diff --git a/Tools/Algorithms/calculate_stencil.ipynb b/Tools/Algorithms/calculate_stencil.ipynb index 131c2e5ee35..1d1dc68c4fe 100644 --- a/Tools/Algorithms/calculate_stencil.ipynb +++ b/Tools/Algorithms/calculate_stencil.ipynb @@ -10,102 +10,58 @@ }, { "cell_type": "code", - "execution_count": 92, + "execution_count": null, "id": "e0410e66-4a48-4c76-9d2c-9b26e3f9b6a1", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "E Stencil coefficients for M=8: [ 1.43221461e+00 -2.23341268e-01 7.56394169e-02 -3.17603545e-02\n", - " 1.41628551e-02 -6.07134562e-03 2.35126503e-03 -6.20850079e-04]\n", - "B Stencil coefficients for M=8: [ 1.00000000e+00 -5.41008543e-14 4.82554949e-14 -3.96439278e-14\n", - " 3.07204625e-14 -2.02832336e-14 1.25914929e-14 -5.05872550e-15]\n", - "[1.43221461e+00 1.20829534e-14 3.65001749e-15 1.25910520e-15\n", - " 4.35089459e-16 1.23146521e-16 2.96059369e-17 3.14071013e-18]\n", - "E Stencil coefficients for M=12: [ 1.44187941e+00 -2.32652752e-01 8.42402686e-02 -3.94170491e-02\n", - " 2.06191397e-02 -1.12972784e-02 6.24485948e-03 -3.37449645e-03\n", - " 1.73819001e-03 -8.12652625e-04 3.30620191e-04 -9.23012748e-05]\n", - "B Stencil coefficients for M=12: [ 1.00000000e+00 -3.18818801e-13 2.98172609e-13 -2.67952880e-13\n", - " 2.31845113e-13 -1.91261392e-13 1.50632870e-13 -1.10500910e-13\n", - " 7.57476224e-14 -4.57699083e-14 2.45554946e-14 -8.94622483e-15]\n", - "[1.44187941e+00 7.41740714e-14 2.51181407e-14 1.05619119e-14\n", - " 4.78044678e-15 2.16073321e-15 9.40681107e-16 3.72884929e-16\n", - " 1.31663760e-16 3.71950362e-17 8.11854229e-18 8.25747956e-19]\n", - "E Stencil coefficients for M=16: [ 1.44614800e+00 -2.36825054e-01 8.82228447e-02 -4.31300614e-02\n", - " 2.39901806e-02 -1.42789887e-02 8.79878105e-03 -5.49473562e-03\n", - " 3.42465560e-03 -2.10027919e-03 1.25174173e-03 -7.11924061e-04\n", - " 3.79739863e-04 -1.82031120e-04 7.51280761e-05 -2.14849307e-05]\n", - "B Stencil coefficients for M=16: [ 1.00000000e+00 -7.42001164e-12 7.07269017e-12 -6.57399947e-12\n", - " 5.95610462e-12 -5.24679190e-12 4.48866675e-12 -3.71258784e-12\n", - " 2.96353112e-12 -2.26288271e-12 1.64793983e-12 -1.12370185e-12\n", - " 7.13055006e-13 -4.01198174e-13 1.96331589e-13 -6.68845702e-14]\n", - "[1.44614800e+00 1.75724465e-12 6.23972846e-13 2.83537001e-13\n", - " 1.42888025e-13 7.49188824e-14 3.94947959e-14 2.03996886e-14\n", - " 1.01490734e-14 4.75268545e-15 2.06279505e-15 7.99990387e-16\n", - " 2.70775410e-16 7.30305531e-17 1.47500145e-17 1.43701035e-18]\n" - ] - }, - { - "data": { - "image/png": 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vw/Llyw2WL1iwQAGUX375Rb8sJiZGqVevnmJra6v/fBX/O21vb68EBAQkG68QQuQWSbXzhw8fVgBl+PDhCeq83k4oSsqvh6tXr/7W6+HXJXZtOnPmTIM2U1F0bSGgTJs2LcH+atasqX+dkmNKTxusKIoCKJMnT072GE6fPp3g88uWLVuSbC/fbItT267ly5dPefHihb7srl27FED57bffEuzrdfH158yZY7A8pcc0adIkBVC2b9+eoHz8+U7qc0VMTIxSoEABpXLlysrLly/1y/fs2aMAyqRJk/TL4t//8ePHJ3s84t0lw7kIkQGeP3+Oqamp/hvV170+LndQUBAhISG4u7tz4cKFBGXz5MkDQGBgYLL7CwsLw87OLtky8etDQ0MNlvfp08egbteuXSlUqBC///47AN7e3ty+fZv333+f58+fExgYSGBgIBERETRr1oxjx44luM38o48+SrD/1487KiqKwMBA3nvvPYBEj/1N8fGMHj3aYPlnn30GwN69ew2Wu7q64unpabAs/hvlXbt2vfXWeCGEEJkrubYSoGPHjhQpUkT/uk6dOtStW1ffHrwuT548b20r4924cQMnJyecnJyoUKECixYtok2bNqxatcqgnK2trcHY6ebm5tSpU4e7d+/ql5mYmOjHE9Vqtbx48QKNRkOtWrUM2jZHR0ciIiI4cOBAknFt2bIFd3d3/bHEP5o3b05cXBzHjh1Lsq69vT1eXl5s3rzZYGiVTZs28d5771G8eHEAtm/fjlarpXv37gb7cHZ2pkyZMokOQxPv999/x8TEhOHDhxss/+yzz1AUhT/++AOAnTt3otVqmTRpEmq14aWFSqVKcvvJ6dOnD//88w8+Pj76ZevXr6dYsWI0btw4yXovXrzg8OHDdO/enbCwMP3xPn/+HE9PT27fvp3g1u3BgwdjYmKSYFsWFhb079/fYNnvv/+Os7OzwYR5ZmZmDB8+nPDwcP766y+D8l26dNHfXSeEELldUu38tm3bUKlUTJ48OUGdN9uJlF4Ph4aGvvV6+HWvX5tGREQQGBhI/fr1URSFixcvJij/5vWtu7u7weeBlBxTetrgtx1DbGwsz58/p3Tp0jg6Oqbo+joxqW3XevTooX+PAH2P79fPTWqk9Ji2bduGm5tbgrvJ4O2fNc6dO0dAQACffPKJwZ1sbdq0oXz58gnyCoDBHQdCvE6S6EJksj179vDee+9haWlJ3rx5cXJyYtmyZYSEhCQoG38h/LaGwM7OjrCwsGTLxK9/88NFmTJlDF6rVCpKly6tH3fs9u3bAPTt21efdIh/rFy5kujo6ASxu7q6Jtj/ixcvGDFiBAULFsTKygonJyd9ucSO/U33799HrVYbDEUD4OzsjKOjI/fv339rDD169KBBgwYMGjSIggUL0rNnTzZv3iwJdSGEyIbebJ8AypYtm+i4mIqipDhBW6JECQ4cOMDBgwc5ceIET58+Zc+ePfohxOIVLVo00Yv5oKAgg2Vr166latWqWFpaki9fPpycnNi7d69B2/bJJ59QtmxZvLy8KFq0KAMGDGDfvn0G27l9+zb79u1L0NbGjyUbEBCQ7HH16NGDhw8fcvr0aQB8fHw4f/68wYTit2/fRlEUypQpk2A/169fT3Yf9+/fp3Dhwgk+R8TfEh7fDvv4+KBWq6lYsWKy8aZGjx49sLCwYP369YDuc8OePXvo3bt3su/7nTt3UBSFr776KsHxxic63jzmxD4/ABQpUiTBBGz379+nTJkyCb4sePOcvG3bQgjxLvHx8aFw4cIpGtIqpdfD9vb2b70eft2DBw/o168fefPm1Y9zHv+l7JvXpvHjm7/uzc8DKTmm9LTBiXn58iWTJk3Sz1OSP39+nJycCA4OTtH1dWJS267Ff0kfLz6h/uZnpZRK6TH5+PhQuXLlNO0j/hjKlSuXYF358uUTHKOpqal+jhQh3iRjoguRAfLly4dGo0nQQ/z48eO0b9+eRo0asXTpUgoVKoSZmRmrV69mw4YNCbYT3/i8eWH/pgoVKuDt7c2DBw8SNGTxLl++DJDqi9r4BPOcOXP0Y7u+6c3eBa9/gxyve/funDp1irFjx1KtWjVsbW3RarW0atUqVUnslCZJEovBysqKY8eOceTIEfbu3cu+ffvYtGkTTZs2Zf/+/Yn2PBNCCJE5kmor0yIoKOitbWU8GxubZCczjZdUm/B6T+9ffvmFfv360bFjR8aOHUuBAgUwMTFh5syZBr2mCxQogLe3N3/++Sd//PEHf/zxB6tXr6ZPnz76ybq0Wi0tWrRg3Lhxie63bNmyycbbrl07rK2t2bx5M/Xr12fz5s2o1Wr9hGLx+1CpVPzxxx+JHl9SdwUYW548eWjbti3r169n0qRJbN26lejoaIM7BRIT//lizJgxCe5Oi/fml/OJfX5IbnlqZMQ2hBAip8iIdj6l18Ply5fn4sWLPHz4kGLFiiVbNi4ujhYtWvDixQs+//xzypcvj42NDY8fP6Zfv34Jrk0z6hoxo9vgTz/9lNWrVzNy5Ejq1auHg4MDKpWKnj17ZlknsZR8VkqN7HBMb7KwsEjwpYIQ8SSJLkQGKF++PKCbkbxq1ar65du2bcPS0pI///wTCwsL/fLVq1cnuh1fX18g6Yk/4rVt25aNGzeybt06vvzyywTrQ0ND2bVrF+XLl09wsRjf0zyeoijcuXNHH3epUqUA3bf7KUk6JCYoKIhDhw4xdepUJk2alOS+IekkuYuLC1qtltu3bxucD39/f4KDg/UzfL+NWq2mWbNmNGvWjHnz5vHNN98wceJEjhw5kubjE0IIkXpJtZXxEmsjbt26RYkSJRIs9/X1xc3NLcNjfJutW7dSsmRJtm/fbtB+JXY7t7m5Oe3ataNdu3ZotVo++eQTfvjhB7766itKly5NqVKlCA8PT3NbZGNjQ9u2bdmyZQvz5s1j06ZNuLu7U7hwYX2ZUqVKoSgKrq6ub03Kv8nFxYWDBw8mSIbcuHFDvz5+H1qtlmvXriX55Xti3vYleZ8+fejQoQNnz55l/fr1VK9enUqVKiVbp2TJkoDuVvTMaONdXFy4fPkyWq3W4AL7zXMihBDvoqTa+VKlSvHnn3/y4sWLt/ZGT+n1cLt27di4cSO//PILEyZMSLbslStXuHXrFmvXrqVPnz765ckNufY2KTmm9LTBidm6dSt9+/blu+++0y+LiooiODjYoFxqhlIzdruW0mMqVaoU//77b7LbSi6vAHDz5k2aNm1qsO7mzZvSdotUka9XhMgA9erVA3Tjbb3OxMQElUpFXFycftm9e/fYuXNnots5f/48KpVKv72kdO3alYoVK/Ltt98m2KdWq+Xjjz8mKCgo0Yv6devWGdz6tnXrVvz8/PDy8gJ0M6KXKlWKuXPnEh4enqD+s2fPko0NXn1D/eY30gsWLEhQ1sbGBiBBQ9m6detE68ybNw/QjWH2Ni9evEiwLP4CPzo6+q31hRBCZJyk2sp4O3fuNBiv+syZM/zzzz/69ileSEgIPj4+1K9fP/OCTUJi7ds///yjH1Il3vPnzw1eq9VqfUIhvv3p3r07p0+f5s8//0ywn+DgYDQazVvj6dGjB0+ePGHlypVcunTJYCgXgM6dO2NiYsLUqVMTtMmKoiSI83WtW7cmLi6OxYsXGyyfP38+KpVK/7507NgRtVrNtGnTEvQaS65nWlLtfzwvLy/y58/PrFmz+Ouvv97aCx10dwB4eHjwww8/4Ofnl2B9Sj7DJKd169Y8ffqUTZs26ZdpNBoWLVqEra1tsuO1CyFEbpdUO9+lSxcURWHq1KkJ6rzZTqTmerhKlSrMmDEjQRsMuqFNJ06cCCTediuKwsKFC1NwVIlLyTGlpw1OjImJSYLtLFq0yCDXAG9vX19n7HYtpcfUpUsXLl26xI4dOxJsI75+Usddq1YtChQowPLlyw1yAH/88QfXr19PUV5BiHjSE12IDFCyZEkqV67MwYMHGTBggH55mzZtmDdvHq1ateL9998nICCAJUuWULp0af1wK687cOAADRo0IF++fMnuz9zcnK1bt9KsWTMaNmxI//79qVWrFsHBwWzYsIELFy7w2Wef0bNnzwR18+bNq6/j7+/PggULKF26NIMHDwZ0F/orV67Ey8uLSpUq0b9/f4oUKcLjx485cuQI9vb2/Pbbb8nGZ29vT6NGjZg9ezaxsbEUKVKE/fv363sWvK5mzZoATJw4kZ49e2JmZka7du1wc3Ojb9++/PjjjwQHB9O4cWPOnDnD2rVr6dixI02aNEk2BoBp06Zx7Ngx2rRpg4uLCwEBASxdupSiRYvSsGHDt9YXQgiRcZJqK+OVLl2ahg0b8vHHHxMdHc2CBQvIly9fguFODh48iKIodOjQIatC12vbti3bt2+nU6dOtGnTBl9fX5YvX07FihUNvngeNGgQL168oGnTphQtWpT79++zaNEiqlWrpu9dN3bsWHbv3k3btm3p168fNWvWJCIigitXrrB161bu3bv31tvZW7dujZ2dHWPGjMHExIQuXboYrC9VqhRff/01EyZM4N69e3Ts2BE7Ozt8fX3ZsWMHQ4YMYcyYMYluu127djRp0oSJEydy79493Nzc2L9/P7t27WLkyJH6O9dKly7NxIkTmT59Ou7u7nTu3BkLCwvOnj1L4cKFmTlzZqLbL1WqFI6Ojixfvhw7OztsbGyoW7eufhxxMzMzevbsyeLFizExMTGY9Cw5S5YsoWHDhlSpUoXBgwdTsmRJ/P39OX36NI8ePeLSpUsp2k5ihgwZwg8//EC/fv04f/48JUqUYOvWrZw8eZIFCxake5giIYTIyZJq55s0acKHH37I999/z+3bt/XDex4/fpwmTZowbNgwfdmUXg+bmZmxfft2mjdvTqNGjejevTsNGjTAzMyMq1evsmHDBvLkycOMGTMoX748pUqVYsyYMTx+/Bh7e3u2bduW5nG8U3pM6WmDE9O2bVt+/vlnHBwcqFixIqdPn+bgwYMJzlW1atUwMTFh1qxZhISEYGFhQdOmTSlQoECCbRq7XUvpMY0dO5atW7fSrVs3BgwYQM2aNXnx4gW7d+9m+fLluLm5Jfu5YtasWfTv35/GjRvTq1cv/P39WbhwISVKlGDUqFGZeowil1GEEBli3rx5iq2trRIZGWmw/KefflLKlCmjWFhYKOXLl1dWr16tTJ48WXnzzy84OFgxNzdXVq5cmeJ9BgQEKKNHj1ZKly6tWFhYKI6Ojkrz5s2V3bt3Jyh75MgRBVA2btyoTJgwQSlQoIBiZWWltGnTRrl//36C8hcvXlQ6d+6s5MuXT7GwsFBcXFyU7t27K4cOHdKXiT+OZ8+eJaj/6NEjpVOnToqjo6Pi4OCgdOvWTXny5IkCKJMnTzYoO336dKVIkSKKWq1WAMXX11dRFEWJjY1Vpk6dqri6uipmZmZKsWLFlAkTJihRUVEG9V1cXJQ2bdokiOHQoUNKhw4dlMKFCyvm5uZK4cKFlV69eim3bt1KyekVQgiRwRJrK319fRVAmTNnjvLdd98pxYoVUywsLBR3d3fl0qVLCbbRo0cPpWHDhinaX+PGjZVKlSqluVzfvn0VFxcX/WutVqt88803iouLi2JhYaFUr15d2bNnT4JyW7duVVq2bKkUKFBAMTc3V4oXL64MHTpU8fPzM9h+WFiYMmHCBKV06dKKubm5kj9/fqV+/frK3LlzlZiYmBQdY+/evRVAad68eZJltm3bpjRs2FCxsbFRbGxslPLlyyv/+9//lJs3byZ5rPHxjRo1SilcuLBiZmamlClTRpkzZ46i1WoT7GPVqlVK9erVFQsLCyVPnjxK48aNlQMHDujXN27cWGncuLFBnV27dikVK1ZUTE1NFUBZvXq1wfozZ84ogNKyZcsUnYt4Pj4+Sp8+fRRnZ2fFzMxMKVKkiNK2bVtl69at+jKrV69WAOXs2bMJ6if3e+Pv76/0799fyZ8/v2Jubq5UqVIlQdyv/04LIcS7JKlrYo1Go8yZM0cpX768Ym5urjg5OSleXl7K+fPn9WXScj0cFBSkTJo0SalSpYpibW2tWFpaKpUrV1YmTJhg0OZeu3ZNad68uWJra6vkz59fGTx4sHLp0qUEbU/fvn0VGxubBPtJ7Po9JcekKGlvg9+8bg4KCtK3P7a2toqnp6dy48YNxcXFRenbt69B3RUrViglS5ZUTExMFEA5cuSIoiiJt8XpbdcSu75/U1L1U3NMz58/V4YNG6YUKVJEMTc3V4oWLar07dtXCQwM1JdJ7nPFpk2b9J9T8ubNq/Tu3Vt59OiRwT6Sev+FiKdSlDTOACCEMBASEkLJkiWZPXs2AwcOTHX9BQsWMHv2bHx8fDJlIqqjR4/SpEkTtmzZQteuXTN8+0IIIcTbpLetfPr0Ka6urvz6669G6YkustalS5eoVq0a69at48MPPzR2OEIIId4iPe18Zl8PCyFEesmY6EJkEAcHB8aNG8ecOXNSPZN0bGws8+bN48svv5QPDEIIIXKt9LSVoLvArlKliiTQ3xErVqzA1taWzp07GzsUIYQQKZDWdl6uh4UQOYH0RBfiHSE90YUQQgiRE/z2229cu3aNr776imHDhuknFRdCCCGEEMJYZGJRIYQQQgghRLbx6aef4u/vT+vWrZk6daqxwxFCCCGEECJ7DOeyZMkSSpQogaWlJXXr1uXMmTNJll2zZg0qlcrgYWlpmYXRCpEzeXh4oCiK9EIXQgghRLZ27949Xr58yc6dO7GzszN2OELkKseOHaNdu3YULlwYlUrFzp0731rn6NGj1KhRAwsLC0qXLs2aNWsM1k+ZMiXBNXr58uUz5wCEEEIIIzF6En3Tpk2MHj2ayZMnc+HCBdzc3PD09CQgICDJOvb29vj5+ekf9+/fz8KIhRBCCCGEEEKInCciIgI3NzeWLFmSovK+vr60adOGJk2a4O3tzciRIxk0aBB//vmnQblKlSoZXKOfOHEiM8IXQgghjMbow7nMmzePwYMH079/fwCWL1/O3r17WbVqFePHj0+0jkqlwtnZOSvDFEIIIYQQQgghcjQvLy+8vLxSXH758uW4urry3XffAVChQgVOnDjB/Pnz8fT01JczNTWVa3QhhBC5mlGT6DExMZw/f54JEybol6nVapo3b87p06eTrBceHo6LiwtarZYaNWrwzTffUKlSpUTLRkdHEx0drX+t1Wp58eIF+fLlQ6VSZdzBCCGEeCcpikJYWBiFCxdGrTb6DV7vFK1Wy5MnT7Czs5M2XQghRLpJm57Q6dOnad68ucEyT09PRo4cabDs9u3bFC5cGEtLS+rVq8fMmTMpXrx4ktuV63QhhBCZKTPadKMm0QMDA4mLi6NgwYIGywsWLMiNGzcSrVOuXDlWrVpF1apVCQkJYe7cudSvX5+rV69StGjRBOVnzpwpExIJIYTIdA8fPky0HRKZ58mTJxQrVszYYQghhMhlpE1/5enTp4ler4eGhvLy5UusrKyoW7cua9asoVy5cvj5+TF16lTc3d35999/k5zXQK7ThRBCZIWMbNONPpxLatWrV4969erpX9evX58KFSrwww8/MH369ATlJ0yYwOjRo/WvQ0JCKF68OL6+vjg6OmZFyLmOVqslMDCQ/PnzSw+NdJDzmH5yDtMvI86hokCnTir++ktFs2YKW7Yo5PYORFqtljFjxlCvXj1atGiBq6urTH5nBPHn/P79+9Kmp5FWq+XZs2c4OTnJ/9F0kPOYfnIO00/OYfoFBwfj4uIibXoqvT48TNWqValbty4uLi5s3ryZgQMHJlpHrtMznlwbZQw5j+kn5zD95BymX3BwcIZfpxs1iZ4/f35MTEzw9/c3WO7v75/i8dTMzMyoXr06d+7cSXS9hYUFFhYWCZY7OjpK45xGWq2WmJgYHB0d5Y85HeQ8pp+cw/TLiHO4cSP89RdYWsIPP0CePBkcZDaj1WoZOnQoq1evZv369Zw/fx5Abj02gvhzbm9vj729vZGjyZm0Wi1RUVHY29vL/9F0kPOYfnIO00/OYfpptVpA2vTXOTs7J3q9bm9vj5WVVaJ1HB0dKVu2bJLX6CDX6ZlBro0yhpzH9JNzmH5yDjNORrbpRn0nzM3NqVmzJocOHdIv02q1HDp0yKC3eXLi4uK4cuUKhQoVyqwwhRBCJCEoCEaN0j3/4gsoVcq48WQ2rVbLkCFDWLlyJWq1mtWrV8vt3kIIIYTIterVq2dwvQ5w4MCBZK/Xw8PD8fHxkWt0IYQQuYrRv84YPXo0K1asYO3atVy/fp2PP/6YiIgI+vfvD0CfPn0MJh6dNm0a+/fv5+7du1y4cIEPPviA+/fvM2jQIGMdghBCvLM+/xz8/aF8eRg3ztjRZC6tVsvgwYP56aefUKvV/PLLL7z//vvGDksIIYQQIsXCw8Px9vbG29sbAF9fX7y9vXnw4AGgG2alT58++vIfffQRd+/eZdy4cdy4cYOlS5eyefNmRsX3ogDGjBnDX3/9xb179zh16hSdOnXCxMSEXr16ZemxCSGEEJnJ6GOi9+jRg2fPnjFp0iSePn1KtWrV2Ldvn37ykgcPHhjcuhAUFMTgwYN5+vQpefLkoWbNmpw6dYqKFSsa6xCEEOKddPw4rFihe/7DD5DIHbm5hlarZdCgQaxevRq1Ws369evp2bOnscMSQgghhEiVc+fO0aRJE/3r+HHJ+/bty5o1a/Dz89Mn1AFcXV3Zu3cvo0aNYuHChRQtWpSVK1fi6empL/Po0SN69erF8+fPcXJyomHDhvz99984OTll3YEJIYQQmczoSXSAYcOGMWzYsETXHT161OD1/PnzmT9/fqbHFBcXR2xsbKbvJyfSarXExsYSFRWVI8ZmMjc3zxFxCpGTREfDkCG654MHQ6NGxo0ns23atInVq1djYmLC+vXr6dGjh7FDEqkgbXrSjNmmS/sshBBZz8PDA0VRkly/Zs2aROtcvHgxyTq//vprRoQmhBBCZGvZIomenSiKwtOnTwkODjZ2KNmWoihotVrCwsJyxKQ7arUaV1dXzM3NjR2KELnGt9/CjRtQsCDMmmXsaDJfz549OXv2LHXr1pUEeg4ibfrbGbNNl/ZZCCGEEEIIkVNIEv0N8RfbBQoUwNraOkckibOaoihoNBpMTU2z/fnRarU8efIEPz8/ihcvnu3jFSInuHEDvvlG93zhQsiTx7jxZJa4uDji4uIwNzdHpVIxb948Y4ckUkna9LczVpsu7bMQQgghhBAiJ5Ek+mvi4uL0F9v58uUzdjjZVk5KogM4OTnx5MkTNBoNZmZmxg5HiBxNq9UN4xITA61bQ/fuxo4oc8TFxTFgwACCgoLYsmULFrl5wPdcStr0lDFmmy7tsxBCCCGEECKnkIEoXxM/Xqq1tbWRIxEZKf428bi4OCNHIkTOt2qVbkJRa2tYuhRywPdoqRafQF+3bh2///47//zzj7FDEmkgbXr2J+2zEEIIIYQQIqeQnuiJyAm9q0XKyfspRMZ4+hTGjtU9nz4dXFyMG09miIuLo3///vz888+YmJjw66+/0ii3z5qay0kbkH3JeyOEEEIIIYTIKaQnuhBCiBQZNQqCg6FGDRg+3NjRZLzXE+impqZs2rSJrl27GjssIYQQQgghhBBCGJkk0XMJDw8PVCoVKpUKb29vjh49ikqlIjg4OMk68eUdHR0zPb41a9ZkyX6EEJnj99/h119BrYYVK8A0l93HFBcXR79+/QwS6F26dDF2WEJkK5GRkXTp0gV7e/u3fsYQQgghhBBCiNxEkui5yODBg/Hz86Ny5copKu/n58eCBQsMlk2ZMkWfXH/9Ub58eX2Z7du307p1a/Lnz69P2ifF1dWVgwcPpuVwEoiKiqJfv35UqVIFU1NTOnbsmCHbFUIkLzwcPvlE93zUKF1P9Nzm5s2b7NixA1NTUzZv3kznzp2NHZJ4h8XFxfHVV1/h6uqKlZUVpUqVYvr06SiKYtS41q5dy/Hjxzl16hR+fn44ODgYNR4hhBBCCCGEyCq5rC/hu83a2hpnZ+cUl3d2dk70ArhSpUoJEt+mr3U7jYiIoH79+nTv3p0hQ4Ykuf3Lly8TFBRE48aNWb9+fYrjSkpcXBxWVlYMHz6cbdu2pXt7QoiUmTwZ7t/XjYE+daqxo8kcFStWZN++fQQGBib7BZ1GE0ZExL9ERt4gJuYpsbEBBAe/yLpAxTth1qxZLFu2jLVr11KpUiXOnTtH//79cXBwYLgRx1Ly8fGhQoUKKf6yXgghhBBCCCFyC+mJ/o6IjIzEy8uLBg0avPX2a1NTU5ydnQ0e+fPn16//8MMP+fLLL2nevHmy29m1axetWrXCzMwswbpnz55Rq1YtOnXqRHR0NAC7d++mTJkyWFpa0qRJE9auXWtwu7iNjQ3Lli1j8ODBqfqyQAiRdhcuQPwNK0uXgo2NUcPJUBqNBh8fH/3rhg0bJkigx8VFEhj4G7dvD+fMmQqcOGHPxYv1uXlzAL6+X/Do0QL8/ddlceQitzt16hQdOnSgTZs2lChRgq5du9KyZUvOnDmTbL3ffvuN2rVrY2lpSf78+enUqZN+XVBQEH369CFPnjxYW1vj5eXF7du3DeqfOHECd3d3rKysKFasGMOHDyciIgLQDRv33XffcezYMVQqFR4eHhl+3EIIIYQQQgiRXUkS/S0UBSIijPPIqLu2g4ODadGiBVqtlgMHDmTZ2OS7d++mQ4cOCZY/fPgQd3d3KleuzNatW7GwsMDX15euXbvSsWNHLl26xNChQ5k4cWKWxCmESFxsLAwaBFot9OwJrVsbO6KMo9Fo+PDDD6lbty6XLl0yWKcoCkFBR7hxoz+nTjnz77/tefx4EZGRNwAwNy9MnjwtcHbuR7Fin1Os2BfGOASRFooC2gjjPFLRqNevX59Dhw5x69YtAC5dusSJEyfw8vJKss7evXvp1KkTrVu35uLFixw6dIg6dero1/fr149z586xe/duTp8+jaIotG7dmtjYWEDXy7xVq1Z06dKFy5cvs2nTJk6cOMGwYcMA3VBugwcPpl69evj5+bF9+/a0vANCCCGEEEIIkSPJcC5vERkJtrbG2Xd4ePp7fT59+pQePXpQpkwZNmzYgLm5+VvrXLlyBds3DvqDDz5g+fLlKd7v48ePuXz5coIL/ps3b9KiRQs6derEggULUKlUAPzwww+UK1eOOXPmAFCuXDn+/fdfZsyYkeJ9CiEy1ty5cPEi5M37qjd6bqDRaPjggw/YtGkTpqam3L9/Hzc3N7TaGAICNvLw4VwiIv7Vl7ewcCFfPi/y5GmJg4M75ub5Dbanu1vmm6w9CJE2SiTcMlKjXjYcVClr1MePH09oaCjly5fHxMSEuLg4ZsyYQe/evZOsM2PGDHr27MnU18ZccnNzA+D27dvs3r2bkydPUr9+fQDWr19PsWLF2LlzJ506dWLmzJn07t2bkSNHAlCmTBm+//57GjduzLJly8ibNy/W1taYm5vL3WBCCCGEEEKId44k0XO5Fi1aUKdOHTZt2oSJiUmK6pQrV47du3cbLLO3t0/Vfnfv3k3Dhg0Ner2/fPkSd3d33n///QQTmt68eZPatWsbLHu9B50QImvduPFq/PMFC6BgQaOGk2FeT6CbmZmxZcsW2rZtzZMnK7l3bwoxMY8BMDGxpUCB9ylY8EMcHBrov/ATIits3ryZ9evXs2HDBipVqoS3tzcjR46kcOHC9O3bN9E63t7eDB48ONF1169fx9TUlLp16+qX5cuXj3LlynH9+nU6derE5cuXuXz5ssEcJoqioNVq8fX1pUKFChl7kEIIIYQQQgiRg0gS/S2srXU9wo217/Rq06YN27Zt49q1a1SpUiVFdczNzSldunS69rt7927at29vsMzCwoLmzZuzZ88exo4dS5EiRdK1DyFE5tBqYeBAiI6GVq3ggw+MHVHG0Gg09O7dm82bN+sT6A0aqDh3riqRkdcB3VAtRYuOoFChIZiZORo3YJHxVNa6HuHG2ncKjR07lvHjx9OzZ08AqlSpwv3795k5c2aSSXQrK6t0hRceHs7QoUMTnbi0ePHi6dq2EEIIIYQQQuR0kkR/C5UqZ0+k9+2332Jra0uzZs04evQoFStWzPR9hoeHc+TIEZYtW2awXK1W8/PPP/P+++/TpEkTjh49SuHChQFd7/fff//doPzZs2czPVYhREJLlsCpU7qhrH74Qfd/MKfTaDS8//77bNmyBTMzMzZuXE7Jkiv59989AJia5sXF5UuKFPkEtdrCyNG+Wzp16sTRo0dp1qwZW7duzdydqVQpHlLFmCIjI1GrDaetMTExQavVJlmnatWqHDp0iP79+ydYV6FCBTQaDf/8849+OJfnz59z8+ZN/eeCGjVqcO3atXR/iS6EEEIIIYQQuZFMLPoOmDt3Lr1796Zp06bcuHHjreU1Gg1Pnz41ePj7++vXv3jxAm9vb65duwbohmLx9vbm6dOnAOzbt4+yZctSokSJBNs2MTFh/fr1uLm50bRpU32doUOHcuPGDT7//HNu3brF5s2bWbNmDYDBMArXrl3D29ubFy9eEBISgre3N97e3mk8M0KIN927BxMm6J7PmgW5pQNqdHQ0/v7+mJmZ8cMPfXFyGs7z53tQqcwoVuxz6tb1oVixUZJAN4IRI0awbt06Y4eRrbRr144ZM2awd+9e7t27x44dO5g3bx6dOnVKss7kyZPZuHEjkydP5vr161y5coVZs2YBuvHNO3TowODBgzlx4gSXLl3igw8+oEiRIvoJwMeNG8epU6cYNmwY3t7e3L59m127duknFk3MhAkT6NOnT8YevBBCCCGEEEJkQ5JEf0fMnz+f7t2707RpU27dupVs2atXr1KoUCGDh4uLi3797t27qVOnDm3btgWgZ8+eVK9eXT/x6K5duxIM5fI6U1NTNm7cSKVKlWjatCkBAQG4urqydetWtm/fTtWqVVm2bBkTJ04EdMPAxGvdujXVq1fnt99+4+jRo1SvXp3q1aun+bwIIV5RFBgyBCIiwN0dPvrI2BFlHBsbG7ZtW8bSpRVwdV2JVhuBvX0DatXyplSpb2XoFiPy8PDAzs7O2GFkK4sWLaJr16588sknVKhQgTFjxjB06FCmT5+eZB0PDw+2bNnC7t27qVatGk2bNuXMmTP69atXr6ZmzZq0bduWevXqoSgKv//+O2ZmZoCuJ/tff/3FrVu3cHd3p3r16kyaNEl/x1hi/Pz8ePDgQcYduBBCCCGEEEJkUypFURRjB5GVQkNDcXBwICgoyGDSS4CoqCh8fX1xdXXF0tLSOAGmkYeHB9WqVUswYefbrFmzhpEjRxIcHJziOoqioNFoMDU1TTDZnkajoWDBgvzxxx/pnhh0xowZLF++nIcPH6ZrO9n1fdVqtQQEBFCgQIEEt+2LlJFzmH6vn8N169T07w+WlnDpEpQta+zo0ic2NpadO3fSrVs3/P1/5datj4iLC8HExJZSpeZSqNBgVKr0/94EBweTJ08eQkJCUj0Jc3Z37Ngx5syZw/nz5/Hz82PHjh107NjRoMySJUuYM2cOT58+xc3NjUWLFqX6///Ro0dZvHhxqodzya1telZKrk3PbLnpPZL2KP3kHKafnMP0y81tenaXXJsuUkb+B2QMOY/pJ+cw/eQcpl9mtOnyTuQiS5cuxdbWlitXrqSovK2tLR9lcFfTFy9eMGrUKGrXrp3qukuXLuXs2bPcvXuXn3/+mTlz5iQ5gZoQImP5+cGoUbrnU6fmjgR6z5496d69OyNH1uD69V7ExYVgb/8etWpdonDhoRmSQM/tIiIicHNzY8mSJYmu37RpE6NHj2by5MlcuHABNzc3PD09CQgI0JepVq0alStXTvB48uRJVh2GEEIIIYQQQgiRLjKxaC6xfv16Xr58CUDxFA5iHD+WuImJSYbFUaBAAb788ss01b19+zZff/01L168oHjx4nz22WdMiB+cWQiRqT79VEVwMNSsCaNHGzua9ImNjaVHjx7s2LEDMzMVzs4XATUuLl/i4vIVarU0fSnl5eWFl5dXkuvnzZvH4MGD9ZNZLl++nL1797Jq1SrGjx8PkKHzVkRHRxMdHa1/HRoaCuh6arw56aZWq0VRFP1DJC3+/GT1eYp/bxJ7/3Ka+N+3nH4cxiTnMP3kHKafnDshhBBCJEUyCblEkSJFUl2ndOnSmRBJ2s2fP5/58+cbOwwh3jl79liwY4cKU1P46ScwzcEtQ0xMDD179vwvgQ7Tpys0bOhExYqbyJOnibHDy1ViYmI4f/68wZedarWa5s2bc/r06UzZ58yZM5k6dWqC5c+ePSMmJsZgWWxsLFqtFo1Gg0ajyZR4cgNFUYiLiwPI8uFcNBoNWq2W58+f68dmz6m0Wi0hISEoiiK33KaRnMP0k3OYfiEhIcYOQQghhBDZVA5OlQghhEivFy9gwgTd+GDjx4Obm5EDSoeYmBh69OjBzp07/0ugQ/PmtalUaRuWlsWMHV6uExgYSFxcHAULFjRYXrBgQW7cuJHi7TRv3pxLly4RERFB0aJF2bJlC/Xq1Uu07IQJExj92q0SoaGhFCtWDCcnp0THRA8LC8PU1BTTnPzNUBYxRhLb1NQUtVpNvnz5csWY6CqVCicnJ0leppGcw/STc5h+5ubmxg5BCCGEENmUXFUKIcQ7bPRoFYGBaipUUPjyy6zthZqRFEWhR4/u7Ny5CzMz+Ppr6NBhEKVLL8LEJGcn53K7gwcPprishYUFFhYWCZar1eoECSO1Wo1KpdI/ROIURdGfn6w+T/HvTWLvX06Um47FWOQcpp+cw/SR8yaEEEKIpEgSXQgh3lF//AE//6xCpVJYsULBwiLnJho1mhDKl7+OuTlMn66id+/FFCnyibHDytXy58+PiYkJ/v7+Bsv9/f1xdnY2UlRCCCFEOsT4GjsCIYQQQmRT8lW7EEK8g8LCYOhQ3fNBgyJJYvSMHOHly3tcvNgAT89bbNhgzcCBeySBngXMzc2pWbMmhw4d0i/TarUcOnQoyeFYhBBCiGxH0UDYDnjoifpBDWNHI4QQQohsSnqiCyHEO2jMGHj4EFxdFcaPDwesjB1SqsXExDB27CBatdqHldUzzM2L0LLlHuzsqhk7tFwjPDycO3fu6F/7+vri7e1N3rx5KV68OKNHj6Zv377UqlWLOnXqsGDBAiIiIujfv78RoxZCCCFSQOMPQcsgZAVongCgGDkkIYQQQmRfkkQXQoh3zIED8OOPuucrVypYW+e8S8bo6Gg6dmzCvn2nOXQIVq2qStWqe7G0LGrs0HKVc+fO0aRJE/3r+Ek9+/bty5o1a+jRowfPnj1j0qRJPH36lGrVqrFv374Ek40KIYQQ2UbUJQhaAKEbQInRLTNxAoeBKHm7A9IbXQghhBAJyXAuuYSHh4d+gi5vb2+OHj2KSqUiODg4yTrx5R0dHbMkxilTplCtWrUs2ZcQInGhoTBwoO75//4HHh5GDSdNoqOjad++Afv2ncbcHIYNq0aNGickgZ4JPDw8UBQlwWPNmjX6MsOGDeP+/ftER0fzzz//ULduXeMFLIzuxo0bvPfee1haWkqbL4TIPhQthP0GD5rCvWoQskaXQLesC4U3QKmHYD0R1dyNxo5UCCGEENmUJNFzkcGDB+Pn50flypVTVN7Pz48FCxYYLJsyZYo+ua5SqXBwcMDd3Z2//vrLoNzKlStp0qQJ9vb2ySbrX758iY2NjcFwAOnh5+fH+++/T9myZVGr1YwcOTJDtivEu+LVMC7w7bfGjib1oqOjadu2Dvv3n8fcHBYvbsiQIX9jampn7NCEyDDHjh2jXbt2FC5cGJVKxc6dOw3Wx8bG8vnnn1OlShVsbGwoXLgwffr04cmTJ8YJ+DWTJ0/GxsaGmzdvGoyXL4QQRqHEQsha8K0Ij9tD5BHABOx6gMtpKPE32PaAXzZBuXKo5swxdsRCCCGEyKYkiZ6LWFtb4+zsjKlpykbpcXZ2xsHBIcHySpUq4efnh5+fH6dPn6ZMmTK0bduWkJAQfZnIyEg8PT354osvkt3HgQMHcHFxoXTp0qk7mCRER0fj5OTEl19+iZubW4ZsU4h3xf79sGKF7vmqVWBra9x4Uis6OprWratx8OBlzM1h2bJWDBp0FLXawtihCZGhIiIicHNzY8mSJYmuj4yM5MKFC3z11VdcuHCB7du3c/PmTdq3b5/FkSbk4+NDw4YNcXFxIV++fMYORwjxrtJGQ9ByuFsW/PpBzE1QO0LesVDqLhT5Fazeg9OnoV496NsXnjwhpnhJY0cuhBBCiGxKkujviMjISLy8vGjQoEGyQ7wAmJqa4uzsjLOzMxUrVmTatGmEh4dz69YtfZnhw4czfvx43nvvvWS3tWvXriQv6n18fChZsiTDhg1DUXRjMq9YsYJixYphbW1Np06dmDdvnsFwMyVKlGDhwoX06dMn0S8AhBCJCwmBQYN0z4cNy3nDuCiKwocf1uHw4RuYm8PKlT3o3/93VCoTY4cmRIbz8vLi66+/plOnTomud3Bw4MCBA3Tv3p1y5crx3nvvsXjxYs6fP8+DBw+S3K5Wq2X27NmULl0aCwsLihcvzowZM/Trr1y5QtOmTbGysiJfvnwMGTKE8PBwg22sXLmSChUqYGlpSfny5Vm6dKl+nUql4vz580ybNg2VSsWUKVPSdyKEECK1tC/hxQK4WxL8P4bYe2BSAJxmQakHUGA2mBWH589149vVrw9nzoCtLbdGL6dlnnPGPgIhhBBCZFMysejbKApERhpn39bWoFKlezPBwcG0adMGW1tbDhw4gLW1dYrrRkdHs3r1ahwdHSlXrlyq9qvVatmzZ0+C29ABLl++jKenJwMHDuTrr78G4OTJk3z00UfMmjWL9u3bc/DgQb766qtU7VMIkbj4YVxKlsx5w7goisLt28No3/4yp0/DrFmDef/9H40dlsiJckGbnpSQkJC3znMyYcIEVqxYwfz582nYsCF+fn5cv34d0PV+9/T0pF69epw9e5aAgAAGDRrEsGHD9GPgr1+/nkmTJrF48WKqV6/OxYsXGTx4MDY2NvTt2xc/Pz+aN29Oq1atGDNmDLY57XYXIUTOpcRCyGoInAaax7plpkUh7zhwHAjq/65/FAXWr4fRo+HZM92y/v1ZW20en0xwJDIy1DjxCyGEECLbkyT620RGGm/Mg/BwsLFJ1yaePn1Kjx49KFOmDBs2bMDc3Pytda5cuaK/8I2MjMTOzo5NmzZhb2+fqn3//fffAAkmmTt16hRt27Zl4sSJfPbZZ/rlixYtwsvLizFjxgBQtmxZTp06xZ49e1K1XyGEoT//hJUrdc9XrUr3v5UspShabt8expMnyyhaVMXJk8soXnyoscMSOVUOb9OTEhUVxeeff06vXr2SbKvDwsJYuHAhixcvpm/fvgCUKlWKBg0aoNFo2LBhA1FRUaxbtw6b/+JcvHgx7dq1Y9asWRQsWJDJkyfz3Xff0blzZwBcXV25du0aP/zwA3379tUPKWdra4uzs3OmHKsQQhhQtBC2GZ59BbH/zcFkWhzyfwkOfUH12rXP3bvw0Udw4IDudaVKvFy0kmG/vMeqEbpF7u4Kx49n7SEIIYQQImeQ4VxyuRYtWlC6dGk2bdqUogQ6QLly5fD29sbb25vz58/z8ccf061bN86dS93tjbt27aJt27ao1a9+zR48eECLFi2YNGmSQQId4ObNm9SpU8dg2ZuvhRCp8/owLp9+Co0bGzee1Hj5MpKWLUuxffsyQEX58qslgS7EG2JjY+nevTuKorBs2bIky12/fp3o6GiaNWuW5Ho3Nzd9Ah2gQYMGaLVabt68SUREBD4+PgwcOBBbW1v94+uvv8bHxyfDj0sIId4q4gDcqwlPeukS6CZOUGAhlLwFjoNfJdAVBZYvhypVdAl0CwuYMYPbmy7w3sj3WLUK1GqYPh127lSMe0xCCCGEyLakJ/rbWFvreo8Za9/p1KZNG7Zt28a1a9eoUqVKiuqYm5sbTARavXp1du7cyYIFC/jll19SvO/du3fz7RvjRjg5OVG4cGE2btzIgAEDUt27XQiROp99Bo8eQalSMHOmsaNJuZcvI/H0LM/x4w85cwbOnVuGs3NfY4clcroc3qa/KT6Bfv/+fQ4fPpxsm2plZZWufcWPjb5ixYoEd5iZmMjcBEKILBRzGwI+g/DfdK/V9pB3DOQZCSZ2hmWfPNGNfb5vn+51kybw44/8dr00vetBWBgUKAAbNkCzZvCWqaOEEEII8Q6TJPrbqFQ5a+yDN3z77bfY2trSrFkzjh49SsWKFdO0HRMTE16+fJni8rdv3+b+/fu0aNHCYLmVlRV79uyhdevWeHp6sn//fuzsdB92y5Urx9mzZw3Kv/laCJFy+/bBTz/p/o2tXp1z/pXpeqCX48SJR1hawurVX1CmjPRAFxkgh7fpr4tPoN++fZsjR46QL1++ZMuXKVMGKysrDh06xKD421NeU6FCBdauXUtERIS+N/rJkydRq9WUK1eOggULUrhwYe7evUvv3r0z5ZiEECJZcaHw/GvdxKHEAqaQ53+Q/yswSeR/4JYtuuFbXrwAS0v49luUYZ8yb4GasWN1HdQbNoRNm6Bw4Sw+FiGEEELkOJJEfwfMnTuXuLg4mjZtytGjRylfvnyy5TUaDU+fPgV0Y6hu2rSJa9eu8fnnn+vLPH36lMDAQO7c0Y09eOXKFezs7ChevDh58+Zl165dNG/ePNFJTG1sbNi7dy9eXl54eXmxb98+bG1t+fTTT2nUqBHz5s2jXbt2HD58mD/++APVGxOxeXt7A7pecc+ePcPb2xtzc/M0f0EgRG4UEgKDB+ueDx8O7u7GjSelIiMjaNmyHCdPPsbSEtav/4LOnWcYOywhslR4eLi+fQXw9fXF29ubvHnzUrx4cWJjY+natSsXLlxgz549xMXF6dvtvHnzJjp8m6WlJZ9//jnjxo3D3NycBg0a8OzZM/7991/69u1L7969mTJlCn379mXKlCk8e/aMTz/9lA8//JCCBQsCMHXqVIYPH46DgwOtWrUiOjqac+fOERQUxOjRoxM9lmbNmtGpUyeGDRuWCWdKCPFOUBQI/QUCxkBcgG6ZTSsoMB8sErmuiYqCESPgx/8mIa9ZE9atI6Z0RT4ZqutgADBkCCxeDGZmWXMYQgghhMjZJIn+jpg/f75BIr1s2bJJlr169SqFChUCwNramlKlSrFs2TL69OmjL/Pjjz/y9ddf6183atQIgNWrV9OvXz927dqln7gsMba2tvzxxx94enrSpk0bfv/9dxo0aMDy5cuZOnUqX375JZ6enowaNYrFixcb1K1evbr++fnz59mwYQMuLi7cu3cvVedEiNxs9GjdMC6lS8M33xg7mpSJjIygRYtynDqlS6Bv2DCRTp2+fntFIXKZc+fO0aRJE/3r+AR13759WbNmDY8fP2b37t0AVKtWzaDukSNH8PDwSHS7X331FaampkyaNIknT55QqFAhhg7V3eVhbW3Nn3/+yYgRI6hduzbW1tZ06dKFefPm6esPGjQIa2tr5syZw9ixY7GxsaFKlSqMHDkyyWPx8fEhMDAwDWdBCCGAmDvw9COIPKR7bV4OCswD29aJl79zB7p1A29v3d1HX3wBkycTEmlGp1Zw5Ihu/PPvvtPl2d/oqyOEEEIIkSSVoijv1OwpoaGhODg4EBQUhKOjo8G6qKgofH19cXV1xdLS0jgBppGHhwfVqlVjwYIFqaq3Zs0aRo4cSXAqBgBUFAWNRoOpqWmCXuIAgYGBFCpUiEePHul7r6XV4MGDuXHjBsePH0/zNrLr+6rVagkICKBAgQIGk6+KlJNzmLg//oDWrXUXhseO6W5VTkp2OYeKomX8+HrMnn0GS0vYuPFLOnacbrR4UiM4OJg8efIQEhIi8zxksdzapmelt7XpmSk3vUfZ5X9pTibnMP1y1TlUYuHFXAicBkoUqCwh/2TIO/rVhKFv2roVBgzQDXSePz+sXw8tWxIQAK1awcWLYGcHv/6q+5yUGGnTjSe5Nl2kTK76H2BEch7TT85h+sk5TL/MaNOlJ3ousnTpUlauXMnp06dTNImora0tGo0mwy9cX7x4wbx589KUQJ87dy4tWrTAxsaGP/74g7Vr17J06dIMjU+I3Cw4+NUwLiNGJJ9Azy4URcvNm0No2fIM16/DgAE5J4EuhBBCiAwWdRH8+kL0Fd1r6+bgvBzMSyVeXquFr756detdw4a6THmRIty/Dy1bwq1buglE9+2D125qFUIIIYRIMUmi5xLr16/XT/xZvHjxFNWJH1vcxMQkQ2MpW7ZsssPFJOfMmTPMnj2bsLAwSpYsyffff5/oBGhCiMSNGAGPH0OZMjAjBwwl/vJlJHfv/o9nz9ZgYqJmxYpfKFiwl7HDEkIIIURWUzTwfBYETgE0YJJfN+65fe+kx10JD4cPP4SdO3Wvx4zRJdPNzLhxA1q00A1v5+ICBw7oPh8JIYQQQqSFJNFziSJFiqS6TunSpTMhkvTZvHmzsUMQIsfavh3WrdON9blmDSQyr2+2EhERTvPmZbGz8+Pzz1VUrryeggV7GjssIYQQQmS1mFvwpA9E/aN7bdtZ1/vc1CnpOvfvQ/v2cPkymJvDypW6hDpw8yY0aQJPn0LFirB/P6ThckkIIYQQQk8G1hFCiFzA3x/+mx+QceOgfn3jxvM2ERFhNG9elr//9uPECbCwmCsJdCGEEOJdoygQ/BP4VtMl0NUOUOhnKLI1+QT6hQtQp44ugV6wIBw9qk+g374NTZvqEuhVq8Jff0kCXQghhBDpJz3RhRAih1MUXQI9MFB3sThlirEjSl5ERBjNmpXln3+eYmUFmzdPpWHD0cYOSwghhBBZSRsOTz+G0F90r62bQqE1YFYs+XqHD0PHjroJRN3cYPdu+G84Sx8fXQ/0J0+gcmU4eFA3x6gQQgghRHpJT3QhhMjh1q6FXbvAzAx+/hksLIwdUdJeT6BbW8OWLdNo23aSscMSQgghRFaKvgr3av+XQDcBp5lQ7MDbE+hbtoCXly6B3qQJHDumT6A/fQrNm+vmhqlQAQ4dAqdkOrMLIYQQQqSGJNGFECIHu38fhg/XPZ82TdcTPbsKDw+lWbMy+gT65s3TadPmK2OHJYQQQoisFLJBl0CPuQGmhaH4Ecg3HlRvuTT94Qfo0QNiYqBLF/j9d7C3ByA0FFq3hnv3oFQpXWf1AgUy/1CEEEII8e6QJLoQQuRQWi3076/rjFW/Powda+yIkqYoceza1Z0LF/z/S6B/TZs2Xxo7LCGEEEJkFUULARPArzcoL8GmJZS4CNbub6+7bBl89JFuDLuPPoJNm8DSEniVU794UZc4//NPcHbO5GMRQgghxDtHkuhCCJFDLVoER46AtbVuSBcTE2NHlDhFiePGjX4UKfIn06er/0ugTzR2WEIIIYTIKnGh8LgjvPhW9zrveCj6O5imoLv4smXwySe65599BkuX6j/0KAoMGqQb+9zGBvbu1fVEF0k7duwY7dq1o3DhwqhUKnbu3PnWOkePHqVGjRpYWFhQunRp1qxZk6DMkiVLKFGiBJaWltStW5czZ85kfPBCCCGEEUkSXQAwZcoUqlWrZuwwhBApdOMGjB+ve/7dd1C6tHHjSUp4eCgHDnTB3/8XVCpTBgzYLAl0IXKxp0+f0qJFC2xsbHB0dDR2OEKI7CD2IdyvD+G/gcoCCv0CBWaCKgXf/r+ZQJ8zB1Qq/eq5c3XzwZiYwLZtUKtWJh1DLhIREYGbmxtLlixJUXlfX1/atGlDkyZN8Pb2ZuTIkQwaNIg///xTX2bTpk2MHj2ayZMnc+HCBdzc3PD09CQgICCzDkMIIYTIcqbGDkAYz8uXL8mfPz+XLl3KkO35+fnx2Wefce7cOe7cucPw4cNZsGBBhmxbCPFKbCx8+CFERYGnJwwdauyIEhcaGkyzZuW4dy+ABQtMaNlyE05OnY0dlhDZ3rFjx5gzZw7nz5/Hz8+PHTt20LFjxwTlrl+/zueff85ff/2FRqOhYsWKbNu2jeL/TbJnDPPnz8fPzw9vb28cHByMFocQIpuIvgoPPUHzGEwLQZGdYFUnZXXXrUs2gb5vH3z+ue75woW6z0Ti7by8vPDy8kpx+eXLl+Pq6sp3330HQIUKFThx4gTz58/H87+TPm/ePAYPHkz//v31dfbu3cuqVasYH9/rI6MpCqAF/vupKK+eo+iGD9K/fn1ZIs/RJiyvJLMuyW0lsW1U6Povqv8b+z+x5yZvL/N6OZUaMDFcpgBKJGijQGX2Wp1XfzfvNP3vyGu/K2/+3qCAVotKiQTtS3TnWPXf+Y5/H1VyTkXWUP77f6Ik9juroPtdtJDfxywkSfR32IEDB3BxcaF0BnVhjY6OxsnJiS+//JL58+dnyDaFEAnNnAnnzoGjI/z0U/ZsM0NDg2natCznzz/Dxgby5/9GEuhCpFB8L8EBAwbQuXPifzc+Pj40bNiQgQMHMnXqVOzt7bl69SqW/40RbCw+Pj7UrFmTMmXKGDUOIUQ2EHkSHrUFbTCYV4Bif4JZsZTV/f13GDBA93zkyAQJ9Js3oWfPV8O5xOfaRcY7ffo0zZs3N1jm6enJyJEjAYiJieH8+fNMmDBBv16tVtO8eXNOnz6d5Hajo6OJjo7Wvw4NDQWg0JTCqM1MUGtNUGvVqOJ/xplgGmuJSYzuoY6x1j9UMTaoXuZFicyHNrIAcZEF0UQ6E/OyELExDqh4PQFqSIWiW5VKKpTUV8qUegqgee21HRCRifszQr1k3p/Mi9MCCM7ifWZwPVV2iPN+Fu8vBfWyxXlJTd3QVNXQ11O9ev32n/+9ev3cqE1ArQYTte6nWq1bZmoCJqZgagqmJphYmGLvqMbODhwcdPN929tDnjwKzs5QqBAULqz76eSk20xW0Wq1Gb5NSaLnIjt27KBnz548evQIJycng3Vjx47l4MGDXLx4Ub9s165dtG/fPtFt+fj40KJFC1q3bs2iRYtQqVSsWLGCadOm8fz5c1q0aEGjRo2YPn06wcHBAJQoUYKFCxcCsGrVqsw5SCHecefPw/TpuudLl0KRIsaNJzFvJtC3bv0WT89xxg5LiBwjJb0EJ06cSOvWrZk9e7Z+WakUDAS8atUqvvvuO+7cuUPevHnp3Lmz/q6xBw8e8Omnn3Lo0CHUajWtWrVi0aJFFCxYUF9/165dTJ06lWvXrlG4cGH69u3LxIkTMTU1pUSJEty/r7tYWrduHX379k103FwhxDsgfC887gpKFFjVg6J7wCRvyur+/Td07QpxcfDBB7px615LoEdEQKdOEBICDRrAkiXZs0NBbvH06VODdgCgYMGChIaG8vLlS4KCgoiLi0u0zI0bN5Lc7syZM5k6dWqC5VFWLyEDvw82jTXFOtwBq9C8mIcWQB3mDKFFiQstTkxoSSKCKxERXgoZ6TYbS3sOUghhNAkbZnNzBReXOEqW1FCqlAZX1zjKldNQqVIs1tYZH0FISEiGb1OS6G+hKApabaRR9q1WW6NKxSfCtWvX4uXllSCBDtCrVy/mzp3L5cuXqVq1Klqtlj179iQ6kczly5fx9PRk4MCBfP311wCcPHmSjz76iFmzZtGuXTv279/PlClT0npoQog0ePlSN4yLRgPdu+t6YGU3ISFBNG1algsXArGxgW3bZkkCXWQbigKRxmnSsbbOuCSPVqtl7969jBs3Dk9PTy5evIirqysTJkxIdNiXeMuWLWP06NF8++23eHl5ERISwokTJ/Tb7NChA7a2tvrhYf73v//Ro0cPjh49CsDx48fp06cP33//Pe7u7vj4+DBkyBAAJk+ezNmzZ+nTpw/29vYsXLgQKyurjDlgIUTOErZbl0AnFmzaQpFNoE7h1fGNG9Cmje5Dj5cXrFqVoNva8OFw/bquV9vWrWBunvGHIDLfhAkTGD16tP51aGgoxYoV46c887GwsESj1aCJi0Oj1RIbF0dMXAyRMS8Jj40gUhNFhCaSiLhIIrUvidRGEkoYoapQwkzDCDcPJ9IyEo2pBo2ZhtA8zwnN8xy4nWgs5jHm5AvPh3OMM4XVRXGxdMHVsSTlC1bCtZArahPD30FFm7asbprrofpvCIdEN0r80A5arYbQ0GDs7W1Ro8tlQJx+vcGwM68Ph6No/yun256iKKDE10tm2BslvpenCl3fV9V/CW/da90Hn9d7vKoxTKzpXiuKymA7r+q/uey/16rX66n0o1okrJ/Y/nlVL7F9AloUwkJDsbO3i6+hf+jOzRvDwiQYJiZ+GfpzpwBo489d/Da1r5VTXlv3im516n9vlPjjU14tSZjUVCV4rn8vEuzyzfP1+irVf3HG/56q0KIlIjwSG1tb1InsJ/5D8av3Pql9vR7Mq5+vTtvr558ky8c/V14vE1/P4By9eeC6cq+WJtaTO7Hfpfja6lfrDP42SKLOq78lrVYhMiISaxtr1GqTJMoDSgxoo4FoUGJQtLqfKNGgjUClDQclHOIidD+14aANRqW8uhMI3ngv4kCJNoHofBDtiBLjgCrGDiLNIeQlvHihezx/jiY6jjDsCMGBUOz1j0Dy40ch/EyL80RdhGcxDsTEqLl925Tbtw1T0Wq1QoUKUKMG1Kql4O4OVaqkv9e6eSZ8QJAk+ltotZEcP25rlH27u4djYmKTorJarZbDhw8zc+bMRNfXqFEDBwcHDhw4QNWqVfn7778BqFu3rkG5U6dO0bZtWyZOnMhnn32mX75o0SK8vLwYM2YMiqJQsmRJ/vnnH/bs2ZPGoxNCpNaXX+ouGp2ddb3Qs1uvqzcT6Dt2zKFFizHGDksIvchIsDVOk054ONikrEl/q4CAAMLDw/n222/5+uuvmTVrFvv27aNz584cOXKExo0bJ1rv66+/5rPPPmPEiBH6ZbVq1UKj0XDo0CGuXLmCr68vxYrphltYt24dlSpV4uzZs9SuXZupU6cyfvx4+vbtC0DJkiWZPn0648aNY/LkyTg5OWFhYYGVlRXOzs4Zc7BCiJwlbBc87gbEgl13KLweVCm85HzxAtq10/2sWxe2bAEzM4MiGzbo8uoqle65/KvJfM7Ozvj7+xss8/f3x97eHisrK0xMTDAxMUm0THJtgYWFBRYWFgmWdx7SL0MmptZqtYSEhPDg0QN8Hvrg+8SX+4H3eRz2mKcvnxKgBPDc5DnBNsHEmMfgl9cPP/y4yH93bmsBP7D0taRwZGFKmZaiQr4KVC9ZnfrV6lO6bGnUWTkuQQpotVoCAgIoUKBAtostJ5HzmH5yDtMv089hXAhoHkLsA90E4Jr7EHMLYm7qfioxidczLQIW1cGqNlg1BE1FePwCfHxePe5668Zd8/HRjzYViymPKMptynDLrha3CzTgpmklLgUW5ulzc65ehatX4eefdUmOvHmhcWPw8IAWLaB8+dTnPzLjvEkSPZcICAggLCzMYHzzDz/8kA4dOtC1a1dAd5v37du6b9937dpF27ZtDX6pHjx4QIsWLZgxY4Z+jLt4N2/epFOnTgbLateuLUl0IbLIX39B/FQDK1dCvnzGjedNWq2Gq1f7Exoan0CfS4sWn729ohAi1eLH9+vQoQOjRo0CoFq1apw6dYrly5cnmkQPCAjgyZMnNGvWLNFtXr9+nWLFiukT6AAVK1bE0dGR69evU7t2bS5dusTJkyeZMWOGvkxcXBxRUVFERkZinRn3YQohco6w3a8l0HtA4V9SnkDXaKBHD7hzB1xc4LffEnzzeOcOfPSR7vlXX+kurEXmq1evHr///rvBsgMHDlCvXj1A19OvZs2aHDp0SH83lFar5dChQwwbNiyrw9VTq9XkyZOHPHny4FbFLclyL6NecuX6Fa7cvML1x9fxee7Dg6gHPFY95pntM6Iso7hreZe73OVA7AG4CdwEm0gbXF+6UtmmMnVK1KFJrSZUrVY1Qa91IYTIlkwcdA+LygnXKXEQex9ibugmCI++CFEXdMl1zWPdIyI+F2gC1jWgTkNo3ACsPwDT/LpV4eFw5QpcuoTZpUu4XriA68WjtAw7AGGvdvfEvjwXKvfhfN4W/B1WkRPnrXnxAnbs0D0ASpfWfc/evj00bKgbkt0YJIn+Fmq1Ne7u4Ubbd2ppNK8mFfH29qZ69eqvbU+tHx5m9+7dfPvttwZ1nZycKFy4MBs3bmTAgAHY29unMXIhREYKDtYN4xI/eVabNsaOyJBWG8v1672JidnFd9+ZYmc3lyZNRry9ohBZzNpa91nOWPvOKPnz58fU1JSKFSsaLK9QoYJ+eJY3ZcTQKuHh4UydOjXRyU6NPaGpEMLIIo7Ak/gEek8o/HPKE+gAo0fDwYO6xPnu3brZx16j0eiGRw8Lg0aNdEl0kTbh4eHcuXNH/9rX1xdvb2/y5s1L8eLFmTBhAo8fP2bdunUAfPTRRyxevJhx48YxYMAADh8+zObNm9m7d69+G6NHj6Zv377UqlWLOnXqsGDBAiIiIujfv3+WH19qWVlaUad6HepUr5NgXVR0FGe9z3Lm6hkuPbzEzdCb3OMez2yfEWEdwb/W//Iv//Lr019hD1hvtqbUy1JUtqlMw1INadO4DS5lXIxwVEIIkQ4qEzAvqXvYtn61XBsOUZd0CfWovyHyBGgeQNRZ3SNoPqACy5pg01L3eK8e/PelK6Abru3cOTh1Svc4dozCwTcofOoL2vIFALFlKnKhzkcctW/PodvF+euYijt3dJ0K58+HPHl0U6f07g3u7lk7Wakk0d9CpVKleEgVYypQoADW1tbcunWLNm3aEB0dze3bt7l27Rqg6w3g6+tL165duX37Nvfv36dFixYG27CysmLPnj20bt0aT09P9u/fj52dHQDlypXj7NmzBuXPnTuXNQcnxDvuf/+Dhw+hVKlXvdGzi+Dg56xa1ZYaNf5GpTKjfv1t5M/fzthhCZEolSrjhlQxJnNzc2rXrs3NmzcNlt+6dQsXl8Qv1u3s7ChRogSHDh2iSZMmCdZXqFCBhw8f8vDhQ31v9GvXrhEcHKxP1teoUYObN28a3PUmhBBEXYTHHXS3ftt2Tn0C/eefYdGiV8+rVk1QZP58+OcfcHCA9euN1wMtNzh37pxBOxA/Lnn8ZNB+fn48ePBAv97V1ZW9e/cyatQoFi5cSNGiRVm5ciWenp76Mj169ODZs2dMmjSJp0+fUq1aNfbt25dgstGcxtLCEve67rjXdTdYHh4RzolzJzh++Tjnnpzjesx1Hts8JtI6kivWV7jCFTY+3sj/1v+PQkGFqKyqTIMiDWj1XitqvVcLEzOTJPYohBDZmNoWrBvoHnyqWxb7AF6e1CXUXx6D6H8h6pzu8fwbUNmAdROwbQt27cGqkC7z7f7f/9W4OF1Sff9+3eP0acxuX6Pu7eHUZTifFypE2Ic9OFCkH7t9q7D3DzWBgbBihe5RrBj06gV9+kClSpl/CuTjRy6hVqvp0KEDixcvpnHjxmzbto2mTZuyY8cOBg4cyJEjR3jx4gXt2rVj165dNG/ePNHbrm1sbNi7dy9eXl54eXmxb98+bG1t+fTTT2nUqBHz5s2jbdu2HDx4kD/++CPBxKfe3t6ArofDs2fP8Pb2xtzcPEFvOSFEymzYoHuYmMAvvxhvPOfEBAc/x8OjLJcuveCzz0wYP347+fO3NXZYQuR4b+slCDB27Fh69OhBo0aNaNKkCfv27eO3337TTwKamClTpvDRRx9RoEABvLy8CAsL48SJE3z88cc0b96cKlWq0Lt3bxYsWIBGo+GTTz6hcePG1KpVC4BJkybRtm1bihcvTteuXVGr1Vy6dIl///1XPxH5m/r06UORIkWSnLNFCJHDxfjAQy/QhoFV49SNgQ66yV7ix2iZMgXeGD4SdHONxvc8nz8fihZNf9jvMg8Pj/8mnEzcmjVrEq1z8eLFZLc7bNgwow7fkpVsbWxp1bgVrRq30i+LjIrk2JljHLt0jDNPznAl7goBNgH6sdYPRB5gyuEp2O+yp9LLSjQq2IiODTpSu1FtSaoLIXIus+K6h30v3WuNH0QcgIj9up9xAbqhXyL2gP9HYFkX7DqCbUewKK9LdNStq3t89RWEhMCBA7pxXPbsAT8/7H5aQGcW0LlAAeJ69uKvih+z/mxZtm5T8fAhzJ6tezRoAEOHQrdukGk3ySrvmJCQEAVQgoKCEqx7+fKlcu3aNeXly5dZH1gGCAgIUFq1aqVYWFgoVapUUW7evKl89913ioODg1KwYEFl+fLliqIoSsOGDZUVK1YY1J08ebLi5uamfx0WFqbUr19fadSokRIeHq4oiqL8+OOPSpEiRRQrKyulffv2yvTp0xVnZ2eD7ZBgWmoUFxeXTD3ut8mu72tcXJzi5+enxMXFGTuUHCu3n8N79xTFwUE35fiUKZmzj7Sew6CgQMXNLa8CKHZ2KIcOLcicAHOAoKAgBVBCQkKMHco7J7e26UeOHEm0Pe3bt69BuZ9++kkpXbq0Ymlpqbi5uSk7d+5867aXL1+ulCtXTjEzM1MKFSqkDBs2TImJiVG0Wq1y//59pX379oqNjY1iZ2endOvWTXn69KlB/X379in169dXrKysFHt7e6VOnTrKjz/+qF/foUMHgzgbN26cIO54Ofk9elNub4+ygpzD9Mvyc6gJVhSfcopyHUW566Z7nRoREYpSqZLug07z5oqi0STchUZR3ntPV6RVK0XRajMm9KRIm248ybXpOdV9//vK0s1LlW5TuymlxpRS1F+pFaZg8Mg3PJ/S/JPmyjfffqNcP3Nd0cal/Zdc/o9mDDmP6SfnMP1yxTnUxinKy4uKEviNovjW1X1eeP3hU05RAiYoysvLidePilKU339XlMGDFcXJSfdhIP5RvrzycvJMZeuyAKVjR0UxMXm1Km9eRRk1SlHOns34Nl2lKMl8DZ0LhYaG4uDgQFBQUIJZv6OiovD19cXV1TXXju0ZGBhIoUKFePToUZpvr1MUBY1Gw8cff8zNmzc5fvx4BkeZsbLr+yozVqdfbj6HcXHQrJluQtH33oPjxzPn1uW0nMOgoEA8PMpx+fIL7Oxg586FNG06POODyyGCg4PJkycPISEhMpdEFnvX2/SMEN+mm5qaJri7LLPlpvcoN7dHWUXOYfpl6TlU4uBRO4j4A0yLQokzYFooddsYOBBWrQJnZ/D2hkSuTRYtguHDwc4Orl7V3badmaRNN57k2vTcIiI6gn0n97H3/F5OBJ7gjuUdFPVr6RgFigUUo56qHh2qdqBth7bYO6f891D+j2YMOY/pJ+cw/XLlOYx9AuG7IXwXRBwCYl+tM68E9j11PdrNSyVSN1Y33Msvv8DOnRAV9Wpdy5b4dRvOqiet+PEnE16NSBYKOGRomy7DubxjXrx4wbx589KUQJ87dy4tWrTA2tqavXv3sm7dOpYuXZoJUQoh5s7VJdBtbHTtRHYZ+zMo6Nl/CfQgSaALIYQQ76pnX+gS6CpLKLoz9Qn03bt1CXSVSjduXSLXJv7+8OWXuuezZmV+Al2IzGZjYUOXpl3o0rQLAMGRwez8ayd7L+zldOhpHls/5mHBhzzkIZufbsZ2ri3VgqrRsmhLenj2oMx7ZVCps/YLbyGEyDBmhSHPR7pHXAhE/A6hm3U/Y65C4Fe6h2VtXTLdvuerzxdmZtCmje4RGgrbtunmUTlyBPbvp9D+/Ux0dmZ8v4HsK/Mpy7YXZO/ejO8znku+zhApVbZsWT799NM01T1z5gwtWrSgatWq/PjjjyxcuJBBgwZlcIRCiAsXXo39+f33uglFs4OXL8P0CXR7e9i1a5Ek0IUQQoh3TegWeDFb97zQarCsmbr6z5/DkCG652PHQiKTHQNMmKC7Tq5R41VxIXITR2tH+nn1Y8vELTya9YgHwx4wu8Js3BV3LDQWhNuFc6L4CSapJ1Hxj4qUH1yej4d9zF8b/yImPMbY4QshRNqZOOgS5UV3QGl/cF4F1i0ANUSdhYDRcKcoPGwDoVtBG/2qrr099O8Phw+Djw+MHw8FCsDTp5h8O4M2gwqxJ86L8/OOZnjY2aRvo8gJNm/eDBje+i2EyFiRkdC7t+5upc6ddW1DdqDVxnDnzofUqBHEvXuwa9diPDz+Z+ywhBBCCJGVYu7B08G653nH6XqJpdb//qfrZl6xIkydmmiR06dh9Wrd88WLdfOOCZHbFctXjLHdxzKWsURrotl3cR+bjm3i8PPD+Fv4c6v4LW5xix9u/IDLARc81B70eq8XDTs1xDqftbHDF0KItDFxBMf+uofGH8K2Quh6eHla10s94ndQ5wX793VlLKrr7mQDKFkSZs7UfZ7YvRt+/FE3Mem+fZTety/DQ5We6EIIkY2MGwc3bkChQrr//1k8RHGitNoYrl7tzvPnu+jXz4K//94gCXQhhBDiXaPEwpNeoA0Bq3rg9HXqt7FjB2zapMuKr1sHicyHoCi6cdBB15mgXr10xi1EDmRhakGH2h3Y8NkG/Gb48e+QfxnnOo6ycWVR1Ar3XO6xptgaPB97Uv7z8rzf9332Lt5LxNMIY4cuhBBpZ1oQ8vwPXE5ByZuQbwKYFgHtCwheDPdqwr1q8GI+aJ69qmduDl276sZNv3MHxoxByYT5NSSJLoQQ2cTvv8OSJbrna9ZAvnxGDQeAFy8C+OCD8jx6tAuVyoIqVXZRoUIvY4clhBBCiKwWOBWi/ga1AxTaACqz1NUPD4cRI3TPP/8caiY+DMy2bXDuHNja6jqXCfGuU6lUVCpUiVl9ZnFz2k3uDr/LlCpTqEQlAB4We8jGkhtp/6I9zRc0Z2CPgRxedJiIAEmoCyFyMPOy4PQNlLoPRfeBXQ9QWUD0Zd1wLz5F4XEviDiq+wY+XqlSMGcOytWrGR6SJNGFECIbCAiAAQN0z0eMgJYtjRsP6BLojRuXY+NGX779Vk2VKrvJm9fT2GEJkSpardbYIYgkKErGT/YjhMgkURfg+be6584/gnmJ1G9j+nR4+BBcXV/NGPoGjQYmTtQ9/+yzROcbFeKd55rHlcmdJ/Pv5H95NOoRM2vNxE3tBiq453qPNZXX0DKgJXU+rcOonqM4u+Ys0aHRb9+wEEJkRyoTsPWEIr9CaT8ouBQsa4ESA2G/wsMm4Fsenn8HmsBX9awzfpgrGdRaCCGMTFFg8GDd8KCVKmWPXlfPnz+lcePyXL0agoMDfP31UvLmzQaZfSFSyNzcHLVazZMnT3BycsLc3BxVdhgfKZt5fZ6TrDw/iqLw7NkzVCoVZmap7M0qhMhaSiz4DQTidL3A7LunfhvXrsG8ebrn338PVlaJFluzBm7dgvz5YfToNEcsxDujiH0RxrcZz/g24/F94cuSg0vYdnMb90zvca3iNa5xjR+u/0DlDyvTyb4T7Tu0p1zbcphaSipICJEDmeSBPB/rHlEXIPhH3fjpMbfg2RgI/ALsuoLjEFCqZvju5T+nEEIY2cqVujkwzM1h/fokryuzzJsJ9D17fqRhw8HGDUqIVFKr1bi6uuLn58eTJ0+MHU62pSgKWq0WtVqd5V8yqFQqihYtionMGChE9vbiO4j21k3qVfD7tG1j9GhdN/MOHaBt20SLREXBlCm65xMngr192nYlxLvKxdGFMY3GMKvLLK48u8KKv1aw6cYmnls/52yNs5zlLAsPLaTOojq8X/F9GvZrSJE6RaSTgRAiZ7KsAc7LwWkOhG2EoB8g+gKEboDQDaiiy2T4LiWJLoQQRnTrFowcqXv+zTfg5mbUcHj+/CmNGpXn2jVJoIvMFxwcTPPmzdFoNGg0GkaMGMHgwRn3+2Zubk7x4sXRaDTExcVl2HZzE61Wy/Pnz8mXLx9qddaO8mdmZiYJdCGyu9hHEDhN97zgfDAtkPptHDoEf/4JZmbw3XdJFlu3Dh4/hqJF4aOP0hivEAKVSkU152os6bGE77Xfc9j3MMuPLue3h7/h7+zPb86/8bvmdyrOrkiTwCZ0a9MNtw/dsCtkZ+zQhRAi9UzsdD3PHYdA1HldMj10A6rY2xm+K0mi5xIeHh5Uq1aNBQsWZMj27t27h6urKxcvXqRatWoZsk0hhKGYGOjdGyIjoWlTGDXKuPFotdG0b19Vn0Dfu3cFDRoMMm5QIlezs7Pj2LFjWFtbExERQeXKlencuTP5MnBW3fjhQmTIkMRptVrMzMywtLTM8iS6ECIHeDYBlJdg1RDsP0x9fa1WN4ko6DLjpUolWiwuDmbP1j0fMwYsLdMYrxDCgInahBalWtCiVAtevHzB+svrWXp8KTcibnCl6hWucIVfHv1Cze416ZK3C+593CnXrhwm5vIltxAiB7KsCYV+hAJz0T5cAYzJ0M1ni6ulJUuWUKJECSwtLalbty5nzpxJUb1ff/0VlUpFx44dMzfAHO7q1at06dKFEiVKoFKpkk209+/fny+TmOgnLWbMmEH9+vWxtrbG0dExw7YrRG7w1Vdw7hzkyQNr14Ix81dabRT//tuZ/v2f4eKiYu/elZJAF5nOxMQE6/8mfImOjkZRFJlsUgghsouX/0DoL4AKCi6AtAz5sHUrnD8PtrZJTiYKsG0b+PhA3rwwSD5+CJEp8lrl5dO6n3Lts2ucHXyWQVUGYaOy4UW+FxxofoBhVYbxwboPGF11NPvH7Of57efGDlkIIdLGxB4cB2b4Zo2eRN+0aROjR49m8uTJXLhwATc3Nzw9PQkICEi23r179xgzZgzu7u5ZFGnOFRkZScmSJfn2229xdnZOslxcXBx79uyhffv2GbbvmJgYunXrxscff5xh2xQiNzh48FWPq5UrdbcuG0tc3EuuXu3Cixe/U7asFefO/UmDBhnf4Iic59ixY7Rr147ChQujUqnYuXNngjJp/SI8XnBwMG5ubhQtWpSxY8eSP3/+DIpeCCFEugT814Pcoa+uZ1dqabUwdaru+ZgxUCDxoWAUBb79Vvd8+HCwsUlDrEKIFFOpVNQqXIsVnVfgP96fle1WUtmxMhozDRdrXOT7Xt8zKGgQQzsPZVWLVVzbeo24WBkWTwghjJ5EnzdvHoMHD6Z///5UrFiR5cuXY21tzapVq5KsExcXR+/evZk6dSolS5bMwmhzjr179+Lg4MD69eupXbs2c+bMoWfPnlhYWCRZ59SpU5iZmVG7du0E6+Li4hgwYADly5fnwYMHANy4cYOGDRtiaWlJxYoVOXjwYIIky9SpUxk1ahRVqlTJ8GMUIqd69gw+/O+O6KFDoXNn48USGPiEdu2qc+zYPtRqK6pU2Uv+/C2MF5DIViIiInBzc2PJkiWJrk/JF+HVqlWjcuXKCR7xk306Ojpy6dIlfH192bBhA/7+/llybEIIIZIR+Re8/AtU5pB/etq2sXs3XLummyE0fgKYRBw/DhcvgrU1DBuWtl0JIdLGxtyGgTUGcnn4ZU4OOEnPSj0xxZSHxR+yres2RriN4JMlnzC97HQOf3mY4PvBxg5ZCCGMxqhjosfExHD+/HkmTJigX6ZWq2nevDmnT59Ost60adMoUKAAAwcO5Pjx48nuIzo6mujoaP3r0NBQQDcGqFarNSir1Wr1t5K/eTt5REREkvswMTHB8rWB+5Irq1arsbKyemtZmzR0wYiPe8OGDXz88cesX7+etm3bJjiWpG6X37VrF23bttWXif8ZFRXF+++/z7179zh27BhOTk5ERUXRqVMnihcvzt9//01YWBhjxoxJcvuvby+rxceT2HtuTPG/b9kpppwmJ55DRYF+/VQ8faqiYkWFuXMVjBX+s2ePady4EjdvhhEQoOL8+Z04ODTOUeczO8jN58vLywsvL68k17/+RTjA8uXL2bt3L6tWrWL8+PEAeHt7p2hfBQsWxM3NjePHj9O1a9dEy6SmTRcpkxP/j2ZHch7TT85h+mXkOVQ9m4oKUOwHoJgUJtUfVhQF1cyZum188gmKnV2S21i6VAWoeP99hTx5jPe5CHJ3my5EclQqFfWL1ad+sfrM85zHigsrWPbPMp7ylL88/uKE5gTVvKtRr2Y96r1Xj1of16KMVxlU6jQM8ySEEDmUUZPogYGBxMXFUbBgQYPlBQsW5MaNG4nWOXHiBD/99FOKL8pnzpzJ1PjbCF/z7NkzYmJiDJbFxsai1WrRaDRoNBqDdXZ2Sc9U7eXlxa5duwzij4yMTLRso0aNOHjwoP61q6srgYGBCcq9GdvbxCeKFy1axKRJk9ixYweNGjVKcByA/hjftGvXLubOnWtw/CEhIbRp04bo6Gj279+Pg4MDsbGx7N+/Hx8fHw4cOKAfImbq1Kl4eXkRFxeXYPvxH0gT229m02g0aLVanj9/nq0mltNqtYSEhKAoikzmlkY58Rz+9JM1v/9uj4WFwqJFzwkP1xAenvVxBAb60aVLI27dCidPHlixYh6KUvWtQ2mJhEJCQowdglGk9Yvw1/n7+2NtbY2dnR0hISEcO3Ys2eG/UtOmi5TJif9HsyM5j+kn5zD9MuocmmnOku/lERTMeKYMRJuGzwbmx4+T98wZFEtLnvXuneQ2nj1Ts327EwDduz8nICDrrxVe96626UK8rpBdISY1nsSEhhPYfn07353+jrNPznK+1nnO1zzPgZsHqP9JfapZVKPup3Wp1q8aFnZJ3/EuhBC5hVGT6KkVFhbGhx9+yIoVK1I8ZuqECRMYPXq0/nVoaCjFihXDyckpwUSXUVFRhIWFYWpqiqlpyk+NSqVKcfmUlk3N/uO3u337dgICAjhx4kSiQ7LEU6vVCbZ//fp1/Pz8aNmypcHxf/jhhxQtWpRDhw4Z9KC/c+cOxYoVo+hrAznXq1cP0PXMf3P78R/kU3tcGcHU1BS1Wk2+fPkM7hgwNq1Wi0qlwsnJSS4W0yinncPLl2H6dF1vjdmzFTw88holjoCAR/oEet68sH79Apo3/1+OOIfZkbm5ubFDMIq0fBH+pvv37zNkyBD9F8GffvppssN/paZNFymT0/6PZldyHtNPzmH6ZdQ5VD35WffE/gPyO9dI2zZ+/m8bAwaQv2LFJMv99BPExqqoW1ehWTPjfC563bvapguRGDMTM3pU7kH3St058eAEc0/PZffN3dwsf5Ob5W9S9GFR6i+rj9tXbtToX4O6n9YlT8k8xg5bCCEyjVGT6Pnz58fExCTB+Kf+/v6JToDp4+PDvXv3aNeunX5ZfA9nU1NTbt68SalSpQzqWFhYJDoOuFqtTvDhUq1Wo1Kp9I/XhSfTVdTExMSgfHI9OeP3Ee/evXuJlntz/ylRvXp1Lly4wOrVq6ldu3aS20js+H777TdatGihT5THr2/dujW//PILf//9N02bNgV0vd7j17++ndeXvbn9xMpnlfh4EnvPjS27xpWT5JRzGBkJ778P0dHQti18+qkaI/w54O//kMaNK/2XQFexZ89qXF09c8Q5zK7kvKVdnTp1UnxnGaSuTRcpl1P+j2Z3ch7TT85h+qX7HMY+gvDtum3lHYEqLdt58AD27tVtY9iwJLeh1eomVwf4+GMV6mwwLIT87gmRkEqlwt3FHXcXd24E3mD+6fmsvbSWR8UesbnHZg4+P4j7UXdOLTpFxTYVqTuiLiWalDDKtb8QQmQmoybRzc3NqVmzJocOHaJjx46ALil+6NAhhiUyq0z58uW5cuWKwbIvv/ySsLAwFi5cSLFixTIt1tSMUZ5ZZd+mVKlSfPfdd3h4eGBiYsLixYtTXHfXrl0MGTIkwfKPP/6YypUr0759e/bu3Uvjxo0BKFu2LA8fPsTf31/fC/Hs2bMZcyBC5EKjRsH161CoEKxejVES6HFxLxk3zl2fQP/997XUrt1bhnARaZLaL8KFEELkAME/AHFg1Qgs3dK2jR9/1GXImzSBChWSLHb6NNy7B7a20K1b2nYlhMha5fOX54d2PzCtyTSWnF3CkrNLeJHvBbs67uKvxn/R8ERDrra8SuGKhak3uh5V3q+CibmJscMWQogMYfThXEaPHk3fvn2pVasWderUYcGCBUREROgnKevTpw9FihRh5syZWFpaUrlyZYP68bdvv7n8XVW2bFmOHDmCh4cHpqamLFiwgJiYGK5duwboxrB9/Pgx3t7e2NraUrp0aQICAjh37hy7d+9OdJuffvopcXFxtG3blj/++IMGDRrQvHlzSpUqRd++fZk9ezZhYWF8+eWXgGFv8wcPHvDixQsePHhAXFycvsdh6dKlsbW1zdyTIUQ2sX277npSpYKff4YUjkaVoeLiIvn33w707n2fwEBTJk9eTZ06H8gEWiLNUvtFuBBCiGxOiYOQ1brnef6Xtm3Exr7evTzZohs26H527gzW1mnbnRDCOAraFmRak2mMazCOZWeXMff0XAIIYE+7PRzzOEb9E/V5NOQRh788zHsj36PmkJpY2Mu46UKInM3oSfQePXrw7NkzJk2axNOnT6lWrRr79u3T925+8OCB3FaXSuXKlePw4cP6Humffvop1atX16+fO3cuc+fOpXHjxhw9epTffvuNOnXqJDvO/MiRI9FqtbRu3Zo//viDOnXqsGPHDgYPHkzt2rUpWbIkc+bMoV27dgbjjk+aNIm1a9fqX8fHEZ/oFyK3e/gQBg3SPR83Dpo1y/oYgoKecu9eb0JCDmNpacP69ftwdGyY9YGIHCc8PJw7d+7oX/v6+uLt7U3evHkpXrz4W78IF0IIkYNE/gWax6B2BNsOadvGgQPg7w8FCsB/X7AmJjYWNm/WPe/dO227EkIYn625LWMbjOV/df7HygsrmX1yNo95zD6vfZxofIJ6J+rx/IvnHJt+jFof16Lu8LrYFbYzdthCCJEmRk+iAwwbNizJXmtHjx5Ntu6aNWsyPqAc6M3zVKFCBYNb7BVFSbLurl27aN++vcGyEiVKJKgzevRoRo8ejaIoaDQaypcvz4kTJ/TrT548Ceh6mcdbs2aNvEfinRUXBx98AEFBULs2TJ+e9TH4+d2jUaPKVK0awYgRNlStKgl0kXLnzp2jSZMm+tfxk3r27duXNWvWvPWLcCGEEDlIaPyEot1BncYeo/Hdy3v2BDOzJIsdPAiBgbpc+3/TLgkhcjBrM2uG1x3O0JpDWeO9hpknZnKf+xxoeYC/G/1NgyMNCP8unNPzTlP1w6rUH1MfpwpOxg5bCCFSJVsk0YVxNWzYkF69eqW63o4dO7Czs6NMmTLcuXOHESNG0KBBgwSTuwrxrvrmGzh2DOzsYOPGZK8lM4Wf3z3c3Svj4xNBUJCKmTM3SAJdpIqHh0eyX8JC8l+ECyGEyCGUGAjTTSiK/Qdp20ZEBOzcqXv+lmuLLVt0P7t3B1O5IhUi17AwtWBoraEMqD6AXy7/wtfHv+Zu0F32ee3jnyb/0HB/Q2LXxOK9ypty7cvRYHwDitXLvLnthBAiI8lHFsG4cePSVC8sLIzx48fz4MED8ufPT/Pmzfnuu+8yODohcqaTJ2HqVN3zpUshq79b8vPzxd29Cj4+EeTLp2LfvvWULdv+7RWFEEII8e6JPA7aUDApCFYN0raN337TJdJdXaFu3SSLabXw+++65x3SOGqMECJ7MzMxo3/1/nxQ9QNWe69m2l/TeMxjfmv/G2c8z9BgbwO0v2m5ufsmrk1dafRVI1wauxjMryaEENmNJNFFmvXp04e+ffsaOwwhsp3gYN34nvHDuXyQxg5daaVLoFfGxyeS/PlV7Nu3gZo1e2ZtEEIIIYTIGtooiL0LcZGYxMWCkhcwT902wvfqftq2BlUa56OK74Xeo4duNvUknD+vGzbd1hYaNUrbroQQOYOZiRlDag6hj1sflp9bzjfHv8Eff7Z33s65dueov7M+ymEF38O+FG9YHPcv3SnVspQk04UQ2ZLM2CmEEBlIUWDwYLh/H0qWhCVLsnb/T57cpWHDVwn0P//8VRLoQgghRG6jCYTnc+BePbhlA76VUD+ojVNYfVR38sLjXhB1PuXbi/gviW7TJm3xxMbCn3/qnrdrl2zRPXt0Pz09wTyVuX4hRM5kaWrJyPdGcnfEXb5p+g2Olo48MHvAr91+ZfMXm3ns+pgHJx6wvtV6VtZdyc3dN986pKAQQmQ1SaInQv5Z5y7yfoqstHw5bN2qG//811/B3j7r9h0XF8Hmze25dy8SJyddAr1Gje5ZF4AQQgghMldcCPh/Bj7F4dk4iPob0ILaHsW0CAqWqJQICPsV7tUC/1GgxCa/zZi7EHMLMAObFmmL69Qp3a14+fIlO5QLwN7/8vVt0pivF0LkXLbmtkxwn4DvCF8muk/E2sya6+bXWdF3BQcnHiSkUAhPzj7h1w6/8kP1H7i65SqKVq7nhRDZgyTRX2P236x/kZGRRo5EZKSYmBgATExMjByJyO28vWHUKN3zWbOgdu2s27dGE87ly62pVu0qU6ZYsW/fJkmgCyGEELlJ+F7wrQBB80B5CZY1oeBSKHUfygSjlHyAv4MP2mKnX00OGrQAHvcERZP0dl8e1/20qg0mafz2Pz4z7uUFyXzmfvFCN5xLfFEhxLvJ0dKRr5t+ze1PbzOw+kDUKjUnzE6w+OPFeH/pTaxTLP6X/NnafStLKy/l6mZJpgshjE/GRH+NiYkJjo6OBAQEAGBtbS1jcSVCURQ0Gg2mpqbZ/vxotVqePXuGtbU1pqby6y4yT1iYbgjQ6Gho2xZGjsy6fT965MPVq+9jYXEGExN7RozYj7198r3AhBBGoCgQ9xxi7+kecU8hLhS0YaBEgcoUVGagsgbTgmDiDGZFwbwcqK2NHb0QwlgULQROhudf616blYGCC8GmleHY44qiG8/cqg7YvAd2neFJTwjfDgHjoOC8xLf/8pTuZ1onFAU4eFD38y2Z8RMndD/LlQNn57TvTgiROxS2K8zK9isZUXcE4w6OY9+dfew03cmRUUfoEd2DYouLEXg9kK09tlKgSgE8pnpQvmP5bJ+HEELkTpJVfIPzf5/m4hPpIiFFUdBqtajV6hzReKnVaooXL54jYhU5k6LAxx/DrVtQtCisWZPsfFoZ6tEjH9zdq6DRvOT7721p1kwS6EJkG9pwiPxLl6CKOq97xAWmYUMqMCsJltXAqjFYe4BFpbRP/ieEyDkUDfgNhNB1uteOw6DAHFBbvr2uXScotAGedIWg+WDXAawbJywXeVL306p+2mIMDYVLl3TPGyey/dcc/6/Tu0woKoR4XZWCVfij9x8cvHuQsQfG4v3Umx9VP1L8i+IMDBuI2TwzAq4EsLnzZgrVKITHNA/KtC4j1/hCiCwlSfQ3qFQqChUqRIECBYiNfcv4ge8orVbL8+fPyZcvH2p19r+ANzc3zxFxipxrzRpYv1539/LGjbrhQLPCw4e3adTIjXv3XuLkpMLVda0k0IUwttjHEPorROz5LzGVyGcJ00JgVgJMC4PaAdT2oLIENLqxi7XhoPHX9VSPvadLvMf66B5h215tw64r2HXXJb4koS5E7qNo4cmHuvHNMYFCq8ChT+q2Yd8FIgZDyAoIGAMuZwy/6Y8LgpiruudpTaKfOgVarW5G9SJFki0an0R3d0/broQQuVvzks05P+Q8v1z+hYmHJ/Ig9AGTmYzHPA96+/YmYEEAfhf82Nh2I0XfK4rHNA9KNi8pyXQhRJaQJHoSTExMZAztJGi1WszMzLC0tJTktHjnXbsG//uf7vn06dCwYdbs9+HD27i7u3H//ksKFFDx55/bqFatU9bsXAhhSBsNYZshZJWu5zmvjdlpVgKsm4JlbbCsARZVQG2Vuu1rAiD6X4j6ByKPQuQJ0PhB0CLdw7wc5PkU7PuAiV0GHpgQwqiejf8vgW4GRTaDXce0bcfpawjbCFHnIGI/2Hq+Whflrftp5gqmBdK2/RRmxiMiXo2HLkl0IURS1Co1fdz60KVCF2adnMXsk7M5+ugox82PM3jdYJqfbs6NJTd49Pcjfmn5Cy6NXPCY5kGJxiWMHboQIpeTDKgQQqRRZCR07w4vX0KLFvD551mz3zcT6Pv3b5cEuhDGEPccAqeBTwnw66NLcKOAlTsUXAQlb0PJu1DoJ8jzkW6c4tQm0EGX2LJpCvkmQLE/ocwLKPob2H8IaluIuQn+w8DHBZ7PBu3LDD5QIUSWC14DL+bonhdak/YEOuj+hzgM+G+7Pxiui/5X99Oiatq3f+q/MdXf0pPgwgXQaHSd1V1c0r47IcS7wcbchmlNpnH9f9fpXKEzcUocy68sZ6jTUOz22FFzeE1MzE24f+w+az3W8nOLn3l89rGxwxZC5GKSRBdCiDQaMQKuXtVNjPXzz5AVN2Y8fHgLd/eqBgl0N7eOmb9jIcQrcaEQOBV8XHWT/cU91Q3Nkn86lLoHLscgzzAwL505EySoLcC2LRReB6We6BL25mVBGwTPPoe7pSF0k27CBiFEzhNzC/z/u80t/xRweD/923QcovsZvhviXry2r/gkeuVXy6KidLfa3bwJMTHJb1dR4OJF3fPatZMt6u2t+1mjRtbNHSOEyPlc87iyrfs2Dn54kEpOlXj+8jkjjo/gq4pfUedUHWp+VBO1mZq7B++yss5KtnTbwvNbz40dthAiF5IkuhBCpMGGDbBype4icP16/s/eeYdHUb1t+J5NL4QEEnrvPfTepIMgoAgiShFBUWz8LGBBsKF+iqAgoFSx0AWkKYQivffeQi+hJaQnu/P98e5mN8km2U02FDn3de01s1POOTM7O7vznPc8LwUL5n6dyclRHDnyLEZjPAULaqxe/acS0BWKe4lugjvT4UxZuDEKTHfBqyYU+V3E8+APweMeh1e65RHBvvQRKDwL3EtC8mW4/Axc6gZJl+9texQKRc7QjXD5OdBjxQoq/0euKderqlkoN0L0SuvylEj0qnDsGPTpI8ldqlaFSpUkUmDkSEhIsF9ueDhERoKHB1SunGkTLLlHQ0NzfDQKheIRpHWZ1ux9aS/jO4wn0DuQfVf30X5ZexZ3XEyfA30I7RsKGhxZcISJVSby10t/cffy3fvdbIVC8R9CiegKhULhJCdPwksvyfxHH0GrVrlfZ3JyFAcOdMDLazfff5+X1asXU6NG19yvWKFQCAlH4HxLuDpQEn16VoAi86DUbgjoDZrH/W2f5iYJB8sch+DRgIdEnIbXgpj197dtCoXCce5MhfidknS48CzXJg327yLTGLOIruuQcFjSOIzfDtWrS5RAbCzkzQt+fnD7tiR96dRJlqfFEl5erRp4emZavWXTmjVdcCwKheKRxMPNg9cbvM6JoScYWGsgANP2TqP+0vrceesOL+19iQqdK6Abdfb8tIfvy31P2PthxN+Jv88tVygU/wWUiK5QKBROEB8vPujR0dC8uYjouc25c0cZN64eUVFbcXcPok2btVSv/kTuV6xQKERkuvUDhNeGuI2g+ULIN1D6EAQ87VqByxUYvCB4JJTeC16hYLwOF9rIMdxPdB2MkZB4BuL3SvRr4ikwxdzfdikUjqInQ9w2uD0Rrr8L116X6e0pkpzTFfZJxltw4wOZD/4EPIrlvExbfB+TaZzZw9x0CxIi4W1g5HgxLO/SBbZvF/E8MhLmzgV/f1i7Fv73v/RlOqiMJyfDoUMObapQKBRZEuIXwtQnprJpwCaqFajGzbibDFgygF57exE6PZT+//anWKNiJMcls2nMJsaXGc+Wb7aQHJ98v5uuUCgeYtzvdwMUCoXiYeKdd+R5MX9+CdZyz+W76LlzR2nevDYXL8bzySd+vP76GvLkqZ27lSoUCsF4C670h+i/5L1fRyg0GTxK3NdmOYRXVSi5Ba6+DFGz4frrEkEfPOremBHrJojfBdErpPMh4YDUbw+3QmIz4dtc7Ct8Gj14nROKR5f4A3DnR4j6A0xRGW/nXhLyvQ6BL4HBL3t13fw/SVjsVQ2CXsleGZnh3QAwQNJZSL4CCRfhfWAFYscyYQIMHmzd3s1NIgfy5ZMM6pMnw/PPQ+PG1m1OnJBpFlYuJ06II4y/P5Qu7eoDUygUjypNSjRhz+A9jNs2jlEbRvHvuX8JnRzKO43f4YP1H3Bh5QXWvr+WiCMRrH5nNdvHb6fl6JaE9g3F4K7+aygUCudQdw2FQqFwkEWL5PkS4JdfoGjR3K0vPPwIzZrV4vz5eAoWNNC161wloCsU94rEExDeUAR0zRMKjIdiyx8OAd2CwVfsIII/k/c3P7FGueYWxttw8ytJbnquAdwcDbFrrQK65gvuhcGtAGhmodF4FWLXwI2RcL4pnC4J14dD0sXcbatCkRlJF+DysxAeCnemiIBuyCeWKEFvQv4PZOrXQa7r5HNw/X9wpirErHO+PuNtuDNR5oM/By0XeundAsDTLHbH74FPvoZlgLsGCxemFtBtadMGBoptAp98kmqV6eRplvE4wzZ253//g3/+sR+Ub9HaK1a8N4nYFQrFo4OHmwfvNHmHI68c4YmKT5BsSmbMpjFUm1SN8KrhvHzgZZ6Y/gQBxQOIuhjF0oFLmVxzMidXnkRXSdgVCoUTqL8wCoVC4QDh4fDCCzL/zjtiDZqbnD17mGbNanPhQgKFCxtYvfovqlV7PHcrVSgUQsx6EdCTToJ7CSi5XSJM70UEt6vRNAj+QDoBAG6OgdsTXF+Pngg3v4XTZSFiuES6GvJAnqeg0BQouRMqREPFGCh3Gcpfg4rRUP4WlNwBBSdCnp7iA518EW59BafLwJWBkHTJ9e1VKDIj8nc4W12izwHyPA3F10L5CCi2FAp+ByGfybT4Sih/AwpNNSf2PScWSnd+cq7O2xPNyYqrg39n1x+TBa8qMl21BP5vocx/U09sXDLj/fdl+s8/cP48ACdP6NTfN4UuLOO7v8oxdiy0by//l4zG1LufOSPTsmVddBwKhUKRhpKBJVnyzBIW91pM8YDihN8Jp+NvHem/tD8lepXgtROv0fabtvjk8yHicAS/d/qdX9v/yrUD1+530xUKxUOCEtEVCoUiCxISZDRzZCQ0bAiff5679Z05c4jmzetw8aJVQK9aNZdVe4VCIUSvgIsdwHRbbEVK7QDvmve7VTkn3+sQ/KnMX3sdYv5xXdkJhyG8AUS8LefNsyoUmg7lrkLRBRA4GHzq2re4cAsCn3piXVF0rnmfheDbEkiCyOlwtpII9Lox/f65jW6EuB1w43O41FOE1ZOF4LgvnMgLp4pBeEO0qy/gkzBTfN5VVFv20RPEBujuYrgzDSJnyXzCUdCT7kH9Jrj+HlzpA6ZIsT8ptQeKzgO/xzK2GTL4QOBAKHMIAvoCJrj6EtyZ7mC9Rqvonu/d3LUz8qwM0cDQ3+Ra7QX0bpH1fmXKwGOPyT5z5rB/PzRsqLPbWIsAInllcBIvvigOMDNnwmefpd799GmZKhFdoVDkNl0rdeXIq0d4q+FbGDQDsw/MpsqPVfjz9J80GtaI1069RqP/NcLN040zq88wueZklr64lLuX797vpisUigcc5YmuUCgUWfDOO7BzJwQFwZw5YhuaW1y7dpYWLeqmCOhhYcupXLlD7lWoUCis3F0sQilJ4N8NivwBBu/73CgXkv8DSAqHyGlw+TkotU/8yHPC3aVw+RnQ48AtP4T8H+TtC5pb9sozeEOeJ+UVt1XsMeK2ikAfsxKKzBY7mNwm8YxYeETOlOSs9tDjxOIj+RJa/HbyAoSPEJEy70AIHABu+XK/rRmh62JLFLcFEo9LhL/pLuAmowQ8Spm96JuBew6vg5yQfAPuzkOLmkvBuG1okYn2t9P8wK89BDwLebpl/xrLCN0EV16AqFnyPv9HkqTXGVsVgz8UngnuBeHW/4mQ7lleznFmxKyB5AtgCII8PbJ9CA7hVQm+B67FQil/GBHt+Heqe3dYt47zS/fR9hu4ddtAPXbwZ6FXKDplFyBJ1/v2hS++gP79oWRJ2VWJ6AqF4l7i7+nP2PZj6VW1Fy8sfYEjEUfouaAn3Sp148dOP9Lum3bUe6Uea4av4cj8I+ydtpdDfxyi8buNaTis4f1uvkKheEBRkegKhUKRCfPnww8/yPzs2daHwdwgKek2Fy48Tf36SkBXKO45Mavh0tNAktiKFJ333xLQQaxdCk4Ar1AwRsDVF3IWNX1nKlzqLmKyb1sofUiEY1eJmz6NoMQmscnQ/CA2DMLrSKLH3CL5GlwdAmcqwK2vRUA3BID/kxDyjfjil9oHZU5DmeNiU1NkHqb8H5Pg3gQdD0g8KqL/6VIQ8TEY73FkW+JpuD4CzpSRKP6rL4g9TtRvEL0Uov+EqF/EI/9yTzhVGMLrwa0fwBh579qZHAHX3xEP/GuvosX9i0YiulsweDcEv8dFNPeuK5+/HgPRi+ByD/l8oua7Lupf1+H6W2YB3V2E8JBPsudLrmkQ8hXkeQZIluTEppjM94k0R6wH9Mn9+85JDX4zz39aAbwAt2DH9m3bliTc6b3lNSIioGbJ2/xDO4pWsI4yee45aNkSEhPhxx+tuyoRXaFQ3A8aFGvAnsF7GNl8JO4GdxYfW0zliZWZvnc6gaUDeXre07yw+QWKNSxGUmwSG0Zt4MdKP3JszjFMRtP9br5CoXjAUCK6QqFQZMCJE9Y8WsOHw+O5aEmelHSbAwfaER29m7feys/WreuUgK5Q3Cvi98ClJ4FkEdCL/AZaLg45uZ8YvKHIXNC8IOZvuDs3e+VEzYergwET5B0ExVfkTjSzZhCbjFK7xSYm+Qqcbw6xW1xfV9QcOFMJ7kwGjNIxUHSx+F0XWwj5/wf+ncA7FDzLgGcFsakJeBryj+S2/wL0stfFA96rhkR93/wEzlaTTprcJjFcRhicqQC3vpRRB5o3+DSDoNcg5GtpW8FJEPIF5H1ROlTQxELl+usi/N/4HEyxuddOXYfIX+Vc3/oG9FjwCsUU8g0Rebagl7kKpbZC8WVQfBWU2gkVoqDULsg3XJJ7Jp2RDoCLT4DxVs7bFPkz3P5e5gvPhLz9claepsm5di8ubb35RcbbmuIkgTFAYP+c1esIX/4OJqAN0CRZlrnld2zfihUZ6/sRW/RGBPgls7DPIgKJhGLFUjbRNHjjDZn/9Vf5uI1GyS0D4gqjUCgU9xIvdy9GPzaa3YN3U7dIXSITIhm4dCDtfm1H+J1wijcuzgtbXqDH3B4Elg7k7uW7bHhrA1PrTeVM2Jn73XyFQvEAoUR0hUKhsENsLPToAXfvytDkTz/NvbpOnz5I794VuXlzFx4ewdSsuY6SJZvnXoUKhcJK0iW48DiYosH3MSj8S/aiTx8mvCpCfkkSqEUMQ9Ojnds/bhdceQ7QIfBlEQtz+5x5VYSSG0UQNkXCxcch/qBrytaT4eqrcLk3mO6AV20osQFK/AN5ujrXoeIWIB7wpfZCkfngURqSz8OFdhIdrudCVJtugltj4WxViTbHJBHcReZB+ZtQ8l8o+D3kf0faFvQy5B8BhX+G0vug3DUo8L3Y0JjuwI0P4WwoxG5yfVtNCRIZf+V5MN0SEb/YCjlfQW9hdCttP4GvZgDvOlBgDJS7AMGjzB1By2R0QuLJ7Lcp/iBcM6u+IWMgb5/sl2WLWwAUNCf0vTVeIu/tERsmoznci8u1l5scOQILl8n8a0g+A3A4Ev3SZY1PE94BYHzPLZRJOi4rCqXuQOvQAXx94fJl2L8fbt6E5GT5aAvfAzcmhUKhsEeNgjXYOnAr/9f2//B292bNmTVUn1SdqXumAlC1Z1VePfoqbb5ug2eAJ9f2X2N2m9n83vl3bhy/cZ9br1AoHgSUiK5QKBR2eO01OHgQChQQH3T3XNKHTp06QPPmdVm4MIIpU7wJDV2Lv3/13KlMoVCkRk+UaFbjVfGGLvonGLzud6vuDfneA49yaMZr+CZMdXw/Y5TZAz0R/J8Qexh7omdu4BYkkck+TUTsvdgBkq/mrExTvIxCuPMjoEH+kVBqG/jmsCNTM0BADyh9AAJflWW3voRLPURIdhXGSLHUuf4/iej2aS4R28VXSYS8wTfrMtxDIN9rUPogFP4N3ItC0ik43xJuT3JhW6PgQhvxmccgiW5L7QT/js5dQwZfCP4YSm4DjzIScX++ZfaEdD0ZrvQFPR78OkpST1fi303Efz0Gbo+3v40lCt2/S+5/l8aPl9Dwtt5QAcCcrNfBSPSRIyHG6EMjttDXZz5cNX//ChZMtZ23N7RuLfNr1lg3Cw7O3bwyCueYOHEipUqVwtvbmwYNGrBjx44Mt01KSuKTTz6hbNmyeHt7ExoayqpVq1JtM2rUKDRNS/WqVKlSbh+GQuEU7gZ33m78NgeHHKRpiaZEJ0Yz6K9BdPmjC1fuXsHdy51G/2vEM1ueod7QehjcDZxcfpJJ1Sbxz9v/EB8Zf78PQaFQ3EeUiK5QKBRpmDkTpk8HgwH++CP3oqZOndpPixb1uHw5kWLF3Pjii7+UgK5Q3EuuvyNJFw15RUB3y3u/W3TvMHhJNC/glzAZjHcc2+/GR5B0GtxLiO2Fq5M7ZoXBF4otBc8qkHwZLvcB3Zi9snSj7B/9l9ieFF0IIaNda+Vj8IdCE6DwbImcjv4TLj8tnRA5JTkCzrcQn3PNCwpOhhLrRbTNDpob5H1WvO0DngWMcO0ViHg/597jphgZPRC3Sb5vxVdC8Ic5O9feNaHkVrPNz2W40Mnx69jCncmQsA8Mgebr2cWPRpomFjQgvud6Uvptos1CpH9n19adlqgo+M1shv5C8dTrHIhEP38efvlF5r/lfxhOHLOq42ki0QEamvPy7dkD167JfBqtXXEfmTt3LsOGDePjjz9mz549hIaG0r59e65ft59I+cMPP2TKlCn88MMPHDlyhJdffpnu3buzd+/eVNtVrVqVK1eupLw2bcqFES0KhQsol68c6/ut5//a/h+ebp4sP7mcapOqMfeQ2Nz55Pehw/gODDk0hPKPl8eUbGLrt1v5ofwP7Jm6R/mlKxSPKEpEVygUChsOHoRXXpH50aOhVavcqefkyX20aFE/RUAPC/ubihXb5E5lCoUiPdErbDyQfwHPco7tFxEhQtRrr0HTppJt2NNTxDKDQVSiWrWgb1+YONGaTe9BJOAZdM/KGPRIa2LDzIg/ALcnyHzhqRIZfj9wyyeCt+YLsWvFVzs7XH9XElVqnpIwNE9317bTlrzPSR2at4j2V4fkTJg23oELrSBhP7gVlASsQS+5JpLZLRAK/wrBn8v7m2Pg5ufZL0/XJbmmRUAvEQZ+7XLeTgD3AlBiLbiXlOj5K/0cP6/GKIgYKfMhX0hZuUGeJ8CtgPj5x/ydel3SBbH7wQ18m+VO/RZ++w1iYqBSJWhkK6K7S/LcLPjmG7FkaVX7No3YJibnFnXcjohe2+xMs2dPplq74j4xduxYBg0axIABA6hSpQqTJ0/G19eX6dPt/xbMnj2b999/n06dOlGmTBmGDBlCp06d+Pbbb1Nt5+7uTqFChVJewcEOJq1VKO4DbgY33m78NnsG76F24drcirvFMwufoffC3tyKl3wbwRWDeXbZszy74lnyV8xPbEQsfw36i5/r/cy5jefu8xEoFIp7jRLRFQqFwkxUlPigx8VB+/bw/vu5U48I6A1SBPS1a/+hQoXWuVOZQqFIj/E2XB0k80FvisiVGQkJkiHvscdEBXruOZgwATZvlvDMJHN0qa7D9euwbx/Mng1Dh0K5cqImTZggAtaDhOaGHihe0Frk5Kz9uiM+AEyQ5ynwa5v77csMr0piJQNwYxQknnVu/+hlcHuszBf+FfxyqcfUFr/WUHQRYJBOizsTs1eOngyXe0HCIXAvLP7tPnVd2lQ0DYLfhwLmc3TjI4hakL2ybo2FuwsADyi2LPuR8hnhXgCKmTtDopc6niz3zkQw3QbPSuIVn1tonpKwGODuktTr4jbL1CtURi3kJrNny3TwYHC36QBzy5dl50tMDMyYIfPDh5nvd+fOiek52A0xr1VLpidOwFnz11OJ6A8GiYmJ7N69mzZtrMEbBoOBNm3asHXrVrv7JCQk4O3tnWqZj49PukjzkydPUqRIEcqUKUOfPn04f/686w9AoXAxVQtUZdvAbXzc4mPcNDfmHZnHY/MfY/nJ5SnblO9YniEHh9BubDu88npxde9VZjafycLeC4k8H3kfW69QKO4l//HMWQqFQuEYui7PlSdOQLFiopcZcqGbMSEhgo4dG3HlikVAX0358o+5viKFQpEx194U+wfPChKBmhEJCfDjj/DVV9aISxB1qEULqFsXypYVzycvLzCZJFL93DkJv9y4ETZsgL17JXJ91Cj44AMR1x8UY+CAZzFdfxdD0mmIXZNxhHD8AUniiEGSLz4I5O0PUbMhdh1cfwuKLXZsP+MtuDJA5oPeEO/we4V/Rwj5GiLeFh9z38fAq6pzZdwYCTH/SCR+sRWSdDW3yPeWfFdufQNXB4iFiqOjNgASjkDECJkvOA58m+ZGK8G7NuT/AG58LN9vv06S2DMjTLEi7oPsl9u2RHmegDsTZBSCbrLaxsRtkamj5yUhAW7dgjx5wN8J0f3SJbCIoz17guGIdZ0DUegLF0J0tNzu2vTKD/3cpPPwhjnRXkhIun0KFICAAAlQ2L5dlik7lweDGzduYDQaKZjmAylYsCDHjh2zu0/79u0ZO3YszZs3p2zZsoSFhbFo0SKMRqudVoMGDZg5cyYVK1bkypUrjB49mmbNmnHo0CHy5MmTrsyEhAQSEqw5IqKiogAwmUyYTMoqIzuYTCZ0XVfnLxu4aW6MbD6STuU60X9Jf47eOMoTc57gxVovMrbdWPw8/dDcNBq80YBqvauxfuR69kzdw6E5hzi25BiN321M47cb4+H7gPy/u8+oazHnqHOYc3Lj3CkRXaFQKBCdbO5cSSA6b54kv3I1SUk3OXiwHW+8Ec+ECe4sX76acuVaur4ihUKRMbEbIeoXQBMPZIOP/e1WrBCx2xJCWbQoDBkCffpAqVIZl1+kCISGwhPm6PYbNyS5wrhxcOYMDBsGU6eKuXAdF0fkZgeDH/Ge3fFNnAVRczMW0W9/J9M8PcCz/L1rX2ZoGhScCGerQfQSiN/tWJRzxEgw3hAv7ZCvcr+dack3TIT/mOVw5QUoucVxETduO9w0t7nwDBG1c5uQMRC3A+L+hasvQ/HVjtnG6Ca4OhhIAr/OEDgkd9uZ7z2I+g0ST4jtUHAmw8nuLpBrwKMUBDyTu+0C8G0hkebGa5BwwPq5xZv9pL3rZ7yvyQRLl8polk2bREgH6cx78014/vmsP4/Fi2XaqJHcy67bRKI7kHzW4vAxYABo7m6QP7+MurGQN30+CU2D0qVh/36w5Ku0o7UrHhLGjx/PoEGDqFSpEpqmUbZsWQYMGJDK/qVjx44p8zVq1KBBgwaULFmSefPmMXDgwHRljhkzhtGjR6dbHhERQWKiC/JGPIKYTCYiIyPRdR1DbkQDPQKUcC/BX13+4rPNnzHrxCym7p3KurPr+LHVj9QIqZGyXb1P6lH66dJsGbmFK9uu8O/of9nz8x4ajGxA2SfKot2rpOsPKOpazDnqHOacyEjXjxJRIrpCoXjk2bkT3npL5r/+Wp4xXU1CQgQHDrQlJmY/tWsXZNeuMPLkcTL6UKFQ5AzdCNfEvoTAQeBj58t+967cEKZNk/eFC8Mnn0C/ftmLHg8Olij0V14RJer99+HIEbnRjB0rQv19Jt6ji4jodxdDocnpkz2aoiFqvswHvX7P25cpXpUhoLeIpzc+zToaPeEo3Jkk8wV/kASr9xpNg0JT4GwViN8BUb9D3uez3k83mkVpEwT0gYCeud5UADR3KDxdOitiw8zt7ZP1fncXiV2J5geFfnSNX3tmGLwg/0i48hzc+hbyvZ6xRcods/CX90U5vtxG8wTvRhC7Ws6Jd00ZApdwWNZ7VbO/38WL0L8/hIXZlKXJvnv3yn1p/nyJAvDNRAz/6y+ZPvmkTA2BNuVl0JFo04QNG6Tavn3NC0NCrCK6m1uGdVtEdEvAemCg3c0U95jg4GDc3Ny4ZjvCCrh27RqFMvDcCQkJYfHixcTHx3Pz5k2KFCnC8OHDKVOmTIb1BAYGUqFCBU6dOmV3/YgRIxg2bFjK+6ioKIoXL05ISAiB6mLJFiaTCU3TCAkJUaJbDjCZTHzR8gv61OtD/6X9OX3nNJ0Xd+bzVp/zVsO3MJhHExVoXYDKrSpzdMFR1ry7hsjzkYS9HMaJX0/QYXwHCtV8dD2s1LWYc9Q5zDmenp4uL1N9EgqF4pHm9m14+mkZldy9uwR1uZrjx3dTs2ZJ9u/fj4dHQWrWXKcEdIXifhA5AxL2SnLD4M/Srz99Gho0EAFd00RMP3kSXnwx5/Yrbm4waBAcPw7duslN57XX4O23JdL0PpLo3hDdrQCYbkmEdFruLgQ9BjzKg0/je9/ArMj/IaBJNHriycy3vfklYAL/ruB3H620PIpCfnOkdMRHYErIfHuQjoKEAyKAFhyfq81Lh2dZ83lG/NH1pMy3103iVQ+Q73/gUTzTzV1GQC/wKCvXctQ8+9sknoW4DYAB8va7N+0C8G0iU4sPuvGqeLJjAE87ljyHD0PDhiKg+/jAiBFy/zAaJVPn55+LjdSyZfDUU7LcHklJEsEOkvAFwM0mcjyj0Thmli2TacOGUNzyMdqGlAcEZNhBklaPtROwrrgPeHp6UqdOHcJsOmdMJhNhYWE0yiKSxNvbm6JFi5KcnMzChQvp2rVrhttGR0dz+vRpChcubHe9l5cXAQEBqV4g/uzqlf2Xpmn3vQ3/hZemabQq04r9L++ne6XuJJmSeHfNu3T8vSNXY66mbOfm5ka1XtV49eirtBzdEncfdy5susDUelNZ9foqEiIT7vux3M9zeL/b8LC/1DnM+cvVKBFdoVA8sphMEsR17hyUKSNBoq4OlDt2bBctWzbi2LE4fvjBg9DQdfj5VXZtJQqFImtM8eKXDBA8CtzT+Aps3Aj168PRo2LJsm6dRIr7+bm2HfnywaJF8OWX8v7bbyVKXdddW48zaG7g97jMx6xOv94ShZ7XAduI+4FXJfDrIPN3pmW8XdIFiaIG8cG+3wS9Du5FIfkcRM3KfFs9ScR2gPwjwC1/7rcvLfneBLcCkHQWIn/JfNvoJZB4WDqs8r11T5oHSFR54IsyH5nBtRBtjsr2bQ4exe5NuwC8G8jUYuFiiUL3KAuG1AkbOXtWEhlfugRVqkiy4i++gAoVzDZGBWVUy9q1EgW+ahV88439enftksyg+fNDVXMHvmYTOa5lbueydKlMLQ5VQGoRPRNlPK19ixLRHxyGDRvGzz//zKxZszh69ChDhgwhJiaGAQMkX0Tfvn0ZMWJEyvbbt29n0aJFnDlzho0bN9KhQwdMJhPvvvtuyjZvv/02GzZsIDw8nC1bttC9e3fc3Nzo3bv3PT8+hcJV5PfNz8KeC/mp80/4eviy5swaakyqwdLjS1Nt5+HrQYuRLRh6fChVe1VFN+nsnLiTCRUmsHf6XnTTffyfp1AoXIYS0RUKxSPLN9/ICGcvL1iwwPXDjI8d20nLlo25ejWJEiXcWLRoDf7+SkBXKO4LkVMlQaJ7cQh6JfW6deugQwdJ2Fevnng8tWiRe23RNHjvPZg1SzIYT5kCH3+ce/U5gO7bSmbSRqKb4iF2rcz7ZxxxeN8JHCTTyJmgJ9vfJnImkAw+LcCn3j1qWCYYfCRKG+D2D5l3pNxdBMnnRcQOeu3etC8tBj/I947M3/4+8/beNlvmBA4Bt8Bcb1oq8vYD3CRpp72RCdHm0Gr/Lve0WSkJZBNPysiDFCuXNCPTYmKgc2dJUlyzpnTwVahgv8zGjcUrHeCTT+Dy5fTbrF8v0xYtrBnTbX3QM4lEj40VnR6gi+3psk0co0T0h5JevXrxzTffMHLkSGrWrMm+fftYtWpVSrLR8+fPc+XKlZTt4+Pj+fDDD6lSpQrdu3enaNGibNq0KZXtysWLF+nduzcVK1akZ8+e5M+fn23bthGizPAVDzmapjGoziB2D95NrUK1uBl3k65zuvLK8leITYpNtW3e4nnpMacHfcP6ElIlhNgbsSwduJRpjadxebede7RCoXioUCK6QqF4JFm/XkZGA3z/veTnciVHj+6gZcsmXLuWRMmSbqxdu46yZZu7thKFQuEYpgSzjQcSxavZ+ONt3AiPPy5qUYcOYv5bpMi9aVffvpLVGODTTyVCPTeIjBQf9iNHxMfYnvjpa7Y2id8DxtvW5XEbQY8D9yLgVT132ucK/DuDW7AkbozdmH69rkPkbJkPfOHeti0z8g4Qz/CEQ5K4MyNufy/TwCFZ2m/kKoEvgOYttjLx2+1vk3hGvL/RIHDwPW0eAO6FrdezJercgvEuxK6Xecvoi3uFezEwBABGSX6aFC7LPcul3m74cPmuFikiXir58mVebv/+kmMhNhbt22/Tr99o/j60bGldlioSPePraccOyWNapIgExKdgtt1IN58GJaI/2AwdOpRz586RkJDA9u3badCgQcq69evXM3PmzJT3LVq04MiRI8THx3Pjxg1++eUXiqT5rZwzZw6XL18mISGBixcvMmfOHMqWLXuvDkehyHUqBVdi68Ct/K+RdIBP2jWJ+j/X50jEkXTblm5Vmpf2vUS7b9vhmceTS9sv8XO9n1n28jJib8am216hUDwcKBFdoVA8cly6BL16iZ3L88+LTbErSS+gr6ds2WaurUShUDhO1GxIviTWGXltBNTjx6FrV4iLg06d4M8/xXv4XvLSS+KLDvDCC3DmjGvKPXgQXn1VvKoCA8XGoWpVsYEoWBD69IHly61+7O6FxfMcHeJ3WsuJ3SBT37YPppWLBc3DGlkcvTj9+vgdkHRSxMM8T97TpmWKW6AkRgWI+sP+NoknJaoaNwh66V61zD5u+SBPL5nPyDonao5MfduAZ+l70660+JsF8ujlqZfHbQGSwKM0eGYQ3Z1baJpNNPoRSL4g8+42fvGbNlkjy2fNgqJFHSv3Q7Nf/cyZ0iFoy759Mq1b17osVSR6xnYuFiv1Zs3SfP3z5LE/nwYloisUiv8aXu5efNPuG/557h8K+RficMRh6v1cj1/2p7c5c/Nwo9GwRgw9PpTqfaqDDrun7GZCxQns/mk3JuP9zYmjUCicR4noCoXikSIxURKJXr8ONWrA5Mmu1YUSE6/z5pvtuH49mVKl3Fm7dj1lyjR1XQUKhcI5dF2sMgCC3gKDl8zfuiUR6LdvS8a8BQvA2zvjcnKTL74QW4bISBHVc+KPfuUK9OwpN7gffxRvZRAhPV8+ueFFRMDvv0PnzmihoXha7B6868g0fre1vLgdMvVpmP023Sv8u8k0bfQxWMVU/85g8L9nTXKIALMofXehfSsaiye9X2vp7Ljf5H1OptGLQbeTzDJ6iUwDetyzJqXDIqLH/gsmG1E5fptMfZrcn04hD3NUblI4JF00LzOL6LoO75jtcgYOhDZtHC+3QwcoUwbtzh28//7buvz6dbknaBpUr054uFipd3qyNs8M+4MFfz+FSc9aRG+a9m+MbfS5l1eG+6cVzf0fsK+eQqFQZJe2Zduy76V9tCnThtikWPot7seAJQOISYxJt22ewnl48tcn6b+hPwWqFyDuZhzLXlrGtIbTuLTj0n1ovUKhyC5KRFcoFI8Ub78NW7fKg92iRZKPy1UkJl5n375WvPlmJJ07+xIWpgR0heK+E7dRrCc0X6uNh66LSHX6NJQqBUuW3PsIdFs8PCTq1MsL1qyBPzKISM6K9euhWjWYP1+8j3v0kMQPkZHSWXDzJkRHw7//wptvQkAA2pEj5OvdG+3FFwGzXYtFRNdtotJ96ufwIO8Bvo8BbpL4Mul86nUxq2Tq1/GeNytLfFuarWhuWK1GbLk7T6Z5nr6XrcoY3xZgCJL2xm1KvS75ikT9w733HLfFo5xYEJEM8busy+MsIroLOoV0HVaulBEkdepA+fISsv3RR3D+vP19PErKNOmcTSS6Obnp0qWwbZv8Mfn0U+faYjDIEDvAa9Uq6/L9+2Varhw//uJP5cowZgys/CeIuSuf4ek3F/D0oIEkJKQv0miU/0sATZqkWWmbcNnDI8NmpXV6uV/9lAqFQpEbFPQvyKo+q/ik5ScYNAMz982k/lT79i4AJZuX5KU9L9F+XHu8Ary4vOsyUxtOZemgpcTeUBYvCsXDQLZE9NmzZ9OkSROKFCnCuXPnABg3bhxLlixxaeMUCoXClfz2G/xgDkidPRtcadN49eox9u17jNjYw+TNW4S5c/dRpkzap06FQnHPuW22Rsj7HLgFyfzkybB4sYg/CxdCgQL3rXkplCtntWR4/30ZNuMMf/0F7dpJhH3t2rB7t4jpnTunVrJ8fUXo++47OH8e/Y030A0GtBkzoOsvcBtrwsOkU2C6A5pXzv3Qk5Ol02LjRtiyBcLDcxZxbw+3POBdW+ZjbfzFjTetQqp/e9fW6Qo0d6vgHLM69bqki5CwHzBYI+3vN5qHNdI75p/U66LNAq53vfsbNa9p4NNY5uO2yFTXIc7s455TEX3vXqhfX2ygZsyAPXvg1CkJ3f7sM/k+f/GFKNG2eJSQadJp6XAAayT6V1/J9PXXoXA2zl1XSfzrtX69tV6ziP6p56e8+irEx0Pz5jBlwgXee/FLPD0SWLS8Gm+8kb64U6cgKkpuGdXTfv1tOx09PcmItE4vmejtCoVC8VDiZnDjoxYfseb5NRTyL8SRiCPU+7kes/bNsru9wd1AwzcaMvT4UEL7hoIOe6fu5YcKP7Bz0k5l8aJQPOA4LaJPmjSJYcOG0alTJ+7cuYPR/CctMDCQcePGubp9CoVC4RIOHoTB5vxmH34IXVwYIHf48FZq1KjOpElH8PQsSs2a6/H1Le+6ChQKRfYw3rZaSwQOkenJkzBsmMx/9ZUIzg8K//ufiGfnzsH06Y7vt22bWLgkJUn0+aZNULNm1vvlzYs+diy358xBz58fdh+HgcD1U2IrknBQtvOqJsJpdti0CXr3huBgERabN5ew1tKlIX9+6NfP6hnhCnxbyNRWRI/bAejgWfHBsEOxhyURZuza1MstnvTetcE9+N62KTNS2rsh9fK4zeb1re9te+zhbRbKLR0oyZfAdBtwy1mn0C+/SCLPXbvEn2ToUBnNsmGDfG9btpTv4gcfyPVtK6Rbos7j9wO6tMWtgHR6bd0qKrM9RdsR6tRB9/fHEBUFh80dYSdOMI+nGXlYotQ/+0wGrAx+8S5f/m8Eiyd0Q9N0pkyRASq2HDok06pVwd09TV3ZFNHd3Jw/LIVCoXgYeKz0Y6nsXfov6Z+hvQuAfyF/us3qxoBNAygYWpD42/GseGUFU+tP5dJOZfGiUDyoOC2i//DDD/z888988MEHuNn8E6pbty4HDx50aeMUCoXCFURGwpNPSq6tdu1g1CjXlX3o0GYee6w5ERHJrF/vTvnyK5SArlA8KNxdAHqiCGbeNSUS1RKO2aZNhmKVrksA57ffwnPPQYsWYlneti289ppoaLdv50J7fXwkCh0kijXZjj92WiIj4Zln5Jgef1y8zp20pkls1gx9wwaJyD8KvJUMcacloSVkLwHjhQvQsaNEvc+ZI+309hYhvUwZEQtv35aT2ayZ3JxPn3a+nrT4NJKpra+7xZLGu17Oy88tLKJ0/B4wRlqXW+xdfFve6xZljm9zmcbtAFOcdbkl6tsSBX4/8aomU8vIisSjMvUsB1rGwm+mTJ8O/ftDQoL0xp86JUPcnnhCOogGDIC1a2HaNFGef/sNhg+37u9mzrRpvGZ+nw80A0yZIu979IBChbLXNnd3ye8AsFk6My4fjWQQPwNit/7BB2YreHOnWMfmq3ipn0Srp/1vZBHRq1WzU5etL0smIvr9dMlSKBSKe01G9i7HbxzPcJ8STUoweNdgOv7QEa+8XlzZc4WpDaay/JXlxN2Oy3A/hUJxf3BaRD979iy1atVKt9zLy4uYGPu9bAqFQnG/MJkkEOzUKShRQp5nXRUJJQJ6SyIikild2p116zYRElLDNYUrFIqcE/mrTAPMiRDnzYPVq8V7fNIk8RG2ITlZNLJatSSQ++235Z7x778SJLpmDUyYIPeUggWhTx84etTFbX7xRYnavnABli3Levu33pLI9TJlxEs9u34JlSvLAfoaYBvw4UeQeErWeTjZMbh2rfg/rFolAtvgwXICo6NlJMDp0xATI9YuL74obV69GkJDRXDPCV6hMk08bE3SeWMrLAbeOCojD0qWlOPt0gW+/FLO3/3Goxh4lAZMaTy8zVH6lgj7BwWPsmbP8SRre423rEK1pTPjXnPxIowdC926QYt3oTfwznGY9wfEmFVhz8rZK3vDBrmWdV1605YskRtBWjRNfNJ/Nd9/vvkGLMk+3dNYR7nlk6j1hQvl/cCB2WubhQYNpAn79gEwbO9zRJGX+pXv8sUXtm20Ct8j3tqFwQDr1sFxG53HEhtlV0S3VcczueeoyHOFQvGoYbF3Cesblsre5c+jf2a4j8HdQP2h9Rl6fCg1nq8BOuyatIuJlSayf/Z+dFfb3ykUimzjtIheunRp9pn/mNmyatUqKlfO5p9ShUKhyCW+/lqecz09YcEC0aZcwcGDG3nssZbcuJFMmTLurFu3mVKlGrimcIXiEaJUqVLUqFGDmjVr8thjj7mu4KTzEPcvoEFAb4kcfecdWff++xIRbYPFAWXgQIlC9/aWwO4vvhBt+s8/xfr47bdFVEpKkqDv6tUlj6C9xHzZwtvbKqRNmpT5tnv3SqNAIrrTeic4S/Xq8F0dmR+/AHaYo7k9nRDRV6yQCPTISPGMPnBAomwbNkytqHl4QNOm8PPP0hPRvLkI6717w/jx2T8Gj9Jg8Ac9AaIPyQfY8G8YASzYLefs/Hk4dkw6KUaMkOSyPXvCmTPZrzcrkpKk0+Cnn+SHacIE6bSIirJu420+9/F7ZGqKhcQT5nV1c69t2UHTwMtshZRwQKbxe2XqUTa19UxCgnRUXLiQ3iPcVdy9K7YqZcqILdKSJbDnAOwDFunQ61mo+zFsAryy8bxy44Yk7jQapfds/HhzSHcm9OolI19AfM6TkqyR6Bbc8ou/yq1b8gelRc46S/QqVWTmyBH27UxibkwXNExMGReXxpLFKnyXKBZLe3OqAIuWD1lEojto56JQKBSPKi1LtWTP4D00K9GMu4l3eXLek4xYMwKjKePfQf+C/nT/pTv91vUjuHIwMddjWNx3Mb+0+oWIoxH3sPUKhSIjnBbRhw0bxquvvsrcuXPRdZ0dO3bw+eefM2LECN59993caKNCoVBki7AwGboMolfUc9FI/oMHN9Kq1WNmAd2Ddes2U7JkfdcUrlA8gmzZsoV9+/axbt061xUavVSmPk0lcd+UKSLiFS1qFdOR0SqjR4t2dfgwBAXB//0fXL5s1VifeUYCW/v3l3UHD4odcpcuoql99hm0bg0Rrnq+sSRwWL0arl7NeDvLDa53b/EZdwVP1IcugEmH9w6BEfB0MAvz3r0iRicmwlNPSeRuxYpZ71e2rESvv/66vH/zTWvngLNoBvCsCueBJt3kHEXqUAIY8bYkYN22TX4gxo+XD07TJAlrtWowy34isGxz5YrYBhUsKB0FL70E770nkcxt28ry3r3hyBHwMo/0TDCL0QlHAJMIr252Ip4dQdfl3L75Jjz2mETg164NTz8tP4w3bmT/2LzNI6/i99u0F7FRiY6GceMkMtrPTzoqSpQQD/F27aRnylWC+pEj0gM2caII1U2bihfT0qUwoQy8AATnhQt3YRDw3WHnk9qOGAHXrolB+E8/ZS2gW/jiC7FJOnFCMpobfEHzs6435LMq108+acd83ElsRPRPR0py4mcM86nZJk0EgW2OA81At24yu9R82zSZ4OxZma9gz83Jy8s6r0R0hUKhsEvhPIUJ6xvGmw3eBODLzV/S4bcORMRk/oexVMtSvLzvZVp90Qp3H3fC14czOXQyYe+HkRSbdA9arlAoMkTPBr/++qterlw5XdM0XdM0vWjRovrUqVOzU9Q9JzIyUgf027dv3++mPLQYjUb9ypUrutFovN9NeahR5zHnZHYOz5/X9eBgXQddf+EFXTeZXFNnfPxl/YMPCumAXrash37u3A7XFHyfUNdhzrl9+7YO6JGRkfe7KQ8lJUuW1O/evZutfTP9TT/fTtePous3/k/Xo6N1vUABuSFMnpyySUKCrj/zjCwGXe/bV9dv3nSuDQsW6HrevLJ/+fK6fuVKtg4lPfXqSaGTJtlff+yYrNc0XT95MtvVpLsH3Bij61vQ9UBPKX8Mup5wNuuCYmLkBICut2mj64mJzjfGZNL14cOlDHd3Xd+yxfkydF3X/+6o6/nMH2r+vLr+Fbp+NCTj7ffv1/WWLa0XwvDhTv9opDuPJpOu//STrvv6WssNCdH1jh3lQuveXddLlbKuMxh0fWh3Xd+Prp+pJmXcnibX8LnW2TwPf+t6aKi1DnsvT09dHzZM17Nz/4qcK+0720DeX3lZ3v/cTY41bT3u7qmXVa8u5z6jc+gIe/boev78Ul7Jkrq+Zk3q9Re6S5sujtX1fsHWuj/5xPE6duyw7rdpk+P7Wfj6a9m3WjW5Lk4WlTYdRdcv9dX1smVl/V9/OV92GowxMbrJYNDPU0zXNJMOun64sJ3rJ/m2tQ03v9fPn5cmuLnJV/nSJev7pCQ7FR06ZD0nH3+caZtsP/KHAfWbfv9Qz+k5R/2vdw25cR7/OPiH7vu5r84o9OJji+s7Ljr2DHn77G399y6/66MYpY9ilP5dye/0Y0uPuaxduYW6FnOOOoc5Jzd+052ORAfo06cPJ0+eJDo6mqtXr3Lx4kUG5tTDT6FQKFxEQoLk5rpxQ7yNJ0xwPGgs83Ivs29fS9q0ucqoUflZu3YzJUo8wInqFIoc8u+//9KlSxeKFCmCpmksXrw43TYTJ06kVKlSeHt706BBA3bs2OFUHZqm0aJFC+rVq8dvv/3mmoYb71oTMvp3lsjR69fF6uGFFwAJlu7WTSy4PTwk8HnWLMiXz7mqnnpK7L5LlRK77w4d4M4dFxxDjx4ytfVXsOXHH2XauXM6a5oc4V4UgoCXzbYTEwDyZ73fRx/JCShSRLzns+PNrmkSuduzpxjUP/ec2HQ4Q3g4PPcv3AKqBcOWMfAE4JNJctQaNcRaxZJZ8csvYeRI59tvwWiEl1+WEQWxsRKNvWqVRKWvWCEX2qJFYh+zc6dEIJtMMOFP6A/cOCWao8Umxau6c/UnJ0tUf/v24k3k7y/X/S+/SFT6smVynuvUkS/C2LHyY7l/v3P1eJpHGSSZE8LGHYYvgEGLZVhG2bLyA3zunCS+jY+XqPFRoyAwUIZ01K8vXknZ4fJluf5v3pRydu+WkQW2eBQ3T6/CB4itD8jnawm7zopPPpHp889nb8THoEHg6yv+KDt2iN2QhSua5Ahwc5ORCjnF2xtToULMYAC6rvEYa6lSLCr9draR6BgpXly+ukajnEZLmoCiRTMIjk9rzaRQKBSKTHmm2jNsf3E75fOV50LUBZrOaMrPu3/Ocr/AUoH0XtqbXot7EVA8gMhzkcx5Yg5zus0h8nxklvsrFArXki0R3YKvry8FChTIekOFQqG4h7z1ljynBgWJ/mRr3ZldDh3ayIYNzYmLO4GXVwnefXenEtAV/3liYmIIDQ1l4sSJdtfPnTuXYcOG8fHHH7Nnzx5CQ0Np3749169fT9mmZs2aVKtWLd3r8uXLAGzatIndu3ezdOlSvvjiCw4cOJDzhseuAT1RvJndysH338vy994DDw90XfJZrlwp2tayZWLVkl0qVxZ3kEKFRIccMMB5t4h0PPmkTNevF69wW5KTrUkLX3klhxWlwb2QTHtFQD7gErBsdeb7nD5tPcc//yw33+yiadLpUaKEiMzOiNmJidC9O0TEQEVgTnXIZ7Yr8cxERAcRBT/+WERfEI+euXOdb7+ui2j600+SuPbrr2HLFhG002ZZ1DSoW1d+qJYuFWF5L9AvHm6dsCZ2dcbDOzFROmB++EHeDx0qHQvTpokI/NhjYvY/YoR4Eq1cKT1AZ85As2awfbvjdXmUkqnxhnRcvbcHZpvXffCBCOavviqfpabJ8VeuLOf55Eno1El6vXv2dFzQtmAyiQ3O5ctS5j//QH47nT3uZhE98ZS0sy/w+kuy7KWX4PbtzOs5cEBuEAaDdBRlh8BAeOIJmZ8/P7WIvs18fdapAwEB2Ss/DclFijKDAQAMZJrYyaRFs7VgMQEpOUnZvt0qopcsmUEltsq6snNRKBQKh6hWoBo7B+2ka8WuJBoTGbxsMC8ufZH45Pgs963UtRKvHn2Vxu82xuBu4PiS40ysPJHNX2/GmJRL+UYUCkU6HDLeq1WrFpqDYZx79uzJUYMUCoUiJ8yaJbn4NA1++w1Kl855mfv3r6dVqzbkz2/khx+K0aDBenx8XFCwQvGA07FjRzp27Jjh+rFjxzJo0CAGDBDBZvLkySxfvpzp06czfPhwALvJyG0pWrQoAIULF6ZTp07s2bOHGjVq2N02ISGBBJsMnlHmpIwmkwmTyZSyXItejQbofh3RlyzBEB6Onj8/ep8+YDLx+ecwe7YBNzedefN02rQRTS4nlColOmDTphqLF2tMmGBKySmYLcqUQStRAu38eUybNol/toX16zHcuiXH1KpVjhpvMpnQdd16/rRAibDwToSngSmgT5iAbjFNtoP28cdoycnoHTqgd+iQ85OZJw9MnoyhUyep+6WXMjBmTtOOTz9F27cPPV8A2uQodO8LkHRBrgW34uiOtGvIELTwcLRvvkF/8UX0hg2hePEsd7OcR/2bb2DGDHSDAf3338V7XDbIvIDHH4f169Fa10E7akR//gX4PgoNMLkVd+yc6jraoEFoS5age3mh//abdCpkVn+7drBzJ1qPHmgbNqC3b4++bZtD5xstD5ohCM10G9MXH2CYHwNuYJo6HvoOzbzefPlg8WK0/v3Rfv8dvU8fTFu2oAcHp/ouZ8iUKRj+/Rfdzw998WK5Zuzt514MA6DHbZPrQPNG/+JbtL/Xox0/jj56NPrYsRkf4uTJsl/37uhly2b/2u7RA8OcOegLFsDQElieqvQ916X8Jk3SXZ9GoyREX7hQ48oVGUgzcKCeacC6yWRir19jwimND7F050/0kF7pr33dkBJJZTIZwWQiNBT+/NPAkSM6yck6YKBECR2TyU6PoMFmfw+PLM6LNWbLoc/2PvMwtFGhUDy85PXOy6Jei/hy05d8uPZDpu2dxqHrh/iz158UzlM40309/Txp+1VbQp8PZfkryzm/8Txr3lvD/ln7eXzS45RsnlHPp0KhcBUOiejdbB6c4uPj+fHHH6lSpQqNGjUCYNu2bRw+fJhXXB0NpVAoFE6wb5+MoAcJdMtE+3MYi4B+65aR/Pk9qFJliRLQFQogMTGR3bt3M2LEiJRlBoOBNm3asHXrVofKiImJwWQykSdPHqKjo1m7di09e/bMcPsxY8YwevTodMsjIiJITExMeZ//7lo8gDuJNfEdOxYvIKZPH6Lv3mXrP/GMGiWeLV99FUWdOnHYBM7niOLF4aOPfPnoowBGjIBmzW5QqFD2BZm8DRrgc/48sStWEB0amrI8z5w5+AFx7dsTdetWjtpsMpmIjIxE13UMBgNuRgixrOwF+s+grVvHjV27MJYokW5/w9WrhMyZA8DNN94g2VUns1YtAlu3xjssjPiRI4m0RLpngNvZswR/+SUAUV+8S95CH6InXSIx5jzeQFScL3GOtu3NN8m3fj2eu3aRMHgwd2bOzNITzGQyEb9tGwZzste7n35KbIsWOHVxFSxIvp9q4Nl7L9rKLZh+8kJ7AW5G+WGMyboc3xkzCPjlF3SDgdvTppHYpInD9WvTpxPUqxeeu3aR3KMHN//6y6FhXPm1YngcuI02SiL49fcNXG//lOPH/dVXBIWH47VlC6bnnuPOb7+lXIsZtvXOHULMnXR3hw8nNiAgw/o8kn3ID2hGGfli1Apy4+5dPD/+mHzPPgtTpnDjhRcw2YvWTkigwB9/oAG3e/QgMSfXdq1aFPTwQDt3joTTRfCSvkOMB67iDkSWKUO8TflXrhh46aVAdu60Rnlv2QK//qoxaFAMo0fftXtJmkwmlkSKyt6W1fgSR7S/P9F22m4ec0JMdBQxydcJCfEGAjl6NAl39yTAj8DAGK5fj063r+HOHSxn7G5CQhbfrUIpc9dddX/IRSIjlT2CQqHIXQyagfebvU/dInV5ZsEzbL+0nbo/12Vxr8XUK5r1SOcC1QrQf0N/9v+yn9VvrybiSAQzW8wktF8obf+vLX4hflmWoVAosomzJuoDBw7UP/zww3TLR44cqQ8YMCDHJu25jUpYknNUggPXoM5jzrE9hzduWHO0deyo6644rXv2hOn58rnpgF6+vId+4cKenBf6gKGuw5zzqCQhA/Q///wz5f2lS5d0QN+SJvnjO++8o9evX9+hMk+fPq3XqFFDr1Gjhl61alV93LhxmW4fHx+vR0ZGprwuXLigA/rNmzd1o9Eor8RrKQnzjMe26zroJk3TjeHh+s2bRr1YMUm29/zzJus+LnwlJRn1hg2ljt69s1dHYqJR//NPo/5is6N6U/7VmwTs1/v3N+lz5hj1uDijbqpWTddBN86f74L2JumXL1/Wk5KSzOfvtjXh4FF0UxNJEGn86iv7ZXzyiZzjJk1cfz63bZOy3d1147lzmW5rMmeINbVvrxuTIq3tP11NroU7C5yr+8AB3eThIce+alXW5zE+Xk+sXl3a8OSTujE5OVvHbLo0QNdHm7MweqHrq9CNSZFZ73vqlG7y85P2fvNN9s73xYu6yZyA1/Tuu46193RXXS9nbm9ndNPJEtmr15yd987nn1uvxYzq/PBDaWP16roxMTHzsmMPpb6ez9SV5cnJuqlBAyln+HD7+86fL+uLFs26HkfOVbNmUt5XdaQ9h9FN/l7yme3fn7LduXNGvUwZuYfkyWPS339fvvsDB5pSEnR+8IH9e0tSUpJeu/B5HXT9ZwZmej2k3CcjPteNRqO+ZYtRB10vWtSkP/ec1PXVVxl/ZpbGGKdMyfS4bROL5vQc3ovXzZs3H4nf9AcR9Zyec4xG9b/eFdzL83jy5km98oTKOqPQvT710mfvn+3U/rE3Y/Wlg5emJB79MuhLfefknbrJ6FyCdFejrsWco85hzsmN53SnRfSAgAD9xIkT6ZafOHFCDwgIcEmjchP145xz1JfZNajzmHMs5zAhwai3aSMPaGXK6PrNmzkve8+eMD0oyCKge+oXL+7NeaEPIOo6zDlKRM++iJ5T7P6mR/0p4tDpKrpuFnj1Nm10Xdf1oUPlbblyun73bu61a/duq2h08KDz+9aooacSnmxfJYsn63/xuLy5fj3HbU13DzCZdP2om1V4/Kqp1FWvXvqdTSZr7+Uvv+S4LXZp0ULKf//9jLc5dUrXNU2227tXlh3zTSWe6jGbna/79delzEaN5FgzwThzpgikgYG6fuWK83VZuP6Brh9B15sGmnuFPR3br0sX2b5Fi5z1Ii9ZIuV4eOj68eNZbz+muWyfz03Xt6Dr4Y2zV+/EiboOenJIiG6Mjs54u7t3dT0gQOpcuDDrcpOupr4OzrW1rjOL5HqRIrqenJx+3379ZP2wYU4fjl0++EDKe6a8tOVvS2eJl64nJuq6rusJCbpu1vb1smV1/fTp1EVMmybrDAZd3749fRW3bhl1TRMB/CJFMv9uWs5JxGe6ruv6jRvW+0zLljKdNi2DY7l+3brxzJmZHrbt/eth4FH5TX8QUc/pOUf9r3cN9/o8RsZH6l1+76IzCp1R6O/8846ebLTzu5QJF7Ze0CeFTkoR06c2nKpf2ZeD/yM5RF2LOUedw5yTG7/pTicW9fHxYfPmzemWb968GW9v72zEwisUCkXO+OADjTVrJEHg4sVitZoT9u4No3Xrdty+baRCBU/WrdtO0aI1XdFUheI/Q3BwMG5ubly7di3V8mvXrlGoUKEM9roHxP4rU59m8MsvMt+3L7t3w48/ytspU8Df3/7urqB2bcntCPD5547vt3w5NGkiuQwDA+GN10zM8XieufTknYG3KFQIzl1wowvLGJl/InpwSJZlOo2mgZvNTbRDFZnu2gU3b6bedv9+SVrp6wtPPeX6tgAMGSLT337L2Hd5yhTR6Dp0gJo1ZZl7GnsO94LO1z18OHh7w9atsGlTxtslJ6N99hkA+nvvSYbZ7OJeGDTgnQSZrkyEvXsz32fbNvjrL0ncOWWKJMHMLl26iBdaUhJ8+mnm28bHw3hz214xQhDgXjR79Q4ahF6yJG4REZIENSPmzYOoKChfHjLx6U/BLSjj9126SDLSy5dhzZrU25lMsGqVzD/+uEOHkCW1a8v0yB2ZmvPGUqUKeHgA8OWXktgzMFBypZYpk7qIF14Ac2oHzI42qdi+HXRdowynKYpY2GSdsFS+V/nyWTe1pLgKDs5gF9vEomkT5ioUCoXCKQK8Alj8zGLeb/o+AP+35f/o8kcX7sTfcbiMYg2LMXjXYNqPa49nHk8ubrvIT3V+4u9hf5NwNyHrAhQKhUM4/S/7zTffZMiQIbz++uv8+uuv/Prrr7z22mu8+uqrvPXWW7nRRoVCociQJUu8+eYbMQadMQOqV89ZefHxFzh1agBubhYBfacS0BUKO3h6elKnTh3CwsJSlplMJsLCwlJyptwX4rfL9GgROHUK/Pyge3fefluEp969oVWr3G/Ghx/KdP58uHIl6+23b4cnnxRdsmNHOHECxn1voFetE/RkPl+3W8OpU/Bm/S0AfHrzFd57L5cab7AR3QoXgqpVRaRety71dkuWyLRdOxHSc4MuXaTH49w5MYVOS2IiTJ8u87a5edxcIKIXLiyKJcDPP2e83fLlaKdOYcqXL3UbsoO7OalYhTjoZF42blzm+1h6avr2hYoVc1a/psEnn8j8H3/Iec+IOXPg6l0ojCShBXDLn716PTzQ33lHmjBxolxv9rB8Di++6FhngeYJBpseM1sR3cvL2vmzbFnq/fbvh2vX5Npr2tTBg8gCSwfPsVuQBFwwLy9bFpBTPWaMLJo0Kb2AbuGLL0TDXrdO+rZs2bpV/g81wiYvRZY9hiKiaxoUNH9NzDmbyZ/Rx2krouek00ahUCgUgPikf976c+Y8NQcfdx9WnlpJw6kNOX7juONluBto+EZDXj36KlWeroJu1Nn23TYmVp7I0UVH0TP6bVUoFA7j9L+e4cOHM2vWLHbv3s3rr7/O66+/zp49e5gxYwbD7YVEKBQKRS6xfz+89ZaIPe+9B5nkI3SI+Pjz7NvXkpCQC0yaVJx163ZSpEgNF7RUoXg4iY6OZt++fezbtw+As2fPsm/fPs6fPw/AsGHD+Pnnn5k1axZHjx5lyJAhxMTEMGDAgPvTYN0I8dJW/jZHYT7+OGt3+LN+PXh6SqTnvSA0VKLKjUbp4MuMqCjR8hIT4YknRJsOsQSZVzFHgp84gZ8ffFfk/5jMSwD83/9lru06wv79MH68Hy+9pPHaazB1KkTcLm7dwOAPbdrIfNpoXUukbpcuOWtEZvj6Su8CwIIF6devXSsR8oUKQadO1uVugdZ5zSe1kOoMgwfLdN48uH3b/jZTpwIQ27t3zoc42IrQfc3TuXPTjwKwcP48rFgh8676H163LrRuLRevZfiGPSwX3zOAJf9l2shvZ3juOUw+PmgnTkj0f1rOnpWoe4NBOgwcxWAzssKQpn2WKPMVK1IL95YOmyZN5MbhILduyaCF/fshOTnNytKlIU8eSDTCOeCSeblZLR8zRjrRWraEXr0yrqNECev/nbT3lm3bZNoYmw6nrK5J3ZgyWzBNX5NDkehKRFcoFAqX0ataLza9sIniAcU5fvM4DaY24O9TfztVRkDRAJ6e9zTPrniWwNKB3L10l3lPzeOPLn9w+2wG/2UUCoVDZOtfT8+ePdm8eTO3bt3i1q1bbN68mZ45Va8UCoXCCW7dgqee0oiLM9C2re6UZYI9du9ezaRJ9YmPP4O3dxk6d96sBHTFI8+uXbuoVasWtWrVAkQ0r1WrFiNHjgSgV69efPPNN4wcOZKaNWuyb98+Vq1aRcG0Ssy9IvEE6LGg+cEKsZ7Tn+iKubkMHiwC1L1i0CCZTpuWcWAtwMiRcOkSlCsHv/6a4uwglCsn01Nm74dDh3iJn/ik/xkA3ngDTp50vm3h4RLxXru2gS+/zMPUqRoTJkibizdZxTv/9zWxcT5g8INmzWSnHTusBcTHw+7dMt+ypfMNcIYnnpDpP/+kX/fnnzLt1i21rYQhj3XeVlB3lnr1JBI/ISF9tDLIMAOziB3Xu3f267FgCLTOVwdqBEvds2fb337qVBli8dhjUKFCzuu3YImo//VXEdPTcuSICM3ubtDdZrkhB35qefKQYOmQ+f339Ov/+kumTZs6Z5njZjOyIu210KqViORnzli/Y2C91hs0cKiK06ehe3fp/GrWTILOS5SQfoaU776mpUSdcxFrJHrp0ly7BjNnytvRo2XTzHj+eZnOn5/64zl0SKa12WNd6OeXReutNkkF0gzgyDAS3fa7lmX5QlbHpFAoFAqhduHa7By0k6YlmhKZEMnjvz/OpJ2TnC6nfMfyvHL4FZp92AyDh4GTy0/yY9Uf2ThmI8ZEO7/tCoUiS1TogEKheOgwGsWS4exZjRIlkvn9dz1Hlpy7dv1NmzYdeO+9axw5UoSaNdfj7V086x0Viv84LVu2RJck5KleMy1qDzB06FDOnTtHQkIC27dvp4GDolOuEG8Wjq5XEjXJzY3tIZ3ZvFmcG0aMuLfN6dEDfHxEn9u/3/424eEwYYLMT5wogaqpsBXR4+JErQM++MKP1q1l0ZAhmYv0adm6VeyZV60Cd3edDh3i+fhjE+++K8sTEr34Zvo7NOq9lYtXCoiQDHDwoIjnIAJ6UpKErpYu7Xjl2aFVK4l2PXoULl60Ltd1MZIHUTBtsRXRtRxEh2uaNRLeYl9jy9KlYDKhN2yI0SKQ5oRUEfTAM9KBxcKF6bfVdbFUAWuPjat4/HExyb58GdavT7/e0p62jcDWmt8tByI6EG8ZTbB8efqL2tKJYelUcRTbz19LYzvk72+9vi1h3CD+SuCQiL5uHdSpIzlZTCYoVQry5pX+lcGD4dVXbQ7F8l25hAjpAGXKMH269JXUr2/ts8qM1q3FvzwiwnpviYyEy5dFqa7M0dTHmCn2RXRNg6CMBhbYRqI7KKIr63SFQqFwnIL+BQnrG0b/mv0x6kZeWfEKb656E6PJOfHbw8eDVp+2YsiBIZRqWYrkuGTWvr+WyTUnE74hPHcar1D8h3FaRDcYDLi5uWX4UigUitzmgw8kINHXV2fGjDs5SiS6c+cq2rbtxJ07JsqW9aJ797+VgK5QPKxYRPR/zaJOs2Z8P1OiUHv3hiJF7m1z/PygfXuZtwRMp2XcOOkYbNNGrMXTUb68TE+eFOsOXYc8eTAUKsDUqRJEGxYGfzs40vfgQcm/efu2CHaHDsl9dORI+Oor8Vj+a8bnFAy+yoHjobTs3IEI7+ISYpucLFlPwWp30bhxpiGmkZFiO9O8ORQvLn0CPXqIBptRntB0BAVZhU5bX/azZyWE38MjvfJo6+ueXSsXC127ynTVKvHcscUcHa27ytLGNhIdoLNZxN28Ga5eTb3u2DG5Ljw9oXNn19RvwcvLetyWjgpbli6V6RMdUi/PoYie2KwZuqen9C4dO2ZdkZRkTe7aoYPdfTPEYCPyGrzSr2/YUKYWC5moKDhu9qCtXz/TovfulVMfGSlfhUOH5LK8fh2+/lq+GpMmwdix5h0sIvpFIMK8rFixlMD7l15yLGLbwwNatJB5S1qKo2bdvFDBZPISZd04IxFdM9vU+FpvPLb/p/z9MxG+bS1cskxcKqjHRIVCoXAOTzdPpj8xnTGtJWHG+O3j6TqnK3cT7jpdVnClYPqu7Uv32d3xDfHlxtEbzGo5i8X9FxMTEePqpisU/1mcFtH//PNPFi1alPKaO3cuw4cPp3Dhwvz000+50UaFQqFIYd48EXoAfv5Zp0qVtKajjrNjx0ratn2cO3dMVK7sxdq1uyhcuJqLWqpQKO45CeaQzG3RAFxp9CTz58ui1167P02yBEjb0yGjo1PstDHnVExPqVIyvX7dajdRvDhoGqVKWY9r1Kis2xIbK17KUVEiaq9bZ9XoLWgadG53mG1zGlKq6FlOn/Xnyac0jNVrygYWpc4S/moRt+2wdKm4V7z7LmzcKEHkp0+LgN6jhwT5Hnc0X1bjxjLdudO67N9/rW3w8QFsrC1sI9FzKqLXri2+FjExoppaSEy0KpgWb+2cYsiDhKCbKV5SPMp1Pb0nvUXIbt3azhAGF9Cxo0xXrky9/No1a0bLzmk6DwyOCaoZofv6ysUJ1nMLcr3FxUmHSuXKzhVq+/lr3oD0vUyfLkk6f4nvyVUKWo/JclEWLpyJKbh8f7t3l+9Vu3bS3KpVZZ2np3ynf/hB3o8YIcmCU0T0c0CkzB66UYhDh2Qfy6AHR7C4KG0W56qUr2b58mmiFDMS0ctegBKbwa9lyiLboHLzVypjBgyQDo3atR1qrxLRFQqFwnk0TWN40+HMf3o+3u7eLD+5nKYzmnIh8kLWO9spq8ZzNRh6fCh1XqoDGuyftZ8JFSewZ+oedJNKPKpQZIXTInrXrl1TvXr06MHnn3/O119/zVLLn3mFQqHIBQ4elGc2kIfTZ57Jflnbt6+gXbvOREZaBPTdSkBXKB52Eo+LM8FWsTyZcasrycmivzqo87ic1q1lunevRKvasmyZ6LJly0LbthkUEBQkUcFg9Wkubh0t8847Ir5t357astwen38uwb2FC4uQ7eubwYaaF6WKnmPlTx3JkyeZTZvg/2LMHtkWgfHIEZlaEp+m4aefJJD55k2oVEnyU+7YIcL9iBFid7Frlwjp9nJIpsMi1tse5KZN6MA/xV6ga1c5Ve7uons+/eJzbNhhFmNzKqJrmiSYNNeZwt69Ym8THAzVXPT7oRlSC9Gaj/idA2zYkHpby3vLcAdX07atKJ/HjskoCAsW1bZaNShSJvU+hqyU16zRmzaVGdsLwzLyoVEj5xNZ2kSix8b5MnSo9E0NHCgj2/pNrE8pwvlg/9MkJ+nWCPiKFTMtduRIOHcOSpaUDn5v7/TbvPKK9EUkJcH772NNymAJstc0/lwXCIgeHRjo+GFZ7mmW/iyLiF6hYprgAi870fcA7gXAt3GqRbZ6e4b3BwvTp0sHi4OfhxLRFQqFIvv0qNKDDf03UNCvIAeuHaD+1PrsurwrW2X5BPnQeXJnBm4ZSMHQgsTfjuevQX8xvel0rh245uKWKxT/Ldyz3sQxGjZsyODBg11VnEKhUKTi1i3JGxcbK7YHX3yR/bKOHt1I+/ZdUgT0dev2ULCgfSFI8R8lMRFu3BBVMzJSQnPTTmNixKQ2Pl6maV8mE5hMaGntHRT3B1MMJF+EU8DNSHQfX377V8TmF1+8f80qWlQsTE6dEu3RYvkMMHeuTHv1ysTCQdPEh+bsWatPs0121IIFpUPxl1/EW/2XX+wXc+kSfPedzP/4Y6YBtinRupXKHOeHsRfoP6g0o/d05jmKUuz4cbn2LUKjnajg5cvFlgLEr33cOBH6LbRsKT7RPXuKNtqhg2jjmWqWdevKdN8+CTd3cyNq90leZC7z56VObn/zJixYWokFSzfwXJfZTP52NY65NttH12F9od4spSVnv2mM907xwH4m+iDFQexAXJk10ZAXTOYeF4M5Mvv//s8aeQ/yGViEZYvo7GoCAyE0FPbsEb9wy3VnqbdJE7PHuAaYo9e0nIvotvYqZ8/C6tVwfWohijCA9lVDKepseZqIyLfuBNG2dxv27LNWU7ky7N9nYs9eb75IfIcDneJYVOcEHpDpBXnunDXKfPJk6RSyW7Umti4rV8KiRXC2dzFKA1wxb5AvL2vWighte29whNBQmYaHw507MgUoUSJNJLoT16atiJ5lJLqTKBFdoVAockb9ovXZ/uJ2uvzRhYPXD9J8RnN+ffJXnqzsxDAmG4o1LMbgXYPZ/sN21o9cz8WtF5lSewoN32pIy49b4unvmXUhCsUjhktE9Li4OL7//nuKFnX6b61CoVBkidEIzz4ryflKlZI8au7uTvjp2hAXd5abN/tQv76JS5e8WLtWCej/GXRdBPALFyRq8sIF8RC+fj3169o1URxchAulM0VOSDwp012+QCwHajzHke0aXl7OWSTkBi1aiIj+779WoSwpScRBgKeeyqKAwoVTi+g2kegAL78s4vmff4rjhT3xa9w4Wde0qdXqOkM0a+Rq3z53mToLNm1y52NGM+34d/LdiosTZbxM6kjkq1ehb1+Zf+klSZZqT8MrWlRyW7RvL50LTz4pWm1GQbOUKSMrExLg3Dnu5C1J+/3fsIN6uLvrDB2q8fzzUKyY/FbM/OkEU38pw69/Pc/JS435Z53D1s2pOHUK+vWDLVvMQ5+uAnOlA+QDQ3+GcYNP60NO9MGEBPj1V/n8Tp4EL+0falfeSv/uM2n5pA80NYv0J05IJsmQEDh8WO53fn5WNTUTzp8XN5hr1yR55GOPpfvo7NOokXwwW7dKrwdYI9GbNAHNwIlzoSxe3ZaT58rjW7AEDZuIzYm9yGyHqFePm+TjjbOf8HtZHV3XgJ5AT9zHmngpVoTpLCOlLWheJCZ60HXoEvbsCyQ4GH7/3Tr6Q9cNzC/6Jv2ujGHZGh+GhTfmB4AKFTIs8uuvJUVA69ZZW7RXqyZ1rV4NP68phW0MQExQ0ZSAe8uoFUcJCpJbwYUL4sV+6ZIsL1zYuaRzttjauTh8fh1EiegKhUKRc0oGlmTTC5t4ZsEzrDy1kqfmPcWXrb/k3SbvomWjQ9/gbqDRW42o+nRVVr25iqMLj7L1m60cnnuYjt93pGLXitkqV6H4r+K0iB4UFJTqS6TrOnfv3sXX15dff/3VpY1TKBQKgI8+kqR5Pj6weLFY02aHuLiz7NvXkuTkC4waVZ4KFZYRHJzxQ7LiASQ2VlStkyfldfasVTA/fx7uOpFox81NwgcDAqxT23l/fxHtLC9vb+u8p6f05BgMmGJioH//XDtkhYMkmm1G9vgAsfzu0Q8Qq+qMokTvFfXrw7RpokVa2LNHBjsEBUHNmlkUULCgTC2dP4ULp1rdsKEECZ8/LxGvaTsN4uNhxgyZf+89BwJTNav6qRnc+fprscSZzfN8Hj6GQufOycoSJeR7YMMHH8jIoVq1YPz4zOvy84MFC+T4jxyBMWMy8XZ3cxNR8+BBTEeO8dy3Bdih1yM/N1i+IYgGja0KXYEC0LDKfvq0Gki3oYvZvqcsPXpIXlBnnEC2bRORPyoKfHx0no2bRl12cfeT71j6jw+bNrnzFcPZtuA2S99wvFxbdu6UpLenT9surcjB4xWZtbg/XeffYMYvgQSVLSv3vgMHRG21eMPXr5/uM7Dl6lUYNkw6n/U0VqfduknnSsmSmTSwQQPpCbH4hRuNMhoAiKraiDdfgJkzd6Pr1hP7/US5RKdMgezkWz1zK5B2bns4aywJOrRorlNu00wOmSqz3diQiRPls1mzxkH7E82TTyd9xKbdzcibN5l169xTue9oGvSsewbvv3rRlaVMONWR7jxGK5sRH7ZERVm/Tx984NgxDRokIvrcVXn5HGvn6zbP5iQlyVepbFnHyrKlQgX5+Tt92iqiFyqUjQgDM7kZie6sC49CoVAo7BPgFcDS3kt5a9VbTNg5geFhwwm/E84PnX7A3ZC9ONmAYgH0XNCTE8tPsHLoSu6E32Fu97lU6FKBjj90JLBkoGsPQqF4SHH6G/bdd9+lEtENBgMhISE0aNCAoKAglzZOoVAoFiwQYQVEhHIg4M4uW7f+xbffPsuQIdH4+1egZs11eHkVcV1DFa5D10UNOHhQlLUTJ6yi+cWLWe+fP78oEsWLiw1GgQL2X0FBrnmqd2FUuyIHWET0w2Kvs/Sc3Cx69bpfDbJSq5ZM9+2Ty1vTYP16Wda8uQOXYdr/V2l6EjUNnn4avv1WfNbTiuiLFonFSYkS1lyRmWITiY7mQaNG0LihkS3bPJkS04ePLebLaUYgHjpkFRd//DGTqHIbChWC77+Xz2nMGBEbMxzYWKkSHDzIxGneLF/vjxfx/F3xDeo0/s3uMTSru4l/prWj+fNbWb3ak6++Ej92RzhxwiqgN2oEc+dqFG88Wu5Brfvyzrt1+NPnWfrr09lwIIinntJTjt1R1qyBzp0lEr1wYXj9dekQiTn7Dn/9XZZpCweyZFkwDRvCvxWaUfDUKTHAbt1aItEBatTIsPz9++XzvmK2DmnSRBLJnj0riV4XLxaL96VL5RjtUr26TI8ckYs3PBzi47nuVZzW/cpy6BCAgfZNV9Go5lbuGN5lwSI/Ll6EJ54Qkf4NJzoYbt7U6NpV46yxJGU4zZwPDlGvXxWo8AL4+LD6z2iefc7A7t3SCRAWlnWE85ETxRnz85sATP3xNNWq2bFpKVGCJ5