{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "#Position Concentration Risk\n", "\n", "By Maxwell Margenot and Delaney Granizo-Mackenzie.\n", "\n", "Part of the Quantopian Lecture Series:\n", "\n", "www.quantopian.com/lectures\n", "github.com/quantopian/research_public\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "When trading, it is important to diversify your risks. By concentrating your positions in only a few assets, you can negatively be impacted by their risks. This notebook is designed to show how diversifying your portfolio can result in a lower overall risk profile." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##Intuition\n", "\n", "Let's say you learned to card count at Blackjack, whereas most casinos will throw you out if you are caught, it will give you a [1% edge over the house](https://en.wikipedia.org/wiki/Card_counting). If you walked into the casino with \\$10,000 to bet, it would clearly be insane to place all the money on one game. Whereas you have a 51% chance of winning that game, the house still has a 49% chance. The expected outcome is for you to win the game, but the variance is increadibly high.\n", "\n", "Let's say you placed your money on 100 different tables. This is known as making independent bets, because the outcome of one table doesn't affect any of the others. Your variance will be reduced as you make more and more bets. You would still expect to win 51% of the tables, but the chance of losing money is greatly reduced. Let's see this in action." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "###Simulating Blackjack Games\n", "\n", "Each game will be won with a 51% probability. We can simulate this using a binomial distribution, which is parameterized with the number of trials we perform (games), and the chance of each trial succeeding.\n", "\n", "First we'll simulate 1000 different universes in which you walk into the casino and play one game." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "universes = 1000\n", "\n", "results = np.zeros((universes, 1))\n", "for i in range(universes):\n", " results[i] = np.random.binomial(n = 1, p=0.51)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's check the mean and standard deviation of the results. We see that because there are so many 0s and so many 1s, and nothing in between, the standard deviation is very high. This is saying that you should expect to win half a game, with the potential outcomes being approximately evenly distributed between a loss and a win. Because you played so few games, you have given no time for your edge to work." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(0.53200000000000003, 0.49897494927100305)" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.mean(results), np.std(results)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's simulate 1000 universes in which you walk into the casino and play 100 games." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(51.201000000000001, 4.9920535854495789)" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "universes = 1000\n", "\n", "results = np.zeros((universes, 1))\n", "for i in range(universes):\n", " results[i] = np.random.binomial(n = 100, p=0.51)\n", "\n", "np.mean(results), np.std(results)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we see that the average result is much closer to 51 games won, with a smaller standard deviation. We see here that you're likely still not safe, as your expected edge is only one game, whereas the standard deviation is many games. This would indicate that you can reasonably expect to lose more games than you win. Finally let's try 10,000 games." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(5100.6019999999999, 48.676150176446782)" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "universes = 1000\n", "\n", "results = np.zeros((universes, 1))\n", "for i in range(universes):\n", " results[i] = np.random.binomial(n = 10000, p=0.51)\n", "\n", "np.mean(results), np.std(results)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this case we're much safer, as the expected edge is 100 games." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "NOTE: There is a subtlety that it's not always valid to use a standard deviation, as the underlying distribution of data in this case is not normal. We use it here because standard deviation is the metric of volatility used in finance, and it still reflects how much 'spread' exists in the data. Be careful not to abuse standard deviation in practice by assuming the underlying data is normal." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##Expanding to Portfolio Theory\n", "\n", "The same exact principle exists in portfolio theory. If you think you have an edge over the market in picking stocks that will go up or down, you should try to make as many independent bets as possible. This can be accomplished by investing in as many uncorrelated assets as possible. Let's take a look at an example.\n", "\n", "Remember that in finance, volatility is measured by the standard deviation of a time series, and the amount of future risk of a portfolio is estimated by past portfolio volatility." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "####Case 1: Investing in Few Assets\n", "\n", "Let's simulate some assets by sampling from a normal distribution.\n", "\n", "NOTE: In practice real financial asset returns rarely are normally distributed, so this is not a great assumption. However it's okay here to get our point across because we are just concerned with correlation and level of volaility." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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AALQoq6xTYVmtYiIDDA1HQH9j6AjSxo0bVV5erlWrVrU1Z5g9e7ZiYmK0dOlS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\n45MPFerepzfqi+Scy/5M2FdxRYN2HS5UbISfRkYHXnCswXC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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "R_1 = np.random.normal(1.01, 0.03, 100)\n", "A_1 = np.cumprod(R_1)\n", "P = A_1\n", "plt.plot(P)\n", "plt.xlabel('Time')\n", "plt.ylabel('Price');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this case, we're totally exposed to the volatility of that asset, as our portfolio is entirely that asset." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "####Case 2: Investing in Many Correlated Assets\n", "\n", "In this case we expand our asset pool, but there is still a large amount of pairwise correlation between the returns. We simulate this by simulating assets 2 through N as asset 1 plus some noise." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Asset Volatilities\n", "[0.028284024256736047, 0.030739948626595206, 0.031591494947059345, 0.029374731232950157, 0.030155544749912645, 0.030279129828505846, 0.029689363035443027, 0.029602827861575445, 0.03021005066716944, 0.030774932310216038]\n", "Mean Asset Volatility\n", "0.0300702047516\n", "Portfolio Volatility\n", "0.0287023902616\n" ] }, { "data": { "image/png": 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KOkgiIiIiclvVoWF3skcdGzKbcancnBdHALGugcXH6wAi7U32aaK8F+WcJcsd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mzAWTc9fwCISIyvxpRiJ7JCU44MdWXpdI++med9iD1bbYnxUV5jSkfia43DaIk1kRi1OUBIJUgS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U1mozQwhVjPluSd63EC3Pg5t8J3c2+XJjIMayO3pcoiDcKGj0PpbJoRDkabolJ0mblGJtrN6e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\nP2I0doyNRFj3b+OtfaAsakJgcOBtbCjrQCf3eJuTRhZMNujQZ2E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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "N = 10\n", "\n", "returns = np.zeros((N, 100))\n", "assets = np.zeros((N, 100))\n", "\n", "R_1 = np.random.normal(1.01, 0.03, 100)\n", "returns[0] = R_1\n", "assets[0] = np.cumprod(R_1)\n", "plt.plot(assets[0], alpha=0.1)\n", "\n", "for i in range(1, N):\n", " R_i = R_1 + np.random.normal(0.001, 0.01, 100)\n", " returns[i] = R_i\n", " assets[i] = np.cumprod(R_i)\n", " \n", " plt.plot(assets[i], alpha=0.1)\n", "\n", "R_P = np.mean(returns, axis=0)\n", "P = np.mean(assets, axis=0)\n", "plt.plot(P)\n", "plt.xlabel('Time')\n", "plt.ylabel('Price');\n", "\n", "print 'Asset Volatilities'\n", "print [np.std(R) for R in returns]\n", "print 'Mean Asset Volatility'\n", "print np.mean([np.std(R) for R in returns])\n", "print 'Portfolio Volatility'\n", "print np.std(R_P)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here you can see the portfolio accompanied by all the assets, the assets being drawn much softer. The important thing to note is that the portfolio undergoes all the same shocks as the assets, because when one asset is up or down, all the others are likely to be so as well. This is the problem with correlated assets. Let's take a look at the volatility of the assets and the volatility of the portfolio." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The mean volatility of our assets is the same as the portfolio volatility. We haven't gained anything by making more bets. You can think of correlated bets as identical to the original bet. If the outcome of the second bet is correlated with the first, then really you've just made the same bet twice and you haven't reduced your volatility." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "####Case 3: Investing in Many Uncorrelated Assets\n", "\n", "In this case we independently generate a bunch of assets an construct a portfolio that combines all of them." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Asset Volatilities\n", "[0.030237858089015177, 0.032903881322195787, 0.0292815777308091, 0.026911876873315674, 0.026684189948320374, 0.029975323398649917, 0.030531226213826916, 0.029564231016589962, 0.029162481483272634, 0.031000764537970443]\n", "Mean Asset Volatility\n", "0.0296253410614\n", "Portfolio Volatility\n", "0.00944852118336\n" ] }, { "data": { "image/png": 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JBiQiIiIiulRiTMfqFveF+vY1X1XpWNoJ78z4/v6OXFLtfZGElBBZBqEDQpNDlSXMeITQ\nT2uAVEd+b7gRUsLc2AFCOPp4X1kiTKZLp0hzMstgbijYyTQ16C2a+MLeEUCtILQ+9HWfL5/Vg8Gp\n7jFdVgxIRERERHSphK5D9AGq2LsvJIsCvq7hm+Zk1dsxInR92FpRbHDR9ld7C6WglAKOK5IQAjim\nOlxmGaRWR06RgDQZMjd24Ps2Ol83yG7dhNlZ3XIXrIVvO0ijl+6UusquT9QjIiIiomvB1+m+0P4X\n3qosIJRclAOsK1qbpiF5dikLBA4EuFMcHzyO6iu3fX10G58Q82NyMdWYW4vulbuwu5N0BK+q4ft7\nU8G5xTHA63S0bo4TJCIiIiK6NNL0yB9ariqEgB4MYCdTuKpae4ePb/pmuEs65TgwLdtAgJNZ+joe\nN0UCkI4wZnk6jhdjX9CwOoyqsli7/e4quX6fERERERFdWfNAs+y+kMxSU1ro0q6f4woX0gt8u6jR\nvowW1d4bDHCqLPpGu2blPqnFkTmtDoTPGPtluPN/fABC6N/v1V4IuwoDEhERERFdCvMlp9IcbmSb\nU4MS4a6Fm1UwN3ZWTl1828JX6RjYJo6unYfgHIJ1qQxhgwFO5XnavdS2/VHFgx8rxrh3ZO6eRa/z\nu06XNWBuAu8gEREREdGlsJimlKunKVJrqCJP06F+t9GB9+Ec7O4u3HQGREAv2e9zWYTm+M/3vMw/\nxvx+137ze12qyK/lkbmTYkAiIiIiogs333W0zq4iVZYQUsA3DWJ/3CtNQWawd3cRrIPKM5gbO5f2\n7lEMAaHrINR2djOpPO/vIrUHSi7mQVMoeW2PzJ0UAxIRERERXTjfT4PW2VUkZHoxH0OE79vV7N27\n8E2bKqt3xtCj0caPhUXv0x2dE0pTrglijFDF9qZby6ZIblal5yjLa7XL6Cw4QyMiIiKiCxVDQGi7\nNMVY8ziczHOIpoVvW6BfKqvKMt2x2UAbXPQ+LXD1HtF5RO8QQ4SQ/cddc1Ll6zodaevD0TbvR917\nFyndgUp3vi7rMcSLwIBERERERBdqb1Hq+ke8hBDQwwHcZAqhNfRwcO4TI9+2CG2bAtE9kyKhFGQm\nEW3aCeSbFnpQrlxGG72Hm80QrINQEmY42srRunvtNdrVCNYuvo60hwGJiIiIiC5MjBGhbSDkyRel\nSmNgHri5kYlRcC4VPSCFIaU1hE5tbkLrxceMIaSpUNPCTqaQRkOV5YHw49sWfn6ULc+gBoMLO862\nN0Xq0s/L8r5qqFsHAxIRERERXZjQtoihvwNziqCzkeN0McLPUjgyO+MjJz1CSujhEKoo4Kqq39E0\ngcozyDyHbxqErp/UjIaX4ijbfIoklNpKg95Vw4BERERERBfGN026P7TFsoLjhKZBcB4qz9c+BidU\nWrAarE0TpbZbTGmkMRs5AnhaKs+BECCzbCMB86pjQCIiIiKiCxGsRfQhVVBfkga16D18nY78qcHJ\na6+lMZDGLO4vSWMuZX32ZXymy4IBiYiIiIguRJhPWPLlxQYXYV57rYfDM4U2leeX4jgdndzliOpE\nREREdF+JMfaLUuWFtLkt49s21V5nrL2+nzEgEREREdHWha5DjBEyuxxBJIYAX1WpTGHA2uvLKoSI\nqrHw4eQLetfFgEREREREWzc/XqcuyfE6X1WpTW/A2uvLKsaIaW1Rtw7Oh419HAYkIiIiItqq6H06\nymb0pQgjoUuNc9JoqIK115fVrHGwziMzCrnZ3PcNAxIRERERbdWi/voS3POJMcLNj9YNhxf9OLRC\n1Vi0nYNWEqNys3fWGJCIiIiIaKtC10EIcSnKGXxVIfoAWRSXYppFh7XWo24dpBQYDza/u4kBiYiI\niIi2Ju0+8pCZufDdR8Fa+KaFUAqq5NG6bQkhIqxZsmBdwKy2EEJgZ5BBys0vtuUeJCIiIiLamnCJ\njtf5ugEA6OFg41MJSmKMuDtrESOQGYUyU1BqeVD2PmBapbbDnWG28u3OGwMSEREREW1FjBHBXo7d\nRzGEVBSh1YU/y/2k7TxCiBBCoO0c2s4hNwplrg8EoBAiJpVFiBHD0sDo7R1/ZEAiIiIioq0IXZeq\ntMuLnx6Frp9kZZejZvx+UXcOQgjcGOVwPqBpHVrr0drUTlfmGkoKTGsLHwLKXKPIthtZGJCIiIiI\naCv2dh9dhoBkATAgbVNr0/SoyFIIUjLVdXd9CUNnPTrrIaVACBGZURgU25/uMSARERER0cZdpt1H\nl+lZ7idN6wAARX4wgmRGITMK1nnUrYd1fit13qswIBERERHRxl2mI23Bcnq0bdZ5OB+QGwW1oonO\naAWjFbwPkFJcWHEGAxIRERERbZxv+91HlyCUXKawdr+oWw/g8PRomW211a3CPUhEREREdGoxBPi2\nRQxh9dt4j+g9hNEXvvsoHa9zkObi9zDdL6wLsM7DaAV9weFnHZwgEREREdGpxBjhJhME5xfTIVnk\nkPqel5j9kbZtlzN4H1B3HrlRMDq9MF9Mj3JOj7al6dLdozK/Gve9GJCIiIiI6FT8rEJwHtLoxSTJ\nty2k0ZB5vneEzTkIKSC2vG9oWls4H9B2DkanCmnMA9IZnsX7AB8iQohQSi7C13nyPsC6sNaRtMvM\n+4DOptKFbe4yOour/RUnIiIioguxCENaQY/HEEIgdB180yJYi2AdhKrTNClGyDzf6qX71qZSgPmL\ncus8utYCswaDUXHs8boYI3yIcD4ghPRj7yNCjIgxHnjbefg6r6BkXcCk6hBjRARSsLui6i7dPbpK\nn8PVeVIiIiIiuhSCc/CzCkIK6NFoEXxklkFmGaL38E2D0Hbw7fYLEWKMqBoLIQSGhYZSEtYFTO9O\n0PiAmQN81aHMNbSSe2HIBbgQFxOie4OQEKLf3yMhpYBScrG7Z37H5qxBqbMe07pv2RMCVWNhtDzR\n3Z0YI6a1hZLiQvYIzfkQ0VkPJSUyczWmRwADEhERERGdQAwBbjpFjBFmPF66R0goBT0cIg4GCG0L\n5EvuJW1Q06WFpGWuF41oRkuMNJANM7giWwQbJeWhqdA8CGmVKqmVklBSQC6pp86NgnUBdetg3dmC\nUms9plVq+xsPUrDZnXWYVhY3RtnaE7hZbdHZNLlRSiK/oHDSdg4xRhTF1YocV+tpiYiIiOhCuekM\n0Qeosjz2Ho8QAqooILY4PQohomkdpBAosr2XutF7BOeRFRmG4xLWeVSNgw9xLwwpAd2HoZMcBzRa\nwujsUFDKjEKRrReUms5hVts+HGWLP1PmGnXrMGvcWotTq8ai7e/8+BAxq+3ic9qmECKazkNKcWEB\n7bQYkIiIiIhoLa6qEKyFzAz0oLzox1mqbh1CjBgW5sDE596jfkYr3Bid7wv3vaCUwtd8SqWVRJ4p\n5EYtDV5161A1FlIIjIfZgeN0Za5hXSqayPTRR9Va61G3DlKmkGV9wLTqMK067AzXn0Cdh6afHpW5\nubCFr6d1+YvIiYiIiOjCha6Dr5vF8bnLyPuApnNQMgWS/UK3vUW1KXzl2BnmyI2C8wGz2uKVSYuq\nsfB+b2dU1dgUjqTAzj3hCEhTuFGZQsastvAh3vvhAKRih/kEameQLSY3849ft26jn/N+MUa0ne+n\neFdregRwgkREREREx4jew01nEEJAj4aXdsFq1YeAQaEPTC2Cc4jeQ+XbnaLMJ0pliGg7h7ZLE566\ndciMgkCa+igpMR5mK4/BKSUxyDVmjcWsttgZHgx5PkRM+9a78SBb3LsCgGFpYPuAlJ5n84Gl7TxC\nTHfArtr0COAEiYiIiIiOEGOEnaRSBjUcbLVs4SSs2zvOdu8xtPly2G3vYZqbt8ndHOcYDdKUqLN+\ncVdo54hwNFfkGplRsM6j2TcNijGFoxAjBoU59LmnCVQKVNPaIqyYQJ2XGCPqzkHccwfsKrmaT01E\nREREWxG6Lk1fihwqzy/6cVaqmhQahkuKDLZ5vO4oQhw89mZdQG7U0na8ZYaFgXMBVeug++rv+TLc\nPNMrdw0ZLTEoDKrGYtZYjAeb+zq0NjUIFple+/O6bDhBIiIiIqKVokvBQ17icNR0LoUEow7d4UnH\n6wJkdrnKArSSKPOThQgpBYal6adG6e7SfGo2PKZKO9WOK3T24ATqvDWtT9OjK7QY