{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Data Driven Modeling\n", "### (Theme of this semester: CODING AS LITERACY)\n", "
\n", "### PhD seminar series at Chair for Computer Aided Architectural Design (CAAD), ETH Zurich\n", "\n", "\n", "[Vahid Moosavi](https://vahidmoosavi.com/)\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "# 17th Session \n", "
\n", "02 May 2017\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Recurrent Neural Nets and Dynamical Systems\n", "### To be discussed\n", "* ** Dynamical Systems**\n", " * **Weather**\n", " * **Traffic**\n", " * **Energy Networks**\n", " * **Water Flow** \n", " * **Wind**\n", " * **Stock Market**\n", " * **Atmospheric Science (e.g. tele-connection)**\n", "* **Some Experiments**\n", "\n", "\n", "
\n", "# Unrolled RNN\n", "- **To linearize in time: Multiple copies of the same cell**\n", "\n", "![](Images/RNN-unrolled.png)\n", "source: http://colah.github.io/posts/2015-08-Understa/nding-LSTMs/\n" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import warnings\n", "warnings.filterwarnings(\"ignore\")\n", "import datetime\n", "import pandas as pd\n", "# import pandas.io.data\n", "import numpy as np\n", "import matplotlib\n", "from matplotlib import pyplot as plt\n", "import sys\n", "import sompylib.sompy as SOM# from pandas import Series, DataFrame\n", "\n", "from ipywidgets import interact, HTML, FloatSlider\n", "import tensorflow as tf\n", "%matplotlib inline\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Sine Waves" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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2o6PyMyhisEo/+RBgMzM8xotJZCQJVySDSWTESEYNsEUymNIl09OyBXN0tPe1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\n/wPEFy3j6Na59gAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Two signals have the same frequencies but with a shift in time\n", "N = 500\n", "t = np.arange(N)\n", "a = np.random.rand(4)*.61\n", "\n", "x = np.sin(a[0]*(t)) #+ np.cos(a[1]*(t)) #+ np.cos(a[2]*(t))#+np.cos(a[3]*(t))+ .1*np.random.rand(N)\n", "plt.plot(x)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(2000, 1000, 1)" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "N = 1000\n", "t = np.arange(N)\n", "Waves = []\n", "for i in range(2000):\n", " \n", " a = np.random.rand(4)*.6\n", " x = np.sin(a[0]*(t)) #+ np.cos(a[1]*(t)) #+ np.cos(a[2]*(t))#+np.cos(a[3]*(t))+ .1*np.random.rand(N)\n", " Waves.append(x[:,np.newaxis])\n", "Waves = np.asarray(Waves)\n", "Waves.shape" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import random\n", "time_lag = 20\n", "train_test_row=1000\n", "train_data = []\n", "test_data= []\n", "\n", "for r in range(train_test_row):\n", " for t in range(0,Waves.shape[1]-time_lag-1):\n", " train_data.append(Waves[r,range(t,t+time_lag+1),:])\n", " \n", "train_data = np.asarray(train_data) \n", " \n", "random.shuffle(train_data)\n", "# train_data = np.transpose(train_data,[1,0,2]) #time,batch,inputdim\n", "\n", "for r in range(train_test_row,train_test_row+1000):\n", " for t in range(0,Waves.shape[1]-time_lag-1):\n", " test_data.append(Waves[r,range(t,t+time_lag+1),:])\n", " \n", "test_data = np.asarray(test_data) \n", "\n", "# random.shuffle(test_data)\n", "# test_data = np.transpose(test_data,[1,0,2]) #time,batch,inputdim" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(979000, 21, 1)\n", "(979000, 21, 1)\n" ] } ], "source": [ "print train_data.shape\n", "print test_data.shape" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "test and training data loaded\n" ] } ], "source": [ "import warnings\n", "warnings.filterwarnings(\"ignore\")\n", "import numpy as np\n", "import random\n", "from random import shuffle\n", "import tensorflow as tf\n", "\n", "NUM_EXAMPLES = 20000\n", "INPUT_SIZE = 1 # 1 bits per timestep\n", "RNN_HIDDEN = 20\n", "OUTPUT_SIZE = 1 # 1 bit per timestep\n", "TINY = 1e-6 # to avoid NaNs in logs\n", "LEARNING_RATE = 0.01\n", "\n", "tf.reset_default_graph()\n", "\n", "test_input = test_data[:NUM_EXAMPLES,:time_lag,:]\n", "test_output = test_data[:NUM_EXAMPLES,time_lag,:]\n", "train_input = train_data[:NUM_EXAMPLES,:time_lag,:]\n", "train_output = train_data[:NUM_EXAMPLES,time_lag,:]\n", "\n", "print \"test and training data loaded\"\n", "\n", "\n", "\n", "data = tf.placeholder(tf.float32, [None, time_lag,INPUT_SIZE]) #Number of examples, number of input, dimension of each input\n", "target = tf.placeholder(tf.float32, [None, OUTPUT_SIZE])\n", "\n", "num_hidden = 24\n", "num_layers=1\n", "cell = tf.nn.rnn_cell.LSTMCell(num_hidden,state_is_tuple=True)\n", "cell = tf.nn.rnn_cell.MultiRNNCell([cell] * num_layers, state_is_tuple=True)\n", "val, _ = tf.nn.dynamic_rnn(cell, data, dtype=tf.float32,)\n", "val = tf.transpose(val, [1, 0, 2])\n", "last = tf.gather(val, int(val.get_shape()[0]) - 1)\n", "\n", "weight = tf.Variable(tf.truncated_normal([num_hidden, int(target.get_shape()[1])]))\n", "bias = tf.Variable(tf.constant(0.1, shape=[target.get_shape()[1]]))\n", "\n", "# prediction = tf.nn.softmax(tf.matmul(last, weight) + bias)\n", "\n", "prediction = tf.matmul(last, weight) + bias\n", "\n", "error = tf.reduce_sum(tf.pow(target-prediction, 2))\n", "# error = tf.reduce_mean(error)\n", "\n", "# cross_entropy = -tf.reduce_sum(target * tf.log(tf.clip_by_value(prediction,1e-10,1.0)))\n", "optimizer = tf.train.AdamOptimizer()\n", "minimize = optimizer.minimize(error)\n", "\n", "# mistakes = tf.not_equal(tf.argmax(target, 1), tf.argmax(prediction, 1))\n", "# error = tf.reduce_mean(tf.cast(mistakes, tf.float32))\n", "\n", "accuracy = tf.abs(1-(target -prediction)/target)*100\n" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(20000, 20, 1) (20000, 1) (20000, 20, 1) (20000, 1)\n" ] } ], "source": [ "print test_input.shape,test_output.shape, train_input.shape,train_output.shape" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 0 error: 151.137661934\n", "Epoch 2 error: 8.03158283234\n", "Epoch 4 error: 5.75895793736\n", "Epoch 6 error: 3.59865501523\n", "Epoch 8 error: 3.99956032634\n", "Epoch 10 error: 1.65121518075\n", "Epoch 12 error: 0.780969532207\n", "Epoch 14 error: 0.483778258786\n", "Epoch 16 error: 0.301916198805\n", "Epoch 18 error: 0.314855552278\n", "Epoch 20 error: 0.149866065476\n", "Epoch 22 error: 0.188259780407\n", "Epoch 24 error: 0.22558174096\n", "Epoch 26 error: 0.343631673604\n", "Epoch 28 error: 0.317805842496\n", "Epoch 30 error: 0.23353160359\n", "Epoch 32 error: 0.146339193452\n", "Epoch 34 error: 0.135138735641\n", "Epoch 36 error: 0.0324470922351\n", "Epoch 38 error: 0.0912318646442\n", "Epoch 40 error: 0.0711301923729\n", "Epoch 42 error: 0.179471354932\n", "Epoch 44 error: 0.362430373207\n", "Epoch 46 error: 0.256106816232\n", "Epoch 48 error: 0.164400832728\n" ] } ], "source": [ "init_op = tf.global_variables_initializer()\n", "sess = tf.Session()\n", "sess.run(init_op)\n", "\n", "batch_size = 100\n", "no_of_batches = int(len(train_input)) / batch_size\n", "epoch = 50\n", "for i in range(epoch):\n", " ptr = 0\n", " for j in range(no_of_batches):\n", " inp, out = train_input[ptr:ptr+batch_size], train_output[ptr:ptr+batch_size]\n", " ptr+=batch_size\n", " sess.run(minimize,{data: inp, target: out})\n", " if i%2 ==0:\n", " incorrect = sess.run(error,{data: inp, target: out})\n", " print \"Epoch {} error: {}\".format(i,incorrect*100)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "collapsed": true }, "outputs": [], "source": [ "test_preds = sess.run(prediction,{data: test_input, target: test_output})" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# for i in range(1):\n", "plt.subplot(111)\n", "plt.plot(test_preds[:,0],test_output[:,0],'.')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## One Step Ahead Prediction " ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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Rbz8p1br9x9s5w2nnIAZBDI+D1qBDfBGkhdArr0hbtx5f1ul348bZ9hytNHTE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\nE0c2RJuVna05tHM84T5bsV1LYkQiEc0sKZFKStj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9nSyZeC+/DJs3u2S3iOxLjbQEqqyE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\nJLVgIU2SJEmSJElqwUKaJEmSJEmS1MJ/EngJYEKtUTcAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(15,5))\n", "plt.plot(test_output[:150,0],'.-')\n", "plt.plot(test_preds[:150,0],'or')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Several Step ahead prediction\n", "## Run sequenctially and replace the vectors with predictions " ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(979, 21)" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n", "N = 1000\n", "t = np.arange(N)\n", "a = np.random.rand(4)*.6\n", "test_wave = np.sin(a[0]*(t)) #+ np.cos(a[1]*(t)) #+ np.cos(a[2]*(t))#+np.cos(a[3]*(t))+ .1*np.random.rand(N)\n", "test_wave_rnn = []\n", "for t in range(0,test_wave.shape[0]-time_lag-1):\n", " test_wave_rnn.append(test_wave[range(t,t+time_lag+1)])\n", " \n", "test_wave_rnn = np.asarray(test_wave_rnn) \n", "test_wave_rnn.shape" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "collapsed": true }, "outputs": [], "source": [ "r = 0\n", "inp = test_input[r:r+1]\n", "inp = test_wave_rnn[:1,:time_lag][:,:,np.newaxis]\n", "preds = []\n", "for step in range(1,500):\n", " \n", " pred = sess.run(prediction,{data:inp})\n", " preds.append(pred[0])\n", " pred_len = len(preds)\n", " if pred_len" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(10,10))\n", "plt.subplot(2,2,1)\n", "\n", "plt.plot(preds[:50,0],'.-')\n", "plt.plot(test_wave_rnn[:50,time_lag],'.-r')\n", "\n", "# plt.plot(Waves[r:r+1,range(t+time_lag,t+time_lag+3),0].T,'.-r')\n", "plt.grid()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Chaotic Systems\n", "## Deterministic but Unpredictable!\n", "#### e.g. Lorenz curve" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "\n", "\n" ], "text/plain": [ "" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from IPython.display import HTML\n", "HTML(\"\"\"\n", "\n", "\"\"\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Now Let's generate some trajectories" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "#Code from: https://jakevdp.github.io/blog/2013/02/16/animating-the-lorentz-system-in-3d/\n", "\n", "import numpy as np\n", "from scipy import integrate\n", "\n", "from matplotlib import pyplot as plt\n", "from mpl_toolkits.mplot3d import Axes3D\n", "from matplotlib.colors import cnames\n", "from matplotlib import animation\n", "%matplotlib inline\n", "N_trajectories = 2000\n", "\n", "\n", "#dx/dt = sigma(y-x)\n", "#dy/dt = x(rho-z)-y\n", "#dz/dt = xy-beta*z\n", "\n", "def lorentz_deriv((x, y, z), t0, sigma=10., beta=8./3, rho=28.0):\n", " \"\"\"Compute the time-derivative of a Lorentz system.\"\"\"\n", " return [sigma * (y - x), x * (rho - z) - y, x * y - beta * z]\n", "\n", "\n", "# Choose random starting points, uniformly distributed from -15 to 15\n", "np.random.seed(1)\n", "x0 = -15 + 30 * np.random.random((N_trajectories, 3))\n", "\n", "# Solve for the trajectories\n", "t = np.linspace(0, 20, 2000)\n", "x_t = np.asarray([integrate.odeint(lorentz_deriv, x0i, t)\n", " for x0i in x0])\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(2000, 2000, 3)" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "x_t.shape" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(2000, 334, 3)" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Data = x_t[:,range(0,2000,6)]\n", "Data.shape" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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3bp/f4yYCGUm8AWwCMBPsD/obAE8S0RFh9ieEzjPo3NEq3hYWqcZDAKbBX85P3307GsjD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Q0icrWIjK1Xt4hcU+G7/DhB3e8Xkd+KyCYRWSUiN4rInNj76p4HEZklIv8rIltFZKWIfFxEhonI\nfyWo//9i7d4jIlclqP9fReTu0vcZEJFfi8iL29Tut9Spu9k297zt1iNvtl1Qux6b0PaatZF3m12b\nXTeC2XXZ+3rRrpPYn9l2weglu05Sfwu2bWPxvNt11nsHZvkAXo/fsuAc4DDgS8B6YGqD9VwK3INP\n8ja99JgcvP4FfCKKU4BjgV8Dv6xR34vxSeP+Hp+44qzY65eU2vly4Ejg+8DDwD5BmZuApcBxwHOB\nvwDXJaj7GuB/Y9+lP1amUt1PAP8IHI5PkPOj0ncenfQ84CeC7sVnvj0Kv63EanzW2x8nqP8XwBdj\nbR+XoP5vlc7LoaXHh4GdwOFtaPeZdeputs0fztp+8vwgh7ZNMe36OpLZXrM28lCCus2u7WF2bXbd\niP2ZbRfoQY/ZdcL6bSzepXaducFlbOy/Aa4I/hdgBfCuJox9aZXXJpR+3FcGx54B7AWOT1D33goG\n+SSwIPYZ2/HJKygZxF781g1a5gx8kouZdeq+BvhejfYclrDuqaVyz0t6HoCXALsJbrbABfgM9iNi\n7Sirv3TsF8Cna7S9kfrXAee3u91h3e1usz3Kzluubbuodl06npptm12bXdd6mF2bXdezP7Pt4j16\n2a5r1G9jcdeddt2zoS8i0gfMA27WY86fyZ8Dz2miyqeXQkYeFpHrRGRW6fg8fPb48HMeAJY38zki\ncjAwM1bfJuDOoL4TgQ3OuT8Eb/05PuvkCQk+5tRSCMkyEblKRCYHrz0nYd0TS8fWl/5Pch5OBO51\nzq0N6lkC9APPjLUxXr9ytoisEZF7ReT/icjo4LW69ZdCUt4AjAHuaGe7Y3X/ul1tNsopom0XyK4h\nXds2uza7rojZdVV61q7BbLvomF3XxMbiXWjXRdtOrJ1MxW99sCp2fBV+FqURfgOcBzwA7Ivf7uw2\nETkSb5y7SkYZ/5yZDX4Opfc4Krd7ZlBmdfiic26PiKxP8Jk3Ad/F77f6NOAjwI9F5Dmlm2HdukVE\ngM8Av3LO6fqaJOdhZpXvpa/dXaN+gP8BHsPPRB4NfByYA7wmQf0niMivgFHAZvys2jIRObbVdovI\nHvyNI6z7gTa0+W/nxCijiLade7uGdG3b7Nrsug5m10PpVbuuZn9m28XD7LoyNhbvUrvuZeFdDd2P\nMDHOuSXBv38Skd/if8DX4dettOVz6pCkvrplnHPXB//+WUTuxa9bORUfipGk7quAI4Dn1WlPojZp\n04K/tf6/Kyvg3NXBv38WkZXAzSJysHPur3XqXw48Cz9792rgWhE5uU3tXlapbufcshbb3M7rpxco\nom3nya4hXds2u47qNpJjdu3pJbuuan9tarfZdvb0rF2DjcXpYrvu2VBzYC0+ocGM2PHpDJ3VaAjn\n3AA+ycGhwEpgHxGZ0KbPWYm/0Gq1e2Xp/78hIsOBSY1+ZumCW4v/LnXrFpErgZcCpzrnnoy1u955\nWFnhe+n/q0qfFdb/VJ3m31l6Dtterf6nnHOPOOeWOufeg5+9uqgd7XbODVapu9U2t3SddjFFtO1c\n23Xp/9Rs2+y6vO4qdfQ6Ztd16CG7rmV/ZtvFwuw6ATYW7x677lnh7ZzbDdwFnK7HSmETp1Me898w\nIjIOHxryZOkzBmOfMwc4EB/y0Gi7/4q/AML6JuDXdGi77wAmlkIzlNPxN4o7aQAROQCYAqhh1ar7\nFaXH851zy2NV1ToPYbuPEpGpwfteBAwA95UMvVr9lTgWPxMVtr1q/bH3DgNGtqPdFdqldbe7zQbF\ntO2c2/WddWyvVRu5oEbdlTC77kHMrhN9j161azDbLiRm14m/i43Fu8WuXZuyEhbxgQ8/2U75Fgbr\ngGkN1vMJ4GRgNj6l/8/wMyBTSq9fhV+ncSo+QcDt1N5ObCw+HOIYfMa+fy/9P6v0+rtK7Xw5Pq39\n94EHKd/G4MfA74Fn48NAHgC+Uavu0msfx988ZuMv8N8D9wN9dep+AJ/d7yT8LJA+RgXvq3ke8EZw\nN35ty9H4DI2rgA+V3lu1fuAQ4L3A3FLbz8JvaXJLgvp/iQ/FmY3fFuIjeAM/rQ3tvrxa3S22+UNZ\n20+eH+TQtimmXX+DOrbXoo38vlbdLdqI2XWXPTC7NruuY39m28V70GN2Xa9+bCze1XaducFl/QDe\nit8Xbjt+RuO4JupYhN/6YDt+fcI3gYOD10cCn8OHiWwGbgCm16jvFLwh7ok9vhaUuQw/i7cNn1nv\n0FgdE/F7dQ6UjOQr+Ax+VevGJxz4CX4mbwfwCH7fvGkJ6q5U5x7gnEbOA/6m8yNgS+mi/ljpgq9Z\nP3AA8H/AmtI5eaBkWOMS1H916btuL333n1Iy9Da0u2rdLbZ5WNa2k/cHObPtWraXY7seU8/2WrQR\ns2uza7Nrs+uGbASz7a570EN2Xa9+bCze1XYtpcoMwzAMwzAMwzAMw0iBnl3jbRiGYRiGYRiGYRid\nwIS3YRiGYRiGYRiGYaSICW/DMAzDMAzDMAzDSBET3oZhGIZhGIZhGIaRIia8DcMwDMMwDMMwDCNF\nTHgbhmEYhmEYhmEYRoqY8DYMwzAMwzAMwzCMFDHhbRiGYRiGYRiGYRgpYsLbMAzDMAzDMAzDMFLE\nhLdRFxE5RUT2iMiErNtiGEZ7MLs2jO7D7NowuhOz7e5AnHNZt8HIGSLyC+APzrl3lP4fAUx2zq3O\ntmWGYTSL2bVhdB9m14bRnZhtdycjsm6AkX+cc4OAGbphdBFm14bRfZhdG0Z3YrbdHViouVGGiFwD\nnAJcJCJ7S2Et55b+nlAqc66IbBCRM0VkmYhsFZHrRWR06bW/ish6EblCRCSoex8R+aSIrBCRLSJy\nh4icktV3NYxewezaMLoPs2vD6E7MtrsX83gbcS4C5gD3Au8DBDgSiK9JGANcCLwOmADcWHpsAF4C\nHAJ8D/gVcEPpPZ8HDiu95ynglcBNInKUc+7h9L6SYfQ8ZteG0X2YXRtGd2K23aWY8DbKcM5tEpFd\nwDbn3BoAEdlToegI4C3OuUdLZb4DvBGY7pzbDiwrrU95PnCDiBwInAfMcs6tLNXxaRF5CXA+8N4U\nv5Zh9DRm14bRfZhdG0Z3YrbdvZjwNpplmxp6iVXAoyVDD49NL/19JDAc+EsY8gLsA6xNs6GGYSTG\n7Nowug+za8PoTsy2C4YJb6NZdsf+d1WOaR6BccAgMBfYGyu3pe2tMwyjGcyuDaP7MLs2jO7EbLtg\nmPA2KrELPyPWTv5QqnOGc+72NtdtGEZ9zK4No/swuzaM7sRsuwsx4W1U4lHgBBGZjZ8BG4ZP7NA0\nzrkHReSbwLUi8k688U8HTgPuds7d1FqTDcOow6OYXRtGt/EoZteG0Y08itl212HbiRmV+CSwB7gP\nv2fggQzNpNgM5wHXlupfhs+8eBywvA11G4ZRG7Nrw+g+zK4Nozsx2+5CxLl2/IaGYRiGYRiGYRiG\nYVTCPN6GYRiGYRiGYRiGkSImvA3DMAzDMAzDMAwjRUx4G4ZhGIZhGIZhGEaKmPA2DMMwDMMwDMMw\njBQx4W0YhmEYhmEYhmEYKWLC2zAMwzAMwzAMwzBSxIS3YRiGYRiGYRiGYaSICW/DMAzDMAzDMAzD\nSBET3oZhGIZhGIZhGIaRIia8DcMwDMMwDMMwDCNFTHgbhmEYhmEYhmEYRoqY8DYMwzAMwzAMwzCM\nFDHhbRiGYRiGYRiGYRgpYsLbMAzDMAzDMAzDMFLEhLdhGIZhGIZhGIZhpIgJb8MwDMMwDMMwDMNI\nERPehmEYhmEYhmEYhpEiJrwNwzAMwzAMwzAMI0UKJ7xF5C0icreIDJQevxaRFwevjxSRz4vIWhHZ\nLCLfEZHpWbbZMIzamF0bRvdhdm0Y3YnZtmE0R+GEN/A4cAkwr/S4BfiBiBxeev0zwJnAq4GTgf2A\n72bQTsMwkmN2bRjdh9m1YXQnZtuG0QTinMu6DS0jIuuAd+KNeg3wBufcjaXXngHcD5zonPttdq00\nDKMRzK4No/swuzaM7sRs2zDqU0SP998QkWEi8gZgDHAHftZtBHCzlnHOPQAsB56TSSMNw2gIs2vD\n6D7Mrg2jOzHbNozkjMi6Ac0gIkfijXsUsBl4pXNumYgcC+xyzm2KvWUVMLPDzTQMowHMrg2j+zC7\nNozuxGzbMBqnkMIbWAY8C5iIXz9yrYicXKO8AFVj6kVkCnAG8Ciwo33NNIyGGAUcBCxxzq3LuC1Z\nYHZtdCNm12bXRnditm22bXQfqdp1IYW3c24QeKT071IROR64CLge2EdEJsRm2qbjZ9qqcQbwP6k0\n1jAa52zgm1k3otOYXRtdjtm12bXRnZhtm20b3Ucqdl1I4V2BYcBI4C5gEDgd0IQOc4AD8eEw1XgU\n4LrrruPwww+vUaw5FixYwMKFC9teb5HrTrv+ItZ9//3388Y3vhFK16Nhdp0WRW17Ees2ux5Cru0a\ninmdWd2dr99sewi5tu2iXsNFrTvt+otq14UT3iJyOXATfiuD8fgZiVOAFznnNonIV4FPi8gG/JqT\nzwK318miuAPg8MMPZ+7cuW1vc39/fyr1FrnutOsvat0lei7Eyuy6c3WnXb/VXRWz6wLYNRT3OrO6\ns6kfs+1C2HZRr+Gi1p12/UW168IJb2AGcC2wLzAA3IM39FtKry8A9gDfwc+8/QR4WwbtNAwjOWbX\nhtF9mF0bRnditm0YTVA44e2ce3Od13cCF5YehmEUALNrw+g+zK4Nozsx2zaM5ij0Pt6GYRiGYRiG\nYRiGkXdMeHeA+fPnW90drr+odRvFocjXWFHbXtS6jWJR1OvM6s6mfqMYFPUaLmrdaddfVLsW56pu\nqdcziMhc4K677ror7YX6hlGVpUuXMm/ePIB5zrmlWben6JhdG3nA7Lq9mF0becFsu72YbRt5IG27\nNo+3YRhdzUknwStfmXUrDMMwDMMwjF7GhLdhGF3Ntm3w/e9n3QrDMAzDMAyjlzHhbRiGYRiGYRiG\nYRgpYsLbMAzDMAzDMAzDMFLEhLdhGIZhGEaX89WvwgMPZN0Kw6jN9u1Zt8Aw0qNwwltE/ktEfisi\nm0RklYjcKCJzYmVGisjnRWStiGwWke+IyPSs2lxEBgdh796sW2EYhmEYRjt485vh5JOzboVh1Mau\nUSMJe/bAunVZt6JxCie8gZOAzwEnAC8A+oCfisjooMxngDOBVwMnA/sB3+1wOwtNXx+cdlrWrTAM\nwzAMo11s3Jh1CwyjNub0MZLwjnfA1KlZt6JxRmTdgEZxzr00/F9EzgNWA/OAX4nIBOCfgDc4524t\nlTkfuF9EjnfO/bbDTS4st96adQsMwzAMw2gXu3Zl3QLDMIzW+dGPsm5BcxTR4x1nIuCA9aX/5+En\nFG7WAs65B4DlwHM63jojFb71LRAB57JuidEObAmJEefb34Zf/SrrVhitYHadHwYHs26B0U2YbRtZ\ns3u3fy7ava3QwltEBB9W/ivn3H2lwzOBXc65TbHiq0qvGV3AJz/pny0JR9dgS0iMMt7wBjjppKxb\nYbSI2XVO2Lkz6xYYXYbZdhOccALcdFPWregOVHAXLYqncKHmMa4CjgCel6Cs4D3jueOGG+DSS+G+\n++qXNTyjRvnn9ethzJhs22K0ji0hMYzuw+w6P5jwNtqJ2XbjOAe//S1ceCE89FDWrSk+ofAukg4o\nrPAWkSuBlwInOeeeDF5aCewjIhNiXu/peK93VRYsWEB/f3/Zsfnz5zN//vyG2va1r/kZrRtuSFb+\n0kvh/vthwwaYNKmhjypjxQoYPx5iX6FhihC+PXKkf96wAQ44INu2NMOiRYtYtGhR2bGBgYGMWpNL\nEi0hERFdQtJznbhhFBCz64ww4W2kjNl2HdQGt23Lth3N8MQTsHIlzJuXdUsiVHgX7d5WSOFdEt2v\nAE5xzi2PvXwXMAicDtxYKj8HOBC4o1a9CxcuZO7cuS23701vaqz87NleeN9/Pzz3uc1/7qxZMGdO\n6/t0FuEiVuG9fn3tcnml0oTO0qVLmZenu1pGpLWEZHAQRhTyjlcsDjkE3vlOeD02FmYAACAASURB\nVOtbs26JkSdsaVi27NiRdQuMbsVsOxlqg0VcInn44bB5c74cc0UNNS/cGm8RuQo4G/gHYKuIzCg9\nRgGUjPyrwKdF5FQRmQdcA9ye19CW/ff3z60KZoC//KX1OoowG7fPPv45a+HtHHz4w/DII9m2o8vQ\nJSRJQk0SLyEpYmdXNAYH4a9/hfe/P+uWGDkkFbvuNX7/e7+Fztatjb2vCBPqRmEx206AjkGKMMaO\ns3lz1i0Yinm8O8db8Eb7f7Hj5wPXlv5eAOwBvgOMBH4CvK1D7WuYPXv8cyvG2M5ZqEY79CxQ4b1h\nQ7btWLsW3vc+v1xAf0ejedJYQuJvB/287nV+f3pobgmJUZ8nnvDPrS7/KNoMtmJLSCqT56VhRePK\nK2HdOli+3HuhklK0wWneMNuuTFp99lln5d+2ReBzn4N/+7dk5dXjXdT+LW+0w+OdhV0XTng75+p6\n6Z1zO4ELS4+OEgpg57xh1kOFbisdYzOzUaedBqec4kVjSJ5m4z73OTj1VDjqqPLjeq42bux4k8rY\nssU/792bbTu6gbSWkMBCYC7f+Ib3FBnp8eij/lmjeJolT/egRrAlJEPJ+9KwoqGDzSRjixAT3q1h\ntj2UNPvsxYvzbdvqaFm4sHHh3UmS6pAi0g7hnYVdFy7UPE0GB+E//xNikx9VWbx4qPALDSvp3nIq\nvFu5eNata6z8Y4/BL34Bl11WvT2QrRd32TJ4+9vh4ouHvtaOc9YO8hh+U0Q6sYTEJkfSZ8UK/zyz\nxRV8eY+6WbEC3vEOu6bqkdelYbt2wQc+0Njyk0cfzcf6Ru2TG106Y2u8jXaSV9vuFGp/jdhVp5e7\nPfEEDBsGP/tZZz+3U+j9uGiTiia8A5Yvh499DC66qH7ZbdvgFa/we/KFqAcUkhtkO0Tk2rWNldc1\nyYcdNvS10NuU5QD49tv98zOeMfQ1bdfu3Z1py86d8MIXwrXXlh834d023gJMwC8heTJ4vC4oswD4\nEX4JiZZ7ddIPsKUA6aN22WoSu7wL7wULvKfjySfrl+1xUrfrZrj5Zj/pfOWVyco/+CAcfDBcd12a\nrUqG9nm2xtvImFzadqdQ+2tEeHd68uvxx/3zD3/YvjpbmXzcsMEvzVy2LFn5nTvhxz+uXy5rB1yj\nmPAO0IH5mjX1y6qnO57MLBTeSWe32iG8G00ytqm04kbXSldqT6ttaoTp0+EjHyk/psssKhl62sI7\nfj6feAJ+/nM499zy4+HvbTSPc26Yc254hce1QZmdzrkLnXNTnXPjnXOvdc6tTvoZJrzTRyftWrXL\nvAtvjWYyL2JtOmHXzTBqlH++//5k5Z96yj/fe2867WkEvfYaXY5hwttoJ3m17U6h9pdn4T2spPAa\nuVc8/HDtSK6kkbyV+O53fTLi7343WfkPfQjOPDNawlYNE94FptrA/Kqr/DZdjz0WHau2tjj0gDbq\n8W7HGu+kazlqCe/QSDvhUd671092vPvd5cdVeFeawGjXAL8SN94IU6bAffdFx5L83ka+sbDg9FFb\nbdUu877GWycDN8U3yjEKgV5f9QZ0SrPrqtPAhHd72bEDvvxlm0Q3GqMZj3enQ821jUnvFatXw6GH\nwhVXlB8Px06tTB7oeDmpUNYJz3r9bNHubSa8A6oNzG+4wYea/fnP0bFqSe+yCjXXOpxLFgpSy5sc\nGmkrs1tJqXYu1dgq3azS9Hh/+tP+eVWQd1OF97CYxeiNxPaHzj/m8U6fdgnvvG/9ZsK7ONSKmEoa\nNqm/c/z+nyZ/+lPlpQztEN42CRnxs5/BBRfAe9+bdUuMIqH214gtddrjrXok6b1CQ9PjWxuH/XEr\n36FRrTN8uH+ut3uRebwLTDUD0g4rFNXVPKBZhZqHn5tk9ieJqIXOeLyrhcmrIK9k6GkKbz03oTdb\nf+94hICe9z178pF4x6iOCe/0aVckSmjzWdrVjh1w111Dj2tfYcI73/z5z14s//GP5ccbzUVQbeI1\nTY46yu8OEB+XqG01KrxDm+rVe+GSJVF+G0VtOOsdUoxy8j451MxyKLXBTt1HGvV4r1zpnydNKj8e\n3jta8S43qnX0/lwpeXQ4LjCPd4EJDT38IfWiCw0tvEmHF0AzoeYq3rIQ3pXa2GmPdyi8w3NQbXLA\nuXSFt9YZDqr199Z9oBX9vZ3rzLkymifvHXk30C6Pd3hfynI2+4or4Ljjhg7W9Z5v2/jmm4cf9s9f\n/3r5ce0/kt4T9P6fxRKI+DXW6GBaCccFvSq8X/xiOPro8mM6durkpIpRn7yPp5q5F2j/qJ7ctNFr\nO2l/rB7v8ePLj7fL463nLKlQVpusJLzD72Qe7wITdkZhZ6cCLBTe4evhRdSox3vPnuj9rczahJ+b\n5CLMq8c7vJlVW+O9a1c0YEqjffr9Kwnv+LltZqLFyIZeHWx2ErXVVjvC0JY6ZVfbtg1NlqnXzPe/\nX35c22Qe73yjg/f479qo50VDHdP4vR97DN7//upCI379q42Z8G6OuKdS+/Ciec26nU7tWNMseh01\nIqLVljvlBNA2Jp3EeOIJ/xy3haxCzdU2K+3aFLbRhHeBCY0h9GjrbEu1UPPwomx0jXe7Mog3Krxr\nhXFn6fEOz0c1r3zaEwPannByRX/vnTvLr5NGIw2M7OjlwWanSCPUvFMDsBe8YOjWhXr/iy+H0XuD\nCe/8cMEFMG1aeX+sv088pLzRAaDe/1uNcLj7bvjMZ8qPfec7PnvvV79a+T3xfkVtrJXtxHrhXnjv\nveXXQrWxjPbhNnGeL/Lu8Vb7i0dB1kKvx04tTWzU4633t/i9JSvhre2ptMY7vJ8VbexdOOEtIieJ\nyGIReUJE9orIWRXKfFBEnhSRbSLyMxE5NEndYWcUrt3VTreaxzu8KBv1gKYhvIu8xjuJxzvN9u3a\nFZ3LSh7veHvC37toxt9rWKh5+qQRat4pkXDHHUOPVZug1HuE7WqQH778Ze8ZCfsTvYfHryHtZ5L2\nuZX6hGY45RS/B3w46FaBsWJFdCxsV7s83mE9eRc1jbBr19AJkZ//3IeUX311dKxeXh7rv/NF3j3e\nan+NCOhO92vNepjjwjurNd5q15XK52U5WjMUTngDY4E/Am8DhlzyInIJ8G/ABcDxwFZgiYhU2Dir\nnHBgrhdIONNSzeMddoBbtkSJCRoR3pMmtR5qrom/Ggk137Fj6I1j2zYYPdr/naXHu57wHjWq/Tfn\nSoM2qC289bxbx51vesHLkzVpCO9O3IOqJWqpNkGZ5naGRmuE/XS136/RLTyb2fLzXe+CF76w/Jj2\naZXGEkkn8Ju99rrV433++TBxYrkN33mnf67Wh4dlTXjnk7zfW5vJM9Tpfq1Rj7eWT9vjndTWai0D\nKfL9rHDC2zn3E+fc+51z3wcq7ap5EfAh59wPnXN/As4B9gP+vl7dlUKIq4nCjRth7Fj/dzzUfMoU\n/3cSARwK71Y93pMnJ//cgQGYMMH/Hb+ot26F/n7/d6c93vFQ83Hjqg88Jk5s/81LlxWMGDE01FwF\ndnyiRX9vC1XLN0W7OReRNELNOzFAqSZ66i13KdpMey/QyHKlpL9fM7/3Jz7hPa+VCLeq1H4m7Fdq\nCe9mJ7eKPFCtxU9+4p/DBIjqMKmWEDf8HW2Ndz7Je1RGuJ1Y0mi6sJ/phA02mri5msc7q1DzWu0v\n8v2scMK7FiJyMDATuFmPOec2AXcCz6n3/kqh5ioKp00b6o3dd1//d3zQ1ogA1jonT25deKunPanH\ne8YM/3clYavCu1Me7wMOiD4b/KBi2zaYObO6t2LixPZPDKjwPvDAoZ32fvv5v+O/99Sp/m/ruPON\nhZqnT1E93uGgPBQ91ULNTXjni/B3qOTx7rTwrjcQ1G17oHLG9GpLmPbujb5Lo3ZR5IFqLQ4tLSQM\nt4xT4R2exzB6MbwezOOdT4ri8Ybkbe10v9auUPNwzNvK79LO+26Rl850lfDGi24HrIodX1V6rSaV\nPN4qxGbNGhoeNrNUY9zjPX68T7jQSeE9MADTp/u/k67xVuFdSdh22uM9a1b02RDdAGbMqC68+/vT\nCzWfNat8ILRxYzTREh8gmfAuBt002MwraWQ170SnGg7KK3m8454KbZ8J73wQRiflQXiHWXj12gnH\nF6HHu5FQ81aSDnar8NbzUElkN5IQ1/rvfJF3MRWOA/MqvBsNNVcbiuePaFey07Q83nm/VuKMqF+k\nKxAqrAePc/XVCwCvOD/9abjxRjjggPnA/IrC+8gj/d/x0OPx431YcpIbudY5aVJ5Z9woGzdGM7/1\nLmrnanu8N22Kwqez8njrQKrTwlsnWvbfH5Yvj45v3Ahz5vi/45324Yf7vxvpuBctWsSiRYvKjg3Y\npsCp0k2DzbxS1FDzah7vSsKtXbP/RvsIf79GhHeja7ybEd5r1vgIqvC6CpdXVQo1D9cmt+vayyJh\nYSeoJbKrebwrCW9bKpYv8n5vbcbjnSTLfjtJw+PdSrvbed8t8kRit3m8V+JF9ozY8ekM9YIP4bzz\nFgKLEVnM2WcvZvHixcyZM58xY7wQDW/stULNx43zwruTa7wHBnw4PNSvZ8cOf6Oo5vHetCkKl++U\nx3v//f3fej5C4T04WG7sOiiZMiUd4d3f7x/xUPN6Hu9GOu758+ezePHissfChQtb/wIFJc3dChQL\nNU+fdoaa6/6onRbeoeiplOCxXTtR9AqdsO1QVOVhjXdceNdqYyMe72a8bMrOndHWR0UbqNZCz284\nPmvE421rvJsjbbvOu/Bu1uMtpcxUefZ4x+9zWYSa79oVfVYl29T74ogRxfN4d5Xwds79FS++T9dj\nIjIBOAH4db33a2fU318eaj55sk+kFnaWGzZUXvO7ZUtjwnvzZj/A7O9vfhDnXHmoeb16dDCi5bP2\neK9Z49syZkx0M9M2VvLKa2K70aPTCTWfMqW8LYOD/neqJrz1XFnH3RKp7VYwapR/7qbBZl7R/BDt\nEN7jxvm/8xBqHt5/tB9Ieo830rNtpRmP99ixjQnvESOaE94aRVVv944kydV0rDF2bHPCe8wY/3e3\n3Au3b4/OZSXhHZ5HCzVvO6nadd6v0a1bYeRI/3cjwruT/drWrV5fNOLxHjNmqC1s3956u53z97hR\noxpzSlZrv7Zx7Nj8XytxChdqLiJjgUOJMpofIiLPAtY75x4HPgO8V0QeAh4FPgSsAH5Qr271iIXC\ne/VqLwrHjYsuhK1b/YWo4dGV1niPHJns4lq/3nu7k5avxNat/sJLusZbO6BKa9Shsx7vwUE/MJk+\nvXxyQ9sYeuXV8AcG/G/U19f+9q1Z44V02JYw4Zq2BfxNZNeuSJBbx908zrmfAD8BEJGauxWUypyD\nj2L5e+D6WnWPHOk7vKLdnIvI9u0+eqXRPYbj6ABlYKBzHm+dOdfB+t690XaBlTzeEyea8E5Cmrat\naH8xYkS5ANu82U/QVhLekyb5vbP37oVhdVwQWj7p7619BkTtqbc1adwLq+0O+xUt08zklgrvTtlU\nJ1BvN9T3eG/Y4Af9O3YMHbO1up1rL5K2Xee9v962zfcBq1Y1Fmo+fry3705lNZ80aeg+95XYtcs/\nZsyo7PHWMXGzY+7t2734TnofrZf/KhTeRbufFdHjfRzwB+Au/Czbp4ClwAcAnHMfBz4HfAmfzXw0\n8BLnXN2fOhTeOvhatcpfiGPHRjdxnc2eNs3fyOMz1Y14vDds8BdW0jXhldCOO6nHWzsrTWgWDkp0\nsNkpj7eey7jw1uOV2rhxo7/hpSG8n3rKRzKEHu/Vq/3z7Nn+WY+H68HBOu60aHW3Ap2VtlDzdNm9\n2w8m2uXx1u0aOzFA2bjR3/NCkb1lix8oTJ9eOdx30qT8h0PmnVZtW9m40Ydw7rvvUI+3/n7h3s0q\npKH+b7h3r//NG/m91671A2z9LIjE4AEHlO8BvHWrv/bi44gJEyKhqGiZCROay2reSZvqBDqWCSdc\n9uyJfve4xzsepehctFzM+u/20Q67zruYaiYJcRYeb71vuTpZrtRWKtnC1q2+3a2MucNtgJPYWr1l\nuGrD48bl/1qJUzjh7Zy71Tk3zDk3PPb4p6DMZc65/ZxzY5xzZzjnHkpSt3ZGkydHIWqh8NYLQW/2\n06b5WenwJq4e7KRCesOGqHyz3hOdzWpUeMc9uBB1XurxTvuC1oRy8VDz1av9edHBS9jGND3eTz45\nVHjr+dp3X/+Z2hYV3urxtuQsqdHSbgUqvLtlsJlXQlHQqic4HNR0KtR84sTy+3m43MU83qnRkm0r\nOhk7fvzQNd4zZnjxHPYVofCu10/rb9+Ix3vtWt+PDB9evjWpiD+ubdRrbN99y6+xTZv8d4kLb62r\nma00d+zovlBz7ZsPOSQ6N+qIOOCA6juThLsvDA6a8E6Blu0672JKPd7QmPDWMW2n1ngnnWBU+5ky\nZagt6BLaVtZTN7qDU5h4ulL5rVv9eHzUqOLdzwonvNNEPWJTpkQ3bxXe48Z5Q9u7t1x4jxkT3cQ3\nb/YXyLRpjXm8WxXeKgCnTfMhc0mE97Bh0exv2LHrQCCpsbaKepMrTW5oRAGUD0rS9Hir8B47NgpP\njk+0xD3eU6cmm2i5+WZ45StNoLeRRLsVmPDuDGqjEya0bpedFt4bN/p7XjXhHdqsegamTDHhnSKJ\nbFvRPmHcuPI1u7t2Dc1lsnu3f2gflzQnytSpjYWaT51avkRNJ3fCyQEdZ+y331CPty5ZqyS8J09u\nLtS8Wz3eBx88NKQ/fk4r5eUJxcbg4NDzcs01cNNN6bS9R0ls13kX3s14vNuxVjopmpws6Vi+Vr+m\nOTFaGXM3mkg6FOqVxtZbt3r9VcTkaoVb450mocf7sce8Bzv0eIO/kevNfurU8oGaisjp05Ov2d6w\nwc/CtrLG+6mn/PPMmckE4OrVvu36neIz7eAHz3196V/QTzzhn2fMGOplVqEL5YOPgQFfvt3Ce9cu\n/7nq8QZ/btas8Z81YUL5RIuGw0+Z4n+/euf9nntgyZJICBqJCXcrCGfQp+OXndRk1Sq/TeAHPwhf\n/rI/Nn/+fObPn9/+lvYw4frTwUF//6y48i8BW7ZEETmdEt5xj3e1LQ1DIRauMQXbJrAJmrbtBQsW\n0F8a+d5zj+9LR4+ez5Yt3q4rJRGdMKF8QAfJhfe0aX6MsGdPlHG/GmvXRn1sKAg1UWvcOxv3eKvw\n3vD/2fvyMDmqqv339swks2+ZSWayTFaSELIvElYRMBBBBD6QXxAF3AAXNCr6uYKgoqhfRMUPEdkU\n8gmIsohGEJEtYUkQQhay7zOZNbMkM5nJzP39ceZ4b1VXdVd1d/U2932eebqnurv6dnede8973nPO\nbXMO+lRUWJu1ecHRo+ozZxPxLiqi32bvXjrG36m918ShQ8CJJ9J9J+INWBvQAcDttwOnnAIsXWps\n2yfiWrOB5fjmN8v+s1MPkH5r9uHDsSneySLeumIM0DzHPr8TIqWas+IdDyfQibeX7BI2repqYOtW\n5/MVFRHxjmc+S4VdG+KtgZusVFTQJN3aShN3XR0RWoB+7Pp6ci7z860KqK6M+lG8Z8yg5x875q3R\nix0NDTSWsjJv78ukdtgwcoz1hV3/DLm5wSve27bRAllQYFW8uakdE2/dKWltBaZNSzzx3r6dbidO\ntO5nWF9PQQ0hwhXv3Fxy5rwQ7/37Kf0tVjIyVCGl3CmE4N0K3gYsuxXcEe31U6euwNq18/H1r1PG\ngUEw0FPNAZrPePsiv+jqUk5NslLNa2qcFW97jXd7O82dJSXhc62Tc7hu3TosWLAgwNFnLuKx7RUr\nVmD+/PkAgGXLKEiuq8k6YQbUb6g7gIA/xRugNccL8Z41y7qmcRlaUZEKlrN/V1tL9sPBKibe+fnW\ndaWzk2wqlq7mutqWLcS7sZF+Xz3TQVe8+/vpe8rLI5+uupp+Oz1LEVC/rZ14c7NcwNi2H8S7ZgMr\n8J3vzMfSpUGOMj7ou/94tcUjR9T1FLQN2uc/P4q3nYvoqebJUrx14u2Wal5URPYcj4+QCrs2qeYa\n+EIrL6dJescOOj5pkooUdXWRGs6NtnRHzU68vUR1Dh4kx46JfSyqd309LdxCeCPee/YoApifbyW1\nDQ10W1OTHMV7+3ZgyuDOjkVFynnfv58+k1OqOTdASzTx3rCBbmfOVA5KZyewaxcwYQL9ryveDQ2k\nhgkRnhLohH37VCM2AyuEEEVCiDlCiLmDhyYN/j/YXu8/uxV8UAgxC8AD8LhbAQdvssXZTFfoijcQ\n/36fyU41tyve7MDX1qrGcQA5NJwRZFLNoyNI22ZwGrddYQbCe3DYiXS0dZodQH6+l9+8pYUcWHuq\nuX1rUp0k6mNsb3dursaEPJa1ubNT2VS2zIUsIrgRb0AFNJz6OOhkAwi/FrhZrkE4grbrdE4fPnqU\n/vRgnBd0dKiAX9Cfz++8ZQ9C6c/XFe94iTfXeEdr9sYBbreeMbrinc7XihMM8dYwMEDREybeugLK\nky8TbzciJoTqjhvtQu/tJeI9blx8xLuhQW0N5oUAbtsGTJ5M9+0Le0MDLUwlJclRvDduBI47ju4X\nFpIxSQns3Enfuz3VvLeXotyjR4erAfHg2DHgmWcoCFJdrVLyWlutxFtXvPUAjJexsOJt4IjAdivg\na8h0NQ8WiSTeyVa8W1vDnfLWVpoD7YppR4f37CIDAAHaNoNTu3UCxqnYdlLrdxcQO1H38ps7pZrr\nire+VWUoFN70i0m6U403E2+/9tXVNTSId3Mz2S37REeO0HfY2xvex8G+taoT8WaF0iAMgdp1Ol+j\nPCf4Ubx5u65kE29ev7wSb6cgVFdX/CRXn0eljP77chNltzJcXfFO52vFCYZ4a+DarfJyurjefJMu\nwvJyZSytre6K944dlJael+etZnv/froAx41Tdb+xOHI7d6p6SF01doKUVpVZHz+gSLwQwSrehw8D\nl19OtXlnnGEde3MzPa4Tbz24ASjinahGZUuXUv3vpZfS/zz52Im3HmjZvVt9715SzXfsUNeNgRVB\n7laQbQ2F0hX2VPNYSSk7KMki3lJSMG/UqHDiXVkZHvxjxXvYMLOdmBcEaduMpiYi0k7E2654+90F\nhJ/Pa0K053d302t4PLq6XVERThIrK1Vgn22IibeT4h2L8nTsGJ0nmcGsZMCJeDc1kXOv92lhgu2W\n1eJEvPv71b7LBuEI2q7T+RqNhXgzsU3WjkF2xdtLqvnw4cpf0ue5RGwn1tZGxN3rbhJMvN2yh48c\nMYp3VoAV71Gj6P8nnwTmzaP7vEgfOECF/lOn0v+6Arp9u1KSvagh3AxEV7xjUXA3bgROOIHu69F0\nJ2zfTovJ9On0v31hr69Xnz9IxfvFF4GVK8nQP/ABOlZcTBMap/hPnBiean7gAN2OGUOP9fYmhlC9\n/DJw6qnAzTfT/zyh7thB78m/t94ATg/ARCPeTU10njlz4h+rgT9k2xY66Qq/C70beP5KVqp5VxfN\nL9xTgu3bTrz12m8m3kbxTj04cMIETCe6OTnhGQuxKN7cg8TL87lh6Lhx4Yq3PdWcU9Lt1xir45FS\nzf3Yl74FHpA9c6E94CKlIuM87x85ogi2XfFua6Pv0okM8O9mUs1Tg3QmU7EQb/uOQUF/PnuNd7R5\ni0sxWAS020K8zdXs5482nkOHImeWmVTzLAETbyalmzYBXF/PNX0vvUQXARMonYjZiXc0Er1lC6WZ\n6c3b/DpyjY0UNZ8xg/6PRLxfew249lr6jKecQsd0R5PHxGp4kIr3xo0qtZwnolGjKPX+3/+mMR5/\nPH0/+fnqM737Lt1OmKBIebzp5keP0kL8qU+paGRBAU0Qzz1H/3MApqyMJoTOTiLe06bR8Ugp/ocP\n03UDGOKdCphU8+SgrY3slW0oXuKdLJJwcLDnrpvizfOMXfE2Nd7pgcOH6beprnZO7WYCphNv/TqN\ntn7ogRYg+nWtB9RLS+n1UqomnfoazSnpOkns7aXH+dqzN1eLpQyMv5NsSjXnXWeYePf303flRLzd\nFG83GwfUd2YU79Qgna/ReBTvZKaa8248gPemy07Eu7NTkdx4FO+KCu/EW1e8+/rC/TeTap6GEEJ8\nVgixUwjRLYRYI4RYFO01nGrOqWkA/tNVUQi6KJ9+mu7Pnk3HKytp8u7pAd55Rx33ooasXUvksrAw\ntlTzhx8Gfv5zur94Md3qKVd2LFlCe0lfeKEyxrIypVRJSQ3GWD3Py0tcDbUdmzZRgEPvDltTQ2N/\n4QUaAxMm/o4BYP16UsK58QwQf7q5vigzuFZ/1SoaBxPs6mqaoN56i76vwaa6EWu8lywBLr6YzsH1\n7AbJg1G8k4O2NlWTBcS+QPP8lay02GjE20mNLC83ine6gJua2lPN9XRtwLpNnH6dRvsNm5tV3xYv\nz9+3j27HjKHrpL2d1pjeXvItiopozervd1a8WZ11SjXnpmt+FW92+rOJeDc10W89aZK1Gap9K9Lu\nbrXVq30LWDsZsJMNwCjeqUI6q5jxEO9kBZT1Bo1AdF9e3+0IUPNcXx/ZWWVl/KnmFRXe51FueMrj\nd9pbPFP38c5K4i2EuAzU6OFGAPMAvAVglRCiKtLrWPEWAvjmN6ne99RT1ePV1dQRfN48tYCNHEmT\n+rp1dEGedBIdtyvJOvbupQv5xReBRYPhAL+Kd2cncNllwPe/D5x2muqW7aZ49/aSIX7hC8Dvf6+O\njxihSO2uXTShMPHW65kTjbY2lerH4DqrP/xBBRIAK/Feu1YFN5z2+I51LICKRDKqquh3Ou00Mm6A\nroHGRlKwCwtVpoFbqvnevcArr9DkcdddZiuxVMAQ7+SAF1beQizWBZoDgeXlZC9BL6rcN8JOvFta\nnNUwTm81Nd7pAS4/qqkhktTXR+sd10/bfz926Lyuuby1pddysC1b6FoqLFQZUrx9GI8RIP/AXo98\n5Iha65yaqzU30xrkNxvNHszKhrmQm99OmWJtfstlB/p32tBAvl0sxNso203engAAIABJREFU3qlB\nOpOpWHY6YLKerBpv+7UdzU/mucVuCy0tdDtiRHwk99AhK/GONo8ePKjWZCCci3BgwSje6YPlAH4t\npXxASrkZwLUAjgD4eKQXseINAN/7HinKuiLLtRL63oIjR9IF++STdFExKdSVZB0tLZRaXlJC6vIl\nl9BxvzXevOhccQWNk6Gn2ulobqbb979fOSIATQJsWH/7G33e00+n/+2N1xKJnh7rOACVadDfT+PU\nx9jaSob70kukIAOJV7ztxJvTwj/0IXWsupq+y8ceo+uASYYb8WaHa80a9b0aJBf5+UTgTKp5sLAT\n71jVYJ6rqqqSE83eto0W8BEjrIHLAweoiaN94deJ2NGj0bdFMQgWvBbqyufhw2rbSfs6wSnoXok3\nO4BeHNjnnwfuvVcF1Fnx5nWAFW+A1ul9+2inC/0a4wyMqqpwxZtVKb/KUzammnPZmf67d3VRsHvc\nOCvx5t41oZBzcM0Q7/SCEOl9jTY2kh2zPXnx25Odan7wIAX6vPrJ9lRznhd14h2v4u0n4MmNnt2I\nN2cLGcU7DSCEyAOwAMA/+JiUUgJ4FsBJkV4rpZVo2/H97wMLFwKf+Yw6NmoUve4Xv6AUbnY6y8pU\nhEvH7t3q/n/9F3DuuXTfr+K9bbA35M9+ppRiwNpcRofuzOpgUtvfD9x5JxFenkz0+vVYsXs3dV23\nw4l4jxun7nPDNYCMq6UF+O1v6f8LL6Rbpz2+I2HfPuDXvw53lFnx1lPNAeBb3wKuugr4xCfUsepq\n+q5ef12NA6DJwel7N4t36pGfTw5XOi/k2YBEKd48VyVrUX33XSoDEULN21IS8eYmjoDakujQIaui\nlqidFQxiw/btRGgLC62klgMnublk//w7ca2111RzDrToXbLd8L73UXO1s86i/8vKaA3lNVAn3kzI\nx461kkRuzsbXHo9bSlUTPtRTzZ96Crj6ahI6iosV8d63j+x3/HjrtdDQoAL7OvHma8SJeHMJAwsu\nBslDTk56kyl99x8vW/gCqgcKE++gs6V4jF5TzTlTxC4C2ol3rL8Ln9/LvNvfT893Cxz099M6PGJE\n+l8rTsg64g2gCkAOgIO24wcB1IQ/XaG/nwzDDe95DxEu3hcUUOnShw8D112njusOnA5OiztwAHj0\nUUX0I12MW7eGG82uXUTmuMaE4ZZq7raIcKr5//wP1U/feKN6LF7Fu7ubmqBNmhQ+MTkR7+JiagD3\n7LPKEQEoOLBrF/DDHwIf+5j6/v0q3ldeSc3lHnvMetypxhugTub33qt+G8D62593nrrPSrgdhnin\nHvn5mZmOlGmw13DFQ7xLSsjugl5UW1qAf/1L9XDgTKXmZpqLdeLd3W2tJ3aLxBskFxs2qIaguvK5\nfz/9fkJYCWx9PZEwPymPXn5vXuuXLAE+/3m6z2vK2rU0Fj04sG0bvWbMGHVuJt6lpfRZ9N4h3EQu\nFuLNaxOv/5k+F95yC91+97t0y+m7//433XLD2sJCmpc42AJY/Rq+RpyId2MjHTdrd/KR7mSKs2AA\nb1vJ8muqq9V6kgzi7TVTp7ubnj9+fLhfbU81j3XcnN3jRWRsbqYMRTfFu62N5k4eU6bNZ7mpHkAS\nIQBETAp85pnlaGkpwwUXqGPLli3DsmXLXF/DNb4zZ6r0MoAcuIEBcgD0ifvAASL39vpmNyfg0CEi\ngAsWAG+8oY4fPuy8ILg1V2OH0UnxbmwEvvMdYPlya211YaEipbGAU8EAygi44Qb1f0+PldAy9O9Q\nH+PmzfR8XmgB/8R70ya6/dKXKE1cVxkA5RBFwuLFROBPOMGams61/na4Ee+VK1di5cqVlmPtTrUJ\nBnGDCZxJNQ8W9fU0HyZC8eZ5KkjF+8gRavDY3Az8+Md0rLyc5mDe0lAnRT09Kg145Eg1pxrinRr0\n9wNnngn8859UGgYo4t3cTM6ZHqTVife556q+HZEcwO5uOpdTyYEdnOH28Y+rgDorzG+8ER4c2LyZ\nbseOJZvJyaF1nckgYFXTdPLc3U2fX0pvfUMaG60d3tOZ1HhBezut45x1Vl1N38OaNfR/XR3dckbf\njh3AGWfQMSbefX1kz26KN2c6mL4syUe6B8p14h2psa4OVqB53gmqcbH9/bwo3rze6f0S9C0PAZXN\nFsu63tVFNqsT70jj4QaVtbXq+9Ln3UTVnacK2Ui8mwH0AxhlOz4S4Sq4Be973wq88sp8PPGE9zcr\nLVXNUHTwgtveHk68R40KT2l3iwK99Rbdrl1L6WoTJ9L/3d3hijHgXuPd0UELiJ0AHn883fb0WEkt\nQAsU16ZFw8GDwCOPANdcoxxvNo5zz6U0/U9+UpFVJ8XbDRdcQI7xNdeQ4TLciHdvL3DTTaSO89Zw\nADlin/88pZv/6Efq8/b2kvF6WWBDIeC++8KPsyM+MGDNmujspHPbgwxOAZ1169ZhAe9fZ5AwDB9u\nUs2TAa6tzBTivWEDvdcnP6n6OPC8vXYt3U6caJ1n2EGZOFHNs4Z4pwYdHUS6R48msgsop3H9erod\nP55umXgPDCiyJUT0zvRbt9LttGnRibfeQI3BSuwbb9B1BqgA79q1NIYpU+i2ooLWqL171TqnBwx4\nm7LRo1UA6OhRb+soq/bsd2T6XMhbCTFyc4l8/+MfZMMccOEeNtu303ahgCLeDQ0q44DnLN2XYOJt\nkHyku+Ld0KAaKXtNNWey7mXeiRfcuHHMGLKNnJzIY+TS1cmTrVlDAM07HDCIVfHm8hmvijeLZNOn\nKxKuj18n3ul+rTgh61LNpZR9ANYCOIuPCSHE4P+vRHqt3lzNDyoqwhtz6cRbR2treHo4oIiZfVF/\n+226LSgA7r9fHe/uVo6Ajro6Intf+ALw5pvq+NGj9B52cnnGGcBtt1Gk2L5thp8a76uuIlL7pz+p\nY2wct99ORnPXXeoxP8T71FMpAPHTn1qPuxHve+8Fbr2VFHz9/Xp6SFH/whcotZ4nlt5eNRnEipEj\nyal78klrqj/vu2qi5qkDK96Z7mymM9rb6Vqvq4ufeO/bp+oxgyTebP///d9q3ufU4DVryGnnRlY5\nOTQX7tihGrGZVPPUgrOJHnxQXS86qQVU4LWggOb/ffvoeuJ+IsOHR3YAOWtr2jRaI0Ih9zVRb6DG\n0LePXLiQbpmMv/AClWKxCl1VRWvm5s2q9EEn3nrQx++1x05/NhFvu79SU0PHZ85U621lJQVhenpU\nxgETbw6qTJ6syhF0FU5XNQ2Si3QmUwMDRFQnT6b//aSa6+npQRLvd9+loJK+644b8d6yhRo0jxxJ\nNjRsGK27PL/u2qUEv1gVb26AOX68txrvjRtpji4pcZ7r9MyzTEw1zzriPYj/AfBpIcTHhBDTAdwJ\noBDAfZFexNuJJQK8T/azz1qJWE+PM2EuK6OJn7e2YTQ00EV/2WWkKDPciPcpp9Dtz39OtWZsbJHI\n5Q03ACeeGH7crcb7K18h1VgH164/9JA61tJCRnHccaQo6eP3Q7wBaqKSa8vPcNtOjB2U555T372+\nZdhnPkNO99NP07G+vviJN0+oF15Iaexc78fE2yB14Bpvk2oeHFiN0xXvWB2LbduUkxzkosrEW1fO\nOGC6Zo01W4ZTVrdvV466Id6phb1LMKDI2Nq19FuyYsnNLzm9mzO9uDO9E7Zto50+amqIFPNv7vZ7\n69vgMfReJSefTLclJXS+AwfU1p0ABXMOHqT35fHl59P7SUnrGjeR83vtNTYqtS3dO0Z7QVdXeGkY\nr8F60lhFBW3bCigSwr/hpk00V7kRqJ07rQ1fDZKHdA6U799Pc4luo14U7717VQlJ0Ir3hg10q4/R\nbZ47/njy2z/wATU/6CWreqZtrM3V3nyT5sXx4yOnmg8MAF/+Mgln8+fTMSc/f/t2sv/q6vQO0rgh\nK4m3lPJhAF8GcDOANwHMBnCOlLIp0utiVbydMGEC3X7xi9bu1261zUJQGgY7sIzOTjKCc8+lKBAT\nXDcCP3o0NUi74w5Ko1y1io6z4u0HTop3by8pz9deqxRtgKL9+fmU+sdGwFt1CEGNyNauVQTYL/F2\ngltX84YGcmx6e6lxEmDdMmzCBHLseUHu7VVkIVYsXkzK2dKldF5OlTHEO/EQQnxWCLFTCNEthFgj\nhHDoDKBgUs2DB6f2sjIIxBYZP3aMIuw68Q5a8daVMyZNW7cCc+eq41VVNJ++/bbVgQcM8U4U/No1\nE28novvWWxSs1ZXP1laal4cPV+uzmwPc3k4B43vugaXnSyTizde7fS358Y9ph4yZM9UxTkc/9VR1\nbMQI4JVX6Dx8jVVU0LzV1UUqFivoejM2L9ixQ9U9x7MlUDqgr4/+7MT7fe+j24svVsc4u6CqSv3m\n5eXkh2zYQN8nB/R1VXBggJRAJi4GscOvXQPpTaZ4reNrw4vi3dkJ7NnjLeAXDwYGqJ/SzTfTWswC\noFtwoLGRXjNvnupzAijiLSWthZMm0fG8PH8Bg2PHaDyPP07vwWn2gPN5Nm+mbFQA+OhH1dgB67yr\nB8CN4p1GkFL+Sko5QUpZIKU8SUr5RrTXJFLxLi6mi+397yfVm1MtItVkjR0L/P3vVvLd1UXn4gX6\n9dfp1q3GG6D65s98hqJrr7yi3tcv8XZyMvT09eeeo9veXqon+X//j+ruWFXgffYAFYXmSSsRxHv4\ncBqjvanZwYPAaafRYvvqq3TMvmXYySdTB3Uef7yKdyhEUbpHH6VzPfssHefAiUFiIIS4DMBPAdwI\nYB6AtwCsEkJUub3GpJoHjzfeoKg4bzkCxObcb9lCizWn2gbloAAqG0ZXJfX6XM4eAmguqa+nrsnc\nANIQ78QhFrvmZmY68c7JUb8L12AC9Ps1NdF1OmuWWufdiPcLL9DtRRdZe58UFkYn3va15CtfoS7c\nerkRr4fnn6+OjRhBQadQSKWl8/rZ0kJrGR/3c+3xdmasrged5ho02G7txPtrXwNWrwZOP10d42DH\nnDnq+x87luaUp59W3ydg3QJ2927yUXgeMogNsdg1QDaQbsS7sZECYl/9KmVCsArshXizT8wBtaAU\n72eeAa6/nsjyRz6ijrsRbx7XQw9ZGy8z8d63j4Qsnq/87nT06KM0ntdfBy69lI5FIt7sr69erQJo\nTnPd1q0qUyUTm6tlLfGOBYkk3gBFyrlxNV9Qboo3QMb89tvAOeeotFhWTEePpuj3O+/QcbdUcx2L\nFyuiHgu5dFK89+yh28pK4OWX6T7XW/Ce5OvW0e2hQ8opmjqV3p9r1hNBvIWgiez5562kirs5Llyo\nav30VHMeDwdDEpFqzigsJKVF/5zRficDX1gO4NdSygeklJsBXAvgCICPu73AdDUPBlJSNs+nPgX8\n5S+KqMZCvP/2N5pb/vUvWki59MVrGl8s6Ooie9WbIQ4frhSw979fHa+qoqBoTw9tKwkY4p1g+Lbr\nri767ewZRfx7nH22OlZdTcT7xRcpKMtwI6GcNv7gg9ZgTEGBu8rspng74Wc/o+tdTzVnx3fuXBWs\nZeL9zjtEynnXES97ijM2bLDWewad5ho03Ih3KETfjx7guOQSuv3yl9Uxbly3e7dK/wdUVgQAvPQS\n3XK6q0HM8G3XQHqqmKtWUcbMhg3AFVeo6yzSGvXqqzQvvPQSzTVB2yBnxP7xj8DXv66OuwUHeC6z\ni0NMvDkrlNfjoiLvWTYAvT4nh0pfuQFmJOK9cycJhrod5+WRbfN3fOwYfa+8DqdzdoQbDPHWkGji\nDdDCOWmSIoCRFO+bb6a9qjdtUs9nxVsIit76Id7HHafqneNJNdcv6rY2Gsvppyv1mrfVmTyZPiuT\nTn2MeXkUIdy5k87X3x8/8QYofe7JJwG9QTh3I501i9LzAZWWyKk3kyaRitDenphUcx1Tp6qmPIkk\n9UMdQog8AAsA/IOPSSklgGcBnOT2uvx8k2oeBDo7Kavn7rvpev/EJ+i4X+L97rtUojFjBjVgPO00\n5VT7jbA7oavLeacHpwZNADkLjz+u9jwGiBS1tdH8YRTvxCJWu+7sJJUyZPNiHnqImoaedZY6Vl1N\n2Vq7d6uUZMDdAe7sJF/AvkbFkmruhPLy8PphVr/PO08dY+J9//00Hv5Mka69a66hUjDuM/K3v1Fw\ngksnMoV4P/20yjzQ4VQi4oaxY8mvW7rUeoyxZIm6rxNvTo01Xc1jR6x2DaQnmVq9msoV/vAHaxaM\nG6l9/HEikN/4Br3mzDNVwCyorJPWVrL1iy+29kRyCw4widazvgBFvB98kEg3N4z003AZoHn05JOp\n8TLzj1CI5i/2ye3jsQfUuPEhz3UvvURj4+0B0zFIEw2+ibcQ4n0RHrsmvuGkFv394Yt4IuCVAE+Y\nQGkZoRClNALWGuGJE5Xi7EUxnjBBdXGNRfGeP58WralTlVPR1kbOzty5imBzBLq4mMj3rl1qjHpw\nYPRoakzBE0AiiPctt9A4//QnZchdXeQgT55M31dfX/h7cs3Kjh2JSTXXoRPvRJ87SGSAbVcByEH4\ntoAHAdSEP52Qk2NSzYMAZ7p88YuU2cMLYShEf16JN6tLhw/TvKdH6hNBvGfMUA64DqcGTQA5S3pd\nL6AcjyVLlEOTKcQ7W+3aLXCybBn1GtHXclaTCwqshNytlMFtN4poxDsnJ/YdLE4/ncq3vvlNdYxr\nlB99lAIG/L9bjbeUFLz69a+B//s/Cor/+teUmcJ+RyYQ795eCkC8973hO8O4Kd5usP8eo0ZRwH7J\nEpUuDCji/fbb5E/w9m/pimy1ayA9U83b2shv/PCHrcE1N1LL5YY/+QkptF/8onosKBtsbVVzhA63\nMfJcZhfxSkqoyeOqVcCVV6rjhYXWZtHR4NbjiLdOdBqPk6BYUkJlIN3dFMg4/nilwqdjkCYaYqGZ\nfxNC/HgwmgUAEEJUCyGeBPDDxA0t+ejtTbziDVAnP6+EuaCA6op4/25WvAFKweD98Lwo3hMmENnY\nvz82xXvBAgoa7NxJkS+AjKWigo43N5Nh8eJfVETvuXOn8xhHj6ZUmEQS7xNOIIWD00+kpImhsJAm\nyf5+qpnv6aHflp1m3uezoSHxqvT48eTwHD2aWcQbmWvbAoB0fVBkZh1QuoOJ96c+Rf0ddPipzW5v\npznurbeoBldP8Y431XznTrL/9nZKv9Ohz63RcN11VAKkBwVCIZpT0514I0vt+tgx75lKXOu7dKlV\n3eFGW3a4OYyRHM++vvgzp973Pus6rY+BM0oA96AP1ygDlA47fjytQTffrI4H2TchUdB7yehjB/wT\nbztyckgc4MazjMpKWrevuoqCdfr3nabISrsGUhsol5LKiuzvb987nuGmeB86RGrvL35BgRw9uyJe\nG+zspHIVLpdksH/uNMZIxNvui48aRT2QcnKsa7tbqnl3N/U4ss+lbvOonl1iP48Trxk3jrKVrriC\ngvP33KMCal63c0sn5EZ/ShjOAPA7AO8XQlwOYCKAewBsBjA3wuvSHkePBkO86+qU0+eFAE+dqhRy\nvTnXmDFEXAcGvBFvTmXbuzc2AhgKUbOj2bMpzeaqq2gyqaigBR0gY9CbFE2cSNF5gMaop2qNGUPb\n9PAE4DcQ4IbJk4lYbdtGaaoDAzRBcDR7587wgIfetCbRqeb8mZua6Nx68580xxlIb9tuBtAPwL67\n6kiER9X/g+XLl6OxsQyPPKJKD5YtW4Zlen2CQUTcfjulfT76qFrwuKmhUzpmSYlzKtnvfkdOrb7l\nT3s7ZdHMnh3+/HgVb1bLqquBb3+bmmVx8M1NMXVCTQ2l7NpRUUF2zqRr5cqVWMmNPf4zhvbwFyYX\nZyAL7frZZ5fj0KEyS3aCm12fdRbwj39Q+ZHlDUaqAJIOt6DMuHFUYvWjH5GT+a1vqeclgnjbIYQa\nu747ihvx5sD8s8/SetjZCVx+uQo0A5mhePMuJNddR/Whl12majp57PH4D05ZCZWVajeSNWvCz5+G\ntn0GstCuAaChYTmeeKLsP9mTQPLW7NWrKcj6la9YO30fPmwtP2K4kdpDhyjT5nOfC38sXht8/HFg\n+XLKFmN/G3BXvKuqwpsQA0SiCwrC7WHxYiohO+ssK5Hn5pIDA9aMop//nJTo9nYql2V0dlqzShiV\nlf4U7wkTiGwDwJ//rHpdAPH7CKmwa9/EW0q5WggxB8CvAawDqebfBnDbYP1GxiIWVdgL6uqI4B05\n4i1FfMwYlX7Z1aUiRmPG0OLe3OyNeOvkMp7PtnAhKVGAiqjpxFtXvMeOpef09ISnmtfWUmdgnnAS\npQTn5tJ4tm2zBgE4PbSxMby2nvdCbW5OvCrN+4k2NmaW4p3uti2l7BNCrAVwFoAnAEAIIQb//7nb\n61asWIGrr56P004DfvnL5Iw1myClSpN77TWV4nXwIAUqnRZ6vUMw49gx4GMfo/tHjyq7YOLthIIC\n5wXaCa+9Rlsd3nWXOh8vyD/9Kb33739PAURAOR3xYOpUUjR++1uq43NyDtetW4cFeqQhychWuz7t\ntBV45535eOIJb+9z5pnhx0aNUiVTOtyUmmnTgPvuox4soRBlTN13Hz0WBPEGSH3r6LCuX25bae7b\nR7eTJllT6nWkG/G++26yoX/9SwWpee64+Wb6rq+4goKmeuZSbiyyUQTwFoZLlqg5Tke62Xa22jUA\n1NWtwCmnzMdddwU/Tju4OfDDDwO33aZIqVP9MeC+R/ahQ6qk0Y54a7y5idrTT1vnKjfiXVfnPM+5\n8YjzzqPSMbu/xNlCPT3WzCE+9yOPkPLN35nbrj4VFf4Ub97//MILgQ99KHxM3d3kp8RS5pMKu461\nonkagIUA9gE4Nvh/YcRXZAB6e2Ovz4oEjpJ5JcB6Srleh6gTOi8Eng2QVd1YCeC0aSqlhYl3bS0t\nfKx4C0Gfiz9rU1O4EVVU0OTFRD2RTsqUKZQloAcBiorIKPn7sn/vVVX03SQ61ZwVQCbeQThjASLd\nbft/AHxaCPExIcR0AHeCxndfpBelm7OZrpCSHA7dodeDv3/+s7rPuxY49cUoLQ2vzeRyG4CcbP38\nbsTbT6r55z9PY3/kEXWMP8fJJ5Mzceed6rFEEKXaWpoTJ0+2dr9OQ2SdXftJNXcDK95796pmZIA7\n8Z4+nW6vvpr2m/3971Vz0aDm+lAoPGsqFCLbsKd9NjfTbaSmYOm2ndjXv06O+2OPqWNMvCsqgDvu\noO2DODU8KOJ9+eU0P9x9d2LPGzCyzq6B5KWaP/00rRk6mETu2UMZnwy3VPPycvIj7Th0yH1d8+OP\n/O53dG3q81N9vVJ69cCjG9EdN44+yyc+oRo3AzR/2BurAbSW/fOf4YEDfq593mlrI3vcsUP1N+Lx\nuKWa79xJyr3eC8aNeF94ITWf/MUvwh8rKKBrJZbtS1OFWJqr/TeA1QCeATATwCLQ/nxvCyEidipM\nd/T2BtNcTVeevSre/Fw9ssQpH21t3gh8Xh45wPEq3uPGkXPc2UkLYmkpTYzV1UQuORIohCLejY3h\ne43zJMTOQSKdlNGjSX2w783LY3T63keMUIp3EKnmjY2Z1dU8E2xbSvkwgC8DuBnAmwBmAzhHStkU\n6XXp5mymK958k9I6r75aHeO0z5oaUt8YkeaUsrJw4r1tm7rPjWcAmlMiKd5OaWTf+154zTY7A3/5\nizqmN49Ztoz6QHBqcSKI2xVXEKn/4x/VvqLphmy160QR75YWUoR+8hN13M1hPO886ily553kDA8M\nkPMOJH+ud9rajJW3SD5GKoOQl12mMgQYXN6n11x3dBCByMmhjLvJk4Mn3qEQdYS3d5tPV2SrXQPJ\n68ny4Q/TNcn7WQMUSHvve8mGnnpKHefeQXboTYx16Nvp2uGnxvtjH6PmpZx1ChDxXryYmhzra3Jv\nr/OazNf0PffQ+ZjEe8mc1cGBB3ufi9ZW2rovP9+6/rrNoyNGUFnHhRda0/ndAgFnnEG7F+k7EjAy\npcmpjlho5hcAXCil/LyUskdKuQHAewA8BuD5RA7ODiHEN4QQLwshDgshHBIVACHEOCHEXwaf0yCE\nuE0I4elz9vQEQ7xZeW5t9UaAuR5r715a2HkRZeJ96JC7gdkxYkT8irdeK65H/XhvVH1C0hVve6o5\nT0KsECSa7HIQAFBj5ONO27hVVQWTaj58OE02XOOdKcQbKbRtP5BS/kpKOUFKWSClPElK+Ua012RC\nQ6Fko7WV6tj0BYt3U3j2WbU4M/H+4AepARpv5xPp2nYi3rt3U3Dukkus2wRFSzW3L6j9/VSvfckl\nVjWc55WXXrI6FnyeU0+l+6+9RrfHjsXvvJ9/PvDyy6prdpoiK+06EcT7xBOp50BeHpUj8HXj1vE+\nL48COMOG0Vo3ZYpqBBZUqrkbJk6ka0+v3eQ+NZF61SSLeHM/GkZzM6mLV1+t1Mz+frLbykqaE/j7\n5wA/45RT6LMCwRHvDERW2jVA12+ir9Err6SSIDUutX7o/TsOHya/8dRTreuUW6r5hAl0TX7pS1ZC\nGo142z/fsWNEpm+7TR3TVVx9jPX1lG115pnA88+r425r8tlnA1/7GmWPbNyoguB+iXckxXvMGLUz\nA0DfrxvxvvZa4NxzKYPo/vvVcb/jiTQmJ3Cz5VQjFpo5S0r5V/2AlLJPSnkDgCUur0kU8gA8DOB/\nnR4cJNhPg2rXFwO4EsBVoGhbVCRL8Y5GmPn5XMfBhJGNuK3NO6Fj4h2v4g2EE++RIxXx1sk4oFLN\nk6V4c8qgXfFm4u30vZeX0wIfBDnmGtcMI96ptO1AMdQV74EBtdsAY8UKIhu//706xml2LS1ElAFF\nvM89lxYuJhrRFG97jXdXF9nlyScTgWfn22+quZ7KxmlzAwM053zoQzS/cFMenXjX1dH8xK9JBPHO\nEGSlXSfi95s1C9iwgVIeDx5UTU29BrZnz1Y2k2ziPX06KXLz5ikH3cs6n4wgZFMTOeI33qiOrVmj\n7nMTs9ZWst0PfpAy1urr6bideM+dS6+R0hBvDVlp1wDN1362rbKgSRcvAAAgAElEQVTj73+3pn+3\ntgIPPEBbxPG609Ki7uvXJgfdFixQ9d6Ae6o5Nw/7xS+o6SJA5+VtbZ3gRLx37qSMrK99TQWsmrS8\ngNdfV/e5yfHChZQSz31Q3PzNsjJqenbFFcRxOKDgpjC7gZ/rpHhXVNB3xsH7o0dVo2M7Jk8G/vpX\n6uGwZYviOrEQbz+K90c+Qn4AzzOpgm+aKaVsjvDYv9weSwSklN+VUt4OYL3LU84BMB3AR6SU66WU\nq0DNJj4rhIg6TR89GgzxLi2l87Li7bU2m+u8+fnDh9NF1tpKi49X4t3aGh8B5NrFxsZwks0qMxtk\nQQE97lTjzYGDoIh3V5c6N49xxAjV7M3+vRcX02uCcJhKSzOPeKfStoPGUFK89Ug+45ZbqF5Lj/Zy\n6tpfNdetuZm2CgTUloasXL/nPTSPcVpepGuba7z1ujRWDGbOpLmBAwFuDg3grHjrdXerV9MtO/Dc\nQGvDBrrt7lb9J4SgBZ9JeV/f0HDes9Wu+/sTN29zMy3OhvC6JkyfTvXHfl6TKCxfTo73gQOqdMMr\n8U5kELKtjYJpevMmLgPR1Sx2roVQRIfV+rPPptv1g56dnXhPmEC23NSkiHcQO9BkErLVrgHyJ512\nxXDC9u3WdaaxkbqSX3SROsbrBKDWL14HTj5ZkUVA7Wgwbx6lkLe0qG1qndapqVMpeL10qUpNZ1/D\njUQ6CQEcjAKAd95RnwWgLTb12uyjR+ncJ5xA//N6F83fLC2lQAG/l1+iy02VFy1SQUopaQ6orKQA\n2YEDaqcPIPJ4uH+Zvl4nSvH+zW/oGtCvDS4L0ksIUoEAaGZKsRjAetuEtApAGYATor04KOIdCtFF\n2dhIi0a0hdGNeANEXtkYvRC6khKaSOJRvPPzaSJqbnZPNdcnpPJyisjZU81Z1Qoq1RxQkykbIxOA\nSMQ7CHKcicQ7m5GtzdV0BYjxgx+E13/+4Q/WW0ARan3P3I4OaqZYVqYWQ1a8R44k8s6OS6Q5paqK\nnIf3vlctfFySYncWIp3HiXjzuOfMUdvD8Zwybx7ZHjsubPfcNHPCBDVHJCJV2SB1SOTvV1lJ1yw3\nEfVKoseMIaV2YCD5xHvhQgoUVFYqpzxo4n3wIJVXMIkGqPnT6tXAd7+rjvHj+/cr++XU28mTld1y\noHzRIpobeE7o6LCmqLKquGuXUbyHAoqKVEmTDntAef9+Kvf4xjfUMU7JfvFFtfY0NKjHObjGxP70\n0ymYy9cpbzPJXe537SJ7GRhwVoeFICX1Qx+i4NORI4p4u/l+w4eHE8UtWxT/YKWd+5GcfjrZFH8n\nvK5Nm0bvz2uylz4Tkyerec4v0a2spKAGoL7zri4KgpaXq6A9f2dA5PHU1amtgGMZD+CueH/609QM\nloN5Uqoxvfqqv/dINLKNeNcgfH/Ag9pjEREU8QbIkWXCHE3xLimhi9Geag5QOgcboxdCxxNYvASw\nqoqc2yNHVNdE/Zg+IZWV0YIqpXXsHMEOQvHmFHfunMyBACbATpkGySDemdRcLZuRLanmdpL93e+S\nvTE5BmhPTcDafIwXJb1BS2cn2fCuXYrMdnbStTtjhoqKHzpEi9uwYRTdZ4Uvkt1cey2pgS++qNLa\nOEBXU0OvY1v1Qrz1z93eTrY8a5ZKO2cnqqyMHCZW0+0L+fjxKoV+CKWaZyUSHTjRrw2va0JtLY2j\nuTn5xBsgp/uEE7wFsRheifeePdSIib8TgGq0//IXShFlcJBrvZaHyGUmAwNqbFxSMn26Igqcslpc\nTEExfq/ubqtPwUqbId5DA06K97ZtNJf/4AfqGGd68B7PgAqsAup6amsjv3riRBX0YeI7ezb5qrwe\ncar5hAn0/86d4SWMTpgzhwjo1q3R95qvq6Ox6Wpsaytd53V1al3jgPIpp6jvAFDEe/hw2u2IRTov\n85ZOvGMR5P78Z+oNwz0Z9L5KdXV0f88epXhHmhNzc+l7jod482+iE2+9zO2f/6Tb9naVKbDeLWc6\nSUg58RZC3CqEGIjw1y+EmJqAt4q6r2FQNd4AObNsRNEudCEosuREvHUC78UxKC6mSSPePcqrqtSW\nK/Y0brviXVamIoy6EeXmkpFw7U0inRTOEti3j74//s64yZNTjXeyUs2NqpZ6ZFqqeWsr8LOfWZsT\n3XILfQ69A+vdd9PCx9t8cUMTILwmDAh3jjnVi9PGOMVzwgTliOhdx0ePVvVRkeaUkSPJ4S4oUNF7\nTjUPhag7Ke85rO/pbcf8+eTMjBmjHG4ez/TpykHhRTc/n3pScEq9vc/E2LHkpHCmgHHeMxdBEG++\n5r2uCdwItb4+NcQbAI4/3lsWCsMpCLl3L80FTz6pjv3pT6Rm6ySbG5zpATwO2m3bpghKRwcRGkAR\nHSbe06apchFWMAsKyG7dgnHl5WSrzc00HwgRnK9mkHo4Ee9XXqHb3/xGHeMUcc68BMi/ZH+QH+dt\ncKdMUaSTCeOMGXTLhJ1TzSsriazr6m0k22LSuXev8jXcnj9lCtkIl3MBau2dNk3Zc1cXXedsSxz0\n1jM49e2HvRDv8ePV+hjLHJqfT43n6uuJo7AN5+fTd1ZYSHbsRfEGrAE3L7s+2cEcQ88g0DNyeP5h\nTnL22eSbpHKn+3SYun4Cqst2+zsewA6P52oAMMp2jP+3K+FhOHZsOV599QJccIH6W7lypce3jgzu\ncg14u7AqK51TzUtK1MbzXoh0olRdVsYARbIrK8lwDx60Eu/SUqXK26NXRUVqoU6k08sd3/ftI8Pn\n1FImwHYHHFBBiVSkmq9cudJynV1wwQVYvnx5Ygdh8B+kk+L91ltWBfftt0lZYiIKAN/6FtVw6o7w\nH/9IiwXXJ/X3q+wRTp87fFiRUF7UBwboWpw7lxxebiijO8esEHOKp528sh3X1iriHc1uQiFyalgR\n0wN0Y8eq80ciCwsXkmPR2Kj2+W1vJ/saP56crO5uaxM1/dz2CPqIEUSQjhwZOjXe2YpEB0504ueV\nRNfW0u2BA6kj3mPGKEczVsX7wQcpQMbZMoAqQdHTMvl91q9XitahQ2SLUqosmfZ2+m5GjlR+A+9r\nzI6/lOHND9lu7XMLixHc38bYbXbDiXgzid69Wymazc20pkipgsrNzZQNVVSkSDY3I9PVXiZqU6dS\nv4CdO2mt5KxOIVSA2AuJHDWKrss9e7wRb4BKo5gQcgfwKVNUIJwzPyoryX9l+4uHeFdX0/fR1xf7\nGsj7e+/ZYyXeQpAde1W8AZoj2I+JZQ51Urz5+3jPexTxZr/lpJPIF2EelQqknHhLKVuklFui/Hnd\n0W81gFlCCH1zlyUA2gFsjP7yFTjllCfwxBPqb9myZb4/kxNKStTF5YUw64q37jiWlCjF2E+qebyK\n94gRKiqlE29AkV1GWZki3nayqxPvRDopJSU0ee7dGx4E6O+niKfTWDgbINnEe9myZZbr7IknnsCK\nFSsSOwiD/yAZivf+/da6tKNHqQ5Kr6F+7TUiwD/8oTr2u9/R389+Zn0eQN2WAXIs2P5YdeLdCkpL\n1XtwNswZZ1ij5gMDlAp37BjNK6yMT5pEdsDEm1PNx40jux4YsC7ytbVk2wMD3uYUXZXWtx3k8wOR\nO0iHQvS8CROUysbKGauNeh0pK2duxFvf2tHUeGc2Ev37VVertdWrA8jXE2/xmYrrqbZWNR2Ltas5\nO/qvvqqUIJ4/NmxQJKWpieaR3l71mkOHKDMFUCRbz5zheUu3295eskG22+HDrXbrtG4a4j10wH6r\nrkru3k0kTQ/wNDcTkQIUoW5uJqFI7+fBivfEiWqtO3KErqOCArom9+4N3462qormBC8kMidHBX2j\nEe8TTqA94wG1HRjbjB5I4zJOIahEq76ePr9eOhkL8QbIlmINFrK6v3u3lXgDikh7Jd7cK2pggP78\n2jb/VhdfrL43vj3jDJXGzll/c+bQbSq3FUs58faDwT265wAYDyBHCDFn8I+p1t9BBPt3QojZQohz\nANwC4JdSyj6X01oQVPqSTry9Kt5OqeZ+ibeu6iYi1RwIJ97793tXvAsLlQEk0knhiLhTEAAgQuKU\nag7QeBLtMJWU0GQ/MGBqvNMBfhoK2VOQDhxQZJfxi1/QXtKM7m5adOfOVceefx649VZaEBgPP0y3\njzyijnFKuL4fJ9sPq9bNzXSdjhmjiCzPJyedpJxgJt6LFtH97m4V6Jo1i2737KHj/f1KOdbTylnx\n7uujBdFOvLmm1csir6em6/ugVlerPhBeyIJex8qp5mPG0P8HDliJd22tqueyE2/OjDEOfOYj0cSb\niZ2U3h3SwkJyuFPZz6O2lsZ88GDsxHv7drLxzk7ld7S0KFLDZKWpiVQkwLrdIAfw9HmE5xZ+bXs7\npYxzwIztdvhw8rt4TnAL6lVW0ppq7Db7UViormnGoUPhpVHNzUSmR4xQJDsS8R49mq7xI0esvYl4\na1wOnOvE2w+J5PUumkKekwPceSfZBzdGZJsZPZre075+cbYZ2y6vyVVVNG/199NftDmoqkp9T7HO\noWVl9GdXvAE1j3pNNefvmLMAY0l9/9Sn6D5n7LS10fd23HF0DfX2qlIELi3guSoVyCjiDdqPex2A\nGwEUD95fB2ABAEgpBwCcD6AfwCsAHgBw3+DzPSFI4u21xhugicRuYACRRb+K9+HDZBzxpprr