jIkFrbmLS3Ie/wf+wsnGg3edTChTIQo1Ila3LPrOjQQfpez4S7cdy9CpWSJafAbl2MzRs0yJ4jUJkycg7OnIHLl2VZoULZj0R3yhPdQXx85HxZ0gooFAqFIue4G9z5odMPlMtXjrf+fovJuydz6e4l5vSYg69H9m/gFR6vQOnHSvPv5/+y5f+2cOKvE5wNO0vzkc1pNKwRbh5qWJHiEUd3knPnzukmkynDdQ86kZGROqDfvn37fjflocVoNOpXrlzRjUbj/W7KQ406j1lz8KCu+/npOuj6//6Xfr2j53DLlqV6njwGHdAHDw7W4+Mv51KLHz7u+3V4+7au//uvrv/4o64PGaLrTZvqemCgfOgZvYKCdL1+fV3v00fXR47U9WnTdP2ff3T92DFdj4m5D4dwWwf0yMjIe173o06q3/RLz+r6drlGTlNaB113c5NL7H4TG6vrBoNcvhcvyrKuXeX9t986UMCwYam/A+vXp9vk779lVfHiup72b9qTT8q6jz5KX7Tde0DEp7p+FHklnNF1Xdf/+EPKKMZ53dj/BXnz7LOpyho0SBZ37+7AMdlgMul6s2ay7+uvZ7LhBx/o1wnW83rG6KDrExkiB2ePu6tSjmH6+IU66Lq3t66fPZt1e+Ljdb1GDWlPkya6Hh1tXtGhgyycMkV+oEDf5tdK9/Mz6aDrb78d5fC99NAhXff1leIef1zX79yxWXmuja4fRd+7KFQvXixBB12vVfiyHoeXrvfrJ9u0by87//ST3fJPntT1kBDZpEoVXd+zJ/X6w4d1vU4dWZ83r7y3S2ysrmuabHjtmq4vWaLH4aXX8jmig64XLqzrG+c8Y71ekiP1+Hhdf+016+U6d65Dp0RPTjbqjz8ep4Oulwq4oV+mkFz7y5ZJQTVr6rqu6/v26bq/vywaMybrcp9+4qAOut619Z+6HrfH/kZffqnroEc89ZKeh0gddH35jKt2N23ZUur+/HPHjstC27ay3zf+H6ScnN5lNumg61984VxZFr74Qorq2NF6vs+du5L6fuEEO3dad+vaNXttSsvRo7r+3nu6HhHhmvJyG/Wbfv9Qz+k5577/r/+P8LCdxwWHF+hen3rpjEJv8HMD/Xr0dZeUe/3wdX1G8xn6KEbpoxilT6w6UQ//N9yhfR+2c/ggos5hzsmN33SnQ/BKly5NREREuuU3b96kdOnSOVP0FQqFwszNmxLFFhMDrVrBl19mr5wtW5bQvn037t41Ua2aN59+ugkvr8JZ76hwPVFRsGGDhMv27i3ZFoOCJBT3lVdg0iQJi7xzR0ILq1QRD96PPhLD561bJRnorVviDf3rrzB6NLzwghjOVqzoehNXxcNDUjiYA6RX5H8eEP9vh+wechkfH6tVw4kTMj1wQKa1aztQQNpI9Hz50m3StKlEul64IIM2LCQkiPc4yD3VITSbKCPNAxCP6zyGaC5SnG0bEmSdTcj47dvylQR4800H67FUocnXHOCnn6Qsu5QowZcMJzLRl1oFLvISUzL2IrGJpu/f+yAtW4qtjSOR6N9/L59PSAjMn2/jE235EMPDUxKrNqgWw08/SQjx2LH+KQHimZGQIMlgY2MlqHzhwjSWQwa5j9WsvJ+1f18jJAT2XinM+3whli5gjUSvWjVd+YmJUn5EhFxfmzdbR0NYqFJFbsdNmoi1+lNPyflJh4+P1Tz98GE4coS3+Ya9cZUJCZEymtbdYdN2b7y8xMpn2DBZNGiQNellZixeDMuXe+PurrNo8N8U5qrVrgtSPuvQUPmMQH4CLDYm9jh6FOYvFe+WT1//KPUoC1vMeQaCj2/mRaYCMGl++uy7t27JMQP06ZP1Mdli8WDfbGqcsmzvbTm3aT8fR7F8BXfvlmlIiI6nJ+iZWPxkRm5EoleqJP/hMk1mrFAoFIps81SVpwjrG0aQdxDbL22n8fTGnL51OusdsyCkSgj91vej68yu+Ab7EnE4gpnNZ7LkhSXE3oh1QcsViocPp0V0Pa2hopno6Gi8s51BSKFQKKwkJYl2evYslC4N8+ZlavmaIVu2LKFDh+4pAvratQcoUMDOMG6F60lOFtPnH36A55+HypVFzWzZEt5+Wwx6LSbAJUpItsX33hMVbv9+6T05fFiy933yiZTRsGH2DfEV/32SLoBZV1zu3g2wJvF8ELDor6dOiXX/2bPy3uKWkSkOiOi+vlZLjo0brcs3bYLoaLELcUiwB1KlydTk5uvlBU+ESAbEBWfNBdmI6AsWiGVDtWrQrJmj9Vhp00bORXw8/PGH/W3u5i/FVF4E4NMKs3HDJPcPexisYqmmuTF2rMzPm5e5oHvzJnz6qcx//XUa+3lLXefPi38GQLlyPPssdOumYzJpDB+etSfHDz+I9U2BAvDbb3ZsbzTPlNlyFTxTbGK+Yxj7TviKCm+xtipfPl35Y8eKqBoUBEuWZNyR5OcnwnWhQtIn8NlnGTTYkmDzzBl279KZyFAAZs+2VG/rwS2dLpoGX30lXvpRUTB8eAZlmzEa4aOP5Ny98w7UamR+prh40SqiFyuWsn3//tIBEB8PX3xBhkybJtMujy2leoVDqfz+U1GokEwPHeJlJgOwfKUb16+n3mztWonTrlIlCy95OzRoINMdiaKYx+LD8duS7yDLvAgZYEmXYGlnSIh5RTatymwf5Vztia5QKBSK3KNJiSZsGbiFknlLcurWKRpNa8SOSzuy3jELNE2jZr+aDD0+lNqD5P/fvhn7mFBxAnum7UE32dcHFYr/Kg7/wxo2bBjDhg1D0zRGjhyZ8n7YsGG88cYb9OrVi5rZ/QeoUCgUNvzvf/Kg6ucnAkB2dNPNmxebBXSd6tV9WLv2ACEh6cUGhYuIjhZj1tGjoV07UW/q1BGT319/FYVG10WEevJJUT3++UcUq3PnYPlyCVXr00c8fh0xU1YoLOhGSL4MRyEJd/69JdG5HTrc53bZUK6cTE+ftgYRFyni4P0trYieQQ6aevVkaolKBRnAAdCiRTZ1NXMkOkC30hI+/w/tZEERa16JP/+U6TPPZM/bWdNkUAnAzJn2t/llTzWiyEtFwwk6Ji6VhRmJ6LZiqeZOrVoSCWwyWaOY7fHTT9LJERoKffumWWlRTc+ftxpQm4XdL7/UcXfXWbFCS8n5aY87d+Dzz2X+q6+sImgqdBtRWvPh8cfhme4SJj4i4i2rgO/tnS6898YNax6RceNS6c52CQ6WvKEgg4SuXrWzkaWQixd5e93jAPRpcJL27e211/rhu7uLN76mSX+oJTepPRYtgqNHNQIDTbz9tm6t88IFa4eBzcFomvSvAsyaJdH0aUlKEqEfYOBTZjU9o0h0my9iBU5Sy/soui4/TbZYRnVYosqdoU4d+Q5eSi7MZQpzhjLoGAgMtGr4zpL2+knpMMkg6CkrPK39N0pEVygUioeMSsGV2PbiNmoVqkVEbASPzXqMZSeWuaRsn3w+dPmpCy9sfoEC1QsQdyuOv178ixnNZ3D90PWsC1Ao/iM4/Di1d+9e9u7di67rHDx4MOX93r17OXbsGKGhoczM6KlHoVAoHGTqVInSA9FeHYrSTMONGwfp2vUp7t7VqVFDCei5QnQ0rFghPR716smTe5s2MGoUrF4t6wMCRMUcPVq2vXZNBPOFC8VToW1buxG1CoXTJF8DjHAa9lKL2CRPgoIkKvpBwRKJfvq0dRCGJcA3S2y9PgyGDNWtunVlaitWbt8uU0sUrGPYRhZbhwG1rCDC8WGqcZ2QFOHR0ocGYvuSXZ55RqY7d1o1alv+WCNhti+bfsQQbhaSzTYc6UgllsoxWGxmZs8WgTUtSUlWQXnYMDudDraR6BYPEXNHQvny0K2bCN2ZifQzZoiQXrWqDLCxj01iSIN81p997YU7SayiI3t/N/sWFS+ersfi++8l8rtmTXjuuYzbYUv37jLQJz4evvnGzgbmc7x7n4H1t2rgThJfvGLroWKys5MQGmq1Pfnuu4zb8PPPMu3XL1aEYMvneuWKdehAmh6Bxx6TiPCYGKuVkC1r10qEdoGQGDo1XyELDRlEoqfpjOhaUHqflixJvdmmTTJt3TrjY8kIPz9rZ9pRKnMGsXKx3BuyQ26K6B4eGW+nUCgUigeTQv6F2NB/A+3Ltic2KZauc7ry0+6fXFZ+8cbFGbx7MG2/aYuHnwcXNl9gSq0prH5vNYkxiS6rR6F4UHFYRF+3bh3r1q2jX79+rFy5MuX9unXr+Pvvv5kyZQrl7QwpVSgUCkfZtEmssUEizLp1c76M2NiTnDjRkbffNlGnji9hYQcIDi7n0nY+kiQmikfEqFHi1RAUBI8/Lr4Bu3bJWPwSJcTrfOJEsWS5dQtWroSRI6FjR/EuUChyg+RLouOFa2xEvESaNs22o0GuYLGVDg8XDRacsINIMeVGBPQMQr0tdi0HD0rEta5nV0S3EeBsItGDi3pRHYlG30CLFMVu61a5RZQsKc5N2aVQIahfX+ZXrEi97tIl2LxD2tKDBVb/igzvK7aWNDLfrp3YXdy4IQJrWsLCpJ6QEOjVy06RFhHd1mLExtJm4MAYQCxj7EVGm0yS+gFkkI6bW/ptBNsLVzoAypbT6BGwGoAf55g7H9N0ICQlSUc0SD+lo9e/rSf91Kliy5MKs3j9w46GAPRkHiVq24rOGYvoAG+9JdP580lnjwLSt7pmjcw/+6y58oIFRcU1mWDHjlTtsG33wIEyv2BB+nJXrpRp1w4n8fBINi/1TL8hpBsS8nhJGS6yfr00AUSsN1vhp4z6cBZLx9kJKqSI6DlJKZXWZzxlkEo2RXRb4dyU+ceqUCgUigeUPF55+Kv3XwyoOQCTbuKlZS/x8bqPM7RmdhY3Dzca/68xrx55lUrdKmFKNrHl6y38WOVHji897pI6FIoHFacfL2fMmEFAQEButEWhUDzCnD8vic2SkqBHD/jwQ+fLiI4+zr59LUlMvESrVlXYvPm0EtBzwsmT4gfQqZNEjDdvLlHlmzaJ53np0vDii2Lqe+6cvH7/XXpCatTITCFSKFxL8kW4BsTpbNSaAyKiP0hYvLWvXJGvCmTsRJKOtCJ6BpQuLSJYfLxovJcuSXJJNzcnExemsuewSUiRPz8tkKyKW2icIqJv3iyrmzbNnpWLLZ07y3TVqtTLLaJ6Q/edFMMmCjojPxwtvRDt7g5PPy1L7ImulmVPP52Bo5Ql7NdoFFNzSCWih4YmU6WKTmKieI2nZdMmua0GBMCzz9pvdrq225zQV8qLiP7H6frE4Z1ORP/rL7m+ChZ0vhO6QwcoVUrE/3RtL1aMGHyZd0W+VEOZkLpuPXO1tXZtGSWRlCS2LWmZO1c031atdEqUMEfhGwzW823JeGrH+8Yy8uHff8UdzBbLNdSh9VnrQi2D3yVv71Tfs5rFb+LrK+fDIpzv3y/tLFIk+/YrFc1pWWxFdEsHW3bw8EjtY54iomdTAbeNRFciukKhUDy8eLh5MO2JaYxsPhKAT/79hFdXvIrRZMxiT8fJWyIvvf7sxTNLnyFvybxEno9kTtc5zOk2h8jzdqIJFIr/AA6J6E8++SRRUVEp85m9FAqFwlliY+WB//p1Gfo9c6bzQsymTQsJDa3G2bOX8fWtQs2a6/DyyuZT7qNKQoJYsbz5poTLVaggIYQrV0oIniU886efxI/izBkZg//ss06ogQpFLmC8AmclfnqroQnw4Iro165Z3SkcjkT39bXOZ5LE3d3dag1x8iScOCHzZcpkupsd7Nu5EBREbfYAsJ/QdCJ6kybO1GGfFi1kunVr6mDaf/+Vadu8Nobjnp6pOxhSYStEW4/BItJbIp8tmExW8bhHjwyKdHe3+mXESNS5rS+8pkHPntLo+fPT724pv1s38PfPoI60bbehaflrFOc8Mbqv+NLbCPi2dfbrl1oMdQSDQfYDO4ldixZlJR2J030ozRka+hxIbTFk29GSAZbOi4UL06+zdJB065YmQs6BXAClS0ufrckEf/9tXX7pEhw/LsfVunm4zR6ZPPrYlO8elCdl9MaWLTK15BpwPEFveiyR6MepyDnkBlCqVPbLA+mUsWA5BM0Fdi5G1+ksCoVCobgPaJrG6MdG82OnH9HQmLRrEs8uepZEo2ttVyp2qcgrh1+hyfAmGNwNHF9ynElVJ7Hvx30Yk9SPieK/hUMiet68edHMilbevHkzfWWHiRMnUqpUKby9vWnQoAE7LMM27bBo0SLq1q1LYGAgfn5+1KxZk9mWrEEKheKhQ9clmdzevaLRLlmSiSaSARs3LqRjx6c5cyaZmTMDqFlzHZ6eyjrEIa5exee339CefFLGhbdrB+PHiwLn4SHGr998A/v2Sca5OXNg0KCchc4pFC5GSxYR/QqFuW4MxmAQT+gHiYIFRWRNToY9okO7PBIdbOwiTlhFdIe911OwjUS3+auYJw812QfAPmqi5wlA10lJpNm4sbP1pKduXdGqL1+2OqaAVURvXviEdWFwcCY9rrYiujX6uFkzKT883JqfE8QC5+ZNEbebNcukgWn9M9LYyTzxhEzXr0/tu67rqUX0zLH/91wrEMKTSCj3Ip5M1ZbERKsYnV1fest+YWHW4G8AgoP5E1n5FAvRgtNE/zsgoj/1lEzXrRMPfQtRUdZOmI4d0+yUNmdGBgl1W7WS6caN1mWWvABVq0LeABuxQMvk0ce2sypv3lT2SLbTnNxbLIL5BYoTgXj8200u6wR58ljn/f1zNlTfdgCZEtEVCoXiv8GQekOY02MOHgYP5h2eR+ffOxOdGJ31jk7g6edJmzFteGnfS5RoVoKk2CS2f7qdn+v+zPnN511al0JxP8n6Xy9i4WJv3hXMnTuXYcOGMXnyZBo0aMC4ceNo3749x48fp4Adn8t8+fLxwQcfUKlSJTw9PVm2bBkDBgygQIECtG/f3qVtUygUuc+YMTKU291dItQcjsw0s337Up577mWio3Vq1vRl7tx9SkDPivBwGVO/aBHali3ktY1YK1RI7Fsef1wShSr7LsXDgDECwkXYBahUKbUe9iDg4SHOIzduiMUKWKPTs8RWOM8ipNySnubUKesyp0X0jKJY8+ShCkdwJ4nb5OPSNdGwIyNFfMuJH7oFX18ZkbR7N2zbJh0N58/Ly90dGhW7CGYnlQytXCCNbYf1766/v/jDb94sgq6lP9Ai0jdpIvVkSP781pPr5ZXu86heXTa5eVM6FywdC+HhcPasXAft2mVxEjKyHClQgM4sYzxvspZW6EFrsXQhbN4sgnSBAlZfeWepUUMC6y9flvNhaaceGMRaRKnuzLIMxezMKFtWft/PnZNRBm3byvItW6RjqWxZ+SxSeabb1uPrm4HHjnR6jBtnX0SXZLu217PjInoV87Vx5IhMnU4IbAfLwIXLFCEftwAJIMgJtiK6cyNOMkfZuSgUCsV/h55VexLkHUT3ud1ZfWY1rX9pzfJnlxPsG5z1zk5QoGoB+m/oz74Z+/jn7X+IOBTBjKYzqPViLdp82Qbf/A/YH3SFwknue8qtsWPHMmjQIAYMGECVKlWYPHkyvr6+TJ8+3e72LVu2pHv37lSuXJmyZcvyxhtvUKNGDTZt2nSPW65QKHLKX39Zvc8nTMgi+s8O//47nz59rAJ6WNgh8uXLQYau/zJHj8Lnn0OdOjL+/X//g82b0XSdxJo1MY0eLarDpUswbRo8+aQS0BUPD8abcA72IsbfD1oUuoW0gbWZacCpsBUPM1V4rbkXL12yin7lnE4NkYF65u+PF4mUREzdT5+2CozlyjlvIZIRlqSNe/fKdN8+mVapAn55bY4/03uUfTsXsArbFnsOgA1i9U7z5lk0zvZDszMC02CAxx6TedvkpZZo69q1HRltlcHf85AQGrEVd5K4SHHOJVvtXCx/g1u1yn5CXU0DSzyKbdtPnfPgKoXxJIEGbE9/ITuI5TfeVuy2DD5t1MjODrYieibCvWXfI0fEHg7Siui2ZHJybD+YgACqVLGWC9bvU04GYllE9Fvk5yLyZU07uMFZbL8GGfQzZAsloisUCsV/i7Zl27K231ry+eRjx6UdNJvRjAuRF7Le0Uk0TSO0fyi9NvWi5gs1Adg7dS8TK01k38x9LktwqlDcDxyKRLfl2rVrvP3224SFhXH9+vV0XwCjE2P/EhMT2b17NyNGjEhZZjAYaNOmDVu3bs1yf13XWbt2LcePH+err76yu01CQgIJCQkp7y3e7iaTCZP6d5gtTCYTuq6r85dDHvXzePgwPPushq5rDBmiM2iQ7tQD24YN8+jS5VliYnRq1fLln38OEhhY8pE9n3Y5dgxtzhyYPx/NkhkN0A0GaNECvXt3TF26cNPLi5CQEKvyos6hU6hr7gEg+RZcsYroTiXRvIdY7LQtOCyi26rTWSTstYjoFy9a7UTSWGc7QMYiOkBZTnOacpw5I9HPQIrg6AosZVluWxYbjerVAS8boTPT4QbpE4tasNh0WGx1wCq6ZmlJYyvmZmBj2LSpJCndaWPfbvHVdszyJgOhNyAAP2Kpyy620Yh/w0tQyrzK8rc5p5Y6TZrAjBmwfbt1mUX0rs8OvEnItojevDn8+mtqEd1yjiwdJ6mwrScTEb1QIRGib9wQwbtuXWvHS506abfOJOGK7fXk5ZUysuLyZSnbYi9kyTuQHYKCwMs9iYRkD+KRESYPaiS6snNRKBSK/x71i9Zn04BNtPu1HcduHKPJ9Cb88/w/VAqu5PK6vPN50+XnLtR6oRbLX17O9UPXWTJgCftm7OPxSY8TUiWHP4AKxX3AaRG9f//+nD9/no8++ojChQuneKVnhxs3bmA0GimYxgywYMGCHLMRfNISGRlJ0aJFSUhIwM3NjR9//JG2lnGhaRgzZgyjR49OtzwiIoLERNcmVHhUMJlMREZGous6huyGOyke6fN4+7bGE0/kJzrancaNExgx4nbqIdxZEB9/gv/9ry8xMTqhoT789ttakpN9ue5MIf9RDJcv471kCT6LFuFx6FDKct3Dg4TmzUno1In4du3QzaFvJpOJyDt3Hsnr0FVERqrs8/cd4w24ak52yYMbiW6rA/r7OxG5bbthFt9Ti2B+6ZLVlaWQ0zmWM4gQMit0ZRAz8TNnxMoFcmZxkZZK5uc4uyL6JQdFdFvv6zT2KBYRff9+EQpjYsRmBMTSJFNso5XT9oqYsXTiWIRccFLkzsi329yJ0ZRNbKMR288E0xfp99y2TTaxG9HtBA0bynTHDrFZcXe3CupNMIfTpxPRHXsWsNjM7N9vvTYtkeh2LWhsQ6xtleK0tWvyua1dK9dKxYqSwgNkHmOajTPC9nry9CRvXjnUW7ck0t9kkk1y4mGuaRDiF8vFSOmAMRh0goKy/ywFys5FoVAoFM5ROaQym1/YTLvZ7Th+8zhNpzdlZZ+V1Ctqr0c755RoUoLBewazbdw2NozawLl/zzE5dDKN3m5Ei49a4OHrkSv1KhS5gdMi+qZNm9i4cSM17+MTap48edi3bx/R0dGEhYUxbNgwypQpQ8uWLdNtO2LECIYNG5byPioqiuLFixMSEkJgBg8/iswxmUxomkZISIgS3XLAo3oek5Phuec0wsM1SpXS+fNPD4KDHfcwj409yunTPRk1KolffsnH55+vpGzZ2o/UOUzHzZuwYIFEnW/ciGZWJ3R3d2jXDr1XL+jSBc+8efEEbKWIR/U6dCWervKwUGSfqAgSoj05g/gsVKt2n9uTAbZ/O5wK5rWNPs8iEt3is37lilUvdFr00zNQz9KI6KdPg2WwnyUC3hVYRPRTpySa3pIgtUoV4I6jkehuGcyL9YyXlyTPvHBBIo1BrDay/FxsRfQMItEtf5HPn5fbc2CgOGqBVcDPnMxF9FD2A3DwjLQlPBxu35ZjCg11pPyMqVxZTmtsrHy+FSuCpT/WUm9mgnZmVKwol+/t23J9eniIB7qmZdBu23OdhTpcvbqI6EeOWG1XgoPN37mbDjbQtj7zfb1ECRHRLZ0URYtmrsM7QqBvMhfNnU/58hpxc3P6cSwVts12pZ2LikRXKBSK/y4l8pZg44CNdPq9E7su7+KxWY+xtPdSWpVulSv1uXm40eSdJlTtWZVVb6zi+JLjbP5yM4fnHKbjDx2p0NmF0RgKRS7i9L+24sWLu8zDKDg4GDc3N65du5Zq+bVr1yiUSdiUwWCgnNngs2bNmhw9epQxY8bYFdG9vLzwsvOP0mAwKMEoB2iaps6hC3gUz+O770JYmDz0LVmiUaCA40+jj6gsmgAAt8BJREFUZ89u5PLlp0lKukbhwqH89ts/3L5teuTOISDK0vLlMu5+xQrpnbDQvDn07o3WowcEB2cZI/goXoeuRJ23+492NY4zVMKEG3ny5CxSNDfJtohuq9plcb1ZLGJsB9s5fz4yENHNCU4tnugXL+aOiF6smGimFpHbEiVeqhSwP+eR6AaDpIY4dkyE+vBwWV69ugONS5N80h4BAdLW8HARzwsVkvPk7e1o8uwMOkrM4nV1JDT/4DEPdN0q0FesKMJ0TjAYpJy9e6XcChWsIrql3lSJbp3A21sS3x47JmWa+wQoXlyKTBf57ISIXtqcDuXcuRzkArD9bM0nskQJGVFg8c/PqfUKQKCf9csZki/n4d62/bgqEl2hUCgUjhLiF8LavmvpPrc7YWfD6PRbJxb2XMjjFR7PtToDSwbyzOJnOLbkGCtfW8md8Dv80eUPKnWvRIfxHchb3P5/K4XiQcHpJ/9x48YxfPhwwi1PHDnA09OTOnXqEBYWlrLMZDIRFhZGIyfGo5pMplS+5wqF4sFk+nQYP17mf/nFgWHzNoSF/Ub16i2YN+8afn6h1KwZhoeHa7OJPxQcPAjDhkk4XPfusHSpCOg1a8LXX0vo44YN8PLLOc9WplA8LFyHE0gES4UKOY8UzS1s7VyyTi6ZAVlEovv7p849GhCQHc0z80j0gkjww7VrYhsD2fFdzxhNs4ryx45JJDCYBWi/7Hiip78gLALrqVNw9qzMO+R1bVtnJifWUpZt8lVLJHaWZGHnUoljuJHMnUgDly9bbW8qucjO1OIFfvSodJRERYG7lkwFzEMCsimiQ2q/+5MnZb58+Qw2dkJEt3ROnDsnnylkw7s8jZ0LWBOBWiyFXCOiWzu98wbkXKm2jRVSIrpCoVAonCGPVx6WP7ucrhW7kmBMoNvcbsw/PD/X663UtRKvHnmVxu80xuBu4Nifx5hYeSJbvt2CMUkNhVI8uDgdid6rVy9iY2MpW7Ysvr6+eKQJeblledJxkGHDhtGvXz/q1q1L/fr1GTduHDExMQwYMACAvn37UrRoUcaMGQOIx3ndunUpW7YsCQkJrFixgtmzZzNp0iRnD0WhUNxDNm0SXRdg1Ch48knH9w0L+5UuXfoSF6ezZYs/X331Dx4e+R+dhI63b8Mff0jUuSX7HUh44/PPQ//+rs3qp1A8bFxNLaI/qFgibyEHOmQWowE1TaLcLSkisheVn7kneiHEcPrSJYkWB9dGooNEAJ86BZvNNtx585otsh0W0W3V6sxFdMuASIeixO0IrfYoW1ZGXZ05Y3U/cVzkzkBpN19AXiRSgvOcpQxnz1oj0V0lolt+To4etXYwlPK/ieddc6baHCi1pUrJ9Px5azGuENFLlJDpuXNiFQMS4S44OILWjp2LpS/aco24QkTP628V0f0yu4QdJLci0ZWdi0KhUDwaeLl7Mf/p+fRb3I8/Dv3BMwufITYpln41++VqvZ7+nrT9ui01nq/B8iHLubD5AqvfXs2BXw7w+OTHKd6oeNaFKBT3GKdF9HHjxrm0Ab169SIiIoKRI0dy9epVatasyapVq1KSjZ4/fz7VUPmYmBheeeUVLl68iI+PD5UqVeLXX3+lV69eLm2XQqFwHeHhEjSdlARPPQUffeT4vmvWzOaJJ/oRF6dTt64/a9YcwdvbcQ/1hxZdh40bYfJkWLTI6png4QFdusCAAdChQ+qQU4XiUSXi4RDRHQxizpykpCw3yZ/fKqJnS/TLyBPdrNZZItFjYmSxmxsUcPFt2SKAbtok0xSB21ERPVU0d/rIbov9R3i49VxZhNhMcVBELyP2/Jw+bRViHbNygaw80UEsdc5ShnPnRKiHTMRoJ7F0MISHi9gNUCLgDtw1b5Du4nV86IflHJ8/b7WesZyrdNjW42Ak+rVr1jY7fU3a1mH+bNN+f1wSie5vVacz7QdyEBWJrlAoFIqc4uHmwezus/Hz8GPq3qn0X9KfmKQYXqn3Sq7XXbB6QQb8O4C9M/ay5t01XDtwjemNp1N7cG3ajGmDT77sj4BTKFyN0+pLv36u740aOnQoQ4cOtbtu/fr1qd5/9tlnfPbZZy5vg0KhyB2iokTzvXFDEqrNmpWlpW8Kq1fPpmtXWwH9KHnzujjc8UEjMlK8biZPtnoAgHjfDBgAffq45ileofgvcRNOI94NTvsg30NsBbNsi2cO5KWx9VvPXg7IDNQzs09OXiLx1BJJ1EVozJ/fQZsSJ7AIoPv2yTQl0t3hk2jriZ5e5LUkYL16VXzXwfWR6CACtyVa32HLmyzsXABKIErxuXPWxKiuGg1g6cA4f95GRA+KArN1T06UWkvZFy5Y+0Msn0U6bM9vFr1O+fJJeTExVv9yp0V0207pNJHoFlwSiZ7H+v1yhYiuItEVCoVC4QrcDG781OUn/Dz9GL99PK+ueJWYxBjeafJOrtetGTRqD6xNpa6VWP3uavbN2Meen/Zw7M9jtPumHTWer4H2oPo1Kh4pnPZEj4qKsvu6e/cuibZZrBQKxSOP0QjPPisJxAoXhiVLHPcB/uefX2wE9Dz/fQF9924YNEgMWF9/XQR0X19ZtmuXKElvvqkEdIXCHnfgAqLOORRNfJ9wSSS6Aw8QtvkubS1kHCbwRZn6Pma/CUCg213r5oHZqCMLLOJlVFTq96nCbnPgiW4Rbi9dsvq6uzIS3SKYX7liLd9xkTuDv+c2PRWW5K7nz1vLt/h35xTLebh40WrnUiIo2rpBuovXQbsUUkeiWyxSMrQcckId1jTrz6NF+Hfayugeiei+Ptbz5Zvd3Ag25FYkuhLR//tMnDiRUqVK4e3tTYMGDdixY0eG2yYlJfHJJ59QtmxZvL29CQ0NZdWqVTkqU6FQPHhomsZ37b/jg2YfAPDumnf5eN3H6A4EcbgC32Bfuk7vSv8N/QmpEkJsRCyL+y3ml1a/EHE04p60QaHIDKdF9MDAQIKCgtK9AgMD8fHxoWTJknz88cePjlexQqHIkPfeg+XL5aFuyRLHBYTo6IP8+ecQ4uJ06tXLw5o1R/6bAnp8vPic168PdevC1KkQGwtVq8KECRJe+NNPUKfOg5spUaF4ANBvwUXkHlH8AbZPdImI7sBDjK1wni0R3asalL8BxVdnuEmAW2zKfG6K6OneO6oYarah8en/7lpE9PBwq1joUOSygyK6RcDNVvJVQ94sN7GI6IcOQbRZ33aViF64sIwYMxph505zffmtnSauiES/ckVEeshE7HZSHc6fP/X7HEWim71mbJMB26sjO/h620ai5/y33TY9le0pyy6W70bXrjkvS/HgMnfuXIYNG8bHH3/Mnj17CA0NpX379ly3+Ful4cMPP2TKlCn88MMPHDlyhJdffpnu3buzd+/ebJepUCgeTDRN47NWn/FFqy8A+OTfT3j7n7fvmZAOULJ5SV7a+xKtv2yNu4874evDmRw6mbAPwkiKzdraUKHILZwW0WfOnEmRIkV4//33Wbx4MYsXL+b999+naNGiTJo0icGDB/P999/z5Zdf5kZ7FQrFQ8K0afDttzI/axbUq+fYftHRB9i/vxW9esUyenQpVq/+D0agX7kCI0dKSN4LL4hK4ekpYfsbN8LBg/Dqq6nDSRUKRYbcvJWPeESVdpWQmBvY6oDZFtEdIMciOoBb/jRCdGoC3GNS5nNDRE8b8ZsiXtoK15nmhMg8Er1QodTv8+ZNLUZmiO0Hl8kOFmE4Ls5qF+OwiJ5vGPg0gQLfZ7hJIbMvvcXuJiAgB591GtzcrOf70CGZFg5KsG6QTtB2XAi2dIboOty5I/OuiEQHF4jotp5E5rrTjp5zxTn28baNRHdtB7kr0qTs3w8rVsDAgTkvS/HgMnbsWAYNGsSAAQOoUqUKkydPxtfXl+nTp9vdfvbs2bz//vt06tSJMmXKMGTIEDp16sS3lj/72ShToVA82IxoNoLvO8h/kbHbxjJk+RBMGeXNyQXcPN1o+l5TXj3yKhU6V8CUZGLTF5uYWHkiRxYcuaeivkJhwem/WrNmzeLbb7+lZ8+eKcu6dOlC9erVmTJlCmFhYZQoUYLPP/+c999/36WNVSgUDwcbNsCQITI/ahTY3C4y5d9//yA+fiienrfIk6cuI0b8g4dHUNY7Pizs2QPjxsGcOdbkgCVKwCuviJiurFoUimxx8ZZ0tBXMn4SXlyNK6P3BVnN94EX0LAhwv7eR6K4W0X19Zffk5DTlZ4Xth5hJJLqfn5z7aBsXlLTCfYa4BUDJTZluEux2G4zW5K6u7jwKDoaICGuUfv4Am6ivHFy8bm5yvVgEdIMh/WedQg5F9AzLzQg7di5pRXRXeJjb2rn4uCAS3XagmisGrYWEQMeOOS9H8eCSmJjI7t27GTFiRMoyg8FAmzZt2Lp1q919EhIS8E7zPfTx8WGTOftzdspUKBQPPq81eA0/Tz8G/TWIKbunkGhM5OcuP+NmcHEynEwILBXIM0uf4djiY/z95t9Eno9k/tPzKd2qNB2+70CBqi7Obq9QZILTIvqWLVuYPHlyuuW1atVK+YFs2rQp5y2GhAqF4pHi9Gl46inRiHv1koBrR1i1ajpPPjmQ8uVhwoRa1KixGg+PwFxt6z3BaBQvm3HjJMrcQpMm4nHerZtrQscUikeYS9ES4lu82IMdkeJEnsQcYSv8OZqHwlny5nIketqEqHZF9MyymaZSFtMPvNQ0afeNG2nKzwo7QmtGBAdbRfQ8eVx7q89vFtEtOO3/nQUhIXD0qE19gTaV5dB4O39+q4geHJzJx2jrTeLAF8b2M/Tzsznfjkaq3SMRPVUkur9rI9GV85vCEW7cuIHRaKRgmhtHwYIFOXbsmN192rdvz9ixY2nevDlly5YlLCyMRYsWYTT3tGWnzISEBBISrKNcosxJMEwmk7KGzSYmkwld19X5yyHqPKamf2h/vNy86Lu4LzP2zSDZlMy0LtMyFdJz4xxW7FqRMm3LsPnrzWz5egtn155lcuhk6g+tT/OPm+Od14WJQR4A1HWYc3Lj3Dn9d7548eJMmzYtnV3LtGnTKG42Orx58yZBaU0EFQrFf57ISOjSBW7eFPuWGTMce6BbtWoa3bu/SHw8+PoGEBq6/OEX0GNixNPmu+/EdBfkAb1XL3jjDcf9bRQKRZak+KGXerA7pO5VJLqt9ph7kehx1vkA15eftt0porrtwTmsStt3L8yWiG7H8iMjbB25XN3REOx2J8O6XFJ+2pEAQTYPITm8ePPlkw53yOK8255fB8y+bR89suUNbrC5TnJRRLftg/D1c9pZM1OUiK7ILcaPH8+gQYOoVKkSmqZRtmxZBgwYkCOrljFjxjB69Oh0yyMiIkhMTMxJcx9ZTCYTkZGR6LqOweDa+8ujhDqP6WldoDWTWk/ilbBXmH1gNrFxsYxvOT5DIT03z2GVV6pQrHMxtn68lfBV4Wwfv50Dvx2g/gf1qdizIprhv/FjqK7DnBMZGenyMp1+2vzmm294+umnWblyJfXMItCuXbs4duwYCxYsAGDnzp306tXLtS1VKBQPNMnJog8fPSq+r4sXO/acvWLFVJ56ahDx8dCoUV5WrTpKQEDhXG9vrnHjhiQFnTBBehNAVIKXXxbblgfZsFmheEi5gtwzipV4sP9gukREdyCq1laky61I9AAPq4juimSGaclQvHQ0Ej0V9h+msiVyOxGJbtu54GoRPa9+Bzc3q91Kborobm5pys/hB54vn3U+7YiDVNieawceHm07XrIVLG8brWT+sqYtxxUieqoRKS6wc7HFIqLrBQqgXb/uhIeQ4lEiODgYNzc3rl27lmr5tWvXKJTBNRMSEsLixYuJj4/n5s2bFClShOHDh1OmTJlslzlixAiGDRuW8j4qKorixYsTEhJCYG4McXoEMJlMaJpGSEiIEt1ygDqP9nmxwIsEBQbx7KJnWXhyIR6eHszqNgt3Q3pZMbfPYYECBSi3vByn/znN32/+zc3jN9nw1gZOzTlFh/EdKFLv4X/mVtdhzvHM4r96dnBaRH/iiSc4fvw4U6ZM4fjx4wB07NiRxYsXU6pUKQCGWMyQFQrFI8Pbb8Pff4swtHSpY1rxihU/89RTg1ME9H/+OY6/v4vHpN8rzp2DsWNh6lSINXsFly0rJ6Zfv9wNO1UoHnEikHwCTicSvMfY/o/Lhf90KTjpgpEtfN2tUYL3TUR3OBLdvlBpq9E43NnwgIjomslIYKC1r9bV5dsK0kFBoHnZHGu6BznnhGDbiPFMR0o4afZtK8hn65q0FdHNn62myeFaVrlCRPfyth6Lh2cuiehhYWiff+64p57igWXt2rU0b94cdxf6QXl6elKnTh3CwsLo1q0bIGJNWFgYQ4cOzXRfb29vihYtSlJSEgsXLkzJk5adMr28vPCy82U1GAxKMMoBmqapc+gC1Hm0z9NVn8bd4E7PBT2Zc3gOJkz82v1XPNzS5yS6F+ewfIfylDlQhu3fb2fD6A1c2n6JaY2mUeuFWrT+ojV+BXIpmuQeoa7DnJEb5y1bv8alSpVizJgxrm6LQqF4SJkyBcaPl/nZs6F27az3WbHiZ558cjAJCdC4cV7+/vshFdAPHoSvv4Y//rCGBNauDe+9J+bwDkdKKhSK7HIDCZt90HPz2kai5+Z/4Ww5njiJt3tyynxudAj4+IggaAm8z1EkumcZu4tthWeHxdEHxM4FoxFfX6uI7upIdNtOBX9/XHrx2orduSWi5zgS3eazta3aFZ1SnmWLp8y7+vuZ0tYqVeR/ieKhp23btly5coUC5l7ihg0bsnDhQooWLZqjcocNG0a/fv2oW7cu9evXZ9y4ccTExDBgwAAA+vbtS9GiRVOe+bdv386lS5eoWbMmly5dYtSoUZhMJt59912Hy1QoFP8NulfuzsKeC+kxrwfzDs/DaDLyx1N/2BXS7wVunm40frsx1ftUZ817azgw+wB7p+3lyIIjPPbJY9R7pR4GdyVCK1xDtv+6xcbGcv78+XR+ZTVq1MhxoxQKxcPD2rVgCTD57DPRjbPi7t09XL/+P7y8oG7dQFatOvbwCeg7d8Inn8CyZdZlrVuLeN6mjTImVSjuITcRY+WHSUTPzf41WwEx10R0D2uiydyIRNc0EbZjzPlLU0RuZyortQ+MN8GjpN3VtqKrwyJ6NiPRXS1yYzSmErpdXb6tuO3rS2rhPIciejqBPiOcFNFty83WNWn7TGPzBbWt2hWdX57B1gvD1fcB9dfjv4eexsLr8OHDqZJxZpdevXoRERHByJEjuXr1KjVr1mTVqlUpiUHPnz+fKoIvPj6eDz/8kDNnzuDv70+nTp2YPXt2KtuVrMpUKBT/HZ6o+ASLei3iqXlPsfDoQnot6MWcHnPwdMvFoZZZkKdwHrr/0p26L9dl5WsrubLnCqveWMWen/fQ4fsOlH6s9H1rm+K/g9OPVhEREQwYMICVK1faXW/J0K1QKP77nDwJPXqIH/qzz8L772e9z927e9i/vw2lSt1lxoxQ2rX7B3//B9yDwZbt22H0aLDcAzVNeg7eew/q1r2/bVMoHlFuPiSR6J6ZOWK4kHsSie5p/b+XW9Y0Pj52RHTbyrL6z+kdmmX59uYzJZsiuitsQNJiW2ZuRqL7+JD6gs2hUmsrnLtSRLftPEodiZ51HgFAsqPfA7LlSOQgSkRXOMPQoUMztFpZv359qvctWrTgyJEjOSpToVD8t+hcoTOLey2m+9zu/HnsT56e/zTzeszDyz0XoiucoHjj4ry440X2TttL2PthXD90nV9a/ULlpyrT9uu2BJUJyroQhSIDnH6Ee/PNN7lz5w7bt2/Hx8eHVatWMWvWLMqXL8/SpUtzo40KheIB5PZt6NxZpg0awLRpWT+8LVs2mdmzW5CcfJuAgEY88cS/D4+AvnUrdOgADRuKgO7mJl7nx47B/PlKQFfkOqVLl6ZMmTJOv77//vv73fRc54aKRE/FPRHRPazWF7klotvqttkS0bPAVjjPViS6R+bDlm0j3XPjHNkK3a4W6dOV7cJw7GyJ6A5gK5ynjkR3sJyoKLuLXR0fZNs2FYmuyApN09BsPti07xUKheJ+0rF8R5Y8swRvd2+WHl9Kj/k9SEjO+WiZnGJwM1BncB1eO/Ea9V6th2bQOLrwKBMrT2T1e6tJiLr/bVQ8nDj9aLV27VqWLFlC3bp1MRgMlCxZkrZt2xIQEMCYMWN4/PHHc6OdCoXiASIpCXr1ghMnoHhxWLw4a//RpUt/5OmnX8XNDaZPD6Vp01W4uwdkvtODwKZNEnm+Zo28d3ODvn0l7L5cufvbNsUjxcyZM7O1nyXp93+ZKAKBB19Et9VfczMS3VaYyzUR3csa3Zsbdi6Q+hylCN62B3Q/RHQnPNFty88NEd22za4uP52I7kI7F9v/C/ckEj3oZbgzCfJ0z7yAIUPgu+9kiJ0NuoOB7I6iItEVzqDrOq1bt05JLBobG0uXLl3wTPOl37Nnz/1onkKhUNC+XHv+6v0XXf7owrITy+i1oBdzn5p7v5sFgE8