diff --git a/simulation.ipynb b/simulation.ipynb index 174883f..7622911 100644 --- a/simulation.ipynb +++ b/simulation.ipynb @@ -2,21 +2,21 @@ "cells": [ { "cell_type": "code", - "execution_count": 12, + "execution_count": 1, "id": "b780b7af-aee0-4d92-b830-64e9b9d3c2f7", "metadata": {}, "outputs": [], "source": [ "%matplotlib ipympl\n", "import numpy as np\n", - "from numba import jit, vectorize, float64, types\n", + "from numba import jit, vectorize, float64, types, int64\n", "import matplotlib.pyplot as plt\n", "from tqdm.notebook import trange, tqdm" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 2, "id": "6fbf192f-aebc-4bce-ae38-339b5610fad1", "metadata": {}, "outputs": [], @@ -24,15 +24,24 @@ "# Coupling formula\n", "alpha = 1\n", "\n", - "a = 0.3\n", - "b = 0.3\n", - "c = 0.5\n", + "# Lattive parameters:\n", + "lattice_x = np.array([1, 0, 0])\n", + "lattice_y = np.array([0, 1, 0])\n", + "lattice_z = np.array([0, 0, 1])\n", "\n", - "@vectorize([float64(float64, float64, float64)])\n", - "def compute_coupling(x, y, z):\n", - " if (x, y, z) == (0,0,0):\n", - " return np.nan\n", - " return alpha/(a*x**2 + b*y**2 + c*z**2)**2*np.abs(3*c*z**2/(a*x**2 + b*y**2 + c*z**2) - 1)\n" + "lattice_s = np.array([\n", + " [0,0,0],\n", + " [0.2,0,0]\n", + "])\n", + "\n", + "site_nb = lattice_s.shape[0]\n", + "\n", + "\n", + "@vectorize([float64(int64, int64, int64, int64, int64)])\n", + "def compute_coupling(x, y, z, a, b):\n", + " vec = x*lattice_x + y*lattice_y + z*lattice_z + lattice_s[a] - lattice_s[b]\n", + " norm = np.linalg.norm(vec)\n", + " return alpha/norm**3*np.abs(3*vec[2]**2/norm**2 - 1)\n" ] }, { @@ -45,14 +54,16 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 3, "id": "062e190f-1561-4f9f-8ffc-aca8e43db8f4", "metadata": {}, "outputs": [], "source": [ - "def generate_lattice_sites(n, max_cell = 5):\n", + "def generate_lattice_sites(n, cell_number = 5):\n", " # TODO: Improve using random picking\n", - " return np.unique(np.random.randint(max_cell, size=(n, 3)), axis = 0)\n", + " r = np.unique(np.random.randint([[cell_number, cell_number, cell_number, len(lattice_s)]], size=(n, 4)), axis = 0)\n", + " np.random.shuffle(r)\n", + " return r\n", "\n", "def add_noise(couplings, sigma):\n", " return np.max(0, couplings + np.random.normal(scale = sigma, size = couplings.shape))\n", @@ -66,23 +77,23 @@ " x = sites[i][0] - sites[j][0]\n", " y = sites[i][1] - sites[j][1]\n", " z = sites[i][2] - sites[j][2]\n", - " couplings[i, j] = compute_coupling(x, y, z)\n", + " couplings[i, j] = compute_coupling(x, y, z, sites[i][3], sites[j][3])\n", " return couplings" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 4, "id": "3d1d36c3-1fc4-42e4-af71-8eda4fb34d86", "metadata": {}, "outputs": [], "source": [ - "test_sites = generate_lattice_sites(25, max_cell=2)" + "test_sites = generate_lattice_sites(25, cell_number=5)" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 5, "id": "ae4ecda6-14db-4e50-bfd2-affcd6153630", "metadata": {}, "outputs": [], @@ -92,25 +103,25 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 6, "id": "35313d97-d4d6-4435-b648-bb4e30c306fe", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a14d72a2641a4ac1a32a61e997deb644", + "model_id": "4ff187e4309849bab70fe6a501f6ba52", "version_major": 2, "version_minor": 0 }, - "image/png": 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g5DgOk5OTcLvdaGxs3CEI2ZQxQRB7AwlAgrgKYS1fNuUbq/jjOA5jY2NYWFhAZmYm2traJFtTKgSgXNiLtYSKrVtYWMDCwgKWlpYwOjq6I7YuFrseKWD7A9k6VSqVsP80VIVQPGVMEMTuQAKQIK4ywnn7RcPpdMJgMAAAmpqasLS0JOm6rlYbGLmgUqmQm5uL9PR0dHR0hIyty87ODkgpSXVsnfjLh9jvUGxDxAQhE4rioRIShASROkgAEsRVQjRvv0isrKxgaGgIlZWVaGpqgslkijm1I1bIBib1iKeAQ8XWMQ/CmZkZOBwO5ObmCgMlqYitCzeVLBaE7D0RShAG7yGk15wgpIMEIEFcBYjj3IDQ3n6h8Pv9GBkZwdraGtra2lBaWircX+rqGlUAd4dwr3taWhqKi4tRXFwMALsSW8dxXNSkE7beUILQ4/GEja0jQUgQyUECkCD2OWJvP/FG/GjYbDb09fVBrVaju7s7YGAgWhRcIsTiAxjPOeVy8ZeTCI3HBzCW2Lr8/HyhQphIbB1rAcdDNEHo8XgAhLadkct7giD2AyQACWKfwvM8PB4PTCYTdDpdzHv9eJ7H4uIiRkdHUVNTg/r6+h0X6VBJIMkSSQCybGGv1wudToeCggLodDpkZWVFNT4m/kIyz0eo2DomCEdGRuD1epGfnx9XbJ0UtjShBCH753a7SRASRIKQACSIfQjzXHM4HHj55Zdx/fXXx3Sx83q9GBoagtVqRXt7u7A/LJjdqgDyPI+FhQWMjY2htrYWeXl52NjYEGxN0tPTBTEYPMVKF/edSJUEAvwltq6ioiJsbF1wSkmwIJRyPQzx9gaVSrVDEIpbxmlpaYIgjMcGiSAOAiQACWKfIfb2i6clx6ps2dnZ6O7ujmgJshsVQJ/Ph8HBQVitVpw+fRoajUaoADJbk83NTVgsFmGKNScnRxAcfr+fKoAhSIXICRVb53A4BEE4NzcXMrYukRZwImsLJwhdLpdwGxKEBBEICUCC2CeE8vZjF1dm9BzufrOzs5iYmEB9fT1qa2ujXvhSXQG02WzQ6/XIysoSxGiwoFOpVCgoKEBBQQGAK9VLJjjY0IJKpcLU1BQKCgqg0Wj2LGlCLkJitwSxQqFAbm4ucnNzUV1dHTa2jr2PHA4HsrOzdzWlBNgpCNl7p62tTTCjJkFIHFRIABLEPiBcnJtYAIbC4/FgYGAANpsNnZ2d0Ol0MZ0vVVPAALCwsIDR0VHU1tairq5O+Hm086WlpQUMLczNzWFlZQUulwtDQ0Pw+XzQaDRCyzgvL+/AXdBT0XKNhXCxdSMjI3A4HHjppZegVqsDKoTR9ndKuTbxeRwOB5RKJTiOEyqE7MsUCULiIEECkCBkDqv6hYpzE0dvBWOxWNDX1wetVovz58/H5fGWihYwO97ExETE/Yexkp6ejoyMDBw7dgw8z8PpdMJqtcJisWBubg4AAlIwdqsCtZfslQAMhsXWZWRkoLS0FGVlZdjc3Nyxv1P8+mRmZqZ8XexviP3diCuEfr8ffr8fLpeLBCFxICABSBAyJdjbL9QFiP23WKzxPI/JyUnMzs6iqakJ1dXVcV+4WOtOKkFht9uh1+sBAOfOnUN2dnbSxwT+InwVCgVycnKQk5ODqqoqcBwHu90Oi8WC9fV1TE5OIi0tTRAbBQUFuxaLttvISaSw949SqRSee/H+TqvVKsTWZWZmCobUqYqtC7VVIlSOsVgQBg+ViHOM5fRcE0S8kAAkCBnCvP2YsAt3sWEXJnY7l8uFvr4+eDwenD17Fvn5+QmdX9yWTfYit7S0hOHhYVRXV8PhcEgWPxapTa1UKpGfn4/8/HwcPnx4h+AYGRlBdna20C5ORQrGXiCXCiAj3BBI8P5On88nmFKHiq3T6XSSvD6R9soyIglCn88n/D54DyEJQmK/QQKQIGSEOM4tVMs3FKxdazQaMTAwgJKSEpw+fTqpFIdIreVYEaeMnDx5EjqdDrOzs3syuRtqoCRUCgYThImYHssBuU1Fx+oDqFarUVRUhKKiIgA7Y+sGBweRm5sbkGOcyPs7FgEYTDhB6PP54PV6AwShOMd4rwaSCCJWSAAShEwIN+gRDYVCgenpaRiNRhw7dgwVFRVJryXWwYxwOBwOGAwGqFQqIWWEPS6pREoygyrBsWhutxsWiyXA9Fij0Qjt4kgDJXISXfulAhiNULF1bMJ4cnJyR2ydVquNSbD7/f6khRkJQuJqgQQgQcgAcZxbPJvNnU6n0N7s7u5GTk6OJOsJtbcwVlZWVjA0NISqqio0NjYKF75kRWW4NUpBRkYGysvLUV5eLpgeM0E4Pz8PAMLetIKCAlkPlMhpXVIJ0vT0dJSWlgpZ1eFi68QpJaEEYSIVwGhEE4RA6JQSEoTEXkMCkCD2EPHeolhbvgwmtJRKJY4ePSqZ+AMSawFzHIfR0VEsLy/j+PHjgl0LI5oATEQopKL6JjY9rqqqAs/zsNlssFqtMJlMmJqaglqtFsSgnJBTNRKQJgouFJFi65aXl+Hz+ULG1qVCAAYTThB6vV54PB7h9yQIib2GBCBB7BGJtnzFe+va2towPj4u+drirQA6nU4YDAYoFAp0d3dHnPKVYwUw2nnYQElNTQ04jhMSSpaWlrC1tQWFQoGxsTFJBxYS4WppAcdLcGyd0+kU9hAuLi6C4zhoNBphTbv5PIUShKziz0ThxsYGKisrBUHIpowJIpWQACSIPSCSt18kbDYb+vr6oFarhb11k5OTKYlti3WP3draGgYGBlBRUYHm5uawF/x4jhkre1HxEluaAIDRaMT4+DgUCoUwsJDI/jQpkJsATFUFMBJiS6Dg2LqlpSVsb2/j0qVLAabUOTk5uyoIxe8Hm82GmZkZlJSUhKwQiqeMCUJKSAASxC4i9vZj1ZFYPth5nsfi4iJGR0dRU1OD+vr6gL11UgtAdtxIAovjOIyNjWFpaQmtra1COy4aUrWA5XJBZJv9GxsbAQTuTxsdHYXH49kxUJLKqphcnhdg9yqAkRDH1nk8Hni9XlRUVGBjYwMWiwXT09NQKpUBgnA393iyTG821SyuEDJBqFQqdwyVyOl1JvYnJAAJYpfgOA4+ny/ulq/X68XQ0BAsFgtOnTolWGUwxD6AUhJJWG5vb8NgMIDjOHR1dcW8/zBaxnC8FzW57XkDAvensYESJghZO1Kr1QqWM1JWn+T2fOxFBTASTGyxlr44ts5qtQqm4WyPpzilJFWPw+/3B1QEgyuE4QThU089BaVSiZtvvjkl6yKufkgAEkSKYR/gHo8HQHhT51Bsbm7CYDAgOzsb58+fD5mOkCoBGE6sMb/BsrIyNDc3x93e3G97AJNBPFDC2pF2ux1WqxVmszlgoESckZsocmsBy209HMft8A9ksXUajUYwDd/a2oLVasXKygrGxsZSGlsXLACDEQtC9rfDcRx+9atfIT8/nwQgkTAkAAkihbBBj9nZWayvr+P06dMxt3xnZ2cxOTmJuro61NbWhr1fKiuAYrHGcRwmJiYwPz+fsN9gtApgvMit4hUNhUKBvLw85OXlCdUnllDCxAaLRCsoKIBWq40rOUVugksOLWAxsUwBq1SqgD2ekWLr2L9k0m1YVTIW2GurUqngdDpRXl6e8HkJggQgQaQIsbefSqWKuR3m8XgwMDAAm82Gjo4O4UIUDqlFlfi4wRFzXq8XXV1dyM3NTfi4B6kCGI3ggRJxJNrs7CzsdruQgFFQUACNRhM1AUMuz8tuT9vGQiI2MJFi6+bm5jA0NIScnJyAoZ94psATNad2OBySWj8RBw8SgAQhMaG8/ZgAjIbFYkFfXx+0Wi3Onz8f04Uk1RVAk8mE/v5+FBcX4+jRo0lNtB70CmA0giPRWAKGxWIJMDxm+weZvx1DTs8HW8t+qwBGI1Js3fT0NBwOR9jYutbWVsFYXMxtt92GH/7wh3Gtg52HIBKFBCBBSEg4b79oIo3neUxNTWFmZgZNTU2orq6OuXKSKgEIAAsLCzAajWhpaUFVVZUkx5RDFJyUpHINwQkYbKDEYrEEDJQwsbEbRsexwt6T+70CGI1IsXUTExNwuVyCLdDPf/5z5OTkCF+ihoeHccstt+C6666L+7wkAIlkIQFIEBLBBj1CefsplUpBFAbD2qsejwdnz55Ffn5+XOdNhQ2M2+2Gx+OBxWLBuXPnkJeXJ8lx5SLa9ivBhscOh0OIrJuZmQHP88jMzER2djYKCgqSGihJFvY6y0kASpEFHI1g0e5yuQRBaLVa4fF4hJSSX/ziF6iqqkJnZ2fc53E6ndQCJpKCBCBBJAlr+Xq93rDefuFawOvr6+jv70dJSQlOnz4ddX9XKKSuAJrNZvT390OhUKC5uVky8QdIKwAPupgU+9uxgZLBwUF4vV6srq5ifHwcGRkZwv7BZIcV4uVqbQHHS2ZmZkDONBOERqMRP/3pT3HzzTdjfX0daWlp0Ol0MflEMvFPFUAiGUgAEkQSxOrtFyzSOI7D+Pg4FhYWEp6oDXfsROF5HtPT05ienkZTUxMWFxclr95ILQCJv6BUKpGeno6cnBzU1dXB7/eHHFZgYlC8Ny0VHJQWcDwoFAqhivvCCy/A4XDgtttuQ25uLmw2GxYWFoS2Pmvt5+XlhXwO7Xa7pF/OiIMHCUCCSACxOSubdIx0oRNXAJ1OJ/r6+sBxHLq7u5Nu40RqL8eKx+NBf38/nE6n0IZeXl6WvMJ2NUTBhUIuIkc8datSqVBYWIjCwkIAEDJnLRaLsDeNtSJ1Oh00Go2k4iiWv4vdZq8EoN/nA8f5kJb+F//AH/3oR7juuutQXFyMgoICVFVVBcTWMeEOYEdsHXDlcyTZCuAzzzyD++67Dz09PVhZWcHPf/5zvPGNb4x4n6effhp33303hoaGUFFRgU984hO4cOFCUusg9gYSgAQRJ+I4NyA2Y2cm0lZWVoQPzki5ufGgVCrh9XoTvr/VakVfXx80Gg26urqEyeNU7C2kCmBqiWS7kp6ejpKSEpSUlABAQELJ8vIyfD6fIDQKCgqQm5ub1HMstxQQYPcFoMNmxdRTjyJz4RmoOA/s2mYUdN4OPqsQTz31FB599NEAI2hxW7+6uho8zwspJWazGdPT0/jOd74Dn88Hu92OtbW1pKx2HA4HTpw4gXe961247bbbot5+ZmYGr3vd6/De974XP/7xj/Hcc8/hzjvvRHFxcUz3J+QFCUCCiAOxtx+b7o0FVjEcGhpCW1ubsEFcChJtAYvNphsbG3Ho0KEdgyu7VQHkOA6jo6MwGo1CpaOgoCDqnjW5VADlRKxiINRACROEs7OzQj4uaxlnZWXFJTTkZgINxGe6nCxejxtT//0llFh64FZlw69Qo9R0GY6Lo/iF8TCKi4txww03wGAwhF2TQqEQYutqamrAcRx4nsevf/1rPPnkk7jllltQUFCAa6+9Fu985zvx2te+Nq413nTTTbjppptivv33v/99HDp0CPfffz8AoKWlBS+//DK++c1vkgDch5AAJIgYCOXtF+vF0GazwWAwAEBcubmxkogA9Hq9GBgYwNbWFjo7O6HVanfcZrcqgC6XCwaDAX6/H3V1dbDZbJifn8fw8DByc3MFE16NRrMjM5UIJFFBHFx5Yvm4FosFa2trGB8fR3p6uiAGdTpdyFjC4LXI7TXazQrg/NDzKNzow2ZGGTj1lWlsF18AnXMGaWN9eOtb3wG1Wh3XZLJSqcSrXvUqHD16FA8//DAWFxcxMDCAJ598EhsbGyl8NFe4fPkyrr/++oCf3XDDDfjBD34Ar9cblwE2sfeQACSIKITz9ovlfouLixgdHUV1dTUcDkdKpjDjFWosXzg3Nxfd3d1h17QbFUCz2Yy+vj4UFxejubkZfr9fqI6KTZBHRkbg9Xqh0WgEQciSJoi/IJXoEufj1tbWCnFoFosFCwsLGB4eDki/0Ol0OwZKDnoL2LE6iSzeL4g/4Mr7f8vFoyXPiZq3vQ1A9CzgkMd2OIQUmVe/+tV49atfLenaw7G6urqje1FaWgqfzweTyUTRdPsMEoAEEYFI3n6R8Pl8GBwchMViwalTp1BQUIDZ2dmUGDbHKtR4nsf8/DzGx8dRX1+Pw4cPR3w8qbBZYcfkeR4zMzOYmpoSTKY5jgsYZhH7qfE8D6fTKQjC2dlZKBQK+P1+LC8vo6CgAJmZmRHOfHBIhegKjkPzer1Cu3hqagrb29uC2XFBQQHy8/Nl1wJm2zB2a02qjBwoeIDnOSgUfzlndnYmys++Hg0NDQASa0uzGLi9ENjB55Sj3yMRGyQACSIEsXj7hYNV2LKzs3H+/HlkZGQIH5KpEoDRjuv1ejE4OIiNjY2Y8oWB1LWA/X4/9Ho9bDYbzpw5A41GE9P9cnJykJOTI4jFtbU1jI6OYmVlBWNjY8jKygrwvEulxYkYOVUhd6vtmpaWFjBQIjY7Hhoags/nQ3Z2Nnw+H7a2tsJamewmu+1LWH7sGliHf4J81zJsGRXgFQqk+2xQ8T7wR64VbpdIBdBut++JACwrK8Pq6mrAz4xGI9RqtTBtTuwfSAASRBDJtHzZUEVdXR1qa2uF+ykUCqhUqqTtWkIRTQBubW0FCNJY29CpaAH7/X5MTEwIE8eJtsSVSqWQg3v69Gn4fL4dFSlmccIqUnKqRqWKvRKjwWbHTqcTi4uL2N7eFva/itvF2dnZuy5e2N/Ibr0PCkqrYT7z/4Prpe9D67qS/+tVZmK9/FU4es2VgQn2RTPeNe1VCkhXVxd+9atfBfzs97//PTo6Omj/3z6EBCBBiGBVv3hbvh6PBwMDA7DZbGErbKnK7A13XJ7nsbCwgLGxMRw5cgRHjhyJ66IrdQVwaWkJW1tbKCkpwalTpyQRAEzwqNXqgDxWl8sFi8UCi8WCpaUlcBwXMF28FwJkN5DD4AWr1hYWFmJzcxMdHR2w2+2wWCxYX1/H5OSkkHrBXo9oAyVSsNsCEAAazlyPzboTWB5+DpzXhfzKFhxvOAHF/62BrSmRFrAU72G73Y7JyUnhv2dmZmAwGFBQUIBDhw7h05/+NJaWlvCjH/0IAHDhwgV873vfw9133433vve9uHz5Mn7wgx/gscceS2odxN5AApAg8JdoJafTKUQxxfrharFY0NfXB61Wi/Pnz4f9JrybAtDn82FoaAgWiwXt7e0JtWekqgByHIeRkRGsrq4iPz8fRUVFkoiUSMfIzMxERUWFYHHCBIjJZMLU1BTS0tKEVnEsdjP7ib0WgAw2BMKqtfn5+Th8+LAwUGK1WrG0tISRkRFkZ2cLr4VWq01JNYlV33f7+dEUlkJzzZtC/i5RAWi32yWJgXv55ZcDBkjuvvtuAMDf//3f45FHHsHKygrm5+eF39fW1uKJJ57ARz7yEfzrv/4rKioq8J3vfIcsYPYpJACJAw/z9ltZWcHq6io6OztjbvlOTU1hZmYGTU1NqK6ujpoGkooWcHCljtnOZGRkoLu7O+HqihRDINvb29Dr9QCA7u5uDA8PJ3W8YGJZn0KhQF5eHvLy8lBTUxMw0RpsN8Mi0nbLK05q5FABZIQbAgk1UMIi66ampoQvYez1CLb/SZR4q/q7gXibSTxIlQP8qle9KuLf0COPPLLjZ6985SvR29ub9LmJvYcEIHFgEce5cRwHtVods3WFy+VCf38/3G63EJ0Wjd2oAC4uLmJkZASHDx9GfX19Uhe7ZFvA6+vr6O/vR1lZGVpaWoSLr1TPQaKPLViAiO1mRkdHd9jNxJKIIRdRIaeBlFj/ltLS0gLa9263GxaLBVarNcD+h7WMWYU+kfXIbR8oGwCJ9/3DpoAJIhlIABIHklCDHrFW6JiwKSkpQXt7e8zTpqkWgAMDA1hfX8epU6dQVFQkyXETqViKK6NHjx5FZWWl8DuphZQUgiea3QzzW2OCUM52M3KrACayloyMjICBku3tbUEQsnakOLIu1r1wchWAiayJBCAhBSQAiQOHOM5N3BKKJgA5jsP4+DgWFhZw7NgxVFRUxHXeRAVVNNxuNzweD5xOJ7q7uyUTKIlU6zweD/r7++F0OkNWRmNpK8cqHNhtpBQ9oexmWCJGOLsZuSEnAZis4FIoFMjOzkZ2djaqqqoCsnHZfk61Wh3weoR7/8tVACbS3paqBUwcbEgAEgeGaHFuKpUqrOBxOp3o6+sDx3Ho7u5O6Nt3pOMnyvLyMoaGhgAAnZ2dkl7g4h0CESeMdHV1hdzIH00AxiPmdkPoBCdihLKbycrKgs/nw8bGxp7bzezHFnA8hMrGFQ+UjI6OIjMzMyCyjr0P5SgAE80mttvtwhYGgkgUEoDEgSAWb79wFcCVlRUMDQ2hoqICTU1NCW9Il7IF7Pf7MTo6itXVVTQ3N2NkZETyi1s8QyBs72E0u5lUpIvsZtszlN3M3Nwc1tbWMDAwsOd2M3JrAadacLH2vE6nw5EjRwQhbrFYMDMzg8HBQSGhRG4DIEDiLeDt7W2qABJJQwKQuOqJ1dsvuEXr9/sxMjKCtbU1tLW17cjAjBepBKDD4YDBYIBSqUR3d7cwzCI1sazX7/djeHgY6+vrMdnNSCkA5XAxZ9Wmra2tAL+7vbKbkZMA3IssYLVajaKiImEPrNvtFiq2JpMJXq8Xvb29wuuR6ECJVCTaArbb7cjOzk7BioiDBAlA4qqF53n4fD74fL6Y4txYi5b5xvX19UGtVqO7uxtZWVlh7xcrUtjArK6uYnBwEJWVlWhqaoJSqYTL5QIgfYsrmlhzOp0wGAxQKBQx7z1MVQVwLxFnocrBbkYuAlAOYjQjIwNlZWUoKyvD8vIylpaWUFpaCqvVisXFRXAcB61WK7wmux2vRnsAib2EBCBxVcJxHHw+X1xxbuyDeH5+HuPj46ipqUF9fb1koiqZCiDHcRgbG8PS0tKOaiRbXyoEYLj1Go1GDAwMoLy8HM3NzTGf92qrAEYiFXYz0ZCD6GLsRgs4HnieR3p6OiorK1FZWSl80bNarTCbzQEDJeyfFF/8IpHoHkCn00kCkEgaEoDEVYXY249dDGO9IDJhMjU1JZmViphEBSAbQOF5Ht3d3TtaP+wiK3UlLNQQCM/zmJycxOzsbEKT0JEEYKLCZa8rgLESbDfD7E2ktJuR03OxFy3gSAR/QRJXbA8dOhQwUMImvjMzMwMEodQtfLKBIfYSEoDEVUPwoEc84o9NsALA6dOnodFoJF9fIjYw4kpbuAEUcQVQSoLFmsfjQV9fH7a3t3Hu3Dnk5eUlfcxQv4/nWPuVYHuTWOxmYvWblMvzIrcKYLQKuXigBIAwUGK1WjE3N4ehoSHk5uYKr4lGo4n5NQlHIi1gFluZyN8fQYghAUhcFYTz9osGz/OYm5vDxMQE6urqMDExkbIYMJVKBZ/PF9NtxZ6Dra2tKC8vD3tb9lilFoDiiuXGxgYMBgM0Gg26u7sTvvBdjXsApSAWuxkWj1ZQUBDWbkZOLeBE25upIt4tEsEDJeIW/tjYGNxuN/Lz8wWBnogFEO0BJPYSEoDEviaat18kPB4PBgYGYLPZ0NHRAZ1Oh5mZmZSYNQOxt4BdLhcMBgN8Pl9MnoOs0pmKCiDHcZifn8fY2Bjq6+tx+PDhPY2XCz6WXJB6LaHsZli7eGlpKazdjJzEsJzEKJD8HllxCx+4YsXCBKF4oIS9LrHs6fT7/Qm1lWkPICEFJACJfUss3n7hsFgs6Ovrg1arxfnz5wWz2FSYNTNiEYAsZq60tBQtLS0xVwdSETPHYtEmJydx+vRpSYxnqQKYGJmZmaioqEBFRYUwvBDKboZNvcsBuRkvS72erKwsZGVlCa+Jw+EQIutmZmYCWsoFBQUhB0oSqZJyHEd7AAlJIAFI7Es4joPH44m76ifOqW1qakJ1dfWONJBUVQAjHZvjOExOTmJubm5Hfm4sSC0AHQ4HxsfHwXEcrrnmGknj5Q7KFHCqiGQ34/P5MDg4uCt2M9GQYwUw2T174VAoFMjNzUVubq4wULK1tQWr1Yq1tTWMj48jIyMjQBCmp6cnNATidDrB8zztASSShgQgsa9gLV825RuP+HO5XOjv74fb7Q6ZUwukVgCGE2nidXV1dSXU2ok3ti0SLNWioKAADodDMvEHUAUwFYjtZtbW1tDU1AS/359Su5lYkNsQSKLt1kRQKpXQarXQarWora2F3+8XBkqYJ2ROTg58Pp8QJRirOHU6nQBALWAiaUgAEvuGRLz9GKy1WlxcjPb29rAftolM6sZKKAFoNpvR19eHoqKiiOtK5NjxwnEcJiYmMD8/j7a2NqSlpQk5w1JBFcDUwrzu8vPzY7KbSaXXndxtYHYTlUqFwsJCISnH4/FgY2MDY2NjMBqNWFpaQn5+vlAh1Gg0YdfqcDigVquRkZGxmw+BuAqRz9czgggDq/ptbW3hj3/8I4DYxR/HcRgdHYXBYEBzczOOHz8eUWSlcg+guLrI/PR6e3vR0NCAtra2pNpTyQpAt9uNl19+GUajEV1dXSgrK0tJtS7aMV0uV9yPY68rgHt9fjHBa2F2M1VVVTh+/DiuueYaHD9+HDk5OVhZWcELL7yAy5cvY2xsDOvr65LuH5RbBVBOexLT09NRUlKC9PR0tLS04Ny5cygvL8f29jaGhobwzDPPwGAwYG5uDjabLeB1ZTFwUjyWBx54ALW1tcjMzMTp06dx6dKliLd/9NFHceLECWRnZ6O8vBzvete7YDabk14HsTdQBZCQNeI4N4VCAY/HE/MFlxkocxwX0zQtsDstYLfbjf7+fmxvb4dtRSd67ESwWq0wGAzQ6XQBVchUTRaHev04jsPIyAgWFhaENIaCggIUFhaGbUGzLwByEmByINIXI6nsZmKBKoDRYXsAQw2UsNdldnYWCoUCOp0Oly9fRk5OjiQ5wI8//jjuuusuPPDAAzh//jweeugh3HTTTRgeHsahQ4d23P7ZZ5/FO97xDnz729/GzTffjKWlJVy4cAHvec978POf/zzp9RC7DwlAQrYwbz8mQtikbizeWSsrKxgaGkJFRUVYA+VQpLoF7PV68fzzz0On0+HUqVOSbUpPRKzxPC/E3jU0NKCmpibggi3lvkLxOoOPyWxv/H4/zp07B6/XC4vFgtXVVYyPjyMrK0sQJDqdLuC1lJPAkAPxDl6Es5uxWq0YGBgIazeTirWkGrkKwODPJvFASXV1tWASvra2hkcffRT9/f1QKBR497vfjde+9rW49tprI/qEhuNb3/oW7rjjDrznPe8BANx///343e9+hwcffBD33nvvjtu/8MILOHz4MD70oQ8BAGpra/H+978f3/jGNxJ45IQcIAFIyI5w3n5MOPh8vrCbuf1+P0ZGRrC2trYjMzcWUlUB5Hkeq6urcLvdOHr06I7p42SJtwLo8/kwNDQEi8UieCAGsxstYFZ9LCwsxNGjR+H3+5GVlbWjQmWxWDA+Pg632w2tVisIQp7nqQIoItnnIla7GfEka6S1yElwyc2YGojty6y4avv000/j//2//4evfe1rKC0txbe//W284x3vwFNPPYVrrrkm5vN6PB709PTgU5/6VMDPr7/+ejz//PMh79Pd3Y3PfvazeOKJJ3DTTTfBaDTipz/9Kf76r/865vMS8oIEICErInn7KRSKiALNbrfDYDBArVaju7t7x+b2S5cu4dvf/jb0ej1WVlbwX//1X3jDG94QcJtUCEBmOL21tQW1Wh2yvZIs8QhA9jylp6eju7s77GbyVHgLMgHI8zwWFhYwNjaGxsZG4TnhOC5AxARXqJxOZ8BAAwBMTk6ipKQkqiA5CEhZdYtkN8MmWSPZzVALODIstzxeUer3+1FeXo6vfe1rAK54msY7EWwymeD3+3d8QS4tLcXq6mrI+3R3d+PRRx/F7bffDpfLBZ/Phze84Q347ne/G9e5CflAApCQDbF4+6nV6h0Cjed5LC0tYWRkBDU1Naivrw/5Qe90OtHW1oZ3vOMdeMtb3hJyDVILQBahlp+fj1OnTuGll16S7NhiYm3Xrq6uYmBgAIcOHUJDQ0PEC2KqKoAcx2FwcBDr6+sBBtOxnCs4P/fpp59Geno6FhYWAgRJQUEBtFrtrl3w5SR0UrUWsd0MEBiNFspuRm6CS47rARC3AHQ6nQH7mZMxaA9+r0T6AjE8PIwPfehD+NznPocbbrgBKysr+PjHP44LFy7gBz/4QcJrIPYOEoCEbPD7/VGNnYMFGjO+tVgsOHXqlJDbGYobbrgBN9xwQ8Q1qFQqeDyexB6ACHHGMNtft729vWcpIyxbeHFxEcePH4+pNZ6KIRCv14uNjQ3k5uaiu7s7KY9BpVIJpVKJ6upq5OTkBAiS4eFh+Hw+oVUZ7/61/cpu7rsTR6OFspvx+/2Yn5+Hx+NJqd1MrMhNAIq7HPFgt9uT9gAsKiqCSqXaUe0zGo1hPxvuvfdenD9/Hh//+McBQJgmv+aaa/DlL385oX2IxN5CApCQDQqFIqq9i1gAbm5uoq+vD1lZWTh//rwkvlhSVAC9Xi8GBwexubmJzs5OaLVa4dis7SP1hSiSAHS5XOjr64PX60VXV1fMEVJsjVKJCrPZjKmpKajVapw9e1ay54BVDoMFCYvmYudl+9cKCwuh0+mEoaKrib3aD8nsZsTV2eeffx6ZmZlYWVnB2NgYMjMzA4Z5UpXKEY6rRQBKEQOXnp6O06dP4+LFi7j11luFn1+8eBG33HJLyPs4nc4drxmrXtI+3P0JCUBCNigUiqhCQ61Ww+v1YnZ2FhMTE6irq0Ntba1kVY9kp4A3NzdhMBiECpd4Txr7oN9NAcgyjwsLC3H69Om4Lrpim5Vknl9xNbSsrAxOp1Oyxx9uXcHRXCyJwWKxYGZmBkNDQ4LdSWFhIfLy8hJek1wufmwdcqhysupsRUUFtFotfD6f8PxLbTcTK3ITgGz/X7yvl8PhkCQF5O6778bb3/52dHR0oKurCw8//DDm5+dx4cIFAMCnP/1pLC0t4Uc/+hEA4Oabb8Z73/tePPjgg0IL+K677sKZM2dQUVGR9HqI3YcEICEbYvkgVCgUmJmZgc/nCzu9mgyJGkGLhxrCiVKxAJSa4HYtz/OYnZ3F5ORkyMzjWJBCsPr9fqFF39nZie3tbczNzSV0rHDEIsCCkxjcbrdQHVxaWgLP8wHt4r1uVyaDHAQgEDgEolarUVRUJGzRkNJuJp71yEkAxjIBHAqHwxFxq0us3H777TCbzbjnnnuwsrKC1tZWPPHEE6ipqQFwxUprfn5euP073/lO2Gw2fO9738NHP/pRaLVaXHvttfj617+e9FqIvYEEILFvsFgs2NjYQHZ2Ns6fPx+1hcf5/ZjUPwXb5GVAqULh0WtRc7QTiggXgURawGwfotVqDRhqCIZdfFJhMyOuAPp8PgwMDOxoQcdLskbLTqcTer1emMrOyMiAy+WStGKWqEjIyMhAeXk5ysvLwfM8bDYbLBYL1tbWdngParXaXW9XJoKcKoBAZBuYWOxmxII82enuVG29SAZmAh0vDocDtbW1kqzhzjvvxJ133hnyd4888siOn33wgx/EBz/4QUnOTew98v9UIw48PM9jamoKMzMzyMvLQ1FRUVTx5/W4MfAfd6PG9DRK4IMCgGf6MfT0vQmn/+5zYe8XrwDc2tqCwWBAVlZWREsV4C97HFNRAWTHtdlsMBgMyMzM3NGCTuSYQGIVS5PJhL6+PpSXl6O5uVk4Viomi5M9nkKhQH5+PvLz83H48OEA78GJiQm4XC5hurWwsBC5ubmyEVli5NKKZsS6dSCS3UzwdHcou5lYYO9huQnARCqATqdTkiSQveKee+7B0NAQysvLkZ2dLbz2bMtGTk4O8vLyoFKphEETIjWQACRkQ6iLhcvlQn9/P9xuN86ePYvFxcWYBMnwk4+h1vQnbCuy4VZqAQBZfhtqZv4f/vSzMgDA7Ows+vr6oNPpBB+6WPcA8jyPxcVFjI6Oora2FnV1dTFd7FIpALe2tvDCCy+gpqYGDQ0NSYuURCqAPM9jZmYGU1NTOHr0KCorK3ccUw4VwEgEew9ub2/DbDbDYrFgbm4OSqVSqEwlY8EhNXKrACbqAxiv3UwsglyOAjBRY2oppoD3Eo/Hg7W1NaytrcFms8HhcMDhcGB7exterxderxfAlc/+5557Dl1dXXu84qsXEoCEbFlfX0d/fz+Ki4uFjNpYK3SK8d9BAR5u1V++Pdp8auicS9D/8JMAgE984hMAgLe97W34t3/7NwCxVQB9Ph+Gh4dhMpnQ3t4u7CuLhVQYTXMcB4vFgq2tLZw6dQolJSWSHJddVGMVrOLW85kzZ6DRaEIeM5oAjHfoJNWVr6ysLFRVVQnTrVtbW7BYLIL3ZEZGBnieh8VigUaj2fO0CbkIQKmSQKLZzSiVSqFdHM5uRo4CMJkKYF5eXgpWtDt8+ctfDvs7r9cLt9sNr9cLh8MRd5ITER8kAAnZwTzrFhYWdlSRVCoV3G531GOofQ5wCPywV2fmIE1diGtvfQ1cTzwQ8n7RhkBYikZaWlpCPnZSVwBZjq7L5UJxcbFk4o8Ra8XO4XBAr9cL6SLRIsKkXN9uolQqodVqodVqceTIEXi9XkxPT8NoNGJkZARer3fPvAflVAFkaS9SryWU3QzbvxnJboZVI+UmABPdA7ifW8AM9v5wuVyYnZ0Fz/M4cuQIcnNzBQ9PIrWQACRkhdPpRF9fHziOQ3d39479H6GSQEIep6wDqtkxKDk/OOWVb9kqzgtAAUXlybD3i1ShW1pawvDwcMS0kWhIKQDNZjP6+vqEdqXNZpPkuGJiSRgxGo3o7+9HVVUVGhsbIz4vsSaWxMNe7n1LS0uDRqOB3W5He3s7nE4nzGbznngPymkPIFtLqgWXOCeXZUeHspvJy8sTJuXlIgITqQAyf8v9XAFkKBQKbGxs4N5778WlS5fwwgsv4NKlSzh//jweeugh5Ofn4y1vectV6dcpF0gAErLB6/Xi8uXLKC8vR1NTU8gPx1hbqIdf+Q6YF/+EIt8K3Fw6FOCRDi+WMhvQcM2bw96PVQDF1Qu/34+RkRGsra3h5MmTwt6wREjUZkaMeJ9dc3MzqqqqMDc3lxIBECkNRDyc09raGnMSgNQVQDkIH+ZhmZOTg5ycHMF7kA0zzMzMYHBwEPn5+SnzvpNbBRDY/bWEs5sxGo3gOA6XLl1Kud1MrCTTAt7PewDF3HvvvfjFL36BL33pS3jPe94jtO8rKirwzW9+E29605tIAKYQEoCEbEhPT8e5c+ciTn3FKgCLKg7D/5YfYOKP30eR8XlwChXM5a9C3Y13IjdPG/Z+YqsWtVoNh8MBg8EAlUqF7u7upP3hkjWa9nq9GBgYwNbWVsA+u1QOl4QSWGwdNpsN586di7kikYoKoFwRDzPU19cL3oMWi0XwvhMPk0jlPSgHAcjei3u9FmY3k5OTA7vdjhMnTuxIh5HSbiYeEh0CkcoIWg488sgj+NWvfoUzZ87gve99r/A3cPz4cYyMjOzq63EQIQFIyIrc3NyIAkGtVsPn88V0rNLqOpS+8z7hv2NxzmIfyBzHYWVlBYODg6iuro7a2oyVZISazWaDXq9HdnZ2yJSR3TCYBq7sg+zt7UV2dja6urri/pC+2iqAsZ4/mvcg27tWWFiYkPegHCuAcmm3MrGVaruZeEikAuj3++F0Oq8KaxSO42C321FZWQmO4+D3+4W9jR6PB9vb21T9SzEkAIl9RSqmaMWwC9bo6CiMRiNOnDgh6WBFohVAtv8wnOVMKgWgWOCsrq5iYGAgYasZqSuAchA7iRDKe3BjYwNms3mH92BBQYGwhy0Sey2ExcilAsgItfcvFXYz8eD3++P+8uRwOADgqtgD6PV60d3djf/8z//E+973PiiVSmRmZsLpdOKxxx7DqVOn9nqJVz0kAAlZEa2ik2oBuL29DeCKwXN3d7fk03bx7gHkOA4jIyNYXV2NuP8w1S1gnucxMTGBubk5tLW1oaysLOFjXk1DIFIRvHdNbHUSynswlOF4KqZuE4WtRS7riWX4Qwq7mXhIpALodDoB4KpoAWdkZOCjH/0o7r77bqyursJms+Gxxx5Df38//ud//gePP/74Xi/xqocEILGvUKlUMbeA42VtbQ0DAwNQKpU4duxYSqwW4hFq29vbMBgM4HkeXV1dEdeTygqgx+NBT08PnE4nurq6krr4RBL4iQgGuQgMqcnKykJlZaXQHgv2HszJyUFhYSEKCgoCvAfl8nwkagKdKuK1XEnUbiYeEtkD6HA4kJ6eftXsjbvxxhvhdrvxta99DQ0NDfjSl76EpqYmPP7447juuuv2enlXPSQAiX0FqwBKWe3gOA5jY2NYWlpCa2srRkdHU1ZVilWosSi10tJStLS0RL1QRJrWTQae5zEyMgKNRoOurq6k9+TIMQpO7oTyHrRarTCbzYL3oFarFYS5HCqBcliDmGTtX2K1m4lnwjsRH0C73b6nk8up4JZbbsEtt9yy18s4kJAAJPYV7Ft2ohN0wbAqG8dx6OrqQk5ODiYmJlIipoDoLWye5zE9PY3p6Wm0tLSgqqoqpuOmYrp2ZWUFTqcTZWVlOHHihCQXnf0QBSd30tLSUFJSgpKSEvA8D6fTGWB18vzzzwe0i/diI71UKSBSIbX/Xzi7GavVKkx4a7XaiIbgibSAHQ7HVTEAwuB5Hi+//DIGBwexsbGB0tJSdHZ2or6+/kD+be82JAAJWRHtj559YCbqoSXGaDRiYGAAZWVlaG5uFo6Xyn2GkSqAXq8X/f39sNvtOHv2LPLz8yU5brywJJbFxUVkZ2ejtLRUsg9jqgBKi9h7UKvVore3Fy0tLcLewaGhIeTl5QntYqm9B8MhtxZwqg2gmd1MRUUFeJ6H3W6PajeTqACUehhlr3C73XjkkUfwla98BU6nE1lZWdjY2AAAfPSjH8UXvvCFPV3fQYAEILGvYB/iPp8v4X0wHMdhYmIC8/PzOHbsGCoqKgJ+n2oByMLOxWxubsJgMCA3Nxfd3d1xV22kEoAejwcGgwEejwddXV0YHByUtW3L1XAhlBLxsAiAkN6DTIgUFhZK5j0YzNXWAo4HhUIRk92M2+2Gw+GIy27maoiBY6/Fs88+iy9+8Yu444478PnPf17o7nz/+9/Hl7/8ZWg0GnzkIx/Z49Ve3ZAAJPYVCoUi5ji4ULhcLvT19cHr9YYdaEjWrDkSoY69uLiIkZERHDlyBEeOHEnowimFANzc3IRer4dGo0F7ezvUarXkewvZYwslENxuNwYHB6FQKISKVahp12AOcgVQTKjnNNh70G63w2w2w2g0YmJiIulBhnDIKXIN2Nv1hLObGR4exvz8PKanp2O2m7Hb7ft+Atjr9SIjIwMDAwOorq7Gl770JQBXnpf09HRcuHABAwMDePrpp0kAphj5/IUSBGKr6CRaoTOZTHj++ecFA+NwH6SprACKbWD8fj8GBwcxNjaGU6dOhfT3i5VkhdrS0hJefPFFHDp0CCdPnhSEQKp8+4KPubm5icuXL0OhUCArKwtLS0t47rnn8OKLL2JqagpWqzXk45NLlUkO64j2OrHK1OHDh9He3o5rrrlG8HKcmprCpUuX0Nvbi9nZWWxtbSX1uh/kCmA0mN2MQqHAyZMncebMGRQXF2NzcxO9vb149tlnMTg4iOXlZcGWiiGlCfQDDzyA2tpaZGZm4vTp07h06VLE27vdbnz2s59FTU0NMjIyUFdXh3//93+P+7zsS92JEydQV1eHxcVFABA6Omw4JrgzQ0gPVQCJfUe8Ao3neUxOTmJ2djamwQop8nrDwSp1TqcTBoMBCoVCsoi5RNbMcRxGR0exsrKCU6dOCZvaGamqAIphiStHjhxBdXU1OI5DXV0dPB6P0L4cHBwMiE4rLCxEZmYmAKoAiolHdEXyHpyfn4dCoYBOp4urGsu42odAkoXneXAcB7VajczMzKh2M5mZmRgaGoLRaJSkAvj444/jrrvuwgMPPIDz58/joYcewk033YTh4WEcOnQo5H3e/OY3Y21tDT/4wQ9QX18Po9EYtyXXSy+9hMuXL6OyshJutxurq6u466678I//+I/Izc1Fbm4uHn74YczPz+OrX/1q0o+TiAwJQGLfEU8cnNvtRl9fH9xud8yZtaneA7i9vY3Lly+jvLwczc3NkkXMAfFd6NxuNwwGA3w+X1ifwVRVANmQwPj4OBYWFoTEFfH+yPT0dJSVlaGsrCygfbm6uorx8XFkZ2fD6/XCZrOhuLh4zy7wchGgyVbdgr0HbTYbzGYzlpaWMDo6iuzsbEGAR9u3JschEDl557HPl+DnMJzdzMsvv4x7770Xi4uLKCwsxOc+9zlcd911OHfuXEJT3t/61rdwxx134D3veQ8A4P7778fvfvc7PPjgg7j33nt33P63v/0tnn76aUxPTwut7MOHD8d93pdffhn3338/CgoKwPM8fD4fenp68Pvf/x6FhYUwGo3w+/1IS0vDSy+9hGPHjsV9DiJ2SAASskLKFrDZbEZ/fz8KCgqEPW2xkCoByPM81tfXYbPZcPz4cUlbHEz8xCpGNjY2oNfrUVBQgNbW1rAX81QNbfh8PvT19cHhcODcuXNRqxrijfWHDx8WvPDGxsawvLyMxcXFgGrVft8onwhSvk5iIRLsPchi0sQ2Jzk5OQF/u1QBjAyrqkcb/mBV2htvvBE33ngjLly4gJWVFUxOTuL73/8+/H4/VlZW4hK3zNj9U5/6VMDPr7/+ejz//PMh7/PLX/4SHR0d+MY3voH//M//RE5ODt7whjfgS1/6Ulzdi5tvvhmtra0ArlScXS4X/H4/XC4Xtre34fP54PF4sLq6SuJvFyABSOw74vHSa2pqQnV1dVzVCKVSKXnaiMfjQV9fn7CJW+r9LeIKYLSLysLCAkZHR9HQ0ICampqIz02qWsAvvviisBczkQoG88JbXFxEWVkZ8vPzYbFYsL6+Lgw3MDGo0+kk8YyUO6ncdxfOe9BisWB6ehpqtVpozet0OllWAOUkAP1+f0LJN2lpaejs7MTXv/51cByH6enpuCubJpMJfr8fpaWlAT8vLS3F6upqyPtMT0/j2WefRWZmJn7+85/DZDLhzjvvhMViiWsfYFVVVczepkTqIQFI7DsixcF5PB709/fD6XTG7aUnPr7H40l2mQLi6drm5mZMT09LdmyGWACGg+M4DA8Pw2g0or29HYWFhTEdV8rKktlsBgAUFRWhpaVFMnNptn/o0KFDQtvMbDZjfHwcHo8HGo0GhYWFKCwsvOqSFBi7NXgh9h5kezZZKgbzHmT7M61WKzQazZ6LLzkKQKVSGffrxXwAgSt/m/X19QmvIfjckd4/TNA/+uij0Gg0AK60kf/mb/4G//qv/xpXFZDtf1SpVLDb7cLnYUZGBrKzs5Gfn4/09PSUWRQRf4EEICErYvlADGcDY7VaYTAYoNVqk4otk6oFzPM8FhYWMDY2hvr6ehw+fBgWiyUl7WXx3rpQuFwu6PV6IVc41g9XqSqAPM9jZmYGU1NTABB24jmRLOBggSoebuB5Htvb2zCbzUK1Ki0tTRCDUlqfyIG9ELahvAenpqYChnfEJsh70Z6XowBMpCotRRJIUVERVCrVjmqf0WjcURVklJeXo7KyUhB/ANDS0gKe57G4uIiGhoaYz69QKKBSqbCxsYF7770XzzzzDPR6vfA74Mp76Mknn8QrX/nKeB8eEQdXzycfcWAIFmg8z2N2dhaTk5NobGzEoUOHkroQSiEA/X4/hoaGYDKZAqptUiZ2iGHtpFDHtlgsMBgMKC4uxtGjR+O68EhRAWR2N1arFZ2dnXjhhRckqypGe50VCgWys7ORnZ2N6upq+P3+HRmuzIOtsLBwX6csyMV6JSMjA3l5efD5fGhraxNSMVh7PiMjI6A9vxsCPJHc3VSSaJSluAKYKOnp6Th9+jQuXryIW2+9Vfj5xYsXw2bynj9/Hj/5yU8CfAjHx8ehVCrjbukyMf7P//zP+MUvfoGvfOUr+OxnP4s3vOENqKurwze/+U3ccMMNOHnyZMKPkYgNEoDEvkMs0LxeLwYGBrC1tYXOzk5otdqkj5+sEbTD4YDBYIBKpUJ3d7fQDmPHTrXFDIPneczPz2N8fDyhvZBA8hXA7e1t6PV6KJVKdHV1CVYiUraV4zmWSqUSqn8NDQ2C9YnZbMbc3Jxg2ssEyl7k6CaKXKaRgb8MgYRKxbBarQECPD8/X3jO8/LyUiJir6YKYCxOBtG4++678fa3vx0dHR3o6uoSrFcuXLgAAPj0pz+NpaUl/OhHPwIAvPWtb8WXvvQlvOtd78IXv/hFmEwmfPzjH8e73/3uuFu17H363//93/jMZz6D2267Df/0T/+Es2fP4rbbbsORI0fwne98B5ubmwEVR0J6SAASsiLWFrDb7cbGxgYMBgPy8vLQ3d0tmc1DMhVAo9GI/v5+VFZWoqmpacdFJ9UpI2KT6aGhIZjNZnR0dECn0yV0zGQEoNVqhV6vR0lJCY4ePSo8F5EmixMRqMkQbH2yubkpiMHh4eEdObpyqLBFQi7rCzcEolKpwnoPLiwsAIDQKi4oKAj48pTseuQmABNZj1RRcLfffjvMZjPuuecerKysoLW1FU888QRqamoAXPHmnJ+fF26fm5uLixcv4oMf/CA6OjpQWFiIN7/5zfjyl78c97nZ+8Jut6O8vBzAlfcFM71+xStegb/7u7+D2+1O9mESUSABSOw7lEolbDYbXnrpJWFvnZQXvkSMoDmOw+TkJObm5tDa2ip8sElx7Fhh7drgqlsyF9FEBSubNA5VeZTaWkaqYymVSuh0OkEsu91uYe/gwsICFApFgBG1+AuHHISXXFrAQOxrCeU9aLFYsLy8jLGxsbi8ByMhRwEY72PheV6yCiAA3HnnnbjzzjtD/u6RRx7Z8bPm5mZcvHgx6fOy90VLSwvGxsZw3XXXobOzE//7v/+LV77ylXjxxRcBgKp/uwAJQEJ2RBIIXq8XKysrcDgc6OzsTLiyFYl4K4Bis+lIEXPAX0RaKi7WSqUSGxsbmJqaQllZGVpaWpK+6MVbARQni4SbNJZSAKZS8GRkZKCiogIVFRUBxsgsuzk3NxeFhYXC67nXyGENjER8AINNkJn3oMViwdjYWMA0dyjvwUjITQAmugfQ6XTu+yxg9pp94AMfgNFoBMdx+PCHP4zXv/716O7uhtFoxAc+8AFhqIhIHSQAiX3D1tYWDAYDlEolcnNzUyL+gPgEIJs81ul0MZlNx+PXFw88z8Pv92N8fBxHjx6VzGsrniEQj8cDvV4fMVkEkG8FMBLBxsjimLr19XVwHIeBgYEdMXW7iZwqgFL4AMbqPcj+RdoCIjcBmMwewP0uABmvf/3rhf9/4sQJvPDCC3jyySdRUVGBa6+9dg9XdnAgAUjIHrGdypEjR5Cbm4vJycmUnS+Wtqd4wCIWQ2UG+9BP9AIQCp/Ph8HBQXi9XjQ2NkpqtBprBXBrawu9vb3QaDQ4ffp0RCEcSQDGW03bK8EjjqlbXFzE6uoq8vLyAmLqmBjUarW7Ij7kJAClTgIJ5T3I9mvOz88L+zWZGAz2HpSjAIx3PSwxI1kbGLnA/s7Ze7ayshJve9vbsLy8jM985jOUBbwLkAAkZIdYIPh8PgwNDcFisQgtRbPZnLJBCiD6Pj3xmuIdsIjFsDkenE4nent7kZaWhpycHMnNU2Op1q2srGBwcBBHjhzBkSNHYrJm2W8VwEgoFAqo1WocPnw4IKbObDZjZGQEXq9312LqrlYBGEzwfk1xRXZoaAh+vz/Ae1BuNjCJfAG02+0AINkewL0m3Ht1fHwc9913HwnAXYAEICFbbDYbDAYDMjIy0N3dLViIpCqrl8EEYKiKit1uh8FgQFpaWsCaYiWSX1+8rK+vo7+/HxUVFWhqasKLL74o+YBJpBYwz/OYmJjA/Pw8Tpw4gZKSkpiOuV/2ACZKcOvS4XDsSkzdXgthMVJvcYiGuCLL8/wO70EAmJmZQUlJiSzMvzmOi3sNDocDAPZ9C1j8Pg3197u9vb0nWygOIiQACVnCNtofPnwY9fX1AR8UkaLgpEDcphV/SK+urmJwcBDV1dVoaGhIuKKQrIAVZx0fO3ZMyBWWOrYNCN8C9vl86Ovrg8PhwLlz5+K6KF1tFcBI7GZM3dXcAo6HYO9Bj8eDZ599FiqVaof34F7Z+/j9/ri/PDocDmRmZu65eE2WaM+10+mM+7khEmN/v5OIq5KRkREsLS3h1KlTgl+YGBYFl6oLXrAA5DgO4+PjWFxcRGtrK8rKypI6fjJm0D6fTzC+Ds46ToXJdChR6XA40Nvbi8zMzIQi96SuAMpZAAaT6pg6uQhAKYZApIKto6GhASqVCi6Xa1e8ByORSEvabrfv+xxrp9MJvV6PvLw8pKenIz09HRkZGUhPT0daWhoyMzNhNpspB3iXIAFIyI7S0lLU1NSE/SBmAi1VbSb2Aev3++F2u2EwGOD1etHV1SXJBuxEhZrdboderxeEV/DUYyoEYHAFcH19HX19faiqqkJjY2NCVZ79JtpiIZGLstQxdVQBDA17/7LnJjMzU7D34XkeW1tbsFgsWFlZwdjYGLKysoQWfTLeg5FIZA+gFDnAe8309DTe8573oKKiQtg7m5aWJojBrKwsIbaSSD0kAAnZUVhYGLFFmopJWjEsrNxqtWJ8fBwFBQVRJ1vjIRFz5bW1NQwMDKC6uhqNjY0hL/SpEoBsMpflLR89ehSVlZVJH1PK9V0NJBtTJ6fnQU5ilFUjQwlShUIR0XvQ7XZDq9UK1UGpsqITFYD7OasauFJp/fu//3uo1WrYbDY4nU44nU64XC64XC7YbDZotVqcOXNmr5d6ICABSOw7WMaoz+eTLP5NDLuQDg0NoampCYcOHdqzpBGe5zE5OYnZ2Vm0tbVFbD+nqgXMPO7MZjPOnDmTtEO/lFFwVzOxxtSxDF05ii45EI8FTPAAj1iEz87OCiI8Fu/BaGtKRACmcoJ8N6ioqMCnPvWpvV4G8X+QACRkRyw2IqmaBGaeehzHoaWlBYcOHZL8HLEKNa/Xi/7+fmHQIpr9g1TTxcFrsNvtksTKMagCGD+xxNRlZGRAoVDA4/Gk5ItRPMitBZzoVgXWoq+qqhJEOHvOh4eHhTSYUN6DkUhkD+DVYgLt9/uFv9vgiEjx/xKphwQgsS9JhQAU77HLzs5O2UbkWASgzWaDXq9HTk5OzIMWUlcArVYrxsbGoFQqcebMGcku6FJWAA/qxSJUTN309DRsNhueffZZwRS5sLAQ+fn5uy7G9msFMBJiEV5XVxfSe5C1iwsLC5GVlRX2OTioewAB7Ko9EBEZEoDEvkRqKxhmZlxTU4OGhgZcvnxZ8moaI5p4XV1dxcDAQEgLnEhIaQPDbHgqKyuxvr4uearD1WQDs9fnZzF1Op0O6enpaGhoEITJwMAAeJ4PMKLejSlXObWjU2UCHew9yPweTSYTpqamkJ6eLrSKdTpdwJe4ZPYA7nfklspykCEBSMiOWC4czAomWTiOw9jYGJaWlgLMjFNpNh2uUsfzPMbHx7GwsIDjx4+jtLQ07uMmu2aO4zA6OoqVlRW0t7cDuDL5KyXhBCDb77ixsRHgi8f453/+Z/zyl78UzJTPnj2Ld77znaivr5d0ffsVJrqChYnNZguYcs3Ozg6Yck3FxVhOF/ndWEuw36N4ontmZgZDQ0MB3oMHsQLI3p9yeV8QJACJfYoUAs3lcsFgMMDv96O7uztAbOy2APR4POjr64PL5YrbWFl8XK/Xm/C6PB4PDAYDPB4Purq6kJ2dDavVmhJz6eBj+nw+9Pf3w263o6ysDGazGZOTk0JqRmFhIZ599lm8733vQ3t7O3w+H+655x588IMfxM9+9jNJ17efCf7ypFAokJ+fj/z8/KgxdaxtKQVyqgDuhRgVT3QD2OE9yFJ0iouLY67K7mcByN4PL7zwAtLT04Uvl6HeJ263G+np6bJ5/1zNkAAk9iXJtoDNZjP6+vpQXFyMo0eP7vg2nmoBKD721tYW9Ho98vPz0dXVlbDdTDJ7AG02G3p7e5Gfn4/29nZhDakYLAkWgNvb2+jp6UFGRgbOnj0Lnudx+PDhgNSM0dFRfPjDH4ZOpxOmXx988EEcOXIEw8PDaGtrk3SN+5FYhHqomDqz2Sx5TN3VMAQiJWLvQa/Xi0uXLiE3NzfAe1DcLg71vDscjqTsl/YSNvX88MMP47e//S0efPBB3HLLLQHDIOx/b731Vtx2222444479nrZVz0kAAnZkcoWMM/zmJmZwdTUFJqbm1FVVRXWUy9VAlBsA7O8vIyhoSEcOXIER44cSepbb6ICkO05rK2tRV1dXcAaUhUvx45ptVqh1+tRVlaG5uZmAFcqkUBgakZjY6MgVoxGIyYmJmCxWABcubjK4SK/18RbdRO3LWtqakLG1ImHGuJJobgah0Ckgv2N1tbWQqlUwufzCd6D4+PjYb0HpdoD+MADD+C+++7DysoKjh07hvvvvx/XXHNN1Ps999xzeOUrX4nW1lYYDIaEzr20tASn04nPfOYzMJlMuOOOO3Z8IVxcXNz3cXf7BXqWiX1JIhU6r9crxKhF87OLx6svXpi4ZJF3J0+elMT5Pt7hCrHHYLg9h6msALJBE+a1CCDsuYLFitfrxd/+7d+itbUVGo0Gly5dCmhlHsQw+WTbrtFi6thQQywxdXJrActp8pTZoDBRqlarUVxcjOLi4gDvQYvFgtnZWfT29uLy5cuYnZ3FqVOnkjr3448/jrvuugsPPPAAzp8/j4ceegg33XQThoeHI1pebW5u4h3veAde85rXYG1tLeHzLy0t4etf/zpMJhM++clPYmtrC3fddZfwOcOErlarTfgcROyQACT2JfEKQGarkp2dje7u7qg+aalsAfM8j7W1NaSlpe3Ye5gM8VQA2Z47m80W0WMwVT57q6ur2NraQnt7u7BPKh4++clPYnJyEt///vdRXFyMiooKmM1mrK6uYnx8HDk5OYIY3A0bFLmIHanWkWxMnZyqbnJaCxBZkIbyHszOzsb8/DyeeeYZfO5zn8PPfvYzXH/99bj55pvxV3/1V3Gd+1vf+hbuuOMOvOc97wEA3H///fjd736HBx98EPfee2/Y+73//e/HW9/6VqhUKvzP//xPXOdkjwu4YrVVVFSE97///cjKysIXv/hFbG1t4eMf/7jwObi9vR2QcU6kDhKAhOyI5SIWj0BjbdZ4bFVUKlVSAxXh2NzcxPLyMtLS0nDu3DlJWx2xCkCn04ne3l5kZGSEzBQOPqaUAtDn82FrawsAcO7cuYib2nmOg3V9CfaNdSiVKmhLqpGrKcDHPvYx/OY3v8FvfvMb+Hw+cByHvLw85OXlCYMOLL2B2aCII9QyMjIkezxyIpVVt3hj6uRWAZSTAIzHlkapVKKzsxOdnZ3Q6/W4cOEC8vLy8Lvf/Q6PPvpoXALQ4/Ggp6dnRxLH9ddfj+effz7s/X74wx9iamoKP/7xj/HlL3855vOFwuVyCX/zd999N0pKSvChD30IZrMZn/vc51BUVASXy0UCcJcgAUjsS9RqNdxud8TbcByHkZERrK6uxt1mValUcLlcyS4zANbyZO0zqfe5xCIATSYT+vr6UFFRgaampqgXInEWcLIXdCY8AaCmpiai+PP5vJgxPAXn0hB4nwsKAOYMDX72h5fwq988h//93//F4cOHMTk5uUOgpqWlobS0FKWlpYINitlsxtLSEkZGRgIi1PLz82UjVJIl+DX66le/iq997WsBtykpKcHk5GTS54oWU8fzPFZWVgAAeXl5e/ocy1EAJtKSZhPyN998M97ylrfEfX+TyQS/379jq0dpaSlWV1dD3mdiYgKf+tSncOnSJUk+r7xer7D1xufz4W1vexvKy8vxtre9DSsrK/je974Hn88XNfWIkAYSgIQsidZ6jFYB3N7ehsFgAM/zgqVJPEiZqiEWou3t7bDZbLBarZIcW0ykNfM8j7m5OUxMTKClpQVVVVUxH5PdP5mLuMVigV6vR3l5Odxud9QL8trcKBxzeqhyS6DOupJz++x//xtcIwN44DsPIy8vD2trazCbzRH3+4ltUGpra4X0BjYFrlAoAipXex2hlizBr1FLSwt++ctfCv+dir1woWLqnn/+eeFvkD3H7Hne7ef4ahCAPM/D6XRKIoyC3yPh/rb9fj/e+ta34otf/CIaGxslOafVahWshtgg32te8xo89dRTuPnmm/GmN70JdrtdeC8RqYUEILEviSQAWZWrtLQULS0tCV30pNoDyLwGOY5Dd3c3srKy4HQ6U7K/MJwA9Pv9GBoagtlsRmdnZ1wbrNkHdzIX0eBhDybMg+F5HhzHwefzwbIwCihUUGblCut46rkX0VSowD/9w/+HQeNfHufnPvc5nDhxIqa1BJskb21twWw2Y2FhYUd1MNbK1V4ngTBCXcjVanXchuLJwlrsTU1NyMjIECqw7H2w2zF1chOAiQ6lJOsDWFRUBJVKtaPaZzQaQ75HbDYbXn75Zej1enzgAx8AcGXtPM9DrVbj97//Pa699tqYzs3el29+85tRVlYm/FylUoHneTQ1NeHPf/4zbr75ZgDYt36H+w0SgMS+JJQPIM/zmJ6exvT0dFxVrnDHT1akWa1WGAwGFBYW4tixY8KHvtSZvYxQVVOXywW9Xg8A6Orqins6VlwBjBee54WUFfGwR6h9hTzPw+/3C/ujeK8bvEIN3s/DDx4KJfDZbz0Mr3ES7zx6LWqOngEATE9PR90KEA6FQgGNRgONRoMjR47A7XYL1cGFhQUoFApBDBYUFMSUx7yXhHqNpqam0NjYiIyMDJw+fRqf//znUVtbm/J1iFMfxM+xuAK7WzF1fr9fVrYiiUbTORyOpCqA6enpOH36NC5evIhbb71V+PnFixdxyy237Lh9fn4+BgYGAn72wAMP4E9/+hN++tOfJvQ++o//+I8de3CZONTpdHjqqafwm9/8RrLBOCIy8vmrIAgR0VrAwT6AXq9XSJI4e/Zs0puIkxGAPM9jYWEBY2NjaGxsxKFDh3Z46+1GBXBjYwN6vX6HAI0Htu54BaDX60VfXx+2t7dDDnuIj8cqf6wyolarkVd6GFub84CCg0KhBM8DfpcDnEKF9FydYKUhJRkZGSgvL0d5eXnIfW35+fmCIAyeepUDwRXAjo4OPPTQQ6ivr4fRaMR9992H6667Dn/+858TmryOZx0AQoqcvYipk1sFMJEWsNfrhcfjSdoH8O6778bb3/52dHR0oKurCw8//DDm5+dx4cIFAMCnP/1pLC0t4Uc/+hGUSiVaW1sD7l9SUoLMzMwdP4+VaANYarVaqAISqYcEILEvEQs0lqSRm5uL7u5uSSo1iYo0v9+P4eFhrK+v4/Tp0ygoKAi59lRUAMUCkLXbGhoaUFNTk7BYEbeAY8XpdKKnpwdZWVk4d+7cjtdDXAFklT92kWbnK687Duf6LHymaSgyNYDfB867jazKY9AVVwmvDROOUl/kg/e1uVwumM3mgKlXJgZTZRcUL8EC8Prrrxf+/7Fjx3DmzBmcOHECjz32mNDSS9U6gOjT/NFi6nw+H3Q6ndAuTjSm7moQgHa7HQCSFoC33347zGYz7rnnHqysrKC1tRVPPPEEampqAAArKyuYn59P6hzE/oEEILEvYQKQCR0pkjSCjx+vSGOb3gGgu7s7bDsrVS1gscH08vIyTp06haKioqSOGW8F0Gw2w2AwRJ0yFlf9gsUfAOTk63Dk7M1YmxmAY20aCnUmCisbUX6kFSp1Gnieh9VqxcrKCqqqqoTtAKztKHXofGZmZsDUK0vMmJ6ehtPpRFpaGubn5+NOzJCaTeMc+i7/AKptE7jSNtS/+h3IzrnSNszJycGxY8cwNTWV0jWw93a8z0GsMXWFhYXQarUxiyi5CcBE9gA6HA4A0uyNu/POO3HnnXeG/N0jjzwS8b5f+MIX8IUvfCHpNRDygAQgIUuiXTyUSiU8Hg/GxsYkETrBxNsCZlOlJSUlOHr0aMQLTqoEoN/vh8/ng9lsTmjyORQKhSLmNJCFhQWMjo6iubkZ1dXVEY/JcZzw/AaLP0aupgC5J18J4JU7fre2toahoSHU19cLooyJSvHrplQqhX9SoVQqhanWhoYGTE9PY319HVarFdPT00hLS0NRUZGQmLFbKRSmgd/hhoVvAwB4KKC2/hprYw9j/S0/R3HllT2OY2Nj6OrqSuk6IrWAYyVSTN3Y2FhcMXVyE4CJVAAdDgeys7NllWhC7H9IABL7DqfTif7+/oQtXmIhVgEotleJJnziPXY82Gw24TlJhcF0pAogx3EYGxvD8vJy2LY3gx3HZDIhOzsbxcXFcdmCsCzn2dlZtLW1Cd6O7MLIhCBrK7N/7HEwQSulIEhLS0N2djba2tqExAyz2YyJiQm4XK6AiLpUbW7fNK/huoV/gRIclCIdVMRbYHj8HzB7zT247777YLPZ8Na3vjUla2DE2gKOh3AxdawKGymmTo4CMN5tKkwAym3fKbG/IQFI7CvW19fR39+PkpIS2O32lKU6xCLS/H4/BgcHYbFY4rJXkboCuLa2hv7+flRWVmJ+fl7yicdIAzls2MPlckUV46xCV11dDbVajcXFRWG4oqioCMXFxRGtVziOw/DwsPB8h5qIZBd6sSBkYpCdnz2mVLSKxXsDgStfVphQmZqaQkZGRkJtzGjMXf4pKuALEH8AoFbwaOf60fyu/w8tJ8/gj3/8Y8TMVylgma6pEiuxxtSxYZJEp25Thd/vj3vaOVkLGIIIBQlAQpaEMiudnJzE7Owsjh49ivLyciwtLcHn86XM3JYJhlAXD6fTCb1eD7Vaje7u7riEqFQCkOd5TE1NYWZmBm1tbdBqtZifn5c8hitcC9jhcKC3txfZ2dlRq47iqlx2djbq6+tRX18Pt9sNk8kEk8kkDFewSk9hYaFwTI/Hg76+PnAch7Nnz8b8fIvbv8HVwVS3igHsECpsyIG1McXVwUSHHACAd9vAQwFgp1BXKhT43cWLKCqvSeKRxLGWXY6BixRTNzs7C47jsLS0JEQC7rWdTyJ7AO12O3JycqgCSEgKCUBC9ng8HvT398PpdOLcuXPIy8sTLjKpmsAUV5CCRQEzmi4vL0dzc3PcooEJwGQulD6fDwMDA9ja2hKeE4/HI6xZSlEcqgXMhj0qKyvR1NQU8XFEGvbIyMjYMVxhMpkwNTWFgYEB6HQ65OfnY2VlBfn5+Whra0v4sUWrDqZ6kEQsblmyg3jIISsrK6A6GM+5Nc2vgmr2ezt+zvHAqrIEBaWJe2LGC6sA7hXBMXXPP/880tLSBDufRMy+pSTRPYBUASSkhgQgIWs2Nzeh1+uRn5+Prq4u4du7QqFIyV46BvuAFpvIsv1nU1NTOHr0KCorK5M6dqJCjWXqpqeno6urS9hDJ650SSkAgyuA8/PzGBsbi2q2zQyBow17MMTDFY2NjXA6nZifn8fc3Bx4nofdbsfExASKi4uh0+mSFmfB1UHxv3iqg4mYZCsUCuTk5CAnJweHDh2Cz+eD1WqFyWTC8PAw/H5/QHUwWsvw8LFzeOEPZ3DG+xKUiivr8fMKqBQ85k9+DMeUuzc8wPO8bFqu7D1XXV0NjUYDt9sNs9kMi8UimH3vdkxdIi1ph8ORtAUMQQRDApCQLWyqtK6uDrW1tTvEQ6g0EKlge5iYEGAVt83NTZw5c0YINE+EZIRaJJsV8XGlRNwOHx0dxcrKSkzDHn6/P2AgIN5Ki8ViwdLSEo4ePYrS0lKYzWaYTCYMDQ3B5/OhoKBAqKglmyARqlXMxOBuVAfVajWKi4tRXFwsWKCYTCasrq5ifHxcMEguLCyERqMJeW73X30aTw7+N46bfg0tv4VpdR02Oz+MY+d3pjykkt1uAUdDXMXPyMhARUUFKioqwHHcnsTUUQWQkAskAAlZsrKygomJiYAIsWCC00CkhF3g/X4/HA4H9Ho90tPT0d3dnXSVgF1U4pkGFE8bh6u8JWLaHAsKhQIejwc9PT1wu90xDXuEMneOFZ7nMTExIXgZMqEp9oiz2+0wmUxYXl7G6OgocnNzBTGo0WiSEiDhWsXhbGakzgIWW6Awg2S2p21oaAh+v18QKYWFhcJ+SKUqDVXXfRCZFffCBaDi//7tNnvdAg4m3D7evYqpS9QHkCqAhNSQACRkSVlZGfLz8yNu9k9lC5gd32w2Y3JyElVVVWhsbJSkIsBEUaxCjeM4DA0NwWQyoaOjQ0inCCYez7544Hkeo6OjyM/Pj2vYIxHx5/f7MTAwAIfDgc7OzpBVD4VCgby8POTl5aG2thYej0eoDjIj7sLCQkEQJrvpP9wgCROELpcLHMfB6/WmpDqYlpaG0tJSlJaWCvFpZrMZy8vLGBsbQ25uLgoLC+H1eiUXo4kgpxYwELsNTKiYOrPZLHlMHVUACblAApCQJUqlMuqkZyoFILu4j4+Po62tDeXl5ZIeP9ZJYJfLBb1eDwDo6uqKWoWQ2mLGZDLB6XSipKQEp06dSnjYIxZcLhcMBgPUajXOnDkTs3BLT08PyPDd2trC+vo6ZmdnMTQ0BI1GI4jBZDN8xdVBNoW9urqKtrY2ABDej2K/QSnFkDg+jYlfVrWy2+2YnJzExsaGIFR2Y09bMHKqADLBHu9rEPw8SxlTR3sACblAApCQJbFcQNRqdUr2AHq9XgwMDMDv96O5uVly8QfEJtQ2Njag1+tRWFiIY8eOxVQ1kLIlyYY9srKyUF5eHvY1iXfYIxRbW1swGAwoLCxES0tLwqJJqVRCq9VCq9WioaEBLpcLJpMJ6+vrgmEwE4MFBQUJD8swT0Kr1YozZ84gNzd3T0yoxVUrZjoNXNk/y/a07fbEq5wqgOLnPxmixdRlZWUJYjCav2OiFUCp044IggQgsW9JRQXQbrcL3na5ubl7ZjS9tLSE4eFh1NfX4/DhwzFfuKWoAHIch5GREaytraGjowPj4+NhRaV4XxwTOPGKDKPRiMHBQRw5cgQ1NTWSipTMzExUVVWhqqpK8OEzmUwYGxuD2+2GTqdDcXExioqKYq7i+Hw+9PX1wev1orOzU6jK7rUJNXAlK7a0tBRHjlyJfmPVQTbxysRgKv3w5FYBBJIXgGJCxdRZrVZYLJaAmDr2PIsTPNh7gfYAEnKABCCxb5FaAK6urmJgYAA1NTVoaGjAiy++mJLMXiC8UGNt58XFxYQyjpMVgMxw2ePxoKurC1lZWWH3FYqrXYmIGTbYMj09jdbWVpSUlCS87lgI9uFjk7Zra2vCHi/2+3B7vFhLPiMjAx0dHRH3Q+62CXWwSM/IyNjRGjebzYIfXn5+viAIk22NB6/jahaAwQRPcItj6qampgJi6lh6TbwC0Ol0kgAkJIcEICFLYrmASCUA2dTp3Nwc2traUFZWJunxQxFKqHm9XhgMBiFWLZFN38kIQFb9zM3NxdmzZwVxEyoKLtlhD2Yps76+jo6ODuTn5ye05kQJN2lrMpkwMDAAjuMCBknS09Nhs9mElny8bergvYPi508qm5lIwkvcGq+rq4PL5RKqgyyBRVwdTCZOUG4t4FTG0gUTS0wdACwuLsYlvGkIhEgFJACJfYsUPoDilJGurq6Ab9mpFoDiY4vFV1dXV8IX4EQFIJugra6uRmNjY8BFKXhfYbLiz+v1or+/H16vF2fPnpXMXiMZgidtt7a2YDKZsLCwgKGhIWRnZ8PlcoX0X4yX4L2AyZhQhzp2LGRmZgb44W1ubsJsNmNmZkYYnGGCMN4IMrm1gPdSjAbH1FksFhgMBmxtbQUIb2ZGHa4tb7fbQ2ZfE0QykAAkZEuoypMYtVoNt9ud8PFtNluA6Ar+8E110ggTakajEX19fTh8+DDq6+uTunjGawPD8zzm5+cxPj4eNt2EHVOKYQ+WoZyTk4MTJ04kVWlKFQqFQvCHq6urE/wX8/LysLKyAqPRGDKvOFGkMqFOtPWqVCqh0+mg0+lQX18f0MKcmZlBWlqaIGJ0Ol3Uxyu3CqBc1gJc+aKhVqtx/PjxAOEtbsuL28XsM9DhcET03oyVBx54APfddx9WVlZw7Ngx3H///bjmmmtC3va///u/8eCDD8JgMMDtduPYsWP4whe+gBtuuCHpdRDyQH6fvgQRI8kItJWVFQwODqK2thZ1dXUhL5zBVTopYceemprC9PR0QOs52ePGOgUcPOwRzl+QVRXFU62JtNWsVquQoRxcZZQjPM9jenoa8/PzOHXqFAoLC4W84vX1dUxOTgp5xUwQijf8J0K8JtRi8SjV9HdWVlbA4MzGxobgh+lyuaDVaoUp6lCPlyqA4RGbQIuFN4CQMXUjIyPw+/2w2WxJVwAff/xx3HXXXXjggQdw/vx5PPTQQ7jpppswPDyMQ4cO7bj9M888g+uuuw5f/epXodVq8cMf/hA333wz/vznP+PUqVNJrYWQByQAiX1LIi1g8ZDFiRMnIg4epLICqFAoMD8/L7RBpdoDF2sL2OPxwGAwwOv1CsMekdbKWr7sHPGyvLyMkZERNDU1RcwPlgtMHJvNZnR0dAgXX3FecVNTE5xOJ0wmE0wmEyYmJpCZmYmioqKU5RVHsplJhQm0uIUJXKngBg84sEoosz+R2xCIlLnYyRLJAiZUTF1PTw8effRRrK2t4cKFC3jTm96EG2+8Maoheyi+9a1v4Y477sB73vMeAMD999+P3/3ud3jwwQdx77337rj9/fffH/DfX/3qV/GLX/wCv/rVr0gAXiWQACRkSywt4HgEGhM9bMI12qZqlUoFr9cb8/Fjxel0YmNjA2lpaZJEy4mJRQCy/YZ5eXlob2+PmuyhVCqxuLgIn8+H4uLisFm04e4/NTWFhYUFnDx5Mmysn5zw+Xzo7++H2+3GmTNnIu5RzM7OxqFDh3Do0CH4/f6U5xUDoW1mHA4H3G43eJ5PWSIJgB0DDswcmdmfhKsi7xVyqwDGagLNYuruuusufPjDH0ZBQQHe/e53o6+vD29605tw4cIF3HPPPTGfl0U5fupTnwr4+fXXX4/nn38+pmMwURopA5zYX5AAJPYt8VToNjc3odfrodFooooe8fFdLleyywzAbDbDYDAIFh1SJzVEE4Dr6+vo6+vDoUOH0NDQELFSw6pN9fX1KCgogMlkQl9fH4ArUWvFxcUoLCwMu3Hd7/djaGgIW1tb6Ozs3Bc2FszmJT09HZ2dnXFVWVQq1a7lFQN/qQ5ubm6iv78flZWV0Ol0Afs0xbdj/18qgm11WHVwcXERLpcLL7zwglA9TCY6LRnkKADjrUh6PB74/X689a1vxcc+9jFwHCdME8eKyWSC3+9HaWlpwM9LS0uxuroa0zH++Z//GQ6HA29+85vjOjchX0gAEvuWWAUgM1Wuq6tDbW1tzBdeKVvA4mGL5uZmbG5upqRlF04AMs+9iYkJHDt2DBUVFRHXKh5ESEtLC8hI3dzcxPr6OmZmZjA4OAitViuYKbOqqtvthsFggFKpxJkzZ/Ykkixe7HY79Ho9CgoKkkojASLnFev1eigUioBBkkRNmc1mM/r6+lBXV4eamhrh58Em1FLYzERCoVAgJycHOTk58Pl8cLlcKC4u3hGdxgThbk1+Xw0C0G63A4DwBUqpVCZsCRP82Rdru/6xxx7DF77wBfziF79IuV8nsXuQACRkS7QPpmhRcMxrbmVlZU9MlcXrGB4ehtFoFIYt7HZ7SvYXhlozO//6+jo6Ozuh1WrD3l8s/NjxxK+DQqEIiFrb3t4WotZYJJZGo4HJZBIi7OR0AQ6HxWIRKqNHjhyRfA9buLxiJqITySteWVnB8PAwjh49uiOuMHjvoFQ2M7HA9t2JzZFZdNra2hrGx8eRnZ0tiMF4thTESyK5u6kkkT2Jdrtd8BdMlKKiIqhUqh3VPqPRuKMqGMzjjz+OO+64Az/5yU/w2te+NuE1EPKDBCCxb4lUoWMVKJ/Ph66uroQ+PKWoALrdbuj1enAcFzBskaoJ42AbGI/HA71eD7/fj3PnzkUc9mCtQ1aZjOXCmZWVherqalRXV8Pn82FmZgZzc3NQKpUwmUwYHBwUWsVyrQIyIdXS0hKxMioVUuQVz8/PY3JyEidOnIj6xUYqm5lYCa4qBUeneb1eYe/g0NAQ/H6/YH1SWFgoafyiHCuA8a6HmUAn8zjS09Nx+vRpXLx4Ebfeeqvw84sXL+KWW24Je7/HHnsM7373u/HYY4/hr//6rxM+PyFPSAAS+xYm0IIvOBsbG0Irr7W1NeEpwGQFINt3qNPpdqxDqVSmZMBEPA3KfA7z8/PR1tYWddgjGXNnnuexvLyMhYUFtLa2orS0VKhyzc3NCebC4lbxXk+K8jwvCNa9HFCJJ684MzMTk5OTWFpawunTp6HRaOI6V6hBEqmrg9F8ANPS0sLulRwbG0NOTo4gBvPz85MSPnIUgInkACdrLwQAd999N97+9rejo6MDXV1dePjhhzE/P48LFy4AAD796U9jaWkJP/rRjwBcEX/veMc78C//8i84d+6cUD1kVX5i/0MCkJAt0T7w2Aep3+8XxM3CwgJGR0fR0NCAmpqapD40kxGAy8vLGBoaQn19PQ4fPrxjHamqALIWsNFoRH9/P2pqaqKaS4srf4nGuo2NjcFoNKK9vV1oMTMz5fr6+oAq19TUFDIyMiS1S4kXtj3AZDIF2LzsNdHyipnNSnNzsyRrDmczw/aBJlIdjKfNGbxX0uv1CjYzAwMD4Hk+oDoYbxX5ahGAUsTA3X777TCbzbjnnnuwsrKC1tZWPPHEE8Le0ZWVFczPzwu3f+ihh+Dz+fAP//AP+Id/+Afh53//93+PRx55JOn1EHsPCUBi38JEH2ursH127e3tklRzEhFpPM9jfHxcsD0pLi4OeTtxEoiUKBQKbGxsCJW44L1hwYirP4nGug0MDAiWKeFazMFVLovFgvX1dcEuhU0Vs9zdVBKPzcteIm6dVldXw2AwwOl0QqPRYGJiAmNjYzvyipMhGRNqMckkgQQPHG1tbQmTxSMjI8jLyxMeM0vKiITcBCDHcXG/Tna7XbKK+Z133ok777wz5O+CRd1TTz2V9PkIeUMCkNi3MMHidDoxOjoKnuejmhrHQ7wizev1oq+vD9vb21F9BqUaMBHDcRzMZjMcDgfOnj0bsU0TbdgjFra3t6HX65GZmRmXZUrwgIDNZsP6+joWFhaEOCwmBmMdiIgVticzLS0NHR0dCU/f7iZer1eYHD537hzS0tJC5hXn5+cLVdVYxFE04jGhFucbS5UEIo7kO3LkiDBJzayUFAqFkKMbbpJabgIwmT2ABCE1JAAJ2RLLRUSpVKK3txclJSU4evSopK7/8bSAmblyTk6OcJGOhNQCkA17eDwewaw5HIkMewSzsbGBvr4+lJaWorGxMeGLrEKhQH5+PvLz81FXVwe32x1yIIK1ipN5fZnNi06nw9GjR2UlDMLhcrnQ29uL7OxstLW1CY8/OK+YPW8mkwlzc3MBrWSp8oqB0CbU7MsEW1cqKttA6Elqs9mM+fl5jIyMID8/X2gVsy8O+ykJJBwkAIlUQQKQ2JcwXz2/34/q6mo0NTVJPlQQqwBk++1iMVeO99ixwIY9mJWIzWYLe1tx5S+Rqh8ArK6uYnh4GPX19SEzRJMhIyMDlZWVqKysFAYi1tfXMTIyAq/Xi4KCAqE6GM+0KLN5qa6uDpv9LDfYl4qioiI0NzdHFKzi5y1aXrEUYiJcddDlcsFms0Gj0cDj8aTMhFo8Sc0EMKsOMgFcWFiI7e1tyWIWpSBRAbgfTNSJ/QcJQGLfwRImzGazkL2aigs623Afro3E8zymp6cxPT0d0347MVJVAI1GI/r6+lBbW4u6ujrMzc2FNZiWYtJ3enoa8/PzOH78eNy+ivESPBDBpkWXlpaE/WCxtDyZzct+ySEGrlRYDQYDqqqq4hase5FXDFypQvf390Or1Qp2OrthQg3szNHd3NyE2WyG0WjExsYGtra2hOrgXk6gJ1KRJAFIpAoSgIRsCfUhzfadKZVKdHV1obe3NyXTtEBguyv4guXz+TA4OIiNjQ2cPXs27ipDsgKQ53nMzs5icnISbW1tKCsri3jcZIc9/H4/hoeHsbGxsSdTs6GSNVireG5uDmq1WhA1zDuPPUczMzMx+eXJhfX1dQwMDKChoQHV1dVJH2838oodDgd6enpQUlISUI3fbRNqdlydTgedToft7W3k5OQgIyMDZrMZMzMzSEtLE8SgTqdLuj0eD7QHkJATJACJfQPb/F1WViZEdUnZSg2GfVCLbWaAKyK0t7cXarUaXV1dCRnXJmMDw3EcBgcHYTabcebMmYD9fsECkNl5sHMlIv48Hg8MBgMA4MyZM5Ia9SZKenp6QMWHtYqZd15BQQF8Ph8cDgc6Ojpk1QaMxPLyMkZGRgQvRalJRV7x1tYWent7Q1Yrd9uEOhiO43ZsK2DVwampKWxvb0Or1QqCUAq/vUgk2gKWi00RcXVBApCQPeJqV0tLS0AbL1ocXDKwC5JYqFksFuj1+gARmgiJ2sCwKVY28RxcsRELwOBhDzapGQ92ux0GgwH5+fk4duyYrDbUM5RKpXABZ9Oxg4ODcLlcQgweqw7m5+fLcv8fy2qemZnBqVOnUFBQkPJzSpFXbLVaYTAYUFtbi8OHD0c8n1Q2M/EQXL1XqVRCe7yhoQFOpxMWiwVms1kYOhJXB6V+vycqAOPZXkIQsUICkJA14lZrqBzbVFYAg48/Pz+PsbExNDU1JT38kEgL2GazoaenB1qtNmAiNNRxpRj2MJvN6O/v31eDEx6PByMjI8jIyMCZM2fA8zzMZjPW19fR29sLpVIpiMHCwkJZCFrmHbm6uorTp0/vWbUy3rxi9v5obGxMaG9lKkyog4lmA5OdnY3s7OyAFBaz2Yzx8XF4PJ4d1cFkSXQPILWAiVRAApCQLV6vFy+88ALS0tLCtlp3QwB6vV4MDQ1hbW0Np0+flqQ6E28LeG1tDf39/cKwRzgxxgRgMsMewJVElfHx8V3Lx5UCh8OB3t5eaLVaHDt2TLjwi0UNm46dmJgQpmPZVLFU/pHxwHEchoaGsLm5ic7OTklEhhREyytmfxc1NTWSVKdirQ6K/QZjEYPx+AAGDx05nU6hIjo5OYmsrCxBDGq12oSqk4nsAXQ6nSQAiZRAApCQLWlpaaitrUV5eXnYD02VSpWyFjBw5YIzPDwsDJ1IbTIdnGMcDMurnZqaChj2iITL5cLq6iqKiorirjawatTKygra29uh0+niuv9ewVqRkaqVwdOxDocD6+vrQsxaTk6OIAZj3f+WDCyRxOPxoLOzUxZ7K8MhTnJhXw6KiopgNBqxsLAguZBO1IQ6mESNoBUKBXJycpCTk4NDhw7B5/MJ1UGxJREzoo7lMbPHQVPAhFwgAUjIFoVCgaqqqrC2JsCVPYBerzcl59/c3ITb7UZWVhY6OjokbReyi1IkAcjsbiwWS9RJY9Y2y8vLQ0VFBaanpzE0NCT45hUXF0ed8PT5fBgYGMD29jbOnDkjm2pUNFZXVzE0NBS3zQu7wB8+fFjIoF1fXw/Y/8ZaxVJPijLjbrVajY6Ojl2dRE2G+fl5TE1NCfsUQ+UVZ2dnC5W0RCtlYuIxoQ5uFSdScQuFWq0OSK9xOBwwm81YW1vD+Pg4srOzheqgRqMRzrm8vIzPfe5zuHjxIlwuF0pLS/Hv//7v6OjoiPncJACJVLE/PnUIIgwqlQoul0vy466srGBwcBDp6ek4dOiQ5HvFIlnMAFeGPXp7ewEA586diyjexHun1Go1Ghoa0NjYKFS4VldXMTY2htzcXOEiFuyb53K5oNfrkZ6ejs7Ozn0RkcYGJ6anp3H8+PGwucuxIM6gZT5yJpMJU1NTO1rFyQpjNkWel5eH1tbWfZFIwjwgFxYW0N7eLkyei/OKmZC2WCwwmUwYGBgAx3GS5hUDkauDwYMkqYiCEz/mmpoa+Hw+YZBkaGgIfr8fBQUFUKvV+Ju/+Ru84hWvwM9+9jNoNBr8+te/jquqzlrR1AImUgEJQELWKBSKiBVAqfcAshbowsICTpw4gdnZ2ZREW4WzmAH+Yquh0+nQ2toaUXxGMncWV7hC+eYxMahSqdDf34/i4uKoiRNyged5jI2NYW1tTXKbF7GPHJsUZc8dq/aIW8XxPF8staW0tDQl6TWpQDyk0tHREbEalZaWhtLSUpSWlu7IK2Y5z4WFhZLmFQOhq4MOhwNerxc8z8Pr9abMhFqtVu+w1jGbzbj33nuRl5eHd73rXdDpdMjJycHJkydRV1cX1/HtdjvZwBApgQQgsa+R0gbG6/Wiv78fDocD586dQ25uLhYWFlIyZCI2yhWzurqKgYEBHDlyBEeOHIm6PzDWYY9wvnmDg4Pwer3Izc2FRqOBz+eTpEqTSvx+PwYGBuB0OnHmzJmUD2+IjZR9Pp/QKu7r6wMAQdCEs0phsH2KNTU1qK2t3Tfib3h4GFarNe4hld3OKwb+Uh202+0YGBjAoUOHkJubG+CFKb5dKqqDzFqnt7cXr371q/HNb34Tf/7zn6HT6XDjjTcK75XCwsKY/taoBUykChKAxL5Gqgqg3W6HXq9HVlYWurq6hAu5VJFtwbBKBFu7OFbu+PHjUU2Ak0n2YMMQW1tb8Pv9aGxshM/nw8LCAkZGRqDRaITqoNxaT263GwaDAUqlck9a1Wq1OqDCtbm5GWCVotVqheqg+LkzGo0YHBxM2DJlL+A4DgMDA4KZdqIpIYzdyitmdknV1dXCl6i9MKGenZ3FD3/4Q3zgAx/AZz/7WVy6dAlf+MIXUFFRge7ubsF4m4nBUB6VbL8hCUAiFZAAJPY1UghAVs2prq5GY2NjwIdwKm1m2CSw3+/H4OAgrFZrzMMeySR7cByHkZERmM1mdHZ2Cuerq6uDy+XC+vq6cGHOysoSxKBWq93TqpXD4YBer0d+fr4s9s4pFIoAq5Tt7W2hVTwxMYGsrCwhfm5xcRFtbW0oKSnZ0zXHit/vR19fH7xeLzo6OiSvCseSV8yEdDx5xWz7BKuyis8H7L4J9alTp/D5z38eAFBVVYU///nP+MUvfoEPfehDgvG22WzG4uIiFAqFMFnMqsnMzFwKAfjAAw/gvvvuw8rKCo4dO4b7778f11xzTdjbP/3007j77rsxNDSEiooKfOITn8CFCxeSXgchH0gAErImmuBIxgZGbLFy7NixkH53qY6ac7lcGBoagkKhiBorJ65gAIkle3g8HvT398Pn8+HMmTM7qjqZmZmorq5GdXV1yHZnKidjI7GxsQGDwYDKykrU19fLsn2alZW147mbmZmBzWaDSqXC6uoq/H5/zK2/vcLr9QrRf6dPn96V11mKvOKNjQ3o9XocOXIENTU1Ec8nlc2MGJ/Pi+XJfjiMs1Co03Ci9sqeWgbHcTh8+DBefPFFADuNt202G0wmE+bn5zEyMoKf/OQnwvsk2cGjxx9/HHfddRceeOABnD9/Hg899BBuuukmDA8PhzS1n5mZwete9zq8973vxY9//GM899xzuPPOO1FcXIzbbrstqbUQ8kHBR9phTxB7jM/niyjANjc30dPTg2uvvTau44qrbqdOnQrI0xUzMjICAGhpaYnr+LHw5JNPgud5FBUVRY1ZE1+gEm1VORwOGAwG5OTkhE0SiXR+1rJbX1/H9vZ2XBYzybC2toahoSE0NDSguro6ZeeREvGQyqlTp8DzPNbX12EymWC324U2O2t3ykXQejwe9Pb2IiMjA8ePH9/zpBRxXvH6+jq2trZC5hWz/ZV1dXVJp/QE28yIoxTDtYrdLidGL/470lZ6oOB8UACYHB3GHxfS8O2fvQDgyv7ez3zmM5ifn8cf/vCHiGtwu934j//4D/z0pz/FCy+8gNLSUtx000143etehxtuuCHuoaezZ8+ivb0dDz74oPCzlpYWvPGNb8S999674/af/OQn8ctf/lL4/AOACxcuoK+vD5cvX47r3IR8oQogsa9JpEK3vb0NvV4vmDtHqrqpVCp4PJ5kl7mD1dVVuN1uVFZWorW1VbJhj3BYLBb09fWhqqoqoQqaQqEQJmPjtZhJFJ7nBd+5tra2pGxedhOO4zA4OAibzRYwpKLRaFBfXx+QqjE1NYWMjAyhshpPu1NqXC4Xent7kZubK4sWOxBbXnFeXh6sVisaGhqSFn9AfDYz7HZz/c8gfenP8ORUAhlX2rXFNV60rz2Jb3/ls3jDW96NP/zhD/j1r3+N7373u1HXkJGRgfe97304f/48rrvuOjz22GP47W9/i3vuuQc6nQ6vfe1rY348Ho8HPT09+NSnPhXw8+uvvx7PP/98yPtcvnwZ119/fcDPbrjhBvzgBz+A1+vdFzZRRHRIABKyJpYWMNvLE4vosFqt0Ov1KCkpwdGjR6Ne5Ng+PangeR5TU1OYmZlBVlYWSkpKUi7+lpaWMDo6iubmZlRWViazfIFIFjNpaWmCoCkoKEhISIgraKdPnw5boZUbPp8PfX198Pl86OzsDNnqFadq+P1+WCwWrK+vC+1ONlUslW9eLDidTvT09KCwsBAtLS2yqUgGE9w2XVhYwMTEBNLT0zExMQGj0Si896SorEYzoWbbTxwzLyFNlQ4+PQfsjBnlR3H0uBU/fPZXOHf/w6ioqMCHP/xh3H777TGf3263Izc3F6961avw6le/Gl//+tcj2mKFwmQywe/37xgsKy0txerqasj7rK6uhry9z+eDyWSSJP6P2HtIABL7GrY/KZSfXjALCwsYHR1FU1MTqqurY7o4SLkHkNmXbGxs4Ny5cxgaGgorLlnrKdFJX3aMyclJLC4uCskNqSDYYoYJmuHh4YQEDWvP2+32XbF5kQq32y2Yace6d06lUgUkTNhsNqyvrwf45rHnLjc3NyXCjHkTlpeXo6GhQbbiLxiz2Szs3y0vL9+RV5yeni60igsKCiRpZwdXB4X9gj4XOIXqLy3j/9s3mK0rwQc+fQHf+6tbMTMzg+3t7bjO53A4dkxEJ/r6hJowjnSsULdP5vyE/CABSOxr2Id6JAHIcRxGR0exsrKC06dPxyWEpBKArL0mbjuLbWDEBA97JCL+mIhibcjdsnNRKpXCRbe5uVkQNPPz8xgeHo5qMePxeGAwGKBQKMJW0OSI0+lEb28vtFptTJXlUCgUCuTn5yM/Pz/ANy9Y0LBWsRSCZnNzM2Bqdr9c3I1GIwYGBtDa2ipUqoIrq1arFSaTCWNjY3C73QGDJFLnFadXtEE19iu4eA688v9eF/cWOIUaOYVXBlv8fn9COcDJVjJZJnhwtc9oNIa1myorKwt5e7VajcLCwoTXQsgLEoCErIn2wcfEUTiRxjJXfT4furu74/7gl0IAsotsYWFhwN6qUO1lcawbgISEhMvlgsFggEqlwpkzZ/ZMRAULmmCLGZaoUVxcDI1GA6fTKdi8RBuKkRNbW1vQ6/UoKyvbYSOUDGLfPCZo1tfXMTIyAo/HE1BZjbSPNRwWiwUGgwH19fWS7J3bLdbW1jA4OBjRVkdsMr0becU1p16D6ZVBZG1OwKvOhZL3QcF54ak4i7LDR+H3++FyuZCWlgafzxezzUyoCmC8sIr0xYsXceuttwo/v3jxIm655ZaQ9+nq6sKvfvWrgJ/9/ve/R0dHB+3/u4ogAUjse9RqdUiRxjzBtFptwnYWyRpBs0zh+vp6HD58OEAcBB9biv1+NpsNer1e2Mslh438jHAWMwaDQXjsRUVFaGlp2Tfijw3X1NbW4vDhwyk7T7CgYZOxS0tLGBkZQV5enlAdjGUIhxlTNzc3h7Q/kisrKysYGRmJK/s5XF7x+vq6ZHnFmsIyHHndh7HQ9yT8K0Pwq7OQW9uBxpOvhFqdjoWFBZjNZhw/fjwuE2q73S5J9f7uu+/G29/+dnR0dKCrqwsPP/ww5ufnBV+/T3/601haWsKPfvQjAFcmfr/3ve/h7rvvxnvf+15cvnwZP/jBD/DYY48lvRZCPpAAJPY9obwA44lUi3bsRCqAbP/d7OwsTpw4EbJSEZwEwip/iYo/dkFjYkTO7Txxogar6Gi1WjgcDjzzzDPQ6XS7YjGTDKurqxgaGkJLS8uuiqhQk7HBOc/iIZxgMb2ysoLh4eF9ZUwNAMvLyxgdHcWJEyeSakPGklfMxGA8E+2awjJorv27HT9fXFzE1NQU2tvbodVq4zKhlioF5Pbbb4fZbMY999yDlZUVtLa24oknnhD8EldWVjA/Py/cvra2Fk888QQ+8pGP4F//9V9RUVGB73znO+QBeJVBPoCErOF5PqoNy6VLl9DS0iJURyYmJjA/P4/jx48nfYGzWCwYGBjAK1/5ypjvw4Y9Njc30d7eHjbIfXBwEBkZGairq0t62IPZpRw7dixqjJycmJ+fx+TkJFpbW4XXilnMrK+vY3NzU7CYKSkpSdkgRLyw6VO52dOIc55NJpOw9421illKSbIiardZXFzE+Pg4Tp48mbJhJgABecVmsznpvGK27lOnTkGn0+34fbDNjPhyrFQq8bWvfQ1LS0v48Y9/nPRjI4hgqAJI7HtYlY5ZcDgcDpw7d06Sb87xVgDZsIdKpUJXV1fEdhLbu5hsrNvo6CjW19f3lV0Kz/MYHx8XBnPE645mMcMqg3vhmcdsfBYXF4WKjpxQKpVClJh47xtrnQJARUUF1Gp1zNZJew37crMbz7eUecVLS0sRxR8Q2WaG4zj85je/2dXEHeJgQe8sYt+jUqngcDgwPj6OrKwsdHV1SbZROdykbihYFBVL9ogkTlir12g0IiMjAyUlJXG3Or1eL/r7++HxePaVXUqwzUukmCuxxYx4EIJ55rFWZ1FRUco3pzOxbTab0dHRIckXjFTC9r7l5OTA6/XC4XCgpqZGsH1hE9usVSxHoTE3N4fp6Wm0t7fv+pebZPKKl5eXMTY2hpMnT4YVf+HOyfYGf/KTn4TJZKLqH5EyqAVMyB632x3x95cvX4bNZkNNTY2kU5jAFXuPS5cu4frrr4943EjDHsGwvT/b29tYW1sTWp15eXkoKSmJycTW6XTCYDAgKysLbW1tsrx4h4LZvADAyZMnE55QFnvmra+vw263Q6vVBsSrSQlr6zudTrS3t8t2X2IwPM9jdHQUJpMJ7e3twvMirm6ZTCa4XC5h36VUNinJMjMzg7m5ObS3t8cdfZZqfD4fLBaLIAjFecUcx2FycjLhNjvHcfinf/on/Nd//ReeeuopNDQ0pOAREAQJQGIfEE4A8jyP2dlZjI+Po7S0FCdPnkzJuZ988klcf/31ISt6bNhjbm4OJ06ciLofLNykr8fjEcSM2WwWqoLFxcXQarUBYnBjYwMGgwHl5eWSC95UwmxeWNSYlJO+YosZi8Wyw2ImmefI6/UKk8qnTp3aNzYYHMdhaGgIW1tbaG9vjyjqWKt4fX0dGxsbyMnJEaqDyT5/8cLzPKanp7GwsIDTp0+H3UMrF8RT2cvLy3A6ncjKykJZWVlAXnGsx/rSl76ERx55BE8++WRKMsgJgkECkJA9Ho9nR/yR3+/H0NAQzGaz4DWXim/KPp8Pf/jDH/Ca17xmx4Xf5/NhYGAAW1tbOH36dNSWoDg5INJ+P7/fL1ikrK+vA4AwBOHxeDA6OorGxkZUV1dL8yB3gc3NTej1+l0RrWKLGZPJBACCGIy31elyuaDX65GZmYnjx4/vG3saVrHc3t5Ge3t7XD6BXq834PlTKBSCGExkECIe2Beq5eXlmP6m5ASbCj927Bh4nheqg+z5Y4Mk4b5A8DyPr3/963jwwQfxpz/9CW1tbbv8CIiDBglAQvYEC0BxqsapU6cwPT0NhUKB5uZmyc/NcRx+//vf41WvelVA2297ext6vR4qlQqnTp2K2Mpk8VBsL6Hi/2KiYj3/5uYmjEYjlpeX4fP5oNFoUFVVtatZscnAPOf2wnCYPX9MTLtcroCp2EitXIfDgd7eXhQUFMjOUzESPp8PBoMBHMclXbFkzx+rDjqdzoBWcaT9m/HCBoNY/vNupddIAbMyOnHiBIqKioSfi58/k8kEh8MBjUazI6+Y53l8+9vfxre//W388Y9/TEk3gyCCIQFIyB6xALRardDr9SgpKREit8bHx+H1enHs2LGUnP93v/sdrrnmGuFit7Gxgd7e3oA1hEOKZA9W7dzY2EBTUxMcDgeMRmPAvreSkhJZ7NsKhtm8yMWeJthiJi8vT6gOii1mWMWysrIS9fX1+6bN7vV6hS8mJ06ckLxaxwYh1tfXYbVahUQN1ipOVCTzPI+xsTFhml1KYZlqmPiLxZx6e3tbEIMWiwU/+9nP4HA4kJaWhieeeAIXL15EZ2fnLq2cOOiQACRkj9frBcdxWFxcxMjICBobG3Ho0CHhojw1NQWHw4Hjx4+n5Px/+MMfcPbsWeTl5WF5eRlDQ0NoaGhATU1NTMMefr8/YXNnt9uNvr4+ADuHJti+N6PRCKvVipycHGHfYDwGtqmA+TEuLy/j5MmTsrNLARBgMWM2mwWLmfT0dMzMzKChoWFfRaS53W709vYiOzsbbW1tKa9Yhmq1s3i6SK3OYHiex8jICCwWC06fPi3LLzLhYJnEiZhq+/1+/OY3v8HXv/516PV6pKWl4bWvfS3++q//Gm984xv3VUILsT/ZH6ODxIGG4zgMDw9jZWUF7e3tOybrQiWBSAk7/vj4OObn53Hy5MmEhz3iwW63Q6/XQ6vV4ujRozv2n4mj1bxer2z88ljFcmtrC52dnbJt5YWymJmbm8PCwgKUSiU2NjaQlpa2KxYzybK9vY2enh7hvbIbr7c4zYXneaHVOTMzIyS7iFudoeB5HsPDw9jY2EBHR8e+ma4G/pK8k2iiilKpFCxlnnzySRQXF+OJJ57AT37yE+Tl5eHtb397ClZNEH+BKoCE7HnhhRfgcDjQ3t4esjW0uLiIlZWVlLVOnn76aWRkZMDj8aC9vV2yYY9ImEwmDAwM4NChQ3FH2XEcB4vFAqPRiPX1dXAch6KiIpSUlKR8E794YjYZm5e9YG5uDlNTUzh+/DjS09NDWswUFxfLrj1pt9uFLQlNTU2yaFezViebys7KyhLEoFarFbzuhoaGYLPZ9pW1DnBF/PX396O1tTWhrQ08z+PRRx/FRz/6Ufzyl7/Eq1/96hSskiAiQwKQkD0mkwlZWVlhhcvKygrm5uZw7tw5yc+9vb2NS5cuITs7G2fOnEnZsIcYFjPW0tKC8vLyhNfO1rS1tSWIQafTiYKCAqFVHM90aDS2t7fR29uLnJwctLW17ZuJWTZ5urS0hFOnTu0wHA4WM1JazCTL1tYWent7UVVVhbq6OlmIv2CYZx5rFXMch4KCArhcLvj9fpw+fVrS92GqMZlM6OvrS0r8/eQnP8EHPvAB/OxnP8MNN9yQglUSRHRIABKyx+fzRUzjMBqNGB8fx1/91V9Jel42cAIgqhgLHvZIRPxxHIfx8XGsrq6mbN8cG4IwGo3Y2tpCfn6+MESSTKt2c3MTBoMBpaWlsqlCxQLbXmC1WgOMksMRyWKmsLBwV0Wv1WqFwWBAbW0tDh8+vGvnTQbWKh4aGoLL5QLHcTtaxXJ+75hMJvT39+Po0aMoKytL6Bg///nP8b73vQ+PP/44Xv/610u8QoKIHdoDSOx71Gp1XHm9sbC0tITh4WE0NjZidXUVHMeFvS0b9kim5evz+dDf3w+Xy4WzZ8+mbCO8OGfX7XYLbc7p6WlkZmYKlcF4KltsL1RdXV3AcI7c8fv9wnN+5syZmKpQ4n1vYouZ8fFxuN3umC1mkoUJkcbGRlRVVaXsPFLDcRxmZmagVqvxile8An6/X6iuTk9PIyMjQxCDe5H1HAmz2Yz+/n60tLQkLP5+/etf433vex9+/OMfk/gj9hyqABKyJ1oFcHNzEz09Pbj22muTPhfzIltYWMDJkydRVFSEnp4eFBcXh5wIlWLYY3t7GwaDARkZGWhra9uTgQNxZWt9fR1KpTLAPDlcZYu1q+Vi8xIrLJJOqVTixIkTST/nPM/D6XTGZDGTLMx25NixYwkLkb3A7/fDYDDA7/eH9Cf0+/0BrWKfzydMFe+156XFYoHBYEhqW8Zvf/tbvP3tb8cPf/hDvPnNb5Z4hQQRP1QBJGRPtAunSqWSpALo8/nQ19cHh8OBc+fOCcMe4Y4vxbAHa52yDfx7VfEIrmxtbGzAaDRidHQUXq8XhYWFKCkpESZixfvm2tvbZWnzEg5m4p2TkyNZJJ1CoQiorootZmZmZpCeni7JVPbS0hLGxsZi8pyTE8ycmud5tLe3h9zPq1KphOdInPW8sLCA4eFhYbtCUVGRpII6Gkz8NTc3Jyz+/vSnP+Ed73gHHnroIfzt3/6txCskiMSgCiAhe/x+f0SbF5fLhaeeego33HBDwhcFp9OJ3t5eZGRk4MSJEwHVhv7+fuTk5KCurg6AdMMeq6urGB4eRn19Paqrq2XZOmU5p2yIhE3E+nw+eDyefZfYwCZmi4qK0NLSsivPeXBly+/3B1S2Yq0+zs3NYXp6GidOnEBBQUGKVy0dPp8Per0eSqUSJ0+eTEhwu93uAM/G9PT0gFZxqvZesn3ATU1NqKysTOgYzzzzDP72b/8W3/nOd/DOd75Tln/nxMGEBCAhe6IJQK/Xiz/+8Y947Wtfm5DFCfuQLysrQ3Nz847qzNDQENLS0tDY2BjQ8mXCL94PdJ7nMTMzg9nZWbS1te2rSo7NZkNfXx88Hg84jkNubq4wRLKbVZlE2NjYgF6vT8haRyrYVDYTg7FYzPA8j+npaSwsLIScUpYzLJlErVbjxIkTkgg15tnInkOPxxMgqKWaKJZC/F2+fBm33norvvGNb+D973+/rP8+iIMHtYAJ2RNLCxi4cmGIVwCydJGmpqawqQ+sBRws/hJp44mnTjs7O5GXlxf3MfaK7e1tDAwMIDc3F21tbeA4DiaTCUajUTCfZkMkzOtNLrBBlYaGBlRXV+/ZOhQKBTQaDTQaDerr6wMsZiYmJnZYzAAQJsM7OjqielDKCa/Xi56eHmRkZOD48eOSVelUKhWKiopQVFQkVKhNJhOWlpYwMjKCvLw8oTqYaCIO+7LQ2NiYsPh76aWXcNttt+ErX/kKiT9CllAFkJA9HMfB6/VGvE1wXm80WPbo0tISTp48uSNdRMzExATcbjeam5uT2u/n8XjQ19cHjuNw8uTJfeV9trW1Bb1eH9bmRdzmXF9fB8/zwkW4qKhoTz0Bl5aWMDo6mrBv224RPIijUCiQlpYGn8+H9vb2ffVlwePxoKenZ9di6cTnFbeK1Wq18D6MNMwkhok/tjUjEfR6PV7/+tfjH//xH3H33XeT+CNkCQlAQvbEIgD/+Mc/orOzE/n5+VGPx4Y9nE5nTN5vU1NTMJlMOHbsGDIzMxP6MHc4HNDr9cjLy5Ns8GC3YNWzI0eORM0/Bv7i9cb8Bl0uV4D59G5Nc/I8j9nZWczOzu7bfXN2ux1qtRoej0ewmJHawFtq3G43enp6kJubi9bW1j2rBHMcF9AqjsWmZ3NzE729vUmJv4GBAbzuda/Dxz72MXzqU58i8UfIFhKAhOzheR4ejyfibZ566imcOHECOp0u4u3Ewx4nT56MuAGfDXtsbm5iZGQENpsNWq0WJSUlKCkpidnnjfmHVVVVob6+fl9dEBYXFzE2NpaU5YjD4RCGSLa2tqDRaAQhk6oBEmbns7q6uu+qZ36/H319ffB6vYJdCjPwZs9hqixmksXlcqGnpwcajWbXMoljged5OBwOoTq4ubmJ3NxcoTqYn58vpKowP8tEGB4exk033YR/+Id/wOc//3nZvC4EEQoSgITsiUUAXrp0CS0tLSgqKgp7G4vFAr1ej/Ly8pDDHsHnZBYvwJW9W263G0ajEUajERsbG8jLyxPEYDghwwRUS0sLKioqYni08oDneUxNTQl+iNGEdaww82mj0RgQq1ZSUoL8/HxJLpgsY3ZzczNsfrRcYVnKCoUCJ0+eDLmn1ePxCGKQTcRKYTGTLNvb2+jp6YFOp8PRo0dlLX48Ho/QbjebzVAoFPD5fCgvL0dTU1NCw2RjY2O46aab8O53vxtf+cpXZP34CQIgAUjsA2IRgM8//zyOHDkStkoVy7CH+HziWLdQF1R2EWZCJisrK0DIAFf2Di4vL+P48eP7qv3IBNTGxgZOnTqVssEDtufNaDTCZDJBqVQKbeKCgoKEhAxr73u9XrS3t++peXC8eDweoTod69BE8N5LjuMSsphJlu3tbbz88ssoKipCc3PzvhI/zEg+Ly8PHo8H29vbAa3iWFJ5pqamcOONN+Itb3kL7rvvPtlUPgkiEiQAiX2B2+2O+PsXX3wRlZWVOyb24hn2YLePN9kjWMioVCoolUpwHIf29vZ9N7nZ19cHn8+HU6dO7dpeM/F+LaPRCJ/PFzBEEouQ8Xg8AZYjiVRx9grWOmV7RBMREGKLmfX1dTgcjqgWM1LgcDjQ09OD0tJSNDY27ivxZ7PZ0NPTg5qaGtTW1gJAQKt4Y2MDOTk5wnsxVETi7OwsbrrpJrzhDW/Av/zLv5D4I/YNJACJfUE0ARgqro2Jme3t7ZiGPb7//e/j29/+NlZXV9HS0oJvfOMbOH/+fFzrZHsMxRVEVhmMdQpxr2AJGVlZWWhra9szAcVSINi+QYfDAZ1OJ1QHQ+293N7eRm9vb1ICaq9wOBzo7e1FYWGhpObU29vbghi0Wq07LGakOI/D4cDLL7+M8vJyNDQ07CvxZ7fb8fLLLweIv2C8Xq/QKjaZTFAoFCgqKsLm5iZaWlrgdDpxww034IYbbsADDzywr953BEECkNgXeDweRHqrGgwGaDQa4YPc6XSip6cHWVlZUbNeeZ7HT37yE9xxxx341re+ha6uLvz7v/87/uM//gM9PT0xTwNubW3BYDAEXMhZpNr6+rpgWCuOVJMLzOZlryPpQiHO2GV7L5mozsnJEdI9wlnUyBmbzYbe3t6UC6hgIaNUKoWqVmFhYUJfTOx2O3p6elBZWYm6urp99bwz8cdMwWOB4zhsbm7CZDLhwx/+MJ599lmkpaXh+PHj+PGPf4yGhoaUrfeZZ57Bfffdh56eHqysrODnP/853vjGN0a8z9NPP427774bQ0NDqKiowCc+8QlcuHAhZWsk9h8kAIl9QTQBODg4iIyMDDQ0NMBsNsNgMKCioiKqmGHDHq985Stx4sQJ/Mu//ItwIWtvb8frX/963HPPPVHXZzQaMTg4GNYqRRypZjQa4XA4AqxR9tLWw2Qyob+/H7W1tTh8+LCsL+TM581oNMJsNiMtLQ0ejwcVFRVRB3vkBvObYxWo3XreWdYzE9Vie5RY34usdRqPgJILTLhWVVUJ8Y7xsra2hmuvvRY6nQ6FhYV4+umnUV9fj29961u48cYbJV4x8Jvf/AbPPfcc2tvbcdttt0UVgDMzM2htbcV73/tevP/978dzzz2HO++8E4899hhuu+02yddH7E9IABL7gmgCcGRkBAqFAjk5ORgdHUVzc3PUyh3b7+d2u1FSUoIf//jHeMMb3iD8/mMf+xj+/+3deViU9fo/8PcM+yL7Jiq4YSCbLGZobmUaosyopZWlZpoe01L7pnkqK7VOaaWdijTLLc1MBtSsVAzFtVJglEVBBERkGXYYYPbn94e/5zkgoDDMwIzcr+s613V6mOUzIzrv+Sz3nZaWhuPHj9/3MdgerQEBAXBzc2vX62loaODCIFsahT1R3J5N57rCFkkeOnSo1o3uu0txcTEyMzNhZ2eH+vp6AOBCjLazWl2loqICV65cweDBg7UuOaILbHmUpiVm7OzsmpXpuTeYsrXy+vfv3+bSqaFil6w7M2tZXl6OyZMnw9/fH/v27YOpqSnq6uqQkJCAgIAADBkyRA8j/x8ej/fAALh69WocOXIE165d464tXrwYV65cwcWLF/U6PmI8jGeXNOnReDzefQMgn89HWVkZ7ty5g7CwsAeeum162KOyshJqtbpFeHN3d8fJkyfbfAyNRoNr166hvLwc4eHh7SpCzbK2tkb//v3Rv39/rrwM2w7MxsaGC4P6qvHWtMxLSEiIUZ1SBu6e6s7OzkZgYCDc3NzAMAw3q5WdnQ25XN5sud2QTgOzs8W+vr7dXhqIx+PB1tYWtra2GDBgAORyOXcAIjc3FxYWFlwYdHBw4LYKsDPdxoQNf56enlqHv8rKSkRHR8PHxwd79+7l9sn26tUL06dP1/WQtXbx4kVMnDix2bVJkybhhx9+gFKpNKjtJ6T7UAAkRk+pVKK0tBQKhQIjR4584GlHhmFQV1OJakkhrHo5gse7u2zY2rJtWx8STU/Ljhgxot1FoVtjYWGBfv36oV+/flAqldwSZ35+PiwsLLgwqKuN+/f2IzamU8oMwyA3NxcFBQUIDQ2Fg4MDgLt/do6OjnB0dISPjw9XfPr27dvIzMzkZlj1eRq2PdhZSza4GhoLCwvuNH3TEjNpaWncF6bevXt3e3DtKHZPsKenp9bF2GtqaiAUCtG3b1/8/PPPBh2iSkpKWrQ9dHd3h0qlQnl5udHN9hP9oABIjBp7gpLH48HBweGBH+4qlRJXT+yB2Y0/YKGqhZRvjjqXYXCyNkFpaWmz20okklY/pBsaGpCamgobG5s2i/Vqy8zMDL1790bv3r2hVqu58jJscWA2DGpb8FepVOLq1atQKpV49NFHDbql2L0YhsH169dRVlZ23+DadFZr4MCBkMlk3BInO8PKHiLp1atXl+29u337Nm7cuNGuckSGwMTEhJv9Y/fVOjk5oba2FklJSXB0dOR+3pXbFjqqoaEBly9fhoeHh9bhr66uDtOmTYOzszNiY2ON4u9Na19oW7tOei4KgMQotPaPFvuh1KdPH9jY2KCkpKTN+7OHPdITf4Zdxl6oTCwgM3eEiUoGt5IkfDC5N/7882SzPYCnTp1CVFRUs8epqqrClStX4OnpqfeyFyYmJlzga1onLyMjA2q1Gi4uLtwSZ3v2u8lkMqSmpsLCwgLh4eFGVSdPrVYjPT0dUqkUw4cP71DgsLS0bDbDyobqy5cvw9TUlJsZ1GcXjby8POTn5zebtTQW7CGhpt1smpaYyc7O5kI121bNUEIG253E3d1d67+v9fX1eOaZZ2BtbY34+PhOzfZ3FQ8Pjxb/HkokEpiamhrFlw/SNYznE4CQJgoKCrgWa3379kVxcTHUanWrt2X3+ynkjeBl/wEN3wyNVneXQNSm1tAozfDYoEZ8v+dH7A4Nw4gRI7Bjxw7cvn0bCxYs4B6nqKiI6ybSt2/fLnmdLD6fD2dnZzg7O+ORRx5BbW0tJBIJcnJykJ6ezu13c3V1bXVpqq6uDqmpqVynBmM6Lcsut2s0GgwfPrxT+/nMzMzg4eEBDw8Pbv/nvaGaLT6ti4DMMAxycnJQVFSE8PBwo+pJDABlZWW4evVqi0NCVlZW8PLygpeXV7MSMykpKeDz+VwY7M7al2x3EldXV60LVDc0NGDmzJng8Xg4cuSI0bQVjIiIwK+//trs2okTJxAeHm7QS9eka9EpYGIUVCoVtwfp+vXrKC4ubnZ4oaysDFlZWXj88ceb3Y+d+VOr1aitLEXZT4ugMrGCyrzJgQ2NBvYNefhTHoxNe46jpKQEQ4cOxaefforHH3+82YGJoKAgg/oGzZ7iZE8US6XSFkWTKyoqcPXqVe7QiaHMzrSHXC7n2qMFBwfrLUw07aIhkUjQ0NDQ6TI97JJ1eXl5uwqRGxqJRIK0tDQEBAS02E/WltZKzDRtTddVS6dNw5+2tSFlMhlmzZoFqVSK48ePd+iQl65JpVLk5OQAAEJCQvDFF19g/PjxcHJygpeXF9asWYM7d+5gz549AP5XBmbRokVYuHAhLl68iMWLF1MZGNIMBUBiFNRqNRobGyEWiyGXyxEaGtrs23hlZSXS0tIwduxY7tq9bd0U8gbk/LAAFqpaNFj9bzaDr6yHtaIS/Enr0H/oiBbPm56ejrq6OgwbNszgD0ywS3MSiQTV1dWwsLCAXC7H4MGD0b9//+4eXoewXVUcHBwwdOjQLp21ZMv0lJWVoaam5oGlUe7F9lOura1FaGioQe+Ra01JSQkyMzM7VNroXtqUmNEFmUyGy5cvw9nZWeu+xHK5HC+++CIkEglOnDgBR0dHnY+zI06fPo3x48e3uD537lzs2rUL8+bNQ35+Pk6fPs39LCkpCStWrOAKQa9evZoKQZNmKAASo1BTU4N//vkHNjY2rfZ5ZRu6P/HEEwDufgCz/2va0/fqHz/A/to+yEztoDCzh4laBlt5KSodAhE4dzNMmjyuXC6HWCwGn89HcHCwQZUSeRCGYXDjxg3cvn0bvXr1Qm1tLaytrbk9hV15+EEbtbW1SElJ6ZK9lg+iUCi4UF1ZWQlLS0vuEElrJ7PVajWuXr0KmUyG0NBQozgw0FRxcTGuXbuGoKAguLi46Oxxm5aYqaioaFFiRhcBnw1/Tk5OWrfVUyqVmDNnDm7duoU///zToGb8CdElCoDEKNy6dQs1NTVt7uWRSqW4ePEiJkyYwM38AXcPjzS9vVIhR/pvMbC+nQRztRRqvjnq7H3hNXkFnN3+Vzi6rq4OYrEYjo6OXT771FlsfcKKigqEhobC1taWK/8gkUhQXl4OMzOzZocfDCkMskWSBw4caHCzlk1PZrO9YZvud2MYBmKxGBqNBiEhIUa33+rOnTvIyspCcHCwXoNP0xIzZWVl0Gg0zVrTafO+yWQyJCcnczPG2vxOq1QqzJ8/H9evX8epU6fg6ura4ccgxFhQACRGQa1WQ6VStflzmUyG06dP48knn+Su3Rv+mqoqK0J1SR4sbB3R29sXvCYBj617xnY6MKRw9CAqlQpXrlyBQqFASEhIqycWNRoNt2lfIpEAADej1Z2b9oG7S48ZGRlG0Zmk6X43iUQChUIBPp8PCwsLhIaGGsVp0aaalqnpysLgTfdflpWVob6+vsMlZuRyOS5fvtyp8KdWq7Fo0SKIxWIkJibCw8NDm5dDiNGgAEiMgkajgVKpbPPnCoUCiYmJCA4OhouLi1YzdgzD4Pbt28jJycHQoUON7gOgaZmXoKCgdp1iZTtosIdIlEpls/IyXVkqpqCgADk5OTpfeuwK7NIjn88Hn8+HVCqFg4MDN8tq6HsACwoKcPPmTYSEhHR7mZqmJWaqqqoeWGJGLpcjOTkZdnZ28Pf31zr8LVu2DBcuXMCpU6fQp08fXb0cQgwWBUBiFO4XABmGgUqlwo0bN1BSUgKGYbi9bk5OTu0KgxqNBllZWZBIJBg2bBjs7e11/RL0ii3z4uzsDD8/P60DcF1dHXf4ob6+njvB6ebmprc9kOwp68LCQoSEhBjde8/Wmmt6WOXeEGNra8u9j/pq76et/Px85OXlITQ01ODe+6YlZsrLy1uUmFGr1bh8+TJ69eqFgIAArd5XjUaDFStW4M8//8Tp06e7tTczIV2JAiAxCm0FwHsPewB3izWzM1pqtZr74HV2dm51eVOpVCItLQ1yuRzDhg0z+Nmae7FlXry9vXW6ZM2e4JRIJKitreXaqbm5uensPWL3K1ZWVhplqRSpVIqUlBS4ubm1WW6Ebe/HhhgzMzPud1JXhx+01bStXneWOWmP1krM8Hg82NjYICgoSKvfSY1Gg9WrV+Po0aM4deoUBg4cqIeRE2KYKAASo8AwDBQKRbP/vt9hD/Y2NTU1XBhUKBRwcXGBu7s7nJ2dYWpqisbGRqSmpsLS0rLdy6aGhC1O3bRLgz6w7dQkEgk3o8WGQW3LeajVaqSlpaGxsbHN/YqGjD2p3LdvXwwaNKhd74Farea+oLCHH9gZLfZ3siuwPZVv376NsLAwoytQLZfLcenSJZiYmIDP56Ourk6rUj3vvvsuYmNjcerUKfj4+HTR6AkxDBQAiVFoGgDZ4Ne0t+WD/rFvurwpkUjQ2NgIOzs71NXVwcPDw+i6YzAMg7y8PNy6davLi1MrlUpuFqa8vByWlpbcXrfWyqK09RhisRgAMGzYMKM7LVtVVQWxWIwBAwZofVKZ/YLCvpeNjY1wcnLiQoy+ysc07U4SFhZm8LUt76VUKpGcnAwrKysEBgaCz+d3uMQMwzBYt24ddu/ejdOnT8PX17ebXg0h3YcCIDEKbAC8t7iztsudeXl5uHnzJszNzaFQKODk5AR3d3e4uroafL0/thtKeXk5QkJCunX2pmlZlLKyMpiYmHDLm2311pXJZEhJSYG1tTUCAwO79dSxNtjeuEOGDNFpS8B7l9zt7Oy4YK2rpXGGYZCdnY3S0lKEhYUZ3ZJ7a+HvXm2VmLGysoKDgwOcnZ3xySefYOvWrTh16hQCAgK64ZUQ0v0oABKjIZPJOh3+2KWvgoICBAYGwsXFhev6wH7wOjg4cGHQ0JYlVSoVrl69CrlcbnDLphqNptn+S3Z5s+n+y/r6eqSkpHBdGoxp1hUASktLkZ6eDn9/f72eEpfL5VyAqayshJWVFfdetnYStj0YhkFWVhbKysoQFhZmNH1tWWz4Y7drtOd3p2mJmZ9//hmbNm2Ch4cHKisrcfDgQUyePFnv446JicGmTZtQXFwMf39/bNmyBaNHj27z9vv27cPGjRtx48YN2Nvb4+mnn8Znn31GBamJzlEAJEbhr7/+wuXLlxEVFQVXV1etgoNarUZmZiaqq6sREhLS6tKXTCaDRCJBaWkp1wLM3d1dpwcftCWTySAWi2FmZoagoCCDXja9d/+lXC6Hvb09amtr0adPnzYLehsytkhyYGBglxYIVqlU3EnYsrIy7iRsR065MwzDHbYJCwvr9t/ljlIqlUhJSYG5uTmCg4O1PuW+du1axMTEIDAwEKmpqfDz88Pzzz+PNWvW6GHUwIEDB/DSSy8hJiYGo0aNwrZt2/D9998jMzOz1dPG586dw9ixY7F582ZMnToVd+7cweLFi+Hj44P4+Hi9jJH0XBQAiVH4448/sHbtWojFYowcORJCoRDR0dHw8PBoV5BQKBTcnrPg4OB27a9iZ2FKS0u5gw9sGOzqpTOpVIrU1FSj7EzCMAwKCwuRlZXFLbk7Ojpyy5uGNIvZllu3biE3NxfBwcFdWiT5XuxJWHbJna3b6OrqChcXl1a/FDAMg4yMDNTU1CAsLMwo3u+mVCoVUlJSYGZm1qnw99133+HDDz/EH3/8gYiICFRXV+PYsWMoKSnB8uXLdT9wACNGjEBoaCi+/fZb7pqfnx+EQiH+85//tLj9Z599hm+//RY3b97krn311VfYuHEjbt++rZcxkp6LAiAxGgzD4NatWxCJRIiLi8Pff/+NESNGQCAQQCAQoG/fvm22iROLxVyhWG32nLEHH0pLS1FRUQEbGxvuFKy+67pVVlbiypUr8PLywsCBA41u5qyoqAjXr1/nims3NjZyM4PsLCv7XhrasmTT07KGVqOQPdjE7htkO2g0DdYajQYZGRmoq6tDWFiY0fUlZsOfqakpgoODtfq7yzAMdu3ahTVr1uDo0aMYM2aMHkbakkKhgLW1NQ4ePIhp06Zx19944w2IxWIkJSW1uM+FCxcwfvx4xMfHIzIyEhKJBDNnzoSfnx+2bt3aJeMmPQcFQGKUGIbBnTt3EBcXB5FIhPPnzyM0NBRCoRACgQD9+/cHj8fD8ePHwTAMBg8e3O5SHQ/C9tUtLS1tdgq2M/uz2lJcXIzMzEz4+voaZXcCtshwWyeVFQoFFwYrKyu5rg/u7u7dXjCZ3TPHHpgw9NOybPFpiUSC6upq2NracjUyhw8fbpThLzU1FXw+H8OGDdM6/O3btw9vvvkmjhw5gvHjx+thpK0rKipCnz59cP78eYwcOZK7/vHHH2P37t3Iyspq9X6xsbF4+eWXIZPJoFKpEB0djdjYWIPe8kGMEwVAYvQYhkFJSQkOHToEkUiEpKQkBAQEwMXFBWfOnMGOHTuafQPXJfYULBsGTU1N4ebmBnd393aXRGkNwzDIz89Hfn5+l5d50QWGYXDjxg0UFxcjJCSkXUWG2WAtkUi4gslssHZwcOjSMMgWqK6qqkJoaKjBzUw+iFwuR2pqKhobG6HRaB5YFsXQqNVqpKSkdDr8HTx4EEuXLoVIJMKkSZP0MNK2sQHwwoULiIiI4K5/9NFH+PHHH3H9+vUW98nMzMSECROwYsUKTJo0CcXFxXjrrbcwfPhw/PDDD105fNIDUAAkDxWGYSCRSPDiiy8iKSkJDMPA19cX0dHRmDZtGvz8/PQWJDQaTbOSKDwejwuDHfnQNaQyL9rQaDTcYRttwxNbyqPpe9nRgw/a0mg0SEtLQ319PUJDQ41uz5xarcaVK1egVCoRGhoKPp/PvZfl5eVgGKZZ8WlDK8OjVquRmpoKAAgJCdF6fPHx8Vi0aBEOHDiAqKgoXQ6xXbRZAn7ppZcgk8lw8OBB7tq5c+cwevRoFBUVoXfv3l0ydtIzGFfbA0IeoLGxEQsWLEBhYSEyMzPh7OyMI0eOIC4uDl988QW8vLwgEAgwbdq0NuuIaatpn9KmJVHS0tK4D122JEpbz6tSqZCWlgaZTIZHH33UaMOHQqHo1LIjW0+QfS/Zgw/Xrl3jDj64ubnBxcVFp90zmoan8PBwg68JeS+1Wg2xWAy1Wo3Q0FBu2ZB9L5uezs7OzoZcLuf6PRtCDUx2/EDnwt/Ro0fx6quvYt++fd0S/gDA3NwcYWFhSEhIaBYAExISIBAIWr1PQ0NDi99n9j2guRqiazQDSB4qarUa69evxxtvvAFHR8dmP6utrcXRo0cRFxeHY8eOwc3NjQuD7EyJPjAMwwUYiUQClUrVrCUd+w88u2xnDGVeWqNQKJCamgoTExMMGzZML23NWuvo4uTkxB186EyAYbuT8Hg8vY1fn1QqFcRiMRiGQUhIyAPHzzBMs+LTdXV1XL9nV1fXLl/2ZsOfRqNp1/jbcuzYMcyZMwc7d+7Es88+q+NRdgxbBmbr1q2IiIjAd999h+3btyMjIwPe3t5Ys2YN7ty5gz179gAAdu3ahYULF+K///0vtwS8fPly8Pl8/P333936WsjDhwIg6ZHq6+vxxx9/QCQS4bfffoOjoyOio6MhEAgwYsQIvS2LsYVp2VqDcrkcLi4usLe3R0FBAZycnIyuzAtwd+Y1JSUFtra2Op9ZvZ/6+nouDNbV1cHBwYELMB2pdadQKJCSkgILCwsEBQUZ3LLog+jiwATb75ktPs0eyHF1ddX54aZ7sTOvarW6U+EvMTERzz33HLZt24YXXnjBIE7Mx8TEYOPGjSguLkZAQAA2b97MnUSeN28e8vPzcfr0ae72X331FbZu3Yq8vDw4ODjgiSeewKeffmqUh8CIYaMASHq8xsZGnDhxAiKRCEePHoWlpSWio6MhFAoxcuRIvc0EMQwDqVSKW7duobi4GDweD87OzlwXEmOZAZRKpUhJSYGrqyt8fX277UOXLeJdVlbG1W1sWqrnfvdLTk5Gr169EBAQYHThmy2SzNbJ00V4ZQ/ksP2e29PiT1sajQZisRgqlQqhoaFa/307c+YMnn32WXz11VeYO3euQYQ/QgwZBUBCmlAoFDh58iREIhGOHDkCHo+HKVOmYNq0aRgzZozOQ1lJSQkyMjLwyCOPwNHRkZsZlEql3NKmm5tbt+/NaktVVRXEYjG8vb0xYMAAg/nQVSgU3IniioqKNkv1NG1Np88DQvrSdOZS2yLJD9J0P2tZWRnUanWz4tOd+YKk0Wi4PaNN9yx21IULFzB9+nRs2rQJr776qtH9ORLSHSgAEtIGpVKJpKQkxMbG4tChQ1AqlYiKioJQKMT48eM7VVeNLWqdm5uLoKAguLi4NPs5Wyy5tLSU60/MBhhDORgikUiQnp6OIUOGoG/fvt09nDap1epm5WVMTEy4WcGcnBx4enrCx8fH6EKDQqFAcnIyrK2tu2zZvWlv3bKyMtTX18PJyYlbKu7I76auwt+lS5cgEAiwYcMGvPbaa0b350hId6EASEg7qNVqnD17FiKRCPHx8ZBKpYiMjIRQKMSECRM6tN9Mo9EgKysLEomkXTXy2L1ZpaWlqK6u5jpnuLu7d1tPV7YvbkBAANzc3LplDNrQaDSorKxEYWEh11eXbe9niCVR2iKXy5GcnAxbW9tuXbZuaGjgDpHU1NSgV69e3B5MGxubNsOYRqPB1atXIZPJEBYWpnX4S01NxZQpU/Dee+9hxYoVFP4I6QAKgIR0kFqtxl9//cWFwfLyckyaNAlCoRATJ068734ztVqNq1evorGxESEhIR0OcPd2zmjvPjddaVqgetiwYS1OWhuDiooKXLlyBYMHD4adnR33fioUCjg7O3PlZQx1Dya7Z9He3h7+/v4GE3ruXXa3sLDgfjebFkVn6yw2NjZ2KvylpaVh8uTJeOutt7B69WqDeR8IMRYUAAnpBI1Gg+TkZMTGxiI+Ph6FhYV46qmnIBAIMHny5Gaze/X19UhPT4eJiQmCg4M7HTDY/sTsB66VlRU3M6iPNmpNW6OFhoYaXYFqAFxdRj8/P3h6enLX2QM5bBhklzbZ2SxDaaPW2NiI5ORkODk5GfSeRbZDDrtUDIDbM1hcXMyFP233tmZmZiIyMhJLly7F2rVrDfZ9IMSQUQAkREfYZS02DN68eRNPPvkkoqOj0b9/fyxYsACffPIJBAKBzpfs7m2jZm5uzoVBXZTw0Gg0SE9PR11dHUJDQ7tt6bkzioqKcO3aNQQGBj5w2bqhoYE79FBTU8Mtu7u5uXVbW7iGhgYkJyfDxcWlW09bd5RGo+GKT9+5c4c7ROLu7g4XF5cOh8CsrCxERkbilVdewYYNG4zmfSDE0FAAJEQPGIbBtWvXEBsbiz179uDmzZvo06cPVq1aBYFAABcXF719cLGzL2yAYQ89sC3pOvq8KpUKV65cgUqlQkhIiMGeSL6f27dv48aNGwgODu5wX2W5XM7NtLL18Zouu3dFAKmvr0dycjLc3d0xZMgQows9Go0GGRkZqK2txdChQ7lTxVKptEO1G3NychAZGYnnn38eGzduNLqSPYQYEgqAhOjRwYMH8fLLL2P16tUwNTVFXFwcxGIxRo0aBaFQiOjoaLi7u+u1PzHbB1YikXA9dd3d3dtVz40tM2Jubo6goCCj647RdM9iSEgIHBwcOvV4SqWy2T43dqb13n1uuiSVSpGcnAxPT08MHjzY6MIfwzDc7HFYWFiz5XT2gJNEIkFVVRUXrl1dXdGrV69mrzU/Px9PP/00hEIhtmzZQuGPkE6iAEiInpSXlyMoKAjbt2/n+pGygUQkEiEuLg7//PMPHnvsMQgEAggEAvTp00evYbBpSzqNRnPf/sQNDQ1ISUnhDhsY2wcuwzDIyclBUVGRXvYs3rvPjQ3Xbm5ucHJy0sn7VVdXh+TkZPTr1w8DBw40yvDHzvzdG/7uxYZrtvi0mZkZCgoKuJPO0dHRmDRpEmJiYozud5EQQ0QBkBA9amhoaHPPGMMwKCwsRFxcHOLi4nD+/HmEhYVBKBRCIBDA29tbbx/4DMNw+7JKS0uhVCq58OLi4sKFPw8PD6NccmSX4CsqKhAaGgobGxu9Pt+94Zrd58aGa21mTmtra5GSkgIvLy8MHDhQD6PWL4ZhkJmZierqaoSHh3foIA07c/3VV19h+/btqK2txcCBA/Hxxx8jMjKySw4gxcTEYNOmTSguLoa/vz+2bNmC0aNHt3l7uVyOdevWYe/evSgpKUHfvn3xzjvvYP78+XofKyHaoABIiAFgGAYlJSWIj4+HSCTCmTNnEBgYCIFAAKFQqNelP4ZhUFdXx4XBxsZGAICbmxv8/PwMthxKW5ruN+uOAytN+z1LJBLIZLJm5WXas4eypqYGKSkpGDBgAPr376//QesYG/6qqqoQHh6udfHy0tJSPP300/D29kZoaCiOHDmC3NxcrFq1CuvWrdPxqP/nwIEDeOmllxATE4NRo0Zh27Zt+P7775GZmQkvL69W7yMQCFBaWooNGzZg8ODBkEgkUKlUGDlypN7GSUhnUAAkxMAwDIPy8nIcPnwYIpEIiYmJeOSRR7j+xPos/8G2pnN2dkZjYyPq6+u58OLq6mrwB0DYOosymQyhoaEGUb5FKpVy+9zq6uoe2NWluroaqampGDRoUJthw5Cxs6+VlZWdCn/l5eWYPHky/P39sW/fPm4WNTs7G/X19QgJCdHlsJsZMWIEQkND8e2333LX/Pz8IBQK8Z///KfF7Y8dO4bnnnsOubm5cHJy0tu4CNElCoCEGDCGYVBdXY0jR45AJBIhISEB3t7eEAgEmDZtmk67QLAnZQMDA+Hq6grg7hJ2aWkpF14cHR258GII4aoplUoFsVgMjUaDkJAQg5y5bGxs5MJgdXU11znDzc0NNjY2qKqqQmpqKnx8fNCvX7/uHm6HMQyD69evo6KiolPhr7KyElOmTMGAAQPwyy+/dOmfpUKhgLW1NQ4ePIhp06Zx19944w2IxWIkJSW1uM+SJUuQnZ2N8PBw/Pjjj7CxsUF0dDTWr19vlCWTSM9gXEf6COlheDweHB0dMXfuXMydOxe1tbU4evQoRCIRnnzySXh4eHDLxKGhoVqFQYZhkJubi4KCAoSGhjY7KWttbY0BAwZgwIABXH/ikpISZGVlwd7engsv3f0hp1AokJqaClNTU4SFhRlsSzcrKyt4eXnBy8sLCoWCC4O5ubkwNzeHXC5H//79Dbq3clvYQuHl5eWdCn/V1dUQCATo27cvDhw40OVBvry8HGq1Gu7u7s2uu7u7o6SkpNX75Obm4ty5c7C0tOS6Ay1ZsgSVlZXYsWNHVwybkA6jGUBCjJRUKsUff/wBkUiE33//HY6Ojtwy8aOPPtquEMQu15WXlyM0NLTd7eTkcjm3x62qqoqbyXJ3d+/yQskymQwpKSmwsbFBYGCgUZ4QLS0tRXp6Onr16oX6+nqYmppyh3IcHBwM/jWx4a+srAzh4eFafyGora2FUCiEvb09Dh8+rHWI7IyioiL06dMHFy5cQEREBHf9o48+wo8//ojr16+3uM/EiRNx9uxZlJSUwN7eHgAQFxeHZ555BvX19d3+BYmQ1tAMICFGytbWFs8++yyeffZZNDY24vjx49yHjrW1NaKjoyEQCDBy5MhWT6Gq1Wqkp6ejvr4ejz76aIc+bC0sLNCvXz/069ev2UzWzZs3uVpu7u7usLGx0esJYrY1moODA4YOHWrwQak1ZWVlSE9Ph7+/Pzw8PJrVbkxLSwPDMM3Kyxja7CbDMMjOzkZZWRnCwsK0DjtSqZT73T106FC3hD8AcHFxgYmJSYvZPolE0mJWkNW7d2/06dOHC3/A3T2D7El/Hx+fDo2BYRijO3lPjA/NABLykJHJZPjzzz8RFxeHw4cPw8TEBFOmTMG0adMwevRomJmZoaysDL/99huGDh2q0/1yTQsll5eXw9LSEu7u7nBzc2tR2LezpFIpUlJS4ObmhkceecQoPzDZmb+AgIBWwwW7B5SdbVUqlXBxcYGrqytcXV27vTA3wzC4ceMGSkpKEB4ervXsb0NDA5555hkwDIPffvut3TPR+jJixAiEhYUhJiaGuzZ06FAIBIJWD4F89913WL58OSQSCTf2w4cPY/r06ZBKpe0OxadOncL48eN18yIIeQAKgIQ8xJRKJZKSkhAbG4tDhw5BqVRi3LhxuHDhAvz8/LiAqA9qtZoLg2VlZTAzM+PCYGe7ZrA18vr27YtBgwYZZfgrKSlBZmZms0M398MwDKRSKRcG6+vr4eTkxJ3Q7upDOWyh7eLiYoSFhWlda1Emk2HWrFmor6/HsWPHYGdnp+ORdhxbBmbr1q2IiIjAd999h+3btyMjIwPe3t5Ys2YN7ty5gz179gC4+2XEz88Pjz32GD788EOUl5djwYIFGDt2LLZv396u5ywuLkb//v0xadIkHDlyBADNBBL9ogBIDE5HC7AmJSVh5cqVyMjIgKenJ1atWoXFixd34YiNg0qlwv79+/Haa69BqVTC3NwcUVFREAqFePLJJ/W6T0mtVjdrScf2J9Zmj1tVVRXEYrHR1sgD7u4zu379OoKCguDi4qLVYzQ0NHDvZ21tbZceymEYBjdv3sSdO3cQHh6udfiTy+WYPXs2ysvLceLEiU636tOlmJgYbNy4EcXFxQgICMDmzZsxZswYAMC8efOQn5+P06dPc7e/fv06li1bhvPnz8PZ2RkzZ87Ehg0b2v1nwTAMTp48iXnz5iE8PByHDx/mrlMIJPpAAZAYlI4WYM3Ly0NAQAAWLlyIRYsW4fz581iyZAn279+PGTNmdMMrMFyXLl3C5MmTMX/+fHz00Uf4+++/uZnB8vJyPP300xAIBJg0aZJeO2doNBpUVVWhtLQUZWVlYBiGCy4PaqFWVlaGtLQ0DBkyxChPygLAnTt3kJWVheDgYDg7O+vkMdlDOWVlZaisrIStrS23b9DW1lbnASInJ6fT4U+pVGLOnDkoKCjAn3/+SfXz/r+kpCQ8//zzCA4Oxh9//AGAQiDRDwqAxKB0tADr6tWrceTIEVy7do27tnjxYly5cgUXL17skjEbi4SEBKSnp2PFihXNrms0Gly+fBmxsbGIj49HUVERnnrqKQgEAkRGRup1SY7d48bWGlSr1c36EzddnmaLVLOHJYwRW2sxJCQEjo6OenmOe/dhWlhYcAG7s0vvAHDz5k0UFhYiLCxM6716KpUK8+fPR1ZWFhITE9u1BN5TaDQaXLhwAbNmzcLQoUNx4sQJ8Hg8CoFE5ygAEoOhTQHWMWPGICQkBF9++SV3LT4+HjNnzkRDQ4NBFgM2ZBqNBleuXIFIJEJcXBxyc3MxYcIEREdHIyoqCg4ODnptSVdbW8uFQYVCwfXTVSgUyMnJafd+OUNUUFCAmzdvIiQkpMuWOtVqNSoqKrjZQT6fz4VBR0fHDp+aZutFhoeHax3+1Go1Fi1aBLFYjFOnTrV5sranUKvVMDExAftRzP79+uuvv/Dss89i0KBBOHnyJExNTSkEEp2iMjDEYGhTgLWkpKTV26tUKpSXl6N37956G+/DiM/nIyQkBCEhIVi/fj0yMzMRGxuLb775BkuXLsW4ceMgFAoxZcoUODs76/TDiMfjwd7eHvb29vDx8YFUKkVpaSmysrKgUCjg4OAApVIJpVJpdME+Pz8feXl5CA0NbVYqRN+a7rVkl94lEgkyMjK42VZXV1eu9Mn95OXloaCgoFMzf2q1GsuWLcPly5dx+vRpCn//P/zl5eVh69atuHLlCsaNG4fw8HBMmDAB8fHxeO655zB27FgkJibCwsKCQiDRGeMrmkUeevf+4/agf/Bau31r10nH8Hg8+Pv74/3334dYLEZ6ejrGjRuHHTt2YNCgQZgyZQq2b9+OkpIS6HohgcfjcSGDYRgEBgbC2dkZBQUFSEpKQkpKCgoLC6FQKHT6vPqQm5uL/Px8hIWFdWn4uxefz4ezszP8/PwwevRorldyTk4OTp8+DbFYjKKiIiiVyhb3zc/Px61btxAWFoZevXpp9fwajQYrVqzA2bNncfLkSXh6enb2JRk1hmFgYmKCW7du4bHHHkNRURGCg4ORnJyMF154AZcuXUJ4eDgOHDiA6upqDBs2DA0NDfTvGtEZmgEkBkObAqweHh6t3t7U1FRnG+zJ3UA2ZMgQ/Pvf/8aaNWuQl5cHkUiEAwcO4M0330RERAQEAgGio6PRp0+fTn9IsZ0lJBJJs+XGgQMHcqdf2ZO0Dg4OcHd3h6ura7cVD25N05OynQlO+tB0tnXw4MGor6+HRCJBQUEBMjMzuZ7Prq6uKCkpQV5eXqfD36pVq5CQkIDTp0+3eqCrp+HxeFAqlVi1ahWmTp2K77//HgAQFBSEiIgI+Pn5AQDCwsKwd+9ezJ49G9evX0doaGh3Dps8RGgPIDEoHS3Aunr1avz666/IzMzkrv3rX/+CWCymQyBdgGEY3L59G3FxcYiPj8f58+cRHh4OgUAAgUAAb2/vDodBjUaDzMxMVFdXP7CzhEwm40qhVFdXw87Ojqs12J3tt9gaeUVFRZ1aMu0ObM9n9j0FwHV90ebEr0ajwbvvvovY2FicOnWqw10xHmZqtRrjx4/Hm2++CYFAgNGjR4PH4+HXX3+Fvb09zp49CxcXF/j5+aG+vl6vp/NJz0MBkBiUjhZgZcvALFq0CAsXLsTFixexePFiKgPTDRiGQXFxMeLj4xEXF4czZ84gKCiIC4ODBw9+YBjUaDRIS0tDfX09QkNDOzSjp1AouODClkJhw2BXfnCyrdFKS0s7VSC5uxUUFCAnJwdeXl6oq6tDRUUFrK2tuT2F7enswjAM1q1bhz179uDUqVPw9fXtotEbLnZLi0ajQV1dHaZPn47ly5dj27ZtqKysxNGjR+Hk5ITKykqsW7cOjz76KJ5//nla+iU6RwGQGJyOFmBNSkrCihUruELQq1evpkLQ3YxhGJSXl+PQoUMQiURITEyEr68vBAIBhEIhfH19W3ygqdVqiMViqFQqhISEwNzcXOvnVyqVKCsrQ2lpKSorK2FlZcWFQX3UxWMxDIPr16+jvLwc4eHh3ToLydq0aRM++OADLFmyBJs2bWrXfW7fvo2cnJxmh1bYg1VseRkzM7Nmxbxb24v7ySefYNu2bUhMTERAQIDOX5uxYBgGGo2m1YM2K1euxJYtWzB06FD8/fff3BeGvXv34r333sNPP/2EiIiIrh4y6QEoABJC9IphGFRVVeHIkSMQiURISEjAgAEDIBAIMG3aNPj7+6OiogKffvopZs2ahZCQEJ32uGWDS2lpKVcXjw2DdnZ2OguDDMMgMzMTVVVVD1y67irJycl46aWX0KtXL4wZM6ZdAZANf/crV6PRaJqVlwEAV1dXWFlZwcPDA1ZWVti8eTM2b96MxMREBAcH6/JlGQ2pVNps+V8mk+Gbb76Bqakp7O3tMW/ePADA/Pnz8csvv+Dbb78FwzCorKzE22+/je+++w5z5szpptGThx0FQEJIl6qpqcHRo0cRFxeHY8eOwdXVFbW1tejXrx9Onjyp1yVTti4eGwZNTU3vO4vVXgzDICMjAzU1NQgLCzOIwyhSqRSjRo3C5s2bsXHjRgQGBj4wABYWFiI7OxuhoaHtrlXIFvOWSCT49ttvsXfvXvTr1w937tzB0aNHMW7cuM6/mHbqaBtJ1vnz5zF27FgEBARALBbrZCxlZWWYP38+BAIBFixYAAAYPHgwrK2toVQqUV1djf79+0MkEsHR0RFvvfUWTpw4AaVSCV9fX7z44ouYPXu2TsZCSGsoABJyHx35QImLi8O3334LsVgMuVwOf39/fPDBB5g0aVIXj9p4XLt2DU8++SRMTExQXV0NZ2dnREdHQygUYvjw4Q+sTdcZ985i8Xg8rYokazQapKenQyqVIiwsDBYWFnobc0csXLgQjo6O2LhxI55++ukHBkC2RV1nupSo1WqsWbMG27dvR9++fVFYWIgJEybg2Wef5Wa79KWjbSRZNTU1CA0NxeDBg1FaWqqzAJiRkYHVq1ejrq4OL7/8Mvh8Pg4fPoyff/4ZdXV1KCws5N6TlJQUAHf3XbJbFPTVKYYQFtUBJKQNBw4cwPLly/HOO+8gNTUVo0ePRmRkJAoKClq9/ZkzZ/DUU0/h999/R3JyMsaPH4+pU6ciNTW1i0duHG7evIlJkyYhOjoa+fn5KC0txZYtW1BVVYUZM2bAz88Pb775Js6ePQuVSqXz5+fz+XB1dYW/vz/GjBmDwMBAAEB6ejrOnDmDjIwMlJWVQaPRtPkYTQ+thIeHG0z4O3jwIMRiMdatW9eu2xcVFSErKwvDhg3TOngwDIM9e/Zgz549OHnyJG7evIn09HSMHTuWCzj69MUXX+CVV17BggUL4Ofnhy1btqBfv37N2kq2ZtGiRXjhhRd0vs/O398fn3zyCby8vLB//37s3r0b/v7+MDMzg5OTE4KCghAXF4eamhosXboUwN3T1k5OTl3WKYb0bDQDSEgbOtqXuDX+/v6YNWsW1q5dq69hGq3q6mrs3r0br7/+eoulV5lMhj///BMikQhHjhyBqakppkyZgmnTpuHxxx/XaycQhmFQU1PDtaRTqVRwcXGBu7t7s/7EbNs8uVyO0NDQTh1a0RWFQobSEglGjxmDI0eOICgoCADuOwPI1lMcNmwYnJyctHpehmGwd+9e/N///R9+/fXXLl32BbRrIwkAO3fuRExMDC5evIgNGzbg0KFDOpsBZGVkZGDjxo04dOgQpkyZgn379gG4+/vD5/OxZMkS3Lp1C7/99ptOn5eQB6FC0IS0QqFQIDk5GW+//Xaz6xMnTsSFCxfa9RhsmQdtP1Qfdg4ODnjjjTda/ZmlpSWioqIQFRUFpVKJ06dPIzY2FvPnz4darcaUKVMgFAoxbtw4nQcvHo8HBwcHODg4YMiQIaitrYVEIsGNGzeQlpYGFxcXuLq6oqioCGq1GmFhYd3emi7zbDxMU3fBRV4ApRx4bkANxo95HMr/P3mpVqtx7tw5bNu2DVVVVVyILS4uxvXr1xEcHNyp8PfLL7/gzTffRFxcXJeHP0C7NpI3btzA22+/jbNnz+r00NG9nYv8/f3x7rvvgs/nIyEhAZs3b8aKFSu4LQbu7u7IyMiAVCqFjY0NlXshXYYCICGt0OYD5V6ff/456uvrMXPmTH0MsccwMzPDU089haeeegrffPMNzp07h4MHD+K1115DfX09oqKiIBAIMGHCBJ0fvri3Y4ZUKkVJSQmuX78OtVoNZ2dnlJWVwdXVtdtCYPqpn9Hv0kcwhwIyWMLVTIG1k1wQLYiA/VOrAQCLFy/GkCFDsHLlymbh79q1awgODu5U15z4+HgsW7YMBw4cwMSJE3XymrTV3jaSarUaL7zwAj788EMMGTJEZ8/P9vYF7s5wW1pawtTUFD4+Pvj3v/8NExMT7Nq1C0VFRZgxYwZKSkqwadMmvP/++0ZVLJw8HCgAEnIfHe1LzNq/fz8++OADHD58GG5ubvoaXo9jamqKcePGYdy4cfjvf/+LixcvQiQSYdWqVaisrMTTTz8NgUCAiRMn6vw0MY/Hg5WVFddxZMiQIaioqGjWPo1tSddVewHVKhVsxN/DDEpUmbAhzgaW6gb4K8SoM1ehr08wbGxs4OTkBH9/fwBASUkJMjMzOx3+jh49ikWLFmHfvn2IiorSwSvSTkfbSNbV1eHy5ctITU3l9t9pNBowDANTU1OcOHECTzzxRIfG0DT8LV26FFevXoVGo8HYsWOxcuVK+Pj44O2338amTZvwzTffYO/evRAKhfj444/x+uuva/nKCdEeBUBCWqFNX2LWgQMH8Morr+DgwYOYMGGCPofZo5mYmODxxx/H448/js8//xyXLl2CSCTCBx98gFdffRUTJ06EQCBAZGSkTvrwKpVKpKamwsTEBMOGDYOJiQns7OwwYMAArn0au5/O3t6eqzWoz5IwlZLbcFJK0ADrZtdlPCs4MZW4lSdGX5/mNfhKS0uRkZGBoKAguLi4aP3cx44dw/z587Fr1y4IhUKtH0cXzM3NERYWhoSEhGZ7ABMSEiAQCFrc3s7ODmlpac2uxcTEIDExEbGxsRgwYECHx8CGP4FAgNzcXLzzzjvIzc3Frl27kJGRgZiYGAwePBjvvvsueDwezp07h5kzZ2L8+PEdfi5CdIECICGt6OgHCmv//v2YP38+9u/f360zIj0Nn8/HiBEjMGLECHzyySe4cuUKYmNj8emnn+Jf//oXnnzySQgEAkRFRcHe3r7D+6yUSiVSUlJgZmaG4ODgFuVprKys4O3tDW9vb8hkMq4LSXZ2Nuzs7LjyMtbW1m08g3YsbXpByTOBKaOGosl1E2igAQ+mlneD77FjxwDc/QKTnp6OoKAguLq6av28iYmJmDNnDr777js888wznXkJOrNy5Uq89NJLCA8P59pIFhQUcF2BmraR5PP5LTqTsGG9Mx1L2JJRp0+fhrOzM9avX4/S0lJYWVlh3rx52LlzJ/r164e33noLkydPpvBHuhUFQELa0JEPFOBu+JszZw6+/PJLPPbYY9zsoZWVFddOi+gfn89HSEgIQkJCsGHDBmRkZCA2NhZff/01li5dinHjxkEoFGLKlClwcnJ6YBhUKBRISUmBpaUlgoKCHlgf0NLSEv369UO/fv2gUCi4MJiTkwNbW1suDOpiz1cvexeIHSPgW/knFBpzqPhm4Gs0sGNqUGXijP5hT3G3lUgkSEtLQ2BgYKfC35kzZ/D888/j66+/NqgetbNmzUJFRQXWrVvHtZH8/fff4e3tDeDunse2SjjpioeHB4RCIZydnbFp0ybExMTg8OHDyM7OxooVKzBv3jzExMTAx8cHgwYN0utYCHkQKgNDyH10pC/xuHHjWi03MXfuXOzatasLR01awzAMsrOzIRKJEBcXhytXrmD06NEQCoWYOnUq3NzcWoQZ9jS4tbU1AgMD210cujVKpZJrSVdRUQErKyu4ubnB3d29U/2JKyV3UL7/X+gjvwEeGPAA1PLtUTv+P/AJu7uPraysDFevXkVgYGCn9qReuHAB06dPx2effYaFCxcaTPgzJNXV1aitrYVQKMTq1asxa9Ys3Lp1iysI/69//avN0++EdCUKgISQHodhGOTl5XFh8PLly4iIiIBAIEB0dDQ8PT1RUFCAnTt3YsaMGfD39+9U+LuXSqVq1pLO3NycC4Pa9CdWKGTI+fsY5KVZMLFxhvej0bB3vhv02PAXEBDwwP2r9/PPP/9AKBRiw4YNeO211yj8oe1DYefPn4dQKERiYiICAwNx6dIlfPHFF1i2bBlGjhzZDSMlpCUKgISQHo1hGNy+fRtxcXGIi4vDhQsXEBQUhNzcXISFheHQoUN6bUnH9idmW9KZmJg0a0nXmaBVXl6OK1eudDr8paSkYOrUqVi7di2WL1/eo8Pf8ePHUVdXB6FQCFNT01ZDYHZ2Nl566SUMHDgQAoEAa9euxcSJE/H1119306gJaYkCICFGxJCa3T+MGIbBpUuXEBUVBVNTU5SVlSE4OBhCoRACgQCDBg3Sa/jRaDSorKyERCKBRCIBj8eDq6sr3N3dO9SfGAAqKipw5coVDB06FB4eHlqP6erVq4iKisKqVauwatWqHhv+GIaBWq3GmDFjUFdXh/Xr1yMqKgpmZmYtQqBGo8E333yDAwcOQCKRYNSoUdi5c2c3jp6QligAEmIkDK3Z/cMoNzeX6+H85ZdforKyEvHx8RCJRDh16hR8fX25MOjr66vXMMQwDKqqqrgwqFaruTDo5OR031lJNvz5+fmhd+/eWo8hMzMTkZGRWLZsGd57770eG/6aqq+vx7PPPovS0lK8/fbbiI6OhoWFRYsQWFtbC5lMBoZhOjX7Soi+UAAkxEho25v4ueeeg4+PD0xMTPTS6/Rhkpubi59++gnvvPNOsw9zNowdPnwYcXFxSEhI4Jb3pk2bhqFDh+p0j+C92P7EEokEpaWlUCqVXH9itmYlq7KyEmKxuNPhLysrC5GRkXjllVewYcMGCn+4u3fT1NQUCoUCQqEQRUVFePvttyEUCpvVe7xx4wZWrlyJN954g2qBEoNFAZAQI2DIze57opqaGvz666+Ii4vD8ePH4enpyc0MDhs2TO9hsK6ujguDMpkMLi4ucHNzg6mpKdLS0uDr6wtPT0+tnyMnJweRkZF44YUX8Omnn+r19RgqdkavoqKiWbcUtuOHWq3G9OnTkZeXh9WrV2PGjBmwtLREfn4+BAIB+Hw+UlNTu/EVEHJ/VAeQECNgSM3uCWBvb48XX3wRL774IqRSKX7//XeIRCJERkbCxcUF0dHREAqFGD58uM7DE4/Hg52dHezs7Lj+xBKJBDdv3kRjYyNsbW3BMAwUCgXMzc07/Pj5+fmYMmUKZsyY0WPDH3D3fU5LS0NkZCQuXbrEzaay4c/ExASHDx/GjBkzuBn44cOHY/bs2bC2tsbFixe7c/iEPBB9KhBiRLq72T1pydbWFjNnzsTMmTPR0NCA48ePQyQSYfr06bC1tcXUqVMhFAoRERGhl9PEtra2UKlUyM/Px6BBg8Dn81FYWIhr167B0dGRO1Hcnv7Et2/fRlRUFCZPnowtW7b02PDHqqurA4/HaxGkm4ZAkUiE5557DuvXr0dNTQ369OlD4Y8YBVoCJsQIdHQJuLq6Go6Ojs0CB9vs3sTERKtm96RjZDIZTp48ibi4OBw+fBhmZmaYOnUqpk2bhlGjRsHMzEwnz1NdXY3U1FT4+Pigb9++zZ6fXSauqamBvb09FwatrKxaPE5xcTEmTZqEsWPH4rvvvtNr6RtjoVAo4OPjg02bNmHmzJktfs6GQAB45plnUFJSgnPnznX1MAnRSs/+ekeIkWjam7iphISEVgvLss3uxWIx97/FixfjkUcegVgsxogRI7pq6D2WpaUlpkyZgh07dqCkpITrQfvyyy9j0KBBWLJkCU6cOAGFQvHgB2tDTU0NUlNTMXjw4Gbhj31+Ly8vDB8+HKNHj4aHhwfKy8tx/vx5/P3338jLy0N+fj4AoLS0FFFRURg5cmSXhr+YmBgMGDAAlpaWCAsLw9mzZ9u8bVxcHJ566im4urrCzs4OEREROH78uM7GotFoWvw3wzDw9PTk3qd7sTOBABAbG0vhjxgVmgEkxEiwZWC2bt3K9Sbevn07MjIy4O3t3aI38b0++OADOgRiAFQqFc6ePYvY2FgcOnQIDQ0NiIqKQnR0NCZMmNDsNOn91NTUICUlBYMGDbpvGaB7sf2Ji4qKMHXqVDg6OqK+vh7h4eH49ddfdTYz+SAdLWu0fPlyeHp6Yvz48XBwcMDOnTvx2Wef4e+//0ZISIhOxpSTk4PU1FRERESgV69esLe3x8aNG5Gamor9+/c3m/FrSqPR9PjlcmJ8KAASYkQ60pv4XhQADY9arcaFCxcgEokQHx+P6upqPP300xAIBJg4cSKsra1bvV9tbS2Sk5M7HP7udfPmTURGRkKtVqOmpgb9+vXDjBkz8PLLL8PHx0frx20PbcsaNeXv749Zs2Zh7dq1nRoLwzBoaGhAdHQ0UlJS4OrqipqaGjz22GO4evUqLC0tuZ7QbYVAQowNBUBCCDEAGo0Gly5dQmxsLOLj41FSUoKnnnoKQqEQTz/9NHr16gUASE5ORnl5OXx9feHt7a3181VXV2Pq1Knw9PSESCSCUqnEsWPHIBKJMHv2bERFRenqpbWgbVmjpjQaDfr3749Vq1Zh6dKlOhlXRUUF7O3tkZmZicuXL6OyshKJiYnIz89HYGAgvv/+e/Tq1YtCIHkoUAAkhBADo9FoIBaLuTCYn5+PCRMmwN/fH9988w3WrVuHRYsWaf34tbW1EAqFcHBwwKFDh9q97KwrRUVF6NOnD86fP99sD+vHH3+M3bt3Iysr64GPsWnTJnzyySe4du0a3NzcdDKu1pZy5XI5RCIRvvzyS3h6emL37t2ws7OjZV9i9Oi3lxCitY5s4gfufpi+88478Pb2hoWFBQYNGoQdO3Z00WiNB5/PR2hoKD7++GNkZmbi0qVL6Nu3Lz777DOu1MyePXtQUVGBjn6Hl0qleOaZZ2BjY4P4+PguD39Ntbes0b3279+PDz74AAcOHNBZ+APABTr2PdVoNLCwsMAzzzyDpUuXory8HJMnT0ZNTQ2FP2L06DeYEKKVAwcOYPny5XjnnXeQmpqK0aNHIzIyEgUFBW3eZ+bMmfjzzz/xww8/ICsrC/v374evr28Xjtr4sIEoNjYWH374ITIzMzFmzBhs374dAwcORHR0NL7//nuUlpY+MAw2NDRg5syZXBHj1srBdAW2fd29RcwlEskD++YeOHAAr7zyCn755Re9tVlj33M+nw+GYWBubo4XXngB8+bNg7u7e4sTw4QYI1oCJoRopaOb+I8dO4bnnnsOubm5cHJy6sqhGr0FCxbA29sb7733HneNYRjk5uZCJBIhLi4OycnJiIiIgEAggEAgQO/evZvNpslkMsyaNQv19fU4duwY7OzsuuOlcEaMGIGwsDDExMRw14YOHQqBQNDmIZD9+/dj/vz52L9/P4RCYReN9H8zkxqNBnK5vNuCMyG6RAGQENJh2mziX7JkCbKzsxEeHo4ff/wRNjY2iI6Oxvr16+kD9QEedOiAYRjcvn2bO0188eJFDB8+nGtJ5+7ujtmzZ6O8vBwnTpyAg4ND1w2+DR0ta7R//37MmTMHX375JaZPn849jpWVFezt7fU+3vYuTxNiLKgVHCEGhv1OZsgfNtr0Js7NzcW5c+dgaWmJ+Ph4lJeXY8mSJaisrKR9gA/woBOnPB4PXl5eWLFiBZYvX46ioiLEx8cjLi4O7777Lnr16gU3NzdcvHjRIMIfAMyaNQsVFRVYt24dV9bo999/5042FxcXN9tOsG3bNqhUKrz22mt47bXXuOtz587Frl279D5eQ/77SIg2aAaQEANSX18PGxub7h7GA7GnOC9cuICIiAju+kcffYQff/wR169fb3GfiRMn4uzZsygpKeFmbOLi4vDMM8+gvr6eZgH1gGEYlJWVYfXq1XjzzTcREBDQ3UMihBgIOgRCiAF55ZVXsGDBAsjlcu4au+HckL6rabOJv3fv3ujTp0+z5To/Pz8wDIPCwkK9jren4vF4cHNzw86dOyn8EUKaoQBIiAFZunQpDh48CJlMBuBu6OPz+SgpKTGoJaiO9iYGgFGjRqGoqAhSqZS7lp2dDT6f36KPLSGEEP2iAEiIAfH09ETfvn3x+++/A7hbs+3LL7/EwIEDsXXr1jbv1x2zgytXrsT333+PHTt24Nq1a1ixYgUKCgqwePFiAMCaNWswZ84c7vYvvPACnJ2d8fLLLyMzMxNnzpzBW2+9hfnz59PyLyGEdDE6BEKIgdBoNBg4cCAcHByQmZmJ6upqzJkzB9nZ2fjss8+4YNXaacTumB3s6CZ+W1tbJCQkYNmyZQgPD4ezszNmzpyJDRs2dPnYCSGkp6NDIIQYmJ9++gkbNmxAXV0dvLy88PXXXyMkJARA81ZVbGmQ48ePIzs7Gy+99JLBnPAkhBBi2GgJmBADwB70KC4uRkZGBq5fv45x48bh6NGjXPgD0Kz9FPv/Dx48iB9//JEOUhBCCGk3CoCEdDO1Wg0+n49bt25BIBDg8uXLAIDw8HA4OjpCqVS2ej8ej4e6ujpkZ2dj7NixGDp0aFcO22B1tD/xvn37EBwcDGtra/Tu3Rsvv/wyKioqumi0hBDSPSgAEtLNTExMcObMGYwePRq9evXCzp07sXDhQiQmJkKtVsPMzKzFfdgZw6SkJEilUgQFBXF9S1vDMAxUKpVBlZLRh472Jz537hzmzJmDV155BRkZGTh48CAuXbqEBQsWdPHICSGka1EAJKQbqVQqLFq0CC+++CIiIyPxxx9/wNPTE9OnT0dSUhLq6+vve/+EhAS4uroiNDS02XU26NXW1qKsrAw8Hg+mpqatHhY5evQo/vjjD929qG70xRdfcLUU/fz8sGXLFvTr169Zv+Km/vrrL/Tv3x+vv/46BgwYgMcffxyLFi3iZmEJIeRhRQGQkG7E4/EQGBiIzZs349tvv4W5uTkYhsGQIUPQu3dvrhzMvfh8PhoaGpCamgpfX1888sgj3OM19csvv0AgEMDPz4/rrQrcXXYGgIqKCuzZswf//ve/9fgqu4ZCoUBycjImTpzY7PrEiRNx4cKFVu8zcuRIFBYW4vfffwfDMCgtLUVsbCyioqK6YsiEENJtKAAS0o1MTEywdOlSzJgxo9kBjwEDBsDR0RFJSUkAmtf5Y5d/z5w5A6lUimHDhsHU1LTZbdgg6OXlhS1btmD16tW4dOkSFi9ejKqqKq63bFZWFgoLCzF79mwAgEwm4x7f2GjTn3jkyJHYt28fZs2aBXNzc3h4eMDBwQFfffVVVwyZEEK6DQVAQgwMG97WrVvHBbXWlm4TEhLg7OyMsLAwAK0Xgx41ahSGDx+OefPm4eeff4ZYLG7WvUMsFqOurg7jx48HAFhaWjYLosbo3veqtbqJrMzMTLz++utYu3YtkpOTcezYMeTl5XE1F0lzHT1gk5SUhLCwMFhaWj6wmDkhpGsZ97/0hDzEJkyYgK+//rrFdT6fD7lcjn/++QeDBw+Gv78/d53V2NiI1atXQygUYsiQIRAIBBCJRAgPD0dqaiqAu8u/V69eRX19PY4ePQo/Pz8sXLgQ+fn5rY7H0A+QaNOf+D//+Q9GjRqFt956C0FBQZg0aRJiYmKwY8cOFBcXd8WwjUZHD9jk5eVh8uTJGD16NFJTU/Hvf/8br7/+OkQiURePnBDSGgqAhBih3Nxc3Lp1C99//z1WrlyJkydPoqamhvv5zp078c0330AgEGDLli145JFHsHHjRhw+fBiPPvooAODmzZs4deoUgLtdOrZs2QKxWIz3338fQMvAx86iqdXqFj8rKyvT22ttL236Ezc0NLSY8WRnXQ098Ha1jh6w2bp1K7cFwc/PDwsWLMD8+fPx2WefdfHICSGtYgghRkmpVDJ79+5lxo0bx5ibmzN2dnbMmjVrmMLCQubVV19lhg8f3uz2n3zyCePg4MDU19czDMMw27ZtYxwdHZmLFy9yt9m9ezfTr18/5sKFC9y12tpa5vjx40xiYmKr4ygqKmJ4PF6bP+9KP//8M2NmZsb88MMPTGZmJrN8+XLGxsaGyc/PZxiGYd5++23mpZde4m6/c+dOxtTUlImJiWFu3rzJnDt3jgkPD2ceffTR7noJBkkulzMmJiZMXFxcs+uvv/46M2bMmFbvM3r0aOb1119vdi0uLo4xNTVlFAqF3sZKCGkf6gVMiJEyNTXF7NmzMXv2bDAMg/379+P69euwtrbG8OHDkZiYiJMnT8LPzw8ikQhbtmxBREQErK2tUVlZicuXL8PHxwePPfYY95hTp07FggULuFPChw8fxqeffgo+n4+8vDwolUqsX78eCxYs4GbKEhIS4OTkZBCFqDvan3jevHmoq6vD119/jTfffBMODg544okn8Omnn3bXSzBI2hywKSkpafX2KpUK5eXl6N27t97GSwh5MAqAhDwEeDweXnjhBe6/p06dikuXLmHatGkYPnw4bG1tUVpainnz5gG4u4SclJSEJ554AsDdEirm5ubIyMgAj8eDt7c3KioqsHDhQnz44Yd45ZVXYG5ujv379+Pjjz/GyJEjERgYCOBuJ40nnniizX12XW3JkiVYsmRJqz/btWtXi2vLli3DsmXL9Dyqh0NHDti0dfvWrhNCuh7tASTkIeTu7o5t27ahrq4OMTExeO+99+Dt7Y1JkyYBAC5fvoza2lpUVFRArVbD3NwcAPD1119jxIgR6NOnD3766SeUl5dj+/bt+Oqrr1BUVITnn38eXl5e3N7BiooKnDlzBjNnzuy210r0T5sDNh4eHq3e3tTUFM7OznobKyGkfSgAEvKQ8/X1xfDhw5GXlwd7e3s0NDSgoKAA5ubm4PF4EIlEuHXrFlauXInffvsNb775Jvh8Pnbv3o2ZM2di7ty5iIuLg6+vL4YOHYqUlBRcu3YNAPDbb7/BwsICjz/+eDe/SsN15swZTJ06FZ6enuDxeDh06NAD72No5VO0OWATERHR4vYnTpxAeHh4q+0NCSFdrJv3IBJCuklBQQGTkJDAODo6Mg4ODkxISAjz3//+l2EYhlGr1cyIESOYDz74oNntt23bxkRGRjIJCQkMwzDMxIkTmWnTpnXL+I3F77//zrzzzjuMSCRiADDx8fH3vX1ubi5jbW3NvPHGG0xmZiazfft2xszMjImNje2aAbehowds2NexYsUKJjMzk/nhhx8M4nUQQu6iAEgIYTIyMpi8vDzuvzUaDfPhhx8yXl5eTGFhYav3qa6uZqytrZmffvqpi0Zp/NoTAFetWsX4+vo2u7Zo0SLmscce0+PI2uebb75hvL29GXNzcyY0NJRJSkrifjZ37lxm7NixzW5/+vRpJiQkhDE3N2f69+/PfPvtt108YkJIW3gMQ8WuCCEtFRcXY9GiRaivr8f8+fMxZMgQ1NTUICAgAB4eHjh48CDmz5+PrKwseHp6dvdwjQKPx0N8fDyEQmGbtxkzZgxCQkLw5Zdfctfi4+Mxc+ZMNDQ00PIpIUQnaA8gIaQFhmHQu3dvfP311xg2bBjef/99zJs3D0ePHkV1dTUA4Oeff8YTTzxB4U/HHlQ+hRBCdIHKwBBCWmDLdHh5eeHzzz/H559/jqKiIigUCvTv3x+1tbWIj4/Hd999180jfThR+RRCiL5RACSEtEvTmT5zc3Ns2bIFU6dO7cYRPZyofAohpCtQACSEdJilpSVef/317h7GQykiIgK//vprs2tUPoUQomu0B5AQQvRIKpVCLBZDLBYDAPLy8iAWi7mWdGvWrMGcOXO42y9evJiry3jt2jXs2LEDP/zwA/7v//6vO4ZPCHlI0SlgQgjRo9OnT2P8+PEtrs+dOxe7du3CvHnzkJ+fj9OnT3M/S0pKwooVK5CRkQFPT0+sXr0aixcv7sJRE0IedhQACSGEEEJ6GFoCJoQQQgjpYSgAEkIIIYT0MBQACSGEEEJ6GAqAhBBCCCE9DAVAQgghhJAehgIgIYQQQkgPQwGQEEIIIaSHoQBICCGEENLDUAAkhBBCCOlhKAASQgghhPQwFAAJIYQQQnoYCoCEEEIIIT0MBUBCCCGEkB6GAiAhhBBCSA9DAZAQQgghpIehAEgIIYQQ0sNQACSEEEII6WEoABJCCCGE9DAUAAkhhBBCehgKgIQQQgghPQwFQEIIIYSQHoYCICGEEEJID0MBkBBCCCGkh6EASAghhBDSw1AAJIQQQgjpYSgAEkIIIYT0MBQACSGEEEJ6GAqAhBBCCCE9DAVAQgghhJAehgIgIYQQQkgPQwGQEEIIIaSHoQBICCGEENLDUAAkhBBCCOlhKAASQgghhPQwFAAJIYQQQnoYCoCEEEIIIT0MBUBCCCGEkB6GAiAhhBBCSA9DAZAQQgghpIehAEgIIYQQ0sNQACSEEEII6WEoABJCCCGE9DAUAAkhhBBCehgKgIQQQgghPQwFQEIIIYSQHoYCICGEEEJID/P/AKGkkWGy+XRcAAAAAElFTkSuQmCC", + "image/png": 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", "text/html": [ "\n", "
\n", "
\n", " Figure\n", "
\n", - " \n", + " \n", "
\n", " " ], @@ -126,15 +137,16 @@ "fig = plt.figure()\n", "ax = fig.add_subplot(projection='3d')\n", "\n", - "ax.scatter(test_sites[:,0], test_sites[:,1], test_sites[:,2])\n", - "ax.scatter(test_sites[:,0], test_sites[:,1], test_sites[:,2])\n", + "positions = lattice_x[None,:]*test_sites[:,0][:,None] + lattice_y[None,:] * test_sites[:,1][:,None] + lattice_z[None,:] * test_sites[:,2][:,None] + lattice_s[test_sites[:,3]]\n", + "\n", + "ax.scatter(positions[:,0], positions[:,1], positions[:,2])\n", "\n", "ax.set_xlabel('X Label')\n", "ax.set_ylabel('Y Label')\n", "ax.set_zlabel('Z Label')\n", "\n", "for i in range(test_sites.shape[0]):\n", - " ax.text(test_sites[i,0], test_sites[i,1], test_sites[i,2], str(i))" + " ax.text(positions[i,0], positions[i,1], positions[i,2], str(i))" ] }, { @@ -147,7 +159,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 15, "id": "daaa4792-069c-44fd-bdbd-90af6f51858f", "metadata": {}, "outputs": [], @@ -155,28 +167,34 @@ "tolerance = 1\n", "\n", "@jit\n", - "def index_to_coord(index, max_distance):\n", + "def index_to_coord(index, max_distance, site_nb):\n", " center = max_distance // 2\n", - " return (index // max_distance**2 - center, index // max_distance % max_distance - center, index % max_distance - center) \n", + " return (\n", + " index // (max_distance**2 * site_nb**2) - center,\n", + " index // (max_distance * site_nb**2) % max_distance - center,\n", + " index // site_nb**2 % max_distance - center,\n", + " index // site_nb % site_nb,\n", + " index % site_nb\n", + " ) \n", "\n", "@jit\n", - "def coord_to_index(vec, max_distance):\n", + "def coord_to_index(vec, max_distance, site_nb):\n", " center = max_distance // 2\n", - " return (vec[0] + center)*max_distance**2 + (vec[1] + center) * max_distance + (vec[2] + center)\n", + " return site_nb**2 * ((vec[0] + center)*max_distance**2 + (vec[1] + center) * max_distance + (vec[2] + center)) + vec[3]*site_nb + vec[4]\n", "\n", "#@jit #(locals={'current_set': types.Set(types.UniTuple(float64, 3))})\n", - "def vector_couplings(max_distance=10, tolerance = 1):\n", + "def vector_couplings(max_distance, site_nb, tolerance):\n", " print(\"Computing vector -> couplings lookup\")\n", - " couplings = np.empty(max_distance*max_distance*max_distance)\n", - " for i in range(max_distance**3):\n", + " couplings = np.empty(max_distance**3*site_nb**2)\n", + " for i in range(max_distance**3*site_nb**2):\n", " couplings[i] = compute_coupling(\n", - " *index_to_coord(i, max_distance)\n", + " *index_to_coord(i, max_distance, site_nb)\n", " )\n", " # Revert the map\n", " print(\"Reverting the map\")\n", - " coupling_values = [] # OK to append because O(number_spins)\n", - " current_set = set(((0,0,0),))\n", - " current_set.remove((0,0,0)) # HACK for type inference\n", + " coupling_values = [] # OK to append to that list because O(number_spins)\n", + " current_set = set(((0,0,0,0),))\n", + " current_set.remove((0,0,0,0)) # HACK for type inference\n", " vectors = [current_set.copy()] # OK to append because O(number_spins)\n", " sorted_couplings = np.argsort(couplings)\n", " # i_max = coupling index st coupling + tolerance < cureent cursor\n", @@ -185,23 +203,24 @@ " while not np.isnan(couplings[sorted_couplings[i_max]]):\n", " if np.isnan(couplings[sorted_couplings[i_min]]) or couplings[sorted_couplings[i_min]] - tolerance > couplings[sorted_couplings[i_max]] + tolerance:\n", " # Depile du côté des maxima (ie on retire un vecteur au set)\n", - " vec = index_to_coord(sorted_couplings[i_max], max_distance)\n", + " vec = index_to_coord(sorted_couplings[i_max], max_distance, site_nb)\n", " current_set.remove(vec) # We want unmutable type here\n", " coupling_values.append(couplings[sorted_couplings[i_max]] + tolerance)\n", " i_max += 1\n", " else:\n", " # Depile du côté des minima (ie on ajoute un vecteur au set)\n", - " vec = index_to_coord(sorted_couplings[i_min], max_distance)\n", + " vec = index_to_coord(sorted_couplings[i_min], max_distance, site_nb)\n", " current_set.add(vec) # We want unmutable type here\n", " coupling_values.append(couplings[sorted_couplings[i_min]] - tolerance)\n", " i_min += 1\n", " vectors.append(current_set.copy())\n", - " return np.array(coupling_values), vectors" + " return np.array(coupling_values), vectors\n", + "#vector_couplings(tolerance = 0.01, max_distance = lattice_size*2, site_nb = site_nb)" ] }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 16, "id": "4a78bf20-e87b-4aeb-99f0-2bccc9dc4233", "metadata": {}, "outputs": [], @@ -217,26 +236,24 @@ " x = sites[i][0] - sites[j][0]\n", " y = sites[i][1] - sites[j][1]\n", " z = sites[i][2] - sites[j][2]\n", - " cost += (couplings[i,j] - compute_coupling(x, y, z))**2\n", + " cost += (couplings[i,j] - compute_coupling(x, y, z, sites[i][3], sites[j][3]))**2\n", " return cost\n", "\n", - "@jit\n", - "def t_add(t1, t2):\n", - " return (t1[0] + t2[0], t1[1] + t2[1], t1[2] + t2[2])\n", + "#def get_placing_order(couplings):\n", " \n", - "@jit\n", - "def t_sub(t1, t2):\n", - " return (t1[0] - t2[0], t1[1] - t2[1], t1[2] - t2[2])\n", "\n", - "def compute_sites(couplings, lattice_size = 10, tolerance = 0.01):\n", + "def compute_sites(couplings, lattice_size = 5, tolerance = 0.01):\n", " print(\"Begin\")\n", " n_placed = 1\n", " n_tot = couplings.shape[0]\n", - " couplings_vectors_tup = vector_couplings(tolerance = tolerance, max_distance = lattice_size*2) # TODO better names\n", - " possible_configurations = [np.zeros((n_tot, 3), dtype=np.int64)]\n", - "\n", - " \n", - " current_couplings = np.empty(n_tot) # stores current coupling\n", + " couplings_vectors_tup = vector_couplings(tolerance = tolerance, max_distance = lattice_size*2, site_nb = site_nb) # TODO better names\n", + " possible_configurations = []\n", + " for i in range(site_nb):\n", + " c = np.zeros((n_tot, 4), dtype = np.int64)\n", + " c[0][3] = i\n", + " possible_configurations.append(c)\n", + " \n", + " current_couplings = np.empty(n_tot) # stores current coupling values to other spins\n", "\n", " print(\"Initialization successful\")\n", " while n_placed < n_tot:\n", @@ -246,25 +263,32 @@ "\n", " for i in range(n_tot):\n", " current_couplings[i] = np.nanmax([couplings[n_to_place, i], couplings[i, n_to_place]])\n", - " print(current_couplings)\n", " # Be careful, position relative to n_to_place-1\n", " candidates = couplings_vectors_tup[1][np.searchsorted(couplings_vectors_tup[0], current_couplings[n_to_place-1])]\n", - " print(candidates)\n", " new_possible_configurations = []\n", " for config in tqdm(possible_configurations):\n", " for candidate in candidates:\n", " good_candidate = True\n", - " for i in range(n_placed):\n", + " # First check the origin lattice site\n", + " if candidate[4] != config[n_to_place - 1][3]:\n", + " continue\n", + " for i in range(n_placed-1):\n", " if np.isnan(current_couplings[i]):\n", - " # no data for the already placed spin\n", + " # no data for this already placed spin\n", " continue\n", - " coupling_candidate = compute_coupling(*t_sub(config[i], t_add(candidate, config[n_to_place-1])))\n", - " if np.isnan(coupling_candidate) or np.abs(current_couplings[i] - coupling_candidate) > tolerance: # TODO: One redundant check\n", + " coupling_candidate = compute_coupling(\n", + " x := candidate[0] + config[n_to_place-1][0] - config[i][0],\n", + " y := candidate[1] + config[n_to_place-1][1] - config[i][1],\n", + " z := candidate[2] + config[n_to_place-1][2] - config[i][2],\n", + " candidate[3],\n", + " config[i][3],\n", + " )\n", + " if np.isnan(coupling_candidate) or np.abs(current_couplings[i] - coupling_candidate) > tolerance:\n", " good_candidate = False\n", " break\n", " if good_candidate:\n", " new_config = config.copy()\n", - " new_config[n_to_place] = np.array(t_add(candidate, config[n_to_place-1]))\n", + " new_config[n_to_place] = np.array((candidate[0] + config[n_to_place-1][0], candidate[1] + config[n_to_place-1][1], candidate[2] + config[n_to_place-1][2], candidate[3]))\n", " new_possible_configurations.append(new_config)\n", " possible_configurations = new_possible_configurations\n", " n_placed+=1\n", @@ -273,7 +297,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": null, "id": "880aae08-77bb-4964-aa86-bff1da5a2815", "metadata": {}, "outputs": [ @@ -285,56 +309,21 @@ "Computing vector -> couplings lookup\n", "Reverting the map\n", "Initialization successful\n", - "Placing 1\n", - "[ 8. nan 1.3671875 11.11111111 1.3671875 11.11111111\n", - " 0.30052592 2.77777778]\n", - "{(0, 0, -1), (0, 0, 1)}\n" + "Placing 1\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "/tmp/ipykernel_35830/924063087.py:40: RuntimeWarning: All-NaN axis encountered\n", + "/tmp/ipykernel_775710/552860360.py:38: RuntimeWarning: All-NaN axis encountered\n", " current_couplings[i] = np.nanmax([couplings[n_to_place, i], couplings[i, n_to_place]])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "213089f3d1c44dbd91d37bde9d8a3e2e", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/1 [00:00