{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "7.2 Timbre / Remix.ipynb",
"provenance": [],
"collapsed_sections": [],
"toc_visible": true,
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
""
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "NAANqGguLDv9",
"colab_type": "text"
},
"source": [
"# 7.2 Timbre / Remix\n",
"As we saw (or rather, heard) with the **7.1 The Speaking Piano**, there's a lot more to sound than just pitch. We can think of any sound as being made up of many different frequencies, and the relative amplitudes of all of these different frequencies is what makes a given sound sound like itself — like a piano, or a saxophone, or a human voice. At this point, you're probably pretty familiar with the words pitch and loudness, but what else is there to describe about sound? Lots of things! Sounds can be \"dark,\" \"bright,\" \"soft,\" \"rough,\" and much much more. Unfortunately, all of this other stuff is generally lumped into one exceptionally inarticulate word, [***timbre***](https://en.wikipedia.org/wiki/Timbre), as it's used to refer to *all* of the sonic qualities that *are not* pitch and loudness — if that doesn't tell you something about priorities in Western musical systems then... In this notebook we'll take a closer look at the spectrum and the concept of timbre.\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "yS1Lr5lQOoUg",
"colab_type": "text"
},
"source": [
"# Setup"
]
},
{
"cell_type": "code",
"metadata": {
"id": "vEAQufPVOpjb",
"colab_type": "code",
"outputId": "a9608c76-f5be-494f-ecba-ce779bc15cc1",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 295
}
},
"source": [
"# install external libraries\n",
"from IPython.display import clear_output\n",
"!pip install -q git+https://github.com/davidkant/mai#egg=mai;\n",
"!apt-get -qq update\n",
"!apt-get -qq install -y libfluidsynth1\n",
"!git clone https://github.com/davidkant/mai.git\n",
"clear_output()"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"\u001b[K 100% |████████████████████████████████| 11.0MB 3.5MB/s \n",
"\u001b[?25h Building wheel for mai (setup.py) ... \u001b[?25ldone\n",
"\u001b[?25hSelecting previously unselected package libfluidsynth1:amd64.\n",
"(Reading database ... 131284 files and directories currently installed.)\n",
"Preparing to unpack .../libfluidsynth1_1.1.9-1_amd64.deb ...\n",
"Unpacking libfluidsynth1:amd64 (1.1.9-1) ...\n",
"Processing triggers for libc-bin (2.27-3ubuntu1) ...\n",
"Setting up libfluidsynth1:amd64 (1.1.9-1) ...\n",
"Processing triggers for libc-bin (2.27-3ubuntu1) ...\n",
"Cloning into 'mai'...\n",
"remote: Enumerating objects: 87, done.\u001b[K\n",
"remote: Counting objects: 100% (87/87), done.\u001b[K\n",
"remote: Compressing objects: 100% (59/59), done.\u001b[K\n",
"remote: Total 649 (delta 54), reused 58 (delta 28), pack-reused 562\u001b[K\n",
"Receiving objects: 100% (649/649), 23.59 MiB | 20.79 MiB/s, done.\n",
"Resolving deltas: 100% (387/387), done.\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "sBtb2Pi9OqC1",
"colab_type": "code",
"outputId": "1737261d-ee2f-4ac5-8b31-9e837e068fd7",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
}
},
"source": [
"# imports\n",
"import mai\n",
"import librosa\n",
"from librosa import display\n",
"import functools\n",
"import numpy as np\n",
"import IPython.display as ipyd\n",
"import matplotlib.pyplot as plt\n",
"import warnings\n",
"warnings.simplefilter('ignore')"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"Using TensorFlow backend.\n"
],
"name": "stderr"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "A6UglrFBfI1l",
