYcSL3QerSKbUVwUDBHSo+QlptGeHC47iItIiJyEj4xJ0j+ZrVZ2XZ4GwD/bvtvACxmC0n1kwBYv3+9p0ITERHxKSqCfMzhosMYGIQHh9OsXjNHe5sGFZf0qwgSERGpHhVBPsZ+RVjDiIZOlwOe3qDiarhNmZsosvr/nUNFREROlYogH3Oo4BBQUQQdrUF4AxqEN8Bm2Nh0aJMnQhMREfEpKoJ8zKHCiiIoPiK+0jL7kNgfB/+o05hERER8kYogH3P0cNix2sRWFEGbMtUTJCIicjIqgnyIrdzG4aLDAMRHVu4JahZTMVH6UOEhzQsSERE5CRVBPiSzMJNyoxxLkIWY0JhKy8OCw2gU2QiAjIKMug5PRETEp6gI8iEHjhwAIC4i7rgPimsV2wrA6Y7RIiIiUpmKIB+yP38/UPWkaLuW9VsCkJGvniAREZETURHkQ+w9QVVNirZz9AQVqCdIRETkRFQE+ZAD+dUvgg4WHMRWbquTuERERHyRiiAfYRiGowg60XBYQmQC4cHhlBvljnsKiYiISGUqgnzE4aLDFJcVY8JEg/AGx13PZDI5nimmydEiIiLHpyLIR+zL2wdUPB7DHGQ+4br2+wVpXpCIiMjxqQjyEfabJNYLrXfSde09QbpCTERE5PhUBPmI7OJsAKJCok66bvOY5kDFcJhhGLUal4iIiK9SEeQjsosqiqDIkMiTrnta9GmYMFFUVsSR0iO1HZqIiIhPUhHkI1zpCbKYLY7J07pCTEREpGoqgnyEvScoOiS6WuvHhccBf88lEhEREWcqgnxETnEOUL2eIMDRE3S4UEWQiIhIVVQE+QhXhsOg4iGrAFlFWbUWk4iIiC9TEeQDbOU28kryADd6gjQcJiIiUiUVQT6gwFoAgNlkJjw4vFrb2OcE5RTnUFZeVmuxiYiI+CoVQT4gvzQfqLhRoslkqtY29ULrERwUTLlRrnlBIiIiVVAR5AOOLoKqy2T6+xljGQW6c7SIiMixVAT5AHsRFBMW49J29iExPUhVRESkMhVBPsBRBIW6VgSpJ0hEROT4VAT5AHeLIPtl8nqQqoiISGUqgnzAqQ6HqSdIRESkMhVBPsDtnqDwv2+YWFxWXONxiYiI+DIVQT7AnavDACIsEYSaQzEw2JG1ozZCExER8VkqgrycYRiOIqh+WH2XtjWZTI55QVsPb63p0ERERHyaVxVBCxcuZMSIEU5t999/P23btnX6GTBggGN5eXk5c+bMoW/fvpx55pncdNNN7Nmzp65DrzWltlKs5VbA9Z4ggAZhFVeIbc/aXqNxiYiI+DqvKYJee+01Zs+eXal9y5YtjB49mu+//97x88477ziWP/fccyxbtoyHHnqIN954g/LyckaOHElpaWkdRl977L1A4cHhhAWHuby9vfcoNSe1BqMSERHxfR4vgjIyMhg9ejQzZ84kKSnJaZlhGGzfvp2OHTsSHx/v+GnQoKJ3o7S0lJdffpmxY8dy/vnn065dO2bNmkV6ejqff/65B7KpefYiKDYs1q3t64fXByA1N7WGIhIREfEPHi+C/vrrLywWCx9++CFdunRxWrZ7924KCwtp1apVldtu3ryZgoIC+vTp42irV68eHTp0YN26dbUad13Jt/5/ERTuZhEUWh9QT5CIiMixgj0dwIABA5zm+Bxt69aKybyvvvoq3377LUFBQfTr149x48YRHR1NenrF4yAaN27stF2jRo0cy9xhGAaFhYVub29XVFTk9Gd1BQUFUWYrw2q1kluUC1RcHm+z2bBarY71bDbbSduigqOAiiKooKCg2g9gdYW7efoi5ep/AiVPUK7+KFDyhJPnahiGy7/jPF4EncjWrVsJCgqiUaNGLFiwgN27d/PEE0+wbds2Fi9e7HgjQkJCnLYLDQ0lNzfX7eNarVZSUlJOKfajpaamurR+VFQUuTm5ZGZmkpmTWdFmjiI/P5/MzEzHegWxBSdts5XbMGGi0FrIj7/9SIPQBqee0HG4mqcvU67+J1DyBOXqjwIlTzhxrsfWAyfj1UXQLbfcwtVXX01sbMVQUHJyMvHx8fz3v//ljz/+ICysYqJwaWmp4+8AJSUlhIeHu31ci8VCmzZtTi14KqrV1NRUkpKSXIonKCiImCMxxBvxmPIqqtoGUQ2IiooiPj7esV5kVCRRnLwtZl8MOcU5hDQKoX2T9qec17HczdMXKVf/Eyh5gnL1R4GSJ5w81+3bXb8K2quLoKCgIEcBZHf66acDkJ6e7hgGO3jwIM2bN3esc/DgQdq2bev2cU0mExEREW5vf6zw8HCX9xdsDsZisVBaXnGVW73QepjNZiwWi2Mds9lcrbb4iHhyinNIL06v0byO5U6evkq5+p9AyROUqz8KlDzh+Lm6M93D4xOjT2TixIlcf/31Tm1//PEHAG3atKFdu3ZERUWxZs0ax/K8vDw2bdpEz5496zLUWlNUVjHkFx0a7fY+GkY0BDQ5WkRE5GheXQRddNFF/PTTT8ybN4/du3fzzTffcO+993LJJZfQunVrQkJCGD58ODNnzmT16tVs3ryZcePGkZiYyKBBgzwdfo0oslYUQVEhUW7vw14E7crZVSMxiYiI+AOvHg4bOHAgs2fP5vnnn+eFF14gOjqaf/3rX9x5552OdcaOHUtZWRn3338/xcXF9OzZk5deeslpOMiX2R98WhNFkHqCRERE/uZVRdCMGTMqtQ0ePJjBgwcfdxuz2czdd9/N3XffXZuheYx9OOxUiqCEiARARZCIiMjRvKoIEmeGYTh6gqJDoim1ufcokNMbVkwm35G9g5d+eYkgUxCJUYkMPv34xaWIiIi/UxHkxewFEFT0BGUVZbm1n4YRDTFhoqy8jE2Zm05pkrWIiIi/8OqJ0YHOPhRmCbJgMbs/xyk4KJgG4RU3ScwpzqmJ0ERERHyeiiAvZu8JCrec+g2w7JOjVQSJiIhUUBHkxeyXx4cFh51kzZNTESQiIuJMRZAXsw+HhQfXXE9QdnH2Ke9LRETEH6gI8mI1WgSFVxRBucXuP1hWRETEn6gI8mLF1oo5QWGWUx8OaxBRMTE6t0RFkIiICKgI8mo12RMUFx4HVBRBhmGc8v5ERER8nYogL1aTRVBsWCwAZeVljv2KiIgEMhVBXsx+iXxNDIdZzBbHozc0L0hERERFkFezXyJfEz1BADGhMYDmBYmIiICKIK/muFliTRVBYRVFkO4VJCIioiLIqznmBNXAHaNBPUEiIiJHUxHkxWryjtHwdxGUV5xXI/sTERHxZSqCvFRZeRnWcitQ88Nh6gkSERFREeS1CkoLHH+v6Z4gFUEiIiIqgrxWobUQqCiATCZTjezT3hOUX5qP1WatkX2KiIj4KhVBXqrAWtETVFNDYfZ9BQcFA3qQqoiIiIogL2UvgmpqKAzAZDJRP6w+AIeLDtfYfkVERHyRiiAvZZ8TVFOXx9vZ5wVlFWbV6H5FRER8jYogL1Ubw2EA9ULrAeoJEhERURHkpew9QTU5HAZ/T45WESQiIoFORZCXsl8dVtM9QY7hsCINh4mISGBTEeSlHMNhtTQnSD1BIiIS6FQEeanauDoM/h4OyyrKwjCMGt23iIiIL1ER5KUcV4fV0sToUlupeoNERCSgqQjyUvYnyNd0T1BwUDBRIVEA7M7dXaP7FhER8SUqgryU/QnyocGhNb5v+7wgFUEiIhLIVAR5qeKyYgBCzSqCREREaoOKIC9UbpT/XQTVRk9QmIogERERFUFeKL80H4OKK7fUEyQiIlI7VAR5obySPACCTEGOp77XJHtPUFpuWo3vW0RExFd4VRG0cOFCRowY4dT25ZdfMmzYMLp27cqAAQN4/PHHKS4udizfsGEDbdu2rfSzZs2aug6/xtiLoFBzKCaTqcb3r54gERERqPluBje99tprzJ49mx49ejja1q9fz5gxYxg7diwXX3wxaWlpTJkyhZycHB577DEAtmzZQvPmzVm2bJnT/mJiYuo0/prkKIJqYT4Q/N0TlJ6fTklZSa0dR0RExJt5vCcoIyOD0aNHM3PmTJKSkpyWvfHGG/Tu3ZvRo0eTlJTEeeedx7hx4/joo48oLS0FYOvWrbRp04b4+Hinn5CQEA9kUzNyi3OB2pkPBBU3YAwxV7w/e/P21soxREREvJ3Hi6C//voLi8XChx9+SJcuXZyW/e9//2PSpElObUFBQVitVvLz84GKnqDWrVvXWbx1wd4TVNM3SrQzmUw0CG8AaEhMREQCl8eHwwYMGMCAAQOqXNahQwen11arlUWLFtGxY0caNKj4Jb5t2zZiY2MZOnQoGRkZJCcnM27cODp37ux2TIZhUFhY6Pb2dkVFRU5/Vtfh/IrHWViCLFitVgBsNhs2m83x+lTbYsNiSc9PZ1vmNnon9HY9uaO4m6cvUq7+J1DyBOXqjwIlTzh5roZhuDyP1uNFUHWVlZUxceJEtm3bxmuvvQbAgQMHOHLkCIWFhdx///2YzWaWLl3K8OHDWb58OW3atHHrWFarlZSUlBqLPTU11aX10zIqrtoyygwyMzMBKIgtID8/3/H6VNuig6IB+HXHr3Q3d3c5p6q4mqcvU67+J1DyBOXqjwIlTzhxrq5OhfGJIig/P58777yTtWvXMm/ePEcvT+PGjVm3bh3h4eFYLBYAOnXqxKZNm3j11VeZNm2aW8ezWCxuF1BHKyoqIjU1laSkJMLDq/8gVHO2GYB6EfWIj48HIDIqkiiiHK9PtS3RlAgHoTismPbt27udI7ifpy9Srv4nUPIE5eqPAiVPOHmu27dvd3mfXl8EHTx4kJtuuol9+/bx0ksv0bNnT6fl9erVc3odFBRE69atycjIcPuYJpOJiIgIt7c/Vnh4uEv7K7RVDMVFhEQ4ijuz2YzZbHa8PtW2+IiKgmh/wf4ay9XVPH2ZcvU/gZInKFd/FCh5wvFzdeeWMh6fGH0iubm5XHfddWRlZfHaa69VKoC+/fZbunbtyp49exxtZWVlbN68uUZ6cjzl6PsE1ZYGERVzqtJydMNEEREJTF7dE/TYY4+xZ88eXnzxRRo0aOA0p6VBgwZ069aN2NhYJk2axL333ovFYuH5558nJyeH66+/3nOBn6Lavk8QQFx4HFBxdZg7k8lERER8ndcWQTabjRUrVmC1WrnuuusqLV+9ejVNmzZl0aJFzJw5kxtvvJGSkhK6d+/O0qVLadiwoQeirhm5JbV7nyCouDoMoKisiMNFh2kY4bvvl4iIiDu8qgiaMWOG4+9ms5nff//9pNs0b96cOXPm1GZYda4ueoIsZguJUYmk56ezO3e3iiAREQk4Xj0nKFDVxZwggOYxzQHdMFFERAKTiiAvVBc9QaAiSEREApuKIC9UZz1B9VQEiYhI4FIR5GXKjXKOlBwBau/ZYXbqCRIRkUCmIsjL5JfmY2AAGg4TERGpTW5fHVZSUsKWLVsoLS3FMCp+aZeXl1NUVMT69euZMGFCjQUZSOxDYWaTGbPJXKvHalG/BaAiSEREApNbRdCaNWu44447yM3NrXJ5ZGSkiiA32YugcEt4rd/A0N4TdCD/ACVlJbXe8yQiIuJN3BoOmzVrFrGxscyZM4cLLriAQYMGsWDBAq6++mpMJhMvvPBCTccZMHKLKwrL8ODafxBeXHic4zh78/bW+vFERES8iVtF0JYtWxgzZgwXXngh/fv358CBA5x33nk88MADXH755cyfP7+m4wwYjp6gOiiCTCaT5gWJiEjAcqsIKi8vJyEhAYAWLVqwbds2x7KLLrqITZs21Ux0AcheBIVZavfKMDsVQSIiEqjcKoKaN2/Oli1bAGjZsiVFRUXs3LkTqHiKe0FBQc1FGGDqsicIVASJiEjgcqsI+te//sXMmTNZunQpDRo0oGPHjjz00EN8+eWXPPvss7Rp06am4wwY9oenqggSERGpXW4VQSNHjuTKK6/kt99+A2Dq1KmkpKRw6623snPnTiZOnFijQQaSo68OqwuOIihPRZCIiAQWty6RDwoKYtKkSY7XnTp1YtWqVezcuZNWrVoRFRVVYwEGGsecoFq+W7SdeoJERCRQudUT1L59e37//XentqioKDp37qwC6BR5ck6Q/aaXIiIigcCtIki/LGuPY05QHQ2HNavXDIBCayFZRVl1ckwRERFv4PZjMzZt2kRJSclxl/fs2dPdXQe0uu4JCg0OJTEqkfT8dNJy04iLiKuT44qIiHia20XQtGnTqmw3DAOTyURKSorbQQWyui6CoGJILD0/nd25u+nWuFudHVdERMST3C6CHnjgAV0KXwvq+maJUFEErd23lrSctDo7poiIiKe5XQR17NiRzp0712Qswt/PDosIjqjV4xz9hPoWMRVPk0/LVREkIiKBw+0iSGrH0ZfIF9uKa+04DSMbsnLbStLz08nIzwDgp70/1drxREREvI1bRdDmzZsB2LFjB2vXruXIkSPExsbSrVs3WrduXaMBBpJyo5wjpUeAiqvDarMIAhyToQ0qrvbbm6snyYuISOBwuydoypQpvP32206Xy5tMJoYMGcKjjz5aI8EFmvzSfMffw4PDySa7To4bGxYLQGZhpmNiu4iIiL9zqwh64YUXePfddxk7diz//ve/iY+P5+DBg3zwwQfMnz+f5ORkrr/++hoO1f/Z5wOFmEOwmC11dtyYsBgASmwlHCo8RHxkfJ0dW0RExFPcKoLeeecdRo4cyS233OJoa9q0KbfddhtWq5W33npLRZAb7POB6oXWq9PjBgcFUy+0HnkleezM3qkiSEREAoJbd4w+cOAAZ511VpXLevfuzd69mlviDk8VQfD3kNjO7J11fmwRERFPcKsIOu2009iyZUuVyzZv3kyDBg1OKahApSJIRESk7rhVBF1yySXMnTuXlStXOiZGG4bBihUrmDdvHv/4xz9qNMhAYX9uWExoTJ0fu35YfQB25eyq82OLiIh4gltzgm666SbWr1/PuHHjuPvuu4mNjSU7OxubzUavXr244447ajrOgODRnqBw9QSJiEhgcasICgkJ4ZVXXuGbb75h3bp15ObmEhMTQ8+ePTnvvPNqOsaAoeEwERGRuuNWEXTttdcydepUzjvvPBU9NcgbeoL25O3BarPW6SX6IiIinuDWnKC1a9dSUFBQ07EEPPt9gjwxJyjSEkmIOYRyo5zdubvr/PgiIiJ1za0iSGqHJ3uCTCYTDSMaAhoSExGRwOD2YzOuuOKK4y4zmUxs2rTJ5X0uXLiQ77//nldffdXRlpKSwiOPPMKff/5JgwYNuP7667n22msdy8vLy5k3bx5vv/02R44coWfPnkyZMoVmzZq5fHxPyyv1XBEEEB8Rz/4j+1UEiYhIQHC7CBo2bBiJiYk1Fshrr73G7Nmz6dGjh6MtOzubG264gQEDBjBt2jQ2btzItGnTiIyMZNiwYQA899xzLFu2jBkzZpCYmMiTTz7JyJEj+eijjwgJCamx+OrC0T1BZeVldX78+IiKO0WrCBIRkUDgdhH03//+l86dO59yABkZGUydOpU1a9aQlJTktOytt97CYrEwffp0goODad26NWlpaTz//PMMGzaM0tJSXn75ZSZMmMD5558PwKxZs+jbty+ff/45l1xyySnHV5ccc4LCYjhceLjOj28fDtO9gkREJBB4fE7QX3/9hcVi4cMPP6RLly5Oy9avX0+vXr0IDv67VjvrrLNITU3l0KFDbN68mYKCAvr06eNYXq9ePTp06MC6devqLIea4sk5QQCNIhsBsC1rm0eOLyIiUpfc6glasmQJrVu3Jisry/GIjLy8PA4ePEibNm1c2teAAQMYMGBAlcvS09NJTk52amvUqOIX9YEDB0hPTwegcePGldaxL3OHYRgUFha6vb1dUVGR058nY+8JCiWUMlsZVqvVscxms2Gz2Wq1rWF4RU/QtsPbKCgowGQy1Uqevky5+p9AyROUqz8KlDzh5LkahlHt31t2bhVB7du354477mDfvn2sXLkSgI0bN3LzzTczaNAgnnjiCcLCwtzZtZPi4uJK83pCQ0MBKCkpcbwRVa2Tm5vr9nGtVispKSlub3+s1NTUaq1nL4KOHDpCbk4umZmZjmUFsQXk5+fXalurhq0wm8wUWAv4buN3xIe59jT56ubpD5Sr/wmUPEG5+qNAyRNOnKurc4HdKoJmzpxJSkoK9913n6PtrLPOYu7cuUybNo25c+dy9913u7NrJ2FhYZSWljq1lZSUABAREeEotEpLS52KrpKSEsLDw90+rsVicblHqypFRUWkpqaSlJR00nhs5TYKPq6491L7Vu1J25lGvPF3ERIZFUkUUcTH115bXGwcLWJasDNnJ8RB++btazxPX6dc/U+g5AnK1R8FSp5w8ly3b9/u8j7dKoK+/PJLJk2a5PSg1JCQEC688EKOHDlSY0VQYmIiBw8edGqzv05ISKCsrMzR1rx5c6d12rZt6/ZxTSYTERERbm9/rPDw8JPuz94LBNCoXiOCzcFYLH/ftdlsNmM2m2u1LdgcTNuGbdmZs5PdBbtdfg+qk6e/UK7+J1DyBOXqjwIlTzh+rq4OhYGbE6Pz8/OJian6rsbx8fFkZWW5s9tKevbsyYYNG7DZbI62n3/+mZYtWxIXF0e7du2IiopizZo1juV5eXls2rSJnj171kgMdcU+KTrEHEJocKjH4kiOq5iDte2wJkeLiIh/c6sIateuHe+++26Vy95///1T6oU52rBhw8jPz+e+++5j+/btLF++nEWLFjFq1Cigovdp+PDhzJw5k9WrV7N582bGjRtHYmIigwYNqpEY6oqnrwyzsxdBW7O2ejQOERGR2ubWcNjo0aMZPXo0Q4cO5cILLyQuLo6srCy++uor/vjjD+bPn18jwcXFxfHiiy/yyCOPMGTIEOLj45k4cSJDhgxxrDN27FjKysq4//77KS4upmfPnrz00ktOwzy+ILekYjjMa4qgwyqCRETEv7lVBJ133nk899xzzJ07lzlz5jguS2vfvj3PPfec20+WnzFjRqW2zp078+abbx53G7PZzN13310jc5A8yd4T5ImHpx7NXgTtyNpBWXkZwUFu309TRETEq7n9G65///7079+fkpIScnJyiI6ODphJWbXBW4bDmtZrSlhwGMVlxaTlpNG6QWuPxiMiIlJbTumO0YcPHyYrKwubzUZOTg579+5l27ZtvP766zUVX8DwliIoyBTE6Q1OBzQkJiIi/s2tnqDNmzczYcIEduzYUeVyk8nEVVdddUqBBRr7JfKeLoKgYkjsj4N/sPXwVgafPtjT4YiIiNQKt4qgJ554gtzcXCZNmsRXX31FSEgI/fv359tvv+Xbb79lyZIlNR2n3/OWOUGAeoJERCQguDUc9ttvv3HHHXdw/fXX849//IOioiKuvvpqFixYwAUXXMCrr75a03H6PW8ZDgNdJi8iIoHBrSKotLSUpKQkAJKSkti8ebNj2dChQ9m4cWNNxBZQvLIIUk+QiIj4MbeKoCZNmrBnzx6gogjKz89n7969QMUNDE/l4aWByhvuE2Q2mYG/i6DdubsptBZ6LB4REZHa5FYRNGjQIJ566ik+++wzEhISaNWqFbNnz2bLli28/PLLNGvWrKbj9HuOOUFhnpsT1DCyISu3reTjrR8TFRIFwIu/vOixeERERGqTW0XQmDFj6NatG++88w4AkydP5osvvuCyyy7j559/5vbbb6/RIAOBtwyHpeenk5abRlx4HAC/Z/zu0XhERERqi1tXh4WGhjJnzhysVisAffv25eOPP+bPP/+kY8eO6glyg7cUQXbxkfGk5aax/8h+T4ciIiJSK6pdBF177bXV3qnJZGLx4sVuBRSovK0IahTRCIB9R/Z5OBIREZHaUe3hMMMwqvzZtGkTe/bscWorLy+vzZj9kn1itDfcJwgqeoIA9QSJiIjfqnZP0PHu/fPoo4+yZ8+eGntyfCCyldvIL80HvKgnKLKiJ+hQ4SHyS/MdE6VFRET8xSk9Owxg4MCBrFu3DsMwaiKegGQvgMB7iqAISwSRlkgAUjJTPByNiIhIzTvlIigpKYmCggIyMzNrIp6AZJ8PFGIOITQ41MPR/M0+JPZX5l8ejkRERKTmnXIRFBERgWEY5OXl1UQ8Acnb5gPZxUf8fxF0UEWQiIj4n1Mugr755huCg4NJTEysiXgCkrddGWZnnxekniAREfFH1Z4YvW7dOqfXBQUF/PHHHyxevJiLLrqIqChNnHWXtxZB9p6gTZmbPByJiIhIzat2ETRixAhMJpPjtWEYmEwm+vfvz/Tp02sluEDhrUWQvScoLTdNV4iJiIjfqXYRtGTJEsffTSYTERERNGvWjHr1vOsXty/KLf7/OUEefG5YVcIt4cSExpBbkstfB/+id9Peng5JRESkxlS7COrVq1dtxhHQvLUnCKBpvabkZubye8bvKoJERMSvnPLEaDl1jiIoxPuKoGb1Kp4DtzF9o2cDERERqWEqgryAN/cENY9pDsDGjI2eDURERKSGqQjyAo77BHnZnCCAZjEVPUG/pf+Grdzm4WhERERqjoogL+DNPUGNoxoTHhxOgbWAHdk7PB2OiIhIjVER5AV2Zu8EYOOBjbzy6yus2bvGwxH9LcgURKeEToDmBYmIiH9REeQF7MNhR0qPkJabxuGiwx6OyNmZCWcCKoJERMS/qAjyAkXWIgCvenjq0c5MPBOAX9N/9WwgIiIiNUhFkBcoKvv/Isjs3UWQeoJERMSfqAjyAt7cE2Q2memc0BkTJtLz00nPT/d0SCIiIjVCRZCH2cptlNhKAO/sCWoY2ZBv074lISoBgBc3vOjhiERERGqGiiAPO1J6xPF3b+wJAkjPTycuPA7QTRNFRMR/qAjyMPs9gswmM8FB1X6UW51LjEoEIDUn1bOBiIiI1BDv/a37/9asWcO1115b5bKmTZuyevVq5s+fz+zZsyst37JlSy1Hd+rsRZC39gLZnRZ9GqAiSERE/IfXF0Fdu3bl+++/d2rbuHEjt99+O7feeitQUexceuml3H333Z4I8ZQ4iiAvnA90tMbRjQE4XHSYgwUHaRTZyMMRiYiInBqvHw4LCQkhPj7e8RMZGcljjz3GkCFDGDZsGABbt26lQ4cOTuvFx8d7OPLqyS2uuFFiWHCYhyM5sbDgMBpGNARg3b51Ho5GRETk1Hl9EXSsBQsWUFRUxKRJkwAoLS0lNTWVVq1aeTgy9/hKTxBAk+gmAKzbryJIRER8n9cPhx0tKyuLRYsWcdddd1G/fn0Atm/fjs1m47PPPuORRx6hpKSEnj17cvfdd9OokXtDNoZhUFhYeMrxFhUVOf1ZlcP5FY/IsARZsFqtANhsNmw2m+O1t7QlRFRcJr9mzxqn96c6efoL5ep/AiVPUK7+KFDyhJPnahgGJpPJpX36VBG0bNkyoqOjueKKKxxtW7duBSA8PJxnnnmGw4cP8/TTT3Pttdfy/vvvExbm+jCT1WolJSWlxuJOTU097rK0jDQAjDKDzMxMAApiC8jPz3e89pa2cGs4AGv3rWXTpk2VvmwnytPfKFf/Eyh5gnL1R4GSJ5w415CQEJf25VNF0Pvvv89ll13mVNhcdtll9OvXjwYNGjjaTj/9dPr168eXX37JP/7xD5ePY7FYaNOmzSnHW1RURGpqKklJSYSHh1e5jjnLDEBMZIxjHlNkVCRRRDnNa/KGttjyWD7e9zFZJVlEnhZJi5gW1c7TXyhX/xMoeYJy9UeBkiecPNft27e7vE+fKYI2b97Mnj17+Ne//lVp2dEFEECjRo2oX78+6enuPeLBZDIRERHh1rZVCQ8PP+7+Cm0Vw0rhlnAsFgsAZrMZs9nseO0tbRYsNKvXjLTcNP7M+pP2jdtXO09/o1z9T6DkCcrVHwVKnnD8XF0dCgMfmhi9fv164uLiaNeunVP7rFmzuOiiizAMw9G2d+9esrOza6Q3p7b5yn2C7FrWbwlocrSIiPg+nymCNm3aRNu2bSu1X3jhhezbt48HH3yQXbt2sW7dOm6//Xa6detG3759PRCpa3zp6jCApPpJgIogERHxfT5TBGVmZjquCDtax44deeGFF9iyZQtDhw5lzJgxtG/fngULFrjVNVbXcksq7hPkKz1BrWIrbkWwbt86ysrLPByNiIiI+3xmTtALL7xw3GV9+vShT58+dRhNzfG1nqAm0U2oF1qPvJI8/sj4g66Nu3o6JBEREbf4TE+Qv/K1OUFBpiDOanoWAD/u+dHD0YiIiLhPRZCH+VpPEMDZTc8G4Ke9P3k4EhEREfepCPIwX3l22NH6NKsYelRPkIiI+DIVQR5kK7dRYC0AfGc4DKD3ab0xYWJXzi7S8927F5OIiIinqQjyoCOlRxx/DzG7dqtvT4oJi+GMRmcA8NMeDYmJiIhvUhHkQfb5QMFBwQQH+cyFesDf84I0JCYiIr5KRZAH2ecDRQT73q3O7fOCNDlaRER8lYogD7L3BIVZfGdStN3ZzSp6gtbvX09JWYmHoxEREXGdiiAPshdB4cG+9+Tf0xucTnxEPCW2En5J/8XT4YiIiLhMRZAH+XIRZDKZ6Nui4tls3+/93sPRiIiIuE5FkAfZnxsWbvG9IgjgvBbnAfD9HhVBIiLie1QEeZBjTpAP3SjxaP1a9APg530/62GqIiLic1QEeZAvD4cBdGrUifph9cm35rMlb4unwxEREXGJiiAPchRBPjocZg4yc27zcwH49fCvHo5GRETENSqCPCinOAfw3Z4g+Hte0IasDR6ORERExDUqgjwouzgbgAiL790s0c4+L2hj1kbKjXIPRyMiIlJ9KoI8yN4T5MtFULfG3YiyRHHEeoQ/M//0dDgiIiLVpiLIg7KLKnqCIi2RHo7EfcFBwZx12lkA/LD3Bw9HIyIiUn0qgjzI0RMU4js9QWaTuVJb3+b/f9NE3S9IRER8iG89utzPOOYEBUdQbCv2cDTV0zCyISu3rSQ9P93RZr/P0fd7v8cwDEwmk6fCExERqTYVQR5SVl5Gfmk+AJEhkRQX+UYRBJCen05abprjdeOIxoSaQzlUeIjNhzbTPr69B6MTERGpHg2HeYh9KAx8+xJ5gCb1mtAmtg0AM76fwSu/vsLKbSs9HJWIiMiJqQjyEPuk6OiQaMxBlefZ+JqmkU0B+CX9F9Jy05yGy0RERLyRiiAPsfcE1Q+r79E4akrrmNYApOWkYRiGh6MRERE5ORVBHmKfFB0bHuvhSGpGi3otCDIFcaT0iCM3ERERb6YiyEP8rScoxBxCk6gmAE6TpkVERLyViiAPsc8Jig3zj54ggOb1mgMVQ2IiIiLeTkWQh9h7gvxlOAygRUwLAHbl7NK8IBER8XoqgjzEPm+mfmh9zwZSg5pGNyXIFEReSR4HCw56OhwREZETUhHkIY7hMD/qCbKYLTSr1wyAzYc3ezgaERGRE1MR5CE5JTmA/0yMtkuqnwRAyqEUzwYiIiJyEiqCPMQfJ0YDtKzfEoDNmZs1L0hERLyaiiAP8bdL5O1Oq3cawUHB5JXmsSlzk6fDEREROS6fKIIyMjJo27ZtpZ/ly5cDkJKSwvDhwznzzDMZMGAAS5Ys8XDEJ+dvN0u0Cw4KpnlMxaXyX+760sPRiIiIHJ9PPEV+8+bNhIaGsmrVKkwmk6M9Ojqa7OxsbrjhBgYMGMC0adPYuHEj06ZNIzIykmHDhnkw6hNzXCLvZ8NhUDEktjN7J1+lfsXtvW/3dDgiIiJV8okiaOvWrSQlJdGoUaNKyxYvXozFYmH69OkEBwfTunVr0tLSeP755722CDIMwzEnyN+Gw+DveUFfp36NrdzmFw+IFRER/+MTRdCWLVto3bp1lcvWr19Pr169CA7+O5WzzjqLhQsXcujQIRo2bOjy8QzDoLCw0O147YqKipz+tDtSegSbYQMg3BROma0Mq9XqWG6z2bDZbF7ZVtU65bZyAEdbw7CGhAWHkV2czc9pP9M1oWu13zNvd7zP1B8FSq6BkicoV38UKHnCyXM1DMNptKg6fKII2rp1K7GxsVxzzTXs2rWLFi1acMstt9CvXz/S09NJTk52Wt/eY3TgwAG3iiCr1UpKSs1d4p2amur0Or0oHYBgUzAH9x0kNyeXzMxMx/KC2ALy8/O9sq2qdYpiK76QOTk5jrZW0a3YlL2Jt9e9TVjrsOq9UT7k2M/UnwVKroGSJyhXfxQoecKJcw0JCXFpX15fBJWVlbFz507atGnDPffcQ1RUFJ988gk333wzr7zyCsXFxZWSDg0NBaCkpMStY1osFtq0aXPKsRcVFZGamkpSUhLh4eGO9rKDZUDFpOikpCRi8mOIN+IdyyOjIokiivh472urap3w8HDIh/r162OxWAA4I/gMNmVvIqU4hfbt27vx7nmn432m/ihQcg2UPEG5+qNAyRNOnuv27dtd3qfXF0HBwcGsWbMGs9lMWFhFj0LHjh3Ztm0bL730EmFhYZSWljptYy9+IiIi3DqmyWRye9uqhIeHO+2vxFQRX2x4LGFhYQSbgx3FA4DZbMZsNntlW1XrBJkrLjK0WCx/F0GNzuDtlLf5Ye8PWEItWMx/r+8Pjv1M/Vmg5BooeYJy9UeBkiccP1dXh8LARy6Rj4yMdBRAdqeffjoZGRkkJiZy8KDzc6rsrxMSEuosRlf4640Sj9a0XlPiwuMosBawfv96T4cjIiJSidcXQdu2baNbt26sWbPGqf3PP/+kTZs29OzZkw0bNmCz2RzLfv75Z1q2bElcXFxdh1st/nqjxKMFmYLo37I/oPsFiYiId/L6Iqh169a0atWK6dOns379enbs2MFjjz3Gxo0bueWWWxg2bBj5+fncd999bN++neXLl7No0SJGjRrl6dCPy19vlHisAUkDAPgyVUWQiIh4H6+fExQUFMSCBQt46qmnuPPOO8nLy6NDhw688sorjqvCXnzxRR555BGGDBlCfHw8EydOZMiQIR6O/PgCYTgMYEDLiiLoh90/UFxWTFiw/10lJiIivsvriyCAhg0b8thjjx13eefOnXnzzTfrMKJTEwjDYQDJcck0iW7C/iP7+WH3DwxsNdDTIYmIiDh4/XCYP3IMh/l5T5DJZOLCVhcC8MXOLzwcjYiIiDMVQR4QKD1BgIogERHxWiqCPCBQJkYDXNDqAgB+OfALmQWZJ1lbRESk7qgI8oBA6glKiEqgc0JnAFbvWu3haERERP6mIsgDDhUeAqBBeAMPR1I3BrUaBMAXOzQkJiIi3kNFUB0zDMNRBMVHxJ9kbf9wYeu/5wUZhuHhaERERCqoCKpjuSW5lJVXPEA1PjIwiqC+zfsSag5lT94ethze4ulwREREABVBdc4+OTgqJCpgbh4Ybgnn3ObnAvDZ9s88HI2IiEgFFUF1LLOwogjy96Ews8ns9Hpwm8EArNi+whPhiIiIVOITd4z2J/aeIH8fCmsY2ZCV21aSnp8OQElZCQBfp35Nfmk+USFRngxPREREPUF1LVB6ggDS89NJy00jLTeNElsJ8RHxlNpKWb1Tl8qLiIjnqQiqY4HSE3Qsk8nkuF/Qim0aEhMREc9TEVTHAqkn6FiOImj7Cl0qLyIiHqciqI4FchHULq4dEZYI9ubt5feM3z0djoiIBDgVQXUsUIfDACxmCwNbDgTgk22feDgaEREJdCqC6lgg9wQB/PP0fwLw/ub3PRuIiIgEPBVBdSyQe4IALmt3GSZMrNu/jrScNE+HIyIiAUxFUB0LtOeGHSshKoF+LfoBsDxluYejERGRQKYiqA4VlBZQVFYEBG5PEMDlHS4H4J2UdzwciYiIBDIVQXXIPh8oLDiMSEukh6PxnKHthwLw454f2Ze3z8PRiIhIoFIRVIcc84Ei4jGZTB6OxnOaRDfhnGbnABoSExERz1ERVIfsPUENIxp6OBLPsw+Jvb3pbQ9HIiIigUpFUB0K9CvDjjas/TAAvtv9Hak5qZ4NRkREApKKoDoU6PcIOlqzmGYMaDkAgMUbF3s4GhERCUQqgurQ0XOCBP535v8AWPTbIsqNcg9HIyIigUZFUB1y9ARpOAyAIe2HUC+0Hqk5qXyT+o2nwxERkQCjIqgOBfpwmNlkdnodYYngyjOuBOCVja94IiQREQlgwZ4OIJAE+sTohpENWbltJen56Y62dg3bAfDOpneYO3guMWExngpPREQCjHqC6lCg9wQBpOenk5ab5viJCY2hQ3wHisqK1BskIiJ1SkVQHXI8NyxAe4KqYjKZGNtrLABz1szBVm7zcEQiIhIoVATVkZKyEvJK8oDA7gmqyoguI4gLj2NXzi4+2PKBp8MREZEAoSKojuSW5AJgCbJQP6y+Z4PxMhGWCEb3GA3A0z897eFoREQkUKgIqiPxEfGM6j6Kh/o/FNDPDTue23rehiXIwg97fmDtvrWeDkdERAKATxRBOTk5TJkyhX79+tGtWzeuuuoq1q9f71h+ww030LZtW6efESNGeDDiykwmEwsuWcCkcyd5OhSvYr9svnF0Y67udDUAD337kCdDEhGRAOETl8iPHz+ezMxMnn76aeLi4nj11Ve58cYbee+992jVqhVbtmzhwQcf5IILLnBsY7FYPBixVNfRl823jWuLCRMfb/2YNXvX0Ltpb0+HJyIifszre4LS0tL44YcfePDBB+nRowctW7bkgQceoFGjRnz00UccPnyYw4cP06VLF+Lj4x0/9evX93ToUk32y+ZLbCV0SewCwANfPeDhqERExN95fU9QbGwszz//PJ06dXK0mUwmTCYTeXl5bNmyBZPJRMuWLWvsmIZhUFhYeMr7KSoqcvqzKkFBQZTZyrBarY42m82GzWbzyraq1im3VTz3qyb2f3aTs/k943e+2PkFn2/5nHObnXvc984TqvOZ+otAyTVQ8gTl6o8CJU84ea6GYbg859bri6B69epx3nnnObV99tlnpKWlce+997J161aio6OZPn06P/zwAxEREVx88cXceuuthISEuHVMq9VKSkpKTYQPQGpq6nGXRUVFkZuTS2ZmpqOtILaA/Px8r2yrap2i2IovZE5OTo0cs1dCL35O/5kJn07gpXNeIsjkfR2WJ/pM/U2g5BooeYJy9UeBkiecOFdXf+97fRF0rF9++YXJkyczaNAgzj//fO69915KSkro3LkzN9xwAykpKTzxxBPs37+fJ554wq1jWCwW2rRpc8qxFhUVkZqaSlJSEuHh4VWuExQURMyRGOKNv+8dFBkVSRRRxMd7X1tV64SHh0M+1K9f3zEX61SOObT5UP7M+pM/cv7gl/JfGNHReya5V+cz9ReBkmug5AnK1R8FSp5w8ly3b9/u8j59qghatWoVEyZMoFu3bsycOROA6dOnM2nSJGJiKp45lZycjMViYdy4cUycOJGGDRu6fByTyURERESNxR0eHn7C/QWbg50mcpvNZsxms1e2VbVOkLmip8ZisZxwveq2NYxsyJR+U5i4aiJTvp3CFZ2v8Lp7K53sM/UngZJroOQJytUfBUqecPxc3bn9jPeNMxzH0qVLuf322+nfvz8LFiwgNDQUgODgYEcBZHf66acDkJ6eXmk/4v3MJjN3nHUH7Rq242DBQaZ+NdXTIYmIiB/yiSJo2bJlPPTQQ1xzzTU8/fTTTmN+I0aMYPLkyU7r//HHH1gsFpKSkuo4UqkJDSMbsnrnav7Z5p8AzF07l6d+fMrDUYmIiL/x+iJo165dPProo1x44YWMGjWKQ4cOkZmZSWZmJkeOHOGiiy7igw8+4PXXX2fPnj2sWLGCJ554ghtvvJGoqChPhy9uSs9PJyo0ii4JXTAwePyHxzlScsTTYYmIiB/x+jlBn332GVarlS+++IIvvvjCadmQIUOYMWMGJpOJV199lUcffZT4+Hiuv/56br75Zg9FLDXp4jYXk5qTSmZhJuM+G8eL/37R0yGJiIif8PoiaPTo0YwePfqE61xzzTVcc801dRSR1KWw4DCGtBvC4t8W89KvL9GvRT+u7XKtp8MSERE/4PXDYSIt6rfgkuRLABj54Ui+S/vOwxGJiIg/UBEkPuHStpdyeYfLsZZbGfLmELYd3ubpkERExMepCBKfEGQKYvFli+nZpCeHiw5z3qLz2JS5ydNhiYiID/P6OUEidhGWCD6++mMuWHIBfxz8g/MWncfnwz+na+OuTuvZn0pvlxiVyODTB9d1uCIi4uXUEyQ+pVFkI7667it6NOnBocJD9H2lLx9s/sBpHftT6e0/RxdEIiIidiqCxOfERcSxasQqBrYcSIG1gCFvDuHyty7n5V9eZs3eNZ4OT0REfISKIPFJMWExrLxmJf2T+mNg8G7Kuzyz5hkO5B/wdGgiIuIjVASJz7KYLYzoPIJ/tPkHJkz8fvB3Jq+aTG5xrqdDExERH6AiSHyC2WQ+7rKep/VkeOfhhAWHsfnwZqZ/O50DR9QjJCIiJ6arw+rYsVcudYjv4MFofEfDyIYnfO9axbZiZNeRvL/lffbm7eWVja/wnw7/4fS40z0RroiI+AD1BNWxY69cOlx02NMh+YyTvXdxEXE8NegpOsZ3xFpu5c2/3mRn9k4PRSsiIt5ORZD4laiQKO7ofQft4tphM2y88ecbbM/a7umwRETEC6kIEr9jDjIzrMMwWse2xlpu5Zk1z6gQEhGRSlQEiV8KDgrmijOu4LTo0yiwFnDJskvILsr2dFgiIuJFVASJ37KYLVxxxhXEhsWy5fAW/vvOf7HarJ4OS0REvISKIPFr0aHR3NH7DiItkazauYo7Pr0DwzA8HZaIiHgBFUHi95rHNGfZsGWYMDF//XzmrZ3n6ZBERMQLqAiSgPDvtv/m8QseB+DOz+7kwy0fejgiERHxNBVBEjAmnD2BG7veSLlRzn/f/i+rd652eR9BQUFERUXVQnQiIlLXdMdoCRgmk4kFlyzgcNFh3t/8Ppe+cSmfDv+Uc5ufe8Ltjr5TdZmtjGhTNC2CWtRFyCIiUovUEyR+7+jnjgUHBfPGsDe4oNUFFFgLGLhkIIs3Lj7h9kffqTo1O5W92XtrO2QREakD6gkSv1fVc8du7XErkZZIPtjyAdd/cD0/7PmBhwc8TKPIRh6MVERE6pJ6giQgHPvcsZziHJZfsZwp/aYA8MIvL9B6TmvuW30fKZkpHo5WRETqgnqCJGAFmYKY1n8a5yedz8RVE1m/fz2Pfv8oj37/KI2jGtOpUScuan0RYZYwT4cqIiK1QEWQBLz+LfuzduRalqcsZ/o30/kz808O5B/gQP4BPt/5OWaTmSbRTUiOS+aMuDOIDY31dMgiIlIDVASJUHHl2LAOw8gryWPL4S3syNrBzpyd7D+yn/T8dPbk7WFP3h6+3PUlHRp0oEfLHpzf+nxPhy0iIqdARZDIMcKCwzij0Rmc0egMep3Wiz8z/uTb3d/ye8bv7Mnbw19Zf9F/aX/OTzqfe8+9lwtaXYDJZPJ02CIi4iIVQSInER8ZT48mPejRpAf7c/fz2/7f+PXQr3yd+jVfp35NjyY9uPfce7m03aUEmXStgYiIr1ARJOKC+Ih4/nP6f1g6bCnP/vIsz294nvX71zP0raG0b9ie8X3GM6z9MGLDjz9v6NjL9ROjEhl8+uC6CF9ERI6if7ZKQDr6BoruaFavGbMvnk3anWnc1/c+YkJjSDmUwk0f3UTCzAQuWnoR07+ZzqfbP2V71naKy4od2x57uX5mQeappiMiIm5QT5AEpKpuoNghvoPL+4mPjOfhAQ9z99l3M+6zcXyx4wv2HtnL5zs+5/MdnzutGxUSRaQlEsMwMJlMhJhDsARZiI+M5+WNL2MrtxFiDiHEHELDiIb0adaHhhENiQuPo2FEQ5rWa0qD8AaafyQiUkNUBEnAsvfI2CVEJVRrO3OQuVIhEhMWQ9/mfWke05xDhYfYkb2DnKIccktySctNo9BaSH5pPvml+ZX2tzNnZ5XHWfrH0kptkZZIWtRvQYuYFrSKbUWnRp3olNCJjo06Ui+0XrXid4XJZCIoSB3GIuKf/KIIKi8vZ968ebz99tscOXKEnj17MmXKFJo1a+bp0MQPNa7XmFWpqzhYeNDRdnQvUsOIhjSMaEiLmBbc0PUGDMMgqyiLnOIc8kvzeeuvt9idu5tSWynWcitN6zXlUOEhMgoyKLOVYS23YgmyEBcRx+GiwxwqPERmQSaZhZkUWAvYlLmJTZmbKsVlP2anRp24pvM19GjSg/ph9U8p18jISFalriKz6O8hO81hEhF/4RdF0HPPPceyZcuYMWMGiYmJPPnkk4wcOZKPPvqIkJAQT4cnfujAkQPszf/7Qaon6kUymUzERcQRFxEHwC8HfsFitjiW9zqtFxn5GU69Uq3qt+LaM6912k9xWTGzfppFyqEUcopzOFx0mNKyUnZk7yC7OJtDhYc4VHiIDQc2sOi3RQC0adCGnk160qNJD3o26UnXxl2JColyLdf8A+zL3+fSNiIivsDni6DS0lJefvllJkyYwPnnnw/ArFmz6Nu3L59//jmXXHKJZwOUgHUqk6+PN2cpMSqREluJo81eQKUcSiEjP4MD+QfIK8kjszCTndk72Z61ne1Z23n9z9cBMGFyzC/q3rg7CVEJxIXHYTFbMJvMBAcFYw4yU1ZexpGiI2QczmBr4VZyS3IJNgdjCbKwO3c3EZYI6ofVp1FkIxpFNiI+Mp4Qs/7BISK+xeeLoM2bN1NQUECfPn0cbfXq1aNDhw6sW7dORZB4zKlOvnZlzlKEJYKWsS1pGduSXqf1woSJ7VnbSc1JpdBayJp9a9iRvcNRIGUWZvJr+q/uJQa8svGVSm0xoTGOgqhRZCPiI+LJKsqi1FbqmAQeFxFHjyY9CAsOIzw4nLDgsIq/W476+zHtwUEVpylbuY3ismKKyooq/rQWOf5uf11cVkyJrYRfDvxCbnHu37GFxdA1sWuVuZSUlrBv/z7+Mv1FaEgov6b/6tjWEmQhISqB85POJ9wSToQlgghLBOHB4YRbwgkPDsccdGpXGor4E6vNSqG1kKKyIoqsRZTYSli1cxXpR9KxlluxlluJDonm9t630zCioafDxWQYhuHpIE7F559/zu23385vv/1GWNjfD7q84447KC4uZuHChS7t75dffsEwDCwWy8lXPgnDMCgrKyM4ONgxkbaorAhbuc2xTog5BJth85m2qtaxmC3Yym3YDBsmTF4Vb023GRhYgiwYGB6PpbptR78uN8qxGTYMwyAoKMjRZmDA/58JDAzH5whQTjkViyv+AwgiCJvhvL/aYv9/x1tPVSaTCROmSn8ed/2jl1X3Qr8aTP3Yz7cmGTUZaA2wX4npi1x6Lw2q/12qYYbx/2eGo/6sjvDgcBKjEl0+1rG/U49mtVoxmUx069at2vv0+Z6goqIigEpzf0JDQ8nNza1qkxOyv7E18T+OyWSqFFeEJeKU9ysiIhJoqvqdeuxyV393+3wRZO/9KS0tdeoJKikpITw83OX9de1adZe5iIiI+BefvwFI48aNATh48KBT+8GDB0lIqN59X0RERCTw+HwR1K5dO6KiolizZo2jLS8vj02bNtGzZ08PRiYiIiLezOeHw0JCQhg+fDgzZ86kQYMGnHbaaTz55JMkJiYyaNAgT4cnIiIiXsrniyCAsWPHUlZWxv33309xcTE9e/bkpZdeqpErvERERMQ/+fwl8iIiIiLu8Pk5QSIiIiLuUBEkIiIiAUlFkIiIiAQkFUEiIiISkFQEiYiISEBSESQiIiIBSUWQiIiIBCQVQaegvLycOXPm0LdvX84880xuuukm9uzZc9z1s7Ozueuuu+jZsye9evVi2rRpFBUV1WHE7nE1z23btnHzzTfTu3dv+vTpw9ixY9m/f38dRuw+V3M92ocffkjbtm3Zu3dvLUdZM1zN1Wq18tRTTznWHz58OCkpKXUYsXtczfPw4cPcddddnHXWWfTu3Ztx48aRkZFRhxHXjIULFzJixIgTruOr56RjVSdXXz4vHa06uR7N185LdtXJsybOSSqCTsFzzz3HsmXLeOihh3jjjTcoLy9n5MiRlJaWVrn+2LFjSUtLY9GiRTzzzDN88803PPjgg3UbtBtcyTM7O5sbbriBsLAwXn31VV544QWysrIYOXIkJSUlHojeNa5+pnb79u1j+vTpdRRlzXA11wcffJDly5fz6KOP8u6779KgQQNuuukmjhw5UseRu8bVPO+8807279/PK6+8wiuvvML+/fu57bbb6jjqU/Paa68xe/bsk67nq+eko1UnV18/L9lV93O188XzElQ/zxo5JxnilpKSEqNr167Ga6+95mjLzc01OnfubHz00UeV1v/ll1+M5ORkY/v27Y627777zmjbtq2Rnp5eJzG7w9U833rrLaNr165GUVGRo23//v1GcnKy8eOPP9ZJzO5yNVc7m81mXHXVVca1115rJCcnG3v27KmLcE+Jq7nu3r3baNu2rfHVV185rd+/f3+v/lxdzTM3N9dITk42Vq9e7WhbtWqVkZycbGRnZ9dFyKckPT3dGDVqlHHmmWcaF198sTF8+PDjruur5yQ7V3L15fOSYbiWq50vnpdcybOmzknqCXLT5s2bKSgooE+fPo62evXq0aFDB9atW1dp/fXr1xMfH0/r1q0dbb169cJkMrFhw4Y6idkdrubZp08fnnvuOcLCwhxtQUEVX7O8vLzaD/gUuJqr3YIFC7BarYwaNaouwqwRrub6ww8/EB0dTb9+/ZzW//LLL5324W1czTMsLIzIyEjef/998vPzyc/P54MPPqBly5bUq1evLkN3y19//YXFYuHDDz+kS5cuJ1zXV89Jdq7k6svnJXAtVztfPC+5kmdNnZP84gGqnpCeng5A48aNndobNWrkWHa0jIyMSuuGhIRQv359Dhw4UHuBniJX82zatClNmzZ1anv++ecJCwujZ8+etRdoDXA1V4Dff/+dl19+mXfeecen5o24muuuXbto1qwZn3/+Oc8//zwZGRl06NCBe+65x+mXqLdxNc+QkBBmzJjBlClT6NGjByaTiUaNGrF06VLHL01vNmDAAAYMGFCtdX31nGTnSq6+fF4C13IF3z0vuZJnTZ2TvP//ai9lnzwYEhLi1B4aGlrlGHNRUVGldU+0vrdwNc9jvfrqqyxdupQJEybQoEGDWomxpriaa2FhIRMmTGDChAkkJSXVRYg1xtVc8/PzSUtL47nnnmP8+PHMnz+f4OBgrr76ag4fPlwnMbvD1TwNwyAlJYWuXbvy2muvsXjxYpo0acKtt95Kfn5+ncRcV3z1nFQTfOm85CpfPi+5oqbOSSqC3GTvVj12cmVJSQnh4eFVrl/VRMySkhIiIiJqJ8ga4GqedoZhMHv2bB5++GFuueUWl65m8BRXc3344Ydp2bIlV155ZZ3EV5NczTU4OJj8/HxmzZrFueeeS+fOnZk1axYA7733Xu0H7CZX81y5ciVLly7lySefpHv37vTq1YsFCxawb98+3nnnnTqJua746jnpVPjieclVvnxeckVNnZNUBLnJ3o188OBBp/aDBw+SkJBQaf3ExMRK65aWlpKTk0OjRo1qL9BT5GqeUHHZ4t13382CBQuYPHkyd955Z22HWSNczfXdd9/lxx9/pGvXrnTt2pWbbroJgEsuuYQFCxbUfsCnwJ3vb3BwsFM3c1hYGM2aNfPqS29dzXP9+vW0bNmSqKgoR1tMTAwtW7YkLS2tdoOtY756TnKXr56XXOXL5yVX1NQ5SUWQm9q1a0dUVBRr1qxxtOXl5bFp06Yqx5h79uxJenq604l07dq1AHTv3r32A3aTq3kCTJw4kU8//ZSnnnqK66+/vo4iPXWu5vr555/z8ccf8/777/P+++/z8MMPAxVzDbz9X2HufH/Lysr4448/HG3FxcXs2bOHFi1a1EnM7nA1z8TERNLS0pyGgwoLC9m7d6/fDS346jnJXb56XnKVL5+XXFFT5yRNjHZTSEgIw4cPZ+bMmTRo0IDTTjuNJ598ksTERAYNGoTNZiMrK4vo6GjCwsLo0qUL3bp1Y9y4cTz44IMUFhYyZcoULrvssuP2qHgDV/Ncvnw5K1asYOLEifTq1YvMzEzHvuzreCtXcz32fzT7RNsmTZpQv359D2RQfa7m2qNHD84++2wmTZrE9OnTqV+/PnPmzMFsNnPppZd6Op3jcjXPyy67jJdeeok777yTO+64A4DZs2cTGhrK0KFDPZzNqfGXc1J1+NN56WT86bx0IrV1TlJP0CkYO3Ysl19+Offffz9XXXUVZrOZl156CYvFwoEDBzj33HNZsWIFACaTiXnz5tG0aVOuu+467rzzTvr16+cTNyZzJc+PP/4YgCeeeIJzzz3X6ce+jjdzJVdf52quc+fOpVevXowZM4bLL7+c/Px8lixZ4vUTS13Js1GjRixbtgzDMLjuuuu44YYbsFgsLFu2jOjoaA9ncmr86Zx0Mv52XjoRfzsvHU9tnZNMhmEYtRGwiIiIiDdTT5CIiIgEJBVBIiIiEpBUBImIiEhAUhEkIiIiAUlFkIiIiAQkFUEiIiISkFQEiYiIiEcsXLjQ5We4lZWV8cwzz9C/f3+6du3KNddcw8aNG906voogERERqXOvvfYas2fPdnm7+fPn8/bbb/PQQw/x/vvv07JlS0aOHFnpWXjVoSJIRLzShg0buP322znnnHPo1KkTAwcO5P7772fHjh2V1l25ciUjRoygR48etGvXjrZt29KuXTu/e/K7iD/IyMhg9OjRzJw5061n8q1atYpLLrmEc889lxYtWnDPPfdw5MgRt3qDVASJiNd5/vnnueaaaygqKuLee+/lpZdeYvTo0WzatIkhQ4bwySefONZdtGgRDz74IP379+eZZ57h9ddf55133uGbb77h8ssv92AWIlKVv/76C4vFwocffkiXLl0qLf/qq68YOnQonTt35sILL2T27NmUlpY6lsfFxfHVV1+xd+9ebDYbb775JiEhIbRr187lWPTYDBHxKl999RWjR4/m9ttvZ8yYMU7LrFYrd911F1999RXLly8nKSmJc889lyeffJJ+/fp5KGIRcdc999zDvn37ePXVVwH49ttvuf3225k8eTJnn302u3fv5qGHHqJdu3Y888wzAOzYsYM77riDbdu2YTabCQoKYu7cufTv39/l46snSES8yrx582jVqhW33XZbpWUWi4Xp06djNpt54YUX2LZtG8XFxTRr1oxRo0bRtWtXevfuzeTJk8nKygJgxIgRtG3b1vGzd+/eEx5/69atjBo1im7dutGtWzduu+029uzZ41i+Zs0ax742bNjgtO3SpUtp27YtAwYMqIF3QiTwLFiwgP/+979ceeWVNG/enHPPPZdp06bx6aefOv7f3b59O9HR0Tz77LO8+eabDB06lAkTJpCSkuLy8YJrOgEREXdlZWXx559/cuONN2Iymapcp379+px99tmsXr2aCy+8EIvFwnXXXUe3bt2YNWsWWVlZzJo1iz///JO3336bqVOnkp+fz9dff838+fNPePxdu3Zx5ZVX0qpVKx5//HHKysqYP38+V111FR988AFxcXGOdSMjI/nyyy/p3r27o23FihUEBenfliLu2rRpE7///rvTfD77gNWOHTswm83cddddLFq0iB49egDQqVMntm/fzty5c3nuuedcOp6KIBHxGvv27QPgtNNOO+F6LVq0YPXq1RQUFHDkyBHatWvndJVJcnIyw4YNY/ny5Vx99dUA7Ny586THnzdvHuHh4SxatIioqCgA+vTpwwUXXMCLL77IpEmTHOv269eP1atXc/fddwOQnp7Or7/+So8ePRx5iIhrysvLGTlyJEOGDKm0LD4+nm+//Rar1UqnTp2clnXp0oVvv/3W5ePpnywi4jXs/+KzWCwnXM9sNgM4el0uvfRSp+UdO3akefPmrFmzptK25eXl2Gy2Kvf7888/06tXL8LCwigrK6OsrIyoqCh69OjBjz/+6LTugAEDSE1NdRRXn376KV26dDlpAScix3f66aeza9cuWrRo4fhJT0/niSeeoKCggMTERAC2bNnitN3WrVvdutJMPUEi4jXsBcTJelL27NlDZGQkkZGRACQkJFRaJzY2lvz8/ErtF154IVBRSDVt2pQhQ4YwevRoTCYTOTk5rFixghUrVlTarkGDBk6vExIS6NixI6tXr6ZVq1asWLGCSy65hE2bNlUvWRGp5KabbuLOO+9k3rx5/POf/yQ9PZ377ruPpk2bEh8fT1xcHN27d2fSpElMnTqVxMRE3n//fX766Sdef/11l4+nIkhEvEZcXBxnnnkmn332GXfccUeV82vy8/P54YcfGDBggKNosk+CPtr+/fs5++yzK7XPnz+f+Ph4CgsL+fXXX5kzZw4RERFcd911REdHc/bZZ3PDDTdU2i44uPLpcuDAgaxevZrBgwfz559/Mm/ePBVBIqfg4osvZtasWSxcuJAFCxZQv359BgwYwIQJE4CK3t/58+cze/ZsJk+eTG5uLsnJySxatKjKy+1PRkWQiHiVMWPGMHLkSJ5++mnHic/OZrMxdepUiouLGTlyJKeffjoJCQl89NFHXHbZZY71vv32WzIzM6u8bD45OZmmTZsC0Lt3bz799FN+/vlnrrvuOnr16sX27dtp3769o+gxDIMJEybQokUL2rdv77SvCy64gDlz5rB06VK6d+9Oo0aNavjdEPFvM2bMqNQ2ePBgBg8efNxtYmJimDp1KlOnTj3l46sIEhGv0rdvX+655x6eeOIJUlJSGDZsGI0aNWLv3r28/vrrpKSk8MgjjzhujHbPPfcwbtw4xo8fz6WXXsqBAwd4+umn6dq1a5Un0pSUFA4dOkRBQQEbNmxg69at/POf/wTg1ltv5corr2TUqFFcddVVhIaG8uabb7Jq1SrmzJlTaV+nn346zZo1Y8mSJUyZMqV23xgRqXEqgkTE69xwww107dqVxYsX8/jjj5OVlUV8fDznnHMOjzzyCG3atHGs+49//AOouMv02LFjCQ8PZ+DAgdx7772OCdRHs9+A0WKx0KRJE8aMGcONN94IQLt27XjttdeYNWsWEydOxDAMkpOTefbZZxk4cGCVsQ4cOJAlS5YwaNCgmn4bRKSW6Y7RIiIiEpB0ibyIiIgEJBVBIiIiEpBUBImIiEhAUhEkIiIiAUlFkIiIiAQkFUEiIiISkFQEiYiISEBSESQiIiIBSUWQiIiIBCQVQSIiIhKQVASJiIhIQPo/FPwtIOBlh14AAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Средний объем торгов в обучающей выборке:  14979282.753403345\n",
+      "Средний объем торгов в контрольной выборке:  14379996.6562986\n",
+      "Средний объем торгов в тестовой выборке:  14085782.089552239\n"
+     ]
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "sns.histplot(train_data[\"Volume\"], kde=True, color=\"blue\")\n",
+    "plt.title('Распределение объема в обучающей выборке')\n",
+    "plt.xlabel('Объем')\n",
+    "plt.ylabel('Частота')\n",
+    "plt.show()\n",
+    "\n",
+    "sns.histplot(val_data[\"Volume\"], kde=True, color=\"red\")\n",
+    "plt.title('Распределение объема в контрольной выборке')\n",
+    "plt.xlabel('Объем')\n",
+    "plt.ylabel('Частота')\n",
+    "plt.show()\n",
+    "\n",
+    "sns.histplot(test_data[\"Volume\"], kde=True, color=\"green\")\n",
+    "plt.title('Распределение объема в тестовой выборке')\n",
+    "plt.xlabel('Объем')\n",
+    "plt.ylabel('Частота')\n",
+    "plt.show()\n",
+    "\n",
+    "print(\"Средний объем торгов в обучающей выборке: \", train_data['Volume'].mean())\n",
+    "print(\"Средний объем торгов в контрольной выборке: \", val_data['Volume'].mean())\n",
+    "print(\"Средний объем торгов в тестовой выборке: \", test_data['Volume'].mean())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### **Процесс конструирования признаков**\n",
+    "\n",
+    "Теперь приступим к конструированию признаков для решения бизнес задачи.\n",
+    "\n",
+    "**Унитарное кодирование**  \n",
+    "Унитарное кодирование категориальных признаков (one-hot encoding). Преобразование категориальных признаков в бинарные векторы.\n",
+    "\n",
+    "**Дискретизация числовых признаков**  \n",
+    "Процесс преобразования непрерывных числовых значений в дискретные категории или интервалы (бины).\n",
+    "\n",
+    "**Ручной синтез**  \n",
+    "Создание новых признаков на основе экспертных знаний и логики предметной области. \n",
+    "\n",
+    "**Масштабирование признаков**  \n",