5wQU\n8QbCyS5PYE4qcxDEWx+PPQgAUDqPfSsIJt6trYl3mIqL1d6KhninHk6p5k1NwFe/at3f+rHHaBHW\nt8a58EKqaWJVubsbuP564HvfU9FUbuCxfbsKUHFN2u7d6lpglXfTJjWezZvp2l2/nhZOKYk0T5lC\nZLO/X6WjnXkmvSeTX0CR7K4uRbwXLqTbPXuUvenEm1P1SkspRY53XOjupmO8S0BTkzW6bj8ebS6r\nraWx27dj4cWZHZpo5zn+eBVwiKZ466p2NMXbOPCZi0QT7xEjyNY6O72XHwmhds5IVao5p7s3NHiz\nyTFjaA7ZqOUA7twJfOADdJ/VxLY2NY9s307fd0sLpceGQtYU8vJy1TAKsKp3HHjjEhF7wIztc8QI\nVRZjFO+hDfYna2vV2tnWRkR1xIjI6nZzMz1Hb5bI1yhvjXvwoDPx5nWEj48YQde8VxLJwaFoijdj\n1ixlb7rNAGQf+hiZeNuJbnk5vaeX7bsA5cvzll+x2hIr7W7E24/izdl7Xp7vhDvvBC6/XDXb0wUE\nKel76+qigEddHb2HUbw9Qkp5tZQyx+HvBe05e6WU50spi6WUo6SUXxsk5J4QZHM1vhC9Kt4Mu+LN\nipxXxZv39Y1X8baPTR+jE9kFnGu82VCDIt56EIDH4rQVBBNvKRNPjvXPaYh36uGk8txzD/DjHwNf\n/rI69tOf0sL9y1/S/93dSpF+4gm61RsL8dYleidVfv7GjUQOpVRE/sABitD39dHjAwO0AJ5+Oi3u\ne/aQg9rbS51Mjx6l13A90okn0mv37lXEmxWoXbtUcI9TP3fvVor3uHFkD/v2qfq5khJFvDlYVlxM\nDgdAC6I+d5SX0y2PMdq1XVNDzkNnpzXVnBdnrw4KKwmcIl9cTGMvKiLC0d1NYwmF1NijEW9T453Z\nCELxBvynYOo7WKSCeHMwrLHRG/E++WS6PeEENYc0NQGLF5P9bN9O81JbG6lDBQWkMHLAf/Royu5x\nIt7szHJWCs8tgMp4YfLDJEIn3oBywp0Ub0O8hwYWLgQ+8xm6/49/0C3XaU+apILlTLz1rK3OTrr2\namqUYt7VResFX3sNDVZSW12t7AdQ155fxdvvusbNPnncJSXugSn+POxX8rkrKujzcZq8H8U7njmL\ngxLRFG8vxLu/X80TsYyHG9Bt3ap8hNJS+n4B8nm4aR5n1/D7pQIZRbyTgSAVb4bXGm+GnXgzvCre\nfp7vBp148wJZWqq+L6f0bsCZeAOkFOTkxD4eJ3Aaqb3DOsNOvPX/E+0wJep7N0gMnBRvJs2rVtFj\n/f0qtZu3wGLnsryctsYCSJnOywNmzlTP372bou41NaqL94EDRKhzclRUe/9+4Kyz6P7WrbRADQyQ\nog5Q8zNeEPSUTibeM2fSbX09LZyhkDq2fz85vMXFRLL5eUy8y8pUZF9XvEeOVAoAQHahL856qjkT\nb65p9aJ4A8rR0RXvvj7v2Tu1tYrA289jJ9g8d3LjNX0OKiujucfUeGc+DPEm6MEwL8R73jzq7AsQ\nqentJad05EgiyvX1ZGcDA/SdcM0pz0H6sZ4een15uUoVB5R6N3Kk+j7ZFocNUxlhbnbrFNRjZc8Q\n7+xHYSFwxx0UpF6zho61tSnV+uBBuqa6usjv43UNUARr1CjVBZ9JdiTizWVVQDjx9koi/RJvvT6b\nbUZfe/UxVlTQuuukeAPedztin5htKR7i3drqTLz1uvho42G/Pd5tho87jr7DpqbwIAb332GxjX/v\nVMEQbxuSQbz9KN5CWBcZv8SbLzQgcYo3L5ShUHSya/+sPIkE4aBEUrztx+3/B6F4B3VuA/9wUrw3\nbSISfOQIEd7t20mV/ehHKa350CFVS3bRRSo1c88emtDnz1fEe88eirpPn662/Kivp2NTptB7SUnO\n6syZZJe7d6vJf+FCsvPt21WUXley2ek9/nh17uZmuuZ1cssLzvDhautBTjUvLycHpbHROdVcT9cu\nLyf7ZvXJiXh7aUqoq3E6gWdb5RT6aHOT7jDZnXU34s1OgU68c3LINjs7jQOf6Uj076cTv/5+72sU\nb1mZquuJVRy2yWi2lJsLPPMMzRvr16tU3spKlVnCxyoqyPZ4bgFUAM8+tzBJ6e8nJ1cvWXEiEWy3\nPCfomSpOc0tREZ3D2O3QweTJqtt4eztdN6NG0RrJ1yOT1aYmIsh9fXStjBxJr2ttVddeZSWtAfZU\ncyZidsJcUUHv4zV70W+q+Zgx6n05k0vvQ2K3mbY2d+LNfkO0MYZCqnldPFlfkRRv/TuINo8yp+E5\nJ9bxcKf4HTtUEKOsTG1DaIh3GiNdFG9ehKRUW2MBViLtl3gnSvHWwZ/Ljey6Kd5BEm+3tHc78dbH\nFiTxtr+vQTiEEN8QQrwshDgshHDc6GGwueJfBp/TIIS4TQjhyWKHDSNSPXYskeyODlqoLryQHl+/\nXpHsSy6h240badEfNoxqq1k93ruXFOUZM4igc8fx8ePVdiVMskePVs4DL5pjxqj6M45S19bS2Pbs\nUccmTaJ5YM8eWoRZVcrLo7Fw6l1+vtpJgBccQKVTtber7q284Oip5qxUcfORggKaBzlyraeaFxTQ\nubwq3uxEcKTeTry5/tMr8a6vJ2ckEvHm92TF26nPhHHgk4Mg7TrRijcHjNkh86t4pyqDQghF/v3s\nXjJzJm31x1knI0bQPHTggDPxtmfJ2Ik3O+I6IdIDb9ECZnqqudPcUlho7DZdEPR6zeC08o4OWlP1\n4LF9DdObo7HiDVhJNq9rTqS2vT2cRLJ/y4HvRCve3KeE17WiIvI3uImybh/l5fSZ7f2TeL3zqnjz\n52LiHeucpfsH+njKy1XAw8t49F5LQOzjcRIghFABQUO80xjppnhHOo/fVPN4FO/Jk52P8zndFO9U\nEG+d6ObmOqfD28cWZKq5/TswcEQegIcB/K/Tg4ML9tMAcgEsBnAlgKtADRejgusa9+8H7r1XNUVb\ntIiI8DvvEPHOzSWSLQSR6h07iCSfcAI9/913iQjX1ZFNdHTQ4sPEe8oUOjdHfGtrFcnmbsGjR4cT\n75Ej1f6XBw/SOLgDMKd5VlZatxXhJmOAVQXgOYLT77gGUwhnxbuy0tpBVneE7anmQtC52MmPNgfZ\nFXJdSQDUe0abm9iJYgdeb35jd+Bzc+lz2VNZGdxw0tR4JwWB2XWiiS5fU1ya4TUYqxPvVF1P5eXe\nFW/GpEnWMhZWvL0Qb86SsSveLS3q+ystVVsXccZLJOJdUEC/p1v/CLZbQ7zTAoGu1wze/ku/Hp0U\n7+pquvZ5PSkuVkEfJt728iSdeJeW0hrItsA25Jd4V1TQONguvNZb19db+xDxumYPDvDnAWJPNQfo\n++nqSlyquRDqPPw9e22ibFe84xlPTo6aq/i8TsSbMyRSBUO8bQiyuRrDb423jnhSzeNRdd3IIy+A\nbiqz0+IJJE/xBtQYU5Vqboh3dEgpvyulvB3AepennANgOoCPSCnXSylXAfg2gM8KIaK6YfPmUcfy\n976X6ho5Hfy446izKCveEyaQzYwfT93Gd+4kB3XqVHr+5s1K8ebUpk2baOFkMt7erra+YpK9a5eq\n5dIV76YmsoWyMkW8GxvJkQiFVOonE29AdQrXibfuHDsp3vw8PtbRQe87fLhauDntW4+wM8HWg4Xs\n5HtRvAsK6Dms9vN5eF5itS3aebg2u60tuuIN0DzZ2elMvAsLjQOfLARp14muqR42jBw3Jo5ez607\nsam6nmJRvLmxE9ugTrx1Mm4n3iUlKoDHznJZmeoKzw3WSksVWeDMFntzRd0+hVDfpdPnYMW7ry/x\n/WEM/CHo9ZoxdiytNRy05nruo0fVelpSoggsN10rLlbHGhrINvVrr6UlnHgD4TsP2dXYaH4in4fr\nlaPZIq/pvNuJfYxOmVxsS7yW8nuyHXuZt3h9jCf4XFlJv83hwzRGzsyNlXjHq3iHQqpfDTdXA6wZ\nfTw2voZSBUO8bUiG4u2F5LkRb79EOlGKN0B1YatWWY9x06h589QxXfHW0+SBYGu8eTFmdYzB75XM\nVHP9vQzxTggWA1gvpWzWjq0CUAbgBC8nuOgi4LLLaFuwt98mG6uspJRLJt6TJtFzp09XxHviRLKj\nujoi1Pv3E/HmLJB//Yui5ZxqDqhGbKx4d3SoGnFdBWeSLYTqzNrYqK5h3kLETrxjUbwBpUrpqVj8\nGC/ofL2ykmffEaGszHuNN0Dn5wZLdofGK/EOheh97Sp2RYVzEzVOpXNTvDll1TRXSzlituuensT+\nfkLQvO13u8v8fLKFY8dSRwhjUby5vpRJDfeLaGwkR5VT2LlJFe+Nm5enHFcm2ax4A6pkp6yM5hAh\nwucWJt72HgzFxe7buRUVkSp4+LAJmGUA4l6vAVVitHkz3ZaXq7WRs9Y41RxQzVCLiujay8lxJrV2\nNZnXTDvx9ksK9XUtJyf6fOBGvLlsQx+jPUDOxJsf96qy8zjjTTUvKyO/p7nZGpj3Ox7mKPEq3gBd\nG3qqOaDUbV3x/uY31fWTChjibYOdKCYKOvH2Qu653inSeZKpeAPUCXXJEuuxK66gW66vAKyKtx1B\nKt68hdKVV1qPuyne+vdhUs3THjUADtqOHdQe84TFi8lB/sMfSO0GSPHetQv497/DibedjP/zn/T6\nujq14D/3HD0eiXgDwOrV9Pxhw+hYezsp75wSV1dHpH7/fnWMay6jEW9dldKJt13xrqwkx7WpSdmp\nF+Jt31mhq8ub4g0QObanx7EtelUS9PPoKXlMOJwc+EjE2yjeaYOY7TrRxBuInXj39JDam2mKN0Bl\nNqWlNPbRo8m+Nm+mc4ZCNLdISb0reM7g+WnLFnqOvgUhq46860lZmSL3dru12yd3OwfC5wR+bUeH\nsdsMQELWa/YrWeBhxRtwJt664s1BZSdS65RqDkQn3l5JZGurNzssKSEbcQoOcHaXPdXcrngPH07n\ncLMbJyQi1VwPVuj+gV/FOyeHPmO8zdUAJUBESzUPiud5hSHeNiRD8Y7n+fpxLwajG0S8ircT7rsv\nfJsmXfG2g40yiIVz8WJyGpjoMOzOPkM3PtNcLfEQQtwqhBiI8NcvhJiagLeSXp84axY5etu3q7rt\n2bPpdudORZynTSOnsrOT7gNEvHmPbt6ua/JkIuN8rKyMJvoXX6RFv6BAXY+vvKKaqfCxN96wEu+B\nAQoAcFSfU81bWpyJNzsM+oKjp1ix4s02yc7xrl3hxJudY514c0dX+8J6+LA/xdsepQ+FyC7sNXWR\nUFGh0gv1dPiODmv6OaCUMzfizdslGQfeP9LJrhP9+xUV+VOOAEW8UxnIYVv1apOAIt6c/QOo+Wnj\nRuXos+q4ZYs1qAdQ4JD7R/Dcwoo3zy8VFeFzCwcK7M0Pi4vd5wReUw3xDgbpZNcMvvaYeHMGBmAl\n3pxtwYo3E6zKSrVmRFK8vRJvr4q3V+LNOwPxGPkadwpM8Ri5llvvu6IHDL02V4s31VwfTzzEG7Da\nfTzBVN5qTk81dyLeqUZGTV9CiPGgOpEzQVGz/QAeBPB9KWWf9rzZAH4JYBGARgC/lFL+2Mt7pAvx\nZlJoT5vWz+MlrS1IcsnntxtKpOZxQZNQp0jWjBlkjJGU50R/N7qBD2HF+ycA7o3ynB0ez9UAsmcd\nbB32yLoFy5cvR5kWDRo2DOjuXobFi5cBUFt0AUSuAZU9oR/jW4BqwQGq816zhhxR/p35GBP7mhp6\nz/37gTlz6BgT7y1b1LZhdXV0u2ePVfHu7aVAwQc/qM7X2KhSQflYSwvZnq5KdXfT+y4a/ObYwd61\nS80l/Hw3xdte411URAvZsWPeCbPTtmFFRf6Jt105KysjpbGlxRpwi1bjzY5Ooh34lStXYuXKlZZj\n7Vw0nD1IC7sGluPuu8vw7LPqyLJly7Bs2TKPbx2OwkL/Nd5MvO1bfyYTHGjym2oOEPHm7B9WGN95\nR5FwnXgzudYVbw7c2Yk3r4Hl5ZGJt71EhMtP0k3xHgK2nSZ2bV2zhQCefx4oKFiGnJxl/9kSbPt2\ntctGbi5dO6x4643UWE3Wj7W0kJ04pZqHQur68ttxm9+jpcW7T6mP0Z4REikd3r4m+1W89+yJL9Xc\nTfHWU81zc72pyyUliSHeo0ZR6d/hw2p8XOOdk+NMvFNh1xlFvEHNGgSATwHYDmAmgLsBFAL4KgAI\nIUpAtSR/B3ANgFkA7hVCtEkp7472BulCvAHg8cep/lRHPBGbIBRvJwhBjv3u3eGP8cRkV8mDxDXX\nkCrJDoITEp2yGHSmQSZAStkCoCVBp1sN4BtCiCqtbmwJgB5LcmAAACAASURBVHYAGyO9cMWKFZiv\nMeknngC+/33g3HPp/+HDVWr5WWfRMb1nwcSJdDtjhjrGhHfOHOD3v1dOKkAq+Jo1itCHQkQKt261\nOrPDhpEdsLPLxBuw1ngDFK3VVSkpiczqNd5S0gLOz9NVqbPPpvu64s2EPy+P7LK+nu5zQM+txru4\nmBxuwLvizTV6dnXLa403QMR73Tq6rzvwAI2dMxP43Hv2kKrtpHhzo6hE270T8Vu3bh0WLFiQ2DdK\nIdLFroEVuP76+fjkJxM0EsRHvPPyUke8ufzDD/EuLaXXdXRY54xQiOyJA4c8j+zerQh6ZSU9b8sW\nYO5cOpafT7a1Y4dKoQXIbpmM6wGz3l5VN84oLlZBMTfFu7098loeFLLdttPHrq1rdl0d9RLg9TEU\nIjK1ZYtKMQfo/vbtqvQBoOv0zTfpvl3xLi11JrX6GpWfT+tha6s3EulX8ebxcK8EPa2cFW+9L1JB\nAQXdc3Ksc41fxZsDdf39sa+BepaAXl6qK95+GlQmosa7pkZlPeiKd08PiW9O/CkVdp1RqeZSylVS\nyk9IKf8hpdwlpXwKFKW7WHvaFaCtDj4hpdwkpXwYwM8BfMnLewRFvPV6DK+44AJVX8qIh8QFoXi7\nYfx44PTTw4+zUSazCc1ll9FirZMjO4L8blJdT5IJGNzzcw6A8QByhBBzBv84af/voAX7d0KI2UKI\ncwDcAspm6XM5rSMuuAB49VWVLg5QlPT115UTmJcHPPww8PLLaiE49VRaoLmvAQCccgrdspMKKALI\nihKgAmh8jGsnAdUdvbhYLbLs7OrXrJ5qzmCCrmfG8PPYKTl6VDmq/FhLi3WxLC8nZ9tey93REZ4O\nGotSnSjF2ynVHKDz2x14J2WA35fJlUlZDRZB23UQvTlirfFOZap5LIo3oNLNOSCXk6PmEk7fHTZM\nPa4/r6qKAlt6aVlVFanb9rnFrnhHstt0VbwNFJK5XvN6pzccHjWKSKPeC6mqSpVVsc9VWanWHl3x\n7uuj64yvqeHD6a+52Wo/Qig11mvKNKAUdS9wU7x5JxDdPkpLw1O7+bP5Id6FhWo7tlhtiYMV9vHo\nirfXOVQfT7yKt318PI/19KRPqnlGEW8XlANo1f5fDOAFKeUx7dgqANOEEBGqjwlBEW8hgG99i5Sw\nVCEdlFee/LzsZZ5IRGr4BiQ3KGHgiJsBrANwI4DiwfvrACwAACnlAIDzAfQDeAXAAwDuG3x+3Bg5\nEli40Hrs0kvV/t8AOZvNzdTXgHHiicAddwD/q+1m+ulPU3T+Qx9Sx5gEL12qjvECw8QbUIssLyA1\nWhsavq+TcT6mP49rM5m8A8o55scAaxZOebnaFoRRWkqL57Fj1p4Fej2WV8W7u5vuuyneXpur8RYg\ndsX76NHwlFUm3k6p5uykGAc+cARq10E0V4tF8T56NLXbXHGQzGv5B4NVRHZOATW/MCkH1HykEx2e\nX3T1mc+jk/GKCpXhpivegHNTRLe5RVe8jd2mHElbryOtezoZ5+vRfu0x7H1OAGvpY2kprRlO29h5\nJZHDhtG16VfxHhiwjqeigjLYnMbIJWX2MfpJNS8o8D/P2cH+Q0eHdTyhEP1/6JB3vzoR4wEiE28g\nfYh3Rk9fQogpAD4Hq5pdg/A6FL2bYsTk/aCINwDccktw546Ec86hbcDs+1unAjyJJJt4uyE312wr\nlA6QUl4N4Oooz9kLWsxTBvtCEgoBn/mM9dioUeFlFjfdRI3dOL0bAL79beCqq6wp7EeO0C0f0+2E\nU9d1Qs0OiH6MnRHdwWDnODdX1VfaVSkgnHgz9MW/qIjSWgHvSjXDrnj399N9L/ann4fHpjtZbt2R\nnYg3j9848MEiaLsOsqu5n+ZqQGq3uSouVsEtP8T7uOPIN+AGk4BSGPWMnZoaarjmlXg7zS2Aslfd\nbu3BOC4DsdttOnzPBoRkrtd8PToR72jXo07M+ZrUj+nrGgdrnYj3gQNWAhcJxcU0h/gh3gx7Roh+\nDFCfwUnxZrvxSrzjLbcaNow+o70HDI+nrc19W+RI44nHtnUBQm8yy0gX4p0Wincs3RSFEGMA/BXA\nH6SU90R7i8HbqN0UgyTeicKvfkUpsF7x1FPAW29FV32TASb/6aC+A2piMIq3QZCorQU+9zlr2cGV\nV5ITqS8Wf/wjcNdd1npvBqfG66oav1a3J76m9QVVd3TZWXFyjnUVXH/cTmoZXhVvht3J5rF7KcfQ\nF3H+PG4OSqTmhvn5/gi/QfoiiK7mHPzyukbxNd3Tk1rizfCztjK5diLeTtk2OvlgdUm3QXZy9bmD\nA2a5ueGZKoB3u+XPZbYBHFrgdc8p4OyVeBcVqXXTjXjzNetEvAHvawX7uF59SraPwkI1Rv0zOI3R\nSfFmeCXerKjHY0uRAgFOhNwNhYVqPIlWvPVrJB3ERyB9FG9f3RSFEKMBPAfgJSnlNbbnNUB1T2Sw\nyUbtkvqnP5Xh3XfVkXi7pAaB667z9/zcXOvCmkqkKtXcDdwhOgjivWoVsGGD82NDoEOqgQfYu/zr\nqeiMF1+kmnSdnC5dCvz1r1YVmKEf44wO3dGtrFQNkBi80OsLfiTFm+HFydfPaVe8vZ4DcE4bZIeq\nvz881ZzhppwBxoHPdASheDP8Kt5AapurMfwQ7+XLidjomTgf+xjwm9+orRUBRbijER0+5kS8S0rU\nHOaFeNt9BP1zGbsdOli6lMo0ucwIcA44O6WaM8l2CkwDwRBvPaDsBfaeLIB1rfNDvEMhb+Uuus3F\nM4dyloDbeLx+B4kaj/7bOmXxpYvinRbTl59uioNK93MAXgfwcYenrAbwPSFEjpRyUNfAEgDvSimj\nMJsVuPTS+bj1Vq8jN/ALNoJ0It5vvx2M8rVkCf05Ids7pBokDqeeSn86Hn+cunfqGTrf+Q41H9NT\nRI8NdrrQFyRe1J0Uby/E26/irTsRboq3F9gDCgA58qWlzt2RGZGIt8l0yWwESbz9Kt5A5inew4cD\nH/mI9dipp6omVYwbbiBioAcG2cHXU4CdFG+eU/Tfyi2bJlLATLdVQ7yHDubNoyzPSy5Rx849l4JG\nelNTJt76tcHrHtdQA9brWg8i87Vn34EoWcRbH0ssqeaAv5pqRlCKN5B84q37Q047HxjFOwYIIWoB\nPA9gF2j7sJFiMIQqpWQ1+yEA3wFwjxDiR6DtxK4H8AUv75EJqeaZjLIyWrCXL0/1SAhz5wJ//7vp\nPG6QWcjLU1v7ML773fDnnXYaKeazZqljvNDGSrzjUbz1BTYexVsH15MZ4j30EERXc8ZQIN5uKLO1\noR07llRHHR/+MO2E8NGPqmNOJILtlss7AKsq51XxFkLVlBq7HToQIjzLc/p06oKtX2e8c4ie3cnX\n4zGt1bLu6+np67zeuRFv+zriBr/rGqfSHz6sjsWaah4L8Y5X8XYaj9/vQP+MQZZ/2XeJShUyiniD\nlOtJg3+DO99BgGq3cwBAStkxuHXBLwG8AaAZwE1Syt96eQNDvIPFsGHWSTDVuOUW2vZM31rKwCBb\n8Ne/ksOrO7pTp9Jx/Zp3aorkpj7pzo5fxVs/JzvZXp0FfRs1Hby4e1XOdGfAOPCZjXRTvFPZ1ZyR\nrP4pJ54IPPSQ9di8eUQarrpKHWPy09PjfB6nLBjAmehwB3nTm8HAnjY8Zw7tLKAHv3jHEG6maUcQ\nxNuv4j11sHsVd/MHrNd30Ip3PLYULRDgNbNVH0+8HGzjRvd+Vm7B+2Qjo4i3lPJ+APd7eN56AO+N\n5T0M8R5aGDYMOO+8VI/CwCAYOKVW3XIL8NnPWhVzvq87KLoD4pZq7lfx1tUGvw6KH+IdSTkzinf2\nINEKc6bWeCda8Y4Vixap3QQYrETqih5A329vr3e7BdRnM3Zr4AS7/VVXA8uWAdOmOT9fz+xgsmYn\nbUEr3ryu8ZZ7XsaYbYo3jycvL/7sU979RcfTT1t7BKQaGUW8kwFDvA0MDLIZJSXhUX12TA5q7Sf1\nRdMt1dzLQm9PW7Wfx+viLAQ55vZgAi+oOsE3qeZDA0GlmodC3n2BdCDeqVC8vYK/00WLrMeZaLjZ\nrVP2AH/XRvE28Ap7VoYOneTpTQB18Npnb4TqBr+ZXEIAt99ubXCow2kbTbuNx6N4ew0oOCFRNd5+\ngxt+4dS0NpUwxNsGQ7wNDAyGGiZMoNuLLnJ+PB7F2y39ls/jZ85taAg/tn073ep9CSM1gDPEO3sQ\nVKq53owpGtKBeMeSIp9MdHW5zwO6QhWt67BRvA2CAjcltc8pQaeaA8D114cfKyqyNkoFFNG120k8\ninc8ZNdN8Y61q7nX4EamwxBvGwzxNjAwGGrIzSWy4ZbmpS/ofhVvN/B5+vr8v0bH9dcDDz5odUZ0\n1cL+mQzxzh4EWePtFelAvHVSmy6de3U4jammhgJpug0a4m2QDGzYALTY9lHi7vydndbjQaeau6Gx\nMZyPMPHmniz29/Sapq3Pc+mgeOup5kMBhmbaYIi3gYHBUITTov3448CFFzrXZgPxORd8Hj/E2wm3\n3w40Nzuf2wmGeGcPguxq7hXpQLx16A2j0hnr1wP79lmPuTVFYphUc4NEYMYM2vFDB6vLHR3W47yW\n+E01j5d4FxaGE1reGWDEiPDnAt4bFydK8Z4/nz6nva7ab3M1/s78ZBplMtJgmUgvGOJtYGBgQLjg\nAvrTEUtX8KeeAkaNsh5jkuPWVCYeRBqXId7Zg3RQvHV7SFVXcx3pMAYvsKt2QPSuw0bxNggK3ORs\nxgzrce7K7/WaS5Ti7QQe4+LFzu/pNYgdbfcArzj/fOfdCvx+Bxxw07cczGYYmmmD2c/ZwCC5EEKM\nF0LcLYTYIYQ4IoTYKoS4SQiRZ3vebCHEC0KIbiHEbiHEDaka81CGPkd6DVSedx6wcKH1GG/1smNH\nYsZlB6cO2mGId3KQDLsOsqt5LGNIB8U7kxHN/zKKd+qRret1eTmwZQvw9a9bj7O63N3t7Ty8Teee\nPYkbG2PxYmDvXuDMM63H/SreiSLe0c7vdX1l4p1OWw0HCbNM2GAUbwODpGM6AAHgUwC2A5gJ4G4A\nhQC+CgBCiBIAqwD8HcA1AGYBuFcI0SalvDsVgzaID27bgyUKGzaEp6ADhngnEYHbdaIJmN5hOxYY\n4h0/rrsO2LrV+TGjeKcFsna91rfYZDDxPnLE2zk+8AG6nTw5MWOyY+zY8GN+FW+d5wSRIcNru9v+\n6XYMNcXbLBM2GOJtYJBcSClXgRZpxi4hxE8AXIvBhRzAFQDyAHxCSnkMwCYhxDwAXwIt+gZJxgc/\nGP85HntMpfIlGuXlzkRKJ96ZkpabiUiGXSeaeNfUxPf6VBLv//u/9Gys5he/+pX7Y2y7hninDkNt\nveaSCK/Eu6AAaG9Pri2ywmxvDJcqcHCgqcnb87kZqlG8hygM8TYwSAuUA2jV/l8M4IXBRZyxCsBX\nhRBlUsr2pI5uiOPIkcSQHrfty4JENpCTDEZC7TrRxDteQpdK4n3ZZal772SBFW+Tap52yNr12m+q\nORC9SWCiMX06cOmlwKxZyX1fN3C6vVfiPdQU74yjmUKIxwfrRbqFEAeEEA8IIWptz4m5tsQQbwOD\n1EIIMQXA5wDcqR2uAXDQ9tSD2mMGSURBQeam1WbquDMdQdh1uhEwc20FCw6aGcU7fZDt6zVnZNl7\nlKQTQiHg4YeBb3871SMh8M4K0ZolMlixHyqKdybSzOcAXApgKoCLAUwG8Ag/qNWW7AQwH8ANAG4S\nQnzSy8kN8TYwSAyEELcKIQYi/PULIabaXjMGwF8B/EFKeU+0txi8lUGM38DAIBzpZNfpRrxN6UKw\nMM3VgkM62XU6ITcX2L0buOWWVI8kc5CTAzzzDPDAA96fDwwd4p1x8Vkp5e3av3uFED8E8CchRI6U\nsh9x1pYY4m1gkDD8BMC9UZ7zn57WQojRoMDaS1LKa2zPawBg25AKvGOtPbJuwfLly1FWVmY5tmzZ\nMixbtizK0AwM/GHlypVYuXKl5Vh7e8ZkVXpFWtg1sBwXXZR4u66vB6RPahAK0R60RvEOFqms8R4C\ntp0mdp1+a3ZdXUreNqNx9tn+X3PKKYkfRzSkwq4zepkQQlQC+AiAlwdJNxBnbYkh3gYGiYGUsgVA\ni5fnDkbOnwPwOoCPOzxlNYDvaQE2AFgC4N1oNr1ixQrMnz/f+8ANDGKEk3O4bt06LFiwIEUjSjzS\nxa6BFXjiicTbdSwN1nJzaT96Q7yDRSqJd7bbdvrYtVmzk4FzzgHeeSfVo1DYtk2lqCcTqbDrjKSZ\nQogfCiG6ADQDGAfgQu3huGpLDPE2MEguBns0PA9gD6gr6kghxCghhB4xfwhAL4B7hBAzhBCXAbge\nwE+TPV4DA4PoGEp23dtLtzaRziDBYOJtUvpTh6Fk19mMv/0N2Lcv1aNQmDxZdTfPdqRFfFYIcSuA\nr0V4igRwvJRyy+D/t4HSxscDuBHA7wCcH+kttPNEwHLccUcZnnpKHTEpqQZBYAikrfnBEgCTBv/2\nDh4TIHvNAQApZYcQ4hwAvwTwBijodpOU8rfJH66BgYEHBGrXa9cGMeTYIASlp5uU1GDBxPvo0dSO\nY4jDrNcGBnEgLYg3fNaWSClbQVsXbBNCbAbVep8opXwVcdWWrMC1187Hddf5GLmBQQzI9rQ1P5BS\n3g/gfg/PWw/gvcGPyCDbccEFwNNPp3oU2Y2hZNebN/uvCzfwDybePT2pHcdQxlCyawODIJAWxNtP\nbYkDOOlocIfH+GpLhkpXPQMDA4OhiscfT/UIDLIJU6dGf45B/DDE28DAINORURXNQohFQojPCiHm\nCCHqhBBngmpJtoIINxBnbYkh3gYGBgYGBgYG6YVFi+h27tzUjsPAwMAgVqSF4u0D3aC9u28CUASg\nHrSH4PellH1A/LUlfX0BjNrAwMDAwMDAwCBmzJ5NPprpHm9gYJCpyKjpS0r5DoCzPDwv5toSo3gb\nGBgYGBgYGKQfDOk2MDDIZGRUqnkyYIi3gYGBgYGBgYGBgYGBQSJhiLcNJtXcwMDAwMDAwMDAwMDA\nIJEwxNsGo3gbGBgYGBgYGBgYGBgYJBKGeNtgFG8DAwMDAwMDAwMDAwODRMIQbxsM8TYwMDAwMDAw\nMDAwMDBIJAzxtsGkmhsYGBgYGBgYGBgYGBgkEoZ423DCCakegYGBgYGBgYGBgYGBgUE2wRBvDX/+\nM3DddYk/78qVKxN/0gw/d9Dnz9RzG2QOMvkay9SxZ+q5DTILmXqdmXOn5vwGmYFMvYYz9dxBnz9T\n7TpjibcQYpgQ4t9CiAEhxGzbY7OFEC8IIbqFELuFEDd4Oee4cYAQiR9rpl54xiCTf+6hCiHE44O2\n2i2EOCCEeEAIUWt7Tkx2HRQy+RrL1LFn6rmHKjLRroHMvc7MuVNz/qEGY9fm3Olw/ky164wl3gBu\nA7APgNQPCiFKAKwCsBPAfAA3ALhJCPHJpI/QwMDAK54DcCmAqQAuBjAZwCP8oLFrA4OMhLFrA4Ps\ng7FrA4MYkZvqAcQCIcRSAO8H8F8APmB7+AoAeQA+IaU8BmCTEGIegC8BuDupAzUwMPAEKeXt2r97\nhRA/BPAnIUSOlLIfxq4NDDIOxq4NDLIPxq4NDGJHxineQohRAO4CGXa3w1MWA3hh0NgZqwBME0KU\nJWGIBgYGcUAIUQngIwBeHlzEAWPXBgYZDWPXBgbZB2PXBgb+kImK970AfiWlfFMIMd7h8RoAO2zH\nDmqPtTu8Jh8ANm3alLBB6mhvb8e6devMuZN4/kw8t3b95Sf85BmAwaj55wAUAlgN4HztYWPXGXJ+\nc24rjF1nll0DmXmdmXMn//xD2bYDsGvArNlZde6gz5+xdi2lTPkfgFsBDET46wfVklwP4EUAocHX\nTRh8fLZ2rlUA/td2/hl8Dpf3vxxUK27+zF86/F2eaptMpl1rz68EMAXAWQBeAPCUsWvzl0V/xq6N\nXZu/7PzLeNtGiu3a2Lb5S8O/QOxaDF7sKYUQYgSAEVGethPAw7BG1QAgB8AxAA9KKa8WQtwPoERK\nebF2/jMA/ANApZQyLNI2+P7nANgFoCfGj2FgEC/yQcGkVVLKlhSPJW54tOsd0pqOxq8dA2AvgJOk\nlK8auzbIYBi7Vq81dm2QTcga2061XWtjMLZtkGoEatdpkWo++MGifjghxOcBfFM7NBoUWfswgNcG\nj60G8D2tyQMALAHwrpuxD77/QzEO38AgkXgl1QNIFLzatQtyBm+HD94auzbIZBi7Jhi7Nsg2ZIVt\np9qutTEY2zZIBwRm12mheMeKwRrvnQDmSinfHjxWCmAzgGcA/AjALAC/BfAFKeVvUzVWAwMDZwgh\nFgF4D4CXALSB0tduBlANYKaUss/YtYFBZsHYtYFB9sHYtYFBfMi4ruYOsEQOpJQdoFSVCQDeAPBj\nADcZYzcwSFt0g/YCfRa0WP8GwL8BnCGl7AOMXRsYZCCMXRsYZB+MXRsYxIGMVrwNDAwMDAwMDAwM\nDAwMDNId2aB4GxgYGBgYGBgYGBgYGBikLYY88RZCfFYIsVMI0S2EWDNYv+L3HDcKIQZsfxu1x4cL\nIe4QQjQLITqFEI8KIUZGON9pQognhBD7B891gcNzbhZCHBBCHBFCPCOEmGJ7vEII8aAQol0I0SaE\n+P/snXmYXFW19t/VnamTHjJ2Z55JiCQQEoZwEQgCyhhQ1EscAUHwgpcbPxC9DjijKERRURRlEM0V\nFBABAWUWSZCEIQkhAiHpTN1JdzqdHtNJ9/7+WLXcu06dmutU1alev+epp6pOVZ06Veesvde719pr\n30ZEw5Ltm4hu9/ktj6Sw768S0YtEtI+IGonofiKa5flc0v+BiCYR0cNE1EFEDUR0AxGVEdEXU9j/\n057j7iWiW1LY/2eI6NXI72klon8Q0ek5Ou7Lk+w702Pu97abjGKz7ZDa9bAUbS9TG/lftWu163RQ\nu476XH+061TsT207ZPQnu05l/1nYtvrixW7XhV47sJA3AP8JXrLgEwAOBXArgD0ARqe5n+sAvAYu\nLlEbuY10Xv8ZeHmEkwAcCa6W91yC/Z0OLlZxHnjdwyWe16+NHOc5AOYCeADA2wAGOe/5C4A1AI4C\n8B8A/gXg7hT2fTuAhz2/pcbzHr99bwfwcQBzwIU0Hor85opU/wfwQNBacKX6eeA5QrsAfAvAIyns\n/ykAP/cce2UK+/+/yP8yM3L7FoD9AObk4LjPSrLvTI/5W4W2n2K+oQhtG+G067uRmu1laiNvpbBv\ntWu9qV2rXadjf2rbIbqhn9l1ivtXX7xE7brgBldgY18J4EfOcwKwDcDnMzD2NXFeq46c3Pc722YD\n6ANwTAr77vMxyB0Alnm+owvAhyPP50Q+d6TznveB1zsfm2TftwO4L8HxHJrivkdH3vfuVP8HAGcA\nOACnsQVwGbhy5gDPcUTtP7LtKQA3JTj2dPbfDOCiXB+3u+9cH7Peov63orbtsNp1ZHtgtq12rXad\n6KZ2rXadzP7UtsN36892nWD/6oub0rTrfpv6QkQDASwE8IRsM/xP/g3AcRns8pBIysjbRHQ3EU2K\nbF8IXi/d/Z6NAOoz+R4imgZgrGd/+wCscva3CECLMeZl56N/A1eAPzaFr1kcSSF5g4huIaKRzmvH\npbjv4ZFteyLPU/kfFgFYa4xpcvbzGIAaAId5jtG7f+GjRLSbiNYS0XeIqMJ5Len+IykpFwAYCl6L\nMmfH7dm3u0ZgVsesRBNG2w6RXQPB2rbatdq1L2rXcem3dg2obYcdteuEqC9egnY9IJ03lxijAZQD\naPRsbwSPoqTDSgAXAtgIYByArwF4lojmgo2zJ2KU3u8Zm+b3IPIZA//jHuu8Z5f7ojGml4j2pPCd\nfwHwR/D66DMAXA/gESI6LtIYJt03ERGAHwL4uzFG5tek8j+MjfO75LVXE+wfAH4LYAt4JPJwADcA\nmAXggyns/1gi+juAIQDawKNqbxDRkdkeNxH1ghsOd98bc3DM//5PlCjCaNtFb9dAsLatdq12nQS1\n61j6q13Hsz+17fChdu2P+uIlatf9WXjHg+BZGzwZxpjHnKfriOhF8An8MHjeSk6+Jwmp7C/pe4wx\n9zhP1xPRWvC8lcXgVIxU9n0LgHcBeHeS40npmOTQnMey/+Oj3mDMbc7T9UTUAOAJIppmjHknyf7r\nARwBHr07H8BdRHRijo77Db99G2PeyPKYc3n99AfCaNvFZNdAsLatdm33raSO2jXTn+w6rv3l6LjV\ntgtPv7VrQH1xlLBd99tUcwBN4IIGdZ7ttYgd1UgLY0wruMjBTAANAAYRUXWOvqcBfKElOu6GyPN/\nQ0TlAEak+52RC64J/FuS7puIfgLgTACLjTE7PMed7H9o8Pld8rwx8l3u/ncmOfxVkXv32OPtf6cx\nZpMxZo0x5kvg0aurcnHcxpiDcfad7TFndZ2WMGG07aK268jzwGxb7Tp633H20d9Ru05CP7LrRPan\nth0u1K5TQH3x0rHrfiu8jTEHAKwGcIpsi6RNnILonP+0IaJKcGrIjsh3HPR8zywAk8EpD+ke9zvg\nC8DdXzV4Tocc9wsAhkdSM4RTwA3FKqQBEU0EMAqAGFaifZ8buZ1sjKn37CrR/+Ae9zwiGu187r0A\nWgG8HjH0ePv340jwSJR77HH37/lsGYDBuThun+OSfef6mBWE07aL3K5XJbG9bG3ksgT79kPtuh+i\ndp3S7+ivdg2obYcSteuUf4v64qVi1yZHVQnDeAOnn3QhegmDZgBj0tzP9wGcCGAKuKT/X8EjIKMi\nr98CnqexGFwg4HkkXk5sGDgdYj64Yt//RJ5Pirz++chxngMua/8AgDcRvYzBIwBeAnA0OA1kI4Df\nJNp35LUbwI3HFPAF/hKADQAGJtn3RnB1vxPAo0ByG+J8LuH/ADaCV8FzWw4HV2hsBPDNyGfj7h/A\ndABfBrAgcuxLwEuaPJnC/p8Dp+JMAS8LcT3YwN+TnEpHSgAAIABJREFUg+P+drx9Z3nM3yy0/RTz\nDUVo2winXf8GSWwvSxt5KdG+s7QRtesSu0HtWu06if2pbYfvhn5m18n2D/XFS9quC25whb4B+C/w\nunBd4BGNozLYxwrw0gdd4PkJvwMwzXl9MIAfg9NE2gDcC6A2wf5OAhtir+f2a+c9XwOP4nWCK+vN\n9OxjOHitztaIkfwSXMEv7r7BBQceBY/kdQPYBF43b0wK+/bbZy+AT6TzP4AbnYcAtEcu6u9FLviE\n+wcwEcDTAHZH/pONEcOqTGH/t0V+a1fktz+OiKHn4Ljj7jvLYy4rtO0U+w1FZtuJbK+I7XpoMtvL\n0kbUrtWu1a7VrtOyEahtl9wN/ciuk+0f6ouXtF1TZGeKoiiKoiiKoiiKogRAv53jrSiKoiiKoiiK\noij5QIW3oiiKoiiKoiiKogSICm9FURRFURRFURRFCRAV3oqiKIqiKIqiKIoSICq8FUVRFEVRFEVR\nFCVAVHgriqIoiqIoiqIoSoCo8FYURVEURVEURVGUAFHhrSiKoiiKoiiKoigBosJbURRFURRFURRF\nUQJEhbeSFCI6iYh6iai60MeiKEpuULtWlNJD7VpRShO17dKAjDGFPgalyCCipwC8bIz5XOT5AAAj\njTG7CntkiqJkitq1opQeateKUpqobZcmAwp9AErxY4w5CEANXVFKCLVrRSk91K4VpTRR2y4NNNVc\niYKIbgdwEoCriKgvktbyycjj6sh7PklELUR0FhG9QUQdRHQPEVVEXnuHiPYQ0Y+IiJx9DyKiHxDR\nNiJqJ6IXiOikQv1WRekvqF0rSumhdq0opYnadumiEW/Fy1UAZgFYC+ArAAjAXADeOQlDAXwWwIcB\nVAO4P3JrAXAGgOkA7gPwdwD3Rj7zUwCHRj6zE8D7AfyFiOYZY94O7icpSr9H7VpRSg+1a0UpTdS2\nSxQV3koUxph9RNQDoNMYsxsAiKjX560DAFxujNkcec8fAHwMQK0xpgvAG5H5KScDuJeIJgO4EMAk\nY0xDZB83EdEZAC4C8OUAf5ai9GvUrhWl9FC7VpTSRG27dFHhrWRKpxh6hEYAmyOG7m6rjTyeC6Ac\nwL/clBcAgwA0BXmgiqKkjNq1opQeateKUpqobYcMFd5KphzwPDdxtkkdgUoABwEsANDneV97zo9O\nUZRMULtWlNJD7VpRShO17ZChwlvxowc8IpZLXo7ss84Y83yO960oSnLUrhWl9FC7VpTSRG27BFHh\nrfixGcCxRDQFPAJWBi7skDHGmDeJ6HcA7iKiq8HGXwvgPQBeNcb8JbtDVhQlCZuhdq0opcZmqF0r\nSimyGWrbJYcuJ6b48QMAvQBeB68ZOBmxlRQz4UIAd0X2/wa48uJRAOpzsG9FURKjdq0opYfataKU\nJmrbJQgZk4tzqCiKoiiKoiiKoiiKHxrxVhRFURRFURRFUZQAUeGtKIqiKIqiKIqiKAGiwltRFEVR\nFEVRFEVRAkSFt6IoiqIoiqIoiqIEiApvRVEURVEURVEURQkQFd6KoiiKoiiKoiiKEiAqvBVFURRF\nURRFURQlQFR4K4qiKIqiKIqiKEqAqPBWFEVRFEVRFEVRlABR4a0oiqIoiqIoiqIoAaLCW1EURVEU\nRVEURVECRIW3oiiKoiiKoiiKogSICm9FURRFURRFURRFCRAV3oqiKIqiKIqiKIoSICq8FUVRFEVR\nFEVRFCVAVHgriqIoiqIoiqIoSoCo8FYURVEURVEURVGUAFHhrSiKoiiKoiiKoigBEmrhTURfJKI+\nIrrJ2TaYiH5KRE1E1EZEfyCi2kIep6IoiSGiy4noVSJqjdz+QUSnO6+rXStKyFC7VpTSR31xRUmd\n0ApvIjoawKUAXvW89EMAZwE4H8CJAMYD+GN+j05RlDTZCuBaAAsjtycB/ImI5kReV7tWlPChdq0o\nJYz64oqSHmSMKfQxpA0RVQJYDeAzAL4C4GVjzOeIqBrAbgAXGGPuj7x3NoANABYZY14s1DEripIe\nRNQM4GpwZ612rSglgNq1opQG6osrSvqENeL9UwB/NsY86dl+FIABAJ6QDcaYjQDqARyXv8NTFCVT\niKiMiC4AMBTAC+BImdq1ooQYtWtFKTnUF1eUNBlQ6ANIl0jHPR9s2F7qAPQYY/Z5tjcCGBv0sSmK\nkjlENBfskA8B0Abg/caYN4joSKhdK0ooUbtWlNJDfXFFyYxQCW8imgieN3KaMeZAOh8FEDennohG\nAXgfgM0AurM5RkXJgiEApgJ4zBjTXOBjKQRvADgCwHDwvLC7iOjEBO9Xu1bCgNq12rVSmvRL21Zf\nXClxArXrUAlvcGraGACriYgi28oBnEhEVwI4HcBgIqr2jLTVgkfa4vE+AL8N4oAVJQM+CuB3hT6I\nfGOMOQhgU+TpGiI6BsBVAO4BMEjtWgk5atdq10pp0t9sW31xpT8QiF2HTXj/DcA8z7Y7wAUbvgtg\nO4ADAE4BIAUdZgGYDE51i8dmALj77rsxZ86cBG/LjGXLlmH58uU532+Y9x30/sO47w0bNuBjH/sY\nELkeFZQBGAwu3nIQateh2L/uOxq16xiK2q6BcF5nuu/8778f27b64rrvgu8/rHYdKuFtjOkA8Lq7\njYg6ADQbYzZEnv8KwE1E1AKeT3YzgOeTVFHsBoA5c+ZgwYIFOT/umpqaQPYb5n0Hvf+w7jtCv0ux\nIqJvA/gLePmhKvBI40kA3muM2ad2HZ79677jonYdArsGwnud6b4Ls3/0M9tWX1z3XQz7D6tdh0p4\nx8E7X2QZgF4AfwCPqj8K4Ip8H5SiKGlRB+AuAOMAtAJ4DeycS7VUtWtFCR9q14rSP1BfXFFSIPTC\n2xjzHs/z/QA+G7kpihICjDGXJHld7VpRQobataL0D9QXV5TUCOs63oqiKIqiKIqiKIoSClR454Gl\nS5fqvvO8/7DuWwkPYb7GwnrsYd23Ei7Cep3pvguzfyUchPUaDuu+g95/WO2ajIm7pF6/gYgWAFi9\nevXqoCfqK0pc1qxZg4ULFwLAQmPMmkIfT9hRu1aKAbXr3KJ2rRQLatu5RW1bKQaCtmuNeCuKoiiK\noiiKoihKgKjwVhRFURRFURRFUZQAUeGtKIqiKIqiKIqiKAGiwtuht7fQR6AoihJNRwewbVuhj0JR\nFEVRFEXJBhXeDgcOFPoIFEVRojntNGDSpEIfhaIoiqIoipINoRPeRHQ5Eb1KRK2R2z+I6HTn9cFE\n9FMiaiKiNiL6AxHVprJvFd6KohQbL7xQ6CNQFEVRFEuQvriilDKhE94AtgK4FsDCyO1JAH8iojmR\n138I4CwA5wM4EcB4AH9MZcc9PTk/VkVRFEVRFEUpJQLzxRWllBlQ6ANIF2PMw55NXyaizwBYRETb\nAVwM4AJjzDMAQEQXAdhARMcYY15MtG8V3oqiKIqiFBuNjUBXFzB1av6+80tfAhYtAs45J3/fqYSD\nIH3x3bsDOWRFKQrCGPH+N0RURkQXABgK4AXwqNsAAE/Ie4wxGwHUAzgu2f401VxRCgMRfZGIXiSi\nfUTUSET3E9Esz3s0dU1RQoTade4YNw6YNi2/3/md7wBLluT3O5XwkWtf/PTTk71DUcJLKIU3Ec0l\nojYA+wHcAuD9xpg3AIwF0GOM2ef5SGPktYRoxFtRCsYJAH4M4FgApwIYCOBxIqpw3qOpa4oSLvqV\nXff1BbdvY4Lbt6JkQlC+uKKUMqFLNY/wBoAjAAwHd9Z3EdGJCd5PAJJ2WxrxVpTCYIw5031ORBcC\n2AUeOf87EVUji9S1fPPoo8C73w1UVuZun729QHl57vanKEFTanadiD/+EfjgB4GmJmDUqEIfjaLk\nhUB8cUUpZUIpvI0xBwFsijxdQ0THALgKwD0ABhFRtWekrRY80paQH/xgGX7/+5qobUuXLsXSpUtz\nc+CKEmHFihVYsWJF1LbW1tYCHU1RMhzcQe+JPPdNXSMiSV0rGge9sxM44wzgoouAX/86d/vt6QEq\nKpK/T1GKmNDadTKkOW9rU+GdLx59FJg3D5gwodBH0j8JyhcHlmHJEvXFleAphC8eSuHtQxmAwQBW\nAzgI4BQA9wNAZD7ZZPC8k4R85jPL8elPLwjwMBWF8etE1qxZg4ULFxboiIoHIiJw+unfjTGvRzbn\nJXWtvh6YPDm7fbS18X1jCu5FOqjw9ufuu7n4U01N8vcqhaOQdp0PpCBUqaSEh+F3nHEG34fhWPsJ\nOfHFgeV48EH1xZXgKYQvHro53kT0bSJ6NxFNicwvuR7ASQDujnTevwJwExEtJqKFAG4H8HwqKWs6\nx1tRioJbALwLQCrD2zlLXdu8GZgyBbjjjuz2sy8iIQYNyvaIotH2KZb6euDjHwe+8pXs9tPVBbz8\ncm6OSYlLQew6XzQ18X2pTFnT9kZJRJC+uKKUMmGMeNcBuAvAOACtAF4D8F5jzJOR15cB6AXwB/DI\n26MArkhlx6XSYSpKWCGinwA4E8AJxpgdzksNyDB1bdmyZaipSZ621tHB948/Dlx4YYY/AFZ4Dx6c\n+T78UEc4li1b+H5Alj3ZhRcC99yTfeRMp5D4U0i7zhcS8Q7CjyiEb9Ldnf/vTIfe3vx+n9p2DIH5\n4opSyoROeBtjLkny+n4An43c0kIdW0UpHBHn/FwAJxlj6j0vZ5y6tnz5cixYkDxtbf9+vt++Pc0D\n96AR7/whwnvixOz28+ijfJ9tATudQhJLoe06X4gGO3gwuH3nk66u/H9nOkh7nS/UtqMJ0hdXlFIm\ndMI7SDTirSiFgYhuAaegLgHQQUR1kZdajTHdxph9RCSpay0A2gDcjBymrnV28v2OHYnflwwV3vlj\n82a+zza7QM7ZgQNaOT6XFINd5wsR3EH4EYUQwcUe8S72gQFFURQ/QjfHO0iCGKlWFCUlLgdQDeBp\nADuc24ed9ywD8BA4dU3ed36uDkAcuWxTGHOZau6mPqvwjsUVzLlA/+OcU3C7BlhErlqVyz3GImt4\nByG88x3dBYpHeP/rX9bOXdzjy3fauaIoSqao8FYUpeAYY8qMMeU+t7uc9+w3xnzWGDPaGFNljPmQ\nMWZXut+1ahXw8MOx20V4DxyY+e8ArJOYi0q77mBgIZzvYkfOWa7EjmY95ZZ82nUili8HFi2yGRJB\nEsQ1VAgR7H6nDCoUgtmzgSVLYre7EW+1W0VRwoIKbwddkkJRSp9Fi4Czz47dLqnm2RbqEuGdC6Hs\n7qM/R2Pjtc1yzjTiraTCI49k9/k//cl/0M4liMy5Qke8C5UNKHa/cmXsa8VwfIqiKOmiwtuhkKO6\niqIUllxFvEUM5iJKpcKb2+WqKuDGG2Nfk3OWq/+mv/7HpY7M229oyG4/553Hg3aJhHDQEe98pVUX\nQyp3Wxvf+9XL0Ii3oihhRIW3g0a8FaX/Io5ctgNw4rBqxDs3dHTw7eqrY1/LRcTbjZapA1+ayFKB\nqdrkgQO20r0fW7cm/myucY87X9doMUSUZW10P+FdDMenKIqSLiq8HVR4K0r/wSuwRcRl68SJgM9F\nxNsV2/1BeK9cCfzmN9HbJOrlRy7meLuRs/7wH/dH2tv5PtXze+ONwBlnABs2+L9eyIh3vq5R1y4K\nFfFubuZ7v0KVGvFWFCWMqPB20FRzRek/eCvl5qpQlzjJuU417w/F1Y47DvjEJ6IHQUU0+SGDJdmI\nEdlHtvtRipd0I96NjXy/e7f/617bdgfrgp7j3Z8i3iK8k0W8VXiXHhoIU0oVFd4OauiKUtq4g2t7\n90a/JsI7VxHvXKeal1o65d13A3feGb1NCtu5a6kHHfF2hbc68KVJuhFvibDGmxPute2ghXF/F95+\ndTeK4fiU4NC2WClVQie8ieiLRPQiEe0jokYiup+IZnneM5iIfkpETUTURkR/IKLaZPtW4a0opY0r\n4lpaol/LVYXsoCLepbZW7cc/Dlx4YfS2yZP5/vXX7bZEwjsX50wj3qVPuhFvEXLbt9ttrn/g3U/Q\n0ddCRHeLobiaDJj4CWtNNS8sQfrigJ5TpXQJnfAGcAKAHwM4FsCpAAYCeJyIKpz3/BDAWQDOB3Ai\ngPEA/phsxyq8w0FPD/DUU4U+CiWMuOnlXkGXq1TzXM7xLpWI9333AWvW2OfJBJCbXu6eJ28bneuI\ntwrv0iTdiLdEWt3MC1fo5Vt4F6LIYjFElOW8+Q2+aap5wQnMFwfC3d8pSiJCJ7yNMWcaY35jjNlg\njFkL4EIAkwEsBAAiqgZwMYBlxphnjDEvA7gIwPFEdEyifesc73Dw1a8C73mPnYenKKniCjqv85yr\nVHNxCHPhDJZCxHvtWuD884H/+R+77Z13/N8rosIVw+4584qOXM/xVge+NEk34i3C27323MfeQbWg\nB8j6a8RbzptfnQd3IERFWv4J0hcHtC3ON0TAt75V6KPoH4ROePswHIABsCfyfCGAAQCekDcYYzYC\nqAdwXKIdacQ7HGzezPeuw6woqSCOHBBfxOUq4p0LZ7AUhPebb/K9277u2eP/XnH2XafajXbFGyzR\niLeSCBFu6Qpv9zpMNGiXz4h3f5rjLe21n11qxLvoyJkvDug5LQQ33VToI+gfhFp4ExGBU1n+boyR\nWYFjAfQYYzw1i9EYeS0uuRLeL70E3HprbvalxFIWuWpdERU0vb3AtdfGr3KrhIMwR7zDGtUREVPm\n9Dbu/HrJNDLGTgVIVXjnYrBElxMrfRIJOD/SvQ5LcY53MUSU5bz19cUOPBbD8SlMrn1xQIV3PhFb\nGjKksMfRXxhQ6APIklsAvAvAu1N4L4FH4+Lypz8tw1tv1URtW7p0KZYuXZrWQR19NN9fdllaH1NS\npLyc7xMVXco1K1cCN9zA4uCGG7Lf34oVK7BixYqoba2trdnvWElIorTlXM/x1og309TE9/EK27W1\nATU1LC7knMSLNHoFiPwnmmquJCLdVHM/4d2fI96FLq4GsI1XOLOHNeJdVOTUFweW4aKLajBsmN2S\niS+upIas8NIfhXchfPHQCm8i+gmAMwGcYIxxSqCgAcAgIqr2jLTVgkfa4nL22cvxox8tyP3BKjlF\nImf5FN6yrMyIEbnZn18nsmbNGixcuDA3XxAyiOgEANeA09PGATjPGPOg5z3fAHAJOKXteQCfMca8\nlc73JHKeRYAdPMgDLETp/QYhiIj3gAHhF95uX+YK75YWFt7u8m6pRBpzJZg11TxY8mXbiUi3uJpc\nc6kKb/caCnod73wWVyPitrDQEW8gVnh3dQGVlXxeVHgXjiB8cWA5brllAWbPzvXRKn5If9wfhXch\nfPFQpppHDP1cACcbY+o9L68GcBDAKc77Z4GLPryQt4NUAkMEUSGE9+jR+fvOfsYwAK8AuAI+o+FE\ndC2AKwFcBuAYAB0AHiOiQel8SbKId2UlP85G5HZ3A1VVuYt4E/G6wmFNpxTh7QprV3iLIE9FeLtR\nLhE7NTXZC++hQ/mxOvCBkBfbjkdfH5/jwYNTi3inMuXBW1xNrsVBg4K5hjo7uU0B8jcA192dm/Yw\nGzo6bIabX5aB/CdhbRvDTpC+uLbF+aM/R7wLQegi3kR0C4ClAJYA6CCiushLrcaYbmPMPiL6FYCb\niKgFQBuAmwE8b4x5MdG+c13VPJuomRKfQgjvnTv5XivfB4Mx5lEAjwL/ni/m5SoA3zTG/Dnynk+A\nR83PA3BPqt/T3g4MG8aOml/UqrraRlAGZNg6dnWxQ5iL63P/fhYMYY54yxzv1lbbJrrCW8SNGxH3\nCp6aGn7dPWfynurq7IV3ZSUPxGjEO/fky7bj0dXF192IEamd364utrXqav+I94gR8SPe2Q4CxUPa\npra2/IlMEd75/E4v7e3AyJFcW8V77kR479ypIq0QBOmLA+Ht78JIf454F4IwRrwvB1AN4GkAO5zb\nh533LAPwEIA/OO87P9mO0y2ulqwzUicucxobgSuv9P8PpZMNQnj/+MfAxRfHbpcqzLlYm1lJDyKa\nBi7G4lZH3QdgFVKojuoiwnvQIP+Id3U1P87U0TSGozS5csBFeJeXh9cRaWriFNHeXps62tICjI2U\n1xHRIqPu48bFLicmmSbxIt7ZzvEeOhQYOFDb7HyTS9uOh1xzI0emFvGWaHdtbazwHjyYxWg84V1V\nFZzwromUn8m38M7nd3rp6LDTu/zaa4l4q/AuCIH54kB4+7swIn3v4MGFPY7+QuiEtzGmzBhT7nO7\ny3nPfmPMZ40xo40xVcaYDxljdiXfd+rHceAAO2o/+Un8fbidtpIet94K/PSnwBNPxL4mjlQQwvu/\n/xu4/fb435lqcR4lp4wFp6h654WlVB3VpaODhbdf2qkrvDN15Hp62GEYPjw3zqqIwgEDwptO2dQE\nTJvGjyVq2NICTJjAj6WddIW3N+Itwtsv4p2rVPOg0oSVhOTMtuMh19zIkakNrIjwrquLvQ6rqvzb\njo4OjhYNHhzMNdTRkf2gYLrkaupNNri2Hy/iDYS3bQwzQfrigGYX5hN3Cp4SPKET3kGSjvAWJ9Er\nvN2IjArv1Hj2WWDr1uhttbV8//rrse8XEZzPxkK+SyPeRUUK1VGjaW1loeYX8ZZ0TiBz51muExHe\n2S5RKAMFYY94T5nCj13hPX48P3Yj3mVl7Gh7Bc+YMfw4yDnefteEUjDStu14ZBrx9grv9nYWon7C\n282aCEIEum1TPiPeUlW6UMJ23774wlsj3qWNCu/8IX2p+rf5IXRzvIMkHUOX+Yjbt0dvd6twqvBO\njZNOYsd6lzMOKg3Bli2x75f/OMjO1js/X4V3QWkAO+J1iI6M1QJ4OdmHly1bhppInuaaNXwOy8qW\nYv9+W8nSGN6erXMr1+bw4Xzf25v5XHHZ37BhfGxhFN4HDnBbOXkyP3dTzQ87jB+7Ee/hw1nAeIX3\nvHn8ON4c72JJNddlAtMmY9t27Vrwq1CbbsRb5jv6ZV5UVvIAjV9xNbmGgko1FwGaLxHc2cmDD0Dh\n2p7WVv9sF4DPgUxXycd/oradX8LY34UV8bdVs+QHFd4OmUS8vVFXFd6ZsXt39HPpz/yEbj6Ed0eH\nTbMD7HnWVPP8Y4x5h4gawNVRXwMAIqoGcCyAnyb7/PLly7FgAS8TePbZHD3+17+inXC5zrKNoLgR\nb4AdwmyF99ChbA9hTKeU2ggS8XaFd20tnws34j18OM8Hdyucu3O8/ZYTy0XEu6IiN6nmukxgemRj\n265dJyLdiLcI7wkTYiPeVVU8IBsv4j1gQOnM8W5rAw49NL/f6dLTw+2yZLskWoUiHxFvte38ohHv\n/FHKEW9jgF/9CvjIR+zqJYVGU80dMhHeXlR4x6e1FbjqKuCNN+w2t4iSi99yLkI+hLdbddn9zlJs\nmIoBIhpGREcQ0fzIpumR55Miz38I4MtEdA4RzQNwF4BtAP6Uzve4qeau8yz1AqSQT6aOpld4Z3uN\ndnaGO9VclhLzSzUfMYI7QmkDmpuBUaNiI95uuqnfVB5NNS9u8mXb8RDbHj2az2+yfn7PHra32lq+\nrsTu9u2LP8c76Ih3IeZ4t7dHDyDmGzlv8YR3dzcPmJWXa6p5KRLG/i6slErEu7MT+O53o9ur118H\nLr0UuOyywh2XFxXeDpkI70GelUZVeDNPP80G4HLHHcDNNwMPPmi3iWPuRSLeiYR3rp0B9/xLpE7Q\niHfgHAVOLV0Nntt5I4A1AL4OAMaYGwD8GMCt4IrHFQDOMMakJZVEeA8eHO3IyUDPqFF8n6kj5001\nz/YaDfsc74YGvp8xg+87Ovh/7+xk4V1RYW18zx6OSrrbDhxg26ut5fnffhHvqqriSTVXfMmLbcdD\nBlFra7mNT2aTLS12ygNgr0UZLOovc7xd4V2Itkd8gHhzvCVTJaj/XCksGvHOH2EU3j09wIueRelu\nvRX44heBxx+322Q502efzd+xJUOFt0M6hi7Ce+DA6O39UXg/8QRw773R2z76UTYAcbwB+9hNzxej\nAKKFbyFSzd3j8ka8dY53sBhjnolTJfVi5z1fM8aMN8YMNca8zxjzVrrfs3evf8Rbrrdshbdfqnk2\nSKp5WKua79zJ9zNn8n1Hh7V5b8TbFd6yTexw5EgWPN7iarlIEZf/WKuaB0O+bDsee/fy4IwI6WSD\nK+51CKQvvINKNc9nBW9jCh/xlsHQeHO8ZRA1qP9cKSwqvPOHtHHF6t92dvL0QJcvfhE49thoX12u\nGXebBPeKaY1yFd4ZIsI73nqeQGkK71dfBV55JXrbqacCH/5wtNFOiiQRPv+83SYG4NYjcSPe7ufj\nRbxlnWQg952tG+X2fq+mmpcG+Y54Z3uNhj3ivXMnR+pGjuSIdUeHLaJYVxdfeLtiB2DBM2RI7GBJ\nLhxvmVuuEe/SRCLYskZtsqyllha+DhNFvL39QFsb22kQItAYO+UkXwNwnZ38vYWMeEub7Jdqbgy/\nXlMT3Lx6pbCEsb8LK9IHF4MdtbfbAXvhwguB2bOjB2NWruT7d96x26Rtr6+322SgP5taO7lGhbdD\nJhHvgwejO8KwRrx37OD0cJff/x44/vjoSPSppwJHHhmbig1EC3JpNP1EtnSoQHTE2/3v4kW83Tl3\nuW4k3FEy93v7+nQd71Kgt5cdZL+It9fJyzbinatCSGGf471zJ1eHJuLf0d4ONEZqV9fVJU81l3bG\nL+ItQijbSLW7HxXepYcMrMi0sGTnuLnZToMAYoW3dwBIvmPEiGBE4P79bPv5FN65bscywZ0iAESf\nt44O/k9k4C2M2UBKYjTinT/yJby903l7e2OXDL7gAl5q1PV3/vY3vt+0yW6TY3a3SVbt5s12m+iO\nYtJjoRPeRHQCET1IRNuJqI+Ilvi85xtEtIOIOonor0Q0M5V9Z1pczT2hrngshtEjIHr0BwDWrwce\neSR62ymnACefHH2xX3AB8I9/RFccl4vYu+42EC1c5TOuyE4W8XazBeIVVwvy/3UHE7xFnOTayCbi\n3dICvPmmdiiFormZz2NtbWy6aLL5hKkiaa25SiCtAAAgAElEQVTi5Oci4h3mVPOtW+163cOG8e9x\nhffQobzNGD4/6US8RQhJpDqTNdP7+myEU1PNSxMRxalGvGWwyBXevb3cRsgAkHcf7rWYazt1bSBf\n7YAUNitkxHvXLh6wk/bDbZOlvdZU88IRpC8OhHOgOayI793bm1k/mgr33cdZb65OuPhiXlZ0/Xq7\n7aWX+P655+y2sohSffVVu000giu8JVLu6jMJ7nlXoCokoRPeAIYBeAXAFeBCLVEQ0bUArgRwGYBj\nAHQAeIyIBnnf6yWdC84Vj17hXV7Oj4OOnrzxRrQDsG0bcN110Z3QbbdxReGNG+22Sy4BzjorOkIt\nlcbl3hWHIrLd/Yqwdp0AudiNsc51OsI7lYi3vCeIyEI84S0GW12dnfB+4AFg1iwV3oVCrsmxY6PF\nHcDX6eDBdh5lprbb3MziXdKa+ntxtddfB+bM4ceVlezQNzby/1xRwTbV1sb/f1dX9LkxxtqkX4qv\nmyIOZPb/tLWxPboCXiktJNU81Yj3jh0s9lzhLX1bvDne8h1BiEA36yPfEe9CzvHetYvb0kGD2PH2\nE97V1ZpqXkAC88UB9ZPySWenHZgMypZ+8AO+f/llu03E9dtv222SZSMBQ6k3AbDGEcSfcwODEvGW\ngUPAagxXXxSa0AlvY8yjxpivGmMeAEA+b7kKwDeNMX82xqwD8AkA4wGcl3zfqR/H3r12sr5XeFdV\n5XaJi+5uXoPOrcr3xhvs0N5wg932i18A3/gG8Mtf2m133MH3MooE2BEgSfFwOzQR43JRA9YA3HkX\ncrG7xdPEOdm3zzrI2aSaV1bGj3gPHx5MZIGIO3nXwZfvHDUqu3O6Z491FJT8I9eqd24xEL3MGJC5\nAGtq4utExGA216gxNho7YED4hPfbbwMbNgBz5/LzkSP59zQ0sMAG+D9vbWWxA/DayTK3dv9+bmcq\nKvgWL+KdTXaBK+w11bw0kSkMqUS8+/q4n5swwQrvzk7bd40aFSu8xU5l8CaoKVBBpbL7IY5rdTX3\niYUS3pJmPmiQfw0YTTUvHEH64oAK73zS2WkFb1Dti/S1a9bYbeJbuxm0oj2kFszevba9lbawvd1+\n1tUY4uP5aYzOzuLxoUInvBNBRNMAjAXwhGwzxuwDL1FyXLLPpzvHe9w4fuyNnIkDnysn7sUXgRUr\ngHPOsdt+9zu+X73ablu7lu/dESURyyKo3Wi0XOx+o0hbtthtfu8T4S0OM2CFtyvGxQB6e63w9Irx\nCRP4sRhSTw93snV18SPew4cHE1mQZWRcx0pG20aOzO6cinOmFAZvirMrvGVeZ7bC2xvxzuYa3beP\nHcpRo3ggL0zOZXMzVzI3hutEAPw7mpu5GMrUqbxN2gNpR7yRxu3buX0gij/HWwY5MjlnbtX0bFLN\ng0rPU7Jn+3a+rlKx7V272M5c4d3VFT0w5L0Ou7t5n0EJ40KkmstAg7RlhUo1F+E9dGisnwVoqnmx\nkq0vDhSPSOoPtLdb3zSIwee+PqspJDW8q8uKa9EWra1WH4i/5gb8RLzLa+Xl0Wnl8SLeMpjv+nyF\npKSEN9jQDYBGz/bGyGsJSTfiHU94V1fnXngD3OHKMUq0+rXX7PtEXEuVv/37bZEB2dbUZDstudjd\nOeAiqGVbVZXdJgLc3bZ9O9/X1FgHQS7+yZPtd+3dy8Y3fXrsaNTkyfxYjEJer6uLH/GuqQlGeI8c\nyZE1v1TzESOyO6eyf6Uw7NxplxXyppo3NLA950J45yri7UbZwpZqLm3W1VcDhx/Oj0eOZBt45x1g\n2jTe5o14u8K7s9MKbyDxHG8gs/ZA/uORIzNPNe/o4HlqTzyR/L1Kfunr42tLBDOQOOItU7KmT48d\nAAK4jfC7DgGbap5rYexmZeRLeO/axZlfI0cWbtCvoYF9ACB2oLQQ/4mSFln54oBGvPNJW1v2K7ok\noqHB+tQiml3d4dUiRFaUu4Oe0tbKPmbNskK9vZ1vU6fGagwZ6Bdf/sCBwg6W95ekV4LPHBQvzzyz\nDEuW1ERtW7p0KZYuXRrz3r17gUMP5cde4V1Vldv5gv/8J993drJ4GD+eixEMGMBiuLeXL6QtW7gj\nEpG9aRM3XlOm2Iv3rcjqqOPHWyEtF/vhh9uLvb6ef8f06baT27aN079nzLAO644d/FtnzoyNeLtG\nIe+fMsUeg2yfNQt44YXY1JG6uuiIPmBHskaMyP3olaT1dnf7p5qPHBmdCZAurvBesWIFVqxYEfV6\nq5sKoOScN9/kaxeIdeSkoFIuUs3nz89NxFtSpEaNCl+q+csvsxBxp8KMGsWDg9u38/KDAAvvffvY\nrkaNsmnlgI00TpzIz90U395ee86yEd7S4UtENN3z/vbbnErf3c1tpVJc7N5tI9jJbLu3l/uhigru\n28Xeurq4T6up4XoL3lRz106DSjUfOpS/N5/Ce8wYFt+Fanveegv4j//gx8OGxbbXlZXW19KId2hI\nyRcHluH662tw5512SzxfXMkOWZpPfNMgbEmi3AsXWtEsQcEjj7T6QPzro4+2WkQi3u96V6zwnj3b\nahvRHbNnW80E8L4XLeJgpQjv734XuPVW7v8L4YuXmvBuABt2HaJH2moBvOz7CYcTTliOFSsWpPRF\nLS35jXifdRbw8MO8iPzo0SwizjgDeOghvjD37WMDOu00rh7Y18fvAYDFi+1SYVLE4PjjrfDesoU7\n2SlTooX35MnsTLjCe+JEFr0isnfs4P9h5Mho4V1Rwe+VCIIY1tSptooxETstU6bwa17hPXYsOzh9\nfbaqoYxkjR4dXZAhF+zZw79tzx7/iHe2qeayf8C/E1mzZg0WLlyY+RcoCdmwgRtvIDbivXMnsGBB\ndmnLsp+xY3NTXM116MOWat7Wxtc6OTP/Ro2y1UtnzeJ7STXfuJE7TCBaeG/dChx7LD93M1EaGlgM\nTJqU3RzvrVv5fA0enFmq+W9+w8f0uc/ZKL5SPMjASioR7+uuA779beCEE9h+y8v5+u3q4v1IdW2v\n8JZ+dOLEYERgY6Nd5jCfwlvSvAsRUe7o4P9c2gTvQKkUwJPjU+FddGTliwPLcfXVC3DBBYEcm+Kw\nf7+d0gYEY0viqy9aBDz2GD/esoXb2COOsH5BfT23oUccYYNuO3fyIP748VbTNDbyZ6dNY78OsML7\nkEOAJ59kjdHby7rEqzGamuyc9kL44iWVam6MeQds8KfINiKqBnAsgH8k+3yqqS379/MJnDSJn7sO\nfFubFd65uIB37+aRoQ9+kJ/X1/PF19vLwtvdBvCSYAcP8oX15pvcYS1cyBevMTyKPHYsR2dckT1l\nCnfublr5pEk2PRSwwnv4cCuyJRXU3SbFkySaBURHvI2x/1lTEwv3AQNsxyqjWjKw4V32qayM9x1E\ncbVEqea5mOOtqeb55+BB4C9/4RoIUmHbL+I9diw35uXlmZ3nvXv5HE+bpqnm+/dboSO41/6CyPim\nTBl59VUrxisr+b65mTtn2e4KHhFUkyZlN1giA4xAZllK+/bxNXXjjel/txI87kBPsoj3T37C9z/7\nGd8T2QG6f/2LHTogdo731q3cJ0n2Ra4d1y1brOOYLxG8e3e02M+3sJXVVeQ/TyS8tbha8ZGtLw5o\nqnm+EB896Ij3uHHsG7kR7wkTOLPVjXhPnMi+mBvxHjeOB/LdiHdtbXQQ0M20PXCAfYU9e1hvSPsp\nvrxMCSwUoRPeRDSMiI4govmRTdMjzyMyGD8E8GUiOoeI5gG4C8A2AH/K1TFIJEpSIL3rT+cq4m2M\nTZk46STuCLdssfO7Tz+d77dsYZFdWWkd2h07WGTPnMkXd08PX4SyrbY2Nrrtt80V3iLGXQOQDtBP\neLuF1HbvZkdGBis6Otih6ezk6LWs5wtYI5T/1x3YaG3N7cCGS6I53uXl/P9mc06l4rWSXx5/HDjz\nTL52lkRWGq2o4HPc18fX5r59dh5QprYrUzymT89NqvmWLdY2wpZq7ie858+3j6UjlOWK1q612Qji\n8D//PJ8fmdLj2qVMj5EoI5DZf71pkz2WTM67tPdK8WEMT22YMYPPUaKId08Ptw933MHz9QUR3rKK\nCMD76euzYq++nvvAAQOCEcaFEN7iAAP5r/b/s58BRx3F/e2RR/I2r/Devt0OzGuqeWEI2hcPU38X\nZmT6ZpAR702b2C+qq+Pv6+pi4T11Kvs4oqkkCFhXx1rEGJtV6+oOqf8wfLjVGA0N3DbLQHpbm9Uz\nMsXQFd6jR+f+d6ZK6IQ3gKPAqSqrwXNFbgSwBsDXAcAYcwOAHwO4FVxBsQLAGcaYpF1HqiNsIgz9\nIt65FN4nnMAp5iNH8gU6ZQpfmK+/zs7p9Ol84UnEW0Q2wB3Tm2/yiLGMDLtivLaWL8LOTtuxJxPe\nfqnmiSLe1dV2NG3nTj5mcbQ7OqJTaYcNs8K7uZkdDEl18y4jElQlU0kF9xbP6ehgJyDbqsfuMkpK\n5hDRFUT0DhF1EdFKIjo60fslFfSWW2yhL6ly2d1tB7LE4c7UdiXrJFcRb7FVIHyp5vv32+UWhUWL\n+P7Tn7Yp6JJKCtj5nKNH8+tSrEyEd0WFbSPWr+f3SVE0IH3b7OvjpU1kQCAT+1bhnTvStetE7NnD\nbe3y5cBxkRrKiSLeIuqGDYveLnU9tmyJHgACbB/hDt4E0S+JgwrkR3gbEz31w2/d8iBZtozvr7zS\n/tfuwDzAAyESDddU84IRmC8OaMQ7X+RDeK9fz+2JFEtsbLTt2qhR3I9KnSoJAvb08HY34i0R7MZG\nm1Xb3c3tk6s7AP6sRNf9hLdGvNPAGPOMMabMGFPuuV3svOdrxpjxxpihxpj3GWPeSrRP+7nUjkGE\n97hxnGIWVHG155/n+4svZkd02jR2xtevt9GhyZP5Yt24kTuiujo+plSEN8AXq1QZHjOGO7emJr7J\nHG8pULNzp001TyXiXVPDRt3XZ6tGi2PT3h69ZIlbPEWMQsSR38BGUEVsZL1XV+zv3Zv9YEprK+9T\nhXd2ENF/gjv46wAcCeBVAI8RUdzxyx07eJ7wZz5jt7mVs9euZedNRG6m53nVKraZMWOsk+9dDi8d\n3n47WniHKQLgF/EeMIBtTFJ5AdshAjwlBuDfOno08NRTPLgoI9PuIODLL3M0jCj9gnjGAF/5CnD/\n/dyeHB2Rd5m02TIQqGRHJnadiCeftIPIV13F94ki3tLHSLsgTJzINVMAe53IVAhxWNessZlmue6X\nmpq4/RLRnw/hvXs322khhHdrK3/XXXcB119vt7sR78ZGPrcyiBpkqvlTT9nVYpRogvTFgXD1d2Em\n6FTz9nZg3Tru3+MJb4D9fol4iz5pbLTLQcqqQlJ0dexYG8hrbWV9UlfnL7yl8KkI70Jnn4ZOeAdJ\nusJ79OjoIk3GWNGYbcTbGBbQn/+87YDmzOFCAuvWxQrvV16x1ZQnTeL3bd3KjruIvVde4eObNcum\nab3wAh/n7Nn2YpcF7idN4s+2tdkK6W7Eu6OD70V4t7TYyK4YgDF8scscWnFaOjrsfHK/VPNRo+xo\ndz4i3l1d/DvHjIlNNW9qsmIq03Mq80/kf1cyZhmAW40xdxlj3gBwOYBOABfH+8COHbGFr9xBnaef\nBo45xgq4dM6zMRyZ+exnOaX9hBNi958qbvtz4ADb69y5/LwUUs0BbifKnF6nrAz4/veBBx6IjpBL\nBy1RcMCuA97bC/zjH9GCGUi9PdiyBfjWt7huxsiR9pxpqnlBSduuE/Hii7aeyFFH8TYpluZ3jsVO\nxW6FiRO5n6qpsanmrqO4Zw/P/5ZBo1z0S8ZwtkdfHw/mATZqH5TI7O62RYpeeIHvJc07n6nmMpgh\nvojgDszLfyLHF2Sq+TXXAD//eTD7VhKjEe/8IMI7iIj35s0ciDxwgDPepF+vr2dNMGWK1SebNllf\nTex/xw5+77RpdmCgpYX78KlT7aD33r12KmxVFW+TVPOhQ9nvGDQoOqtWhXeRkKrw3r2bHeHq6mjh\n3dbGDmdtbfadVWcnNzxHHGHni77rXTyCs2ED8O5387aZM4FHHmFBKqPus2YB997Lv+eww/hYxowB\nHn2UXz/iCJu6JhUGZ82yF/vKlXzvGsVzz/H9jBm2yNirr9ptI0awQ9DczCJzypTokSe/iLe7Nqo3\n1VwGNYDYOd5BCG85lgkTWAC437l7Nx/PoEF8TjIRQCK8NeKdOUQ0EMBCAP9eMdkYYwD8DcBx8T7n\nrlEpyLW1axcL5ve9z76Wju2+8w7w059yYaZ164ALL+TtIiJTXfJu3z62o7vu4ucvvMA28p738PNi\nTDVft46XC/NrN+MJbz+uvho499zobdJ2uNslJe3pp3kw7OyzeXu6wlsKNx15JPDrX9tzlSiyt3u3\nvyOowjt7MrXrRLS3xxayJOJ+RqIeLmKnfhFvgNsHGTByhfd99/F2aT9ykfb86KPAqafykjf33stO\nZ9Cp5jffDMybB7z2Gg+CzZxpo0T5jHjLefAOgLgR7z/8gQMFcnxBZgH09NgBWSV/EKnwzhcSSBRR\nnMtBtt/8hu8/9SnWJ6NHc3v5zDO8ffZsOz32mWfYl/AGAQ8etBoDYF9aNIYb8ZbpsV7dIb+rspLb\n/o4Ofq2QQbC0hTcRnZzgtcuyO5zCkqqh19fzyIpb9RSwqW0ivLPpgGUUynXqRGwD1iE//ni7TeZQ\nzp7NQnLIECvGDzmEHdaKCr6Iq6rYgbjvPn4s0W2AO/7Kymjh/cwz3MFNn25T1599lu9nzrQG8HJk\noYjp06MNoL6enRg34r1tm40wu8JbKhaKQ+yKYJmHnevOVtYCHD+eO3mv8HbThzNpmGTNQmlkipEQ\n2PZoAOWIXp4EkedxhzQOHIgVgXJd33gjN8af/KR9LR3hLZ3WpZfyupCnRGq4EsUWBErEvfeyiP/k\nJ3nk9pvfZLsS+y3GVPOvfAW49lp2hL2kI7z9+PWvgS98wYprwAqe66/nNkyWGctEeFdUAC+9FC3s\nq6psxM2ltZXbo2uuiX0tDMK7VO06ER0dseINYMdPbNYlXqr5CSdw3/jpT9ttch3u2sXtx+mn2/Yk\nFxHphx7i+y99CbjzTs6okZoIQYnMRx7h9uXMM9lZdn9vMQnv118Hfvc7bm+FXAzCX365/8oEPT3Z\ntWNBEgK7zpiysuLr70qVXbvYp5agWC4DWrJM62238fPychbC0sbNnWunxz71FG+bNYuPp7zcZt9M\nn26FtwT8pkyxEe+WFiu83Yj35s22/oYIbwmyyaBqIcgk4v0oEX0/MkoNACCiMUT0ZwDfzd2h5Z9U\nI95uldFEwjubkSM/4T1hAheLuftu29GffDJflJdeasXve9/L90cdZcWiiPL3vIcvaIBH0js62IEV\ngxg+nC/2ww9nY5DvefJJdnYHDrTC+5ln+GIeM8ZWInYNRYyioYEv9hkzrPDet48Fhlz8biqZGJA4\nQW7atxRaCDLiLQYquKnmQGbndcMGvmb8nMEiIqy2TeDiLr74OU9Tp/L1vWIFizuxZ4Dfm+o5lloH\nX/5ydNEwID3h/fbbfH2NGsXX/tNPcxRdbLUYU81lMOlLX4pNqe/uzs5hnT2bBbabfi6C54kngCuu\nsBFId76+F782vbHR1udwqa7m8+4VGQ8+yPc33WTrWAhtbbajL2JK0q4BjjqfcootkCh0dqYnvOMJ\nvjPO4P5IBtQAuz79zTfzIM7Xv25fy0W/tG0b9+tXXcWDWzJHHQhOeG/cCJx/Prc9F10U/Z1BCO+2\nNv6uj30senu88zByJNvt5z/PbfWVV9rXsv3Pe3t50PTqq+1qCUKRR7zDatdJKSvTiHe+kEBXNquD\nxKO7O7bI6uGHs4aaNo01woABrDP++lfWIBIVr61l3TF4MNu8CO9/RBajcwN+b73FPsjkydx2lJWx\nxti82U4zFL9eiu0WUngPyOAziwH8BsBpRPQRANMA/BrAGwDmJ/hc0ZOO8JbCI67wlon8QQlvAPif\n/4l+PmqUXZxeOPtsTn897zy77YMf5Av7v/7Lblu8mKM+Z53Fz4m4iMvKlTaSPnIkX7Dbt9tOUqK2\njz7Kc8/cZcKeeIL/k/HjrSFL6vqMGWwUFRXsMLnCe+hQu9a4ZBR4I97GWOFNlNsGor6e/+uqqljh\n7aaaA5kLbymQU8QsRnHbdhOAXgB1nu21iI2W2Q81LcMf/1iDdevstqVLl6KvbymA6KJrQHzb/cIX\n+Fr41a/sNhHe0im4xBPesjydG13bt4+vj4cfBv72N57bLOtXA4Wv3OsXwX77bXbSf/tb4GtfA773\nvcTvzxZ3moak9APRmTUubW3cYZ97LnD77XZ7V1dsZBOwA4US4RbEGa+o4IFPV2jt3x/tmK9YsQIr\nVqyI2m+rrHdSOBajBO162bJlaGyswcaNnJp91FFs10uXLkVnZ2yFciD9iLcf5eW87+eeA97/fjuH\nHOA+r7eX+yp3EM4PY9iJnDXLDlwDfN2OHQv88Iexn8lWeMsSpUccEW2f7e3c50tFcZcghPemTdz/\n//a3PF1FBvMl680rvA87jI/x4Yc54u0ee7b/yb/+ZR///OfAd75jn7vCuwhtezGK264zRiPe+WPX\nrvwK7/nzeYqr6A6A9dSOHdFZvbW1HN0+5hg+NsmOffBBFtwTJ9rBGQn4zZnD7a6sqPTOO5zFA9hp\nRtu28fNQCW9jzAtEdAR4iYA14Kj5VwDcEJmXFVpSGWEzhhvqM87g567w3rGDOwFZ4ibVaJcf8YR3\nKhBFC2yABfJrr0Vv+9//ZRHrvvfjH+d0cRHZZWXc6a1axUIdsMUK9u616Z4SEX72WY6ul5XxtoED\nedQKsBWaR49mAbNxI/CBD/A2STVvbmZj9Yt4y/Jn48bx+3LZQKxdawtZucK7s5MdtYkTMxPevb3s\nQD37bHQUoRgpdts2xhwgotUATgHwIAAQEUWe3xzvcxUVy3HRRQvwhS9Eb3/xRR4sc+d3A/GFtwjL\nz33OLj22Z49d492Ln/CWdetnzODVCQRJWZ44MVpUCt5K+/lk5052jO+8E/jEJ3ibMTZb5pBDOOJ/\n/vncSQL+y4lly8yZLHqrq6MHOoYO5XPgFd6bNvHAyB13cHRSItNdXf7H5gp4V3jv28e/cckSFt5X\nXRVdAXbgQPteEX4ua9aswUKpvlUAStWuly9fjptvXoCNG7m9vvdeK8g6Omw0xGX0aO4Hb7gB+NCH\nbDQkXqQ1HjNmsFPoDsIAto9I5fpftYodzcWLbZolwL/Frz0B+FrLRgT/9rfcx3/729z/A+z3yJKZ\nfgwenF6RSD/6+qIzTGRqF8Cp7ddey4/jnQfpmwHgP/8z+rV0It7r1wO/+AVnr0g20VuROtsf+hDw\ny18CX/2qPXeu8C422y52u84GjXjnj3wL78sv5+1XXGG3nXIKt4GiBwCb4SbZumVl3A+vXctTgIjY\nhqV+1aBBVmNUVfHA3q5ddltNDQ+qv/02D2zm2j9Jh0yLq80Gr+G3DcDByPPiTqJNgVSaqjffZGdb\nBKcrvN98k1Osy8uDi3jnkhEjWES4EZv/+i/+PbJUB8Ad9IUXAm6fIw6LDECUldlRa+mHyspYJD/x\nBF/oErEaM4ajSO+8Y6uzS6q5uxayN+K9cyffjx1r59Dnqnt59VX7m13hvWkT38+YYf+ndBqmV17h\nFLbWVnZ4QkCx2/ZNAD5NRJ8gokMB/Bx8fHfE+0C8eXrLl3P0xJty7Ge7MhUB4OJDgixB5xfd8hPe\n27ax4/z669GRlmRzhb11B/LJnXfyvTsHcv9+doyGDeO5z0ccYR15eT2IuZFf/Wps1g+R7VRdJKUM\nsEUkgfgR73iR89ZWfu2aa/izEvQyhgfWXOFdxJScXQNsf5MmcZT46aft9nip5mPGsPC+9lrODBPn\nPp2IN8DTrFat4oJkLnINeWsFGGOnogkyVePpp6Ov3UTTFyoro9ezTkRPT6xNyOD7//2f3dbVxceX\nSHhnI/a/+EXeh9veSV/+gQ8Av/+93R5PeE+axCsRvPVWbHudjvC+/noehLv3XrtN+vovfIEH2WX5\nOCA2o6UIKXa7zggV3vlj82a2r3wJ76lTORh1yCF229VXcx/tagyp43DJJXabFFSU6bQAZwo2NXEw\nRH7D2LGcHQOwbwJwGntjY/RyzIUik+JqXwDwAoC/ApgL4GjwupuvEVFGFUiLhWQi7s47bYp5POEt\nF1O2xdXSHYHPJV4RsWQJp2q6x3LnnTz/7LTT7Db57eefb7dJWvpRR9n9jhnDzoYx1gBkObG1a3ng\nYs4cNqKyMhvpk5HpadP8539nwvr1LJzWrQNOOom3ifA2xl94pzOgItXM6+vtyFuxEgbbNsbcA+D/\nAfgGgJcBHA7gfcaY3fE+k26BnGHDYh1nOY8TJ/JAktDS4p9mDvA16hXebqTnr3+1j9vaEgtvt50J\nkttv5wqkbpqfOMnr19v/RZzVykrO8rnoIk69FVEQlPCOh6SWuWzdysc2dy7wpz/Z7ekKbxkUqavj\nlGYZeJH01mIX3qVq1wBnXZ14IvcJ7jmOl2r+3veyk3nNNTz49fzz9v1A6lGQmhqb3eHdDsQK3ltu\n4evHnUPstgV//7t9nCjiHa8AoB8f/zhH/d00bGnH1q61U+NcW/YjHeG9dSsHJlyeeoqP4Z577LYd\nO9gP+NCHOMNOBjbjVZcn4loSM2bEfme8VPMtW2whJkGm5bnXirRZ8+dz0EAcdqC453iHwa4zhUhT\nzfPBgQPs486enT/h7cfgwdw2u9rjggu4r3YHN6+5hqPjbhBLlnl0MxdnzuTfNXiw1Wxjx3L7t369\nzVgsFJlEvK8CcJ4x5rPGmG5jzHoAxwC4D8DTuTy4bCCiK4joHSLqIqKVRHR0ss8kE96ynuPPf27T\n2NxI1IYNdl7moEHZiULpSAZkMgs/D8ybB3zjG9GG8rvfcTViSUkHrBh3qwePHs0d9JAhdi3Oykp2\nKF57jT8zZAjv213aa906djzcNPRsxUgNGBcAACAASURBVMiTT7J4Ovlknq8nx9LXx+dv/Xr+Tomy\nA+kLb6LQLCMWCts2xtxijJlqjKkwxhxnjHkp0ft7e9MTgWPHWrEpiLN71lk8n0iugUSC2S/iLc72\nvHl2VQCAxV2iIl1BCO89e+wcdeGb32Qb/stfot9XV2fXzwassyriZvFi/k9kVYN8C2+/iPe2bZyF\nc9pp9riBzIU3wKnB//wn9xXioBS78EaJ2rUxduDrlFOsiAbiVzU//XQWv9dfz+dUbFCuiWTzspMR\n7xqSZXXuvttu27GDHcQJE+zyOgC3KfFEsLf+iLBrV3RWjjFW6LoDhQ0NXD8CsEuE5lJ4T5vG/bvr\nSzU3872bTr97N6e3ymC31IHp7OQ+3xvVToRfxNsYjqzNnx/dX8vAhwz8A3ytVFTwd556anTmRDFX\nNUdI7DoTX7y8XCPe+eDtt1lrFFp4x8P72eOP5xo4bjHcpUuBc87hwX9BdMfixVZDjR3LWTcbN9qs\n3EKRifCeZ4z5i7vBGHPAGHMNgPfG+UxeIaL/BHAjgOvAI4CvAniMiEYn+lwyQ29u5pSIy5yFGiRS\nu3Mnp04fFxlnTCclzA8Z7StW4e3H6NF88bvOy003sTP/kY/YbTI4ceSRVsxOnMj/72OP2f8Q4A5R\nBjBefZUj5LKMG5C9GNm4kfcp1RMB64C0t7PIOvZY/s5MhfeoUaFwzoEQ2HampOM8jR8fX3ifeipf\nj7IWdCKBGU94V1fz6gIiUoHkqeZBCO/58znq5DrJcm27QmDPHo7uVVfbYxZnXYT3IYewjWzcyM+L\nQXi3tdnI5KZNtqhWd3di4X3uuVYIANHn5qij7DyxEAnvkrTrnh6OeI8YARx9NA+Sir3FSzUXyst5\n7uCqVfw83mBMusSLeMtzd3Bgxw4W3UcdxVOSALbF9vb4g3B+Ee/ubh4Yc6M47ve739nQwMv7jBtn\nvzNT4f35z0dP4Whvt4XlpH00xka3X3opOrV/6FA+jokTud4GkPy8+VFVFTvQ4Q4outkE+/bx/FBZ\nCxhgP03asSOO4ONtaeHf0tdXvBFvhMCuM/XFNeKdH1au5P/68MO5TSwry+063tkK71RYvJgLrrnF\naE8+mdsWN01d1vMGuA0oJGkLb2OMT03Qf7/2TLzX8swyALcaY+4yxrwB4HIAnQAuTvShZBHv5mYW\nly4SHZNRZanKl05KmB8HD7JBpDPyW4yMGsWFl9zOVNJE3GJXkkL21ltsNEJNDXeCfX2cmivR9FwJ\nb3d6gCAOSHMzRwXknLqFc1KloSE00e6w2HZGpCMCx43j6JHrzIktS6EPKYyWKBVRBuVcmpq4DZk3\nj691EQqpCO+ensydkU99KnqOdmcnZ5309nLaKRC9xqUIEoDtb/RodkrFWZffJbYyZAhHmAolvKur\neS1id1kpEVNSu0Fei1dcbcgQ4MMf5sfuOsbuuZGVCcIkvEvVrg8c4Gtz+HC+Nnt77fUXL9XcZdYs\nO5XowIHcCCy5TrzCW8Ttiy9aP2PvXp7mdPjhNiV6/37+HelEvGXudGurrWsgwnPIkGhblqWDXFtO\nRXh7nfHGRuD73+cMAsEt3ipVhvft43Nxzjn8WP5v1yGfOzf6vKUrvGtrOYLuBk7c6P8//8n3vb38\nWyXKLoOI7rUiU982bLC/uViFd0jsOiNfXCPewfLjH3Pa9oMPcvRXCpm5y/rmgnh9bdAsXswDaB/8\noN0mA5NDhtgaVYUi5LIulsiahgsB/DvBKlLh8W8AEs57SSS8e3u5M5MLVJgwgRv5FSs4hWvcON4e\nT3jv28cd7c9+lvh3HDxoq26WGtOmsaOzZInd5s7dOvts+1iij/ffz52rLJGWK+Hd0hK9lAtgHZB7\n7mHnSOasS+fsl+rX0eF/vhPNAVbyR7rC2xge9NkdmWHa3s4DYRMm8DUpIi6RwDz0UI4cX3ON3SZi\ncO5c/g5xOBOllwLp1TRYtoxFqNDWxunjV19t7UW+F+BIFGCd9eOPjxawe/awQHjXu+znvKnmABc+\neecdfpzvuZHz5/PxH3usdZjFuZdOVuZ3JopurljBU4nWrbNzVV3hPX48Xwf19eER3qVKVxfb5fDh\n9hxv3sx21dmZPII9YwYLQZk2kIvssnip5u3tfG02NdnMC7kODzuMU8VbWmwfkijiLfVHBIncArG2\nfMIJNvoM8P9SWelvy+lEvN1pMvL98rtGjQLWrOHHUlDuxBP5XoqnusJ72jTbbmSSeVBby/7S3r12\nmwjviRPtgID8t4cfzuJe/hc34i1Rs7feKn7hXexk44sTqfAOio4O4L//G/jBD9ivliJmgF1yKxUO\nHOCpd1J81Y98RLxTZcEC4LbbeMpLtlOKsqXkhDeA0QDKEbv+ZyOAhLFH6cwaGvxTl4yJFd4TJ3Kn\n9Mgj0XMM/DpIgEeZ167l6uEvvBBf7Pf2hivNPF28v62ujqNMt94aLVTHjeNR/C9/medqSsQxXeH9\n3HM82OH9v/06+qlT+f6669hZkqVMZF6/39Kdxx7LQs07P6bI54j1G9I5B6ecYlOU7r+f70UYE7Gj\nuGULb08kMGVJvh/8wEbI5XqTa0zmHPb0JO6g/K53Y3jNWbfj27uXK4aedZZ1XCSNE8C/1zIXUTlk\nCLB6tf2NAF/Lzc120EGE99SpthKzN9UcYBuWzxw8mF9B+rWvAd/9Lh+XRLKk06+o4AGTVIR3WRlP\nAzDGiof2dvs7Bw5k8b11q7X1Um6nixm5BquqePB06FC+Pg8e5Gs/mcM3fTpfCw0N/JlcnMfBg/m2\nbZvtayR9XOqZiPiUaJDMV6yv9x/QcpH6I247INNiKitt9ooI72OP5f3K++XanzKFt/f1ZZZq7op9\nsTfpF485xv5GiZ4demh0ZXN3wFKEtwyApNtuyNJ/btV4Ed6nnWbbPPHpamq4LROx7wrvigru53fu\nVOGdAzL2xXUd7+CQPvqyy9gndtOx49WQ8OOBB1j3XHhh9EC9SzEJb4Az/0RDFJJSFN7xIAAJk8n7\n+rjzGDeOR4RdESWjud5Uc6naDQAf/ah9XFVl17p1kU5g/nyOkFdXc2GDSy6xzjyQO0cgLBCx6HZT\nPAF2cp9+mkenv/Mduz1d4f3Rj/Jgh1tJGvBvGNy5IO7a2xKFcEfWAbtEgTFcvdYlVymMSnak0/hX\nVfF6rgsW2AiSu8SPZLkAiSPe06ezs0dkxa/ML5Z17+vrrcOZ6DqR9Ev3em9s5Eq/F15oizGKiAas\nk+s6yfK6CO/jjrOrBYhjKoVHxHmW5bSmTuVrv7XVP0o2Zox1fvOdsVNezrZaXm7Tdt00Nzcanyyq\nNmUKO34yyOAdPJs0SSPexYA4iFKIU8RUqudFstMaG3M7UDRqFNvlL37Bz3t6eP/z5/NzN+orIhjg\na0rEXrw2RdogN7uqoYEHqxcutA6wK7wBtvEDB1jMyLSQnh7+7dKmxGsjhwxhe/cWTBs7lo9HxH5r\nK7dhhx9u2x4R3sOGcYaBtDVuvzt1Kv+evXszE96SsXbFFfb79uxhgX3oodaO3SVap02z213hDdjq\nxzLYoP13zknqi+tyYrmhvj7aJwCihffll0dPZ02nNpVMa5kzh23+zDO5VpJLsQnvYqEUpV0TgF4A\ndZ7ttYgdeYvitdeW4fTTuTrK9u1csOXaa5di6dKl/+7ovPMw589nh2/Romhnzu0gXef0zTdZaK9a\nxYVJNm7kC/jee/miXbeOnexSTjVPh4kT+f4DH+AiNEK6wltG46+/PnoNwHgNwyWXsJh254iUl/N5\n9Ua8JeKwYAFHyT/2MZsZ0dPj70isWLECK2RB4H8fo08oXckJmWQdHHKIdSC9wlvEXbKU6qoqtvfV\nqzkjRsRgWRkLuK1bU4us+F3vbgrpyy9ze+WmkP/zn+x4NjdbZ1s+09LCxzB/PvDnP9vfCNh5jtu3\ns6Pe08NtkgiELVts5+zOx/TOtcz3wOGQIZwqKkKgu9sOlNbV2UGBZM7AoEF8jsUx9w6uSGRfhXdh\nketVzuXYsXyOUz0vcm00N+d2oPuhh7gvuOsudm7lOGtr+dqRAXYZAKqr42tuyxabMh+vLZA26Pzz\nubrvkCEsEuvq+LOufQO2vsHWrTbLxhX7W7Ykb39mz+bf8NxzNmVc6t3U1dkBrb17WezOnGn3666P\nPmGC7Su7u22kWu7FptK1J/ERnnySlwlbutTO254yhQX33r3RwnvqVFu93Cu8x43j/1Qj3lmTsS/e\n0rIM//d/NVHLwS1dyr64kjpLlrCvsm2bDRKK8Ba7c4kX8f7e99guP/c5u23PHvZhVq7kFY1+9Ssu\nPvvEE7ZOUxiEdyF88ZIT3saYA0S0GsApAB4EACKiyPObE3127tzl+NSnFmDlSp5nvG6dLbYjo59e\nB37wYE7t9OIKbxlZl+c1NdyYn3MO3wDgyivZSV6xwq6j258i3vG4+GIWCHIehHjCe/VqrqB+3XW2\nknp7O3e6553H6TFr19q1AeNVOP7lL/2Px696skTAb76Z1xL84Q+5kjvAnbdf2qBfJ7JmzRosLPQ6\nByVKJsJ75ky75I5XeEsqaSpFxGbOtCLOjbZ6hXei/fhd767IXruWhXdzMzvD5eU2utTczANBbpRn\nzx5OqZRj6+21junkySyot22zc8orKqIjhPv3c0fsjpbX1vJ3SVtZiIHDqVP5uIHoTr+2NjrFN9k8\nUome+p3j4cN5X2FZx7tUcSPeAAvBpqb0hbd8Jlf97ZFHAsuXA//7v7Gp3OPGWfHpDsKlKvYWLeJ5\n2889xwP3555ri7RNngw8/ji/r6WF+yqpSbBjR3Rk27Xlnh621Xj2KgPeJ53Eg3Hjx9s2Zfhw26a0\ntvLzCRPYbtxoulQw94t4ZzsAUlnJ7ddhh3FNjaVL7XJy7gCDK7zHjbPrmHd08P8nSMHcVNplJT7Z\n+OJjxizH+ecvwHe/G/xxlgqujwKwLcnAxZ13cnsEWOHtzd4F/Od49/TYQsgf+IAdwGtpYbuprubI\n+aWXctt03XUsvI2J718XE4XwxUs11fwmAJ8mok8Q0aEAfg5gKIA7En3IGO78amo4VWzzZltEJN3R\nT7+UMCB2dFU45BBOPX/wQX7e31LN4zFyJI+yyai2EE94P/UURylvusluk7TgK67gtDR3LdV0R+SG\nD49NNZfns2Zxxfa77rJRv3wXmVL8ycR5mjaNHdYDB6Kr7Y4bx3bc2Zna+Z040V6Dbkc0ejQ7m5lG\nvOvrWbxPmWIj867IlgrCss2d1yid5pQp3NY0NEQXdpo4kQWsG7GSlM7du/1/tyxNJg5tIdqvcePs\nWumubbtp8KnY/Pjx/J/I8kjubx0xgv8/jXgXFsm6cAVcc3Pq56Wykt/T1JT7mgQzZrDt7NwZX3i7\nbcGoUam1BUOGsE9yyCEc8QZ4/5WVLLxFMLa3s0M8YAAPOu3cGT2IJkJTvjNR2zN+PPD1r/Pjhx7i\n+z17bDsjbUprK/tOIup37rSp3xUVNoUbiB7M8g6AZHIeysp44FGm8omfNWkSP9+61bZvlZXcHjQ3\ns317B+LGjLFtHKD9d5Zk5Itrqnl6bN7M9u5OjWxu5vuhQ4E//tFu372b3+vnE/lFvGUgG+DMXMFb\nOLi8nAX4c8+xDyDtsNpPLCUpvI0x9wD4fwC+AeBlAIcDeJ8xZnfiz/EFU1fHc6MmTAAefphfS7cR\nlvU8H3gg+kKOJ7wBTuOS+Riaap6YeMJb0vhWr7aOtjjiU6YAZ5wBPPqofX+6yx0kingPH85R9fp6\nG13TOd7FQSbCW1KxmpqiHUXpbFpaUot4u3PCXScvVWcbsIX93DnZEuk65BB7vUkhtOnTrfBuavKP\neI8YYZe6a2xkx3TIEFtAzBslGzqU75ua/J11afMkzbUQwttdg939r900+FQKHo4aZc87EP1+Fd7F\nQbYRbyL7mVwPdM+cyfdvvx1dBE6iqUB03yPXW6p+xpw5tligCO9Jk+y62W5Vd68tV1Twbx0+PL4t\ne/nqVzkjT4pEymCeO6goqebjx/PznTujv1MGHSQSJr9dBgGyEd4A9+/S/0uquTtYKAMPQ4faQcI9\ne2Lb8Joajo6r8M6eTH1xLa4Wn507edqa64eKbrj5ZpuJJX7pRz7ChULFH25ri790qd8cb/EZDjmE\ns2wE8SFcZH3sNWs0IywRJSm8AcAYc4sxZqoxpsIYc5wx5qXkn7HrLhNxBFqKIqWbdiRztb71LVvd\nGEi8TuWhh3In1tamEe9klJVxh+gV3vX1vEYpwGlngG1Iqqp4cGPtWj4PBw9y455OKsyYMRzRvvRS\nOyK7dy938gMHckVXwK4dqhHv4iCTxt+tlus6iq7wTuX8TpjAjt/+/dHO9siR1vEDEu9n4kReJgzg\npcHk+0eMiBbU4hBL1WLARqfGjbPr6soSWVJIUFZykEwdESSu4yxCRaJB3rZQallIh1+IgUMR3n19\nsanmBw/aIpmppCHHGxRR4V0ceCPeIl7TOS/uZ3LZ30o65ubNuY14C9OnRwvvYcOi2yt30Em+U4Sn\nn9hPpY+aOze6Qnh1NX9nezu3KeLQjx7N/6WIfemr6+rsEnCubQ4cyGI3W+E9ebLNUJJU80GD7LKQ\n3d3chg0cmDh7p7pahXcuycQX14g3s2sXT3t0CxveeSdwxx1cr0hwq4rLahwizM89l+9XreL7RMEC\nv4i3+BEf+xjvQ86L31K5U6ey/bzyihXeGkCMpWSFdyb09dmIEcBzm9assfP8gNQb4bIy4PnnudLf\nn/9sHb5EEe9DD+X7jRt1jncqjBgRvYQIwI3EokUsVKQBcsXDvHl8Pl9/PdYRSYVrr+Vze9ttdlBm\n714bkRQhJGuHxiuupuSXbIS3iOZMI96Seul1iL3OdrL93HQTF1WS6046vrFjbXq3CG8pAGYMO5E1\nNVZk79pl2yH5jY2N3OGK8JZjc20HYIc1nrPurfpfiParro47/JYW/8ESmd+W7HqQ3x8v4r1/v01d\nVfsuDH4R7+5u63Cmcl4kupnrge6KCraH3bujhbcM6Bw8yLdMhfeMGZziLXPIJX0asANmMsAvA3xe\nW3YHl1Lxa6ZNs054Rwd/p9umSJS5rMxO7ZDIO5G1wb17Y9tN+f3ZRrz7+jg11vWzJHVc2gOiWOHt\nHosIb/EP1L7zT3+MeO/cCdx3X/S2667jlX4k8xYA/v53vpepJgAPwh15JF+rEvSRfnjuXLYv8YcT\nTbWqquKMOje9vKWFtx9/PLc1Mq3N9XsFIs7GcWugqI6JRYW3gzHRHdbMmdyAp5MC5vIf/wH86Efc\nGchal4mE9+TJfL99u6aap8Jhh3ERM6lOCtj023nz7Oi8my572GH8eP36zIT3okXsNIwYYVPWvQ3Q\n1Kk25U1TzYuDTJwncc68EW851yK8k51fV6i7Ua6RI1m8/X/2zjxOrqrM+78n3Umns3Rn3yAJshNZ\nE0AYZVMBEUEQtx6XAQdfdXTGia/LDDOOjvuCRlwY348yCDLGUdxwRRERQUQlyJqwJmTfOkl39qVz\n3j+eerynbt1bdWu5XfdW/b6fT32q+9atc09V3eec8zvPc55jnrsk98nRRwcdny+8N24snjicOjUQ\nh7azgg2SN2wI2qFRo/T89euLo3HihLfv8Q7XN+zxbkaH63/XfnSBTQrYBGil79pEnIXNh5OrAcGk\nHwcWzSEsvG2pg61tTGLzFlqZxr7zJvj8tcUTJ6qd2eRAraHmM2dq37J1ayCCba30pk3FoeYWoRHe\nNqxaj7flT7B9yceOLW5T4q5pbYovvMOD//Hj64/08xPG2SQAEPwOfnvgrysPt+G9vfoZrR1j/z38\niLS2x/vhh4GvfrV4cuGf/inYrcCwSXZfkK9dqxMTDz4YtIG2DfKJJwZh59bGTJigUaC220c5Z8EF\nF2h7Mnt2IL5tXGDbIZpTybdtH4uwsc/G/rEUCm8PE97+/pKAhovVGnZ0+OF6c9rNWk542xZUaaw5\na0Vsq6++viAUxxqJ448P1qPt3q0N+ahR+t1PnlyasbkaOjt1uxgr3wYhhh/my1DzZIjINSJyr4js\nFJEtMefMFpGfFs5ZLyKfEZFEbVgttjR2rN4bGzfGe7yTrBe2CJqwGDR7t4RDSYX3qlV6n/vC2wbh\n5t32vfXmyY4S3oCe63unrG5RwnvCBO3QoyYcshBqHh7cW71tTZvtX57E4w0E+SHCoajVlNXOpGnX\nYeFtkyvV/C4WWplGf2t2tWOH2kJXV3B/Wri5Pwln7QlQuS3wPbbm8e7qCrzsfmSNebzD/d2ECUFI\ndVLhbSHl1n6EPd6+yLb2zr8eEC+8d+yoz+NtNtvfH4SaA6UebyCw4YGB6FBzKwfgOKwZdHTkU3j7\nTjbjd7/T3CyWCwEAPvxh4B3vKE5WZhnIbXtPINgr+/e/D4719+u2XQcPBjub2NKPY48N8r1YPzx+\nvOoQW45WzuN97rnAZz+rf1siRbPrSZN0bGHJFOPKMeHNUPN4KLw9THhbR+EL7717y2+5EceIERp6\nYftrlhPenZ3aYW3axFDzJLz97ZoFfv36oLGx7/eww7TR8rOWiug5hxxSmjiqWnzP4969xWXMmRN4\nvCm8EzMSwHcA/FfUi4WB+M+gWyCeAeDvAFwJTdpSufAaBnMiweDU/41HjdKOqFqPt4V7WvtiHrqk\nXlhAO1BAJ3a2btX6WYI0f5227623gfnkyfqZwsJ74kTtpP0Z7ClT9BzrvH0BGzdYt/Ka6fH2oxGi\nBto2mE76m9mkiD+5Yt9RNSHNbUxqdh1e420TPxalkMSebPucRq/xBoJwa7M/P9zahLdf9927gz4p\nqfDevDko346b8I4SweFr7thRnfAGtG87cCDayx6+pj+ZF44U8vtMq0sjhPfmzcXtm01qhNeVjxkT\nTCKGQ82B6iInSGMRyV6o+TPPFE8GbNkCvPe9xdt6fvGL6pT5wQ+CY9dco3tdf+MbwTET2RY1OTQU\n5Gy49159tpwkZ5yhY02bONu8GXjRi/TvpUv12YT3kUcGyVcHBvRYR0dx4sE9e+KdBSL6mU49NaiH\nTWKJFO9iUEl40+MdD4W3x8GDxQPjiRP17zVr6hNQfuZPfyY2CltDyVDzyogEWRQfeEAnTizEbM4c\n/Q5tL1Hfq21ZpmsJNTeOPlrFfjhDq5W/fn2QQZkdd2Wcc//pnLsOwCMxp1wI4FgAb3DOPeKcux3A\nBwG8U0QqNu21/gb+er9wuLF5Syp5vP0Bp38v2mDZBnhJEjfa4Hft2sDjbV4n2/7Lkh4BOvC3UPPO\nTh2EhgemEyaU1s0GsRZu5k8WRHmJAC2/uzsbHu+NG9U2w8I7aXK1sPfU/6zWftu+wLTveNK06x07\ndGLbBnZmT1n0eNv9ZNEvFkkRbgvMdpLuQW7lmy3buu1w2Pfu3aWTaLUKbxvYjx2r31lPT2lYuW27\n6R+ziUazTb+9a4Tw7urScuzz23dibVa4n45ry+jxbj7D6fH+y1+K1zQfOKD7Vi9eHBx75BEVtf/8\nz8Gx664DPvc5fRjmJf7Wt4Jj5rX+zW/0eedO3XFk7NggLLy/Xz/vWWepmD54UPsq5/SYcyrMd+/W\ne/uww3ScGfZ4H3mkjj137AiEN6DC2/r98KRXFCefHIh6f0LN36Y0bo/umTODyT+AOiYKCu8Q/uBT\npDjpSa3C2zysvjCMw9ZQMtQ8GRMm6GBm+XL97Zwr3r9z5crSBqIRwnv2bL1eeCYd0Po4pw0f13g3\njDMAPOKc2+wdux1AL4DnV3pzrbZkwjvsFRk7NliTWOn3tcGpZe0ND7ajxF0c/uD3wIFi4W0D4p6e\nwLu9Zo1eM5w0zW+HzOPtD9ZtkGwe3yjhHbcPqHmCm9F+jR+vnzscyjt2rB5P6sUqNyli3xs93g2h\nZrveuTNIlgUE97h5vJu9xttCvH2PtE0MxQnvLVvUbkZUGJlNmqSfe9Uq7Wvs/b7g9YU3EO1lr0Z4\nm5fdQlb99mPLlsoe79Gj9WFtSqM93kDQvvkOjnLC29p2LiXJFtV6vIeGNNePL9bvvVczf9suB4B6\nc08/PTi2a5cmJZs9O1jmceedwKc/rVt2WR3+53/0+dvfDpY1WrIyPzTchPA99wROmZUrVfg++KAe\nswSfL32pnn/gQJAv5KyztE5r1hQfA9Trbf3RlClapol6i3Szce+aNcV9vH+8XKi5cdhhgZ375cya\npfY7NKTfYVQ5kycHW/UB1DFRUHh7hD3eQLHwrmUvYEBvVvOaHzyYzOPNUPPkWPiLhR76wtu8gP5v\nOm1a/B69SfGzQYdFmXk1tmxhqHkDmQFgQ+jYBu+1WEQqD2Tj8D3eficzdmx04q04Jk0KBtvh0Nhq\nhPe4cdrB2mz0xIl6bNy4YOmDhZdNnhzMTtu1/IFplMc77J2ybOm+57jcutBx45obaj5ihH6esMgQ\n0bonDTUvJ7ztO0rqnSRlqdmud+woFW9AdcLbQs3TmOi2CS2LOLFjQGlbYLa4dWuydsDs2wbHfvkm\neMNJzdau1bKtLaxWePf26nUtZLXSNcNRNIDaZpzw3r69McI7HNGTxOMdZd8W0cJx2PDjbyd23XXF\nCXQff1yF4aJFwbFPfQo47zzg+uuDYwsXapj3Lbfo/4OD6p3+058CsfzrXwfn/+EP+nzfffq8d28Q\nEm5LRTdtCvrUhx7SyMf167Wf3L9fbezCC/XY5s1qK85p0rQtW7Rfsj7l7LP1PU8/HS2y7djzn6/3\n8vLlwXsnT9ZIWvPUm8fbX3YWlUzQduqoNGaZO1fPta0Co/IlANHCOzwBSo93KRTeHjZD5XcUFrqV\nZC1nHIccokZoDXm52aZGZPdsNw47rFR4T5yoBh/OZgoEXoF69un0E1VFebyB5Ps8tyoi8kkROVjm\nMSQiRzfgUq7ci/XYUU9P9DrAceOqW0va21vqPa5FeAPq9bZ9O21QPWNGsfAGdHIoSnhv3hzt8Y5a\nf75+fbFXsbdX37tzZ2Xh3awOHLMYQAAAIABJREFUN0p4A9q21urxjgo1b1ePd1bs2jzeht3PtYSa\np7HGO0p4d3frdWxQHdUWJG0HpkwJ1luW83j7tuyPbeyzJx3bjBhRLPb99mPjRnUWRAlv39Fge2oD\nxe2pJVerd9wzZUpp+9bbq2WHJ2p6e9W+nSv+/PYdcSlJ8zDh/cADGt593nnB+O6GG1TQfupTgUfa\nhPRNN+nztm3Btlq23toyhANB2Pfjjwe7DZi4f/hh3ZFoxIjAq/3008BrXhO8PjSkzjTbI/svf1HR\nffAgcP75euyJJ4KJ6xe+UJ+ffTZY7nTaafq8cmVw3qmn6vPq1cH4YvLkIErTdkjo6QmE94EDer+H\nhbevZfz8B0k83nPnBnULJyo0+wKiy7Hxh9WfOqaUXH0lInINgIsBnAxgr3NuUsQ5swF8FcC5ALYD\nuBnAvzjnKq4YCSdXAxoTam6zTTYYLDfbNHZsEPrGmaJkzJqlM5LWGFgiiEmTgszM4Vl3E1NA44W3\niaF69yVtAa4FcGOFc55NWNZ6AKeFjhV+hRKPWRFDQwtx6aW9Rcf6+vrQ19dX8aI9PdG/8dixwQA/\nice7p6d0sB0WCkkjL2bODDLq2702fXogvG3GeerUQHj7a0xth4XwILmnpzQL+IYNxbbjJ4SzqA+f\n7u5ggNSsDtcyO1t9/ONJPd4jR+rvEeXxtjIHBkqjKRYvXozF/uJAAAOm0FuHTNj1nj0LsW1bLy69\nNDjW1dWHrVvVrqsJNU+jnZ4wQQfo69YF9ieifzdCeE+dGghvXwSHPc1+9ErYy3zggArSasR+2OM9\naVKQw8YPb9+1SwWQLY8Bij97VKh5V1f9Hm9LUmXfibVlGzeWTgKYxzDKvk14m323iW0nIu2xeEeH\n3pt+GPfPfqbi99e/DpKIPfKIbqH12GPAvHkq1LdsCZZdvexlwJ//rH8//LD+/ldcEWQJX7ZMkx93\ndwd96sqVusZ52zYV3ra++uqrNRna009r/3LwoAr0ri7te+3eOu88tfNly4L++fTT9fnZZ4N+0ba2\nXbMmsMHJk/U969YFSzvGjQuWq9pODnZs1apAjI8fH/Th5vEOC+/+/vLJ1QwT8LZbgf0/bZr+LmEn\ngk9YeFPHlJIr4Y0gQ+p9AN4SftHLkLoWunZsFoBvAtgH4N8rFW6h4GHh/eST9YWaW3Ilm9VKIrwZ\nap4cC3/xPd5AEK0QJbydqy9raU+P/o7lQs1tgNGuHm/nXD+A/gYVdx+Aa0Rkirce9AIAAwAeL/fG\nMWMW4bbb5td00XJrvG2wmeT3HT8+GLDavdjZqWVW6/GeNQv47W/1b9/jbVlIfY+3JW/x13jbujA/\n1Hz7du3UbfBg54e9ZFb2pk064x5m9OignWtWhxs3uB87trrwcEvUBBT/NiNG6HcyMFBaTtSEzpIl\nS7BgwYIqP0V2yYpdA4tw2GHzcdttwZEZM6r3eDunNp6GxxtQe7OBN6D3Z3gJR63C20Jhwx5vP5dE\nnMfbn/ibNSvZNadMKb3mxInA/ffr3+Hw9nXrgCOOCN5vE5lAtPDu6alfeJs3Myqp27HHBuf29gZb\nP/nfeUeH1mFwUJ8t2qcdbLsKUh2Ld3Wp4PvLX9SD/Oyz2r9dfrkus/roR4EPflDXUltEw//5P+od\nf+CB4B579atVLFuI+OGHq1f5f/9XBeRTT2m4+LhxQYj5ypXAJZfolrTLlgVidc4cFfxPPRU40Q45\nJEg4ZhNMhx2mfePy5YEDbdYsbZueeUZtyLYWnDpVxxHO6f8iQVZwSxZo71+5MhDZ48YF2/uZCLb8\nJjNmlArvUaP0dVtiWcnj7W9X6EeP2HEbQyQJNaeOKSVXoeZpZz6O2tfZEqTUE2pebmuaML7Hmzds\nMiz8xRolayT8vYjDwhsIvGK1bjVl5Ye9oZZBupr9mdudwl6+JwGYC6BDRE4qPCwV4S+hA/FvisiJ\nInIhgI8C+LJzbn9MsQDqDzXfskUn5MKh5tV6vOMGnNUm8fE9SHYv24w0ELQ306YFM+R2zO5Zq5P/\n2rp1gZ10dGjdwoN1G8Ru2hT9uUePDq6ZBY93PcLb95CHP+uYMVpWG0ezJCJNuwZKB37+EpAkv42/\nnjct4b16dTAYBcpHvyRd4w3oAN68sr4I3ratOKGbDcjD0Su1hrebk9fanokTg0nIsPBes6Z04i7K\nNm07tb1767OpKVOCftcPNQdKPf5+2Hv4848Zo+MJjsGiSXss3t2tgu+hh4CTTtItte67TwXuvn3A\nggXACSeoyH70UX3P5ZfrfbRkiYrjGTOCbbceflhF7+GHq4d83z51qFnis+OO09DwXbvUNufM0Uma\npUsDkT1zJnDUUcXCe+ZMLfOZZ/Re6uhQu5g9W8Xppk3a544YESRD6+8Pkp9aCPnAQHCfzpwZbA1q\nfbSd53u845IdTp4cbF3q3+/miEoSat7bq/e+hZX724wC5YU3Pd6VyZXwTkBdmY+j9nW2ULR6Qs1r\nFd68YZMxbZoKIwsbCwvv8Lp9GzDU65G2rKjhhszCCav1ZLY5HwGwBMCHAIwr/L0EwAIAKISnvQLA\nEIDfQ8PWvlE4vyz1Cu8472k1v6/NNgOlg98tW4o9K5Uw4d3TE1zblj6MHRvc/34ouEVhWMgZENiB\nPe/dWyqyDxyIFt4DA9Gfe/TobIWa+7+ZiWUgeSK7uNB02wOYwrsiqdk1UDrw6+6ubm2uvT8NkWX9\n/r59gcgFiid0wsnV+vur83gbvsfbsi6b2B8xIlhDHZeMrhrhDeh3a2VNnBhcMyy8w5PefjRKVHj3\n9u31e7yNsPDesiU6uVq4LlYf83iTmqhrLN7drfflc88BxxwDnHmmRifYmut583S/7CVLVHj39qrY\nPeUUFeNPPqme7COP1N/84YdVtB9xhAp2QMtbu1ZF9nHHaf93zz362uzZKrzXrw8Smc6cGYS4r1un\n/fX06Sq8n31W+5wpU9Te5sxRUb9pU2CntiZ78+bgPvWFtz+Jvm5dsfD2tyYcPVrbKuvfTXiHt/IL\nj3vNiZgk1FwkyJcQ3iEAiF7KZdgOIsxqHk+rCe+aM6QC0R5vE8L1hJpXI7xN6DPUPDnlZv42b473\neNsAoNbO1c+WGv5Nq/WutTvOuauccx0Rj7u9c1Y5517hnBvnnJvunPtAkvVi9QrvAwf073CoubUX\nST3eRlh4b90a3YHFccgh+jzJW1VnHm9/4Gkd86hRpWu9gKATtfYJKF0DGa6v/zmiBuvd3cGsfDND\nze038+s+ZkwwKZDU421CIHwPjR1bv3euHUjTroFS4W0TIkAyu7f379jR+N/StytfeJsN+RnGR43S\nR7Wh5oa/xjvqmlG2XKvHG9A+1CYK/Wv6XnDDb1P89sP/7fx11fW01377FhYLQPFWrv7x8Oc34c0x\nWM3UNRYfPVrXXDunYvmMM3T5xC236L01Y4YK78cf1zXcJ5yg9+OCBYHwPuoo7YOOP15F9ooVKpIn\nT9bQ7dtv13H27NkqvAHgl7/UZxPeQLB0YcYMLXP1ahXaU6Zom3HEEfr/xo1Bn+t7vM1OTWT39wd2\nZMe2bSvv8Z46VduozZsDu7VrhfM8RCVYBLSs7duThZoDxYkKzZb8fAn2O4UZMaI48og2VErThXdW\nMqQCgcc7LLz37NHXavVcdnfr4Dypx3vfPr0mb9hkWMNma2j9WXdrgMJZzYH6Qs2B4vW/UQPAarxr\nJD3qFd5G1KAVSO7xNqK8TtXsJT+/sFzdZpSBQHj7Yte84M5r+XyxHvZ4A8UDU/vsUR5vIN7jbaK3\nWe2X/9tEZb0Gknu8w2UY1sZQeDeXqHYX0HsvSQSJ3dtpLO3ybSXs8fav7Z/jXPIJfl942/fg27J/\nTTse1fYcPJj8PjbB4H+2qDbFF95xE3dRwtu59DzeQPRkBBC9lKTeuuSNLI3Fu7uD8fgRR2h4eHc3\n8NOfqrdbRL3bBw4A3/++imtAhfezz6on/OhCTU86Cfj5z3VcffjheuzEE4PEbXPmqDd63DgV44AK\nZ3v/nXfqPT56tApvQD3jFnl2+OFa10cfDWxyzhwV6Bs3Fgvv1auDUHM7FvZ42xrvsPAGVGTbPWy2\nGOfxDo97x48PIjSTtDFTpgRrvK1su3Y54W3XYqh5PFmQdpnIkAoAu3cvBNCLa64JGuXDDusD0FdV\nOFYU/v6VlYQ3oAbid14kHn892ciRQWdpDdDo0dGiads2bRRq3eO5t1cbl6iGbMyY8ttNMUPq8NEo\n4e2LZ1/E1evxBqoT3jYg8BM2zZunzzb7DQQz4vu9lbL+wDS8xhsoHkRHeclGj1b72r8/XngbzQw1\nN8Kh5kbSxFtAdDSCldtOA/MsEv5t7P+kv0ua9+vIkUHSsCjhHbU+fcuW5NEvNvAGor3Pvh2U83iH\njye5pt/m+df0rzNqlIod3+78OkWFmgP1r/E2rI22LdwOHIj+ToBojzfQds6PzIzF77pLx+IiwDvf\nqff37Nl9ePLJPpx5pp5z4onB+Sa853s5VE85RZ9POkm3IAOCRH8nnqhJ10aMUDEtol7vP/1J7yH7\n/efMUe+5lWvvv+eeYNswE/O//71mTAdUuO/bp157O3booTquX7ECePGL9dghh6iI3bRJk7IBOom+\nY4eGwVsfHiW8Ozu1P4/b2cC50mUeq1Yl93hPnBisFbeybdlKVL4aH8uRYPXMMs0Yizf9K8lOhlQA\nWARgPr761SD05Cc/Ab70Jb0BLcSzFuL2rwxjN/jAQPZv2KxgM4WrV5eGklnSirB4ENHGqZ5OvqdH\nG9GohswPNY8SKMyQOnzUM+PqC2Z/oFqt97SS8K4m1FxEE8GYRxvQAcHxxwMXXxwci8o67gtva1/8\nulUS3iJ6fn9/eUEKNDfU3IgT3tVEKVB4Z5c4j3fS36VRgi+OMWNKhXdUJAkQtClJJ+F8j7cR5/E2\nW47yeEfVJQ4TthbVAhQLbytfRI+HE7pV8ngDjfN4270gEuzZHefxjhPe7WTfWRqLX3bZInzxi/Nx\n1FGBZ/ob3wCuugp43ev0/+5u3ZLrsceACy7QY8ccE5Rhe2LbM6AZyIFgnffkycF43IS3CWk7tnJl\n8L7p04Plp77HG9DJ6Dlz9G973rCh2OMNaHI22xP8kENUIC9bBrz0pXrMyn3iCV1TDhQL79mzg/pN\nmxbv8faXmAHanw0MaD2TtDETJgRb84WXi4STQ4bxtxXNuse7GWPxpoeaV0PaGVKNqIHx1q21r/EG\nipMrJRHe27ZReCelq0t/s7DwnjBBRfG2baXiwdag1BPF4E+mlFtr2E6ddxZplMfbH7T5fydpF6IG\np3451Xi8AfV6+wNHQPc0/dSngv/nzgU+/nHgC18IjvkeIcOP+PCFd5xAsOv6tmb45zar/bJ6d3YW\nd/p+fRvl8WYb3VyikqsB2fB4+/XwJ4OsLYgKNY86Hkctwtsvu7s78JQnvaYJEP97i4vM8z3Oht+e\npuHx9oV31ERpnMfbP9evD+07mrTH4vb9+yL4yis17NkX0rfdpp5rCwHv6NDQ8698JbgvzzhD+7gL\nLwzGe+bB9st6wQv02e5xIBC+dkwk8Hpb3caMKV7b7T8DxcnVDD/UHNCoSTvPhLdlRPfLWLOm+B6e\nNk11hUjxcpO4UPMkzj+jt1e97vYZjbiEsz5Z2N0ky+TtK/kIgDd7/xdyHOI8AHc75w6KyCsA/Bc0\nQ+pOVJEh1Yjb67IekVat8B4czP5MUZaYOFEbCd8L6GdgjPIuVJvUKkxvb3SGVr98gGu8m00awrta\nj7cvaKPEYLXCOynXXFP8f3e3DgBs2UuYSh5vIPhO/M7YyILH2wZcQ0PFx/36JqlbuUkReryzQZzH\nO2m7nrbwtjL9tsPuz6hQc6B677M/oPc/Q6VQcxFtf3bsiLblKI49VsWOv+93VGQNENhGXKi5P+Hn\n16seB4ffLvvfhV0rzuMdFt5+rgASSapjcbsf5s6NPm4cfnixOAd0WzEfkdKtH+fNU++2eb4B4A1v\nAD79aQ1tN844Q0X8RRcFx0xk+0u9xo0LtiEDiieATDT7NmPn+bZjeVr87ULNxseMCTztfh9tdRkz\nJphEmzBBvdrhZStxW/nFMWFCoFnCwnvpUr1e3NjHF97UMaXkqllxzl0F4KoK56yCbk9SM1HC20I3\namX8+GCtZbmOxV7bvZuNfjWY8A57vI2oQc769aVew2ro6dEZWKDU+8fkatkh7VDzJANFv7P0qSXU\nvF6eeiroFMPErdf0scFzlMc7C2u87TO4UAofGzyMGpUs8RZDzbNPnMc7qT2lHaERTkoEBG1B+B6s\nti0YPRr4138F3vSm6NejMnhH9YM7dlTX/lxySfH/ce2frfH0vX9+e+oTXgpWK3F2bX1AnMfbP+7X\nh/YdTdpjcZs0tczi9RL+fYFibzeg94Ml6DXe8AYV3b6Q/shHVHiecUZw7KKLVKDbWnP/PrSIZf8e\nN6+5P0Y14d3Toza1d2+pgA8LbxP1cePe8KRXEg0SVU5U0lVbshlFd3d+1ng3g1yFmg8XUcIbqD/U\nPEk5/mu8YZNjg+2o7ZCA+PV09XSsfvlhj4FtNwRQeDebWpPnAcUDRf83brTwTsvjHcXo0aUh5zYQ\n8OsRF2pu7VJWhXfcd12tF4vJ1bJPIz3eaUx+LVqkIbK+Z83uz3pDzQHgE58I8tEYn/2srnX1782o\nrQOBoO2q97P/6lfArbcWH7OIL98jGSWAwtevty6jRgGvfW3xMfvOo9baA9H7eAMcgzULE3S+uG1W\nPXzxC+ie4qtXF4//vvSl4qzpAPDmQjyA9a0+dswXria8RYL7z++nTWTHebyNuASLcblP4ign4CuV\nMXq07pYA0OMdBYV3iI6O4g6r2m2D4rCbtbOzvBDwOwDesMmxxiZu5i9ukFPPb+p33FEeb4OD8+YS\n9nxWg39/+HbrtwtJft8sCe8o7rwT+Pa3i4+Z/cQJ76jwVP/cZrVf9l2Hbdu+66QTMeXaCArvbFCv\nx3vkyOB+SMMGL7wQuPHG6FDzsPc3ak10Lbz3vZqsyccG+H7yKSCw0Xqv+dKXBtmbDdsOyhcPcR5v\nvy2p93fYs6e0LTOhE5dgMey5o8e7ubziFcBddzVfeCdFpPReueGGIMGY8cMfapvg28Fphdzvfoi5\n3ZtRIetRwtsX1f64N25Xlmo93uFQc6Cy8DY4eVUKhXeIqOzURiOEd6Ub3n+djX5yokJumunxrjaD\nMkmPeoR3HP59lkTIxQ1ssyK858wJssUal1wCXHst8La3FR/Pi8c7bHdmr0nvB2uzbebeh8I7G6xa\nVfx/tR5vIBBdw2WDNqANe3/TXHZi2//4Yd9AILyTrvGuhu9/H7j66mJRGye8fVut9/OLlArp179e\nn8Peyzi4xru5dHQA55zT7FrUR2dnqV298pWaDM7njjuA7363OFniq1+tz7YWHAjajSjh7bddvmD2\n25i4HQXi8K9TrfDOQpLVLEPhHSLc6Hd1BQNrCu/sYknV4kLJ4jzejRLeYRHSqAkbUj9pC+8kiGgi\nleuuKz5u92GSNcfDzaRJwP/9v6XbKCYV3vWE+NeD2WXY7qw9SHo/2MBjcLD0NQrvbBAWUtV6vH2G\nS3jbAPuyy4qPxy3taARvfrOGsp58cvFx+8xpXPPyy4Gvfa34WNw4yG//0vgdXvlKXXMaTtYVBz3e\nZLjo6QmEtvHlL2sGc9vbGwiWq/hC1oS3H12WxOOdxMb8iYAo4V2uzchCktUsw7mIEOGbyTJ/bt/e\nmDXelTo4Cu/aMOHtd6xxWVOBQDQ0KtScHu/W5cEHdU9Nn3AW3CSEvXNAkOnUsuPngXKh5n6H26zJ\nBLP7D36w+Hi1iRQtUc7TT5e+RuHdfH78Y+D884uPWZtczb033B7vKVM0KWe4T7IJrjT6i5NPBtat\nKz0et7VZWli/G7cFWZp1qabN5hpv0kxEirOgA8C7361ZyaMyrPtj3ag8LUD1oeZWdricakPNKbxL\nocc7RFSj34j1wDYLVclTRuFdG/a9hhsrI27rluHwePN3LI+IzBWRr4vIsyKyS0SeEpEPi8jI0Hkn\nisjdIrJbRJ4TkfclKb/eAfXJJ5eGYVfr8Y5j3jx9Xr68MeUNB0mFdzNxDvjnfy4+Vq3H25LdlAs1\n58A8nrTtetas0gGkCTpbX5yENNd4xxE1zrAwcNsNYziwcUkaoeZRiGgUzU9+En9OFtoQerxJ1uju\nBj73ueh137649ScdG5Vcze/nrB8tJ97NfkaMyGY0X7PhsCFEVIfYCO9o0rVFHR16kx84wEa/Gqwh\nCa9hM+LW0zXK4x2+b+jxropjAQiAtwJ4BsDxAL4OYAyA9wOAiIwHcDuAXwJ4G4ATANwoIludc18v\nV3g4g3cjsI6uXhs1cZeFwWZS7F6P6lCHc1u0arGJsighHYWI7lkclZWWHu9EpGrXUdQivEeO1IzE\nzbZBawts79zhwL6v4ZxAuvba8q8PZxvy5jfrbx/G+m9660iWmTgReMc7gH/6p+jXozzVQDKPd9xS\nsSQT2JyYLg+/lhBRN6QJ73pCzU14Jxn0dXWp8OZNm5y+Ph1AXXxx9OtHHVX8fyOSq5XL4Ox7RNl5\nl8c5dzt08G2sEJFrAbwdhQE6gDcCGAng751zBwAsFZFTALwHOpiPxV+r1EgGB+sPERcBfvnL0mzD\nWeazn9X16v76M6PZ4qUcNtlWzZr/8J7FBgcWlUnbrqMwIblnT/L32G/Y7HvXEinZEofh4KyzgJtu\nalwETyMYzt/hppuij1vfnnSSjpBmIAJcf33p8VGjdELJ1yzVeryN8NjZhHfUhFW4fI59o+GwIUTU\nQKqRHu8kg76uLt2GgN6U5HR0lIYD+4RD6RoRal4uhGa4QvdamAkAtnj/nwHg7sLg3LgdwPtFpNc5\nNxBXkHmSGs348fH70lZDeJ1q1pk2Dfj4x6Nfa7Z4KYcNAhqRbM8+ZxqJ+1qchtl1FJYQrxrhbX1A\ns+/dyZOBtWuDfCXDwVveApx7bvH+w80mC1EzWagDIbVyzz2aKd3HH+smbevWrSsdy1obu3Vr/PuY\nI6E8uVrjnfaaMSBaXNusUT3C28Jdk3q8AQrvRvDpT2tSijA2mVKvQI7roCm8a0dEjgTwLgBf9Q7P\nALAhdOoG77VYLr+8cXUj5Wm2eKnEMceUZpavBbPvcrP+pJhG23UUtXi8syK8Ad3Ldzh3AxCJXkrR\nTLLwO1i/nsYypbwzHONwUh+nnQZ85jPxryfVMjNmlG4BeMop+lwuLw093uXJ23xE6mvGom5I65jr\nCTW3AQGF9/Dy/vdHHzePd70ey2XLorMeZyl0r1mIyCcBfKDMKQ7Acc65J733HALg5wD+1zn335Uu\n4ZUTC9fYDx9Z9xQtW9aYcswruWVL+fNakazYdRRm60lzqgCN6d9J/XR1AXv3Nm8bwnBdgPSWKeWc\nYc/dQBrDy1+ufVY9Cc9Gjwbe9CbgBS8ofw4ADA3Vfp1WJlfCezjWjEV1vtYx1zOA7+jQ9YJxSRCi\nrkfhnR4mjOsVCnPmBGvzfOjxBgBcC+DGCuc8a3+IyCwAdwK4xzn3ttB56wGEgzBtw4uwx6yIhQsX\noje0l1RfXx/6+voqVI1USxa8VcNBXCKsxYsXY/HixUXHBgaqipbOA5m26x/9qA+nnlqhdh5Z8ni3\nM0ceCTz2WLNroQwO6rMvvNvEtivSjNwNpDH89KeNKefmm8u/buPq/fsbc71WI1fCO4aGrhmLEruN\nWOMNaIbcJDQqYzKJp1HCu1L57Yxzrh9Af5JzCx6xOwH8CcBbIk65D8DHRKTDOWfzqBcAeKKSTS9a\ntAjz589PXnFSM+0iXuKEd9SEzpIlS7BgwYJhqln6tJpdU3hng1/9CnjwwWbXQrGJm1e9KjjWDrZd\nB6nmbiD5wtpSbiUWTQaCemonjTVjUeL63HP1uVwygUZioVYU3umTlvCmxzs5IjITwF0AVkJnzKeJ\nyHQR8T1h3wKwD8B/i8g8EXkdgH8C8Lnhri+Jp13Eiy1V6U8kP9uTvNg1hXc2mDlTQ2GzwOzZmjjx\n6KObXZPsMxy5G0i+sLY0C8tGskgmPN7ZWTO2EPfc04tLLw2O9PX14S1v6cPq1Sg6niYU3ulzoDAP\nG04c0ShsYB4Hw9aKuADA4YXHqsIxgdprBwA45wZF5EIAXwbwZwCbAXzYOXfD8FeXxNFOWUyPOQZ4\nWzhwmvjkwq7f9jbgXe9qr3uXkDDZGYdzeVjeMYdWHoR3M8biWelqMrFmDFiE97xnPhYuLH0lbvuc\nNLABAIV3epx/PvAf/6EDrjTo6gJ+8Yv4GXOGrQU4524CELOjatF5jwA4J/0aEVKZRiVqa1XyYtfv\nfKc+CGlzMjIO5/KwvJOnrObNGItnQnhnZc3Yd74DXHFF8nqnhYW7cwY+PUaOBP7zP9O9xoUXpls+\nIYQQQki9ZGUcTvIPQ83Lk6uvJe01Y0cckY0bhduJEULyyty5wLXXNrsWhBBCGk1ecjeQ5pGnUPNm\nkDefai7WjNWLebwpvAkheWPFimbXgBBCSEq0xTic1A6zmpcnV8I7L2vG6oXCmxBCCCGEZIl2GYeT\n2mGoeXn4tWQQhpoTQgghhBBC8oSFmuchuVozoPDOIPR4E0IIIYQQQvKEOQ/p8Y6GX0sGofAmhBBC\nCCGE5AnzdFN4R8OvJYOY8OZNSwghhBBCCMkLf//3wOLFza5FNslVcrV2wYT33r3NrQchhBBCCCGE\nJOXrX292DbILfaoZZNo0fabHmxBCCCGEEELyDz3eGeSaa4DnPQ846aRm14QQQgghhBBCSL3QpzoM\nLK5yoUNXF3Dllck2n6+27GpIs+y0y89r2SQ/5Pkey2vd81o2yRd5vc9YdnPKJ/kgr/dwXstOu/y8\n2nXuhLeI/EhEnhOR3SKyVkRuFpGZoXNOFJG7C+c8JyLva1Z9gfzeeDTI4S+7XaFdD1/ZaZfPsomR\nR7sG8nufsezmlN9u0K4g8eFEAAAgAElEQVRZdhbKz6td5054A7gTwGsAHA3gVQCOAPBde1FExgO4\nHcByAPMBvA/Ah0Xk6uGvKiEkIbRrQloP2jUhrQftmpAayd0ab+fcdd6/q0TkUwB+ICIdzrkhAG8E\nMBLA3zvnDgBYKiKnAHgPAObZIySD0K4JaT1o14S0HrRrQmonjx7vvyIikwC8AcC9BWMHgDMA3F0w\nduN2AMeISO9w15EQUh20a0JaD9o1Ia0H7ZqQ6sidxxsACrNr7wIwBsB9AF7hvTwDwLOht2zwXhuI\nKHI0ACxdurSxFS0wMDCAJUuWsOxhLD+PZXv33+iGF54DaNfDU3ba5bPsYmjX+bJrIJ/3Gcse/vLb\n2bZTsGuAfXZLlZ12+bm1a+dc0x8APgngYJnHEICjvfMnATgSwEsA3A3gJ95rtwP4r1D588JlhF7/\nWwCODz4y8vjbZtsk7ZoPPhr+oF3TrvlozUfubRtNtmvaNh8ZfKRi11K42ZuKiEwGMLnCac+64rAV\ne+8hAFYBONM5d7+I3ARgvHPuVd455wL4NYBJzrmSmbbC9S8EsALAnlo/ByF1MhrAYQBud871N7ku\ndUO7JgQA7dp/L+2atBItY9vNtmuvDrRt0mxStetMhJoXPlitH66j8NxVeL4PwMe8JA8AcAGAJ+KM\nvXD9b9V4fUIaye+bXYFGQbsm5K/QrhXaNWk1WsK2m23XXh1o2yQLpGbXmfB4J0VETgNwOoB7AGyF\nhrl8BMBUAMc75/aLSA+AZQB+BeDTAE4AcAOAdzvnbmhKxQkhsdCuCWk9aNeEtB60a0LqI2/C+3gA\n1wE4EcBYAOsA/BzAx51z67zzTgDwZQCnAdgM4IvOuWuHv8aEkErQrglpPWjXhLQetGtC6iNXwpsQ\nQgghhBBCCMkbud7HmxBCCCGEEEIIyTptL7xF5J0islxEdovIHwrrV6ot40MicjD0eNx7vUtEviIi\nm0Vku4jcKiLTypR3lojcJiJrCmVdGnHOR0RkrYjsEpFficiRodcnisj/iMiAiGwVka+LyNhKZYvI\njRGf5WcJyv4PEfmjiAyKyAYR+YGIHB16X8XvQURmi8hPRWSniKwXkc+IyAgR+dcE5d8VqveQiFyf\noPx3iMhDhc8zICK/F5GXNajeb69Qdq11bnvbrUTWbDundj02oe3VaiPX0K5p19VAuy56XzvadRL7\no23njHay6yTl12HbHItn3a6bvXdgMx8AXgfdsuDNAI4F8P8AbAEwpcpyPgTgYWhyiWmFxyTv9f+C\nbo9wDoBToNnyflemvJdBk1VcBt338NLQ6x8o1PMSAMcD+CGAZwCM8s75OYAlAE4F8DcAngRwS4Ky\nbwTw09Bn6Q2dE1X2GgBvAnAcNJHGTwqfuTvp9wCdCHoEugfkCdBtJTYC+BiAnyUo/zcAvhqq+7gE\n5X+78L0cWXh8DMBeAMc1oN4XVyi71jp/rNn2k+UHMmjbyKdd34JktlerjTydoGzaNR+0a9p1NfZH\n287RA21m1wnL51i8Re266QbXZGP/A4DrvP8FwGoA76/B2JfEvNZT+HEv944dA+AggNMTlH0wwiDX\nAlgYusZuAK8t/H9c4X2neOdcCOAAgBkVyr4RwPfL1OfYhGVPKZz3oqTfA4CLAOyH19gCeBs0c2Zn\nqB5F5ReO/QbA58vUvZry+wFc1eh6+2U3us58FH1vmbbtvNp14Xhqtk27pl2Xe9CuadeV7I+2nb9H\nO9t1mfI5FnetaddtG/oiIiMBLADwazvm9Ju8A8CZNRR5VCFk5BkRuUVEZheOL4Dul+5f5wkAK2u5\njog8D8CMUHmDAO73yjsDwFbn3IPeW+8A4AC8IMFlzi2EkCwTketFZJL32pkJy55QOLal8H+S7+EM\nAI845zZ75dwOoBfA80N1DJdvvEFENonIIyLyCRHp9l6rWH4hJOX1AMZA96JsWL1DZft7BNZVZ1JM\nHm07R3YNpGvbtGvadSS061ja1q4B2nbeoV2XhWPxFrTrzmpObjGmAOgAsCF0fAN0FqUa/gDgSgBP\nAJgJ4MMA7hbddmEGgH0FowxfZ0aV10HhPQ7R9Z7hnbPRf9E5NyQiWxJc8+cAvgdgOYAjAHwSwM9E\n5MxCY1ixbBERAF8AcI9zztbXJPkeZsR8LnvtoTLlA8D/AHgOOhN5IoDPADgawKsTlP8CEbkHwGgA\n26GzastE5JR66y0iQ9CGwy/7iQbU+a/fCSkij7adebsG0rVt2jXtugK061La1a7j7I+2nT9o19Fw\nLN6idt3OwjsOgRpUYpxzt3v/Pioif4T+gK+FrltpyHUqkKS8iuc4577j/fuYiDwCXbdyLjQUI0nZ\n1wOYB+BFFeqTqE5WNe9vK/+FRSc493Xv38dEZD2AX4vI85xzyyuUvxLASdDZuysA3CwiZzeo3sui\nynbOLauzzo28f9qBPNp2luwaSNe2addB2SQ5tGulnew61v4aVG/advNpW7sGOBZHC9t124aaA9gM\nTWgwPXR8GkpnNarCOTcATXJwJID1AEaJSE+DrrMeeqOVq/f6wv9/RUQ6AEys9pqFG24z9LNULFtE\nvgzg5QDOdc6tDdW70vewPuJz2f8bCtfyy19Xofr3F579useVv84596xzbolz7t+gs1fvbkS9nXMH\nYsqut8513actTB5tO9N2Xfg/NdumXReXHVNGu0O7rkAb2XU5+6Nt5wvadQI4Fm8du25b4e2c2w/g\nAQAvsWOFsImXoDjmv2pEZBw0NGRt4RoHQtc5GsAcaMhDtfVeDr0B/PJ6oGs6rN73AZhQCM0wXgJt\nKO5HFYjIoQAmAzDDKlf2KwuP85xzK0NFlfse/HqfICJTvPddAGAAwOMFQ48rP4pToDNRft1jyw+9\ndwSArkbUO6JeVnaj60yQT9vOuF3fX8H26rWRt5UpOwradRtCu070OdrVrgHadi6hXSf+LByLt4pd\nuwZlJczjAxp+shvFWxj0A5haZTmfBXA2gLnQlP6/gs6ATC68fj10nca50AQB96L8dmJjoeEQJ0Mz\n9v1z4f/ZhdffX6jnJdC09j8E8BSKtzH4GYA/AzgNGgbyBIBvliu78NpnoI3HXOgN/mcASwGMrFD2\nE9DsfmdBZ4HsMdp7X9nvAWoED0HXtpwIzdC4AcBHC++NLR/A4QD+HcD8Qt0vhW5pcmeC8n8HDcWZ\nC90W4pNQA39xA+r98biy66zzR5ttP1l+IIO2jXza9TdRwfbqtJE/lyu7ThuhXbfYA7Rr2nUF+6Nt\n5++BNrPrSuWDY/GWtuumG1yzHwD+Abov3G7ojMapNZSxGLr1wW7o+oRvAXie93oXgC9Bw0S2A/gu\ngGllyjsHaohDocd/e+d8GDqLtwuaWe/IUBkToHt1DhSM5GvQDH6xZUMTDvwCOpO3B8Cz0H3zpiYo\nO6rMIQBvruZ7gDY6PwGwo3BTf7pww5ctH8ChAO4CsKnwnTxRMKxxCcr/euGz7i589l+iYOgNqHds\n2XXWeUSzbSfrD2TMtsvZXobtekwl26vTRmjXtGvaNe26KhsBbbvlHmgju65UPjgWb2m7lkJhhBBC\nCCGEEEIISYG2XeNNCCGEEEIIIYQMBxTehBBCCCGEEEJIilB4E0IIIYQQQgghKULhTQghhBBCCCGE\npAiFNyGEEEIIIYQQkiIU3oQQQgghhBBCSIpQeBNCCCGEEEIIISlC4U0IIYQQQgghhKQIhTchhBBC\nCCGEEJIiFN6kIiJyjogMiUhPs+tCCGkMtGtCWg/aNSGtCW27NRDnXLPrQDKGiPwGwIPOufcU/u8E\nMMk5t7G5NSOE1ArtmpDWg3ZNSGtC225NOptdAZJ9nHMHANDQCWkhaNeEtB60a0JaE9p2a8BQc1KE\niNwI4BwA7xaRg4Wwlr8r/N1TOOfvRGSriFwsIstEZKeIfEdEuguvLReRLSJynYiIV/YoEblWRFaL\nyA4RuU9EzmnWZyWkXaBdE9J60K4JaU1o260LPd4kzLsBHA3gEQAfBCAAjgcQXpMwBsA/AngtgB4A\nPyg8tgK4CMDhAL4P4B4A3y285ysAji28Zx2AywH8XEROcM49k95HIqTtoV0T0nrQrglpTWjbLQqF\nNynCOTcoIvsA7HLObQIAERmKOLUTwNudcysK59wK4I0ApjnndgNYVlifch6A74rIHABXApjtnFtf\nKOPzInIRgKsA/HuKH4uQtoZ2TUjrQbsmpDWhbbcuFN6kVnaZoRfYAGBFwdD9Y9MKfx8PoAPAk37I\nC4BRADanWVFCSGJo14S0HrRrQloT2nbOoPAmtbI/9L+LOWZ5BMYBOABgPoCDofN2NLx2hJBaoF0T\n0nrQrglpTWjbOYPCm0SxDzoj1kgeLJQ53Tl3b4PLJoRUhnZNSOtBuyakNaFttyAU3iSKFQBeICJz\noTNgI6CJHWrGOfeUiHwLwM0i8l6o8U8D8GIADznnfl5flQkhFVgB2jUhrcYK0K4JaUVWgLbdcnA7\nMRLFtQCGADwO3TNwDkozKdbClQBuLpS/DJp58VQAKxtQNiGkPLRrQloP2jUhrQltuwUR5xrxGxJC\nCCGEEEIIISQKerwJIYQQQgghhJAUofAmhBBCCCGEEEJShMKbEEIIIYQQQghJEQpvQgghhBBCCCEk\nRSi8CSGEEEIIIYSQFKHwJoQQQgghhBBCUoTCmxBCCCGEEEIISREKb0IIIYQQQgghJEUovAkhhBBC\nCCGEkBSh8CaEEEIIIYQQQlKEwpsQQgghhBBCCEkRCm9CCCGEEEIIISRFKLwJIYQQQgghhJAUofAm\nhBBCCCGEEEJShMKbEEIIIYQQQghJEQpvQgghhBBCCCEkRSi8CSGEEEIIIYSQFKHwJoQQQgghhBBC\nUiTXwltE/lVEDorI571jXSLyFRHZLCLbReRWEZnWzHoSQsojIm8XkYdEZKDw+L2IvMx7nXZNSM6g\nXRPS+nAsTkhyciu8ReQ0AG8F8FDopS8AuBjAFQDOBjALwPeGt3aEkCpZBeADABYUHncC+JGIHFd4\nnXZNSP6gXRPSwnAsTkh1iHOu2XWoGhEZB+ABAO8A8EEADzrn3iMiPQA2AXi9c+4HhXOPAbAUwBnO\nuT82q86EkOoQkX4A74V21rRrQloA2jUhrQHH4oRUT1493l8B8GPn3J2h46cC6ATwazvgnHsCwEoA\nZw5f9QghtSIiI0Tk9QDGALgP6imjXROSY2jXhLQcHIsTUiWdza5AtRQ67pOhhh1mOoB9zrnB0PEN\nAGakXTdCSO2IyPHQAfloANsBXO6cWyYip4B2TUguoV0T0npwLE5IbeRKeIvIodB1I+c75/ZX81YA\nsTH1IjIZwIUAVgDYU08dCamD0QAOA3C7c66/yXVpBssAnARgAnRd2M0icnaZ82nXJA/QrmnXpDVp\nS9vmWJy0OKnada6ENzQ0bSqAB0RECsc6AJwtIu8C8DIAXSLSE5ppmwadaYvjQgD/k0aFCamBNwD4\nVrMrMdw45w4AeLbw7xIROR3AuwF8B8Ao2jXJObRr2jVpTdrNtjkWJ+1AKnadN+F9B4ATQse+AU3Y\n8CkAawDsB/ASAJbQ4WgAc6ChbnGsAIDjj78FN910XJnTamPhwoVYtGhRw8vNc9lpl5/HspcuXYo3\nvvGNQOF+JBgBoAuavOUAarTrW265BccdR7servJZdjG06xIybddAPu8zlj385bexbac6Fmef3Rpl\np11+Xu06V8LbObcTwOP+MRHZCaDfObe08P8NAD4vIluh68m+CODeClkU9wDA+PHHYf78+Q2vd29v\nbyrl5rnstMvPa9kF2i7ESkQ+DuDn0O2HxkNnGs8BcIFzbrAeuz7uONr1cJbPsmOhXefAroH83mcs\nuznlo81sO+2xOPvs1ig77fLzate5Et4xhNeLLAQwBOBW6Kz6LwC8M0lBna3wbRCST6YDuBnATAAD\nAB6GDs4tW2rNdk0IaRq0a0Lag4aNxQlpZXIvNZ1zLw79vxfAPxYeVTEir5urEZJznHNXV3i9Zrsm\nhDQH2jUh7UEjx+KEtDKUmh4U3oQQQgghhBBCGg2lpkdHRzrl9vX1pVNwjstOu/y8lk3yQ57vsbzW\nPa9lk3yR1/uMZTenfJIP8noP57XstMvPq12Lc7Fb6rUNIjIfwAMXXPAAbr891YX6hMSyZMkSLFiw\nAAAWOOeWNLs+ecfs+oEHHkg7AQchsdCuGwvtmmQF2nZjoW2TLJC2XdPj7ZGWx5sQQgghhBBCSPtC\n4e3BNd6EEEIIIYQQQhoNpaYHhTchhBBCCCGEkEZDqenBUHNCCCGE5IGtW4GlS5tdC0IIIUmh8Pag\n8CaEEEJIHnjhC4F585pdC0IIIUnJnfAWkbeLyEMiMlB4/F5EXua93iUiXxGRzSKyXURuFZFpScqm\n8CaEEEIag4j8q4j8UUQGRWSDiPxARI4OnVNzn93u0NtNmkWaY3FCWpncCW8AqwB8AMCCwuNOAD8S\nkeMKr38BwMUArgBwNoBZAL6XpGCRhteVENJkduxodg0IaVvOAvAlAC8A8FIAIwH8UkS6vXNq7rNJ\ne3DDDcDPf97sWpAQqY3FV69ueF0JyQydza5AtTjnfho69O8i8g4AZ4jIGgBvAfB659xvAUBErgKw\nVEROd879sVzZ9HgT0np84hPA2Wc3uxaEtB/OuZf7/4vIlQA2Qgfq94hID+ros0l7cPXV+uxcc+tB\nAtIci7/ylfytSeuSR4/3XxGRESLyegBjANwH7cw7AfzaznHOPQFgJYAzK5VH4U1Ic0gzJHXZsvTq\nTQipigkAHIAthf/r6rNJ63PgQLNrQCrR6LE4Ia1MLoW3iBwvItsB7AVwPYDLnXPLAMwAsM85Nxh6\ny4bCa2XhdmKENI3UQlI5oTb8LF0K3Hxzs2tBsoSICNSG73HOPV44XFefTVqfPXuaXQMSR1pjcUJa\nmdyFmhdYBuAk6Oz5FQBuFpFywaQCnWUvCwfohDSHNENSOaE2/Fx4IbBqFfCmNzF3Bvkr1wOYB+BF\nCc5N1Ge3Cs4B+/cDo0Y1uybZY/fuZteAlCGVsTghrUwuhbdz7gCAZwv/LhGR0wG8G8B3AIwSkZ7Q\nTNs06ExbWe64YyEuvbS36FhfXx/6+voaU3FCCixevBiLFy8uOjYwMNCk2mSSRCGpImKha7HCmxNq\nw49NdmzdCkya1Ny6kOYjIl8G8HIAZznn1novrUeNffbChQvR25vN/vq97wU+97nk61Q/9CHgox+t\nbl2rf+7Bg607wZgV4c0+u5S0xuIAx+JkeGiGXedSeEcwAkAXgAcAHADwEgA/AIDCOtE50HUnZbng\ngkX42tfmp1hNQpSoTmTJkiVYsGBBk2qUHRodktqqA9I02L8fGDmy/nJmzACeew5YsYLCu90piO5X\nAjjHObcy9HLNffaiRYswf342++vPfa6682+9VZ8HB4GenmTv2b+/+O+uruqumSb79wOdnY2JdsmK\n8GafnYiGjMWBRbjttmzaNmktmmHXuRuSisjHReRFIjK3sL7kkwDOAXBLYVB+A4DPi8i5IrIAwI0A\n7k2SHfXgwXTrTghJhIWkJpnerhi61tkq04sps3Onhrr+93/XX9b06fr83HP1l0Xyi4hcD+ANAP4W\nwE4RmV54jAaAevvsrJPUgz1xoj5Xs42SL0h9EZ4FRo0C3v3u5Of/+tfA8uXRr2VFeJNi0hyLE9LK\n5HFIOh3AzQBmAhgA8DCAC5xzdxZeXwhgCMCt0Jm3XwB4ZxPqSQipkjRCUp97jmFrSbDoquuuA97y\nlvrKMu9bu+2hznDUEt4OnRi7K3T8Kmg/DrRwn71zJzBuXOXzJkzQ51WrgHnzkpXtJx3LmvAGgC99\nCfjiF5Od+9KX6uTDli2lr/nCu5VD6nMIx+KE1EDuhLdz7uoKr+8F8I+FR1XQ401I80grJPWIIxi2\nlgQb4D7+ePnzkmBCoN22AmI4ajHOuYoyqZ4+u9msWqVe6jNjNkgaGEgmvG2pejUe76wK7337anvf\n1q3Rx8Oe/SyF1LczaY7FCWllcie804TCm5DmUAhJ7QNwKQohqYWXBpxze5xzgyJioWtbAWwH8EUk\nCF0bGkqz5s3HOf2M9YbU2wC3EWLZBt/tJrxJezFvnkZ1xIWUDwwAhxxSuZy9e/V5167k186q8N6+\nvbrzd+4s/7ovvA8coPAmhOQbBu0QQrLA2wH0QENS13qP13rnLATwE2jomp13RaWCW114v+IVgces\nHhq5ltKEBIU3aWUqLaVIusrAyqnGW9wqwnvz5vKvh4U3IYTkGQpvD3q8CWkOzrkRzrmOiMfN3jl7\nnXP/6Jyb4pwb75x7jXNuY6WyW92uf/Yz9ZT5A/Fy3HEH8IUvlB63AW4j1lBaXVp90oO0Bxs2aIbu\n+++Pfr2cxzsJrSS8/cmIJPa/aVP51ym8CSGtBIW3R6sP0AlpR1pd/E2erM+PPprs/PPPBxYuLD1u\nYa6NyALfyLB1QprNgw/q849/HBzzxbZFeISPD4Y3P4yhlYS37/H2v5c4zOMdN+FH4U0IaSUovD2S\nbv1BCMkPrT6hZkK50lrJStgAtxHC20QBB8okTXbvBs45R7ejahQDA8BvflN8zLyyfqI0fz2279n2\nBXES4Qm0rvBOEoVjSdXi9vzO8rZphBBSLRTeHhTehLQere7xNnFbazZhwwa4I0fWVw5A4U2Gh40b\ngbvv1u2oauHRR0szib/iFcCLXwwsWxYcsz2mfbG9bVvwty+8/VDrpELRxGo1NpxVT3C1Hm87f2go\negyW1c9J0qOjo9k1ICQ9KLw9Wt0zRkg70up2bYP7pN41I3y+DXAbMeih8CbDQTX317p1pQkETzgB\nmD27WPDZdnr+2mMT5xu9jBJJhHdSIW3vqcajmwePdzXCG4j+vii82w/u1U5aGd7eHvR4E9J6tLrH\n2wbd1Xq8w+tPzZvXiMFtKydX27AB6O9vdi0IEH+vPvww8MMfFh877DBg2rTo8zdsCP42e/KFtf3e\nvhj3xbZvS/6SjyQ2OTQUiMt2DDWvJNQpvNsPerxJK0Ph7UHhTUjr0Yriz6eaUPNyiZ9sgNuIQXyr\neLwfeaRYlAHAJZcAU6ZUt+cySQf//rLIloMHgZNOAi6/PHht3z597NgRvMe/z22dsX/cF9Zbtuiz\nP+HiC3Pflqr1eFcr1I2sCm//81fr8a4kvLP0OUl60ONNWpnc3d4i8q8i8kcRGRSRDSLyAxE5OnRO\nl4h8RUQ2i8h2EblVRGLmugNaPSSVkHak1e26mlBzf1Ac3uqoFq9bFM61jvA+8UTglFOKj/3pT/oc\nXhtMohGRs0TkNhFZIyIHReTSiHM+IiJrRWSXiPxKRI5MUnaUeF6/Pjhmtr9uXel5fti4Hdu/P7h3\no4S3LwJ94e3bXrVCupbQdCC7wrueUPMoD/nu3YEHNO/tSSuR5licwpu0Mnm8vc8C8CUALwDwUgAj\nAfxSRLq9c74A4GIAVwA4G8AsAN+rVHAWPd4/+lGpx4UQkpxW9nj7A/VqvWtxHu+4JEdJ2b8/EDx5\nGii/+tXR2bF90eZDj3dixgL4C4B3Aii5s0TkAwDeBeBtAE4HsBPA7SIyqlLB/v1lYeArVwbHbKuq\nNWtKj/m/qwlrew0oFtb2elxyNV8wmpAeNao64T1yZHXC27flrAnvri79O2mouWU0jxLqe/YA48fr\n33lqT9qA1MbiDDXPJnfcAXznO82uRf7JnfB2zr3cOfdN59xS59wjAK4EMAfAAgAQkR4AbwGw0Dn3\nW+fcgwCuAvBCETm9fNnp1r0WLrsMeNWrml0LQvJLK3u86/Gu+X8DxaKinoG8P9jO4kDZOWDRotL1\nut/7HvDWtwbHKn0HFN7JcM79wjn3H865HwKI2jTq3QA+6pz7sXPuUQBvhg7QL6tUtn9/mWj2hffa\ntfrsC28LF/c94+bxjlvDvWUL0N1duoXYlCkqEnxPuNnkpEnV2WTS8/3r9PTo31kT3lOn6t9JPd5T\npsSfv3s3hXcWSXMsTo93Njn/fOB1r2t2LfJPK9zeE6Cz6IU5aSwA0Angr74L59wTAFYCOLNcQVkb\noFsnY4MHQkj1ZM2uG0m1wrvc+Y1aS+kL72ZHGzgH3HJL8edZvhx4z3uAf/mX4JhtHTVhQnDMvJzh\n8oxwhmxSPSLyPAAzUNxfDwK4HxX6a6CyxztKePsebxH1TNtvbWVMnBh4tPfsUcF96KGlHu/eXmD0\n6FKPt4i+Vo3wnjixOuG9Y0dwv2ZNeJcT0tWev3t3NicYSAkNG4tTeLcfu3cDDz7Y7FoMD7m+vUVE\noKEs9zjnCpuAYAaAfYXO22dD4bVYsubxtkHycNfrrW8F3ve+4b0mIWnRbPGXJr6QrnaNd9x2YkDr\neLz/8AfgTW8CrrsuOGYi26+nHTPPGlDs/bTP4X/f9Hg3hBnQwXp4QVXF/hqI9nivWgUcfrj+bd7t\nNWuAuXOLz1u/XrOcT51a6vE+4ohg7bGJ8ijhPWFCtPAeO1bDrav1eFdjdzt3qlgHsiVId+yoTngP\nDJT3kNPjnX0aPRYn7ccllwDz5ze7FsNDZ7MrUCfXA5gH4EUJzhVErC/z+eMfF+LSS3uLjvX19aGv\nr6/mCtZDs4T317+uz5/97PBeN+vcd58Owi6+ONn5d9yhM3hRkxiLFy/G4sWLi44NhLNdkYZAj3dA\nuUROrSi8TTQ9/HBwzPZp9u8LCzv2TdBf72veRX9dL4V3qlTsrxcuXIh9+4L++vOfB8aN68Pq1X04\n8kj1dpugXrtWhffWrcFvuG4dMGOGTsz5Hu9Ro4CZMwNb8YX3734XXN+Ed3d38T0/MKDHq13jPWlS\n6fKPSu/LqsfbJjmSrPHetg045hj9u5LHu5ntCfvssjR0LD44mK2xeCty6aU6Pl21Ktn5aesQy6/i\nXJDzYThohl3nVniLyJcBvBzAWc45Pxh7PYBRItITmmmbhtJZ9SIWLFiE226rf8plcFAzph6ZKC9r\nPM0S3iSav/kbfRtQ7zIAACAASURBVE76e5x/vj5HCe+oTmTJkiVYsGBBHTXMLyJyFoD3QcPTZgK4\nzDl3W+icjwC4GhrSdi+Adzjnnq5Udrt4vKsNNQ8PcnftCrx3jRDenZ3NF96WedzPYG0DjagkXP66\nX19479xJ4Z0S66ED8eko7p+nASgbeLho0SJs3DgfF10EjBsHXHQR0Nen6/dPOEG9wSa816wBDjkE\nWLGiWHjPnKm/o523ebN6X8ePD8LUTXjPnq338/79mgjNBHbY420h6EmFt3nWJ06MXt4Qh92TQPaE\n9+TJ+ncSj/fWrToBEnf+7t362wHNbU/YZ0eTxlh87NjGjMWzxD33AFdfDTz2WPLkcVu3BlEtjebH\nP67ufL/vS5OhIR07DBfNsOtchpoXDP2VAM5zzq0MvfwAgAMAXuKdfzQ06cN95cptlMD9m78Bjjqq\n/nKaIbyTdJT18P3vA1ddle41wtx6K/CTnwzvNX04cZKI1DIft4PwHjOmulBzkWiPdyPWUprnfNy4\n7AhvP4O7hRP7ezLb3/5Etx9qbt8zhXdjcc4thw7Q/f66B5op+ffl3rt/f3B/zZgR/F6rV6tInjCh\nVHj39ga/8fr1KrwnTSr2eE+dqvdulMcbCH73uDXe5glPKry3blW76+6ufo332LE6SM2S8B4YULHQ\n2Vm5TRoaUtusJLwt1DxLn5OkNxZvxSi1T3wCeOKJ4gndcnzzm9o2ZWVXo/AuKGlR73ameSB3Hm8R\nuR5AH4BLAewUkemFlwacc3ucc4MicgOAz4vIVgDbAXwRwL3OuT+WK7tRAumxxxpTju+dGi7S3pv2\niiv0+cYb072Oz2teo8/NEsDmGSHxOOd+AeAXwF/Xi4X5a+bjwjlvhs6aXwag7AYXrdiJG9ZGJE3M\ntGOHeuu6u6PXePf2qne4ns7PRMi4cc2f9LD2zBfMJtCiwsr37FEx19lZGmoeLofJ1ZIhImMBHIkg\no/nhInISgC3OuVXQtaH/LiJPA1gB4KMAVgP4UblyfeE9c6b+Xvv2qaA+9NDA4+2cCu9Zs4qjFtat\nA847T/+2Nf7r1wPTpxcLb5uUmTVLn3ftUjuJW+Ntx/fvTy68J05MLtSNnTu1niNHZkuQ9verxzv8\nvURhNji9MIrjGu/8kOZYvBX77DFj9HnDhuB+L8cvf6nPW7cmO79WkoZ2p9nf+WPzffuC76pVyaPH\n++0AegDcBWCt93itd85CAD8BcKt33hWVCm6WsV90EfDtb5ceT1N4L1+ug4dwxnTzELQiSYX34GD5\nsJqk98nIkfqclRnLvFJv5uNmi780qXbrop071UsWNchvlMfbBttjxzZ/oGzZrKOEtz+D39+vIgYI\nQn83bw5CAu17NqEwaRI93lVwKjRs/AFoNMvnACwB8J8A4Jz7DHQ/4P8HteluABc558re0fv2lXq8\n163Tdt4X3tu2BeHK5vF2Lgg19z3edizs8e7tDWzD93hHCe9q13ib8K52H2/zeGdJeFsG+EmTNLlc\nJY+3jTfKebwHBoLQ9Wa3J6SIlhuLp4kvvJNgQrdewTs4WH5cn3Q5c5rC228/28HjnTvh7Zwb4Zzr\niHjc7J2z1zn3j865Kc658c651zjnNpYrV99XXV3+8AfgppvqKwMAfvELXZsWJs1Q8x/9SA3yrrui\nr5l2coO0Q9qjSNrgzZ1bfl2NDcwrMXasPm+seOeRCtSV+Rho3XD/HTvUOztuXPKte8aNi864vGtX\nY4V3VkLNR4woFt4bN6qN79oVfM7+fuCww/RvX3jbMT/UvKtL2wcK72QU9vCN6rff4p3zYefcLOfc\nGOfchUlyN0R5vC3CYfbsQHjb5MshhwQe723b9P6fObN4bfW6derZ9oX3pk2apdsGzrt2aXuyZYsK\nzHrXeDfC491sOzPse5w8uTrhHefxPnBA7XHaNP0/KxMMJN2xOIV30KYkHW/GYZOLcfhLrsqRpvD2\n+1IK7zaj2sH5mWcCV15ZfMz3UifxtJW7ydIU3tawhZM8mAEkTf4Qx9q1wJ/+FP96vY1JFP39wJ13\nxr+edI1KpSQSSaMCzOPdylEETaZidlSjVb3e5TzYUQwMBKIgKtS8kcJ7/PjmC4LVq4HnP18/2969\n2pZu3hwkvvRF9vOeV3xs06ZAePuh5hMm6CCKwru5RK3xtsR5hx6qYm3TpmLhbSHi69YF75s0Sdvo\ngwdLPd4Wpn7IIcUREf39ev2ZM0uzmteyxnvixGRC1WdgQG0sSx5vE95RExJR2HKOqVOj14SbN47C\nu71oxYlya6v8BJ7lMKFb71i5Uj+VdM15mv1dtUli807u1ninSSNm2Xwj2bMn8HrGUS7Mw27GNESD\nfdbwZ7Zr1iu8X/c6zeK4a5cOTMJs3x7s9VkLUetSzjgDePppnVG0jtqnUV72rVuDAXk57Hrt0JCk\nTM2Zj5WFuOyyXozwphlbZWuSWoX30FB0qHlvYQeXVvB4Dw5qO3P88cAjj+hnHzVKP9uRR+r2JfZ9\n+Dbti/FTTtG/fY93WHgfPKjZsmfNAn7wA245NFz4oeaWnfyhh1TE9vSoqF63TvuEkSNVjFvCteXL\n9X2HHaaTMwcOaJZ784Lv2qXH9u0LhLdNSm3fXizcR48O+nHnVOxPnqzlJhXehx6q5STto/bv1/t7\n6tRsCW/zniX1eNtStxkzos+3SevJk6MTQpLWpBU93tavJBXS1QrvLVuA978f+NKXgjF3kv43yZZ/\nfn3SgMK7jalmli3uXN9Idu9ujPBOY/BqN3f4+o3yeFsH+tvfAi97mf7tf2f1ZkgcMQL4t38DPvax\n4NjTTwdlm/D2v7ukDUwUfjlJ91q177gdGpI0cc4tFxHLfPwwUJT5+CuVS1iE//3f+RVtMY+Y8I4K\nHY9icFAFxI4d8cnVgPqFd0eH1imNyJakmKfz+OP1edu2YLLOPN6Wz+HgwWjhPWuWCptywru/Hzji\nCOCHP+SWQ8NJ2OMNAL/5jW4lJqLHBgeBv/xFf5/OThXVGzYATz2lQnfWrCAM889/1ufDD9eJFEDv\nhTVrgNNPD4T34CD+Ook3c6aWY16s7dv1vpg1C1i6NJlN9vcn9xD77wFUkGZJeJv3rBrhPW2aToiN\nHl06uDfhbaH4WfmcJF1a0eNt/UrS8aDd60n70E9/GrjhBuBv/xZ48Yv1WFyyZH88m9SmfNscGqpf\nI/gw1LyNqcbYfWPwb5Sw8K6EL3zD1zeBl0ZnYx1aOKy6UV52y0Lqh1n7nXBS4T00VLq3qQ2ob7gh\n+j3+9+7/HtV6vP1ZV19sJ/097HocLFRGRMaKyEkicnLh0OGF/2cX/rfMx5eIyAkAbkaCzMdGq4aa\nb9+uthYVOh6FH2rut1tDQzrob0SouUW5dHY293u3QYcvvC3fwhFH6PPAQCBi/FBz81xOnaoTG2b/\nW7cGwtvaGWuf0tpvlURjwrujAzjmGD12//3B721i/Le/BY4+Wv+eNUvfd//9KrBHjAh+N1sadcQR\nwbHNm0tDzQcHA4/3zJl6f1i/6R9PYpPO6X1qHu+kXiUTuFOmZEt4r1qltm/J1SpNJKxdG2SL979H\nwxfe1SafI/mllT3eSe9hs4WkwtsmC30dEbfMsRYPs982NdoO/fqk1ZZl6Z6i8Pao5ofxBatvGOFQ\n80r4AjTcSdvNmMaNaIPFsPC2mSdbD1kr9tn9may476kcn/2szp77Dcj99+uzDbDCxF0zye/hn+P/\nNnETLXHs2xd8fxwsJCKVzMdGqwrvbduqS8xkwjvsjbL725Z/1NPmmFe9s7O5oeYmvOfN0+dt24KM\n5r7H20SM7/HetUvbgilTVHBZW7x5s7ZH3d1BO2NtU7kENqTxWKh5Z2fx0h/bIsyE91NPARZwYCLv\n9tuB447Tv+13+9OfdKKlpyeImHrwQR1wHnWUCvxx4/SeWbFCzx09Ws+3vsIX3v7kTBz9/WqHJryH\nhpLZTFaF98qVwJw5GnGQJHR+zRr9roBiOzPMtmzNfFY+J0mXLImkRmFtRNLxoE32Jh0rW9vjj5X9\n8b0/nq92PAsMn/BOY7z8ta9p+532dslJofD2qEZoJhHe1Xq8w+c3Q3g3aubJPpcvgn2vcVKP95NP\n6vP3vx8cM6/VqFHBMb+uccI7iUfQ967H/cZJGoZaGrZ2Jq3Mx0YrC+9qEjnFebzNXk1413PPZkV4\nr1mjAmrqVP3fhLdI4N32Pd7mpdy+vVjY+J64/v4gw7W1M/R4NwfzeHd26m/6D/+gYvrCC/X1Y48N\nzn3Ri/TZhPfWrRo+DgS/2113BZM0Jrzvvru4rJ4evWeefDLwovvC29Ysm/CulJDIBoImvIFkE8RZ\nF95AslDzpUuDaIUoj/fatfo99vTQ491utFq4uY0Jk0ZeVrsm3GzDH7f6+sK3HX8sntSm/Las0e1N\n2sL74x/X5+eea3zZtUDh7VGr8I7zjDZKeB840PhGyAaLYQHsG1c9a6Jt1q0eEezjZ160gbL/3fl/\n+9f0P1+Sz5NEeCepey0NG0mPVhfeSTMiDwzoIDZ8vtlJIzzeFv7ebOH9zDPqCR0/XoXZtm26FtfC\nxzs79XNv2KCvT5mi527fHnjGTXibPW/eXCq8/XBYMnzs36+PzkKmmq98BXj88WCZ08iRwN/9nQq7\ns87SY+ZdBYJjvb36+zsXiPFJkzQM/Te/UVuZO1ePm8h+6in1ggPBPQOoIJ82TY8lEd42EJw9uzrh\nvWaNnt/bmy3h/fTTQfRBpTZp1y49/4QT9P8o4f3cc4EHnR7v9qLVvN7VhJo7F/Q5ScfKNl6N83j7\nY9haxqdperzTXuNtZWZlhyEKb49aQ80bJbzDHW61W5NVg92AceHtUfWppfw4j3fSxsS82/53HOWt\n9/+uJ9Tc39Mwbq04Pd75o9WFdxKPt3Px54c93o0INe/oaK7wfvxx9YCOGKECZWBAPYyzZ+tA3ryX\na9fqPsKdnYGIsr1WZ8wIQmBtK7LJk0uFd1dX9O4NJD38UPM4brhBvaq2tWNnp3o/Xv5y3QUD0PvU\nJrbPPlufR4xQW3jiCeDUU4NEQj092v88+mjgHe/p0b5i/3695+x4EuH90EMq8mfMCO6fJP3UU0/p\nWvQRI/QzZUGQ7t6t38v8+fp/uWRx69YB112n37vtHOBPcBkrVwaTHtXuc07yTTsL7717g74z6VjZ\nxsW+uPT1hW9b7RZqbu1jpa2Ch4vcCW8ROUtEbhORNSJyUEQujTjnIyKyVkR2icivROTIJGVn1eMN\nNL5jNSMNd4z+QKHW7bf27g0+S70ebxsA++81cRwnvOtJruZ7vOsR3vR4ZwsKbz13/34VmeEs6GkI\n72YmV7vnHuCPfwzW8U6YoJ/fElkBKsYHB4sTPJnwXrtWxfm0aYEnbvt2HQxFhZpPnFi6vSGpDhF5\np4gsF5HdIvIHETmt3PkWam6iOoqOjtLf5ZprgJ/+tPj49derwL7oouDY9On6bGHqgP7Od9+tv/0L\nXqDH/G3GHn00uOdsjXc5AbFkiQpPWxMNJBfe5nHPgsd72TKNOBgaAk4r/GrlPN6XXaa/w9FHAycX\n0mlGrfFevjwIXc/C5yQBaY7FgdYS3vv3B7ZQbcRkkvOdq+yQivN415LVPE+h5s4Fn50e79oZC+Av\nAN4JTcJUhIh8AMC7ALwNwOkAdgK4XURGhc8NU6vHOyzQurpKj8dRyeNts/nDJbx37Ahm92v1ePs3\nd73CO8rjbcLbv06Sa1br8Y5LtEaPd/5opuc1TaoJNTdbmj5dhXrU/T15sj43Sng3494fHAzCiC+4\nQJ+jhLfv8Y4S3uYFHzdO20X7/qZMUe+kte+2HRSpHRF5HTSh4ocAnALgIWi/PSXuPf4a73p5xzs0\nuZq/Rc5ll+nzVVcFx445RsXgqFFBwjYT3s/8f/a+PLyuqlz//ZImbTM3bdokHaGFDhQKLWCZBIpQ\nRW4viApFxQteFRWFwgW9DDIqCmIFKwIqKKhR/HG5zMMFREQmoQUKlBY6JGmapBmaNGk6Juv3x5fP\ntfY+e5+z95lPst7nyXOSnX323mefvdb3vev9hvWsrh9zDP9dVMSvXnbnjjuAM88EnngCOOEE3haU\neCvFBF9yozNNSHt6eLHhsss4F14UbL85adcuXhQ75hj+/LIA4g41FwVdiLlVvLMOKfPFgaFFvFMt\n3PT06EXuICmY8finqSTHfX26a0Syj222TrWKd5xQSj2llPq+Uup/AXhpDBcBuEEp9ahS6l0A5wKo\nBXB67GMHvw6pJgxEEm8p5hMm59J9HIAf9IoK/j2ZhnXXLj5Xfn6kke/pSdz59iPBMpmMGRN8FU8U\nb69Q874+PTlHCzUfOZIHdVjF27w3PT2612iYiXPMGOssZAOGIvHesYOf6aBVzWUsjR/PpMB8vru7\nddXmvLzEc7zLyjKXk/nXv/LrdddpEjB2LBPnTZu0giaK9+bNkcS7uTmyzZFZCMtUvM19LeLGMgB3\nKaXuU0p9AOACAH0Azvd7Q5BQ80Tw/e87i38BOh/56KP5uQB0Tvlf/sKvUlVdiLdXuPm3vsUFQ/v7\ngXPP5W3RiHdnpy40unYtLwwdfzz/nWniLePi7LOBhx/WPc792okJGbj8ct3WD4gk3q+/zt/vUUfx\n35n+nBZOpNIXB4Ym8S4vDyfcVFaG81sLCpw8ortbLwqbY7G3V6dbBfVPe3pSR4537NB8KtnHlgVz\nwBLvlICI9gNQDeA52aaU2g5uP3RUrPeHJd4SiuYmaEJcgxJvr+MA/DCWl/PvyTQ4QoxrayOv0bz+\neAeAHL+mxpsEFxcHn3zk+tyh5uLoyvG7unSBJHdxNSkmFVTxljY07u9V+iWHnTgt8c48hqLDJu1D\namvDEe8JEyLzT6U/NVHiDu727XqsZOK+b97Mn+H739fbpkzhNoTbt0dWqP7oI91erLQ0kowLIWhs\n5L8nTtT3TymnYm4RHkRUAGABnHZbAXgWUex2MhVvL4wY4ayMDnAExcknA8uX622yOH7rrZwjLs+C\nH/GWwn3XXcc54bIQ5Ee8lWLVd+ZMVtXvuoufXclHzzQhlSix739fV3oH/NuJiW0UJ17gJt53382F\n2g45hP+2infuIFFfHBhaxNssXppK4j1xopN4R+MpJSXhxlRvrybxqQg1l3k02WNc5tviYhtqnipU\ng0NeWl3bWwf/FxVhQ83HjIksINLTox/OoO19hOhFU7yTqdjJIK2pia54J0q8J050Oh1+PYT9IERh\n+vTIUHMJFzWJd3k5TybuCITS0mA9RQG+NxMn8u+JEO/eXnaISkuts5ANGIqKd1MTv9bWRuZse6G5\nmZ/fiopI4t3crOehRB35tjbd5igTz/7u3TrdRzBliibOQqbGjQPeeYfHthAGUbw//FCTcQk137yZ\n5/ziYr5/SvG5LPFOGOMA5COk3U614u2FKVOAZ57R4c+AVm0HBriKusCPeIvie9xxTjXdj3h3deln\n9/DDgZ/9DPje97TiXlCQvvlt167IzyP+hDvdQnqeuyGkQiIFzP1lsf3SS4E//pHzwCX8P9MLDBah\nkJAvDgwt4i3P/NixwQU5gKPTgthQGYOTJkX63F7Eu7c3nD8r7wnDbcJAQs1TUShSFO8ZM4K3Zks1\n0miyMgqCRw6KGx99tAxLlpQ7ti1duhRLly6N2FdyK0eN8iZ6Ydr7TJ7Mv3uRYHESk/kwyiCtrQVW\nr448p7QDSQbxNh90uWcjRgS7N+aAaWjg3wcG+PqPP55D0WSFXBQ7N6GQ74MouOJdVcVG3p0DK2E5\nQYl3tBXFuro61NXVObZ1mwk5FknFUHTYpGewKN6xxpSQSSJv4i2tlhIhzD09PCarq3Wl53TDj3gD\nPPfsvz//Pn068Nvf8u9SqEqqVm/cqMm4KHENDXquFtLgzhG3SCqi2u2HHloGoBzt7cCSwbJOfvY6\nlRgxglXZd94BPvc5vd2PePsRTz/iLYryXXdxzvPcucBXv6r/ny5C2tvLjv38+cDzz0den5t419Tw\n4nl/vzN3XtKw3J9/6lTuGnDCCcCbbwI//Snwn/+p/58uxVspzj0/+WQ+p8Da7KQgkC8OLMPZZ5c7\nCidmYmwnCybxNkOf/SCP1YQJzla6fpAxOGkSR3AJurq0bfNSvIP6swCP21SFg+/YwXY2FYv1onhP\nm+ZNvDMxroca8W4BD+wJcK60jQewKtab999/OR55ZH6gE3V1sXPppXhPmRKOeB9+OP9uEnilmOwl\no9iRG6bi/c9/Ov+XLMW7sJCP02p8C93dTI7NCo/RIO+dMYMdDoDvycCAdoBNxVtIvRfxDnpOUbzd\nCypy/O3bg0cySJ6r1/5eRmTlypVYIBV7LJKKoUi8m5r42Q66cv3BB1phKypyhnU2N2tCmogj39LC\nrzU1rBBnSvEWEiOQ/sxHH60V0hlGfV25L1Om8AIF4OzT3N3tzPcVkvHuu3w+aXlkERfaAfSD7baJ\n8YhUzP6FxYuXIz9/Pv7+d+CRR1J5ebHx7LNss00y6Ue8hXi6Q63lmXVHvolT/bGPAV/7WuS500W8\nP/iAx8Ff/8qLDBIC3tnJn9tdXb6mhkl3e7tW3QD/hQeJInj1VeDpp3VhREG6iPf//R9w2mnAf/83\n8MMf6u3WZodCQr44sBz33z//X102ch3C46qqdE2EaOjq4sWqykod2RYNnZ28/4QJPDbN83qlTkr0\naXd38Lmjt1f73akINS8qSs0Y37qVuUhFhXNRQpCJcT2kQs2VUhvBA/4k2UZEZQA+BuDlWO8PG2pe\nUeGsbguED+Ho7OSBkZfnHBh9fWy0Uk283WTUJPvxDoDOTp4wioudTkeYCswAE+8RI9ipFWMt1+5H\nvEePjjxneXn0nqImOjr487v3l9SCoN/rtm3h9rdILYZiqPkHH+gw15Ejeb7wa9/V0MAG2Wx1JDnK\ngFPxTiQ3W/LOa2oyl+PtpXjPncsO/Z/+pLdJv+VFi7QiZ+aoit2dPJnn+Jde0u+ROfLlQatihgxb\nhINSai+AN+G02zT4t6/d3rWLbbappmYKVVUcFmpC1CG3wuWn+EotEhlDAiHe8sy5kQrivWoV55BL\nVA2gF9WIWH0XdHZ6X5tEgaxYoRezAH/iPXMmL3p//euRpBtIzedsbY283w8/zK9/+EO4uj8WGon6\n4sDQCjXfto19/HHjgvm+4rcGSSEDovvc48ZF8ouw/iyQ+lDz4uLUEe+qKp0ylg3IOeJNRMVENI+I\nJMtq/8G/B6kYfgbgKiL6NyI6GMB9ADYDeDjWscNMskKsvBTvoKHmSjmJnkngk9nex+vaRSkzr11U\n4USJ99atunKyF/EOOri2bOFFifJyvq8DA9oJEeItqp300nWfU5yCoGRfJjAv4h3m2mX/TOW5Wjgx\nFBXvt98G5s3j3yUk0utZe/ZZXrzauhX49Kd5W1ERk/S9e/mnsVGrtok4uOLEVldn7tnftSuSeAOs\nGMriAsCK3cqVwP/7f3qbEOiRIzVxktSb/n4m8ICTeJvh6xZx46cAvkZE5xLRLAB3AigC8Fu/N0hX\ni7ws9WKqqvjngguABx/U2/2Ki+Xl8bO2caNzeyziHSTNJBq8wk2vugr4+9+57ZmguZlJ97e/Dfzv\n/2piJGlYbgjxvvFGJvHi9Mrnlxx1QUEBz0N33ul9nalwyj/9ab5Oc3GkrY2/i4YGXoCw8EYqfXFg\n6BFvSU0N4z+G8VvHjnUKT0rpKFO3PyvXE5Z4i01MheKdKuLd0sKRAJZ4J4bDwaEqb4JzRW4FsBLA\ndQCglLoZwM8B3AWuoDgawKeUUjG/zrBVzcvLIxXvMMS7u5udOXdfWPkfkDrFu7IystK3mYeSyDnb\n2qIT76CTieROlpXxd7Njh87XkJxNOf7Wrbpas3kfZUIKoni7F0ISId5W8U4diOhbRLSRiHYS0atE\ndESs9wwl4l1fz87vG29wviUQnXi//jq/fu97wMKF/LsZBvvhh3x/DjqItyVCvNes4bFfXs7XtG9f\n+lUjL8XbD4cdpp0JgMPPf/EL4K239DYh3oBu4SQr/88+y1EE7jBbi3BQSj0A4FIA14Pt+yEAFiul\n2vzes3NndhNvIl4gbmsDPvtZHreAdv7cxBPghaGf/Qy45Ra9raOD/YPRo73PU1bmXcQsKD7xCbZ5\nplMqRPTJJ/W25mYe20uWsG1es4a3+y101dYCN98M/OhH7Pw+8wxv7+nh+ccrUoG8mlINIlHF++KL\ngdtv138rxbnkAPDYY3p7Rwd/xlGjdGtCC0+kzBcHhh7xDuMPhvWV29vZJpk+t9RY8Yr4jEcYSqXi\nHU+V9aBoauLcd5N4f/ghLyxmCllqsvyhlPqbUipPKZXv+jnf2OdapVStUqpIKbVYKeUR2R+JoAN9\n925+cMePdz7QJnEL8gCZK9nugWG2HwCSX9Vc1Pp9+/SxhezLOVOleIcl3hKSJv11Aa0wmcTb65wd\nHXqRIdY5+/p4n8pKdnK8JqqgoT9mKM9QIn2ZBhGdBTbw1wA4DMDbAJ4moqjZYEMp1Pyb3+TwTQD4\n/Of5NRrxfvdd4JhjgJtu0iRFnP6+Pl1gMRnEW4o/mdeU7uc/DPF2g4jvr9lGqrKSc8PPPJMVTIDv\nUVmZs8+wRWJQSt2hlJqmlBqtlDpKKfVGtP2znXgDwO9/z4W6Cgo0uevtZfviVY1dahFcfrmzrol0\nN/GC5GoGwRlncMVwwcAAO6C9vZzbLNi6lcO+V63Sx25t5cXtI47gcSL1YfzGGxFw2WXAd7/LC1rP\nPac/vzvMPAjCOOU33aTTQABe/LjtNuCii7TzbYbRm5+9s5MXQBYuBP7xj/DXOVyQSl8cGLrEO2jt\nJ1m8DhodWlvrTCETkaqqKnEhSaJiUkW8w/CmsNi8WRNvERd/9zvgnHOSe54wyGKTlX4EVWbMAkKm\nUt3VxY5YVVUwoifVCiVEJF2Kd0uLLgwH6OuUgSrttOIdAG1tfA+8SPCYMeGId02NDmPbvp2Jd1WV\ndkR27NCTIjU0bwAAIABJREFUjJt4K+UfOu4FMz810dCceEJ5LAJhGYC7lFL3KaU+AHABgD4A50d7\n01Ba/PjoI+Ckk1iVlcIp4vh6jaumJqdqCzgV7xdeYMdYFtzCEu/ubq1sv/66Dn8XFTiXiLcXiNgB\nN0PSAT2uTzgheeeyCI5sDzUHOBriU59iQi0kTjpeeOGGG9hOjhzJ0RQA2yE/tRvQxNv0XwYGWGW/\n9Va9bds2DhH/6U914VKzcJOou0rx/z/9af5dijX19LAtLivjWggrV/L2IOPtiCP0QoJX8cMg8JqX\nlAKWLXNGqGzYwG3IjjlGb3vDWMJ59VV+lXtw7LFa+QY0CZg3T1+zRfoxnIm3KNhBfeWmJvbbi4r4\nvu3dq5/vCRO8/dkwCryIhOJvJNOmm356sv3lgQGteJeW6tpZcr8yhSw2WelHUOLtR9DMFaYgAyaI\n4p0K4i2E1k28ZSFA8iDjHQCtrZoES6/V3bt5sNfUBLs3/f3AunVs4N2Kd00NG2GpYC6Vxt3Eu7eX\nzx10AhMnxF3VfPduPmbYHG9ZZAhS1M0iNoioAMACAM/JNqWUAvAsgKi641Ai3tu3c86kEFwguuLt\n5bgL8d6+HXj0UeCTn9T/C0O8e3p43M2bB7z2Gudonnpq7GtKBC0twPnnc3E5LySbePvhllv4PP/+\n76k/l0UkckHxFsyZo59XSUfzQmEh26sjjwReeYW37doVnaiWl/N4Ne3Mhg2cV/5f/6Xt4dtv6/9L\nOzCp8nvYYZq8Si/t447juUAiYnbu1PPIAQfwOYBg4+3AA4G1a/n3PXucbbqCorAw0pa+8w6H5kuk\nAOAMDxdfTXyz4mKthIu4ceKJHHoqPpeQgIMOAtavt/Y7UxiKxHvUqGBEuqUluK8MsKo7caIen319\nWiB0d19Syql4B7H1wlWqqtjvTqZN7+lhP33s2OTXhWlp4eNNnqwXO/v6NBnPFEKbLCI6Mcr/vp7Y\n5WQWQQe6hCi5FW/Jixo/PjjRy8vjFSm34t3ezjlQokIlm3jX1ka2LzEXDuIdAD09PEinTtXO/c6d\nevWtujrYql99PU8Us2c7FW+zZ25xMZNrOXZVlbO4hBlREETxNvsimwTejHAIcu39/f654tmMHBjb\n4wDkI7LFUCuA6mhvHEqh5l7FjCR03Kt4iJfjLo7/fffxPHTeefp/YcZ+YyPv+/77vBgwc6ZWgFOl\neD/7LHDvvcBZZ3nP2eki3hdeyHObzHPZihwY13Ehl4j3rFlMPAcGnAQ22v5CinfujE28AWe4uanU\nvvQSv374IUdvTJyoSbZ0CfnEJ3ibUtqPmTiRCbbkcpvPulkELijxbm3la9yzJ76aCOPHR1aIl/D1\nvXuZTADaXgNa3W5r4znv8MN5rgL0/lL3Yv16/iw7djDxnjWLvy9ZYMg2DNVxLfDr0JGLkDSN0aP5\nWY312URgCiL09PTwz8SJmlz29PA5iZhDmH5oZyc/1+PGBReGTF862aq0kHpRvJPpL0i0zsEH63uz\nfbteqMgU4jFZTxHRLYPqEwCAiKqI6FEAP0repaUfQRXvzZt1n2pTGTWJa5CHs76eSV5BQSRBa27m\ngSoGLVkP48AAH7u2VjvrUhlcjNPIkfEPLjFS++/vDGc1qx3HypMeGNCVTQ86yKl4b9qkC6tVVPBK\nohStEbIv34f0S5w4MfhCiFR7N/NBooWge2HrViZ6kyZF5opnOXJ1bBO4uIsvclHxXruWw0LNeam/\nn8eTm3hL7nGbRykqL0d/v/2YsNx2G+cvS5E2IJziLWPjiiuA008H/ud/dO5qqhTvxkZ+fecdLpjk\nHtfpIt5A9GJQWYRcHddRkQuh5oLp0/l629p4PMR6Pvffn4mgUsEUb8BJvNes4e3Fxdr57Opi2zZv\nHvDee7xNbNyCBfx7e7s+TkUFE2yxr319eh7Zbz+2xUoFG2/SMaGpKX7Fe/JkJhPmfLJ5s55vXnuN\nX1tauM7EuHFarZeWQjNnauVdPudhh/Hrhg3aFyot1YpYkD7KGcKQHNeCoaR4uxVpU2RzY88eJqPi\nK+/eHZ2byMLYgQfqFMzubh4H48bx+DD9VhGY3JGd0SDEe9y45Lf1k8W/ZJP6vj5eoC8t5XlMooc7\nOnIz1PwEAGcA+CcRzSGiTwN4F0AZgEOjvTHbEXSgr1nDE3heHn+pJkEbMSJ4aHN9vTZIbsVb8rDF\nqCRLsduyRZNCk9ACOjcbiH/lSYj39OlO4u3Oizdzv9247joO4zz8cL7Oigp2cNvbedX+gAN4v8pK\nJt4bN/J3MWmSU6kWB33y5GCEef16nQtrfq+mEu7+nrzgF7KeAzgB2T222wH0A5jg2j4ekSq4gWW4\n9dYlWLJE/9TV1aXuKpOERYu4EJJZfdOvB66MW7ciBHg77iNH6vnuwgud//Mb+y+9BDzyiHObjOsr\nrgAeeED3uQa0qpWIIV2/Xn9mQWMjk4fbb+cFumOPdZKOdBJvN+rq6hzP2ZIlS7Bs2bLMXIzGCcju\ncR0XcknxltxIIY6xiOf06fxMd3bGJt7ibN98sx63bW18zjlzNMmW1kJz5mhnvaeHx4r0r9+4UZPP\nkhJe5G5o4L/NBbzJk9nObtsWbLxJj/OtW/ka4yHeQoSlqBvA88/RR/N1yWcS3+mAA3T/cPFthHhL\nq6WiIt63tJR9F7HVo0fryDpZwM9CnIAhOK4FQ4V479jBi14ixADRfUKJ4JRQc6Wi++JvvcXRsQcd\npOeCri5eGDP5hfjF4p8G9WcBHYEbpuBbUKRKTb/0UvZJ/u3f2EaIj/Tee6x6z5iRnPPEA4+6mtGh\nlHqFiOaBWwSsBJP3qwHcPJhvmbMIevXvvacrAJsVRTdu5Ac9P58HTKwH2lRv3cRQcjySHa4pIWhz\n5+pwFwlPbWzUxibeAfDGG7p/qUm86+v5nowbxwZdjLsXXn2VjaH0Pi0o4PetWsXvE+I9Zowm3pMn\n835u4l1eHry929tvc29fgN9jVj8tKOCJwV0wzgsm8Q46sWUDsn1sK6X2EtGbAE4C8AgAEBEN/n27\n/zuX45vfnI+vfS0dV5k8yPirq+MwbkDnIboV75ISfsa9FG8/x/2LX2SV6LOfdW73W9E+7jh+lRoO\nAC82lpZ6t0ZKtKq5Umwc3b2NGxp4vH/72+x0n3ACF6X6yU/4/5kk3kuXLsXSpUsd21auXIkFCxZk\n5oKQ/eM6XuSS4j1hcKmwpYWfz1jEU9SY5ubYxHviRL4H99zDhdw++1mdwzlzps4tlxao06axbRwY\n0PnmsuC8caNe1CsuZn/mT3/iv03iLU5sR0d44h2v4i3E+9hjuf7LAQfwXFRTw7+vW8f/b2nhz5OX\np7cJ8Z46lT9HR4e+H0Ra2TeJt/gr2ap4D9VxLRgqxNv0B8UHjeYTrl/Pr9OmaT+5r897zDz1FPD1\nrwOHHsrPrEm8P/pIk0svIcmdKhsNW7ey/5uXl3zi3dDAx62tTe6xH3qII3OkA4zMWZJ6Y3YuSTfi\nNVkzwT38NgPYN/h3lme6xUasqWrXLu5J+fe/69BMk3ivX88r1UDsB6i/n1eqDh1cl3QPgOZmJp/J\nJt7vvMMGddq0SMV7/Xo9UOMZAN/4BvDDH3K+GJGTeK9dy8YxLy92I/vt29mBkEUJgAeltPyYPZtf\nhXivW6fve1GRLuZWX++/sGFi3z4m3e+8owtWmRPVxo18HPlMsYh3fT3fP682DjmAbB/bPwXwNSI6\nl4hmAbgTfH2/9XvDiBHZHWq+dy/nGT7wgN42MMBq16hRwOOP67nJj3gT8fP2i18A11zjdFr8HPf7\n7mOn3J1v6UW8zWfYVL3NKBk3Eg0137RJv5qtfzo7de2LBQt43rn3Xr2QmEnincXI9nEdGrt35x7x\nDqp4m6kjsYj32LHsoM+dq8emFHOaNk0r1tKiaMoUXfV4+3a2dWPG8GtDg3b2i4uZLHR1sc0zc7xl\n/LW3BxtvZWW8TyLE+8ADdSs06S9uqttCstvb+f5Nn64j8KQlmyxoNDXp+wHwMVpbtW2XBYZJk7KX\neA9iyI1rwVAh3iaRDqJ4v/8++ywzZui8ZD9/+Ytf5Ndrr+VXM+3ko4+0SGXylMZGXggrLAyeCrlh\nA5NYIPmh5hs38jgrKEgu8e7qAi65hOc2gOe3wkLgxRdZHBXOkAnEU1ztewBeAfB/AOYCOALcT/cd\nIsrpjqaxBvqTTwL//d/8u4gaZiuP9et1f+loCuu6dcCNN/Jg+tjHeJu76qCQSTFoySBvZ5zBPTWP\nP14TYEAPanPhIGxxtZ07dV725Zfzq1nMYO1aXn2X7dGIt7QtMVFTw2FjFRV6cUCIt7mAIXkcnZ0c\nmSChr9GKSDzwAL+/r4/vEeAk3u+/r48TZIXwnXc4IiIvL7cU71wY20qpBwBcCuB6AKsAHAJgsVLK\nQ+tlZDvxfvRRVp6/8hW9rbub56Nzz2VDKbmKfsQb4PGwbh1w/fXAH/6gt/u1IyLyJi0lJfo8ApP4\nPvVU7GMD4RYNV6/mnuRm5eVVq/Tvzzzjf87TT+fxLi2DLPF2IhfGdTzYt49/coF4jx7NY1aId6zn\nU4h3e3ts4g3w/xcu1IXDhHhPmcKL+Hv26FDzyZN5n4YGp62dMIGJsUm8TWXbzPE28yWDjDciXRxt\n7974iqvl53NUy7HH6tZsW7fycadO1allQqgnTtTn6+nhec0k3maRSrk2U/EGuAaGOxUnWzBUx7Vg\nqBRXe+stfs6mTg1GvFev5kWmgoLoxFuK+P7qV7qzxujR/L4NG9hmi89dXq6LCb7/vhavgvqnYUTF\nsNi0SUfcJOvY/f08L5mFT0WcePddjmzNpI8Qj8m6CMDpSqlvK6V2KaXeA3AkgP8B8EIyLy4RENG3\niGgjEe0koleJ6IhY74lFvGX1tL5ehz2Vl/OX3NnJD7QoptGI3uWX8wrVpEm6oqY5AJqbeZDMmcPG\nprAwcfLW1cU9PAHgssv4taiIH8aeHl5Z7+jQK2RhB4D09Fy1SpNgCS9raWGHWsLzi4v52H4OuVfV\nZgmBX7hQO1pjxvB3smGDPqesxLe1MQGW0PFobRyk2MqDD2pSL8XVlHKmFgRRvN96Sz8Ho0fzZ82R\n1ducGNtKqTuUUtOUUqOVUkcppd6Itv+IEdlT1fyZZ4BTTtHqDKCV3R079Kq0VPr8zGf42ZXqvWKA\nvfoA33YbcNNNwFFHcZgVwHPT3r3h+uaK+mNCiPhJJ3E7HlHgozndfor37t3aCRA89BDwl7/oxTuA\nyQPA86C0AAIiqzwvWMBzghSRssQ7Ahkb10R0BRH9g4h2EFGnzz6TiejxwX1aiOhmIgrkm+zalRvE\nG2Cnr60tWKh5eTnPW0EUb8GBB/K8opSTeCvlVHiFeDc2OlubTZjA4763l8fPiBFOZdsMNRfiHVTx\nBvhY7e3xK96C2bNZzZPPWVnJC/NS6FH8B/EZ5DOVlvLcRsSkxOynLp/dTbw//nFt+7MQOWGv4/HF\ngaFBvJUCXn+d/VOi6MS7pQX48Y/ZBh5/PG+LRrxlm6jcAJ+jokL7C0ccofcR3+Lddzk6BghOvM2w\n9WRXHl+zRh87We3ExEd3dxwR3nbMMYmfIxHEY7IOVko9aW5QSu1VSl0G4JTkXFZiIKKzANwK4Brw\nCuDbAJ4monHR3heEeM+d6wyBlof+r39l514U7LKyyKJAgpYWrqT5t79pg2Uq3qL6mGQvUeItBVbe\nflu3+8nL0y25xLGVhYCwxFsGtYTUATxpFBdzaH57O+djynbAP8/bq8/pOefwq9n2qLpaExSZqMRR\nePlldu4lJSDaQkhDA39uUbsBPv++ffydNzaycw9En6huu41Vyzff1Pmw4jDlSLh51o/teJApxbuh\nQbezETz4IKdMmIq0GFCldGVeKThSW8utMGROkMUjL0f3xBOB732Pif0LL+iKyEA44i1OqAmZy04+\nmR1cCb+Mpt75Kd5XX82kQAofAVqtknQSOWdRES8kvP663u5WvEeO5EgjyWXdt08XpbQAkNlxXQDg\nAQC/9PrnIMF+AlxvZiGALwP4D3BES0zs3Jk7xFuc3yDEU9oAhSHeBxyg2wgJ8TZJtuQ0V1bygn5b\nmzfx3rFD12zwI96FhezjhCHeZWVMihMl3vvtp4vA9fcz0aip4c/S3c3bTeK9ZYtWvAsKeAGkpYWd\nc/mcbuKd7S0CB5H19jpeXxzIfeJ9++08N/3v/3KBL0CPHy9/8O672X4DHOkGRCfe4nO7RaoxY5hb\njBmjCa3MPV1dbCf9Uly90NjI40XEpGT22u7t5QXzeHmHH4R4u2vPnDI4KkwekQmENllKqfYo//tb\nYpeTNCwDcJdS6j6l1AcALgDQB+D8aG+KRbw3bdJ5DgIh3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g0s5jQ3a6IZzc+fOpXt4ty5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XD2AzeN+84ijqDlZnE4BrW/M9gDudVwAcDvypHwj84cPWD6A/gHcB7A98J+sDhtU9ivqf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kS3kp8ygQBXcMMNi7J0RXQBefZ4d+Ke3ZXzxe1aCyrhLcTwY2bHmdk7zOxoM5tnZi/Cyww9gN/A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\nCCGEEEIII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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# No