diff --git a/docs/source/examples/MultiTaskTest.ipynb b/docs/source/examples/MultiTaskTest.ipynb index db58a8d..bf545d8 100644 --- a/docs/source/examples/MultiTaskTest.ipynb +++ b/docs/source/examples/MultiTaskTest.ipynb @@ -17,7 +17,7 @@ "outputs": [], "source": [ "##first install the newest version of fvgp\n", - "#!pip install fvgp==4.0.0" + "#!pip install fvgp==4.0.5" ] }, { @@ -133,7 +133,7 @@ "source": [ "## A simple kernel definition\n", "It is vital in the multi-task case to think hard about kernel design. The kernel is now a function\n", - "over $\\mathcal{X} \\times \\mathcal{X} \\times T \\times T$, where $\\mathcal{X}$ is the input and $T$ is the output space. Print the input into kernel, it will have the dimensionality of this cartesian product space. \n", + "over X x X x T x T, where X is the input and T is the output space. Print the input into kernel, it will have the dimensionality of this cartesian product space. \n", "The default kernel in fvgp is a deep kernel, which can be good, but there is no guarantee.\n", "To use the default kernel, pytorch has to be installed manually (pip install torch)." ] @@ -182,7 +182,7 @@ "\n", "#my_gp2.update_gp_data(x_data3,y_data3)\n", "print(\"Global Training in progress\")\n", - "my_gp2.train(hps_bounds, max_iter = 200)" + "my_gp2.train(hps_bounds, max_iter = 20)" ] }, { @@ -272,6 +272,14 @@ "fig.show()\n", "\n" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "80723910", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/docs/source/examples/NonEuclideanInputSpaces.ipynb b/docs/source/examples/NonEuclideanInputSpaces.ipynb index d066b56..e700de8 100644 --- a/docs/source/examples/NonEuclideanInputSpaces.ipynb +++ b/docs/source/examples/NonEuclideanInputSpaces.ipynb @@ -8,7 +8,7 @@ "# GPs on Non-Euclidean Input Spaces\n", "GPs on non-euclidean input spaces have become more and more relevant in recent years. fvgp can be used for that purpose as long as a correct kernel is defined. Of course if mean functions and noise functions are also provided, they have to operate on these non-Euclidean spaces. \n", "\n", - "In this example, we run a small GP on words. It's a proof of concept, the result are not super relevant" + "In this example, we run a small GP on words. It's a proof of concept, the result are not super relevant." ] }, { @@ -19,7 +19,7 @@ "outputs": [], "source": [ "#install the newest version of fvgp\n", - "#!pip install fvgp==4.0.0" + "#!pip install fvgp==4.0.5" ] }, { diff --git a/docs/source/examples/SingleTaskTest.ipynb b/docs/source/examples/SingleTaskTest.ipynb index bd6dd1f..76c27b2 100644 --- a/docs/source/examples/SingleTaskTest.ipynb +++ b/docs/source/examples/SingleTaskTest.ipynb @@ -24,7 +24,7 @@ "outputs": [], "source": [ "##first install the newest version of fvgp\n", - "#!pip install fvgp==4.0.0" + "#!pip install fvgp==4.0.5" ] }, { diff --git a/docs/source/examples/gp2ScaleTest.ipynb b/docs/source/examples/gp2ScaleTest.ipynb index 05b9b15..f145548 100644 --- a/docs/source/examples/gp2ScaleTest.ipynb +++ b/docs/source/examples/gp2ScaleTest.ipynb @@ -13,13 +13,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "c8a50af7", "metadata": {}, "outputs": [], "source": [ "##first install the newest version of fvgp\n", - "#!pip install fvgp==4.0.0" + "#!pip install fvgp==4.0.5" ] }, { @@ -32,7 +32,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "8a20595d", "metadata": {}, "outputs": [], @@ -63,7 +63,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "ee0b9649", "metadata": {}, "outputs": [], @@ -84,7 +84,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "0805781d", "metadata": { "scrolled": false @@ -103,10 +103,38 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "de466547", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[1.9673543 0.01571433]\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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nxVO2y2X7bhzvQFqkyq3tzjvv7I9pnZKNGze6Xs+aGIfZPmWSMQ1OX7z0w0EAwLRp02A2m6HRaDBhwgRERkaioaHB7Wn7qlWrAABvrc1Di+glOd/iYc2u1y0tLdx+TERERAPK6XSisLAQW7duRW1tLYKDgxEaGgq1Wo36+nrs3bsXP//8MzZu3Ii8vDxUVVWdMXmoiYiI6OzEQOEg4uMhYOykWV0WNnn9sgi3wiZHjhyBzWbrvwn2wIcffuh6/fhcreyYlwsj0WqywN/fHwqFAi0tLYiKikJwcDAmTpwIrVaLpqYm13iNRgO1Wg2bzY6N+ijJ+UZ61GNMfITr+J577unFT0RERETUfUajETt37sTevXshiiJCQ0OhUqkgCAI0Gg2Cg4MRFhYGX19fmM1mHD58GL/++is2bNiAnTt3ori4WJKKhYiIiKivMVA4yKSEq/F06QTZPHyTAwz4/awwt7YXXnihv6bWI5mZmQCAqWNiMM+vRNLf7PTGC98fAgCMHTsWVqsVarUacXFxAACtVovx48cDgNtNclhY++f/7qgdci6eEul6fXywkoiIiKg/iKKI8vJybNmyBWVlZfD394e/vz8EQZCMFQQBarUa/v7+CA8PR1BQexqVsrIy7Nq1C1u2bIFOp+vvj0BERERDGAOFg9C8cdF42ThXtu/p8wQEeitdxy+//HJ/TavbbDYbamtrAQCPLwiUHbOqJAoGY3sA8KGHHoLBYMCwYcNcN8gAMHz4cCQmJrpVT05JSQEAfLejGHZR+sf3gliL67XZbOb2YyIiIuo3FosFe/fuxc6dO2E2mxEWFga1Wt3t9yuVSvj6+iI0NBRhYWEwGAzYsWMHKisr+3DWRERERJ0YKByEpqel4G9fHUSJM0zSF6Q049krRruOKysrB10C7I5VjqnJw7HEv1jS3yJ64V/fHQUAeHt7Q61WQ6lUIj4+3u1puyAIGD16NIYPH47GxkaIoog//OEPAICG5hbsMEdLzj1FU4mwQD/X8X333dern42IiIhITl1dHbZu3Yr8/Hz4+PggKChIdhVhdwmCgJCQENhsNuzevRvHjh1jpWQiIiLqcwwUDkJKpRLGssN44FCSbP//RZVj6pjOHH1r1qzpr6l1yzPPPAMAeGxBqGz/m2WxaNS3AACuvfZa6PV6hIWFubYVH0+lUrnyFTY2NkKj0SA8vL0y9A8l0if0SkHERTPiXcesfkxERER9yW6349ChQ9i2bRuampoQGhoKjUbTK+cWBMEVcNy7dy8OHz4Mp9PZK+cmIiIiksNA4SAVHh6Oz7/NxDrzGEmfQhBxf0ZnEG4wrZqz2WxobGxE7LBAXBgoXU1oEtV45vt81/GSJUsAACNGjOjyqbufnx8mTJgAQRDQ2tqK9957DwDw1c4K2fFLEzv/WBsMBm4/JiIioj5hMBiwbds27N+/HyqVCiEhIVAqlSd/Yw/5+/vDy8sLBw4cwL59+2C3y+dqJiIiIjpdDBQOUrfddhtEuw13flMnW9gkI7AGwv9qIBcWFvb39LrUse34wikxUAjS7THvVsajrkEPAPDy8oLFYkFISAgiIiIkY48XGRmJ5ORkGI1GqFQq+Pr6oqCsFofbwiVjM/wr4Knu/Jrdddddp/ORiIiIiCR0Oh22b9+O6upqBAcHw9fX97S2Gp+Mj48PtFot8vPzsWfPHlit1j67FhEREQ1dqoGeAMmbPn06ACA//xg+rJmCm4YddesPUrRi6tho7DxYBlEUYTQa4evrOxBTdfPqq68CAObHy98oP7u2c5VhRkYGHA4HRowYcdKn74IgIDk5GU1NTaioqMC0adOwceNGrKn0x+i4Wrex3oINi6Yl4JstRwAAn3/+Od58883T+VhERERELhUVFcjNzYXZbEZoaCgUiq6fvdfW1uKmm26CwWA46XmVSiX+9Kc/Ye7cubL3Rl5eXlAoFCgpKYHNZkNaWhp8fHxO67P0F1EU0dbWBqvV6vZLq9UiJCRkoKdHRERE/8NA4SClVCoxY8YMbN++HWsPteCmYdIx548Pwc6DZQCAq666Ct99910/z9Kdw+FAeXk5lAoFZmlrJP0HbREoq+rcdrxy5UoEBAQgMjKyW+fvyFdoNBoxY8YMbNy4EV/nNuC+OOnYZWO98c2W9tfNzc1wOBx9shWIiIiIhg5RFFFUVIT9+/dDFEWEhITIriK02WxYvXo1Pvzwwx6d3+Fw4Omnn8bTTz+NhIQEvPjii5IHwWq1GiEhIaiursb27dsxefJkBAQEnM7H6lXNzc0wGo2uQKDJZHL9amtrg8PhgN1uh9PphCiK8PPzwznnnAN/f/+BnjoRERGBgcJBbfny5di+fTsyc0pgy9BALbhXN86IasOT/3s9GAqarF27FgAwY3wMAhSNkv6NtZ03gGFhYVAoFEhISICHh3RrdVf8/Pwwfvx4tLS0F0PZtq8EtRcOR7jC/Sn9+SF1ECBARPv2582bN2Pu3Lk9/kxEREREQHsQ7+DBg8jPz4darYZWq5Ud969//Qs//vijW9uiaSNx7zneCFNbcdTojS1lTmw6UIuDx6QPVjsUFRVh6dKliIuLc+Vn7qBSqRAaGgqdTocdO3YgLS0NoaHyReT6U3V1Nfbs2eOWH1oQBKhUKiiVSqhUKqjVaqhUKtcqzLq6OuTm5mLGjBlQq6WF6oiIiKh/MVA4iKWkpAAAjCYLss0JmOFd7tY/1bsSGi81zBYbHA7HgG8/fvzxxwEAi8cHA5AGCn863BnMe+mll6DVahEVFSUZdzKRkZEYM2YMQkJCoNPp8JMuHNeGuQcKI5QGTB8fg+37S9uv/dNPDBQSERHRKbHZbNi3bx+OHTsGPz8/eHt7S8YYjUYsXbrUrS3I3wevXJ2EK0OLXG0TPIHLggFMAnTOSOwwhGJLhQJZh+qRfaQSTtE9x3NJSQnS09OxZs0at2rKCoXCFSzcuXMnUlJSTum+qrc0NjZi7969sNlsCA0N7Xa+xuDgYNTU1ODQoUOYOHFin+Z5JCIiopNjMZNBTKlUYvjw4QCAjVUaSb+XYEdGarzr+Iorrui3uck5ePAgAGBupLTKsEX0QFZOe37CjifI8fHx8PT07PF1OvIV/ulPfwIAfHdQvqrxxamd+W5eeumlHl+HiIiIyGQyYdeuXSgqKkJAQIBskPD3v/+9JEh4RcYYHL4zwC1I+FshCiMuCCjGP8cVYdcKA5oeC8WGeyfgiStSMTslDh6qzrQpixcvdt37dBAEASEhIbDZbNizZw+OHTsGUZQWk+trRqMR2dnZaG1tRVBQUI+CfSqVClqtFkVFRSgrK+vDWRIREVF3MFA4yF1wwQUAgJ8ONMj2LxzVuYJw8+bN/TElWTabDTabDQF+GqR6VUn6t7UOh8VqAwBoNBr4+PggJibmlK+nUqlw0003AQDW7iqCSZRuVVkS2bnK0GazuW2DISIiIjqZ5uZmbNu2DZWVlQgJCZF9wDlv3jwUFha6joeF+uO7u1LwyawKhClaenQ9rWDBPL8S/Dm5ED8va0Txg8NxZcYYV//u3bslOyQEQXAF5/bu3YujR4/2a7DQarUiOzsbDQ0NCA4OPqUVgRqNBgqFAgcOHEBzc3PvT5KIiIi6jYHCQe6SSy4BAGzfXwq9U/oEOyO88wa0tbUVDodDMqY/dKzYW5gWB5XglPRnlnfmIYyMjERsbKzsE/me8Pf3h1qthtlixWaDdKvNGHUtEqI6VxXee++9p3W9gWI0Ggfs+0pERDRU1dbWYvv27WhoaEBoaChUKmnGnrlz57r9H/37ReNx6BYNlgYc65U5DFc24+NZFbjn4hRXm9PpRHp6umRsx33RgQMHcOjQITid0vux3ma327F3715UV1cjJCTkhNWfTyYgIACtra3Izc2FzWbrxVkSERFRTzBQOMh1JMt2Op3YYoiQ9I9V1yAipDOZ9vr16/tzei5vvfUWAGBhsnzwb01urev1zJkzERsb2yvXXb58OQDgu8Iu+qdHu15/+umnvXLN/lRXV4dffvkFhw4dGpCtREREREONKIooLS3Fzp070dra6irA9lvp6emuYFxcZAgy752AN6eWIkBh6vLcVvHU0oM/P+EYHrx0klvb/PnzJeP8/Pyg0Whw8OBB5OXl9emDRqfTif3796O0tBRBQUGygdSe6FgZWVtbi4MHD/K+h4iIaIAwUHgGuPzyywEAG0rl+xemdgbdHn744f6YkhuHw4H8/HwAQEaIdIt0jcMf+/IrXMe33HJLl5UCe+qNN94AAHy9/RiconSrywVxba7Xzc3NZ9QT6qamJmRnZ8NgMKCgoADV1dUDPSUiIqKzmiiKyM/PR3Z2NpxOZ5dbaTtW9AkQcPdFKdh/o4C5fiUnPPeGlngkv61A+CsCrtgSg1WVScizRsIhc/8i5+mxRXjiilTXsd1ux/nnny8Z5+PjAz8/Pxw9ehR79+5FW1ubZMzp6vg6FRYWQqvV9lq14uPzFZaWdnHjS0RERH2KgcIzwKWXXgoAWJdbI9s/f2TnzdmRI0f6ZU7H27hxIwAgOTYMsSppteNNjWGu1yqVCklJSb12bT8/P6jVatQ1GLDbMlzSP8O7AoFaH9fxCy+80GvX7kstLS3YvXs3WlpaEB4eDlEUsX//frS2tg701IiIiM5Koiji6NGj2L9/Pzw8PBAQEHDCIOHo+Aj8ev8YvDDxGHwFa5fnbXT64PqdcVjw/D6UVulQ16DHfzcdwB/e3oOJ/ziCoBfsWLZxOJ4vTcIuczRsorLLc/05uRBPXd0ZLLRarcjIyJCM02g0CAgIQFFREbKzs2G1dj2/U1FaWoqDBw9Co9G4VWLuDRqNBiqVCgcOHEBTU1OvnpuIiIhOjoHCM4BarYZKpcLRkhqUOYIk/elB9a7XFoul3/PZvf/++wCARZMiZfs3FHU+yY6OjkZgYGCvXn/8+PEAgB/LpDeqKsGJZTNGuI4/+OCDXr12XzCbzdizZw+ampoQEhICQRAQGBiI5ubmPt9GRERENBR1rJA7ePAgvLy84OfnJzuuI0h44TnJ2PM7O2Z4l5/wvN80JWDMKhPe+ymvyzGGllZ8t/Uw7nt/D6Y9cxABz5rw5/yuH6o+PLIQz17TGSwURVE2Z6GnpycCAwNRUlKC3bt391pRt5qaGuzbtw9KpRK+vr4nfwPai8q98cYbyMjIQHp6utuvSy65BPX19W7j/f39YTKZkJub2+tBTiIiIjoxBgrPEGPHjgUAZDUES/oilc0Ym9CZv7C/8xRmZmYCABbEyeeSWbOnxPV65cqVp1QN70Q68hR+uUtabRkALkzuzJlTUlIiO2awsNlsyM7ORl1dnVtScIVCgcDAQJSXl7tVViQiIqLTI4oiCgoKcODAAajV6i6DXx3BuKXnJOO/c+vhLXSdzqTGocXlv0Tj4pf2oland7W/++67yMrKkvxat26da4zZbMWTn+zB/QdHdnn+P8YX4qXr02Tndzy1Wo2QkBBUVlZi586dMBqNXZ6zO5qampCTk4O2tjb4+/ufdHxtbS3mzZuHhQsX4tNPP5XNO9jU1IQVK1YgPT0d9913H4xGIwRBQHBwMPMVEhERDQAGCs8QV155JQBgQ4H8U9VFE4e5Xj/77LP9MiegPT9hfX09VColztVKc+jlWYehrsHgOn7kkUd6fQ733XcfAODQsWoU2UMl/XMDquDxvwTbZrN50K7I66gcWFlZieDgYCiV7luP1Go1NBoNjhw5InnyTkRERD0niiIKCwuxf/9+qNXqk64kXDIzCZ/NrYeXYO/ynB/VJWLMS034LOugq+2uu+5CVlYW4uPjZd+jVquRlZWFjz/+2NX2ry9ycGduQpfXuSO6AK//3j1YKFfgRKVSISQkBLW1tdi5cyf0er1kTHe0trZiz549MBqNXeZu7GA2m5Geno4rrriiy/uuYaFaLJgyEpGhnQHHnJwcLF26FDfeeCOUSiUCAgJw7NixQf+gl4iI6GzCQOEZYtKk9kp367LLZIt2ZMQ6Xa/37NnTb/Nau3YtAGD2hFj4CRZJf2ZN5w13ZGQkPD09e30OarUaw4a1B0rXVAdI+rWCGfMnd24/XrNmTa/P4XR1VA4sKSlBYGBgl5UDfX19YbPZkJeXB4tF+vUmIiKi7hFFEUVFRcjLy+tWkHDR9CR8Ma+hyyBhmSMIi9dH4HerstFk6MwpnJmZiYsuuqhbcxo2bBiysrJcxy9/uxe3Zo+QvfcDgJsjC/DezakQ0N5vt9tlg4VKpRKhoaHQ6XTYuXMnGhulOaVPxGq1Ijs7G42Nja60KF256667sHjxYtk+ra8GNy+egF/+OA4VtwpYt7gOpbcKePAy94rORUVFSE9Ph5eXF1QqFQ4ePNjjORMREdGpYaDwDGAymdDY2AiVSgVdkwH7bcMkY871q4ZK1b4CraWlpd9WzT366KMAgPPHyecd/OlQ51Prt99+u8/m8corrwAAvt4n/5R82fjOm/+VK1f22TxOhSiKOHz4MAoKCuDv73/CyoGCICAoKAg6nY5bcYiIiE6RKIo4duwY8vLy4OHhcdIg4fnTEvHVggZ4CfIVhD/VJWLs8zVYuz3f1ebh4YGsrCzJDoHuyMrKcqUfef2HXNy4K7bL6sjXRRTioz+kuMbb7XYsWLBAMk6hUCA0NBR6vR47d+7E4cOHXZWLO1btlZWVoaKiAlVVVaipqUFtbS3q6+uRm5uLqqoqBAcHu67zWx2rCPPy3PMxqpQKXHRuMr66IwW193rj9SklmOVTBoXQfg+jEpx4ekwR7liWIjlneno68xUSERH1M0EcxJEGg8EAf39/6PV6aLXagZ5Onzh69Cj27duHsLAwSZ/T6URjYyMUCgUSEhKwaNEiVFdX4/nrJuOe2HzJ+PTvg7E5pxhA+6q5RYsW9fn8FQoFRFFE9gOjkOrlniOwVfRE0D+aYLO1P3m32+2ndLPcHXa7HR4eHlAoFKh/JBxBCvfqwBWOQET/rdR1bLVaTxiQ6y8dW5727dsHjUYDHx+fk78J7UVrjEYjJk+ejLi4uL6dJBER0VlEFEUUFxcjNzcXKpWqy3vMjiDhgimJ+GZREzRd5CT8qC4R16zKgYjOW+q0tDT861//Ou25ZmRkuB4KXj1vPN6fWQ6V4JQd+0VDAq54bR8czvb+hIQE2Ye0oiiiqakJdnvX26c7CIIAQRBgt9sRFBTU5b3TQw89hB07dri1zRwfg2unh2B5RA2CFSfPjegQBVzxcyS++PmwpC8zMxP19fVITExEampqr+e7JiIiOtv1JL7GFYWDlMlkQl1dHQICAjBz5kxMmDABF1xwAQBg3WGD7HsWju2siPz888/3+RxtNhtEUURwgC9SPKX5CX81RrqChIIg9FmQEGjPv+Ph4QGn04l1jdIVl1HKJqSNjnYdP/fcc302l54oKyvD/v374enp2e0gIQDXVpwDBw6ccq4hIiKioeb4IKFSqTxpkHDelJEnDBKurpcGCWfOnNkrQUIA2LRpkytty+rM/bh6y3DYRPn7qUuDi/Dl7ROg9mhPX1JUVISHHnpIMq5jd0JYWNgJf4WGhiI4OBiBgYEICwvrMkh48cUXu4KEI6NC8LerJ6Hw4Xj8ekkzboos7FaQEACUgogPz6vHuRPjJH3z5s1DQEAASktLmaeZiIiojzFQOMg4nU7odDpYLBaMGjUK5557LiIiIiAIAv79738DALL2FsMsSm/WMoaZXa9/u+2jL3Rs9z1/cpxr+8jxMks7b2S7qiDYm6ZNmwYA+O6w/LaUS9I6V21+8MEHfT6fk6mursa+ffugUCi63PJ0Iv7+/mhtbcW+ffvQ1ia/FYqIiIg6lZSUYN++fVAqlV1W7e0IEs6dnIBvFzV3GST8uD4Rv1u11y1I+Nhjj+Gpp57q1Tn/9NNPCA8PBwB8lnUQV2yOgEX0kB27LPAYNt+djGD/9oePO3bswKuvvnpK1xUEAQqFAkqlssvtxvPnz0dzczN8NZ748JZJOHp9Gx4ZWYQEj4ZTuqZGsOHbC60YHR8h6Vu0aBHsdjtKSkqYeoWIiKgPMVA4iJjNZtTX10Or1WL69OmYOHEivLy8XP0ajQZeXl6w2dqwvTVS8v5UrypofTUAgLq6Oths8je2veXnn38GACwYKf+E+ce9nasMV6xY0adzAYCHH34YAPDDjiJYRGkxkCVRnduRi4uLB/QmU6fTIScnB21tbV3+oHIygiAgODgY1dXVOHLkCG+aiYiITqCkpAS5ublQKBQnDRKmpybg28UGeHcRJPxUl4jfvb4Xoti5DXjdunXIyMjo/YkD+PTTT5GQ0F4B+etfDuPSzJAug4UzvMux87ZwJMe2PyD94osvsGnTpl6dj81mQ3p6Oux2OyaMHIace6Lwu/Ai2QfHXSm1B8m2BylasfYqL0SESL9Ht912G6qqqribgoiIqA8xUDgIiKKIhoYGmEwmJCYmYvbs2YiMjJTNvzJiRHv13k0V0ptDleDEgrQ413HHCsS+smHDBgDA3BCdpK/CEYhDxzoDhS+//HKfzgWAK3G30WTBFmO0pH+iZxVihrXflNpsNtTW1vb5nOS0tLQgOzsbJpMJQUFBku+z2WzGU089hblz5yI9Pd3t18KFC/HAAw/AaGzfxqNSqeDr64uCggJUV0u3fxMREQ11DocDJSUl2Lt3LwRBOGmQcE5qPL67wAAfQX6HwmcNI3H1qr1wOjuDhE8++eRJcx9bLBbU1dWhtrYWjY2NMBqNrjQu3fH222+7tkr/uO0olv0UBJPMDhMASPDQYds1SsxJjQcA/PWvf+21YOFrr72GhQsXAgB+f/447LiqDYke3dsOXOkIxAtlyZj0qRZxT5Xgvdok2XGxqkb8dGMEfL293Np1Oh3efPNNlJWVnd6HICIioi4xUDgIOBwO+Pn5Yfr06Zg0aZLbKsLfSkpqv6H6Ka9Otn9+krfr9VdffdW7Ez2O0WiE2WzG2IQIDFc2S/o3NYS4XgcEBECj0fTZXDoolUpXAZfvi+STXF88Lcb1+q677urzOf2W0+nEgQMH0NTUhJCQELcgodlsxmWXXYbFixcjMzPT7QeQDjabDbt27cLSpUtx6aWXwmazwcfHB6IoYv/+/WhtbZW8h4iIaChpa2uDTqdDUVERdu3ahfXr12PPnj0QBAEBAQGy7+kIEs5Kicd3F7TCt4sg4ReNI3Hla7lu/0c/9NBDmD17dpfzsdvt0Ol0aG1tRXx8PMaOHYvQ0FAIgoDW1lbU19ejtrYWOp0OBoMBZrMZDodD9lzffvutaxvw+l0FuOAHf7SI8veNQYpW/HSBHtcuGA+gPVh4qtuQOzzwwAP4/PPPofH0wH9unYQ3p5V1uTW7g0HU4KP6JCz4KQLRT5Xj3vd2I/doBQDgxjdzsNYwQvZ9Ez2r8c0tSVAp3X9cWbt2LQoLC2EymU7rsxAREZE8Vj0eYNXV1a4qbt0JphmNRvj5+UGAgNrHIhGqaHHrL2wLReLfiwC0b1Xuq5uoCy+8EN9//z3uXz4Jz4wrkvSv/DUGqzMPAACuvvpqfPTRR30yj9/asGEDFixYgKjwQJTfIr3J3miMw7zn2vM3+vj4oLGxsV+rH5eUlGD37t3w9/d3u+7DDz+M7du3u429dPYoPHVOG/yVFvxQG4b7Pj0CfYv5t6fEJZdcgttuuw319fWIiYnB1KlT+7RwDBER0WBisVig1+uh1+uh0+nQ2NgIq9UKu90OhUIBLy8veHl5wcNDfquu+0rCVvgJFtlxXzWNxIpXcl1VhYH2B7hvvPGG7HhRFGEwGGCxWBAWFoZRo0a58k4D7QHE1tZWGI1GGI1G6PV6NDU1wWKxuFYaqlQqBAYGSnYfzJ8/31W1eFJSFL5foZB9cNvhrwWJePzjbACnXpF52bJlMBgMGBMfgc+v8MMYddc7M9pEJTYZY/Gf/U58tfUozObOwKufnx8+/vhjNDU14ZprroG3xhM/35mAyV4VsudaXTcSK1fluLUlJSXh+++/dz1AJyIiohPrSXyNgcIzkEKhgCiK+PyOVFwaVCjpj3tThdLqRgCA1Wrtk0BYaGgodDod1t0zEQu0xW59DlFA+EsONDS3b49dt26da1twX3M4HFCp2vMT5jwwCpO8qtz6raIKoc+b0WJsD7gVFBRg5MiR/TI3o9GIX375BVarFYGBga72q6++GlVV7vO8a9kEvJhS4taWY4nEeS8Vw2iWrnIIDAzEp59+iubmZqSkpPDGmYiIzloOhwMNDQ1oaGhAfX099Ho9LBYLnE4nlEqlKzCoVCpl07gcryNI+OBlk/CX0SXwEORX8n3TlIBLX9nnFiSMjIzE6tWrZcebzWYYDAb4+voiKSkJcXFxXQYqjyeKIkwmE1pbW2EwGHD06FGYzWYEBwdLPkvH3AFgeFgAfrg+AimeVb89pcsnupG49o08tP0vwJiZmdmtB4tGoxFLly4FAFy7YCxemV7X5YpLAMi1DseKT5pQUFoj6VuzZo3kwfgDDzyA4sIj2HFrCEaopOlsAOCfxxLx4H+y3dq+/fZbnH/++f36wJeIiOhM1ZP4Grcen4EiI9sLmWw4Jn8ze35aZ36+559/vtev73A4oNPpoFarcK5fpaQ/1xrpChICwNy5c3t9Dl1RKpWuCsI/lPtI+j0FO5ZOS3Adv/jii/1SBEQURRw6dAgtLS1u254eeughSZDw94vGS4KEQHuxmu/+kAQPlfSmvqmpCddddx3UajWKi4tdqwyIiIjOBqIooqmpCUeOHMGmTZuwZcsW5OXlQafTQaFQICgoCOHh4QgJCYGvry9UKtUJg4S1tbVIT09HsL8P1tw9EU+PKeoySPhdcwIufTXPLUi4bNky2SCh3W5HfX09zGYzEhIScN555yExMbFbQUKgvVCZj48PwsLCMHLkSKSlpUGtVqOpqUlyv5KVleV6XVnXjHNfKsYavfw2XgC4MqQQWfeMQpC2/f5o3rx5+PLLL7scbzQacf7552Pp0qXwVKvwzk2peH9G+QmDhG9WJ2Pa84WSIOFFF12ErKws2d0z//znPzFrzjyc/x8j6p1+sud9YEQB7rhwolvbH//4R8k9FBEREZ0+BgrPQIsXLwYA/JQjv0Vjfnznt7Wr7TCnY/369QCAORPjZasBbqzuDND5+vr2+zbYjjxBX++R3xJz4ajOJ8+rV69GU1NTn8+pvLwcZWVlCAgIcP3gsmnTJuzYscNt3Mp5Y7BqStcJutN9S/HfW8dDIfPDT3V1NbZv3w6DwYD6+u4lFSciIhrMjEYjioqK8Msvv2Dz5s3Yt28fjEYjtFotwsPDERQUBB8fnx7dayxcuBBXXHEFzp0Yh9w7QrDIv7jLsT80j8DyV/PccgZOmzYNd999t9s4URSh1+vR0NCAkJAQzJw5E2lpafD19e3xZz5eREQE0tLSoFQqZSv9Hh8sbDVZsfSlPLxS3vWugnO8y7Dz9ggkRocCAF555RWkp6fjqaeegtncvtuitrYWGRkZWLp0KaxWK5JiQrH73gRcP0y6i6VDi+iFldvicPObu2Gztbn1rVu37qR5oe+44w74h8Vg6dceaBU9Zce8kFKCS2aNch0XFBTgyJEjXeZzJCIiolPDrcdnILPZDG/v9qIl+Q8nSCrN6Zy+CPtrNUSI8PLyct349ZZZs2Zh69ateP66NNwTWyDpz/ghDFnZ7TeTUVFRKC8v79Xrn0xHHkcAKH0kDjGqRrf+JqcPQp+qda0M2LFjB6ZNm9Zn8zGZTNiyZQtaW1sRFNReddnhcGDevHlu4y6ZPQqfzqntckXD8d6uGonfv5Uj2/fJJ58gMTERaWlppz95IiKiftZRHbiqqgq1tbWwWCxQqVTw9fWFWq0+6XbirpjNZtfD1gdXpOIvo4pP+H/uj/oRuOiVA26r9MPCwvDf//5Xcl69Xg8/Pz8kJSUhPj7elQalt5SWliInJwdKpVL2nvj4bcgAcNfFk/Cv8cVQCdLCaADQ4PTFn3YHw2R1wtNDAS8PAZ6q9t+9VAI8lYBaJcDXA7gqshzaLvI2AsAB2zBc9qkBR4qr3do9PT3x008/9ehzpqen48JzR+PLjGrZuZtFNeZ/44tf80pcbZWVla7dNkRERCSPOQqHALVajba2Nrz++8m4OTJf0j/lv/7Yc6QcgiCgra2tV1f1deRI3PdgMiZ4ut8UtoheCPp7A+z29hvvG2+8EW+99VavXbu7Or8+abg5UhrMXLA2HBt2tbcvWrQIX3/9NTw95Z9gnw5RFJGTk4OCggKEhYW5KhX+9oZ+8fREfLWgAZ5C97cM/6NoJB76SBosnDFjBh5++GHMmzfvhBW0iYiIBgun0+kKDlZVVcFkMrm24Wo0mlMODnb44x//iOzsbAQH+OKj/0vA+dquVxE6RQHPliTi4Y9y3Kobq1QqbNiwwW2sXq+H3W5HbGwsRo0addorCLsiiiKKi4uxd+9eqNVq1wPR4/323mLpuaOwOqOxy+IsveH92iT84f39MFvctyOPHDnylO7/OoK5t1yQglVpx2THNDh9kfKmGRW17TtCLr74Ynz55Zen/WeEiIjobMYchUPAJZdcAgDYkN8q23/+xPYtJaIoYvPmzb16bVEUERaklQQJAWCrYZgrSAgAL730Uq9eu7s6VtN9nSfdpgMAN07tvMHevXt3n+W4qaqqQklJCQICAlxBwiVLlriNmZsWjy8WNHUZJLSJ8kHeBxMKce/FKZL27du3Q6/Xo7a262qEREREg4HNZkNxcTF+/vlnbN26FYWF7TsSQkJCEBoaCm9v79MKAFVWViI9PR3Z2dmYlRKP3NuDTxgkrHf64YIN4Xjwwz1uQUKtVisJEra2tqKtrQ0pKSm9ss34RARBQHx8PMaNGwer1YrWVun93/HbkAHg+61HMOczT1Q5Anp9Pq2iJ67fGY//e32PJEh46aWXnvJDYo1Gg8mTJ+P1H3LxVJH8FupghRFPXRzvOv76669RXS29JyUiIqJTw0DhGer6668HAKzPLoFdlH4bM6I6g06bNm3qtet2bGNeNDlWtn99qftc5JJW94fly5cDADZmF6PRKS1qsiyoBKFB7VF0nU6HY8eOuf1A0BssFgsOHjwIAK6VffX19TCZTK4x54yPwTdLjNDI5HoEgJcrkrFkbSgsonwS9GfHF+Oa+eMk7StXrkRFRUW/FGohIiLqKaPRiMOHD2PTpk3YtWsXGhsb4e/vj7CwMPj6+roerp2qjmIlK1euhADgkRWp2HhhM6KUXecl3toag0lvmrB2u/tOjWXLluHbb791a7NYLGhtbcXo0aMxYsSIflnNJggCkpKSMGbMGJhMJrf7iQ6/DRbmHCnHtLdakGcd1mvzONIWjumrPfDeT/skfevWrcNtt912Wud/9tlnAQCPfrQHH9Qlyo65NKwMWt/Oe8y//OUvp3VNIiIi6sRA4Rlq7ty5UCqVaDGakW2R5mWZ4VMJT3V7cKk3A4UdybsXJsoHrtbkdK7Mi4qK6rXr9tSdd94JALDbHVhdKf36eAp23Dy/8+YzMzMTDQ0NvXZ9URRx5MgRNDY2IjAw0NW+YsUK1+vJo4bjh4tsXVYPfKcmGXe+sxuZu/Nx7ZYIOETpDyEKQcRbMyqxZGaypO/Pf/4zWlpaeuHTEBERnT5RFNHQ0ICcnBxs2rQJ+/btg9VqRUhICIKDg7tdGbgrer0et9xyC9LT03HFFVcAAIaF+uOneybgb6MLu8xH6BQF/ONYIs57/hAqa90DiZdffrmkcElbWxv0ej0SEhIwevToft3yKggCRo8ejeTkZBiNRlgs0m3Fvw0WVtQ2YeZLpVh7gorI3fWJLhGTXyzDgSL3nRhKpRJZWVlQq9VdvLNnOqox3/DGXmS2xEn6vQUbrpvbee/z9ttvyxZ7ISIiop7r00DhL7/8gqVLlyIyMhKCIOCbb77py8sNKUqlEmPGjAEAbKrylvR7CW1InxQHANi5c6dbIu7T8eOPPwIA0gPrJH0l9mDkl3Zudz3dJ8qn4/j8Pa9tkq8Off3IRghov7lftWoVKirkx52K2tpaHDt2DFqt1rUqYtmyZa7+cSMi8NNlIgIU0tUAAPCxLhG/fzMbAPD999/j0lufwB1742XHqgUHPpvXgHMmxLm1Z2Zm9nshGSIiot9yOByorKzEtm3b8PPPP6OgoABKpRLh4eHw9/c/rTzKlZWVmD9/PtLT03HRRRfh6NGjCA7wxW1LJyLrvvEou1XAAm1Jl++vc/phyfpwPPSfbMnOgnXr1uGWW26RfJaGhgZER0djwoQJp73y8VQIgoBx48YhMTERer0eVqv0gWNWVpbbro5WkwUXvJSHF8uSZB88nohdVKCgLQw37IrHVa9mo9Xkfr377rsPmZmZPf4cDocDOp0ODQ0Nkh0QQUFBUKlUcDideGCN/CrQG0Z3FutzOBw4evRoj+dAREREUr1bku03WltbMXHiRFx//fWunHrUe0aMGIH9+/dj3cFGPJQg7V84WoufdrY/wf/yyy9x+eWXn9b1zGYzKisrkZIUhQilQdKfpQsC0Jn359577z2t652uhx56CA8//DCOlNTiZ+N4nOdb6tYfr2rAknOS8MOvR6HX61FaWork5GRXRelTZbVacfDgQTidTte5GhsbYTC0f82SY0Kx4SoVghXSryEAfN00Er9btRei6HStCvD19cXSW/+Oxz98DH9JlhZn8RZs+H6ZFXNMkcgr7HzKf/fdd2PdunUD8oMMERENbXa7HWVlZSguLkZjYyMAwM/PD56enqe0Cq+xsRG33nor6uqkDysD/LyxYvZIXJYMnOdbDg+h6zyEHba0xuLyD8pQXV8p6fvtqjygveCKTqdDeHg4Jk2adNorIE+HQqHAhAkT4HA4UFRUhMDAQMlqvjVr1mDNmjWurbxOpxP3vLcH/44Mwbj4YDicgNXmgKXNDsv/frfa7LDY7DBb7LDY2mCxtcHpcABolp1HZmZmjwO9oijCaDTCZDIhJCQEbW1tqK+vR0hIiNv9ynfffYfFixcj50g5si2jkebl/n2a4FmNaWNjsPNgGQBg1qxZaG5uHrC0N0RERGeLPg0ULlq0CIsWLerLSwxps2fPxrfffouteaUwLA2BVjC79WdEGF2vX3/9dVx22WWnFTD6/PPPAQDnp4QBkAa51uV3bn/RarW9tv3kVN133314+OGHAQCv5zhw3mzpmD9M8cIPv7a/3r59O8aNG4eRI0ee8jVFUUR+fj50Oh1CQkJc7R1bjuMig5B5jTciusiRtNaQgBWv5cHpdGLdunVufRqNBuuKVQj1TsId0dJK14GKVqy9IgDnvBeCkkodgPYb+Pr6eoSHh5/yZyIiIuopq9WK3NxclJaWQqVSITAwECpVz2476+vrcfPNN6OpSf7/TK2vBpeeOxKXjVYg3a8cnkJJt87bsdX4sY9zZPMTywUJO7ZNBwQEIC0tbVAEo5RKJVJSUuBwOFBcXCy7fXvx4sVYuHAhLr30UjQ3NwMASqp0KKnSnda1Y2Ji8MEHH/T4fTabDc3NzfDy8sKECROQkJAAk8mE3bt3u4KFHYFHjUaDKVOmYPfu3XjnkBppqdLz3TIr1BUotNlsOHjwICZPnnxan42IiGioG1TLjKxWKwwGg9sv6trtt98OoH27xa8GaZLqceoahAa2b7/dtWvXaVX2NZvNrhw986Ol25jtogI/7el8ej9nzpxTvlZvOX778ec/H0GNw18yZoG2BLHDggEA7733HkpLS+FwyOcw6o76+noUFRXB19fXdaO7fv16OBwORARrsen//LtMpJ5ljMNFrx6A3W7HkiVLZAOt//zHP3D3+zn4uF4+mBmpbMaGa/0RFtRZ7vxPf/rTKX8eIiKinjIajdixYweKi4sREBDg2kZ6MjabDatWrUJ6ejrS09OxYsUKSZAwLjIINy2ZgO/vSkHtvRq8M60U52uL4Sl0L8VKrVOLRT+F4ZGP9kiChHFxcbJBQgBoamqCRqNBWloatFqt7JiBoFKpMGnSJMTExKChoQFtbW2SMUqlEl9//XWvpABSqVT4/vvvexwkdDqdrt0V0dHRmD17NkaPHg21Wo2AgABMnz4doaGh0Ol0bulynnnmGQDAhxuPokX0kpz30rAy+Hp3ti9btkz2a0BERETdN6gChU8//TT8/f1dv6Kjowd6SoOaWq12bW3dWCZf6GLh/6oTm0wmHD58+JRzFe7fvx9NTU3w8lRjpo90i062JRL6ls58e6tXrz6l6/S2q666CgDgcDrxfmmYpF8piPjD/DgA7UG+pqYm1NfXn9K12tracPDgQbS1tbm+Lw6HA08//TQA4INr4hCvki+Yst0cgwteOwqbrf3m9o9//GOX11m7di2ueT0Xaw3yOQtHetTj2xujXfkXP/zwQ9lk50RERL2tsbER27dvR01NDUJCQk66u8BsNuPJJ59Eeno6Fi5ciM8++8ytPzxYi9/NH4f3bknDsUdGoPj3drwxuQQXBByDVzeDgx1+1I9AyqoWrN8lTeHxyCOP4L333pN9n8FggCAISElJcdstMFio1WqkpaUhNjYWTU1NaG1tlR3n7++PrKwsfPrppz2+RmJiIr755hts2LABvr6+3X6fKIpobW1FXV0dfH19MXXqVEybNg0BAQFu4/z8/DB9+nQMGzYMOp3OLdin0WjQarLgi1rpzwW+ghXXzh3lOq6qqmJ+ZiIiotM0qAKFDz30EPR6vesX/6M/uYyMDADA2twa2f75CZ036D///DPKysp6fA2j0ehavZiRGgcvQfqkdmNV5xYcpVLZo5vIvvTCCy+4Xr+2oRh2UfpH/pqYWqhU7av/TCbTKf+5KygoQF1dHQIDA125lzqqLy+fPbrLZOrZluFY+NoxmMztycF/u+X4t9RqNcaNH4/lqw5ju0k+mD5dU44VGWNcx8uXL+/pxyEiIuqR6upq7NixA01NTQgNDT3hKkK9Xo/Fixdj8eLF2Lx5s6s9wE+Dy84bhddvTMOhhxJRczvw4cwyXBdegHhVz7fL5lmH4fGjiUh81xMXvJiLGp17ZdyRI0ciMzMT8+bNk32/yWSCzWbD+PHjERUV1ePr9xdPT09MmTIFo0ePhsViQVNTk6RASIfw8HBkZWVhzZo1WLhwoewYhUKByZMn4/vvv0dWVhbefPNN+PtLd2acSEfuwba2NowePRqzZ89GTExMl2lwvL29MXXqVMTExKCxsRE2mw0AcP/99wMAVm2Rf5B7wxj3h6FffPGF7JZyIiIi6h5B7OouorcvJAj4+uuvcdFFF3X7PQaDAf7+/tDr9YNqm8dgYjQaXdtrKx6NwXBls1t/uSMQMX9rL+Lh5eWFb775BnPmzIGnp2e3r7Fv3z7Mnj0bBoMBL12fhjuipU/iZ30bjK257VuPIyIiUF1dfYqfqPcpFArXzfL3d6XggoBjkjFXbYnGJ5sOIjU1FU888QQyMjJ6FOysr6/Htm3b3IKkZrMZixcvhqfaA0fvH45YVaPkfQdsw3Dea5Vo1Lfnk7zoootw1113nfR6NpsNCxcuhL+fN369PQpj1dJA8VrDCCx+Idd1bLVaBzxvJBERnX1EUURJSQny8vJgt9sRFBTUZbESvV6P5cuXu6X5GBbqj7vPT8CCSBPGe1ZDKZzerelBWwS+LNXik20VOFIi/yAVAB577DHXA1c5VqsVzc3NGD16NMaPH39KBVj6myiKKC8vR15eHkwmE4KDg0+rqvSpzkGv18NmsyEiIgJjxoxBcHBwt79+NpsNubm5KC4uhr+/Pzw8PFyB3L0PjkKKpzSVzpTP/LHncPuD3uTkZGRlZWHYMGlaHiIioqGqJ/G1QbWikHru+GBWVmOopD9a2YRRce2FLCwWC2pqalBcfPJKgB2am5tRUlICo7E9kJUR3iId4/TG9rzOisJTpkzp9vn7w/Gr6VbtNMmOuSW1/a9CTk4OzGZzt/I5trW1obKyErt27cL27dthtVrh4+Pj6r/22msBAI9eNl42SKhz+mLeWzWuIKEgCN0KEgLtqwpjY2OhbzFh/tu1qJbJvzjPrxThIZ3t//znP7t1biIiou5yOp04fPgwcnJyAKDLIKHD4cDy5ctx0UUXuYKEXp4eePLKVBTcqsafRhQixavqlIOER9vC8PeiJIz7yAfjns7HEx/v6TJIOGXKFGRmZp4wSGi329HU1IQRI0Zg7NixZ0SQEGi/l4iJicE555yDkJAQ1NfXw2q19su17XY79Ho9amtrXduhO+bRk6+fWq1GamoqEhMTYTAYYLVakZKSAgB495A0TyEA3DKrM73M0aNHUVhY2OWKSiIiIjqxPg0UGo1G5ObmIjc3FwBQXFyM3NzcU9r+Sl3ruPnaUGiT7V+Y0vlE9dVXX0VRUVGX+WuOJ4oiCgsL0dzcDKfTieFhAbIr17YYIuA4bovHxx9/3NOP0Kduuukm1+u1OwpQbJfmF5rtU4rR8REAOldGyOVzFEURjY2NOHjwIDZu3Iht27ahpKQESqUSoaGhru+F2WxGfX09RgwPwR8TSiXnAYDH9oah9rgtUD/++GOPPteqVasAANX1erxXIs2/6CE4cN2cBNfxn//85x6dn4iI6ETa2tqQm5uLAwcOwMvLC/7+/rIBoZ9++gnz5s1DY2PnQ7Nr5o9Fwf2ReDypED7CqQWyCtrC8ExxEiZ9osWovxfikY/24GBR1zsazjnnHKxbtw7PPPPMCVfZOZ1ONDQ0ICoqChMnTuz3FXm9ITAwEDNnzsSIESOg1+tdD3x7m9PphNFoRF1dnaua8fjx4zF79mwkJCSc8tdOpVIhJSUFo0aNQmtrKx5++GEAwPubjqJVlO6KuSyiAj6azvbnn3/e7c8bERERdd/JS9Cdhj179iA9Pd11fO+99wJoX2n1/vvv9+WlhxQ/Pz8YDAasyykFZkj758UC//7f69LSUhiNRhQVFWHChAknPG9DQwPKy8vx6quvAgAWTY4BUCIZt+G4BYparXbQ5CfscPyKAREi3ioIwN9HS/Mc3Z4RhdveqcFzzz2HP/3pT6itrcXw4cMBtOcoqqmpQXl5uauqoJeXF4KCgmRvgpctWwYA+PelUfASpFudsy3D8cYP+1zH3t7e0Gg0knEnotFoEBYWhrq6OryzuRQPJ0jHrExsRcc6QqfTiZaWFtdWdSIiolNlNpuxd+9elJeXw9/fH15e0pVeDocDF1xwgVtBrZnjY/HCIh9M1fQ8H3ClIxA/N4ZgU4kdG/ZWoqy6sFvvu+eee7BkyZKTBq1EUYTJZEJLSwtCQ0ORmpp6Rqfs8PLywuTJk6HVanH48GE0NDSccFt4d4miCIvFAqPRCFEU4e3tjZEjR2LYsGEnzU3ZEwqFAuPHj4eHhwcOHjwIrVYLg8GAL+rH4Now9zQ4WsGMlRnJeOPHPADAN998g4cffhjBwcG9MhciIqKhpE8DhXPmzOGy/37w9ttvY8WKFajVGXDAloxxaven6bP9q+Dr7QWjyYK6ujr4+PiguLgYsbGxXSamFkURBQUFaGtrQ15eHgQIuHOC/BP/H3MqXK+feOKJ3vtgvUSpVGLOnDmuZOlvrS/A46M8JNUSr4qswB+91NizZw8cDgfKysqgUChQWVmJ6upqmEwmqFQq+Pr6Qq1WnzD/UltbGxZPT5LNh+gUBdz+oxkiOv9udLUKs+OHFk9PT9kb7/fffx+LFy/GsQodtpnGYqa3+w9e49TVSB0VjZwj7e2zZs1yrfAlIiI6FQaDAdnZ2aitrUVwcDA8PDwkY9asWYNnn33WdRw7LAjPLo/FZcFFAJq6dR2d0xdb9BHIKhWxfl81jpaUApBfpf9bCxYswN13392th3AdlXmNRiO8vb2RnJyMxMREeHt7d+tag5lCoUBycjK0Wi327duHuro6BAcHn1Iwz2azwWg0uh6WDh8+HMOHD0d4eLhsoLg3CIKAUaNGwcPDA6+99hpWrlyJ17c04FqZGm03jLPjjeM2Z3z77bcYNWoUH5ASERH1UJ8GCql/XHLJJa7Xm2r9MC7aPVCoFSx4dPlYPPifbADtOWSsVisKCgqQlpYmG/Cqra1FVVUVfH19YbVace2C8RjvKb05L2wLxbGKItdxR3XkwWbNmjWuG35dcwu+aUjFFSHuKxECFCb8bu4ovPljHo4cOQKVSoXKyko4nU74+PggLCysW0/hr7jiCnioVHgxwyHb/2FdInYc2OM61mq1sgFbURTR1NQEQRBgNBqh1WolP/BoNBoEBASgubkZHxxSYeZk6fWuPyfcFSjct28fHA7HGbmNioiIBp5Op0N2djaam5sRGhoq+//JkiVLYDK15wT20XjisUvH4c74UmiEIsnY38o0xmNDmQrr8+qQe7QCwMlzBgNAUlISnnnmmR5V5hVFEUajESaTCd7e3hgzZgzi4uLOugJ6giAgMjISvr6+2Lt3L6qrqxEQEOAW3BNFEQ6Hw/XL6XRKXnt4eCAgIADR0dEIDw+Hn59fv+RuFAQBCQkJUKlUEAQBOw6U4MDSJIz7TTqcKV4VmJQUhb357Q+wn3/+eVx99dUYPXp0n8+RiIjobMJiJmcBpVKJESNGAAC+2dcsO+bO+FJERwQCAB5++GFotVqUl5dDp5NuwXU6nSgoKIDT6cS2bdugVqvw5BRpERMAeP1I51NaDw+PQbtFR6PRYOzYsa7j135tlh1387j2PI9PPvkkvL29ERAQgLCwMPj4+HTrZnjTpk2wWCy4/5IJSPSol/Q3O73xp8/y3dq++uorybiOIKFKpUJaWhqSkpJgNBqh1+slq3T/85//AAA++TkfJlH69b8sstrtB7m1a9ee9HMQERH9Vl1dHXbt2gWDwdBlkDA9PR0mkwkCBNy4aDwK7wvDAyMKoBHk8yh32GOJwuxvQzH/uX145vNs5B4tB9D1rpSRI0fim2++QVZWFrKysvDGG290O0jodDphMBhQW1sLQRAwbtw4pKenY8KECWddkPB4Wq0WM2bMQGJiIlpaWlBbW4u6ujrU1dWhvr4eer0eZrMZdrsdgiDA29sboaGhiI2NdeUdnDNnDhITE6HVavu1wIsgCIiNjcU111wDAHj7iI/suJvPC3e9NpvNOHr0qGzOaSIiIuqaIA7ivcE9Kd881K1ZswZLliwBAGy9fxzO8ZYWjFldPxIrX8uBIAjYtGkT6urqEBUVhRkzZrjd7FVUVGDHjh3QarVYuHAh7l+eimfGSfMAldiDkfTPcrT97wZszJgxOHjwYB99wtO3fv16LFy40HV84KEk2eIsUz8PwO5DZfjyyy8RFBTU7fM7HA7MmzcPUWEBOHyLB3xlkrPfnZeAf3+913V8zz334MILL3Qb01EwxcPDA5MnT0ZkZCREUcSxY8dw4MABtLW1ISgoCApFZ5x/wYIFaGtrw6e3peLyEOn36pKs4fj6l8MA2nMWmc3mbn8uIiKi2tpa7NmzB2azGcHBwZIgUcf/gQAwLNQfX//fcEzTVMidyk2lIxCP7vbH++v240SBwfT0dNx///09zud7vI5cvRaLBX5+foiPj0dMTAx8fOSDTmcrp9OJsrIymM1mqNVq14Pe3/5+/H3GYHHo0CGMHTsW/n7eqLrHG96/CUA3O70R+WwjzJb29nnz5uH999935ZwmIiIaqnoSXxt8dwB0So4PgN27tgVOUfqU98qQIkweFQ1RFGE2mxEQEIDq6mpUV3duVbbb7SgoaE8Q7XA4oPX1xgNjpME0AHhil48rSAjA9ZR3sJo7d67b8RuH5HMP3T67vSry3Xff3aPzX3DBBQCA51fEywYJD9iG4eVv97m1yQUJGxoaoFarMWXKFERGRgLo3HYzY8YMaLVa1NfXo62tzfW+6667DgDw/h75lZ/XTercXtSRgJyIiKg7ampqsHv37i6DhJs3b3YFCWOHBWHrTcEnDRK2ip74W1ESEp+rwfvr8vDbIGFAQAA+++wz14rBxx9//JSDhA6HA83Nzaivr4darcbEiRORnp6O0aNHD7kgIdCetzAuLg6jR49GQkICYmJiEBERgeDgYPj5+cHLy2tQBgkBIDo6GlqtFvoWE77WxUr6AxQmXJU+ynW8e/duVFScPGBNREREnQbnXQD1mFKpdAWVdh0oxWcNIyVjFIKI5y5o35bzyiuvQK1WQxRF5Ofnw+Foz6dXUVEBnU6HgIAAvPLKK3jkkjEIVkiDSnnWYfjPBvfVg/fcc09vf6xepVQq3bYlvZd5FC2iNPn2pWFl8PfToLy8+xUZ6+vrYbFYkJE28n+J2qXuWGeH0+l0Hf/lL39x6+8IEnp5eWHKlCkYNmyY5BxhYWGYOXMmhg8fjsbGRtfKwEsvvRQAsG5nISodAZL3LfQvRXBAZzXq+Pj4bn82IiIauqqrq7Fnzx5YLBbZIOGqVavw5JNPAgASo0Ox5QY/jFBJ05p0cIoCVtcnYtQbDjz20R6Yze4P1j788ENkZWXh66+/Rmho6GnN3WazQafToaGhARqNBqmpqUhPT8eoUaNOa2UiDRxfX19kZGQAAF7fJl8U58bxnQ+x9Xo9Kisr0dIi/yCViIiIpBgoPIvcddddrtcPflUKiyitQjjbpwzLzh2FDRs2AGh/Yl9XV4eKigrYbDYUFBRAqVRCpVIhL2cnbo8rkb3Wg5tFt6q9Pj4+gzY/4fHeeecd12tjqxmf1URLxngLNtwwr/1pdHdX3q1YsQJKhQIvLZD/K/Vf3UhsznEPIM6cOdP1uiNIqNFoMGXKFERERHR5LV9fX0ybNg3JyclobW2FXq+Hh4cHZs2aBREiPi2X/mDlKdixMj3RdazT6bj9mIiITqiqqgq7d++G1WqVDRK++uqr+OyzzwAAYxMi8Mu1XohWdl3ReJs5BjO+CsTK17JRUdvoavfy8sK6deuQlZWF6Gjp/8s9IYoiTCYT6urq0NLSgtDQUEybNg0ZGRlITEzss+q81D8EQcDf//53AMDW3GM4ZJPeL03XVGD8yM6Hrf/617/cds8QERHRiTFQeBY5fqtsabUOr5TKrxp7ZrYdTocDNpsNKpUKKpUK+fn5KCoqQlNTE/z9/WE2m/GXZfGS3C8AsNkYi7U73AtyPProo736WfrKRRdd5Hb8yuZa2XE3jW5/8rxy5cqTnrO2tv0cdy6bKJvzsEX0wn2fH3Nre+ihh1xJ4EVRhE6ng7e3N6ZMmYLw8HDJOX7Lw8MDEydORGpqKgRBgE6nw2OPPQYAeOeXStn3/C7J4nZ85513nvQ6REQ0NFVWVmLPnj2uvLhyKwm/+OILAEBq8nBsvkqBCKVe9lxljiBcuTUG5zxzALsOlLj1ffPNN1i7du1pP2zsKFBSV1eHtrY2xMXF4dxzz8WsWbMQGxsLDw/pw1M6M8XFxbl2iLx7VH7r+C3ndeYk3L59OwoLC127Z4iIiOjEGCg8i6jVanh6erqO//LlQdQ7/STjkjzqcNvSCbj//vsBAP7+/mhsbERxcTHUajWUSiW+XP02fhcuLYoBAH9a2yxpu/fee3vnQ/QxpVKJ9PR013FufgV2mKWrF5I96jA3LQF6vR6rVq064TmvuOIKhAVp8fg4+afVTx+JRmVds+vY19cXCxYsANAZJPTx8cGUKVMQFhbW7c8iCAJGjBiBGTNmuL6HarUah4trsNsSJRmf5lWJMSM6n7C/99573b4WERENHeXl5dizZw/sdrtskHDTpk2ulYQzxsdi4woHQmTSlADAQVsEpr7ehE83HnBrHzlyJLKysrpdqbgrdrsdjY2NqK+vh1KpxLhx4zBnzhzXg7fBmmuPTp1Go8FXX30FAHgvM192B82VkZXwVHe2f/TRR6ivr++3ORIREZ3JePd0ljl+BVyL0Yy/5skHnh6dUI+SYwWw2WxQKpXQaDRu1W+WhZZAJTgl7/uiIQG7D7nn7hs3btwZse24w48//uh2/MY+pey4P8xs/1p89tlnsNmkKysB4MorrwQAPLtiJAIUJkl/flsYnv3KvYDJl19+CaA9SFhfXw9fX19MnTr1lHMxhYaG4pxzzsHw4cOxbNkyAMB/jsh/P26Y3fmE3eFwsKgJERG5KSsrQ3Z2NpxOJwIDAyVBwvXr1+Ovf/0rACAjdQTWXWyW/f8PAHIsw3HeqirU6txXGn7//fd46623Tml+TqcTVqsVRqMR9fX1aGpqglarxeTJkzF37tz2irj+/pJ509klKSkJYWFhaDS04puGOEl/oKIVVx5X1GTDhg2orJTfcUFERETuGCg8y7z88stux699vw9H26TBwlBFCx5fPgaff/45AECr1SIiIgIKhQJ1RblY6i9dTWgTlXj4W2nluF27dvXS7PuHRqNxKwf+cdZh6Jy+knEXBJYgIrh93OrVqyX9er0eNTU1mDk+DivD5AuY3LVJCftxlaHPO+88VxGZ+vp6aLVaTJ06FSEhIaf1mXx8fDB9+nTcd999AID/ZBXAIqok466IqnNbXdER6CQiIiotLUVOTg5EUURAQIAk2HbzzTfj6aefBgAsmp6EHy4wwE+wyJ0K283RSH+1FA3NnQ+ktFotsrKy4Osr/T/3eKIowuFwwGw2w2AwoKGhAXV1dairq0NDQwPMZjMEQcDw4cMxc+ZMpKenIyEhgfkHh5CwsDBXyp03tjfLjrlxQmcu7YaGBlRVVcFkkg9qExERUScGCs8yGo3G7Qbc4XTiT7/I5+W5LbYEm3761nUsCAJEpxNR+e/Ijn+vegQKyt23bURFRZ2RlQNLS0tdr222NnxUESkZoxYcuGVBe/XoDz/8UNJ/0UUXQYCAVxZ7QSGIkv5vmxPw046jbm2PPfYYnE4n6uvr4e/vj6lTpyI4OPh0Pw4AQKVSYezYsVAqlWg2tOKn5ljJmEhlM86f1lnU5IcffuiVaxMR0ZlLFEUUFxcjJycHAGRXEl599dXIz2/PT3zJrFH4aoEOGpk8xgCwuTUW814uhMHYGZS55JJL8O2338qOB9pXCjY2NqK2tta1UtBms8HDwwMREREYM2YMJk+ejNmzZ2Pu3Lk4//zzMXPmTAwfPtyV85eGDrVajfnz5wMANucUIV/mofg53mUYHd9e7EQURTQ3N7OoCRERUTdIlxzRGe/RRx/Fgw8+6Dr+buthbJ4+HnN8St3GeQlt+PuykTAaja7gYn3+NqzQlEnO2SJ64fEvCyTtxxdQOZMEBARApVK5Vvu9trEMd14nSAJ+NyXUw/t3qfBRA2X/vQ8jo8Pg4bTAZtBh7wOj4K+yIl5VJTm/WVTj7i/ct2h3FDDp2CY1depUBAYG9urn8vX1xfTp0/Hrr7/i/RwzLporHXNdmg/WbO88rq+vP+Vtz0REdGbrCBLu27cPCoVCNmfgK6+8gqqq9v/rrp43Du/NrISHIF8Y4ifDCFz06kFYbW2utnXr1p0wRYnFYkFzczOCgoIQHR0Nb29veHt7w8fHB15eXswzSLKioqIwbNgwVFdX4918Lf4xtk4y5tb04bizuL3Q3KOPPor3338f8fHx/DNFRER0AoIoitKlUIOEwWCAv7+/W+48OjmbzeZW1AQA0kZFY9cKg+zKt3O+CcFTL74Dp9OOYRtvw2gPaeXepwoT8ejqbEm71Wo9o/ITHq++vt6teEjmfRMw17ekV87914JEPP5x59fLw8MD69evdyVdnzx5MkaMGNEr1/qtI0eOYPTo0VAqFKh8JBLhCoNbv1lUI+L5VhiMZgBAdHQ0ysqkwWEiIjq7iaKIgoICHDhwAEqlUjZIaLPZsHDhQgDAjYsm4PUppVDK3EsAwDdNCbjstf1uKTeysrJOeP3m5mY4HA7ExsZi3LhxZ+QuBRoYdrsdt9xyC9555x2EBPih/E41vIQ2tzENTl9E/qMOtrb2P5OffPIJ5s6dywekREQ05PQkvsbHaWchtVqNmTNnurVlHynHx7qRsuOfXeCN5qZm6A9tlA0S1jn98PTXByTtoaGhZ2yQEGif//HblV7Pll8d0VPF9mA89UWeW1tHdb7m5maEhIQgJiamV64lJyEhAUqlEg6nE59Vhkv6NYINV6cnuY7Ly8slY4iI6OzmdDpx+PBh5OXlwcPDo8vqwx1Bwj8snYi3ppZ0GST8RJeI5a/s63aQ0Gazoa6uDp6enpgyZQomT57MICH1iEqlwm233QYA0DW34PtGacqVYIURK85Ldh3/8MMPrtWxREREJI+BwrPUpk2bJG0PfXkMJlEa2JvpXYYvVz2OqXWfyp7rqbxQtJqskvYDB6TBwzNNRUVncZavfjmMSkfAaZ/zvi1ebluuEhIS4Ovr66qcnJSUBJWq73b9e3h44MUXXwQAvLu1VnbM70bZ3Y6tVun3l4iIzk4OhwP79+/HwYMHodFo4OfnJzsuPT0dAHDZnNF4aVJJl+d7tyYJV7+aA6fT6WrrKkgoiiIMBgOam5sRExODWbNmITY2llWK6ZRER0cjMrI9z/SbO1tkx9yU0vlna9OmTaioqIDFIl+Eh4iIiBgoPGt5enpKth9X1DbhpWLp01YAeGdGBYYrGiXtx+wheO3H/bLvOX7b7pkqIiIC0dHRANpXV7ySf3pbUd6rTcLXvxx2a3v77bcBtFdJjoiIcN3Q9qUVK1YAAHLzK5BnHSbpn+FdjsTozs/6j3/8o8/nREREA89ut2Pfvn04cuQIfH194ePjIzuuI0g4KyUeH86u63Il4SvlSbjhjT0Q0dnfVZDQbrejrq49j1xqaiqmTp3aZZCSqDuCgoJw5513AgAydxegyC69j5vlU4bk2PZ71urqarS0tKCmRrqDhoiIiNoxUHgWKywslLT97csDqHFI96Oru0hK/tgODex2ad/o0aNPf4KDxI4dO1yvn/1iLz6qT5IdZxLVqHf6ocQejIO2COyyRCHLGIcfmkfgo7pEXLs9Fje87p7HMTMzE0B7onalUomkpKR+SaAdGhrqCkh+VOAtO+b6OZ3bn//85z/3+ZyIiGhg2Ww2ZGdno6CgAP7+/l1u9e0IEo6Oj8A3Sy2SvG8d/nEsCXe8u8etTS5IKIoijEYjGhoaEBERgVmzZmHkyJGsVkynTaFQYOnSpa7jdwvkt9DfmhHtev3555+jvLwcgzhNOxER0YBiMZOznNxWnlsumIhVacUnfW+OJRJp/zwi29fQ0ICgoKDTnt9g4HQ68eSTT+Ivf/mLq83fX4vIED8YTFa0tFphbDXD6bCf4CxSjz32GDIyMiCKIurq6hAfH48pU6b02/aqnJwcpKWlISxIi4rblZIKlaX2IMQ/VepaBXLkyBEkJyfLnYqIiM5wFosFOTk5KC8vR2BgYJc5hjuChMNC/bH9pkDEqqS7DQD5ImdyQUKHw4HGxkZ4eHggKSkJiYmJ8PDwOM1PQ9SpubkZkydPRlFREUKDtCi/XQVPwf2eTef0ReTTdWj7Xw7Nzz//HBkZGWfNvSwREdHJsJgJuRgMBknbm2v246At4qTvfWCTfGAsJCTkrLqxUigUuOaaa7BgwQJXm15vwOGiSlRW62AwtPQ4SDh9+nRkZGQAAEwmE7y8vJCYmNivOZiSk5OhVCpR12jABoN0y3msqhEZkxNcx6mpqf02NyIi6j8mkwm7du1CWVkZgoKCugwSLlmyBADg5+OFn26I6DJI+G5NkiRI2LGC/nhWqxU6nQ5BQUGYOXMmxowZwyAh9Tp/f3/8+9//BgDUNxrwY3OcZEyIwojL53Q+DN21axeqq6v7a4pERERnFAYKz3J+fn6YOHGiW5vT6cSfNp/4fRta4pC5W7p1GQDq6+t7aXaDR2RkJO64445eqbg4bNgwPP300wDat1u1tLQgLi4OgYGBp33unvDx8cGtt94KAPhgn012zHVTO7fomEwmt2qVRER05mtpacHOnTtRXV2NkJCQLgN1L730EkwmE1QqJb65JRETPOWDKGv0I/D7t3Lc2p588knJNmKbzYbm5mbEx8fj3HPPPSvyGtPgJAgCRo0aBV9fXwDA6zvki5r8/riiJu+++y7KysrQ1ia/rZ6IiGgoY6BwCMjNzZWsZFuzPR+ZLXGy452igAd/bJDtq62Vr6J7ptNoNIiKisJ7770nKQLTE0lJSfj4449dxy0tLfD19UVCQsIJ3tV37rvvPgDA11vy0eiUJqxfFlIOb03n5z169Gi/zY2IiPpWc3MzduzYgbq6OoSEhEClUsmOs9ls+PrrrwEAH9w0ERm+pbLjdluicOnrh92qGz/22GOYPXu227i2tjY0NTUhNjYWkyZNOq3/V4m6Izw83FU8bsMu+aIms33KkBwbDqA9hY5er2dREyIiIhkMFA4Rctsr/vhDAxyidCvsZw0JyDlaKWn39PQ8q1cEREVFwcPDA99++y2WLVvW4/c/8sgjeOONN1zHTqcTZrMZCQkJrqfc/S0qKgrBwcFos9vxeY202rKfYMHl53VuxVm4cCGTexMRnQUaGhqwc+dONDY2IjQ09ISFQxYuXAgAeOaaNFwVKr+boMgeisVvVsBssbraLrzwQleajQ52ux2NjY2Ijo5GamoqtxpTv/Dx8UF0dGfBkq6LmkS5Xh84cIBFTYiIiGQwUDhEhIeHu6rgdtiXX4l/FY90a6tyBOBPX5bInqO1tbWvpjcoBAcHIzg4GC0tLbj77ruxbt06yddMzqxZs5CZmYl58+a5tev1evj7+yM+Pr6vpnxSKpUK119/PQDgvW3yW8avHdd5g1xZWXlWbi0nIhpK6urqsHPnTuj1eoSFhUGh6Pp2r6N4yR3LUnB/fIH8+Zx+OP9DA3RNnXmPVSoV7rnnHrdxdrsdOp0Ow4cPR1paWpe5EIl6myAIGD58OLy8vAAAb2UWwipKV9BeHVUNj/+trP3ggw9QV1cnm8+biIhoKGOgcAgpKyuTtD34n2zclhOPtfp4vF6ZiPQPzSivkSYv//jjj0+4GuFsIAgCYmNj4XQ64XQ6oVarsXr1aqxZswbz5s2TbN++8sorsW7dOvzlL3+RfG3sdjtsNhsSExNdN60DpWP78c6DZTjSFi7pn+Vdhthhwa7jTz75pN/mRkREvauurg67d++GyWRCaGjoCYtodQQJl88ejRcmFsuOaRU9ceFXShSWuz9E2rBhg9uxw+FAQ0MDhg0bhrS0NG43pn4XFhaGiy++GEB7UZMfmuIkY44valJRUQGj0ciiJkRERL8hiIN4vX1PyjdT99TU1GDYsGE9es/LL7+M22+/vY9mNLhYrVZs3LgRdrv9tP7M6XQ6BAYGYvbs2QO+7UoURfj4+MBsNuORy9Pwt1HSFSNP5ifiz5+0V7D09/dHZWUlfHykOQ2JiGjwqq+vdwUJg4ODTxgkXLx4McxmM86dGIf1y4zQCNKiV22iEss3heP7rUfc2rOystyOnU4n6uvrERYWhmnTpsHb27t3PhBRD23btg3nnHMOAGD+1ESsXyTNrb2lNQaz/3UAAPC73/0OK1euREZGRpc5PImIiM4GPYmvcUXhEBMeHo6dO3ciNjb2pGM9PDywdu1a3HTTTf0ws8HB09MTMTExMJvNp5yzpqOCXlJS0oAHCYH2lZIdgd73s4pk81JeO6IRAtrb9Xo9SkpK+nOKRER0mnoSJLziiitgNpsxKi4c31xokw0SAsDt2THdChLqdDqEhIRgypQpDBLSgIqNjUVAQACArouazPIpw6i49h0Wa9asgV6vR11dXX9Ok4iIaFBjoHCIEQQBycnJeOmll/DJJ59g4sSJkjHh4eH49NNPsXr1aowePXrI5RgaPnw41Go1rFbryQfLaGpqQnh4OIYPH97LMzt1jzzyCACgsq4ZWUZpkDhO1YBFM5Jcx19++aUr4ElERINbT4KEF198MWpraxEZ5o+1V3sjWGGUHfe3wiS8+eM+t7augoSBgYGYMmXKgBXuIuoQGhqKSy65xHXcZVGT9PaiJg0NDXA4HKioqOiX+REREZ0JGCgcgvz9/TFy5EgIgoDnn38eWVlZbr8+/fRTKBQKhIWFISoq6uQnPMsEBAQgLCwMLS0tPX6vxWKBUqlEUlLSCZPH9zd/f39Xvqi39zpkx9w6VeN6/fe//x1VVVX9MjciIjp1HUHC1tbWkwYJH3jgATQ3NyMsSItNN4YiTtUgO+792kQ8tnqPW9tvg4SiKEKn0yEgIABTpkxhihgaFNRqNW655RbX8YmKmqg92ttfeukl1NTUwGiUD5oTERENNYMnkkH9asSIEQgMDIRer5f0Wa1WKBQKJCUlnfUFTOQIgoCYmBgAgNFohMMhH1j7LVEUodfrERUVhbCwsL6c4im57LLLAABfbjmCGof0Cfv5/iWICg8E0P5n4PDhw3A6nf06RyIi6r7jg4QhISEnDBK+/PLL2LVrFwL8vJF50zAke8hvtfzJMAI3vrnXrS0zM9PtuCNIqNVqMXnyZNdWT6LBICYmBqGh7VuOuypqEqww4vLz2ouabN++HS0tLYOiqInNZoNOpzvl9DdERES9gYHCIcrLywtJSUloa2tz22LaEeyKjIxERETEAM5wYEVERCAuLg4A0NjYiNraWjQ1NcFisXR582YymeDp6YnExMQT/rA2UFatWgUAsNsd+KBUWv1YJThxy7wRruPnnnsOOp2u3+ZHRETd15Mg4SOPPIKvvvoKvt6eWH9rHMZ7ygdEsi3Dcekbh+E47iHRE0884fbQUBRFNDQ0wMfHB5MnT0ZQUFDvfSiiXhASEoLXX3/ddfz6DvkdIr9P6fw7s27dOhQVFaG+vl52bF8TRRG1tbXYunUrtm/fjsbGxgGZBxEREcBA4ZAWHR2NiIgINDc3u9rMZjPUajWSkpIGZbCrv3h4eGDKlCmYP38+zj33XIwbNw5arRYWiwV1dXWor69HS0sL7HY7gPYbPKPRiNjY2EH7Q5Ovry/8/dtXEq7KLJEtanJdfL1ry/TmzZtRWlrar3MkIqKT0+l03Q4Srlq1Ctu2bYOXpwfW/iERUzTyudjy28Kw+K1KtJo68/MuX74cc+bMcRvX1NQELy8vTJ48GSEhIb3yeYh6k1KpxKhRo6DRtKdUydxdgMK2Exc1+fHHH9HS0oIdO3agvLy8X1f0WSwW5OXlYdu2bWhoaIDJZEJ+fj5XFRIR0YBhoHAIUyqVSE5OhlKpdFX5bWlpQUxMzKANdvU3T09PDBs2DGPHjkVGRgYyMjIwbdo0xMXFQaFQoLm5GbW1tairq4OPjw9Gjhw50FM+obfeegsAUFqtw4aWeEn/cGUzLjq3fSuO3W5HYWEhDAZDv86RiIi6ptPpsGvXrm4FCW02Gz777DN4qFT47rbRONenTHZcsT0Yc99pRF1j57/3CQkJuP32293GGY1GCIKASZMmDcoUG0QdwsPDXfc8APBuYYDsuI6iJo2NjdBqtbDb7dizZ0+/BOpEUURVVRW2bNmCI0eOwNPTE6GhoQgICEBVVRVqamr69PpERERdYaBwiAsLC0NMTAwMBgOMRiO8vb0H7dbZgSYIArRaLeLi4jBlyhQsWLAAs2fPxsSJExEREYHExET4+fkN9DRP6OKLL3a9fmO3RXbMzWmdVa7/9a9/sRIgEdEg0ZOVhACwcOFCKBUKfHnbOMz3K5EdU+kIwNz3jaio7dzq6OHhgbffftttnM1mg8lkwqhRoxAZGXnan4WoLwUGBmLYsGFQq9vvad7OLDhpUZObbroJgYGBUKlUyMvLQ15enmvnSG8zmUzYu3cvtm/fDr1ej9DQUHh7ewNof0jtdDqRn5/f7TzZREREvYmBwiFOEAQkJyfD29sbBoMBCQkJgz7YNVh4eHggLCwMo0aNwnnnnYfk5OSBntJJqVQqV+7J77blo8IRKBkzz68E8cPbt5Pl5eWhpKQEVqtVMo6IiPpPR5DQaDR2K0iYnp4OAQJW3zoRSwOOyY6pc/ph3uo2FFd25mVTq9VYv3692ziHw4GmpibExsYO+dQkdGZQKBSIjY3F8uXLAbQXNfm+q6Imc0YBAMrKymA2m+Hn5wdfX18cOXIE2dnZvXoPJIoiysrKsGXLFhQUFMDb2xshISGutC8dAgICUFdXh8rKyl67NhERUXcxUEjw8/PDyJEjERYWhvh46XZUOrt0bCVzOp1475g0v5RCEHHr3DgA7duPGxsbeaNKRDSAGhoaehwkBIB3bp6Ey0OKZMc0On2w8L8CjhR3FjYZMWIE1q1b5zauo3hJSEgIJk6c6FbYhGgwGzZsmCtQCABvdFXUZGLn61dffRUAoNFoEBgYiJKSEuzYsQNGo/G052M0GrF7925X6oDQ0FBXHsXf8vDwgEKhQH5+vlvRQSIiov7AQCEBAJKTk3Huued2ecNCZ4/777/f9fqNzCK0idIf+q6JrYFK1d7+7rvvoqSkhNtfiIgGQEeQsKWlpUdBwpevT8P/RRTKjjGIGiz+2hO5+Z2pJWJiYvDOO+9Ixur1enh7e2PSpEnw8vI6jU9C1L+8vb0xYsQI106Z7hQ12bx5s6tdrVYjODgY1dXV2LZt2ylXInY6nSguLsYvv/yC4uJi+Pn5ISgoSLKK8LcCAgLQ0NDAwnJERNTvGCgkAO1bNBgkHBrUajUmTZoEAKisa8ZP+jjJmHCFAZfNbt+Kk5WVhcbGRtTV1fXnNImIhrzGxkbs3r0bBoMBoaGhJwwSOhwOV5DwHytTcXt0gew4k6jGsh98sfNAiVv7Bx98IB1rMsHhcGD8+PEsckZnpKioKNxxxx2u43dOUtSktbXV7cGoSqVCWFgY9Ho9tm/fjqqqqpNe0+l0orm5GaWlpdi3bx82bdqEPXv2wGazISwsDJ6ent2au1KphKenJwoKCmCxyOeVJiIi6gsMFBINQf/4xz9cr1ftapUdc9Okzn8eTCYTSkpK+rwCIBERtesIEra0tJw0SLh582bMmzcPAPDo5al4IEF+JaFF9MDy9cHYnOO+HTkrK0sytq2tDS0tLUhMTERMTMxpfBKigRMSEoK5c+e6jt/ecPKiJrfccotbn0KhQEhICCwWC3bt2oWioiK3+6G2tjbodDoUFRVhz549WL9+PbKysrBz504cPXoURqMR/v7+CAgI6HF+T61WC71ej2PH5POMEhER9QXp/5REdNY7/qb5p+0FKM6IR7xK5zZmjm8pkmPDcbS0Fv/+97/x2GOPobm5GYGB0gIoRETUe5qamrB7925XNdQTBRdef/11/Pe//wUAPLJiEv46Sj5I2CYqcdXmcPy045Bbu1yQ0Ol0orGxEVFRURgzZgyLl9AZSxAEjBgxAhEREaipqYGuyYDvm1JxaZD735OOoib/2XAAhYWFMJvNbjttBEFAcHAwDAYD9u7di9bWVnh6eqKhoQGNjY2wWq2w2+1QKBTw9PSEj48PPDw8TvvvjkKhgI+PD4qKihAdHc2Cg0RE1C+4opBoCFIqlRgxYgQAQISId7vYivOHudEAgL1798JqtWLv3r2nnKOHiIhOrrm5udtBwvXr1+O///0vBAAv/V8a/jZavnCJQxTwf9ui8PUvJw8SiqKIxsZGBAYGIiUlBSoVnynTmW3YsGF44YUXXMevb5cvanLTcUVNVqxYITtGq9XC29sbhw4dQm5urmsrslarRVhYGEJDQ6HVaqFWq08aJCwtLUV6errsr9///vfQ6/UAAF9fX7S2tqKwUP4hABERUW9joJBoiMrOzna9fnNDofxWnOFVUKtVEEURgYGB0Ol02LZtG7chExH1gebmZuzatQvNzc0nLVzywAMP4Omnn4ZKqcDHt03CHTHyOQkB4NbsOKzO3O/WJhckBICWlhZ4eHhg4sSJ8PHxObUPQjSIeHp6YuzYsa7jjXsKUNAWJhl3rk8ZRv+vqInRaOyy0rG3tzfCw8MRHh6OkJAQ+Pr6dnv1oMPhwLZt25Ceno7rrruuy3GFhYW46KKLkJGRgaamJmi1WpSWlvJhLRER9QsGComGqICAANfrukYDvm+Kk4wJVhhx5ZzRAIAlS5YgNDQUdrsde/bsQW5uLmw2Wz/Nlojo7KbX67Fr1y40NTUhJCTkhBVRFy1ahF27dsFH44k1d43DFSHyKwkB4J68kXjrx31ubV0FCS0WC6xWK8aOHYvw8PBT+yBEg1BUVBRef/111/G7Bf6y4zqKmgDA3/72ty7Pdypbin/44QfMmzcPjzzyiGx/sL8PLjwnCXPTRrj+/ouiiOXLl+Pqq6+G1WpFQUEBH9QSEVGfY6CQaAi75pprXK9f366XHXPzRCcAwG63o66uDgEBAfDx8UF+fj62b9/u2hpDRESnRq/XY+fOnWhubkZoaOgJg4Tp6emwWCwIDvDF5jtHYL5fiew4pyjgjwdG4sWvc9zauwoSOhwO6PV6jBgxwpWaguhsERAQgHHjxrmO384sgEX0kIy7KqoaXp7t7Tt37uy16y9cuBDPPfecbF9q8nB8eGsqKu7ywrfzapB5gQ5b7xsNX+/O6sjNzc1YuXIlKioqUFdX12vzIiIiksNAIdEQdvzT9Y17ipAvsxVnhnc5xo8cBgC49dZbAQAajQbBwcGoqanBr7/+ivLycj7hJiI6BQaDodsrCdPT0wEAMcOC8OsfIjDZq1J2nE1U4rodsXjuy+4FCUVRhE6nQ0REBMaPH3/CORCdiQRBQExMDF599VUA+F9Rk1jJuGCFET/eNgqe6vZg4Q8//HDa105PT5fswFAoFFgxZzS2/nEcsq9owe/CCuEltLn6Z3iX48WV49zeY7fbcfPNNyM/Px9Op/O050VERNQV3gkSDWEajQahoaGu43fytbLjbkuPBNBeibODSqVCWFgYLBYLdu3ahQMHDsBut/fJPEVRhF6vR0lJCfbs2YMDBw6gra3t5G8kIhrEDAYDdu7cicbGxm6tJASAcQnDsO0GXyR7yK8qahU9cXFmOP6zPs+tvasgIdD+b7ufnx9SUlKgVqtP4ZMQDX4RERFISEhwHb+x3SA7LsOvFGvvGAUvTw8899xzcDgcp3S9xsZG19/bDgFaHzx42SQceygG/z2vEuf4lHX5/v+LKMTM8XFubQ0NDbj77rtRWSn/kICIiKg3MFBINMQdX0Xv7fVHZbfiXB5RCW+v9h8ej3+6LggCgoKCoNFocOjQIezYsaPL5N89ZTabUVVVhQMHDmDjxo3YtGkTdu7cieLiYhw8eBDbt2+HwSB/k09ENNh15CTsSZDwnAlx+OUqYLiyWXZcg9MX8772xZptR9zaTxQkbGlpgSAImDBhAvz95fO2EZ0NPDw8EBMT46povHFPIfZZI2XHpvuW4qfbR8HbS40nnniix9datmwZli9f7joeM2IY3ropDRV3e+PpMUWIVZ28KIlCELFqiafk34acnBy88cYbffZwloiISBAH8X5Bg8EAf39/6PV6aLXyK52I6PSFh4e7ct6s/kMargqVVs+8eU8c3vyxfYVKZmYmlEqlW39bWxsaGxsREBCACRMmICIiokfJvu12O5qamtDU1IS6ujo0NjbCarVCFEWo1WpoNBqo1WoIggC73Y6GhgZotVpMmDABkZGRp5RYnIhoIOh0OmRnZ580J6HD4cC8efMAAEvPScancxvgLcgXkSp3BGLhxzYcPlbt1n6iIKHZbIbRaMSECROQlJTEf0fprGcwGLBu3TpXsDAlKQpZl9sRoDDJjt/SGoPzXynA/Q88iDlz5nTrGsevIlwycxTumaHGXN+SU57z/fsT8K+v9kra8/PzkZiYeMrnJSKioaUn8TUGCokIa9euxeLFiwEA56bEY8uyBsmYbMtwTP7nYQDA7373O1x//fWSMaIoorGxEQqFAiNGjIBarYYoim6/nE4nnE6n27HD4UBjYyPMZjPsdjtUKhU0Gg28vLy6/AG641qCIGDUqFFITk6WBC+JiAab6upq5OTkwGQyISQkpMvg3ObNm/Hkk08CAP7v/Al4Y2o5PAT5LZCHbeFY8G4DKmrdVymdKEhos9nQ1NSE5ORkTJw4kUFCGhJEUcSuXbvw2GOPYcOGDQCAKWNisG55GwIVrbLv2doag/NfLcC33/940vuMjiDhtHGxeH6RH2Z6d721+LccogClIP2xzCBqMOZ1Kyrrmt3a/f39UVNTAy8vr25fg4iIhi4GComoRxwOB1Qqlev4wENJGKuukYyb8l9/7DlSDkB+VWEHo9GI1tZW1w+eHf/MdBwf/wNpx2tPT094eXnBw0O69flEWltb0draiujoaEyYMAE+Pj49ej8RUX8QRRFlZWXIzc2F3W5HUFBQl8G5l156CV9//TUA4MHLUvH0mELZcQCwwxyNJa+XoNHgHuQ4UZDQ4XCgvr4ecXFxmDx5stu//0Rnu6qqKmzbtg2XXXaZqy1tdAzWX9qGoC6ChdtM0Th/1TF89/0a2X6z2YwlS5YgJiII/7wkFpeHdP139rfK7EFYVRCM97IKsfX3IRjpUS8Z81VjApa/LF1VuGPHDkybNq3b1yIioqGLgUIi6rGxY8fi0KFDAIA7L0rBvycek4x5ryYR17+RDQD461//inPPPbdf59iVjpUxgYGBSElJQViYtHozEdFAEUURBQUFOHDgABQKBfz9/bsMEl5wwQVobW2FQhDw6g2puGW4NBVEh7WGEVi+6jDMFqtb+4mChE6nE/X19YiIiMC0adO4GomGHIfDgU2bNqGqqgrXXXedqz11VDTWX+ZAsEI+1/J2UzQWvFqE739c69b+4IMP4tDBPDy+fAxujy1xq158IltbY/DSHhFf/nLYVcV44bQk/HS+9EEtACxZF4E1O/Ld2hQKBQwGAx+SEhHRSfUkvsZiJkQEANi6davr9fuZR9EqekrGXBZeBj9fDQDgb3/7W7/N7WTUajVCQ0NhMBiwfft2FBQUuG66iYgGktPpxKFDh5CXlwcPDw8EBAR0GSRMT09Ha2srNF5qfHvnxBMGCT+qT8TSf+f1KEgoiiIaGhoQGBiI1NRUBglpSFIqlYiLi4OXl5dble+cI+WY95kCOqev7PtmeJdjw+0jcOEFi/D6669jzZo1mDd3LqaGW1F4TxD+GFdw0iChRfTAf+oSkfZff8z61wF8vvkgnE4n3n33XaxZswbrdubj88aRsu99ZW4bPNXuq387/n0hIiLqTQwUEhEAIDAw0PVE2mA04/O6GMkYX8GK6+YmAwCsVitee+21fp3jiSgUCgQHB0MQBOTm5iI7OxsWi2Wgp0VEQ5jdbkdubi4OHjwIb29v+Pn5dTm2I7dZaKAfNt85EhcESFd1d3ihNAm/ey0bjuMeiKhUqhMGCQGgqakJGo0GqampJ5wL0dkuMjISGo0Gq1evdmvPPVqBef9VoN4p//djuqYCmbeNwNofv8PhX7/D/gcS8NKkYwhTtJzwejUOLZ7MT0TMK224ZlU2cv6XxmXy5MnIyspCfHw8NBoNsrKycNd/j0EvaiTniFc14IkVEyXts2fP7u7HJiIi6hZuPSYil9LSUsTFxQFoT+6967Jm6Rh7EGa/Y0BZTXvS/HXr1rk9ke8NZrMZzz//PDZu3IgT/RM1f/583HPPPdBo3G+orVarq5poSkoKgoKCenV+REQnY7VakZubi5KSEvj7+59w9V5GRgZEUURidCh+usYPI1S6Lsc+dGgk/vF5jlvb5MmT8eyzz55wPi0tLbDb7ZgyZQqioqJ69mGIzkLZ2dkoKirCc889h127drn1TUgcjg1XoMsAYIPTt8styscziWq8eCwWf//qAFpN7qt/16xZI7l/6fDtS/fihQlFknaLqELKBx44Wlrr1m4wGBj8JyKiE2KOQiI6JaIowsfHB2azGQCQ88AoTPKqkoyrcARiwWorDhfXYMKECfj3v//dK9evrq7GypUre7xtODU1Fc8995xbm8PhQENDA3x9fTF79mz4+spvJSIi6m0mkwnZ2dmorKxEUFBQlw9THA4H5s2bBwCYMT4O317UhtAuAhMW0QM3bhuG1ZkH3NqXL1+O22+//YTzMZvNaG1txYQJE5CUlHQKn4jo7FNbW4utW7fCz88P559/vuTB5LiESGRepUC4wtDjcztFAR/rRuKhL4+horZJ0t+d1b/xux5Giqf0HizLGIuM5/a7ta1cuRL/+c9/ejxPIiIaOpijkIhOiSAI2L59u+v4rUPSPIUAEKVswi8rFZgyJgZ5eXmw2Wyndd3a2lqkp6fjqquu6jJImJY8HI+smITXbkjFHRdOgIeqs+JyTk4O0tPTUVvb+YRdqVQiNDQULS0tOHas6y18RES9yWAwYMeOHaisrERISEiXQcLMzExXkHD57NHIvNjYZZCw2emNxT8GSoKEl19++UmDhDabDS0tLUhMTERiYuIpfCKis1NoaCiCgoLQ0tKCH3/8UdJ/oKgKGasdqHH0bLHCz62xmPqZFr97LfuUgoRAezqY29bY4BCl+UzTfUuxct5Yt7bPPvusR3MkIiI6Ea4oJCI3JpMJgYGBsNls8FCpkP3HBIz3rJYd2yJ6YflaLTblFCMzM7PH16qursZVV10l2xca6IfFU2KxcKQaGUF1CFe6P9Hfb43A+e/Uoqpe79auUqnw008/QalsDyQajUY4nU6kp6dzWw4R9ammpibs3r0bTU1NCAkJcf079Fs33XQTCgraC5XctSwFz00shlKQvx0rcwRh8SdWHCxy/3e4O2kf7HY7GhoaEBcXh8mTJ3c5H6Kh6tixY9i9ezdCQ0PxyCOPYMeOHZIxo0cMw6arVIhQ6mXO0Cm/LQwP/KLCN1uPdDmmO0HCDkajEVXfPYmbIvMlfTUOLZJfbIDBaHa1mUymLrcyExERcUUhEZ0yb29v15P1Nrsdi9+rx2FbuOxYP8GC7xY1YvmsJFxyySXdvobZbHatIOygVCgwJzUe/7wmDTkPjELNHQq8P6MMV4YWSoKEADDeswY7bgrAuBERbu12ux3z5s3DL7/8AgCurdRcVUhEfclsNiMnJ8eVH7WroNySJUtQUFAAAcDz16XhxZRjXQYJ91kjMf2NJkmQMCsr66RBQqfTiYaGBkRERCAlJYVBQiIZkZGR8PX1RWtrK55++mnZnMaHj1Uj/aM2VDsCZM+hc/ri7rwEjPlncZdBQq1W26MgIQD4+vribz+Wo9Yp/WEuQmnAP68Y49YWEyMtQkdERHQqGCgkIokxY8bA398fAFBR24hzX6vGbot88nsvwY6PZ1fhspnRyMjIOOF5jUYjli1bhsWLFwMAggP88IelKfjurkloeDQUWUsb8Kf4AkzyqoKiix+cjxetasKWq4GM1HhJ3xNPPIFffvkFgiDAx8cHpaWlMBh6nmeIiOhknE4n8vLyUF9fj5CQECgU8rdXy5Ytg8lkgtpDhc9un4R7Ygu6POeGlnic+1IJqn+zaro7wQZRFKHT6RAYGIi0tDR4esqnkSAa6ry8vBAVFQWTyQRRFPHll19i+vTpknFHSmqQ/h8riu0hrjaLqMILpUkY+WIz/v31XjgcDtlrXHLJJfj2229PaX5vvP0e/rRTviDb7yMLMWVMtOtYp9PBaDx5gRUiIqKT4dZjIpKw2+1Yv349lixZ4mrz8fbEt7cmY65vSZfve/jwSDz9WY5kS5zRaMRll10Gi8UCtdoDy89NwsoJHpinLYVakL+x7gmLqMINWyPw8aZDkr7MzEwoFArU1tZi9OjRmDhx4mlfj4joeEeOHEFeXh4CAgK6XOk3d+5cOJ1OaH01+PGWBJzrU9bl+d6vTcKNb+bAcVzOVo1GgzVr1px0Lh0rCb29vTF9+nQEBwf3/AMRDSENDQ34+eef4ePj4wqqm81m10PN42m81Lh0djJ8PRX4bmcpKuuaT3ju7qQIOJnFixdj7W0jcZ5PqaQvxxKJKc8chfN/P85NnDgRubm5p3U9IiI6O7HqMRGdtkOHDuHNN990q2jsoVLhk1snYHlQYZfve6E0Efe+n+3WJkBAeloCrpnij2WhlQhQmHp9vk5RwCOH4vGPL3IlfVlZWWhtbYXD4cB5553nWi1JRHS6qqursWPHDnh4eHRZXT09PR0AEBLgh8xbIjGxi7yvAPCXgiQ88fEet7YRI0bgnXfeOelcOnISBgYGYtKkSQgNDe3BJyEamkRRxNatW1FbW4uQkBC3vo4Af09FR0fjww8/PKW5OJ1Ot1QBH3/8MbZu/AF7V1rhKdgl77krNx4vfbvPdWy325lqgIiIJJijkIhO27Bhw3Deeee5/eDbZrfjsldy8XZ115Uz74ktwPu3pEGhUGBswjA8e20aSh6NxcYL6nBteMEpBQlL7MF4pyYJV26NxS5ztOwYhSDi6bHH8NoNqVAI7lUC09PT4e3tzVyFRNSrWlpasG/fPjgcjpMGCYeHBWDLH8K7DBK2iUrcuCteEiRMSkrqVpDQYrGgoaEBkZGRmDlzJoOERN0kCALi4uIAtBcEOd7GjRvx8ccfd/tcqamp+P7777sVJPx/9u47Tq6q/v/4a+rubO8lm2x2syW9F1IoSQhERapIEQEVRSz4lS8iIvrzi4qIiAUFRRQLKEiREggEUpAA6b33bNr22Ta7O/3+/lh2NsPMloRkk919Px+PfXDvPWfunFHYnXnPOedjGAZ+v5/m5macTieVlZVUV1dTXV2Nx+MJ9bv66qvZsb+c3xwcFvU+942rJCej4wPfG2+80ePxioiIRKMZhSISlWEYLF++nLKyMm666aaI9gdunMz3hnW+v1Z5IJncbioEdqbFsLPclcfbZRZeW1/OrgMdH6xjY2J47rZRXJqyr9PHL6gbxjWPb8Pt8YVdf+211/D7/VxwwQWkpKSc1NhERAB8Ph+rVq3i6NGjZGVlYfrIFxTQERIOG5zB4psTKbTWRr1Xo+Hg2rdSeHPlrrDrV199Nd/4xje6HUtTUxNut5uioiLGjh2LzWY7iVckMnAZhsHWrVvZsWMHSUlJxMbGRvQ5evQot9xyS1iIB21h/i9+8YtuVysEg0E8Hg8ejwev14thGFitVmJiYkhKSiI9PZ2kpCTKy8s5cOAAmZmZof1OL7roIqwWM9u/kxf198hTVcXc9If1AFgsFvz+yJmHIiIysGnpsYicEgcOHGDNmjX84Ac/YM+eyFDwO5+ZxENjOl+GfCK2e7NZXJnMwm2NLNuwH6+38ze5JpOZR788ma8N2tVpn1Wtg/n0nw5RU9+xsfeUKVP4zne+Q0lJCZMmTTol4xaRgccwDDZv3szOnTtJT0/HarVG9GkPCUcPy+Htz9k6/eKkIpDMp56HDbsOh13vyd5mhmHgdDqxWCyMGjWK4uLiTgupiEjXAoEAGzZsYN++faSlpZ2SwN0wDBoaGvB4PJjNZux2O/Hx8aSnp5OSkkJSUhKJiYlh/623tLTw3nvv0djYGFoKXVlZyXXXXcenZ41gwbxjEc/jNqyk/6KZFndbiFlfX69tVkREJIyCQhE5JVpbW1m8eDEmk4kbb7yR+vr6iD5f/MQ4Hp92GNtJFCU54E/n34fS+Nu7R9hVVhm1T05ODk888URoWZ/T6eQzn/kMAN+7ZjL3j9jbaYXkvb5MPvGPBvYdqQlde+GFF7BarZpVKCInraysjLVr1xIXF4fD4Yhobw8Jp4wYwhufDZBhjl6J9KA/nYv+4WLv4eqw6z2pbBwIBKipqSEpKYnx48czaNCgk3glInI8n8/H2rVrKSsrIyMjI+qXAD1lGAa1tbXY7XZKS0tDwaDD4Yg6A/l4x44dY+XKlcTGxhIXFwd0/F55+VsTuTw1clXFJYtyWLhyNwAzZ87k/fffP+mxi4hI/6M9CkXklHA4HOTl5dHS0sJLL70UerN6vL++uZnPLs2m1ehZVb+6YDx/KS/h/FcyGHb/Ae55al3UkPC8885j0aJFPPPMM2F7f6WlpbFs2TKuuuoqfv7cOm5aMRS3Ef1b/2JbNR98MYZzRnfsa3j11VfjdrvZt28fZ/H3JCJylnI6nWzZsgWLxdJlSHjehEIWX+PtNCTc5cvivD83nFRI6PV6qa6uJisri5kzZyokFDlFbDYbEydOJDc3l9ra2pMqZAJty4yrq6uJj4/nnHPOYcSIEeTk5BAXF9dtSAht+0QXFxfT1NREIND2Rey0adMAeOi/9VEfc+HwxNDxhg0bTmrcIiIioBmFItKNiooK3nvvPVJSUrBarVx++eU0NjZG9JszqYiXPu0i2dQa0eY2rLzVMJSnN3l4+b3d+LrYOycnJ4enn366RxX7vF4v8+fPZ+6UYl78pKvTQilNRiznPGVmx4EKACZPnswPfvADLrjgAlJTU7t9HhERaCsY8sEHH1BTU0NmZmbEB/72kPAT55Twwvx64k2eaLdhsyeXeX8qp9rZ8bvUbDazZMmSbsfQ3NxMc3MzQ4cOZfz48VH3UhORj6e5uZkVK1bgdDqj/rfelfbq4+np6UyePPmk32d4vV4++OADqqqqyMzMpLm5mUsvvRSLxULdvekkmtxh/de685j64I7Qucfj6Xb7AhERGTg0o1BETpnMzEySkpJwudpmxbzyyivk5ORE9Fu2fh9zn7Oxzp0XuraiZQjfXD+M3N94uPy3G3j+ne2dhoRWq5UFCxbwzDPP9CgkBLDb7SxatIila/dy/rMWDgeivxlPNLn53ZVZofN169bR1NSkWYUi0mPBYJAtW7ZQVVVFenp6pyHhZ84fyUvzazsNCVe2DuH8x46EhYQOh6PbkNAwDOrq6nC73YwZM4YpU6YoJBQ5TeLj45kyZQpJSUnU1NT0+L2C1+ulpqaGnJwcZsyY8bG+jLTb7YwdO5bY2FiamppISEggJiaGQCDASlduRP8JMeUkxnf8Tnj44YdP+rlFRGRgU1AoIl2yWCzk5+fjdrtDb5SfeeYZhg8fHtF3/c4jTHlwBwV/spP0sI+ZD23j0QUbqW9s7vI5FixYwNtvvx22xLin7HY7l156KVv2HGXGE41s8US+eQa4MPEgcycNC53fe++9HDlyhLq6uhN+ThEZePbs2cOBAwdITU2N+DKjPSS8+eIxPDu7nFhT9C9ElrkKuPB3e2k47nfitGnTWLhwYZfPHQgEqK6uxmazMXXqVEaOHNnjL1RE5OSkpKQwefJkHA5Hj94ruN1u6urqKCgoYPr06cTHx3/sMaSnpzNixAjcbjder5dzzz0XgP8ejfzv32oKMmfC0NC5gkIRETlZCgpFpFu5ubnExsbidncsc/njH//IggULovYvK6+hyRW5BPl4cXFxPPfccyxbtuykAsLj/e///i8ARyvrmPX7Qyx1FUTtd/+FHd+0Hz58mJaWFs0qFJFuVVZWsmPHDhwOBzExMWFt7SHh7ZeN58nph7Gaou9p9lpDEZ/43XZaWjtmGl599dU8+OCDXT632+2mpqaG9PR0ZsyYQX5+/gktgxSRk5eZmcnEiRMxm800NESvXA5tS5UbGxspKSlhypQpEb8nPo6ioiIGDx5MXV0d8+fPB2Dx1pqofS8s7Xg/VVtbG9rfUERE5EQoKBSRbiUlJZGVlUVDQ0PYxt4JCQksW7aM5557rkcVhM1mM/fccw+LFy/m9ddfJzMz84THEggEom4u3l4AoMnVytVP7KM+GFl4ZXrcES6d2TET8gtf+AJHjhzB6XSe8DhEZGBwuVxs2rQJv98f8aVGe0h499UTeWTigU4rsD9bU8IVj2zC6+2YafjDH/6Qb3zjG50+r2EYNDQ00NTURFFREbNmzSI9Pf0UvCIRORF5eXmMGzcOv98f2obleI2NjaEtASZMmPCxKiVHY7FYGDt2LElJSRQUFACwZseRqO9zzs8KX8Hx6quvntKxiIjIwHBq/5KJSL9kMpkYN24cLS0tUTfxz8zM5KWXXjotz20YBh6Ph9bWVrxeL2azmUAgQHp6OjZbeLXjBQsWcOmll1LX2Mxv9o7g/0r3RNzvp+fDgg/ajn0+H48//jh5eXmkpaVplo6IhGloaGDz5s3U1dVF/N47PiT8+eh9nd7jLxWlfOXxdRh0hIg//OEPmTt3bqePCQQCOJ1OYmJimDRpEoWFhZjN+m5X5EwpLCzE4/GwdevWUMXz9n1DzWYzEydOpLCw8LS9j0hMTGT06NGsWbOG3NxcysvLWdGUwyeT94f1GxtTTnJiHA1NbcXdvvGNb3DllVeeljGJiEj/pXedItIjCQkJTJ06leTkZKqrq0/rcl2/309TUxPV1dVUVVXhdrtJSkpizJgxnHvuueTn5+N0OvH5fBFjTEtLA+CXr2ylKpgYce9xMeVcN3d06HzRokUcOHCA2tra0/Z6RKRv8fv97Nq1i+XLl3Ps2DHS09PDgrpPfvKTQPch4a/LSvny42vDQsJrr722y5DQ7XZTXV1Neno6s2bNoqioSCGhyBlmMpkYPnw4JSUlNDY24vF4qKmpwW63M3XqVIYNG3bav2wcMmQIhYWF3H///QC8cyTy94LFZDBvYsc+heXl5ad1TCIi0j9pRqGI9FhycjJTpkxh1apV1NbWRq38eTIMw8DtdtPa2orP5wt9W19QUEBmZiZpaWkkJiaGnqv9eQ8dOkRaWlrYzMJnnnmG+fPn09zi4Rfbs/nlmKaI57tvuofn3jGHljA/9thjFBQUnLLXIyJ9V01NDdu2baOyspLY2FiysrJOaibhfbtL+L9n1oZd62omoWEYNDY24vP5KC4uZuzYsad0nzMR+XjMZjNjx47F6/Wyb98+0tLSmDRp0klto3IyTCYTo0aNCm2XsnhrNYyO7De3JJ4X3+2VIYmISD+loFBETkh6ejqTJ09m9erV1NXVkZqa+rHCtebmZpqamnA4HKSmppKbm0taWhqpqakRS4vb2e12Jk+eDEBZWVnYMmS73c5VV13Ff/7zH363YDPfHpnHYEt4tcJSWxVfmj+GP7+xGYB3332XQ4cOMWzYsF57wy8iZxePx8Pu3bvZt28fPp+PtLS0iL3G2kPC73YTEn53WzEPvbAu7NqPfvQjZs+eHbV/IBCgtrYWh8MRWmqsLy1Ezj4Wi4UJEyaQkJBAXl4eycnJvfr8sbGxjBs3jsTERDbsPIIzmEOaOXxfwvOzGsPOA4GAqqSLiMgJ0VoWETlh2dnZTJo0CYvF0mUVwK4Eg0Fqamrwer2MHj2auXPnMnv2bEaMGEFWVlanIWG79rBw6NCh1NbW4vV6Q2233347NpsNr9fPTzemRn38Dyc1YjsuBHjooYfYu3evKiCLDDCGYXDs2DGWL1/O9u3bsdlsZGRkhIWEgUAgLCR8sIuQ8K6txTz0wvqwa/fdd1+nIWH7UuOMjAxmzZrVK0sYReTk2e12Ro0a1eshYbusrCy++MUvYmDwfmNORPsYewUZKR2Fl370ox/15vBERKQfUFAoIiclLy+P8ePHEwwGaWqKXN7bFY/HQ1VVFUlJSUyfPp0xY8aELS3uqfawsKCggLq6urCw8JVXXgHgzws3s9cXOUsw3+rk658eEzpfs2YNhw4doqqq6oTGICJ9V0tLC+vXr2fFihXU19eTkZFBfHx82O+id999l3nz5gE9Cwl/+WJ4SLh48WLOP//8iL6GYVBfX4/L5aKkpIRZs2aF9lgVEenKAw88AMA7h6O/bzp+n8Kf/exnBAKBXhmXiIj0DwoKReSkDR06lLFjx+LxeGhubu62f/sH46amJoqKijjvvPPIzc39WLNn7HY7kyZNYujQoWFhocPhYPTo0QSCQe5bExf1sd8bU0NcrD10fuedd7JlyxZaW1tPejwicvYLBoMcPHiQ//73v+zZs4e4uDgyMjIilue9++67odk4d32m65Dwu1FCwmXLlkVd8mcYBk6nE7PZzOTJk5k0aZL2IxSRHouLiyMhIYHFWyqjts8pjg0dG4bBW2+91VtDExGRfkBBoYicNJPJRHFxMaNGjaKlpaXLgM3n81FVVYXNZmPy5MlMnjwZh8NxSsZx/DLk48PC3/72twD88+2tbPXmRjwux9LI/17eMavw6NGjlJeXs2XLllChExHpX5qbm1m1ahVr1qzB7XaTlZUV9XdRIBAICwl/MaabPQmjhITRGIZBbW0tMTExTJs2TfsRishJKSgoYPOeo1QFEyPazs8M3xbmV7/6VW8NS0RE+gEFhSLysZhMJkaMGEFpaSmNjY243e6wdsMwcLlc1NXVMWjQIM4991wKCwsxm0/tr5/2ALKgoACn04nX68VisTB37lwMDP7fe9E/iP9vaTlJCR0hwTPPPMPBgwfZs2fPKR2fiJx5LS0trFmzhrKyMpKTk0lNTe30d1H7cuPvXNV1SHj3tvA9CWNjY7sNCWNjY5kyZQo5OZH7i4mI9MTnP/95AN5vyIpoG2GrIjs9KXReX1/fW8MSEZF+QEGhiHxsZrOZMWPGUFxcTENDQ2hGX3vBEr/fz9ixY5kxY8Zp3fzbZrOFKoa2zyy8++67AXhp+U5Wtw6OeEyquZl7rhwVOn/zzTdxOBzs3LlT+xWK9COtra2sWbOGiooKMjMzsdvtnfZtL1zynasm8tDYrkPCX3ykcMkbb7wRte/xIeHUqVMVEorIx3LHHXcAsKwsehG2iyYOCR37fL5eGZOIiPQPCgpF5JSwWCyMHz8+NKPP5XJRXV1NamoqM2fOZOTIkWFVRE+X9rCwvcAJwLBhwwC4d1n0N8rfLDxEZmrb0h3DMPjrX/+Kz+dj48aNtLS0nPYxi8jp5Xa7Wbt2LeXl5VH3IjzexwkJu5tJ6HA4mDp1KtnZ2SfxKkREOtjtdq666ioWb66I2j63qGOfwk2bNoUVfBMREemKgkIROWWsVisTJ05kyJAheL1eSkpKOPfcc8nKilwWczp9dGbhb37zGwAWr9nDO66hEf0TTB5+eGVp6Pyll14iISGBuro6Nm3apGqBIn2Yx+Nh3bp1HD16lIyMjC6/sGgPCe++uuuQ8HsKCUXkLHD11Vez40AF5YGUiLbz0uvDzh955JHeGZSIiPR5CgpF5JSy2+1MmTKFWbNmMXHiRGJjY7t/0Glgs9mYOHEiGRkZeL1epk+fDsD333ZF7f+VwQcZkpMaOn/44YdJTU3l0KFD7N69G8OIvrRHRM5eXq+X9evXc/jwYdLT03sUEt5zzSR+3kV14+9tL+HBEwgJa2pqiIuLY9q0ab3+pYmI9G+5uW2F2pbXZ0S0FduqGZzd8b7m5Zdf7q1hiYhIH6egUEROuZiYGLKzs894JU+bzUZpaSnBYJAf//jHmEwmVmw+wOsNwyL6xpp83Hd5x/XFixdjsViIj49n586dVFREX9ojImcnn8/H+vXrKSsrIz09HZvN1mnf9pDw/103iZ+N3Ntpv3u2F/Pg8+vCrnUXEsbHxzN16lQyMzNP4lWIiHTuvPPOw2Kx8E5Z9JUP8yZ07M186NCh3hqWiIj0cQoKRaRfy8vLIzs7m/r6eu6//34A7l1YQ9CIDDE/n72fkiEdH+bvu+8+EhISCAQCbN68GZcr+mxEETm7+P1+NmzYQFlZGWlpaT0KCe+7fjL3De86JPz58yc2kzAhIYFp06YpJBSR08JisTBy5Eje3ngsavucYR1Fm44cOaKtVEREpEcUFIpIv2Y2myktLcVsNjN+/HgANu0+wgvOooi+NlOAn1zWUSVw+fLleL1e0tPTqa+vZ9OmTfj9/l4bu4icOL/fz8aNGzlw4ACpqak9qm58/+cn8/9K93Ta7+5tJxYSVldXk5CQwNSpU8nIiFwSKCJyqlx66aXsPVzN4UBqRNt5ac7QsWEYLFmypDeHJiIifZSCQhHp97Kzsxk0aBAul4sLL7wQgB8uOILPiKx8+tn0fYwvzQudP/XUU5hMJtLS0jhy5Ag7duzQfoUiZ6lAIMCmTZvYt28fKSkpXYaEF110EQAP3jSZ7xd1HhLeuSWycMmiRYui9m0PCZOSkpg2bZpCQhE57drf1yx3Rv6+KbTWUjAoPXT+j3/8o9fGJSIifZeCQhHp90wmE6WlpdhsNr75zW8CsLusiqcrI/cqNJsMfvrJjmWCTz/9NNC232FCQgJ79uzh6NGjvTNwEemxYDDI5s2b2bdvH8nJycTExETt5/V6mTNnDn6/n1/ePJnvFnYeEv7PpmH86j/hIeG1114bNYD0+/1UVVWFQsL09PSIPiIip9rs2bOxWCwsO+CL2n7RhI4vP994443eGpaIiPRhCgpFZEBIS0sjPz8fj8dDQUEBAD965QBuI7IK6qdT9jN9TH7o3Ov1AhAfHw/Ali1baGxsPP2DFpEeCQaDbNmyhT179pCUlNRptfU//vGPzJ8/H4Bff3EydxZ0HhLevmEYj7y8Mezatddey2233RbRt7m5mdraWnJzc5kxYwZpaWkn/2JERE6AxWJh5syZvL0x+peYcwo73uc4nU5aW1t7a2giItJHKSgUkQHBZDJRXFyMw+HgF7/4BQCHK5z85WjkrEKA++cnh47bgwWA1NRUGhsb2bhxIz5f9G/vRaT3BINBtm7dyq5du0hMTOw0JPz973/Pv//9bwAe+dJkvp0fPSQMGia+tq6Q37+6Mez6okWLIkLCYDBITU0NXq+XsWPHMnPmTJKTkxER6U0/+MEPKCuv5YA/cibzeam1Yeff/va3e2lUIiLSVykoFJEBIzk5mcLCQgKBAImJiQD8+KXduIzIJYpzE8qYO7k4dF5ZWQm0BY7p6emUl5ezfft27Vcocga1VyTfuXMnCQkJOByOqP3uueceXnzxRQD+8OXJ3D6k85Dwq2uH8sfXNoVdX7ZsWcRyY7fbTXV1NcnJycycOZORI0ditUbOUBYROd069imMnM082FJHyZCOLVUWLlzYa+MSEZG+SUGhiAwoRUVFJCYm8vjjjwNQ5WzksYP5Ufvef2FHgHjTTTeFjq1WK4mJiezbty8UIIpI72ovXNI+kzAuLi5qv1tvvZWVK1cC8PhXJnNbXvSQMGCY+PLqofx54eaw6x+tbmwYBvX19TQ1NVFUVMS5555LdnY2JpPpFLwqEZETZ7FYiI2NZdl+b9T2iyYMCh0fOXKkt4YlIiJ9lIJCERlQ4uLiKCoqwmw2Yza3/Qr82Us7qA9GhgzTHYe5dNZwoG2fwva9CtvvEwwG2bZtW9h1ETn9/H4/GzZsYO/evSQnJ3c6k/Caa65hz549WMxmnvr6ZG4dFD0k9BtmvrQyn7++2XVI6PP5qKqqwmazMXXqVCZPntzpc4uI9KasrCze3nA4atvsoZaw84aGht4YkoiI9FEKCkVkwCksLCQlJYU//elPADQ0tfDrPYOi9v3JeR2zhD73uc+FtaWmplJTU8OuXbtO32BFJIzP52P9+vWh6sad7Ul48cUXU11dTYzdxiu3j+PzmZ2HhF/4YDD/eGtL6JrVag0LCQ3DwOVyUVdXR15eHueeey4FBQWaRSgiZ41Zs2ZxtKqePb7MiLbzUqrDzj/5yU/21rBERKQPUlAoIgNOTEwMJSUloX0KAR5+dRtVwcSIvuNjjnHd3NEA1NbW4nK5Qm0Wi4WEhAT27dtHdXV1xGNF5NTyer2sXbuWAwcOkJqaSkxM5P6i0FaAyOfzkZjg4O1vjeCSlP1R+/kMCze+l8c/F28Nu/7222+HjtsLlvj9fsaOHcv06dNVsEREzjpf+MIXAFhemxrRlmNpYGRhTuh827ZtvTUsERHpgxQUisiAlJ+fT3p6On//+98BaG7x8NC2rKh9/2+6J7RM+fOf/3xYW1xcHF6vl23btqkKsshp5PF4WLNmDYcOHSI1NTWiuEi7iy66CK/XS2ZaEu9+cyjnxZdF7ec1LNzwbi7PLg3/wHz8TMJAIEBVVRWpqanMmDFDBUtE5KzVXtBk6T531PZ54zqCQm2ZIiIiXVFQKCIDktVqpbS0FIfDgc1mA+CR17ZwJBD5TfxwWxVfnD8GaNvXp7W1NdRmMplIS0ujsrKSffv29c7gRQaY1tZW1qxZw+HDh0lLS+s0JJwzZw5+v5+huem8f1smE2KORb+fYefqJVk8/872sOsfXW5cW1tLVlYWs2bNIjs7+9S9IBGRU8xisVBSUsLbGw5FbZ8ztGOrBJ/PRyAQ6K2hiYhIH6OgUEQGrLy8PLKzs/nLX/4CgNfr5/6NKVH7/mBSU2gm0de+9rWwNqvVSlxcHLt376auru60jllkoGlpaWH16tUcOXKEjIyMULD/UXPmzAFg1LBc3r8lnhJb9O0A6oNxfHJBEgveD99b9KOFSxobG4mNjWX8+PEqWCIifcKtt95KVW0jO7yRX2ycm1wVOg4EAixfvrw3hyYiIn2IgkIRGbDMZjOlpaXExcWFCiI8sXAL+3wZEX0LrLV87ZKxAJSVlUUs20lISMDtdrN161Z9Sy9yijQ3N7N69WoqKirIyMjodNlve0g4bXQ+/73BRJ6lPmq/ymASc5+z8t8N4XsWfjQkdLvdeL1exowZQ3p6+sd/ISIiveBb3/oWAO/WJEW0ZZqbGF/SUbitvLy818YlIiJ9i4JCERnQsrOzGTRoEI8//jgAgWCQH6+Ji9r3+2NrcMS2LXm8+eabw9pMJhOpqamUl5dz4MCB0ztokQGgqamJlStXUllZ2aOQ8KKpxSz+jJsMsytqv4P+dM77m4cNu46EXf9oSBgIBKivr6ewsJDCwsJT8EpERHqH3W7nmmuuYdne6PsUXjimY6Zhbm5ubw1LRET6GAWFIjKgmUwmSktLwyogP/X2NrZ5cyL65lga+J/L2mYVVlRUhO1VCGCz2YiJiWHnzp00NDSc3oGL9GNOp5OVK1dSU1NDRkYGFoslar/2kPCzs0fy6iedJJqifzje7s3m3Cfq2HM4fDnyR0NCwzBwOp1kZWUxZswYTCYTIiJ9yd/+9jcWbygjaET+/pqTb4SOH3744d4cloiI9CEKCkVkwEtLSyM/P5+rrroKAAODH70fPZj4zvByEhPa9iv75je/GdGelJREc3Mz27ZtIxgMnr5Bi/RDhmFw9OhRVqxYQV1dHZmZmVFDwkAgEAoJv/Kpcfzr/HJiTf6o91zVOpjzHj3G0ar6sOsfDQmhbV/CmJgYxo8fH9qOQESkL3n88ceprXex3Re5T+GspEpMtAWIr732WsQXniIiIqCgUEQEk8lEcXEx119/fejai+/uYJ07L6JvutnFdy8fDcD+/ft55513Iu6VmprK0aNHKSsrO63jFulPgsEgu3fvZvXq1Xg8HjIzMzGbI9+mvPXWW8ybNw+Ae66ZxJ+mHsRqih7KL24qYO7v9uFsbA67Hi0k1L6EItIf7Nu3D4B3qyL3KUw1NzNpxODQ+V133dVr4xIRkb5DQaGICJCcnExRURETJ04MXbv3negzlL5VdJj0lAQA7rvvvojiJXa7HZvNxo4dO3C5ou+XJiIdfD4fGzduZPPmzVitVtLS0qIu+7322mt54IEHsJjN/OnWyfxs5N5O7/mCs5hPPrKdllZP6JrNZosaEh6/L2FBQcEpeU0iImdCUVERAEv3NEdtnzemo2Dbrl27ovYREZGBTUGhiMiHBg8ezPe+973Q+aJVe1jenB/RL8nUyr1XjAid/+hHP4rok5ycTFNTE9u3b8cwjIh2EWnT3NzMqlWr2LNnD4mJiWH7hR7vwgsvpKqqioS4GF7/n7F8JXdPp/f8c3kJ1/xuA35/R9jvcDh46623Ivp+dF/CaLMYRUT6iq9//esALN5QRiDKPoUXDOmYgb1ly5ZeG5eIiPQdejcsIvKh9PR0MjMzufrqq0PXvv929BmBX80/SG5mMgDvv/8+Xq83rN1kMpGSksKhQ4c4cuRItFuIDHi1tbV88MEHHDlyhPT09E73BZwzZw7BYJC8rBTe/1YB85M6ryz+4P5SvvKndRh0BPQpKSksXLgwan/tSygi/YndbsdisdDQ1MJmb2Rl45mJFaEvRCorKyPev4iIiCgoFBH5kNlsZujQoaGiJgDvbTrIosaCiL5xJi8/uqIkdH7JJZdE9ImJicFsNrN9+3ZaWlpOy5hF+iLDMDh8+HCoaElWVhZWqzVq3/aiJRNK81h5azLjYsqj9gsaJr67tZjvPbU27Pr06dN56aWXoj6mfV/C0aNHa19CEek32oPAdysTItqSTa1MHdmxT+Gvf/3rXhuXiIj0DQoKRUSOk5ubS0JCAt/+9rdD1+59wxm17xdy91OQ17bXj9/vx+mM7JeSkkJ9fT07duw45VWQDcOgqamJuro6LW+WPiMYDLJz507WrFmDz+frtGjJ8ZWNPzm9lP9e52ewpS7qPd2GjRveG8xDL64Pu75w4UIeeOCBqI8JBAI0NDRQWFhIYWHhx3xVIiJnj0GDBgGwZHdT1Pa5ozv2KXzqqad6ZUwiItJ3RP/6XkRkgHI4HOTl5TF9+nSsVit+v591O4/wknMiV6btC+sbY/Lzk8tKuPEPNQDceuutvPDCC2F9zGYzSUlJ7Nu3j+rqatLS0khNTSUxMZGkpCQcDkfUog3R+P1+GhsbaWhooK6ujpqamtBMxZEjR1JaWtrje4mcCV6vl82bN3PgwAEcDgcJCZGzXQCWLl3KT37yEwC+esk4fjf5MDZTIGrfmmACV7waw/ubtoVdj1a0pF37voQZGRnal1BE+p01a9aQlZXFsg1l+C+MjagMPzO347yioqK3hyciImc5k3EWT0NpbGwkOTmZhoYGkpKSzvRwRGSAqKqqYvny5VitVq644goARhXmsPnGViym8F+ZfsPMlUtyeO39nUBbFeTzzz8/4p5erze0zDEQCGA2m7Hb7cTHx5ORkUFycnIoPLTb7RiGgdvtDgWDtbW1OJ1O3G43fr8fk8lETEwMMTEx+Hw+3G43I0aMYPTo0Qo95KzU1NTEhg0bOHbsGKmpqcTExETt953vfId169YB8OBNk/luYedFS/b6MvnUU43sOVwddr2rkBCgoaEBk8nErFmztORYRPql9i8ON3xvBBNijoW1VQcTyfrJUQAsFktY4ScREemfTiRf04xCEZGPyMjIIDU1lfr6egYNGsSxY8fYfqCCZ6sncUPW3rC+VlOQ5y6s4VJPCUvW7uFHP/oRixcvxmKxhPWz2+3Y7fbQeSAQwOv14nK5cDqdGIaB1WrFbreTlJREMBikqakJj8eDYRiYzWZiYmJISkrCarWGzRyMjY3FYrGwY8cOfD4f48aN63S/N5HeFgwGKSsrY8eOHTQ1NZGRkdHtfoR2u5Wnbh3HNemdh4QftORz2RMHqa0PLzjUXUjY0tKC1+tl0qRJCglFpN9KT0+ntraWlTXxTMgLb8s0NzGiIIedBysIBAK0trbicDjOzEBFROSso2knIiIfYTabyc/Px+fz8eSTT4au//CVQ3gNS0R/h8nLS59qYOb4tn3O5s2b1+1zWCwWHA4HKSkpZGVlkZWVRXJyMmazmdraWurr67FaraSlpZGVlUVGRgaJiYnYbLaoy4vj4uJISkpiz549rF27Fo/H8zH+FxA5NZqamli9ejVr167F6/X2qGhJWlI8y/5nBNek743aD+D52mLm/HbnCYWEhmHQ0NBAS0sLpaWl2pdQRPq1nJwcAJYfiP5+4IIx2aHju+66q1fGJCIifYOCQhGRKAYNGkRcXBx+vz9UBfnAsRoe3hc9XEg0uXn9slYmjRgCwNy5c0/o+UwmE1arlfj4+NA+hnFxcREzE7sSGxtLamoqBw8eZPXq1aq0LGdMMBjkwIEDLF++nLKyMpKTk0lJSel0D832kHBkYQ6rvpnDzLhDnd77oQOlXPP79Xi9HUvlTCZTtyFhbW0tAJMmTWLcuHFaoi8i/dqNN94IwH+3HInafm5+x5c2u3fv7pUxiYhI36B3ySIiUcTFxTFo0CCam5u5/fbbQ0ty7v3nep6qKo76mBRzC29+NsioolwMw+Daa6/tzSEDbUucMzIyOHbsGCtXrqSxsbHXxyADW1NTE6tWrQqbRXj8svvjuVyuUEh46azhrLjRoNhWHbWvz7DwtXWFfPcfa8OuJyYmsnTp0k7H4/f7qaqqIjExkenTpzNs2DAV/RGRfu+OO+4A4GhVPQf8kdsszEjpqCK/b9++iHYRERm4FBSKiHQiLy8Ps9mMz+fj5ZdfBsAAvvD4Rv7jLIr6mExzE4uvt1E8JJOqqip++9vf9t6AP2S1WsnIyKC6upqVK1fidDp7fQwy8LTPInz33Xc5dOhQt7MIb7nlFi699FIAfnjtJF6+sIJkU2vUvo2GgyvezuSPr20Ku37VVVfx6quvdjomj8dDbW0tOTk5zJw5k+zs7E77ioj0J3a7ndLSUgBW1qdFtBfZashKa9vMfv/+/Xi93l4dn4iInL0UFIqIdCIzM5OUlBRcLhd2u50rr7wSaAtErv3DZt5oiL4MOddSz9s3JTAkN42XX36ZP/zhD705bKBtD8TMzEwaGhpYuXIllZWVvT4GGTiOn0Xo8/m6nEUIbUuN9+/fT1ysnRdun8iPR+zF/JGK4u2OBlKY/ayNhSvCl8YtWrSI22+/vdPncLlcNDQ0UFRUxIwZM0hMTDy5Fyci0kdlZmYC8MHhQNT22eMHh45//etf98qYRETk7KegUESkExaLhaFDh+L1ejEMg29961uhNr8/wJWPbeMd19Cojy2w1rLki6lkpSfx3HPPsXDhwt4adojZbCYjI4OWlhZWrVrF4cOHe30M0r8Fg0H279/f41mEXq83tNS4YFAGK75dyGfSOl/ytskziOlPNLFhd8ceW1arlWXLlnUaRBqGgdPpxOv1Mm7cOCZNmtRlaCki0l8VFBQA8M726F8WnlvYUen48ccf740hiYhIH6CgUESkC7m5uTgcjlBhkAULFoTaPF4/n35sNytbB0d9bImtmiW35pKWnMBDDz3EJZdc0utLe0wmE+np6QQCAdauXcu+ffswjOgzt0ROhMvlYtWqVaxbt65HswgfffRR5s+fD8DcSUWsviWGcTHlnfZ/vraYGb/Zz5HKjn20kpOTefvttzt9TCAQoLq6mpiYGKZNm8bw4cNVtEREBqybbroJgK17y3EG4yPaZ2Z2FD1TATQREWmnd88iIl1ISEggNzeX5ubm0Hn7nj8Aza0ePvGHA2zy5EZ9/Bh7OYtuyycxoS1snD9/fq/vW2gymUhNTcVisbBx40Y2btyI2+3u1TFI/2EYBkePHuW9997rUUVjgJtvvpkXXngBgNsvn8Cbn3aSaW6K2jdgmPjBzmKu+f16Wt0dwXpmZmZor9BofD4fNTU1pKenM3PmTAYPHqyiJSIyoF144YWh41WuyD1ax8VUEBcbA0BKSkpvDUtERM5yCgpFRLoxePBgzGYzfr8faFuec/x+Zw1Nrcz741F2eKMXSpgSe4Q3vlaE48M34y+//DJz5sxhzpw5PPbYY702yzApKQmHw8GuXbt49913OXr0qGYXygnxer1s3ryZVatW0dzc3O0sQmjbj/DQoUPYrFae/OpkHpmwH5sp+n5Z9cE4rliSw/3/Xh92PSUlheeee67T52hpacHpdJKfn8/MmTNJTU098RcnItLPWCwWMjIyAPjgmCWi3WYKMHPsEAAOHjzYm0MTEZGzmMk4iz8lNjY2kpycTENDA0lJSWd6OCIyQAUCAZYuXYrL5QoLINr3WmuXm5nM+7emUWitjXqfnb5s3q9JYmNFgPUH69m4u5wWt+eUjTM5OZnHH3+828quwWCQurq25ZwFBQWMHDmSuLi4UzYO6Z/q6urYtGkTlZWVJCYm9ujfmfb/RnIyknjpS4OZ7jjSad/dviwu/5eLnQcrwq4PGjSIf/7zn1EfYxgG9fX1BINBSkpKGDVqFFar9QRelYhI/5abm0tFRQUXTBzGO5fVRLT/ZE8J/+9f64C2L10cDkdEHxER6ftOJF9TUCgi0gO7d+9mw4YNZGVlhS1n/GhYWDAoneVfSmCwpe6jt4gQMEzs92ew1ZXEpiozG440s353BUeq6j/2eIcNG8avfvUrkpOTO+3T2tpKQ0MDqampjBo1Sks1JapgMMiBAwfYvn07ra2tpKWldRvGNTQ0cMUVVwAwa1wB/74sSJ6lvtP+bzQWct0Tu2l0tYZdf/nllzv9dzgQCFBbW0tcXBxjx44lPz9f//6KiHzE5ZdfzquvvordbqXhe0nEmvxh7UtcBcx7eDMAt956q4qaiIj0UwoKRUROsaamJpYuXYrNZouYSfXRsHD40Cz+e6OdbEvjST1XbTCB+kAsHsOCzzDjCVrwBs14gma8QRPeoAlPoOOfu2qD/Pv9Mg5VOKPe79lnn+10lmEwGAzNyMrPz2f06NHEx0dueC4DU0tLC1u3bqWsrAy73U5SUlK3Ydx1111HZWUlJkzce+1E/t/wA50uNQb4xYESvveP9RiEvx1ZtmxZp4/xeDzU19eTmZnJhAkTSEtLO7EXJiIyQLhcrtB2KR98dzQzHIfD2huNWFJ/WkMwGGTw4MEcPnw42m1ERKSPU1AoInIarF69moMHD5KVlRXR9tGwcHzJIJZeZ5Bmbu6VsXkMK09VFPKTVw9EDQwtFguLFi3CYoncowg6gpekpCRGjhxJfn6+qsUOYIZhUFFRwZYtW6irqyMlJYWYmJguHxMIBJg3bx4A2RlJ/OvmocxNKOu0f4th5yvv5/CvJVvDrpvNZpYsWdLpuJqamnC73RQWFjJ27FhiY2NP8NWJiAwsFouFYDDIw1+Ywv8O3R3RPuXfSazbeQSz2Uwg0PkXOyIi0nedSL6mT4EiIj3UvjS3vajJ8T46+2nTnmN84kUbdcHemZ0XY/Lz5dw97L4V/vSVyQzJCZ9h1R7ivPnmm9EfHxNDVlYWbrebNWvWsHr1apqaolellf7N7/ezfft2Vq5cSWNjI5mZmd2GhAsXLgyFhJ84p4RNtyV1GRIe8qdx3nOxESFhUlJSpyFhMBiktrYWwzCYMGECkydPVkgoItID48ePB2D5XlfU9vNGZgJtv2ddruh9RERk4FBQKCLSQ1lZWSQnJ3f6JvqjYeGa7YeY8ISHn+0t5q3GAo4FUk77GGNMfr4yaA97boXHowSGDz74IPPmzYv6GkwmE6mpqSQnJ1NWVsa7777L/v37VRl5AKmvr2fFihVs3boVu91ORkZGlzNLA4EAF110EQ899BAWs5lf3DyZ1+dXdbnsfnnzUKb8wcn6neGFTe6++25eeeWVqI/x+XxUV1eTlJTE9OnTKS0t1YxXEZEeuvjiiwF4d3P0ZcXnDu44vvHGG3tjSCIichbT0mMRkROwc+dONm3aFFHU5HiXXHIJLS0tUdsyUhKZPDybifmJjM8yMTbJRYmtGnsXe7h9HG7Dyt/LC/npq/s5UhleYKWkpIQ//elPUR9nGAYNDQ34/X5KS0sZPXp0p8uWpe8LBAIcOHCAnTt30tzcTHp6ercFS1577TUefvhhoK2Iz7Ofz+acLqoaBwwTDx0o5t5/biAYDIa1LV68uNN/v5qbm3G5XAwePJgJEyZoD00RkRO0ZMmS0Kzv7feUMNJeGdZ+NJDC4J8eAmD06NFs3bo14h4iItK3aY9CEZHTpLGxkWXLlmG323E4HJ32q66u5pprrunRPW1WK+OKc5k4LJWJuXYKEv3EWILEmILYzR/+mILEmAPYTAHs+IkxBbCZ/CSYPD16jrbAcBg/eXUfR48LDOPi4nj99dc7fVxLSwsul4uCggLGjx/f7RJU6XuamprYsmULR48e7XHBknnz5oX2sbp29kj+eF4dKebo4ThARSCZmxbF8vaaPWHXu9uPsK6uDsMwKC0tZeTIkd2GlyIiEikQCGC32wkGgzz51cl8MWdPRJ/CJ+wcPFajoFBEpJ9SUCgicpoYhsGqVas4fPgwmZmZ3fY/fPgwN91002kbz8hhufzok7lcnb4Pi6n7X+duw8bjhwu5+5+b8Hh9oevdVZitq6tj0KBBTJo0iYSEhFMydjmzgsEgZWVl7Nixg8bGRtLS0rDb7V0+prW1lU996lMAxNit/O7m8XxlUOQHzuO91VTI5/92gGpn+HLkYcOG8Ze//CXqYwKBALW1tSQkJDB27NjQ/qAiInJyhg8fzu7du/niJ8bx5DkHI9q/sGIof39rC6Wlpezatav3BygiIqeVipmIiJwmJpOJIUOGAPSoMuCQIUNYtmwZL7/8MkVFRad8PDv2l3Pdo+sZ93Qcz9UWEzC6DlNiTT7+J383i741grjYjtmBH63afLyYmBgyMjIoLy9nxYoVOJ2RVZWlb2lubmbNmjWsW7cOr9dLdnZ2tyHhXXfdFQoJxxTlsPbOYV2GhF7Dwj3bi5n/q80RIeHMmTM7DQk9Hg/V1dVkZWUxc+ZMhgwZopBQRORjav9y850t5VHbzyto+xuwZ88eVT4WERngNKNQROQE+Xw+li5ditvtJjk5+YQfX11dzVe/+lXq6uq673yCRhe1zTD8TNo+zN3MMHy3eSif/P1uWtwdy5e7mlnYXnU2Li6OCRMmkJeXd8rGLb3DMAyOHDnCtm3baGhoICUlpdvl5F6vl/nz5wNgtVr44WfHc3fJQWJMkdW/2x3wp/O5VwxWbj0Y0bZw4cJOl+03NTXR2trKsGHDGDt2rJa6i4icIr/85S+56667ADj2gyHkWhrC2rd5cxjzwG4AFi1aFCqAIiIi/YOWHouInGY7duxg06ZNJCQkEB8ff8ZmPLW2tvLII4/w5ptvhl0fXZTL/30yl6u6CQzfa87nE4/tobmlZ2GhYRg4nU4sFgtjxoyhqKhIs736iNbWVrZt20ZZWRkmk4mUlJRuKwf/9re/5eWXXwZg6qh8nrw8ljH2ii4f86KzmC/9dQeNrtaw67GxsbzxxhtRH2MYBrW1tVitVkaOHElJSYmqGouInEJerzf05ct/vjWRK1P3hbUHDRPpv/FT39jMDTfcwNNPP30mhikiIqeJgkIRkdPM6/Wya9cuDhw4QGtrK8nJycTGxp7RMblcLi699NKwa2OKc/m/T+ZwZer+TgPDD1ryufjRnoeF0Pb72ev1qiJyH2AYBuXl5WzdupW6uroe/bvqcrm47LLLMAwDR6ydn103lm/m78NqCnb6mFbDzp0b8vjDgk0RbccvW/4ov99PbW0tycnJjB8/ntzc3BN7gSIi0iN5eXkcO3aMO6+ayC/H7otov3xxLq++v4vhw4ezc+fOMzBCERE5XRQUioj0kvr6enbv3s2RI0fw+/2kpqZis9nO6JiiVVyePiaf1670k252RX3MipYhXPzoPlwt7tC17sLClpYWmpqaKCwsVEXks1RjYyN79+7l4MGDBINB0tLSup2p9+Uvf5l9+9o+QF44pYg/zTcYZq3p8jHbvTlc97yLLXuPhV232+0sXLiw0yDZ7XbT0NBATk4OEydO1N96EZHT6KKLLmLx4sVMGZnPmmvqI9p/ebCEu/6+DpvNRmtrq74EFBHpR1TMRESkl6SkpDB16lRmzZpFbm4u9fX11NbWntGNwDMzM1m2bFnY7MKVWw9x0b/N1ASjVyyeEXeYt79ZRGJCx95xc+fO7fJ54uLiSE1NZf/+/axatQqXK3oIKb2vfZnxO++8w549e3A4HGRkZHQZEjY0NDBnzhz27dtHUoKDv3x1Mosvqe4yJAwaJv5wtJQpvz4YERJeddVVLFq0KOoHTcMwaGxspKmpiZKSEmbMmKGQUETkNJsyZQoA63cdocmInFk+M6ttZYHP5+Odd97pzaGJiMhZRDMKRUROkWAwyJEjR9i1axdOp5PY2FiSkpLO6B5+xxeiABhfmsfb10KmuSlq/1Wtg7n4sQNh+8t1N7OwfeloWloaU6ZMITU19dQMXk6Y1+vl4MGD7N27l8bGRuLj40lISOjy30GXy8VVV12Fz+cD4MrzRvD7C1oYZKnv8rl2+bL48sIg723cH9G2aNGiTqsoB4NBnE4nNpuN0aNHM2zYMO1HKCLSC5YsWcK8efMAWHrnOOYkHAxrdxs2kn7WgM/v5/vf/z7333//GRiliIicDppRKCJyBpjNZvLz87nggguYMGECNpuNqqoqmpubOVPfydjtdpYtWxZaDr1p91HmPWNQFUyM2v8cxxEWf72QpONmFs6ZM6fL57BarWRmZlJXV8eqVauoqel6maqcen6/n4MHD/LOO++wYcMGfD4fWVlZJCYmdhoSBgIBrrvuOi699NK2/mlJPH/7JP4z91iXIaHXsPDz/SWM++XBiJAwKyuLZcuWdRoS+v1+qqqqSExMZPr06RQXFyskFBHpJbNnzw69H/igInKblFiTj3PGDAFg+fLlvTo2ERE5e2hGoYjIadLc3My+ffs4cOAAbrebmJgYbDZb6Ke3ZxpecskltLS0AG1FTpZcbyark5mFa915zHusjIamtv5ms5klS5Z0eX/DMKipqSEuLo7JkyeTk5Nzal+ARAgGg5SXl7N7926qq6uxWq0kJyd3u6/Ua6+9xsMPPwy0/X97++Xj+X9jKkgzN3f5uPXuPG55uYmNu45EtL388sskJyd3+tjW1lYaGxsZNGgQEydOJCEh+jJ4ERE5fcaOHcvWrVu5eFoJiz5ZGdF+745ifvbceqDtyx3tUygi0j+omImIyFmkrq6OgwcP4nQ6aW1txefzhZZ5AmHhoc1mO60zrK644goaGhoAGF2Uy+LrLeRYGqP2Xe8exIWPHaL+w7DQarXy9ttvd3l/wzCora3FbrczadIkBg8efGpfgABt/ztXV1eze/duKioqgLb9Mq1Wa5ePczqdfOYznwmdz5tawm/mmRhtr+jyca2GnR/vyOcXL24kGAyvfJyVlcW///3vLsfa1NSE1+ulqKiIMWPGnPGCPyIiA9W5557L+++/T3xcDHXficNmCt9TeWHDMC75zca244UL+eQnP3kGRikiIqeagkIRkbOUz+ejubmZlpYWWlpacLlcNDQ04HK5QgGiYRiYTCZiY2NxOBzdhj8n6qtf/Sq7d+8GYOSwXJZ+zkqOpSFq343uQcz9w2HqGttmmk2aNCk0E60zhmFQV1eH2WxmwoQJDB069Izu09gXGIaBz+fD7/eH/QQCgYhrPp8Pl8tFRUUFgUCA5OTkTpf6tmtoaOCqq64KhXwFeRn8+jNDuCJ1X7djW948lFueq2TPoaqItnvuuYeLL76408cevx/hmDFjGDZsmP5dEBE5gz7/+c/zz3/+E4B1d49kUuzRsPbaYAIZP2krTjV37txuVxOIiEjfoKBQRKSPCQQCofCwubkZp9NJVVUVLS0tBAIBbDYbDoeD2NjYUxK0VFdXc8011wAwoiCHpZ+3k9vJvnSbPLnMfewIzg/DwtLSUh5//PEu728YBg0NDQSDQcaNG0dRUZECoih8Ph+VlZUcPnyYmpoagsFgxM/x/7u1h8hms5mEhARiYyOrVn7UZz7zGZxOJwCO2Bh+ePUYvj2sDIfJ2+XjGgwH39+Qw2MLNkW02e12Fi5c2OWStPYiNykpKUyYMIHs7OxuxyoiIqfXW2+9FSpy9ugtU/j64N0RfUY/Fc/2/eWkp6dr32ERkX5CQaGISD/g9/upq6vD6XRSUVFBfX09Ho8HIGy24ckGcD/4wQ94//33ARj+YVjYWRGLzZ5c5v7hCLUNbWHhjBkz+NnPftbtczQ2NuL1ehkzZgzDhw9XWEhb2NfY2MixY8c4dOgQjY1tS7/j4uKwWCyYzebQj8lkOun/zcrLy/nc5z4XOr9h3hh+Pr2JwZa6bh/7ev0wbnu2jCOVkX3vuusuPvWpT3X5eLfbTUNDA7m5uUycOJHExOjFc0REpHcFAoHQSoXr5o7mmfMOR/T5xvrC0JdE2qdQRKR/UFAoItLPGIZBS0sLTqeTmpoaKisraW5uDr2Bt1qtWCyWiJ/uQqa7776b1atXA1A6NJulN8aQ10lYuMWTw9w/HqOm3gW07V3kcDii9j2ey+XC7XYzfPhwRo8e3Ser3BqGgd/vJxgMYrfbTyq88/v9odmDFRUVeDweYmJiSExMPKUfwgKBABdddFGo0vakEYN55NIUZsUd6vaxe3yZ/O9/rbz2/q6IttTUVJ5//vlux9rU1ITb7Q7tR9jdsmgREeldgwcP5ujRo+RkJFP+jciPgv+qLuaGx9oKmrz11ltcdNFFvT1EERE5xRQUioj0c4FAIDTb0Ol00tLSgtvtDu1pFwgEIopOmM1mLBYLiYmJYfseXnfddVRWtlU+LMnPYulNjk5nnW3z5jDnj+VU17VVS162bFmPxtu+H2NJSQnjxo07bbMTfD4fdXV1+P3+iLbO/twFg8GIfQC9Xm/Yj8/nIxgMYhgGNpuNxMREEhMTiYuLw+FwhH4+ujS8vZDH0aNHw2YPti8bPpUzLCsrK7nxxhtDhXKyM5K4/6oSvpCzF4up6z/1jYaDB3bk8cuXNuH3ByLau6toDB2FbKxWK6NGjaK4uLhPhsIiIv3dDTfcwL/+9S8A9t07jGHW8OXF+/0ZFN2/H2h7j/DMM8/0+hhFROTUUlAoIjIABYNBfD4fHo8nIujyeDy0trbS0NCA0+kkKysrLKSaN28egUBbQFQ0JJNlN8cxpKuw8PEKqp1todfixYt7FPy1L0ctKipi/Pjxp6zyrdfrpaamhqqqKsrLy2lubg6FpO17+nUmWrthGGHLfz+6FPj4QLGdxWLBZrNht9tDIaLD4aC2tpbKykpaW1uJjY0lISHhlBenaW1t5ZJLLgkFoUkJDu65chTfLDxEgsnT5WODhol/Vhdz1/N7qKyJrH6dlJTEK6+80u0YAoEANTU1JCUlMWHCBHJzc0/uxYiIyGn39ttvhwpRPf31ydyQuSeiT+6jJipqGoiNjaW1tbW3hygiIqeYgkIREYnK5XLx3nvv0dzcTHp6eljbR8PCpTfHk29xRr3Pdm82cx6vpOrDsPDee+9l3rx53T6/x+Ohvr6eoUOHMmbMGBwOx0nNLvR4PKEl2OXl5bS0tGAYBrGxscTFxZ3yMK4r7cuS2ysSHx8imkym0zJ7EMDpdHLdddeFZhDG2G3ccflY7hpRTpq5udvHr2kdzO2vu1i1LfqS5BdffJG0tLRu7+PxeKirqwvtR6i/1yIiZ7fj9yn8+qXjeXTSgYg+1y8fwrNLtwFtqwJ6stWIiIicvRQUiohIp44dO8aqVauw2+3Ex8eHtX3iE58IFUwpzMtk2RfiGWqNHhbu8GYz50+VVNa2hYU9qYYMbTMAnU5nqBhLXFwcSUlJxMfHhy3hdTgcYbMO3W43NTU1VFRUUFlZGQoHHQ5HqBDIQBAIBPj0pz+N2+0GwGI28+VPjeWHE+o63V/yeBWBZL6/NpW/vrk5antPA0LDMEL7TxYWFjJ27FhiYmJO6LWIiMiZMW7cOLZs2cKoYblsuzHyy6XHjpTyjb+sBeBLX/oSf/nLX3p7iCIicgopKBQRkU4ZhsH27dvZtm0bqampEUuAjw8LC/IyWPaFRAqstVHvtdOXxew/VYWWrfZ0qWowGMTr9YbNwmv/c2QymbBardhsNmJjY0lMTMRkMlFVVUVLSwsmkykUKA6UcBDaZhB+6UtfoqGhIXTturmjuW+6h1JbVbeP9xhWHi0r5EfPb8PV4o5oHzZsWI8/CLbPDI2NjWX48OGUlpZqP0IRkT7kjTfeCFWwr/nhINLNrrD2De5BTHpwJwDp6enU1NRE3ON0MwyD8vJy0tPT9UWUiMjHpKBQRES65Pf7WbVqFUeOHInYrxBgzpw5oeOhuRks+1IihZ2Ehbs+DAsrPgwLTSYTS5cuPemxte+1+NEQsX3m4EALpD46gxBg/jkl/Gy2lUmxR3t0jwX1RXzn5aPsLosMFDMzM3nyySdJSEjo9j5+v5/6+nqgrWrm8OHDSU1N7dkLERGRs8bxy49f//YEPpW8P6zdZ1hI/WULzS0eLBZL1CJhp1MwGGTbtm3s2bOH3Nxcpk6d2qvbioiI9DcKCkVEpFsul4v3338fl8sVsV8hhIeF+bnpvPOlZAqt0WcU7PZlMfuJasqr22a7WSwWFi9efHoGPkA4nU5uueWWUDAHcOGUIn5wQRyzE8p6dI//uoZyz1uNrNgS2T8tLY1nnnkGu93e7X2CwSCNjY14vV4yMjIYMWIEubm5p3zfRRER6T05OTlUVlby/Wsmcf/IvRHt89/I5q3VbYVOamtre7Qtxang9/vZvHkze/fuDRVTGTFiBOPGjdPfHRGRk3Qi+drAmpYhIiIhCQkJjB07FrPZTHNz5P5Ey5YtCx0fKq/lgifr2e/PiHqvUlsV//1KBoOykoG2mQoXXnhhqDiK9JzT6WTOnDl85jOfob6+nvi4GG6/bALb7ilh8SXVPQoJN7oH8alFOcx+eEvUkHDBggW8+OKL3YaEhmHQ3NxMVVUVdrudSZMmcf755zNo0CB9WBMR6eNuuukmAN7dXRe1/fySjg+SP//5z3tlTF6vl3Xr1rFnzx6SkpJCP3v27GH//v3d30BERD42BYUiIgNYbm4uw4cPx+VyharnHu/4sPBwuZML/lzPPn9m1HuV2Kr54CupfPaCkUDbLLR58+ZpZmEPtFcwbg8IAYYPzebRW6Zw9DspPDJxP6Psld3eZ48vk+uXD2Higzt5Y+XuiPavfvWrLFu2rEfLjD0eD1VVVfj9fkaNGsXs2bMpLi7W0i8RkX5i/vz5AKzaehi3YYton5njDR0vXbo0bAuM06G1tZXVq1dz8OBBUlNTiY2NBcDhcGC329m6dSsVFRWndQwiIqKlxyIiA153+xVC+DLkvOxU3rkljWJbdaf3XNU6mLveamX5xgPAiS1zHSicTiff/va3OXz4cOiaCROXnTucb06zMy/xYI/vdTSQwk83pvLEwi0EgsGI9ilTpvDzn/+8R8VfAoEAdXVts0vy8vIYPnx4ry03ExGR3nP8PoXv3zWGmXGHwtqbjFhSflpDMBjEbDazc+dOSkpKTstYmpqaWLt2LVVVVaSnp0d8KWUYBrW1tcTHxzNz5kySk5NPyzhERPor7VEoIiInpLv9CiE8LByUmcI7X0mnpIuwEOC1+mHc/WoF2w+0zQBITEzkqaeeGpBv8F0uF//v//0/NmzYENGWlhTPrfNLubW0vtOiMdE4g/E8tDOXX7+yBY83ckZocnIyzz33XI8C2kAgQGNjIz6fj/T0dEaMGKElxiIi/ZzNZsPv9/PQzVP4TkHkTPSpzyWzdkfbF1oLFixg/vz52GyRsw8/jvr6etasWYPT6SQjI6PTL7UMw6C6uprMzExmzJgRmnEoIiLdU1AoIiIn7NixY6xatQqbzdbp0tTjw8KczGTe+Uomw22RlXSP5zfMPFU5jB/8Zx/HPix2AjB58mT+7//+r0fLYKNxuVz89Kc/ZePGjXg8npO6x8nIzc3l97//fdRZdq2trfzqV7/qdrm1IzaG6aOHMKs4iek5QeYkHyHO5O3yMcerDSbwxMFcHnhpO42u1oh2s9nMK6+80uNKxu0BYWpqKkVFReTn55/yD4IiInL2SUtLo66ujkvPHcGrFx6LaP/OliIe/k/bF1zXXXcdDzzwAAUFBafs+aurq1m3bh2NjY1kZGRgNne9M1YgEKCmpoahQ4cyZcoUbYchItJDCgpFROSEGYbBjh072LJlC2lpaZ0GRWFhYUYyr90yiMmxR7u9f4th5/cHhvLT/2yjqTn6PkfJyck8/vjjZGdnU11dza233hpW9fdUMJvNOGLtOGLsxNgtNLjcuJojw7ZTqXRoNrNGZjMj38a0tGZG2SuxmU680MtGzyAe3WTnqSU7os4gBHjuuefIzIy+j+Tx/H4/DQ0NBAIB0tLSKCoqYvDgwQoIRUQGkJ/+9Kf88Ic/JDkpHue3rZhN4R8NX68fxqd/uxGApKQkXnrpJS644IIebWXRnWPHjrF+/XpaW1vJyMjo8Qx2r9dLfX09I0aMYOzYsZr5LiLSAwoKRUTkpBy/X2FmZman3+x/6lOforW1LVyzmM189dPj+OG4WnIsDVH7H68mmMADW7N49PWteLz+kx5rTkYywwalUpCZwNB0O0OTTeQn+Em1+Yk1B4gxBT78p//DHx8x+KMGdD7DQr0RR30gljp/DHU+G/VeC3UeM043OFuD1Lr8tPqCmE1gMoHZZMJkattXsP2aydRxPDjZxrRsP1MSqsgwu076dXoMKy/XFvDIcicfbD7Yab+eBoQ+n4+GhgYMwyA9PZ2ioiLy8vI0K0NEZADyer3ExMQAsPWeUkbbw4uF+A0zI560su9IDQDPPvss5557Lnl5eSf9nIZhUFZWxqZNm/D7/aSlpYWFfV1t1QGQk5PDww8/jN1uZ9KkSQwbNuykxyIiMlCcdUHho48+ykMPPURFRQXjx4/nd7/7HdOmTev2cQoKRUR6X/t+hU1NTWRkZHTa7/rrrw+rPhjniOG7V47ljuLDJJl6NkOv1bDTEIylMRhLg99Og99Kg89Co9dMvQfq3QYN7iAZcRbykyE/zsuQmGbyrA3EmqLPqOsvygPJ/Hl/Jo++tZfKmsZO+z377LNkZ2d3ez+v10tDQwMmk4nMzEyGDRvGoEGDTsmsEBER6bvsdjs+n49ffWEKdwyN3KfwifISbv3TOgB+8IMfMH/+fGbNmnVSM/kMw2DPnj1s3boVs9lMcnJy2H1uueUW9u/f36N7te97fM4555CTk3PCYxERGUjOqqDw3//+NzfddBN//OMfOeecc/jNb37D888/z65du8jKyurysQoKRUTOjPLyclauXNnlfoUAt912G7t27Qq7lpmWxH1XlXLLoH3YT2J57UD3fks+v19n8Pw7O6JWMG735JNPUlhY2O39PB4PDQ0NmM1msrOzKSoqIicnp9t9oEREZGAYOnQohw4dIj83nT1fCUb87XYbNgoe81FZ08ioUaP48Y9/zHnnndftZ7mP8vv9bN++nd27dxMTE0NiYmJY+/Fbm4wuyuWe+YPIiPHz4i54YuGmTu+7cOFCVUIWEenGWRUUnnPOOUydOpXf//73AASDQYYMGcLtt9/O9773vS4fq6BQROTMaN+vcOvWrSQnJ4eWJUXjcrm49NJLI64X52fxwOWDuTpt7+kcap/nMyxs82bzQXU8TyyvZOPuI532tdlsPP/88z36MNQ+g9BsNpOTk0NRURFZWVkKCEVEJMxll13GggULAPjn1yfxuczIv9sPHSjlu/9YC8AzzzzDsGHDmDp1ao9nFba2trJx40YOHz5MQkICcXFxYe3Hh4SzxhWw6Ipm4k0dhcqOf/5oli5dqkrIIiJdOGuCQq/XS1xcHC+88AJXXHFF6PrNN99MfX09r7zySlh/j8cTVrmysbGRIUOGKCgUETkDAoEAGzZsYN++fV0WN2l3/Jv8400bM5SHPpHE+fFlp2OYfU5FIJk1TemsLDezYm89K7cfodXddcXjYcOG8dvf/rZHVYzb9yAEyM7OpqSkhOzsbG32LiIiUblcrtDsvjHFuWy5oTmiT30wjvxfN9DkauUnP/kJY8aM4YILLiA1NbXb+9fX17N+/XqqqqpIS0vDbreHtc+dO5f2j6QlQzL54Au2qHv7fmbZYP7z7vaoz5GQkMDbb7/N1KlTtaWGiEgUJxIUntady2tqaggEAhF7J2VnZ7Nz586I/g888AD33Xff6RySiIj0kMViYfz48Xi9Xg4fPkxGRkaXb76XLVsWdW+h1VvLuGArfHrWCH5+fjBio/RTqSqYSKUvgZagBU/QgjtgxhM04w6YPvwBtx88AfD4wRcwSIoxkRoLaTEBUu1+Uqw+UiweUiwtJJmiV2fuKY9hZbM7m9W1cawo8/DetmOUlR8GDvfo8ffccw8XXnhhjz70tFcxDgaDZGVlUVxcTG5urmYQiohIlxISEoiJicHj8bB1bzkLGybwqeTwv+Up5ha+8amR/Py59SxdupSSkhLKysq6DQqPHTvGxo0bcblcZGZmRvw9u+KKK0IhYVpSPK/fmESGuTrqvf5ygZMN+zI5cDSy3eVy8fe//53k5GRGjhx5Ii9fREQ+4rTOKDx27Bh5eXl88MEHzJgxI3T9u9/9Lv/9739ZtWpVWH/NKBQROfu43W5WrlxJZWVll5WQ27lcLj7/+c+HZrUdz2Qyc/G0YmYVJZIaayI5xiDZHiTZ5ifZ6iPZ4iXR7CbZ1BpRndhnWCgPJHPEm8ChFjuHmkwcqgtwoKaFAxWNHCx3djsz70RZLWbSkuJJT44jPdlBjNWCYRgEDAPDgOCH/zQMg6BhEAy2HRuGgdvnZ/ehGry+E6vsfNNNN3HDDTdEzLjoTCAQoKGhAb/fT0ZGBiUlJSpSIiIiJ+QXv/gFd999NwDnTihk+eW1EX0qAskMfbAcs8XK888/TzAYZO7cuVFnu7cXLdm+fTuBQCCisjHA5z73OcrLywGw26ws/fYIZsUd6nKc6915TH94Dz5/9L+tixYt4qKLLtIsehGRj+izS48/SnsUioicHZqamlixYgX19fVkZmb26A14a2srl156KYHAyRU0iYuNIS05jpTEWJqavRyurCPYRXGPvqy4uJhf/vKXJ7QRezAYpKGhAZ/PR2pqKiUlJQwePBir9bQuFhARkX7I6/WG7Uf8/l1jmBkltPvaukL++Nom3nzzTerr6xk7diyjRo0K6+Pz+di6dSt79+4lNjY2omgJtM2YX7lyZej82W9M4tqMnu1p/MejpXztz9H3K5w+fTpLly7F4XD06F4iIgPFieRrp3U9kt1uZ/LkySxZsiR0LRgMsmTJkrAZhiIicnZLTExkypQpJCQkUFtbS0++Y3I4HCxevJgXX3yRnJycE37OFreHI5V1bN1bTll5bb8JCU0mE1OmTGHBggUsW7aMZcuW8cQTT/Q4JDQMg4aGBqqrq4mLi2Py5MnMnj2bgoIChYQiInJS7HZ7WFD48xXRZ+zdOc6FCRMvvvgiDoeDgwcP4nZ3bNPR3NzMqlWr2L17N4mJiVFDwqVLl4aFhA/cOLnHISHAbXm7uf7CMVHbVq5cSW1t5GxIERHpudNe9fjf//43N998M48//jjTpk3jN7/5Dc899xw7d+6M2LvwozSjUETk7FJRUcHq1asJBoOkpKSc8OPLy8v58pe/TEtLyykdV1xcHE8++WS3f1c+jsrKSm699VYaGxu77ZuQkMD555/PN7/5zVM6qyEQCFBbW0t8fDylpaXk5+d3WZFaRESkpy699FJee+210PnWe0qj7it83btD+M97u3nzzTeprq5m0qRJlJSUUFtby/r163E6nZ0WQQsEAsybNy90/pVPjeNPUw9GHc+xQAqtQStFtpqItkbDwbS/w66yyoi2K664gpdeeqknL1lEZMA4a5Yet/v973/PQw89REVFBRMmTOCRRx7hnHPO6fZxCgpFRM4+ZWVlrFu3DpvNFnWmwImqrq7mtttuw+l0Rm3Py8vjkUceIS0t7WM/V1/m8Xioq6sjOzubiRMnnlRQKyIi0pnjqx8D3HzxWP42oyyi33p3HpMf3MGCBQvw+XyhL6+2bt1Ka2sr6enpne5nPH/+fLzetv2EL55WwoJP1GA3RW5R0mTEcsGzbXv1vn+dG4cpcg/ird4cpv7qIG5PZJvf79devSIixznrgsKTpaBQROTsYxgGu3fvZsuWLcTHx2sfoNPMMAyamprweDwUFhYyduxYzSIUEZHTIjExEZfLBYDFbGbfPfkMtUZ+kTd/YTabDjXyz3/+k9raWqxWKyaTiZSUlE73MV64cCEPPfQQAGOKc3nvc0GSTa0R/fyGmSsWZ/H6B7sB+NZnzuG3Y3ZEvedfK0v40h/XRVy/6qqrePHFF3v2okVEBoCzZo9CERHpf0wmE6WlpZSWloYCLDk9gsEgtbVt+zOOHz+eSZMmKSQUEZHT5oUXXggdB4JBfrM9NWq/u893UFlZSSAQID4+npiYGFJTUzsNCQOBQCgkzMlI5vVrY6KGhADf3jA0FBLGxsZy5Td/zjv286P2/WL2Hr74iXER1//zn/+EZi6KiMiJUVAoIiInzGQyMXr0aAoLC6mvr8fn853pIfU7Pp+P6upqEhMTmTFjBqWlpZ0u5RIRETkVjt8/EODxN7ZRE0yI6Dc34SBTR+Xzn//8h/j4eOLj47u872c/+1kA4mJjWHhLLvlRZikC/KqslEcXbAIgJiaGN954AwDflG+wy58b9TG/m1bO2OJBkdd/97suxyQiItHpE4eIiJwUi8XC+PHjycvLw+l0EghE7jEkJ6elpQWn00leXh6zZs06rUVaRERE2lkslrAtRVrdXv6wL3pAd8+8dJ5//vlu7/nWW29RV1eH2Wzmua+OZGLssaj9Xqor4jt/61hG/Oabb4aObfZY9oz/Ps1G5Kz6eJOH566JJz4uvG358uXdjk1ERCIpKBQRkZNmt9uZPHkyWVlZ1NTU0NzcjNfrJRgMnumh9UmGYVBfX09raysjRozgnHPOISEhciaHiIjI6fK9730v7Pw3r+3EFSWguyxlPxmJ1i6X+AYCAR544AEAfvfFiVySsj9qv1Wtg7n+j1sxaNs+f9GiRRF9EjLz+YNrbtTHj7BV8ucvjgm7tnHjxk7HJSIinVNQKCIiH4vD4WDy5Mnk5ORgGAbNzc3U1NRQVVVFVVUVtbW1NDY20trait/v5yyuoXVGBQIBampqsFqtTJ48mXHjxmGz2c70sEREZID5aFDobGzmr0fyI/pZTAbf+8QQLrnkkk7vNW/ePIYPzeKNO8bz9cF7ovY54M/g0j8fweNt28bkiiuuwG63R+07bv6X+GtFSdS26zL28LVLx4fOy8rKtE+hiMhJUNVjERE5ZXw+Hy0tLbS0tNDa2kpzczONjY00NTXh9Xrx+XyhJcqGYXS66XlXTCYTFosFs9mMxWIJ/bSft9/TMAyCwWC3P2azGbvdTkxMTKhq46lw/HMYhhH2E+2a2+0mMzOTiRMnkpaWdkrGICIicjI++9nPhhU2GZKTxt5bDeym8G1G3IaVYX8I8NtHnyAzMzOs7bprP8Pdnyrk6/kHiDH5oz6PMxjPrKcMdh6sANr2JTx+yXE09//kx/xq2jHGxpRHtLkNG7Oei2P9zsMAnHvuuVqCLCLCieVrCgpFROS0aw/C2gPElpYWAoEAJpOp2592Pp8Pr9eL2+0O/Xg8HgKBQOinPYCDtkDRbDZH/FgsFmw2G3a7HbvdjtfrpaGhAa/XG5rx2N7eXXhoGAZ+vx+fzxf6aR/D8c8Z7XUdH3RarVaSkpIYOXJk2N5QIiIiZ0IgEMBqtYZd+8fXJnNjVuSswF+XlfC/f1vHsmXLADCCQRb9/QG+nb+LHEtDp8/hMax88rVUlq3fF7q2ePFiLBYL0PaFW01NDYmJiWF/GwOBAF//0vWs+YKJJJM74r67fFmM+vn+0DYoHo+n0xmKIiIDxYnka9YuW0VERE4Bk8mEw+E45SGYYRihAPH4f5rNZqxWa9hPeyDXHtwdz+fz4XK5aGpqoqmpCafTSUNDA01NTWHhoc1mCwWD7dqDR4fDQXZ2NomJicTFxREXF4fdbg8LKI//Z7RxiIiInA0sFgslJSXs2dMRDP580TFu+LwJsyl8nskt+Ue4LzGOiy++mBf//nsGb32Unxce7PY5bl2Zx7L1W0Lnd999dygkBHA6nSQmJtLY2Ijdbg+1WSwWyiob+eryYp45/3DEfYfbqrhkRgkL3t8FwK9//WvuvvvuE3r9IiIDmYJCERHps0wmU2hm4Mdhs9lITU0lNTU1dC1aeOhyuUhMTCQ5OZmEhAQcDkcoFIyJiVHwJyIi/caaNWtISUkJnW/fX87Chgl8+iMFSZJMrfzf1SNJjYFLdn4Xs63rBWvOYDz/szKdp9/uCAnj4uL4xCc+ETpvbm7GYrEwevRo9u7dS01NDZmZmaG/s0VFRTy7bBvnF03ma3mRsxzPL05gwfttx08//bSCQhGRE6ClxyIiIj10svsqioiI9EVxcXG0traGzmeOK+D9K50ndS+/YebJ8iK+//wuautdYW3HLzn2+/3U1tYyZswYRo0aRW1tLe+//z5ms5nExEQAGhoauOKKK7BZrTi/n0qCyRN2v3dcQ5nzcFsQ6XA4aGlpOakxi4j0FyeSr6nqsYiISA8pJBQRkYGktrY27PyDzQdZ3jz0hO/zXnM+055N4KtPrIsICe+9995QSGgYBrW1teTm5jJ8+HBMJhMZGRkMHz6clpaW0NYfycnJAPj8fja1Zkc834S46tBxa2trWNgpIiJdU1AoIiIiIiIiERwOB/n5+WHXHvzA2+PHHwmk8rnlQzjvl1vZsPtIRHtpaSnz5s0LnTc0NBAfH8+4cePCiqkUFxeTl5eH0+kMFS1r33ZkbU1sxH1TzC2MKMgJnf/P//xPj8csIjLQKSgUERERERGRqHbu3Bl2/voHu9jiye3yMW7DxgP7Shj+ywqeWbotap+UlBQef/zx0LnH48Hn8zF69OiwvREBrFYrY8eOJT4+noaGtkrK7fsKrz4UWfkYYPrwrI4xv/56l+MVEZEOCgpFREREREQkKofDwUUXXRR27RfrbJ32f6WuiFF/MfH9p9fR4vZE7WOz2XjppZdC58FgkLq6OgoKChg6NPrS5uTkZEaNGoXP58Pj8fC73/0OgA92VETtf86QjjEeO3as0/GKiEg4BYUiIiIiIiLSqbfeeivs/J9vb+OVuqKwa9u92Vy8MJsrHtnAgaM1nd7LbrdH3M/pdJKWlsaYMWMwmzv/iFpQUEB+fj719fWkp6cDcPBYDVXBxIi+k9PD9yXUPoUiIj2joFBERERERES61NTUFDo2MLj2j1u5ecVQfnuolGv+O5hxD+7j7TV7uryHyWRi0aJFYdeam5uxWCyMGzcOh8PR5ePNZjNjxowhOTmZ+vp6Ro4cCcAGV0ZE37ExlVitltD5HXfc0e1rFBERBYUiIiIiIiLSjYSEBDZu3Bg693h9/OOtLXz7r2t5/p3tBILBLh8fGxvL0qVLw675/X5cLhclJSVkZ0dWL44mPj6e0aNHYxgGP/rRjwBYW2WN6Bdr8jGxNC90/re//a1H9xcRGegUFIqIiIiIiEi3CgoKePnll0lMjFzq25XnnnuON954I+yaYRg4nU5yc3MZPnw4JpOpx/cbPHgwhYWFGIaByWRi1UFX1H7Ti9NCxx6PB5crej8REemgoFBERERERES6lZyczODBg3niiSd44YUXug33ioqKWLZsGZmZmRFtDQ0NxMXFMW7cOGy2zoujRGMymRg1ahQZGRkUFRWxYlv0YiVT8yxh59ddd90JPY+IyECkoFBERERERER6pLCwELvdTlxcHEuXLuXll1+muLg4rM/EiRNZsGABf/7zn6Pew+Px4PP5GDVqFCkpKSc1jtjYWMaOHcuMGTOoqW/igD89os/klMaw8xUrVpzUc4mIDCSRmzmIiIiIiIiIRJGamsqgQYMoKyvD4XCQnJzME0880ePHB4NB6uvrKSwspKCg4GONJSsrizvuuIOnnnqKDY0pFKbVhrUPt1URHxdDc4sHgJaWlo/1fCIiA4FmFIqIiIiIiEiPmEwmCgsLsVqteDyeE3680+kkNTWVMWPGYDZ/vI+jJpOJMWPGkJWVxZqKyGXQFpPBOSOHhM7dbjder/djPaeISH+noFBERERERER6LDMzk+zsbBobG7vvTFvhkpaWFqqrq7FYLIwdO5a4uLhTMhabzca1117Lyn31UdvPKUoKO//Vr351Sp5XRKS/UlAoIiIiIiIiPWYymRg2bBgmk6nTGXqGYdDa2kpNTQ1VVVX4/X7y8vKYOnUqOTk5p3Q8ycnJrN5+FL8R+fF2ao4Rdv7HP/7xlD63iEh/oz0KRURERERE5IRkZ2eTmZlJdXU1GRkZQFs46PF4aG5uxu/3ExsbS05ODnl5eWRlZREfH39axjJ79mx++tOfsss3lNH2irC2SYl1Yee1teH7GIqISDgFhSIiIiIiInJCzGYzRUVFVFVV0dLSgtvtxufzYbfbycjIIC8vj+zsbBISEjCZIvcPPJVmz54NwNq6REZnhweFQ61OMtOSqHa2LZN2uVyndSwiIn2dgkIRERERERE5Ybm5uaSnp1NfX09KSgqDBw8mKyuL5OTk0x4OHs9isWA2m1l7LMDN2ZHtM0YN4tX3OvZTdLlcJCQk9Nr4RET6EgWFIiIiIiIicsIsFgtTpkzB7/eTmpraq+HgR8XHx7Nidy1MjGybXhDPq+91nH/uc5/j1Vdf7b3BiYj0ISpmIiIiIiIiIiclKSmJtLS0MxoSApx//vls3H2UVsMe0TY50x92vmbNmt4alohIn6OgUERERERERPq0Z599lkAwyGZ3VkTbpITqsPPY2NjeGpaISJ+joFBERERERET6tISEBJKSklhXGxfRlmF2UZiXETpvbm7uzaGJiPQpCgpFRERERESkz5s9ezarD3uits0cmRM6rq6uprW1tbeGJSLSpygoFBERERERkT4vKSmJFbsqo7adkx8Tdn7XXXf1xpBERPocBYUiIiIiIiLS5914443sLquiLhgf0TY5PXym4Y4dO3prWCIifYqCQhEREREREenzLrzwQgA2tGRGtI13VGI2d3z83bt3b6+NS0SkL1FQKCIiIiIiIn2exWIhLi6OtdW2iLZ4k4exxbmh86NHj/bm0ERE+gwFhSIiIiIiItIvxMXFsepg9EIl00s7Kh8HAgEVNBERiUJBoYiIiIiIiPQLV1xxBR/siD5b8Jw8a9j5nXfe2RtDEhHpUxQUioiIiIiISL/wyCOPUFHdwJFAakTbpNTmsPM1a9b01rBERPoMBYUiIiIiIiLSLzgcDtLT09nQlBbRNspeSYy9Y//ClJSUXhyZiEjfoKBQRERERERE+o3bb7+dNRWRH3VtpgBTR+aFzs8777zeHJaISJ+goFBERERERET6jVdffZWVBxqjtk0v6liS/Pe//723hiQi0mcoKBQREREREZF+o66ujpXbjxA0TBFtUwd1XNu/fz+BQKA3hyYictZTUCgiIiIiIiL9xrhx42hytbLHnxnRNimpIez87bff7q1hiYj0CQoKRUREREREpN94+umnAVhXnxzRVmyrJiUpPnT+y1/+stfGJSLSFygoFBERERERkX4jISEBq9XKmvJg1PYZozoKmmzYsKG3hiUi0icoKBQREREREZF+JSEhgZV7nFHbzilMDB07nU7tUygichwFhSIiIiIiItKvxMXFsW7nUTyGNaJtanZ4MLh48eLeGpaIyFlPQaGIiIiIiIj0KyNHjsTn97PNkx3RNjGhNuz8wQcf7K1hiYic9RQUioiIiIiISL9y5513ArDWGR/RlmtpYEhOauh8y5YtvTYuEZGznYJCERERERER6VcuvvhiANYc8UZtnzEiN3QcExPTK2MSEekLFBSKiIiIiIhIv2KxWJg0aRIrdldHbZ821BE6zs6OXJ4sIjJQKSgUERERERGRfufCCy9k+74KGg1HRNuUjI6Zhps3b1blYxGRDykoFBERERERkX6nvLwcA4NNLVkRbePjqjFhAsDv97NkyZLeHp6IyFlJQaGIiIiIiIj0O/n5+QCsrYncgzDF3MKIwo4lx//4xz96bVwiImczBYUiIiIiIiLS78ydOxeAVYdao7bPGJ4ZOj548GBvDElE5KynoFBERERERET6ndmzZ2O1Wlmxozxq+7QhHTMNVflYRKSNgkIRERERERHpdywWC9OmTeNQuZOKQFJE++S05tCx2+3uzaGJiJy1FBSKiIiIiIhIvxQXFwfABldGRNuYmEpsVgsA69atU+VjEREUFIqIiIiIiEg/FR8fD8DaKktEW6zJz8TheQB4PB6WL1/eq2MTETkbKSgUERERERGRfum8884DYOUBV9T26cVpoePDhw/3yphERM5mCgpFRERERESkX7r99tsBWLn9aNT2aXkdH4lXrFjRK2MSETmbKSgUERERERGRfslut1NUVISzwcV+f+Q+hWOTOgqaaEahiIiCQhEREREREenHEhMTAdjSlBzRVmKvxWwyAbB169ZeHZeIyNlIQaGIiIiIiIj0W+Xl5QBsd0Z+/HWYvJTkZwJw8OBBVT4WkQFPQaGIiIiIiIj0W6YPZwxuKfdEbR9X2LEkefHixb0yJhGRs5WCQhEREREREem3pk6dCsDmg7VR28cOig0d/+IXv+iVMYmInK0UFIqIiIiIiEi/9a9//QuAnQcq8RjWiPZR6UboeNOmTb02LhGRs5GCQhEREREREem3EhISAAgEg+z1RVY+HpngCh23tLT02rhERM5GCgpFRERERESkX2uvfLzDlRDRVmSrxWpp+2hstUbOOBQRGUgUFIqIiIiIiEi/5nA4ANheY4poizH5GVGQHdZPRGSgUlAoIiIiIiIi/Vp6ejoAW8tbo7aPK2hrt9vtvTYmEZGzkYJCERERERER6dcmTJgAwKYDNVHbxw6KAaCiooJAINBbwxIROesoKBQREREREZF+7Ytf/CIAe8qqaTUiZw2OSgsC4Pf7WbJkSa+OTUTkbKKgUERERERERPq1uXPnYrFYMDDY7Y1S+Ti+MXT8j3/8ozeHJiJyVlFQKCIiIiIiIv2axWKhuLgYgB1NcRHthdZa7Pa2isfLli3r1bGJiJxNFBSKiIiIiIhIvxcfHw/AtiiVj62mIGMK2yofHzt2DK/X26tjExE5WygoFBERERERkX5v8ODBAGw52hy1fezQtNDxY4891itjEhE52ygoFBERERERkX7vggsuALqofJzbUeRkz549vTImEZGzjYJCERERERER6fe++c1vAnDwaA1NRmxE+6hUf+jY7/dHtIuIDAQKCkVERERERKTfs9vtDBkyBIBdnvSI9hHHVT7eu3dvr41LRORsoqBQREREREREBoTs7LaCJTsaIysfD7U4iYuNAaCxsTGiXURkIFBQKCIiIiIiIgPClClTANhWbUS0mU0GY4qyw/qJiAw0CgpFRERERERkQPjVr34FwJajrqjt4/JTwvqJiAw0CgpFRERERERkQHA4HFx++eVs2l8dtX1MTlvl4+uvv743hyUictZQUCgiIiIiIiIDxjPPPMPRyjrqg5H7FI5K9QHwyiuv0Nra2ttDExE54xQUioiIiIiIyIDx7W9/G4Ad0Sofx9VH9BMRGUgUFIqIiIiIiMiAsWzZMgB2NsRGtA2x1JGY4AjrJyIykCgoFBERERERkQGjqakJgG3Vwajt44Zlh/UTERlIFBSKiIiIiIjIgFFQUADA5sPRKx+PH5oMgMlk6q0hiYicNRQUioiIiIiIyIBx1VVXAbBpX2XU9tFZNgDKy8vxer29Ni4RkbOBgkIREREREREZMP7nf/4HgCpnI9XBxIj2USme0PHvfve7XhuXiMjZQEGhiIiIiIiIDBh2u52SkhIAdrWmRrSPcNSHjt97773eGpaIyFlBQaGIiIiIiIgMKFOmTAFgW0NMRFuOpYG0pHgAHA5Hr45LRORMU1AoIiIiIiIiA0piYtuS421Vgajt44tzAKipqem1MYmInA0UFIqIiIiIiMiAYrVaAdhyuClq+9j8tiBxxYoVBALRw0QRkf5IQaGIiIiIiIgMKO17FG7aWxG1fXSmBQCXy8Xy5ct7bVwiImeagkIREREREREZUL7+9a9jMpmoa2ymPJAS0T76uMrHR48e7cWRiYicWQoKRUREREREZECx2+1ccMEFAOxsTYloHx7rDB1XVlb21rBERM44BYUiIiIiIiIy4MyYMQOA7fX2iLYMs4vsjCRABU1EZGBRUCgiIiIiIiIDzqFDhwDYWumL2j5+WDYAL7/8cm8NSUTkjFNQKCIiIiIiIgPW5kMNUa+PG5wAwI4dO/B6vb05JBGRM0ZBoYiIiIiIiAw4Q4cOBWDzvuh7EI7K7Pi4/Nvf/rZXxiQicqYpKBQREREREZEBZ+7cuQC4mls5FEiLaB+V3Bo61vJjERkoFBSKiIiIiIjIgDN79mwsFgsAO5uTI9qHx3RUPq6vr++tYYmInFEKCkVERERERGTAsVgsZGRkALCj3hbRnmJuYUhOKgAej6dXxyYicqYoKBQREREREZEByWq1ArClInqxknHDsgA4cuRIr41JRORMUlAoIiIiIiIiA1IoKDxUH7V9bF4c0DajsLW1NWqfs5HX66Wuru5MD0NE+iAFhSIiIiIiIjIgTZ8+HYAt+yoIGqaI9tHHVT6+8847e21cJ8vlcrFz506WLl3KihUr+lS4KSJnBwWFIiIiIiIiMiB96UtfAqDV7aUskB7RPiqxOXS8atWqXhvXiTAMg+rqatatW8fSpUvZtGkTbreb5uZmGhsbz/TwRKSPsZ7pAYiIiIiIiIicCRdeeGHoeEdzEoXJNWHtpTG1mAADKC8v793BdcPv91NeXs7Bgweprq7G5/ORkJBAVlYWJpOJyspKmpqayM7OPtNDFZE+REGhiIiIiIiIDEgWi4XY2Fjcbjfb6yx8Kjm8PcHkoXBwBvuP1Jw1e/61tLRw5MgRDh48SH19PWazmcTERGJiYsL6mc3ms2bMItJ3KCgUERERERGRAStU0KTcCwWR7eML24JCt9tNIBDAYrH07gA/5HK52Lt3L4cPH6alpYWYmBjS09M7HU9MTAxOp5NgMIjZrF3HRKRn9NtCREREREREBqz2pblbDkaffdde+RhgyZIlvTKmjzIMgy1btrBjxw5MJhNZWVmkpKR0GVra7XZaW1tpbm7utI+IyEcpKBQREREREZEB68orrwRg6/4KfEZk8DbquBon//jHP3prWGGampqoqqoiJSWFhIQETKbICs0fZbfb8fl8NDU19cIIRaS/0NJjERERERERGbA+8YlP8Mtf/hKf388Bfzqltqqw9uMrHx88eLCXR9emoqKC1tZWkpKSAGhoaOC73/0uu3fvDusXGxvLk08+SW5uLmazmWAwqKBQRE6IgkIREREREREZsGbPno3VasXv97PDlUhpanhQWGKvCYVueXl5vT6+QCBAWVkZMTExmEwmbrjhBo4dOxa1r9vt5nOf+xxms5klS5ZgsVhwOp29PGIR6cu09FhEREREREQGLIvFwrhx4wDY7oz8iBxr8lGanwnA3r17e3VsANXV1TQ0NJCQkMAVV1zRaUh4vGAwyJw5c4iJiaGuro5AINALIxWR/kBBoYiIiIiIiAxo7Xv+bSn3RG0fV9i2UeGmTZt6PXQ7duwYwWCQyy67jIaGhhN67GWXXYbH49HyYxHpMQWFIiIiIiIiMqClpqYCsPlgbdT2MbkOoG0Z8DvvvNNbw6K1tZWjR4/yxS9+EbfbfVL3uOmmmxQUikiPKSgUERERERGRAe1///d/Adh5oBKPEbmV/+j0YOi4N4PCiooKXnvtNVpaWk76Hi6Xi6eeeuoUjkpE+jMFhSIiIiIiIjKgXXzxxZhMJgLBIHt9GRHtIxJcoWOPJ/ry5FPNMAwOHDjAn/70p499r3vvvVf7FIpIjygoFBERERERkQHNYrEwefJkAHa64iPai201WK0WAN56661eGVNdXR133333Kbvfvffee8ruJSL9V+ScahEREREREZEBpn3G3bYaM59JC2+zmwKMKMhi697yUEETi8VyWsdTVlbG2rVrQ+dDcjPITY8nI8lBRoKdjAQr6XFm0h2QFhskze4nzeYl1eIh2ezmmD+RX66P5W+LNgPw4IMPcv/995/2cYtI36agUERERERERAa85uZmALaWt0JpZPv4gnS27i0HYMmSJVx88cWnbSw+n48ZM2YAMGNcIY9fYmesvRzwAnU9ukeqvZm/ToeKhlLeXLkbOP3jFpG+T0uPRUREREREZMAbPnw4AJsO1ERtH5MbEzr+29/+dlrHsmPHDjweD0kJDp67LPhhSHhybpvWsZT673//+6kYnoj0YwoKRUREREREZMC74IILANhTVk2rYY9oH53WUfnY6XSetnEYhsHEiRMBuGnucAZbejaDsDNTkmpDx//9738/1r1EpP9TUCgiIiIiIiID3u233w6AgcFub5TKx/GNoePExMTTNo6jR48SDLaFkjeN9H7s++VZ6snLTg3d2+v9+PcUkf5LQaGIiIiIiIgMeHa7nalTpwKwoykuor3QWkuM3QbAli1bQmHeqfbpT38agFHDcpkae6RHj2kw4jjgT+eAPzLgBJg5clDouLi4+OMPUkT6LQWFIiIiIiIiInTsU7gtyjaFVlOQeVOGAbBr1y5qaqLvZfhxBAIBtm/fDsCXz8+L2ud3h0uY/Wo6Y56KI/sRg0XTn2Ht+U8z7P4DXPbv1qiPmV7gCB0fPnwYl8t1yscuIv2DgkIRERERERERID8/H4D39tRHbb98TELo+Fe/+tUpf/7Kykp8Ph9ms5nrB1dGtHsMK//3wk7+u+EA2/ZXMHLcJGJi47BYLIwfP55teytoNBwRj5ua4Qk7v+aaa0752EWkf1BQKCIiIiIiIgLMnTsXgHc3HqQ2mBDR/qms6tDxG2+8ccqf/8c//jEAl8wsJcfSENH+Rv1QnI3NofMf/vCHoeMbbrgBA4ONLVkRj5sQV4kJU8d9TsPYRaR/UFAoIiIiIiIiAsyePRur1UowGGRRbU5Ee56lnikjhwBQW1uL2+0+Zc/d3NzMn/70JwC+NClyViDAk+taQsf33nsvFosldD5p0iQA1lRHVmxONLkZW5wbdq21NfoyZREZ2BQUioiIiIiIiAAWi4XrrrsOgFd3eKL2uXJy24y9qqoqqquro/Y5Gd///vcxDIO05AQ+mVIW0V4RSOb1FXsAiImJYd68eRFjt9vtrCrrZJ/C4Zlh53feeecpGrmI9CcKCkVEREREREQ+dNNNNwHw+qp9uA1rRPslg9uW/vp8PhYtWnRKntPv9/PII4+0Pf/cEmJM/og+zxzJClVaHjp0aNT7XHjhhby//WjUtumDw1/L6tWrP86QRaSfUlAoIiIiIiIi8qH2asauFjfLXUMi2sfHHCM/Nw2ARYsWhcK7j+M///lP6Pim4dFnBP75vx0BYHt15o+6/fbbOVbVwNFASkTb5NTwSsdbtmw5iZGKSH+noFBERERERETkQ7m5HXv5LdhnitrninPaqiMvX76chobIoiMn6qGHHgJgfOlgJsYci2hf0zqY7QcqQudf+9rXot7H4XCQnp7Ouqb0iLaR9iocsR37F3q93lMydhHpXxQUioiIiIiIiHzovPPOCx2/vOpQ1D6XDmubRVhXV4fT6fxYz+fz+Vi7di0At5wbWUAF4KmdHQFfbGwsDkf0YicA8+fPZ01FZMBpMwWYNnJwRF8RkeMpKBQRERERERH5kMViCVUTPlzhZKNnUESf8xKOkBAXi9frpby8/GM93/79+wGwWi1cmxd5r1bDzj+W7Qqd//Of/+zyfpMnT2bFvugzBWcUp4SdtweUIiLtFBSKiIiIiIiIHCc2NjZ0/Prh+Ij2GJOfT08vAmDx4sW43e6Tfq5JkyYBcNms4WSZmyLaX3MOoaGpbd9Ck8lEWlpal/cbP348K7cfIWBEziqcmht+HggECAQCJzlyEemPFBSKiIiIiIiIHCczMzN0/NK6qqh9LhsZA8CLL7540suPy8vLaWlpAeCLE+xR+/x1bXPo+O6778btdmMYRqf3tFgsxMTGs9OXHdE2OTFynEuWLDnRYYtIP6agUEREREREROQ4t912W+h43c7DHAmkRvSZn1aO2WympqYmVCn5RF1//fUAZKYlcXFyWUT70UAKb67cEzo///zzcbvdVFdXU11dTVNTE36/P+JxX/jCF1hblxhxfajVSVZaUti1v/3tbyc1dhHpnxQUioiIiIiIiBznjjvuCDtfWJkR0SfN3MwFEwqJi4ujoqKCYDB4Qs/hdrt5//33AfjCnGLspsglwP86lIlB2+xBu93OzJkzufDCC5k2bRoFBQWYzWbq6+uprKykrq4uNNtwyJAhrDkafUnxrNHhey5u3rz5hMYtIv2bgkIRERERERGR49jtdkaMGBE6f2Vr5N6BAFdMSKWyshKXy0VDQ/QCItG4XC4++OCD0GzAm0qbo/b7838Ph44vvvhikpKSSExMpKCggKlTp3LxxRdz3nnnMXbsWJKTk3G73VRVVZGbm8uKPbVR7zm9MHzPxcbGxh6PW0T6PwWFIiIiIiIiIh9x1VVXhY7fXrOfJiM2os+ncupobm6mqamJ2trowdxHOZ1OPvjgA5YuXQrAlJFDGGOPrHa8omUIu8s69kd86KGHMJnCC5TYbDays7MZNWoUc+bMYe7cuZxzzjkUFBSw67CTZiMm4r5TMn1h5ycScIpI/6egUEREREREROQj5s6dGzr2+f0sqc+L6FNsq2bUsFweffRRqqqiFz05Xnl5OStXrqShoYHHHnsMgFtmRRYdAfj7dkvoOCMjg4KCgi7vbTKZSEpKoqCggMmTJ5OcnMym1sh7T4oLH2djY6MqH4tIiIJCERERERERkY+YPXs2ZnPHR+ZXd0cP066cmsvGjRupra3F7XZH7WMYBgcOHGD16tW0trYSGxtLXV0dNquVz+Yei+jfYtj51zu7Q+evvPIKsbGRMxo7Y7VamTp1KmtrImcUpphbGFGQE3ZNlY9FpJ2CQhEREREREZGPsFgslJaWhs5fXbkfvxH5EfqSoR58Ph/19fVRlx8Hg0F27tzJ+vXrAUhLS+MnP/kJAFedP5x0syviMa/U5tPU3BY6OhwOhg0bdsLj/9GPfsTKsujB5cwRmWHnqnwsIu0UFIqIiIiIiIhE8d3vfjd0XFvvYlXr4Ig+02KPkJmWxG9+8xtqamrC2vx+P5s2bWLLli3ExMSQnJyMyWRizZo1ANw83hb1ef+6qmPfwLlz55KZmRm1X1eys7NZs7cmatu0Ifaw87feeuuE7y8i/ZOCQhEREREREZEoCgsLw85fO2iP6GMxGVx+TgH79++nsrKSYDAIgNvtZs2aNezevZukpCQSEhIAaG1tBSAnGKNWPAAAgQZJREFUM5mLEg9G3K/Mn8bitftC5z/+8Y+xWCwR/bqTlJREQ2uAikBSRNvUtJaw89raWrxe7wk/h4j0PwoKRURERERERKI477zzwioN/2f1kaj9Liu14PF4cLlc1NfX43K5WLVqFWVlZaSmpobtL/iDH/wAgC/OKcZqCkbc659l6RjHnZ/MsmOA+Ph4MjIyWe/KiGgbHVOJ3W4Nu/brX//6pJ5HRPoXBYUiIiIiIiIiUVgslrDqx7vLqtjly4roNyf5CIGAn9bWVg4dOsSKFSsoLy8nIyMDu71jFmIgEAjtVXhjUWPU5/zLO2Wh4+HDh5OcnHxSYzeZTFx00UWsqYycjRhj8jNlRPgy6qeffvqknkdE+hcFhSIiIiIiIiKduPnmm8POFx5LieiTYPJw8dRhvPXWW5SVlVFXV0dWVhZWa/isvU2bNgEwfUwBI+2VEfdZ3pzP/iMd+wo+++yzYTMaT9Rtt93Giv3RA8kZxalh5x6P56SfR0T6DwWFIiIiIiIiIp0YMmRI2PlLG51R+10xOoGVK1cCkJmZidkc+XH7iSeeAOCWmelR7/H3rR2hoNlsZvjw4Sc15nYZGRlsLWsgaESGjdMGhV9LTU2N6CMiA4+CQhEREREREZFOnHfeedhsHdWJ3998kOpgYkS/T2ZVs3v3bhISEqLOAvR6vezcuZMYu42rs49GtDcZsTz7392h869//es4HI6PNfakpCSw2Njjj6yaPDm5Iex869atH+u5RKR/UFAoIiIiIiIi0gmLxcL48eND58FgkEW1ORH9BlnqmToqP7QH4Uc9//zzmDDx65vGk2JuiWh/uXowza0dy3/vvPPOjz32mJgYXC4X6+ojKx8XWatJS04Inbe0tIQqMovIwKWgUERERERERKQL119/fdj5gu3RA7UrJ2Xx4x//OGrbU//4Oy9+ayJfy9sdtf3JVXWh48zMTAYPHhy134nKyMhg1bHI6soAM8fkhZ3fdtttp+Q5RaTvUlAoIiIiIiIi0oVvfvObYeevr96H27BG9LtkcBMulwuXyxV2/diRA7zz7VKuTN0b9f77/Rm8s/5A6PwnP/lJRCGUk3XNNdewYnf0fRWnFySEnb/wwgun5DlFpO86bUHh/fffz8yZM4mLiyMlJeV0PY2IiIiIiIjIaWW324mLiwudN7d4eLdpSES/cTHl5Oemc8cdd3T0rStn2o77me443On9v7XUEnZ+5ZVXnoJRt7njjjvYsPsobsMW0TY1yx927vf7I/qIyMBy2oJCr9fLZz/7Wb72ta+drqcQERERERER6RUXXnhh2Plr+yILlgBcOT2fvXv3EggEaDy2k+kbv0uxrTpqX69h4Ysr8nl9xZ7QtUmTJpGZGVl85GSlpaVhtdrY5M6OaJuUED4uBYUictqCwvvuu4877riDsWPH9vgxHo+Hxv/f3p3Hx13We/9/T2YyyWTf96RN0nShG6UCBQ3UgoCiguBR0ANy43bLIiL6E5dz8Hi8jx6Py/GAuCCKoIDrAQVEoBhbZCl0gULplqTZ932fZGZ+f4yZyfT6ts0yM0mb1/Px6OO+5vu55vv9ZJI53n68ruvT3x/yDwAAAACA+fbggw+GvP7fF49YzntPmUeStO0PP9KFB/5VmTbr/17b53Xp3U9k6L6nQrsN/+IXv7DsmjxbdrtdhYWF2tmVYMSyYga1rDhYlPR6verr6zPmAVg8FtQZhd/4xjeUmpoa+FdcbC7lBgAAAAAg2pKSkhQbG9y+29jeq92jBca8tyU26isf3Kh/zXpaCbYxIy5JjZ50nfdwjJ5+pdp4RmlpaXgTl9TX16cX60ctY+esDF1peMkll4T9+QBOHguqUPjFL35RfX19gX8NDcc+wwEAAAAAgGj67W9/G/L6sYZEY06cbUL/vvKQ7Daf5T32juXr7J/06rVDLUbskUceUWKiec+5ys/P1wv72yxjm0riQ/PbuzfszwcWuuHhYb3++uvy+ay/t4vJjAqFt99+u2w223H/7d+/f9bJxMXFKSUlJeQfAAAAAAALwbvf/e6Q14/sbJ3R+58ZWKpz/+eImtvN7b0xMTFasWLFnPI7ljvuuEOHGzrU6U0yYhszh0Neh3PbM3Cy6O3tVXt7uzwez3ynMu9m1G/9tttu03XXXXfcOWVlZXPJBwAAAACABclutysjI0Pd3d2SpF0HmtTgWaJie88J33tf2zJ97Cd75PF6LeP333+/cnJywprvpMsuu0yStGswWxelDIbE1se3yeGwa2LCXyCJj4833g+c6txuN0XCf5hRoTA7Ozus3ZcAAAAAADiZ7N+/P6Sg90Rblj5ZcPxC4b8dXKavPrTruHPWrl0rp9MZlhyP5nA4FBsbq5fbHbroqI178bZxbVheqJf31UuShoaGIpIDsJBRKAyK2BmF9fX12rNnj+rr6+XxeLRnzx7t2bNHg4ODJ34zAAAAAAALUHZ2dkhB79G9A8ec6/bZ9X9eXHLCIuE999yj/Pz8sOVoxW6368Uj1v99/JzlGYHx6Kh10xPgVEahMChihcJ//dd/1YYNG3THHXdocHBQGzZs0IYNG/TKK69E6pEAAAAAAETcwECwOPjMKzXqsjj7r8/n0rv/nKn7/nLi5iBlZWXKzMwMa45HKy8v1/N7Gy1jZxXYA2Ofz8cCHyw6o6OjNDL5h4gVCu+77z75fD7j3+bNmyP1SAAAAAAAIs7pdOrGG2+UJI1PTOjLu7JC4g2edJ3/kF1Pv3z4hPe6//77VVxcrJiYiP3Xc0nSO9/5TnX3D6l6PMuIvSUttLnK1VdfHdFcgIVmZGRkvlNYMCL7f4kAAAAAADgF3XXXXYqNjZUk/fjx13Teo1n6Vm2FPre3XKu+06pXDzWf8B5nnnmmUlJSlJeXF+l0dckll0iSdvanGbEKR4dSklyB1+wExGJDoTBoRs1MAAAAAACAX29vrxITEyVJ2/fUaPue6b83LS1Nn//855Wdna2kJHPrcrhN7u7b0ezTB47a5Rxj8+mc1UX6y0uHJIktmFhUPB6PxsfH5zuNBYMVhQAAAAAAzEJCQoJeeOGFGb8vLS1NDz/8sCSpqKhINpst3KkZ7Ha7CgoK9MJh6w7N55QF2yFP7eoMnOpoZBKKQiEAAAAAALOUl5enX//619M+Y3DTpk365S9/qb6+PpWWlqqgoCDCGQaNj4/rlf2NGvOZmwvPzA0WSurr66OWEzDfKBSGYusxAAAAAACzlJ2drfj4eP3pT39SX1+frr/+eo2OjobMsdvtuvDCC3XLLbdofHxcIyMjWr16tVatWhXxJiZTxcTEyO2e0BtjuTojvikkdkZSZ2Dc19cnj8cju91+9C2AU85koXDyzNHFjkIhAAAAAACzlJCQoMzMTLW0tCg/P19//vOfLef5fD719PQoJiZGGzZsUFlZWVS2HE915pln6rHHHtPL3Qk646iFjHn2fpXkZ6i+pVuSVFVVpQsuuCCq+QHzgRWFodh6DAAAAADALNlsNuXn58vj8RyzCYjX61VnZ6ecTqfOPPNMlZeXR71IKEkPPfSQJGlHg9sy/tZV+YFxVVVVNFIC5t34+DiFwikoFAIAAAAAMAeT24+P3nIs+TuqdnR0KCUlRZs2bVJhYeE8ZOiXlJSknJwcPb+/wzJ+9hJXYOz1eqOVFjCvWFEYikIhAAAAAABzkJSUpIyMDA0PD4dcHx8fV2dnp3JycnTOOecoKytrnjIM+sxnPqP9R1rV600wYmdmBQudaWlpUcwKmD9jY2MUCqegUAgAAAAAwBzYbDYVFBRoYmIisP14bGxM3d3dKioq0qZNm5SSkjLPWfoNDg5KknYN5xix9a62QHOVP/zhD1HNC5gvo6Oj83IUwEJFoRAAAAAAgDnKyspSXFycxsbGNDw8rL6+PpWXl+uss86Sy+U68Q2iZLIQ+EqH2eE10TampQUZkqQXX3xRbrf1WYbAqWRkZIQO31NQKAQAAAAAYI5SUlKUnp6u7u5uDQ8Pa9WqVdqwYYNiY82C3HzavHmzJOmNVusi4IqijMD47rvvjkZKwLzx+XwaHR2lUDgFhUIAAAAAAOZocvtxcnKyTj/9dK1Zs2ZBFh82b96suLg4HWzut4xX5AXPLjx06FC00gLmhcfjkdvtXpDf1fnimO8EAAAAAAA4FSxdulSZmZnKyMg48eR5Yrfbdf755+uVF/8uySyOLMsIXuPcNpzqJjseUygMYkUhAAAAAABhEBsbu6CLhJOuuuoqdfcPqdubaMSWpUwExhs3boxmWkDUjY+PUyg8CoVCAAAAAAAWkZdeekmSVOtOM2KlCcPGPOBUxYpCE4VCAAAAAAAWkVdffVWSVDNkdmNe6uiWTf4tx3/961+jmhcQbW63Wz6fL9ANHJxRCAAAAADAotLW1iZJqu6zSZmhsXjbuEryM1TX0qXq6mpWW+GUdrhtQK3DUvfh1zXY0ymXy6XNmzcv6r95SqYAAAAAACwi+fn5kqSDHeOW8RXF/nMWPR6Ptm/fHrW8gGj76qN79d39ibqvf41+492ka39To9J//rr+8Ic/zHdq84YVhQAAAAAALCLve9/79Pzzz+tgc79lfHleop76x7ipqSl6iQFR9Ic//EFX99+r9ck9avOlq82Rrrb4dFVrXFde+VX9/ve/1xVXXDHfaUYdKwoBAAAAAFhEPv3pT0uSDtR3WcaXZQbXFDU3N0clJyCaPB6PPvGJT+j0hHadHbNf77W/oI87ntBXYn+lz6VtlSR94hOfkMfjmedMo49CIQAAAAAAi4jT6dTKlSvV2TugXm+CES9PmQiM9+zZE8XMgOioqqpSV0+vcu0DRqxl1ClJ6urqUlVVVZQzm38UCgEAAAAAWGRWrFghSToynmbEShOGA+OhoaFopQREzZe+9CXZE1OVa+sxYi1DwVLZM888E820FgQKhQAAAAAALDIZGf6GJTVDLiNWGtttzANOFW63Wzt27FBWZobibWZDn+YBb2D8yiuvRDO1BYFCIQAAAAAAi8zkluLDfXYjlmBzqyg3XZL017/+NZppRczQ0JC8Xu+JJ+KU99///d+SpKLMRMt4U1+weJiYaD3nVEahEAAAAACARaa3t1eSdKjDbRlfUexfSXjkyJGTvqGD2+3Wiy++SAdnSJIeeOABSVJhhrmaVpKaukcC48rKyqjktJBQKAQAAAAAYJFZs2aNJOlQ66BlvCIvKTDeunVrVHKKlLa2NnV1damzs3O+U8ECMDY2JkkqTHNaxhs7gt+Jm2++OSo5LSQUCgEAAAAAWGQefPBBSdL+BuviWUVWbGB8//33RyWnSPD5fGpsbNTIyIja29tP+tWRmLvly5dLkgqSrUtijV3+QmFZWZmcTuti4qmMQiEAAAAAAItMUlKSkpKS1NbZrwFfvBEvTwkW1Orq6qKZWlgNDAyovb1daWlpGhoaUl9f33ynhHlWUVEhScpPNIvGXp9NbYM+SdJ73/veqOa1UFAoBAAAAABgEXrXu94lSTriTjdiZQlDgXFBQUHUcgq31tZWjY6OKiUlRePj4+rp6ZnvlDDPtm3bJknKjzc7Hnd4EuXxhc5bbCgUAgAAAACwCNXX10uSaoYTjFipM1hQO1kLJl6vV/X19XI6nbLZbIqJieGcQmhgYECSlBc7bMRa3C5j3mJDoRAAAAAAgEWora1NknS4zywNJNnGlJeVKsm/Ks/ttu6OvJB1dnaqt7dXSUn+xiwul0sdHR0aHzdXkmHx6Ovrk2IcynWYhcCWkeDZnMnJydFMa8GgUAgAAAAAwCKUkZEhSTrUNWEZX1mSGRjffffdUckpnJqamuTxeBQb6y/+xMfHa3R0lO3Hi5jb7VZHR4cciWnKUa8RbxkKlskuvPDCKGa2cFAoBAAAAABgEfq3f/s3SdKhliHLeEVeUmBcXV0dlZzCZXR0VM3NzUpICG6rdjgc8ng8FAoXsbvvvls+n095OWmKtZnNTJoHvIHxRRddFM3UFgwKhQAAAAAALEKXXHKJYmJidKDB+ty+iixnYFxaWhqttMKira1Ng4ODSkxMDLnucDjU1tYmn883T5lhPk0WvIsykyzjTb3+LfZxcXHavHlztNJaUCgUAgAAAACwCNntdt1+++1qau/VsM9pxMtTgyuuVq5cGc3U5sTn86mhoUF2u10xMaFlD5fLpd7eXo2Ojs5TdphPS5culSQVprss403d/gYnV111lex2e7TSWlAoFAIAAAAAsEhNdj6uHc8wYuWJI4HxQw89FLWc5qqvr0+dnZ2BJiZTxcfHa2xsjO3Hi9SKFSskSYVpDst4Y4e/wcn73//+qOW00Fh/MgAAAAAA4JTX398vSaoZTtTqoxYVLnX2GPNOBi0tLRobG5PdbtfXvvY17du3T2NjY8rIyNDGjRv1gQ98QN3d3SooKJjvVBFlv/71ryVJBck2y3hj13Bg3rvf/e6o5bWQUCgEAAAAAGCRq+6PkdJCr6XaRpSdkaKO7n61tLTMS14zNTExoYaGBn3xi19UbW1tSKy5uVnNzc3605/+pLPOOksvvviibDbrghFOTc8884wkKT/Ba8TGfTHqHPafXTk4OBjVvBYSth4DAAAAALBITa6qO9xpdoCVpBUlmZKk1157TR6P9ZyFpKOjQ+9+97sDRUKbLUZXbl6jj1+6QSUFWYF5O3bsUF5e3nyliXkwMjKi1tZWSVJ+/JgRb5tI0mSLm7e97W1RzGxhoVAIAAAAAMAiNXlm28HWIcv48jz/OX9jY2OqqqqKVlqzVlhYqPHxcUn+Dsd///xp+t359frJW6q172M2XbxpRWBue3v7ot1euhjddtttgXFu7LARb3EHG5zcfPPNUclpIaJQCAAAAADAInXDDTdIkg40dlnGK7KDBxc+9dRTUclptrKzs+Xz+QKvb718vc5x1QdeJ9rG9N9bQrecPv744xoZGRFOfS+99JJ/YHco326eudk6EitJysnJkdNpdgFfLCgUAgAAAACwSDmdTuXk5KihpUejvlgjviw1WFibPN9tIeru7lZnZ2fItY8t7zPmrYxt05ry0CYmCQkJEc0NC8PkuYNxyenKlFkobB70n1eZlpYWzbQWHAqFAAAAAAAsYsnJyfLJpyMTGUasLHE0MO7rMwtvC0VWVlbI6/M2lGl5bLvl3EvPyDeuTa6sxKlrcpt9YXaaYmw+I9484AmZt1hRKAQAAAAAYBGb3HpbM5xoxEqdvYFxd3d3tFKake7u7pAtx5L08U3px5x/ccm4ce2HP/yh3G532HPDwnH++edLkgozzb9zSWrqdYfMW6woFAIAAAAAAFX3241r6TFDykzzNzTp6+tbkJ2PJzs3T0pKdOny7PpjzJbOSWxSgivOuP79738/7Llh4ZhcNVqYEW8Zb+waDpm3WFEoBAAAAABgEZts3HCoy7oIuLzYv63X6/Vq+/btUctrOgYHBzU2NhZy7ZotK5RkGzvGO6R427gu2lhqXL/33nvDnh8Wjueff16SVJhinsUpSY0dfSHzFisKhQAAAAAALGJnn322JOlQ27BlfHl+cmDc1NQUlZyma+3atca161adeAvxJauSjGsHDhxYkCsmER4/+tGPJElT/pxDNHX7t+BXVVVFKaOFiUIhAAAAAACL2Ec/+lFJ0oEG6zMIl+c4A+PW1tao5DQdbrdbR44cCbm2dlmBznI1nvC978ix/lmfeuqpcKSGBcbj8eiPf/yjJKkgwSwGj/gc6h01Li9KFAoBAAAAAFjEtmzZIofDobqWbo35HEa8PDXYKKSzszOaqR3X9773PePaJ84rsJhpKnN0avmSXOP6xz/+8TnnhYXn2WefDTSryYszt6W3jgdXmG7evDlaaS1IFAoBAAAAAFjE7Ha7zj77bHm9XtVNZBjxsqTgUqujV/DNp//8z/8MeR3rcOiqwuZpv//dGwuNa01NTXQ/PgX94he/CIzznUNGvHXM3+DE6XRSKJzvBAAAAAAAwPwaGfGfz1YzkmjESp29gfHBgwejldJxud1u9fT0hFy78vyVyooZNOY+O7BEXp/NuH7xUuvzCK1WKuLkNlngtjmcyo3pN+ItI/4GJ2VlZbLbze7fiwmFQgAAAAAAFrnBQX+Brabf7AibFTOo1OQESdLrr78e1byOxaqYd/166wLPf24f0Wtuc0vy25KaFOc0f9777rtvzvktdKOjoxoaMlfWnary8/MlSQkpaUq3mcXk5n98FGvWrIlmWgsShUIAAAAAABa54uJiSdKhbutVditKsiT5V/JNFhXn0/333x/yujg/U1uSjhjzjkxkavveRh10rjZiCTa3LthYZr5nAW2vjpRDhw5px44dGh8fn+9UouKNN96QJBVlp1nGm/s9IfMWMwqFAAAAAAAscrfddpsk6VDbsGV8eUFKYPyhD30oKjkdz5tvvhny+uNbSmW3+Yx599dkaP3pp8tZfr7lfd51WrJxbWJiIjxJLmA9PT1qbW1VdXX1fKcSFe3t7ZKkwqwEy3hTjztk3mJGoRAAAAAAgEXuoosukiQdbOi2jC/PdgbGL7/8clRyOpbBwUH5fMGioE02XbvU7Mbs8dn007/W6Mtf/rJSilaq12sWiS7M7TWuORxm5+dTycTEhAYGBiT5Vxb29fXNc0bRU5geb3m9sWv+V8kuFBQKAQAAAABY5Ox2uxISElTT1KVxn3nWX3lacDw6OmrEo+noFY0XnV2hJQ6zwLl1YKnae4aVlJSkmBiH/j6yxJizIrZdSwuzQ66Njo7K47Hegn0qGBoaktvtVkZGhoaHh7Vv3z55vd75TiuiYmP9Z1EWpFgXgRs7/YXT8vLyqOW0UFEoBAAAAAAAysrKksfrVb0nw4iVJY0FxikpKUY8mv72t7+FvP7YWUmW8362Z1xf+9rXAq/Hiist573nLUXGtTvuuGMOGS5sQ0NDGh8fl9vt1re+9S2de+65stvtstlsstls+ud//udAF+xTgdvtVmtrqySpwPpPRc3d/p+3oqIiWmktWBQKAQAAAACACgr8nYFrRsxqSmlcnzFvPrjdbvX39wdeZ6Qk6t3pR4x5Hd5k/X77AW3cuDFwLaF0k+U9Lyk1zzb8xje+ccquKhwaGtIXvvAFvfe979WuXbuM+K9+9SslJCTo8ssvj35yEXD33XcHxvkJ5u90wBunQf8Rhbr22mujldaCRaEQAAAAAAAoMzNTklQzEGvEcmP6lZTgP99tPhs+3HnnnSGvr7twheJtZvORhxvztHbtOtnt/m3UQ0NDik1I0xvufGNuZUqzYo86l9Dr9eqZZ54JY+YLxxlnnDGtzs6PPvroKVEsnNqwJT/OXCnZMu4vjDscDl1wwQVRy2uholAIAAAAAAACRbXDXdYr6VaU+M/yq6mpkdvtjlpeU23bti3k9XXLhyzn/Xhbk0pKSiRJ4+Pj6u/vV19fn57rzzXmJttGtfmMUuP6N7/5zTBkvLBceumlGhycfuOORx999KTfhjz5dyBJebHm30vrWJwk6eqrrw58BxYzCoUAAAAAACBw9uDBduvC0IrC4NmER6/si5b6+vrA+MzTSrQ2rsWY89JIkd6oblVRkf/swYGBAWVkZGh8fFxjuRuN+ZL0rtWpxjWrbbkns5GRET3xxBMzfl9eXl4Esok+W2yccmP6jestI/7VpGvXro12SgsShUIAAAAAAKBrrrlGknSwsdcyXpEdHxhv3749GikZpnZc/sTbsi3n/PwNf+Hnve99r3w+n8bHx5Weni6Hw6FlG96ufl+88Z535JkFpKlnIZ4KzjrrrFm9r7+/X7feemuYs4me2tpaSVJqWrqSbWYRvHkwdN5iR6EQAAAAAADoggsukM1m0+HGTk34zHJBeXpwPF9FtMkVha54p/4pr9GID/ri9Ku/HlBcXJycTqeGh4flcrm0cuVKJSYmasLr07Y+sxnLamerinLNbs/ztcU63Nxut15//fVZv/+///u/T9rPorHR/3dSmG3drbu53xMyb7GjUAgAAAAAAGS327V69WpNTEyowZNuxMuTxgLjmJjolxPcbreGh4clSVdtXqlUi9Vhf2gv1uDwmLKysiT5m5gUFBQoJSVFeXl5Gh0d1dYGh/E+SXr3mSXGtfnaYh1un/zkJwPjd7ylTLe//3RdUbliRvf41re+Fe60osJms0mSijITLeNN3aMh8xY7CoUAAAAAAECSVFZWJkmqHU02YqVxfYFxYqJ10SWSvvOd7wTG16/xWs6554VuSf7OvuPj44qJiQmcVZidnS2bzaZ2m/WZe5eUmYWi5557bq5pzzuPx6P77rtPkvRf156hpy7t1DdW1+j3W1r0q09t0HTLY3fccUfEcoykgwcPSpIK0+Ms401d/gYn8/E3vRBRKAQAAAAAAJKk/Px8SVL1QKwZs/cpId5fbJl6VmC0fO9735MkLV+So7cl1hvxA+M5eu7VI5KkT33qUxocHFRaWpqys/1nGWZmZio+Pl7vu+oj2u/OMd6/ObVF9qNWSiYkJIT5p4i+p556SpKUn52qm5ceCYl9KKda//LBDdO6j9frnVHH5IXA7XZr//79kqSCFOuOxg0d/gI4hUI/CoUAAAAAAECSlJHhP6evutt6xd7yEn/Rbdu2bfJ4PFHLy+PxqKOjQ5L08c3mFmFJuu+Q/wy6mJgYxcfHy+12q6SkRHa7v0AUHx+v7Oxs+Xw+/bUry3h/asywKk8vDbnW1tYWzh9jXkyuxHz7uiLF2SaM+L+sqNXmDaXGdSsf/vCHw5pbpE3dOl6QZD2nuce/pf7NN9+MRkoLHoVCAAAAAAAgSYGi2qF26xWDKwr9xbjR0VFVVVVFK63As2JiYvTh4nYj7vbZde/Ww5L826dHRkbkcrlUUBDauCQ3N1der1cvtZkrJiXpXWtCz2Z89tlno1oQjYQXXnhBkrQ63+z2LEkOm1e/utSjrLRjVNKmiObvPBy2bdsWGBe4xo14tydBYyf3rzfsKBQCAAAAAABJ0ubNmyVJB5p6LeMVOcFiUzSLRs8884wk6b3nLle+vdeIP9m3VB3d/k7M119/vYaGhpSXl6ekpNDiV2ZmpuLi4rS7pkdDPvPMuncUhG6t9fl82rp1a5h+iuib2gDmtAzrVaKSVGDv1a/+T9kJzyvs7+8/qbofNzQ0BMZ5cWbxu3U8uN34sssui0pOCx2FQgAAAAAAIMlfKHS5XDrU0CGPzywblafPT2fYV155RZL00Y3Wq+J++spwYHzGGWdIUqCJyVTJyclKTU3V+tM3aPtAgRE/Pa5ZuVmpIdfuv//+Wec93ybPdZSklUnHP1/wopQj+uIHzjjhPe++++455xUtLpcrMM5zDBnxlrFgsfiWW26JSk4LHYVCAAAAAAAgyb/1+Atf+ILc7gk1edKNeHlScDXZ5OrDaOjt7VVMTIzentpkxJo8aXr8hUOSpOXLl2tkZESpqanKyTEblthsNuXn5+viiy/WX2qti56Xnrk05HVtbe3cf4B58uMf/1iS5HDYVeboPOH8r66s1dtOP/55hZNdhE8GpaX+n8XmdCk3pteItwz7t9qvWrVKTqczmqktWBQKAQAAAABAwBe/+EXZbDbVjiUbsdJ4//bemJgYVVZWRiUfj8ejPXv2aN2yAiXaxoz4bxuz5fX6t9WuWLFCY2NjWrJkiRwOh+X9Jrsf/3V/j2X8nctCu+MODZkr0U4Wk81YVi3NkdN24sP4Ym0ePfRurzKPc17h5OrOk8GHPvQhSVJmRpribeYZhS2DPknSt7/97ajmtZBRKAQAAAAAAAHPP/+8fD6fagbMFVYFMb2Kc8bK6/Xq+eefj0o+W7du1cTEhM5ebnYqlqTtNcFtxxUVFYqPj1d+fv4x75eRkaHExETVNveoety855a0FsXEBMslJ9MKuqmmnk+4bmnmtN9XZO/RA/+n/Jjx119//aRp8LJ3715JUlF2imW8qX8iZB4oFAIAAAAAgClaWlokSYd6fEYsxubT8hJ/ce3RRx+NSj733XefJOnsQrtl/Pl9zYFxcnKycnNzlZxsroacZLfblZeXJ7fbrafbze3VGTFD2rSmJPB6ZGTkpGrgMel//ud/AuM1+WbjFkl6uLPC8vo7U2r1hfdvsIyNjIxo+/btc08wCv70pz9JkooyEyzjTd1jIfNAoRAAAAAAAEwxuRrvcLvZJVaSVhSmSfKffxeNlWWvvvqqJOmMdHMLcKMnXa2dfZL8BcBVq1apqKhINtvxm65kZ2crMTFRT7xp3eDj0nWhKw3vvPPO2aQ+rx555JHA+LQM8/c04nPqmh/v0XPDSyzf/7XTjuicddbnFU7tJryQ9fX5/zYK06wLpU2dgyHzQKEQAAAAAABMUVlZqczMTB1osi6eLMv1d5IdGRnR1q1bI55Pe3u74pyxOs3ZZsR2DWQExgkJCUpLS1Nubu4J75mZmal3vetdevqVGo36Yo34OwqHQ15v27ZtFpnPr56e4BmMKxLNgughd6YmJjy69akJdfnMrblOm0cPv9en9JREI3ayfB5r1qyRJBWkWJe/Gjr6QuaBQiEAAAAAAJjCbrfrtNNO08H6Dnl95sq8ivTgtV/84hcRzcXj8ai7u1tvWVmoWItmHK+0BssaqampKikpUWysWfg7Wnx8vD72sY9pdGxcfx8sNOJnxDUpMy24fbmpyey2vNAdOuTvBB3rcKjM0WXE3xzwFwCb2nv1XOlnLH/XJfZu3X/9cuN6tM6nnKuNGzdKkgoSzW30Xp9NrX3ukHmgUAgAAAAAAI7i9Xo1OuZWizfViJUlBc/rq6uri2geVVVV8nq92rTMPEtQkl6q6Q+Mly5detwmJkcrLi5WTk6O/lJnnn1ot/n0rrOWBl4XFprFxIVscHBQ4+P+Lr+nleVaFln3dfkLg0lJSUpdulFPp7zP8l7vTq3WbVeeEXKtpqYmzBlHxuQW6XyX2fG4w5ukCX+z7Bn93ZzqKBQCAAAAAIAQJSX+Zh61o+aW1NL4AWNepDz77LOSpDPzzdVuXp9NL77ZGHh95ZVXKjXVLGweS2Zmpi666CI9tqvFMv7OimDX53PPPXfa910IrrrqqsB47RLrIuvrzSOSpJUrV0qSnBs+rBdHii3n/r/VR3TWmqWB16Ojowu+wYvH49FDDz0kScqPM8/bbB0PNjg52QrBkUShEAAAAAAAhEhI8BdRqgfNJhBF9h7FOhwh8yLlueeekySdkWqel3h4Ilv9g/5iV0xMjC6//PITNjGZKjk5WXFxcXqztlV1ExlG/IKMVtnkv5/X651N+vNm8nOTpDV51o08XqvtkCR96lOfkiTZYhz6wjanurxJxtw424R+fZlNyUnB3/fUrsoL0fbt29XR4f8Zcx3mGY2to/5CcHZ2tiorK6Oa20JGoRAAAAAAAITYt2+fJKm6x4zZbT5VFGeFzIsEj8ejl19+WanJCaqI7TDiO/uCqx03bdqkgoKCGd3fZrNp9+7dkqSnOzKNeE7MgN5ymn+F3f333z+je8+3wcFgYey0DLPIOexzqrqhU5LkcrkC11etP0v/Z6tZKJSkpY4uffLilYHXv/nNb8KVbkRMnisZ43Qpx2YWmluG/FvOP/ShD8luN7efL1YUCgEAAAAAQIiWFv923EMd5pZNSVpRlCZJeuONNyKWQ1VVlUZGRrTptCLL+MvNwQLY9ddfL6fTaTnveCYbnzy5f9gyvmmZf6XhwYMH5fGY5/wtVFMLXysT+434IXeWfPIZjV+uuOIK/en5g/pe3TLL+15aGjzr79VXXw1TtpHR3NwsScrNTrc8o7F50N/ghG3HoSgUAgAAAACAEJOr8w40mSuxJKki178Ftb+/P2Jn1W3dulWStKk02TL+4uFeSZLT6dRll102q2dcccUVkqS/vdZoGS/N8G+x9nq9gXwWOo/HE2hk4nQ6VHqcjsfZ2dkaGRkJXJ8stv5/D+zRfneO8b6SuKHAeKGfUbhnzx5JUnG29d9PU99EyDz4USgEAAAAAAAhLr/8cknSwQZzy68klacHzwL8/ve/H5EcduzYIUl6S665Gszts2vnAX9xr7CwUJmZ5tbh6fjMZz4jSersHdCAL96IL00JPvtk2X68detW+Xz+1XKnLc2Tw2ZuPd73j9rh9ddfr4GBAY2NjQViNptNEx6vdvWZjWwK7b2BcxslLehVlkND/qJmYYb1OZpNPSMh8+BHoRAAAAAAAIS45ZZbJElDw2Nq9ZidhMtTgltQH3300YjkcPDgQUnShuRuI7ZvLFdut39FmMPhmFETk6mcTqdyc3MlSfXjaUZ8iSu49bq6unpWz4i2++67LzBeuyTNcs7rzf6t1ps3b1ZZWZl6e3sDKwQnt+LW9ZufaZxtQkX5wS7KC3mV5eSq2MI06y3pjR2DIfPgR6EQAAAAAACEcDqdgVV6tWPmyrKy+GCzjN7e3rA/3+PxqKWlRQXZaSq0m/ff2ZMYGM92NeGkyfP86kdcRqzEGdx6PVm4XOj27t0bGK/JP1bH407Z7XZt3rxZp59+upYuXaqenh6Nj49rxYoVkqSarnHL95ZPKRT+9Kc/DWPm4XX22WdLkgpSrEtfDR29IfPgR6EQAAAAAAAY1q1bJ0mqHjK35Bbbu+Vw+AtsdXV1YX/29u3bNTExoXNOy7eM72gKFrGuvPLKOT1rsqHHkUGHEcuKGVRSgv/n7+npWdBbbSf19ARbVZ+WbuY75ItTTUOn8vLyZLfb5XA4tGHDBhUVFam7u1sXXnihJKm2w3pLbllusEi7bdu2MGcfPv/1X/8lSSpINLdej/ti1NHvX5Ha2dkZ1bwWOgqFAAAAAADAEBPjLxlU95gxh82r8sIsSdLg4KAGBwfNSXMwWXw8e0miZfzFA8Hizqc//ek5PWv9+vWSpNoes6AkScuK/D+nz+fT9u3b5/SsSPN4PIFuv5K0MnHAmHPInSmffHK5gisonU6nNm7cqPz8fC1ZskSSdLjJ4hcvqTQjuJV3tlu+I21kZCTQkTs/3lwZ2e5Jlu8f4+5uc2v7YkahEAAAAAAAGJKSkiRJhzrGLOPLi9IC4w996ENhffbvf/97SdLGbLOz7qAvTq/XtEqSysrKAp16Z+tXv/qVJKmmY9QyXp4f7Jrb1NQ0p2dFWlVVVaCRidPp0FLLjsf+5h4pKaFbyuPj4/WWt7xFubm5Ki0tVUNbr9w+u/H+pam+wHjyPMOF5vOf/3xgnBc3YsRbx4MNTiYL4vDj0wAAAAAAAIbzzjtPknSgqd8yvroguNrv5ZdfDuuzJ1fFbUgwuy6/OpIrr9e/+i89Pd2Iz1RSUpKKiopU3WquvpOksqzgyru2trY5Py+SqqqqAuM1ZcfoePyPxZhnnXWWEUtISNCZZ56p73znO/J6vWrypBlzliQEi7fV1dULcjv2oUOHAuM8u7natWU0NjDevHlzNFI6aVAoBAAAAAAAhptuukmS9GZduzw+c4vp2fnBlWWTq9jCxe12a/mSXKXHmOfk7ewMNuhIS0sLy/OuueYaHW60PquuND1YOjmZzrNbW2JdRN3b5O94/N3vftcynpycrLe//e0qLCxUw5i59bskLlhQ7e3tDSlOLhQVFRWSJEd8orJsZqG7Zci/UjIuLo5C4VEoFAIAAAAAAIPT6VRGRoaGhkf15nieET8rJbitNTs7O2zP9Xg82r9/vzatyLGM72gIboV+xzveEZZnNjY2anB4VJ3eJCO2NGkiZN5CNrWD7+q8Y3c8Puuss0LOKDxaWlqa/umf/kl1Q+Y9Cux9sk/Zrvvss8/OIePI+OY3vylJKsxJU4zNLGI3D/hXWt57772Brtfwo1AIAAAAAAAsTXYEfqnLLKAV2Hu1JD9TktTRYW4Rnq2tW7dqfHxcZxdbF7qef7M1MC4qKgrLMyfvU+9OMWIlruHA+ODBg2F5XqT89Kc/DYxPy5gw4oO+ONU2dSo/37qb9FRtbW060mcW2WJtHpX84/cuSbW1tbPMNnJeeeUVSVJRVrJlvKnP3+BkoZ6xOJ8oFAIAAAAAAEtut/88ur/Xm51jJen8Nf6CU29vb9ie+cADD0iSzsg0m1B0epNU2xTc/huuQk9Wlr+zcd2wucpuSWyw++9LL70U+EwWop07dwbGVh2PD475f87Dhw+f8F4dHR2q7bL+vZcXpIXMW2haWlokSYUZ1qsmm7pHQ+YhiEIhAAAAAACwlJnpXzm2/Q3rgsq5S/2r/sbGxsJWQOvv75c9Jkbr483GIbsGg1uc4+LiVFlZGZZn5ubmSpKODJhlkiTbmLIzgisNv/e974XlmeHm8XgCXZnjnLFaajfPU9w/4C+c2WzmmZNHc7lcqm4zz4iUpLKchJB5C01Ojn/bemFarGW8sWMgZB6CKBQCAAAAAABL73vf+yRJhxs61OY1t+VuygwWku68886wPHPv3r1av7xQLptZeNzZ4QiM16xZE7bz5SZXJtZ2W3fwXVaYERj/8pe/DMszw23r1q2BpjJryvNktzibb98/jpU899xzT3g/m82mmuZuy1hpRvD3sG/fvllkG1mTnZgLkq3LXvXtfSHzEEShEAAAAAAAWLr44osD4x39ZsOS1c5WJSb4VxVu3759zs9zu92qra3VpopMy/iLR4KFSafTOefnTaqsrJTdbld1+7BlvDwveEbjQt16fP/99wfGJ+p4vGrVqhPer6CgQE3tvRr1OYzY0pRgEbK6unrBfSaTnZgLEr1GbNQXq97hiZB5CKJQCAAAAAAALG3evFkOh79Q9HyLuV3VYfPq3NUlkqShIettqjPxP//zP5KkMwutVwq+sK85MA5nt1q73a4tW7aouqXXMl6WGSxKvv3tbw/bc8NpalORNXnWW25fq/FvR77hhhtOeL8VK1bIJ6lpIs2ILUkYC3l99913Tz/RKHjwwQclSXnxZgGzdSLY4GSy6QmCKBQCAAAAAABLdrtdZ599tiTpuYM9lnMqK/xbkkdGzOYjM/W///u/kqSNaYNGrH4iQx3d/YHXl1122ZyfN9Wjjz6qmqYueX1mQXRpavDaQj2jMCEheG7gaelmx+MBX7yONHeqpKRkWqsxJ4uJdWNmx+uSuNBGKYcOHZppuhHjdrtVV1cnScpzmn+TrePBMxWnfmbwo1AIAAAAAACOqaioSJK0Y1+D5TbUTXn+otSOHTvmfOZbc3OzXPFxWuW0aGQyELqd9tOf/vScnnU0p9MpuyNWLd5UI7Y0Kdj99/HHHw/rc8MlKSlY0Fth2fHYv537qquumtb9nE6n1q9fr7pBc3ViXkyfYh3Bv4XJsxEXgrvuuiswznOYn0PrSPDnOe+886KS08mEQiEAAAAAADimydVibveEXh3NM+JnJrbJJpvGx8fnfOZbb2+vzlxVKIfNPFvu5dbgqr6CgoKwnlEo+c9YHB0dVd2Y2bRlSXxwheNHP/rRBdcEw+Px6Nlnn5Ukxcc5tcTeZcx5c8C/em4mnX4vvvhiHekzi4B2m09LC4INXpKTk40582XyrMz4xCRl2MyVqc1DwVLYTTfdFLW8ThYUCgEAAAAAwDHZbMEC3UsdLiOeFjOs1cv8BcSnn3561s8ZGRlRb2+vNpWnWcZfqukLjG+99dZZP+dYWlpaJElHhswCZKG9Vzb5P4f+/v4F1wRj+/bt6u/3b8teU2bd8fiNTv+1vDyz2HssO3fuVG2XdaOS8oK0kHkLRWJioiSpKCfNMt484C/yrlq1KuzF5lMBhUIAAAAAAHBMZ511VmD8XK31OYTnrfKvUptLofC2226TJL3Foo7l8dn00r7GwOtwbzuWpPz8fEnSkX7zjMI424SK84Nbn//85z+H/flzMVnklKS1S9Is57zR5G82U1hYOO37Njc3q6bNXJUnSWXZwfP99u/fP+17Rtq6deskSUVZ1qscm/r8W+Wvu+66aKV0UqFQCAAAAAAAjuk73/lOYLzt9UbLOecU+8+r6+mxbngyHTt27JAknZHaZ8QOjudocNjfaTc3NzciK8EqKytls9lU0zVuGV82Zavtww8/HPbnz0VmZmZgvCbP+rN5raZDmZmZqqysnPZ9h4eHdbip2zJWmhE8o7C1tXXBbMfu6/P//RRmxFnGm7qGQ+YhFIVCAAAAAABwTC6XS3Fx/qJLW2e/aieyjDmb0nolza3zsdfrVXpKosodHUZsV19wdVhBQcGsn3E8drtdDodDNW1DlvGy3OAKuu5u6+LZfNm7d29gvMqi43G/z6W6lm5deumlstvt075vYWGh2rr6Newzi49LkoPnSHo8nsDZgAtFYap1wbSx02xwgiAKhQAAAAAA4LhKSkoC45d604z4stgOZWekqKvLbKIxXW63W5tWW2+Lfbk5WJRKSzOfHy5JSUk63Gy9KrIsI1h4io+Pj1gOs3HkyJHAeGWCxYrMMf9qyJQUs1HL8Vx++eWSpIaJNCO2JGE05PXU7c/zafLvoyDZ3EIuSQ3tfSHzEIpCIQAAAAAAOK4lS5YExs83mh2JJalyTaHGx8c1OGh9pt3xeDwe7du3T5tKrc+Ve/FQcAWf223dXCMcLrzwQjW29mjU5zBiS1N9IfMWksnPPCE+Tkvs5mrHN/v9qyHLy8tndN9bbrlFklQ/mmDESpyhK/Nm0k05kia3v+cnmFuhB7zxGhz1hMxDKAqFAAAAAADguD772c8Gxtvf7LSc89Yyf7fZD33oQzO+/9atW+Xz+fSWHLO4M+ZzaNeBpsDrpUuXzvj+0/Xxj39cPvnUZLGCbumUFXQf//jHI5bDTHk8Hv32t7+VJK0uy1WMRcfjff/oePzJT35yRvd2Op268sordWQw1ojl2fsU5wxej2QBdyYaGhokSfnxZj5tniRjHkJRKAQAAAAAAMd10UUXBcavHmxSv89lzNmU7S+kHTp0aMb3v//++yVJG5LM1XCvj+VqfCJYQLz22mtnfP/p2rJli5KSklQ3lmTESuL8K+iSk5O1ZcuWiOUwU1u3btXQkP9cxbVL0i3n7P1Hx+OXXnppxvePi4vTkV6z+ChJZUXB8yp/+ctfzvjekTC5TT7POWzEWsZcxjyEolAIAAAAAACOy263a/ny5ZIkn3x6ZSjXmLPB1SqHwx5ofDITR44cUVFuhvLtvUZsZ3dw22tMTIwuuOCCGd9/uux2u37xi1+ozmIFXX5Mn2JjHdqyZcuMGoJE2gMPPBAYr8k185akvTX+BjGzOUewrq5OtZ1jlrHy/OCZh7t27ZrxvSMhNtb/GeTazaYlraPBz2chFXsXEgqFAAAAAADghDZs2BAYv9hmFqRcNrfOXFWspqYmI3YiBw4c0Dmr8i1jOxqCW0hXr14d8SLdFVdcoaE487y9GJtP5YVZevTRR/X//X//X0RzmIne3t7A2LrjcbzqW/0rNfPzrT/j4ykpKVFNm3Wn4NKsYBG3rq5OHo+5dTyaPB6P7r33XiWnpCjFZnbgbv5HQ+uMjAxt3rw5usmdJCgUAgAAAACAExoeDm7lfO6wdeGockWGOjs7Q4pXJzIyMqLOzk6dvcTczixJLx7qCIwvvfTSad93ttxut17aZ31+XXlBqiTpO9/5zoI5k29qp2mrjscHRv3bg2NjY1VZWTnj+2/YsEGHm8wt4ZJUlhEsK42MjGj79u0zvn84bd++XY2NjSrKSbWMN/f7G/HccsstC2pV6EJCoRAAAAAAAJxQTEywhPDc6w3y+GzGnHMK/GfZffrTn572fT/zmc9IkjZmm9tb+30u7atuC7yORrfhu+66S4db+y1jZdn+YqbX69Vdd90V8VymY2zM/7kluOJUYtnxOF6SVFRUNKviWEFBgbp6BzXgizdiS5JDO2DPd4OQydWshVnmGZOS1NTjL+7OtPvzYkKhEAAAAAAAnFBBQUFgPDA4ojfHzXMKz0rxr26bycqyxx57TJJNG1wdRuzV4Wz5FGykEY3totu2bdPhxmOtoLOHzFsI0tP9DUzWlucdt+NxWVnZrO5fWFgoSWoYN1fplbhGQ17PpllKOLW2tkqSitKtz8ls6hkOmQcThUIAAAAAAHBCk81MJr3YlWzMKbD3akl+lkZGzPPhrIyNjam5uVkrl+YqNcbsUruzM1jwcTgcUdkuOjQ0pM5jrKBbOmUF3e7duyOey3S0t7dLktaWWG+33dvoP5hvtoXCyspKuVwu1Y0kGLESZ+jKy/Hx8Vk9I1w6OzslSYWp1k1dGtoHQubBRKEQAAAAAACc0A033BDy+vk66zP6zl+br9HR0ROe4ed2u/Xcc89JkjatMJuHSNJLdaOW1yMpJ8efS/14mhFb4goWQOvr6+f9nEK3263XX39dkrQ612k557UafyFxshvwTNntdq1Zs0b1Qw4jlh0zoARXsJg73yv1GhsbJUkFZg3bH2/vC5kHE4VCAAAAAABwQk6nUwkJwVVl295osZx37pI49fX1qbvbevuu5F95tnv3bv3Hf/yHJOnsYusi1wv7g89wOq3nhNvSpUslSfUjZnOVo1fQ3X333dFI6Zjuvvtu+Xz+rcWr0s3VfH1elxrbeyVJFRUVs35Obm6uanu8lrFlRVmBsddrPSdaSkpKJEn5CWYePd4EjU14Q+bBRKEQAAAAAABMS2lpaWBc3dipNk+KMWdT5qAk6ZlnnrG8x8TEhPbs2aMjR45oz549kqQzMsxtx22eFNW1BIuN69atm0vq07ZlyxZJ0pFBcwVdZsygkhKCW5IPHDgQlZyO5eDBg4HxSpdFx+OxzMD46BWhM9HS0qLaTrPZjCSV5QaX7+3bt2/WzwiHyd9dfpyZa+tEkjEPJgqFAAAAAABgWq699tqQ1zsGso05q52tSkyI1+HDh42Yx+PRa6+9ppqaGqWlpWlgYEAOh13r4tuMubuHMkNeP/nkk3PMfno2b96s2NjYY66gq5iygm6+t7A2NzdLkhIT4rXEceyOx2VlZXNakVlYWKjq1gHLWGl2cOVlTU2NPB7PrJ8zV5WVlZKkvFiz8Nw6Fm/Mg4lCIQAAAAAAmJbPfOYzIa+fbzbnOGxenbumWA0NDSHNLbxer15//XUdOnRIqampcjgcGh8f1+kVhYq3mdtmX2kPbVySmmrdrCPc7Ha7li5dquoO6/MRy/ODK+jmuynGZFFubXm+ZXxfh39b8mmnnTan55x//vk63NRlGStND/09PfXUU3N61lx8/etfl2RTrr3fiLWMBM9o/Nvf/hbFrE4uFAoBAAAAAMC0OJ1OnXXWWYHXzx3ssZxXuSxFjz/+uPr6/NthfT6f3njjDR04cEApKSmKj4/Xrl27JEmbKjIt7/FS7VBgPNdC10zFxsaqutUsNklS2ZQVdP391nOiZXTUX8xcW2JuAZekvY2DIfNm66abblLfwLB6vWbn46XJoSsIv/3tb8/pWbPl8Xj09a9/XenpyXLZzCYzzcE/Jz3wwANRzOzkQqEQAAAAAABM24oVKwLjHfsaNeozz/LblDehtrY2tbS0yOfzaf/+/dq/f7+SkpLkcvkLbZNbic8stC5NvLivKTD+yEc+Es4f4YTGx8d1uNF6tWBpWkzIvPmUne3f+r0m17qj8au17SHzZsvpdCo+Pl4N4+aqzpIpnaAl6bXXXpvTs2brz3/+s3w+n4pzrFeeNvcHt5IPDFhvowaFQgAAAAAAMAPFxcWBsXt8Qq+O5hlzzkxsk002ffWrX9XBgwf1xhtvKCEhIaRr8s6dOyVJG9PMok3tRKY6ewcDr4/e8hxpycnJGhoeU4c32YgtSZ4IjOfzPD7JfyagJK1KMwuWvd4ENbf7V3RObUIzWzabTXVWnaBjQ5uoDA0NGXOi4Y477pAkFWUlWcabe4KrKjmj8NgoFAIAAAAAgGk7umPsSx1m8SgtZlhrluXrtdde0+uvv664uDglJiYG4h6PR319fUpwxWlFbLvx/t39aYFxYmLinBpxzMbZZ58tSap3m1t6l8QHG2W0trbOW7HQ7XbrpZdekiStSDA7Hu8fywiMw9Hld3R0VEcG7cb19JghpSS5QubNh64u/xmKRelxlvHG7uDKx5tuuikqOZ2MKBQCAAAAAIBp27x5s2JiguWE52rNDrOSVHlajtxut2JjY5WcHLoyb8eOHZKkz79vnRw2s7vwy63BcUFBQRiynpnvfOc7kqS64XgjVhIbPJdxeHhY27dvj1peU915552SpKREl0rsZsfj/f/oeOxyubR58+Y5P89ms6nuGJ2glxVlhsybDyMj/kJgQYq5FV6S6v+xutLlckW98HwyoVAIAAAAAACmzW63hzQX2ba3yXLeOUV2NTU1KSXFXJV377336uJNK/Qvyw5avvfF6t7AeOXKlXNLeBZcLpc2btyoIwPmCrok25iyM4I/U0tLSzRTC3juueckSWvLza3fUrDj8dq1a2W3mz/HTDmdTtV0jFjGynJTQubNB6/XX8QsSDILlV6fTS2d/i3uU1e2wkShEAAAAAAAzEh5eXlg3NbVr9qJLGPOprReeTwedXebq93cw3365TsGZLf5jFjtRKa27T4SeH3++eeHJ+kZ+s///E/Vdk9YxqauoMvJyYlWSiGSkvxn8a0ttm7esbfRXxhbvnx5WJ63ZMkS1bRZNwEpzQquvMzIyLCcE2mTn0d+gvk76/QlacLjDZkHaxQKAQAAAADAjBzdDOKlXrNYtSy2Q9kZKbrttttCrg8PD+n31+YoK2bQeI/HZ9Mn/2KT1xcsIN58881hynpmPB6Pqtutt1Uvyw09b3E+XHPNNZKkNbnWW21frWkPmTdXFRUVOtzYZRkrTQ+Wl7q6uublM5k8hzEvbsyItY0nGvNgjUIhAAAAAACYkaOLd883misDJalybZGOHDkScm1o+106M77Rcv5X95fq6VdqAq9jYmLmbSvr3/72N1W39FrGyjLjQubNhwsuuEBJSUmWHY97vIlq6ehXUlKSLrjggrA8Ly0tTYPDo+rymivyliQFV/GNjY3Ny7mNkys782LNrsstY/HGPFijUAgAAAAAAGbE6XSGNK3Y/maH5by3liZICjaa6N5fpX+Ke95y7uO9pfr6b/aEXFu7dm0Ysp2duro61TR1yeMzz7xbmhY6bz7Y7Xb94he/0MqEXiO2f9S//fe+++4Ly/mEUnBlomUnaFfoysv5OrfRZotRTky/cb1lxHrVJUwUCgEAAAAAwIxlZ2cHxq8ebFa/z+wQvCl7VJL0gx/8QP3tdbq45W7Le9VOZOrDPzMbm3z9618PU7azMzHhUYs3zbi+NNEd/WQsPPzgAyqy9xjX9w/E6xvf+IauvPLKsD3rggsuUFxcnOpHzN9zUWxfyOv09PSwPXe6+vr6lJ2ZLKfN3PbcMhg6D8dGoRAAAAAAAMzY2WefHRj75NMrQ7nGnA2uVjkcDu148Xmt3fdNJdrM8+NGfE69/7dj6hswO+q+853vDG/SM1BSUiJJqh+z2GobH9zeOjxsfY5hpF1++eVqOvyaZeyNdo+eeuqpsD7PbrfrvPPO05EBc3Veqm1EGSnBcwAfeeSRsD57Omw2m0py0ixjzf2ekHk4NgqFAAAAAABgxh588MGQ1y+2xhpzXDa3zjqtSD/551KVqtnyPp/ekaddB81YaWlp2LbNzkZWlr+T85GhOCNWaO9RTIy/pPLss89GvXnHyMiIHn30Ua0rNrcBS9LrjYP661//GtjyHS7d3d2q7bHuBF0+pRP0K6+8EtbnTkdFRYWKMhMsY409oyHzcGwUCgEAAAAAwIwlJSUFimWS9NzhAct5P7w0XpenHbaM/axlmX765OuWsTvvvHPuSc5Bbq5/heSRfnMFmtPmUXGuf3ttX19f1Jt3fPazn5UkrT5Wx+Pq9pB54eL1elXTYV18LM9LDpkXbTfccIOKMsxt0ZLU2Olf9Wm323XDDTdEM62TDoVCAAAAAAAwK5s3bw6Mn3u9wbLxxzqn9UrCPaP5+tTPrbfOStIll1wy5/zmorCwUJJU02l9HuGywrTAONrNO15++WV/Dinm6r4eb6Jau/pD5oVLSkqKalqtz/hbmhUs0o2NmVvMI+2xxx5TUar1CtT6tl5J/sLpfHXRPllQKAQAAAAAALPyuc99LjAeGBrVPrd5TqGVHm+irnigQ+5x622sy5cvn9dtx5JUWVmprKws1bQPWcbLcoJn8uXk5EQrLUmSz+eTJJW6Bo1YtTvNmBcuXV1dqmnqtoyVpgbH+/bti+p2bI/Ho1tuuUWFiebPO+ZzqL17QElJSfrGN74RtZxOVhQKAQAAAADArFx00UUhr1/qTj7GzCCvz6aPbE1SbbN1wUmSPvaxj805t7my2+268cYbdbjZ7CosSWWZ5pmM0bJs2TLZbDFa4jBzqx2KD5kXTqmpqRoZdavNa56NuCQptOj79NNPh/XZx7N9+3Y1NjaqIGHciLV5UuSTNDg4GPUt4icjCoUAAAAAAGBW7Ha7Vq5cGXj9fN2Jt5x+s7pMf3r+0HHn3HLLLXPOLRzKy8vV2NqrUZ95FuDSlODqteZm6+3VkdLS0qLivAzF28zCWHVvcPt3bGx4i5mXX365JKnBbRaEl7hCuz9/97vfDeuzj2dy63d+nHl+YrM7wZiHY6NQCAAAAAAAZu36668PjLe90XrcuVsHlugrv9pz3Dm5ubkL5hy5559/Xj751DiRbsSWJI6FzIsWj8ejPXv2aEWxmZMkHeoMFg+XLFkS1md/+tOfliTVDZtNQ4odvSGve3qsV2JGQn5+viSpwGE21GkZdRrzcGwUCgEAAAAAwKxNXf1X3dipNo+5LVWSGifS9cF7a+TT8c/NO3DgQFjzm4vJFWh1Y4lGbIkzWJR65JFHopWStm/froGBAVXkmTlJ0qGWYF5btmwJ67OdTqfWrVunun6znJRoG1N2RvB3v3HjxrA++3gqKyu1rLxMqbZhI9Y45D/rsri4WJWVlVHL6WRFoRAAAAAAAMya0+nUBz7wgcDr53qzjTljPof+6RGvuvqsG4NMcrlcSk1NPe6caEpO9m+xrRs0t/DmxfTJ6fRvSW5tbdXIiLntNRKampokScsyzO3QknSgvkuSlJSUFNKVOly++c1vqrbHulHJsqLMwPiyyy4L+7OPxW63q3LT6Zax5n6vJOmqq66a9wY5JwMKhQAAAAAAYE4efPBB2Wz+s/G+9mSLPL7gOXlen023vlKgF99oOOF92tvbI5bjbFxzzTWSpNpecxVkjM2nsoKswOvbbrstKjm1tvq3d5enmsW6AV+82nv8KwqvvPLKiBTGOjs7VdNurtyTQjtBd3Z2hv3Zx/K73/1OTYdft4w19rglST/72c+i2on5ZEWhEAAAAAAAzIndbtcDDzwgSXrtcKvOejhBv+4o08PtZbr48Qz98AnrIs5UqampSkpKinSqM3LBBRfIZrOpptNtGS8vSAuMd+zYEZWcurv93aJLXWax7og7eG5hYWFhRJ7/wgsvqLqlzzJWlhkXMi8aPB6PrrnmGhVluCzj9V3+z6mrq0tVVVVRyelkRqEQAAAAAADM2Yc//GFlZflX2O062KKr7t6jq3+4R8/srJ3W+xdiR1q73a4lS5aourXfMl6WHSxO+XzHP3sx3JY6zWYhtcPWxbJwam5uVm1zl7xTVo0GckoLXnvllVcinoskbd26VaOjoypOs96K3dAeLGpSKDwxCoUAAAAAACAsJrfFztSll14qlyvyRa7ZKC0t1eGmbstYeUZwa2+0zlZMSUlRTmaqkm2jRqy6zx4yLxKSk5PlHp9Qq9f8eZckBVdevvrqq1HZ6ju5krUw2Sxcen02Nbb1RjyHUwmFQgAAAAAAEBZ2u10/+tGPZvSe1NRUPfbYYxHKaO5GRkbU1Tuofp9ZyFya7AmZFw1PPPGEVpZkWsYOd08Exnv37o3I8yfPbax3m9vES+KCzWrcbndUVvANDPjPZCxMmDBinb4kjXu8gdeRaO5yqqFQCAAAAAAAwuYDH/iAPv/5z09r7hlnnKHe3t7IJjRHbrd/lVzDuMUKuoQRY14keTwevfDCC1qWl2wZP9QyGBgPDR2/w/RsXXDBBYqNjVX9cLwRK3b0hrx+9tlnI5LDVPn5+f7/N37MiLWMB4uZcXFxFAqngUIhAAAAAAAIm+TkZJ1//vl65JFHtGzZsmPOqa+v186dO6Oc3cwVFBRIkupGEoxYSWzw/LvGxsaI51JVVaXx8XFVZMVaxg80Bs8tfNvb3haRHOx2u8455xwd6Te3+sbbxlWQnRZ43dBw4k7Xc3XWWWdJkgocg0aseTRYzPzoRz8akS7Qpxrrkx4BAAAAAABmweFwKC0tTa2trbrnnns0MjKin/zkJ2psbFR+fr4+8IEP6C1veYuKi4vnO9VpKSoqkiQdGXBIRy0qzIgZUnKSSwODI2pvb9fIyEhEz1qcXKFXluo1YqM+hxpag4XCm2++OWJ5vPWtb1Xt3iekUjNWXpih5o5eScHPLpJeeOEFORwOZceYDWeahoNlr/Hx8YjncipgRSEAAAAAAAirjIyMQCMLl8ulW265Rd/61rf0z//8zyouLj7mSsOF6Nxzz5Uk1fZYN+aoKAqeFzjdLdezVVdXJ0kqSzQbmdRNZMgnf+flVatWyel0RiyP9PR01bQPW8bKchJD5kXa3//+dxXmpCnGZnadbh7whczDiVEoBAAAAAAAYTXZcdfnCxZqhoaGFBcXp9WrV8vhOHk2OE6ufKzpsG5WUp4X7C785ptvRjSXyeJrqbPXiNWOBAt069evj2ge3d3dqm7usYyVZTpD5kVaf3+/SnKsOzw39I6HzMOJUSgEAAAAAABhlZycLKfTGWjw4fF4NDQ0pIqKCmVlZc1zdjNTWVmpmJgYVbdaF5rKsuIC45qamojmcvDgQaWmJCozxjyPr6bfETIvkurq6nSkuVsTPrOstCQtdF6kVVRUqCgr0TLW2D0SMg8nRqEQAAAAAACEVVJSkuLj4zU25u9E293drezs7JNqy/Eku92uzMxMHW7ssoyXpgcbZExdQRkJAwMDWlGcaRk73O0JmRdJbW1t8ni9avFadIJOdIfMizSPx6PiNOvmLg0dwYLqxRdfHPFcTgUUCgEAAAAAQFjFxMQoIyNDY2NjGhoaksPh0Jo1ayJ6bl4kpaWlaWhkTB3eZCO2JCm4vTXSP19iYqIq8s3inCQdahsOmRdJw8P+Z9WPWXwecUOB8f79+yOah9vt1rZt21SYYt3NuH5Kc5doNFY5FVAoBAAAAAAAYZeeni6Px6PBwUGVl5crOzt7vlOatdNPP12SVO82z8JbEj9szIuUiYkJVWRbFyMPNQaLYhkZGRHNY3JLed2QmUuhvUc2m7/c1NzcHJgbCf/zP//jf2ai2Wim3xevgeGxYF6FhRHL41RCoRAAAAAAAIRdcnJyYNvuihUrZLPZ5julWYuJ8ZdP6objjVhJbG9g3NzcHLEcPB6PDh06pPI0Mzbhi1F1U3BrdHKyudIvnCZX5x3pN3+nTptHxXlpgdff//73I5bHo48+KkkqiDeLkS0TwaJubGysKisrI5bHqSRihcIjR47oox/9qEpLS+VyuVReXq477rgjopVkAAAAAACwMKSmpiojI0OrV69WXFzcid+wgLW3t0uSavvNMkqibUw5mf6i1I4dOwKdicNt+/btGhsbU1nSmBFr8KRrwuMNvI50Uey8886TJNV2jVvGywuCKxoni3mRMHkmZL5zyIi1jLkC47KyMtnt1tuTESpihcL9+/fL6/Xqxz/+sd544w1973vf049+9CN96UtfitQjAQAAAADAAuFyuVRZWan8/Pz5TmXOJhc91XZbFwGXFfoLY+Pj46qqqopIDg0NDZKkpXFm9+Ujo0mBsc1m08033xyRHCZN3r+2wyzQSVJZTkJg3NfXF7E81qxZI8mmPLv5mTQNBxucbN68OWI5nGoiVii85JJL9POf/1wXXXSRysrK9N73vlef+9zn9Ic//CFSjwQAAAAAAAvIydq85GhLly6VJFV3DFvGy/OCW32ffvrpiOTw0ksvyRUfpwJ7rxGrHgh+zuvXr4/45+50OrVixQodbjJzkaTSjGCR7rTTTotYHm9961uVnZmseJu5srF5yBYyD9MT1TMK+/r6jnug5tjYmPr7+0P+AQAAAAAAzKdrr71WklTd1GMZL8sMFuaeeeaZiOQwPj6uimLrhjDVPcFtx2eddVZEnn+0iooKNbT1yO0zt/QundKYebJDciTk5uaqJCfNMtbQ5wmZh+mJWqHw8OHDuvPOO/XJT37ymHO+8Y1vKDU1NfCvuLg4WukBAAAAAABYuuCCCyRJtS3d8vjMBh6lUwpjXq/XiIdDe3u7lhemWsYOt4+GzIuGlpYWeb1eNXnSjNiShLGQeZGye/dulWQnWcYau0dD5mF6ZlwovP3222Wz2Y77b//+/SHvaWpq0iWXXKJ/+qd/0sc//vFj3vuLX/yi+vr6Av8m998DAAAAAADMF7vdruXLl2tiwqNmb5oRX5oUbNwaH292Rg6H/Px8LcuxvvfB5t6QedGQlpYmSWoYSzRiJXGDgXEkm9r+8Y9/VFG6daOchinnJ/7xj3+MWA6nGsdM33DbbbfpuuuuO+6csrKywLi5uVlvf/vbde655+onP/nJcd8XFxd30ndCAgAAAAAAp56KigodPHhQ9WPJKk4I3YI8tTB2vCPX5mL58uVK3v+yZexgfWfIvGh4xzveoa1bt+rIUJzOO6pWWGDvlT0mRh6vV/v375fH44lI1+Hm5ma9d1mWZay+rTdkHqZnxoXC7OxsZWdb74k/WlNTk97+9rdr48aN+vnPf66YmKgeiQgAAAAAABAWY2P+7bRHhuL01oTQWKG9VzExMfJ6vRHbHZmfn6+cRnN1XosnVaNj/h4PdrtdN9xwQ0Sef7SioiJJUl2fT8oJjTlsXi0pyFBNY6fGx8f17LPP6h3veEfYc4iPj1dhks+4PuZzqL2nO2QepidilbumpiZt3rxZJSUl+va3v62Ojg61traqtbU1Uo8EAAAAAACIiMlFU0f6zJjT5lFJnn8l4cGDB+XxeMxJc+DxeHTjjTdqafyAEasdSwmMb7311qh1mi4sLJQk1XSZHYclqbwgPTD++c9/HpEcXC6XClzm81s9KcY8TM+MVxRO19NPP63Dhw/r8OHDgSrzJJ/PrPYCAAAAAAAsVKWlpZKkmi63tMyMLytM05HmTo2Ojmr79u3avHlz2J5dVVWlvr4+FdvNAmT1YHC13CWXXBK2Z55IZWWl7Ha7atqGLOOl2cFll3v37o1IDna7XQVTtn1PanGHLvmkWe70RWxF4XXXXSefz2f5DwAAAAAA4GSyZcsWSVJNu3VhrCwneFBfuDv9VlVVqawoSw6b2VG5ptcXMi9a7Ha7li1bpurmbst4WUZwbVpycnLYn+/xeHTw4EHlO8xVls2jof0vzjvvvLA//1TFoYEAAAAAAAAnsHnzZiUnJ+twU49lfGphLCvLusHGbE1MTGh5Yapl7FCHO2ReNJ133nlqbu/TqM/csLpkyu7fNWvWhP3Z27dvl8czrlTbsBFrGgqWu2w2m26++eawP/9URaEQAAAAAADgBOx2u97znveoqa3XsjC2NCW4sm/37t1hffbOnTtVkZNoGTvYHDw0sbe3N6zPPZG0tDT55FPTRJoRW5I4GjIv3FpaWlSSa33fpv7gystLL700auc2ngooFAIAAAAAAExDXV2dfPKpcSLdiJUlBQtjf/zjH8P2TI/Ho6qqKi3LsC7hHGzoDIybm5vD9tzp2LVrlySpbizJiJU4B4x54ZSTk6OSbOstzY09wVWWn/nMZ8L+7FMZhUIAAAAAAIBp6Ovzr947PGIWxlbGdcomW8i8cKiqqtL4+LjKUsxtxV3eJPUNjARej4yMGHMiaXTUXxytG4w1YvkxfYqNdYTMC7eiTOtuxvVd5nZkTA+FQgAAAAAAgGmYPHvw9W5z63GybVTlxf54OBu5Pvvss5KkUpfZ3bfWHXpu4caNG8P23OmY7CZ8pM/8eWNsPpUX+j+P2trasD+7vb1dRalmgVKSGtr7QuZh+igUAgAAAAAATEN/f78k6bXmMcv46WXZkqSDBw/K4/GE5Zl1dXWyyaYlDrO7cM1Q6Iq6Cy+8MCzPnK4zzjhDknSo3frzWFGUJsm/JTrcqx3z8/NVZLHz2OuzqbGtN2Qepo9CIQAAAAAAwDTYbP6txbtruizj64sSJEnj4+Pavn17WJ7p9XpVnJ+heJu59bimzxYYx8bGavPmzWF55nQVFBRIkg4291vGl+cmBMaf//znw/rsjo4OFSSYxdgOb7ImPP5mJpmZmaqsrAzrc091FAoBAAAAAACm4cwzz5QkvVnbZtn5eG1msHDV0tISlmfabDatKM6wjB3qCDbt2LRpk+x2e1ieOV2FhYWSpAP11tt7y6c0YDl06FDYnuvxeHT99derIN5cpdg6Yd0dGtNDoRAAAAAAAGAavvvd70qSPF6vDrqzjfjqpODKuszMzLA8s6SkRBW51sWvQ63Bcwvf+ta3huV5M1FZWanExEQNDo+p1ZNixJelBAuZFRUVYXvu1q1bNTg4qPzYISPWPBofGHd1dYVtZediQaEQAAAAAABgGlwul1avXi1Jer3fLN6VOjrlio+TJO3duzcsz2xqatKyTHP1oiQdqA9ugU5PTw/L82bCbrfrnnvukWQ2VpGksvhgIfO//uu/wvbcBx54QA6HQ9k2c8tz03DoZxWulZ2LBYVCAAAAAACAaTrvvPMkSXs7zE6/dptP65blSZKqq6vn/CyPx6OHHnpIZSnmWXwDvni1dwcLZbt27Zrz82bj6quv1plnnqmawTgjVmTvkcNh12WXXSaXy2Xx7tnp7+9XYU6aYmzm76BpIPQazUxmhkIhAAAAAADANDU2NkqSXm0wt71K0ulL00PmzcWzzz6riYkJlSUMG7Ej7tAVhG+88cacnzdbO3bsUF9sjnE91ubR+9/zDj3yyCNhfZ7P59OSXHOrsyQ19o4HxnFxcTQzmSEKhQAAAAAAANPU2dkpSdp1uNUyvj7P31Dk5ZdfnvOz7r33XknSEmevEasdCV2hl5pqbv2NprMv+oDl9WuvfGfYn+Xz+VSUmWAZa+gONjhZu3Zt1Bu8nOwoFAIAAAAAAEzTwMCAJKmts1/t3mQjvjrN38CjtbVVbrfbiM9EVVWVcjJTlGIzu/tW94UWwC677LI5PWuu0oqWW17f/vhD+sMf/hDWZ42Ojqo43dzqLEkN7cFzEdPS0sL63MWAQiEAAAAAAMA0rVu3LjB+czjDiK92BRuM3H333XN+3sqSLMvrh7smQl7fcsstc37WXOzcd8Ty+pKkCV155ZVhLRa+5S1vUWGyzTJW39oTMg8zQ6EQAAAAAABgmq677rrAeG+v04hnxgyqIDtN0twbmpSWlmpZXpJl7FBr8IzE/Px8OZ1mLtHi8Xh0w023WK6wLEv2nxn4iU98Qh6P2ZRlNi688EIVJHqN631elwZHxkLmYWYoFAIAAAAAAEzTli1bAkW511rGLedsqPB3Pi4pKZnTsz72sY+pIivWMnagoTsw/vd///c5PWeuqqqq1NXVpdox85zEMpd/K3BXV5eqqqrC8rxzzz1XBa4x43qrJ9mYh5mhUAgAAAAAADBNdrtdH/zgByVJe470Ws45vdi60cZMPffccypL9RnXR30ONUzZYjt5buJ8efbZZyVJ1YPxRqzE3i17TEzIvLm69NJLlR9rdoJuHgtt8PLjH/84LM9bTCgUAgAAAAAAzEBiYqIk6bXDLZrwmaWVNVn+8/Nqampm/QyPx6Pf/e53Kks0G5nUTWTIp2ABMTs7e9bPCYfa2lpJUnWveW5grM2jsqKskHlz4Xa79de/VinP3m/EmodDV1/Odev3YkShEAAAAAAAYAZ27twpSRpzj6tmwmw2sibFv9326aefnvUzqqqqNDg4qKXOPiNWO5IY8rqwsHDWzwmHtrY2SdKhDnM7sCQtL8oImTcXd999t7IzUxRvM7d9Nw2GFirLy8vn/LzFhkIhAAAAAADADBw4cCAwfmPAbOBREdshh8Ou6urqWTfw2Lp1q1KSEpQVM2jEavodgXFSUpIqKytn9YxwGRnxr3o80Gyu8pOk5bmukHlzcejQIS3JTbOMNfYHP2ubzaYbbrhhzs9bbCgUAgAAAAAAzMDU4t/eTrO0Emeb0OqyfEmadQOPHTt2aEWJuVpRkg53B5+/dOlS2e32WT0jXCabuxyo77CMV2T6P6O+PnN15Ex5vV4VZyVaxhq6RwPj9evXz2sn6JMVhUIAAAAAAIAZWLt2bWD8apPZVEOS1i9NlzT7Bh7Nzc1aXpBiGTvUFlyZN9sVi+HU1NQkSeobGFGnN8mIlyVPSJL27ds353xTUlJUlB5nGWvsCK6+vOiii+b0nMWKQiEAAAAAAMAMPPnkk4Hx7sPWq+jWF/iLWXV1dbN6RldXlyqyrQtiB5t6QubNt6nFv5qxNCNe7goW8P7yl7/M6VlNTU0qSrVeQVnX1hcyDzNHoRAAAAAAAGAGUlNTlZTkXzlX29ypfl+8MWdNhtlsYyY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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "x_pred = np.linspace(0,1,100) ##for big GPs, this is usually not a good idea, but in 1d, we can still do it\n", " ##It's better to do predicitons only for a handful of points.\n", diff --git a/fvgp/sparse_matrixOBS.py b/fvgp/sparse_matrixOBS.py deleted file mode 100755 index 1d7363a..0000000 --- a/fvgp/sparse_matrixOBS.py +++ /dev/null @@ -1,125 +0,0 @@ - -import scipy.sparse as sparse -import time -import numpy as np -class gp2ScaleSparseMatrix: # pragma: no cover - - def __init__(self,n): - self.n = n - self.V = sparse.coo_matrix((n,n)) - self.K = sparse.coo_matrix((n,n)) - self.st = time.time() - - def get_result(self): - return self. K - - - def reset_prior(self): - self.V = sparse.coo_matrix((self.n,self.n)) - self.K = sparse.coo_matrix((self.n,self.n)) - return 0 - - def insert_many(self, list_of_3_tuples): - l = list_of_3_tuples - bg = self.K - row_list = [bg.row] - col_list = [bg.col] - data = [bg.data] - - for entry in l: - row_list.append(entry[0].row + entry[1]) - col_list.append(entry[0].col + entry[2]) - data.append(entry[0].data) - if entry[1] != entry[2]: - row_list.append(entry[0].col + entry[2]) - col_list.append(entry[0].row + entry[1]) - data.append(entry[0].data) - - rows = np.concatenate(row_list).astype(int) - columns = np.concatenate(col_list).astype(int) - - res = sparse.coo_matrix((np.concatenate(data),(rows,columns)), shape = bg.shape) - self.K = res - return 0 - - def get_future_results(self, futures, info = False): - res = [] - for future in futures: - SparseCov_sub, ranges, ketime, worker = future.result() - #if info: print("Collected Future ", future.key, " has finished its work in", ketime," seconds. time stamp: ",time.time() - self.st, flush = True) - res.append((SparseCov_sub,ranges[0],ranges[1])) - - self.insert_many(res) - #if info: print(" Size of the current covariance matrix: ", self.K.count_nonzero(), flush = True) - del futures - return 0 - - """ - def compute_LU_KV(self): - A = self.KV.tocsc() - A_new = A.__class__(A.shape) - A_new.data = A.data - A_new.indptr = np.array(A.indptr, copy=False, dtype=np.intc) - A_new.indices = np.array(A.indices, copy=False, dtype=np.intc) - self.LU = splu(A_new, diag_pivot_thresh = 0.01, options = dict(SymmetricMode = True), permc_spec = "MMD_AT_PLUS_A") - return True - - - def solveKV(self,x): - success = True - try: r = self.LU.solve(x) - except: success = False - if success is False: - try: - r,info = sparse.linalg.cg(self.KV,x) - if info == 0: success = True - except: pass - if success is False: - try: - r, info = sparse.linalg.cgs(self.KV,x) - if info == 0: success = True - except: pass - if success is False: - try: - r,info = sparse.linalg.minres(self.KV,x) - success = True - except: raise Exception("No solve method was successful. EXIT") - return r - - def logdetKV(self): - success = True - try: - upper_diag = abs(self.LU.U.diagonal()) - r = np.sum(np.log(upper_diag)) - except: success = False - if success is False: - try: r = self.random_logdet(self.KV) - except: raise Exception("No logdet() method was successful, EXIT") - return r - - def random_logdet(self, A,eps = 0.50, delta = 0.01,m = 10): - #from: https://www.boutsidis.org/Boutsidis_LAA2017.pdf - A = sparse.csc_matrix(A) - N = A.shape[0] - alpha = 7.0 * sparse.linalg.eigsh(A,k=1,tol=0.0001, return_eigenvectors=False)[0] - A.data = A.data / alpha - diag = sparse.eye(N, format="csc") - C = sparse.csc_matrix(diag - A) - p = math.ceil(20.0 * np.log(2./delta)/eps**2) - gamma = np.zeros((p,m)) - for i in range(p): - g = np.random.normal(0, 1., size = N) - v = C @ g - gamma[i,0] = g.T @ v - for k in range(1,m): - v = C @ v - gamma[i,k] = g.T @ v - s = np.sum(gamma, axis = 0) / float(p) - s = s / np.arange(1,len(s)+1) - return N * np.log(alpha) - np.sum(s) - """ - def traceKXX(self,X): # pragma: no cover - res = np.empty(X.shape) - for i in range(X.shape[1]): res[:,i] = self.solve(X[:,i]) - tr = np.sum(X * res) - return tr