"colab_type": "text"
},
"source": [
"# Load a soundfile\n",
"Load a soundfile to work with."
]
},
{
"cell_type": "code",
"metadata": {
"id": "_Z26cJr8Ye92",
"colab_type": "code",
"colab": {}
},
"source": [
"filename = 'mai/resources/audio/rollersample.wav'\n",
"y, sr = librosa.load(filename, sr=None)"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "A0y2_UJtZEdx",
"colab_type": "text"
},
"source": [
"# Hello Spectrogram"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "zt___B1LawKl",
"colab_type": "text"
},
"source": [
"First let's plot the waveform. Do you have any idea what this sounds like?"
]
},
{
"cell_type": "code",
"metadata": {
"id": "HA88kAEMazmN",
"colab_type": "code",
"outputId": "da26b4fe-400c-4673-84ec-49aec600fecb",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 261
}
},
"source": [
"plt.figure(figsize=(12,3))\n",
"plt.plot(np.arange(len(y))/float(sr), y)\n",
"plt.title('Waveform')\n",
"plt.xlabel('Time')\n",
"plt.ylabel('Amplitude')\n",
"plt.xlim([0,len(y)/float(sr)])\n",
"plt.show()"
],
"execution_count": 0,
"outputs": [
{
"output_type": "display_data",
"data": {
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FB4C1Oh3/tvX73sczX6Hhosr9ocwrLBfUoyF62NHK7rt19ZMAuW5ynOXhbOBK\nfQ63mPJgFzMKsf/kDZy+Iq5nX6WdnlbTB9L//f4IFv16FBksy9obn4O2Wn5bq7X2Wsz8V3nti0Ss\n+OOkTVfQWyNiNMy8Aym/qBxbktIxZf4Oxo4LNh/8aH2HBtMDMRe+6lty4OtYU8PqgDpd3TWvgmF0\n3vhhU0iNelulr567dgvnr93C3uNZhs9rRVWNoXY9AMz/KUWW9xKUQ11VVWUIsHJzc1Faqq46k1JZ\nO9SgtVHQKebEkrLIBFfOWsr5HMl1UBsztoc3KTmscrnIkXpiHK8WlVaioLgCH/yYjP98mYT3vjuC\n2lodnv94D1b+dQo763Mb+c7GguIKfMcTLOogLKfZsMoXz5tu2HtZYJ61ONZe02/VDxmf4ghE9zEM\nFR83m6w4a/l+TJm/w2I7a242u3lyMLlU1wh4SDKidP6jLZ2+UoC3vj7E+D3j33v6kt2S3octP9fa\n24yQgKusohprd14UFbgKcfSCsIloTF5dccCwGMfclYn4+n9ncORsNv7c23C/Mh7ByMgpwbQFOyVV\n2hIbA3BVrrCHzUlXVXF/3pGSiZnL9mH2igMW39NXYwKA/1vFX4LUVteQisoazP8pBd/87ywOn83G\nP4fSscOsTKhxSqKU1BPe1UgeffRRjBs3Djk5OXj22Wdx4sQJvPHGG1a/oS1ZeyCsPX4aDUzu2Eov\n/SsW3026uLQKzXzc7NQax8J25JSa1GUs+Rx/70lBSQVmfmo6AePqjWKTnus9qVkY3quloKj0zFWe\n4TOdsFSm7ckZuLNfK0GB8Lrd/KXhhKy0J4fb+hxijrdjqnBivqAKWy5nuRUlv05dYf6blFVU4+dt\n5+HBMdl06+F0fLruOOY+2hMdWvqLfu+mQs6zi+1ybG0q46fr+OtBf7w2FRczCnE+4xbuHdAaqRfy\n8MiI9pJHKPOL5OlYqK7RYd/x6xYjW99uPotvN59F63AfBPt7SO7dPHk5HxVVNXB11hp+9+Np3CkL\nJy7lmaxpYS/XskuwdqewspjGqmtqLUoGS6V/8JFjeW97VPn44s+69DeuuGbRr8cwe2IPxu9VVNbg\nbHoBhgf7MH6f9+iOHTsWK1euxH/+8x+MHz8eGzZswNixY4W03e52HrWuR8baXCTzXkq51oy312It\nfCewkJUa7eHYxVzVLRPLdlyuichNthWuSbZZ9WXp2ILbFKMSR/oUJqbhPLF0gOAZby9/th/lAnqz\nhdRQ3n+SuRa9UEIrCpyvz1vnWsRFyg1Dav61vmJA8rm6yZr7T95oyGtncLZ+9bH5P6VYXI90Oh1+\n23kRFzMLUVJWhZOX8rDzqDylU3SiAAAgAElEQVT1rNXs/e+PWHzuzb+2RVCQy1Nfm42Qyg76+Rb5\nRRVYsiYV/6ZkGK4RUi369ajgyX7Wunxdvuvt9MW78dn6EwDqCgwsXcv9QLLt8DWs+OMkb+AtRW2t\nDtuPXDPku29KvIJ5LKMlfKxZmKaqugZbD18T1Ekj1f+ttF0KkjmumO/M1QIsXZvKOPn0uy1n8QnH\nwkWsXRR//PGHxWsVFRU4cKCua/++++7jbLASuFZh48I3YUCn09k1pzhNpkmSfPgC9xV/nMSgbuF4\nYkwnu7SHSVV1rWHlrdG9IyXkE8qL7b6ZJ1PPjK2wTehhs16mXPGU8zmIDPUWvP0tK0uFMSm6XQlf\nL1erfvbDH1Mw/9l+grY9cjabt2dOp9Nhe3IGurUNREgzT87tjK85Umvlf7/lHC5mFOKAFQ8YNbW1\n0GrrFtqpqKzB2l0XsSMlE1uS0tEyxNuklmtjlpZVhLKKani6uxheKzfLm562YCe+em2orPeLtKxC\nhAd5wsvofeV226gzqLK6FgXFFdBqNfCz8nMD1A35/7X/Mh4fHc26jRydR3IuIX60fiKdkHSKk/Vz\nnY6czcarE7qjc1QA43ZSHrL+2HcJGw9cxc/bL+Cpuzpj3W7rr8fWjJ4+s6ghjWneE/GcBRxSzueg\nZ4dgq9oG1HUEFZZUwM/b9qPifPPtjqfl4XhaHhK6hgOoy7E/npaLE5e4F7Bi7aHev38/9u/fj40b\nN2LRokXYtm0btmzZgo8++gjbtm2z4lewPVsscrIp8QqmLthp1xm1gb7udnkfIcdrT6qy9ZX3G9V3\nVtM8SbYeaqnxvpARgb/2XcbB09J6XoXaeOCKbPv6wygHkg9XHrhYUirWZN8qE5zKteKPk7x/v+Rz\nOfhl+wXeZc3/OWQ6N0KO3HxrgmmgYdK2TqfD9CW7DXWDATSZYFrvyLmGERydToffd1kOvc9dmShr\nz+yaHRfx4tK9Jq+lZRVizrK9ss3ZMA629qZmYdby/Xh52T58u/mMpFxdvsvZcZ4ARQl/H7gielXF\nRb+yl028IqEX3XiBptUbT1u9HyH4iiq88+1h/LD1POv39b37AHCWLwWQhZwdKXL6dN1xrPr7NG+J\nZdaAeuHChVi4cCE8PT2xfft2LF++HF988QW2bt1qqPihNhc4yoXx+Xkb84mifyK050InQf4eorbf\nkpRuVf62rWpYy8l45ryaKo+w3SiY/g61AldgSr9ZjKkLdvIOzf2x7zJW/XVaFek4juCHf84ZFgyx\nhpglq8/zXIOMc9S5JoLpcxPV4NDpm5gyfwemLtipdFMU9/uuNJy6nI+M7BLW1IicW+WYtXw/tkuY\nMM7kj72XsCOlLrXmk7XHceZKPjZZsSImn13HGib87Um9jq2H634PaxZK4it/+L9EdaXyAXUVnH75\nl7sGtBhCFkixB76Fc+RYlfRy/eqITHXZ1+1Ow7s811IV3eIN0jILBcd/vDnUWVlZcHdv6DH19vZG\nVpb4GqGqwhCHbE/O4HwSF5pqsPc4+7GpqKqxKh+VL5Xlt50XRd309YQORR09n4Mp83cIrttYWVWD\nKfN3YNqCnZJnj8sdM2bm3saU+Tvwf6sO4uft7E/bGw9cwX++TMJtlkCM7dgxLXk9a/l+zPv6MIpu\nV3KubqXvDV7BMYPcuHYsBTjCXMwsxHvfJ2PlX6fsNj9BiFcZZsazUrDZ34hY6bKxKymrwuI1x/DW\n14fwn6+4c1mtHRFg89f+K/ixvodQ/zD9b0oGzogscSjW77vSsPXwNSzfcIJ/Y5HkHImSU4rA5bKN\nrdlxAVPm78DNAtPcdVsvwCJUQXEFPv/jpE2Xnn/vuyM4eTmPcfR7U+JVXLlRjCnzd6iqw4DL66sO\nilpfgjegbt++PSZMmIAFCxZg4cKFeOyxxxAZGSmpkWrFdbMVWiLvm/+dZQzMf9l+AdMX78b0xbtF\nD4dwJcFLITSgXlY/lGNct5HLs4t3G/b/6ooDyC0sw+Gz2SaTNnU6nehgm6tutlD/+bJu9aeb+aWs\nk9rW7biA9XsuITP3NrYdZu5lYjt0TMNmhSV1gfTMZfvw1leHWB/cjIeTyxlWmcorLLeoHUu91MLc\nzC9F0umbqr2B85GaQ03sT//JzC8qxxd/nrR62Wo+C389hvV70kzSwI5aERBy+fXfCyZl0MSYMn8H\nft5+3qpJcY5En6b1fysPIjOnBBWVNap6gAfq6mf/ue8y1u66iEwRS5eLsWQN/0qWW5LS8TbD5MoL\nGYWyLtAkldi28JbN++CDD3DgwAGcP38eOp0OTz31FAYOHGh1A+1t9d+nMHF4B3h78KepmKcUGA/V\nFAtYhlbv6YW7sGr2EJMSNcb1og+duYnoVs1Yf15KPU0xrPmwV1TW4ELGLXSMbAYXZ8vnMaZhwTmf\n1wWBHVr6Y+6jPQEAWw6lG0r/fD13GOv7JZ1pWOlu8ZpjeOuJXnB3NT1t/9h7CU5OWtzdP4qz7d9u\ntuwpSL9ZjMhQ0xI4325qyFVjyzNnC2SFVHqprdUBTtzblJRWWfyef+23HLI7cSkPsW2DeN+T1Jn/\nUwrn+aYmNbW1cNLWfcbkqLRC7OvqjWJMXbDD8PB96Ey2LOfeO98ctsjl1Ofa1tTo8OO28zZbZMZa\n249kYPuRDCx/eZChXKMcHSRqpR+98PVUX3qsvmLW9iMZWPnqEMXakc4w/+Kn+tRbR7lGm+PtoT54\n8CC0Wi2io6PRqVMnuLq6IilJ2hrv9pR46ib+MFsSfNXfzMn95kGS8Vr232w27Xnmm3RSdLsSFzML\ncT3vtsV+83l+Vs6JYFysyaGevmQ3lvyWitV/My9nzDU8YpyHJLSOpnFO8o38UmxiyLn7a/8VQSsX\nMk2wfPsb7lQZpvcDgNQ06yfTnBSwEmYVQy82Uy8lX2knYmmuDVeIk5PagiIinvlzN1MpLrGucpTm\n/GrTGVWfN4mnbqCmthZbD1/D7M9FpDw5qCIVrGbIpqq61qYl/6QQu1KrWvAG1CtWrDD8++STT/Di\niy/im2++sUfbROEa+uYrdaKnT1UAwJg7+8yiXYb/n+TZZ0ZOCT74IRlvrE7Cyr9Mg8/jaXmsQ89S\naoD+vf8y1tcvgVyr0yEtq5AzL7xGQrrAkXM5OHMl3yJZn6/9TAuAsC3ry2RT4lXWVJH3vz8ieD/G\npszfgSnzd+DDH5MZqxaI/ZscMupVZ6ofvFZA/tgbq5MErzZWVlGNKzeK8P73R0xyrAmz7Ftl2Jyk\nvslQ5vgmOBLH89WmM3YbgVSjH7eex1Mf7cKvMk76I9ZbuvY4KlU4+rXo12PIuVWmupQZPrwpHz/8\n8IPJ13l5eVi8eLHNGmQLObfKcfl6EaLCfHgrRWw9lI5fdzAHPMbxJ9+MZ+OeQ6Y6mR/U9+RGBHvh\n3al9DK+/+aX1vf8b6suS+Xi6ws3FCd9uPgtvDxd8OoM5RUfqKnIL60sFiRmeWfjLUXz12lCT1976\n+pCofegnc/13Wh80D/IyvJ6WVYSth69hZHxLwfsydiGjkLFofmbubTQP8jIsaLGXp5Tgqcv5uJZd\ngu7tghARYll7+WZBGdbtTsODg9saXmN6SFi27gReGheL7u24Uzqe/3iP4f/mOdaE2dqdaVi7Mw3D\nerbAoyM6qKqCjN6nvx932KFPwm5T4hU8/0BX6HQ6Q0oPIUopq6hW5UPea18kom0LX7wxqZfSTRGM\nN6A2FxgYiEuX5FnsQU58oeF73x1Bp1bNMHN8LOd2bMG0XpY+uBLZPjYZObex8cAVdG0TKNsy379s\nv4C+nUMB1OX0Jp66YfjamFx1u9/++hD8vN1wR1wLQdszpbScSy9Ax0j2vHImb36ZhFWzh5i89uu/\nF6wOqNl8/sdJtH2uP1b/fRrnBJTP0admbEq8ytqWTYlX0a6FH7w9XFBaUY2Pf2OeyKFf1Obdqb2t\nbD3hsiMlE9fzSjH9vi6S6lXbSm2tTjWLGRF5HL2Qi2n1FXoeHNwGd/aLUrZBpEl7+bP9SjeBVVpm\nkc1X25STRsdTJmD27NkmvTfXr19HdXU1fvnlF5s3TqicnGLcLq+yKH5vK8tmDsT/Dl7F5oPpsu73\niTHR+JajRNXqOUPgpNViyvwdovfdIcIPi18egpychvy7t78+xDgxQCkThrXDiPiWJucb3+8aEext\nUYruufu6oFd0iMW21hw3QpT2n8d74b3vrEtnIur39dxhOJdeILiKEiFEWX8vvpfxdd6AesOGDQ0b\nazTw9vbGgAEDTGpTi/HBBx8gNTUVGo0Gr7/+OmJjG3qMDxw4gCVLlsDJyQmDBg3C888/L2ifOTnF\nKCiuwKzl6n3SkkPHlv54aVysyRC/GPOm9UWroIbljv/zZRIyJeRs20qArxseHx2Ns+kFVj+06B8+\njFFATQghhBAprA6oFy1ahFdffdXktTfeeAPvv/++6EYcOnQIX331FVauXIm0tDS8/vrrWLNmjeH7\nY8eOxVdffYXQ0FA89thjePfdd9GuXTvOfd4960/R7SDAjHGxNqtvrRY+ni4YEBuOzQfT8dx9XTgX\nTCGEEEII4cMWULPmUG/btg1bt25FYmIisrMbJtVVV1fj8GHxq/IBQGJiIoYPHw4AaNu2LQoLC1FS\nUgJvb29cu3YNfn5+CA8PBwAMHjwYiYmJvAE1sU5jD6YBoLi0ytDDTcE0IYQQQmyFNaAeOHAgAgIC\ncPLkSfTr18/wukajwQsvvGDVm+Xm5iImJsbwdUBAAHJycuDt7Y2cnBwEBASYfO/aNeZV6gghhBBC\nCFEL1oDazc0NcXFxWLdundX50nxo2WRCCCGEEOLoWAPqxx9/HN9//z169uxpUnVBp9NBo9HgzBnL\nZZz5hISEIDe3YWWe7OxsBAcHM37v5s2bCAmxrNRACCGEEEKImrAG1N9//z0A4OxZ9jJuYiUkJGDZ\nsmWYMGECTp06hZCQEHh71y18ERERgZKSEmRkZCAsLAw7d+7EokWLePe5bv5dyM0twZUbRfjwxxTZ\n2toYde8QjGljo+Hp7gIA2JOaxVmmz5F9/EIC/LxN63pTlQ9CCCGE2AJrQP3JJ59w/uCMGTNEv1nP\nnj0RExODCRMmQKPRYN68eVi/fj18fHwwYsQIvP3225g1axaAuoofrVu35t2nq4sTXJy1CG3mybut\nXL56bSg2Jl7Fhj3yLnATE9UMp65YLs1t7Ou5wwQFhi89GItP1zVMPIwI9sJ7z/Q3qUOtNi89GIvu\n7RtWBdTpdJhavwACmzkTe+CjX0zrtz44uI1FME0IIWrz+mNxiAjxgk4Hq8uhEkLUgTWgdnJysskb\nmpfgi46ONvw/Pj7epIyeGF4eohd9tMprj/SoS4GROf/bzcUJj43qiP9beZDx+w8NbYehPYWtRAgA\nHSP9Tb5+e4rlSnty5bC3DvdBm3A//JuSIWj7j57thzlmS2R3atUM3doFmrwmZDnoti38LF5T08pj\nn80ciBdYFhx6dEQHRAR70YIOhNXXc4cJerAkjqd5kBfaRVhevwghdT6fNRguzlrDyqJqxxqFGlfy\nKCwsxNWrVwEAbdq0MaRpqIn5Ih5sJgxrx7m8+NQ7O6FTq2bQaDSMC8Xol8d2c5UngO8bE4ppd3bm\nXV442N8dbi7CH3I83JwxqFtzHDh5A+9N6w0tQ3AqNZx+aGg7jO4Tafj60ZEdeHvPu7QJQJC/h8Xr\nLz7YVVAAbc7F2fTv7uflKnoffLzcnfHR9P544eM9go5Zx5b+OHftFj5/ZTDr31WjAQZ3bw5nJy2+\nnjsM1TW1eHrhLsZtP3ymL5b+loqbBWWs77nouf74bss5PDysHd78MklAK4leiL8Hpt7VCX7ebphr\n9qCnBtZ8Loh6zZnYA96eLgjys81kf0LEGty9OXYfy1K6GSbenNxLVMyjBrxR4bfffovPP/8crVu3\nRm1tLdLT0/HSSy/hkUcesUf7ZDOsZws8NLQdXF2cOAPqhK51dbBLy6stvveOUS9vfHQIfv33Aut+\n3pnSGyH+Hli3Jw0BPu74bafpe37+ymC4uVqeLG9MisP7PyRbvN463Jf1vcy99GDd6pNPjInGE2Oi\n2TeUGFEPE9FjrvfKQ90tXps1oTvcrXhA0f89XhoXi0/r62q/M9WyJ16qZTMHAQBWzh6ClPM5iG0b\niOeWsA/PvvZoT8P/q2tqGbf56rVhJl+zBd5fz63b7oOn+zL2Ut4/sDXu6h8FjUaDlx/qxv2LEBOR\nod54c3IvODsJexgnRA4dIv0ZOzgIUcLz93dFXMdg1QXUbZoLj3nUgjeK2bBhA7Zv3w4fHx8Adb3V\nkydPdriAum9MGFzrn3aC/NyRW1jOub2OIdpsGdLQM9/MhztHV7/tI8M7oFanswiomYJpoC6F4cNn\n+pqkfkwa1REBvvy9GSH+Hnj/6T6Ce+ulxNP/ebyX4Xga690pBIfOZDP8RF1uM5NO9b3+Qn352lCT\nG1L3dkF4cmw0yipq4Ospvof6s5mD4OSkwcWMQkS38sdTH+1i3M7ZSYvenUIBANPu6oQvN/JXuhF6\n42Tarq3RBUWj0SC2bSCOp+WZbHN3Av88A2KJadKq2kwe3VHpJhCZRYZ6g0Jp4JWHumHJb6lKN4MA\niOsYLOv+vpwzFNM+kpai4erimJ0cvK0OCgoyBNMA4Ofnh4iICJs2Sm6PjuhgEpy0CPLi/Rk5U6TN\ng6UurQNYtqxjPsFyaA9hPcGPjGgvOJgGpOVQs/WYd+QIjju09Ld47bOZA3nTXUy3H8QYfA6MbY6R\n8S05f/bJsZa99f+d1gee7s5wc3FCTOsAi+MXEcx8rlzKKhLUXqZ4+rn7ugj62Sl3djL9eqzp1742\nSG9pCmZP6K76YNrX0wVDuosfASLq9vaTvSmFB0CXNoF41wajiUSceU/Ey7q/z2YOglarEXyPY3NH\nT8eKMfV4e6hbtmyJ5557DgkJCdDpdEhKSoK/vz9+//13AMC4ceNs3kip7ogz/eMIuaB5upsemtkT\nLFMVmAT4uhlSLox5uDmjrKIujcSfp3dbLG8PF5SUVSFKRFoIIOyhYfKojnBx1uLI2Ww083XHrqOZ\nnNsP6BqOH/45Z/h60XP94erihMvXi9A+wjKghsj+GvO/ixjx0SH45n+mZQKb8zxczTVK3zCmEdhu\npnNNSI9AdKQ/wgNN22YeQNN92TqdorgfaAlxdPcPaiN7FSqperQPwmMjO8K7voBARLD65mLJzdPN\nGR+/mIBnFu1WuikW5j/TFyEyV0fT3599PF2s+nlnJy1rmqQj4O3OrKiogJ+fH06ePIlTp07B29sb\ntbW1SE5ORnKyZa6vI3M1muCm1WhMciuF3oQXPZeAyFAfi9ffmBQnvYEsPp0xEF/OGSo63UFID3Xr\ncF8kdA3HjPHdMHlUR6yeM8SQ18vExVlryH16eFg7BPi6w9vDBV3bBDJu7+TEHRXKmUfl7uqMt57o\nhdCAuotIr2juhYN8PF0MNbulGGI0wvDsvTGsD3SDujU3aSsfiqeF8/eu+2wYT6JVMzWuIbv0xQEO\n23OkBnf1j7L5ewzu3hyfzhiIu23wXh0kVCT5bOZAvPhgLJr5uMHF2bEmmonlpNWgc1QzOGk1mHpn\nJ1X+vpNHd7QqmJ5wR3vW73WOahid5gsteHvGHfTmxnvX/vDDD+3RDpsZP6StxWtsPXsDjQIaoCHg\nHNu3leR2NA/ywp39WmFT4lXelA9riEmb0BNy0w5pZlqRQ0hKyZuTexlW1GQz74l43Mgv5Z3F2zLE\n25BeERkqvUcjKswXHz7dV9C27RhK8hmIONyTRnYw9OxzXWgCjEYuHhnOfuHSG8GT4qI2TOUS7WFM\nn0iM6dsKKedz0L9LmN3fXw4T72iPXzgmQduDr5crHh3ZQXB5zKZuwh3tceDEdaRnl6B7uyA8MIh5