regularity in the behavior \n", "# The effect of initial value\n", "figure =plt.figure(figsize=(10,10))\n", "for i in range(20):\n", " plt.subplot(5,4,i+1);\n", " plt.plot(Data[i,:,1]);\n", " plt.xlabel('time')\n", " plt.ylabel('x')\n", "plt.tight_layout();" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import random\n", "time_lag = 1\n", "train_test_row=1000\n", "train_data = []\n", "test_data= []\n", "\n", "for r in range(train_test_row):\n", " for t in range(0,Data.shape[1]-time_lag-1):\n", " train_data.append(Data[r,range(t,t+time_lag+1),:])\n", " \n", "train_data = np.asarray(train_data) \n", " \n", "random.shuffle(train_data)\n", "# train_data = np.transpose(train_data,[1,0,2]) #time,batch,inputdim\n", "\n", "for r in range(train_test_row,train_test_row+1000):\n", " for t in range(0,Data.shape[1]-time_lag-1):\n", " test_data.append(Data[r,range(t,t+time_lag+1),:])\n", " \n", "\n", "# We don't need to shuffle it and later easily will use it for predictions \n", "test_data = np.asarray(test_data) \n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "test and training data loaded\n" ] } ], "source": [ "import warnings\n", "warnings.filterwarnings(\"ignore\")\n", "import numpy as np\n", "import random\n", "from random import shuffle\n", "import tensorflow as tf\n", "tf.reset_default_graph()\n", "\n", "NUM_EXAMPLES = 20000\n", "INPUT_SIZE = 3 # 2 bits per timestep\n", "RNN_HIDDEN = 20\n", "OUTPUT_SIZE = 3 # 1 bit per timestep\n", "TINY = 1e-6 # to avoid NaNs in logs\n", "LEARNING_RATE = 0.01\n", "\n", "\n", "\n", "test_input = test_data[:NUM_EXAMPLES,:time_lag,:]\n", "test_output = test_data[:NUM_EXAMPLES,time_lag,:]\n", "train_input = train_data[:NUM_EXAMPLES,:time_lag,:]\n", "train_output = train_data[:NUM_EXAMPLES,time_lag,:]\n", "\n", "print \"test and training data loaded\"\n", "\n", "\n", "\n", "data = tf.placeholder(tf.float32, [None, time_lag,INPUT_SIZE]) #Number of examples, number of input, dimension of each input\n", "target = tf.placeholder(tf.float32, [None, OUTPUT_SIZE])\n", "\n", "num_hidden = 24\n", "num_layers=2\n", "cell = tf.nn.rnn_cell.LSTMCell(num_hidden,state_is_tuple=True)\n", "cell = tf.nn.rnn_cell.MultiRNNCell([cell] * num_layers, state_is_tuple=True)\n", "val, _ = tf.nn.dynamic_rnn(cell, data, dtype=tf.float32)\n", "val = tf.transpose(val, [1, 0, 2])\n", "last = tf.gather(val, int(val.get_shape()[0]) - 1)\n", "\n", "weight = tf.Variable(tf.truncated_normal([num_hidden, int(target.get_shape()[1])]))\n", "bias = tf.Variable(tf.constant(0.1, shape=[target.get_shape()[1]]))\n", "\n", "# prediction = tf.nn.softmax(tf.matmul(last, weight) + bias)\n", "\n", "prediction = tf.matmul(last, weight) + bias\n", "\n", "error = tf.reduce_sum(tf.pow(target-prediction, 2))\n", "# error = tf.reduce_mean(error)\n", "\n", "# cross_entropy = -tf.reduce_sum(target * tf.log(tf.clip_by_value(prediction,1e-10,1.0)))\n", "optimizer = tf.train.AdamOptimizer()\n", "minimize = optimizer.minimize(error)\n", "\n", "# mistakes = tf.not_equal(tf.argmax(target, 1), tf.argmax(prediction, 1))\n", "# error = tf.reduce_mean(tf.cast(mistakes, tf.float32))\n", "\n", "accuracy = tf.abs(1-(target -prediction)/target)*100\n", "\n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(20000, 1, 3) (20000, 3) (20000, 1, 3) (20000, 3)\n" ] } ], "source": [ "print test_input.shape,test_output.shape, train_input.shape,train_output.shape" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 0 error: 11489012.5\n", "Epoch 3 error: 2854307.03125\n", "Epoch 6 error: 1628328.22266\n", "Epoch 9 error: 959440.625\n", "Epoch 12 error: 607786.425781\n", "Epoch 15 error: 404043.62793\n", "Epoch 18 error: 279811.938477\n", "Epoch 21 error: 201083.483887\n", "Epoch 24 error: 148937.82959\n", "Epoch 27 error: 111654.541016\n", "Epoch 30 error: 83870.2148438\n", "Epoch 33 error: 63246.661377\n", "Epoch 36 error: 48217.4102783\n", "Epoch 39 error: 37168.8842773\n", "Epoch 42 error: 29102.8045654\n", "Epoch 45 error: 23247.1557617\n", "Epoch 48 error: 18867.8787231\n", "Epoch 51 error: 15487.5152588\n", "Epoch 54 error: 12921.7697144\n", "Epoch 57 error: 11046.9238281\n", "Epoch 60 error: 9603.9276123\n", "Epoch 63 error: 8395.11413574\n", "Epoch 66 error: 7303.97186279\n", "Epoch 69 error: 6400.340271\n", "Epoch 72 error: 5572.66235352\n", "Epoch 75 error: 4741.63131714\n", "Epoch 78 error: 3892.06161499\n", "Epoch 81 error: 3123.98872375\n", "Epoch 84 error: 2584.26246643\n", "Epoch 87 error: 2203.18202972\n", "Epoch 90 error: 1926.78127289\n", "Epoch 93 error: 1687.9196167\n", "Epoch 96 error: 1515.82260132\n", "Epoch 99 error: 1395.79143524\n" ] } ], "source": [ "init_op = tf.global_variables_initializer()\n", "sess = tf.Session()\n", "sess.run(init_op)\n", "\n", "batch_size = 200\n", "no_of_batches = int(len(train_input)) / batch_size\n", "epoch = 100\n", "for i in range(epoch):\n", " ptr = 0\n", " for j in range(no_of_batches):\n", " inp, out = train_input[ptr:ptr+batch_size], train_output[ptr:ptr+batch_size]\n", " ptr+=batch_size\n", " sess.run(minimize,{data: inp, target: out})\n", " if i%3 ==0:\n", " incorrect = sess.run(error,{data: inp, target: out})\n", " print \"Epoch {} error: {}\".format(i,incorrect*100)\n", " " ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": true }, "outputs": [], "source": [ "test_preds = sess.run(prediction,{data: test_input, target: test_output})" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [], "source": [ "ac = sess.run(accuracy,{data:test_input, target: test_output})" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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eV0hCGZ0/32W0zlSsQgnNuz+GPPVU4fn27XDvvenmGj7c0i+PP77welxmSzVy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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "for i in range(3):\n", " plt.subplot(3,3,i+1)\n", " plt.plot(test_preds[:,i],test_output[:,i],'.')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## One Step Ahead Prediction " ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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49VSR88+3Z13//Ke+nWe6CIHTvvMdkRNOcLoVwcbAGQNnlAY7Lz5jwaYJE/Qh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\neKLgDAAAAOBoJjgbgKpu1JngDAAAAODoJTgbkOXLBWcAAAAARzPB2YA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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(15,5))\n", "plt.plot(test_output[:150,0],'.-')\n", "plt.plot(test_preds[:150,0],'or')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Run sequenctially " ] }, { "cell_type": "code", "execution_count": 72, "metadata": { "collapsed": false }, "outputs": [], "source": [ "r = train_test_row+900\n", "t = 80\n", "inp = Data[r:r+1,range(t,t+time_lag),:]\n", "preds = []\n", "for step in range(1800):\n", " \n", " pred = sess.run(prediction,{data: inp})\n", " preds.append(pred[0])\n", " pred_len = len(preds)\n", " pred_len = np.minimum(pred_len,time_lag)\n", " x = list(inp[0,:,:])\n", " x = x[step+1:]+preds[-pred_len:]\n", " inp = np.asarray(x)[np.newaxis,:,:]\n", " \n", " \n", "preds = np.asarray(preds)" ] }, { "cell_type": "code", "execution_count": 71, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# preds1 = preds.copy()\n", "# preds2 = preds.copy()\n", "# preds3 = preds.copy()" ] }, { "cell_type": "code", "execution_count": 73, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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d7CVcOLg4SjEhQikMKyswtlxLW0v0UK/GRoWPxqx0OdJKYFHpZgs1TFPli3Bx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tgx1p967XgnR0oKkJWFyy9n2xWPa1TPnGHKx1bcraQ1uBwjR/IjJ5EIb5GfX99NQg2kpnKrWl1t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\nqy24u//+nD1xv/BCm8O2cWN6Xj+lpXcAw4bBzTfDT3/auwPiddd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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(10,10))\n", "plt.subplot(2,2,1)\n", "plt.plot(preds[:100,0],'.-r')\n", "plt.plot(Data[r:r+1,range(t+time_lag,t+time_lag+100),0].T)\n", "\n", "plt.subplot(2,2,2)\n", "plt.plot(preds[:100,1],'.-r')\n", "plt.plot(Data[r:r+1,range(t+time_lag,t+time_lag+100),1].T)\n", "\n", "plt.subplot(2,2,3)\n", "plt.plot(preds[:100,2],'.-r')\n", "plt.plot(Data[r:r+1,range(t+time_lag,t+time_lag+100),2].T)\n" ] }, { "cell_type": "code", "execution_count": 77, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(1, 1800, 3)" ] }, "execution_count": 77, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pred_trajs = preds[np.newaxis,:,:]\n", "# pred_trajs = np.concatenate((preds3[np.newaxis,:Data.shape[1]-(t+time_lag),:],preds2[np.newaxis,:Data.shape[1]-(t+time_lag),:],preds1[np.newaxis,:Data.shape[1]-(t+time_lag),:],preds[np.newaxis,:Data.shape[1]-(t+time_lag),:]),axis=0)\n", "\n", "# pred_trajs = np.concatenate((Data[r:r+1,t+time_lag:,:],preds[np.newaxis,:Data.shape[1]-(t+time_lag),:]),axis=0)\n", "pred_trajs.shape" ] }, { "cell_type": "code", "execution_count": 78, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# Set up figure & 3D axis for animation\n", "fig = plt.figure()\n", "ax = fig.add_axes([0, 0, 1, 1], projection='3d')\n", "ax.axis('off')\n", "plt.set_cmap(plt.cm.YlOrRd_r)\n", "# plt.set_cmap(plt.cm.hot)\n", "# choose a different color for each trajectory\n", "N_trajectories = pred_trajs.shape[0]\n", "colors = plt.cm.jet_r(np.linspace(0, 1, N_trajectories))\n", "\n", "\n", "# set up lines and points\n", "lines = sum([ax.plot([], [], [], '-', c=c)\n", " for c in colors], [])\n", "pts = sum([ax.plot([], [], [], 'o', c=c)\n", " for c in colors], [])\n", "\n", "# prepare the axes limits\n", "ax.set_xlim((-25, 25))\n", "ax.set_ylim((-35, 35))\n", "ax.set_zlim((5, 55))\n", "\n", "# set point-of-view: specified by (altitude degrees, azimuth degrees)\n", "ax.view_init(30, 0)\n", "\n", "# initialization function: plot the background of each frame\n", "def init():\n", " for line, pt in zip(lines, pts):\n", " line.set_data([], [])\n", " line.set_3d_properties([])\n", "\n", " pt.set_data([], [])\n", " pt.set_3d_properties([])\n", " return lines + pts\n", "\n", "# animation function. This will be called sequentially with the frame number\n", "def animate(i):\n", " # we'll step two time-steps per frame. This leads to nice results.\n", " i = (2 * i) % x_t.shape[1]\n", " \n", " \n", " for line, pt, xi in zip(lines, pts, x_t):\n", " x, y, z = xi[:i].T\n", " line.set_data(x, y)\n", " line.set_3d_properties(z)\n", "\n", " pt.set_data(x[-1:], y[-1:])\n", " pt.set_3d_properties(z[-1:])\n", "\n", " ax.view_init(30, 0.3 * i)\n", " fig.canvas.draw()\n", " return lines + pts\n", "\n", "# instantiate the animator.\n", "anim = animation.FuncAnimation(fig, animate, init_func=init,\n", " frames=500, interval=10, blit=True)\n", "\n", "# Save as mp4. This requires mplayer or ffmpeg to be installed\n", "anim.save('./Images/lorenz_preds.mp4', fps=15, extra_args=['-vcodec', 'libx264'],dpi=200)\n", "\n", "plt.close()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## It can't predict the whole process, but ...\n", "# Seemingly it has learned the underlying dynamics and inter-dependencies\n", "### (i.e. the differential equations)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "\n", "\n" ], "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from IPython.display import HTML\n", "HTML(\"\"\"\n", "\n", "\"\"\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# One possible application of the trained RNN:\n", "## For resampling on dependent observations! (like a stochastic process)\n", "![](Images/srn_elman.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "# Financial Time Series\n", "## Forex \n", "#### Can we learn it as well? We don't know if there is an underlying system there." ] }, { "cell_type": "code", "execution_count": 368, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "14\n" ] } ], "source": [ "import glob\n", "import os\n", "path = './Data/Forex_10m/'\n", "path = './Data/Forex_hourly/'\n", "all_pairs = []\n", "counter = 1\n", "for filename in glob.glob(os.path.join(path, '*.csv')):\n", " all_pairs.append(filename)\n", "\n", "print len(all_pairs)" ] }, { "cell_type": "code", "execution_count": 369, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2001-01-02 23:00:00 2017-03-31 20:00:00 AUDJPY (142366, 1)\n", "2001-01-02 23:00:00 2017-03-31 20:00:00 AUDUSD (142366, 1)\n", "2001-01-02 23:00:00 2017-03-31 20:00:00 CHFJPY (142366, 1)\n", "2001-01-02 23:00:00 2017-03-31 20:00:00 EURCAD (142366, 1)\n", "2001-01-02 23:00:00 2017-03-31 20:00:00 EURCHF (142366, 1)\n", "2001-01-02 23:00:00 2017-03-31 20:00:00 EURGBP (142366, 1)\n", "2001-01-02 23:00:00 2017-03-31 20:00:00 EURJPY (142366, 1)\n", "2001-01-02 23:00:00 2017-03-31 20:00:00 EURUSD (142366, 1)\n", "2001-01-02 23:00:00 2017-03-31 20:00:00 GBPCHF (142366, 1)\n", "2001-01-02 23:00:00 2017-03-31 20:00:00 GBPJPY (142366, 1)\n", "2001-01-02 23:00:00 2017-03-31 20:00:00 GBPUSD (142366, 1)\n", "2001-01-02 23:00:00 2017-03-31 20:00:00 USDCAD (142366, 1)\n", "2001-01-02 23:00:00 2017-03-31 20:00:00 USDCHF (142366, 1)\n", "2001-01-02 23:00:00 2017-03-31 20:00:00 USDJPY (142366, 1)\n" ] } ], "source": [ "all_opens = pd.DataFrame()\n", "for pair in all_pairs[:]:\n", " DF = pd.read_csv(pair,index_col=0)\n", " Ticker = pair.replace(path,'').replace('.csv','')\n", " DF[Ticker] = DF[Ticker].fillna(method='backfill',limit=1,axis=0)\n", " all_opens[Ticker] = DF[Ticker]\n", " print DF.index[0],DF.index[-1], Ticker, DF.shape" ] }, { "cell_type": "code", "execution_count": 370, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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2001-01-03 03:00:0064.6643100.56442071.5610001.4186561.5209960.632241108.8732730.9501662.404674172.1263331.5024371.4929671.600336114.553750
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" ], "text/plain": [ " AUDJPY AUDUSD CHFJPY EURCAD EURCHF \\\n", "Date \n", "2001-01-02 23:00:00 64.285435 0.561779 71.512308 1.419355 1.520868 \n", "2001-01-03 00:00:00 64.429483 0.562908 71.499831 1.418677 1.521016 \n", "2001-01-03 01:00:00 64.508947 0.563557 71.505614 1.419098 1.520830 \n", "2001-01-03 02:00:00 64.510862 0.563386 71.510351 1.418898 1.521014 \n", "2001-01-03 03:00:00 64.664310 0.564420 71.561000 1.418656 1.520996 \n", "\n", " EURGBP EURJPY EURUSD GBPCHF GBPJPY \\\n", "Date \n", "2001-01-02 23:00:00 0.632968 108.794898 0.950700 2.401669 171.806923 \n", "2001-01-03 00:00:00 0.632986 108.781897 0.950402 2.401876 171.778475 \n", "2001-01-03 01:00:00 0.632505 108.779167 0.950341 2.403367 171.897818 \n", "2001-01-03 02:00:00 0.632103 108.800667 0.950155 2.405223 172.048276 \n", "2001-01-03 03:00:00 0.632241 108.873273 0.950166 2.404674 172.126333 \n", "\n", " GBPUSD USDCAD USDCHF USDJPY \n", "Date \n", "2001-01-02 23:00:00 1.501474 1.492754 1.599382 114.405116 \n", "2001-01-03 00:00:00 1.501043 1.492696 1.600027 114.428036 \n", "2001-01-03 01:00:00 1.502067 1.493226 1.599927 114.434074 \n", "2001-01-03 02:00:00 1.502704 1.493200 1.600433 114.477679 \n", "2001-01-03 03:00:00 1.502437 1.492967 1.600336 114.553750 " ] }, "execution_count": 370, "metadata": {}, "output_type": "execute_result" } ], "source": [ "all_opens.head()" ] }, { "cell_type": "code", "execution_count": 390, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(50, 14)\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 390, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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/Hk1dxwUXXFAS11GMf4/KysqCvY5XX33Hwf3225u+jub+PXbddaDvvXfzruOb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\nSiIkEWPGjIldhLKl2Mej2Mej2MeR0yTCzPYys6f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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "DF = all_opens.ix[:50]\n", "print DF.shape\n", "DF = DF.fillna(method='backfill',limit=1,axis=0)\n", "DF[DF.columns[1:2]].plot(logy=False,legend=False,rot=45,style='.-',grid=True)" ] }, { "cell_type": "code", "execution_count": 372, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import random\n", "time_lag = 20\n", "train_data = []\n", "maxdlen = min(all_opens.shape[0],250000)\n", "for t in range(0,maxdlen-time_lag-1):\n", " train_data.append(all_opens.values[:][range(t,t+time_lag+1),:])\n", "train_data = np.asarray(train_data)" ] }, { "cell_type": "code", "execution_count": 373, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(83041, 21, 14)\n", "(60000, 21, 14)\n", "(23041, 21, 14)\n" ] } ], "source": [ "indnan = np.isnan(train_data).sum(axis=2).sum(axis=1)\n", "ind = indnan==0\n", "train_data = train_data[ind]\n", "train_data.shape\n", "print train_data.shape\n", "NUM_EXAMPLES = 60000\n", "test_data = train_data[NUM_EXAMPLES:]\n", "train_data = train_data[:NUM_EXAMPLES]\n", "print train_data.shape\n", "print test_data.shape\n", "random.shuffle(train_data)" ] }, { "cell_type": "code", "execution_count": 374, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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\n", "
" ], "text/plain": [ " 0 1 2 3 4 5 6 7 8 \\\n", "0 AUDJPY AUDUSD CHFJPY EURCAD EURCHF EURGBP EURJPY EURUSD GBPCHF \n", "\n", " 9 10 11 12 13 \n", "0 GBPJPY GBPUSD USDCAD USDCHF USDJPY " ] }, "execution_count": 374, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.DataFrame(data=all_opens.columns).T" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# predicting the real values of one ticker " ] }, { "cell_type": "code", "execution_count": 379, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "test and training data loaded\n" ] } ], "source": [ "import warnings\n", "warnings.filterwarnings(\"ignore\")\n", "import numpy as np\n", "import random\n", "from random import shuffle\n", "import tensorflow as tf\n", "tf.reset_default_graph()\n", "\n", "\n", "\n", "# Target = sel_cols\n", "Target = [12]\n", "sel_cols = [7,10,11,13,12]\n", "\n", "\n", "NUM_EXAMPLES = 20000\n", "INPUT_SIZE = len(sel_cols) \n", "RNN_HIDDEN = 20\n", "OUTPUT_SIZE = len(Target) \n", "TINY = 1e-6 # to avoid NaNs in logs\n", "LEARNING_RATE = 0.01\n", "\n", "\n", "\n", "test_input = train_data[:NUM_EXAMPLES,:time_lag,sel_cols]\n", "if len(Target)>1:\n", " test_output = train_data[:NUM_EXAMPLES,time_lag,Target]\n", " train_output = train_data[:NUM_EXAMPLES,time_lag,Target]\n", "else:\n", " test_output = train_data[:NUM_EXAMPLES,time_lag,Target[0]:Target[0]+1]\n", " train_output = train_data[:NUM_EXAMPLES,time_lag,Target[0]:Target[0]+1]\n", "train_input = train_data[:NUM_EXAMPLES,:time_lag,sel_cols]\n", "print \"test and training data loaded\"\n", "\n", "\n", "\n", "data = tf.placeholder(tf.float32, [None, time_lag,INPUT_SIZE]) #Number of examples, number of input, dimension of each input\n", "target = tf.placeholder(tf.float32, [None, OUTPUT_SIZE])\n", "\n", "num_hidden = 24\n", "num_layers=2\n", "cell = tf.nn.rnn_cell.LSTMCell(num_hidden,state_is_tuple=True)\n", "cell = tf.nn.rnn_cell.MultiRNNCell([cell] * num_layers, state_is_tuple=True)\n", "val, _ = tf.nn.dynamic_rnn(cell, data, dtype=tf.float32)\n", "val = tf.transpose(val, [1, 0, 2])\n", "last = tf.gather(val, int(val.get_shape()[0]) - 1)\n", "\n", "weight = tf.Variable(tf.truncated_normal([num_hidden, int(target.get_shape()[1])]))\n", "bias = tf.Variable(tf.constant(0.1, shape=[target.get_shape()[1]]))\n", "\n", "# prediction = tf.nn.softmax(tf.matmul(last, weight) + bias)\n", "\n", "prediction = tf.matmul(last, weight) + bias\n", "\n", "error = tf.reduce_sum(tf.pow(target-prediction, 2))\n", "# error = tf.reduce_mean(error)\n", "\n", "# cross_entropy = -tf.reduce_sum(target * tf.log(tf.clip_by_value(prediction,1e-10,1.0)))\n", "optimizer = tf.train.AdamOptimizer()\n", "minimize = optimizer.minimize(error)\n", "\n", "# mistakes = tf.not_equal(tf.argmax(target, 1), tf.argmax(prediction, 1))\n", "# error = tf.reduce_mean(tf.cast(mistakes, tf.float32))\n", "\n", "accuracy = tf.abs(1-(target -prediction)/target)*100\n", "\n" ] }, { "cell_type": "code", "execution_count": 380, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(20000, 20, 5) (20000, 1) (20000, 20, 5) (20000, 1)\n" ] } ], "source": [ "print test_input.shape,test_output.shape, train_input.shape,train_output.shape" ] }, { "cell_type": "code", "execution_count": 381, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 0 error: 6.55176973343\n", "Epoch 3 error: 3.89536499977\n", "Epoch 6 error: 1.88389110565\n", "Epoch 9 error: 1.46300196648\n", "Epoch 12 error: 0.986657738686\n", "Epoch 15 error: 0.20409283042\n", "Epoch 18 error: 0.040967117995\n", "Epoch 21 error: 0.0389034375548\n", "Epoch 24 error: 0.0364233143628\n", "Epoch 27 error: 0.0300719439983\n", "Epoch 30 error: 0.0283087622374\n", "Epoch 33 error: 0.0246626548469\n", "Epoch 36 error: 0.0229454580694\n", "Epoch 39 error: 0.0461691729724\n", "Epoch 42 error: 0.0551976561546\n", "Epoch 