{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from pystencils.session import *\n", "from lbmpy.session import *\n", "import lbmpy\n", "from lbmpy.macroscopic_value_kernels import macroscopic_values_setter\n", "from lbmpy.boundaries.boundaryhandling import LatticeBoltzmannBoundaryHandling\n", "from lbmpy.boundaries import NoSlip\n", "\n", "import pystencils.opencl.autoinit" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Lattice Boltzmann\n", "\n", "## Definitions" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "L = (34, 34)\n", "\n", "lb_stencil = get_stencil(\"D2Q9\")\n", "eta = 1\n", "omega = lbmpy.relaxationrates.relaxation_rate_from_lattice_viscosity(eta)\n", "\n", "f_pre = 0.00001" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data structures" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "dh = ps.create_data_handling(L, periodicity=(True, False), default_target='cpu')\n", "\n", "opts = {'cpu_openmp': True, \n", " 'cpu_vectorize_info': None,\n", " 'target': dh.default_target}\n", "\n", "src = dh.add_array('src', values_per_cell=len(lb_stencil))\n", "dst = dh.add_array_like('dst', 'src')\n", "ρ = dh.add_array('rho', latex_name='\\\\rho')\n", "u = dh.add_array('u', values_per_cell=dh.dim)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "collision = create_lb_update_rule(stencil=lb_stencil,\n", " relaxation_rate=omega, \n", " compressible=True,\n", " force_model='guo', \n", " force=sp.Matrix([f_pre,0]),\n", " kernel_type='collide_only',\n", " optimization={'symbolic_field': src})\n", "\n", "stream = create_stream_pull_with_output_kernel(collision.method, src, dst, {'velocity': u})\n", "\n", "lbbh = LatticeBoltzmannBoundaryHandling(collision.method, dh, src.name, target=dh.default_target)\n", "\n", "stream_kernel = ps.create_kernel(stream, **opts).compile()\n", "collision_kernel = ps.create_kernel(collision, **opts).compile()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Set up the simulation" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "init = macroscopic_values_setter(collision.method, velocity=(0,)*dh.dim, \n", " pdfs=src.center_vector, density=ρ.center)\n", "init_kernel = ps.create_kernel(init, ghost_layers=0).compile()\n", "\n", "noslip = NoSlip()\n", "lbbh.set_boundary(noslip, make_slice[:, :4])\n", "lbbh.set_boundary(noslip, make_slice[:, -4:])\n", "\n", "for bh in lbbh, :\n", " assert len(bh._boundary_object_to_boundary_info) == 1, \"Restart kernel to clear boundaries\"\n", "\n", "def init():\n", " dh.fill(ρ.name, 1)\n", " dh.fill(u.name, np.nan, ghost_layers=True, inner_ghost_layers=True)\n", " dh.fill(u.name, 0)\n", " \n", " dh.run_kernel(init_kernel)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "sync_pdfs = dh.synchronization_function([src.name])\n", "\n", "def time_loop(steps):\n", " dh.all_to_gpu()\n", " vmid = np.empty((2,steps//10+1))\n", " i = -1\n", " for i in range(steps):\n", " dh.run_kernel(collision_kernel)\n", " sync_pdfs()\n", " lbbh()\n", " dh.run_kernel(stream_kernel)\n", " \n", " dh.swap(src.name, dst.name)\n", " \n", " if i % 10 == 0:\n", " if u.name in dh.gpu_arrays:\n", " dh.to_cpu(u.name)\n", " uu = dh.gather_array(u.name)\n", " uu = uu[L[0]//2-1:L[0]//2+1, L[1]//2-1:L[1]//2+1, 0].mean()\n", " vmid[:, i//10] = [i, uu]\n", " if 1/np.sqrt(3) < uu:\n", " break\n", " if dh.is_on_gpu(u.name):\n", " dh.to_cpu(u.name)\n", " \n", " return vmid[:,:i//10+1]" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "def plot():\n", " uu = dh.gather_array(u.name)\n", " \n", " plt.subplot(2,2,1)\n", " plt.title(\"$u$\")\n", " plt.xlabel(\"$x$\")\n", " plt.ylabel(\"$y$\")\n", " plt.vector_field_magnitude(uu)\n", " plt.colorbar();\n", " \n", " plt.subplot(2,2,2)\n", " plt.title(\"$u$\")\n", " plt.xlabel(\"$x/2$\")\n", " plt.ylabel(\"$y/2$\")\n", " plt.vector_field(uu, step=2)\n", " \n", " actualwidth = np.sum(1-np.isnan(uu[0,:,0]))\n", " uref = f_pre*actualwidth**2/(8*(eta))\n", " \n", " plt.subplot(2,2,3)\n", " plt.title(\"flow profile\")\n", " plt.xlabel(\"$y$\")\n", " plt.ylabel(r\"$u_x$\")\n", " plt.plot((uu[L[0]//2-1,:, 0]+uu[L[0]//2,:, 0])/2)\n", " \n", " plt.subplot(2,2,4)\n", " plt.title(\"convergence\")\n", " plt.xlabel(\"$t$\")\n", " plt.plot(vmid[0,:], vmid[1,:]/uref)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Run the simulation" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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s3nLLLSxcuJDY2FisVitWq5Xg4GCzvWvXrvTu3Zvz589jGAZWq5UBAwbg5PR//9bdfPPNrF+/nvj4eAzDICEhgVatWpnt8fHxtGnThqCgILOPHj162GxPvvnmm3nllVfMeYwaNQpPT0+zfeLEiTz66KP079/fHGdERITNXK+99lo2btxonmPYsGG4uLjYnGPx4sWMGjUKwzBITEwkMDDQbO/duzdRUVEUFRWZffTr189my/jNN9/Mjh07SEhIwDAM4uLiaNmypdluGAZ+fn6Eh4ebc+nWrZvdXN99911zHlW3x//lL39h3rx5DB482BxH1e3x8fHx7N692/x7dbQ9XohLURVXx5qyPn366C1btjT0MK5a3R58rqGHIK4ye5+c0dBDuGoppbZqrfvUZZ+hUc31vR8NcNh2b9fVdX4+cXWQz2ZRnZSUFDp06GATjFZ26tQpXF1dbQK0yrTWJCcn06lTJ7t7ZSscPnwYf39/u/uXK+Tn53Py5EmH9y9XSE1NpV27dtUGaJmZmRQWFjq8f7lCcnIykZGRdvcvVzh58iQeHh4O71+GsrmmpKTQsWPHaud66NAhWrdujbu7u8P23Nxczpw5Q7t27aod5/79+wkLC7O7f7nCuXPnKC0tdXj/coXk5OQax3n8+HG8vb1p3txxbpvS0lJSU1PtLoYIAb/u+42sIAshhKhXsoIshKhLlwqA2rRpU2O7UorOnTvXeExNwSCAm5tbjcExYLeSW1V1AXxljpJVVVZ5pdcRpdQl+2jfvn2N7R4eHpf884iMjKyx3dfXt8Z2uPRcK6/gO2KxWCQ4FnVCAmQhhBD1qiJJlxBCCCHElU4CZCGEEPWuREvRBCGEEEJc+eQbixBCiHpVscVayjwJIepaSUkJX3zxBdnZ2dUe8/PPP5tZmB25cOECX3/9tVkmypHvvvuOY8eOVdt+5MgR1q9fb5aJcmTlypWcO3eu2vY9e/awY8cOqssPVFxczBdffGGWiXJk48aNpKamVtuekZHB6tWrzWzQjqxZs4aTJ09W256WlsZPP/1U7Vy11nz55ZdkZmZW28fOnTvZvXt3tXMtKChgxYoV5ObmVtvH+vXrOXjwYLXt6enpfPvtt2aZKCFqS1aQRb3LDZLac0I0ZRokGBZC1JmsrCyburZLly5l/PjxDB8+3MxqHRAQYLbn5ubSv39/IiMjzezH3bp1M5Nnaa155JFHSEpKYsyYMVitVoYPH06LFi3MPlJTUxk5ciQxMTFmRurKybNcXFwYP348RUVFjB07FsMwGDRokE2Sr7Vr12K1Ws0szGPGjCE0NNRMSmWxWOjXrx9t2rQxMz3HxMTYZNd+++23uf766xk5ciRWq5XRo0fj5+dntp8/f56BAwfSuXNnc65dunSxSZ41a9YsDh48SFxcnJnBu3Liq6SkJEaNGkWfPn0wDIP4+HgiIiLMcbq6umK1WnFycjIziffv399mrt988w3jxo1j6NChWK1W4uLibO4h1loTExNDaGioOdcePXrYzPWVV17h+uuvJzY2FsMwiI2NtbmX+cyZMwwZMoRu3bphGAZjx46lS5cuZvI2Jycn7rjjDk6fPl1tJnEhHJEs1kimzPoW9uL8hh6CuMocnD6zoYdw1aqPLNZturXSf31/tMO2+dEfShZr4ZB8NovqhIWFcejQoYYexiUppapdIb3aNJa5WiwWrrnmGubNm0f//v0bejjiMpIs1kIIIa4YWkOJdly2Qwghfq358+dz8eJF8/nSpUtZuXIlLi4ujBw5kt69e9OqVStzZfXs2bPMnFl2YbVTp04kJibi6upKZGSkudr43HPPsWPHDry8vIiLi6NLly60bt3aXFnds2cPzzzzDFBWF3jUqFG4u7vTvn17Mzh84IEHOH36NH5+fiQmJhIaGkpISIhZPmn16tW89957ODk5MWTIEAYNGoSPj4+ZibqgoIBp06ZRVFRE27ZtMQwDHx8fwsPDzdXud999lzVr1uDq6kpsbCwxMTH4+fmZq6InT57kwQcfBMpqNY8dOxZXV1ciIiLM1e6nnnqKpKQkmjdvTnx8PB07diQwMBAvLy8Atm3bxgsvvABAv379GDFiBJ6enrRt29ac67333ktGRgYBAQFYrVYCAwNp27Ytbm5uAHz55Zd8+OGHNGvWjKFDhzJw4EBatGhhlrTKzc1l2rRplJaWEhYWhmEYeHp6EhERYa52v/HGG6xbtw53d3dGjRpFz5498fPzM7N/Hz58mEceeQSAqKgo4uPjcXd3Jzw83Jzr448/zv79+2nRogUJCQlYrVbi4+NlFVnUqNEGyEqpUOBdoA1QCizUWr+glJoL3AacKT90ttb6q4YZpRBCCI2iuFS2WAsh6sZ1111n/lxSUsK+ffu47bbbGD16tBnkVfbZZ58xf/58DMNwWI7owoUL7Nq1i6effpphw4bZbPOtsHDhQl5//XWsVitBQUF27ampqdx6661YrVb69+/vsEbz0aNHWbJkSbUB2g8//MCcOXMwDIPu3bvb1QMuLi5m7969TJ8+ndjYWDw9Pe36+Oijj3j++eexWq106NDBrj0jI4OdO3fy4osvMnToUFxcXOyOyc7O5o033iAxMdFhyaykpCTuuOMODMOgb9++djWatdYcOnSIpUuXEhcXZ7NVvcKaNWt44oknMAyDrl272s21oKCA3bt3c//99xMbG+uwRvP777/PggULsFqtDktVnT59mt27d5OYmMjgwYOrrUctRFWNdou1UioQCNRab1NKeQNbgWuBG4CLWutna9uXbOOqXxEfPN7QQxBXmdQb/9nQQ7hq1ccWa/+uvvpPi8c6bHu9z3uyxVo4JJ/NQggh6sqv+X7TaLNYa61Paq23lf+cDewDaq4gLoQQogEoirWTw0et3q1UvFIqWSmVqpR60EG7q1Lqg/L2TUqp9pXaHip/PVkpFXepPpVSsUqpbUqpHUqpH5VSEb9r6kIIIYRoVBptgFxZ+ZehGGBT+Ut3KqV2KaXeUkq1bLCBCSGEMO9BdvS4FKWUE/AykAB0BSYqpbpWOWwykKm1jgCeA54qf29XYALQDYgHXlFKOV2iz1eBv2ito4H3AdmuIIQQQjQhjT5AVkp5AZ8A92itL1D25aYDEA2cBBymUFZKTVVKbVFKbTlz5oyjQ4QQQtSBinuQHT1qoR+QqrVO01oXAkuBcVWOGQe8U/7zx0CsKruhbRywVGtdoLU+CKSW91dTnxqoqHfiA5z4TZMWQjSImuoQ16a9tLTUpoTUbz3HpW5h/L3jrIs+SktLG8U4tdaXZa5CVGi0SboAlFLOlAXHS7TWnwJorU9Xav9/wApH79VaLwQWQtl9TvU/2qYr1L/6QvFCiKufBop1tddj/ZRSlW80XVj+73