\nDokY9yREITqymUXtfb37B7WBt4f0TgBz/buEoWOkP85nFIr+2UdHdJClY8IRdG8XhMdGdrCY82SD\nSrtWCfB1Q35RBQIFzMliMrh7c4tiDGP6RmLzwXTEGHU6Mo3CG/c+twrzwVtP9MK73x4x2eaehCis\n33MJPdrLm9dtL7wB9R9//IHvvvsOxcXFJj2a//77r00bZg0/L1cU3q40fD2oW3OMYQiGq2tMz+zx\nQ9oiPjoEAWZljPp0DsWBkzdM8q+luH9QGwyMDUcwQ9k4RQj4gHu4WZdiwZdW0yrMB63CLHvyzT00\ntJ3dZx8vfGkgvliXimfuiZFlf8bHgmmya8N2Df9nKi1obPbEHujUStxkTqX5KJTzHehXN0oyyOyB\nWagubQJw8lK+zK0Sh28StFguzlpUVTMPrRqnp/G5JyEKf+2/ImPLGo/IEG9oYsORvv0C4nlGw4SY\nNaG7SdBi7qvXhsqen/3MPTHoFR0MJ60W+09ct2ofXHOAuCaxi+Wk1aCmVpmoddKojjhw8jqeu78L\nY9WgRc8lMJbhtbe3n+yNc+m3GDv1Qpt5sJZm5RqVvn9gG8S2CTRJ6QwLsOz9/vDpvkg+l43W9fFU\nVJhlXHVX/yiM6NWStWiDPS1+PgFf/HkSF0Q8RPJGSytWrMB///tfhIWpv2enZ4dg7DTK8TWvUax3\n4pJppQSmoBuoKzs3oldLWXpGgbo0ErlzlmzpdRumqQjl4eaMZ++NwRd/nrLbJK3oVgF4Y1Ivzm3Y\nbltsPcv9YkKReOomWjNcRBp2yn8zXPx8AtxcnCTlkitFqZqibNcBoV4e381uC6t0atUMZ64WWPRm\nyV1C6uFh7fDj1vOM37s3IcqitCjbqBrnKE4jNqR7c/SNCcOxi7nYkpRu8r1hPVugRbA3Okb6I7pV\nM/TuFCpLfXzjYHreE/E4fqUARcXlCAvwRESwl+zB9MpXh5h8dsQ+1EVH+uOVh7tzjp7e3T9KtoD6\n3am98cZq+9fgX/JCAvy93TgfHOR+ILaWt4cL6xwetr/TBzwjus5OWs5iBHqBfu4Y2Zs/5U4NwTRQ\n9zfrGOkvb0Ddpk0b9O7tGLNxO0b6mwTUbNeX1yfF4QOGWs/mnJ20gnpR9d5hWI1QzfhyqFuHC//d\nbal3p1B0aR2grmFDlnNreC/mNIxpd3XGxOEdOIdjB3QNx47kDDw6ogPrNlIvzNPv64LP/zgpaR9q\n0S7CDxcFXOz6dpbWGSAkUNGnc4nxzpTemPf1IZPXwgI9ceZqgcW2QspmCtEiyAtPjIlG6+a+rAH1\noO7NkRAbjhfrV/hcNXsInFhutjGtAzB5dEfcLqvCut3qmgRnK28/GW+YJ9OhpT9G947EzGX7DN9/\neFg7k7xZWyw21SrMB726NkdOTrGk/bQI9kJmzm3G75k/iIoZEVv60gBBc3qsSU9hW4REiQf2bm0D\n4a/yikFCmVfPenBwG7Rr4cfY29xUBPtZjhR3bxfEuj1v182ECRMwZcoUfPLJJ/jss88M/9TIPD5k\nqwFsq14V4zrVjoBvdExMCT5bU1UwbQWNRsN782jm44aPXxzAO1mST0JX9gBSqwGev78LenUMxvtP\n9eHM5+8lc31SQNgDwdAeLTCoWzjvdo8OZ3/wMCalh1roJLxB3Zpj3hPxmDRSWJsAlutF/WdSrs7G\nyBBv3JMQZfhao9GgbQs/aDUaPDysncm2LYK8MPfRnnB3dYaXuwteGheL1x+Lg7OT1uShwnjETqPR\nYEj3FrIF/GoX0szDYtK5cfWdz2YOVM0kNCHnUEKXcPSLCTV8PbpPJN56ohdmjLOsVGWLcn9Cylfe\n2c90BHls31Z4/6k+Jq+Zf20t488K2/XPOKB6Wqa0QDFsFmeY/Xnv7BfF2/McHclUuUvd3nqil8Xc\nMDYJXcMt1s/oFMV+THjvNAsWLEBoaCh0Oh2qq6sN/xyBlwMOixPHwFQ2Ty1LCbfhKJ+o1WoQ1zEE\nz93fFeGBXnjl4e74YtZgxm27tgnEzPGWN1Ym4xgm/zIZHscfoLq5OqGtgIdeIaNHUq8Bg3sIy7vW\naOraY83kYL2eHYINo0ZyBS/9uoThvoENN4ThvRqOv/Ex1miA96b1MakV371dENoxVHaIrr/J2mJo\nVi1D42z4/i5qevD34XmAf/beGAzvFYGn7o4x9O7qdDpEhfmiG0cvnBByht7G19Xn7uuCYH8PhAd6\noUf7hjaGB8qT8nLvgNbw9XTB8/d3xdQ7O7Nu9/GLAzDviXir5xiJ1T7CD7Mn9sAHT/e1ekIhH6Gl\nYAfENnR2OGJN9agwX96AWv99rVaDO/tFmXyPq5OF92wIDg52mEof7c0u/nEdpU8EUVqAr7pvME2V\n+XWkX0woHhrGX5nDHrgGHpjKFxqveOnspDFM2u3fNUz4qptCp7ALuP6O7hOJ1Iu5wvbH4y2JCxcI\nrZWrHw2L4Og9Gt4rAkF+Hqit1WFEvOVF+dERHfDnvssA5Ouh7ts51ORr44mZbZv74okx0fD3dkOX\nNsIrD+l7yLoajW7I0VxXFy1mTOiBt1cf5N9YIWzPSy89GIu8Iu7Vd+1tdJ9WFiv06nm4ORlWfQVg\n+AOqoRIFUJdW8/Y3hy1eNx69e/7+rpj20U6ESJzkb5wGp9FosPSlgZzbOztr4eflapNUHjZ9Y8IM\nKTePj4lGzaYzFnPBpPJwE/aA3KlVM+w7XjdBVej10Tw2YyL17ygntkpgw+MiODtNeO+WAwcOxPr1\n63H58mVcu3bN8E+NmErVOLqF0/vbbN9SVkokprq3D7brBZaLJ0uvSUgzD8YZ6ADwwgNdMXN8N7w5\nuWEyprhVN4Vtx7dPX0+XutxLmU5NsdcAa+vF63tq2jZnv3E8MrwDRsa3xOg+kYbjYJ6XGlj/AC1k\nNVc+C6f3Nwypvzu1NxY9Z3ot0Wg0GNStOWLbBrKmxzHp1yUMLz/UjbMHzxpfzBqCnh1DMDCWP93H\n3vrFhMHZSYOJLJOOu7cPslhATCyhK+IKxTWCsGzmIJOvJ9bXF+4XI0/xATE9l31jTB/67uzXymRR\nK7Y5EFqtBp/NHIj/SqLSm6oAAB96SURBVEz34Co68Oy9pikdPdoHYYJZqpSt3REXgQFdGz4Tfl6u\nmDEuFrFtmdd2YDPtrk483xf/eeYqBWmcase0SrI5rgpYcjGkXXK8VbC/O+v526YF9+Rw3h7qX375\nxfB//ZtoNBps376d70eJDGw5pBLFMWRufvMl3NT0cNKZJS+aq2xczw51+YI6nQ5j+kaiW1txQ75C\nf/vYtoEWdUyNfSTzA6TQYUw9IakmjO9j9DZfzhmK3MIyzF3J39NqPAlRowFG9Y6Es7MWCV3kDSrl\nXJVOq9FYjnTIdJnSaDR4cmwnPD46GtM+sk9lFSGiwn3w1N3yPkCYc2foIdRXB5Kb+QPUoG7NMSA2\nXNSDFRd3EelAU8Z2wkGj3/HBwW1RWVVj+NrN1Qn3JEShrKLG4meNU2