{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Simulate both drift and start point biases" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "from Leite & Ratcliff (2011) -- What cognitive processes drive response biases? A diffusion model analysis:\n", "\n", "\"In the diffusion model, there are two ways to model response bias (Ratcliff, 1985; Ratcliff et al., 1999; Ratcliff & McKoon, 2008). One, analogous to the change in criterion threshold in SDT, involves a shift in the criterion that separates positive from negative drift rates. That is, one parameter (referred to as a “drift criterion” parameter, “dc”) produces an estimate of the amount to be added to or subtracted from the mean drift rates between conditions such that a null mean drift rate (a horizontal line starting at z in Figure 1.1) in an unbiased condition would be shifted to a positive or negative mean drift rate in a biased condition, for example. For small to moderate biases in drift rates, there are only small changes in the leading edges of the RT distributions between biased and unbiased conditions. The other way to model response bias involves moving the starting point of the diffusion process nearer the boundary toward which the responses are biased (Figure 1.1). This predicts a shorter leading edge of the RT distribution in the biased condition than in the unbiased condition (Ratcliff, 1985, 2002).\"\n", "\n", "Can we replicate this?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, let's try this analytically!" ] }, { "cell_type": "code", "execution_count": 75, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from __future__ import division\n", "import numpy as np\n", "from scipy import integrate\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "import seaborn as sns\n", "import math" ] }, { "cell_type": "code", "execution_count": 76, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def DDM(timepoints,v,a,z,s,eta,sz):\n", " \n", " Ge = np.zeros(len(timepoints))\n", " Gc = np.zeros(len(timepoints))\n", " \n", " if eta == 0 and sz == 0:\n", " Pe = sim_Pe(v,a,z,s)\n", " for i, t in enumerate(timepoints):\n", " Ge[i] = sim_G(t,v,a,z,s,Pe)\n", " Gc[i] = sim_G(t,-v,a,a-z,s,1-Pe)\n", " \n", " if eta > 0 and sz == 0:\n", " x, w = lgwt(21,v-(4*eta),v+(4*eta))\n", " Fe = np.zeros(len(w))\n", " Fc = np.zeros(len(w))\n", " for i, t in enumerate(timepoints):\n", " for j in range(len(x)):\n", " Pe = sim_Pe(x[j],a,z,s)\n", " Fe[j] = sim_G(t,x[j],a,z,s,Pe) *(1/np.sqrt(2*np.pi*(eta**2)))*(math.e**(-(((v-x[j])**2)/(2*(eta**2)))))\n", " Fc[j] = sim_G(t,-x[j],a,a-z,s,1-Pe) *(1/np.sqrt(2*np.pi*(eta**2)))*(math.e**(-(((v-x[j])**2)/(2*(eta**2)))))\n", " Ge[i] = np.sum(Fe*w)\n", " Gc[i] = np.sum(Fc*w)\n", " \n", " if eta == 0 and sz > 0:\n", " x, w = lgwt(21,z-(sz/2),z+(sz/2))\n", " Fe = np.zeros(len(w))\n", " Fc = np.zeros(len(w))\n", " for i, t in enumerate(timepoints):\n", " for j in range(len(x)):\n", " Pe = sim_Pe(v,a,x[j],s)\n", " Fe[j] = sim_G(t,v,a,x[j],s,Pe) *(1/sz)\n", " Fc[j] = sim_G(t,-v,a,a-x[j],s,1-Pe) *(1/sz)\n", " Ge[i] = np.sum(Fe*w)\n", " Gc[i] = np.sum(Fc*w)\n", " \n", " return Gc, Ge\n", "\n", "def sim_Pe(v,a,z,s):\n", " \"\"\"\n", " function for estimating probability of an incorrect response given:\n", " v = drift rate\n", " a = boundary separation\n", " z = starting point\n", " s = noise\n", " \"\"\"\n", " return (math.e**(-2*v*a/(s**2))-math.e**(-2*v*z/(s**2)))/(math.e**(-2*v*a/(s**2))-1)\n", "\n", "def sim_G(t,v,a,z,s,Pe):\n", "\n", " \"\"\"\n", " function for estimating probability of an incorrect response given:\n", " t = current time point (in seconds)\n", " v = drift rate\n", " a = boundary separation\n", " z = starting point\n", " s = noise\n", " Pe = probability of incorrect response\n", " \"\"\"\n", "\n", " tol = 10e-29 # threshold for terminating sum component of equation\n", " sum_terms = [0]\n", " diff_terms= [1,1]\n", " k = 0\n", " while True:\n", " k += 1\n", " sum_terms.append(sum_terms[k-1] + ((2*k*np.sin(k*np.pi*z/a)*math.e**(-0.5*((((v**2)/(s**2))+((np.pi**2)*(k**2)*(s**2)/(a**2)))*t)))/(((v**2)/(s**2))+((np.pi**2)*(k**2)*(s**2)/(a**2)))))\n", " diff_terms.append( sum_terms[k] - sum_terms[k-1] )\n", " if (abs(diff_terms[k]) < (sum_terms[k-1]*tol)) and (abs(diff_terms[k-1]) < (sum_terms[k-2]*tol)):\n", " break\n", " \n", " return Pe-((((np.pi*(s**2))/(a**2))*math.e**(-(v*z/(s**2))))*sum_terms[k])\n", "\n", "def lgwt(N,a,b):\n", "\n", " \"\"\"\n", " This script is for computing definite integrals using Legendre-Gauss \n", " Quadrature. Computes the Legendre-Gauss nodes and weights on an interval\n", " [a,b] with truncation order N\n", "\n", " Suppose you have a continuous function f(x) which is defined on [a,b]\n", " which you can evaluate at any x in [a,b]. Simply evaluate it at all of\n", " the values contained in the x vector to obtain a vector f. Then compute\n", " the definite integral using sum(f.*w);\n", "\n", " Written by Greg von Winckel - 02/25/2004\n", " Translated to Python by JW de Gee - 2016.\n", " \"\"\"\n", " \n", " # Params:\n", " N = N-1\n", " N1 = N+1\n", " N2 = N+2\n", " \n", " # Initial guess\n", " xu = np.linspace(-1,1,N1)\n", " y = np.cos((2*(np.arange(0,N+1))+1)*np.pi/(2*N+2))+(0.27/N1)*np.sin(np.pi*xu*N/N2)\n", "\n", " # Legendre-Gauss Vandermonde Matrix\n", " L_raw = np.zeros((N1,N2))\n", "\n", " # Derivative of LGVM\n", " Lp_raw = np.zeros((N1,N2))\n", "\n", " # Compute the zeros of the N+1 Legendre Polynomial\n", " # using the recursion relation and the Newton-Raphson method\n", " while True:\n", " L = L_raw.copy()\n", " L[:,0] = 1\n", " L[:,1] = y\n", " Lp = Lp_raw.copy()\n", " Lp[:,0] = 0\n", " Lp[:,1] = 1\n", " for k in range(2,N1+1):\n", " L[:,k] = ((2*k-1)*y*L[:,k-1]-(k-1)*L[:,k-2]) / k\n", " Lp = (N2)*( (L[:,N1-1]) - (y*L[:,N2-1]) )/(1-y**2)\n", " y0 = y.copy()\n", " y = y0 - (L[:,N2-1] / Lp)\n", " if max(abs(y-y0)) < np.spacing(1):\n", " break\n", " \n", " # Linear map from[-1,1] to [a,b]\n", " x = (a*(1-y)+b*(1+y)) / 2 \n", "\n", " # Compute the weights\n", " w = (b-a)/((1-y**2)*Lp**2)*(N2/N1)**2\n", "\n", " return x, w" ] }, { "cell_type": "code", "execution_count": 77, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# Set timing parameters\n", "tmax = 4.0 # max RT (in seconds) to estimate first passage times to\n", "dt = 0.01 # time step (in