9l4MSERERES0\nUvRpn86yfUeXQYwRdZuOdJVLlqLOj9dd9PTovMyrw31I94qUlBgP1rtbNSxNWj7bpkB53lrr4UMK\nqtuuFT9PG412TdPgU5/6FF588UV0XYdPfOITeOc737n4/e9+97v4whe+AKUU3vGOd+CTn/zkJh+H\niIiIiE4oOg+pl9dTXwZ16/aWwi55UR66DkKKC7t/tAmDIlV/p1IGs/YUSvUTqEmVls+OBwYRQNqR\nGxEj+p+ne0qraslXqftjjld5egRsOCB9+9vfxhvf+EZ8/OMfx7PPPouPfexjBwLSZz/7WTz55JO4\nffs2/uAP/gDve9/78LrXvW6Tj0REREREawou7bKR6nK+4PXzZaRCLL1/E6xNS23z/NIGvNMQQuDG\nKEOMOPE9n/kEqukcXpm2R76tcwGjNe8rdfPpUbY8qF4lG/1uf//737/48bPPPotHHnlk8fOnn34a\nN2/exEMPPQQAeOyxx/C9732PAYmIiIjoklgcr9tgNfRpj/CFEDGZpWrrQbn8fpFvGgCAzK/H8br9\nhBA4beZLNehAiIAAFu9HCJF+LgWa1qG1HsZ65Ecsp52b71kqr+Deo3tt5a8DPvShD+G5557Dl7/8\n5cWvvfDCC7h169bi57du3cLTTz+9jcchIiIiojXMCxo2ef/ITiZAjNCjEeSax+BijJhUHXwIKHO9\ntE46WIvQWUhj1n6/9wshUu34UbQUuDvrMKsttJJHToU66xclGUpd/YqDrQSkp556Cj/60Y/wx3/8\nx/jWt7619G3mZx2Pc+fOnfN8NKIj8fuNto3fc7RN/H6j48SqArwHRqMzH1Fb9v0WvQeqqv+ZAAbl\nWmGsagOcjzBaoMwOvyCPMab3GwIwGFzagonLrnMBTRehJDAsVn8NZ42HD8CwODpIXRUbDUg//OEP\n8eCDD+Lhhx/GG97wBnjv8dJLL+HWrVu4ffs2nn/++cXb/uIXv8Dt27ePfZ9vfetbN/nIRAt37tzh\n9xttFb/naJv4/Ubr6F56GUJJmBs3zvR+Vn2/uaqCrxuoPIdvWwghoMdHT5JmtUXTORitMB6sOFpX\n13BVDVXk0MPhmZ79fjetOrTWo8z10qmTdR67sw6ZURvdr3QSZ/3Ln43OwL7//e/jySefBJCO1NV1\nvThW9+pXvxqz2QzPPvssnHP4zne+g9/+7d/e5OMQERER0Zqi94gxQmywoCF0FkIIqOEAZjwCALjJ\nFMHapW9fNSkcaSVXhqMYAnzdQEgBVZYbe/b7xaBILXl162Dd4Wrw+YLeVUtqr6KNfiYf/vCH8elP\nfxof+chH0LYtPvOZz+DrX/86xuMx3v3ud+OJJ57A448/DgD4wAc+gNe85jWbfBwiIiIiWlOY3z/a\nUEFD9B7R+8UCV5Fl0CPATWdwk+mhSVLTOdStg5QCoyP2/viqRowRejCAkFf/PsxFk1JgVBrszjpM\n6w43R3uNgNYFOB+QLVnQe5VtNCDleY7Pf/7zK3//0UcfxVNPPbXJRyAiIiKiU9h0QcOyBa4yy6DH\nAm4yTSFpNITMMnTWY1ZbSCGwM8hW3nMJzsG3LaRWUEWxkee+HxmtUOYadeswaxxGZQqu8+a6ZSUZ\nV9n1+myIiIiI6FzsVXxv5uVisOnF9b33jaQx0ONRCknTGWIRMHOpeW00yI5sSfN94YMaDDbyzPez\nMk/LadvOwWgJKQSs8zBawejrMz0CNnwHiYiIiIiupug8hFIbWbAaQ0CwFtLopcfg5iEpxIiXn38F\nvm0xKs2RL8R92yJYB5VnrPXeACHSUTshBKraomrSPbEyv34NgQxIRERERHTAvKBBbuj+0byE4agg\nI42By1PJgnEdRLW6vCHGCF/XqfCBxQwbo5TEoNAIMcL5AK0kzAaXCF8UBiQiIiIiOmCvoGEzx+ti\nH3TEEQEpxggbBLIbYwxHBYLzsLsTuOl0cfxvztc1og+QRcGdRxtWZBqZSV/jQXE9b+tcz8+KiIiI\niE5tcf/UvCurAAAgAElEQVRoA2EjxpjqvZWEPCKANZ1HiBFlkcEUBsFa+KqCbzuEzkIWBVRZACEg\nNC2EkunntHGj0sDn+lo11+3HgEREREREB8QNTpCic4gxQpnVS0VjjGhaByHEoiFNGgN54wZ826ag\nVNcIXQshZar1LgcbuS9FhwkhoNX1/VozIBERERHRAZssaFhW732vdj49yjXkPZXeKs8hsywFpKZF\n8A7SaKg8P/dnpfsTAxIRERHRNTdfsJqb44/MzQsa1AYLGoQQK6dTMUbU3cHp0b2EENCDAWKew7ct\nwxGdKwYkIiIiomus6dyikjkWBkV+9Mu/sMEFscE5RB+g8mzldKq1HiFEFNnh6dG9hFLQ3HlE5+x6\n3qwiIiIiIngfUDVpGiOFwKyxaK0/8s9sckHsOu11TevT9OiYIEe0KQxIRERERNfUtLaIMWJYGoyH\nGaQQmFYduiNCUnSbC0jH7T9qrYcPAZlRUMdMj4g2hQGJiIiI6BqqGgvnA3KjkBsFrSRGg3S0bVpb\nWLc8JEXvNlLQEENAsA7SGAi5/CVo06bjfWXGXUZ0cRiQiIiIiK4Z68KimGFQ7E1rjJYYD1J73KQ6\nHJKi94ghQm6goGFverR8MtVZvwh06pru16Gzi8HDdTOE4Db2MfjdR0RERHSNxBgxrVOV9qjMDhUd\npJCUQlMKSWHxexstaDim3rueT49494iO4H270XAEMCARERERXSuzxiGEtEPI6OUv9YxWGJUmhamq\ng/MpJG2qoCHGiGj7o3tLwpd1aXqUcXpER4jBI3gLIRWk3FyQ5ncgERER0TXRWo+2c9BKHjuJyYzC\naJAhxIjJrIP3Ya+g4bwnSP1uJZktL2eo2/RxOT2io3ifppBKbXbvFQMSERER0TXgQ0RVpyWso9Ks\nVbKQG4VhaRBixN1Zh67t0pRnRYnCqfVH95a111kXYJ2H0alIgmiZND3qIISCVKtr4s8DvwuJiIiI\nroFp1SHEiEGhT3RMrcg0RoMMMQRMZi1aH8//4ZyDkOJQQAohLpbYcnpER1lMj/Rmp0cAAxIRERHR\nlVe3bnGHp8hOHjRyozDKJKQUaFy6lxTj+QSlYC0QI6Q5WM5gncfdWQvnA4xWK+9LEcUYtjY9AgBG\ndSIiIqIrLISYKr2FwLA4/YtHhYDxIEOjTL+wNWI0yM68sHVR793fPwohomod2m6vtY7To+slhIAQ\nA7Q6n3+v3rUAtjM9AhiQiIiIiK60unWIMWJQmEOV3icRnYcUAjd2SlStR2s9dmctRmV26ulO6DqE\npgUgIIyBdR7T2iKECK0khqXhvaNrJoSA3XaCgIiBLlCY4kzvL8aAGOzWpkcAj9gRERERXVneBzSd\ng5ISeXa25rnoHYSSkCq12w0KgxAiJlWH1vrj38E9grVw01l630WOWeOwO+sWFeQ7w4zh6JoJMWDS\nTREQISFQuQaVrc/2Pl2LGOPWpkcAAxIRERHRlbVYrlrotVrrVoneI4YIuW//0TzECKQCiHmZwjqC\ntXCTaXrfZYnKyUX9+I1RjkGxXsseXR0xRky7Cj4GFDrHTj6GEhKNa1F1pwtJMQaELU+PAAYkIiIi\noo1rWoeXdhs0faA5D84HtNZDK4ncnHV6tHz/kRbAUHqEqsJsUmGyRnnD/nDUZQWmXUSI4NTompvZ\nCi44ZMpgYEpIKTHOR9BCofEtpt3sxMUfe9Oj7Pg3Pke8g0RERES0ISFEzBqLrj+iVrcOeabOZXpS\nNSlsDYqzv5wL8wWxWiN6n+4Odd3i10cGmNUNZk0LOyxx4+ZoaXnDPByFGNGoHN4DUgoMC4nBGQok\nrqMYI2xwMPJs07/LoLI1Om+hpcbQDBa/LoXEKB9i2lXovAVihWE2WOvz3ZseSQi53e8dBiQiIiKi\nDXA+YFKlOzdGK0gp0HYOnQtnnvhY5xfLVY0+4/QoBISuRWgaOCkQw97f8ktjIPMMQimYosXu3Rna\n3SlebBrceGAHebl3L2QejqwPaGWGKCQyozAszJmb8K6jxrWoXQMpJAa6QLblKcl5aVyLxrVQQmK0\nJPxIITHOhph2M3TBInQzjLPhsSFpPj3Spth6gGRAIiIiIjpnTetQ9e1yZa4xKAx8iGg7h6Z1Jw5I\nvm3h6wZSKwitMWs8IuSx06Po/d4/IQAxpgAUQzruFGKaZNy9C0BAFsUiFEljIOTecTg50nigLDB7\nZYLJpMZLv3gJ43GJwY0RECPcZIqqdbAmh9Tpc2Z993IhBrSuhYBId3dsBe07DEwJLc8WeLep8xaV\nrSEhMM5GkGL58UkhBEbZELOuQhcsJu0Uo3y48u0vcnoEMCARERERnZv9R+qkEBgPs8WER0mBzCh0\n1sO6sHZ1dowRvqoQQ4T3Ht2sQV1b5EYhSgunUmgSUiI6h+gDYvCIzq+88yGEAKSA0Aqh6yCNgRqU\nyB64eSAUHfpzSmH04E2YYYm7L6Wg1DUdBoXGtLaIRQmdZ2eqBr8fdK5b1GAbZVDbBl2w2G0nyFWG\n0hQrw8Nl4bzDrKsgIDDKR5BHfN8AfUjKU0hqfYdpO8NOMV76tsF3/d2j7U+PAAYkIiIionNx75G6\nYXn4aFmRpYDUdg5mzSNVoW0RQ4QqC6g8x/SVGVQuMSgEgnWAdQDaQ39OKAWlFSAVpFaAlH0wSv8b\nY4SfVRBCQg+H0OPRkeFov7zI8eDDGe7encFWNe5OO8hBibwsMCrPto/puosxonEtJAQynS3u6dh+\nGtP6DtZbFKZArrJLeT/JB59KFxAxzoYnmnoNswFiF9F5i8a1KO6p747BI/gOQsitNtftx4BERERE\ndEYhROzOugNH6g69jbXQWkMridZ6lCEeezcnxgjfNBBCQBUFWhcAbTAYlChKgxhjmho5hxiR9hhp\nvReGVr1f72EnU0TvIbWCHo0ONdgdR0mBB24OMc0ztJ3HoFj+edNBrU/To1IfnBIZZbAjNVrfobFp\nf1DjWmTSQEsFLfWxU5pt6LzFrKsQETE0A5hThJiBKWG9Q2MbZMosvg4xBjhb93ePygsLhwxIRERE\ntDBfDJobhYL3R9bWdOm+0ap7N8Fa2N0JZGaQ5yVcHdB27thAEboO0QeoIgeEQN06CCEWH0MIAWEM\nYNZ/kerbFn5WpSNMRQ41WK9VbBkhBMaDDMMicmq0hvn0SEAgXzJBFEKg0DkyZdDYNoUl3wL9nl4l\nJLTU0FLDXEBgqm2D2jXpWJ0ZnLpYQgqJ0hSobI3aNmmqFCO8rRGjh9L5hU2PAAYkIiIi2qfpHJwP\n8CHCGMX2sTXEGNF26c5RkS2fwvimAQCEzsJkGaQQaDuPMj+64tnX6c+pokDTeYSQJlSn+fcyP1Ln\n2xZCCOjRECrPj/+Da2A4Wk/nLUK/SPWoO0ZSSAyyEmUs4IOHCw42OLjg0foOre8AAFpqjLLBxu8r\nhRhQdTW6YNORwBMeq1um0Dk6lz6X3GcQwSIEB6kMlC7O6clPhwGJiIiIAOy90J//uGosxoOrWT28\nTa31CP3RumVhJ+0VshBKIvoAX9fI8iGazqG1HkW2/OVYmh55qDxHFBJN2/Yh7OQv387jSB2d3Xz6\nUqj1gqkQAlppaKUxjwxuHpi8hQ0O03Z2ZCPcWc3vG/kYYKTGcI1AlspBIsQxbzcwJXa7KSbNLoZK\nQUgFpctzfPrTufiDjERERHQp7H+hb3QqE5gvOKXV5qEyXxFcfJv+tl8VBVRZIPoA7S0AoGlXf319\nXac/VxaoWocQI4pcn3haE2OE3d1NYavIoXd2GI4uQOc6hBiQq+xMR+O0VCh0jnE+Qq4yuOgx7aqV\njYVn0XmL3XYK30+9xvnqKu+5GCOcncG2k/7IXFj5tlppGCHRdTO03kKb0x/3PE8MSERERARg78V6\nnmkM+/06s8Zu5IXXdWGdh/Np8euqY2+hS0faZJ5DlSWEkhBdi0wCPgRYdzgkBWsRnIfMDKou3VfS\nSq48wneU0HWLFjw9PH5BJ21G7dJxyXtb285imA2QKQMXHCbd7Fz/v1rbBtNuBgAYmQEGZr3Jjnc1\nYvAQQsD7Dq6bIvRHAu8Vg0eGACklOghclv/SMCAREREROuvhQ0CepfstSkmUuUYIEXXrLvrxLq26\nPXp6NC9ZkFmqaxZCQJVlKkhw6UVj0x0OSPO7Rw00mj4cjQenq3wObaoAP6/7RnRynbfw5zA9WmaU\nDRchaXoOISnGiGk7Q+0aSCExzkdrlzF41yB4Cyk1dDZe3CVytobtpghh778l88Y6AYFhsQMhFSpb\nn+nZzwsDEhERES1epO+fUJT9ca6m8/Bh/RddJ3nbq8z7NP3RSq5ciur7cCKLvXCi8jwtZg0eKqRj\njN7vHUMK1iJYiyYIdAFQMoWj0xQhBOcQrIM0hsfqLlBjz396tN/QDJBJAxvS8tbThqQQAibtFF2w\nMFJjJx+tXcYQfAfvWgihoPqKbqVz6GwEqQxi8HDdrK/xDgca6wb5GFoodN7C+Yv/CxkGJCIiovuc\n61/oG62g1d5LAyEEBoVZFDYcx4eIu9MWr0watPfB3aW6D5XLar2BvXIGqVXaTbSPHqa7Fsq1iPHg\nFMk3DarWoZMaSkrsDE8XjoB906OC06NVjrojcx46b+GiR6YM1Bmb31YRQmCYDWCkRhcsZrY68ftw\nwWO3m8JFj1xlGGXrFz+E4OBd2teV9hft/++IhDYD6GwIIRWC72DbyaHGuvkRvpldHfCcd6i6Gneb\n3Y0GKQYkIiKi+1zTH6Er88Mv3nKj1ipssC5gd9bC9ZOQWW0PTEWumxAiOushpUBmVlR79+UMsjhc\nWSyUgiwKGAGgS4EyxojgHGaTGl0UMFmG8RnCUYwRoe3S8tiMbYT3ijHAdlO4brrRkNS4FFKLDVdX\nCyH6+m2NztvF/aF1dN5i0k4RYsBAFxhm65clxODh+1CjzABiRQiUUsNkIyidpkv3NtZppZGrDD6G\nRY05kFr0atvgbrOL3W6KxrcpQG3wLh0DEhER0X3Mh4jWzo+JLX9hc1xhQ9M5TKoOIaRFqaNBlu4x\n1Ne34GG+GLY8onJ7Uc6wIpyoskiV2y4VMrSdx+zuFHXnYcoC42F2pj1UoesQY4TMOD26VwguBaOQ\ngqnvQ8x5s97CBYdMmjPvDVqHEALjfSFpt52isQ18WP2XG83+MoZsiMKsH+Tm94hijNCmhJTHV9Ar\nnUFnY2hzuDCkNAUkBGrboLENdpsJ7rYT1K5BiBGZMigRUf3z3yJ007Wf86S4B4mIiOg+1nZpepQf\n0Y42L2yoW4e6dRgUacN9Onrn0HQOUgiMh9kiZNlMo+0cqsZhWJrNfyJbtH8x7Kqv27ycQRX5yr+J\nF0JADwbInUdb15gJoJvU0Ebjxs3RmZf07pUzcHq0X/A2Na3FCKULBG8RfIeospXTj9Pamx5tL6Sm\nSdIAs67ql8s6oC9cMFLDyLRXSUCgsjVa3516+ev+e0RSrf99tur/E1JIlKbEzFao+ta/TBpkysAo\ng65+Cf/wg6+irV5AOXoI2cNvOtHzrosBiYiI6D4VQkTTpWNi+YpjYnNlrtFaj6bzyI2CEAKTqoPz\noS8RMFD77i8NCw3nQmpg0/LY93+VHLcYFthXznBMc5zMMug8g2lrdNMZpBC4cWt89nA0L2fIWM6w\nn3dNXyQgoM0AUhkIIeFsBe9baDk4t4/VuQ42uEUg2aZ5+1wIATY42JDKD1rfpeNrNr1NiAFaqHTf\nSErEGBGj7ydrHgICEKK/U9T/b/9zb+tD94jOQ64zhBgghECmzOIe1Gz3GfzkB1+D66Z4+FffhZsP\n/etz+5j3YkAiIiK6T83vvZS5Ofa+wbywYVp1mNYWIUaEEJEZhVF5+M8LITAeGNyddZjVFrqvDr8O\nmmOqvRflDEYfKmdYRg8GKFsL0TkUwwJZefYXm6z2Pigdo6sRvF2UBsynRVIZCK8QvEVU/lymSJ3r\nMLUVJMTa+4M2QUqJXGbIkaY7LnhYb2GDgw8eRigMdIbgW3iXgtFJCHHwHtF5Ke855nf3hb/Hz/7T\n/4LgLf7lG/4dbv/Kvz33j7kfAxIREdF9KMaIpnMQ4vjp0VxuFFqtFotNB4VZ2eAGpKN5w3IvVO0M\nT7fH5zKxrt8XdcRi2EU5w5rhRCiFbFhCihp6ePYXmyxnOCjdk6kQg4eUuq+gPhjWlS7gutm5TJE6\nbzG1FQQERvloY811p6GlghICmQcCQqrb7o+yCSEgpYaQCkKoxdcoIgIxpPuEMfQ/T3cL53Xem/Ti\ns/8n/ssP/wJCSLz2TR/FAw+9caMfD2BAIiIiui85n47YFZk+UUvasNCo2hSWVrW37Zcbda3uI80X\nwxarqr1jTOUMcnU5wzKqLCGMWWvidJx5OYPKNtuadhXE4FM4igFSZVC6WPqCXkoNKXW6j6TcWmUD\ny1hvMetSOBqf4k7PJsUYEFyLEFJ5ihACUmUQQkFKBQi59Gtz3vEneIt//sl/gG3uYvzg67Hz4G8g\nLx9Y8rwRP//Hv8KzP/kPULrEr735Yxg98Kvn/DTLMSARERHdhzqXao1XvdBfRam0tPQk9t9HMlqu\nFawuo/2LYfWK44LR2mPLGVY5j3AEAKFJE4H7vZwhhaPZooxBHVOUIHWO0DkE10Ie0U64ivUW0y7t\nHxplg63fO1olBg/vWwSfdpkJIaF00d+/2u5E17YT/OT/+p9Q7T4NAHj5F38HAMgHv4Sdf/Hr2Hnw\n1zF+4HWQyuDpH30Dzz/9f8AUN/H6t/yPKEcPbe05L8e/OSIiItqadEwMRx4TO0/33kdSSm7k48YY\nYV2A0cv/JvwsnA+omvm+qNUvn3wzX8x6MdOb4ByC8/d9OUMIbrGbR5tyrYa1xRQpuFQ+cIIpkvPu\nQDgy6uInpYeDkYLSOYRcXS6ySfX05/jJD55E17yMW4+8BQ//6rsweekn2H3xx5i89FM8/09/g+f/\n6W8ghEJWPtA31T2CX3vLx5EVN7b6rAxIRERE94kQIpwPqPvFsCedHp2FUhKDQmNWW+zOWsh9L9D2\nr0qKiFBSItMSZs0AZ11A2y+yjTHCaIWd4dmnJ97P32+AD2niptXqCVj0HsGmcoaLCiehYTnDwXCU\nmurWpXSB0E1PNEVy3mHSzRARMcqGlyMcxbCYnkmpIVV2oq/Dedt98cf46X/6XxFcg1e97r14+LXv\nhhAC5egh3P6Vf4sQHGav/BN2X/x77L74Y1S7/4ydB38dr/3XfwB1ASUXDEhERETXVIwpEFmX/nE+\nLH5PK7HymNimFJleVIv7PhUdij8iTbis80BjF4EkuycshX7Bbdv5RXiRUkBJCes8qsYu9jWdhA8R\nXR+25l8vIQQyo5AbBaNXf83WrfbelHT/6f4uZ5iHIwAnDkcAIKSCVKbfjWSP/fMueEzn4cgMkF2C\ncASkOvN0tLCE0hf7vfD8M9/DP/0/X4eAwK++8b/DrUfefOhtpNQY33otxrdei1e//r858QTvvDEg\nERERXTMpIDj4EFPzFPqlpErCaAmjFcrsYtrkBoU5Nrj4EGGtR+fSnZ90vM0unn8eYgAsWvjyTMFo\nhRAidmcd6tZBqZPtX5rVFk2/OBfAIphlS47sxRAQvd/3T0B07sTlDPsFayGUgpCnC66hbe/rcob5\nAlgAUGZw6hfYSuXpffn2yIAUY8S0nSLMw9EFB5G5EFyqM5fqQsNRjAH//OP/Hb/4f/8a2gzxun/z\n369dsnCR4QhgQCIiIrpWYoyYVmlPUQoUaeqh1cEX+Ze5bltJAZVrFHmaFHUuHXNzPsD1xwN1H34y\now608El5z30nefykLMaIaW3RWQ8lJYpcIdPqULufb1uEtkP0DjHEQ+9HKAlVLG9JO46rKvg6lStI\noyGNgcyyEx3V29t9dDleqG9T8BbOVhBCnCkcAetPkay3CIgodH5pwhEABNd/H5zj8tYTP4Pv8I//\n+c/xynP/N/LBL+H1b/kfkA/+xYU9z0kxIBEREV0j1gWEmOq7r3qlNpACT5FpFNneHSp5TOhRSmJU\nGkyqDpOqw41hvrLKPMaISWVhnYfRCuPB8mYv37Zw0xkA9EfY0j2jA/+cMnQG5+DrBkJJCCkRrEOw\nDqhqCKUgM5MCk1n97zNYe9+WMwTfwdn6XMLR3GKK5FZPkVqf9l3lKwog0iSnS/d/tjQRCd6m42nK\nXNgUxtkKP/nB1zC7+08YP/A6vPbf/Htoc7bdUtvGgERERHSNtP3Rszy7fi+ShQCkbVMd9jGtZJlR\nGBQGVWMxqbqlS2pDiJhUHZwPyIzCqFwejoJz8LM0ndA743Or457zVX9nZjiENAYxhBR4ug7RpvDk\n6yY92/zxFs85/99+cecFteddFO8aeNemfzdmCHFOe4fSFClD8N0i5OwXQoANDlrqQ4tgY4wIroHv\nA1QMDiIbHVpOe95ijPAufZ9c1PSoa+7iH+58Bc3sF7j1yFvwmn/1exd+XO40rt4TExER0VLzuzlH\n7em5ykKTgoIHYMajY+/6lLleNNHNGofRvomaDxGTWQcfAvJMH/i9/WIIcNNpascbj84/HLUtgnVQ\nebaYEAkpofIcKs8RY0S0FqGz6Wjf4mRfnD/g4qfHTZmukxgDvK0RgoMQEtoMzi0czSmdIwabCg+C\nT0tV+4/RrZgepZKIGjGGxQJW7zt4W0Nnw3N9vnsF3yLGkKq8NxzGlmmrF/DjO19BV7+E27/y2/jl\n3/hvL+Q5zgMDEhER0TUxLy44STHBVRG9T1MUKYAIuOkMeiyODQTD0sCHiLZzEF2LTASIosSk9Qgh\nosz1ytKIGCPcdJYWv5bluTfDxRDgq/7eTLm8ylgIAZFl920r3TLzMoYYI6QyULrYyAvxtFC1TFMq\n38H7LlVm6xyt7yAgYPplsDEGeNcsdg4pnUOqtCw4IvbP3GxsshNjQPAdhBCQavstivXk/8OP73wF\nrpvgkde9F4/0Nd5X1cYD0p/92Z/hBz/4Abz3+MM//EO85z3vWfzeu971LrzqVa9K/+cXAp/73Odw\n+/btTT8SERHRtdR2flFJfd34Or0g1oMBhFKwuxO46RRmZ+fIOzdCCAxLg1eeexmTtkWZa9jaQRQl\nBoU5eulrVaW9RpmBHpz/LhZf1YghQg8H9929odOIMSL4dnGkbhsV1lKZfYUNHUJw6JoGbdcgz4YQ\nEAcCm5AKWpcHpllKF2lpq2sh+mW0521e661NufVgMn3lv+AnP3gS3tX4l7/xO7j9mt/e6McLIWDa\nzTAwJbTaTJTZaED627/9W/z0pz/FU089hVdeeQW/+7u/eyAgCSHw1a9+FcV9dl6WiIjovFmXlpnm\n5nD72lUXrIVvO0itFnds9GgIN53BTiYw4/HKgBG9R5xOUaqImTGoGwshPXZujo8OR20L37QQSkGP\nRhv6nNoDnxOtlhafVojBQwiVgsA5H6k7yjwoxeBR13cBROjo4bpJCkb9vR+lD09vhJBQpoTrZvC2\nhsiG5zrx2l/rfe9dqU3bfeHv8dP/+D8jRI//6r/+EB581Vs3/jEb38JFj4DDTZLnZaMB6bd+67fw\npje9CQCws7ODuv/bn3myjXFvPwMRERGd3nUuZ5iXGKjBXhOWynMgBLiqhp1MYXbGh/YHha6Dm80Q\nQ4QxGqXwmE5aFDpCtzWiWb5zKFibShmkgBmPzv1v5GOMcLP+cxpu9l7KdXD4SN32pyQLQiJIBZOP\nUJgi1YBLlY75HRHYpNRQOod3LbxrzrXV7aJqvV/++d/hH//z/wYIgde96d/j5u1/tdafCyHChwgl\nxan+MqdzHSQEzAbLHzYakIQQi+nQX/zFX+Cxxx479A39xBNP4JlnnsGjjz6Kxx9/fJOPQ0REdC3F\nmMoZpBQw+noFJN80CM5D5fmh+0aqLFNzV93ATafQ4/HidYar6nQsz7tF41smBR586CbaF19G9/Jd\nROchswxyX0FC9H5fKcPqydSZPqe6QfQeqsjPvfThutm/30ibcusTkntZbxH73UdpYrR+KJkftQve\nIsjDzXinse1a7655Bbsv/gN2X/x7vPzzv4NUGX7tzR/D+NbrDj9biPAhwPsUiHz/89DvEJNCYDzM\nTlQo03mL1jp4KzE0YWP/vRNxCyOcv/zLv8RXvvIVfO1rX8No35j6m9/8Jt7+9rfj5s2b+OQnP4kP\nfvCDeO//z96bxkiWneeZzznnbnEjIrOqurqavbHFptiiSVo0hxyRY0MkbVIiZWPMEUxTMwMt1h/D\n8B8JsAHDsH54gSDYsmH94sgcSNDAACVAtmFhYFqGJVke2oYWNmmZ1NbNJlvsvbu6qjIj4m5nmx/n\nRlTuGZEZmZVVdR4gUZmVsZyIvBFx3vt93/t+7/ceejtPP/30WS81EolEIpG7js44ms6Tp4I8vTtd\now7Cew+zkD3EcHho1cDXNRgDSYLPc0Tb4tsWtIa0zwVKEsjzkDM0nUHbQprcvk0pIU3DdZwLlz0D\nYwTvHMyq4M59xGOKAN6CD25xiBwugCNabRuMtwzVAHmS9XgHPlR8Tv2YvO9vy5/d8+M16DdAvxq+\n7Pbt38khjP8cJFd2XcV5T9M5jN1/c1KEl5oQAm08QkCZS9SSlaRJ2zDtNANVMC6SI6/3/vefvN3v\nzKXmF7/4RT73uc/tE0cAn/rUpxbff/jDH+aZZ545UiDB6R5sJLIKTz/9dDzeIudKPOYiJ2Vr2mKs\n49K4WHqjcTccb2Y6w7YtybA8ck7He4+ZTLFti+86nDXgQ0ueynPUoNhVfbJNg5lVJOUAkSShStXp\nxe9VnpOMzqb1TW9PcFqTjIahTfA+YdXjzXuH6aa98UB5aFjreeKc41a7TSITNvKTz6UtqmJSheym\nE4rkeQaU6qtZ68J7z/b1P+K15/8z01vP431QOlKmjK6+k40HnmLjgacohtf2rV0bx7TucM6TKEma\nSJQKAkhJsevyTWeY1RopBBvDDHVMJanuNK/cvIGUkkcvP0CaHH750xZVzlQgTadTfvqnf5pf+IVf\nYOAmBFAAACAASURBVDwe7/vdj/3Yj/GzP/uzpGnK7/7u7/LJT37yLJcTiUQikcg9h7UOY0OrybLi\n6G5gFRMDIQTJeITe3sY2LarISTfGwZr7ABtwmWWIqsa2HVl/GW9tCGZ1btes0zoJmUcamab3lTha\nlSCOKrz3qGRwIcQRHJ59tCpSpUjXh9CaBpWu7pB4Vrbes1vf4sVn/x3Tm98ABOXGowtBNLz0xJFt\nfE1rmDXhRMNxDpEARRZ+P6s127PuSJHUdIabkxlCwAPj4ZHiaB2cqUD6whe+wK1bt/jxH//xhTnD\nhz70IZ566ik+/vGP89GPfpQf+IEfoCgK3vWud/GJT3ziLJcTiUQikcg9x71qznCQMcNRuKYJMz1p\nQnb58pG5QUJKZJZi224hWIRSh2YRrQNv7SLzKBmejQC7VwhBqxalsjO38V6FvdlHp2Fh/W07xAnm\nh27bepdradNsZq/z0rO/yq3XvwrA5oPv4tFv/z4G47cce13vPbNa02qLFIJRmS49G1RkCXiYNYeL\npLnwst4wKlOG2dmbUZypQPrMZz7DZz7zmUN//0M/9EP80A/90FkuIRKJRCKRe5q2C5uS7IzPqJ4n\nRxkzHIQzJoTIKkV25cqBznR7kXkeBFLbLXUfp8G2LXZW9TlOg/su88iaDlzIEDpOCFhdL0wHTlJZ\nOSuMNVjvyFR6stmjPcxNJ4xe3fp7bustZXJkda3afpGu2SIrNknzSyRZue8+dLvNy8/9R66/9Dvg\nHcPNJ3j0qb/I+PKTS63FWsek0ljnSJRkVGYrV7KLvtJ0kEiaiyPvHUUhKdIMucTr+7RE65RIJBKJ\nRO5SOm1x3lNkyT0z7O+dw9Z1yJVZIpzVe4+Zzm67