9557 lines
639 KiB
Plaintext
9557 lines
639 KiB
Plaintext
{
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"metadata": {},
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"source": [
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"import pandas as pd\n",
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"import plotly.express as px\n",
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"from pathlib import Path\n",
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"import sys\n",
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"\n",
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"from docx import Document\n",
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"from docx.shared import Inches, Pt, RGBColor\n",
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"from docx.enum.text import WD_ALIGN_PARAGRAPH\n",
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"\n",
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"notebook_dir = Path().resolve() # Current working directory\n",
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"project_root = notebook_dir.parent.parent # Goes up to root/\n",
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"sys.path.insert(0, str(project_root / \"libs\"))\n",
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"\n",
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"from word_library import WordDocumentBuilder, PageConfig\n",
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"from pasbdc_data_cleaning import clean_center_name"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "cb1dce41-696a-42b7-a67f-aa020471f166",
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"metadata": {},
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"outputs": [],
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"source": [
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"nbs_df = pd.read_csv('merged_nbs_data.csv')\n",
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"mask = nbs_df['Milestone Date'].between('2024-10-01', '2025-09-30')\n",
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"nbs_df = nbs_df[mask]\n",
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"\n",
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"center_translation_table = {\n",
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" \"gannon\":\"Gannon\", \n",
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"\t\"upitt\":\"Pittsburg\",\n",
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"\t\"duquesne\":\"Duquesne\", \n",
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"\t\"psu\":\"Penn State\", \n",
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"\t\"bucknell\":\"Bucknell\", \n",
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"\t\"lehigh\":\"Lehigh\", \n",
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"\t\"kutztown\":\"Kutztown\", \n",
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"\t\"stfrancis\":\"St. Francis\", \n",
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"\t\"wilkes\":\"Wilkes\", \n",
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"\t\"temple\":\"Temple\", \n",
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"\t\"pennwest\":\"Clarion\", \n",
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"\t\"widener\":\"Widener\", \n",
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"\t\"scranton\":\"Scranton\", \n",
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"\t\"shippensburg\":\"Shippensburg\", \n",
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"\t\"stvincent\":\"St. Vincent\",\n",
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"}\n",
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"\n",
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"def fix_center(series):\n",
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" series['Center'] = center_translation_table[series['Center']]\n",
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" return series\n",
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"\n",
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"nbs_df = nbs_df.apply(fix_center, axis=1)\n",
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"\n",
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"nbs_df['Center'].value_counts()\n",
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"nbs_df.head()\n",
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"nbs_df.to_csv(\"cleaned_nbs_data.csv\")"
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]
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},
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"id": "f9a91967-7968-41ff-94ad-835a71291d4c",
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"text": "<b>NOTE:</b>Documentation levels were determined as follows.<br><br><b>Documented:</b>There is a non-blank, non-'Requested on eCenter' <br>attribution source with a value in the affirmation column. If the <br>attribution source is eCenter, then no value is required in the <br>affirmation column as this is a data entry automatically generated <br>by Neoserra.<br><br><b>Has documentation but not in correct spot:</b> There is a non-blank, <br>non-'Requested on eCenter' attribution source, but no value in the <br>affirmation column <br><br><b>Not Documented</b>:There is a non-blank, non-'Requested on eCenter' <br>attribution source with a value in the affirmation column. If the attribution <br>source is eCenter, then no value is required in the affirmation column.",
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Xkwtu8IKLWujXgr/OmyvjtrqudC5Vvj1JbejPl7bakI2MgteUxqNx63hbbeSSrzFpbP7fcfWlpGO5tFWIsgpIKCClwGi2d9Ck61d/Juic689SXT/pygSP6c88BYP1OEEFx4L57COAAAIIIJCbAKURQAABBBBAAAEEEIinAIGQIp1XfTtYSd/S3b5jZ7NetFCmBTMtxrsFcP9Wi+taZFcltxCrQIAWqPv06uG9B0TfstZnHVPgQou1Kqs67U1a0NTCZq7taOHOzUOPbNH8tUibLhiUa9v6dr0CBAoUuD7827tmTPbedaF2tTCob227fDkr6KFv07t5KRji8rXVN7+1ANmewI3OmR5tls2CpO4E0aOLclnw1NwKkXSnkgJnQUt3znS3iHMqRH/taUMvp29P/WzqahFb77FIlfV90MKyzqfyVc6XldXH9v5O6LrU9emS/zp3d6voGnL5wa2u86wGmqaQgq36c0p/vqTJbnZINjLS77yuo+A4tJ/LI7maNZ5mJ5c/gfgWOgAAEABJREFUQ9NUD+WhfIIgmoh+V/VndiH/HaB2SQgggAACCIRDgMd6hOM8MAoEEEAgpgJMCwEEEiVAIKRIp1sLg6OHn2r6JvTvnv9Ts17cAma2C4z6prEWzec/uNj0WW0r6fOixS/Y6jXrUsebdZTnjhY01b6rriCM+5xpe9/Cp5o9Ekv19fgeLaQWYjFbdwYomPHKqjWZhuAdV4DhhWWveZ/dDy0Ga0FZC9pa2H74t882eySWyrm7Ydqaq+apPlQnmNItSGrcwXLad99oz5SvMtmkXOvr3QZ6nJK+Qa6Akb8PnTNdU7pmlZTnrlV9DqZc+w7Wz2Zf50OPVVLgz18+m2sql/Ep0Ka7ZHS3jL8fd9eF8v3Hs/msa0XXhCsr30L+TijwqcXvYgWuXGBPf/a0ds1rnpqjjNIZKi/flOn6c8ez+TM0375LVU/XyIVXTjUFYhW0VfAsl771Z5r+bAv+uZ1LG5RFAIFkCzB7BMItwGM9wn1+GB0CCCCAAAIIIBAdAQIhRTxX+na0khYH/d1oAdo9OkvfAvbnaaFai2LauuP6ZrY+b922w3sslj4r6fg76+tNSZ91LN+kxTjdMaFH7ejlxmpH49SCuRbO3XhUTo+ecQvlKqf08so37NyLftIswKC7VZTX3rGpDRfMUN/BO0y073e84sc3m//ODo1dc9BcNKf3Nn5gZ3+/xj5d3FXzpgCLAi16v4B3IMOP7Q27TI8d0jmShSumzxqbzrUWu7XorTx9c11bZ6HPSnqMme5w8S/kapyjf1hrGofKZJMytZ+pblvz1Ptt/ONqbbE9174zjckd17fa5ej2dQ61OKyAovNUQESBEf/ifya3XMY38tsne+8I8b83Ru1qX/0p340r222xfydkomtN15yuPb+dPl/e9Hvgv8azHbe/3DUTRnsuuub1e+bP074ee6V56riMZHXxxGnNfreUp3OppM+5pEzXn36Pc/kzNJc+S1lW50nnTudQj9bTn3OZ+te5HH7plGZ/xqq+/txWHQVztSUhgAACCCCAAAIIIIBARgEyEEAAAQQSLEAgpIgnXwuVWsRN14UWvPRoIi3Q67n2LukdGPpWvhb6XD337WctMmoh2B3XZx3TY45Uxh1va6tn62th0/WprRY0Vc+9f0CflbQQqm+da1wqd8rwq2zc984xBXiU71KwnMoueKjOHvxlrfc+A1euPVs9WkffmNbCodp3qab2TnPBG32LvbbmEtMjuVy+xj78rGpTffWvb1zrEVZ+A7XR1kKkq6sxKBAkM9eHPusb2f7Hmql8uvFoAVnnV+8y8Z9/BUFumDLee/Gx6maTMrWfrq4WTfWoNgU6FIhJV0bjUsBI41IgQNewXsasb5xrjpqvCzrl0ne6voLH9M6bU5quL/WhNOuehy14TtKNJ5NbLuNTu3rslOau60X9a6t9HVd+cLxt7ef2O5HfYx80R/3Oaizu/Gjs+tylslO7f/c0b81f13zw9077Ou5+r1xZvfPG/7ul8ejPAgXZNM5cktrMdP3l8mdoLn2WsqzuQFIQJN2fyXI7Ydj4VFBJf9537dzJdF0qT0nn2Zr++fXsn5t+d5s+8n8EshCgCAIIIIAAAggggAACCCCAAALJE0heIKQI51gLcnoGvrbB5nVMeXpnRXChSvs6rnx/0kK9vx1XTguSWhh0efqsY2pDZdzx1rZq29+X/7PaUpv++trXcVdOC/3HD/qy6ZhbAFX5YDmVD45Lfau+Fm9VR0ltBMvpeLqyOu481b5LwTbTlVF7qu+S+nX1tQ224cql26ZrX22ozWzKq77K6Zxp7qqrpM9Hfamvaesfr9rVMZVXvWBSe6rvkvaDZbTvzlFrbalcsD/1qzqufeWrnJL6cse11b6Oq4zqqK72/Ulz83urjMo+Nu/fTcfVjpI++68V14YrrzJKqpvOTeU1HpVxSfuuvsaoMv6kY66sttr352eq62z1e6HPqqOt9tWOSxqr2lB+89T8sQ8qo7LB/pvX2bOXrh/1568rR3nKfk+t3H7KTW0Gk44HW1IfwXKai+akstpq3z8+HXfzkJk+65iSK+/a9NcL5rkyGoPqKumz5i4D7WeTXLv+vtqql08/GpPG5sYd3CpPZdS3TGQTLKNjylMZEgIIIIAAAggggEBAgF0EEEAAgZwE8vuaZk5dUBiBsgkQCCkbPR0jgAACCCBQfAF6iIoA/8kRlTPFOBFAAAEEEEAAAQQQiKtA869pxnWW8Z0XM2tdgEBI6z7kIoAAAggggAACJRDgPzlKgEwXCCAQfwFmiAACCCCAAAIIIIBAWgECIWlZOIgAAghEVYBxI4AAAggggAACCCCAAAIIIIBA/AWYIQII5CJAICQXLcoigAACCCCAAAIIIIBAeAQYCQIIIIAAAggggAACCCCQhQCBkCyQKIJAmAUYGwIIIIAAAggggAACCCCAAAIIxF+AGSKAAAII5C9AICR/O2oigAACCCCAAAIIlFaA3hBAAAEEEEAAAQQQQAABBBDIWYBASM5k5a5A/wgggAACCCCAAAIIIIAAAgggEH8BZogAAggggAAChRIgEFIoSdpBAAEEEEAAgcIL0CICCCCAAAIIIIAAAggggAACCMRfoMgzJBBSZGCaRwABBBBAAAEEEEAAAQQQQCAbAcoggAACCCCAAAIIFEeAQEhxXGkVAQQQQCA/AWohgAACCCCAAAIIIIAAAggggED8BZghAiUVIBBSUm46S6pAY5gmHqrBhAmGsSCAAAIIIIAAAqUWoL9CCfBX3EJJ0g4CCCCAAAIIIBBPAQIh8TyvzCpkAhVhGk+oBmNmYbJhLAgggAACCCCAAAKRFOCvuJE8bQwaAQSSJsB8EUAAgTIKEAgpIz5dI4AAAggggAACCCRLgNkigAACCCCAAAIIIIAAAgiUXoBASOnNk94j80cAAQQQQAABBBBAAAEEEEAgeQLJe4Zb8s4xM0YAAQQQCK0AgZDQnhoGhgACCCCAAALRF2AGCCCAAAIIIIDApwI8w+1TCDYIIIBAuQWITJf7DJSj/+IHQsoxK/pEAAEEEEAAAQQQQAABBBBAAIHSCtAbAggggAACkRAgMh2J01TgQRIIKTAozSGAAAIIJFuA2SOAAAIIIIAAAggggAACCCCAQPwFmGG0BAiEROt8MVoEEEAAAQQQQAABBBBAICwCjAMBBBBAAAEEEEAAgUgIEAiJxGlikAggEF4BRoYAAggggAACCCCAAAIIIIAAAvEXYIYIIBBlAQIhUT57jB0BBBBAAAEEEEAAgVIK0BcCCCCAAAIIIIAAAgggEEEBAiERPGkMubwC9I4AAggggAACCCCAAAIIIIAAAvEXYIYIIIAAAvERIBASn3PJTBBAAAEEEEAAgUIL0B4CCCCAAAIIFESgsSCt0AgCCCCAAAII5CdAIKRNNwoggAACCCCAAAIIIIAAAggggED8BYo5w4piNk7bCCCAQEgECPqG5EQwjDQCBELSoHAIAQQQQACBxAowcQQQQAABBBBAAAEEEEAAAQTyEiDomxdbuSolrF8CIQk74UwXAQQQQAABBBBAAAEEEEBgjwA/EUAAAQQQQAABBJIhQCAkGeeZWSKAAAKZBDiOAAIIIIAAAggggAACCCCAAALxF2CGCCRagEBIAk8/T+tL4ElnyggggAACCCCAAAJmBgICCCCAAAIIIIAAAggkUYBASALPOk/rS+BJ90+ZzwgggAACCCAQEOBrIgEQdhFAAAEEEEAgDgLMAQEEEEAgJUAgJEXBBwQQQAABBBBAAIG4CWQ3H74mkp0TpRBAAAEEEEAAAQQQQACBaAoQCGnneVu/eaeFPDE+zhHXANcA1wDXANcA1wDXANcA1wDXANcA1wDXQMSugTyWK6iCQNkEuL+2bPR0jAACWQoQCMkSimIIIIAAAgggEAUBxogAAggggAACCCCAAAKlFuD+2lKL0x8CCJjlZkAgJDcvSiOAAAIIIIAAAggggAACCCAQDgFGgQACCCCAAAIIIJCVAIGQrJgohAACCCAQVgHGhQACCCCAAAIIIIAAAggggAAC8Rdghgi0R4BASHv0qIsAAggggAACCCAQKgGeTx2q08FgCi9AiwgggAACCCCAAAIIIJCHQKICIbPnPWI1193ZjKlh5y678MqpNqB6TCotfmZZszKq5/JVVnWaFWAHAQRKKEBXCCCAAAIIZBbg+dSZbchBAAEEEEAAAQSiJcBoEUAAgcIJJCIQosCGAhk3zJzfQm5Hwy7rVXWQvfjo7baibo7dWnuF1dTeaStWrfXKqu6Ch+qs7v4bvXyVvfbGuV4ePxBAAAEEEEAAAQQQKKoAjSOAAAIIIIAAAggggAACCLRbIBGBkCGDB3lBjKvGjmgB1rN7N6u9+hKr7NTRy/vKEf3sgP27WP3mD7z9J55+yYafVW0qpwNDTzrWli5fbRs3b9EuqQQCdFFcAR4hUlxfWkcAAQQQQAABBBBAAAEEEMhOgFLREdAXh0+/YBLrY9E5ZYwUgcQLJCIQkstZrt+0xRobG62q+4GmR2BtqH+/WXUdV77KKaNDhRkJgyhfA3tVGNdwhWFQYRhUGAYVhkGFlduA/isMgwrDoMIwqDAMKgyDCsOgwhJroDWHYiY9OlxPz/CnE4aNTz0hwxLyjx6Hns9j0NPV05dmFRxQXjH5tF6lMescFrMf2kYAAQTiJBDCQEj5ePUvkum332cjzh5iA47omxrI4Ycdkvoc/NCzW0cjYcA1wDUQvAaqDuxkJAy4BrgGuAa4BrgGuAayuQaCf49gvyP/jZWY/87kXLf2+x5cfyjG/tcHHZl6VLgeF15bc4mNGDvFWGDPT1tPE1l07zS7aOSZ+TVALQQQQACBogl0KFrLEWtYQZDLam7y3hcS/BfWX958N+Ns3vtgl5Ew4BrgGgheAxve32kkDLK6BrhW+F3hGuAa4BpI/DUQ/HsE+/zdkmuAa0DXQMaFiCJmDBk8yObPnGKLlywz/10NWjPRHQju7hHd9aC7H/xD0btWdUdJsEy6Ryip7Gkj/zV194krc9/Cp8zVV1sqp3G4Y+n69eernNpy49Jn1dFW7SlfSfsqo63eJ/v8slftuDPGeX2rPeUpGKSyLqkdN+dM9ZSvcspXG0qag79vtavjSs5Vfeq460vWylOZ9iR/mxqDxqL2ND6NU+PVvksqr+T2VV713Lj8ea4MWwQQyEGAomUVIBDSxK9/ubggiN4X0nTI+7/eG9Kr6iDvs/uhd4dUVFRYVY9u7hBbBBBAAAEEEEAAAQQQQACBLAQoggAC4RfQEzKGnDjIlryw3HtkuH/NRHeNKA0/q9pG/7A29X4ILZhfPHGa6Y4S5Sv90/mnm3useDazfnt9vb288g1TXSWNQXenvLF2XerYMQP724w7FqSaUwBB43zx0du9Mgri1NTeaVrod4XU7twFj9uTC27wylw1doRNvXWeN3YFfrTvvzPGfTm2S+dOXlBIY2kQLlMAABAASURBVFFS35OvnemZtFbP9att0EXj1CPYgwEFBWOGnnSsN766+2+09e9ttnkPPKUm8k6uD41dSedG50hj+soR/bx2X1m1xtvqh4IiS5evNo1D+yp31ZT/tFnTJ3njyjR2lSUhgAACURBIfCDE/Qv9xOMHmj8I4k6e/gWw4KE671+QOvbE0y+Z/uWn2x21T0IAAQRyFKA4AggggAACCCCAAAIIIBBqgS/07eMtxu9o2GVr3tpg6zZsslHnDk2N+exTB3uf3UL6Pb9+whS4UIDAy2j6cf45Jzd77HjToVb///neVXblpcNTZbQek+6YFuu1aK+0aPELNnHc+aYvsqqiC+Jo7Ub7Smpj6jVjU2W+ccxR3rth2wrS1Fz+3Wbj1/y37dhpMlG72aTnlq60I/sfZgq0qLzGOXr4qebmoGNKCsY4O603ad1JASDl5ZMUxFi9Zl0zT41BY9GYXB8KEGldTH3oXPY+uHtqrDqn/kfHZxq76pIyCpCBAAIhEkhEIETfBNBtfIqwL3xsiemzjuk86F/or65+05Sn4y65yLn+RaRvOlSfN8Grp8j9NRNGqyoJAQQQQAABBBBAAAEEWhUgEwEEEEAg6gJ6MkafXj2s36G9UlNxC+l6lLgW0rVWosBFqkAJPiiQ8c76eu+dJm4tR1ut+xSie81Lj6hSm0q6O0X9qd9s21cwQ1+8VRDB1dHdGF27VOZ0t4yrm+1W52zl62vNrWVp/Hr0lx4B5tpQYEcBLq2Laa4Kirixal/nNLhWpqepuPpsEUAAgagJJCIQomCGbgP0Jx3TydK3BZ59+DbvNj9/vv/uEN0W6fLumjE59S0C1Sch0KYABRBAAAEEEEAAAQQQQAABBBCIkIAW8HV3QOfKjuEddYXZ/l07N3t8lVu78a/p5DMB3VFxyvCrvPfIujb12C3112p7IcrUnTB6zJYbv9tqjUvDVGBLAS7dIaJgiIIiultGeS7pThVXz20X3TvNFAhzZdgigAACURFIRCAkKieDcSKAAAIIIIAAAlEXYPwIIIAAAgggEG0BBQEWL1lmeoST7mSo6n6g92gsLZa7memxVHq80+GHHeJ9WVTvV/U/jsqVK+a2qns3q6ioMN390J5+NIdgfbWpx0i19kSQdPWC7Xyhb5/Uu1Zcnh5BtW17Q1HfPVvVdM4aGxuttbtXdG51B4jesfLb3/3BFBRRcETjVJ7OqQJi2ichgAACcRAgEFL4s0iLCCCAAAIIIIAAAggggAACCCAQf4HYzVCPEdcjoPzv+9DiuBbJ9c4IN+EHH3/G+6jHPOmDHoulR1KpvvaV7lv4lCmookX5D7duNwUAdFyPXZp++322ddsO7eaddFeC3qVRU3un149rSGOYPe8Rt5vVVo9M9wd6VMl/LNOY/WVUJ5h0h4XKuEdSqR09gkrj1viD5Qu1787ZxJ/dZgpauXblIh+3r3e9rH9vs93xq4dSgS+X586p6rhjakuPktc83DG2CCCAQFQECIRE5UwxTgQQQAABBEIpwKAQQAABBBBAAAEEoiqgBXq9O0LvkFBSUEGPgPI/Wkp3B9xae4XpnREDqseY0oKH6mzuLTWpRyTp8eMqo3dIKF/pv+5b5N31oEeS19ZcYi7vlOFX2WnVx3mPtWqvm8Z58ahhzd4TojkoAJFt2xq7Aj8KAGncWvjXMX+76casMsF6wT4191nTJ5nGpLZlrTstNO5g2Xz2FXxSu/6kQIXOmR7troCL/z0hOm8ueKX+FIxRGT1Gy39ceZqfroVZ9zzsnXP1obZ0l4vaVxkSAggkTSDa8yUQEu3zx+gRQAABBBBAAAEEEEAAAQRKJUA/CMRIQIvx7r0Pbvvsw7eZFu+D09TCtxbWXbl074nQwrnL19Zfxp+nPs4/52R7bN6/p/pSvr+8+s/2mN55of5cUvtuDunaUJ6/b/Xlt1B7Oqatv83gmFUmWE+BBc1D/SpfSf1pTK4t1dFxJeeqvrTvksoouf3g1tVzbfq3/nr67M/T2DRGf3sqk+64ygTHrrbcWDXHTPVUl4QAAgiETYBASNjOCONBAIHwCFSEZyhhGgljQSA2AvyOx+ZUMhEEEEAAAQQQQMAv0Ojf4TMCCOQtQEUE4iRAICROZ5O5IIBAYQX423NhPWkNgbAJ8DsetjPCeBAIowBjQgABBBCIoADfd4ngSWPICCCAQJEFCIQUGZjmEYi+ADNAAAEEEEAAAQQQQAABBBBAAIH4CzBDBBBAIL4CBELie26ZGQIIIIAAAsZND1wECOQoQHEEEEAAAQQQQAABBBBAAIHYCRAIid0pbf+EaAEBBBBAID4CPBYgPueSmSCAAAIIIIAAAoUWoD0EEEAAAQQyCcTti5UEQjKdaY4jgAACCCCAQBIEmCMCCCCAAAIIIIAAAggggAACCAQE4vbFyg5mgRmyiwACCCCAAAIIIIAAAggggAACMRRgSggggAACCCCAQDIFuCMkmeedWSOAAALhFijm/ZfhnjmjQwABBBBAAAEEEEAgVAK7m/5u/sbmv9jqza9nmf5su1UpVLNgMAggkEgBJo2AT4BAiA+DjwgggEBUBF5Zu8ZmP/aIzVr0/2KZlqxcHpVTwTgRQAABBBAItQCDQwABBNor8MnfdttTb8+zX776b1mlx968y3Z+8lF7u6V+BoGNm7fY6RdMssXPLMtQgsMIIIAAAukECISkU+EYAgjESSCWc9m+a5f94le/tJ/efVcs07rNm6yx6X+xPHlMCgEEEEAAAQQQQACBiAn8dfcOa/hkS1Zp1yfb855dw85dduGVU21A9ZhmKU6L/itWrbXTRv6raZs3FBUzCXAcAQQQyChAICQjDRkIIIAAAggggAACCERNgPEigAACCCAQfYGrxo6wFXVzvDR/5hSrqb3TZs97JPoTYwYIIIAAAmUTIBBSNno6LpoADSOAAAIIIIAAAggggAACCCCAQCwEBhzR12ZNn2TzH1zc7C6KmuvutAGf3jmiz/7J6g4Sd1fJCcPGe/V0B4b/Tgx394nKWtM/CrQMv3SKKbm6ylPb/v2mot7/XX2Xp/peRtMP1bn8xzen7m5xY1Cd6bffZ++8u9FGjJ3i3fWiPpqqeI+6cm3p0VcbN2/RYS9p7GpD+dXnTbC319d7x/mBAAIIIJC9AIGQ7K0oiQACCCCAAAIIhE6AASGAAAIIIIAAAnEX6HdoL+vTq4c9t3SlN1UFHTbUv28vPnq7l/RZwQdlKrCgO0h0J4nuKlEQZUfDLmW1md5pCjBMmTjGuxNFd6VcVnOTDT3p2NT+3AWPm4IZSsrrVXWQl1d3/422aPELXsDFdfListds4rjzvfyLRw0zBUCUp2OfO6SnufENGTzIC4L4xzz8rGqbcccCFTcFRCb+7DZTG5qP+vp87yovjx8IIIAAAtkLxCEQkv1sKYkAAggggAACCCCAAAIIIIAAAlEVYNwJFajs1NEUdND0FYRY8sJyO/H4gabjSqOHn2pLl6/2ggZPPP2SDTlxkOlOEpXX9vhBX9bHNtOR/Q8zBV1U8PDDDjEFHL5yRD/tmvbXv7fZFFRZ89YGW7dhk406d6iX17N7N+vfr08qUKOD/jGoro5lSsExf+OYo2z1mnXefF5Ztcardvapg70tPxBAAAEE8hPokF81aiGAAAIIxE1g9Ckn29bf/Lc1PvZIs6RjyvPP9+ff+6599PBC++31tf7DfC6JAJ0ggAACCCCAAAIIIJAsAQU/dNeHf9b+4EJV9wOta5fKVPYX+vZJfS7Wh63bdqQebzWgeowtfGxJu7pSfbWjpMdmbdvekGqv98HdrXNlx9Q+HxBAICkCzLOQAgRCCqlJWwgggECEBeY++ZTt/51/tIrTzkylJ5f90d7euMmU56amIMjkEcNt3332cYfYIoAAAggggAACxRGgVQQQQKBJwN2BoTslmna9///lzXe9rX7Ub/7A/IGDN9au0+Gips/1rjI9pkqPq3LpopFn5t2nHsXl2tF20b3TTHeaqEF3J4o+kxBAAAEE8hMgEJKfG7UQQACBkgmUqyPdBXL04f3s/t//PjUEHfvBsP9l/+fh/2frNm0y/kEAAQQQQAABBBBAAAEEiimgF4VfPHGajTh7iPe4Kz0KS4/FWvBQnffoKN0tond3HDOwvxc40Ds9Fi9Zlnpfh94ZolTVo5tVVFSYgiYa7/PLXjUlfc416fFZXTt3Sr3HQ/U1zvsWPqWPrabgOFRYY551z8OpMevYzbPv9+bnHs3lHpGlLS9Ll1A8E7MKsUBjiMfG0LISIBCSFROFEEAAgeQJfH/ot6x+y4f2k7t/5U1eQZD/vGy8LXz2OXvw2ee9Y/xAAAEEEECgwAI0hwACCCCAgN0wc77pEVFKekxUbc0l5r/bQp8V+Kg+b4Idd8Y47/0htVdf4skNGTzILh41LPXYqpraO02PztLdFZMvG2mX1dzktf2bR39nXx90pFcn1x8Kxtxae4XpcV0Dqsd47SlY85UvH95mUxrH8LOqU+NQkEZj1hw1V9ee2lZZJf+4FfTRu0va7IgCCCBQWIGKwjZHa6UXIBBSenN6RKANAbIRKL+Agh7+u0FOPvpou+7CMTb/f35nF8+4qfwDZAQIIIAAAggggAACCCAQOwEFGO6aMdn0aCh/UqAgOFkFPlwZffbnK1Di8p59+DbvThLlqx13/OZfXG7qS8eUpzra1xi0r+P+x1MF91VO5V17/n40HiW1o6S6Kqs62ldfe+rNMeXpmLbumLbB+jqmpHY0LpVXPRICCCCAQHYCBEKyc6IUAgggkCiBH50/otndIH16dLf9KyvtotNPs8bHHrEnp11nfXr0sFMGfc1+e31tomyYLAIIFFiA5hBAAAEEEEAg1AIdKipsYI9T7PTP/yCrdFzP/2X77rVfqOfE4BBAAAEEkidAICQE55whIIAAAmES+Pn3vmuf79mj2btB5j75lO3/nX+0itPO9NIpk6723hHy5LI/2rd+VBOm4TMWBBBAAAEEEEAAAQRCKxDFge29V4Wd+LmT7ZR+38kq/f1hp9o+TXWiOFfGjAACCCAQXwECIfE9t8wMAQQQyEvgvL//e3t746bUu0HyaoRKCGQWIAcBBBBAAAEEEEAgYgJ7daiwXJLxDwIIIIAAAmahMih4IKQxVNNjMAgggAACuQjMuvIK+2LvQ5rdDZJLfcoigAACCCCAAAII+AX4jAACCCCAAALZCbCqnJ0TpfIVKHggpCLfkVAPAQQQQKDsAnoR+n7DzmnzbpCnXn7ZPjfqe9k9Fqvss2IACCCAAAIIIIAAAggggAACCCBQdIF2dcCqcrv4qNymQMEDIW32SAEEEEAAAQQQQAABBBBAIKYCTAsBBBBAAAEEEEAAAQTCJ0AgJHznhBEhEHUBxo8AAggggAACCCCAAAIIIIAAAvEXYIYIIIBAZAQIhETmVDFQBBBAAAEEEEAgXwFuM89Xru16lEAAAQQQQCDeArsbzXaoBp2gAAAQAElEQVRsWm07Nr6aVdq2cZXtVqV4szA7BBBAoOwCTX88l30MURoAgZAona2wjpVxIYAAAggggEDIBfgrcshPEMNDAAEEEEAgtAKf/G23dXhztnV85YfWMYu095pb7ZNPPgrtfDINbOPmLXb6BZNs8TPLMhVJ1PGa6+40pUJPesWqtXbayH81bQvddina0/Wh60TXSyn6ow8EWhPg626t6bTMIxDS0oQjCCCAAAIIIIBARgEyEEAAAQQQQACBpAnstXu77fXJ+9mlv23Nm6dh5y678MqpNnveI83a0L6OK79ZRlJ3GlufuIIMuQQbci3feu/Fy1XwQUEIBSOK0UtUHAo592KbZhprufrNNB6OJ0Mgn0BIMmSYJQIIIIAAAggggAACCCCAAALJFmD2CCAQRoESfA289upLTCmM0y/nmIYMHmSL7p1mPbt3K+cw6BsBBPIQIBCSBxpVEEAAAQSSJMBcEUAAAQQQQAABBBBAIEwCukNkQPUYc8l/h4C+1X/CsPGpvNYe7+QvW33eBHt7fX2zaaqu60Of/Znq0+WpP7Wl5L8TQ3ew6E4WlVVdtaF93dWguqr3wrLXvLtg3L7aUFklV195Spq3jiuprct/fHOLuqoz/fb77J13N9qIsVM8B/XvvoGvdpQ0DpVVSlde7SupLyWNS+NVXW21r+Ou3Ztm3W86rnzXtvIzpZm/etAbm8r7+9FnJVdPY3ftzbhjgXeOLqu5yavr93DlNS6dA41HbSv521M51dNxJdd2JgeV9yeNR+dP81bSZ/WV7dxdHfWtpLGo/eBx9aPjShq//1yrjpLGruNqR2VUVvW0r6SxqV0dV9JnHVOektrIxlR1VVZ1XFI/Oq5+NQaNRXly0DlQnpK/nsrIWcez7VdlS5voLc4CBELifHaZGwIIIIAAAggggAACCCCQiwBlEUAAgZALaCF1+46d9uKjt9uKujl21dgRNvXWeaZFXuVpUb+25hIvT2UO7nmQ6XhwWio/8We32cWjhnll6+6/0T7fuypVTAu4G+rf9/pRO/qsRV8V0CJwTe2dNn/mFK/urOmTbEfDLmW1mda/t9nm3lLj1Rty4iC7oimYMXHc+an9e379hNeGxqwF/15VB3l5Gt+ixS80e7fGi01BFFdX89DcVVnHPndIz9T4dBfDK6vW2OTLRqba0jjmPfCUVXbqaOnKqx2XnJVz1fbiidOajeXlFX+2Jxfc4HmpntrWNl3aum2HHX3UF1NjWbp8dVbvZrny0uHeObq19gqv7kUjz0zXvKn99za+75WRm799nbsFD9WZjuv6ka+c1VBbDiqTLmU7dzmO/mGtDT+r2hubrqsulR2963PytTNTx3Vd6frSWF1//nPt5v38slftO2d802tLd++ovOqpvuamfhRwUBuZ+s7GVIENXXvOTO3Xb/xAzXrJPzZ3Her61XjSWSsvm369xvmBQAEFCIQUEJOmEEAgHgLMAgEEEIicQEXkRsyAEUAAAQRCKcC/UEJ5WhI4qBtmzve+8T+g+vveVvuOQQv3V1x8nreAr2PfOOYoa2xstPpNW7xghBb4//Lmu8ryyvjLegc//aHAgD6efepgbZolLdQueWG5nXj8QK8N9Tl6+KmmBXUtKD/x9EumIMaAI/p69bQ9ftCXvc9t/ThmYP/UY5W+0LePHdn/MOt3aC+vmvYVcFH/a97aYOs2bLJR5w718vQopv79+thzS1d6+/rhH8Phhx2iQxnTkMGDTEkF1JbG8cbaddptMzmrrxzRzyv79UFHeuP2j0U+clJScMErmOHH/l07m86bst1YZKr9QiS179w6NwUaeh/cPdWs+tHc1a8Oqpyc5a39fFK2c3eO7pqT1fnnnGzqW2NwJrqedG41Vjce7eu429dW50FJn5VU3l9O7a1es84LEmbqW/XaSvWbP7B31td7v2Mqq3Fo3PqsFOxTc9GcNJ5CW6s/EgL5ChAIyVeOeggggAACCCCAQFgEGsMyEMYRQQGGjAACCPgE+BeKD4OPZRTQXR76RvuKul9633bXvn84+oa6HsGjR/Ho8U+6A0D5Wtye/tPxNuueh015SvpWuvLSJS2Qa6E8XZ6O+YMLVd0PtK5dKnXYSwpaeB+K+EPz0vw0D6WFjy1pV2+6o0XtKOXalt9KC/htBTtyGWgpLP3j8fdX1aObKXDizy/mZ7+jvx+NQWNxx/xjdMey2eq86vwq6drZtr0hVS1T36kCGT4ogKY7PdSe2j39gklecCVdcc1Bc3F5/nkE81wZtgiUSoBASKmk6SfEAgwNAQQQQAABBBBAAAEEEEAAAQSiIKAgiB7LpMczraib4z3+yb/wqm+rP/vwbV4ARY9Qco/N2jO35j9190hrj7Ryd5aolr4V719UzvZuCtXNN32ud5W5xxFprkrusUi5tqkgiO420eOY1M45p52YUxN+K92xorZyaqCVwqWw9Hfv7093Eing5M8v5me/o78fjUFjccf8Y3THstkqaKjz69Kie6el7kDK1Hc27eq6c23qLg/3yK1gXc1Bc3HH/fMI5rkybBEolQCBkFJJ0w8CZRbgu11lPgF0jwACCIRFgHEggAACCCCAAAIRF1DgQ3doaBoKULiFVz226ubZ9+twm8k95sk9Mkjbt9fXe/V0x4Mei6X3G6hNLfzPXfC4aQFYd50MPelYW7xkWeodGbrrREnfeK+oqLD6zXven6B3OCh5jeb4Q4/L6tq5k/kXnBUEum/hU222FByHq6C7ODQ3zccfyMhU3tVzVg8+/ox3SHN6dfWbqcdbeQfz/KE5/eFPr6ceAaY7CDQ2jVFJ7q5p3b2juxr8ASqXl+02eO70TpY+vXp4jydryyHbPjKVCzrq2tL1qnOtMWgsqisTXV8aq/azTSqvu6FU39VR++onU9/ZmOraVnJttrbVHP7uq18yBSQ1Hs3DjUd5mqfmm02/rfVDHgL5CCQyEJIPVDzq8LzXeJzH/GbB2c/PLd61CI/F+/wyOwQQQAABBBBAAAEE4iegBVYttLrH9Fx/y72pRxtpcfWPr/w59Vismto7TY/KUvAiKKFjky8baZfV3OSV14L753tXpYrpG/AKfFSfN8GOO2OcKYhQe/UlXn7wUUHqR4GZYJu/efR35n+Hg1c5yx8KWOiOFgUF9DgiJd0J85UvH95mCxrH8LOqU3PTIrbehaFFabVzyvCrvPeP2Kf/pCv/aZa3Ub4ctciu+prvrOmTvMVur0COPxS4cudP2x/98IJUWyO/fbLXmsw1zqMHfNHb1w+Z6H0cemeMxjF73iM6nFMKnjv5yllta55Bt5wab6Ow2vc76trqXNnJew/N1GvGeu+g0bxkojueNFbL4R+VVz3VVztKmp/6VcrUd1umurZ1ztWektq8ZsLo1Mj8j+Py52k8/kdqKc9Zy7utflMd8AGBAgkQCCkQZDSaYdEzGueJUSJQKgHCY6WSLnM/dI8AAggggAACCCCAQCQEtDh614zJpiCEf8Da13Hl67gCEu4xPY/N+3dTUoBE+Srn8vSILB1XnXRJC7WurOrpMUI65sr6+9Fnd1xbjcnV9fej+u74zb+43NSujqmO2lDSZyW1oXyNO92+jivftefvR+0oqZ6S+lBZ1dG+2nb1lCcH1dcxbWXmrx8srzwltaUUrK99HdcCezo3taf8YFI99a9xuKTxuXIav+ahPJW74uLzPEMdVxmVVZ5Suj7UvuamrcqrntpTPe0rqZ7qKylPZXRcyZ/nr6M8JR3TfDVvJX3WMeUpyUxt6HO6pHFpXupbyZV1bemYUrBNtetvT/WCY1e+6qm+S/56mfreU+e/vMfJqV2140/BesF+9Zg1118wT+1lytvT75yM/frHwOesBSjYigCBkFZwyEIAgbAJsHAftjPCeBBAAAEEEEAAgXAJMBoEECi0QIeKCtvV40zb0fdfskq7qv7RKvbar9DDoD0EECiqAOstReWl8VAIEAgJxWlgEAggkJ0AdzVl5UQhBBBAAAEEEEAAAQQQQKBAAnvvVWGdDzvDOn5hZFapc79htk9TnQJ1TzMIINCaQJnzdMeJUpmHQfcIZCVAICQrJgolXoDAeOIvAQAQQCA+AoRU43MumQkCEiAhgAACCBRfYK8OFZZLMv5BAAEEEEAgZAIEQkJ2QhhOSAXCvWoWUjSGhQACCIRTgNh2OM8Lo0IAAQQQQAABBBBoU4ACCCCAAAJ5ChAIyROOaggggAACCIRegBX/0J8iBpiPAHUQQAABBBBAAAEEEEAAAQQQyE2AQEhuXuEozSgQQAABBBDIRoC72bJRogwCCCCAAAIIIBBeAUaGAAIIIIAAAgURIBBSEEYaQQABBBBAAIFiCdAuAggggAACCCCAAAIIIIAAAgjEX6CYMyQQUkxd2kYAAQQQQAABBBBAAAEEEEAgewFKIhA6gd2NZi+9vsaefXV1Vun5196w3aoUupkwIAQQQACBJAsQCEny2WfuCCCAQCgFGBQCCCCAAAIIIIAAAgiEReCTv+226/7v/7VzfvrTrNKPf/lL2/7RX8MyfMaRh0DDzl124ZVTbfa8R/KoTRUEchGgLAKlEyAQUjprekIAAQQQQAABBBBAAAEEmguwhwACCERAYFtDg238cEtWacv27XnPyC3AD6geY4ufWZZqR5+1MK/81MEMH2quu9OUMmR7h7XArz78qa06XsWI/Ni4eYudfsGkZoYRGTrDRAABBIomQCCkaLQ0jAAC2QpQDgEEEEAAAQQQQAABBBBAAAEncM5pJ9rcBY9bNoEPVyfX7dcHHWkvPnq7raib42031L/v3QVRzD5zHWMcyzMnBBBAoFwCBELKJU+/CCCAAAIIIIAAAkkUYM4IIIAAAggg0IbA4OO+4pV4ftmr3jb4w93x4O7o0B0jKqPtwseWmJLysr2LpLJTR7u19go1YfMeeMrb6of/zpFgW8ExqKw7pnGovpLuNFGePms7/NIppqTxKamsyuizkvZV1iXV0XEl/xh0XPuX//hmU56SqzvjjgX29vp6u6zmJi9PZdWeG5/KKrnywbzjzhhnmexVloQAAghEUYBASBTPWuTHzAQQQAABBBBAAAEEEEAAAQQQQCD+AvnNsHNlRxs9/NS0d4Xojo3J18604WdVe3dzzJ85xWpq7/QeAzVk8CDT3SRKutPjrhmTTUGObEahciceP9CWvLDcuxNFQYIFD9VZ3f03ev30qjrICyyofwUURv+wNjUG3VnSpXPHbLqxd5oCFFMmjvHavGrsCK/NoScdm9r33wmjAEZwDP5AjYIV3znjm15dBXKm3jrPNLYrLx1un+9d5QV35HDRyDO94/4xy+22OQu945qTTI8Z2N9rS/PRHTNZTYhCCCCAQEQECIRE5EQxTAQQQAABBBCIqADDRgABBBBAAAEEEMhZwC3Ea7HfX3nNWxts3YZN9o1jjvIODziirw05cZA98fRL1t5/Dj/skFQTak+BgZ7du3nHRp07LnqlMwAAEABJREFU1OtX/b+yao137OxTB3tbBVHOP/tk73NbP47sf5j1O7SXV0z9KWDxlSP6pfbXv7fZdjTs8oIxCsoo4OPGoICJjilwoQoyUtLnqu4HWtculfqYNgXHrDF07dzJdFxzkqnmmLYyBxFAAIEYCJQkEBIDJ6aAAAIIIIAAAggggAACCCCAAAJtCJCNQKEEFFxwd4UoMOBvd/+una2qx54AhTX984W+fZp+tv//f3nz3WaN+NtVf+rXFeh9cHfTnStuv1jbG2bOtwHVY7ykR121px89Lqv6vAleW8HHX2lummN72qcuAgggEGYBAiFhPjuMDQEEEEAgigKMGQEEEEAAAQQQQAABBAog4O52eObFV5q1tnXbDqvftCV17I2161Kf8/2guyx0t4Uej6UgjNrxt6v+1K+OK7k7N/S5mEmPvNLjrVzK5XFfwXHJU4+9cm1pO2TwIK+Y5qY5ejv8QACBbAUoFyEBAiEROlkMFQEEEEAAAQQQQAABBBAIlwCjQQABBIonoICE7gpZ+NiSVCd6pFOfXj3snl8/4R1bsWqtLV6yzPTYKB3QXRwb6t/3Hi2l/WySgiDubouR397ziCu1p3bVvtpQf+pX/btHWT34+DPK8t6zcfPs+707RHSniLuzRHXVhlcoxx+au4Iy7r0fqq5x3jTr/jbnpjtV/ONQXY1ZwRv/O0b0HhQlzUlze27pShU1PSrr1dVvep/5gQACCMRFgEBIXM4k80AAgfIJ0DMCERdojPj4GT4CCCCAAAIIIIBAfAV0F4OSm6ECBFOvGWtLl6/2HvE0YuwUq625xNydDXpvhxb89einC6+cmjFooHePqIweO6WtXobuv9tC7V08apipfZVRcEV3Z6h/vbNj+k/H26x7HvbGoMdNda7s5L2YfeK481PHp99+nx036MuW7z96ybneEaL2NQaNs0vnPf201qbGqACSe6yWXrquMc+9pcb08nW1paQgiwIkKu8f95Tpc+xzvata6yK5ecwcAQQiK0AgJLKnjoEjgAACCCBQGIGKwjRDKwggkBABpokAAggggECxBLQgr2CEghCuD3dMx/VZx7Wov+jeaaZHOyn5y/vz/HVUzyUFGFTPn2qvvsRlp7b+csG2BhzR1559+LbUGFRWFf3HVefmX1xuLk9bHXPz0Lg1D41ZdYP7OqY6/nFq3x33t6V+F9wxxfxtuXqujvLUnzuuzzqm9lTfzUftKLl6yichgAACURcgEBL1M8j4yyFAnwgggAACCCCAAAIIIIAAAggkQqBDRYWNGHKyTbvo0qzSRaedYZ323TcuNswDAQQQQCAmAgRCYnIimQYCCCCAAAIIIFAcAVpFAAEEEEAAgSQL7L1Xhf3T0Gq76h/PySpdfOa3bJ+mOkk2Y+4IIIAAAuETIBCSzTmhDAIIIIAAAggggAACCCCAAAIIxF+AGaYV2KtDheWSjH8QQAABBBAImQCBkJCdEIaDAAIIIIBAuQXoHwEEEEAAAQQQQAABBBBAAAEE4i+QpBkSCEnS2WauCCCAAAIIIIAAAggggAACfgE+I4AAAggggAACCCRAgEBIAk4yU0QAAQRaFyAXAQQQQAABBBBAAAEEEEAAAQTiL8AMEUiuAIGQ5J77SM28MVKjZbAIIIAAAggggAACoRVgYAgggAACCCCAAAIIIJA4AQIhiTvl0ZxwRTSHHdpRMzAEEEAAAQQQQAABBBBAAAEEEIi/ADNEAAEEENgjQCBkjwM/EUAAAQQQQAABBOIpwKwQQAABBBBAAAEEEEAAAQQSLkAgJBEXAJNEAAEEEEAAAQQQQAABBBBAAIH4CzBDBBBAAAEEEEgnQCAknQrHEEAAAQQQQCC6AowcAQQQQAABBBBAAAEEEEAAAQTiL5DDDAmE5IBFUQQQQAABBBBAAAEEEEAAAQTCJMBYEEAAAQQQQAABBNoWIBDSthElEEAAAQTCLcDoEEAAAQQQQAABBBBAAAEEEEAg/gLMEIG8BQiE5E1HRQQQQAABBBBAAAEEEECg1AL0hwACCCCAAAIIIIAAArkKEAjJVYzyCCBQfgFGgAACCCCAAAIIhFWgIqwDY1wIIIAAAghEUIAhI4AAAgUSIBBSIEiaQQABBBBAAAEEEECgGAK0GTGBxoiNl+HGX4DgXPzPMTNEAAEEEEAAgTYFCIS0SUSBEAgwBAQQQAABBBBAAAEEEEAAgXwECM7lo0ad8gnQMwIIIIAAAkURiF8ghL/kFeVCoVEEEEAAAQQQKJUA/SCAAAIIIIAAAggggAACCCCAQCEFwhkIac8MW7ntd/a8R6zmujtbtL5x8xY7/YJJNqB6jJcWP7OsWRnVc3kXXjnVGnbuapbPTgQFWrlOIjgbhowAAggggAACCCCAAAIIRFOAUSOAAAIIIIAAAiUQiF8gJA2aAhsKZNwwc36LXAU1Jl8704afVW0r6ubY/JlT7Ppb7rUVq9Z6ZVV3wUN1Vnf/jV5+r6qD7Nob53p5/IiwQNTvHCKQE+GLj6Ej0FKAIwgggAACCCCAAAIIIIAAAgggEH8BZlg+gUQEQoYMHuQFMa4aO6KF9Jq3Nti2HTvt7FMHe3n9Du1lfXr1sOeWrvT2n3j6JS9I0rN7N29/6EnH2tLlq013kXgH+IFAOQSiHsgphxl9IoAAAggggAACCIRBgDEggAACCCCAAAIIIFBygUQEQlpTrd/8gW3b3pAqUtmpo+mujzfWrvMegbWh/v1Unj5UdT/QGhsbrX7TFu2SEEAAgTwEqIIAAggggAACCCCAAAIIIIAAAvEXYIYIIBAWgcQHQnQieh/c3TpXdtTHtOnwww5Je1wHu3Ta20gYcA1wDQSvga5NfzYUM+3dId7PR9uraX5dOu5txTSkbXy5BrgGuAZKdA2k/p24D3+upyya2wf/HsH+3vw3VtO1wnXAdaA1BxICCCCAAAIIFEagQ2GaiXYr69/bbDsaMr8A/S9vvptxglqKJJlh0LoBPsnzsYqms17UZDH/p9h+tF/8axRjjLkGuAaC10DTv7qK+u/GYH/R2W8aqZEMAzMMzDAwSxkY/0RSgEEjgAACCIRTIPGBED3qqmuXytTZadi5y/Q4rC/07WOVnz4mK5XZ9EGP0qqoqLCqHnveGbJt5ydGwoBrgGugxTXQ8LFtK2L65G/xflHM33bvtu07i2tYzPND25y7hF8DRf3zD1t+v2J5DfDfFNbi71KYYMI10LQCwf8RQAABBBBAoFACiQ+E6OXoXTt3sgcff8Yz1cvT123YZN845ihvXy9HX/BQXerl6Hp5+jED+5t7ebpXqMWPBBzQV9YSME2miAACCCCAAAIIIIAAAggggEBmAXIQQAABBBBAIAoCiQiELH5mmQ2oHmM3zJxvCx9b4n3WMZ0g3fUx9ZqxpmCHyowYO8V+9MMLbMARfZVtQwYPsuFnVVv1eRO8erpb5JoJo728RP+I95fRE31qmTwCCCCQswAVEEAAAQQQQAABBBBAAAEEEEAg/gIRnmEiAiEKZqyom2P+pGPuvOnujkX3Tkvl+/NU5qKRZ6by7pox2Xtklo6TEEAAAQQQQAABBBBAAAEEkiXAbBFAAAEEEEAAAQSiJ5CIQEj0TgsjRgABBEItwOAQQAABBBBAoKgCPIe2qLw0jgACCCCAAALZClAOgdgIEAiJzalkIggggAACCCCAAAIIIFB4gXK0yHNoy6FOnwgggAACCCCAAALxFSAQEt9zy8wQKJwALSGAAAIIIIAAAggggAACCCCAQPwFmCECCCAQUwECITE9sUwLAQQQQAABBBBAID8BaiGAAAIIIIAAAggggAACCMRLgEBIvM5noWZDOwgggAACCCCAAAIIIIAAAgggEH8BZogAAggggEAiBAiEJOI0M0kEEEAAAQQQyCxADgIIIIAAAggggAACCCCAAAIIxFlgTyAkzjNkbggggAACCCCAAAIIIIAAAgggsEeAnwgggAACCCCAQAIFCIQk8KQzZQQQQCDpAswfAQQQQAABBBBAAAEEEEAAAQTiL8AMEXACBEKcBFsEEEAAAQQQQAABBBBAIH4CzAgBBBBAAAEEEEAAgcQLEAhJ/CUAAAJJEGCOCCCAQA4CFTmUpSgCCCCAAAIIIIAAAgiESIChIIAAAukFCISkd+EoAggggAACCCRVoDGpE2fesRFgIggggAACCCCAAAIIIIAAAs0ECIQ042AnLgLMAwEEEEAAAQQQQAABBBBAAAEE4i/ADBFAAAEEEMhGgEBINkqUQQABBBBAAAEEwivAyBBAAAEEEEAAAQQQQAABBBBAoBWBmARCWpkhWQgggAACCCCAAAIIIIAAAgggEBMBpoEAAggggAACCOQuQCAkdzNqIBAxAd76G4kTxmmKxGkKzSAZCAIIIIAAAggggAACCCDQhgCvvmsDiGwEoiDAGAsmQCCkYJQ0hEBYBfirT1jPTLNxcZqacbCDAAIIIIAAAgg4AbYIIJBAAf77qCAnne/bFYSRRhBAICYCBEJiciKZBgIIxFqAySGAAAIIIIAAAggggAACyRFgBT8555qZBgXYRwCBIgkQCCkSLM0igAACCCCAAAIIIIBAPgLUQQABBBBAAAEEEEAAAQQKK0AgpLCetIZAYQRoBQEEEEAg+gJ8kzH655AZIIAAAggggAACxRagfQQQQACBkggQCCkJM50ggAACCCCAQOIEeLZ11qecgggggAACCCCAAAIIIIAAAggUU4BASDF1s2+bkggggAACCCCAAAIIIIAAAgggEH8BZogAAggggAACZRAgEFIGdLpEAAEEEEAg2QLMHgEEEEAAAQQQQAABBBBAAAEE4i8QnhkSCAnPuWAkmQR4xnommfAf59yF/xwxQgQQQAABBBBAAIHiCtA6AggggAACCCCAQNkFCISU/RQwgDYFeMZ6m0ShLcC5C+2pKfXA6A8BBBBAAAEEEEAAAQQQQAABBOIvwAwRCKsAgZCwnhnGhQACCCCAAAIIIIAAAlEUYMwIIIAAAggggIDx3VAuAgTCJUAgJFzng9EgEBMBpoEAAggggAACCCCAAAIIIIAAAvEXYIaZBHhaeCYZjiNQHgECIeVxp1cEEEAAAQQQQCBhAjH+T8GEnUmmiwACCCCAAAIIIIAAAghETYBASNTOWEjHy7AQQAABBBBAAIHWBXg4QOs+5CKAAAIIIBANAUaJAAL5CvD34XzlqIdAIQQIhBRCkTYQQAABBBBAIEkCzBUBBBBAAAEEEEAAAQQQyFGAO6RzBKM4AgUVyDMQUtAx0BgCCCAQfgH+vhL+c8QIEUAAAQQQQAABBIogQJMIIIAAAggggED0BQiERP8cMoOkC7BAX5orgDtYS+Mc1l4YFwIIIIAAAggggAACCCCAAAIIxF+AGcZWgEBIbE8tE0uMAAv0iTnVTBQBBBBAAAEEECiFAH0ggAACCCCAAAIIIBA3AQIhcTujzAcBBAohQBsIIIAAAggggAACCCCAAMqhgj4AABAASURBVAIIIBB/AWaIAAIJESAQkpATzTQRQAABBBBAAAEEEEgvwFEEEEAAAQQQQAABBBBAIN4CBELifX6ZXbYClEMAAQQQQAABBBBAAAEEEEAAgfgLMEMEEEAAgUQKEAhJ5Gln0ggggAACCCCQZAHmjgACCCCAAAIIIIAAAggggECSBJIaCEnSOWauCCCAAAIIIIAAAggggAACCCRVgHkjgAACCCCAAAJGIISLAAEEEEAAgdgLMEEEEEAAAQQQQAABBBBAAAEEEIi/ADPMJEAgJJMMxxFAAAEEEEAAAQQQQAABBKInwIgRQAABBBBAAAEEEAgIEAgJgLCLAAIIxEGAOSCAAAIIIIAAAggggAACCCBQUIHGgrZGYwUSoBkEEMhOgEBIdk6UQgABBBBAAAEEEEAAgXAKMCoEEEAAAQQQKIVARSk6oQ8EEECgOAIEQorjSqsIlFiA7hBAAAEEEEAAAQQQQAABBMIiwBfnw3Im4jgO5oQAAgggkI8AgZB81KiDAAIIIIAAAgggUD4BekYAAQQQQCDkAnxxPuQniOHlJEBgLycuCiOAQEgFCISE9MS0NSzyEUAAAQQQQAABBBBAAAEEEEAg/gLMEIFyCxDYK/cZoH8EECiEAIGQQijSBgIIIIAAAggUU4C2EUAAAQQQQAABBBBAAAEEEEAg/gJFmyGBkKLR0jACCCCAAAIIIIAAAggggAACuQpQPqMAX0vPSEMGAggggAACCLQuQCCkdR9yEUAAAQTKIUCfCCCAAAIIIIAAAggEBXhRQVCEfQQQQCD6AswAgRIJEAgpETTdIIAAAggggAACCCCAAALpBDiGAAIIIIAAAggggAACxRUgEFJcX1pHAIHsBCiFAAIIIIAAAggggAACCCCAAALxF2CGCCCAQFkECISUhZ1OEUAAgWQK8FjnZJ53Zo0AAkEB9hFAAAEEEEAAAQQQQAABBEopQCCklNr09ZkAnxBAIJECPNY5kaedSSOAAAIIIIAAAggkWYC5I4AAAu0VYDGhvYLUbxIgENKEwP8RQAABBBBAAIFiCiSlbf77JClnmnkigAACCCCAAAIIIFBCAR4vUULs+HZVqkBIfAWZGQIIIIAAAggggIAnwH+feAz8QAABBJIuwPwRQAABBBBAAIHQCRAICd0pYUAIIIAAAtEXYAYIIIAAAggggAACCCCAAAIIIBB/AWYYFQECIVE5U4wTAQQQQAABBBBAAAEEEAijAGNCAAEEEEAAAQQQQCDkAgRCQn6CGB4CCERDgFEigAACCCCAAAIIIIBAggV4PmSCTz5TT5oA80UAgWgKEAiJ5nlj1AgggAACCCCAAAIIlEuAfhFAAAEEggKNwQPsI4AAAggggECYBAiEhOlsMJYICTBUBBBAAAEEEEAAAQQQQAABBBCIvwAzRAABBBCIgwCBkDicReaAAAIJFuCrZ7mefMRyFaM8AmYGAgIIIJAQAf6ekJATzTQRQAABBBBAIHECBEKyPOUUQwABBMIpwMOIcz0viOUqRnkEEEAAAQSSI8DfE5JzrlubKXkIIIAAAgggED8BAiHxO6fMCAEEEEAAgfYKUB8BBBBAAAEEEEAAAQQQQAABBOIvkJgZEghJzKlmoggggAACCCCAAAIIIIAAAi0FOIIAAggggAACCCAQdwECIXE/w8wPAQQQyEaAMggggAACCCCAAAIIIIAAAgggEH8BZohAQgUIhCT0xDNtBBBAAAEEki3AU+CTff6ZfdIFmD8CCCCAAAIIIIAAAggkS4BASLLON7NFwAmwRQABBBIu0Jjw+TN9BBBAAAEEEEAAgYQIME0EEEAAgSYBAiFNCPwfAQQQQAABBBAIpwB3rhTmvNAKAggggAACCCCAAAIIIIBAkgUIhCTl7DNPBBBAAAEEEIigAHeuRPCkMWQEEEAAAQTKK0DvCCCQmwB/5c7Ni9IIRFSAQEhETxzDRgABBBBAAIHMAuQggAACCCCAAAIIIIAAAlkJcBN2VkwUQiCsAtmOi0BItlKUQwABBBBAAAEEEEAAAQQQQCB8AowIAQQQQAABBBBAoA0BAiFtAJGNAAIIIBAFAcaIAAIIIIAAAggggAACCCCAAALxF2CGCOQnQCAkPzdqIYAAAggggAACCCCAAALlEaBXBBBAAAEEEEAAAQQQyEmAQEhOXBRGAIGwCDAOBBBAAAEEEEAAAQQQQAABBBCIvwAzRAABBAohQCCkEIq0gQACCCCAAAIIIIBA8QRoGQEEEEAAAQQQQAABBBBAoB0CBELagUfVUgrQFwIIIIAAAggggAACCCCAAAIIxF+AGSKAAAIIIFB4AQIhhTelRQQQQCDBAo0JnjtTR6CAAjSFAAIIIIAAAggggAACCCCAAAIFEwhtIKRgM6QhBBBAAIESClSUsC+6QgABBBBAAAEEEIiDAHNAAAEEEEAAAQSKLUAgpNjCtI8AAggggEDbApRAAAEEEEAAAQQQQAABBBBAAIH4CzDDMgkQCCkTPN0igAACCCCAAAIIIIAAAskUYNYIIIAAAggggAACCJRWgEBIab3pDQEEENgjwE8EEEAAAQQQQAABBNolwCNJ28VHZQQQQKBUAvSDAAKhECAQEorTwCAQQAABBBBAAAEEEIivADNDAIFiCDQWo1HaRAABBBBAAAEEYilAIKTptK5YtdZOGDbeBlSP8dLseY80Hf3s/9p3eRdeOdUadu76LJNPCGQnQCkEEEAAAQQQQAABBBBAAAEEEIi/ADNEAAEEEAihQOIDIRs3b7GJP7vNamsusRV1c6zu/httwUN1tviZZd7p0lb7Oq78XlUH2bU3zvXy+IEAAggggAACCCCQToBjCCCAAAIIIIAAAggggAACCIRHIPGBkPpNW6yxsdGquh/onZXOlR2t98Hd7S9vvuvtP/H0Szb8rGrr2b2btz/0pGNt6fLVpgCKdyDTD44jgAACCCCAAAIIIIAAAggggED8BZghAggggAACCIReIPGBkAFH9LW/++qX7OKJ00yPyFrz1gbbtmOnnX3qYO8RWBvq3292EhUwUeBEAZRmGewggAACCCCQYAGmjgACCCCAAAIIIIAAAggggAAC8ReI6gwTHwjRidNdHvt37ewFQ0aMnWKnDzk+dQeI8g8/7BBt0qaDu3U0UhEMDmxqk2QHYxBZg14HdbJipv32ifcf3/vs3aHp3BfXsJjnh7Y5d1wDXANcA1wDuVwD/J0vcn/3b/p7CmPmui3QNdDKmkLaRQgOIoAAAggggEBeAvFeScuCRHeB3DZnof3q1n+zZx++LfWOkNnzHknVdo/JSh3wfdi4dZeRimCwpalNkm3EILIG9R/stGKmv3682/cnUTk+FrfPT/62u+ncF9ewmOeHtjl3XANcA1wDXAO5XAP8nY+/+3MNJPgaaGVNobh/46Z1BBBAIFsByiEQD4HEB0LqN39gXTt3Mr0bRKdU7wI5ZmB/e2PtOqvs1NF6VR2kw6mk8hUVFVbVY887Q3Y3rUWSzApu0NjUJsl2Y4BBhmug6XDqz6U4fmhsmiDXP38Ocg1wDXANcA2E5hrg30v8nYxrgGugWNdAK2sKcfx7PnNCAAEEEECgXAKJD4TonR+vrn7Tnl/2qncONm7eYkuXr7Yv9O3j7euxWQseqjMd14Ennn7JFChRwET7JASSIsA8EUAAAQQQQAABBBBAAAEEEEAg/gLMEAEEEIijQOIDIQOO6Gu1NZfYZTU32YDqMVZ93gQbfla1XTTyTO98Dxk8yNvX8QHVY2xD/ft2zYTRXh4/EEAAAQQQQAABBGIpwKQQQAABBBBAAAEEEEAAAQRiJJD4QIjOpYIdK+rmmEsuCKI8Je27vLtmTPYemaXj8U7MDgEEEMhWoDHbgpRDAAEEEEAAAQQQQACB0AkwIAQQQAABBOIvQCAk/ueYGSKAAAJFFqgocvs0j0AJBOgCAQQQQAABBBBAAAEEEEAAAQRiK5AKhMR2hkwMAQQQQAABBBBAAAEEEEAAAQRSAnxAAAEEEEAAAQSSJkAgJGlnnPkigAACCEiAhAACCCCAAAIIIFBMAW4aLqYubSOAAAIIZC9ASQQ8AQIhHgM/EEAAAQQQQAABBBBAAIG4CjAvBMogwGvkyoAesi65BkJ2QhgOAgggkGwBAiHJPv/MHoHkCDBTBBBAAAEEEEAAAQQQQACB0glwV1DprOmpuQB7CCCAQBoBAiFpUDiEAAIIIIAAAggggECUBRg7AggggAACCCCAAAIIIIDAZwIEQj6z4FO8BJgNAggggAACCCCAAAIIIIAAAgjEX4AZIoAAAggg0KYAgZA2iSiAAAIIIIAAAgiEXYDxIYAAAggggAACCCCAAAIIIIBAJoH4BEIyzZDjCCCAAAIIIIAAAggggAACCCAQHwFmggACCCCAAAII5ChAICRHMIojgAACCCAQBgHGgAACCCBQaoGKUndIfwgggAACCCCAAAIIGASFESAQUhhHWkEAAQQQQAABBBBAAIFYCzTGenYhnxzDQwABBBBAAAEEEECgXQIEQtrFR2UEEECgVAL0gwACCCCAAAIIIIAAAggggAAC8RdghgggUAwBAiHFUKVNBBBAAAEEEEAAAQQQyF+AmggggAACCCCAAAIIIIBAAQUIhBQQk6YQKKQAbSGAAAIIIIAAAggggAACCCCAQPwFmCECCCCAQPEFCIQU35geEEAAAQQQQAABBFoXIBcBBBBAAAEEEEAAAQQQQACBogkQCCkaba4NUx4BBBBAAAEEEEAAAQQQQAABBOIvwAwRQAABBBBAoNQCBEJKLU5/CCCAAAIIIGCGAQIIIIAAAggggEDeAo1516QiAggggAACJRYISXdlCYTUXHenXXjlVGvYuctL+jygeoydMGy8rVi11vgHAQQQQAABBBBAAAEEEEAAgbgIMA8ECi1QUegGaQ8BBBBAAIGYC5Q8ELJx8xZbuny1jR5+qlV26mjPL3vVI37x0duttuYSm377fV5wxDvIDwQQQACBuAgwDwQQQAABBBBAAAEEEEAAAQQQiL8AM0QglAIlD4RIoWuXSqvqfqA+2hNPv2S9qg7ygiI6tm3HTtvRsMvLM+Nmz08h2CCAAAIIIIAAAggggEBkBBgoAggggAACCCCAAAIIhEmg5IGQzpUdrWvnTla/+QNzd4cMPelYz0THtm1v8D7v+VGxZ8NPBBCIngAjRgABBBBAAAEEEEAAAQQQQACB+AswQwQQQCACAiUPhOhxWBPHnW81tXda9XkT7JiB/W3I4EFeUGTqrfO8/Z7du0WAjiEigAACCCCAAAIIILBHgJ8IIIAAAggggAACCCCAAALhFSh5IER3gUyZPsdmTZ9kK+rmWO3Vl3g6Cn5Mvmykbah/n3eEeCKR+8GAEUAAAQQKIhDjuyFjPLWCnHoaQQABBBBAAAEEoiHAKBFAAAEEEIicQMkDIa0JtXxHSGulyUMgqQKsJCb1zDPvpAjE+P1YsZpaUq61Wg0kAAAQAElEQVRH5okAAggggEB4BfirRXjPDSNDAAEEEEAgbAL5B0KKMJPnlq703h+i94gUoXmaRCAmAvx1PyYnkmkggAACCCCAAAIIIBANgZCOkq+IhfTEMCwEEEAAAQRCKFCyQMiKVWvthGHjvfeCrHx9rY0YO8UGVI9plmbd87Dp/SF6j0gIrRgSAggggECCBZg6AggggAACCCCAAAIIIIAAAgjEX4AZxlOgZIGQAUf0tWcfvs3q7r/RjvpSX5s/c4r3jpAVdXNSW+WrXDypmRUCCCCAAAIIIIAAAgggEAkBBokAAggggAACCCCAQKwEShYIcWo9u3ezBXdMMQIeToQtAgiEU4BRIYAAAggggAACCCCAAAIIIIBA/AWYIQIIJEGg5IGQJKAyRwQQQAABBBBAAAEEIiXAYBFAAAEEEEAAAQQQQACBGAuUJRCycfMWO/2CSc3eD+LeF6Ljyo+xOVMLqQDDQgABBBBAAAEEEEAAAQQQQACB+AswQwQQQACB5AmUJRAy444FdszA/ql3g/jfE7Lo3mmmx2cl71QkZ8bL3lhtv3/lT7FMz776im3csiU5J5OZIoAAAghEVYBxI4AAAggggAACCCCAAAIIpBFoTHOMQ9EXKHkgRHd7rF6zzkadO7TMenRfDgH9QfLfv3vazq/9WSzThP9zq21p2FEOWvpEAAEEEEAAAQQQQAABBBBIK8BBBBBAAAEEsheoyL4oJSMkUPJASIRsGCoCCCCAAALxEWAmCCCAAAIIIIAAAggggAACCCAQfwFmmFag5IEQPfaqf78+9tzSlWkHxEEEEEAAAQQQQAABBBBAAAEE2iNAXQQQQAABBBBAAAEE/AIlD4Socz0W6+WVf7aGnbu0S0IAAQQQKLwALSKAAAIIIIBAGQX0SNgydl/0rnc3xn2GRSekAwQQQAABBAolQDsIIJCFQMkDIXpHyMSf3WZP/m6pHXfGOBtQPaZZOv2CSaYyWYydIgi0KvDb62ut8bFHTNtWC5KJAAIIIIAAAgggEHGB8A3/hddetbN+cnVs09Mvv2xGLCR8Fx4jQgABBBBAAAEEEEgrUPJAiB6Ntejeabaibk7apDyVSTtaDiKQo8DKN9+yQw46yN655247+eijc6wdseIMFwEEEEAAAQQQQCA0Ah99/LEt/fPrsU27/vpRaKwZCAIIIJA4ASaMAAIxFuCbJsU6uSUPhBRrIrSLQCaBAZeOs0Uv/cEemPJjG33KyZmKcRwBBBBAAAEEIiTAUBFAAAEEEEAAAQQQQACB+AlUxG9KIZlRyQMheuyVHn8VfCSW21eeyoTEJ8zDYGw5CFw84ya78TcP2Kwrr/BSDlUpigACCCCAAAIIxFiA/9CK8cllagggEB8BZoIAAggggAAC7RQoeSBEj73S46+Cj8Z68dHb7ZRvHmPTfzreVKad86J6QgV0x8fW3/y3926QUwZ9zY467FDvs94V8uNRF9i+++xjI/7hm9wZktDrg2kjgECUBRh7KQVeev01q1v+x1imJStfsQ+2by8lZ8j74tb7kJ8ghocAAggggAACCCCAQMIEijPdkgdCMk2jslNHO/qoL9o9v34iUxGOI9CmwNwnn7L9v/OPVnHamfbksj+a3hGiz/6kfJVrszEKIIAAAgggkFCB2Y89aqOu+0Us09WzZ9r2nQ0JPbNMGwEEIiPAQBFAAAEEEEAAAQQKKhCaQIhm9Y1jjrLVa9YZj8aSBgkBBBAopUD4vhFcytnTFwIIIIAAAlET+O31tbbijtvTDlt3SW+cP89+/r3vps3nIAIIIIAAAgggECYBxoJAKQRCFQgpxYTpIzkC3/pRjQ24dFxyJsxMEWiXAM+IbxcflRFAAAEEEGifQNa19c47PfZVj4ENVjr56KPtnXvutrsn/YvtX1kZzGYfAQQQQAABBBBAAIHECoQqEKLHYvXv14d3hCT2cmTiyRZg9ggggAACCCCAAAJtCVw846bUY2CDZZ96+WX73Kjv2fem/YdtbeARcEEf9hFAAAEEwiLAOBBAAIHSC5Q8EKLHXp1+wSQbUD2mRdpQ/75dM2F06RXoEQEEEEAAAQQQQACBUgrQFwIIIIAAAggggAACCCCAQMkESh4I6dm9my26d5qtqJvTIt01Y7Lppeklmz0dlVWAzhFAAAEEEEAgOQJ6Z8HW3/y36ZE+SvqsY34Bve9AeUp6vI8e8+PP5zMCCCCAAAIIRFOAUSOAAAIIIFBugZIHQtyEFz+zrMUdITrm8tkigAACCCCAAAKlFGgsbmeJb/2krw60F1a97j3Sp+K0M73P1104xlyw47fX19oBnSvtlElXe0lgt/zzD7QhIYAAAggggAACCCCAAAIIINAugRIGQj4bpwIeU2+dZ3X335i6K2T+zClWU3unzZ73yGcF+RRLgf323tv271QZy9SlY6dYnjMmhQACCCRBoCIJkyzjHPVeg2/9qCY1grXvvee9zLlPj+6mO0OOP+JLtuilP5jecaCkz5/v2cPLS1XiAwIIIIBARAQYJgIIIIAAAgggEC6BkgdCGnbusrkLHrfJl400PSbLcQw4oq/V1lxiS15YbirjjrONl0CjNdoZg46028dfFMv0s5HnWdd9/havk8ZsEEAgPwFqIYBAqwInHHmkbW1osHWbNqctt37znuP9+/ROm89BBBBAAAEEEEAAAQQQQCAUAgwiEgIlD4TsaNhl23bstKruB7YA0jHlqUyLTA7EQqDCKuxb+y+xkRX/Fst03j4zrE9XHq4Si4uVSURegN/EyJ9CJhBTAT0CS+8A0d0eV981x7sDZO6TT9nbGzeZgiMxnTbTQqBgArOuvMJ7184pg75mRx12qPdZx9SBHjWn9+vcPelfrMcBB9iPR11g2tdx5Rcz0TYCCCCAAAIIIIAAAmEWKHkgpHNlR+vauZPVb/6ghYuOKU9lWmRyAAEEEAi3AKMLmUBFyMbDcBBAYI+AHo+ld4TM/5/f2X9eNj716Kvr75tvCo4oSKKkBVzVWL1uvTYkBBD4VECPmdPvkD/pmLL1WLnPjfpe6l08KqN9HVc+CQEEEEAAAQQKIkAjCCAQQYGSB0IqO3W0E48faHpHyMbNW1JkK1at9d4RojyVSWXwAQEEEEAAAQQQQCB2Ak//abl99PHH5h59pbtC9v/OP6YWcGcvesy7S0THYzf5WEyISSCAAAIIIIAAAggggAAC0REoeSBENBeNPNN7R0j1eRNsQPUYL40YO8V7R4jyVIaEQHsENm2rsGsf7GLvfdjBtu8ye+Tl/drTXPq6HEUAAQQQQACBrAX0SCz3+B5V+v7Qb9l+++xj6e74+Pn3vmsj/uGbdv/vf6+iJAQQQAABBBBAoLwC9I4AAgggEHmBsgRCpDZk8CBbUTenWdIx5ZEQKITAoEM/tiWr97U3N+1lH/+tEC3SBgIIIIAAAskVaO/Mn1m50nsMlh57pXT8EV+yf771NnN3fCj48dHDC733HUz4zre9vJ/c/av2dkt9BBAICPDoyAAIuwgggAACCCCAAAKJEChbICSCugw5QgJdOzba3/X72L59zC7ruX+jnfqVjyI0eoaKAAIIIIBA/AR+0hTU2G/YOalHX+kxWC4Iotn684N5yichgEBhBBoL0wytIBB3AeaHAAIIIIAAAjETKGkgZPEzy7zHYGkbdNQxPSZL22Ae+wjkKrDfPma9DthtHZqu8Kr9d1unfXNtgfIIIIBA0gWYPwIIIIAAAggggAACCCCAAAIIxF8gGTNsWiYu3USfePolO+e0Ey3dI7B0THkqU7oR0VM5BHZ32M92790tpukAaywHKn0igAACCCCAAAIIIIBA/gLURAABBBBAAIHyC7CoVv5zEOMRlCwQsnHzFlu6fLUNPenYjJzKUxmVzViIjEgL6JnE6w74ur1y2KRYplWHXGzbGveO9Dli8MkVYOYIIIAAAggggAACCCCAAAIIIBB/gdDOUAuHoR0cA4u6QMkCIYLq2qXSqrofqI9pk/JUJm0mB2MhoMDuC1v/YHPemh7L9N/vzrZdHTTLWJwuJoEAAggggAACCMRVgHkhgAACCCCAAAIIIIBAggRaCYQUdjG3c2VH69q5k9Vv/iAjr/JURmUzFiIDAQQKJEAzCCCAAAIIIIAAAggggAACCCAQfwFmiAACCCDQSiCkoqA6lZ062onHD7TW3gGiPJVR2YJ2TmMIIIAAAggggAACyRZg9ggggAACCCCAAAIIIIAAAokVaCUQUniTkd8+2TbUv28XXjnVGnbuSnWgzzqm94Ocferg1HE+FFaA1hBIqkBh729LqiLzRgABBBBAAAEEEEAAgagIME4EEEAAAQQQaC5Q0kCI7vS4a8Zk786Q484YZwOqx3hJn3UnyKJ7p1nP7t2aj5A9BBBAoJ0Chb2/rZ2DoToCCJRKgH4QQAABBBBAAAEEEEAAAQQQQCD+AlnNsKSBEDeii0aeaSvq5jRLOuby2SKQr8BbDzTa8v9tXtJnfzt/+6jR3rh7T57K1P/en8tnBBBAIFkC3CmVrPPNbBFAAAEE4i7A/BBAAAEEEEAAAQRaEyhLIKS1AZGHQL4CLvAx8N/MlA799mf3ASgIsva+Cut6+J485Vf9fb49UQ8BBEIpwKByEvjsT8icqlEYAQQQQAABBBBAAAEEEEAAgfIK0DsCeQgQCMkDjSrhE/jwNbOPt1ZYnzPSj23zixW2z/6NRvAjvQ9HEUAAAQQQQKBAAkQZCwRJM20JkI8AAggggAACCCCAAALZCxAIyd6KkiEW+GiTWcPbZiv/o8J7LJYefaXgiBvyrk2N9uGKz/JW/kdT+XU8GMb5RHTLsBFAAAEEEAifAH+9CN85YUQIIIAAAgggEHUBxo8AAgi0W4BASLsJaSAMAgp0HHzSZ4+9OvQ8s3UP7wl26LFYultEx/RILKUe3zB769e6i4TVijCcP8aAAAIIIIAAAm0JkI8AAggggAACCCCAAAIIIJCvAIGQfOWoV3qBHHrs0q/R9qsy274m/fMpDvzqngBIw/r0+Tl0RdEcBPao51CBoggggAACCCCAAAIIIIAAAskTYMYIIIAAAggUWIBASIFBaa48Ah17VJjuCgn2vl8Ps7322/N+ED0+y5+/V8em411ZmvebFPtzRbE7oH0EEEAgRgJMBQEEEEAAAQQQQAABBBBAAAEECiNQlkDIxs1b7PQLJtmA6jEtko4r38wKM0NaSYSA7gDZ/ucKc+8F0Z0gH3/YaJW99wQ6DvhyhW16bs+jsgTywZ8qrMN+ZgqUGP8ggAACCCCAAAIIIIAAAgiUU4C+EUAAAQQQQACBogqUJRAy444FdszA/raibk6LtOjeadaze7eiTprG4ydQ2afC+gwze+t+s+X/e8/7QQ4912yf/ffcg3DAl830XpA35lR4+e8va7RDv93o3S0SPw1mhAAC0RRg1AgggAACCCCAAAIIIIAAAgggEH8BZlgOgQ6l7lR3e6xes85GRQHH5wAAEABJREFUnTu01F3TX8wFFOwY+G9mSkf9i5mCI/4pV/39njzlf/mHFakgib8MnxFAAAEEEEAAAQQQQKAEAnSBAAIIIIAAAggggEAJBUoeCCnh3OgKAQQQCLUAg0MAAQQQQAABBBBAAAEEEEAAgfgLMEMEECilwJ5XJQR7LHkgRI+96t+vjz23dGVwLOwjgAACCCCAAAIIIIBAPAWYFQIIIIAAAggggAACCCBQAoE9r0oIdlTyQIgGoMdivbzyz9awc5d2SQgkRIBpIoAAAggggAACCCCAAAIIIIBA/AWYIQIIIIBA2ARKHgjRO0Im/uw2e/J3S+24M8bZgOoxzdLpF0wylQkbFONBAAEEEEAAAQQQyEGAoggggAACCCCAAAIIIIAAAskWSP+UqrKYlDwQokdjLbp3mq2om5M2KU9lyqJR4E5pDgEEEEAAAQQQQAABBBBAAAEE4i/ADBFAAAEEEEAgjUD6p1SlKVj8QyUPhBR/SvSAAAIIIIAAAmUQoEsEEEAAAQQQQACBBAmE6Eu+CVJnqggggEAoBCI5iLIFQhY/s6zZI7H0iCwdK5ei+tYYlIKP55o975HUWC+8cirvNinXSaJfBBBAoJACIfpWQiGnRVsIIIAAAgggUAoB+kAAAf46zTWAAAIIIBAlgbIEQhR0mHrrPKu7/8bU47Hmz5xiNbV3moIOpQYMjsf/eC7lLXioLjXWXlUH2bU3zi31EOkPAQQQCJ9A1EfEV9iifgYZPwIBAX6pAyDsIoAAAggggAACCCBQGAFaQSAGAiUPhDTs3GVzFzxuky8baf53gQw4oq/V1lxiS15YXtI7LjZu3mK3zVlo0386vtl43Ll94umXbPhZ1am8oScda0uXrzbVc2XYIoAAAggggAACCJRbgO+llvsMxL1/5ocAAggggAACCCCAAALRFSh5IGRHwy7btmOnVXU/sIWajilPZVpkFulA/aYt9s76ehsxdkrq8Vc1193p9aagzYb6973P7ofG2NjYaKrnjrFFICECTBMBBBBAAAEEEEAAAQQQQAABBOIvwAwRQACB2AmUPBDSubKjde3cyeo3f9ACU8eUpzItMot0QH0e2f8we/HR273HdOlxXbrjw/+IrsMPOyRj7/vt08FI2Rvsu3cHq6jIyBmLjL06VHBN8HtR9Gtgr5j/HlVU8HvEv1s6FP33COP0xvvuXWEVsfg3cuZJ7L1Xhyyur5ZlZLNv07/jYpua/p7G70XL856vyT5772V9D+4V27TvvvuYfhf2a/qdIBXuusESS/81kPnfZOQggAACCCCAQK4CHXKt0N7ylZ062onHDzS9I8T/eKkVq9Z67whRnsq0t5986+txXXoUlv8RXX95892MzXXptI/FNhVhbpUd97am9c2MnnHIULCHa4Lfi2JfA3s1LeLF4fcl0xz2agoodu7IdVTs64j2ucbSXQOd9kvAv6ubFm7Tzb21Y3J59MUX7IZf/3fZ0/QijOE/H1pob9Zv4O+1Bfz775FVe9m88cNim752yN7WtZI/R1v7c4M8ro/2XgOZ/q5clOM0igACeQvwprq86aiIQEkFOpS0t087u2jkmd47QqrPm5B6HJUeTaV3hCjv02Il2ehRV+kex9Wr6iDrcVA309Y/EN1BUlFRYVU9unmHN2/9yEjZG2zZ/lfbvduji+2PnX/9G9cEvxdFvwb++km8f5E++dtue39b9n+28OcwVoW4Bmhjz3X04Y6PbXfM/2uuYdcnOf85/UHT32H+sHq1XTfvnrKn64swhv9c+EDTn7sNObvwe7Pn9yadw8H7brNvbLs2tqnPvh/Y5g8zzz+dCcfwKvQ1sCnm/90R2/9oZmIIxEygImbzYToIxFXAHwgp6RyHDB7kPYpqRd2c1FbHSjqIps76HdrL9DiuGXcsaNoz010qCx6qs6EnHevta6t9HdeBJ55+yY4Z2N9054j2SQgggAACCCCAAAIIIIAAAghETCAWw2XxMRankUkggAACCCBQEoGyBUJKMrssOqns1NGmXjPW9F6QAdVjTHep6NFYLiijrfZ1XPkb6t+3ayaMNv5BAAEEEIi6AONHAAEEEEAAAQQQQAABBBBAAIH4CzBDBMxKFgjRHRWnXzDJ7lv4lGmroEK6pDyVLeXJ0d0di+6dlrozJfh4Lu27O1fumjHZFDwp5fjoCwEEEEAAAQQKL9C4u9HWbHjX3li/LpZpbdPcCq9GiwggEFkBBo4AAggggAACCCCAQIIFShYIccGG88852fxBBxdgcFvlqWyCzwlTRwCBIgnQLAIIIOAX2PXJX+0nd99l5/3iJ7FMP5n7X7bro7/6p8xnBBBAAAEEEEAAAQQSIcAkEUAAgaBAyQIhrmPd7TH80im2YtVadyi1XfzMMrvwyqnWsHNX6hgfEEAAAQQQQACBYgls2b7dNn64JZZpy/ZtxWKj3QIKnHz00fbOPXdb42OPpNKsK69I9aDP/jyVVZ1UgcwfyEmAQO1DXWzU7d1s07aK1GzveaaTDZ3W3Uvfvukge239Xqk8PiCAAAIIIIAAAgggkFSBkgdCWoOu6n6gbdux03Y0EAhpzYm8bAUohwACCCCAAAIIhFugT4/u9uGOBjtl0tVWcdqZNnvRYzb6lJPt59/7rjfwvgcf7B1Tnsro4C3//ANtSAkXUBBk8av7NVP4/ev72iN/2s/m/eB9e2LSZvuXM7bbLx7s2ixQ0qwCOwgggEBsBJgIAggggAACrQuEKhDy3NKV1rVzJ+tc2bH1UZOLAAIIIIAAAggg0FyAvUgKzH3yKRtw6Th76uWXvfE//afl9tHHH1vv7t29/W/9qMYunnGT91llXnv7HTugc6VxV4hHktgfuutDk//pt5vf+fXmpr2sav/dVrlvo7KtR5e/edtN20L1n33emPiBAAIIIIAAAggggEApBUr2N2I9CuuEYeOt+rwJtvL1tTZi7BQbUD2mWZp1z8M2cdz5eb+MvJRw9IUAAggggAACCCCAQKEF+vfp7TW5fvNmbxv8cchBB3l3kCgoEsxjPxkCCoK8tHYfm3Dq9hYTPm3gLqvf2sH+7f79reEjsz+s3dcG9PnEvtx7T0CkRQUOIBBhAYaOAAIIIIAAAgjkIlCyQMiAI/rasw/fZnX332hHfamvzZ85xVbUzWmWlK9yuUyAsggggAACCCRUgGkjgEBWAnu+GZ9V0TIX0l0eF552qr2w6nX7yd2/ajEavS/k8z172PX3zW+Rx4FkCOjRVy81BUH+93lbrbL5U7E8gB5dG73Ax/ZdFXbOTd1twYud7Ny/2+nl8QMBBBBAAAEEEEAgsgIMvAACJQuEuLH27N7NFtwxxQh4OBG2CCCAAAIIIBAnAb3fYetv/tsaH3vES/qsY8E5/vb6Wltxx+3Bw+wXXOCzl0gXvOkCNqggyN2TJnp3e+hxWMGmFQTRdXTjbx4wPU4rmM9+MgT06KtX3tnHC3IMndbdfvZAV6vfupddcc8B3ntAdLeIJO688MPUO0J+tOCAmLwwXTMjIYBA+wSi8+WA9s2T2ggggAACCLQUKHkgpOUQOIIAAgggkJUAhRBAIBICJ311oPeN/orTzjQlfbv/ugvHpN7poAVtBUlOGfS1SMyHQRZfwB8E0ftCgj3qmlEQZOr8BWnvFAmWZz++AqMG7/QCHE9M2uxt9Y6Qqv3/ZjeN+tB0N8ibm/eyw7p/9hisLx/ysXXeb7dt2r5XfFGYGQII5CAQjS8H5DAhiiIQXwFmhoATIIbtJNq9LXkgZOPmLXb6BZOavRvE/64Q5alMu2dGAwgggAACCCCAQBkE9GJr/zf61773nu1fWWl9enT3RqN8BUieXPZHb58fyRZwQRC9BD1TEGTEP3zTe2F6usdlxVmPueUuoCDII3/az7s7RLVfe3cf2/FRB+vR5bPgiI6TEEAAAQQQQACBrAVYiM+aqigFiWEXjLXkgRA9GmvRvdOavRtE7wp58dHb7ZRvHmPTfzreVKZgM6QhBKIrwMgRQAABBGIgcMKRR9rWhgZbt2lzDGbDFAotUH30QOt5wAF2yqCveY9S091CSu6xabp+ujYF0u6e9C+p/I8eXmg//953Cz0U2ouBgO4YGdDnExv5fw4yPTrrPx7tYtcP/9C+3JtASAxOL1NAAIF4CzA7BMIrwEJ8eM8NI8tJoOSBkEyjq+zU0Y4+6ot2z6+fyFSE4wgggAACCCCAQGQE9A4QLWjr5dZX3zXHnnr55ciMvTwDTWavustjv2HneI9R051CLrm7Q7R1x9xW5VUvmWLM2i/w91/6q90zbovpsVjueM1Z273HZunxWQ9c8T5BEAfDFgEEEEAAAQQQQCDRAqEJhOgsfOOYo2z1mnWW2EdjCYGEAAIIIIAAArEQ0OOxtHA9/39+Z/952XjTOx5iMTEmgQACCCCAAALtF6AFBBBAAAEEECipQKgCISWdOZ0hgAACCCCAQFkFktL5039abh99/LH179M7KVNmnggggAACCCCAAAIIIIAAAgikBMLwIVSBED0Wq3+/PrwjJAxXBmNAAIHMAjwfM7MNOQggYHok1qwrr0hJfH/ot2y/ffax1evWp47xAQEEEEAgcQJMGAEEEEAAgZIINJakFzpBIHoCJQ+E6LFXp18wyQZUj2mRNtS/b9dMGB09RUaMAALJEuBvFXmeb6ohkAyBZ1au9B6DpfeDKB1/xJfsn2+9zeY++ZQHoCCJjp8y6Gt21GGHmj7rmJfJDwQQQAABBBBAAAEEEECgHQLh+O5mOyZAVQSKJFDyQEjP7t1s0b3TbEXdnBbprhmTrbJTxyJNlWYRQAABBBBAAIHiC+gl1nqZtd4PorT/d/4xFQRR7xfPuKnFi7F1THkkBIoqwH8VF5W3ReMcQAABBBBAAAEEEEAAgdAIlDwQ4mY+e94jze4IOWHYeFuxaq3xDwIIxEeAmSCAAAIIIIBAiAS4ozFEJ4OhIIAAAgggEC8BZoMAAgiEXaAsgRAFQRY8VGd199+Yuitk1vRJdvHEabb4mWVhN2N8CCCAAAIIIIAAAggEBdhHAAEEEEAAAQQQQAABBBAIqUDJAyF6R4iCIJMvG9nspegDjuhrtTWX2NwFj1vDzl0h5WJYrQuQiwACCCCAAAIIIIAAAggggEBLAW5Ka2kS7SOMHgEEEEAAgWgJlDwQIp6uXSqtqvuB+tgs6di2HTttRwOBkGYw7CCAAAIIIIBA+AQYEQIIIIAAAghkLVCRdUkKIoAAAggggAAChRdoVyAkn+F0ruxoXTt3svrNH+RTnToIIIAAAggggAACCCCAAAIIIFBiAbpDAAEEEEAAAQSiLFDyQEhlp442evipaR+B9dzSlda/X59mj8yKMi5jRwABBBCIlQCTyUeAr3/mo0YdBBBAAAEEEEAAAQQQQACB8gnQcwwFShII0XtBTr9gkg2oHuOly2pusueXvWrHnTHO23fHb5g535YuX20qH0NrpoQAAggggEDyBPgeC84AABAASURBVHggePLOOTNGAIGYCDANBBBAAAEEEEAAAQTiI1CSQEjP7t1s0b3TbEXdnDaTyql8fIiZCQIIRFaAgSOAAAIIIIAAAggggAACCCCAQPwFmCECCMReoCSBkNgrMkEEEEAAAQQQQAABBCIuwPARQAABBBBAAAEEEEAAgbgKEAiJ65llXvkIUAcBBBBAAAEEEEAAAQQQQAABBOIvwAwRCLUATxgO9elhcBEVKFkgRO/90HtC7lv4lGnr3gsS3CpPZSPqybARyE+g6d9wf1rzhv3P8j/FMv3+leX29nvv5WdDLQQQQACBIgnQLAIIIIAAAggggAACCIRRoCKMg2JMCERcoGSBEL33Q+//OP+ck1t9X4jKqGxJXOkEgbAINP0b7vnXXrUx/14by/TPt8ywjVs/DIs240AAAQQQQAABBBBAAIGkCTBfBBBAAAEEEEi0QMkCIU5Zd3sMv3SKrVi11h1iiwACTQK7Gxvto08+jmX6a9O8mqbI/xFAoMwCdI8AAggggAACCCCAAAIIIIAAAvEXYIYtBUoeCGk5BI4ggAACCCCAAAIIIIAAAgggUFABGkMAAQQQQAABBBBAICVQ8kCIHnvVv18fq9/8QWoQfEAAAQQQKIYAbSKAAAIIIIAAAggggAACCCCAQPwFmCECCLQlUPJAiAY06tyh9ptHf2cNO3dpl4QAAggggAACCCCAAAIItE+A2ggggAACCCAQKQE9Nv+0kf9alMfn11x3pykVC6SYYy/WmFtrd/a8R+zCK6eGcq1W51GptfHnk7f4mWV2+gWTTK9xyKd+tnV0rZwwbLwNqB5jcm6tnuappDKlGp/6SkoqeSBEF9fEn91mT/5uqR13xjjvItCF4FIpLsCknFzmmTyBdDNeccft1vjYI6k068orUsX02Z/3zj1328lHH53K5wMCCCCAAAIIIIAAAggggAACYRLQl2q1YKt1JC0uapFR49N6k9aUlPRZx5T85VVHyS00Kl8LkzqWKWkxUildfrAvtedSujoat8bjyrRnG4a6clTKdiwqq5RtecqFT0C/b8UKXoVvtu0fkX7fp99+n108apitqJtjF408s/2N0kLeAiUPhOjRWIvuneadfF0AwaQ8lcl7RlREAIGUwOhTTvY+nzLpaqs47Uz7xT332oh/+Kb9/Hvf9Y73Pfhgm73oMS9PZXTwln/+gTYkBBBAILwCFeEdGiMrqQCdIYAAAggggEDCBbZub7B7fv1ERgUt2p4y/Cp7dfWbNn/mFG8t6tbaK2zhY0tS3wTXwqRbmzrntBO9trR1x4YMHuQd04+vDzrSXnz0dq8d5be1hvX53lVWd/+NqfK9qg6ycy/6SdG/ga6xRiENOKKvPTbv303bKIyXMZZHoPbqS0ypPL23r9cdDbts/Xub7fDDDmlfQ9QuiEDJAyGKyg+/tOlfPqvWtpiAouVxi463mGRBD9AYAq0LzH3yKRtw6Th76uWXvYKr1633tr27d/e23/pRjV084ybvs8q89vY7dkDnSu4K8UT4gQACoRVoDO3IGBgCCCCAAAIIIFAkAZoNCuzfpdI+d0hPW7xkWcZHKylIomCJvo3tFtsV2FCg4+319fbg488Em81rX9/61nqW7hrR2lamRrSYe8zA/jbjjgWpIgrWnDBsz2NztNW+y/S3q7bd3RTaKrly6lP9q7zW3XSnivJVR0l5Lyx7zdS+21dZV9/VUZ6S2lOexqJv/9806/7UE13UrvJURgElJdVRH2ozeIeNymUq/4eXV5naVz8qo6T21Z6SPuuYktpVH5f/+ObUWFzbym8rZZqj+lBy9TUH9aP+dCxTPeX5k+bgfINj95dTu64/15ebh9rQmqn6VB0dV1tKOqfuuMrJzZ0Xl6d8fVZ5JdVXO5mSxqFySjfMnN+sWLq2NF7d3fDOuxttxNgp3nlwfWirdpQ0BtVXg+nG+vvnl3vn3X8uNRZ/G9pXfSV9VtLnYHvqz+UpX8nfjn8sypO/6ihdVrNnPUzH0yX1lemcan5qW+0o6ZqRj78dlRn9w1rTnzXqS22pTZXRmFVPSZ91rK2k9vx9ap6qo+O6blzbOu4fj9rXvFVWW/XpksrqeFJSyQMhrcFWdT/Qtu3YaYqWtVaOPAQQyE/gpK8OtP322cfWb96ctoFDDjrIPtzRkAqcpC3EQQQQQKBcAvSLAAIIIIAAAggggIBP4ML/7wxvT4uzwbUkLQ4uXb7ayw9+G3voScd6x5e8sLzk70RQ3xqXxqekx8fX1lzi3TWi7cUTp3mBHS2qavFUd5Ho7hOlo4/6Qk7jVR3dkaJvpN9+90J7csEN3h0q2n9+2auegcagxdrhZ1V7Y9CdM7fNWZi6a2Xrth323sb3vTy1pbFr8dQFlBRUUj93zZjstbe9aV3P3TVz1dgRNvXWeV5b6cp37LifV8f90CLthvr3vbtu1IY+axHX5WvM3znjm95YdGePa9vlZ9q2Nke9x3j1mnXeGFV/zVsbvLXJs08d7B1rzUbllXSudA3q/MlCYz+450Fpz5WuRc1LddTXq6vftCeefknNWP3mD6xr507WubKjybim9k7T+VCbOj/+AJr/vOjOJDWQzVhVTknWOpc6p2pf50rHlTJ56Xds4rjzTQFINy6d11zHemC3rqbxH33UF71zqbYU0JSDxqL9P/zpde/3QOMJJtVNd02qXGtjUd6sex5OmeoaUp1M6ZXX/mKzpk9qNka1ofI6FzonGq/S177yxRbr2Xri0dxbakx3hqmvZx++zbv7Sfa6BnSdKOmz/zpX+8Gk62XytTPN9SkjXR8aj64XXTe6flRPjrqudH2pntrXdadAyaLFL3h/BmjMaqN+4weqEs5UhFGFKhDy3NKVqV/4IsyVJhFIrIAehfXRwwvtotNPM90l8pO7f9XCQu8L+XzPHnb9ffNb5HEAAQQQQAABBBBAAAEESitAbwgg0LbAV758uA05cZBpgfz5pjWldDV054i+eJsuL9dj6ue4M8Z534TXN6rd4mVlp46mQIAWF7Uw3Fq7GkvXLpVekVdWrfG2Xzmin7fVo7eO7H+YaX1Mi5jrNmyyUecO9fL04/xzTjb1pc9tJQVcVEaLpL0P7m4nHj/Qq+v2//Lmu8o2NwYt/OtAv0N7eWtz7vj+XTunxuDqqly6pLFdcfF5Xj/K/8YxR1ljY6PVb9qi3VaTFmwVmHLjVFujh59qWqzXwrwqy0dJn/2O2m8tubmkm2NwvrLv36+PaRG7tXr+/hQgUHDJmWrsfgd/WZ1rfQlc51d9ndUUcNFCteao+m7+WszWte3uZJKlP2DjPy9qP9uxqqyz1qK65qlj/pRLW6qX61hVR+PXnPS5qkc3O2D/LuauWe1XVFSYW9hXGX9SXfd7EbwmWxtLMM/fZrrP+n1z/rpO9LupcyQ/nbM31q5LVbv8ovO8ayZ1IMMH1W3rOk9XVdeL/jxwZhqXrg/NSdebrht91nWksem60vWla1Pt6bqT5zvr6839PqoNzVH5SUkdSjVRRZ1OGDbeqs+bYCtfX5u6hWpA9ZjUv0AUlVNkUSewVOOiHwSSIKDAx37DzrHvTfsP0ztCFPTwz1v7ep/Ijb95wAuU+PP4jEAZBegaAQTCIlCu97KUq9+wuDMOBBBAAAEEEGhT4MpLh3vfuL7r/z5qH27d3qK8Ho2lBUB/hhYz/fvZftYivL7BrYCHkh51lW1dV05j2ba9we2aghRazNUBrYfpDhB9VtKCrxaF9bmYSY/u0Xqd1ugU6FHAJ9/+3Pqf2tLjk/Tt/Vza0jfXXflcgh2uTqZtpjnK3C0iu0VqtyCvtjLVU55LCiZM/+l407qm5q2kb+q7fP9W59p9e193NZxz2t+bzrmCD280Laz75+8eO6b2ZOm/bvxtus/ZjNWV1dbfl/b9Kde2ch2rv69PPxds09pYvtC3T9b96HrQI6YGNK1d+38vdM1MvWasF6RTnpLu8rAc/vHbZ3udB/888M9F7SkAooDJF5sCebquXl75Z9N+ly577jJSkFaPCdS1pDGffsEk766nHIYd+aIlC4QoyqRbgHTL1VFf6mu6/Ub/0vAn5atc5FWZAAIhFdDdIG9v3GR9Dz44NUIXBJk6f4EpYJLK4AMCCCCAAAJOoFzvZSlXv27ebBEoqQCdIYAAAgjkI6BFaH2zXe8tUNDDtaHjeh+H9oOBDy0467gWwLWoqc+lSvrWtsal8alP3UngvrWthVctZuq4koII7tvb2i9WCgZ4tFanRdNc+1MQRI/2co+I0tqfFm9zacd/roJBo1zaCZZtbY76lr3utlAASIvGKuvq67M/+JXJRuuZWtdUvh6DlOmxXbredN09+9IK02PEdKeBAi9zFzxuOvf65r7rW4+rUnsu6RFY7rpxZfzbbMfq6vit3TG3zbWtXMfq+inGtrWxvNEUbMqmT/0u+h9Np2tAJq6uzoPOh86NrvP5Dy7O+CgvV8e/9dtne50H/zzwz8VdN7/93Ut2wrEDTNeV+vvVrx83PYJM1532Lxp5pveoL41bfw7pEV86npRUskBINqCKlirSpostm/KUQQCB1gX0SKw/3HpzqpD2v9j7EFv73nveMQVBdIeIXpgeiiCINyp+IIAAAggggAACCCCAAAIIIJC9gB55pOfwB2vo8Tl6NJa+qa9FeuVr7UnfGFd51dOx9iatY2k9S9+yVvuZ2tOjtPSoJ93FojJu8dK9tF0L8Xq2vxbmtZDZp1cP0wvfVVZ96OXY2uqb4Fo012clLaKrTD5JY1AwZt4DT6Wqaw5KqQMZPvjH4Yoo8KFvuGtfC7xavNVnpWbldcCXtFCrAMGCh+q8b6m7eWmxVovOvqI5f2xrjgpi6HFY//lfDzRbNG6rnhuIHkd08+z73W6bW317/55f/9bkoXm7flRRd4xoq+CI/7rVMfWhvvQ5mFwb2ZxH9SlrPaJJzkr67NpsrS3doVRRUWH1mz97t0SuY3X9FGPb2liUp98/Z6igZFtj0DlSGQUr9Xuiz/Jyv4vazyU5+1yv8+CfB/rzTO9V0ZzUv7tu/ue5P5nOn/pRAOTJ3y01XW8qo99pJX0OJrWnJzllyg+Wj+p+qAIh+oNSz8nTxRVVUMaNQJgE6l5ebgcf2M0aH3vESz8edYH36CsFPjTOE4480rpWVtrdk/7Fy1c5vUtEARPlkxBAAAEEEECgeAK0jAACCCCAAAKFEdBC+eTLRrZoTAvcTy64wfRsf/c4GH3L+5zTTjR9m1v1WlRq5YACFXpEjgIeSm09Wsb/eCGVV/Di17N/nnqXgPr3P1KppvZOmzV9kmncWsj0P35H/epRSjo+8tsne6PUsVOGX2VHD/iit5/PD41h7i01poVZjVFJdzNoMbWt9hRI0uKwxqFAkBZr/+6rX0o9Dv/6W+41BUZcO8Hyu3Z95LK8rb6trsCHHtOlNvXIqHweP+Y15vuRzRy1oLzu3Y2mIJSrmk09ldUi9B9f+bPW7B+zAAAQAElEQVTJTknnUedV9ZUfTLLV03JcXyqneSs4ofOr8kMGDzLdWeOuW7Wr60dllR9MOp7LeQxeQ7oTxrXZWlvK0x1Y+j3SmLRwnutYXT/F2LY2FuXJWdeXxt5a/zoPekfNDTPne+f17O/XeO+7UR3l6XdR16ja0Tn60Q8v8H5vld9Wyuc6V5/+Pw/Up64PzUn9KV/Xj+anc6Rjur50nel6077W3XVtasxKup6umTBaWYlJoQqE6CUuek6e/gBJzBlI9kSZfZEFnnr5ZfvcqO9ZxWlnppILgqjrAZeOSx13ZfQuEe4OkQ4JAQQQQCB7AZ5hlb0VJRFAAAEEEEikQMEmrQW/u2ZMNj2GSAED17AWBPW4l2CAw5VXnkuZFtd1XGW0de1q69pWnj+5vvx9qGymOhq3yirfJc1Bc1G72mrf5WlBU30oT8mNS22oLR1TnSsuPs+0r+OujhuHjilPi69qN7ivY66O2lNSnzqmsTw2799TC7yurmtbZVRWddSH8jVG7SuprpLaCfaj8n939BHmz1cZf3191jEljV911If21eaCO6akgko65k+qq+SO+ceqsWncOubyNSdZql13TFuVUVnVUdJnHVM5N3aNSWNTvlK6dtSWS6qvsasNd0xj1RzdvrYak9pzSWV0XPVc39p3Se1qfK68PuuYy/dv/WPWeG/+xeWpa0jlVE/107WlcbrjGqPKa+uOadvaWIPjd32pDbUV3FdbSsoL1nXzcHVVRp81BpdcXeXps/+45qj+lBdM/nZkJHPNXeX87ag9ldXxYFLb6iOY76+vz66ePitpX3VUV21oX1vtqz8l5eu4Sxqbq6tjstJ1pnpuX/NQXSVds/Lz5wXbVF6cUskCIe4WG0XdVr6+NhUdVgTKJd3yNXHc+eZOQpygmQsCCCCAAAIIJF0gzvOviPPkmBsCCCCAAAIIIIAAAggggEDEBUoWCFEU6tmHb7O6+2803ZajF8msqJuTekGLPisqpXIRN2X4CCCAAAIIIIAAAggggAACCCRbgNkjgAACCCCAAAIhEihZIMTNWbfj6LYcAh5OhC0CCCCAQFwFmBcC3CfBNYAAAggggAACCCCAAAIIxF+AGYZfoOSBkEwkGzdvMb1kSkmfM5XjOAIIIIAAAgggEBUB3pwRlTPFOBFAoAACNIEAAggggAACCCCAQGgFyh4IWfzMMtM7QvTukA+3brfpPx2f8UVHoVVkYAgggIAnwA8EEEAAAQQQQAABBBBAAAEEEIi/ADNEAIGoCZQtEFJz3Z1eAOSymps8s1trrzDeEeJR8AMBBBBAAAEEEEAAgfALMEIEEEicAHc6Ju6UM2EEEEAAAQRiI1DSQIgeeaVHX+kOkIWPLbGrxo7wXp7++d5VsQFlIskSYLYIIIAAAggggAACCCCAQFIEePdVUs4080wnwDEEEEAAgWgLlCwQoiDI6B/Wmh5/NX/mFFtRN8cuGnlmtPUYPQIIIIAAAgggkBwBZooAAggggAACCCCAAAIIIIBAJAVKFghxOkf2P8z6HdrL7UZsy3ARQAABBBBAAAEEEEAAAQQQQCD+AswQAQQQQAABBOIkULJASM/u3WzuLTW2/r3NdtwZ4+yEYeNtxaq1xj8IIIAAAgggEFIBhoUAAggggAACCCCAAAIIIIAAAvEXSMAMSxYIkaWCIYvuneY9FmvIiYNsxNgpVn3eBHt7fb2ySQgggAACCCCAAAIIIIAAAgiURYBOEUAAAQQQQAABBOIrUNJAiJ+x9upLvIDIrbVXeIcvq7nJTr9gkuldIt4BfiCAAAIIlFqA/hBAAAEEEEAAAQQQQAABBBBAIP4CzBCBxAmULRDipIcMHuQFROruv9E7NPqHtQRDPAl+IIAAAggggAACCCCAQPEEaBkBBBBAAAEEEEAAAQSSIlD2QIiDdo/N0qOz9NkdZ4sAAkUUoGkEEEAAAQQQQAABBBBAAAEEEIi/ADNEAAEEEi4QmkBIws8D00cAAQQQQAABBBAosgDNI4AAAggggAACCCCAAAIIJFOAQEiyzjuzRQABBBBAAAEEEEAAAQQQQACB+AswQwQQQAABBBDwCRAI8WHwEQEEEEAAAQTiJMBcEEAAAQQQQAABBBBAAAEEEEAg/gJtz5BASNtGlEAAAQQQQAABBBBAAAEEEEAg3AKMDgEEEEAAAQQQQCCjAIGQjDRkIIAAAghETYDxIoAAAggggAACCCCAAAIIIIBA/AWYIQK5ChAIyVWM8gggkHCBioTPn+kjgAACCCCAQEgEGAYCCCCAAAIIIIAAAghkKUAgJEsoiiGAQBgFyjGmxnJ0Sp8IIIAAAggggAACCCCAAAIIFERg8TPLbED1GDv9gkm2cfOWnNtUHdVVOzlXzrvCnooNO3fZhVdOtdnzHtlzICY/NR/NS/MLTmnFqrV22sh/NW2Debnsl/O85TJOV7Y1E1cmrtskzz2Xc5qrE4GQXHQpiwACCCCAAAIIIIBAuQToFwEEEEAAAQRMC8VaMNZCvj9pYV4LvXEm8s+9mEEILbifMGy8FyzxG7vPS15cHmdm5hYSgcMPO8R6VR1klZ06egE7/Y67a1Bb/Tmg34mQDLfZMHJdoG9WOWQ7Mpa1zF2que7Odo+yEEb+aySbAREIyUaJMqERYCAIIIAAAggggAACCCCAAAIIIBB/gWxmeGvtFbaibo7V3X+jV7z6vAlWzACB10kCfgw4oq89+/Btnu38mVPsc4f0NG1lrXTicQPLpqBF8btmTLaLRp5ZtjHQcfkE3O/8i4/e7g3i2hvnelt+ZCGQxwNOFFw+96KfeAEp/e671KVzp3bfoZTFiAtehEBIwUlpEAEEEEAAAQQQKIgAjSCAAAII5CTAu9xy4qIwAjES6Nm9m03/6Xjbv0ulTb11nvftcU1Pi3j+b5GfMGx8i8U7fSvZfctZW5VXPX3jWfvaWtM/CrBo3+W7uybU5k2z7k/dPaHyqq9y/vJNTXj/d+0oT0nftNY3rpXpxqJjl//45lSbqqMyl9XcZM8ve1VFTZ9VX3k6oK32XVIbqqM8JY3L5amujrmkciqvfLXjjre1/dPKv5jmr3qqr3ZcHb+B8l27ctNjnpyZnFRWddWGyirJwrXl37pyLl911YbqKKkNlfHXcZ9VR2VccmNy+f6tyqqt4HlwZYL9+ttqq65rI7jdtmOnff+K65ud92AZ7cvQuWsuOrc6rpRL324O/vpqI1NSv/5zF+xb9dSWjivps44p5TIulVcaMniQ1V59iT62SAqInXj8QNtQ/753l5gKuPmobyX/OQnmKV9jUj1tda7ddaN5Dr90SurPER1XvuooqbzqKals8Fzo2Kx7HvZ+V487Y1yzR9CprtpQUptqW+0oyUvHlW6YOV+HMqbgfPxzVTu6btW+2tL4NCZr5a9Jmcb14OPPWO+Du9s1E0Y3G0vN5d81BUx1MNNY1Gem60V5uRoF56Uxt3aNaGzBFPJASHC47COAAAIIIIAAAggggAACCCCQTiCPrzqma4ZjZRKgWwTaJ1DVo5sdsH8Xe3t9vb2yao23iDn6h7X24dbtprsZdNeI8keMnZK6a0QLa1pwPOe0E727H/Qt82MG9s9pIFu3N9h7G983tf/53lW28LElpn7n3lJjalfj0WKiGtXCnYIQOq5vVl81doS3WBr8VruCHd8545umb7+rnoI7Oxp2eftfH3SkDnmf1YYWAttqV/kal+pqjq5dr6F2/Hh5xZ/tyQU3mNpUM/MeeEqblP3ws6o9V/nfNmehd1wFtm7b4Zlp/IvunWadKzt6gR09BknHZLlo8QstglaqG0wz7lhgrh/V/dpXvmiyCpbTgvP2pkCDxqpysperFnGDZd2+Ow8qLzNXXm1NvnZmql/Nr6b2ztR1pfqZ6iovU3qn6dqdMnGMZ+bvL1j+ldf+YrOmT/LKqe/FS5bl3Ld/DpmCDcF+te8/dzpPS5evTvWt60yBCRkr6bN+x1RPKR8T1UuXNP4lLyw3BUMUFNF51O+duxbkctun15zK6nzpd1vnUmPT70K6doPHVFe/s+muTeVNv/0+q625xDsXavfgngdZv0N72cWjhpn60DFd4wrWymfBQ3XenxUah9p0vzPKk6VMlafrMzgWt69+NR//XIPX34vLXrOJ4873xqWxaJyq59rwb9V3unGpvN/YX8d9bs1dZTJdLwqiaFy5GKk9/7zyuSusgxohIYAAAggggEAIBBgCAggggAACCCCAAAII5CWgxXR9c9lVVjBEQYgj+x/mLUxqIVILh8p/4umXvEV5LTzqLpJR5w7VYe9dBFoUVlnvQBY/XH1//5MvG2lq4wt9+3gtvLF2nfetdS0q6sDQk47VxvR8e33QOLSgqM9KWhxUqup+oHeXi4I59Zu2KKtFcouVykjX7lvvbDDX7+jhp3pzVFl/0kKyHjelBVgFVvx5rX127am+FnVdWdnr89mnDtbG8+/auZMXoNKB/bt2Nmeu/TVvbbB1Gzaljsmuf78+9tzSlcrOmDR3LbbL1xW6/KLzPHu377Ya4xUXn5ea/zeOOcoaGxstk6vq6Rwo6bPORdculfpobrxqQwe0qDvkxEGm60r7SqqnpM/+utrPlNy1qvyvHNFPm5SZt/Ppj/PPOTn1bXwtuqveX95899Nc8xbgW+tbgSIt7iuIkOtisv/c+a95nQtdZ2pT1kq6PvzXtsakpIFma6Ky/qRxD6geY7rTQu278bd2zbnz5b/m/G229jlY139tynH9e5vN2WvO/mvM367z0Z9BakN5Q5v+HJDZpve3eL+j/jzlZ0puTK1df7oedV2qDffnjD4HU2vjUp7Kt1a/NXfVzXS9KC+Y1J88/A76M03HlKfy/nlpP9dEICRXMcojgAACCCCAAAIIIIAAAgi0W4AGEEAAgUIKuEVJ16ZbnHT7/q0Wz9965z3vbhH/8WJ+9o/PLeZq294+22q3YedHpsXa9vaTa30FofTOFrdorbsBWmtD3xzX3Toqr6Q7WFor//+z9yYAUhXX/v9pFoFhlU0ExS0qgktwS1zyghpE/Wk04WEeGhP/EZX4d40GI0leyEtCFOOC+jeomEdU5CnB4PJTkaj4giZqIlFEcVcUlFXZZtj7358aqqm5093TPdM908tXOX3vrTp16tSn6vbM1LlVlzwmnq/72YXGZDtlEJ5utzT/sR0P2wShR13UmUa1wWQmeFmF5BV90MtfpzuGPuBHOn/DIEPUVnXNBvPbHhEQaIhttDyrCRgTPlAVzW/KdThpnm2wI2wPTGgbaan8YKUMqywIqISBJ3Qzjblof6GfrTBOGC/4hvixSUCDLfnY4ol0JNyiKpV9VqChh0Tv/5BdqrJhWrQ92Y6/0EZ4nsmvTN+l2MjEnfxcJZMvudqK6isQEiWiaxEQAREQAREQAREQAREofgLyUAREQAREQAREICDAk/2snGB7Kp6mzzSpyOqF/rvt4rbSCkwU9DSc2GYyl9UXhhUNhQAAEABJREFUXvzWOY1xoCG7Pbp3bYzZJpdhopoJa99GjplWm+zWt7f5bYHQRfzT/pmcYTIafuizHdKDjzybckstAhCjrpyQ3MYIXSaTM9nOlMfkOGPO64SrUnxaqiNP6f/tsdvdlkX4nK6NYYArtEOAgAl0xjDlYQzrUKehc7ZdYtUSARHsNaSfS344ab5s5ee2dl11g8UJaPkVSbSJc9LSFSTPB8DCwAMc4IENL37MRfsrne1U6ZnGZtif3Nd++7RUdkhDx/vGMWxryA7dTBJtT7bjL53NVH717N7NbT0WrshIVT4T91T6DaWl8oU+b6hcNvkKhGRDSTpFSkBuiYAIiIAIiIAIiIAIiIAIiEARE8jwYtIi9lquiUAREsjsEttKXfnL2433dTDBy+Q4wRCCIm++85HbyogJXyb0/FZW6PDOAMpMfWi2qwAd3mmAvaY+Ye0MBh9M5LFtEEn3Tn/KbZXFOXVRJ3Vzna34SdOG7BIooZ3YjT5BTxpC3TyFz1Pq4cQyeY0R2LPiwL//ABvYRTiPCts7sXUW7/vweQQuHni49p0jPi16xO+Jk2ckWUbzo9cEPlilQDqT9Ewmc56r4G+/Pj3Njxt85T0dbOOTq610+rxXhq3emGROpePHZ7qASaoyPo0gIQECxiNBFTiSRzuGjfxxykAS+ZnEj0PeNcGYxibjnLHHvZapbGPysMm9zrsx8DvTmPP95bdaY2spvhd8vfBgvMKSNPrVB3Aom25s0s5b7p5BkXoSten5hIESGDF+KUxf8P1EGsI56akEn/I1/jL5hR+sGoLNr2++t44r42+5z42TTNzrFEhxkQsjfElhIuckBUJyRqYCIiACIiACIiACItACBFSlCIiACIhAVgTiWWk1k1JROdNMbVY1ItCMBJjEZfKeLZiolhUFTPByzkTpvbeOdas+2NaGLYSY/Jx8w5jk+xV4HwhPx7PVDXbQYZslyjMBSCDF51EX6U0Rnv7naWe2MqIu6sR3turKxi6TlrwAmWCO3z6G4EJDdn92+TnuvRH5bEsmfz17JsVpI8IEMJOmqcrRLrjAAV2E1RsHDtg7lXoyjXJLl69y74ugDP38k0vOSvZvUjFxwpP7hx28n6GD7rW33m8ERhJZOf+jXr8iAVvY5IXZfuzlbHB7gXBcwI46qGt7tjtwzbsxfP9/8/tj3btOXGaOH4wbVpYwtploJlDABDsT7TmacurYI/DBmGZ8Y5t7zGUW4APevHCbscLqHO53uNEniB9zMOO+8VtYjbthirHKw7uEHe835XjhuX8fDGXTjU2CjP96/V2jDEJQhq2yGP8EsAhkweKks8a4dxLBh/dfkIY+jDp17ODeWzPyjOOdO6SdMOJH1qlTB3ed6gOfGBt8V2GnqeMvk1+05aG7/8vCe5M6162vcfcZ+em4p/I9TMuVUVi2seclFQhpbCNVTgREQAREQAREQAREQAREQAREoDIIaBFGefSzWiEC6QgwCch2MmwrEwrbIzEpF5bjmnSvx5ZETIiHOkwC+nyO6FMO4Zy0UEgjDzvYQzgP/WJilTq87XAymLzQHue0h/Je319jF/sI59jkyDXlEOyRzpHrULwdbHMe5nHu2xLmYwd7Xqhv1rTr3aSnT6P9lA11aSP+R3WoB0GfcqnsUSb0AX3aiC55oXg9Xxf1ou8l9Cksx3moS5uQVHWgi32YUR/X6E2/c5zRBq450qZU9TZUlvJRoYy3xRHb1IEedYe+0kZ0EDiRR3l0OabzG3vYpTy6CEy8PtsrEWTxbSY/lKgf6FE2ag+/EGz78pn88jqZjql8Rx+7MMA3r0PdCG0lDT3y0SP9jxN/YqzyIN0LvpKHXDZquIV97dtJHoId7KVLx2aYF/qBv9jwwnVUH/u3/OpSgy12yI8K7cKutxPtA9rjy5CXyRZ6+OFtceSadAQfKE+6l9B+1Bf8Ig1GjE2OoR38Ca+x6cuQTt2keeGadOpEOG+sKBDSWHIqJwIiIAIiIAKFJSDrIiACIiACIiACIiACIiACIiACIlBwAmzzxFP/6VbtFNwBVSACzUBAgZBmgKwqREAEREAEREAEREAEREAEREAEMhFQngiIgAiIgAiIQEsR4Al+nvrn2FI+NFe9foWDX2nQXPWqnpYnoEBIy/eBPBABERCBWgI5fHbp0MYuOf1Uu+KM08tSdu/RNQcaUhUBERABEShVAnp9Qqn2nPwWAREQAREQARFoEgEVFgERaHYCCoQ0O3JVKAIiIAJNJ3Bwr632q0PftN8cvqAsZchuNU2HJAsiIAIiIAJFTQDn9C4HKEhEQAREQAREQAREQAREQAQKTUCBkEITln0RSE9AOSLQaAKttm20Dl88n5C5ZSmttqxuNBsVFAEREAEREAEREAEREAEREIEiIyB3REAEREAEWpiAAiEt3AGqXgREQAREQAREQAQqg4BaKQIiIAIiIAIiIALFS+DZF+bZSWeNseUrv3DCOWn58HjBWx/asJE/No75sFfuNuCUiRd9lM/+yQfP6poN9oMrrrO7pz2eD3N1bIz97V2G1ElswgU+4is+N8FMVkXxe9CQc5P3FvcU18gfH3yyRe+LhsZZVg3Mo1Kx+ZNN08L+5LyhMi197yoQ0lAP5TNftkRABERABERABERABERABERABERABMqfgFrYYgSYeEW8Ay0x8Ub9iPdBx6YRgCXSNCuVWbolJ9eZGH9l/js2Z8bN9uT9E1wHXHfbNLtt/GW2YM4UO/yQAS6tuT4YQ0hz1VdO9dCXBK+Qo069yAV1+W4N+/O4owdb9D94I9H0lrpWICQgTySUiCjCuc8iUkpHI9E8r6OjCIiACIiACIhAXQK6EgEREAEREAEREAEREIFSIcAkHpO1vXp0y7vLg/bf02ZNu9445t14MxuMN0N9cCoXXvnANf6a8w3Jh63mtPH+R59a3116WMeq9q7aZSu+sHg8br177OyuW7qfW7p+B6FEPvh+JIC1e9/e9sgfx7vvsmh/lkJTFAjZ3ksEPi4eO9FenPfm9pTaAxGv6Y/OcdFLopV9ene3X998b22mPkVABERABERABERABERABERABETATAxEQASakUD4wCoPrTJ3Q/UcH571vCGk8zDr9b//H/t4yTJjzoc0yvqn5CdOnmGksc3SzFlzk9v3YAuZ/dw/XD462GLuiHRshNfYG3HBOLelViof/vnqW/W2AOIpaewinGMX8bYv/fktybqxSV4qoW6e0MYOErVFGhL1N9x6inaR7+uJ+uBtkn/gkHOdX9RJ3fjEk+EwpB4EPdKjgh6cfDn0qJf60aUe6ibf+4cO/YlgG/2amg2o22tvvG/44dO9HZcZ+cA2eghlqCOi4i5J93W7hMQHPtA+/Mc/bHghL6FS7x96+Op9wi5tx4ZXRsfbCXV9vj/iO8I1dvDPj13K+zzyQ6HuGyY9YJ98utzOvHCc67fQ35+Mv9OlYSNMpxz+kI7gZ2g3PMcfeKKHeF8oc+MdD7p51iNOHm0//MlNNurKCUlfTjprjM19cX6d+4KyjHtfNzYQuCHYR/AVXc4Rrr1P6JPmxedxZAwh5FFHIe9L/KFO6kJgBCvSOXIdTScvFNqI+DTs4Tf9gw3GAbywg6CLDucI174sXCgb6qPr83M9Un+0P8OxjT3swxvBH+rP5t6lHPoI4yRqF9uNFQVCtpMjuHHMkQfZjy48c3tK7YEfeiNOG2L+iYChXz/cWNaVz06orUmfIiACIlA8BKa+0MHGP9qpnkNz397Jhk7o4eTsSd1sxdpYoKNTERABERABERABERABERABESgsASYB162vsZefmOS212Eeh+1ZmKfhqeXThx1jCA+z/uGmq+3HP/wP4ylmnmYm7byRpzgH16xdb0uXr3I2WAnStXNHlx79oAx1kT5t5jMcMspxRw929Yc+tG/frk4ZJiU/W7bKtQHbnIeTljyk+62Tv+Z8w2/fvjpGEhewYKJ7/NjznS62dunV3UhnMjH6YC/BIPISRRv8F/rAagTsjR1/lz14xzhX1+Qbxtj66g0u+HPOJeONuTNYkX/7lIdderQSVgZ07tjBlq383GUx5/bmOx/ZB4s+cz7DYe89dnV5/iMVzw4dalcYvLrgXXt6+o2OI/rp+oexwYPN+Iccd8xgg1sqFqwSOOzg/ezvr7yBSSf4SfvwP93Yc4o5fDAGov2Tzv+o2XDssu0U85T0T1SvKsHpytHfsd127ZXsN3iiF/ZvOMZgwjjxvLD/5LMvua2QKLdDas9eX/i+MRbgSt8/+/w8wxfuM+7Nrww+wPXP76+9wul5X7jndu7WudZI8PnyvIWGz9jDBlmfJAKZ46481407bOIf87PocH3v9Kfc+MH3dP1Du7knEcrx3VCo+xKfYZDufrnyl7ebv2c5ElAgsEC5XIRxcMjALzkunj1jlfZx/c/X3q7Tb+n6PJc6vS73Cf0e9qefO/c6qZg3dO9GuXHf3XTndG+yyUcFQhII/Q8bf4Mlktw/biC+hN3F9g+Wb7GMi+U/25N0EAEREIGyIeADHVPmVtVr08Ilre33z1TZrd/9wmaPWWmnHLzRfvNoZ6veWE9VCSIgAiIgAiJQ/gTUQhEQAREQgRYhwOTuZaOGG0cc+OqhA912O7nO03RJBD7O/vZQTKQVJlvJpC4enn3+pfluwpW0xgpzTdjBHnaRc0acWOehWyaPEepgHqpzp/p/n5FHIGLJ0pXGFkRcY8uzYUL00IP2TT7YS1sXf7bCBR3QbUioH/F62COAwAQoaRyPHDzAXn/rAy7tmyce7Y579e9jBDt8ukvc/oF/tBtbBCeYczstUY6gA21B7cD99+KQlcANmwgT9+kKMUF76XnDk9n0K9x8ncmM7Sfk00f0FX6+88FiY5xRj+eLKmmNmSPELvaZ5MU3bIV1cp1JwrFLcIbtpzLpp8qjbxHywjFGUIpxwnghD//23atfncAQ6V6+c/rxbpskrun7A/bdIzkeSctVwjHmy2IT21wTKCOw6ccJ174vm9I/vk8Yn9hBGF8EmRgD1A0vhPOQGddRYYyHbYneL95/7NE+7oGojYauGQeMQfR69+xmXbt0MsaRv47FYsmgI2nUhXDekP/oFFJgC2MkvHej3Ggf95/vg6b6VPGBECKwQCS6zTGVcFOlSiete+edTJI9g64d21qrMh917XdqnfOY6Jbg0roEuXAPZCs7tc2dC/fWmurV9vGyT0tOPln+qWUj62vWWI8u7XKWtm0KM2CO3W+TC3Kce2x1va7954c72aB+W2xA360u77A9N9myNa1s0crW7jqfH21axxL3Ue5cGsNSZSqXc+cObfM5bIvSVufEz5dcx3jXRJlWZb7Yq6p9m5y/d3futFPid5jyBtO+baucueQ6vipJn59lRfnFkCen2rSJ2c76Wyjx+0r2fwvxu61EvHIZA3m6XcvSDE9PH3XqRW5bH7b84cnoQjc009xQY+oO7TV2UpJJ6id8wIMAABAASURBVBt+cZFNnvqYY8FWMjxR7f3ZZ89+/tSYKGXiNJmQ4wnqoT2uvbD12JDhl9ugIeca2yDx5LnPix5pNwEQJty/lJhgP33YsfbqG++6AE2nTh2S75OIlmvqNVzwD2FFQSZ7TFKvXV/jfCKgQ2DHT8Tnc+yxdRT+IA35lMnffOdxP3Ff4RfC1kbp6iCAwJZH6DXU9+ls5DO9qf3D+PT+NPa+9OXT3S8ErghgoRcNBJBW6cJ4YzwhjMO16+rPTzWWUWFm0hrrTQuUe+/Dxcm9IwHMlxBf2HwBcTPjko+scx6V9Ru2mCR7BjUbt1q8Od6sFe2oZrzevGVbzmOieuMW27atGZ1sgaq2bM2dy7rE/fXS2+/aWdf+puRk5G9/Y9nI6x99YutqNucsWxM8m7sbP4oEPHp2rh20K9blPxBC89ZvyJ1LY1iqTOVy3pD47m3u+6i566tJtDHXMU6Zcv9ZvWnztpy/d9dv3GLbyv13mMSXb67jRfrpv0O3lvmA2bY1nvPvvPq7Kfu/m8RKrBgDzf17Q6nUx0QnW8mwpcyCOVOMLWCaOsGfTdszzQ1lUz6qE9pjq6jGTvbxpPnfHrvdbY8TbnFEfcx5cURYMcMEN+eNldBeaIOnzNmWi/7wwrY4oY4/J8jA+V/++g876vBB5gMM9z30lLHNDxPD5OdTCIKE2xTBKZN9Akx+FQRPqPun1/M99vDD8+LIdk2FaH+mtqbK261vb2NLLHzyEt1Fh3LMmzJ/yhP96DEGGAvktYTko3/ydV/S/nT3i1/Bgg4MCQxyLqklwHZnjCcvbKPGPVmb27TPig+EsBLEg+UIbG5avox6du9m3MwhYn44xWIxF0knfWPiD+nKkW3W1LZuSgQJyn1yhT96c+W0aUvcynxuxbYlJgNy5sL9tWmTvf/Zp2Urm7ZsadR9lcDJV1Czyx49aleDFLpilhfnOl6k3/Tv6EpjuLmlbqRC30CB/S2Jny+59msl/EwiOJ8zl8TPpHJ/miMRB2nUz6RcWVaKfrn/zstXKEHFSulPtVO/Z7TEGAh+pLfAaXFXSeCDp7XxknmacIKfp7CZWGSCkXyevOYJ7HCCk/RchG1ZeJ+DnxDnqfFwMnPqQ7MtDGREfQjrYqKb7Xewh1385B0H4TZWoX6mc8rfcveMlCpskcP7GpgcRgEf+/Xp6QIPrA6JxXZsm8MDwQh66SRqj+ACQmADFuH7LUhHsBWd66A/SP/fv79mlIUHAZCn//qKwZW8qGTiGdVNd822QbSb/GzGAltDPfHMi8a2PPhJOSTT2CPfC22Bi99+C/5+jNBmxkD47hfGwcTJM5q89Zqv3x9pcyy2o699erojgSlWwITvZWAMPfBw+vfj0D/Yo620mfOWkkz9g5/hd0Poo++TfNyX2M10v5D/yFMvcDDuO96TwxZQLiH4CP1lfPA9EWTn9ZQdk046a0zKd/s0paKwDdnYgRsr3BhzXp/vOL7r/HVTjhUfCGkIHh3gbwJ0iQQ35ocTZSUiIAIiUOoEoqtCSr098l8EMhJQpgiIgAiIgAiIgAiIQNERYAXEYQfvZ2yZws4e1956vzH56R3lXRVMxrJND1v2kE4Agx1A0GfCj7RshKfdKcO2T7zPwa9y4MjcEOnk79Kru3UO3uMR9WHDho11quPpel8eP3kIlwd16yhlcUFQ4V+vv+u2pMIPVj2wVRZPT+PjqLNPTXJiApiHfpnwJf/qi0eab9+fn/ir8VBwpiqj9qiLYBS27r11rDF3hg8IE/w+eBDdWJT6CQLQfspSJ5PAA/fb0wVGuI5KlGdNzYaoSsZr2kYwzPcXAY6MBRKZBAS6JPqUlSHez4bGXqJY8h+8aKOvMzpGGAOMKZ/POOjUsUPy3TdJQ008wXfq8X3tA1TpzNI/jBPGC32JsALrwAF71yuCbnhvffP7Y42HGuspNlNCQ/0THUeFui9pLv0f3n/h/cI9ymQ/bEnnpeP4TrlQRp5xvLtkbJww4kd2yKAvueuW+GDcMIbYBo9+DgMVmfyJMm/o3oUbq/389zuMGIuM40z1pMyLRmETShkDIYn8iv9HB/CF4b+YgP+zy8+peC4CIAIiUHkEoqtBVqyt/RHSs1PzrBKpPOJqsQiIgAiIgAiIgAg0HwHVJAKlRICgAbt6ILOmXW+In0hkwoytVMjzWw0xt8M1wgQ0umEZ2o4O5SiPcI6+F8qh5yX04bJRw236neOMcuRz9OXx4bBD9q/jIzphec5JQ6iHMkwyc42voW3SvKCDrveRLbLQ9/nY8nnooe/zaK/Pu+VXlxr5pJFPOa5DfZ/uy4R1he0ln7aTRplUgv2wzfgctpHrsH+whU1s41f/3foY18cdNThpHnvYTSYEJ7SDcpRH/nTXL1157AZqdU59GeyGGVxjA8FHBH+9fuhDqBsdI9hEFzteuCY9KthBSKcuXyfXvl7fd6RFBbu+DvS4hgdl0cVmyJ908n2ZsK/RDwV7oR6+YR8djtjBHtfUQz7HVNe0ESHPS9QG9dH3vu+i15T3/lAX4uujDGXJx69C3Zeh79SFhAzxh+tU6aG/cMNPr8cY4pp0bIS6vm3woP7odZQj5cM+Jx82lKN8VLCLHwi+Ux4JfYiW4Rp72KUcvifv3aPT37thXZSjT7GVs0SjsAkDtbNYiRP9qyVAx9MxDKraFDPSAI9E87yOjiIgAiJQ7gR4OfqCxW1s4ZLWrqm8PL13l23Wv5m2y3KVFvZD1kVABERABERABERABERABERABEqFQIqJzlJxXX62OAE5UIEEFAipwE5Xk0VABEQgHYG5b+9kQyf0sClzq+zZN9u5c9LQH9B3q/3w+Gq75L5uLv3x19rZT09ba1XtyJWIgAiIgAiIgAiUFgF5KwIiIAIiIAIiIAIiIAKVQ0CBkMrpa7VUBEQgSiBxveDOSfaXa8cnzur/Iy8+63FDOK+vUX4px+63yWaPWVlHSPMt5dznTx39hfXsnGLTRa+sowiIgAiIgAiIgAiIgAiIgAiIgAgUAwH5IAIiUPEEFAip+CEgACJQmQQIfhDgGLhH/5QAfOAjNuwUQwZdMDqlnhJFQAREQAREoFQIyE8REAEREAEREAEREAEREAERqFQCCoRUas9XZrvVahFIEvjGT8a6AMcbHy1KpvmTyVdcZl07Vtkl/9/vfZKOIiACIiACImAH77mHXT1iRFnKRf/n/1iH1lrlp2FeeAKr1q62txd/kqUszlIvW3uF1/t4+bLCQ1QNIiAC2RDIWefZF+bZSWeNseUrv3DCOWk5G0pRYMFbH9qwkT82jimyKyapumaD/eCK6+zuaY9XTJtzbShjpJLGytjf3mVIrpwa0ufe5R7mfm5It6Xy8+1jJnv5HldwhS91thS/xtSrQEhjqKmMCIhAWRPYc5ddrF/Pnvb0hN+6bbFYOUJwpKwbrcaJgAiUIQE1Kd8Evr3nZzZu4NyylDEDXrb9em3LNzLZE4F6BD5autR+eMuN9v0J47OQ32Shk42d5tN5bv6rppBivW5Xggg0KwEmVRFfaUtM2FE/4n3QsfAEmOg96tSLbNCQc5OSj0la+hEpRAtaYmwWoh2yWf4EuAeQUm9peQdCSr135L8IiECLENi1e3d7et6/3IoRtsW6+8lZds4Jx9t/fe+7LeKPKhUBERABESgOAm22rLT26+eVp9S8brFtCoQUx0grby+2xeP2yYpltmj50rKUmo0by7sDfeti/qSIjnJFBJpI4LijB9uT90+wXj26NdFS/eKD9t/TZk273jjWz62clKoO7e0PN11t5408Ja+NJuBx5oXjbPzY823BnClO5sy42WY/9w+rrtmQ17pkrDQIHFfA+zlfBJrTR7579B1kpkBIvkZvBdrRk04V2OkV2uT7n5ljy1evtqMHDqxQAmp2qRCQnyIgAiIgAiIgAiLQLAT0x2CzYFYl6QmwtVKqJ/+ZEH941vOGkM82TNf//n/s4yXL7OKxE91KAcqyeoDthyZOnuHS2OJl5qy5ya2xfM1MpGMHwZafVMdGeI29EReMc1tqpfLhn6++VW9rLJ6uxi7Cua/T277057c438jHps+PHqk7XAkRtUV5JOov7acs9mgX+b6eqA/eJvnYQqjTl/crG0hH0MNuVHw92CcvWg4f0CEvKqSTj33E2yD93ulP2Y8uPNOYWPblCGiNv+Z8I/hCGj5RDqG/qZt07GA3FW/KMJYQyqFHfQjnpCHYwBY2sc24gg/iGZEflZvunF5vbHqdv/z1n8n+9/x9HvVRL4If+EMe6Vynagv5UcEuupTBVtRf3x7yEHhEbXDt9cJ82u3HGOfYxgZCvZSLCnq+DHm0C99Cu5xjA4E1daMbFfTCfNhQxgv50TJco0edcEHX+0o92CMNCcvjd9i+MJ/yCLYRymGftnGOTWyThx71ko8NfCGdI9cIeZQlHQnz+I4jLZXgY8iWctiiPuwi+JOqLOncAwh6lKvZHmB87Y33zbed9NA3yqGPhO1MVUdzpSkQ0lyky7CeWBm2SU0SAQh8umqVsSqE81A+XLo0vNR5MRLQH+XF2CvySQREQAREQAQKQUA2RUAEKpQAE23r1tfYy09Mck/+MwF+3W3TXBCCifDThx1jCCsDWH3w4x/+h+3et7fdNv4yp+9XI6xZu96WLl/l0lgJ0rVzx5REsUNdZE6b+QyHjJLKh/bt29UpwyTkZ8tWuTZgm3MmQb3Si/PetG+d/DXnG3779vl8f4TFDZMeSK6EwNYuvbq7VRBMQk5/dI6xMoI29Ond3QWDKOPLZzqGPhBQwN7Y8XfZg3eMc35NvmGMra/e4Lifc8l4G3HaEJdO/u1THnbpmeyTRyDAl8PHLx/4JWeTvFDwmUle2oAebXry2ZfcO1c+WPSZLf5shX310IFhkTrnUd+pk7q9UtjWkHeqvqRMOl/IQ15d8K49Pf1G+9tjt2dcBXTFBSMaHJu09ZX57xhtwDZjJ9qv4bhM1xbKppKX5y20K0d/x/XdqLNPNcYTvJGrf31HnX6l/70foS2CTjAlcOjT//7KG3bYwfu59r++8H1jvNB3jI9nn5+XbI/Xz+ZI3fiADWxRZ9iP6WwQBGC8wJJylF+2/PN06hYyZOwTqEg3xsm78pe3G+ywTR1836Q13kBG2B98V2Xqb3hMnvpY8p5k7DZgvk522E7KpvueSXUfdOjQ3tnyY53vHhL8WMS3xvQVNgopCoQUkq5si4AIlCSBF954w77Ud1fz7wU56/gh1qWqyp57bX6RtUfuRAm899kSu+vxR+22hx8qS5n1j5e173i003UtAiIgAiIgAiIgAiJQUQR4wv+yUcOTT/ozAR6Px23Zii9y4tAlEfg4+9tDM5YZ+vXDXT51HnPkQfb8S/NdkMElNvKDCWbsYA+7yDkjTjQmu5lUxexXBh9gCOe9e+xsnTtVcVpPCEQsWbrS3v/oU5eHLc+GSelDD9o3udUXbSVgQODAKTfwQf0VjrhdAAAQAElEQVSIV8PecccMdhPbpLHVzpGDB9jrb33ApX3zxKPdca/+faxzxw7JdJeY4gMOBIDe+3BxMvfS84Yn/U0mJk7wGd9pQ+LS6ey7Vz9jsp1r+rJ3z/RbmkV9Z8y888HiZLCGdiLYysSb/IZ8QYf+pC84b4zQHt/WjlXtre8uPczM3Nhj7BAAIPiAbcYoafDkmnYgnDfUFnTCPt17j11JcuLbCSsS6G90Ycl1VNDzTPEFn/ANve+cfnxy3DA+Dth3j+SYJT9boW58wBfKhHVynU6WrfzcPlmyLPkdQXl8SqcPP8TnZxrj0TxfprHHsH2eY7r+jvLItU7aiFAum7GCXlT8WGe8E6j0+VHfsu0rX75QRwVCCkVWdkVABIqawF+uHW/xWY/bwD362wmDv2wbH3s4+Q6Q/7znPrv36WfsvJOGOR3eD3Lzn2e6tKJulJwz9uUmCPLbB6ZaOcprH7xnioRooIuACFQsATVcBERABERABLYT4Alvvx0L74Zgdcf2rIIdwknifFQS2mvsJCST4Tf84iLjqXC2n0F4Etv7t8+e/fypEShggj2Z0IiT0F5YnK3Hhgy/3AYNOdeOOHm0e6I+zE91zsTpdT+70AWAKIfw9Lul+Y8+pq/RQ9imx6uS11AgDH3KIdhZu67aF8/5SH3YwBaC7ZyNNKHAjXc86FhTN6tTdpiK7zjNwxnjhXHjTaXrf/IJcPgAGEGUtetr7MD99yLLBXDYNgl/sx0frmCKD1hjB6EPsulHVjSwYgN9yjVmm6ZMY5xAVcdEwCqFu3lJSt/fZpn6JC+VN8FIY/qqCdVlVbQZAiH5vQmzapWURKBMCahZ+SPwjZ+MtdiwU5LS7tTTjQCIr2HUTRPT5nkdHUVABERABEQgHwTGP9rJhk7okZS5b++UNMt5mHfF/V2semMyWyciIAIRAjzssuDOSZHUHZfHH3KIfTL1Hiec78jRmQiIQKkQIAgy6soJye2g2OaGCdtC++9XXeSrntAeT6xHJ3SzrYen29mCiW15otvbvBestiBQwAR+tnZT6YX2wvyvDD7A2BoHH7ww+RzqpDonkMO2ZJShHx985Fm33VUq3d369ja2HULXC1sHMQHfr0/P5OqQVGVJYws1X44j9VI/eblKOl9ytdNYffqZNnhhCzgCS2b53cSe8cK4se3/pet/sqmfVU6sBGClzknHHelW7rCqgWANqwXwl3HCeKFMY6Sx/chYoX6ElVLZbKkV+ofP+E55L36MsyqL1Vmhfj7P0/e3WaY+yacPjbHV2L5qTF3ZlmmGQEh+b8JsGyY9ERABERABERABERCBkiZQEc6vWFv7u/LDl6202WNW2q3f/cJ+/0yVLVzS2rX/oxWt7RdnrHV56JB481OdOEhEQAQCAmxpympfVvoGyXVOCXzcM+ZK69ezZ510XYiACJQeAQIfrKLAc4IITNhyjuyzZz9jyyUmYLnmSW2e2A4DD6TnImxZxXsZ/DYwrOYIJz+nPjTbwkBG1IewLj9hjD3s4ue9058yJmdznZin/C13zwjNJ8/Zloh3MRA4IhEfCRgQOOAp/1gsZstW1r4ngXcFIOilk6g9Vp4gPPUPC/9uAMqTjnCeTmj3xMkz3GqBdDo+HZ9ZbRBOXtOuBx5+xm2RRr/w1HxYJ2x47wr14DurZijjbcINHX+d7hjty0y+pLKBD0iqvFzHph874bscaF+2HFP5kC6NdjJeGDfowI7xBEuuUwnbo7E91hPPvFjvnS1wpAwBA8YL51FpaFxSd2P6kXGBROvL9jrTGCcPO36LLI6sHiENod3++4i+4