seconds)\n", "timepoints = np.arange(dt,tmax,dt)" ] }, { "cell_type": "code", "execution_count": 78, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 78, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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4ByPiz++HkSOTWLLEwaWXBrj7bl/cB/fl+/J4fMkjvPDLs/hCPo5p0pXbTvyX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\nLCyfpwHvkHQFqZvza6SLz1BWPlvGWUo+Jb3e5ij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pMH6p1ZacJdk5ACTGxBv6nfzpeE4Z9Q59pvXh72seYcPEDYQEhZS1+VPOykhO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\n/4a8zfJx6xjZegwbT/zGdfO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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Set parameters\n", "v = 0.08 # drift rate\n", "eta = 0 # drift rate variability\n", "a = 0.2 # boundary separation\n", "z = a / 2 # starting point\n", "sz = 0 # starting point variability\n", "Ter = 1.0 # non-decision time\n", "s = 0.1 # noise\n", "\n", "# Estimate choice probabilities and defective cumulative probability distributions\n", "Gc, Ge = DDM(timepoints,v,a,z,s,eta,sz)\n", "RTe = np.diff(Ge)\n", "RTc = np.diff(Gc)\n", " \n", "plt.figure()\n", "plt.plot(np.arange(dt,tmax,dt)+Ter, Gc+Ge, color='b', label='all trials')\n", "plt.plot(np.arange(dt,tmax,dt)+Ter, Gc, color='g', label='corrects')\n", "plt.plot(np.arange(dt,tmax,dt)+Ter, Ge, color='r', label='errors')\n", "plt.legend()\n", "plt.xlabel('Time (s)')\n", "plt.ylabel('Cumulative proportion of trials terminated by bound')\n", "\n", "plt.figure()\n", "plt.plot(np.arange(dt,tmax,dt)[:-1]+Ter, RTc, color='g', label='corrects')\n", "plt.plot(np.arange(dt,tmax,dt)[:-1]+Ter, RTe, color='r', label='errors')\n", "plt.xlim(0,tmax)\n", "plt.legend()\n", "plt.xlabel('Time (s)')\n", "plt.ylabel('RT probability')" ] }, { "cell_type": "code", "execution_count": 79, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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iEgVRqPmq90nuo49S+OgjD716+TnpJP9fljdtGuS55wo55ZRMxo9PY599AvTp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\nZ/ztIVKvqN5LONavdxEIuBx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S76xdGzpBbu3+HVdREaVm77jmCTZuwpZZzxPIziHnqsvx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\n7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LZblNdey1m/5o+IZI7qvWysshKiUSctiy7XdeSRbpP/ued0/S+SDslM1zoD2NNae6G1\ndgKwD3BRemNJe7FkifsS6tOndRf+Y8aEAHjwQX2SK+IRqvlST6qnayWMGhUmEnGYPVsX+iJZoHov\nGygvd2t9cXF6mzy9esXZc88oCxfmrH9/EZHUSabJUwmEN7pdnZ440t58/71bmLfeunVvBtttF+eA\nAyK8+64fa5N5OYpImqnmSz3pavKMGOEuwPnMM2ryiGSB6r1sINHk6dIlvU0egKOPdqdszZ2r+i+S\nao3+rTLGXF377SpgoTHmMSACHAssykA2aQe+/95Hbm68TRf+Y8aEefNNPw8/HOCGG7Q4j0g2qOZL\nU1avdi/8N9kktRf+W2wRZ+DAKG+95WfpUodevdL/DwuRzk71XhpTXu5+TfdIHnCnbF19Ncye7ef3\nvw83f4KIJK2p1mli7Nz7tV8Lar8uSPbBjTEOMAXoi/vJwDhr7eI6x48ErsL9FOEBa+20xs4xxpQA\n9wHdgBzgVGvtt8lmkfT4/nuHrbaK42vDIJzDDovQs2eMxx8PcPnlNRQWpi6fiCStTTVf9b5jW7PG\nIT8/TkFB8/dtqWOOifDWW35mzQpw/vmh1D+BiGxM9V4alBjJU1SU/ufaaqs4e+0V5Z13cvjpJ4fN\nNlOTXyRVGv2nubX22sR/uEX5I+BfwL21P0vGCCDXWrsfcBkwOXHAGOOvvX0IMBg4s7bQN3bOLcAM\na+1g3DeOHZP9n5T0WLcOfv7Zx1ZbtW0hzkAAfve7MGVljhZgE8mSFNR81fsObPVqJ21b6g4fHiYY\njPP006r/Ipmgei+N+aXJk5mGi6ZsiaRHMrtrDQU+BU4DxgD/NsYMT/LxBwLzAKy17wF71Tm2E7DI\nWltmrQ0DbwEHNnDOnrX33x/Y2hjzEnAy8HqSGSRNfvjBfSPo1avtu62MHh3G54vz4IPBNj+WiLRe\nG2q+6n0Hls4mT9eucMghEf773xy++EJrs4lkiuq9bKyiwv2aiTV54JddtrT4vkhqJXM1dQMw0Fo7\nylo7EtgXuD7Jxy8GSuvcjhhjfI0cqwC6AkUb/TxqjMnB3d5xtbV2CLAUuDTJDJImP/zg/lFutVXb\n3wi22irOoYdG+PTTHD79VBf5IlnU2pqvet9BhUJQUeGkfD2eukaNci/0tQCzSOQ5D2IAACAASURB\nVEap3ssGMjldC2DLLeP07x/hnXdyWLFCu2yJpEoyV1OBunNja+fPJvuv8DLcop7gs9bG6hwrrnOs\nCFjTyDlRY8wqYE7tz+aQxJtQSUmGKlQrtfd8VVXu11//OpeSktw2P98FF8C8efD444UMGdK2bNnm\n5XxezgbezuflbCnU2pqf1XoP3v7z8XI2aDrfsmXu1y228Kft/+Okk2D8eHj22Vxuvz13g3Xe2vPv\nzgu8nM/L2cD7+VJA9T5NvJyvqWzRqPu1V698Skoyk2f0aHj/fViwoAu77NJ+f3de4OV8Xs4G3s/X\nUsk0ef5njPkjML329jhgSZKPvxAYDjxljBkAfFbn2H+B7Y0x3YAqYBBwa+2xhs55CzgCeBQ4APhP\nc0++cmV5kjEzr6SkqN3nW7QoCORSUFDFypXRNj9nv37Qu3chM2c6XHppBV27tj5bNnk5n5ezgbfz\neTkbpPTNqbU1P6v1Hrxb89vDa6epfIsW+YBCCgpCrFyZvh0Qjzgij8ceCzB3bhUDBkSTypZtytd6\nXs4G3s6neu/deg/ef+00lW358lwgSDRaycqVbV+OIRmHHOLg9xfywAMxJkzIabe/u2zzcj4vZ4P2\nka+lkunWj8UdvrkY+Lb2+zOTfPxZQI0xZiFwGzDeGHOSMWactTYCTMBdyX8hMN1au6yhc2of6yJg\njDHmbWAo8OckM0iaJIZVbr55aobw+3xw6qlhqqocnnwykJLHFJEWa23NV73voNasSc/26RsbNcrd\nQlcLMItkjOq9bCCxJk+mFl4G6NEjzsEHR/n88xw+/zxjTyvSoSVzJXW+tfaE1jy4tTYOnL3Rj7+q\nc3wuMDeJc7DW/g84tDU5JD2WL3cv/FO55eFJJ4W5+eYgDz0UYOzYMI6m54pkWqtqvup9x7VqVWaa\nPAMHRtlssxizZwe44YYaglqHXyTdVO9lA5lekyfh+OPDzJ/v55FH4KKLMvvcIh1RMiN5jjTG6J/a\nUs+KFQ45OXE23TR1F/4lJXGGD49gbQ7vvZeTsscVkaSp5ssGEiN50rW7VkJODowcGWHNGoeXXtJo\nHpEMUL2XDSSaPJnaXSthyJAIxcVxHn30l3WBRKT1krmKWgV8aYz5GFiX+KG19vS0pZJ2YflyHyUl\ncXJS3Iv5/e/DzJoV4MEHA+vXZRCRjFHNlw2sXZuZJg/AySeH+fvfg8yYEWDYsEjan0+kk1O9lw2U\nl0NOTpyCgsw+b14eHH10mEceCfL22zkceKCu/0XaIpkmz0NpTyHtTjwOP/3ksOOOqV+UbcCAKMZE\nmTPHz6RJDiUlmf00QaSTU82XDZSVuV+Li9Nfi3faKcaee0Z59dUcvv/eydjuLiKdlOq9bKC83KGo\niKwsl3DccREeeSTIk08G1OQRaaNmp2tZax8C/gX0ALoC79X+TDqxsjKornZSuh5PguPAmDFhwmGH\nmTO1ALNIJqnmy8ZKS92r/cZ2PEy1U08NEY87PPqo6r9IOqney8YqKpyMLrpcV//+Ufr0geef91NZ\nmZUIIh1Gs00eY8yFwJPAlsC2wBxjzGnpDibe9vPP7kV/SUl6tlc87rgwBQVxHn44QCwzOziKCKr5\nUl9ZWaLJk5kL/6OOilBUFGfmzIDWZhBJI9V72Vh5uZPx9XgSfD4YPRqqqhyef17rsom0RTILL/8B\n2NNae5G1djzQH7g4vbHE637+2X3p9OiRnjeCrl1h5Mgw//ufj9df1wLMIhmkmi8bSIzkydSnu4WF\ncMwxYX780ce8eRl5SpHOSvVe1ovH3TV5sjWSB+D3v3e/zpihkZwibZFMk2c1EK5zuwIoT08caS8S\nI3lSubPWxsaMcV92Dz6oQi+SQar5soGyMge/P7MLcY4e7b4Ep07N3HOKdEKq97LeunUQjToZ3z69\nru22gwMPjPDee36sTeafqSLSkGTGwn0DvGuMmQlEgJFAmTHmagBr7XVpzCcelWjypGskD8Duu8fY\nffcoCxb4+eEHh6220gLMIhmgmi8bKCtzp2plciHO3XaL0bdvlLlzc1i+3GHzzVX/RdJA9V7WS2yf\nns2RPACnnhrmjTf8zJgRYNKkmqxmEWmvkmmRfgXMAvKALsBLwNuAU/ufdEKrVqV/JA+4o3liMUfD\nNkUyRzVfNlBamp1PdkePDhONwsMPq/6LpInqvaxXXjuGK9tNnqFDI2y6aYwnnghQXZ3VKCLtVrMj\neay112YiiLQvmZiuBTBiRJiJE3OZMSPAhAkhArrWF0kr1XzZWHm5w+abZ34F/GOOCTNpUh4PPRTg\nj38MEQxmPIJIh6Z6L3UlRvJ06ZLdHMEgnHhimL/+NZe5c/2MGhXJbiCRdkiTHaVVMjWSp7AQjj8+\nzIoVPubN00r7IiKZFAq5O50UF2f+k90uXWDsWFi50sfs2ar/IiLp5JXpWgCnnOIuFfXII/p0V6Q1\n1OSRVsnEmjwJiQWY77tPhV5EJJMS26dno8kDcM454Dhxpk3TMB4RkXTyUpNnu+3iDBoU4Z13/Hz9\ntWYOirRUo00eY8yYTAaR9uXnn91PdjMxfN6YGAcfHOGf//Tz0UfqS4qkg2q+NKSszP3atWt2Lvq3\n285dn+Hjj3NU/0VSRPVeGpJYkydbTf2NJXZZfOghNflFWqqpK6YLMpZC2p01axy6d8/cm8A554QA\nuOceFXqRNFHNl3p+GcmTvQzjxiVGc6r+i6SI6r3UU1HhjTV5Eo44IkLPnjH+8Y8AFRXZTiPSvuhj\nMWmV0tLMNnn23z9au52un0WLMva0IiKdWmlpdqdrAQwaFMWYKHPm+FmxQsP2RUTSwUvTtcBdgPm0\n08KUlzs89piWbBBpiaZWMtzZGLO4gZ87QNxau12aMonHrVsH69Y5GR2+7zhw7rkhzjgjn8mT4brr\nMvbUIp2Far7UkxjJk63pWuDW/3Hjwlx8cR4PPBDg0ktDWcsi0kGo3ks9XtlCva5TTw1z++1Bpk4N\ncvrpYXwaniCSlKaaPF8DR2QqiLQfiU92MzmSB2DYsAi9e8d48EEf553nUFLinTchkQ5ANV/qyfbC\nywnHHRfmppuC3H9/kHPPDXlmOoFIO6V6L/X8MpIny0Hq2HTTOMceG+bRR4O89FIOQ4dGsx1JpF1o\nqskTstYuyVgSaTfWrs3OJ7t+P5x9dojLLstj+nR9miuSYqr5Uk9pqfs1m2vyABQUuKN5br45lxkz\nApx1Vji7gUTaN9V7qSexJk9hobc+RD3jDLfJM3VqkKFD12U7jki70NSgt4UZSyHtSqLJk+mRPAAn\nnRRm001h+vTg+l1fRCQlVPOlHi9M10o4/fQQBQVx/va3ICH1+EXaQvVe6qmsdL926ZL9el/Xb34T\nY9CgCG+95eeLLzRfSyQZjf5Nsdaea1xb1v25MWYzY8zU9EcTr1q71v3arVvm3wQKCuDCC90pY9pp\nRSR1VPOlIV6ZrgXQvbu7pe6yZT6efrqpgcgi0hTVe2lIZaVb7wsKshykAWee6Xb2p07VAswiyWi0\nyWOMmQh8BHxljDnEGJNjjLkUdx7vNpkKKN6TGMmTjSYPwDnnwCabxLj3Xo3mEUkV1XxpiBd216rr\n7LNDBAJx7r47SCyW7TQi7ZPqvTSkqsohNzdOwIN9lCFDomy/fZQnnwzwww/aZVGkOU2NeRsD7AAc\nCIwH5gG/A46z1g7NQDbxqF+aPNl5/qIiOPvsMKWlDtOmaTSPSIqo5ks9XpquBbDllnGOPTbC11/n\nMG+eRvOItJLqvdRTWem99XgSfD44//wQ4bDDlCm69hdpTlNNnnJr7TJr7UdAf+DfwO7W2vmZiSZe\nle2RPABjx4bo3j3OvfcG12/5KCJtopov9ZSVgePEPbXbyrnnhnCcOJMnB4l7898jIl6nei/1VFY6\nnpyqlTBqVIStt44xY0aAlSs1mkekKU01eeoOhP7ZWnuhtVb71glr1qSnyeP77lsCr79K8MW5+D/9\nGKqrG71vly7usP21azWaRyRFVPOlntJShy5d3E9RvWKHHWIcfXSEf/87hxdf1GgekVZQvZd6qqq8\nO5IHIBCAc84JsW6do7V5RJrR1GVb3b/l2q9O1kus0ZCS3bXicXKfeZJuQw6kR/++dDt+BF3HnET3\nQwez6Y7bUnz6aAIL36Khj2vHjg3RrZu700piMWgRaTXVfKmnrMzxzFStui6+OITPF+fmm7U2j0gr\nqN5LPZWVDoWF2U7RtJNPDlNSEuP++4OUlmY7jYh3NfUR2M7GmMW1329V53sHiFtrt0tvNPGqxEie\ntl74O2WldJlwPnmzZxH3+agZMpTI7nsQzy8g5/v/EXjjNXKff47c558j3H8AFTfcTKRvv/XnFxXB\neeeFmDQpl7vvDnLVVdpTV6QNVPOlntJSh169vNdF2WGHGKNGRXjyyQCzZ/sZMSKS7Ugi7YnqvWwg\nEoHqasfTI3kA8vPhrLPCTJqUy/33Bxk/Xtf+Ig1pqsnz64ylkHaltNRdfT8/vw0Psm4dXX93PIH3\n3iW8z76U3X0vsT7b1rub/8P3KbhrMrnzXqDboYNZ93/nw203rz8+blyI6dMD3HdfkLFjw2y5pbff\nnEQ8TDVfNhCLQUWFd3bW2tiFF9bwzDN+br01yJFHRsjJyXYikXZD9V42UFXlfvV6kwfgtNNC3H13\nkHvvDTJ2bIji4mwnEvGeRps81tolmQwi7ceaNe7wfae1a57F4xSfNZbAe+9SffQxlN87ncauziN7\n9afs4ccIvPUGXS66gIJ77oSFb5Dz1/uI/tqQnw+XXFLDBRfkc8stQe64o6b1/2MinZhqvmysogLi\nccezF9DbbRfnxBPDPPpokKef9nP88RrNI5IM1XvZWGWle1Hv5YWXE7p0cRfgv/76XKZMCXLppRrN\nI7IxDy2lKO1FaWnb1uPJm/EQuS8+T2jgAZT/9e+NNnjqCg86kDWvvM26U8bAp5/S7bCDCM5/EYDj\nj4+w445RHnsswJdf6iUtIpIKFRXuRX+XLt79ZHfChBCBQJxbb82lRj1+EZFWqax0v7aHkTzgrstZ\nUhLj3nuD2mlLpAFp3ZbCGOMAU4C+QDUwzlq7uM7xI4GrgDDwgLV2WhLnnAyca63dL53ZpWGxmLuF\n+vbbt26NBt+yHym85kpiRcWU3zMVcnOTP7lLFyom303+sMNwTj+d4lNPpPKKiaw7bzxXXlnDKacU\ncMMNuTzyiNYQFMk01fuOJ9Hk8fJFf69ecU47LczUqUHuvz/A2WeHsx1JpMNTve942tNIHoDCQrfJ\nf9lledx1V5BJk9TlF6kr3cMeRgC5tQX7MmBy4oAxxl97+xBgMHCmMaakmXP6AaenObM0oaICYjGH\n7t1bd37hpIn4ysuonDiJ2BZbtu5BTjyRtbPnEdtiS7pcfw1dLpnAkINC7LtvhPnz/bz5phZmEMkC\n1fsOpqLC/dqlS3ZzNOfCC2vo2jXO5Mm5rF6d7TQinYLqfQdTVeX9pv7GRo8O07t3jAceCPD99xrN\nI1JXups8A4F5ANba94C96hzbCVhkrS2z1oaBt4ADGzvHGNMDuB64IM2ZpQmJnbW6dWv5m4Bv8Tfk\nPvMkkZ12pvqUMW3KEenbj7XzXyOy867kPzidrn84jUlXleM4ca64IpewPswVyTTV+w6mvNyt90VF\n3r7o797dbfSUljrcdlsLRoeKSGup3ncwv0zXym6OlggG4aKLagiFHG67LZjtOCKeku4mTzFQWud2\nxBjja+RYBdAVKGrgnCAwDZgAVOJu8ShZsHZt65s8BXffjhOLUTXhYvC1/aUX67k5a597gdC++5M7\n51kG3TiSU0+swtoc7r8/0ObHF5EWUb3vYNrDmjwJp58epk8f9xPdb77RS0YkzVTvO5jEdK32NJIH\n4LjjIhgTZebMAF98oXU5RRLSuiYPUIZb1BN81tpYnWN19+woAtY0dA6wG7A98DcgH9jJGDPZWjuh\nqScvKSlq6nDWted8W20VpKSkBV3zH36Ax/8BO+5I8WmnJLXYclLZSorg1Zfh5JMJzprFbXsfy+xu\nL3DrrXmccUYePXu26Wnans+DvJwNvJ3Py9k8IKv1Hrz95+PlbNBwvkQvfost8igpyctwol8k+7v7\ny1/g2GPhxhu78NxzaQ5VR3v8s/UKL2cD7+fLItX7Zng5n5frPbT8dzd5MgwbBtddV8jLL9P63X+T\n4OU/V/B2Pi9nA+/na6l0N3kWAsOBp4wxA4DP6hz7L7C9MaYbUAUMAm6tPbbBOdbaD4FdAYwx2wAz\nk3kDWLmyPGX/I6lWUlLULvN9950fyCcQqGblyuTnRBVMmUphJEL5uLOpXl2V+mz3TKfI8dPjmSe5\nttctnL/0EsaPD3PnndVteq6U5fMIL2cDb+fzcjbwxJtTVus9eLfmt4fXTkP5fvwxAOQB61i5MrXb\nk/u+XUzwjdfwLfsBZ101sZ6bE9lpJ8L9991gEaCW/O4GDYIBA/KZPdvP449XcdBB0ZRmbkh7/bP1\nAi9nA2/nU733br0H7792Gsq2fLlb76PR1Nf7lmjN727vveGgg/J59VU/Dz+8jiOOSE9+L/+5grfz\neTkbtI98LZXuJs8sYIgxZmHt7dOMMScBhbUr7U8AFuAOz5xurV1mjKl3TpozSgskpmt17dqC4Zzx\nOLkzZxDPz6dm5Kj0BPP73d26/H7+74nLmZY3gpkzDSefHGaffdJ/oS8iqvcdTTqma/k/fJ/CSRMJ\nvruwwePxQIDQoYez7tTTCA8+qEWP7Thw4401HHJIDpdcksebb1aSn5+K1CKyEdX7Dqa9TtdKuO66\nGt58M4drrsnl4IMjLdq8V6QjSmuTx1obB87e6Mdf1Tk+F5ibxDl1jy8BtL1ilpSWtnxNHv97/8T/\n7WKqjz2BeFFx8ye0Vk4O5XdOoYvfz9/+cRoDeZsL/+jnldejKvYiaaZ63/EkdtdKyUKc8TgFk2+h\n8OYbAAgNPoiaYUcRNTsSz83Ft2wZgY8/JPjSPHLnziZ37mzCe/WHG2+Avvsk/TQ77xzjjDPC3Htv\nkLvuCnLJJaEUhBeRulTvO55fFl5un02eX/86xumnh5k6NcjUqUHOO0+1Xzo3rVAlLVJeO5KtJVvq\n5j3+KADVJ/4uDYk2kpNDxeS76XfqTvwfU/jqmyB33qiRPCIiLZWykTzxOF0mnEfhzTcQ7dWbtbPn\nUfrEs1SPOZ3wgP2I9NuT0BHDqbzyGta8/i5r5r1KzRFHEvjwfRgyhOJTT8L3/dKkn+5Pf6phiy1i\n3H13kMWLtY6riEhzEiN5CgqyHKQNLrqohk02iXH77UGWL1ftl85NTR5pkbIyt2gWFyd50R+JkPvC\nHKKbb0F44AFpTFaHz0fFrbdz9WjL1izlzimFfPluafPniYjIeokmT1u3UC+44y/kP/ow4d37sWbe\na4QHNPFhveMQ2WMvyh58lDUvvwkHHkjuvLlsMrA/edPuhXjzWbp0geuvd7fVveSSvGROERHp1Kpq\nl8tsryN5ALp1g8suC1FR4XDFFRrCL52bmjzSIi1t8gQ+fB/fmjWEDj08JdumJ81xcP5yA3cOeZYw\nAS46YRWxFT9n7vlFRNq51ozc3FjwlQUU3jiJ6Na9KJ3xJPGSkqTPjey2O7z2GmV3/Y14Xi5Fl/+J\n4pOPxfnpp2bPHT48wkEHRXjjDT9PPJHu5QdFRNq3X9bkyXKQNho9Oszee0eZMyfAggVt28lXpD1T\nk0dapLy8ZU2e4LwXAAgddnjaMjXKcRg0YwzH/ep93q/uy0MHP4WzcmXmc4iItENtnq5VWUmXi8cT\nDwQofWgm8c02a/ljOA41J/6O1W+8R+i3B5P7yktsMnhfgq8saO40brmlmsLCOFdemaeh+yIiTWjv\nCy8n+Hxw223VBAJxLr00b/3aciKdjZo80iJlZeA48aQ/2Q0ueJF4QQGhgQemN1hjHIdrZ+/EZvml\nXPXT+fxv2AQ1ekREklBZ6RAMxlu9cH3hrTeS8/1Sqs65gOiuu7UpS7xnT0pnPk3FpBtxykrpetKx\nFNx6I8RijZ7Tu3eciRNrKC11uPBCTdsSEWlMZaV7fd8RdiTccccY554b4vvvfdx8s6ZtSeekJo+0\nSFmZQ5cuyc28yvlmEf6vFxE68CDIy0t/uEZsWgJ3TAsQIpcx300ib8TIpIb7i4h0ZhUVrR/F41v6\nP/KnTiHauw9Vf7woNYF8Ptb94RzWvvgK0d7bUHjrjRSPPgFn7ZpGTxkzJsygQRFeesnP449r2paI\nSEMqKx0KCjK7skI6/fGPIbbdNsZ99wX45JMO8j8l0gJ61UuLlJc7ya/H89orAISGDE1npKQcMiTK\naaeF+JxduXrRGLqNGq5Gj4hIE8rLnVavx1Pw1ztwIhEq/3RZyrdriezalzULXic0+CByX5pP90MH\nk/Ofzxu8r+PAHXf8Mm3rxx81bUtEZGOVlU67n6pVV34+TJ5cTSzmcM45eaxbl+1EIpmlJo+0SEua\nPMGFbwMQGpSlqVobmTixhu23j3I7E3jdbkW3Y4bhrFiR7VgiIp5UUdG6i37fiuXk/eMRor37UHPM\ncWlIBvFNelA682kq/3gROd99S/dhQwi+OLfB+/bqFefaa2soK3Mv9qPRtEQSEWm3KivTt326b8l3\n5E3/O0Xnn03X446m6wkjKTrrdAom30Lg7TchHE7L8+6/f5Qzzwzx9dc53HCDpm1J56ImjyQtHnd3\nW0lqO91YjMC7bxPduhex3tukP1wSCgpgyhR3MbaT85/hp6/K1OgREWlAPO5O12rN9un5992LU1ND\n1fnjwZ/GKVI5OVRdfjWl988A4hT//mTy77q9wW3WR48Oc/jhYRYu9HPXXcH0ZRIRaYeqqlI/kidn\n0VcUjz2VHnvvRtFlF5P32KME33iN4GuvkPfMUxTedD3djhlOj9/8iqJz/4D/g/carN9tccUVNeyw\nQ5SpU4O8+aZ225LOQ00eSVplJUSjDkVFzd8358v/4lu9mvB+A93x8h6x++4xrrmmhpXrijl+izdh\n0Td0O2YYvhXLsx1NRMQz1q2DWKwV07XCYfJmziDWrRvVx5+UlmwbCw0/irVz5hPbYku6XD+RovPO\ngpqaDe6TmLa15ZYxbrklyPvv6/JHRATcvkplZWp31sqdOYPuBw8kd86zhPvtQfmtd7D6nY9Y+d1y\nVi5ZwaoPP6P04cdYd/oZxLt0Ie+JmXQfNgT69yc4d07Kmj35+XDPPdXk5MQ5//w8SktT8rAinqer\nHElaS7ZPD7xbO1Vr/0FpzdQa48aFOeqoMAuXbc+f+s3Dv+gruo5Uo0dEJCFR71u68HLw1ZfxrfyJ\n6mNPyOiC+5Fd+7J2/muE99iTvCdm0m3UkfV2Uuze3R3NGY/D2Wfn62JfRAS3Jx6NOhQWpubxCm75\nM8UX/B/x3DxKpz/M2nmvUT3mdKLb7+AOq8/PJ9Z7G0KHHUHFTbex+uP/sPaZ56k5fDh8/DFdT/sd\n3Y44mMDCt1KSZ/fdY0yYEOLHH33aaVE6DTV5JGllZe5FfzLD9xPr8YT3G5jWTK3hOHD77dVst12M\n2z85hCcOvw//14voOuIIfMuXZTueiEjWVVa6X1s6XSvvH48AUH3S6FRHalas5+asnfUC1SNHEXj/\nn3Q/7LfkfPGfDe6z335Rxo8PsXSpj/POy2tqB3YRkU6hstK9vk/FSJ78v99D4V9uIrpNH9a89Aah\nI0c0P6LfcQgPPICyh/4BX3xBzZEjCHz0Id1GDqP4lOPx/W9Jm3ONHx+if/8Is2cHePDBQJsfT8Tr\n1OSRpJWVuV+bHckTj7vr8Wy1tWfW49lYURFMn76O/Pw4Y98ay4cn3YT/m6/dET1q9IhIJ1dRkRjJ\nk/w5zsqVBF+aR3jXvkR33S1NyZqRn0/5vfdTeckV5Cz9H92GDSG44MUN7nLhhSEGDYowb16A22/X\n+jwi0rklmvptHckTeOdtCq++nGjPzVn71GxifbZt+YMYQ9n0h1kz/zVC+w8id8E8NhnUn/y7JkMo\n1Opsfj9MnVrNJpvEuOqqXP79b/0TWDo2vcIlab9M12r6fr4l3+FbtYpw/308tR7PxnbeOcadd1ZT\nUeFw7DsXs3TcFW6jZ8QR+Jb9mO14IiJZk2jytOST3dz5L+BEItQce0K6YiXHcai68BJKpz+ME4tS\nPPpE8u+5a/0aD4mL/a23dtfnefllLcYpIp1XKkbyOKVrKTrnTPD5KHtgBrFt+rQpU6TfnpQ+8zxl\nU+4jXtiFLtdfQ/eDB+J/75+tfswtt4xzzz3VhEIO48blr//wWqQjUpNHkpbsdK3Axx8CboH2uhEj\nIkyYUMOSJT5O+uIaSs+5CP/ib+g2/FByFn+d7XgiIllRXu5+bcmaPMEX5gBQc/iwdERqsdCRI1g7\nex6xnpvT5dor3QWZq6sB6NEjzgMPrCMYdNfnWbzYux9IiIikU2IkT0FB65s8hdddTc4P31M14U9E\n9uqfmmCOQ82xJ7D6nQ9ZN2YsOV9Zuh01lMKJV6yv5S118MFRzj+/hu++05Rd6djU5JGkJZo8zU3X\n8n/yEQDhfnulPVMq/OlPIYYNC7PwHT/nld5AxSVXusP8hw/F/9m/sh1PRCTjEiN5ktlNEcCpKCf4\n5utEfrNL64bop0mkbz/WvvTGLwsy11lkv2/fGLfeWk1pqcPo0fmsXZvlsCIiWZAYydPi3RRr5Xz5\nX/IefZiI2ZGq8RenMJkr3q07FbfeztrZ84n22ZaCv93tjuqp/VC5pS69NMT++0d48cUAf/mLpuxK\nx6QmjyQt2TV5Ah99SDwnh8hufTOQqu18PvjrX6vZZZcoj8wIcoNzJeU3T8ZZ9TNdRwwj8O7CbEcU\nEcmoX9bkSe6T3cCrL+OEQtQcMTydsVol1nNz1j77ItXHnkDgow/oduhg/J9+DMCJJ0Y466wQixbl\nMHZsfluWfBARaZdaMz23rsJJV+PEYlRefZ07HzZNIvsMYM2rC1k39kz811fFfwAAIABJREFUi76i\n27AhFPz5Ond7sBbw+2HatGp6947xl7/kMmdO+jKLZIuaPJK0pNbkCYfxf/YvIr/ZBfLzMxMsBQoL\nYebMdfTqFeOmm3KZFjib8nun46yrousJIwnOf7H5BxER6SAqKtyvyTZ5cl94HsDdAteL8vIov2cq\nFVdPwrd8Gd2OOozcWU8BMHFiDYcfHuatt/xcfLG21xWRziUxXas1I3n8H75P7kvzCe0/iNAhQ1Mb\nrCGFhVTc+BfWPvM8sS234v/Zu+swp87sgePfG5tkXBhscLu4DRQt1hYodaOlS92NrWxlu79tu9ut\nb9ttl7pQV1paWtxdihZ9gcV9YHwyErm/P24GBhijMJNM5nyeJ0/kJuHkJXNyc/K+50b9598kDB2E\ndd3vp/U0SUkGn32WT2SkwQMPONmwQb4Si/Ai72hRacXLtcrb6bdt2oBWWFgj+vGcrF49g2+/dZOY\n6Ocvf4lgYuS1ZH3xLVgsxN58PRHffR3sEIUQoloUF/UrtVzL78cxbza+Bg3xdexUtYGdCU0j//4/\nk/3ldxh2B7F33Urk8//Eqvl5++0Cunb18fXXcsQtIUTtciYzeVzvvgWA+5HHq/VgK57+A8iYt4T8\nG27BtmkDCcMH43rjVfB6K/0c7dv7eeutAtxujdGjXRw4IL3ZRPiQIo+otMr05LGtNNfHelJrRj+e\nk7VqZfDll/k4nXDHHS5m24eT+f3PGDExxN5/F5Gvv4L8zCuECHfHezRUnO+sG9abR1QcMCikj6hY\nrOj8YWROmYWvWXOi/vNvYm++nmgjh88/z6dRI3M25yef2IMdphBCVIvTyfclWfbsJuLXn/F26ISn\n37lVEVq5jOgYcl99g6yvx+NPTCL6uX8Qf8mw0zpwykUXefnb3wrZt8/CqFFyxC0RPqTIIyqt+Ggr\n5RZ51pvTJb2du1ZHSFUiNdXPxx/n4/fDDTe4mO/pazZ7a9SYqBeeJfrB+8DjCXaYQghRZU5nuZZj\nwTwAigYMqsKIzi5fG52MaXMoOncQEVMnEz98CA2zNvP9927q1PHz+OMR/Pij9GkQQoS/4uVaUVGn\n9zjXh++h+f24774vqAX+ovOGkjF/KQVXXo195W8kDO6H86P3qeyhs8aMKeKWW4rYuNHKLbdIbzYR\nHqTIIyqtMtP3bRs3YNhs+Fq3qaaoqsaQIT4+/jgfjweuv97FosyOZEyZjadrN1xff0HcdVehZcmh\nWIQQ4ak431emR4Nj/hwAcyZPDWIkJJL17Y+477oX2xZF/LDBtF//A99+m090NNx/v5MZM6zBDlMI\nIapU8Uye01qu5fHg/O4r/HXqUHj5VVUUWeUZCYnkvPsx2R98guF0EvPXvxA38gos+/ZW+FhNg+ef\nP96bbcwYJz5fNQQtRBWSIo+otOxsjchIo+zG+X4/1s2b8LVqDY6a39Ng6FAfH35YQFERjBrlYvnu\nBmROmEzh8BE4Fswl/uKhWPbsDnaYQghx1h0v6lew019YiH3pYrxt2+GvV78aIjvLbDbynn2R7A8+\nQTMMYu+4md7fPcaXn+Zgs8Gtt7qYPVsKPUKI8HW6jfYBHLNnYjl6lIIrr4GIiCqK7PQVXnYlGfOX\nUXj+UBzz55AwsI/ZU7OCVgtWK7z7bgE9e/r48Uc7jz4aId0ZRI0mRR5RadnZWrlLtSx7dmPJy8Xb\nrn01RlW1LrzQy3vvFVBQANdeG8miNbFkj/sS9533YFObSRg2CPvSxcEOUwghzqqcHA2bzcDpLP9+\n9lUr0Nxuis4dWD2BVZHCy64kY/pcvK3bEPne2wx/cRif/2cfmgY33uhi5kwp9AghwtPxmTyVf0zE\n998AUHjNdVUR0hnx16tP9pffk/Pqm+DzEXv/XcTeegPakSPlPs7lgq++ctO5s48vvnDwt79JoUfU\nXFLkEZWWk1NBP55NGwHwtetQXSFVi0su8fL++wUUFsJ117mYMj2CvH+9RM6Lr6JlZhJ35cU4x30o\nDZmFEGEjN9fM9xW1WbD9thwAT+9+1RBV1fK10cmcNoeCS6/AvnwpV/49lW8eXYzVCjfd5GLqVCn0\nCCHCz+keXUvLyiRi2mS8bfTQ7cGpaRTccDMZcxdT1LsvEZMmkjigF44pk8p9WFwcfPedm3btfHz4\noYNnn3XI7r2okaTIIyrFMMyZPOX249lsFnm8YVbkAbPQ8+WX+VitcOutTr75xkbBrXeQNX4iRnw8\nMY8/TPRf/gyFhcEOVQghzlhOjlapfjz21SsB8HZPreKIqocRHUPOB5+Q++wLaJkZXPZsf34c9hb2\nwNKtX3+VZsxCiPBS3Hg5MrJy93dMmYRWWEjh1deG/BEV/U2bkTVhErnPPIeWk03cTaOIGXMPWnZW\nmY9JTITvv8+nZUs/Y8dG8NRTMqNH1DxS5BGVkp8PXm/5y7WsmzYAhNVyrZIGDfLxww9uYmJgzBgX\nb79tp6hPfzKmz8PTqQuuzz8h/sqL4cCBYIcqhBBnJCdHq7gfD2Bbswp/cl38DVOqIapqomnk33Uf\nmZNm4G3eguE/PcCvje8gwuHn9tudfP65HF5dCBE+8vI0oqIMLJX8VhgRmA1TeMllVRjVWWS1kn/v\nA2TMmI+nc1ec33xJwqC+2BfOL/MhdesaTJjgRtd9vPeeg0ceiZBmzKJGkSKPqJTsbLNSHxdX/nIt\nf1Q0/kaNqyusapea6mfiRDf16/t55hknjz0WQWG9xmT+Ms08dONvy6BrV+zz5gQ7VCGE+EMMw1ye\nW1GRRzt8GOu+vXi6dQ/5X3P/CG/X7mTOWkDBNdcxeMtHzDTOJyGygEcecfLSSzKFXwgRHnJztcof\nWSs/H8e82Xhbt8HXsnXVBnaW+dq2I3PKLPIeeRzLgf3EX3kx0Y8+VOasnvr1DX76Kf9Yj54bbgCP\np5qDFuIPkiKPqJSsLHMHvsyZPEVFWLdtxde2HZX+KaCGatvWz5Qpbjp08PHppw5GjXKRWRRJzjsf\nkfuvFyEjg7iRlxP50nNI2V8IUdPk5YFhlL88F8C+JrBUq2v3aogqOIzoGHLeep/st97nHMsKluR2\npnnUIV59NYKHH47A6w12hEIIcWby8irfdNkxf67ZbH/YiKoNqqrY7bgf/xuZk2fi1dvi+vQjEvr1\nxPHrxFLvnpRk8OOPbs45x8vXX5vLdt3uao5ZiD+gSheX67quAW8DXYAC4Hal1PYS2y8B/g54gHFK\nqQ/Leoyu612BNwEvUAjcqJRKq8r4xXHZ2eZ5WTN5rFu3oHm9eNuHXz+e0qSkGPzyi5t773Uydaqd\nESMi+eKLfFrceS/RQ4fgv/oaol59CfvSxeS8+1HNPLSwEKdB8n34KG7CWdFMHtuqQJGnW/gWeYoV\nXnMdntSeNLvnNpas7swI2wy+/LIzR4/C2LEQGxvsCIWoPpLvw0turkbduv5K3dcxbTIAhcMvqsqQ\nqpy3WyoZsxYSOfY/RL72MnG3jqbwwovJfeGVU5Yfx8bCt9/mc+edMUybZuOKKyL57LN86tWT6Zwi\ndFX1lIvLgQilVF/gr8BrxRt0XbcFrp8PDALu1HU9uZzH/Ae4Tyk1BJgAPFHFsYsSipdrlbUjawvz\nfjyliY6GceMKuPfeIrZtszJsWBTTp1uhZ08yZi2gcMQlOBYtIGFwPxzTpwQ7XCGqmuT7MJGTY+b7\n6Ojyd2Dta1YB4OkaHk2XK+Jv0ZLMSTOJfvJu5jCI4Uxh6lQYPtTJtm3ht1xNiHJIvg8Tfj+43ZU8\nspZh4Jg+FX+dZLypPao+uKrmcOB++DEy5i6hqE8/Iqb8SkL/c3B+9L45MCVERcGvv8J113lYvdrK\niBGRbN4c3isXRM1W1e/O/sBUAKXUMqBkRmgHbFVKZSulPMACYGApjynee7xWKbUucNkG5Fdx7KKE\nipZr2TZvAsLv8OkVsVrhmWcKefPNfAoLYfToSJ58EjxR8WSP+4Lcf72Ilp1F3OhriX7kz+ZxiYUI\nT5Lvw0ROjnle7nItw8C2ZhW+Js0wkpKqJa6QYLPhfvAveGdMYkKHJ3mUl9m23c7w8yOYNUsOsS5q\nDcn3YcLtNpfnVuZoitb/bcN6+BBFAwaaO8BhwteqNVkTJpHz+liwWon561+IH3EetsDRI4s5HPDG\nGwU88UQhe/ZYuOiiSObNC59xEOGlqos8sUDJblZeXdctZWzLBeKAmJNu9+m6blFKHQLQdb0vcB/w\nepVFLU5RXOQpc7lWLZzJU9J113mZNMlNs2Z+XngBRo50cTjNQv6d95IxfR7e9h1xfT6OxCH9sC1f\nFuxwhagKku/DRPFMnvKWa1l278KSnm42Xa6FfB06kjN9Fi8/7eYzy00Uun1cP8rJG897Tv4BWIhw\nJPk+TOTlmfm+MjN57EsWAeDp3a9KYwoKi4WCP91I+sLfzAOprFpJ/PAhRD90P9qRI8fupmnw8MNF\nvPOO+ePuddeZR9uVRvwi1FRpTx4gGzOpF7MopfwltpVc/BMDZJT3GF3Xr8Wc4jlCKXW0on88ObmC\nrpFBVpPiK95pbdLERXJyKXdWm6BBA+rozao9tlAxZAisXg233AI//WTjvPOi+fhjGDGiN6xaAU8/\njfXll0m4dBg8/jg89RQ4ndUeZyiOXUmhHF8oxxYCgprvIbT/f0I5NjgxvuLe+Q0aRJCcHFH6A2Zv\nBMDZvw/OKn5tIT12zzzDDZeuot31t3GFepHn/tOYFTP28tnMhtStHxpT+UN5/EI5Ngj9+IJI8n0F\nQjm+krFlZprnderYSU62l//AVeaPlDEXDyOmCl9fUMcuOQZ++B7mzkV74AFcX36Ga9JE+Oc/4Z57\njsV2993QqRNcfTU884yT9eudfPxxBTNgqyP8GvK+C0WhHt/pquoizyLgYmC8ruu9gXUltm0CWum6\nHg+4gXOBVwLbTnmMruujgTuBQUqpzMr842lpOWflRVSF5OSYGhXf/v0OIALDyCMt7cSfKbXsLOrs\n3k3RwMFkVcNrCvWx+/HHGJ59toDnnovgoos0brmliKefLiLykb9h7zeYmPvvwvrCC3i/+57c1/6L\np0/1/SIS6mMXyvGFcmwQEh9OQc33ELo5vya8d0rGt2+fDXChafmkpZV++KioeYuIBDLbdMRTha+t\nRoxd49Y0nTOW+f/9nHtf1pm6YRhdmhzhnZfT6PenRsGPL0THL5Rjg9COT/J96OZ7CP33TsnY9uyx\nAFFYrUWkpRWW/UDDIHHOXLSkJI4mpUAVvb6QGbsOqTB9Ps5PPiTqxeewjBkDH3xA5t+fxTNoCABt\n2sCMGRp33OFk/Hgba9f6GDeugDZtgjOdM2TGrhShHBvUjPhOV1X/zDQBKNR1fRHwKvCQruujdF2/\nXSnlBR4GpmN+WHyklDpQymMeDEwBfQOIBibouj5b1/Wnqzh2UcLxnjynbrNuMvvxeGtZP56yaBrc\nc4+HqVPdtG3rY9w4B+efH8maNRY8vfuSPncJ7jvvwbr9f8RfdiHRj/wZLavS+zVChCrJ92HieOPl\nsu9jW7MKw2LB06lLNUUV4mw2oh+6hc9+a8oLbcdxxBPHlQ/p/PvCJXiOZgc7OiHONsn3YaL4aIoV\nLdey7N6Fdf8+c6mWVksazdtsFNx+N+lLVpH/pxth/XriR15O3MjLsa4365r16hn88EM+d91VxNat\nVoYOjeSrr2yyfEsEXZXO5FFKGcA9J928pcT2ScCkSjwGoBZ1dgw9xUfXKq0nz7Eja9WSw6dXVseO\nfqZPd/PccxG8956D4cMjuftuD489BvzrJQqvuJqYhx/A9fk4HNOnkPvcSxRdcnnt+fAUYUXyffio\nsCePz4d97Rp8bfTyK0G1UaMUbpt/NT3enscdz+q8vHIo0zqu550H59HqLyPCqlmpqL0k34ePvDzz\nPCqq/Psd68fTNwz78VTASE4m9/WxuP7yEEUPPoxj7mwS5s2hcOQo8p74P+wpjXj22UJ69PDxyCNO\nHnzQxcyZHl59tYCEhGBHL2qr0FgwLkLe8UOol13k8dXSpsvlcTrh2WcL+eEHN02aGLz9toMBA6KY\nO9eKN7UnGTPmk/fE/2HJSCfu9puIu/pSrIEjlQkhRDBUVOSxblFo7jy8XWtn0+XK6HJvL2atdXJz\nlxWs9XVk4KtX827nz9Dmzg92aEIIcUxlZ/LYly4GoCgcmy5XVteuZH3/M5nfTsDXrgPOb78isU93\nov7xd7SjR7nsMi9z5uTRu7eXX3+1M2hQFPPnS2FfBIcUeUSlZGVp2O0GLtep26ybN2FYLHjbtK3+\nwGqIc8/1MXduHg88UMi+fRojR0Zy331OjmRH4H74MTLmL6Xw/KE4FswjYXBfov7vcVnCJYQIiooO\noW5bswoAT7fU0u8gAIip6+TlGTrfvLWXOq5cnkobw9CRDVCXPiXFfCFESCg+ulZ0dPlFHsfihfjj\n4vHJrH08g88jY9YCsv/7Lv6kOkS+9QZJqR2Jeu4fNIk6woQJ+Tz5ZCFpaRpXXx3JI49EkC2rdkU1\nkyKPqJTsbHMWzykriQwD26YN+Jq3oNQKkDgmMhL+/vcipk9306WLj++/t9O7dxTvvmsnv1Ersr8a\nT9aX3+Fr0pTI998hsU93nB9/AB5PsEMXQtQixb/sljWTx756JQDeWnr49NM15Jo45q21M+qCg6ym\nOwOWvsqTA1bhvf1BLDu2Bzs8IUQtVpnlWpYD+7Hu3IGnV29ZclrMaqXw2utJX7KKnOdfxh8TQ+Qb\nr5LYozMxrzzLQzcfYvJkN+3a+fj8cwf9+0cxdaqMnag+UuQRlZKVpZXadNly8ACWzEx80nS50jp1\n8jNlipvnny9A0+Cpp5wMGhTJrFlWii4YTsb8ZeT+3z/Q3PnEPPEICf174pg4AeniJoSoDscbL5ee\nc2yrV2E4HHjbd6zOsGq0+Hh448sofpqQR5uGObzH3XSd+DyT+rxO1MN/xrJ/X7BDFELUQpVZrnWs\nH09tXqpVFqfTbM68fC25z74ALhdRr71CYmon+v3yd2Z9uZ3HHy8kPV3jxhsjue02J3v3Su9NUfWk\nyCMqJSdHK7XpsrW46bL04zktNhvcfruHpUvzuOWWIrZvtzBqVCSjRrnYsM1F/piHOLp8Lfm33oF1\nz27ibr+J+OGDsS+Ufg5CiKqVkwOaZpT+y25hIbaN6/F26AgOR7XHVtP17edn1nIL//e3AnIcSdzk\n/4Tzv7idzT3vJurJR7Hs3RPsEIUQtUjxTJ7ylmvZl5j9eGpj0+VKc7nIv+s+jv72O7nPPAcREUT+\n93Xq9+7I0/vvZs6nm+nRw8cvv9jp1y+KV191kJ8f7KBFOJMij6hQYSHk52ulN13euBEAb1sp8vwR\nSUkGL71UyOzZbs4918usWTaGDInkrrucbMupR+6Lr5K+8DcKLr8S++pVxF95MXGXj8A+f67M7BFC\nVImcHI2YmNIP9GfbsA7N48Er/Xj+MIcDxvzZw4LFBVw0oogl9KW/Zy43fng+R3teRcwDd2PdooId\nphCiFjg+k6fs+9iXLsKIjMLbqUs1RVWDRUaSf+8DHF25npyXX8ffMAXX55/Q5/oOzK93NW89vJHo\naIOXXorg3HOjmDRJDrcuqoYUeUSFKnP4dF97KfKcifbt/Ywfn8/XX7vp1MnPhAl2+veP4sEHI9hl\nb0XO+5+QMX2u2Zx58ULir76U+IuHYp89Q4o9QoizyizylL1UC8AjR9Y6Y02aGIz7pJBffnGT2t3L\nD1xNB9/vPPZtLwr7X0LszX/CtmpFsMMUQoSxihova0eOYFOb8fQ8B+z26gytZnO5KLj5NtKXrCL7\ng0/wduqCa9JP3PtaBzY1GMSY89Zw4IDGLbe4uPxyF8uXy1dycXbJO0pUqLgjfGkzeaybN2G4XPia\ntajmqMKPpsF55/mYMcPNRx/l07Kln6++ctCrVxRjxjjZFNWD7K/Gm8We4Rdh/20Z8dddRfzwwTgm\n/wo+X7BfghAiDOTmVqbpsszkOVt69fIxeUo+H32UT6NmFv7LGFpoO3hi8mAKhl9P/CXDiPj5R2nC\nL4Q463JzzfOyZvIUHzrd07d/NUUUZqxWCi+7kswZ88gcP5HC4SNIXLeQN2Z1Y21UHy5svpElS2xc\nfHEUo0e72LBBvpqLs0PeSaJCxTN5Tmm87PVi27LZPHS6dNs/azQNLrnEy7x5bsaOzad5cz/ffGOn\nf/9IbrnFyQp6kP3Z16TPXkThJZdjX72KuJuvN4/G9eG7xz+xhRDiNBmGOZMnOrr07bY1q/BHReNr\n1bp6AwtzxXl/4UI3r7xSQJ0UB//hIVpYdvKXZdeSe8dfSezRicj//BvtyJFghyuECBMVzeSxLw00\nXe4j/XjOiKbhGTCI7M++IX35Wtz3P4iubWHyjg4ssAygf+J6pk83WzbcfbcTpeQrujgz8g4SFcrK\nKn25lnXHdrTCQnzSdLlKWK0wcqSXBQvcfPxxPl26+Jk0yc7QoVFccYWLn3d2I/29z0hfsJz8G27G\ncmA/MU8+RlLXdkQ983/SwFMIcdoKC8HjKX25lpabg3XrFrxdu0lhv4o4HHDTTWZT/n//u4DkFDtv\n8meaW3ZxW9pL7Hj+B5K6tSPm/rvMX9hlua4Q4gzk5mrYbEaZffTtixdhRETgkdmbZ42/aTPynvon\nR9dsJvuNt+nVIZv56Z2YyjC6Wdfx4492zj03iptucrJypXxVF3+MvHNEhcrqyXP8yFpy+PSqZLHA\nxRd7mTbNzfjxbgYM8LJokY1bb3XRs2cUr03tzK4n/8vR1ZvIe/xvZkf/t98ksUcnYm+8DseMqbKU\nSwhRKcWHTy+tyGNbuwbNMPBKP54q53DAjTd6WLIkj9deK6BxcyufekfTifUMt0xnwXdpxF06nIS+\nqbj++x+0Q4eCHbIQogbKzjb370trtK9lZWLbsA5Pak+IiKj+4MKdy0XhqNFkzpxP5rQ5DLi5Mctc\nA/mJy+jFUqZMsXPhhVFceamdOXOsUtMXp0WKPKJCxTN5Tt7pt22Uw6dXJ02DAQN8jB+fz4IF5qHX\nMzI0nnsugq5do7j/H42Y3e9JjqzcQPab7+Dt2JmIqZOJ+9NIc5r/Ky/AHpndI4QoW06OeV5qkWeV\n2Y/H002KPNXF4YDRoz0sWpTH55+76dvXy/T8AQxlBu1j9jB212V4nn2NpK5tib1xFI5fJ0JBQbDD\nFkLUEJmZGnFxpW+zL1uCZhh4evet3qBqG03D2y2V3JdfJ2O9YvC7lzHv3CeZxRAuYDoLlzq59tpI\nzu3i46N3DOnKICpFijyiQsWNl0+eyWPbZB4+XZZrVT9d9/PSS4X8/nsuzz1XQEqKwbff2rn00kh6\nD0zkxQO3sPGzBWTMmEf+jbeiZWYS9coL0KwZsaOuIuKH7yAvL9gvQwgRYopnbpbWk8e+xjyylszk\nqX4WCwwb5uOnn/KZPj2PK6/08L+CFB7y/puGtsPcGPMjK6emE3vraJI6tCJmzD3Y584GrzfYoQsh\nQpRhmD/kxseX0Y9niTRdrnYuF4VXXkP2Dz/TZeV/mfDEApY2vYo/8QU7Dkby16dj6drGwt//tJ+t\n66UZvyibFHlEhY4v1zrxdtumDfgTE/HXrReEqASYzbDvuMPD4sV5jB/v5qqrPBw4oPHCCxF06xbF\nlc/15ZPeY9m1ZCs5r4+FHj2ImDWD2Htup06HVsTcdyf2ObPki4AQAoD0dDPfJyaWMpNnzSr8derg\nb9ykusMSJXTt6ufddwtYuzaPp54qoEFjK19kXko/FtMxcR+vaI9y5Ju5xI+8HFJSiHryUWxLl8iy\nXSHECfLzoahIO+VH3GL2pYswbDZzuZaodv7GTXA//BgtfvuEN+e1ZvOdL/BM/OtEezN5b4ZOvyGJ\nXKrv4+s/ryZ3T0awwxUhRoo8okKZmcVH1yrxIZCXh2XXTrMfT2kLeUW1sljMpVzvvFPA+vW5vPpq\nAampfubOtXHvvS7an1OPUTPv5NuHl7Fn1mryHn4Mf51knN9/Q/y1V5DYtR3Rjz2Efd4cOUyvELVY\nRoaZzxMSTtzp19LSsO7Zjadrd8n5IaJOHYP77zf79owf7+ayyzxszWnAE9n/RxNtD4Pqb+Rj93V4\nPvyahEuHkdSpNdEP3Y9j2hTz250QolYrbsdQ6kye3Fxsa1bj7dKt7OOri2rja9eemH89zL3qNlZP\n2c5nQ8dxgXM+yzLa8OevB9AhtQ431J/O8sd/xfjfjmCHK0KALdgBiNB39Kj5IZCUdPxDwLZ+ndmA\ns2PnYIUlyhAbCzfc4OGGGzxs26YxYYKdn3+2MWmSnUmTwOXqwgUXdGD4408zLHE5DaZ9QcQvP+H6\n5CNcn3yEPz6eomEjKBxxCUWDhoDLFeyXJISoJsUzeUrmewD7GrMfjyzVCj3FRf4BA3xkZMDEiXbG\nj7cxb1k75vEG99pfY1j9NVyV+RGXfvkV8V9+hhEZSdHg8ykcdiFFg8/HqCczcoWobYp/xC1tJo99\nxXI0n0+WaoUaTUNL7crwL7oy3DA4uGAd4/97hK+WtuaLQ0P5YhzUH3eAK2MncEX/g6SObIrv3P4Y\nMbHBjlxUMynyiAoVF3lKTt+3rVsDgLdzl6DEJCqnVSuDRx8t4tFHi9i0ycLMmVF89ZXBxIl2Jk60\nY7UO5Jxz+jP03je5qN5vdFjzNRGTfsH57Vc4v/0KIzKKogGDKDrvAoqGnC/LNIQIc8VFnpNn8thW\nB/rxSNPlkJaQYB6C/aabPOzerTFtWjSffgoTt6QykVRs1rEMbLiFK/K/4qpJ71N/0kQAvO07UjT4\nPIoGDcHTqw84nUF+JUKIqlbeTB77koUAePpI0+WQpWnUH9CC+we04D4Dtiw5ykcvHuCXlY15O/tG\n3p4MDSbv5yrtRy5rt4meF9fBP3igOTvLJiWAcCf/w6JCR45oJCQY2O3Hb7OvDRR5unQLUlTidLVr\n52fAALj//jw2bbIwfbqNadNsLF1qZcmSSP7BQFq0OJfzLnqDwY2v4J4VAAAgAElEQVQUgw98Q52Z\n3xMxdRIRUycB4G2jUzTELPh4eveVLwJChJmylmvZV60AwNM1tdpjEn9MkyYGTz4Jd9zhZssWC5Mn\n25g0ycastW2ZxT+5n3/SrcEBhtlnMWLrx/TZOJbIt97AcLnw9OlnFnz6nYu3fUewWoP9coQQZ1lm\npnle6kyeJYsxLBY85/Su5qjEH6Fp0P+yJPS+Dp7zwMJ52fwyLpvJCxIYW3A/YzdC/MYMhr88lQsj\nHuX81KPEDeyEp08/cxm27M+HHSnyiAodOaJRp47/hNtsv6/FiIzE17JVkKISf5SmQfv2ftq3L+LB\nB4tIS9OYOdPK9Ok25syx8cGHEXxAZ6zWTnTr9iwDb03jPOs8+m3/gpjFs4h8dyyR747FcDrx9DgH\nT9/+5ql7D/mQEKKGKy7ynNB42efDtuI3vC1aYiQnBykycSbatPHTpo2Z8/fs0ZgyxcbUqTaWLavP\nas9oXmQ0sZFFDKm3geHuHxk6+wuazZ6JBvhjYvH06o2ndz88ffqaP+44HMF+SUKIM1S8XCs+/qQN\nBQXYV63A27EzRmwZx1cXIctuh8Hnaww+P46XPH4WLHAz7WcfM6bZ+SZ9FN8UjsKy2EfvxUu5iEmc\nZ3+WTqlWjL698Kb2xNOtB0adOsF+GeIMSZFHlMvnM6fvt2lTosiTn491y2a83XvIr3thIDnZYNQo\nL6NGeSkqgpUrrcybZ2X+fBurV1tYsaI+r3ItTudIunXx0LvBTvoXzKL/ji+pu3A+joXzATAiIvCk\n9jQLPn364e3WHSM6JsivTghxOkpbrmXdvAlLdhZFIy4OVljiLGrc2ODOOz3ceaeH3FxYtMjK7Nk2\nZs2y8dOObvxEN+BZGiXkcG7c7wzMncR5M7+j5czpaGDO9EntGfgykIq3eyr++g2C/bKEEKepeLnW\nyTN57Ct/QysqkqVaYcBuhyFDfAwZAi8aBps25TFzpo3pkwyWrunDYqMff/NA7NIsBiydzxBmM4R/\n0b5xDr4e3fF2S8XTvSfeTp2lR2cNI0UeUa70dA3D0E5surxxvdmMrUvXIEYmqoLDAX36+OjTx8cT\nTxSRkwOLF5sFn8WLrSxdbmeJ0YbXaQPcg96qiN4pe+ijLeacvT/RcfFEohab67gNiwWf3tb8MtC9\nB57uPfDpbaUwKEQIS0/XiIw0TpiUZ1++FECm7Yeh6GgYNszHsGE+DKOQHTs0Zs+2sWiRlaVLo/h6\nZz++ph/wPA3i3fRL2ECvvNn0Xfgz3Ra+RRwFAPgaNAx8GUjF2y0Vb5euMgNAiBBXPHPz5J489nlz\nAPAMGFTdIYkqVHIm/5gxkJ7uYf58GwsXWlk4P5Jfd17Cr1wCQNLeo/Tds4g+E5bQh3/Rw7qaiPbN\n8XbshK9DR7wdOuHt0BEjPiHIr0qURYo8olxHjpgfAHXqlCjyFPfj6SxFnnAXE3P8CwBATg6sWGFl\n+XLztHKlHbWtJZ/SErgBl9NPp0bpdHdtJNW9gHN2/Ez7TV/g+uJTAPxR0Xi7dsPbsTPejp3wduyM\nr3UbmfovRIjIyNBOXKqFFHlqC02DFi0MWrTwcPvtHvx+UMrC4sVWliyxsnixk/E7ejKensDj2Kx+\nOiUfoKd9Db0zp9F78gzaTJ6EFXPmr69pM7ztO+It/kLQvgP+ps3Mw4EJIYKurKNrOebOwrDbKeoj\nR9YKZ4mJcPnlXi6/3AvA/v2FZsFnoY3FixL4Zc+l/MKlAFh9XjqvX0efdYvpwxJ6MI7WbIWUhoEc\nb+Z5X/uO+Jo1l8bOIUD+B0S5io+sdWKRZzUA3k5yZK3aJiYGBg/2MXiwWfTxemHDBgsrV1r5/XcL\na9daWbk5ieW+AcAA4G+4Iny0r5tGB7uiU84SOi+aTcdFP9KAt8yp/3Y7Xr0dvo6doHdP7E1a4W3T\n1uz9oWnBfLlC1Drp6RotW57Yg83+2zL8CQn4WrUOUlQiGCwWs2F/u3Z+brvNg2HAjh0aq1ZZWb3a\nyqpVVtata8jqohTe5yIAnHYv7RP200VbR7e0+XSdspjOU94mjmzALPT72nfA264DdO+MvX4TfK3b\n4E9pJMUfIarZwYPmPlb9+sf38bX0o9jWrsHTp5851U/UGg0bGowc6WXkSLPoc/CgxooV1sDJwtq1\nXVld2I23uQ+ASEs+nQ+tp9u+3+g2fTXdeJOOrCfC7sfXvAW+1jre1m3MfYde3dGSGkobh2okRR5R\nrtJm8tiXLcEfE4uvbbtghSVChM0GXbr46dLl+JfC/HzYuNEs+BQXftaqeqz01gcGAk8AEO8qoEPM\nLjr419Fh82LarN9I62/epCm7sOHDHxePr3UbvG10fK3a4GvTBm9rHX+TprLkS4gqkJUFbrd2wg6/\n5eABrLt3UTjsQvkSXssdn+nj5eqrzS8BhYVmoX/VKitr11rZsMHCOtWYVZ4mjAsUfgCaxmXQ0fU/\n2hatpd2KJbT9bRNtP/uJJNIBs8+Pt2VrfK1bm/m+dRt8LVria9oMI+7krrBCiLPhwAELDodxQksG\nx4J5aIaBZ9CQIEYmQkH9+gYXX+zl4ovNfF9UBOvXF/+wa2XdOgcrtvRgKT2PPcaq+Wht3UX77eto\nv+V32rORdsxAR1GHAnwNU47ldl+z5vgD576mzTASEoP1UsOSFHlEufbsMXfqGzQwPwAshw5i2/4/\nCs8fKl+0RalcLkhN9ZOaerzwU1QE27dbUMrCpk0WNm+2oJSDJTvasMivA1cfu6/d4qWZ6yCtPVtp\ns3ItbVYoWjOX5oyjMXuwR1iOfSD4mjYzPyCaBq43aQqRkUF41ULUfLt3m/m+cePjf7v2+XMB8PSS\nBpziVBER0L27n+7d/YAHAI8Htm61sGGDhQ0brIHzOCYd7MEkegC3HXt8kiuPNq7dtDU20W7zb7Ra\nv5nmTKY5b5FQPPsnPv5YjvcH8v6x/J/SyOwsKoQ4bQcOmEX9kvV7+9zZABRJkUecxOE4Nd8XFJjL\netets7JunXmuVHM2F7TgRy479lgNP82dB2h3dCP6/t9pufB/tGQJLfiSZuzEjtf8cbe4+NOkKb6U\nFPwNG+FPScHXsBFGUpLM8D8NUuQR5dq50/xjat7c3Om3B5rqenr3C1pMouZxOKBtWz9t2/q57HjO\nJz8ftm2zsHWrhe3bLezfH8GmTRrbt6ewNaMRkxl8wvNo+GngO0LTbTtoqrbTlF00ZSdNmUdTdtGE\n3UTWiza/CDRpij+lEb4GDfE3TMHfsCG+Binmh4TMSBDiFHv3mn8XjRodL/I4Zs8AoOi8C4ISk6h5\n7Pbi5p5+rrnGe+z2o0c1tm61sG2bedq928GGDS6W7WrLEn874MoTnifBkUeziP0082yn+fqNtFi7\njeZsphlTSWEfiWSDxYK/Xn38DRvib5BifilocDzf+xs2NI/8JYUgIU7g8cChQxq9evmO3+jz4Zg5\nHX9iorRkEJXidJ46o98wzPeWUha2bDFPO3Y42LixAZOOpDCJE/cnLJqfxhGHaenZQcsNG2j5+1aa\nsJvG/EZj9tCQ/djxYjid5j59SiP8DVOOF4Hq1cdfty7+uvXwJ9c1f30QUuQR5du509zpb9rU/ON1\nzJgGgGfgoGCFJMKIywWdOvnp1Ml8fyUnR5CW5gYgI8Oc/VN82rPHwt69Gnv31uG3/cksoVepzxl1\nOI+Gh/bRYPkBGrKfBhygIb/RgAPmyX6EevUgKiUGI8X8YmB+MCTjT65rnuokm8Ugma0mapG9e82i\nfpMmgan7Xi+OObPwpTSS5bnijCUlGSQl+ejd2/xSmZzsIC0tj8JCc19j61YLu3Zp7N5tYfduC3v2\nONm0uxWrC1oDw055vihbAQ1th0lJ30ujgztIMcwvAymsJIWJpLCPuhzGoXnMHF+3HkbJPJ9c98S8\nX7ceRmKi/AggaoXDh82j5zZseGI7Buuhg+SPvkn2f8QfpmnmUq/69X0MHHhivj96VGPHDo2dOy3s\n3Glh1y4LO3dq7NxZl9mH6jObPqc+H37qR2TQyLKfRvt20WTHtkDxZy/1WUE9DlGPQySSjoY5+7O4\n4HO8+FMvcLkuRmIS/oREjMREs0dQmM4OkiKPKNfOnRYaNPDjcmHu8M+chq9hihxZS1S5hIRTl30V\n8/nMhnDHCz/m+b59Fg4dcnLoUCu2HWmNYZSSuD3AXnDsLaQOR6jDEZJJI5k06rCLZFaYt2tHSYop\nIinJT0JdGwXNYoiKj8ZITDQ/HBIS8McnnHAezh8WIvwVL9cqnsnjmDsLS0YG+VdeI+9rUWUiIkDX\n/ej6qbneMMwvo7t3a4HCj4U9ezQOHrRw4ICdgwcbsfVIE6Ds5YSxllzqHj1CctpB6voPkkwadTlM\nMoeoy7rA5TQSSSfeko0ryQV1kqBuMrFRsfgTEzHiE459KfDHJ5xyLr8ci5pm/34zpxe3YwCI+OF7\nAAovvSIoMYnwZxb7DXr0ODXfu92wa5dZ7N+3z8L+/Rr795vn+/YlsOZAIr95OpX53HbNS117BnXz\nD1N/xz7qb9lLPQ5Rl8MksY0klpFIOkkcJZF0EsjAYrfiT0iE5DrExcabBaDERIwEc1+/OP8bcXH4\nY2IxYotPcSFfCJUijyhTYaH5y26fPmYV1jF3FpbMTNnhF0FntUJKikFKiq/M+3g8kJamceiQ+YXA\nPNc4fNi8nn7UytHDyWxPr8fv+aWkQgPIDpx2AMsgggLiyTzptI94NhBPJnFaNnGRRcRF+4iL9RMd\nbyEqzk5UvI3IBAeRCXac8U6IjcGIicWIiTl28keZ57hc8vclgqJ4Jk+jRuZOf8R3XwNQcM11QYtJ\n1G6aBvXqGdSrZ9Cz56lfCsDcVzl0SOPAAQsHD2ocOGBePnRIIy1N4+hRF0eONGHH0ab4qCC3+sGW\n5iHhSCbxmzJIoLTTDhLIIJ5MYsghhhyinT6iYgyiYzSi4y3YYiIxYuPwx5TI9bGxGDGx+GNjMaKP\nXzeiojBcLozIKLNYJPlfVIN9+4p7bpp/V1pWJs4fvsXXqDGe/gOCGZqopSIji4/oCHDq/r3fbx4Q\nyCz6mDn+8GEzz5snC2lpSWxOq8Pqwg6V+jfj/dkkpWeQePQISb7Dx4o/cWQRSzax7C1x+fgpjiyi\nI/3Y4iKPFX38xwpA8RixZq4nMhIjKtrM8ydcjjLPA5erYklxlRZ5dF3XgLeBLkABcLtSanuJ7ZcA\nf8f8bX2cUurDsh6j63pL4BPAD6xXSt1XlbEL2LLFgmFox/rxuD58D4CCP90YzLCEqBS73TwcpDkV\nufQvB8UKCiAjQ+PoUfOUnn788tGjGulpfgpyDI4c8pCdHUV6bhzb3a3x+E6q4htAXuB0qPR/y4KP\naHJPOmUTzX7zspZLtL0IV4QPp8PAGeHD6fDjcho4XRpOl0GEy4Iz0oIz2oIzyoYz2kry63eehVH7\n4yTf12yGAevWWYmNNUhONrBs