├── hmpback1.wav ├── mel-spectrogram.png ├── Killerwhales_jumping (1).png ├── README.md └── OrcaNet_Main_V1.ipynb /hmpback1.wav: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rohankrgupta/Orca-call-Classifier-Machine-learning/HEAD/hmpback1.wav -------------------------------------------------------------------------------- /mel-spectrogram.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rohankrgupta/Orca-call-Classifier-Machine-learning/HEAD/mel-spectrogram.png -------------------------------------------------------------------------------- /Killerwhales_jumping (1).png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rohankrgupta/Orca-call-Classifier-Machine-learning/HEAD/Killerwhales_jumping (1).png -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Orca-call-Classifier-Machine-learning 2 | Advanced ML Project : An Orca Call classifier using mel-spectrograms as audio representations to detect Killer whales 3 | 4 | I have used the Killer Whale (Orca) Call Audios for making the dataset from the FOSS Organisation OrcaSound, which has hydrophones in Seattle to listen to the Southern Resident Killer Whales. The audio has been downloaded from AWS Bucket and preprocessed to obtain spectrograms. 5 | 6 | Dataset Size I have used is about 240 Audio Clips. The Instructions to download Audio Clips is given in the page below : 7 | 8 | (https://github.com/orcasound/orcadata/wiki/Pod.Cast-data-archive) 9 | 10 | ![mel-spectrogram](https://github.com/rohankrgupta/Orca-call-Classifier-Machine-learning/blob/main/mel-spectrogram.png) 11 | ![Killer Whale](https://github.com/rohankrgupta/Orca-call-Classifier-Machine-learning/blob/main/Killerwhales_jumping%20(1).png) 12 | -------------------------------------------------------------------------------- /OrcaNet_Main_V1.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "name": "OrcaNet_Main_V1.ipynb", 7 | "provenance": [], 8 | "authorship_tag": "ABX9TyMstrgHe/DG1K0V9suAjn3Q", 9 | "include_colab_link": true 10 | }, 11 | "kernelspec": { 12 | "name": "python3", 13 | "display_name": "Python 3" 14 | }, 15 | "accelerator": "GPU" 16 | }, 17 | "cells": [ 18 | { 19 | "cell_type": "markdown", 20 | "metadata": { 21 | "id": "view-in-github", 22 | "colab_type": "text" 23 | }, 24 | "source": [ 25 | "\"Open" 26 | ] 27 | }, 28 | { 29 | "cell_type": "markdown", 30 | "metadata": { 31 | "id": "Fqf5c4V0-2Sl" 32 | }, 33 | "source": [ 34 | "We have a total of 240 Spectrograms representing 10 second Audio of Orca Calls/No Calls
\n", 35 | "Due to data scarcity, we cant use CNNs efficiently. Thus we first extract the features using OpenCV library and then train a Random Decision Forest on top to outperform CNN benchmark achieving overall 88% accuracy.

\n", 36 | "Total Orca Call positive Spectrograms : 120\n", 37 | "Total Orca Call negative Spectrograms : 120 " 38 | ] 39 | }, 40 | { 41 | "cell_type": "code", 42 | "metadata": { 43 | "id": "ih_ZilKkKznb" 44 | }, 45 | "source": [ 46 | "#dependencies\n", 47 | "\n", 48 | "%matplotlib inline\n", 49 | "\n", 50 | "import matplotlib\n", 51 | "import os\n", 52 | "import random\n", 53 | "import pandas as pd\n", 54 | "import imageio\n", 55 | "import cv2\n", 56 | "import shutil\n", 57 | "from scipy.stats.mstats import linregress\n", 58 | "from tensorflow.keras.preprocessing.image import img_to_array\n", 59 | "from random import uniform\n", 60 | "from sklearn.preprocessing import LabelBinarizer\n", 61 | "import numpy as np\n", 62 | "import tensorflow as tf\n", 63 | "from tensorflow import keras\n", 64 | "\n", 65 | "from sklearn.ensemble import RandomForestClassifier\n", 66 | "from sklearn.model_selection import train_test_split\n", 67 | "\n", 68 | "matplotlib.use('Agg')" 69 | ], 70 | "execution_count": 1, 71 | "outputs": [] 72 | }, 73 | { 74 | "cell_type": "markdown", 75 | "metadata": { 76 | "id": "0_JHw0kP7hgC" 77 | }, 78 | "source": [ 79 | "Importing the Pre-processed Mel-Spectrograms in order to perform the call classification" 80 | ] 81 | }, 82 | { 83 | "cell_type": "code", 84 | "metadata": { 85 | "colab": { 86 | "resources": { 87 | "http://localhost:8080/nbextensions/google.colab/files.js": { 88 | "data": 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", 89 | "ok": true, 90 | "headers": [ 91 | [ 92 | "content-type", 93 | "application/javascript" 94 | ] 95 | ], 96 | "status": 200, 97 | "status_text": "" 98 | } 99 | }, 100 | "base_uri": "https://localhost:8080/", 101 | "height": 89 102 | }, 103 | "id": "Ug0FhcRZmdjk", 104 | "outputId": "e3b00a76-2dfa-499a-d12e-d70142f8f824" 105 | }, 106 | "source": [ 107 | "from google.colab import files\n", 108 | "\n", 109 | "uploaded = files.upload()\n", 110 | "\n", 111 | "for fn in uploaded.keys():\n", 112 | " print('User uploaded file \"{name}\" with length {length} bytes'.format(\n", 113 | " name=fn, length=len(uploaded[fn])))" 114 | ], 115 | "execution_count": 5, 116 | "outputs": [ 117 | { 118 | "output_type": "display_data", 119 | "data": { 120 | "text/html": [ 121 | "\n", 122 | " \n", 124 | " \n", 125 | " Upload widget is only available when the cell has been executed in the\n", 126 | " current browser session. Please rerun this cell to enable.\n", 127 | " \n", 128 | " " 129 | ], 130 | "text/plain": [ 131 | "" 132 | ] 133 | }, 134 | "metadata": { 135 | "tags": [] 136 | } 137 | }, 138 | { 139 | "output_type": "stream", 140 | "text": [ 141 | "Saving Spectrograms.zip to Spectrograms.zip\n", 142 | "User uploaded file \"Spectrograms.zip\" with length 217168372 bytes\n" 143 | ], 144 | "name": "stdout" 145 | } 146 | ] 147 | }, 148 | { 149 | "cell_type": "code", 150 | "metadata": { 151 | "id": "95WuRRAXnFuh" 152 | }, 153 | "source": [ 154 | "import os\n", 155 | "import zipfile\n", 156 | "\n", 157 | "local_zip = '/content/Spectrograms.zip'\n", 158 | "zip_ref = zipfile.ZipFile(local_zip, 'r')\n", 159 | "\n", 160 | "zip_ref.extractall('/content')\n", 161 | "zip_ref.close()\n", 162 | "\n", 163 | "base_dir = '/content/Spectrograms'" 164 | ], 165 | "execution_count": 25, 166 | "outputs": [] 167 | }, 168 | { 169 | "cell_type": "markdown", 170 | "metadata": { 171 | "id": "062LpyzF7w6M" 172 | }, 173 | "source": [ 174 | "Sample Mel-Spectrogram for a Positive Orca Call " 175 | ] 176 | }, 177 | { 178 | "cell_type": "code", 179 | "metadata": { 180 | "colab": { 181 | "base_uri": "https://localhost:8080/", 182 | "height": 286 183 | }, 184 | "id": "-ruxqnmFmmCh", 185 | "outputId": "dde0c43c-48c7-4626-825d-baee33ad1c10" 186 | }, 187 | "source": [ 188 | "import matplotlib.pyplot as plt\n", 189 | "\n", 190 | "image = cv2.imread('/content/Spectrograms/train/call/spect-123.png')\n", 191 | "plt.imshow(image)" 192 | ], 193 | "execution_count": 4, 194 | "outputs": [ 195 | { 196 | "output_type": "execute_result", 197 | "data": { 198 | "text/plain": [ 199 | "" 200 | ] 201 | }, 202 | "metadata": { 203 | "tags": [] 204 | }, 205 | "execution_count": 4 206 | }, 207 | { 208 | "output_type": "display_data", 209 | "data": { 210 | "image/png": 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dv17qers1+nPmxjdIY1N0gzx1dQup8MQSp+MfsMpMJvAoA7171mbXPg5qXpwDHRMLJ+4NZGhxEriB1o2pxXPaakurDck5TUV1zz4wYdMRlVUSvde3Y2c7lVqdD3Jirz21VjQ0BDUocc6vOMqRTKahptOWUSb3MEYK38g4RDZQQYWahkEmFpnptGPVhYqOpBnBvUZirKfVqSHR21rR0GrPwri1vWipFS0KJE1kMicZ2esNd/qcPj4jxJZmGQmxY1gneloH64mehlbNcP01D+zdh1u5NpdRzow0VBzlxI6e2WGgYLA6kR2SwUF7Gm1NA5OBwj1rHIaWRZYlE92tk1jdvGC7temDFSszSkYI9Lp3rdQ+R4RWDQhnFFGhp2dwSsNOe05y5rm+5MyRhYWKiQMveKnP6OXWNDhN1NKz6JlJJzp2BKlY80hLx708mO4pwsv8jEEGRj05aaOlwZwfUWqCNARq1jz6e9TMjCQGOvYIsDITiFRauUngjPgYPtMbKhqCGLqJ2gKJI/eGXEjU4QCqSKip2BFCQ4gt5+nH9PWnLOsDIpG77h8jVodNmnTLkbQcOaWvGeREIvOMT4haUze3CBGRSJMeEYQln4n5wedZ5eDefJ1nOSKY0yMgLLLQUPGlvOZBTtzmHVEjz/U5r8PpiVPvz/EZAxM7aflSHwkIB2l5yCO1REYW9vx/7Dz4ZYqp2SvP9QYQbvOBB3kkSmR3+McZTgMzZsPptGVhYScNkUgve1o50OWBL+QnHGVAVDaoU7hwgtJQX3g1auBGWUmSCBpZWWjda1fpRd1tKfTKSFBhlXVzoe/puedoA6iX/RkXClEiSTNfyRsiwjM9kMh8JQ/cYrafQQbMK2gg8+INs3ccZDB6g3YUDl6nHT07TnJy4Ww2Int+YOTsS98c8JlMpKIhszC7Ta9BRKm6l4znP+aR14TlgSDBQa1BxpmVzrlhZxaec3DKgPDIwCfc8SAnKrfZPXDiTg/UWlNRMTOjok6DsAlcuY961ZWjnICZzrmCZYLXWlHR+FZTrHT5CoavVxuTLXyAmZGBMzfcUaEIkSMP7NlTuH9CYGJkpz0jJxf+PUb2TjTa8lp+yl4PZBJZT5w5Mcpkm1WeqWkw2BuZZGZSmGRmpzsWWUzdAhrZEaUGLZtmRRZIahB1YrDnCqgGFlZg8Q21d1tdYGGko6cNNyTnganDweBQfmWFDFFqNCVEAppnn68V4/KKQM2U3tCSEc1otg1SJBCkopWegTM1FU3cU1d3ECrQTF4HM0/khagVHTtmRt8UbBQSE7NOzGL1VhI3r/jAAghJEjvdU9Pxg/w9vg6vWJg4M7NjZpXExMKd9DzqRCJzGzqKt/ikywflyTcHir5VnkKg+EQ9le3fuz/g6mtRb9+jsX5YibVJdw0d3qfqw1Xd7uwpjrQPqvpX7Sn1KbrdV9p83cJr9Vzf+nwB0h8A5iLoW30gV/8ubZWn7XHBca3pPu0hfefzNRfw+vvr2j/YKdf3yNPan8C3n4sQ39PWt8bkbeb+u625NlPYPFC9wCp9z8/bLVDRt8bpunb5wHtcQze2a973jMvG9YF+/UBXK2pexydsfvvu8o7K27Hj1mb79+5YPvUmI2/H01zVe/Uu+s69stFutprfgqZlfZjTVd//7lflG6OxjSweQdCxrG9YnEA4MUN9YAorMQe+Jz/gpF8zMSMIUQN1vKHqv08ePqdKX7niq8xSHAS2m3XaUrkxepaZWYz1HlSuOssAzMJKS4+SbXfD1OojR4eQNhCJxOJQ7V7OKJhqLa95rs/p6Ghywyt57VyfllprJjmxpyNS2E3QaM3KzCiDaZvZWHuKbrwkwUy/rXYkVlYHakpmdoN045C61mrTKEYGAsbzMsJxTdLEwmBOjGnPoEcmMU3urBPf4qXzn0z1f8OJhcRzdnzOm43kLMBLvovoFyRWBpm8rwxigvEI99rR+jgkWRnkRK87BKFzMqp4vxZOe0VFlGZjvclVv88y06txviIWVaIoo7P6G202LS+5o2ZmpqFhkonaOY4j06Yp1rTeQzZ3St/17BkZ6X2OhsKrYqGPL2jykT73dHLDqiNN2KN5NQgoFUEqcp7JurK6ppXFDCNNuKMPL8l5Ac3EUEGGk76hU4sjWVmoaYDJ3kdnss5Gk0CZGahoWHR2vppQhT1rHlBdyGom/YETO/Y+44QxP1DNA0Fq6mpPTgNJZ4ToLMyBYXlFXh02h4YlD2S1tr+RR05hQFEmNS7pDR2V2JyMRM5MPOhkHk86vsvzjQ/3Wl6zSmZioYT0tVgUzRvOVAQGkq0BIoPO7KQh6coxzx+UJ98Ija1I5LIfqOarXQsuEZNmS3oqrQ12SYiIXKJL337AtZay7ZxS9hZ5eu2miV0Mrttu4zvy21rAtcZz/X2Bpu/bw7eo0mvNQgrR9t398R0NUq53+qIBXlpxbba+1gveNtMqGfRCoS17bLhqgVIotfbueXvbQqyN2/UbLUPypjVeWvRUg7p2XHxIt3vyHk+M6E+dH+WVrtt1PR5FCJR7rrXkDxnYTRu/aDhlY7luhcglfK+YPsLmww0EiVw3/NLDl9kTxO68aEbh7Zn5tLhmVTSst7XRJ+OuT7Wm6zlbRlY1b62DvNW0mQDUiMmqdm2ZKxdjgNl7VxJJ0marLu03W63N7EDY+lglO0kmbU+/zMqn73ita/LW72+Xb4TGpkCN8bUSmRMPm1G815b18Q8QVUZ3mffsWbDYskSyiVffUdUn9mnPomavqrWmVjMbC9DQumlzJea4sbeLa3phKS47ItEd7YladkStXTOwCTfr7JqSRTtY7F+J5bOA6sTCIKOHMgnP9cAtL52yUPOGN4yysPPJdmTgVg8g6vwetZ1WkmtZZidL3jdlMtVqWl3R3zLKzETrXLTVnw9m9aspGlBmZiKo8JB/ikXOwshElMikE3vtSGKT+IaOwe1qeF+81Du+lnvqmx/Q3H/FYzBu0UF7HuRkzgAsPO2WZzzwhkik0mj97e3Af2s9EkS5OI8qLKLCFpaYzU3U5oAvnpWFhpakRo8pAe3Jl9vKSqcXp0FNtYUoVUaMwDhtIw17Zk6bwX/WiZEzHcbSL7xHK2JaFkarUX3gKGducvLrhTWdyZq4mA9gcefAXm7NMZJGm3ehIaeFoMKeg20wUiOaqUJLyhOTUzZmBkzLrOk8DKrw5gI1EiIVO7IuLPlklCDpEYUYOzRXRF1JzCyMhNWEcdZMU91wS88uD5x4w6RvbK0qRAkc5cwu94A5vw7ac+c0oL1r4aOMKOoROBWPjOxp2bvG2OqOV/IFCjzoxDMx27ZgCsyOmlUzgy70YjzIOSfamNlLi/4MtewbI9h6WtrcsTBzK5/wNV9YXKdkNBtfrKdDFLrue6QxM+gjKkrc/7ZNFzXb0EFe8ppXNlga3EheM8lEVgu1skVsnjNzKBjsKVlEMkIWOHOi0oqZiZ4dQQOTzE4qNcP/JMaYq4l8zZEdPR3dBqezZG7ynkhk4kRFxegcncqJmosstNSc5WwCSxK3+cAs87bgZ1nMEXFlLF9kRtU4bZFIVou/3OuBSOU8IwWCwzBjdy1OKq0cjs2MBAl0tMwyc3AuVKPmzRQxI/vqQdk7D7fJZJ7rDbL7LuOjEWQnEi0LPS2L+yh7bWnCjl2anXBbsk5UCAlcQBe4uMrqY9caIVQuAf/m1zbhvmIB8CVUqt4g6cXZADa2Jzk5/y1Sa83MQq+9eRj9PsuWYTGSaeOe9QhCE29BlVgfTKPSBaQihJrb1LAujwSJtHogu2d2zUa8rUNPFfaoLqxpoEKNnBtvAd0EW0qTGdDlkVYbQFh1si1MJ5+vLdnJ6hUWP11JixBJah5i22EzKU/MeqaLz0ANCYz6hoo9i5pZxWbvQq0ddWypVEATqgk0u7e/JWhEvd+DmlPKiNSduwxqSuT2wsyZkUcZ2GnLre5pQ01Qy9rynE8A+Hb+lJkZwj2igaPOVKHiuSe1+MP8Na1UNFSsJA6h5Zhm6hiZdf2gTPlGCDYBRC8qfiBu8OU6uUsgmB1GLPTd7hWIjf/u8E8s+0LWCwQqaXCyJMQZ15lMVKGkPAoYQfDagFo0mwtUls3IrXqxtRUVenUqRiAY/8i1m6J+m9otG6y7pJeR7XlscNQWv4WZFRj11KD8fgNzed7TNEOX665h5KXnSk8YtHwKza65eeX9gooz1yNI5e/k4EaUkh3iAhrCFYy7OGOePGfr3+ywjCc12O8XLY+rELz3GfNLEUqanKewsEDF4igw+JoRt1te2uU5YARzZkmAnEEiSCRKTZbKKBiq4BtKmcUFbmZNVyMezGO5QT+/Q9Q1vPKNA3/fuK/ftZgFrvt0q0t1g43F43p9b3luMTPY30ubCiS9wG9DA3ZHgdzRrcTlmmLfKzD3Oh3StYMgurW3piI7wgGf73pJfZTIlh3FceglHdL7Zv2lfCMEG2D0CU0eyrSy6GrR/1pT1QfCHMxRsP8O0tzRt89I93+XKT8imiFECA2LZLp6x2G9Q3JPCccB6LRHZEdiRR3ziyhRAwXRj3omXMFQC6SxPTKTqel4zYNfXbhSkT2twR8xrtQruedOTeU2Nn1NzwEL4LEA5HsGPuWG0Vn5jbam5utAJw2rrLTaEF2TKTA0EJwDZi7zy6JVkqys2GKvfIJlyYgGJlmoteJRju6IMAi2uiPmyMi35DuMfM6siW/zHVYGzhwRYGaho2HWhd8KPyDnE1lX9i//IqiFjD3jwCNnRNhC2KIE7uRTIpEuHMjZnBwVFYOcAYPRjfQErSzqg0CS1U0Ol3lizpxIrYFFLKOHiFBri7KY5qmXiIVAYGSk3npDSG6IF8Qgv0JNy4jxzjKTP8c2k1p2JJ1JjhzydLJlLBV1dYvqSs4zxT5sbHrTYTIrtXZE8WiA0NJE4xOihWIRCaGxCIV8BhV6dlROaQGDv5V0RpnJR0oUw8rCxEylM8LKiUcAbqnJOjNxsvco2o0YzWZODzTxlof0Eyy0LoLCmN5QSQNkJh04yYk9ByoxR4wNhrDIilBRa8OJiUoaGg7g19R03OiBhpqVxEM4e6igcNDEyBGLhJkZZDKzjlhmlKzKT3jDt3jGXTDOJwqDv0PE8t/VfDj64Bsj2M4ybabXKt5wn0e+o8/Y6w1x933u0pFlvYebPw8iRE0cdr9NO31t8XXrAxJrWumpqhtuaJGwonkl59EGRIIPzEirloQwittr9HylNSUmmd3fWGwZyuw7S6WB1r1oJzlZNgXnY73wDAglnrHYwB7kxMSKMaQSDwzsxBZ+FtPcenbM6BYrOTLR0rLIwsTkKYYgiYUlLbJQa03vsHFituu28KnBhJrvpDUVJxn8HWrP9bVSYk7PYaapX8DyueXw0hohs8o9FZEJI9sGAr3ckIDqxT+NHv5J0k/+B88EZoJ3YuGZPqOWmZfh+/ThjpwGAhVmg7Q9OWvh1DXUTry+NvzbtnEJQSrfFINzJtNpi4D3h+WhaxxaAg5rLdNLsUU2tDREHsXyk91odFhbdKnIyEBHz6wWUpR1KUvRNdaK4/qGHTegiVnH7d7iCIjSkZjQPKNi+nnOK2xaYroIr9Ag2eZgSehjOTFmRCoagTWPGO3YNMqznOyd1MamItJIDxpYnCD8yBtavSVWPSFYH8dqTwgNcfiKXftd0vzIl3xueQ31xE14QSsHZp0Z5EzWlV18QS0H01B1b2snz3QpEWmoqgOqK5oXslrca+c5FQcna/c0JEk8cuIe29QqT0O2o2HSxKKJF2HHqit7aZhInhrMtLQuVCRVeC+txso3wisKZgjP4qq/VE6oNWWX2FKLCRKNPYQaJBBD57YFIK+b9iQSidKYqz3YbiTudRK5nrpxY0tfoNElEy1Y32VKp14gaQmKTpJIkikeG0s9kzdNqXhQE5lZJtNMPTC+ckN/lsu7mzUsbNoC3paimV17k1ZvV/k+OwS0v0OWdHmPotpv9QRE5eqdzCUQtoy63nYpKR0voKgUkUion0Fo0eWRJHkLMs9X7arpEKne8uCVVoQn/7+AjGsjQri678o7DVvb4S0P6HVfXQlL/Jvy9CymBV8cGJd+vgjY9KQHLj8rSx7Jamgje1yLbnZNtv67hn/FJxgAACAASURBVH2ak2tr/gbqYyBllORJW8vT7Oq0XaM+d65NFIWQXe4UidvcggASzQMbWkTMCRJDRxBLImBz0zSrKG639W3SNMuaEBoqaU0QbyDTWQnFA3zFN4v+A2yQc5WVUWYmWX17yohaTGjJZ5jlojVfz7vrtfGh8o3R2F7mF4xiTPmcR3pqjnLmefw+1LeE+o56PaKhhfMPmc8/ou4+I/bfQkLttg6hCbeErCzpAZJrGMEzDzhHp0yomcnxvEGySAUizO5VRdkGpNjDLBjfeG4rlunDvKNKEst0av47G6yS5bbG8n+trAQJzgGrPCvDZeDMGJws84PMJMmcxaBRQ8mgYHdU3g5zZAQQdS7cheHWqCXcBGi1owQtX+ozjpklBRAkNuxzz0Ge0bSfkZZ76lwxMrOjo9KKs5x5TJ+DKnfNS+LwR3yuP2ZyL+WzfMMkM4/OgRNgXY9kNR4X4GFQunl4IxUCmyY2YUx51cRRjubldY1rkmm7TzBaSQl8X7EFk8n0ag4cFeVBTuZhJ7HTjsyZho5FV0v6iGlJkyd5vOE5O5SaBgvptgwyq2cimWUm+RiMWMbcRRaiRlukrAgTMZvxodGWkA1arjpCAhGbeUEqg7BaUYUdc34gsxKITKav2Of8QGLGvPOm8TXZct/V9FShR6JpTml+JIY9sbnjebq1iIzsUK79BPIEoaaW1jUs4z/2HAwm5hEJHb3c0rJn1QkI5JzAGf+qJaqgQcTYoiJCjMKabT4VAlalkZ2YY+7EyGu1jCN7MY/pvQ6svukeaLbkCx0Ns6+mViqOeeIm9Cx54pQ/HHnwjRBsArTacJIjiZk3+Sc0EpmYzfbw8PuEww9oY4voxHT8f3hcfsRNOhOlpuq+Zftp9y2aww+QdWCcviAnm+w5mLCpqKiD2zp0ofIdLuvqu0B272hNow2LzLZ/qziUayw1jhggsXwalv7mzMhCshQwYtlvFUsl3UrtgG/mNh84cqKTyheKTduGint5AErql6K1JRqttgSLgoXstNoQCQwyMchI5d7ako2k9rjWScx+ZvSKdevvBzmy045VEoOM9NpSU4FY+2/1QGzuCM0tz08Tr/IXtNrQ0rOLL1nWRzIrMn7BeP93WRi4y7eMYTDnvkYe5EgkMKUHgpqONnIioSwyW+ZbWakIqMKX3FNJoCaQHdLOMntaoNUhtLj9sGKU0af86JuO2fNmWYkaOMlARWD0nBjFCRNk8hjRR4NH2vJa3nCrN97H5okUhDruyemewcPTADp6E6DMJBKNdpvQK3pdErN9XShCSlRzei1uw0Nt6dfqG5bORLF46VEGixOVghYUS1ZuG+DMTG8RvEaTlkgVWkJ1g9R7EynVDiTQVXtYz3Z2RRoJoULTQk4TlXTkNJKLp1mzE4InBj07NadBUM7pa7OLMlisLHDkxCKzzar0U4xWVdsGJuoZSowiVGvlGXSVT3lGUKHXloXEgwxEoqkXcjm7YWFl1IU7er7Ils59IbMLDatenC5vl2+EYLsuSbLHzV2Injp9Dc/+GcJ6g+SVtB5ZdGRdHoCa2Dw3OCKRUN1AWnwi+CTNBv+CZz29JgRToIZePJUW2l1i2zJBgntkCk3BQEfnRBLjwCWyXiBQ4bsZtHSYuHmB3GvqmlrxHJldL/j+XAiLugm5AmhKSp9tEZEQuaTbLnndLKtv2lzs61WOuUUWMrU7G4wCI2Ke3NWpBBIihJaGnsoFZZSKmgOZs/Xb8sA6v0JE6GhZdd7gR/FwpjyDg6RE8o1hJUp0jl8NbnfZ0SJU5n3EcuhffK0Gcy3GVzYYtqqlUFolb70iIqy6EGmch2de8iDiyQTE+8DqtRRZN5d5yOL6hts1SSCm3ZefMl9Le0QvHl/zixrHMmiNSnYtzNJsFe9oiTe2+93L7l7xC4S8eI/LuKer+RuuUvhIMCgosUFCA7qiYu9gyRwTmhfrzzzbmGuiJB4q7SkcxxLtIuDCvmGWwZwzKkxy3gR4oRplzxdY0Xr9Twntgp13IYijhtm1VyHKlXfU10bZ+BfX2hLZ8iaG/x84DxaZaN3jNoupmDOJnCeWdKat74go6MpJjr5jHrmtvoPEDmIPKLl5hsz3RA3gXiXL9FFRiZEXEQt3Vs0eIMwmBC8UCYN1lxOOIhODeay0Q8LMwMRBd0wyU9InT66JqLBx2yZ3LiSHjZtwuXJz7xwmRrFzBI5ypqUhKD7ZZBNoK5mjDDRaUXkyTSPx2sIoOe07akquklIuHD5rX7H/TSx0uWUaviCRuZcH9usZff5PEKoDd69XWGeau38KiQd20x3r+CXz+Y8RIjc8o69eICnStZ+iaSZyYxM6jzTNSyRnJNesOprTQg2W1w4xn4mFK1n+tjMriV47gghzobu4y38WA/GNVkSNTLJQqeXPL4JhdUgY1JI0Ahw8wQBYSm8RO/Wsdj5YIR8PMppw1q9JWN66RRffmCxnWy0LbW638CnLbLdSS4dgBnFRzOsuakHl2rDIylq0HN/wGm2dmH3yjTAzMG60CjvLoMB1SxoZME6jEAlSM6dHwrTQ1M9tbudEWh9Nk0yJKnSoZtblDYHAms2ZM3FGNNNL6yF0ZdPNTD5XAoE3crS5JJlVFRGYZHGt1FBNsZfaHHo0IruIHzIzM+m6eTNPMnNHzwMjS04Q7KS3RRMEQZ2buZOGL/PRNDnVDZY+l/6D8uSXFmwi8lvAfwF8y6QFv6Oq/7GI/PvAvw186Zf+dc+m+7NqM7yte5I8YFk/Fx7zxKIn3vCKT0KFdt+jmj7nKGdqhDNnYn7NbqiI1S1RF0QX5vlLyAt12NnO6Atp1QlUETHuTFLLwLvISGHnC6adLcw8yJkOy4hba83Rs1ckH/SBmd6JIDUVIoEj5y3h5Z6WE56VwBfMKH6gBReIUk4TSu5QaIhEjSxSMldYRoQbZ8IbqXKlkYpFEyXjbhal1ktAz+bykMwDJ/elRdTz0ye5HBMHRsYd16+NPkEFaUaWe9h9jz7/BTIQus+Q6Sti3BPjyGn6MSc5caN3VNWBfdwRYofqQM2OnI38WYWenM9Unq0kszBxcs3FFkjtMAQtR/C59qWBLDCLxQaW9FMlTGeSlShiiQxRN+EnFknb6QEW2ZIJan0wyOT6WHAtUJhltvMffEMDOOk9IoHWPa8VDRMjoxgMbemcFJvcthao6chYrv+MhRg1dKBqRngFxDLEVC6YN42vaC4aGcPEinlzZ1mpPUJmZOalPt9oQrMOBFZWHQjr4ALLHFtTPrG6hzurbWKthi3LsB0faW60VlvehK9JZA50VBo5y8Tg5oyBGc/5S8BSeQ3YmPTUlFPQLBrCIjvMmWKRCg95JKG0EjnqSBZLdWXH7em25rtQcXaB2FDRU/OGgb00POQJUEZWunDxfL9dfhWNbQX+XVX930TkBvhfReS/97/9R6r6N/8klRl8seZY+hWbnEkXRhmNCV2ZRzSJ0mIptMf8QD1HJC3mBVUlL/eoroS4Q7IxxC3cxbC+aHbz+oRiCyZJcm3AJvpK4lHOBHYOM9PG3SknWWWHd8AG/SbsQJOZxHP2vOZMdguGkUHd9O/8uY1N7/F1eAhSQ82ZkSxQMv4GjagkShRgUEsSUA43KZqg6aORCwFXGWT0zKVxg8rZBUPxaxnr3xZ8px2gyPQVtJ9B/xkhtCZ01iPkBUTcwjVwwNJNhWqPaIG8wWMQBdVMVguhEglsqTdw+gqLaVqa3WwgBA0bHNtiEWV176o4vLbFdUOPiC3cRVZmNYKIHSnI5oEu82uSmdo94puH0TXXymkZqMN+cbiPbNrfmcHOx1R1w7pS0mIjQsqL97GNq5/FZDw7hExgxYR0cQqVfMOZyzmmF7aAUs48nWVFVDxsrmFlJujFA56zpSSfmRjCaERdyUw6s0gisHcYnJiZabnFAstMwRhY2NNtmlfZAAXjJjbu+ELZwu0yJQOx/UStaMUET/HbztgJVQU1tFQMOnMjLSJ2WtisiQONrTk3PRRyeHM1xwvZ50PllxZsqvo58Ln//igiv4sdlPxLlZqGmQkLyVkcowei+FlB5z9CuoV0//tU6eIGnpi5EWOFp/kVy/KKV/lLRGb6bHv6KAMl68WiZkQ2O5Z55iwK4ZKOevUFEV3ACsJZpg33n5kpiZQKraGktDahbAJ0ZHZfq03cciSbYuc22DWm2RksWnyXM9pEyXfW+T2jjA6NTXgVja4IJlXT5I46+SlZ5sCY3PfaSEJUNm2ntH9yT23S8hezM+Z1ZD7/kJgmmu4ziD1p+JwfT3+PQ4qEbPwlgHu5R5aWVp+R88iaRoJEjvoGSCzpJyw6UlIiQeYsg/eR5XubWV0zMZOBLT3xSZw2AS9i6cBr7GzXxfsruRY968qiFk8ovogsk54JhbMudJT4WqvLZop7prXiDSdeuJDZssygjPLaZ44dPdzJEVBavWgPJaD8YvQ3OnixCBnBuKSqNzqSbbQzUTOTjMyyuGBZt2Pveh+vnbaMjjKKsOu15ywWO1rS4a8kRmYaMYJrRt2bn8gy0mhNTcWDPNLT8pqHLXTp5IlKB12oXPtPZPbaMWLe32IXq7a1YutyZiGJ8TejBgb3IDcSSdjaS34gi52H2lEO3Qa2v1cSWNTGCzAtTSomd/bdp/GD8uRPxcYmIr8N/AXgfwb+EvDXROTfBP4XTKt7/Z57tgOTA0KlRh5N2LmZQcyQaFyaQBi/IIaG6fRDKs2IT8xFViPeIqTlnjVP3MtrKmEjPx5ltJ1Zjf+0ik2JhYTKJaHkKOsmbCp2dsScu8FHsV3ZbFN2uDDgk1M2eFlp2ATjyEItkV4bT8OXKGeKlokyU+I+I6LC4ry4hB0zVhI3gjL5BCnEVReB5hXDtL9RFx49DrWV6LA1bdpZcP7bJCu1Rt9JV0oSgmKQjxLJaWJavqSd75Gqh7yQH/+Qn+r/TeaGRmueyWcAHOVEn95YJEM+MutIpOIk91RSMafJjMziMFMCR0ZPOmjH+5kZ2g6mLpqzYIdVm7etYhLPgq+m25blXYTIyExSWzy9mxEKty9i43mUmc4DzEt/ZrloAEYovVAJTDO0z2embfHPZM5yxo7yi5TQPBNs12w8nKtmUTAiRvLOaklIg1hs5eJJJwc5U+yqZWPKtmjImtjROd3E6NWiFkc9ehouiwQwe9REItBuhzav5M2J1PrxgK94IKA8YOeuLkSOWKbaSReCZz+e1VwW5pG180aCw04Twsnmpaw2qto6cjClwLJGG9m2aHE7adhpy6OYJitiXLZiqhl14eRpnmYSrVwOzH7UD6ct+pUFm4gcgP8a+HdU9UFE/hPgb9jU428A/wHwb7193/WBybVEnWQiSaLDDn2ww2lN4CwkxvFz2gxDfmDyJQ1GE1l1RESdGb4groVQdgcDjR45INR+huMoC7Ouztsv5FDLNLL4hKl9Ehce24q5q0csg2+xdy1Ospx05aQzIph9hIpXeqL2ZJnlJPFy8EXvGk/hwa2kTaBF11qLl9HOEy2ZwAo4Ma2j2OsSlreqJlIOrAHo3GheNg70kqmkoaIkz86oazUnWlXOMpARhvH36dgz6WtaKs5M3HJHjHumvDIw+6HAkP2szyln9mKG/UmXzc61+DiUUrh8q9obTGIHOCcXDYX8vJBYNV9gCgaFRC+0mUkTjcSNbnNm3riFJclivWkGhRF44RGubjZoJHLSERHLD1bseeWw6uLRHFnsRHRxmgPKwErxiRdy9yoLUY1wXvl5mJVaiF6UhqALi5z9+KG0tW12rWxV3SgvKBtXr2ikWR43uF5hcbwzZohPW74zA8RRI2cZOXnev+QhdyOrI4eJG93RUHn6beubRiqDsyRec6QhMmuiHD5j0QMXh9WMUZTOTKyazcbrMD+q0EnFSWcUYXK00EpFLZFTnjnrwkkndtLwkC2jyaA2W3ahNq3vA+VXEmwiUmNC7b9U1f8GQFV/cvX3/xT4b3+RuqI0RBb29CRdecWR2vOrjcycph8xL68Y9EiW7CbF7GmJZkY1btAia9k3Ocm0eWFWNbpsLzVRAw12WPDk3rXiEIjYsV/GSlMXO1YW165qidspSyVVUaMVD4ycdCKpMovFstUaeaVnPpPDZvdSlD0NjTabFpMoyXVKYkT1kxEu2atmn7SrZqce2M/k0MP6nO3U9NEhvWBCbNDFbUZwybWmtO5tW9zDNVI8diZ0lBNfD1/wbV4wuvZ7ZubQ/lli7FiHzEmNK2bjYELktZy55VPEtcqGCCqceUD8WL2Dxi0x5hkTgMLF7W+C14T64CJtVuunKIW7Zh7po04upIywMGMC1xKjO3FWxDXVEkFiHseF5AciDwwymfCWcdMcil21UHg6T1de2l25FhZo3PSxUhLTg6W5KtESmWgeRSZWMadP0pWZ2bWui7BPZFChknKMpKXZLuaahopFEicetowsUGzW9vSGmoGJCmVHtwnpkwysxXFFZlIjdXe0TmVqaGh4zSOxzBMp51uc6ZyfWfnGMWKcRGCrvyCCoEIjFai56RBTII5ufop+z07s8OxJbaMa1FBPwO4/6eSe0bdD/p+WX8UrKsB/Bvyuqv6HV99/x+1vAP8q8Pd+bl0IO7lFctqCk0tYBRjcW2Vl1nsK2fSWG1bPgy5YKhsLmi7elMiIemiHRw6I5aa37AkmOAphsOyQZSLMrIwuSIrNZ2alFqXW6OeAVhbzScuemld6YtbETWhR15yiBM9cYou1UhvMZ57cqOQUy3LRGloqP/LtqbG0aBYDM6Kw98DqmZWyd0UuJ7AXjad229TZ3DHsy6EuXELEZpZtIWaFPTfE0FHniizZJhTmoS355ar+O0iyLKdlERa75A07crDMH1Eb7vycioqKRzmz8y2joaLXHbPMPDJy9ogDo1SUw0HCZpsp/VF4jpZeoCIrPOSJZ7GzjYVlC58z+6I5EcpiyL5xCPDAQEkhVfhnUcyUf3aBXcwIlQSS5k3TNu3ODqlpqLnhOY/6hgc5bvOpcO5m7GSA1oX3ICMVJ/Z5R1Ahh+xjfdFIjQuIb+PKUSY6X7bmZLLolcE1skhwKBppNKJS09Ns/VFpZJR5s8FZpuhqg9qKOpfQHEgCRDm5LS06DM9UjkACsiGXMv9KgJuZEGzzUDEUsZ3p67SN4r0/SLON76ALSZVOKk8KMdEG86fPbqeb8koVPhwR+qtobH8J+DeA/0NE/o5/99eBvywi/ywmT/5f4K/+IpXF7iXxfCKGlnu9x6L3ayQ0xBx90dhCryhB0BcvVy3tpu+U77Je4EqZZKtrWImLSqzIhQ6AbMb2coJkdo2upjK2fKFXoLRqME5ck6s1+CS/wOiyiy2ageItK65uj8VUTx3knr2gYTNsm+DSjf9TYJqA2y2aDSZfIgwvntotU69/V95NXVi0GPkxOICqJBKrG0LcEQfTdFaK28IPG9ZI7r5FOP2h51EzgdpoTRDLxHLDgV5uEVX3xhoYuuWGqMbUr2mpZYci3Oqe4u8ssDk46dXOke2ZZd7guY2zuGA1m6K9o0F3Iyt7pKIWR1AwMwItqjamrZjWD7CjJWHZZQqfqzynPNOSSq5uX7JnNlpvPW3Z8YxShJZx8Lp8KK5jby0ut7yPnXC6YoTvWqonkLkQdcu8DBpYrzzHF1qLva/NQXuXRpsNlSjQex6/0pYdzfZ7y466fo4wcZeURWcSlqygI7tTW90Ec7F/WoIIe47Z2kwLDK5BigvIIJlTtnA3UeHITCeVmw2wyCNdmXOiCeYkasWTGORs3+WS2und8qt4Rf8n3q8N/sKnv29FArz45+jWM6Ha8+X4e6ScmAnE/Z+hf/wD7DjZnonBYy4v2VNNONg+YXwhT6KIURtmLYLBdu2yu/W02wLoXKVXVR48fKZMgIGZVTOfyGGDkrXD0AO9LXeBViMx9DRSceNwdiGxC/VmXJ1YtmiFkwybMChCpiEykaiB2Rf4mZlZE7cYWbWTmuJGKPYxs8yk7f2KTVBVyYJPJlsWpuUUe5A5QlpPg7SI25BCQ2huqIbIwIgonIJRQRqtuNE92n+X9OZ/dw9loJGKnbYcdUCAF3pHF59Zrn9WyglSL/QZZ45kSQZRw46kK7fa04vBppmZwokqWtmN7jly8sgFz7DsQUWTrNyKnWDUS+OOAoOrrcfL2iILPHoao+Da+HNtCfKAqvKCPZ/zGpDNvlaY74qRtjtt7Pg4PZBYufFcIaKBEDsOsqOiZ9SBWhoPAzNzQ1ZzNNTSoBgNJrrzqi4unC0XIey0YfIjDE/MqEJHRwYeZSAwc9KZWkyQFcGmqjwy0olpdBYpAEdGnnMwAad+YjvmULiVztCFRjrZ0dQvqPNIlYTMzCP3dOzo2XPWE4ssrO64wFFQIHDQDktyCqMsxM2ZoixmOAKEk07saYj/kLo3+bFkydL7fsfMfLpjROT88k01dLGr2Y1eqCgBkghSIEFQ0kISAXElQAv9EeJaK/4L0o5aCJA2BLkQCFEEpCaoXpAltsgmeyhWdb355RTjHXwyO1oc83sj8mW+fsWqFp48ERk37r3ubm5ubnaG7/uOCNvU451NfgFh6atD/NJn5kzLkBMYx2zz27ZvB/NAhHb1G8yv/iVSnrFvByoXuEkdLL9Hsfm/mKcZgZooVvLMLDZMYVeh0w1OYMaKLRtaOhZi4NkdQgcHYu2lbkkqVBTsM6G6yF0x5liDlfmC/lbRCJNXiRmMGDIa3HMp16yZoQIrmoN7N6M8JC887hg8z6nwiSEwo2ZHS5cjHlM7Ap5eRqImWh1ZiN5JNpjClR13gp0MRHbaM5eSMX+nVM9KDBfeE/OkPrXN8IJP9Iyt25KIBHUM3QtcBkB2MrCQim0uf1hg7qmMW/r2uRHWxYLFkjNqQbzVL808xEF7KlkwRRNb6UhiUj81oyUbnMlNj2IquibWaUICqNDItKCMBxzgPN/TqXbqSDQ3V4UlBdeYVHlNyZyaXgaqDIqtqYiSmLNgklzylESUezJjS8cig6wbGhJq0u3YAzxTK324yGrFAEVY4MKCMq5Yji3iCiumkuynyJNYKTMqKnrdM6n+mpvYoQysdHZYmA3WkmjZ4NUzY0aUyEtu2NLRE5nL/Ii7w7Gj4yLteerXh7H9Um5IJO7r2txsac01VM8EdQKT0FeNpHFDil2mxCXjproFlSqFBnptqaSgYcYzLtnSGdtFEoU6TljjKOh0Y2BsURodeZbr/lYSqF2w0IuDrfbMXUmdF91OR2rn2evIXAo2qWNEqZwxHCr39unr2zGxKbjUk+oneD1ixIxX56mYqBMJp8aFmzBjE7HbY4FJwKAit8x/cwWL7C5YRaQgEzHZMeZYjMvYIs8k6WN1SGeiiGaOohgXs9BAyiurZaFctp5KbjIE4BDby9dTaEDEXIwMWjjELKxdk+LH0e0L6miVnEix4xgK7KgyOp3b8GxH7iHZNZlcYVNLMMt2cuFKbimeqpHLlawN5utDjGpy0y2+Yv6C9BeHSbyaHkO17JmlanoKBqaakx2JgHFzu4whFDytbonZvY8ZgGwP+zGsYFdzhGSImhUqGV5jcZxbxUMkkTIn9Kjaaxi1aXEQXKbemUCCZIt/xZxCA1Uu1jxZ2Mf4nD3kkxyPSMD7ORp7NCXIPFCVXIRIAi6UkHqCuiyhFfBJKQTLkgqQQy6m/EwmzU/jaGRGSZAClwtKz7QykUk8VR7bk3ssYsoZVR6riuHCpvqyRYa4J1UKKshxW59rUQgOl3YmosmIlwLRyKRyMokpKVNdCslJKHORe7HC057IkP2JCTeoCt5Z5hY4xC8nPGZSS575PFYbKXJG9ig0GcT9/4EEnyi3PyOtfoi/+PEhqOuzFMpK7nPNF4eO7OnppKPR+hAAn1bMyEhJTa22ykx4qJm6A8LbI8bLU8tyRhIVktH+PTOqTGMZDu7RZBUMh8xRmWNHwZQwEOYYJudKthmScsxsVlqx1CYHelu6TA8ywGNPEMcJc8psyXVi4Fyjr1jR2JJJK02zG2rB3EA46OMniZbKp8PhOMt8OqeSVW1tIlOxCbnOj+00TJe6IIoSZh9AdcJ4M3Kje0TMAm2ZoBiRdPkvUE3UYpzWmhqPZ0HNqIbxKtRzLTckgS2tuatUbMSsvyRGQA9qk8RUYGWpzQH2EPIEMjEPJi28Uu2+JEwdeScdHuPPRjF3vNKCOtdNsAxwxT28qd/KApdsBDVa4yio3JIPdMGeDaXus4Ve0dJRyLFWwz09Q8hKt1JSVo+M8ZJG0wZ0NoWTIi40uOoMHXcUGpHQoGOL6wOVS8Z1RonjBpcROqMkZiwRoNJo5QLzox+cQaIesMpxWqFJdU6USa6qJZzIikWa5fEewFVUUbDCNzUzjbTSMmNFq6Z0UlIbNk/KrOZrxadLcYh69uk6W5HlQXdwpKfBc48FpgUn7NkzMhCSp5eBKSG4ly4vxM5isTg6tbBRcLaE7XMGuqHAibCUigLPTnr6nDSYScEEqH7T9q2Y2FQVd/7PkZPfgLi3GpMo92jw44bkSjZuQ6GBPe2BjRMlZv2xjpExB947lu4+TvdEbY1tkLOGkxbZlAwAq2K+055KpmpKgRlWW2kqmjIQEUkHC/GSPQ9ZElU51RkC7GXHIIlWOtY0Ft+gYE7NFVtOdJmD2JYA6WTIuLVjwqMkUFKwomGfg9KRxFJqo7FoYCN7Q+dnLN50PVPAPqmBbFOOBy2ZMYkc7ukPgd5zbg6I/xOdW1EYlIqGEUVOfwvtXrCRHTfa8UAWzKny6mpySV33JUpirjO20vJQTziSzWf0+XwKzLOLvqOjksL6WWvLzMlAQ01FyS5XXjJLZcyFRMxV6xnw4qi0OMRGAe7pCQnj3KrCTJscPyryAzKde4uRfwIzOSWUZ/Tds8wfDVR+DSjBLWgiTEq5S12xlWcHl25yHQc6apYYT8jjfENKW4sZ+8ok60Vt4nIhA8lzj4jgYe+ddwAAIABJREFUnLl8kuWENA15soAZcwo/I6aWQMCpp6IyKImOeUKPzGkOAfpRRxas2LFjrcscfWxouWbuzli6miGe0+qGlg01jdGVclnClS7zQr2mKu7jJBDjnm26odcLlmIqOk6t1ltJyvVFDQS9oKFhhqhjyw29Gw+ogxm1ZUkFZs68kjIvrMYgiiyp2GiXQevH7PSOgRUuYwsHOo2sxOWY8Zu3b8XEBkpKLT62aDKU+TTDk1rI0sHKmDtWsgto+TGX81cTTABxmdPHwQSe8hxGoSKbwZahmWmVC7weJYLMpDd3yGdZmiJPklOsblJbncKYpRYZBJo5ftn0NhduzA9iOhSSCepztR9y1M5nyzPLxWQajK3EuYAKOfishj277WZNn/tsyVkbJ4mjozZryJlcC/rr4YorN0eSw9f3TcY6xxanzN+RXJ+YaZ1jOoY2P/TtrVV0UnI9iHXK0S2fQMYTJWfKxk0u32RBSnZ7p+OGjPAXdYjcrR0a1B+WCbv2rMSaY4kigtcSK+OnhxZPNQomKpRz7iArdCg+TLCaFASm7K7Pk1TSRIw7SJ3xYVMPoyJptEkvdTDu0WheBICm0ZgxOnIQJZKAV1tSfRZvdGIWkGjMrrOh971MaiQuIwSP0KCS0kC/UuFdQwCcq03KaAwmaCmC0wI3PVN5dDixxNGk/Gv3MUtxY7JVLrvmTj0TADnfrTwe7LsFpbVfnLnD2lPRZWbPMVcvIvl5tMx/h4HYpzFr11RQyHDHav667VsysUG3/4JZdWYaUVgma2CA9hneV7SDobkXeW1PelSUrdyCkDp2bExGxXkrCKJbNmJikwduZ55UqmwyL6hYMGPQkWvZMtM6q2046lTTSkuTcV8LXVAQWLNkkJ5JVtzK7AXOdMbNoSaqDdZOTKF1J5NbU+dBUbLOgMoaz0wXh8G5kx0zrXLELOWK7SNeCxoMR+dxB8XRmAdXyA/dInmWkKV9TGrnmOr3LFgd6FRJLOvkpWRdfIe2f0nz8K+i4w7aZ4ySWEnNRKyfUbLTnnd1Rcrxk0JyIRtGjkpaSsOMgfZwXYnETKcpdWJUmKSUKBl4bbSjaeBOyDWb5IRZrvweCIw6HmI6E1/SLE8bG620zHXOyMggA6VWzMM92vHSps+UJwvf4GmIsc0PtJX7K7RgJidEHThx95mzJiarmi6IiTRmGES/+5whu/8hdYg4vGvM6mlfAecAOF9m+WwlpZExmvpucFaPoNQ5BTO8rxFX4H2DppFBBwIFolbkpmHFQE+gYsaKJMZLBuWePCa4Gb5Y4Mo1pQs5XBkh9vhUgwQ7ftrhXUUdLdlThpVpGmqusauRpXvKyICPIyGVOGdl/kr12TvoMlBdCDnzXFDQyCmz4j7iChM3GG4odc7AzzEWTjyEQ0I2Rs6o6Rm5Lwt22h1MkjNy0iYI+zSw5+2l9+BbMrEJwpClh115wrhPzDD1Ax33iFom8lRX7MUK3pYUdHQsZI2oUsrMoBqyJeqYs46aU+fpEDT26tliNCFDoxuau5MjBCRkaygdyuhpJo9bRtZhIoZLFnkwB9aypssAYofwRE+pmaEa2cqOmTa0dMyY4fGcyWMueY5JeGedOCywbgoOA0GVhS7YZ2E/EaXRkkkIs9QsCindwYI0FdIFIATd04r18KTqMRHcJyuq1DmWjBGkXDP0n1P6Bv/8H9N3L7lkh6Kc5iK3JSGDaC3aGSh4xUu8iPU7E/F85IJXFFLwkitOWYJa4mauCy7lCmNETLALu5/TBNjojIYZowwUksGwalWiQo6yjRl9b5aLZ5CBWmsmfoChySpGBha6tOVNSiq/zJZJQfAznG9QzUWu45ZxvKHx92jHF9Z3UrCuP0Q0EvddljdPBL/EJczCosxVrpYUfmbip+JAR1LfE6ONWzcJQJIgDQxqAg06GvfFZystxj3EFu8qdLLYxYOONP4UEBbjkiA13tVoipTlfUtc+Bp0RHyVdQoTFEvoX1m8T5ZQrpHyhKADjCYDho6k9hWxfYmvzpB6bRZSsaZyJfHqD4ndK6b6pJMYqEGxlEqtnu6UFCplZpLhqlZ7pDyhGkdOxhlDDiDN1WLAvQxMmm6NlHnCK7mmpZGSkZElNTt6Vq5my9t5ojZGvg2bmAqohvlBj0rUanwiDiRQSo2VICtw6pnynpO2FRnhb5mUCQVtLtuQEdAT2HMqmnGoJsTBGbDwR3aHTIhSXqsfenSYBGdFMRIoZlUVUhE1Htw7PbiruWiLptfcR59lWY7tPp5HDy6okg7fs4zplCvUO3tM+aojgNVxREWZAuwECZgmEZfNfk2WDUPNbRNX4JLc6RfyYLY+O1LEbFKebK3JRbRMspej2znhyaaWi8Io5s5OxzlmdYFDbdjjVU6vpiIujmOJRSBbptllEsnKtregy/mYqlYtilt7TtbU5DKKmIov6MF9tWtzh7EreAOSa41zDeIaxNfEtEPSwFSy7iBiqtHGLIKTAARESltexFxfcj1Qq7EQDkVSJPfhRJoSCYjziIYMLXGI86gKZDfQirgYlg7VY/ZYx0MdBLu+HLYRU0gjjXlRj3lM3KqhK9ld11yV6yBfpIcW2u3LStDJVIOTZmUQVyCSCKnKoQZ73gMFjUsUKRAxLmtSNYgUx3vlkQx4f/P2LZnYPJVbMp7+CLSnevX3bVXWgCsWiHieDN8DGZmTGOMOJCugIqbDJkYumWuDjxFJyhknJE28kssD800x1dXgKkqqPMgsW+jyQ1Vl8ciRkVJN2aNRC8Kb+W+ikgUzyuYp4/45u3TOF/45v+5/xKb/1NwGHAOROtOJjNayo9KSMltAS11a+l0aBrXAueQoRSs9tY5UWtHS5vxnwYVcUmtNjQkZusMkpRhHcn+YemttGOjZi9GGagp2XDNnaY6k9Jno7Ij7Z5TUhPEa8SVF85hqGw7c08nia3I/zuSUC75gQs9HmSoQDNQ0RFqa7DQhZu05dbxyF8zUaGeewDNesZDGIAO5loMXi9+gVvjFzg2jDIQJvpAZH7UsaHWD0CM4trLhVE+pZQkKFSlPIGpZSyClnrHfUc/fJ/Ub0MgYd5TVA8b+nDFuzPaWAjSisc9B9ohQEPzcYkOuxtPg6nus431oHiK+QcOczfnvELobSjfDuxLnG9BEGne4Yo64goo1vjwx6yoNgEPHDXHY0OqObbrhlEcUfo2mHpxBcVQThZtR1PdAAj7NkeZ+nkTVrMKsKk2xhrjLlpbCuIdyDf0FxB7C3FzPwXT2nK8g9mh8Ba5AcuLDhTkqLwHwUpHiliIn2iqNbGQL9DTa2ISrShw2qEb6tKNlSy8dS9bM/Tv4YkYablBNxGydiq95WJ8y7r7gfPyIOTV/xBeA8pQzmy5EWGrFM928dUr5dkxsE/UpVKhY6NsRUGcVxhFnBZFz5W3REnSqBOTy7B+Q5JhqLoozTJVoPK7e2Sry4g9/ew7oGaY1cbJ4JvnFKcA6rdaSLUqEHPy19hdaMEWFYo4fTBAVgCAFXgt8JvoK5AEwHiYOMEvzYF1y26KYpr3b1efltfKKtxFXh9Ye99W7bbLj2LToUWQqv1eszIVgwvcdLdopoGvB+KmYs+KlyPvYvwlz5XNgfurXKb526JccAT221h36ePrbPp0C7eT3Jir08fr01nGmCmRmZvqMc9RsiftDOcCpFybi1N2qlClPcJKtj2Mmzt6bkgFZRDNbN+iI6BQhOiLgQHKGNOQk6WSlucN3JstpGp/Hu2TJJ7O+xCac6diTRZYtUvtJ1r7UW7vA+uFgdWcYiPh83MImstwtmvpDnC3vlD84WunHmgbu8E9ksjAnCz5PqEzWnlmZ5o15UL1TaY5kArPAIfnm89iLJLxM6Ym3b9+OiQ1IaeDV/R/Snq354CffBQ9+8R4076JE/LBBY4+r71FoIu2fU0TTSPPzp9Yp209Z9JGivIcPC9K4ReNAiBawt5swMoXCgUMCIuokWGMxsRPOKFngXEGdtgiBmEvt+WyNgdLvjO8vON5L79P3V4wy0rFjrnNa11FpTSEF9/07ALgwp++eUdAwa95jbC9IqT9kwE44Y6+bbI2sGLUlyQ7UEaRmqSnDXWMGV5qU+XHinfiVBs81cK2n1goT9NwzYjFN1CR1OlqWsqAsT1BXcvmd/4pm8xEnl/97HliBKfe1ZmnuqwTOwoesxlz4tjojDRuGOLCUM05cg3hHHVdc6pfcsKXQkhO1GN+NXOMIPNZ73MgNjc4oM1/RqcfU/AtKNze2QrrOD6+jpGGkIwmIeAotcCoMDNTUBEqi9gTX4KWiKE/ouucHaavSz9Fhh6bBFJaHDUW5NqJ4eULfmbL9ELfUpZV4HNtrQhYeEOcQVzL0FzaZpx4XZvjuAvU76M4JUXP9TrumFHt8ucJXZxbz0gSxg9CgsYNuR0oDw3ADKKU0lDQ2V6WBmFpUHIUU4CK+PMuTqFpFqtgxudC4AP25GQPbj9H6vrW7OkN8mV3QgFan4E0GHj/D53qnmnq66z9i7LfMxCNhhvgqJwJMmNSsVm+l+jArSsRb0W0gjVtitILPZs3D4ITan6LFDJWAFksYNoTyAWiPaGJsn3MRP2dk4DmX3GNBpQYs3qWBE9+wpWfhqrfOJ9+OiU1N6Uqdw3cDvlwhJz+kW/wASJS7j81M1mRwkLgnjTvQiK9OrYBydQ/pL4n9C5N2Fn9AgRdSA9MKZ5Po5PunfCO9GC1c1OF0jnc10+oJgnPBhCB1T8wgUucqxmjYqFIakg4oiZU8JOnAlbzgvryHL+aG4nc+uwNQNe9Q+Zph84nFFV0gpp5ON1ihjokUb9CGQgOF1NkVMjdsZMBLaVXjpaWng6zpbxZTleNccsgOWoJkwUBLwGSlb7hi7s4on/wV9NU/Y6gf085WrC5uUDHhQo/BbNYsOPPvgQScrxARSl8Txx0iVkx3MVpwPtT3SP0N4kZ8DKx1gQANC1LGXglCmcugTLlSk8/2h2scdM8EKbF3rfqRSQ0kxrTNWdOCRMea+6iMeZ0XfFiSxo7CmfvntUaToemRQIq9LVpxjy/XMNzgpcDgRQHVyNC+IJRnkOweG+C1wLvKJq/QIMWC1F0w7j4jlCfM6qdIMTcLZ7jGp8HcPl8jqqh4KBYw7tD2OWls8dUpVViQ+gsrrCyQYoe4QBnu47LgJ64k7l/g6zOzdooVDDfHmKFvbPLSbZ7kLkmD0ctcdYqAJQKkwM3fgf6asX1BmL2LlEvS/oVBkaQk9pd0+09pZu9Rzj+A0Ni5XEnqL/HZAh67c+K4ZezPrU9cQeHWVL4B8aThmkW84aL/OcPwbywxxp6GBrpPAGXmzvDFgrXc5zM+4r6ueKAPuZILeun5wJ9xzpYzmbOle+uU8q2pBA/g4h4Xu2xjymESIAdOre7nmLNSFszVbHJPAdrs33EECRz/2TZBRu9uX30n3dpPj8fndgCbAzwAyBOnO3zfnAcrbTYFZ1Nu/5SYQFzGvh2dsbtGttz65JYbdPgkt12nau7yle/ePd50Rcc0iH3DodkZB4dLPWiWVNJ06KDD9zNe73hN5oLdce9yADxpeq33b8sP5eOq3Pr89hXedau5c81f30e3t6mPrc/zTz7S4R7K3QTO8ci3HB/xFg5xwcIjt967+zgdkx9TFvH2fTiMoUN/ucM4P+x/a1zc3mu635P7OY31u9uU/MjPjpJ/5+fikNmUo8tKDq2kEUQsKZEn/0OFdyYX9w3Pkcihn/W2S3z7mdPj+LvbF8dn1MIWEz7uGKQ5hCZUDpTHt23fDostb0//8H9EmycgHnU11fbn9LOn9M1TCqBtn5HazwGlLs4Y0w46C8b6jC3yBKQ8Y+wuGQeDX0QdcC5Yoid1RB0J3tDoYyZbo9EqcmOabpquD0F5wWAVlVvSq7mjhZQmWhhWAAzjlmb9Q9LuCzbdJxhXcuAz/RMedQ+pwhnX42cZNxaY+zOq6pRy/g6puySl0YqljAknBZ121iZvgNJZWuJdw5h2OfYScvwvMEiHU2Gl62ydTjEoUxW2qkkjBu2MgBVJroCauSUVwn362btUl/8Pfbnm0cf/EC7/JdfsuGDPU06otGIhJ7lmZUEctuzHl7TsKCgoxitz08VoPf3+GUPa0mbIiMn9dOxka2kQPUrmlFkuaMzFhI1PWeCzgqtqym3tLWSgMd/tKlOIDGIw5yQPeIfLViUaLeDua0gG2xaxBETsLgjNA6QL+OYhqX2BuBpfLIjDSHBzUuoIxQoJNczexekIrgLxjP01bvUds8TSSOpeWMw35HKQ3StbdKpTblXK5e5kGfDNI5xGNLagI66Y23MwWrgljS1CwkXLKGpscb7OCQeFfgO+BBcsQbJ7bgmJ+gESd+juS1y5YNy/Yth+ifM1vlqhY0fcfJwnNsf1ze9TuyVV8wS//L5Ze0DRvjKDYdhAdwkkNFqCAPHgK0J1Hw1z+v6VMSYkEbXDpZbgczhBN/Ri8vUz5gwyHCqHbV1Lwwn98ILP5DMU2LDnXWcMiRkztrpjLQ3z1HCeBQ7etH07JjaBIA3j1R/j08C4+5KiPIX+nCpu2J3+O3T9OT1WLTqRSGm0+VyEUJ8hcWPH8XOoHsDQ4qUgaaSTPV5LanxeA7KMkV/Ss2ebrlnlB2LKimZ6OaZrOhwwaTNWtGzYs6FIc5QWcYGqMjel619x425A4Z4+oA73UDcCkZksKYozfHWP2D5nuPkZYfE+SUeG8ZqqfoTXASeeRTyj1xviuCPpYOTj2HHkxVpbO92RGKmZmWuFGkZLDKxLgkH3WBaxMkS782hUGrdGxNPEEcXR1vdo6odIGpDLf0UadjSU7BiYac2Sk3xss0624zOu5ZqFzpkEZxDYsSGmS054lBcbz8h4qOhVaUnEStINdDgp0AwbsMmqJMjs4NorysCOQGXu+CH4P2U7c2hde4SAc4EhboFbqRdxFpSOO2JqKcKSkDFeqkqMO6S7tMlER9z6hzRxB/2VTTbrX0c0oWFu5PbUIZoo7//I3NmwBI2E+S5bcwXD1R/jfYWbP4Uwg7gHV4KvOFg/aYAU8m81q3fc44Jp1KFby/qXpQmidhcmQ17fZ+jOqZbfMbfTz4yl42fIeAPVmZ1jvAFni92wf0ZMfR4XgrYXiAsM4xWd7pj7B1y6Sx5oReytDoIgaOyI4w5frnBhdrRU82fiM3ZQHK6+TyEOjS2hfmAWWxrM+Bh6Gr/mJm3YS8srOcerZ5n124I6dnrB3N3jA/0OzpXcpGdEeuNWa8+pnvKxfM6SFb+hS/5XPnrjlPKtcEV1wqJNf0+u3G1X8872urtxC1d0WAWndVHJBXFe2+/uqnk3Q3b7O6+f6pZrJJP7wsHEP2T1smLI0VV9/dz5vVsu7lev7/bv2y7mm13SP739R3P/K3tk91/lq8cSyFbRrffk2I5Dy+Tu38hr1z15Jq+3XW9fx93zv9nduD1WpqtU7t7C7BLd6V+90yYbX3C7n/Tg0r/hnHeyjuQxmt24KRuaJ0o9jNlb4YzDO7fd1HzIYwOYwiwHJ00PTtrxOg6e3THsMbmUhx+mdqQ741vExqXcch0lY92OWWQBvD1XBzypHK7k2Ka7/X3357bbqYfvvTlk8Hq45HYI6c3j+8/UFRWRnwM3YNRMVf2RiJwB/zPwIaai+zffVKnqznFcMP9+3HGePuPsyjo5IFT1Q1odqFhkQu99C+5PKe3qHlKeotc/ITSPwFVE8UTtOOcFDsM6CR6fa2FGHQg6WCFcnZkSAQUiLsMbIl0mQReUBKnMtQkNse8oVAy5fv9HDM//CXHccnP1McvyKU/CO2jsUB3xiw/w2QrQqz8mDhuTBJKArx+g3QW+XJHiHkgU5Rn4Et0/I2hl2B5XUKQeEQuGj7mwBahxO32Nlwolme6XDtm1tiRKQUPSkZ6WPdecpgdUsswZrT2lm1GU99iLI9WPSK5kApGWFNyXBRvdcyqPzWLzNZRrFv1DwhgIUuMkU4VEWWtt9UV9zdi9ZIiTsKOnZW8gTJYWoFdDBxbS4KUkaWLMZfpsYpoqVDU5awxOPCKOqD0xtXhXM6aegZZCKxwlhZ/jXEVKHd4vQDwxXlPU9ylcwZCz2Whku/0JdXhAip25gSc/NH5nBstKaEjFEtl9Zo9Y3JorSkQ3nwBi/FBX0HevcK7E+waJLSn1+PYFlCsISzQs7Lxxb/uo0ZwQ0DSSOsuQi+ws2ZTDJFNcy4WKYbhGU0co1sT9M5ukXMk4bNHU4XydY2OCppFxvMa5Cu8XxHSOcw1h/pTYPscVK0oJVC7gqnu8cyM4X+GW30Nn75gbrYmQ9rD5CPK4Jo8tKVfgG0McFGs0J5Doz9GxRVNPGs16xhX4ceBU7hsKQTSLvVZUrqJVK/l3pc8YNVLHGV/6c35N3kGTTWJb2RBJ7GVHy59x+T3gP1LVl7f+/lvAP1LVvy0ifyv//d++bWcBfFhYDCL11FofeHt+3OM3P8UB3tX4tMeHGYIQwpwYW9h9hugARBgH2PyM2D5H1bTZRxlNbsV5CldDrkeomhh0f8jCGWm3IjHkKFYJOIJrGOOOTq8phpG6uMc4bhnjjjBc4/yMFHesZj9Ac8a27y/Yc4Wcf8yqeJ9+fGWxPkzxrB9eUjf3LfUuBaFYQR6MgCUYsnmPJhvsCD7Mc9xPGdV4kT5PDjINthzMN9WPgpS1zgIFJzTECfKQZgS/wFX36J/8VfbzM+bbh5TDDczeYff8d7jyW7w6TllSrX4A/YU9cOMOFxoqXYME+vECIVDXj5BiiYiiw5Y2XlPSkDK3b86KvWzMeFIopWHPlkGvEBWDNyAMaWd0IQKJkeCNnpNiZxlqHC4UpDQyJIPGBAKFm1mGOe7R5GysuAKKBQUWD0rdOeXyu2h5im5+jhtmaLIMmy9WaH/J+PAvA4nQPUPGLW7ckmbvI8MFkpzFs/orXH2G9tcgFYQZpQukYYvU9wjF0iZInLmKmpBxZ/c49RabcmWeJEHYgi/QuD3gw3xRgzjSsEPjDvGFue5phFx+TkXo+hcEZ5PmAXOXxmxZKWPa5HGVde/2zxiGS4b+Akcg0sL+c1RHKncP3XyEbD+2NhYLUneJoEixwDVPob8ylzrHBIkR3eZJXlMG5o50aUOnlrXupWelawIlj+Qd8CWv4ucUbs5z/QgFllTM3H2ep4/o2XOaFvwTfteKIYlnKyZm+YpL1rp464T0Z+WK/mfA38mv/w7wn3/dlw8G9jd1Bw/ba+6dvt08lVvf+eoZjtnBb3rmu1nWr+502y27045bruwbj6v69Z9/bau+6faWzGE+w7GfvtpfU3hAb71+vYWTK6V33rvV9lu/vppce5tbffcUtxyrP/37t0/6+j4it+4Jx6zpYbe7TuAbD6uTS3j7i2/e7/gVufO9rz3HL/jJdE+m3wew8nRdr2Xhj+7o61nYW9vdiMJbPvwm90LuvJZvsO/RqeXY17ffe8P2q7DYFPjfRESB/z7XC310q1LVl8CjP+0Qsb/Gh/kBa6Moo26hg5KMPWNkXj4xNycTiV2soHmE9tekcUPfv6KYvUMne0Z2SC4u4ZAcjA5EyYTj1NPqjl5Gap0DjqQDIoEQFvSDZX8AnAtGCXIVSGDLJSt5zHD5B5hCxAId95wPP6XWmsqtmLFC8LTDc0q/xmukqB/gmkfULjBuPrHaAoUi5RrRgTS2oHb+trfEgcPUFLyriOMe78ztC0nMwpeClK03J4W5pigxWhk9JyUpK0F4V5Myf3GvV8ypkfoBY3HK8vJjyut/nV38IQsIlrzSrRXSGG5ou2fU7imxe0nSjj7tDG8FJHq0/ZyiX6CMGQzb53J+ttU0OBx79uzZUdFQMUMpGekIvsZT0MfNAUN4iPuo0uoma9TdA7XMZ+lWJAaGtKNN1zRykuVyxDKHkoPzYYFIBnS7yqzP8tTGUn9tVlB1hsyemqKzK+H6J+jiQ/BzpH9lnsFwg+6fGWi2v86Z14SON3TDFaqRkpGgCcaWsb/ELd5D6gcc+JuasrUTDYepY7aGC3xYAoorVqCRNBhm08j6vbnhcY8Pc8bh4tBHmkYSPUSz4tp4ycyfmcKI9oCnrh6bBauR+vS3rB0kk6Qfb8yybJ7AzZ+ALwz46wrD9/XX6LiF7iJbaR2EGlyNlg1SP7T300AYt8Td54zdBWOWwq+0JBRLmvl37drTwONhjgCPx/dRlFAtuOo+slqnCK10nDHjho57FKyZc8WWZS4a/bbtVzGx/Yeq+pmIPAT+oYj84Z0pS1XzpHdne70S/Jhagst8OKBnl6XsBhDHyEiBdbA0j3LHjFCuefa9v0ExKKsv/hHu5T9F4kCVagpZUOpACEvK6hGWou5YyKkhzmPP2r1jK5hCaO6Db9D+EtJAXd5nGK6JqSOEBc5XpNgSxy0LzhjSnua9/wL98nfY9Z/Typ6z4juWqvcNRXZLC43gKvruGd3+M2pfk2JLWH6AIMTdM6RYAglXnkJ1D25+QumXJlujkaAj3jekNCAukFJmXfiKmHqS9jhbAlCNRO2Ne6qOUhq81IypxVHgnEmQS5LsuipFf0G1N1dCu5dcXf3fFJgc0WPWJgm0f0anN8j+Mzu3mzHSsadlwYKWHZXM2acLejpUkoWfSJRaZepVomKeAbdiChCAkxKvhVHJBEq/IGkkpg6HJyVT1SgoqXLWN6Ue50rGuAdRZqVVpVcEzZ/ZgztaZlBHmH0A/Su0uyANV8Z/VCXFnVGbxj20L5Dz3yOEGTJ/H3UV9C+RcWvH8DPLkI57wuwpUp2aazlcMZs9NRfN12h3jhQLwvwdtDgBsTJ0kgYYNzBc2SIiRh2ULFWkriC2Fwz7z5lwkc5ZPNKXa9NL8xU67qiad4n9JaG+x7B/gVOlaB5CeULZX5rlHDu8mouPDpkyOsDuS+un6h46XDH0l5TL74JvSHGPdi+N01qsDuEbaR4Z93TMYODhxl7vv0T83z/LAAAgAElEQVTHnenSAaF5RKgfclqeQbDxPm4+Io4dLy9/l720NFpz4a5wCBsd+J6+y1X/nJU84LT6Nbr2BT5d8XvxM/58+ZiOgRNd4MXdKQb+pu2XdkVV9bP8+znwd4F/F3gmIk/yBPYEeP6G/f4HVf2Rqv7oTTmo17fXc4rT72/sknxTj+VXsN12Bd7srr1lv9d+/yq2X/Syv3LuN7nuX++jf/X1r/KCvu7Ub2jY213Bt2yvZYW/SdP/bS9PX/vJDfi3PNo32X75Y7/e5m86FH65L72h3V8TdoJfvhL8HHCqepNf/zXgvwP+PvBfA387//57f9qxfM54IZI1vQKTvBCuYF4+JsYd3eO/RrX/FB03pPpRVnkNbE7u49JfZL5/gQsziv6StP+CAnDViZn1OdunqTN10zQAYmoME5ndFUh1BuMmuxp7vNS40BiNC4eIo0/XlH6NdK+Q6pSZKIv6EXH3Be3+o8MNu+GSGXO6oWMrWx7L+/TbT0jaUTcPoX6Ibj9n3HxEqB9CCBAaUoo5gZKL44YlaXJd1JHSgAsNilGuvNRGcXIWWBYtCdpkKZuUBQFbfFgaLgsxipEEpJgR+lew+4S4/k1C6lnPfoCmgaa7Jqqp/r7gUxpqEj2lrEATjazZ0/IFzzlhkV0eSxJYyb2GgR0dLSMDM3cKquy4odQS72rDoqnJTFtGz5Fib1lolwnwmRUQ1STMnTNAdox7nHhzsXXEu4Y03Ji7hQXdfXMPmT2F1KHbnwOQsqKtVNaeUN1Dmodm2aU2Z3gL0sXv405/K4c+NqTtl+ACbvYOrjwlbT9ByrW5zfMPYP8ljJnGhLOkRH8JzgqBS85w4isoP8zuaILyFE3mnknq8Ckio8+1E6zSKjpi4g/OrLtiRdx9aX037Ii5IlgYd5OdRxquzX11BWHxgbVNoyVR+kvLcIsgvqJcfg/RAX31Y9z61w17pxFyeAZNqLPva072af04Z9HVwiJIlmoa7Wc0KqQrTyjDHHSkEUdqX5JSz2z/OYVbgIAPcxbVCal9BeIpyjWh3/KXw6+z4AHX+py5nqCqzFnyc/nkrfPJL+uKPgL+bg5KBuB/UtV/ICL/FPhfROS/AT4C/ubXHWRSckpxj/ONDdSMoE/a45pHdmNF6Cai8nCDxA0y3PDgi9+lb96lq+9BdUY/e5ew/TluuELjAGOH6lV+yDWju1OOk5ryhA43NjgzpENjB86qIAje4i9Zq8syRydGSr78A9zsMc4/BnF040tuuMSJ49R/QDXuqdyaTp/zjvs+PsxxsycwbtH9S9BkfL9yTdo/Axq4+mPG4ZykvXlRGRQrLiBi4OFCTDoJ8aaEoFOcJR6UFQyuEFEdiOPeKDKZyTD0rwgyw3tTVHH9ubngCFo9RG8+ou2es6flPg9pdZvdylxAT1t63dLTcSoPqfSShiXRIM+mcMtAl3meM1ZcyisqRgrXsEinjLSMcYsTT6c7Ax6PN0wrtOndTeUGU3abPX66j0Ao16Rxj7iQY5A5RqvJmAIjFsMarmHcWQxp3NhClWWCcAEdt7ZI+oU9zMWc1L7Azd9Hdh/b8J49Jj3964Aw+hlu3ODLE9rFr9E2j+irJWV3fVD1qNpnqBTEMCO5gmK4wUcTTk0uMIYlyZcU/TVhvLGx0J8jcYvM38PHnY3DNEDc46qHdo9CjQ4b4rglzB6Dq5C4o1l8QNp/ackAZ8WGRBSkwBVrtDTWCMMGfE3aP8OFAN540XbdKyTM0czYYNxCmFt6bf+pTcRji44tVCe4ck3qzo3/OnuS5dAjGvdsb/41Q7xm5R8TtWM7PEe9Z+3fYRxv2KYLzt0FoyqP0j00vqAe1nyuH7EaFrS0VFJyyQafCpTEjks+lpc8ylIOb9t+qYlNVX8G/PYb3n8F/JVvepy3uaKSY1+/zCbyS5rfdxJo8la30jI3v9hhvz7/+TXNubXzMdP1hu9OmNJfsD3fNDP5CxzwV7a98X7+GUQhfmmn7Zcdd9Nh+Ppu/ArM9ZCN/8XG19u+cziOvPb3L3CMX/n2DU707aBUoVzoM9bjPUJsiTqQNOKlotUbZP1bFN0/RnxN3T7j03//PyauZrz7f/59qsuBvn6ESy3FcIMUC8byBJHvI8tfww3XuLgHHUgSbPUab8zVDAtUCmT/Ka4+M1d12JKGa/zsCTpuKf27pOEGSLj6AcSWGHcUi/fx+2emhNBdELsL+nhF4ec8mv0A6ofQX7DuF6hG1oOjmD2BSXtq8SFuuEb3z4z+oiNSnkB5CrVQxD2xvzBKTta9V1VcscxWiTKMG5wYziulHvHHykeqVmRYM6eyCEs0jcTeRCQFT9Q9cSwomvdI4pGrP+Dl43+P+fVnLM5/TKvXdDLSs6dnYKYNtaxoFt8HEcLuU+Zq6r51NFpVIXPuh8f42WO0O2foL9CsnDpTw3KNsoVb+ngmTlSZIoifg0ZiMrAmGi0LLt6AnmrWm3PO5o4MXE1pz5HEbllHjR1u/hjtr9Aps7j6PgwViENia0H71Nn9GluIX5hVJx63+DADdYts1Qh+9wmEJaH9Q7R7AfUj6t1HuDQQxnskF1AXKIYNsVihOHzcU/avEE0kX5OkRtJA1b1AUo+Le2S4RuLOgLsIOlxDbBFfk1JH335J4+uMh7OEWrF431Q9csZY+wsmQv5Rudb6j7iH3SekYYMsv8fw8scU86fZGmxh9q4lzq7+kN32p9Tbz3Hl0tRH9p9Deca4/k1wJX7/GW77Mdq8g5Yn6OK7CDBc/Atk3BLKNWhkXj5B4ykSGlyKrMPKkmQilHFF4T6k2fyMNt0w82dcxs8Z9CXvyneoZk8Yds9wYcaif0lVPmDff8GsfMrTwWqp/pq+i+H/v7p9KyhVth3xT/bX29EyKhxK8H3lEG/bacLnfM2CL3e+f/ulvPb3V79x513JiKCMkZroVdNnb9u+iiJ6HQP31l2/wfbma39rQ9749hH3NCGfLELwDQ78/2Hy5k/b3tTewzt61279ikVkX+L2L1TvjqE3HvgtbXnj77fbaF89/i/QsV8R1nzjl954zjed5U0UuGl/+dr/7776urfetB0UPr5mh2+JxQZrHuBzuTbJRKaoHZGRi7Mf8uj6XyMdbBffgaqkWHo+/Qv/Ke7VHnl/Ruzg9F/9EeW2oK/WaLFAUkLrJ4ap8SXJV/ixzXGOgeRqkq9wqz9HGC4tCOsaQv+CJAHXX4A4HNFWc/GQBiseW6zwqYf6Punm5ygjdfUYV55ADvTG3TP64dKsJY2Muy+smMe4Q4YbpH5g6XPxtqKGGam6h8S9kbzJBeR8hbiSONyQYosvLA7kYk2KHSkOhLDA+3mmBRkGaFq1xRfZ6usRVxkh2VmR3oQi2tM171MXJdvvP2Tx40/Al1zKNScsqVmxk2dUajprFCsYd4TZU4sBaWJWPzD6TveSsPwQwgwpFpT7Ch33xHFnkK2sMRJcjTA3wrgmXAr53muuCq84V1vM1VdMaP04XiMScFRZ5tviWaqRcbhBEFMykdLgIKrIFDfafQbtc7My+mvG7pJy9hT86SGgTpgBMFz/sZ3HlTmW9cRil84jwyUUa9K9H+GGK4gbiu1PKXY/R/pLe0B9YzprnY0hnb9Hqh8jsUdSi+iI6y+R8ZpJzSbO3kddaXG29JFZminCuKcszojdBYjgiqU91LG3Hx3BOajNAhNXQWrR/jqHz0bTfmueICgUK4rFh1b7NMzo179N8pXF5GYf0LRf2jFTh/oGdTWa6WW+/RJ2n9t5upeoL3G5WLcteGrXromxe0nXfomXkiKscK4gjTsrGJ16BCsLmLjJIp2eVjo+4qc83FziCXwRf8KH7nuZTuhoh+e0dASx4tpv274lE5swsGfQPY07ZdSBAGy5ZuUe8cXpKefpbzDffMzFe9/j5Pd+gosj3X/yQ/iNE9obCB4u4w+QONJVJ4TLn1Hvn9M1T9gunhK9qdNW3TUMLj9MPX7cEX3FfvYeZXdB8g2xmFO2X6JhjsStBeHLNcTuuEZ0lwZkbF/gVt/HFQvD8mw/ZxiuCdUpKbaUxRn9cE4R1vjZQ4gDLD+07Fn7DGZPoX1pLk/hLfi6/RTLg2UgZ06uWPWhiLoAMYKvjDI0WOYT8TnxYaqwQM6qqk2KaSAUggs1jLayujAnuRqXIq6aUz70lP052t3wUB8ZFUpMtmlgT7P8c2j9CPpzw3X52tylmz8BXxvdpzxBdMwS2NZjvlwR+ggpMepIjC0qidKfWSY0FaTUG27NVajLyRGNjP0FkwR88PPsZqfDezqJhfrKgKsUxs2NLXQXqCssoO8KC3R352gacb4h3vyUFAc7rwRCsWIYLk1Q0RXgAiGNsHjPkg/DtYF74x6XWvrF9yl2H1txZBTCjJgxa66/Nlcu9Ujs8fvPieUZqTzFt8/sXhan4AIpLHCpR3afIN259VuY24QsV8Yf7m+Qcm10rrFF4x7pDSPJoc8riBsISyQM6HB1SK7QfknqLu3ayyXavWLor6jEKHKMN9A8tevefcq4+8JwlESb5OcfoM0jhod/idB+iY87w7H5EroLzne/TzdecNJ+SrP6bfy9v8A8debi7p+h7TM0NLRXf2AKxuLYjS8pXMUfDT+mloIzPeFR+D5h9RRiy6L+S8Tzf2FlBMctMbUMEukY+L78JvDP3zijfGtc0TcG5eVowGpWGNAcEZekmRlyyyCdRO4OAdTb4dO7n91ybF/7+9brt5r5t0OoeoSlcEwuvDnJcHRLv97qfkuC4mvaI29ovu3z9Ra+vP6X3O2Xr7T0Ni3nNTrS2456571f2CW95RreCSvk9t25n98sPnGgGgm3lDimUMhRn/8wauT2HXudEPWG2MUd5ZO3XfKU/bn77lE/4/abx747HPX1fn/L2LgzHm+LPh5eT9XLEqIpL6hqC0FmJXB4PbXZHa5RDj1gx9LbSiJThayDgOl0wUf1koPFTbr1JGaFHG6xTm51lHGovz4E8i2x2GAnW9acMuqWSozcOtMlo+5ZP/uU/eoxZX+C7xP1/iXV5k9I/0DYLR9xcvkRQ7Ei/faH7B68g7/YE9or/P4zZt1zqv1DIKHiUT/L6O+IixZQLrLKggyXecU9JYYFbri2GzpZVGkwtwEHcW8ra1gYxSZFxut/A5ooT/886kqjX+lAM27R6hHD/Dv01Skqnnr7MeH8nyHDNZRrdPeFJQ7iztydck1ZnZHaF5myJLjqfl65r204uDJbSS4rRaSDezaRqPvhCjCNthDmGbE/Mo4bRDzelfjhkhLQxfeIm4Fy+zOimt7dnh2FDqYUgoBYwRri3ty32AJbxuGG4Ctzk8aNuXX9JcP+JYIQ06usAFJSOKssltKQXeeISMGhKnp2oYdoWmSFn6M6MI6mfReqU2LcMQzX1MVDnAuk3up2TlpxqiPe14aHcwGdYCSuQPtrJMwYupcm7R0aiuqJVWrXRFl/iA43BnNoX2a6WzyMgzS+xM0eIcMNxau/h8zfNxaBWIUp0X+DZFc0RlNicapo85i+fkAsTvFhiR+3uNSik47e5udw8zOcr+zBT4NBkSaIRRpNnaNYmLAlJu+dknk4cf8c3zw0OEe4uuWmFrhyDWDKJWB4TQqq7hlUD0j1Y2wCSrj2C/oH/wGaMZFhOEf6K4b5hyCe5Epi+QDcFal+QiyWuNhyr7qHdC+gvM+4+C7Rz/Djjd0X38DyuyCO2fw9pL+GuKeUH6DDNb+2aywJtXg/t89D8RB8jX/0F2G8QnZfIDg+0O/Spw1S1W+dT741E9uKEwq3IOlguv/S4CjYc83J+Y+5/PC/pFv+gPrqhiQl6ucsX/4+i/M/spk9deyvThh/+Jjm936KT9FAhLHF3/zEsEP1I1LlSH5GCjMQCN1zwJPCAj9uoX1ug7C22Jf66oAXw5uAIAChJA172id/ndnz/wNSS5g/hf+XujfpsS3L8rx+azfnnNtY9/rn7uERHpkZFZmVFFklIQEDJiUGMEBiBgOQQEJMmDGCAZOaIRBDpOID8AUQ45pQAzLJIoOsiozK9Ijw9nVmz5rbnWbvvRisfa6Ze4aTIitL8rqhF8+fvWfX7j1n373X+q9/s3hJf/r7NP0rm3K5Fm3ViI1kQtoiCuoXlPN/zfC0vEMWz83hVQJUKxqLQuuqsZ8zXV4ewYVjNSqa0doy2UI2738o+BBwxTh5znfgW8pkeEbTPq3JSoI7fA39Gw5P/x2W/+QLdPsZ1+kLEhMtDYlcE9gVhvcw3pHHW5OX6YR3kUO5xe03BOloRaAkbofPCOrx4nnNG07KkrV7XKsFcx3RUsjFNJ8i1Y1jJoNWeZhteOYf5nBoTjhpafwZRQt5usP7JdN0Z5ZGLppRKWrTTM3192JyJGcYZozn5LxDgHQwcYxzAc0HkIBoRk5/y0JRtl9YBeIXcPa3yeGE7Be47gX7xYc4TffW9tVyye9+iTZPzIQy7yh+RTNe4/ZfImln6WR+CWmPjIafqWuMYN2c2SY8bQ2eCI3JvcTZNRm25LQndo/R4QYqf1HHW/teHJpvK7dssuQp549OIuoXkHZImUh+jaglWaXmMTQXFL+y1lYK6haIbIg3/7fVaL47aj1d+9hCl1UhG64Hkbj/nGn7KeP+a5p4gWuqs3E+IO0jyvCeNLyDuOZy+DOCegYmHm16NnKHCqz1BCeeZfcx03BFKj1X8opCYSs96+n2O/eT783G9o2pYa1QZSZiaUadWBzfscwFKRkpYouwWFoP3oHoNyLpRMs3S+n6BMbmpla59ecfPeSpvcqDEnpuv3Q2DDfcZv4a4gz/mv3h55ZkLtu1lvjzc0uNIHv4b7/Rmzwozr/V3nzznczvpzYHAugDI8xvPbf99YOfNfvgi0NyNSZ8kEvw8P5YGzHnOMwmhjMOmO2/6695Q1KtYdHf9uXXh//xsOW89+if//bbM7XjNWRuTR5clQffKw+/U2rr+G044oHFiLlgcFxnc0iwvdc5JNk/+BWqHbd9XV1Eju/TyL/29/U+FAsgPsb0VUoLmpj93+5f27x+7L3OziMzb+AYxffgus3QyP3H5MFzfOu6HS/WQ76oCH8ZoarXsOS61hOzqSZaqt36PatBa1trrsCj/a4WQmSqmHl9FAQLUrZmeE6oTbVbTswmnnMnUur/5kSR73p8bza26K393JT3DNJzqt4yOAm4w2skZfTlmnQ44N9vcbln7J7THL4G3ZObJ1z82adcjQ3uzsrfqXuOSzu8ZvPU6t8guce1T8h+ieQDbniLbRzB1ADjDZL2hP2rGmI7Ug5vzOWgTDZEmDbmZNA8Jky3ENZoWJGbxyCe9vZn0L81NwTNllSUZulPY4x4BD39W2wv/g6r65+h7TNEJ3I4JTbnpLt/DmWsTiZ1wY93drHE1YWYKZNFn0lcVsvpWsWRjxKsUhLeK5r3aO6tJddigmVxyP5rVITF5i8oCExblqy5lWt27DkwcqGW7aAImkzo7HzHNO05qOVDXMo1z9Uq3ZRuWbpH5HKoBgbeQrBdA6VQcs+kPU04YVuuaelq1Jya0B/z2ytlqCakgCRwnpzu6rBE8CxxOEruKWrJVEV7mNTUCL41uCCu0DKi/ZUl3C9eUIZLHAUXlkz9Fh9OkCqDEke1895D9wLd/ho8SDhBpltk9xneN+TVj2kPrxEdoeTaCThc2iNhTQknNgEd3lnVnvc2ZJJglVUe7H62FxXq2MCcbD9tbDJZXX01T8ZBDF1VokSLzFvW+x7NYcb83yKyeGpVHlrj/jLl9hfIyY/s62lHGa6RN/8IzSNT3gKOZlnb0jIi3iRq+IAuf1irPhvEqQRkujEeoHjKcG2KhPwKHW6IYUVYfoTmkTy8N/NVgXG4JPolXhrScMtF+JjX6VMWtOzZstITWrdGNbHlhrH/c07cEy7LFzzWF/wJP+eFnD5A5f7y43uzsQnm5tpqx1JOaZpz0Mxh2lB2X3L+5efsdi85u/yM9uoPkfGaePpTRCduH/09bn/wW+S25eKLP+P09R/jcp0K5kPFGVrUW3kvZcBrQvJoiz4PoBN0T6F9YqdWHmB4iybLnhSKLcBxYzc27RDNxKs/QpsTNJzg+1dweE2/+SUOiM0j8nRHqNFsLp6gu68gtLb5vP8nLFxbiZsL3DSYZlOTOYkUm/4h4V63h7k1aDG9J2J2NaTe5FLz6SaeOVnIedPbihaLb3PBnE0108Sz6vDwyNK/xNWTFEYmnvAUz839gV/MCmnWQSqFliU77niijy3MxVlkHWouxJ2c4PHcyB1NtqzMSXsL0SmZFaeAkotNJ+e8Blc/QBR7PaqFMVVbILcGby14SSNeVpa2XgOA7TqMFqUHVR9bkLgyi6vDK45ytrAizhWTFlx3AXhLQ5/2sFqaprR7Uq95JJ99gErEv/8jXPsY8h5dfIC/+jlChsVL9PCKsPu1HZDNhVkeaTb3lmL4l2md7ys8aR/b2pvX7fzIvU0f0bpereoRb7Qd0t6CW4rJwWTa2mtdPjVZVDwldS+Q1Y7UPiYOlxDPLa4omzxK9orEZSWKPya1z8nV2LS4llgOhMPXSBnRsLLXEE+tfQ6n6OJDXNoCau9r2to90AM+LNAqY4vdD4/T7FAmNO35IJv0z/uOPt+AZjbyngMDL+U5ufSc6wVtc4GbYKWLfxU2tvvS2LKkLdTjPpI64XJCpoIryU6SMtWSWCm+IceW3LS4kpA05w2W+3JfuG/9FL5RytcWYU7Jtii0uqiqd/19o1Nj82oZLmVEOQEEKalq+6o7Khy/yzzl60lc2wMpI65ULs487aU8+Df33//NNvXBRJaHrcnDn1f/dJxe1Tbs288jUiEh95eeZQ63cTonpPOgRXs4cxYQren18/N/8zVat3Mf82Z/b/fCiTu2vkphzp2/b/8eXI/q5c9xUjnnrz581w/e3zGnoNz/TGAeUMzDBnkIH1TrcfKDdkdcbRXra3ERJNY2KxleBscNy1q0ZG2nuCN0YcvLP4A4HmImgpWF7h5yOcIQeryLPAAJHrad1vra70e44RtwR7SqXqIN0Bxw1BxbxN78S11EfVdxX2eb1zQdr+5DkALMjgnnoDR2R/SbbfJ8bWeKDmLifht6mq90JjPnx9qn08wXBDtsfVWrzLyC/y9Kx/dkY9PqSrEluAUhrCsPy1kqVR5Y3/xTmumOOF4j6WDZAbvPoX3CevMZw+U5U3tCvPsS9l8yHL5CVLnlmtafcuKfIIsXJvJNW/Nyy331fxOryoqlqeMaGK8p087Adt+hxRYqvq0VoLUchqGYI4RqYdq/JjaPzBFCEy6cMi4+QLQwdE9Yhz9iXP2YZvvnlP4d/vAl4+lPCfvPIZwb8RGgfYR30bzywaZ06HESaolzBYLJc2anEly8n6Zpqae+LQzydHyvlIJ3lpY0pTuascH1b1g0jxDxOA2ccoJSiDR4gonUXYS8J6U99xlQjj09lgNWGPZfIgjedXRlXQ8qd9yySw2cVhIqbf0QOJwIve4JCE1NGT8G+YhDJCKMFm4tlpEhakdhKfnoXWdqj5ZcDvj2rFpYj/bBqsA6sVrR594m3r61wUAekLBED++sihGPNo/M6aV5glAYupd2TUXQD/59892TwNhe0Cw+tC6yOadZveE4gFK19ZAP9dfOqqr54EVq0tRQq7qa8l59B4UM7RM0nCDjNXn1CWH/OePJ74BE60wqBi2akXiKywdKWCN+CRRc2iJ5ZxLDaYvkPWn7Ob69QHQ2hvA2aMkHwnh5fA4nB+Lmz3H9GxsazG2vTuRpY4T1sKYMV6h4io6Mh6+50Rt2bHk0nZLIJJTH043dT5Sh7LiW94yMPNZTNvqGK7njGWd8Wt6wLSMaHbFuis20o5PIW73hgu+2Bv+ebGzYGN+ZRi/nvmoeJ4toSxsW27+gO3yJlEQ+vLEN6fAap5k4XvP08DmlfULYv0aqGaRoJjDiyp6c3hu5kgcBxWpTt5R3ZplzaKoD7YKS+4rZBnLa47RUC5mC5oS4A4Q1ef3b1oKK+eCHZ/+2Lbzlx/jbn6Hr36o4S8apGH6XNobvLZ7VOLcGlw+V1qF2mrlcK5NwtB4y9YOFyJSyNYKmTnYCupmdb5QPEW8E1LQ1bWsdcmg2B1bnIqUUNI/EeAYomnbcPv4pj7e/xA/vcUXYsiESuJM7TnWNtOdI6ohxjaaBmBSH56l+SJDAWLa0zXPEL8jDFdGtUCCWwIWe0rgFonCQDaIgJRKkodcNjT9hwSNy7qsdUbC2VCwr0+7TiMeIuFkHvFvg/co261rx5DLQLF4ik6Okg53xzZndo3hqFUf3HPo36PJDo9y0T9HmkX1Q4xl+eF/bf6WEJSqNYUko7f4LZLqGkuuh9JmttfQMpKG4jna8MkNQ1xKmW/zw1oZOvjM2P8EO0jJBXNt0tIxW+UU7zOTwptovqQH04tDmDA0r0uIDxuWHtP07VApOR2TzFRI6tFp9kba4aWPWSd1zZHgLqOUupB0sXtTDI0M8QdrCsP8MP1xRSiIunuObc3we0dBRlh9T2qfmBpOqBnuyJHjiqdl6lQlIOOdplx/xhA95FFrCtDc3FXEWmtScoXnEje9pwkcM+89ZLT9m7eBZXBNUWG/+gm265KBbWjpWaofRC31E7wYe8eI795PvzcYGHNuB+2mH8bGKZgPSa/unFXvSko7lfhjv6uKbvtGama7M2iBybVHncrtSCkoZbRKTM+LqqaWWtSnONot7HKQ+t2b7Cc7sXUTVpop+bSlG84KpBbPK7MWVql9VsQ1LwrG2F9J9awz3bZS42i7YOzp+wzH2LdjrRO6/xy4o8wb+7SbznlxbjG9Xp1IpLKwirK97nkDNydwyJ6FLpLiEq/cs0hxfl7hYP5AcT2bBkkfndqpQsL/RBz8Hs7GGOhx40PbOk9v57j6ImbNW775FUso9RWbGosRbuzS3ZnNbKZUq4+dQFX88JAw+qO2wGOQxzukAACAASURBVMdLwNZi2lsFVpINpMpkgxknRikpU5UhKVImXK6ifhcetHEVDkHuYYrZUVcLFvxWccbjv7dNS8VTqt2QaLEqrfRQalutzqARzbaBqtbqXTh6pYm/Zx6Iq87MI06dHRT5gJQF5D1CIUuEsLT3Vao3YHUz1vq+7lenGTI4BPErNCteQ70vYhI/BFxrHnraWM6reCRcoCWxkiUqLQe2SA1VVkrtHTyhSjB/0+N7s7FpBY6LTsaNUiNLTlqT2vNgQGX/tuIU0cwjwXCttKuLOFFyz8jBbJIxf/ckOwYGBKke+7apOTxOPEEWR3wBtYmfGLRKLiOUQAgrNB3Q6j+fT34HIVO6l4yLD/Fpi5/u0M2vYf+GkjYw/iN83RAUMa1cmcj717h4wnj+AXH/Jbl7iksb+5luAYd3jMNbYlwh4cTaXakbcxnNV6tMVfYT6wanNvkrpe7Nh2qOCSX35vQwGyBqhmq5Ld4yFCSc4LKN9JVCQ0cmc+UeJEi5CM4OFNs4FBc6crKJ5MjIKq6PGzclHZORgErEnejUktKDa/F+SZNHpHr2W5CxO+JgpUzkcrDKz62Ys1qd2DQwZdO+imuRPEcTihFZxUFYoM0FOZyZDMi1MN3YcMAFtHlUKQgjJaytyopnBkm4gLqIH6+s2nINkgdK8xih4N/9Y2TxGEqP79+gqcehiG/J/XvDUeOasnj5DaxtxlTnaD1KTwlr8vJHlpzev64uI4JOe5uIDu9huEV8pO3fUbqnuM2nR1t52iemCw1Lg1maC6buBWG8YVq8YJqj/zQjmkjxhLj8xPC0sIAyEc5+H1c1t321OR/jCnUBr9CMt7g8ggTb4JpH4CKpfYquPsFNu4qxTchwVYcgGIQST+16+hXFd7YRNmdIGWjbfxMNC6R/g5aMVovxTOalfFwLjUQjKxp3ylC+ut/vf8Pj+7OxPeRCkW3kL3P15mCeSh7B5xo1B8yhylIj1MyN1T4UoVYFqpksU60YcuXO3MuhXMVt5p8xi261Js7Pg4a5XVRA/QqXt6hvKX55PwjIvWEeKDK+t0GHhAroRiTtjQQaFoa/lB4NjzhWBlUjWebcyZmP9gDAl1leNrfWR5D8IScr1/eCVZhaK4CZ8yXzdce+5sI9zw6OQO1EslzQGWCvr+Ne0nIP4xZRU07kcv8aH8rL6tDBPbAssmtdOYpSEBoeTmfvg3+pr8Fe3Vx1l99wjY4gfeWaqavWQ7m6IBdLmb+X/cyC+vocM8VG5spvBBb379U1NugYb6B7XDen4Ui8RVdGus2HeskqwP7g6tpNsv+TOv0uYY2kfF+5HSvzUt11D4i2IB6fVvbzfLSnCeujZhioG9baDjvXkePZA0C/kF2LV1AJFGek7oAdPointE9QF5g6U8vIuEFly9xF2DU3GERdi4YTLGRZ7bM43RrPdL5fvrHNsB4Q95y4gosVKpitp2pHpKL1gB1IJIMniPxVosS/9sYmIn8LC0WeHz8G/jvgHPgvgHf16/+tqv7vf9XzjfmGpCORtjYciUH72uJg6VXliyPO5CqIr6VUp4BVregu2aa3qGYKMDHgiThq+G0t05XJCKNap3bqib6jlLEC7cZ499IZjcAvQCGXAyGekfp3hHSLHL5GV59QnMePl3Dz/xg+5LojwbCUHuc6s5/unhjWpza2D8Mlx3bRtUZqrRuslwYdbmwzdHWRVyzJKB/JqBWzo4ezttZcKAIUMcpEXejOWcvmworUv8W5pjpneIoq6eSnrDZfIP1bUjkgEhiZeFoe8c69J5eE9leMwzsE5VDuCEXwOjGVA61f02iL9tdMaXvEyfqyIWmil0TMexq/ZJ/viGpOH1PaWBXBnKYUcNJW/h6IOIKz9mw+bBCP+JYy3TG3v/MG4FzD7vA5q+5DO/TyHSw+sA/bTKOY7gzG2P6SMm4tC9V5nBbbPMvBKrs01UPKIdM12jyixDP7oAP65N+gNI8MhqAgD+AO3z7BlZ7cvWRcfgQoPvUIivMDlB43XFap38qqwTLi0s425Tm303eIa0xB0lxY2xzPzBlk8RR1LTleoC5SuhZB0PYF6htSWJN9Z69XM65MiBay72iH94S0Y2zOCXlvmBlCas7x4zWx+rulYGt/eftPCYfXdt3ygTLeGr9Tk/E547lx7wB0Ytz+kpQ2eAlkRtJeaVni/RoflijCmHcc8hWn7Sckybw+/AlFlKKJx9mCzLd6RcuCLj5lSndc8YqtbPmy/LPv3E/+2hubqv4C+ANbeOKBr7Awl/8M+J9U9X/4//N8W73lRB7hXUPOE9Gt0aJE6QwnUCX1VwDkykMjQYin6OlPyIsP8GWAvU1tIpGMYQqegPcLFmotmHMNrVuSy0jKOzKJzJ6gi+r6YOZ+qfTs5c5i9MROoiHfEtrHVuHd/cJO0fYZ3eU/ht0XjPsvTK50+lPc9lNwgWn/lXn0Nyfkk5/gxytcY+aSLu9rIO/WFsZYLXFybycnoMO1YXTOkuq1FEvfLpk83OJ8g6tSHKv6xDaKORXJR8R1lhNRv+6bC3Ta1I1xrAu/0N39GdPmU3bc0emCgKeph81ATztcMqQrCoW97EmSeaJPObDFZUfr1qCJQ7okaAOiJB0IeCYsOStqS5KJRjprZV3AOzPkRDzONd/AzY5V9CwHKtOxCnJ+YYD7kby6tEk2hnnqtMctX9j7mzYms0ubSstQGO9wIhBXZuMz3ppP/3w45ME2jLDG96+QkhDJVqmhlPaZ2aqDta6+re3qAQkrpEScFuJoLiMpnjG251bJnv4QyojPhjf63BOHa1sL9bDScELpXlpVj1XhMlUuJWoE3lq/yHiDK/Z9ZfEhqiPd/nMzkAgrGG+QPCAuklEknuPSHn/42gZjwzs7JOMZTgR3+BK0sN7+OTreEQSI55TmsZm1xgu0f2XPmXvy9nNSsoPGuw7vAn7x0iCCtIXDlziZSOkth6EnUbhlwyM95X3+GQtdQdmyYsWoiSANS9YMHFj7x3aoaSbRs6QjPkArv/34m2pF/z7wqap+9te14k4kI3fiDWiWhlArrUydCFXws+iEy5X7FE9M29Y8xo1XYJA/4MhSDenEtIheC6WyuL1r7YOT9yDm46+VI/VwiDHpAZV5rKzHzdK5YKeTi4hO+MNr8mA5BRI6aB8j/dfIA9Io4m0KqtZmWyVQ+U6lR8OptTOasOyCGmJSzJ/snpNU6THOW5shvtK9Zo6dHEH1Yxiui+gDd07nO3I9XbUOOVwZcGnDNO1IdTjvuW+fihhEkMkULGl+kLFKpnKNx1sBQtZEoKltvNbWs7o4zDBAbevM9yxQSh08iOcbMh97kRyHITxoiF2syq7KS6uVnZMHWGJ1v0UncKtjBTvfU/GdYUyugzDeQxrzIVF5XcchTEnmp4ei8QJJGyNchxWlDnhcPiB12GX/DcV3pHhGCovqtOtQccTRhg8y3iJ6yVFiVa2WNJ4huVJtpluOQwwJoHv7s1oVxXRr2HH7CIrDjUa/QIsJ1HMPrsPpZOL7vCdkrDodb2rFVcwyabqFknDTLaW/QhbPKYsFJZ7d//zhXYVoEmW6JadKS/KZ2D3HxQtrPfEob3EukPLAVPZMZPay5QnnDPmGtqpTlrrAUao/Y2HgYAd3/Xx6HA2RpXz39vU3tbH9R8D/+uDP/5WI/KfAHwH/tape/1VPsObUQoFVK0nPzutCYqDHT7e2kNRMBH1YkdKWPG0J/VuCi8jhNXm8wakAgYmDbYoKWhy+hqLkckBToafnwIZO7ZJSN4Ocd6Qy4KVhoScInpz2+Lhm2X5g083mlDJucKcfGffIBVw8IZ78mGn9W9BcEJYfk+OpVRUugqq5huQ94/ITVIRmusHFEXKkNGc4zeYM0pxA6Yy1fmxvpFpBlzo9WlUOUtW3zuEkYXE/xteazJV7lIIPFZBOhyoIj8bdch42n4KO9GxYsGRipKWlZ+CxntGyslAO2dFpy0IXjEz07IkaibK0jT3tiHQVo3McZCCoo1Xb6IomFrrAO5sapryHYhtZrBNaO8BGa7cx+0mPkEkUSTR+RanUFZOOKVKqUam4GpTs7QMuwaROrsHlnR2S8QT6SySefROE9guQXQ2VqbhetfAmD1U+FI2SoROy/wyKhZdIPMPFA2W4pkx3ZpIZ1+bI4gLqjMjtSiI1HdkHpCjFOcJUJ63pzipGpGJkS8CY/MV15vIxbhC/orSPrHKaM1NdgHhSHWxs4p5Xn+DKRPELCGumsDLSbUnsLz5CRQnDQBx7JP8YNONV2Z8+J/Rb3NQT0w4/3hDynhzPKWFNimtElTDjivlAcC2uWrqLNNA9pzRntfXuiM6Klma8Rg9K1InGndL6C5x2hBI4lQVeHT5PhPYcl3tOw1Nc+wLdfw0oC12yDBc2sP6Ox7/wxiYiDfAfAP9N/dL/DPyDujP9A+B/BP7z3/B93whMXvhzxnxHKQmLbTOAfMfdkWtMBfmzDuTS2+LVAv0bnCZLqC6TVX9iF9HVqiCVA87ZBDSVEdGAOrUbqw2idorPTH7vO7xf4aYNzsXq/nkgxBXjeEXT/Mg0oPHMAoQlwPID3OoTUvuIML63diSucdEmP/3m50g6mKPt6e8Zcbd/Y5dKk8lhZgulsKwVHWZWOLPZfWde/XmoXLXW2of54aJZxJSptmw2ZNEyHjE/TQcjrEIF9gWJKyRv0DwRaPBiYP7ISCcmmQoagMIkE0sWTJLoaBjoabDp5ia/YlUCvsqivuJr1tqycVsuyhmtLFFVWlkiapWdc5FR93iJlcJh7VQuB0oZLQdBHKWCx/Y+TAtrbau3aXre42RpU8i0t+SpGrno+rd2GFQumuCsSkPJh0ty/xYfznDtWa1qolUvzYUNhcrAtPox0+KFuS7ngTjdIeN7QHDTteFkYWn3OO8Z1z9mPPmBrQ3XkuOKONyx2vyKbgdg02WXJ0IaLITZdWg4tXY5rEyPWXpIe9y0g7Awadd4ZQdWVRHgLCwbtZa8uEgJK6Z4DhSyN+ne1JyRfEsJnrFbkRuT2i1vrvFppF+foqvA6Bcsr66J44Ey7WnGa/zmF/jh0nBB1yCYWavhliMuLHHZV8g4U4Z3Fhot2OGOotMeqcMSUYhFyezxKohzaNmTEDayY42wLe85KS+QxmR3afySSUakFCb+5SbB/3vAH6vqG/uc2O8AIvK/AP/bb/omVf2HwD8EiOL1iCdZuJt9P46BgRVLvDOHVSFQisWSNU1nuFLua37haBWZZERtU/MScOqPrZOf2xCRqmsIx8HC/HDVscGFjpK21tL5hjJurOrKB44WyGLebPjOFqI3WZef7iDd4afKrM970uFrmmGLLJ8Tlh8y8qLaRM8uCKNxhlzlhKkC2VQO+cHxNGeieqnqApvuzriQzBKl2mKKbyhluFci1Emc3Qeb9opramtzqLhmIRA5yIE1F9zyvnaH96aLExORwESiiE2SRwbWD67ltdzySD9kJCFAkJasY1UOZJssSqCgeGbStG1cWj3hZh6fgono82TT6uPUNyAkSklmBR5ayniDrzGLUr321EV7LrUpubgWzT1lvCOXLb4ZDbQvo5Fzy2hTPxFQR+meMXbPqsW8EX+dqxIiZzQd9Z054VJIq4/pT35sgwVVigvE8ZZmuLJDrxyqJKvyM/2CtPiIohmX7mxTm1tfncxnrf0R4Ophfot2TwCtg4fBWuKq+S0ukn2LOk92rVVuLlB8IMUWKbamcowUH/F5IrUd48UJ9PkoxysuWtuqGT9VfLIOdpBgxhFUTfMcIlQGGK2VVQnQmm1RGW/BOQtsIpPV+KOOgJPAVHY4Agd3QMtEX25ZTWvbqOIJhczISCoHRnlwoH/r8Texsf3HPGhDReSlqr6qf/wPgT/9q59C8HFFyDuyThgxojBrwkzKE2pOohDlhJJHwJmxYfsIcYE8XCMu2AezDhAmmZiYaSAO0Uo+FU/jO5yKbXyVQ6cIpRwIumCmHKTS08qZCdPTnqwjabjGrz4yjMF3lPapVVD7L8njDWm65TC9phtu6HVHKNXKWhzTeI2/+5Rm2loF4SKEk2OrqcUWcZnuEGc0C9uUqAu3iqnzULGlijgd6Q5aReA16FZqepVLzIHKpVZwzlezvplukwdyGclMx8NAyTgcd9yy0iUdHTeyIeDoWFHYEjWCQMeCrAOlWtI80ws8gaYuNdVcqTWmcZwrsKgNTpxRXI5UDts8HRMR81UruaeQcerqAeTvlRZCDVJ2+LgybGf9I3LzCHKPm24MjHcRVHDpDsLKqvt8QNonlQ4yk2aNGjS2H5rziuuI05YJaMYby8bwJ7UV6wFH8QubYmthWK4YFyvCOBCGPV5Ghu4RY7um27+hGczI1KR8ICWZ7OmhwQEeIVVtqjMmgDPOIfXemYKhN1mfa9Ga9OXKSDNckcOaWN7jxxtK6UnrT5BsWFxxoHFN3F3jx1vi4SmH8SfEww3t+1/hpz1SCi4PdWjRPBhcTKCmjTb+pBF/Jx0oeSCo4afiW6a8YZsvKXlknU/ItYARcXh/wl1+x2M5I9AS4zlPnAVydyzY6x1xvAXxLBc/Yjj8gl56DvTfuaP8TSTB/7vAf/ngy/+9iPyBvXN+/a2/+67nQZozS21PO8R5IzpKYFGWtOEcF0/Ap0qA9BY1JxYibBMk476UMuLVM3JgrsmMhWY8rl4OqCgr1ngaHBOI1ptl+sWkA6KOfdqwZFWrh8p5KpO1rbX9091XyOpDxLfo/kvTGI63jHlHYo+6jMjAIW+ImPtGmnbI9lew+xWsfmDZCb616VW0k012X5Kmu3t5l3hcJV4e3R3giDtq5R4dBw0lM8fbzXIj5ztUTW+qydo8BeLq4/vN1d3y0OtqgXGjfBUqA6xYM1FqLEsmaqBhgZaJhgVJjWKTGTnBnFGVwl4ONKxo3JIZQ1Vsww5Ec/cgVw2rQQjBGfBfylgrazvwZjG8qL0/Y+/VsGgBISC+I69+hBSrEGdFiIYzJG1RTZTuA+hemKQtniL9a6sGp011zi02YApr4v4ziGeE8T1heINsP0P9og6gBJEGkVek6YZQRuKwwW2/JvZ3uFyY2gs2zz9gPFnTbF/QbLf4MRHGPXHc0+w+q/F+S3stNTZScCbzqqHekge0e2aww/jeNrrp1gwZ/AKVxtpuLTTjO0bxNPvPbciRB5JrbMKr2UjKs5tNf0l7u6TbXhKmG9z43tZUHgAhL16i8dQq0JLsXqQ9NI+QtEPzYPKz6Rp/eIXza7R7buE56Y4wtnb3/DPaskOL0Utk9Tt0uz/FywVt3+DO/4C1b2DasEo/YNz9c6vYNdOe/C7d4XMUx0m8AP7kN+4p/6KByTvg8be+9p/8tZ7MNfjm1Ppv35GSeTy1tAS3RHyHuEzJk4mf5wlhSWi+Mb8pcWbBUqzSgEKjHTZIGPESOMhA0WTyWbUpnxNvaes4s+7BxDsHvWMlpyb9mc3yXMRLtLSmarli7eiA7l9Tpg2z0DticpNOGgZubZqotiBKGcl6IKbHlZw5V13GAj/qQ9EaxtFUTHFiNt+TSpK07NDqkVUG41OhtV2YuW9VMpN6XKyuwEAm0XbVKicsEb+wU1Qtr3ShHQUjNi/15ChgP9cTDuwZ5UBDgyNUHzVHqbKXUkmVnsJIRsSMApwL5DwiIuYVJ03tvOfqsxKuFaJf2nOW3hK+ZN6sZ4fdhBlcmuyrLkKraus009eU9WOrhFima9qa/U5t4VUaUyGM1+YUXO204/DGaOL7z0wbnA/IcIUe3uJKxUGbcwAk7SjjNaV5RLe7QoYDPm3IYcXUnpPXHfl8waFtGJoz4ran6feglwSUMN6gvjF6yfAWKUIJK6vCKjwhaUdZvASCUS3CulaatqahVMdmmwSb3KrCJ2FZNyXqlF1MKwuG1ebBwmnKgJkFzHZZGGE3rCiuNbmWOFNyoLXSnND2Cb5/Ryypaql/SG6f4NOO0/6EglDa58S8w6UNpST6s9/nXCdUIeSRdPJj1LX4tCOkHXG4NrpKPXwcnpYVbfhXQiuazXNeIpr7Ss50JpebP/S+A7enpB2+OTlGzbnumXlRpQ1OFaeFSe+INIiKtTMSCGLcF8Vi1VTkuJEZLcoj6ghugZNovBqgaCY4Txp3hHhmFYOIWTKDYV75mn2+pMU2oKBLFDUwGqHJS+LiQ4I01kqVQu57pvGayI9sgZb3VYjdAooPK8TF6uxSMchKTDV/saoWCDOLfd7s/HFTvG9NTcFhOkprGzOJIOvaSphNtS4/JPZvmIb3KBOpEpyDRgtvdisDidPW3jaJSIv3HaoTzrU0EgnSkqaBGcvzOBptaixepqi1X65aBCUdbZQvEaWQdCAx0NDhags/2/dQ75WTpt67gEiprZu5aNh9GXHbX5rmsYrMcQ0yXh03Atl/gdmAj0hYW/KWlhrDp4yLDwjjNSBo85jslzgRRB9Rzlr84StKPKtCeY87fEXwHbr6IYJ50k3xnGHxmLFdEzY9fhhhKoTDnmZ/Rxj3NP0lvoyUxXPjKI43ZnxasmFYzd6q9enGBkfTnU1D09421TKCW9imJd6qOt+RwxkqjtQ8NV6fC0ztBc2MkWnBD5d27cIFoqMNyuIpqbmwTXW2eAonuJJw1TDShh22LnM8JYUFKZ7QaCYM53VIkK1NV6W4DhVhai8Io7eN0Nvhk9rnprkNl9Yyh4VVy+nW7kXaU8ZrUygApUonv+vx/djYanAFJaFloqSNqRDckoS9AVcm+xB7C/0w1vnOJmEn/xYsPyLsfo3HBLwpvaHBY2z2PY0/I8iKLtv0xfmWVEaUVAFxV1uzQuPX1s8Xb66sVT+aS09wjwzHCSvG/jXu4g/wpYfhxjaPs5+i4dRY25pg9REoLPwSv7bFrvUth9CaxhUBPJJ25O4DioumX23Pa3tpH0iKGWZKdTdFTZNoTg4HSj1lpfp5abVypmKWSKgZCpE5M/Oobggdd49/l6bfs9x/RRpuAGFiQIGAhajI4kOIJ4ThinB4Rcl7mxqHU/K0wfsWXf4AVwaanZKnjCdygdBRg1nKhLjGbIUwnl/WhA+rOpzpKa5OLusH1R0npjZw8K5jJu766rTrZ45cHpktj9zmU8PaVoZJjYsPif0r+tUPKS7Q7b8yKx6AaHY+uMh08XdJccn22R/Q7d/SDFvG008QdWYwOm1I4YSiPwF/hiuZ4s36STQxrn6Ay3vSas24esQYTyk+0ux2dFfX+DzQDJc2SKA6bqCWSJ8HZLo1eKHsbcpKzRrQYrGQaQcy2EGXdtWJ12Rj2du0t/gFGhrjy7XPjhZwOazIzRNrv5035oCmOgwLNoiruHHxLSmeImWi2X+JH2+rTMzoROoCqoqGJSVaXKVLO6bS049fIdM7OndhetIykqUg3sjCpU5XfalONumOYbqE6z+kuGhdymimk02ZKP0VipH2r/SSdUrf3kmOj+/HxiYYCO48ZXxPKSNDucUVITFYVmRNM5qBZZkdG1Cm7jm0T/G7XxkO5cJxwuZmTWlN5fH4yugXawGZCZ/CVHqKFJpZDC+RKR+IoQL6AGWySVhckw8DXPzrcPV/ArCKLyiP/h7FLQmHL0EnUvcSFSH4xoBdtaDYEh8br6d/awC4tFZFxXPUVcfbubqq1arqvrYPD1q2WSxeDwX7sJvrAxV/upcmCS6cWFUjgehPrDpJO0pccvfodzi7/Kw6tXKcf44cCHgknqDLD+rmqgSyhXeIQ+JJFdhDPvkdmK5opjvKtMNLQysrwNKyCoUYVuRpqD/FEaXDhzP69N7aYzEvuFIm1BklRCuGqoKRrbPxB0M8QaZ01Axrmeo6qORdv6C0z5AyMCw/wgGH098m+5aWUO2sDJc014sFw9nv0y8eszt/wticcnL7NbuTZ3S7O8MrFVJYsj39hDCNhKknhwYWTxFgitYK9s/PyOsOpmK3MU/o1uHKRJjucGlnlbJfGHZbkpFnq4uG08kq9HBqbs9k+7fDe5ugV6v6WUiv/oLiW7K37xdNdfPY4dPesnRr4EwYr47dh6QNMt5SumeG2eUDzfDWBiEIPu2Iu89weVe9AYWZgqQlQXNunLYyIsMl28NnXB9+TqClked4Z3rPiYnTNKBpQx43iAiNa5GwIpeew/5TQChkPIHZ0CCufmIQz+ENQRZcynUl7P/mx/djY0OMq5V626VdpFGPZHDqjUh6TAO3IUBKWwTT9bkaMSclGT6BErWptiaOgpJKT8b4Tk4Fr1onaaFODv1RCK8VcJ9L8L9Mk7ATzseLozWNlhFpH5PCGleqnVDaW6RfdZ3Q8aYmIFklaXjayhZmNK6T6IRkq2BL6sFVv7Xco3kwQHkWOZeJMm3uAfSSER+YQ1XuQ06osrSKSaWx4pTBKsGwgO4cvWjRKzMa9L5lzHscnsS8kdpDJdgAwi/Bm7W1pcwbjIBWbpOzEb44o5vILOquZgJuXriz8FmM0OsIOGe0EDMCdWS19lX0oXXSbIyQq1lBDUipvvxaxqN1doprfILiG/rFU1LskJwZmwva9glFIn42fYwnqAg5BFZ3r5n8CVOzJEwDbf8aFU8YLpEx0LRLmv6aMFyT4xoNC1QCftowNae4foVPG8Kwt0pvuyemPT7t7b65xhQkEkA9jmp+WkZ7f655oJ6YKT+CulqpazbTzNRb8hTeiL4lUcTj0sY2tnyocrEdbo4THK8pMwG69BZRmHqc2LCGGlXp097WXdraOsvT8T6mtLVQJXHk3WcIikt7SD2ttgTXIRLJOrHXDYNMtOMlY7lj1B2ijrUa2Rk1bLyVNZmJQc3RxVV82HVP0ekWUaXLsa7L3/z4/mxszSNEbvFpCa4lijDtX1kAiO+QmqgNNv1K4zXBr80Ysn+NqyRZbc7JFBZqOJkTT0EZ0warFQq+KEFtgualsZG0qxO3ulGVeeReTybN8yanVeY00ixecpilHrnHrT9mbB7T9ZWpComT+QAAIABJREFUnu4IZaySmB26+ZXpGN3CxOntU7N9uf25TSTDGldPPcqITtU/fvHMLJDyiEyhAtWClpE83XJ0DinJUt7LnOpTUTYRNNvXpAzk8RYlE2KHCys0rtDVS8qHK8qvouU3hBUlvyPQQLV7mt0XVIK1Q2JnK+lgp3j7GKaNRdCNd4hvzZMrdOTxgPcLu9vi0DISZoxMvFVbdSDkXYMPS0quSUjiTERd9lXRUM0MZpfvkoynVytCCV2FKjaW5ZAnpuaR6Y1Dx375GPWexfY9/eIlIW3I4cxME52g3gZROTQ8ev0zLp//XYbujOXmkuX2L4AA4xVNGUjNI5a7X+N3v0bbp6TFB5anOd2xOfsx025N29+x2F4S5nZTxKb/lbtm3LKqMODG1lIlEuMt4EbDyqqluiY1LNGwNhlhWILc1vyBQEg19EcV17+y9pIC+1fk4RrfPkZEKeMdJc3PqaR8sMlzWJDSDl8HSSGsjZc22w7lgw13fMc4XSOqxDQw7j7F+c4qrWSaTy9LnG8Y0jW3eslOJ5YHx627ZU+P4GlLsWm4tGQptO6UrAM38p5MtQT3DWH5Ibr7Ek171nnBnn+5PLa/mYdvYVIDcituJGEB+QYJK/O/ShtkvKn4id4D6qORL8V36HB1D6CKGdOZxEoqLyvXzYtKa3hYAdwTdWd6h3ONfWB8x2xubVrVEfwCX5UDEpYAxOEtrn9F6d9BuoNKNJTpjpR3pHKg9QuG4WsaxFKA8mCODlKr07Qx945aQZiVd62aKpfJPiCzR72r1adVcqWMHM0pdTZKlPp30/H6aUmV4DyajQxKHN6j43vGsqVQuXcIiVSrWctqkFRlR6k/tsFShvpBtFwKnR1HNJN0pBSMj0a1kSIxZyooJoD3bgHFXhtFjwfNPDGV4/2pQx/f1mIv3G++Dww6Ne0R35n7BErTX6EiuOFAs39NaS5sLenEHJ4ieUfY/YqFT7jxmsXmM4pvafobS3eaTTRLIuy/sESyMlnAz3CJU4XpjsYJyp449oT+Gp9H8jxo8Iuj8YCKR8UZsTcPJmx3rVVxlXirEqwtzHvUr4zPWP+9VYmxGkpi1RzV6y0dqnLFqj8zAbV7wqxhrpCMajYqR11P8+cCzFuvdE8tIzXtQFOd1DtEHeAJeW1T9WxZs84vkLACv8JPS1ZJCExEecyKFaEcEC14dwI6EsIJbThH/Atc3rMcdxRxdnBWQ1ktE6X0dCzxbvWd28n3ZGMTa2u02EINHbgOH09x4zv88kPS4gP88I7Sv7NpmG/M7UGEafNLyxloTkiHN1aKi1kNTXlDUCNA5OoCi44kHXDqwXmrcqp7hDH0qx+cC4R4Sj+9Z9U8R1KD+EgZbyjTDhfXNNf/l8lunG2q3e4r6N+QhltylXx46SppdWTUA005ZXv7M86aa/ziA/uQDld1hAD0rxmnGoKLJ43vzVbchfphtUrOhUW9fmq2Si6QxtuajHVSmePzJa6T3Dzg4pIybZnShkYcpUyk5gkcRpaXf0i6/QWHdFmbbm8pVGISn+KXuOnOBNU1NFnC0tpmbnDrj6H01iL7zpxS0p6Jg5FkZ0diETITqEdLQTAXksgppSRy2lu771qrUVQJYtbtiJjNtPNEv6AkS4y3g6hlzrFwYYmmPa59QnP4EvUL1jevafrnNP1r3OEV0+nv4sYbM/ksw3HiuLz7c5bblzDecrH/nLz8AS5tKyfPIX6BAt31H6MqlDqZ9PvP0e1nIMLy8AXr9+ta5Zo1A90LaJ+bhx+Cq6oTl3b40lt4tiaDKVyH+mjDqbS3qql/Z6sk7+ctHujQeGqr20XULYnpFspIkVBdURSWC+NJhoXZhoszU4ZiwxaZHEJE4hk+niJhjRM1SlPziOn875C6p7WNNsedOP3QeHMoofSoXyKHN8TxCrpn5LBGXUMz3fC8f2trPZ6zynuLpywzlJGRxVPi4kM74IZLHt8mighaNozDO4IWynhDyhtOuCC6M+D/+I07yvdkY6Oy6I3jxbQDvYHcE2WBxrXF0qUteTB3AxdWoBNl6lFN5ipQJko+oCTTKrqAFE+hkGSioyUQGXTHkG9ZyAnO2ZTQQltaSk24KiREzS77wIYV2EYSV3B4Yx3qtLOT+vT3YHxPvvrjqogoqCq93gJChzKwZemfIAVy2rNgSRrvICfC6SccJVoISCCVHimFGE7ox3e0zTPcMQXLmOiuBrlordBmBxRTHQyUZGaK3i8NYxNftaRLyrhhKjuaupFM4YJyM8DNn5LTgUA4trGtnJAr+TPHC/PtEm9DhrSDsMK5G+P1OYsWpCRoGpisbWy0M7yFQNId0a+JbkXOB1IZiGHJLHbXuZqkGL4irpJ67WHyL7OvmmP+VDO5jLTNBWWoeF4wfEfjClHF7T8HiXSHL49VXdz9Cvo30FwY3pi29kN8C9MGrfZEOZ4jWkhL+yD7dEfxHTH3sHiBevsA+/5ryuaXhJPfrpkAG1sry4/t521/RTy8Mt4lGJZWhjr4CZTVDyl+id/+El8mex1lwKeDsfvzYHSLmUN58bcBUL9gf/KTGiou+Lufg1+g3UuTbklj9kuuAxKhTm9d9/JYzS+q7hURJJ5SwhlMt7j+DXn5Q6hmqn7aVJy41A3YfhX/GHUNQQuBqXZLZsBgHLoFaKG0T3HTrW2OrAyL7k7QeIL6Bb5/hx5eU9KeYXrPYvkxd/t/xnK8MWpPNcnI8736DY/vzcY2n5ZmVb2oOEzmyKZ3sYbBclz41kyW6qpp3K1jHJ1SJVIFR6i+nsrEwESaDXMq8DwZraPMl0OO/6OY/U4pk1mRPyzRtWYUoFBGktoNFMzWyOVYJSOdyW7qAjKxcGZOedJg1ar67r5dYJYd5SNWeB+NVrWhsxqCajk9OwnPrbU3YP0+zdzem7V1FXgVD+2K/PyE9twZEVosvX0i0dTW0RGr0BqO8YLVA38W59uHwlul6Gqb4zxoxIeFMfOrzMZeh/Hs5si1+5YTxHnju1UoYb63Myl5BhLm9twckVMdisyRfdhGXhIldOYO7GaMalGzNx9kDlQ1h9aDQ+CoAgAhhxXFNWS/wKc744e1T8BX+ZaLFhbTPUPDKcU1HDXQflG7gmAKk6oHtnBrd3wfc36GXV9rH6naT6NjVCfgaq1llI4VU3NGDm2daGZSWJkxBHO+rK1RwdmA6mhJPutjJ2tbazwfJVcayd60qnmPG97aEpuukUqq5oHW2IWVtdfDJWW8JYuSXTQ7Ms2kvKmSSU9JOyRtSExMecuits5alGF8jaZr81xEGcqmWhg5ejkgCr1OTA+dmb/1+J5sbAr7r0mHN6CFsHhuiyZtDRgfjQhbdl+QtQdNlFQQ58llIsY1Uv37AdM36oCOJp9qZGm0Bd2zkx1JEo07tXYoHaD0THlP62Y6iTvaDJV0YO0t+Nivf4TmwUBVF63la59Qhks4vGafr2lZ0PhTfDxhgQXS+vbc6GrNM9wkhPWP8Ie3FlvmAto+B5TcPkFdS8wHQjyt3LSR1p/g/dJwvBr4bFNaM80stbUrNfUohBPLbPCNmUiWCedmy2VbzKWYEkN8h3/2e0x//29xKnvc8gNcf0nSxJ27Y6VnqBY6f0Zpn9rPHK8Mn4mnuOYUhvfmvtCc2QfYBXMn8Z05jbhqv1SdRcKM9+kEePz/S92bxEqSpPl9v8/Mt9jjLfle7pW1dVc3e7ae6WmRHIAcERBAXngQIEAnQRCgC3UXb7ryLAg6ChIvEgTpIAmQBFAUhzNDcdgznK27uru6qrI6MyvXt8Xuq9mng7nHi5eZlVWjnqGKnoiMeB7mm5mH+bf8v/+/pbNRFywSRLC2T91U0HLXNT7HmoSo1TxwLUWTiATQqVuFsa7Xbf1oCT6GOA6VBPGk7bOgEaHZTaT6SfAUTJsdri7CxFqvkOFb4T09oB5/CzUxVXqAuII6iknrOeIbir1fIapC2EBNDNlNkoMeKgYnJpAhuDyEWnD4eA+1GT49bDOIqzCB+DrEiX0Z3M6uGsUEFl1BQi1rR6/dYgF9eo06GpIPbuCsQcWRNCV1sofxDXE9DzW5bhXiuLSYRl8EaiVCygKXB1bl9CBYr/UqZEldcPllXRLPf4yUFzR+0/IZtsIyPpT8kYxoqPBVjvOOjb+gYEOfEZkMWeqMFSuOuEag/Tas/Yxzs+Ce3g37FGHRPKOSmkNu4nA8LX/MHfMOxqY8dZ/jcMzIedEsv3BG+dpMbG7zlKqZEUmImWizwfkNQkTUBKoT16zJ3SkJPYwkLTGl4Jtim9n0uqHQNRBoiAsKEumR0ifShLFaGqmxHa+7D3qT2gJnO73KyA6o6hmRyTC2R9OsgtvVFkn7ZoNrCqJ+QnPyLwEYyl7ICiUTSKdEw/dDKYuv6aeHNP23SdefBIvUV9TlKUnvKDBPtPQ4rrWK4uSAxj3HmpZbzIRidqIM6mb7dO8IFnEljVuh4omTMVtgb0sCaOI+3pU0zZokyrCSIh2MIxmRjiB/DKMouK2N1FQty4oxEcb2Q7avY3d1RZBs8w6iAW71AMmutcNZB4Ep107AWFwZ0PvS1ay6msJdkCWHga1DXeCI08ukSCQtGFulhY2kmKiHcwX4miQeob4KWDcaInrB0mtyXFNg7AapZsE9zvK2zjaInNAqdIU6SBOwfOVF22dR0KmwCZo/gcl38LZPUp4SLz8OPkH+OMSFgHjz88BkEY/CRGSisL/0WoiZ5c8xhBK3pn+Pevg2pgWdN2kPSfZw0RBRT7z+OVK8QMvAymuSxeXkW54GAG8cMIE+u46pl2TFC6wriYvnUF9AvAdaB02OZtUy34RYnpYXYPtBzGXzDNJqm2CpqxlanRLbCaijcqsQMuhdxxfnmLiHmIjE7uHchqI541Lg2DNvfs6ZzJjomD0d4ahw4sjZYNSwZM6CnIEGSNaanFgiKq0pdYV1BR5PjwGOJdZm1M0FT5lxzySYeMxRfcTH8hk3ZY9ryZAfrE9fO6N8TSY26FyC4H41NHrJtRR4t7pni2mdjA6g2uKfOrxW+8+07URDzKBjqgiBaLMF/tEJorS8u6CtInXn6nTraWsuo9aFat2leBqwUuoIyNEsAC7jCU08wroWdIlFzU7W1WZIshfiID64I4HeJtQyBipwixLwbUgnAbeT+RPap3rIHBqxeNmVa+tcsq6kSi+hFRAyoy3I0m0UmYcfv6ObTEzIXGqoVBAfMnZBayKon/smbx8GGjJ6LX2391XAEWtHnxR47K0kYR0uPJS0U0u32xFFO5e0E1qR7fh0NE3Blb0siA9JhVbqsGWBuWQ4idtsZhbwWL4JDygJQi/4YP2KCRjGjtm3E0aRlkoquLJJ6IO2j6VZhRintvRZEIq7m00oedK6uyrUJPgow3flfD6UDYoGaw3ftPdsBxxvM9ombs9L2odZHfj0Og0HV4RCfO0y3CG4j0nZCjD7umXfCBhJhS1bsRKEVkzUx3cF/SbFaBkSDyYkdi4ZnIM7b9ryN9GQZIqISUmwahAskemRmBQrCcbHxD4lbQfZtAEiS0TPDDEuCuQH2mDskFiCiE5k+/Rc2ib0Skw0InKt9N6/AQbdX2hR9eTugkgivChVdUKhawZM8DjK/BFROQgirqRhwhEo/RqDEsd74D3O5RSsKaVkyBRVR0xE5IVc5ngJNCiRxtiWZkfach3jg/vZSEPuVtiW7dW0lpJAwNWNvwH6GK8lNrtBfv3vMLAJkj8NMcHhWxCN2Uy+TZHtEzUFiCEtTtpsrQ03X+8WZvJLNNoQzX6Ii94ODA7VGRoF8Q6TTJBkGiZLX6MdpKGN13QlRcYm4B2xSSAKLjptsFabwGja0cpEHQmlBOhHXc0wVc38zzcc/uGP8YtPgngxKWMPpQQQZRz3iFefoPUqWBO+BldSrB8SpVPEe/zyPnZwCxVLlT8JfHjRgKYOSZSNv2BgjqCp8OqIJaOu56BKEk/DA6i9gcURit5tmAjRVh+2qw82SXjg2RR8Q5YctUQF4dEkEoS3lZjEZvjVfTj4TWTxIVIvkPI0VFFgwa2g3kB2GADATfhx0xQQT4hX9zG9m0HpqXeDaP1ZcLmlxpz9IGC7fI2655h4RFE8bscjMByHuFWETw+p+zepkgEuygLEw9UYV2JdhVVP1DL1YlO0Wbdu8gAtT8FKyJ7XS7TZYJt1qJpwRchCRkN8/gw2j8OEPLgV6plNEOsBkKiHq5bYbA8ZvYe3KZRnuNHbIeu4eoDxDfRvEBfnSHZAk/TANdgmDxU9LRtzz/ZYuTMsllSGxEwZ6xFKjTUpSXY9iBdJhC/PSKsDnDhW1RP6DOmrQ6KM6+lNmmpBnB3gqyXR+G36GFh8wji7y7cXPZx4qvIZwxt/j+tPnzOWQ+LkAPjBa+eUr8XEBvCIB7zNuyz8czyeIaHYtXMxvC8pdd2WWQilX/LCnHAreo+OQbXwM1YsyaWgx2SrgoQECyg2QxIGOFcirqFuNjRaEEuKsT1sNIR6wZBxyFa2AFJt6y69ronqOSYZ4ssZ5uC7gKGcfpfM/QuIBjSDd4mWP6G3eUxv/QABXDTEVqfI6n54ymiNaVbUvTvM9j/gcPYjXDQk799EsmMGq/vE0XO0ZQoRMW0NYRFuZIkAF6wO9ZcWRzRo3aBW8g2DmJbVw1UBCqGKMUHtvm4WeC2INYWzkrhZISamJ0NQQ0yKYFgzJ948I8bS5M+w6QGowzdLPDWL8ucM5TDQAgGCUrgZfbuHdznWpFRuGcqyMDS6IY6n4UnvYhQXAMvAxp0j3gUgrnMh8dKykiiemBhj09byDJz4JuoF0efWsunEYOLsEJl+O2T2JA7WSzwOrlp9AfF+YAFJ9wlYNh+KzFtMIq6E5ABN9siH75FU5yHYLwkM7oIraDZPiQe3Antzp8uhEEVDjGkTMc1mC6kYuA0D2tK5eIJpVoEeyAcdXd08CRZUPA4yjWVg1Xf1KmRDmyLEK9GQHLBpa8EVoXgeRXrHaPECyrM2Y39CtfebIIaoDvtrJGbTvw0iZPkz5tP3EXUM1ifE5Snr0T2iJqdMp6ynB8R5zt7ph6QXf4KpLog0YOPGfhhiqgTBmCSZhHOuF9C/FfrWVdiojx29TVyvyIqDNumkaHotoB6iIOZjXRHu6zZRKDajf/AbYfLePKHp32UvuhMo7js84WuWr8XE5rl0jYC2WsBtM5nBjfFt2xaJ3GY/OzVwCPk1w1W18a4MRTRkOS89uEBhiXbZOW0xSl2mDVCh0YaEttrAXGpabrFJHV2MSS7jWq7CNytM68oESurWDRDdvgf2XBcyoZ1L1maHtkK63evK0rrg2wxw0KGUV1q1tZNbrdG2nAku4R8E90J814agZNVuLwpePE4bYjr19TCRXhJR6tZ97dzeDjMoCiqdjlJ3Vi1jbLdGuz5p1dfbQne6TG83Jtu+3ynv2mbC236Sq9qdW9dumzxxwT1sy+TEN6jZ6Z+uTzt+u7bYO4xPp8FqLsVdokEA29oOctPWJbf8fgEcHYdsrGm1U9UjrcUrHYPubliF9l7rdG67F1xee+cSdu70tm2E2hQ1IXHjbFuHaeMQ92zz9tplStvPKmA8eBMqLnQnk67S9fnlOHbUWeHB6lAJ5y8dG7D6ltk6b8HaDaLxdgKXrvC9Y4/ehkcCpKnxa9AKcWsstP0UMru1BgHzhq95rWiQQ1ZK1hgsYznikXzKkT8KHFuaU1GgBA7+sUxbBSSo3TpoW9oeqRkz8WA0COBupMSqwWhETwaBdFaKUF/a0s+4sqShRrylrudtZcAYVcUbOPGPuO3fw8aDkDEiJBhM1MPZPv0n/yfl8b9LM3wPU82JZn9Cs/iM4uz/IbVTbO8Q65tgcfkquBdtiUt8/gP6yR5++ksBQGpSXDzE1uf44iSQHQqBvsb2A5jTROGGaSdE6iWuPEdMgo16tLyNW0vOV8sWBKltjGKAx1PVF6TxPmoy6mhKMl8hrkZFWLNo9YKCBVRIhegZSTWi8kvIVwT1sIoNK1SEZ/KIA39I1PRRbTg3F/R1smX/tdGAqi5wrqTQDa5RIg3VHk7LwIAeD8j8mMpdULDCaIR4aTUPZFvJICYN149uLTmjfZzPSQdvhf6CQGqoGhg7ksOASyvPg3WlCj7EkIJodZtRT6aIy6mG75GaGJ9MsZtHZOs+CIF6Jx5T9W6GmtHebSobKHbi4gmy+ZxeHJhEtAUpS7rXjrmEzGs1Q/JnARgecqPB5fY1kkxCFUg0wHaxxmiAde2EYINerYmngCLxOHCV2dZa71+nmnyHqL+mTvbJs0PqdIgXIS0W2Dpq8WwpUTXD2ZQqGgQ3symooh6r0TG2yonb2J0xJUiDaTpBJR9U7tWDiXAtgacRwfgSrRY01SzUjhobFM+Mp28P0SbHmgwvPtAolS+CPOb+r4aZYPOAzeoTHjUf0ZOUsqq5Le9hTYjnRef/is/cR+w3Ez6Vp3zR8rWY2BTY8yNO5Izrekzjc17InCmjrWByX6acyTNiDTeIJQ18+1qQkmJ8oCtOzZDSF9RUJBq1SQRPrQWnco7ThgOd0nempZGW1rVdkUofS0TZLGikphftM9QM7yqiNu2u7Q/CiMFuHtCsH5IUTzH5YzR/QbV5TOM3KJ6NO6VePWVsjnD55/QG79DkLwACpbnNGJ7+PpvD38JuPidbfoRLD5DlZ/g6FBy7/DnWhsws6bR94ndPynJrSaovQ1Yx6oWSnCbUuqp6bKtspT5Qa4tNQ+VFMyfuT1GTBYaKtsYwaYXQFE9Fzk15F6UGiSnJiUlYMSclo8+Qz+UJtThumqA6XvoFh0wBh5eaWjcUboNByP05BstzecKeTjGqxKSUbonoFGsHxKZiqavgJpNiUaxEWJOE6ouWJVh9Q+1zKnIG2K0egkgENqFYf0pWLzDpHjr/MFi1vWO0PAuWQnmBDu+FIHt1jqaHrKa/GmJ9EqESkS1+hM9uYKoXaHIQmHO1JlsuQYQqu0VcngGBaTfAWsL5mWQcoBkSwgPiy6AW1hEaNEmIh0oEvhUmsoEwwW+ehoncpmizCrx9caCxks5ac0WoRBADWQLrJwiQ8sNwzm7D+OKPqHt3iTcPApZy/RD6d6A6DcwsCCTjAHquAqFjM/kOdvUJbJ5CPOTg8z00PQilY9UF9ebpFm6iTUHpFnhqyuYRkaSISri/sDitcXga37DwJ2QM6LsxFzxjoyUvdMm35A6jp2dEUZ8a5UHzU05ZMqHHmoqZ/jlT1wt1o4ufsqHkAFjpF9eKmi/8ZmcRkf9GRF6IyI921u2LyD8RkY/b9712vYjIfykin4jIn4vId7/SMXb+qfigc9BlnjrXsnMFOvdELzOhdJ/ajFkIItO6o21WSq+07NZu//fb7dm22preXK7fHgMN8wyEWE3nEndanhK1oFrZtg8NzGWAXxVvWs1RMShm63Vp+3RU7VzIrhDdBldiu9/LDK9uXRTTrrp024L7vZsxbc9p6/YGl/bKtW7753Kd7IxLl4XWtiMuM9ZdH/vX7o9tu7avXnKkX17ThSSubtudi7xyHDpxmxbnFt7jnfVdhrnty3Y/3gaAsfiyDR84tqDZKyGBlsXYd65Us62Z7bj/1bdVEd07Gmo+TdbCQuK2HrRD7yctxXvrVnb917p2QeTo8hx2b9Xu3u6om+jOq8uednyHbSZcfVvh0V5H2EebwfbttXS1ytt7pGmB0HplPLrwTQD/7o7b5Tei4RWO6Gj5j7eYA79znUBrkOyOd9ibxbZkpC//Vq8uX9Vi+2+B/wr4xzvr/iHwT1X1H4nIP2z//s8JqlXvt6/vE+T4vv+mnQfa6QEZKZaUpzziO3yDglV7aZa1zngq57ytN6kpEbXELURgowuGph9KgSRYcoKjkJJGHAMvZGTkGgbTiSdnReZ6NFQtP3/Dkgv6DEnNEPEeV6/J6KPicc2qtbIMrpoRxYdQnNBojhHh/PSf0ZOgoRibEc7NGO39BlRLfLXA2gxfzVEgyg6R4Vv48x+i0YyLo7exrsC4giae0Ft+hIl6NPWS0i+J1WEkQaIh3iR4k2HqC6Q8Bamx8agNdO8F5LtcIKZgl0JdWzfH1itUPf342rYsJ10/oIrHRKtPqN2GUkq8BrmNXApGLR25ugJL0A+FDaqwYkmpgfrG02CISc0I7+fkLPEabuFgeRnWsmZAQq1BBNuqCQwtEmOc20I1xjqmIkcRvCtxWgaaI4mwySS08zVJNMY3DSv3gh6HRCZQ5MTpDfpx0PHU0TeQ5cfo3q+h9XlgkvElun5ENfqAOtlj0Czw8YT5tdskmw03fvRfI8kIXX8ewMcmw1QX20SDlidBEu/iR+BrTDzCN2uK8jmoEkkWsromDhlcVUx2SHXwPer+HaJqRlydI66gifq45DD8FnxFVJ0GmcnFx2i9xGnFUk/Jqycc6hFJvBdcfF+B9MMkWDy/hJsUDSw/w3hHWc+DMlsyxbkKk4xpzv8Y9Q3WDijqE5JoTDy8S52/wPuKpF5RF6c4n5O05AqaP8Xlp2zcGZEECiWLwYihsp5Y+gy9DVqweLx4amkQtfQ0VK+UFORSMGNGQc3MF9yzR9Q4nusjDup9KhqcgVsc8IQ5kSQkqpQ0OFXeM+8TZdf4KP/nFM0vSFukqr8rIvdeWv33gb/dfv7vgN8hTGx/H/jHGqbTPxCR6UvKVa+d2AA2kpMRNAYuOCESS8aIBWecyZyVr+jbQ2IN0IEDvQbiWwxVYIoo/RJHRS454+gGqU+YywsKLbgpU0QMkcaIM4goMT2cBFHlse4RmVDOFZsBjc/xNDhfBnenTIiGdyjdnEiOaZYP6A/uwuYRlpgZJxzIDUQMo9E3Atq9dxNO/mXgWhNLnF5D978Lq49bZo2adLWiSg8DDMCmpOu3icRgqjl9exBYEtwK3BhMjK0vWtySD6j2NoNk6gXgW/0Hi1RnocC9mmPTKR0+C5Pg3QyyS1/ZAAAgAElEQVQTZZRaUu9/NwiBRCOqes6JzHhb71JT0NM+iqPRnNgMGSV3aJolH+nn3JV9MlLu6FE7hp5znnAtfp8hPYrqHE+NRynYkNGjpz1KCjCK9zWWPnE0CtTivqFoLrCSEJk+xkchs4ihdGscGwY+CzFLf4kPs1gGskdkhwFE7Wu0OA1VD6N38fEYm13DuBWsPw+QnDxAM9LzH5BGY9AKqw237v8+W+bj5ccA+PUTwAdq7A4YXVxQFi8AJY7H+HqJawIjcMkSIykr94LYJQzSWwEjF4/w8TDsMxpQA1Gz3BaRG19jiqfY+Y9QwKZ7ASxdn1P4kqlOW7biFJNMgvXZEZGWszZxYdFoCN5Tlp/RG34TrWaYwW2a2YcYHRKP3oXiFNdsyKLAbrue/QhLQsESU2bE2SGJzSA9wK+D8przJf3okKh3DZEYP3gL0YZDCPHjzdOWj8/RjweYeISW5/h6Q+7niBiuRW+xKB8yZo8mhvH013DNhnz2QxI7wvoN3+l9gER93m5JFz4/+Z8Y6ZBMxiTTb+E3TzFq+J69xx/xeoDuV3JFv2A53pmsngHH7edbwKOddp+3664sIvKfisgficgfOfyOyySBT33rj4XMWnC4rtY8Xrpi3fI6N2dnXy83eWXZca3af7vZvM513M3vdRnGq/vuMk+y1WbstAjoagU7l/EVF2c3C9i6Ta8M00sXsQUnv7QXfbnlS9upvrJ295q7XPEW/LzNUHZnZ9pM6I6LeTXBvd3HlTa8NCZw6RaxGybYucSd/191S7/kGruso17d7hLsu9OWNrO3HdvXHOfKfnb7pjt+W5YnXYZ+5z7tXP6Whoe2bld2wgFdlli3Ayjb/UgXZulCFFfOT166+p1z6+6/Lcj2MtsaNGk7uqKWQcZE7cuGwvqu9re9ny9DHrbNqrYA9G2Y5BLI252LtFli2R63C73snpu9sg1wGVO88lt8dah3l7+U5IGqqoi8ccp4zTY7gsmRZmaCek9kUtZSMNBWTIOcMYd4Vd6R9zEalOBTGZBkxzTlObWuyX0o2UlkQE3NUEdkmlFrTqoxpsVQhcWQy4aCc8aMsZqQyRAjCaWfU1JQSUUtnmNuIBLT+AVVPUc2QUREcWzcOWO3z+nZ/wUoffrE6QHSO4Lhu+E6MZjeEZId49Mjzq/9JrYpGaHI6iGb9X0Onv8BxfA96njIeP4Q4wqI+kS9I/z4WyEoXV+EAuN6jpRn4UltokDJbftoZ8G1lhMt9z+uDE95JJBB+gYk0FQ3zQrSCS7KMFWNtzErPeeWHrGRQP/cUNO3N1D1NM2aQhekMuQuBxxziw0zXphzrvk9SjYBeR4PccU5JevAgCcNDY61XDD2QdH7tt5mI0saGmJtKKsFuS5JzYjGbzBEJHaIsT28r4jpkUgvlFBVizB9iAluuLFUrTK6K2f47YPGIW5DtPhJ6I/NU3w5w/bvgElw64eYaBDinek1pJ4TLz/ZxuHUlfhqBmIwybRNyuQhs6qeqC38b5oVG39BPzoMfWCGJP07xM1+qDqxPSQZgSvonf0g4C7LC7ReB+yWTbC9a+AqXHlOXZ4DhPisScjSI26Q4lxOlO7h6gXl/HPSaEo8DErzYhM03Q8WqVhEG/rDd9rffoPr38VMfilQq5uUqP8UY/oggsw/ZDj5JkRDkngPKZ6xvPZbbEY3UWMZLh4R1RvSxYeY9cPAMJxew2XXKbMjvM3C47DFoUX1jKi6QJtV0IGtLuin1xn0rkOyT6/5AEyCIpTjbxMXz+gN3wOTENczyJ+B1pAdIS7ndu97ofKgZRWpy3MOdUrGF/Ox/SIW23MRuREGQG4AL9r1j4E7O+1ut+vesOjW6uj+vPL+0ucvm0F3EwRX118GPTub6Iu2fd1ypX1nucnLYe5da+fSYru03nbbtS/V9lnbWYVh292DvtE+eRXAtt3idV35+r28bOm89OeOZSA7T9TLPn15b5cJlu12Ki83+vLBfKWhvPLty8sbW8juukuv4JX3l5Iul+2vWiEvr++skittt9ZNl+joLKbddV9wf8jO6+X9dndNl1h65by4vI5X7r+XO+XqNvoaL6Bre3krvNRvrywvDfBLibnX3QCd5X6Z2Ojwjrt2/+W/L1p+EYvtfwX+I+Afte//y876/0xE/gdC0mD+pvgahGykkQSDpfJLjthjIxv22WchC2JShjokigbUzYL73Ocud1vgbIRHSc2EtV5Q6wUzsyIlxriIzO6RmD6N23Aupzit2+4I2piOJlS5mQHOCEtdIAiZZsR4kCAJNzLXiJMprlkRSYLWK4b99/BHv83BM8dZ8VOG0U249tdRhCY9brNtHjk6wrgNLhoRV6uWSXVEdPibDKoz9OJP6dXnRNV72GaNrB+FGE/L2aXxOKgWAdKl6LcTX0snVOdt9q2GqghUPVrjXYGNh602abQlfhSJcGzI7Bi7fEBcPMWsHjHmkIoNERFFm04v6hMK1hg1ZATLdt/vY0xEQclDd8FURvRJ6NGn2jzilOccyg3OeEZCQqoRYyY4GhayxuvlTzFvzrHEoapEPTU1kUkAQ10veKZPaai54Y+IozFiM3yzQtXQFCcYm9BoE7QsEYwk1OUFoNh6ifc1yeSbYKJAFb74GD38HgzfRc/+VYBMtPxgxFPUFzC4hyLYbB8m34b8KX78baSZYQa3oJpjmhUuPyHJDkn6vw7JHglCk+xTJgdE9QVNPKGOJxhfUycDbFMQNUXLntsBsn3gOSueYvUnmOww0Kx3+D3bC/E3bQJkQ5sgHb34GPp3cdl1OnC4LZ4HS8cXgW5eLJQX+GiCSopGMeJrvB0Gxl2JA2NIFKyfMjuG/h3qdIyLQqa+SibgIakW4Z4unkMzJ86fIMP3Qs20SWmSQ4zbYJsc6gX5xQ8oi8cIlqp5zCh/RhwNt1AnlSiUAS4/RYb3QD2+eMbn8/8bBUbzESfmjJv+mI2sybTP8uxn/Ln/nD3bY19/QQZdEfnvCYmCQxH5HPgv2gntfxSR/wR4APwHbfP/Hfh7wCfABviPv3T/QF6/oJaQoaykZqwjInqs5DmiZ/Tp41zOmgVv6W1iSVjlP6cfHxNrisEyYEzBimN/jaiTdXNrTIuB6mmfjSxAoUc/FCKLwZBQ+TUSKkvpaY+CIARcaUlEH2tSvCuJhvdw60fk9TnxW/+AqJ4hh9/nkN9AUbwdEq0+ImmWUDwLgezBO9DMicoz/PwjssPfDMXY2XXWB3+Tfvm/Ifkz/PjbEFvM8B6y/ARXnoUfz+SXAjV5fYFWF2gyDbZQcYKYtKUldyErVoZCfWyKxEOMK8nrEwrdsJ+8hauXVNUFisNICr4gW/wYbdZoNSdOJpzWT+lrD4MwZIyI8CEPuc6E6xqUn2oq8HMiLN8xt/m5vOBX9NvkumCavMNFfZ+RXzEM0tTU1JzIKYcckpHixLVuaEZNhZcNscZYtWQywKilcjMaKobEKJaSNd5DRqjrNTZDqxl1PSc1g0CnIwmYiDg7DlhAdWFSq+cQjfDjD2iSKVVySORyUjFw/ocw+ia6+jQInBz+dareLZJ4jJz/a8rhe5QHfx3rcgZPfxzKgcoL1G0wySToXVa9gOuKx6hJMdpQZdepkjHiHWnxPKhEuTVJdYazA9QkLVLfBfBr/qyt7YxDMqUTsS7PwsRj0nAd2VGg6O7fCyQCKPgKs3kATSALJRmjrsCvn+DdBvvk/wj03s0Kk11DfEmdvwCEJ/5jbpj3cW5Nev6nyPg9es+CDCFRPyQFqgVNs6LRGuerQMRKRLp5EtxbVxKJCbE/k7BhxbJ5xkqKUKfqDH/CfW7KiKSJiLCU1CTLiJKG/iplQJ+15vzr5gHX4xELfcKe9jiTz/gbg79LU5zzM/+Qmy2A/jN/9otNbKr6H37BV3/nNW0V+AdfZb9/tcvrXSvV3YTAX2xvX7TVZTj90jTX9r37fNUpe9XEf9PfX3a2VxIFqoi83kW7dCe/3J174yKvCaq/YSevuAxv6sz/n5YQs/vqJ/Xa/v2yBp0z9cp3etl+6x3ra/tIX/Ppda7glXttJ0n0SmjiC8btC4foTTfLl3bKl2z/VZYrl/1X44r+pS6x9InpU7Dgp/qU35Lf4AkPmOmGPimpDLE2I6lTFMeFvmAi11BXEUk/uFk+Bp9TUgSNRvV4as45QVXJSGnEs5GCiD4jJkHiDU9iRxBlpOWGnt2j8Wc85hnHeoBxgR7amh49uYNIRJZeZ9U7ZHLyO/jxB9TZLeLyOXbzkHr2YbCk2jiKXz3EZtfI1/eJzRBdf46v5vj5RyTpNXT0PtKsiasZLh5RZ8c0J7+HrXOSdB+bPwpBf5si8ThQQtskTJotbU2nHNQ0eXh6podIW7KTmTGJS4MFYCzWJlSuxOmKqvaMou8HqEg8xK1O2dM9Ehlyoc8wYkmiA643gZRAgBc8JZWUSBMy+hS64Vu8RcGCXAom6hmQtXWknlMz49gf06NuiQcHrFiRkpJIxtAcAIa1nmFICWnxiNjGeLcIVjZCXy0lBYkvqf0KqQ21gZmccl1vEpk+gQp9gEmnmHQ/gFGz41CREQ1x8QTxjuHFHyPVKb7/FvRvo8l+qN2tl3jbp3fyz6HZsF58xCA9wEx+mXh9P9SA5s/w5UWgq2o2NPWSonxMTIaRoHNqkylJdkjfJKGwvVqGkrZ4GCwyBIlHdMBdSSaBRHT8AdosqecfbfkAOwsptkMKP2eU3QtQlvH7yOKjl5iNBSRFq0Cn1DRLVv6EPfbw1YyiPqXXFjE2LsCE+vRBHU/kc8bFBf3iSVurnQYqIUAwPObnJBiMCHNZM9MNx8ULDpiSS46jDowuLiIhJSPjtMU5HtoRN5gw0oxCanoaGDsshoyYjZRBFhNL5R0xlm/YYy50wx2uQTwmkoi7q0OMWv5Z/RM2rv7C+eRrM7EFokfPY/OCu+zhtSIj4Zt6F48jZ05ez3luztnTISMmJPGUqr7A+YKevY6nYSBT5pyQ6xJBWJp1S3Edk2nKVMcoSmOCgMiKDReccthMyZohPTMi9zNyVhxzwFD2tk8JwbbsGgabTBmsHobAsMlIVx8jxXPKix8CHnUluc7oyz5x7xitl6TJtZbZtQm1gXVFdPIvaI7+FlGzwhSfY5oR4InTI/L6E1bzP6M3eIcoGgfWA1eHelPbCz8E7aT2AlLdmhQkQZsVVfEMaDnYBKJ4n6aaUboFFQUbydnTHlKdBvR7lNFoQWb3WbtTUlKs9CjqE6YyZE2QZzvUIxQlIuVEnnDGknt6k/vylHt6nWX1iH0m2JaE8C19O9z0aljKmr5MGeuEUzlB9ZyhC9oGdSvzF2lE7TbEdkxk+wxcjhFLSgZewCi95DqYmLi6IONmW8ITb6+VZD+wXfgqxMwkRspzomiCWX2K+pJ6eR8z/xTnNkT9Z0E3Uwx28zTEJ+vAVlKe/Sly/udoegjZPtXmCbm7IJMhnpq6fTiWrGi0QaozbGVZrFcYhCkHZDY8RImPiXs38NEIlxwEmm5ftbqiLgCvUaL+TWRjMPGIWF1QLRNI6wCWLtf3Ses5mCQwrsSTMLGhiLQKbybBRgNGTgJTss2ImhVVdUZkh2x0xkD2KSho/CNGDLiQJRljrEYUrIhaWUNPw7FcJ7YjbJQRNw+5zZAn+oxn/gX7OmEjjrnMSImZMEAVjswB1+J3sMmUpjwhr16AQkNDJSUbKhbkTOmFWLlY7iX73OWQXCse1Bec2zXfv0jpmSmPOeNAhvw7yT3+qH4IZf7a+eQXyYr+27W8KSH0xs2kxfn81Z3CV/3+je1/gfP7i2x6WU715h3sll39Qgf8S1j+Qod7DUvKv+nlSm70L/FkvtDVft0QfeXjvsYdfMO2Wy2RNy1v+no3b/aGk/zaWGxncsIh17nrA895TdGWZdQMdMSaJX0G9DUl1R4zuWCviZlzRoQh8YGA0GnDMy7wUnNDjxj5EYn0sGqoybFYhgwREhBh5AZYPLlsyBiioqx0EQKbGnNinnNs32JTn5IyoC4vuGgecs1ERC9+F21WmPgh9dkfUjYXNDhKyRmzx1o2xJoi5QmCwfmSWjdIMyOxATle509DVt+VgfBw/QhJ9tAmZylzBmaML87xqeDdBnV1wF65AnXa4oEC0FRs4CFTV9PUOY3mCIZaayrTcNAMMTbFuBgvJTfMOzjZqT1skzN4OJEgv3fbj6jImbHinrzHcx5yzF0qXXIiT7BY3vLXeSFnfKBvE0sfpyUbVgxln1xnZNEBL9xTVB0jBuQ6o5aGiU5RGoxJqHRDRisM08YIHRWRRvRkTCM1G12RkGIkReI+irZZ7uDyrvw5Q3NAVT7DzmMkHqDa4Ms5Ng3aDawehIxjS2gwq+4zNAc0m8chuN4qXxnTo2pmpPEh3m1wPuc0/1MOy7s81wf0SDEq5GywWFYSiA/GOiGXDRU1U52G88Ugw3skruVNazOqsrrfVo5UW8UlbyxldUZFATZi7JJA4+M2bPycF/aMd+qUSDIUWOafAcooGuF9FRIqEOQV6xlJckDllsRak68fE0ejkARwK6bpu+TlU/b0gA1LBjLFqiWWhEYLBmYfazNWzXNiTcnG34DxBwAc+O+iJuX9zePAAOwK9us1Eg8AwSf70L+DaI23fWoTE+ePGaqD1Wegnj0EbTbkuuFH9R/SF0cuDd+Pfgs7fhe/fszt6Jt85P+MobnJWXOfPQYkmtCjx2+bv8af8fuvnU++FhObAId6nbmcALRZ0Ql97ZOQEcpmg6qTQYglYaAgCkOGRKTgGmrdEEnKASP6MmIucyo2xBqEPlaUZKTs6Qh1BSt5QY8xRmIiUiIZsPJnFFIx8D1OzZwj3cc1OT2Z4LVmWT/lmbngmkS48gQU7OYxeXNOQp+KGSOmCBH7XCNnST++Q148xtPQz+6ivqKu57zgMZU0vH3ye9C7ge+9jyx/BsCs+izESHSNwWGaoLPqpUBsgqtXoA6vcxq3CVTL8RQbD1s91BG+ZTod2ilVs6JgTj+7QcYBqRtibII1WdAHrVdsVj+lx4ATXnBT7/AH/DkHTMgYcKAeR4nF8mM+5Jt8g0OOWyclxDpiGaDUpPE+i2aOtT1Ms2RVP2dlNtziJktmDNo0fdUCoSMGZAwRoKZAiGikxPkVaApI4HvDkEggKGzqGVFygDUpGz/nTF5gJWVibwWKpPIFWgozfc6+vY0x19jMPyS2g1ZYEGw0IHMDOnHsTrrQq6Nuzoikh9gEK8qyOmXECBv1uNG8TTS+hUQDzOxP6Q3eZa+aY+IBq/znJC6lN3gXV51jTUo0uMXy+G9T9W6RljPS/CnR5gFUS1w5RzslMZthe0f0x9+kN7iDN32kWWBW9/HLT0m1x/vRd8FEVMUzRHuMb//7SDVH8PjRB+CCxobNP8c2a/zklxlsHkB6SHL4NxFfkG0eodEIbMKwfgfNrtNrdR56eMQXpPkLyA4BwzgaAoL4Am8HSLMIyvUmheE7od9MhmvDI2C2fG+2niGuRCSiHryNlxjbu41tdVyNKxiU53yvDDoKs/JTmmaDdRWSjJFyxm13BEZJtUcjjrXkjHUayEO/YPn6uaLy2o+8Foj6SquXVnVgTAnx6K0J+yWn8Cbg39WGr0eYvtENe8P6KwSKX+0M/j+17s7iL9ZaXl7xilvxVdyXK2f6ldrvbPGG9vqF3725b7buzOsyvW/ecntCcmXdy5/av4QtGDd8+XKefGc72dnmle9f2fPOWbw8RnLlXbrPIq+0Ftr1XdsWeC5XAMKvnOnVz9vre7ntl8OoX++iymvbbtt//V3RoEKUakZCxlJmWCznMmOsQsaIKft4bUgJrlfPTIlsD2lWWJNRuiWP5Ql9UhKN2DBj4FMOmLKRNaXkLJoFa2r2TGB9CG5EhCXCeEfNgtikDLRPSo+BVogKczvnuP+rgbfdXmcv+TVMPEEXGyTqBx0APHEyZcKUsjohiSd4XzLSHuBJ7IRoeAeSCVSLgGlSw135BhQXVAd/A6IRcTYDt2Eg+wzaLHFDCdU5af9GkLtrJfRElchOoDL4VmbPuzxk7lxNHI1b6b0UMQUVm1b9q2LtXpD6AWm8TzP/GDERqZkQZfuYTSANfJdr3OcZ3+ED1mxACWSCIsz0hAl7nHHC2hTc8je40Gd4UQ5cQqYpjVtyKhc8Y8axjjnhOY5QeraWgp6mjBgGARsTB1fT9gM7hzc4UVQgkR6xZmxYsZA5+/YWxvTQOrhvVmL69DmQW1T1nFLX9MwUiVJy70n2fxkfjcmKU+zgDuXsxyTXvkc9/hX6Fz+gWXy6Zb1tynOywV2qo98myR/gercw5TkH5Qua/l1Mdb6VZlSb0hu9j7cZtApjif27iK9oTExUnSLNhvXofRaHH2Cdo7d+EsSKq/OQqOhfb2my27rR7AhsnyYeU6XXSExKrA1xMiG2wXrVeEo9/ibabDg5eJ9sPcPbmKI/xjY1o/ljiqPv09ucYtRhW41R8TXiqhaf1oPyJCAHbBbK9qoZxGM0GoN/guTPAo7OBPrx/PT3cdUcI4bYtNTnyTCwm0QDzOBOm8AATEy+/DF5/piMPiIxUTTA2jgQttYrfDWnpOSx+5g7/i2WesHH8pjKP2I8+yGRGEptSI2ldI8ZmoSNVgxI+ZncZ8kX87F9TSY2Qv2cOpJoj0f+U8asWVMEJXA1KI6FLDm27zB3T6l8Qep7CIJzJR7HNZ0GcjsaKqlopGatC6xaUk15z9wg1YSYFENMoxUNJY0WNOLw2rDyBZ/LCUcyJqOHlYxTTjiqlkgH0rVHkEww2SES9XHrx6QMg2wgHsFg4gE0gh3cCjQ52XWaeEj0/HeQ/k1i4GYxpChP6JSWREu68pvI9hHbJzZHNNV5UIXyTYgtVefgyi0mL4qnqCmp6gvEeawmNM2S2A5bFyvwiVmFsr4IMAxREjNAMES944B9c1WoLwVmesoeU0qpabRgbUL97pg9nnHBqcxJfcIfu0fcjMbE0megoXLjAZ9yU27yc3nA527Gnukx1TEP5AV70sOqZUkBApn26Wp4IyLUNaxlhRVDrwXvFoTrXDPHaBwSozahLM7I3TkRMZnpYVu67r4El9xkB7zl9tB4L8CBRvfw/bvE/Zu4eD9ohe79OlF2HZcdhfvQO5wEJl2Hx+aPqPv3kOwIW51DHsgcfX6CRD1k+kvY4mmgjYrHkB0Dgq061glPUl1w+OxDbDPHbh6xnv8J4gp6dh8wGF+3PG51EJAxEdHshyS9GygC5QvE9iE9ROMhVe8mq/EtiskYU9eMLx7ibEovP0O0IVv+DKPfICmeB3evPEXjSYj1uiLI+LkCLc4h6iHPf5eifE7l1wyiayHW6Eo+18/oa8qIvS3h/lqWgKfwz+m7Pkmdcm5maOnprzP6jPAop5xSURFjgq6o9vik+mNy57hdTJmxJlLDo2bONMp4wjlJ675WvmFqevQ047GcstaKD/QtVmbJBRtmmrMnPSr9Ytqir58rSlsN1j6tX/WALhkMXnYZdw3s7Tc7tfmGl03tLzj2a9a9DjL7MoljR363e4ytkd0xKrTQR+n4/dt9v87YvqxD3XE4ZLvJ9pzkiqvwZe7Uq3WXl0SYu67wm4HMXa2eb993SSy7bbffbY91FV76VVz+l0kqXz82L2drL10Y2SHu3F7jVk0eLlkuWhYV0zFM0NZLhvHaagB0oi+ddkF7FnKlX6/WQUpXC7xl4/CvvZLta8tI4hEu2UYul1drS6U9L+m2U92+4PJ9u5/dMIp2RJiuZTzp2E18e66OjuDyZfYbOoJIAkmlttKKHXxr97fj8fjt+hbl2B6re9h+kTu/e299lYDB18Zii5IJz6ofM/AHxBhu+ht8JD/Ht2y6P5VH3GI/qCg1PSISnpjH7PspCYEPPaFHTcmZzBnrmAjBEmMwnErAHY10yJxzamosFi/KgAEVJZU4JmYP65QBY6wkNFSMfUbVLEmH97DqaZafIZvHqETUd/890vx/JooniFjs8C18dohGUxaTb1EM96nTjPH5U9JqQSQWbIqb/DXcwYD+/MPgEuQPqUffRKMR4jbY4W3wDW5wLyg4mRgvEbgN0rtJVJ4F7cpW9MSiJDYN1NgmQl2Jc3mr8hST9m6SiuDKC8TExFpTuAXD3u1WG2GOivC8/ileHAPtY4gY0sMS0ydlIHssOeeAMSs2jM0xvyZrFrLhXJ9zaG8z8YYJ+8TS50j3ecqCG/6Avozoy4yJn5CZESlneHUYiVmwAA3KZCU5jgrFUOBJZUBqxzitmLp9BEPjVoFJVQ1DExII3lfUzQoRS+NzEhcFdtZ0GsSMixfo+FvI5gH0bhEtf4YtZ9THfwuXHBAK0xuQGFNfkD75JyExUs2x8Y+xg1vUi48Ds6v6IP2nDn3+eyz8c2bMuW7ukZp+cGld2YYBYpw2IfHjCkin9KMjivohpT8ntRO8t4H9pX+LcvgetjrHvPinrM5/l7E5bglDI0xxikQDsnrO8eYzVuvfYDj/CdHmYbC0k70gvu1rss1jROIwUfs6xA9Xj/BNjmoD1RJQ8s19RMOkvZEC3CniQoLumGsYDGuWDGSPxA4ZNBWxZHitMWJQVa6pZcGCioYeEGlMqY7PdcZIMvoSEjZ3uUZhK1bkHDHBoxxH+zznnNt6xH2ecIMpF2aFALmU9EmoxDGMjomblBUFP3XPeTs64H5z8cXzyV/9lPXVF+0UnLjkXutmZ0+nREX7HiyC3WWXR4yd1uG526FspWUO0J22u2aQtGb3q+TUQYQ3aHluOb5a0VbpAq/GtlTPUYBidLTPYq+yK4gFiQOHP7K97m2gV3YsiXZiQyy4jruq5bPaPuSCddIdY9ey7fanO/sONM277cJfvlOX4nI/yKU13FlgXbDZtr3VqUrtWpjdGO5aU7vfd0/oYHy2FoHsMrDoK/sULsfv6l53LcLLUe3OeVeHNfR3UKlC9Y5dR1kAACAASURBVIoi0+Vw12wVw3xNx6GmEu/cK+F71QZPoAOnLcQP+25ATUvLXbd/+zDhKK03sWt1R+04h7xtyNJ2XHKXimWiHuMbxLugAeobRC/PcWu1SavCRrDornge6tvfgtsZo2ClBaUwDaSaXf9tW8n2F9L9brq12nlHys4IXvWYDHJlVG3LWLK9V7qkxUvH3U0v/FtksYUOvu4OeSwPuKWHJGbIMROWbDiSlFscEmvw/WOJETXc1BusJDztM4bEdoD1KYksSe2YzFtqH7BcezoOIhPkDBljbSh5cr7AErV8bGHCGMge1mTEyR64Bb6ZEUVD1vOfksZTymZBrCOi69+nsT16g5ugSj35Dg6INg8Qk9HLnyI0VPWE/uYRyfrngd/r7M8wh79OlV2nnPwy8foJrn8HMIFxwVVovQz8U+khItFW5k98HSw13+DbMiqJh+CCbqVEAxATpAurGU2zDlaDy7H/L3Nv0mPZlt33/dbe+3S3v9FkvsyX9V69YrHIEimasghrJhuwBXhgzfQBbA8EfQIDhD3yzPBHMGx44oEHAjy2Bh5YBmibrpJEqugiq31NttHduM3p9t7Lg3UiMouqIgugYLzIwYuMlzfuveees85a69+5xhbfUqBpj8uZu/2fsKo+JWui7V+xZstJDizLF9wPX9IzMGrPUleoZDo6vHq2LAHlXJ8w0wN3ck+fdnzhvuJT/SbiAnWcUUmgYUHhajZqqoqUB74hH/NSvuJer1nLBYUYS77KI0vep707VxJziwJN+YQHT37No72XHMl5IOnwuFMU8YTqDI0nxsPPyURz5L35PrvTD6nv/hRRoSiWhLf/G6nfWceX98xmn0FqyfHEcXzL0e1Z92e48Y4gFX52QWrfkTURqi2xe0uhBSvmpmYgQbIeetATpVvzRt4wj3u29beRxTfRcku1+VvTuW9Rfn25pa+fknzJrH1NoGDpnpjzcVggoUFDA64mVU9AI8t3/9wmhykPljRCOplgvr+FB4F+WEI1FdjpHM/jHudnzOoX7Lufsyg/ZjXYGNly4iAH3nHPJ/psGhoTMR5J2lNWFxSxoou3QKZwMwLDZPNno+bHXFBK4E729NLhFY6mH0KAHUfmUnEnO7bakBj5Jk+tVxD4mV6DwjO35oka967VPaUEsiqtDJyHBrj7pRXla1HYBGj710RGWukJOKq8Y8EcJ44bXrPhYQw50XPiXg4sdMbRnSh1i5/ugkripANN7mjp8QIjkTT9UVEarZnrhlIqej3yEDbh8JOsw6Lc+u6ejp633NAMX7B0l/hqS5F7QnVOLs+Z332fcf236ZqP8Gmgufs+ev8XpOF7JB1YNM/NX94FjqefUocV4mo4/JQ6Huk2v4/Mn+NQXPslMtyQT+bytOt/Sv32imr2id19p+7OujxsYa15itfDXD5EILWAIc3iwE0BwDn3jHGHl4qYOwo3w2mPptY0fhIIUuPVdKiNrEiaqGROqLa87n9gx44NPUd8MSePkRkLjhxpqo/4ZAi07Kn8OU3xgvPhK4pc4nxDE2sEGGlp/CWXyZLX6+oJkoyn9pDdmlLLQ8ameeyrmRZOwcNOSpIkjvkdgZLKLRjinRUwF8jDjpR72mTjypyK7vRz67Byh5OGtn9F+TDOq1og9OklKXd2HnHgjd6yYEFVXOLO/g652OKrr+D+zxFX0ucDBTWz8ikxHgm+IaUehxjRPO25U0v/2mjCxSOSBjTMJo1nQhIUcU/or0jta9Ltv2DMowVDuxLSkTTc4so1Op7w8yMaDxBbYvuGU7piUX5MTu+se9SMdwVeE333hpP8iFX7DM0DpwlssWvplkBJyYwcT5QyY6fv8HgKLfkGjblwiO3AClew8C9wUjHqHc38M+J4RxxuqXBkKhIRBSq34KnUbNmyYstBbznIHfe5Y6Uzvimf4nzFLr2hYcY7d8VGl3QMfJvfJIryA/6MlS74grec6PEinOs5M/cah9Dq110rKtideJrUsthC0uFwKkRJ1qyKe0zJeQjk/cV2dXr8tIDNkh9HVguY0A8WmDo5Ythoon+pzbVxx5agSTJKfAQA5ENb5TxM46aRhK2biJP3e2v+WXm0nMncga6mF5msO0OmkQF+IS1KxJ4/9UbtmEZeG6cerMU/WDbzACD8Ehjig58/LHpthPggqeqDgdH2SDp9N9lc48nk6SfvR5EHEESm9xGm2D57Xou2fs+dskdl7P25aTCRD5f58sFY/pdef9Y4jaAPY+jDClo/GIf1/ec3BS8/jlmaHt/lw6N5fK0Px+jhZwZgvY/QFitErjSN7vSa7f/a8bHf7R6P44fwyodAAqTHVcZj+pVmRAY0tVbUPxi0dQolfh/2bNQNnUbbPI2s+pgslYDwuMjPOiGu05Vjw2Z4PL+FYgK9pmSoKVw8PL6X9wCNPFp363ROuulcer8eejhiDkfAPybOPRwN62c9D4sMh3tcNakogfA46DqEKEbQd+px6h7Bub9qJP1aFDZV6OTEnCVFrviZvJpsp+8pKdi4j0jpxK2YFKfRmjd6z7l7ztM8oy7O8FKQ00CvHaUIBQWFQpgSqFRHnAajD0hPq3ucRjKZKLYXqbQxLzAJqCqewErmfJuKKCOheQKzZ9C+tuQiTdC9Y//8H1C3N9T7H5gJn2ZavUNRvhi/x6f5U/J4TeEWjyfx2L4i6EB9932un/8D5qcrCiJanuGqS6R7xe34p2xSxrevKdbftSIpDkJDat9C7EjpSIoHBMFXFxTlhhw78rhHc2SgpRuvWftnZB9oY8vKLUg5cquvUed4Wn5KHvbGuNd7RhkY8juWatD9kI/kQTnjCZDNajw7hvHaOGfS0ErPy+EHNFQcOTEbrij9mnWe0+uebjzgVOmkt5M02qjxI77iSdey0QWFXxC1m7pnu4gyiVbvUZReIi1HljqnzwMLndNKx5ETUQccHq8VMXbTKmFDHkaq2adIjsTTDaXMKcPKgpejR3VECEQ1L7esiR03rLlAEH7LfZfKNbhqi/Rv0e41xJPls45HHtw5TuMbar+xLNg8UFZnNDHT5TsumTOjoW+/YuhfA0LwC6PpMFm4i22ccrJxL5MZ4o7h9CWLPMPhKdKeIR1ww1sO7FjpljbfoST64R0jA5XMidrRxyNFOjLoyUxbfYMrFqzkKSIF4+Fzmu3fRcYTOt6ZG025YnMs6cYrZvVzfGPBRM1wgy8vGNZ/m6HcoBJw8UhyBWG4oUot5A73EEyjESSQi8kRxlWs+zesDj8kicP5OcX8N0AzF2ScZmbxDjfcQzFHqmd4Cfx+912Ca1j37/CuIB2+oFp8i7+v36XA8Wnq+b/u/7tfWlO+FoUNlIYlX7ivOMsLnrBipCcQGOgNgcKz1BVfudeUFCykJOeeXjrq6jNcFmJqcSqUEuh1T6MVrRwoqEgCLUdmLJhTEBnJZHoZ6aRnJVuyzPhJ+jnP9ZwgBTvuODFyyYYFW8buLWV1Zneq8sxeugjJ15TDLW64RYc9x+ErAgXBNZynRFlt2fU/YV1/h7vuL1i7jxGFu9OfsykWHC6eMf/iDam8NOSzuqAU4fz+kkIsr1SL1WQoKeAKC1BWtYg3hGG8AUYKX5lpZI4gQiEzJEGKJ0YZiU4hVByHV0DGYSCHKxZUeSTmEyc90KtFuf2IVzxxK5IqG+Y0VFRuy0ve8iw/wRN4w1ccGXA4KgINNUkH3uafEhloqLhhR5ZMkkRB4F7vGCVx0o5eWxI1pD3tpLmsaSh1RmZkpzuSJM7zlooVghK0puNEcplt3iAIUSI9Ha/kHd92vw0SSICbvUD3P2ax+l2Yf4obbtD2LcE3RlhOHV5LimLDz4d/hUcoijXrUWk2f4d8/DmxfU1wJVKfg6tw80/BVcx3Aamf2sWuCbq3BAHqZ7j7H7LQBcvmCVRPrM9xFTkscHmwPsdNQIGrkNRS9G8J8WN0PNCklrG/xrsKX8zI44HgGu7yayotGTmyqj6x7AsJ1ItPcOOBXCyR4c6O0/xbNNqRqo+IrrFTloScd4zlmXV/qechSEXPRuq4J5ZbRj8D50gI6mvU1+b0G0+WwIYSm+fGwxMhi+W2So7m+JtHXO6sO89rfPNN1AVS/ZRYWfaTijdXFfdtXPvSyNoaLaxaCzQO+OXfQnJPQQ3FwiR5rqDs/wZGkyLyPwD/CfBWVX93+tl/C/xDYAB+DPxnqno3RfT9GfDD6eF/pKr/5NcpbQ7HyEiWTDGNMw/ETfve4/GP7aefPKUSiYdw4A9b5odxKJMef54lTeOQNxSJBxxoGldE6BmmUTUQJTGo2bY4vLXzmrCx7wFJm0aGaYzUaTTwVBjZxEKTdWrdE4bEiQhpEu5nb+9FH04ucSCBQMA9jMriEML0dPIeNcU9jqnvscCH8dJN79Ysyh/HfTH003aL0/ESbyAFfjoqhkR3jIyMNg5ohVLCVEQe1gCR8RfWAm4aT6IOE9JtI0qSPI0itiZITIlMD+Pjh2uC6d9ZUHAikT8YW2w18YCKB8Lj95kpz/JDVN2F6SZgnmxMna9Ow46d04Y2R4m4iSjkH5yIcY+jnCGXOoE0pak6wtxG1NRPRcajvrZRyzm8n1uxQcmuQYqVOShrQp0dT3xtq43Y2LmURkMypTCqhxR2lk5d7EOgsJ9GY8QjYQk54sMCSXbe+mIDOpDC0oKaxdBW8TXqG3tPruIxgwGmqMAV2VUGNLiC7Ao77fOIaJ6QZAU8KnbuZl9bEZNo/18fEOJp0ePCdPwqs2lCyC7YhOQqO4Y5Q87Iw7iuRsFBknkQPl57fzUF99fp2P5H/s2w5H8G/KGqRhH5b4A/xDJFAX6sqr//a/zeD74UwfM0n3OQIyWegkhJTSc9hRZULEhEai0IGviG+4xe7ik1QL+Dcksn5oix58S5bkkkDnS2eMQxm2yq99zTiQniR00cdODCOYI6GgJvuOEZF5zrBUvtCRREGXnLGz49bc1Xq7zA3fwx/ekrNu/+T9z19+jaLyj9go6Oe9nzRD+m8eekdOStu6XpXnLgxJkvyYPJgeLxSxbXb3A5E06fQ44czv6AUqwoeyDrQDj+DGbfgNiT2leQBluSZ3OG8FIS1KHjvW3Oqi05Gmrq/IyUOlxoSPGGNOxYsEHEc+IwESsjfbzB+zlv044zFsyZsZWGM12RyAyMeOlp0j1e/HSrKagp+U3/TYbxlgLPO3fNchrRwGzBX+Y71r5irXMKglmF656numEtC0DZywFRoaExIEcyrXQkRiqqqctWPI5EJOA507PH4p2BW264VOsmyCOz+jmPe8fpZiQa0fkLW8zvfkhwS/r+LWV9wQv5PbsIz/4eIbUmoyrWhPYlafVbICUqbipIIGd/YBxDV1mGQf2MFBqyn+GrS6J4xrBAXYHL0QqAq9DyF3eigk7i/GwOIGGGlBuCmA06xZqi2qJp4GKo8LMX0L2F5bcsR1S8+buFhaHe1aVtI32Nug0ALp0QMpJ7wBP6K9QV5LBE8oiLB2J1SfYNYby37glhLMyK3t/8sRmSps6E6uUaX52ZCibUaP3MOsBpT3w4/Cv69ks2cmFNQ9qTJDMffgPnTUamEkjta8rVb5BPX3J7+jMccJCOJgm3cuDbwz3OW0jzz/rv4dVuSPu8/5UV5a8tbL8sLFlV/9cP/vpHwD/6637PX/0lk3OEuWnOdMFRDiRNlJS26vQz+nTkTM84yYGCEtGZLSxjSw4LSq0pKFhqwygD4BGBoJ6RxKiJJUtDwKYuKuCZyYyZrOgYGSRSEEg54YgoiY6RqAcWuabr31BObfR4+BkOR3H7p/SHn+F9NYXmOpa6JNLic8Iu1RLyyJoVeTzhiyWLmPGuYvP2ezjNyPELk8Csfwey3bGzjngpSae31k3laHQPxWLmxJEf+GBpYBhf4pxZMqXUU/iGnHrQSBcHXuo1SRJb3ZA10sic4fSKROSKd3zEnJWY7vKYrnmhTxCxO24kUmvNG3nNWheTdU6i0RlzWXEtX7DSOYnMrds/LpRXeCKZQs3rvtTSxtH4lo/9nIYFgjBXITEiWBeYNAKJfkIovQgFJYWWdBzpZWCpwl6OJCzHYs+JJXOGtGPQzKb5PdL+x1Y+komztP5o+vsJtr9HCgtcjgzVGfXOurpcboENvnuFlucWqJJaOP6F6Tk1meVQ8zHSfmmovCtRX0EuCOnWvscj8WCxiZPJqGUZzK0DyYMV3PEA3TVp3JHiAQWKYoXmHsUhscUFu7jL2QuTb4UlQobhFsIMd/uFTQDxhFv9BviKw6t/zrz5jK79krq65Nh9xbz6iL6/RrUni+KkopCaU7oj+BXeNaR0wLuSmDsyYnvJcYemnjGfbDHevyYdAzmPZFHUlRRS413FQe+4Tp+TU8eJL+g0cZX3JDLa/Uu2fsE35RJwvNXXDMMfE3Jkl26pKdjpiWey4Zo9q/QvOZNnhHJFO15x0J5Xw56n1eJXVpR/Gzu2/xz4nz/4+2ci8n3gHvivVPV//3V+SVajYhiGEmwokfiIqDyMcyXhg5FnygqdFvJu6iECNlKoGqrjcQx2SG0JS0FSGzXddLE4CvK0d3PTKJdJZEmTP1xkwZycR2QCFzSPNt6k1pbQMifnbkKDbJy2sRQCFjZbamG6T1cQpjEjjHsbJ/IwidvjIzL4SJbVCLk3dIyJ7EO21/IA9GkmPyKtZsMD8ogOJo1WvBl5wIcLPJp7MpFBRkShJFBQoWQqCnoexnEbBQcG5lhCuxJxGFI2irm7isI4HVunbkI/3+OFD59KVhuX3SRhCmpI3cOC4D05WxmIZMn21ieEzQbUTJx6uXpyYbXHRCLRdkfxZP+dvN6QahqTFC2WaLEB8WRX20jop12mOCSdUC5sJB2sQFEs7PHxSNZhAnW8Id8i02c4kGXaaaXO/NdyZ2jmeDR0M9fWnYmHcUcebsixQ3NraK8UGMIpkzVQANQ6TQBfQTwhuUNzsMKjCuM9Lj2zo9i9QtwS7V7ZMe9fgzRo/5Y80aAgoLIg6i2eE/gZOR3wfoamI0qE0E2nWJzGcodO7sRZp2MNeDfHuxmj3jByBIFOO446sONA1syQEl57RjGt98kd6OJISaBjQFB64vTpZnptUR1sTAVGbMp6SGj/ZV9/o8ImIv8lEIH/afrRK+ATVb0Wkb8L/C8i8juqE5HnFx/7j4F/DA8ECk/NjKSRIDVf6i2/zTdoxcwhYzogOEYG5rrgSl9x5i650xuWLND+CsFkGIWWBA0ENccQQz2hUs+d3HIrOxrmLKSh0wO1OjtBxUrmnZ4IzlFrOQX+JmbaEKgQ53HNJfnwQ47cswkX7E8/Au0pWHHKNzgCDs9P5QsS8Nv6HWZ5RiYRpKaoz4jjjpRaXJjD/idGIZj2YvXN93HO4/Dcy56RO0YiT1JBk0ujCIhMEP8Jl5SskU7uGOkgG0oaKPGpNeNEKah05GO2BHWcOIEItayJuSWTuOQpSXsrmqHiXw8v+XvhdxE9cC/33NMyZ8aMCq8e5wKqiY4WjS+pteSlXLOgss9UHTta7mXPJ1ywYUNioJWOmc6pXIEDjtxT0VC4mld6Q6bnmA102EjDTAoajKc4MtLJLZ30qGbeyC0bFqxZkjVyLktDpeVEzkJsX9EObxBXMl98gtz/CKnPSIcvOY2vmT/5jxAEl/pHLzNNJw6v/w+bClJLOHyJL5aM3Rty3BFii6/O0OEGHfak8Z6siZMcURGCNNRuiQ+rx1VBzidEmag0g3HgZOSkO7wGZrlENT52Q1kSXTwCQtCCkzsiKVBREfo3OCkow4ZufIfHkcXzTr/kOS8Y45H+7l9QuiWBgrG/QsmM4w0HOTCLR27lllZ6PsqXtJxQNd7dV/KSQTNLKVnlFXeyQ1FWKTOTBYO29HKi0BKnDsVI2w9UjyMt87yedqiWDzpjyVN3RtTEUQeidtzlE3/hX4LajTdqYuvmeBwqypASr92O69jyUbmhKM+R+TdIt38EwDpULKn/7Rc2EflPMVDhP5ySqVDVHsxLRFX/HxH5MfAd4I//8uN/MQne68jAzG3o8j1Re+ZSMurIgjXX7oor3bEUCwjZ6Dk9t0TteKVXJCIrjVQyt7g3zexkT5TEQueIClmS5YGik3o0E7XnQEsS4ZmswZfElBEVKkqyCLWc8SfD/8vvh09x4imKDTmdeH38Hgu1Zf51fsWGJcO4Y9COOWsU69TO2DLmEzVzRBxJR1zzhPv+J1Rqd9lCM65Yma4R8Lkld/cMeiCo5yQtIXvycMuOSCUzKjHmP2ScBHqOnHSP1/ecsopAn+/JKIVWJHo2rLmTO06yp6Jig9JzwuFpmHPSHTM1M8fKW3/7Tm7Z6oq9a4mYddRruaHMM+5lRycteeLHeYQsygVPcQS+yH/GRuZsWU6GlJmgZhVVuQAkghYM0tLRMqNA1VFKSaklIkpDOZV8Tz05fgQ18CCLMtcFXgpuZEdPYsuZ7Zw0cjf8DEgs3Zp0ekUcrti3PZu0IMUr9PZPEV8zjFcUUtPHO+s62hveyTv2dLwYnzJ60NSzZMOQXsJ4RZ/3KJkylxxkzztuqQic64aTswvaaebEEVGlkQVV/QJfPoHUUWmPp0bSgJeAiOCidZZ9PnLUexRhq2cUyTh/3gkx3/GAhDsFoSAT8TKSaMk6sBvfkMXxxD/nLlv2RZ2Ud7JjE3cEHCqJoxwNjFFrMD7PV3xbniOS2bPDI/xgfM03Qs+SAw9cwUJqOnp6Ou45UeDthpc9oxwZdSCIR4BSAwup2MiMksCFX9LJQFblXd6zmtyAg3oudcG9HPjMXfKFXiMCN3rgG/FIMR64zS2djgyajCP5b7Owich/DPwXwL+vqqcPfn4J3KhqEpFvAb8J/OTX+Z0JCySxESMyoySKAQgDI0fpaaYRFUwpkDXRMtLTk7G2v1QTrkeJZJXH0fLBgcITqDTgUJJGRhcRnfYcEyHT9kAFvSQCDfvc87DkdZN10TFes+FjVG2pDkzdjuLUExmnUIsFlsFYTqNbB65i1J4S81HDq409rrD/AsQTSYeJyGiFlhwZxKyoq2nhbsfdkchEHfFYMhXicOoYdILiSSSiUV/IDBIJasTMNKGMwETPmINmZs4cSo/a8oRzu5vaM3KkIzHQ006WT0bNLMVWBRU1Zg2VH5f7HQ9j+gMxU6Zi6Bl1YGCg1gaxy50ggX56jE7axYCNY2EiDKNCoEBFGEn0OuKlwFEi9Bx1R0GJl8q6q3SizVesxfazDLegShpf42VJokPcSJCCjp57OTLmnja1iAhLHDl3aOwZOE6EUqGno5XelhgKvZ4o1D69UToegm1caAjlBh0Pk/xPUFoe4vZcTuQcifTTIGbTzMOu2VOS6DHUuTM79Yn8XFFM2lIYZGDAXKdHBkTseumJZEZL0FXPKIOtC8SuqU4j8ylPrJOehob71NP6gcK5iYpsRNk0cUD7iTg9ozLmgmayxEcdsQNEwYujwLOUhkLsudIHZGwFSgq8OpbUfMmNebJhPoMaj/QaGTQRNf8V5qK/Ht3jl4Ul/yFQAf9sYgE/0Dr+PvBfi4jdmuGfqOrNX/ccijIL5xzyLTdywzN9zg0nEFjngQUzaipqremlN6kQgtfAR2wIAk7DRO2wInmTTtQSWDLnRo94HOvJBWSuS5LY6DDTmrnOGNIBFJY0dJJpWKG6p0L5Lf8Mrx5xdmG33eecscVJgavOaPqKVjo8kVXxAh0PBBou6+9SjOlxFHTFAhkLcnnGTJaojrx1b3maCqpssWxabHDjDik3zOMTxsH807IkrjEL6IV/8h5VSgNJe4ocrCBhu0anbsqNEBq3th41Z3qOiJocZSUzRu2mwgChWDJLift8haSCj/SSVu85ysBJjix0RqUVb+WWUuw5Ztpwz8HGITxVrrhze1IeUclcyJyA4yhHGpYcuSfKSCRzJjNqDRw4cid7lswe93CB6j3tQ2VaJ5jnxyiJFSuSjjwqIjQw14aGhiSJslgiuaQajxycIdEpHvFSs5Gn+DAjpOOUcZAp/IqUOkZ6yI6WI+dcUueGTjresecj3eBcgTh4qV8xo+Qe68ZXbFB1VFpQUDJTnTa+jkZnBKkpqydIdY76iR7yQHXxR6N/5JEHc6DgaubJLLmVbAv+YoWmAUfgXnZs2BKkZswtkYF5uMBTMMaWWmtKVfC2TS0pqGTOnAoFarfmyImOgXM9o6djL0cKeS9oX+iCvTvSBI84WOqalhMNNTY7DCQSXoRBI0c6RomWbjbtrButGVT5s/w52Q1UlDylsUIvJzahphLPWudkUbvZinKQloWWrLXhpAMijqF/R6eRj9yK0UVu8umXVJNfs7D9irDk//5X/Nt/CvzTv+53/rKvQmbc8ZoDFrV2YmBJSSZRaUklxlcaGXkv4XEsaSxHdOLViBiX6Zh6xNmocqRnpvVEE1BKqvecOQ3UlNZtJagk0DNSSEXQI17hiVtN3CzraobxlpksTGoUZhR4RjEVQ+XXdOMe7wrq8JScbx6BABcWhGw6wZKKnoEDe85zR6XZOGxhZqLmMKN0C6Lcm7RHlSMdlXhLQXcFmgWViOY8dTAlkf5xv5UkogKFM75S0IqT7gDrbpwKmREz58w4V1HkOR1fMsstSxacODCQDDDQOZ7ASTrKDzrJB7GUx9sIPwEvorAQ27eNDKylYj915ArMKB5H7aO0LPKMB78IL4HIg4QKHoR0o0QGl/HZXDYejEXfvxaT5xg9wBQoI9HAJ414VzGTGnElXgI5RyDjXcPI3jpbHRjpWMslBcI11xzpJpTXkPYDLY2WdAwgUDMjY4i69VUFD04YBRNaGJaIn1kCPNadm6fbg0vIxFlUxUt47NIQxUmB93NStnyEXnoCFU4KlAOJSOXmqFohC2qCqIcOzj6f0jpqVQppcOqIJApKWg709LgPHGgqam7YUUxTRE1Nj90IT+xBkoFCIvSa6YnWwU6ULAQ8Sm53nAAAIABJREFUgV4zr/WWGcbNLKZ9aed6GilwKiym0dZNIGHPSCmBGRUHNafcGI+Mmlm6ikzBy/xvrO4fv74mygNAE6/0jl5GruUKp8JWt7yT2+kCCBbaQstJdzRa46WgYU7t15DMATeR7EN3jhk1Kpk5xbSnUXoZOHEk4GlyPWGonp6BvRyn0VUZ9DihdJmKBi8lRblFfEUpc4piS4xHKLYs5JzsMMywXFMUc5yviPNvIeO9yU/Ckn7+MaMIcfst5v01zeFHXLZKkAqap4yzT3EPrblm3Oxj6lBz6V8Qxp463tkJLzNDyOqnuHiiGO8socjZDo/+Hh9mECz0JU8iedVIpeYK7LWkpqCl44o9T9mQ0omcWzacE+mtiNDzjA1XHEhOec43Oc9rSgnTaFRQYfuwl3LFE6yb7mi5lxNHepY6N5RVEzUlQs1JTnbBEsjAjIowIa69jBSMhKngevHMaDhyYs+RhgXOlWgy3OwkRxIH6kf9YyTFIylZWMx5eIGmHu9nliEa5ka5QHDegqRz7idU3cbvGrsZPPy9y5Fa5oz5aDtFEq/0hpkUnDji1XGQI1Eyl/KUez0x1xlgF7/XZJ53+lNUbAdqXbcyjjec0hWZzDIZCXWUxJXc4LDzuOfA+eho844rbqwA5xF1NqFkMlfpJWtW9GLjey0bbnhn3RsVkY6KglLmpAm9r8T2gw6oKDmXOffcU1PQ01FrwXO3tUYApaRgZCARWcsZjZacdM/Ijkhi1EjJgrUsLWNVPFu34rf0OQFHMbEcsiiNzsjsmVMRSSx1RUfHuXxElMzb/NVUKJ3lxorjN+Upq7zk5I7M/4owl69FYROEO33L67zj3M/oaae9xUBipNQFg/RERmbMca7CJ0eiRxRqWXInrynVT5ukhIjdYQotWUx3lgN7RmO0kaclOMBejrT0HGk51zWNQE9LTcPAiZIGL5UhYaGmPM0I5RbqC3ZP/z1Wh5+h4z1SrunP/oChPiOHgrG5wI8dLrakYk7yC8ZyRixLwkf/AeX+m5y/LRDfoLNP6GefUJ8+N9G8QJ59iiw+Y+5rfPsVs9GMFIlH6+6aj6wAxgNusjUij2R9hXjT/qnbE7trHrobS+guWfotcXJAOfCWT+UFOQ/c6zVL3XBi4CgH9trxsT7hJ/KSN7rjhTgu3VP6fMBNf1a6osC6l5dyw4WuOcqRlo6VzqeuJdByIIntUj2OUiuCFMyZUaqnlhlHsYBro42UONwkwyqoqRAJLFiQdJjMAzKjjuzkyHMuGEjcck0dF/hyix92rOe/gx6/wLnAmBKak7HlMTWGaWRPOAKlmLa1dmve8ZoLLomSOZM5tVsYB9I1zHLNSKShYhTTKJ+kw6mQdCQROcoRBzTaWCcZj+Tx3hQgTvB+hqcgpT1jviGLMmKIouSCQMFAx5Fk3L14PYFfftp35kdWfy89Obe8Yk8Q2HABQK8H/OTvJipUWhB8TZtumDGnZ+BO7jnPa5JkNjLnSndcsubkOhZ5xonBFhyuYl1ckkOFp2dePKfMjnneU/dfMYzXqK9YuA2z8BRfzVBXULkV87jHpaN1kMMtRfBIdmhcMivP0faKZfGEoQhUs++imgj9DwFhefyclEYqmfFZ+ISYO5KOfMIz4ItfWlO+FoUN4KB3jORJdeAREXbcc8aSSitOHBnpWbClkAVH3hKnFrXSTEdPmAAEN7XzIjYGjAyWPM0wtdQlA9HGR80cpGUkgorxszTQiqWAjwwUVIYduADeLlRxBaF5ymH9TTbVGTmdrLAtPuM0f0IqClJR4scBSZkcAn4cyN7jcqavtqCOevevkXJNDDOSr4xrlU0SpL4hlRuyq6x4+cYWxUMxsba9JcL7ComFSXrE40JjJ7ILRtyUnbmlSCCruZQEP5vMBwMlgVrmKMKJE3MW+KlbOk6a3QUVX2pri2c34yQ20toI2GBDmuOaA5/qM45yopLAVpeMk0ytk44kxidstJoUBpZtAIngSpCWkN20bDfPDOtIEhUVJY5GG8Z8opB6WkvYSAW22L3RPS8kUpVbyuEaqc7Q45eTu8cDv89kZjn1ZB2JDJR4ky5NO9EdOy70kkTi3M2NxuMcpZsxy+8oZMY4dUtJbFiuqVCNFOLppKPQAifmTIPq9NxYt4XgbNKkoGByPTNkXdesWXFPomdkow0jIzUN55QM2k2mKR5R94hWv5MbLllRMqPNd3jnOdEZmKUVD+4mdmM3MvU4yesGGafu0K6VkcSKJQcMuPOupCmfItU5C81odQk6Mks9ZXaMIwS/Nv5bdc5s+S3TxvoZRTrip/AYVMxEIicqCqT6iNhFyvKMojojrn4bySPnzqMI6zZxTK8Q8ZRSEzEwZsv2V9aTr0VhU5QFK7buliCeQgsimTVLamqCm9FoR0/HqC0xJ15zwzkLKhpOurOlrVQc2dPLSO0CEIk60k2FzSGUlFQ6Q2SwUNpJmbCnI6pat0dmkJFKRyOXiscXK1vuh5kZN8aWNPsEcOTqguwb+tW36Zs1LkfcmCjGFhcHwKFRqO9/jIaaXCxxKZGlIs4/NflKHqm6N8Zud4UFMcd71BX2KaUWgOyXOL1DdESGayN3umpybs3mZ1YszU4p9micDCqdRylo9ZpCIymZnY13DeuJY4c4LOp3QMk0WrPh/Y7mKWsLqtZznMrUWb/fJW1ZkUQZGNi6J9O4Y9u/fsokTZoeMVEmjDRKS89AOelo3bQgcNN3Cds/CoFMJE/kWgARIahnyQxjeSUuZUNZbBBfUsw/Qf3CNIx+jkcZ4x1OA0cOLOUM72o0HaacSp1uchkRIerAKIlLeWaW48zRHFm4C0N60x2iDq/CnIYC4x/OZW2mk6gpRIoZ3plrGeLR8fbRbde5glq2hvKmYdp9WUBRiek1PcVkA1VZMI1bkMYDbhp1F6wp/ZxnsqRO9pl5ClbhOVU6UFQX1CwJdHgW1MkR/IptdCwkMWOFuCcUWfl4LFgWF2RRZqx4Fku8Jgq/hGKNhrkVrGJNdpZHCh5fbiDMyb4mFyty9QR1AXUlqgtcYRxDV6wnfbPCuDf9rpsxVmtysTKVBxjIognXPCHEWyMma6Yun0K8IpQXv7KmfC0KG8CCDUv32joqbdiyZM2KkgrvSxZ6wRv9c4J6dvmKPUc2zCik4o2+ZqULggSSZE701BIIKmQiLQO3emRJzUxmlBMvqpMWr8KMhg6jh5xcS6mBgZEr7nnKBVmyOUFk07b1nChTRT//FvPDS1LzjK55Sjt7RhhvqA4vYdzjxiMu1Lb+Fk91/wOk3JLKM2L7mrz6Dql+jk8dogNV+3o6Ebw5Lux/hC+vcfVT3HDzOHbk4XYSIydy7pFijUwianxtouyo5P6WPJE8RQqyJE6cWFMxphOddGzUtKA6Lc3DBAo4CkrNzMWAlgLPBVveTlkFCxpaTgwMLFjiJHCma+uDJLFhSdJAR0uJodmV1pxcR6m20D9xokbZc2AnB2pWDJoo1KEygQAYnSYpRiUgMaox860MWYlcq8lrHEIpBcEZEFHMPkF1MHlZmBOKJd34jkjPtbtBCFYU3BLBseeOV9yw0gtKAqHccpY6c5QoKnzYgitY+Y9BPEX/xuyOnKPELMCDq+3fpbeoJgq3QJpvWLc/cbtC/w7iHjcVrAKFeCTFe1xqSblF455F8RT1JYUGcNZRSrGEPDLIO5xCWVxQ54yfvWAhjtzfgHhqEqHYkGOLmz21opBNwdLoOUjBWV/aOeNKLMZamY/P8WGO5AjO0/RzcjoB5rybU4uUW8gJrS9BvGlG6wtUAvog6M895M7OUz8jh7X13+U5fpL5SXVp/65+Ygw58bjT59Bf0w5vuNcdT2RrawMSL/UVL+TbXHOgZPiV9eRrU9hMiziR/yj4iEl4KyU5R0KYc4wDW8lcc2BDgzPrBpPbYEaCDshiQulCwyN/6C6fcOJ4IhMqp4ksxoprtOZiWujeyh0lAVS45shzecZAb7bK8QiTK2vpz8iuYLH7GepK2tkzAFZ3P8Uf/gI9vTS5S/PEPjjfoMMduAqvMF793zQaGTb/jqkO1IwNU1ji1CyF8uk1btzjxZksKPWIRtJwZ7sK8aTxzrzvq43JgTQhD2lBqSfniHPlxGOKRjrWOb20ZgmVDRU1NK1jLXNKsfzKjhMjkUF6HgwDVZRrbllNhaSXjhXW9cTU0mhtp2BujZUuLY0sqXJlLHgyQTIjkZ4BzZGjtLSYjU9HxEmJyGTySeIgJ0otqKbQkZGJd4jYrkwVc4fpSCi37HmRBkgTkjnckFJLSB24wpA6Tpzo2esNjZbUYcsQ79hzwxt2fEdNblbXH/GsK2iHN8yrT5FyOs6+MTTUVyZt8jXVw+fkSnJ5znp4ase92BDLLclXKA6Xe3x1iYsH05y60rSkww3OVxR5ZBh3pNxSFeeWw5nayQFEzDKrv6KSpxA7ZPEJOtyhy2+BQihX7zMy1GJqcBWkg/1MFGis6IiAbyYDyYz6hlAsTd43HqxzdQWSC9J4tDzQPFLU5zjf4LS3dYDoVLiGiaIT8f2VyctyTy42pOYZ5ESszvHxiEsdKoIfd8T6I1wekNTj7v6UeHpFm97wyr3mwv+7jHpCkvI5X/J02PBzvmTV+19ZT742hS0zTjyyGTJhbQ5hLztDT5Ky1AqvRgB1IhTScJADtVYUUpI1U1KynMTxpgH1zLVhTo2tY2sGSRw4ISoENZpIQWWCYAPfzTmCJaK2O0qpMySufUOQCmme2odz+pK4/A5hPFF0L3HjHYz3UyHJSDQmuPhqGkF25PFgF23/Dnf8Gam+JLSvodwCgg47iB0PaUgy3IEEJJhjqfh6kmAZuUF8A5MNDA/cr0m76DQh3jhhXj1Lf4loZaHM/gyS0GtPK5G121JrQcrRjDtRTgxsOaPF6IilFnhMiVlMdISkI4GGB3un4EriNMY/OO7ecjTrbSItyqCJLQszIVAjdlZ+RqFHJBu9ZcB4T3O1LFLjdOk0pk5WTZMr7nsX3cSCetJwdgztzymyMGpPTrdUauaHhZvbeSFrHCU5DwQ/Z57XPNUB5ysWcgFkpFzj4920/zRrIuIRE666KSTYmahd/KPzh4aZfR7ipnHNyNTuwVU5D2Z2IGK602FnP1NQJ2YHlUfAuJDGWxxx5TSauwoN2OtwpRU/td9FubHXO+ysyOkBHe8BIcd7xNWkeE+fbqhzZJx8/6riAnEV4/AOTS09vXVuOTJwImqkIiCxNnPJ1mzbo/ZkX+KlxLsZmiMx3pG0x+WMHw9onBD6dmWbvhxtvxnvoL+xiSsd6Ma37PQd7/I10WWu9C0nDlxoQZpQ8BLP5+lv4Mf2/8eXIMTcg4OtLnEEKilI2nPNFZe6xaUTW+aU05LV46hlwZfyOWd5RSUzBk5UWnGG2dYU2EHfsuJWTgQ8FTOuZccNO850SYF/5CENMuCnQlcSuGBtY4MGYjxQuhLtbyhlhlt8RjHukPsfkte/Qzncs7j+Y9P59ddWfFDycA+iFsjhAqm7sgg0IuPhC8rxRP/JPyLc/gkUW3Pl6K7sbqYRHQeEN7jFp49eYi7MLFFeleCnOzMPvnCTDNyXSDEHHXGhIaeOQgNn5afE1KLphk34mD7fcJITewaehG9R5oF9/srQOjJ76Zix5q2+Awx4QWGQjrmuqFSJ9FSYyiNQUMmae31NSWkSL3G8kbvJyU1oJzjnI54QcCwR1hqY+Q21HiAfiCSO0uFzYMMSwGTRkggaps82o2oifHvuQJbEVhfmaCIHTqcvmcmWARvziklNUbsN27Rn454YATgfqKqP2EShzgHvG7bOFtyufkLo3llxia3th/KUQl6srLPx037TldbBAVqsHrlpLg8GHIjDjbf2ecUOyb3ZIA23aPfO0ODQkIKpGXLucTmZ+YGM6LiHbKHGKgHx00AeGiQerLCN93aT1Azd22k1cST3t6gz7WgIC/rxiju55YwTB+7smikjvjqnPf6ErCO3siOIw6s3BF06LnVDMQZGeqrYknXkmG9JEmlY0sjCVA56mIJcAnNZg3jGfLQMi7AGcaTxjlZ3VMwJxZYx3rLnji//P/beJFayLM3z+n3nTnZtfPYGf+/5EB4ekZGZEVFDZlZmFtVIrRZItMQChIRQr9giBDtW7Nj0DsQSCSQWrBAbJNQSi2q6W1U0XV2qaqpyqsyIyPAYfHjzs/naHc75WJxz7Zm7P4+Iyky1AsgTeuFm167d2c75n+/7f/8/Zzy2VzyId3jiPqUWy1gHNDimMqGjMT9vnr+2T/ladGzgS0ByUkqpmOsVO+Skkvk4BymOxitGaE0uCQrU6qWO2uZLgzzBVnE0ohgNSvSCL28JFBI/MYrRkFGrqVnoKsRZfFFvP1BNJzrjDnlQU1hiTIZGGaY8x5d3OaLFxzTrc8+RchYoKdxsEwBPmpUviLZrTAiEF6yI3YAm7qLJABd1MHaNJH20WaFqqViTS/BJCK7umBQkQXQN6IaTJXE3CPyFsjOJN65V6rzyhj+Glf+e88TWDj1WNKAW60oqamJtNmU26plhQGt6q9RYurjg9h3T6DpQaRyJ1ih4eW51iBh6mlGyJlVfU+jL0HzJj99mzcpNiFRxGCpKSm18OQ2OhIRSPJvK4Mm7Fk9MbuXf/Z/SNV2cq8HFVFSklKTSwxnBaklFBbr0KC/KPYqqK3wH0cPYBXO9YuDGlM2arOn50IUtvE+FNkjwy6jdCtOUXnCyKZCog62u/JQzHoI2G08CxFeuRLagEYfagpQUXEFdnVO5CWutqKvYyz+p49pdMqpTjHU4B2rX6PoCCdltQbABiRFIzWlTUa8+I8IwaZ6S64DcZazdjFg7LJiTK1T4mGqjNUsp6GnHmyXVjkIKYhU65Ex1TpcUryfTyoFaSirQFZbaU10QLEtKtQjKmgJHQ4wjow5PS8Wahq6LWUgBrENZnhC5HKsNlTQsXIUg1GpZu4bMxKyDtJnFsdZmU6VyW/vadGxLWbIjXWYs+dhd8r7c5Vge0tWcTHosdUJBiTOWMV1fF+gWdAiKr6I0NERETFmCWAxCLBEdTYnwxbgrXdBIQZ+cDjkqwloKGjWc6yV7DDiTS0QNe7KDU3jMcw7l2COg9QVxMsLGQ5KrP/dkS7WkZ3/Kev0Ekz9EXYVrCmbOJ0P6OvSVAK7AakUnPSTSmok+odsMKPI98vyYJt0hLZ5g8kPK1TOcViyZkkaH/kaZ2Mf60jHEOawXHiHWM8D4rFTbTOK5bEkPVy9wje/MbLOkqj3B05fnCDtywFKXOFtSuwVLWZEGDpkJ07sqyNJ4AnTDkpIdHbKUBXscULoZhRQgkLkMUNJ4hGm8ccgdGfJYV3SJONQ9X7oknkVfY2mkZmmX9N2AWgxL1iwCKXOHAR3tUbNiLQ0RKUtmFBTsyx0iUipdsZQFlVG60R6FPSVysJAVMQk78X1M1GGx/pRCltTOy/DE2S4qhjgoIEedA9JmyWfup+QaM9Nz9vCGzK689s8altj0UG1Y6DmR+ioBIylJPKJsLnFakWfHqK2pmylN0Jnzbk9dCgpqLdiJ72EkZlZ9ztwsOGvmTJuK79uH1FJxaj/mUVHQ0ZySFSDk9cqHIUxKFHUpqzPAT3OXzBjJEYvlT+hIj4/lI44YcTd6l7k9paNdzs0ZO3aFFUdXc2oKzpnSo8O6uWZuZyzFx1tH7PFLd8KhMSQhodOIpVFPaPc1vp5H2CVj6eY+XCCGUvy0NSKhEwa2WhrmlOzZil/KUw9SBHoUpDZ4XLDmwnrJo8LVXNQrHmZj5rIgDcBl4goS8/+CGFtbWJtITGeDppRWGa0lACh+SnIjE+3RXqpeutmpJ+cm6ot+2qJ5g/HER/X0Di9m6KcxkRqMKjlZiN5EoVTYP4ypxCG4apC4hyQjb4DcBOs+u9qgpMrOMNqWfUFKThz1QCRkCNNACm3IZUCL+OpsjKCIOlzcxSQ9KuflippmRYLzQeY2gByqCWidgtSTTSXKQnmODfEaj+gkTMFULZFkENjjUdTBuZJIDRUFDTUxreadn5LPmPtrIymiQkoSEjZemmZFQYfMc7HUy7hb8XQSECoKRIUeGV1yDMKKilxTj//Ex/8EoZaGmoaMhB6dUIMayLTg40/cFNb74nGP+YyKV1dVRyQpxnTIdYB1ziPXuENcD3xZmq1YsfIipeK8TykGY9dYV3skpBWJdLFuTYGPSXrem/PKw4TKB1YMEBIVIi1pnalqt8SohPiVFwPF33EqGkqtcFrTlqQZFXJJscY/46r4QnMarpnTCVHVmoqKhq4qoknQ2KgZ4wc2PxDVpGrJSVlL7WNdanzMjBuzcUNEGSoSImIWgcKTYolJQJU+HQqtcIFfqiiVVCCKUy8fX6q/ZzY8E1EgZacER69wLiUNpdbUgX7VavVFeEJ+Tc3MrYkQX4/s0z+hUM2LZJRYMonpSMrrfEW/WDj8X1vToK7qIfiu6dLVLupsuAkNqfhCeFCKAKH9FNUxlQWFevTS4HXVBgwZ6giDIOovspUaEaWrXuBuLQWWiky9sPQdRqSk9Ei9dhQrGikYmhxjOohExN1jzOBNbNTBrk5BhLg8836XRMzKT6ibOa1qxUD2ybIjRAxXck5kMpxbU7sl++aBv7FqWey8FySVG2x2SNy9x8qUrCgoylOcq7HJCM32vMNSPfcdXOSPa+M2bjIfxG7WaDVHmwVazYjiHibu41xFFu+QklPpijjbw5NsY2Z6xoplyGx6GceBZHzKEw50h8wMMBj6dOnTCdUgllM5I4uG9LVPRzNiySilorFzBMNUzzEIx+xyhwMiIs6Y4jDUga/V0U4gYq9YyooRPe7JmI746aSlpnWLd+rrUDuaekqrVjTURETeACRwrtJ0j4P4IaWpibpHmO498vwB4+wb9GTM3Cxp1heUy89wtvCOX+sLGudLpAqdM4juUFbnnHFKlI4wEtNQc6Kfc8YzHJbP5Iy5zKlYUTVTnNY4LIv6lMb5OlgrBDUKP72fa8GEBZVbebPr8CO/Y4Y8SHdYyRoHrLVhRckH+rlXrBHHkhnPeMraTbF2xUwm/FKeYEL5l9WgSkLJHUZMdEXZXJGQcGUmeEs7H4aISSmkZFf6pHT4nDM62mXHDci1h2K5JztcugUTVhgEJ46ZzAGv7nHlFly7le/gXM1Kq1DKmDOiTx6msZVUTFky1YKlWZJIRCoRuY/GMjVTzs01n9prMhOzG3dJxAebOuI7SaeOiSsYRTnfTo5e26N8TTo2giR3FoLArXxRTbkZn7xhiKjQ0YwssNbbwuvWoHbBmrX6WE8VYj4mjB6ivvhbRUjpeFa4BhQYkEKrBJqJp1qug4JBE6SNVAx1uofboCeDBEkbb+4bDD4CI1yxmx9kookvYI9upIUarYjsGmcibNQJpi3ea9JsRlZBVAOvyHuYatTxcZsQkPYorgatUVpzZc+sJ2wDEY/cjDduMQGZqVovXaMRJTUzCgwxa+qNpE3bahpi0lBVecNktyGu1hA8Q9WPtIpHydFmNPfZwY4kgB/tg23LZltxwAy6le30Aj54xV9ad1hHSY2RdFM2ZLEeHYn4yougstHGt1AfSxTxsj2+BRFzScJ0DzJyjxTVx18z0qB8HG+OM1IfP+1pJ8jPe9pRa7xdin/+Yo0CMhGiuO8VYeI9+tGerwAxKUnUo2MGJOKfy4QYCVM6nwn2MlQES8lOEFms1VfGDOihOEw4p5bebLFkWxOzlvg8c+uQafbLPGIOnhCBQrWSwl9TcURiwmzGkJKSBGJ2q5CsCkYNuWR41bWb+yTtExjWHZCTakKqsZ+lEZOo55YmGpOEe9UJfNNMYmr1BjaNuiCFhRcgeE372nRsVzKjZ3ZpxNITr3q7khnnTLiWK5ZMcFhiYo50n325Fx6qHgfugJiIlax5rKec6JRSSy5lQiEVkSQM6JESM5cVzkTsyD5DHZLRCdm/JTOzYGmWGCPcMQNSzThhQqElS3cJUYaThOn+D6jTIXH3yHcUqxPAYExC3+yRpfuISXzhsStCcB+GOiROx0S5F2EUE7PUazrLZ9R5Tpnf8coP6tPrscZUan1np5aomePiITY7QDtHOFuhzQqJOhiJPYu7mnu+UzLwyqTFGW15lYghSUaYqEMUd8lMHw2We5mvyeCCKT9zT0mlxxkTUq9mFh5ey0wKejKmr136jEnF/1TWborDsZQVra6WEIUpkNAzYwqpWbEA8VUMKg3nMsHiFWPb0EJPe4zYxUpEEzLgDTWJCCO6WPHcukLWXEYzsnjHlweJo5QwvZMYSYeIWnKXB9d1xTVL1BbEyYCBdgEw4p2S4mTIhfsMRTnkLmtT0tgVM5mxp7tovcLEPT94qSEno0ufRxzSpesRIA2J5DTGcSkz1lL5ODEdYlKy7iPSve/zYPiHfKP7A/qdN0nTXUadR9zJvs1OdMxQB/S1D0bpmxRnGnrGp9EiIgbscFe9MPaCa3Y54Fs8wmkdivd9pxCTsmTNgY42U8+R65NqzN80J6TqaSl97ZNrh1jS4IEQMTFznshzrEBJTS9K6EpKn5wddhmqp0IlmmyYCqlm3DO7vGH26TvvO1JLFToZR6K+S/ym3GesQ/YYkGrMjg4ZsgMoI3oMowxVONIdHMpB0mOqBbEmTG3JwlZECGe8Xt3ja9OxJfjRtcYSqfFlLfhC9iiI2kkYK2uaTRzDYhGTEJkMi5KIxxObUV1dkL+BlgflvQhuXJTaTF/bYvUjrgAZCZm2KgKCxl1sHGPcTVmPt3dzHqVJ7NETLa9K/VQxyLGgFnUlJkwhY5NjtMFYi6jzBi7Bn7Ed5Y1EHnkFgm5r9ee35Y/DYXEtpQBfHO3UuzWo1lhXbpzC1dV+uqQ1ztWhhlZChtKjolaCR0PHsqbyVzs4mG/ugfo7UQYk5uWdgqpYUNVt7fhMmIapOtr/CtfggiyZbv3nM5eQabK5/5X6XKioYK7LAAAgAElEQVRH4dHN2sEv40bmKHg+SOQzf8kQVYutZxv6RUvUFROF++Nfe+5jHJ4Db5fYloy16Lt1yIrxQp01vrY3IsKIl1EqtSbWGFGlFm92YkwGcRdnclzcQ5MBxD007vnByCRY/G9AxPgaUo1QZaOKEUniS6ok8YOj+lpaMFTihQGc2vD8ymbq6C0Fzea6jehiJN0884pShFgbCBb1Yo4B7UcYYm2veevy7qkmPsd/I0DhK28banXUajezp/ZZal3f25hbFTLaLXJP8FNUX8vtOat9etRSE0v7q2hx8+3ta9OxjV2fRksmuqCnXc7wXJ83eUBOh1UofDUYLs0VTfihLWRB1Dmgn73BVByHjDg0Q2pTstA1KyqmMsFLS/vi98ZVlCyppUIFVrKmpNkghoHrUaslxnCXXR62thES04zfpxiPyMqLTdE56Rhrl0RJnzgbg8S4Zk0iGQ0VxB2i1JctuaagXj6h072PSfqMOo9Iy0uy5YSoKcCuqbJ9nEk8t4eYOB5Qrz7DFk8x9cQTPO3Ka+lXE0QttSsoy1O0niN2Da6i0hVzrinra1bFE5ryEg0mvFV9zdJesq7OODEXRCQkpkuFZRx1WDLhQAY00tCnw+dyztrNWVJhtWYqCxpdh4e24bk5R3GkmuC0CtPCkoqSjA7OVnTUT2FK1qypWEnJL9fXFI0ftCrx036njnPOiFQ51kN69JlScsKEucxZsaZLH0VpXEXTzLGiTM2CRryunEQ5TdzlVJ8xHP8R2ixZXP1L1JZeLDIb02dMFPdJkiFxZxeiDgfcI4n6IMpIxyz0miRcm8YtcU3Bijkj7TNkH8VxaaYYkzHUIR0zYCFznnHBjo6I1HIpl5SRknUfwOBdyv7b1KPfxY6/gxu9D6P3kP5DpLPPKmq4NHMi6RATMQqFTvsMUBG60R5JMiJL9+lGe8REFMwwJuGpeUYaj1jjkSMCHTJf92z6pNKhK/66/Z34XXrxvu+s8R3Kh3zMPXaJMCy0ZKoFVn2ibkSXHe1TYXFiyOiyq2OswCBKGZkOc7Nkahacy5QTmXClSy50wUIKTsw1lSnpSkIpaxRYsuaJu+aMq5CM8YPAHTPgOB5wyZxCaxKJ+K55nzOuGUUZeeS15tIvyH1+bTq237bftt+237bfVPvSjk1E/kcRORORn2wt+69E5KmI/FX4+3e3PvsvReQjEfmFiPz9r3ogXk7GB8xrrCd9Emoe0YCmXJgCQa11CNSaTUD8Jn3cBp3ZgqsB6AaFUac++EyYKvkAr2xoB61Pws3xCWpinCSIbRC79lMgVR+0x6tVaLACFGmD52G/rtlsy/uBRoEB4DXFjPqpKGEKBT4QHhN54ix+Cqm2QO0qUDm8vZ8L5Nu2Rs/ZAnWevNsG3m0YmTdnE4qxRWJa/wB/XdrJum6mWpFGm3IoT1Wob4Lh+CB8S+SVkMQxm8hKO9F3m+spIZxs1NAxMZG02vjeerH1Q/AJmfaIg21foHu4rdCEP282ZOyGOpRa4TPnxlNgjMT+OoV7dPP43yjNtm2TrAqJLO8K5qkUJgTX26lvhAnJHu/NcEPq8M+AIyh8hGSPBItFcU1IZjTByq7yx0lLaWnTYyFxQBCVVF+K1F7T9hhj9YoZPinEZnlES1cCwhb9sTlkc7VbM2mhDmGFOHBEG6yvHgvPs6MN47TVLmYjniDaJlXMZrKoGtgu6iXE6/As3hTcyYZeXYVEVhJ0UuJ24ikxmXSIJSInVHZs/T5fbr+qEzzAf6uq//X2AhF5D/gHwPvAXeAfi8g3VdXyJS3TjKVMGNHlU3PKu+4Rn5mngdhXMaDLtcy5ZsWInOd8zgG7dLWD6T6EZkledRhozlSnNFLRMb5zjDTCaU0sSqPKTFc48bZh+4wYao8R/Y1Bc0PNgJxGrHdKwmAkpek+YNl/SO/yjPTqz3HV1NePLj8jTvpIOsQVF16bzfioiLNTsBW2nm0enjlXdDo/hOVzyHaQekqnOMc4i8YDys6IDLiUM+6wR9NMmLBgb52SLJ8gJg2GIFPK+orErnChsL8uzqmXn3gaimRkmrFgycKseVPGgJdhSsyQytbk2SF3VnOWLIjtmgUlIilzs+It3uNT/Tl3dI8OGZ+bE/qkfKC/5C09whBzyD1GOuNULgCvR3bJOfvcwdIwkwWJJPScd//0mmoJVmYMXZ8/yO/Rc75WtCtjutrHZ0vb0ENEQ0WC0AvF+UtZEQfRRCeWUtZkmrNDn5qGM/cJd/A6fYfRI9ajd+lMfkQ/u89q/QQq9fJYcc8ni6OeL15PE38/1XLOM/bYp8eAKy5CZ2Ep7YScHn/NBxyyYMSAA7eHZU1uhjSu8DEiYmLpYHDMXEnqJozqCcn6lMQWGy6i2LWvMilOKZoL6vqUvibULOhJTqbdwP2LqbRgYp8xaIZUlCSSspaSXd3H2hX3uYsayzC5y6W9IiKjoOShvOOfl7ImigfsVr5Cp7ErEtMnxVNEPP0j5mM+RcVyKENqXfFUr3iTQx9G0Ia5XmK0Tx7tAnM6znAgMWdMiFzKrnQxMmce9BK9+YoCER/qCbsy4D0ZMNIBU1PQlZQznXLWLLBO+cP4Lbo6YCrXuNgPQGl+zLfrPh/X/4oH0SN+wk+DaMbt7UsRm6r+CfClhiyh/fvA/6yqpao+Bj4CfvhVvujkBpmF5DuhMCiMBC0VIKSWb8Z1vKmsD2b6UQXQkIpWP2o1WJxqiNK1lsg3vX6LLFqCYRt8DakGPzJqg6jDNOsNpQAJpEVtt+YNblu01mIKGwQGlVC07exmFFe1fvQGT1NQ3aDBdv+tMXCF50i1FA4/Km+PXmG5eIqDhPM1KjRtac8mBOwD/Nth2KQlCmi0OdZ2q5HeEC23m5fvjkOCx/tCtojK4VFAE5Cx3SR9XEDc7fa3/2vP+OXlLal081TQUko2CEJlgws1mFvfQIb22G/O1wtvBmwf1HitNptkkhCFY27Jsh6tJCF9cCPceHMHPJL1mL/Z3Cs2iRvrChq7xNk1zq2DoUyzIXm3W2rpKzfH4u9lm5zSLRTVtiYguTZJc9M0PKMvLArXwD9rbWA/wnjUFSggrZsYm3f+fOuAatv7KVsb9UOSCXlc/61tlL11VNjwDFq9SeG16TyPksN2BeLgVyFIMNy+vf06lQf/uYj8x3jP0P9CVa+Be8Cfba3zJCx7pb1smHwp1/TI2eOAGSti6bDSilgyOjR+iqKGB+zzlCve0gfk0qPRNWZ9gXTv82b0Dk1zyQXX5HQYao9KKs5kwqd6ybHucWTGqPgLZmXJSktyCIFnHyht1GHUsM8QK5YpcwYKo9UTkv43GJ38MWrXXjAvP0QXJegcLacsq+f0swebbGVXdqirCWd8xphd1vU5OT109piiOiF3FWIyss4nlN1HNMkOaTmnWT3FuYpSYWYWLCiZ2Q+YuZI33DH34i6RScizI1buGtcUnrqiBUmUkyQjQEiiPh27InJXPNZf8mbjb0eE55e5akosGZYZHTLel3sUlBzrMVf6hE5QIC6l5L7e4RN5zqld8KapqViTqONCrngk3+YX0U/4tvkuT9wpiU7Zk0NWUjF2Q37Jc97hDZ7JKfs65NTOiSRipF1EDCsKcIZGGqzUXLGgx4BIDFWQCl1SkpOyp7t0tMuaJZEIS/XyOka8kOjaWNKoR339Y7Ld76DWT8sdyrm54FF87KeEJmWy/iV7gz+ApEtdnPBLfkZOypKSXSx5esTT+m841prn0QmFVtxzB7zHI2JynFSoKldyQUoPh5LJgCOpiVzDx5wGMmzDonpKb1JxygVzd86B7hLj7fEyTYlISU2XKdcMNGbNmiszoaMZu7pH3xyggStX6wxFydST1lue4if6AQ/q+wylx4wLL/IANNU1jRbEOsBIRKNrQIicZSZX9BjwQA+Yypz7ekBFxUB8If2hKTxpWvcY0afjEuay4FKf0SHBiHClS3I8NcVpwoEbsyPeThHgKppxxZyRdkhbfidCqTUnzDnQIZ8Wn3OY9nDiuJILKrWsApeSoK7zaOfvoyYjvvwR11q/tnP6VZMH/x3wNvAdvPv7f/O33YCq/veq+n1V/f6G1oDZzOWBTYyljd+YgE5aRAcBaWkTRqOWZsHWWrIxg90eK9o4WovwWkTikaFuUtLtCNqSNb3WmR9dW6qBV5lwYSS9uaRuewauhKmobKakN9/3hFzRlvJhN/v0I+GNNaxIizc2gQuUdoTbRPQC2vOxre1QxM16ryLSbVSEvoho23/bkVglxNPEbUb0FhG0DuFs7t0Nstgu57mJvoWKgs3+b2Kl7c15YWzWG8zl1Nu3bH94c0/DNXJVoEAEakwbGw0IQkOs1fsstFu5uZptfFfCLKBFisgNOrxBkO13PNppr9fmfNq1dVNI9cJ9QdtiPH8Mbuv3sLmmL+zxJgp5Q7C9QXESYnNOb5DqDR7mBq3CpqheuIk9tnsX9XEur5VnaMUdos1/8aYs0sdHjaekSIxIEqKnMbHEIcbXxg99VNULhEYk0n5mMOK3DNzERvF0oi8qgIdfEbGp6mn7WkT+B+AfhbdPgQdbq94Py76wCTDSAT0ZUFMy0l4g1WZEktFRZSoT7stDPuMxAiTSp7QzzswF6fKKo2yHNN1h0nxK7JSBDumZIZUuyVlxxwhj10VUqIIR7AN3jMNxxoSFtbwnD1my4BM54cquGEY9Rox4KudMtWRv8jd0s0Oqyx95s9p0F20KbDWjcjN62T799MgHglW54Cn7chfVhpycTnJAWykgJmYhc2zZ0E/vEc0+JLMFRDlpAZf2nFOmrKj4TvRdVvYzVupdszskuGbtO+FQ+HwtZ+yxT197lHaGsxUNPsaRStd7BUjEY/mMPR3S0Q4Dc8DazXkmzwJ3yicGUB+knssKFFIpWAVp7zf0mN14wCkT3tExP+IDfle/wcKesZQS60recHf5uXzCntz15FBpGJOzZsmx7vFLnlNLzadccCBrumTkmnEuF2SkDLXPMfu0nCs/oDm884GQ44m1FsdzJqwbx+9GPUqpEI04dHdxWlLqkqyZET37R0zKj1maFSUVs/pz+uYAqwU9s0+x+BCIOJOnDOlxzWKD7nrNHm/ILlM9oUcnxBu9S1YUd5nVF4ySY7JmQWQyCp3TaM04/wbarHm78rGxbryHcb7THZDT0R0GyR1i6XBZf8ZTc0afEXf1GKOOQlbUqkwoOGIfIaJw12TSRzD02cVSkouvQIhMhsQ5TfMxielTcAoKRzxAiLnST7iTfhPBMeWKpRTs6y4ds4txE4xEDM0hxoonyuspickxEtG3C7p06Y6/yzDuU01+Cs2ae1EWdAoT3gKaZkWr/xGlI9LOkRdjMAm79RKtPIm7Li+Ioy7DKGdcH1C7BY3U/Ee9H6DAMD7G2oIo6vLAlfzY/Yh1+RxDSrb/h3D9V+zqkPPgS3Jb+5UQm4gcb739D4A2Y/q/Af9ARDIReYR3gv/zL9ue0qKzMDLJTUxkG4VAOy7djCg3MbWATjaj94uRJ/QGEdzk0m7eb48A24gQfHnQJiqn2/t44QwAn9UUka3Rb2tkkRsk2h79BnuobgitLYpr0cGLY/IWktk64ptRvUVw+lIMoo0jbecZXz0N3UJDN2jLvLB6i6BvymU0lLncIFEJ29vcn829UrYwzyvHffP6xXe8cCW2M4/b92pre9oiNvcCcpav8MjLJjYZ+fKzgDA8+Trxwo3hT0yCJ/e2/8ab+KZHdSbEYT0JuF0HE2/e++2k3nPBeDK3BLKvR36Rj73iM+/iXVzCFWz9biXEVP26qLyIxtp7o8rNXGX7O9HmWP0zHIfXESJJOFbDhmsQZiciJnzPbIjo7Z9KYApsrkO73kuvCQITROF9uKvhPF9kKATP2jbe+Jr2qzrB/z0R+Q7+5/UJ8J+Ei/ZTEflfgJ8BDfCffZWMKCgD9hDxtWZPOKGvEwbkLLjCIDzjij15g1wz7vEAnM8K7bsxJ+aC9eTHNM5Sswz9h2K1pGRFJTWJxjzTS3J6HMmQQlYQlA72dcCuOEpWWBp2pMtxNCalQ9eMeNN67S9sCed/ykwv6DJAFaKkz2z9S/rREbPFzxmOf4iunmPyA44K/0g1zYIh+0TZHq48R+IBguMgeRuJOjTllfcmKJ6S9N7AlddIs+Zd3uDMXJJKSlcyjnWHke74KZB6h60o7jLQAUbXxAolPuN7aieccc375iGdqEMadYjqS0bkxOpd41UclRY444jUT48+5ZLv8AiD4ViP+Mh8ym70iEv7f5OTU1Cwo7s84ZI/46e8yR6n5ox/vnrMv5d9n1InTGVCXzKcVvS1z6fmKftuxEj2eWaect/tkoVpx8h5t/ErmdPg9dVO5JKey4NA6IxC1ox1yI72KaUM1og975pEwk6cYTQGIvY5xGpBYy2P9XPemhn+mp/zPfkWc13yiEdcmjMGEhFph8atiCTDYYmIuGbBe9EPfHWIyZGDP+Tu/CO0vEL2fp+q/w4ANupRRx125z+n7hwzsl40ctwskOoKTUaweMyI+xD3cZ0DXDzEmYyeCANboBjUROwh7EmMaRZIPaPTzPxPq7zmzfAjI5TOkfS9IKVrcPWSePweWl6h5RVm9C1+pxijJuFwuiaNh5j8iHrxCUf9H9AUJ4BwJ/0WdXVFku1iRu9wYN8OJi1DxloituIgymhS70ewD6hE2LgP1RVJ74F3ro86RHEP4i6o89JPEpSNTYoGpRk/oHqNttg1xG2iRCJSV5I23lZSJYJqjro1UbOGzh5pec23Vo84N6fck3egnvLT4p/xLXmPP+KIf/qaCeFv1Ak+rP8PgX/4Zdu9vYWi6ZfQxIvvbxDHTdbnxfU9UNnKUenW57cClRcRWLv+S1GnzZdFthHT9gj28r+37TB8dluC6hWEdfOpbK0nL63z6inpS8u1Dcfd2loE9vKVfvXKS0DTL61xy7m0Gd0tTOr3oP5b7esXzuDmlt1845Zj1pfu2AZ9bMXHto/tRYTc8qICitCArgOSQdrYmXkBdam0XK+t5w9oEYluZhwBRUmLpDRsbzsuF95vIartx+nm7snW9bjBuJtn65Xt3vK03TJLeH10qp0lyS1L21ebHOXLRx7g/taMqX3oNCBF2crGb9Yh+H34729FiWnnBdtxXm2fZV793W63r4Uem6Jc6nP25T5nPOGeO8IG5dRrmfGAhzQ8o3YrdnREHHlZ6EoXOBxj1ycWSEyfjit5zjVTWfFAjxkwosZxKVf0o5Shep5apr68u2DNhfGyyJmm9LXLjg454ZInzTN+N6mYmAWHHJLkR9SrZ+x1vuUL4usFMnibcZyDLRjKXbT/DtJ9iCw/IercQe2aGEfUf+RNMbrHaLoH5SlReeWlwrXB4eNyifjOfRgfoa7hwIJWUw7oe9VYqYjJMCbDRB3qZkZMzMgc0tgilCVV7JqcHfE+pVfNExJietKnJzuUOvfi3FqzkCVH7g5Ls2Tf3MNqE4yMcywVsRicXbPvxhgMJ1wjCN/Qu3wgT7nPQ055wmHWZ2KuuWe+wZ8s/5KDLGdpSt6RN9nTYSjTuWIneF5+rOccyl16gRtlpWFAD4OhQ80qlMSttQFtjfUaYs1ZmiXXTKnVcV8PseJIyehqw4fmQ9Y4fp/3ec+8x8yesCdeAus4ekR6+He5e/0TZPg2RD3S1ado9x6a7HKvPOfe/CMYvUs1+n2s1jTxALv/b2BcRdnZATE0kS+oN84y37nvhSrrkqipvDmJrX1HOf4DRBvipsCZmCbpYaOUuPYKIjbuENfFpjfqFOeYqIckY1zcRVxDFAxfRCtUQk1yOgJbYpIdbLZLzIeQjdHswE8HVel055juMYqQZHsQDzDmylMlREiSAagnmmM60Cy83LjJ0XSAuALjSrBrNM4RuyZdPoby0hPFm7UHIUk/yOCzNQ31PqraFGCL4NsgIDHOromy8cacSEUo1+dk+RGqjrI44YJnXDPnzfUb/IgPuGd2qNQyc8+xp/8rlyy54imFlK/tU77+JVWhU5at1y9//EU9t+oLK7640RfaLQhrS67n9lHOj9S6lR3bvN+MzGFv8uJnNyP+7dt98fU2rnnpSGRrJH/lHIRXt/VF+7rl0xbtvrTpV7Hd9iovbXODmF9/xi8fp7z2HG7Z1AsI8vXbfHlb24+EbpAaL9z31+1XNhD4NQfyBRyr21Z/OTaMvrzs5fVv9vOaI9hkqTf/bi1/5TtbaOmVv9fA/duj2e0+/ett7tw27oJtbLaNwrf+f8sl1hdef8Ev6Is+/NfVEon0Px3+kFhSFjKnrwME4cd8zHfk2xjgknOGOmQiE47itynqSyIMH8szRuRYLHeiN/jAPibDcqh7pEHgLiLFYZnKlEuZYhD2dURXu0REVFJTsGKgQ9KoTxqPcXYNYijrSyrW9OIj0sEjyukvSLvHEA9w43d5/If/IXf/+s/JZz+m7j7k+Rt/h2rcJVrVxEVJb3ZJpzhn1TuiSXKaJMFmKWIdg6tTRld/gXv2x8TZEG1K2P0upp74GI3JoJl5nf1QfqPpGB9cdqik2GQHTIyprjDlBa44Q+sFJj9AsjHYNXb1lHp9QZrsUOuaZX3KwBygKHFnH1d5r8jKLYglZ8El4+QtyvoMQ4IxCXG6S1We8ZiPuO987qihpmv2qNyMmHzTZ1S6omOGfCQfsOdGQX664omc80jeInKeDmG9KDiWmoQOkUSsWdGJ90iDEc/aLSjtjLWUSNThDscUbspEz3B4VzKvX+bLbFb4DF4W7ZD136ScfUSpK3rJMXL338YlO0TVNaa+RtVh82OadJ8qHWNaJyiJiYKPZrp+zqr/Nut8l7y4pLN6go0HRM0c0yxYjN4ltiVRUyBaYSPvMWGaBTbqYdSSlCcYW+KirvfKWJ+iJsWlY+Ly0k8/bUm0+MRLvpvgzRnl3qGsWeCTDBk0QZaqKaD3BlRX1Nc/I+neQeM+WpwicR9XTz16Mxnz1Yfk0a7nCzYXxCQYSUjTPVblUwqWXJkph+4OGTlJ1OfaPSNSIWdIEvWwrqTWgigo4n7OE1IidtnlKedcMeFQR6xpUIEOMZXU7OmQXPMwqbSsaTg3l/TIKKWh0JpLu6RnUrrideieuym5JLyhB/yT9S/YS7v8PfM7XMk1f1Y95jgdsCM5Ey34J5Nnf6mq33+5T/n6I7Zfo73cZW9Q35f25b9mZy8BAfya7aXx+tbPvtIGfq29v+7T20bw2wKHv7Fd/hob/upbkE0A5zYc9BvY7ytA4mVE8+Kbl/HTreu+5sheiEPeEtf9ldtX2flXWf5Fx/NrHuvXJsZmxQIVc/FGFbscsi89RGHCNU+5YsCQPT3A1gWZ9IhMxlAndF1GjwFNs2Rm59yXPZyxIIaElEoLLJahjsily4zpVqmLkGnupbJZUrsrtHakiXefFokYZm8SZfuQ7pDmRxTLT8gG3+TkzX+H/L0elyfv0uvsc/k736LzdoJcOty0oQbqIqdJ3sDGMd35OYihTnKKwZjr+2/QpBl7IsjiEyTdYbHzeyT1zDtfNbONSa7aKnTMNRp1oZ76K9fSBqIcTUYYk4Jdb64srkacI46H3me0rshlgE07nFQ/50HTpbFz0vwu6+WEtU6JiVlWzzg1Z+SaMbZ7xLKPkZhvyO/hdM01z0k1DcXmhhUT5gEt9WWEEDGgg4B3nJKKnmSk2T5RXVE1U9YsmZg5PdcNgfnUc8SaBo00qBAHd3eNMI2jwtsZ1jgKGo7Z5cw892rIGK5Z8Q4DrvWUO0UfFZhHK4b736PK9slmP0PFUJz8HwiG/ODfJJ5/SJbfA62wyT7iVsjFvwxS7Y6e+9/p7/8Quf4J0j0KtZ4xJ5M/ZffZkS/8ToaorRG7Ioq7mHQEarHVlFnzjIROUIm1mxrHJNvHisGuL710ezLEVROW1VPO9CkrKoYMuRe9jdWGafOElRR0NWdmCu4u3uBz/ZgH+pDzxV8w1gPPbcvu0tQLCnfNMP9GIMzG1HbOtVxxIlMcyvfq79DN7pFUV6CCpaZC+Mg95r762tCKFUEUGUGITErllt7zVbucyRknesnSVXRMwsh0KKi4pmCofYwaZjKjoxk1DStZM6THkoIhXV/mqIY32OepXjFmgGHOlS3YSZZ0TMxb8S6lK+lrl4fpDleu4CDqk2/pyb3c/j+N2H7bftt+2/7/2b4WiK0NFMekHLo91pQsufblKNJhwpz7ukdCjuC4kOccJt8kIqaylkFQev1EnvMg3kGwGE0QtTyWT5nIkkMdM8AXgWekOHFcypSZLBlpj1QTClOx58ZMzYR9HTGtT/iFPuZ7VfAIiDoQ58TJLs3Rv0WZdXB/tSQFrh+8CUNDeWLZ+7Of0F09IZ3/AmmW1MP3ieprpFlgs2NEa/RCmI/eZ90dc370dzn4+AkkI5aju6TrHXqzD4mWnwEOlx34VEN55mvmJIaoizZL4vIC1EGUodkdVAxGG4/ayjmunmKbFVE6xDVLqmbGimvydUVfMwp7QkOFXVYk0Q4/cz/m2/oWM7n2bmDBvUqKzzCkKBVWS57LFd+Sb9BoAXjFDYBLmXDCJTWWHhlrKnYYMtABfR1gizPE5N5FSmNSjYMsecfHYdSX+pumQlHO5AIVx1gHoeh6To8BKX2u9RwVb7k40gEJKZlJSRmwy4C6npFkY4ZVDdqQTn7E8uxPMJIg4dFvJj8FVWT5OVovca6i0YILOeOQN1i4C/rmgHT2EZLfgWwPFh9j1yf0XYcn+gFWHLvFmM/klDflIWk557z6CR1NyclZypyVnCPADjt0NGUiUzrq2NNDJB5iosyj8iihlx4zLmsu9TEzd8Gu825mCSnHcodGlFM+4Eqf85a8S9TZ5dDuIpGvyChWn5AlY/rRMRfrnzKOHyJRB22uOeCQruaA4KgpymcAoZpDuZIr7rBDTIz3c01Zs8CqJcKwdDMSUsb0SEhQHG+bO4s8tucAACAASURBVKypWbAmdR1KFVIMd+UOldTEKJF0uOR0U+/rVDAas5SSUdThYz2j1IYdUxGJcDceEmvEUTZgRI/dzjte3r14Sozw2F5xEPVf26d87RDbrSyblsfzmgTZK6t+pYVf3l4bh3nNuptaQNWbWM1r1pdfIWlzW47zK1ySv1XTdsOv+1xv8levtNuoe69s67UpzC9vX/Fk5Zb45mu/thVTeyH+9cop/gYCVL+pG/Wa7bx43nLr8tex2F7PbvsqB91y5b7km7c9sF9xt3/b5/xrgdgAMvVZtQZLIw1zVhzomFJnrKTint4lNilWS8Y6JiLiqvmUY7dHTIZgeKT3WLOkK6NwERxH7HHH7ZCS4VCuZYIhoq85F3pBqY7cZDxxlzyrp3w3jRjaEZW9BCr6EjPVc1hfMq6mAMSjd7jcfZ/9Zx/Qm/4Ns93vYq5r9FNDb/4R8fJjWJ95rk7/EdHiQyh8eW1UPPfa9tOP2Zn+lHr3B5y+8Udo9y4uHpIvrombBVGzRMsLmtUz4sEjJNuHpkDL68BjWvu/uIer5xD3IL/r2dv1FNTibElTXoM6qvUZDQ15doeqLHkqJ7xl3gET09Sn1JT0kzvcLcc85xlD7XOoe0EKyvAjfsFbHHFmrrnn7vBQj0iTXX5m/4I9HTHUER/zhI7EjLVPz/X4F+4D3ozGNFJjdIBBOJVTL78tMQtdUVITSYEJJOETueKKOfe5x7Ec0adkrXO801jKtUyY6YJd3SFnnwLv7eq9ZVMi9TaH+/m3uVr9hGFtGO58j/Ls//LcPxJWOiFnQEPJqp6QkpGbu6zsxUaO4Tj+JqfuI3blEKclTXFCnN9FbAXxgKr+hMT0uePaoLzyLt8iTnao60koBo9IJMdQsKf7DGSXeOfbSO8BA61RidG4FwiqETbqYpMhUT2hc/0vuHs9ZSQ7rJijCEPZI+kckriG99wIawvPS8vGSJNCMkDsmu7O73kUGncxl58DYPJDUlvh7JqD7lsgEcv5L1AcqQz4jI95GH+bxC4Ym/sYIhq7otECAfpml1g6IXPe4ZLPGUdD7updGrvkUi4Y6pAhQ2Y8RzViJQXXMiGnS2kLznXJcTTiUuaMJMcoHLodPuGCgcmYNyVzCo4ZcaELnjSndE3Mv3JPuN/5HuQHFEVDLBE/X5yz7HztXapuWNEvLXoJHXwBD0u+aJ3XtZZvH97p9risL63JrdykbXTWvpYt/a92+5u/zfov57m2j/vltNGXpHJ/FTAhm/+9slg3r1/kqb9Yg7F93V9Nc72CAG4bcr8CRe3F4/1KC1+zHb31/t18vM2yumW9zYPyxRf7dYd5cyW3azjl1veb2ckts5QX62Jv/t38tYo4m0qDre+K3LocQF9Y8FXx26t1DK+i5Rc5dF+wsc2ydhO3/Npec1Svtq9Jx6ZMzDWDzkOsNOzoDjvaZx0UJb6pb5JJl8rNiUiJJME2y031Rk3JJSdEcY++7Gzcc8CQaEZGl6lZsDaWgYyCdVvJO+Zt3o+/SULGHbNHP004YUIttXe+QnhT7wdNKctz/QQngh1/DxcZBqd/Amf/J8PLP2Pw8f/E8PQfY+or3PQXXM3+Esn2ERw6f4wrr1HAFqeUk595x/Z6SXL2T+lfP0NNjrE1g5M/Jp9/RJnfwwVNtWb+Ka68griLdPa9DE955ZnoKFVzRVWeIavPiYqnaHmJW52g9ZQoHZMO34FsyFoKTJQxzB9xzx6xspfgLL3snjfjrVcYImrj2B98l5UUZGbHo2EO6ekQh3czEiKK+gSjwmPOSMjJJWVHBywpyKNdvhs95K4eBhvBFZF0KKThUp9T6oKuZtRqg46Zdx+7o2MesE+sDVYsY7nDvh4Sa0qiMUfuiLvyBh0z9LW82mOsI/qMuJZrVGBPjnHaUEaQ7X4H59ZM3Tlze8rP5RcsZUVNSUPN53LKVKa4Zkke7dJNjsmiHcDSdTmtuEKU9KB4xvL0nwHq7SCDHlhscu8fmu/j7BqDeP00RlxyScGKyKTerjE/3FgoNh3PoauTXWwywMUdRBuMXdJphAO5F4zC+1jjSOIBJF0kP0DyPRq39hJaYnC2xC4+RSVB6xmkvkqipsbaFbo+w7nSf8dZlvMPAeVv5BNqKhI1WLtm4PoYiZnaE1Z6TeuRWrgJGkU0Ypm6E+Y6o7IrFMvHckIVZJie8oSxZByaAYWsGGqPhooimrAb51hp2KXPvtsFIJGYoWQoyhvxDooXcIgQvhUfUKhFcTxb/xWTy3/OgfRYa8MfDI45igev7VG+Jh3by9iJIMnjX7+qvbTBWFvf/wr7kJdHvO1x1I82r3LfbkEsm1HJ29y1Gmrte9UthPUKa/vF994ceXt/rXrI3zaqsBXXexlAvRR7abf86vnwwnovlNjqq+u8wBXfQgK62c9tQbf2Gy+h1Q1QuQUFbI55G228/P9Qx/rS/rYVQUBxcoPMICCVFnzeqr6ydYyqsKlP/gJ0unUEN2z+7fu5jczk9suzOY4b/ZPbrsWXPvkt+nkNf+5VdHrb8/66jW+j3LBE9AWvivbL7c/51Tt08/i9PGMThBerJ9z2x7fGUtv2tYmx3ZW3cc2SXXPfjxZSkNMhNX1W7ppUBkTEmCgjice4Zs25m3KE953saRfbzOnEY1BBHcRxF+tKrC0YuC4VJZHEHHLonctFMeq1xzIifo+3WLIk1czXqoqSmD6VnTPigHGUE+//kOuddxldfYzOPuT/Ye9NfmzJkjO/n53B3e8cwxtzqqyBlZxJsdAS1BoWAv+CXmjYaak/QivttRca0FrQogFttNNGakEbdUPsEiEWWUlWVg6Vb4oXwx3d/ZxjWti5N+IVM7tabArIBW8i8d6LuOHh97i7nc8+++wz1R598y/QfGDY/bLalkPLFOubixBX5P4zpE5lD2GJW/4IxhvwU85e/3PUT5D1X5P3r5HLFcU3VYXuoWTK9gtk+l51eFjeT4XvntOGOXnzGf31T/HNOT7aTuaaJUzeo/gJfvsFk9JR8g4k4MVmOQCUPJiDRpyx6h8TSwO+JWki05t9D0LPjlVFv6/0hk/0x7xfnvEhnsSej/kBL/iSJ+UCkczj5kc41/Bl/3+z4RrPDU/LOVvZMGhPIvGh+5jOLchlj48Lm6U5vqEwIkXBKcFPGAsUHTB78YyXzix9XMsNL+nKgTt6nvAeOe8p+zUrWaJpQ9m9YsqCHWs+Kk+JtQq75pqtDvx+/DF5XFdVvUeL0udbBE83+4ir3Z8T0h2Mt9y6K5r1p6zcU3bpiq2scXrLQQaadE7XPeZ2/zcIA43MuNBzPE95La8Z9z/jYrQxcxKmNO0lQB3QM6BqPZgpb9jntxww7vHK3dJo4CZ9wWK9x7uWlHdkRrruMeP6F2zHr5n6C4ab/4cmzpG7T1HgQM8rvuSD8D6aB2JoOOw/50beMtUpv89vE2VCQ2SjV3g8HYWZnDHqtjqfbIhEUGUaLomp4QelI8qUW33DBZEZplnLDPaciqPnYEOIqltzW637Q51A3+qEl+41l7rkig2XrPiVXDGjw6ljzoSf+O+xlQNTnaAUBjJnruM5ZzVyfPmN8eQ7E9iO0dm8mr79XQ93voc7xTsI5J2jGq/wEHHIN2FAuZ+aQz368Qj3R3LgfJ3MfnT0BEqdT1COcw3cO7vPcWfRB9OrkHtXMhuAfEQD3zKgQu/dUx+eHXI8FnBEjQ/X6+TdVT+Lwr0DA+8c7bRe7/R2qh3m5ABS170e4+iYajMi3Om9x3U294vjtbp3bjn+xuM0qnusdv8fvOu79rdvDKlA6p4ZO73juNaV2K9jAk5OZCckczrPv428jm4gJyfe42/RX/f0e3jvHZHuQ4R1P6ibB8OuObknZ0QTlGQN48fB1mJTIfTo/0+drnX8X9Su7cnH7yGqqecs9+d2j3Dunxyn7sFa6Dvn/bdf+g1X6Dig+nhbPUDcv3aIv33MX7+68s47BcE/GJB88k+Ub3qC3319ZwKbefWvGNOaqA1eeuacU3SgZUbWgYNuKanQibDJr7jWLZ0ELrlk4s4RhJR2bOSOiSxw+VArah4VIWpLYiSLsnCPEPHkfMATGBlp8UyZEqUFcVB2jHkHmHKbMKFf/gGzu8+ZvPhfzKqmObc+v9AyaZe83v2UJ7Of2M+7AOO1TR3vHiG+QdOBPNzgREx7Nrw1x4Q8cOhf0MRzcvuEyc2/Qm//0i7f0bBvuGFMO+BoFgiy+xWUvj7IDeQRZG+mleMaP1yRNTOMV2TgevwrLvUxYONvxrJBiuex+4BxuCbGBXHYkTdfEQhkHejiY3QU9tzSaYuI44YrvOuI+ciKDLzlBZ02Nug5Lk5ecx54mTcsXYu617wuG77HE85Y4Qrc6teoJuZMGMqGQdeA4MMSVPnzw8/o6fnd8D6OjsZN6kAPxenAo/IIxNMzcNAdE1lSRJhNPmJ7+1OCNOzYspBL1rxlLktEPIfyNX+gP2Qcr83yOkzJ4x1X5SvmzNnImmn/lpU8w/sph+E1U6bgwXeXLNKU2+HPWeoFcy24XNDcg2a67j2iHkfeCe/LOeN4RxHB+wljf8V4eF0twRPRTck6kktvw5nF8YY173HBSuco8EruWMoT7sorlvGZ9ZCmPT7OmfMU315YT3F11shpx1SnTHTGuHuJb5ak4bpiskIgEpslLi443x2sf1d6xnRH272PjA3WeXFObFY4Cbgwo4kr3PAW35zRuUAeriFncjkQ1Vw/Op0hQBHlsXzEgR1rfWMjF5nSyoSNXnNWLBNTucOpEHBEAisu+ZRfsGLCihk9PcfhPzMavtZbPu9vvjWefHc4tnd0X8eIXXfSI+LhuCOZ22w57WXv7ozl9NVfq+Q9TOEfICbe2Snuv/awnnNCDBIMYZXh/meqYy7VylqcN5fUhz8vR/dTd/pa/eB197adGrCAWVLd0d9ZJAtY5bjTK0K+R3MnpPCAZKtIUKtXVtH07u+v73f4ikDv0eWD1XoXgT78Tq20CXyDj37lpbif4lTQ06Sqe/T20HPrfv7C8ewyiaSZh6jo3btEcKfr+fB6e/Q0D+P+9x1dWpX72Znvoply+huquJOr6wNUcXSMrcd76OZqqMLS9/tJYd6OYzuVocw6P0MrYj/Ohj1+itN61t9ZHqzR/X16fEed2nb8bPV4ovbb7/1e9d1b/ujKe/q//vajC7Qcs56KkU7u0OY55yTw0Pn24TU4nuP9nKqHWM84UffuyZw+j8OdJtdJfe9xzgZ1bf6txu99y8Dk//HBsOTPROTP6tc/FpH9g+/9d7/p+P/w+ofXP7z+4fX3/fo7DUxW1f/s+HcR+W+B2wfv/2tV/eP/ryfymfuc3/bP+GX+c57oOSMjr/manfT8MPwR43DFyIgnsB/fspY1Z9KyKHNav8IRuNJfUWQgaCDpjrfymoDjjEcn79NBDhQdKWXEScS7CBoY2LPSKVFsMMaY1nRMUHFM22fkcUucf8xIoXvzvyNxyrD9HJE1Ic5I44Y4e58zMSNJ3XxmNjh1yg7iwUXK4Q1h+hy9+xtozyhpi2vOAWVy/oeWTvsJlANX5Su6BK3MCH6OZiOWUSW6JYxrchl4q19Txi2rskDzjsN4hbhI6+aM+5cQOnoO3LGmZ2Sle7w0rOWGc3nGPl9D3lKc0DUf4IeWsez4kresWNXrrMwwY4CsR+PAwoZr+z42N/LMjKQZxmta33DNS0ThR/KUGzZclBW39GxkR4NnyQUF5Qve8AGPmOG5kx1eHdMy4mi4DAveyjVbDkzdJc5PyHlnBQc3QZzQ6w6Ho5Up3nc4maDtis1mTZI7nsdPEHFcyCN03JHyjmfu+5R8oGku0TIyDFc4POc8xfuWZQbnW8R58B2T7hObXO86sxaaNLwXPK55CsMNTD+E/Ves3A9x0w8h7yFtzcCxe0rMe8OJrqXpzyH3tRKvuDAzkZLvEFUudl8y71c0bkLKe4qOLDUT4pzJcEC10DSPYPEDXD7g8gXav4U4wzVnyOEt4jyX0x+jhyszfUQRiaCZZ/ET/PlPcBQ0zAmX/wh1kSZtccMVefoh2U8RVXzaUPyE9fwDxmZO8YHYbxCg7a9xucflA2G4ZXnkb6UhBGvTKgS6vKFLFiZ82iNiCTFlRH3H2f4Lgl+YaWv7DIfwh4cvcS7ixg0qEQ4veURivfkZnb/gB/GKv9o/nPZ5//o3sQb/30Tk42/6nhh+/0+B/+Q3Hedf9zoOXwUhycgxgcySGUmIuFN6Yv/ZuF13ovsNMmfNlTsAUBIJR3gAdo/mj3pfgcfIdT0Rwg+J6zrur/q4izN9nMsHc92gwDHVqd7uvg69QAta6jDeB8JIG/gSoIz3BYMj3K+80TGFyySKHsfD2WeyAcfHf5nMJOtYNVXVSllHLC3G3DdOg5fzfaInx6EYx4HDtqLUdEmxAS3vXO8K8K0LwJ9G/AEnmyaroGa0uqdkLL1u6hracBI5/cZ6YJLmWoCw6VMPizheHE6OKZ6cgsGJuH4nTT5uYQ4VTxH71M5F+75EMvaQeyIqPadhKNWH30vARuf507EEAdfYcZx5kuEagnR2L7jGPNTEIVKHvJTRji0eXGOyIPL9MBgtNa1TxJlThfgOtOBdpBEb8OIZkFP6+WCMn3i7Z8poLi8ci2/HgSwO5zrK6Z7UunaCp0HCDHQA1yJhbp8LQfIO/ASCcXsOKL6jNCtyDWxeA6KFkgecNEbRlBFX03N10WZ7qKIiOBF8tQD3CMcBhciA+gnRzcBPcX5BjitAadOyPisFpAHX4jUSCDTYHJBve/3bFg/+I+Clqv78wde+LyL/F3AH/Neq+s9/00EcwrPyiJJ2nJU5M/+Yt3pLIvG0XOCctUx1TJj4FSnveeK+x75cE3CgmV25ZSUXHFgz8Ut63TLTjpmc2aTyMCfSktIrFMeeDYeyY+ZWeIlEjagIuRxQNTQXw8ImheOIZ7/LOP8RPh/sxgkz4uQ5Om5x7Rkl75FmhU87iDNk8THp5i8Ik6d1l1QrFqhaI/v0PbMRKj20l4ifsLv89+jWP2dozgndE7OTxgwvU96w4ZZpfETUxngN3yDtJZe6Ylc+JeGZxufktAUK3k8oaY+mA9HNKdwwlQmdW6GaONPHFB2ZuDP6smYqZyCRoiOJnk/4gEQCCkkHGmkYdEuQhpU8I5Udezkw0yl7OXApz0GFl7xizoSWZ2xkz+NywUbuuCl73sPzW/I+qG1mRRJeHR9wyaJ4Bt3R4mnp2JUbPA0tgafylJUu6fOdVTcloARyOTBy4MCGVhvUCaF7DM2KgqPTDk+yyjXgFh8Ru0tc+4gSz+g2P0d3L3DTZ7j4W3C4gskT9md/AmXk7eI9mmFPHLdszj5gmEzBOTR6ShPwmy2lm2AGlRE3HJCU0LYj7A9QCrmJlKZDXdUCBY/0A+4wos6hAq6ATxkUwrBnun6By/v677d4FCeC4mnGtwzT7+H6V7x5+o/xqac4T9+1aIjkSYff73HDgIaW1Ztf4HJPs/+CkLYwXJOWv8PV+/8+LicOF2eUGIykdYoMA9p1aBOQApQMTihNi5qfAP24QFJh158jpSA5n6zRwSqkUhSfRlzJuDIabwzVDkotWJcRFY+f/9CKHhJQF3D1eolmxtkPiMM1Id1CXLHIO9zkPXz/Bm7/12+MKf+2ge2/AP6HB//+GvhIVa9E5CfA/yQiv6eqd7/+g78+CT6qkdcBj6tuHUbuhhMZbejMTjlIQ9DA0Xy7aKp9eTZoFT1StpHMgIgd19Xdoog9rEWz7bA8JLKtCioScMchwL6zHfk4mFlcHblWx6sh9qez3V5dY6rwU1HkHjeq6ulnzeXUxrGVMAMJqLO0lSNyFEGLOc1yIm6pN2IkqH1mRWyuggRDkFKLLxUZoEdJi69TmQKFXAngija5lya0NGTuyXdbH0NJnnDCf8evBxoKo6ndMQRyRNZWBDCE1hJrLXA8keWNxNovWk5UuCFKQ5WBYNVr7SsRHiryyxxHS0tN+8UF8A2i+URaH4tTtu6CxCXEFeInVqxx0dwx/NqcU9pL0EzunpBlg5fA2F0yTqYgQmkDpfGEPCNPjtcKJCbcmClNoOgBFEoTyU0A71AHBIfzCecS6gR1DkmZMCZDJzSU5oDkSUXolfg/oi5N0FygeUuKS9QNFBcYp0tK8ORJQ6DHhYQ6R4nXEEYY39ph8h7CgrFZ4HJmmKzQWAfZeCAU6Dy0DjJQtH7d6AdE61UpBnKLIr5QKupEBCkFlxKooJLNdeb4/ZqpiBacG1HsOTiN6VOlOAcSUZz5D7pNfb4avDeU7I+zFr7h9XcObGL52T8BfnL8mqr2YFN6VfVfishfAz8G/sWv/7yq/lPgn4JZg7cy51P9S77nvkcqW+bM6Jiwly2Hwwuin5JyT2jPKYce7ztiqYHMNQRt8K4hlcJ1eclUZ8zlgoE9ox6Y5pZRRyiFKIYAC4lBdzSpxaPcyCuc86zkMaUM5LwnlR3Kgan8iLE5J4y3VThbYfD570EZ8O0jNC6qFsluvLj8sVk4txf2Z7PCL34AeWc3kXj7XkkMy99l6M7xy99iP39MO7zh8fSPGNNfQjHN3Kr9iBiWFii6p3bD1yA+8Rd24dtHFhzHOySuIB2AQuMWzIYJRWDUHUl7optxq28QdTREE/Y6C9KdrAhhRik9WgYKSohz2lTY6g1Lt4ACZ3pB62Y02uN9Q0k9U1pAOfQvuSxndGHFkHt8rdpFN2evhrzeyBWJxLLMoCSCGspq6PgsvSZIww/jh7ZeZcThGcsO9dDEhXGlTPClBRGSKNo9QZsVeviakZEpC1x3wXj+J4ztJdlFiu/IvkPn79lYRYnk2CF5oDQThuklKpB9w2G1QOQpqe2MymhsYApOSI8mp4cZAXWBkqyqOK6isRVHPd2J+oAiwR5kB+ocfl+gL/g00vQbfNpT6uZXXENxLcVFSyvbS7bLDwiTM/arJaEfKTEYMowebTypnUCfCbuBHFr8cODE97oGlzZ0uzt8GhinEwuupZCmLRocsh5hA5IL6oxOaTcbZndfE/s7irS4MlCkNeMFhCLRtkVxuDzQHK7w6Q7J/f1mLw71hnDdUaZUBtTPEE0WdA8vTMw+3rI7fMX0yZ8i+y/Y3fyUrn3Ofv857bjnML76+w9swJ8CP1PVk/RXRB4Db1U1i8gPsIHJf/NvcjCHZ1fTnMSGgKehYcuaUnrETwBDOlJ5C0MfhjJOYlBRkg7AnEA07RvpXvLAEft5m3fACBhvlRjwtKcyvmqmaELVeIlSeZrTcFlAwhxJa9tVJJpWDTXOIc7MgUNCHYQbkGCFgVOJu3ItJczsxvVTSmhQF2n9kkKEylMFN7FiB2KzHMtQW7mccT/iwTd2zKqjO7aJObGiu3Fw98Olk4ym9pd4L1EAvATjTigUHU6fWyraO74vEHAE4omNsWupKKX0NNVf3+FP0gEn/iQ/GRhJkjhJKzB5gIjjoJlGEkFs3RPjCaVBQVzAUaAIgcYCkYy2BtVdVSnG+7mItpfkuCD5rrppNJTQ1fdB9sahqvek2J0e6NwE1Ds0iCGYIMdLAtGZAkkAJ/ZEVa2BirvXy6YHoyLre9WbsBV/TN/qGpRs6dqJEza+0NK0BnWOFO28SwjkrJQQKN6h3p2OTf61BqZ6zyLO0GxOuDwiudSUsyBZ0QBk6xaQlCGYJMbvR5rtlqa/JfsJrgxkn1BnyCr7cnIq8flAHDf4cY2UPeBRb8W4goCmGtgUKXsLimXApS0yXKP5gI5rcv8Kl3eQtuS0Rt2SUg5o2pHz7ptCSb0vf8PrmwYmq+p/D/znvJuGAvzHwH8jIhYt4L9S1be/6XfYq/B9vk8uA46IqOClYa4LgpvgQkcoEzTtie0jNO0Zy4EoLdHNaMNT0Ew3TohFaP0U76ZMSiYWjyvKW24ojKzUxKmdLGhlaePEVGkUBjE+xokFHC8Nzi/R5owUGma3LwAlxzN8s0J1JHfPkJJQsendhBmUnZHRYUZpLnD7nVXJXITuGepa0IHcPsb3byh+SjNsOXQX6O9d8vbz3+fx7pf4uynOCzkfkHgGrQ1zKe0lQ/fEYHxJuLQmjLcUCZauhznj8sfI/EeQD4ThNefTp5S8J/gz4u5zfHvB5TAj9zd4sYCpaYd3ExN75pGhrBn1wCQ+AizYDwy8Kp/zOLzHLr3Ba8RVBOtdhxZlwTltWLHOL1FV5uEJT/O1afV8SygNjZsjGvm6vOZWtiyahrbMiKxAC+/r1oJSfSCLZkud8UilLhQl5TVFM8FNaf3K1tnPkf6OmZzTTD5g//g/JDdnxOEGtBDSFtXEdvkjigv4Yvq+4gJuHOl2VxTfMNl+zm7xMUM7Z7J/Q7v7nNxd4HdfIRLYnX1CSFvrRHGBsVmAgs/96e8h7QjDHaIZKclG6eGQsQdRNMyR9efI+pc4iej+NR5PbEygTNoQmhXEJRqX5OYcV3qKa+j6K8JwRw4dPq1RH5GyY5h9hKSR9uZnhM0Lyu5r3PxDOLwh91dIf8N88xkuTGleFqRdwbhHg4Ppczi8hXSoI/kcpAO+eHxJSH9tukHX4PLhNF4v6QCa8GGOKOh4R6p6T+cipSQKFgijn7Mf37Dhjpm2DGIb7YEDT8sFu/wGinLHDZur/5lnPOe1u+JyFF6612zKS16O13/3wPYtA5NR1f/yG772z4B/9puO+Y3HQ5kxM3R1ku1549jwFaF5g7BhQhq3lV8x2O99ZzML1SME442cx5cA2I4/MKCSKKcKpvFRSRRRV7mgezHnsU3ISUR9gzpvhC6grjmhLXUTYM9pUK4Eg9RUvufILZRkFTTfgURLW731lKrzOM1k38CqoZ+dUYJNbjKuLxk/5Lv6/pbcnKESkTJCmFhqo/V3iEPjOYQ5kna4sqfxE3Tc2myE/jUuzOjywCiHeu7Y+lYuQ7NVWzMjwRm/qBSKFEa2ti4VAd6LqT2IBo5WVgAAIABJREFU8W3etWi29QwyocPmcUrlFiNt9cmDgVTXwJBjKQMT13ASc8KD6nBF6HWMXNHxlOk5iUZ2o0gZCdJY10D3xIK+JlxJ+Lw35KzVdKByPlJNDeKwo7hMt3vDGJ9QaGi3d0zWL0iDEjdfIhJJ7jnNeIvTYqijs7Qz5J1xVApxXNP0V/V3D7h8oLiI1C6SEs/g7ktk/SniO8b9K1yY4evmWNIeryOQrZXNT2DYkMIc3+8J4zXFT/HDFUiD5DtcXiJlpFt/ie5fkXZfweSx3ZfJ+KqYdkhzhk9rc40Zt7ZuQ4bDS3TcQuhMlTBuwE8R31D6a7sqYQbDjXVbAC7bZuHiyq5h2lYO2xvSTCZbwQkSL8jDC3quaHXJKHsU2EtPkY4x3yE4RjeQhy9Rf07PwKh79nLgumx5o+tvjSffiZYqRVnLLQs9A4QYZ8Rxg5Jp4rmRkwhOAjntcGEOIjRuiijksz+wNGf9KY1fsM8jpUL5TGLUHk/DGUsG9iQSnUxqmlZIrtCTWcgljfbgIn2yIcqNX+DjHM09Lg1weI361tI+BMY7aJ/j9r+qEpBKvscVLu9RP4PSm713GZFyIDXv48cbwOPGW3CB2F9xmLyPz4npE3j7y6q41gIh4mWKVF1Qjku2y48Zukc11VGaYU3YvzBdULMiO9gt3ieMe8Jwiys9OcyQvLdBvPkD1EUIC0KYw3B7Gpzr48K0W6EljGbOWMqAjysiKxbjll4PuOk5Xd5Yq41rcXFG7q9pS0eIU8RFFt1HpsEbdzwKH+GL1t7ahPhAzA2PqgllJOKCVXJT3hI1mpxC1R6YuuaG1DK57CnOMbjMPNpQlZL3yP4Fzk8paYfzE3TxfbKLzO5+ht98hoYZHF6hZWS++8qsgHCn4CkSGG//wu4vgenuC7q4IOKQw0vCcAv7rykl0e5fEeKMMtwSXMSFuVWrXUsMrZmNHq44dtRSRvQ4bKcWZVyYQNpQ8kDOB06yndyb/dL4hlAOjIcviH6Jj5cISuZA132I0xEX57B/ZfdI3uPXn+O7S3S4oQzXtsHmPeP+NT50iAuMaYN3Hk0HXH+DuEge18j6FzgXbP1EKGW0QDXcnjpq7M+C8xN2+caskUomuhY0M2azWQ9uijjPmA354wOz+BRwFN9xlXY8kqcIwo4NAeuSiNU8ttOOX3GNoAQ8Bzmw0hlX7HgvLvl0v/3GmPKdCGxgk4wKydLQysmoKt5NUDVOyh70dPoZX6UJpXtsei0JeNeg5b5h29ikjEPpaFAMgbiTdknJTklSiG6Cyw6cswoklY9zDVmzpRJ5h4aJkcVInQilSNoAakJCADGi1HRGFZmxg7yz6upoyMXlHsTh88Gqc1poTVHAEalI1UYZQlTUNYztijFMrSwuDl+GimgK6juKdwzNHNSIXPVTS2HyxHiPuLCg6TucFii9aaE043xrn00M+To4abzENadpS+I7Q3Jw0lSBGu8mxvM1fon4jjzumbgVMKDFZk8gxnVOaBEwbq0+MFkHvHqCRI5NNFKvWq5pS9GEEsmiBD+j5B50Txm3uDJUHWGAuELFEYcr6F+heU7Zv0A00aQ1EufGg6rpEnEN491f4GQG3SNifwVhhjRnMK6N7B43aN7j+ze4yRPK4TXuWLELU6u6jh6GW5vzEGZ2X+ho51lq4Qc191vEWqxKf7ovTaKSSGWHKAy6xssenwbbLMtbfOUSRRM6XCOlR/OA66/wUoyrqveYBVWTI4GjlAGXB5OqpAPSRDQPUG6hXVmKqRnNPRJmaBls6lmYcjJecMFa3oplKEFaq2qWwaRSVU9XynCq6js/gTyA8xwYTU9IlePUz+4JiLjKgxtN4HEkMi0NCCzc/386tr+XlyDMWdI2j63EnvcUCoU9rQtohnG84aB3No5tuMW5xh5611IkkOOK0D5Cck+TJ6z1BnVTgmuhTAgywbnIlI5cDtZUXzKtX9G6OZoOFAZ7nmtwUif3lcLc48poaWU+4MZb4+Ym7wEF4gKVwH75OzTDLepadPoxIR8Y20vjYOQSP8wZmnN8/4axe4wf75C8Q9KGtn9DGTy5/z7zt18iGvCzDy0pPlyhrsW5SA4zxvkcyQV3MH4jDFvEdfbwl4Hs54TxQEg7RDPFt5WotcpTCTNkXJuI1EVozk097xqr1I5rJEwpmolxWQOXR/yKMN7WFNPVtHFEfETCBBdmTLzHtZeU4QaZPDZLc8347pJh+wUhTAmlQ/MBLx0zf2kbUykU3ZPyvnJrCj4griWnHT1m+ROkJdTBxEUTndjfre+y4DSTNn9DKlva5SfWPbL+lHT3c276T7mI30PzAedb0nBHaFbouKakvT38YkOEfJhwO37Bwj3CiWPc3BDDjKNyZ5PfGPrIQx3GklDdIaqUcV0HqOzQkijjLWjB+alt0CJWaCoW6MRFnDeJkIiZD/SjpVqJhFez0fJ+jmtX6OEtk+aJbRB5QJozKzSMG6RZ4MrCzqHcS0V0uMX5iZmcooTmzGRMxZAy4itithQ4lwFJO0oeEN+dClTivAXAYGhMxFEoNDIlyMRoBj9lLHuyjjQypYnnlsEotsZaiCo8kjlKxtMwZ0UqAxnbpKNf0KYdC9fhmhWP9XfIh7fsyw2DJibf9WEugtBqhw9zvO9QtQlFFuGtQpnLnoEDid7SDRdMm1bTwhJmJox10aqh7EhiKC5Ig3cR71qb9C4TCpmxTlgKrqXRcEKD4jyn3gPfYTX5ZJUq8aawznvbzeLKvu6M+xq656bS9g2luTRZQTwjhxk5nlOac3KwBzE1Z8bVAVJ6wrimGW4oY6Hd3iA4fHtuNx9aq2KR4lpy25iYshTjjEpf9XDRbmZx91Uv1ZPbrmg28toZShKtyMFPoaJeCTPDit6qos53ONeYFs53OGnukcKxqb+q651vaMISiTNbT28T3UFroEzgAl4CWhJOAo2bEWVihHMZKTqcGq2lagMLhZGBxGCCVtfiXMNxFgIiaLWPgkI5XJHVHngQ4uEVZf+KbXpFGbeV8HY1LRTjf8a18ULjrXG0EtnnazSPaB7I/ZVp6KrQtC8bW3NN93xjGQ1N9Tc1WG7NsKG6bRx1H9ZYbh0BhoysI+XIPxZNDGVNKjsy+cQnO9ciYYpUNEwNFKdX7u0a+hZOxD4cC0On4CTgw/QUUPFd7VSI1QDB0n8tg/1JOV0LcNWiS06UjIrijj5/4vDO1AWFhHOB4KZENzV363p8D8xorXItnpYJLa0VGLBr7Al0RFyYMg/PmGJegxml+dfgsu8EYkOEcPEnRk4eXhDigk6qv5brcO0lcbhiLhnJA0E6JCzQ8gbxLX79c0gb4zBE8O0l58XR+nOCKCrGeaDmd+XiggkTg+LSgDpiPK/oJSCuownnSLOsmjW7mD4dQDP4huJnjMvfZnvxCc1hQ+saNsvnHObn9B8vLLBMAi4dGMsU3xTaVUQ5IHHG5mbG9tWU9s0cl/ZMNy9ZX3yfdDmDbYP88GPc80e4Lz5AtpZeebdgun/N/uIJw2KOaxJJehNC8pgUrAQfxg3ZtxQXTDcknhRndfc27lFKb+lXTS80zNDpB7jhBvVTdPoRUgZCc2FSm5KMtG6W+MkjJC/QcY3EFd419iCV3kb9zT6CMLOhwWVES7b0o4yEsEBcS4hnlva6trZ9GcksYg/BUQB9/L5Xzyw8QXyD11opdR6RCUGmiJ/im4xzVjVm/4Jm8WMrCmx/CeMdIo7z9oeQssmGmrk1nhWTA5lBZyGPG3xzBrlnNfktPBYAgq7swdZMKYmpW1pK6SP41joD0h7aSxOjlgHnJ5RaSPJhirSXJtWpXmxOq7SjupNI2lkRo+xwaiR8S8ETCXmNCzMIU1x7ZumcAHGG9jdI9xj2L2xtfIsOd7g4Mx1Zs6Qc3uK6S5O+pK2h8zLUFq9Qxw+O+MkTSjoYb+0neGfcIGFu6FJKVRKMCI7Wr5CciG6Ga8+Nu84DTUWk6lqkmeKGtzBuDTDEJWEsLNxjol9BSUizxI13tgkwmhiXhkf+Q7v3gF43XMuWiONN2XxrSPluBDYEv/gt0BHyGu9nxlWIh/EGaR/hnCdKsIoO1MqQNXv7/VfgHFJFjz4uWWQLZioFcOBaStqA9jg/xbsG8t4WHiWEOXm8MzjuG6JfEJrHFtTEVNmuDBg6MYHnOP2Q7fJD0Nf4klmf/9h0Rd8/ByAuBVRI20KYC+GpaaG8h931Uzb/ak8+tEjJNGNiu3yf4cMLwiEi7z+3m3Z8gtwcrFiy39GmA/3ijDztyL6QcyAcBlBH9hN8HirPp2g1xVRxFN+cqmyCIDqatq4U0AH8OcS5cW2+g+YC+leEuISauuBbxBt/5GIhb7/CdU9xztnDUZJVppszcObddTRNFN+YADdMwDX4gO3cLphAtlaUxUdcaawSHCYggTyap17jV1bIKenkOyau9mX61kwH4sIKR4cr4uxjZLiGwysjvnEs4lPy+MIIfj/BN1T0Uex8wcj0MKfkPdP2Q6RKFoLO6mZgG1wrdbMIDvGGgEtJSFwiqAUS31S9laF/aZbWQqfZZCmqp2AJzqRC+YDLFY+ctJOO2Ns54zvjyfJgaa1v4fAWmX0AwxVHfhSK9ai6gPgpqq/AW6p45FePOkuRcEKjvjknDZ8breEbLPbvDMGnHcce6aN0J/oZzo2Ib3BxgfVG73F0aDpY32izxOVdraAKEmf4fGDqVrbWaYtvznGqpGzKBXERJ54z96jeg8KoO9ayx+O408O3RpTvTGDbLj4mjHu6cU1qLqy26FqrbjVnJzJaSxX2uQZcQ3Ed7vCCY7poMocF2l7YgqYdysoC4eG1lQzCBMICyhQZ72y3CJ2ZPx7TTd+izflJqqFxZSJJPyF3z9iefYz7kw958sGC9eeeOF/wwfM5zcTBM0EV4sQsynUUXAvNFJwvqArpudJfBIYXC158WrjrPiL+aE58Glg8FXBCCHB13dJ9HEijoPuW/q/eg8sF3bOAqJJvBFcCkluGTUL2I8P2KM2I+GzBOIeW6DzCyHbxDJ96mv6O0F8jeUfqnpF9R5BIbs4pvrMqH4ES54T+DeP0Q9R3RC1WYXUzcnOGH29J7SXh8NrGBsaliVO7J7b+0zlS9ibQbM5MEjK8BZytcdrg6jUn73HdE7temmqD9hTfrKB7Ym07xfRSNh+iKtr9BMk2dFrKiO8ekZpLQtpDHaojqtBcWBaQ98aLaoa4MrTVPsYl42/L9EMkztHmDKWm2+Pa5DN5g6QtLg9WMAkzrGgzQ9MOyVU+YwSC3buxNp3XAouCBRRqk1oVLNvj4Kp0xx7uk1lCJUgYN5CtM0bQmj4a0W886mAcWe5xzdLORwtD2eLzHgnnVvyq/ctD/4qm/cRkO6dWP9s0tGQLjGFixz4Ndm5tIxvWJpSOU6MC0s7WzQUYN7Zp+GKpfu6N2nHW0C6uMdwQJjbWUBNHb8HYnBs6D3P6fMukjOi4IcqEM2a8zGs2+UEK/muv70ZgE9jOP6LtjUBP3XNc3lL8DB+mZD8/9YWpRJubKcEIb7yloeLqLi5onENzbrzSYA62hMWJOBc/gWbFyeAxH5AwswnrpT8FNpqzKqQtaFxVLmpC6p6yW37E9B99xKMfwd1PF8SP4el7ynIJIVIrug8YFYGi1heZkhIC6CeBN68XvFRlrR1nP2ppF8Lle7YmbQe3v2qYfeA57KDfQX/9DLmY0z4J+EbYTzwuWGvOeFUodxm9XUBW4uFA3PUU70lNVx8WZX32PiENzG9/Zbty6hjap6Q4pfgZKc4oYup9H+bksMT7lmH+Q9BCyDty+wwfbX3cMCFPPiJoxqcNOS4xhNch+xfQPrY+Rd+Bm9ijnA+miZq+hww3pp3Lezi8NLQYl8h4Q/ETRC1lK9MPrTZaDtUdZcD4nYbsW8LhBcQVlAOuXNI3F4T+taVuxWY9aHuB6x4jhxcQ5oaamgt7zrvnsE+45oI0ed/mt1JbgFAk3KBhhaQbXNrag0iA0JnsJyxg9ysoB0RiDVmKc8EQZZiZxObUEOBPtfujls6Iz9r6VDlPKBaAj50D47ZWOHvb6JszqwAfzSSzKfq19EhYgL8DCqPu6dIOuse1d9gQ3dC/pnF/YOdw7GA58m0lGYp2k3rKjQVMV9PMvIPmDFfn22reI3EBEk/8nNNS5zpYoKUibHysBakO57Yn/aGK0lT+OYQZ+/0bujKi/TWRjqVO2OaB2/Ttc0W/G4FNIY57213BmmPznhzmprnSdZVaHGxn1mIppnjbTcMcyKeURnJ/L8PIViDQvDeFRpzZblWGe8nGEe1VzkYRC5LDDRKXtcfN48drcnPB4fw5F/94wcVHivfww9+B5SVM5ybTGMfqtGIfjRAgJzj0QnDK4SBMZ0o3geUSPvpt+GzrmSxguoLhYP/nORS1oKjZTjc/mZFcwG2UHJW8V2jBTwUXheIFWutlzL5h6Ke4g930YdydHo7iPNm3ZF/TL3H4bJIPn3vEHZ8+Z03XyEntbm0/5nJiRQlvnB1qx68PoeS6xgLqpxVh1YleofZYlmRpcS0wUIscVARydIKwkyxVCzbYOVXC3VIj+3kLmj2le2rCZVXUNxDPrBcxbdFg7W+nCKMJqt0SUO8xQz3oaKlV3RSRYMjt9PuhuNZQkessGNYA4+LSzk286eQ02c+6wyl4UK3ETVu9r5xdY4GgjHa+JZ0qieInkPdWgW4vOfYcS+hOPa+WpvbGGWqyYlv32Oy+jy13YW5rk3c2VOaYIla9m3SX1t9cgx9KpRRapL2w61gSlMbE3GDprVbbLDnaO4XaiWPec0iov7twbHjHT8Hd1WrtHC9GHSHOht7ElW1OcUEgMysFP/6cRr699vndCGwocdiYGhxqH1udNVBGnG5BGtx4U7XnGVFvD5kIGhfIeGvIS8Q4kLw3SJ52lpLmOhgkLox0zYfaU+hOaE98Zxc+HyzV6d/Yw9tY83Ez/Iph+hG7yw/56E/PeP9DeP0SfvjHhsBSgvVG2O2gFDk9j00LQw+3NxCCY7eBXIS2U87PlfhHcPU6MD0TVufw5gWs38LR7EF8lT05yO8tGK4KcltwjZB3doOEhcO3SgoCE9NHlcYxFKV5s8GVgWbYMjZz44K8J4eOFK3Qoc4T0p4UpoRxbf2KNVC5kmpj857ijG/zaUf2JhGwYLjHOB2PaLb0qvSmWge7mcdbC1QlVSFpj+hoAUiwm9zFmpIeA8vDcYRmc+NKb9wdYsT9qXugop7SU6af2PtQ1E2Q5hLSHQzXlZNraqAEymD3SBkr8T6951PLoQbXAUlmrmgZQ+Q02Ne11n7ke1x7Af1bEHDtGTqsrYe08oIy3mJcmnFlOt7a98IEPbxBVe3n0s4Qj3hDZposlY1zu8/jnBBnHL0Aj8JcfGNolztCYwUxSw9XTGYfW2CVaBlL7mG4pmmf1aBtjhrkPW76gaHQowYuH2x3jgsL2LnytbWdys6xcm95RJoWXIPikGaBHqo+zwXjGfO+Bnc1NcMQDOG7aAaVEhEy6iJdvjS/uGbAizDPU7w4Ov9dr4oCze6XJgYd76yknXaEKjiUvAOXLH3RK0sp8t4qbS4i5WA3cz6YIDYPaL6qlSY1dMYxh1cr8R9nH6qaZ5ko3pnHF1W+oICGCSXMDLWFwPDJ93j873TM57C+hVd/XXj6TMgZNjdw/avC8Np6T4v3yJiJXslD4bBVvFP2JdIvHNvHnrMPHI+ew/sfg0RlGGD4mz36ZiB1in+T2c+WaIhoAd8IvhNKUvRuhH1BB0jZk6muEwGst1/R4MlNwO8Ha/p2obYLeUNmmmtgOuDynph3ljqIdUW4YtIQlzYmfq6Ggioe16/RsLCHQsfTzSpp8yAg1TV2Ae/CCUkD9t5cK83FpAWk7QNu6cEkJ7BCQN6f5A2GFIw7c/UBk7xDNZNdQ3N4aRvccFXRea2AlpF7GNwY/aBaq99YitvfcTQBJTjrzCiDySdyj7RzE0QXQ4Hi2/sMIExtnVAIyWJ2bE6/UzEtmBVMGnDO1rHNpzTSAtXRLMAhVU6k49pkG+ItnQtTO/8wt+/nvRV5ytHSRyu3F4xOwdVqaDIjye6ZHefoNlMRrobFvYwJteMPt3YMb8LYEmZQMi5talCqhaBmZTxrsY1GwwI6Z7xpbTlUP7Nq6bhBnY2U1PbS2sw022dItck9TFBnHKX6KdlFPt59yJv8ir/imyuj35nA1l3/GTJ5DsNbggiMNzT1ASPdmlwjrY3biAvK5kukWdhF861VONMWmghpR+6vcc0CiQt7eI4GkQiMa0tZGrvZSzKLbV8DJWA3glprVG4uyL6jtB27/+AP+Z0/hbMz5dOfCb/4PzMf/G7k9kb41S+U13+W8L/Ymrxo2uC3PS5lXEr4cUS00C8W5DZSHnU8+Xdb/vR7yu/+sXJzAz//C2H7L++Ql3cMeSSWzF1s6D6xwBY70IVwuFF408OgaMqM1560miBRcI1Q+gJJzc5m0iLbHSlOyL6h3d+SQkcYt7gyUnxD01/j8g43XqPxDLTgd5/ZeoU5mtZ4xJBc6W1T2P4CaR8bmEqlplktbnhr16J9VFNfNQcIaXDpbUXK1v8ro9EMmvcwbihpZzotZ7NNxaX7ILn/urZ+mVuHxKU5WJRk6YsIjLcULSQ/YbL70tLW/u3JPMCQxx78DKgSlrH2PlYERtqh28/s7825VQwPry3trn2WOvvQUup0jRuvT2p+xBka8lM0bU8VT20e2WaaKmIqw4m8VxpoH1lb1HAD/RWuWaFpjyazuHJhhgro4Q15rA313TmEJ5DUuMV3PptaCjjcmsRDAqU9r215AcoObS6gfWzPWN4hzbmhtOaM3FziXaxodaT4BU4+txQfS0mHyUc4IO5+CShOniHJuHGNywoy9pTm0my28gE5vLB7wU0oYYrff22WRe0T8uQDQv/aCIUwwx9eWlElZtR15oEXzxm75/zR9U/56/Rn/B+8/MZ48h0JbJVC7d/iyLZrpx0pbfHNI6uuNKFyJrmKKgvk3gJI2pLyGqfJeCKo4kITVtrBR1Br1tUqFUBz1eNUi+zqvqBV14RzqETGMCWHKaG5ZPUYvIe7a9j8bM/0xWte/+V76FdX6FVL97pnJKLe0Wy3yFBo+rVRLVkJaYO4gW33HLcdSJ9lXn3VcflUGHph/1lPc/sSv7sxfqIU2tdvyBeRPG0RbymuJsWNGTeqBcxinlwsIhRB+gyDIQ43DoRxh88jLvf4tMeltQn7886as9PGApZmQ07ibX1runm8TnK0XCo9pAOFt0izMs7rWPEro+XOVQ5APpxsp+y4g10X35gWTvOJszLhtavatjqp65RqZrOSSj3qg/W4VhJdfFuJboW4tPeO63ofJNzkuaXJ3iQkJczs85ZUkUoV954C0SXqGvLkiY3my3tyc0bWisBmH1CcEPZLcmNBzQTPgDhKmODGXUW3kNvzeh8ezIEjj/d8VFHoLoyTTJcwPiHmTOjfWuAtvSEn56AOI9b2MfjGbLR9By5aCaI5o0yf1TkBQpk9hTKSp48o7QynB9QFZHiMzs4xsa0gDIgUOOxQJpTJEsexUp3QMCHIHKaXOCloTqTuETpC6qNlB8Uh9JaahymOS+MqmzOKOnQckeEcpa2V7BbXL6GZo4c9pb3A5SUuqs1+ONgskLLZodNH1mIW54yyIs4+YpqB67/4xojynQhsehwRt/7UdsLDK3RcM+x+yfTiJ5Td15Zjp0PN4a09Rf/f9s4sxrIkveu/L+Isd8mbS2VlVXVXL9Pd0zMjGxt7vAtrhIRYPC8DL8gvbPKjLYEEEgN+8aNBggckZAmEJYMQFhIgjAQC2wJhC9l4xhrPynh6unu6q7prr1zudpaIj4cvzrk3s7K6ezzTU4vuJ6Vu5rkn48R2Iv7xLf+vmUIzpWkOmek9xtklXGuQOsYlEtLRLGR2HApJGYoYt3wX8xdbc0EIDciy14eQeaIfUg0u0mRD3GjCy58QigJef0258V/ucXDjC3w13+e5L3wRHVxip51y5+on0DJj/O7btPmIyfHbPVHgcP4WcTZidukZ8tszqus1X3nxOX7kz8LJCRz+7jF7175CvrxLKPdBlfyrM26HEeHVi7jcEQNopfhFDctA1lT4tiUETxxlECIcN8bkmnuK2YzB/B6IUFR3QSPZ8gb11stk1R3U5WTVLdO1AdJO7fjQHKcjTsoXoNHypEpp+qrmmLi4gd/7AdNr5jtJL7NIjr8VZENcc5S87MWOFMvbxMUNXLFNWN4x840rknN0ibicGJYQUi6ATtcWawgVdXtI8I6t/IJ59tdHpkiPFZqNLMwtNsTFuyhCiA3Z/o+CeHy5QPHE8sAW8+pOCpOzPAi40vRHk48SigvMxy9Q1PfJyz2mk49SlxOydklTjGgGQ0bHd1iOdmxOaSRrakSVJi8p6jkotHlJMxjY2uwcMc/wTTJsOIfE7nNFmb11/zqT49eRMMNXyTfNl3bsbk8I448gzRH16HlTyGtLVV4g+oImH5K1S6LzLCZ7uLal3hoRtwrjj8sEWkX2MgigVYRCkEzQkwDzFrZzZOAQb+hfMmF4yZNvCT4TQqM4D9VUbWhapV2YqgTAeaWYuORHLYRaqeeKtkrnpdE5Mrgc2uOIOAEP5a4xzZh6T6mutTBKHHgZcBKY3PopLsmn4O2zzGkmj8XCBvQe6kaVDXhzC9A26QzSuZuQJnlyCO2CanN2cW6AORuKvSCSWSBuxF4WIqo13m/1egJzyE2+Nd6sO6RwEQEkLMxfKStpi5IY4M41ZfnGnMH0bVxYMjg5Sll67oIbkFcLvDTk1X0Ec4EgA4nGrCGyJJ/PKJcn+LYhXJtx65tDjqcOP5+a02c7M6pqbfAiDE5u09zJcbWnqGr8vQX5yX07TbUtrlmg2ZLmMKB5jptNjY1EWsrpPbLmENWAaywZsYQlbnnL/PhItDR1OZFlAAAgAElEQVRgC760aLQwIEEgGIIOocH7EtUlji7LpUukiPS6stjO0VDjk4OuLXJ1msnLpGdJNNcpNA5JIW3JE16SqwHtHBFHUENmzmUp7C4Qg32nfkRHJCouQyVLcb25xRb7DCSjLnbQ3FtegMkVpFngqi3TqUVDkPiBLcjbB8Rigk52CI2HZoDf3aYohriQI3mJLwqKxQQZDpMRQnEhw6HkWYFvrI15nlMWhSFtJ5B5XJuO6OIgGiG6tkpo1f4e7rIoLiOzGVmWdFr5EHXg6hnt/rO4sEO7vZ+CkwKMJrg8JysKsmDkmIxLXPDk4xyGHsmcEVvGiJ8404M1DskFvKA7CpWHsUMKQZwQG4fz6YQ9ME1AZ9QsC/PVjAFio+YtAuaHOaDzbSe20A4hBmunqrkodRF9YZjoqZypDUGIQwUV3EWH5kIzUyQX2sOWNt9K/oXny2OxsAmg9ZEdgVwOMjQ3i+OvEhe3cGPbgSl2oTKTv/ih6R+ygiIbUbikt0DR0JDnO+Ay6uoWIjl5dmDJQ9oThuVlC0lpji1soxwm3xsLFI5hgcu3LOatukVZXabNBsy2D2gq+NJvBcrfeYcrb/8WWuyx/8Y3yOu7FLPXONn/KbYOb+Niw9bx1wjlJbLldUJ5BVffBilxYcr2jesMF7cA4fg3PX9w7UU09zxz4xquXcDiHQu3CTO8eC68XjO7O0NdQbG8TVHdxjcWbI9kuPo24e6Q+dEPELItyuq+WTfrO5b0whXQntiM9CNojiimr9uxpF2an5S2yOhqYjI1ipti5xPo/DpaH9Es3sHv/aCF7YxfSJuK9bsky5mGOc38XVtEU2A89YkhNpdDdT8FTxegwfSa2RARRz1/19x7fIkrdomLW8TlXVy+RR2PCLFmPHiB3A9w1T3C4hb56Dn8aBdd3EyK7zExG5GFuUUSaMRlWzR+yHTn48x2LtBMhrBf2FG9ToaMTFYTMhOyZ3J8LowPhFoNcWwfQFaIpSUQU0k4t0dWJMNnuu4kreGWmwXnzOWns5I7z0qnJ9A29lMtYXFixsfF4R6Hr7+Ae2tKObUwpGqyheaefLmk/vgFAIo93xuNxxcd+QAGJfgUMJMnMuUss2suLTTOW/1TErV+AdLo+5fydILxdPixvC64TiWS9rQYpX9Od+/6DyrEaH3nnPXV6XscGs2zIHT2IhHaGprnHPVcOb4J4pXZ64Hp1gu4Naafs/K+QfAi8ryI/E8R+aqIfEVE/na6fkFEflNEvpE+99J1EZF/JiKvicgXReST7/eMjWxkIxv5bsoHQWwt8HdV9Q9FZAJ8XkR+E/ibwG+r6i+LyGeBzwJ/H/gZLNfBq8BPAL+SPt9TpLNCppAMEGMiSLGNpuA1h0iNEbzSxAUZg+T4Z3z+JFLCjimBFJoC0fQ4Pt0Pdgyw3zAnz0iXH9SUqk3yqavwsYYQmd2LZIfH5ItbiQVBzNydnunDAtEmpRurzVVFo1ETxRb1JaIR306Tp7iSVffIZ/vELEfayvi+YgoZUjVrWqzImmOiK3BJyW9HvwowZb1Q4at7EBtcfd/cEJI/lPQQogWXcpD222nqA1WzTiZlvVn0koOquOQFnwwA3aeY57D2rhnpONuHFUHvMR+TI+66KwjpCBLbRNmzyijauyCIMea6RELYMWOotkRtcd3RFk2GkDkdoYG2C6MPcgXR+3QUXIMjHVLz0kVBQS7942MAETV7ienRDZlhzchzu6ape52HKGZE6NEIhkI6X2MXV6gu6eYJDbSV0iZ3sVhjOsYQEluLR2I0ZJOSw9gwaKeRMb1X1jVN+vJdGq4Y1pqdQ9s1vUNZ3WjIqt7oCtWFRmkqEjPI2tRJ9xsKtOfGaPWK614/qc98lvoj9U/fbwHaGkKlRouVCWGpBHE0xxF/5wSynGJxTNZMk6/r+fJBqMHfxdLqoaonIvI14CrwGSwXAsCvAf8LW9g+A/xrNf6Y3xORXRF5JpVzvoiY4+ziJs3xaxQ7H0dcziC/SGineBFzaGyObQFr54jLOKrfYHd4EdfR1tSHoIGmPiIbXMR5C6aOzZQYlgzKK5B38WVqlqY2BdKGyiykbfIuTxTIvtihWFwjZgXT6bO89r8qLv3OHzK+8d9TPOQVBidfs2DzYp/h7Fu2oGiA+i55dQfNtvDVN02PNBxDXLJ1+BVicQHigr2jL5HFQPBjypNryPIGoTnBhwv2gvoRfvEO49rCkjQ5yUo7TToyBVfgllOGs7eMRLKd2tvSBVgnFmDahUVwiLdFq3vjolkc25PXyfJtxA/Jim2ojD5JXUlR7CKhMRebxBgh7czesHaaqKRHFOOrhPmtXo8p2SBZKU2fR0ghUd73Z6BQHdG2JxSDS2lhM0W+y40ux8gtHVqfGN9YsQ31EW19SDG8RJ9suj4k53V7Tr5Du7iD33+OaniZajAmFDls5RZooIK7sPYKpH2wW4fFQ30CxRa4TGgqWCYXuDb5m072Ic5XL2axpoPqut6s9EkPlaKefLa6r22hWcLiCOb3osWXVxGmLeV8Tl7NaYoRrmksvV6eo63iR55QK3EBUpgLUKhtYRlMrH6hgSxxGIR0coutxS0n9iXy5KoWI+SlLXr1YrX4+LSfTe/C/HYgtpBvOWKrZEPBZfbMYrjqv9jC8kiTn7UtuD7p44qx2GYQQFXN9W0ihEpp50r9bgNVhImHk4BczNF3l1z9yudYDi+zd/I6vjnCL67xMPm2dGwpI/wPA78PXF5brG4Al9PvV4G31/7tWrr28IWtf0DH92QZz0lGgBXqSru7mld85oZ0WdvtutLHHpF2NefN2ZMu2zsr5bWk2dcjNxsVWQ/VSA6dEhZk9RR3XBtLgSuSllSTEtOZl3U8zTigKQN6jzi1RWJABSxkyLZeF2uiG6TwJU3txpAQ2qMYQ5kJWaaA/V7R0flRWWRxQlPpbYWVxrdTqvRvsZrDqGJKe40WgdGGVX929ztL96c9uiWhR0OvvZ60d3ZNbLmYcQjX5UXtdDmur7+TxPWVHGlF1leZlFO2b0/yYk8hXh3kUA1ouzCDkAhd5i2jc5pDFQjziGsCzCq02EltUNRhljkH2aLCV5YjwVcZZDkub9BWcAS0sX6UEBH1iNgnhaWrUxVi5pKxqzXH76CWzg7Aq6FEFaSNuErITgLFkRLbgNYtTBdkyyOyaobqAtUCpwPEecLxHMcYpzVh0SC5kC1zsgXgM9wS8B6tI74IRAqbDhrQmONmFQTrWymxekSQwhy8pQIJHTI0qJkdBvIj0KBkraUZ9JXHuYg4tX3MOcQJ0irZSYurI0qGeMHntrr7pUOCN71cbHF1IKszpPXIvIaTxvSfKjALSF6gs4U57/ucWN8ltEeU7XeA2DoRkS0sUcvfUdXj7jhnL5+qSEdN8IHL6xMme4y2OC/3DNWEGtE5kg3JOgbZ+r7xtbmcNswpdMLe6PvtDCBqR6zY0DbHOF/2x9i82Id8L/lWJctXtmUK7LBMLBLJCumwlHkpwBcNaHUXpy2Ddsql+oTsq2+aBXf8olkLNUA2RsUT/Yh8+g0L+gZDl+WBOYAWezB7E1ebM7Foa0djAS12GU7fZDl+CVffQ1D89kvmSNzMzNHSpwTEfmzHzPqeLR75hI5TrWtbLC5Y2c1JvzlocsEwL3RvC6evVguLs3hGKbZpptfwF34QPXnT8pOW++ALMwQUO+YpfvIaPftufQTamNPm9E2K8XP4ch8IFl6ERYrEsMQNL0E+wqlRWEs2suQgGinLy4k1ooH6vgV3uxwa4xXrNfJIYn7Yx+c7vRoA59HqDnX1GoPJx9B8C18aK8tgfp1ycQsXZjTlZYrFddzyHY4v/3mLTdaGKJ7oSpw2jA+/QCwO8NUN1G+zHL9AsbgOkuOaQzTbIroS3xzSFhfx7RFtsQ/NCSEbE11Bk2+RN0fk1W1CcdHUCa3F60pYEjKDOFlY4F3BKKFvCTOo7qH1cYoSsDwcNDMztCQq/Gb3kxTzN8xxWRWGV2xhLy+jtMR8D9+cQJjSjF4EEXx9j2r4AsOTr6DZrvVdyj9gZKoNgqdIaRsBc6wNC4btzMIXNRo5AZGQTU75QEZnicUltkhziIQ5cfgs4JEwxTUn9q6UB8REXCD1IXFwmZjvki2um+Vc1WjOwU5WzRHazChiw/H8j7kn93iWFx66vnyghU2MK/s/AP9WVf9junyzO2KKyDNAl730OvD82r8/l66dkvWEyYVkhlVV7XhiT4W0s+saSrP6dGiDXs/V7e4r94GUYV3VXjDXhczYTquJqdTqsgqiXul3VnobUpwiGu3/7HCxUhKkvKSdk6mqGsrrdUmm/5MuQDzpiuzhAU35O41uZoVMrR5d+jlZe+YaQmNtP5EOCenqbzqUl0J4+rJlFfbT97XDeCg7dNahrkCfq9RcmVNPyQrxqjuFkCx/Ar0rB9pZrbsedqvndPU+FdTsEkpLqNdlqc6xb7/0ZXWoPf2VmIZJCJBYm6Osc5ZQJyxsTmgwthcw95A011yszBm8Z5+1mEhRy19PN/5pvEQbQ5ih6p2KTc9qf0tCt/ZdY30cKyQ4+tjY7nlyduy70Cu/6qM0B1YvfmJNTouUxVIraGOhh7G2+RsTNXys0rh27MqaThIpT62QFHJZqv9am7sTROdQ3fdBe+rT3oW1sy/JN7QLkYuNvbPdu5eYhzu03l8H05l3DCiYzt2lU9LD5H0XNjFo9q+Ar6nqP1376jeAvwH8cvr8z2vXf0FEfh0zGhy9p37NHgLDZ6C6b5nM25mhMwEdPgPaEu+8hR+PAMjzHUMeguU/zIaQjfDFds+CyuCioZku6NrOWclPqjR+NW8KfgsGPlztjC5H/JZxdDVTIyUMC3xz3xKD1PdtR+kV+Barmrez5JxawclrFlbSTo1zrLoF+Z7trpOX4egGjNTi70Yv4qpbDNv/ZwgnS6FdGo1lId+2diQn0tic4EjxhInBwiiVxmi5b2E/sbX/C0vrByls0mXGhqvZ0MKM5teTV7slFKGdG7mkeBg/Z2Xe/Rzs/5gtzNmWBZJnAzvKlAf2UgDaTskHF83ZafyC6US1tUQoscEvbiQyyxTQjbXTsUdHXKjJ3038kJ7hodgzfV2s0cUt4uIm3qX8rbh0PA6mClAlH10lTl5BJSNrj5Gjr8HwMq7YQ5a3KaevJSLN+0zu/I6VI7kp5aWA9hhZ3DTP/3IfCVMG02/Yi9tO07jOTcfjClx7Au0JfvZNc1IuL+HaYyO99iOknVGkxdWcz48sT2c2gvHzhgKrlGHMj9DciApkeMnGvfU2ltnYFsYwQ8KS/N7n0dEVGL0I7RFM30ImHzWyyWyHbPo68f6XodwjKw6QOEfqQ0bVbTSb4KavocOr5lKESxRfpfX1/B109DwsrtlYZWNAkOpu8g88tGD5ROXVx/j6gWUBa+eWU6PYxc/fNuIAP7D52szJBie2OXpzjnazbyVOvH10dt10uIM9U/ksb9EZ80IzJSNnT/coBnt/8oUN+DPAXwO+JCJfSNf+YVrQ/r2I/BzwLeCvpu/+K/Bp4DVgDvytD/CMJAkZQdq9O0tl7PU8mnQwQrQFvUdVRlnTWdAAOuvb6XyUnb4pWUL7Hysm7RG243W7gmQrC2LHyNtT5awxSyT005MHiqzKV0uo2wfm93rD1G7xpncTb2E52uXrTO1IJIKrinbPW7cudu1KiHTtXpWu7WcclPrnuz4CZF3vxboVtJfefmbP0Q7rdtZE6ftxhdC0t1r3jB8x9aWYrsnq1SHqzhq6hmBOfcpa/3f6us6K6vo2dDpJSc6wsvaM9XI00QtBXDkck9CuRjqEt0K8623j9O/9WK3QZY/uZTUGnSXy9Biej0JJG7Nqak/qHxPLgNuPU+wQDmm+rc3Xbnxh7f5gaDb1lZ56fhqXjuEX+vdqVddVf62qG+n46OjeB+3Kc32/auyc1tLLt2Zq7SOSVI27LdUsSrRqv4cf2wexiv4up0dwXf7cOfcr8PPvV+55IvkWVHd7okFihSzfATcwXUo2Qf2QePIGUhs3uqU+u2vJRVTTzpaQTDs35LO8Z9eGl9Fgx0Gp7xp7gDhjJBUx3qqO8jifIIPL4AqaycfJqju45bt2xBkcGLlle2zluZQirjV9mGUK2rbdr7prMYDVPXTn+4Fou5nPzNHVD1CgHT6Hbw6RySvo9HVkedvQ3LA0y2dznNgROlPaYhU9gdjvGpD2hFjsm1tLdcdcTNqZBbL70njJwrQbLIvbLPfR8gCZXyPUh2STl2F+zaimw8Iyg7fTFPuyMCfbfGK7c74L9R1z+tXWvvNDq2Mztb7q8mk2M3shB5esrPl1Y3Twg+SWUhk6gxSjKvQxN5ra6QpcPkouJUl5XGwb5XW+Y+gUR10cUE6/bvqm2TVc2aDZDmRz8MbMSz5G8z1zyYlz8PtIddP6TARiQ8y2cc0hMnvb6jM4sCNurBL1j6H1/ogI+Nm36JO8+MqYMqLpqaye3aKTpdwTacHsCE5VEfGm503M0YTaTiHN1ObN1osWg6uKtlM030UmA2iP0aOv47Y/Bhrw42chG+Or2xah0dyHbBuJS+LoJaS+BSffhJ2PmQP87B0YbUNW2hE70SDp9C3ED5FsgFb3jFTTl6ZfTeQH3UIsGon1IdrOzKNBcgt8r4/wo8t9Rnvmb6P1kZFhtidmDPLJw8EXvRVdwxK5+BPGurz8A+5ym30uclK99dC15H0ddL+XYmiMtZ2o0zVI4u5PCKjflbvbOn1NunetxK4Y2zseLHdV/poOY92SuKaT01M76vp+mval7tmdI1CHMCXtPh0S1LWdsNvRkrVS066lHfrodFGdNbPfiWWtPnK6bqm+tjOuXCq6n9W9nUVXVo1JSEBT3c8iE+0RRyL5XO/PHjWs1eNUv6/rTNPffV/qqh39GHRJjCX1bdeGVS4H7fvYJ3SWxvKU7nFVp76clNRmvU2aFid7Ztffa0irH6/VmMMaWpX1+buGjtfBXPecdUtzj9iz9F1XJ9e36Wx7ur5fn+v9nJE1BNsj64QS1+5flef69qzes3VUut7vWfrskO/6u7Je9umTgaS/V4eOlQ7NpJuHET2LCIV+PiPSY8qH463HJKTKFLwBJq/A8Vdtl9KQdERz2w22XjZm0/mbZHufgNjiZm9bSNT2R013NH2LOHgGFxd2pg+SqG8yYnkBXGkKUlmPbWzQwSXi4Eqy7lhaPUvo6tDRFYLfYrH7DJMwA79lO3ynMwDTO7XTpBNqEqqeQ3nJdFdaocevGclgrEzPlw2N2nz6Jr7Y5/DiDzM5+gb58qahotEVpLyIZhNzXM1GppdZ3jZyxWwPTfTnEiqzCKaFoyku0GYjymyCuZJUKJb4OeY7lvrOlbjqFjq6gpZXDFH4IdneD1ibyn2zCh5/1drRHtmkzsbo1gvE8grEhWWyL/asPwaXkGxknF0akMEBMdtOVtsWt/U8sTwwZNIcwfCyufdEUx7H8iBZmB1tsW8uNu2x0cG7DGKNcw4dHBgjbzuzmOLkgCthSRRoBlfx7YnpaeMS2f+RxAYbwG+BC7C4ZvWltQTT5Q4h3yGffhORHEbPo2Fq4WhhDqPnbIzrQ0MrzkMzT/o5cxbW4VXTQeUTQ3VhYe13RZ+JKuZ7SGtxzFrsJfVERrv1qvHitSe45ti+z7Yt98TiHdMzabC0hvkOMd/G13eSDnUPaY+JxT7t4FkKxUgKMtO5ar4HWtuRVDLzBog15PsAyPh5YjYBFBk9aykl25mhw3zH/mdwQL31KjHbJl9cR7Ql+DGuvmOW/G5BErFxygqbp2AnGjc2NUCozCOhvmfz2uUIEcZXoZ0T5zdo62NUlHL3+4mz66hkhMEVKA8opm9yf/p59tln7C48dEV5LBa2fpdLOhVdQxend1WwXTztFt3ufhaxpPIUkuXl9Mq+jnTk1K5p5fS7ixV05n/6B5y5luqiPFBv6Y5RKw0ep3e107qyTj+2vp+tVeWBNjxwX0KG55Uha7vk6Z2Z3qN9tVt2+rrVTr/S3dHrTPqx6VGGILref2eR4npf2D1yqi+6bzq0dLpGnCqHU3qZ1f/FNJbWV+u+ibrekQ9Iqmtqs66N5aq/pa/1eWPUI8tzn7NqzwPXz6uNrlmg+4vnlSsrtNm9R2fLcV2bXI8upTslrZezjohOeRC41bt5pm2nytDz2rJ2Ujkz30+XdQaNdXNyjU3ZiXvgnT4rj8XChgixuIAQkeFl8zvzQ0No4hG8JXhpj5GtVxBtjLQwGxD9Fl0KNxk9gzhzPdDhVaiPiMXuSsfRHKPZmJhvI82x5Xx0xn0fsxEhn6A4fOzyJZg/TZuPmE8OmBxNELXQn7j1ijGIarQg962PAoJvj20As22IC9s1cbjJR1Kikn0oLxsKyLZg8irSTimWx/jWMjlx4YfM1y0siL7ENbVZLv0o+eKVaL5NyHfNWquNTWOBkA3xYUmxvGFWRlcicWn8Yn5sKC3pKnVw1RyKOzcVv0U7uGwsJTj88l10cBHcwHSbxQVCcZGsOUTUwsVCeQXXHiH5DjHbodr+U0TJyOt7FPO3aYoLIIKL+xbcL56QjcmWNxGticMXEGeuFLE8QJpjRFuy5ghZ3jSdZ3kJ4/AaQGZ5YtviIllzz+ZEmBP9kLa8RNYeky/exc3epNn70+Qnf0wcvUAYvYQPU1jeJI6exzf3DU1JgYRjoh+Y8+r4eUNaxUVLEq2BMHweaS0bk/iSUF60sZbcGFu0MeJEP8TlO7TFgREJZAtDI4j5drXGz2Y5OtILLubL6NsTyzvRHtuL7PKk+1vSjp4nS6n0AEJ5YJbYpAtWIloc4GdvsLj0Cnl1E02It1ddhDma7aAaiJOPAxF1A9rxS/guy5sIoZjgF6ZPIxsT8l2mk48hRBZbB/imps3G+FhTzK+Z87sfGpJFE63+6phPlzipOaFjbtHYwPIuMrhgp552liJXprT1EeIyvDMruOQTfKzJ7v4fUIjtkh/Mf8JozDq3lXPk8dGxrTv8yhoKWEcE3fdndux1ZLVW4JmdRfqd8iH7yal71neMdWxxavc8tTOt7lqv/9m6r+5c1VNPXT2NCldoh15fdapM6co4ix4e3FHXkcTZPjjvb+0Q2QPfremXzrWwru22p/Sl57StQ0Hn6Az1gXY92O6HIYfT9Tqnjjw4PufNufeeL3B+36+e2ff7qfl6ztzsy33w2nn1Pnvvad1eNwdd//vq8/TYrX93ns6YM+WeldNvgDzQ3q7/umf194us3X+2j1Zz/oFnpzrJOe/VujwWiE000haX8O0xOn6FkG2hkuPiHM2eo83G5igYK5p8x2iRY4XrnBs1oJmlyyM2kO8SMguWU5fj22OCPzB00y6JfgQ4ogjRFeTVXdCWurzUH0OyZo7me2TNParBBbZO7tAWF4h+SF7dNE9tkmNnx0nWuW+4EnUlmu/R5rs4nzyziwugjVkt2cE1x4Ths0hYMKjuIbEi5hNUcrJ2ThhcoSkPyKu7ljgF8GFmQfeAhCVteZG2vIILcyTWNPk2Idui8ENUMqIvyOsjgh9RF9vAq5TVHcvyXt2iGr9EXt0Dn1hLNaKuoC32KY6/zuLZT1Ms3zU69pRdKGRj2mLfjjyxIeQ7RD+knL3BdOsKebMwpJONmY+vkjdTVDx5c0Je36MudqkufYq8OcaHBVW5nxLG5DACF2ojESgP6LJYqctRBN+Y8290A8sbKp4oWe8Mq35IUx6gWy9bprPxR1gOnyO6AtEdBqrUgytmZScYjTXPEvyQvJ0RxiPLjqatUdP7IcGPjK5cg+VQzXdo/Zj5+CMU9X0EIYrljZB8GxDafJesvkvMxjT5Di4uyQbPABBdjostvj3ChYrYBem7nLa4gA8Lgh8Zag0LVHJ08AzBlcy3XsaHBYNFS33hxwCjz2/9iHx0leAHhOICi9HzRFcwXNykS8vXDK5QD6+mKIGW6OzEIrGlLfbIqzsWNeFfwYUFTXmJxegydbFF1iwgQl2OWYx3Gc7uG423yw1BxrpHiJbPICXHUYi+RF2GCxWuY7+efJR10glJrjHF9kctMUx50fSEiWuPdmYUW+MXLfIDtb6+8WvnrimPD2JLstpN3u/O7oZ1u9B5Z/UP/sz3vvre5Z3FbpIsm6cQwbk7+/uX+YH+52E3fRsPfPita0gjaW9WCOvDk141+WGUvYbI1q9J0lM9XB6OXrry/iRjvCr7vOd9e2WeKv8sKnsfpPO+8pD/P//UdP595/XRw+b62esrdMdDdHkmjwViU3G02ZimvGCZxNPuFV1Bm23RZkMmR1/DaaCoblKVV2iHe+T1IXl9D7+8QTN6kVDsktWHlucxUReIGrc84onZFg4hupymNI75rJ0mn6WK6PKELgTRhrbYxWnLcHGHcn6dttijLvbwYYZKQVbdpC0PcI25GIR8C6djUMXXd4h+lzbbQmJFKA+M1rmxGM8oA1xY4toZTXkJ3xwR8l1CNiZvDkEc0Y8JLiHRNaVu54ypLqPNRogqHkM8IZugIriwNASYTVDxlr1J9ukcioMfkonDxYq22AMCKlliMtkmZCMYHpBXtyyRjR8mJDkDoMm2iL6gXN6hyUdJP7NLUc/ImylNPsG3c9qswEXLSB/FUxf7BD9gMd5nclzhYo1vLW4yuoKsOQaE4Ae4uESdpWSTGExvpTURC/Vps61uBiGtErJRQkeNkRCKpykOLH9qNsK3S5ryIvPxJcrqmMH8Gm02oc3G5O0MxRvqS8mb1Ze0+Q4uzCgW77DYehXRyGx8hS4yupILCIbC8voYgRTCJIbEEEtNKI662AXx+LCgdSVRHDlHNnf8kLq8gAs1KkJd7Kd2KOoymuxin04QcSyHz/eoWIGmGOO0IWQDmvIiTTEh+IKsnVs52YQ63wGUYXOESomgZO1xOqlAdIWlV/RDFqPncIlJejS/jeJYbu1Q7W4Tcw+Z4OInKG7BkuAAAAPSSURBVKojfDBdl42PocOYQuBEW4sewMr3Lkt+gq7/3qJ4GoIf4ZscMgvh02IfBaKU5niU8lWsHNy/A6LJjWxkIxt50kT0PeDc96wSIreBGXDnUdfluyQXeTra8rS0AzZteVzlO23Li6p6cPbiY7GwAYjI51T1Rx91Pb4b8rS05WlpB2za8rjKh9WWzVF0IxvZyFMnm4VtIxvZyFMnj9PC9i8edQW+i/K0tOVpaQds2vK4yofSlsdGx7aRjWxkI98teZwQ20Y2spGNfFfkkS9sIvKXROTrKcHyZx91fb5dEZE3ReRLIvIFEflcunZuMunHTUTkV0Xkloh8ee3aE5kI+yFt+SURuZ7G5gsi8um17/5BasvXReQvPppaPyhPU4Ly92jLhz8uqvrIfjBO528CLwMF8EfA9z3KOv0J2vAmcPHMtX8MfDb9/lngHz3qej6k7p8CPgl8+f3qjtG9/zcsBOIngd9/1PX/AG35JeDvnXPv96W5VgIvpTnoH3UbUt2eAT6Zfp8Af5zq+8SNy3u05UMfl0eN2H4ceE1VX1fVGvh1LOHyky6fwZJIkz7/8iOsy0NFVf83cO/M5YfVvU+Eraq/B+ym7GSPhTykLQ+TzwC/rqqVqr6B5ef48Q+tct+GqOq7qvqH6fcTYD1B+RM1Lu/RlofJd21cHvXC9rDkyk+SKPA/ROTzKVcqPDyZ9JMg324i7MddfiEd0X51TSXwRLTlO0xQ/ljJmbbAhzwuj3phexrkp1X1k8DPAD8vIp9a/1INYz+Rpucnue5JfgV4Bfgh4F3gnzza6nxwOZugfP27J21czmnLhz4uj3ph+0DJlR9nUdXr6fMW8J8w6HyzOw6cSSb9JMjD6v7EjZWq3lTVoJYd5F+yOtY81m15rwTl6fsnZlzOa8v3Ylwe9cL2B8CrIvKSiBTAz2IJl58IEZGxiEy634G/AHyZVTJpOJ1M+kmQh9X9N4C/nqxwP8kHSYT9iOWMrumvYGMD1pafFZFSRF4CXgX+7/e6fufJB0hQDk/IuDysLd+TcXkMLCefxqwl3wR+8VHX59us+8uYFeePgK909Qf2gd8GvgH8FnDhUdf1IfX/d9hRoMH0GT/3sLpjVrd/nsbpS8CPPur6f4C2/JtU1y+ml+aZtft/MbXl68DPPOr6r9Xrp7Fj5heBL6SfTz+J4/IebfnQx2UTebCRjWzkqZNHfRTdyEY2spHvumwWto1sZCNPnWwWto1sZCNPnWwWto1sZCNPnWwWto1sZCNPnWwWto1sZCNPnWwWto1sZCNPnWwWto1sZCNPnfx/gzp+tCQKR2wAAAAASUVORK5CYII=\n", 211 | "text/plain": [ 212 | "
" 213 | ] 214 | }, 215 | "metadata": { 216 | "tags": [], 217 | "needs_background": "light" 218 | } 219 | } 220 | ] 221 | }, 222 | { 223 | "cell_type": "markdown", 224 | "metadata": { 225 | "id": "okKJqlGG77NH" 226 | }, 227 | "source": [ 228 | "Model Class - OrcaNet
\n", 229 | "Consists of :
\n", 230 | "1) Feature Extractor
\n", 231 | "2) Random Descision Forest Classifier" 232 | ] 233 | }, 234 | { 235 | "cell_type": "code", 236 | "metadata": { 237 | "id": "rOR3JsXvnL0Z" 238 | }, 239 | "source": [ 240 | "class OrcaNet:\n", 241 | " @staticmethod\n", 242 | " def extract_features(image_path, vector_size=32):\n", 243 | " image = cv2.imread(image_path)\n", 244 | " image = cv2.resize(image, (224,224))\n", 245 | " try:\n", 246 | " # Using KAZE, cause SIFT, ORB and other was moved to additional module\n", 247 | " # which is adding addtional pain during install\n", 248 | " alg = cv2.KAZE_create()\n", 249 | " # Dinding image keypoints\n", 250 | " kps = alg.detect(image)\n", 251 | " # Getting first 32 of them. \n", 252 | " # Number of keypoints is varies depend on image size and color pallet\n", 253 | " # Sorting them based on keypoint response value(bigger is better)\n", 254 | " kps = sorted(kps, key=lambda x: -x.response)[:vector_size]\n", 255 | " # computing descriptors vector\n", 256 | " kps, dsc = alg.compute(image, kps)\n", 257 | " # Flatten all of them in one big vector - our feature vector\n", 258 | " dsc = dsc.flatten()\n", 259 | " # Making descriptor of same size\n", 260 | " # Descriptor vector size is 64\n", 261 | " needed_size = (vector_size * 64)\n", 262 | " if dsc.size < needed_size:\n", 263 | " # if we have less the 32 descriptors then just adding zeros at the\n", 264 | " # end of our feature vector\n", 265 | " dsc = np.concatenate([dsc, np.zeros(needed_size - dsc.size)])\n", 266 | " except cv2.error as e:\n", 267 | " print('Error: ', e)\n", 268 | " return None\n", 269 | "\n", 270 | " return dsc\n", 271 | " def classifier(n_estimators=100,random_state=42):\n", 272 | " rf = RandomForestClassifier(n_estimators=100,random_state=42)\n", 273 | " return rf\n", 274 | "\n" 275 | ], 276 | "execution_count": 39, 277 | "outputs": [] 278 | }, 279 | { 280 | "cell_type": "markdown", 281 | "metadata": { 282 | "id": "VahSvpMZ8PAL" 283 | }, 284 | "source": [ 285 | "Extracting the features from Spectrograms and converting to Matrix \n" 286 | ] 287 | }, 288 | { 289 | "cell_type": "code", 290 | "metadata": { 291 | "id": "-zdJ9k8ppFCb" 292 | }, 293 | "source": [ 294 | "def find_files(directory, pattern):\n", 295 | " for root, dirs, files in os.walk(directory):\n", 296 | " for basename in files:\n", 297 | " filename = os.path.join(root, basename)\n", 298 | " yield filename" 299 | ], 300 | "execution_count": 12, 301 | "outputs": [] 302 | }, 303 | { 304 | "cell_type": "code", 305 | "metadata": { 306 | "colab": { 307 | "base_uri": "https://localhost:8080/" 308 | }, 309 | "id": "X5vKkEypnRgg", 310 | "outputId": "ffadaa7c-888d-4f87-cc93-a1e2f075abac" 311 | }, 312 | "source": [ 313 | "positive = [] #empty list\n", 314 | "negative = [] #empty list\n", 315 | "\n", 316 | "num_calls = 0\n", 317 | "num_no_calls = 0\n", 318 | "\n", 319 | "train_dir = \"/content/Spectrograms/test/\"\n", 320 | "class_names = ['call', 'no_call']\n", 321 | "\n", 322 | "for c in class_names:\n", 323 | " images = [x for x in os.listdir(os.path.join(train_dir, c)) if x.lower().endswith('png')]\n", 324 | " for image in images:\n", 325 | " img = cv2.imread(train_dir + c + image)\n", 326 | " img_path = os.path.join(train_dir + c + '/' + image)\n", 327 | " feat_vector = OrcaNet.extract_features(img_path, 64)\n", 328 | " if c == 'call':\n", 329 | " positive.append(feat_vector)\n", 330 | " num_calls = num_calls + 1\n", 331 | " else:\n", 332 | " negative.append(feat_vector)\n", 333 | " num_no_calls = num_no_calls + 1 \n", 334 | "\n", 335 | "\n", 336 | "x = np.concatenate((positive, negative), axis = 0)\n", 337 | "\n", 338 | "z = np.zeros(num_calls)\n", 339 | "o = np.ones(num_no_calls)\n", 340 | "y = np.concatenate((z,o), axis=0).reshape(x.shape[0], 1) \n", 341 | "\n", 342 | "print(\"x shape\", x.shape)\n", 343 | "print(\"y shape\", y.shape)\n" 344 | ], 345 | "execution_count": 37, 346 | "outputs": [ 347 | { 348 | "output_type": "stream", 349 | "text": [ 350 | "x shape (241, 4096)\n", 351 | "y shape (241, 1)\n" 352 | ], 353 | "name": "stdout" 354 | } 355 | ] 356 | }, 357 | { 358 | "cell_type": "markdown", 359 | "metadata": { 360 | "id": "kFZ3cV0W8e0-" 361 | }, 362 | "source": [ 363 | "Preparing Training and Test Sets" 364 | ] 365 | }, 366 | { 367 | "cell_type": "code", 368 | "metadata": { 369 | "id": "QKd6db2U1sI7" 370 | }, 371 | "source": [ 372 | "x_train,x_test,y_train,y_test = train_test_split(x,y,test_size=0.10,random_state=42)\n", 373 | "x_train = x_train.T\n", 374 | "y_train = y_train.T\n", 375 | "x_test = x_test.T\n", 376 | "y_test = y_test.T\n" 377 | ], 378 | "execution_count": 43, 379 | "outputs": [] 380 | }, 381 | { 382 | "cell_type": "markdown", 383 | "metadata": { 384 | "id": "iacehABg8l0o" 385 | }, 386 | "source": [ 387 | "Creating the Model & Training Phase.
\n", 388 | "Model Achieves an 88% Accuracy on Test Set" 389 | ] 390 | }, 391 | { 392 | "cell_type": "code", 393 | "metadata": { 394 | "colab": { 395 | "base_uri": "https://localhost:8080/" 396 | }, 397 | "id": "tUKSlydlnUwi", 398 | "outputId": "aeb8cb60-2337-49c0-fd7b-f5cce26ec14b" 399 | }, 400 | "source": [ 401 | "model = OrcaNet.classifier()\n", 402 | "model.fit(x_train.T,y_train.T)\n", 403 | "print(\"Random Forest Classification Test Score:\",model.score(x_test.T,y_test.T))" 404 | ], 405 | "execution_count": 46, 406 | "outputs": [ 407 | { 408 | "output_type": "stream", 409 | "text": [ 410 | "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:2: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n", 411 | " \n" 412 | ], 413 | "name": "stderr" 414 | }, 415 | { 416 | "output_type": "stream", 417 | "text": [ 418 | "Random Forest Classification Test Score: 0.88\n" 419 | ], 420 | "name": "stdout" 421 | } 422 | ] 423 | }, 424 | { 425 | "cell_type": "markdown", 426 | "metadata": { 427 | "id": "tY5NiNBE8_pq" 428 | }, 429 | "source": [ 430 | "Analysing the Model Performance through Confusion Matrix : " 431 | ] 432 | }, 433 | { 434 | "cell_type": "code", 435 | "metadata": { 436 | "colab": { 437 | "base_uri": "https://localhost:8080/", 438 | "height": 405 439 | }, 440 | "id": "dVaVwU8enazm", 441 | "outputId": "a532a15c-2cee-470f-e175-ab3a17eb5063" 442 | }, 443 | "source": [ 444 | "import seaborn as sns\n", 445 | "print(x_test.shape)\n", 446 | "\n", 447 | "y_prediction = model.predict(x_test.T)\n", 448 | "y_true = y_test.T\n", 449 | "\n", 450 | "from sklearn.metrics import confusion_matrix\n", 451 | "cm = confusion_matrix(y_true,y_prediction)\n", 452 | "\n", 453 | "f, ax= plt.subplots(figsize=(6,6))\n", 454 | "sns.heatmap(cm,annot= True,linewidths=0.4,linecolor=\"red\",fmt= \".0f\",ax=ax)\n", 455 | "plt.xlabel(\"Prediction number of y\")\n", 456 | "plt.ylabel(\"True number of y\")\n", 457 | "plt.show()" 458 | ], 459 | "execution_count": 48, 460 | "outputs": [ 461 | { 462 | "output_type": "stream", 463 | "text": [ 464 | "(4096, 25)\n" 465 | ], 466 | "name": "stdout" 467 | }, 468 | { 469 | "output_type": "display_data", 470 | "data": { 471 | "image/png": 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\n", 472 | "text/plain": [ 473 | "
" 474 | ] 475 | }, 476 | "metadata": { 477 | "tags": [], 478 | "needs_background": "light" 479 | } 480 | } 481 | ] 482 | }, 483 | { 484 | "cell_type": "markdown", 485 | "metadata": { 486 | "id": "OYPni9407Vkt" 487 | }, 488 | "source": [ 489 | "" 490 | ] 491 | }, 492 | { 493 | "cell_type": "markdown", 494 | "metadata": { 495 | "id": "XHrvUBmj9KDs" 496 | }, 497 | "source": [ 498 | "Confusion Matrix Analysis \n", 499 | "
\n", 500 | "True Positive : 13\n", 501 | "
\n", 502 | "False Positive : 0\n", 503 | "
\n", 504 | "True Negative : 9\n", 505 | "
\n", 506 | "False Negative : 3 " 507 | ] 508 | } 509 | ] 510 | } --------------------------------------------------------------------------------