l4nPRtpqL/hEW6pRxAqG7uN0QnbkU15fGtMX2Vjuyk6zRAIaYp7pV32g88+tXeXLG6CFG/Z9z9dUtqdk6X3Ws+UJSipiYAIiIAIiIAINIpAz85xG3vaOqva/g7Vnp23OTsr1tUGQs4+usaO3W+TS0Pn8D032/K1rbQqxBHRhwjsIOBX8z497187EiNnt/6/P7SFH39imXQiRXQpAs1IQFVlS4AVEIcdvJ/5bW6uvfV+IzDiyzMZy0QrW/CwHQ/pfqKcbXEybb+Ebig8yU4Ztn1in37/BDhHAhekk79Lr+513uMR9WHDhrrLOXk63ZfHT56WH3/N+WHVWZ0zkf6v1981fEDGjr/L2CqLgAo+htsBMRnLk+VMrpJ/9cUjzbfvz0/8NflOknQVR+1RF8EobN1761gjsIMPCBP1foI4nT38WLp8ldtKizL0508uOSv5LomwHLr4ThvQRVgVdOCAvZ0avrGiBJ/IQ+gbJmMpS/74secnxwz52MJ3ZyDDR7QvUc3kC/leCLQwUY0fPi084luuY5Oxw1ikfbSD8dOpYwcXEAptN/Uc364Lti6jf2AIy3S24cm7W7p0qjICKehhJ2zjN78/1ninD3lRoXymcUnd+IAvtB3Jph8Zp+HYoMzPLj8nWn3aa/xKN8bJC30m0LF7395JWyPPON6d008njPiRHTLoS+46249M/Q0P/z0Ci2xtNkYveh/U1GzIaAbfGtNXGY3mIVOBkDxATGfi2gem2n+M/2VZys/v+YOtXLsmXdPLJr32Gc2yaY4aIgIiIALFTUDeiYAI2MJP29r6ja2sZ6etKWl8tLK19UoESwiKpFRQogiIQEoCfrsstkdNqaBEERCBkiJA0MBvTzNr2vWGECChEUxMsu0R+X7LICbluEaYWEQ3LEM5dChHeYRz9L1QDj0voQ+XjRpu0+8c57YCIj8sjw+HHbJ/HR/RCctzThpCPZRhAplrfA1tk+YFHXS9j2yRhb7Px5bPQw99n0d7fd4tv7rUyCeNfMpxHer7dF8mrCtsL/mwI40yoWAPu9gnnXaj78XXT15UfFmvG9aPLu0mzedzDO1xTpoX6qYcvuBThw7tuXSBmJA37aA9lEMPPxDOSUOol/q9LnVhjG2l9ttnt4xBJnSxgeALdsKx6etCD5sIeuh74dqn4xdluMZW2BbSQoEB4tOoIyzv2+PrId/rpjtiL7SBHuW8DVjRPu8z+gh6SKgbHZfRfGyGZcn3gh36jTbAgXrRR6L++TIc8StVPnawR3mEc9IoQ12kIQSPSPNCX2CPPHzgu4Jr0ikX2qEtiC/rj/hEeS9c+zz0fTrnoT2vwxEGcOfINTa8H1yTnmms0FZsUxfl+u/Wx7imDZRHqB+7nCPkoe+FfNKT0oiTpj6wrkBII6BnW2RVIlDw6aqVVo6yYvXqbDFITwREQATKhkC6fcfPOeF4W/PnPxlbciBsz1E2jVZDREAEmoUAW2GdMbG7/XJmZ7vq5HU2oG/9QAjvC1mwuI1dMGR9s/ikSkSgXAjw85u2DLpgNIeiETkiAiIgAiJQPAQK8SAs78o4ZOCX8r5ao3ioyRMRaF4CTb1PFQhp3v5SbSIgAiIgAjsIlMwZgQ0CHKn2HWe/8d/+4Fx76a23LTbsFPvV1PvtzH/7mv3X975bMu2ToyIgAi1PgMDHzMtW2bQfrnLvCCHoEXrF9e+e6GQ//+Za69m5qc9ChZZ1LgLlT2DX7t1t4B79kw8s8POc94TwvhB+jpc/AbVQBERABESgJQjwdDzSEnUXYZ0V4ZJfOcFqiIpocIk1UoGQEuswuSsCIiACItD8BDLtOz7kkIOsXdu29sfZf3GOzXl1vq2prrajBw501/oQAREQgVwIEOQY1G+L8ZJ0X84HQa4dsTrlShGvp2OxE5B/LUVg0AWj3cMKPLCA8I6QxStW2Pcm3GDPvPpqS7mlekVABERABERABERABJqRgAIhzQhbVYlAxRMQABEoQwJ9e/RwgRDfNCZUVq+vNp4+9Wk6ioAIiEA6AmyJdfOsqmQ21y+9v5Pt0bN2ayyCIL9/psom/+BzBUGSlHQiAiIgAiIgAiJQ9ATkoAiIgAgUGQEFQoqsQ+SOCIiACIhA6RFgBcjiFStLz3F5LAIiUFAC2Rjv32OrfbSyjQ2d0MPJJfd1c+8IOXa/Ta74/761ky1b09pG/r67y0ePd4ksXNLa5etDBESglkC4jaXfBou02lx9ioAIiIAIiIAIiIAIVDoBBUJKbASw5/zGxx5O7m/Ly3l5Sa9vBueksZc9suDOST6rJY6qUwREQAQqgkCXqirr17NHRbRVjRQBEcgvgap2ZjedtcZmj1mZFB8Eoaaxp61Lpnsd3iXCO0XIl4iACNQS8NtYsvWVF9Jqc+t+fuMnY223s7+nbbHqYtGVCDSVQNGUr67ZYD+44jobNORcd+R67G/vctcnnTXGZs6aaxyXr/yiRXx+9oV5LVp/tNGwQaLp5XRN+5BUbVrw1oc2bOSPjWOq/HRpLdGPjGXG9t3THk/nltKLnADjrDHjLWxWOPY0JkIy9c+jfBQIqc+oqFP69uhhf319QXKP24+XrzBe0stL/hDO/Qt7TxhzjXXtWGV/uXZ8UbdJzomACIhAKRNYsnKlbdy8OdkEvov57v101apkmk4qhYDaKQIiIAIiIAIiIAIi0NIEps18xrnw8hOT7A83XW0vznvTXpn/js2ZcbM9ef8E69q5o8tvjg+CLQRdmLhsjvpUh7mAxrBGBDbKjR3BEoImTAQ3d9tasu5UbW1JfwjAIan8Ulp2BOCHZKedWSu/gZDMdSk3DwR4qoknmLypv735pnXZ/iQyTyNz/uHSpS5b+9Q7DPoQAREQgYISmPPqfCMQ8v2h33D1DDnkIPe9/MIbb7hrfYiACIiACIiACIhAWRJQo0SgSAm89+Fi69O7u1V1aO88fP+jT63vLj2sY1Xt9XFHD3YBkV49urn85v5o6fqbu73FXt+g/fe0WdOuN465+Kp+zIWWdD0Bxlljxpsvr2PTCCgQ0jR+LV56z112Mb83/b1PP2OsBjnvpGHGfrhsk9W7W1ebMXdui/spB0RABESglAnwncp2gycM/rKF+47TJoLO1/xhih25/35u28Kfn32WPfi/f7X/vOc+siUiIAIiIAIiIAIiIAIiIAJ5JsAT3mx95cWvuOCp4YdnPW8IeaOvvtFuvONBtyrkiJNHG/noskqD1RoI5xMnz7CjTr3IydwX57utq9DFBsKT9S/NW+jy/XX4pH2oix22v6HJN9053T5esswuHjvRbc2F32H96HgfsIuQTzqC3Ut/fovb4ou80Db5UcEnfEUXobzX4Zw0hHOfHh69L1Ef8Bs9jiMuGGcIdhB0scc5wjW6COm5+I99bHgJbcGU9vs8bFNHKLT/hkkP2CefLrczLxznmHsb66prUnLE7rBgBQnXDdVDndhl7MCM60y+k+8Ffcr5dtBf+O3zo8dQnzHMCievE+Zhz9uiDZOnPpYc99SHLunZtC2dfdpMHraw6e+bbOqmv8Kx8JuJ99Xbkgz72MU+9UQFG9SF0A7agw7HsA/hCQvskZeKBeVCe5yThtCXjHGEuhBsocM5wjW6CHXgD+kIeqSjw3cRQjo+/fPVt1K2m3wEO9ijPHZIQ8J08lIJibaAbAAAEABJREFU3OBHvT4fWyEbn+6P5GObOryE5WHh0/EftpTFt7A/sYEt8hD00PdlsUO699GPHV+OfK/L0fvAEX4I6djENsI5aQjlsY/4OkiP3jMKhECoRIX3hTDx9odZTyX3t+UJ5LXV1Xbmv33N7hlzlS37YrUm40q0f+W2CIhA8RBgNZ7fb9wfSfMeEoju8q1/T25bGOZ5HR1FQAREQAREoMQJyP0WJhBv4fpVvQgUCwEmwNatrzG2vlowZ4r96MIz7brbphmTX+OvOd9OH3aME/ImXfcjl/+VwQc4ffJTtePVBe/a09NvtL89drvt/6XdkyoLEvbZUmvJ0pU26Z6HnY6/9hPS1MsKFHSR444ZbEzG4+cVF4yw3fv2ttvGX2bknTfylKRtTtC5+td32IjThrj8B+8YZ2PH32VM/pGPvJwIwFw5+jsuf9TZpyZtkxcKtgi4hL4cMnAfI51Jws+WrXIM4MY5E5lh+WzPP0kEdsZdea7zB/bUOfTrhyev753+lKvT28vF/3T9ShtgOn7s+a4e2rBLr+516qE+VgHBarddexksYX7c0YPJsmz8yLYeZzD4YAL4yWdfctuvUSd1L1v+eaCx4/T1tz6wqy8e6drhx5Lfzm2HVu0Z/jA+Dj1oX6dPuxnLtblm6Wyx6oCxgi5l2BKOFVCvL3zfJt8wxtnCx2efn1dnrHm7HBnX51wyvs7YvH3Kw+4+Ix/x9w11cE070tVNftgHP73su3bYwfvZ31+p3UmBtjJ2uBfwFf1Q8Ccc2+F9FupFz9P509A9kcs4T8eVsRd+H7FVX/v27eq4yL3OPU9/MHbon/XVGxznXNsLN/jNfu4fyTqmPjTbcYZDMnH7CUyv/OXtxlihbsYj31fbsw1G0x+dkxzX+EMf+/ywP7HBPUo/InwvoO/tcn9wn/iyfuzwnbtX/z6W7t5PxRAb6exTd6Z7RoEQ6JWgEAS5+swRdZ46ZgXID0/9P3bzn2caE3L+HSEL7pxk+k8ERCAfBGRDBESgIARiBbEqoyIgAiIgAiJQVgT047KsulONaQIBJrsvGzU8ufXVVw8daPF43JataPzLz88ZcWLSnneNyX3OO1a1d1trHXPkQU7HX7PlFvlMPl563nBOnVCOwAmTmS4hw8cHiz6zxZ+tMNqAGpOVTPCGE5lck07+3nvsyiGleFtnf3toMv87px/vzp9/ab55/+FHe3lvChOhTiGHjwP23cOYuKQI/jBxeuD+e3FpXEfbnq3/+JWuX2GJXc88qusqb+AjGz/q1mOuv0Of0lWxbOXnxsS5H4P0l2cfLcPELkI6Y4cgx3sfLuaynqTq01AJOwhpDdlCB5/wjXP6kL70TEkLhSAL19888WgOrs87d+zggi8uIfHBOKIvECa9E0kZ/4V9gCJjlQlyxiFtXZsIcPr6yA+F9jX2PgvtcM5keUP3BGxghD7jOtM4z4Ur9kLhXg+50D9HDh5gjW0v/N75YLF7Vw5cOYdzWKc/j/axT+foGRFYwRfS+G6DG3lch37DiDSEvuR7zddL+X336pcMeqHjxw7njJ/wPuP7MNN3eib70Tzsh6JASEijRM59EIQnkMOnjvft19e14J3FS9yR7VoWfvyJde1YZccfcohL04cIiIAIiIAIFB0BPeJadF0ih0TAEdCHCIiACIiACBQpAZ4sZksVtj5hC6Q1a9e3jKfbf4/lqW58QXhSORdnunTuaL177nhfyT579rPG/he1FdoJJyp799jZOneqCrOL4jxdvzKResMvLjK2OBo05FxDYJ5vpxtbD8EInohnLOIb2xMxCZ3OP1bjoIew5U86PdIz9Sn5udhiAttvJxTdMghbUWFbtyHDL3e8s9GPlm/omkCDD66wMoTJcvogXTn6HGZIrvdZKpv5uidy5Rr1Jd0935j2wg+O8CTQAV84R+v01+H7k3xaeGRrQXgjuTDnO9nfD5RtaJynu/dDX8LzTPYz3TMKhIQUS+CcIMjl3zrDrntwuoVBEFwnANKubVvzL+wl+DFg991s9frq5NZZ6EmyJyBNERABERABERABERABERABERABERCB4iHAhNmoKyeY3yaJLWWY+Gqqh40qHzO3tVC4tQ3bYOViiwk9v5KAculWB5DXkERthfrhk/+sYFi7rjrMbvHzhvqVJ+XZRoetdmDst0PLt+ONrYdtz/ANYZUH74dJ5RuBC7YmYzspdNk6KZWeT8vUp7nYYrKeiWxWblAv9bN1lq8n1ZF89ND3QtAnlW5j0lgJwMqAa2+93x585FnzKwhS2SIo0JT7LJXNfNwTjeEa9SXVPd+U9sIRnnCFL5yjdfprVlqxEspfR4/ca77vObK9VyZ7vvxufXsbW21Rxgv3iM8Pjw3d+6GuP89kP9M9o0CIJ1gix6MHDrTOVVXGy3jjsx53L+blOPmKy4wVImyL9bUDB7n0pyf81gVBBl0wukRaJzdFQAREQAREQARakICqFgEREAEREAEREIGSIEDgg1UNOMukPhNfnLeUdO3SKbmqI5xcjW6jFfWPJ7X79elp7ONPHhOCvLeBLWi4zkWitqprNhgvJMYG22Kx1z+rFEjnXQxM1vP0OPleov56f3x+oY/p+hW/b7l7RlbVs7omFovZspWp39GRyUgu9YR2mLRGwrRM5wQjmEymLwiKpNP1fcrT/eiw7c+b73zEaVLS2WK1Q6pJbr/6gMlv8pOGIidsd0Z++E4I2ohEVOtdpqu7nmIigXpisZhxH9DeRFLaf+nus2if8/4exBuK+gP7bO8Jb6OhYzqupNPH9HUqG9zr3PPca+TDF+E8XXvJyyRwhGcsFjP4ptP1eawcQYcjq4A494zCgCNt4DuFIzrphPpZiRIGA2nfAw8/k66Ipbv3KRBlmMk+ebQ93T2jQAhEk1L8J9/4yViLDTulnvjVIf95z33W7tTTk/kKghR/n8pDERABERABERABERABERABERCB5ibQcH3xhlWk0QIEeGL/sIP3M7/tCk89M4nWAq64Kr8y+ABjexm/hdATz7zo0vlgMpEnsv32MndPe5zkpJB/3c8uNN7XwfYxtImVLscdPdhy/S9qi62Mli5f5d5zwZPYBD7wkXQmz8dfc369KrBx5ejvJLegumHSA3bE4AH19AqRkKlfCdD86/V33RZNcGJlAFtlRQM5+EUa7zVg9QO6flKZvIYkl3pCWwTl8In6ECa+f3b5OaFK8pyn9Zn4Ru+EET9y74ixNP9F+2PcDVOMJ+G9eiZb4bg86awxRuAjHIvf/P5Y924dbyt6hOO9t441Amj4ijAp7ifPo/rhdbRuAkxhfngOc+4ffKO9YV54HtrEl/A+w9erLx5pvs///MRfDX1fnnPqYPzDAn+yvSe8jXRHfMZ3f49HufLODgJK3HdsS7Zhw8Y6prjXw23VGEeMp9DnaHvrGEhxgU/c49wHsEmh4pLIC7kRIB24355G/SjACBtwwwfa0KljB/edQn46oX5WknAfUA5hFd+BA/ZOWSTTvU+BKEPS0tmn7vA7LHrPKBACPYkIiIAIiIAIVCIBtVkEREAEREAEREAERCAtgVjaHGW0NAEm8f12K7OmXW8Ik2n4RR7COcJkXridCxOPT94/wb2MmIlAzklDF4mmMbFGeeyQn+7a+/Onu35p2MQO+tj2edjgOsxHj2uvQz7lENqBcI6Qhy/4wHVUorbCspz7Ojj3ZTlH/DUc/RZU1HXLry41/CafI2m+fvzBd+olP3qNXYQ8hPywPGmhoOt9pE8R/KE+yvk8/CM9LBue46fXpU7sIl6HNOxhFzuNqQcbvu3YwCdfp7ft6wuPoS5lqDv0LdTlPNSffuc4Q2hfNC9qi7bhBz55P/GZa8Tre1vYiwr9Sln0Ec5JQzjHni9DG7ytVHWTj3h9f2SVS6dOHeoELnxeeAxt4kum+4wxS9u9f2FZ/MZ/bOMPthDOSUNoB+UpxzV2wnKprrGBRLlSF2XJw+Zhh+xf5/sK+9RHPkJ5+py60ScNCdsb1u/1sIEthEAPQQgCCFwnJcUJtrCPEEBAhRU2HBHskueFa9LhhXCOYAd/8Ydrjlz7cr5dngf66HnBltflnkDgQL4vQz42sY1wThri7aNPOa5J535BvN8KhEBIIgIiIAIlRmBzrI19vttoW7XbxWUpm9p0N4vrT88SG5ZyVwREQAREQASKmoCcE4FaAvods5aDPouNgFYgFVuPyJ/mIMC2cIcM/FKDqwyaw5dyqeORp14wVoQQQGioTbxnZtCQc91qK1ZtjLvyXBckbqhcqeYrEFKqPSe/RUAEKprAonhru+3z5+zWz5/JRUpG93XbYhbTnwKm/0RABERABERABERABPJMQL9j5hmozOWJgEJ0eQIpM55ASRxZCeCf1i8Jh0vASXjCNRtX0WPlBMIqClZTZFOuVHUUCCnVnpPfIiAClU0gts3WbFpmqzctLUvZum1TZfevWi8CIiACIpAHAjIhAiIgAs1IQLPYzQhbVYmACIiACIhA7gQUCMmdmUqIQOkQkKciIAIiIAIiIAIiIAIiIAIiIAKFJ6CFJoVnrBoyE1CuCIiACIhARgIKhGTEo0wREAEREAERKH0C/F1e3kLrSr+fiqkFu3bvYQP32LPkJBuf9+nbz2IxPbZbTONNvoiACIiACIhALgSWr/zCTjprjD37wrxciklXBERABESgwgkoEFJeA0CtEQEREAEREIF6BJZ9scru+L+P2PUPTitLmfHX50yhkHrd3ugEWH73iN3sznOOKUv5z1MPsh7ttjSajwqKgAiIgAiIQJEQkBt5IOCDKkedepEteOtD8//dPe1xG/vbu/yljiIgAiIgAmVAQIGQMuhENUEEREAEREAEMhHYtGmLTX36KZs4809lJrXtefa1VzM1X3k5EmCtxGFtn7NjNtxQlvKVLfdZp3a0MkcwUhcBERABERABEShLAp07VdkRgwfY1Idml2X71CgREAERKA8CTW+FAiFNZygLIiACIlA2BJbNNZv/mx3CtW9c9eK4vfG7HXkLb43b5jU8O+41dBQBERABERABERABESgYARkWARGoQ2D2c/+wQUPOdfKDK66z6poN5ld4hNtmsdJj2Mgf11nxUcdQ4uJbJ3/N3vlgcVodb9fXF9rPlEfdrDbx5cJVJtjw6Wz1hZ2EK8ZqFNpz6c9vcW2jDHZow8TJM1wa+gvf+chtEeZtUAYG2JCIgAiIgAjUJ6BASH0mShEBERCBiiSwdWPcNqyI24BL4nbQT80dV82L2+qFtTg2r41Zz6+ayyO/anezRTNjRrlajcJ/qgYREAEREAEREAEREAEREAER8AQWzJliLz8xyV1Om/mM9erRzUacNsQIkrjExAcrPQ47eD8btP+eiavU/3r32NlOOu7IlKtCCFCcc8l4Z5f6HrxjnN0+5WEXdCHwcPWv76iTN3b8Xe79JeTdMOkBGz/2fKMcfu7Sq7sL2BAEQQ9b5OHzTXdOT6VFyscAABAASURBVDr34rw3jeAMeeOvOd+lr1m73pYuX+VsPXn/BPs0cX71xSPd9ZwZN9uSpSsNBk5ZHyJQBgTUBBHINwEFQvJNVPZEQAREoEQJtG4Xs/5nxKxtl9otY1q1M2vbNWYbV9Q2qOsAs97H1p7z2XVAzDavjtu2jVxJRMDsL9eOt/isx91RPERABERABJpMQAYqiMDSzz+3/339NXv2tXllKS+/tdDiif8rqEvV1GYgMPTrh7taqjq0t2OOPMief2m+CzJ888Sjk6s7CGKw0uPsbw91upk+wnKh3utvfeAuyedkr/59rHPHDkb6B4s+s8WfrbCvHjqQLBdsOe6YwS4Qs756gwtOvP/Rpy4PPy8bNdw4EqhBzwdnKI+f+IvyVwYfYAjnXrp07mhhO447erAh5BMAOvSgfe29DxdzKREBERABEUhBoFWKNCWJgAiIQJEQkBstSYAAyMZlZu16pvaCfAIlBExSayi1Egm88dEi27V7d/tk6j12/CGHVCICtVkEREAEREAEciawpqbafnHP3TZ64g1lKU/84+85M1EBEciFwN577JpUJyiw71797O+vvOGCFQQtCF4kFdKcUC7dqpCPlyyzIcMvd9tSHXHyaGPFhjdDgKJ3z27+0vbZs587x94Nv7jIJk99zAZt38KLlSAuM/Hx8Kznk+lnXjjO1q6rTqTm9o9ts7xt7OVWuti05Y8IiIAIFJaAAiGF5SvrIiACIlByBHjvB+//eG9KzG2F1XVA/SbwvpBV/zLb9YS4sZKkvoZSKpnAoAtG25P/+KfNHPdzO+eE4ysZhdoeEFi4pLWdMbG7DZ3Qw8nZk7rZirW1K9C82tQXOrg8dK64v4tVb/Q5FXJUM0VABCqaQPWGjbaupqYsZdOWLRXdt2p84Qn4VRe+JlZOPPjIs3btrffbOSNOdKswfF6mI6s+WJnx6hvv1lFjdQZbW7FVlRe/GoMtq5at+CKpH67KYMXH3x673W1fddv4y+y626a5LbVQ/tGFZ7p0b4/trgiekJeNEAT5bNkqtzUYNk4fdkw2xaQjAiIgAhVLQIGQiu364my4vBIBEWh5AmyNNeCSmA28Km5r3zdbNreuTwRBPpwWs12/YVbVr+4kZl1NXVUygVE3TbSb/zzTJl9xmZNKZqG21xJYsa61jTiixmaPWelkUL8t9ptHOyeDHXPf3skef62dTfvhKpffq/M2u/mpTrWF9SkCIiACIiACIlB2BPLVILaTmv7onDoBD1aA9OvT02KxmB24/15ZV0UgglUhT//1lWQZykffv8HKDsTXw3tIKLDgrQ/t2efnGdt24dctd88guZ6Qz0oR9H0mupTx19kc+/Tu7oI8vI+EoEhYhkDJD664zm0XFqbrXAREQAQqlYACIZXa82q3CIiACDRAgJUenfc227AintT0QZB+p5qlWimSVNRJxRBgxceaP//JvRvkhMFftoF79HfnvCvk52efZTu1bWtn/tvXtDIk9YioqNRj99tkZx9dk2zzv+2/yZataWXVm2oDqv/71k52ysEbrWfn2u8c8hcsblNv1UjSgE5EQAREQAREQAQqmsDFYye6raXYsmrEaUOS78sACu/hIEhAOsEN0rIVVoXs3rd3Up3y99461gi2+G2oWNlBgIR6rvvZhfbK/HecL2xxNX7s+c6XjlXt7V+vv+vSKTd2/F3GVlnYYzUJeuiThxDIIM+y/I9VLwRdKHvCiB+5d5WY/hMBERABEUhLoIUDIWn9UoYIiIAIiEAzE2BLrEUz47Z1Y+0kJNer5sWtfc/aSUqCIIv+HLM9R8YVBGnmvinm6u59+hnr8q1/t9iwU+zpef+yNz5a5M659kI+esXcDvnW/AQ+WtHaenfZZlU7xd2qkOVr6/5a2rPTVufUiki6S9SHCIiACIhACRKQyyKQHwIEC9hGiu2gvJw38pQ6xllZQWCBoEadjMgFtqbfOc7YwspnkYb98dec75PMp/n6yCcNBY5c+7zjjh5Mslup8Yebrk5uf8UWWWE96PkyHH19tIVyBFmcocQH5WZNu76On6Rhk7Icyfc2EkWM86gd0iUiIAIiUKkE6v7FWakU1G4REAEREAFjSywwvPG7mM3/jdnCW2PWfXDMeh9Lqtm6D2K2ebXZe1Nq89FBVi+szddnFgSkIgIi4AgsXNLabYN14ZD1VtXOJbmPPXrWBj/chT5EQAREQATyRuC/vvddW/7gtDorNI8/5BD7ZOo9yZWcrOZkS8u8VSpDItCCBB556gVjRQhBihZ0Q1WLgAhUMgG1vegIKBBSdF0ih0RABESg5Qj0PyNmB/3UkuKDIHjEeZjnz7VFFnQkEPjGT8baoAtGcyoRgbQECIL8ZHpX++Hx1Tagb93AB6tE0hZUhgiIQMkRkMMtT8BvYcl2le3atq3jUL+ePWz1+mo7Ycw1bjXn3U/OcoESgiZ1FHUhAiVIgFUVrIgoQdflsgiIgAiIQIEIKBBSILAyKwIiIAJmJggiIAIiIAIBAR8EuerkdcY7Q3wWq0J6dd7mL91xxbrW7tgzku4S9SECIiACIpAVAbamZIvKX0293zZu3lynDHk8wPDMq6+69Odem+90+vbo4a71IQIiIAIikBMBKYuACBQ5AQVCiryD5J4IiIAIiIAIiEBhCLRrs5P9/D+G2/+Mubws5WdnDrf27eo+/VsYktlZJQjyq0c627UjVtcJgvjSvBz98dfaJV+OzsvTB/Xbknx5utfTsZgJyDcREIFSJrBvv77O/SUrV7qjPkRABERABERABESgnAgoEFJOvam2tDwBeSACIiACIlAyBFrHNtpJre+1EfbrspST2t5rsW2biqY//vnhTrZsTWu75L5uNnRCj6TMfXsn5yMrRE45eKON/H13l7d8bSu7/MR1Lk8fIiACIiAChSXA+0J+MOxEe+mtt+0/77mvsJXJugiUCwG1QwREQAREoKQIKBBSUt0lZ0VABERABERABPJJoJXVWKtt68pT4hvyiSqlrVwSzz66xmaPWVlPCIB4O6HOTWetsap2PkdHERABERCBQhEgCHLPmCvd+0J431eh6pFdERABERABERABEWhJAgqENI2+SouACIiACIiACIiACIiACIiACIhASRIIgyC8L6QkG9F8TqsmERABERABERCBEiagQEgJd55cFwEREIGyIxBvWotatWptB++9jx22735lKT27dm0UoFgsZoP23CsPTIqT6+69eqfk0sThlNKmEkVABERABESgXAj4IMjCjz8xBUFaplf1u0rLcFetIiACIiAC2RAoPx0FQsqvT9UiERABEShdArGmuX7QLtvsz9/bzeZc0L8sZfQRHRoFqEvXbfaDkXvZVT8cUJbyf4buYqmGTqq0RgFUIREQgeImoJu9uPunlL0rA9/POeF4W/PnP9nPzz7LeKDinjFX2YI7J7mWDTnkIOvVtaudMPjLFp/1eFJ8vlPSR0EJ6OuroHhlXAREQAREQATqEFAgpA4OXYiACIiACIQESu08tnWTdVo+3Totva8sZaeadxvdJfNXzbKXls8oS/lo3Twr9icqxz/ayYZO6OHkivu7WPXGRnelCoqACEQJFPsXQNRfXYtAMxK49+lnrMu3/t1iw05Jil/98Z/33GftTj09me51fH4zuqmqREAEREAEioCAXBCBciegQEi597DaJwIiIAIiIAIi0KIEpr7QwZavbWUPX7bSCc7c/FQnDhIREIHiIiBvmkpAj7c3laDKi4AIiIAI5IOAHpLIB0XZEIGyI6BASNl1qRokAk0hoLIiIAIiIAL5JLBibcwef62dDT98g1W1MyecL1jcxsjLZ12yJQIiIAItTkATTy3eBXJABERABLInUMaaCsyXceeqaSLQeAIKhDSenUqKgAiIgAiIgAiIQM4Eenba6sqsWKtfwxyIlvxQ3SIgAiIgAiIgAiIgAiIgAiIgAhVBQH+BV0Q3p2+kckRABERABERABApHoGfnuA3qt8X+962dCleJLIuACIiACIiACIhAFgSkIgIiIAIiIAKVTECBkErufbVdBERABEQgJwK864GXXkcLscXR2ZO6uRdh80LsuW9XxqT36oVm83+zQ967x2zrxtp9UaoXx+2N3+3I83qhTpRjM1y3SBUXDFlvbIXF2EAuua+b86Nn523uqA8RyJVA7V2Waynpi4AIiIAIiIAIiIAIiIAIiEDFEKjXUAVC6iFRggiIgAiIgAjUJUBggwnsKXOr6mYkrqo3mv3m0c52ysEbbfaYlXbrd7+w3z9TZQuXtE7klve/jSvM+g83O+inZgOvqp2aXfxEbZur+sUSabV55CNdB8Wt895mrdvFapUq5LNn57hNHf2FGx+MkV+csdatEiG9QhComXkmUFl3UJ7hyZwIVBQBNVYEREAEREAEREAERMATUCDEk9BRBERABESg/AjkqUXH7rfJTWKfe2x1PYuLVra29RtjNuygDS6vf4+t1rvLNvvnhzu563L+6H2sWdcBtS0kuEGQY/OaWHJVSG1O7ScrRDYuj9nOB9cGTGpTK++TABmBsm8fVlN5jVeLRUAEREAEREAEREAEREAERKBQBGRXBBogoEBIA4CULQIiIAIiIAKZCKxYVxsI8TpV7cx6dd5mHyUCJD6tUo4bVsStbZd4yhUfK14263qAJfIr71l2gh9nTOzutk771SOdbeLZq21A362VMizUzuYiUHm3VnORLal65KwIiIAIiIAIiIAIiIAIiEBqAq1SJytVBERABEqSgJwWgRYhwAqQqp0qe6UD7wup/ths1+Prd0GlrwYh6DHzslVuVRFbZBXXlliaPa8/Yks0pbK/gkq00+S2CIiACIiACIhAEwioqAiIgAjkRECBkJxwSVkEREAEREAE6hNYtqaVVW+q3AllgiCLHzPr/22rt+Jj68a4ffp0rGJXg9QfLcWWotnzYuuR3PyRtgiIgAiIgAiIQGkS0O9gpdlv8loERKCUCbQqZefluwiYEFQEAaaXy1UqogPLvJE9O221ju12/CFTvdFs+dpWtkePytj6yAdB9hwZt6p+3Kl1O3zdBzHbvDpe8e8GqUtFVyIgAiIgAvzEKEdRz4qACBSQQFmZ5huwrBqkxoiACIhA0RNQIKTou0gOikBlE9i3T1d78CdXla3069a+sju4DFrPy9EJhMyaX9uXvDydFSKH7bmpDFqXuQkEQT6dHbd9L4inDIKwGmTFS2bdB8fqrRTJbFm56QgoXQREQARKnUDvjq3tj5dfXLa/2x2zb/9EF+14QCJxUVb/NHVbVt2pxjSRwN3THrdBQ861H1xxnVXXbGiitfIvvuCtD+2oUy9ywnkhWozdQtdRCL8z2dQ4y0SndPIYm8NG/tg4NrfX1NlSdReyrWN/e5chqeogHYnmlVogJOq/rkVABEqOQG5/Ph3cZZn9+5arCiqn1Vxlx64ck6yD6xPX/jh5Xcj6B3RdU3I9WIkOz317Jxs6oYdaO1ssAAAQAElEQVRNmVtlz77Zzp2TBouqdmY/PW2tPf5abfol93WzHx5fbbwXgvxyltUL47Z5TcwW3hqz+b8xJ2/8zox3gtDulS9rNQgcJCIgAiIgAjsI7N11g52x9efN8ntWIX+HS2f7yC4LE43N7ffdRIGS+dfMIZ6S4SJHm5cAQQeCDwQhnn1hXrJyzkk76awxtnzlF8l0nTSeABzhSXCBydRsLfnJ+1QTkdnaaCk9P44YY4y1QvmBbepgzFJnoeopJbtwgAdc4NMSvjd1zON/VLiHPv9ibUs0R3VGCCgQEgGiSxEQgUITKL4/n9ZuiNnMf7ZPTHDv5GTW/HZ2z/MdbOPmQrOQ/VIhcOx+m9yLrmePWZk8kub95+XXvATb54d5Xqdxx+Iu1f+MmB30U6sjA6+y5OqQ3seaDbgkptUgxd2N8k4EREAEREAEREAEREAECk5g0P572t8eu90J5wWvsEwqOG/kKbZgzhT7w01XW1WH2l0IyqRpZdUM30/01Y8uPNO+MvgAe/mJSa7vnrx/gu3crXMW7S2MCvfbrGnXG8fC1FA6VhUIKZ2+kqciIAIFJNCn6zY7aLfNTo7ed5ON/EqNtYoVX9CmgAhkWgREQAREQAREQARaloBqFwEREIE8EvBPdodPZ0dXNvgn0EMdVjOkcoMn1HlS3eveeMeD9dRYNUEdXocnwfHDK0ZtoDf2t3e5FSzoco1P6JPONUeu8YtrfLj057e4bbm4Rh/hHPH6lEF8OfKQMJ9z0rCHXc7xn3bg9zmXjLePlyyzNeuq7cwLxyW3tfLl0PdCPb4+z+bhWc87P9HHJrYRztHlyLW3AQPqJY8j1+RNnDzD1c05fsIRnUzyl7/+09VNGepHN7QJM9LI8zqkXTx2Isn24rw37YiTR6fd+syXS8XOGUh8pGsf/lMPdSTUjHN8oH6uQ4Ereb7d3ibc4EIegj9huei5t4MuAlt4oEdZ0rygSzrCOenUT1s5x8906ZQhHz0vlKXN5CHRfNryx+lPOg7kwyUT+2h56sEfyvq2DBv54+SYwT7cyEc4J41yiGcBj3Rj3tcZbQv2cpFU49KX93WEPpFH26jX86eNpOMvvqOPUJ70qNBeeHAkj2PYfm+PvKiQh22EMpSN6vhrdPERX1PpUxYb0TzfDsazz8dGOGZ8HdHjZ8tWmWdAWeqI6nANQ+pVIAQaEhEQgeIkkIhDxGPtbWPnwwsqO/UabIcesr917ntYUjolzrftfERB66Vd8VjbOux1IQIiIAIiIAIiIAIiIAIiIAIi0HQCvXp0M57E5glt5ME7xjmjV/7ydhd4YMJs7Pi7bPe+vW3OjJvdk9vo8WS3U4x8/Prme93k+OnDjnG6PPUdqmBv1JUTrGuXTs4e9a1es86++f2x7r0ATPZ9+7z/dDZuG3+Zs4FOp44dQjMNnjNJ/K2Tv2bYQJlJ9NnP/cPVSVuefX6eq488JiYJSuArbcN3ghNMCpLv5eV5C+3K0d8x9Ah63DDpAetY1d7uvXWs49OlU5XhKys6eKp8/DXnO/+xyVPvPP1OPUzEwg872KY+dNDnOpSGeIW6ry541x7543j3lD3tnzbzmTC73jltWLp8lXsiH99oM77VU4wkHHf04CRXytG2hlZipGLHBG6m9n2w6DNXD3XgAn25YM4Uo36usxHfRsYu/Z6pjX4c+P6gXYcetK+rhjzK0mf4gA59SbpT2P4B96f/+sr2qx2HaDpjizGJHexhFx3uH0r5fNqOH+icduLRdvjBAxwTdHxeKvZwzea+7denpz09/UZnE1aM6Yb6ZdmKL9KOefxqqqxZu94Yl7SZfntl/jvmxyVH2sV9Rv6I04bYTXdOT1YJQ+578rif+D4haIMeaZS7fcrD7rstWSjFCQxgMX5s7T1MH+zSq3vK9xxRR5/e3ZP3+nHHDDbKYiOFaZfk7wd8GnX2qUl9bPHd6+vlyPcl/ekKJj64z+kzfEpcWkP3OTpLlq50fRatjzwv+LtufY37PlAgxFPRUQREoPgIxMzea9vZpnU4oKDyUJdB9kzfgwtaR7o2LGpdVXzc5ZEIiIAIiIAINA8B1SICIiACIiACTSLAhCtP+SKcR40x+XbSWWPcygBWNDAh6nWWrfzcrXRgxcMjT73gk1MescOkJQGBs789NKXO3195w9ljgpkgDAEDJg6pk7zX3/rAra5gkhfBCDpjL/0up1kLZZHePXY2/GES/IoLRrjARd9dejgfaFvo81cPHejs77NnP3d8/qX5dSY+8RNf9t5jV5fP5OL66g3uPN0HE+WDhpzrVk0wSZtOL106TGCTjldY7pwRJxpMmZQl/b0PF3NIK3Chn9hKypchWJS2QBMy0rHLpX2Nqd63kYAV/Y6N9z/6lEMdCccBTMiEC5PpnPtx7ccIOtgmnbLoIIw5JqiZcA4DNmE654wt9Id+/XAO5scU9hZ98pn5fPoUP1DiHmD8cd6QMLYZNw3dt/Q79v198uY7HxkBqMb2C22m7amCMw357PO7dO5o8OU67DeuGZ9+LHFNf7zzweJkYAO2CHkI3yccv5kIInHcq38f65wIqvp00lIJ9zX3tx8rMLps1PCU265xz1163vCkGfqUsthIJkZOwjb4vkfF+3Xg/ntx6YKaB+y7h9EfLiHx4ccEPtF/iaQG//nvDxRhtvizFa6fufaCPd9GBUI8FR1FoEUIqNKGCFRvWW2vff542crGrdUNIVC+CIiACIhACRCIl4CPclEEKonA+Ec72dAJPerI1Bdye+q6kniprSJQqgT8k/RMUHIetoMnjVmNwaoMnpbmCWyCBl6HiU2eWueaJ+CZ1Ed4Mpu0UHhSHDthWvQ80+Q8ee9/VH+SOmojn9feZyaNCQLRNtrZ1Dp4uppta6KrCHK1C5N0ZTLlpSuTLn2f7cGfdPmFSs/Uhkx5+fbHj4NUdjPlMd7JT1UuXRoT5EyUk09gkjHHkWukumaj+Xyus5cdv2nnct9iv3fPbm6VFudIJvaZ8ihbaOGeghnCPbt2Xeb5IoJBQ4ZfbuizlVg2AUmCGzf84iKbPPUxV46yqb7zfFvJQwcJ+9Ln53IkYEcAiDIEJ7INdoQ+4AfX2IgKfU2wKZrONT8P2DpLgRBoSERABERABERABERABApPoIxriJVx2wrfNNErPOPKrOG4Azba7DErk3L20TWVCUKtFoEKJcCTxgQBeOqYp6VTYeCpeIIoCFv4oMOT2RxzlUwT7uSFT0fnarsx+kwKsk0XT/cTCKKNXpryVDtP1fN0PXZ5ArsxvlEGJhxTSaa8VPqZ0lpqcjtTGzLlZWpLY/L8OEhVNlMeY4f8VOXSpTHJzWQ3+QQm/Xjj+OT9E6z/bruYz0cne6n7u2Iu9y3BHII6vq5M7DPl+fKFPPIdtGDOlORWVDAjcJGuTlaI+FU6vhyBonT6Pp3VN2xzRxn66brbpiVXnngdjgQcwu260CW9sUIQjGAZ5atrNhjv9+C8IaFN+OqF61Rl6Gu2H4vmEQRhGy6241IgJEqnwNcyLwIiIAIiIAIiIAIiIAIiEBLY8ZRfmKpzERABESh1AvK/ZQlEAw9szcIT1Om8yjRhTiCFgAqBFQIsqWwQFCA4wBZAbCmEcM4qFLavYUsYznlqG8EGE3Tjb7kvua0VafkSJlDZNgafpz40O2nW15lMyOIEG2xJhCqT40ySc474dnIeFSY6mfCMpnPdEC90mireN/qFLYnCifqGbIeTtg3ppsrPpX1+m6JUdpqalmoc0CdsbYZtP0b8uOZIf/PuCcqik63wlP8xRx7k1O+d/lRy+zX6wdeXKp97gHHpCiY+cmGf6b5NmHJbL9Eev2VTtv1CGT/msUNQgNUIrIaCH2n5FLadYpVGyOGWu2ekDFBQL98ncJoWvC8HHxHy0wl9gd10+dF07nXuedKbMk7xFxt+G0K+Awmo0h+k50P4njvs4P2MQE/UHitF2CZNgZAoGV2LgAiIgAiIgAjki4DsiIAIiIAIiECLEXj2zXbJrbG0LVaLdYMqFoEWI8BTw2x9xYQb28YwMUsgwjvES5uZ2PTCtjTo87S51/FHJniv+9mFRnm2l6IMR5/Pkcm3yTeMMZ4+Z7sahPR7bx3r3m/BpPJDd/+X2xufLWawwfY3vMQX++yPj77Pwx+umyK0hafMsUV9iK8zG7v4fPXFI50qfrG1DE9dk8ZEMbZ4YXP0Kf+RZxzv2unZ+0lwZ2j7R0O8tqs16uB9ow8IfvEkOPVlw9mPG8pRvrET39SXaTzgy5Wjv+Pe88JYom8amsRuFIxEoeg44H4gSJfIMvIY994HjoyZ80aeQnbOQjlWDvi+p11wJCiGsVT5j25/R89xRw82fMnEPtv71o952sPKiZ9dfg7Vu0nyTP2SasyHwQlnpAAftJ1xyj0FMwRm+JOqOtL5bpn+6JzkFles7PABh1RlSCMY+K/X302WYcUHW2Vhj/xQ4Ma9Tf/hzxPPvBhmpzpPm4Z96iHYgy3qpR+4T9IWyiLD9zM24eX7OSxKHQRIYKtASEhG5yIgAiIgAiIgAiIgAiIgAiIgAiVPYOxp65JbYt363S9s+ssdbO7bOxW4XTIvAiLQHASYQGZrJ7ZJYfLQ18k5aeF2MkzykoZQhjyESTkmZEkPBX1vL3qkDGVDfc6xi0/oM+Hmt5whD33KkYeghz55Xnyd3n+f7o8+3/tLeez4unwdpJFHOWxRH+LLke7F2+RIGkd0Kce1txmmkU7bqNfrkYZutN7QF3SwTznKI5xjmyPX6CDY8rw4ck069aGPHa45ch2VqD10EV8efc5Ji0pok3OfT9toD2VD8TocSfd28RnfSYv6E+alyscG6aH4/vN+eJtw4xzfyMNfdMOy4Tl56HgJfaENPp0jur4s56RRB3U1lE4+7aBMKGH5aL5vC2VDX8Iy5CHen9A2ZcgLhYCK14nagRt1+vyQBTZC/9BD36dFbaEfFXyM6mFj1rTrXSAGfViig12uEc69Txx9u1LZQ59xhu/oIpyTRl4oYd2+XvQR375Q359Hdf901y8tXR2UwV+Ec4T20EbscI0f1BetF5+xiz56CHZoN+fpBB1seQnrIg/xZTlHT4EQT0RHERCBiiGwdWPc3rvHbP5vdsjqhTuav3lN3BbeGk/mc07aDg2dpSWgDBEQAREQAREQAREoMgID+m61I/feZB+taF1knskdERABERABEShhAnJdBEqMgAIhJdZhclcERKDpBLZtNGvbJW4Dr4rbQT816z/cbPFjZtWLa/cor14Ss+6DYy6PfM4XzYwZAZSm1y4LIiACIiACIiAC5UJA7RABERABERABERABESgeAv7Jf47F45U8KRYCrYrFEfkhApVMgOn3nTt1suO+fGipSVb+HnPQwRZrVTxfN227xKz/GTFr3S5m/FfVN26t2sVt89ra664DzHofS06ttOtptnl13Aig1KboUwREQAREQAREQAREoFgJrEj8TnfXrQY9mgAAEABJREFUnA5J9xYuaW0LFrexw/bclEzTiQiIgAiIQM4EVEAEREAESppA8cxMthDG6poNxouPeKmKl+jLicIX8aBLmRZyV9WWKQGm3793UMwePdPKUh78dsyO6LOtaHtv89qEa7GYte1MSCpxHvm3emHc2naNJYIlpv9EQAREQAQqmoAaLwIiUAoEqnaK2xtL2trQCT2cXHJfN/vh8dXGFlml4L98FAEREAEREAEREAERyD+Big+ErK/eYH16d7eXn5hkC+ZMsdvGX2a8uX7BWx862gRFpj86x+bMuNnlo/vrm+91eRX5oUYXjECbzZ9Zx1WPF1RqPnrCnn/uL8k6uP7nC7OT1wWr//PZ1so2F4xdUwyz3dWnT8es+5fNqvoRktphbdlcc+8Jqf7YrP8Z8eQKkh0aOhMBERABERABERABESg2AlXtzG46a43NHrMyKcfut6nY3JQ/IlD8BOShI7B85Rd20lljjPkhl1BBH5Xc9ly6mTnEYSN/bBxzKdcUXeoK6xz727sMaYpNXzZq26fraK6PQ+7lyKRQ/c/CAhYYsOAgH9wa8/1U8YGQXj26GfvGVXVo7/rgwP33sq5dOtmylZ+769nP/cNGnDbE0CNh6NcPt1fmv2PA5loiAqVGYO477ez6xzs6+e+/Vtn8T9rastV1AwCl1qbG+ksQ5MMHYsb7QsKtsLw90nhHyK5DY/beH802r0m9YsTr6ygCIlB+BNQiERABERABERABERCByibQsaq97bfPbta7x84OBJN4g4aca6EUa5CkUBOaDkQLfMA55H7UqRe5iWlrwn/5YNS7Zzfr16encczVFcYTk8NMEvuyBDQQf13oI3Uhha6n0u3nY6xVMkPGKNIUBg0FQppiuyTLLlvxhcXjcfcDji+hz5atqtMOfvCRjx4ZrRLzx+mE/HKXdG3PlB5LMCtnLjQvU/tT5cEkbq0t3rp9QSXWpp2dcOA2u+q0rUm5aNg269W9XUHrjbeqDTSmantDaYUaK2EQhPeFZKqHd4i0bh+zzWyhlUmxEXmNGS8wo1wjqiuZIrSPduYq3Esl08hGOporE/QbWVVJFeMXGtqaizDOSqqRjXCWNubCxOk2op5URYo5dNwoLhRK1dAySuM71I2BRFt1NPMMGsuljIZGyqbABfGcsj1SJqXBMkrMlkWoFyuO9hfMC9oXtlfnVvsdkyCeiUUiW/+KlMBXBh9g6XYWKVKXS94tAgbs4PLgHeOMHV2QyTeMsYdnzS35tjWmAYP239NmTbveODamfKYy2CyU7Uz1Kq+8CbAI4Q83XW3njTylxRrKvEGLVV5sFRP4uGHSA3bmN4+r80Wy9x67pnW1984dLJV069wubZlyyejSsW3Ktqfi4dO6d2nvfuErFwap2lHVvk3OXHp162DrO+5tn+55TUFl44HX2L4njyloHSnb0P8y27JTu9y5JO6vtm1apcLcpDQfBOm8t1mqIAhbYq1euKOKz1+L2dYNcWvbeUdavs52atsqZy7cT5TLlw/FaKdNm5j1StwXtDUX6bBT6yY2p7iLt078pdyja3vLhQm6nTq0Le6GNdE7JtV27pL7d0zXTuX/s7pr551yHi+wTAy1JvaKWcyK979OVbn/DsO917p1Mbeq6bw7JL5D+c7IRXolflZ/sHSJPf/ma2UpLyTatXz1KsuFiddtW4DfYZrey/mz0CbRPt/WXI7t2rbJnxNFaKlN4nuiZyN+VvM3RBE2J28utUr8YOFvwVzGCrptW2+zl995syy/X/je/Od771j3DOMlbx1QZobYoYOtqiZOnmFHnXqRW5kRfaKeSXO/ciDMy6ZsFFdVh/Z2y68urTNPFOpEdxYhL1395PFEs/eNo/cv+rQ4c1TksQqCcgjnlEFgQHtI58g16QjlVqz6wpjj+uTT5XbmheMcJ8qjzxE9hHKUJx3BD891yPDL7eMly0hOK+naih22EKKfqAeh7WkNJTLS+YV/bFs/fuz5dfqBCfuxl343UdLM86IeBL9cRuKDei/9+S3JdwTTPvyjTK6MKBe2C36JKowJXr+bDNehUIY68QvBH/JJnzz1MXtx3pt2xMmj3RZsMxOBnYdnPZ8I8Dzv+oy+/Oerb1m0zrkvzndp2MAWwsPc+EMd1OfzOFKeI3q0G7vwRtLV5/Upg8/YRTgnDUEH29n2M33pfcQWfuCPt4XfpHPENum+DL5yjeCD72OO2KGPKUseOr4caQh6pFMf+oOG1K7s8unkZSt33PeI6x/s+vooyznCOYLP1JXpfkTPC21uiCf2qRfh3JeNHslDfLpvt28vedhAQt5e3x/RQ/y1bxP2SItyJp/0qKAPC18/R659v+FHurKkR8dpTc0GV8Vrb7yf9mcB5bCLMO7yP8PoXCi9Dzrj4rET3ftCopGp9z/6NG2DPltVY6lk1ZqNacuUS8aa9ZtTtj0VD5+2YvUG27qtXAikbsf6DVty5rLs8xr7R80n9rtFt5Sl3PbJXbZ489acuSxN3F+bt+R/wGxcYbYx8bvc0udq3wEy/ze1x0Uza59f7rRX3BY/VptG3qp5cdvn+2Ztu8RSd3oTUjdu3pYzF+4nyjWh2qIvunlL3JYm7gvamotUb9xa9G1rioNbt8Vt+Rcbch4z62qK8x09TWERlo0nbt2ViZ+7uYwVdL9YV/4/q79Yuynn8QLLxFALEZfd+drq3H+H4d7bujUx2MqOxo4G8R3KvZGL8LP672++Zf/+X78sSznrt+PtvSWf5XwfwXBzAX6H2dFbeTprgpnNid9h6H/amots2LSlCbUWf9Etie+JZY34Wc3fEMXfusZ7yO8w/C2Yy1hBd/HKtXbN5Mll+f3C9+a1/zPVln+e/ne7xhOvjJKvLnjXnp5+o1uZQYunzXyGg3uXB5Pmc2bc7FYO9Ond3ZjvYd7HKSQ+0pVNZOX87/W3PnBlCIhwwuRetH7vG3lst+59+9GFZ1IkK2FCL1wRwTbuN9053ZXlyPWCOVNcm7984JeM35GvHP0d223XXuZXURx39GDHJ50dJjSv/OXtNursU50d/Ny9b29XR6oPfIq2NWS9Zu16W7p8VdIWbadMOlvp/Ioyjpanb6mXvoYBfj/57Et1ts16ed5Cgwf5tI8ACHZIy4URZcJ2PXn/BEsXAEEXeX3h+8bqFeqmL559fp7rBwI5+OJXGGHrjGHH2unDjnGCPgGW9u3bWbTOnbt1xnQdWbJ0pd1761jHG7u0ETZ1lCIXjIlU9YVqjFuCLKyCQjgPJ8ZD32CfqZ9TjdX11RvcKwgYewS7aDfHUVdOqNOHoU/Rc4JJ3zr5a67tvAKBsXzOJePd6w6wh9+dqtq7gFlDYyVqO3pNew8Z+CVXV0Pt9WUJqKYaaz4/PGI/3X3TUF+Eds7+9lB754PFji3pHyz6zNaur7Fvnni0S/P3C3yOO2awC5w2NF6wE0qUM+P79ikPO/uhXrrzsN9uG3+ZXXfbtJRlU43TDokgNXbTfZ/zXRP9TmlFgUoXOtnfBNwsngeDlEHhrzny7pBYLNaoff8oLxEBEWh5ArwUfeBVZrz/IxS/OiSaP+CSWEGCIC1PQh6IgAiIgAiIgAiIgAiIgAiIQGkSOGfEica8DRLO3cx+7h926EH7JienmQxc/NkKYxLQtzRdWZ/f0JHJO57gHzTkXLt3+lP20N3/5epjfun5l+a7yVc/Oc67ZknjiXCOBCx8XkP1hPm0i8lKJs9J/+qhA90k56JPEgH7ZavsvQ8Xk+zk0vOGO3/cReQjnR0mNH3AgYnSSLGUl9jKxLpL544GfwrzrpW+u/TgNKVgK1X78IsClMUG51Ghb+ljXxd8992rn/39lTeSqtj27DLt/EKBhnwJ24V+Q/Kd049PrmTZq38fO2DfPSzTQ9ep7GVTZ9gXjA+YwCaVvWzT/Jg+5siDkvcb9w/BDt83oW/0EX2Vyj62CKKkGqt+7PmAIsEhOIV9mMqmT0Mf8dfenh/LfE/QD/CAS6ax4m2kO9Je+JLPWIM7Y4brfAj2vX8hT/jxHZKpL8L6GWudO3YwzwKW3Bf4jPA94fX5niKQRlDKp2Vz9LY952idDdmgzxD0eB1F505VnOYkjEf6F4n+LAjve/qs4gMhDCKCIAyiMAjiiTMQiG77m5uBzQBnwHgdHUVABERABERABERABESgBAjIRREQAREQARGoCAL77Nkv2c7ePbsZE4vJhAwnPOU+KBHcQE46a0zKJ5MpzsQdT5jzBPOb73xUJ8hC/o13PGjYQJhzIs1LQ5PwXi/Vka1hsImw3dXaddXGU9HX/exCY2KadISnxi3Df6nseHUmsZl89dcNHRvLOpXdTH41NEnLU/Qwof0ItlLVkW0a5bGDYBfW2ZaN6jH3yBZA2CKARiAtqpPv61zGfTZ1h+O2sRPWTFRnGqvh2EM3nNTOxseoTmgvzMv3WAnvgbCeQp1n2xcwZL6buWzGIEEU5rm9X6yYYEwi0e8pr5PNke3z2EYPO801vrPxC53ofVzxgRAigfzQCn9I0XH88AMYS2+I1vsOJXL5s8vPIUtSkgTktAiIgAiIgAjsILCpapBt6HpsWQpti7Mnwo7m6kwESprAOSccb29OvsPOP/kkO/mIw+1PPxtb0u2pVOfj1so2djmqLL93+XmytXXnon5HUqWOO7W78gjUPnFe2+5lK74wJj5rrzJ/8oAs28QgbFPU0EOwzBml2oKIAAk2vLC9UdX2bVxyXQkQesxWWt4mR+8jfnJOGlvTPPjIsxm3FEpnh7oaCjigE0pjWYc2/Hk6v/wqAf/0udcPj7v17W1sUwQDL9Gt70P9hs7T+dJQuWg+E9BMMjOpj18E0AikRfXyfZ3LuM+m7nDcsltOYwNDmcZqOPbgxhxsNr6l0wnthTr5HivhPRDWU6jzXPqCVRBsj0XwrVOnDubHHkGQcNsovrMa6y82GdeMby98NzbWXj7LRe/jig+EsCzub4/d7vZ1853FkR9+HjxfnKQh4Q8vn6+jCIiACIiACIhA6RHYnJiq+r9tu9uUNj3KUmjb5lir0usYeSwCGQi88dEiO/2or9rXDhxkbVq3zqCprGIl8Enr9ja1zc5Wrt+9r7bpYuX9NqFiHVnySwR2EOCJZ97BwEuHSZ360Gzr16ensWUL1/mWkWcc70z++uZ73dZBPIEd7nPPhO7EyTOcDnk8lU0awrnLSHzwBH8sFjMmmROXxsQlwjlCuyZPfaxOgOOWu2cYW2NhH3vohRK1SV46O+yEEg04EHjgaW/KpRJs5Ys1tlK1D7+YPOchZSZufb/iD+fjb7nP9S1bAPH+CdIR8h54uPa9MVynk1wZpbPTULpfNcDWQ0zQe32e7ueadJ+GLkGAVH3qdRo6Mu4PO3g/tyVXtI2MK8TbyFQfATzGrd8tB5/YDq4xu+VQNt1Y9WPvkadecG7hHw+uM5HPCiVWd/gAAH3LuHOKaT6i9hhH3C98D2QaK9jmZeUc0xmuWIsAABAASURBVJiuk4zeP197O7kFXMiS9sLKF4j2g0/P9tiYvmDem+2w/r//nmm81wQbvr6uXTolX/3g2fq88JipTXBm/Pr3IFGOIAvCeT4l9CMbu6m+U1plU7CUdeS7CFQyga0b4/bePWbzf7NDVi+sS2TZ3B156FKmroauREAERKB8CSxa/5q9vWZuWcqi9a+Wb8epZRVJ4J3FS2z2K/Ns9C232XtLPrWb/zyzIjmUeqO3bdtk76z9e1l+7/LzZO2WlaXeRSXtf2Od/8u14y0+6/E6suDOSY01p3ItTIAnkVmlwXZG7PjBhDJPO4cTgPl0Ebt+ux92F+FhWibt/c4ibBXTqWMHFyTxQRPSThjxI+MJbe8Lk/1XXzzSWD2A339+4q/Jp7fRoV3jx55vvl3o0Lb+u/WxpctXGTZJI/8nl5zlJsCxiS/eJpOT6eygi4Q+MIm7e9/eVJ9SsJUv1thK1T58onK4RvNHXTnBTh92rGNLH8MDBgh5Bw7Ym6IZBfu5MMpoLEUm44N3GPidaL75/bEWrtrmaXom+RkvJ23fjo33LTC5TJ+ypdaGDRtTWK6fFG4DBAu/ow1tDPs1OrYaqg/2BD7wEZ9Y3RI+QF7fk9QpsMg0Vm/4xUVGMIz+I+g1+YYxbhxT7srR30nm3TDpATti8IDUlWxPpc2hPXzvWFV7H2YaK7xHo6HAKSvMuM/wk6O/36g6eo8fMuhLJDvBp+hYcxk5fDSmLwgILP50uRFU8lWF4452PPHMiz6r3rGhNt1761gjUIYdhEAwAZJ6hpqYEB2nNTUbMlpM9Z2iQEhGZMoUgdImsC3xs7Jtl7gNvCpuvBS8/3CzxY+ZVS+ufU6NoMiqeXEbcEltPrqLnyjtNst7EahwAmq+CIiACJQtgb8vXGiT/u/j9smKFXb3rKdszmvzy7atapgIiEDzE1ic+G45Ycw1Fht2ipNBF4xufidUY1YEmExkGygmuXwBJmWZIPTXnC+YM8Xt/hHu7JFNWW8j3RHboU30vF384BodXz9HrklnQpeypLE7CU9ok+6FNpGH3PKrSw1d0lLlo+Pr48i1l7AMdUfTyfdpHCmfqg7qj7L2ev4Y2kefNpLHk+izpl3vJrK5Jp186uY6lZCHP15Cv9CP5sOQesjz9n3ZMA87CHoIdvCFMlyHbSCPNI7eFkdfnvrCdqHbkIS28Ivy1Ek5fMAX6oA1YwnhnDTyDjtkf6MMdVMG4TxMwz/0vVAO2+gioQ/RsZVNfaF9zrGJRP2gTuqmPvKjQlnvI8dQD1vwIZ0j174856SRh33a4BlyJI26vT7HsAzl0CMdPfRJQ7CLLnnvfbjYCFyhw3VU0EOfcl7CNlDO20bvslHD3X1MOrbwIVU58hDsh/1KOeyFdQQMjXPKZRLK4gu2vZ636335012/NMYcYwG9VD6gi51omyhDWfIRzknzdfmjrxMGpHGkbaRzTb3T7xxnqcqSTzq2qYNyBIG5pn3kI/DALucIeeh7USAEKhIRKFMCbbvErP8ZMWvdLmb8V9U3bq3axW3z2trr1Qvj1n1wzNAjv+uAmFV/bLZ5TW2ghDSJCIiACIiACFQEgdofjRXR1Hw3snWr1tatY6eylK4dO1qrmAZHvsdM/uyVjyVGWZeqqrK8j/h+aNd2p/LpLLVEBERABESgLAmwfRYraQqxmqEsgZVgo1qVoM9yWQREoJEENq9NFEz8Md+2c9zYAmvzGv7kSqRt/0e6JfKd3vY0HYqcgNwTAREQARHIDwE9A9AojvFtZl//Ug+bdc2ospRHr/p/7Es99CdTowaHCuVEYNequP33D88sy/uI74dR/3Zggkfdvz0SCUX1r1/Pnvb0hN+67bG0LVZRdU1ZO8OTyzzZ7J+ILuvGqnFNJyALBSXAigPuR44FrUjGW4yAfqtvTvTF/Xtfc5JQXS1AgMDHp0/HrPuXzar67RiM7Xq2gDOqUgREQAREQAREoCwI8D7+Pdp9ZEd+8ZNmkWavZ/XPbJf2G8qir9SI4ibQpf1WO3TN9eV5HyW+H/aPP5fogOKNOH/jJ2Pddlhsi/W9Cb+z3Xv1NN4bknBa/0RABESgCAkU7/dpEcKSSyKQJKBASBJFM5zoe6oZIJd9FY1qIEGQDx9gC6y49T62romNK+pe60oEREAERCA/BNhm8J27LPleJm+V9IW3xm3+b8zJsrk+R0cREAEREIGmEuA7ddHM+n948Y68N35X+73L9y/vymtqXSpfngTuffoZe+mtt23X7t3Ls4FqVSkRkK8ikIbAjodb0ygoWQREIAUBBUJSQFGSCJQTgTAIwvtCfNt4b0jbLnX/SNzMu0PicWvb2WvpKAIiIAIikCsBvnffu8ds4a0x27y6bmnyFs2MGe9nOuinZvucG7cVfzcr5Qm5uj9J6ra36VeyIAIiIALZEeB7lADHUhYeRIoQgF70kFm/U8347u0/3GzxY1YvUB0ppksREAEREAEREAEREIEyIqBASLF3pvwTgSYQYMKNlSCd9zYLgyDeZNcBMVs1L278cUja6oVxq9rdrG0XPV0AD0npEdgca2Of9x5un/c5pyylukPiZi69bqk4jwk07/M9swGXJALLXes2f90HBEfitvPBteEDtirs9KV4IhBSe11XuzSu9BOjNPqpHLyc+kIHGzqhh3Esh/aoDfkl0HVAbZBjl6/Xt/v5azFr2zVmnfaq/a7l2K63Gd/J9bWVUmkEjj/kEHv+pt8ZR9p+zgnH25H772d/e/NNLptXVFteCFTXbLAfXHGdDRpyrjtyPfa3d7nrk84aYzNnzTWOy1d+kZf6cjXy7AvzWrT+qL+wQaLpxXZd+w1ebF7JHxEQgVIi0KqUnJWvIiACuRFg26uNy8x4Mo4n5Lz47QL4g5GnknlqmbzNa2LW7+Tc6pC2CBQTgRXWxmZs/tzu27SsLGWebSkm3AXxpRKNtu+ZCI4kvn8JXldi+9VmEciFwHEHbLSPVra2K+7vYtUbcykpXRHYQYCANSujN6zQtNoOKpV79syrr1q3jp3s6Qm/tfisx+2eMVe5rbFG3TSxcqGUeMunzXzGteDlJyYZLz5+cd6b9sr8d2zOjJvtyfsnWNfOHV1+c3wQbCHoQvCjOeor5zr08E05967aVqkEmrvdCoQ0N3HVJwLNSIAnjQdeZW4LALYB8BKuDuGdIT6dJ5j5w7AZXVRVFU8gv7/ObksEChat/Zd9sPYfZSlrNi6v+BFT6gCq+tZOulUvye/YL3Uu8l8EciEw9rR1NvzwDXb+f3ezFWzrmUth6VYkAVaAbF5jxkNCRQag2d1hRRUrq0IZ/2inZvej2CocdMFoiw07JSnf+MnYYnNR/uRA4L0PF1uf3t2tqkN7V+r9jz61vrv0sI5VtdfHHT3YBUR69ejm8pv7o6Xrb+72qj4REAERKBYCCoQUS0/IDxEQARGoSAK1k8IV2XQ1uiIJsPXgrkNjtmiGGSvxEFbt8WSyAtEVOSTU6EYSOHa/Tfbzb661UX/Y2ea+vVMjrahYpRDg4aDuXzZ7b0os+d27ekHMWJFXKQzCdh6422Z7+LKVNntMrRBcDPN1LgKlQODuaY+7ra7Y/grxKy7Y4unhWc8bQvroq2+0G+940FgVcsTJo418dFmlwWoNhPOJk2fYUade5GTui/Pd1lXoYgNhq62X5i10+f66umZDElWoi50Fb33o8m66c7p9vGSZXTx2ovMXv8P6UfI+YBchn3QEu5f+/Ba3xRd5oW3yo4JP+IouQnmvwzlpCOc+PTx6X6I+4Dd6HEdcMM4Q7CDoYo9zhGt0EdJz8Z8yknImoLaJQMsSUCCkZfmrdhEQAREQgUIQUHylEFRlM08E2JbQr8Tj2HVQ3LoO0AqRPOGVmTIjwIqPsyd1c+8GmTK3yp59s507Hzqhh11yXzdbvzFmv3+mqnRWhpRZ/5RSc8JV0AOvilvnfeLJd4aUUjvkqwiIgBmT/evW1xhbXy2YM8V+dOGZdt1t04xJ/PHXnG+nDzvGCXmTrvuRy//K4AOcPvmpGL664F17evqN9rfHbrf9v7R7UmVBwj5bai1ZutIm3fOw0/HXBFdQpF5WoKCLHHfMYLth0gPOzysuGGG79+1tt42/zMg7b+QpFEkKbbn613fYiNOGuPwH7xhnY8ffZWEw4eVEAObK0d9x+aPOPjVpO2lk+wm2CLiEvhwycB/nBwGMz5atcgzgxjlBiu1Fczp8kgjsjLvyXOcP7Klz6NcPT17fO/0pV6c3mq3/Xl9HERABESgUAQVCCkVWdkVABFISUKIINAsBzSk3C2ZV0nQCy+aabV4T02Rc01HKQpkS6Nk5blNHf+GeXD/32GrjHSH+KXZ/JB+9MkWgZhWAwOInzFq1N2OlSAHMF73J1z9pa6dP7OGCitoWq+i7Sw6mIMCWV5eNGp7c+uqrhw60eDxuy1Y0/uXn54w4MWnPV8nkPudsqcXWWscceZDT8ddsuUU+W2xdet5wTp1QjsDJ+uoN7jrTxweLPrPFn60w2oDeoP33NAIps5/7h/n/uCad67332JVDSvG2zv720GT+d04/3p0//9J88/7Dj/by3hSCOE4hh48D9t3D9urfx5XAHwI9B+6/V/I6bDuJ2fqPrkQEREAECklAgZBC0i1b23rUumy7Vg0TAREQARFoMgFeev7ePWYLb43ZhmW1W7FwTTrGCX6wJRbCi3r1fiaolK2oYSIgAs1EYPXC2i0H2W6Qba/4jiXNV79oZjy5LRZbYoXvzPM6lXA8++gaF1gkkDjth6tsweI2xntDKqHtamN5EWDrKbaJYiumMy8cZ2vWrm/RBrKCA18QVkjk4kyXzh2td88d7yvZZ89+1tj/orZCOwQt/HXvHjtb505V/lJHERABEagIAgqEVEQ357uRsRwMSlUERKCyCJT39wMT2EykhH1avThub/yudvKFSRcv4cR3qK/z8ifAuz4IbrDtlReuSaf14fYslToRBweJCORKgAlcvcsgV2qVo991gJn/zvVH0jwBvm99Ot/DPr2Sj6ykOuXgjfbRytaVjEFtzyuB5jFGEGTUlRNs/Njz3XZMbCdFAKB5aq9fC0EQtrPCD7a/Yhus+lrpUwjihKtZ3vtwcXrlBnKitkJ1v4KFtGUrP7e166o5lYiACIhAxRBQIKRiuloNFYHmJlDeE+LNTbN06ivPFWM8UUqAg6dMo33BthoDr6o7+cI7HzrvbeYnvqNldF3GBNQ0ERABERABERABERCBghMg8MGqBipiUp8AAOctJV27dEqu6ggDDtFttKL+scVUvz49bepDs10WQZ5nn59nbK/lEnL4iNrinSETJ89wFtgWa/qjc9x7VEjnPR6HHrSvsa2XU9j+EfXX+7M9WwcREAERKGkCeQ+ElDQNOS8CIpBHAuU5IZ5HQDJVQgR4opSnSHf5esNOs0Jk4/KY7Xyw7oGGaUlDBERABERABESguQhUbzS789kOxpE6V6xzJRfNAAAQAElEQVSN2eOvtbN/238Tl42SQhdqHYvb2UO+bmOGDy9LOf2ooyxm+p0x13HE+zIOO3g/Y0usQUPOtWtvvd8IjORqJ1/6Xxl8gPEOkSHDLzf8eeKZF5Om/fs4brzjQZd397THk3mckH/dzy403tdBWdrESpfjjh5suf4XtXXEyaNt6fJV7r0m5408xQh84CPpfXp3t/HXnF+vCmxcOfo7NnnqY87fGyY9YEcMHlBPTwkiIALFQUA/QXLrBwVCcuMlbREQAREQAREICdQ7X/GyWdcDzNp2idXLU4IIiIAIiIAIiIAItBSBqnZmK9a1ttMn9rChE3rYyN93N7bGOna/4g2E9KiK2yUD37RfHvxiWcqF+76bCIPod8bG3BNM4rMNFTJr2vWGECDBFnkI5whBgD/cdLULCHB9XCLI8OT9E4zVEAjnpJGHRNMIDlAeO+Snu8YX5E93/dKwiR30sU06gg2uw3z0uCYfIZ9yCO1AOEfIwxd84DoqUVthWc6xj3Duy3KO+Gs4/u2x2922Y9R1y68uNfwmnyNpvn78wXfqJT96jV2EPIT8sDxpEhEoIQJF56p+guTWJa1yU5e2CIiACIiACIhAOgJaDZKOjNJFQAREQATKg4BaUeoEeM/O7DErzQvv3in2NrVb/4a1X/uPspSdat4udvzyTwREQAREQATKhoACIWXTlWqICIhAsxBQJSKQhsDWjXH79OmYVoOk4aNkERABERABERABERABERABESgpAnJWBESgrAgoEFJW3anGiIAIiIAItBSBdR/EbPPquOndIC3VA6pXBESgEASysRm3tra1be8ylV4WN/3JlM04kI4IiIAIiIAIiIAIiIAIFDMB/VZfzL0j34qBQPP4oE39moezahGBAhFgNciKl8y6D47p3SAFYiyzIiACxUlgWyJMsLRdL3t9t4vKU/pdYKtatTP9JwIiIAIiUJ9AGb6kt34jyzRFfVemHatmiYAIZCSgQEhGPMoUgWYioN9Cmgm0qhGBxhFYvdBs/m/Mlj5ntnpBzJ2T5q2tfFmrQTwLHUudgPwXgdwItLKYLdq00v74ya1lKfctnmSrbXNuUKQtAiIgAhVCQM/zlW5Hq+9Kt+/kuQiIQOMJtGp80TItqWaJQBEQUFykCDpBLohAQKDrALODflpXSPMqvY81G3CJVoN4HjqKgAiIgAiIgAiIQCkQWLiktV3w311txdq608JTX+hgQyf0qCPjH+1UCk2SjyIgAiIgAiIgAmkIKBCSBoySRaAlCdT9NbwlPVHdIiAC5U5A7RMBERABERABERCBSiNA4OPsSd3skvu62fqNqf/6OnC3zfbwZStt9phaGXvaukrDpPaKgAiIgAiUGYFKb44CIZU+AtR+ERABERABERABERABERABEagMAkXbyq2xmK3pPcI+33VUWUpNp0Fm21IHHFqiU3p2jtvU0V/Yrd/9wjq203r8lugD1SkCIiACIiACzU1AgZDmJq76REAERKBFCahyERABERABERABERCBYiOwclsbm1bzoU1ev7AsZe7mtWatSivg8Ponbe30ibXbY2lbrGK7Y+SPCIhAdgSkJQIiEBJQICSkoXMREAEREAEREAEREAEREIGiIrBoZtyWzU3vUvXiuL3xO0utk76YckSguAi02mbLNrxrn9a8WZaydsvK4uLdgDdnH12T3BJr2g9X2YLFbYz3hjRQTNkiIAIiIAIiIAJFTECBkCLuHLkmAvkgIBsiIAIiIAIiIAIiUIoECH7M/43Z6gWxtO4TBPlwWsy2bkyrogwREAERaBIBttE65eCN9tHK1k2yo8Ii0BwEVIcIiIAIiEB6AgqEpGejHBEQAREQAREQAREQgdIiIG/LiEDvY80O+qlZ10Gpt9PZvCZuix+P2e7D41a1exE2PNbGtrbbtWwlbm2KELpcEgEREAEREAEREAEREIHUBBQISc2lhFPlugiIgAiIgAiIgAiIgAiUNwGCIO/90az318yq+hZnW5fH2tn8vqPKVpa26WSWfrGO6T8RKFUC1RvN7ny2g3GkDSvWxuzx19rZv+2/icsiE7kjAiIgAiIgAqVCIPXDTc3pvQIhzUlbdYmACOSdQMt/jea9STJYjgQ0UAvXq7IsAiJQcQS2bozbopkx23VozLoOKN7mr4pvsns+ub1sZdm2ajP9fCveASjPMhIguHH2pG52yX3d7IPlbWzk77vb+EcTwb1Eqap2ZivWtbbTJ/awoRN6uDy2xjp2PwVCEnj0TwREQAREQAQaSSAPT9A0smZfTIEQT0JHERCBkiTQ8l+jJYlNTjc3AQ3U5iau+kRABMqYwLaNZptXJ4IhM8x4h8gbv4tZ9cdmS58z470iZdx0NU0ErLEIeJ/OO3cl7p01daNXi2bG3X3EvYSsXtjYGkqrHO/9mDr6C5s9ZmVSxp62LtkIzsO8s4+uSebpRAREQAREQAREoDQJKBCS7Le6vxAmk3UiAiIgAiJQTATkiwiIgAiIQD4IlHCAtm2XmA24JObeH8I7RAZeFXfvCNnl62a8VyQfeGRDBMqFANvILbw1bu9NidnWDXX/5iWPdnIPcS/tc27cPv2LGUET0iUiIAIiIAIi0MIEVL0I5JWAAiFJnCX812CyDToRAREQAREQAREQgaYRiMe32brOX7HP+15QlrKm93DbXHcusGnASrW0GJRIz8lNEWgaAR84JMjRun3dv3nJ639GzFq3q01v29nM4nHbvLb2OnGlfyIgAiIgAiIgAiJQNgQUCCmbrlRDRKBMCahZIiACIiACzUogFmtlz2xeZneue7Us5X+q37HViTY2K1RV1igCbHPltupZEHPbXr3xOz2p3iiQKiQCWRKoXhKzbRtj1razIqVZIpOaCIhAvgnIngiIgAgUkIACIQWEK9MiIAIiIAIiIAIiUIoEVm9Zbktr3i1LWblhkRXzL8ClOF4K5TPbXLFdj5eBV5lV9av/pDpPs+/zvcrbFotAEe93CPmzpREBIwJICFsi+e2PQj2di0BIwI+bRTPM+p2a+j4L9XUuAiIgAiIgAiIgAqVIQH8HlmKvlbfPap0IiIAIiIAIiIAIiIAIiEAaArzMmiDH0ufqK7ClUc+vWvL9KVW7my2aGbOtG/WEf31aSvEECDASaBxwSdw+nR03xpjP01EECkxA5kVABERABESg2Qg0TyBEv3c3W4eqIhEQARFIEtB3bxKFTkSgeAnIMxEQARHIjUDXAbWBjl2+Xr8ceayk8TldB8Rs8+q4bdvoU3QUgfQEeGcIwbONK9LrKEcEREAEGkPg2Rfm2aAh59pJZ42x5Su/aIwJW/DWhzZs5I/dsVEGmlCoJetugtsZi9IP9Ad9k0px7G/vMiRVXi5pd0973H5wxXVWXbMhl2ItpkubkRZzoIUqpn/oJ/qrhVxolmozBELyOINWfwX7jsbpTAREQAREoDAE9N1bGK6yKgIiIAIiIAIlQoAJ7bZdY9aqnek/EahHgC2xPnl8x9/9XK97N2btetZTzV+CLIlAHgj4CTsm1o869aLkxLif2GVyl3PL4j8mgbHDBCB2UxUhnXz0QsmlnlR2SyEtbDusCukzk88h3/Ac/hs2KKpfSP6yXUtgnz37GcIVYz4ch5wXa6CA7zy+k/AZ30tdCD7y/Q5zL01tG4xapQejGbT0bJQjAiIgAiIgAo0joFIiIAIiIAIikBuBxv1dxqT2qn+Z7XpC3HiPSm51SrtcCPCOGN4V896UmG1YZrbw1pj5d8sQ8Ni4ImZstYagwztCug4ol9arHZVAYM26apv60Oxma+pt4y+zBXOm2JwZN7s6hwy/3Jo6OecM6cPGX3O+Ywvf04cdYwjnyB9uutrat2+5qP6g/fe0WdOuN47qqsoisHvf3u5+Zxw+eMc4mzz1sZzu+cqilZ/W8p165oXjbPzYHd8JfOfOfu4fTV5ZlCEQkh/nZUUEREAEREAEREAEREAEPAEm5d65y4xJWp8WHkknH70wXeciULkEdjyxny0D7qMPp8Vs129YyhfMZ2snD3oy0cIE2O5qwCWx5HtjDvqpWf8zaoNrBMj2+V7tVmukIwqCtHCHqfqcCHTpVGW77drLnn1+XnJVSCoD0ZUG/oluJtsuHjvRFXlx3pt2xMmjs97Cp1ePbnbDLy4yfLjutmnJ7Z544pinsv0TzEcFK1ZcRYkP6vf5HNGnnPeTY0LNTbaG+f4JaWxOnDzDyEPQpzx2uObINTYQ2km6F1ZXsNKDPO8LaZf+/JakTcqgAx/YoMs5NsjjmiPXXrBBGfIQ/PJ5lCUtFN8e7ITpDZ3/5a//TPpJHaG+bw/1hv6QzrVvoy9H3egiUW6hXXwNt+Ximn6gHOLthWX8OXnoIJShrM8Lj/QZPtC36KGPzyFTyvo8jlxjI5uy6KUSJpepC4nWF+qna0euddMXoe9hHanOqZd+wzd8jJaFAWmp8hoqm6q+80aeYkiqvL3697ED9t3D3v/o02R2pjFEW/HLC/0LL4RzynpD+Iq+v/Y6vmxU16fTdhjcdOd0+3jJMuNeI8/bymQnzOP7z9/r3ofokXqoD/scuUbH28k0dtELxZfBFuLbx3i/d/pT9qMLz7Tjjh6cLMJ3LsHSqg7tXRrtoxzC2KAcGaRzzZghD/G2YaRACJQkIiACIlAwAjIsAiIgAiIAga0b4/bePbVPI29eTUpdIfDhn1reuiH3id+61nQlApVLwAdB9GR/5Y4BtVwEKonAD/7jZNfcGyY9YOur67+DgMnFh2c97ybVeKKbVQY33vGge/cBk2ys8MDAVwYfYC8/MclYeeAn2kjPJL17drOuXTq5ycfX3/rABUPOuWS8rV6zznhynCeYyefJZj8Rhz/Ujx/4Q52HHrRvpmrq5bEKZunyVYZ9nlanfdR7761j3SoKJkMfeeoFV45JQSZGfX1MLjLZ+eub73X5/oO0b538NfM8CO7Ak2vYoMc5PsOtIbvk4xdlaSNlsdFUWbN2vdF2/KD9r8x/xwWMsEud0x+d47iQ36d3d5s28xmynPg2kseEKn0ydvxdrq9IG3HaEGOi1Cln+GDClfHmn1anfbv06r79SfW6BZnsxQ/sI8cdM9goi426mjuuXl3wrj09/UY3Hkn1bcDWlb+8PfmUPPWPunJCnSBgurLYyST4RjvQ8fVx7oW6G2pHNnXDnD565I/jc1pd8/K8hXbl6O+4FUOjzj41yRC/GmKSrqxvWy7HDxZ9Zos/W2FfPXSgK0Z70o0h8lg9wncBfHO5B2gX9zRjkrLYuH3Kw+47BrufLVvlxgd5jINlKz+3Ky4YYXwfUA/pBHMy2WEMXv3rO4zvH/Tpf+5X17AUH9hqiHU2YwDT2ErXvihj9KOSy70OD77PqBNGCoREaepaBERABERABERABEQg7wT8k8cDLolb2671zfunlvc5N26t29c+rVxfSylFT0AOtigBgiCL/hyzPUfGTU/2t2hXqHIREIFm7+mOxwAAEABJREFUInDggL2NyWUmuV985Y06tTLxxUQ5qzb8xOXZ3x7qVnGQTn6dAjledKxqb3136ZEsRTCEIARPjPPkOE8wM5GJAk/dUx/14g9+kE7QhUl5dLnORnz5sP6rLx5p2PDvNnjvw8VuYv75l+Y7k0O/frg77r3Hru6IH/jjLhIfTIAivXvs7PgQzFm24otETv1/TKBmsrvok8/M558z4kSjjfWtmJsI/9tjtxuBlVT5qdK6dO5onl3Yfu8TvOFAWdqMH+RxTfsQzhH6hLHjt7tijLzzwWI32Ux+OiFAtGTpyuSqANp32ajhKduJL5eeNzxpCp8oi41kYuTEM8MuwQefzfji/MD99+JgtIWx9vdg3Kcr6wqk+cAnsqjvmCMPcn3nmZGOZNOOhup+5vl5xoQ0ATvsYTdbCfvJj2HKZsMkXVnKZyPc02yBx8oCAgH33fZTN3Ypm2kMRfPQz1Z8u7554tGuCN8nnTt2MNJZjRKOIe4fxClGPtAnKZUdH3Dw9xN6mcTbysf487ZS+YUP3OcEmjmPCmOT+zrbe53vtM6dqpJmWiXPdCICIpAXAjIiAiIgAiIgAiIgAiIgAoUisHqhuXc6LH3ObPWC2vc7kEZ96z6IGSuueNcD73zw4vPRkYiACIhAuRHgKV+ehP7D/zzhVmP49jGRz4S+vw6PpJMfpuV6zmQ2E5K+HBOU/jx65AnuRZ8sreNfVCff16F/rAphIpdjU+tpyG51zUYLuTS1vlzKs9qGdiLZtJVVK+girNxZu666weqYxGdbNJ72pxzCU/rpCpKHDpKNT+nskE7gjQAQ5wQuwkAJaemElUjUj5x01pi0wZ4wyBC11ZR2EKhk9UE4eR2139jrxjIJ2wMXrlP5wHcLq49YlcH3hp/E97qZxpAPTHrdXI5hACbctoqVHqzi8MEZtoGqrtmQ1nQ6OxTIFHAgPyqNZR21w3Umv1j51dD3c673OnUiCoRAQSICIiACIiACIiACItAYAiojAiLQzARY6cG7HEIhDTd6H2t13gXhdXw+OhIREAERKDcCTEwzwfrJp8uNbaN8+3iimK2p/HV4JJ38MC3XcybqmBhlopSnpDNNIjNh3X+3XdxWWrnW01h9JsyZuKQ828Ow/Y2XJ++f4FaQkJerNGS3R/cUS39zraSR+tF2NrTVGVuFeSYcs+XCKhJWs1CGOlnpEK6w8e4zuR5unYSuz2vMkQATgSjKMvlNgI3zhoRVR/iKZGpjumBeU9vBPfJ/773WrTbBVkP+5pLfWCasooCHF64z1Uufsw1VtK8zjSFWZmWymSmPFT9sV+X94+h99P1JPjamBVvAcR1KJjvZBBxCW41lHdrw5+n8YvVLvz49LVzp5MuER+4lmHhp6F73ZRUI8SQafVRBERABERABERABERABERABERABERCB8iegFhYrAbZYYbI19I8ACU9OExzxk2ocuSZwQr7XDyf4fFqmI5PebJODLb8tFcEQfHjznY+MbWeYqGYLF7+VFfV5f6Y+NNuZR4en9bHXlKfHnbHIBysG2OqI5HunP+W2yuKcuqiTurnOVvwkeUN2CZTQTuyyPRDHVLLgrQ/tqFMvSr7jI5VOtmnep3CSmvZNnDwj2e6oLbaEYlUHfvi8W+6ekXa1hNeBH3r+mmOmt9uFQTfPkDK5CuOLMv79L6yyYKyxpRfpTRXaxfs7/BZXUXtNaQcBOQKP1/3sQrc9VhgM4TzTKpWoH+F1oZmEdXFOIIKxzeoWxlemMUReuAVdeC9wj8DEjwfG4LPPz6MKJ7SL76QwwAEn5IGHn6nzXhhXIPERtZlIskx2ogEHvrMYT5RLJdgiPR/jD1vp2se9zBhkxQftpU6E8cn3Fud8r+Vyr1MGgZECIZAokOzeq7ftv9vuZSl79O5TIGoyKwIiIAIiUNQE5JwIiIAIiIAIiIAIiIAIFBkBggwEJKJu8eT06cOOMSbV2P6GI09ws70Mukxsku+3aWlomxm2NsIO29JQni1zsME5PvD+AyaM2WaJ7WyYWJx8w5jkOwXwh/r9djroMFlKeR/M8XnURXpThHby5DST5tTlfc92JQGTkrykmmAO7CjP5GRDdn92+TnuHRb5bEtDHPCJABd9g5+0t1PHDinf3YEt+o0n/Okr9BG40I/kpxMmU//1+ruGPsKKjxt/cVHKFTY89c6Et/fpiWdeTGe2wXT8Crfkot5wbDVoII0C44x24CP84BJVzVc7fBvwnXFEPQQICC6Qx3UuQplCMMnkA2ObfLjBJd0YgiPtgit8KePF31cE4sjjBfpHDB7gs91Y4ruEwBT5CBP/BBB699rZ/JhljLPajLGPTR9AQJ8XisMnnR30ube9D+NumGK79e2d9CF5sv0EW/lija10flEd7NiKjHFCWxA4ElzCb9rLWCWNPDhkutexiVBWgRBIFECIBl96/CD7w7nHlaWMPflg695Ow6cAQ0cmRUAEREAEREAEREAEREAEioSA3BABESg+AkxmsQ0KWxOxXY33kMkztkmJbv1D8IF0L0yi+TIcw3zsYp90L1yT7sv7Y7Qe9JngI93rRH1Eh/p9Pkf0KYdwTloopJFHW7GHcB76RdtD27SJa4S80B7ntIfy3hd/jV3sI5xTniPXlEOwRzpHrkPxdrDNeZjHuW8L5b1d7HAdCv4jYRr6s6Zdnwwq+TrC8r491IVwjQ2O+EMZrr1QFj0v0Tq9Xlg3NrDly8CGfK8bHqO6f7rrlxYyCHXpY/LwyafjD777a+qhPurmyDV52ZRFLxRfBltewrqoG6FMpnZ4O+n8xia8sIEtfMZ39FlVsa66xs7+9lCyUgo+ID6Tcqns0QbsYt/rUg7x19GyPj3dEX36hDZ6HdpB/Qjn6FC3l7A+zn06k/jeBkf8xF/ysXXLry41WJGHUCd1k49wTlqm+sI8b4sylMUGwjlp1BH6MP3OcYb4cuRHJdTHd67RwR52qZ9rhLZnsuXL4BNCedIoi2CbOsjzEtrHtk/nyDXlOMKTvuEaO7TL29ZMNlQKILGEzcNthh29YULBZMCK623Lv25K2ue609s3Jq8LWfcR8futdastiVbqnwiIQJkTUPNEQAREIC8Etm6M23v3mC28NWYblpm9NyXmrkmngs1r4om8hE4inXz0Fs3k0RJyJSIgAiIgAiIgAiIgAiIgAgUm0Kzm2Y6JCtmmiaNEBApNQIGQQhMuoP1tibmBP7/Swa64v4uTcTM7270vdLClq9WtBcQu0yIgAiIgAiIgAo0g0LpdzPb5ntV5kTPXpGOubZeYDbgkVie//xk8WkKuRASai4DqEQEREAEREAEREAERaA4CPK3PSgj/9H5z1NlSdbCaIbrqoaV8qeR6NWNe4r1/8kEb7Kaz1ji55btr7Pr/WGu7dN1W4q2S+y1KQJWLgAiIgAiIgAiIgAiIgAiIgAiIgAiUPwG1UAREQAQqiIACIQXs7DXdT7FVu11SMGl1wMV2+MkXFsx+Jt/X9Py2xeOtC0hPpkVABERABERABESg8ARUgwiIgAiIgAiIgAiIgAiIgAiIQPkTUCCkgH38p/Xz7eZVTxW7NMq/qetesfWt4gWkJ9MiIAIiIAIiIAIiIAIiIAIiIAIiIAJ5JCBTIiACIiACIlCxBBQIKWDX12xZY+s2ryhLqd7yeQHJybQIiIAIiIAIFIqA7IqACIiACIiACIiACIhAfQLPvjDPTjprjC1f+YUTzkmrr5l7yoK3PrRhI39sHHMvXXkl4JSJF32Uz/7JB+Hqmg32gyuus7unPZ4Pc3VsjP3tXYbUSWzCBT7iKz43wUxWRfF70JBzk/cW9xTXyB8ffLJF74uGxllWDcyjUrH5k03Twv7kvKEyzX/vbvdo+7P8CoRs56GDCIiACIiACIiACIiACIiACIiACJQVATVGBCqQABOviG96S0y8UT/ifdCxaQRgiTTNSmWWbsnJdSbGX5n/js2ZcbM9ef8E1wHX3TbNbht/mS2YM8UOP2SAS2uuD8YQ0lz1lVM99CXBK+SoUy9yQV2+W8P+PO7owRb9D95INL3Q1/hWJ1gaM+ezAiGFJi/7IiACIiACLUpAlYuACIhAvghsbdPVNlftV57SYR/b/qBUvnDJjgiIgAiIgAiUFAEm8Zis7dWjW979HrT/njZr2vXGMe/Gy9AgnMRrR8eOv+Z8Q3aklMbZ+x99an136WEdq9o7h5et+MLi8bj17rGzuy5EPzvDWX60dP1ZulkUanw/EsDavW9ve+SP4913WbQ/i8LRBpxQIKQBQMoWAREQAREQAREQAREQAaIE/2q/pz3S4+SylCe7HWefWjt1dOkTUAtEQAREoCIIsLUPTyZ74WllGs7x4VnPG0Ie2/9c//v/sY+XLLOLx0400ijrn5KfOHmGS+PJ4Zmz5ia378EWMvu5f7h8ymHLbyWEjfAaeyMuGOe21Erlwz9ffaveFkA8JY1dhHPqQ7ztS39+S7JubJKXSqibJ7Sxg0RtkYZE/Q23nqJd5Pt6oj54m+RjC6FO6sYn//Q16Qh6pEcFPTj5cuhRL/WjSz3UTb73Dx36E8E2+jU1G1C319543/DDp3s7LjPygW30EMpQR0TFXZLu63YJiQ98YIzgP/5hwwt5CZV6/9DDV+8Tdmk7NrwyOt5OqOvz/RHfEa6xg39+7FLe55EfCnXfMOkB++TT5XbmhePceAr9/cn4O10aNsJ0yuEP6Qh+hnbDc/yBJ3qI94UyN97xoL0470074uTR9sOf3GSjrpyQ9OWks8bY3Bfn17kvKMu493VjA4Ebgn0EX9HlHOHa+4Q+aV58HkfGEEIedRTyvsQf6qQuBEawIp0j19F08kKhjYhPwx5+0z/YYBzACzsIuuhwjnDty8KFsqE+uj4/1yP1R/szHNvYwz68Efyh/mzuXcqhjzBOonax7YU2oofAFL/Iu+nO6XW+939/z8PGvaBACHQkIiACZURATREBERABERCBAhCImS2tedue/+y+spSXl8+weGxLAcDJpAiIgAiIgAjklwCTgOvW19jLT0xy2+v86MIzje1ZmCzjqeXThx1jCFvv/OGmq+3HP/wP4ylmnmYm7byRpziH1qxdb0uXr3I2WAnStXNHlx79oAx1kT5t5jMcMspxRw929Yc+tG9f92EDJiU/W7bKtQHbnDOh5w0zefytk7/mfMNv3z6f74+wYHJv/NjznS62dunV3UhnMnH6o3OMbYloQ5/e3V0wiDxfPtMx9IHVCNgbO/4ue/COca6uyTeMsfXVG1zw55xLxtuI04a4dPJvn/KwS4/aZ2VA544dbNnK2vfOEmh6852P7INFnzmf4bD3HrvWKZaKZ4cO7Z3Oqwvetaen3+g4kpCufxgbtB8OyHHHDHaToqlYsErgsIP3s7+/8gYmneAn7cP/dGPPKebwwRiI9k86/6Nmw7FL/7L9FP0T1atKcLpy9Hdst117JfsNnuiF/RuOMZgQNPS8sP/kszjvkB4AABAASURBVC+5bYUoF5XXF75vjAW40vfPPj/P8IX7jHvzK4MPcP3z+2uvcHreF+65nbt1jpqzl+ctNHzGHjZQ+CQRyBx35blufGET/4Z+/fDk9b3Tn3LjB9/T9Q/t5p5EsM13Q6HuS3yGQbr75cpf3m7+nuVIQMFP4FM2W2EcHDLwS46DZ89YpX1c//O1t+v0W7o+z7a+UI/7hH4P+zO6mi4V84bu3Sg37juCGmHd/jzTfX3FBSPqfO//8Hunu3GlQIinV6LHRTPjNv83Vk9WLyzRBsltERABERABERABERCB7AlIUwREoFkIaOu4ZsGsSkQgKwJM7l42arhxpMBXDx3ottthmxaus5UuicDH2d8emlGdyVYUqOuYIw+y51+a7yZcSWusMFmLHexhFzlnxInGZDYTe9hl8hjhnG2EOneq4rSeEIhYsnSlsQURmdjybJgQPfSgfc1PTtLWxZ+tcEEHdBsS6ke8HvYIIDABShrHIwcPsNff+oBL++aJR7vjXv37GMEOn+4St3/gH+3GFm0l8HFaohxBB9qC2oH778UhK4EbNhEm7tMVgsGl5w1PZtOvcPN1JjO2n5D//Euvu77Gz3c+WGyMM+rxfFElja2ech17fgwwyYtv2KqtM7vxFY5dgjNsP4WNXIS+RSgTjjGCUowTxgt5+LfvXv3qBIZI9/Kd04932yRxTd8fsO8eyfFIWq4SjjFfFpvY5ppAGYFNP0649n3ZlP7xfcL4xA7C+GrMfYmfjPGwLdH7xftPH9A+7gHK5SKMA8YgZXr37GZdu3QyxpG/jsViyaAjadSFcB72OdfNLbCFMRLeu1FutI/7j/sw6iNjM5f7mvIKhEChhKX/GTE76KeWlH3OjVv73mZVfSvnV/US7j65LgIiIAIiIAIiIAIiIAIiUAIEYiXgo1wUgUog4NvI09NHnXqR29aHLX94MtrnFerIhGs+bYf2GjspyUTgDb+4yCZPfcyxYHsYnqj2fu6zZz9/akyUMnGaTGjESWgvLM7WY0OGX26DhpzrtkHiyfMwPzyn3QRAmHD/UmKC/fRhx9qrb7zrAjSdOnVIvk8iLJOPc7jgH8KKgkw2maReu77a+URAh8COn4jP59hj6yj8QRryKZO/+c7jfuK+wi+ErY3S1UEAgS2P0GMLrEx9n85GPtOb2j+MT+9PY+9LXz7d/ULgigAWetFAAGmVLow3xhPCOFy7rjotklzua4woEAKFMpIVL5t1PcCsbRf9ql5G3aqmiIAIiIAIiIAnoKMIiIAIiIAIiIAIVDQBJjrZSoYtZRbMmWJsAdPUCf5sgPpVF9noZqMT2mOrqEyTfZns8aT53x673W2PE25xRJn3PlzMwQmrFpjgdheN/AjthSZ4ypxtuegPL2yLE+r4c4IMnP/lr/+wow4fZD7AcN9DTxnb/DAxTH4+hcnScJsiOGWyT4DJr4LgCXX/9Hq+xx5+eF4c2a6pEO3P1NZUebv17W1siYVPXvw2VaE+QRACODzRjx5jgLEQ6jTneT76J1/3Je1Od7/4FSzowJDAIOctI8X3ID3bnzGevLCNGvdklE+u9zXlW/FRWiJv0xGoXhy3jctjtvPBxTeI0/msdBEQAREQAREQAREQAREQAREQARFITUCpIpCaAIEPntYmlyBCOMHPU9hMLDLBSD5PXvMEdjjBSXouwrYsvM/BT4jvvceuFk5mTn1otoWBjKgPYV1MdLP9Dvawi5+84yDcxirUz3RO+VvunpFShS1yeF8Dk8Mo4GO/Pj1d4IHVIbHYjm1zeIofQS+dRO0xCYkQ2IBF+H4L0pFUtugP0v/3768ZZeFBAOTpv75icCUvKpl4RnXTXbNtEO0mP5uxwNZQTzzzorEtD35SDsk09sj3Qlvg4rffgr8fI7SZMRC++4VxMHHyDLcdl7eRjyNtjsV29HVDNglMsQImfC8DY+iBh9O/H4f+wS5tpc2ct5Rk6h/8DL8bQh99n+TjvsRupvuF/EeeeoGDcd/xnhy2gHIJwUfoL+OD74kgO0+ntQ/S886ak84ak/LdPk2pKGxDNnbgxgo3xpzX5zuO7zp/HR7T3dd8z0S/97kXFAgJ6ZX4uVaDlHgHyn0REAERSEVAaSIgAhVJIHwPHOcVCUGNFgEREAEREIEUBFgBwcus2TKFrVOuvfV+Y/LTq/KuCiZj2aaHLXtIJ4DhtyFiwo+0bISn3amDbZ94n4Nf5cCRwAXp5O/Sq7t1Dt7jEfVhw4aNdarj6XpfHj95on78NefX0cnmgsm+f73+rtuSCj9Y9cBWWTw9jY+jzj7VPCcmgFmBwIQv+VdfPNJ8+/78xF+toSf5o/aoi2AUtu69dawxgYwPCBP8YfAgbAv1EwSg/ZQlj0nggfvt6QIjXEclyrOmZkNUJeM1bWNS1PcXAY6MBRKZBAS6JPqUlSHez4bGXqJY8h+8aKOvMzpGGAOMKZ/POOjUsUPy3TdJQ008wXfq8X2dLkDlq6F/GCeMF/oSYQXWgQP29irJI7rhvfXN74917+tJKjTzSUP9Ex1HhbovaTb9H95/4f3CPcpkP2xJ56Xj+E45Cz5GnnG8u2JsnDDiR3bIoC+565b4YNwwhtgGj34OAxWZ/Ikyb+jehRur/fz3FowYi4zjaD2Z7uvo2OR7HxsKhEQpluj16oVm1R+bVoOUaP/JbREQAREQAREQARHwBHzgw78HjnfC+TwdRaDcCah9IiACIpANAYIGftuUWdOuN8RPJDLZxVYq5Puthphc4xphAhrdsAx1okM5yiOco++Fcuh5CX24bNRwm37nOKMc+Rx9eXw47JD96/iITliec9IQ6qEME3lc42tomzQv6KDrfWSLLPR9PrZ8Hnro+zza6/Nu+dWlRj5p5FOO61Dfp/syYV1he8mn7aRRJpVgP2wzPodt5DrsH2xhE9v41X+3Psa195c6sIddzqNCOyhHeeRPd/3SlcduVNdf+zLY9WkcucYGgo8I/nr90IdQNzpGsIUudrxwTXpUsIOQTl2+Tq59vSEL0kPBrq8DPa7hQVn0sBnyJ518Xybsa/RDwV6oh2/YR4cjdrDHNfWQzzHVNW1EyPMStUF99L3vu+g15b0/1IX4+ihDWfLxq1D3Zeg7dSEhQ/zhOlV66C/c8NPrMYa4Jh0boa5vGzyoP3od5Uj5sM/Jhw3lKB8V7OIHgu+UR0IfomW4xh52KYfv2dy7YV2Uo0+x9f+zdxYAVlRfGP8e3d2rpDRIKyApHdKNNEgISEiDdImkiLSEIB0KSIcoSkiHlIJ/RaQkpOs/38VZH+vuwsLu8t68D/a+92bmzp17fnPnzsw5554bMJEDy2QepoDXtXs5lI/7yxBCCl6e7t9+iAs7gAS5XJobxMvPpaovAiIgAiIgAiLg2wTo3HL3qgt+5Xybg6QXARH4DwGtEAEREAEREAEREAEReA4CMoQ8BzxP2fXvX1y4e+WhRoN4yglRPURABMKIgIoVAREQAecTuH0BZpTv4Y9cODAYJtE44nzJJaEIiIAIiIAIiIAIiIAI2AT0LQKhT0CGkNBnGq4l3r36EH+se6jRIOFKXQcTAREQAREQAREQgbAhcOvCQyQtCviHxaoO/L7CMo78/jBsDqhSPZeAaiYCIiACIiACIiACIiACIhBqBGQICTWUL6agyHFcyNTOhSSFXszxdVQRCEsCKlsEREAEREAEfJ1ArDQPETUJwBHAvs5C8ouACIiACIiACDiXgCQTAREQgbAmIENIWBNW+SIgAiIgAiIgAiIgAiLwZAImR7RELnBUiFlw+4iayG1BP0VABERABERABLyGwKZte1C2Xlecv3jZa+oc3hWd9sUqNO04HDdu3grvQz/b8Z5joC5lpKyU+dkOHvRePYdOAVPQOV78FtaPKbRqQo7kSa4Bywzta+/Q0VMoU7cL+B3wWKG9zLpnLdYYTPzNYxao2MYsfzprubleKHtoH/dpyiNrMn9Rxw9Yx5DUR4aQgPS0/AIJ6NAiIAIiIAIiIAIi4NsEOALk7xMu2POCcCQI54KLkeI53rh9G6mkFwEREAER8EgCqlRoEKCClIpSO1FRSoXp85RNgw0NNyz7ecoJal/WL7yUyUHV4bnXu567BBXg4QTC+joITnwee/j4LzB+yHs4tHkGXs+VGSMnzkfz+hXNcqOaZYLbPdS30eBBwwcNDqFeeDgXKENIOAPX4URABERABLyRgJ50vfGseXydVUERCIRADD8X/CoCvy4GDgx+ND9IymoAw6EGkl2rREAEREAEREAEPJxA8YK5sHruh0icMF6o1pTKyZ5DpmDBpH5GOXrIUphOHdkVy9d8G6rHUWHeQ2BIjxZg8uQas35M4VHHsLr2wrru5y5cxsOHD5EkYXxzqOs3buHMnxeRNlVysxwjejRMH90NzeqWN8vh/fGij/888kZ4np2fd1/tLwIiIAIiIALeQUCe2N5xnlRLEXAGgbiZgOy9HqUs7wM0jjhDMkkhAiLgywQkuwiEJgEaAexREPx2H73AsDtcx8Tf9nG5j7tXM0cm1Hynn3/IKuZt32ecCTnDfZmf+/Kby0wcKUFvba7nMbmOyX09t7kn5nPfzuNy5Ab3Y+Jx3fO7/+axuC/zMbEsbuf6hV9txpCeLZA1Y2quMom/e7Z/2/zmh3vd3WXnMd1lZX1YL+4zevJC/O/MObTtOdaE4WEZXM9jBlYX7scRHmOnLjb5mYd5uU/ARI9yerb/9sd51GrZz+S3ZWLe7kMmm3XusnI992P9uZ7JrhO3BScLt7sn1ov1Y10pM8tiuSzfzkd57G385rK9zf2b6yk3v+31lIXl8zisI8u3E7fZ+dy/mc+9DizPvV0yL/PY5bjn5Tb3RBZM9jr+tvcLThbmc28PPB7LYJ3t/W25uJ6Jeext/La3U3b+5r7Mx8Tymd/+zWX+tvPa58OuI88H5WS5TPa+3IeJ+3M906hJC7gq0MQ6sC48DjNwP3c57eNxW8AU1HXAfOu3/ujfTlkm19mJdWW9mCgDZbG3BfzmvszHZNeF57955w9hXyOlandGvXcH+V+TzPfjvqOmn+KxWCa/eSzKxrJYLsth+7TX2evJhL+ZmI/7M5FR2Xpd/eVieaw7y5k6ZwW27zmCfOVamTB/v/529rHjc3/WgWUy2ftyvV2ufY4DbmeegMneh3mZWDbzBFxPWbg+YGJ+9zpQBvuakiEkIC0ti4AIiIAIiEDYEFCpIiACIiACIiACvkBAA0l94SxLxhdIgEqt1Zt2YPPiMWYkBEdEnDv/l6kRFWBnz13Czq8nmsTf7so+kymYj517fkLnVrVNufS2Znk0ONjHGtClKeitTQWc+2iMmm8VAxWnwRRtNlGxSEMADRgcwcF6Jk2cINC5Maj0a9BuCFg281LOCTOWG8PNwaO/mPKyZUxjvgP7CFj3ZEkS4ItlG/2zusvKkDusF+vX8Z2aeDlFEv+wPOQQXF1Y4NVr1/Hn+UuGW3CMG/0vAAAQAElEQVSjX+hJTr4vJU/sP5KleMFcLMIoWquWK2zKYEgghgbicVknGmVYf3LgueD5ZzswO1ofQclibQr0b9+hE9iwcJRpI8xgc+HxOvefYAxMPBbPE5XS7sdifiYanfK8mgE/7D7MRZPWbdllzlfMGNHw9/WbpnyW06llLdjymIwh+HjSeQyqKLZRtn+2MdaBspy7+Og6CWwfd4Y859w/qDbObVSOs02ybJ6vwMp82nX2+fh+xQSkSZnMGOGCOt/ksfvAcf/rn2yf9jjM5y6ne7vnNvcU2HXA7e5tnW2RdSEPbmPd3PoLUAa7bXG7e2Jb43byYyr+Ri4T/oryc2SXfY2smz8Scz/p7X9NklHmDKncizK/aaiwrx97xA3rmiPLK+aa4rna9N0esI3yeFz+cf8x//lO2Kd0a1vX5KVcHIHCurOdkxPDc7Et8fpOFGB0G+UPKDevWV67pnLWh32OWYa1+FhfxGU7kYt7v8f8sazriWV1GzTJXF92/dk+eWx736f5liHkaSgpjwiIgAiIgAiIgAiIgAiIgAiIQAgI+HBWDST14ZMv0cODAJW5v505ZwwSPB4VdbUrv2mMCd/tOIA3XssOKtyZGtQsDSoqqVxj3iclKiNZHvNR8cbyaIiww1q9liuTGYFBZaJ73vy5s+D4L78bIwX3DSrZIW5+Pv2HycI6vte8uqmvWeH2QcUkFyuVLsgvoyCOHTM67PUpkiYEFe5mY4CPwOpeqmheUB5uY3b3+tshd7g+sGQfM6i6xIkdE/WrlQps16deR0UrE3dgSKDYsWLwJ3759Sx+P3vBv3yei/Rp/B4zQIREFhbKdkH2TFRGcx2TLadtYGJ9MqdP9dixmM9O7kzZxtgG2BZYrvt55TqGOqIRzd73ab55rnjO3Nug+zGDK4NtjMpstjnmo8GJib8DS+4MuT24Nh5wG/M/T7LPB8sI7nwHxoP7hCS5y/mkdh9Yue5tndcfr0PmC6xuwZ0rtuP2zapzV5OY1/18mZUh+GBbZXLfhXVl2+O6JIniIW6cWOBx7GWXywX2p1xm22Dib9Ytd/b0OHnqdy4+MbE9MD/3Y2b2BbxmeS65zGSfY14b7tcct7kn+xq0+xrmZ//OslimLQ/7aZ5LHtt9/yf9DiNDiJ78ngRe20VABHyAgEQUARF4oQT0NPJC8evgIiACIiACIiACIhAmBKiso4eyHVqJ4VyohLYP5q7cdFeo29tD+u1envu+y9d85x9GhnW59vcN982B/qaicGTfNqA3PUO+MAXn0cwQVcWqdzDHYVgaen3bBT+N0pRhg3gMJnpo2/s+y3dwdXmW8kKyDz3byZhyMJF9SPYPSV4qtqng5j5UwgantKXB5Nr1m8ZYc/DoL6Chih793JejSBjGiPVl3SkD1z9LepbzyFEdVE7b7cc9VNDT1oGcWX8myuDextOl9nvaYkKcj6x4vKzFGoOJ9XAvJKhr0j3Pi/odknPFa5/yMT3v9Rka8nL0HOvCFJD5k8p3bw80utAI86R9gtrufg2652GZLNte535Me92TvsPIEKKxwE8Cr+0iIAIiIAIiIAJhS0BPI2HLV6WLQEACWhYBERABERCB8CJAJS/DozBR2eseloqe8HY96O3srry114fk27089/0YkofHtxNDxtDQ4Z4nsN/0ZGZ4G+7HkELBhUyihzdDwzCvnWgIogKeZdve0/wdWGL59n78nj66W6CjTwLbN+C6oOoSMN9zLQfxAP9SiiRguB7KYCe2gec6VhA7uxuY6OXP8FJBZAXPtz06hZ7pttc7jSAMqcVwVKwvwxBRiRtUOU9a/6znkSGSeHy2IR6DoY74/W8K3nUsuDb+tKMF/j3W0/960vkO6pp8+iOEXc6nPVc0gjC0E9sGzxH3C7taPblkGkHY1tlWWJ/KZd548k5uOdzbA0c+0ZjltjlEP92vQfcdWSbLtte5H9Ne96TvMDKEPOmw2i4CjiQgoURABERABERABERABERABERABERABMKQABWITAEPQe99hsVirHqOEKESe/bCtaChhAprepG7K9jmLFmH4IwkAcvj8eYv32hi6pcqmteM6qDCm+uZxk1b/MTQWKwX8zH/kxKNHayvu/KacjNRHoZLoiLVvQ78PWTc58bYQRbuRhbyGDt1sQkhFtyxORqCHtnuyubg6hKwLB6How84X0LAbVymR7fL9W9IHq7zT4Ho5TnCgiMt3I1dlJPnwn+/UPpBOVnUl2u38cvMW3Lk+GnY4XjMygAfDAP09cbtJjSavT+z0PDBEUn8fe7iX6ASl78DpuDapd0Gn+U8kg85BTze48tBWJ6sTAyhxJFL7mWw7bINc5t7yDkagaxdzF/A9sP9OTeF2fgUH8Gdb5sHw4WxnTHx91MUG+IsAeV4UgF23UJyrhiqitcDy3a/3rj8IhJHP1EOcqVRxK5DwDZqr7e/2R54jnmuuY59q1+yRCacH5dDkuxryL4G2d7Y7tguWCbLZnk8Fo/JY3PZPQWsL/ex+3oZQtxJ6bcIiIAIiIAIiIAIiMBTElA2ERABERABERABEQh/AlQu0wDA8C1MVNj17tDAVISjBGj4YDgghpKiYo9e8dzIkRT2Nu6XNHEC2PNQcHtgyb087vPZ/NWg4pJl0dvfPXwP60EDRWDl2OuoXN178IQJ98PyKAdDZQW2H9fN/rgnaNhhXiYqWW1FIesWsA4chVC5TCFzOG6nsYQsuC95xIoZ3RhJTIYgPqgI5cgGO8QPDRpPqot7UQFj+btv42+WxXoxFBDrRcMO1weVWB96y5Mv8zNRzmyZ0ga1yzOvZ914PmgA4HF4fjhxNUfxBFUoFbRxYsUAR4Zwf+Zj/jyvZoDdPoZ9PBc0jHBbwMS2FFy7fNbzmCRxfP/j89zzWmBZAY8f1DLrFbB98RxQRm5zr7N7GTxfnVvVNoZCMhw5cT7y5crkniXY39w/uPNdt8qbZn/KVKJmJ8SKFd0sh/YH6xHwOnjSMciXbftprjmOsKLB0c5LY9qTyg/L7fWrlQINCzxn5Mr5OOzjudeVoQgvXLxsbzLfbA/u4QrZTngOydBkCMEH25f7NUg+MWM86reG925p5nxiHXltsX3y2Ajwj+vc22dSt75ehpAAsAJbZKdPyEy0atMyZvLpQwREQAREQAREQAREQAREQAREQAREwPkEJKHHEKCS2Q4txRAuAcM90fDB9Uz87V5xLnM903vNq2Ph5H4mvBHzcBsTf7snrmN+JvfwV1S2cZ2dmM99P/s389n7UTHI+tr7UA7KY+cN+E2lIPe18/M319n5WLa9jd8By6NiluvtxGXuy7oy8TcTy2G9WD97OeA+PC6Pb6/nb65j/dd8MQL85r4c/UAjgL3MdQET62GXw2Nz2f343Pffc/PQGG+43d7HXU7KwWQfg+Uxry2LvZ7frC/rzTxcZuK+PD5/M/HYLJ/H4jeXuT6oxOPweCzHPQ+XWQYT+TCxLDu/+zHd8wZslyyTeVmOnbjM9QETy2Hiespo5+e3vZ7bAiZuYwq4PrgymJ/lMgX0yqecZMdtZDNuYHvYdeZ+TDxWYOeD621G3J+JZbHMgNu4nmXzGNyH290T68/zzeNwPY/LxN9M3B7UvvZ2Hp+J9Wcd7PPI7Twm92c5XGZiPua3E5e5PmCy97XzLZrSH3ZdAx6H9ec2+zj2vnbZ/J4+6vGwd08qI2CZzE+erA+/KafNyj4et7EeKV9KBsrN49py8Te3M3Eb9+G2gMfhOpbL/PwdWHKvC8uz89plcR1TUDxYJo/BPEzu15QMIaQTTKJlmtZ3OxYhLaiDxswOZg9tEgEREAEREAFnErClCmTEur1J395OIOjR8d4umeovAiIgAiIgAiIgAiIQDgQYJimgYvz5DqsH1Ofjp719gkAYXCZO5CZDyBPOKjtwDmui1YlZ2Zm7x8HjOiUREAEREAER8CUCesZy8NmWlcvBJ1eiiYAIhJCAsouACIiACDwDAXpi257az7C7dvFCAjzfHClg6069UARV2UcIyBASzIlmCCzGNXPPwliUDx8+xLkLj8dDc8+j3yIgAiLgDAKSQgREQAREQAREQAREQAREQAREQAREwPkEJKEIOJ+ADCFPcY7TpkoeZK4UCaMjsJQoblQkiZ4GL8fM5siUNHo6xIsVOVDZA+Nhr0sSLxriRU3sSCY818ljZESs6CHnkjR+NMSKEtexXPxiZkaMaNFC3F6SW9dXjCgxHMuFbSZGlKgh5sLrKUaUKHgpZlbHsokZJSaSJ4geYjaxolk8Y2ZyLJc4UROC/QXbQEhS7OhRkDxGBsdyiR81ORJb992QMGHeBLGjImn0tI7lQtkSxokS4uuILBNETeFYLsljpEecmFFDzIXXXpyoiRzLJYXVd8aMFvL2kszqq2NGie0MLoE8t/NeGz1yyLmwj4kROZpjubxsseIzGp/VKGtIUsxo0eAXM4tj2fCZPpn1bB8SJswby3qHcPa9OjH4LkhZQ5LixYyCu1b/dCd2Tjgx3Y2RDtQdBMUE+icCIiACIiACIhBqBGQIeQqUP5/+4ylyPZ4lSqQIqJ+tHTrmG+3I1OTVrkgUI8HjQj/FUuSILlTKUN+RTHiuW+bqizTxUz8FicezRIzgwptpyr1wLpQhLFLbPEOROXGmx4V+iiWXlec1vwKO5ULWOZPnsqQM+V/2ZNnRId9HjmXzRspiiOByhRhM+kSvoE3uQY7lUvaVqohk9aMhBeMXLwWa5+ztWC41MzcD77sh5RIranQ0zN7JsVwoG2UMKZfI1jNMjczNHculec5e8IuTLKRYECmCC2XTVXMslza5BiJ9wvQh5mJhwRspizqWy3t5RyB7sldDzIU75EyRCx0d+i5AuV57KT+e4VZtPRNmRvs8wxzLpnjqsuCzPdtASBLfIVpZ7xJk68T0VoZ6iBwx5OqHaLESIUauAYiSf7ojU6wc3RA1csi5hKRtKa8IBEVA60XgcQKKkfs4Dy05kYDuuMGc1RjRoyFZkseV/ecu/mU98LuQJFG8YPbUJhEQAREQAREQAREQAQ8noOqJgAiIgAiIgAiIgAiIgAgYAiF3RDS76UMEvIiADCFPOFmcHH3hV5tx/uKjOUE4eXru7OmROKETDCFPEF6bRUAEREAEREAEREAEREAEREAEREAEHEBAIoiACIiACIiAbxOQIeQJ5794wVyo+VYxFKveAVmLNcbZc5fQu0ODJ+ylzSIgAiIgAiIgAh5HQBUSAREQAREQAREQAREQAREQAREQARFwPoFAJJQhJBAoAVc1q1sehzbPMGn66G5gyKyAebQsAiIgAiIgAiIgAiIgAiIgAi+SwN/Xb+LGzVsvsgo6tgcRUFVEQAREQAREQAREQAT+JSBDyL8sHPHr1u07mL1oLf44d8kR8kiIsCewfuuP+GH3YTx8qImxwp629x/h4NFfsPHb3d7SXsIN+MW/rpq+V8qnx5GTy6yFa0DF3ONbk7jDqQAAEABJREFUfHtJ92rfPv+SXgTCksDK9d+jXP1uWLnhB9y//yAsD+V1Zc9YsBrTvljldfUO6wqLS1gT9uTy9f7nyWdHdRMBEQgxAe0gAk8kIEPIExF5V4ZN3+3BlDkrUK/NAIyatEAeYf+cPiqdVlgvhv0+moEh4+Zg94Hjejm02Px+9gI++Wwpeg+bijY9xoDL1mqf/6Pi4Ptdh0xbYXvhb67zdTBU8o+auAC//O8sXC5NpGa3BxoRl6z6Blu377dX6dsiYHOh0qlasz5YuGKz+l2LC/94r54+bxXqvzsQ46cvBe9RXO/riddQ8RqPQpFWbtJLRvp/GoS4/AMiwNeR46fBdsLQtWw3UvwTEFC78puYPqorPl+8Dm+3G4z9h0/KecFCc/vOXezYcwRJE8W3lvRnExAXm8Tj33fv3ceYKYuQu3QLvFqiKTr3n+BQR0M9zz9+5rUkAiIgAiLgdAIyhDjoDNPzlgqnLq3r4KuZQ41ipdF7w3DGUnY7SMwQi3L2/CU07jAM9ErOnjktMqZ7GcPGz8H7AybgytXrIS7PKTtQScnRQ2lTpcDKz4ejQsn8aGJx2vL9Pu8VMRRqfu3vG+gycCJ6DpuCBPFim/Yyde5KVG/+AU6ePhMKR/DeIjZs3Y2rFp8qZQt5rxBhUPOTp85g6ddb0bJBJYVOdONrcxnV713MHNcTazbvxMDRs0Dlgls2n/tp36s7vVMLX84YgjN/XkC7XuPAvsfnYLgJ/NeVaxg9eSHaN6uOfRumYVjPdzB60kIMHDPbp9uMuLg1ErefVN5+PH0JihfMZdrLzLE9sHrTDrzbc4zPX0vElC61H3q0rYdz5//Cex98jI59P3GoEpfSPl06d+EvnL94BZkzpPLfYefen7Br31GfNhSJi39zeOzHLqttrNm8A4umDsDOryehSP4cxnlh3Te7HsunBREQgRdMQIcXAREQgRASiBDC/MruwQSWrf4WcWLFQInCuRErZnT0aFcfBfJkwYSZy332AZ9etoMtJcrLKRJjxpjuqF6hiElzPumDV6yXxPcHfOqzL8yHj50GvZKb1imPqFEio2LJAhjW6x2MmbIQv/7+pwe39LCrGo1Dn83/Gn9axrOFk/ujVcNKpr1MHdkF7ZtXR9ueY3HgyM9hVwEPLpkGRXqwN6pZBgnjxzHXzVdrt6FO6wEoUrU9vt643YNrH3ZVu3f/PmYtWoO8OTIiR9Z0YXcgLys5IJfkSRKgb6dG2Hf4BE6e+t3LpAnd6ga8V3ezlJV/37iJvYdOmAPdvHXHJ0fO3Lt3Hw8ePESql5IiUsSIyJw+FSaPeB+nfzuL8ZbC28DxwY8ncSGS+/cf+Nxz3n2r771lXSt8lmN7SemXFCP6tEKSRPHQ96PPcPfuPaLx2cTnX44Qr1z2Daz6/EO8miUt3nl/hHU9+ebzHRvC8V9+N+9JvB9xmQptjoZe8OUm3H/guyHExIWt4b/p1p07iBsnlnnm5XtS5TJvYGTfNvhwwjz8uP/Yf3fQGhEQgVAi8DCUylExIiACIhA4ARlCAufidWtPWA/3c5esB8MEMJQP5wiht9xvf5w3Hsoul8vrZHqKCj8xy869R3HCUrq1a1rNcLB3iBwpIupXK4XYsaLjyrXrOPW/s8aj+571Ym3ncfI3X5AnzlpuRoFkcfOMy5UtPTKkexmbtu11svhBysa2smrDdnRqWQuJEsT1z+dyufDmG7nQuFYZcHSIrylYaCCiosDlchkjWaXGvVChQXfsPnjcGFw3LByNcm++7s/Ll34wzAa9SZvXq2CUt74ke3CykgvD+dStUsKfC5Xcvj4VEe/VXyxdj7erl/K/Jz2wFHC8xsiTRpAOH3yMCTOXcdGnUvx4sZH71QxGyUTDK4WPGycm3m9VG5UsBRSXfTE9iQvbziczlmLox3N8Ck+M6NFQpEAOUHY++1L4aFGjoFWDStb1VRqRI0cyz8R8HuY2X0vsf/kOUPOt4ogeLQro9LJk2kCk9Eviayj85WWIMI4MZ9vZ8v0+fDbva+Sx+hx6+tOYxowcsehrz3jiwjP/30Rj/O3bdzD586/8RyXmzPoKerV/2zLUpzQOQbsPHPNJx4X/0grXNTqY4wm4HC+hBBQBEXixBGQIebH8Q+XoVN7TI/mN17Jh/YJRSJsqOSo16onCVdpbiv4YeOftiqFyHG8shC+CeV7NiJdT/PfFL17cWPiwTyskTZwADK/wvzPnEDGCb1wS5GK/ILtc/z5suFwuJE+S0IRS8Mbz/bx13nPgOFIkTWhecAIrq3yJ/Ojetp5RsAS23anrTp46g+WrvzPX0fqtP6Ja+cLYsmQs6OGfI0s60LDoVNmDk4tzpkydsxLVKxS1lEtJg8vqU9tsLnFix0SrbqPMvFVrNu9El4GfWm0oMVK/nMyneNjC2vdqKmj7j5pp5iDatG0Peg2bijt37iJLhtSg0mXcoPZGmUsF9/37Ab2U7dKc901F5PutapnRmk06DDNKbEpJZVS6VCn40yfTk7ictPrnjd/uQdVyhX2ODx1aKpcphBbvfwQqtgkgRbJE4H2JxjTOC3fwJ98bxcnwe5Nmf2WMH8mTJCAWM2KII8+uXb9pln3tg/elw8dO4fVcmbHn4HFM+2Il+nRsaOY7s0Nl0Ulo4OiZJowYjdK+wEhcgj7Lyaz3w4/6tsG3Ow6g26BJxvDhcrlQrGBO67k3Ejj35CefLcPtO3eCLkRbREAEREAEREAEPI6Ad2l9PQ6fZ1Ro36GTJr5twxplEDNGNPPis2hKf6PMbVC9tPFs58N9z6FTzISJnlHr8KnF39dvIE3K5OZFJ7AjUsGwc+8R0AhSq1LxIPMFtq+3rrt85W/MmL8adSq/aRk9Hr0g27IwRv3OvT+Z0CRcd+HSFZ/ydKKCIHGieIgeLSrFN3Ma1H93kLluqJSMHSsGkluGEnoMOlVBGXAwMmX9dNZyFLVe/Eb2a4OiBXLi59NnHrtWyIYTSnI0jQHnIx8btu4Ocs4UxvUfMWEeyr/dzYRpCeiVTGa8vvjtNFw2l+mjumHexL748/xf4Ai0YlbbGd67Jf6y+iC2qZETF+CXX/9wmvhBymPfqz8e9B5Wzh5mQrSMm7rYMr4mMiGguGPLriOxbddB0Fiy2zLMNmg32OJ1jZscm9Zs3uEfWo+e2n07NzahGrsPmYwzbnOc3baMRVTwOrXvDXiCn4aL3T+/WSgXMr2SMmARjlym9zrDNLLvpBG+ZYO30NkyoA2wjIt26EoqvKs164OIESPgtZyZHckhOKHcw+8x30nrnl2rZX+QCR2lOnwwHrz/cJuvJN6Dr9+4BRqDeG9mP/PgwUOrr40IGot4LQ37eC7O/HkRQ3u2AA0EvYdPM+8HL5xRwAezUKyQV3AJRXmfVBTbAZ9n7RDBNMJPG9kVly5fBZ9ZuJ0jhgaNnY1BY2ajavnC/qM7n1S2touACIiACIiACHgGARlCPOM8PHMtbty8DSqUsmZMDb/kif3L8UueyBhA/vfHObOOIwBOnjrzWB6zweEf6VL74eiJX3EviJBXVPzTo5sGI3r+OByHEW/52u/MC3DenJnMsvvH5m17jcdT4fw5zKSa73T5yKfi4GZJnwq8TqhsI5eShfOgWd3yxmO7h2VI5PV2//4DjJq0ACVrd8KcJetBIyPzOiW5AgjCUTIMO8KwYDQcsq/57cx5oySwsx4+dhobv92NDGlfslc5/pvKfcZfL/RadnDkg7vA9ERu2nE4okaNjOmju6FAnqxo3W2Uv4c785JZs84fgmH5uBxU8rb15MJ5dnjdcC4ZKph6d2iApdMHoU3jKvhu50HUf3egMTZyZEjXQZMwY8Fq463sbbKGpL7sO3ivptd+utQpzDxebZtWNVzIh6H4qLzk/Ab5rL55wszl6PPhNJSw+qD4cWOH5FBel/fq3zfwqSUvlbWsPJXbjWuXQ7w4sYwnLhVP9G4vWu091HqnH96s2RG8V1ERzvxOTU/iQrl37j2CLd/vNaE9qehevWmH450XqMyet2wjfvjxMBEYo3yVsoWQN2dGfLXue7OOzgyJ4sc18f0btB8CGhXNBh/4oAJ38cotaF6/glHQ0vmFCv3c2dNj/fxR2LRoNF7PnRk0BtwL4tnYiZiOWM8pHAnNvoYjQajgPnT0F6RNmcIyhkQG5xP87ex5jO73rhlNzzkhOPdX7JgxXjyOgA9moVij5+Wy+8Ax/O2gUUace4jzUvEefOPmLUOa9+fOrWpjh9Xf8vqKFCmieYZhOOHJn6/AsPFzHfcuYATXhwiIgAiIwAshoIOGPYEIYX8IHSEsCcSIHhUDuzZD1ChRUL15H+NVyRAb33y/zwz9pgKFL0GzF61F49plzYRvrA/XUfl06fI1Ljo2VSiZH6d+Owu+NN+3FNgBBV214QfzEl2icG4T/5XhSjhyxsleyrUrFUfDmmXQ4v0RxpuJilgqbjn3xfBPvkDbptWQLHF8LPxqkxlNk8t6eSY3Kp0CY8htTkl5LQVktoxpMG7aYvNSQ2/S/HmygKNA0qd5yVIqRDUept3erYu5Ez4wI0Xa9RpnjEdOYRBQjjyvZjDe6in9kppNDDPHkTNU0nEFlZT0zn2rdEFQwWuvY//CkVZcZvuauXCNYcplJ6Sk1jUyuv+7OHzsFKo17Y0fdh/2V+YvXrEFv/1xwRg5OCdG2eKvgXzWbN4J/rOZVSxZADQGcJ1TErlMG9UVJYvk/Y9INDBSCRU3dkwUtgxI1SsUwah+bbDpuz04d+Hyf/I7aQXv1SM/aIMGNUqbe05A2ahcWbFuG1rUr4hYMaIjccK4+N1qQzQwnjz1u8lOoyvvT/SINysc8lGjQlHUqVLC3JNWWIpsXh9HT/5qyX8enLNq9cbtWLXxByyY1BcbFo7C7I97YvxnSx0/l9WTuNiOHH07NcbGhaMxoEsTw4UGNbtpsF3VtIxHBy2Fr73O278L5M2KXu81QK/hU82cXVRW/vr7ORw+egqM33/PUu7PWrQGBfNlw4ShHTB+cHvzTOPtcj9N/e9bz7lfWEai3NkzIN8/I2G27TpkGcfuW9fTBROe8PezF0AF/x/nLuLK1evWtgegcelpyg+nPGFymJ9/PWPu0f3fbwKG27tntRPO78VnnDFTFoJGEPbRHPlLRlRuF379VTCMbphUyEMKfR4unPOK4edO//anh0jz/NXgPEMDujTFnTv30KzzCBw9+T/jTPfdjgPgO3WShPGs577T2LbzIPp1bmzuSxWsZ7mIESM+/8FVggiIgAiIgAiIQLgQkCEkXDCH7UHocTuoWzN8PKg95n+5CXnLtUTPYVPRskElEyd52ZpvjVdc8Tdy+VdkzeYd2PrDfkSLGtl/nRN/cJTH6P5tTYijyk16oc+H0zF68kLQAMQXnUUrvzFeygzHQS/U9s2qWS+PmcDwJFTkUvnvNC58yK9frSS+nDEEKZIlROvuo8BQCXsPnsDMsd1RumhecNLUrEUAABAASURBVFTEN1b7aN2wMsiFDLiuXpuBcNILD+VyT5S167t1wHAJVS3lNicIX/r1t2B7ocfpSUshOWTcHOPBzv0GdW9ujCNbLMMjl58/eV4JESNGwEtuo82o6KY3nB2yhqPNeC1VK1/EX8G7c+8RfLnmO0SKFAncNmvBGmM0iuiwF8V0qf0w6cPO6NWhgfEmfX/ApyCXfYdPYuzAtqhXtSS6WOvYZrieChae4c3b9oCjatyZcb1TEpUFkSP9VylAoxG39bMUUQPHzDb9Ma8tyn3n7l0TgoThkGgw4TqnpbhxYlr33Cj/EYsKORqiX8+dBdkzpwXlX/TVFoz4oDXaWfekibO/BEdmUfnPftjP7Xr8T2FeuMLlclnXSglMGfG+ibmep0wLtOkxBs0to1DalMmx4KvNaPl2Jf95eGiUpUc3+yUqcqmMc+K92uUKmgvnwHB35HC5XEa5y1GMVNyxGZBJ8qSJMKxnCzPvCtc5JRUtkANzPuljnkcKVW4H3q9LFM6DUtbzy449R0y42HpVS5h7EtsL5w1xiuzByRHRul93alkLfTs18n92o8GD7eJjyyDE94Lugyeb+Q6SJ0lovRvExPY9h1HXerY7dPSUCfUYXPnevK1d02rYsGCU6WMpx8VLV0EnjTWbdxplN40g7KN53cxetBYRIrgMH+YNmNjv/PHnxYCrvXL5WbnwvjXrH4NjlgypjKPLbIvbhUtXvJKDe6X5rDaiTys0qlkGnftPQI4SzfD1pu3g6M3IkSOZUJ8li+Qxzj98p8qeKY3/9eZejn6LgAiIwNMRUC4REIHwJiBDSHgTD8PjpbOUcjPGdMf+DdPxw4oJZg6Iy1f/NkaAt6uX8lfAMB7s4lXf+BsA6E3HcCX0GKQnpnsV799/YDyo3Nd522+/ZIkwa1wPjB/8HtKkTAZ69sezFFJ8YM+cPiVyZE2H8xcvg3HtqZSrVPoNfGZxpBfq4WOnvU3cp65vrJjRzXwyX8/5EDtWTcT4Ie9ZD/V+xvNp8udfoUj+V63lRxPU3rt/H7OsF55c2dNbyqgkT30Mb8xIo9jArk1Ne2GolkUrNoMGoTt376HLwInG8EElb6tuI9G+9zgw1AJDAFFWvhw7VSlH+Zj4gpgtY2qQze07d0E+HGVkM2B/Mm3uKjSpXc54tS/7eis4GoSKuwiWso5lOCm5XC7ktxTYC6f0Bw2MsWLFAENq8OWYXrczx/YwfcyP+4+haP4cMKPx5q/GuYt/GeVdZctAu3PvT05CEqQs7EcSJYyLVy1l/2eju6FCyfzoZRntkyaKj2RJEphQc2stpVTd1gPQtudY0PAYZGEO2sC5Q/YeOmmMARRriXV/Zogs9sFsWyP6tEZMq7/+au020GB0+co1ZnNc4jPMxOGdHnuGOW8p1e5aRrLcr6Z/TF72J+nT+Fl9y2p8OOELnD13CeyPHsvkkIXAuJw9/5dxfGlWr7x1T4pmJKUCkpP60oudK3468SuadBhm2g77I67zyPSMlUpu9Rm8V+9eOwVMHVrUwIMHD/D54nV4u3pp61nl0SjGZyzea3fj8wmVtbYAyS2Dx7Gff7Oe7R4gY7qXwXtS60aV0aBmaXAEOe/XKZImBEMalqvf1YT+DPguYJflzd8ulwvuXDjXGUfX8RluWM93/I0efO6ntz/nXWQ4UN6H6MzA0IZ8V6ChZObC1fho4nwzktybmbDuLtezceF9i31Mo1pljcFx6/b94Ig+lysM43ixwuGUaFTkaN4Vs4bi0OYZWP7ZYGNsplMC36Pp6OJyPb2sHNHp9JGv4XRqdBgREAEREAEReG4CMoQ8N0LPLuDevfvmRYfKXdbUPMAvWG0m1aQBgJ7spet0wRdLN2DUxAWo3bIfqOBkXiaOiug3cob1AnWfi16bXC4XGIKmaZ3yqFiqAI4c/9UMa+aLzpmzF/B228EmxvbgMbPxVqMeYPzxiG7e6zdu3g6TFx5PBPrX5Wv45X9nUaJQHvNywzq6v/BwmWGA6ljKSobccGJMcpfLZRmB/NCjXX0Tw79E4dz46cRpEzeaoWvqVyuFZdMHgV5wVCDksgxE5tqyXo67DZ6EVRu3gyHHuI68nJSoGGBYEs51wFjKt27dAY1qtoxU1vI3mTEs1M+//gGGQNp94DhaWsYjO6QW8zgpUdHIcCRxLEMI5w35ePoSMxdPxIgRUKFEfiyeOsBqUynAEXoJ4scBDZBbloxFqwaVwEk3ObcGeVAB1dUyuE37YhUXHZXSp3kJDDu499AJ07dQyb/IMiD17dwYjFO+ffdhLPtsEFZ+PhxFC+ZA215jTX5HQQhEGIYv4pwq9Fw/eeoMeA2xn2GbsrNTyZQ1Y2q817wGOvWfgO93HbI3Ofo7QbzYiBAhggnrE1BQslq3ZRcSxo+LIR/PMXOHrLEMaQHzOXF53rINyJYpDV7LldmIx3vN3KXrkeqlpGA4R/YjU+eutLZnAg2NXOZzjMns4I8bN2/hryt/m742pGLSSN1t0KTHwhyGtAxPzF/49ewm9FVvy+hMBS7vSaWK5EW2jGlMX8M6j+rXBh990BpzP+mDb37Yb0Zw/mUZXNmuuN2JiaPv3m9dB8N6vWPmVKSMt27fMd7+lcsWwitp/DBv+UY07fShCY91+/Zd1H93EL5YthHrv/nROMjQ6MT9nJSehguvswkzlqF6+SJIbhkkee3MXrQW7iGYncTEXRaGfKWDXdw4sdxXP/H38V9+R+vuo4zj3RMzK4PjCUhAERCBsCTwMCwLV9kOISBDiENOZFBicII3xqZv23MMhlqKgnHTllgvOftAA8D5i1cwduoifNCpkRkNMH10N7RqWBmM90rPdipnlq/5DpVKvwEqP4M6hjeujxkjGto3r25edDZt2wsqmMYMbAsy4Ivglu/3Gg9lxifni1G3QRNBJYO7rAxf0nv4NBPOxX29t/+OHCmSmQfj0LFTJnZ0wBeeRSu3oNfQqWhcqyzojbly/ff4ZMZSMJ+3yx5c/anE5TlnO6CsfBlaZ70MN65dzoy2OmkpMDd+uwfVKxQFPbb5wjPQMqxRARVcud66jX0CDax1q5bAIEvOHkOmmHjtVODbXso79x4xiuzWjaqA82mMHdAOf567BI6CWLnhB9O+vFX+4Opdo2IxMBQJ5WzXe5zVd2zAQ+s/28ySVVvNtUMlt8vlMn0QWdLTn2Vaq9CxZS1ULvMGFx2VGMqIYVu6DZoEznVBIyonWaVibsqcFZaRuqDx4o4cKSJKF81nKafiGU9/R0EIRBgaFe3zvfvAMdMmslhGDzurfS9uVrcCihXMaTxTaXzdtuugmXye/ZGd1/6+d/++/dPTvkNUH4ZSYx/bf+QMrNqwHTQYsk9lood2qaJ5MaRHcxMadNHk/kjllxSN3hsKzlvEthWig3lRZs7l1adDQ/9nM95/qJylswevH/a97G9qVSpujI5LrPs2Q36yLQXWXrxI9GCryvbStE450Jg8fvpS3L17L9j87htppGZYQ7Y1suJIAPft3vqbozh5/301Szo0bD8E1Zr1AZ9laBRhOF37fk35eM1wJHmPIZNNPoZNPXLcmSOj6cDB0fIMoUvZmWhwptc+Q6FydO+shWswqt+7aNOoMjjiiMaij6ctRsl/wiJxH6elJ3GhvBxBTyNZ+RL5uQhGGeDcX8XdQjCbDQ78KPfm62b0IUeu2mEIn0bMs+cuIr5l2I8ZI/rTZFceERABERCBZybgeuY9taPvEJAhJFzPdfgfzOVyGaUbvZFfy5nZeLpR6ZIudQps/WEfkiSKZ0Ig2TV7s1Au9GhXDzFiRMWMBWtQMG9W5M6e3t7smG+ODqGikgKlTZnCjIKhIoHLDC/BMBu2QmHr9v340VJOzV2yHvkrtgHnAWAILYa/Yeib2DFjcDfHJE4MyTABqyxFdYG32qBUnfdx49ZtlCn2mgkDNXPBGgzs1hQcMp7plZQY0LUpvttxEOMsIxtfjODQf1TiThjaEZwjpUqT3mDi+efIKlspx+unbpU3wREjE4d3xr5DJ0DFk0ORGLHoWcrQAXwhPnT0F9BDOZ/V19BD8JPPloFhs+gx6HK5ENMyQKZP+xLIhp7cVMqcPPW7KYcfbD/37z/gT69OVOyzDWxcOBoNqpdGsQI5EDFCBGMQsdsMBaS8X2/cjnSpUiB50oTGmNiu1zgcOXbKMgLEZRbHJY4C4agPxvjnqCn2o1utPtZWPtkC7z/8M25a/Q7bC9et+2YXWnUbZTybuezUlD1zWnDE4sr1Pxhlyz3LoEHPfvd2w/6GIcUmzFiOxSu/QfXmfc293WbCPuftdweBijx7nTd/l7aMHWMHtsPOfT9hxKfzcMtqFzv/MbLWfOuRop/y8RpiexnYtRnYnqjwZchPbnNaorHDDvPDNjJrkfW8li+bGaVo973se6jktRXeiRPGtfjNN/f0L5ZZxlkO2XMaGEse3pO+njMcVcsXRiTLqDph5nKwn2V/a20O9I/XDOcE+6BTQzMKlM83HAnAkEhOMBzR8F6/Wkmsm/cRlkwbiASWQnbhV5us9pIavF8TCvsVtotqFrc1X4wA71+VLIM8Rzc6Newc5bYTjUDzlm1E49plkTB+HKzZvMOMmuEznn+eGzfxsl8S2AZGe72TvwNyYX/CMGrN61cwo6R57dBprnHtcsYpiO2IIz+dcN0Edl5pWPx0WEdjfH85RWLQWY6OhsGHOIVxCuII8hjRowZWrNaJgAiIgAiIgAiEI4FnM4RotFE4nqLQORRHhpQonNt4ZfNlyOVy4ciJX80LEF+Q7KPQMzlLhtSgEmrXvqOoV7WE8Sa0tzvxm8aet6uXAj34i9fogIbvDUHBfxQK9JqbOmcl+r/fBI9eDEfhzTdy4/LVaxg2fi4Yi5uGA6dxoaFoxpju2LJkHMinXdOqoJx7D57AS8kTWcaxDP4i/3z6DzywFCoNapQ268ZMWWQ8d82Cwz5SWi/Ag7o1AxW5dauUQBPrhZnXTGBKuV9/PwcqxKlw4Ivh4LGzsX3PEYcReSQOXwwZfqN3h4bo0roOqKTbffC4CWlDA8mjXP9+0jDyUd/WoDGS4dWo5OZWxpfu0He8pQC/w0WvT1Tyv5YrEzhRL72zDx09hca1yvh7cTMWOb2433n7LbOOXpZXr11/7PryegiBCMCRRDSstmpYCQ8ePMSM+atBpQqVT8xORe7EWcvRqGYZYxDiMvMcPfkrGMO+soPnVcmcPhUmDO2Aw8dOGcPzH39eBNtNXcvAyr6GfK5c/Rs0IrVrVg2j+rXBh71bYsSEeaCRlsreuUs3gKMZU6dMxuyOSGlSJkffTo1M+B4KxPtyE0vxxr6Ey5Sb8eq/2b4PVDR1b1sPHd+piXFTFxsDI/M4NbFdtG5Y2YTqcblcRoHL5zo+85HLzAWrwTBaH/ZpZZR34wa2NyF/fj97walIrDYQDQxfw373yzXfgf2qy+UKVF4y4jWT0i+p6XvJrlr5IljXDpsiAAAQAElEQVQ5exgyp08Z6D7evpJG5us3bqFJnXLmfk15+BzDfsc2LrpcdF6IbpTbfJa5f/+Bow3RsWJGx/ghHcxoRPLg9ZHxlZTm3sxl3ofo3NGgemnQwMhnPI4KL/92N4yatAA0GDCf05I7F14rNKCxP86XM7MJm0ynuVdS++HnX8+gWecPUbhKOzP318bv9oRoRJY3cXO5XKDhnc8yvGZoaL17L+jRZ+R28vQZpLM4uct59vwl1G0zEBNnfWlYum/TbxEQAREQARHwWgJeUPFnM4QE/i7hBeKqinx454MbSeTLkQnf7TiAa3/f4KJ/onfLDOvFmV5hfskSm9ESfMinIpeeQP4ZHfKDL3g1KxYz3m+cRDJrhjRoVKusMQAtW/2tGTVDgwfFJbtyb76GBV9utpS8Lv/JFbnNiSl6tCgY0ae1ZQzJZsS7ePmqJXMsUMHLFfT4mjBjGWpUKGKUDoePncbGb3cjQ9qXuNmxie2gS5s6eDlFEnP9BFTKkcvni9eCRgCG6ti594iZg6b74Emg4p8hgahUcBogKrLjxolpxOLcIby2qOg2K/75YB/CMEhl63YxhqGpI7uCowT6j5qJT2YsQ6XSBcF29092x3xRyTb7454m9BOFunvvvgnfY4fYoNF1ztL1aFavgjE6UtHdtudYBKVk4Yu1E9oQ2wvbAA3M5MK0ZvMOo3yjIpfLDFkT3LwqzOOkRCVTj3b1zUgh9jX0/Kdzgn2+eZ1VKJkfA0fPMvfn7JnTYmTfNvCzjNS7DxzHtl2H0NxqR1SQO4mLLQv7FYb8tNsH19OI2uL9EWDf2rTjcLzT5aP/xGI/cvy0Y5WVVMrxWqIyduv2A2jTuIoxBvCe7D7xM1klSRQPUSJHhu3l72Qu7Hdp0KAHP2UPLPGa4QjFM5ZhqGaLvmZ0FftXKoA5gprXYGD7efM6ymT3MZSDzyzT5q7yH8HJdVTSLlu9FTUqFjXGgO17DhulLQ2zTp3ri88e7F8of44s6fDtjv3gMwuX3e9LvGaadBiGV62+lyF1kyVJiOZW/0NmzOu0ZHO5eesO+GzH/oUOL/sOncTazTvBsE/Tv/ga7ZtVx9ZlH2PuhD6oWLIA7lrGge92HgQd6+5azzxO40J5ODfcpkVjUCBPVi4Gmni9nDl7ERnS/PtuZLehXFlfQePaZUGWnIOGBrhAC9FKERABERABERCBUCPwbIaQUDu8CnqRBEoVzYvUKZOjiaU0+GLZBuw/fNJUhy+EnLT26w3b8UbltugzfBpeSp7YelArh2SJ4xuPMFshY3Zw0Adfmqd89D6SJ0lgQhqtWLcNLepXNEo5W0x3xULECBEMN4ZPYLzy8xcv29kc+f1azkzYtfco5loKW77wrVj/A27dvmPCZvElh3HZqaBKlzqFkZ/raFSjV6ZZ4cAPvjRTZnelHD37qZCqUqaQv6Gkb6fGxtg2oEsTjP9sKWhkcyAOf5HYv+S0XvAqN+mFH/cfA5Vz9Hyr/+5AM1Jm0ZQBmDi8Exh6jwqnGNGi4tyFv8CQQLbiwb8wB/5gf/vbmfMmxAbFm7NkHfySJTKjzBjSiDHqc2RNZzHqbIyy7/X52IwQYF6mFeu+h1NGz0S3DK68jigXz7173HqG3VjyhHlVuJ9TE40eDFW47ptdmDznK2NovnT5Gjgaol7VkqCxjJ6mHMV3z1I0zZj/NTiKpMX7H5l5EsjTaWyoxHVXUN+4eRvL136Hbu/Ww/BeLbF8xmC0bVIVnK/orVIFjUGA7ahj30/MPEZUzN24ectpWIw87EvHD3kPeV7NYCkh7xtjK+9P9j2ZmTiyk6MekiSMZ55zbC6btu1xpKGIfYvLFbgHF59feM1ULvuGCYnVq0MDDB4zGwMsIyPnF+F2Kv6d+szL9sD0869/gIY0thUu0xDEUGF09siXMzN4vdBQwtA+DIvEkXl0kOIzHvMz0Xi/9OutjvFsr1ahKIoWyIla7/RFzpLNMHLSAmNgjBIlMj6b9zWuW33IiVO/I1aM6Khb5U28ktrPPB+ThVMTR9t1fbeuMdLz2uDzPUdzjhvU3oQTY/9DAwnl3/L9PlRs2AOLV36DmQvXGI5U/nOb01JwfQxl5Yg08kpivUNzmWwY6rNBjTKgUxWdyzhqj9EHkv6Th/mUREAERMBLCKiaIuB1BGQI8bpTFnoV5sNqH+ulj5P/cXLEqFGjmAkUP1+8Du2aVgNjbbduVNl49tCbjko6o4DpOAzL13yLv65cA1+WQq9GnlXSb3+cR6mi+UBvW7tmfJBlyJbKZQuBigU+3LfrPQ70xKVyhp6oB478bGd33Hfm9KkwdWQXnD33F4aOm4ORE+fj3SZVjAf71u37QU8mhpRwuVxG9p17j+DLNd8hUqRIZtmJHzzv7ko5evbzGqKHF8OJca4Vl8uFEoVzG4U2GTIk1NGT/3MiDn+ZIkeKCE4uum7+SCS2FG6jJs1HvDixjLKJ8++QjZ355KkzlqFkPzgiq5RloJ08+0t/b2U7j9O+aQD6bEx3JEucAJSfIbLIxWoqmPz5V+Cko/TqT+mXxHDMmjE12lt9DdsXE0ePsN1Ft4wITmKTxGorI/q0MnPN8P4yd+kGuM+PwXUMQ2HPqxKY7MzD+xM5OUGBSSMHjYY0yn+78yDGTl1krg8q317Nkhabt+01GDZ9twdXrl038wAsnT4QL6VIbIwhAUd9mswO+uA1kOblZNi6Y79R5LtcLlDhRsUk+122B7ajLBlSIWO6l0Ej4lsNe8J9/hDODcZl5nUKms2WYWPn3p/AdPb8X0YsGlk5Io8hkai0dOeydvMuVG7cCwwxZjL7wAevGRoL+YxLZSZHJy6c0h8t6lUAR2LRMajPh9NM2B8aAwJH4v1rs2VMg1H93jVGQ0rjfk/ivfyrtdu42srTxoSn+2JCH2y2FN2cF4wbaBD5ePoS0OklYgRnvFpS7sa1ypoRDsN7t0KVsoVB54S/LEP0/6z3g9kf9wRHAzR6b6gxsF66fBUxYkQzhqB+H80wxhKyeZ708Hl2DuN9Hzx4gDffyIXq5YuAz3NJLQU+wzPysLymPvp0Hormz4EhPZqbkHzvNa8BhoCyR6Ixn68kOsnFihkNCePFAfvcAaNmgg4OdvjpTdv2omPf8eDIPqeO5PSVcy05RUAEREAEvIOAM55WvYO1R9bS5XKBShbGlzYKgvXfG+VJnSolTLiaw8dOPWbsoBf7rdt3sefgCTRoNwQN2w/F2fOXPFK2561UwbzZ0KZRZaO8tsuisp+TsFaxDCF8UaTHHF8eGcueqWPLWkaJ6eQHfYZt6dSypjEEFXotO+gtSHkXrdhswirQg5m8qDSgByE9lznChus4PJwKSicpmyiXe6Ly9fXcmVGsYC4TUsHdu535qHD7dscB4/nPZXKihzITf3OdkxKVCVTmf/HpByhVJA8YeoQjh27dvmPEpAKFXoWcl4cecRVK5Effzo1x8+Zt0EPZqSEVXC6XpXSKahhQztKW0ZWKWipZ6L1evUIR/77nytXr2HvoBKgITxAvNtxHj5gCHPRBZWS61H6gMoBKNXpjNw5mXpWAolPp37r7aFRo0B1Vm/YGRyT9sPvwY/exgPt4yzKZvN+qFqJFjYpqzfqg26BJ2HPgOHJlewXsdziPSsMapUGlFA20da37+O07d4yBmjLeu3+fX45LLpcLbZtUA0eVlazdGaXqvI/RUxahWb3yIAeGPmK4MBpmy735ulHMMbTYl2u2GRbsi6bOXQnez+9byj2z0ss/OJ8B20PnVrXBvqRGC6v/tbg06jAUdauWQPGCOREYlzcL5QJHYHm5+E9Vfc6RwREMfHajQdreKVrUKGZeJ15TNDjzGXnS7K9Mu+IoI44UcfIzDDm435Oo1A74HBM3TizEjR3T3KeZn04v7K9pUHK5XFzlqFSmWD70bF/f3JdcLpcJD8t2Urb4a5jzSW8zypX3aYbTYoij9Vt/BEfa56/YBp37TwCf+54FiCeTZN9KZwzOEcd7E98hOdKVcm79YR/8kicGQ4bxXZEhc5MlSYCrf183o4uYx5fSmbMXrTYTBRNmLgPvM5M/eh8F8mY1CNhXT7PuP+WKv46YliHthvXsy+dis1EfIuCpBFQvERABEfByAhG8vP6qfigTqFe1pPFSofLylTR+OHvuEjhaBNY/ehIuX/0thvZogYFdmxrP7lQvJcW8ZRutrc7/Y6gjykpPfyr7t1gP+tkypjEeYrb08eLExL37D3D