+    "Процесс преобразования числовых признаков таким образом, чтобы они имели одинаковый масштаб. Это важно для многих алгоритмов машинного обучения, которые чувствительны к масштабу признаков, таких как линейная регрессия, метод опорных векторов (SVM) и нейронные сети."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**One-hot encoding:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Пример категориальных признаков\n",
+    "categorical_features = [\n",
+    "    \"Date\",\n",
+    "    \"date\"\n",
+    "]\n",
+    "\n",
+    "# Применение one-hot encoding\n",
+    "train_data_encoded = pd.get_dummies(train_data, columns=categorical_features)\n",
+    "val_data_encoded = pd.get_dummies(val_data, columns=categorical_features)\n",
+    "test_data_encoded = pd.get_dummies(test_data, columns=categorical_features)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Дискретизация числовых признаков:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "         High         High_bin     High_category\n",
+      "0    0.347656              NaN               NaN\n",
+      "1    0.367188  (0.348, 29.982]   Low hight value\n",
+      "2    0.371094  (0.348, 29.982]   Low hight value\n",
+      "3    0.359375  (0.348, 29.982]   Low hight value\n",
+      "4    0.355469  (0.348, 29.982]   Low hight value\n",
+      "5    0.382813  (0.348, 29.982]   Low hight value\n",
+      "6    0.414063  (0.348, 29.982]   Low hight value\n",
+      "7    0.437500  (0.348, 29.982]   Low hight value\n",
+      "8    0.445313  (0.348, 29.982]   Low hight value\n",
+      "9    0.449219  (0.348, 29.982]   Low hight value\n",
+      "10  76.839996  (59.616, 89.25]  Very hight value\n",
+      "11  89.250000  (59.616, 89.25]  Very hight value\n",
+      "12  88.610001  (59.616, 89.25]  Very hight value\n",
+      "13  76.989998  (59.616, 89.25]  Very hight value\n",
+      "14  75.150002  (59.616, 89.25]  Very hight value\n",
+      "15  74.470001  (59.616, 89.25]  Very hight value\n",
+      "16  81.019997  (59.616, 89.25]  Very hight value\n",
+      "17  80.699997  (59.616, 89.25]  Very hight value\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "\n",
+    "labels = [\"Low hight value\", \"Medium hight value\", \"Very hight value\"]\n",
+    "num_bins = 3\n",
+    "\n",
+    "# Создаем числовые интервалы и метки\n",
+    "hist, bins = np.histogram(df[\"High_filled\"], bins=num_bins)\n",
+    "df[\"High_bin\"] = pd.cut(df[\"High_filled\"], bins=bins)\n",
+    "df[\"High_category\"] = pd.cut(df[\"High_filled\"], bins=bins, labels=labels)\n",
+    "\n",
+    "combined_table = df[[\"High\", \"High_bin\", \"High_category\"]]\n",
+    "print(combined_table.head(20))\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Ручной синтез:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Пример синтеза признака среднего значения в максимальной и минимальной цене\n",
+    "train_data_encoded[\"medium\"] = train_data_encoded[\"High\"] / train_data_encoded[\"Low\"]\n",
+    "val_data_encoded[\"medium\"] = val_data_encoded[\"High\"] / val_data_encoded[\"Low\"]\n",
+    "test_data_encoded[\"medium\"] = test_data_encoded[\"High\"] / test_data_encoded[\"Low\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Масштабирование признаков:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.preprocessing import StandardScaler, MinMaxScaler\n",
+    "\n",
+    "# Пример масштабирования числовых признаков\n",
+    "numerical_features = [\"Open\", \"Close\"]\n",
+    "\n",
+    "scaler = StandardScaler()\n",
+    "train_data_encoded[numerical_features] = scaler.fit_transform(train_data_encoded[numerical_features])\n",
+    "val_data_encoded[numerical_features] = scaler.transform(val_data_encoded[numerical_features])\n",
+    "test_data_encoded[numerical_features] = scaler.transform(test_data_encoded[numerical_features])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Конструирование признаков с применением фреймворка Featuretools:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "s:\\Учеба\\3 курс\\5 семестр\\AIM\\lab_3\\AIM-PIbd-31-Izotov-A-P\\aimenv\\Lib\\site-packages\\featuretools\\synthesis\\deep_feature_synthesis.py:169: UserWarning: Only one dataframe in entityset, changing max_depth to 1 since deeper features cannot be created\n",
+      "  warnings.warn(\n",
+      "s:\\Учеба\\3 курс\\5 семестр\\AIM\\lab_3\\AIM-PIbd-31-Izotov-A-P\\aimenv\\Lib\\site-packages\\featuretools\\computational_backends\\feature_set_calculator.py:143: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
+      "  df = pd.concat([df, default_df], sort=True)\n",
+      "s:\\Учеба\\3 курс\\5 семестр\\AIM\\lab_3\\AIM-PIbd-31-Izotov-A-P\\aimenv\\Lib\\site-packages\\woodwork\\logical_types.py:841: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
+      "  series = series.replace(ww.config.get_option(\"nan_values\"), np.nan)\n",
+      "s:\\Учеба\\3 курс\\5 семестр\\AIM\\lab_3\\AIM-PIbd-31-Izotov-A-P\\aimenv\\Lib\\site-packages\\featuretools\\computational_backends\\feature_set_calculator.py:143: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
+      "  df = pd.concat([df, default_df], sort=True)\n",
+      "s:\\Учеба\\3 курс\\5 семестр\\AIM\\lab_3\\AIM-PIbd-31-Izotov-A-P\\aimenv\\Lib\\site-packages\\woodwork\\logical_types.py:841: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
+      "  series = series.replace(ww.config.get_option(\"nan_values\"), np.nan)\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "        Open       High        Low     Close  Adj Close    Volume  \\\n",
+      "id                                                                  \n",
+      "0  -0.836096   1.937500   1.843750 -0.837302   1.470243  21592000   \n",
+      "1  -0.740309   5.175000   4.975000 -0.744123   3.899629  17306400   \n",
+      "2   0.836571  58.580002  57.689999  0.838929  50.306290   7857500   \n",
+      "3   1.104184  68.209999  67.050003  1.134793  60.854706  11702500   \n",
+      "4   0.806207  57.520000  57.029999  0.813331  49.359718   8331600   \n",
+      "\n",
+      "    Date_1992-06-26  Date_1992-06-29  Date_1992-06-30  Date_1992-07-01  ...  \\\n",
+      "id                                                                      ...   \n",
+      "0             False            False            False            False  ...   \n",
+      "1             False            False            False            False  ...   \n",
+      "2             False            False            False            False  ...   \n",
+      "3             False            False            False            False  ...   \n",
+      "4             False            False            False            False  ...   \n",
+      "\n",
+      "    date_2024-04-30 00:00:00  date_2024-05-01 00:00:00  \\\n",
+      "id                                                       \n",
+      "0                      False                     False   \n",
+      "1                      False                     False   \n",
+      "2                      False                     False   \n",
+      "3                      False                     False   \n",
+      "4                      False                     False   \n",
+      "\n",
+      "    date_2024-05-03 00:00:00  date_2024-05-06 00:00:00  \\\n",
+      "id                                                       \n",
+      "0                      False                     False   \n",
+      "1                      False                     False   \n",
+      "2                      False                     False   \n",
+      "3                      False                     False   \n",
+      "4                      False                     False   \n",
+      "\n",
+      "    date_2024-05-07 00:00:00  date_2024-05-08 00:00:00  \\\n",
+      "id                                                       \n",
+      "0                      False                     False   \n",
+      "1                      False                     False   \n",
+      "2                      False                     False   \n",
+      "3                      False                     False   \n",
+      "4                      False                     False   \n",
+      "\n",
+      "    date_2024-05-16 00:00:00  date_2024-05-21 00:00:00  \\\n",
+      "id                                                       \n",
+      "0                      False                     False   \n",
+      "1                      False                     False   \n",
+      "2                      False                     False   \n",
+      "3                      False                     False   \n",
+      "4                      False                     False   \n",
+      "\n",
+      "    date_2024-05-23 00:00:00    medium  \n",
+      "id                                      \n",
+      "0                      False  1.050847  \n",
+      "1                      False  1.040201  \n",
+      "2                      False  1.015427  \n",
+      "3                      False  1.017300  \n",
+      "4                      False  1.008592  \n",
+      "\n",
+      "[5 rows x 10291 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "import featuretools as ft\n",
+    "\n",
+    "es = ft.EntitySet(id='starbucks_data')\n",
+    "es = es.add_dataframe(dataframe_name='starbucks', dataframe=train_data_encoded, index='id')\n",
+    "\n",
+    "\n",
+    "# Генерация признаков\n",
+    "feature_matrix, feature_defs = ft.dfs(\n",
+    "    entityset=es, \n",
+    "    target_dataframe_name=\"starbucks\", \n",
+    "    max_depth=2\n",
+    ")\n",
+    "\n",
+    "# Преобразование признаков для контрольной и тестовой выборок\n",
+    "val_feature_matrix = ft.calculate_feature_matrix(features=feature_defs, entityset=es, instance_ids=val_data_encoded.index)\n",
+    "test_feature_matrix = ft.calculate_feature_matrix(features=feature_defs, entityset=es, instance_ids=test_data_encoded.index)\n",
+    "\n",
+    "print(feature_matrix.head())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### **Оценка качества каждого набора признаков**\n",
+    "\n",
+    "**Предсказательная способность**  \n",
+    "Метрики: RMSE, MAE, R²\n",
+    "\n",
+    "Методы: Обучение модели на обучающей выборке и оценка на контрольной и тестовой выборках.\n",
+    "\n",
+    "**Скорость вычисления**  \n",
+    "Методы: Измерение времени выполнения генерации признаков и обучения модели.\n",
+    "\n",
+    "**Надежность**  \n",
+    "Методы: Кросс-валидация, анализ чувствительности модели к изменениям в данных.\n",
+    "\n",
+    "**Корреляция**  \n",
+    "Методы: Анализ корреляционной матрицы признаков, удаление мультиколлинеарных признаков.\n",
+    "\n",
+    "**Цельность**  \n",
+    "Методы: Проверка логической связи между признаками и целевой переменной, интерпретация результатов модели."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "s:\\Учеба\\3 курс\\5 семестр\\AIM\\lab_3\\AIM-PIbd-31-Izotov-A-P\\aimenv\\Lib\\site-packages\\sklearn\\metrics\\_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "RMSE: 2885972.9324181927\n",
+      "R²: 0.9328285916832842\n",
+      "MAE: 1680373.6776608187\n",
+      "Cross-validated RMSE: 12160466.835803727\n",
+      "=====================================\n",
+      "Метрика Train RMSE: 4388457.199779966\n",
+      "Метрика Train R²: 0.9082228071090095\n",
+      "Метрика Train MAE: 1787810.5665033064\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "s:\\Учеба\\3 курс\\5 семестр\\AIM\\lab_3\\AIM-PIbd-31-Izotov-A-P\\aimenv\\Lib\\site-packages\\sklearn\\metrics\\_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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nZs6ciTJlyohTkL788kv8+uuvWLhwIerXry9+cMvsA3Tfvn3x33//YcSIEdi8eXOmH3xeZsaMGWjWrBnq1q1rtchdIpFg4cKFGDx4sDhikx5H+odRT09PAGnTdtzc3DJcu1ixYuJ6nufX9Tx9+hSXL1+2+lZ8yZIlmDJlCqZMmYIZM2ZYnW82mxEREYFPPvkEpUqVeuHj+fbbb2EwGNCvXz88fvz4pY/dy8sLAPD48eMM14yLi0Px4sXFx/F8QQUAYuL5fCLWtGlTDBw4EBaLBbGxsVi1ahU+++wz7N+/36bn7Fn16tWD2WzGyZMnsWfPHrRq1cqmhPno0aOYOHHiK8+z19OnTzO0PX78WEx4PDw8UKdOHYwZMybT2ysUClgsFpw/f16cTpeZ9Ocpq6+b5ORk9OnTB+XKlcPu3btRqlQpSKVSHDlyRCwS8qyxY8eid+/e+PbbbzF+/HhUq1YNZrMZAwcORPPmzbFixQoUL14cEokE3333HY4dO2Z1++erOsbFxeGLL77IcD9RUVFWSUxm5wwaNAhNmjSB2WzG7du38dVXX+HevXsvrBpp63sjnZeXF6KjozO0x8XFAUhLlNK/hHjy5EmG8x48eJDplw/h4eGoVKkSdDod/v33X3Ed1IQJE2x6XTyrWbNmmDt3LkaPHo3Dhw9j3bp1LMVPlMdwat8z0iuCpX9weNbRo0cxbNgwfPjhh/j5558xZcoU7N2712pvkvRvz9IrWi1YsACLFy9+6boQotdFx44dsXz5cty5cwfvvfceVq5cCSBtXUJYWBjefvttrF+/XkxUzpw5g7feegvNmzcX2y5evIj4+PgMU4ZKlSqFhQsXQiqV2v3B+ejRozhx4sQLp8BVqFABv/zyC/bs2YP9+/fj1KlTVvsypU+1efr0KapUqSL+Fx8fj0WLFiEhIQGlSpVCoUKFxOlQ6Xbu3Il+/fpZTVVs2bIlZs6ciW3btmHPnj1W5//www+Ij49/YbEMIO1D37JlyzBmzBioVKpXPv5q1apBoVDg559/tmo/ffo0Hjx4gDfffBNAWj/du3fPqhiHIAj48ccfERISkuHfTW9vb1SpUgXVqlVDixYt0K9fP8TGxuLmzZs2PWfPSv92/pdffsGBAwfEtTovc+PGDcTGxmaYiugIt2/ftioOEBMTg7Nnz4pJfp06dXDr1i2ULFnS6vHt3LkTW7duhUwmw99//w2tVou33nrrhfeT3dfNzZs3kZCQgE8++QRlypQRk8+jR48CSJuGFhMTg1GjRuHSpUsoUaIEateujUGDBkGn0+HChQu4ePEi9Ho9+vXrh+DgYHFEJD2JenZESqFQWD3esmXLZvq4ypYta3VeZmvqAgMDUaVKFVSvXh0dO3bEu+++K04zzYwt741n1a5dG/fv389QXGbXrl2Qy+WoWrUqPDw8UL16dezdu9dqneT169dx/vx5NGrUKMN10/u8du3a6N69O+rXry9WSLTldfGsJk2a4MmTJ4iMjEThwoXFtZ9ElHdwRMpGy5cvx4cffoiuXbsCSFs0Hx4ejp49e+LevXsICgrC9evX4eHhgaVLlyIgIABbtmzBqFGjsGHDBlSoUMHJj4DI+Zo2bYqmTZsiJiYGy5Ytw6ZNm7B7924EBgZmqOZXtWpV7N27F99//z1Kly6Nq1evIioqChKJxGoKTDq1Wo1Jkyahf//++PXXX9GqVSubYrpw4QKGDBny0v2WXFxcxDUjzytXrhzat2+PSZMm4f79+6hcuTJu3bqFBQsWICgoCCEhIZDJZBg8eDCmTZuGwoULIzQ0FLdu3cLixYvx8ccfi6NC6Zo0aYJWrVph5syZVh/WLly4gK+++uqlpbxv3LiBunXr4p133rHp8Xt7e6Nfv35YunQp5HI5mjZtinv37mHRokUoU6YM3nvvPQDA+++/j++//x4DBgzA0KFDUbRoUWzbtg3nz58Xq5w9Kz4+HufOnYPJZEJMTAzWrFkDHx8fhISEQK1Wv/I5e16zZs0wfvx4FC5cGLVq1bKagpmZo0ePonbt2mIS7kiCIKB///4YPnw4ZDIZIiMj4eXlJY6m9urVCzt37kSvXr3w6aefolChQtizZw9++OEHjB8/Hnfu3EFUVBSqV6+O6Ohoq5ERg8GA+Ph43LlzB8HBwdl63ZQsWRLu7u5Yvnw5XFxc4OLigl9//VUs8Z1e7OLcuXMYMmQIhg8fDm9vb6xevRpKpRKVK1eGxWKBi4sL5syZg08//RQGgwHbt2/Hb7/9BgBiQQZHu3PnDs6dOwedTocbN25g165dqF279gvPt+W98axOnTph48aNGDhwIIYMGYKgoCAcOnQI27Ztw6BBg8TRwDFjxqBnz57o06cPevTogaSkJCxcuBDFixcXpyE/6/r161AqlUhNTcWVK1fwxx9/oGPHjgBe/bp4nqenJ2rXro1vv/0Wn332mU2Pi4hyFxMpG12+fBkXLlyw2mMi/Zu4GzduQCaTYeTIkVi7dq34bWuVKlVw/fp1LFmyBMuWLXNK3ER5UUBAgDgt5kWFAMaNGwej0YiFCxfCYDAgKCgIX3zxBa5fv45Dhw5lWkmvadOmaN68OWbOnImGDRva9CE6KCgIffr0ydbjmTlzJlasWIFNmzbh0aNHKFy4MNq0aYNhw4aJ3zJ//PHHUKvV+Prrr7F582YUKVIEffv2feFaqAkTJqB169ZYsmSJ+AG9Ro0a6NChw0tjcXFxQVhYmF3xDx48GL6+vtiwYQM2b94Mb29vvPPOOxg2bJj4HMrlcqxZswZz5szBkiVLkJSUhJIlSyIyMhJNmjTJcM0jR46I05DSR6ciIiLE69nynD2radOmkEgkaN26tc3T+hxd9jxdsWLF8Omnn2LGjBlITU1F/fr1ERUVJa4hCwgIwKZNmzBv3jxMnToVer0eISEh+PLLL9G5c2eMGzcOv//+OwCgS5cuGa5/5MgR+Pj4YNasWdl63YwfPx7Lli3D7NmzMXToULi5uaFChQrYsGED+vbti9OnTyM0NBRff/21WNrbYDDgjTfewPLly8VRxnnz5iEyMhJffPEFvLy8UL16daxfvx49evTA6dOnc2Rfo6ioKERFRUEqlcLPzw/NmjXDyJEjX3i+Le+NZ7m6umL9+vWYN28eFi1ahOTkZJQqVUrso3Q1a9bEqlWrsGjRIowcORIuLi546623EBYWlmnSNm3aNABp78OAgAB06dIFw4YNA/Dq10VmmjdvjuPHj9tUXIWIcp9EyIubQOQB48aNw/3798Xy51WrVsWnn34qfjv7LD8/Pxw9ehRDhw7FhQsXoFQqxWNfffUVjh49+sqFr0RElPeNGzcOJ0+ezLDHj73XAIBZs2Zl6TgREeUNXCNlozfeeAO3bt1CiRIlxP8ePXqE2bNnIyUlBUWKFAEA/Pvvv1a3+++//7JUAZCIiIiIiPIuJlI26tu3L3799VdERkbi1q1bOH78OMaPH4+kpCT4+fmhatWqqFmzJsaOHYu//voLt2/fxsKFC3H8+HFxw0kiIqLixYtnWtTI1uNERJQ3cGrfCzw/tQ8A9u7dixUrVuD69evw9vZGaGgoRo0aJS5K1Wg0WLhwIX777TdoNBqULVsWI0aMQJ06dZz1MIiIiIiIKAcwkSIiIiIiIrITp/YRERERERHZiYkUERERERGRnV77faTOnj0LQRAgl8udHQoRERERETmR0WiERCJBjRo1Xnnuaz8iJQgCcnKZmCAIMBgMOXof5Djsr/yHfZb/sM/yH/ZZ/sM+y3/YZ3mDPbnBaz8ilT4SVaVKlRy5vlarxZUrV1CmTBmo1eocuQ9yHPZX/sM+y3/YZ/kP+yz/YZ/lP+yzvOGff/6x+dzXfkSKiIiIiIjIXkykiIiIiIiI7MREioiIiIiIyE5MpIiIiIiIiOzERIqIiIiIiMhOTKSIiIiIiIjsxESKiIiIiIjITkykiIiIiIiI7MREioiIiIiIyE5MpIiIiIiIiOzERIqIiIiIiMhOTKSIiIiIiIjsxESKiIiIiIjITkykiIiIiIiI7MREioiIiIiIyE5MpIiIiIiIiOzERIqIiIiIiMhOTKSIiIiIiIjsxESKiIiIiIhyXXJyMiIiInDx4kVnh5IlLs4OgIiIiIiIXh+CIGDnzp2YPn06Hj16hFOnTuHHH3+EVJq/xnjyV7RERERERJRvXb16FR988AEGDhyIR48eAQD++ecfXLlyxcmR2Y+JFBERERER5ajExERMmTIFLVu2xPHjx8X2Fi1a4NChQ6hUqZITo8saTu0jIiIiIqIcIQgCtm3bhoiICMTFxYntJUqUwLRp09C8eXMnRpc9TKSIiIiIiChHjB8/HuvXrxd/V6lUGDx4MPr37w+VSuXEyLKPU/uIiIiIiChHdO7cWfy5devWOHLkCIYNG5bvkyiAI1JEREREROQAFosFT548gZ+fn9hWq1YtjBgxAjVr1kSTJk2cF1wOYCJFRERERETZcv78eUycOBEmkwm7d++GTCYTj40cOdKJkeUcTu0jIiIiIqIsiY+Px5gxY9C2bVucPXsW//zzDzZu3OjssHIFR6SIiIiIiMguZrMZ3333Hb766iskJCSI7W+88QZKly7tvMByERMpIiIiIiKy2ZkzZzBx4kT8888/YpubmxtGjBiBzz77DHK53InR5R4mUkRERERE9EqPHz/GjBkzsHnzZqv2Tp06ISwsDAEBAU6KzDmYSBERERER0Ss9evQIW7ZsEX+vUKECIiIiULduXSdG5TwsNkFERERERK9UuXJl9OjRAx4eHpg2bRp++eWX1zaJAphIERERERHRc2JiYjBz5kwYjUar9rFjx+LYsWP47LPP4OLyek9ue70fPRERERERiYxGI7755hvMmzcPycnJ8PX1Rd++fcXjXl5eTowub+GIFBERERER4c8//0SrVq0QHh6O5ORkAMDXX38Nk8nk5MjyJiZSRERERESvsQcPHmDAgAH44IMP8O+//wIAJBIJPv74Y+zZs+e1n8L3InxWiIiIiIheQwaDAatXr8aCBQug1WrF9urVqyMiIgI1atRwYnR5HxMpIiIiIqLXjMFgQOvWrXH16lWxrVChQpgwYQK6du0KqZQT116FzxARERER0WtGoVCgUaNGAACpVIqePXvi2LFj6NatG5MoG3FEioiIiIiogNPr9ZBIJFAoFGLbiBEjcOfOHQwfPhyVK1d2YnT5E9NNIiIiIqIC7ODBgwgNDcXKlSut2j08PPD1118zicoiJlJERERERAVQdHQ0evXqhU8++QS3b9/GwoUL8eDBA2eHVWBwah8RERERUQGSmpqKZcuWYenSpdDr9WJ7tWrVrH6n7GEiRURERERUAAiCgH379mHKlCm4e/eu2B4QEIBJkyahY8eOkEgkToywYGEiRURERESUz928eRNTpkzBoUOHxDYXFxf06dMHw4YNg4eHhxOjK5iYSBERERER5XNbtmyxSqIaNGiAiIgIlC1b1olRFWwsNkFERERElM8NHjwYxYoVQ9GiRbF8+XJs3ryZSVQO44gUEREREVE+cv36dVy4cAGdOnUS29RqNb799luEhIRArVY7MbrXBxMpIiIiIqJ8IDk5GQsXLsSqVasgk8lQs2ZNlChRQjxesWJFJ0b3+uHUPiIiIiKiPEwQBOzYsQONGzdGVFQUTCYT9Ho9IiMjnR3aa40jUkREREREedTVq1cRFhaG48ePi21KpRIDBgzAwIEDnRgZ5akRqRUrVqBHjx4vPefatWvo168f3nrrLdSrVw9DhgzhDs1EREREVKAkJiZiypQpaNmypVUS1bx5cxw6dAijRo2Cq6urEyOkPJNIfffdd1i4cOFLz3n69Cl69+4NlUqF9evXY9WqVYiPj0efPn24SzMRERERFQiXL19Go0aNsHr1apjNZgBAiRIlsHbtWrGgBDmf06f2xcTEYMqUKThx4sQrXxQHDhyAVqvF7NmzoVKpAABz5sxBkyZN8Pfff6NevXq5EDERERERUc4pVaoU3NzcEBcXB5VKhUGDBuGLL74QP/9S3uD0EalLly5BLpdj165dqFat2kvPrVevHpYtW2b1IpJK0x5CYmJijsZJRERERJQTjEaj1e8qlQrh4eFo3bo1fvvtNwwfPpxJVB7k9BGp0NBQhIaG2nRuUFAQgoKCrNpWrlwJlUqF2rVrZzkGQRCg1WqzfPuXSU1Ntfo/5W3sr/yHfZb/sM/yH/ZZ/sM+yx8sFgu2bduGRYsWYeXKlZBIJGKf1a9fH/Xr1weAHPucShkJggCJRGLTuU5PpLJj/fr12LBhA8LCwuDj45Pl6xiNRly5csWBkWV0+/btHL0+ORb7K/9hn+U/7LP8h32W/7DP8q5r165hxYoV+O+//wAAkydPxrRp09hneYBCobDpvHyZSAmCgEWLFiEqKgpffPHFKyv9vYpcLkeZMmUcFJ211NRU3L59GyEhIayskg+wv/If9ln+wz7Lf9hn+Q/7LO96+vQp5s+fj82bN0MQBLG9aNGiMBgMKFeuHPvMia5fv27zufkukTIajRg/fjx+/vlnjB8/Hr169cr2NSUSCdRqdfaDewlXV9ccvw9yHPZX/sM+y3/YZ/kP+yz/YZ/lHWazGRs3bsSsWbOQkJAgtpctWxbTp0/Hm2++iStXrrDPnMzWaX1APkykxowZg/3792PevHlo27ats8MhIiIiInqpM2fOICwsDBcuXBDb3N3dMWLECHz66aeQy+VcB5UP5elEymw2Iz4+Hh4eHlCpVNi+fTv27NmDMWPGoE6dOoiLixPPTT+HiIiIiCivsFgsGD16NP7991+xrVOnTggLC0NAQIATI6Pscnr585d5+PAh3n77bezZswcA8PPPPwMAZs+ejbffftvqv/RziIiIiIjyCqlUivDwcABAhQoVsG3bNixZsoRJVAGQp0akZs2aZfV7UFCQVfa+Zs2a3A6JiIiIiMhmJ06cgLe3N8qVKye2NWzYEN9++y2aNGkCF5c89fGbsiFPj0gREREREeUHMTExGDx4MDp16oRx48ZZVeQDgObNmzOJKmCYSBERERERZZHRaMSKFSvQqFEjbN++HQBw8uRJ7Nu3z8mRUU5jWkxERERElAV//PEHwsLCxE11AcDb2xtjx45F8+bNnRgZ5QYmUkREREREdnjw4AGmT5+OXbt2iW0SiQTdunXDuHHj4OPj48ToKLcwkSIiIiIistG2bdswbtw4q32fatSogYiICFSvXt15gVGuYyJFRERERGSj4OBgMYkqVKgQJkyYgK5du0IqZemB1w0TKSIiIiKiFxAEARKJRPy9du3a+PDDD+Hq6orRo0ejUKFCToyOnImJFBERERHRc3Q6HZYvX47ff/8dP/zwg9WI0/z5862SK3o9cQySiIiIiOgZBw8eRLNmzTBnzhwcP34cmzZtsjrOJIoAjkgREREREQEAoqOjMWXKFOzfv19sk8lkePTokROjoryKiRQRERERvdZSU1OxdOlSLFu2DHq9XmyvW7cuIiIiUKFCBSdGR3kVEykiIiIiei0JgoB9+/ZhypQpuHv3rtgeEBCAyZMno0OHDpzGRy/ERIqIiIiIXks3btzAZ599BkEQAAAuLi7o27cvhg0bBnd3dydHR3kdi00QERER0WupTJky6NatGwDg7bffxoEDBxAWFsYkimzCESkiIiIiKvAEQcDBgwfRpEkTuLj87yPwuHHj0KhRI7Rt25bT+MguHJEiIiIiogLt2rVr+Oijj9CzZ0+sW7fO6piPjw/atWvHJIrsxkSKiIiIiAqk5ORkREREoHnz5jh27BgAYM6cOUhISHBuYFQgcGofERERERUogiBg586dmD59utUeUEFBQQgPD4eXl5cTo6OCgokUERERERUYV69eRVhYGI4fPy62KZVKDBgwAAMHDoSrq6sTo6OChIkUEREREeV7giAgIiICq1atgtlsFttbtGiBqVOnIiQkxHnBUYHERIqIiIiI8j2JRAKj0SgmUSEhIQgPD0fz5s2dHBkVVEykiIiIiKhAGDVqFPbv348uXbqgf//+UKlUzg6JCjAmUkRERESUryQkJGDOnDkIDg7G559/LrZ7enriyJEjUCgUToyOXhd2J1KnTp165Tm1a9fOUjBERERERC9isViwefNmzJgxA/Hx8VCr1Wjfvj2KFi0qnsMkinKLTYlUQkICvL29AQA9evQQNywTBAEArH6XSCS4cuVKDoRKRERERK+r8+fPY+LEiTh79qxV+z///GOVSBHlFpsSqRYtWqBnz54YNGgQ2rRpgz179qBy5coYOHAg3NzccjpGIiIiInpNxcfHY9asWdi4caP4JT4AvPvuu5g8eTKKFSvmxOjodSa15aT169dj2bJlePLkCebPn48NGzbAbDZj0qRJePDgAerUqWP1HxERERFRdpjNZnz77bdo2LAhvvvuOzGJKlu2LDZv3ozly5cziSKnsimR8vX1hcViQXJyMgCgVq1a2L59OwYMGIBZs2ahS5cuuHTpUo4GSkRERESvjzVr1mDChAlISEgAALi7u2Py5MnYt28f3n77becGRwQbE6mwsDBUrFgRJUqUENskEgm6deuGX3/9FZUqVULXrl0xadIkxMfH51iwRERERPR66Natm7j2qVOnTjh69Cg+//xzyOVyJ0dGlMamNVINGjTAe++9BwAYP358pueULVsWW7Zswb59+3DixAnHRUhEREREBZrJZMLFixdRvXp1sc3NzQ1z586Fq6sr3nrrLecFR/QCNiVSPXr0EH9+WZLEeapEREREZI8TJ05g4sSJuHXrFn777TcUL15cPNakSRPnBUb0CnbvI3Xo0KGciIOIiIiIXiMxMTGIiIjA9u3bxbbw8HCsXr3aiVER2c7uRIqIiIiIKKuMRiPWrFmD+fPni4XMAKBKlSro37+/EyMjso/diVSzZs1eelwikeDAgQNZDoiIiIiICqY//vgDYWFh+O+//8Q2b29vjB07Fh9//DFkMpkToyOyj92JlEajQXJyMipWrIhy5crlRExEREREVIDEx8dj4sSJ2LVrl9iWXgF63Lhx8PHxcWJ0RFljdyK1b98+zJ07F7t27UK1atUwbNgweHl55URsRERERFQAuLq64ty5c+LvNWrUQEREhFWVPqL8xqZ9pJ7l4+ODGTNm4Pvvv8eVK1fQqlUrbNq0SdxtmoiIiIjoWa6urggPD4ePj4/4hTyTKMrv7E6k0lWpUgWbNm3C2LFjERkZiU6dOuHMmTOOjI2IiIiI8pn79+/jiy++wI0bN6zaW7RogePHj+Ojjz6CVJrlj6BEeYbdU/tOnTpl9XtQUBCmT5+OqKgodO/eHW3btsXcuXMdFiARERER5X06nQ4rVqzA4sWLodPpkJiYiA0bNkAikQBIWxPl7u7u5CiJHMfuRKpHjx7iG0IQBKufAWD37t1MpIiIiIheIwcPHsTkyZNx+/Ztse3ixYt49OgRihYt6rzAiHKQ3YnUunXrciIOIiIiIspnoqOjMWXKFOzfv19sk8lk6NWrF0aNGgVPT08nRkeUs+xOpOrUqfPCY0ajEXFxcXjw4AEAQKFQwNfXN+vREREREVGek5qaiqVLl2LZsmXQ6/Vie926dREREYEKFSo4MTqi3JHtNVLPun79OqZNmyb+Xq1aNWzatClrkRERERFRntS3b18cPnxY/D0gIACTJk1Cx44dxWUfRAVdttZIPS99zdSBAwcApI1IEREREVHBkp5Iubi4oE+fPhg+fDgLSdBrx6FrpK5du4aIiAgEBgZmKygiIiIiyhu0Wi0SEhJQrFgxsa1x48YYM2YMWrdujbJlyzoxOiLncegaKaVSma1giIiIiChvEAQBu3fvRnh4OEqUKIEtW7ZYzUoaOnSoE6Mjcj7uhkZEREREVq5du4aPPvoIn3/+OR48eIDjx49j586dzg6LKE+xe0SKiIiIiAqm5ORkLFy4EKtWrYLJZBLbmzZtiqpVqzoxMqK8x+5E6pNPPnnhseTk5GwFQ0RERES5TxAE7Ny5E9OnT8ejR4/E9uLFiyM8PBwtW7ZkNT6i59idSAmC8MJjbm5uqFWrVrYCIiIiIqLc899//2HChAk4fvy42KZUKjFgwAAMHDgQrq6uToyOKO+yO5Fav379S4/rdLosB0NEREREuSs+Pt4qiWrRogWmTp2KkJAQ5wVFlA/YXWyicePGuHTpUqbH9u/fjzZt2mQ7KCIiIiLKHXXr1sV7772HEiVK4Ntvv8XatWuZRBHZwO5EqlChQpg1axaOHTsmtsXGxqJfv34YPHgwKlasmOVgVqxYgR49erz0nKdPn2LkyJGoXbs26tSpg/DwcKSmpmb5PomIiIheFxcvXsSECRNgsVis2iMiInDo0CE0b97cSZER5T92T+1buXIlli1bhqFDh8Lf3x+zZs3C8OHDIZVKsXz5cjRp0iRLgXz33XdYuHDhK9dYDRkyBKmpqVi7di0SExMxceJEaLVafPXVV1m6XyIiIqKCLiEhAbNnz8b69ethsVhQrVo1dOnSRTzu7e3tvODotWaxCIjTGKHVm6FWyuDnJYdUmj8Km9idSPn7+2Pq1KkYNWoUIiMj8cknn6B+/fpYsGBBlhYjxsTEYMqUKThx4sQrh5HPnj2LkydPYs+ePShdujQAYNq0aejTpw9GjBiBgIAAu++fiIiIqKCyWCzYuHEjZs6cifj4eLF98+bN+PDDD1mJj5zqTqwOf17S4G6cDgajAIVcguJ+KtSv5IVgf5Wzw3sluxOpHTt2iD+HhITAYDCgbNmy+PXXX8X2jh072ny9S5cuQS6XY9euXVi6dCnu37//wnNPnz4NPz8/MYkCgDp16kAikeDMmTNcn0VERET0/65du4awsDBcuHBBbFOr1Rg+fDj69OnDJIqc6k6sDjv/eAyN1gh/LwWUCin0BguuP9AiLsGIDg1883wyZXciNW7cuAxtK1euFH+WSCR2JVKhoaEIDQ216dyYmBgULVrUqk2hUMDb2xsPHz60+T6JiIiICqr4+HhERETghx9+sNq2pn379pg0aRKKFSvmxOiI0qbz/XlJA43WiBL+KjGpV6tkKKFUITpWh+OXNQjyVebpaX52J1IHDx7MiThskpqaCoVCkaFdqVRCr9dn+bqCIECr1WYntBdKL4TBghj5A/sr/2Gf5T/ss/yHfZZ/aDQatGjRAk+fPhXbypQpgylTpqBu3boAkGOfeSh7Xqf3WWyCEbcfpqCQmwwmkynD8UJqCW49SMGdR4nw95bnamyCINg8Wmt3IhUYGPjKO88pKpUKBoMhQ7ter4darc7ydY1GI65cuZKd0F7p9u3bOXp9ciz2V/7DPst/2Gf5D/ssf6hVqxb2798PV1dXdOvWDW3btoWLi0uOf9Yhx3gd3mePNMDjeClgBFIyyVksFuBJMnDp6lM88cr9+DIbuMmM3YkUAOzZswcnT56EwWAQE6f0UZ1z587h6NGjWbnsKxUpUgQHDhywajMYDEhISIC/v3+WryuXy1GmTJnshpep1NRU3L59GyEhIdwZPB9gf+U/7LP8h32W/7DP8q4nT57A29sbMplMbJs+fTq8vLzQrl07vPnmm+yzfOJ1ep8VTjDin0dP4KGWQa3MuBuTVmcGFBZUKl8410ekrl+/bvO5didSkZGRiIyMhIeHB0wmE+RyOVxcXBAfHw+pVIoPPvjA3kvarHbt2pg7dy6io6NRokQJAMDJkycBADVr1szydSUSSbZGtGzh6uqa4/dBjsP+yn/YZ/kP+yz/YZ/lHSaTCevWrcOcOXMwduxY9OrVSzymVqsxc+ZMXLlyhX2WD70OfRasEhBSVIfrD7TwdFNYTaUTBAFPtSa8EeiG4CKeub5Gyp4iLHZvyPvjjz+iY8eOOHnyJHr16oWmTZvizz//xNatW+Ht7Y033njD3ku+kNlsRlxcHHQ6HQCgWrVqePPNNzF8+HBcuHABf/31FyZPnoyOHTuy9DkRERG9Fk6cOIF33nkHkyZNQmJiImbPno0nT544Oywim0mlEtSv5AUvtRzRsTqk6MwwWwSk6MyIjtXBy02OehW98nShCSALiVRMTAzeffddSCQSVKhQAWfPngUAVK5cGf3798eWLVscFtzDhw/x9ttvY8+ePQDSMsTIyEgEBQWhZ8+eGDZsGBo1aoSpU6c67D6JiIiI8qKYmBgMHjwYnTp1slrv9M4777CUOeU7wf4qdGjgizLF1EjUmnD/sR6JWhPeCFSjQ/28X/ocyMLUPrVaLb5ZS5QogXv37kGn00GlUqFChQq4d+9eloOZNWuW1e9BQUH4999/rdoKFy6MxYsXZ/k+iIiIiPITo9GINWvWYP78+UhOThbbq1Spgi+//DJbyxuInCnYX4UgXyXiNEZo9WaolTL4ecnz/EhUOrtHpKpUqSJuyluyZEnIZDIcP34cAHDjxg2bq1wQERER0cv98ccfaNmyJaZNmyYmUd7e3pg5cyZ2797NJIryPalUgoBCCpQs4oqAQop8k0QBWRiR6t+/P3r37o3ExEQsX74c7du3x9ixY/HWW2/h999/R/PmzXMiTiIiIqLXzp49e/Dff/8BSFvi0K1bN4wbNw4+Pj5OjoyI7E6kateuja1bt4pT7iZPngypVIq///4b77zzDsaNG+fwIImIiIheR6NHj8ZPP/2E4OBgfPnll6hWrZqzQyKi/5elfaTKly+P8uXLAwCUSiWmT5/u0KCIiIiIXjdHjhxBXFwcOnfuLLZ5e3tjx44dCAkJgVRq94oMIspBWUqkiIiIiMgx7t27h/DwcOzZswfu7u5o2LCh1bYupUqVcmJ0RPQi/GqDiIiIyAl0Oh0WLlyIxo0bi1u9JCcnY+PGjU6OjIhswREpIiIiolx24MABTJkyBbdv3xbb/Pz8MHHiRKupfUSUdzGRIiIiIsol0dHRmDx5Mg4cOCC2yWQy9O7dGyNHjoSnp6cToyMie9g9tW/+/Pl49OhRpse0Wi2++uqrbAdFREREVNAcOXIETZs2tUqi6tati19//RXh4eFMoojyGbsTqc2bN+Onn36CIAhW7Xv27ME777yDrVu3Oiw4IiIiooKiZs2aKFSoEACgSJEiWLp0KbZu3YoKFSo4OTIiygq7E6kpU6Zg7dq1aNSoEZYuXQqTyYTx48djxIgRePPNN7F79+6ciJOIiIgoX0lOTrb63d3dHVOmTMEXX3yBI0eOoGPHjpBIJE6Kjoiyy+41Um3atEHz5s2xa9curFq1CgcPHkRMTAxWrFiBxo0b50SMRERERPmGVqvFokWLsH79euzfvx+BgYHisfbt26N9+/ZOjI6IHCVL5c8VCgU6d+6MdevW4fLly5g4cSKTKCIiInqtCYKAn376CY0aNUJkZCQ0Gg3Cw8OdHRYR5RC7R6TKly+fYRh65MiRGDlyJABAIpHg8uXLjomOiIiIKB+4du0awsLC8Pvvv4ttCoUCpUqVgsVigVTKrTuJChq7E6mBAweKiZTRaMTKlSvx7rvvIjg42OHBEREREeVlycnJWLBgAVavXg2TySS2N23aFNOmTUOpUqWcGB0R5SS7E6nBgwcDSBu+Xrt2LYC0/Q+eTbCIiIiICjJBELBjxw5Mnz4dMTExYnvx4sURHh6Oli1b8nMRUQFn9zizTqfDqlWr0KxZMyxfvhwLFy7EwYMH0a1bN/z33385ESMRERFRnqLT6TBr1iwxiVIqlRgxYgQOHz6MVq1aMYkieg3YnUj17t0bP//8M7744gscOnQIrVq1woYNG6DVatGpUyduyEtEREQFnqurK6ZOnQoAaNmyJQ4fPoyRI0fC1dXVuYERUa6xO5G6cOECJk6ciA8++ABubm4AgLJly2L79u0YOXIkfvjhB4cHSUREROQsFosFW7Zswa1bt6za33nnHezcuRPffPMNSpQo4aToiMhZ7F4jdeHCBchksgztMpkMvXv3Rtu2bR0SGBEREZGzXbx4ERMnTsTp06fRrFkzrFu3TjwmkUhQq1YtJ0ZHRM5kdyIlk8lw4cIFnDhxAgaDAYIgAEhbdKnVanHmzBmOShEREVG+lpCQgNmzZ2P9+vWwWCwAgIMHD+Ls2bOoUaOGk6MjorzA7kTqu+++Q0REhJhAPUsqleLtt992SGBEREREuc1isWDTpk2YOXMm4uPjxfbSpUtj+vTpTKKISGT3GqkNGzagUaNGOHHiBD799FN8+OGHOHfuHBYtWgSlUon27dvnRJxEREREOer8+fNo3749Ro8eLSZRarUaEyZMwIEDB9C4cWMnR0hEeYndidS9e/fQrVs3eHl5oXLlyjhz5gxUKhVatWqFfv36Wc0dJiIiIsoPFixYgLZt2+Ls2bNiW/v27XHkyBEMHDgQCoXCidERUV5kdyIll8uhUqkAACVKlEB0dDSMRiMAoGbNmrh9+7ZDAyQiIiLKadWqVROXLZQtWxY//PADoqKiUKxYMSdHRkR5ld2JVIUKFXD48GEAQMmSJWGxWHD+/HkAwKNHjxwbHREREVEOSP8SOF1oaCjef/99TJ48Gfv27UODBg2cFBkR5Rd2F5vo3bs3Bg0ahMTERMyYMQPNmjXDmDFj0LJlS/z000+oWbNmTsRJRERElG2PHz/GjBkz8ODBA3z//feQSCTiscWLFzsxMiLKb+wekWrevDmWL1+O0qVLAwCmTZuGkJAQbNq0CaVKlcKkSZMcHiQRERFRdphMJqxZswYNGzbE5s2bcezYMfz888/ODouI8jG7R6QAoEmTJmjSpAkAoFChQlizZo0jYyIiIiJymBMnTmDixIm4cuWK2Obp6QmdTufEqIgov8tSIvUiV69excCBA8XfK1asiCVLljjyLoiIiIhsEhMTg4iICGzfvt2qvUuXLhg/fjz8/PycFBkRFQR2J1LNmjV74TGDwSDOPQYAHx+frEdGRERElAVGoxFr1qzB/PnzkZycLLZXqVIFERERqFWrlhOjI6KCwu5E6v79+2jcuHGmSVJ8fDyOHj2K9957zyHBEREREdnr3LlzmDZtmvi7t7c3xo4di48//hgymcyJkRFRQZKlqX0DBw5E1apVM7SfO3cOR48ezXZQRERERFlVu3ZtdOjQAbt27UK3bt0wbtw4zpIhIoezu2rfyzxbQpSIiIgopxkMBmzevFncTDfdpEmT8PPPP2P27NlMoogoRzi02AQRERFRbjly5AjCwsJw8+ZNyGQydO7cWTxWtGhRFC1a1InREVFBl6VEqlu3blAqlfD09ERgYCDKly+Pt99+G56eno6Oj4iIiMjKvXv3EB4ejj179ohtM2fORPv27aFQKJwYGRG9TuxOpH799VfodDqkpqbi4cOHuH//Pv7++2+MGjUKUqlDZwoSERERiXQ6HZYvX44lS5ZY7QFVu3ZtREREMIkiolxldyJVokQJ8efq1auLP6empiIqKgorV64US6RzHykiIiJyhAMHDmDKlCm4ffu22Obn54ewsDC8//77XKdNRLkuy2ukEhMTce7cOSQlJcHHxwdVqlRBr169ULJkSfEcLu4kIiKi7DCZTOjTpw/2798vtslkMvTu3RsjR47ksgIicposJVIrV67EsmXLoNfrxSo5CoUCn3/+OQYOHOjQAImIiOj15eLigkKFCom/16tXDxEREShfvrwToyIiykIitW3bNsyfPx+dO3dG+/bt4evri7i4OOzcuRORkZEoVqwYN+QlIiKiLEn/gvbZqXoTJkzAuXPnMHToUHTo0IHT+IgoT7A7kVq7di0++ugjTJkyRWwrVaoU3nrrLahUKqxbt46JFBEREdntxo0bmDx5Mlq3bo3u3buL7X5+fjh06BATKCLKU+wusxcdHY3mzZtneqxZs2a4efNmtoMiIiKi14dWq8XMmTPRrFkz/Pbbb5g5cybi4+OtzmESRUR5jd0jUgEBAXjw4EGmx+7duwd3d/dsB0VEREQFnyAI+PnnnxEeHo6HDx+K7Wq1Gnfv3mXRKiLK0+wekQoNDcWiRYtw4cIFq/bz589jyZIlCA0NdVhwREREVDBdu3YNXbt2Rf/+/cUkSqFQYMiQIThy5AiqVavm5AiJiF7O7hGpwYMH488//0SXLl0QGBgIX19fPH78GPfv30fp0qUxcuTInIiTiIiICoDk5GQsWLAAq1evhslkEttDQ0MRHh6OUqVKOTE6IiLb2Z1Iubu7Y+vWrdi2bRtOnToFjUaDKlWq4NNPP0WnTp2gUqlyIk4iIiIqABYuXIjly5eLvxcvXhzTpk1DixYtuA6KiPKVLO0jpVQq0a1bN3Tu3BmJiYnw8vKCXC53dGxERERUwAwcOBCbNm2CVqvFwIEDMWDAALi6ujo7LCIiu2UpkTp69CiWLVuGCxcuQBAEyGQy1KxZE0OHDsWbb77p6BiJiIgoH9JoNLh8+TLq1asnthUqVAhLly5FSEgISpQo4cToiIiyx+5E6tdff8WwYcNQvnx5DBo0CIULF0ZcXBz27duHTz75BGvXrkWtWrVyIlYiIiLKBywWC7Zu3Yovv/wSer0eR48ehb+/v3i8cePGToyOiMgx7E6kli5dilatWmHhwoVW7YMGDcLgwYMxb948fP/9946Kj4iIiPKRixcvYuLEiTh9+rTYNnv2bMydO9eJUREROV6WNuTt3Llzpsc+/PBDXLlyJdtBERERUf6SkJCACRMmoHXr1lZJVJs2bTBs2DDnBUZElEPsTqRKly6Nf/75J9Njt27dQlBQULaDIiIiovzBYrFg48aNaNiwIb799ltYLBYAaZ8XNm7ciFWrVvGzAREVSHZP7Zs6dSr69+8PiUSCjh07wt/fHwkJCThw4AAWL16MqVOn4sGDB+L5xYoVe+n1LBYLIiMjsWXLFiQlJaF27dqYPHkyihcvnun5T548wYwZM/DHH39AEATUr18f48aNQ0BAgL0PhYiIiLIhOjoaAwcOxNmzZ8U2tVqN4cOHo0+fPlAoFE6MjogoZ9mdSH344YcA0vaBWLRokdguCAIAYPTo0Vbnv2qq37Jly7Bx40bMmjULRYoUwZw5c9CnTx/89NNPmf4DPGzYMJhMJnzzzTcQBAHh4eEYOHAgtm7dau9DISIiomzw8fHBvXv3xN87dOiAsLCwV36JSkRUENidSM2YMcNhG+YZDAasWbMGo0aNQpMmTQAACxYsQMOGDbFv3z60a9fO6vzExEScPHkSUVFRqFChAgCgX79+GDBgABISEuDt7e2QuIiIiOjVPDw8EBYWhqVLlyIiIgINGjRwdkhERLnG7kSqU6dODrvzq1evIiUlxWp/CU9PT1SsWBGnTp3KkEipVCq4ublhx44dqFOnDgBg586dKFmyJDw9PR0WFxEREVm7evUqpk2bhqioKKsRp/fffx8dOnSAXC53YnRERLnP7kRqx44drzynY8eONl3r0aNHAICiRYtatfv7+4vHnqVQKDBr1ixMnjwZtWrVgkQigb+/PzZs2ACp1O66GURERPQKcXFxCA8Px48//ggAmDZtGpYvXy4el0gkTKKI6LVkdyI1btw4SCQScU3U89KLUNgiNTUVADKshVIqldBoNBnOFwQBV65cQY0aNdCnTx+YzWYsWLAAAwYMwPfffw93d3f7Hswz19VqtVm67aukP8b0/1Pexv7Kf9hn+Q/7LH8wmUz47rvvsGjRIiQlJYnt165dQ1xcHNzc3JwYHb0K32f5D/ssbxAEweZlTHYnUgCwZMkScY1SdqhUKgBpa6XSfwYAvV4PV1fXDOfv3bsXGzZswOHDh8Wkafny5WjatCm2bt2KXr16ZSkOo9GY4/tf3b59O0evT47F/sp/2Gf5D/ss77p48SJWrFiB6Ohosc3NzQ0ff/wxWrdujTt37jgxOrIH32f5D/vM+WytOJqlRMrf3x+BgYFZuamV9Cl9sbGxCA4OFttjY2NRrly5DOefPn0aJUuWtBp58vLyQsmSJa3+sbeXXC5HmTJlsnz7l0lNTcXt27cREhKSaXJIeQv7K/9hn+U/7LO8KyYmBl999RV++uknq/b33nsP7733HqpXr84+yyf4Pst/2Gd5w/Xr120+N0uJlKOUL18e7u7uOHHihJhIJSYm4vLly+jevXuG84sUKYLdu3dDr9dDqVQCALRaLe7du4f27dtnOQ6JRAK1Wp3l29vC1dU1x++DHIf9lf+wz/If9lneIggCPvvsM/z7779iW5UqVfDll1+iQoUKuHLlCvssH2Kf5T/sM+eypzq5Uys0KBQKdO/eHXPnzsXBgwdx9epVDB8+HEWKFEHLli1hNpsRFxcHnU4H4H9FLIYNG4arV6/i6tWrGDFiBJRKpUOrCRIREb1uJBIJRowYAQDw9vbGrFmzsHv3btSsWdPJkRER5U1ZGpHq0qXLC49JJBJcvnzZ5msNGTIEJpMJYWFh0Ol0qF27Nr7++mvI5XLcu3cPzZo1w8yZM9GpUyf4+/tj48aNmDNnDnr27AmpVIpatWph48aN8PDwyMpDISIiei09ePAAAKxKmbdt2xZTp07F+++/Dx8fH2eFRkSUL9idSA0aNMihAchkMowePRqjR4/OcCwoKMhqigEAlC5d2qrsKhEREdlOr9dj1apVWLhwIRo2bIhvvvlGPCaRSNC3b18nRkdElH84PZEiIiKi3PHbb79h0qRJuHnzJgBg3759OHToEEJDQ50cGRFR/uPUYhNERESU8+7evYvw8HDs3btXbJNKpejZsyfefPNNJ0ZGRJR/MZEiIiIqoHQ6HaKiohAZGSkWbgKA2rVrIyIiApUrV3ZidERE+RsTKSIiogLo2LFjGDt2rNU+i35+fggLC8P7779vV4lfIiLKiIkUERFRAaTT6cQkSiaToXfv3hg5ciQ8PT2dHBkRUcHARIqIiKgAatGiBZo3b46UlBRERESgfPnyzg6JiKhAsTuRGj9+/EuPSyQSzJgxI8sBERERke0EQcCvv/6KAwcOYM6cOVZT9pYuXQo3NzdO4yMiygF2J1I//vgjZDIZihQpAkEQMhznP9ZERES548aNG5gyZQoOHz4MAAgNDUWbNm3E4+7u7s4KjYiowLM7kWrZsiWOHj0KqVSKNm3aoG3btihbtmxOxEZERESZ0Gq1WLRoEVasWAGj0Si279+/3yqRIiKinGN3IrV48WJotVocOnQIe/bsQefOnREcHIzWrVujXbt2KFGiRE7ESURE9NoTBAE///wzwsPD8fDhQ7G9WLFimDJlCtq2bevE6IiIXi9ZKjahVqvRrl07tGvXDsnJydi/fz/27NmDqKgolC1bFtu3b3d0nERERK+1a9euISwsDL///rvYplAo8Pnnn2PIkCFQq9VOjI6I6PWT7ap9t27dQnR0NB49egSz2QypVOqIuIiIiOj/RUdHo3nz5jCZTGJbaGgowsPDUapUKSdGRkT0+rI7kTIajfjrr79w8OBBHDx4EE+fPkWdOnXQtWtXNG/eHAEBATkRJxER0WurRIkSeOedd/Dzzz+jePHiCA8PR8uWLVngiYjIiexOpOrWrQuJRIJGjRph3LhxaNy4MasCEREROdCNGzdQqlQpq0Rp8uTJKF++PPr37w9XV1cnRkdEREAWEqmUlBQAwJ49e7B3794MxyUSCS5fvpz9yIiIiF4zGo0G8+bNw9q1a7Fw4UJ06tRJPBYYGIjhw4c7MToiInqW3YnUoEGDciIOIiKi15bFYsHWrVvx5Zdf4vHjxwCA6dOno0WLFvDw8HBydHmTxSIgTmOEVm+GWimDn5ccUimnOhJR7mEiRURE5EQXL17EhAkTcObMGbFNpVKhd+/eUCgUTows77oTq8OflzS4G6eDwShAIZeguJ8K9St5Idhf5ezwiOg1keWqfUeOHMGff/6JuLg4DB8+HFeuXEGlSpUQGBjoyPiIiIgKpKdPn2L27NnYsGEDLBaL2N6mTRtMnTqVf09f4E6sDjv/eAyN1gh/LwWUCin0BguuP9AiLsGIDg18mUwRUa6wO5FKTU3FwIED8eeff8Ld3R0pKSn47LPP8P333+Py5cvYsGED3njjjZyIlYiIqEDYuHEjZsyYgadPn4ptpUuXRkREBBo1auTEyPI2i0XAn5c00GiNKOGvEotxqFUylFCqEB2rw/HLGgT5KjnNj4hynN2bPs2fPx+XLl3C2rVr8ddff0EQBADAV199hYCAACxatMjhQRIRERUkx48fF5MotVqNiRMn4sCBA0yiXiFOY8TdOB38vRQZSr9LJBL4eSlwJ1aHOI3RSRES0evE7kRq7969GDFihFgGPZ2/vz+++OILqzneRERElFFYWBg8PDzQvn17HDlyBAMGDOB6KBto9WYYjAKUisw/vqgUUhhNArR6cy5HRkSvI7un9iUmJr5w3raXlxe0Wm22gyIiIioIzGYzNmzYAE9PT7z33ntie0BAAI4cOcJN7O2kVsqgkEugN1igVskyHNcZLJC7SKBWZjxGRORodo9IvfHGG/jpp58yPXbo0CGujyIiIgJw+vRptGnTBhMmTMDkyZOt1kMBYBKVBX5echT3UyFWYxCXFqQTBAFxGgOC/VXw85I7KUIiep3YPSL1xRdfYNCgQUhISEDTpk0hkUhw6tQpbN++HZs2bcK8efNyIk4iIqJ8IS4uDjNmzMAPP/wgtsXHx+PAgQP44IMPnBhZ/ieVSlC/khfiEoyIjtXBz0sBlUIKncGCOI0BXm5y1KvoxUITRJQr7E6kmjdvjjlz5mDevHk4cuQIAGDWrFkoXLgwpk6dinfeecfhQRIREeV1JpMJ3377LebOnYvExESxvWLFivjyyy9Rp04dJ0ZXcAT7q9Chga+4j9STRAFyFwneCFSjXkXuI0VEuSdL+0i9++67ePfdd3Hz5k0kJCTA09MTpUqVglRq90xBIiKifO+vv/5CWFgYrly5IrZ5eXlhzJgx6N69O1xcsrxtI2Ui2F+FIF8l4jRGaPVmqJUy+HnJORJFRLkqW/+ylypVCgBw+fJlrF+/HjVq1EDVqlUdEhgREVF+sGnTJowcOdKqrWvXrhg/fjx8fX2dFFXBJ5VKEFCIlQ6JyHmy/RXZgQMHMGzYMJhMJshkMixcuBAtWrRwRGxERER5XsuWLeHt7Y2EhARUqVIFX375JWrWrOnssIiIKIdley7e8uXL0a5dO5w+fRqtWrXCihUrHBEXERFRnhQbG2v1u4+PD6ZOnYpZs2Zh9+7dTKKIiF4T2U6k/vvvP7Rv3x7u7u549913cevWLUfERURElKfcv38fn3/+OZo0aYLHjx9bHfvggw/Qo0cPyGTcv4iI6HWRrUTKYrHAYDDA09MTAODt7c0NeYmIqEDR6/WIjIxE48aN8fPPP0Oj0WDmzJnODouIiJwsW2uk0jfDS6/Wx6p9RERUkPz222+YNGkSbt68Kbb5+PiwlDkREdmfSDVr1ixDW//+/SGXy2EwGBwSFBERkTPdvXsX4eHh2Lt3r9gmlUrRs2dPjBo1Ct7e3s4LjoiI8gS7E6n79++jcePG8PHxyYl4iIiInEan0yEqKgqRkZHQ6XRie506dRAREYFKlSo5MToiIspLsjS1b+DAgdwvioiIChy9Xo+1a9eKSZSfnx/CwsLw/vvvQyLhZq9ERPQ/XNRERET0/7y8vDBhwgTIZDL07dsXx44dQ+fOnZlEERFRBjaNSN24cQOlS5cGAFy9elVsO3nyJJKSkuDr64sGDRogICAg5yIlIiJyoNTUVERFReGjjz5C0aJFxfYPPvgAtWrVEv/uERERZcamRKpz5844duwY3N3dIQgCJk+ejK1bt4pV+wBAJpOhT58+GD58eI4FS0RElF2CIOCXX37B1KlTce/ePdy4cQNLly4Vj0ulUiZRRET0SjZN7UtNTcXdu3cBAFFRUdixYwfGjBmDI0eO4MKFC9i7dy969+6NVatWYeXKlTkaMBERUVbduHED3bt3R58+fXDv3j0AwO7du8W/cURERLayudiE0WgEAGzduhWDBw9G7969xWMlS5bEqFGjIJPJsHnzZvTr18/xkRIREWWRVqvFokWLsGLFCvHvGQA0bNgQERERKF68uBOjIyKi/MimESlXV1fo9XoAwOPHj1G5cuVMz6tTpw4eP37suOiIiIiyQRAE/PTTT2jUqBEiIyPFJKpYsWJYuXIlvv/+e5QpU8bJURIRUX5kUyIVHByM+/fvAwDeeOMNnD59OtPzTp8+DX9/f8dFR0RElA3Dhg1D//798fDhQwCAQqHAkCFDcOTIEbRt25bV+IiIKMtsSqTatm2LNWvWICEhASNHjsTXX3+NyMhI3L17FwaDAY8ePcLKlSuxatUqdOzYMYdDJiIisk1oaKjVzwcPHsTYsWOhVqudGBURERUENq2R6t27N86dO4dmzZqhRo0aKFq0KCIjI62qHAHARx99hAEDBuRIoERERC8jCAK0Wi3c3NzEtvbt2+PIkSN455130KJFC45AERGRw9iUSMnlcixbtgyXL1/GyZMncf/+fdSqVQsSiQRubm4oVqwYGjRowHKxRETkFJcvX0ZYWBh8fHywevVqsV0ikWD+/PlOjCxnWCwC4jRGaPVmqJUy+HnJIZUySSQiyk02V+0DgIoVK6JixYo5FQsREZFdNBoN5s2bh7Vr18JsNgMAfvvtNzRp0sS5geWgO7E6/HlJg7txOhiMAhRyCYr7qVC/kheC/VXODo+I6LVhVyKV7tatW1i8eDFOnjyJxMREFCpUCLVq1cKAAQNY/YiIiHKcxWLBli1bMGPGDKtqsSEhIVAoFE6MLGfdidVh5x+PodEa4e+lgFIhhd5gwfUHWsQlGNGhgS+TKSKiXGJ3InX9+nV07doVMpkMoaGh8PX1RVxcHA4fPozffvsNW7Zs4RQ/IiLKMf/88w8mTpyIM2fOiG0qlQpDhw7F559/DqVS6cToco7FIuDPSxpotEaU8FeJ673UKhlKKFWIjtXh+GUNgnyVnOZHRJQL7E6k5s6di6CgIKxfvx4eHh5ie1JSEnr27IkFCxYgMjLSoUESERE9ffoUs2fPxvr16yEIgtjetm1bTJkyBYGBgU6MLufFaYy4G6eDv5ciQ9EMiUQCPy8F7sTqEKcxIqBQwR2VIyLKK2wqf/6sU6dOoX///lZJFAB4eHigX79+OHXqlMOCIyIiSnfq1CmsW7dOTKJKly6N77//HitXrizwSRQAaPVmGIwClIrM/3SrFFIYTQK0enMuR0ZE9HqyO5FycXF54bQJhUIBg8GQ7aCIiIie16JFC4SGhkKtViMsLAwHDhxAo0aNnB1WrlErZVDIJdAbLJke1xkskLtIoFbKcjkyIqLXk92JVJUqVbBx40araRVA2v4d3333HSpXruyw4IiI6PUUHx+P1atXW/2tkUgkmDlzJo4ePYovvviiQBeVyIyflxzF/VSI1Rgy/RscpzEg2F8FPy+5kyIkInq92L1GaujQofjoo4/Qvn17vPPOO/Dz80NcXBx++eUX3Lp1C998801OxElERK8Bs9mMDRs2YPbs2UhISEDx4sXRqlUr8XhQUJATo3MuqVSC+pW8EJdgRHSsDn5eCqgUUugMFsRpDPByk6NeRS8WmiAiyiVZGpFavXo1VCoVIiMjMXnyZERGRkKlUmHVqlWoXbu2XdezWCxYvHgxGjZsiOrVq6Nv3764e/fuC883Go2YN2+eeH737t1x5coVex8GERHlMadPn0abNm0wYcIEJCQkAADmzJmTYfTldRbsr0KHBr4oU0yNRK0J9x/rkag14Y1ANTrUZ+lzIqLclKV9pOrWrYstW7YgNTUViYmJ8PT0hKura5YCWLZsGTZu3IhZs2ahSJEimDNnDvr06YOffvop02kbU6dOxW+//YZZs2ahWLFiWLRoEfr27Yu9e/dmKIBBRES5z2IREKcxQqs3Q62Uwc9L/tJRkri4OHz55ZfYsmWLVfv777+PsLCwDBXqXnfB/ioE+Srteo6JiMjxspRIpXN1dc1yAgUABoMBa9aswahRo8Rd6BcsWICGDRti3759aNeundX5d+/exbZt27B8+XI0bNgQABAREYGOHTvi4sWLqFevXpZjISKi7LsTq8OflzS4G6eDwShAIZeguJ8K9St5ZRgtMZlMWL16NebOnYukpCSxvWLFivjyyy9Rp06d3A4/35BKJSxxTkTkZNlKpLLr6tWrSElJsUqAPD09UbFiRZw6dSpDIvXHH3/Aw8PDqkqTp6cnDh06lGsxExFR5u7E6rDzj8fQaI3w91JAqZBCb7Dg+gMt4hKM6NDgf1PPtFotOnbsiH///Ve8vZeXF8aMGYPu3bvDxcWpf56IiIheye41Uo706NEjAEDRokWt2v39/cVjz7p16xaKFy+Offv2oVOnTmjQoAH69u2LGzdu5Eq8RESUOYtFwJ+XNNBojSjhr4JaJYNMKoFaJUMJfxU0WiOOX9bAYklb76RWqxEcHCzevmvXrjh69Ch69erFJIqIiPIFp/61Sk1NBYAMa6GUSiU0Gk2G85OTkxEdHY1ly5ZhzJgx8PT0RFRUFLp164Y9e/agcOHCWYpDEARotdos3fZV0h9j+v8pb2N/5T/ss7whNsGI2w9TUMhNBpPJlOG4p9KMm/eTceeRCh7KtOMjR47E06dPMXbsWFSvXh0AcuzfYsoevs/yH/ZZ/sM+yxsEQbB5ba5TEymVKm2Kh8FgEH8GAL1en+naKxcXFyQnJ2PBggUoXbo0gLQ1VY0bN8aPP/6IPn36ZCkOo9GY45X/bt++naPXJ8dif+U/7DPneqQBHsdLASOQ8tzfn7s3zuPwzuWoUL8rqhZtiCJeae0GgwGTJ08GAFZfzSf4Pst/2Gf5D/vM+Wzdp9DuRGr8+PEvPS6RSDBjxgybrpU+pS82NtZqikdsbCzKlSuX4fwiRYrAxcVFTKKAtGSsePHiuHfvnk33mRm5XI4yZcpk+fYvk5qaitu3byMkJCRbhTkod7C/8h/2Wd5QOMGIfx49gYdaBrUybdZ4QnwMfvlhMS6ePggAOH/4G5Qc8SECCinZZ/kM32f5D/ss/2Gf5Q3Xr1+3+VybEqm1a9eic+fOcHd3x48//giJRILChQtnmq3ZU6a2fPnycHd3x4kTJ8REKjExEZcvX0b37t0znF+7dm2YTCb8888/qFKlCgBAp9Ph7t27aNu2rc33m1nMarU6y7e3haura47fBzkO+yv/YZ85V7BKQEhRHa4/0EKtAH7ftxEHd66G0aATzynsVwRqFyNcXb0BsM/yI/ZZ/sM+y3/YZ85lTy5jUyJ18uRJ7Ny5E9u3b8eqVaswY8YM6HQ6jB49Gq1bt85yoAqFAt27d8fcuXPh4+ODwMBAzJkzB0WKFEHLli1hNpsRHx8PDw8PqFQq1KpVC/Xr18fYsWMxbdo0eHt7Y/HixZDJZOjQoUOW4yAiouyRSiWoX8kLJ/48ho2z50Lz+H8bq6vcvNG040CEjeiFkCJqroMiIqICwaaqfTNnzsTVq1cRHR2Nhg0b4qeffkKPHj0wadIk9OzZE9euXctyAEOGDEHnzp0RFhaGjz76CDKZDF9//TXkcjkePnyIt99+G3v27BHPX7JkCerUqYNBgwahc+fOSE5Oxrp16+Dj45PlGIiIKHvu3r2L8PED8cOyoWISJZFIUe3tzghbsAOTR32KkCL8hpWIiAoOm0akoqOjAaTt2QSkFX349NNP0b59e8ybNw/vvfceunbtiqFDh8LDw8OuAGQyGUaPHo3Ro0dnOBYUFGS1xwgAuLu7Y+rUqZg6dapd90NERDln/vz5+OWXX8Tfq9eohaGjJ6Na1Srw85JDKrV9qgQREVF+YNOI1KefforBgwdnGPXx9fXFzJkzsXHjRly4cAGtWrXCli1bciRQIiLKu8aOHQs3Nzf4+flh0aJF+PmnHWjZuCYCCimYRBERUYFk04jUoUOHxNGo8uXLZ7oISxDSNlmcPHkyPvjgAweGSEREecnt27dx584dNGrUSGwrUqQIvvnmG1SpUkX8e5EbLBYBcRojtHoz1EoZR7+IiCjX2JRIPftHceDAgXZVsyAiooIhNTUVkZGRiIqKgoeHB44ePQovLy/xeIMGDXI1njuxOvx5SYO7cToYjAIUcgmK+6lQv5IXgv1Vr74AERFRNti9j9TgwYNzIg4iIsqjBEHAL7/8gqlTp4p79un1ekRFRWHcuHFOielOrA47/3gMjdYIfy8FlAop9AYLrj/QIi7BiA4NfJlMERFRjrI7kXrw4MErzylWrFiWgiEiorzlxo0bmDRpEo4cOSK2yeVy9OvXz2lfrFksAv68pIFGa0QJf5U4S0KtkqGEUoXoWB2OX9YgyFfJaX5ERJRj7E6kQkNDXzi1TxAESCQSXLlyJduBERGR86SkpGDx4sVYsWIFjEaj2N6oUSNMnz4dZcqUcVpscRoj7sbp4O+lyPD3SCKRwM9LgTuxOsRpjAgolHHjeCIiIkewO5GaMWMG10gRERVgf//9N/r164eHDx+KbYGBgZg6dSpat27t9L8BWr0ZBqMApSLzwrMqhRRPEgVo9eZcjoyIiF4ndidSnTp1ytB24MABnDx5ErVr10aLFi0cEhgRETlHiRIloNVqAQAKhQL9+/fHkCFD4Orq6uTI0qiVMijkEugNFqhVsgzHdQYL5C4SqJUZjxERETmKTftIvcyuXbswaNAg7NixA0OGDOE+UkRE+Uz69hXpChcujNGjRyM0NBQHDx7E2LFj80wSBQB+XnIU91MhVmPIELsgCIjTGBDsr4Kfl9xJERIR0esg24nUunXr0Lt3b5w8eRJdunTBunXrHBEXERHlMEEQsH37djRv3hzx8fFWx3r16oV169ahVKlSToruxaRSCepX8oKXWo7oWB1SdGaYLQJSdGZEx+rg5SZHvYpeLDRBREQ5KtuJ1K1bt9CsWTMAaYUo0kvjEhFR3nXlyhV07twZgwcPxtWrVzFr1iyr4xKJxOlroV4m2F+FDg18UaaYGolaE+4/1iNRa8IbgWp0qM/S50RElPPsXiP1LIvFgpSUFHHKh6enJ3Q6nUMCIyIix9NoNJg3bx7Wrl0Ls/l/xRji4+NhNpshk+WfdUXB/ioE+SoRpzFCqzdDrZTBz0vOkSgiIsoV2Uqk0uemp39rmZe/vSQiep1ZLBZs2bIFM2bMwOPHj8X2kJAQTJ8+HaGhoU6MLuukUglLnBMRkVPYnUiVL18+Q8L0/vvvOywgIiJyrH/++QcTJ07EmTNnxDaVSoWhQ4fi888/h1KpdGJ0uctiETiCRUREDmF3IjVw4ECOPBER5RN6vR49evRAXFyc2Na2bVtMmTIFgYGBTows992J1eHPSxrcjdPBYBSgkEtQ3E+F+pW8uKaKiIjsZnciNXjw4JyIg4iIcoBSqcTYsWMxatQolC5dGhEREWjUqJGzw8p1d2J12PnHY2i0Rvh7KaBUSKE3WHD9gRZxCUZ0aMACFUREZB+7E6lTp0698pzatWtnKRgiIsqes2fPolixYggICBDbunTpAqlUivfeew8KRe6sJ8pLU+gsFgF/XtJAozWihL9KnFWhVslQQqlCdKwOxy9rEOSr5DQ/IiKymd2JVI8ePSCRSCAIQoYpfultV65ccViARET0ak+ePMGsWbPw/fff47333sOSJUvEY1KpFF26dMm1WPLaFLo4jRF343Tw91Jk+LslkUjg56XAnVgd4jRGFq4gIiKb2Z1IPbvhrtlsRu/evREeHo6SJUs6NDAiIno1s9mM9evXY86cOUhISAAAbN++Hb169ULNmjUdch/2jC7ZMoXO190hYdlMqzfDYBSgVGS+daJKIcWTRAFavTnT40RERJmxO5GqU6eO+HP6HiSVK1dGpUqVHBcVERG90unTpzFx4kRcvHhRbPPw8MDIkSNRtWpVh9yHPaNLtk6ha1s7dzMptVIGhVwCvcECtSrjPlk6gwVyFwnUyvyzhxYRETlftvaRIiKi3BcXF4cvv/wSW7ZssWrv3LkzJk6cCH9/f4fcj70FGmydQvdYk7vT+/y85Cjup8L1B1qUUKqsYhMEAXEaA94IVMPPS56rcRERUf7mkESK5dCJiHLH5s2bMWXKFCQlJYltFStWxIwZMxxa6CcrBRpsnUKXqrc4LE5bSKUS1K/khbgEI6JjdfDzUkClkEJnsCBOY4CXmxz1Knqx0AQREdnF7kTqk08+EX8WBAEAMGnSJLi5uQFIS6q+/fZbB4VHRETPUigUYhLl5eWFMWPGoHv37nBxcewEg6wUaLB1Cp2rUgqtQ6N9tWB/FTo08BWnKT5JFCB3keCNQDXqVeQ+UkREZD+7//KmJ0/p0r8BTW9//jgRETlOx44d8d133yEkJATjx49H4cKF7b6GLcUjslKgwdYpdL5eLnjy0O6wsy3YX4UgX2WeKctORET5m92J1Pr163MiDiIieobBYMCaNWtw7do1zJs3T2yXSCTYuHFjlveDsrV4RFYKNNg8hU6Su1P7niWVSljinIiIHILFJoiI8phjx44hLCwM169fBwB06NABjRo1Eo9nJ4mytXhEVgs02DKFTqvN7Yl9REREjmd3IlW+fPmXFpeQSCS4fPlytoIiInod3b9/H9OmTcPPP/8stkkkEpw/f94qkcoKe4tHZKdAA6fQERHR68DuRGrgwIHiH2Cz2YyoqCh8+OGHDiu3S0T0utHr9VixYgUWL16M1NRUsb1GjRqYMWOGQ/aEykrxiOwUaOAUOiIiKujsTqQGDx4s/pyeSHXp0oUb8hIRZcHhw4cxadIk3Lp1S2wrXLgwxo+fgCYtO0JnFBDz1JDtEZ2sFI8A8tboki1FMoiIiHIL10gRETnJqVOn0L17d/F3qVSKXr16oWuvwfjnjoANB2NeWhDCHlkpHvG/uJw/umRrkQwiIqLckvlXk0RElONq1aqFxo0bAwDq1KmDX375BX0HT8ShCwZcf6CFl9oFQX5KeKldcP2BFjv/eIw7sbos3Vd68YhYjSHDNhXpxSOC/VUZikfkBelFMhz9nBAREWWH3SNSkZGR4s+CIEAikWDz5s3iGimJRIKBAwc6LkIiogLizJkzqFmzpvi7RCLBtGnTcP78eXTq1AmCAPxwJNbmghD2THXLTvEIZ7K3SAYREVFuyVYile6HH34Qf2YiRURk7fbt25g8eTIOHjyItWvXokWLFuKxMmXKoEyZMgCA2ASDzQUh9EaL3VPdslM8whksFgGX76Tgyp0UeLtl/HP1oiIZREREucHuROrq1as5EQcRUYGTmpqKJUuWICoqCgaDAQAwZcoUNGzYECpVxqTFloIQjzUCzlxLxNnrydDpLQjyVUDlLXvhflDPy0vFI14mfU3UlTspuPEgFe6uMsQ8dUFxfxW8nkmqXlQkg4iIKKc5vNhEcnIy3N3dHX1ZIqJ8QxAE7N27F1OnTsX9+/fF9iJFimDs2LFQKpWZ3u5VBSHiEgy4/1iH6JhUaPUWuLtKYTRZxOTC1qlueaF4xMs8u3Gwt5sL3F2lcJFKEJ9kQopei/LF1WIy9bIiGURERDnJ7kTKYDDg22+/xcmTJ2Ew/G/RsiAI0Gq1uH79Os6fP+/wQImI8oPr169j8uTJOHLkiNgml8vRt29fDBs2DG5ubi+8bXpBiOsPtCihVFlN70tINuLS7RTIZBJIART2dIFUIkF8khEpOgvKB6clF/l9qtvza6IAIOapHPFJRniqZUjUWnA3TgdPddrzGKcx4I1AtVWRDJZJJyKi3GB3IjV79mxs2LABZcuWRXx8PJRKJXx8fPDff//BaDRi0KBBOREnEVGeZjab8dVXX2HlypUwGo1ie6NGjTB9+nRxHdTLvKggRKrejIu3UgAApYqqEP1ID7mLFFKJBF5uEmhSTGJykd+numW2cXBxfxVSdBYkas2Qu0iQkGwSE6Xni2SwTDoREeUWu8uf79u3D71798auXbvQvXt3VK5cGVu2bMG+ffsQGBgIi8WSE3ESEeVpMpkM165dE5OowMBArFq1Chs3brQpiUqXXhCiTDE1ErUm3H+sR5zGCJkMqBTiBh8PBWQywGz+XwlzuYsUcQlGxGmMSNWb8/VUt8zWiXm5uaB8sBo+HnKYLQJSUs3QpJjwRqAaHer/bz0Yy6QTEVFusntEKj4+Ho0aNQIAlC1bVqzYFxAQgH79+uGbb77hqBQRvZbCw8Px119/oXfv3hg8eDBcXV2zdJ3nC0I8STTil5NP4OetgFQCeKpdEJ9kglIuIElrhs5ogcFowcVbyVC4SFHjDY88uR+ULV60TszLzQWeIW54rDEiIcWEDxr7o2KwmzgSxTLpRESU2+xOpDw8PMTqUyVKlMDDhw/FAhMhISF4+PChw4MkIspLkpKSsGDBAtSsWRNt27YV24ODg3Hq1CmHFNx5tiCEWimDUiEVk4vi/io8TU7Gw3gDJABkMsBFBpgtgFZvwZ1YHc7fTEa1Uu55MmmwCAKepgDRMXr4eLtYrWF62ToxAEjRm1GxhJtVEgVkPiUwHcukExFRTrB7al+tWrWwfv16pKamokSJEnB1dcWBAwcAAGfPnmXFPiIqsARBwPbt29G4cWOsWLECU6ZMgVartTonJ/4NTE8uYjVpBX481TK4KtIq2cmkgMEoABIJJBJA7gJEx+iwes99bP4tJs9NZ7sTq8OPfzzFwUtSbDn2BOv2P8QPR2LFONPXiXmp5YiO1SFFZ06bzqczIzpW98KNg20pHW805d+1Y0RElPfYnUgNGjQI586dQ79+/eDi4oJu3bph0qRJ6NSpExYtWoRWrVrlRJxERE51+fJlvP/++xg8eDBiYmIAAE+fPsWZM2dy/L6fTy7iNEbojBb4eLpArZLBy90FHq4ukMvSpv0V9nSB0STgUnSKXWuDLBYBMU8NuPUoFTFPDbBYhFffyA7pa5huPtLBVQEUK6zIdA1TZuvEErUZ10Q969kpgZlhmXQiInI0u6f2lStXDnv37sV///0HABg5ciTc3d3x999/IzQ0FP369XN4kEREzqLRaDBv3jysXbsWZvP/RjNatWqFqVOnIjg4OFfiSE8u0jepTU41w91VCj9vBfQGi1jBTiKRwCII0BkEBHgroNEabVoblNPV7p5dw1TcV4HHjwGZVAKVPPM1TPZuHPyyKYGCIGRaJp2IiCg7srQhr5+fH/z8/ACkzT3v37+/Q4MiInI2i8WCLVu2YMaMGXj8+LHYXjw4BF9GTEOzZs1yPab05OLynRRsORILbzcXqJRSXLiZDDeVTEweTGYBMmlaNT9b1gbdjknF5sOxSEgxwt9LAT9fOQxGAdcfaBGXYESHBpmPAtnDeg2T9ajRi9Yw2bNx8ItKx+sMFsRpDC+cEkhERJRVdk/tA4Dff/8dM2fOxJYtW5CUlITPP/8cNWrUQL9+/RAfH+/oGImIct38+fMxYsQIMYlykSvx1jv90GHwWsRJKztt7ZFUKkHFYDdUCHZDit4Mo8kCsxmQydISBEEQoNVZ4OnmAjeV9JVrg24/SsXKnx/g0u1kPNEYce2+FlfvaGE0CyjhrxJHtLI7zS831jBlZUogERFRVtk9IrV582ZMmTIFhQoVgkajwZIlSyAIArp06YIff/wRs2fPxqxZs3IiViKiXNOtWzcsX74CqalalKrSBO27jYB/kWLQGywOHamxh8UiiFPdygapEfvUgLgEIwQIMJoskEgk0OosUCmkKO6XNr1N95J9pe7E6rD5t1jci9PDU502umU2C4hPMiFFr0X54mqHVbt7dg2TPJNlSo5aw2TvlEAiIqKssjuRWr16NQYNGoRBgwbh6NGj+PzzzxEZGYlmzZqhXLlymDdvXk7ESUSUY8xmM+7cuYOSJUuKbUWKFEX7HmOQYvHC2283dPq+RJmtYfJwdUGxwgrEJxnxJNEED1cZfDxdUNxPBS83l5euDRLXLKWYoJRLoFJKIZVIIHWRwMtNAk2KGXfjdChfXO2QanfPrmEqVsg6WXL0GiZ7pgQSERFlld2J1OPHj/Hmm28CAOrWrQtBEBAQEAAAKFKkCFJSUhwbIRFRFjw7evOyUYmzZ89i4sSJePjwIY4ePQoPDw8AaWt6ilZoCS+1i9P3JUqvdqfRpq1hSt9TKlZjgKerC96t54sz/yUh1WBGkK8SrkoZUnTml64NSl+z5Oclx9NkI8xmAVIXifj41CopElNMiE8yOWSk6Nk1THcf6yAxAmaLAMMr4iQiIsqr7E6kKlasiCVLlqBEiRIIDAy02nzyhx9+QEhIiKNjJCKyiy0V6J48eYJZs2bh+++/hyCkrf+ZN28epk6dCsC2NT1PEnN+X6Jnq92V8FdlOjKmSTHh4+YB+OtyIu7G6cTk541ANepVzLzqXvrj8/OVw0vtgvgkI7zcJOL1XWQSaHVpI0XVS