/x8Rv/yMt207vN1Sgx2eEGWKiDCXGDZpUnbRH8wvCFlZcOSIhaNH\niwtAGkeOmOcZGRpZWRqZmRayshLJyq7DzgzweCpRdCkInNICMVFwrABU8hRNLjHkEMleInHjIh8X\n+ccvawU4I/y4Ivy4XAZOJ7giwRlpxRWt4Yy24oqxwVcfnfG4nQnJ9zXf8uXm/kuHDoF9/PfeRnO7\nyX/4cfPQqUKEGIsF6tY1qFvXoGvXsvfrDQNyc80feg8ftnDkiEZmprlvn5lp7u8XnzIzo0hPj2ZP\nRlOKyv8IOZUbnPkFxB7MJtbIIoo8osgjEncp5/tOub3kZZfNg8NlISLSiiPSiiPKSkSUHUeUDbvT\nBpN+Pu3xquq/4suBCKVUX13XewGvBW5D13Vb4HoqkA8s0nX9Z6B/GY95DXhSKbVA1/V3dF2/TCl1\n+q9YVNqkSebbY+BAH44ZU3HMnklR777SjE2EHafTnLJcctryyZKTY0hLK24i6sUwvOTnQ3a2+cUg\nK6vkZY2sTMjL9ODOKCIvy09uth93HuTlQZ7bQl5BJJkFsewrcpDnLTHV3wCKAqfTYLx+uq/6rJN8\nX4Nt2mT2QbniCg+a30fMk4+i+Xy4H3lcZhaIsGCxmMuAExL8tG5d8f2Tk2M4fDgHt5tA8UcrcW7e\nlpenkZsLubla4AR5eRp5OVZys+PIzY3jaJ6F3Hwrfn8l/o4MjheMssq521eVfNFVR/J9DTd/vpXI\nSIMePXzY1q0lcux/8NWrT8Gttwc7NCHOiKZBTAzExBi0aFG5yk2dOjHs3p0TKPxo5OSY+TwnRyM7\nWyMnx8zzJa+b97GTnV2H7Jw6HHSD261VLtefzAvkBE4nvx78FfxUXbqqLvL0B6YCKKWW6breo8S2\ndsBWpVQ2gK7rC4CBQJ+THlP8E2KqUmpB4PIU4AJAPgSqQNrGo3zwwmo+mHMOkbYirpj9ILETPsWw\n28l98dVghydESNA0c2ppZKRB/fplF4fAUcEzFeH3F+F2B74c5JkfJPn5GgUF5lKEArdBfraHwhwv\nBbkeCnN9FOR5KcjzU+A2KHAbQKuz+Or+EMn3NdRX9y3i/V/rAy25JO9b4ke8jn31KooGn0fhJZcH\nOzwhgkbTICoKoqKMExrUni7DMI8mWVwUKijQyM8/fp6ff+L1krcXFEB+np+CXJ95nmcAsWfvRf4x\nku9rqI0Tt/HOvw6zZUtfhjbbTNKTLxPx4/dQWEjuS6+ZvQWFqGVK7tOnpJxZri8qMvO9260dOzdP\nZk4v67yw0HxsQYFGUREUFUKB209RgQE4TzuWqi7yxHLibxFeXdctSil/KdtygTgg5qTbfbquW+GE\nhdQ5gfuWR0tODu1EFarxJQ+Mof3AZjx57Jb3AidIDFJMJwvVsSsWyvGFcmwQ2vGFcmwhIJj5HkI8\n54dybNe/1Y/r3yq+NjpwMsuTyUGKqaRQHjuQ+M5EKMcGoR9fEEm+r0Coxpd8aQz/vbQV/wWgLfAx\nfPYxULmBrw6hOnYQ2rFBaMcXyrFB6Md3uqr6OJHZmEn92L8X+AAo3lbyp4gYIKOMx/g4salGDJB5\n9sMVQgjxB0m+F0KI2kHyvRBChLCqLvIsAkYA6LreG1hXYtsmoJWu6/G6rjuAc4ElwOIyHrNK1/Xi\ndu8XAgsQQggRKiTfCyFE7SD5XgghQphmGH983VlFSnTS7xy46RbMRmxRgU77FwFPY07V/Egp9W5p\nj1FKbdF1vTXwAWDH/AC5QylVdcELIYSoNMn3QghRO0i+F0KI0FalRR4hhBBCCCGEEEIIUT2qermW\nEEIIIYQQQgghhKgGUuQRQgghhBBCCCGECANS5BFCCCGEEEIIIYQIA7ZgB3CmSjRy6wIUALcrpbaX\n2H4J8HfAA4xTSn0YQrE9CNwOHA7cdJdSamt1xVcijl7Ai0qpwSfdHrSxq0RsQR07XddtwMdAM8AB\nPKeU+qXE9mC+7yqKLdhjZ8FssqhjHjr1bqXUxhLbg/q+q0R8Qf+71XW9LrACOF8ptaXE7UH/m61K\noZzvKxlfKLx3QjbfVxBf0MYulPN9JeML5thJvj/zGGtlvofQzvmS76s0vmDvp4Zszg/lfB/490M2\n59eEfB+I46zk/Bpf5AEuByKUUn0DyeK1wG3FfwivYXb8zwcW6br+s1IqLdixBaQCNyilVldTPKfQ\ndf1R4AYg96Tbgz12ZcYWEOyxGw0cUUrdqOt6ArAG+AVCYuzKjC0g2GN3CWAopfrruj4QeJ7Q+Zst\nN76AoI5fYIzeBdyl3B7ssatqoZzvy40vINjvnZDN9+XFFxDMsQvlfF9ufAHBHDvJ92eglud7CO2c\nL/m+CuILCPZ+aijn/FDO9xDaOT+k8z2c3ZwfDsu1+gNTAZRSy4AeJba1A7YqpbKVUh5gITAgRGID\n8z/qr7quL9B1/YlqjKukbcAVpdwe7LGDsmOD4I/dd5jVVDD/jjwltgV77MqLDYI8dkqpn4E7A1eb\nARklNgd77CqKD4L/3vs38A6w/6Tbgz521SCU831F8UHw3zuhnO8hdHN+KOf7iuKDII6d5PszVpvz\nPYR2zpd8f2ZCNd9DaOf8kM33ENo5vwbkeziLOT8cijyxQFaJ697AdKzStuUAcdUVWCn/fsnYAL4G\n7gYGA/11XR9RjbEBoJSaAHhL2RTssSsvNgjy2Cml3EqpPF3XY4Dvgb+V2BzUsasgNgiN951f1/VP\ngDeAL0tsCvr7DsqND4I4frqu3wwcVkrNALSTNofE2FWxUM73pcUQUjk/lPM9hG7OD+V8X4n4IPjv\nO8n3f4DkeyC0c77k+zMQqvkeQjvnh3q+D8QYsjk/VPM9nP2cHw5FnmwgpsR1i1LKX2JbbIltMUBm\ndQVG+bEBvKGUSldKeYFJQLdqjK0iwR67igR97HRdbwzMBj5VSn1bYlPQx66c2CAExg5AKXUz0Ab4\nUNd1V+DmoI9dsTLig+CO3y3ABbquzwG6Ap8F1u5CCI1dFQrlfF8cQ03M+aEwdhUJ6tiFcr6H0M/5\nku//kNqe7yG0c77k+6oT9LEL5Zwf6vkeQjvnh2i+h7Oc88OhJ88i4GJgvK7rvYF1JbZtAlrpuh6P\nubZtAPBKKMSm63ossF7X9baYa+uGAB9VY2wnO7liGOyxK+mE2EJh7HRdrwdMA+5TSs05aXNQx668\n2EJk7EYDjZRSL2I2K/RhNkCDEHjflRdfsMdPKTWwRJxzMJvCFTeIC/rYVYNQzvflxhfs985JQjnf\nQ4jl/FDO9xXFFwJjJ/n+D5J8D4R2zpd8f3aEVL4PxBCyOT+U830ghpDN+aGc7+Hs5/xwKPJMwKx6\nLQpcv0XX9VFAlFLqQ13XHwamYyaRD5VSB0Iotr8CczHfaLOUUlOrMbaTGQAhNHYVxRbssfsrEA/8\nXdf1pwIxfkBojF1FsQV77H4Exum6Pg8zBz0IXKnreiiMXWXiC/b4FQvlv9mqEsr5vjLxyXvnj8cX\nzLEL5XxfmfiCOXaS78+OUP+brSqhnPMl31ddfMEeu1DO+aGc7yG0c35NyfdwFv5uNcMwqj5MIYQQ\nQgghhBBCCFGlwqEnjxBCCCGEEEIIIUStJ0UeIYQQQgghhBBCiDAgRR4hhBBCCCGEEEKIMCBFHiGE\nEEIIIYQQQogwIEUeIYQQQgghhBBCiDAgRR4hhBBCCCGEEEKIMGALdgBCBJOu62OBfoADaAVsCGx6\nA3AChlLq/bP8b3YDRiql/lrG9geBrUqpSWfz3xVCiNpOcr4QQtQOku9FbaYZhhHsGIQIOl3XmwJz\nlFItquHfmgtcrpTKLGO7HZgPDFBKeao6HiGEqG0k5wshRO0g+V7URjKTR4gy6Lr+NGaV/5+6rh8A\nfgHOBQ4AbwNjgBTgZqXUAl3XWwLvAImAGxijlFpz0nMOBvYrpTJ1XbcBHwMdApvfUUp9qJTy6Lq+\nALge+LTqX6kQQgjJ+UIIUTtIvhfhTnryCFE59YCJSql2geuXK6UGAP8AHgzc9inwqFKqB3AX8E0p\nz3MpZgUfoC+QqJRKBS4IXC+2IHBfIYQQ1U9yvhBC1A6S70XYkSKPEJU3NXC+C5hd4nKCrutRQE9g\nnK7rq4GvgEhd1xNOeo7WwN7A5fVAG13XpwKjgcdL3G9X4L5CCCGCQ3K+EELUDpLvRViRIo8QlaSU\n8pa46j1psxXIV0p1V0p1U0p1A/oopTJOup+/+LFKqXSgI/AmoAOrdV2PDdzPE7ivEEKIIJCcL4QQ\ntYPkexFupMgjxHHaH32gUiob2Krr+p8AdF2/AJhXyl3/BzQN3OcS4Aul1GTgz0AO0Dhwv+bAtj8a\njxBCiApJzhdCiNpB8r2oVaTII8Rx5R1qzijjckmjgdt1XV8LPAeMLOU+vwBDApenAG5d1zcAS4Ef\nlFLFh3ccDPxc2cCFEEKcNsn5QghRO0i+F7WKHEJdiGoW6Kp/WWAqZ2nbHcBCoJ8cXlEIIWo2yflC\nCFE7SL4XoUJm8ghR/R7kxAZsJ7sf+JckfyGECAuS84UQonaQfC9CgszkEUIIIYQQQgghhAgDMpNH\nCCGEEEIIIYQQIgxIkUcIIYQQQgghhBAiDEiRRwghhBBCCCGEECIMSJFHCCGEEEIIIYQQIgxIkUcI\nIYQQQgghhBAiDEiRRwghhBBCCCGEECIMSJFHCCGEEEIIIYQQIgxIkUcIIYQQQgghhBAiDEiRRwgh\nhBBCCCGEECIMSJFHCCGEEEIIIYQQIgzYgh2AqF10XR8IjFVKdSpl2z+ArUqpL6o/MtB1/SLgecAB\n/A7cppTKrez9dF2PBT4C2gIa8JlS6uUK/s2mwHqlVEwp2+4C4ip6jqqi63ovYCwQCewHRiulDgUj\nFiFEaJAcfspz1fgcXtH9dF2PB+YBtyilVgVu6wgsAbaWeKprlVIlrwshwojk/1OeK2zzv67r9sDt\n/QEDmAI8ppQyqukliDMkM3lEMJSaIJRSTwfxw6EO8DFwhVKqHbADeOk07/cssCfw4XcOcE8geVak\nrPF4L4gfDnbge+ABpVQH4AfM1y2EEJLDT1Rjc3hF99N1fQSwDNBPemhf4EulVPcSJynwCBH+JP+f\nKFzz//1AUuD2zkA/YGQ1hC/OEpnJI4IhRtf174FWQAZwp1Jqm67r44B1SqnXdF2/FbgTsAOJwEtK\nqXd1Xa8HfAYkBZ5rslLqqZJPruv6OcB7mIlXA5pgVtoHBn5pMJRSz5wU01BguVJqe+D6O8Ba4L7K\n3k8p9Wdd14sLpw0xfyXIqsR4WHVd/wBIBYqAMUqp5bquP42ZYMfoun4x8NfAeNTF/IXhKV3Xo4Bx\ngbH0AyuVUnedNB4XAK8qpToHrsdhfrA1B64DUpVSd54UU08gSym1NHD9I+A/uq4nKKUyKvGahBDh\nS3L4iWpyDq/ofvcDNwJfn/T8fYHmuq4vw/x/ekkpNaESYyWEqNkk/58oXPP/67quvxm4PRmIB9Ir\nMR4iRMhMHhEMjYB/K6W6Ye44nlD5DyS924ALlVKpmEmsuNuQqmMAACAASURBVBp+B/A/pVQPYADQ\nStf1E6ZJKqWWK6W6KaW6B+6fA9we2PZ0KR8OAI2BPSWu78X8IIs+nfsppfy6rn+OOQV0LqAqGAsA\nFzAtEO9TwPe6rp9cgH0IuFEpdQ7QB/irruuJwBVAdOCx5wDout6i5AOVUjOAKF3XuwduGgX8qpTK\nCvzScPKHwymvUynlAdKAlEq8HiFEeJMcfqKanMPLvZ9SaoRSahnml62ScoGvlFK9gJuBd3Rd71bq\n6Aghwonk/xOFc/736br+ArANOAgsqMR4iBAhRR4RDL8HdhqB/2fvvuPkqur/j7/uzPaWAptQTIOE\nQwik0kICxFBEJaCgIupXlK5SpPkDVIoI+lVBURSk8xUFFQiIQUARIQmhJIQUAieUkIC09GTbzE75\n/XF3spOyu7O7M3PPzL6fjweP2d07c+fDZuczZz73nM/hbmBSepK31jYCM4BjjTE/Ar4PVLcdfhw4\n0RgzCzgLuNRau3lHT2KMGQk8hL++tKtp5B29FuLdvZ+19n+AnfGvVFzRwf3TrbfWPtD22Cfbfrb3\nNvc5DtjfGHMFcEPbz6qBOcAYY8zTwKXAr9KuUKS7E38gDvBN4PYuYsr09yEifY9y+NYKOYf3KNdb\na8+x1v6+7evXgb/g/z+