+HzpN6ETdl+vy97C/ObP6DFu+3sK+Gfto9Vkrag2shcFN+aUrHMfpv24xMTEpiU2CgoKIiIigQoUKVK9eXf14KxSPALoOr70Gq1fLQ/bSpVDo/9m777iq6j+O46/LBrcijty5J+7MmVvLXW7FbZo5yBy5NffIcmHmwDL3TlOTHLlXuMWRaabiyq2g3Pv74ybBD1CQCwfw/Xw8eMS959xzPvfLTbjv+z2fb8aXP+ZFgB4cDBUqpKFeva0JP0DfvRuGDQM/P+ttBwfrzPMvvoBckS9SJxKXKleubHQJCZqdyUyaNAn7j+D4Wmc4PkJ0Z5f/0rq4mokeVmhuGzYlDLsQ5GsIG0K/1kz0V3x6EPXMaNsIG3S/YlJ8jIUNt23dziXsuIR9DhHE8DxhP7QIF6Lbp4W3L7/6eHnyWGej/1+yH3aBW1t4nbVxo0shetIzbNiwcLcbNGhgUCUiIlGrnqs661us54MfP2BtwFparW7F1ApTjS4rlEdhD1pvbs25jefY8tkWbgfc5qeuP3FwxkFqTqlJrmp6fy/RE+O3Vvny5SMgIIAcOXJQrFgxZs+eTY4cOfDx8SFTpkxxUaOIJCBTpsDs2dY3aj/+CJ6eL99/7doZNG3ag+BgqFgxDT//fJZkydzjpdbX8vvvMHgwbNxove3gAO3bW8PzN2BGr0h8CggIoFmzZuFuL168mIYNG8b4WGlcnmBn97JEznjxFaKHzTttHqJ/+SXMnYv9h43g388Y4ypEf/78FTsY3c4lbL+WSIQNcjUT/T9hP1B46YcLNmvnEoNjRfIztXWIHrY2W1+RohA96fn/EF1EJKGqnqs6a5qvocGSBqw8vZKQ4BCWNV8WbpFiI5lMJvK+n5e3a77NoVmH2D58O4HHAvm++vfkq5+PGpNqkC5POqPLlAQuxq/mXr16ce3aNcD6S/3nn38mW7ZsfPPNN4wZM8bmBYpIwrFmDXz+ufX7KVOgfv1X7T8t8QToZ89ae9SUKGEN0O3toXNnOH8evv1WAbokChcuXKBq1apGlxFt+fLlw9/fH39/f3bt2kWyZMmoUaPGax0rpWuwjauzvbD562uHctF4YJzORB80CP74Awf31KF3xVU7l1dONI9liB627tdq5/LSXiRxH6KHDbqNDdFjltxGu2d/2PNE43Uf9rivajFnpLA/q1heTBGBQnQRETFS7dy1WfHRChztHFlzYQ0d1nUgxGzjxUViyd7RnrI9y/LpuU8p82kZTPYmAtYFMLPQTDZ7b+bJP0+MLlESsBiH6K1bt6Zdu3YAlCxZkkuXLnHw4EH++uuvcLPJRCRpOXQIWra0vo/t3h169Xr5/tu3+9KsWU+Cg6FSpbQJN0C/fBk6dYKCBWHZMus70JYtrQuGfvstZM9udIUi0fbw4UN27NhhdBmvZd26dVSrVo1kL+3vELWUbgnrD/TIhM1fbd1nOaw4nYn+rxi0Bn9tUU5cypzZ+t/33ovV8cPWHXZW+kuF7Zvi/vLfadGecf2awgb/tm7nEjaEfuXCok4xWx8k2iF6DBPhGHTaiRFbB9M2XBs3AoXoIiJitHr56rG4yWLsTfb8cPwHuqzvgtli40+NbcAtnRt1vqlDt+PdyFM3D+ZnZvZ9tY9peaZxYMYBzM8TXs1ivFi/tXJzc6NEiRK2qEVEEqjLl6FePXjyBOrUga+/fvkbtfv39xMS8iklS4KjY1o2bjxLsmQJ7NKoGzdg7FiYOROC/53BWr8+jBoFRYsaW5tIFL755puXbv/7779ter6dO3cyceJEDh8+zLVr11i9enWEViszZsxg4sSJXL9+nWLFijFt2jTKlCkT43MtW7aMtm3bvnatqVIk/D904ytEj4+e6GHPEVcz0aOs/cIFePAg1ivJhg0zox1Cu7rCkiXW79OkeemucT0TPS6PH3Y8XtkTPeNcuPEZpOkRrWOHrfulLY5imAiHPZYtZ6IrRBcREYmZRvkbMbPaTLr5dWOe/zwc7R2Z9f4sTAnwF1X6AulpuaEl5zefZ4v3Fm6eusnPPX7m4PSDVBtXjXz18yXIusUYMX5rZbFYWLFiBdu2bePGjRuY/+86xFWrVtmsOBEx3v378MEHcP06FClizQ5eFsrcv7+fo0drYm//gK++qkCRImtxc0sbfwW/ysOHMHkyTJwIjx5Z76tSBcaMgXLlDC1N5FV69+5NpkyZcIoiMQsOtm1Lk0ePHlGsWDE6dOhA48aNI2xfunQp3t7e+Pj4ULZsWaZOnUqtWrUICAgIXYTc09OT55E0t96yZQuZ/51RfP/+ffbs2cOSF+Hka0iZXCH6C0llJnqUAauLi01S0rDhf4z61Ufzysuw4xIXYxT2Z2vrmehh63V25uUz0R0zw1uLo33sN30metjhU4guIiJJVf236+Oa3BWvNV7MPjwbJ3snvq79dYINpHPXyk2uo7k4/O1htg3dxq0zt1jacCnZKmSjxsQaZHkni9ElSgIQ47dWvXv3Zvbs2bz33ntkyJAhwf4PICKx9/y5NSs4fhwyZoSffoKUKaPef+XKr1i+fABduwaTOnUlihTZgIPDy3vGxpuQEJg/H4YMsX4iAFC6tDU8r1ZN7zwlUciePTvjx4+nadOmkW739/enZMmSNjtfnTp1qFOnTpTbp0yZQufOnWnfvj0APj4+bNiwgXnz5jFgwIDQml5l7dq11KxZE5dXBKNBQUEEBQWF3r5//37o9ymSWyJ8sJ/QWP+ZsSZoZrM5Rv2QX+RuFsDyigeGPY+d3cvPYzabsVhiPnZhz+HgELPnEl12diZe9NuOi5+tNXS1PgeTKXbPIbJxjIsxChtf29ubbX78F8KOjb29GbPZHHpuM8Sqmbf1A4uIr88IY2ix/HdOs/mV5ww/3hbMZlt9UhUXr0Nrnc+fx/7nZv1Azu7f71/v/2f5T0Icu2fPnlG7dm18fHzIkyeP0eWIiERbqyKtMFvMtF/bnmkHpuFo58ikmpMSbI5o52BH6e6lKdKqCLsn7GbflH1c3nWZueXmUvDDglQdU1WLj77hYhyif//996xatYq6devGRT0ikkBYLNa+55s2WS/lXr8esmWLev+VK7+iZUtvgoMhX768DB26EXv71+ttbFMWi/VJ9OsHJ05Y78uVC8aNgw8/VHguiUrJkiU5fPhwlCG6yWTCEpdTnMMIDg7m8OHDDBw4MPQ+Ozs7qlevzt69e2N0rGXLltGlS5dX7jd27FhGjBgR6TZn5yBu3LgRo/MaIyMA9+7d58aNpzF8FDwPDub2K57nvXuOQLp/v7/NjRtRT3c1m83cu3cPi8WCXZRNyCN68MAJsF5l9PDhy8/x+tx58adqXPxsnzxxBqwtWR48uMONGxGvmIiuyMYx7BgFBcXs5x2VjGG+f/r0EZDi33PZ9mdw964JyADA48ePuHv3Li+uKbt56xaWSK4uia6wr8/Hj/8blwhj+Phx6PO9/+ABT1/5uv+v5uDgR9y48fC1awzLZMoQ+r3tXofWZ/bPP7F/XTx44AZYZzjcvHmD+/dj/v+z/OfevXtGlxCBo6Mjx44dM7oMEZHX4uXpRXBIMF1+6sKUfVNwtHdkbLWxCTZIB3BJ5UK10dUo3a0024Ztw3++P6dWnOLMmjOU/LgklYdUJplHAsg6JN7FOERPlSoVuXLliotaRCQB+fpra7twkwkWLYJSpaLed8WKKbRs+RnPnkHVqu4MGLAvYQTo/v7w+eewdav1dtq0MHQodOsWd/0HROLQyJEjefz4cZTbCxYsyMWLF+Olllu3bhESEkKGDBnC3Z8hQwbOnDkT7ePcu3ePAwcOsHLlylfuO3DgQLy9vUNv379/n6xZswLg4eEc2kImMUiZMiUeHi+5tCcKDo6Or3yeYde7zJAhHS/b3Ww2YzKZSJ8+fYxCt7DnyJTp5ed4XY6O/725ioufbdiW6u7uaWP1HCIbx3RhJiq5u7/ez/tlUqf+7/dsxoy2/RmEbYfi5paM1KlTh95OnyEDpEr12scOOy5p0/43LhHG8MmT0P1SpkhBylc8wbCLw6ZK5YaHh1vUO8dA2Pf4tn4d5soV+9dFihT/fZ8hgwd2djH//1n+E1W7NKO1bt2auXPnMm7cOKNLERGJsc4lO/PM/IxPNn7C+N3jSe6UnMGVBhtd1iulzJKSBnMb8E7vd/Ab4Me5jec4OP0gR32PUr5/ecr1KYejm4176kmCFuMQffjw4YwYMYJ58+bhGvavVRFJMtatgxc51YQJ0KhR1PuuWDGZli37hgboGzacw8UldbzUGaUrV2DwYFi40DoT3ckJevaEL7545UJwIglZwYIFX7rd0dGR7Nmzx1M1tpEqVSoCAwOjta+zszPOUTQ7TpXGPlGFRiaTXYTW0tF6HGB6xQPD9oZ2cnr1eUwmE3Z2djEav7A9uF1cXu+5vErYPuVx8bMNvzBn7J/D/49jXI+Ro+N/B7T18cOOjcUS/rVh5+AQsS96DIQdl/8f93BjGOYFYGdn98pzhj2uo6PtxiN8O3jbHHTZMmurvBo17GJ9Qdz/1/c6/z/LfxLquD1//px58+axdetWSpYsSbJk4SerTJkyxaDKRESip3vp7gQ9D8J7izdDtg0hhVMKer3Ty+iyoiVDkQy03NCSi79e5Jd+v3Dt8DW2Dd7GoZmHqDKyCp7tPLGzT5i/P8S2YhyiN23alMWLF+Ph4UGOHDlw/L+VjI4cOWKz4kQk/h05Ai1aWLPnLl3gs8+i3nf58km0avX5vwF6ejZsOGtsgP74sTX1nzDhvxlsLVrA6NGQM6dxdYkkQe7u7tjb20cIwAMDA8mYMWMUj4o7KVMnrj9c47LrTtjwOT4WFrXlIo5hxXWWFXbCaYwWFo2muB6jsMePy4VFIyx+GcvUN+zP9aXjHvY80Thn2Ne6LV/3yZLB09h34gnno4+sXyLRdeLECUqUKAHA2bNnw21LyC0RRETC6lOuDw+CHzBs+zB6b+5NCucUdCjeweiyoi1n1Zx0PtCZE0tP8OugX7l78S7rO61n7+S9vDfqPQo0LqB/k5O4GP+J6eXlxeHDh2ndurUWFhVJYq5cgXr1rFl0jRowfXrU71vPn/+Jtm2tAXq1aun56adzuLi8/uXdsWKxwNKl1tYtf/1lva9SJZg0ybp4qIjYnJOTEyVLlsTPz4+GDRsC1nYMfn5+9OjRI97rSZk2jtLiOBKXIXrYkDKuQvSwa+/FVfeDuAi2wwpbd1yMU9j642KMwv5+tvXxw9YeEsL/T3eO1bGj/foMe85o/A8TVx8epUgBt2/b7ngir2Pbtm1GlyAiYhNDKg3hQdADJu2dRKd1nUjmmIxmhZsZXVa0mexMFGlRhAKNC3Bo1iF2jtrJrdO3WP7hcjKVzETV0VV5u+bbykqTqBj/iblhwwY2b95MhQoV4qIeETHIw4fWAP3qVShUCJYvj3pm2927u7h2rQV9+8KBAx6sXXvWsADd4cQJTKNGwc6d1juyZ4fJk6FxYy0aKhJLDx8+5Pz586G3L168iL+/P2nTpiVbtmx4e3vj5eVFqVKlKFOmDFOnTuXRo0e0b98+3mtNljpx9SNM7CF62NnJcTUTPT5D9Lg4V/i2OrY/ftjXUFy2cQ77gQkQfyF6DM8TV697T0/480/bHU8ktq5cuQJAlixZDK5ERCTmTCYTE2pM4H7Qfb498i2tV7cmuVNy3s/7vtGlxYiDswPv9H4Hz/ae7J2yl31T9nHt8DUW1V5E9krZqTq6KtkqZDO6TLGxGP8VnDVrVlKmtO3CSCJirJAQa9cTf3/w8ICffop6zbBbt7Zz7FhtQkIe0qRJNTZs+MOYAP3mTUzdupGuVi1MO3daVxQbORJOn4YmTRSgi9jAoUOHKF68OMWLFwfA29ub4sWLM3ToUACaNWvGpEmTGDp0KJ6envj7+7Np06YIi43GB9eUSTxEfzG7f/ToGB07PkL0uApw47qdS9jwPzHORA8bbtu6nUuE84R9UcXyBxPtGeMx/D0edndbjsfs2dCq1X+f1YsYwWw2M3LkSFKlSkX27NnJnj07qVOnZtSoUZgjfNIlIpKwmUwmZr4/k5ZFWvLc/Jwmy5qw7WLivOLGJZUL7414j55/9KTcZ+Wwd7bn0s5LzK84n0V1F3HtyDWjSxQbivFfwZMnT6Zfv378qSkZIkmGt7c1OHdxsS4qmiNH5PstXjyOMmWqEhj4iDRpqlOkyDocHJJFvnNcefYMvv4a8ubF9O23mMxmLM2aQUAADBliDdNF3iBXrlyJszfQVapUwWKxRPhasGBB6D49evTg0qVLBAUFsX//fsqWLRsntbyKS4rEFaLnyRPDB3zzDdy9CzVrvnLXsC+H+AjR42rGeGKfiR7XPdHjK0SPy57otgzRw7Ll697DA374ASpWtN0xRWJq0KBBTJ8+nXHjxvH777/z+++/M2bMGKZNm8aQIUOMLk9EJMbs7exZ0GAB9fPVJygkiPpL6rP/yn6jy3ptydIno+akmvQ835OSXUti52DH+Z/P823Jb1nedDm3ztwyukSxgRiH6K1bt2bbtm28/fbbpEiRgrRp04b7EpHEZdo0azYD8P33EFX+tXjxWNq2HcjFixZ++ikbhQuvw97eLf4KBfj1V+t11b17w927WDw9ub16NZYff4SsWeO3FpEEomDBgvpgG3B1SxxXn+zZA/PnQ4y74plMUV8i9H/iO0SPqwt/4nNh0cQ4E92Gk8NfymwmznqiR3th0RiKq9e9iFF8fX357rvv6NatG0WLFqVo0aJ0796dOXPmhPtgW0QkMXG0d2Tph0uplrMaD4MfUmdRHY4FHjO6rFhJmSUlH/h8wCenP6FIqyJgglPLTzGz0EzWtFvDnfN3jC5RYiHGf2JOnTo1DsoQESOsXQu9elm/HzcOPvww8v1+/HEsXl5f8Pw51KyZgW+/PYG9fTzO+L52DT77DBYvtt52d4fRo7G0b88zrfYlbzhLXDbXTkQSy0Uo5cpZv+JSfITocdUHPay4nokedvZ2XHwQENch+vPntj9mZGzdEz2u2rmEFZcz80WMcOfOHfLnzx/h/vz583PnjgIZEUm8XBxcWNN8DTW/r8neK3up+X1NdrbfSd50eY0uLVbS5k5L4x8aU2FABbYN2caZNWc46nuUYz8co2jrolQaXIm0uTURObGJ8VsrLy+vuKhDROLZ/v3WPugWC3TtCv36Rb7fjz+OxstrMM+fQ61aGVm79izOzinip8jnz2HWLBg8GO7ft75x79YNRo2CNGkieWcvIm8qFxejK0g4wn6uEldBdJUq1uUnihSJm+MDdOpk/V1VpkzcHD/s2ERoWWLj48fFhw5NmsDQoRDXf5ob1s4lFjQTXZKaYsWKMX36dL55cfnov6ZPn06xYsUMqkpExDaSOyVnY6uNvOf7Hv7X/am+sDq7OuwiW6rEvzCnR2EPmq1uxt8H/mbHiB2c23jOGqZ/bw3TKw6uSLo86YwuU6JJf2KKvIEuXIB69eDJE6hbF6ZPj/w98aJFX9Ku3RCeP4fatTOyZk08Buj791sD899/t94uXdoaqJcsGT/nF0kkvvjiC7VTI/HMRI8PYT9fjKs2H3Z2sGJF3Bz7hY4doVChuAvqw75mksXB8h5hx95mM9F79bKuCzJyJHnyWD9fjutZ17b+gCE+QvR/10IWSTImTJjA+++/z9atWyn37+VMe/fu5a+//mLjxo0GVyciEnupXVKzufVmKs2vRMDtAGp+X5NdHXbh7uZudGk28VaZt2i5oaU1TB+5g3MbznF0oXVmepFWRag0uBLp8ipMT+jiuNukiCQ0t29bg/ObN6FECVi6NPI3sTdv+jFkyNAwAfq5+AnQ79yBjz+29jv4/XdIndoanu/dqwBdJBIDBw4kderURpdhOIXo/4mLQNgIJpP1V0Hy5HFzfFdX66Laq1dbf9XYWtgPM2wWok+ZAmfOWK/QwnoFRly3vbH1RV/RbufyGi5csK47kDdxXwEuEkHlypU5e/YsjRo14u7du9y9e5fGjRsTEBBARa16KyJJhEcyD35p8wtZU2Yl4HYAdRfV5WHwQ6PLsqm3yrxFy59a0ulAJ/J+kBeL2cKx748xo8AMVrVepQVIEzjNRBd5gzx9Cg0awNmzkC2bNTyILJz4559tnD5djwkTLGzYkBMfn2M4O8dRivGCxQK+vvD553Dr318cXl4wYQJ4eMTtuUUk0VM7l/8ULWqdsKz1ll/t/ffj7thhZ3DbLES3s4N8+Wx0sOixddAd7YVFw4pmC5lcuaxfIknN5cuXyZo1K6NHj450W7Zsib/lgYgIQNZUWdnSZgsV5lXg4NWDNF7amJ9a/oSTfRwsMGOgt0q/RYv1Lbh6+Co7Ruzg7PqzHF90nOM/Hqdws8KU61cOu0ya95zQ6Cci8oYwm62Z9O7dkCoVbNwImTJF3O/UqWUcP/4+ZvMT8uatw3ffnYr7AP3MGWuD3fbtrQF6oUKwYwcsWKAAXUSiRTPR/2MywdSp1vWYxTgpwly8FRcLi8a1ceMgd24YNAibrrz6Wu1ctICyvOFy5szJzZs3I9x/+/ZtcubMaUBFIiJxJ797fja22kgyx2T88scvtF3dFrMlaa6HlrlkZlqsa0GXw13I1yAfWODEkhPMKTGHn1v/zOXfLhtdooShEF3kDTFgACxbZu2dunq1Naf+f76+wyhevBlbtjwhbdq6FCq0Cnv7OJzeGRwMX34JxYrBzp3g5madef7771CpUtydV0SSFBMhWkhQEpwMGWDuXFiyJO5brsSF/v3h3LnIP3CPjfjoiS6S1FgsFkyRfJj18OFDXHQplogkQWXeKsOqZqtwtHNk6cml9Py5J5Yk/KF6phKZaL6mOV1/70rh5oUx2Zm47HcZ3yq+zKswj7M/nU3Szz+xiNafro0bN472AVetWvXaxYhI3Jg5EyZOtH4/fz68917EfXx9h9Gx40hCQuDo0bcYOXIVdnbOcVfUvn3QuTOcOGG9XaeOtfd59uxxd04RSZJceYLJlMboMkQi6NDB6AoSnrjsiS6S1Hh7ewNgMpkYMmQIbm5uodtCQkLYv38/np6eBlUnIhK3ar5dk+8bfU+LlS2YcXAGHsk8GFp5qNFlxamMnhlpsrgJlUdU5tdRv3J22Vn+2v0Xi+stxqOwB+UHlKdws8LYOWhOtBGi9adrqlSpQr+3WCysXr2aVKlSUapUKQAOHz4curiJiCQs69fDp59av//yS2jVKuI+CxYMpVOnUYSEQN26mVm16mzcBegPHlivDZ8+3Xp5trs7fPMNNG9u08vFRZK6M2fO8MMPP/DHH3+QPHlyChQoQIcOHcL9zn5TONk9M7oEkaStfHl4+22brNgZ9ld9YpyhLxKffv/9d8D6Hvz48eM4hekN5eTkRLFixejbt69R5YmIxLlmhZtx8/FNPv35U4ZtH0Z6t/R0K93N6LLiXNrcaak0sRK1xtXiwNcHODTrEDdO3GB169VsG7yNdz9/l2JexXBKlgh7BiZi0QrR58+fH/p9//79adq0KT4+Ptj/+5dvSEgI3bt3J2XKlHFTpYi8lkOHrNm02QydOsEXX0TcZ8GCIXTq9CUhIfDBB2+xatVZHB3dIu5oCxs2QLdu8Ndf1ttt28LkydYgXUSibdOmTTRo0IAcOXJQtGhRbt26xfTp0xk1ahTr16+nfPnyRpcYr+xNIa/eSURen5OTdVVyG3/Yrc/ORV5u27ZtALRv356vv/5a77dF5I3Uo0wPbj66ycidI/lk4ye4u7nzUaGPjC4rXqTIlIIaE2pQYWAFDs48yP6p+7n75102frKRbUO2UfLjkpT5pAwpMqd49cEk1mI8/3/evHn07ds3NEAHsLe3x9vbm3nz5tm0OBF5fRcvwvvvw+PHUKuWtaXL/79ZnT9/cJgAPUvcBeg3bkCLFvDBB9YAPWdO2LIFfH0VoIu8hl69ejF+/HgCAgJYvnw5q1at4vz587Ru3Zru3bsbXV68c1CILhL37OxsknqHbeepEF0keqZOncrz588j3H/nzh3u379vQEUiIvFreJXhdCvVDQsWWq1qxdY/thpdUrxyTeNKpUGV6H2pN7W/qU3qnKl5cucJu8bsYmqOqaxuu5prv18zuswkL8adCJ8/f86ZM2fIly9fuPvPnDmD2Zw0V8sVSWzu3IG6da3ZtacnLF9uXVA0/D5b2LRpHCEhUK9eFlauDLB9gG6xwKJF0KuXtSg7O+jTB0aMgGTJbHsukTfI/fv32bp1K5cvX45w/6lTp0J7qAJMmTIlvsuLdw6miMGCiCRMYUN0O7XzFImW5s2bU69evQgflC9btox169axceNGgyoTEYkfJpOJaXWmcevxLZafWk7DJQ3Z3m47pTKXMrq0eOXo5kjZT8tSuntpAtYGsO+rfVzedZlj3x/j2PfHyFElB+94v0Pe9/NistNsBVuLcYjevn17OnbsyIULFyhTpgwA+/fvZ9y4cbRv397mBYpIzAQFQaNGcOYMZM1q7aCS4v+u7LlzZzPHjzfg449DKF68BJ99tgtHR1fbFnLtGnz8MaxbZ73t6QnffQclS9r2PCJvoCVLljBt2jT8/f3DrdL+9OlTzGZzaA9V0xsyzVMz0UUSD3d3698lJhOk0XrAItGyf//+SD8Ur1KlCoMGDTKgIhGR+GdvZ8/3jb7nzpM7+F30o+6iuuztuJe3075tdGnxzs7ejgKNC1CgcQH+PvA3+77ax8nlJ/lz+5/8uf1P0uZJS9leZSnWthjOKeJovbs3UIxD9EmTJpExY0YmT57MtWvWSwUyZcrE559/zmeffWbzAkUk+sxmaNcOdu6ElClh40bInDn8PmvXTsDNbQiOjsG4uzegX79l2NnZcDGKF7PPe/aEf/6xToEfNgz69Ys4HV5EXsvEiRNp0aIFrf5vpeDZs2dz/fr10B6qbwp7O4XoIomFg4P1SjmTSQuLikRXUFBQpO1cnj17xpMnTwyoSETEGM4OzqxutpoqvlU4cu0ItRfVZk+HPaRPlt7o0gzzVpm3aLK4CdUnVOfAtAMc/vYwd87d4eceP+M3wI+ibYtSuntpPAp5GF1qohfjEN3Ozo5+/frRr1+/0P5rWuBEJGEYNAiWLLG+QV21CgoXDr99zpwBfPzxeMqWhRkz6lOokI0D9P+ffV6yJCxYELEQEYmVDz74gLZt27JkyRLKli0LWGepbdq0CV9fX4Ori38OJrWTE0lMXFyMrkAkcSlTpgzffvst06ZNC3e/j48PJXWVp4i8YVI4p2BDyw2Um1uO83fO88HiD/i17a8kc3qzW8amypqKGhNqUHloZX6f/zsHZxzkdsBtDs08xKGZh8heOTulPylN/ob5sXfUTIbXEeMQHax90bdv386FCxdo2bIlAFevXiVlypQkT57cpgWKSPTMng3jxlm//+47qFYt/PZvv+1Pt24TMJshQ4ZsFCmy1HYBumafi8Srjz/+mDx58jBr1ixWrFiBvb09BQoUYN++fW/km2kHzUQXkTdU2B7zknR9+eWXVK9enaNHj1Lt3z/y/fz8OHjwIFu2bDG4OhGR+JcxeUY2tdrEu/Pe5cDfB2i+sjmrm63Gwe61Ys4kxSm5E2U/LUuZHmW4+OtFDs08xJm1Z7i04xKXdlwieabklOhcgpJdSpLyLU2KjokYv7ouXbpE7dq1uXz5MkFBQdSoUYMUKVIwfvx4goKC8PHxiYs6ReQl1q2DF+sMDR8OXl7ht8+e3Y/u3SdiNkOjRtlZtiwABwcb9cXS7HMRQ1SrVi30jfSbTiG6iIgkZeXLl2fv3r1MnDiRZcuW4erqStGiRZk7dy558uQxujwREUPkc8/H+hbrqbawGj+d/YlPNnyCzwc+b8y6UK9iMpnIVS0Xuarl4v6V+xz+9jCHvz3Mw2sP2TlyJ7+N/o28H+SlRKcS5K6dGzsHrfj+KjEO0Xv16kWpUqU4evQo6dKlC72/UaNGdO7c2abFicir7d0LzZtb+6F36gRDh4bf7uPTl08+mYzZDI0bZ2fpUhsF6Jp9LpIg3L17l3Xr1uHq6krFihXJmDGj0SXFO4XoIvKmUk7w5vD09GTRokVGlyEikqC8m/Vdfmz8I02WNeHbI9+SNVVWBlcabHRZCU7KLCl5b+R7VBpcidOrT3No5iEu7bxEwNoAAtYGkDxTcjzbeVK8Q3HS5k5rdLkJVoxD9N9++409e/bg5BS+DUSOHDn4+++/bVaYiLxaQAB88AE8eQLvvw+zZoV/M/Xtt5+HCdBzsHTpGdsE6LduWWefr1xpva3Z5yJx7tmzZ0ydOpXdu3fj4OBAnTp1aNiwISVKlOD27duYTCZMJhNr167lvffeM7rceOVgF3GxNRERkaTo6dOnBAcHh7tPa5SJyJusUYFGTKszjR4/92DItiFkSZmFdp7tjC4rQbJ3sqdws8IUblaYGydv8Pu83zm28BgPrz1k19hd7Bq7i+yVs1O8Y3EKNimIo5smSIYV47n6ZrOZkJCIM76uXLlCihQpbFKUiLzatWtQuzbcuQNlysDSpdYFRV+4desngoK+wtkZmjTJabsA/eefoUgRa4Du4ACjRlmnwytAF4lTffr0wcfHh3z58pEsWTI++eQT3nnnHfLmzcudO3e4d+8enTt3ZuDAgUaXGu8cTJqJLiIiSdfjx4/p0aMHHh4eJEuWjDRp0oT7EhF5031S5hP6l+8PQOf1ndl8frPBFSV8HoU8qDW5Ft5/e/PR8o/IXTs3mODSjkusabuGyZkms77rei7vuozFrEVY4DVC9Jo1azJ16tTQ2yaTiYcPHzJs2DDq1q1ry9pEJAr370PduvDnn5A7N/z0EyQLsxD1rVvrOXmyMUWKhLBsWW2WLDkd+wD90SPo1s164uvXoWBB2L8fBg9W+xaReLBmzRqWLl3K+PHj8fX1ZfHixfzxxx/06tULJycn7Ozs+OSTTzh16pTRpcY7Bzv9USciIknX559/zq+//sqsWbNwdnbmu+++Y8SIEWTOnJmFCxcaXZ6ISIIwptoYWhVpxXPzc5osa8KRa0eMLilRsHeyp+CHBWn1cyt6X+pNlZFVSJ0jNUH3gzjy7RHmV5zP17m+xm+QHzdP3TS6XEPFOESfPHkyu3fvpmDBgjx9+pSWLVuGtnIZP358XNQoImEEB0OTJuDvDx4esHkzpE//3/Y5c/qyZk1jLJZnpE//EXXrrot9gL5/PxQvDi8WDu7dGw4dghIlYndcEYm2Bw8e4OrqGnq7Xr16pE+fnty5c4fed+PGDdzc3Iwoz1AO9pqJLiIiSdf69euZOXMmTZo0wcHBgYoVKzJ48GDGjBmjPukiIv+yM9kxr8E8quWsxqNnj6i7qC4X/7lodFmJSqqsqag8pDI9L/SkrV9bPNt54pTCiXuX7rFrzC5mFprJ7BKz2TtlLw+uPTC63HgX457oWbJk4ejRoyxdupSjR4/y8OFDOnbsSKtWrcK9uRcR2zOboUMH2LrVOvN840bIleu/7TNn9qZHj69JkQJWrHifAgV+xM4uxv+b/+fZM/jySxg9GkJCIEsWa+/zatVi/VxEJGbKlClDly5dGDp0KJkyZQJgy5YtBAcHc+zYMZ4/f06fPn0oX748x48fx2Kxzs4uWrSokWXHC3stLCoiIknYnTt3yPXvH/0pU6bkzp07AFSoUIFu3boZWZqISILiZO/EyqYrqbSgEscCj1FnUR32dNxDWlctlhkTJjsTOavmJGfVnNSdWZez689y7IdjnP/5PNd/v87136/zy+e/kOO9HBT8qCD5G+YneYbkRpcd514rXXNwcKBVq1a0atXK1vWIyEt88QUsWmRtRb5ihXU9zxdmzOjNp59+jcUCtWu/zXvvrYpdgB4QAK1bW2ecA7RqBdOnQ+rUsXoOIvJ6Zs2aRdu2balTp07ofSaTKTQsD2vNmjVYLBZMJlOk65gkNZqJLiIiSVmuXLm4ePEi2bJlI3/+/CxbtowyZcqwfv16UutvcxGRcFK5pOLnVj/zznfvEHA7gMZLG7O59WacbbFG3BvI0dWRQk0LUahpIR7feszJ5Sc5vug4f+3+i4t+F7nod5GN3TeSvVJ2CnxYgAKNCpAic9JcMzPGCZu9vT2VKlVi5cqVpE373yc5gYGBZM6c+Y14sy5ihGnT4EXHpO++sy4q+t+2nvTqNQ2LBZo1y80PP5zEwcHp9U5kscDMmfD55/DkCaRJA7NmQbNmsX8SIvLacufOzZ49e3jy5Ak3b96MNDx/UznYm40uQUTiQu3asHMnNGhgdCUihmrfvj1Hjx6lcuXKDBgwgHr16jF9+nSePXvGlClTjC5PRCTByZwiMxtabqD8vPLsuLSDzus749vQF5PJZHRpiZqbuxulu5WmdLfS/HPxH04tP8WpFae4evAqf27/kz+3/8nPn/5M1nezUvDDghRoXIBU2VIZXbbNxDhEt1gsBAUFUapUKdavX0+hQoXCbRMR21uxAnr1sn4/ejR4ef23bdq0T+nVa3pogL5o0Sns7V9zoc+bN6F9e9iwwXq7Rg2YPx/eeit2T0BEbMbV1ZVs2bIZXUaC4qB2LiJJ08aN1tZyTq85MUAkkfvjjz/ImTMnffr0Cb2vevXqnDlzhsOHD5M7d+43om2biMjrKJKhCMs/Ws77P77P98e+J3fa3AytPNTospKMNDnTUL5fecr3K8/dS3c5vfI0p1ac4sreK/y1+y/+2v0Xm/tsJkPRDOT5IA95P8jLW2Xews4+xstzJhgxrtxkMrFy5Urq1atHuXLlWLt2bbhtImJbO3dau6pYLNC9Owwc+N+2H38cFBqgN2+eJ3YB+i+/QNGi1gDd2Rm++QY2bVKALiIJnoOdZqKLJEkmkwJ0eaPlyZOHmzdvht5u1qwZgYGBZM+encaNGytAFxF5hVq5azHz/ZkADNs+jB+O/WBwRUlT6uypKeddjo57OtLnrz7U/ro22Spmw2RnIvBYILvG7GLeu/OYnHEya7zWcHL5SZ7ee2p02TH2WjPR7e3t+frrrylUqBDNmjVj8ODBdOrUKS7qE3mjnTxpvYI5KAgaNrTm2i8+q7p5cyVp046nSBEoWDAPP/xw8vUC9OBgGDQIJk2y3i5YEBYvtgbqIpJg5MyZ87U+rO7duzc9e/aMg4oSDnuTZqKLyJspTx6jK5C49P9Xem/cuJGxY8caVI2ISOLUpWQXLty5wIQ9E+i4riPZUmWjUvZKRpeVZKXMkpKyPctStmdZHt9+zPlN5zn30znO/XyOx7cec3ThUY4uPIqdgx1Z381Krhq5yFU9F5lLZcbOIWHPUo/FqoPQpUsX8uTJw0cffcTOnTttVZOIAFeuWFuB3r0L774LP/4I9vbWbTdvruTUqea4uIQwf34zPD1/eL1FRM+dgxYt4PBh6+1u3WDyZHB1tdnzEBHbWLBgwWs9LkeOHDatIyGyVzsXEXlD1aljXTfH09PoSkRERBKusdXHcuGfC6w8vZKGSxqyt+Ne8rnnM7qsJM8tnRtFWxWlaKuihDwL4a89f3H2p7Oc++kct87c4tLOS1zaeYltQ7bhnMqZnO/lJGf1nOSqnot0edMluI4nMU7dsmfPjv2LJA9477332LdvH/Xq1bNpYSJvsrt3rW+KrlyB/Plh3br/cu2vv+6Ov78PXl4WMmRoTf78CzCZ7F96vAgsFvD1hR494NEjSJsW5s61TncXkQSpcuXKRpeQYKknuoi8qUwm659zAGZ1tkpyTCZThADBVoHCjBkzmDhxItevX6dYsWJMmzaNMmXKRLn/1KlTmTVrFpcvX8bd3Z0PP/yQsWPH4uLiAsDw4cMZMWJEuMfky5ePM2fO2KReEZHYsDPZ8X2j77ly/wr7/97P+z++z75O+3B3cze6tDeGvaM9OSrnIEflHNScWJM7F+7wx9Y/+OOXP7j460We/vOUM2vOcGaN9fdGyiwpyVYxG9kqWL88CntgsjM2VI9xiH7x4sUI9+XOnZvff/+dwMBAmxQl8iZ70brlxAnIlMnaljxdOuu2r77qhre3DwDlylWlcuXXCNDv3rXOOF+yxHq7ShX4/nvIksVWT0FEJF4pRBcRkaTIYrHQrl07nJ2dAXj69Ckff/wxyZIlC7ffqlWrYnTcpUuX4u3tjY+PD2XLlmXq1KnUqlWLgIAAPDw8Iuz/448/MmDAAObNm8e7777L2bNnadeuHSaTiSlTpoTuV6hQIbZu3Rp628EhVhe+i4jYlKujK2ubr+Wdue9w4Z8LNFzSkK1tt+Li4GJ0aW+ktG+nJe3baSnVtRTmEDPXf7/OhV8ucHHrRS7vusz9K/c5sfgEJxafAMA5lTPZymcja4WsZKuQjcwlM+Po9pprAr4mm/1Wc3FxIXv27LY6nMgbyWyGtm1hxw5IkQJ+/hle/G81ZcrHfPbZbABat85Pp06bYx6g79kDLVvCpUvW3jAjR0L//v/1iRERSYQUoouISFLk5eUV7nbr1q1tctwpU6bQuXNn2rdvD4CPjw8bNmxg3rx5DBgwIML+e/bsoXz58rRs2RKwtopr0aIF+/fvD7efg4MDGTNmtEmNIiJxIUPyDGxsuZFyc8ux+6/dtF/bnkWNF2FnSti9uJM6O3s7MpfKTOZSmak4sCLPHj/jyv4rXP7tMpd3XebK3isE3Qvi3MZznNt4DgCTnYn0hdJbH1fa+tgMRTPg4Bx3H+BG68hp06bl7NmzuLu7kyZNmpdeQnbnzh2bFSfyJrFYwNsbli0DR0dYvRqKFbNumzy5K337fgtAmzYFWLDgWMx6oJvNMH48DBkCISGQM6d18dCyZePgmYiIxC8tLCoiIknR/PnzbX7M4OBgDh8+zMCBA0Pvs7Ozo3r16uzduzfSx7z77rv88MMPHDhwgDJlyvDHH3+wceNG2rRpE26/c+fOkTlzZlxcXChXrhxjx44lW7ZskR4zKCiIoKCg0Nv3798HwGw2Y1ZvotdiNpuxWCwav1jSOMZeQh/DfOnyseKjFdT5sQ5LTiwhV+pcjHpvlNFlhZPQxzCu2bvYk71ydrJXts4qNT83E3g0kMu7L3P5t8tc2XOFh9cfcuP4DW4cv4H/fH8A7BztyFA0Axk9M5Isb7KXnOH1RCuF++qrr0iRIgVg7YUmIrY3bhx8/bX1+wULoFo16/eTJnXm88+/A6Bt2wLMnx/DAP3mTWjTBjZvtt5u2RJmzYKUKW1XvIiIgeztLEaXICIikijcunWLkJAQMmTIEO7+DBkyRNm/vGXLlty6dYsKFSpgsVh4/vw5H3/8MV988UXoPmXLlmXBggXky5ePa9euMWLECCpWrMiJEydCs4Swxo4dG6GHOsDNmzcJDg6O5bN8M5nNZu7du4fFYsHOTrNqX5fGMfYSwxgWTlaYiRUn0mdHH8bsGoOHgwfN8jUzuqxQiWEM45t9VntyNs9JzuY5AXh07RE3j97k5tGb3PC/wa2jt3j6z1OuHb7GtcPXeMpTm9cQrSQu7GVk/39JmYjE3ty58OJv0K++subcALt2TaFfP2uA7uVVkHnzjsYsQN+5E1q0gKtXwcUFZsyA9u2tq1CJiCQRdqY3c4aGiIhIfNi+fTtjxoxh5syZlC1blvPnz9OrVy9GjRrFkCFDAKhTp07o/kWLFqVs2bJkz56dZcuW0bFjxwjHHDhwIN7e3qG379+/T9asWUmfPj2pU6eO8+eUFJnNZkwmE+nTp1foFgsax9hLLGPY06MnN0NuMmbXGD7f+TnFsxenQrYKRpcFJJ4xNJQH5CyWM/SmxWLh3qV7XD14letHr3Px0EX4xbanjFYa9+LSquhIqdmtIjGydi106WL9fsAA6N3b+n1g4BKeP/+cTz+F+/cLMXeuf/QDdLPZOrV9yBDr9/nzW/vEFCkSJ89BREREREQSPnd3d+zt7QkMDAx3f2BgYJT9zIcMGUKbNm3o1KkTAEWKFOHRo0d06dKFQYMGRRrwpE6dmrx583L+/PlIj+ns7By6YGpYdnZ2CoxiwWQyaQxtQOMYe4llDEdVHcXZO2dZcWoFTZY34UCnA+RMk/PVD4wHiWUME5K0udKSNldaCjcrzN27d+mSpotNjx+tn0Tq1KlJkybNS79e7CMi0bdvnyMtW5owm6FDBxgzxnr/X399z+nTrQAz3bq1Z968GLRwuXED6tSBQYOsAXqbNnDwoAJ0EREREZE3nJOTEyVLlsTPzy/0PrPZjJ+fH+XKlYv0MY8fP44Q4tjb2wPWmX+RefjwIRcuXCBTpkw2qlxExPbsTHb4NvSlRKYS3Hp8i3qL63E/KPoTieXNEq1Ubtu2bXFdh8gb59gx8PJKw9OnJurXh9mzrV1Wxo1rz7x5C5g4EfLl60C+fHMwRXel6B07rO1brl0DV1dr+5Z27dS+RUREREREAPD29sbLy4tSpUpRpkwZpk6dyqNHj2jfvj0Abdu25a233mLs2LEA1KtXjylTplC8ePHQdi5DhgyhXr16oWF63759qVevHtmzZ+fq1asMGzYMe3t7WrRoYdjzFBGJDjdHN9Y2X0uZOWU4efMkLVe2ZG3ztdjb2RtdmiQw0QrRK1euHNd1iLxRLl6EunVN3L9vokIFC0uWmHBwgHHj2jFwoC8A+/eXpX79aAboZjOMHQtDh1q/L1AAli+HQoXi+JmIiIiIiEhi0qxZM27evMnQoUO5fv06np6ebNq0KXSx0cuXL4ebeT548GBMJhODBw/m77//Jn369NSrV4/Ro0eH7nPlyhVatGjB7du3SZ8+PRUqVGDfvn2kT58+3p+fiEhMZUmZhbXN