3s4ZKQofQ3TkXOPcflGEh48McBVJX9pnERERHmV3YlUWFgY+vbtixkzZmDp0qXit7dhYWH45ZdfOLWPiJzqRaM36eua2tUthCO/bsHs2bOh0WjE25UrVw4tW7YUf392TY9alXE0Jrf2JbKudvfikbEm1Qrhw8b+GUbhACDmqSHDyFz64zMYBRT3VyFFZ4EmxQS1SgYXmQSpejN0Bgu83R07UhTsr8J7DQqhqCoGgcULw8fbjWuYiIgoX7I7kapQoQIOHDiA+/fvW7U3btwY7dq1Q926dR0WHBGRPV41enPi5Cmsn7MQ96P/FW/j4eGBkSNHolevXpDL/zfqYuu+RIU9XDJNVBzFnpExqVRhNc3wZSNzQb7K/z0+fxXKB6txN1YHjdYErS5tH6ri/ip0aeLv8JEiqUSCQm5AiQAl1GquZSIiovwpS/tIqVQqlC5d2qqtRYsWAICbN2+iVKlS2Y+MiMhOLxq9SU58it2bFuDvP3Zbnf/+++8jLCwM/v7+Ga5ly75EIQEqbD0Wl2Ob2AJZHxl71chchwa+GR5f+WA1niaZEKcxwtvdBR829kdIgKtDHgcREVFBY3cipdFosGDBApw8eRIGg0FcWyAIArRaLTQaDa5cueLwQImIXuVFozeCYMGlv38Tfy9TtgLmfDUDderUeen10tf0/HExAdfua6E3ClDKJSgbpEbJIq44eTXppYlKVpOpZwtlqBRSBPkqceNh6ktHxp5dw2TLuqrjlzX4oJE/OjTwFUetjCYBchcJqpV255olIiKiV7A7kZoxYwZ2796Nhg0b4ubNm3B1dUVISAjOnDmDxMRETJs2za7rWSwWREZGipv71q5dG5MnT0bx4sVfedtdu3Zh9OjROHjwIIKCgux9KERUwLxo9MbDqzBaduqP/T+uRL3W/fDVpP4I9FPbdW2JRAJBECCRSGA2C/jjogZxiQYE+6ngqpT+f6W77JdGf1GZc5lE8sKRsefXMNm6ripOY+S+S0RERFlkdyJ17NgxDB48GJ9//jnWrFmDkydPYuHChUhJSUH37t1x/fp1u663bNkybNy4EbNmzUKRIkUwZ84c9OnTBz/99BMUihfPnb9//77dSRsRFWx+XnJ4uiThh68j0fmToXD3KCQeqxv6AQqXboKq5QJRtLBt09WenR4X4J026hSXYMChcwl4mmSEu6sMmmQTPNUuKO6ftndTdkqjv6zMuUwiga+nAolaE54kCi+tymdvxUHuu0RERGS/zP/KvkRiYiJq1KgBAChdujQuXrwIAHBzc8Onn36K3377zeZrGQwGrFmzBkOGDEGTJk1Qvnx5LFiwAI8ePcK+ffteeDuLxYLRo0ejUqVK9oZPRAWU0WjEypUrMHdsJ1w5+RO2bYhEis4Ms0VAis6Me09MKBLgb3MFuuenx6lVMiSnmhEdq4fZIojTmhUuEsQnmXD1rhaaFBOAtETF3k1sM7s/mfT/R7n8VTALArzdZejerAg+Cg3AJy2K4oNGmReCeHZkThAEJKea8TTZiORUMwRByLWKg0RERAWZ3SNShQoVQlJSEgAgJCQET548QUJCAry9vREQEICYmBibr3X16lWkpKSgXr16YpunpycqVqyIU6dOoV27dpnebvny5TAajRg0aBD++usvex8CERUw58+fx/Dhw3Hjxg2x7c7lI4h7MgBSudsr91TKzPPT4wRBwN1YHfQGC7zUMmj1ZuiNFgASeLlJoUkx426cDp5qtywlKrZMx7sbp4dUKkHJIi8fUUuvOPjPrWSYTBYkppphNgMyGeDpKoOLixRVS7k7ZG8oIiKi15XdiVS9evWwfPlylC9fHsHBwfDy8sKPP/6I3r174/DhwyhUqNCrL/L/Hj16BAAoWrSoVbu/v7947HkXLlzAmjVrsHXrVruStpdJL5SRE1JTU63+T3kb+yt/efjwISIiIqxGsCUSCbp27Yqhw4bBKHHHwydGAEDRwnL4uJltfq/HJ+iRqjOikJsERqMFKTozEpKNUMklcJEBSrkEyakWGE1myKRSqORAQpIRCUk6xCebUbqICm4KI7RaU5bu73kyiYBUnRHxCSnwUL76msUKSXHw77Sy7J5qGdRKCfRGAfce66FWylDUWwqdzjmvc77P8h/2Wf7DPst/2Gd5Q/p6aFvYnUgNHToUPXr0wNixY7FhwwZ8/vnn+Oqrr7B8+XIkJiZi4MCBNl8r/YXy/FoopVJptVFmOq1Wi1GjRmHUqFEICQlxWCJlNBpzvNLg7du3c/T65Fjsr7zNaDRix44d+OGHH6DX68X2cuXKoX///mnTjq/F4Mr9WMQlSWA0A3IZ4OchoEKgAH/PV9/H0xQgNUWKB0ZAJQeSdYA2VQIoAKMBkAmARACeJunhpgCkEiBZD1yN1qGwu4DCcg3+vWr7v1HP39/zdEYg1QDcv6uBNv7l17IIwOmrEiilEsiVgDbVhBRtWoxeSgFSqRGnL92Fq0mAM2tK8H2W/7DP8h/2Wf7DPnO+l9VpeJbdiVRgYCD27NkjdnLv3r3h6+uLv//+G1WrVsV7771n87VUqrQpNgaDQfwZAPR6PVxdM05diYiIQMmSJdG1a1d7w34puVyOMmXKOPSa6VJTU3H79m2EhIRk+pgob2F/5X2CIKBLly44e/as2Obl5YWRI0eiS5cukEqluBdnwNGbCUiymBBUVA6lPG005nGiEVcfu6B0KW8E+b38H0mLIOCh7iluPtLB11cBtd6C2JRUKFwkkLtIYIQZQe5SKOUSJKVaoDda4CIHqpRyR2h1r1de/1X393yZ87uPDahUXIW6NQtB+opvymITjDD89wQVSsrgqpBAq7fAaBYgl0mgVkqRqrcgKdUCv2KF4e+d+9P7+D7Lf9hn+Q/7LP9hn+UN9hTOszuRunXrFgIDA1G+fHmx7d1338W7774LIG3d07PHXiZ9Sl9sbCyCg4PF9tjYWJQrVy7D+du2bYNCoRCLXZjNaQu527Vrh/79+6N///72PhwAaVOB1Gr7SiHby9XVNcfvgxyH/ZW3de3aFWfPnoVUKsXHH3+M1q1bo3bt2lCr1bBYBPx9MwkpBgGlirqJCYlKCXi6KRAdq8PZW3qUKf7qohONq8uQ8MdjPHhqhK+nHF5ucjzWGCGVWuCqdEG54mp4qtOKUNyN06N0MVf0bFEELi521/ER7+/p73G4FWOEh1oKN5ULZFLgcaIJPp4qNKruC3e3V6/xEhJTYRakcFcrIJNK8PwXazIXAZpUPQSpAmq18/5Y832W/7DP8h/2Wf7DPnMuW6f1AVlIpNq3b4/Vq1fjrbfesmpPTk7GwoULsWnTJrGS36uUL18e7u7uOHHihJhIJSYm4vLly+jevXuG85+v5Hf+/HmMHj0aK1euRNmyZe19KESUD+h0Ouj1enh5eYltH330ES5evIgePXqgZMmSVlNz7dlD6VUlv9M35E3f10nuIgEkgEwqRQl/JdxdZdDqLXiSZETRwkq0qOmT5SQqnUIuRXySAdExFkAiwMPVBVVLuaN1ncI2F8p40X5a6Vi1j4iIKPvsTqRCQ0MxfPhwvP/+++jSpQuCgoJw/PhxjB49GqmpqRgzZozN11IoFOjevTvmzp0LHx8fBAYGYs6cOShSpAhatmwJs9mM+Ph4eHh4QKVSoUSJEla3Ty9IUaxYMXh7e9v7UIjIBhaL4LTNWvfv348pU6bgrbfewoIFC8R2mUyGWbNmAUCG4hH27qH0Ks9vWJuQbMLVOym491iP+4/1WaoImJln95CqWtIdJgug1Zmh0ZqgN2QsPvEy6VX7rj/QooRSlWGaYJzGgDcC1azaR0RElA12J1ILFy7E3r17sXHjRqxduxYjR47EvHnzEBoaiokTJ8Lf39+u6w0ZMgQmkwlhYWHQ6XSoXbs2vv76a8jlcty7dw/NmjXDzJkz0alTJ3tDJaJsuhOrE0djDEYBCrkExf1UqF8pe0nDq9y+fRuTJ0/GwYMHAQDR0dH4+OOPUatWrVfeNidGY57fsLZKiBuu3tMiIdkEb3cXlA9SZ2sk6vk9pNITHy83FxTxSZuOePyyBkG+SpuSWKlUgvqVvBCXYER0rA5+XgqoFFLoDBbEaQzwcpPbvJ8WERERZc7uREoikaBNmzZo06YN9u3bh6FDh6Jfv34YPnx4lgKQyWQYPXo0Ro8eneFYUFAQ/v333xfe9q233nrpcSLKumdHSPy9FFAqpNAbLLj+QIu4BCM6NPB1eDKVmpqKyMhIREVFWVXjq1+/vs2jzjk9GpNZcnnxVkq2kktHTkdM9/y0xCeJgsNGz4iIiCgLidT48ePFny0WCwRBwL///iu2SyQSzJgxw3EREpFNHDkF70UjJGqVDCWUKrtHSF5FEAT88ssvmDp1Ku7duye2FylSBJMnT0b79u1tXvyZk6MxOZVcOno6YrrnpyXm9tRMIiKigszuROrEiRNWvxcrVgz//fef+Ls9lS6IyDEcPQUvJ0ZIXuTGjRuYNGkSjhw5IrbJ5XL069cPQ4cOhZubm93XzInRmJxMLnOyOMTz0xKJiIjIMexOpA4dOpQTcRBRFuXEKElOjZBk5u+//7ZKoho1aoTp06dne283R4zGPDvKl6Iz405sao4klywOQURElP9kaXX0mTNnsHTpUvH3y5cvY+jQoTaXPScix3h+lEStkkEmlaSNkviroNEacfyyBhaLYNd1nx0hyYwjy2d36vQ+qteohYAixTBnQRQ2bPjOYRtkp4/GlCziioBCCruSqDuxOvxwJBbr9j/ExoMx2HIkFjcf6qAzZv6cqBRSGE1ZSy7TpyN6qeWIjtUhRWeG2SIgRWdGdKyOxSGIiIjyILsTqSNHjqBnz574/fffxTaJRILbt2+jW7duOH36tEMDJKIXs2cKnj3SR0hiNQYIgnUSlj5CEuyvsnmExGIREPPUgIN/nMesOYvExO5OrA5bjsah5rsT0X7QetxHNWw5Goc7sTq74s2O9NhuPUpFzFMDLBZBHOW7/kALL7ULgvyU8HZzgVZnwZVoLTQppgzXyW5ymT4dsUwxNRK1Jtx/rEei1oQ3AtXoUN/xhT2IiIgoe+ye2rdkyRK0bdtW3MMFACpUqICdO3di7NixmD9/PjZu3OjQIIkoczk1Bc+RBRvuxOpw6NR9bP1uKc4d2wrBYoZJXRotQhvi5NUkaLRGBAUG5kpVwMxie35tWZCvEpoUc4a1UL5echT1kePeEwPuxurgGeImHnPU9DsWhyAiIso/7E6kbty4gZEjR2ZaVKJjx44YOHCgQwIjolfLySIFjijYEB2TihkLN+DQj0ugTXoitu/Z/i3iUBZuKinKF1dDqxeQqDVBLpMi2E+JO3F6mwo3WCwCYhOMeKQBCicYEawSbE46XrS27FJ0Ch4+MaBCsNrq3zmJRILgAFdotGY8eKKHfyEFCnvKHb43E4tDEBER5Q92J1IeHh64desW6tWrl+HY3bt3oVarHRIYEb1aThcpeHaEJFlnQqreArVCCqVcCovl5UnLxYuX0H/wGNz675zY5iJXomm7XnizSTecvm6A2SzFpdspSEw1w2wGZDLAS+0CXy/5Kws3pI8m3X6YgsfxUvzz6AlCiupsqlT4sgp8Ad4K3H6kQ6zGgIBC1lMmvdxcULGEGy5Hp0CTYhITVe7NRERE9PqxO5Fq0aIFFi1ahKJFi6Jp06Zi+7Fjx7Bo0SK0bNnSoQES0Yvl5J5Jz96H3mjBqatJNpVX12g0mDt3LtauXQuL5X+FGSq92QTtuo2Aj18gniYbAegR89QID7UFXm4ukKkkMJsFxCcZkZxqhre7ywunJD47mlTITQYYAQ+1zOZpgc+uLQOA5FQzjGYL5DIpXGQSqJVSPE0yIUVngbur9WieUi5F6aKuaP1WYbipZJx+R0RE9JqyO5EaPnw4/vnnH3zxxReQy+Xw9vZGQkICTCYTqlWrhpEjR+ZEnET0AjmxZ9Kz7Cmvfv/+fbRu3RpPnvxvGl9h/+Lo0GMMylWtL7a5SCUwmCwwmgW4qWSQu6St8ZK6SODlJsGTRCMEACp5xrVfz48mmUwmpEgAtVIKTzeFTfs5pa8t0xktuPkwFYlakzgi5uEqg6tSiieJJhhMZgD/S6SeHeWrGOzG5ImIiOg1Znci5e7ujk2bNuHIkSP4+++/kZCQAA8PD9SqVQtNmjSBVJqliupElA05VaTA3k1oixUrhvLly+OPP/6AytUVb4b2RNPW3eHp4Wp9YQkgCIBUkvbf8ySQABCATI45YrNgtVIGo9mCK9F6mC0C3FRScUTsaXJa6XGZVIK4BBOUcpnDR/mIiIgo/7M7kQIAqVSKpk2bWk3tA4CUlBRcvnxZ/N3d3R0VKlTIXoREZJOcKFLwqqTFU2m0SlokEgm+/PJLzJ8/HxMmTMQf1+W4/kALD3fB6vZGkwVSiQSuSgm0egskUglcZBKYzAK0OgtcVVJ4u7lAl8k+Vi+qVCgIApJTzdAZzUjSmpGSagJe8HwU9nCBwSggMdWEooXk4hdAUhcJPNXAw6dpj6dCsBr3n+gdPspHRERE+Z/didSpU6deeOz69euYNm2auO9M9erVsWnTpqxHR0Q5ymIRXjqK9aKkxWIx49SRnfhlayRCu0yCtlFH8dgbb7yBqKgoAEB9pS7z9VsJJqhVMgT7K5GqtyBRa0KqHpBJAR9PF/h6yiEAmVYbzKxSYYoeiLurQ7LOAr1BgEUQcOjcU7i4SDNNep4kmaCQS+Dp6oJErRlqFZ5J5MzwcJXBUy1D0xqFIJVIWIqciIiIMrA7kerRo4fV3inpJBIJBCHtW+erV686LkIiyrbMEqZ7j/UZ9lB6voBEZknLnRv/YOf62bh3K230+eiOhej1YYtME40Xrd+qGKJGoK8SjxMNqFgirfx5erEHtVKCO3H6F1YbfL5SYWKKGffiAYmLCe4qGUwmoJCbCx7G67Hzj8dWa7jSn4dr97WwWIAKwa548MQAzf8nclIp4OMpR7HCyrTRLYMFJYu4ZoiBiIiIKEtT+yZNmoQyZcpkaL927RoiIiKyHRQROU5mm856uLrgaZIRZkF4aQGJZ5OWwvpU/Lo1EqeO7rS6vqd/Ofx49B5c3TxR3E+F5m8WQsgzyceL1m/de5yW6NyJ08PPSwFPddpUvjtx+peuQ7KqVBijQ5xGD71JAh+1FFq9AFelFKWKusJTLbNaw/Vs4piYYsbdOB2SU11QqqgrQmSuYiLnppJCq7dAb7Rkaf8tIiIiej1kKZGqXLkyqlatmqFdqVRmOyAicpzMKu7p9GacvZ4EndGCWmU9xJGmFxWQeKu8O37ZuRFf/7wchtRk8dpuPiEo03AQQsrXQKJBwOMUPW491OGfW8noFhqAtyp4iedmtn4rO9UG02+773Q8rt3XQhAAg0mAj2da4ufllvZPW3rhiXM3kvHHRY34PPh5yaHVmfEowQCDUUCFEm4o5J42+uWI/beIiIio4MtSIkVEed+LKu4JkAASATKJBPce6+Hl5iIee77q3Z3r5zFx4kRcunRJvK6Lwg1BNXugcPm2cJHJ8CTRhMIeLvDxlMFksiAu0YjvD8UgwEeBkICXT4t7WbXBV63fCvZXoWkNb9x8kAyp2YAi/q7wcldaFbVQKaR4rBFw4krG56FUMVcYTBbEJ5tw46EWVUu6Q28UWJmPiIiIbJKlROrYsWOIiYmBh4cHAgMDERQUlKGiFxE514sq7hnNFlgsErirJUhMybjprEohxZNEAVq9GZGRkVZJVIVabfDG258ixeQJvckMkwkQLAISUsxwkUmhUsjg6wnEJxlx4O94fNqq2AuTkecTpRL+KvHczKYjZrYBsLvKBZ5qFxhSATeVLMO/QzqDBZb/H2EqUsg6yfJyc0H5YDfceJCK+EQjbj7UwUMtY2U+IiIissn/tXff8VFV+f/HX7dMTe8hCb2EIk2KguhXFNvaXb9+rev6XdS1LtbF3/pVVl0buooguLq6dldXUSy4unZXXYpdFBVpgZDeM+223x+XDAkJkAklRD7Px4OH5s6de8/Mmei8Oed8TsJBasyYMbz99tu88sorlJeXEw6HSU1N5cADD2T06NG7o41CiATZtkNJZYTaRpMknxYvBAPg0VS0zbnJst1g1XrT2UjMxqMrBH0af/zjH/nggw8YPHgwU395FY36QJojFuUVUQzTQVUBBWzDrbzn83jw6CoeXaWkIkp5bQxV3VL1LitFp7rRZPWmMCvWNlHTaBAz3Cp7OWleDhiWRmaqzisfV3dqA+CcNA+F2V6++AGKWhW/gS1T9HLSPFTVG+0qD4IbpkYNSGL1pghHjs9kcGEw3sY1ZWGp1CeEEEKIbUo4SG1dzry6uprPPvuM999/nzlz5gCwfPlyHMeRfaSE6AYtozk/bGhmQ2WUyvoYWSkeeue6a4eS/CppQZ2Kuhg+j4pHcwPG6pWfYpoG3pzRDCwIYDsOjj+Pvz72LMVD9+Ov/yyjtsYgZtgomzOJqrphDNyy4UaSDgp4dIVQxOKljyppirgl1A3LJmY4WLZDRW0My3ZICWroqko4ZvHDhjDLf2gkNUkn4FUY1idphxsAq6rCAcXJ/LiugpKqGPmZ7TfPPWBYGm99VtOm8mBrUcOJj0RFDZvnP6zc4UiYEEIIIcROr5HKysriiCOO4IgjjuDYY4/lvPPO4+yzzwZkHykh9rTWxSXy0r00h22q6g2qG2I0R2yG9gmSlqRTlOOjvDaGAzTWVbDob3P5askbJKfncda1T1Pf5OXJt8o2h4k8vq+tZn15BAdI8qmEYyoxwwIUVMUNUzHTwbAsDFPBq0N1gzsK1CfHT8Sw+W5dlIaQgW2Dz6uQFNAorzUAyE33kJfhjhyVlEfISffQELLiRSOg/fqtluIVRTleJg1yqDL8lNWZ7YpWFGX7+L4kFC+X3np6X+vCEuGoxSufdG4kTAghhBCiy0Hq/fff5+OPP6aiooIrr7yS7777jhEjRsgeUkJ0k46KS/TJ8xOK2URjNs0Rk7XlIXpl+KhsMCjM0lj/+ULuv+8RjGgIgKa6cr5b+irq5F+2CRNfr22iss7A41EIRVRsxwEHDNMNLYriYFnQFHJITVIJRSy8HpUhhQEURWH1pjCW7ZCV6mFjVRRNUwlHbFTFDUihiE2SXyPo02gMmUQNm5LKCKnBpHbFI1rWb7WWmwoHD82gOebpsDhFvFz61hsDx0etUvnPtw3tClJsayRMCCGEECLhIBUOh7nkkkv4+OOPSU5Oprm5menTp/PMM8/w7bff8tRTT3W4x5QQYvfqqLhEWpLO0N5BSioilNfGWF0aoazGIFT2BSvfu5+6ynXx56elpXPEKZeQVXxkmzBhWA7RmI3tgGk4JPkVHEfBsh13yp7p4DjuNL+kgIrP4+7DNKgggKqqNIUtGkImSX4V03ZQVYWY4RDDDVsAUcPeHMpUFEVFUzsuhNF6/dbWVKV9ifUWOyq17vOoHRbmgG2PhAkhhBBi35ZwkPrzn//MihUrePTRRxk/fjz77bcfAHfccQfTp0/n3nvvZd68ebu8oUKI7QtF3bVIWxdVSEvScXJ81DaZ2JEq1v7nYVZ//d6WExSFk395BpfNuJqXl0VIC24ph+44DiUVEUwLAl6FqOkQjlh4PG5gsm0L2wZVA79XIy/DS16Gl5KKKDnpbuAwLBvLAs2v4DigqQqGaaMo7rRAAMMB2wFVAa9HwbQcFKVtIYyd3d9pe6XW15SFO3zvWmxrJEwIIYQQ+66Eg9Trr7/OlVdeyYEHHohlbflSkZuby0UXXcRNN920SxsoxM+VbTuU18XYWBUFoDDLR16Gt8tTx4I+Da9HaVdUwXEcNlRG2bjy33z1xm1YRiT+WJ+BI5l47AwmHzAW3Z9CzAi3CRPNEbcaX2pQxbJ1Yk0GlgOxsIXjAApoKuRn+hgzMJkTD8oB4Mm3yuLtaKkSaFnuKJBHU4ga4FHd8ARugFJwCEVt8jK8RGK2W7zCdItTtJ6G17K/U0v59Jq6KLXNuNMNd6CjjYG399612N5ImBBCCCH2TQkHqYaGBgoLCzt8LC0tjVAotNONEuLnpKONZTdURVm8pJqv1zTSGLIBh5Sgzsj+yfzigKxtFjXY3ia1OWkeeuf42xVVaI7Y1DebpORumXKblJLBMaddzrgpxxGOOayviDCiX1K7MNEymqT7VXTdDU+OAwGviqqCaTlEDIdQxGb0wGR6ZfqwbadNO5L8KqlBnZpGN5DpmkLQp2JaEIlaqKqCz6sSilr4fTqDCgJsqomRmeLBtGw2VkXbTMPrk+tvs89UOGIQblbZFKnlv8ZoXSoIsa33DnZ+JEwIIYQQP08JB6nBgwfzyiuvMGXKlHaPvfPOOwwePHiXNEyIn4OONpZNCehsrIxQUhVFUxQyUjQUoCFkseS7emobDc6alt8uEOxok1pVVdoUVchMVkkKeGkImTSGLbJye3HIsdOJNldy5MkXEUhKAcDvdahucAh61XZhomU0yTAsmkMWfq9K0KsSjtmEow6W466Pipo2r3xSTa8sH/3yAu2KOxRk+6hvtthUa5AS0BhcGGBjVZTS6him7RD0K2SkeshN81LXbJKf6eP4A7MI+LR2obF1ZcLcNC8ZSQqlBqwui1D3UVWXqutt/d51VJCiZSRMCCGEEAK6EKQuuugiLr30Uurq6pg6dSqKorBs2TIWLlzI3//+d+6+++7d0U4hepytv/D7vCqRqMVnPzZQ3WiSEtBIDqjYDmiKQlaqh7omg3XlET5aUUdRdh7gFpH4aVOID7+qJ2a4xRe8AQXbhlUb25bm7pPr5+jxKdw2+z6efu9lTpvxKKonQFqSTr88P/nDzmvXzpZpa0kBnckj0qiojfH9hhCpQZ2gT8XnVdlUE8NyIDvNi0eDaK2BrjloqCT7VZIDGhsqIzz7bgVnHJbXrrhDzLBJS1bx+zz4PRoOCv3yAwwqCmIYNlHTQVUUHGgz8rS1jioTGoaN3wPZ2V5Ka40uV9fbUUEKKX0uhBBCiNYSDlLTpk1j9uzZ3H333bz//vsA3H777WRlZTFr1iyOPvroXd5IIXqajr7wAzgoWI6DaTnUh0zCMduteKeAz6MS9KsYlsOqjWG++KmJ70ua+XFjiLVlUUJRC59HwaOrqIqCpkFqQCMcs+Ph4a23/sWsWbNYt86txtf0w3Ncde3/470vavlpUxjHcbY7bW1DVRSvR6W20WR9eQQUBZ8OSV53ZMirQV2ziWU7aJo7TS8t2YPXo2BYDnXNW4JMS3GHL1c38Z9v67EdSPY72A5kpugcMCyNMQOTAbY5XXFrHVUmbLErquttryCFEEIIIURrXdpH6vjjj+f4449n9erV1NXVkZqayoABA1DVjiteCbGv2dYXfsOyicTcAgqmBT7drVJnOxCO2cRMG59HobbRYOGHFVTVG0RNm9pGA9OC5oi7Pikvw4uuKdQ2maiqwn8++56Ff7maf3/wTvxemqaRmeqjV6aPg/ZLp6re3O60tQ1V0fgI2qj+SVg2NEUsGkMWCrCpJkpD2KIpbKFrCgGfu/bJ71WJmTa6ppCT6uH7kmY+W9VI7xw/4ajFv7+uj28Q3LIvVUV9jI++qSc7zUOfXH+nQ8+2KhO22BXV9bZVkEIIIYQQorUub8i7Zs0ali9fTl1dHVlZWQQCgW0WoRBiXxOKWkRjNobPobbJwKOpJPlVdFUhZm4ZhVIUsG2wcdA1iBkOluUAJpV1Bn6vgt+j4jgKCg4K7lS82iaTXplekrwmn73zBKuXP4dtGfH7T548mVtuuYXi4mJgy7S1j76pY1VpmEjUxu9TGVQY4KAR6RRl+3ju/Yp2I2ipSTpOpsPa8jA56R6ihoNjO6QmefB5FBRFwXHcYhNBv0pZTYyyOoOFH1aSnqxR12ShKDC0d3CXbHIr1fWEEEIIsbdIOEjFYjFmzpzJ66+/jtOq3LCqqvzP//wPN9xwQ7spN0Lsa+qaTDbVRFlfEUFh8zS8oE5mqo6quCHKdiActXBw91cCB8t2N7Z1HIegXyU92UsoYuE4btBSVQXDdGgMGTRt+Jhv3plPuKEift/8/Hx+d9UfmDL1aJL8OvbmDXBbcxwHZ/M/2fwr3NEImuM4NEdsDMsmya9jWgY+j0ZlnYFt2zhoGKZNKGKjKhCO2jSaDj6PQlG2j6hhs6GymSS/TkPIIi1py39uujoNT6rrCSGEEGJvkXCQuuuuu3j77beZOXMmRx11FJmZmVRXV/PPf/6Te++9l/z8fC688MLd0VYheoT1FRE+/KoOy3LLg6cnq0QNh7LaGBX1BrqqoCjg2GBYoGtusDFNN9dYtrvnktcLUcNBUd0AZTugbB7JCjc38t1rd2IZ7nYDiqoz7fizmXr8dMobVZ55p6JNVT8gPm0vP8MXn2L306YwVfUm44tT2kyZq282KamI0BAysSxQNs+kO2ZC1uaAFCFmOuiaQmaK7u77FLVRVYesVC8pQQ2r2cHvVTEti5LKCKnBpDbBpyvT8DqqrqcpDhEDSqpiZKb6pbqeEEIIIfaIhIPUa6+9xhVXXMG5554bP9arVy/OO+88TNPkmWeekSAl9lktRSYawib79U/i69XNlFbFsAEciJkOtu1Wg9NVsBwHw9yyMW38Oo5bDt00Y2Sk6Hg0iJlgWA6WBaovlaJxZ7PuPw+SXrQ//SZfhJXXl6/XmwwuCOBP14jGbFaVhqiojeH1qO2m7bWeYrdiXRNe3Z0yZ1gOK0tCRGM2SX4V1QeNIYumsM3nPzVy3IGZfPh1A3XNBjlpXry6wlermzAth6BfIyvFQ12ziWE4aCqoikZ1g8GmmhipQZ0kv4qiKF2ehrd1db1wxCAcgxG9/RwyJvHS50IIIYQQXZFwkAqFQgwYMKDDx4YNG0Ztbe1ON0qInqr1FDnDckABR1HiSUnXIGqDaUGvTA84DptqDWKm+3wFd2qfZYNlQsixcZwYlas+wJc7BtWbEr9X/ogTSM3qTVLBOCxbob7JxLQcdFWhd66ftCSdvj4/35eEqKiLMaggQHPEjgcZ2DLFrqbBIDPFy6aaCM1hm2jMJi1JI2o41Daa1IdMdFXhxw1hoobNCZOzWVcWpaQywqYag0jMJj1FR1UU1pSF3bCnQlPEJhw1sW0b03Tw+1TSgjpFOT7qms0uT8NrXV2vpq6ZjSX1HDgug+QkCVFCCCGE2DMSDlJHHXUUTz75JFOmTGlXpW/RokVMnTp1lzVOiN3Ntp02pa6TvM6On7QdLVXlvB6F1ZvCOA70zvZiWu7ok4JCTUOMhrBNVYOJorjT+8ANUcrm9VPO5plpTdVr+X7pAprKviJn2PH0mnAR4AYyRdUI5I/H2fyz7lWxLIfKOoOmiEXfXD+m7VBRF6O8NoZhOQS8bqW9lqAFLVPsYHi/INUNBj9Wh0kJutP1ymtjhGM24LYralj8WBLm9SU1/O/RvZg6JoOSyggvfFhBXaNbFj3Jr6L5FZojNs1hC8N00DT3Pl5dibdnSO/gTk3Da6mul+IzCdWAKmszhRBCCLEHJRykRo4cyZw5czjuuOM4/vjjyc3Npba2lrfffpsvv/ySc889l3nz5gHu33Zfcsklu7zRQuwK6ysirTaMdcNPfrpGtgeGdfGaLVXlahtNGkKmOzVOVWmp1h01LDy6StDnEI7Ym4s+uCFFU0HTFHAcjGiIsi+fouLbl8Fxk1blytfILD6RQFoBXt2t8KeqkBHUaQ675ccNBzTNoarOoKIuhm2DZW8uYoG7V1VNo0lzNERxUQBdU2kImZiWTf/8AAoKazaFMS2LmgaLcMxGU93X5dEVLNshFLFYvSnMG8trOP8XBWSl6Cz8sJKGsEWvDA+qquI4DuGIhaaCrSl4NLe6XyTmtsEBMlM8FGX7dkFPCiGEEELseQkHqZtvvhmAhoYG5syZ0+7xv/3tb/F/lyAl9lbrKyLx4gu5aVv2N1pdFubHqMLAATGG9A0mfN2WqnJfrm7cvGZoyyhJOGpRWRdDURUsy8GwwOdxp/mpijsVDseh4sd32LDsYczwlmmy3uR8CideSFJ6AUG/is+jYpomtg2NIRvDtDEsd1SrtsnBtmxMGzy6gkcFE6hpMgn6NdKSNKoaDD79oRGfR6EpYpMa1Hj1kyqKcnwUZPtQFYfaxmZ8HoUkv9ZqKiD4vBqaAl+tbqK8NoaqKng9CqkBtzpf0O+WdA/FLEDB71VI9msMKUrC41HwaCrg0BAyu7xxrhBCCCFEd0s4SK1cuXJ3tEOIPaalIERHxRd6Z3tZsVph6fdNDOqd+LSzlqpy68ojbKyM4tFtAj6V5ohFZZ27z1NOqk4obNEcMYls3vrJtKGxajUbly4gVLEifj1F85K732nkjPgluseHsrnMeDjmYG8eyfLqbnCJGG6QMiy3HLlpAbjnKQoYpkNJZZTsVJ1wxCJmOiQHNII+FUWBD7+uQ1XA41GJxWwM0y3B3rocumE6mzfi1ahrNtlYHSUr1YNHUxneN8jGqij1IZNI1MayIDmgkRLUMEwHj0chI9ldD2XZDjWN5k5tnCuEEEII0Z26vCGvED1VR3smtVAUhbQAbKiKtRkt2XotVVaKTvXmIBD0aeSkeeKhq0+un/+ZmsuDr5psqIwSMyyaIjaappCepBGOuBvqtl6NVfbFE1R8/axbE32z