maths/operations_research/bnb.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MIP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step 1: Solving root relaxation (continuous problem)\n",
      "Root relaxation objective: 11.500000\n",
      "Root solution: [4.41996831e-10 6.28249789e-09 2.00000000e+00 4.99999999e-01]\n",
      "\n",
      "Starting branch and bound process:\n",
      "\n",
      "Step 2: Exploring node S0\n",
      "  Branching on variable x_4 with value 0.500000\n",
      "  Creating two branches: x_4 ≤ 0 and x_4 ≥ 1\n",
      "  S1 relaxation objective: 10.500000\n",
      "  S1 solution: [2.34547440e-10 4.29042723e-10 1.50000000e+00 9.87950288e-12]\n",
      "  S2 relaxation objective: 9.000000\n",
      "  S2 solution: [3.74607140e-10 7.58122976e-09 2.00000000e+00 9.99999998e-01]\n",
      "  Found new best integer solution with objective 9.000000\n",
      "\n",
      "Step 3: Exploring node S1\n",
      "  Branching on variable x_3 with value 1.500000\n",
      "  Creating two branches: x_3 ≤ 1 and x_3 ≥ 2\n",
      "  S3 relaxation objective: 7.000000\n",
      "  S3 solution: [ 1.81128910e-13  6.48071634e-10  1.00000000e+00 -1.17886828e-10]\n",
      "  S4 is infeasible\n",
      "\n",
      "Branch and bound completed!\n",
      "Nodes explored: 2\n",
      "Optimal objective: 9.000000\n",
      "Optimal solution: [3.74607140e-10 7.58122976e-09 2.00000000e+00 9.99999998e-01]\n",
      "+--------+------+--------------------------+------+--------------------------+------+------+---------------------+\n",
      "| Node   |    z | x                        | z*   | x*                       |   UB | LB   | Z at end of stage   |\n",
      "+========+======+==========================+======+==========================+======+======+=====================+\n",
      "| S0     | 11.5 | (0.00, 0.00, 2.00, 0.50) | -    | -                        | 11.5 | -    | {S0}                |\n",
      "+--------+------+--------------------------+------+--------------------------+------+------+---------------------+\n",
      "| S0     | 11.5 | (0.00, 0.00, 2.00, 0.50) | 9.00 | (0.00, 0.00, 2.00, 1.00) | 10.5 | 9.00 | {S1}                |\n",
      "+--------+------+--------------------------+------+--------------------------+------+------+---------------------+\n",
      "| S1     | 10.5 | (0.00, 0.00, 1.50, 0.00) | 9.00 | (0.00, 0.00, 2.00, 1.00) |  9   | 9.00 | ∅                   |\n",
      "+--------+------+--------------------------+------+--------------------------+------+------+---------------------+\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAB8YAAAMWCAYAAACDduxsAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAA0O9JREFUeJzs3QeYlNXdN+D/0pfeRZSiCKKiqCCo2FABkWZiEpOYZnrMl8T08iamx5j6Jqb35I0xPVIUkKIURVHsBRsiCii9s8DCftc5yW6oStllttz3de01nJlnnjlThE1+8zunqKysrCwAAAAAAAAAoJaqV+gJAAAAAAAAAEBVEowDAAAAAAAAUKsJxgEAAAAAAACo1QTjAAAAAAAAANRqgnEAAAAAAAAAajXBOAAAAAAAAAC1mmAcAAAAAAAAgFpNMA4AAAAAAABArSYYBwAAAAAAAKBWE4wDAABQLXXv3j3/1GQLFy6MoqKieMc73lHoqVQb6bVIr0l6bQAAAOBwEYwDAADU4MB1959mzZrFKaecEl/+8pdjw4YNhZ4mB+hLX/rSHu9p/fr1o3379jF06NAYO3Zs1BXpSxF7+4zv60fQDgAAwCtp8Iq3AgAAUK316NEj3vKWt+Q/l5WVxfLly2PixIk5YJ00aVLMnj07B6vULJdffnn06dMn/3nr1q3x7LPPxrhx42LKlCnxox/9KD74wQ9GbXfNNdfEmjVrdrnud7/7XTz//PPxkY98JFq3br3LbbuPAQAAYGeCcQAAgBrsuOOOyyH4zrZs2RJnnXVW3H333TFjxoy48MILCzY/Ds7rXve6eOMb37jLdffee28MGDAgrr/++joTjO/ujjvuyMF4uq2mL7MPAADA4WUpdQAAgFqmcePGMXjw4PznFStW7HXf7tTE/X//7/9Fly5dokGDBrmJm8ybNy9fn9rKrVq1iuLi4jj55JPjm9/8Zmzbtm2Pxyo/X1q2PbV4O3funB8/Lef+97//fa/zSw3o73//+3HGGWdEixYtonnz5nHiiSfGxz72sVi9evUexx/Iufdm7dq1OUw+//zz8zkaNWqUL9/2trflJva+ljNPIeyf/vSnOPXUU/PrcOSRR+Z5bN68eY/7bN++PT9G+qJCkyZN8uV1110XO3bsiMqSXq+2bdvu8Z6W++1vfxsDBw7Mr2f6SX8uf193lq5Lz29vt6XnnG7b/csW6boLLrggXn755Xj729+el3ZPr8mZZ56Z77M3jz32WIwcOTK/x+mzdOmll8ajjz4aVaF8fosXL87va6dOnaJevXq7zG3mzJkxatSoPPf0OerZs2d8/vOfj02bNu31nAd6PAAAANWbxjgAAEAtk4Ln8oAzhbq7S43y1CJPgfPo0aNzMH7EEUfk2375y1/G+PHj47zzzstBZgoB07k++9nP5sbyP/7xjz3OlwLztP91CrXTEuDpPn/+85/jDW94Q17OPd1WLoXKQ4YMiTvvvDMHjVdddVUOHZ9++un4+c9/nkPNNm3aHNS59+WJJ56Ia6+9Nn9Z4DWveU3eh33+/Pk59L7lllvi/vvvj27duu1xv7RkeXqMMWPG5Ncr/fmHP/xhDqZvvPHGXY5973vfG7/5zW/imGOOyW3ukpKS+N73vhd33XVXVJb0pYVVq1bFoEGD9rjtwx/+cNxwww1x1FFHxbve9a58XXqv0uv7wAMPxA9+8INDfvz0ZYpzzjknh9xvfetbY9myZfGXv/wlhg0bludWvvR7kgLwNM/0GXvta1+b3+u5c+fm6/r27RtVYeXKlXmlhPTlgdS2T+9By5Yt820//elP8/uSlltPYXfHjh3jvvvui69//etx++2355/0hYlyB3o8AAAANUAZAAAANc5zzz1Xlv4nXY8ePcq++MUv5p9rr7227Oqrr87XNWnSpOzb3/72Hvfr1q1bvt+wYcPKNm3atMftzz//fFlpaeku1+3YsaPsne98Z77f7Nmz93q+MWPGlG3ZsqXi+qlTp1Y8zs4+/vGP5+vf+ta37vE4a9asKVu/fv1Bn3tf0nlXrly5x/XTp08vq1evXtm73/3uXa5Pr2U6f6tWrcrmz59fcX16vXr16pXvs3jx4orrb7/99nx83759yzZs2FBx/YsvvljWvn37fNvb3/72/Zpr+WNffvnlFe/rZz/72bI3vvGNZU2bNi079thjyx588MFd7jNjxox8nxNOOCE/13KrVq3K8023zZw5s+L63/72t/m6dLm78ueSHndn6br0kz5f27dvr7j+V7/6Vb7+fe973y7Hn3/++fn6P/7xj7tcn55L+bnSZ/hAlZ939/uWn/Oqq67a43P12GOPlTVo0CC/PytWrNjltuuuuy7f7zvf+c5BHw8AAEDNYCl1AACAGiwtBf7lL385/3zlK1+Jn/zkJ/m6iy++OP/sy7e+9a28FPbuunbtGvXr19/lutQ8L9/TeurUqXs9X1oafecG7UUXXZRb2KllXq60tDR+8Ytf5MZxajDv/jjp+rQE+MGc+5Wk86YW8e5Sg/ykk07a53NKy6Yff/zxFeP0er3pTW/Ky6OnhnS5P/zhD/kytdJTG71cam+ncxyM1PYuf1/TkuypJZ/eh/T4aZn2nf3+97/Pl2n58/Rcy6Xm/Re/+MX8570tm36g0nNLy8WnJcrLpWXV04oDO78XixYtynvbpyXvr7zyyl3O8bnPfS63sKtC+oykz/Xun6u0EkH67KVGfbt27Xa57VOf+lR06NAhbrrppoM+HgAAgJrBUuoAAAA1WFrGOi3xvfNy0mmZ8hTIpmWrp0+fnvea3lnaAzvtG76vZdjTEuIpiE3LjaelsP9dyP23JUuW7HGfFHSmJcR3d/TRR8ecOXMqxul869evz4H9zsulv5L9PferScvB/+///m/cc889eSn0FHyW29eS2P369dvr45YvK17uoYceypfnnnvuHsfv7br9kYLXtBx4kuaa9s5O4XYKyqdMmZLf4xRIJ2mp9CTtsb278r3mH3zwwThUvXr12uOLC+XL8O/t9UjLru8u3T8t77+vfckPRfqcpP3Ad3f33Xfny8mTJ8e0adP2uL1hw4b5s3mwxwMAAFAzCMYBAABqkdRwTfuGN23aNO/l/fnPfz4HqTtL+yWn9vHevO51r8t7jKcQ9IorrsjHpiAwBZ+p5Z32J9/dzi3l3UPT1K4ut3bt2oom9f7a33O/kr/97W/5uaRQNn2RoHv37vn1Sa9BCpuff/75vd6vfH/q3R832b59+y7PK7Wo9xbKlu/dfijSY6aGfGp/p73Y0/7maW/v8jb2unXr8uOnJvPeHj89z3TModrb61E+v91fjyR9dvamMl6TAzlv2pc9SfuD748DPR4AAICaQTAOAABQC5W3xPe23Pi+QvF0bArFU3h8yy237LIkdWrRpmD8UJQvoZ3az4dTWmI8teTT8uc9e/bc5bbUjD9UKbxPIX1qou8eTr/88stR2e9rCsbTe1UejKfAOj3+8uXL9wijly1blhv/O4fa5Uuh79ya3z3UPhTlX2ZIj703lf2avNrnuvy5py8HtGjR4lXPc6DHAwAAUDPYYxwAAKAWWr16db7c31Z1kvYmT0aMGLHHPs2zZs065Dml/bpT6JhC3fL5HQ7peZ1wwgl7hOJLly6NBQsWHPL5+/btu8/XqDJet1d7X0877bR8ubflycuvS8uXlytfxn5vX1AoX5a9Ml6P2bNn73FbWpq/MpZ1P5gviZQvkV7ZxwMAAFAzCMYBAABqoe9973v58rzzztvv+6TluvcWaD722GNx3XXXHfKc0pLb73vf+3IrOe2BvvPy20m6PgWnlS09r2eeeWaXpnJJSUl84AMfiG3bth3y+d/61rfmy6985SuxcePGiutT8HyoLfvdQ/Hf/va3e7yvb3/72/Nl2n985yXT0+uZrtv5mPK901O7OrXl0+tQLi3TXhnz7dq1a57fww8/nNvtO/vGN76xy37kh8PVV1+dP3sf+tCHYtGiRXvcnuaz8xcCDvR4AAAAagZLqQMAANRgKfBNS4XvvD/ynXfeGffff39uBl9//fX7fa4BAwbkn7/+9a+5TX3mmWfmYHDcuHG5Rf73v//9kOebwuPUxP2///u/fDl8+PBo3Lhxbm5PmjQph/I7t5srQwo4009qVqc91NMS4mnf9bTEeGo3P/TQQ4d0/sGDB8dVV12VQ+uTTz45XvOa1+S92NM+4Ok1nDBhwgGfM73W8+fPz39OXyB48cUX8/uQ3t9LLrkkXvva11Ycm0Lo9PxuuOGG6NOnT1x++eX5uf3jH//I9/vwhz+8S5DeuXPneNOb3hR/+tOfckiezpeWPf/Xv/6V/5zud6h+/OMfx6BBg+Jtb3tb3HzzzbmtP3fu3LxawLnnnlvpTfpXkl6Tn/zkJ/mLEGnVgksvvTR69OgR69evz5+7GTNmxDve8Y742c9+dlDHAwAAUDMIxgEAAGqwtEx4eSs4SSHz0UcfnUO9z3zmM7m9u7/S8ukpxE33SyF1CjFToPmd73wnB9iVEYynvb5TKP2jH/0o/vjHP8Yvf/nL/Lhpnu9///uje/fuUdk++MEPRsOGDXNwnB4v7XWegv7Ugn/9619fKY+RzturV698mZ5beg8+9rGPxRve8IaDCsZTOL1zQJ32uj7ppJPizW9+c35vy/cJL/fDH/4wB/8//elP4xe/+EW+Lh2fvoiQQvvd/epXv4r27dvn8D6F2CkATvdLoXllBOMpXE5f0Pj0pz+dP0uTJ0+Oc845J1+XPk+HMxhP3vOe9+QvXKSVFGbOnBnjx4/Pe6Gnz91HP/rRXRr1B3M8AAAA1V9RWfoaOQAAAAAAAADUUvYYBwAAAAAAAKBWE4wDAAAAAAAAUKsJxgEAAAAAAACo1QTjAAAAAAAAANRqgnEAAAAAAAAAajXBOAAAAAAAAAC1mmAcAAAAAAAAgFpNMA4AAAAAAABArSYYBwAAAAAAAKBWE4wDAAAAAAAAUKsJxgEAAAAAAACo1QTjAAAAAAAAANRqgnEAAAAAAAAAajXBOAAAAAAAAAC1mmAcAAAAAAAAgFpNMA4AAAAAAABArSYYBwAAAAAAAKBWE4wDAAAAAAAAUKsJxgEAAAAAAACo1QTjAAAAAAAAANRqgnEAAAAAAAAAajXBOAAAAAAAAAC1mmAcAAAAAAAAgFpNMA4AAAAAAABArSYYBwAAAAAAAKBWE4wDAAAAAAAAUKsJxgEAAAAAAACo1QTjAAAAAAAAANRqgnEAAAAAAAAAajXBOAAAAAAAAAC1mmAcAAAAAAAAgFpNMA4AAAAAAABArSYYBwAAAAAAAKBWE4wDAAAAAAAAUKsJxgEAAAAAAACo1QTjAAAAAAAAANRqgnEAAAAAAAAAajXBOAAAAAAAAAC1mmAcAAAAAAAAgFpNMA4AAAAAAABArdag0BOAQ7W9rCzWbtkR23aURWlZWWwvi6hfFNGgqCga1iuKVo3rRf2iokJPEwAAAAAAACgQwTg1LgRfsXl7vLS5NF7eVBpLNm6L5SXbcxi+Lykk79CkfnRu1jCOaNogOhU3iPbF9YXlAAAAAAAAUEcUlZWVvUKkCNXD0o3bYt6Kknhi9ZaKEDztA7DjAM6x8/EpLD+hTePo16FJHNm0YVVMGQAAAAAAAKgmBONUW2lp9BSE37d8cyzbvD1Sv7syP6zl5zuiuH7061Ccg/K09DoAAAAAAABQuwjGqZaB+JyXNsV9y0ti646ySg/Ed1d+/kb1iqJ/hyZxVqemAnIAAAAAAACoRQTjVCuLN26L8QvXx9qtO6o0DN+XFIe3alQvRnVvEUc1s8Q6AAAAAAAA1AaCcapNS3zW0k0xd9nmKm+Iv5ryxx/QsTjOPVJ7HAAAAAAAAGo6wThR11vir6S19jgAAAAAAADUeIJxCmr+6i0xduH6/Ofq+EEs74qP6d4ierdpXODZAAAAAAAAAAdDME7BPLSyJCYu2hA1xfCuzaNvuyaFngYAAAAAAABwgOod6B2gLobiSZpvmjcAAAAAAABQswjGKcjy6TUtFC+X5p3mDwAAAAAAANQcgnEOq8Ubt1XsKV5Tpfmn5wEAAAAAAADUDIJxDpttO8pifA0Pxcul55GeDwAAAAAAAFD9CcY5bGYt3RRrt+6Imh4np/mv2bojZi/dVOipAAAAAAAAAPtBMM5hkZYen7tsc40PxXd2z7LNllQHAAAAAACAGkAwzmFbQr0oapf0fCypDgAAAAAAANWfYJwqN+el2rGE+r6WVE/PDwAAAAAAAKi+GhR6AtRuqU193/KSSg/FN6xeEVN/en3Mnz0lNqxcHsUtW8WRPU+KC9/7ieh4TK+Y+rPr4+m774g1Ly2OZm3axYkXDI+hH/hsNGnRspJnEjFveUmc1alpNKxX2zrxAAAAAAAAUDsIxqlST6zeElurYKnxGz9xVWzfti1e/+UfRdujusWGVcvj2bkzY9Pa1bFu+Uv559Jrvhwdj+0Va5a+GP/6xidi/fKX4spv/7bS57JlR1nMX70lTm7XpNLPDQAAAAAAABy6orKystq2wjXVyG/mr47lm7dXamN88/q18ZXzj4v3/PLmOLbfoP26zyNTxsZfPn91fPnO56N+g8r9PkjqiXcsrh9X9W5TqecFAAAAAAAAKoc9xqkySzdui2WVHIonjYqbRaOmzeLx2ydG6dYt+3Wfkg3rokmzFpUeiifp+b28eXt+vgAAAAAAAED1IxinysxbUZLb1JUthduv//INcf+Ev8SXzz8ufnbVpTH5hq/F0qce2+vxG1evjOm//F6c8dq3RlX+h3T/ipIqOz8AAAAAAABw8CylTpXYXlYW33toZWyvwk/Xti0lsfCBu2PRI/PiqTunxYuP3R+v/cL3o9/oN1UcU7Jhffz66tdF05at423f/2PUb9iwyuZTvyji433bRb2iqvg6AAAAAAAAAHCwBONUiZc3lcZvn1xzWB/zH1+5Jp65e0Z8+tYH8njLxg3xmw++IRo2KY63/+DGaNi4SZXP4Z29W0fH4spfrh0AAAAAAAA4eJZSp0q8tLn0sD9mx2OPj60lm3Zqir8+N8Tf9v3/OyyhePLSpsP/vAEAAAAAAIBXptpKlTXG07cudlTBuTeuWRV/+tS7ov+YN0ennidG42bNY/HjD8bM398QJ55/SQ7Ff3P162Nbyea44ms/iS0b1+efpFmb9lGvfv0q+5ZJCsZPaVclpwcAAAAAAAAOkmCcKrFk47YqCcWTxk2bRZeTT4/ZN/4sVr24MLaXlkbrTp3jjNe8NQa/85p44dH744VH5+VjvzNmwC73/dSEedGmc9cqmdeO/zxvAAAAAAAAoHqxxziVbntZWXz3oZWxow5+suoXRXy8b7uoV1RU6KkAAAAAAAAA/2GPcSrd2i076mQonmwvi1izpaq68gAAAAAAAMDBEIxT6bbV1VT8P+r68wcAAAAAAIDqRjBOpSut46vzp6XkAQAAAAAAgOpDME6VLCdel5XW8ecPAAAAAAAA1Y1g/CCtXLkyOnbsGAsXLoya4nDNuX5R1GkN6vDznzRpUpx66qmxY8d/91nfunVrdO/ePe67776Czg0AAAAAAIC6SzB+kL7+9a/HmDFjcuBXbtq0aXH22WdHixYtolOnTvHpT386SktLX/E8JSUl8cEPfjDatWsXzZs3j8svvzxefvnlXY5ZtGhRjBgxIpo2bZqD7U9+8pOvet79nfPBnHvVqlVx5ZVXRsuWLaN169bxrne9KzZs2FBxe4Oiolj61GPx83eOjC+ceXR8c3jfmPG7Gw54vmVlZTHlp9+Mbww9Kb5wVpf41fsvjxWLnn3V+835y6/j+hGn58f+8duGxQuP3r/L7du2lMTY6z4VXxncK744qFv88RPviPUrlx3Q3B6dNiF+/YHXxdcu7B1fOveY+Mnbh8dTd03Pt9Uv2ncy/vDDD8e5554bTZo0iS5dusS3vvWtPY7529/+Fr17987HnHzyyXHrrbfGwbzX6bOY3tf0Hu3v633ttdfGkUceGcXFxXHxxRfH008/fUDv/SWXXBINGzaMG2+8seK6Ro0axSc+8Yn83wMAAAAAAAAUgmD8IGzatCl+/etf51Cw3EMPPRSXXnppDgYfeOCB+Mtf/hLjxo2Lz3zmM694ro9+9KMxfvz4HIbOmDEjlixZEq997Wsrbt++fXsOrlPr9q677orf//738bvf/S4HmIc654M9dwpGH3vssZgyZUpMmDAhZs6cGe9973srbt+8YX385oOvj9ZHdon/d+PUGH7Nl2LaL74dc//xhwOa88zf3xB33fTLuOxz34mrfz8pGhU3jd988IocbO/Lw5P/Fbd879q46L2fiP/3p2lxZM+T4jcffENsWLW84phbvvuFeGLWbXHl9b+O9/5yXKxb/nLc+Il3HNDcnrt/Thw38Px4+w035efYo/+g+MM1b4kl8x+OhvX2HoyvW7cuhg4dGt26dYt58+bFt7/97fjSl74Uv/jFLyqOSe/Dm970pvw+pc/RZZddln8effTRA5pfek9f//rXxwc+8IH9vk8K6X/4wx/Gz372s7jnnnuiWbNmMWzYsPzljf1975N3vOMd+Tw7S/ebPXt2vi8AAAAAAAAcbkVlqSbKAfn73/8eV199dSxb9t+W8ec+97kcFt57770V16XA+w1veEM+LrXId7d27dro0KFD/OlPf4rXve51+br58+fHCSecEHPmzIkzzzwzJk6cGCNHjsyB+RFHHJGPScFlat8uX748t3EPds4Hc+4nnngiTjzxxPw8+/fvX7F8dvpSwIsvvhidO3eOH//kJ/HJz/5PfG7KY9Gg4b/PMemHX4nH75gYH/vnnP2ab/pYXjesT5zzlqvjvLd9MF9Xsn5dfH3IifG6L98QfYe9Zq/3Sw3xo088NcZ85vo8Tkt6Xz+8b5z1xnfHBVd9JJ/jaxf1jiu+8bM4+eLR+Zhlzz0d37/87PjA7yZG11P+/ZwOxvdfd070HXpZTPrJdVFvL63xn/70p/E///M/8dJLL1W8tumLEzfffHN+35MrrrgiNm7cmEPnculzkJYnT+/NgUpfdLjmmmtizZo1r/p6p/fu4x//eG53l38+0+cineONb3zjfr335asQpPD/mWeeiR49elQ8xoUXXhiDBg2Kr371qwf8PAAAAAAAAOBQaIwfhFmzZkW/fv12uW7Lli156eudpeWoU9s2tYP3Jl2/bdu2vGR1ubSEdteuXXMwnqTLtJx2eXCdpBZvah8fSPt2b3M+mHOn+6QltMuD0STNv169erllnNxz993R+4yzK0LxpOdZF8byhc/E5nWvHNCWW734+Vi/YlkcN/C8iuuatGgZXfqcHose/u+XD3ZWum1rLHniodzkLpfm1WPgebHo4X/vb734iYdie+m2XY7peEzPaN3p6IpjDkYK4Lds2hAd27fdayhe/tqdd955u3zhIL3eTz75ZKxevbrimJ0/D+XHlH8eqspzzz2XA/udH7tVq1YxcODAXT6Lr/beJ+nzmz5T6TO3swEDBuxxHQAAAAAAABwOgvGD8Pzzz1e0Y3cOL9My2DfddFNeonzx4sXxla98Jd+2dOnSvZ6nvDm8+x7QKVRMt5Ufs3NwXX57+W2HMueDOXe6Pu1FvrMGDRpE27Ztd5nzkUccscuHq3m7Dvkyhd37o3zP7+Zt/32/nc+zr3NsWrMqdmzfvsd9WrTtWHG+dFm/YaMobtFqz/Me4D7jO5v1hx/H1k0bY/RrX7/PY/bn9d7XMQfyXh+M8vO/0mPvz3tfLn3W0mfu1a4DAAAAAACAw0EwfhA2b968Rzs87R2d9ox+//vfH40bN45evXrlJaaT1KitjnOuSsUN6sWOqBsenPiPmPaL78Sbr/9V9O56ZKGnUy2k1RLSvvavdh0AAAAAAAAcDoVPbGug9u3bVyx9vbOPfexjeS/ntMfyihUrYsyYMfn6Y489dq/n6dSpU2zdunWP/Z9ffvnlfFv5MWm8++3ltx3KnA/m3On6nfcpT0pLS2PVqlW7zHnjquW7HLNh5b/HLdrv2jjelxbt/n3chr2cZ1/naNq6bdSrX3+P+6xftazifOly+7atsXn92j3P+59jDsRDk/8V//zqR+PN1/8yL8/eqWmDfR67P6/3vo45kPf6YJSf/5Uee3/e+3Lpug4dOrzqdQAAAAAAAHA4CMYPwmmnnRaPP/74Xm8rKirKS0andmxaVr1Lly5x+umn7/XYtOd3w4YNY9q0aRXXpf2mU7B+1lln5XG6fOSRR3YJJKdMmRItW7aME0888ZDmfDDnTvdJQf7O+6ZPnz4977Gd9qMuP+aeO2elTb8rjnnm7juiQ/fjorjlrsvG70ubo7rlAPzZuf/dk7pkw/p44dH7o+spZ+z1PmlP884n9I1n586suC7NK52j6yn/3hf7qBP6Rv0GDXc5Ju19vualFyuO2V8PTvpn/P1LH443fuPn0fvcoVG/KKJ9k/r7PD69LjNnzsz7yu/8eh9//PHRpk2bimN2/jyUH1P+eagqxxxzTA63d37stNd82jt858/iq733SUlJSTz77LP5M7ezRx99dI/rAAAAAAAA4HAQjB+EtJ/4Y489tkcDOy2lnoLmdNtXv/rV+OY3vxk//OEPo379f4elad/x3r17x9y5c/O4VatW8a53vSs3zW+//fYcOF511VU5gDzzzDMrlmhPIfVb3/rWeOihh2Ly5Mnx+c9/Pj74wQ/mJdsPZc77c+401zTnNPfkhBNOiEsuuSTe85735NvuvPPO+H//7//FG9/4xoo9zN/85jfnvdNv++bHYtmz8+Phyf+KO2/6ZZxz5Qf2e77pCwaD3vy+mP6r78XjMybFS08/Hn+79oPRokOnOPGC4RXH/ep9r427/vyrivG5V74/7v3XH2Pe+D/HsgVPxdhvfDK2bt4U/Ua/Kd/epEXL6H/ZlXHLd6+NZ++dHYsffyiH2ylsP5BgPC2fnuZz6Ue/HF36nB4bV7wcR25bE+vXras45kc/+lFcdNFFFePy1yW95+m9+Mtf/hI/+MEP8vtf7iMf+UhMmjQpvvvd78b8+fPjS1/6Utx33335NT4Q6csVDz74YL5Me96nP6efDRs2VByT3td//etfFa/3NddcE1/72tdi3Lhx+XP8tre9Lb+nl1122X6/98ndd9+dPz+7h/mzZs3KnzkAAAAAAAA43ATjB+Hkk0/OLfC//vWvu1w/ceLEOPfcc6N///5xyy23xNixYytCxSQ1hVMjfOd9lr///e/HyJEj4/LLL4/zzjsvt3b/+c9/VtyeQvUJEybkyxQ0vuUtb8mB5Ve+8pWKYxYuXJiDzTvuuOOA5rw/505zTXPeueV844035lA1hb5pH/VzzjknfvGLX1TcngL/2267LTYufSFuuPLiuOX7X4yL3vvxGHD52yqOWXDfnfHZ0zvE6iWL9jnn897+oTj7je+Of33tY/Hjtw6NLZs2xlU/+ks0bPzfvdJXvrgwNq1ZVTE+ZdhrYvg1X4qpP70+fvimwbHkqUfzfXZeJn3Ex78avc8dEjd+8qr4+btH59ve8p3f7vLY1484Pab+7Fv7nNvcf/4hdpSWxrhvfjq+MbRPfG1on3jrgJ452C6XltNPzendX5fnnnsurxbw8Y9/PK699tp473vfW3HM2WefHX/605/y69m3b9/4+9//HjfffHP06dOn4pgUlnfv3j1eSTpvamd/8YtfzGF4+nP6SSF7ufS+rl373yXlP/WpT8WHPvShPJ8zzjgj3y+F9DvvTf9q732SVkq48soro2nTphXXzZkzJz/W6173ulecNwAAAAAAAFSForKysrIqOXMtl4LvT37yk3l56Hr1Cvv9gtQ2f+1rXxsLFiyoWJK7usz5N/NXx/LN22P3D9l9Y/8Ud/zmf+Ojf78z6jdsGNVJaph/9cLj46ob/hzH9h/0qscXRUTH4vpxVe99v/aV6e1vf3v+IsTvfve7qG7SlwHS0vApgE/Ls5e74oorctD/uc99rqDzAwAAAAAAoG5qUOgJ1FQjRoyIp59+Oi8xnvYRL6Rbb701B46vFIoXas79OxTHrYv+u3x3uSfvnBrD/t//VLtQPFlw3+zoccY5+xWKJ2X/eZ6HQ/oeS1oZYPbs2VEdpdULfvKTn+wSim/dujWvWPDRj360oHMDAAAAAACg7tIYp0pt21EWNzyyKrbuqL0fs8b1iuL/ndw2GtZL3XEAAAAAAACgurHHOFUqhcX9OzTJy43XVv06NBGKAwAAAAAAQDUmGKfKndWpabRqVK/2heNlZdG6Ub04u1PTQs8EAAAAAAAAeAWCcapcalOP6t4i78Vdm6Tns3nuxFj8wqJCTwUAAAAAAAB4BfYY57CZvnhj3Ltscy0JyMui/qLHY9ODd+TRGWecERdffHE0atSo0BMDAAAAAAAAdiMY57DZtqMsfv3E6li7dUeNDsfTkvCtG9eLK7sXx/SpU+KBBx7I17du3TpGjx4dxxxzTKGnCAAAAAAAAOxEMM5htXjjtvjjU2trfDD+ll6t4qhmDfP42WefjfHjx8fatWvzuF+/fjFkyJBo3LhxgWcKAAAAAAAAJIJxDrv5q7fEzQvXR0112TEtonfrXUPvLVu2xJQpU2LevHl53KpVqxg1alT06NGjQLMEAAAAAAAAygnGKYiHVpbExEUboqYZ3rV59G3XZJ+3P/fcczFu3LhYs2ZNHp922mkxdOjQaNJk3/cBAAAAAAAAqpZgnIKpaeH4q4Xi5bZu3RpTp06Ne++9N49btmwZI0eOjJ49ex6GWQIAAAAAAAC7E4xT8GXVx/5nWfWyarqfeDJmL8unv5rnn38+xo4dG6tXr87jU089NbfHi4uLq2CmAAAAAAAAwL4Ixim4xRu3xfiF62Pt1h3VLhxv3ahejOreIo5q1vCg7r9t27aYNm1a3HPPPXncokWL3B7v1atXJc8UAAAAAAAA2BfBONXCth1lMWvpppi7bHNuaRfyQ1n++AM7Fsc5RzaNhvXKe+MHb9GiRXnv8ZUrV+bxKaecEpdccon2OAAAAAAAABwGgnGqlerQHj/Ulvgrtcdvv/32uPvuuyP9Z9e8efMYMWJE9O7du1IfBwAAAAAAANiVYJxq2R6f89KmmLe8JLbsKKvyBnn5+RvXK4p+HZrEWZ0qpyW+Ly+++GLee3zFihV53KdPnxg+fHg0bdq0yh4TAAAAAAAA6jLBONU6IH9i9ZaYt3xzvLx5e6UH5PUiYkdEHFFcP/p3KI7ebRpXaSC+s9LS0rjjjjvirrvuyu3xZs2axaWXXhonnnjiYXl8AAAAAAAAqEsE49QISzdui/tXlMTjq7fE9rJdg+39tfPx9YsiTmzTOE7v0CSObFq5S6YfiMWLF+f2+PLly/M4BeMpIE9BOQAAAAAAAFA5BOPUKDvKymJFyfZ4aVNp/lmycVssL9leEZbvTQrBOzSpH52bNYxOTRvkn/ZN6ke9osPTDt+f9vjMmTNj9uzZuT2ellRPS6ufdNJJUVRN5ggAAAAAAAA1mWCcWhGWr9myIy+9vr2sLErLIhoUpUC8KC+N3rpxvWoTgr+SpUuX5vb4yy+/nMe9e/eOESNGRPPmzQs9NQAAAAAAAKjRBONQjWzfvj1mzZqVf3bs2BHFxcVxySWXxMknn6w9DgAAAAAAAAdJMA7V0EsvvZTb4+ky6dWrV4wcOTJatGhR6KkBAAAAAABAjSMYh2rcHr/zzjtjxowZuT3epEmTGDZsWPTt21d7HAAAAAAAAA6AYByquWXLluX2+JIlS/L4uOOOi1GjRkXLli0LPTUAAAAAAACoEQTjUAOkxvhdd90Vd9xxR26SN27cOIYOHRqnnXaa9jgAAAAAAAC8CsE41CDLly/P7fHFixfncY8ePXJ7vFWrVoWeGgAAAAAAAFRbgnGoge3xu+++O26//fYoLS2NRo0axZAhQ6Jfv37a4wAAAAAAALAXgnGooVauXJnb4y+88EIeH3PMMTF69Oho3bp1oacGAAAAAAAA1YpgHGp4e3zu3Lkxbdq03B5v2LBhXHzxxXHGGWdojwMAAAAAAMB/CMahFli1alVujy9atCiPu3Xrltvjbdu2LfTUAAAAAAAAoOAE41BLpP+U77333pg6dWps27Ytt8cvvPDCGDhwoPY4AAAAAAAAdZpgHGqZ1atXx7hx42LhwoV53LVr19web9euXaGnBgAAAAAAAAUhGIdaKP1nPW/evJgyZUps3bo1GjRoEIMHD44zzzwz6tWrV+jpAQAAAAAAwGElGIdabM2aNTF+/PhYsGBBHh999NExZsyYaN++faGnBgAAAAAAAIeNYBxqufSf+AMPPBCTJ0/O7fH69evHBRdcEGeffbb2OAAAAAAAAHWCYBzqiLVr18aECRPimWeeyePOnTvn9njHjh0LPTUAAAAAAACoUoJxqEPSf+4PPfRQTJo0KbZs2ZLb4+eff34MGjRIexwAAAAAAIBaSzAOddC6devilltuiaeeeiqPjzzyyNweP+KIIwo9NQAAAAAAAKh0gnGoo9J/+o888khMnDgxSkpKcmP8vPPOi3POOSc3yQEAAAAAAKC2EIxDHbd+/fq49dZbY/78+XmcWuOXXXZZdOrUqdBTAwAAAAAAgEohGAdye/yxxx7LAfnmzZtzezw1x1ODXHscAAAAAACAmk4wDlTYsGFDDsefeOKJPO7YsWPee7xz586FnhoAAAAAAAAcNME4sIfy9vimTZuiqKgoBg0aFOeff340aNCg0FMDAAAAAACAAyYYB/Zq48aNMXHixBySJx06dMjt8aOOOqrQUwMAAAAAAIADIhgHXlFaVv2WW27JQXlqj5911llxwQUXRMOGDQs9NQAAAAAAANgvgnHgVaUl1SdNmhSPPPJIHrdr1y63x7t06VLoqQEAAAAAAMCrEowD++3JJ5+MCRMmxIYNG/L4zDPPjAsvvFB7HAAAAAAAgGpNMA4ckM2bN8fkyZPjoYceyuO2bdvG6NGjo1u3boWeGgAAAAAAAOyVYBw4KE8//XSMHz8+1q9fn8cDBgyIiy66KBo1alToqQEAAAAAAMAuBOPAQSspKYnbbrstHnjggTxu06ZNbo9379690FMDAAAAAACACoJx4JA988wzuT2+bt26PO7fv38MGTJEexwAAAAAAIBqQTAOVIotW7bElClTYt68eXncqlWr3B4/9thjCz01AAAAAAAA6jjBOFCpFixYkNvja9asyePTTz89hg4dGo0bNy701AAAAAAAAKijBONApdu6dWtMnTo17r333jxu2bJljBo1Ko477rhCTw0AAAAAAIA6SDAOVJmFCxfGuHHjYvXq1Xl86qmnxrBhw6JJkyaFnhoAAAAAAAB1iGAcqPL2+LRp02Lu3Ll53KJFixg5cmT06tWr0FMDAAAAAACgjhCMA4fFokWLYuzYsbFq1ao87tu3b26PFxcXF3pqAAAAAAAA1HKCceCw2bZtW0yfPj3uvvvuPG7evHlujx9//PGFnhoAAAAAAAC1mGAcOOxeeOGF3B5fuXJlHp988slxySWXRNOmTQs9NQAAAAAAAGohwThQsPb4HXfcEXPmzIn011CzZs1ixIgRccIJJxR6agAAAAAAANQygnGgoBYvXpzb48uXL8/jk046KYYPH56DcgAAAAAAAKgMgnGg4EpLS2PGjBlx55135vZ4WlL90ksvzSE5AAAAAAAAHCrBOFBtLFmyJLfHly1blsdpWfUUkDdv3rzQUwMAAAAAAKAGE4wD1cr27dtj5syZMXv27NixY0cUFxfnpdX79OkTRUVFhZ4eAAAAAAAANZBgHKiWXnrppdweT5fJ8ccfHyNGjIgWLVoUemoAAAAAAADUMIJxoFq3x1NzPDXIU3u8SZMmcckll8Qpp5yiPQ4AAAAAAMB+E4wD1d7LL7+c2+NLly7N4549e8bIkSOjZcuWhZ4aAAAAAAAANYBgHKgx7fG77rorZsyYkf/cuHHjGDZsWJx66qna4wAAAAAAALwiwThQoyxbtizGjRsXixcvzuMePXrEqFGjolWrVoWeGgAAAAAAANWUYByocdJ+43PmzInbb789t8cbNWoUQ4cOjdNPP117HAAAAAAAgD0IxoEaa8WKFXnv8RdffDGPjz322Nweb926daGnBgAAAAAAQDUiGAdqfHv8nnvuienTp0dpaWluj1988cXRv39/7XEAAAAAAAAywThQK6xcuTLvPb5o0aI87t69e4wePTratGlT6KkBAAAAAABQYIJxoNZIf53NnTs3pk2bFtu2bYuGDRvGRRddFAMGDNAeBwAAAAAAqMME40Cts2rVqhg/fnwsXLgwj7t165bb423bti301AAAAAAAACgAwThQK6W/2u67776YMmVKbo83aNAgLrzwwhg4cGDUq1ev0NMDAAAAAADgMBKMA7XamjVr8t7jzz33XB536dIlt8fbt29f6KkBAAAAAABwmAjGgVov/TV3//33x2233RZbt27N7fELLrggzjrrLO1xAAAAAACAOkAwDtQZa9euzXuPP/vss3l81FFHxZgxY6JDhw6FnhoAAAAAAABVSDAO1Cnpr7wHH3wwJk+eHFu2bIn69evH+eefH4MGDdIeBwAAAAAAqKUE40CdtG7dupgwYUI8/fTTedy5c+fcHu/YsWOhpwYAAAAAAEAlE4wDdVb66+/hhx+OSZMmRUlJSW6Mn3feeXHOOefkJjkAAAAAAAC1g2AcqPPWr18ft9xySzz55JN53KlTp9weT5cAAAAAAADUfIJxgP+0xx999NGYOHFibN68ObfHzz333PyjPQ4AAAAAAFCzCcYBdrJhw4a49dZb44knnsjjI444IrfHjzzyyEJPDQAAAAAAgIMkGAfYTfpr8fHHH88B+aZNm6KoqCjvO572H2/QoEGhpwcAAAAAAMABEowD7MPGjRvz0uqPPfZYHnfo0CG3x4866qhCTw0AAAAAAIADIBgHeBXl7fEUlKf2+Nlnnx0XXHCB9jgAAAAAAEANIRgH2A9pSfVJkybFI488ksft27fP7fGjjz660FMDAAAAAADgVQjGAQ7A/Pnz45ZbbokNGzbk9viZZ54ZgwcPjoYNGxZ6agAAAAAAAOyDYBzgAG3evDkmT54cDz30UB63a9cuRo8eHV27di301AAAAAAAANgLwTjAQXrqqadiwoQJsX79+jweOHBgXHjhhdGoUaNCTw0AAAAAAICdCMYBDkFJSUlujz/44IN53KZNm9we7969e6GnBgAAAAAAwH8IxgEqwTPPPBPjx4+PdevW5fEZZ5wRF198sfY4AAAAAABANSAYB6jE9viUKVPi/vvvz+PWrVvn9vgxxxxT6KkBAAAAAADUaYJxgEr27LPP5vb42rVr87hfv34xZMiQaNy4caGnBgAAAAAAUCcJxgGqwJYtW2Lq1Klx33335XGrVq1i1KhR0aNHj0JPDQAAAAAAoM4RjANUoeeeey7GjRsXa9asyePTTjsthg4dGk2aNCn01AAAAAAAAOoMwThAFdu6dWtMmzYt5s6dm8ctW7aMkSNHRs+ePQs9NQAAAAAAgDpBMA5wmDz//PMxduzYWL16dR6feuqpuT1eXFxc6KkBAAAAAADUaoJxgMNo27ZtMX369Lj77rvzuHnz5rk9fvzxxxd6agAAAAAAALWWYBygAF544YXcHl+5cmUen3LKKXHJJZdojwMAAAAAAFQBwThAAdvjd9xxR8yZMyfSX8XNmjXL7fHevXsXemoAAAAAAAC1imAcoMBefPHF3B5fsWJFHvfp0yeGDx8eTZs2LfTUAAAAAAAAagXBOEA1UFpamtvjd911V26Pp1B8xIgRceKJJxZ6agAAAAAAADWeYBygGlmyZElujy9btiyPUzB+6aWX5mXWAQAAAAAAODiCcYBq2B6fOXNmzJ49O7fHi4uLczh+0kknRVFRUaGnBwAAAAAAUOMIxgGqqaVLl+b2+Msvv5zHvXv3zsurN2/evNBTAwAAAAAAqFEE4wDV2Pbt22PWrFn5Z8eOHdGkSZMYPnx4nHzyydrjAAAAAAAA+0kwDlADvPTSS7k9ni6TXr16xciRI6NFixaFnhoAAAAAAEC1JxgHqEHt8TvvvDNmzJhR0R4fNmxY9O3bV3scAAAAAADgFQjGAWqYZcuW5fb4kiVL8viss86KIUOGvGI4noL0evXqHcZZAgAAAAAAVB9SEoAapmPHjvGud70rLrroomjcuHH0798/9vUdp9tuuy1fCsUBAAAAAIC6TGMcoAbbtGlTFBcX77Utvnbt2ujTp09cd9118Za3vKXi+vTXvqXXAQAAAACAukSFEKAGa9q06T5D7latWsWRRx4ZzzzzzC7Xp+N9JwoAAAAAAKhLBOMAtdD27dujtLQ0jjjiiGjevHm+7r777otrr702nn32WY1xAAAAAACgTmlQ6AkAUPnq16+fL9Me5L/+9a/j3nvvjWnTpkWHDh3ipJNOimOPPVY4DgAAAAAA1BmCcYBa6He/+11uiP/zn/+M9u3bx4knnhif+tSn4rTTTot69SwWAgAAAAAA1C2CcYBaYsOGDfGBD3wg5s+fHwsWLIjRo0dHnz594vLLL48vfvGLFUusAwAAAAAA1DWCcYBaIu0lfvTRR8fQoUPjrLPOiuOOOy6uvvrqHJTvvsQ6AAAAAABAXSIYB6hFrrvuuny5Y8eOfLl27dpo3bp1/nNpaWk0aLB/f+2nZrkQHQAAAAAAqC1sNAtQS5SVlVX8uXwf8dQif/TRR/Of9zcUT8pD8Xnz5sUNN9ywy7kBAAAAAABqGo1xgFqiqKhoj+s+9KEPxZQpU6KkpCQaN26812NSu7w8SE8B+EsvvRQ//OEP4/nnn4+77rorFi1aFLfffnv87W9/0yIHAAAAAABqJME4QC2VAu8+ffrkn1dSHor/6U9/ij//+c+xatWq6Ny5c7z73e+Onj17xs033xxXXnllDsVTcL63cB0AAAAAAKA6s5Q6QC2UAuwUeG/cuHGXfcP3tST6//zP/8Rb3vKWeNOb3hSzZ8+Ov/71r9GiRYuYPn16DBgwIC6//PJ8nFAcAAAAAACoiQTjALVQeYD9jW98I0455ZR4/PHHc+M7XZ8C8t2ddNJJ0b59+/jZz36Wl13fsGFD/PznP4/Nmzfnc5Q30AEAAAAAAGoiwThALfbpT386zjvvvBg4cGB88YtfzNelgHz39vib3/zmmDNnTrRt2zbatGkTb33rW+Pee++Nr371q9GhQ4d8fPmS6wAAAAAAADVNUdm+1tUFoNaYMmVKfOQjH4nGjRvH73//+9wi35dPfOIT8eMf/zgaNWoUixcvjubNm7/q+VNwngJ3AAAAAACA6kj9D6AOGDJkSNxzzz1xwQUXxKmnnho//OEPd7m9/DtSCxcuzMuo9+zZM/r375+P27Jlyz7Pe8stt+T7CsUBAAAAAIDqTGMcoI65/fbbcxP88ssvj+Li4orr0z8HP/jBD+LrX/96/OhHP4orrrgi1q1bFy1bttzrebZu3RoXXXRRtG7dOn71q1/FEUcccRifBQAAAAAAwP4TjANQYenSpfGHP/wh702+P2bOnBnXX399jBgxIq6++up83Y4dO+xHDgAAAAAAVCuCcQCy9M9BUVHRAe8b/r//+7/xmc98Jr73ve9VhOMAAAAAAADVSYNCTwCA6mHnUDzZVyj+zDPPxGOPPRbt27ePQYMGxTXXXBPt2rWLH//4x9GiRYu48sor87l2Px8AAAAAAEChCMYBOKBW+cSJE+OnP/1pDsPTPuMpGG/Tpk2cfvrpMW3atLjggguiS5cuhZ4qAAAAAABABUupA7Dffv/730eHDh2iR48esXLlyvjb3/4WU6ZMiZNOOinmzZsXCxYsyAH5uHHjonPnzoWeLgAAAAAAQFbv3xcA8OpWr14dI0eOjG984xvRvXv3+P73v59b4ldddVV84QtfiH79+kW9evXiiSeeeNVzbdmy5bDMGQAAAAAAQGMcgAPywgsvxOWXXx5PP/10Dsbf8Y537HJ72n/82GOPjeLi4n2e46abboq//OUv8eY3vzne8IY3HIZZAwAAAAAAdZnGOAD7JX2Pavv27Xn/8Llz58a1114b73nPe+I1r3lNDsvLpWXVXykUT+fYsGFDbpy/5S1vyT8lJSWH6VkAAAAAAAB1kWAcgP1SVFQU9evXz8F28tGPfjSef/75WLFiRfTs2TP+8Y9/7Nd50jlSoD569Og488wzY9WqVRXnBAAAAAAAqAqCcQAOSAq2kxRmd+7cOWbNmhXf+973Yvbs2bF+/fpXvG/57h2bNm2qCNI/+9nPRrNmzWLHjh2HYfYAAAAAAEBd1KDQEwCgZipvj6fLq6++OkpLS6NBgwav2jpP/u///i/mzZsXl112WZx77rn5unr1fFcLAAAAAACoGlIIAA65PZ6a4K8Wipe3xVMgfvPNN0e3bt1yoJ5oiwMAAAAAAFVJMA7AIStvgu+ufO/w1CZPx5SUlMRvfvObvOT6+9///mjZsmUOxbXFAQAAAACAqiSJAKBKG+XLli2Lq666KhYsWBA33XRT3H///TF8+PAYPHhwPkYoDgAAAAAAVDV7jANQpVq0aBGLFi2KE044IY488sgYMGBAfOhDH8q3aYsDAAAAAACHgzQCgCpVXFwcM2bMiD/84Q+xYcOGePzxx2P58uX5tr2F4uV7kQMAAAAAAFQWwTgAVap8n/Errrginn/++ejUqVP07t07Vq5cudfjU4v8tttui02bNh3mmQIAAAAAALVVUZlqHgCHQWlpaTRo8O8dPB577LE46aST9lhKPf2TNH369Jg9e3Y0a9YsRowYkZdgBwAAAAAAOBSCcQAOa3u8fv36r3jM4sWLY+zYsRXLracAffjw4TkoBwAAAAAAOBiCcQCqZbt85syZuTme/plq2rRpXHrppXHiiSdGUVFRoacHAAAAAADUMIJxAKqtJUuW5Pb4smXL8jgtq54C8ubNmxd6agAAAAAAQA0iGAeg2i+/PmvWrPyT9iQvLi7OS6v36dNHexwAAAAAANgvgnEAaoSXXnopt8fTZXL88cfHiBEjokWLFoWeGgAAAAAAUM0JxgGoUe3xtO942n88tcebNGkSl1xySZxyyina4wAAAAAAwD4JxgGocV5++eXcHl+6dGke9+zZM0aOHBktW7Ys9NQAAAAAAIBqSDAOQI2UGuN33nlnzJgxIzfJGzduHMOGDYtTTz1VexwAAAAAANiFYByAGm358uW5Pb548eI87tGjR4waNSpatWpV6KkBAAAAAADVhGAcgFrRHp8zZ07cfvvtuT3eqFGjGDp0aJx++una4wAAAAAAgGAcgNpjxYoVuT3+4osv5vExxxwTo0ePjtatWxd6agAAAAAAQAEJxgGode3xe+65J6ZPnx6lpaXRsGHDGDJkSPTv3197HAAAAAAA6ijBOAC10sqVK2PcuHGxaNGiPO7evXtuj7dp06bQUwMAAAAAAA4zwTgAtVb6J27u3Lkxbdq02LZtW26PX3TRRTFgwADtcQAAAAAAqEME4wDUeqtXr87t8YULF+Zx165dc3u8Xbt2hZ4aAAAAAABwGAjGAagT0j939913X0ydOjW2bt0aDRo0iAsvvDAGDhwY9erVK/T0AAAAAACAKiQYB6BOWbNmTYwfPz4WLFiQx0cffXSMGTMm2rdvX+ipAQAAAAAAVUQwDkCdk/7pu//+++O2227L7fH69evH4MGD46yzztIeBwAAAACAWkgwDkCdtXbt2twef/bZZ/P4qKOOyu3xDh06FHpqAAAAAABAJRKMA1CnpX8GH3zwwZg8eXJs2bIlt8fPP//8GDRokPY4AAAAAADUEoJxAIiIdevWxYQJE+Lpp5/O4yOPPDK3x4844ohCTw0AAAAAADhEgnEA+I/0T+LDDz8ckyZNipKSktwYP++88+Kcc87JTXIAAAAAAKBmEowDwG7Wr18ft9xySzz55JN53KlTp9weT5cAAAAAAEDNIxgHgL1I/zw++uijMXHixNi8eXNuj6fmeGqQa48DAAAAAEDNIhgHgFewYcOGuPXWW+OJJ57I444dO8Zll12W9yAHAAAAAABqBsE4ALyK9E/l448/ngPyTZs2RVFRUUV7vEGDBoWeHgAAAAAA8CoE4wCwnzZu3JiXVn/sscfyuEOHDnnv8aOOOqrQUwMAAAAAAF6BYBwADlBaVv2WW27JQXlqj5999tlxwQUXaI8DAAAAAEA1JRgHgIOQllSfNGlSPPLII3ncvn37GD16dHTp0qXQUwMAAAAAAHYjGAeAQzB//vzcHt+wYUMen3XWWTF48OBo2LBhoacGAAAAAAD8h2AcAA7R5s2bY/LkyfHQQw/lcdu2bfPe4127di301AAAAAAAAME4AFSep556KiZMmBDr16/P44EDB8aFF14YjRo1KvTUAAAAAACgThOMA0AlKikpye3xBx98MI/btGmT9x7v3r17oacGAAAAAAB1lmAcAKrAM888E+PHj49169bl8RlnnBEXX3yx9jgAAAAAABSAYBwAqsiWLVvitttui/vvvz+PW7duHaNGjYpjjz220FMDAAAAAIA6RTAOAFVswYIFMW7cuFi7dm0e9+vXL4YMGRKNGzcu9NQAAAAAAKBOEIwDwGFqj0+dOjXuu+++PG7ZsmXee7xHjx6FnhoAAAAAANR6gnEAOIyee+653B5fs2ZNHp922mkxdOjQaNKkSaGnBgAAAAAAtZZgHAAOs61bt8a0adNi7ty5Fe3xkSNHRs+ePQs9NQAAAAAAqJUE4wBQIM8//3xuj69atSqP+/btG8OGDYvi4uJCTw0AAAAAAGoVwTgAFNC2bdti+vTpcffdd+dx8+bNc3v8+OOPL/TUAAAAAACg1hCMA0A18MILL8TYsWNj5cqVeXzyySfHJZdcEk2bNi301AAAAAAAoMYTjANANWqP33HHHTFnzpxI/zw3a9YsRowYESeccEKhpwYAAAAAADWaYBwAqpkXX3wxt8dXrFiRxyeddFIMHz48B+UAAAAAAMCBE4wDQDVUWloaM2bMiDvvvDO3x9OS6pdeemkOyQEAAAAAgAMjGAeAamzJkiW5Pb5s2bI8PvHEE3NArj0OAAAAAAD7TzAOADWgPT5r1qyYPXt27NixI4qLi/PS6n369ImioqJCTw8AAAAAAKo9wTgA1BBLly7N7fGXX345j3v37h0jRoyI5s2bF3pqAAAAAABQrQnGAaAG2b59e26Oz5w5M7fHmzRpEpdcckmccsop2uMAAAAAALAPgnEAqIFSazy1x1OLPOnVq1eMHDkyWrRoUeipAQAAAABAtSMYB4Aa3B6/6667YsaMGfnPqT0+bNiw6Nu3r/Y4AAAAAADsRDAOADXcsmXLcnt8yZIleXzcccfl9nirVq0KPTUAAAAAAKgWBOMAUAuk/cbnzJkTt99+e26PN27cOIYOHRqnnXaa9jgAAAAAAHWeYBwAapEVK1bk9viLL76Yx8cee2yMGjUqWrduXeipAQAAAABAwQjGAaAWtsfvueeemD59epSWlkajRo1iyJAh0a9fP+1xAAAAAADqJME4ANRSK1euzO3xF154IY+7d+8eo0ePjjZt2hR6agAAAAAAcFgJxgGglrfH586dG9OmTcvt8YYNG8bFF18cZ5xxhvY4AAAAAAB1hmAcAOqAVatWxbhx4+L555/P427duuX2eNu2bQs9NQAAAAAAqHKCcQCoI9I/+ffee29MnTo1tm3bFg0aNIiLLrooBgwYEPXq1Sv09AAAAAAAoMoIxgGgjlm9enWMHz8+nnvuuTzu0qVLbo+3b9++0FMDAAAAAIAqIRgHgDoo/fM/b968mDJlSmzdujW3xwcPHhxnnnmm9jgAAAAAALWOYBwA6rA1a9bk9viCBQvy+Oijj87t8Q4dOhR6agAAAAAAUGkE4wBQx6VfBR544IG47bbbYsuWLVG/fv244IIL4uyzz9YeBwAAAACgVhCMAwDZunXrcnv8mWeeyePOnTvHmDFjomPHjoWeGgAAAAAAHBLBOABQIf1a8NBDD8XkyZOjpKQkN8bPP//8GDRoUG6SAwAAAABATSQYBwD2sH79+pgwYUI89dRTedypU6e47LLL4ogjjij01AAAAAAA4IAJxgGAvUq/IjzyyCMxceLEivb4ueeem3+0xwEAAAAAqEkE4wDAK9qwYUPccsstMX/+/DxOrfG09/iRRx5Z6KkBAAAAAMB+EYwDAK8q/brw2GOPxa233hqbN2+OoqKiOOecc+K8886LBg0aFHp6AAAAAADwigTjAMB+27hxYw7HH3/88Tzu0KFD3nu8c+fOhZ4aAAAAAADsk2AcADhgKRhPy6tv2rQpt8fPPvvsuOCCC7THAQAAAAColgTjAMBBSaH4xIkT49FHH83j9u3b573Hjz766EJPDQAAAAAAdiEYBwAOyfz582PChAl5mfXUHj/zzDNj8ODB0bBhw0JPDQAAAAAAMsE4AHDINm/eHJMmTYqHH344j9u1a5fb4126dCn01AAAAAAAQDAOAFSep556KrfH169fn8epPX7hhRdqjwMAAAAAUFCCcQCg0tvjt912Wzz44IN53LZt2xg9enR069at0FMDAAAAAKCOEowDAFXi6aefzu3xdevW5fGAAQPioosuikaNGhV6agAAAAAA1DGCcQCgypSUlOT2+AMPPJDHrVu3zu3xY445ptBTAwAAAACgDhGMAwBV7tlnn43x48fH2rVr87h///5x8cUXR+PGjQs9NQAAAAAA6gDBOABwWGzZsiWmTJkS8+bNy+NWrVrl9vixxx5b6KkBAAAAAFDLCcYBgMPqueeei3HjxsWaNWvy+PTTT48hQ4ZEkyZNCj01AAAAAABqKcE4AHDYbd26NaZOnRr33ntvHrds2TJGjRoVxx13XKGnBgAAAABALSQYBwAKZuHChbk9vnr16jw+9dRTY9iwYdrjAAAAAABUKsE4AFDw9vj06dPjnnvuyeMWLVrEyJEjo1evXoWeGgAAAAAAtYRgHACoFhYtWhRjx46NVatW5fEpp5wSl1xySRQXFxd6agAAAAAA1HCCcQCg2ti2bVvcfvvtcffdd0f6FaV58+YxYsSI6N27d6GnBgAAAABADSYYBwCqnRdffDG3x1esWJHHffr0ieHDh0fTpk0LPTUAAAAAAGogwTgAUC2VlpbGHXfcEXfddVdujzdr1iwuvfTSOPHEEws9NQAAAAAAahjBOABQrS1evDi3x5cvX57HKRhPAXkKygEAAAAAYH8IxgGAGtEenzlzZsyePTu3x9OS6mlp9ZNOOimKiooKPT0AAAAAAKo5wTgAUGMsXbo0t8dffvnlPD7hhBNye7x58+aFnhoAAAAAANWYYBwAqFG2b98es2bNyj87duyI4uLiuOSSS+Lkk0/WHgcAAAAAYK8E4wBAjfTSSy/l9ni6TI4//vgYMWJEtGjRIqq77WVlsXbLjti2oyxKy8pie1lE/aKIBkVF0bBeUbRqXC/qC/kBAAAAACqNYBwAqNHt8TvvvDNmzJiR2+NNmjSJYcOGRd++fatNezyF4Cs2b4+XNpfGy5tKY8nGbbG8ZHsOw/clheQdmtSPzs0axhFNG0Sn4gbRvri+sBwAAAAA4CAJxgGAGi/tOZ7a42kP8qRnz54xcuTIaNmyZcHmtHTjtpi3oiSeWL2lIgSvFxE7DuAcOx+fwvIT2jSOfh2axJFNG1bFlAEAAAAAai3BOABQK6TG+F133RV33HFHbpI3btw4hg4dGqeddtpha4+npdFTEH7f8s2xbPP2SI9amb9olZ/viOL60a9DcQ7K09LrAAAAAAC8MsE4AFCrLF++PLfHFy9enMc9evSIUaNGRatWrao0EJ/z0qa4b3lJbN1RVumB+O7Kz9+oXlH079AkzurUVEAOAAAAAPAKBOMAQK1sj999990xffr03B5v1KhRDBkyJPr161fp7fHFG7fF+IXrY+3WHVUahu9LejatGtWLUd1bxFHNLLEOAAAAALA3gnEAoNZasWJFjBs3Ll544YU8PuaYY2L06NHRunXrSmmJz1q6KeYu21zlDfFXU/74AzoWx7lHao8DAAAAAOxOMA4A1Pr2+Ny5c2PatGlRWloaDRs2zO3x/v37H3R7vNAt8VfSWnscAAAAAGAPgnEAoE5YtWpV3nt80aJFedy9e/e893jbtm0P6DzzV2+JsQvX5z9Xx1+iyqP+Md1bRO82jQs8GwAAAACA6kEwDgDUGenXnnvvvTemTp0a27Zty+3xiy66KAYMGLBf7fGHVpbExEUboqYY3rV59G3XpNDTAAAAAAAoOME4AFDnrF69Ou89vnDhwjzu2rVr3nu8Xbt2tSYULyccBwAAAAAQjAMAdVT6FWjevHkxZcqU2Lp1azRo0CAuvPDCGDhwYNSrV2+P5dNv/s/y6TXRZZZVBwAAAADqOME4AFCnrVmzJsaPHx8LFizI46OPPjrGjBkT7du3z+PFG7fFH59aWy33E99faZH4t/RqFUc1a1joqQAAAAAAFIRgHACo89KvQ/fff3/cdtttuT1ev379GDx4cPQfeGb89sm1sXbrjhofjLdqVC/edUKbaFjv1fdSBwAAAACobQTjAAD/sXbt2twef/bZZ/O41YChUdLpuP9EyzXfwI7FMfioZoWeBgAAAADAYScYBwDYSfrV6MEHH4zJdz8QZQNHRVFR7QjFy73VkuoAAAAAQB0kGAcA2M22HWXxy8dWxrptOyKK6kVtYUl1AAAAAKCuqj3/Ty8AQCWZ89KmWF+akuTa9atS+jbkmq078vMDAAAAAKhLGhR6AgAA1a0tft/ykhwiV6YNq1fE1J9eH/NnT4kNK5dHcctWcWTPk+LC934iup86MLZtKYlbv3dtPHTbzbF965boedbgGPPZb0WLdh0reSYR85aXxFmdmmqNAwAAAAB1hmAcAGAnT6zeElt3VP5OMzd+4qrYvm1bvP7LP4q2R3WLDauWx7NzZ8amtavz7bd89ws5NL/y+l9Hk+YtY+z1n4kbP/GOeP9vb630uWzZURbzV2+Jk9s1qfRzAwAAAABUR4JxAICd3Ld8c96LuzKj8c3r18bCB+6O9/zy5ji236B8XZvOXaJLn9Pzn0vWr4v7br4xrvjGz6LHgHPzda/70g/j+5efHYsevi+6ntK/0vcaT89TMA4AAAAA1BW1a+NMAIBDsHTjtli2eXulL6PeqLhZNGraLB6/fWKUbt2yx+2Ln3gotpdui+MGnl9xXcdjekbrTkfnYLyypef38ubt+fkCAAAAANQFgnEAgP+Yt6Ikt6krW/0GDeL1X74h7p/wl/jy+cfFz666NCbf8LVY+tRj+fb1K5dF/YaNorhFq13u17xdh3xbVf0SeP+Kkio5NwAAAABAdWMpdQCAiNheVpb3F6/83cX/rc9Fo+L4c4bkJdUXPTIvnrpzWsz8w4/itV/4fg7FD7cdEfH46i0xvGvzqFdUFV8HAAAAAACoPjTGAQAiYsXm7bG9qlLx/2jYuEn0PPOCuOg9H48P/O7WOH3UG2Pqz74VLdp1jO3btua9yHe2YeXyfFtVSc93Rcn2Kjs/AAAAAEB1IRgHAIiIlzaXHvbH7Hjs8bG1ZFMcdULfqN+gYTw7d2bFbcsXPhNrXnoxup7Sv0rn8NKmw/+8AQAAAAAON0upAwBExMubSvM3BtMS45Vt45pV8adPvSv6j3lzdOp5YjRu1jwWP/5gzPz9DXHi+ZdEkxYto/9lV8Yt3702ilu2iSbNWsS4b302up5yRpUG4/X+E4yf0q7KHgIAAAAAoFoQjAMARMSSjduqJBRPGjdtFl1OPj1m3/izWPXiwtheWhqtO3WOM17z1hj8zmvyMSM+/tUoKiqKGz95VZRu3Rq9zhocYz57fVSlHf953gAAAAAAtV1RWVlZFe+mCQBQvW0vK4vvPrQydtTB34rqF0V8vG+7qFdUVOipAAAAAABUGXuMAwB13totO+pkKJ5sL4tYs6WquvIAAAAAANWDYBwAqPO21dVU/D/q+vMHAAAAAGo/wTgAUOeV1vGdZdJS8gAAAAAAtZlgHACo89Jy4nVZaR1//gAAAABA7ScYB4BaauXKldGxY8dYuHBh1CZPPvlkdOrUKdavX19p56xfFHVagzr+/Hf3mc98Jj70oQ/tct3jjz8eRx99dGzcuLFg8wIAAAAADp5gHABqqa9//esxZsyY6N69e8V1H/7wh6Nfv37RuHHjOPXUU/e4T0lJSbzjHe+Ik08+ORo0aBCXXXbZfj1WeoyioqJdfr75zW