OFYOBopefHgKq1OcxjtNbFSqkswLf89Y1V3ltxK051fU4BvlJK5QEXgAHVz0wIcaWZPn06mZmZZv3eiozHFTZv3sy9995r1giOioqySRCllGLcuHG0adPGrL1bub4vlGXNfuedd8z6vWFhYTbt+fn5xMXF0a9fPwzDYMiQIXYJoubNm8fWrVsxDIPExEQzu3OFo0ePcsMNNxAfH4/VaqVPnz52ybBuv/12CgoKMAyDuLg4fHx8bNrXrVvHww8/bI6zS5cudsmwxo4dS/v27TEMgxEjRtglw3r77bf56KOPMAwDwzBo27atTfvFixeJj483azsPHjzYpuYywJw5c/jll1/MWsX+/v427ampqdx8880kJCRgGAa9evWy+zuZNGkSTk5OZv1ob29vmz5Wr17NvHnzzHF26tTJpr20tJT4+Hg6depkztVRMjYhoHEn6VKUrRhkaK3vqfR6oNb6ZPnPM4D+WusJNfUliUDq14hvpWatqFvfjZTa2vWlPpJ0terir0e/9SeHbR8Oer3G8ymlrgfitNZTyp/fBPTTWt9V6Zi95cccK39+gLJV4seAn7TW75W//ibwFWW7pxz2qZT6FHhKa71JKXUf0KniOHF5yWezqM4999xDdbv/jh49yrp164CywMrf35/g4GCCg4PNkk2ffvop+fn5AHh6eprtAQEBODk5kZSUxI4dO4Cyurlt2rQxj/Hw8KCoqIiPPvrIPKePj4/Z7ufnh1KKjRs3kpaWBoCzszOBgYGEhIQQFBSEi4sLGRkZrFq1yuzD19fX7KMiqP/mm284e/YsAG5ubmZ7mzZtaNasGYcOHWLDhg3mXAMCAggODiYkJAQvLy+01nz88ccUFRUB4OXlZTNXi8XCrl272LNnDwBOTk42c3V3d6egoIBPPvnEHGeLFi3Mdl9fX5RS/Pjjjxw5cgQAFxcXc66BgYG4uLhw5swZVq9ebfbh5+dn9lGR4XrlypVkZpYtqLi7u5vtrVu3plmzZhw4cIBNmzaZc23durU5V09PT7TWfPDBB+bqv7e3t9mHv78/FouF7du3s2/fPvPvfcyYMeYFioCAgFr85onGrKnUQR4M3ATsVkrtKH9tNmX3kkVTtmhxCLi9YYYnhBACQGtV0wrypRwDQis9D8F+23PFMceUUs0o2xqdcYn32r2ulPIHemqtK/JZfACsQghxRTl06BAnTji++yErK8v8WWtNZmYmWmsuXryIj48PSimbLdS5ubmcOnWKgoICMjIyzOC1QmlpKefOnaO0tJTs7Gy8vb3ttupmZ2dz8uRJ8vLyOHfuHE5OTmRnZ5vtRUVFnD17luLiYrKysvDw8CAvL8/huHNycmjRogUWi4WCggKzPT8/n/T0dAoLCzl//jyurq5mQOlors2bNzdrFlfIycnh1KlT5Ofnk5GRgbOzM+fPnzfbS0pKOHfuHCUlJWRnZ+Pl5WW3dfnChQsopcjLy+Ps2bM4OTmRk5NjthcWFtrM1d3d3aYdMM+Zk5ODj48PFouFwsJCsz0vL4/Tp09TUFBAZmYmrq6unDt3zmauGRkZlJaWmnOt6uLFi5w8eZL8/HzOnTuHs7Ozze9GTk4O+/fvZ//+/aSlpeHv72+3ui6arkYbIGutfwQc/SZLzWMhhLiCaKC49DcHyJuBSKVUGHCcsqRbf65yzOfALcBPwHjgW621Vkp9DryvlPo3EAREAj9T9tnhqM9MwEcp1VFrnQKMpqxCghDiCvLZZ59V2zZ9+nSaN29ubrWNjo62CXySkpKIjY0lISEBq9XK6NGj7bbrjh07lvDwcHMbdseOHW3aP//8c+6++26z/ZprrrHZrltUVESvXr3o37+/uUIZHGxbaOWZZ57hnXfeMcdZtXbymTNniImJITExEavVSkJCgl3t5KlTp+Lr62v2UbV28vbt2xk7diyJiYkYhsGoUaNsaidrrYmNjTW3HTuqnfzBBx8we/Zs8xxVaycXFBTQs2dPhgwZgtVqJTExkcDAQJs+HnvsMT755BOzj6q1k48fP07fvn0ZN26cuTW+au3km266ydz2brVa6datm81cN2zYwPXXX29uJx85cqTN1nitNUOGDCEqKgqr1YrVarXbGi9EhUa7xbouyTau+iVbrEVdky3W9ac+tlj7dG6thyy80WHbV9csuOT5lFJjgecBJ+AtrfUTSqnHgC1a68+VUm7AYsqqGWQAE7TWaeXv/QdwK1BMWTLHldX1Wf76Hynbml1KWcB8a0Vf4vKSz2bxW2RkZNgFkpWdP3+e5s2b293PW6G0tJSsrCy7e5ernqNly5bVrjjm5eWhtba7d/nXjPPChQu4u7vb3bv8a/rIzMw0V2gdKS4uNldxazpHTXPNzc1FKWV37/KvGWdWVhaenp529y5XqFgdv9RcW7RoUe04i4qKyM/Pt7sYIpqOprLFWjQSnXzSG3oIQogGVupww0/taK2/osruIK31I5V+zgeur+a9TwBP1KbP8teXAct+82CFEA2qpiAKsFuZrMpisdQYHNfmHDUFi7Xtw9G24V/bx6Xm0axZsxqD49qco6aLALXt41JjUEr97rk6OzvXeLFBiMokQBZCCFGvtP5dW6yFEEIIIS4bCZCFEELUq7I6yBIgCyGEEOLKJ99YhBBC1LsSbXH4EEKI+rB9+3bef/99m0zPlZWWlrJgwQJ27dpll5W6wn//+18+//xzcnNzHbZnZ2ezYMECs5yTIx999BHffvtenhJfAAAgAElEQVStWWqpqrS0NN58801OnTpVbR9vvPEGmzZtssm+XdnPP//MBx98YJOlubLi4mJefPFF9u7dW+1cV61axZdffmmXXbtCZmYmL7/8MocPH652nEuXLmXt2rUUFxc7bE9OTubtt98mPd3xrXdaa15//XW2bNlS7Vw3bNjAxx9/zIULFxy2FxYW8uKLL/LLL79UO9cVK1awcuVKs9SXEFXJCrKod108Tjb0EIQQDUhrKNVSPkMIUTe2b99uUwKpqjNnznD48GFmzZpFUVGRmWV58ODBtGvXjtLSUpKSkli2bBnTp0+nTZs2DB48mCFDhtCrVy9cXFw4fvw4+/bt4+GHH8bFxYU+ffqYxwQEBJCXl8eBAwd47bXXmD59Ou3bt2fIkCFmpmQnJyfS0tLYsGEDL7/8Mh4eHgwcOJAhQ4YwcOBAfHx8yMrK4vDhw8yePZspU6bQtWtXc5yRkZEopfjll1/4+uuvue2222jZsqU5hn79+uHu7k56ejqHDh1i5syZaK2Jjo42jwkNDaW4uJhffvmFjz76iLvvvpvAwEBznDExMTg7O3P06FH27NnDY489hqurK3379jXH4efnR05ODgcPHuT555/nzjvvpEOHDuY5unbtipOTE6mpqaxbt46FCxfi5eVlznXAgAE0b96czMxMjhw5wv3338///M//EBUVZfbRoUMHlFIkJSXx1Vdf8be//Q1fX1+zvW/fvri5uXHq1CnS0tK47777UErRq1cvcy5BQUEUFRWRnJzMkiVLuPvuuwkJCTH7iI6ONpOAnTp1ittuuw1PT09Gjx5tZhpv3br15foVFlc4yWKNZMqsby/sG9XQQxBXmbu7/Lehh3DVqo8s1l4dA3X3l25x2LYx7qk6P5+4Oshns6hOWFgYhw4dauhhiKuIk5MT06dPZ+7cubVKkCYaH8liLYQQ4oqhgRK5B1kIUUeWLVtGYWFhte1nz57l8OHDzJgxg+LiYmJiYsyVxtDQUEpLS9m3bx9LlixhzZo1BAUFMWTIEIYOHWquqp44cYJ9+/Yxe/ZsXF1d6devn7mq6u/vT35+PgcOHODZZ58lKSmJDh06MHToUJtV1YMHD7J+/XoWLFiAl5cXgwYNMleQmzdvTlZWlrmqmpGRQVRUlNlHxapqcnIyX3zxBR999BG+vr7mOCtWVStWkGfMmIHWml69epl9BAcHU1xcTHJyMosWLWLdunWEhISY7RWrqseOHWP37t3MnTsXNzc3+vfvb87V19eX3NxcDh48yLx589i/fz+RkZHmOLp06YLFYiEtLY3vv/+e1157jebNmzNo0CCGDh3KgAED8PLy4vz58xw5coSZM2eSnZ1N9+7dzXGEhYWhlGLfvn0sW7aM5cuX4+/vb/6d9enTBzc3N06fPk1aWhr33nsvFouF3r17m30EBgZSVFRESkoKr7/+Ops2baJt27bmOHv06GGuIO/evZspU6bg5eVFXFwchmEwduxY/P39L9evsLjCSYAshBCifumybdZCCFEXoqOjL3nM9u3beeedd4iLi3NY2qlfv37k5eXxwgsv0LVrV4f1c729vVmxYgUjR450WLopJiaGvLw8xo4dS/v27R2eo1mzZvzpT39i8ODBDuv8pqWlMX/+fMaOHUtAQIDDPoqKirj//vvp1auXw5rGmzdv5j//+Q9jxoxxuPrZr18/cnNzWbhwIZ06dbKba79+/fD09GTlypUMHz4cNzc3uz569uxJfn4+VquV0NBQh+dQSvHnP/+ZgQMHOpxrSkoKL730EgkJCfj5+dm19+3bl8LCQubMmUN0dLTDv5MNGzbw0UcfMXr0aIc1jfv27Utubi6LFy8mMjLSrh3KtuB//fXXXHPNNbi6ujo8RjRtssUa2cZV32SLtahrssW6/tTHFmuPyEDd+YXJDtu2Jz4hW6yFQ/LZLIQQoq7IFmtxRYl0rT4zoxCiKVCUlEqSLiGEEEJc+eSmMCGEEPVKaygttTh8iKuLUuotpVS6UmpPpddaKaVWK6X2l/+3ZUOOUQghhKiJfDsRQghR70q1cvgQV523gfgqrz0IrNFaRwJryp8LcVmcO3euxvasrKxqaxTXto+MjIxq6/YCFBUVVVujuPI5arrtMScnp9oaxbUd5/nz56utUQxldYhrM9eaxllYWEh2dvbvGufFixdrLONVmz7Onz9PSUlJte21matouhptgKyUClVKfaeU2qeU2quUurv8dblSLYQQV5jSUuXwIa4uWusfgIwqL48D3in/+R3g2ss6KNGkvf7660RFRfHQQw+xYcMGu6ApLy+Pdu3aMWHCBJYsWUJGRtVfX5g1axYDBgzgiSeeYOfOnXYBYmpqKsHBwUyZMoXly5eTk5Nj096sWTMMw2DUqFE8//zzHDhwwO4cK1euJCIignvuuYc1a9bYZem2WCx0796dcePG8cYbb3Dy5Em7Pp5//nl69uzJP//5TzZu3GgXtGdnZxMaGspf/vIXli5dyvnz523alVJMmzaNwYMHM2/ePPbs2WM31927dxMSEsLtt9/OihUryM3NtZtrbGwsY8aMYcGCBQ7LcX366ad07NiRmTNn8t1339ldoNBa06lTJ6677joWLVpEenq6XR/z5s2jV69ePPLII2zevNlurmfPniU4OJibb76ZDz/80O4ChVKKyZMnM3ToUJ5++mn27dtXY+AvmpZGm6RLKRUIBGqttymlvIGtlH3oTgIytNZPKqUeBFpqrR+oqS9JBFK/9h4JbughiKtMt7bHG3oIV636SNLlFhGs2z19u8O2lD/NkSRdVxmlVHtghdY6qvz5ea11i0rtmVrrS168ls9mUZ0//OEPnDhxotr2c+fOmUFVaWkp+fn5ZluzZs1o3rw5Fy9eNDMt5+fn2wRYXl5eWCwWCgsLsVgsFBcX2wSsLi4ueHp6kpubi5OTE4BNoKiUwtvbm5KSEkpLS1FKUVRUZBMIurm54ebmRl5eHk5OTmitbVaILRYLPj4+5OXloZRCKUVBQYFNgO/h4YGzszMFBQVYLJZq55qTk2OO09FclVIUFxeb/606Vy8vL5s+qs61efPmFBcXm3MtLCy0WamumGt+fj4Wi8Vurk5OTjRv3rzGuXp6etKsWTNzriUlJTarzI7mmpeXZxP0ent706JFC1q0aIGLiwtnzpzhyJEjZnuHDh2wWq384Q9/YMSIEQ6zaIvGq0kk6dJanwROlv+crZTaBwRTdqV6ePlh7wBrgRoDZCGEEPVIg5bVYlELSqmpwFSAtm3bNvBoxJUqIiICHx+fatuPHz9uBjf5+fk2q60tW7YkKCiIs2fP4uLiYh5fERS6u7sTGBiIxWKhoKAApRTZ2dmcPXsWKAtcfX198ff3JyMjA2dnZ7TWHD582AzGvLy8CA4OprCwkJKSEpRSZGRkmKuYzZo1w9/fHx8fHy5cuICTkxMlJSU2wZqPjw8hISFkZWVhsVhQSnH69GkzOHVxcaFNmza4ubmRk5ODxWIhLy+PU6f+LzFqq1atCAoK4syZM+Zcjx07ZgbIHh4eBAUFAWVbo5VSXLhwwdx6bLFY8PPzw8/Pj8zMTJo1a4bW2mZV2Nvbm+DgYDPwVkpx7tw5Lly4YM41ICCA5s2bm3MtKiri2LFjdnOtOAfAqVOnzCDa1dWV1q1b4+rqSm5uLhaLhdzcXE6fPg2UBem+vr60adOGc+fO4ezsDMCRI0fMINvT05OgoCBCQkIICAgwg+iKP3M3Nze6dOlCly5dHJbCEk1Low2QKyu/Wh0DbAJalwfPaK1PKqXsi8oJIYS4rLTcb9yUnVZKBZZ/JgcC9vsly2mtFwILoWwF+XINUDQu//73v2t97Jw5c0hKSsIwDMaOHWtXf3f//v3cdNNNJCQkYBgGMTExdsHRpEmTUEphGIbD+rurV6/miSeewDAMDMOgY8eONu3FxcWMHTuWTp06YbVaGT58uF393ddff50vvvgCwzCwWq0EB9vuvsvIyMBqtTJs2DAMw2DAgAFmkFfhwQcf5NChQxiGQXx8PL6+vjbte/fuZcqUKSQmJmIYBj169LCb68SJE/H09MRqtTJq1Ci8vLxs2r/44guef/55c5wRERE27YWFhcTHx9O9e3cMw2DYsGFmcF7hhRde4NtvvzX/TiqC9AqnT59m3LhxxMbGYhgG/fr1s6v/PGPGDNLT07FarcTHx9Oype2mlK1btzJ9+nSsVitWq5WoqCibuWqt+dOf/kSvXr0wDIPY2Fg8PDwQAhrxFusKSikv4HvgCa31p7XdylXlKnXvw4cPX7YxNzWyxVrUNdliXX/qY4u1a4dgHfK/f3fYljbhn7LF+irjYIv1M8C5Src+tdJa33+pfmSLtagLpaWldsHVr2mviz4qVlZrWpW8EsaptUZrLXMVV6UmscUaQCnlDHwCLNFaf1r+cq2uVMtV6svH30n+eIVo0mSLdZOhlPoPZbc5+SmljgFzgCeBD5VSk4EjwPUNN0LR1FwqAKpNgPR7+7gc56iLPi4V2NbFOa6UPmozV9F0NdoAWZX9Vr8J7NNaV95r8zlwC2UfyLcAyxtgeEIIISqT62RNgtZ6YjVNsZd1IEIIIcRv1GgDZGAwcBOwWym1o/y12ciVaiGEuMIoWUEWQgghRKPQaDfea61/1ForrXUPrXV0+eMrrfU5rXWs1jqy/L/2Be2EEEJcPuVbrB09hBCivs2fP58333zTJsNzZdu2bePhhx/m559/tqunC2X3q86ePZsPPvjArp5uhS+//JInn3ySvXv3Oqynm5OTw4wZM/jyyy9tShxV9tZbb/HSSy9RXV6cI0eOMGvWLL7//nubMkqVPfnkk7z99tucOXPGYfvGjRuZM2cOW7ZscTjXkpISHnjgAT7++GMzE3VVy5Yt45lnnuGXX35xONcLFy4wY8YMVq1aZVN2qrLXX3+dV199laNHjzpsT01N5f7772fdunXVzvXxxx9n8eLFZtbtqn744Qcee+wxtm/f7nCcxcXF3HfffSxbtoyLFy867EM0TY0+SVddkEQg9Sv9eNClDxLiVwgIrr7+pfh96iVJV1iIDpx7l8O2w5MelCRdwiH5bBbV+eSTT2oMaI4fP87BgwfN56mpqaxduxaAsLAwoqOjgbIySEoptNa89957FBQU0Lx5c3r27Enr1q3x8vIyyw5t3bqV7du3Y7FY6NSpE126dDFr70JZzd0lS5YA4OfnR0xMDD4+Pnh7e5vZptesWcPBgwdxdnamW7dudOjQAVdXVzN78qlTp1ixYgUAISEhREdH4+zsbI4T4NNPPyUjIwMPDw+6d+9OaGgo7u7uZlbs5ORk1q1bB5TV9e3ZsydQVt5KKUVJSQnvvfceRUVF+Pj4EB0djb+/v81cN23axO7du3FycqJz58507tyZZs2amdm7s7Oz+eCDDwAICAggOjqa5s2b28z1m2++4ciRI7i4uBAVFUV4eDiurq64u7sDZeWmVq1aBZSVdOvZsyfNmjWz+Tv5+OOPycrKwtPTkx49ehASEoK7u7uZFXvv3r389NNPKKWIiIige/fuKKVo0aKFWdN58eLFlJSU0LJlS6Kjo4mOjqZLly5mH4sXL2bNmjW4uLgwYsQIMzt3u3btavnbKBqLX/P9RgJk5EO4vhWcDG/oIYirjGtgWkMP4apVbwHynGoC5P+RAFk4Jp/NojphYWE2tXiFqEu9evXiH//4B3/84x8lkddVpMlksRZCCNEISBZrIUQd2rlzp8MtsxUKCgpstvYuWrSIuXPn0q9fPxISEoiLiyMoKMgMfrKyshg4cCDe3t7Ex8cTHx9Pnz59cHZ2Nvt4+OGHef/99xk6dCgJCQmMGjXKps7w/v37GTVqFOHh4SQkJBAfH09UVJRNNuWJEyeyc+dORo4cSXx8PCNGjMDT09Ns/+abb7jtttvo0aMH8fHxJCQkEBYWZo6zpKSEoUOHkpubS1xcHPHx8QwaNMimpvKrr77KU089xYABA8y5tG7d2uwjIyODAQMG4OfnR1xcHAkJCfTu3dumpvKsWbNYvnw5w4YNIz4+ntjYWFq1amW27969G6vVSmRkpDnXrl27mufQWnPdddeRkpLCqFGjiIuLY/jw4TZ1hpcvX8706dOJjo42/07at29v9lFYWMigQYMoLS015zpw4ECbmsrPPfccL774IoMGDSIuLo64uDhat25ttp8+fZpBgwYRGBho/nkOHjzY5s9r8uTJfPnll2bNZUc1qEXTIwGyEEKI+vc7AmSlVDzwAuAEvKG1frJKuyvwLtAbOAfcqLU+VN72EDAZKAGma62/rqnP8goJj1OW4LEEeFVr/eJvHrwQos5VbGuurcGDB5Oeno6/v7/D9v379/PDDz8QExPjcMVQa82NN97ISy+9ZG4zrurs2bMkJyfTsWNHh+05OTk88sgjDB8+3CZAq6xTp04cPXqUkJAQh+0nTpzggw8+YMCAATYBbWUjRoxg1qxZNsF7Zbm5uWzcuJGePXs6nGtJSQmTJk3irbfewsvLy2Ef6enp7N+/n4iICIftFy5c4KmnnmLYsGE2AW1lPXr04Pjx4wQFOb4N78iRIyxfvpx+/fpVO9f4+HgeeeQRWrZs6bA9Ozubbdu2ERUV5XCuxcXF3Hrrrbz77rs2wbsQssUa2cZV32SLtahrssW6/tTLFut2ITrwH3c7bDt8+/01nk8p5QSkAKOBY8BmYKLWOqnSMX8Hemit/6aUmgD8UWt9o1KqK/AfoB8QBPwXqPj26rBPpdT/ACOASVrrUqVUgNY6/ffMv7FQSnUGgoFNWuuLlV6P11qvutzjkc9mIYQQdUW2WIsrirNyfOVPCNFUKNC/eQW5H5CqtU4DUEotBcYBSZWOGQfMLf/5Y+Cl8pXgccBSrXUBcFAplVreHzX0eQfwZ611KUATCo6nA9OAfcCbSqm7tdbLy5v/F7jsAbIQQgjREBptmSchhBCNSGk1j0sLBirXATlW/prDY7TWxUAW4FvDe2vqswNwo1Jqi1JqpVIqslajbPxuA3prra8FhgMPK6Uqlv3lBnIhhBBNhgTIQggh6pem7B5kRw/wKw9GKx5Tq7zbUXBW9d6g6o75ta8DuAL55duw/h/wVjWzuto4VWyrLr9/eziQoJT6NxIgi0YuKSmpxrJQmZmZ7N+/v8Y+duzYQUFBQbXtx44d4/jx49W2a63ZunUrJSUl1R6zf/9+MjIyqm3Pz8+/ZIKyPXv2kJOTU2372bNnOXDgQLXtANu3b6ewsLDa9iNHjlRbUxrK5lpdneUKKSkpnD9/vtr2nJwc9uzZU+Ncd+/eXW1NaSi7V/pS2c63bdtGUVFRjceIpqfBAmSl1H+VUj0b6vxCCCEuH6UdP4CzWus+lR4Lq7z1GBBa6XkIULUQtnmMUqoZ4ANk1PDemvo8BnxS/vMyoMevnmzjdEopFV3xpDxYtgJ+QPcGG5UQdeDw4cP4+voSHx/Pyy+/zOHDh23avb29sVqtdO7cmVmzZvH9999TXFxsc8zatWvx8/Nj/PjxvPPOO5w5c8am3cPDg65du9K7d2/mzp3L1q1bbYI7pRRvvPEGbdq04ZZbbuHjjz/mwoULNn3k5+fTunVrrrnmGp599lmSk5Nt2t3c3JgxYwbt27dn2rRprFq1yiZbN5QFnr6+viQmJvLaa69x7Ngxm/bmzZsTGxtL165deeCBB/jxxx/tgvZVq1bh7+/PDTfcwOLFizl37pxNu6urKxEREfTr149//etfbN++3W6uL730EoGBgdx6660sW7bM7gJFVlYW/v7+jBw5kn//+992Fyg8PDy47bbbCA8PZ/r06axevdruAsWuXbvw9fXFMAwWLlzIiRO2Hw3e3t4MGjSI7t27M3v2bDZs2GA3188++4yAgAAmTpzI+++/T2ZmJkI0WJIupVQv4FngMDBba32yQQaCJAKpb6WnmsoORXG5WNrUfKVf/Hb1kqSrbagOuu8eh22Hps+6VJKuZpQl1IoFjlOWUOvPWuu9lY6ZBnSvlKTrOq31DUqpbsD7/F+SrjVAJGUrog77VEo9CaRord9SSg0HntFa9/19fwJXPqXUMGC/o89ipdRgrfX6yz0m+WwW1YmKirILcisrLCyscQVUNF1KKZycnHBxccFisVBcXGxzkcHJyYkhQ4YwYcIEpkyZQrNmkq7patEoknRprbcBI5VSfwJWKaU+BZ7WWle/V0IIIUSjpH5jmSetdbFS6k7ga8pKMr1VHsg+BmzRWn8OvAksLk/ClQFMKH/vXqXUh5Ql3yoGpmmtSwAc9Vl+yieBJUqpGcBFYMpvGnjj82egv1IqmbKEXKu01qcAGiI4FqImt99+O1lZWdW2Hz161GYbcW5uLj/99BNQtgobGRlJaWkpvr6+Zq3j7du3m9ubQ0ND8fX1xdXVFU9PT5RSnD17lp07dwLg5eVFeHhZhY5WrVqZZYjWr19Pfn4+FouFsLAwvLy88PT0xN3dHSjbmlyxUtqqVSvatm2LUooWLVpgsVgoKSnh+++/R2uNs7MzERERODk50bJlS7Nc0r59+8yV0jZt2tCmTRucnZ3x9vZGKcXFixfZtGkTAO7u7kRERKC1xtfX1wz2tm7dyvnz51FKERoaSqtWrXBzc8PDwwOlFOnp6ezevRsoW3EOCwsDoGXLljg5OaG15scff6SwsBAnJyfCwsLw8PDA29sbNzc3AA4ePEhaWlnFCT8/P0JCQrBYLLRo0QKlFEVFRfzwww8AuLi4EBERgcVisZnr3r17za3cQUFBBAQE2Mz1woULbN68GShbce7QoYP5Z1sx159//pns7GyUUrRt25bOnTvTuXNn/Pz8gLKt8598UrZpqG3btmYt5OHDh0tw3IQ1aJmn8iyj3YAhlNWdzAce0lovvpzjkKvU9UtWkEVdkxXk+lMvK8ihoTr43hkO2w7eO7POzyd+u/JSTwlAHGVb1b+jLGBeX3Fx4XKRz2ZRV95++2327NmDYRgMHjzYLvA5e/Ys06dPZ8yYMYwdO5aAgAC7Pv73f/+XwsJCDMMgJiYGi8X2LsXdu3fz7LPPYhgGY8aMsavVrLXm7rvvpm3btlitVjp16mRXm/err77iyy+/xDAMhg8fbgabFfLz85k6dSoDBw7EarUSGhpKVQsXLuTAgQMYhsHAgQPtagifPHmSmTNnkpCQQEJCghkoVjZ37lwsFguGYRAdHW03zi1btvDKK69gGAajR4+2q5estebvf/87kZGRGIZBZKT998Bly5bx3XffYbVaueaaa+xqQ+fm5jJ16lSGDRtGYmIiwcFVczPCSy+9xPHjxzEMg/79+9vN9ciRIzz00EMkJiYSHx9Pq1at7PqYPXs2np6eGIZB9+7dHdZLFleHX/P9piG3WP8IhAN7gY3AJuAX4G7AVWtdNVFLvZEP4folAbKoaxIg15/6CpBDZjgOkNNmSoB8pVJKuVNWEzoBGHi5/57ks1kIIURdaRRbrIG/AXu1fYR+l1Jq36XerJR6i7IEIula66jy1+ZSVqqiInPCbK31V3U3ZCGEEL9J7Uo6iQamlPovMFNrvbP8lqevyh9CCCFEk9CQ9yDvqaE5sRZdvA28BLxb5fXntNbP/tZxibpXdHl35YkmwPXSh4griNK//R5kcdndDzynlGrwBJpCCCFEQ7gi6yBrrdNqccwPlCVjEUIIcYVTpY4f4sqitd6mtR4JrKAsgeac8q3WQgghRJNwRQbIv9OdSqldSqm3lFItqztIKTVVKbVFKbWlai07IYQQdUxX8xBXnPIEmsnAq8BdwH6l1E0NOyohfpuMjAyuvfZaFixYwKFDhxwe8/jjjzNz5ky+++47ioqK7Nr37dvHddddx6JFi0hPT7dr11pzxx138Mgjj7B582ZKS+2v/q1atYqbb76ZDz/80GEG7sLCQm644Qaefvpp9u3bh6McQQsXLuSOO+7gq6++sqt/DJCens61117LK6+8wpEjRxzO9eGHH+a+++7jhx9+sKv1DGVZna+//nqHtZ4r5jp58mQeffRRtm3b5nCcn332GZMmTeKTTz4hOzvbrj0vL4/x48czf/58UlJSHI5zwYIF3HnnnXz99dd29Y8Bjh8/zrXXXuuw1nOFBx54gAcffJD169fb1T8G2LhxIzfeeCPvvfeeXa1n0bQ1aBbr30sp1R5YUeke5NbAWcq+dv0LCNRa33qpfiQRSP0qOBne0EMQVxnXwEtuMhG/UX0k6XILDtVt/36vw7b9/7xXknRdQSSBpmgMnnnmGTIzM6ttr1rm6ZdffjGP9/PzIyIigosXL+Ll5YVSiqysLJKSkgBwdXUlPDzczMxckfF6+/btZlAaFBREaGgo+fn5eHh4AHDq1CkOHjwIgKenp1m2qKLebmlpKT///DNaa7PkUGBgIAUFBTalkSrKGrVo0YKIiAgKCwvN8kt5eXns2LHDHFdYWBitWrWiuLjYLI2UlJRkBuD+/v506NCBnJwccz4ZGRkkJycDZSWvOnTogLu7O0opmzJQFXWkg4ODCQ0NJS8vz5zriRMnzDrUXl5eREREoJQy51pSUsLPP/8MgMVioV27dgQEBFBUVGRmqz5w4IB5saFly5ZERkaSl5dnltXKzc01y2o5OzsTFhZGixYtKC0tNUtz7dmzxwzAW7duTfv27cnNzTXneu7cOTMAd3d3p0OHDkRERBAeHo6rqytaa1588UVyc3OxWCwMHjzYLPPUuXNnyWh9lWkUWazrQtUAubZtVcmHcP1KPx7U0EMQV5mA4BMNPYSrVn0FyO3+5jhATnlEAuQriVIqCscJNFFK7dNad7lcY5HPZlGdvn37cvTo0Wrbc3NzycnJMZ9XXdFVSpmBasXPVX/lLRaLeYyjPiqC3t/bR8V7HPVROUD7ree4HHOtOs7azNXROC/HXF1cXHBzczNrU589e9Zmdblz584YhsEdd9xh1n8WVyjbGBMAACAASURBVIdf8/3mqtpirZQKrPT0j0BNicCEEEIIUYnWeo+j4LhcbRJoClHvNm/ezKlTp6p9XLhwgZKSEkpKSigoKKBjx47ExMSYW6CLi4vRWlNaWkpJSQnz58/H19eXm266ydwCXVJSYranp6fTokULhg4dytNPP01SUpJdH1OnTiUkJMTcAp2Xl2fTx44dO3BzcyMhIYGXX36Zw4cPm+0Vx1xzzTV07tzZ3AJdWFho0/7xxx/j7e3N+PHjzS3Qlc+Rl5dH+/bt6dOnD48++ihbt26lpKTEZpyPP/44/v7+5hboij+rivbjx4/j7e3N8OHDefbZZ0lOTrbr46abbqJdu3bmFui8vDybcW7cuBE3NzcSExPNLdCV51pcXEz//v3p1q0bDzzwAD/++CNFRUU2fSxevBgfHx9zC3RFIFvRfvHiRYKCgujfvz//+te/2LFjh904//GPf9C6dWsmT57MZ/+fvTsPj6o8H///vrOHhCWEkARIACEi+5KwhAgCspNxr6KWWkWpVr+u7U+ttqitdWuVVuv2cbco7hUVFUXBHWRTiOw7IQuEkH2f5/fHORknySQETJiZcL+ua8zMec48c58h5pz7PNv//kdxcTEVFRUUFBSQnZ3N999/T1hYGJMmTeKRRx5h27ZtbNq0iQcffFCT45Oc37Ygi8irwASgC5ADzLdfD8PqYr0b+F1zZuDUu9StS1uQVUvTFuTW0yotyN0STK/feW5B3nKXtiArz/TcrFpCQUEBRUVF9OjRo9F9Nm/eTFJSEoGBgR7Ls7OzCQ4OJjo62mO5MYZNmzbRv3//Rrvl7tmzh+joaFf33/oqKyvZu3cvffv2bTTO7du3k5iY6OpOXV9+fj5lZWV069b4ddfRjjUrK4uwsDCiojxP42OMYfPmzU12Qd69ezddu3Z1dcmur6ysjKysLE45pfEheNu2baNXr16u7tT15eXlUV1dTWxsbKN1bNq0iX79+hEQ4Lk9MDMzk8jISDp27NhoHartOGm6WLcUPQm3Lk2QVUvTBLn1tFqCfFUjCfI9miArz/TcrJRSqqUcy/WN19ZBVkopdXIQdEknpZRSSvkHTZBVqztYo7MAqpbV1dsBqGNjQLSzklJKKaX8QJuapEsppZSPcjbyUEqpVrJu3TpWrlzpcV1isMb9vvnmmx7XJa61YsUKMjIyPK73C3Dw4EE++OADysrKGq1jyZIlrmWRPNm6dSvLly/3uC4xWON+33rrLY9rMNdavXo1q1evbvRYy8rKXJNyNebzzz9n8+bNjR5rVlYWH374occ1mGu9//77Tc4wvmnTJr788stGj9XpdPLmm29y6NChRutYuXIl69atazTO4uJi3n77bYqLixut49NPP2Xbtm2NlquTm7YgK6WUanXaxVop1VJycnLqLM1TX0lJCUVFReTk5JCenk7nzp2ZPHkyU6ZMYfz48YSHh5OTkwPAE088wezZsxkzZoxrn969e1NQUEBZWRlbt25lwoQJJCQkMGXKFKZMmcKYMWMQEfLy8jDGcMMNN5CZmcm4ceOYMmUKkydPJjY2lsOHD1NZWck333zDrFmzOO2001zlw4cPp7KykoKCAkpLSznrrLMQESZOnMjUqVOZMGECnTp1Ijc3F6fTydtvv80FF1xAcnKyK87TTjuNkpISiouLyczM5JxzzqFr166u8nHjxhEaGupKrB955BFmz55Namqq61gSExM5cuQI5eXlZGRkMGnSJHr16uWKc/To0RhjOHz4ME6nk9/97nccOnSI8ePHu/aJiYkhLy+Pqqoqli9fjsPhYODAga44hg4d6po9uqioiOnTp7tmj54yZQoTJkygQ4cO5OTkYIxh0aJFXHjhhSQnJzN16lSmTJlCUlISxcXFlJSUsHfvXi688ELi4uJcn5GWlkZISAgHDx4E4L777mP27NmMHTvWdazuE7Xt2bOHKVOm0K9fP9LT03E4HKSlpbnWglYnN52kC50IpLVl7O3u7RBUGzMwMdPbIbRZrTFJV3hcgunzG8+TdGU8pJN0Kc/03Kwa07t3b3bv3u3tMFQbExUVxe9//3v+9Kc/NToDt/JfOkmX8il7qj0vFaDU8Rro7QDUsdN7sUqpFvLYY49RWlraaPmBAwfYs2cPFRUVPPnkkzidTrp3705ycjIpKSn06dOH2psvS5cuJSMjg/DwcIYOHUpKSgrDhg3j4MGD5Obmkpuby8KFCwHo06cPycnJJCcnExMTw4YNGwB47bXXOHDgAB06dGDEiBGkpKQwZMgQtm/fTlFREVu2bGHJkiUEBATQv39/Vx3BwcFs27YNYwxPPfUUZWVlxMTEuOLs378/P/zwA1VVVXz77bd89913BAcHM3jwYFJSUhgxYgSlpaXs27eP0tJSnnrqKQASEhJcn9G7d2/WrFkDWF29t2zZQrt27Rg2bJjrWLOysjh06BAHDhzgtddeAyApKclVR1RUFBkZGQAsXLjQtS507bEOGjSIrVu3UlJSQkZGBkuXLiUgIIABAwa44gwICGDHjh3U1NTw5JNPUllZSWxsrOsz+vfvz9q1a6mpqeHLL79k9erVhISEMGTIEFcdhYWFZGZmUlRUxDPPPANAYmIiKSkpJCcnk5CQwLp16wBYvHgxO3bsICIiguHDh5OSksLQoUOJiIgAYMOGDfz1r39FREhNTcXhcOBwOBgwYECjy1epk4cmyEoppVqddrFWSrWUWbNmNWu/5cuXk5SUhMPhoE+fPnXKLrnkEiorK2nXrh3/+te/GDdunMf1hV9//XUmTJjArFmziI+Pb1Cem5tLREQEs2bNYtSoUR7X3H388ceZM2cO06dPp1OnTg3Kf/zxR7p27erqmuyeoF1yySUYY7j33nu54447mDRpksfWzU8++YSBAweSnp5O796965RdeumllJWVER4ezuTJkzn99NM9ri+8cOFCpk2bxsyZMz2uL1y7brDD4SA5Odnjsf773//myiuvZOrUqR7XF16zZg3du3fH4XA0WEv54osvxul08te//pW7776bSZMmERYW1qCOJUuWMHz4cNLT00lMTKxTNmfOHIqLiwkPD2fatGmMHTvWY7fp0tJSXnzxRWbMmEFMTEyDcnVy0y7WaDeu1rZk5yBvh6DamJmnbPR2CG1Wa3SxbhebYPpe6rmL9YZHtIu18kzPzUoppVqKdrFWSinlW/RerFJKKaX8gCbIqtVtq4jzdghKKS/TLtZKKaWU8ge6DrJSSqnWZawE2dNDnTxEZLeIbBCR9SKifadVq6mqqmqyvLq6utH1gptbR1VVVaPr8B5LHU1xOp2Nrhfc3Dqqq6tbPc6WqKOmpqbJpbua+xm/9FiVAk2QlVJKnQCaICvbRGPMMB13rlrTe++9x9ixY7nvvvvYuHFjg6TJ6XSSlpbGvHnzeO+99zzOiL1gwQKmTp3Ko48+yq5duxqU5+XlMWzYMG6++WY+//xzj4nXDTfcwHnnncdzzz3nWnfZ3bp16xg+fDh/+ctf+P777xsk7SLC2WefzZw5c3j99dcpKChoUMcbb7zBuHHjePDBB/npp58aHGtVVRWjR4/mmmuuYcmSJZSXlzeo4/7772fGjBn85z//Ye/evQ3Ks7KyGDp0KH/84x/54osvPCbtV199NRdccAEvvviiay1id9999x0pKSncddddrFmzpkGcIsL06dP57W9/y1tvvUVRUVGDOl5++WUmTJjAP/7xD7Zs2dKgvLy8nJSUFK677jo+/vhjKioqGuxz9913M2vWLJ588kn279/foFwp0Em6AJ0IpLX9a9Nkb4eg2pgb+n/q7RDarFaZpKtrgul3gedJutY/oZN0nSxEZDeQYow51Jz99dysGnP11VeTm5vbaHlmZiarVq1yvW7Xrh1xcXHEx8fTpUsXwJr1uTYxDggIoGvXrsTFxREXF0d4eDibNm1i8+bNrjrat29PfHw8cXFxdO7cmdLSUpYvX05lZSUAQUFBrvfHxsYSEhLCqlWryMzMdNURFRXlqqNjx47k5eXx1VdfuRLj0NBQV5wxMTEEBQXx+eefc+TIEcBKIrt06eKqIyIigr1797qWcao91vj4eOLj44mOjsbpdPLpp59SVlYGQGBgYJ1jDQsLY8OGDWzfvt1VR4cOHVyfERUVRXFxMStWrHDdBAgODiY2Npb4+HhiY2MJDg7m22+/JTs721VH586dXXV06NCBgwcP8vXXX7sS47CwsDrHGhgYyLJlyygsLHQda0xMjGufdu3asWvXLtavX+/6jIiICNdnREdHU11dzbJly1w3AWqPtXaf0NBQDh8+zIoVK1x11M6G3dTM3KptOCkm6RKR54B0INcYM8je1hl4DegF7AYuNMbkeytGpZRSuLpYq5OeAZaKiAGeMsY8XX8HEZkHzAMaLN+iVK38/Hzy8vIaLa9NsmpVVFRQVFRESEgIxhgCAgLqtII6nU5KSko4cuQIgYGBREREUFxc3KCOwsJCgoODcTqdVFRU1Gnxrampobi4mPz8fAICAggLC3MlpbXKysooKCggKCiIqqoqCgoK6rSkVlVVUVxczOHDhxERgoODXQk4gDGG0tJSV5zl5eUNjrWysrLOsQJ1jrWmpqbOsbZr165BC3ptvcHBwdTU1FBWVlbnWKurqykpKXEda2hoaIOWafdjraysdCX57nHWHitYSbd7K3ztsdbWERkZ2aBVufbfNTg4GGMMTqezTjftmpqaOt9XeHh4gzoOHTpEXl4eeXl5VFdXe1zqS518/DZBBl4AHgNectt2G7DMGHO/iNxmv77VC7EpN5tKG64bqJQ6eQi/LEEWkenAv4BA4BljzP31ykOxzgXJQB5wkTFmt112OzAXqAGuN8Z83Mw6HwUuN8ZEHn/kqp40Y8wBEekKfCIim40xX7jvYCfNT4PVguyNIJXve+2115osX7JkCTfddBMOhwOHw0FaWlqdtXCrq6sZNWoUvXv3xuFwMHPmTLp27VqnjgULFvDyyy/jcDhIT09nxIgRdVoX8/LyGDlyJOPGjcPhcDB16lQ6dOhQp47f//73ZGRkuOro169fnXV/f/zxR8466yxmzZqFw+FgwoQJDdb9nT59OgEBAa46EhIS6pS/9dZb/PnPf3aVp6am1jnWyspKkpOT6d+/Pw6HgxkzZrha0Wvdd999vPPOO66W1GHDhtWJMzs7mzFjxjBp0iQcDgeTJ0+mffv2deq44oor2LVrl+s7T0pKqlO+atUqLrroIlecZ5xxBqGhoa5yYwyTJk1yrbM8a9YsunfvXqeO//73vzzwwAOuOEePHk1gYKCrvKysjBEjRjBs2DAcDgfTp0+nc+fOdeqYP38+ISEhrjgHDx5c51iVAj/vYi0ivYD33VqQtwATjDFZIhIPLDfG9DtaPdqNq3VdvWaOt0NQbcyTyS97O4Q2qzW6WEfEJJj+Z9/ksWzNs7c0+XkiEghsBaYA+4HvgYuNMT+57fN7YIgx5moRmQ2ca4y5SEQGAK8Co4BuwKfAqfbbGq1TRFKAG+x6NEFuBSJyF1BsjPlHY/vouVkdr6KiogYJnLvasanuCdqx1lFSUkJYWFidBO1Y6ygqKiIyMrLRBM3pdFJWVkZERMRxf0Z5eTkBAQFNtow251jDw8Ob7H78S4+1urqayspK2rVrd9yfUVZWRlBQEMHBwcddh2q7juX6pq11tI81xmQB2D+7NrajiMwTkdUistrTZAJKKaVaiGnicXSjgO3GmJ3GmEpgEXB2vX3OBl60n78JnCnWVdjZwCJjTIUxZhew3a6v0TrthPwh4P87voNVnohIhIi0r30OTAU2ejcq1VYdLQEKDQ1tMjluTh0RERFNJsfNqaN9+/ZNtl4GBAQ0mRw35zPCwsKO2m24Ocd6tLG5v/RYg4KCmkyOm/MZ4eHhTSbHzalDKWh7CXKzGWOeNsakGGNSYmJivB2OUkq1aU3MYt2l9mal/ZhX763dgX1ur/fb2zzuY4ypBgqA6Cbe21Sd1wGLa2+2qhYTC3wlIj8Aq4APjDEfeTkmpZRSqgF/HoPsSY6IxLt1sW58ikN1wmwpaLQhXyl1kmhiDPKho3R58tTkUL/tubF9Gtvu6eawEZFuwK+ACU3Eo46DMWYnMNTbcSillFJH09ZakBcDl9nPLwPe9WIsSimlwJrFupFHM+wH3Gel6QEcaGwfEQkCOgKHm3hvY9uHA32B7faSRO1EZDtKKZ+3detWHn/8cY/r+NZ69NFHG13HF+Drr7/mpZde4tAhzyuRVVZW8uCDD7J27doG6/jWWrx4MW+//bbHdXwBDh48yD//+U+2bt3aaJwvvPBCo+v4AmRkZPDUU0/VWULKnTGGBQsW8PXXX9eZ1dnd8uXLWbhwoWsW6frKy8t58MEH+eGHHxo91rfeeov//e9/lJSUeCw/cOAACxYsYMeOHR7LAZ555hk+/fTTOrN1u1u/fj3/93//R1aW5049TqeThx9+mO+++67BOtK1Pv30U1599VXy83VhG9U8ftuCLCKvYt3l7yIi+4H5wP3A6yIyF9iL1RKglFLKi37hLNbfA0ki0hvIBGYDl9Tbp/bm6LfABcBnxhgjIouBV0TkYaxJupKwuveKpzqNMRlAnCtukWJjTN/jjlwp1Sq+/fbbBssKOZ1O5s+fz7XXXkv//v1JTk4mNTWVfv36ucbP/vDDD1x//fVERUUxYsQIxo4dy8iRI4mMtObiKywsZO7cuTidToYOHUpycjJjx46lZ8+ervGzy5Yt49ZbbyU+Pt5VPnz4cNeY5gMHDnDNNdcQEhLCiBEjGDlyJKmpqcTFuf608Oyzz/KHP/yBU045xRXn4MGDXWOat23bxuWXX05kZCTJycmMHj2a0aNHExUVBVgTWt12221cffXVDBgwwBVHUlKS61jXrl3LTTfdRHR0tOszUlJSXGOa8/LymDNnDiLCsGHDSElJYezYsSQkJLiOdcmSJdx66610796dlJQUxowZw/Dhw11jmjMzM7nhhhsIDQ0lOTnZdazuM4I/+uij3HTTTfTt29cVx8CBA13HumXLFq666io6dOjAiBEjGDNmDKNHj6Zjx46AdVPipptuYt68eQwePNhVR9++fV1xrly5kltuuYWYmBiSk5MZM2YMI0eOJDw8HLBuSlxyySUEBga6Zh33NNO2UrX8ehbrlqIzZbauiZ/d4u0QVBvz+aR/ejuENqs1ZrGOjE4wg6fd6LHsu1f/cNTPE5GZwAKsJZmeM8bcKyL3AKuNMYtFJAx4GasF+DAw2+7Si4jcAVwBVAM3GmM+bKxOD59brLNYe4+em1Vjevfuze7du70dhvJjAQEBXH755dx3333oXEQnh2O5vvHbFmSllFJ+woB47uXXvLcbswRYUm/bX9yel9NIjyE78W2Q/Hqq08M+mhwr5YM+/PBDqqqq6myrrq5m6tSpFBQUkJqaSmpqKmeccQY9evRw7fPkk0/y+OOPc8oppzB27FjOOOMMRowY4Zr5+NChQ0yZMoXQ0FDGjRtHamoq48ePr7Nu8G233caSJUsYPHiw6zMGDhxYp5V6zpw5REVFMW7cOE4//XTGjh3rWiPZGMPs2bPZsmWLq8V1/Pjx9OnTx9Ui+u677/LnP/+Z7t27k5aWxvjx4xk1apRrjeSKigomT55MWVkZqampjB07lvHjx9dZN3jBggU899xzJCUlkZqayoQJExg6dKjrWLOyspg+fToRERGuGMeNG0d0dLSrjhtvvJHPPvuMYcOGMWbMGM444wz69+/vOtZVq1Zx5ZVXEh0dXedYa1vkjTGce+657N69m1GjRrni6NWrl+tYX3/9df72t7+RkJBAWloa48aNY9SoUa4W+dLSUs4880yqq6tJS0tzfefuLfIPPPAACxcu5LTTTnN9n0OHDnWtB71nzx4cDgft27dn+vTpja4HrVQtTZBVq9t3MMrbISilvE07KymlWshpp53WYNv27dt5/PHHmTZtmisZrW/UqFFcd911nHbaaR6XHFq1ahXvvfceEydOdCWj7iorKzn33HN54oknSExM9PgZWVlZfPHFF6SmproSNHcHDx7ktttuY+bMmY0maFu2bGHNmjUMHz7cY5ybN2/mueeeY8qUKR6XLTLGcPrpp3Prrbdy6qmnNigHaz3gjz76iDPOOMPjklfl5eVcfPHFvPTSS3USb3f79u3jq6++YsyYMR6XvMrKyuKee+5hxowZdO7c2WMdP/30E+vXr2fIkCEej3Xjxo3897//ZcqUKR6XvHI6nUyaNIm7776bPn36ePyM/Px8PvnkE8aPH3/UJa+UAu1iDWg3rtbW97W/eTsE1cZsv+hOb4fQZrVKF+uoBDP0zBs8ln3z1h9b/PNU26DnZqWUUi1Fu1grpZTyKb9gki6llFJKqRNGE2SllFKtSoxBnNpbSSmllFK+TxNk1epqcsK9HYJSysuaueaxUko1W1ZWFvHx8Y2WHzx4kE6dOrkmpqqvpqaGQ4cOERsb22gd2dnZdO3a1TUxVX0lJSVUV1e7liXy5MCBA8THx3scYwvWGNnw8HCP455rHe1Yc3Nz6dy5s8dxzwBVVVUcOXKkyRmbs7KyiIuLazTO2rWdPY17bm6ceXl5REZGehz3DNb46ezs7CbryMnJoUuXLh7HPYM1iVlxcXGdCceUOhae/29XSimlWpA4PT+UUup4/e1vf2PQoEHcfvvtfPPNN9TU1J0uPzc3l7i4OC6++GIWLlzI4cOH65QHBgYyZ84cxowZw7333suPP/5I/bl5Vq5cSffu3bnyyit59913KSkpqVMeEhLCqFGjmDx5Mv/617/YsWNHgzhffvll+vbty4033siyZcuorKysU15VVUViYiLnnHMOzzzzDNnZ2Q3quPPOOxk6dCh33nknK1euxOms+wd0//79xMbGcumll7Jo0SKOHDlSpzwoKIjzzz+ftLQ07r//fjZu3NjgWFesWEGPHj343e9+x/vvv09ZWVmd8uDgYIYOHcq0adN49NFHPS619dRTT3Hqqadyyy23sHz58gazjZeXl9O9e3fOO+88nn/+eXJzc+uUiwi33HILI0aMYP78+Xz//fcNjnX79u3Exsbym9/8hjfeeIPCwsI65SEhIcyYMYPx48fz4IMPsmnTpgbHqlRTdJIudCKQ1tb737pmrWpZu67XtbVbS2tM0tW+Yw8zIu16j2VffHirTtKlPNJzs2rM1KlTyczMpKioiH379rm2d+nShZkzZ9K+fXs+//xzALZu3Up1dTVgJcRpaWnMmDGD559/nqCgIPLy8sjJyXHVkZiYSHp6OoWFhaxduxZjDJs2bXKVh4aGcuaZZzJy5EgWLVpEYGAgBw4cqJOQ9u/fH4fDQUZGBrt27aK8vJydO3e6yjt06MC0adPo2bMnH3zwASLCrl276iSkI0eOxOFwsHjxYkpLSyksLGT//v2u8q5duzJr1ixCQ0P54osvAGv269qbBEFBQYwbN47Jkyfz4osvEhQUxMGDBzl48KCrjt69e5Oens6hQ4f44YcfqKmpYcuWLa7y8PBwzjzzTIYPH84bb7xBQEAA+/fvr5OQDho0CIfDwZo1a9i/fz9lZWXs2rXLVd6pUyemT59OfHw8H330ESLCzp07KS8vB6yEePTo0aSnp/PGG2+4WroPHDjgqiMuLo709HREhK+//hqgTtIbHBzM+PHjmThxIi+99BJBQUHk5OSQl5fnqqNPnz44HA7OP/98Tj/99Ia/VKrN00m6lFJK+RTtYq2UainJycn06tWL7du3uxLk8PBwUlNTOf3004mMjKSyshJjDDt27HAlyP379yctLY20tDR27NiBiLBmzRpXgtypUydXeUFBAeHh4ZSXl7sSZBFh+PDhpKWlMXLkSDIzMxERli1b5kqQ4+LiXHV06NCBbt26kZ2d7UqQg4ODGTVqFKeffjqJiYkUFBQAVrfh2gS5T58+rjry8/MpLi5my5YtrgS5Xbt2pKamkpaWRmhoKDU1NRhj2Lp1q+s7GjhwoKuOXbt2ISKsXLnSlSBHRUUxduxY0tLSyM3NJTIykpKSEleCHBAQwIgRI0hLS2PYsGFkZWUhIixdutSVINeu01wbR2ZmJpmZma4EubZ1PS0tjW7dulFcXAxAZmamK0FOSkpy1ZGdnU1FRQUZGRmuBDkyMtIVZ62amho2b97sSpAHDx7sqmP37t2ICN98840rQY6OjnaVDxky5Jf98qmTgrYgo3epW9vA2x7xdgiqjcm4/yZvh9BmtVYLcsqY/+exbPnS27QFWXmk52Z1NNdccw1OpxOHw8GkSZNo165dnfIVK1bw97//HYfDQXp6Or169apTXlNTw3nnnUffvn1xOBykpaU1GK/8wgsv8N5775Gens7MmTMbjFc+cuQI5513HuPGjcPhcDBixIgG45Xvuusudu7cicPh8LhO89atW5k3bx6zZs0iPT3d4zrNV1xxBWFhYTgcDo/rNC9dupQFCxaQnp5Oenp6g3Waq6qqOPfccxkwYAAOh8PjOs1PPfUUn376KQ6Hw+M6zYcOHeJXv/oVEydOJD093eM6zbfffjvZ2dk4HA6P6zRv2LCBG264gVmzZuFwOBqs02yMYc6cOURFReFwODyu07x48WKefvpp179r/XWay8vLOeeccxg+fDjp6emNrtOsTi7Hcn2jCTJ6Em5tmiCrlqYJcutpjQS5Q4ceJmX0dR7LPv/0dk2QlUd6blZHY4xpdEKplihvS3X4U5xAqx+rOvloF2ullFI+RWr0ZqxSqmUdLQn6peVtqQ6NU6nma5MJsojsBoqAGqBaWyeUUsqLjP1QSimllPJxbTJBtk00xhzydhBKKaUM4tQMWSmllFK+ry0nyMpHtN+ji50qdVIz2sVaKdVyKioqGkzcdCzlxhiqqqoICQk57jqqq6sRkSYnfzpaHZWVlQQHBzfZJdgXjrWqqorAwMAGcu69rAAAIABJREFUk48dSx0n4lidTic1NTUNJlpT6lg1/pvu3wywVETWiMg8bwejlFInPafx/FBKqWN09dVXM23aNB577DH27NnToHzNmjX069ePP/zhD6xYscK1zFMtYwzTpk3j/PPP54UXXqizNnCtV199leTkZO666y5Wr16N01n3Zn95eTlDhw7lsssu480336yzNnCtv/71r4wfP56HHnqozrJEtTIzM0lKSuLaa6/lo48+ci195O63v/0tM2fO5Iknnqiz5nOtr776igEDBnDrrbfy5ZdfNjhWp9PJxIkTufDCC3n55ZfrrA1c6/nnn2fkyJHcc889rFu3rkGcJSUlDBw4kCuuuIJ33nnHtVyTuz/96U9MnDiRhx9+mG3btjUo37lzJ6eeeirXX389S5cupaKiosE+F198MQ6Hg6effprMzMwG5Z988gmDBg3i9ttv55tvvnGt+VyrpqaGtLQ0Lr74YhYuXMjhw4cb1KFUc7TVBDnNGDMCmAFcKyLj6+8gIvNEZLWIrPb0h1EppVTLEWM8PpRS6lj99NNPLF26lJtuuom5c+fy+eef1ynfsWMHW7du5Z///CdXXHEFf//73yktLXWVV1dXs3HjRt5++22uvfZarr76ajZs2FCnju3bt7N27Vruvvtu5s6dy1NPPVUnIcvKymLPnj289NJLzJs3jxtvvLFBArtlyxa+/PJLbr31VubOncs777xTJ/ncsWMHe/bs4fHHH2fu3Lnccccd5Ofn16kjIyODDz/8kBtuuIGrrrqKr776qsGxbtq0iQcffJC5c+fy0EMP1Um0y8rK2Lx5M2+88QbXXHMN11xzjWtd51rbtm1j9erVzJ8/n7lz5/Lss8/WuSGwf/9+9u7dy/PPP89VV13FzTff7Fqn2P1Yly9fzh//+Efmzp3Le++91+BYd+7cyaOPPsqVV17J/PnzG9xU2LBhA++//z7XX3898+bN47vvvmtwrBkZGdx///3MnTuXRx55hMrKSld5YWEh27ZtY9GiRVxzzTVce+21ddaGVqq52mQXa2PMAftnroi8A4wCvqi3z9PA02AtJXHCg1RKqZOFAbSLtVKqhcydO5dbbrmFadOm0bFjxwblI0aM4IEHHsDhcHhcUzg4OJhbbrmFIUOGMGnSpAZrCgNMmjSJbt26eVxTGCAhIYGbbrqJyZMnM3bs2AZrCgNccMEFrvWTY2JiGpQPHDiQO++8E4fD4XFNYbBay2NjY5k6dWqDNYUBRo0axT/+8Q+PawoDREREcPPNN5OSksKECRM8dlGeOnUqSUlJpKen06NHjwblvXv3dn3fja0pPHv2bGbPns2MGTOIjo5uUD548GDuvvtuHA4HQ4YM8Xis1113HT179mTy5MlERkY2KE9NTeXhhx/G4XDQt2/fBuVRUVHcfPPNpKamMn78+Ca7lSvVlDa3DrKIRAABxpgi+/knwD3GmI8ae4+utdi6po2Y7+0QVBvz8dq7vR1Cm9Ua6yB3jOhmxvT3PNpl6Zq7dR1k5ZGem5VSSrWUk30d5FjgHfvOVBDwSlPJsVJKqROgjd2MVUoppVTb1OYSZGPMTmCot+NQSill01mslVJKKeUn2lyCrJRSytcYcOpyb0oppZTyfZogq1bnXP+Tt0NQSnmTTtKllFJKKT+hCbJSSqlWp0s6KaWUUsofaIKslFKqdRmgRrtYK6WUUsr3BXg7AKWUUm2dPQbZ06MZRGS6iGwRke0icpuH8lARec0uXykivdzKbre3bxGRaUerU0QW2ts3ishzIhL8iw5dKaWUUn5FE2SllFKtq7YF2dPjKEQkEPgPMAMYAFwsIgPq7TYXyDfG9AUeAR6w3zsAmA0MBKYDj4tI4FHqXAicBgwGwoErf8GRK6WUUsrPaBdr1eo+cb7h7RCUUl5lwBx3F+tRwHZ7CT9EZBFwNuA++9/ZwF328zeBx0RE7O2LjDEVwC4R2W7XR2N1GmOW1FYqIquAHscbuFJKKaX8j7YgK6WUal1NtyB3EZHVbo959d7dHdjn9nq/vc3jPsaYaqAAiG7ivUet0+5aPQf46JiPVymllFJ+S1uQlVJKtb7GxxsfMsakNPFO8bCt/pTYje3T2HZPN4fr1/k48IUx5ssmYlNKKaVUG6MtyEoppVqZAdPI4+j2Awlur3sABxrbR0SCgI7A4Sbe22SdIjIfiAFubk6AqnmONtmaUkop5Qs0QVZKKdW6DFBT4/lxdN8DSSLSW0RCsCbdWlxvn8XAZfbzC4DPjDHG3j7bnuW6N5AErGqqThG5EpgGXGzM8Q+cVnU1c7I1pZRSyuu0i7VSSqlWZo57HWRjTLWIXAd8DAQCzxljMkTkHmC1MWYx8Czwsj0J12GshBd7v9exJvSqBq41xtQAeKrT/sgngT3At9Y8X7xtjLnnuIJX7poz2ZpSSinldZogK6WUal0GTPNaiz2/3ZpZekm9bX9xe14O/KqR994L3NucOu3tel5sHZ4mRhtdfyd7krZ5AImJiScmMqWUUspNm+xireOclFLKxxz/GGTVNjRnsjWMMU8bY1KMMSkxMTEnICyllFKqrjZ3p9xtnNMUrDvU34vIYmOMduNSSilvMKa5441V29WcydaUUkopr2uLLciucU7GmEqgdpyTUkoprzCYmhqPD3XSaM5ka0oppZTXtbkWZJo5zkkppdQJUjuLtTppNTbZmpfDUkoppRpoiwlys8Y56UQgSil1YhjAOHW88cmusYnRlFJKKV/SFrtYN2uck04EopRSJ4jRLtZKKaWU8g9i2tgsoiISBGwFzgQyscY9XdJUVy4ROYi17iVAF+BQa8fZQvwpVtB4W5M/xQr+Fa8/xQq/PN6expgWvWsoIh9hxeXJIWPM9Jb8PNU21Ds3+zt/+zvi6/T7bFn6fbY8/U5bVkt8n82+vmlzCTKAiMwEFvDzOKcGa2A28d7VxpiUVguuBflTrKDxtiZ/ihX8K15/ihX8L16lTgb6/2XL0u+zZen32fL0O21ZJ/r7bItjkHWck1JKKaWUUkqpY9YWxyArpZRSSimllFLHTBPkhp72dgDHwJ9iBY23NflTrOBf8fpTrOB/8Sp1MtD/L1uWfp8tS7/Plqffacs6od9nmxyDrJRSSimllFJKHSttQVZKKaWUUkoppdAEGQAReUhENovIjyLyjoh0ciu7XUS2i8gWEZnmzThricivRCRDRJwiklKvzOfiBRCR6XZM20XkNm/H405EnhORXBHZ6Lats4h8IiLb7J9R3ozRnYgkiMjnIrLJ/j24wd7uczGLSJiIrBKRH+xY77a39xaRlXasr4lIiLdjdScigSKyTkTet1/7bLwisltENojIehFZbW/zud8FpU5G/ni+9nW+fD3hD/ztmsfX+dM1mT/wletGTZAtnwCDjDFDsNZQvh1ARAYAs4GBwHTgcREJ9FqUP9sInAd84b7RV+O1Y/gPMAMYAFxsx+orXsD6vtzdBiwzxiQBy+zXvqIauMUY0x8YA1xrf5++GHMFMMkYMxQYBkwXkTHAA8Ajdqz5wFwvxujJDcAmt9e+Hu9EY8wwtyUQfPF3QamTkV+dr32dH1xP+IMX8K9rHl/nT9dk/sAnrhs1QQaMMUuNMdX2y++AHvbzs4FFxpgKY8wuYDswyhsxujPGbDLGbPFQ5JPxYsWw3Riz0xhTCSzCitUnGGO+AA7X23w28KL9/EXgnBMaVBOMMVnGmLX28yKsRK47PhizsRTbL4PthwEmAW/a230i1loi0gOYBTxjvxZ8ON5G+NzvglInIz88X/s6n76e8Af+ds3j6/zpmswf+Mp1oybIDV0BfGg/7w7scyvbb2/zVb4ar6/G1ZRYY0wWWH/8gK5ejscjEekFDAdW4qMx292V1wO5WL01dgBH3G5K+drvwwLg/wOc9utofDteAywVkTUiMs/e5pO/C0opF388L/oC/d5ah54zWoA/XJP5A1+4bgxqzcp9iYh8CsR5KLrDGPOuvc8dWF0lFta+zcP+J2Ta7+bE6+ltHrb5wjTlvhqXXxORSOAt4EZjTKHV0Ol7jDE1wDCxxva/A/T3tNuJjcozEUkHco0xa0RkQu1mD7v6RLy2NGPMARHpCnwiIpu9HZBSJ5M2dr72dfq9KZ/kL9dk/sAXrhtPmgTZGDO5qXIRuQxIB840P699tR9IcNutB3CgdSKs62jxNsJr8R6Fr8bVlBwRiTfGZIlIPNZdLJ8hIsFYf4gXGmPetjf7dMzGmCMishxrjE4nEQmy7wb60u9DGnCWiMwEwoAOWC3KvhovxpgD9s9cEXkHqwuiT/8uKNWWtLHzta/T76116DnjF/DHazJ/4M3rRu1ijTUjInArcJYxptStaDEwW0RCRaQ3kASs8kaMzeSr8X4PJNkz0IVgTUyy2MsxHc1i4DL7+WVAY60AJ5w9JvZZYJMx5mG3Ip+LWURi7DuAiEg4MBlrfM7nwAX2bj4RK4Ax5nZjTA9jTC+s39PPjDGX4qPxikiEiLSvfQ5MxZoUyOd+F5RSdfjq+drX+eP1hD/Qc8Zx8qdrMn/gK9eN8nNj6clLRLYDoUCevek7Y8zVdtkdWOOSq7G6TXzouZYTR0TOBR4FYoAjwHpjzDS7zOfiBbBb5BYAgcBzxph7vRySi4i8CkwAugA5wHzgf8DrQCKwF/iVMab+pBYnlIj0w5qQpB8QjjWLXyWQDfwJa8yLr8U8BGsyhUCsG3J5WLO2GiATGIJ11/XXwMfAf40xz3gn2rrsLtZ/MMaki8gpWN99Z2Ad8GtjTIU34wOw43rHfhkEvGKMuVdEovGx3wWlTkb+eL72db58PeEP/OWax1+IyOnAl8AGfp67xCevyfyBh+vG140x95zo6zBNkJXyEyLyLFBojLnJfv0CsN8Yc6dXA2smEUnAWkatpzGmQVcjuxuNzyTISimllFLq5KNdrJXyHz2BDG8H0ZhmrOHZE8jzlBwrpZRS6viIyEkzp5BSJ4ImyEr5ARH5DJgIPCYixSJyqod9rhKR7SJyWEQWi0g3e/vdIvKo/TxYREpE5EH7dbiIlItIlIf6JojIfhH5k4gcEpHdInKpW/kLIvKEiCwRkRJgooh0FJGXROSgiOwRkTtFJEBEJmNN1d/Njv8FEeklIqaxE7uIXCEim0QkX0Q+FpGeLfBVKqWUUsdFRBJE5G37HJcnIo/Z57g77XNern0O7GjvX3ueu0xE9trn0jvssm4iUiYind3qH27vE2y/bvQ8aNd7rYhsA7bZ26aKyBYRKRCRx0VkhYhc6faeo9V3tYhss8v/Y4+vrS2/yn5vkYj8JCIj3I7jLfs72SUi17faP4BSJ4gmyEr5AWPMJKwxLtcZYyKNMVvdy0VkEnAfcCEQD+zBGqsBsAJrvBHASKwxy2fYr1OBLcaY/EY+Og5rnFJ3rEkRnrbHQte6BLgXaA98hTXWriNwiv0ZvwEuN8Z8CswADtjx/7ap4xWRc7DG8JyHNXbvS+DVpt6jlFJKtRa7l9T7WOfXXljnxUXAb+3HRKxzXyTwWL23n441f8iZwF9EpL+9AsG3wPlu+10CvGmMqWrmefAcYDQwQES6AG8CtwPRwBZgrFv8zakvHes6YSjW9UTtePlfAXdhndM7AGcBeSISALwH/GB/H2cCN4rINM/folL+QRNkpdqGS7EmK1lrT1pwO5Aq1qL132LN+hkNjMeabbG7WGv2nYGVQDflz8aYCmPMCuADrJNmrXeNMV8bY5xAFXARcLsxpsgYsxv4JzDnOI7nd8B9xphN9pT+f8daE09bkZVSSnnDKKAb8EdjTIkxptwY8xXW+fdhY8xOY0wx1vl3dr3eUXcbY8qMMT9gJZND7e2vABeDazbk2fY2aN558D5jzGFjTBkwE8gwxrxt7/9vrBviHEN99xtjjhhj9mLNGjzM3n4l8KAx5ntj2W6M2YOVTMcYY+4xxlQaY3YC/2cfh1J+SxNkpdqGblh3tQGwT9J5QHf7xLkaKxkej5UQf4O15u/REuR8Y0yJ2+s99mfV2uf2vAsQ4h6H/bz7sR4M1njlf4nIERE5AhwG5DjrUkoppX6pBGCPnVy6q3P+tZ8HAbFu29wT1VKsVmawWnxT7SFR47FWePjSLmvOedD9HNzN/bWxZuHd71benPoaizMB2EFDPbGGTh1xq/dP9Y5dKb+jg/qVahsOYJ2oANeauNFYSymBlQRPAoZjrSO5Aqvr1CjgiybqjRKRCLckORFrnd1a7tPgH8JqRe4J/OS2fybHbh9wrzFm4XG8VymllGpp+4BEEQmqlyTXOf9infeqsZZQ6tFUhcaYIyKyFKtnVn/gVfPz8jLNOQ+6n4Oz3D/PbpF2//xfcl7dB/RpZPsuY0zScdSplM/SFmSl2oZXgMtFZJiIhGJ1nVppd3MGKyH+DfCTMaYSWI7VZWqXMebgUeq+W0RCRGQc1vikNzztZIypwVrz714RaW9327oZ+O9xHM+TwO0iMhDAnvzrV8dRj1JKKdUSVmElofeLSISIhIlIGtY43ptEpLc9dOnvwGseWpob8wrW+fl8fu5eDcd+HvwAGCwi59jdu6/FmkfkeOtz9wzwBxFJFktf+xy/CigUkVvFmvQzUEQGicjIZtarlE/SBFkpLxORz0Vkiv38byLy72OtwxizDPgz8BbWCbwPdccAfQOE83Nr8U9AOU23HoPV3Sof6w75QuBqY8zmJvb/f0AJsBNr0q5XgOeO5VgAjDHvAA8Ai0SkEKvVesax1qOUUkq1BPsmsAPoC+zF6r58EdY57mWs8+kurHPr/zuGqhcDSUCOPUa59vOafR4UkaeAgVjn3teACju21fbzX3ReNca8gTUh5ytAEfA/oLPbdzLMPvZDWMl0x+YfvlK+R37uyaGU8gYRGQ/cgzWxxSXAWfZJx6tEZALwX2NMk13ElFJKKeU9IrIemAXEGmPWikh7YA3QCbjIGPO5VwNUys9oC7JSXmaM+QJrooybgdm+kBwrpZRSync01ttMRPoDW40xmUCMiHQCKoEaIBD4zlsxK+WvdJIupbxMRAZjrV18yBhT5O14lFJKKeVz5gP3iEhXrAk3z7K3zwA+sp+nYnWDDgWCgen2ShZKqWOgXayV8iIRiQc+xhor9G/gH8aYj70blVJKKaV8jYiswFp6aULtDXUR+Ri43BhzwH4diTUx573GmLe9FqxSfky7WCvlJSLSDngbuMUYswn4K3CXV4NSSimllM9x621W4ZYctwM6uSXHwViTdS7U5Fip46cJslJeYowpNcakGmM+sV9/YYxJ9XZcSimllPIddm+zhcDZQImITLOLJgKf2/sI8CywyRjzsFcCVaqN0C7WQJcuXUyvXr28HYZSSqk2YM2aNYeMMTHejsPf6blZKaVUSzmWc7NO0gX06tWL1atXezsMpZRSbYCI7PF2DG2BnpuVUkq1lGM5N2sXa6WUUkoppZRSCk2QlVJKKaWUUkopQBNkpZRSSimllFIK0DHISp3UKqud5BSWk11YTlZBObmF5VTVHPvEfUEBQtcOocR1CCO+YzixHUMJDQpshYiVUkqpk4MxBqeBGqehxmmodjpxOqHGGNc2p2n4s/Y9TmNwOrG3WduNMRjA6fz5tdNY+xisn9S+dttu3N5r7WLsn9Z2at/r2rdumXH9x3qvaz+3+mq3ue3q2lD/yqQ2nsbK6ryu950ei6Z2Nw0+uXnvO+pnHv9bj163H87N3CMqHMfQbif0MzVBVqqNKq2sJrugnOwCK/nNLnR/XkZ2QTmHiitb7fOjI0KI7RBGfMcw4jpaP2PtBDrO3hYZqn+ClFJK+Q5jDGVVNZRU1FBWWUNpVTVllTWUVdVQXlVDWaWT8qoayqtrqKhyun5WVDuprHZSUV3jel5Z7aSqxklljfWzqsZQXeOk0v5Zu602+XV/Xl1jqHb6YTajVAs7vW8XTZCVUseurLKGDZkFrNubz/p9R1i39wjZheUN9uvULpi4DlZyOrh7R+I6hBPXMZS4juFWAts+jNDgYx95UVHt5GCRlXxn2Ul5bUJ+oKCctXvzyS+tavC+mPahDEvoxPDETgxL6MTQHp2I0KRZKaXUcXI6DUXl1eSVVHCkrIqC0iqOlFVypLSKwrJqCsurKCyroqi8mqKKKorLqymqqKakopqSihpKKquPq5UtJCiA0MAAQoLcHvbr4EDreVhwAEGhQfY2ISjAKgsKEIICxf5pvQ4MEPtnAEGBQoBYrwMChECBQLssQLC3We+pfV67PaDecwFEIFAEscvcf4qAgP0+6zX2axHs8p/3s8rd3m9/H+774b7N3uBpP9euUvtDXPu4v+fn+up+Xp2y+nvXi6Mpnj6nufvWfV/Tn9N0DL/gzUeru/WqbhXeiPeEXImKyHTgX0Ag8Iwx5v565aHAS0AykAdcZIzZbZfdDswFaoDrjTEf29ufA9KBXGPMILe6OgOvAb2A3cCFxpj8Vjw8pU4op9OwK6+EdXuPsH5fPuv2HmFzdhE19p3mhM7hjOrdmX5x7enWya3VtkMY4SGt0+05LDiQjuHB9O3avtF9yqtqyCn8OYHOKihnW04R6/Yd4ZOfcgAIEDg1tj3DEzsxPCGKYYmd6BsTSUCAn/01V0op1aJKK6vJKignp7Cc3MIK62dRBYeK7UdRJXklFeSXVrnOh55EhATSITyY9mFBtA8LplO7EHpEtSMyNIh2oYHWz5AgIkIDCQ8OpF1IEOEhAYQHBxEeYm0LCw4gLDiQsKBAQoMDCA0KaDKJUkr5l1ZPkEUkEPgPMAXYD3wvIouNMT+57TYXyDfG9BWR2cADwEUiMgCYDQwEugGfisipxpga4AXgMazE2t1twDJjzP0icpv9+tbWO0KlWld+SSXr9x+xE+IjrN+bT2F5NQCRoUEMTejINWf0YVhCJ4YldqJLZKiXI/YsLDiQntER9IyOaFBW/xg/+DGLV1ftA6B9aBBDEjpaCbOPH6NSSqnjU15Vw568UvbklbAvv4x9h0vZn19G5pEysgrKOOKhF1J4cCAx7UPpEhlCz+h2jOjZic4RIUS1C7F+RoTQKdxKgjuGB9MhLIigQJ2fVinVtBPRgjwK2G6M2QkgIouAswH3BPls4C77+ZvAY2LdijsbWGSMqQB2ich2u75vjTFfiEgvD593NjDBfv4isBxNkJWf2ZtXyocbs/hwYzbr9x0Bfm5dnTUk3tW62icmksA20LoaFRHCxH5dmdivK+C5lfyJFTtcrQKDundgxqB4pg+Ko09MpDdDV+qk11iPLrdywepFNhMoBX5rjFl7YqNUviK/pJKtOUVsyy1mW04R2w8Ws/tQKQcKyup0bW4XEkhCVDt6RIWT3LMT8R3DXb2iah86j4VSqjWciL8s3YF9bq/3A6Mb28cYUy0iBUC0vf27eu/tfpTPizXGZNl1ZYlI118Qu1InzPbcYj6yk+KMA4WAlQjePOVURvbqzJAeHU+a8bkBAUKfmEj6xERyQXIP4Odx1qv3HGZpRg4PfbyFhz7eQr/Y9kwfFMeMwXH0i22v3dyUOvFewHOPrlozgCT7MRp4gobXAaqNMcaQeaSMH/YVkHGggE1ZhfyUVUhOYYVrn4iQQPp2jWRkryh6delB7y5WL6OEqHA6R4To33OllFeciKttT3/d6g8OaWyf5rz3uIjIPGAeQGJiYktUqdQxMcawObuIDzdm89HGLLbmFAMwIrETd8zsz/RBcSR0buflKH1HeEggo3p3ZlTvzvx+Ql8OHCnj44xsPtyYzb8/28a/lm2jd5cIZgyKY8ageAZ176AXV0qdAE306Kp1NvCSsdZX+U5EOolIfO3NbNU2lFfV8MO+I6zek8+aPfn8uP+Ia6WEoAChb9dI0vp0oX98B06Na09S10jiO4bp32mllM85EQnyfiDB7XUP4EAj++wXkSCgI3C4me+tL6f2xCsi8UCup52MMU8DTwOkpKToPPrqhDDG8OP+AldSvDuvlACBkb06c5djANMGxRHfMdzbYfqFbp3CuTytN5en9Sa3qJylGTl8tDGbp77YyePLd9AjKpzpA62W5eEJUTrRl1Le46knWXdAE2Q/VlntZN3efL7efoivd+SxYX8BlTVOAPp2jWRCv64M7dGRoQmd6BfXntCg1pkkUimlWtqJSJC/B5JEpDeQiTXp1iX19lkMXAZ8C1wAfGaMMSKyGHhFRB7GmqQrCVh1lM+rret+++e7LXUgSh2vvXml/HflHj74MYvMI2UEBghj+0Qzb3wfpg6M1UmnfqGu7cP49Zie/HpMT/JLKvlkk5Usv/TtHp75ahexHUKZMSieX4/pSd+uOmZZqROs2b3BtHeXbztwpIxlm3P5bFMO3+08TFlVDQECQ3p04vK0Xozs1ZnknlFERYR4O1SllDpurZ4g22OKrwM+xlrm6TljTIaI3AOsNsYsBp4FXrYn4TqMlURj7/c61oRe1cC19gzWiMirWJNxdRGR/cB8Y8yzWInx6yIyF9gL/Kq1j1EpT4wxfLsjj+e+3s2yzTkEinDGqTHcODmJKQNi6dROLyBaQ1RECBemJHBhSgKF5VV8timXDzdm8cqqvbzwzW7GnxrD5Wm9OCMpRluVlToxmt0bTHt3+Z7tucW8/+MBlmbk8FOWNT9Gz+h2XJjSg7S+XRh9SjQdw4O9HKVSSrUcMcezGnobk5KSYlavXu3tMFQbUV5Vw//WZfL817vZklNEdEQIl4xO5NdjehLbIczb4Z208ooreHXVXl7+bg85hRWc0iWCy8b24oLkHifN5GfqxBCRNcaYFG/HcSLZY5Dfb2QW61nAdVizWI8G/m2MGXW0OvXc7D3780v537pM3v8xi83ZRYhAcmIUkwfEMrl/V/rEROrYYaWUXzmWc7MmyOhJWLWMrIIyXv52D6+u2kt+aRX94ztweVovzhrajbBgHXvlKyqrnXy4MYvnv97N+n1HaB8axIUjE7gstReJ0TpT/W5lAAAgAElEQVQpmvrlTrYE2b1HF5ADzAeCAYwxT9rLPD0GTMda5ulyY8xRT7p6bj6xyqtq+DgjmzdW7+frHYcwBpJ7RpE+JJ6Zg+P1Bq9Syq8dy7lZm02U+gWMMazdm89zX+/mo43ZGGOYMiCWy9N6M7p3Z73D7oNCggI4e1h3zh7WnbV783n+6928+M1unvt6F5P7x3J5Wi9ST4nWfzulmskYc/FRyg1w7QkKRx2jfYdLefm7PSxatZfC8mp6RIVz45mncn5yd3pE6U1DpdTJRxNkpY5DZbWTDzYc4Pmvd/Pj/gLahwVxRVovfpPaS5dm8iMjEqMYkRhF9sz+vPzdbl5ZuZdPfsrhtLj2XJ7Wi7OHddfWf6VUm7Rq12Ge/Wonn/yUg4gwfWAcl45OZMwp0To/g1LqpKZdrNFuXKr5yqtqeOGb3Tz71S4OFlVwSkwEl4/txXkjdBxrW1BeVcO7663x45uzi4hqF8xlY3tx5bhTiNR/X9VMJ1sX69ai5+aWZ4zhq+2HeHTZdlbtPkyndsFcPCqROWN60q2TLjGolGq7tIu1Ui2sxml4a81+Hv5kK9mF5YxL6sJDFwxhvM6E3KaEBQdy0chELkxJ4NudeTz31S4WfLqN/363h+vPTGL2yERCggK8HaZSSh2zL7Ye5OFPtrJ+3xHiOoQx3zGA2SMTCQ/RXjJKKeVOE2SlmmCMYdmmXB74aDPbcosZltCJBbOHMeaUaG+HplqRiDC2TxfG9unCur353P/hZv7ybgbPfrWLP07rx6zB8TpGWSnlF346UMh9H27iy22H6N4pnHvPHcQFyT0IDdLEWCmlPNEEWalGrN2bz/1LNrNq92F6d4ngiUtHMH1QnCZGJ5nhiVEsmjeGz7fk8sCHW7julXX8X4+d3DajP6l99EaJUso35RaW88BHW3h73X46hgfz5/QB/HpMoibGSil1FJogK1XPzoPFPPTxFj7cmE2XyFD+es4gZo9M4P9v777DoyrTuI9/7xR6h4BUCUUgoRNRRFcsK9hg9QWEteCKYl3bupbVVVdf3VXXtq64oih2QGzoYkfXggihSicEhFBDCz0hyf3+MaNvxAQSSOYkmd/nurycOfOcw28eDjNzn/Oc58THamhttDIzTu3YhJOPaczbs0ND7Yc/N51+HRK4/cyOdDyqTtARRUSA0CVBr33/I498tJTsvHxGndSGa05pR93q8UFHExGpEFQgi4Rt2rmPJz9bzviZa6gWF8NNpx/D5SclavIt+VlsjDEkpSXndmvGuGmrGP1FGmc++TXn92jBzWccQ3NNciMiAVq4Lou/vLOAeWu2c1L7Rtw/qDOtG9UMOpaISIWiX/4S9XZl5zLmq3Se/zqdnNx8LjyuFX88tT0JtasGHU3KqWrxsVx1cluGHduS0V+uYNy0Vbw/fx1/OKE11/RrR90aOlMjIpGTm5fP01+s4F9Tl1O/RjxPDuvOwG7NdEmQiMhhUIEsUWt/Xj5vzFjNk58tZ8vuHM7u2pRbzuhAoo62SzHVq1GFv5zViUv6HM1jny5jzNfpvDFjNdee0o5L+7bWtX4iUuZ+3LKbGyfMZc7q7fyuezP+NrCzDtKJiBwBFcgSlRaszeK2t+azcN0Ojm/TgBfO7ES3lvWCjiUVVIv6NXhsaHeuOKkND320hL9/uISJqWt4eHBXeh3dIOh4IlJJvZm6hnsmLyQuxnhqeA/O7dYs6EgiIhWeCmSJKvv25/Gvz5fz7FfpNKhZhf9c1JP+yZqZWkpHp6Z1GPeH3ny5dBN3vrOAwf/5jhF9WvPn/h10LbuIlJrs3DzunbyIN2aspk+bhjx2QTea1tUcCCIipUG/2CRqpK7ayq1vzSc9czdDerXgrrOTNAxNykS/Do35+Kbf8MhHSxg3bRWfLd7I38/vwkntE4KOJiIV3PqsvVz16mzmrdnONf3a8qczOhAbo4O8IiKlRQWyVHq7s3N5+KMlvDz9R5rXq84rI3urUJEyV6tqHH8b1JlzujXjtrfmc/HYGQxNacGdZ+nAjIgcntRVW7nq1VnszcnjPxf1ZEDnpkFHEhGpdFQgS6X21bJM7nj7B9Zl7dVQVwnEsa0bMOX6k3jy8+WM+SqdL5Zm8n9/15n+yUcFHU1EKpCPFqzn+vFzaV6vOuNHHU+7xrWDjiQiUinFBB1ApCxs35PDLW/O45IXZlAtPoY3r+zDvQOTVRxLIKrFx3LbgI68d21fEmpV5cpXZnHta7PJ3JkddDQRqQBe/m4VV782m+RmdXj76hNUHIuIlCFVC1LpfLRgPXe9u5Bte3K47pR2XHdqO6rF63Y7ErzOzevy3nV9GfNVOk9+tpxvV2zm7nOSOK9Hc00UJyK/4u488vFSRn+5gtM7NeGp4T2oXkXfZyIiZUkFslQam3bu4573FvLhgg0kN6vDS5cdS3KzukHHEvmF+NgYrj2lHf2Tj+K2t+Zz88R5TJ63jgfO60LzepqFVkRC3J17Ji/k5e9+ZHjvVtw/KJm4WA38ExEpa/qklQrP3XlrVga/fewrPl+yiVsHdODda/uqOJZyrV3jWky8sg/3npvEjJVbOeOx//HK9B9x96CjiZSImQ0ws6VmlmZmtxfyeisz+8LM5pjZfDM7K4icFYm787f3F/Hydz9y+YmJPHheZxXHIiIRojPIUqHtycnlrncW8PactaQcXZ+HBnelbUKtoGOJFEtsjHFp30RO69SEv7zzA399dwHfLM/k4cHdqFtdM11L+WdmscDTwG+BDGCmmU1290UFmt0FTHT3Z8wsCZgCtI542ArC3bnvg0WMm7aKkScmcufZnXQJhohIBEXkcGQxji5XNbMJ4de/N7PWBV67I7x8qZn1P9Q2zew0M5ttZnPN7Bsza1fW70+CsXzjTgb9+1vembuWm397DBOu7KPiWCqklg1q8PJlvbnr7E58vngT5z71DQvWZgUdS6Q4egNp7p7u7jnAeGDQAW0cqBN+XBdYF8F8FYq788B/F/Pit6v4Q9/W3KXiWEQk4sq8QC5wdPlMIAkYHj6CXNBIYJu7twMeBx4Kr5sEDAOSgQHAaDOLPcQ2nwEudPfuwOuEjlxLJfPOnAwG/vtbtu3J4dWRx3H9ae2JjdGPCKm4zIzLT2rDhCv7sD8vn/NHT+NVDbmW8q85sKbA84zwsoLuBS4yswxCZ4//GJloFc+zX6Xz/DcrGdHnaO4+J0nFsYhIACJxBrk4R5cHAS+FH08CTrPQt8IgYLy7Z7v7SiAtvL2DbVNHqiuxffvzuOPtH7hpwjy6tKjLf68/ib7tGgUdS6TU9Dq6Pv+9/iT6tG3IXe8u4MYJc9mdnRt0LJGiFFbBHXhUZzgwzt1bAGcBr5hZob8/zGyUmaWaWWpmZmYpRy3f3pu7ln98uIRzujblnnOTVRyLiAQkEgVycY4u/9zG3XOBLKDhQdY92DYvB6aEj1RfDPyjsFDR/CVcUa3avJvzR0/jjRmruaZfW16//Dia1KkWdCyRUtegZhVevPRY/ty/A+/PW8fAf3/D0g07g44lUpgMoGWB5y349YHpkcBEAHf/DqgGFHpk093HuHuKu6ckJCSUQdzyaXr6Fv785nx6Jzbg0aHdiNGIKBGRwESiQC7O0eWi2pR0OcBNwFnhI9UvAo8VFipav4Qrqg9/WM85T33D2u17eeHSFG4d0FEzekqlFhNjXHtKO169/Diy9uYy6OlvmDQrI+hYIgeaCbQ3s0Qzq0LosqjJB7RZDZwGYGadCBXIOjIdtnzjTka9nEqrhjV47uIUqsbpPsciIkGKRIVRnKPLP7cxszhCQ6O3HmTdQpebWQLQzd2/Dy+fAJxQOm9DgpCTm8/f3l/I1a/Npl3jWvz3+hM5tWOToGOJRMwJbRsx5YYT6d6yHre8OY/bJs1n3/68oGOJAD+P+roO+BhYTGi26oVmdp+ZDQw3+xNwhZnNA94ALnVdXA9A1p79jHwplarxsYz7w7HUraHZ60VEghaJ2zz9fHQZWEvo6PLvD2gzGRgBfAcMBqa6u5vZZOB1M3sMaAa0B2YQOoNc2Da3AXXN7Bh3X0bothOLy/oNStnI2LaHa1+fw7w127msbyK3n9mRKnE6ayzRp3Htarx2+fE88dkynpqaxryM7Yy+sCdtNGu7lAPuPoXQ5FsFl91d4PEioG+kc5V3+fnOTRPnsj5rLxOu7EOL+jWCjiQiIkSgQHb3XDP76ehyLPDCT0eXgVR3nwyMJTRpRxqhM8fDwusuNLOJwCIgF7jW3fMACttmePkVwFtmlk+oYL6srN+jlL6pSzZy04R55Oc7z1zYkzO7NA06kkigYmOMP53RgV5H1+emCXM596lveGhwV87p2izoaCJyGP79RRpTl2zi/kHJ9GxVP+g4IiISZhrlBCkpKZ6amhp0DAFy8/J59NNlPPPlCpKa1mH0hT1p3ahm0LFEypV12/dy3euzmb16OyP6HM1fzu6k6xbLETOb5e4pQeeo6Crzd/P/lmVy6Ysz+F335jw2tJtmrBYRKWMl+W6OxBBrkWLJ2rufq1+dxbQVW/j9ca24+5wkqsXrR7/IgZrVq86EK/vw8EdLeO7rlcxfm8Vzl6TQqFbVoKOJyCFkbNvDDePn0KFJbR48r4uKYxGRckYXdEq5sGbrHgY/M42Zq7byzyHdePC8LiqORQ4iPjaGO89O4pkLe7J4/Q7OG/0tKzJ3BR1LRA4iL9+5ecI88vKc/1zUi+pV9D0nIlLeqECWwM3P2M55o6exccc+Xr7sOAb3ahF0JJEK48wuTRk/qg97c/I4f/Q0vk/fEnQkESnC81+nM2PVVu4dmKzLh0REyikVyBKoTxdt5IJnp1MtPoa3rzmBPm0bBh1JpMLp3rIe71zTl0a1qnDx2Bm8N3dt0JFE5ACL1+/g0U+WMSD5KM7v2TzoOCIiUgQVyBKYcd+uZNQrqRzTpBbvXNOXdo1rBx1JpMJq2aAGb1/dlx6t6nHD+Ln8e+pyNAmjSPmQnZvHTRPmUqd6PA+er+uORUTKMxXIEnF5+c597y/i3vcXcXqnJowf1YeE2ppcSORI1a0Rz8sje3Nej+b885Nl3PbWfPbn5QcdSyTqPf7pcpZs2MnDg7vQoGaVoOOIiMhBaBZriai9OXncMH4OnyzayB/6tuaus5OIjdGRdJHSUjUulseGdqNl/er8a2oa67P28fSFPalTLT7oaCJRae6a7Tz71QqG927FqR2bBB1HREQOQWeQJWIyd2Yz7LnpfLp4I/ecm8Q95yarOBYpA2bGzWd04OHBXfluxRaGPPMda7fvDTqWSNTJzcvnznd+oHHtqtx5dqeg44iISDGoQJaISNu0k/NGf8vSDTt49qJe/KFvYtCRRCq9oSkteemy3qzbvpfznv6WBWuzgo4kElVemf4jC9ft4O5zkqlVVYP2REQqAhXIUua+W7GF80dPY9/+fCaM6sMZyUcFHUkkavRt14hJV59AfGwMQ5/9jqlLNgYdSSQqbNyxj0c/WcZvjkngrC763hMRqShUIEuZemdOBpe88D2N61TjnWtOoFvLekFHEok6HY6qzTvXnECbhJpc/lIqr0z/MehIIpXe/R8sIicvn/sGJmvWahGRCkQFspQJd+dfny/npgnz6HV0fd666gRaNqgRdCyRqNW4TjUmjOpDvw6N+eu7C3hwymLy83UbKJGy8PXyTD6Yv55r+7WjdaOaQccREZESUIEspS4/37ln8kIe+3QZ5/dozsuXHUfdGppBVyRoNavGMebiXlx8/NGM+SqdP705j1zdBkqkVO3Py+fu9xaS2KgmV/VrE3QcEREpIc0YIaUqP9+5890feGPGGq44KZG/nNVJQ8tEypG42BjuG5RM49pVefTTZeTmO48N7UZ8rI6XipSGN2asZuXm3YwdkULVuNig44iISAmpQJZSk5fv3PbWfCbNyuDaU9pyyxkdVByLlENmxh9Pa098XAz/+HAJuXn5PDmsB1XiVCSLHIld2bk8+dlyjktswKkdGwcdR0REDoN+DUmpyM3L5+aJc5k0K4ObTj9GxbFIBXDVyW356zlJfLhgA9e8Novs3LygI0kFZGYDzGypmaWZ2e1FtBlqZovMbKGZvR7pjJEy5qt0tuzO4Q6NnhIRqbBUIMsR25+Xzw3j5/Le3HX8uX8Hbji9vX4YiFQQI09M5P5ByXy2eBOjXp7Fvv0qkqX4zCwWeBo4E0gChptZ0gFt2gN3AH3dPRm4MeJBI2DTjn0891U6Z3dtSnfdsUFEpMJSgSxHJDs3j2tfm81/f1jPnWd14tpT2gUdSURK6OI+rfnH+V34ankml7+Uyt4cFclSbL2BNHdPd/ccYDww6IA2VwBPu/s2AHffFOGMEfHE58vJzc/n1v4dgo4iIiJHQAWyHLZ9+/O4+tXZfLJoI/eem8QVv9FsnSIV1bDerfjn4G5MW7GZS1+cwe7s3KAjScXQHFhT4HlGeFlBxwDHmNm3ZjbdzAYUtTEzG2VmqWaWmpmZWQZxy8aKzF1MmLmGC487mqMb6rZOIiIVmQpkOSx7c/K44uVUpi7ZxAPndebSvolBRxKRI/R/erXg8Qu6k/rjNka8MIOd+/YHHUnKv8KupznwBttxQHugHzAceN7MCh2D7O5j3D3F3VMSEhJKNWhZeuyTZVSPj+WPp2oUlYhIRacCWUpsT04ul42byTdpm3l4cFcuPO7ooCOJSCkZ1L05Tw3vwdw127lo7Ayy9qpIloPKAFoWeN4CWFdIm/fcfb+7rwSWEiqYK4W0TTuZsmA9l57Qmoa1qgYdR0REjlBECuRDzXBpZlXNbEL49e/NrHWB1+4IL19qZv0PtU0LecDMlpnZYjO7vqzfXzTZlZ3LpS/M5PuVW3hsaDeGprQ89EoiUqGc1aUpoy/syaJ1WVz4/HS27c4JOpKUXzOB9maWaGZVgGHA5APavAucAmBmjQgNuU6PaMoyNPqLFVSLi+WyEzWSSkSkMijzArk4M1wCI4Ft7t4OeBx4KLxuEqEv22RgADDazGIPsc1LCR3N7ujunQhNGCKlYMe+/Vw89ntmrd7Gk8N6cF6PFkFHEpEyckbyUYy5OIVlG3cx/LnpbNmVHXQkKYfcPRe4DvgYWAxMdPeFZnafmQ0MN/sY2GJmi4AvgD+7+5ZgEpeu1Vv28N68dVx0fCsa1KwSdBwRESkFJSqQw4VpSRVnhstBwEvhx5OA0yx0n6BBwHh3zw4Py0oLb+9g27wauM/d86HyzpYZaVl79nPR89+zYG0WT/++B+d2axZ0JBEpY6d0bMzYESms2rKbYWOms2nnvqAjSTnk7lPc/Rh3b+vuD4SX3e3uk8OP3d1vdvckd+/i7pXmwPUz/1tBbIxxxUmapFJEpLIo6RnkMWZWA8DMflPMdYozw+XPbcJHo7OAhgdZ92DbbAtcEJ4F88Pw/Rd/paLOlBmErbtzGP7cdJas38kzF/ZiQOemQUcSkQg5qX0CL17am7Xb9zJszHQ2ZKlIFgFYn7WXSbPWcEFKSxrXqRZ0HBERKSUlLZDvBsaa2SvAscVcpzgzXBbVpqTLAaoC+9w9BXgOeKGwUBV1psxI274nh98/N50VmbsYc0kvTk9qEnQkEYmwPm0b8tJlvdm0I5sLxnzHph0qkkWe/V867nDlyTp7LCJSmZS0QL6f0OyTDkws5jrFneGyJYCZxQF1ga0HWfdg28wA3go/fgfoWsyccoDd2blc+uJM0jN3M3bEsfTr0DjoSCISkGNbN+Dlkb3J3JnNJS/MIGuPZreW6JW5M5s3Zqzm/J7NaVG/RtBxRESkFJW0QL7V3e8FrgHuKeY6xZnhcjIwIvx4MDDV3T28fFh4lutEQreFmHGIbb4LnBp+fDKwrITvUYCc3HyuenUW8zO286/hPTixfaOgI4lIwHq2qs+Yi1NIz9zNZS/NZG9OXtCRRALxyneryMnL5+p+uu+xiEhlc8gC2cxmmtlYM7sR6GpmCe6+C7iyOH9AMWe4HAs0NLM04Gbg9vC6CwmdqV4EfARc6+55RW0zvK1/AP/HzH4A/g5cXpyc8v/l5Ts3T5zL18s384/zuzKg81FBRxKRcuLE9o14clh35qzextWvzSInNz/oSCIRlZ2bx2vfr+a0jo1JbFQz6DgiIlLK4orRZhChYcpdgauAs81ss7sfXdw/xN2nAFMOWHZ3gcf7gCFFrPsA8EBxthlevh04u7jZ5JfcnbvfW8AH89dzx5kdGXqs7nMsIr90ZpemPHBeF+54+wdueXMeT1zQnZiYwqaGEKl8Ppi3ni27c7j0BN33WESkMjpkgezu6whd3/sRgJl1IjQMWiqhxz5dxmvfr+aqk9ty5cltg44jIuXU8N6t2LYnh4c/Wkr9GvHcOzCZ0N35RCovd2fctFW0b1yLvu0aBh1HRETKwCELZDNr5e6rf3ru7ovNLLlsY0kQxn6zkqempnFBSktuG9Ah6DgiUs5dfXJbtu3O4bmvV1K/ZhVuPP2YoCOJlKlZP27jh7VZPHBeZx0QEhGppIozxHqCmbUEVgI/APuAjmWaSiLu7dkZ3P/BIgYkH6UvfhEpFjPjL2d1Yvue/Tzx2XLqVY/n0r4adiqV14vTVlGnWhzn9WgedBQRESkjxRli3QfAzNoBXYAGwGNlnEsi6LNFG/nzpPmc0LYhTwzrTlxsSSc3F5FoZWb8/fwubN+7n3vfX0S9GlX4nYoHqYTWZ+3lowUbuPzERGpUKc75BRERqYiK/Qnv7mlAWhlmkQDMWLmVa1+fTXKzOoy5JIVq8bFBRxKRCiYuNoanhvdgxAszuOXNedStHs8pHXXfdKlcXvnuR9ydi44v9hylIiJSAelUYRRbuC6LkeNm0rx+dcb9oTe1quqIuIgcnmrxsTw/IoWOTWtz9WuzSF21NehIIqVm3/483pixmt8mNaFlgxpBxxERkTKkAjlKrdy8mxEvzKB2tTheHXkcDWpWCTqSiFRwtavFM+4PvWlWtzqXjZvJ4vU7go4kUio+WbSRbXv2c/HxrYOOIiIiZUwFchTauGMfF4/9nrx85+WRx9GsXvWgI4lIJdGoVlVeHtmbGlXiuOSFGfy4ZXfQkUSO2MSZa2hRvzontNWtnUREKjsVyFFm+54cLhk7g227c3jpst60a1wr6EgiUsm0qF+DV0b2Zn9ePhePncGmHfuCjiRy2NZs3cM3aZsZ0qslMTG6w4OISGWnAjmK7MnJ5bJxM1m5eTfPXZJC1xb1go4kIpVU+ya1efHSY9m8K5tLXphB1p79QUcSOSyTZmVgBoNTWgQdRUREIkAFcpTIy3eue30Oc9ds51/Du3NCu0ZBRxKRSq5Hq/o8e3EvVmTu4oqXU8nOzQs6kkiJ5OU7k2ZlcGK7RjTX5UgiIlFBBXKUeHDKYqYu2cTfBnVmQOemQccRkShxUvsE/jmkGzNWbeXOdxbg7kFHklJmZgPMbKmZpZnZ7QdpN9jM3MxSIpnvSHybtpm12/dywbEtg44iIiIRogI5CrwxYzVjv1nJpSe05mLdv1FEImxQ9+Zcf1p7Js3K4Nmv0oOOI6XIzGKBp4EzgSRguJklFdKuNnA98H1kEx6ZialrqFcjnt8mNQk6ioiIRIgK5Epu2orN/PXdBZx8TAJ3nd0p6DgiEqVuPK09Z3dtykMfLeGThRuCjiOlpzeQ5u7p7p4DjAcGFdLufuBhoMLM2LZtdw6fLNzI77o3p2pcbNBxREQkQlQgV2IrN+/m6ldnk9ioJk/9vgdxsfrrFpFgxMQYjw7pRtfmdblxwlwWrssKOpKUjubAmgLPM8LLfmZmPYCW7v7BoTZmZqPMLNXMUjMzM0s3aQm9O3ctOXn5DE3R8GoRkWiiiqmSytqzn5HjZhIbY4wdcSx1qsUHHUlEoly1+FieuySFOtXiueKlVDbtrDAnE6Vohd336OcLzc0sBngc+FNxNubuY9w9xd1TEhISSini4Zk0K4POzeuQ1KxOoDlERCSyVCBXQvvz8rnm9Vms2baH/1zUi1YNawQdSUQEgMZ1qvH8iBS27dnPqJdnsW+/Zrau4DKAgqdYWwDrCjyvDXQGvjSzVcDxwOTyPlFX2qZdLFy3g/N66NZOIiLRRgVyJePu3Dt5Id+mbeHB87rQO7FB0JFERH6hc/O6PH5Bd+au2c6tk+ZrZuuKbSbQ3swSzawKMAyY/NOL7p7l7o3cvbW7twamAwPdPTWYuMXz/rx1mME5XXXXBxGRaKMCuZJ5adoqXvt+NVee3IYhum5KRMqpAZ2P4tYBHZg8bx1PTU0LOo4cJnfPBa4DPgYWAxPdfaGZ3WdmA4NNd3jcnffnreO4xAY0qVMt6DgiIhJhcUEHkNLz5dJN3PfBIn6b1ITb+ncMOo6IyEFdfXJb0jbt4rFPl9EmoSbndG0WdCQ5DO4+BZhywLK7i2jbLxKZjsTCdTtI37yby09qE3QUEREJQETOIJvZADNbamZpZnZ7Ia9XNbMJ4de/N7PWBV67I7x8qZn1L8E2nzKzXWX1nsqb5Rt38sfX59DhqDo8cUF3YmIKmzdFRKT8MDP+fn4XUo6uz58mzmPemu1BRxLh/XnriIsxzux8VNBRREQkAGVeIJtZLPA0cCaQBAw3s6QDmo0Etrl7O0KzXT4UXjeJ0PVMycAAYLSZxR5qm+HJP+qV6RsrR7buzmHkS6lUjY/l+REp1KyqgQEiUjFUjYvl2Yt7kVC7Kle8nMr6rL1BR5Iolp8fGl79m2MSqF+zStBxREQkAJE4g9wbSHP3dHfPAcYDgw5oMwh4Kfx4EnCamVl4+Xh3z3b3lUBaeHtFbjNcPD8C3FrG76tcyM7N46pXZrFhxz6eu6QXzetVDzqSiEiJNKxVlbEjjmVPTh6Xv5TKnpzcoCNJlJq1ehvrsvZxbjdNziUiEq0iUSA3B9YUeJ4RXlZom/CEH1lAw4Ose7BtXgdMdvf1pZS/3HJ37npnATNWbYIJE1YAABbKSURBVOWfQ7rRo1X9oCOJiByWDkfV5qnhPVi8fgc3T5hHfr5mtpbImzx3HVXjYvhtkoZXi4hEq0gUyIVdDHvgL5+i2pRouZk1A4YATx0ylNkoM0s1s9TMzMxDNS+XxnyVzpuzMrj+tPYM7KbJbUSkYjulY2PuPDuJjxZu4NFPlwYdR6JMbl4+U35Yz+mdmlBLlyqJiEStSBTIGUDB+w21ANYV1cbM4oC6wNaDrFvU8h5AOyDNzFYBNcys0PuHuPsYd09x95SEhITDe2cB+nTRRv7x0RLO7tqUG09rH3QcEZFScVnf1gzv3Yqnv1jB27Mzgo4jUWTaii1s2Z2j4dUiIlEuEgXyTKC9mSWaWRVCk25NPqDNZGBE+PFgYKq7e3j5sPAs14lAe2BGUdt09/+6+1Hu3trdWwN7whN/VSpLNuzghvFz6Nq8Lo8O6aYZq0Wk0jAz7huUzAltG3L7Wz8w68dtQUeSKPHf+eupVTWOfh0aBx1FREQCVOYFcvia4uuAj4HFwER3X2hm95nZwHCzsUDD8Nnem4Hbw+suBCYCi4CPgGvdPa+obZb1eykPduzbz1WvzKJW1TjGXJJCtfjYoCOJiJSq+NgYRl/Yk6b1qnHta7PZvCs76EhSyeXlO58t3sgpHRvre1VEJMpF5CIbd58CTDlg2d0FHu8jdO1wYes+ADxQnG0W0qbW4eQtr9ydW9+cz5pte3njiuNpUqda0JFERMpEvRpVGH1hT84fPY0bxs/h5cuOI1ajZaSMzPpxG1t253BGUpOgo4iISMAiMcRaSsnYb1by0cIN3D6gI70TGwQdR0SkTCU3q8v9gzrzbdoWnvxsWdBxpBL7eOEGqsTG0K9DxZuTRERESpcK5Api5qqt/P3DJfRPbsLlJyUGHUdEJCKGHtuSoSkt+NfUNL5YuinoOFIJuTufLNpA33YNqV0tPug4IiISMBXIFUDmzmyufW02LetX55Eh3TDTMEMRiR73DepMp6Z1uGnCXDK27Qk6jlQyi9fvZM3WvZyRrHsfi4iICuRyLy/fuf6NOWTt3c/oC3tRR0e3RSTKVIuP5ZkLe5KX51zz2myyc/OCjiSVyMcLN2AGp3fS9cciIqICudx77NOlfJe+hf/7u84kNasTdBwRkUC0blSTfw7txvyMLO7/YFHQcaQS+WTRRlKOrk9C7apBRxERkXJABXI59vnijTz9xQqGHduSISktg44jIhKo/slHceVv2vDq9NW8O2dt0HGkElizdQ+L1++gv4ZXi4hImArkcmrN1j3cNGEuyc3qcO/A5KDjiIiUC3/u34HeiQ244+0fWLZxZ9BxpIL7eOEGAM5IUoEsIiIhKpDLoX3787j6tVk48MyFvagWHxt0JBGRciEuNoZ/D+9BzapxXPXqLHZl5wYdKeqZ2QAzW2pmaWZ2eyGv32xmi8xsvpl9bmZHB5GzMJ8s3EjHo2rTqmGNoKOIiEg5oQK5HLrvg0UsWLuDx4Z215e2iMgBGtepxlPDe7Bq825ue2s+7h50pKhlZrHA08CZQBIw3MySDmg2B0hx967AJODhyKYs3OZd2aT+uFXDq0VE5BdUIJczb8/O4PXvV3PVyW35bZJm1BQRKUyftg35c/+O/Hf+esZNWxV0nGjWG0hz93R3zwHGA4MKNnD3L9z9p/tzTQdaRDhjob5Ysol8R9+1IiLyCyqQy5ElG3bwl3d+4Pg2DbjljGOCjiMiUq5ddXIbTu/UhAf+u5hZP24LOk60ag6sKfA8I7ysKCOBD8s0UTF9sXQTTepUJVl3iBARkQJUIJcTO/ft5+pXZ1O7Wjz/Gt6DuFj91YiIHIyZ8ejQbjStV43rXp/Nll3ZQUeKRlbIskLHvJvZRUAK8EiRGzMbZWapZpaamZlZShF/bX9ePl8v28wpHRpjVthbEBGRaKUqrBxwd257az6rt+7h38N70Lh2taAjiYhUCHWrx/PMhb3YsjuHGyfMJS9f1yNHWAZQ8D6ELYB1BzYys9OBO4GB7l7kkQx3H+PuKe6ekpCQUOphf5K6ahs7s3M5pWPjMvszRESkYlKBXA688O0qpvywgVv7d+C4Ng2DjiMiUqF0bl6X+wYm8/XyzTz5+fKg40SbmUB7M0s0syrAMGBywQZm1gN4llBxvCmAjL/yxdJNxMcafds1CjqKiIiUMyqQA5a6ait/n7KYM5KaMOo3bYKOIyJSIV1wbEsG92rBU1OX8+XSclGDRQV3zwWuAz4GFgMT3X2hmd1nZgPDzR4BagFvmtlcM5tcxOYi5oslmzgusSG1qsYFHUVERMoZfTMEaNvuHK57fQ7N61fnkSHddB2UiMhhMjPuH9SZBWuzuHHCXD684SSa1q0edKyo4O5TgCkHLLu7wOPTIx7qINZs3cPyTbsY1rtV0FFERKQc0hnkgLg7t789ny27s3n69z2pWz0+6EgiIhVa9SqxPHNRL3Jy8/nTxHnk63pkKcQX4REGp3Qou2ucRUSk4lKBHJCJqWv4eOFG/ty/A52b1w06johIpZDYqCb3nJvEtBVbeP6b9KDjSDn0xZJNtG5YgzYJtYKOIiIi5ZAK5ACs3Lybeycv4oS2Dbn8RF13LCJSmoamtKR/chMe+XgpC9ZmBR1HypG9OXlMW7FFs1eLiEiRVCBH2P68fG4cP4cqcTE8OrQbMTG67lhEpDSZGf84vysNalbhxglz2ZuTF3QkKSe+S99Mdm4+p3RQgSwiIoVTgRxhT362nHkZWfzj/C6aQEZEpIzUr1mFR4d0J23TLh6csjjoOFJOfLEkk+rxsRzXpkHQUUREpJyKSIFsZgPMbKmZpZnZ7YW8XtXMJoRf/97MWhd47Y7w8qVm1v9Q2zSz18LLF5jZC2ZWbma/mrFyK09/mcbQlBac2aVp0HFERCq1E9s34oqTEnll+o98vnhj0HEkYO7O1CWb6NuuEVXjYoOOIyIi5VSZF8hmFgs8DZwJJAHDzSzpgGYjgW3u3g54HHgovG4SMAxIBgYAo80s9hDbfA3oCHQBqgOXl+HbK7asvfu5acJcWjWowT3nJgcdR0QkKtzSvwOdmtbh1knzydyZHXQcCdCKzF2s3b6XUzpq9moRESlaJM4g9wbS3D3d3XOA8cCgA9oMAl4KP54EnGahmwIPAsa7e7a7rwTSwtsrcpvuPsXDgBlAizJ+f8Vy93sL2LBjH09c0J2aVXX7aRGRSKgaF8uTw7qzKzuXP0+aR+irQaLRl0szAein649FROQgIlEgNwfWFHieEV5WaBt3zwWygIYHWfeQ2wwPrb4Y+KiwUGY2ysxSzSw1MzOzhG+pZN6ds5b35q7jxtPa06NV/TL9s0RE5JeOaVKbO8/uxJdLM3n5ux+DjiMB+XJpJu0b16J5Pc3/ISIiRYtEgVzYNM0HHsIvqk1Jlxc0GvjK3b8uLJS7j3H3FHdPSUgou+FWa7bu4a/vLiDl6Ppcc0q7MvtzRESkaBcffzSndEjgwSmLWbZxZ9BxJMJ2Z+cyY+VW+nXQ8GoRETm4SBTIGUDLAs9bAOuKamNmcUBdYOtB1j3oNs3sHiABuLlU3sFhys3L56YJcwF4/ILuxOqWTiIigTAzHh7cjVpV47j+jTlk5+rWT9FkevoWcvLyOfkYDa8WEZGDi0SBPBNob2aJZlaF0KRbkw9oMxkYEX48GJgavoZ4MjAsPMt1ItCe0HXFRW7TzC4H+gPD3T2/jN/bQT3z5QpSf9zG/b/rTMsGNYKMIiIS9RJqV+WRIV1ZsmEnj3y0NOg4EkFfLs2kRpVYjk3UZU4iInJwZV4gh68pvg74GFgMTHT3hWZ2n5kNDDcbCzQ0szRCZ31vD6+7EJgILCJ0LfG17p5X1DbD2/oP0AT4zszmmtndZf0eCzN3zXae+Hw5A7s143c9DrzkWkREgnBqxyZcfPzRPP/NSr5ZvjnoOBIB7s6XyzZxQtuGur2TiIgcUkSmU3b3KcCUA5bdXeDxPmBIEes+ADxQnG2Glwc+RfTu7FxuGD+Ho+pU4/7fdQ46joiIFPCXszrxXfoWbp44l49v/A31a1YJOpKUofTNu1mzdS+jTmoTdBQREakAIjHEOur87f2FrNm6h8cv6E7d6vFBxxERkQKqVwnd+mnbnhxuf3u+bv1Uyf1Pt3cSEZESUIFcyj78YT0TUzO4pl87eic2CDqOiIgUIrlZXW7t35GPF25kYuqaQ68gFdaXyzJpk1BTc4GIiEixqEAuReuz9nL72z/QrUVdbji9fdBxRETkIEaemEjfdg25d/Ii0jN3BR1HysDenDymp2+hn2avFhGRYlKBXEry850/TZxHTm4+TwzrQXysulZEpDyLiTEeHdKdKnEx3DhhLvvzAr3xQYVlZgPMbKmZpZnZ7YW8XtXMJoRf/97MWkcq2/T0LeTk5nOy7n8sIiLFpCqulDz/TTrTVmzh3oFJJDaqGXQcEREphqPqVuMf53dhfkYWT3y2LOg4FY6ZxQJPA2cCScBwM0s6oNlIYJu7twMeBx6KVL7/LcukWnwMx+mSJxERKSYVyKVk045sBiQfxdCUlkFHERGREjizS1OGprQgc2e2Juwqud5Amrunu3sOMB4YdECbQcBL4ceTgNPMzCIV8PROTagWr9s7iYhI8QR+S6TK4q5zksjNyyeC3/kiIlJKHjyvC3G6NOZwNAcKznKWARxXVBt3zzWzLKAh8KsbUZvZKGAUQKtWrY443L0Dk494GyIiEl30a6AU6ceViEjFpM/vw1bYUeEDT8MXp01oofsYd09x95SEBF03LCIikadfBCIiInK4MoCC1xa1ANYV1cbM4oC6wNaIpBMRESkhFcgiIiJyuGYC7c0s0cyqAMOAyQe0mQyMCD8eDEx1XewtIiLllK5BFhERkcMSvqb4OuBjIBZ4wd0Xmtl9QKq7TwbGAq+YWRqhM8fDgkssIiJycCqQRURE5LC5+xRgygHL7i7weB8wJNK5REREDodplBOYWSbwY9A5SqgRhcwAGuXUJ7+k/vgl9cevqU9+qbT642h31wxTR6gUv5u1nxef+qp41E/Fp74qHvVT8R1uXxX7u1kFcgVlZqnunhJ0jvJEffJL6o9fUn/8mvrkl9QflZP+XotPfVU86qfiU18Vj/qp+CLRV5qkS0RERERERAQVyCIiIiIiIiKACuSKbEzQAcoh9ckvqT9+Sf3xa+qTX1J/VE76ey0+9VXxqJ+KT31VPOqn4ivzvtI1yCIiIiIiIiLoDLKIiIiIiIgIoAK5QjKzVWb2g5nNNbPUoPMEwcxeMLNNZragwLIGZvapmS0P/79+kBkjqYj+uNfM1ob3k7lmdlaQGSPJzFqa2RdmttjMFprZDeHlUbmPHKQ/onIfMbNqZjbDzOaF++Nv4eWJZvZ9eP+YYGZVgs4qR8bMBpjZUjNLM7Pbg84TpJJ+LlrIv8J9N9/Megb7DiLLzGLNbI6ZfRB+Xujng5lVDT9PC7/eOsjckWZm9cxskpktCe9bfbRP/ZqZ3RT+d7fAzN4Ifw9pn6Jkv+kPtg+Z2Yhw++VmNuJIMqlArrhOcffuUTwl/DhgwAHLbgc+d/f2wOfh59FiHL/uD4DHw/tJd3efEuFMQcoF/uTunYDjgWvNLIno3UeK6g+Izn0kGzjV3bsB3YEBZnY88BCh/mgPbANGBphRjpCZxQJPA2cCScDwAvt9NCrp5+KZQPvwf6OAZyIfOVA3AIsLPC/q82EksM3d2wGPh9tFkyeBj9y9I9CNUJ9pnyrAzJoD1wMp7t4ZiAWGoX3qJ+Mo/m/6QvchM2sA3AMcB/QG7jmSkyAqkKVCcvevgK0HLB4EvBR+/BLwu4iGClAR/RG13H29u88OP95J6Au7OVG6jxykP6KSh+wKP40P/+fAqcCk8PKo2T8qsd5Amrunu3sOMJ7QZ0BUOozPxUHAy+F/L9OBembWNMKxA2FmLYCzgefDz42iPx8K9t8k4LRw+0rPzOoAvwHGArh7jrtvR/tUYeKA6mYWB9QA1qN9Cijxb/qi9qH+wKfuvtXdtwGfUviJo2JRgVwxOfCJmc0ys1FBhylHmrj7egj9EAAaB5ynPLguPATlhSM5klaRhYcm9QC+R/vIgf0BUbqPhIdPzgU2EfoiXQFsd/fccJMMovggQiXRHFhT4Ln+TsOK+bkYzf33BHArkB9+3pCiPx9+7qfw61nh9tGgDZAJvBgejv68mdVE+9QvuPta4J/AakKFcRYwC+1TB1PSfahU9y0VyBVTX3fvSWiYwbVm9pugA0m59AzQltAQ0vXAo8HGiTwzqwW8Bdzo7juCzhO0QvojavcRd89z9+5AC0JnGjsV1iyyqaSUFXbGJer/TkvwuRiV/Wdm5wCb3H1WwcWFNPVivFbZxQE9gWfcvQewm4NfuhSVfRU++DwISASaATUJ/YY/kPapQyuqb0q1z1QgV0Duvi78/03AO4R+3Als/GmoTvj/mwLOEyh33xguAvKB54iy/cTM4gn9CHzN3d8OL47afaSw/oj2fQQgPBzwS0LXZNYLD3+DUOG8LqhcUioygJYFnkf932kJPxejtf/6AgPNbBWhYfmnEjqjXNTnw8/9FH69LtFzyVMGkOHuP41ImkSoYNY+9UunAyvdPdPd9wNvAyegfepgSroPleq+pQK5gjGzmmZW+6fHwBnAgoOvFTUmAz/NWjcCeC/ALIE74Lqe84ii/SR8rc5YYLG7P1bgpajcR4rqj2jdR8wswczqhR9XJ/TjZTHwBTA43Cxq9o9KbCbQPjxTbBVCk+JMDjhTYA7jc3EycEl41tjjgayfhjxWZu5+h7u3cPfWhPaZqe5+IUV/PhTsv8Hh9lFxts/dNwBrzKxDeNFpwCK0Tx1oNXC8mdUI/zv8qZ+0TxWtpPvQx8AZZlY/fMb+jPCyw2LR198Vm5m1IXTWGEJDW1539wcCjBQIM3sD6Ac0AjYSmrnuXWAi0IrQh9EQd4+KI25F9Ec/QkNnHVgFXBklX0SY2YnA18AP/P9ryP5C6Hq7qNtHDtIfw4nCfcTMuhKa9COW0IHiie5+X/jzdTzQAJgDXOTu2cEllSNloVuXPUHo7/qFaPy+/ElJPxfDP+T/TWiimz3AH9w9qm4taWb9gFvc/ZyiPh/MrBrwCqFrurcCw9w9PajMkWZm3QlNZlYFSAf+QPhzFe1TP7PQ7QQvIDSb/BzgckLXyEb9PlWS3/QH24fM7DJCn2kAD7j7i4edSQWyiIiIiIiIiIZYi4iIiIiIiAAqkEVEREREREQAFcgiIiIiIiIigApkEREREREREUAFsoiIiIiIiAigAllEREREREQEUIEsIiIiIiIiAqhAFpGDMLMuZvZtgec9zWxqkJlEREQEzKyFmV0QdA6RykYFsogczEKgrZnFhp8/CtwSYB4REREJOQ3oGXQIkcomLugAIlJ+uXu+mS0Eks2sPbDa3WcHnUtERCSamdmJwGPAdjPrD5zn7isDjiVSKahAFpFDmQ70Ba4BBgScRUREJOq5+zdmNhO4xd0XBJ1HpDJRgSwihzIdGAc87e5rA84iIiIiIR2ApUGHEKlsdA2yiBzKEiAbeCjoICIiIgJm1hDIcvf9QWcRqWxUIIvIodwA3OHuu4MOIiIiIgAkAuuCDiFSGalAFpFCmVlbM1sCVHf3l4LOIyIiIj9bAjQyswVmdkLQYUQqE3P3oDOIiIiIiIiIBE5nkEVERERERERQgSwiIiIiIiICqEAWERERERERAVQgi4iIiIiIiAAqkEVEREREREQAFcgiIiIiIiIigApkEREREREREUAFsoiIiIiIiAgA/w9zWnIHhBkACAAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "init()\n", "vmid = time_loop(1000)\n", "plot()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.9" } }, "nbformat": 4, "nbformat_minor": 2 }