/H4UTvVK5n73dKd80Atke7GwrlJdxg2PFjO4vou1BSI9cvgQy1E+lRj2NAu/ttoPNZL/+mR30g/OjdLIMYuQyb9kGULn/Wq7MRkIqT+YuXY9U1nWTP08W47VcvfkHxnjG8AHVm/cFvZJNZod9UGnA0UJLpg00/Uq/kTPMRJpUoNCrtIGlwHW5Hr32M2xARYZUWPENqMyr12Ygzpy94DAi/4pDA0fbplX9DR//bnn0a/Gqb4zSiaNEeO1RUUkv7+pW25mzZD2oyH2U01mfKf2Sgl63/KZkVA7QiGbPq8J1ARMNRn9axvkvZwzBN0vHmbkzBo2ZbTx271t9c8D83rZM5RMVcrPG9cRbpQtipvVNr2Q6KXDuh0Kvv+ovEhWTESNGRNLE8UFlC0csfr/rkP92J/1gWB8aUH9YMQHtm1YDDR7sd3ltmNBHZd7wn5/n9p27OPbz//BK6hRmBEkby3C2xLrGKpcpZBSdT+LiDdt/O3seHMVL43OZYq+ZsIxzLYXtunkfoa4xkN21+tavUdmNi8vlsvqgCJbxKKoRkfcrOi7QgcGscNgHlY6fDuuEiqUK/Ecyym4bnDkagCOnl00fBBqsO/b9BG9ZzzKcj8YJfcp/hLdW2Pck6ycWfrUJWTKkNk4vXGbi+wCV2i/7JfEP/9mgemm4G5SYz4mJz/+ZXkmJT2YsM0p9PttwNOfMcT3M/GYc0dnOup+vta61zYvHGOX2GMswyzblRB62THT+oRKf/eu16zet9pIJLRu8hc9GdzPz7jTuMMzqc/0QJXIkdB04EdnfbILiNTqAIzydzubKtb/x3c4DYAg6jqrniFab25rNO8B3J74r8X7VbdBEfDpzmXFucGr/YsuubxEQAREQARF4UQQivKgD67ieSYDKW4YDYO2oPOH3n+f/spT79zFr0RoUzJfNeiFKxdXWCzNwx1Io0BvIrHD4Bx9Uxw/pYF6EKerp384io/UyRE8oLvNBng/0LyVPZL0MRX0s9rbTvP3psV6tQhH/tkDlXN2qJTDIUjj2GDLFKB3pOdmsXnlEjhwZQz+eY7UXF1bP/RCcVPCdt9/C4LGfmxdosnNqamsp5Pp0aOivXKMS2zYg3b17FyMmzAONAzPGdDchJ/q93xijJy90NBdeRz3bv/3I4Gq9EG/etg+Mw02lHdsBvU/HTFmIXu+9Dca6Z2L4ACoS7v1jYGQ+p6ZECeKidLF86GQp26ic3br9ABav98yYsAAAEABJREFU3ILGtcuBSm2OnqlWvjC2LBmLCUM7gHNHfDxtiVNxPCYXvU3teVVcLtdj24JaoJfqpA87G2ULjSRB5fO29WwnhS2jB0fbnf7tT8y1DGKvZkkHxhqnLFSoMI59AcvgypB0VLZEjhTpMcM98zkx0UDUt1Mj0+8y9NGVa9dRvXwRf1E5OuTS5WsoUiAHIkWKaBSVeV7NiB5DJptY9k7oZ+ik8WGfVpZRI5qRm+2CIQp5r+YKcjl/6Qro0c1lJoa23Ln3CF7LlQknT59BrZb9jeMCHRg6fDD+mb3aWbanpogRI5hnk4D1O3nqDOx7dWSrjXA7+b2cIjE+HtweYwe0xfwvN2Ig5xK558yRVpT58LHToJGVoTx/ttoE19Gxhfdjtp2XkieGe/hPbuc9fMPW3cbZhc/FXOek5HK5wNFl7IM5+uz9AZ9ijaXM5rsA5abzUxnL+EiZaSTJ9EoqYzBxymgzyhVYohNQt3frGkNHhrQv4/sfD5lnWfuZb8GkvmhWr4IZifbrmXPGUWHuhA+wwDK0cd4ZJ7YVm1O9qiWx6vPhGD/4PbDd2Ov5LjVn6QbwnYh989bt+3H8l99x/uIVtO4+ClWa9DIOU3b+F/itQ4uACIiACIiAowhEcJQ0EiZUCcSPGxsfdGyI+/cfgEO9jxz/FQ3cvLYPHz1lYkkzBiwfYLdaCrtG7w1FzXf6ITBPuXsOUGJGjxbFUkY+umyohNq26yA4HJ7g133zIzZ+u8cotrk813q4ZagbKuICi0nOPN6a3iyUG4yd7HL9q4wsVSQvVswaivIl8oMe/q/lygyGzeJvvkDzZah55xHgCzXnO7hjGQL4wuytDJ6m3lSgRI4cyWRl+5+1aI2/MZHXFD1tqUxwuR5x5EiR+9b1RiUmd2LoDi7zt1NTfktRu/Hb3WC4MHr8M6QCjbDF38jlL/IraV7CzVu3jeGV1xyVDf4bHfSDI8j2HDxuJsIe1qsl6D04eOxs5M+T1SiwqaQ8fOwUar5V3CjvqISqUaEofvnfH2bOCAehCFQU93lVAs1greQE/QktY1KvYVP9+2Ya2T7q2wY0FDCUI+d2sq8xa5cn/Hn+ZvYb8y0lE8PIcaQVDfJdBk7Erdt3TVs6e/4vcFRRm8ZV/BXj7HsZsoXKb8+X8NlryL6kQ4uaYLgwlsKRMQxDYnuvb7UUTwx3OahbM3C0Wl7LIBIxQgRmdWxiyCeOtGOM/08+W2pGxfA5hjH9c2R5BenTvIzew6eB19v6+aOwadFoMNwjDff3HPAc96QTy/sQDc4cecZnOObnMy6vLxo+lqzaioTx44JhUdn3Hjhyklkcl8iBI/AYCpaj0DhyqmStTqjYsIcJx1e/WikTdm/Rym/AviVy5MgY8ek8NO04DJu/34tugyaZdO3vG45jQwPH+61qY/WcD1HDugfzeZfX1Zyl60Flv3t/s3L99yhZOK8xzJIp25HTnKPsE2wbFvNbz3V89+EoED7f0XiWPGkicMRQ8iQJ8ZdliN659yiSJ0mAQd2aI06smHYRjvx2uVx4OUUSsN3YArJP4XtizqzpzPMd28/UOSvRuVUtE3Vh/sS+qFTmDXBOJ1/od20u+hYBERABERCB8CAQ/NteeNRAx/BoAulS+4FKa3oHvl29FKhQYoVv3b5jHs4qly0EhtCiYmn4J3PRuWUtjOjTCvQ25CgA++GNL0Ktuo2Ck8JycBh4oXzZUalxT3B498DRM0GP/szpUxmPp227DqFDixomRAcnC3SPSU6GTkwcHVT49ezo3aEhurSuAxoCGFojQ7qXTbsY1usdTJr9JVq8PwIRI0QwL0E79/6EOq0HBGlAcwonegu2blgZTC6XC4ePn0aGtC895h22e/9xY3jkyxJfippYCoXla74FGfKlySks3OUoXjCn9SLcDN/8sA9Xr10HvfZpQCMDO983llIlerSoiGwZlVZt2I5Tv521NznqmwrZ7oMng4bT9Gn8kDVDakS3jK/N6pY3RqBpc1eZeXioPKDg7IdXrN+GQq+96j8SgOudmlwul6XIjxqoeHbcfvZBIz9oY/Lx+jnzT0i1tCmT49yFvzBrwRrsP3wSESNGDLQcb11JL9OxA9sha8Y02L77CPLnzoyxA9uakBszF6xGpldSGmUL5WNfwnA3/J0kUXxQOceQJlx2WsqdPQOo0LflWrN5h1FGlSic24QemTT7K/DZJmH8OIYVFd8HjvyMIePm4NNZy3H+4mV7V8d808M/SaJ4mDayK3i9FKnaHoWrtkPihPHR9d064D35vmXw+P2PC+gy8FOj7M6bIyP+OHfRGBfvW8Z6GukdAyQQQQrmzWZCiLlcj5wUDh87DRpXGQqKbaJ2q/5mBCy9/zlfBqx/p/531lHthf3lw4cA5/3IlS09Vn8xAvMs5SxDPjH8Z6SIETB70VpkTv+ob9m8bQ8WW0YRPvcO6NIEcyf0QcyY0c1oPAuPI/94/VDpT8exbTsPIqWl7KaTlC0sDdAJ4sUG5945Yj3zcXQVjZBLv94Khrbcahli7bwe9f2cleGzPw1FHJn39abtpj+9c+eOeZblO2O/zo0xfPxckEOKpAlRo2JR49zxnIf1qt3poHD05K9oXq+CMZLZ/bLdflwul3nu40iRiBEieJVsqqwIiIAIiIAIeDoB3Vk9/Qx5SP1qvVXMxJK2q8OHdyrt6Cn22x/nMX/5Rty4eQv/s37T64UvScd/+Q1//HnR7LJqww94+OChvyJm94FjxgvRbPTSDz7oN6lTDnwpXDi5PzYuGmMmwKZycsb8rw0vO7Y9Y+baMcm9VNwQVZtKJcZs5058QaQ3GD1O6cE+sm8bdGtbD/Sao0Jl5KQFqFP5TdBIQk/mweM+N4o57uu0lNx64bO5ZM+UFmes64MeypSTCttJn3+JiiXzG+UUX4pu3b6LPQdPgJNNNmw/FGfPX2JWRyWXy2U89Rkui+2GIWqoMKByloJSKUkP3CrlCpk+g6EE8ufOwk0m7vSEmcvNy6JZEQofL7KIogVymDkfOP9Q/optMHH2lxjQtZkxQK/dsstUjWF/zA/rY5217trfN1H+zdetJd/9472nm2VAorKSFHiNDe35DrJlSgOOkOD2e5Zid5mlfKLRPkeWdIhgtTvmdVKi8ZD3ahrk61crZRmDohll/54Dx8FRRJH+Mf6cPHXGMjzuN0ZZ3seWrNyCDh98bN3DbzsJx39kYRtgmKx3m1Q1bDZs/dEyRMdBqaJ5TV4aiNg+2vUeB7/kiUyeph2Hg32QyeCADzKIEzuG8eCnEpdK691rp2D/humg1z+VbjR4lCycx4SAatmgEmic7TZoEpInSQheW9v3HEbdNgNx6Ogpq83ccgCVx0XgNVG+xOuWYSie/4Yfdh9GzmyvoFHNMmjVsBJWfj4MNBLky5kJNLLyPt5j6BSMm7YEmyyDAJf9d/bSH3R8GtWvDejFTxHIhQbXOLFicBHsb6n8b1ijjHHgoFK7qfVMvGbzTjCUGu/V6dO8hBNWf2N2cPgH780MR0dOFJXyL1/zHRjWkqOvOKIqRbKEGNKzBT76oLUZUcQRN3R0YX6nJZfLZZ7tRvShrG0sI+EVdOr3CfisWyBvVozu/y448ooGRKfJ/jTyJE+SAJ+N7g6+J7KtrFi3DZybh/dx7s/RmuutexT7Ii5v/SfqQv13B4HPg/ctgzTXM1n2Sn4piYAIiIAIPCMB7eZ7BGQI8b1z/twS0/OWIz4a1y4LKi5p8EiTMjloDKACs37bQdjy/V48sAwfUSJHBkNw0CuKQ+f5ks1JFvt9NAOMa/7clfGAAhh7my+H9ssP2VDZUj2ImOQeUOVwrQI9lFO9lAwMw3Ly1O/m2FRkv5EvGyJGjADGrb90+apRJjA8CZVRNJzcuHnbsQYRWP9yZU+PVzOnRb13B6Lb4El4u91g0AhQrUJR8BpZvvpbDO3RwgyRXzp9EFK9lBTzlm209nT2X2lLKWm9P6Nu6wFg7O1W3UehQc3SKJAnK3774wI4KoQKmjWbd5iX6oM//QwnvQTy5ZhKEionl382GNktZT7P+FulCoJzFLEP5TJHDH2+eJ2lZCkLOwwH1/tiihIlMl6yFNeDxs72NxZSmUDl///OnDPthkpLhhqrXqGIGbHXsttIMDSdL/C6ZxmBrv193YhKAyNHOhTJ/yrSpU5h7s9zl20AwxeWrdcFlZv0MnxMZod90BDEWOz2CJETloI2Q9qX/UdT0UC04MtNRkFJhTdTx5a1wMmP6czgBBxkULNiMWROnypIcZJbBo9jP/+Ge5aijeFtZo7tgdaNKpt++M6du+DINHpxM64/50gYNWmBo+/VBJXn1QzYtfeoGa3Ha4ihLU9YzzOcv8rlcpk5IvgMWNBS8H6/67C5jtZ988h4zf09PD1T9WLGiIb2zaubUeH3rT4mUqSIeCNfdnP9tG9WDX0+nA7O92V7uD/TQbx4J46O4UiqHFnTmfDCt27fQYlCeVDPMiIuWfUNOHcT70uXLl8zUvL9iSOMzIIDP/gMy/ngWnUfDSr1nT6qLCSnkA6FpYrmQ3brnYD78T2Io624zLBrNNAPGTcbzetVRJ+ODfHV2u8w2M1p7NG4Ne6pJAIiIAIiIAIi8DQEZAh5GkrK8xgBKiKHWAracm8+8kLmi3X0aFGNpyCHQo/u3xbbdh0CFXiJE8aFe1gOKmRmuc2TAAf+S5o4PjoEE5PcgSIHKxKVA73av42abxVDx34TUKJWJ6Pov28pWThvCL1QF361BVSqUMnLSbLjx42FboMm4tOZy0CFL/MGe5Bn3vjidiQXjpyaNqobShfJh+nWd58ODWDpVBDwGuE6KqDowfviahw+R6aMH/ZuZTwmyxV/HYumDIA9H82RY6esfiUtVm3cDnpaMqSArcikl2HHvuNNGJfwqWn4HoVGw+jRovgflCOGGN7GV5VM/iCsH7wHtWtWHZyvqnbL/iY8y6+/n8Pni9fildR+SOmXBDv3HsEvv/5hKXSrGE/UsQPambBj9Lq8b/VFVjGO/KORvkOLGugxZAqqNeuD5p0/BBW4Nd8qbuTl/ZkjZBj2ZsuSsXi/VR1wH7PR4R+Na5UxzyqtLcUcHTY4EitbxjT+I1cpfrw4MY1BgIpeGtW6D5ls7knc5tTE8JZUUvYeNtUYytj3cA4wsvlq7TYjNkcK0GC7YFI/cL4Dp86TYYS1Pjj30NhB7SyDx06Uq9cFzToNR7Xyha2+JSnozT1n6Qa817yGCYXKZ5oO1jXHERJOMaBZCP7zl/rlZODIIW6Ibr0DJE0U37qeDoJK3HRWv0sD2vTR3ZAvZ0Zm8bnUtmk19Ghbz4Q9unXnDsiLhrNFU/rj8tW/UatlP+seFBV07GAb6jJwonUtHQBHiJCh04C5XC7zLDe6Xxt8ufZbjJq80Lrf1DZcnCZrSOUpmDcb2jSqbD3/PzJpuI+2OnvukgkhxrlU2DczzCXfwa/fuIk/HVAqL78AABAASURBVDhKPKTslF8Eno2A9hIBEfB1AjKE+HoLCAX5s2RIbZSPX1kvyHx4T54kgVE0dW5VG0eO/wp76DyVVfSi++nEr2hUq6z/A18oVMGjigguJrlHVTQcK0NFStnir+HLGYOxceFopE6ZDPTeZsiRzOlTYdKHnYyn5cbvdpuXxq3b9+P4L7+bofStu49ClSa9rLZ0OhxrHH6H4vVSonBu8zLocrmM5yCvmwY1SvtfI4ePngKvGyp6w69mL+5ILpfL8CAX8mFN7t2/b0Jh/fDjIXAUCJVwZ8/9hawZU5tQC+37fGwpXDKDnsoMtcA47tzPqalS6YLo27mxme/AqTKGRC4aFhmyZsaY7thz8Dg4DxFHhZDRrVt38Mlny/znV3G5XKA38+n//YnW3UejVJ3OWLnhBxPeJSTH9Ja8NJax3/1kSAfQa7t53QrgdeWubOH92eVygYqWBw8eoG3PsSj/djfQ29+pXsopkiUCJ6Sl4prGn9O/nUXGV1KaexDPLZ9nGK6Ro43YluYsWY+1m3ea0Wrkc/LUoxGOzOtV6QmVpTGaYWtezZIODdsPMQY0OiTQWDT/y01oVq+8CRvGYsiI31Gj/Guk5bITEw1B44e8hy8+/QB1qpRAlTKFjNJ/rmUEyZk1nb8BjUwOHzuFl5In8R9tdPXvG44egeZyuax2UQEbv9uDboMmmeeVq39fB+e54rXjxPbwJJl4T6LjGPO9lDwxTv/2p3lXIo+mdcpjweT+6NGuvmkjbEMcIfLtjoMmFGrLriNNKFDu67REIxnDZS2c3M+637zq/5zrNDmfR54N3/6ISmXeMKM2OVKI92s+69plso8e3L25eY5hyDXeq/t+9JkxXNt59C0CIiACIiACIhA0ARlCgmajLU9JIGH8OOC8D0tWbcVbjXqi/6iZoCLy7r17mDhrOSr/M6H6jZu3MGHGMlQvX8QoYZ6y+FDNFt6FUXnLMFl2TPLwPr6nHo9KN4Y66j18mlFuMwY155bhnBlUuEydsxKdW9UyYaGoqOILwZQ5K0CenipTaNXr5OkzeLt6KeMlyDIZToGy29cR1/liumYpktiv5MmREf27NLUQuMAQanFjxzJ9TsVSBVC3ypvgXDROi9VuCfufv8QJ4/mM5/5/hA9mBcM0MsTemi9GoP/7TQyj3ZZhJEKECChfIv9je3LSVhpnGaf788XrMHPhaqPYZCb2NbMXrQVHAXDZ2xON0ZyjaOLwzobD3Xv3wfj0b5UuaJQttnwMy0clHMO5MK/L5cJ7lpGRoTvsPE76JpeUfklBpSUNRtt2HTR9CGVc982P2PjtHlSznlkO/vQLtu8+jGWfDcLKz4ejaMEcaNtrrBllxLxOS1TW1q9WEuvmfYQl0wYiQbzYWPjVJtDxJV/OzEZcKvxpKKLxOV3qFGY0QKHK7fBqiaYmFCb7Z5PR+mDeXfuOOkK5y763e9t6YEhCOnOwXXB0Ip9rLFGNEWD77iOoWq6QuUfxeipXvysqNuhulNwchcZ8TJz3yylGez7HfTa6G4oUyIGBo2dh1YbtUnLzJFvpldR+qFCyAJp3HmG8+3neeU2l9EtiQhFu23UIQ3o0N8+8HDHS3TKQcMS0tav+fJBA+2bVwT7F5XLh9u27xvBMJwZ3FOxfOYdV1KiRwZFXfKdq3W2UY53G3GV/lt/aRwREQAREQATcCcgQ4k5Dv5+ZAId2zxrXA5M+7AyGs3kpRRLQq//chcuoYhlCWPCGrbuNkimgMorbnJr4Yuwek9ypcj6LXJwLgl6nE2d9idfKtwJDSLxVqiAChvxxuVxgWCiGzYoYwfldVq23iqFymTf8kQa8jvw3+NiP+HFjY/6kfuj0Ti2jtKRh9cKlyxg2fg4K5M1qJrF1uVxYs3mH2e5Lsdp9rCmEWFyOCKHC+8GDh2bfC5euoOvAiajUuBfGTl1sKRmiomf7t80E4jSkMXEi7YUrtph7ltnJez8eqzkV/mRx+co1xIkd0yj5Xa5H4Tho/OF8GMXfyGWUMFTSMcQPPVHb9x7n+JBQxQrmQqF82a120RPFa3TAwNEz0e/9xqBxjcboitb9KeU/RpPSRfNZRrZ4OHvu0mN8nbpw89ZtMFxWkzrlTP9KOU+eOgOOBG7VsLKZE276vK+NA8OetVNRMG82tLKUcmfOXmBWMO+AUTONV7xZ4ZAPXkN0dGG7oEg0ME6duxIli+SxDIx+GPrxHDBc6oYFo8DQc/WqlgBDOFIRzuttzuL1mDBzuWOcPGhAq2gp/Od80hs0pJGJEoxBiOd+wtAO2H/kZ/QaNhUMgUVHlxnzvzbPfHYbIsO0KZND/0SABPLmzAg6Iqzbsuux55HF1vMJ582jgxDnmuGo+7dKF7SegXdyNyUREAEREAEREIFgCDhcqxiM5NoU6gRcLpfxYn8tVybcvn0H85ZtROPaZcERIwypwDkgmtevAA7pDfWDq0CvJJAutR8Yymbv+mmYOLwT/r5+AyvWbUOL+hX9Q/7Qe3L91h9RvsTr5mWSCnAqX+hxuOX7fY4NZ8MTevfuPWz6bo//dcR1vpxsJS4ZsE85cep3VCxVwN8IwjjbvhirnTyUgiZQqmhe5Mz6Cio36YUf9x8DFZX3HzzA+MHvIaVfEjR/fwR6D5+KJAnjIVas6Pjp5K/o99EMJEscHwnixQm6YC/eQq/2vp0amfuzLcZfl6+Z+Q6qVyhi+lqup1Fo76ETpk/mvZzrnJrYv1DRv3beR1g4uT82LhpjQrcEZozef/hn0DiQPu1LTsXxmFx0RGAYn3SpUpj1VOLPcpvvLXq0KGY+HoaY4z26WvnCRhHOfDQOzFiwGgXzZUOWDKnM/k754LwP9jwZlGnnP3MRcQ4ehsfiPYrOMFRuu1wuUFnZpHY5xIkVA2fOXkS9aiXB65BOM9xfydkEaFTl+Z42sis4gobPdxw1Xr18EWcLHu7SOeeAbCecN4+hGQtVaWdGQF+5+jf2HT6JsQPbol7Vkugy4FMMGTfH6lMu+L9j7z5wHIPGzMaNm7edA0OSiIAIiIAIiEAoEZAhJJRAqpjHCXBI9/ghHUCvSYZEYEgFvgDYIRUez60lEXhEgF5PpYrmQ/bMac0Ktp3Zi9aa5ddyZTYP+Q3bD8X2PUeQN0dGrFz/vQlPwrBJZgeHfUSOHAlDerQwE7A6TLTnFidL+lSY9+kHoFLJ5XIZTznG2X5SrPbnPrCnF6D6/YcAFdwc2bBu/khkSPsyqJykQpJGkKrlCmPcwPZW+4GZu4oKyXPn/7IMJEktpW1qMz/Cfkvh8J9CfWTF4lXfIG7smOAoER8R2cTs55whbDdXrl7HjPmrQScO2xB0+crfYNjPRjXLgPl8hYu7nGfOXjDzHXAuKyraOKKzfbNqhke7f0YP8dpK6ZcUNA7ss4xpFUrkx7XrN92Lcdxvemi3bFDJhH89dvJ/yPRKSuMgZAvqcrnM/fzOnXvoMWQydu39yd6kbx8kwNFCHVrUNGHWfFB8ifyUBGhw/Xx8LxOqkGH5IkeObO5TNLDyXWjm2B5mjiI6ehTNnwMcafTZvFVYvuY7VG3aG5o/5ClBK5sIiIAIeCsB1TvEBCKEeA/tIAJPSSB6tChgCI6bt+6AoUnaNK7iH1LhKYtQNh8jwHAabRpV9vdGPnzsNLbtPIiGNcogYoQImGUZRej1/7plFKGRbUjPFiaszc59R32MlMRl30Ilm8v1KKzPgSM/Y/vuw2BcZSqzSeinE79a646YWO1cVvJtAlRsx44VHWWK5TOekotXfmOMqwzPx1Bq9FbnHEWcL4SK7w4tamDZZ4OROUNqnwBHpX5pi02nvp9giWUA2br9ABav3ILGtcv5j9DzCRBuQsaNExNTR3bFm2/k9l/L8HtUQJUo/O86/40+8oN9L73aGRb101nLMXfpekSPFhUDuzYDJ4b+bN7XhsSNm7cwbe4q+CVPjJkL14BzZYyatAAcJWIyOOyDoS3Zv1Asznv2x58X/eec4To7ubchjm4cM2URRk5c4Ng5Z2y5w+rbW8vNnT0DcmdP763VV73DmQBH5kWNEtm89xR6LTs+nr7EzEPE52EamhdPHYB0qVOYkeQcacQ5npZOH2hGfr7XZxxoxIf1jyP16GTmlDnQLJH0JwIiIAIiIAIhIiBDSIhwKfOzEIgRPSq6vlsXdkiFZylD+/gmgQ3f/ghOlM4Heyoo9x48jnGD2uPAT7+g0XtDsXv/ceMVdePGLd8EBEjufwgEF6udXrn/ZNOXLxF4GLiwNSoUxfRRXcHY2r2HT8O+wydAz3bmnrNkHZIkimdCInGZ9y+G7BsxYR7Kv93NsZ6VR46fxh6rf+UIq2G9WuLnX//A4LGzkT9PVuNpSha+mqL/49RB+am0nv/lJjSrV95SRkXjKp9P9aqUwNcbd5j5MKj4v3//gT8ThrHkwqh+bfDRB62xYFI/7NhzBBwtwfVOTnlzZkLalCnQc9gUc21xTgiOcmW4z0WWEZbOQZS/97CpJnzNy35J0KnfJ5ZRaQOYj9uUREAERCAwAjUqFgPD8jHkJ0fhzV1q9Rt4iEuXr5lRjHymiRc3lrlPcXQe5xG5ePmqMcw6dQ60wDhpnQg4lIDEEgEReE4CMoQ8J0DtLgIiEHYE2jerbjz8Xa5HoY+iRYsKDhHv2b4+RlhKlblL15uY/zmzvRJ2lVDJXkGA7YIvhXZld7rFane5Ho0asbfp20cIBHHaXS4X0qX2MxM7f9CpEXq2fxv0bD934TI471CzehX8R0BwUuOmHYcjatTImD66GwpYhoHW3UaBhgMnUaTs3QdPxop13yN9Gj9kzZAaNAA0q1se9ggrJ8n7rLJwHpkRfVqBoRqftQyn7ZciWSLM/rinmVS+c/8JiGYZjjgvRmBGI4ZNjRw5Mq5eu24w8DpiPrPw1B/ekZEj0Pp0bIjald7EpNlfmmuLBg56YmdOn9IYGG/fuYtr128gl/UMw9EknwzpADqA/Pr7Oe8QUrUUARF4IQQ4CqR+tVLYuHA0GlQvjWIFcph79bLV3z7mzMHKcXRnwvixzXPOTz4wBxr0TwREQAREQASeQECGkCcA0mYR8CgCPlyZ+PFiI2mi+KCHKT1OkydJgNH938W8iR+YUBw+jEaiB0LAPVZ7IJu1SgQMARrQGGKCC3fv3eMXHjz416N98YotYFvi6BF6VHJukbdKF8SazTtNXqd8FLWUKDPH9cSWH/Yhf8U2mGgpbgd0bWYUJ06RMTTkoPIpnWVEk3HocZoMFVa3SgksnNwPfS3jYpzYMcC54bJkSA33ueFO/PI7GC4rbaoU4CjPfh/NwMGffn68MActsb3w2po4vLMZdXbk+K/+4T7ZhuLHjY0W9StixKfzjBGWRqXR/dsipV8SB1GQKCIgAmFFgKGyXsuVCew7Tv/2p3lHatWwsr8zB8MJz1u+0epn3jLrNAdaWJ2JMC5XxYuACIiACIQqARlCQhWnChOBUCAQRDjgUdRuAAAQAElEQVSXUCjZq4ug0qBLmzrYsecnvN1uMBjfn96kVCR4tWCqfJgQoHdtmWL5wqRsFepMApzbgPOCdB04EeOnLzUK232HT2LswLaoV7Ukugz4FEPGzTHzisSOFcNxEGhcZvii3WunYPlng5E9UxqPkFGV8D4CN2/dxvmLV/Dz6TP4488LRoArV6+bmPY0JCZNHB+BeS5fuHQFdHQwOzjwI2aMaGjfvDrSpU6BaV+sApWUpYrkxeBuza2+5XMzwjWO1be4XEEMZ3MgE4kkAiIQOgRSvZQUcyf0Aec7Y4kcgTZ36QbkzJrOjECj8dlX50AjDyUREAEREAERsAnIEGKT8Mxv1SqUCXiFjUHvv0Ge9UQJ4mLi8E7o0bYeOMlfxIgRg8yrDSIgAiIQUgKFX38Va774CC0bVrJ2dYHelvR2z5sjI2aO7WGUCT/uP4ai+XNY2/UnAiIQGAFO6juwa1O0blQZjTsMQ+k676NUnc7ImjE1GM6FBoAV67YhoOdy004f4oCDR4hwBJodwpG2jr4ffQaGBsufJwsY4nPvoROB4dQ6ERAB3yLwzNJyXjOX69GL5OFjp/1HoEWMEAGBzYHGEH7PfDDtKAIiIAIiIAJeSiCCl9Zb1RaBZyLw6NHwmXbVTh5CIGLECHg1SzrQcztjupc9pFaqhgiIQOgQePGlsI+hcoAKBYbN+nj6EtBTnesrlMiPxVMHGI/uF19T1UAEPJsADYtfz/kQcz7pjfULRqFL6zqIZN3DOU/G67mz/MdzmQbHbJnSGEeH7kMmm/BZni3hs9XO5XKhUc2yqFGxGOq/OxAla3XG4aOnUKJQ7mcrUHuJgAiIQAAC6VKnwJiB7fBKGj9wHrCAc6AFyK5FERABERABEXhBBML/sDKEhD9zHVEEREAEREAERMALCFBRSQ/uyk16oV3vcWCYiYd4CJdLZnUvOH2qogcQ4KiqxAnjgSGfWB2GzTp56gxez53Z/zo6cORnbN99GI1rlUHECBEwZ8l6/PDjYYyevBAM5fL39Zvc1VHJNqyumzcSi6b2x5Lpg8ARI44SUsI8HQHlEoEwIMDRrGlTJjclBzYHmtmgDxEQAREQARHwQQIyhPjgSZfIIiACIuApBFQPEfBkAlRWMpTPxoWj0aB6aRQrkAORFJLPk0+Z6ubhBKJEiYzUlnJuyaqtOPW/s7hy7To+nfUlKpYqiJR+SWEbRT4e/B6a16tglhd+tdnDpXr26rGP4VxnHIX27KVoTxEQAREImkDAOdCCzqktIiACIhD2BHQEEXjRBGQIedFnQMcXAREQAREQARHwaAL0an8tVyakSJbIo+upyomApxOgIbFrmzoomDcrugyciOrN+uDP85dQpWwh3Lp9B1PmrDBGkeyZ0pgREsN7t0TdqiWwYv336PfRDPPNfJ4uZzD10yYREAERCHcCDFX47xxo4X54HVAEREAEREAEPIaADCEecypUERHwBQKSUQREQAREQAREwJcJMGRL3SolMO/TD9C8fkV0fKcWEsaPg63b95tY9jSK2Hxu3LyFjn0/MeGycmZ7Bd98vw/teo3DX1eu2Vn0LQIiIAIi8BQEOAJNo8+eApSyhDIBFec5BB56TlVUExF4gQRkCHmB8HVoERABERABERABERABBxOQaEESoFKuTuU3Ufj17Lhy9TpmzF9tGUYqGKOIvdNXa7fhKsNnDe1oRo1whAhHZ73VsCcOHztlZ9O3CIiACIiACIiACIhAsAQ0x2GweLTRZwjIEOIzp/rFCKqjioAIiIAIiIAIiIAIiEBwBOLGiYmpI7vizTdy+2e7cfM2Nny7G/WrlUK8uLH811/86ypKF8uHDOle9l+nHyIgAiIgAp5BQLUQAREQAREQAU8mIEOIJ58d1U0EREAEREAERMCbCKiuIiACz0ggerQo4CiRf3d/aC1HRLIk8f1X7T5wHNt2HULjWmXA+Ub8N+iHCIiACIiACIiACIiACIiACDyBQCgbQp5wNG0WAREQAREQAREQAREQAREIBQLOjvUcPVpU5MuZEcPHf4FDR0+ZeUGmfbESlcu8gZR+SUOBn4oQARF4fgIqQQREQAREQAREQAS8h4AMIf7nytkvk/5i6ocIiIAIiEDoEVBJIiACIvDCCDg31vO1v2/gf2fOo1HNsmhWrwKGjPscVZv2wdlzl8xcIS8MuQ4sAiIgAiIgAiIgAiLguwQkudcTkCHE/xQ692XSX0T9EAEREAEREAEREAEREAEPJ7D30Ak07/whvv/xEEoVyYMRfVohUYK4aNu02mOTqXu4GI6snoQSAREQAREQAREQAREQAW8lIEOIt5451VsEROBFENAxRUAEREAEREAEwphA4ddfxafDOuKTGctQtNp7qNb8A5QsnAdcH8aHVvEiIAIiIAIiIAIiYBPQtwiIgMMIyBDisBMqcURABERABERABERABEQgdAi8uFLSpfbDFxP6YMXsYdi4cBRaNayEyJEivrgK6cgiIAIiIAIiIAIiIAIi4FUENA1EwNMlQ0hAIloWAXcC+i0CIiACIiACIiACIvDCCMSJFQMxokd7YcfXgUVABERABHyIgEQVAREQAUcR0DQQAU+nDCEBiWhZBERABERABERABHyUgMQWAREQAREQAREQAREQAREQAREQAScSkCHk8bOqJREQAREQAREQAREQAREQAREQAREQAecTkIQiIAIiIAIiIAI+RECGEB862RJVBERABERABB4noCUREAGPIqAwvh51OlQZERABERABERABERABEXAOAUkiQ4jagAiIgAiIQCgSkBYvFGGqKBEQAV8joDC+vnbGJW94E9DxREAEREAEREAEREAEfJaADCE+e+oluAiIgC8SCHuZpcULe8Y6ggiIgAiIgAiIgAiIgAiIgAiIgCcS8CTXQE/kozqJwIskIEPIi6SvY4uACIiACIiACIiACIiACIQVAZUrAiIgAiIgAiIgAuFKQK6B4YpbBxOBEBGQISREuJRZBLyNgOorAiIgAiIgAiIgAiIgAiIgAiIgAiLgfAKSUAREwJ+Ahub4o9CPfwnIEPIvC/0SAREQAREQAREQARHwZgKquwiIgAiIgAiIgAiIgAiIgAhoaI7aQCAEZAgJBIo3r1LdRUAEREAEREAEREAEnEpArm1OPbOSSwREQASehYD2EQEREAEREAEReHoCMoQ8PSvlFAEREAEREAER8CwCqo0I+BgBubb52AmXuCIgAiIgAiIgAiIgAiIgAo8IPPenDCHPjVAFiIAIiIAIiIAIiIAIiIAIiIAIiEBYE1D5IiACIiACIiACIiACz0pAhpBnJaf9REAEREAEwp+AjigCIiACIiACIiACIiACIiACIiACIuB8ApJQBEKZgAwhoQxUxYmACIiACIiACIiACIiACIhAaBBQGSIgAiIgAiIgAiIgAiIgAqFDQIaQ0OGoUkRABMKGgEoVAREQAREQAREQAREQAREQAREQARFwPgFJKALOJfDQuaJ5k2QyhHjT2VJdRUAEREAEREAEwo3AoaOnUKBiG2Qt1tg/cZnrQ6sSm7btQdl6XXH+4uXQKlLleDUBVV4EREAEREAEHicg3dnjPLQkAiIgAl5JwOWVtXZcpWUIcdwp9XKBVH0REAEREAER8AAC075YhVot+2FIzxY4tHmGf+LyyInzcePmLQ+opaogAiIgAiIgAiLgdAKO1p05/eRJPhEQAREQAY8iIEOIR50OVUYEREAEREAEROBFE+CIj6lzVmD8kPdQvGCux6rD5emjuyFG9GhmPfNylIg9aqTn0ClmPT84yoOjPVas/x5NOw73H1Vi5+G+PYdMwf/OnEOx6h3Mdnsb96cxxi6X3xw9wvVM/M2y+W0fn/m5TUkEREAEREAEREAEREAEREAEREAEROBxAi/aEPJ4bbQkAiIgAiIgAiIgAi+YwA+7DyNunFjIljFNsDWhIaNTv08wdWRXM2Jk59cTcfbcJbgbM1jA4DGz0blVbZNnwaR+2PTdHtCAkTVjajPi5OUUSbB58RizfUiPFtwFNGp8t+MAWCZHpHA/Gk24n8lgfdCAMnvhWmxYOMrs26xueWut/kTAQwgolouHnAhVQwQ8ioAqIwIiIAIiIAIiIAIvjIAMIS8MvQ4sAiIgAiLgewQksTcQOHnqd6RImhAxYzwa9RFUnecsWYdalYqDBg3m4SiRBjVLY/eB44/N+cFwWnaeNCmTIXP6VPj59B/cJdDEkSSrN+0wxhOWyUzcv/gbubBuyy4umkQDyvDeLf1Hp5iV+hABTyGgWC6eciZUDxEQARHwDAIykHvGeVAtREAEwpGADuVpBGQI8bQzovqIgAiIgAiIgAh4PAHOEcLRH6MmLTAhrRi6iqltz7HPXfdzFy7jtzPnzBwlLNNOy9d899xlqwAREAERCFcCOpgIhAsBadjDBfPzHkQG8uclqP1FQAREQASek4AMIc8JULuLgAiIQHAEtE0ERMD7CKRL7Yczf17E9Ru3nlj5Ti1rmbBUDF9lp9VzP0TihPGeuG9wGeLEjgmGw7LLtL/t0FnB7attIiACIiACIuBbBKRh963zLWlFwHMJqGYOJCBbu6NOqgwhjjqdEkYEREAEREAEROB5CeTPnQVXrv6Ng0d/+U9RHAkydupisz5ZkgRgGC2z8IwfSRLGR+xYMR7bO0mieHC5XDh38a/H1mtBBLyAgKooAiIgAiIgAiIgAiIgAs4h4ABbu2w5/zZHGUL+ZaFfIhAKBFSECIiACIiAtxPgfBzN61cEw1xt2rbHXxzO3VGt2QfYd+iEWVeqaF4wXNW0L1aZZX4wT8+hU0CDCZefJjEMlrvRhaNJcmdPj55DpuDQ0VP+RbAu7sfy36AfIiACIiACIiACIiACL4CADikCIiACnk/AAbacUIMsQ0iooVRBIiACIiACIiACTiHQrG55E5qKxgh7jo5i1TuABorpo7uZCcqLF8xl8kydswLueRhay57k/Ek83I0uLINGFO7DEFg0xtRq2c+/bNaFo1W43WOSKiICIiACIiACIiACIiACIiACIiACXkBAhpDnPEnaXQREQAREQAREwJkEaKT4fsWEx+YAoYHCXdrA8tCIwjwc2cH5Qmgw4TITDSQ0pNh5uI6/A5sDxH09t7MuPB73YZksm8fgspIIiIAIiIAIiEDYE9ARREAEREAEREAEvJeADCHee+5UcxEQAREQAREIbwI6ngiIgAiIgAiIgAiIgAh4JAHFwffI06JKiYAIeC8Bx9VchhDHnVIJJAIiIAIiIAIiIAIiIAIOJyBtl8NPsKeIp3qIgAh4EwHFwfems6W6ioAIiED4E5AhJPyZ64giIAIi4D0EVFMREAEREAER8EQC0nZ54llRnURABERABERABMKMQDh4gYRZ3VWwCHgGARlCPOM8qBYiIAIiIAIi4EwCel535nmVVCLgUAISSwREQAREQAREQAQ8k4C8QDzzvKhW3kRAhhBvmQ+uSwAAAdRJREFUOluqqwiEPQEdQQREQARCl4Ce10OXp0oTgeckINvkcwLU7iIgAiIgAiLgHAKSRAREQAR8ioAMIT51uiWsCIiACIiACIiACIjAvwR875dsk753ziWxCIiACHgrARnvvfXMqd4iIAIi4JkEZAjxzPMSfrXSkURABERABERABERABERABERABERABJxPwMsklPHey06YqisCIiACHk5AhhAPP0GqngiIgAiIgAiIQOgRUEnPQkD+mM9CTfuIgAiIgAiEHgHdiUKPZdiWpDMVtnxVugg4iIC6CwedTM8VJWDNZAgJSETLIiACIiACIiACIiACbgTkj+kGQz9FQAREwJsIOKauuhN5y6nUmfKWM6V6isALJ6Du4oWfAl+sgAwhvnjWJbMIeDkBOQ54+QkM1+rrYCIgAiIgAiIgAiIgAiIgAiIgAiIgAs4nIAlFIHgCMoQEz0dbRUAEPJCAHAc88KSoSiIgAiIgAiIgAi+egGoAyGNGrSCcCajJhTNwHU4EPISArn0PORGqhgiEgIAMISGApawiIAKeT0A1FAEREIEXQUAvQmFEXWDDCKyKFQEHE5DHjINPrmeKpibnmedFtfINAi9SSl37L5K+ji0Cz0bg/wAAAP//vq9KegAAAAZJREFUAwBVYky15iXMugAAAABJRU5ErkJggg=="
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"agg_df = nbs_df.groupby(['Center', 'Documentation Level']).size().reset_index(name='Count')\n",
|
|
"\n",
|
|
"fig = px.bar(\n",
|
|
" agg_df,\n",
|
|
" x='Center',\n",
|
|
" y='Count',\n",
|
|
" color='Documentation Level',\n",
|
|
" text='Count',\n",
|
|
" color_discrete_sequence=['#71bf44', '#ffba31', '#004649'],\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.update_traces(\n",
|
|
" textposition='inside',\n",
|
|
" textfont_size=12\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.update_layout(\n",
|
|
" xaxis_title='Center', \n",
|
|
" yaxis_title='Attribution Counts', \n",
|
|
" title='New Business Start Attributions Per Center FY 25', \n",
|
|
" height=700,\n",
|
|
" width=1500,\n",
|
|
" margin=dict(r=470)\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.add_annotation(x=1.5, y=0.0, xref='paper', yref='paper', showarrow=False, align='left',\n",
|
|
" text=\"<b>NOTE:</b>Documentation levels were determined as follows.<br><br>\"\n",
|
|
" \"<b>Documented:</b>There is a non-blank, non-'Requested on eCenter' <br>attribution source with a value in the affirmation column. If the <br>attribution source is eCenter, then no value is required in the <br>affirmation column as this is a data entry automatically generated <br>by Neoserra.<br><br>\"\n",
|
|
" \"<b>Has documentation but not in correct spot:</b> There is a non-blank, <br>non-'Requested on eCenter' attribution source, but no value in the <br>affirmation column <br><br>\"\n",
|
|
" \"<b>Not Documented</b>:There is a non-blank, non-'Requested on eCenter' <br>attribution source with a value in the affirmation column. If the attribution <br>source is eCenter, then no value is required in the affirmation column.\"\n",
|
|
" )\n",
|
|
"\n",
|
|
"fig.write_image('nbs_attribution_count_chart.png')\n",
|
|
"\n",
|
|
"fig.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"id": "dccee2ab-1357-4558-a99d-a23b25c3d1aa",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>Center</th>\n",
|
|
" <th>Total</th>\n",
|
|
" <th>Documented Count</th>\n",
|
|
" <th>Percent Documented</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>Bucknell</td>\n",
|
|
" <td>36</td>\n",
|
|
" <td>7.0</td>\n",
|
|
" <td>0.194444</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>Clarion</td>\n",
|
|
" <td>72</td>\n",
|
|
" <td>66.0</td>\n",
|
|
" <td>0.916667</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>Duquesne</td>\n",
|
|
" <td>53</td>\n",
|
|
" <td>20.0</td>\n",
|
|
" <td>0.377358</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>Gannon</td>\n",
|
|
" <td>40</td>\n",
|
|
" <td>23.0</td>\n",
|
|
" <td>0.575000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>Kutztown</td>\n",
|
|
" <td>116</td>\n",
|
|
" <td>32.0</td>\n",
|
|
" <td>0.275862</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>Lehigh</td>\n",
|
|
" <td>37</td>\n",
|
|
" <td>17.0</td>\n",
|
|
" <td>0.459459</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>Penn State</td>\n",
|
|
" <td>31</td>\n",
|
|
" <td>27.0</td>\n",
|
|
" <td>0.870968</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>Pittsburg</td>\n",
|
|
" <td>59</td>\n",
|
|
" <td>19.0</td>\n",
|
|
" <td>0.322034</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>8</th>\n",
|
|
" <td>Scranton</td>\n",
|
|
" <td>70</td>\n",
|
|
" <td>11.0</td>\n",
|
|
" <td>0.157143</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>9</th>\n",
|
|
" <td>Shippensburg</td>\n",
|
|
" <td>60</td>\n",
|
|
" <td>6.0</td>\n",
|
|
" <td>0.100000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>10</th>\n",
|
|
" <td>St. Francis</td>\n",
|
|
" <td>20</td>\n",
|
|
" <td>14.0</td>\n",
|
|
" <td>0.700000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11</th>\n",
|
|
" <td>St. Vincent</td>\n",
|
|
" <td>20</td>\n",
|
|
" <td>0.0</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>12</th>\n",
|
|
" <td>Temple</td>\n",
|
|
" <td>71</td>\n",
|
|
" <td>12.0</td>\n",
|
|
" <td>0.169014</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>13</th>\n",
|
|
" <td>Widener</td>\n",
|
|
" <td>38</td>\n",
|
|
" <td>19.0</td>\n",
|
|
" <td>0.500000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>14</th>\n",
|
|
" <td>Wilkes</td>\n",
|
|
" <td>30</td>\n",
|
|
" <td>13.0</td>\n",
|
|
" <td>0.433333</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>15</th>\n",
|
|
" <td>Network Total</td>\n",
|
|
" <td>753</td>\n",
|
|
" <td>286.0</td>\n",
|
|
" <td>0.379814</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" Center Total Documented Count Percent Documented\n",
|
|
"0 Bucknell 36 7.0 0.194444\n",
|
|
"1 Clarion 72 66.0 0.916667\n",
|
|
"2 Duquesne 53 20.0 0.377358\n",
|
|
"3 Gannon 40 23.0 0.575000\n",
|
|
"4 Kutztown 116 32.0 0.275862\n",
|
|
"5 Lehigh 37 17.0 0.459459\n",
|
|
"6 Penn State 31 27.0 0.870968\n",
|
|
"7 Pittsburg 59 19.0 0.322034\n",
|
|
"8 Scranton 70 11.0 0.157143\n",
|
|
"9 Shippensburg 60 6.0 0.100000\n",
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|
"10 St. Francis 20 14.0 0.700000\n",
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|
"11 St. Vincent 20 0.0 0.000000\n",
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|
"12 Temple 71 12.0 0.169014\n",
|
|
"13 Widener 38 19.0 0.500000\n",
|
|
"14 Wilkes 30 13.0 0.433333\n",
|
|
"15 Network Total 753 286.0 0.379814"
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]
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},
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"agg_df = nbs_df.groupby(['Center', 'Documentation Level']).size().reset_index(name='Count')\n",
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"\n",
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"nbs_documented = agg_df[agg_df['Documentation Level'] == 'Documented'].groupby('Center')['Count'].sum()\n",
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"
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"fig = px.bar(\n",
|
|
" combined_df[~combined_df['Center'].isin(['Network Total'])],\n",
|
|
" x='Center',\n",
|
|
" y='Percent Documented',\n",
|
|
" text='Percent Documented',\n",
|
|
" color_discrete_sequence=['#71bf44']\n",
|
|
")\n",
|
|
"\n",
|
|
"# Network total\n",
|
|
"net_total = combined_df[combined_df['Center'].isin(['Network Total'])]['Percent Documented'].iloc[0]\n",
|
|
"fig.add_hline(y=net_total, \n",
|
|
" line_dash=\"dash\", \n",
|
|
" line_color=\"#004649\", \n",
|
|
" annotation_text=f\"Network Total: {net_total * 100:.2f}%\", \n",
|
|
" annotation_position=\"top left\")\n",
|
|
"\n",
|
|
"fig.update_traces(\n",
|
|
" textposition='inside',\n",
|
|
" textfont_size=12,\n",
|
|
" texttemplate=\"%{text:.0%}\"\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.update_layout(\n",
|
|
" xaxis_title='Center', \n",
|
|
" yaxis_title='Documented Percentage', \n",
|
|
" title='New Business Start Attribution Rates Per Center FY 25', \n",
|
|
" yaxis_tickformat='.0%',\n",
|
|
" height=700,\n",
|
|
" width=1500\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.write_image('nbs_attribution_percentage_chart.png')\n",
|
|
"\n",
|
|
"fig.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 52,
|
|
"id": "e15a8709-cc0e-489d-bfe4-bd4b0c10985b",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"\"\\ntemp_agg = nbs_df.groupby(['Center', 'Documentation Level']).size().reset_index(name='Count')\\ncombined_and_wrong_spot_df = temp_agg[temp_agg['Documentation Level'].isin(['Documented', 'Has documentation but not in correct spot'])]\\ncombined_and_wrong_spot_df.head(20)\\n\""
|
|
]
|
|
},
|
|
"execution_count": 52,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"'''\n",
|
|
"temp_agg = nbs_df.groupby(['Center', 'Documentation Level']).size().reset_index(name='Count')\n",
|
|
"combined_and_wrong_spot_df = temp_agg[temp_agg['Documentation Level'].isin(['Documented', 'Has documentation but not in correct spot'])]\n",
|
|
"combined_and_wrong_spot_df.head(20)\n",
|
|
"'''"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 56,
|
|
"id": "399b7387-f4d1-454d-b655-6590bb165d32",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>Center</th>\n",
|
|
" <th>Documentation_Levels_Combined</th>\n",
|
|
" <th>Documented_Count</th>\n",
|
|
" <th>Grand_Total_Count</th>\n",
|
|
" <th>Percent_Documented</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>Bucknell</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>36</td>\n",
|
|
" <td>0.222222</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>Clarion</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>68</td>\n",
|
|
" <td>72</td>\n",
|
|
" <td>0.944444</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>Duquesne</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>21</td>\n",
|
|
" <td>53</td>\n",
|
|
" <td>0.396226</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>Gannon</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>24</td>\n",
|
|
" <td>40</td>\n",
|
|
" <td>0.600000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>Kutztown</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>42</td>\n",
|
|
" <td>116</td>\n",
|
|
" <td>0.362069</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>Lehigh</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>27</td>\n",
|
|
" <td>37</td>\n",
|
|
" <td>0.729730</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>Penn State</td>\n",
|
|
" <td>Documented</td>\n",
|
|
" <td>27</td>\n",
|
|
" <td>31</td>\n",
|
|
" <td>0.870968</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>Pittsburg</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>28</td>\n",
|
|
" <td>59</td>\n",
|
|
" <td>0.474576</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>8</th>\n",
|
|
" <td>Scranton</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>31</td>\n",
|
|
" <td>70</td>\n",
|
|
" <td>0.442857</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>9</th>\n",
|
|
" <td>Shippensburg</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>38</td>\n",
|
|
" <td>60</td>\n",
|
|
" <td>0.633333</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>10</th>\n",
|
|
" <td>St. Francis</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>18</td>\n",
|
|
" <td>20</td>\n",
|
|
" <td>0.900000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11</th>\n",
|
|
" <td>St. Vincent</td>\n",
|
|
" <td>Has documentation but not in correct spot</td>\n",
|
|
" <td>15</td>\n",
|
|
" <td>20</td>\n",
|
|
" <td>0.750000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>12</th>\n",
|
|
" <td>Temple</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>60</td>\n",
|
|
" <td>71</td>\n",
|
|
" <td>0.845070</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>13</th>\n",
|
|
" <td>Widener</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>24</td>\n",
|
|
" <td>38</td>\n",
|
|
" <td>0.631579</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>14</th>\n",
|
|
" <td>Wilkes</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>18</td>\n",
|
|
" <td>30</td>\n",
|
|
" <td>0.600000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>15</th>\n",
|
|
" <td>Network Total</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>449</td>\n",
|
|
" <td>753</td>\n",
|
|
" <td>0.596282</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" Center Documentation_Levels_Combined \\\n",
|
|
"0 Bucknell Documented,Has documentation but not in correc... \n",
|
|
"1 Clarion Documented,Has documentation but not in correc... \n",
|
|
"2 Duquesne Documented,Has documentation but not in correc... \n",
|
|
"3 Gannon Documented,Has documentation but not in correc... \n",
|
|
"4 Kutztown Documented,Has documentation but not in correc... \n",
|
|
"5 Lehigh Documented,Has documentation but not in correc... \n",
|
|
"6 Penn State Documented \n",
|
|
"7 Pittsburg Documented,Has documentation but not in correc... \n",
|
|
"8 Scranton Documented,Has documentation but not in correc... \n",
|
|
"9 Shippensburg Documented,Has documentation but not in correc... \n",
|
|
"10 St. Francis Documented,Has documentation but not in correc... \n",
|
|
"11 St. Vincent Has documentation but not in correct spot \n",
|
|
"12 Temple Documented,Has documentation but not in correc... \n",
|
|
"13 Widener Documented,Has documentation but not in correc... \n",
|
|
"14 Wilkes Documented,Has documentation but not in correc... \n",
|
|
"15 Network Total NaN \n",
|
|
"\n",
|
|
" Documented_Count Grand_Total_Count Percent_Documented \n",
|
|
"0 8 36 0.222222 \n",
|
|
"1 68 72 0.944444 \n",
|
|
"2 21 53 0.396226 \n",
|
|
"3 24 40 0.600000 \n",
|
|
"4 42 116 0.362069 \n",
|
|
"5 27 37 0.729730 \n",
|
|
"6 27 31 0.870968 \n",
|
|
"7 28 59 0.474576 \n",
|
|
"8 31 70 0.442857 \n",
|
|
"9 38 60 0.633333 \n",
|
|
"10 18 20 0.900000 \n",
|
|
"11 15 20 0.750000 \n",
|
|
"12 60 71 0.845070 \n",
|
|
"13 24 38 0.631579 \n",
|
|
"14 18 30 0.600000 \n",
|
|
"15 449 753 0.596282 "
|
|
]
|
|
},
|
|
"execution_count": 56,
|
|
"metadata": {},
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"output_type": "execute_result"
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}
|
|
],
|
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"source": [
|
|
"temp_agg = nbs_df.groupby(['Center', 'Documentation Level']).size().reset_index(name='Count')\n",
|
|
"\n",
|
|
"combined_and_wrong_spot_df = temp_agg[temp_agg['Documentation Level'].isin(\n",
|
|
" ['Documented', 'Has documentation but not in correct spot']\n",
|
|
")]\n",
|
|
"\n",
|
|
"documented_agg_df = combined_and_wrong_spot_df.groupby('Center').agg(\n",
|
|
" Documentation_Levels_Combined=('Documentation Level', ','.join), \n",
|
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" Documented_Count=('Count', 'sum')\n",
|
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").reset_index()\n",
|
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"\n",
|
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"total_agg_df = temp_agg.groupby('Center').agg(\n",
|
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" Grand_Total_Count=('Count', 'sum')\n",
|
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").reset_index()\n",
|
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"\n",
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"final_df = pd.merge(\n",
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" documented_agg_df, \n",
|
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" total_agg_df, \n",
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" on='Center', \n",
|
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" how='outer' \n",
|
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" \n",
|
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")\n",
|
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"\n",
|
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"final_df['Documented_Count'] = final_df['Documented_Count'].fillna(0).astype(int)\n",
|
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"final_df['Documentation_Levels_Combined'] = final_df['Documentation_Levels_Combined'].fillna(0)\n",
|
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"\n",
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|
"final_df['Percent_Documented'] = final_df['Documented_Count'] / final_df['Grand_Total_Count']\n",
|
|
"\n",
|
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"total_nbs_milestones = nbs_df.shape[0]\n",
|
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|
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"network_total = total_group / total_nbs_milestones\n",
|
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"\n",
|
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"network_total_count = pd.DataFrame({\n",