/ucszDDz8c5557bjRp0iS6dOkS3/rWtw7qeX32s5/NoWWLFi0O6dyLFi2KESNGRNOmTaNv96Pi1u9/KbaXlu5yzIL77owb3nxhfH7gUfHt0WfEvHE3HfB8t20pibHXfSq+MrhXfHFQt/jjJ94R61cue8X7lJWVxZSffjO+MfSk+MJZXeJX7788Vix6dpdjNq1dHX/+n/fHl849Jr58Xo/4x5c/Els2bTiguc395//Fz985Mk48umO0adMmLr744pg7d+6r3u+OO+6I008/PX+OjjvuuPjd7363xzE//vGP8+civScDBw7cr/O+0nuUvuTxyU9+Mkp3e4+q4rP4iU98In7/+9/HggULKq478cQT48wzz4zvfe97B/w8AAAAAIDCE4wDQC20adOm+PWvfx3vete79rjtne98Z1xxxRV7vd/27dujuLg4B+gpJD0QX/nKV2Lp0qUVPzs3btetWxdDhw6Nbt26xbx58+Lb3/52fOlLX4pf/OIXBxyUTpgwIYf3h3Lu9DxT4Lp169a466674ie/+k3cP/7PMfWn/w1QVy1+Pn734TfHsf3PiQ/fdHsMevP74p9f/Wg8ddf0A5rzLd/9Qjwx67a48vpfx3t/OS7WLX85bvzEf+e/NzN/f0PcddMv47LPfSeu/v2kaFTcNH7zwStyyF7uL//z/lj27Px450/+Hm//wY3x3P1z4l9f+/gBzW3BvDvjlEteG2MnTY05c+bkkDi9losXL97nfZ577rn82g0ePDgefPDBuOaaa+Ld7353TJ48+b9z+8tf4mMf+1h88YtfjPvvvz/69u0bw4YNi2XLXvkLAa/0HqWgOgXw1157bZV/Ftu3b5/n+9Of/nSX81511VX5ulcL5wEAAACA6qeoLFWSAIBa5e9//3tcffXV+wwiUxB4880352BzX1L4vGbNmnzcq0kt3RSQpp+9SWHi//zP/8RLL70UjRo1qliuOp17/vz5+/28vvOd7+TQ9d577z2kc0+cODFGjhwZS5YsiSOOOCK2l5XF6z//3bj1h1+Jz0+bHw0aNoqJP/hKPDl7Slzzt1kV97vpM++JzevXxjt//Nf9mm/J+nXxtYt6xxXf+FmcfPHofN2y556O719+dnzgdxOj6yn997hP+tXsumF94py3XB3nve2DFef5+pAT43VfviH6DntNLFvwVHz/dYPig3+cEkef+O/m/5N3Tovff/hN8ZlJD0fLDp0OaBn5j/dtF/WKinIYnZrjP/rRj+Jtb3vbXo//9Kc/Hbfccks8+uijFde98Y1vzJ+VSZMm5XFqiJ9xxhn5PMmOHTty6J4C6vTe7I/d36PkZz/7WX785cuXV7zXVfVZ/MMf/pCPe+GFFyquSyF9y5Yt8/O/6KKL9ut5AAAAAADVg8Y4ANRCs2bNykumH05puep27drFaaedllu4O7dqUxv5vPPO2yXMTI3ctF/46tWrD+h59e+/a5h8MOdO90nLxZcHrvWLiuKswRfHlg3rcws7WfTwvdFjwHm73K/nWYNj0SP37fd8Fz/xUGwv3RbHDTy/4rqOx/SM1p2OjkUP7/08qxc/H+tXLIvjBv73sZu0aBld+pye51Q+tyYtWlWE4kl6jKJ69eKFR+bFgejQpH4OxctXGti2bVu0bdt2n8en12731QTS652uLw+PUxN752Pq1auXx+XH7I/d36Pyx0mN78cee6zKP4sDBgyIF198MRYuXFhxXbpP2oIgfQ4BAAAAgJqlQaEnAABUvueffz46d+582B4vLb2e9pxOgWpa9jrtA56WsC7fjzm1c4855phd7lMeeKbbUkt5f5/X7sH4wZw7Xb9z4Joc3/Xfr1f5/t/pskW7Drsc07xdhxyebyvZHA2bFL/qfNM56jdsFMUtWu1xnn3tM15+ffO2ez52CszLj2netv0ut9dv0CCKW7Z51f3Ld/+GZOdmDSvGqY2dPjevtIz+3l67NE6B9ebNm3O4nJrnezvmQFYH2NfjlN9W1Z/F8v9+0mcutdDLpevTdQAAAABAzSIYB4BaKAWUTZo0OWyPl/aTLnfKKafkZu373ve+uO6666Jx48Y14nl1LK57vxbtiIhOTRtUtKz//Oc/xx133HFYPzvV9bNYXFxc0aLf/frdrwMAAAAAqj9LqQNALdS+ffsDWqK8sqU9ptPy1eXLUHfq1ClefvnlXY4pH6fbDuV5Hcy593afeutX5ssW7TpWXK5fuXyXYzasXB6Nm7fYr7Z4+Tm2b9ua9yXf/Tzlj7O3++RjVu352C3a/3duG1at2OX27aWlsXnd6n2ed19SMJ72bk/B+G233ZbD5Fc8fh+vd9p7O4XG6T2qX7/+Xo85kPe6sj4zB/tZXLVqVb7s0GHX5n66fvfrAAAAAIDqTzAOALVQ2lv58ccfL9jjP/jgg3lf6Y4d/x3SnnXWWTFz5sy8f3W5KVOmxPHHH7/fy6jv63kdzLnTfR555JFYtuy/y47fP2t6NGneIjoee3wedz3ljHj23l33kn7mnhnR9eRdl3J/JUed0DfqN2gYz86dWXHd8oXPxJqXXoyup+z9PG2O6pYD8Gfn/vexSzasjxcevT/PqXxuJevXxuLHH6o4Js21bMeO6HLy/u8tX78o4rc//G589atfjUmTJu2xTP2+Xrtp06btcl16vdP1SWpop/3tdz5mx44deVx+zP7Y23uUHicF8CeeeGKVfxYfffTRaNiwYZx00km7nC9dnz6HAAAAAEDNIhgHgFpo2LBh8dhjj+3Rrn7mmWdyUJj2Uk7Lkqc/p5+tW7dWHJOC53RdasauXbu24phyc+fOjd69e8fixYvzeM6cOfG///u/8dBDD8WCBQvixhtvjI9+9KPxlre8pSJofPOb35wD03e96115Xn/5y1/iBz/4wS7LXu/v80qPl/awLrc/5/7Xv/6V51xu6NChOVx961vfmuc9efLkuPYLX4hRb3tvNGz07+W2B77u7bHqxedj4v9+OZY993TM+etv4pEpY+OcK9+/3/Nt0qJl9L/syrjlu9fGs/fOzkH237/04Rxs7xyMf++1Z8Vj02/Jfy4qKopBb35fTP/V9+LxGZPipacfj79d+8Fo0aFTnHjB8HxMx2N7Ra+zL4x/fu2jOTBf+OA9Me76z8Qpw14TLTt02u9fAh//80/i2muvjd/85jd5H+30uUg/GzZsqDgu7dH9tre9rWL8/ve/P7/Pn/rUp/Ke4T/5yU/ir3/9a37Py6XX/pe//GX8/ve/jyeeeCI+8IEPxMaNG+Oqq67a79dub+/R5z//+fjgBz9YsSR6VX4WZ82aFeeee27FkupJap2nx3qlPdgBAAAAgOqp7m2mCQB1wMknnxynn356DizT/srl3v3ud8eMGTMqxuXN1+eeey4Ho8mll14azz///B7HlJWV5cu0v/KTTz5Z0bhNIWXam/pLX/pSbNmyJY455pgcRu4cNLZq1Sov051CzdQmTsttp0D2ve99b8UxaW/rwYMH7zKX3Q0fPjwaNGgQU6dOzSH5/p47BfxpzuXSUt8TJkzIgW1qEDdr1ize/va3x0e+8NW4ccHGfEzbo7rFO374p5jw3c/HnTf9Ilod0Tle+4Xv50C63LxxN+Wg+7r7d132fGcjPv7VHHbf+MmronTr1uh11uAY89nrdzkmtchLNqyrGJ/39g/F1s2b4l9f+1iUrF8X3U4dGFf96C/RsPF/9/6+4us/y2H4r97/2iiqVy/6XDgyRn3qG7uc97Ond4jXfemH0W/0m/a6v/jUm36TvxTxute9bpfbvvjFL+b3M1m6dGksWrSo4rb0/t5yyy35PU6B8tFHHx2/+tWvKt6PPLcrrojly5fn9yEF7aeeempupB9xxBEVx7zjHe/IQXN63/dmX+/RV77ylYpjquqzmJSfZ2c33XRTDuy7deu21zkDAAAAANVXUVn5/8sNANQqKbz85Cc/mZd+TktJV3e//e1v4xvf+EZurKclrPflxz/+cYwbNy43iKvCb+avjuWbt8f+/II05afXx3P33xXv/eXYqG5WLX4+vvuaM+Ojf58d7bv22OW2otQ6L64fV/Xe/2XsK9v555+fvwixe/hcHUycODE+/vGPx8MPP5y/iJGkLxD07Nkz/vSnP8WgQYMKPUUAAAAA4ABpjANALTVixIh4+umn89LPXbp0ieru1ltvzcH4K4XiSWrAr1mzJtavXx8tWrSo9Hn071Acty7671Lir+Spu6bF6E9/M6qjJ2dPjQGveeseoXhS9p/nWSipwf/ss8/mL29UR2nZ9/RFjfJQPEmt+c997nNCcQAAAACooTTGAQB2sm1HWdzwyKrYuqP2/orUuF5R/L+T20bDeqk7DgAAAABQ+1X/dVUBAA6jFBb379AkLzdeW/Xr0EQoDgAAAADUKYJxAIDdnNWpabRqVK/WheNFURZtGteLszs1LfRUAAAAAAAOK8E4AMBuUpt6VPcWeS/u2iStDn/UqmeiqGxHoacCAAAAAHBY2WMcAGAfpi/eGPcu21w7AvKysih99oHY/vicOPLII+Oyyy6Ljh07FnpWAAAAAACHhcY4AMA+nHtk7VhSPc2/deP6MfL4I6NJkyaxdOnS+PnPfx6zZs2KHTu0xwEAAACA2k9jHADgFSzeuC3++NTaGt0aT8H4W3q1iqOaNYz169fHhAkT4qmnnsq3de7cObfHO3ToUOhpAgAAAABUGcE4AMCrmL96S9y8cH3UVJcd0yJ6t25cMU6//j388MMxadKkKCkpifr168cFF1wQZ599dtSrZ0EhAAAAAKD2EYwDAOyHh1aWxMRFG6KmGd61efRt12Svt6X2+Pjx4+Ppp5/O46OOOiq3x9u3b3+YZwkAAAAAULUE4wAAtTQcf6VQvFz6VfChhx7K7fEtW7bk9viFF14YZ555pvY4AAAAAFBrCMYBAA5wWfWx/1lWvaya7ieejNlt+fRXs27dutwef+aZZ/L46KOPzu3xdu3aVdFMAQAAAAAOH8E4AMABWrxxW4xfuD7Wbt1R7cLx1o3qxajuLeKoZg0P+L7p18IHHnggJk+eHFu3bo0GDRrk9vjAgQO1xwEAAACAGk0wDgBwELbtKItZSzfF3GWbc0u7kL9QlT/+wI7Fcc6RTaNhvfLe+MFZu3ZtjBs3LhYsWJDHXbt2jTFjxkTbtm0racYAAAAAAIeXYBwAoIa3xw+lJb4v6VfE+++/P2677baK9vjFF18cAwYMiKKiQwveAQAAAAAON8E4AEAltMfnvLQp5i0viS07yqq8QV5+/sb1iqJfhyZxVqdDb4nvy5o1a3J7/Lnnnsvjbt265fZ4mzZtquTxAAAAAACqgmAcAKASA/InVm+Jecs3x8ubt1d6QJ52+d4REUcU14/+HYqjd5vGVRaI7yz9unjffffFlClTYtu2bdGwYcPcHj/jjDO0xwEAAACAGkEwDgBQBZZu3Bb3ryiJx1dvie1luwbb+2vn4+sXRZzYpnGc3qFJHNm08pZMPxCrV6/O7fGFCxfmcffu3XN7vHXr1gWZDwAAAADA/hKMAwBUoR1lZbGiZHu8tKk0/yzZuC2Wl2yvCMv3JoXgHZrUj87NGkanpg3yT/sm9aNeNWhnp18d77333pg6dWpujzdq1CiGDBkS/fr10x4HAAAAAKotwTgAQAHC8jVbduSl17eXlUVpWUSDohSIF+Wl0Vs3rlctQvBXsmrVqhg7dmwsWrQoj4899tgYNWqU9jgAAAAAUC0JxgEAOCjp18h77rknpk2bFqWlpbk9PnTo0Dj99NO1xwEAAACAakUwDgDAIVm5cmVuj7/wwgt53KNHj9web9WqVaGnBgAAAACQCcYBADhkO3bsyO3x6dOn5/Z448aNY9iwYXHqqadqjwMAAAAABScYBwCg0qxYsSK3x1988cU8Pu6443J7vGXLloWeGgAAAABQhwnGAQCo9Pb4nDlz4vbbb4/t27fn9vgll1wSffv21R4HAAAAAApCMA4AQJVYvnx53HzzzbFkyZI87tWrV4wcOTJatGhR6KkBAAAAAHWMYBwAgCptj991111xxx135PZ4kyZNYvjw4XHyySdrjwMAAAAAh41gHACAKrds2bLcHl+6dGkeH3/88bk93rx580JPDQAAAACoAwTjAAAcFqkxfuedd8aMGTNyk7y4uDi3x/v06aM9DgAAAABUKcE4AACH1csvv5zb4y+99FIen3DCCTFixIho1qxZoacGAAAAANRSgnEAAArSHp89e3bMnDkzt8ebNm0al156aZx00kmFnhoAAAAAUAsJxgEAKJjUGk/t8dQiT0488cQckGuPAwAAAACVSTAOAEDB2+OpOT5r1qxIv5qm9nhaWj2F5AAAAAAAlUEwDgBAtbB06dLcHl+2bFke9+nTJ4YPH56DcgAAAACAQyEYBwCg2igtLc3t8bT/ePo1NS2pPnLkyOjdu3ehpwYAAAAA1GCCcQAAqp3FixfH2LFjY/ny5Xl88skn5/Z4cXFxoacGAAAAANRAgnEAAKpte/yOO+6Iu+66K7fHmzdvntvjxx9/fKGnBgAAAADUMIJxAACqtRdffDG3x1esWJHHffv2jWHDhmmPAwAAAAD7TTAOAEC1t23btor2eNKiRYsYNWpU9OzZs9BTAwAAAABqAME4AAA1xgsvvJDb4ytXrszjU089NbfHmzRpUuipAQAAAADVmGAcAIAa1x6fPn163H333XncsmXL3B4/7rjjCj01AAAAAKCaEowDAFAjLVq0KLfHV61alcennXZabo83bty40FMDAAAAAKoZwTgAADW6PT5t2rS45557KtrjY8aMiWOPPbbQUwMAAAAAqhHBOAAANd7ChQtj3LhxsXr16jzu169fDBkyRHscAAAAAMgE4wAA1Apbt26NqVOnxr333pvHrVq1yu3xY445ptBTAwAAAAAKTDAOAECt8txzz+X2+Jo1a/K4f//+uT3eqFGjQk8NAAAAACgQwTgAALXOli1bYsqUKTFv3rw8bt26dW6Pd+/evdBTAwAAAAAKQDAOAECttWDBgtweX7t2bR4PGDAgLrroIu1xAAAAAKhjBOMAANT69vhtt90W999/fx63adMmt8e7detW6KkBAAAAAIeJYBwAgDrhmWeeifHjx8e6devyeODAgbk93rBhw0JPDQAAAACoYoJxAADqjJKSkpg8eXI8+OCDedy2bdu47LLLokuXLoWeGgAAAABQhQTjAADUOU8//XRuj69fvz6PzzrrrBg8eLD2OAAAAADUUoJxAADqpN3b4+3atcvt8aOPPrrQUwMAAAAAKplgHACAOu2pp57K7fENGzZEUVFRRXu8QYMGhZ4aAAAAAFBJBOMAANR5mzdvjkmTJsXDDz+cx+3bt8/t8aOOOqrQUwMAAAAAKoFgHAAA/mP+/PkxYcKE2LhxY26PDxo0KM4//3ztcQAAAACo4QTjAACwk02bNsXEiRPj0UcfzeOOHTvGmDFjonPnzoWeGgAAAABwkATjAACwF0888URuj6egPLXHzz333DjvvPOifv36hZ4aAAAAAHCABOMAALAPaUn11B5/7LHH8viII47Ie4936tSp0FMDAAAAAA6AYBwAAF5FCsZvvfXW3B6vV69ebo+nH+1xAAAAAKgZBOMAALCf7fFbbrklL7GepNZ42ntcexwAAAAAqj/BOAAA7Kf0q3N5e3zz5s25PX7++efHoEGDtMcBAAAAoBoTjAMAwAHasGFDbo/Pnz8/j4888si893jHjh0LPTUAAAAAYC8E4wAAcBDSr9GPPvpobo+XlJTkxnh5ezw1yQEAAACA6kMwDgAAh2D9+vUxYcKEeOqpp/K4c+fOuT3eoUOHQk8NAAAAAPgPwTgAAByi9Cv1ww8/HJMmTapojw8ePDjOOuss7XEAAAAAqAYE4wAAUEnWrVuX2+NPP/10Hh999NExZsyYaN++faGnBgAAAAB1mmAcAAAqUfr1+sEHH4zJkyfHli1bcnv8wgsvjDPPPFN7HAAAAAAKRDAOAABVYO3atTF+/Ph49tln87hLly65Pd6uXbtCTw0AAAAA6hzBOAAAVJH0q/YDDzyQ2+Nbt26NBg0axEUXXRQDBw6MoqKiQk8PAAAAAOoMwTgAAByG9vi4ceNiwYIFedy1a9fcHm/btm2hpwYAAAAAdYJgHAAADoP0a/e8efNiypQpFe3xiy++OAYMGKA9DgAAAABVTDAOAACH0Zo1a3J7/Lnnnsvjbt265fZ4mzZtCj01AAAAAKi1BOMAAHCYpV/B77vvvtwe37ZtWzRs2DCGDBkS/fv31x4HAAAAgCogGAcAgAJZvXp1jB07Np5//vk8PuaYY2L06NHRunXrQk8NAAAAAGoVwTgAABRQ+nV87ty5MXXq1CgtLY1GjRrl9ni/fv20xwEAAACgkgjGAQCgGli1alVujy9atCiPjz322Nweb9WqVaGnBgAAAAA1nmAcAACqifSr+T333BPTpk2raI8PGzYsTjvtNO1xAAAAADgEgnEAAKhmVq5cmdvjL7zwQh736NEjt8dbtmxZ6KkBAAAAQI0kGAcAgGpox44dcffdd8f06dNj+/bt0bhx49weP/XUU7XHAQAAAOAACcYBAKAaW7FiRdx8882xePHiPO7Zs2eMHDlSexwAAAAADoBgHAAAakB7fM6cOXH77bfn9niTJk3ikksuiVNOOUV7HAAAAAD2g2AcAABqiOXLl+f2+JIlS/K4V69euT3eokWLQk8NAAAAAKo1wTgAANSw9vidd94Zd9xxR/5zao8PHz48Tj75ZO1xAAAAANgHwTgAANRAy5Yty+3xpUuX5nHv3r1jxIgR0bx580JPDQAAAACqHcE4AADUUGm/8dQenzFjRm6PFxcXx6WXXhonnXSS9jgAAAAA7EQwDgAANdzLL7+c2+MvvfRSHp9wwgm5Pd6sWbNCTw0AAAAAqgXBOAAA1JL2+KxZs/JPao83bdq0oj0OAAAAAHWdYBwAAGqR1BpP7fHUIk9SMJ4C8hSUAwAAAEBdJRgHAIBa2B6fOXNmbo+nX/fTkuppafW0xDoAAAAA1EWCcQAAqKWWLFmS2+PLly/P4z59+sTw4cO1xwEAAACocwTjAABQi5WWlsaMGTPizjvvrGiPjxw5Mnr37l3oqQEAAADAYSMYBwCAOmDx4sUxduzYivb4KaecEpdcckkUFxcXemoAAAAAUOUE4wAAUIfa43fccUfcdddduT3evHnzGDVqVPTq1avQUwMAAACAKiUYBwCAOubFF1/Me4+vXLkyj/v27Zvb402aNCn01AAAAACgSgjGAQCgDtq2bVvcfvvtMWfOnDxu0aJFbo/37Nmz0FMDAAAAgEonGAcAgDrshRdeyO3xVatW5fGpp54aw4YN0x4HAAAAoFYRjAMAQB2X2uPTp0+Pu+++O49btmwZo0ePjh49ehR6agAAAABQKQTjAABA9vzzz8fYsWNj9erVeXz66afH0KFDo3HjxoWeGgAAAAAcEsE4AABQYevWrTFt2rSYO3duHrdq1Sq3x4899thCTw0AAAAADppgHAAA2MPChQtze3zNmjV53K9fvxgyZIj2OAAAAAA1kmAcAADYZ3t86tSpce+99+Zx69atc3v8mGOOKfTUAAAAAOCACMYBAIBX9Nxzz+X2+Nq1a/P4jDPOiIsvvjgaNWpU6KkBAAAAwH4RjAMAAK9qy5YtMWXKlJg3b14et2nTJsaMGRPdunUr9NQAAAAA4FUJxgEAgP327LPPxrhx42LdunV5PGDAgLjooou0xwEAAACo1gTjAADAAbfHJ0+eHA888EAet23bNrfHu3btWuipAQAAAMBeCcYBAICD8swzz8T48eMr2uNnnnlmXHjhhdGwYcNCTw0AAAAAdiEYBwAADlpJSUlujz/44IN53K5du9we79KlS6GnBgAAAAAVBOMAAMAhe/rpp3N7fP369VFUVJTb44MHD9YeBwAAAKBaEIwDAACVYvPmzbk9/tBDD+Vx+/btc3v86KOPLvTUAAAAAKjjBOMAAEClevLJJ2PChAmxYcOG3B4/++yz44ILLogGDRoUemoAAAAA1FGCcQAAoEra45MmTYqHH344jzt06JDb40cddVShpwYAAABAHSQYBwAAqsz8+fNze3zjxo25PX7hhRfGoEGD8p/3ZceOHVGvXr3DOk8AAAAAajf/bxMAAFBlevfuHVdffXX06dMn0ndyO3funC/3Zvbs2flSKA4AAABAZdMYBwAADoslS5bkYHxvUqP8lFNOic985jPxnve857DPDQAAAIDaTRUDAAA4LF6pLd6sWbPo1q1bXnp9b0urAwAAAMChEIwDAACHzd72Fk/Bd/pp3bp1tG3bNl+XAvIf//jHsXjxYkurAwAAAHDIGhz6KQAAAA5eefDdokWL+OMf/xgLFy6Mf/3rX9G4ceNo0KBBXlpdOA4AAADAoRCMAwAABfW3v/0t5s2bF//3f/8XzZs3j5YtW8ZNN90UgwYNiqZNmxZ6egAAAADUAoJxAADgsNu4cWNcc8018dhjj+WfSy+9NHr16hWvec1r4rrrrsvH2FscAAAAgMoiGAcAAA67Zs2a5T3F3/72t8c555wTJ510UnzkIx+JBQsWVBxj+XQAAAAAKotgHAAAKIhvf/vb+bKsrCxfrljx/9u7D+ioyq2N4zu9QwIEQkKJ9A5SBVSkSK9X/OTqtYCKYLsqiiLqtaJiwYKKBTuo2OgdpCNVepPeSUJCSO/f2q9OTEISJmSSyUz+v7VmTc6Zc868UyCZec7eb5QEBQWZnzMyMsTNzc2q42hlOSE6AAAAAAAACsO3RwAAAABKnSUMVy4uLuZa5xbfs2eP+dmaUNxyDEsofubMGVm8eHEJjRgAAAAAAACOjGAcAAAAQKmzhOE5DR8+XHr16iXJycm5gvPCAnXd9sMPP5QHHnhAOnfuLL179zbHYX5yAAAAAAAA5EQrdQAAAAB2p0F2+/btzcWaQH3FihUybdo0Mye5tl0fMWKEqTifO3euOQat1QEAAAAAAJAT3xYBAAAAsCutAtcgOykpKXtdenp6gdu/9NJLMmDAAGnevLl8++23snz5crn66qvljz/+kMaNG8vo0aOzjwsAAAAAAAAognEAAAAAdmWpAn/++efluuuuM3OFu7v/1dxKq8Fz0rDb39/fhOibN2+W6tWrS2pqqnzwwQdy+vRpefXVV7P3y69dOwAAAAAAAMongnEAAAAAZcKYMWOkdu3apupbg27l5uaWKxzXsPvRRx+VNWvWyK5du0ww/sQTT8i6devM/nXr1jVt2XU/AAAAAAAAwMIli/6CAAAAAMqQH374QR5//HFp0KCBTJ8+XapVq5bvdhqA33HHHTJjxgwJCQmR48ePm/X6EYdqcQAAAAAAAORExTgAAACAMuWWW26RTZs2mbA7LCzMBN85Wc7t1dbpQUFBpspc17322mumrTqhOAAAAAAAAPL6a+I+AAAAAChDNBSfNm2aDBgwQC5evGjmFPfx8TG3afCtQbgG5r/88ouZV1wrxyMjI8XT07PQ42qVuaurK1XlAAAAAAAA5Qyt1AEAAACUaZYwO6+tW7fKV199Je+++26h++tHnvnz50u3bt2yw/XCjgsAAAAAAADnQzAOAAAAwOFlZGSIm5tbvretWrVKbrjhBqlZs6aMGDFCKlSoIEOGDJHw8PBc21FFDgAAAAAA4LwojwAAAADgkHKe41tQKK4aNGggvXr1khMnTsjKlStly5Yt0qxZM7n11lvl008/lTVr1pjtCMUBAAAAAACcFxXjAAAAAJxecnKy3H///ZKamioPP/ywpKenmxbsurxr1y5zm64vLGAHAAAAAACA4yIYBwAAAOCU5syZI3Xq1JGmTZua5QULFsjEiRNl8ODB8t///tesO3z4sKSlpZmAvHnz5nYeMQAAAAAAAEqKe4kdGQAAAADsaMaMGTJt2jSZNGmSCcL79Okj0dHRMnz4cImPj5fx48eb4BwAAAAAAADOjznGAQAAADilb775RqZPn24C8Ouvv172798vt912m1m/dOlS+eWXX3LNU16QCxcuyMmTJ02YDgAAAAAAAMdEMA4AAADA6WRkZJjrYcOGSUREhAQEBEirVq1k8uTJ0rVrV6lfv74JxxMSEi7ZNzMz01zHxMTITz/9JC1atJD+/ftLgwYNZOrUqaX+WAAAAAAAAFB8tFIHAAAA4HTc3NzMdXp6uvj6+sq8efNMpfj9999v5hp///335cSJE+Lv759rP60gd3X96/zhN99807Rj79u3r6k0P3TokDz77LNSqVIlGTJkiF0eFwAAAAAAAK6MS5Y1vQMBAAAAwIGrxy1BeVxcnAwdOlRatmwpL7/8snh6epow3MXFxdxu+fmjjz6Szz//XHr16mW2s+jevbs0a9ZM3n33Xbs9HgAAAAAAABQdFeMAAAAAyk31uLZUX7RokZw7d86E4ipvKH7gwAH5/vvvTQD+wAMPZB9H9w8ODpakpCTzs7s7H6cAAAAAAAAcBXOMAwAAACgXNMi2zB9erVq1S263BOQ693hycrKpLK9evboJzJXOVb5hwwapUaMGoTgAAAAAAICDIRgHAAAAUG5Y5g/PjyUA37Jli3h7e0u/fv1y3a7zksfHx8sTTzxR4uMEAAAAAACAbVHmAAAAAAB/V4xrRfmpU6ekXr16udYvWbJE3nzzTTP3uI+PT655yQEAAAAAAFD2UTEOAAAAADkqygcMGCB//PGHnD59Wi5cuCAzZsyQe+65R4YNG2auFaE4AAAAAACAY3HJsvQLBAAAAABIXFycmV98+/btZi7ymJgY6dixo/zwww/2HhoAAAAAAACuEME4AAAAAPxNW6lb5iGfN2+eqRhv3ry51K1bV/z8/HLdbtk+JSXFtFcHAAAAAABA2UUwDgAAAAA5ZGRkiJub22W3049Sy5cvl23btkn//v2lYcOGpTI+AAAAAAAAFB1zjAMAAABADtaE4iotLU32798v8fHx8v3338uvv/4qSUlJJT4+AAAAAAAAFB0V4wAAAABwhdLT0+W3336T9evXmwpyf39/GTBggDRo0MDeQwMAAAAAAEAOBOMAAAAAUEwnT56UmTNnyvnz581yq1atpFevXuLt7W3voQEAAAAAAIBgHAAAAABsQ1urW6rHVUBAgAwcOFDq1atn76EBAAAAAACUewTjAAAAAGBDx48fl1mzZkl0dLRZvvrqq6Vnz55UjwMAAAAAANgRwTgAAAAAlED1+LJly2TDhg1muUKFCqZ6vG7duvYeGgAAAAAAQLlEMA4AAAAAJeTYsWOmejwmJsYst27d2lSPe3l52XtoAAAAAAAA5QrBOAAAAACUoNTUVFM9vnHjRrNcsWJFUz1ep04dew8NAAAAAACg3CAYBwAAAIBScPToUVM9fuHCBbPctm1bufHGG8XT09PeQwMAAAAAAHB6BOMAAAAAUIrV40uWLJHNmzeb5cDAQBk0aJCEh4fbe2gAAAAAAABOjWAcAAAAAErZkSNHTPV4bGysWW7Xrp306NGD6nEAAAAAAIASQjAOAAAAAHaQkpJiqse3bNliloOCgkz1eO3ate09NAAAAAAAAKdDMA4AAAAAdnTo0CGZPXu2XLx40Sx36NBBunfvLh4eHvYeGgAAAAAAgNMgGAcAAAAAO0tOTpbFixfLH3/8YZYrVapkqsdr1apl76EBAAAAAAA4BYJxAAAAACgjDh48aKrH4+LizPI111wj3bp1o3ocAAAAAACgmAjGAQAAAKCMVY8vWrRItm3bZpYrV65sqsdr1qxp76EBAAAAAAA4LIJxAAAAACiDDhw4IHPmzJH4+HhxcXGRjh07SteuXcXd3d3eQwMAAAAAAHA4BOMAAAAAUEYlJSWZ6vHt27eb5SpVqsjgwYMlLCzM3kMDAAAAAABwKATjAAAAAFDG7d+/X+bOnZtdPd6pUye54YYbqB4HAAAAAACwEsE4AAAAADiAxMREWbhwoezcudMsBwcHm+rx0NBQew8NAAAAAACgzCMYBwAAAAAHsnfvXpk3b54kJCSY6vFrr71Wrr/+eqrHAQAAAAAACkEwDgAAAAAOWD2+YMEC2bVrl1muWrWqqR6vXr26vYcGAAAAAABQJhGMAwAAAICD2rNnj6ke16Dc1dU1u3rczc3N3kMDAAAAAAAoUwjGAQAAAMCBaUv1+fPnm5BcVatWzVSPh4SE2HtoAAAAAAAAZQbBOAAAAAA4gd27d5vq8aSkJFM9rpXjWkFO9TgAAAAAAADBOAAAAAA4jfj4eBOO79u3zyzrnOODBg0yVeQAAAAAAADlGcE4AAAAADgR/Yi3a9cu0149OTnZVI936dLFVI/rzwAAAAAAAOURwTgAAAAAOKG4uDhTPb5//36zHBoaaqrHq1atau+hAQAAAAAAlDqCcQAAAABwUvpxb+fOnbJgwQJTPa7zjd9www3SqVMnqscBAAAAAEC5QjAOAAAAAOWgenzOnDny559/muWwsDBTPR4cHGzvoQEAAAAAAJQKgnEAAAAAKAf0o9/27dtl4cKFkpKSYqrHu3btKh07dqR6HAAAAAAAOD2CcQAAAAAoRy5evGiqxw8ePGiWa9SoYarHq1SpYu+hAQAAAAAAlBiCcQAAAAAoZ/Rj4LZt22TRokWmetzd3V26desmHTp0oHocAAAAAAA4JYJxAAAAACinYmNjZfbs2XL48GGzXLNmTVM9XrlyZXsPDQAAAAAAwKYIxgEAAACgHNOPhFu3bpXFixdLamqqqR7v3r27qR53cXGx9/AAAAAAAABsgmAcAAAAACAXLlww1eNHjhwxy7Vr15aBAwdKpUqV7D00AAAAAACAYiMYBwAAAAAY+vFwy5Ytpno8LS1NPDw8pEePHtKuXTuqxwEAAAAAgEMjGAcAAAAA5BITE2Oqx48ePWqWw8PDTfV4UFCQvYcGAAAAAABwRQjGAQAAAACX0I+KmzZtkqVLl2ZXj/fs2VPatGlD9TgAAAAAAHA4BOMAAAAAgAJFR0fLrFmz5Pjx42a5Tp06MmDAAAkMDLT30AAAAAAAAKxGMA4AAAAAKJR+bNy4caOpHk9PTxdPT09TPd66dWuqxwEAAAAAgEMgGAcAAAAAWOX8+fOmevzEiRNmuW7duqZ6vGLFivYeGgAAAAAAQKEIxgEAAAAAVsvMzJQNGzbI8uXLTfW4l5eX9OrVS1q1akX1OAAAAAAAKLMIxgEAAAAARRYVFWWqx0+ePGmW69WrZ6rHK1SoYO+hAQAAAAAAXIJgHAAAAABwxdXjv//+u6kez8jIMNXjvXv3lpYtW1I9DgAAAAAAyhSCcQAAAABAsURGRprq8VOnTpnl+vXrm+rxgIAAew8NAAAAAGCljKwsiU3JlLTMLEnPypKMLBE3FxF3FxfxcHWRil6u4sZJ0HBgBOMAAAAAAJtUj69bt05WrFhhqse9vb2lT58+0rx5c6rHAQAAAKAMhuBRSRlyNildziWmy+mENIlMzjBheEE0JA/2dpNQPw+p5usuIT7uUsXHjbAcDoNgHAAAAABgMxERETJz5kw5c+aMWW7YsKH0799f/P397T00AAAAACj3ziSkyZaoZNkbk5Idgrvqyc5FOEbO7TUsbxzkJW2CvaW6r0dJDBmwGYJxAAAAAIBNacX42rVrZeXKlaaS3MfHx1SPN2vWjOpxAAAAAChl2hpdg/DNkUkSkZQh+qnMluGg5XjVfNykTbCPCcq19TpQ1hCMAwAAAABKxLlz50z1+NmzZ81yo0aNpF+/flSPAwAAAEApBeLrzybK5shkSc3Msnkgnpfl+J6uLtI22Fs6hvgSkKNMIRgHAAAAAJRo9fiaNWtk1apV2dXjGo43bdrU3kMDAAAAAKd1KiFN5hyNk9jUzBINwwuicXhFT1cZEB4gYX60WEfZQDAOAAAAAChxWjWu1eNaRa6aNGkiffv2FT8/P3sPDQAAAACcqkp89ZlE2RiRVOIV4pdjuf/2VX3kuupUj8P+CMYBAAAAAKVWPa6V46tXrxb9KOrr62uqxzUkBwAAAAA4dpV4YQKpHkcZQDAOAAAAAChVZ86cMdXjERERZrlZs2bSp08fE5QDAAAAAIpuX0yKzDoaZ34ui8GfpVZ8UHiANArysvNoUF4RjAMAAAAASl16erqpHtf5x/VjqbZU79+/vzRq1MjeQwMAAAAAh7L9fLIsOB4vjqJPLX9pWdnb3sNAOUQwDgAAAACwm9OnT5vq8cjISLPcvHlzUz3u4+Nj76EBAAAAQJnnaKG4BeE47IFgHAAAAABg9+rxFStWyLp160z1uL+/v6keb9iwob2HBgAAAABlun36zL/bpzuiwbRVRykjGAcAAAAAlAknT56UWbNmSVRUlFlu2bKl9OrVi+pxAAAAAMjjVEKafHsgtkzOJ16Uecf/06CihPl52HsoKCcIxgEAAAAAZap6/LfffpP169eb6vGAgAAZMGCA1K9f395DAwAAAIAyIS0zS6bujZHY1EyHD8YrerrK3Y2DxMNVl4CSRTAOAAAAAChzTpw4YarHz58/b5ZbtWplqse9vZmDDgAAAED5tvxUgmyKSHLoUDynDlV9pGuYn72HgXKAYBwAAAAAUCalpaXJ8uXL5ffffzfLWj0+cOBAqVevnr2HBgAAAAB2a6H+zYFYcTa301IdpYBgHAAAAABQph0/ftxUj0dHR5vlq6++2lSPe3l52XtoAAAAAFBqnKWFel60VEdpIRgHAAAAADhE9fiyZctkw4YNZrlChQqmerxu3br2HhoAAAAAlIpVpxNk/TnnaaGeV6dqPnJ9KC3VUXIIxgEAAAAADuPo0aMye/ZsiYmJMctt2rSRG2+8kepxAAAAAE5fLf7+zmhJzbRtrBcfEyVLP3pd9q1ZIvHnI8WnQkWpXr+pdBv5uIS36iC/vjxGDm5cJRcjz4qXj5/UatlOej/8nFS9qr7YmperizzYvBJV4ygxBOMAAAAAAIeSmpoqS5culU2bNpnlihUryqBBg+Sqq66y99AAAAAAoETsOJ8s84/H2/y4H989QDLS0qTXQ89IpbDaEh8dKYc2rpKqdRtJky69ZePPX0tweD0JrF5DEmNjZNnHb8jpA7tk7Jwt4urmZvPx9KvlL80re9v8uIAiGAcAAAAAOKQjR46Y6vELFy6Y5bZt25rqcU9PT3sPDQAAAABs6vN9MRKZlGHTNupJcbHyYpd6cu+nM6VOm85W7XPmwG55b9gN8visjVK5pm1PTtY68ao+bjK8UZBNjwtYuGb/BAAAAACAA9EK8dGjR5tAXG3evFk++ugj024dAAAAAJzFmYQ0ibBxKK48ffzE09dP9vy2QNJTUy67fWpSgmyZ/Z0EhdWWiiFhNh6NmMd3LinDPF6gJFAxDgAAAABweIcPHzbV47GxsWa5ffv20r17d6rHAQAAADi8ucfiZHd0is2DcbVr2Rz55aXHJC0lWcIaNZerWneSFr2GSPUGTbO3WT/jc1n47guSmpRo2qrf+e50m1eL56zobVrJS/rVDiiR46N8IxgHAAAAADiFlJQUWbx4sWzdutUsBwUFmbnHa9eube+hAQAAAMAVycjKkre3n5eMEkzzNBQ/+sfvcnznFjmwdpmc3L1V/vXsJGkz8N/m9uS4ixIfEylxkedk9TcfSmzEGRn1xTzx8CqZucDdXETGtKwsri7aXB2wHYJxAAAAAIBTOXTokKkev3jxolnu0KGDqR738PCw99AAAAAAoEjOJabLF/svlOp9/vziI3Lw95Xy5Pw/LrktPS1VXuxSX/713CRp1ftfJTaGEY0CpaqPe4kdH+UTc4wDAAAAAJxK3bp1zdzjV199tVnesGGDTJkyRU6cOGHvoQEAAABAkZxNSi/1+6xap6GkJifmf6Opt82SDCvmJC+Os4ml/7jh/AjGAQAAAABOx9vbWwYOHCi33nqrBAQESHR0tHz++eem1XpaWpq9hwcAAAAAVleMl1SYl3AhWj4dOUT+mPejnDmwW6JPHZOdS2bJqq/elyZdekv0yaOy4vN35NSe7XLhzEk5tn2jTB97t7h7eUvDa3uUaHhJMI6SQCt1AAAAAIBTS05OlkWLFsm2bdvMcuXKlWXw4MFSo0YNew8NAAAAAAr15b4YOZuUUSLHTk9NkaUfT5Q/168wIXhGeroEhoRKsx4DpeuIRyQpLta0VT+9d4ckXbwg/pWDJbx1R+l+7+MSHF5PSlKIj5vc1SioRO8D5Q/BOAAAAACgXDhw4IDMmTNH4uPjxcXFRTp27Chdu3YVd3fmrQMAAABQ9mRkZclb289LZjlM8txcRMa0rCyuLi72HgqcCME4AAAAAKDcSEpKkoULF8qOHTvMcpUqVUz1eFhYmL2HBgAAAAC5RCdnyCd7Y6S8Gtk4SCp5u9l7GHAiBOMAAAAAgHJn3759MnfuXElISDDV4507d5YuXbpQPQ4AAACgTM0v/sX+C1JeDW8YKNV8+YwG2yEYBwAAAACUS4mJiaZ6fOfOnWa5atWqMmjQIAkNDbX30AAAAABATiWkyTcHYqW8uqNBRQn187D3MOBECMYBAAAAAOXa3r17TfW4BuVaPX7ttdea6nE3N1r2AQAAALCfI7HJ8sPheCmvbq1fUWr5E4zDdgjGAQAAAADlnrZUX7BggezevdssV6tWzVSPV69e3d5DAwAAAJzS+fPnpXHjxrJx40YJDw8XR7B//35zEu2ff/4pAQEBl90+IyNDUlJSJDk5WZKSksy1tRfdPrNCFfG8bqiUV1SM/+Wpp54yn1nff//97HV79uyRnj17mvekn5+fXcfnSAjGAQAAAAD4mwbj8+fPN9Xjrq6uct1115kL1eMAAACAbT322GMSFxcnn376qVn+8ssvZfjw4flue+7cOTP1UX6io6PloYcekjlz5pi/4W+66SZ59913xd/fP3ubHTt2yAMPPCCbNm2S4OBgs/3YsWMvO0aN0CzBtl7uvPNOadSokdx1113Z67QD1eTJk+XgwYPmPjU4v/76602wnZaWlu9xL1y4IPPmzZMjR46Ip6entGrVSrp3757rc4fetnjpMomIiJCK1UKl2z2PSZuB/5aiSEtJlvlvPyfbF8+UjNQUqd+xqwwaN1ECKlct9DEvnfK6bPr1G0mKuyi1W7aXwU9PlCq16mZvkxgbI7MnjpN9qxaJi4urNOveX/o/8Yp4+f7znF/OuUP7ZMlHr8mpvTvkwpkT0m/MS3LtbaMuO8e4Na/ljz/+KM8++6wcPXpU6tevL6+//rr07dtXiuv48eMyevRo+e2338xrre+HV199VdzdC54H3Rbvz6ioKKlTp45s27bNXFsMHTpUWrZsaR4rrMOM9QAAAAAA/K1p06amWkW/pNIvuFauXGnOwNfq8ZCQEHsPDwAAAHAKeiLq1KlTZdGiRdnrbrnlFundu3eu7SwBdEGhuLrtttvkzJkzsmTJEhNEa7g+cuRImT59ugl5tTL9xhtvNCe8aji5c+dOGT9+vMTExJj7u1zlds4we+nSpdKsWTOZPXu2Wae3axWvhpX33nuvCfBnzZol6enp0rZt2+x9Nfz29vY2Fy8vL/PYK1WqJJMmTTKVwK+99poJ3J944gmzjYbhXbt2ldtH3C2+NwyTgxtXyS8vPSoBVapJg07drH6e5731rOxbs0Rue32qePtXkFmvPyXTHr9LRn0xv8B9Vn31vqz77lO5+cXJEhRay4TXnz9wizz60xrx8PI22/wwfpTERZ2TER/+JJnpafLT8w/Lry+PkWETPrZ6bKnJSVIpLFya3zhI5r31TL7beLi65Fq+ePGiqZLu0aOHTJkyxbyWI0aMkMDAQPOaq3Xr1sm///1vE1j379/fvA8GDx4sW7duNa/dldLq/379+pnPhXof+p674447xMPDQyZMmHBF709rH1OVKlWkV69e8tFHH8kbb7yRfWw9lr7vxo0bV2g4j39QMQ4AAAAAQB76UdlSPa6VHnpmv1Z96PzjVI8DAAAAxfPTTz/J/fffbwLggkRGRkpYWJh88sknpjI2v3bk+/btM+HkW2+9JTVr1jTrNm/ebMLqp59+2oTQGzZskGXLlsnjjz+eHR5qSKn7amWuNXS/33//3VT2/u9//8sOufW433zzjQnctbW6rnvvvfdMgK4t4i3b6ecJC53CSQPb06dPmymclAaiTz75pHnMGqLrz3qy7vadO+Wt7eclM0vku6fulaS4WBnxwQyrxpwcd1Fe7t5IbpkwRZr3GGjWRRz5Uybd1ElGf7lAarX4J7jP+Tno1V7N5Nr/3C/X3/FA9nFeubGJDH3hfWnZa4hEHD4gk4Z2lge+XSI1mrQy2+xfu0y+evjf8tTCHVIhuOgnFL/er7V0vnVkropxNxeRMS0ri6vLP+G4BsN6UsPZs2fN82RpMz5z5kzzelpOsNCTDebOnZu93zXXXGOq8vV5vlLWvG556cnWTZo0MZXglhMlFi5caKrXT548KaGhoVY9JvX111+b7U6cOJG9LjU1VSpUqGDeK9pxAJfH6QMAAAAAAOTh4uJiqgks1eP6hcSKFStM9bhWGxRWsQIAAACg8Hm2NfTTFtdr164tsFJbA0Q9KVVblGvwnR+tAtbgWVuy65zLqmLFiuZa99M5zDVI1L/rNUDUbX18fMxJr3rfDRo0MK2rLQF2QRcNxrWLlAaaWs1roY+jW7dupn26hQazH3/8sflM4evre8mY169fL82bN88OV5VWA2uLbj059+qrrzbbaAWxm4uLVPV2k7NJGaYN+twCKqvzc2rvdslIT5N6Hf4ZW9Wr6ktgSA05vmNzvsF4zKljEhcVIfU6XJ+9zjuggtRs1lqO79hkgnG99g6omB2KK70PF1dXObFzizTt1k9sIdjbLVcorvR50dcuZwitz522StcOAEFBQWYbbdOfk26jr1VxWPO65bePVn7n7B6gr6ueKKEnbAwZMsSqx6Tat29vwnRtD6/vZ2Vpw7969WqCcSsRjAMAAAAAUACd9+3//u//ZNeuXaZ6XFvg6ZdcN9xwg3Tu3DlX5QcAAADgjHLOs523Yvtyl4Lm2daqbg2NtbK6IFqhrSeraqtqZQmpNdi2/Pznn3+aNtPadjxnkP3hhx9K69atZdSoUbJmzRq56qqrTJtyCw3RtdW2hooanlvj2LFjuQJOpVW+euycLMGp3mYJNfPukzNczbtP3m1C/TwkIilD/CsHS0p8nKQlJ4mHt89lxxt3PkLcPDzFJ+CvEwUs9Dh6W0H7mG0qBV+6T1RE9jb+larkut3N3V18KgQVeNyicv37cedlzfNd0PNreW6vlDWvW3775D2pWk+y0Db6OV9ra95DWl1ueR9agnHLel0H6xCMAwAAAABQCK300MoA/fJB2/EdOHBAli9fbqrItXpcK0wAAACAshxsazidM6wuSrCtobgt5JxnW8NBDbRbtmxp2p3nDLv1osF1VFSU/Pjjj9KxY0ezr/5dnpdWhWubaq24zUlPYNXW5lolrvvlt29R6XOhYytt1XzdJVPKF328Ib72izD79OljqrBV7dq1TUW4vem/EZWYmHjJ+rzrUDCCcQAAAAAArKBfrA0bNszMK6htHXVuOUv1eKdOnageBwAAQIlJT0+/omDbcsnMLH60qmF2flXb+QXb+V1y/r2sVdwa2OuJpvl54403TDW3/q1dmJCQkEvmKdfnKjo62txm2ebcuXO5trEsW7axhgb52to67/0X9di6XucfL2yfnMcN8fkryos/Hyle/gFWVYurgMpVJSMt1cxLnrNqXI+jtxW0j9kmOjLXXOG6T/WGzbK3iY+OyrVfRnq6JF2MKfC4VyK/YNya57ugbYryWn/22Wfm35mydCyw5nUryfen7qPynpit6+vWrWv1YyvvCMYBAAAAALCSVppoVYu2utPqcW3duGzZsuzqcf2yDAAAALBmnu2iVG3r/sWlwXRxgm0Nxm1F52P+9ttv870tPj5eZsyYYVqdX45Wk1+4cEG2bNkibdq0Meu0u5OeCNChQ4fsbcaPH2+q5i0h55IlS6Rhw4b5tjovbMyWecxz3n9Rj637vPLKKyYwtbTZ1n20ur1JkybZ2+hUTqqKj5u4uYgc3LBSajW/dF7wgoQ1bilu7h5yaOMqadZ9gFkXefSgXDh7Mt/5xVVQWG0JqFJVDm1cLaENm5t1yfFxcmLXVulw83CzXKtFO0mOi5VTe7ZLWJOWZt2hTaslKzNTajb/6zUoLn28VbzdLllvzfOt2+hntEceeSR7P91G11srLCzsil63knx/6vReenvTpk1z3YeuHzp0qNWPrbxzydJTcgAAAAAAQJHox+nt27eb6nH9ktPNzU26desm11xzDdXjAAAATqYk5tm+ElcabOvtGmzboqW4LezcudPMAa4hY94AeerUqfLggw/KmTNnJDAwMNdtWrF7xx13mODTEl5q22utsJ0yZYp5nocPH27mAp8+fbq5PTY21oSMPXv2lCeffNIEiSNGjJBJkybJyJEjrR7znDlz5J577jGdo/Rvf2uP/euvv8q4cePMybRKT3LQanidG3rixIlmHunbb7/dHHvChAlmmyNHjpj51R944AFzvHd/mi+fPD9W7nx3ujTo1M3qMc+c8ITsX7NUhr7wvnj7BcjsiePM+tFf/hW6q7f/1VF6PfiMNO3Wzyyv/PI9WfHFe3Lzi5OlUmgtWfLRa3Lmzz3y6E9rxMPrr1byXzx4i6kqH/z0m5KRniY/Pf+w1GjSSoZN+NjqsaWnpUrE4f3m5y8f+re06jNUWvW9Sbx9/KRLq8bSr3aATJ482Tx/+npb+3yvW7dOunTpIq+99pr069dPvv/+e/O8bt261TynV8qa160k35/PP/+8ae9ueS7U0aNHpU6dOub9oi3fcXkE4wAAAAAAFMPFixdl9uzZcujQIbNcs2ZNGTRokFSuXNneQwMAAEA+82xfSbBdEvNsFyXc1tsKmmfbUWnFrAaA9913X671Ok2RdmiaNm3aJfusWLFCunbtaoLA8PDw7FbSGqRrcK0nqN50003y3nvvib+/f/Z+Oh2Shsw6H7l2eXrooYdMCFnYcfPSFtgaPn7++efSq1cvq4/95ZdfmjA0Zxx37NgxGT16tLlfPz8/ufPOO02Qm7MqX2979NFHTZV69bAa0u7OR6TNwH9n375l9ncmkH51a2SBz3FaSrLMf/s52b7oV0lPTZUGHbvKoHGvS0CVatnbjGsdLEOffy/72DrOpVNel42/fC3JcReldqsOMmjcRAmu/U+77sTYGJn9+lOyd9UicXF1lWbd+suAsRPEy9e/wOPmFXP6uEzsf2mF+VVtOsnaVSukuq+HCYP1+dMA2NrnW+nc9M8884zZr379+ibI7tu3b/bt+R3XGpd73Urq/akaNWpkxq3Te1loV4WVK1eak7VhHYJxAAAAAACKST9a//HHH7Jo0SJJTU01X4xo9bh+2Uf1OAAAgH3n2bZsa4s4xJbzbJd38+bNkyeeeMJUyNr7efniiy9M1a+G0JZ21vn54IMPzEmx+nd/aft8X4xEJmWI5V285KPX5cjWdTLy01lS1kSfOiZvDbnGVJlXqWX9/Nd62kdVHzcZ3sj6FvdXQgNtPclEw3FHsGDBAhkzZowJ0C0hvH7u1NBfK887d+5s7yE6DOYYBwAAAACgmPRLFW0FWbduXfNF2eHDh2Xx4sWmXaJWj1eqVMneQwQAALA75tlGTtrm+s8//5RTp06Zrkv2pPN5azBeWCiutLpd54yOi4uTgIAAKU1tg31k/vH47OUD65bJwCdfk7JI27e3H3J7kUJxlfX34yxJeoKMVnavWbNGHEVCQoI5eSPn/z/Hjx+Xp59+mlC8iKgYBwAAAADAhvRjts5fp8G4pXq8R48e0r59e6dqfQkAAMof5tkG7CctM0ve3xktqZnOG+t5ubrIg80riYcr/0ZRMgjGAQAAAAAoAVpJotXjOr+c0vkItXo8KKhk2wICAAA4yjzb1lRoO/s820BRrDqdIOvPJWW3U3c2nar5yPWhfvYeBpwYwTgAAAAAACVEP3Jv3rxZlixZYr6E1taMWj3erl07vtAFAJRrGrTq78bSbkXsDBx5nm29Tbex93zSgCNXjU/dGyOxqZlOFY7rJ6NAL1e5u1GQuFMtjhJEMA4AAAAAQAmLiYmRWbNmybFjx8xyeHi4qR4PDAyUsiwjK0tiUzLNF3DpWVmSkSXi5iLi7uJi2htW9HIVNwJ+AMDfMjMzCw089fYxY8bIypUrZdu2bXLdddfJsmXLyt2czcyzDaA4TiWkyTcHYsXZ3N6gooT5FT7HO1BcBOMAAAAAAJQC/fi9adMmWbp0qamQ0zagN954o7Rp06ZMVI9rCB6VlCFnk9LlXGK6nE5Ik8jkDBOGF0RD8mBvNwn185Bqvu4S4uMuVXzcCMsBwEEkJCTI+fPnJSoqygS1Ou1HaGhoif4uvP/++6VFixayYsUKiY2NlR9//NHhqsaZZxuAvS0/lSCbIpynpXqHqj7SNYwW6ih5BOMAAAAAAJSi6OhoUz1+/Phxs1ynTh0ZMGCA3arHzySkyZaoZNkbk5IdgmutX2YRjpFzew3LGwd5SZtgb6nuS8UHAJS1qm2L7du3y+OPPy67du0yy/p7SH8nvfrqqya4LqpTp06ZY2qb7169epmANj8aDGsw+8wzz8iaNWvkhx9+kGrVqklpYp5tAI7OWVqq00IdpY1gHAAAAACAUqYfxTds2GDax2qAoF9u9+zZU1q3bl0qX3LrF2kahG+OTJKIpAzzhZQtvxywHK+aj5u0CfYxQbm2XgcAlB1//vmn7Nu3z4TgNWrUkNOnT5sTtRo1aiRTpkyx6oStxMREOXfunCxevFjWrl0rO3bskIEDB8rYsWPF39+/0H01gJ83b558/fXXJpC/0nm2ryTYtvU821cSbDPPNgBbtFT/9kCswwfj/6GFOkoRE4EAAAAAAFDKNPy+5pprpH79+qZ6/MSJEzJ37lzZu3evCSUqVqxYYoH4+rOJsjkyWVIzs8wXUcrWX6ZZjqeh+/zj8bL0ZIK0DfaWjiG+BOQAYEMa8mqFuJ/fP+1nf/rpJxN0d+jQodCTrfR3kF4satasaeb83r9/vwm8CwvG9XYNtfV32G+//WbC3n79+sl7771njlHY/Voq2nXM+nN8fLxZr0F1fvvp8TW0zxts23OebUuwzTzbAOxJw+RB4QEy82icOKpBVwUQiqNU8ZsbAAAAAAA7qVy5stx1113Z1eOHDh2Sjz76yLSgbdWqlU2rx7WiZM7RuFztFku6usRyfA3h159Lkj0xKTIgnC+/AMBW+vbta8LdqVOnSnh4uKxatUpGjBghb775pjkByxqRkZGmDbr+Dtq5c6f5vVS9evUCt3/iiSdMAB4UFCS9e/eWr776Snr06FHksecNxgtiGVtBmGcbQHnWKMhL+mRmyYLjhf9fWhb1qeUvjQLzn3YDKCkE4wAAAAAA2JEGGh07djRVezNnzjQBwOzZs031eP/+/aVChQrFrhJffSZRNkYk2bxlelHo/Woo/82BWGlf1Ueuq071OAAUl1aHd+3aVSZMmCCvvfaajB8/XoYNGyYjR4687L5ace3m5mb2/eyzz0xA3Lx5c6lbt26hYXFAQIAJnrVyW39nrVixQiIiIkyYXqVKFRPQ6zaXY2m1frlgXCvfmzVrxjzbAFCAlpW9zbUjheMailvGDZQm5hgHAAAAAKCM0Mq59evXm7axGlho8NCnTx8z/+uVfPGfX5V4WRHo6Ur1OAAUg6X1+PLly00gHhsbK2FhYfLWW2+Z3xuWluWXk5KSYn7naHt0nRt89+7d8s4775iTtvI7hm6vgfrx48dNtxOdX3zTpk0mqK5Vq5a0b9/eVK1fddVV+bZHtxxTW7G//PLL5j6HDBli8+cHAMqbfTEpMuvvtupl7W9/5ZKjfTqV4rAXgnEAAAAAAMoYbWur1eM6p6pq0KCBqR63pgLP4b4YCw8wLSABoDzSQFqD5pxzZ+d3adq0qQmd84bUlqpvDbIfe+wxefLJJ+XVV1+1OhS3sGx/9uxZGTRokJnS48UXX8w+vjX0d9bChQvlwoULMnDgQKlXr16+28XFxZltNBifNGmSdOvWTdq1a2fmOL/xxhsLnGscAHB5nBgLFI5W6gAAAAAAlDHBwcFy9913y7p160yL2gMHDsiHH35oqse1ze3lAoPt55PLfCtFyxd1M4/GmXkRaaUIwBFpiGtNsJ3fRbdPS0uz6n4qV65sguO8NLTWY2mVt9q6dav5vXHDDTdIenq6mUPbmkDcEqJv2LBBzp8/L1WrVjXL+f2+0cryc+fOmfvVgDsmJkaio6NNS3S9zdfXt9D70q4ogwcPNmPTduoakH/zzTfy0EMPmWAcAHDlNHS+u3FQmZhKSVnuv0NVH7mWqZRQBlAxDgAAAABAGabztmr1+JkzZ8xyw4YNTfW4ZW5WRwzF88M8gwDsQb8a1XD6SoNtDcVtQefKtsybnXcubb1o9XVoaGiuKnBLZfUnn3wib7/9trn8+uuv8scff8iCBQvMSVaFVY7v379f5syZY1qe6/2eOHFCfvjhB6lYsaJ88MEH5v7yo1XeY8aMEQ8PD3P/Oj4/Pz+zn04B0qRJE3n00Uelbdu2+e6vgb1lupC8ilrpDgAo29XjVImjrCEYBwAAAACgjNMAYe3atbJy5UoTGmiA0bdvX9NaN2c1n7ZP1wpsRzWYtuoAroAGrVcabOu1Lb4e1ernwoLtgi66vQbEVxoG7927V2677Tbp0aOHTJw4UQ4fPizDhw83vytmzZollSpVKnBfbZv+xhtvmIptfR5CQkKkd+/eMnr0aKlWrVqB++nzps9ZQZXhRaHHsVz09xmhOADYVlpmlqw/myhbIpMlJTOrxCvILcf3cnWRNsHe0jGEKnGULQTjAAAAAAA4CG1dq9XjGmaoxo0bS79+/UylnlaEfHsgtszNJVgU+pXZfxpUpKIEKKfzbF9psK37F5cGssUJti/XsrykvPDCCzJ79mxZv369GYM+jh07dsjUqVNNwN2oUSNTEa+hs+VEKmsC6KLM860hvOUrZsu1tnhnnnAAKFsB+d6YFNkSmSTnkjJsHpDrb5VMEanm4yZtg33Mya4E4iiLCMYBAAAAAHAgGgCtXr3aXDSM0Iq9Xn36yjqX6nZtk2gL+tVZRU9XMy8iX6QBzj/PtmVba+fZvpycYbXlZw2tCwu7LbdpqFxeg1yqtgGgfDmTkCZbo5JlT0yKZGTlDratlXN7NxeRJkFe0jrYW6r7coIryjaCcQAAAAAAHJBWjWv1uFaRuzXpJO51W2kZoDiDDlV9pGuYn72HAZQbjjLPdmHhtu5bnoPtvI9d18XHx8v48ePl1KlTEhMTI7GxsRIXF2eu9XnTucl79eplt3EDAOwrMytLopIz5GxiurmcTkiTyOSM7LA8PxqCB3u7Saifh4T4uptLFW83cS2nv4PheAjGAQAAAABw4OrxeWs3y27/Ok4XCN1OS3WgSMrzPNvIn56w8PTTT5vXpXLlyma+8aCgIAkMDDTXDRs2NFNxAACQMyy/kJJpWq9nZGVJepaIu4sG4i6mo1OglyshOBwawTgAAAAAAA5Kv7CaujdGYlMzJMs0IncOtFRHecQ82wAAAEDJ4q9VAAAAAAAc1PqziX/PK+5c4bGewX8hNdM8vutDqWaEY2CebQAAAKBsIxgHAAAAAMBBq8U3RyabENmW4mOiZOlHr8u+NUsk/nyk+FSoKNXrN5VuIx+X8FYdZOPPX8u2hT/L6X07JCUhXp5beVB8AipKSdgSmSwdQ3ypGkepYJ5tAAAAwLkRjAMAAAAA4ID2xqRIaqbtZ0eb9vhwyUhLk5tfmCyVwmpLfHSkHNq4ShJjY8ztqcmJ0qBTN3NZ9P7LUpJSMrNkX0yKNK/sXaL3A+fBPNsAAAAACkIwDgAAAACAA9ocmWQaqNsyGk+Ki5Wjf/wu9346U+q06WzWBYXWlJrNWmdvc+1to8z14c1rpaS5/P04CcbLD+bZBgAAAFBS+EsdAAAAAAAHcyYhTSKSih8A5uXp4yeevn6y57cFUqt5W3H39BJ70tD/XFKGebzV/TzsOhZYh3m2AQAAAJRVBOMAAAAAADiYLVHJNq8WV27u7nLzC+/LLy89Jht+/krCGjWXq1p3kha9hkj1Bk3FHrSp9NaoZOlHMF4qmGcbAAAAgLMiGAcAAAAAwIFkZGWZ+cVtP7v4X5p1HyANr73RtFQ/vnOLHFi7TFZ9PVn+9ewkaTPw31LaMkVkT0yK9KnlL66EnVZhnm0AAAAAuBTBOAAAAAAADiQqKUMySioV/5uHl7fUv+YGc+l+7xj5+cVHZOmUiXYJxpU+3qjkDKnqUz6+xmCebQAAAACwPT6lAAAAAADgQM4mpZf6fVat01D2rFgg9nQ2Md1hgvGyMM+2thK/3JzazLMNAAAAoDxxjE+UAAAAAADAOJeYbubd1hbjtpZwIVqmj71b2g66VULqNxEvP385tWebrPrqfWnSpbfZJi7qnMSdj5DzJw6b5bN/7jHbBYbUEN+KQSU2z7gG4y0qS6lw5Hm2LdsyzzYAAAAA5EYwDgAAAACAAzmdkFYiobjy8vWTms1by5ppUyT65FHJSE+XwJBQaTfkduk64hGzzYafvpJln7yRvc8n9ww010Off6/EWq1n/v24i4J5tgEAAAAAOblk2eKTHgAAAAAAKHEZWVny1vbzklkOP8m7Spb08YiQ1BTm2QYAAAAAFB2f0AAAAAAAcBCxKZnlMhRXmeIivy5cIlkJsVbvwzzbAAAAAAALgnEAAAAAABxEWnlNxf9WvUZNCZAQ5tkGAAAAABQZwTgAAAAAAA4ivZzPhtZvwEAJ9fOw9zAAAAAAAA6IYBwAAAAAgDIiKytLUlNTJSUlxcyTrdc5fz6X5iriVVPKq/TyfV4AAAAAAKAYCMYBAAAAAHZz/vx5ady4sWzcuFHCw8PFkWVmZmYH2EuXLpVx48bJ7NmzJT09PXt9zrA7b+htuS6MS1A18byu/Abj7nRFz/bUU09JQkKCvP/++9nr9uzZIz179pT9+/eLn5+fXccHAAAAAGWNS5aejg4AAAAAgB089thjEhcXJ59++mn2uocffljWrl0ru3btMqH5tm3bLtlvx44d8sADD8imTZskODhYHnroIRk7dmyh95XfXNPfffed3HLLLSa81lB62bJl8swzz8iBAwekWrVqcvfdd0uvXr1yhdda0Z1f0J2WlpZ93I8//lg6duwoLVq0yF535MgRWbRokURGRkqFChXk+uuvl6uvvrrAseoc2XriwC+//CJHjx41+/QaOERaPPxarm13LpklSz56TWJOn5DKtepI74eflUbX3ihFkRgbI7MnjpN9qxaJi4urNOveX/o/8Yp4+foXuE9aSrLMf/s52b54pmSkpkj9jl1l0LiJElC5avY2F86clJmvPiGHN68VTx8/ad3/Fun10DPi5m79efpHtqyTVV9/IKf2bpe4qHPy66+/yuDBgwvdZ8WKFdK1a9dL1p85c0ZCQkKylz/44AN544035OzZs9KyZUsTMrdv316K4vjx4zJ69Gj57bffxN/fX+6880559dVXxb2QxxgdHW3es3PmzBFXV1e56aab5N133zX7W/sej4qKkjp16ph/H3ptMXToUPNYnn322SI9DgAAAABwdlSMAwAAAADsIjExUaZOnWrC4rxGjBghGzZsMOFgXhcvXjRVsT169JCPPvpItm7dKqNGjTIB4//93/8VWomt2zVq1Mgsa8B96NAhefnll021d0xMjHz44YfStm1buffee+Xw4cPywgsvyMGDB6VevXpWP66TJ0+aY1177bUm6NSAOzY21oSl/fr1k4EDB5rHpUFo3759pXv37mYbLy8vc9GfNVTVEwYaNGhgHufMmTNl586d5nlJDmsi7W+6w9zXse0b5fun75NeDz4jja7rKdsW/izfPnanPDh9mYTUa2z1mH8YP8qEziM+/Eky09Pkp+cfll9fHiPDJnxc4D7z3npW9q1ZIre9PlW8/SvIrNefkmmP3yWjvphvbs/MyJAv/3urCcpHfTHPHP/HZx80obiG49ZKTU6U6g2aSttBt8q3j98lRaGV03pCgUXVqv+E9j/88IM5MWPKlCnSoUMHeeedd8xJELpPzu0Kk5GRYV5TDdvXrVtngvc77rhDPDw8ZMKECQXud9ttt5ltlyxZYk6oGD58uIwcOVKmT59+yXtcx2d57QMDA812qkqVKma8+m9Aw30LPZa+f7VjQWHhPAAAAACUN1SMAwAAAADsYsaMGaYiVoPIvGG2XjTwW7VqlQksc1ZpL1682LQof/rpp00wqTRg3Ldvn6mqLcjzzz9vqsO1Cj0/egwNwZ988snsoFor2fV+X3rppVzBdc7rvD//97//lXPnzsmPP/6YfWw95rx580wVvMWwYcPkwoULsnDhwnzHo49//PjxpprZ09PTrBv75JPy5Yxf5LFf1pvl6U/eI6lJiXLXe38FqurDO3pL9YbNZMj4N616HSIOH5BJQzvLA98ukRpNWpl1+9cuk68e/rc8tXCHVAj+p8LaIjnuorzcvZHcMmGKNO8x8K/jHPlTJt3USUZ/uUBqtWgr+9cula/+e5uMW7Qzu4p8w09fyoL3XpRnlu0Td4+/HpO13FxExl4dXKSKcT1BQcPk/GgY3q5dO5k8ebJZ1pMjatasad5D2qbcGgsWLJD+/fvL6dOnTYcBpUG2vt7aGcDyuuW0d+9eadKkiakE15MwlL4H9CQJPakiNDQ039dex6QnSOj73OLrr7822504cSJ7nf5b0ZMB9P2mJ10AAAAAAP7CqcMAAAAAgCLR86u1yjW/MLugubTz20bbSGtomXOO5Jy09bjOoawV4XmDxVq1amWH4qp+/fqm/boG00FBQbnCaw0W9VotX77cVKhrAKqVvbfffru5TS/aRl3D6kcffTRXS/NHHnnEhJ/WWr16tdx666251q1fv95U/+ak1b567ILoPtpuPWe42qd3b3lj4kRJunhBfCoEyvGdm+Xa20bl2k9bmu9ZscDq8R7fsUm8Aypmh+KqXocu4uLqKid2bpGm3fpdso+2Nc9ITzPbWVS9qr4EhtSQ4zs2m2Bcr7VqPWdrdR3bzAlPSMShfRLa6J8289YI9naTomrVqpV5rzVr1sycGNG5c+fs8HjLli2mqtpCOw7oa6TPu7V02+bNm2eH4pbXVVur7969O99W+bqPvu8tobjS+9X71y4JQ4YMyfe11+O+/vrrJuzX97jStu8apmur/fDwcLNO99HHre9DgnEAAAAA+AfBOAAAAACUI1oVm7P6uqAwu7C5tPWixykurZYOCAgwbafzq8DWylithO3SpUuuoHvp0qVSu3ZtefDBB7O31znBv/zySxk0aFCBFeEvvviidOvWTXx9fU3Vuc4lriGizmmutDo3Z8CpdFnbWiclJYmPj49Vj+vYsWOm6jenKzm27nPVVVddso+Kj4owwbhe++cInpV/5WCJPx8h1oo7HyH+larkWqftzn0qBJnbCtrHzcNTfAIqXnLfln3idGyVgnPf/vdyQcctiKuIhPp5WL199erVTeW2hs/6fv3ss8/khhtuMMFz69atzfzcemJFfq9JzorsyynodbXcVtA+eVu1a8vzSpUqZe9T2Guvt1mCccv7TN9zlmDcsl7XAQAAAAD+QTAOAAAAAA4iPT292FXaGnbbilZTW4LpvC3GLVXahbUcX7Nmjan01pbo+dGKW60O10AzJw2R/fz8pHLlyrnGcjnPPvts9s9ayavV6Do3syUYtxUNui0V6iWlvM2JpqdhhPha/xVGw4YNzcWiU6dOZj75SZMmyTfffCPOwnJCRWJi4iXr864DAAAAgPKOYBwAAAAASqn1uDVV2oUF2zlbhxeXm5tbgfNlFxZm59xeK72tCaQLolWzWjVeVCEhIWYO75wsy3qbtXSOaZ07XJ9ffUwFHVfna7a2WlxVqVLFtLu2ZsyFHbuwxxlQ5a+KY/8qVS+pDo8/H3lJFXlhtNV5fHRUrnUZ6emSdDEmVxv0vPtkpKVKUlxsrqpxvW/LPjrGk7tzt8GPj47M3r+oihKM50fbjuvJGJbXSP8N5Pf8FuU9pNtu3LjxkmNYbiton4iIiEtOeomOjs7ex9r3uO6jgoNzV+br+rp161r9OAAAAACgPCAYBwAAAIBCaMvw4lZp60XDcVvRauzCwmtrgm1t3WxvWrX97bffFnm/jh07yvjx483JBhrOqyVLlpgKYUuLaWts27bNbK/Ph+W48+fPz7WNHlfXF/Vx7dmz55IxF/XYhT1O/4qBkpElUqt5Wzm0cXWuecYPblhp5vi2Vq0W7SQ5LlZO7dkuYU1amnWHNq2WrMxMqdm8Tb77hDVuKW7uHnJo4ypp1n2AWRd59KBcOHsy+771+repk0wYbmmhfvD3leLlHyBV6/xTzW0NNxeRKlcwx3je11tbrFv+DbVp08bMKz948ODsf+u6rC36raWv0SuvvGKCbkt7dH2N9ISHJk2aFLiPnhCic5zrGNTy5cvN/evJGkV5j+/atcvc3rRp01z3oeuHDh1axGcIAAAAAJyb/b8JAQAAAIASolWYxa3S1mDKVrS6ujhhtqVFuaurzrjs+Hr16iXjxo0z1dU5w76DBw9KfHy8mUtZ25JroKk0aNTHf+utt8oLL7wgd999tzz55JMmBHz33XdNm2yLX3/91RzbMl/0nDlzTMXtNddcY55HDRknTJggjz/+ePY+o0aNksmTJ8vYsWNlxIgRJqycMWOGzJs3r8iP66uvvsq1zppj6+06bg1nVWGPMzTIS3ZHp0jnW0fKJ/cOktXffCgNr71Rdiz6VU7t2SZDnnnL6vFWrdNAGnTqJr+8/KgMfvpNyUhPk9mvPyUteg2RCsF/VSfHRpyRqaP+JTe/+IHUbNZavAMqSNvBt8m8t54zc5F7+wXI7InjTMhuCcbrX9PVBOAznrlf+jzyPzPn+OIPX5WON48Qd8+/TkawRlpivPjFnpId4meWjxw5Yt4TOid3rVq1zDp9rU+dOiVff/21WX7nnXfMHN0aGOu/Y51jXJ9znVve4rHHHpM777zTzEOu1eS6j7bXHz58uNVj69mzp3lf3n777TJx4kTzntW56x944IHsEy60ovyOO+4wr2tYWJg0btxYevfuLffee6+ZB13/j9EwftiwYdlzhlvzHlerV6+W6667LlfXgaNHj5rnokePHlY/DgAAAAAoDwjGAQAAAJQ5Wl2tc2FfaZht+dmWrce1wvpKqrRzritu63Fn07x5c2ndurUJiO+7777s9ffcc4+sXLkyVwW2JRANDw+XihUrmoBTw0etuNW22M8995yMHDkye5/Y2FjZv39/9rI+9x988IE8+uij5v1Vr149efvtt004aaFBqgbVuo2GkDVq1DCBqgbdFl9++aUJTgvrAHDbbbeZAFzv3zLPtTXHjoqKMvNgWxT2OM8kpMmu6BSp3bK9DHtligmcF01+RarUqiP/efsrCanXOPs4S6dMlC1zvpcn5+Vua57TLa9MMWH4Z6P+JS6urtKsW38ZMHZC9u2Z6WmmIjwtOSl7Xb8xL5n387Qnhkt6aqo06NhVBo17Pft2Vzc3ufOdaTLz1Sfko7v6iqe3r7QecIv0GP1U9jYxp4/LxP5t5N5PZkqdtp3zHduJPdvluZF/VXVbAm2loba+HurMmTNy/Pjx7G30/48xY8aYgNjX11datGghS5cula5du/7zmG+5RSIjI81zqoF2q1atZOHChVKtWrXsbe666y4TNK9YsSLfsWk79rlz58ro0aNNlbefn58Z14svvpi9jc71re+FnCfZTJs2zYTh3bt3Nye63HTTTfLee+9l327Ne1x9//338vzzz+da991335nAvnbt2vmOGQAAAADKK5csW/bzA+B0MrKyJDYlU9IysyQ9K8u0a9Q2hu4uLuLh6iIVvVzFjS93AQBADtoOuLhV2nptSwWF19aE2ZafNQCD7WlY/MQTT5iKWEeohP/f//5nQvuCglILfUwXL16Ujz/+uMTG8vm+GIlMypDLfaif8dwDJsC++YXJUtYc2rRGvn38Lhk7Z7P4VAi85Hb9pFHVx02GN7K+Rb4tdenSxYTpecPnsmDBggUm/N+xY0f21Ah6QkD9+vVl+vTp0rlz/icaAAAAAEB5RcU4gFwheFRShpxNSpdzielyOiFNIpMzTBheEA3Jg73dJNTPQ6r5ukuIj7tU8XEjLAcAwAHpObPaetyaMLuwYNuWrcc1KLW2SruwbajSLrv69esnf/75p6nsrVmzppR1GkZqy/PL0fmhP/zwQ3OiSEkF/m2DfWT+8fjL/rs+snmd3Pf5XCmL9q9ZKl1HPJJvKK6y/n6c9qBdB7SCv6it9EuLtn3/4osvskNxpVXzTz/9NKE4AAAAAOSDinEApg3jlqhk2RuTkh2C61d3mUU4Rs7tNSxvHOQlbYK9pbqvR0kMGQAA5KF/1l8uwLamSltDPFvR1tUFzZF9uTDb8rMGPoTaQP60q9P7O6MlNdN5P9Z7ubrIg80rmW5VAAAAAAAUB8E4UI6/RNMgfHNkkkQkZZgWhbb8z8ByvGo+btIm2McE5XyZBQCwiIiIMPOiLlq0yMzdqnOn6jyqQ4cOdYhWyram82AXp0pbr7V9ri0VVIldlCptWo8DJW/V6QRZfy7Jpn/LlyWdqvnI9aF+9h4GAAAAAMAJ0EodKIeB+PqzibI5MtlUlliialt/kWY5nobu2t5x6ckEaRvsLR1DfAnIAaCM0vbXOh9uYmKiBAQESGBg/m1tLSyVxVcSZGsgvnr1arn66qvlP//5jxw7dkzuueceOX/+vNx3330OE47rOab6vBW3Slvbl9uKhtHWth4v6Get6KZKG3AM+vf1npgUiU3NdKpwXP8HCvRylU4hvvYeCgAAAADASVAxDpQjpxLSZM7ROLt9aaZfblX0dJUB4QES5keLdQAoadbOa3vw4EEZN26crFy5UpKSkiQoKEg6duwozz//vDRu3LhExrZv3z4zvrp165ogVo0aNcpUj3/66aelMs+w3r9WWRenSluvbfnntLYeL6hK+3Jhds7W4wDK39/53xyIFWdze4OKfG4AAAAAANgM35oB5aRKfPWZRNkYkWTzlulFoferobx+ade+qo9cV53qcQAoSdZWXWtl8L/+9S8TjterV8+0OR8yZIg8++yz8tFHH0lwcPAl+2goPHz4cBMs6749evSQatWqmds0KL5ctXGjRo2yf9aKaw2EK1eubIJxbSt+OVphbU2YbWkxnl/4bcvW4/p4r6RKO+82jlIpD6Bs0fBY/77eFOE8LdU7VPUhFAcAAAAA2BQV44CTs3eVeGECqR4HAJuxtOP28/tnHtbFixdLhQoVpEOHDkVui/3iiy/K0qVL5bPPPpMGDRrkG3brHOFr166Vbdu2ydatW02ArgF5t27dpG3btibo1nbshc0zbalqj4+Pl/bt25tA/pVXXsl32yVLlpj70sdqTXhuLa2wvlxV9uWCbQ32aT0OwN4nw07dG1Mm/+6/khbqdzcKEndOogUAAAAA2BAV44AT2xeTIrOOxpmfy+KXY/ql3bcHYmVQeIA0CvqrjS4A4MrccsstptL7888/N9XYf/zxh9x2223yyCOPyDXXXGPVMTRs1jnGT548KatWrZKuXbtK7dq1zW35hb7Dhg2Tvn37mlBb5yXfvXu3CePHjBkj586dk5tuukneffddCQ0NLfA+LRXSI0eONMH6/fffX2CArsG/3k9OOhd2cau0aT0OwBloJyY96VT/vnZ0/WsHEIoDAAAAAGyOinHASW0/nywLjseLo+hTy19aVva29zAAwGHFxsZK7969JTw8XKZMmSK33367CX2/++67ywa/GohrVfczzzwjEyZMMOt0jvF33nlH2rVrZ9X9a2j9888/m8uaNWskICBA7rvvPtNuXecsL8zYsWNl4cKF8vXXX0urVq3y3Ub/ZNXHqNXilmBbQ3FajwPApSfHzvz75FhHNPiqAGkUyEmzAAAAAADbIxgHnJCjheIWhOMAcCn9Uy3nHNkacmvQnLOC29LmXANpnSf8/PnzZr7vl19+WTp37pwdfF+OVotrRbbe19NPPy2HDh2SDz74wLRFz6+VelRUlMydOze7pXqNGjVk0KBBcvPNN0ubNm2senwTJ06Ujz/+2Mxl3rNnT6vmJwcAFI7PAwAAAAAAXIpgHHAyDl8hQlt1AE5EA2kNs/ViCbZz/pxzXUHb6CWnZs2amRbl+d2Xht9Tp06Ve++9V0aPHm1Cbcsc3tayBNOnT582rdJ1fvI33ngj33Bd12vrdg3Ce/XqZQJ0reS21rRp0+Stt94yIfzQoUPNWPXx6niLchwAgOOH44TiAAAAAICSxoSKgBM5lZCWPae4o9LxB3i6Spifh72HAqAc03BYW4NfLsy+XLCtx7AVDYu1hbiHR/7/P2porZXlO3bsMMv79++X5cuXS7du3cw4rJ1H21KtfezYMdO6XFuiF0TDbD1+zZo1zfG1Uj0uLs7MOR4TE2PCdA3yw8LCLtn38OHD8tJLL8mBAwfk4YcfNkG+VqzrccaPH2/CcgDAldOQ2cvVJfvzQVk8I97SH2QQ7dMBAAAAAKWAYBxwEmmZWTLHwUNxC30cdzcOEg9XWukCuLJQuzhhtuVnrV62FQ2ztQLaMje25dpyyblc0M8aGF+uxfiMGTNk3rx58ssvv8iSJUvk0UcflWXLlkmVKlUKrRw/cuSILFiwwITYgYGBcvLkSfnkk0/Ex8fHhN8qv1bsv//+u9x9991mOw3ELScC6OPV16FBgwamVboG43lbpGs7+EmTJpmfdX8N4CtVqmTuv2LFisV6vgEAf9FOTHrSqf59HZuaWebC8YqerjIgPICTYgEAAAAApYJW6oCTWH4qQTZFJJW5L7uuVIeqPtI1zM/ewwBQyrTC+HJh9uWCba2athUNcvMLsPXa09Mz36A7v5+L0sr8Sh08eFBuvfVW0/r8/fffl6NHj8pdd91lAvHZs2ebwLkgZ8+elQkTJsjMmTNN1bYG1D169JCxY8dKvXr1Cpz3+8SJE+Z+dT5zS6Dt58f/3QBQFk+iXX0mUTZGJJkqbXt+ZrDcv/69f211X06GBQAAAACUGoJxwElaqH9zIFacze0NKlI9AjgI/XMiLS2tWFXaeq3BuK1ohXNxqrQtbcsvV6VdVrz22mtmzu6NGzdmh/E7d+6Ud955Rx555BFp3ry5eY0sj8dyrdvpzwVVlBcUil+O7qeXwk4KsGyTd0wAgJL73GDv6vFAqsQBAAAAAHZCMA44QfXH1L0xZbI1YnG4/N1akZbqQMnTQPRyldkFBds519vyTwqtxs4vsC5Klba1c2rjUpY28tZUul9pcA4AsN/nh/VnE2VLZLKkZGaVeAW55fg633mbYG/pGEKVOAAAAADAPgjGAQe36nSCrD/nPC3U8+pUzUeuD6UtL1AQndP5cmH25aq1tYrY1q3Hi1OlreF3abQed0b5hdS6LjEx0VSUnz59WmJiYiQ2Nta0TL9w4YI5geDdd9+Vnj172m3cAAD7BOR7Y1JkS2SSnEvKsHlArr/J9TSraj5u0jbYx8x3TiAOAAAAALAnSqkAB/8ya3NkcomE4vExUbL0o9dl35olEn8+UnwqVJTq9ZtKt5GPS3irDrkCly8fGiYH1i2X/7z1lTTt2tem49BKFqpK4Iz0347OhW1tmF3QbbZsPa4BaWHhtTXBtiO1HndG+T33uk5f24iICHPSQcOGDc184EFBQVKhQgUzn3i7du3sMl4AgP3o39ctKnuby5mENNkalSx7YlIkIyt3sG2tnNu7uYg0CfKS1sHeUt2XlukAAAAAgLKBYBxwYFrhkZpZMrXi0x4fLhlpaXLzC5OlUlhtiY+OlEMbV0libEyu7dZO+1hTFykp2t5xX0yKNK/sXWL3AVxJm+niVmnrtS0V1GLc2iptvdY5ueGc9PX9+OOP7T0MAEAZVd3PQ/r5eUifWv4SlZwhZxPTzeV0QppEJmdkh+X50RA82NtNQv08JMTX3VyqeLuJKyfKAQAAAADKGIJxwIFtjkwqkTkBk+Ji5egfv8u9n86UOm06m3VBoTWlZrPWubY7vX+nrP72Q3nw2yUyoWczKQkufz9OgnHYqkpbW49bE2YXFmzbsvW4tgy/kirtvNtQpQ0AAIpLw+yqPu7m0qLyX+sys7LkQkqm6VaVoX9LZYm4u2gg7mKqzgO9XAnBAQAAAAAOgWAccFDa7jAiyXYtlHPy9PETT18/2fPbAqnVvK24e3pdsk1qUqL88PQoGfTU6xJQpZqUFA39dc5DfbxayYLyHWpfrq24NVXaWu1tK9qeurhV2noMQm0AAFBWaehdyZuuMgAAAAAAx0cwDjioLVHJJVItrtzc3eXmF96XX156TDb8/JWENWouV7XuJC16DZHqDZqabea99azUatlOmtzQR0qazleocx5qe0c4Jp0H25owu7Bg29atx21RpU3rcQAAAAAAAAAAHAPBOOCAtIWhzi9eMrOL/6VZ9wHS8NobTUv14zu3yIG1y2TV15PlX89OEp+KQXJo02p56LvlUhq0vndPTIqZ85A2jaVfpa1tw680zLb8rO3Lbdl6PL+guijBts7HTZU2AAAAAAAAAADlh0uWph4AHMq5xHT5Yv+FUr/fn198RA7+vlKadO0r67//VFxctZb7L5kZGWY5/OprZOSns0rk/kc0CjTzHcI62jI8NTX1iqu0Lde2/DXh4eFRrCpt/VlbjwMAAAAAAAAAABQF6QLggM4m2a76tiiq1mkoe1YskBuGPyzthvwn123v/t/10m/MS9L4+l4ldv9nE9PLTTCuFdbWhNl6XVD4rettRaurLzd3tjXBtlZ7AwAAAAAAAAAAlLbykTABTlgx7vp3i/GSkHAhWqaPvVvaDrpVQuo3ES8/fzm1Z5us+up9adKltwRUqWYueQWG1JBKYbVLZEyufwfjLSpLmabV1RpIXy7MvlzrcZ2T21Z0HuziVmlrpTetxwEAAAAAAAAAgKMiGAcc0OmEtBILxZWXr5/UbN5a1kybItEnj0pGeroEhoRKuyG3S9cRj4g9ZP79uEv0PjIzrQqzC6vStnXrcZ0L29oq7YK2ofU4AAAAAAAAAAAo75hjHHAwGVlZ8tb285JZDv/lurmIjGlZWVzzVC7rf2OW1uPFqdJOS7Nd8K7V1cWt0tZQnNbjAAAAAAAAAAAAxUcZIeBgYlMyy2UorjKyRKb9Mlsy4y9cEmxrtbetaIV1cau0aT0OAAAAAAAAAABQdhCMAw4mrbym4n87cvyEZF08X+DtBVVlW1ulrdc6JzcAAAAAAAAAAACcB8E44GDSy/nsB52vu16qebsWGH5TpQ0AAAAAAAAAAIC8CMYBB2wnXp7Vb9RYavl72HsYAAAAAAAAAAAAcCCu9h4AgKJxK2JBdFzUOZk6eqg816m2vHB9XSkNn9w7SOa8MT57+fV+rWXNtCmF7jOudbDs/m3+ZY/tTkE4AAAAAAAAAAAAioiKccDBPHbf3bLrVJTc/vbXVm2/ZtrHJhx/+Pvl4u1fQUrDf978UtzcS6aq241W6QAAAAAAAAAAACgignHAwbgWMRiOPnlEQhu3kCq1SqdaXPlWDCqxY3u4EowDAAAAAAAAAACgaAjGAQfjmaOXurYsD6nfRDw8vWXTzG/FzcNDOtx0l/QYNTa7hfmFMyfMz3/MnSGtB9wiN78wWZLiYmX+pP/J3hULJT0tRcIat5L+j78k1Rs0M9ueP3FE5r39nJzYuUVSkxIk+KoG0vuhZ6Rehy7Z971+xueydtoUiT132lSih1/dQW5744vscemxBjzxSvb2KYkJ8t24kbJ35SLxCaggN4x4RDrecneBj/PC2VMyf9Jz8uf6FeLi6irhV18jg8a+IoGtKpfAswoAAAAAAAAAAABnxhzjgIPRWNwrRzi+de4P4uHjK/d/vVD6/Pd/svzTN+XP31eY2x74drE06NRNmt84SJ5evEsGPD7BrJ8+9m5JiI6SuyZ/Lw9OWyphjVvIZ6NuksTYGHO7huENO/eQu6f8LA99t9wc46tH/iMXzpw0t5/cs03mvvG09Bj9lDz2y3oZPvl7CW/dsdBxr/56slRv0NQcr8vwh2Xum+Ozx5lXRlqafPHA/4mXr7/cN3WOjPp8nnj6+smXDw6T9LQ0mz2XAAAAAAAAAAAAKB+oGAcckLebS/ZZLdXrNZEe9z1hftZ26et/mCqHNq6S+tfcIP5BVcTd00s8vL0loEo1s83RP36XE7u3yjNL95rbVN9HX5Ddv82XXUvnSPub7jDV3pbqcdXz/nGy57f5smflQuk07B4TkGsY3/i6nuLl5y9BoTUltFGLQsdcu2V7uWH4f83PwbXryrFtG2XNtClmnHntWDxTsrIy5V/PvSMuf7eO/7/n35MXu9STFStWSM+ePW30TAIAAAAAAAAAAKA8IBgHHJBWjGf+/bO2Us9JA/D46KgC9z1zYLekJibIS10b5FqflpIs508eNT+nJMbLso/fkH2rl0hc1DnJzEg3t8eePWVu1zA7KKSmvDGgrdTv1M1UlDft2lc8fXwLvN9aLdrlWW4ra6d/UuAYtZ3789eGXzLGQ4cOFXgfAAAAAAAAAAAAQH4IxgEH5O32zywIru4euW7TCmutti6ItknX8PzeT2ZecptPQEVzPX/S83Jww0rp+8jzUrnmVeLu5S3Tx46Q9LRUc7tWiT84fZkc2bLWzAG+dMrrsuzjifLAt0uyj1EcOsbQxi3llpc/yrX+5roVpFHN6sU+PgAAAAAAAAAAAMoXgnHAAXm6uUiOacaLRFuex5+PEDd3dwkKrZXvNse2b5TWA4ZJ0279sivIY06fkKva/LON7l+vQxdz6X7f4/JCl3pyaONqada9f77HPL5zc57lLRJ8Vf0Cx6jt1P0rBYu3f8Bf9+ci0q5pZXH9u7U6AAAAAAAAAAAAYK1/yk4BOAyNhhsH/TU/eFFpkF2reVv55rE75MD63yTm9HEThC+a/Iqc3