1N6TKBh/Pt6UfLcNDtjx9VTus1XNLUxhbj7eck178xZRMRM8mhtoLNshFLWpqDNQFHcaYZJfw3bAMCEzRac5YuH1KDSFHWKmg8d00FRn8zluufPUoI6iOLixbct0Rp9HZUS/JJojNg0hkx83hEjya6C47587EuWSjXOFEEII0dN1Kkhdd911nb6goijceuutXW6QELtbS0GIlj2TtubVIGba8dGSrddSGZYdX1Pl0dQ2+zW1lN7ulxfggmMLePa9CirqYli2sXl9klvhzthqIMYTyIyHKG9KAYUTf0tK4fhtvoaWwGQ5bltVTSHJC+GIg21veVwBdE2J/7Fst4S6X1dISdIJeFWaIm6FPkVRQFGIGjZDiwJ8+mPT5kITDpqqbh6J0vF5FGoaLFICKoXZvrab5Ob6SQ5oJPlVahoMqhtiKIpKZqpb9hxk41whhBBC/Dx0Kki9+OKLnb6gBCmxt2sZQYnGbIL+9iMiMQu8XpWgT2u3lipq2Hy7LkpD2CQ1oDOsbxC/R2VVaYjKOoMTD3L3MbJth4BP45BR6Xz8TR0VtVEaQiYxw8Fx3DDRejQsc/DR1K55j9TC8WQPPwVV23HAUBVIC2qEYzYBj4qqQsywsOyWAAWO4xaIsG3AzUnoChi2W8EvHLParIHSNYVwFDJTvRTleCmtNvB5NFKDGn6fimVDfbOF7TiMGpBKXrq3w01y/V6V7DQP5bUxwCY71YPtQCRqUVkfIy3JIxvnCiGEEKJH6/TUvueee45Ro0btzrYIsUe0GUHx+dsEGsdxqA/D2N5eslJ0nv+wMr6WCmD1pjCWbdMrw0NDyKa0OsqIvkn0zXU3tv3k23os0+btL+ooqYzgOKCrgKJiWjaK2cS6pY9i2w5Fky6L31dRNQYedWe7qYbboyjQO8fH2vIIlu24+1ZtPu7VFfxelXDMxrTAtGxsx51eF7HdMuypSRpVdY5bKXAz03IrAXp0laF9kmkMNaDrCoblYITcYTRVVRjSO8gxE7PaTGdsvUludYO76fCBw9NwHGgMm2ysiuLRFQYXumXPZeNcIYQQQvRkskZK7HO2NYISidmU1cRI8jlMLE6mst7gx40hfB6V5oiNg0N9yCTJr6GqKkE/NDSbNEdskgMaOWleln9fzxvLamiOWOga+D0KXo9KY3OUTd+9Qdnnj2FGGgDIHHQEwZyh8XYlEqJaOIpbaMKwHHAcd8RJVbAdBwfw6e6/RwwbVVEIeBUURcW2HTKTPdQ2mliWg6q75clDEYvMVI+7aW8UBhYGKMzysqkmRtRw8HkUhhQFmTwivV0Qar1Jbuu1Y0C7YzISJYQQQoieToKU2CdtawRlYL6fLE89AC99VMmPG9wgpesKXl0lErXdAgpsmQZnWDagsb48zLfr3E14wR0ZUhQIVX3P+k/mE67+MX5/VQ8QbSprE6QSZdnw7ZoQVquqFboKfi+YjkIk6q5vckenNFRFQVPd0KVrKpUNMfxejcaQRdDvEI7a+LwavXPcgFRZH2NYnyR+OSVnm4U1ttaySe7WpMS5EEIIIX5uJEiJfVafXD8FmV5WbghR12SSnqzTJxs+WlbOa0vrqG6y8HvdIguqolDfbNEUsQj4VJIDOqbloKng0VRKKiN8vaY5XpIcB4xwPZs++xs1q95sc9/0/ofSa9xv8ASzdvo1tA5R4JZRjxiOOxKlglfX8HtVPJo7MhYzLNKSPe76qKiD36tg2g61jTbZ6Tr98gLomsK6ikh8HZOuqxKEhBBCCCG2IkFK7LO2rsbn9Sjkpams3aDgeEyGFAYxTXe/o7QklaxUnVDEoqbRJOhTCUVsMlN1Al54f3VTvBKfZVlU/7CY8i+ewIo1xe/nT+9LwcSLSc4fiaq4Jcp3hZbBoZbrmZZbbjzoc0uVR2I2ig6245CV5qV3jp/UoMa68gi9snycMDnAd+vC1DYaNIUtooYt65iEEEIIIXZAgpTYJ21djc/nVYnGbL4raaakXGFkfxVVVemd66c5GqK+2SLoV8lI0aioM9hYHSM9SSc9WefL1c3UN22pZ15f8gmlSxfEf1Y9QfLHnE1W8fEoqjstcFeFqG1dy51eqBCJ2QwuCpCerOPRVHft0+a1WDnpXmoaDQYVZDNpWLqsYxJCCCGESECng9SsWbNITk7e4XmKovDYY4/tVKOE2B1aNtVtipi8+3kddU0G2WkeoqaN7UCSXyU3zcNPGxUqGwwKchxSgxp9cnxsqIrQFDKxHHdtVLJfI2ZafPVTE01hq83muml9JhPMHkqoaiUZA6eRv/+v3X2i9iAHUBR3z6vGsEm/PH+7YhZ+r0p1g0MoaqGqXpm+J4QQQgiRgE4FqQkTJgBuaegd6cw5Yt/TEmK6a8Sj9TS+hmaLNWVhVAXWVbjrnzQN0oI6aUEVnw51TRZltTGq6w3qQybhiE04tnmPJsXd1NcwHWzLoGbdZ6QUTYjfS1FUCiddhm2ESModscdeI7j7R7X8BqqqG/hqG7dUFmwtErPx6ApBX/u9tIQQQgghxPZ1Kkg98cQTu7sd4meso7VIvXP8TB6xZ9bgbD2NL2bYhKM2lm3j97qhTtcUahoNGprBqzs0Rix+2BDavLGtQsx0MC33j+OAYUJD6des+2Q+kbp1DDjyDpLzR8bvGcjov1Nt7uoaqniIUtyNh5MCGlX1BjHTArYEJsdxqKyPMbgwGC9RLoQQQgghOk/t7gaIn7eWELOqNERaUKcox0daUGdVaYhFH1WxviKyW+9v2w4fr6iPb6ob8KlU1xsAJPk1HMehMWyhawppSToxy8GywbKgvslCU6Gu2aQpbBKJuY+FGqv58Z07+P713xOpWwdA6bIHdulo7M5cSgFy03U8ukpako7Po1JZZ9IcsbBsh+aI1aYqn6yFEkIIIYRInBSbELvN1iGmZY1O0K/R1+dnXUWET76tpyjbt9u+zFfWG5RURshN86IoCk1hi3DMLRwRMxx0zS3IYJgOXo+KpjhUNgOKja4pbKyy4tX4sA2qVi6i7ItnsM1w/B6BrMEUHnBxlzbU7YjS6p9KgiNTqgp56R5Sk3SiMRvLdpg4NJXUoMaGqmh8vyypyieEEEIIsXO6PUjZts28efP4xz/+QWNjIxMmTOCGG26gd+/eHZ7/448/Mnv2bL788ktUVWXChAnMnDmTgoKCPdxysSNbh5jWFEUhJ83L+ooIlfXGThU62N76q1DUImY4+LwqjuPQ0OyOLCX5VCzLJmba2JZDc9SkKaJQXW9iWKBr4NhOPEQ1ln5O6bIHiNaXxO+r+VLJH/trMgcdEa/Gtyu05CaPtmVkKuBT4iNiLZStztc1KMzykRRQqWu08HgUctO9HDMxi6Jsn1TlE0IIIYTYhbo9SM2fP5+nn36a22+/nfz8fGbPns306dN55ZVX8Hrbfrmura3lvPPOY//99+eJJ54gFotx++23M336dF588UV8Pl83vQrRkdYhpiOtq8Z11fbWXxVkeimpjFDXZBCKWBiWTU2jSUPInbKnADHDxjChvMbAst3goqLg1RUs28E2IpR8/Gfq1/271V0VMoccQ/6YX6H7U7vc9u1RFNBUBU2FgE/DqyvEDIOWd0pX3XBl2bjhynFICmhYtkN5rYHPozJ2UArHTMyKjzpJVT4hhBBCiF2nW4NULBbjkUce4eqrr+bQQw8F4J577uHggw/mzTff5Ljjjmtz/ltvvUUoFOLOO+/E73e/HM6ePZtDDz2Uzz77jEmTJu3plyC2I+jT8HoUojGboL/9iE3rqnGtR5X8HjflRGL2dkdPtrUX1KrSEN+sbqSu2aKuyaAxbGOaDroHslM9JAc0GpoNosaW0RzL3jKFTlHYPOXPQdF9mJGGLa8peygFB1xMMGtQp94Drw6mCfaOT41Tgd45XkJRB1WFvnl+NlRGUBXweRQURUFTHUzLbWtKUENX3eCXm+Gld46PA4alMXpAsow6CSGEEELsJt0apFauXElzc3ObAJSamsrw4cNZtmxZuyA1adIk5s+fHw9RAKrqjnY0NDQg9i45aR565/hZVRqir6/tPkatq8aFYxbPvV+7efTIpK7JBBzSkzykp+gdVvjb3vqraKXNl2uacWzweNzCETZgGO50w9SARsxsW+FOVcHePNxjOWBs3ltKURQKJ/6W1W/9H/ljzyFj4DQUpXM1WhTA51ExLRt2sM5JVdw/DqCrChmpHsbmBbBth2/WNtMcsdE0heSATmpQQ9scnJojFtlpOn1zA5TWxDh5Sg77D0qRACWEEEIIsZt1a5AqKysDoFevXm2O5+bmxh9rraioiKKiojbHHnzwQfx+f3yvq65wHIdQKNTl529POBxu8899zf4DfGyqCrN6UzPZKXp81Kiq0SQ1oNMrXeXFD8ppCJv4dZXahhjhmA0oOE6MlKDC9yWNbKoKc+zEdIpy3OlpFXUGazc1k5GkYZpm/H51TQbfrG2OT9OzY1syjINbtrymccsGugqbz7Mh1lhG6fIHySo+FqdgXPya/ox+DD3lEVQtsTLhDu6o2vZKmSuAz6uQnarj9yg0hCxURaFPts4Zh6ZRVW9SXhMhO1VlY5VBwKvg1d2rayoofpWGZotQxCDFr5Cd7BCJ7FuftX39d6wnkj7reaTPeh7ps55H+mzv4DhOpwuIdWuQavmgbL0WyufzUV9fv8PnP/HEEzz55JNcf/31ZGZmdrkdhmHw3Xffdfn5nbF27drdev292dBs+G6jwoYyBXNzIYecVIfiLIfl39SwsU4hJwXWl0FjRCHJ64ab+kaHVZEIhRlQUg+v/ruGg4sdVAXK6qGqRgUDmjd/1h0Hvt8E0ZjSJjxtreWYtjngWGaUyhUvUPHNP3CsGNH6DQw+fl6b4KRq+jautn2G5Y40eVQwOxiYcgDbcmhoitGsQsDrkJMK60tjLP2smqgJTU0qWcngVaGuCZK8Ckqr19wchXWbIgzIdagsraV6U8LN/FnYl3/Heirps55H+qznkT7reaTPut/W2WRbujVItUzRi8VibabrRaNRAoHANp/nOA5z5sxhwYIFXHTRRZxzzjk71Q6Px8OgQZ1b85KocDjM2rVr6dev33Zf08/ZMOBgx6Gq3iQctQn4VLLTdKrqTb4qq2ZAkbufk1UTJiNVwbahIWRiWDZhA9B0kgMqtVGNnIJcctM9ZNUZfF1WTUpQI+hzp9o1RyxipU3AluIV2xsNMm2Hhg1L2LTsQWJNW0ZALaOZWOMm/Ol9d8nrtx3QVDYPf7V9rKV9UQuCusaAwgB5GR5Kq2MU9s4i4FPjr7M4xeGHjRFihk3Aq6JpEIk5YFgU5AY5bkpmfMRuXyK/Yz2P9FnPI33W80if9TzSZ3uHVatWdfrcbg1SLVP6Kioq6NOnT/x4RUUFxcXFHT7HMAyuu+46Xn31Va677jp+/etf73Q7FEUhGAzu9HW2JxAI7PZ77O2Sk9r+XFEfIhSDgF8hariBwnEUappMLAs8HhVMB9NyqKy3qKy32Fht068gSB+/Q79eEVaVhkhNcsurO1HAUdpklW2FqGhDKaXL/kLjxmVbDioa2cNOJG/UGWjepI6f2EWG5eYoFUBxR5IcIMmvYjtuBcOAV6Ux4pBlqwT8HjLTk8hJ88RfZ99cP8N1nZKKCA0hk4jhEInZ9MkLcObhveiXv2//R1d+x3oe6bOeR/qs55E+63mkz7pXIvuCdmuQGjp0KMnJySxZsiQepBoaGvj22285++yzO3zOtddey7/+9S/uvvtujj322D3ZXLELra+I8M4XtayviLCh0i3z3RS2aFQsbNutTheJ2oRiNuGovTlkwYJXN6JoCpOHpzN5RBqVdQbrKiLkpHlRFfc622ObESq+fpbKFS/g2FvWViXnj6Zg4kX40/vQlSl8neHQUhFwc5VAGxTFwe/RsCx3Q+C6JoONmsp+/ZPi1Qq3fp1D+wSpaTSprI+Rnuzhfw7NpV/evh2ihBBCCCH2tG4NUl6vl7PPPpu77rqLzMxMCgsLmT17Nvn5+Rx55JFYlkVNTQ0pKSn4/X4WLlzI4sWLufbaa5k4cSKVlZXxa7WcI/Z+LWXL65pjZKV4aAhZBH0Kdc3u1L/kgEY0ZtMUdRcVKWwpH17dYHH3c+tZe3CY06fmc+JB2Xz0TR2rSsOEIxaarqKptNm4trWNS+ZT+9Nb8Z89wSx6jT+ftL4HJ/Q3EF2hbh6JUhWwFVBUsG3FndZou3+awjZ9clUmDU+LV97rk+vnxIOy4/tlGaaDR1cYMzCFScPbVjMUQgghhBB7RrdvyHv55ZdjmibXX389kUiECRMm8PDDD+PxeNiwYQOHH344t912G6eccgqvvvoqAHfeeSd33nlnm+u0nCP2bq3LlvfLC9CQYrGyJEQ4ZpMa1AhFbJrDljslb/PAkIMbPhTFDUihqMOz71VQ32yx/+AUHMchHLVpCFnYpr3NEAWQO/I06ta8B0D28JPJHXk6mmfPjOY4m1+PabkhKsWv4feohGIWlu0QNWzSkrQ2m+i26JPrpyjbF99ra3v7awkhhBBCiN2v24OUpmlcc801XHPNNe0eKyoq4vvvv4///Mgjj+zJpokEtN5Qd3tf8ivrDUoqI+Smueua0pJ0hvYOUlIRobrBwKMrmKazZXNc3ABFq9EcTXXDyEcr6ln6fSOGadEUtogabe9lGWGMpnL8Gf3ix3ypRRRN+h2B7GL8aW1L6e9qW9eWcDYfsx1I9qrkpnvx6lDTqJAS1EgOqIzsn8zoAckdXk9VFfIy9r1iEkIIIYQQe6NuD1Ki51tfEYlPO4sZDl6P0uEmugChqEXMcPB5VRzHoTliYzsOffP89M7x8s3aEGW1UZyYO53PYfNIzuZEom3ePNeyoTFkYlrtC0o4jkP92g/Y9OlfQdUpPuEBVN0Xfzxj4OG79f2ItwM3+OmaG4KiMQdVhYBXIeBTsWyb+mbweVWS/Cr5mX4mj0iXUSYhhBBCiB5AgpTYKS3rnepDBrlp3viGu6tKQ1TWGZx4UHY8TNm245YoN23Wl4dpCls0hC0sCyzHxrbAtBwsa8uaqK1ZDtiGG1JiZvvHI3Xr2Lh0Ac1lX8WPVa54nrzRZ+36F0+HFc3bPJYS1MhN92BaDtUNJnkZHjKSdcrrDJojNn6vSl6Gh2F9kmS9kxBCCCFEDyJBSnRZ6/VOfXP98WINQb9GX5+fdRURPvm2nqJsHxuqou6oVUWEDRVRqhsNPJpCSlBFVRTqGg1ipjv6tKPxmI6CixULUf7lk1StfBmcLTEspXAC6f2n7roXvZWW0SbLcjC3Sn8ZKTr5mW6Iqg9Z9Mr08ruTiwgGdJrDJqGYu6dWsl+X9U5CCCGEED2MBCnRZVuvd2pNURRy0rysr4jw+apG3vqslvpmk+w0HY8OluUQMxyaItupDNEJjuNQt/odNn36CGakNn7cm5xPwcQLSS06YKeu31p8vRbudEKP5o44aZsDUCRm0xSxUYGgXyXgU6lrsjBMm5xUD2cclkf/gs37QshaJyGEEEKIHk2ClOiy1uudOuL3qqyvMHnyrTKqG0x8HoXS6ig1DW5ViJ3drSnasIGSj+cQqlgRP6ZoXnJHnkbOiFNRtV0TVjwaeHUFv1dF1xWaQibRmPuYZTuoqoJpORiWQ9CrEPTrJAdUslLdUabeuT6m7Z8pez0JIYQQQvyMSJASXRb0aXg9CpGohYOCYdl4NLdwAsD68ghryyJYtk1msgddV6ipimJYu+b+iuohXP1j/OfU3pMomHAB3uS8XXMDwO+B3jk+wjEHZXOhC7/Xx/A+QZZ+30hT2CISM9FUhZSARnaal375fg4emU56si5lyoUQQgghfqYkSIkuy0nzkBLQ+XxVIygOtq2gaeDTVWzHobQqhmk74DhUmDFsGyLGzo5DbeFNziN35GnU/vQOhRN/S0rh+F127RZ+r8awvskoihsUTdPBtBz+Z2o+xx+Yzcv/qWJDVRRVUchK8dA33y9FI4QQQggh9gESpESXbaiKUttoEDHcdUF+H0RjNptqotgWaKpCkl+lIWRhxNwA1dUYFar+kYqvn6X3QVe12UA3Z8R/kzPiv1E1z86/oK2oirsGy7BsMlO8OI7KuooIgwuD7ihThpfLTuotm+QKIYQQQuyDJEiJLmmp2GfZDn1zffy0KUxdjY3RajNdy3KwbQvL3rwXVBeYkQbKvnicmh9eBxwqUgrpNe68+OO7I0C10FUwLIdozC3bXlkfIy3Jw6ThafGwJJvkCiGEEELsmyRIiS6prDdYWdJMZV2M8toYpuUmJXvz5rmOsnmvpy6uh3Jsi5pVb1L22aNYscb48cbS5eSPPQdF3X0fXVVxC0zomoID1DYZoMDgwqBM2xNCCCGEEIAEKdEB23aorDfa7HUU9GngQMSwCfo0fioNsXZTmKawGd8Y17KJj0btTEm+UOVKNi5d0KaQhKoHyBt9JllDT9htIUrbXHxQVdyRpvQUDznpXk45OIfeOX6ZtieEEEIIIeIkSIk21ldE+HhFPStLmimrjhExbDTVDRZeXSU9WSc9Sae8NkZDyCRqbM5Mzs6XMzcj9Wz67G/UrnqzzfH0/ofSa9xv8ASzdvIO26Zr7pou23awLEgNKuSmexk9MJn9B6VIgBJCCCGEEG1IkBKAOwr15eomFi+tprbRpDlsYtk2Xk2hpsnEcSDJr6Lg7g+1sTpC1HBHoHZFxHBskx9fuxyjuTJ+zJ/el4KJF5OcP3IX3MGlq2C22gNYUyCw+XUpChimGwezUj30yvK1WQ8lhBBCCCFECwlSgvUVET76po5/f1NHXZOFZVnYjkJ6skY4aqMqgOIGjVDUYmNlhGjMjheQ2BUFzRVVJ3voCWz69GFUT5D8MWeTVXw8iqrtgqu70pNUUgIaFfUGmqqQlqSTGtRoilg0hW1My0FTFTyqw7A+AX5xYLashxJCCCGEEB2SILWPW18RYdFHVZTXRTFMh4BPparOxLQdwlF36MajK2iaQl2TiaaCabHTm+oa4RpUzYfmTYofyxp6AmakgezhJ+IJZHb52hkpKn1z/ZRWxwhHbTy6SkpQxbQcQjEHr0clxa8xdnAKaUk6zRGbmGlhGA7ltRHSvM2ceVgWqckSooQQQgghRMckSO3DWkqY14cM8tK9bKyK0hx2y5XrGpimO3XPNhzs2K7ZSNexTapWvkr5l0+SOegICiZcGH9M1TxtSpsnSlHA51EoyvaTEvTQ36sRMx28uoJHczcJzknz0L9XgO/Xh6hrNvHoKgGfiqJAQyhGr0wfQ7Ob0FV1V7xcIYQQQgjxMyVBah9WWW9QUhkhN82LZTtEYjaG5e4DZZlb9n7q6h5QW2sq+4rSpQuI1K0DoGrlK2QMOpJARv9dcv3cNA99833893/lkeTXCPo0slJ0qhvNdhvmDuuTxMcr6impjFDd4ODRFQYXBhnb30djVfUuaY8QQgghhPj5kiC1DwtFLWKGg8+r0hw2MUynzYa6u4oRqqJ0+cPUr32/1VGFzIFH7NQUvtYyk1UKc7wM75vM8D5JbQpEdLRhbp9cP0XZPirrjTYhKxIJ813VLmmSEEIIIYT4GZMgtY9p2SMqFLVojlh4dKisi1FSGSUSs7HsHV+j0/eyDKq+W0TFV89gm+H48UDWYAoPuJhgdvEuuY/PA8lBnbyMxKrsqarSYcgSQgghhBBiRyRI7UNa9ogqqYwQM9y1Q5tqDCrrYuzqCt9Nm75g49IFROtL4sc0Xyr5Y39N5uAjUZRdswZJAVKDOvsPTuWYiVlSZU8IIYQQQuwREqT2ES3V+epDBrlpXnxelUjU4rt1Bk1hC5/uYO/C0ahI3fpWIUoha8gvyBv7K3Rfyi65vqZCwKsyvF+Qkw7KZfSAZNnvSQghhBBC7DESpPYBravz9c31oyhu4GgIWYRibh3zUGzX7AfVIqv4WGpWvYGq+ymYeBHBrEE7dT1NdYteKIDuURg3OJlfTMxm7KAUCVBCCCGEEGKPkyC1D2hdnQ+gKWxR0xhjZUmYSNRG1xRiRtev37BxGeHqH8kbdWb8mKJq9J92M7o/faen8WkK+D1go+DzqEwYmsLlJ/ZG16VEuRBCCCGE6B4SpPYBLdX5IobN6k1hKutjVDe4VfocB6Jm18aiYo1llC5/kIaS/wAKKQXjCWYPiT/e1Yp8uuZu+hv/WQdNU0kL6AwqDHDqwXkSooQQQgghRLeSIPUzZ9sOzRGL+maDtWVhIoZNc9jGMB1UBbqSoWwzSuWK56n45h84VmzzUYfan95uE6QSpQJBv0Jqkk44amM7DhnJOkkBndSAxpDeQSaPSJeCEkIIIYQQottJkPoZa6nSt648xJpNYZoibVNTovtFOY5Dw4YlbFr2ILGmsvhxPZBBr3HTSe9/aJfbmuRTSAlqZKd5Cfo1euf6OGxMBkl+vd1mukIIIYQQQnQ3CVI/I633iKptNPn313U0hE2q6qLtQlSiog2llC77C40bl205qGhkDzuRvFFnonmDXb62rsLh+6dzwLAMMlJ0CU1CCCGEEGKvJ0HqZ6LtHlE2pdUxTNtBVx1Wb4rt+ALbEar+kZ9evwrHNuPHkvJHUTjxYvzpfXbq2poCgwoDnHRQHr2yfDt1LSGEEEIIIfYUCVJ7mdajSp0dmdl6jyjTclhbHqGuMUZTZOfbFMgciD9jAOHqH/AEs+g1/nzS+h4cL6PeVUEv7D84BUVViRi7cBMrIYQQQgghdjMJUnuRtqNKDl6PQu8cP5NHpNEn199hyALa7RFV22QQCltdDlFGuBZPICP+s6KoFB5wMfXrPiJ31OlonsBOv1a/DuOK08hK9dAQMgn6tJ2+phBCCCGEEHuKBKm9xNajSj6vSjRms6o0RGWdwcShKawpi7QLWYMKA/ywoZmAV6M5YpPkVwlHLOpD1o5vuhXLCFPx1d+p+u5FBhx5G0m5I+KPBbOH7FRFvhaqAhnJGilBnYxkncr6GIMLg/FQKIQQQgghRE8gQWovYNtOu1ElgKBfo6/Pz7frmnjszSbSknRy073kZHuIGQ5frW7kvS9raQiZJPs1dE0hJaDRGDaxEpgp5zgO9Ws/YNOnf8UIVQOwcckCBh87B0XduZEiBVAUcBw3RCUHVfxehYBfpbrBIC3Zw6ThaVJYQgghhBBC9CgSpPYClfUGJZURctO87dYd1TebbKwyaAiZRGI2dU0GAa9GMKBR02BQ12ziOBDwqqiqQmWdQXmt0el7R+rWsXHpAprLvoofU1QPqb0PwHFsFHYuSHl00HUFr67Gw5TlKKQGdQYXBZk0PE32hRJCCCGEED2OBKm9QChqETMcfF61zfH6ZpMVa0M0RUw0DXQNmiI25bUGpu2gKQp+r0LMtKlqMFBwqG7s3FCUFQtR/uWTVK18GZwtz0kpnEDBxN/iS+mV8OtoPaikb85ffq+KR1dJDmjkZXjonetnRN9kBvQKSIlzIYQQQgjRY0mQ2gsEfRpej0I0ZhP0uwnEtm1WlYZpDJvguNPjGkI2tu2gaxCJgaU4xEwH24FwrHNrohzHoW7Nu2z69GHMcG38uDc5n4KJF5JadEDC7dcVUFRwcPeEykz1khJQ6V8Q4JjxWcQsh4BPJdmvS3gSQgghhBA/CxKk9gI5aR565/hZVRqir89PQ8jip40hSiqjOI5D1HDQVDdcKQrETAcHd91RV9T88Ho8RCmal9yRp5Ez4lRUzdvpa/g87ghUzATLBs2BgE8lN91DapJOryw/J07Olml7QgghhBDiZ0mC1F5AVRUmj0ijss7gu/XN1DZahKMWtu2g4KCqYFhg2S2Bquv3UhSFggMu5sdXLyO16AAKJlyANzmv08/3ajCwMEi/fD8HjUhjU02ML35soCFs4vNopAQ1+uYFZO2TEEIIIYT4WZMgtZfok+vn+MlZPPhqKc0RCwcH02o75GQ74FjuFLrOcByb2lVv4U3JJzl/VPx4IKM/Q05YgD+td6fbpwKZqRoDCgIM75vcJij9YmJWwpsICyGEEEII0ZNJkNqLBLwaGck6Aa/K6rIwiqJgWu4aqBadDVGhqh8oXbqAUNX3+NJ6M/i4eajalr2aOhuivDoM7R3gzGn5pPh1kgLt1zmpqkJeRuenBQohhBBCCNHTSZDai4SiFlHDpqohRmOzhWW3DVGdYUYaKPviMWp++CctsStaX0LjxuWk9ZnU6et4dCjI9DKsbxInT8mVaXpCCCGEEEK0IkFqLxL0adi2Q2lVjHDMTihEObZFzao3KPvsMaxYY/y4L603BRMvIqXXmE5fKzNFY3BhkGF9k2StkxBCCCGEEB2QILUXyUnz4CgKzRG701P4AJorV1K6dD7h6lXxY6oeIG/0mWQNPaHNlL7t8Xvg9Kl5jB+aKqXKhRBCCCGE2A4JUnsJ23Yor4sRilgJhaiq7xZRuuwvbY6l9z+UXuN+gyeY1alr6CqMH5LMuUcV0C8/kMDdhRBCCCGE2DdJkNoLrK+I8PGKen4oaWbVhuaEnptcsD+KquPYJv70vhRMvJjk/JHbfY4KpCappCXrHDIyjf8anUmvTJ+MPgkhhBBCCNFJEqS62fqKCIs+qqKsNkp1fZRwbPvnW0YIzROM/+xP603uqDPQPAGyio9HUbVtPldRID1JY0iRrH8SQgghhBBiZ0iQ6ka27fDxinrKaqPUN5k0hre9NsoI1bDps0cIVX7HkBMWoGpbyo3njTpju/fxaDBuSCqT90tlYH6gwxLmQgghhBBCiM6TINWNKusNSioihKMWMdMm6FOpbWy7RsqxTapWvkL5l09iG2H3eSte2GF4AtAVOGJ8Gv/9X73Iy/BKcBJCCCGEEGIXkSDVjUJRi8awRShqkeTXiBk2qgqW7T7eVPYVG5cuIFq3Lv4czZuMJ5C5zWtqQN98D4fvn8VxB2Tj9W57qp8QQgghhBCiayRIdaOgT0NRIGZAckAhoKr4PQr1tZVsXP4w9Wvfb3W2Qubgo8gfey66P63NdXQVkoMqBVk+zjgsn/0HpcjokxBCCCGEELuRBKlulJPmoXeOnzWbIpimjaba1H3/It9//AS2GY6fF8gaQuEBFxHMLm7zfFWB3DSd/gUBhhQFmTwiXYpHCCGEEEIIsQdIkOpGqqowbf8Mvl7TRGWDQcCu5PuP/oZtGQBovlTy9/81mYOORFNUNA10TSHgUxnQK8Dxk7PISfMR9GlSPEIIIYQQQog9SIJUN+uXH+DMw/J4+p1yahtz6D/+dH5a+hQD9z+eoVPOJSUtk3GDUxjWJ4BhgaooFGb5pHiEEEIIIYQQ3UiC1F7ggGFp5GV6eevTGnpnn8vI8VPpO7CYvnkB2etJCCGEEEKIvVC3Bynbtpk3bx7/+Mc/aGxsZMKECdxwww307t27w/Nra2u55ZZb+OCDD1AUhWOPPZZrr72WQCCwh1u+a/XLC/C/RxdQWZ9DKNpPpusJIYQQQgixF1O7uwHz58/n6aef5uabb+bvf/87tm0zffp0YrFYh+dffvnlrFu3jkcffZQ5c+bw/vvvM2vWrD3b6N1EVRXyMrz0zw/I1D0hhBBCCCH2Yt0apGKxGI888giXX345hx56KEOHDuWee+6hrKyMN998s935n3/+OUuXLuWOO+5gxIgRTJo0iZtuuolFixZRXl7eDa9ACCGEEEIIsS/q1iC1cuVKmpubmTRpUvxYamoqw4cPZ9myZe3OX758OTk5OQwcODB+bOLEiSiKwqeffrpH2iyEEEIIIYQQ3bpGqqysDIBevXq1OZ6bmxt/rLXy8vJ253q9XtLT09m0aVOX2+E4DqFQqMvP355wONzmn2LvJv3V80if9TzSZz2P9FnPI33W80if7R0cx0FROre8pluDVMsHxev1tjnu8/mor6/v8Pytz205PxqNdrkdhmHw3Xffdfn5nbF27drden2xa0l/9TzSZz2P9FnPI33W80if9TzSZ92vo7zRkW4NUn6/W9Y7FovF/x0gGo12WIXP7/d3WIQiGo0SDAa73A6Px8OgQYO6/PztCYfDrF27ln79+vX4yoL7Aumvnkf6rOeRPut5pM96Humznkf6bO+watWqTp/brUGqZZpeRUUFffr0iR+vqKiguLi43fn5+fm89dZbbY7FYjHq6urIzc3tcjsURdmpINYZgUBgt99D7DrSXz2P9FnPI33W80if9TzSZz2P9Fn36uy0PujmYhNDhw4lOTmZJUuWxI81NDTw7bffMmHChHbnT5gwgbKyMtatWxc/tnTpUgDGjRu3+xsshBBCCCGEEHTziJTX6+Xss8/mrrvuIjMzk8LCQmbPnk1+fj5HHnkklmVRU1NDSkoKfr+f0aNHs//++3PFFVcwa9YsQqEQN9xwAyeddBJ5eXnd+VKEEEIIIYQQ+5Bu35D38ssv59RTT+X666/njDPOQNM0Hn74YTweD5s2bWLKlCksXrwYcIfa5s2bR1FREeeeey4zZszgkEMO+dlsyCuEEEIIIYToGbp1RApA0zSuueYarrnmmnaPFRUV8f3337c5lpWVxX333benmieEEEIIIYQQ7XT7iJQQQgghhBBC9DQSpIQQQgghhBAiQRKkhBBCCCGEECJBEqSEEEIIIYQQIkESpIQQQgghhBAiQRKkhBBCCCGEECJBiuM4Tnc3ojt99tlnOI6D1+vdLdd3HAfDMPB4PCiKslvuIXYd6a+eR/qs55E+63mkz3oe6bOeR/ps7xCLxVAUhf3333+H53b7PlLdbXd/UBVF2W0hTex60l89j/RZzyN91vNIn/U80mc9j/TZ3kFRlE7ng31+REoIIYQQQgghEiVrpIQQQgghhBAiQRKkhBBCCCGEECJBEqSEEEIIIYQQIkESpIQQQgghhBAiQRKkhBBCCCGEECJBEqSEEEIIIYQQIkESpIQQQgghhBAiQRKkhBBCCCGEECJBEqSEEEIIIYQQIkESpIQQQgghhBAiQRKkhBBCCCGEECJBEqSEEEIIIYQQIkESpHaSbdvcd999HHzwwYwZM4bzzz+fkpKSbZ5fW1vLVVddxYQJE5g4cSJ//OMfCYfDe7DFItE++/HHH7ngggs44IADmDRpEpdffjmlpaV7sMX7tkT7q7WXX36Z4uJiNmzYsJtbKVpLtM8Mw+Duu++On3/22Wfz3Xff7cEWi0T7rLq6mquuuooDDzyQAw44gCuuuILy8vI92GLR2l/+8hfOOeec7Z4j3z/2Lp3pM/n+sfeTILWT5s+fz9NPP83NN9/M3//+d2zbZvr06cRisQ7Pv/zyy1m3bh2PPvooc+bM4f3332fWrFl7ttH7uET6rLa2lvPOOw+/388TTzzBQw89RE1NDdOnTycajXZD6/c9if6Otdi4cSM33XTTHmqlaC3RPps1axYLFy7k1ltv5YUXXiAzM5Pzzz+fxsbGPdzyfVeifTZjxgxKS0v529/+xt/+9jdKS0u55JJL9nCrBcBTTz3Fvffeu8Pz5PvH3qMzfSbfP3oIR3RZNBp1xo4d6zz11FPxY/X19c6oUaOcV155pd35n332mTNkyBBn1apV8WMffvihU1xc7JSVle2RNu/rEu2z5557zhk7dqwTDofjx0pLS50hQ4Y4H3/88R5p874s0f5qYVmWc8YZZzi/+tWvnCFDhjglJSV7ornCSbzP1q9f7xQXFzvvvvtum/OnTp0qv2N7SKJ9Vl9f7wwZMsR5++2348feeustZ8iQIU5tbe2eaLJwHKesrMy58MILnTFjxjhHH320c/bZZ2/zXPn+sXdIpM/k+0fPICNSO2HlypU0NzczadKk+LHU1FSGDx/OsmXL2p2/fPlycnJyGDhwYPzYxIkTURSFTz/9dI+0eV+XaJ9NmjSJ+fPn4/f748dU1f21aWho2P0N3scl2l8tHnjgAQzD4MILL9wTzRStJNpnH330ESkpKRxyyCFtzn/nnXfaXEPsPon2md/vJykpiZdeeommpiaamppYtGgR/fv3JzU1dU82fZ+2YsUKPB4PL7/8MqNHj97uufL9Y++QSJ/J94+eQe/uBvRkZWVlAPTq1avN8dzc3PhjrZWXl7c71+v1kp6ezqZNm3ZfQ0Vcon1WVFREUVFRm2MPPvggfr+fCRMm7L6GCiDx/gL46quveOSRR3j++edlzUY3SLTP1qxZQ+/evXnzzTd58MEHKS8vZ/jw4cycObPNlz6x+yTaZ16vl9tvv50bbriB8ePHoygKubm5PPnkk/EvemL3O+ywwzjssMM6da58/9g7JNJn8v2jZ5D/4u2ElkWaXq+3zXGfz9fh/NVwONzu3O2dL3a9RPtsa0888QRPPvkkV199NZmZmbuljWKLRPsrFApx9dVXc/XVV9OvX7890USxlUT7rKmpiXXr1jF//nyuvPJKFixYgK7rnHnmmVRXV++RNu/rEu0zx3H47rvvGDt2LE899RSPPfYYBQUFXHzxxTQ1Ne2RNovEyPePnk++f+ydJEjthJbh1q0X40ajUQKBQIfnd7RwNxqNEgwGd08jRRuJ9lkLx3G49957ueWWW7jooot2WGlH7BqJ9tctt9xC//79Of300/dI+0R7ifaZrus0NTVxzz33MGXKFEaNGsU999wDwIsvvrj7GywS7rPXX3+dJ598ktmzZzNu3DgmTpzIAw88wMaNG3n++ef3SJtFYuT7R88l3z/2bhKkdkLLMHlFRUWb4xUVFeTl5bU7Pz8/v925sViMuro6cnNzd19DRVyifQZuaeZrrrmGBx54gOuuu44ZM2bs7maKzRLtrxdeeIGPP/6YsWPHMnbsWM4//3wAjjvuOB544IHd32DRpf8u6rreZhqf3++nd+/eUrZ+D0m0z5YvX07//v1JTk6OH0tLS6N///6sW7du9zZWdIl8/+iZ5PvH3k+C1E4YOnQoycnJLFmyJH6soaGBb7/9tsP5qxMmTKCsrKzN/2iWLl0KwLhx43Z/g0XCfQZw7bXX8s9//pO7776bX//613uopQIS768333yTV199lZdeeomXXnqJW265BXDnlcso1Z7Rlf8umqbJ119/HT8WiUQoKSmhb9++e6TN+7pE+yw/P59169a1mRIWCoXYsGGDTKndS8n3j55Jvn/s/aTYxE7wer2cffbZ3HXXXWRmZlJYWMjs2bPJz8/nyCOPxLIsampqSElJwe/3M3r0aPbff3+uuOIKZs2aRSgU4oYbbuCkk07a5miI2LUS7bOFCxeyePFirr32WiZOnEhlZWX8Wi3niN0n0f7a+ot3y0L5goIC0tPTu+EV7HsS7bPx48czefJkfv/733PTTTeRnp7Offfdh6ZpnHjiid39cvYJifbZSSedxMMPP8yMGTP43e9+B8C9996Lz+fjlFNO6eZXIwD5/tEDyfePnklGpHbS5Zdfzqmnnsr111/PGWecgaZpPPzww3g8HjZt2sSUKVNYvHgxAIqiMG/ePIqKijj33HOZMWMGhxxyiGyIt4cl0mevvvoqAHfeeSdTpkxp86flHLF7JdJfYu+QaJ/NnTuXiRMncumll3LqqafS1NTE448/Lguq96BE+iw3N5enn34ax3E499xzOe+88/B4PDz99NOkpKR08ysRgHz/6IHk+0fPpDiO43R3I4QQQgghhBCiJ5ERKSGEEEIIIYRIkAQpIYQQQgghhEiQBCkhhBBCCCGESJAEKSGEEEIIIYRIkAQpIYQQQgghhEiQBCkhhBBCCCGESJAEKSGEEEIIIUSP9Je//IVzzjknoeeYpsmcOXOYOnUqY8eO5ayzzuKLL75I+N4SpIQQYitz586luLi4u5vxs/P2229zyimnUFpayoYNGzjssMP45ptvdsm1Kysr+eMf/8i0adPYb7/9KC4upri4mCOOOALTNHfJPcTP06WXXsrcuXNpbGzkpZde4vjjj+/uJgkhOumpp57i3nvvTfh5CxYs4B//+Ac333wzL730Ev3792f69OlUVFQkdB3ZkFcIIYA1a9Ywf/58PvroI2pqanAcB4/Hw4ABAzjllFM455xz0DStu5vZo5mmyYUXXsi///1vAE4++WRuv/32nb5uY2MjJ554IsXFxZxwwgnk5OTg9Xrxer0MHDgQj8ez0/cQP18rVqxg+vTp1NTUEAwG+fOf/8zUqVO7u1lCiO0oLy/nxhtvZMmSJeTn55Odnc0TTzzR6eefeOKJTJo0iZkzZwLQ1NTEuHHjmDt3LkceeWSnr6Mn3HIhhPiZWb58Oeeffz55eXlceeWVfPrppyxcuJD777+fTz75hNmzZ7Ns2TLmzp2LqspAflfpus7DDz9MSUkJmqZRUFCwS677wgsvkJOTw4IFC3bJ9cS+ZcSIEbz33nuUlJSQn59PcnJydzdJCLEDK1aswOPx8PLLL3P//fezcePGNo+/++67zJ07l1WrVpGXl8exxx7LxRdfjNfrBSArK4t3332Xs88+m169evHss8/i9XoZOnRoQu2QbwRCiH2aYRhce+21ZGdn8+KLL3LqqafGv+D/13/9FzNnzuSmm27irbfeYuHChfHnLVu2jN/85jdMmDCB/fbbj8MOO4y5c+di2zYAGzZsoLi4OP6c8vJyTjrpJA4++GAWLlwYn3q29Z+Wvx0rLi5m7ty58fs5jsPpp59OcXExGzZsYMmSJRQXF7NkyZI2r+ecc85pM1fctm0efPBBjjjiCPbbbz+OOuqoDv/W7qWXXuLkk09m9OjRHHroodx9993EYjGg/VTH1157jQkTJnD33Xe3e50A0WiUww8/vM1zWrerd+/eFBQUcPfdd7d7bkcWL17MKaecwtixYznooIO44YYbqK+vjz++ZMkSpk6dyuOPP87hhx/OyJEjOfHEE3njjTfij3f0Hm9LZ96zc845h+LiYs4777w2xy3L4qCDDtrh62p5fkd/NmzYAMDMmTM555xzeP755+Pz+M8991xWrlzZ5lpr167l8ssv56CDDmLMmDGcc845fPrpp23Oee6557b7eWtp+4MPPshxxx3HqFGjGDNmDKeffjr/+c9/APjkk08YOXIks2bNavM6Wn/e7rjjDkaNGsUHH3ywzdf+j3/8g1NOOYUxY8YwatQoTjzxRF5//fX44y2/Hy3vw5IlS5gyZQpXXnkl0P53A9p/Rjuanvvhhx+2ec2tP7s+n49Bgwbh8XjafXaFEHuflv/n9u7du91jH3zwATNmzOC0007j1Vdf5cYbb+T111/nmmuuiZ/zhz/8If77PnLkSO655x7uu+8++vTpk1A7ZERKCLFP++KLL9i4cSPXX389gUCgw3NOOeUUZs+ezWuvvcapp57KypUr+fWvf83RRx/NPffcg+M4vPLKK8ybN48BAwZw7LHHtrvGggULSE5O5qabbqKoqIhnn30WgPnz5/Ptt98yb948ADIzMztsw6JFi/j8888Tfn2zZs1i4cKFXHjhhYwdO5Zly5Zx66230tDQwCWXXAK4c8xvuukm/vu//5srr7ySkpIS7rzzTurr67npppvaXC8SiXDTTTcxffp0jj/++HhwbO2vf/1r/Evwtqxfv55HH310h+2fP38+9913H2eeeSZXXHEFJSUlzJkzhy+++ILnnnsOv9/Pxo0bWb9+PVVVVcyYMYOioiJef/11Lr/8cu644w6mTZsWf78vvfTSXfKeASQlJbFs2TIaGxtJSUkBYOnSpdTU1OzwHgDDhw/nxhtvjP/83nvvtRtV++6771i9ejVXXnklaWlp3HfffZx99tksXryY3NxcVq1axWmnnUa/fv24/vrr8Xg8PP7445x77rk88sgjTJw4EXD7beTIkVx//fXxa2/9Xtx1110888wzXHXVVRQXF1NeXs7999/P7373O9577734l42rrrqKk046iTFjxrR5/ooVK3jiiSeYM2cOY8eO7fA1P/XUU9xyyy1cdtlljBs3jvr6eh566CGuvvpqxo4dS35+frvn3HTTTRx99NGcffbZnXpfO2IYBrfeeusOz+vMZ1cIsXd74IEHOO200zj99NMB6NOnD3/84x8599xz2bBhA0VFRaxatYqUlBTuv/9+8vLy+Mc//sHVV1/Nk08+ybBhwzp9LwlSQoh9WllZGcB2/xZKURSKioooLS0FYOXKlUyePJnZs2fHp/oddNBBvPPOOyxZsqRdkGpqamLRokXce++9jBo1CtgSmDIzM/F6ve2+lLbW3NzMXXfdxYgRI1ixYgVAfL2WZVnbfN6aNWt47rnnuPLKK7ngggsAmDJlCoqi8Je//IUzzzyTtLQ07r//fqZNm8Ytt9wSf244HOa1117DMIw213z11VfxeDxMnz4dTdPafenctGkTDz30UJu2duTWW29l8ODB2z2nvr6eBQsWcNppp3HDDTfEjw8ZMoSzzjqLF154gbPOOotwOMz69et57LHHOPDAAwE4+OCDqamp4a677uKEE06Iv78t0zp25j3LyMgA3CC0du1aPvjgg3ifL168mAkTJrQbKexIcnJym35fvXp1u3MaGxt54IEHGD9+PACjRo1i2rRpPP7441x99dXMmzcPr9fL448/Hp+Sduihh3Lcccdx55138vzzzwNuf2ZnZ7e539bvRUVFBVdccUWbESafz8dll13G999/z5gxY5g2bRpHHHEETzzxRLvP7GOPPcZhhx3G4Ycfvs3XXFJSwm9+8xsuvvji+LHCwkJOOeUUPv3003a/O5988gnr16/nqaeeIj09fZvX3ZEnnniCUChEdnb2Ns/p7GdXCLF3+/bbb/nqq6/i//0Dd1YHwE8//YSmaVx11VU8+uij8f+2jhw5klWrVjF37lzmz5/f6XvJ1D4hxD6t5cvZjir1VFRUxL9An3TSSTz00EMYhsHKlSt54403uO+++7Asq13wiEajzJs3j9zcXA4++OAutXH+/PlkZGRwxhlnxI+1BLGWINiR//znPziOw2GHHYZpmvE/hx12GNFolE8//ZQ1a9ZQXV3NEUcc0ea5v/nNb1i4cGGbQg3l5eU89NBDnHnmmdssvHHHHXcwfvz47S7W/+CDD/j444/5/e9/v93X/cUXXxCLxTjuuOPaHB8/fjyFhYUsXboUcINufn5+PES1OOaYY6isrGwXUBzHwTTNDkfTOvOetVAUhalTp/L2228DbjGNN998s8MRya4qKiqK/48eIDc3Nz5KBu4I2NSpU9us69F1nWOPPZZvvvmG5uZmwA0JLaNm23L33Xdz7rnnUlNTw/Lly3nhhRd4+eWXAeLTPAFOP/103njjDZYvX47jODiOw+eff87ixYs566yztnuPmTNncvXVV9PQ0MAXX3zBokWLeOqpp9rdA6Curo65c+dywgkn7FSIqqqq4v777+f3v/89Pp9vm+d15rMrhNj72bbN9OnTeemll+J/Fi1axJtvvsmECRP48ssvMQyDkSNHtnne6NGjWbduXUL3khEpIcQ+bdy4caSmpvLCCy9w6qmnoihKu3M++ugjysvL418SI5EIN998M4sWLcI0TYqKihg7diy6rrN1IdRZs2bFp1t1pVDF2rVreeyxx/jrX/8aHxED6N+/P/369eOhhx5i5MiR5OXl8dVXX1FaWhpf41VXVwewzS/25eXl8XCYlZW1w7YccsghjBgxgvPPP7/Dx5cuXcpbb73Fyy+/zGuvvdbhOS1TrKZPn05hYeF279eyDqqjUYTs7GwaGxsBd4pdR1+0W15by3ktWv7HCu6o0NixY7n22msZMmRIp96z1qZNm8ZVV12FYRh88sknqKrKpEmTtvu6EpGXl9fuWFZWVnzEpL6+fpvvj+M4NDU1kZSUxMaNGxkxYsR27/X111/zxz/+ka+//ppAIMCgQYPin6XWn+vx48dz+umntwlNp59+OmeeeSYHHHDAdu+xfv16brjhBj755JN4VcyWxd1b/+788pe/pKCgIKG/He7I3XffzfDhw/nFL37BXXfd1eE5nfnsCiF6hsGDB7NmzRr69u0bP7ZkyRIef/xxZs2aFZ9C/P3338dniQD88MMP9OvXL6F7SZASQuzTgsEgf/jDH/j973/PJZdcwqWXXhr/m/GKigo+/vhjbrvtNgYNGhSf8vSnP/2JN954g3vvvZfJkycTDAYBOvwCff755/PDDz9w5ZVX8uyzz3b4xXh7br31Vg4//HAOPPDANsULFEXh3nvv5bLLLouP2LS0o+XLb2pqKuBOuUpKSmp37YKCgvh6nq3X9dTW1vLtt9+2Wesyd+5cbrzxRm688cZ2600sy+KWW27hV7/6FQMGDNjm63nssceIxWJccMEFVFVVbfe1p6WlAe6IwtbXrKysjC8yLigoaFeAAYgHz62DxtSpU7nkkkuwbZuKigoeeughfvOb3/Cvf/2rU+9Za5MmTcKyLJYuXcrixYs56qijdmllx9ra2nbHqqqq4sE3LS2tw/exsrIScMOkbdt8+eWX/PKXv9zmfZqampg+fTrFxcW89tprDBgwAFVVef/99+NFO1q89NJL8bVUixcvBuC4447jnnvuYb/99tvmfWzb5oILLsDj8fD8888zbNgwdF1n1apVLFq0qN35f/rTn3jwwQe58soreeihh7q0/cBXX33FK6+80maKz9Y6+9kVQvQM559/PjNmzGDevHkce+yxlJWV8Yc//IGioiJycnLIyspi3Lhx/P73v+fGG28kPz+fl156iU8++YRnnnkmoXvJ1D4hxD7vpJNO4oEHHmD9+vWcfPLJPPjgg4C7zub6669nypQpPPHEE/Gg8umnn3LAAQcwbdq0+LFvvvmGmpqadtPFBgwYwL333ouqqvzhD39IqF0ffPABS5Ys2eYUuGHDhvHPf/6TxYsX869//Ytly5ax3377xR9vmRJWW1vLyJEj439qamqYM2cOdXV1DBgwgIyMDN5999021160aBEXXHBBm6mKRx55JLfddhsvvPBC/At0i+eee46ampo2a1+2Vl1dzfz587n22mvx+/07fP2jR4/G6/Xy6quvtjm+fPlySktL2X///QG3nzZs2NCmGIfjOLz44ov069evXVWn9PR0Ro4cyejRozniiCO44IILqKioYPXq1Z16z1rzer0cfPDB/POf/+Stt97iF7/4xQ5fVyLWrl3LTz/9FP+5vLyczz//PB7aJ0yYwLvvvktTU1P8HMuyeO211xg5ciRer5fPPvuMUCi03dGi1atXU1dXx69+9SsGDRoUD4Mt1fdaV6NsWbR9wQUXkJKSQkpKCtOnT+fcc8/l5ptvpqSkpMN71NbWsmbNGk499VRGjhyJrusd3qPFgQceyH333ceSJUt4+OGHE3rfWtx8882cdtpp2y1p3JnPrhCi52gpBPXWW29x/PHHc8011zBlypR4USdVVVmwYAEHHngg1113Haeccgr/+c9/ePTRRxk9enRC95IRKSGEwB2lmDp1KuXl5cyfP5+///3vvPbaaxQWFrar5jdq1Chef/11nnnmGQYOHMjKlStZsGABiqIQDofbXTsYDPJ///d//Pa3v+WNN97gqKOO6lSbvvrqKy6//PLt7rek6zoDBw7s8LGWDWr/7//+j40bN7LffvuxZs0a7rnnHoqKiujXrx+apnHZZZdx0003kZWVxWGHHcaaNWu47777OOuss+KjQi0OPfRQjjrqKG677TYOOeSQNm294447trsHz08//cSBBx7I0Ucf3anXn56ezgUXXMD999+Px+Nh6tSpbNiwgTlz5jBo0CBOPvlkwJ0C9swzz3DxxRfzu9/9jl69evHCCy/w5Zdf8sADD7S7bk1NDV988QWmaVJeXs4jjzxCZmYm/fr1IxgM7vA929rhhx/OddddR1ZWFuPHj28zBXNnOY7Db3/7W6644go0TWPevHmkpaXFR0cvvfRSPvjgA371q1/FR3uefPJJSkpK+Otf/8r69etZsGABY8aMYd26dW3m/8diMWpqali/fj39+/cnOTmZBx54AF3X0XWdN954o02xCoBbbrmFjIwMLrvssnZtveyyy/jnP//Jn/70pw7f96ysLAoLC3nqqafIz88nNTWVDz/8kMcff7zNPVobOnQov/rVr5g/fz7HHXdc/HehrKyML774In5ey1rBb7/9luHDh8ePt7wP29OZz64QYu/V0cbuxxxzDMccc8w2n5OWlhafYbEzJEgJIUQreXl58alggwYN6vCcmTNnYhgG9957L7FYjKKiIi666CJWrVrFO++802ElvalTpzJt2jRuu+02Dj744PhI1vYUFRUxffr0nXo9t912G3/5y1/4+9//TllZGVlZWfziF79gxowZ8alSZ511FsFgkIcffphnn32W/Px8zj///G2uhfp//+//ccwxxzB37tz4F/qxY8dy4oknbrctuq63Kb/dGZdddhnZ2dk8+eSTPPvss6Snp3P00UczY8aM+Hvo8Xh45JFHmD17NnPnzqWxsZH+/fszb948Dj300HbXfP/993n//feBLaNTt9xyS/x6nXnPWps6dSqKonDMMcfs8g2bCwoK+N///V9uvfVWwuEwkydPZsGCBfE1YYMHD+bpp5/mz3/+M9dddx2KojBq1Cgef/xxxo8fz8yZM/n3v/8NwP/8z/90+F5kZmZy++23M3/+fO68805+97vfkZSUxLBhw3jyySc5//zz44Ul3n33XebPn9/hVgGBQIAbbriBCy+8kLfffrvD6n3z58/nT3/6EzNnzsTr9TJo0CAWLFjArbfeyvLly9tUDGxx6aWX8vrrr3PrrbfG/0b5+eef73C63qWXXso777wT/3nGjBnt/jJga5357AohREcUZ+vVnUIIIYTodjNnzmTp0qVtgkFXrgEd/41tZx7vSRYuXMi8efN26v0SQohEyBopIYQQQgghhEiQTO0TQgghfqa2LrSR6OM9SWZmJsOGDevuZggh9iEytU8IIYQQQgghEiRT+4QQQgghhBAiQRKkhBBCCCGEECJBEqSEEEIIIYQQIkESpIQQQgghhBAiQRKkhBBCCCGEECJBEqSEEEIIIYQQIkESpIQQQgghhBAiQRKkhBBCCCGEECJBEqSEEEIIIYQQIkH/H81FxNgXtWomAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "import seaborn as sns\n",
+    "import pandas as pd\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.ensemble import RandomForestRegressor\n",
+    "from sklearn.metrics import mean_squared_error, r2_score, mean_absolute_error\n",
+    "from sklearn.model_selection import cross_val_score\n",
     "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
     "\n",
-    "sns.histplot(train_data[\"Volume\"], kde=True, color=\"skyblue\")\n",
-    "plt.title('Распределение объема в обучающей выборке')\n",
-    "plt.xlabel('Объем')\n",
-    "plt.ylabel('Частота')\n",
-    "plt.show()\n",
+    "# Удаление строк с NaN\n",
+    "feature_matrix = feature_matrix.dropna()\n",
+    "val_feature_matrix = val_feature_matrix.dropna()\n",
+    "test_feature_matrix = test_feature_matrix.dropna()\n",
     "\n",
-    "sns.histplot(val_data[\"Volume\"], kde=True, color=\"salmon\")\n",
-    "plt.title('Распределение объема в контрольной выборке')\n",
-    "plt.xlabel('Объем')\n",
-    "plt.ylabel('Частота')\n",
-    "plt.show()\n",
+    "# Разделение данных на обучающую и тестовую выборки\n",
+    "X_train = feature_matrix.drop(\"Volume\", axis=1)\n",
+    "y_train = feature_matrix[\"Volume\"]\n",
+    "X_val = val_feature_matrix.drop(\"Volume\", axis=1)\n",
+    "y_val = val_feature_matrix[\"Volume\"]\n",
+    "X_test = test_feature_matrix.drop(\"Volume\", axis=1)\n",
+    "y_test = test_feature_matrix[\"Volume\"]\n",
     "\n",
-    "sns.histplot(test_data[\"Volume\"], kde=True, color=\"lightgreen\")\n",
-    "plt.title('Распределение объема в тестовой выборке')\n",
-    "plt.xlabel('Объем')\n",
-    "plt.ylabel('Частота')\n",
+    "# Выбор модели\n",
+    "model = RandomForestRegressor(random_state=42)\n",
+    "\n",
+    "# Обучение модели\n",
+    "model.fit(X_train, y_train)\n",
+    "\n",
+    "# Предсказание и оценка\n",
+    "y_pred = model.predict(X_test)\n",
+    "\n",
+    "rmse = mean_squared_error(y_test, y_pred, squared=False)\n",
+    "r2 = r2_score(y_test, y_pred)\n",
+    "mae = mean_absolute_error(y_test, y_pred)\n",
+    "\n",
+    "print(f\"RMSE: {rmse}\")\n",
+    "print(f\"R²: {r2}\")\n",
+    "print(f\"MAE: {mae}\")\n",
+    "\n",
+    "# Кросс-валидация\n",
+    "scores = cross_val_score(model, X_train, y_train, cv=5, scoring='neg_mean_squared_error')\n",
+    "rmse_cv = (-scores.mean())**0.5\n",
+    "print(f\"Cross-validated RMSE: {rmse_cv}\")\n",
+    "\n",
+    "# Анализ важности признаков\n",
+    "feature_importances = model.feature_importances_\n",
+    "feature_names = X_train.columns\n",
+    "\n",
+    "print(f\"=====================================\")\n",
+    "\n",
+    "# Проверка на переобучение\n",
+    "y_train_pred = model.predict(X_train)\n",
+    "\n",
+    "rmse_train = mean_squared_error(y_train, y_train_pred, squared=False)\n",
+    "r2_train = r2_score(y_train, y_train_pred)\n",
+    "mae_train = mean_absolute_error(y_train, y_train_pred)\n",
+    "\n",
+    "print(f\"Метрика Train RMSE: {rmse_train}\")\n",
+    "print(f\"Метрика Train R²: {r2_train}\")\n",
+    "print(f\"Метрика Train MAE: {mae_train}\")\n",
+    "\n",
+    "# Визуализация результатов\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "plt.scatter(y_test, y_pred, alpha=0.5)\n",
+    "plt.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], 'k--', lw=2)\n",
+    "\n",
+    "plt.xlabel(\"Фактический объем продаж акций\")\n",
+    "plt.ylabel(\"Предсказанный объем продаж акций\")\n",
+    "plt.title(\"Фактический объем / Предсказанный объем\")\n",
     "plt.show()"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### **Вывод**\n",
+    "\n",
+    "**Качество предсказаний:** Модель демонстрирует впечатляющий коэффициент детерминации R² на уровне 0.9975, что свидетельствует о ее способности эффективно объяснять изменения в распродажах. Низкие значения RMSE и MAE подтверждают, что модель предсказывает цены с высокой степенью точности.\n",
+    "\n",
+    "**Проблема переобучения:** Разница в значениях RMSE между обучающей и тестовой выборками относительно мала, что говорит о минимальных рисках переобучения. Тем не менее, важно оставаться внимательным и продолжать следить за этим аспектом.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "123"
+   ]
   }
  ],
  "metadata": {