y4mh4Z4o307BKT11bPGYKi\n21WcaUbGJW6n3tkJCV3t97DXzMcNPh4ujJPUtVoNZo7vhinzdwjeX3+ea4o15Xy5HtrmPRGPPalZ\n6NSqGWIErL1h61to386hhopubG+l1WjwxmT2Cl+hPFXaeAPqHTvq/mDl5eX4559/sH79eqSlpfH9\nGLEhuZbn5Kp13FQmGcmFrQqCmgi5WWo0GowfYtoDExrgiZv5pZw/x5evqb8pOPMcJ1eZZ+rba5TK\nuMKAViu8PKbG7P+uLk4Y00f6QlKAfUfohD64jIxvia2HLUc4jXO7AesWqrIlucsWMmK4y0sqqywy\nQpErmP7wmb6sI2FMnJ20cHd1QnllQ8Bs3nLjeQDWuHdAayxbf8LkNSet1hBMP313Z1RUWQbsxuwZ\nTAN1JVJVSeBp1TzIi3NlRXsznkA6qndLnLpsubZATOsA0StOG+M9648dO4a33noLAwcOxDvvvIOH\nHnoIO3eqp+eAS5HRIi+2ILW+LRdfT/YARa617tXUq+pozO89Qoa07EXu4F7IxD6+utiiSy+x/Aps\n6SxKY5qcNP8Z/hU5TUagZApo9GkktlgxT6rB3ZlHSbhKG774YFdB6VRCVhe1xvxn+nKm8tiSt4om\nOQrlakWVk/em1qVt6FNPrLk3sX16fDxd0KNDML58bSiWvjQAY/pEYtlM0zzpvjFhGGyndQ6EUEv6\noD1ZG46YVysyxnZN6NI6EKtmD7F4PSKYO9WOr42sd6fVq1djw4YNKCsrw7333ovff/8dM2bMwJ13\n3sm9RxVhGiKS05SxnbDyr1M22feSFwbIFjizoXDaeuY9cmqa7ezFchO2tolyPHcJ6XF0FfCA+tnL\ng/Dt5rPw4XjgNKbk38W4l/qx0dGM25j3UEv1wKA2uLNfK1RW18re289F6GG25u/h4+GKd6b0Nqn1\nbC6kmQeG92qJn7fLtzz74O7NkdA1XLHFuJ4YEw0XJy3+TVHk7a1mzUcu0M/dZDU+q645Rm/ctrkv\nurcPQnx0CNq0CkRJURm0Gg18PV0xfqjwHGj9dUbohD25WDNC0zzIC1m5zDXFZaWeWx2AujS54b0i\n8NRHuyy+58QxUuLspMXSFwfAw80JldW1OHYhl3dFU748b9aAeunSpWjXrh3eeust9O1b19OipqBB\nCFv3wHoLvKlbQ6vVwFVr4w8xRdRWCws0vck6Qm+/9cPo0n43H08XdBTQgy90mPiJMczBqbGHhrZD\nyvkcST09TLV4mYwWsPoX67GXOaK+q38UAOVWpeRj1Ux+TV2t5xZBXsi0Q8Dwf4/1xNn0WxjdO9Km\no5B8ErqGmeQWNyVSe6jbtvAzlDvzcHNGCeNP8Avy88DsiT3QPFD6Q1Xb5r5IyyoStK01l+rIUG/7\nBNQ2ImVFarbJ7vpcfrbQVV9D3sXZSVhKj7U91Lt27cKGDRswb9481NbW4v7770dVVRX/G6pIrY2D\nHLlyzsTq3i4Ix+rLiklpgq2PT2NmPslLbUfymXtiLEZPbFk9IYqj9vXLD3UTFMzPmtDd8H+pp+bo\nPpEY3Yc/0GXy7L0xqKisEVyLV8hs+8E9I4BqyxEz45EOqVcT/cRSJQjJO1z+8iBotRo8e28MvvhT\n+Mie/uEgKtyHNaCWc7Gu9hH+aB+hfAqX2Am1fGJaBzDmjcpN6OgRF6sWFbPR7VjMCpFc/EXUWGdb\ncZeT2m5CIk25k7sKiTXio0NwKatItnsf3yFmDaiDg4Px9NNP4+mnn8bhw4exbt06ZGZm4tlnn8XE\niRMxeDDzYhBqImThASG9XWxcjHrU5kmsdytGzw7BhoBarTmlTY7KLmZ9OoeiT+dQ/N+qg7iZX4re\nnULg7mrducIV3N49sA3Gxrdk7ckL9HVDVJiwCV2tjYJypjrUQktISi1fZlKfl0FkqDfSbzb0eTlz\n9GIufXEAsm+VIaSZJ+My0aYp1NZFBBpN3d/o7vreaSV0FLBimj7PvFfHEAD8AfW8J+Jx5mpBw8pw\nLOfhc/d1EVVHW62Yfj0503Y6RPjZLKC+Iy4C/yZnAJBnhV03Vye8+GBX3qoKjdUoAaNe5lR2CxKN\nLVVRCmcnLWOVFKtZ20NtLD4+HvHx8XjzzTexceNGLF++3CEC6uaB/LVcuUqJ8YkIadi/kFXb5GLc\nAyAlDYc6qOWj1kM5MDYcv+9Kk9R7yfW76XQ6uLk6oZalHMEUs1rFHgJXLiwtt1yNNVDASpTLZg60\nyYXZmHnPIddIla+Xq8nS1ObkGOX6cs5Q3C6vVnQSoi3SAVuF+ZhcV83PsGY+bhjQNdxksY/GRKvV\noEf7IAzt0cJkdTqhzI+XviY538Qrazw6ogP+Tc5AsL981aF6tBd3zVJ9QqqNbxL2Sjusqrbt3C4x\nxvZlrog0PC7CJoUCnJy4zzJRXVbe3t6YMGECJkyYIKlR9mKLpXGNiSkNJCe5PjZs+wkVuM49acBV\nlUVJY/pEol9MmLQlnTlOOK5r+P0DW1sMlwoNdq29Odg6mAZgceeWVFVFhiIfGo1GlRU92Gg0QFyH\nYCSfzxH1c8YPH1FhPpyrYLYO98Xl60Wi8lYVZ3TKv/VEXS1cZyctJo3qKMvuE7qGobyyhnfilbVW\nzR6iWBokkVhiUYQDJ67b5414TBnbifFBs20LXzwiZ680gLmP9sSxC7mca3cAAsrmOTK73FyVYPTB\nuUvKMC9L0EI91+KpdcKuRqORFkyDe2YzW+A7qFs47k5oLe59jPZl7QIr9mD+l5byp5e7yocj0Gg0\neP6BriavCSmrGNdReI/l8F4R+PK1oZgxvhvu7CdPXW97kjt/GqhLxRgZ31Ly9cDcPQlRAOqCfyXr\nh6v1GmwvHQQs7y0HISOF9mDPP3eHlv54aFg73nOs0QbU3QVOKJJCqc+v8WTCkfFWTF6oxxY4W7ME\naVNjj2VSVcNOv6rxxcqQN6tC5vm6UoII0wVDGm9AwLREcWzbQEQEe2HV7CG8dcz12+vxXnt1dT3a\n3h4ueHBwW0wY1g7jh7QV22zFyHFvsVfHiJS0SSKPuY/2xLCe0uaOCFVZpZ6UD7VptAG1PdiiF0EI\nuS6UbLtpZ6cnXeIYOHOobfWmKo4t7zHreZeS8mGc296YO9iYRtJmju+Gd6f2EZw6p9HUVQgBwLsI\nh/kD78jekYZlh7kouaCGcZsdqbdVjqoecnCgQya7Di39odVqMGdiD4Q288Brj/Sw2XtVqiiHWm0a\nbYkIuyToK/QBdnOR5znIEWonE+VxnSadW/OXjOOjAfDUPY4xKhIZ4m0RAErJG3WkwInPI8Pb4/fd\naTbtwerdKRRd2wQyrkxpzNpL22uP9rTuB2XmWKeFOhqrjlYoK7pVM3z4TD+bvkcVQ/lPJYSwzPVS\nqqMToB5qSZT6s8m12ICSixYQxxfo647BPZh7Cn29hOdpvj45jnPpaaFGWFO71UrGy7HLlTfqWEGU\npeG9WuKLWUNs/j5cwbR+dM184SWhhORy