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" 'Center': [\"Network Total\"],\n",
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" 'Grand_Total_Count' : [total_nbs_milestones],\n",
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" 'Documented_Count': [total_group],\n",
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" 'Percent_Documented': [network_total]\n",
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"})\n",
|
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"\n",
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|
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]
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POi73xjaY7w+cqL4upQmOR2+awwJBhbYV7FP9Fkqav84c0ps6/7j0ZlxBI3040pv0sHoyVcChUN+l5ql/fRhQIEXBKf3lXZcaX//1i3P7Tn0pmKR7cQXvLan56w236rjk9r8+TGouLl+Oqqtx642lAmvBOtpX8tN+cO30KCO11bKSzrRS0od5rUclHUv+9qqv9kr+PsLm745xtVMK2year3/fqW6cSePQ5ck6Zg8df5C3qbB95RVW6EfYfirUvV4L9IHCJX3YC34I0TGh1wcFe/RhztXVowJ1hfqNynMBXPc80jH10Q8d2esS2qh+/OXqQ9b+1ysd18HXBx1Tmovuu+na6zn+vX/5slsNfdRz8tqblpiOeR23rqLaK09lquPy9dqr4KGOPeXJUmfP6HmsIJzydJyU8lqjfvV6oCCB5qW26k+BtU/PmKbVoknHoHzc7wLXnwJArkxn7akTjU1jLPRhVOWlplLmX6wvuSr567jj2wVPXFl/t6V+XJ8KyGhdr0FKF3E+hgAAEABJREFU2j/aT8rrb9Jxon2mfVdKX6rvf33UsTRQr2M640vHgQL7brw69vQ7SPkq988hOFbZKek5569XaFnPJ/3O0uv8tJMvMr2+KBUKdujY1XNN21M715+OFeWpTHVcfl8edRwpkOXvV+01V81Zc5eB8pS0P+Z9+b9q0Yq9Bul3qn63ehWL/ND2o14z1FxzVdKyS4WeG4XGpPp9eW5rO0pq51KhbalMr60KijojPeo1WK9dpewTPc8G+vemxqxgqval5uBPKis0n7B8/zz1nPl+5veKv1/lBX8H+LcXvZw2dywOxPPSjSf4XkHPzeAZstrX+myh5/B/u/w73tUrCpa6Pvr6qGNBr716TrjXZNeHjkcFml1SwFm/3xQo1ftcV49HBBBAAAEEGlGAwGgF9qo++OoNnT8ooG4VeFMATmeG6M2ILuXSX/l1KZPeyKlONZPeUOsNZ6HxuDdMG/fdEy9qnC4wUKyeCwwoaBCspzwFInVJqqvXlw8Zwf4KrWsf6Kwybce9+dWHS73xUxDD30bryi9lXmH739+fggMKgAaPEb3pVVDGHSP+NoWWS62nttq/epOtN9tK+mCsN9cqc0nz17gUVHN5hR7dPtF+CpYrT6bad8GySq+7cfiPWbev9MFP+7jS21R/2k/6IFrKB3EFEdwHC/eooIDO9NDZUW6M6lP3l1QdtdF2lNyHJV+AVNklJX2wVsV/ueHH3mX12jdaLyfp+Cn19UHPVQV/9fxy89M2p0+dGBmY1XGj46fQWNWvylRH/RVLOtPFvV6546RQn8pzfbrXaJkHzxbUJYhRr9Mq1x9r5CQvjXPE8BbT89yVuePSjc29thabSzll/vlHtVcwScExvS4oueB9VDtXXuq2dCxo/not1fNU7eWi568CYtpPyquF1JdjrT/j1e8Uv4frS6/Bei1Wucsr9ljq7wIX7NBrkIIh6lP7T8EOHQM6FpSnY1fPCz0/tO5PcdloroUs3Lb1nNJzS8eLjhuXr0f3PHLPK+X1Nckh2F4ectHzQin43HBj0vM+OKa+bj9qW1H9aX9pv0XV0/NMzze/o56PstfzU8/TqD5qrVyv19o/LukPjOWPMWVhx2Jcz0uNVb/39fvfn/SeQO8NVO6S/hCipHUFSYPlyi816SxjvQ/UVQL+4HKh9jq+3R9wFUytx+Ok0LzIQwABBBBAoJBAjQVGCw2x9vL0RlpvqPVhQaPTGyo9BpPeVOjNs4KhCorqDazeyAbrVWvdjUeX5bk3l+5RH5o0x0qOzbnpDazbjntUntuWq6fLAF1euY8KeLhtKDCofnS5pd4Q6k2ePlzqTaLKXD09al35qh+Vwva/v53qKHCkD1nq3580Rn/dSizrQ4O2paCre9Otv/67N9fahpu/gvcKECkvLLl9ov3kH7uWlRfWrtL5CjDruPQfs25f6YOfPgBWepuuP33RgT5I6qxvPZ9dfimPOt70QSRsjDp7ze0nPeoDk46Lvp6loQ9MCuA+/uRy01j9+7uUcfrr9OX1QcGXQmem6Tj091lo2R1bhcr0GqD9rTqFysPyVF/tdGzqGPUn5bl2eo3Wpcly8h9TCowoaOHqFXtUIEmv6/LS8an7vbrnk8rc67/+CKF9ooBEsf7iLlPAXa/vOh51rCnpklX9ca/S29bzUce8Xkv1PHX7QdbaP/Kq9DbL7U/HWrltS23nXnML1dcxo9di/U5SvUJ1+pOn1yBdzqz9raRAqfrT65m2554zygsm2Wh/qU6wrNx1bVNzLdZezyk9t3S8uGPHPeoY1piKte9rWSnPDTcm9/6vr9tw9UvZlqvb30c9z2Tld9TzUc9LPT/1PO3vNgaqvQLT+oOv/tCoY1jHspJex8sdQ7FjMe7nZSlj1u8pBbX1hw1dzVNKm0J1dMzpfYV+V+t3dqE6wTy9p9D7SPd7LFjOOgKVEaAXBBBAoPoCBEbL2Af6gKs3KO6MhbA3yO7Nlj7s6M2V+8tzGZuMpYkbj94k6Y1loRS89K0/A9EbOrnpDWyhbelDmz68uXr92ZZrqwCTf1v+yy31ZlOBawVFFDT013PLCli5vsIew/a/v77qKPCgAITr2//oH5e/XTnL+uCgy6k192Ljd/MvZRtun0Ttu1L6KreOf15+Oy3rA5L61QdAPcaR5KXL9fRh8jfLV5e1CX04LSW4oNsD6Lmis5H7uiG9Lqmtxqox97W9q9/X1wd90NK+UNLzSc8rfRCPCu66Y8tt1/+o+WsuquPPj1pWfbUr5XiVkZ5/GreSO5Z0rzsdc6VsS3V07OkPIPoAqz6Vp3EosKNjRkEgvd64MpUPdFKwV2c96zVf+yvu7euSY50FGXzdc8dHLZ2tpmMtbg/tex0DhbajP7Yo+KBy1StUp5J5+l2r2wdom9q2jlU9ZwptQzYqU51C5eXkaY6aa7G2fX0NKtZXVFmpzw03pqj+QsszBaVuK1O13//0GubeD+j1zZ/ca51eu/q9oQHqQLc30muq/9YI/d10sWNRzw09R3Ssql5/t1Wt9uUERTXW4OcY5ZEQQAABBBBoRAECo33cq+4Nrc620QcLNdfZFDobUDc017pLwTdUCo4qSFrow6D61Y3VXVu9EVN7tx7HY7Hx9Gd78ijU3n2gUGC5ULnLK7Weq9+fRwUs+3vGhOZbaP9rXHc/8CvTG8tidVSvnOScgm37ckZLqfN324rad8GxVHJdzy856yy8YL86C09n4+kDoD4IBssrta5gn9IP/8/D3hfr9LVfF1zQGL9/x32hzTdu2ep9aYqOm9BKIQV6XdIfGfr7R42+vD6449wNSR8gdbsKzVdBFeWHzaXYsaVAowJrqqM+Sk2qr3ZRx6v2w4O/fDavW/np9V0fvvVcyisssOKOvXt+9oR3+wL/PF3Zo79eZnqdKXTsBrt0Yw/mV2K9P8dVX7cvW10GrbONdNaRv72ODwWQFTBWUpnfTev+pNcp/3ocyzrW9Bqifeb6L/UY6Mv4VFfHQvAsPR1r2p7K3fb7+6jnpd5bFOpHv5cUrNd7Ej3X3XFX6DkjGz2fVMffl3tu+/P6sqy5FrLQ2DR2jUvjK/SeqS/bKaVuqc+NSoyp1G2VMu6oOrXwezNqjH0pDzsWC/Wh46tQfqE81S10LMbxvCy0/bjy9FzSLXx0pqj+UNjXP4jpc4g+j9R7YDguX/pFAAEEEGgcAQKjfdiX+ourLt/SWRa+NxemAITOzpu34HZzH0L0ZkT321P37kbp+jCoYIHefOk+PypTUpsvXbHQdnd0aNX04VkBIL2h9TIyP3RJqs6+yixW7J9/PLq8VGN2nWv5y//0/dx8XH4pj+6skuBZCPpwrPsj6Q2aLP196UO03rzpUfV0ObDObJKNqycDtXXrlXh0l0fL378t9a3tKWm5WCq0/1Vfc/zF0mVazB0jcg6eQad11fUq9uFH2Ac0fbDXB3z/h0ntT23bBSHcZnRPSn3g1ZldLk/7QGfL6exGl6d9Usq+c/XjeNQHdp11q/s3BvvXsawzJIPPm2C9/q677fxlwyYvcFlqf9rHev7qtUOBN7V76PHfeF+GojKtu6R17Su9pujYcvkD/ai5utcrjUfHkBuDlv2vD39Y/aqdft4/m44dV8c9/3UGq/JKeV3wP9+0rOe7jjsdf+qj1KT6aqf2weeWxuhea9TfTT/8qfnraG567ug5pOeS6hRLclKQT8eEnkv+49OV6dYGwbKwPsOe12H1+5Kvsek5pOeSayePcy5dYHruuLxKPOr3l/rU77NC/em1xz+WsONDbRU0VV/qU+v9TQoIaj+7ftyxptcQ7TPlu+PWHcfKc89NLftTX8bnfufoNVb26kePWtcxp3LlVSLtau80vWfR8e6fr5b1nNZ7ET3HNWf/c0Yebvta1vNIzyfVUb6eFxqrnifqS3maQ1+PI81V/Wjuaq9+1J/GptcUjUvj0ziVpzLVUdKy/zVIef1JpT43NCYdJ/pdquS2qWNDr/Fuvdhjqdsq1kepZXqu63mmbQbbuLlU8rkV3Eal1/V6Ehyv7HV8BLdVq8/L4DjjWtdzRC56/ujs4GLvJ/T+d/YF8/N+h6t98HNMXGOlXwTqUIAhI4BAgwkQGA3ZoXrDq3swuftZ6VFnv+iSwEKXJytPZxnpQ4jqqq26/skd3zT3YULrCoromzrVl+opqY3aujctetSljnpDo3IltVWeHiuZNB7dc1N9aszalpKWh7cMjfziFLULJvW5YN75pg8J6ktJb1xVT3OToX/+Ktf9MBVccFYKPMtENipXUnsFi/RYqaQPBrqMNrgtbU9nH+rDeynbCu5/tdccdeN6bUN9qI7+Yu/fr6qngLounVadviT1q/7113ztL6+va2435Ws76svlf2r239tFX/ic6WxH5bskb307rMaq9kr6cKsPwTrbz9XTY6n7TnUrnfSmXYHyQmefuW3pg58+AOqDoMuL41GGSmF9K4ggR3/SPtc+0TGgdnLXa4P6UZm/ro4HfYhxdVV/wFI6f0t6Lpfy+vC1y84xndml57Gbi54/eq1TH+pVj8VeFzRn3TfOtdey8nTcqX1fk9pFvdZoP1z/9Yu9Mz3ddvWc0dkxel3Qc6mU7eoDuOrJQIFNLbtUrMzV8T9qm4We1/465S5rvoWe7/82/2LTc6fcfoPt9IFaX9ahPvW8DJZrXWPR81mvPQqKRR0f+v3nnit9uQesthVM69/cbHpNdPu80LFWaDx6bdHzONifjrVSx6f9q2NLc3fPFz1qXfkqD/Zf7rp+j2q8wfcz7hjXmeWap+tf89BzTh7FbDTG4DGq3xt9PY7Uj+asuctA29TYNB69puhR4yvlNUh1+5N0PJb63JCTXN3xqHHr2NAxUMoY+rKtUvoLq1O535thWxj4/DB77Y/gaFRX+8Ttp2KvG4WORR2TOjZ1jKo82H+tr+usdAVF9Udu/3tpHa9Kfg/9sUP3x9acVabknot6r6Jjttbny/gQQAABBBDojwCB0YCe3vzoTZD/PkxuudC3Rfqb60OIq6tH9aP+/HW0rDcY6kt1XFJblbmkdVemR60rqZ3aq54eta58rbvU13yNUWPVdvzJH5jRhxN9iArblr+uxqE3pP6+tK58JTc+f7mWg31rXfkuaV3b0Vg1ZvUVltw2VD+sjj9ffbvtuEfZqh/VC5u/ylwK9uFv7+rIwfXvHuWq/lVH21O74Lg1X81bScuqq+Tqu75cO9VRXZevbegbwpXn6qi9UrAPbV/5Su4sLi0rBeu6/jV3lRdLqqNxuLm6MQbHU6gPtVHbYnXd2Fwd10bbdX2qTPNTXZdX6NGNTV5a9tfRuvI1d3/f6lN9K79Q0r4P68dfX/PU2P11w5bdWDQeLYfV0ziD/QYtvPEvWWjK9/ejftW/f4xa9tcrVEcW6tPflwzU1iWtu3LNWWN0ZVpWnivXY6F5KF/9qJ0ete6Stq9xqMyf1I+ro21oW1750kWmR//cXL1ij9qu2l+6jP4AABAASURBVMlJFv66xcrc+ILbc/nqU8mVa9waq8ZcaBvalj+/0HKwb/lMOnKC6VH9uzZaLndbMpCF+tT2XJ/BR83LX0fj13xd0rpro/G4fDcu9a326sfV8z8qX+Wqp3w9av0XS/7V1EewP9XxJ23f1dGj+lOe2gb3QV/Hp77Up0ta92/bjTWY72zlq2V/m0LLGq/bhv8x2K9rq3lpfq6ulpXnyt2jG5+rJ9e+HEeuHz1qLK4fPQbnpnkqT2X+pHZqXyxpvxSag3PRo2tf6pxUX+2CY9G25KB+VKdYUh3VdX1ouZCf5qgy1ff3p20Vmpe/jvab6qgPf75/Wf2qf1fHrav/QvWC+W4b/nz1pT7Vl78PLateobK+5BeyV57mqvFoOy6pX2fsyjUujUHjdPXco/JcfT1q3ZXpMaytO0Z1nGpZdcNSWB9h9ZWvebjxa72UJAu10TwKJZWpjvrSmDX2YD3lqUx14kiBv8XGsQn6RAABBBBAoCQBAqMlMTVeJWaEgAR0ZlfwckTl6Wwv/2XfqktCAAEEEEAAAQQQQKASAqlKdEIfCCBQsgAVEUAgXIDAaLgNJQgkQmDXrg7vPnS6dEpJl0/ptgbBMyUSgcEkEUAAAQQQQKDeBRg/AggggAACCCBQsgCB0ZKpqIhA4wnoEildKhW8fEqXbTXebJkRAo0owJwQQAABBBBAAAEEEEAAAQTKFSAwWq4c7QZegC0igAACCCCAAAIIIIAAAggggEDjCzBDBAZIgMDoAEGzGQQQQAABBBBAAAEEEECgkAB5CCCAAAIIIFAdAQKj1XFnqwgggAACCCRVgHkjgAACCCCAAAIIIIAAAjUhQGC0JnYDg2hcAWaGAAIIIIAAAggggAACCCCAAAKNL8AM61GAwGg97jXGjAACCCCAAAIIIIAAAghUU4BtI4AAAggg0AACBEYbYCcyBQQQQAABBBCIV4DeEUAAAQQQQAABBBBAoPEECIw23j5lRgj0V4D2CCCAAAIIIIAAAggggAACCCDQ+AKJnyGB0cQfAgAggAACCCCAAAIIIIAAAkkQYI4IIIAAAgjkCxAYzfdgDQEEEEAAAQQQaAwBZoEAAggggAACCCCAAAJFBQiMFuWhEAEE6kWAcSKAAAIIIIAAAggggAACCCCAQOMLVHKGBEYrqUlfCCCAAAIIIIAAAggggAACCFROgJ4QQAABBGIUIDAaIy5dI4AAAggggAACCPRFgLoIIIAAAggggAACCAycAIHRgbNmSwgggEC+AGsIIIAAAggggAACCCCAAAIIIFA1gQELjFZthmwYAQQQQAABBBBAAAEEEEAAAQQGTIANIYAAAvUiQGC0XvYU40QAAQQQQAABBBCoRQHGVM8C6XoePGNHAAEEEEAAgf4KEBjtryDtEUAAgUQJMFkEEEAAAQQaSCDVQHNhKggggAACCCDQZwECo8XIKEMAAQQQQAABBBBAAAEEEEAAgcYXYIYIIJBIAQKjidztTBoBBBBAAAEEEEAgyQLMHQEEEEAAAQQQQMCMwChHAQIIIIBAowswPwQQQAABBBBAAAEEEEAAAQR6CRAY7UVS7xmMHwEEEEAAAQQQQAABBBBAAAEEGl+AGSKAQH8FCIz2V5D2CCCAAAIIIIAAAgggEL8AW0AAAQQQQAABBCosQGC0wqB0hwACCCCAQCUE6AMBBBBAAAEEEEAAAQQQQCBeAQKj8frSe2kC1EIAAQQQQAABBBBAAAEE6k4gXXcjZsAIVF2AASBQUwIERmtqdzAYBBpVgLeMjbpnmRcCCAQEeLkLgLCKQNIFmH+jC6QafYLMDwEEEGhwAQKjDb6DmR4CtSHAW8ba2A+MAoGYBejejJc74z8EEEAAAQQQQAABBOpFgMBovewpxllzAgwIAQQQQAABBGpMoJ9n7PazeY1hMBwEEEAAAQQQqJQA/TSuAIHRfu7bN7Z0GAkDjgGOAY4BjgGOAY4BjoEaOAbe7t8YNvC+jve1HAM6BkgcBxwDHAMcA3V0DPQzrJX45gRGE38IAIAAAggggECSBZg7AggggAACCCCAAAIIJFWAwGhS9zzzTqYAs0YAAQQQQAABBBBAAAEEEEAAgcYXYIYlCRAYLYmJSggggAACCCCAAAIIIIAAArUqwLgQQAABBBAoR4DAaDlqtEEAAQQQQAABBKonwJYRQAABBBBAAAEEEECgAgIERiuASBcIIBCnAH0jgAACCCCAAAIIIIAAAggggEDjCwz8DAmMDrw5W0QAAQQQQAABBBBAAAEEEEi6APNHAAEEEKi6AIHRqu8CBoAAAggggAACCDS+ADNEAAEEEEAAAQQQQKDWBAiM1toeYTwIINAIAswBAQQQQAABBBBAAAEEEEAAAQRqXKACgdEanyHDQwABBBBAAAEEEEAAAQT6IpDqS2XqIpAkAeaKAAIINJYAgdHG2p/MBgEEEEAAAQQQQKBSAvSTXIF0cqfOzBFAAAEEEEiSAIHRJO1t5ooAAggUEHCf/QoUkYUAAgggkDQBzpRM2h5nvggggAACCCRaIKmB0UTvdCaPAAII+AX4DOzXYBkBBBBIuAB/LUv4AcD0EWhIASaFAAIIhAoQGA2loQABBBBAAAEEEEAAgXoTYLwIIIAAAggggAACpQoQGC1VinoIIIAAArUnwIgQQAABBBBAAAEEEEAAAQQQKFOAwGiZcNVoxjYRQAABBBBAAAEEEEAAAQQQQKDxBZghAggMjACB0YFxZisIIIAAAggMsAB3jx1gcDaHAALlC9ASAQQQQAABBBCoigCB0aqws1EEEEAAgeQKDNTM+QaVgZJmOwggUIsC/HGoFvcKY0IAAQQQQKDWBAiM1toeabTxMB8EEEAAAQQQQAABBAZcgD8ODTg5G0QAAQQQQKAOBQiM1uFOY8gIIIAAAggggAACCCBQXQG2jgACCCCAAAL1L0BgtP73ITNAAAEEEEAgbgH6RwABBBBAAAEEEEAAAQQaToDAaMPtUibUfwF6QAABBBBAAAEEEEAAAQQQQACBxhdghkkXIDCa9COA+SOAAAIIIIAAAggggEAyBJglAggggAACCOQJEBjN42AFAQQQQAABBBpFgHkggAAC/RdI9b8LekAAAQQQQACBmhUgMFqzu4aBIdAnASojgAACDSxAYKKBdy5TQ6DGBdI1Pj6GhwACCCCQQAGmXEEBAqMVxKQrBBBAAAEEEIhDgMBEHKr0iQACCNSHAKNEAAEEEEAgPgECo/HZ0jMCCCCAAAIIINA3AWojgAACCCCAAAIIIIDAgAkQGB0wajaEAAJBAdYRQAABBBBAAAEEEEAAAQQQQKDxBWp1hgRGa3XPMC5LJ/jKyb17Ezx5jn0EEEAAAQQQQAABBOpbgNEjgAACCNSJAIHROtlRSRzmym2/tLte/YdEptXbf2WERpN41DNnBBBAoB4FGDMCCCCAAAIIIIAAAvUpQGC0PvdbIkbdtWeXbWh/KZGpMzP3ROzkepwkY0YAAQQQQAABBBBAAAEEEEAAgYYQKBoYbYgZMgkEEEAAAQQQQAABBBBAAAEEECgqQCECCCCQRAECo0nc68wZAQQQQAABBBBItgCzRwABBBBAAAEEEEDAYg2Mtnd02rmXX2uTZ8y1Y0+92Fa9tNZc3h1LHjL+QwABBBAYCAG2gQACCCCAAAIIIIAAAggggAACQYFYA6PfuuFOO376FFv28C02bepEb9stQ5vtnNkn2dPPr/SCpF5mJX/QFwIIIIAAAggggAACCCCAAAIINL4AM0QAAQT6KRBbYHTTlm32ypr1dszRk3oNsa11tO3c3WG72zt7lZGBQBwC3TvS9uKNaVv5bfPSxqcKb6V9fdpWX2fmL3d5avvqj832dKVzjdfdn86rmyvwL/RU9+eyjAACCCCAAAII9EmAyggggAACCCCAAAKVFYgtMFpsmBu3bLURw4basJbmYtUoQ6AiAgpkrrs/ZQdOTdmUr5odPjdtm58z2/5ifvcKgK5dksoEPvPzNy8zG3eqeW0HH5C2XWtSXgXV35uJ7bdOi4h8Zqt7bfiBAAIlC1ARAQQQQAABBBBAAAEEEEAAgVgFYguMjm0dZbNmTrfrb7k778xQnUl67U1LvEvsdVl9rLOrm84ZaJwCCmR2b0/b6A9lA5gt41I2/APpTGA0u65t64zS9Q+l7H1npK3lfcrJJgVVFfwcPCJbt3lMyro2Z8sUMB39kZQNGkLk0/r0H1594qIyAggggAACCCCAAAIINJAAU0EAgVoSiC0wqkmeN+cU736iM864zB5/crmdeeF80/LVl8wxlakOCYFqCCjA2b1DZ4emTUHRV39k1vZxs5ZD8kejoGdTs1n3zmwwr3Nz2oaMMXNniw4/NBswzW/FWnEBzIr7UIoAAggggEADCTAVBBBAAAEEEECghgViDYxq3jOPm2qrli7KS8pTGQmBgRBoOSQbiGt/Ixvc9G9TZ4TqMvuDT0zZyOz3g/mLveUx08zWP5i9N6mCqQqGurNFdTaq7j2qpPuNeg34gQACiRVg4ggggAACCCCAAAIIIIAAAvUjEHtgtH4oGGkfBeqm+uADUqbA57r7ssFNBTHf+rWZ7heaspTpMntXtvq6lLW/bqZy9wVMuvR+0pXZe4we/gXzLqXX5fUKuG79fdq7Z+mkK3XmacqC9y2tGyQGigACCCCAAAIIIIAAAggggEBhAXIRaFiBprhmpnuJzjr7Kps8Y27RdMeSh+IaAv0ikBPQ2aD64iWXRk5O28iJqUxwNGUTL81+KZPKFODUPUbf8wmzthNyzfMW3NmiynSX2OuSewValUdCAAEEEEAAAQQQqGcBxo4AAggggAACSRGILTCqL186esoR9vcXnpl3Gf2yh2+xv576Qbtpwd+Zlp9+fqURHE3K4VYb89SZoO6S+L6OyH9v0aYhZu5LmXRJvvrsa3/URwABBKouwAAQQAABBBBAAAEEEEAAgYQKNMU1b50x+sqa9XbM0ZPyNtEytNmOnz7FHvv1b03L58w+yRQcbe/ozKvHCgKVFFAwVJfQK+kLlHRJvM7y7Ms2FPzc+KSZvqRJbZW0vHZJynQJvs4YHRlyn9K+bIe6CCCAQOIEUombMRNGAAEEEEAAAQQQiFmA7hEoRSC2wGixjR/2/oPtzY1vm4Khba2jbefuDtvdTmC0mBll/RPQZfG6VF5p/Gnhn8AV7FTQVPWDW1TZhP+SMt1z1JVp2d1/tFi/rj6PCCCAAAIFBLLfkVeggCwEEEAAgRIFqIYAAggggAACZQjEFhgd1tJsI4YNtY1bthYdlsp37movWodCBBBAAAEEEECgR4AlBBBAAAEEEKhnAf4mWs97j7Ej0FgCsQVG3WXy8xbcbqteWptT0yX21960xHQJveq89ucNdsh7Wk2B1FwlFhBAoEeAJQQQQAABBBBAAAEEEECggQTCr+FroEkyFQTKEaDNgAvEFhjVTGYeN9V+cP1V9qUrFtrkGXO9NOMunvk5AAAQAElEQVSMy+zqS+aYylTnvDmn2A+/e7V3v1GtkxBAAAEEEEAAAQQQQAABBBpfoPwZElYr346WCCCAAAJ+gVgDo9rQ5KMm2LMP3myrli7KpZmZgKnKSAgggAACCCCAQEIEmCYCCCCAQMUEuBC7YpR0hAACCCRcIPbAaMJ9mT4CCRVg2ggggAACCCCAAAIIIIAAAggg0PgC9T3DhguM6n6mx556sXfZvi7ff+KZFXl7SOvKV5p19lWme566CncseSjXTssuX3VmXzA/716proxHBBBAAAEEEEAAAQQQQKC6AlxaPmD+bAgBBBBAoKEEYg2MBoOUCka6FAxKVkJVAcwrvnGzLZh3vnfZ/k0L/s78X/6k8XznxsV2z62ZIOfSRTb7MzPs6m/dau0dnV6A9OnnV9rS+27wkpbVn8b1s0efsVkzp5tuC6B1EgIIIIAAAgggkAQB5ogAAvUiwKXl9bKnGCcCCCCAQG0JxBYYVbDx+lvuti99/lQvEPmpjx9tyx6+xQtYfu7Tx3tfwDS2dZRV8j8FMA95T6v99dQPet3q8YNHvN+eW77aW9fjRz90ZC7AeczRk2z9m5ttzbo3bePmbTZ8+FAb1tLsJS0rT8FRBUk/e9JxXh/8QACBhhVgYggggAACCCCAAAIIIIAAAggg0PgCuRnGFhjd3d5pO3d3mIKP2tqGt9425Wn5xE98zO6891HvTE2tx5VahjbbQW0H2qtr13ubcI/eSuZH25hRlkqlbOOWrablXbs6vDFqnFpWnoKtx0+fYpUO4mY2zz8EEEAAAQQQQAABBBBAAAEEYhagewQQQACBMIHYAqP+DSrAOGLY0FxWW+toL2iqAGQuswILCsK6M0DDujt8wriCRQp8KgA644zLTEnLqujOFp13ze02ecZcL+k+pSpTGj18fyNV3mBky2AblOBbJQ1qStmojAHHVuWPrYqajsiMr8bTAZnj6MDMGEn7GwYYcAwk5BjgNY/XuwY/BkZn5tfdtMl2p9cnMr3TtHlAj3G9l5I5qcLve/kcTRyBY6Bix4BiU6TyBWILjOqSdAVDdfm6go46c1NnX2qoylOZ6mi9Ukn3AD3zszPtzAvnewFMBTIf+MXT5g+GBs8a9W/7vDmneJf6r1q6yLSs8SpAqkvqd7V3eLcC0P1Jb170gHdPUrXteOddI1XeoLP7Xdsr4ISmdDptMuDYqvyxVVHTzsz4qpw6Irbf9c4ea+8iYcAxwDHAMcAxwDHQMMdA5nf/C1uW292vfDuR6aUtK2x3xmCg9mdX9x6Ler9FeRnvifkcTRyBY6Bix0BCwyYVm3ZsgVFdxv7D717tBRg12ssvmG33/nypF7D8wV0P2hUXnWWqY6X/V1JNBTQV2FTSPU11b1OdSarG/gCp1hXwVABKZ7Bq3Z/89xbVpfa6tF7lwbNfO9/Za6TKG3R1py0TGxR5ItPetFlnxoBjq/LHVkVNuzPjq/HU9W5mjJngaCfJMNiDAc8DjgGOAY6BBjgGujLvPbr2dNjbXX9JZOra026dGYOB+r0ub2972iYpa18Jh+jP0VbR9+1sD88GPgYSGTSp4KRjC4wqsDj7gvm26qW13nB11ugjixd6Z2QumHe+6YuZ9AVNXmFMP751w502vGVo3pct/e6PL+fGpDNXxx00xg4df1CvEbizRTVuBU71ZUyqpGCq7p2qZRICCCCAAAIIIIAAAv0XoAcEEEAAAQQQQACBagjEFhgtNhkFGhVcrPQ9RrVN/71AdYbogn88X9le0qX2X7n07Nyl9jqD9dqvXdjrzFUFc/+w+k8257RP5tp9eNIHbNrJF3ltL577Ob6MyZPhBwIIIFCGAE0QQAABBBBAAAEEEEAAAQQQqAGBqgRGdaZmafcYTfeZSIFQXUavpMvqgx3MPG6qd9aqynUGq84IDdZRAPX73/xyXsBUfamNkvoItglbJx8BBBBAAAEEEEAAAQQQQACBxAkk8Mt0E7ePmTACDSBQ8cCozrY89tSLbcYZl9nql9d6Z1hOnjHXu7eoeyz9HqNVfCWt4qYb4LhiCggggAACCCCAAAKNLcDsEEAAgeICfT/PqXh/lCKAAAIxCFQ8MKqzLZ998GZbet8NNunICXbPrfNzZ2iuWrrIW1a56sUwH7pEAAEEEEAgBgG6RAABBBBAoDEFunek7cUb07by2+aljU/lz3P7i9l8laue6rsa7evTtvq6bPmrPzbb09UTCVt3f9qCfbl2PCKAAAIIIFArAhUPjLqJ6RL1e2+bn/viI5fPYx0IMEQEEEAAAQQQQAABBBBoeAEFMtfdn7IDp6ZsylfNDp+bts3PmSkYqskr8Lnhl9l8laue6qudyjcvMxt3qnltBx+Qtl1rspfdqd3eTrPWaT2BUtUnIYBADQowJAQSLhBbYDThrkwfAQQQQAABBBBAAAEEakyA4eQLKJDZvT1toz+UDWC2jEvZ8A+kM4HR7LrKW96bNuWr5fBD09a9w6xrc/bsUAU/B4/I1m0ek/LyVU8B09EfSdmgIdlAqfEfAggggAACNSoQa2B005ZtNuvsq/LuL+ruM6p8ldeoC8NCAAEEEECg3gUYPwIIIIAAAn0WUICze0fKuyy+c3M26Ok6GTwis5TOBEd3prygZ1OzWXdm2TL/qe6QMWbubFEFUTPZ/EMAAQQQQKCmBWINjH73tnvt6ClHePcVXbXv/qLu8ZHFC02X29e0DoOrIwGGigACCCCAwAAKcBLUAGKzKQQQiEug5ZBs4LP9jfAXNQVKw7Y/ZprZ+gez9xhVMFXBUHe2qM421X1JlXS/0bA+yEcAAQT6LkALBConEFtgVGeDvrJmvX3+9BMrN1p6QgABBBBAAAEEakEgG0uohZEwBgQQaHSBGOc3+ICUHXxiytbdlw1uKoj51q/NdL9Qdxm8zgQNG4IusZ90ZfYeo4d/IXuJvS6vV8B16+/T3j1LJ12ZNgVN3X1Lw/oiHwEEEEAAgWoINFVjo2wTAQQQQAABBBAoJEAeAggggMDACoycmA1s6suVlEZOTtvIidkzSINni3bvzIwtlTJ3X9HMWt4/d7aoMrv3XWKvAKsCrcojIYAAAgggUGsCsQVGdZn8EYeOs+eWr661OTMeBGpFgHEggAACCCCAAAIIIFAzAhufMu/sTl0Sr0Hpsf0vKe++oVrX5fGDDzDTvUS17k/+e4s2DbFc8HRPV/aMUX9dlhFAAIEECjDlGhVoinNcuoz+D6v/ZO0dnXFuhr4RQAABBBBAAAEEEEAAAQTKEFAwVJfQK+myeV0Sr7M81ZUulT/4P5m9uihlKn97RdrGn5b2vnhJ5S4p+LnxSbO2j5tXNmhIylteuyRlq69LeZfmj5zoavOIAAIIIIBA7QjEFhjVPUav+MbN9viTy23ayRfZ5Blz89Kss68y1akdCkaCAAIIIIAAAgiUIUATBBBAoI4F2k7ouZR+/GmpXjNRQFOX2CtNvDSVCXL2rqNA6oT/kjIFUl0HWnb3Hy3Ur6vHIwIIIIAAAtUUiC0wqkvpH1m80FYtXVQwqUx1qjl5to0AAn0XoAUCCCBQiwJvd71hW7r+ksjU3r29FncJY0IAAQQQQAABBBCoc4EkDD+2wGgS8JgjAggggAACCFRfoGtvhy3dcIf9+5qvJy498OdrbFv3W9XfCYwAAQQQqH8BZoAAAgggkECBWAOjurfouZdf611Cf+ypF9uql9Z69xtV3h1LHjL+QwABBBBAAAEEKiHQ/u4229m9KXFpV/dmS2f+77shLRBAAAEEEEAAAQQQQKDEwGi6LKlv3XCnHT99ii17+BabNjV7t+2Woc12zuyT7OnnV3pB0rI6phECCCDQFwHqIoAAAggggAACCCCAAAIIIIBA4wv0cYYlBkZ732A7ajv6YqVX1qy3Y46e1KtqW+to27m7w3a3d/YqIwMBBBBAoJYE+v76X0ujZywIIIAAAggggEClBco7bajSo8j2x08EEEAAgf4JlBgY7d9Ggq03btlqI4YNtWEtzcEi1hFAAAEEakqAt/41tTsYDALJFmD2CCCAQE0I8GfjmtgNDAIBBBCoiEBsgdGxraNs1szpdv0td+edGaozSa+9aYl3ib0uq6/ILOgEAQQQaDgBJoQAAggggAACCCCAAAIIIIAAAnEKxBYY1aDPm3OKdz/RGWdcZo8/udzOvHC+afnqS+aYylTHS/xAAAEEEEAAAQRqRGDjU2Yrv51Nq68za1/fc+b0uvvTuTJXR4/bX8wO3l/u8lSiPl653ax7R09fyichgAACCCCQOAEmjAACCNSQQKyBUc1z5nFTbdXSRXlJeSojIYAAAggggAACtSSgYObbK9I28dK0Tfmq2bhTzdb9pCegOf60lJevMqXD56atuc2s5ZC0F0Dd22k26cq0KX/r79O2pysbCN28zKzt42aDD+ACzFra3wMxFraBAAIIIIAAAgggULsCTbU7NEaGAAIIIFBnAgwXgboX6NpsNnhkypqGmPff4BGZwGYqZd07vdVePxTwHPnBTJtMwLN7Z8qams0GDUnZ4BFme95J2d4uywVMhx+a6cv4DwEEEEAAAQQQqBeBVL0MlHEiULZAU9ktS2g475rb7dzLr7X2js5cbS0r744lD+Xy6nOBUSOAAAIIIIBAowmM/lDaurenbe3dKe9sz11rUtby3rS1jOv9wUCXx3dtSpnayEFBVJ0xqrNEuzOB1EH7p70Aq4Knoz+S8gKmxn8IIIAAAgggUIcCSR0yf9RN6p5P0rxjC4wqAPrmxre9e4z6v2RJy+fMPsmefn5lXsA0SejMFQEEBlaAX+cD683WEKhnAV3q3vI+sz2daVt9Xco2P2c2ZlrhGSng6c4WVQ0FT3XGqNq9uigTMM0EQ3UGqoKlutT+1R8Xvm+p2pIQqCkBBoMAAggggAACCCREILbA6O72Ttu5u8PaWkf3olSeylSnVyEZCCCAQIUFep/nVeEN0F1dCzB4BPwC+uIlrR95QfZeorrH6NolKe9yeOW7pHuRtr9uubNFXb7/HqQjJ5opeDo6EyBtfyNlgw/ouW/phsezZ6S6djwigAACCCCAQO0JcIJF7e0TRoRApQViC4wOa2m2EcOG2sYtW3uNWXkqU51ehWTEKUDfCCCAAAIIIFBEoHNz2prH9Pw5RWd6Ng1JW/fOnjxdKr/5ebMDpyrY2ZMf7FaX2utsUd1bVGeOunJdcq/L7N06jwgggAACCCBQmwLhv+Vrc7yBUbGKAAIlCMQWGHWXzM9bcLutemltbihaVt7x06eY6uQKWEAAAQQQQAABBKosoKDo2ysygdAd2XNEdKbn3q5MAFRfwrRvbLrvqO5D6u4tui+714M7W1RfxjRkTE+xgqz6YqaeHJYQQKD/AvSAAAIIIIAAAgj0XSC2wKiGMvO4qfaD66+yL12x0CbPmOulMy+cbwvmnW/nzTlFVUgIIIAAAggg0FcB6scm0HaCme4x+uKNKVv5bbP1S3XBbQAAEABJREFUD5pNmNPz5UvdmYDphsfSkWeL6lJ7DVKX0/sfXZ8HfyrNlzEJhoQAAo0rkP37UuPOL4kzy+zTzV3rbFNC0+7u7WXsdc45LQONJggMqECsgVHNZPJRE+zZB2+2VUsX5dLMTMBUZSQEShGgDgIIIIAAAgMp4L9P6KQrM4HScT0favTlTBMvTZkCqMXGpICo+vHX0fqUr5oF+/TXYRkBBBBoGIGel86GmVLSJ9KV7rBn3lpiP//zdxKXHll3g23v3ljGIZCJJpfRKslNmDsCAy0QW2B005ZtNvuC+XmX0Q/05NgeAggggAACCCCAAAIIIFCjAgwLgboT2PHORnu76y+JS1vfWW9p21t3+4sBI4BAtEBsgdHoTVMDAQQQQAABBJIjwEwRQAABBBBAAAEEEEAAgdoSiC0wOrZ1lB1x6DjbuGVrbc2Y0SAwEAJsAwEEEEAAAQQQQAABBBBAAAEEGl+AGda1QFOco//86SfaTx9+0to7OuPcDH0jgAACCCCAAAIIIIAAAggMgACbQAABBBBAoJEEYguM6h6jV3zjZnv8yeU27eSLbPKMuXlp1tlXmeo0EiZzQQABBBBAAIGGEmAyCCCAAAIIIIAAAggg0MACsQVGdSn9I4sX2qqliwomlalOA9syNQTqTIDhIoAAAggggAACCCCAAAIDI7DxKbOV386m1deZta9P5zasZeW5cj2+eGPaundk66y7P51ru/3FXDOvj1dut1y9nhKWEEAgX4A1JxBbYNRtgEcEEEAAAQQQQAABBBBAAAEEqibAhmtOQMHMt1ekbeKlaZvyVbNxp5qt+0l+QLOp2ezwudly1Zl4acoGH5Dygp97O80mXZn2yrf+Pm17urIB083LzNo+bl69mps0A0IAgZoUaIpzVLq36LmXX+tdQn/sqRfbqpfWevcbVd4dSx4y/kMAAQQQQAABBBCorAC9IYAAAgggUOsCXZvNBo9MWdMQ8/4bPCIT2EylrHunt1r0R/fOlCloOmhIJlA6wmzPOynb22W5gOnwQzN9Gf8hgAACpQk0lVatvFrfuuFOO376FFv28C02bepEr5OWoc12zuyT7OnnV3pBUi+THwgggEB5ArRCAAEEEEAAAQQQQACBOhMY/aG0dW9P29q7U97ZnrvWpKzlvWlrGZfKzURnhb66KOVdMu+/jF5BVJXpLNHuTCB10P5pL8Cqs0VHfyRlCpga/yGAQCMKxDKn2AKj+mKlV9ast2OOntRr4G2to23n7g7b3d7Zq4wMBBBAAAEEEEAAAQQQQAABBJIt0Niz1yXxLe8z29OZttXXpWzzc2ZjpvXMWQHSSVead5m9LqNX3XX3Z4OoKtMZo2qnwKmCoToDVcHSlkPS9uqPC9+3tKd3lhBAAIEegdgCoz2b6L20cctWGzFsqA1rae5dSA4CCCCAAAIIIIBAsgSYLQIIIIBAogT0xUua8JEXpLzgp+4xunZJ9v6hyg8mBU11ubySysaflm2noOnIiWbubNH2N1I2+IB0rs8Nj2eDqWpDQgABBAoJxBYYHds6ymbNnG7X33J33pmhOpP02puWeJfY67L6QoMiDwEEEGhkAeaGAAIIIIAAAggggECSBTo3p615TM9l8zrTs2lI2rp39uSV6tO+Pm06W1T3FtWZo66dLrnXZfZunUcEEECgkEBsgVFt7Lw5p3j3E51xxmX2+JPL7cwL55uWr75kjp035xRVISGAAAIIINBnAW6p32cyGiCAAAIIIIBArQr0PRZYqzMpeVwKir69IhMI3ZF9V6czPfd2pUzBTHWiM0AV8NSyktaHjE2bLsHXuj+pTJfT696iQ8b0lCjIqi9m6slhCQEEEOgtEGtgVJubedxUW7V0UV5SnspICCCAAAIIlCOQwM8P5TDRBgEEYhWgcwQQQKBCAtnYYIU6q49u2k4w031DX7wx5X250voHzSbM6fnypcEjzHT/0JXfzt4vtHtHysad3Htu21/M5ulyei25R7VTnwd/Ks2XMQmGhAACoQKxBUbnXXO7TZ4x10taDh0BBQgggAACtS/ACBFAAAEEEEAAAQQQqKCA/z6h+qIlfamS614BTt0/1KXDv2AFA5yqp35cOz1qXe2CfaqMhAAC1RKo3b8AxRIYvWPJQ/bmxrdt2cO3eGeKil15eqyHxBgRQAABBBBAAAEEEEAAAQQQQKDxBZghAggMhEBqIDZS1jYqHhht7+i0p59f6d1b1H250udPP9EeeeJ50xcvlTVKGiGAAAIIIIAAAggggEB/BWiPAAIIIIAAAggg4BOoeGB0d3un7dzdYW2to3ObaRszylveuHmb98gPBBBAAAEE4hdgCwgggAACCCCAAAIIIIAAAgiEC1Q8MBq2qZ272m3jlq1hxeT3V4D2CCCAAAIIIIAAAgjUqEDt3lmsRsEYFgIIIFBMgDIEEKiYwIAFRis2YjpCAAEEEEAAAQQQQACBuhLoz53F6mqiDBYBBBBAAAEE6koglsCozg4988L5NnnGXC/NOOMye/2NjXbJvO9568qfdfZVsdxzdNVLa+3YUy/ObSf4pU9PPLMiVxYcg+pqbEpadntS90adfcF8U98uj0cEEEAAAQRiEKBLBBBAAAEEEEAAAQQQQACBARKoeGB0bOsoe2TxQlu1dFHRpDqqW8l5KoB5xTdutgXzzve2vfS+G+zeny81BUO1HQU2v3PjYrvn1kyQMzO+2Z+ZYVd/61bTF0aprb40Sm2UtKw8tfvZo8/YrJnTbfJRE7RKqpgAHSGAAAIIIIAAArUjwOXetbMvGAkCCCCAQKMJMB8EalOg4oHRak5TX+6UTqdzX/w0rKXZDnlPq7325w3esJ5bvto++qEjcwHOY46eZOvf3Gxr1r1pajt8+FBTGyUtK0/BUQVJP3vScV4f/GhkgVQjT465IYAAAggggECEAO8EIoAoLl2AmggggAACCCBQFwINFRjVGZ0KfH7pioXeZe8KeO7c3WEuqPnq2vV5O6VtzChLpVKmL4XS8q5dHba7vdNLWlaezhY9fvoUq/TZrXkDYaVGBDhPpEZ2BMNAAIE6E2C4CCCAAAIIIIAAAggggEA9CjRUYFQ74MRPfMwOGDHMFBzVfU51Cbw/qHn4hHGq1iupjgKguh+qkpZVyZ0tOu+a223yvnumukvzVd7SPMhIlTcYOqTJmmrztA3t9thTUyZg35IxGJY5vkiDDIPyDfRcGta8X8aQhEPjHgPNgwfF/rpcyxvYb1CK5zivcxwDCToGhg4ZxPvkjMFA/V6XN+9Fs+9Fmwc31fKvw9jHlv19m7XgmEiGQ0vzoLqI98R+8Df4BhrqlU33EL150QP2v2/6qj374M2me4XqHqP+L1IKnjXq37/nzTnFuzep7o+qZXe2qC6p39XeYcsevsW7P6m2oUvs1XZwU5ORKm8wqKmhDk3r63+ZuKgNamoiYVCRY0Bv4kgpw6BxDZqaUn19mW2o+vqdwfHduMc3+5Z9W+gYiOdFrD569V7zMq/7hVziyMv87aki78cGNTXVfT+pVMI/o2WeIoOa6n8/DmpiDoOaSjOol1hP5tDkXz8EYntlU+Bw9gXzvUvag+PTGZfnXn6t96VHwbL+rOuS+BHDsvcJVT86C/ToKUeYC4YGzxZVwNN/T1K1cUnjd2eLql9dWq8yXV6vbWhZaXt7t5Eqb7Cr413buze5l7bvycx9Z8ZgR+b4InUbBuUb6Lm0fXe3kTBo5GOgvetd/UruW2qg2t3vpnmO8zrHMZCgY2Bn+7uWeavYQK9ifZuK3ifvyLxPHqjfa7s69/BedN9nko53Ev77dk+aY2HfsZCUz2f1Euvp26sotYMCZQdG+xOyamsdbbr3p+7nGRxQf9bV7wuv/Nl+s+IFrxsFN5evfMVcQFRftvS7P76cC9bqy5jGHTTGDh1/kFff/8OdLargqvrVlzGpXMFUjV3LdZmSfVJNXe6ySgyaPhBAAAEEEEAAAQQQQAABBBBAoPEFmGHfBMoOjPYnvqaApM66HNbS3LfRRtTWly8tmHe+XTLve979QHWv0NmfmWG6LF5NVf6VS8823XtU9wvVZfbXfu1CaxmaPw5dkv+H1X+yOad9Us1M7T486QM27eSLvLYXz/2cKWDqFdbbj/5EtOttrowXAQQQQAABBBBAAAEEGlmAuSGAAAIIINAvgbIDo2FbVVDx2FMvNgUlV7+81gskKgjpTz+460G74qKzegUkw/rsS/7M46bm7hO6aumiXFDU9eEvf2TxwoIBTgVCv/8vX84bn4Kr6k9Jfbj+eEQAAQQQQAABBAZGgK0ggAACCCCAAAIIIIBAJQUqHhhVUNF98dGkIyfYPbfOzwtUKrCoctWr5EToCwEEGkyA6SCAAAIIIIAAAggggAACCCCAQOMLVHGGFQ+MurnoUvN7b5vvXYbu8nhEAAEEEEAAAQQQQAABBBBAIMkCzB0BBBBAoHYEYguM1s4UGQkCCCCAAAIIIIBAlQTYLAIIIIAAAggggAACNSsQe2D0iWdWeF+E5L/HqPJqVoSBIYAAAmUL0BABBBBAAAEEEEAAAQQQQAABBOpFoPzAaAkzVAD02puW2NL7bsjdZ1T3HJ234Ha7Y8lDJfRAFQQQQAABBBBAAAEEEEAAAQQQqKoAG0cAAQQaVCC2wGh7R6fdee+jdvUlc0z3G3V++tKlBfPOt6efX2mq4/J5RAABBBBAAAEEEECgFgQYAwIIIIAAAggggEAyBGILjO5u77SduzusrXV0L0nlqUx1ehWSgQACCCAwkAJsCwEEEEAAAQQQQAABBBBAAIFECsQWGB3W0mwjhg21jVu29oJVnspUp1dhrBl0jgACCCCAAAIIIIAAAggggAACjS/ADBFAAIFogdgCoy1Dm+346VNM9xjdtGVbbiSrXlpruseoylQnV8ACAggggAACCCCAAAIIlCdAKwQQQAABBBBAAIE+C8QWGNVIzptzineP0RlnXGaTZ8z10pkXzjfdY1RlqkNCAAEEEECgrwLURwABBBBAAAEEEEAAAQQQQKC/ArEGRjW4mcdNzX0j/aqli7xl5amMVJIAlRBAAAEEEEAAAQQQQAABBBBAoPEFmCEC/RBI96NtcpvGHhhNLi0zRwABBBBAAAEEEEAAgXABShBAAAEEEECgcgKpynWVoJ5iD4zeseQh7xJ6dyn9sadebLrPqPEfAggggAACSRJgrggggAACCCCAAAIIIIAAAjUlEGtgVEHRe3++1Jbed4N3Cb0upf/B9VfZl65YaE88s6KmIBhMZQXoDQEEEEAAAQQQQAABBBBAAAEEGl+AGSJQzwKxBUY3bdlmCopefckcG9s6Kmc0+agJ3pcv3Xnvo9be0ZnLZwEBBBBAAAEEEEAAAQQQqHEBhocAAggggAACDSQQW2BURiOGt1hb62gt5iXl7dzdYbvbCYzmwbCCAAIIIIBATQkwGAQQQAABBBBAAAEEEECgcQViC4wOa2m2EVz26WEAABAASURBVMOG2sYtWxtXj5k1lgCzQQABBBBAAAEEEEAAAQQQQACBxhdghgjsE4gtMNoytNnOmX2SFbpk/rnlq+2IQ8flXWK/bzw8IIAAAggggAACCCCAAAIIVFCArhBAAAEEEECgsEBsgVHdY/Tam5bYb1a8YNNOvsgmz5ibS/926z32wC+ezq3POvsqU/3CQyQXAQQQQAABBBAoWYCKCCCAAAIIIIAAAggggEBJArEFRvWFS48sXmirli6KTKqn+iWNmEoIIOATYBEBBBBAAAEEEEAAAQQQQAABBBpfgBnGIRBLYPSOJQ/ZsadebKteWmvuvyeeWZE7Q1TlLp9HBBBAAAEEEEAAAQQQQAABBPIEWEEAAQQQQGAABGIJjL66dr3NPH6qTT5qgjcFXSZ/86IH7J5b59uyh2+xp59faQqUeoX8QAABBBBAAAEEEi7A9BFAAAEEEEAAAQQQQGDgBSoeGFUQdPnKV+zET3wsN5v/eGmNjRg21A4df5AV+1KmXAMWEECgkQWYGwIIIIAAAggggEB/BNLp/rSmLQIIIIAAAgMlUPPbqXhgVDMeMbzF2lpHa9FLj/36t3ZQ24FeUFQZKtu5u8N2t3dqlYQAAggggAACCCCAAAIIIIBA7AJpizOoHPvw2QACCCCAQIUFYgmMFhrj4RPGFcomDwEEEEAAAQQQQKAeBRgzAgggUIcCWzr/Ys9t+nd7ZuPdiUsrtjxi3Xs5OakOD1uGjAACMQpUPDA6rKXZu2x+45at3rDbOzrtzY1v22HvP9hb1w+V7dzVrkUSAgggUBcCDBIBBBBAAAEEEECg/gW69u6232y8x555667EpVVbf2l7OWO2/g9iZoAAAhUVKBQY7dcGdA/R46dPsTvvfdQUFP3Nihfsjbe22F8ddWiuX11af/SUI2xs66hcHgsIIIAAAggggAACCCCAAAIIIFC+QLrvTWmBAAIIJFqg4oFRaZ435xTvnqLTTr7ILpn3Pbv6kjm5IOgTz6ywB37xdN6XM6kNCQEEEECgtgR4Y11b+4PRIIBAJQToAwEEEGhsgVRjT4/ZIYAAAhUXiCUwqlEu+MfzbdXSRV6aedxUZXlJy8rXo5fBDwQQQACBeAT62StvrPsJSHMEEEAAAQQQQACBOhLg3W8d7SyGikDFBGILjFZshCV2RDUEEEAAAQQQQAABBBBAAAEEEGh8gXhmyPVS8bjSKwK1LUBgtLb3D6NDAAEEEEAAAQQQSLYAs0cAgRoVWHd/2lZ+23ql7S9mB7zxqd5laqPS7h1pe/HGbHs9al35Smrn6mmdhAACCCAQnwCB0fhs6RkBBBBAoM8CNEAAAQQQQAABBOpDYPxpKZvyVculw+emrbnNrOWQnjMPW95nNunKdK6O2mh2W/+YsgOnZtvrUevKV4B052tmB39SayQEEEAAgbgFCIzGLVysf8oQQAABBBBAAAEEEEAAAQQaQmDzMrORHzQbfED0vSo7N6dtyJjstPWoda0pQDrisNL6UH1SHQkwVAQQqEmBppocFYNCAAEEEEAAAQQQQACBuhVg4AgkTaB9fdq6NqVs9Id6zhaVQfvrZquvS3mX2/svj28ek7Kuzaph3qPW3dmiwT6ytfiJAAIIIBCHQGyB0U1bttnsC+bbqpfW9hr3E8+ssHMvv9baOzp7lZGBAAIIIIBAnQkwXAQQQAABBBBIuEChs0XbTrDcJfQTL02bgqS6f6ioFPx8e0X2HqN61Lo7W7R7p4Kp2fuTvvpjsz1d+cFWtSchgAACCFRGILbAaLHhtbWOtp27O2x3O4HRYk61WcaoEEAAAQRiEUjzoScWVzpFAAEEEEAgZgF92ZKCngpuhm1Kl9frXqLuknmtT7w0e49RPaqd7i2qPhRkHXdqNqg6+IC0bVkWfWm+2pMQqLwAPSLQ+AJVCYw+t3y1jRg21Ia1NDe+MDNEAAEEEECgBIENna/av6+db3e/Ni9x6bH1N1vX3o4SlKiCAAIIxChA1wiUIaCzOTc/b94XKSnYWUYXXhN3tmjTELPuHT2BUF1i71XgBwIIIIBALAIVD4zq0vljT73YZpxxma1+ea2deeF8mzxjbl76wV0P2hUXnWUtQwmMxrJX6RQBBBBAoO4E9qbftfW7V9vru/9jQFItbeetjtfqbn8xYAQQQACB2hKo1nUXu9akrHt7ute9RRUw3fB4OncZvO4fqkvmR07sCXo6QZW5s0UHDUmZzhJ1Ze4MU7fOIwIIIIBAZQUqHhidfNQEe/bBm23pfTfYpCMn2D23zrdVSxflJZWrXmWnQm8IhApQgAACCCCAAAIIIIAAAg0s0DvcGP9kFdDc8Fi64NmiCnBm7xWa8r546cUbU169kRN7j2vDr8zGTLdMQDQ7i4M/aaZ+V347e/Zo67RqhX17jzWXU4NDyo2NhaQLMH8E+iTQ1Kfafag8tnWU3XvbfCMA2gc0qiKAAAIIIIAAAggggAACJQtQsZoCunRe9wfVlywVGsf407L3EJ3y1ez9QovV8wdMXb9qd/gXzBRkLdR/VfNSVd06G0cAAQQqJhBbYFQjnHfN7Xbu5ddae0fPlyxpWXl3LHlIVUgIIIAAAggggEBpAtRCAAEEEEAAAQQQSIYAwfdk7OcamGVsgVEFQN/c+LadM/ukvHuJ6r6iynv6+ZV5AdMasGAICNSUAINBAAEEEEAAAQQQQAABBBBoIAGCfaXvzITdrqF0GGpWWiC2wOju9k7bubvD2lpH9xqz8lSmOr0KyUAAAQQQQACBfgmsuz/t3c9M9ybzp+0vZrvd+JTllWs9W6J7maXtxRuz7fWo+6e5MtVT326dRwQQQAABBMoQoAkCyRUg2Jfcfc/Ma1YgtsDosJZmGzFsqG3csrXX5JWnMtXpVUgGAggggEBNC8T3fo4/oVdqxwfvaXb43LQ1t5m1HJL2vh1X33A78dK06d5letS35Lqg6dY/Zr8cQmUHTk2Z1jUuBUj1jbn6Qgitk0oVoB4CCCCAAAIIIIAAAgjUqkBsgVF3yfy8BbfbqpfW5uavZeUdP31K3iX2uQosIIBA/Qow8kQIxBe+jC/kmogdU2SSm5eZjfygmb7MQV/goMCpltWkaUgmf2TKujZrzUxB0yFjsst61LrWFCAdcVim7gHxHQHaDgkBBBBAAAEEEEAAAQTqQKBBhtgU5zxmHjfVfnD9VfalKxba5BlzvXTmhfNtwbzz7bw5p8S5afpGAAEEEEAAgYxA+/q0dW1K2egPFQ48KyDatdFMQdBMdWse0xMkVZnW3dmiYX2oHQkBBBBAAIFGFmBuCCCAAAKNKRBrYFRkk4+aYM8+eLOtWrool2ZmAqYqIyGAAAIIIIBAvAL+s0X9W1KwU/cQfXVRysYcYzZyYrZUwU9dWq97k+pR6+5s0e6dZquvy96f9NUfm3dZfrYVPxtMgOkggAACCCCAAAIIIJAIgdgDo4lQZJIIIFDHAo0x9MLnAjbG3JhF+QK6b2j761bwbFFdSj/x0pRNujJtuneovlhJW3L5useoypWncgVIFWQdd6p59yYdfEDatizjsnr5kBBAAAEEEEAAAQQQQKAeBHqPMdbAaHtHp517+bXeJfTHnnqxd69Rl3fHkoeM/xBAAIG+CRCECfNCJkwmufl7utK2+XkzfYGSgp1hErrnqO4d6u4lGqznzhbVvUi7d/QcabrEPliXdQQQQAABBBCoIQGGggACCJQskNxTbWINjH7rhjtNX7K07OFbbNrU7DV67kuZnn5+pSlIWvI+KqGivthJAVh3P1P3qOCs29YTz6zwArUqm3X2VbZpy7ZczwrWKl9Jy65AdWZfMN8L7Lo8HhFAoBoCyX2xroY226xvgV1rUta9Pd3rbFFdQr/u/nTuMnit65L5QoFOlbmzRRVA1VmiTiUskOrKeURgoAXYHgIIIIAAAggggEC5Aj0nQJTbQ722iy0wqmDiK2vW2zFHT+pl09Y62nbu7rDd7Z29yvqTUeh+pp/79PFecFYBWQVOv3PjYrvn1kyQc+kim/2ZGXb1t271ArQar4K1S++7wZS0rDyN52ePPmOzZk439a91EgIIIFBlATaPQFEBBTQ3PJYueLaoO3t09XUp031EX7wx5dVrO6F3lxt+ZTZmuplrc/AnzdSv2uns0dZp/LGitxo5CCCAAAIIIIAAAgggUC8CTdUY6MYtW23EsKE2rKW5hM2XX0WBUAVnP3vScV4nzy1fbR/90JG5AKeCtuvf3Gxr1r1pGzdvs+HDs2PSuLSsPAVHFSR1fXgd8QMBBBBAAIEaFlAgU/cHLRTs1LDHn5by7hOq+4gqFavnvpRJ7Vy/anP4F8x0FqnySQgggAACCCCAQGUE6AUBBBAYWIHYAqNjW0d5Z1lef8vdeWeGKtB47U1Lcmdxxjndu37ymDcGjUXbeXXtej3kUtuYUZZKpUyBWi3v2pU9i1VnsmpZeTpbVLcDcH3kGu9b2G9QykiVNxjUlDLL/LOE/pc5LG2/zLOTY6vyx1biTDmOrF72eWZXJfQVLzttve6Xu6/UNttLMn/qV2a5drSr8u8Z3kfWzWt0LT1XvNc83ieXfezw+7b81z3v2Evmr1pv1vy+Lf/YqaXX0EYci3eA8qNsgVh/L5w35xQ7Z/ZJNuOMy+zxJ5fbmRfO95avvmSOqazsUZfQMHi2qGty+IRxbjHvUYFPBUA1ViUtq4I7W3TeNbfb5BlzvaT7lKpMafSIIUaqvMHI4ftbkn/xDspERkcOr7wrx2ryTIe37F8zr1Ecf8WPv8GDB+nXSmLT8KGDyz5Wh2XaJhYuM/HBmb+k8fwq/vzCB59GOgZG8j7ZRvbjfTK/b/l9m/nVWdY/ft/yu6RWf5eUdUDTKCcQa2BUW5l53FRbtXRRXlKeyuJK+qIlnamq+4Iq4OnfTvCsUX+ZgrVurFp2Z4vqkvpd7R2mL5HS/UlvXvRA7kubNm3rtAKJvH66vL2jy/bsSe69697dm7YtGQOOLZ5f/T0Gtu16h9ejfr4e9XcflNq+q3uP/1dS4pa37y7/WN2RaZs4MN+Eu7r38jyvk+d5qa8H1OP3f7FjgPfJ/XufzO9bft/6foX2abHI71t+D/N7uKrHQJ8OZCr3EogtMKpL5mdfMN905mavrcac8ZsVL9gbb22x4H1Bg2eLKuCZTqdNXwYVHJLG784W1aX2urRedXR5ve6PqmUSAggggAACCCCAAALJEmC2CCCAAAIIIIBA4wjEFhitFpHOFr3z3kdt9mdmWPBsUX3Z0u/++HIuWKsvYxp30Bg7dPxBvYbrzhZVHwqc6suYVEnB1J27O7RIQgABBBBodAHmhwACCCCAAAIIIIAAAggg0LACsQVGFVA84tBx3hcbDaTekvt/VfBsUY1h8lET7CuXnu3d61T3C73350vt2q9daC1Dm1WcSzrL9Q+r/2RzTvukl6d2H570AZt28kVe24vnfq5X0NWrWOc/GD4CCCCAAAIIIIBfgRy8AAAQAElEQVQAAggggAACCDS+ADNEAIGsQGyBUXX/+dNPtJ8+/KTpLE6tD0TSvUEfWbwwNHCp+5u6+4iG1VMg9Pv/8uW8gKn6de3Ux0DMhW0ggAACCCCAAAIIIIBAvwXoAAEEEEAAAQQQKCgQW2BU9+i84hs32+NPLvfOtNQZmv406+yrcl9gVHBkZCKAAAIIIIBAGQI0QQABBBBAAAEEEEAAAQQQKEUgtsCoLqXXGZnuLMvgo8pUp5RBUqd2BGrue+Jrh4aRIIAAAggggAACCCCAAAIIIIBAXAL0i0AMArEFRnXG6OwL5ue+6CiGsdNlFQRSVdgmmxwIAfbsQCizDQQQQAABBBBAoFQB6iGAAAIINL4AJ59Vfx/HFhit/tQYAQIIlC7Ay3HpVtTMCRBPz1Gw0G8BOkAAAQQQQAABBBBAIHECfKSq/i6PLTCqy+SPOHScbdyytfqzZAQI1JQAg0GgQQSIpzfIjmQaCCCAAAIIIIAAAgggEI8AvcYnUJkPpLEFRjXxz59+ov304SetvaNTqyQEEEAAAQQQQAABBBBAAIFGFWBeCCCAAAIIDJhAZc63jS0wqnuMXvGNm+3xJ5fbtJMvsskz5ualWWdfZaozYF5sCAEEEEAAAQQQqKAAXSGAAAIIIIAAAggggEB9C8QWGNWl9I8sXmirli4qmFSmOvXNx+gRSIwAE0UAAQQQQAABBBBAAAEEEEAAgcYXSNQMYwuMJkqRySKAAAIIIIAAAggggAACCNShAENGAAEEEEiyQOyB0SeeWZF3Cb0uqVdektGZOwIIIIAAAgggUBUBNooAAggggAACCCCAAAI5gVgDowqAXnvTElt63w25y+nvuXW+zVtwu92x5KHcIPq9UJkvour3MOgAAQRqS4DRIIAAAggggAACCCCAAAIIIIBA4wuUO8PYAqPtHZ12572P2tWXzDH/vUQnHzXBFsw7355+fqWpTrkDz2tXmS+iyuuSFQQQQAABBBBAAAEEEEAAAQRqUIAhIYAAAghUSCC2wOju9k7bubvD2lpH9xqq8lSmOr0KyUAAAQQQQAABBBBAICfAAgIIIIAAAggggAAC8QjEFhgd1tJsI4YNtY1btvYaufJUpjq9CslAAAEEkizA3BFAAAEEEEAAAQQQQACBhhXgkt+G3bV1OrHYAqMtQ5vt+OlTTPcY3bRlW45n1UtrvXuMqkx1cgUsIIAAAggggAACCCCAAAIIIIBAQwowKQSyAnxJTNaBn7UiEFtgVBM8b84p3j1GZ5xxmU2eMddLZ14437vHqMpUh4QAAggggEC1BHhbVi15totA/wVq/Pnb/wnSAwIIIIAAAggggEDsArEGRjX6mcdNtVVLF+Ul5amMhAACCCDQCAL1Owcu5KnffcfIEeD5yzGAAAIIIIAAAggg0F+B2AOj/R1gzbVnQAgggAACCCCAAAIIIIAAAggg0PgCCZghV2AkYCczxaICsQRGn3hmhXfZvB6DW1eeLqvXY7CMdQQQQAABBBBAAAEEEKiOAFtFAAEEEEieAFdgJG+fM+N8gVgCo4/9+rf2uU8fb4UumVeeylQnfyisIYAAAgggMGACbAgBBBBAAAEEEEAAAQQQQCDhAhUPjG7ass2Wr3zFTvzEx0JpVaY6qhtaiYIKCtAVAggggAACCCCAwMAKcA7OwHqzNQQQQACBrAA/EUCgLwIVD4xq4yOGt1hb62gtFkwqU52ChWQigAACCCCAAAIIIFD3Aty1bUB2IRtBAAEEEEAAAQT6IVDxwOiwlmYbMWyobdyyNXRYKlMd1Q2tRAECCCCAAAII5AmwggACCCCAQHUEUtXZLFtFAAEEEEAgZoGKB0Zbhjbb8dOnWLF7iKpMdVQ35vnRff0KMHIEEEAAAQQQQAABBBCoCQHOgK6J3cAgEGhcAWaGQNUEKh4Y1UzmnPZJe3Pj23bu5ddae0ensrykZeXp/qKfPek4L48fCCCAAAIIIIAAAggggEByBJgpAggggAACCNSKQCyBUZ0J+sPvXu2dOTrt5Its8oy5XtKyzhR9ZPFCG9s6qlYMGAcCCCCAAAIIxCVAvwgggAACCCCAAAIIIIBAjQrEEhh1cz1vzim2aumivKQ8V84jAo0mwHwQQAABBBBAAAEEEEAAAQQQQKDxBZhhYwjEGhhtDCJmgQACCCCAAAIIIIAAAggkWoDJI4AAAggg0JACBEYbcrcyKQQQQAABBBAoX4CWCCCAAAIIIIAAAgggkAQBAqNJ2MvMEYFiApQhgAACCCCAAAIIIIAAAggggEDjCzDDXgIERnuRkIEAAvEKpOLtnt4RQAABBOpPgF8N9bfPGDECdSDAEBFAAAEEEIgSIDAaJUQ5AghUWCBd4f6q011jzKI6dmwVAQRiEajvTnlRre/9VzOjJ8JeM7uCgSCAAAIIIFAnArEGRjdt2Wazzr7KJs+Y2yspX+V14sQwkyjAh7Qa3uvVHxofvaq/DxgBAggggEB9C+itVmVT2irbn8XaX33vPUaPAAIIIIDAQAnEu51YA6Pfve1eO3rKEbZq6aJe6ZHFC21s66h4Z0fvCPRHgMhXf/RoiwACCCCAAAIIhAp07+20FVv+rz391l2JS89uvNve7no91IaChAswfQQQQACBARWILTCqs0FfWbPePn/6iQM6ITaGAAIIIIAAAgggUB8CjDK5Anstbau3/sqeywQJk5Z+u+kn1rmnPbk7n5kjkFCB13b+LvOHoCWJTK/uWJ7Qvc6060EgtsBoPUyeMSKAAAIDKMCmBkBAl1AOwGbYBAIIIIAAAggggAACfRLY0vW6PbtxSSLT1ndez/w5rE9cVEZgwARiCoyad5n8EYeOs+eWrx6wybAhBBBAAIFkC9TCHTAIzib7GGT2CCCAAAIIJE/ACHolcaczZwQaRCC2wKh8dBn9H1b/ydo7OrVKQgABBBBAoOEFaiE42/DITBCBagqwbQQQQACBXgK8/+lFQgYCCNSJQGyBUd1j9Ipv3GyPP7ncpp18kU2eMTcvzTr7KlOdOnFimAgggEAiBZg0AggggAACCCCAAAIIIIAAAo0qEFtgVN84/8jihb2+jd59Q73KVKeGYBkKAggggAACCCCAAAII1KnAuvvTtvLb5iUtu2m0r0/b6uuy+Sp/9cdme7p6bnyiuspX2v6ia2Wmdq/cbta9o6duTylLCCBQ5wIMHwEEEPAEYguMer3zAwEEEEAAAQQQQAABBKos0PibV3BTs5zyVTOl8af1XNi7a03Kxp2azVfZ4APStv5h1TYv+Lm302zSlWk7fG7atv4+nQuabl5m1vZxs8EH9PSVbcVPBBBAoPoC+uON+6OPHrWuUemPOS/e2POHIi0rT2VKqqf6+mNQoT8UbXxKtUgIJEegKTlTZaZOYMvb2+yL//2f7dnf/tFlVf1RY9GYNLaqD4YBIIBAfQswegQQQACBRAnoLM/uHZng58mFp912gtnIiT1lzWNSpvo6a7R7Z8qams0GDUnZ4BFme95J2d6unoDp8EM5W9T4DwEEak5Awc11P03ZhDlp749Bk640axmX8sbZ/kbKDpya8vL1xyAtr7s/lfdHH/fHIv2hSH88UkP1qT8UtU7jdU8epOQIVDwwqvuG6v6hdz/wK9Nj8N6ibl1lqtso1B0dnfYPX7/BTjzjb/MCjgr4KV/lxeaqgKACg6pfrF6wLO71u+9/1JuT5hVMGq/GXWgML//pz/aFi//J9FiovFJ5K386yn4xf1xeeu2p4bnu/eXLFrXau+/kigouqFz1XJ/+vrTs8vWodddJ584m+3/fe483Dj1q3ZWpnsbh1nlEAAEEEEAAAQQQqJxA1+ZMIPN1s9XXpbzL6HUWlIKlhbagYOjO18wUDMgGQ9OmQIDyu3eaDdo/bU1DzHS26OiPpEx1jP8QQACBGhHQMPR6teHxlB38n3qCocp3SX8I0h+E3PqQMWbd2zOvdZk/+qitXvMGj8gGP/WHIr2Gqi6ve1IgJVGgqdKT1n1Ddf/Qsz73SdPjqqWLCt5nVGWqW+ntV7u/E2ccYz/5+a8sKhBa7XGWuv2zTjvJHrvvf3rpS+f8jX3kr46yn/3v73rrP/of37TWA0eV2lVs9Q758G779Pz1uXTYCbu8bSkg2bl9kH1q3novKfOF/xs+XgVFVyxutdYPdPXqS2W7N+1nn7hig1emx7/8bphtfCnzzjnT8Rt/aLH3fjQ7Dj1qPZNtCpBu+dMQO+I/7dAqCQEEEEAAAQQQQKA0gZJrdW5O23s+Ybmzo8afYbb+wUywdH32g7/rSJfbK3iq9XEn62c2qKAzRpX/6qKUKRiqIIECBy2HpE2XmSrQuvq63v1le+AnAgggMLACOqtdgc5194XfO9k/ou0vpm3wyJT3Rx/9sUeved07U6b/9PqpwKk7W5Sz5KVCSppAxQOjSQMMzvejH/mgl/X7VS97j8EfCpjqDFJ39uXd9z/qVbnjrgfsjTc32T9f8z+9MzSVr7Twxh955a6dO6NUZ2Je/A/XmDtjU+unf+EKU7961Loaqlxndv5w8c9M+UqvrV2volxyddy2cgUlLGiM2qaS5qVxKt1+509tw1ub7b9f/R1vTBq3247qKrn6hTajutf901Om4Gah8qg8BSQVuHz/sbtsv/3NS1reum6IF6ws1H7d88OteeQec4FVfx31MeVvtlnziL1e9n5D9trQke/ark2DvXUFTYeP7faW9ah1rShAqkCra6c8EgIIINBbgBwEEEAAgUoJ6IP9kDYzd3mo63f8adlLS0ccZrb27lTuslKXr0tOdaaVO2tKl6PqzFLl67JTnaGls61cfzwigAAC1RDo1tntzSmbeKm7jD77RyB372Q3Jt0rVH/YaX/dbPxp6dwZ8GOmZf94pDLdVkSvme51T6+bylfSH5NcXzwiUJ5A9tgsr+3AtWoauE0lY0stQ5vt9M98suBZowoY/vN3brGxY0Z7Z1z+n9uvsV8//TvvcvPzPv85O+SgsfbNf/xbr0xnao5/70G2afNWU7vX179lr6553Z58doUHuWXbdhvWMtS0PQURv/3dO+wfvvxFr60ev/LN73v9epUzP1546TW769Zv209+fL0dNmFcJif7T31/53uL7JQTT7CrLv1iNrPEnwp2PvTYU6Z56KxSzUvzU/Pzz/kbO/g9Y+x/XPsVb0zHfuxD9vJr6+yi//af7bH7/qfXZuPmt+1nv/h/qt6v9MYfhnmXsP9i/riigdQhw/d62+naMch7DP5QMNPf1+PfOci2r88GPnvXHWw73hxsCoKqbNjYniCpgqVaV3BWZ4se8uF2VSEhgAACCCCAAAIIxCCgS0F11lOwa50FFczTuoIAOuNKSev+5D9rSmeOujJddqrL7N06jwgggECtCOgs0DHTzRQA9X/Jki6n1x92Dj4xZa/+yMyV6V6kuiepyg7/gple69xZ8lt/n/a+iE5fSKegadhtSfo0dyonWCB7ZnKtAzTVOwb84QAAEABJREFU+gDrcXwfmXykN+zgWaMKbr61aYuddvIMr1yXoU8Yf4it+I+XvPXgjyMPG2+72ztM7VTnU5+Y7gVKFQhd95c37WNTJ9nQTCBWAUe1VX09avuHH/q+vH4VrFVdlbvU3tFpCmSqn7NOO8lll/yoIO3kiYfnLqfXvDQ/jbdQJwqOKqlMc1fbP7++Qau9ksqv/JcTCp696a+sszg/ve8y+mPO32hrnhruXd6uMzRHj++yt1YP9VcPXdal8rrsfuqczd6l8urz0BN22R/+/cC8M0wV7NQ9RJ+7vc1U3nZUl9engp86Q1XBWT1q/Y0/tHiX5SsQqyCrypaVcJ9Tr0N+IIAAAggggAACCJQkoEDnrj+lzH2A1xlPusxUl8Krg788lPa+fV7LSjozSvcRVdK6P6lMl9Mr0OAPrHbvTHlfzOSvW2iZPAQQQCBuAX1RnLbRvVM/e5K7XL4nJ7uk18JBzSkL1s+W9txTWevdmdc6Peo1UGfMa5mEQKMLEBiNYQ8rAKlA5E9+/itT8NG/iV272nOXl+ty8seWPucvzlvW2aA6K1Rnh27estVO/MQx3tmmCoQqoKgzSl2DtjEHemePal3b19mbWi6WvnPD/zKdtfmf/r/Mn5eKVSxS9v73HZwrbT1wpA0f1pJbL7Sgy/U1b6Vicy/UNipv5LhuazuqM3d5u+7rqUvnFZBUUjBTfQw5YI8eIpOCm6q0442es0YVcP3//u4t756lOhvUXerv8hVQVbnaqVx9rHt+mE35m61ewFWX6uuSfZWTEEAAgToXYPgIIIBATQjo7Cdd6u7ut6f7i44/3WzwAdkzVUYcljLdP1SXhirpLKgJZ6Vzl5W6SbjAqi6nV557VBv1efCnerdRPRICCCAwkAJ6bRsyNm3u9h66xcfm581GHGbe65ouoXevZxrX1j9m/rDTmTYXUFWeS/6z5PXHIp0drzL1qddKLZMQaHSBpkac4BPPrLDJM+Z6adbZV9mmLdty0yxWdseSh7w2aqtl10jtZ18w31a9tNZlRT7qrE1V+t3vX9BDLh30njHeZeS69NylsLM1FeDU2ZzL//CC7W7vtPeNe499/Nip3mX6usTenSGqzhXgdEFYXR6vcuUXS/oyJV3arkvp1aZY3bAyBWhd2Za3t9uu3e1utdejgqIal/vyJn1RVa9KFczwBysVsNTZoDqLVPnBzegeogpa6jJ4f9l+zXstewm+P9e8e5a2fqDLdPl9fkl2zZ0tut+QvaYzUbO5ZsPGvusWeUQAAQQQQAABBBCokICCmLosVEmXiLaMS+V69pepXJeO6myoXIV9C6qn+43uW/UetK42wT69Qn4ggAACVRJwXyC3+rqUKensTl06r+HoLHr9MUd/1FF6e0XaDv+i5f5YpDpKCn5ufNKs7ePmBVT1uqjltUt6+tTrourWTkoN0FDYTJIEmuKabLFgooKT515+ba+zKSsxFvV97U1LbOl9N9iqpYvskcULbWzrKK9rBTa/c+Niu+fWTJAzUzb7MzPs6m/d6o1D4336+ZVeO7XVsvLU8GePPmOzZk63yUdN0GpJSUFNnTXqPytSgU2dAaovWnKd6EuSfv6L/+ed7amzPnWJvCvTo84Kvf+hpaYzM9WngqEKgqpMZ5TqUXl6/OX/y/yZKLOgS/h1P9Kpf3VUZi38n/rWpe0KvuqS+r4GRxWkfW7ZH3P3Mr3/4aX2nrGtXgBXZ4+mUinT2a7+EehMVs1D21KQ1F/mX97y9jaL+vIlXdb+yq9G5JrpfqA6Q7T10Ozl7bmCzILKXnxklI2fvjuzlv2nsz11Wbz6Uc57JnV4l+KrrtYV3BycCWwOG9vtXU6/8qejTJfcq0xtdMl8oUCnytzZoi7gqjZKYYFUlZEQQAABBBBAAAEEEBhwATaIAAJ1J6Agpv7Ioz/cKOmPOG4S+sOQ/pijfKWJl6Z6BUVVV31M+C8pU32tK2nZtfX3qbLaSOnaGAajaCiB2AKjxZTaWkfbzt0d3lmQxer1tUyBzJsXPWDXf/3iXDDU38dzy1fbRz90ZC7AeczRk2z9m5ttzbo3bePmbTZ8+FAb1tLsJS0rT30qSPrZk47zd1XSss4a/YgvOKmA4De/cpEpIKhLyZX0JUlHHf5+716hCqT+4M6fmvLvvv9RbxsKeh5x2HhzQU7de1P35lQwU/2pkvK+evl5dvdPfuG1/dfv/8i+889ftiM/8H4VRyadsaqAZV+DowqqnnX6p3O3BtC8ND+NS2PSFzr98zX/0xuTvqhJ9yBVIPXEM/7WPn/hV033I40cXJEKOhtz27r9c1+8pEvlJ87aZrqkXs0U4HT39tS9QqefuylXpvJgajuqy7tvqPrRpfcKfE45Y6t3dqg7y/TxBeO87f36+oPtvR/dbYedsCvYjb3yywPs/cfuMtdGl/QrKKs+dfbo+Om92/TqhIzaE0jV3pAYEQII9F2AFgggUE8CNf7Ll8/n9XQwMVYEqiRQ469jVVJhswjUkkBVAqMKUI4Ylg1CVhJDgcy/vLHRzrxwfu6S+HnX3J7bxKtr1+eWtdA2ZpSlUinbuGWraXnXrg4vWKvL1rWsPJ0tevz0KQUDrerDJQUD//Ubl5mChcE85atc+XrUuruM/ic/vj4XwFRbl3/Wvi9DUoDx5n/9x1wd9XHVpV+0s/aVa11JQVD1pfZ61Lry1f5H/+ObeeMqlKc+NS6NT+0KJW0zWEd52qZSsTLNTWPS2FRXjz+++V9M29W2VK5xamxa12PUly/pbMxpc7d49+7UpfJKCm6qvZICpJ/6ypteue776QKVKlNSUDOYrzz1oxQs83/Rk8pVV/0Ek+r5x6Htqi+10Xg17mCbmNbptpICfPippCZ9IYAAAgggUIJAjf/yJd5Rwj6kCgJJF6jx17Gk757Gmj+zKVOg4oFRXa5+7KkX24wzLrPVL6/NC1JOnpG97+cP7nrQrrjoLO/y8TLHXbCZApwfPOL9tuzhW7zL6HVJ/PKVr5j/fqGHTxhXsK0ut1cAVONW0rIqurNFFWCdvG/8ulxfZUoHHdhspMobjB01xPbbL7nvNgcPSllbxqCSx9bBmWOV1GxRBiOHp+ytd16wDV0rGyKt7+zDPDr/w/YM2myHtA4lVcFg6P6D9Gslsal1xP5lH3cHZtomFi4zcR07PG953aq3Y4Dn7aCyX/PeM7o58e+TDxrdXLafXjMzL52J/Xfg8P0j3w+HvV8enWmbWLjMxIfu31S2nT7b7Zf5jJfpJpH/+vv59t3MZ5Q3uv7D3sh8RktaerPrBRt9QFPRuFMiD6oKTrrigVHdh/PZB2/27tU56cgJ5u7nqft9uqRy1avgPAp2pWCn7iOq4Kb7YqLgWaP+hufNOcULqGqcWnZni+pM1F3tHV7AVfO5edEDpkvs1fanT/3WotJbb3daVIrqQ+VRfahc9aKS6kWlqD5UHtWHylUvKqleMG3e1mXvvtvz17XX/5yyqKT9EZWi+lB5VB8qV72opHpRKayP5S9usAee+Z13bAVtCq1HGat8Q+Y4jEr3ZY7nqBTVh8qj+lC56kUl1YtKUX2oPKoPlaue0sYd7fbLdf/Llrz89V5p4WNft6hUqF0wL6oPlQfbFFpXvah09yu95xHsy/Xxb49/y/7vsmX270/2Tm9s6bCoVKhdMC+qD5UH2xRaV72oVKhdMC+qD5UH2xRaV72oVKidP++pP74S9ZLhlYe9bvjzvYoRP/z1w5YjuvCKw9r6872KET/+729+X/DY8xuFGb+9851c7/7thi3nKhdZCGvrzy/SPFfkrx+2nKsctpDJD2u7bu1e07EjpzAff77qRSV//bDlqD5UHtbWn696UclfP2w5qg+Vh7X156teVPLXD1uO6kPlYW39+aoXlfz1w5aj+lB5WFt/vupFJX/9sGX18VDmOf/qmo7Q93eZwz7yX9jzwp8f2Ummgr9+2HKmWuS/sLb+fNdJxzt7Qn+vyqdY+unTv817n+z6DD76txu2HGxTaD2srT+/ULtgnr9+2HKwTaF1vU+WQTGjsGNP+bJXv2Fj8OerXlTy1w9bjupD5WFt/fmqF5X89YPLes499PzvTe95o5LeHwfTw5m26sP1GzUWlbu6xR5VLyoVa+/KovpQuatb7FH1CqWOd/bm7II2hdb9xhv1+XZPz+db13+xcbgyV7fYo6tb7LFYe1dWrL0rc3WLPbq67lHPW/f5Vp9NlQp9rg3mqZ7Sw8uet+/+8lv2r5nPY8H0fzKf26JSsE2h9ag+VF6oXTBP9aJSsE2hddfHr15fZG9t210wpiQbpWL7grJogYoHRt0mFZS897b5uft5uvw4H9taC9+79KC2A72zU4NniyrgmU6nTe2C41LgUwFV3Vt045atpkvrVUeX1+s2AFpW+s/f+rpFJb38RaWoPlQe1YfKVS8qqV5UiupD5VF9qFz1opLqFUrydenfF+9nUcnVLfYY1YfKi7V3ZaoXlVzdYo9hfXztxkdt9r5jq5BNMC/KWOXFxuHKtM2o5OoWe4zqQ+Vh7f35qheV/PXDlqP6ULm/bdr22F57t1e6Z3HKolKhdsG8qD5UHmxTaF31olKhdsE818fiu7rtb6/7gXfsycSf/D5hy/76Ycthbf35YW39+f76Ycv++mHLYW39+WFt/fn++mHL/vqFlv/2ujvCmublh71u+PPzGoSs+OuHLYc0zcsOa+vPz2sQsnL2ggUFjz2/VUjTvGz/dsOW8xqErIS19eeHNM3L9tcPW85rELIS1nbJXXtzz9uQpnnZfs+w5bwGISthbf35IU3zsv31w5bzGoSshLX154c0zcv21w9bzmsQshLW1p8f0jQv218/bDmvQchKWFt/fkjTvGx//bDlvAYhK2qr5/xt/+ut0Pd3IU3zssOeF/78vAYhK/76YcshTfOyw9r68/MahKzIJyqFNM3L9m83bDmvQchKWFt/fkjTvGx//bDlvAYhK+59cjGjkKZ52WFj8OfnNQhZ8dcPWw5pmpcd1tafn9cgZMVfP7h82/960/TcC2mal13IV21v8z1v8xqErATHUGg9pGledqF2wby8BiErwTaF1kOa5mUX8gnm5TUIWSm0/WBeSNO87GCbQut5DUJWCrUL5oU0zcsOtnHPW30udSn4mbbQuqt7UeZ9sj6ruM8t/sfgZ5tC6/76YcuF2gXzwtr684NtCq3764ct97TbY4VslOd88vDrbKUWhhtbYNRNTpedu0vQ3aPyXHklHw8df5ApaPnd2+71ulVw896fL7UTP/Exb11ftvS7P75sutxfGbrX6biDxpjaad2f3NmiCvAqcKovY1K5gqn64igtKx37wckWlVQvKkX1ofKoPlSuelFJ9aJSVB8qj+pD5aoXlVQvKr33fWmLSlF9qDyqD5WrXlRSvagU1YfKw/r4qw+8J3dcqV5UijJWeVQfKle9qKR6USmqD5VH9aFy1YtKqheVovpQeVQfKg/bXwv691AAABAASURBVP581YtK/vphy1F9qDysrT9f9aKSq/++8Sk7+shDc8eeXFyK6kPlrm6xR9WLSsXau7KoPlTu6hZ7VL2oVKy9K4vqQ+Wubtij7FUvKrn9Vewxqg+VF2vvylQvKrm6xR6j+lD5X0/8YMFjz++lelGp2DhcWVQfKnd1iz2qXlQq1t6VRfWhclc3+Oh/3qpeVPJ7hi1H9aHysLb+fNWLSv76YctRfag8rK0/X/Wikr9+2HJUHyoPa+vPV72o5K8fthzVh8rD2vrzVS8q+euHLUf1oXK11XP+sAnNoe/vVC8qBZ8Phdaj+lB5oXbBPNWLSsE2hdaj+lC5fKKS6kWlQtsP5kX1ofJgm0LrqheVCrUL5kX1oXL/++QwJ9WLSsFtF1qP6kPlhdoF81TPzIo+BNsUWi/awb7CQu1cnp5zeu7tq1r0oZCt2qoP11/RDvYVurrFHvdVLfpQrL0rK9rBvkJXt9jjvqpFHwr5BPOKdrCvsNg4XNm+qkUfXN1ij0U72FdYrL0r21e16IOr6x4LPW+LdrCv0JnqfbLe87j+/I/7qhZ98NcPWy7awb7CsLb+/H1Viz7464ctF+1gX6Hz2bfKQ5kCsQZGFQC99qYl3mX1ujxdSZeiz1twe959P8sce69mLUOb7dqvXWi6r6iCsLpXqC6ln3ncVNN/unz/K5eenbvvqYKmqq92KndJgdM/rP6TzTntk16W2n140gds2skXeW0vnvu53Jcx/fs/fdOiktdJxI+oPlQe0YVXrHpRyasY8SOqD5VHdOEVq15U8ipG/Jj9X9+1qBTRhVcc1YfKvYoRP1QvKkV04RWH9fHtL3/a7t13bHkVI35EGas8oguvWPWiklcx4kdUHyqP6MIrVr2o5FWM+BHVh8ojuvCKw/aXP9+rGPHDXz9sOaILrzisrT/fqxjxw9U/+5xBdstV5xd8TYvowiuWY1TyKkb8iOpD5RFdeMWqF5W8ihE/ovpQeUQXXrHqFUu3XPUlr17UD7e/ij1G9aHyYu1dmepFJVe32GNUHypf8rWvFjz2/GaqF5WKjcOVRfWhcle32KPqRaVi7V1ZVB8qd3WDj/7nrepFJb9n2HJUHyoPa9uT/01Vi0z++mHLkZ1kKoS19ednqkX+89cPW47sJFMhrK0/P1Mt8p+/fthyZCeZCmFt/fmZapH//PXDliM7yVRQWz3nLzz3oND3d5lqkf+Cz4dC65GdZCoUahfMy1SL/BdsU2g9spNMBflEpUy1yH+Fth/Mi+wkUyHYptB6plrkv0LtgnmRnWQq+N8nhzllqkX+C2670HpkJ5kKhdoF8zLVIv8F2xRaj+wkU6FQO5d34bkHm557mWqR/wrZqu2FvudtZCeZCm7bxR4z1SL/FWvvyiI7yVRwdYs9ZqpF/ivkE8yL7CRTodg4XFmmWuQ/V7fYY2QnmQrF2ruyTLXIf66ueyz0vI3sJFPBmep98pxzmgr+zshUi/znxlHsMbKTTIVi7V1ZplrkP1e32GNkJ5kKziezyL9+CMQWGNU9Pe+891G7+pI5uSCixqkg44J555suU1cd5VUy6QzPRxYvzLtXqL9/BUkVoFVSPdX3l2tZY/z+v3zZu/xe60rnzem5/+jMfYFW5ZMQQAABgwABBBBAoLEEkvv9j421H5kNAggggAACCCAQIdDnwGhEf7ni3e2dpkvOdRl6LnPfgvJUpjr7snhAAAEEGlZg3f1pW/lt85KW/RPd+FQ2X+Wv/thsT5fuFpOtobrKV9r+YjZPP9vXp+2V2826d/TUVT6p3gSIvNTbHmO8CRLg5TVBO5upIoBAMQHKEGhEAX3m0mcvfc5S0mcyN89iZfr89eKN2c92etS6a6c+9PnNrfNYPwKxBUaHtTR79/vUFxcFOZSne4GqTrCMdQQQQKCRBNwvxylfNVMaf1pPMEzBzrdXpG3ipWmvbPABaVv/cHb2Cn7u7TSbdGXaDp+btq2/T+eCppuXmbV93GzwAT19ZVvxs74EiLzU1/5itAkQYIoIIIAAAggg0OACCnyuvTtlIw7Lfj7TZ7S2E3omrc9j+lymfH1O0+c1fW5Tja1/TNmBU1PeZzc9al35CpDufM3s4OzdGJVFqiOBprjGqvt2Hj99iukeo/oSJLcd3b9T9xhVmeq4fB7rQ4CP8fWxnxhlbQjoF2j3jpSNO7nweLa/mPZ+sboA58iJKWt/PXsmaPfOlDU1mw0akrLBI8z2vJOyvV1mLmA6/ND+PhuN/xBAAAEEEEAAAQQQQACBRAlsWZb5fHVA2vzBUAegAGfXppSNmZbN0ee0lveZ6XObcjo3p23IGC2Z96h1rSlAqkCr6mudVF8CsQVGxaD7cuoeo/oSJH0ZktKZF8433WNUZaozIImNVEwgVbGe6AiBxhfo2pwJZGYCnauvS3mX0esyDQVLNXP9pVJBUy27NHhEJtiZSln3TssEQ9OmM0a9epn1QfunrWmImc4WHf2RlBcwNf5DAAEEEEAAAQQQQACBfAHWECgioGDm9lU9n89WX5f5zLY+8zks00afw/Z0ZRZ8/5rHZD6f7Uh5V+9pWZ/xVKxHrSuYqrNFR38o24fKBjxVcdMDPtcYNtgUQ595XeqLilYtXZT7MiQtKy+vEisIIIBAAwrol+57PtFzicb4M8zWP9jzi1dTdn9x1LI/tYxLeWeMrs4EVV9dlDIFQ/XLV8HSlkPS5u6Js9r3i9z4DwEEEEAgcQJMGAEEEEAAAQRKE/BOOskEOfW5TJfKK405xmzdT7JX7amXQUPMdMWeloNJwU9dWq8TXvSodXe2qIKq+mymMn1W07aC7WNb5wy2ftE29as1jRFAAAEEShbQ5e9D2sx2ren5zaVgZ1gHuh+pflkrjZzYc7Zo+xspc/e9GXeq2YbHs3/BDOungfKZCgIIIIAAAggggAACCCBQMQEFN9WZPmPpUWeMKsip5WDSpfITL83eY1SPKndni+rKPn0202c3fVbTJfsqJ9W+AIHRmt1HDAyBZAo00lUAurRCZ40G96TOEh2ke4cekD/b7p2ZgGk6XfAvlP57i/qDqbr8XpfZB7fBOgIIIIAAAggggAACCNSLAOMcCAH3Gcz/eUrbHdScynwGy34OGzREOT1Jn+cU6ByU+fzWk5tdcmeL6pZn/tuk6XNgtgY/60Gg4oFRfdHSrLOvMt1PtFhSHdWtByTGiEDfBDLBrb41oLZPoJH0dIborj+lzN1XVGeKdm9Pmy6F15RHTkyZLsHQfWm0rpt66+be+kuk1v1Jf4HU5fT6hazAqitTMFVfzOTWeUQAAQQQQKDmBRggAggggAACVRLQZ7DNz/Xc3kzBTQU29RlLn8OGjE173+ug4elzWvvrZmqjdX9SmTtbVJ/RFDx15QqmumUea1+g4oHRsa2j7JHFC/PuKar7irr0uU8fX/sqjBCBfgnknwXYr65oXNcCuk+oLqdYd595X76k+4uOP91Mv3A1sZETzQ6cmrIXb8ze/Ft/ZRx3skrykwusqr5K3KPuX6M+D/5Umi9jEkyNJoaFAAIIIIAAAggggAACtSGgz1K6r6i+x0Gfp3SiyvjTej5P6fOYPpepTJ/T9HlNbYKj3/ArszHTez7bHfxJsw2Ppb3PfWrfOo24QNCsVtebBmpgTzyzwjuL9IFfPG03Lfg7L3iqIOpAbZ/tDIgAG0EAgYCAfonqPjNKk640U7DUX6XtBDOVKR3+BSsY4FQfut+ov53W1aZQn/56LCOAAAIIIIAAAggggAACMQjUbZf+z2C6V6g7cUUT0tmf+lymz1pKqqv8YNLnMX1Oc/nqQ32pjdqrH1fGY20LxB4Ybe/otHMvv9Yumfc909miOnN05nFTa1uF0SGAAAIIIIAAAghUQCBVgT7oAoFaEGAMCCCAAAIIINCIArEGRu9Y8pBNO/kie+GVP9s9t863Bf94fiMaMicEEEAAAQQaS4DZIFAxAS4jqxglHSGAAAIIIIAAAghUXCCWwOiql9basadebP926z329xeeac8+eLNNPmpCxQdPhwhUQoA+EEAAAQQQQAABBBBAAAEEEECg8QWYIQJBgYoHRjdt2WZXfONm++AR77dlD99i5805JbhN1hFAAAEEEEAAAQQQQAABBOIVoHcEEEAAAQQQiBCoeGDUbe83K17wLqOfPGOu96VLwcdZZ19lCqK6+jwigAACCCCAAALlC9ASAQQQQAABBBBAAAEEEOibQMUDo2NbR9kjixeavmSpWFId1e3bcKldPwJ82UKs+4rOEUAAAQTqSIDfiXW0sxgqAggggAACCCBQWwKMJlaBigdGYx0tndeRAF+20Htn8cG4twk5CCCAQBIE+J2YhL3MHBFAoDIC9IJAVQX4lV1VfjaOQDUECIxWQ51tJlSA37IJ3fFMGwEEEAgTIL+qAvzBsqr8bBwBBBCoRQF+NdTiXmFMCMQqQGA0Vl46RwCBHgGWEEAAAQQQqCUB/mBZS3uDsSCAAAIIIIBAIwnUz1wIjNbPvmKkCCCAAAIIIIAAAggggAACtSbAeBBAAAEE6lYgtsDopi3bbPYF823VS2t74TzxzAo79/Jrrb2js1cZGQgggAACCCCAAAK1K8DIEEAAAQQQQAABBBBoFIHYAqPFgNpaR9vO3R22u53AaDEnyhBAoOoCDAABBBBAAAEEEEAAAQQQQAABBBpUwBcYHbgZPrd8tY0YNtSGtTQP3EbZEgIIIIAAAggggAACCCCAAAIImBkICCCAAAISqHhgVJfOH3vqxTbjjMts9ctr7cwL59vkGXPz0g/uetCuuOgsaxlKYFQ7gYQAAggggAACCCAQowBdI4AAAggggAACCCBQQKDigdHJR02wZx+82Zbed4NNOnKC3XPrfFu1dFFeUrnqFRgPWQgggAAC/RSgOQIIIIAAAggggAACCCCAAAIIRAtUPDDqNjm2dZTde9t8izkA6jbHIwIIIIAAAggggAACCCCAAAIINK4AM0MAgWoIpKux0YHbZmyB0YGbAltCAAEEEEAAAQQQ6L9Aqv9d0EMFBegKAQQQQAABBBCoAYEGf4sYW2B005ZtNuvsq/LuLeq/16jKVKcGdjFDQAABBBCotgDbRwCBGhBo8NMBakCYISCAAAIIIIAAAgjUlkBsgVFdSv/I4oV59xbVvUaXPXyLferjR9v1X7/YVKe2OAZmNGwFAQQQQAABBBBAAAEEEEAAAQQaX4AZIoBAbQvEFhgNm3bL0Gb78KQP2F0/eSysCvkIIIAAAggggAACCCBQfwKMGAEEEEAAAQQQqCuBAQ+MSueYoyfZK2vWG5fSS4OEAAIIIFCfAowaAQQQQAABBBBAAAEEEECgngWqEhitZ7DEjp2JI4AAAgjUvQB3kKz7XcgEEEAAAQQQQACB+AXYAgIJEqhKYFSX0R9x6DjuMZqgA42pIoAAAghUX6DBv1Cy+sCMAAEE6lKAQSOAAAIIIIBAcgViC4zqMvlZZ19lk2fYUgcsAAAQAElEQVTM7ZXe3Pi2fe2yc/qhzjkv/cCjKQIIIIBAcgWYOQIIIIAAAggggAACCCCAwD6B2AKjY1tH2SOLF9qqpYt6pR9+92rTlzDtG0MZD5zzUgZaApsw5YoI8HSrCCOdIIAAAggggAACCCCAQCMJ8EGptvYmo0GgPIHYAqPB4cy75vbcmaN3LHkoWMw6AgjUqgAnaNfqnmFcCCCAAAIIIJBUAeaNAAI1IMAHpRrYCQwBgX4LxBIYXfXSWjv21Iu9QKiCoE88s8IbqM4eXfbwLfb08ytN+V4mPxBAAAEEEEAAgSICFCGAAAIIIIAAAggggAACcQhUPDDa3tFp199yt33p86d6l9Br0JfM+56d+ImPadG7hP6c2Sd5wVHV9TL5gQACToBHBBBIqgBXYyV1zzNvBBBAAAEEEEAAgWQKMOsaEKh4YHR3e6ft3N1hxxw9yZveZ086ziYdOcHaWkd76/qhZdVRXa2TEECgQgIEVioESTcIVEGAq7GqgM4mEUAAAQQGToAtIYAAAgggUHsCFQ+M1t4UGRECCRIgsJKgnc1UEUCgpgUYHAIIIIAAAggggAACCNS8AIHRmt9FDBCB2hdghAgggAACCCCAAAIIIIAAAggg0PgCjTbDKgZGObWt0Q4m5oMAAggggAACCCCAwIAI8FFiQJjZiEGAAAIIINDgArEERnfuarczL5xvk2fMtRlnXGarX16bW588Y663vHNXR4PTMr2qCfBGuWr0bBgBBBBAoJ4FGDsCdSTAfdXraGcxVAQQQAABBGpXoOKB0bGto+yRxQtt1dJFRZPqqG7t0jCyuhXgjXLd7roBHTgbQwABBBBAAAEEEEAAgYwAH6AyCPxDAIFGFigyt4oHRotsiyIEEEAAgVgFeFMbKy+dI4AAAggggAACdSDQ9yFyyV3fzWiBAAKNIkBgtFH2JPNAAAEEjDe1HAQIIJA4ASaMAAIIIIAAAggggEDZAgRGy6ajIQIIIDDQAmwPAQQQQAABBBBAAAEEEEAAAQQqJVC7gdFKzZB+EEAAAQQQQAABBBBAAAEEEECgdgUYGQIIIFAlgYYLjM675nabPGNuXrpjyUM53ieeWZErm3X2VbZpy7Zcmeq5tlp2Baoz+4L5tuqltS6LRwQQQAABBBBAAAEEyhKgEQIIIIAAAggggEBtCDRcYFSsn/v08bZq6aJcOm/OKcr2ApvfuXGx3XNrJsiZKZ/9mRl29bdutfaOTi9A+vTzK23pfTd4ScsKiKrhzx59xmbNnG6Tj5qgVRICCCCAQOkC1EQAAQQQQAABBBBAAAEEEECgJgViDYwqsKizMt1ZmP5H5at8IFWeW77aPvqhI3MBzmOOnmTr39xsa9a9aRs3b7Phw4fasJZmL2lZeRqjgqSfPem4EoZKlUoKpPkimUpy0hcCCCCAAAIIIIAAAggggEDFBOgIAQQaQSDWwOh3b7vXjp5yRO7MTf9ZnI8sXmhjW0fFYvjAL57OXS7vvyT+1bXr87bXNmaUpVIp27hlq2l5164O293e6SUtK09nix4/fUpsY80bECsIIIAAAggggAACCNSiAGNCAAEEEEAAAQQaUCC2wKjOtHxlzXr7/OknDijbgn88PxeI1SXzP7jrQdN9Rd0gDp8wzi3mPSpIqwDojDMuMyUtq4I7W9R/71J/fweO2N9IlTcYNWywDRqU0i5IZBrUlDIZcGxV/tiKMh0+dL9EHnNu0kMGN1nrAUMSn6phMGS/QW43JPJxxNDBZR93aptItH2T5nnLa1Y1XrP6u02et+X/vh01fP/Ev08enTEo9xjk9+1+ZX9+Tfr75P33ayrbTp/tBsUWfdn3hqCGHwb18/Pt/oMSjJfZryMyn1GLfY7NVOFfPwQa+ujSPUFnHj/VXvvzhhxR8KzRXEFmQfcidWe1atmdLapL6ne1d9iyh2/x7k9686IHvHuSZprY7s536z3V5Pjbu961vXvTIk5kSqfT1pEx4Pga+OdXV/eeRB5zbtLd76ZtV0c3qQoG7+7Z63ZDIh+73nm37OOus/vdRJq5SfO85TWrHl+3ed6W//u2vbM78e+TZVDucc/v2z1lf/5L+vvkd/eky7bLfr51v7mr+liVjff38+2eBMcGtMO63in+vFUdUvkCsQVGdQbmEYeOM93Xs/zhVbZl8GxRBTz1BG1rHd1rQzrj1Z0tqkvtdWm9Kuny+hHDhmrRS13de41UeYN3MsGZTGzQM07iD73ud2UMOLYqf2xFmSrAkMRjzs15b+aJF2VEeTzH5Z6MvdsPSXx8J/Nho9xji+dtmvcivB+ru2NgYJ63tftq2p/ft7xPNuvP+2R+35b/O4Pnbfl23vO2dl+SYh9Zfz/f8rwtfuzFvgMbfAOxBUblpsvo/7D6T9be0anVbIrxJEAFM79/x33Z7WR+rnpprf3ujy+bvmQps+o9al35WlfQdtxBY+zQ8QdpNS+5s0UV4FXgVF/GpAoKpu7c3aFFEgIIIIAAArUjwEgQQAABBBBAAAEEEEAAAQT6JBBbYFRByiu+cbM9/uRym3byRTZ5xtxsmpl9nHX2VbnL0fs04iKVh7U02+//40/Z7WS2d+aF8+0rl55tuqRezfSodeVrPPf+fKld+7ULrWVos4pzSYFTBXTnnPZJL0/tPjzpA9481PbiuZ8zBUy9Qn5URYCNIoAAAggggAACCCCAAAIIIIBA4wswQwTiFIgtMKrA4SOLF+a+CGnV0kV5yypTnUpOTgHOH3736rztzDxuat4mtO7GEjYGBUK//y9fzguY6p6jrp36yOuUFQQQQKDPAsn9crE+U9EAAQQQQACB5AgwUwQQQAABBBAYQIHYAqMDOAc2hQACCNShQIz3FalDDYacVAHmjQACCCCAAAIIIIAAAgjEK1Ds03fsgdEnnlmRu7Rdl68rKS/eKdM7AjUowJAQQAABBBBAAAEEEEAAAQQQQKDxBZhhTQkUu14z1sCoAqDX3rTElt53Q+7y9ntunW/zFtxudyx5qKaQGAwCCCCAAAIIIIAAAggggEDfBWiBAAIIIIBAvQrEFhht7+i0O+991K6+ZE7eFxXp/p0L5p1vTz+/0lSnXuEYNwIIIIAAAggkUoBJRwoU+5t8ZGMqIIAAAggggAACCCAwYAKxBUZ3t3fazt0d1tY6utdklKcy1elVSAYCCNSQAENBAAEEEECgrwLF7uLU176ojwACCCCAAAIIIDAwAsncSmyB0WEtzTZi2FDbuGVrL1nlqUx1ehWSgQACCCCAAAIIIIAAAggggECcAvSNAAIIIIBARiC2wGjL0GY7fvoU0z1GN23ZltlU9t+ql9Z69xhVmepkc/mJAAIIIIAAAgggEJcA/SKAAAIIIIAAAggggEBvgdgCo9rUeXNO8e4xOuOMy2zyjLleOvPC+aZ7jKpMdUgIIIBAhQXoDgEEEEAAAQQQQAABBBBAAAEEGl+g3zOMNTCq0c08bqqtWrooLylPZSQEEEAAAQQQQAABBBBAAAEEEChFgDoIIIAAApUWiD0wWukB0x8CCCCAAAIIJFCALzqPbadv6HjZ1uxcUXtpAMa0of1lM74rKrZji44RQAABBBBAAIFaFyAwWut7KMnjSyX3k0o6ndy5J/WQZ94IIBAhwMtiBFD5xW+0v2g/W3dNIpOCwmmC7uUfPLREAAEEEEAAAQTqXKDigVF90dKss6+yux/4lenR3VvU9+jda1Rlqlvnfgw/ToEEf1JJpfiUFuehRd8IIIAAAj0Ce9N7rXtvZyLT3vSeHgiWEEAAAQTiEKBPBBBAoKYFKh4YHds6yh5ZvNA+ecLRNmJ4i91z6/y8+4uuWrrIblrwd3bIe1ptWEtzTeMwOAQQQAABBBBAAAEEShegJgIIIIAAAggggEA9CVQ8MFrK5NtaR9vO3R22u72zlOrUQQABBBCoRQHGhAACCCCAAAIIIIAAAggggEAdC1QlMPrc8tU2YtjQujpjtI73MUNHAAEEEEAAAQQQQAABBBBAAIESBaiGQL0JcDv+8vdYxQOjq15aa8eeerHNOOMyW/3yWjvzwvnePUUnz5ibe/zBXQ/aFRedZS1DuZS+/F1HSwQQQAABBBBAoHYF1t2fthdvTFv3juxb9Y1Pma38du+kfM2ifX3aVl+XLX/1x2Z7urLtVKa+XD2tkyoqQGcIIIAAAgggUOcCfEtJ+Tuw4oHRyUdNsGcfvNmW3neDTTpyghW6x6jKVa/8YdMSAQQQQACBcgRogwACAyGgQOb2Vflv0dtOMJvy1Z408dK0NbeZDT80GwDdvMxs3Knm1Rl8QNp2rcm2V8B0b6dZ67RsvYEYP9tAAAEEEEAAAQQQSIZAxQOjjk1fwnTvbfONAKgTqcIjm0QAAQQQQAABBAZYwJ3ZOf6M4hve+seUDRmbtpZxKe/sUAU/B4/IBj+bx6Ssa3O2vQKmoz+SskFDsoFS4z8EEEAAAQQQ6C1ADgIIlCXQVFYrGiGAAAIIIIAAAgggEBBQUHTna2bjTg4UBFZ1ef32F8zGTMsWKOjZ1GzWvTMb/OzcnLYhY8zc2aLurNJsbX4iYJZ0g7Rl/4iQdAfmjwACCCCAQH8FCIz2V5D2CCCAAAIIxCtA7wjUhcD2F80UFJ1wVjry7E7/2aJucgqSrn8we4/R7h0p7xJ7d7aoLqt39yfVZfquDY8IIIAAAggggAACCPRHINbAqPsiJv8XL7nlWWdfZZu2bOvP2GnbkAJMCgEEEECgHAHOHSpHrRHbZM+4rMbMdOl7++tmq69LeV+ytO4+MwU4X/2RHnuOUJ0F+vbve84WdWPVJfWTrszeY/TwL5h3Kb0ur285JG1bf5+2w+embdKV+jKnlCkI69rxiAACCCCAAAL1KsC4Eai+QGyB0faOTrv+lrvtS58/1fsCpk99/Ghb9vAttmrpIvvcp4+3qy+ZY7oPqfEfAggggAACCPRboFrhsJ5wV7+nQAcVEajeHgl+uZLuMaovUTr8i2aDD+g5QnUWaMt7s/cWLTZl1dO9RVXHXWKvS+7Vp/JICNSdAANGAAEEEEAAgZoTaIprRLvbO23n7g475uhJ3iY2vPW2KU8rJ37iY3bnvY+agqdaJyGAAAIIIIBAfQr0hLvyx88aAoUEdLZo+19SuXuLFqqjPNXT2aK6t2jTEDP3pUx7urJnjKoOCQEEEEAAAQQQQACB/go09beDUtq3jRllI4YNzVVtax3tBU1doDRXwAIC9SnAqBFAAAEEEEAgQkBBzQ2PpyzqbFHV2/ikWdvHzbtXqc4S1fLaJSnvMn2dMTpyYsTGKEaggQV0XniSv3xpb3qvWVoKDbyTmRoCCNSyAGNrMIHYAqPDWpq9YOhzy1d7l8wf1Hag/ezRZzw+5SlQqjpeBj8QQAABBBBAAAEEGkpAwcuJl6Zyl9ErwKl7h44/LVV0nqo34b9kAqjjeur57z8a1b5o5xQi0AACemakLDVAM6m9zTSlMh9hU8mdf+3t3RwdfQAAEABJREFUEUaEAAII1LdA5rdKPBNoGdpsP/zu1XbenFO8DVx+wWy79+dLTV++9IO7HrQrLjrLVMf4D4EBF+CN1ICTs0EEEECgHgQYIwIIIIAAAggggAACCCRKILbA6KYt22z2BfNt1UtrPVB90dIjixd6X760YN753hczcY9Rj4YfAy7ApTciJyGAAAIIIIAAAggggAACCCCAQOMLMMNwgdgCo+GbNOMeo8V0KEMAAQQQQAABBBBAAAEEEChTgGYIIIAAAgiULFCVwCj3GC15/1ARAQQQQAABBBAoIkBRNQXe6HjFHvjzNXbf2m8kLv3yjdvsnb3t1eRn2wgggAACCCCAQL8FKh4Y1aXzx556sc044zJb/fJaO/PC+d59RSfPmJt75B6j/d5vdIBAMgWYNQIIIIAAAjUkkE7vsbW7Vtianb+rifTaAI7jzfaXLZ3gLwCqocOQoSCAAAIIINCYAgM0q4oHRicfNcGeffBmW3rfDTbpyAl2z63zvfuKrlq6KPeoctUboDmyGQQQQAABBBBAAAEEGl6Ar5ds+F3MBBtYgKkhgAACCFRHoOKBUTcNfdnSvbfNNwKgToRHBBBAAAEEEEAAATMDAQEEEEAAAQQQQACBmhCILTBaE7NjEAgggEDVBRgAAggggAACCCCAAAIIIIAAAgjUokBlA6OBGW7ass1mnX1V7t6i/vuMKl/lgSasIoAAAggggAACCCCAAAIIIIBArQswPgQQQKABBGINjH73tnvt6ClH5O4t6r/P6COLF5out28AQ6aAAAIIIIAAAggg0OACAzm97S+arfy2mR4LbXfd/Wl78ca0de9Ie8V61Lra6FHrXkHmx8anzFQ/s8g/BBBAAAEEEEAAgYBAbIFRnQ36ypr19vnTTwxsklUEEEAAgRoXYHgIIIAAAlUSUDB03X3hG1eQc/uq/K9Z2vrHlB04NWVTvmreo9bVgwKkO18zO/iTWiMhgAACCCCAQP8F8n8H978/eqi2QGyB0WpPrPTtUxMBBBBAAAEEEEAAgeoLtK9P28YnzQ7/b2kbfED2bFD/qHT2p9bHn6GfPalzc9qGjMmu61HrWlOAdMRhlumLD3HyICGAAAJmGCDQX4Hev5/72yPtqyvQFNfmdZn8EYeOs+eWr45rEw3eL29gG3wHMz0EEEAAAQQQQCAnoKDoup+mbNwpmaDo8Fx2bkFBUZ39Oe7kXFZuoXlMyro2Z1f1qHXvbNHXzEZ/iA9wWRl+IoAAAggggAACvQV6B0Yr+N5Jl9H/YfWfrL2js/eWyYkQqOCOiNgSxQgggEAjCDAHBBBAoF4FFMRc/1DKxv9N2lrG9f7juC6vV1B0wllpGzSkd7mCn2+vSHv3JdWj1t3Zot07zVZfl71n6as/NtvTxXvMej1OGDcCCCCAAAIIVF6gd2C093utsraqe4xe8Y2b7fEnl9u0ky/q9c30fCt9WayuEY8IIIAAAggggAACDSKg4GX3drNXF6W84OaLN6ase0fKdK9RBUV1Fmj76wpwZsuVr/JXf2SZemnvUvmJl2bvMapHsSiQqgDp5mVm40417/6jujx/y7IKvdnXRkgIIIAAAgMhwDYQQCBGgd6B0QptTJfSP7J4oa1auqhgUpnqVGhzdIMAAggggAACMQpwjlmMuHSdeAGdJTrpymzwUl+gNPFSBTvTpnuJjpxo1nZCT5nKla8g5+FfNC8oGgR0Z4s2DVHgtCcQqkvsg3Vrb50RIYAAAggggAACAyfQNHCbYksIIIAAAgggkCdQRys9oZU6GjRDRSCBAros350tqsvuFUB1DO5Lmdw6jwgggAACCCCAQNIFYg2M6t6i515+rXcZ/bGnXmyrXlrr3W9UeXcsecj4L1kCzBYBBBBAAAEEEEAgXoENvzIbM91yZ5Ie/EmzDY9l7z+qy+9bp3H+d7x7gN7rToCnRN3tMgZcHwKMEoF6EWiKc6DfuuFOO376FFv28C02bepEb1MtQ5vtnNkn2dPPr/SCpF4mPxBAAAEEEEAAAQQQQMATGHxAynSvUF1G72UEfihf5aoXKLLxp6VM5S5fdVRXl+Af/gUr+OVNri6PZQvQsJ4FUvU8eMaOAAIIINBfgdgCo/rypVfWrLdjjp7Ua4xtraNt5+4O293e2auMDAQQQAABBBCoZQHGhgACCCCAAAIIIIAAAgg0hkBsgdFiPBu3bLURw4basJbmYtUoQ6D6AowAAQQQQAABBBBAAAEEEEAAAQQaX4AZJlIgtsDo2NZRNmvmdLv+lrvzzgzVmaTX3rTEu8Rel9UnUp1JI4AAAggggAACCCCAAAJVFGDTCCCAAAIIIGAWW2BUuOfNOcW7n+iMMy6zx59cbmdeON+0fPUlc0xlqkNCAAEEEEAAAQRiFqB7BBBAAAEEEEDg/2fvfuClqut9/38GRdl7g4IbiOJmmJkGUQdLU6xHm7oZ+qD05gP6QT/v5aclPvxpR/Nc6FC/e+jWoeBmWnp5QGo/zvEIP+VnJ82rpKfjPo/yT1qS0SZNDbJDEoKgwN5bEefOe22+w9qzZ2bPrFlrZv158eC7Z/35ru/6fp/ru9as+cxaaxBAAAEEhghEGhjV2mbNnGE93WsHJU3TvChTb1+/XXLNCi9p2K3roUc22bSuhV6avWCx6QpWN+/W9fd50zVfw2668sy9bJn1PLPNTeIVAQQQQAABBBBAAIEYC1A1BBBAAAEEEEAAgeEEIg+MDleBKOYrEHrl0u/aLzb9blDxCmx+68Z1dueaQpCzEKyd+6kuW/KNNab8Cn4+/Phm677rBi9pWNNUwD0PPOI9FmDaqVM0SkIAAQQQiJsA9UEAAQQQQAABBBBAAAEEEECgToFUBka/ccNt3jNMv7Ro3iCOx57cYh9437vNBTj1i/nbd+yyrS/ssJ279tro0QM/CKUfhdKwpik4qiDpp8+dOaisVo6wbgQQQAABBBBAAAEEEEAAAQQQSL8ALUQAgWgFIg2M6grNs+dcUbw9Xbeou1R6G3tYzVz6zZu9oso9w/T5bdu9ee7PxPFjLZfL2c7de0zD+/f3eT8UdaC33zSsabpa9Jwzp5t+TMotxysCCCCAAAIIIIAAAgiELkCBCCCAAAIIIIBAUwUiC4zq9vTrVt9hn//cnEHPF3XPG924bmXowUb3XNDlf/uFiognT5lcdp4CnwqA6sehlDSsjO5qUQVcpx1+NqmeU6p5SqPbjjZS+Abto46yEYWgtYyzmNT2joIBfevopu9fo445Kotdrtjmo4/KNd08u/18cP8eOSJX3A5ZHNC+F7QvaNksmrk2N7LfDrzfupKy9zqicK7RyPst++1Rgd8z2G+Dv98O7LfZfc9gv23sWK19j/fbYIa83wZz01Lst1IInobbb4OXzJISGKE/USRddbnvQJ/pdvUoyi9Xpq4IvfsnD5sLYH5nzZ3ec0b1vFEFarWM8ui1XNJVpi5wq2F3tahuqd/f22dP3L/a9HzSVWvvLv5ok3ZwUs4LYlZ1KHzwqHd+YRHL6j+1vV4v8udC6Yc5y1mW/6n19KVcKH2pXkfTjm/Z/acTknrNXP6c5bILV2i5Wu8sgrwWisjsf+12QczcMqYCMqtnxn4bfOPnCou6fhTkNctdT20PYuaWqbzfaqsUNkzK/7PfBt/A6iGuHwV5Db7mBC5ZUuXo9tuSFaV0dLj9NqXNblqz5BvJyvSczjEdbd5t6pGsoEyhulLUBTb1qmeMfmjGe+ym5X9t7W2jrPRqUQU88/m8TewcN6Q0/7NFdau9bq1XJt1er3ZpWOnV3oNGCt9gf98bdujNvIgzmdT2fQUD+tbBpu9ffa+/kck+5xp98FC+6eb084F+fvDQm24zZPK19/VDgfse+23w/Vbvtxl+u/XONRp5v2W/Zb/VATtIOtjA+632W50rBllvGpZR26PZb7Px2YP32+B7QaP7Le+3bwQ+1zvIeXJVu+C9miUlEFlgVIFI3Y5+24YHrLevX+tqedLVq7/6ze9Nzz5VZfRjTJMnjbeTTpyk0UHJXS2qW+wVONWPMSmDgqm6ElbDJATiKrDrtT/aEy/9s/3ipQ2ZS0+9vNEOvhmPY05c+wf1QqABARZFAAEEEEAAAQQQQAABBFIjEFlgVEIKRP7u2T/aGeddXry93d3mHtWPL2m9ldK0U6fYl69aYPMWLfPqs+HH3bbiq4u8q0n9yyhw+tSW52z+hR/zJmu59099l9cOLXvFwgtCfz6qtyL+xEwgudV57VCfPbJzvf1sx22ZS5tf/hd707LxjX9yeyg1RwABBBBAAAEEEEAAAQTiJEBdsioQWWBUV4k2+8eXSjeinhP6g+uXDAp8zpo5o/hjUJV+AEqB0O99/YuDllNZPd1rvWVVRum6mjFOqKcZyqwDAQQQQAABBBBAYDgBzkuHE4r5fKqHAAIIIIAAAp5AZIHRVvz4kteiFP/Rw55T3DyahgACCCCAQCQCFIoAAuELcF4aviklIoAAAggggEDzBSILjLbix5eaz8caEYidABVCAAEEmifAJWPNs2ZNCCCAQEoFeCtJ6YalWQgg0AwB1hGCQGSB0Tj++FIIXhSBAAIIIIAAAk6AS8acBK8IIIAAAgEFan8rCbgCFkMAAQQQQKCKQGSB0Zd27zX9uNEvNv3O+9Ei96NL7rUVP75UxYFZCCBQg8ArT5tt/nszvbrsh17L2/P/ODBd83b+3M0xO/hq3p6+Me8to1eNu7nK98KPuEbAefCKAAIIDBJgBAEEEEAAAQQQQAABBCIXiCwwOqFzrOnHjXoO/2BR6avmKU/kLWQFCCAQioCCoS/cNbSo7febjTwub9O/YnbaVXl7eVO+GDjd85ucnTAj583Tq8ZVggKk+/5g9taPacyMvwgggAACCCCAAAIIIIAAAgggkH6BuLVwRNwqRH0QQCB+Ar3b87bzZ2Yn/195LwjqaqgA52sv5Wz8GQNTRh6Xs/a364rSgStB+3fl7djxA/P0qnGNKUA65p1WKIubp+RBQgABBBBAAAEEEEilAI1CAAEEEIi5wIio6qdb6XW7vLt1vvRV85QnqvVTLgIIhCOgoOgL/5yzyecXgqKjB5d5cJ/ZodcGTxs1PmcHX80VpudNw6/tGpivV40rmKqrRce9byB4OjCXvwgggAACyRegBQgggAACCCCAAAIIJEsgssCobpPX7fKlt9A/cf9q+/hHTrfr/u4KU55kcVFbBLIloCDm9vtyduJ/ylv75PJXdx51rNnIMeVdFPzUrfV69qheNe6uFlVQdcu3B55NqmeU6lml5UuJ6VSqhQACCCCAAAIIIIAAAgggkHkBLvlJdhcYUUv1w8zT3jbK3j/1XXb7Dx8Ms1jKQgCBCAQUvDz4itnza3OHf0Bp4GpQPWtUzxzVKnXFqPJpuDTp1vrTrhp4xqheNd9dLbrrCbPJc8x7/qieUbr7ifKBVy1DQgABBBBAAAEEEEAAgeYIsBYEEKhPgE+y9XnFLXnho8EAABAASURBVHfTA6MCOOv0qfbs1u3GrfTSICEQXwFdJTr1bwaCl+7HlRTEPPEis+NPM+9KUV0x6m+BniOqPEcdO/TtwV0tOuJY8263d8vpFns3zCsCCCCAAAJNFGBVCCCAAAIIIIAAAhkWGJHhttN0BBBoUEBXhB47IW+6+lNF6db73j9ZIWg6NCiqee5qUQVNFTzVMkoKpuqVFLUA5SOAAAIIIIAAAggggAACCCCAgBNoSWBUt9GfctLkaJ8x6lrIKwIIRCow+byBqz/1HNGnb8zZCTNyhcDo0FW++K9m4880UzBVc9/6MbMXH8x7t+jrx5o6z+DJLHIhIYAAAggggAACCCCAQJ0CZEcAAQQCCowIuNywi+k2+dkLFtu0roVD0o6dL9tXr7542DLIgAAC8RJQUFPPCtVt9K5muvrz5P985Hb7iR92cwa/nnjh4ICpK0u36Gt5lTN4CcYQQAABBBBAoJwA0xBAAAEEEEAAAQTCEYgsMDqhc6xtXLfSerrXDkk/uH6J6UeYwmkCpSCAAAIIpFiApiGAAAIIIIAAAggggAACCCAQiUBkgVHVduk3b7ZLrllhvX39GvWShjXt1vX3eeP88QswjAACCCCAAAIIIIAAAggggAAC6ReghQggEAeByAKjCoDqlvmL55476OpQXSmqaQ8/vnlQwDQOGNQBAQQQQAABBBBAAAEEIhCgSAQQQAABBBBAIIYCkQVGD/T2274DfTaxc9yQZmua5inPkJlMQAABBBBItIB+RiuTSY0+vOV4QQABBBBAAAEEEEAAAQTiIcAHlWrbIbLAaEf7KBvT0WY7d+8Zsn5N0zzlGTKTCUkToL4IIIDAgEA+b3/Y9yt7+C+3ZzJtPfDkgAN/EUAAAQQQQAABBBBIpwCtSqRALpG1blalIwuMulvmly6/2Xqe2VZsj4Y17Zwzpw+6xb6YgQEEEEAAgWQK5HK2+7U/2WM778hkern/T8Z3scnsutQaAQQQKC/AVAQQQAABBJotQBCzdvFwPn1FFhhVQ2bNnGG3XLfYPn/tSpvWtdBL8xYts+VLv2CXzj9fWUgIIIAAAgggEAcB6oAAAggggAACCCCAAAItFggn2FdzI5q8uprrVVPGcILIkQZG1Y5pp06xR+9dZT3da4tpViFgqnkkBFolwHoRQAABBBBAAAEEEEAAAQQQQCD9ArSwikA4scUqK4j/rMgDo/EnoIYIIIAAAggggAACCCCAQCoEaAQCCCCAAAII1CEQeWD0oUc2ebfQu1vp9appddSRrAgggAACCCCAQBkBJiGQRAEuzUjiVqPOCCCAAAIIIJBOgUgDowqArrhpvXXfdUPxNvo71ywz/fjSrevvS6corUIgKgHKRSBjAjt/brb5748kjZcSvPCjfDGPht383u152/LtgWWf/0ezQ68deXiO8pUryy3LKwIIIBCtwJHjUbTroXQEEEAAAQQQSKwAFW+aQGSB0d6+frttwwO25Mr5NqFzbLFBeuaofnzp4cc3m/IUZzCAAAIIIIDAYQEFMvt35e20q/I2/Svmvb68KW+vPH04Q+FFAc7CizdfeU688MhVWLueMJs8x7x5I4/L2/6tA/MUMH2z36zzDAITsiMhgAACCCAQBwHqgAACCCCAQKsEIguMHujtt30H+mxi57ghbdM0zVOeITOZgAACCCCQeYGjjs2ZAp0jjxsIaI441mzk8Tl7bdcAjQKkB1/N2eTzBsb9fxVUVfBz5JiB4Oeo8UeWU8B03F/lTOUb/xBojQBrRQABBBBAAAEEEEAAgZgIjIiqHh3to2xMR5vt3L1nyCo0TfOUZ8hMJiCAQIoEaAoC4QgoIPraTrNjxw+Up/HeP5lt+XaueCu9gqWaq6DniFFmB/cNBFV15amWc1eLjj5pIGCqvCQEEEAAAQQQQAABBBBAAIEwBJJZRmSB0fa2UXbOmdNNzxh9affeok7PM9u8Z4xqnvIUZzCAAAIIIIBAicDBV/P29I15e35tzsafZXb8aQMZFOx8y0cHbpX3bqO/yGz7vWYKfirH+DMGxvWMUl1ZqmCou1pUt9VrupK7HV/LkBBAAAEEEEAAgZoFyIgAAgggkAqByAKj0rl0/vneM0a7LrrapnUt9NK8RctMzxjVPOUhIYAAAgggUElAt9KfdlXOpv5N3vb9wazSjyYp8HnsRCs+S7R9spYx7xmjJ/9n827B1+317W/L255f5+3khXmvTAVN3ZWmlerAdAQQMMMAAQQQQAABBBBAAIE0CkQaGBXYrJkzrKd77aCkaZoX38RtlvHdNtQMgcgFWEEMBXR7/Jh3mulKUVVPzw11wxp3SbfMu2H/q7taVNPcLfYqUz/MpGkkBBBAAAEEEEAAAQQQQACBzAlYpIHRhx7Z5F0l6q4WPXvOFaZb6S32/waeSxf7alJBBBBAIKUCuoVet7nrh5TURI2/vClvCohqXFeI7n8uZ+5qT90ef/CVvOmKUM33J91er6tFtYz3I06Hf5RJZeuKUX9ehhFAAAEEEEAAgfQK0DIEEEAAgVKByAKjS795s/d80e67biheLXrPPyy3a7+2yjSvtCKMI4AAAggg4AR0C72G3Y8rPX1jzk6YkbOJH9ZUM90qP3mO2Qt3mffjS3q+6ImfMXPLDeQyU/Bz58/MJn7ETFeIKml42/qc98NNumLUPbfULcMrAgikRIBmxEcgF5+qUBMEEEAAAQQQQMAvMMI/EtawrhR9cvOzdtuNS21C59hisRrWNM1TnuIMBhBAAAEEGhJI48InXpjznhGqH1dSckFR11YFNDVdaerfDARL3Tz3qkDolP8j5wVS3TQFVZVfy2kdbjqvCCCAAAIRCfCUqohgKRYBBBBAAAEEGhWIJDD64L/90uZ+qmtQUNRVVMFRzVMeN63OV7IjgAACCCCAAAIIIIAAAggggED6BWghAgggEKlA6IHR3r5+27HzZXvnO95aseKapzzKWzETMxBAAAEEEEAAAQQQyJQAjUUAAQQQQAABBBBopkDogdEDvf2270CfTewcV7Edmqc8ylsxEzMQQAABBNItQOsQQAABBBBAAAEEEEAAAQQQaKFA6IHRFrYl1qumcggggAACCCCAAAIIIIAAAgggkH4BWogAAskRIDCanG1FTRFAAAEEEEAAAQQQiJsA9UEAAQQQQAABBBIrEElgdN/+Xpu3aJlN61pYNmme8iRWjYo3RSBnuaash5UggAACtQuQEwEEEEAAAQQQQAABBBBAIC0CoQdGJ3SOtY3rVlpP99qqSXmUNy2QqWwHjUIAAQRCE+CLjtAoKQgBBOInkA+pSmGVE1J1KAYBBBBAIEMCNBWBjAqEHhjNqCPNRgABBBCoKsCn/ao8zEQAgWQLhPXdT1jlJFuzKbVnJQgggAACCCCAgAQIjEqBhAACCCCAQHoFaBkCCRUgSpjQDUe1EUAAAQQQQACBxAgQGE3MpqKitQmQCwEEEEAAAQTSIcCV5unYjrQCAQQQQACBqAQoF4HGBQiMNm5ICQgggAACCCCAAAIIIIBAtAKUjgACCCCAAAKhCxAYDZ2UAuMvwK158d9G1BABBLIuQPsRQCClApyGpXTD0iwEEEAAAQSSKUBgNJnbjVo3JBC7W/Maag0LI4AAAggggAACiRHgNCwxm4qKIoAAAghEIkChMRMgMBqzDUJ1EEAAAQQQQAABBBBAAIF0CNAKBBBAAAEE4i0QaWB06TdvtkuuWWG9ff1e0vC0roV29pwrrOeZbcY/BBBAAAEEEEAgNQI0BAEEEEAAAQQQQAABBBIlEFlg9KXde+3Jzc/axXPPtfa2UfaLTb/zYJ64f7UtX/oFu271HV6w1JsY4h8FYxV8demhRzYNKl3jbt7sBYtN9XQZbl1/n7l5GnbTlWfuZcsI5joQXhEwMxAQQAABBBBAAAEEEEAAAQQQQCD9AmluYWSBUaGNGd1uEzvHadAe/Ldf2qSJJ3hBUk3bd6DPDvT2e/PC+qMApspS8LWne63duWaZfevGdcWApq5S1bima/7cT3XZkm+s8QK0Wvbhxzdb9103eEnDmqby7nngEZs960ybduoUjZIQQAABBBBAAAEEEEAAAQTSKUCrEEAAAQQyJBBZYLSjfZSN6Wiznbv3eFdl6urRT3z0gx6tpu3b3+sNh/lnQudYW/63X/CCryp34vixlsvlvDpo/LEnt9gH3vfuYoDzrNOn2vYdu2zrCzts5669Nnp0m6neShrWNAVHFST99LkzVQQJAQQQQAABBBBIkQBNQQABBBBAAAEEEEAguwKRBUZ1+/y1l3/Wli6/2bouutpOn36KzZo5wwuSrrhpvTeuQGaU9L99Zqu98ur+4lWrz2/bPmh1/sCphvfvH7iKVVeyaljTdLXoOR+ablHXdVDFGEEAgWgEKBUBBBBAAAEEEEiBQM5yKWgFTUAAAQQQQCBCgRqLjiwwqvXr1vNH711lum1dV3JqmgKMG9et9K7s1HgUSbfM6weerlz6Xe95pqqHW8/JUya7wUGvqtc5Z073grgK5GpYGbyrRT8x0/zPLtVzSjVP6ZijRxgpfIORR+Usl5NwNtOIQtuPKRgE7VsjsoxX6DLqP0Htji64F4rI7H/1naB2ci903QzbmbHfBt/86j9B+x77bS7wuYjc2W+D++mYGbzXJ39J9R/222DbUX0nqJ3cs3yqN6Jw0OL9dmi/q3WK+k/Qvsf7bfD3C7kXum6tmyl1+dhvG9uk6j/V9tvGSmfpEWkkUCBUAVk9L1RXp/oDmaVXjfrbf+n8870grgK5GvauFi0ES3VL/f7ePtOzS/V80lVr7/aufNWyY9qPNlL4Bh1tR9sIHT2FnMGUy+VMBkH7lg6cGWQrNnnUMUcF3i/bCssWC8rgwMijc3Zcx8hAaXT7SDsqw/vtiMJ+K4OgfiMLX7RlsMsVm9x27NGB+p28tWyxoAwOZHC/DW0rs982Rql9T/tgkKRlG1t7spdudL/N8nky+21jfZ/z5OB+2m+Dfj7TZ7sRI4KvO+lL5nI5Pt82sBGH228bKJpFCwKR7pruys1pXQutNM1esLgYXCzUI5L/ugpUt/D/4Y8veuWXXi2qgGc+nzf9GJSXwffH/2xRPRNVt9Zrtm6v17NTNay0+9XXjRS+wd79B+3QobyIM5kOvZm3PQWDoH3rtTfezKSba/S+vjcC75da1pUTj9fm1uK1g2/arldeC5T27Hvd3ij03ebWOD5rU9tfLhgE9Xvt4KH4NKYFNXm192CgfifvfYVlW1Dl2KyS/Tb4pmC/DW6nJdlvpRAsNbrfZvk8mf02WJ9zS+lcN+hnDC3rysniq/bboHbe59sMf0Tj821je4z2vWp9r7HSWTqywGhvX79dt/oO+/zn5ni/Dv/xj5zuXXHZ073WLvjkObbkyvlDn9tpjf1TIHb59/6pWIjGH3p4k73zHW/1punHln71m9+bpmuCfoxp8qTxdtKJkzQ6KLmrRRVcVeBUP8bKqaBMAAAQAElEQVSkDAqm7jvQp0ESAggggAACCCCAAAIIIIAAAggEEWAZBBBAIAYCkQVG9QNGCiAqGKl2vviXl03TNPyJj37QbtvwgCl4qvGwkgKcz23dXrw6dd6iZd4zRmfNnOGtQrfYf/mqBabpuoJ1w4+7bcVXF5l+KMrLcPiPAqdPbXnO5l/4MW+Klnv/1HfZGedd7i17xcILQg/qeiviDwIIIIAAAggggEAqBWgUAggggAACCCCAQPwEIguM+ptaevu5rsBU0NQFSv15GxlWgPMH1y8pPidUV6e6oKgrV+OarqQfgdIVoW6ee1Ug9Htf/+KggKmeOapllFSGy8srAggggMAQASYggAACCCCAAAIIIIAAAgggEHuByAKjHe2jTM/i1O3qCj5OmniC6fZ0iWia5imPxpOdqD0CCCCAAAIINFsgu0+hbrY060MAAQQQQACBIwIMIYBA2gQiC4y6qzd1paXQrrlsrunWdd3Cfsvt99q1l3920BWZxj8EEEAAAQQQQKBGgVyN+ciGAAINCLAoAggggAACCCCQcoHIAqOlbrpqVLeu61b0R+9dZbpdvTQP4wgggAACCLRKgPUigAACCCCAAAIIIIAAAghkSyD0wOhLu/fa7AWLiz+ApCtEyyXlUd5sccemtVQEAQQQQAABBBBAAAEEEEAAAQTSL0ALEUCgikDogVH/laG6OrT7rhts6run2J1rlg36USRdPaq8VerGLAQQQAABBBBAAAEEEECgDgGyIoAAAggggAACtQuEHhitfdXkRAABBBBAAIGGBFgYAQQQQAABBBBAAAEEEEAgsACB0cB0LNhsAdaHAAIIIIAAAggggAACCCCAAALpF6CFCDRLgMBos6RZDwIZFchntN00GwEEEEAAAQQQqFGAbAgggAACCCDQIgECoy2CZ7UIZEUgl5WG0k4EEKhRgGwIIIAAAggggAACCCCAQDwECIzGYztQi7QK0C4EEEAAAQQQQAABBBBAAAEEEEi/AC1MpACB0URuNiqNAAIIIIAAAggggAACCLROgDUjgAACCCCQBoHQA6Mv7d5rsxcstmldC73UddHVtuX322zeomXe+LTD05VHedOASBsQQAABBBBAINUCNA4BBBBAAAEEEEAAAQRSKBB6YHRC51jbuG6l9XSvrZqUR3lTaEqTEEi4ANVHAAEEEEAAAQQQQAABBBBAAIH0C9DC0AOjkCKAAAIIIIAAAggggAACCCAQOwEqhAACCCCAQIkAgdESEEYRQAABBBBAAIE0CNAGBBBAAAEEEEAAAQQQqC5AYLS6D3MRQCAZAtQSAQQQQAABBBBAAAEEEEAgZgL5mNWH6qRCINRGEBgNlZPCEEAAAQQQQAABBBBAAAEEEAhLIHg5BKSC27Fk/QKV+luu/qJYAoGmChAYbSo3K0MAAQQQQAABBBCoKMAMBBBAAIHQBAhIhUZJQTUI0N9qQCJLLAUIjMZys1ApBBDIggBtRAABBBBAAAEEEEAAAQQQQACB1gmEGhh9afdem71gsU3rWliahowrn/K3rumsGQEEEEAAAQQQQAABBBBAAAEEQhagOAQQQCAxAqEGRid0jrWN61ZaT/daL13wyXPsS4vmecNu2hP3r7YPzXiPLblyvil/YqSoKAIIIIAAAggMEaj0PKkhGZmAQGoFaBgCCCCAAALcSE4fQCCpAiOiqriuBn1263Y76/Spg1bR3jbKLp57rt224QHr7esfNI+REAU4LoeISVEIIFAUYACBEgHebkpAGEUAAQQQQACBDArwVXEGNzpNTolAZIHRaj4TO8fZvgN9dqA33oHRam2I/TyOy7HfRFQQAQQQQAABBBBAAAEEEEAgHgLUAgEEsikQWWC0o32Ujelos8ee3DJEdufuPbZvf++Q6UxIrgBx2ORuO2qOAAIIIIAAApkToMEIIIAAAggggAACBYHIAqPulvlbbr/Xep7ZVljVwH/dYr/ipvU291NdPGN0gCQVf7mVMhWbkUYgkFIBmoUAAggggAACCCCAAAIIIIDAUIHIAqNa1ayZM+yef1hu135tVfFX6bsuutr74aVL55+vLKSwBSgPAQQQQAABBBBAAAEEEEAAAQTSL0ALEUCgYYFIA6Oq3YTOsbZx3Urr6V5bTLMKAVPNIyGAAAIIIIAAAkkV4DEySd1y1DupAtQbAQQQQAABBBAIWyDywGjYFaY8BBBAAAEEMiBAExMgwGNkErCRqCICCCCAAAIIIIAAAlUEIg2M6nmisxcsLt5GP61rYXFY0zW/St2YlRkBGooAAggggAACCCCAAAIIIIAAAukXoIUIxEsg0sDo9d/fYKdPP6V4C73/dnrdXq/b7OPFQW0QQAABBBBAAAEEEEAAgZAEKAYBBBBAAAEEYi0QWWBUV4M+u3W7fe4zn4g1AJVDAAEEEEAAgXAEKAUBBBBAAAEEEEAAAQQQSJJAZIHRJCFQVwQCCLAIAggggAACCCCAAAIIIIAAAgikX4AWplggssCobpM/5aTJ9tiTW1LMR9MQQAABBBBAAAEEEEAAgTQJ0BYEEEAAAQSyIxBZYFSEuo3+qS3PWW9fv0ZJCCCAAAIIIIBAvASoDQIIIIAAAggggAACCGRWILLAqJ4xeu3XVtlPf/aknXHe5Tata+GgNHvBYlOezMrTcARaIMAqEYheIBf9KlgDAggggAACCCCAAAIIIIBAVQFm1iYQWWBUt9JvXLfSerrXlk2apzy1VZNcCCCAAALJEMgno5rUEgEEEEAAAQTSJEBbEEAAAQQQCCQQWWC0Ym34zFyRhhkIIIAAAggggMDwAuRAAAEEEEAAAQQQQACBMAQiDYz2PLPNzp5zxaBb6KfNGrilnlvpw9h8lIFABgRoIgIIIIAAAggggAACCCCAAAIIpF+gBS2MLDCqH1y6bvUd9vnPzbE71yyzj3/kdHvi/tXebfUXfPIcW3LlfONWeuMfAggggAACCCCAAAIIIIBABgVoMgIIIIBA6wUiC4we6O23fQf67KzTp3qtfPEvL5umaeQTH/2g3bbhAVPwVOMkBBBAAAEEEEAAgVQL0DgEEEAAAQQQQAABBGInEFlg1N/SiePH2piOtuKkiZ3jvKCpC5QWZ6Rs4OCh1+1PB35r2/b/OnPpj/ufsj2vvZiyLUpzEKhVgHwIIIAAAggggAACCCCAAAIIIBB3gcYDoxVa2NE+yguGPvbkFu+W+UkTT7B7HnjEy61pCpQqjzchpX/ezB2yn+/4J/vRtr/PXPpfL1xnvYdeTemWpVkIIIAAAggggAACCCCAQAYFaDICCCCQMoHIAqPtbaPsB9cvsUvnn++RXXPZXNvw427vh5huuf1eu/byz5ryWMr/HcoftDfyr2UypXzT0jwEEEAAAQQQSLkAzUMAAQQQQAABBBBIt0BkgdFSNv3Q0sZ1K70fX3r03lU27dQppVkYRwABBBBonQBrRgABBBBAAAEEEEAAAQQQQCBTAk0LjMZLldoggAACCCCAAAIIIIAAAggggED6BWghAgggUFmAwGhlG+YggAACCCCAAAIIIJAsAWqLAAIIIIAAAgggULMAgdGaqVqbsXd73rZ822zz3xfScrOnb8zbwVfzxUq98nRhuuYdTs//o9mh147Mf+FH+YFlC/OV1y2ocp+92QaV5ebxigACCMRdgPohgAACCCCAAAIIIIAAAnYk/AEGAnUJEBiti6t1mQ/uy9n4s8ymf6WQlpq1v93shR/lisHP13aZnXhRYV5h/tS/GTgibL9/oL4Kfr7Zb6bpJy/M255f54vL7XrCbOJHzEYelxvIzF8EEEAAAQQQQAABBBBAAAEEEGilAOuuV4CQRr1i5D8sMOLwKy8xFzj+tEIA88NHKnn8aTk7+Ere3nxtYNrEwrzjC3k0dtSxORvzTl0FOhA4PbgvZyNGmWn6yDFmh17Pecu5gOnokwYCqcY/BBBAAAEEEEAAAQSaLsAKEahFIFdLJvIggAACCCBQl0CqAqO9ff12yTUrbFrXwmJ66JFNg0A07ubPXrDYXtq9tzj/1vX3FZfTsJuhPHMvW2Y9z2xzk1r+qitERx6fsxHHWtl//bvyNvK4/OFgaCGA2m/eVaIH95kddUzeW05Xi477q5wpYGr8QwABBBBojgBrQQABBBBAAIEAAlzMEQCNRRBAAAEEhhEINTCqAKKCjS7wWO1V+ZR/mPrVNftAb79NmniCPXH/auvpXms3Lf9rW7r85mJAU4HNb924zu5cs8ybP/dTXbbkG2tMAVXV5eHHN1v3XTd4ScOapgrc88AjNnvWmTbt1CkabXnSlZ4v/9rsrR/Plw1q6hmivX8qzP/YQFXbJ+e8K0a3fDtnz6/NmYKhCqzq9vr2t+VNzyPVs0u3fNtMZVuI/ygKAQQQyJRALlOtpbEIIIAAAggggAACCBQFGEAgiQKhBkYndI61jetWekFHBSYv+OQ59qVF84rjmqag5YdmvMeWXDnflD9MNJW3/G+/YO1to7xi33vqSXb8caNt5+493vhjT26xD7zv3cUA51mnT7XtO3bZ1hd22M5de2306DbraB/lJQ1rmoKjCpJ++tyZXhmt/qPA5bb1OXvrfzRTwLO0PgqKbr/X7MTPmPmfG3rihbmB55N+xUy33LurRXv/nCvky3vzJs8xe/GnA7ffl5bLOAIIIIBADQJczFIDElkQQACBVAjQCAQQQAABBBBIgcCIqNqggOKzW7ebgo/+dShoefHcc+22DQ94V2r654U9rMBmPp+3iZ3jvKKf37bde3V/Jo4fa7lczhQ41fD+/X2mq06VNKxpulr0nDOnhx7EdXWo59UFRRXAVHCzdFkXFJ0yP182aOryqxxdLapni+rKUTd95Ji86TZ7N84rAggggAACAwL8RQABBBBAAAEEEEAAAQTSJxBZYLQalQKV+w4MBCGr5Wtknm6Pv271HTbv07OKV4iqvJOnTNbLkKSrTRUA7broalPSsDK5q0WXfvNmm3b42aV6TqnmKb31hFFWKY0bfYyyhJIUzHzhn3OmoGeloOiLD+btlMuqB0VVGXe1qJ4teux4TRlIB/flvB9mGhhr/G/bMSMq2lQyc9Mnjj3Wjj66RfekNt70hksYeVTO3lIwcB71vo4aeVTDdUhyAScU9r16zVz+MPfbJBq2HXOUva2zLVB6y7hRdnSh7yax3WHUeWSh7ZMKBkH9ZB9GPZJaRueYYwL1O3mfUFg2qe0Oo97qO3IIkthvc8Z+G7wXst8Gt2t4v834eTL7bfC+x34b3K6t0c+3hXPF4GtP9pI6T47t59sE0A73+TYBTYh1FSMLjOqW9DEdbabb10sFdIXmvv29pZNDG1dQ9Mql3/WeN3rp/PMHlVt61ah/pvLqdn8lDburRXXl6f7ePu/ZpXo+6aq1dxd/tOnFl/utUtqz/3V/8Q0N79+as4OvmPeMUD0P1CVdJaqCX3k6bwdfzdnTN+bMzSv3zFCX3wVX3auW0S34zf+bLQAAEABJREFUlZ5bqnXUm/pef7OiTSUzN33n3tfsjTeye0/qwUN5+0vBwHnU+9p/8FC9mytV+V8u7Hv1mrn8Ye63SUTte/2Q/Xl3X6D0lz399kah7yax3WHUWfvtjoJBUD/Zh1GPpJaxe9/rgfqdvF8uLJvUdodRb/UdOQRJ7Ld5Y78N3gvZb4PbNbzfBjxPDl7j+CzJ+21j24L9Nrhfw59vM36ezOfb4H1vuM+3wUtmSQlEFhh1t8zfcvu9xR8/0gp1i/2Km9abfvhIV2lqWpjJHxTV80b9ZZdeLaqAp/9We39e1dNdLbpz9x7TrfWar9vrFfDVcDPTxA+b9xzQ6V8Z/OoCm/5niLo8U//GhtxSr/zK66+7xrVMufz+fAwjgAACCCCQIAGqigACCCCAAAIIIIAAAghUFYgsMKq1zpo5w+75h+V27ddWFW9D123q+uElXZGpPGEmFxTVbfClQVGtR887/dVvfl8M1Opq1smTxttJJ07S7EHJXS2q4O3EznHeDzMpg4KpegyAhkkIxEeAmiCAAAIIIIAAAgikWSC791KleavSNgQQQCCIAMuEKRBpYFQVVWBx47qVptvTXVLAVPPCTltf2GG/e/aP9p01dxYDsXouqJ4PqnVNO3WKffmqBTZv0TJv/oYfd9uKry4yXd2q+S71PLPNntrynM2/8GPeJC33/qnvsjPOu9xb9oqFF5ja5c3kDwIIIIAAAggggAACCCAQsUBmn74fsSvFI4AAAghkWyDywGgzeRXAfPTeVYOCsArG+q8eVVBW05QUsC0X4FQ53/v6FwcFTHWFq5ZRUhnNbBfrQgABBBBAAIFsCNBKBBBAAAEEEEAAAQQQaJ5ApIFR3dp+yTUrvKszz55zhXcLu5t26/r7jH8IIJBpARqPAAIIIIAAAggggAACjQjwjIVG9FgWAQSaJxDbNUUaGP3GDbeZnvf5xP2r7YwZp3kIum394rnnmn7YSEFSbyJ/EEAAAQQQQAABBBBAAAEEEEiFQBMbwTMWmojNqhBAII0CkQVGX9q9157dut30g0elcPoxI/2A0YHe/tJZjCOAAAIIIIAAAjER4NNmTRuCTAgggAACCCCAAAIIJFQgssBoNY+du/fYmI4262gfVS0b8xBAAIHYCVAhBBDIkgD3J2Zpa9NWBBBAAAEEEEAAgewJVAuMNqShHzWaPetMu271Hea/MlRXkq64ab13i71uq29oJSyMAAIIIIAAAggggAACCCCAAAKNCrA8AgggkEmByAKj0rx0/vmm54l