11JpQSU2nNtA/639mVRzktFlSQITgxUKw3v8+DGXL1+OsHJ20aJFY12USFJ24wbUqgXXrpnIn/8Za9bY4+pqYuxYL774YiEAHTsW4csvd0cvQL9xA1q3hl/+XTHBy8s6Az1Zsjh8FiIitjFp0iTmz5+PyWRiwIABtG7d2uiSREREkrwePXrQo0ePSLdt37493G0HBweGDRvGsGHDojzekiVLbFmeiEi8K/1WaRY0WEDzlc2ZvHcyBdwL0LFExIWR5c0V4+70N2/e5IMPPiBFihQUKlSI4sWLh/t6HTNmzCBHjhy4uLhQtmxZDhw4EOW+c+bMoWLFiqG92KtXr/7S/UUSkgcP4P334dw5yJ7dwuLF/5AmDeEC9E6divLtt79jF51Lh3bvBk9Pa4Du6grz58OCBQrQRSRROH78OD/++COHDx/m4MGDTJ8+nbt37xpdloiIiIiIvIGaFW7GsMrWDwy7bejGzks7Da5IEpIYh+i9e/fm7t277N+/H1dXVzZt2oSvry958uRh3bp1MS5g6dKleHt7M2zYMI4cOUKxYsWoVasWN27ciHT/7du306JFC7Zt28bevXvJmjUrNWvW5O+//47xuUXiU3AwNG4Mhw6Buzv8/LOFjBnN4QL0zp2LMXv2kVcH6BYLTJ0KVapY+58XKGBdPLRdu7h+GiIiNnP69GnKlSuHi4sLrq6uFCtWjE2bNsX8QFr3QUREREREbGBo5aE0LdSUZ+ZnNF7amD/++cPokiSBiHGI/uuvvzJlyhRKlSqFnZ0d2bNnp3Xr1kyYMCF04ZGYmDJlCp07d6Z9+/YULFgQHx8f3NzcmDdvXqT7L1q0iO7du+Pp6Un+/Pn57rvvQlcTF0mozGZrl5WtW62TxDduhHz54O+/F/LNNz8A0LmzJz4+h18doD94AM2bQ58+8Pw5NGsGBw6o/7mI2NzOnTupV68emTNnxmQysWbNmgj7xORqsv9XuHBhtm/fzt27d/nnn3/Yvn27PhQXERERERHD2JnsmN9gPqUyl+L2k9vUW1yP+0H3jS5LEoAYh+iPHj3Cw8MDgDRp0nDz5k0AihQpwpEjR2J0rODgYA4fPkz16tX/K8jOjurVq7N3795oHePx48c8e/aMtGnTxujcIvHFYoHevWHJEnB0hFWroHRpuH7dlwcPBjBlCnz2WVl8fA69OkA/fRrKloVly8DBAb7+GhYvhuTJ4+W5iMib5dGjRxQrVowZM2ZEuj06V5N5enpSuHDhCF9Xr16lYMGC9OzZk6pVq9K4cWPeeecd7O2j0cpKREREREQkjrg5urGm2Royp8jMqZunaL6iOSHmEKPLEoPFeGHRfPnyERAQQI4cOShWrBizZ88mR44c+Pj4kClTphgd69atW4SEhISuAv5ChgwZOHPmTLSO0b9/fzJnzhwuiA8rKCiIoKCg0Nv371s/PTKbzZjN5hjVK1ZmsxmLxaLxi6YxY2DaNOvnVfPnm6leHQ4cmMTjxwMACyVLdqV58+mA6eVjumwZpk6dMD16hCVzZixLlkD58taU3mKJl+eS0Oi1GHsaw9hLymNXp04d6tSpE+X2sFeTAfj4+LBhwwbmzZvHgAEDAPD393/pObp27UrXrl0B6NSpE3ny5Ily36h+p6PX8GvTvwG2oXGMPY1h7GkMY09jJyIiL7yV8i3WNl9LpfmV+Pn8z3z+y+dMqTXF6LLEQDEO0Xv16sW1a9cAGDZsGLVr12bRokU4OTmxYMECW9f3UuPGjWPJkiVs374dFxeXSPcZO3YsI0aMiHD/zZs3CQ4OjusSkySz2cy9e/ewWCzY2cX4YoY3yg8/uDJkSCoARo26T7Vqjxk8uBuTJq1hxAioWrU5KVIM4ebNW1Ef5NkzUowcSbLvvgMg6N13uefjgzl9eohi7YA3hV6LsacxjL179+4ZXYIhXlxNNnDgwND7Yno1GcCNGzfw8PAgICCAAwcO4OPjE+W+Uf1ON1ssUa6lIi+nfwNsQ+MYexrD2NMYxt6b+jtdREQiVypzKXwb+tJ0RVO+2vcVhT0K06F4B6PLEoPEOERv3bp16PclS5bk0qVLnDlzhmzZsuHu7h6jY7m7u2Nvb09gYGC4+wMDA8mYMeNLHztp0iTGjRvH1q1bKVq0aJT7DRw4EG9v79Db9+/fJ2vWrKRPn57UqVPHqF6xMpvNmEwm0qdPrz/QX2L1aujf37rY3cCBFr74IjmjRnVh7Ng1AFy5UpKsWSfj4eER9ThevYqpRQtMu3cDYOnXD8dRo3B3iPH/ukmSXouxpzGMPScnJ6NLMIQtriYDaNCgAffu3SNZsmTMnz8fh5f8+xbV73Q7O7vQVnMSM/o3wDY0jrGnMYw9jWHsvam/00VEJGofFfqI4TeHM3zHcLpt6EbB9AV5J8s7RpclBoh1Eufm5kaJEiVe67FOTk6ULFkSPz8/GjZsCBC6SGiPHj2ifNyECRMYPXo0mzdvplSpUi89h7OzM87OzhHut7Oz0x+XsWAymTSGL7FjB7RqZV1QtGNHGD3axMiRLRg+fCkA3bqV4uuv93Lr1q2ox3H7duuioTduQMqU4OuLqWFDTPH7VBI8vRZjT2MYOxq32InJrPWofqeDfg6xoX8DbEPjGHsaw9jTGMaOxk1ERCIzpPIQjgYeZfWZ1TRe2phDXQ6ROUVmo8uSeBbjEN1isbBixQq2bdvGjRs3IvSNW7VqVYyO5+3tjZeXF6VKlaJMmTJMnTqVR48ehfZXbdu2LW+99RZjx44FYPz48QwdOpQff/yRHDlycP36dQCSJ09Oci2uKAnA0aNQvz4EBUGDBuDjAyNGNGPEiGUAfPJJab75Zl/UB7BYYMoU6N8fQkKgSBFYuRJe0idYRCS+xeZqMhERERERkcTCzmSHb0Nfzs07x4kbJ2i0tBE72u3AxSHy1tKSNMX4o/bevXvTpk0bLl68SPLkyUmVKlW4r5hq1qwZkyZNYujQoXh6euLv78+mTZtCLw+/fPlyaA92gFmzZhEcHMyHH35IpkyZQr8mTZoU43OL2Noff0Dt2nD/PlSsCIsXw6hRTSME6FHOcnn82DqFvW9fa4Depg3s26cAXUQSnLBXk73w4mqycuXKGViZiIiIiIiIbaVwTsGaZmtI45KGA38f4OOfPsZisRhdlsSjGM9E//7771m1ahV169a1WRE9evSIsn3L9u3bw93+888/bXZeEVu6dg1q1IDr162Tx9etgzt3vmXfvuUA9OhRhm++2YfJFEVDlj//hEaNwN8fHBzgq6/gk08gqv1FROLYw4cPOX/+fOjtixcv4u/vT9q0acmWLdsrryYTERERERFJKt5O+zbLPlpGrR9q4XvUl+IZi9PrnV5GlyXxJMYheqpUqciVK1dc1CKSaP3zD9SsaZ2JnisXbN4Mjx9/y7lzXenXD+rXf5/u3ddHHaD7+Vn7n9++DenTw4oVUKlS/D4JEZH/c+jQId57773Q2y8W9fTy8mLBggU0a9aMmzdvMnToUK5fv46np2e4q8lERERERESSkuq5qjOpxiS8t3jz2ZbPKOxRmGq5qhldlsSDGLdzGT58OCNGjODJkydxUY9IovPoEbz/Ppw4AZkywS+/wJYtn3D6dFcAsmfvHXWAbrFYZ5zXrGkN0EuVgsOHFaCLSIJQpUoVLBZLhK8FCxaE7tOjRw8uXbpEUFAQ+/fvp2zZsvFfqC7YERERERGReNL7nd60LdaWEEsITVc05Y9//jC6JIkHMQ7RmzZtyj///IOHhwdFihShRIkS4b5E3iTBwdC4MezdC6lTW2egf/ddI9q1m8n48ZA5c2/efntK5AH648ek6tEDu759wWwGLy/YuROyZo335yEiIiIiIiIiIq9mMpmY/cFsSmcuzZ0nd2i4pCEPgx8aXZbEsRi3c/Hy8uLw4cO0bt2aDBkyRN2eQiSJe7Hu55Yt4OYGGzfC4sWNGDt2DQAFCpQjT54oAvRLlzA1bIirvz8We3tMX30FPXqo/7mIiIiIiIiISALn4uDC6marKTWnFMdvHKfdmnYs/2i5ctIkLMYh+oYNG9i8eTMVKlSIi3pEEgWLxbrm57Jl4OgIq1fDunUNGTduLQA9e77L1Km7Iv/H89dfoWlTTLdvE5IuHablyzGF6TksIiIiIiIiIiIJ21sp32JV01VU8a3CytMrGf3baAZXGmx0WRJHYtzOJWvWrKRMmTIuahFJNAYNgtmzrRPHf/gBtm2rHxqg9+5dPvIA3WKBqVND+59bSpbk9qZNULly/D8BERERERERERGJlXJZyzGz7kwAhmwbwtozaw2uSOJKjEP0yZMn069fP/788884KEck4Zs8GcaOtX7v4wNHjzZk3Lj1APTpU4EpU36LGKA/fWrted6nT2gfGMuOHZizZInn6kVERERERERExFY6luhIj9I9AGizug1nbp0xuCKJCzEO0Vu3bs22bdt4++23SZEiBWnTpg33JZKUzZsHfftavx87FurWnU7KlGtxdARv74pMnrwzYoB+7RpUqQLffw/29tbZ6L6+4Ooa3+WLiIiIiIiIiIiNTak1hcrZK/Mg+AGNljbiQdADo0sSG4txT/SpU6fGQRkiCd+qVdC5s/X7vn2hdetpnD/fk7JlYdOmLrz3nk/EAP3IEWjQAK5cgTRpYPlyqFbNus1iid8nICIiIiIiIiIiNudo78jSD5dS8tuSnLl1hnZr27HioxVaaDQJiVGI/uzZM3bs2MGQIUPImTNnXNUkkuD4+UGLFmA2Q8eOkCxZY7ZvX02WLJAt2wBy5hwT8R/G5cutLVyePIH8+WH9esid25gnICKSlOkPUxERERERMViG5BlY2XQllRZUYtXpVUzYPYH+FfobXZbYSIzauTg6OrJy5cq4qkUkQTpwwDqZPDgYGjeGlCnrMGLEavr0gdSp+0QM0M1mGDYMmja1Bui1a8O+fQrQRURERERERESSsLJZyvJN7W8A+OLXL9j6x1aDKxJbiXFP9IYNG7JmzZo4KEUk4Tl1CurUgUePrF1YsmWrzVdfbQKgQ4f3KFZscvgA/dEja3g+cqT19mefwU8/QapUBlQvIiIiIiIiIiLxqUvJLnTw7IDZYqb5iuZcunvJ6JLEBmLcEz1PnjyMHDmS3bt3U7JkSZIlSxZue8+ePW1WnIiRLl2CmjXhzh0oUwYKFqzF1KlbAOjXryrjxm0NH6Bfvmydsu7vD46OMHs2tG9vTPEiIiIiIiIiIhLvTCYTM96fwbEbxzh09RCNlzVmV/tduDq6Gl2axEKMQ/S5c+eSOnVqDh8+zOHDh8NtM5lMCtElSQgMhBo14O+/oWBBKF26FtOmWQP0AQOqMWbML+ED9D17oFEjuHEDPDysq5CWL29Q9SIiIiIiIiIiYhQXBxdWfLSCkt+W5Mi1I3Tf2J159edpodFELMYh+sWLF+OiDpEE4949axvzc+cge3Zo0uRDRo16SYC+YAF07Wptml6sGKxda32giIiIiIiIiIi8kbKnzs6SD5dQ64daLPBfQNm3yvJxqY+NLkteU4x7oodlsViwWCy2qkXEcI8fQ7161o4s1gnlkyhVaiV58sDAgdXDB+ghIfD559aWLcHB1pnou3YpQBcREREREREREarnqs7YamMB6PlzT/Zd2WdwRfK6XitEX7hwIUWKFMHV1RVXV1eKFi3K999/b+vaROJVcLB1TdDffoOUKWHt2kncv/85KVPCunVfMHr0lv8C9IcPoWFDmDTJenvIEFixApInN6x+ERERERERERFJWD5/93OaFGjCM/MzmixrQuDDQKNLktcQ4xB9ypQpdOvWjbp167Js2TKWLVtG7dq1+fjjj/nqq6/iokaROBcSAm3awIYN4OJioWHD6ixe/DkA2bMPI3/+0f8F6FeuQMWK8NNP4OwMixfDyJFgF6sLO0REREREREREJIkxmUzMbzCf/O75ufrgKk1XNOVZyDOjy5IYinFP9GnTpjFr1izatm0bel/9+vUpVKgQw4cPp0+fPjYtUCSuWSzWlubLloGDg4XGjauzcOGvANSq1ZWcOYf/t/Phw9Z+L9euWfu9rF0L77xjTOEiIiIiIiIiIpLgpXBOwepmqykzpww7L+2k3y/9+Kq2JiMnJjGeOnvt2jXefffdCPe/++67XLt2zSZFicQXiwU++wzmzgWTyUKTJtX48UdrgD54cC3q1vX5b+c1a6BSJWuAXqgQ7N+vAF1ERERERERERF4pv3t+fBv6AjB1/1SWn1xucEUSEzEO0XPnzs2yZcsi3L906VLy5Mljk6JE4svIkWDtQmShceOqLF26DYAhQ2ozatQm604WC0yeDI0bW1cerVkTdu+GHDmMKltERERERERERBKZRgUa0b98fwA6rOtAwK0AgyuS6IpxO5cRI0bQrFkzdu7cSfny5QHYvXs3fn5+kYbrIgnVlCkwfDiAhQYN3mPlyh2ANUAfOfJn607PnsEnn8CcOdbb3brBN9+AQ4z/1xERERERERERkTfcl1W/ZO+Vvey8tJMmy5qwv9N+kjklM7oseYUYz0Rv0qQJ+/fvx93dnTVr1rBmzRrc3d05cOAAjRo1iosaRWzuu++sbVwA+vfvzNq11gB96NC6/wXod+9C3brWAN1ksk5ZnzFDAbqIiIiIiIiIiLwWBzsHljRZQoZkGTh58yTdNnTDYrEYXZa8wmulgSVLluSHH36wdS0i8WLpUujSxfr97NmjyZt3LjduQLZs7zN8+E/WDX/8AR98AKdPQ7JksHixdUFRERFJeExGFyAiIiIiIhJ9mVJkYumHS6m6sCrfH/ueitkq0rlkZ6PLkpeI8Ux0kcRswwZo3RosFguTJw8jb97BAAwbNvq/AH3PHihb1hqgv/UW7NqlAF1ERERERERERGymco7KjKk6BoBPf/6UI9eOGFyRvEy0Q3Q7Ozvs7e1f+uWgNheSgG3bBk2awPPnFipXroiv70iePIGcOceQPfsX1p0WL4aqVeHWLShRAg4cAE9PQ+sWEREREREREZGk5/Pyn1Mvbz2CQoL4cNmH/PPkH6NLkihEO/VevXp1lNv27t3LN998g9lstklRIra2fz/Urw9BQRYqVqzIjh27Abh0qRV16gwEiwVGj4YhQ6wPaNgQfvjB2spFRERERERERETExuxMdvg29KXktyW5ePciXmu8WNV0ldFlSSSiHaI3aNAgwn0BAQEMGDCA9evX06pVK0aOHGnT4kRs4fhxqFMHHj608O67Ffjttz0AjBrVgI8//gGePYNu3WDuXOsD+vaF8ePBTt2OREREREREREQk7qRxTcOKpit4d+67rD+7nsl7J+OV28vosuT/vFZKePXqVTp37kyRIkV4/vw5/v7++Pr6kj17dlvXJxIr585BjRrwzz8W3nmnPHv2vAjQGzJ48Bp48MDa73zuXGtoPnMmTJyoAF1EREREREREROJFiUwlmFZnGgCDfh3Enqt7DK5I/l+MksJ79+7Rv39/cufOzcmTJ/Hz82P9+vUULlw4ruoTeW2XL0P16hAYaKF06XfZt28vAF9+2YjBg1fD1atQqRJs3gxubrB2rXVGuoiIiIiIiIiISDzqVKITbYu1JcQSQje/blx7cM3okiSMaIfoEyZMIFeuXPz0008sXryYPXv2ULFixbisTeS1BQZaZ6BfvmyhSxdvAgL2ATB6dGMGDVoFJ07AO++Avz94eMCOHfDBB8YWLSIiIiIiIiIibySTycSs92dROH1hbjy+QavVrXhufm50WfKvaPdEHzBgAK6uruTOnRtfX198fX0j3W/VKjW/F2P98w/UrAlnz1ro3XsYDRpMpXRpuHu3KX37LoVff4VGjeD+fciXD37+GXLmNLpsERF5XSajCxAREREREYk9N0c3ln+0nNJzSrPj0g6G/DqEsdXHGl2WEIMQvW3btphMepcqCdvDh1C3Lhw7ZqZt209p0GAmALVqTSZrVm/4/nvo2NG6mGiFCtYWLmnTGly1iIiIiIiIiIgI5E2XlymVp9BlaxfG7R5HhWwVeD/v+0aX9caLdoi+YMGCOCxDJPaePoUGDWDfPjNFi77DsmUHKVUKGjacQtYsveHLL2HIEOvOzZrBggXg4mJkySIiIiIiIiIiIuHUe7sen97/lGkHpuG1xgv/j/3JkjKL0WW90WK0sKhIQvXsmTUX//VXM0WKvMOxYwd5+hSCgpqRNWMP6NLlvwC9Xz/48UcF6CIiIiIiIiIikiCNrzaekplKcvvJbVqsbKH+6AZTiC6JXkgIeHnBunVmChcuy/HjBwEYP74ZfbvOgXr14LvvwM4OZsyA8eOt34uIiIiIiIiIiCRAzg7OLPtoGSmdU7Lr8i6GbhtqdElvNCWJkqiZzdC1KyxebKZQoTKcOHEIkwkmTmxOv9ZToFIl2LwZ3NxgzRro3t3okkVERERERAw1Y8YMcuTIgYuLC2XLluXAgQMv3X/q1Knky5cPV1dXsmbNSp8+fXj69GmsjikiIq+WK00u5tafC8DYXWPZfH6zwRW9uRSiS6JlsUCvXjB3rplChUpz8uRhTCaYMKEFfesOgXfeAX9/8PCA7dutM9JFRERERETeYEuXLsXb25thw4Zx5MgRihUrRq1atbhx40ak+//4448MGDCAYcOGcfr0aebOncvSpUv54osvXvuYIiISfR8W/JDupayTQtusbsPVB1cNrujNpBBdEiWLBQYMgOnTLXTq1I9UqY78OwO9JX3f6Q7ly8Nff0G+fLBvH5QubXTJIiISZ0xGFyAiIpJoTJkyhc6dO9O+fXsKFiyIj48Pbm5uzJs3L9L99+zZQ/ny5WnZsiU5cuSgZs2atGjRItxM85geU0REYmZyrcl4ZvTk5uObtFzZUv3RDeBgdAEir2PUKJgwwULXrv1p3nwywcFw82Z3WiWrATVqwNOnUK4crF8P6dIZXa6IiIiIiIjhgoODOXz4MAMHDgy9z87OjurVq7N3795IH/Puu+/yww8/cODAAcqUKcMff/zBxo0badOmzWsfMygoiKCgoNDb9+/fB8BsNmM2m6OsPyQkhGfPnkX/Cb9BzGYzwcHBPH78GLt4XgPMyckp3s8ZV8xmMxaL5aWvQ3k5jWHsRTaGTnZOLGm8hFLflWLHpR2M2D6CEVVGGFhlwhYXrz+F6JLoTJwIw4aZqV69Ic2arQegUKHpvLXeHto2sTZKr18fFi+29kIXERERERERbt26RUhICBkyZAh3f4YMGThz5kykj2nZsiW3bt2iQoUKWCwWnj9/zscffxzazuV1jjl27FhGjIgY/ty8eZPg4OAI91ssFh4+fMjTp08xmXQFWlTMZnPoBxLxLU2aNNjb2xtyblsym83cu3cPi8WSZD4YiG8aw9iLagxTkYqJFSfSza8bo38bTZGURaiUpZKBlSZc9+7ds/kxFaJLojJjBvTrF0LBgiXZuvUoqVPD1K+m89a3N2DkSOtOnTvDzJngoJe3iIiIiIhIbGzfvp0xY8Ywc+ZMypYty/nz5+nVqxejRo1iyJAhr3XMgQMH4u3tHXr7/v37ZM2alfTp05M6deoI+1+/fp3nz5+TKVMm3NzcFKRH4dmzZzg6OsbrOc1mM1evXuXZs2dkzJgx0f9szGYzJpOJ9OnTKwB+TRrD2HvZGHbx6MKRf44w58gcPt3+KUc6HyFTikwGVZpwOTk52fyYShkl0Zg3D3r0CKFgwRKcOnUMkwnKl2vNWyP84bvvrDsNG2b9SuS/uEVEkppGjRqxfft2qlWrxooVK6K9LVr0T76IiEi0uLu7Y29vT2BgYLj7AwMDyZgxY6SPGTJkCG3atKFTp04AFClShEePHtGlSxcGDRr0Wsd0dnbG2dk5wv12dnYRAqOQkBDu3buHh4cH6dSqM0oWiwUHBwccHBziPcj28PDg6tWrmM3meA/x44LJZIr0tSjRpzGMvZeN4de1v2b/3/s5FniMNmva8EubX7C3S/xXgthSXLz29GqWRGHxYujYMYSCBYuHBuhfTWxF7x33rQG6nR34+MDw4QrQRUQSoF69erFw4cIYbxMRERHbcXJyomTJkvj5+YXeZzab8fPzo1y5cpE+JrIe2y/adlgsltc6Zky86IHupladCdaLGZ8hISEGVyLyZnB1dGXZh8tI5piMbX9u48udXxpd0htBIbokeKtXQ+vWIRQs6MmpU8etAfq4FvRadRHWrQMXF1i5Erp2NbpUERGJQpUqVUiRIkWMt4mIiIhteXt7M2fOHHx9fTl9+jTdunXj0aNHtG/fHoC2bduGWyS0Xr16zJo1iyVLlnDx4kV++eUXhgwZQr169ULD9Fcd0xYSe5uQpEw/G5H4l889Hz4f+AAwYscItl3cZnBFSZ9CdEnQNm2CZs0s/85AP4HJBFNHf0SvBf6wZw+kTg2//AINGxpcqYhI4rVz507q1atH5syZMZlMrFmzJsI+M2bMIEeOHLi4uFC2bFkOHDgQ/4WKiIhIrDVr1oxJkyYxdOhQPD098ff3Z9OmTaELg16+fJlr166F7j948GA+++wzBg8eTMGCBenYsSO1atVi9uzZ0T6mJCyPHz+mSZMmpEyZEpPJxN27d40uSUReQ+uireng2QELFlquakngw8BXP0hem3qiS4K1fTs0amShS5c+pElznDNnYMqQhnw6fTdcvQpZslhT9kKFjC5VRCRRe/ToEcWKFaNDhw40btw4wvalS5fi7e2Nj48PZcuWZerUqdSqVYuAgAA8PDwA8PT05Pnz5xEeu2XLFjJnzhznz0FERESir0ePHvTo0SPSbdu3bw9328HBgWHDhjFs2LDXPuabKiQkhOHDh/PDDz9w/fp1MmfOTLt27Rg8eLChs7d9fX357bff2LNnD+7u7qRKlcqwWkQkdqbVncb+v/dz8uZJ2q1tx4aWG7Azac50XFCILgnS3r3wwQcWOnXqTZMm3wBQv3AXSnddCvfuWYPzTZusQbqIiMRKnTp1qFOnTpTbp0yZQufOnUMvyfbx8WHDhg3MmzePAQMGAODv7x/ndQYFBREUFBR6+/79+6Hfm83mOD9/UmQ2m7FYLBq/WNI4xp7GMPY0hrGnsRNbGz9+PLNmzcLX15dChQpx6NAh2rdvT6pUqejZs6dhdV24cIECBQpQuHBhw2oQEdtwc3Rj2UfLKPVtKTad38TUfVPxLudtdFlJkkJ0SXAOH4ZatUIoWLAclSodBCDvw4/J7DUfgoKgYkVYuxbSpDG4UhGRpC84OJjDhw+H641qZ2dH9erV2bt3b7zWMnbsWEaMGBHh/pAQMzdu3IjXWpIKs9nMvXv3sFgscbKC/ZtC4xh7GsPY0xjG3r1794wuQZKYPXv20KBBA95//30AcuTIweLFi1/ZFm/9+vWMHDmS48ePkzx5cipWrMjq1asB+Oeff+jVqxfr168nKCiIypUr880335A7d+7Qx+/atYuBAwdy6NAh3N3dadSoEWPHjiVZsmRUqVKFHTt2ANZe5pUrV45w9YGIJC4F0xdkau2pdP2pKwO2DqBy9sqUzFzS6LKSHIXokqCcOAE1aoSQNWsRDh48Td++sHNUczK3mw0WCzRqBIsWgaur0aWKiLwRbt26RUhISISephkyZODMmTPRPk716tU5evQojx49IkuWLCxfvpxy5cq9cltYAwcOxNv7v1kV9+/fJ2vWrNjb24W2lZGYMZvNmEwm0qdPr9AtFjSOsacxjD2NYew5OTkZXYIkMe+++y7ffvstZ8+eJW/evBw9epRdu3YxZcqUKB+zYcMGGjVqxKBBg1i4cCHBwcFs3LgxdHu7du04d+4c69atI2XKlPTv35+6dety8uRJTCYTFy5coHbt2nz55ZfMmzePmzdvhrbamT9/PqtWrWLAgAGcOHGCVatW6XUvkkR0LtGZLRe2sPL0SpqvbM6RLkdI4ZzC6LKSFIXokmCcPQvVqoWQKVNhTp06g50d9K9eguxeS6w7dOsG06bBvyvAi4hI4rF169bX2haWs7Mzzs7OkW5TYPT6TCYTdnZ2GsNY0jjGnsYw9jSGsaNxS0QsFrA8NubcJjeIZj/zAQMGcP/+ffLnz4+9vT0hISGMHj2aVq1aRfmY0aNH07x583BX3xUrVgwgNDzfvXs37777LgCLFi0ia9asrFmzJnTGeatWrejduzcAefLk4ZtvvqFy5crMmjWLtGnT4ubmhpOTExkzZnzNQRCRhMZkMjGn3hwO/H2A83fO8+nPn7Kg4QKjy0pSFKJLgnDxIlStGoK7+38B+vQWBek274h1h+HDYejQaP+xIiIituHu7o69vT2BgeFXeg8MDNQbLxERETGG5TGcTW7MufM+BFOyaO26bNkyFi1axI8//kihQoXw9/end+/eZM6cGS8vr0gf4+/vT+fOnSPddvr0aRwcHChbtmzofenSpSNfvnycPn2aRo0acezYMY4dO8aiRYtC93mxXsLFixcpUKBADJ6siCQmaVzT8GOTH6m8oDK+R32pkasGrYpG/aGdxIw+ahfDXbkC1ao9I1WqQqEB+oxGb9Nt0SlraD5jBgwbpgBdRMQATk5OlCxZEj8/v9D7zGYzfn5+kbZcERERERGrzz//nAEDBtC8eXOKFClCmzZt6NOnD2PHjo3yMa6xbF368OFDunbtir+/f+jX0aNHOXfuHG+//Xasji0iCV+FbBUYVnkYAN02dOPCnQsGV5R0aCa6GCowEKpXN5M+/TscOBBgDdDrZuXjlRfA0REWLoTmzY0uU0QkSXv48CHnz58PvX3x4kX8/f1JmzYt2bJlw9vbGy8vL0qVKkWZMmWYOnUqjx49on379gZWHYY+YxUREXmzmNysM8KNOnc0PX78OEKbIHt7e8xmc5SPKVq0KH5+fpH+nVWgQAGeP3/O/v37Q9u53L59m4CAAAoWLAhAiRIlOHXqVLiFRkXkzTKo4iD8Lvqx89JOWqxswa4Ou3Cy1/oHsaUQXQxz+zbUqGGmbt3uvPvuEfr2hS/yZaDLT3+BmxusWgW1ahldpohIknfo0CHee++90NsvFu/08vJiwYIFNGvWjJs3bzJ06FCuX7+Op6cnmzZtirDYqIiIiEi8MJmi3VLFSPXq1WP06NFky5aNQoUK8fvvvzNlyhQ6dOgQ5WOGDRtGtWrVePvtt2nevDnPnz9n48aN9O/fnzx58tCgQQM6d+7M7NmzSZEiBQMGDOCtt96iQYMGAPTr149y5crRo0cPOnXqRLJkyTh16hS//PIL06dPj/ScAwcO5O+//2bhwoVxMg4iEr/s7ez5odEPFPMpxsGrBxm6bSjjqo8zuqxET+1cxBD37kHt2maqV+9O/fqzcXc38dt7memyJRDSpAE/PwXoIiLxpEqVKlgslghfCxYsCN2nR48eXLp0iaCgIPbv3x+uF6eIiIiIRDRt2jQ+/PBDunfvToECBejbty9du3Zl1KhRUT6mSpUqLF++nHXr1uHp6UnVqlU5cOBA6Pb58+dTsmRJPvjgA8qVK4fFYmHjxo04OjoC1pnsO3bs4OzZs1SsWJHixYszdOhQMmfOHOU5r127xuXLl233xEXEcFlTZWVu/bkAjN89nl8u/GJwRYmfZqJLvHvwAGrXfsaTJ4VxdT0LFhP556Ql4+KrkDkzbNkChQoZXaaIiIiIiIjIa0uRIgVTp05l6tSpMXpc48aNady4caTb0qRJE+mMcYvFEvp96dKl2bJlS5TH//96wk6cEJGko1GBRnQr1Y1Zh2bRZnUbjnU7hkcyD6PLSrQ0E13i1aNHULfuM+7fL8jJk2eZOBFSTXQj4+LbkCcP7N6tAF1ERGJITdFFRERERET+3+SakymUvhCBjwLxWuOF2RL1mgzycgrRJd48fgwffPCM27cLcurUeeztYWZRR4r//AiKF4dduyBHDqPLFBERERERERERSfRcHV1Z8uESXBxc2HR+E1/v+9rokhIthegSL54+hYYNnxEYWIDTp60B+rdF7Oh0+BlUrgzbt4OHLikRERERERERERGxlcIehfmq1lcA9N/anyPXjhhcUeKkEF3iXHAwNGnyjCtXCnD69AXs7WFOIejgb4aGDWHTJkiZ0ugyRUQksVI3FxERERERkSh1LdmVRvkb8cz8jOYrmvMw+KHRJSU6CtElTj17Bs2amTGZavwXoBeE9seA9u1h+XJwcTG6TBERERERERERkSTJZDLxXf3vyJIyC+funMN7s7fRJSU6CtElzjx/Dq1amcmbtxOffbaDph/BdwWh/XHg889h7lxwcDC6TBERERERERERkSQtrWtaFjZciAkTc47MYc2ZNUaXlKgoRJc4ERICbdsGkTVrO+rUmY/JYuKbW9DuODBhgvXLpOvvRURERERERERE4sN7Od/j83c/B6DTuk5cfXDV4IoSD4XoYnNmM3TsGMTvv+dn797vCX4CBb+0kGGHHXz3nXUWuoiIiIiIiIiIiMSrUVVHUTxjcW4/uU37te0xW8xGl5QoKEQXm7JY4OOPg9i/Px9nzvzJwYMQPAg8djnCkiXQsaPRJYqIiIiIiIiIiLyRnOydWNR4ES4OLmy5sIVp+6cZXVKioBBdbMZigR49gvjtt3ycOXMJBweYmw8+OOMK69bBRx8ZXaKIiIiIiIiIvMKZM2d45513cHFxwdPT0+hyRMTGCqQvwJSaUwDov7U/xwOPG1xRwqcQXWzCYoE+fZ7y66//Bejz8kHbyylg82aoXdvoEkVERERERETizc6dO6lXrx6ZM2fGZDKxZs2acNufPXtG//79KVKkCMmSJSNz5sy0bduWq1eN71E8bNgwkiVLRkBAAH5+fkaXIyJx4ONSH/NB3g8ICgmi5aqWPH3+1OiSEjSF6BJrFgv07/+UzZvDB+htrqeDX3+FihWNLlFERJIyrVMtIiIiCdCjR48oVqwYM2bMiHT748ePOXLkCEOGDOHIkSOsWrWKgIAA6tevH8+VRnThwgUqVKhA9uzZSZcundHliEgcMJlMzK0/F49kHpy4cYKBWwcaXVKCphBdYm3EiBDu3v2QS5cu4+gIC/JBmzuZYOdOKFXK6PJERERERERE4l2dOnX48ssvadSoUaTbU6VKxS+//ELTpk3Jly8f77zzDtOnT+fw4cNcvnw5yuOazWYmTJhA7ty5cXZ2Jlu2bIwePTp0+/Hjx6latSqurq6kS5eOLl268PDhw3DH+O677yhQoAAuLi7kz5+fmTNnhm4zmUwcPnyYkSNHYjKZGD58eOwGQkQSLI9kHsxvMB+AqfunsuXCFoMrSrgMD9FnzJhBjhw5cHFxoWzZshw4cCDKfU+ePEmTJk3IkSMHJpOJqVOnxl+hEqkxY57z/HlbWrbcwPgxsCAvtHqcE3btgoIFjS5PREREREREJNG4d+8eJpOJ1KlTR7nPwIEDGTduHEOGDOHUqVP8+OOPZMiQAbDOfq9VqxZp0qTh4MGDLF++nK1bt9KjR4/Qxy9atIihQ4cyevRoTp8+zZgxYxgyZAi+vr4AXLt2jUKFCvHZZ59x7do1+vbtG6fPWUSMVTdPXT4p/QkAXmu8uPX4lsEVJUwORp586dKleHt74+PjQ9myZZk6dSq1atUiICAADw+PCPs/fvyYXLly8dFHH9GnTx8DKpawJkx4wt9/N+ejj37C9Byar4T0loLw2xZ46y2jyxMRkTeG+rmIiIi8USwWePzYmHO7uYEpbv72ePr0Kf3796dFixakTJky0n0ePHjA119/zfTp0/Hy8gLg7bffpnz58jx//pwff/yRp0+fsnDhQpIlSwbA9OnTqVevHuPHjydDhgwMGzaMyZMn07hxYwBy5szJqVOnmD17Nl5eXmTMmBEHBweSJ09OxowZ4+S5ikjCMrHGRH69+Cunb52m8/rOrGq6ClMc/VuXWBkaok+ZMoXOnTvTvn17AHx8fNiwYQPz5s1jwIABEfYvXbo0pUuXBoh0u8QfHx9YsiQ/165doXgRaLAI0j8pCTs2gbu70eWJiIiIiIhIUvX4MSRPbsy5Hz6Ef8NpW3r27BlNmzbFYrEwa9asKPc7ffo0QUFBVKtWLcrtxYoVCw3QAcqXL4/ZbCYgIIDkyZNz4cIFOnbsSOfOnUP3ef78OalSpbLdExKRRMXV0ZUfm/xImTllWHNmDXN/n0unEp2MLitBMaydS3BwMIcPH6Z69er/FWNnR/Xq1dm7d69RZUk0TJ/+mCVLShEQcIUnTyDFNEhvV8m6iKgCdBEREREREZFoexGgX7p0iV9++SXKWegArq6usTrXi97oc+bMwd/fP/TrxIkT7Nu3L1bHFpHEzTOjJ2OqjQGg16ZenL191uCKEhbDZqLfunWLkJCQ0L5dL2TIkIEzZ87Y7DxBQUEEBQWF3r5//z5gXYjDbDbb7Dxvim+/fcyMGfk5e/ZvHB3h+zzQNFttzMuXWy9r05hGm9lsxmKx6HUYCxrD2NMYxp7GTkRERCSeublZZ4QbdW4behGgnzt3jm3btpEuXbqX7p8nTx5cXV3x8/OjU6eIs0QLFCiAr68vjx49Cp2Nvnv3buzs7MiXLx8ZMmQgc+bM/PHHH7Rq1cqmz0VEEj/vct78fP5nfr34K61XtWZ3h9042jsaXVaCYGg7l/gwduxYRowYEeH+mzdvEhwcbEBFideSJWZ8fEpz9uxVHB3hh9xQ7+16BE6fbv0Dxqg/YhIps9nMvXv3sFgs2NkZvsZvoqQxjD2NYezdu3fP6BJERERE3iwmU5y0VLG1hw8fcv78+dDbFy9exN/fn7Rp05ItWzaePXvGhx9+yJEjR/jpp58ICQnh+vXrAKRNmxYnJ6cIx3RxcaF///7069cPJycnypcvz82bNzlx4gReXl60atWK4cOH4+XlxfDhw7l58yaffvopbdq0CZ3EOGLECHr27EmqVKmoXbs2QUFBHDp0iH/++Qdvb+9In0u1atVo1KhRuAVKRSTpsTPZ4dvQl6KzinLw6kFG7BjBl1W/NLqsBMGwEN3d3R17e3sCAwPD3R8YGGjThSsGDhwY7pfA/fv3yZo1K+nTp3/patcS3qJFj/DxyU9AwH8B+ofvtIfZs/Gwtze6vETJbDZjMplInz69wsvXpDGMPY1h7EX25kZERERE5NChQ7z33nuht19kE15eXixYsIC///6bdevWAeDp6Rnusdu2baNKlSqRHnfIkCE4ODgwdOhQrl69SqZMmejatSsAbm5ubN68mV69elG6dGnc3Nxo0qQJU6ZMCX18p06dcHNzY+LEiXz++eckS5aMIkWK0Lt37yify4ULF7h169ZrjIKIJDZZUmbh23rf8tHyjxi7ayzv53mfclnLGV2W4QwL0Z2cnChZsiR+fn40bNgQsIY5fn5+Nv1k09nZGWdn5wj329nZKTCKplWrnnHmTFtcXP4L0N+v2AVmzsROAXqsmEwmvRZjSWMYexrD2NG4iYiIiEhkqlSpgsViiXJ7jhw5Xro9KnZ2dgwaNIhBgwaF3mexWHj+/DkARYoU4ddff33pMVq2bEnLli2j3O7v7x/u9p9//hnjOkUk8fqw4Ie0LtqaH479QNs1bfHv6k8yp4R/BVBcMvSdv7e3N3PmzMHX15fTp0/TrVs3Hj16RPv27QFo27YtAwcODN0/ODg4dNGL4OBg/v77b/z9/cNdHiW2tX79M06eaEGNGmsYNxLW5IUPmw7jwfDh1kvoREREREREREREJEmZVmcaWVJm4fyd8/Td0tfocgxnaIjerFkzJk2axNChQ/H09MTf359NmzaF9um6fPky165dC93/6tWrFC9enOLFi3Pt2jUmTZpE8eLFI11MQ2Jv7dqHfP99eSpWWokpGEqPhbodp8DQoQrQRUQk4dCvJBEREREREZtK7ZKaBQ0WAOBz2Iefz/1sbEEGM3xh0R49ekTZvmX79u3hbr/upU4Sc+vWPaR/vzwEnL1OqmQw7jSka+8DXbuC2Wx0eSIiIiIiIiIiIhKHquWqRs8yPfnmwDd0XNeR492Ok84tndFlGUKNXCWCn356QL/PcxNw9jpOTlBnP6Tr7msN0EVEREREREREROSNMK76OPK75+faw2t039j9jZ3grBBdwtm48QF9++Yh4Gwgzs6wOLeJxiOWQdu2RpcmIiIiIiIiIiIi8cjV0ZXvG32Pg50Dy04uY/GJxUaXZAiF6BJq06b7ePfJTUDAiwDdjsbj1sJHHxldmoiIiIiIiIiIiBigVOZSDKk0BIBPNn7ClftXDK4o/ilEFwB+/fUpfXrnIeDsjX8DdAcafbUJ6tUzujQREREREREREREx0BcVv6DMW2W4+/Qu7de2x2x5s9ZMVIgu7NwZzJH9jalV+wYuzrAkryONZvpBjRpGlyYiIiIiIiIiIiIGc7BzYGHDhbg6uLL1j63MODDD6JLilUL0N9yuXUEc2lufUuV+plFdOFTClYZzfoNKlYwuTUREJHpMRhcgIiIiIiKS9OVzz8eEGhMA6Le1H2dunTG4ovijEP0Ntm3bPQYNyMvb+TdjFwSFx6ek0Mw9ULas0aWJiIiIiIiIiEGuX79OjRo1SJYsGalTpza6HBFJQLqX7k6NXDV4+vwpbVa34VnIM6NLihcK0d9QO3bco/vHudi5+zJDBkHBialJN20veHoaXZqIiIiIiIhIordz507q1atH5syZMZlMrFmzJtL9Tp8+Tf369UmVKhXJkiWjdOnSXL58OX6L/T9fffUV165dw9/fn7Nnzxpai4gkLHYmO+Y3mE9ql9QcunqI0b+NNrqkeKEQ/Q20c+ddPu6SizNn7+DiDF+6pcJ91gEoWNDo0kRERERERESShEePHlGsWDFmzIi6b/CFCxeoUKEC+fPnZ/v27Rw7dowhQ4bg4uISj5VGXlfJkiXJkycPHh4ehtYiIgnPWynfYmbdmQB8ufNLDvx9wOCK4p5C9DfMrl3/0LWTNUB3dYFlxdNSf/lRyJPH6NJEREREREREkow6derw5Zdf0qhRoyj3GTRoEHXr1mXChAkUL16ct99+m/r1678yuJ43bx6FChXC2dmZTJky0aNHj9Btly9fpkGDBiRPnpyUKVPStGlTAgMDwz1+7dq1lChRAhcXF3LlysWIESN4/vw5ADly5GDlypUsXLgQk8lEu3btXn8QRCTJalGkBc0KNSPEEkKb1W14/Oyx0SXFKYXob5A9e/6hS4dcnDn3jzVAL+lBvRXHIHt2o0sTERERERERiRaLBR49MubLYrHd8zCbzWzYsIG8efNSq1YtPDw8KFu2bJRtX16YNWsWn3zyCV26dOH48eOsW7eO3Llzhx6zQYMG3Llzhx07dvDLL7/wxx9/0KxZs9DH//bbb7Rt25ZevXpx6tQpZs+ezYIFCxg92tqS4eDBg9SuXZumTZty7do1vv76a9s9aRFJUma+P5NMyTNx9vZZvvD7wuhy4pSD0QVI/PD3f0rfXvk4fe6uNUAvk4kPlvuDLssSERERERGRROTxY0ie3JhzP3wIyZLZ5lg3btzg4cOHjBs3ji+//JLx48ezadMmGjduzLZt26hcuXKkj/vyyy/57LPP6NWrV+h9pUqV4vnz5/j5+XH8+HEuXrxI1qxZAVi4cCGFChXi4MGDlC5dmhEjRjBgwAC8vLwAyJUrF6NGjaJfv34MGzaM9OnT4+zsjKurKxkzZrTNkxWRJCmta1rmNZhHnUV1+Hr/1zTK34jKOSL/tyux00z0N8DRo0857Pcen/S+SbassKxcVj5YfUIBuoiIiIiIyBtoxowZ5MiRAxcXF8qWLcuBA1H3sq1SpQomkynC1/vvvx+6T7t27SJsr127dnw8lUTNbDYD0KBBA/r06YOnpycDBgzggw8+wMfHJ9LH3Lhxg6tXr1KtWrVIt58+fZqsWbOGBugABQsWJHXq1Jw+fRqAo0ePMnLkSJInTx761blzZ65du8bjx0m7HYOI2F7t3LXpVLwTAO3Xtudh8EODK4obmomexB079oTf/arwdskD2D2FAxUKkcFnD6RMaXRpIiIitmEyugAREZHEY+nSpXh7e+Pj40PZsmWZOnUqtWrVIiAgINI+3KtWrSI4ODj09u3btylWrBgfffRRuP1q167N/PnzQ287OzvH2XNwc7POCDeCm5vtjuXu7o6DgwMFCxYMd3+BAgXYtWtXpI9xdXWN9XkfPnzIiBEjaNy4cYRtRi9oKiKJ0+Rak9nyxxYu3r1Iv1/6MfP9mUaXZHMK0ZOwgwfv0KltTpq3vU+uJ1BwaQnc5+y03bVnIiIiIiIikqhMmTKFzp070759ewB8fHzYsGED8+bNY8CAARH2T5s2bbjbS5Yswc3NLUKI7uzsHG+tP0ympPG21snJidKlSxMQEBDu/rNnz5I9irXLUqRIQY4cOfDz8+O9996LsL1AgQL89ddf/PXXX6Gz0U+dOsXdu3dDw/oSJUoQEBAQ2kddRCS2UjqnZF79eVT/vjqzDs2icYHGVM9V3eiybErtXJKow4dv065VDo6duc/4cZBtcUncfXYnjb80REQk0WnUqBFp0qThww8/DHf/3bt3KVWqFJ6enhQuXJg5c+YYVKGIiEjSFxwczOHDh6le/b9gw87OjurVq7N3795oHWPu3Lk0b96cZP/33nL79u14eHiQL18+unXrxu3bt21ae2L08OFD/P398ff3B+DixYv4+/tz+fLl0H0+//xzli5dypw5czh//jzTp09n/fr1dO/ePcrjDh8+nMmTJ/PNN99w7tw5jhw5wrRp0wCoXr06RYoUoVWrVhw5coQDBw7Qtm1bKleuTKlSpQAYOnQoCxcuZMSIEZw8eZLTp0+zZMkSBg8eHOU527Zty8CBA20wKiKSVFXLVY3upaz/dnVc15H7QfcNrsi2NBM9CTpy5BZtm+fk1PmHuLnCoiqFyTFnN8Th5XQiIiIv06tXLzp06ICvr2+4+1OkSMHOnTtxc3Pj0aNHFC5cmMaNG5MuXboYHF39XERERKLj1q1bhISEkCFDhnD3Z8iQgTNnzrzy8QcOHODEiRPMnTs33P21a9emcePG5MyZkwsXLvDFF19Qp04d9u7di729fYTjBAUFERQUFHr7/n1r0GI2m0P7hL9gNpuxWCyhX4nJwYMHqVq1auhtb29vALy8vEJb3zRs2JBZs2Yxbtw4evbsSb58+VixYgXly5eP8vm2bduWJ0+eMHXqVPr27Yu7uztNmjTBYrFgMplYs2YNPXv2pFKlStjZ2VG7dm2++eab0OPVrFmT9evXM2rUKMaPH4+joyP58+enY8eOEc754vbly5exs7OLtKYXP5vIfn6JzYvXW2J/HkbSGMZeYh7DsdXGsunCJv745w/6bOrDnHrGTJKKi7FTiJ7E/P77LVo3y8Hp849wc4XltTypu3Q/ODkZXZqIiLzBqlSpwvbt2yPcb29vj9u/zUWDgoIS5RtkERGRN8XcuXMpUqQIZcqUCXd/8+bNQ78vUqQIRYsW5e2332b79u2RLoA5duxYRowYEeH+mzdvhuu/DvDs2TPMZjPPnz/n+fPnNnom8aNChQoRns8LYZ9L27Ztadu2bZTbI9OxY0c6duwYettisRASEgJA5syZWbFixUvPWa1atUh/Ni/2Wb58ebjbv/zyS5R1PX/+HLPZzO3bt3F0dHxp3Qmd2Wzm3r17WCwW7OzUvOF1aAxjL7GP4aQKk2iyvgnz/OdRNVNVqmWLfCHkuHTv3j2bH1MhehLi73+T1k1zhgboy+qWpO6SfeCgH7OIiERt586dTJw4kcOHD3Pt2jVWr15Nw4YNw+0zY8YMJk6cyPXr1ylWrBjTpk2L8Ab6dd29e5fKlStz7tw5Jk6ciLu7u02OKyIiIuG5u7tjb29PYGBguPsDAwNf2c/80aNHLFmyhJEjR77yPLly5cLd3Z3z589HGtQOHDgwdFY2WGeiZ82alfTp05M6depw+z59+pQHDx7g4OCAg97bvpIRIbaDgwN2dnakS5cu0S9MajabMZlMpE+fPlGGlwmBxjD2EvsYNvBoQM8bPfl6/9f029WPY12PkcY1TbzW4BQHk4n1GyiJOHfuMZOGFeHU+Uckc4Nl75eh7o+7FaCLiMgrPXr0iGLFitGhQwcaN24cYfvSpUvx9vbGx8eHsmXLMnXqVGrVqkVAQAAeHh4AeHp6RjozacuWLWTOnPml50+dOjVHjx4lMDCQxo0b8+GHH0a4zFxERERiz8nJiZIlS+Ln5xf6gbnZbMbPz48ePXq89LHLly8nKCiI1q1bv/I8V65c4fbt22TKlCnS7c7OzjhH0m7Uzs4uQmBkZ2eHyWQK/ZLIvWjlAsT7OL342UT280uMktJzMYrGMPYS+xiOqTaGn8//zNnbZ+mzpQ8LGy2M1/PHxbgpYU0CLlx4jP/PpWjfM5BHIdA5eTnqLvoNIuk9JyIi8v/q1KlDnTp1otw+ZcoUOnfuTPv27QHw8fFhw4YNzJs3jwEDBgCELpgVGxkyZKBYsWL89ttvERYghaj7p0Lc9Lx7EyTmfosJicYx9jSGsacxjL03Zey8vb3x8vKiVKlSlClThqlTp/Lo0aPQ3/Nt27blrbfeYuzYseEeN3fuXBo2bBhh3ZKHDx8yYsQImjRpQsaMGblw4QL9+vUjd+7c1KpVK96el4iIJBxujm4saLCACvMr8P2x72lSoAkN8jcwuqxYUYieyJ08eYuTv1TAwzMA+8fgk78BGSasgkT6SZWIiCQswcHBHD58mIEDB4beZ2dnR/Xq1dm7d2+sjx8YGIibmxspUqTg3r177Ny5k27dukW6b1T9U0NCQrhx40asa3kTJfZ+iwmFxjH2NIaxpzGMvbjon5oQNWvWjJs3bzJ06FCuX7+Op6cnmzZtCr0K7MUCkmEFBASwa9cutmzZEuF49vb2HDt2DF9fX+7evUvmzJmpWbMmo0aNinS2uYiIvBnKZS1H33J9mbBnAl1/6kqFbBVI55bu1Q9MoBSiJ2InTwbyUYOcZMn1hC/ehty7m5Bh4nLQJW4iImIjt27dIiQkJEJ7lQwZMnDmzJloH6d69eocPXqUR48ekSVLFpYvX065cuW4dOkSXbp0CV1Q9NNPP6VIkSKRHiOq/qn29vahbWUkZhJ7v8WEQuMYexrD2NMYxl5c9E9NqHr06BFl+5bIFgLPly9flAt/u7q6snnzZluWJyIiScSI90bw07mfOHXzFJ9s/IQlHy4xuqTXphA9kTp1KpCmDXJw+sJTLl8Dh1x1yTRLAbqIiCRMW7dujfT+MmXKRLsVTFT9UzHFTc+7N0Vi77eYUGgcY09jGHsaw9jRuImIiNiWi4MLvg19eee7d1h6cilNCjTho0IfGV3Wa9FfCYnQqVPX+bBeDk5deEryZLC0eR0qzPpJAbqIiNicu7s79vb2BAYGhrs/MDCQjBkzGlSViIiIiIiIJAalMpdiYAVre9DuG7tz41HibMWpED2ReRGgn/7j3wC95Qe8/90GBegiIhInnJycKFmyJH5+fqH3mc1m/Pz8KFeunIGViYiIiIiISGIwpPIQimYoyq3Ht/j4p4+jbBGWkClET0ROnbz6b4AeRPJksKR1Q+p+u14BuoiIxMrDhw/x9/cPbaty8eJF/P39uXz5MgDe3t7MmTMHX19fTp8+Tbdu3Xj06BHt27c3sGoRERERERFJDJzsnfBt6IuDnQOrz6xmyYnE1xtdIXoicfnSA9Z/V5zzf/0boLf7kPd9VhtdloiIJAGHDh2iePHiFC9eHLCG5sWLF2fo0KEANGvWjEmTJjF06FA8PT3x9/dn06ZNERYbFREREREREYmMZ0ZPhlQaAsCnP3+a6Nq6KERPBC5fesDJnwpStsENRn8BSzo25/3py40uS0REkogqVapgsVgifC1YsCB0nx49enDp0iWCgoLYv38/ZcuWNa5gERERkQTOYrFQvXp1atWqFWHbzJkzSZ06NVeuXDGgMhER4wysMJBiGYpx+8ltemzsYXQ5MaIQPYE7eeIKfr65cS10BfuH0CJVX97/erHRZYmIiIiIiIhIFEwmE/Pnz2f//v3Mnj079P6LFy/Sr18/pk2bRpYsWQysUEQk/jnaOzK/wXzsTfYsP7WcladWGl1StClET8BOHLvMh/Vz0W/aDa6ehRwXB5Klz0SjyxIRERERERGRV8iaNStff/01ffv25eLFi1gsFjp27EjNmjUpXrw4derUIXny5GTIkIE2bdpw69at0MeazWbGjh1Lzpw5cXV1pVixYqxYscLAZyMiYhvFMxVnQIUBAHTf2J3bj28bXFH0KERPoE4cu0zThrk5c/EZQU8h9R+dyPrpGKPLEhERSXi0wLaIiMgbxWKxEPwo2JAvi8USo1q9vLyoVq0aHTp0YPr06Zw4cYLZs2dTtWpVihcvzqFDh9i0aROBgYE0bdo09HFjx45l4cKF+Pj4cPLkSfr06UPr1q3ZsWOHrYdTRCTeDak0hILpC3Lj0Q16bepldDnR4mB0ARLRiaOX+Khhbs78+ZwUyWFJz67UHe1jdFkiIiIiIiIihnv2+Bljk4815NwDHw7EKZlTjB7z7bffUqhQIXbu3MnKlSuZPXs2xYsXZ8yY/ybKzZs3j6xZs3L27FmyZ8/OmDFj2Lp1K+XKlQMgV65c7Nq1i9mzZ1O5cmWbPicRkfjm7ODM/AbzKTe3HIuOL6JZoWbUy1fP6LJeSjPRE5gTR/8MDdBTpoCl3j0UoIuIiIiIiIgkUh4eHnTt2pUCBQrQsGFDjh49yrZt20iePHnoV/78+QG4cOEC58+f5/Hjx9SoUSPcPgsXLuTChQsGPxsREdso81YZPiv3GQAfb/iYu0/vGlvQK2gmegJywv8iHzXKGxqgL+nbmzpDvzK6LBEREREREZEEw9HNkYEPBxp27tfh4OCAg4M1gnn48CH16tVj/PjxEfbLlCkTJ06cAGDDhg289dZb4bY7Ozu/1vlFRBKiEVVGsDZgLWdvn8V7szfzGswzuqQoKURPIC5duMUFvxKEOP4boPf7jDqDJxldloiIiIiIiEiCYjKZYtxSJSEpUaIEK1euJEeOHKHBelgFCxbE2dmZy5cvq3WLiCRpro6uzKs/j4rzKzLffz7NCjWjVu5aRpcVKbVzSQAunb/JhV/ykqrkXb4aBssH9VeALiIiIiIiIpIEffLJJ9y5c4cWLVpw8OBBLly4wObNm2nfvj0hISGkSJGCvn370qdPH3x9fblw4QJHjhxh2rRp+Pr6Gl2+iIhNlc9Wnp5lewLQeX1n7gfdN7iiyClEN9ixI+eZMzYndvn/weEeFDZNo2b/cUa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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "import numpy as np\n", - "from scipy import integrate\n", - "from scipy.special import factorial\n", - "from scipy.linalg import solve\n", "import matplotlib.pyplot as plt\n", + "import numpy as np\n", "from scipy.integrate import quad\n", - "\n", - "\n", + "from scipy.special import factorial\n", "\n", "#######\n", "# fig 1, comparing the k space operators, k_E, k_B, k1 and the dispersion relation omega\n", "# fig 2, comparing the error in the phase velocity for 8, 12 and 16 coefficients\n", - "# in fig 3, Comparing the cancellation factor (indicates E B balance) for the yee, xu and new solver from Li 2020 \n", + "# in fig 3, Comparing the cancellation factor (indicates E B balance) for the yee, xu and new solver from Li 2020\n", "# 'A new field solver for modeling of relativistic particle-laser interactions using the particle-in-cell algorithm'\n", "#######\n", "\n", - "#function kernel_sine( x, arglst ) in fortran line 1235. Not sure about the use of v and u, looks related to a fourier\n", - "#expansion to approximate the operator. Basically copied the fortran code\n", - "def kernel_sine(x, args): \n", + "\n", + "# function kernel_sine( x, arglst ) in fortran line 1235. Not sure about the use of v and u, looks related to a fourier\n", + "# expansion to approximate the operator. Basically copied the fortran code\n", + "def kernel_sine(x, args):\n", " # args\n", - " u = (2.0 * args[0] - 1.0) *np.pi\n", - " v = (2.0 * args[1] - 1.0) *np.pi\n", - " return np.sin(u*x) * np.sin(v*x)\n", + " u = (2.0 * args[0] - 1.0) * np.pi\n", + " v = (2.0 * args[1] - 1.0) * np.pi\n", + " return np.sin(u * x) * np.sin(v * x)\n", + "\n", "\n", - "#function kernel_dual_e( x, arglst ) fortran line 1302\n", - "#paper equation 14\n", + "# function kernel_dual_e( x, arglst ) fortran line 1302\n", + "# paper equation 14\n", "def kernel_dual_e(x, args):\n", - " u = (2.0 * args[0] - 1.0) *np.pi\n", - " v = args[1] *np.pi\n", - " k_cons = np.sin(v*x) / v\n", - " omega = np.arcsin(v*k_cons) / v\n", - " return np.sin(u*x) * k_cons / np.cos(v*omega)\n", - "\n", - "#function kernel_dual_b( x, arglst ) fortran line 1321\n", - "#paper equation 15\n", + " u = (2.0 * args[0] - 1.0) * np.pi\n", + " v = args[1] * np.pi\n", + " k_cons = np.sin(v * x) / v\n", + " omega = np.arcsin(v * k_cons) / v\n", + " return np.sin(u * x) * k_cons / np.cos(v * omega)\n", + "\n", + "\n", + "# function kernel_dual_b( x, arglst ) fortran line 1321\n", + "# paper equation 15\n", "def kernel_dual_b(x, args):\n", - " u = (2.0 * args[0] - 1.0) *np.pi\n", + " u = (2.0 * args[0] - 1.0) * np.pi\n", " v = args[1] * np.pi\n", - " k_cons = np.sin(v*x) / v\n", - " omega = np.arcsin(v*k_cons) / v\n", + " k_cons = np.sin(v * x) / v\n", + " omega = np.arcsin(v * k_cons) / v\n", "\n", - " return np.sin(u*x) * k_cons * np.cos(v*omega)\n", + " return np.sin(u * x) * k_cons * np.cos(v * omega)\n", "\n", - "#function weight( x, w, n ) fortran line 1695\n", - "#weighting function from appendix b\n", + "\n", + "# function weight( x, w, n ) fortran line 1695\n", + "# weighting function from appendix b\n", "def weight(x, w, n):\n", - " return np.exp(-np.log(2)*(x/w)**n)\n", + " return np.exp(-np.log(2) * (x / w) ** n)\n", "\n", "\n", "def integral(fun, args, upper=0.5, lower=0.0, tol=1e-16, w=0.36, n=10):\n", @@ -119,161 +75,167 @@ " result, error = quad(integrand, lower, upper, args=(args, w, n), epsabs=1e-16)\n", " return result\n", "\n", + "\n", "# subroutine precond( A, b, n ) line 1622\n", - "#from fortran comment: precondition the linear equations Ax=b of dimension n to improve the condition number\n", + "# from fortran comment: precondition the linear equations Ax=b of dimension n to improve the condition number\n", "def precondition(A, b):\n", " d = 1.0 / np.max(np.abs(A), axis=1)\n", " A_scaled = A * d[:, np.newaxis]\n", " b_scaled = b * d\n", " return A_scaled, b_scaled\n", "\n", - "#subroutine gen_solver_coef( fun, arglst, ord, n_coef, coef, w, n ) implemented from fortran 1162 \n", - "#perform the integral from B.8 and B.9, build the A and b matrices,\n", + "\n", + "# subroutine gen_solver_coef( fun, arglst, ord, n_coef, coef, w, n ) implemented from fortran 1162\n", + "# perform the integral from B.8 and B.9, build the A and b matrices,\n", "def gen_solver_coef(kernel_func, args, ord, n_coef, w=0.35, n=10):\n", - " size = n_coef + ord//2\n", + " size = n_coef + ord // 2\n", " A = np.zeros((size, size))\n", " b = np.zeros(size)\n", - " \n", + "\n", " for i in range(n_coef):\n", " for j in range(n_coef):\n", - " lst = [i+1, j+1]\n", - " A[i,j] = (2/np.pi**2) * integral(kernel_sine, lst, w=w, n=n)\n", - " \n", - " for i in range(ord//2):\n", + " lst = [i + 1, j + 1]\n", + " A[i, j] = (2 / np.pi**2) * integral(kernel_sine, lst, w=w, n=n)\n", + "\n", + " for i in range(ord // 2):\n", " for j in range(n_coef):\n", - " val = (2*j+1)**(2*i+1) / factorial(2*i+1)\n", - " A[i+n_coef,j] = val\n", - " A[j,i+n_coef] = val\n", - " \n", + " val = (2 * j + 1) ** (2 * i + 1) / factorial(2 * i + 1)\n", + " A[i + n_coef, j] = val\n", + " A[j, i + n_coef] = val\n", + "\n", " for i in range(n_coef):\n", - " lst = [i+1] + list(args)\n", - " b[i] = (2/np.pi) * integral(kernel_func, lst, w=w, n=n)\n", + " lst = [i + 1] + list(args)\n", + " b[i] = (2 / np.pi) * integral(kernel_func, lst, w=w, n=n)\n", " b[n_coef] = 1.0\n", - " \n", + "\n", " # Print A and b for debugging\n", - " #print(\"Matrix A (before preconditioning):\\n\", A)\n", - " #print(\"Vector b (before preconditioning):\\n\", b)\n", - " \n", + " # print(\"Matrix A (before preconditioning):\\n\", A)\n", + " # print(\"Vector b (before preconditioning):\\n\", b)\n", + "\n", " A_scaled, b_scaled = precondition(A, b)\n", - " \n", + "\n", " # With this higher precision approach:\n", - " from scipy.linalg import solve_triangular, qr\n", - " q, r = qr(A_scaled, mode='economic')\n", + " from scipy.linalg import qr, solve_triangular\n", + "\n", + " q, r = qr(A_scaled, mode=\"economic\")\n", " y = np.dot(q.T, b_scaled)\n", " x = solve_triangular(r, y)\n", - " \n", + "\n", " return x[:n_coef]\n", "\n", + "\n", "# takes the calculated stencil coefficients and does equation 6 from the paper\n", "def calculate_operators(k1, dx1, dt, coef_e, coef_b):\n", " \"\"\"Calculate kE1 and kB1 operators\"\"\"\n", " kE1 = np.zeros_like(k1)\n", " kB1 = np.zeros_like(k1)\n", - " \n", + "\n", " for j in range(len(coef_e)):\n", - " kE1 += coef_e[j] * np.sin((2*j+1)*k1*dx1/2)/(dx1/2)\n", - " kB1 += coef_b[j] * np.sin((2*j+1)*k1*dx1/2)/(dx1/2)\n", - " \n", + " kE1 += coef_e[j] * np.sin((2 * j + 1) * k1 * dx1 / 2) / (dx1 / 2)\n", + " kB1 += coef_b[j] * np.sin((2 * j + 1) * k1 * dx1 / 2) / (dx1 / 2)\n", + "\n", " return kE1, kB1\n", "\n", "\n", "def calculate_phase_velocity(kE1, kB1, k1, dt):\n", " \"\"\"Calculate phase velocity using equation 5 from the paper\"\"\"\n", " # βφ ≡ ω/k1 = (2/k1Δt) arcsin((Δt/2)√[k]B1[k]E1)\n", - " return (2/(k1*dt)) * np.arcsin((dt/2) * np.sqrt(kE1 * kB1))\n", + " return (2 / (k1 * dt)) * np.arcsin((dt / 2) * np.sqrt(kE1 * kB1))\n", + "\n", + "\n", "# cancellation factor defined in figure 2 description. Ideally F = 1\n", "def calculate_cancellation_factor(kE1, kB1, k1, dt):\n", " \"\"\"Calculate cancellation factor F with proper normalization\"\"\"\n", - " k1t = np.sin(k1*dt/2)/(dt/2)\n", - " \n", - " kE1_scaled = kE1/k1t\n", - " kB1_scaled = kB1/k1t\n", - " \n", + " k1t = np.sin(k1 * dt / 2) / (dt / 2)\n", + "\n", + " kE1_scaled = kE1 / k1t\n", + " kB1_scaled = kB1 / k1t\n", + "\n", " omega = k1 * np.sqrt(kE1_scaled * kB1_scaled)\n", - " \n", - " F = np.sqrt(kE1_scaled/kB1_scaled) * np.cos(omega*dt/2)\n", - " \n", + "\n", + " F = np.sqrt(kE1_scaled / kB1_scaled) * np.cos(omega * dt / 2)\n", + "\n", " return F\n", "\n", - "#used claude to write this part to make figure 2 from the paper\n", + "\n", + "# used claude to write this part to make figure 2 from the paper\n", "def test_operators():\n", " \"\"\"test and plot results\"\"\"\n", " # Parameters matching paper\n", - " \n", + "\n", " k0 = 1.0\n", - " dx1 = 0.2/k0\n", - " dt = 0.5*dx1\n", - " kg1 = 2*np.pi/dx1\n", - " \n", - " \n", - " k1 = np.linspace(1e-10, 0.5*kg1, 2000)\n", + " dx1 = 0.2 / k0\n", + " dt = 0.5 * dx1\n", + " kg1 = 2 * np.pi / dx1\n", + "\n", + " k1 = np.linspace(1e-10, 0.5 * kg1, 2000)\n", "\n", " # Create figure\n", " fig, axs = plt.subplots(1, 3, figsize=(15, 5))\n", - " \n", + "\n", " # Plot operators for different stencil sizes\n", - " for M, color in zip([8, 12, 16], ['gold', 'red', 'blue']):\n", - " \n", - " coef_e = gen_solver_coef(kernel_dual_e, [dt/dx1], 2, M)\n", - " coef_b = gen_solver_coef(kernel_dual_b, [dt/dx1], 2, M)\n", + " for M, color in zip([8, 12, 16], [\"gold\", \"red\", \"blue\"]):\n", + " coef_e = gen_solver_coef(kernel_dual_e, [dt / dx1], 2, M)\n", + " coef_b = gen_solver_coef(kernel_dual_b, [dt / dx1], 2, M)\n", " print(f\"E Stencil coefficients for M={M}:\", coef_e)\n", " print(f\"B Stencil coefficients for M={M}:\", coef_b)\n", " print(coef_b * coef_e)\n", "\n", " # Calculate operators\n", " kE1, kB1 = calculate_operators(k1, dx1, dt, coef_e, coef_b)\n", - " \n", + "\n", " # Plot operators (only for M=16)\n", " if M == 16:\n", - " omega_t = (2/dt) * np.arcsin((dt/2) * np.sqrt(kE1 * kB1))\n", - " axs[0].plot(k1/kg1, kE1/kg1, 'b-', label='[k]E1/kg1')\n", - " axs[0].plot(k1/kg1, kB1/kg1, 'r-', label='[k]B1/kg1')\n", - " axs[0].plot(k1/kg1, omega_t/kg1, 'y-', label='ω/kg1')\n", - " axs[0].plot(k1/kg1, k1/kg1, 'k--', label='k1/kg1')\n", - " \n", + " omega_t = (2 / dt) * np.arcsin((dt / 2) * np.sqrt(kE1 * kB1))\n", + " axs[0].plot(k1 / kg1, kE1 / kg1, \"b-\", label=\"[k]E1/kg1\")\n", + " axs[0].plot(k1 / kg1, kB1 / kg1, \"r-\", label=\"[k]B1/kg1\")\n", + " axs[0].plot(k1 / kg1, omega_t / kg1, \"y-\", label=\"ω/kg1\")\n", + " axs[0].plot(k1 / kg1, k1 / kg1, \"k--\", label=\"k1/kg1\")\n", + "\n", " # Phase velocity error\n", " vph = calculate_phase_velocity(kE1, kB1, k1, dt)\n", "\n", - " axs[1].semilogy(k1/kg1, np.abs(vph - 1), color=color, label=f'{M} coef.')\n", - " \n", + " axs[1].semilogy(k1 / kg1, np.abs(vph - 1), color=color, label=f\"{M} coef.\")\n", + "\n", " # Cancellation factor\n", " F = calculate_cancellation_factor(kE1, kB1, k1, dt)\n", - " axs[2].plot(k1/kg1, F, color=color, label=f'{M} coef.')\n", - " \n", + " axs[2].plot(k1 / kg1, F, color=color, label=f\"{M} coef.\")\n", + "\n", " # Add Yee solver comparison\n", - " k1_yee = np.sin(k1*dx1/2)/(dx1/2)\n", + " k1_yee = np.sin(k1 * dx1 / 2) / (dx1 / 2)\n", " F_yee = calculate_cancellation_factor(k1_yee, k1_yee, k1, dt)\n", - " axs[2].plot(k1/kg1, F_yee, 'purple', label='Yee')\n", - " \n", + " axs[2].plot(k1 / kg1, F_yee, \"purple\", label=\"Yee\")\n", + "\n", " # Add Xu solver comparison\n", - " k1_xu = np.sin(k1*dt/2)/(dt/2)\n", + " k1_xu = np.sin(k1 * dt / 2) / (dt / 2)\n", " F_xu = calculate_cancellation_factor(k1_xu, k1_xu, k1, dt)\n", - " axs[2].plot(k1/kg1, F_xu, 'green', label='Xu')\n", - " \n", + " axs[2].plot(k1 / kg1, F_xu, \"green\", label=\"Xu\")\n", + "\n", " # Configure plots\n", - " titles = ['(a) Operators', '(b) Phase velocity error', '(c) Cancellation factor']\n", + " titles = [\"(a) Operators\", \"(b) Phase velocity error\", \"(c) Cancellation factor\"]\n", " for ax, title in zip(axs, titles):\n", " ax.set_title(title)\n", - " ax.set_xlabel('k1/kg1')\n", - " ax.grid(True, which='both', alpha=0.3)\n", + " ax.set_xlabel(\"k1/kg1\")\n", + " ax.grid(True, which=\"both\", alpha=0.3)\n", " ax.set_xlim(0, 0.5)\n", - " \n", - " axs[0].set_ylabel('Normalized magnitude')\n", + "\n", + " axs[0].set_ylabel(\"Normalized magnitude\")\n", " axs[0].set_ylim(0, 0.5)\n", - " \n", - " axs[1].set_ylabel('|βφ - 1|')\n", - " axs[1].set_yscale('log')\n", + "\n", + " axs[1].set_ylabel(\"|βφ - 1|\")\n", + " axs[1].set_yscale(\"log\")\n", " axs[1].set_ylim(1e-15, 1)\n", - " \n", - " axs[2].set_ylabel('Factor F')\n", + "\n", + " axs[2].set_ylabel(\"Factor F\")\n", " axs[2].set_ylim(0.7, 1.05)\n", - " \n", + "\n", " for ax in axs:\n", - " ax.legend(loc='best')\n", - " \n", + " ax.legend(loc=\"best\")\n", + "\n", " plt.tight_layout()\n", " return fig, axs\n", "\n", + "\n", "fig, axs = test_operators()\n", "plt.show()" ]