45 error: 0.0351951792836\n", "Epoch 48 error: 0.0201646499336\n", "Epoch 51 error: 0.032220967114\n", "Epoch 54 error: 0.0309986621141\n", "Epoch 57 error: 0.0301187001169\n", "Epoch 60 error: 0.0380215346813\n", "Epoch 63 error: 0.0487026534975\n", "Epoch 66 error: 0.0469816327095\n", "Epoch 69 error: 0.0302092656493\n", "Epoch 72 error: 0.0180076546967\n", "Epoch 75 error: 0.0161619912833\n", "Epoch 78 error: 0.0271464847028\n", "Epoch 81 error: 0.0429531447589\n", "Epoch 84 error: 0.0427145287395\n", "Epoch 87 error: 0.0419983938336\n", "Epoch 90 error: 0.0414374172688\n", "Epoch 93 error: 0.0416199155152\n", "Epoch 96 error: 0.0402094312012\n", "Epoch 99 error: 0.0399771854281\n", "Epoch 102 error: 0.0385561212897\n", "Epoch 105 error: 0.0380765460432\n", "Epoch 108 error: 0.0365743748844\n", "Epoch 111 error: 0.0331384390593\n", "Epoch 114 error: 0.0340393036604\n", "Epoch 117 error: 0.0267145484686\n", "Epoch 120 error: 0.0306864418089\n", "Epoch 123 error: 0.0129253240302\n", "Epoch 126 error: 0.0118629792705\n", "Epoch 129 error: 0.00793247669935\n", "Epoch 132 error: 0.00597347784787\n", "Epoch 135 error: 0.00955007597804\n", "Epoch 138 error: 0.0230343081057\n", "Epoch 141 error: 0.0292865559459\n", "Epoch 144 error: 0.00565265119076\n", "Epoch 147 error: 0.0144629999995\n", "Epoch 150 error: 0.0204198695719\n", "Epoch 153 error: 0.0174022875726\n", "Epoch 156 error: 0.0112942028791\n", "Epoch 159 error: 0.00883933342993\n", "Epoch 162 error: 0.0083374120295\n", "Epoch 165 error: 0.00591534096748\n", "Epoch 168 error: 0.0073094656691\n", "Epoch 171 error: 0.00984713435173\n", "Epoch 174 error: 0.010978018865\n", "Epoch 177 error: 0.00654088519514\n", "Epoch 180 error: 0.00899933837354\n", "Epoch 183 error: 0.00457765953615\n", "Epoch 186 error: 0.00881194416434\n", "Epoch 189 error: 0.00408240221441\n", "Epoch 192 error: 0.00615442870185\n", "Epoch 195 error: 0.00865379162133\n", "Epoch 198 error: 0.0110528310761\n" ] } ], "source": [ "init_op = tf.global_variables_initializer()\n", "sess = tf.Session()\n", "sess.run(init_op)\n", "\n", "batch_size = 200\n", "no_of_batches = int(len(train_input)) / batch_size\n", "epoch = 50\n", "for i in range(epoch):\n", " ptr = 0\n", " for j in range(no_of_batches):\n", " inp, out = train_input[ptr:ptr+batch_size], train_output[ptr:ptr+batch_size]\n", " ptr+=batch_size\n", " sess.run(minimize,{data: inp, target: out})\n", " if i%3 ==0:\n", " SE = sess.run(error,{data: inp, target: out})\n", " print \"Epoch {} error: {}\".format(i,SE)\n", " " ] }, { "cell_type": "code", "execution_count": 382, "metadata": { "collapsed": true }, "outputs": [], "source": [ "test_preds = sess.run(prediction,{data: test_input, target: test_output})\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 383, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "for i in range(len(Target)):\n", " plt.subplot(3,3,i+1)\n", " plt.plot(test_preds[:,i],test_output[:,i],'.')" ] }, { "cell_type": "code", "execution_count": 393, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 393, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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XLdInzW66yfnjcgctgzJv3REXQghhrgsv1Jf9+sliW3aGAcXF+t/e+vdZgrIWPvsMXn1V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rBQPMZCTll3t3gMhaOsOLOYOCUOa791zm1jufOlFMp84HX76zT2NYa12+XZxHLnS8eg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\na3ahbMIzQb/HRrZSqovQ96KMo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/tCqzZWA3DY4fuHymjUV+llpB1lcKYbrjekUKZzaj+o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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(15,5))\n", "plt.plot(test_output[:50,0],'.-')\n", "plt.plot(test_preds[:50,0],'.-')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "## But what matters is...\n", "# Binary Classification\n", "### If you want to earn some money!" ] }, { "cell_type": "code", "execution_count": 409, "metadata": { "collapsed": false }, "outputs": [], "source": [ "diff_preds = test_input[:,-1,-1]-test_preds[:,-1]\n", "diff_preds[diff_preds>=0]=1\n", "# diff_preds[diff_preds==0]=0\n", "diff_preds[diff_preds<0]=-1\n", "\n", "diff_real = test_input[:,-1,-1]-test_output[:,-1]\n", "diff_real[diff_real>=0]=1\n", "# diff_real[diff_real==0]=0\n", "diff_real[diff_real<0]=-1" ] }, { "cell_type": "code", "execution_count": 411, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([-1., -1., -1., ..., 1., 1., 1.])" ] }, "execution_count": 411, "metadata": {}, "output_type": "execute_result" } ], "source": [ "diff_real" ] }, { "cell_type": "code", "execution_count": 396, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "from sklearn.metrics import confusion_matrix\n", "\n", "%matplotlib inline\n", "import itertools\n", "def plot_confusion_matrix(cm, classes,\n", " normalize=False,\n", " title='Confusion matrix',\n", " cmap=plt.cm.Blues):\n", " \"\"\"\n", " This function prints and plots the confusion matrix.\n", " Normalization can be applied by setting `normalize=True`.\n", " \"\"\"\n", " plt.imshow(cm, interpolation='nearest', cmap=cmap)\n", " plt.title(title)\n", " plt.colorbar()\n", " tick_marks = np.arange(len(classes))\n", " plt.xticks(tick_marks, classes, rotation=45)\n", " plt.yticks(tick_marks, classes)\n", "\n", " if normalize:\n", " cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n", " print(\"Normalized confusion matrix\")\n", " else:\n", " print('Confusion matrix, without normalization')\n", "\n", " print(cm)\n", "\n", " thresh = cm.max() / 2.\n", " for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n", " plt.text(j, i, cm[i, j],\n", " horizontalalignment=\"center\",\n", " color=\"green\" if cm[i, j] > thresh else \"black\")\n", "\n", " plt.tight_layout()\n", " plt.ylabel('True label')\n", " plt.xlabel('Predicted label')\n", " font = {'size' : 8}\n", " plt.rc('font', **font)" ] }, { "cell_type": "code", "execution_count": 398, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Confusion matrix, without normalization\n", "[[ 91 9771]\n", " [ 129 10009]]\n" ] }, { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from sklearn.metrics import confusion_matrix\n", "# Compute confusion matrix\n", "cnf_matrix = confusion_matrix(diff_real, diff_preds)\n", "\n", "np.set_printoptions(precision=1)\n", "class_names = [str(i) for i in np.unique(diff_real)]\n", "# Plot non-normalized confusion matrix\n", "plt.figure()\n", "plot_confusion_matrix(cnf_matrix,normalize=False, classes=class_names,\n", " title='Confusion matrix, without normalization')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Binary Classification" ] }, { "cell_type": "code", "execution_count": 503, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import random\n", "time_lag = 5\n", "train_data = []\n", "maxdlen = min(all_opens.shape[0],250000)\n", "for t in range(0,maxdlen-time_lag-1):\n", " train_data.append(all_opens.values[:][range(t,t+time_lag+1),:])\n", "train_data = np.asarray(train_data)" ] }, { "cell_type": "code", "execution_count": 504, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(96039, 6, 14)\n", "(40000, 6, 14)\n", "(56039, 6, 14)\n" ] } ], "source": [ "indnan = np.isnan(train_data).sum(axis=2).sum(axis=1)\n", "ind = indnan==0\n", "train_data = train_data[ind]\n", "train_data.shape\n", "print train_data.shape\n", "NUM_EXAMPLES = 40000\n", "test_data = train_data[NUM_EXAMPLES:]\n", "train_data = train_data[:NUM_EXAMPLES]\n", "print train_data.shape\n", "print test_data.shape\n", "# random.shuffle(train_data)" ] }, { "cell_type": "code", "execution_count": 505, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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0AUDJPYAUDUSDCHFJPYEURCADEURCHFEURGBPEURJPYEURUSDGBPCHFGBPJPYGBPUSDUSDCADUSDCHFUSDJPY
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" ], "text/plain": [ " 0 1 2 3 4 5 6 7 8 \\\n", "0 AUDJPY AUDUSD CHFJPY EURCAD EURCHF EURGBP EURJPY EURUSD GBPCHF \n", "\n", " 9 10 11 12 13 \n", "0 GBPJPY GBPUSD USDCAD USDCHF USDJPY " ] }, "execution_count": 505, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.DataFrame(data=all_opens.columns).T" ] }, { "cell_type": "code", "execution_count": 506, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "predicting USDCHF\n", "(39999,) (39999, 5, 3)\n", "(56038,) (56038, 5, 3)\n", "test and training data loaded\n" ] } ], "source": [ "import warnings\n", "warnings.filterwarnings(\"ignore\")\n", "import numpy as np\n", "import random\n", "from random import shuffle\n", "import tensorflow as tf\n", "tf.reset_default_graph()\n", "\n", "sel_cols = [7,10,12]\n", "\n", "\n", "Target = 12\n", "print 'predicting {}'.format(all_opens.columns[Target])\n", "\n", "n_ahead = 1\n", "# train_output = train_data[:,time_lag,Target].copy()\n", "train_output = 100*np.diff(train_data[:,time_lag,Target])/train_data[n_ahead::,time_lag-1,Target]\n", "train_output = np.around(train_output,decimals=2)\n", "\n", "train_data[n_ahead:,time_lag,Target]= train_output\n", "\n", "#no empty\n", "train_data= train_data[n_ahead:]\n", "\n", "\n", "random.shuffle(train_data)\n", "\n", "\n", "train_input = train_data[:,:time_lag,sel_cols].copy()\n", "train_output = train_data[:,time_lag,Target].copy()\n", "\n", "\n", "print train_output.shape, train_input.shape\n", "\n", "\n", "\n", "\n", "\n", "\n", "test_output = test_data[:,time_lag,Target].copy()\n", "test_output = 100*np.diff(test_output)/test_data[n_ahead::,time_lag-1,Target]\n", "test_data[n_ahead:,time_lag,Target]= test_output\n", "\n", "#no empty\n", "test_data= test_data[n_ahead:]\n", "\n", "# No need to shuffle\n", "test_input = test_data[:,:time_lag,sel_cols]\n", "test_output = np.around(test_output,decimals=2)\n", "\n", "\n", "\n", "\n", "\n", "# test_input = test_data[n_ahead:,:time_lag,sel_cols]\n", "# test_output =100*np.diff(test_data[:,time_lag,Target],n=n_ahead)/test_data[:-n_ahead,time_lag,Target]\n", "# test_output = np.around(test_output,decimals=2)\n", "print test_output.shape, test_input.shape\n", "\n", "\n", "\n", "print \"test and training data loaded\"" ] }, { "cell_type": "code", "execution_count": 507, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 507, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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dLBOdJibSkIdlIs/ff/bZwI9+lN/x6ooWE1V0If3wh8A557S7FNWilpaJrHSam6MVyqyL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\nFSQuMTFhAnDGGdkHVJ0B08xwHBc7tdNObmvH8ce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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(train_output[20000:21000])" ] }, { "cell_type": "code", "execution_count": 508, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 508, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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e210jIdRY7XntBxwA3Hkn8L73hafW5bFMHHus/xhAVCfr1wNf/3pckMnUQFdo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\nYey+L8MNnIbvul5zDTB7dvXnbgsxYT/dCyEx4Q7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039999.0-0.0002020.116888-1.05-0.12-0.040.00.040.121.2
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" ], "text/plain": [ " count mean std min 10% 30% 50% 70% 90% max\n", "0 39999.0 -0.000202 0.116888 -1.05 -0.12 -0.04 0.0 0.04 0.12 1.2" ] }, "execution_count": 510, "metadata": {}, "output_type": "execute_result" } ], "source": [ "DF = pd.DataFrame(data=train_output)\n", "stat = DF.describe(percentiles=[.1,.3,.5,.7,.9]).T\n", "stat" ] }, { "cell_type": "code", "execution_count": 511, "metadata": { "collapsed": false }, "outputs": [], "source": [ "ind_10 = train_output= stat['30%'].values[:])&(train_output< stat['70%'].values[:])\n", "# ind_50 = (train_output>= stat['30%'].values[:])&(train_output< stat['50%'].values[:])\n", "# ind_70 = (train_output>= stat['50%'].values[:])&(train_output< stat['70%'].values[:])\n", "# ind_70p = (train_output>= stat['70%'].values[:])&(train_output< stat['90%'].values[:])\n", "ind_90 = (train_output>= stat['70%'].values[:])\n", "\n", "train_output[ind_10] = 0\n", "train_output[ind_30] = 1\n", "# train_output[ind_50] = 2\n", "# train_output[ind_70] = 3\n", "# train_output[ind_70p] = 4\n", "train_output[ind_90] = 2\n", "\n", "\n", "\n", "ind_10 = test_output= stat['30%'].values[:])&(test_output< stat['70%'].values[:])\n", "# ind_50 = (test_output>= stat['30%'].values[:])&(test_output< stat['50%'].values[:])\n", "# ind_70 = (test_output>= stat['50%'].values[:])&(test_output< stat['70%'].values[:])\n", "# ind_70p = (test_output>= stat['70%'].values[:])&(test_output< stat['90%'].values[:])\n", "ind_90 = (test_output>= stat['70%'].values[:])\n", "\n", "test_output[ind_10] = 0\n", "test_output[ind_30] = 1\n", "# test_output[ind_50] = 2\n", "# test_output[ind_70] = 3\n", "# test_output[ind_70p] = 4\n", "test_output[ind_90] = 2\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 512, "metadata": { "collapsed": false }, "outputs": [], "source": [ "\n", "\n", "# test_output[test_output>= 0]=0 #Long Position\n", "# test_output[test_output<0]=1 #Short Position\n", "# outputs[outputs==0]=0 #Hold\n", "with tf.Session():\n", " test_Label= tf.one_hot(test_output,len(np.unique(test_output))).eval()\n", "\n", " \n", " \n", "# train_output[train_output>= 0]=0 #Long Position\n", "# train_output[train_output<0]=1#Short Position\n", "# # outputs[outputs==0]=0 #Hold\n", "\n", "with tf.Session():\n", " train_Label= tf.one_hot(train_output,len(np.unique(train_output))).eval()\n" ] }, { "cell_type": "code", "execution_count": 513, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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kSWrGYCFJkpoxWEiSpGYMFpIkqRmDhSRJasZgIUmSmjFYSJKkZgwWkiSpGYOFJElqxmAh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\nGYOFJElq5v8D0ppWnbY6qzQAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.hist(train_output,bins=100);" ] }, { "cell_type": "code", "execution_count": 514, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 1. 1. 2. 1. 1. 2. 0. 2. 2. 2.]\n" ] }, { "data": { "text/plain": [ "array([[ 0., 1., 0.],\n", " [ 0., 1., 0.],\n", " [ 0., 0., 1.],\n", " [ 0., 1., 0.],\n", " [ 0., 1., 0.],\n", " [ 0., 0., 1.],\n", " [ 1., 0., 0.],\n", " [ 0., 0., 1.],\n", " [ 0., 0., 1.],\n", " [ 0., 0., 1.]], dtype=float32)" ] }, "execution_count": 514, "metadata": {}, "output_type": "execute_result" } ], "source": [ "print train_output[:10]\n", "train_Label[:10]" ] }, { "cell_type": "code", "execution_count": 515, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(39999, 5, 3) (56038, 5, 3) (39999, 3)\n", "test and training data loaded\n" ] } ], "source": [ "# test_input = inputs[NUM_EXAMPLES:]\n", "# test_output = Labels[NUM_EXAMPLES:]\n", "# train_input = inputs[:NUM_EXAMPLES]\n", "# train_output = Labels[:NUM_EXAMPLES]\n", "train_output = train_Label\n", "test_output = test_Label\n", "print train_input.shape, test_input.shape,train_output.shape\n", "print \"test and training data loaded\"\n" ] }, { "cell_type": "code", "execution_count": 516, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 516, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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DD3xrjSb24GSGuyzGDfZGM86cnM3cGVlMShse2QsQ6WcUJoJ649JQEQlNIOBYtamKV9eW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\nMWFmZmaleDFhZmZmpfwLVxBvLXx6iuUAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(train_input[10,:,0])\n", "plt.plot(train_input[11,:,0])\n", "plt.plot(train_input[42,:,0])\n", "plt.plot(train_input[43,:,0])" ] }, { "cell_type": "code", "execution_count": 517, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(39999, 3)" ] }, "execution_count": 517, "metadata": {}, "output_type": "execute_result" } ], "source": [ "train_output.shape" ] }, { "cell_type": "code", "execution_count": 518, "metadata": { "collapsed": false }, "outputs": [], "source": [ "INPUT_SIZE = len(sel_cols) \n", "RNN_HIDDEN = 20\n", "OUTPUT_SIZE =train_output.shape[1] \n", "TINY = 1e-6 # to avoid NaNs in logs\n", "LEARNING_RATE = 0.01\n", "\n", "tf.reset_default_graph()\n", "data = tf.placeholder(tf.float32, [None, time_lag,INPUT_SIZE]) #Number of examples, number of input, dimension of each input\n", "target = tf.placeholder(tf.float32, [None, OUTPUT_SIZE])\n", "\n", "num_hidden = 20\n", "num_layers=2\n", "cell = tf.nn.rnn_cell.LSTMCell(num_hidden,state_is_tuple=True)\n", "cell = tf.nn.rnn_cell.MultiRNNCell([cell] * num_layers, state_is_tuple=True)\n", "cell = tf.nn.rnn_cell.DropoutWrapper(cell, output_keep_prob=.8)\n", "val, _ = tf.nn.dynamic_rnn(cell, data, dtype=tf.float32)\n", "val = tf.transpose(val, [1, 0, 2])\n", "last = tf.gather(val, int(val.get_shape()[0]) - 1)\n", "\n", "weight = tf.Variable(tf.truncated_normal([num_hidden, int(target.get_shape()[1])]))\n", "bias = tf.Variable(tf.constant(0.1, shape=[target.get_shape()[1]]))\n", "\n", "# prediction = tf.nn.softmax(tf.matmul(last, weight) + bias)\n", "\n", "# prediction = tf.sigmoid(tf.matmul(last, weight) + bias)\n", "\n", "# # prediction = tf.nn.xw_plus_b(last, weight, bias)\n", "# cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(prediction, target))\n", "# optimizer = tf.train.AdamOptimizer()\n", "# minimize = optimizer.minimize(cost)\n", "\n", "\n", "prediction = tf.nn.softmax(tf.matmul(last, weight) + bias)\n", "\n", "cross_entropy = -tf.reduce_sum(target * tf.log(tf.clip_by_value(prediction,1e-10,1.0)))\n", "optimizer = tf.train.AdamOptimizer()\n", "minimize = optimizer.minimize(cross_entropy)\n", "\n", "mistakes = tf.not_equal(tf.argmax(target, 1), tf.argmax(prediction, 1))\n", "error = tf.reduce_mean(tf.cast(mistakes, tf.float32))\n", "\n", "\n", "\n", "\n", "# Evaluate model\n", "correct_pred = tf.equal(tf.argmax(prediction,1), tf.argmax(target,1))\n", "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 519, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 0 training accuracy: 47.9999989271\n", "Epoch 0 test accuracy: 50.1999974251\n", "Epoch 3 training accuracy: 47.9999989271\n", "Epoch 3 test accuracy: 50.1999974251\n", "Epoch 6 training accuracy: 47.9999989271\n", "Epoch 6 test accuracy: 50.1999974251\n", "Epoch 9 training accuracy: 47.9999989271\n", "Epoch 9 test accuracy: 50.1999974251\n", "Epoch 12 training accuracy: 47.9999989271\n", "Epoch 12 test accuracy: 50.1999974251\n", "Epoch 15 training accuracy: 47.9999989271\n", "Epoch 15 test accuracy: 50.1999974251\n", "Epoch 18 training accuracy: 47.9999989271\n", "Epoch 18 test accuracy: 50.1999974251\n", "Epoch 21 training accuracy: 47.9999989271\n", "Epoch 21 test accuracy: 50.1999974251\n", "Epoch 24 training accuracy: 47.9999989271\n", "Epoch 24 test accuracy: 50.1999974251\n", "Epoch 27 training accuracy: 47.9999989271\n", "Epoch 27 test accuracy: 50.1999974251\n" ] } ], "source": [ "init_op = tf.global_variables_initializer()\n", "sess = tf.Session()\n", "sess.run(init_op)\n", "\n", "batch_size = 50\n", "no_of_batches = int(len(train_input)) / batch_size\n", "epoch = 30\n", "for i in range(epoch):\n", " ptr = 0\n", " for j in range(no_of_batches):\n", " inp, out = train_input[ptr:ptr+batch_size], train_output[ptr:ptr+batch_size]\n", " ptr+=batch_size\n", " sess.run(minimize,{data: inp, target: out})\n", " if i%3 ==0:\n", " acc = sess.run(accuracy,{data: inp, target: out})\n", " print \"Epoch {} training accuracy: {}\".format(i,acc*100)\n", " ind = np.random.randint(0,high=test_input.shape[0],size=1000)\n", " acc = sess.run(accuracy,{data: test_input[:1000], target: test_output[:1000]})\n", " print \"Epoch {} test accuracy: {}\".format(i,acc*100)" ] }, { "cell_type": "code", "execution_count": 520, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 29 accuracy: 50.1999974251\n" ] } ], "source": [ "howmany = 1000\n", "test_preds = sess.run(prediction,{data: test_input[:howmany]})\n", "np.argmax(test_output[:],axis=1).shape\n", "acc = sess.run(accuracy,{data: test_input[:howmany], target: test_output[:howmany]})\n", "print \"Epoch {} accuracy: {}\".format(i,acc*100)" ] }, { "cell_type": "code", "execution_count": 521, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(56038, 5, 3)" ] }, "execution_count": 521, "metadata": {}, "output_type": "execute_result" } ], "source": [ "test_input.shape" ] }, { "cell_type": "code", "execution_count": 522, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "from sklearn.metrics import confusion_matrix\n", "\n", "%matplotlib inline\n", "import itertools\n", "def plot_confusion_matrix(cm, classes,\n", " normalize=False,\n", " title='Confusion matrix',\n", " cmap=plt.cm.Blues):\n", " \"\"\"\n", " This function prints and plots the confusion matrix.\n", " Normalization can be applied by setting `normalize=True`.\n", " \"\"\"\n", " plt.imshow(cm, interpolation='nearest', cmap=cmap)\n", " plt.title(title)\n", " plt.colorbar()\n", " tick_marks = np.arange(len(classes))\n", " plt.xticks(tick_marks, classes, rotation=45)\n", " plt.yticks(tick_marks, classes)\n", "\n", " if normalize:\n", " cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n", " print(\"Normalized confusion matrix\")\n", " else:\n", " print('Confusion matrix, without normalization')\n", "\n", " print(cm)\n", "\n", " thresh = cm.max() / 2.\n", " for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n", " plt.text(j, i, cm[i, j],\n", " horizontalalignment=\"center\",\n", " color=\"white\" if cm[i, j] > thresh else \"black\")\n", "\n", " plt.tight_layout()\n", " plt.ylabel('True label')\n", " plt.xlabel('Predicted label')\n", " font = {'size' : 8}\n", " plt.rc('font', **font)\n", "\n" ] }, { "cell_type": "code", "execution_count": 523, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Normalized confusion matrix\n", "[[ 0. 1. 0.]\n", " [ 0. 1. 0.]\n", " [ 0. 1. 0.]]\n" ] }, { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from sklearn.metrics import confusion_matrix\n", "# Compute confusion matrix\n", "cnf_matrix = confusion_matrix(np.argmax(test_output[:howmany],axis=1), np.argmax(test_preds,axis=1))\n", "# cnf_matrix = confusion_matrix(np.argmax(test_output[:],axis=1), np.zeros(len(test_preds)))\n", "\n", "np.set_printoptions(precision=1)\n", "class_names = [str(i) for i in range(train_output.shape[1])]\n", "# Plot non-normalized confusion matrix\n", "plt.figure()\n", "plot_confusion_matrix(cnf_matrix,normalize=True, classes=class_names,\n", " title='Confusion matrix, without normalization')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Conclusion: Doesn't work at the moment!" ] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python [default]", "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": "2.7.13" } }, "nbformat": 4, "nbformat_minor": 0 }