zi25eQpVIxna6vx6zsIftDY7q7BtCDa93+aO\nIAgeazvAYrpZv6nPDtzYW9OFiopUqOTiiCMI7mlw+va6ncxzi1ax/vbeY3UDHG7r7azmxWf/HW98\n67/uvj+hSItNsnyTtNhEqpQbr/x3vNMUw2s8+o7vY/PBdy/9Wmi1ZVZrfP8eVBbLvw855wAWYmeX\nSKo6NsqMzjiqJswoJTloL9f6/B9FFEiRSCQSidyl3Gvtdd57bFXhnScZlkuJHVtVty2zV6wEySzH\n1jWu69YuXJwxQbhZi0xC2Oz9VDkKG/kK50zIBxIZUiah+uEMwihUkiFkihBikXUUKitnI1hPivee\nznZIIUnXPA+lkmJREXJSHztv5Wy3aD88KHep2n6Jb3718zSz1ymG13jgkfej2wldc4uu2UK3W0xv\nPQ99yGqab/Dw2z/F1Uc+sFLwbtVo6tYghGBUZuTp8tf13rPdTkAINvLRoiK3UyRtzbqQeyUFG2XG\nRE9D9tE5zaNFgRSJRCKRyF2IcyH7KFFypRyR4/DWYqoqGAkcYI7grcXMKmSerVVUOK0xs2ohKI4z\nZphfxzZtmB86gbGCyrMgkNp2qcfitMZbi1AKkRx+ttzWdcg68h41KFCDOxhsegfw3mF0hXc2BKSm\nJQhFkg0XczfOdhhdI0SLwWNMR67S3tXtYrWLaqtxeIozql4kSd9qZ2qEVIc+/mDMEKqRMsn3/e61\n5/8zL3/9P+C95cG3/jkee8dfOlBweWfR3QTdTRkMr62Ux+S9Z1prOm1RUjIu02Pd5/bS2g6HB++p\ndM0ou+0YWeQJniDA5uLIYXHeUaj83F5HUSBFIpFIJHLB0H1rSaIkWaoOdGxaVI9WOHN7HN5a9GSC\nty7YXnu/y7ggtLNNccYGcVI3JMPyVDM8c0E2t9meC4pjr+ccZjpdtK6dZOMklEKm6S7hcxiu69CT\n6b7rCyURKkEmCqHU4rEIKUjH4zOfb7poeGeDOPIumCzsmSMSUpHIAT7Jg0gyDdv1BACTSYbekXGx\nKm3tEe511eRlvDMUw2snttoOrXZ5b9t9eKvdbWOGwS4R1dY3eP6rv8T01jdJ8w2eePdn2Lz6HUfe\nX1ZcIisurbRO6zzTqlu4Zo4GKXLFeSPvPY1pEQiUkHRW05mObIcZxyBPSHprcCkFdVcDkJ2jm2EU\nSJFIJBKJXCCc84scEWMdTWeCCUOqdomltrOI/v/Xcr/GYCYTvAtVD9d1mKrujQXChs1WVW+ekAEC\n27bo7QkyTUNL3AotZN57XNMsKi0yTVBliUyW25qY2Sy04pWDpa9zEDLPFpbiySFVKNd1mOlsMRfl\nncMbi7cG11lAszMTU6ZpEG3nMEx+kXDOYPXcnrtAJYdX5YSQqKSgdQ6ZFKQqwQnBtJuRyoQyHaBW\naPk6K5xzaGdIZLJYj/ee6c1v8Mpz/5HJzecWl03zTYrhNYrRNQbDaxTDa+Tlg0iV4p3Fe4f3/b/O\nwvxnF/413QzrNLJvO5znD6mkQMg0nLBIS5K0DCHKwI1Xvsy3/ujf4kzDpWvv4Yl3fZokW3+Gl7GO\nSRXel/IsYbjCvNFOtNWLalCeZGy3Uypdk8hkl/nC/H3OeYe2BiUkyRrcA5clCqRIJBKJRC4Qs0bj\nnGeQJ6SJpNUOrS1NZxZiKU0k1jnyVK18BvcgnNaY6XQx+6OKAp/n6MkUWzfgPTJNb7ezDUPFRhY5\ntqpxWtPd2kIVeWgnO0YY7GynE1KQDFczL7Bti+v6PKFTWnPLLEPICtd1cIBACs/NDIBkPNpXEfLW\nhgwlY8FZRJIs1R54r2FNt2uGaNnsos4ZkiRjs9jAeUela7QzbLUTCpVTpPmpXOOMNdSmoUjyE82v\nzLOPMpXivWdy41leee7XmN76JsAiMLWZvU49e53JjWeZ3Hj2xOtdFiEUMsmxukKqnCfe/RkeeOQD\nZ9KC1mnLtDdjWCbf6Cga0wJQJDlSSsp0wExXzHTF+IDwXW0NHk++xqynZYgCKRKJRCKRC0LTGjpt\nSRNFWYTNXJoofJFgrFuIpXWaMzitMZNpqBTtcFkTSpGOR71Iqulu3iIpy13tbDJJkBvjRbXJNm2w\nzS5yQAAenMd7F2bCvcP7ICqApQXVTry12FnVC6vT5wkJIZBZFtbeZyLtfW7gYHEE8zY7hbw4cT3n\nzk5xpNJy6Uyfrq8m5CoL1xWKcT6is5pa1zS2pbMdRVpQHFGNOgzvPVNdhSpEZxgkBYN0efHamS5s\n6D00N7/B89/4dWZbfwLA5tU/xcNv/zjDzbfuuo41Dc3sDZrZ6/3XG4BDCAVCIoRCyP5fEeaNbv8s\nCYUhh5RpyErCY7oZRs9wVuOdXrTiWdMw3Hwrb33n/0ZePrDy87MMc5vtk5gx7EVbjfE2WKX3r/k8\nydBW0zlNY9p9f+d2IVDP9wUWBVIkEolEIhcAYx1VGypEw8HujbgQgjRRu8SS8ywdxngY89YxgHQ8\n2heuKpQi3RhTv/wKtmlRRXFgG53MMtI0xbXtwqDgIIQQIEILmjpBa5y3NlS6vCcZDtfmCifzvBd3\n7UIE7RJHo+F9N0u0LME4oOkrR8OVnNA608/27NkUZyollQmtaalNS6VrjDO7hvmXodYNrs8uMs5S\nmwbjDMOsPLIq5VyoZFXNTZpbzzN9+UvUk5cAuHTt3Tz85McpNx478LoqKRhuPs5w8/GV1roT081w\nzoRZI5lguv44zEbnamAxq/Wiaj0qswNnIVfhdvVot0gtswGmMdS6Id3RymidxThDuqf97jyIAikS\niUQikTuM955pFVpYjgtanIulU9+n1uhJb3JwSHUECKIhz0EIEAIznQbL6j2tPEIIVFEgswxvzOLy\nov938f1J1mottm6wbdhgqTxfq4OeTBKEUrhOh3kQaxdVtYOEY+Q21rT9zNFgJXHknKNzmkQokgOu\nJ4SgSAuyJGPaVXT24ArDYRhraGyLEpJhWuLxVF1N5zTbzYRhVu5rubO65sb1Z9h684+pbj2Prt5Y\n/O7SQ9/Jw09+jHL8yNKP8aSodIDvpljTIGRy+/k9R3FUNUEcKSkZD1cPf92LcRbdi529f28pJGVW\nMu1mzLrQaieEONIc46yJAikSiUQikTvMrDFY5yiyZG2mC0dh2xaaJrSpjY4QR8Zg6waZKLIrD2Fn\nwaHNTKaoIogmIeUuASSkRKxJUHhrsU2Da0MmilAqmDKcgWBReRbaBKsap7tFy2EUR4cT8nvmwa6r\nPU+Lze8xgkcKySgt2W4n1LohOWCDvRff20cDDPtMJYFglA9pTEutGybdjEFSILoJb778JbbffJZq\n+0Xm+UBCpmw88BTjK9/OpWvvphheW+nxnYa5gYXRNd7qEz2/p6HpDHUbxNHGMFvLnGNjQlX5MIGb\nqZRMpQshPEgLOqsR55h9tJMokCKRSCQSuYO02tJ2hkRJyuLsP5bnAaYIQTIeH9rmFiy9Z30VZYxU\nCjEeBZvvTuO03ncdIQTIIJJO0wLnnQvCqGlvC6NBsfYw153IPIeqXlSpds5jRQ7G9pveVe2tvfe0\ntkMglrJulnJnhWHGRj4+shrZmhbjLbnK9jmfFUlOIhMmzTavfOPXuPWt/xLc4oQk33iU4eUnuXL1\nTzG+/G1Lz1KdBVJlyD5A9qT24SchRAyEtrpxubqN90FYZ+lsqBYeJXbKdLBohRSwaz7tvIkCKRKJ\nRCKRM2Buw3vUh7t1nlndD0AP0nPZCNhZmDmiKI6cAbK9y5waFIsKU8gcGgXHN+fCY+y/vPO9CYPH\naYPe3j6yOnXo/e4IWRVKkgzK4DR3xs+NkDIEx7ZdFEdLYE0XgmBVtrKQ0M6sHPyZqZQiyWlMy0xX\nh84jWWepTYtEHGrI0G6/xMt/8Ms001dR2Ygrb/sYwytPMRpcIj/HSs1xJGmJT9y5tdbNc46896Gt\nbk0B1G0/a3Zce6QUkmE6YNLNqHrxfSfa6yAKpEgkEolE1k7TGqrWAJAoSaLC3FCibs/hhLmjsBkZ\nDlZPoz8JtmkWOUbiCHHkug7btshE7bPRFkIcKx5s22JnVWjFG5ZLiQ1vLWY2w2kTWv8GA2RRnOvZ\nYzUcBle9NZk/3KvsNGY4KuvoMNp+WH9VMTJICkxfjWhNd+D1K13j8QzT/UYM1rS8/PVf5fVv/VfA\nc/WxD/Hg2z6OVymDpDh3I4BlOC9xNH8/ct4zLNK1zDlCqAK1tkMKuSsM9jBSlVKofDE/dp7ZRzuJ\nAikSiUQikTVhrWPWGLSxSBFS4LWxaAN1a0IFphdM3gfnujxVFNnZfxx7a7FVjZACdUggKvTipqoW\n1aKTCBSV5wgpMdNpaOdz7si8Itd1i+BXmaWhPe8ObFaFEBDF0bHsMmZYcQN/UPDqsgghFvNIIVxU\n7bqN1nRoZ8hkum8zvvXGH/GtP/zXdM0t8vJBnnjXpxlfeXKl+7+XmdU6vB9lCcUpco720poOj2ew\nQpvgIA325ndi9mhOFEiRSCQSiayBedXIe0+WhhwjJQXOeYx1aOP6f4NgApByv6X3WWGq6rY99gHi\nw2mNrSqcsaEyMCxPVUmRaUq6sYGeTDBVjbeOZLS7Lcp7j62qEEArxCKkNnJxWRgziJMZBzS2t3o+\nYevUznmk6Y55JOcdta4RCMr0thg3uuKFP/y33Hj1KyAkb3nyYzz8to8tHWR7P1C3hlZbEiUZrnEO\n0ntP27c7rtIqJ4RgmJ0+4+w0RIEUiUQikcgpsNYx7c++SiEY7glTlFKQSbVwp3POo63D9tWjc5k7\naltcF0JQ97a7BQvtGtuGOQGVZ2trMwths2PMdIptW7xzJONQlZqbRXhrkYkK1apYvbnwLIwZVghc\nneO9pzMd8pTOZNmONqxK1wyzkkrXODxlOli0yul2m2ee/r9ppq9SbjzOt737rzIYP3zi+70X6bSl\najRSCsblemf9WtPi+urRnTBaOA1RIEUikUgkckLqNtjheu/J+6rRca5PUgpyqeAc7Lyhd4Sbt8wN\nb5+V9d5jqhrXBEMEmSaowWDtgahCKZKNDcxkGsJXt7eRWbYwYlBFjirLu24DdT/i7NyYIT2Rw5u2\nGoenSJY3ZziMQVpgnAl24R3BJU0mCyOArr7JM09/jra6zoOP/zkef+dfPtccobuB+ckdIYI4Wodj\n3RzvPU3vVHiRjC+WZakjZWtri3/8j/8xf/tv/20AfuM3foMbN26c6cIikUgkErmoOOfZmrZUjUYA\n4zJjtOYNxrqwVY13HjUoFhUa13Uwm2HrGqQgGQ1JNzbWLo7mCCFIN8aoPMcZi6lqEJCOR6HlL4qj\nC4/3LgSXCnFi2+l1Bn/O27AEYmEZPuxb65rqOn/8u5+lra7zlrf9BR5/56eiONqDc55JH049HKQk\nazaJ0VYvbLr3mmXcDSy14p/4iZ/g4Ycf5sUXXwSg6zr+zt/5O2e6sEgkEolEjmNWa6pG02m7sNU+\na6x1bM+6hcHC5ig/l3DXk+C0xrYtQilkP9vjjEFPpuBBDQakm5vnZmmdjIZhzijPgiCLIax3Da43\nZpAqP5HYcD6YM6QnMGc4DCXVQhQVSY6Sinr6Kn/8O5+la27xyLd/kkff8X1RgB/AtNZY5xjkya6W\n4HXgvV/YdB9n7X1RWeoIv3HjBj/8wz9M2p9Z+uQnP0nTNGe6sEgkEolEjqJpzSLxfVJ13NhuFlUd\nbdyZCCZtgjiabywuatUI+ha6WQVAMrzdwmar8H8MCpJycO6bR1UUcd7oguO9xzuLsxprGoyusL0x\ngzxh9Ue74EyySvVIt1O233yG1//kv3Dr9T/A2f3hxFmScanYYJAWzLZf5I9/9//CdBMe/45P8fCT\nHzvRWu91ZrVGG7swk1k3la5x3l1Y6/RlWLqBVGu9eBO9fv061fwNNhKJRCKRc8Y6T9WGtPfhIN3l\nEmesW1hqp4mkzJO1ZAw1naFqwiZvOEjPxZr7NNi6CUGvRb5onbNti9Pm2BykyP2HNR3eG7xzeG93\n/c55R2M05WDjRILae4/25lBzBu8s9ew16skr4Wv6CtXkZUw33XU5qXI2r76TSw+9h82r71y0+kkh\nmd78Js9+5edxpuWJd/9Vrj76XSuv836g6cKJJSUlozNw0NRW09qORKi7tnoESwqkH/zBH+TTn/40\nb7zxBn/jb/wNvvrVr/L3/t7fO+u1RSKRSCRyIHUTeufLQUqW7naIm4slbRydthjr2BjmqFNUeqpG\nU/eCbFSuL0RxnSwqZt7jrcU1DULJRebRTrOGozKJ7me0cYC/kH/fs8SaduFOJ4RAyiS00QmFkJJp\nV+ESwVQ3FH51V7LOajyeLNnvkhbMFP5v2uqNXf+fFZfZfPBdDMYPMxg+RDV5iVuvfY2br/0eN1/7\nPYRM2LjyDi499B5UMuD5r/4izlve9qf/T648/GdO/6Tcg2jjmNUaKQTj4Xod6yAI6dncaj27u41X\nlhJI3/d938f73vc+vvKVr5BlGf/wH/5Drl27dtZri0QikUhkH9rYRWbH3irOXkvtujVUjWZadWyc\nYEPgvWdWa1ptkVKwUWZrqUadFlPVuLaBhSY6uJ0wLYc7WuuCWUNSrsfC+17Aex+EtHFobXH985il\niuESjoR76XSovCRKrr310jqLdXZfAOppCa10fQ5VOkTsmQ9qTYfxjkQmeO9oTIu2mmE2JDlmlsg5\nR22ahTlDoXZXFNrqBs986Wfpmptcfui9jC4/STl+mMHoLah0t4i/8vD7ePQdf4l6+gq3Xv8at177\nGlvX/5Ct638IgBCKt7/3h7l07d2nfUruSazzTKvwdxiV2alOGB3GvLWuTIpjj42LzlIC6etf/zq/\n8iu/wt/6W38LgL/7d/8uP/qjP8pTTz11pouLRCKRSGQnQbDcbnM7jkGeYK2j1ZZZrRmVy28ug8tT\nMGNIlFy7De5J8N5jZ1UwXpACoSQIQViVoP8GIQQiSRYmCAeZNdyvzHOotLZ0O2bVpBDkWTheOm2x\n1jMql3P32pmFNSdRkkRJ0kSeSjA572h0uwhYLXub7HXgvceYOgQIp+U+ceSco+orAqM0VARq3dDY\nlkk7ZZDkFAfkIc3X3NoOj0cJyUDmu+ZRmuo6z3zpX6CbWzzy7Z/g4Sc/fux6hRCU40cox4/wyNu/\nl6a6zq3Xvsb05je49sR3s/HAO07/pNyDeB/EkfOeYZGSJus/ydNZfdtq/QQZWReNpQTSP/gH/4Af\n+7EfW/z8V/7KX+Ef/aN/xL/8l//yzBYWiUQikche6tYsDBKWtaUdDlKs87TaolrDID/+o89Yx6Tq\ncC7kGw0H6R1vF/HeL7KEZKJIxmPEkgPQc2OGnWYN9yPa2IW1MYCSkixTpInatWmct1RuzzrKIjl0\n3sx7T90ami64KGapQkmBsb6fhzM04aT9QiwVWbKUWPLe09qORje4XmR476l1szYnOGfbPtcoQx4w\nG1TpGo9nmJYLcVNmA1KbMNM1lWnonGGYDlBS9bNKLa0JwkgKSZkMyJOMZEduUjN7PYijdptH3/EX\necvb/vyJ1l+UV3nL2z4Kb/voia5/vzAX70WWUCzx/rcqzjuqrtpltX63s9SzZK3lAx/4wOLnD3zg\nA+dmpxqJRCKRCISz9E0XWt2WETlz5iGIW7PgcKekONKWu2kNVR/+OsiTM3F5WhXvHGYywRmLTFOS\n8WhpoWObBmcsKs/PLOfobmEuZObWxoe1S5ZFqBzNas2s1hjj9onk+TyHdQ4pBaNBtuu48n73PJx1\nHtMajPVsDI+uZGqrqXSN9Q6JoEwHeCuZNi2GFsmMjWJ8KrHrncWaFiEk6oCKVGc6OqdJZbIv6DNV\nKRtSUemazmq22ymZShezRlJIBklBrva3tdbTV3nmS/8C00157Dv+Mg898d0nfgyR45nHIKSJoizO\nxpil6mocnjIp1mbhfqdZ6pkaj8d8/vOf54Mf/CDOOb74xS8yHA7Pem2RSCQSiSyYNaYPNVx9lkjK\nIJK2Zx3TWrMhxb4K1K55o36I+SIM63tr0ZNpcKTLc9QKVSBvLbaqEVKgynvjzO5JcS7MGyVKLiV6\ns15ATauOVluM9YzLMJdUNcEJDKDIEgb5/qpQcFFUi2PIe8+0DpvVVtsDs2ess9S6oXPBzrpQOUWa\n471gq2qRQmG04EZXY63g8nB5obwT7z1G1wCodLAv18j52611w7Q88DakkIyyIZ3pqHRNazskgkE6\nOFAYAVSTl3n2S5/D6BmPv/P7ufbWP7vy2iPL02pL3d52rDuL6vFcSN8rrXVzlhJIP/VTP8U/+2f/\njF/8xV8E4H3vex8/9VM/daYLi0QikUhkTqst2oSzoCcNNUxU2CRMqo5J1bE5zBebWmsdkypUAxIl\nz2yIeVWcMZjJBO88ajAgWVHk2LqfLynLpdvx7lU6M2+DW/4supKCjWG2EERbsw4hgthSUjIcLD/P\nIYSgzBO0cVSNJkvkrg1rY1qqXrSkMmGQDhaD7pO6CycHipQiU1yfbnFzNsMawbDIl27bm+Nsi/cW\npTKk3P98VLqvCKSDY3Nssr59zjhDqo7YhJsbPPO7v4I1DU+869NcfeyDS683sjpNa5g1uq+gr244\nsgx7Z9TuJZZ6l7hy5Qo/+ZM/edZriUQikUhkH855qjp80A9P2SKSpYpBnizCZTeGGdqEAXvvPUWW\nUBbJhZjTcVpjJtMgcIYlakVzhWDM0CHTZOXr3osEC2/IVhxQF33WVpKEljvvg/nHIN9/nLSmQ4qD\ns34AlJIUmaJuQ8BxWaR473dVYMqsJNtx/U7bRYvUfH4kTS9xfbrdCypB01mKTB0qlJxzzHSweM9l\ngjdtCH1N9h8XneluD9svaQYhpSSTB7cNOmfYvv5HsP2fsN7wbe/5DA888oEDLxs5Pd57Zo2h7eax\nBGfnvLmKkL7bOPKT5sd//Mf5mZ/5GT7ykY8c+GHxm7/5m2e1rkgkEolEgGDM4Pq5kXV80JdFiutN\nG7amHdY5RL+ROGl1at04rdHbk9CmNR4t3OiWxXuPmQVjhnkO0v3Mzva6kx5DeapIlcTDgdXFStc0\nJjjN5SpjkBZIsf++BnlCqy1NZ0kTQW0bjDMkQjHKhrs2mmGzu//kQJakXB4Og4mCtQgfRFerLZdG\n+a49W9u3wHl8EGPdTVKpGJVX9u3tdrfWnbwl0znD5M1nufna/+DW67+PNUHIve1P/x9cefh9J77d\nyNHMrbznzpunqYQbZ5l2MzjIc0AI8B6HJ11BSN9NHCmQfuInfgKAz3/+8+eymEgkEolEdmKsW6S+\nr2LMcBxzZztjHUpKxmV6IfKNIMwNmek05NKMRycyVnBNE2aWihyZnM1g9t3ESdrrDuKwNqW5OFJC\nIhC0tkNbTZkO9uUWCSEoi5Stac1rkyllkZDJlOEBwZpVY3Du4JMDRZKjrcYIS5kItFG0naEzjjxV\nC7HTWb1ogTKmoRICIyQTXVM4R5Hctt9eVAROMGwfKkXPcPO132PrjT9YBM+m+SYPPPJ+Xt8qozg6\nQ7SxTCuN8548SxieshLemAbn3eKY9uwRSkKQCHXojNrdzpHvFFevXgXgp3/6p/mZn/mZc1lQJBKJ\nRO4urPNrn9dxztNpS93NM4/W2/Y2d7brTBiWvwgtdXPMbBYCXYflicSR9x7bNMGYYXB/GzPMOWl7\n3TLsFEfjfIQUkkY31KZlqiuyXijtrAxJ6WhcjTaWcT5glO83vjru5IAQgmFWst1OqU3DMBvRdmH2\nRErHrA/tTGQS5kO8BTybg02cSGlsyFZqbUeeZCihQmudUMcO23tnaarr1JOXqSYvUU1eZnbrW7g+\nqykrLvHAo9/F5Yf+NMPNtyKE5PWnnz7dEx05lHkgdqg0pqe28nbOLY6FjWK8plXeXSz1DD722GP8\nq3/1r3jf+95HtqPM//jjj5/ZwiKRSCRy8Wm1ZVp1JCps4o6yz14G01t5dzqc8RciWHqfhZuclOLQ\nfJs7halqnDbILD3x3JDrut7UobjvjRlgPe11h3GQOAIo0oJUpcx0Tec0ujWUacgDanRDZZpg2CAy\nvE0Wx/pOZnVwsjvq5ICSikFa9OuoSVTKpK3o8CgVrLYHaYH3DqPrUJVMBgipyNOc1nTUplm0e9Wo\nzQAAIABJREFUBop+BmovzmrefOXLVFsvUE1epp6+gndm12Xy8iqXHvwQlx/6TsrNxy/USYd7lb3O\nm6MyW0sIbGtDeNfe6uf9xFKfDF/4whcQQuzKPhJC8Ou//utntrBIJBKJXGy899RN2CTNg1XnFsqr\nfEh77+mMo2kNxoYz/SHrKCVP1Zm4L11EnNbYukYoSXKKKA3Xhs2uyu+9uYCTMG+vW7fIPkwczVFS\nsZGPFjNAM11R921LEsHGYESX+F2GDXPmr4U8Vceuu0hyjDV0TmO9pjUtUmVcHoxIVBLEUVfhvUf1\n4mhOnmRkKqW1Ha1pyZN84Zw3R7fbfP0rv0C1/QIAQigGo7cw2HiEcvwIg/EjlKOHUfdIQOjdgnOe\nyZrmjXYyDygWCHIVBdKBTKdTPvvZz/LUU0/xgQ98gB/5kR8hvc9D5iKRSCQSaDuLdSGdPe+duTpt\n2Z61C7e4vVlDc4x1/ZdHa4vrT8CliaLI1KkrUXcb3jnMbAZAMhyeuPLjjFlUoIS6v57Dw5i3163T\ngOM4cbSTPMlIZRLmgZzeZcYghaftgmFDniUoKXAuiCbZzyotQ5kNMI2BBIo0JxcFUqjQbqnrYOmd\n5KgDKgJCCIok3zdob51n68YLfOtr/w+222b4wHdy6ZHvZuPyWyijK+IdZac4ylO1L8T4NGircd5R\nqPy+rgIe+Q789//+3wfgB37gB3juuef47Gc/ex5rikQikcgFx3tP3ZlFC1yiJOMyY2OYkyaKTlu2\npi3TqkMbR6stVaPZmrbc2G7YmrahNaSfMRrkCZdGORvD7L4TR9DPHVlHUg5ONHc0xzV99ShuYIGz\naa9bRRzNkVIyyods5ONwnV4ASykYFElfjQ0tdVWjF66Ny1ZPZb+WjWzElWGYGem0xZoa5wxSZagD\nLL334n1wd9yedbz0J0/z/H//WWw34eoT38tb3/2/kw3fQt0GpzTnDnA3i5w5u8RRljAqVw/OPoqm\nb6/L7+P2OjimgvTSSy/xT//pPwXgwx/+MH/tr/2181hTJBKJRC44TWcX7lo7N3FpIkmTDG0sVRNs\nh1ttd103bFYViRLheynu6zOVtq5xnUam6alMFbxzuK5DKHkqkXUvoa1ba3tdrZuVxdFO9ravARRZ\nQtuF14lswjxJouTKg/Zz1zkpQgVqVk0ZDwRSJseKI+/DdeZV4a2X/zO3XvwNpMz4tu/8Ya685T0A\n5FnCtOpCcLN1jAbpmcwHRg5mnzgarPd1bpwNgb8yWdnF8F7jyFdfssMaVMVSfSQSiUQIH9JN3wJ0\nmMlBmig2RypspIxDySCGEnV/i6G9OGOwdXCcS0YnnzuC3pzBe5I8Vo/mdL04X0d7nXOO2jSLas1B\n4khri5ICuWK1ajhI2Zq21K1Z/HxSpBQkaGrTYt2ANN9vH76X+RwU3nDzm/+W7Tf+B1lxibe/70cp\nx48sLqekYHOUUzWaujVsz7pDQ3Mj6+WsxRGEkGCA/B7MNVqVIwXS3oM9HvyRSCQSaboQ3FoW6bEt\nQHmqLkz46kXDO4eZTkOFYzw+teOcbVqEEMi73Jxhbgh12j3Hutvr5k5vZbI/ANY7T11rrHEIKRiO\nVmt7SpSkyBKazhw5u7cM1nQkyiKExPjj12GsC2HMZsL1Z3+JavsFhpee4O3v/RHS/GCL52DEopjV\nQShpE6pJFyVL7F7jPMSR847WdkghyVSsQB8pkL7yla/w0Y9+dPHzm2++yUc/+tGFHeVv/uZvnvHy\nIpFIJHKRcM7TdLavHkXhc1K899iqwluHGhSnbolzWodg2Dy/q629vfdU0w4PlGW6ciVmJ+tsr9u5\neUz3bB6NsTSVxnsQIogl3VmyFVvkyiJBKXGqEwrOaqypQ6trNqQzPmSK1W9w6/Wv0dY3cLbDmg5n\nw5fWLc62ODPD2Y4rD7+fJ979aaQ8ev1pItkcZcwaQ9sZtmYdRaYosuVnpyLHcx7iCKCzGo9noO7u\nEyzr4sij/1d/9VfPax2RSCQSuQuoW4Pvq0exq2B1vLXYtsW1Ld55ZJqQlKdPordNA4DM7+7B6rYx\ni+H/2axjUKYkJxQ462yva0wbNo9JsTjuvfd0raFr+/spEtJUMZ22dK0hzVYLIBZHtKzqdspLz36B\nyY1nKTceY3zl7Ywvv51i9BCir2Y5Z7AmZB2ptETMXuPWK7/HKzf/gLZ67ZA7lUiZIVVGVlzi6mMf\n5Npbv3vpdQshGA1SskQy69vums5SZCq23a2B8xJHAK1pEYj7OvtoJ0cKpEcfffS81hGJRCKRC451\nweFKSkEeq0cr4bTGNg2uC05lQgrUoFiL25y3Npg8JOquNmewxgXXQ21RqcIZR9saylHOoFhts73O\n9rqQ09Uhd+TCOOdpqg5rPUIKBuXt9rIsS+hac6Iq0v77dlx/8bd56dl/jzU1UuXcev1r3Hr9awCo\ntGR06W0MNx+n3HgcgOnN57j1+tdoZq8DIETC5oPvCgGuG4+hkhypMqxPmNYWJUMl6DRiJksVaSJp\nOkvTzzO1nWWQhwiAe1ko6f49cd3thecpjrTVWO/IVLqy8ci9ysWKEI9EIpHIhWVePRoO1msre6/i\nncO1LbZt8fMA3DRB5jkyW99zaNswWC3XaO1trDuxu2DdGprWkCaSPDs+6BTCXNuNNyuMdRRlmG/R\nAqpaU71pyPKEwSAEECslyRJ55NrW2V7XmhaHp+yrR1pb2jq01CWppNiTQZNlCt2ZUEVKFeKE7WbV\n9kv8yR/8a6rtF5BJwePv/BQPPva/0LVbTG48x+TG15nceI6tN36frTd+f9d1hUy4dO09lJffTTJ6\nO5sbG7vs8733TKZhpmpdGTpzy/+iz0RrOhuqSv1c1b2Gd56m0RjtQMBgkJKsad7SOs9k1i1y5k5j\n2rEMbW/OUMT2ugX33hEbiUQikbVjraPtDErKaLqwBE7rYMDgwsyuynNkkSOT9X7seu9xbXDBk9l6\nWmOa1jBrNImSbAxXE3Jdn3cFLCzepQxzNfMg1L2Xr1tD1Z8pHw5zLm3kKCWx1tGVGZNJi9aWmXNk\nfduWFIJykB56LK6rvc57T7Oj9ahtdGipE1AMEtIDWuKEFGR5QtsYus6SFwneO3Q7QbdbJGlJVlxG\nyJ2CxfUzQQZnW1795n/i+ku/A3guP/ReHvuO/5Ws2AwuhemIzavvZOOBpwAw3ZRq+0Wmt76Jd47N\na+9m8+o7UUmOsY6taUvT2V0CqepbGQd5Qpqst2Ig+oDbIktCJUlbZrVm2liazpCnd39FyRhLUxu8\n8yglsM5TV5pi4A88JlbBWsd2nzM1yJOlw4JPinNuEWCcqCgL5sRnIhKJRCLHUvX2w2URPzaOw2mN\nmQR3uqQcIM/QOMF1XdikDYq1bDqbLogjCFWkSaUZl8tVGKx1TGuNEIKNYYb3QSTNRVDdGtJELdoz\nm9ZgrMNah3CeS+Oc8cbtx6GUZNC7u1VVhzUOLwRJJml1aMdrE8WwSHa1N3nve2v507fXtbbD4SmS\nHGc9dVUhpWA0Gu0zkHDOUE9epqmu01Y3qCbX0e0trN6iq2/i/Y48MCHJikvkgytkxSXSYpOsuIyz\nHa9+8zcw3ZRscIVHv/2TjC4/CYButxePTwiBUhkyycmKTcqNR7n62Af3rT9Y60u0sVjrUP33TWdI\nlDzTyo6UguEgpciDUHKO4HrXGPLsYMF8N9A2oToIYe4syxOscdRVF0ST58StlcY6JrNu4RJ6HpW3\nxoZKYrT23k38pItEIpHIkRjr6PrwyixWj47EdR1mOgMgHY/WVtU59P7asLlRa7D27voz/VIIxsOM\nujXh/xpx7PyDc57tKuQwjcpsYVOdJhJfJKGa1Fm0CV9zskTiATFQDIYHCzEhBeUwo6n7dibrGZcZ\nTRfWtzVzu0wBOhPa67I1zMktqkdSMdvexhpNVqZYW9PWU6rtF5htha968vJuEdSj0iGD8SPkgyuk\nxQamm9FWb9LWbzK58fUDHm/Cw09+D9ee+G6EUOAt3rve/tyjkmCqIJacFSny2+GuhRALEbuu1rrj\nUDIcP6MiCLK2s4sWvCwJgbinsTU/L/bNnQ1SnLBsNxMSmVAOc6pKL4xGihXb4rSxTCrdtzGnhxp2\nrJOd83XR2ns3USBFIpFI5EiqJlaPlsG2LWY6QwhBMh4daZjgncNWFUIpZHGy6o8zBqcNMk0Rpwxz\n18YuNs7jYRA4o0HKtvO0nUEKDm318d4zrfWiJWhvW9vcna3IktCqqS3eQ5EpjHZ0xpNm6ki3OiEE\ngzKIJN1ZdGsYD7NewOlFK9ewSNfWXteZDusMKdDVM7q2or71+1x//utUk5dx/Zn3sD7FYPwIw83H\nGYweIiuukBaXMHaIkCnDUY6UAu8strfXht55Ts/omi26+gZG11x99H8mLx841dp3kiUSKQRtZ3Eu\n2H6XRXruokRKsaiKtJ2l6eyiDTNRkrJI1jIzdhYYbWl2zJ1lmaK2NZ2bV1tD22U5LKhnHbqzeO/3\nzacdRqfD6w9gXGbndiJKW72okN7tbY/rJn7aRSKRSORQWh3O+KfJcsP29yu2aTCzCiEFyXh87KyR\nreqFuYJoGlRRrCyUFtWj4nTVI21CKx3AuLy9cRZCMC4ztmYtdWuQ8mAb6qoxaBNmXI6bl1BKUva3\nb62jaw1CCvIlxXcxSHHOY43DGrdwT5u38E2q8Jyuo71u1k6xumKQZLzxrS9z89XfwppQHczLqwxG\nTzHcfJzR5ScpNx49MDdI65CR1DYdWeqwvTASQvVucinwAMPNUy31SIQIrpNzEXnWrXXLrKfIE4o8\nQRtL3Yb3mO1ZtziGLlLr3aKlToSWOicN27rG40lkwiDJqXRNY1qkkJTDjLrqMNpRe83gmBbVpjPM\n5icneoOS86Kx0ZzhMKJAikQikciBWOep5u0492n1aD7vcRSmqrF1jVCSdDw+tprjtMa2LTJRiDTD\nNQ2mqoNQGvQzS8fcZzBn6BBKnqqNz9gwy+N9aFvbuzmTUrBRZmzPukX73c6z201rFvMsq9oQN/0Z\n82KwmoV3nidUpgsW4Em2MAXIU8W01r0t8sk3md476mabttmiffMPeeXlL2G6CVLlvOXJj/HQW78b\nlZZYU+OsRgh1aLtbmioaKupZgyhTVJLsEEbnR94bJsxziy4K8xMvxjpmtabTFm3cwg3vTlc1rAki\nXkpBkkPtKqxxSARlWpL3mUFjodhuJ1S6RmaSwY6W0GrWoRKJ7at31jqcDycInPM4PHmW9K+/86vq\nNbrBOEMmU+RdHC59Vtyfn3iRSCQSOZZpFYaFh4N07RkfF535hs06z+YwO/Txm9kM27RLiyPvPWZW\nAaCGQ2SS4Isc27RBKM2q2xWlXih558KXtdB/b7XBGEs+Gp74Mc6thF0/N3RYW49SklGZMak6prVm\nQ4p+8N8xa4JoGpUrut21BmePb607cD2JDBtO4zDGLq6vlGRzFJzbDmsf237zGW68+t9J0hH54HJv\nkHCJrNhECIn3DmsaXnvht9l66XeweoqQGVce+TCPfvufJytGi9tK0hJLjbUdppuRpOUuZ7oQ3Nqg\npEEDxibk5fCObPqVDH8jKbiQr+Wk/9s1naFuDFWjaTvLsLd2vxN472lqjXMOl1paG1o3C5VTpPmu\nvCApJaN8xKSdMusqxtmQYpAycx03tmq8P/g+hAjVzjQXJOr8jotGN1SmQQrJIF1fPMA6Webk1FkS\nBVIkEolE9lE1/Zn4VJ3LsPBFwXtP1YSqyJxprXfZXXvvcV2Hazuc1gilSMejpeaAbF3jrUUNikUb\nnpCSpBz0QqnBNW0QSnUNnn44/zbaWKrG4IXAlYLRCTYS1nnq1gUBXBxulz0nTUKFaFJ1TGYdozJl\n2rfljcpspZYoZ0MArBChGnQS5lWkrrX7BNZB4qiprvPiH/+/bL3xB4feZpKNyYpNunYb024jZMrV\nxz/MxoN/lsFwg+yA9kGVDkBIrGkwekaSDkEIrGlwNjw/WZHjKPBO4Hpb6DvB3WDPX2QJWTLPUTJs\nz1ryLKHME+Q5tt1575lUNbOmhsSTiyQYMaQDEnnw85hIxSgrmXQzpt2MMinRzpMXQeRJKVBCoJRA\nyv5LSLrOYLSjqTWD8mxNXWC3OBpnQ9Qhj+dOoq1jpi1SQKYkmQpzdOfJ/fOpF4lEIpGl0MYtZk7O\nOoPjIjEf+HfOo6RkOEhodch/qhpNIYMw8tosRItME5LRaCkbb2cMtm4QSqIGg32/D0KpxBdFEEpd\nh5ACISVCSryQ1J2lw6M2Q+Wls46taRAsyw7dLx6nD8YLxZIiJUsVwyJl1mi2Z2F2YVisfoa/bQ14\nKMr0xCGqh1WR9mJNwyvf+A1e/5P/D+8tw8238tC3fTS43TXbdM0tdHOLrrlF19yk2n4JIRUbj36Q\nR9/2F3CmxHO0kFP9gLvRNUaHGSXvPUIqVFIgZUIhLPVM07VmsQn23uP7tqv5l/eeLE8uZJXnvJjb\ng2ep6itJBq3t4v/OCu892hk629F2mqrqEALGxYAizRftdEeRqpRhWjJpZ7y6tcUgGbAxyo98jRUq\npXZhZqltzNLzeCfhbhBHjbE0xgIC52//nMoglNJzem1EgRSJRCKRBc55pnXY/I4G2bmetb1TOOfD\nRqx3Pxvkye0hdq1p6orprRYGwd1NKIXKMlSereQeZ6vQWpcMj26zmgslynLxf3MLbicUaR6qOVKK\nhTnB9qyj7AffD8NYtzBUEEKQp2LlYf0iT3DeU7cmONOteH3vPEY7pBIkJ9jseu9xtkOq9HYVqTEk\nI7Xnco43X36al57995huQppv8vCTH2PzwfeQZrtb4ea3671H245JNyVPCpQvsN6EcNpjXgdSZSQI\nrKkBSNIBUt3eUCeJQiV2MZMyF0YHYU1HOcz25Szdb6RJ33bXGqrWMK01YyHW3nLnnKMxLV2feQWg\nO0uhMsajkiJfraqTqRSrFdq2ZGlLlu0/GbKTuUPjbNb1806cOmz2IC66OPLeUxmLti4EQacJSkBn\nHZ11aBe+pBHnUlWKAikSiUQiC6rmtl3zner934ntN5Fn5Wo1n3lw3i+MBuZn7/Vkgus0A+mYSklD\nwuXN0bEOdQdhmwanDSrPjrT/3stO8TY3I9gpauZ2zbNaM+vbIvfm2zjnFy1LECpBZZ6Qpyf7+84N\nEU5S5dC9CE0PEUemm/HmK1+mmb6KMQ1W11hTY3WNMTXWNOBdCFrNN0myS6hsg8HwCsXwAbLiEgAv\nf/0/UG2/gJApDz3xEa4+9iHSbIhGMtV1EEQEUTTfFM+RMiGXGW0d2gCzfLmNpFRpL7zEgQJ4Luis\ncWH2RAmkkrfbraTAmFBFqGZRJM0p8gSlBNuzjmnVsXHETOCqeO+ZdFOsD8YLhcoRXpEqR5LKlcVR\naM3TJCJlPChJUsesqxhlx50UEZRlSjULYbNCipVn847ioosj5z2zzmB9X71P1UL85IkiTxTG+YVY\nmleVhmlyZhWlMxdI/+Sf/BO+/OUvY63lr//1v873fM/3LH733/7bf+Of//N/jlKKD3/4w/zNv/k3\nz3o5kUgkEjmEnZkkd9IGGOYzMoa2C85bx1VHVkUbt5izCi59u1vNbNviOo1MEwabG6B9EFPaM1xx\nGd5abFUjpEDtqAodx86Wv73ibSdZL1bmYaDG+kXLXdNXmJy/3Ta4Dhvhk25QzQECyXvP9OY3uf7i\nb3Hztf+xL2xVyhSVDkizMcXwGiopsLruW+KeBzyT6/vv69K19/DQt/158sFljFBMrcZ6B4BAIAhn\n7xOhkAgQIJFIKXFagIesWM1h76jwVpVIhuM83O8hgj/rn9coknaTJorhIGVWa7arjs1hvpbqdq0b\nrHcUKqfMBnjnmU3b3tJ79fbiWV+hTRPFlbJg1lV0TjPrKoZZeeSxJJVkUGZUVUddacqhWIsQvOji\nyDhHpS3OezIlGSQHuxcmUpBIxSCRdM5jnLt7K0i//du/zXPPPccv/dIvcevWLb7/+79/l0D6yZ/8\nSX7+53+ea9eu8YM/+IN84hOf4O1vf/tZLikSiUQiB2B71zZxAkeydeJcECJNH7SopMR7z6zRdCZU\nR05TTbLOU+9op8tTxWBP7soixFWI0A6nFKXyaONoOkOWypVEhqkqvPfhtpaYVdppFHFQ1egglBRs\nDLNdLXdSCKxzi9u407bJzjqs9ahEIqTA6Io3X36a6y/+Fs3sdQDy8kEefPxDbF59JyotFzM8h96m\nM0xuXaeZ3UQwwXZb6HbCxtWnGIwfwwBTZ/FYRF8hKJL8SFtjZx2zrkNKQXoKu/CDWGZTn/V/6yiS\ndlNkyaIaOukrSac5nrXVNLZF7XBya1uD9yHvaFUBNp+XSpRk3GcfDbMS381CoOwSIkklkmKQ0lS6\nF0mna3O+6OKos0EcgadIFMUS76tCCHIlyM/4NXGmAum7vuu7eO973wvAxsYGdV0vbPteeOEFLl26\nxEMPPQTARz7yEX7rt34rCqRIJBI5Z7z3TGuN7+2e70RIo/eeprM0fbVjbhAx3xTNmpCRsjV1lEWy\nsrOe9/M2syC8EiUpDzEYsFWFd56kHCxmjIJwTNmatkxrzeZQLrVxcV3XV6JSVH58GKN1nmnVYaxD\nSbmS+cJcCM1b7qxzd8QB7DC6ztA1b1I3L/HCs3/E7Pof4p1BCMXlt/wZHnzsQ4wuP7nSplfKhNHm\nNaS6hBCWPPc4Z9DOMHMWpOqFUXasMJrTtqEVMV+xerROdomkSlOWaRRJhPZO56Ht+pmkE7q+ee+Z\n6TAvNkyDaLHGoTuLVKsL43mlVknJeMcJJiEEo2zItBdJvpsd226XpgpfeNrGUFdBIJ/kODTOXmhx\ntNOM4Sxb5U7KmQokIQRFEVT5L//yL/ORj3xk8Ue+fv06V65cWVz2ypUrvPDCC2e5nEgkEonsYV6t\nmFt6n7cVsPeetrOLNjB5QLVDSsG4zGi1pap1Hyi5fDWp1XYxWyWFoBykhwos13XYtkOmyT6nuXnr\nYd0GV7thkeD7Cs1BZg3eOcyiEnV8a502lmmlcd6Tp2rfLNGyZKkiUaHydqfc0HQ3pZ68Qj19lXr6\nSv/9a3inF5dJBlfYfMv/xLVHv4uyvHzsbQYTBU1n9WJuyDuH94ZZU6G1phgkJFmKUBlSKPIVhBGE\nYFCjHeqEJhLrJIqkgxkW4aTJ3LhkeEzwre3DWXc64FW6xnnHIClIVLLIPAIoitVed/NWWCkE4wMq\nPjtFknaG6RIiKcvDY9SdPbH9d7UQgIMLJ47aXhxJEcTRnTgpdxzn0mT+a7/2a/ybf/Nv+Lmf+7lD\nL7M35+Ewnn766XUtKxI5lni8Rc6b8zrmvPd0xqONx3mQAsri7FyBnPc41//rCd+78D2EwMQsEWTJ\nwQPui9txnkY7jA3XydMQsOg9t78It+t9uLx1y92+9x5mM/DAsDy0HW7WWGxnKFzHrj20EOFLyvCv\nc2AtZBnimOpRqx2t9ovHlJ2TQcbajzf9BtS/D/rVXf/tkXgxRqsRpJsk6UO06hK3bliev/FVlJBk\nMiMR+zdy1juMM2hv8HNDBe8ROPCh2uOcR7cSqRRZkZCIhFQmu8I8j8Mah9Y+zB7lEnmH8or2YrTD\n9MdGlssTW6Mfh3O+P4TP7nGv63gLTooO68LrZa/hiHMebT3Ghtc/3L6c8ZbaNqG1Tha9RXt4jlUi\nSLPljhltQ9vt/L2ozOWRG33vPY1rMd6SCEUh8yOfa+89uvM4u9q6ALQzNK4lEYqBulhBsNZD40AA\nhQyfPReRMxdIX/ziF/nc5z7Hz/3czzEa3U6gvnbtGm+88cbi59dee41r164de3vvf//7z2Sdkche\nnn766Xi8Rc6V8zjm5jM+bReGYoUQFJki///Ze7Me2drzPO96xzVUVe/9jSQ/kqZIURQjybFsy5E8\nBE4cJU4CJYcEEiBwznIq6A/oBwj6D0ISBEKQHAVQDERwJNtyCAWObdmwLYuTKHH45r27a03vmIN3\nVXX33j0Pe1wX0OihqquqV6+qeu/3eZ77tne/i7dvm3PhTEtjKcoQslaC2l6vDWx0oYSlXmFz7aw5\no7MI2444TaimQbfnW/O6rufTjx4jBDx8Y4MUcyVjVn4nH5NQCvPg4NyFULFV9/gQ95Wyq7bU3Za7\nPN+OPvk2P/rO73J0+C0A1g+/zPqNL9NsPkez/hyZAx71HbqWPFxtsKrs+qeU6MOAm0NVjdQ0pkEK\ngQuOKTpiTuScEICVGisVIsd9y75UFqks41ACN5uVuZYDWEqZafQEX1Ztda3vxWb5NrgpMI3FVU8b\nhdKyWM7fwXM259LO5V2cRZjGXHNeLcVUzEQuqLrd9etbTJnDbiKl0hpslMTNRjNhp4ooBg8xpfl6\nmiGWcY9NtUZLVWbOOldmhlb2wmOaUmbyp1/TjFZXdv3MOe+NG4zUl1aScs70nSPFjK3UlYwjcs48\nno7IOfOg2ly5evosiClzNLtprq1C3+Nju60Yv9dXgO12y2/8xm/wW7/1W2w2m1OXff7zn6frOn74\nwx/y7rvv8nu/93v85m/+5n0+nIWFhYXXlhhTCRn1ZWG5a2WrjLqX+ZQwmz6EOdPCaIWSJUVeybLT\nepv7rW1xYxtGT6bsektRRJeQArn7Xl5ckdqRvCdOE1IrVHP+jmvoOvI40daGSVf0FOElVLk/IQTk\nhIRiR630bFWeOfUohCClxHYorX+7ENYXYVboqhT3uW/zw2//X2w//Q4AB299jc995ZdZv/HlU9f9\n8ONHRBIPqnYvjgCklKztipAigy9CaXQD5Ai5NNJZKdFSz7+XIQUQAqUrpLJ75zhbaYI/OxfpPLwL\njGMJrt0NyL+I/4N9u91UhIx3xWRESrEPzVXqanNxJ0kpM/aOGMvc304sORepKnWpUAw+4lwkhiJI\njE3Ul7S83RVq3lDY2X+fRCtJZRR2fn0LMXHYOT48PKKqBRvboKU6bq3LUDfn512FmBinb1JKAAAg\nAElEQVRPvH6WjSVNba9nd78zbmAWSUeuY3OBSBJC0LaWvnO4qVj920sMW8Yw7dsHXyRxlHKm8wHI\ntEbfqzi6C+5VIP3O7/wOjx494ld/9Vf3J9Qv/dIv8bWvfY1f/uVf5td//df5tV/7NQB+5Vd+hS99\n6Uv3+XAWFhYWXkv60TPMg+dKSupKU92To9nODGF3f/dpEqBkcdy7LTlnQteV2zwnxDWnRNh2JO8R\nSrF++AAxld3qE5vVZ+AvuhDgSi51z5oYHDEU9z3mCg5k8vy1Hx/z4+/+32wffReAg7e/XoTRw6ff\nx/tpYggTdWVozwnNVEArFSo6hnlOyShDpQ1KGhBiFkISISVCPH3+KiXRRhJ8Yhz8qZyhJ6+bUlkY\nxzBXjZoXr2r0JLvKToplpiaERIyJdFIwqbKAPi9n6iQhRMbekzMl86cxkGczDRcZh4CbIrY+fXs5\nZfwsjPIup0wJMuwfx3VE0k6kCSmorzl3t3OMO+o9SgoqozBGPVUt1kqiTWYaHEyGt9vS8uqmQIwZ\nbeSZ1a+TBjFw/Pppb7GxtBdJvsfFIpLWtj23HVRIQbMqImlXRTzvXN2F3kohqfXlpjDPimKKUboW\naq32dvYvMvf6avCNb3yDb3zjG+de/gu/8Av89m//9n0+hIWFhYXXGh+KAcLOFe4+TRh8iHRDIKaE\nlIJ1Y+4kc+e+iX1PjgnV1GeGwOYY8UdbcoxIa9Dr9exqp1hTFlE57+aeypRMTpl0otVu9+WTDYGV\nUS9EIO9JPv7hP+X7//p/J6XLxd2Dd36Gz33ll1k9+OKZl6eUOOq2CAQP2s2pxW/OmZwCKTpSKoLa\nKENlW6Q0IOS1RbytNDG4UmXZ/VAUMS2VLAv5PDvVzcKgeokqd0IIlC5VIzuvf+MslEJIxJAYe88k\nA9aqc1vlpjHgpjDn/ejjqsSc/2Osxs3VqrH3OBXmY5tK2G8u1zXzfSglyam0g+1a9a7SDhZjYuh9\nEVox0ydH217c5vYkRivePLj4dSblRMKVqpKo6MdApSVuKq2tZwm6mDJHnSOmNLte3k2GGDzhbhc9\nh+MRjWmo9NkbPvLJIFlxtolI7wcymZVunqul/5P0IRJTwih5JSvvF4EXe7tkYWFhYeHG7Oy7gXud\nbUkp08+hrgBNpWmq52ORnPM8BzR/kBJIiVCqfDxZSfCeOE4IpZ5yrdtdHrZbcsqopkafEfRaFteC\nl+Nt/3xyivz5n/wOH/zpP0Tqmjfe/VmEkKVyM4sVQflaSs2bn/t52oMvXHibW9fhQqS1NZUti9Cc\nUxFF0e3ntaTU8yzR7dqzlCphrCllYihzJ3HOX4rxWDQJAdVLUDW6CrsWO1uV56KbAt7HvQjaVZSE\nFOSUGed5KyEFTWNQZwj0nWiwVjFNZbZr7MvRE1JgK7W/zR27Sscwt4OBoKrPP77BR4a5va2qj13b\n+v76IukyejeQyLy12TCNgn70jBmsltTt01WrEBNHnSsVD6svdcq7KWu7YgwTgx/pfM8U3bmuc6eC\nZAdPK8Sp/52PHpd8aUc9R2g9C/J+wygjEHgyfo4taF8ScQSLQFpYWFh4ZenHMkjcVPrexFGce/vT\nnC20aq6e23NbckrEcYIUiyCKxy0/5yHUCbGkFHEYAdCr0wGO5bZH4jCW3dr16ko5Ri8rwXV854/+\nZ44++Rb16l1+8uf/HvXqcuOkixj9yOgcRmjWTRGWKQWi7/dt90/OEd0FQsyzbifOw5zzXjTlXCof\nL0vV6DrshE1VaZwrFaBpDExTwBhFCMVMRGlJ05hLRchuUR5jIvg4tzGev8iVJ9rB3BT2pg9PsjOd\nQEDTmlO36V2k7xzNLUNSd4xh2guHxtRYmfjxhxMxJto326dmiJyP+1y4VW2o77n9tdYVVhp6P+CS\n53DaUusSaPxUG6mWNK1h6HwRkiu7f/w7W+/WnG8wc5ekmPA+kVJ5Tu2r5idegqeYcClijGa1er5B\n1ddlEUgLCwsLryA+JEZXggvvc76lG0t+0bOsGuUYieNImo4rEGK215amzKiUqlGpeuzFU0zkGEjO\nc3I2SNUV0szVjVl0pXEsi3gl0avV/vJXkf7oh3z7n/0WbvyUB+/8DF/+i/8NSt/OGjjEQB9GUoDG\n1BgjiWEkhmkWRg1S3Szn6SacJZpeZYQUVLXBWl3mheZ2OSiC5aLKzlkoJa987KQUtCdmZnb3uWMc\n/L4Nr2ntqSpImUECNxWRdNvspzFM9H5AIlibItKDj1RGMQFTyNSzWIcS+NqNHiGKAYR9RllYUkrW\n1QoXPb0fGMKIi46VadHq9P9Ka0Xdwth7hq6IJJc9MScqZdHPIPPI+7g3t9ghZlMcKcs8WsjFop8k\nMAnGzuNkwFiFvidzoLtkEUgLCwsLrxg5Z7q5te6mYaNXYfIRHyLWKNorzBvclhwjcRiJ0wSUapCu\nG6QxZwa1nns7e8EUIWdkXT8tjKRANw2yrl+qXc/r8smP/znf+1f/Kzl5PveV/5TP/eQv37qak3Ji\n63tyylgsSglSHEgpIIREmxbxggVXvqqUdrhi7hB8LOf1M2hzOjkzszMWyDkz9I7g077SdNYiuZqD\nWm8bkDv6kT6MSCHZ2BVSSkKIuCnSWE3dGKY5bHbdWrrBM7qwD3x9VpXwk1hlMFIz+JExThy6LVYZ\nalWdEkrGKHJdHAe325EhDWgjaeqrbWyklAk+EkIJRbb2fAe/k5y0hN+Zm0glSWRiLnNbPh/PX1ZK\n02qFzEVUhZBKRXMMZcNCqzk27th99L5yvq7LIpAWFhYWXjGGqRglXDWb4ybknOnnndb7FkcpBNI4\nEqdi5VvmhWqktTcSL0LOVSZjijAaxtdOGOWcoPsXfPeP/g1SVXzl5/8eD9/9uTu57d4PpJzQWBAZ\nkUdSkkhlULq+03a6hashhHjm81ZSyf1MUnHESwSf9m1iFz2/9rbmY9i3212n+vekOFJSzW55vizs\n22LMEedco3A07c0Y1q2980y46yCEoLUNNs5td9HjokciMMpglSlzRvMxerzdMoWATBUDHmOeng+D\n0gIXQsT7tLdlB4ihtDVeln+VZkONlDJSCbRVjED0kZOlJCEEZo5y2H2Gkt+1fwwuznOB4exjIEVx\n6zPqUlvz+2IRSAsLCwuvED4khun+W+uG6Xi+6b4WE8n7Il58qYZJrZB1fWezQMl7wtH2tRNGjz/8\nt7z/vd+D8btU7dv85M//9zTrz9zJ7U/B4WKZ92BKhDBSVUUYqRfIdnjh2aBOiKScyuzXVS3AbaUR\nAsYhzO129kxDiScZ/Mgwi6MDu95nAY29I8+GEDuxtW4th9sijoxWbC4Rbs8SrTQHaoOPHh8DLpbg\n5Ck6BAKjNFppZJNZxYpGNsSQmWKZOdNalkoT7KtFOx2jVHHB06ZUFnczYXtTjyeE0sm8MGMVwkiG\nMFufC4GSCi0Feq4CnYeQRagbW0w50hywXbx18uxsWRxBS4BzIMZEXV8+L3fXLAJpYWFh4RXhWbXW\nxZj21uF3LcJyzqRpIo5TaYEDpNGoprnzOaA4DOSc0e2rL4y82/LxD/6QD//sm7jx0/JD83m+/ov/\nA/qOhrpjivR+QGSwOdO5AW0Utl4j5bLceF1RStKuLKaS1w6RNVaDEGXeZjYluKjd7jxxNI1+n3d0\nsiKhZGmnCyHdWzbcbTHKYJShpSHEUCpKye8rS2VeaoVRZp9R5V0k+FKx2yGVwJin5392LofORZwL\nx0HBdTH32bsezpW3KGAIJbR2ZdSNA1/LvNL57Z67fKzgE3101K15pjOEyyvWwsLCwivCrrWutvfX\nWgfFmAFgVd+dCMsxEqeJNE7HDmdVhayrM7OJbksKgeQD0pgz7b1fBXLOdI//lA//7J/w6Y//iJwj\nUhre/sIv8s4X/wb/5t/96M7EUc6ZzvWkHKmFwE8OKTVNu1nE0cI+g+omGKOgyaWS1Psiks6oJvR+\nYAwTSkg2J8RRqZCU+av6jHZgreRzmTe6CXquGrU0hBTx0SMoIgqOZ85spffOgyAwRl4oLIuph97b\nunsf9+2I5FJxqluLS4lxL440+h6rOlIK2nXFNPq9aUddPztr/uVVa2FhYeEVIJyo6rTXdKi6DieN\nGe7C4ankEI2zs1x5o1Z1g6qrMid0T6Sx2Hur5nZubS8iKQU++dH/xwff/wOGox8CUK/e5Z0v/nXe\n+txfRe1F0Y/u7D4HP+KTR6eI0ZYhSZSxGLMsMxZuT2nJKvbgu0rSyc2Z88SRd4FxOLYTf1EMAO4C\nLdWFjnXXcR7cIXb5V5Xe52nZqswBDSHhYkTO4uhZzWlVdakcjYNnHAIxZqr6/h1Tl1euhYWFhZec\nk61163tsrbtLY4acM3EY9jlE0mhkVd3YeOFa9x0jcXIIpV4p++7gez78s2/ywff/McEdgZA8fPfn\neOeLf5PNmz95b8fVRc8QBnKYqE0DaKRUaCNfqQXpwvOlqjU5lzDZofc0rcGnwOhHQo5PiaPdTI0Q\nXNvk4XVnl6e1a4nsfcDFhBSCtdUXzhndB9ooWiUZejcbPCSa5nYW8Jfe573d8sLCwsLCM2GYAiEm\nKqsx92jhe1fGDMl7QteRY0IohV61z1So7GzCX5Xq0dR/wgff/0d89IM/JEWHVBWf+dLf5t0v/S1s\n/fBe7zulRDdtiX5gYxqkqnBOArm0Ri0s3CF1Y8g5M46Ore/QVXkdssrQmgY5OyTus5Zmu/H7XEi/\nyuSc6X3Ep4SSkpVRz1wc7djla+1sxrvudFDuXbMIpIWFhYWXmJgyoyttD+09utbdhTFDTonYD6cE\nimqaZzoYvTOBEFIgrX1m93tdUvRsH30XACkNQhmknD+URkrD2H/I+9/7h3z6/h8BGVM94L2f/M94\n+/P/wYk2uvvlaDrCu45GVyjZMI2CnPM+DPJlw0VPiIHGvNqmHS8rMUWCdPRpIPrEStQ82Kz3rWY5\nZ8bBX5q1tHA5ISXGkAgpoWdx9LyfE0KUypbSEje76t0Xi0BaWFhYeInpR0/OmVV7vwuB2xozJOcI\nfX9cNVqvLjVfSCnRhwHyHKCobt8+mKaJnPIzF2ZXJYaRD//sm7z/p/+wtMldgWbzHp/5ib/Nm5/5\nS880gLWbtkzTEUYqrF4zOQGzjfJ9ZpeklEqw5B3//3z0bF0HgBSC2rwaFcZXgZQSQxiZYslCW69q\ncBKJIvkM1S6I1hPn8NOmtUuL5zVIOeNTJsREyMVyG8BISfsCiKOT7LKe7pNFIC0sLCy8pPgQcT6i\nlaS6xzeLmxoz5JzJIRTb7skVZ7qmQTUX787nnJnCxBAm8rxF6JJH+JL9USm7d226LnGcyuOoX6xM\nnuA6Pvj+H/DB9/8xMQxIVfHuX/hbaLsiRU9KnhQ9ef6cokdqy9uf/0U2b371mS9eJtfTDY+QQmDV\nAW4SZRB+ZdD32OY5honeD2ih2FTrO/u7Q4psXY9AIIAhTFhl9/MsC8+WlBIhheLUljwxF7tqLRS1\nqbHKkGyi7xzTWOaMnIuk2cq7vsdZzFcJH1MRRSmR8nE5RgqBUQojBeY1bU9cBNLCwsLCS0gxZpir\nOtfMFrkOzkf6YTZmuKQqkGMkhUCeP9IcJAgl5FWv1wh18eI5xEDne2JOSAQr06KkwkXPFN1xqryQ\nWGWwyl7o5HSS5Bw5RlR1vw5518FPh7z/vd/nwz//Jik6lGl576t/l3e++DfQpn3eD+9MQpg47D8p\nrXTyASmoZzLrsXMqEwhCjmxdx9qubl9VTInttCWTWdtVeW75nt4PrKvVHT36hYtIKeFTmEVR2Asi\noISiyrIxYvVxW6xUkqa19L0rTnVcL4j2dSamzBAiIe2Os8BIOYe9ymfmUPciswikhYWFhZeQ0cV9\n5tF9ZHhMPjKMJVcJoK2fDulLIZC9J/lZFJ3YgRRCII1GKIXQGlVdXLFJOTH44xaaWlXUptoPXTdS\n0Zj6OCgxOsYwMYaJSllW9nIxEV8ga28/HfKjb/8uH/3gD8k5YqoD3vvq3+Xtz/8iSr9Y1a2TOD/y\nuPuImDKaNTKbe29n2mUsueRRQrK2KwY/4pKn8z1re3MRk3LiyG1JZFrTYOfK5BTdPozT3rBauXAx\ncc7xcdET8onNFARWmtnGuuT+nIfSkqYxjIPHWE11jxEHrwI5Z8aQmOYQbi0llSrCaKm4nWY5kxYW\nFhaeMyEmjjrH6NLlV2be/ZsCUtzcMOEscs5FGM1udQCV1TRWoZQkp0TynuwDKXhyPLHLqxRKa4Qu\ngkioq/esT8Ex+IFERgtFa5pzF0W7oMQm13uL3yk6lJcXzoycDIa9rIp1n8TgeP9Pf4/3v/f7pOiw\nzZt89st/h7fe+6svdKBqzplh7Phk+zE5Qm02VLrBWPVUJknOmZjihQvbq5JyYut6QgoYqVnZFikk\nK9uSXIeLnt4NtPb6phQ5Z7auVCtrXVGfEKataTicjuj9gJH3n7nyuhD2osidqhIZqTHKFEF0zTk6\nbRTrl9AQ5FnjYgl5TTmX9w6tXtv2uavw4r4aLywsLLwGpJQ56h0pZ1zIbHvH6pL++WE2ZmgbcyfG\nDDkXJ7zRFWEkhKC2mrrSSFFCVf1cKdohpEBVFmFMER03aFlLOdG5Hp8CAkFrmlOL1IsQQmCVQQvF\nodvShxEl1bmzSc86GHZX6ZJSUuuKnBMf//Cf8sNv/X38dIi2a77w0/8Vb7/3156pscJVSTERQiKl\nTIyJfthyNDxGSMGmeYPK1FTV2WYMW9fhU6DWFe0t3PRiihy5jpQTVhlWpt0/L4QQrG3LduoY44Tw\nguaapgrdLLx2FtEn0VJR62pfpbzubS+cxgVHF3oOp2I8IuYqkVEGo/S+Urxw95xupxPUWlEpuYj+\nS1gE0sLCwsJzIufMdvAnsoVKa1vKsGnPFkk+JKbZmKG2d7BDnzKPu2kvjJpKU9mSc5RCwG878tyO\nIY1GaIO05lIHusvw0dO5nkTGyjnD5AYiS8rScnU0belcz6Zao54QHM8qGDblhAuO6eTueIRHH/0x\nH3/ndxm3P0JIw2e/8p/w2Z/4j1D6xVx0hxAZOr//fjsdMfktttK8uXmbqqqR57Tk9H7ApyKkx1Ds\n3G8ikkIMbF1HItPo+kyBIud2u0O3ZQgjUkgqfTXr9t4NuORLVeqcWa9G17joGcOEVeap82rhasQU\n6fxAprhR7oTRskC/f8YQGedZUCMltVbLfNEVWQTSwsLCwnOiH8PeHa6tDW0lsUbhfOSwy2zOsO7u\nx7JwbevbL/RznqtXKVNbTVNppCw5NqEfiMMAgKqrYot9R8YGgx8ZwnjtqtF5aKlYmYat79m6jk21\nPrUjfV/BsNPwKeP2fWKO+BSJOZEpwkFLjRaCD/70H9F98icAPPzsX+aLX/svbx3emnPGRY9PHjJ7\np798fAUyuQiG2fHvqovRnPJ+4N1Wit4fIc3Iuq542L6NvkCAuFDmwnZzQlvX7U0VrlOBccHNC+rM\nyrQXih4pJZudQPb9vrJ4EaMfGeOEFoqVbc89NkIIWl2znQ0bNtX6yn/DQmE3P5bJ1NLeal5s4XrE\nlBlDXNrpbsgikBYWFhaeA5MvLW1KStaz65IQgnVj6ObLDzvHZmX3O37jFAgxUVmN0bd/s+sGT4gJ\nq+XeCS/HSNhuSSEilESvVndWdUkpsfWlrWm3+3/deYPzsNpS58gYpn0lCe4nGHbYvs+Pv/sP+OTH\n/xzy5XNjqze+whs/8Xcw688wCo1K8UbViJwz02xOkc6532JSDQLwOeBTQHpBpSuqK9hWj6Mnp4y2\nkj4e4kKPUYYHq7dQFwiPXZVAIFjbFUoqNnbN0VzdAS4VSSklel8qOwLBxq6uZOeupCpVRNfRuR5p\nV/v5p5QSMUfiLGBjTqfOv8tau6y2mOjwKSyGDTdgDBMhRypl0S/wjN2riJ8NdqpFHN2I5WxdWFhY\neMaEmOgGjxTiqVY6IQTr1iIGz+gCh93EQWsRQjBM4Up221dhmAKTj0gJQY48HifqqBCTI+eMqipU\ne3dVozJMP7fUzTMfly1Oc87EYYQUQSqkVsX84RyThdY0xRkrBXo/0JrmToNh+8Mf8OPv/gM+ff9f\nAhnTvsP6nZ9BSYUWsylFTqWikzOQWT/8Mgdvf51MLov/6DmctjS6unIQacqJKTimMDHXqKhVRaXL\neSE4u90tpsgUHC46hlCqdlYaKn06RyrnTMwJNzm6YSKLjAyeGCYqbTlo30JeYLhQjBS6vU32TvyV\n6s563wIn4Ny/+ZRRh9SsTHMtEamVZm1bjlzH1nVIqYgp7qtrOwRiXzm6aktnMWzYLoYN1ySkuG99\nXGa4nj0ulpkju7TU3YhFIC0sLDxTcs5l8Dsdf959nXJGAG1j7jX49HmyM2XIObNu7VPW2TuKUUMR\nMoedQ2tJyplVfXtjBucj/eiRUqBMwIeA73qmEFnZlubBwzurtuScGcK4b7W6akvdyUrWjt1XQoji\nlicVQis4sWCtsyKEid5tkTYip3jrYNju0ff50Xd+l8cf/ZtyH+v3OPji32D99tc5OGPm6Sx2lZWd\nUOzDiEuBRlfocxbdKSfGMDEFV1rmEDS6ptL2SkPtSipa29DkMkszhalYV7tilz3EkUfjISkXM4bd\n3JG1iRg9janZrN5CXHJfvRv2TnBPVliklBzMIqmfK0knRVJKic7fzKjjSYwyrE1L5wdiKq1FSmqU\nUCipUEIixfWH05VUVNoyhokhjLcynnhdKK11HQCrK2yGLNwtu+BXs5gx3JhFIC0sLFyZnIu9tNES\no68nYHa/O0zhzMvLYkYQU3Fy8/NcznXEgA+lpUBK8cIOop40ZbCXiMC2Nkgh6EaP8xElJZW9nXAM\nMbGdg1+NzUzBIbqBVhhGqxhbjRCR20SUhhQJ0c/Bj2UXXwnJ6ootdXGaiF1fKll1haprcoynP0Ik\n5QDT079fpcSR73ncdazNiqppr10Jyzlx9PGf8OPv/T5H8wzR6uFP8MYX/yb6wZcwUpcWrWverlUG\nXW/21aQjF5AIjDJYZZBCElOcZ4zCE8KouvJiJ/hIShlbFfFVaUulLSEGxjjhYyjZM7lUbPwYqXVF\nZQRWR5Rcoe3qUnG0yyMyUp8rHM4TSWOYGPxIJu/NEm5i1HESe6I6dpcLw51hwxQclbKLYcMlDGEs\nollVV2qTXLhb3BzBYF+QQOyXkUUgLSwsXImdcAkxMUzQVGWo/yqLkJO/K6XAzE46OyEjhdgLoTgv\n4Ccf8TGxbsylYmzycT+fc5Jy+xIpBVKAUhKrn9+OWj/6U6YMV6GuNEIKhjFcav99GfFE9aqtFWMa\nyP3AStWY1YqmsvvB+pjiPnPmIkKK9L5HocgiE2IgnWhr0qKEPTamvvSx55yJXVcc56RAr1b7gNkn\n2+pyzpASKYSTPyz3CchQc+Q7RjJ1c/WKhHdbPv7B/8uHf/5N3PAJAJs3f4rPfvnvwOozhBzRsrRz\n3XRXfDf/srMCH+PE0bTFJU9KCT1nwlTK0piaStmrmyzkzDQGvCv1tuAj9QmzD600a6VLBVO1PGwe\n4KaAkAEIVCYihL6SOHLR71uoLgvq3ZspuI4+jHunP4lgZVrsFd3nrsJ9PL+FKNWt7Tzn1Nr2zubn\nroqLnhDDlZ5Lz5MQw96sY2mte/bknPGpZB0ts0c3ZxFICwsLlxJi2rudVUYRYqkG+VAEzHltYlCq\nOts556cy6tJFvlKSB+tqX2067By11bRnhFEWYRSJu2FUo5BSHLfw5Yw/0aIFYI1i097dYuyq7AJY\nT5oyXJXKqAtbDocpMLqAURJjykDuk5W3nItI3VWvfB6J00iNRtniUgewqdb7bKKjaXtqpuTkbYUU\n2Lqew2lLzBGBYGUarLZU0mBkCXRNw0jsBoJ2x5lJ+mlhnUIgzJbi0mj0anVhoKsQApRCnXMdRQ3e\n0IeRLowcqPMdyHLObD/9Lh/++f/Do/f/JTlHhDS89d5f450v/nWag8/vw0qtNBc6n12HYhpQzk8l\nFIpUzCSkRAoB8zzOVe8rxcQweFLMSFU2HYJPdNuJujGYE+eQEGVuKcXENAVy9lgbEUKiTXupOIop\n0rl+3zp41Za/neNcnLONrjKL9qJgZ9E6RcfhdIRVhkbX915NyjkzzM57AIibWac/C3LOdL4HOJVb\ntfDs8CmTc8Y+x0DsV4FFIC0sLFzI5CPdMAeT1oamKrvP3RiYXOBx52hrfWYmzzCFvS31qjbU1zAX\naKri1Lbti1mBD4lVY1BS7CtGKZfsnspqGqvOFGq7maeUM/0YcLNQae7A6OCq7I6hOMOU4S5ue3eM\npxSZfFlwayX3rZBaib1jXWU1qIB3Hj1FrGnQq+Pdfykkm2pN7wfGMHE4bVnZFi0ULvl91WM3NyIR\nbMyqVAOEpDXNfg4lDgNxGBFSlFmiEMv3QiC0LrlKxpBDIPZDaalr6jsxVIDSxhVSxCXP4EcaU5fz\nIYx4d4SfjuiPfshHf/5Nxu6D8jurz/DOF36JN9/7K2jTklI6taC/q0Vf53qm6ADQUtPqGju7zIUY\nGNzE0dCTY8fD1ebS+ww+MgzF9ttYRTVvKHgXGMfA2HuiTfuf7xgHTwoebTxKabRZXRpcG1Kk25ky\nmOtVUpRUHFQbUk57p7mXiZVtsdGU1sLocdFTq4raVPci9FIqBhghR9R8+2OYsNK8kMdv8ON+Hu1F\nfHyvA37XXrdUj27FcvYuLCycSz/6vXPaprX7mZmdHbXRkm7wZfE9CxghxD4A1fmIlIJ1Y29kS62V\n5MHanqgmTfvbfzLU9DyEECglUMCmlTzeTvSj3wuI+2Z3DKUQrNuLq23XxYe0F14HK7v/mQ+JEBNh\nPm67Y6aVxJrM1k/QjzS6Qq3aMys1rWnQQtH5ge08bA2lcjCGCSkkD6oDHlYblFL46Nm6kkO0Mi06\nliwloSRmswEpyd6TvCf5MH/2QMlaElJgNpsLLcVzTkz9R/RHP2Q4+tH+c84RqYYEJLcAACAASURB\nVCxKWaSqkMqW77VFCM04HRLclux7vNuSkz91u0Io3vzsX+btL/4S64dfJlMEtQuOPoykeZaitXez\na9+7gSk6tFBnzjGJLBFeQRAc+QEZNFVVKkDqiXP2VEudgLo9XSkyVqOUZBg83kViSNTzeRh8wjuH\nEBPW2gvF0S57aYqOMAfB1rq6UWuclBLJy7t4M6oEnbpQ3AHHODFFR6Uttb47oXTS+bFSltY0hBSK\nnbnvOZCXC+dniZ/bRZWQNC9oCPKrTsoZnxJKvLhzuC8Li0BaWFh4ipwz3TwHJGURR/qMhX1lFFpJ\ntr3bzwy1tWEYAzEltJJnhp1eByEEbV3mkLaDgwxNbfbtdNdByiJSDjvHdnA8WFW3doQ7j5MiUUnJ\n5o7FUYyldTHnzMHq+P+jlaSp5j70WSz5UFq3Vo1m6zvSONEKg7R2P+NzFlZbpFQMc75NyoksMivb\nUqvq1CyEUYbNHA561D3GTpHaVJjNZi/AhLV7d7wcIykEsi+LbdXUTwm1qf+Eo0++RXf4ffrDHzJs\nf/yUuDHVA5RuSNHh/CNidGdnEwmJMiua9WcwdoOpDtB2jbBr1m99HWkaUk48Gg+fsoZudH1nsxS9\nG/Yhpevq6da0ECJDXypBm3U7tzt6pJN4V56PxiqMUWRg7B0xZqQUNK1BnnGOSSVpVxY3BdwU6bcO\nYxXBBXKaaFYGZdozxVGIgSk6XPT742KlwWr72mcC7QwhdtlUY5hwwe2DeaWQSMTeOe86Dnq7Cq6Y\nZ7R2YblGGWpVMcZyfy/KjE/Kic6XzY6VXb1Qwu11Yqke3R2LQFpYWDjFzoY6xKsJHCVL9WJX5dn2\npW2oqfSVjQiugtGSNza3XwwYrWgqzTAFutHfyzzSSVOKuxCJT1L+R77Yfp9jYiGEwBp1yilvO3XE\n4Kl8QhuLXl2eaq/nEM6dW5kUcj9r9NR1laaVNY+7RwxkqBriFImhVLnEbMwhhEBKEEojtUHMP/Nu\ny9En3+Lo429x+Mmf7E0Syh8kadafoVm/R3vwXvm8+RzaPv03pBRI0c0fHm1aPIIhOozUVLpiChN+\nroQEgDmcdGcFLYVESllMJs5pFYppnh+6YovZpeJo1yYHNK1BaUkU5ftaa4JPhJCYxsC0c4PMoI2k\nvmS2TwhBVZfbHIfANE6Ap2o0ulohT4R47gJppzARZ7EphSzZS1cIm32dEEIU9z9lmWaRtGudPPP6\nu3NMSpRQSCH330shT4Upn+f8WJsKl3xptVPmuTvqFUvvnpQTja6fuXnFwjE797rFnOH2LAJpYWFh\nT86Zw84RU7qSocKO4yqPZJgitVWXWlg/T9raEGK+l3mkEBNH3WxKYTWr+vbBkjlG4jii6hqk5Kgv\n/6OmKrNfOZeh3IsWrlNwReAMDqsqVHu59fW+rSpM+xmIs0wbTj7OtO2wueJIZKZxpA6Z1jbz7E/m\npGVGSp7h8Hv0h99iOPwuY/ej/WVK1zx452c5eOurrB9+mXr9mVOL+IuQUpfrmhOzVSmx9QOH4xar\nTZmRkLpYNp9YoF6FOAdguljEi5G6LAwvmLno/bBvPzpLHHkfGXsPoogjPYteqyxjnMgi0bSWnDLe\nR7yLpJypG405Y/7vPLRWtK2gO+rQWlDVx+IopcQYSxVkF0i7MyZYrJovRghBbYoVe8qpnO85kcin\nvt+F8oYYgdPVUEl5nUhkrDS09mwDi92s39Z1dH7goDrfgOS+STmxncqMlJXmxhlWC7cnpkzMGbM3\neVm4DYtAWlhY2DO64ghXWX1tpzUo1Znr5iM9L9aN4XGX7nQe6SxDi9uSvCdst+SUSZNjFJoJgVKQ\nZeZwHEueDbCxqzMXsjFFej+Q59Y6VV3cWufcyDgNOD+RYyCHSGVrVu0BMj99/ZwzfvIMnzzGu4Be\ntWyMYWJE6IS0idY2ZQHefcTjj/4tRx//MdtH3yHPVRwhNO3BV9i8+VM8fOenWD34wqVmAVfBRY+b\nxaEQAgHklG8USLqbv9qbKwhVKl8p4N32XKG0a5dSswHGU+LIBcYhFHey1p6aM6p0EUhjdFhtEVJg\nK42dzVJuIr5z9lS1QluDVIaQYgmRndvorhtIu3CMEAIlLj9vUyoOhjGnOai3fJ/z1c5NO+dmuVgq\nSc9DmKSUOHLFwKRS9lKr91eRlDMh5Rdi5mepHt0ti0BaWFgAStvWOJsJtM/Q4e15sTOPOOymO5lH\n2jn2PWlocRuOA1MTXgsOHx/SDSO6tmzefsAUJQKBlnpvu3xQbfaVpJTTfi4iBU8VBFIrVHt6IZO8\nx40jzg1MbiTtWseExCqLtQ0SQewHYj8gtUIYizCamATT4HBHW3KMVOuW+mCFNooQBI+37/PJo2/z\n48ffo/vkW6fa5ur1Z3nw9k+zefNrVO0XCUGUKCMBzmWszYgb/E9STrjgGKMjzS1iu2rRA7sp+Uhz\ne9JVBEBKiWHO7oEijGpT72dwQgwMYTwllGpdAjIHPx6LI/u0OHJTYBoDQkCzsk/NqSmpMFLvQ3dP\nti/dTBxlUixmJyELjqbtvtVQCUmtiwvhMkNyv+yMKm5Tl2tNU849P2KleaatjyFFtq4rBia6emFt\nx++DmIoRgk95HzEBgtUcsfC88CmVAPDFnOFOePVXQQsLC1dimG2zV7W5N+OC2zL6kUxxz7qLBZzR\nkrY29KNnO/i9E9x12YkjKQUH7dOLXCgL4ZTOKL+c4OTlcRiKC5wQ+NpwFDy9MeiYeWA0ZgxUmwdY\nW3aOxzDR+4Gt72l1fWqwXmSwLpdsotXqVGudH3qOHn18vEhWmqbZUNkaU1UIpRBSlvY570muuM+F\nsWOaAiGOdIf/mhQekxmJHwx7C+20y22Zkari4bt/kQdv/zQHb/80tn546vKcM97F2Uwg4F3AWI21\n6kpC6clKiEBQKUulq1PCos11yUdyPZtz2pNyzsQU985tmbx353py/korzUatnxBKZYYk5nQsjp5Y\nwE5jmENaBe05BgsAla7wLjCFCX3LXfoUXankpciQyhzWbi7rdTddeNnYt9r5ns6ffy7fNSGGIo64\nWSX2ZSSkhI9FGKV8/DqtpEQLwRQTnY+0PB+DBB/L47JKLZsbd8QikBYWFogxMboSYlrZF7NFbme5\nDOBTYG3aO9kxbSpNiAk35wld11hiPCmOVtVTbRYp5b3T2GW4KZFiIo0DcZwQSiLahm7cMk6RN9qH\nPHinAjcRhxG2PbHNqLqm1hVjGHk8HnLElsbWyJSpUOgIGYWqqr2LHEDoew4ff0wkUT98g9oW84Wz\n3mDFHMoqjMUPDhd7Dh//Cz794B+T4njymmi7omrf2rvFmeoBcvMedvMem2pzrjW0EKV9zFj1lFCq\nngg6PXXc5jajnf20FJJGFQvqsypEtamLiEmB0Y8YZYgpEnIkpVQ+n3DCK8LobGOKk+yFUoqMJ0wt\nzhZHHjfFIo5WF5t47CpdLnqaOW/qJuyqR1P0BKnRomQSLUP1Ly9WW2z0uOSZgtu73d0XLno61+8z\nsG5i8/4yEVOm8+GEKBIYKUtbthT7WR8tBZ2P9D6Qs6K6Yqt5nlv05C1b9Fzaudct4uiuWATSwsIC\n/eyI1d6BocB9kFKin62mjdS45Dmcjljb1Z2EEa5qQ4iJYQrzHNXVFqCjK054UsyVoyfe4LyPjHN4\npzYSO7cunnWEQ0iQMocffEptQBmNXq/5dOzoxsDKtBysarSWoFukMYTtltD1hGlisoLgHWEYIARa\nE2h0CwQys8A5EQgb+p7HszhqHr7Bpjm48G/NKeNcwLlI9+mf8OH3/0/c8CFK17z31f+CB2//NKba\nnJulE1LkaNrS+VIVu2jo/6RQclPEuRJ0GkykOlHhDDGw9f1ezFynErKyLYfTtojuMJ66TM7nmZIK\nLdS1F4FaFpe6mOLe3vkk45xJJKWguUQc7aiVpQ8jLjjqG1o7p+hLcG5OaKmoZbWIo1eA1jT4KTD4\nASP1vbXaTcHR+R6BYG1Xr3zFcYqJwUcgY5TESomeHTefxCjJWgg6HxhCnDsdzn9uFQOcxBiLcUeh\niCQ9i6WrzjXlnPGxiCy9OEzeGYtAWlh4zfEh4nycQ0RfzMVS5/tT7RyjH+nDyKHb3kmLx03mkXaG\nDHIOaT3ZVvdUeOcVnMYMGRVG0uSYsmHzxoY+eD7d9hileXOzOiXcpDGYBw8I247D7aeEbcRIzVuy\nZRQTISUwCm0rhNZIfXz/frvl8OhTosg0D95k02zOfEwpZXLKxJjKrEz/ER9+/+/TPfpjQPD2F36J\n9776dzH28taeYhfezmGypR3ossV5sabWGCMZxzDbXE9Yq4gqMIbSwlerikrba9kdSyFZm5YhjMVq\nWSrU/PmujAnOejxD7wg+IZWgbe2VZ6ystgyzQcRNBFLOmRhGetcjTMvKNC/kZsjC9ZFS0ph632Jr\npH7Krv62uFkcyVkc3cXG1ItKzpk+lFw/IQSt1leaLdJSsDaazgfGEMkZmjPeU6eYmEKcq1KCSiky\npZIUUypOn7PdZzH9EFRKnvsYXMpAaa9buDte3TN8YWHhSvRjqR6tbuBa9ywY57yakxaytanRUrN1\nHb0fCKlUWG6z4NNKUCvoh4lD79m0BnIupgE5QQakQFUVPsG2d8WQ4QlxFGNi7D0pZaQSNM35syU7\nknOEvkfLTLVpiKri8eHII79FCME7BwdnVrWElMTW4nqF8AJj1yhrqWVmSBNbkThQuuSrxEQG/NGW\nw+2nRDL1wUNq3eJdIOciiHaiKOXMLi81hoGPf/B7PHr/m5ATmzd+ki98/b+m3bx3rWNslGE1z0xs\nXcfBGa1nZ7ELOvUu0PWOjw6PQELbWDb1zRdru5a4Z0HOmXHwBJ9QStBcQxxBEXR2DiX10V/bdjtF\nzxAGstS0ul5su18xal3ho5/NPMKpywSlFUwJVdzvrlkRjSmWyi+C9RU2Nl5mQsr0c0udkpKVUdey\nzFZSsLaarQtMMZaNPV3mglxMjE8Io0qftuQuNvCZmDJh9zklQkrIILBKYtXp31nCYe+HRSAtLLzG\njC4QYsk80i/gi2tMkcGPSAStPe2SpJXmoNqw9T0uelLasrLttaoIJ40HcgjonFGTYwwJMSrq6ulF\n5NT19Ekh65pNa08dt50jGYCtFLa6uGUxx0joepKf81CqitVbD3n0eODjx1sCjs+8/YDGnr2g8T7w\nyeNDotAcbDYgJBEQCYQPdHHCT4es5jwgv92y7Q+JAurNASpVJXvnBNH3uOF9pvF9XP8+U/8+U/c+\nKTls8yZf+Nqv8PDdn7uxGLXa0pLp/cCR255pe30eUQSicYgEOhlUsEQPSt7M7vpZkXNm6D0xJJSW\nNO3NXOIqXc0Bru5aAifnjHMdU3RYe0Bzwxa9hRebTbUmpjI/t7cPny3EU064XGaV1nBlkZRzZuu6\n/czRyyiOxhBxMc0taMeta08KnylEhpCATKUUtZY3ep5KUURS50sVqsvHwgfAzrd9lvASorTYaQm7\nvoiYMlOMuJgZQ2QMCasklZIIUQwk1JJ9dOcsAmlh4TUl58wwBYQQNNc0JngW7NLZM5mVfTpYE0pr\nycauipVynDiaiki6aPGYQiiCyDtSiCdvjCAV1cbiR88oBHVbl1wnUfrOp9HRfXJITp6VSsgoQVek\nmBjHQAwJIQV1o/dBn2f+bSkRx7EYLVDa5fSqRVhbRGvOJBGptcbmpxcyKWWm0XPYd4SYOGhXbFZN\nyfiZq15V0hyNxdAiyYAYHJPfIivJ6uAB63qNEIKcEx//4J9w9Mm/Y+x+THBHp+9MSOr2Hd5676/w\n7l/4D5F3UHmo5zDNMUyl3c6uLlyIpJTY+p6QAkpJ3nnwEJFK252bAs6F0rOvJVJJlJIvjBNjTplh\nNunQRlJfMXz5LLRU6HkGL6V05dapFB2975HSsL7kWC+83CipUKgz7cNPzgFKIa9Uee39QMyJejY9\nednofcTFCAhSToRj75W9MYIWgpDztVvqLkIKwdooOl8EDJQ5pVqpa5sxKClopabWZW6pfJS/ayeK\nlurR3bMIpIWF15Rhtp1uKv3cA+7OYgglALVS9sJhYCFKdUlOgu3hJ3yaDml1Q6UN+ZRxXC4tc7OV\nthACaQzSGrLSbMd4nGlhJEf9RP/JxINNhZ4X3C4K1MEBrYio4AnbjvGwIyiLVLosgGtzYetUnCZi\n35NTRiiJbtu9s5wLiW7w+OR5+IZFRk2KpTWrbszeBrvYa0c8nvWq5sHqeNErZgsIheQNfcDj4TFu\n+wiZMqpRrB+8wboq1/duy/f+1f/C0cd/Uv7s+iEHb3+dZv05ms1nadafpV69i5R3/1bRmqbsakfP\n0bQ9VfkTT9hY7Gy2rTK0piliWcFKSZwLhJCIMRNjZNe8L6RAKYFSEmPPtr7NKZKiQyp7J6G0T99+\npu8d6Q7E0Y5aWbYpMMaJVl6ePZNzphsPiSRW1cNXenZk4WJ2c4BHrmPrOjbV+sKK+xQcU3RooV66\nqmPOmc7HUl0RgtU8AxpTqeSE+bOPiV0N/SYtdRchRMlGckmi5urVbZBCUGtFrRUuJqaY5vesJfvo\nPlheKRcWXkNiyoyu7D41L2AorJ9tm9Wc83EZyTlkP9Ci6YKji1tSrI6H2XdveEKiKo20BmHKYjXG\nxFHvSClT2SIWU8pIAdvBs+09q+b4GK1bS2UU0Xm6Tw8Jg0OICb2uMU1LjoEcn36MOSXSOJJCcTbT\nbYOoKjKCEBM+JEZXhm2NTWU+pl0zDrPZAxBDIqWMEJC1p60tG3v+7FV2DtN7XPBgDc3m4V4cbR/9\nKd/5F/8TfnrMg7f/Pb70s9/APKMclR0r05JzV+Ym4hkHbUYiWJ1hKSykoKoNFTsL62IoEWMihkTw\neTZ2SLRPZFzlnAi+hPCm5FG6uVZ1rNyfAwTqjJ31nDJ9V84rYxX1Hc34GWWQXuCCo9H1pYLL+Z4x\njGhd0ZrbZSgtvPyUOcCWzvccXTAHGFKk98PelOFlqjqmnOlcIOaMkZLWHG+QSCVOVdd2sz4A9hyH\nutsghKC6B+vt3SxSmDf8lva6u+fFWxktLCzcO8MUyDnT3sGO9l2TcqLzA8Ap44WYMkedA2DdGrSS\npa+770tmkBBUmwMq+xZHriPkhFeW9gK3Lh8S296RcqatzSmxuGoMdeVwPlJbRW01zC0ZbgpMU0TU\nK6qmQfiBbnxMPz5mXa2Q4vSubEqJT/sjUoKmOUA0NXhBdk8EqQqwVcZnQW1qlFK0raTv3F4kGasQ\nOuECWGnObCcss00dyQesNqj2HbI53gX+4Pt/wJ//8f9Bzon3vvqf89kv/8eIO3Juuw5CCDbVmjRX\n7jLHJb/9Vzkjpbx0TkkIgdKlzW7HrhUx+MQ0Bqr6+P8b/UDOCakMOQWC71G5QunLd8pzioQwkFP5\nn0ipTlWgcs4Mg79zcbT7OytdMYQRF/2FuTcpJ47GQxCwad544Z7rC8+HSltSTgxh3FeSTp4bpb25\nO25vfomso0+aLFilaC9xZlVSoM4MXng5uG1VauF8FoG0sPCaEWJimkNh60usp58HvR9IOdHoet8O\nlGZxtGuBO+wcrZWoaSgVGaXQ69XeyvqgWrOdylB6yunMHVDnI9vBk3MuYuiMY7HLRxpdxBqFBLpt\naZkSAurWEEWk9xqhV+QYGETioFpR0o4yo0886joGBMJqks6sBHOehkSKsugVAmoLPnuUkFSqLHzF\nnJXjXUAbhZSCx9MRAnFmdS0OA3EYyTkjrUGvVth5gROD4/v/+n/jkx//M7RZ8eV//7/l4K2v3dF/\n7ubc1wJMSkFdG7rocFNAKYE2iugHUgpIZdCmLYLH98QwkVNEmeZMwbgLWo2zvbiUmpQCKTrUiXa3\naZ5H27XV3TWVsgxhZArTbEv+dNYSQDcekVKgtevFtW7hFI2pSTkxRcfWdadeIzvfl7mjK2aKvSj4\nmOjm3KJdK9rCwk158VZHCwsL90ZKmW4oHdcn28aeyX3nxOBHpugQ85SJEPNXQiDnXTyXPFrqfbUj\npcxRX8RRU2m0khw+2vL4047aKFYHa9TqdJuZFJJNtaZzPS6VGZf1iZ3Q0QW6wZcKRmvPzX+SUrCq\nDJ8eDnz0cU9rNVIKjFVUlWaII6OfkAgerB/iU8nmGWXGyIp+9IScCUawWR2wqit88kgRWNvqqf5/\nP3fDN09UveTcSganBeRJYXGyaiSkQK9WqOo4H2rsPuDb//x/ZOzeZ/XgL/CVv/TfYeuHN/13vjQI\nKWhaQ9+5MstFETRCKJRu5usotF3thVN2Hdq0p6pCKQWiH8k5IoScRZQiuy0peWSuZyOP0hIplbgX\ncQRFUOqcmfwRzncgFFIopFT7HCeBYHRbtFC09cUhwAuvJyvbkqeMS57eD6xsyxgmXCyvwVdpb35R\nKA50xYxhZW5vsrCwsAikhYXXhHiiClNZXdzZnhE+erp5Ya+ERAhJziWXJ+WTSeJlQH81vzHvxFGI\nidpq/n/23u1JtvQs8/t9p3XKrNp7t7pbLaklAQLMSMY2BjtgMJiRCSAcjsCBHUGECUVwDRdE8A9w\nwwUXXHJBELrj1r4gfGET4/AEeBwzmJEGDyMPCKTWoSV1t7p7712VuU7f4fXFtzIra+867qratQ/r\n6cjOXZWVK9cp1/qe732f56lLS1yvWeBZKc3oKpRyLOVIZrRdjlIsywXt2NHHgYNxxV6xYPRC2+eA\n12VTnJgvlGLWrYSQtSxapmBYEfb3S7TVUxtfwCjNslhgtMEZRz96PlivMWrM7X0msnSOZdlQ2ZLO\n93Shf8xxz0dPkIjV9tRZ25giQxjRSh8Lx43DQFy3iAimLNB1RfBruvvfZeg+pG+/z3vf/JekOPDa\np36WN3/0v7sR44VnFcZoqsrSrQfWhx11U2AfIaFK6UySQk8MA8GvMbZGaXusamRMgd7R/mhTEENP\nip4khnHIBLVpiiduaZMpMDKbO5hjjnybwNdSqbxuIkgKJPEEEh4FemoaEmFR30E/h9bMN4XNvj3L\nZfJlwqJoSJMFvIyCjyHrjp4jvdqGHGVTBDu3nc24Frw8d8gZM15ixJg4mIwI6tLSPCVbbxHZWnAD\n1LaisuXJjmIimSipXAESOSJHZWFZ1A7/8CEpRGxZ8Mrdu7Q+MfrIw3V6LJNog6ao0V5xOHS82z2A\nZChtwf6iRGtFimkaZEp2QpuMEDYwRrG/V+GqQExCNwbeXx8QU6Swjr2yopeEMZIJlTekBNoGijIx\npoRRZtsyV7sKrfSUA7TO5gPG0Q4tiJw5a9v6LusCdrVZw8DBO3/Pw/v/AR8OGIcHDN2HyCNhkVo7\nfvDH/yde+dhPXP5AvgCwTqP1gB8TITqKU0iDsRVKGWLoCL6drNAlV5xc9Rix1MaR4oAfenwsUAqa\n5mwnw12kJKSYXfhSys+yc/4NQ8A5Q1EYlGanPdCyLPcQBEkJkZgfUw5OkoSyJcVzVAW4aaSY6KYQ\n57ISimfQoOZpQymVne2GFWPMFezlc6Q78jFtydFeYWezghnXhvnqMGPGC44QE4frk40IbvZzAyvf\nbqtGi2JxZsigUkcOQiLCwXrchtgua0cac26RLhx2mUXFew7a3tMNgYP1yKJ2FFZnZ6Jp0BliIibw\no+agnQhGOdAPa5x222yZLWlTeTBtrcZasx3olpWlGz0H/SHOKipVUehyspc+IiOFtXysuUcXWx70\nDyltwbI6roEqbYFRmtW45mF/QBh6TO9xncccsyY/whg9PgXcToVpff9tvvsP/xsHD766/Ttja+rl\nG5T1KxT1K5T1K5TNR6j3Po4rnq5L3bMCESH6DldohIoYFH4MuFM0eNo4lNIE3yESMbZEm5OJfa6G\nGtq2xRjFYr9Bn9PeE2PCj5Hg4yNW9LklMJO5HALpx4gfI2M/oNSIKzTWFbm6pSZD9J2PExGQTJhQ\n+kbsy59HhBDpW5/3t8rE89Hq3MsKPVXB12NLYYvnRq8Wk9Bu2+quz557xgyYCdKMGS80fMgW1iLC\nonJUT4EciQhd6OmnlqTKlheyI959/2Hrj8hRkysvscvOdrY5rjdqquxoly25x+2M/9HyIIWETpp7\n1R7aJKJEokS88kQVCIw46yhNgTYKlBAlEGJAgrD5z8eAc5o7dbO1EBcRQsxtO1qprZ4pjo77yUPk\nRGKoVU5pXw9r/MEBS9tgBNoHH2IXC7Q7PkjpJme/xtX44YDvfPV/54Pv/RtAWNz5NB//4V+m2X8T\nO1cMHkMKPSkFjC1YFFXWI/VhGyp7Eja6JJAzHf4kCeOYz7mikFNbt1KSLSnaVCjVRMaN0WijMFo/\nVnkqSsvQd/RtP1U3S5JYSiUYexJhU6AMipkYbTAOgaEPoKCqLSLZSGPoPXXz/IWf3gSMNuxXe7e9\nGhdGEmHtJzdWZ7HPScVrxvODmSDNmPGCYuPSBkfZPTeNJInDYUXcVI1cc6lgShFh1Xl8yK5xi0nk\nnrwnhYgpC5R5fDsKZ7ij1XZ7jTFYrXLbnI+IMyhlKCu7rQqJCCEFfAyMyZMk0UsP4bHFb6FRLIrF\nMY2QUgpnFY7jN+iYIpUpccayGlv2dlyi+jDQ+Z4kib1gieUeumnonOJwWKOGFt3UmPL44M0JvPv1\n/4N3v/GXpDRSVq/w8R/5b7n3xn8yWzifghRHYhxR2myrLlXt6FpP33qaRXFqO1zep6fvVxGha0dE\nNFVVYqwgKW6rNikJwWdSFONE2idS5JzBWH3mcRMRUuhRjDSLAlElYcx5WG0YMUbhSos9ZzkvK0Rk\na5qhFNRNsbWB9z4SfNYYmhN0iDOeXYgIrY8kEUpjKGZDhhk3gJkgzZjxAmLwcVtN2WvcUzNk6MNA\nlER5Tv7QaVj3gdFHnM1tdVudzVQ90tXpGTXGaO4ss3HBbv4NsHWd2x0IK6VwJucINdSEFIlTrs2j\nDnt5mKyOtQGehSGMBIncqbJGZIyezvcUtqAdW4JENIpyTDhboxd3iJWjLGU/QQAAIABJREFUrBr2\n7n6EsF4jQ8SoiC4sfnjI+v7X+PY3/5IwrrB2wRuf/Dyv/8DPYsrnK+H+aSKlQAx9Dubd0W1ZZ7I+\nbIj0T1hFEBFWhz1DH7FWowtL17b03SHaVI+1zhmrcU5jd0Irs15IOPpjmf6ZA4MlRVIKuZrlGpTS\nFEUmSOMY8gC/9SiVz3HnzLntfS8LJGXyGqOgjaJuimPtdFU1ORv2nsWyPGNJM541dCERUsJpTf0U\nJv5mvJyYCdKMGS8IYkz4kPAxGxec5dJ2ExCRrcPak5AjHyLDGLBGs9cckaPkPckHdOG2OUdnrcM4\nRMYxgGSDhbJ2p7ZR7SJrka5+s83GFB0KtW0tTGlFH4etWUVpCooIKUa0s5imZnj4Lcrx2zz4zgOG\n9fv06/cZhwfE0G6XrXXBax/7r3jtjZ+mvPvKY214M46QbbnzvjMTudhFWbmsUfOJ9eFAUZpj5OUs\njL3n4YOOEFJujysMKWpSUig82pQYk9vljNEnal1iGImhO/eztHHbytcGxmpqW5BiwvtJozTkh7Ga\nosjb8rIiTmYMkmSbRfXocTVW4woz7bswGzY8JxhCZIwRo9S5IbAzZlwF8xVhxoznFCkJfkOKQjzu\nvKY1y8ad6Op2UxjCgCDUp4jZz8KmtQ5g8chgJnY9AOaM6hHkGeN2nZ36lFaUtcXdwg20DwMJOZZT\ntCwWHIwrFFlDZBKM6wesDt9itXqLh+//B4JfA/DOW5slKVyxT7n8JEV5h3LxKnuLz2CLBW5vOZOj\nMyApEn22PbeuOdXSvK4dwxDwPtJ3ATVEisLgipOJUvCR1WqgW3tAqBvHYq/M2iGlSEkRQ4+xGmNP\nr0qk6ImhQymFNiWbNr78kRuzkFzBPMtkQRtNaTRFaQkh4YccUNuFhNKBojAv3cA/xkS7HkGyfqus\nTt/+srR4nwmSc+bCzoMzbge7jnWLws5tpTNuFC/XlXPGjOccIsLgI/0QiSltf6+VonQGazXOGswt\n3Oj7KQC2sJdvV2r7QIyJyoEmIpJb2XL1yKOdO5MQbLQgKUlup6ue7OaZ7ZyffN+llOjD8FhOkdaa\nO+UeMfQ8fPff8eF3/obVw6+RUiaFtljyyhs/wYcHis/86H9GufgIZXkXZRyx67cthpI8qrYkAmFc\nZ0vq2aXsGCRFgl8fkaMzHLmUznqkorT4MTCOkaEP24rCZtAcfG7F61uP9xHrDPt3qm147wZaZcvv\nFMdTCVJu++umtr/FtRw/pRTO5Ra7FBPjGPE+b4vS6lYmCm4Dua3Og0DVuHO3W2lFWdps2DCEGwv2\nnXF1zI51M542ZoI0Y8ZzgsFH2j5neGRjAIOzGmf1U60UnYQxjCRJVKZEn+H4tYGkmINiJTKOntW6\nRytwpSN4j1I6B3B2UzhnfXb1aOgDMR6101wUkhLJe8QHUvBITOjCYer63Ha+XSTvScPAalgTNOwv\n70xueon24DscfvgPHHzwj6zufz3bLwNF9Qp3P/rj7L3yGerlx7Cu4cP/92+5+/o/ObZs29Roa4h9\nj6n3UNZsg0nFr9GmRJsnDyV9kSCSCFPlyNj6THK0C60VZeUoCpvJxRi2g2atFcEnhj5rfRZ7Jctl\neaLWRymN1o4YR1L0j33+prIFU9vfDZBbbTRVndvs1uuRvvMYrV4KbVLf57a6Dbm9CDI5zm2KrjAX\nase9LYgIAi8NOUgihLR55EDxenasm/GUcOME6atf/Sq//du/zW/+5m/yG7/xG8de+/znP8/HP/7x\nrfD5D//wD3n99ddvepVmzHiuMPhI1wdiStmBq7BUpb2VKtFp6OMI5Hyfs5DiSAz91oZbRFi1HtAs\nFyXWOZBESh7fr4jrFaZsUGeYTIxDdqnSRp1LjkQECWEiRdkZbwOlFdoa0uhJo78QUUrjSOx7kg+E\nFOjGljQ+5IN3/ob16tusDr5Jiv327+vFx9i788PcffVzLD/6QxPRGdGmwJyx73RRoIuj161rSDq3\nacXQk5LH2MdDTF8miCTC2CKSMLY6c3+eBqUVZWUpyiNtyjhEQojbdq2T9Cy70KaYCNJ4jCBl8rY+\nt+3vupCJkqNvPV03ufW9wAPrccimFcbqM9vqTkJZW7q1Z+g8zTNo2BCTMMYcOi0iLJzFPcNE7kkR\nJyIURIhJsoHJForKGsoXcLtnPJu40St013X8/u//Pj/zMz9z4utKKb74xS9SnaMtmDHjZcToI90Q\nCDG30pWFpb5lYpS1Ez1K223eToiZHBTaYc6YEU/RE/xGd+FQytCNgrIFy9JR75AbLSWpu59/cIow\nrlDaYUxxbNY9hEjfecJ4nzi+zfe/+U0QwRZLXLnMz0V+1hQwQIw9wbfEsCamnph6QmyJoSXGkcXe\nmyyaT2Fl/0SiJCKZGHU9EiPer3l4+BaHh1+ne/gN0qQlAijKuyzu/Rh7r3yGvXufQQWDMhq3v0+K\nnrS1n778NVAbh9KGGHJLVxjX57aUvag4qhzlUNez9D8XgVKKorT5WEfBVm4iTuffMpU2aG1JKWwt\nv4/I2+UqW1eFc4ZY5FDaoX9xW8hiSNt2wvoJttFag3XZ9vusAOGnCZmqJ0PMjm1wZDvfhshSqWdq\nkuwsJBH6kOgSHAy5rVjYMW/k8XRspRROa4xWWK0wF3QQnTHjunCjV4GyLPniF7/In/zJn5z4uogc\nC3ScMWMGhJhYd/6IGDmTidEtzpzlgeJAnMJfJY4E8mBv68x2xox9JkftMd1FjIkxjBijaaYZX0mS\nNepJICpcfQdTN6RpRj7FEaUMQ/cBqwff4OH7b9EdfovoD69tW++/8zcAFNU9lvs/yHL5Ayz2P42r\n99DWEvqe9vA7HD78GocHX6Nff2/7Xlssufuxn2DvlR9heecHsXpBGkckRgj5pm+XS4S0o0NpnvjG\nr5TGuppkHNG32RVNqZeqkiQiRN8hKWJM8URk8yRkLVJEW01du0tl5WhbksZAjANG1Y+Qt6cTTLq5\nt5aVJYZMkqzVL5y7nSShmwxe6to9sdFCWTlCGBj6sM1Kuw0kydWiIabtMTQ6m3E4rRiT0PnA2gf2\nngOjgiEm+hCn8d7R7xWgc54COUQh/2y0xj5H5G/Gi4sbvYtqrSmKs28Gv/d7v8fbb7/NT/3UT/G7\nv/u7N7k6M2Y80xARuiHQDTmptHCG5paJUV6vRPRdzmNRBuMqUhimCkhkSAGnLe6UWfFdcgQF3cM1\nyjkOuogPiUVlWa/GTI4AFKixxyK4piFJoFt9l9WDb7J++C3WD7+11XFA1nLsv/pPWNz5FIs7n8La\niiTZxMAPh4yr+/jhkBg7kgwYV2GLvamyND2XS1yxB0qx+vBrPPzgqxx+8A98+N6X+fC9LwOKZvkJ\nnNtndfiNHettRbX/KfZf/Y945fXP0ex9/PEBS1OTQiCNI9palNGEcbVd90ftp58EWluweSAefYu6\nJvH/swgRAUlbDdumUqONw0xVzaui73wOF9WKZlE8ZtF9HrS2KGWQyWo8r9/1kbdHkaaWpLjznCbD\nkYUzVM2U+dN5GqMvvT2PYog5TqA0+tZbvbou647Kyl4p8FXfsmGDiNCFxBinLDalKExuKdslC6VR\nxGQYY6T1kcUzUO06CSEJXdiYCeX2uFrDfrnbdirEmAg+EXxEtKJoZjfBGc8GlDyFEs4f/dEfce/e\nvcc0SH/2Z3/Gz/3cz3H37l1+67d+i1/7tV/jl37pl05dzpe+9KWbXtUZM24FIQq9T6SUZ9GqQmPN\nM3CTkAgyTj8YUC7P+ImAjAypx6dIafZOJkjT+0WEEBxx1UOMjEEYROPKgmpRoNTG3Dgh/n10/y5a\nHaD1AUpWx5epa6J6jaQ+AsWruHI/v1lyuCbkG7KIha7Pv7cWqupys62SIHwI/nvg30HCB7m4pUqi\nfZ3o3kC7N3DmEhWgab9BmvblNQ9uJIB4MsssN77Rzy9EgJiPBbLzeBQG9NUrMyJC8EIMgtJQFPrJ\nB2vbYwGgQV+PtkUkn+Fxek7y+B7ZTMxv5hwqDRITYRS0hqJ6MvIcBLwcLRegUOBuiSPlgXUOgi3K\nq69EzlFLSAJXaIx9Ot+fIDAmJgMGsCrPXp/29RWBfjoOTkExbXqMJ3TlPPKjNurKBPksiMAoeZsg\nb4tTU7WIqRshQYpCjDsnr8rreuXv3YwZO/jJn/zJJ37vrU49/Oqv/ur23z//8z/PV7/61TMJElxt\nY2fMuAy+9KUv3fj5JiK0faAfc9WoKizNE1pUb5eZIilFtLFPXJ3YbalTSmUDAFM89jcfrN6DFNiv\n9nHF4tjnpZSrOOMQiVJAEFK7xlWO1RAgRO4sC2xZIDrywXtf5r1v/d+E8RCmxWhdUS0+Q73/Jnuv\nfJq9u59CWDAOIYdlNscF830YUCnA0BHWHdoUuMU+trlaZaH3PavuAcGvqBcfpXYVxRPoSKLviJN4\n37rmsdev45yLoc/HTZvczvickSSRhKSQK5QpHHtNKb19oAxK7/x85c+VrGfzCWMUdVNcaZAmIoRx\nnb8/V2ij3GhRQpJJvJ6Ova6ndiSjpodWW5czHxNrnysSC2cIk5HBxnDiouebj4k+pu1nF0bjtKYL\nkSSCM5rGXixk97oQQqRbe5RWLBZXO1a7iDHRrUdEoKrtjeqRkuQqi4+bKktupbvIfkwirMaA94kC\nUOl4C9upUNA0xZWqbaetj09CHyIpCgqhsgarVZ4XSsKXv/xv+Y8/9+Pb9VRa5WgKZzBWM/Q+t7Vq\nRf0EldsZM3Zx1aLKrRGk1WrF7/zO7/DHf/zHOOf467/+a37lV37ltlZnxoynDh8iqy7bdhutWdQO\nd8WbVtq09IiQokJpizHlpdqtHm2ps64+8f1DHNG2pKAESVuTAKUNKQa69QF+DChTY4xFSYtdOHpb\n40pF4zTh8Dt87x//FQ8++PeIBLQuuLP/OZrFJ7j75mdxi48yjvmGCxCCIsYjMfZmIJEksR5bfArE\nbqD2KVelSg3uyfONUkqsfEtIAetq9hcfeSJiBBDDSNyaMlxPK9hJMLaajv9I9O2VBudPCyKJFAOS\njpMirS1K29xCqC42cHyyz8/5OTGkE4n3k0AphS2enKA+Sko22Gg0rD5Ohk6CM5oFsPaRtQ9UzqCi\nTBMM569XmAa8G5MAZzSVOcpZM1qx9nmAvxKeWj5NSkLfelBX0x2dBGM09aKgW4/0XUCmwNkNNhWa\nq54fu9ocozPBvKjuJrelRWSI9KOnB5aFpSxym+FJSwkp0fuUXT8Pe/b3SuwZ7qC72JD03LoJQiZj\nKSVCFHxIpJgfAKUxFFrhveB3lhODgFI4d0SKdrHJFRuHSLsen6i9dcaM68KNEqSvfOUr/MEf/AHf\n/e53sdby53/+53z+85/nzTff5Bd/8Rf5hV/4BX7913+dqqr47Gc/yy//8i/f5OrMmPHMYN35bdWo\nLrM73VVvuCmOW5c4Y0tSnGbho0drizbFie5ZWTwb86x9CqSY18vYAmPrU9erDwMKRVPtZdMG3zP2\nK9Al3XqFpIR2NWVZgUSGdWDQlmTAr9/iw3f/FQfv/x0ArrzLveXn2N/7MVy9RFmLTgX0LXXTkFCM\nU9ZRngE9GhTFFDkc1oRxQI2B6Ac6Y7h77zUgkOKISJzMEC5OQIcw0voOQSi0oynqC2U8bffrVMkT\nCUgKW5J2FVOGi8K6moCQoofQbx0HnzVIisSY9WwbbEmRcddSGTp/HXLI8G6O1nUdnyci5SJ0PuIn\nUrJLiKy+vJOXM5qlUqx9oI8R53QeWHfhVJMkP1lK+2nAa7XeVgN2oZVi6QxtyO9ZjULj7GN/d1nE\nabC9Wb38fFQhiSG/dlXd0WkwRtMsCtr1yNBPmtDSbqs2ScAZRaEvr8GKkzYnTNqc2hrKCxKVECJD\nF0hTj6NWsKwcXgFWU5T2GEGVyfBhjIkoAlahRNN2ge5Bx96ypLAaq/WxY7ZLiHzKurZNL1yMWTcU\nQ8qZfJnzoFCU1lC5TPRyfMvRd0Dp3Aa53Du71TSTJMU4hJkkzbhV3ChB+tznPsef/umfnvr6F77w\nBb7whS/c5CrMmPHMoRtyS501uWp0HSGv27aqqZ1Ha4uxuaKUwpCfU0AFk4mSNpO4fUOKhBDybLUk\njdIObTRKjdub3NGzyuRhHChUQRt8nk0MmhR7RHqiCNrWaFPQ+og/OEBCYEzf5uE//AvG9l0Alnd/\nkNc++bMsyjeRkMBolLO4ZkHsupxJ9PAAU5bUTc3G5E4bPekFOg5XD4l+pNSO2lYMlcWXhi55lsWC\nFDc22KvtvjkLSRLt2DEmj0KxdA3FBZzHcmtY3O5XkaOZf6UMxpgp0PXpCDaMrWFTSZraJB9bX0lb\nw4NtpeYpQCSRwkCc8rOyNXZxpbbQJ1qPJLTrkZQEV5hbtcEWkamqkPVWl60qnAWrFUtnWfuAF0FZ\nhQ7C0Ce6NjtJioIAhB13WaOyuP4sEpCNICy9ivQhshoDjTMUJ7wnTeYRGw2Te4TwpZgYpjbAc7fJ\n6QvZrj8p9IYktZ6hz5WkoNmaX/jJqEIHtW05POlYbQw0NmGncdq3TmvqS1TcYkh0bZ5IsDsVGKUU\nnY8MMdJNpg1xsgcf40a7l4lyaTQUjlaPrDvPajVMraQxT95olQ1EdwgR5PMgBSH5iBGFVaC0xjiN\nsRprNcacrxvSF9TVlpVFqewk2a5Hmsa9FEHHLxv8mCc981dAbTV3ahJRbu71t0WQn037kxkzXlD4\nEGl7j9aKvebqM2MiQgwdKfoT2+G0tujCTjP1I5JyuKhPQgwpzwQmhcKgdJGXUeab7saWNSXZDawA\nYDV2hJRopv58rRXYgjEKve8oqhptC0JKqBgxccWH3/8LDu//f6A0r7zxE7z+6Z+jWX48k6ckmP0l\nHYEgERd7yrrEliWx7YjDQBpHTF2BtYSuo+0OaX2PAhblgqpeoIuC0lrWY8sQcwVoWS6IypBiTxjX\naOO2VYpHB+Nj9LRjS0Jw2rJwDfqc1PZMMMdtlQjYyXqyT33Qv0EmyzUyttmeXSQPeSb3t8erB8ON\n5yhtWv9SHKaKmsHY8taym/rePxPkKKRE6+N28F1Ze+2BmEYrloXNFRADPmaisuo8fieU01hF5SyV\n01TOXrh9rbIGo3LLXesDIWkUakuK4lQF2sUm68YpRfQRP2a9lDEKV5jtIImpQsHGzEXdrNHABnqn\nknSwHkhWsagLloUlpMQYc4WmD5GeiNGawuQWtw0hejTsdGPZfRKBPA0xZiKLQL1wj7XG1c5M1Z7E\nweC3n6knJ7zC6GNEbH9RUhpN3wfER1xticK2YmiUwupcMVQijH2AmEm7nYiZvQAhugo25HdLkhbF\nTJJeEKSU9Z4xnD8RAmCsxrl87j3NdvGZIM2Y8ZQQk7CaZgCX9XWQoyOtkNYW4+rTB+JKgyoIUeOH\nPrdG6BzWWhT5hnfWTW+bYSGCDwFnFEuzYFk2jD7SjzFXjYqCvarCWY2zeUb1/bf+Jd/75j8nxp7F\nnU/z6c/9j9TLN3LI6kSOVFOxxpMkYZTGp4BPAY2iWBRYn2AYCW2XjS1Cj5eAqyr2FncoyuMtZI2r\nSZIYk6f1HY2rUVoTfb9tO4Sjdi6UposjY8xVo8ZWVO50S+ZcKcrL2VSK8mDfPtVKzHnY5CQFv95W\na/LvzVQh3BgcKGLoCL7FcjMkaRMyLJKmNtB6IpG3MzsYQtwaMtwWOcoBmnGa6c/mB5W9OR2PVpkk\nrccAhUZKg6kdKiWMgJHsKqYShCGxGgecM7l16wLXK2c0e1M732abMhRGgVZ5oK4nh70hRA77AT/G\nbbVq2bhnIqh1A60VrrI54HQUtEtQMLWlQW01PmWiFFKiS8e3e9O+ZtSTtUimJEemEc3j5GiDxhlW\nYyajdiJqj1bodlFWjpSE4BPKC3uNyxV6lc+TXKGPjGMAyVWrqrpevdd5eJQk1Yvi1mMvZlwNwedw\nd5nOqWL6rgv52nOUHZzHHMHHPJkbEvQhm3oU5sL6uavg2bkKzZjxAkNEWLUjSYRFdbYZQxasbwaz\nkzBdqe1AVimFpDiFT6ac/zJphWKKdKEnpEipHQZHDIkQ0vbKo01JUU2k6ITydYiBJGnrMbuN8Zva\n7DxTS13UPFgNR4GUzlAWBjdduPr193nrK/8zqwdfR+uCT/7Yf89rn/wZlNKZHB0e5uyjuqAlz3rW\ntqJ2FTFFhjgyhpE+DKDAVAbrE0McSUVJXeyzLBYnVniUUiyKhsNhRR8GjDKUtkCXy2NtcDF6hnFN\nN+mpnC1ZFA1GKWIYt6X/aaEg6Zi7Wq4UFduq1LMIpQ22yNud3d9OMTtQiujbayVJIjLt52H6fDVV\njJ5eq+Fp6zV0+RiWt0SOQhLWPlcdjVLUzmDPqVZeB7RSLApL5yNGwbK0jw2kNxqTccxVHT9GXJEn\nU86bxd9UqmKS7WD7UcInIpkUjREbAaPRTqOcoRWh8JHS6qdi+HAeYhK6mKibAuMT0Sf6zk9tYGrK\nK8ptdpuQV8gEyuxocJ4EskOOysrizgj53ZDfzb8vgqp2dJJn8vvOUze5lXjzc55IU1S1vbWA4cdI\n0hkkccazCxFh6EOuEqt8Pl+kRbYoLSnl60XwcbL2Tyjl8zXpGvTbp+HZvKPPmPGCoRsCISZKZ6jO\nuCjEME46ntP9WjcXAxHB2BJjK5IkurGnj8M2dO8w9mgUla0oXYErNNY+7hy0wRg9fRgIj1grH1u/\nKKx7j0oaUyq0hrp0lM5siZakyDvf+Au+9/V/jqTA3p0f5lOf+x+olq/m1zfkKCZSmbULgrBwDeWk\n9THa0Oia2lb46BnimB3qHOAKKuNYnGN2oJVmWSw4HFasfYtWCmdcdpHTBh81XQwENMY4Km2zQ10K\nxDP2AbA1vchterc/iDsPSmnUOQNbrS24huhbYuimNqbL3yI2pCglf6ztMBP56laJ0QZ+jNvWutuY\nkY475KiyhuopD/g2JKnSnNjqZUyePClKi/eRcRrY+DFutT9n7Tet1DG9SUpHwv5swHDUirq3cLjC\nkIRsKJASQ8wmFcvC3ipJSpKPEwiL0uIqRduOebAWUiYOO8dOT1Ww64CI0LZZH1eU5kKDycvuK6UU\ndePo1iNhIn5KZRc5AFcYyvLibZY3hWJah77zdGtPVcszVWWccTZSzPq5lAStFVXjLnXd1VpRVjma\nIIaE95ksjUNEG33mxMFVMJ9hM15K+OgZpzYrtW1sz//e9Lj7Heexq2DwkW4IWyvvkyApEkM/WWvn\n9iOl9VRmzuGnWVC/+VkmvZGl9z1dGAghEkfBKUdpKrzyBO1J1pNc1qOYE2aox+jpfU+QfFMstMOa\n6dIw6VaE3IrRDx6DZVlXLOsCZw1hXNM+fI9+/R7d+j0O3v97+vW72GLJx978Re6+/uMUy/1pOxP+\ncIXEhHea0SQUir1icWLQrFKKwhYUtiClXD3KGo2LhW4abTJJGtesx5a9colC0fpswgDQFAsqV+Yj\nL2kq9W8I6sY5ayNaVk/NXe02cIwk+RYuYGqxQUoBiT4To60WK7cdau0uZTV/k0hJGIaAUlDeoMj/\n1M+XI3J0GQez24JzBucMwcetgULwI8bm6vOjAms4ypKOMeXw0t1kWZU1RsbmitRm8G0U1NpQiaYP\nmST1IdK42xumbHRhpTkynWgWRW49GwLd2uOKdO0kYmM7n2Im8Rv765tAJklZZ7XRgGmtKB8hf7cN\nNxladG22X09JbnS/zLgejENgGHKbZj6XrzapuJEDSJUrSzc5wTUTpBkvDbJL1MgQBqKcLw7s08Dh\nuGZ5AaH+aYgxse58nik9IVtlN5AVLjfLPoSRbjjE+0AYElY7GlNsy87GNLnlzveMyXMwHFIYR2Nr\ntNaMYaQL/XZfFMZR2Qp7UuaRj/TBY2NPfP/f8mD8Pu+NH9Kvv0/w60f+WvGRT/wXfPRj/zVaHLZp\nttsaViskRgYLwYFGsSyXJ37mo9BaU+vTdUGnwRrLwtWsfMvhsNoSPqstjauPf7YyJ2aIvEy4KEk6\nZg9/TIulMKZAPaNth0PvQaCsn/7MeBJhPQbSVDl61snRLqwzWGcIIVeUYkjEC7xPqaw12FSltDlb\nh5MnQDQ+ZRe2wqSn0nr4KDqfrbjt5Da3u35lZbFO03d+2/pT1e7a2tA2AvaN7fxNQ03BrH2bie9N\nti1dBcZm04yuzYGyKcm12vLPuBzGIVeW8xzi8a4X2fmHUpN+7horPfk+c8NxGTe69BkzngHEFBnC\nyBBHBEGhMhkwJVrpHHoHU7Xk6N9OWUIKHAyHNEVz6YBQEeGwzbPpy+Zxcelx0brGuPpCA8oxejrf\nMfqAHxMWS2MrisI+1vpitGFZLvDRZ6IUPT7mKlWSTahfQWVLzCkkpRsCh6sDDt/51xy+86+JsZte\nURTVPfbvfIp6+TrV4uihcfiDQ3Th0DZvU1it8cPAaIVUFBil2SuWT0w+L4PCFtSS6EKPVpqFrS9k\n3f2yQmsLtiZMJEm5BUqbHStzf6JrX9YWPV2nocsghty/ro166i06IsLaZzOTwjz9trrrgrUGuzSk\nNFWzp+BQ4EhkvXHEM/qJnMeUUpPpQKD1kb3i8uYGV8EYcwVLT+txEjZZSX7MlbWu9VgXr2xk0Hf+\nVsxDtFY0y4tV5m8TG2fBrs1tgV0aJ6vyZ/Oac9MIISLCjbWZnQQR2Z6nTDrD4yXkbVPO1B7nnsss\nq5kgzXhh4SdNjZ/0JFppKlNmsf4FKjSVKVm4htZ3rMY1lS2pbXXhG/W688SUqApLuXPxEkm5nS76\nHdF6ee5yNxWf0QfGMWLFsjANrrCU5dmBic44nHG56hSyxqkyJZUtTyUoIsLDgwe8/63/i4P3/h8k\nDhhT8can/hl3XvsclgaFQVuDWSzQ1pIkEVKkf/CA6D26MnT9Ib7v8G2LNgZTLnHasiyaSwWvXhW1\nq3DaYvSzO4B/lqCNw9IQfEvwa5QyW3MKyLomYxzKuGeaFO2i73Pnaa1tAAAgAElEQVRbZXWNrTkX\nbcNtfSSmhDP61EH384Q84Lm5Y261pjRmarVLx6o4N4U0BaS2PgI53+ksXY9SiqK0WKu3A8Z1GChr\nd+kBqySh7/2WwNdN8Vx8p24D24rXZp+/hFlJKQnDdL4AhGsg5xf93K4dSVEyib+GuJJnFTNBmvFC\nYggja98CYLWlMkUW6F/yhlPaAqMN63E9GRjEC7Xc9UNg8BFrNE119DXLVaNsVZ3DXKtztRljGGnH\njn4MBB9xyrEwDUXhziVGJ23PphJ21r7o2/t852v/gofv/hskeaxb8JE3/imvvfnTlHdeAbKeKLYd\nY7em7VuS06SqQEIg9it04TBakHEgdj3OOMr9fax1lPZ8QngT2GqrZlwImSTVBN8hEra26Pn59gf5\nkoQQE1qrc3vRxyFsNR2X+c6chk27XBRwRlFMds4nndetD/ipXat5TitHt4FNq90QI87k/Xtd2AS4\nxp3n3cyihbMXDunVRtMsy63eom893ua2u4sMHmNIdJ3PeXDToPNlrYhcFBvt1NAHxiE73LnJZfEk\nd9bTkE1lstZUa3Xh/f6o8cjTrJTs6npMtkrckvOzrOCvihAifZtdbK9DT/SsYx4tzHjhME7kSKNY\nFosrD4qtNuyXe6x9yxj9uS13PkTWvc+2q9Ms4ONVoxpzTovXGEYO+5Zh9MQgFNqxdBVVWWxT1J8E\nJ13QRISh/T6H99/i4IN/4MF7/x4kYsu7vP7xf8rdu5/Flg12b0lKacop8gQTCKUitR7pItYHSmNR\nRUNx5y5Ga2K/Qoolbn8P7WZR7fMGbQqcMjtW87eLFLNtffCRGI8GtNZpytKeOIssSRiv0Zhh40K3\nCXb1MeFjmoJPp/DTaT06n3OOjFIsnnLQ4fMOpRS1Nax9oPOBvfLq148hRIb4aIBrbhNyOme3Wa2e\nSPdUlNkOe6MhWq8GyvJ0O+OcNRS2rnFFaSnK+Ry5DMrKok12uMv7Me9LpbNGxewQpiRCSkKKQkpp\nen40vDgTJT29Z/MQOApXf9R4BEhRCCHnht2U81+Mk/16zBb6ZW23rcIb0rQ1Drlm8jIOgaEPoKDa\n+dwXGS/+Fs54qTCGkdWGHJ0j/s+i8ov1tiuVydYQxmMtd407HlAaY2LVZhK0bAqMVpeqGqWUGMLA\nqusZxmyLWZocvlqWuW3jOi68Iol+9R6H97/G6v5bHN7/OmE83L5uq4/w6qd+gY++/uPEbkAZg10u\nCCmwGtut5kArTVMtMc0dzBiIXZ9/XzqsKwhTEKxdNDM5eo5xk9WiTRVoEzm1cZXcuEkq8mztJth1\nd0CzcUPbvBb8uDUpYXJSE4QwxG2WzFW/PyEl1j4es+gOKeGjbI0FxphQQWGVwqe0tdWeB76XhzOa\nImnGmOhDfGLtVhKh89k+HI7IkFEKox/PanpSaK2yNslHhs7n7JfJxGG3yplirhqlmLOG6tpdS2Xz\nZYRzBms1KU5VnamyE7xsW9BOgpocFXNoNlvyFKMQ4+kWJMeMRyY3xxDSNucn+EhRWlxxPWT3USJ9\nUmhvMXWT9G02DokxUddXbzvc1Ru9bOfpTJBmvDAYo2flW9SmcnTKoE5ESKEnTpbROcvGorU5dyD4\naMudRlG57KyWUjZlSCIsaoc1EHy7UzWqMCfYU4vINuunG0bGISApmycsFjVV9WQXJJGEHw4Zuw8Z\n+vv5ucvP7eF3s0PZBFfuc+f1/xS7+BTl3g9w9+7HKLXgD1corXB7SyLCaszvaWyFM+64sYMtMGVJ\n7HtMVRHXa1KImLLEVJd3n5vx4iPFRDsFYV4I08DEOoM1GhSMSdBGEXyg7wNx5ZFDsEVOaU9JCENg\nWboLZcmcBR8zOQKhdpZyGnxYrbEaajJZGieytCFHt53n87yjsgafhD6kLbG5DHxMdCFbdludNWA3\nfTzcdI5udEXtatzmGW2MHa7L+njG5Gpm1bF75W4b3CaDJ1eHFFqf3oa3abtLOw9gW5E6iXRsSJof\n47baMo6RsjRPVG0RkW1m2DhGZFr/s+zXjdE0y2JL1Nbr8cwK5rHPm0xXkuR2w83Pm0kps9HFvUSt\nnzNBmvFCwEfPemy3mTqntdVJipOeIqJUvsik6AFPZArUnDQWp43arDbslUsO+kPa0GMn4f+q84QY\nqQuN04kwdtmhThusrR8jXyFFxjAyxhEfc+iZSprKVCyWJVV5+YtRt3qH99/+Kx6+//eM/X3klMDT\norrHnVd/jL17P8Ty3g+RzF26IbvbLWuHVUI4WKGUwi6XJAWrYYUgLIvFqe2FyhjsYkHsOuIwop3F\nLJpLbcOMlwMxJrqJHG3aijaZU5uv3q5L3mbGNjsw5sHymNJRqLJWlI0jhcTYBwiCj2ES3ie44qzn\nGNMk3s/6FHfKzOyGLDGRJa2urzrxskJPrXatD3QhsrzggFOm82SYqgFPO5RX6TyoDCHSd7kC4Mdc\nzVQKyubyZg4zLo5MiMyl97FSCmUUly2cb0w7nDOMYyZIm+NunZ4mZHNmmFZq+zPkyaKY5LEw5Q0u\n2n6pVHY/3BiHbDRaZ2Eb9XcKXlYSPxOkGc89QgzbysayaE4lRzGMpJgd3Iwp0JMjXbYuDjnoMgVS\nHElxBOnxw2HWXajp4rajxWhczcFwyMPuATpZ/BhwFpx2xMCpVaOYImvfEVLI7UVjQiXDQpeUtTtV\nR3EaUhy5/+6/4/tv/xXrB98AwNiKevkxyvoeRf3KzvMrFNU99ERwRIR1n3uXtVbsNQWGXDkSEdze\nEozhcFyREBbufLvz5D2h7VBaYReL5+qimkTmwewjEMk3bRQYra9lBnGXHF2mnz0mYQiBMeY0q5yZ\nY7Baozd2s4AsJM/kTq0mAxqPTLk6lydKQ4h0ITubLQtzYX3KbeT3vKgojMbHjWlD2lbvTkNMQusD\ncfpON+7ix+26Ya1hsdTbmX1j9YUNHGY8f1CTYYMr7DYraNMe9/gfT89y/He5ffgoP+yy113rDI3R\nDL1/jGw9Cq2YiFt+aM2WvGl1ceOKFw0zQZrxXCPEwOGYg0qXRYM7YfAukoi+I6UwzUQ3W4IAU9XI\nFGiTTRM2RAn09ufT4FLkYdcSgnCn2mNZV9tWPaUeb9nbaJgEQQUNUVMrgyn0pZPLu8Pv8f23/4oP\nv/clYugBxf5HfpRX3/xp7r722VPbBUPbEoYVKQmrzhNjwhhNXTmS70jkQbFtanCWw2FFkkRjK8pz\njCUkRsLqqPKkzPMxO7qrT2icfaJB9IuGGBLeR7yPx27ej4qYNwLoi95EY0i07QiXIEc+5kFxSFlP\noJWitJbiFNe47UxuYYghsdCKlY+0PqLV5YhLHyJ9iCiVbZ+v00ltxuVQO4MfhD5EzKRPg93TM/8r\nJqELCRAKo6nt7RsfbGb2b0rAP+PZg9ZHx3yTGyYipMT231sHPbtjKHFOmPJlPr9u5ry/J8VMkGY8\nkxARYorEKcx0e6mYLhpq+psN2VgWixPJ0WMGCa4+14lLawvagi5x5d4UhphyiGxKQCL4QEoJZxqi\nRLBCtVzgivrEZSZJtL5jjB4loL3FYEFnV63zxJwiwtg/oD34Nu3B2xx88I+0B98Gsn7otU/+LK9+\n4r+kbF45c9tC2xG7PlsU9zm0siwdzSPlc+0KVFWyGtZESVS23GqtTkPynjBVnuxycSOmDH2I+JjP\niUfnxDY/26mqcFGdQki5dWrjatX6uBVuv2xIMeF9JkYblyalFa7YTBacLmI2VlMU5sy09GPkaKe9\nKImQhG0PfBJITM/TQAJyBasy+tT2tkeRJ0TyZyyAtQ+sp+DR8yqFSYRuOt9mHdGzgdxqp+lCZDX6\nc/5aPZOTHTM5evmg9Mt5P3neMROkGc8MQoqE6PEpEFI8Smc/B8tT2r6i77ZGDKcZJFwESilQBgWE\nGBkHwQfDEGDVeUzRYMrAg74liMIoiwBG5Z73lCIr35IkYbXFRceD+39HigeUZUWwuXqljUPr/Ky0\noV+/x/rgbdqHb9MevE3w62PrtXfvR3jtkz/D3ddPrxYd2x/DQGhbfBJ80aD2FHulpTkhNFNEOBzX\nBImUpnjMre+xZfc9Yd1OlaMFprz+RPZhmsnPzoP5d7u3nM2/fUr4USiNprL67Lyn7TLzsdJK0frA\n2gf2XiLXMe8jfghHttkq951bp0+saorsCJg3WSAh0YWE0gHnDEVx3HExhEjX5kFt3TisM3mSY4f0\nngStFNZoSqOv1CLljKYWMw2uzz6+w+SYJiIYrVk8BVH/jIuhtAaBHZtutfP/6Tcqt+TNx2zGjBlP\nipkgzbg1iAhj9DlPJwbSDiEySuN0ccwlbUuYphujkA0THq0cZc1EN7nHGax73CDhsuu50TNIyjPc\nXYwc9B7vA7V26NEwqIGYVizLJVppInA49MCYB2e2gv6Ab3zlf6E9+Pql1qGoX+HeK5+h3vsEpblH\nVb2OsTVKKWI/YKoKdcrg0YfE0PX0Dw6ISTB7e2itWVSW6oT2JhFhPbaEFCiMY1GcbbIQ1mtiP2TN\n0XJ5I5WjkKbBt1LsnTOTv7EDHmJkTInKmsf0CkmEtY/ESUS/q08IyTDGSBsiC/fiXyK3+RbkKpAr\nshvTWeRQqU3GCLCpAsXEOOaWvHEIjGPA2uwkJyJ03USOaret6mzIUa7YHemIjp6vd4BbWkMU8vH1\nkcUj539uzYpTK182BijnYNdnDk/TaGHGjBkvJ178u/+MZxIpJVZThQJynk6pHU5brLboJ5wpFhGi\nb4nRM6SIcwX2CcMtJQlD77euQygwLouE16NHu8i9xuG0IgZBgibGkaDW3F3u87Dv6MKIUppKO+5/\n8y95563/E5HI8u6P8JGP/+egZDKF8KQ0PUdPSp6yfoXF/ps0+29iiwUAYbUiDiOmrlFaZbe4rif1\nA7qqMFVJlMRq6Bl9JIRE9J64WgFQ3NnHFoKzkUhiPY47xHM6NpIIEnHasnCnkyNJibBak7xHW3Nj\nmqMkMrmHCY09v82pMBqn1VQFSHQ+MAZFPZEgHxPtVB1wkz5hd5m11USRrHvR54vBn2dsHI6UVjTN\n1TIztNFUtaasso1xzgPJ2UQAqKlyNA1uWx8yOdKa5VMMUG2cIUm24e58pJ7IWq4mZt2K05p6rhrN\nmDFjxkuLmSDNeOrYWHInhMqU22yhq0IkEXzL6Hv6GMCWhDgwxJHS5s/R55CljWOX95GhT9l6W2WL\nTXTkw77jg1WLQtivC3K8j4BJGKDtB9ZDRzv27DUN96qK9f1v8c1//F/x3fsYt8erH/1n3Ft+GqUs\n1euvXbjiEodha51tm9zypsuS1PfEvid2He3hivd9TzJZCKwQdN/hnOD297CVBSJe4iZw/EQ4bVkW\npzvQSYzZ6S5GdOEyObqhweRGH1RZcyntSWUNhdH0ITLGxGoMGKWIE9vdzbF59L0LZzgcs3GDUeqF\nFOYfI0eL4toctTYGCUVpCSFOoYVyLGCw9fmYGKWeKjnaoHGG1SgMMX+/fUxEya54tX32dCszZsyY\nMePpYiZIM66EFMKUGXAxgtOHgdZ3KBQL15zrinZRiCTGcUU3rvEorKupXQUi9GGgCz1DGE4lSjEm\ngj/KqABQGlypiTrQxjWHnedg7dEoXlsuuDfl+wiCFEAt7I8NHxwcEMbAENbcf/cvePje3wCK5iM/\nSbn4KUpXgChi19O/9x71G2+cu/8kRuKk8TFNQ0iCUVOrU10TbcH64YoH64f4GNirK/bLBSZFWO5h\n6gZTP26ysPWBUsd/d9aANXlPWK2QJJiqxC4W5x6fJ0U/tTtZrZ+orSa3z1kKk1unYsqD8sbZM0Wz\nWikaa1j7QOvDCyfQvyly9CisNY9pmDofGWMmnotb0nnpyZFu5cNWg1YYvdWhzZgxY8aMlxszQZrx\nRJAYCeuW5LOuQGmFMhZlLdrl592Bz8ZxbogjGsXyjDDXS69LirT9Q7qxBeMoiwULV2+rUqUtGcKw\nJUp9GKhsSaEdMQjD6AkhkWTKerHZcjO6kVZaJAidT3S90Nia15cNy+bIEjyMLWFc4cdDwrii6A8Y\nVu/zzvf/Fok9tv4o+6//PCJ3CAQORBhcTaUter0ivvsOizc+dmZbYViviSmR6po+Cil4tFIYpQhT\nK92owd5ZcEfDIhni4YrgQzZNsBatztaVXASblj4RwS4aTHW2s91V4Cct0UYjdBVYnbVLu8TyPDij\nKZNhiDkD50XRIz0tcnQSNtowPZGj2yQjRudK4RByNtJFq5MzZsyYMePFx4txx5/x1CAp5UFyPwCg\nnUNpRQoxkyXviV3+W20NylrEaNahJyrBGceyWKC1zgGtknJe0CUHSiKSB3p+oOsf4sVjbMXSLal1\nBaJI2TeYlASdLBWafhzo/MAqDRxJbwRrNdYZjFUkpUhAlEShHT4qoo/UBu6UGn/4d/zj33+Z1f2v\nE0N36jpqU3D3k/8NxvwwbevBQLN0JAOjM/iqILQr9AfvUfmexeuvorXBKI1RmsIUaK0Z1y1tNxKs\nyaRSwKBYdZ5hDAiKwoK2kT1Xsl8uSesWKTzaObRzhNUapVt0WWHK4tJaoU2+UQox2z7v7d2IGcMG\naXI3g9wOdV0D6cu2ytXOEDZ6JBWfe8H+0HvGIeZ8jFsgRxvC+6xU5KzW2GImRjNmzJgx4zhmgvQM\nIeft5IdMgYibZ23trYZuighpGIhdhyRBGYNtanRx1CInKSEhkEJAQkBCZBzXrH1PIpONsoAwHCAS\nERVRxqCsw9gSbYoLEaUYEl3n6YeWdf+AJIKzNbXeg2Dowun5GAbHwll88oxxwFpLVTqMyYNwpfTk\nnqVZmgalCg67gbD6NnLwFd56/2+3pKhsXqXZ/wS2WOKK5bFn6xZYs4/yeVBalRpQGPEYV+AWC4IS\nujcKunffoT1YMSpFcfcOhcmOXquxx+Dwhy0JMK5EomAQQhQcCu0s2ir61DGOIy4WDP0hJiXsosHu\n7UFKxL4njeNUAfr/2bv3GMvSsu773/uwTntXVVf39HSPAwiCPPO+wEAGfNRx5OBkHkiUvP4hRiNg\njCZGmUSiiWggAhoQBYRgkCgORtHoCBoNfznE42sCwjyDoo7PKwqCM9NMD910V9Xeex3u0/vHvWp3\n1fRhaqa7+jBzfZJKV/Wu2rX2rtXV67fv676uFl0W6LJEl4/9nO9cNTJViZlMztsx71KZu9xEobHm\nolo7XwrL/Ug+YrS64sfzRO1HOEopMcQcIBV5ZU4r8hDPHd3o+qswHAkhhBDnIwHpCksp5eGa3i+H\nIZ6PLgpMU+/rK/fnEp3DzxekkFcP7KRB1/VZF9ZKa9R40Q0w+IFusYkqalZ0QYkmDB2h7/LnK43S\nhhQX+MKgyxJbTTFFdc5hrikl2vmCdmuO7xd0bkZRG1YO3sCkXoO0PZ2a5dRqpRRaK5TOLYOVzjN0\nwiISOpOHtkaFtvas53VwMx74widpT/4zsf86kIeyHn7at3LoxhczWb3x3M/XGESiCySlSM2URikK\n3+FCAVVDcvnV6/ViwuoN38ji+MP4ucfWwKRmqx2Y9wv6rTkNJWvr6xRJEX0kMu6haApKnVi0W7j5\nFjpAMjAHTFkyaSZYyGF2OiVNJsRhwM0XDIseO7i8qlSU6Ko86/GftWq0srIrEO+Xdmy/XRh9VazY\n7NyPNHeByuQuZ9fK4L/t1VY3XLpwFFNiCJE+xMf8vTWOdR6bX0g4EkIIcfWTgHSF+dmM6BzKGLTW\n42BFBXrcKD++xb4nOrf8XFNX6Kq66D0lKYS88hPjuHKVIO1+P46lTqauxvbSj/0KeoiBhWvRRcGq\nrdBEYnCYssaoCUZZSDo3H+gHgsuDRv1snru0VRNss4Iylth3DO2C+eYMP7g8JNQGqqakKabUA6jC\n72k4afQeN5vnsGcMKQa6zRP03Un64SRDf4q+O0k7f4TKzZhvgdIFB2+4hcM3voTV6557zvAGOUjm\nYDTOlKkqBgzKJ6xv0VqxcmAVjKXvPcFHvEuApjhwiP7YcRb/fRx18CB6ZUox5FU5O4Gy1kyqAqMV\nKgZU8MR2Rud6FsOCQhsOHFiHosRpjUuKLkSGmAemlkYTQ6L3imAaEoGYPCVx7I7X53OwLDFVOYa8\ny7tqBHnf0fYelclVEI62FUZTJ0Pn876ojtxkoBif26v1on97tTXFhDaKyaTcNbz1cd9fzJ3fhpDY\nDj2VMVRjd7o4vkgRUyLseB+V26lfK6FSCCHEU5sEpCvILxbEIe8TKdZWL/i5pqqI3hO7njgM+PkC\n1bboqsJU1Z7L786Uv42lcBeYYA9jyUxRYCYN2u7tdEkpMRvmhOiptYHQEwGlDcZU6EcNdrWTyRiU\nekK/wPctg9tkmG+hUAyDp+8DSmmq6YRqpWGh8oyjFVURxmCVQsgB7jwXq26+xeLUgyzmD9P3X6Nr\nH6GbHyf47qzP1XaNnht42jd9Gzc+8yUUZXP2cxkTWquzgpEuC+xkQkyKMB/ADxiVf4bbKzDNpCSl\nRNd72s7RJUNYXSee+Brq5CkarVgzmurwdQwTS3Qtbt5jlMl7q8h7pzoVMStTDkwPUtj8vJbkV/h7\nn1/hn3UO7wImQanzXiuMIgSD04rKggqOOLhlCR5wWVeNIIejuQtA7jJ3JbqbXch223AXEz5EXIyE\nsXTsagtLO1eNAMrKUFZnntOU8vSrlMYujI+1CEQewOu2S37HYFSa3Y0/cv658o9fCCGEuBgSkK6Q\n0PeEtsvlTyt7a5OsrUWvWFJsCF1P7DtCm9+U2rnqNK5Eje8DORQFn1eFRkordFnk7nPj5yut8+DQ\nFElqXE1SCh7H4sGs32IY5hRKUxiL1hZtyrOC0U55T9MEO5lQhEDoF7h2TrvoibqmXq9p1laoqoLN\nfoaOiknRYEyBtha3NcsrHt7nmTxa0249zOz0fzHfeJDFxgN0i0dIacfwH6WpJ4dZPfTN1NOjVJPr\n8WqNWVehA8y+9J/ccOj/Jm61DCavsChjUUbT9bkteOpaVAoYoynqCrsywYylat2sJ4VAkTzKGsw4\nuyilxKLz9OM+G1R+ZX/9QE1aLxlOfB3XzQnG4rSmjp7Wd7Qp4G3J6vQApqqYhx6VDFNbL8PR8lxR\nilKpPNOpD7gQiVahC50vlrXCDZGh93QDlFVNOZ0Sh4E4DCit97xaeCnkcOSB3Flsv+YObTfuUPrC\nrczPJwcDRWX0OGw077/xO8KS1bkjWvkEv8fF2rVqpBVlbXEktgY/hqI9pKHzMFovVySFEEKIJysJ\nSFdAdC7PtNGKYnXlcV+EKq2xk4bU1PmCth9yoEmJFOLuELDz64zBVBa2u8tpPV4wBpSKpOiJMZzz\nAioGh1IGbQq0Kc69RygGtroN2n6ONYaVagVtK7R+fKeZNgY9WWWIJYWJ2MJQNwVaK4bg8NFT6oJi\nDFzKGIoDa/jZjNAPbP73P3Hia59lduqLZx67MtSTo0zWnkYzOUpVXU9VHcaYIrckt4ZTQ6IdAuWa\n4tCk5Osnj2GahuQDKXji4ABH3zm8i2it8gWnNlA2JG0Z2oDpY+7sFxIMLbrQ2LFELcbE1mLAh/z1\ndWkpC4PdvuCsD1IYRf/1UwSl8T7QK8V05SDORpxOLFSkJOCSp9CWutjdajv4uCzhA5jWBeulwQN9\n2C4Ryxf7qdAMnaNbBIrBMJkU2JXysq6CDCGyGMPRSrl/TRmG3tN3/sxfjA0E8usI4141pSgKs6cy\ntHOFpWEMSz5GWhSFUZT68rSQfvSqUVFqktXMQ2S7HE4BWuv8eocaZ14xvpbCsrHjOdlruEGFEEII\n8XhIQLrMtje+p5QoVlcvqjOdUgozltjt+h65SwEpJUKI9D6QjMl7mcbbk4vE0BNjT0qJaWEo9NjF\nzdjcelsbQOeOc9GToiP4jhh61PaqkLakGAihpxsWtEOLsQUHJoew5omXZg29J4ZEURqacebQ9iwl\nIA+B3f2o2Zp/iYe/9Fe0s68CMF19FgfW/y/q6jD19Ch6x1BapVUOiSEShp6TpwbmQ6A0muvWJ1RY\n2F5F2S5LCoG+HYheY2ygaQps04CxhBAJPuY/Q4KQCH1HZRSmyo0rQohsLgZiTFSFYdoU51xhKA4c\nyN3ltCYkTe8iLkFpLEY7upDnOelx2O427wJD7/P3B4zVVJXFjPtDCqCyeiyVyk0skgZb5z1RfTcw\n7x1VbbGFzWWBY3MLo9Ty/UupD5HW+XED//6HI6UV1uplE48UEzH3dN/1uWVlKcq9t59/dFgaQszP\nc4gMLhBDQoVEXRqa8/zcn6iUUp6D1fll2acqDT35BROtFJW1VLLqI4QQQuyJBKTLKKWUw1HMQzb3\nqxudUgqMwYfIPCXYDmEp7xFQKZDCgCaijcZhGDBURYUdPzelRDcOVwWobElVTCBGYhiIwY2rSnme\nkY+BRRiwRcP65OBySOsTEUNeAVEK6vrMc9T7npgitamW9x+D4+Sx/83xL/8dfXsSUKxf/wIOrr2Q\nIh0YO7hNcgMCa1BFmVtjj899CJETGws6q2hs4nCl0SnlfTiLBe706TzrqSgIyuBC7uL36AGbWhuK\n4sxz5weHHwLGasxkgvOB2cIRU6KpLJP6AuWGSmEnOfgYwJSRduEYeo8tDI2t6ePApMjhzQ2eoQ/L\nvUm20JTlmWC0k1aK2hq242XeRA+xKuh7T9s6whCIPqKMxlj9qI5nCrO95JDv4JyrDlYrSqMvGHh2\nhyO7b2V1zoUcjhRMJgX6UUFhu/NhSong4zJMDUOgqu3y57pX28+xBdrO0/Zu2dRgMThsO7C2UlEV\n9qKaFgQfcS7gXFgu/SirCEblocfk46jMxQ8IFkIIIZ5KJCBdItstpS8kzOdEH/KqT31mBSSXtKXz\ndkd7IraHMuY9HfniM6VA9D1RebBgTI22FS7CwnkWPrKiNUMY6FxHJKHHY+p8T+8HKlNSFxMgB6UU\nPUkpupSwxYSVcnomvDhHdH4MJnt/1bxrHSSoJ8Wy1CmmSCXsii0AACAASURBVOt7NIq6qOgWJzh5\n7HOcePDT+GGG0pbDT/92jj7r5RRmFb+5SRw8dnWKrqpxoO3u53fwgUc2W5yPrKxMuH61ygNsx3lO\nFAUolbvsLTq6NqAKw8r6lFxcp8ayxjC+xbzPK0RSyC2V7XRK7yPz1uUg0BTU5eP7Z2eMZjotadtc\n2qeCYrVZIfjIfBjyvjIFRWkoS3NWALgQpXLgMSiKScmksnSty6tQCUIf8zY2o1BGo/S42DJegOf7\nGO9rvM8EyxUUrXJQKo3OJVwxdzXrXGAx5HK3xhgGN9Cn3FxCq0s3p8e7QLfInQ+baXnO50aNZXag\n8l6ywjAMOSB1C8dgfF5V20NXvRi2Q0tc7veblgUHCk3SikXnWHSeUxsdZW2pK/u4mjvEmOj7fGwx\nRnKDOIWxCowmjHdRGk1tL92AXSGEEOKpRALSRYopsXABHyNGa4qxTv/Rr4b7RUvoB3RhMdMzZVHB\nD8TQjQErl7VpbXaUuD1+CxcYtlslFxZDHEvj8gBVbQqMqZb3XxoI0TAbOmbDjNrmnQmNraltLt/r\nw5BXlEJ+q0xJbSuMbdga5qANE1tjkxq78w3LDnmBcY/Heebt7LRdImaLvHqxHTxb1+GGTdzX/5Ov\nHv8XFpsPjI+lYv0ZL+PA026jrFbzQMrTmyilKQ9fRzAGFxNhCPjoiDERQh606kIgpsRqU3J49Uxg\n3Z7npOqacn0d3w+0pxdgIqWB2LYMbYsy+pxdAPNjzatUXVS0vcsDMiclxTlWdfZCacVkWuaVjd6z\nmA/jDblDWVHaSxIotNFMVipiTHgX8GPZIAEIEaVymZ4e29HvvP5evq8Ugwv0IdC5yGwsZTMq/9tI\nJHq/3crbAunMOaIUMSba+cBkenEtqb0PtK0DlbsGmj0GR6UVVV1QlHa536ydO4wNlJWB5Zyt7dWn\ndObjMRSpMbAWhdm1kleXltXas7UYcENgHhJVbeh8LmPsIszGZgrbq3MpJpwPuCESQt5fpFD530hp\ncsngeP9W52C0X6txQgghxFOBBKSL4GNi4fzyVe8QI/l6OV/8Wa2wgPa5fbIyOndYU4qUIsG1xOjH\nYaY2r/CEQBx7LCilUDrvB8rSjpKm7ffTsrwmpcjcR3xMGAVNYUhO4dLYmlfbczZN8DHgY0vve3yM\nVKZhvZksV48AaltR24rBD7S+ow8DfRgwSuODx/qE7ntcWORj12psa13k9uTDcGbejlbocaCsLoq8\nYhMCwXkWWx0pBMrGMLSJGDo25l/i5COfp9v48ng0mubgc1k98iLWj7wAbSpiSsQYGbY2IUaYNGzO\nHSH052w6sT1A9lBTcWBy/r1SKSa6IWHqmunBFazJbb3j4EgxoAs7drcb37TO85VSYt46+sFjtGZ1\nUuz5Av1CqtpijFqW2+21ocDjpbWirCxldab0zG+/uQu3ht9WkAORSwmvEpFEULmDXFOUrJQWa/Xy\nZ7Gt7xxDn8NNM3li+3WCz2WJAM2kOGe54WPRWtFM8t6xvstNL1p/nseuxtLIIrdR335c51KUlnVr\n6BYDzkdCH9GVIZBnB/kYc5D3eV9bHEO4AsoiN/UoSo1WetlcQSmFVkgTBSGEEOISkIC0BynGPKBV\n6+UFcO68FYCU93RYQ0wJHxODcwxtT+8c0ft8YWM0K2uruZNZGAg+rxppU2BsvSyvSzGMneR8fj/k\nzmnns30RFhPMXSCkvP9juuMC7XzzhwAWrl3uM1qrKkKyKKVxEapzLGCVtqS0JUNwtP2CfmsT4yN1\nNQUV0WWR5zLtKKnTZQmTyRgschvp0PWErh/DYg4wi4UjhIi1Pae+9l9snv4PZhtfWnblq9e+kZUj\nL2J6+AU09RpNcaaEKKWE29ikLiyDKegwFCpSlxZrcoMBo/X4pjBmPLYLXHynlGgXuYQtb9rP/1yM\nMbtKJB9tZ6c6azSrk0tTLrbNFibPMrpM8oX/me8ZQ1zOzwHYkdHZHqiTw31eETpTJpmbF4SYdv3s\nHq2qi3EFKweTunl8e/WCjywWeYWtaYo9lcZdiDGaybTE+0Dw6UzXux0d8B5viNM6lxGaPu8fY4i5\n/XqMlD6vchbkvYSmtMvn/1KeR0IIIYQ4NwlIjyF0HaFtd80P6kJiUAqtDdPKUmqILhKHAZyjCJEC\n8CRiVeK0IRUFsxAp/RZWxfGis0E/qtOb0mbcw7PduS2SziwpjU15GeuZ8oWZj4neeXSRqI1hsseL\n5851dL7HKM2kaChMQYiJmfO0LmAu8Iq0TYpmSBSqxE7znqpz7fPZSRdFLq+bTnNY6gei92ijmc+/\nzsbG/8di6wu0Ww+wfcldT49Srj6bcvpcpis3YFdXaaryrI5cfmtG8D4PXDUGlRIrZUFdmSd8geyG\ntCz3q+q9/VMJMbE1HwgxXrBT3bXs8exx2vV1Y/OCvaibgkXMZWhKqb0//yHSLgZIeeXoUgZJaw17\nnJW8J/lx5dWtbpFXzYLL55wxSkKREEIIcYVIQDqP6BxhsSD6fIFmmoaYEu3g6IPHxEijEqoPuL5f\nfl1uvV2iioJyR2Bo+555P2dIicoWrDRT9B72GCUUQ9LkfHampG58b9mFbOdK1l4MfmDuWoJL1LbB\nbK+OaMXEGubOM3eB1fLs1s5xGPCzOSklqpVVTNPs6XsuH1NK+LCgbY8xO/0VTj9yP9384fFWxcr6\ns1g/8nyqAzdx0mmGGJkqi02Rul1gjQJTLe9r2Jwx35rTDolUTzDBM6kK0lgSpZQbLzY15gIdvVJM\n+JAHwObSpoSxes8rGD5EtsY23o/VqU5cmBqH587nA0Pv0UZdsJtcSgk35DbnKUHd2Mu6ynYxrDVM\nVzTD4LGlYrpaSSgSQgghriAJSI+SYiQsWsIYekxVYiYTIorOeZKxTKaaSWFQ496ZFPJwVV2MQ0fH\nsrHcNW4gRo9JgZXCMFAQlWXuIo1V5xwgmR41dPL8comPVtBYu+dhlD54NhYzhj4wsROCTyxmfW5p\nXOb7aZKh9YH54Fkp7TJUhK7Dzxd5oObqSi6fu4AYBtrZcdqtr9LOvspi/DO4xZlHoSzT9Zs4eMML\nWD/yPFTR0LuBB0/NaN1ApQpiVdJGT7/ZYWcdtq7RzQS/6Jid3sAnhV5ZYVoaJnVu5ay1WjYbcEMY\nVyNY7hEx4zyc4MdQtGMWznZnsL3OrHE+MlsMxJSY1AVNJf+0LpbSismkYDEf6Nrc6OLRe4mWwWgI\npJjL3+rmTDnktWK7MYQ9q626EEIIIS63a+sqYp/tLKfbnp+jiwIfI7PBA4nKGJrtV6bHjfnbYvRn\nWl+nsKs5gNaWomiolV624J47TxkNzbhfKIyhaBiHvAIYnVsAG3Vm4j2c2Zj9eA3OcXJjAxcCq+WE\nSVOhFPS9p2s9zkXqpqCyhjDuGVm4wKQwhMUi7xvSCru6ij5PvVGKgY0T/87JY/ey8bX/s9xDtH3k\nZXOI6fo3Ua/cgKmPoMqnYcqSotbMU2SYb/Lw1xd0fWC1LjncNKSocFETTU2cz2G2QVG1eY+X0awe\nOsiBtebcqwxNsZwZ431chqVH2y5rMjavNBWl3lMDhN4F5m3eJ7YyKamukZWLa4E2mnpS0M4d7SJ3\nttsu8XODp+/Dss15WRnK0u5L0wohhBBCPHVIQAKi98sZRUqpHIyqCqXUso03JCaFpTzHKk3wPfFR\n3dK29xIpbcdOdGcu2nIbXs3CefphoJ/nGTlRKZS1aGOojMnB6BJd7KWYaLuBU7NNQoqsNVPWVqbL\nV6ttYZYtjeeznqqyNKUhJhhCwG3NaAgoYylWV3YFw23t7Dgnj93LyWOfww9bABST66kPPJNq5Qjl\n9AjF5PrlvqvgI13rSSlhdcJ1AecTm20AX3D9dMqNh1bQOnfr0jrvt/J+Sj9b4NoWVZasXHeQ6fT8\nTROAHHrG1YfckS2HJa3HvR5mb2Ho0breM+/yz291UlBcZEMAcTZrDXWT6FpPu3CUlTkzGHdsp11V\nEoyEEEIIcWk8pQNSSonQtoS2A8ZyuqbZdfHfujwrp7bmPOGoI/jcjU2bEq0tSpsLDn1NIaCGgbrv\naXvHMM42sVpTGE1hTV6dsZZo7bJ99IUex46GYjtvAMD7SN85toYFSSXWV1dYa6YAdIsTDO1pynqN\nsjqALQr61tF3Hu8CdaEIszmDG0hVxdrYiW+bdy2njv8zJx/6LPON/87Po21Y+4Zvob7uBShzPYUp\nUKg8ZLTLe3VCzpwYVVAVliJZhpSIyWO1Zu1AwQ3XTc8KiBagsqxMK1w3AaUoqguX+T3adliqHtdX\nnW3ROdreo5VidVpiL0Ebb3FuRWmJMc/J6lo//p2hrC7N/CchhBBCiG1P2YAUncPPFzmsGI2uG0y5\nezBl7wMuxuXwxUcLriWEAaUMtpycMxQtZ6iEiAoeFRyEgDFq3IheM9luiR0iKXiS98Qhz9rZtr0X\nalc48blUbC9zaRauxZSwUjWY7iQPPfj/js0Rju/6PGNriuoAxq6i9RSjJ2ijCQyE1PPwlxYk3xLc\nHD/MiXH7GBUrh57L9OjN1IeeC9GQnKaxFUorXO9xfcgzj5JGj4MurTUUhcYpUFZjNKwVlrVJ+Zir\nZ0V9sRHniZvtnHE0fexjFRcvd7LLA1klGAkhhBBivzzlAtLOJgwhRJIt8UERTm6hlEaXFlsWJGNo\nQ8AYTVOcHXy8a4kXCEcpJvre07c9sRtI3hHHhgu6sGhlMVWFNQajNMooTHGmzGu7+UP0geQGwtgS\n20wmhKRxw1hiBGijzrpY3FnSt3AzhvaLdF/9T46f/A/cWP6mdMGB659Hs/oN+H6LoTvN0J5m6DaI\nYXdw2nXfuqQop9TTI9hyymT9WTTXPx+KCQAlBdErQsoXsykkjDWYsTlCsaN1cUiJPiZUjKgIBVBY\nQ11evaVq2+FoP2YciQurpDOgEEIIIfbZUyogxWGg29jCD4GIQjUNcfDEvsuDQ2MgzAfcLLHwE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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "N = 10\n", "\n", "assets = np.zeros((N, 100))\n", "returns = np.zeros((N, 100))\n", "\n", "for i in range(N):\n", " R_i = np.random.normal(1.01, 0.03, 100)\n", " returns[i] = R_i\n", " assets[i] = np.cumprod(R_i)\n", " \n", " plt.plot(assets[i], alpha=0.1)\n", "\n", "R_P = np.mean(returns, axis=0)\n", "P = np.mean(assets, axis=0)\n", "plt.plot(P)\n", "plt.xlabel('Time')\n", "plt.ylabel('Price');\n", "\n", "print 'Asset Volatilities'\n", "print [np.std(R) for R in returns]\n", "print 'Mean Asset Volatility'\n", "print np.mean([np.std(R) for R in returns])\n", "print 'Portfolio Volatility'\n", "print np.std(R_P)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we see the benefits of diversification. Holding more uncorrelated assets smooths out our portfolio. When one is down, the others are no more likely to be down, so the bumps both upwards and downwards are often much smaller. The more assets we hold, the more we'll reduce our volatility as well. Let's check that." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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K8uARP6nxXlP7i9noBwAAAAQap52pAQMG6NZbb9WoUaMkSTk5OcrIyPB6YZ5m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\noyYpaSyj0cjRM/n8EZvKrv1nKa2ovmAfexstfl72+Hk54OdVEz63x50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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "portfolio_volatilities_by_size = np.zeros((100,1))\n", "\n", "for N in range(1,100):\n", "\n", " assets = np.zeros((N, 100))\n", " returns = np.zeros((N, 100))\n", "\n", " for i in range(N):\n", " R_i = np.random.normal(1.01, 0.03, 100)\n", " returns[i] = R_i\n", "\n", " R_P = np.mean(returns, axis=0)\n", "\n", " portfolio_volatilities_by_size[N] = np.std(R_P)\n", " \n", "plt.plot(portfolio_volatilities_by_size)\n", "plt.xlabel('Uncorrelated Portfolio Size')\n", "plt.ylabel('Uncorrelated Portfolio Volatility');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##Final Point\n", "\n", "Be invested in as many uncorrelated assets as possible. In finance this is known as diversification. If you have a pricing model, price everything and invest accordingly. This concept is explained in the Long-Short Equity Lecture.\n", "\n", "###Capital Constraints\n", "\n", "Because of transaction costs, you need to have certain minimum amounts of capital to invest in large numbers of assets. Therefore sometimes you are unable to invest in hundreds or thousands. In this case you should still try to maximize your portfolio size, keeping in mind that if you have a portfolio of size 20, you can still find 20 relatively uncorrelated assets and that's better than nothing." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##Now Let's Explain with Math Rather Than Pictures\n", "\n", "One of the key aspects of modern portfolio theory is that by combining multiple assets into a portfolio, you can reduce the entire package's overall risk. Since we represent the volatility of an asset by its standard deviation, we can easily show this mathematically.\n", "\n", "Say that we have two assets in a portfolio, $S_1$ and $S_2$, with weights $\\omega_1$ and $\\omega_2$ such that $\\omega_1 + \\omega_2 = 1$. Call the portfolio $P$ and say that $S_1$ and $S_2$ have mean and standard deviation $\\mu_1, \\sigma_1$ and $\\mu_2, \\sigma_2$ respectively. We can calculate the value of $P$ easily.\n", "\n", "$$ P = \\omega_1 S_1 + \\omega_2 S_2 $$\n", "\n", "Now we set $\\mu_P$ as the return of the portfolio $P$. It is simple to calculate the expected return of this portfolio:\n", "\n", "$$ E[\\mu_P] = E[\\omega_1 \\mu_1 + \\omega_2 \\mu_2] = \\omega_1 E[\\mu_1] + \\omega_2 E[\\mu_2] $$\n", "\n", "As you can see, the expected return of the overall portfolio can be directly determined using the expected returns of the assets *in* the portfolio as well as their associated weights. Similarly, we can use these same characteristics to determine the overall risk of the portfolio, $\\sigma_p$. First, we calculate the variance of the portfolio, $\\sigma_p^2 = VAR[P]$. Then we say that the correlation between $S_1$ and $S_2$ is $COR[S_1,S_2] = \\frac{COV[S_1,S_2]}{\\sigma_1\\sigma_2} = \\rho_{12}$. The calculations then follow:\n", "\n", "\\begin{eqnarray}\n", "\\sigma_p^2 &=& VAR[P] \\\\\n", " &=& VAR[\\omega_1 S_1 + \\omega_2 S_2] \\\\\n", " &=& VAR[\\omega_1 S_1] + VAR[\\omega_2 S_2] + COV[\\omega_1 S_1,\\omega_2 S_2] \\\\\n", " &=& \\omega_1^2 VAR[S_1] + \\omega_2^2 VAR[S_2] + 2\\omega_1\\omega_2 COV[S_1,S_2] \\\\\n", " &=& \\omega_1^2 \\sigma_1^2 + \\omega_2^2 \\sigma_2^2 + 2\\rho_{12}\\omega_1\\omega_2\\sigma_1\\sigma_2\n", "\\end{eqnarray}" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [], "source": [ "stocks = np.array([100, 75])\n", "mean_returns = np.array([4, 6])\n", "\n", "r_12 = 0.20\n", "cov_12 = r_12 * 0.05 * 0.08\n", "covariance_matrix = np.array([[0.05**2,cov_12],[cov_12,0.08**2]])\n", "\n", "weights = np.array([0.7, 0.3])\n", "\n", "P = np.dot(weights, stocks.T)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we will calculate the overall risk of the portfolio:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The overall risk of the portfolio is: 0.0462276973253\n" ] } ], "source": [ "var_p = np.dot(np.dot(weights, covariance_matrix), weights.T)\n", "sigma_p = np.sqrt(var_p)\n", "print \"The overall risk of the portfolio is: \", sigma_p" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "By combining assets into a portfolio, we were able to create a package with lower overall risk than either of the individual assets. If we include even more assets in the portfolio we can further reduce the risk of exposure to any individual asset." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##Benefits Of Additional Bets\n", "\n", "We can extend this idea to a portfolio made of of $n$ securities fairly easily. The more assets you include in your portfolio, the lower your overall risk will be. Here is the general form for the variance of your portfolio in the case where you have $n$ assets:\n", "\n", "$$ \\sigma_p^2 = \\sum_i \\omega_i^2 \\sigma_i^2 + \\sum_i\\sum_{j\\neq i} \\omega_i\\omega_j\\sigma_i\\sigma_j\\rho_{ij}, \\ i, j \\in \\lbrace 1,\\ldots, n\\rbrace $$\n", "\n", "These benefits can be increased by ensuring that your assets are independent from each other. When two assets are independent, they are uncorrelated, i.e. $\\rho_{ij}=0$. The correlation between each pairwise set of assets plays a very important part in our calcuations for determining the variance of a portfolio. The higher the correlations between assets, the more assets we need to include to reduce our risk by a comparable amount." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [], "source": [ "stocks = np.array([230, 176, 192, 105])\n", "mean_returns = np.array([2.0, 3.5, 7.5, 5.0])\n", "std_dev = np.array([0.05, 0.07, 0.11, 0.09])\n", "weights = np.array([0.35, 0.30, 0.15, 0.20])\n", "\n", "\n", "r_12 = 0.2\n", "r_13 = 0.08\n", "r_14 = 0.1\n", "r_23 = 0.6\n", "r_24 = 0.4\n", "r_34 = 0.8\n", "covariance_matrix = np.array([[0.05**2, r_12 * 0.05 * 0.07, r_13 * 0.05 * 0.11, r_14 * 0.05 * 0.09],\n", " [r_12 * 0.05 * 0.07, 0.07**2, r_23 * 0.07 * 0.11, r_24 * 0.07 * 0.09],\n", " [r_13 * 0.05 * 0.11, r_23 * 0.07 * 0.11, 0.11**2, r_34 * 0.11 * 0.09],\n", " [r_14 * 0.05 * 0.09, r_24 * 0.07 * 0.09, r_34 * 0.11 * 0.09, 0.09**2]])\n" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The overall risk of the portfolio is: 0.052849787133\n" ] } ], "source": [ "var_p = np.dot(np.dot(weights, covariance_matrix), weights.T)\n", "sigma_p = np.sqrt(var_p)\n", "print \"The overall risk of the portfolio is: \", sigma_p" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's assume that the correlations between all of these assets are $0$, that they are all pairwise independent. We will assume that everything else remains the same as before. Using our calcualtions for the portfolio's risk we get:" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The overall risk of the portfolio is: [ 0.03665379]\n" ] } ], "source": [ "covariance_matrix = np.array([[0.05**2, 0, 0, 0],\n", " [0, 0.07**2, 0, 0],\n", " [0, 0, 0.11**2, 0],\n", " [0, 0, 0, 0.09**2]])\n", "var_p = np.dot(np.dot(weights, covariance_matrix), weights.T).flatten()\n", "sigma_p = np.sqrt(var_p)\n", "print \"The overall risk of the portfolio is: \", sigma_p" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We were able to significantly reduce the overall risk of the portfolio simply by selecting for assets that were independent of each other. While you are still able to reduce your risk by adding assets that are correlated, you will need to add a greater number of assets in order to have the same effect as with uncorrelated assets.\n", "\n", "The following function will allow you to randomly generate a portfolio of arbitrary length:" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# Generate an almost entirely random portfolio\n", "# Only constraint is that an asset's variance\n", "def generate_portfolio(n = 5):\n", " assets = np.random.normal(100, 20, n)\n", " weights = np.random.uniform(0, 1, n)\n", " weights = weights/sum(weights)\n", " returns = np.random.normal(5, 2, n) # Say that 5 is the average return for our assets\n", " # Generate covariance matrix for assets\n", " cov_matrix = np.ndarray(shape = (n, n))\n", " std_dev = np.zeros(n)\n", " for i in range(n):\n", " for j in range(i + 1):\n", " if j == i:\n", " std_dev[i] = returns[i]/100\n", " cov_matrix[i][j] = std_dev[i]**2\n", " else:\n", " cov_matrix[i][j] = np.random.uniform(-1, 1)\n", " cov_matrix[j][i] = cov_matrix[i][j]\n", " # Ensures that the covariance matrix is symmetric\n", " # Serves the double purpose of squaring the volatility (already present in the matrix) so we get variance\n", " return weights, assets, returns, std_dev, cov_matrix" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can now use this function to randomly generate a set of assets, each with a different return, as well as a covariance matrix of the assets." ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "collapsed": false, "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Weights:\n", "[ 0.03771786 0.2617164 0.32334968 0.03268904 0.22775498 0.11677204]\n", "Assets:\n", "[ 115.37124584 101.36414593 95.20524606 100.33388728 86.71550432\n", " 155.74599695]\n", "Returns:\n", "[ 3.55723833 5.87428717 3.83180457 4.71999371 4.37647257 4.81654685]\n", "Volatilities:\n", "[ 0.03557238 0.05874287 0.03831805 0.04719994 0.04376473 0.04816547]\n", "\n", "Covariance Matrix:\n", "[[ 0.00126539 0.66993696 0.52734301 0.09290323 -0.3467869 -0.2007909 ]\n", " [ 0.66993696 0.00345072 0.82253812 0.45047425 -0.26179841 -0.59875253]\n", " [ 0.52734301 0.82253812 0.00146827 0.52685025 -0.28920058 0.0422018 ]\n", " [ 0.09290323 0.45047425 0.52685025 0.00222783 -0.3957568 -0.32035693]\n", " [-0.3467869 -0.26179841 -0.28920058 -0.3957568 0.00191535 0.70913521]\n", " [-0.2007909 -0.59875253 0.0422018 -0.32035693 0.70913521 0.00231991]]\n" ] } ], "source": [ "w, S, mu, sigma, cov = generate_portfolio(6)\n", "print \"Weights:\\n\", w\n", "print \"Assets:\\n\", S\n", "print \"Returns:\\n\", mu\n", "print \"Volatilities:\\n\", sigma\n", "print \"\\nCovariance Matrix:\\n\", cov" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And now we can easily perform the same calculations that we did before to determine overall portfolio value and risk." ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Portfolio Value: 102.881285796\n", "Portfolio Volatility: 0.31518681162\n" ] } ], "source": [ "P = np.dot(w, S)\n", "var_p = np.dot(np.dot(w, cov), w.T)\n", "sigma_p = np.sqrt(var_p)\n", "print \"Portfolio Value: \", P\n", "print \"Portfolio Volatility: \", sigma_p" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Keep in mind that if you choose to change this function at all, you must include some failsafe so that higher returns always correspond to higher volatilites. This is one of the core assumptions of portfolio theory and, while not pertinent here due to our arbitrary weight values, it is essential to calculating the weights of an optimal portfolio." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "*This presentation is for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation for any security; nor does it constitute an offer to provide investment advisory or other services by Quantopian, Inc. (\"Quantopian\"). Nothing contained herein constitutes investment advice or offers any opinion with respect to the suitability of any security, and any views expressed herein should not be taken as advice to buy, sell, or hold any security or as an endorsement of any security or company. In preparing the information contained herein, Quantopian, Inc. has not taken into account the investment needs, objectives, and financial circumstances of any particular investor. Any views expressed and data illustrated herein were prepared based upon information, believed to be reliable, available to Quantopian, Inc. at the time of publication. Quantopian makes no guarantees as to their accuracy or completeness. All information is subject to change and may quickly become unreliable for various reasons, including changes in market conditions or economic circumstances.*" ] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.12" } }, "nbformat": 4, "nbformat_minor": 0 }