KSHFT/t9aUed/a+1l+LN4VgK3dPG84hAVeSQI6UnGw5+S2Zr6gTFmd+AV\n/Cmas4EfpI5Za+fjT1H8PTAMeMkYc/C2T2CMGQQ8BlxirZ2TQUyr8KdnpnwCP3E3Z3o/Y8zRxphd\n2+Jswr/CMZGu7Sjppv8+qvB/HxOABcAlQAzwrLXv4E/zvA6oBZ4yxpywg+e4C/iSMWYcfiO4Z7uI\naav/z7arEjsD/83g/0dEipty+NYKOYd3O9cbY0LGmMvbrtineOn/zyJStJT/t1Zs+X8n4L/GmEOM\nMaPAn9GDX9DTbM0CoiKPBGG8MWZs29dnAXOstS1px/cHPrbWXts2TXEGgDHGa5s2eIW19m/W2u8C\nrwJ7pZ+8beA5C7jDWvvnDGN6EjjIGLNnWlyPZHi/h9u+/hJtVX9jTHnb9//O4Ll3Nn5zS4wxM4Bm\ntt6xZBRQA/zAWjsLmIa/VjhsjDkbuNta+8+2avsTwL7bPoG19n3gRfw31q6uAIDfaHNg2pvvacBz\n1tpNGTxWRIqbcvjWCjmHdzvXW2sT+Femz2z7fx4GnIDftFNEipvy/9aKLf/Pa7vfdOAGY0y4rVfR\nV8ns9yGOUONlCcIy4Mq2JPsRcErbz1Md6p8ATjXGWPx1/y/irxEdCfwKuMcYsxiI4DdM27Yh5LnA\nfkDMGHMSbVcarLUTTQdN26y1q40x3wQeNH63+bfwm01ijJkE3Gb93UM6vB9wIfB7Y8wS/AZqD1tr\nb2w7x9Vtz3PlDn4fH+FPX70WaAROaFsXnIptUdvUVmuMWY+/NnZZ2+/jHmCaMWZZ22NXAjd28Hu/\nDb+L/ozUD4y/xeN2TdustbG2qwm/bbsKsTbt/1NE+jbl8K0VVA5vu1o9C/iMtfbDDHP9tjvIfKXt\nd/VN/AuG51trM+lfISKFTfl/a8Wa//8X+CX+v1Ecf2nZZR3EJg7ykkltdy+Sa8ZfW/wda+0FQcci\nIiLdoxwuItI3Kf9LIdJyLZH8MPhVcRERKTzK4SIifZPyvxQczeQRERERERERESkCRduTJxaLJ9ev\nbwo6jA4NGFCF4usZl2MDt+NzOTZwOz6XYwOor6/1go4hSC7nfNf/dlyOz+XYQPH1hsuxgdvxKd+7\nm+/B7b+dTGN77rkwn/tcFQB77plgzpxGwuFcR1ccv7uguByfy7GB+/H1JOcX7XKtkpI8ZKJeUHw9\n53Js4HZ8LscGbsfncmzi9r+Py7GB2/G5HBsovt5wOTZwP76+zPV/G5fjyzS2v/zFnwfwiU8keOut\nEE89lZ//p2L43QXF5fhcjg3cj68nirbIIyIiIiIiIplLJmH27BL69Uty993NAPzxj6UBRyUi3aEi\nj4iIiIiIiLBypce774aYMiXG2LEJRoxIMHt2CdFo0JGJSKZU5BERERERERGWLvWXrhxwQByA6dNj\nNDR4zJ9ffEtaRIqVijwiIiIiIiLCihX+x8M99vB3YJ42LQbAs8+qyCNSKHK6u5YxxgN+B4wDWoDT\nrbVvpx2fAfwQaAXustbennbsIOCn1tpPtn0/Hvg1EAMiwNettatzGb+IiGRG+V5EpG9Qvi9u77zj\nb+QzYkQCgAMP9Gf0aCaPSOHI9UyezwHl1tpDgMuAG1IHjDElbd8fCUwDzjTG1LcduwS4DShPO9ev\ngO9Ya6cDM4FLcxy7iIhkTvleRKRvUL4vYqmZPMOG+UWeAQNg5Mg4L78cJh4PMjIRyVSuizxTgccB\nrLUvAPunHRsNvGGt3WStbQXmAIe1HXsT+Pw25zrJWruk7esSoDlnUYuISHcp34uI9A3K90VsxYoQ\nu++eoLKy/Wf775+gocHDWnX6ECkEuX6l1gEb076PGWNCHRzbDPQDsNbOxJ+2uYW19iMAY8whwHeA\nX+YoZhER6T7lexGRvkH5vkhFIvD++x7Dhye2+vmECf4UnsWLVeQRKQQ57ckDbAJq074PWWsTacfq\n0o7VAhs6O5kx5iT8aaGfsdau7erJ6+tru7pLoBRfz7kcG7gdn8uxgdvx9SS28847j3333ZczzzwT\ngMbGRk488URuvPFGjDHZDjFIgeZ7KL6/nXxyOT6XYwPF1xsuxwbK+Z1Qvu+Cy/F1FtuqVZBMwvDh\nJVvdb+pU/3bFikrq64OLL2guxwZux+dybFB8+T7XRZ65wLHAA8aYg4ElacdeA0YaY/oDTfhTOX++\nzeO91BfGmK8BZwLTrLWdvlmkrF69uReh51Z9fa3i6yGXYwO343M5NnA7vp7Gdt55l3D66V9n4sTJ\nDBs2nF/84ifMmPF5Bg7cLav/rw68eQaa78HdnO/y3zW4HZ/LsYHi6w2XYwO3c77yvbv5Htz+2+4q\nttdfDwHV1NZGWb06suXnu+4KnlfDSy/FWb06dyvqCvl3FzSX43M5NnA736fi665cF3lmAkcZY+a2\nff9NY8zJQLW19nZjzIXAk/jJ/nZr7QfbPD4J0DYF9EZgJTDTGJMEnrHWXp3j+EWkSFRf9QPKH324\n5ycIeQxMJLf6UWTG52i86sedPqxfv/5ccMH3+OlPf8SZZ36H999/n4svvoy33nqTG2/8BQB1df24\n/PIriEZbufLKy0gmk0SjUS6++DJGjhzV85jzS/leRJyhnJ9TyvdFavVqv/5WX7/1335NDQwfnuTV\nV8Mkk+B5O3q0SDCU77eX0yKPtTYJfGubHy9POz4LmNXBY1cCh7R9nQB2ylGYIiI5dcghU3nmmX/z\nk5/8iJtvvgOAn/3sWi6//EqGDRvO3//+CPfeew/77TeWfv3684MfXM2KFW/T0lI4/SeV70VEfMWe\n85Xvi9fHH/s9d+rrE9sd23ffOI8+Wsr773vsvntyu+MifZGr+T7XM3lERJzQeNWPu6zId6a+vpZ1\nvZh6ecwxnyUSibDTTjsDsHLlCq6//qcAxGIxPvGJIUyePJV3332XSy+9kJKSUk455bQeP5+ISF+m\nnC/SfamZPIMGbV/E2XffBI8+Cq++GmL33bWXurhD+X57KvKIiARg6NDh/OAHVzNo0GCWLFnEunVr\nefnl+ey0087ccMNNLF26hFtv/S033nhz0KGKiEgvKedLIehouRbAmDF+YWfp0jBHH60ij0hHXMj3\nKvKIiATgoosu5ZprriAejxMKhbj00h9SV1fHlVdezsMPP0AikeCb3zwj6DBFRCQLlPOlEHRW5Nl3\nX38J19Kl2kZdpDMu5HsvmSzaNZXJYuzinS8ux+dybOB2fC7HBm7H53JsAPX1tX29DaKzOb8A/nac\njc/l2EDx9YbLsYHb8Snfu5vvwfm/nU5j+9znKnnuuRL++9/NlJZufSyZhL33rmHAgCTPP98YSHxB\ncjk2cDs+l2ODgoiv2zlfpVgREREREZE+bu1ajwEDktsVeMDfUcuYOO+84xGJbH9cRNyhIo+IiIh0\nqakJzjijgssvL2ezuxe8RESkhzZs8OjXr+NVHqNGJUgkPN56Sx8hRVymnjwiIiLSpauvLueRR/zL\nu01N8Ktf6VKuiEgx2bTJY5ddtt8+PcUY/9jy5SH22afj+4lIsFSGFRERkU61tMD995ey664Jhg5N\ncP/9paxY0dfbgoiIFI9oFJqbPerqOp7Js9defmHHWn2EFHGZXqEiIiLSqfnzwzQ3exx3XIxLLomQ\nSHjMnLmDpg0iIlKQNm3yC/edLddKzeR54w19hBRxmV6hIiIi0qlnngkDcNhhMT796RhlZUn+9jet\n+BYRKRabNvm3nRV5dtklSU1NkuXL9RFSxGV6hYqI5NDChQs45phprF798Zaf3XLLTfzjH38PMCqR\n7lm82C/yHHRQnLo6OPzwOMuWhXn3XS3ZEkmnnC+FauNGP5/X1XV8H3+HrQRvvRWitTVPgYk4yuV8\nryKPiEiOlZaWcd11VwcdhkiPvfVWiEGDElsG/4cfHgNgzpxwgFGJuEk5XwpRqsjT2Uwe8PvytLZ6\nvPOOPkaKuJrvNddaRPqEq64q59FHe57yQiFIJKq3+tmMGTGuuqrrHYYmTtwfSPLgg3/hxBO/tOXn\n999/L0899SQlJSWMGzeRs88+p8fxieRKSwu8+67H5MnxLT+bOtX/evbsEk4+ORZUaCIdUs4X6Z5M\nevIAjBoVB0pZvjzEqFHaYUuCp3y/PZVgRURyzPM8LrroMv761/v473/fA6CpqZGnn36K3//+bm6+\n+U7efXcl8+bNCThSke29806IZNJjzz3bB/N7751gp50SzJunmTwi21LOl0KUKvJ0trsWbL2Nukhf\n52q+10weEekTrroqklFFviP19bWsXt3Y48fX1dVx7rkX8uMfX8nYseOJRKKMGbMvoZA/SBo3b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tn96zIo9f1V+8WH9yIiKuy8ZMHtAVXRER17W2Zne5Vijk92Rbvjy05YKBiORXSS5PbozxgN8B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\nhy8/K31xUhLJLVsTbtGScMtWhFq0JNy8JeFmzY/fpUwIUWH795v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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Set parameters\n", "v = 0.08 # drift rate\n", "eta = 0 # drift rate variability\n", "a = 0.2 # boundary separation\n", "z = a / 2 # starting point\n", "sz = 0 # starting point variability\n", "Ter = 1.0 # non-decision time\n", "s = 0.1 # noise\n", "\n", "start_biases = [0, 0.015, 0.03,]\n", "drift_biases = [0, 0.015, 0.03,]\n", "\n", "plt.figure(figsize=(16,12))\n", "plot_nr = 1\n", "for start_bias in start_biases:\n", " for drift_bias in drift_biases:\n", " \n", " # Estimate choice probabilities and defective cumulative probability distributions\n", " Gc_with, Ge_against = DDM(timepoints,v+drift_bias,a,z+start_bias,s,eta,sz)\n", " Gc_against, Ge_with = DDM(timepoints,v-drift_bias,a,z-start_bias,s,eta,sz)\n", " \n", " RTe_with = np.diff(Ge_with)\n", " RTe_against = np.diff(Ge_against)\n", " RTc_with = np.diff(Gc_with)\n", " RTc_against = np.diff(Gc_against)\n", " \n", " RT_with = (RTc_with+RTe_with) / 2.0\n", " RT_against = (RTc_against+RTe_against) / 2.0\n", " \n", " plt.subplot(len(start_biases),len(drift_criterions),plot_nr)\n", " plt.plot(np.arange(dt,tmax,dt)[:-1]+Ter, RT_against, 'red', label='Yes')\n", " plt.plot(np.arange(dt,tmax,dt)[:-1]+Ter, RT_with, 'blue', label='No')\n", " plt.ylim(0,0.0125)\n", " plt.xlim(0,tmax)\n", " plt.xlabel('Time (s)')\n", " plt.ylabel('RT probability')\n", " plt.title('bias z: {}, bias v: {}'.format(start_bias, drift_bias))\n", " plt.legend()\n", " plot_nr = plot_nr + 1\n", "plt.tight_layout()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.11" } }, "nbformat": 4, "nbformat_minor": 0 }