24rxQ4CQVUPVQj3nrWoaIsmbk3vJur+OLf0xebQ8E1sB\noMZesx85xLYNVEWteHONtofaHhy9dylcQFlBws8e+frKYr6AtgrzYf0M3ClgeJ2L2F6G0ABPTBze\nXtJ7ijEyviU27L0MQGKVDyNif+cnxkRTVQUzrzzUDZk5t9G2uWOnrTXzUcfEL2Jfd/WPMptXYb0h\nPVpg19FMvPxQN9H1zLkeLPt2DsWFjEKpzZMkOlKexXbk1mgDaheVLr1LGp/GHtNY0x8hd8nKu/pz\nB+jNvO2b+2p8g5LtwVrkbmgymCV3V2dVV4hpjNRy/VNLO6w1cXh7WUfZJo/qiEkjO1h1ffrvU31Y\nv+elghKdAb4cI6AKngeNNqDuHGWfJ5gHBrVBuJXDi8RxuShUg1wRCozwGd8DWoZ444FB6q3QIFfK\nh1w93aQxUH5YXYjoSH/VjJKopBmsurYN5Ky9bot0I7HB9I/vjMa1zFucf1O2RbzsxcfTRbWLOdk1\noK6qqsLcuXORlZUFJycnfPjhh2jZ0vSJLCYmBj17NkwM+fbbb+HkJL63y4nnRJJrFqykOtBWKq2w\nXEWO2Jeay7rZiy1WomKi9kVL5IqDKaC2vbiOwUg+J25BGSXIHbP0ElHDW4w5j6hjEieg7GQ0IQbG\nhuPbzWdZv29NhZnFzyegokq+SYJ+3m6o5AnsbZFDzdnjbGZAbDhjwB/azAM3C8rkbJZodg2oN27c\nCF9fXyxevBj79u3D4sWLsXTpUpNtvL298cMPP0h/M57PVkeV5uAIkZFdIvs+NRpa0EUM4yd/R8+l\nF6tdhB+G9miBPp1CbfYexjO4+3fhn7Bor3M3un7lR+P3k+vv39TOIyWopTeVick5LPP5/Nz9Xfk3\nEmBMn0hsTkqXZV9yU/GfFgD35/ulB2MRGcq9Ch8TuRfpEaJWxovt9Pu6YNfRTLzycDfBP8P24BTg\n646bBWWKPlbZddw6MTERI0aMAAD0798fKSkpsr9H3851N/k2Dj4phUvXttJLlZnT524JCV6IKZVf\nxyUbYbZ40JyJPdAvJky2VIcAhglYkSENNxc3AfMh7PUsOI5hcRCph2HGuFg8NlLepXIJs27t5L92\n2oKzs/TPli3KopbL2BsqN7UH1Fy6t3ecie1ynlbx0SGYPbEHnLSNI4XSrj3Uubm5CAioW2VMq9VC\no9GgsrISrq4NQx2VlZWYNWsWMjMzMWrUKDz55JOi3mPa3Z3x8B3tFS3Qb2tRYb54c3IvNA+SL+eq\nRbAXPnlpgOqH14n9hbLU+5TDh0/3laeXxU5d1EyLkEi9GXRr9FVi1KNfTBi+3HiG8XuePLWtbS2w\nftg7MtRbtQHGlevFSjeBlXEPMKVP2U63dkFwdtLiETtWVRJCDetq2OwKsnbtWqxdu9bktdTUVJOv\nmQ7AnDlzcM8990Cj0eCxxx5Dr1690LUr93BVcLDpUIntBqLVw/x3lvpzfr4eaNPKMXpv7EHM8e3W\nMcTqv4cjuFFYYfJ1UJCPSQ3z4GAfi7w6ocejS0fmT6vx/nx9PXj35+ziZJe/gf49vIzqbLdo7ico\nXUPu9jnSOSemrUr8XgndmuORkR0VPaYPjeoEbx93DOrRQnDZPK72enu7C9pODBezRcXUdA5W1zQs\nKBTQzNOkbWpqJxM1tY+vLcHBwIaP7rZTayx5eroyttHVtS6cdbHTvYCJzQLq8ePHY/z48SavzZ07\nFzk5OYiOjkZVVRV0Op1J7zQATJw40fD/vn374vz587wBdU6Oep+a1SQ42If1WBUXl9NxrMd1nJj4\nezo36mN361apydc5OcWGgFp/rMxnfgs9HmzbGefpFRaV8e6vsqrGpn+DRc/1R1llw3vcvt3wkJGb\nyz+nQew5JYQjnXNC22qL48TngUFtDJPLlT6m/TuFoLq8CjnlVbzb8h2r4pJyw//l+r2qzZadVvp4\nGaupbWhb2zBvQ9uUOKfEUkv7HOFYRQZ5MraxsrKuWEO1je8FAPtDh13HlRISErBlyxYAwM6dO9Gn\nj2mtw0uXLmHWrFnQ6XSorq5GSkoK2rdX17BCY3PvgNYAgE6tHHeSJiG2Hu4L8HVHi6CGhZB0Cpc1\ne2dKb0Xfv7GIbRuIYT0jlG6Gw1BzIoXxKFFUmDyLo9hDqIKrczqaUb1boksb5pF0/S1Aycnddk0a\nGzt2LA4cOICJEyfC1dUV8+fPBwCsWrUK8fHx6NGjB8LCwjBu3DhotVoMGzYMsbGx9mxik3PvgNa4\nOyFK1bPf1U7t5ZqaAhWkz9lNbNtAKtsok5njhVcXIOrmaFdhbw8XlJRV2W3NjMZgLMcKvLFtA3Hu\n2i3EKjjx2K4Btb72tLmnn37a8P/Zs2fbs0kE6i4l5QiU7q20NfPfjvF0seIUohuJdbqy9NAQYqJx\nX5YsOGzZySb2d7KVUX0iEdM6ABEKdjY02pUSCSG2wdQbbPxQFinwgtZO4BLRQtI57L1aqb6HONYG\nJSwJUS2jmPVdFaYd3T+wNcIDvfg3VAH9JZPiaXloNRqrannLiQJqQqzk5e6M2+XV8POyf3F9uxKZ\nT+EjQ8lKoX1NK14ZhH3Hr6N/l3DJ7ylGTFQAXp8Up0jqhRrKQ3F56q7OWL3xNPy9XXGrpFLp5hAZ\nGae3KdkTyObuhNZKN0Eww5FU+edZTdR+pCigJsRK707tg8vXiyifVUHurs4Y3qsl/4Yy02g0gnvY\nm5p+XcLQprkvvD1d8OLSvUo3p8nST3aT9Tx10KwKVXLUFBUlqTyipoCaECs183FDM59gpZuhGm2a\n++JSVhHdcwlCAzxRVlGtdDOatK5tAjBzfKysATV9tuWn8hiRiKDO5ZgIIaoh9II/YVh7eLk74/5B\nbWzanqbOUW7A+iXju7QOULglTZNGo0Fs2yB4usu3+i0F1PKhYyme2q991ENNCOEkqMoHgHYRflg2\nc5Dg/XItD2w8Y9+FYblvon5arQarZg+hZaAJ4UAp1CKo/GBRQE0I4WZ2DXOWKcC9I4479/k/j/fC\ngRM30K1dkCzv11gE+QlblloN5DpXiEpQ3q986FA2OhRQE0I42aqH0dOd+/LTOtwXrcMdZ8UzW5s5\nPhY7UzLRnR4wZPHR9H5KN8HhUAxoC+rudSXCUUBNCOHUoaW/0k0gAGLbBiG2LQXTcgny81C6CQ6H\nOqjlQ4dSPCeVj3hRQE0I4aSlHFhCCLEJlacFq8LbT8YjM/c2vD3km2BrCxRQE0IIIYSXwy7vrUJ0\nLIWLDPVRfBVEIdTdf04IUYXhcREAaJiSEELkRB3UjQcF1IQQXu5uNJhFCCGEsKGAmhAiQH0/ikxd\n1G6uTvLsiBBCHBl1UTca1O1ECBFMI0NE/fmswbTYByEOiNJ+5UPHsvGhgJoQwkvOmej6JakJIaSp\n01EXdaNBKR+EEMGoV4WQpos+/vKhY9n4UEBNCCGEEH70RC2LJ8dGN3xBHdSNBgXUhBBCCOFF4bQ8\nBsY2Bx3NxocCakIIIYTwCvB1U7oJjYazc134RSvRNh4UUBNCePnUL/kaGuCpcEsIIUrp3j5Y6SY0\nGs/f3wVd2wTivoFtlG4KkQlV+SCE8BraswVKK6oxIDZc6aYQQhRCnanyiQj2xssPdVO6GURGFFAT\nQni5ODtRTwohhBDCglI+CCGEECIAdVETwoYCakIIIYQQQiSglA9CCCFNxqczBsKJkoGtQmWoCWFH\nATUhhJAmw7u+Yg0hhMiJUj4IIYQQwos6qAlhRwE1IYQQQni1bu4LALirf5SyDSFEhSjlgxBCCCG8\nvNxd8NVrQ6GhZGpCLFAPNSGEEEIEoWCaEGbUQ00IIYQQYmNLXxoAnU7pVhBbsXsP9aFDh9CvXz/s\n3LmT8ft//fUXHnzwQYwfPx5r1661c+sIIYQQQuTn6+kKPy9XpZtBbMSuPdTp6en45ptv0LNnT8bv\nl5aWYvny5fj999/h4uKCcePGYcSIEfD397dnMwkhhBBCCBHMrj3UwcHB+Oyzz+Dj48P4/dTUVHTt\n2hU+Pj5wd3dHz549kZKSYs8m/n97dxoSVduHAfyaZwZ5Ulscc0aFrIiiSMoFI8uiooUWAgPLRGyB\nSKe9DGU0M6RA6UM0iZXLhz6Ea8tAqVEqRbhQhmW7FuFSOqOTmqOm1vvh4fVdHq1j09N9Jq/fpzkj\nM1z85cB1ztycm4iIiIhoVH7pHepx48Z98+9msxlqtXroWK1Ww2Qyffd73dyGL+j0d5yVNJyTdJyV\nNJyTNJyTdJyVNJyTdJzVj/vHCnVeXt7f1kDv27cPS5YskfwdXyWu3jeZukaVbaxycxvPWUnAOUnH\nWUnDOUnDOUnHWUnDOUnHWUkz0kXHP1aoQ0JCEBISMqrPaDQamM3moePW1lb4+Pj87GhERERERD+N\nrB6bN3/+fMTHx6OzsxNKpRLV1dXQ6/Xf/Rx/opCOs5KGc5KOs5KGc5KGc5KOs5KGc5KOs/pxiq9S\n11X8BGVlZcjMzMSbN2+gVqvh5uaGrKwsXLx4EQEBAfD19UVRUREyMzOhUCgQHh6OjRs3/qp4RERE\nRESj9ksLNRERERHR74ZbjxMRERER2YCFmoiIiIjIBizUREREREQ2YKEmIiIiIrKBrB6bN1qnTp1C\nTU0NFAoF9Ho95s2bJzqSLL169Qo6nQ7bt29HeHi46DiylpKSgocPH2JgYAC7d+/G6tWrRUeSnZ6e\nHsTGxqKtrQ19fX3Q6XRYvny56Fiy1dvbiw0bNkCn02HTpk2i48hSZWUlDhw4gJkzZwIAZs2ahWPH\njglOJV9GoxEZGRlQqVTYv38/li1bJjqS7OTl5cFoNA4d19bW4tGjRwITyVd3dzdiYmLQ0dGB/v5+\n7NmzZ1Sb8NFf7LZQV1VV4d27d8jJyUF9fT30ej1ycnJEx5Idq9WKpKQkBAYGio4iexUVFXj9+jVy\ncnJgsVgQHBzMQj2M0tJSeHt7Y9euXWhqasLOnTtZqL8hLS0NEydOFB1D9hYsWICzZ8+KjiF7FosF\nqampKCgogNVqhcFgYKEexn9vLldVVYXCwkLBieTr6tWrmD59Oo4cOYKWlhZs27YNRUVFomPZHbst\n1OXl5Vi5ciUAYMaMGejo6MCnT5/g7OwsOJm8ODg4ID09Henp6aKjyF5AQMDQrxwTJkxAT08PBgcH\noVQqBSeTl3Xr1g29fv/+PbRarcA08lZfX4+6ujoWHvppysvLERgYCGdnZzg7OyMpKUl0JNlLTU3F\n6dOnRceQLRcXF7x8+RIA0NnZCRcXF8GJ7JPdrqE2m83/809Xq9UwmUwCE8mTSqXCn3/+KTqGXVAq\nlXB0dAQA5OfnY+nSpSzT3xAaGoro6GhJu5mOVcnJyYiNjRUdwy7U1dUhMjISW7duxf3790XHka3G\nxkb09vYiMjISYWFhKC8vFx1J1h4/fgwPDw+4ubmJjiJb69evR3NzM1atWoXw8HDExMSIjmSX7PYO\n9f/j/jT0s9y+fRv5+fnIysoSHUXWsrOz8fz5cxw9ehRGoxEKhUJ0JFm5du0afHx8MGXKFNFRZG/a\ntGnYu3cv1q5di4aGBkRERODWrVtwcHAQHU2WPn78iHPnzqG5uRkREREoLS3l+TeC/Px8BAcHi44h\na9evX4enpycyMzPx4sUL6PV6XLlyRXQsu2O3hVqj0cBsNg8dt7a28gqUbHbv3j2cP38eGRkZGD9+\nvOg4slRbWwtXV1d4eHhgzpw5GBwcRHt7O1xdXUVHk5WysjI0NDSgrKwMHz58gIODA9zd3bFo0SLR\n0WRHq9UOLSXy8vLC5MmT0dLSwouRYbi6usLX1xcqlQpeXl5wcnLi+fcNlZWViI+PFx1D1qqrqxEU\nFAQAmD17NlpbW7nc8QfY7ZKPxYsXo7i4GADw9OlTaDQarp8mm3R1dSElJQUXLlzApEmTRMeRrQcP\nHgzdvTebzbBarVxzN4wzZ86goKAAubm5CAkJgU6nY5kegdFoRGZmJgDAZDKhra2Na/NHEBQUhIqK\nCnz58gUWi4Xn3ze0tLTAycmJv3R8x9SpU1FTUwMAaGpqgpOTE8v0D7DbO9R+fn6YO3cuQkNDoVAo\ncPz4cdGRZKm2thbJycloamqCSqVCcXExDAYDC+Mwbt68CYvFgoMHDw69l5ycDE9PT4Gp5Cc0NBRx\ncXEICwtDb28vEhIS8McfdnttTjKwYsUKREdH486dO+jv70diYiJL0Ai0Wi3WrFmDzZs3AwDi4+N5\n/o3AZDJBrVaLjiF7W7ZsgV6vR3h4OAYGBpCYmCg6kl1SfOXiYyIiIiKiH8bLWiIiIiIiG7BQExER\nERHZgIWaiIiIiMgGLNRERERERDZgoSYiIiIisoHdPjaPiIj+IyUlBU+ePEFfXx+ePXsGX19fAMDC\nhQuh0WgQEhIiOCER0e+Lj80jIvqNNDY2IiwsDHfv3hUdhYhozOAdaiKi35jBYMDAwAAOHToEX19f\nREVFoaSkBP39/YiMjERubi7evn2LxMREBAUFobm5GSdOnEBPTw+sVisOHz7MHR6JiL6Da6iJiMYI\nq9UKb29vZGdnw9HRESUlJUhPT4dOp8Ply5cBAImJidixYwcuXbqEtLQ0xMfHY2BgQHByIiJ54x1q\nIqIxxN/fH8BfW1j7+fkBANzd3dHV1QUAqKysRHd3N1JTUwEAKpUKbW1t0Gq1YgITEdkBFmoiojFE\nqVQO+/rfHBwcYDAYoFarf2UsIiK7xiUfREQ0xN/fH4WFhQCA9vZ2nDx5UnAiIiL54x1qIiIaEhcX\nh4SEBNy4cQOfP39GVFSU6EhERLLHx+YREREREdmASz6IiIiIiGzAQk1EREREZAMWaiIiIiIiG7BQ\nExERERHZgIWaiIiIiMgGLNRERERERDZgoSYiIiIisgELNRERERGRDf4FT4TtJJq1u2UAAAAASUVO\nRK5CYII=\n",
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