LPNbFOlZh3ZvXyunN6/U84c2CU/PD0qVxX63lWLZe13n5jbNTDfOneGZGVmSnB4vQLvV+9j5ZfvS+SxQ2Ye9F1LZ0vnf4/Md9tWfW4S38BK8s1jt8uRrevlwqljkr5vozzy3//KyZMnr+hxAwAAAAAAAAAAoPyiYhxwUG2qeF/Rftpq/a73v5dFH7wiPz//sCTEnBf/KlXlqqs7mgpt1W/Mi/LT8/+VKcP7mYC6y50PSXJCXPYxfAIqyO7l88w85OmpKVK5Zh0ZNuFjqVa3UYH3e91/7pdTe7fJsk/eFG9/f+n72ItmbvL86Fzl9302Wxa896JMe3y4qVgPCwuTnj26S4UKFa7ocQMAAAAAAAAAAKD8csnKysqy9yAAXJnP98VIZFKGZDl5dXxVHzcZ3ijI3kMBAAAAAAAAAACAg6KVOuDA2gb7OHUorrL+fpwAAAAAAAAAAADAlSIYBxyYzjPu6ao11c7Ly9VFGl3hfOoAAAAAAAAAAACAIhgHHJiHq4u0DfY27cadVZtgb/M4AQAAAAAAAAAAgCtFMA44uI4hvlLR09XpwnF9PEFertIpxNfeQwEAAAAAAAAAAICDIxgHHJxWUw8ID3C6ucb18fSvHSDuVIsDAAAAAAAAAACgmAjGAScQ5uch7av6OFXVeIeqPuZxAQAAAAAAAAAAAMVFMA44ieuqO0dLdUsLdX08AAAAAAAAAAAAgC0QjANO1lLdGdBCHQAAAAAAAAAAALZEMA44EW09PsjBw/FBVwXQQh0AAAAAAAAAAAA2RTAOOJlGQV7Sp5a/OCIdd6NAL3sPAwAAAAAAAAAAAE6GYBxwQi0reztcOK7j1XEDAAAAAAAAAAAAtuaSlZWVZfOjAigT9sWkyKyjcebnsvgP3SVH+3QqxQEAAAAAAAAAAFBSCMYBJ3cqIU3mHI2T2NTMMheOB3q6yoBw5hQHAAAAAAAAAABAySIYB8qBtMwsWX0mUTZGJJkqbXv+o7fcf4eqPnJtdV/xcLXUjQMAAAAAAAAAAAAlg2AcKEfKQvU4VeIAAAAAAAAAAAAobQTjQDmsHl9/NlG2RCZLSmZWiVeQW47v5eoibYK9pWMIVeIAAAAAAAAAAAAoXQTjQDkOyPfGpMiWyCQ5l5Rh84DcVUQyRaSaj5u0DfaRRkFeBOIAAAAAAAAAAACwC4JxAHImIU22RiXLnpgUycjKHWxbK+f2bi4iTYK8pHWwt1T3pWU6AAAAAAAAAAAA7ItgHEC2zKwsiUrOkLOJ6eZyOiFNIpMzssPy/GgIHuztJqF+HhLi624uVbzdxNWF6nAAAAAAAAAAAACUDQTjAC4bll9IyTSt1zOysiQ9S8TdRQNxF9MaPdDLlRAcAAAAAAAAAAAAZRrBOAAAAAAAAAAAAADAqem0wAAAAAAAAAAAAAAAOC2CcQAAAAAAAAAAAACAUyMYBwAAAAAAAAAAAAA4NYJxAAAAAAAAAAAAAIBTIxgHAAAAAAAAAAAAADg1gnEAAAAAAAAAAAAAgFMjGAcAAAAAAAAAAAAAODWCcQAAAAAAAAAAAACAUyMYBwAAAAAAAAAAAAA4NYJxAAAAAAAAAAAAAIBTIxgHAAAAAAAAAAAAADg1gnEAAAAAAAAAAAAAgFMjGAcAAAAAAAAAAAAAODWCcQAAAAAAAAAAAACAUyMYBwAAAAAAAAAAAAA4NYJxAAAAAAAAAAAAAIBTIxgHAAAAAAAAAAAAADg1gnEAAAAAAAAAAAAAgFMjGAcAAAAAAAAAAAAAODWCcQAAAAAAAAAAAACAUyMYBwAAAAAAAAAAAAA4NYJxAAAAAAAAAAAAAIBTIxgHAAAAAAAAAAAAADg1gnEAAAAAAAAAAAAAgFMjGAcAAAAAAAAAAAAAODWCcQAAAAAAAAAAAACAUyMYBwAAAAAAAAAAAAA4NYJxAAAAAAAAAAAAAIBTIxgHAAAAAAAAAAAAADg1gnEAAAAAAAAAAAAAgFMjGAcAAAAAAAAAAAAAODWCcQAAAAAAAAAAAACAUyMYBwAAAAAAAAAAAAA4NYJxAAAAAAAAAAAAAIBTIxgHAAAAAAAAAAAAADg1gnEAAAAAAAAAAAAAgFMjGAcAAAAAAAAAAAAAODWCcQAAAAAAAAAAAACAUyMYBwAAAAAAAAAAAAA4NYJxAAAAAAAAAAAAAIBTIxgHAAAAAAAAAAAAAIgz+3/4B1YEJJ1USwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 2000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Validation with CVXPY's integer solver:\n",
      "CVXPY integer optimizer objective: 9.0\n",
      "CVXPY integer optimizer solution: [-0. -0.  2.  1.]\n",
      "\n",
      "Continuous solution for comparison:\n",
      "Optimal continuous objective value: 11.499999988735462\n",
      "Optimal continuous solution: [4.41996831e-10 6.28249789e-09 2.00000000e+00 4.99999999e-01]\n"
     ]
    }
   ],
   "source": [
    "import cvxpy as cp\n",
    "import numpy as np\n",
    "from functions.BranchAndBoundSolver import BranchAndBoundSolver\n",
    "\n",
    "# Example using the Branch and Bound solver\n",
    "if __name__ == \"__main__\":\n",
    "    # Set up the problem data\n",
    "    c = np.array([-4, -2, 7, -5])  # Objective coefficients\n",
    "    A = np.array([\n",
    "        [1, 0, 5, 0],\n",
    "        [1, 1, -1, 0],\n",
    "        [6, -5, 0, 0],\n",
    "        [-1, 0, 2, -2],\n",
    "    ])\n",
    "    b = np.array([10, 1, 0, 3])\n",
    "    \n",
    "    # Create and run the solver\n",
    "    solver = BranchAndBoundSolver(c, A, b, integer_vars=[0, 1, 2, 3], maximize=True)\n",
    "    solution, objective = solver.solve(verbose=True)\n",
    "    \n",
    "    # Compare with CVXPY's integer solver (for validation)\n",
    "    print(\"\\nValidation with CVXPY's integer solver:\")\n",
    "    x = cp.Variable(4, integer=True)\n",
    "    objective_fn = cp.Maximize(c @ x)\n",
    "    constraints = [A @ x <= b, x >= 0]\n",
    "    int_prob = cp.Problem(objective_fn, constraints)\n",
    "    int_result = int_prob.solve()\n",
    "    \n",
    "    print(f\"CVXPY integer optimizer objective: {int_result}\")\n",
    "    print(f\"CVXPY integer optimizer solution: {x.value}\")\n",
    "    \n",
    "    # Compare with continuous solution\n",
    "    print(\"\\nContinuous solution for comparison:\")\n",
    "    x_cont = cp.Variable(4)\n",
    "    objective_cont = cp.Maximize(c @ x_cont)\n",
    "    constraints_cont = [A @ x_cont <= b, x_cont >= 0]\n",
    "    cont_prob = cp.Problem(objective_cont, constraints_cont)\n",
    "    cont_result = cont_prob.solve()\n",
    "    \n",
    "    print(f\"Optimal continuous objective value: {cont_result}\")\n",
    "    print(f\"Optimal continuous solution: {x_cont.value}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## BIP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step 1: Solving root relaxation (continuous problem)\n",
      "Root relaxation objective: 66.000000\n",
      "Root solution: [9.99999997e-01 9.99999997e-01 9.99999998e-01 1.99999992e-01\n",
      " 1.05312628e-08]\n",
      "\n",
      "Starting branch and bound process:\n",
      "\n",
      "Step 2: Exploring node S0\n",
      "  Branching on binary variable x_4 with value 0.200000\n",
      "  Creating two branches: x_4 = 0 and x_4 = 1\n",
      "  S1 relaxation objective: 65.833333\n",
      "  S1 solution: [9.99999999e-01 9.99999999e-01 9.99999999e-01 3.51358697e-11\n",
      " 1.66666668e-01]\n",
      "  S2 relaxation objective: 65.000000\n",
      "  S2 solution: [9.99999998e-01 2.46970164e-09 9.99999998e-01 1.00000000e+00\n",
      " 3.28711590e-10]\n",
      "  Found new best integer solution with objective 65.000000\n",
      "\n",
      "Step 3: Exploring node S1\n",
      "  Branching on binary variable x_5 with value 0.166667\n",
      "  Creating two branches: x_5 = 0 and x_5 = 1\n",
      "  S3 relaxation objective: 60.000000\n",
      "  S3 solution: [1.00000000e+00 1.00000000e+00 1.00000000e+00 3.96218586e-11\n",
      " 3.44760560e-11]\n",
      "  S4 relaxation objective: 63.333333\n",
      "  S4 solution: [ 9.99999985e-01  6.21791747e-10  6.66666678e-01 -4.26170484e-10\n",
      "  1.00000000e+00]\n",
      "\n",
      "Branch and bound completed!\n",
      "Nodes explored: 2\n",
      "Optimal objective: 65.000000\n",
      "Optimal solution: [9.99999998e-01 2.46970164e-09 9.99999998e-01 1.00000000e+00\n",
      " 3.28711590e-10]\n",
      "+--------+-------+--------------------------------+-------+--------------------------------+-------+-------+---------------------+\n",
      "| Node   |     z | x                              | z*    | x*                             |    UB | LB    | Z at end of stage   |\n",
      "+========+=======+================================+=======+================================+=======+=======+=====================+\n",
      "| S0     | 66    | (1.00, 1.00, 1.00, 0.20, 0.00) | -     | -                              | 66    | -     | {S0}                |\n",
      "+--------+-------+--------------------------------+-------+--------------------------------+-------+-------+---------------------+\n",
      "| S0     | 66    | (1.00, 1.00, 1.00, 0.20, 0.00) | 65.00 | (1.00, 0.00, 1.00, 1.00, 0.00) | 65.83 | 65.00 | {S1}                |\n",
      "+--------+-------+--------------------------------+-------+--------------------------------+-------+-------+---------------------+\n",
      "| S1     | 65.83 | (1.00, 1.00, 1.00, 0.00, 0.17) | 65.00 | (1.00, 0.00, 1.00, 1.00, 0.00) | 65    | 65.00 | ∅                   |\n",
      "+--------+-------+--------------------------------+-------+--------------------------------+-------+-------+---------------------+\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Validation with CVXPY's integer solver:\n",
      "CVXPY integer optimizer objective: 65.0\n",
      "CVXPY integer optimizer solution: [1. 0. 1. 1. 0.]\n",
      "\n",
      "Continuous solution for comparison:\n",
      "Optimal continuous objective value: 65.99999997918597\n",
      "Optimal continuous solution: [9.99999997e-01 9.99999997e-01 9.99999998e-01 1.99999992e-01\n",
      " 1.05312629e-08]\n"
     ]
    }
   ],
   "source": [
    "import cvxpy as cp\n",
    "import numpy as np\n",
    "from functions.BranchAndBoundSolver import BranchAndBoundSolver\n",
    "\n",
    "# Example using the Branch and Bound solver on the provided problem\n",
    "if __name__ == \"__main__\":\n",
    "    # Set up the problem data\n",
    "    c = np.array([15, 25, 20, 30, 35])  # Objective coefficients\n",
    "    A = np.array([\n",
    "        [10, 20, 15, 25, 30],  # Constraint coefficients\n",
    "    ])\n",
    "    b = np.array([50])  # Constraint right-hand side\n",
    "\n",
    "    # Create and run the solver\n",
    "    solver = BranchAndBoundSolver(c, A, b, \n",
    "                                  binary_vars=[0, 1, 2, 3, 4],  # Make all variables binary\n",
    "                                  maximize=True)\n",
    "    solution, objective = solver.solve(verbose=True)\n",
    "    \n",
    "    # Compare with CVXPY's integer solver (for validation)\n",
    "    print(\"\\nValidation with CVXPY's integer solver:\")\n",
    "    x_cvx = cp.Variable(5, boolean=True)  # Fix: Change dimension to 5 to match c\n",
    "    objective_fn = cp.Maximize(c @ x_cvx)\n",
    "    constraints = [A @ x_cvx <= b]\n",
    "    int_prob = cp.Problem(objective_fn, constraints)\n",
    "    int_result = int_prob.solve()\n",
    "    \n",
    "    print(f\"CVXPY integer optimizer objective: {int_result}\")\n",
    "    print(f\"CVXPY integer optimizer solution: {x_cvx.value}\")\n",
    "    \n",
    "    # Compare with continuous solution\n",
    "    print(\"\\nContinuous solution for comparison:\")\n",
    "    x_cont = cp.Variable(5)  # Fix: Change dimension to 5 to match c\n",
    "    objective_cont = cp.Maximize(c @ x_cont)\n",
    "    constraints_cont = [A @ x_cont <= b, x_cont >= 0, x_cont <= 1]  # Box constraints\n",
    "    cont_prob = cp.Problem(objective_cont, constraints_cont)\n",
    "    cont_result = cont_prob.solve()\n",
    "    \n",
    "    print(f\"Optimal continuous objective value: {cont_result}\")\n",
    "    print(f\"Optimal continuous solution: {x_cont.value}\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv (3.13.2)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}