2XXS1/fRnT9q8RctMw0uunG+apzwkBBBAAAEEEEAAAQSaK8DaEEAAAQQQQAABBBAwizQwKuBZM2dYT/faQUnTNI+EAAIIINAEAVaBAAIIIIAAAggggAACCCCAAAJDBCILjOqW+bmXLbOeZ7YNWelDj2yyS65ZYVH8Kv2QlTEBAQQQQAABBBBAAAEEEEAAAQRSJ0CDEEAAgUYFIguMVqvYxM5xtu9A36Bnj1bLzzwEEEAAAQQQQAABBDIuQPMRQAABBBBAAAEEQhZoSWD0sSe32JiONutoHxVycygOAQRSI8CPQadmUwZrCEshgAACCCCAAAIIIIAAAgggEK1A6IFR3Tp/9pwrvB9Z2vL7bd4PLk3rWmj+dMvt99q1l3/W+FX6wxuXFwQQGCqQGzqJKQgggAACCCCAAAIIIIBAogWoPAJxFcjoxUmhB0annTrFHr13lXXfdYNNffcUu3PNskE/vNTTvdabr3xx7QvUCwEEEEAAAQQQQAABBBoXoAQEEEAAAQQQSIhARi9OCj0w6jb3hM6xtuH7y4wAqBPhFQEEEEAg5QI0DwEEEEAAAQQQQAABBBBAIEECkQVGE2RAVQMJsBACCCCAAAIIIIAAAggggAACCKRfgBYikF6BSAOjL+3ea7MXLB70fFH3rFFN1/z00tIyBBBAAIG4CGT0cTlx4aceCGRagONPAjc/VUYAAQQQQACBzAhEGhi9/vsb7PTppwx5xqieM7px3UrT7faZkaahCCCAAAItE8jo43Jq8i7NRBCnVCT542zT1m5Djj+t9WftCCBQIsBBqQSEUQQQyLpAZIFRXQ367Nbt9rnPfCLrxrQ/PgLUBAEEEEBgGAE+Lw0DlMDZbNMEbjSqjEAmBDg6tWQz821ZS9hZaUsEWCkCNQlEFhitae1kQgABBBBAAAEEEEAAAQQQaFAgiYsToUviVqPOCCCAQNoEIguM6jb5U06abI89uSVtZrQHAQQQQAABBFopwLoRQAABBBBAAAEEEEAAgRAEIguMqm66jf6pLc9Zb1+/RkkIIBBAgEUQQAABBBBAAAEEEEAAAQQQQCD9ArSw+QKRBUb1jNFrv7bKfvqzJ+2M8y63aV0LB6XZCxab8jS/yawRAQQQQAABBBBAAIGMC3AXc8Y7QCyaTyUQQAABBBBouUBkgVHdSr9x3Urr6V5bNmme8rRcgAoggAACCCCAAAKRC7ACBGImwO/exGyDUB0EEEAAAQQQaIVAZIHRVjSGdSKAQEwEqAYCCCCAAAIIIIAAAggggAACCKRfIOEtjDQwqmeLXnLNCu8W+rPnXGE9z2zznjeqabeuv8/4hwACCCCAAAIIIIAAAggggEBSBKgnAggggEC6BCINjH7jhtvsnDOn2xP3r7YzZpzmybW3jbKL555rDz++2QuSehP5gwACCCCAAAIIIBA3AeqDAAIIIIAAAggggECqBSILjOqHlZ7dut3OOn3qEMCJneNs34E+O9DbP2QeExBAAIHWCLBWBBBAAAEEEibADyglbINRXQQQQAABBBCIh8CRWkQWGD2yiqFDO3fvsTEdbdbRPmroTKYggAACCCCAAAIIIIDA8AL8gNLwRuRAAAEzDBBAAAEEKgpEFhid0DnWZs86065bfcegK0N1JemKm9Z7t9jrtvqKNWMGAggggAACCCCAAAJ1CpAdAQQQQAABBBBAAIFaBSILjKoCl84/33ueaNdFV9tPf/akzVu0zDS85Mr5pnnKQ0IAAQQQCCzAgggggAACCCCAAAIIIIAAAgggEFAg0sCo6jRr5gzr6V47KGma5tWXyI0AAggggAACCCCAAAIIIIAAAukXoIWVBXiOSmUb5iBQv0DkgdH6q8QSCCCAAAIIIIAAAvEU4MNYJNuFQhFAAAEEEKhZgF/eq5mKjAjUIEBgtAYksiCAAAIIhCdASQggkGSBZH0YS1Ztk9wvqDsCCCCAAAIIIJBMgUgDoz3PbLOz51xh07oWDkmzFyw2/RBTMtlqrjUZEUAAAQQQQAABBFokwPWtLYJntQgggEA2BWg1AggkUCCywGhvX79dt/oO+/zn5gx6vqh73ujGdSttQufYBJJRZQQQQAABBBBAAAEEsi5A+xFAAAEEEEAAgeQLRBYYPdDbb/sO9NlZp09NvhItQAABBBDItgCtRwABBBBAAAEEEEAAAQQQSJ1AZIHRjvZRNqajzXbu3pM6tLQ3iPYhgAACCCCAAAIIIIAAAggggED6BWghAlkXiCww2t42ys45c7rdtuEB0231WYem/QgggAACCCCAAAIIINBSAVaOAAIIIIAAAggMEogsMKq16Db63z37RzvjvMv58SWBkBBAAAEEEGiaACtCAAEEEEAAAQQQQAABBBCoJhBZYFRXifLjS9XomReqAIUhgAACCCCAAAIIIIAAAggggED6BVrawlxL187KwxeILDDKjy+Fv7EoEQEEEEAAAQQQQAABBLIlQGsRQAABBOIkkI9TZahLCAKRBUb58aUQtg5FIIAAAgggkC0BWosAAggggAACCCCAAAIINE0gssAoP77UtG3IihIrQMURQAABBBBAAAEEEEAAAQQQQCD9ArQwrgKRBUZf2r3XNvy4236x6Xf8+FJctz71QgABBBBAAAEEEEAAAQTCFqA8BBBAAAEEEiIQWWB0QudY27hupfV0ry2bNE95EuJENRFAIKAAT2AJCMdiCCCQGAEqigACCCCAAAJlBPggUAaFSQggEDeByAKjcWso9UEAgVAE6i6E3+yrm4wFEEAAAQQQQAABBBBIvgAfBJK/DWlB1gUy0f7IAqO6lX72gsU2rWth2aR5ypMJZRqJAAIIIIAAAggggAACCCAQYwGqhgACCCCQRYHIAqO6TV63y5feSv/E/avt4x853a77uytMebKITpsRQAABBBBAAIGWCrByBBBAAAEEEEAAAQQQsMgCo5Vs29tG2funvstu/+GDlbIwHYEECnCfSJw3GnVDAAEEEEAAAQTSJ8D5Z/q2KS1CAIF4CnC8jed2KV+reqc2PTCqCp51+lR7dut2i+RW+sMPeF76zZvt1vX3aXWD0kOPbCre2l96O7/yu1v/NewWVD3nXrbMep7Z5ibxikCJwOGOVzKVUQQQQAABBBBAAAEEohHg/DMa10SVSmURQKApAhxvm8LcopW0JDAaZVtv/f/u8wKfd//k4SGrUWDzWzeuszvXFIKc3Wtt7qe6bMk31lhvX78XpH348c3WfdcNXtKwAqIq5J4HHrHZs860aadO0SgJAQQQQAABBBBAoOkCrBABBBBAAAEEEEAAgXAFWhIY1W30p5w0OZJnjF46/3zTc00v+OQ5Q6Qee3KLfeB97y4GOHXl6vYdu2zrCzts5669Nnp0m3W0j/KShjVNwVEFST997swh5TEBAQQQiEyAghFAAAEEEEAAAQQQQAABBBBAIFKByAKjCijqVnV3a7r/dcfOl+2rV19cbFizBp7ftn3QqiaOH2u5XM527t5jGt6/v88O9PZ7ScOapqtFzzlzeiRB3EGVYQQBBBBAAAEEEEAAAQQQQACBlAvQPAQQQCBOApEFRid0jrWN61Z6V2/qCk5/+sH1S0w/wtQKiJOnTC67WtVXAdCui642JQ0ro7taVM8snda10JT0nFLNUxp/3LFWKY1pG6ksmU3HjhxR0aaSmZs+bvQxdtRR2X3A8dEjcnZCwcB51Pt67NFHZbbfqeHHFfa9es1cfvbbEQ3tt+q72gZZTGo7+23wLc9+G9yu0fdb9d3ga0/2kmp7xPttsoGGqT377TBAVWY3ut9ynnxM4PMVzpNHBrbjPJnz5CqHtaqzeL+tyjPszOHeb4ctgAxVBSILjGqtCiZecs0K7xmeGlfS8zw1zf/jRprerFR61ah/ve42fAVxNeyuFtUt9ft7++yJ+1d7zyddtfZu75mkWvbVvoNWKfUdfENZMpsOvpGvaFPJzE3f33/Q3nwzuw84fjOfNxk4j3pfDx56M7P9Tg3ve/2NwH2P/baR/fagHWK/Ddz32G/fCGzHfst+q2N/kMT7bRC1I8vwfnvEot4hzpPrFTuSn/32iEWQIfbbIGoDyzS633KeXDl2MtznXc6Tq58nD/RQ/gYViCwwqgCobpm/eO65g64O1ZWimqYrMZUnaMWDLFd6tagCnvlCAGpi57ghxelRAKqjni2qW+11a70y6fb6MR1tZhoppMpSlRcAABAASURBVNcPvmmV0huFwGAhS2b/66Slks1w0/WmU9g0GbYze73Qf4ZzqjRf9pnFKzT84KF8xf2ykpmbzn4b3M7bbwv+Wf2vmDD7bfCtz34b3E7HfHcMq/eV/Zb32+A9z4z9Nrhew/ttdq8fMN5vg/c7Lcl+K4UAqbBIw/ttoYys/me/bWzLD7ffNlY6S0cWGNWzOvcd6LNyQUdN0zzlaeYm0I8t/eo3v7eeZ7Z5q9WPMU2eNN5OOnGSN+7/464W1S32qq9+jEnzFUxV3TVMQgABBBBAAAEEEEAgbQK0BwEEEEAAAQQQyIpAZIHRjvZRpisrdbVlKaamaZ7ylM5rdFy36Os5oHf/5GH7zpo77ew5VxQDodNOnWJfvmqBzVu0zHtW6IYfd9uKry4adEWrFf4pcPrUluds/oUfK4yZabn3T32XnXHe5d6yVyy8wBQw9WbyBwEEEEAgyQLUHQEEEEAAAQQQQAABBBBAIKMCkQVG3S3zS5ffXAxMylhBR03Tjxspj6aFmfRs0J7utcUffXr03lVeYNOtY9bMGcV5+nGocgFOBUK/9/UvDgqY+stVGa68ZL1SWwQQQAABBBBAAAEEEEAAAQQQSL8ALUQAgVoEIguMauUKIN5y3WL7/LUrvSs0dSWnrtZcvvQLpkCj8pAQQAABBBBAAAEEsimQ4cckZnODR9lqykYAAQQQQAABBAIIRBoYVX109aWu2vRfxamAqeaREEAAAQQQQKB+AZZAIC0CubQ0hHYggAACCCCAAAIIJFIg8sDoQ49sKl4tqitGlTQtkVpUuhUCrBMBBBBAAAEEEEAAAQQQQAABBNIvQAsRaLpApIFRBUBX3LTeuu+6ofhczzvXLDM9Y1Q/ktT01rJCBBBAAAEEEEAAAQQQQCAWAlQCAQQQQAABBFotEFlgtLev327b8IAtuXK++X/gSLfW6xmjDz++2ZSn1QCsHwEEkirADZhJ3XLUO6MCNBsBBBBAAAEEEEAAAQQQiJlAZIHRA739tu9An03sHDekyZqmecozZCYTEEiBAE1ohgA/2dEMZdaBAAIIIIAAAggggAACCCBQWYA5yRaILDDa0T7KxnS02c7de4YIaZrmKc+QmUxAAAEEEEAAAQQQQAABBBCIowB1QgABBBBAIFUCkQVG29tG2TlnTjc9Y/Sl3XuLaD3PbPOeMap5ylOcwQACCGRcgFvjM94BaD4CMRSgSggggAACCCCAAAIIIJBmgcgCo0K7dP753jNGuy662qZ1LfTSvEXLTM8Y1TzlISGAQEwEWl4Nbo1v+SagAggggAACCCCAAAIIIIAAAukXoIVFgUgDo1rLrJkzrKd77aCkaZpHQgABBBBAAAEEEEAAgeYJxOprSG4Wad6Gz/iaaD4CnkCsDoBejfiDAAIxEIg8MBqDNlIFBBBAAAEEEEAgKwK0E4GqArGKRRKkqLqtmIkAAiELxOoAGHLbKA4BBAILRBoYfeiRTd7t8+42+rPnXGF6xqjxDwEEEAhFgEIQQAABBBBAAAEEEEAAAQQQQCD9AtG0MLLA6NJv3uz98FL3XTcUb6O/5x+W27VfW2WaF01zKBUBBBBAAAEEEEAAAQQQQACBhAtQfQQQqEOAy4HrwCJriUAkgVFdKfrk5mftthuX2oTOscVValjTNE95ijMYQAABBBBAAAEEEMisAA1HAAEEEEAAAQSCC/BsluB2LBlJYPTBf/ulzf1U16CgqKNWcFTzlMdN4xUBBBDIkABNRQABBBBAAAEEEEAAAQQQQACBGAiEHhjt7eu3HTtftne+461mVr6Fmqc8yls+B1MRQAABBBBAAAEEEEAAAQQQQCA5AvXWlNuf6xUjPwIIhC8QemD0QG+/7TvQZxM7x1WsreYpj/JWzMQMBBBAAAEEEEAgBgL5GNSBKsRQgCohgAACCDQowDtsg4AsjgACIQiEHhgNoU4UgQACCCAQMwGqg0CWBbieJctbn7YjgAACCCCAAAIIpFmAwOjQrcsUBBBAAAEEEIiVAKHJWG0OKoMAAggggEB6BGgJAghkXCCSwOi+/b02b9Eym9a1sGzSPOXJuD3NRwABBBBAAIGaBLjVriYmMiEwrAAZEEAAAQQQQAABBPwCoQdGJ3SOtY3rVlpP99qqSXmU118ZhhFAAAEEEAhNgIIQQAABBBBAAAEEEEAAAQQQqCIQemC0yrqYFaEARSOAAAIIIIAAAggggAACCCCAQPoFaCECCIQnQGA0PEtKQgABBBBAAAEEEEAAgXAFKA0BBBBAAAEEEIhMgMBoZLQUjAACCCCAQL0C5EcAAQQQQAABBBBAAAEEEGiWAIHRZkmznqECTEEAAQQQQAABBBBAAAEEEEAAgfQL0EIEYipAYDSmG4ZqIYAAAggggAACCCCAQDIFqDUCCCCAAAIIJEOAwGgythO1RAABBBBAIK4C1AsBBBBAAAEEEEAAAQQQSKQAgdFEbjYq3ToB1owAAggggAACCCCAAAIIIIAAAukXoIVZECAwmoWtTBsRQAABBBBAAAEEEEAAgWoCzEMAAQQQQCCDAgRGM7jRaTICCCCAAAJZF6D9CCCAAAIIIIAAAggggACBUfoAAukXoIUIIIAAAggggAACCCCAQBMFck1cF6tCAAGfAIN1ChAYrROM7AgggAACCKRfgA8z6d/GtBABBBBIgwBtiK9APr5Vo2YIIICAT4DAqA+DQQQQQAABBBCQAB9mpBC7RIUQQAABBBBAAAEEEEAgVAECo6FyUhgCCIQlQDkIIIAAAggggAACCCCAAAIIIJB+gVa2kMBoK/VZd3WBHLdyVgdiLgIIIIAAAggggAACCCRMgOoigEDoAsQOQifNUIEERjO0sWkqAggggAACCCDQXAHWhgACCCCAAAIIRC3AY6CiFk5z+QRG07x1aRsCCDRXgLXFR4Bzo/hsC2qCAAIIIIAAAggggAACCMRUIHBgNKbtoVoIIIAAAgiYcTeN8Q8BBBAYToDvkIYTYj4CCDgBXhFAAIG0ChAYTeuWpV0IIIAAAggg0EIBovMtxG901ZlZnl6amU1NQxFAAAEEEECgggCB0QowTM6WAFdMZGt701q/AMMIIBCNAO8s0bhSamsECKG2xp21IoAAAggggEDUAtkKjEatSfmJFeB0P7GbjoojgAACCCCAQOQCBPojJ2YFCCAQvgAlIoAAAjUIEBitAYksCCCAAAIIIIAAAgjEWYC6IYAAAggggAACCNQvQGC0fjOWQAABBBBorQBrRwABBBBAAAEEEEAAAQQQQKBhAQKjDRNGXQDlI4AAAggggAACCCCAAAIIIIBA+gVoIQIINFuAwGizxVkfAggggAACCCCAAAIImGGAAAIIIIAAAgi0WIDAaIs3AKtHAAEEEMiGAK1EAAEEEEAAAQQQQAABBBCIlwCB0Xhtj7TUhnYggAACCCCAAAIIIIAAAggggED6BWghAokWIDCa6M1H5RFAAAEEEEAAAQQQQKB5AjFZUy4Xk4pQDQQQQAABBJItkLnA6EOPbLJpXQu9NHvBYntp997iFrx1/X3edM3XsJuhPHMvW2Y9z2xzk3hFAAEEEEAg/QK0EAEEEEAAAQQQQAABBBBIsUCmAqMKbH7rxnV255pCkLN7rc39VJct+cYa6+3r9wKkDz++2brvusFLGlZAVNv+ngcesdmzzrRpp07RKCmlAjQLAQQQQAABBBBAAAEEEEAAAQTSL0ALEXACmQqMPvbkFvvA+95dDHCedfpU275jl219YYft3LXXRo9us472UV7SsKYpOKog6afPnenMeEUAAQQQQAABBBBAAAEEkiJAPRFAAAEEEECggkCmAqPPb9s+iGHi+LGWy+Vs5+49puH9+/vsQG+/lzSsabpa9Jwzp9uEzrGDlmUEAQQQQAABBOIoQJ0QQAABBBBAAAEEEEAAgdoEMhUYFcnJUybrZUhS4FMB0K6LrjYlDSuTu1p06TdvtmmHn02q55RqntLbOtusUjphzDH2lraT7e0d701HGl17OyZ3TLWOY4+taFPJzE1/y7hRNvqY49PhFmD7jym0fVLBwHlUfK3Q/zqOOca0DVLT9+owfEvbO62zsO/Va+byp26/rcNOfYb9tvbjXOn+xX4b3C6S/baO96zSbZmkcfbb4P1O25n9NrhfJPttHe9Z2n5JTey3wfudtjn7bXA/9tvgduy3we3YbxuzG7TfVvj8r9gUKbhA5gKjpVeN+ukunX++9XSv9ZKG3dWiuqV+f2+fPXH/au/5pKvW3u09k9S/bLnh40eNtv/yvmvtmjOuT0f6YO3tuOoD37KpE99TjqWmaUeNyNnHTzo/HW4Btv+sk84zGdSEVSbT1LdMsy9+YEUm/bTPHVfY98qw1DQpdfttHf2P/bb2Y1y543r29tvvhHaMiWS/reM9q9z2TMo09lv221b11Uj22zres1rV7jDWy35b235byTp777eNefkd2W+DW7LfBrdTH2S/De7X6H5b04fgjGfKVGC09GpRBTzz+bxN7Bw3pBv4ny2qW+11a70y6fb6MR1tGiQhgAACCCCQYYFchtseetMpEAEEEEAAAQQQQAABBFogkKnAqH5s6Ve/+b31PLPNo9aPMU2eNN5OOnGSN+7/464W1S32CpyOHj0QDFUwdd+BPn9WhhFAoC4BMiOAAAIIIIAAAggggAACCCCAQPoF4t/CTAVGp506xb581QKbt2iZ97zQDT/uthVfXWTtbaMGbSkFTp/a8pzNv/Bj3nQt9/6p77IzzrvcW/aKhRfE+seYbl1/n11yzQrr7ev36h/GH5WlMlW2ytNzVmcvWFzTIwWUv9WptP711kd94pPz/2sxqF7v8uRHAAEE4iSg52YrlatTPcd3jo3lBNM/rdH31FIh9UWl0umMp1tA55Q6t1R/Km1p3I8t6q9KpfVmPBwB2SqFU1qTS6mwurj36QrVTvzkes5pktbY4fpUtWNs0trarPr6+0upr45JSs2qC+tprkCmAqOinTVzhvcMUT1LdOO6lWUDnAqEfu/rXxwUMNUzR7WMkspQWY0m7XjuB53cKztbY6o6gJ095wov8O1M5dxYqcleWm+KzsK90s/C26blfLPe5/y6+sCrD75y8k9XH9R0zfdPLx3WcrXk03L15FX+NCT1tSR9SRWVufqR+ok7xulVfSyq9VUrV/1Q6/cnbScto3mqp+qr8eFSvfmHK6+e+aqj6upvR6mpK69cPZVXyeXJ4qtc/H4adn2hWR6qg7ajtmez1ulfj/qA2u2SztF0rubPw3BwAT36S+8Bzlev/u0tf6V61qA+qnL8KY3bTS6V2ljvfqP9S+5artRa61Eqnd7sce13zb7IQ+32G/uH5SW3ZjvEeX1uf9Y+6OqpYe3jmuemybVcX3PzeT0iUMlPhi6XbOdetowLoBxIRl8zFxiN23Z++9smWvddN3jBWr0+uflZ0w4ct3omoT5y09XAy5d+wfNUEFumD/7bLxu+elZjnmgFAAAQAElEQVTB8p+s/x+m1yRYlNbxQzPe4/14mEz0I2I7dr4c+lXFpetM2fiQ5uhkTid1Dz++uWgrX/W52zY8kJirqYc0rAkT3MnID65fMugLqCasmlXUIKAv/yp9cVjD4i3N8qVF87zjvzvOub7WrErpfUh3o+g4oOOB0p1rltmjv+xpVhVCX085U91po/1XXxqHvsKUFJjGvlDvptEHd51vaH/UvqCkczQ9ymq4snS+leTzruHaF8Z8nYcs+cYam/upLu+4J1+ld5002ba+sKOhVfg/n6jMR+9d1dRz4OV/+wVTaqgRVRZupG+WK1bHxHPOnG46J9R2cXk0rH3gEx/9oOeXtT6tbaj+o3TBJ88xJQ0r6T1Ebs6KV/Mu2Dp9+in2hz++WOTQ59hXXt1vepyfJiqIp3jBO9/x1kz2KRnUk9576kk2ZnT7ED/tl9o/VdZvn9lq+/b3mn5LJsnnwGoLKbhAmcBo8MJYsjGBjvZR9ra3dBYPhqXf7GnnVSBGJ9tuTXpjd9++lX6b5M/jvulVfpXxxf/ne8WrKv3laRnlcWUqr9ar6XFOqqOCUfoApwOaq6ueEas35dI3Xr2pyKtcO537d2+5yzNSvp//YrOVfsuqD9xueQ27dcpPbtWMXd6mvfp+I0UWNy3/a2/V63/0r96rq7McNUEG+uZMThpXUhtde/WqNip/Lcsqj5ZRcsupTK1HfVPTlbQOTVd+5atmqDxaRkl5VRct26z0i02/sz//ZfeQx3Goz+lkT6+qi9qkOiqprWqzpstWfUv9TNM1398OtU/jlQzc8lpOyb8fa51aTstrnsp369W6W5nULq1f+6VeXTtK6698qvMtt99rstajTOT19LN/NL2qXS6pfff85BErzauytQ55uLwa1jQlrcONq//Iy9VD63b7gPJpnkxdOS6fyolrcm1ydVY7/HXd39vnfUGi+TJUmzVfbZOx89M0OSmfS/JQ+Zqn9C8/+5V3vNR85dW0ViYd5y6ee665E1+1RW1S/ZTURtXPTQ+6H6oMf9IHGH2ocfu/5inAs/SL/6d3JUK5Pip3+ateSs5P08vlV5nalsqrVLotND+K5Dfd9fJer++oHuXq+aOf/Nzu/snDXvLXUfk17pLbDqqvtpXbRvJQuZquV//7r/qd2uyWlZf2TU1TuVqHltOrxl1S2dremteMVK0vuPWrPqqXq6Pq7Ka5Puks1E6Xz01TOaX5lUcWcpJdpT7kL0/DKktJddDyMlVZSs5a82tNWr+CRAoWqe+45XSOVhpQ//Ly7xePH25dqrt/u1erVzUDt14tr7YoqX2qn+ZpusYrtVfztYxLrn5aNmifVZn+dTp/TXfr0av6htqmdZVLCn5u37HL9BsK/vk63ui4o7qW2w/9eesdVh1L665tpT6pOiu59qjs0vyar3ppnkvKo+lKrs0qQ8nl0bDmK2ldWqebV++rtn21vqmyK+031dal7aDtoe3i8mlYv02h4IzK9fdptUn9Tp7l2qVtLw/NU5KTylX93TL+6ZpXqUwtc93qO+zfX3zJeyyclhu8HbR085PapLooqU2qp2qh6ToHU9I8JdVX7dOwksaVV0nTq1kqj0tah9alMpS0LjcvDq8nT5lsz2/b7lVFddXAp86dae4LJQVIFegr16eUVxZql9J31typScVU2qecoZvu3ne0rIzc+lWA8mq6kvqlltF016+1bOk8zW91UnxlTEeb7dy9x6uK/HSeNnp0W/ELJAWiNU3nbmqnv33eQhX+yNqfV31JBkp+P1kpn6Yr+edVKJrJLRAgMNoC9EqrPNDbb3rz1BtrpTz+6dr5/Fem/Pf/eolpZ/fn0c6tPPf8w3LvWyXNU5DhP533Ee/bZQXIVty0vnh1W2mZkyaeYC54pmXjmnTioZORWu30zdCSK+d7BrqyRwEufztf3XfA/vLSy958XTk1buyYQU2Xk06IdRWEkoZ1cHSZqhm7PE19zQ9emz6k6MOKTgz9b3qDcx0ZU3v17aSs9C2vAtBH5lYf0rLqg25Z16e0Xp2k6eoRlSnHt0w4oXh1bzXDSmVWr0m4c8t96C1dg94I1V61T2nWOTNMbVbbXd6nep6zn274jnfVqab5+2ElAy3vv0pEV6QtXX7zoKvNn9j0tF17+We9Pvz5z80Zsl6tq9lJxyP1ua9efXFNq9YHO9XdXfGsffG0U95hepWnkq4+kOunPznTSvPqBEd9Rfun+peSht2+qm/bNS5PHUN+Vwi6aruqcjqB0omUTqg0XmlbaF4ck9p05dLvmut/2v82PvS4F5xz9a21j8iw2v7vP15qPcqrbe3W06pXnehq3bt277WLr1pevKpK+8uqtXcX3/eUJ8h+qOVKkz7QKBBRrv3l+rP66G+f/oPdct1ib19V3R56eJO3L1fKr+1R7phaWpcoxp2pv+xy9bzwkx/2rgzS/qn9VF8WaR9TH1Qf0TS1dedLAx9UVJ7eh2+7cannoH259FipPJWSvy8r6CZ/BTa0Dq1L5zrFZZs0UK0vqAp6f/D3Sx2fRhe+INc8JdcndaWermJx+7Lao2NeqY/Lr3K0vN5Lym0b9Tn1IR37lFdJw+64qGXDON7pPEN11nbQB2eVWy7Vs67h8pYz0DrV3mr7TKVyVe+o+qx/nfqiMEifVb/I5XIV398VhNY+qKR+o/1Q20UmjaTSulc6hrl1+PNrX6z2uaPSZxn1UfVVtUPnjXqPduXX+yqDan2z0n4z3HpOOnGSTZ40vhjAUn4Fs045abJ3JaDGS5P/2OU/7lU6PgR9b9d6dU74H946wdxxUf1D01uVhtsv//3PO23ZtQu99wR97tA5ja68VR/QuC6IkYerfyVLN1+vyq9ytP1Vjt6PtI9rX9f8OCR9ln1263bvHEXvm/oS+31TTzYXLFXf95+f+ussU52DqV1qn5zc/NI+pX5Q67mQjk/6nKFlVK6uUr/++xtc0eY/D9Q5ut5nijNbPKD9XZ953fm99km9P49uPxIsla2m1VNVWeu49MNb/7u3f2u80vuMrGQmO6W/eu+7THGfetZH3ugFCIxGb1x1DX8qHPS7LrrapnUtNL3qTaDqAodn6sCuAIN2MnfwOXPGacXgp7L9a+HDlU4+9EHD5dF0BRmUNDyxc5x3ebmGy5WpNyCtR/OUJ87puDEd3iXwVsM/nQwoKats9C2RDooaV1JZn/vMJzQ4JMlCJjrI6mCrpCuT9EakNx0tIF8lDfuNNR6XpKBQLXVx7fX3tVqWU55yy7o+pWCFPgi7D9py/OvPX1S8tVp+SirHb1itTM1T/mYl/5uo3hC1HyvpW0H1BfWtL156UbE6arva7H8zVN9R25V0olbMXBhQ+5UKg+Y30ImS/4sAncTrg7J701d+jWu6hmvd1sobVdIP2umkyrU3jPXIXPvdNZfNLVuc+kO1fVXftuvLKHnqREnfyOskR9tO/dLt4ypc20FJw/5tofE4JrVJfcQdx9QX9eFM7XT1raWPOMNq+7//eKlAsu58cOto1au2oU5QtQ2ff2HglrRPnzvTq44+vOpDhb4g8yYU/rh+Wc9+WFhsyH8F5fRBRB+8dCxQcseDIZkPT/jsBR8rvnerbu8pBP/V/w7PHvRSbnvouKJ+rnmDMoc84jeVU73F68OcznHcF7g6Pqntrhy9D6ufalwfDNV/1Y81Plzy92Xl1bGwdJqm+26e0Gikabi+4Pqf65cy9Xu4PqlKyqWR9xKV4ZL6ifqL9g2tU0nr0rFU21j5dKxT0nAjxzsF/LQd9Jgj7QtKpVfKaD1KtaxL+ZSUV8dvvTpHDasdao+S2qd26upmvfqPYaX7jMpUUhn+9kbZZ7U+Ja1TqVKf1bxKSf1C5/g6r9BdFfJV0ntjpWVqne7/fFJapuqt5MpSv9X+rPFyxzDlVdJ8v6/ri/5tU/pZRsvoeKg2unMnnb8raV7QVEvfrLds9Tv1QfU3tU1Jw+pvlcrS/uHs/Odqrl+XHh90TNSxsdH39kr1adZ0Z+Pf9nKSl+apHnovVH/SsGz0eAe332vc3yeUx29Z6T2kFj+V1cqkLzy0fr1X6hikH4DW/uPOT3Ws0PFN/U35XJKb/Pymbp5eS/uUbGs9F9I6S31d8FZl+88DNR63pP4iPxnpwif1D/U3tUvve2qLptVabx1jZa0verQdVK7G/fYqX9P0HqR1++MMej/X8bvW9ZGvOQJpCYw2RyuCtegg777V0TcI+hb02q+t8r4lqmV12tHL5dO3s+6Ksnp3PF12r5MgJX24K1d+HKfp2yq9idRaN10doTYq6QqfWpdz+fz2/hM9Nz/urzrRrKeO/vbWs5zylutT4zvH2nV/d4V3+7O2gZK+kVT+WlK5MmtZLsw8/jc5fQjWPqw3Sf861Ca1TSnM/UknIe7kSevzB2k1Hre0f3+ffeXqi03B0TC+mVcZd97zkNeHhjvG+fuuf19VEE8nhTrx1InSBZ/8sHeFpU4etW39y8XNs5b66JjoD0gEOc659STFwh0X9EWjTlC1X6oN/g/5CiDoPVLTo0hap44FSrrCSYFivR/rxLnc+jRdwSIdI2qtm2unlgnzuFKufm5dpabl8labpkCGrohyfbJawFjHNh3jvPICRjPLHRNLbp7wio/yz3B9QX1Dx6Fa6hD2e4l/n/YfF2upSz15FIDSvqCk810FM75xw231FFE2r9zkV3ZmYaK/fYVRc/24nn0mcJ/VCgOkcn12uGL0/qcrtOSrpHMQtVX9Zbhlq80v/Xyivlwpf5BjmL+s0m3ln6dhrVtfnOgYpO2n46XWqXmNpCj6pgJ37gtXBeF0u66CWkHqqf6tfl66bJjv7aVlN3tcfVXbVCnAe1nF6g56DynJFXc/7dPui2wF7rR/qB+oL6lPKcimaSXNKo5Wm9fIuZDOIbWdlPQ+rmdyFlca8wG3X+rc77mt270LqfS+p6txZarqq8/odbgkB/VbfQmioKg/v6bLR8n1Z+VZ8dVFpi8fNV1JgVXjX+wECIzGbJNoxx3je0DwcNWrFNzSCc3/uu1b3kPA6z050kmVTq5cCuvWm+Ha0sh8fetVevtKtfIUFNUbiz60qp26zaha/nLz/PYKrCTpDUInlPoWq9w3juXaqmn+9mq8nlSpT+lbct0mqG2gPLrCWd/c1VK28ms5l5rdT/VNoN7kqtVX+54Cge7WE9W5tG0BP/ObTuz8XwQokFdadpzG1dfm/Mezvdvd6/nyp1wbZK4yvnzVguKVduXyuWn+vuvfV3Wyonrph3H2H+gzHUe0XXV7lo4POh67MpL4+h98P+7n9hN9wAzSFr9hkOWbtYyu1izXVn0wdcd7N19Bj6jrpT6mk2cFg9zVTv516lisk2ddLa56qY6qqz9PuWEdS5TfpSiPf5VMy9VruGnqf67OCnTo9rJyy+jYpmOcNy9gNDNux8RyfaFSv/Da7fvz0CObvC+Vqr2X+LLXNOjfp/3HxZoWDphJH/j1Ipb4OAAAEABJREFUhYWOr+r7AYvxFtP+JD9vpMwff/s0O+g+E6jPaoUBUhh9VscPpdL2B6hOTYtoOwY5hvkLr6WuLoipY6SW1aMi9BpWCqtvqhwX1NIdGrraT/t+kHqqf6ufly4b5nt7adnNHg+6Xw5Xz0HvISWZk+CnL0l0p5WqrnNR9SH1pX/52S81yTTNGyjzp9r+pGOD9iH3PqzXWs+F/OcCWk5fyKi/l6lC7CYpsKwLIX6z5Q+mH6dTvXXOr4o++qse0z6raRofLslQMRY9hkAXafjzV+rPKltectP7uC7sKF3WXw7DrREgMNoa94pr1ZVKCrDpWwulXC5nOmHVAvqWQ0nDOkDqA71uFVSQQNPuuPtfi8+P07eMWl7fUCjYpACN8lRLrkzld2XqhEcPU9ZrtWVbPU9114dPfVPjb6vaoSBoufrrg6iW0zydpNfaBi3jt9fyCqToQ54OfLWW06p8qq9OYrX++Rd+TC+mbxf9J2C3//BBUz/UTNdeBVK1rJKGNU+plmXL9akX/n2Hfe/Wu1REXcnVp1yZqltdhTWQWW+M2s+qXQmm4o8/brT3zaSGy52sBPnMrzdzfRGg7aRy9eaq5xIqqKfxOCd9yNS+4tx0siJHZ9PzzDZTW1wbSvuXpiuYojJKT+ZK87q+4o6T6h+l+6qWuf2H/2I6CVV+nWxqX9B6VDe9JjGpj+gkUFau/uonep9w47W8ykTHO+3z8lPScC3LxiWP26b+D9J6n1AKu456vyktV1d8qL/q/UH9Tf2r9MOu+p/qoumar2Gl0vxue7T6+Ke6+VNpPTVPbdJ7q/qMxuWipOHhko5tH3jfu70vPnQuk8uVPxeqVI6Ohf4vrrQNKuWNavpwfUH9Uuu+54FH9OLdKVTtPXG49xKvkDJ/SreN60PVjotliql7kra7fgxFxx23sKbp+KFjiurhpgd5lZveO/ReXLq8zv3UPp0Xjj9hrGl9QfYZ9Vel0vLLjbeiz8pWxnJ1ddLVT7rV2t0WWrofKp+uVqp2xbby1Ju0Hi1TegzTtEpJfUDbRttK20z59B6ldmnYpXLT3Lwgr/KSm389mubvm6X7jdZTq5uOP3pupcpz20HL15MqHR8aeW8vPZbWU5+w87ptH2S/rKUu/v3Rn78RP385UQ+r3+iZqXoPdeei6pM6X9W63TQNu+RM1e/Un5U07OarT+n8Isi5kPp06fOi9X7l9lu3jri+Opvv/9OPTb9noXpqmp4zqmnu+KXpwyXFD6a8fZL3/NsvLfufXuxFZelYVq4/61b6JMRShmt3FuYTGG3hVtaq/Ze069Jq7VB6XpA+QCktuXK+KYilef98/8/MfwLoAgzu1pL/946NxQCMylZSGbpdWVet1XJypzL1bb4rU7f1je5oKz73UWXGNSlIom9h1FZ5KakdOpjrgOWv9+c+8wkv+KI8H5/7JdNJpNXxT076oKvyZaSDpL7NrqOIpmZVQF31VHv1qvr6rzCSnWuP8uhNQ1cuu0q6AKqWldfo0W1ulg23rKzK9SndSv/r3z7nPV9X69R2U19Vny0WXmGgUpml27nC4qFM1rpkqDdCuagNSv59WPurPripn2je/f/6i9DWrS899MFf5eqWFj2GQ9silBVEXIj78aXPXPrfvIeP6wcBdMKltugHRc6YcVqxBn5DfZD7+S82e/uubmVRfqWz51zhnZiU5tUJm/qK69vaTur7/n1VJ4pT3z3FdBJqhX/qf8qv7aptXJgU+/+l7yPy0IdjfXOtk2oZKX3+2pX23tPeWXd7yu3/ckyKj7ap3lf14VsOStpPte3rxhhmAb3fuPdsrUdJi7g+V9pHFURQ8EZf6invp//LUsvn81rES6X5XZ8ud0xt5fYoV089G08fwrTf6dbX4zravase1U4l9U13LFBj/fu0f562X7VzIS1bmnQs1H7sjr2ar2NxuQ+TmhdFGq4vqF16z3PHPtW1o/3Ie6u/Tn5f2dXzXuJfdvaCxV4Adrjjon/dQYfVH3WFk96fVGcl9QUdW7X+IOX6z2W0P+t9UOtxZbl9T5baR9QPNE/r07imu3rUcm6rWy11bqJllPz9UuW2us8qyKPH1MhV9VPScf47y/5v70sF1bF0P1SwRNPDSvKvdgwbbj3aNv59tdxnmYkTxpnrR2qr3n+03HBlV5qvOg/XN8vtN5XKK52u9xZ3cYG2Uen8WsYrHR9U96Dv7SpT+4HbT2r5XFhLXYPm0TZUferdLyutr9L+6M/fiJ+/nEaGa1lWQWx9Gaa+rjprGfUr3RGqY6ibpun+VO58zc3X9g96LqRjqT5nuP1QxxodD1WmKz/urwosq47uVcN6nz5udHvxM4Cm1Zp016PuXNMxV1+yVOrP+nJOj+vSsUtuMtRyWr7WdZGvOQIERpvjXHYtOsjokmp/0mXW/oOMP8/3vv5FUyBG01yB+rDllnfLasdUPnfQ1I6n25W1XLl5G76/zPs1NVem8rgy9apxlaUyNax8KsutT+NxSa6tqrdLqmtp/f35ZPOT9f/DZKl2aJ7G9apxJQ2XTlN+tw4NK5+SjGSldWpcy5Yaa3qzkurj6ule/fV19dA0N18/guSvs9qiNmm+vHRC6ZbTa7VlNb+0Dhr3l+nKlZXLr/Upj8Y13V8fTVMZWs4ljWt6s5PW6+qgV/9+ofqrHZqu9P/f/DVz87Wfa1j909VZjipP43rVsipD46UGbnmVq1RajsrSckqa5y9L05qVVH+tW+1x63TT1H61Q21Tv1I7lFfHOpff5dU85f/wh6aby6tpShpXGaV5VbbWKQvlU9KwprmkPOpbWt5NUx63fk3TsOql8jWuvFpGy2q8lUnbVu3yp3Iemu+mq75qo5KGlVSOa6OGZe3ap3ZrnitD37C7b9dl4T82urwqQ+U2K7n1aluVW6faojapDUoa1jQlDfvrKxdXjl7VdpWvctXeatte5ah8f1J5WlZJ5ag8zdd6tX7/MtpG8tR6K+XXdM1XGS5pXNPDTK6u5counefGVR/XLrVNw5qmNn/g/acO2nc1TcupzjJSPpf88zTfb6Tjg+ZrmuZpWSUN+5OmufLUX/0fMP35ohpW/dz63avq5F+f+pO2uZsva+em5V1eOanNLl897yX+ZbU9VL7KVV1ceRrWNCXVQevSchpXHav1eeWpkExluXW4V01z+TVcaV1ar/YFvbr8Cla520D9bXHzFTAqtx7N17rcPL1q3E2vVgf/9vHnk5nKcck/T+Vq+7l5pX1W6y7Nr2X8ZdbSZ7WNVI5bj15VX7+ZtresNE95tYzWr2map/WWJtW90nwt68pxyym/ylfS+rXdlE/z9erPr7qV9id/u916NU1JZfjL1zrcdM0LmlQvleVPmubKk5PqrfmuTprvhl2+cq9yVT4tr3JcHrVdNnrVNLVDScNKaqd/GeWTp+qgpPUrn8pUPk1TUh7l1TyVp6RhpdIyVYaWUdI85WlWUr2U/Ovz10d10rjm61VtVFs1rrrKVLblxjVNj0VTGUrVllWZmq98Sn4/lROHpHaqvX4vN002ro7a7v4+5W+b2uWOPZquZVwZareS1qFpShqWs/Ipad3+dWmelnFJ85WvtA6aFsfk6q9XVz8Ny0lt8E+ThUw03e+rNiv58/qXl5fz0avGlVfLaNwlrVfTSfESIDAar+1BbRBAAAEEEieQ7grrm3BdhapvupXUWneyp2ESAnET0JW1ujpS/VVJtxP6r06NW32pDwL0WfoAAggggAACrRMgMNo6+2SumVojUBBQUETftrpvIAuT+I8AAikV0Dfm+kbcfdOtb75T2lSalRIBXemhKz5cn+X9Kvkbttp5h9veSb4Kx7WBPpv8vkoLmi+g8xKl5q85I2ukmQhkQIDAaAY2cuRNPPI4tMhXxQoQQAABBBBAAAEEEIhCgDIRSJ4AH8SSt82oMQIIxE2AwGjctkgS65NLYqWpMwIIIJBpARqPAAIIIIAAAokX4INY4jchDUAAgZYLEBht+SagAtELsAYEEEAAAQQQQAABBBBAAAEEEEi/AC1EoD4BAqP1eZEbAQQQQAABBBBAAAEEEIiHALVAAAEEEEAAgYYECIw2xMfCCCCAAAIIINAsAdaDAAIIIIAAAggggAACCIQpQGA0TE3KQiA8AUoqCvBQ+SIFAwgggAACCCCAAAIIIIAAAmkToD0tFCAw2kJ8Vo0AArUI8FD5WpTIgwACCCCAAAIIJEOAWiKAAAIIIBAfAQKj8dkW1AQBBBAIRYBrbENhpBAEwhGgFAQQQAABBBBAAAEEEIitAIHR2G4aKoZA8gSocTwEuMY2HtuBWiCAAAIIIIAAAggggAACaRVIS7sIjKZlS9IOBBBAAAEEEEAAAQQQQACBKAQoEwEEEEAgpQIERlO6YWkWAggggAACCCAQTIClEEAAAQQQQAABBBDIhgCB0WxsZ1qJAAKVBJiOAAIIIIAAAggggAACCCCAAALpFyjTQgKjZVCYhAACCCCAAAIIIIAAAggggECSBag7AggggMDwAoXAaH74XORAAAEEEEAAAQQQQCC+AtQMAQQQQAABBBBAAIG6BQqBUX6/uG41FkAAAQRaKsDKEUAAgdYI9Dyzzc6ec4VN61pYTBrX9LBq9NAjm2z2gsX20u69YRVJOQgggAACCCCAAAIIlBUoBEbLTo/PRGqCAAIIIIAAAhkR4C6WOG/oW9ffZ/MWLbPlS79gPd1ri0nj162+w3r7+uNcfeqGAAIIIJAEAeqIAAIINFmAwGiTwVkdAggggAACCFQS4C6WSjKtnq4rQm+5/V67aflf26yZMwZVR+M/uH6JtbeN8qYrr64idVeVLv3mzd50/dFVoLoa9N5/edQuuWZF8apTl0fLLl1+s/3pzzut66KrvflunpZXcNaVq1ddXarpShpW2Xp161d+zYtrol4IIIAAAggggAACrRXIZmCUC1Ja2+tYOwIIZFGANiOAQIIFHntyix1/3Gh776knVW2FAptfWvY/7ZbrFntXlD5x/2rbsfNl8wc3VcDf33CbXXv5Z708d65ZZg89vMkU0Jx26hTvitS3v22idd91gzd/+d9+QYuYgpwPP77ZVKauWNVyCqJqOS9D4Y8CqrdteMB+uuE73rKXzj+/MJX/CCCAAAIIIIAAAgiUF8hmYDTyC1LKYzMVAQQQQAABBBBIosDz27bb297SaR3tA1eFVmrD7T980OZ9epYpwKk8uor04rnn2pObnx30zFDdfu/ynHTiJHvPKe+wP/zxRS1SNulK040PPe4FU1WmMmn5WefMsAf/7Zca9ZICqiu+uqh49ao3kT8IIIAAAghEKkDhCCCQZIFsBkaTvMWoOwIIIIAAAgggEEMBPWNUV4d+Z82d3i3wutVd6cql3224tjt37bV///NO7xmnKtOlu3/ycMNlU0CdAmRHAAEEEEAAAQQOC6ThhmwCo4c3Ji8IIIAAAgiUCjCOAAIDAidPmWx//stuO1XD63wAAAdgSURBVNA7/A8sfWnRPO82dt3u7tLGdSttQufYgcIC/j1uTIfp9nlXpnt1t9oHLJbFEEAAAQQQQAABBAIKpOGGbAKjATd+ChejSQgggAACCCCAQFmBs06faq+8ut9++8zWIfN1peh3b7nLmz5p4gmm2+69kYB/JnaOszGj2wctPXH8WMvlcrZz955B0xlBAAEEEEAAgUACLIQAAocvdyUwSldAAAEEEEAAAQQQqCqg53l+/nNzTLfF+3/sSM/+/Myl/82e6nnOW/4TH/2g6fZ2/VCSN6HwR3n040sKoBZGa/qv2+b9QVhdbXr69FNMP7akH3hyhagu/nW56fW/Hj4zrn/B1CyRboHUbCYaggACCCCAAAJhCRy+3JXAaFiglIMAAggggEAcBKgDAhEJXDr/fO9WdgUn3TM+uy662hSw/MH1S7wfPJo1c4aX55bb7zV/Ht2K7340abjq+YOwKkNBVS2jW+YVnJ23aFmxbNVFV7NqfmPp8JlxY4UkemkEEr35qDwCCCCAAAIIBBQgMBoQjsXiIUAtEEAAAQQQQKB5AgpaPnrvqkHPEFXA0l+DcnkUVFUeXfmp540qgKpxJQVMFVh1eTRNw+WeIeqfrvmqi9anZVSmytY6NE5CAAEEEEAAgXQJ0BoEohAgMBqFKmUigAACCCCAAAIIIIAAAsEFWBIBBBBAAAEEmiBAYLQJyKwCAQQQQAABBKoJMA8BBBBAAAEEEEAAAQQQaL4AgdHmm7PGrAvQfgQQQAABBBBAAAEEEEAAAQQQSL8ALYy9AIHR2G8iKogAAggggAACCCCAAAIIxF+AGiKAAAIIIJA0AQKjSdti1BcBBBBAAAEE4iBAHRBAAAEEEEAAAQQQQCDhAgRGE74BqX58BfLxrVqAmrEIAggggAACCCCAAAIIIIAAAgikXyBbLSQwmq3tTWubKJBr4rpYFQIINEGAbzuagMwqEEAAAQQQaLIAq0MAAQQQyLQAgdFMb34ajwACCCBQswDfdtRMRcb4ClAzBBBAAAEEEEAAAQQQOCJAYPSIBUMINFeAq8+i9qZ8BBBAAAEEEEAAAQQQQAABBBBIv0DgFhIYDUzHggg0KMDVZw0CsjgCCCCAAAIIIIAAAlkUoM0IIIAAAmEJEBgNS5JyEEAAAQQQQAABBMIXoEQEEEAAAQQQQAABBCISIDAaESzFIoAAAkEEWAYBBBBAAAEEEEAAAQQQQAABBJoj0MrAaHNayFoQQAABBBBAAAEEEEAAAQQQQKCVAqwbAQQQiKUAgdFYbhYqhQACCCCAAAIIIJBcAWqOAAIIIIAAAgggkAQBAqNJ2ErUEQEEEIizAHVDAAEEEEAAAQQQQAABBOIikI9LRahHEgQIjNa5lciOAAIIIIAAAggggAACCCCAAALpF6CFCRXIJbTeVLslAgRGW8LOShFAAAEEEEAAAQQQiJUAlUEAAQQQQAABBDInQGA0c5ucBiOAAAIImGGAAAIIIIAAAggggAACCCCQdQECo1noAbQRAQQQQAABBBBAAAEEEEAAAQTSL0ALEUCgLgECo3VxkRkBBBBAAAEEEEAAAQTiIkA9EEAAAQQQQACBRgQyEhjlJ8ka6SQsiwACCCAQCwEqgQACCCCAAAIIIIAAAgggEKJARgKj/CRZiH2mSUWxGgQQQAABBBBAAAEEEEAAAQQQSL8ALUSgdQIZCYy2Dpg1I4AAAggggAACCCCAAAJFAQYQQAABBGIhwL3FsdgMLa8EgdGWbwIqgAACCCCAQHoFaBkCCCCAAAIIIIAAAnEU4N7iOG6V5teJwGjzzVljegVoGQIIIIAAAgjEWoBrQ2K9eagcAggggAACyRGgpikRIDCakg1JMxBAAAEEEEAAAQSGE+DakOGEmI9AeQGmIoAAAgggkE4BAqPp3K60CgEEEEAAAQSCCrAcAggggAACCCCAAAIIZEKAwGgmNjONRKCyAHMQQAABBBBAAAEEEEAAAQQQQCD9ArRwqACB0aEmTEEAAQQQQAABBBBAAAEEEEi2ALVHAAEEEEBgWAECo8MSkQEBBBBAAAEEEIi7APVDAAEEEEAAAQQQQACBegUIjNYrRn4EEGi9ADVAAAEEEEAAAQQQQAABBBBAAIH0C0TcQgKjEQNTPAIIIIBATAXyMa0X1UIAAQQQQACBzArQcAQQQACB5goQGG2uN2tDAAEEEIiLQC4uFaEeCGRWgIYjgAACCCCAAAIIINBSAQKjLeVn5QggkB0BWooAAggggAACCCCAAAIIIIAAAnESiCYwGqcWUhcEEEAAAQQQQAABBBBAAAEEEIhGgFIRQACBBAsQGE3wxqPqCCCAAAIIIIAAAs0VYG0IIIAAAggggAAC6REgMJqebdm6lvADJq2zZ80IRCtA6QgggAACCCCAAAIIIIAAAggMK5DU0BCB0eKmZSCwAD9gEpiOBRFAAAEEEEAAAQQQQAABBJotwPoQQCBsgaSGhgiMht0TKA8BBBBAAAEEEEAAgTgJUBcEEEAAAQQQQACBsgL/GwAA///rrj7BAAAABklEQVQDAE7Om/EOl25xAAAAAElFTkSuQmCC"
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"net_total = final_df[final_df['Center'].isin(['Network Total'])]['Percent_Documented'].iloc[0]\n",
|
|
"fig = px.bar(\n",
|
|
" final_df[~final_df['Center'].isin(['Network Total'])],\n",
|
|
" x='Center',\n",
|
|
" y='Percent_Documented',\n",
|
|
" text='Percent_Documented',\n",
|
|
" color_discrete_sequence=['#71bf44']\n",
|
|
")\n",
|
|
"\n",
|
|
"# Network total\n",
|
|
"fig.add_hline(y=net_total, \n",
|
|
" line_dash=\"dash\", \n",
|
|
" line_color=\"#004649\", \n",
|
|
" annotation_text=f\"Network Total: {net_total * 100:.2f}%\", \n",
|
|
" annotation_position=\"top left\")\n",
|
|
"\n",
|
|
"\n",
|
|
"fig.update_traces(\n",
|
|
" textposition='inside',\n",
|
|
" textfont_size=12,\n",
|
|
" texttemplate=\"%{text:.0%}\"\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.update_layout(\n",
|
|
" xaxis_title='Center', \n",
|
|
" yaxis_title='Documented and Has Documentation But Not in Correct Spot Percentage', \n",
|
|
" yaxis_tickformat='.0%',\n",
|
|
" title='Documented Percentage if All NBS Milestones With an Attribution Source had an Affirmation FY 25', \n",
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|
" height=700,\n",
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|
" width=1500\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.write_image('nbs_documented_not_documented_chart.png')\n",
|
|
"\n",
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"fig.show()"
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|
]
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|
},
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|
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|
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|
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" <th>Center</th>\n",
|
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|
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" </thead>\n",
|
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" <tbody>\n",
|
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" <tr>\n",
|
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" <th>0</th>\n",
|
|
" <td>Bucknell</td>\n",
|
|
" <td>36</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0.027778</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>Clarion</td>\n",
|
|
" <td>72</td>\n",
|
|
" <td>3</td>\n",
|
|
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|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>Duquesne</td>\n",
|
|
" <td>53</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>0.037736</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>Gannon</td>\n",
|
|
" <td>40</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0.025000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>Kutztown</td>\n",
|
|
" <td>116</td>\n",
|
|
" <td>0</td>\n",
|
|
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|
|
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|
|
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|
|
" <th>5</th>\n",
|
|
" <td>Lehigh</td>\n",
|
|
" <td>37</td>\n",
|
|
" <td>4</td>\n",
|
|
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|
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|
|
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|
|
" <th>6</th>\n",
|
|
" <td>Penn State</td>\n",
|
|
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|
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|
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|
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|
|
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|
|
" <th>7</th>\n",
|
|
" <td>Pittsburg</td>\n",
|
|
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|
|
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|
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
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|
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|
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|
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|
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|
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|
" <th>10</th>\n",
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|
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|
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|
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|
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" <tr>\n",
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|
" <th>11</th>\n",
|
|
" <td>St. Vincent</td>\n",
|
|
" <td>20</td>\n",
|
|
" <td>1</td>\n",
|
|
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|
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|
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|
|
" <th>12</th>\n",
|
|
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|
|
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|
|
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|
|
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|
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|
" <tr>\n",
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|
" <th>13</th>\n",
|
|
" <td>Widener</td>\n",
|
|
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|
|
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|
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|
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|
" <th>14</th>\n",
|
|
" <td>Wilkes</td>\n",
|
|
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|
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" Center Total Count Director Count Percent Director\n",
|
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"0 Bucknell 36 1 0.027778\n",
|
|
"1 Clarion 72 3 0.041667\n",
|
|
"2 Duquesne 53 2 0.037736\n",
|
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"total_counts = nbs_df.groupby('Center').size()\n",
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"director_counts = nbs_df[nbs_df['Attribution Source'].str.contains(\"Director\", na=False)] \\\n",
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"
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"fig = px.bar(\n",
|
|
" combined_df,\n",
|
|
" x='Center',\n",
|
|
" y='Percent Director',\n",
|
|
" text='Percent Director',\n",
|
|
" color_discrete_sequence=['#ffba31']\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.update_traces(\n",
|
|
" textposition='inside',\n",
|
|
" textfont_size=12,\n",
|
|
" texttemplate=\"%{text:.0%}\"\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.update_layout(\n",
|
|
" xaxis_title='Center', \n",
|
|
" yaxis_title='Percent of Director Confirmed Attributions', \n",
|
|
" yaxis_tickformat='.0%',\n",
|
|
" title='Percentage of Director Confirmed NBS Attributions Per Center FY 25', \n",
|
|
" height=700,\n",
|
|
" width=1500\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.write_image('nbs_director_attribution_percentage_chart.png')\n",
|
|
"\n",
|
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"fig.show()"
|
|
]
|
|
},
|
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{
|
|
"cell_type": "code",
|
|
"execution_count": 101,
|
|
"id": "7fb3835c-8dea-4784-9109-865e6074503f",
|
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"metadata": {},
|
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"outputs": [
|
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|
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"data": {
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" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>Affirmation</th>\n",
|
|
" <th>Amount Approved</th>\n",
|
|
" <th>Attribution Date</th>\n",
|
|
" <th>Attribution Source</th>\n",
|
|
" <th>Attribution Statement</th>\n",
|
|
" <th>Center</th>\n",
|
|
" <th>Client</th>\n",
|
|
" <th>Completion Status</th>\n",
|
|
" <th>Documentation Level</th>\n",
|
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" <th>Funding Type</th>\n",
|
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" <th>Reporting Date</th>\n",
|
|
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|
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|
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" <th>0</th>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>50000.0</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>Quarterly Assessment Survey</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>University of Pittsburgh SBDC</td>\n",
|
|
" <td>SignBox Systems LLC (PI706576)</td>\n",
|
|
" <td>Approved</td>\n",
|
|
" <td>Has documentation but not in correct spot</td>\n",
|
|
" <td>Owner Investment</td>\n",
|
|
" <td>2025-09-30</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>from 10-13 survey</td>\n",
|
|
" <td>5000.0</td>\n",
|
|
" <td>2025-10-24 16:52:00</td>\n",
|
|
" <td>eCenter</td>\n",
|
|
" <td><p>You recorded the following positive economi...</td>\n",
|
|
" <td>University of Pittsburgh SBDC</td>\n",
|
|
" <td>Colorful Voices (PI707914)</td>\n",
|
|
" <td>Approved</td>\n",
|
|
" <td>Documented</td>\n",
|
|
" <td>Owner Investment</td>\n",
|
|
" <td>2025-09-30</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>NaN</td>\n",
|
|
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|
|
" <td>NaN</td>\n",
|
|
" <td>Quarterly Assessment Survey</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>University of Pittsburgh SBDC</td>\n",
|
|
" <td>Creative Wellness Studio LLC (PI707865)</td>\n",
|
|
" <td>Approved</td>\n",
|
|
" <td>Has documentation but not in correct spot</td>\n",
|
|
" <td>Owner Investment</td>\n",
|
|
" <td>2025-09-30</td>\n",
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
" <td>NaN</td>\n",
|
|
" <td>Quarterly Assessment Survey</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>University of Pittsburgh SBDC</td>\n",
|
|
" <td>Creative Wellness Studio LLC (PI707865)</td>\n",
|
|
" <td>Approved</td>\n",
|
|
" <td>Has documentation but not in correct spot</td>\n",
|
|
" <td>Owner Investment</td>\n",
|
|
" <td>2025-09-30</td>\n",
|
|
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|
|
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|
|
" <th>4</th>\n",
|
|
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|
|
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|
|
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|
|
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|
|
" <td>NaN</td>\n",
|
|
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|
|
" <td>Future Stars Early Learning Academy (PI707895)</td>\n",
|
|
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|
|
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|
|
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|
|
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|
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" Affirmation Amount Approved Attribution Date \\\n",
|
|
"0 NaN 50000.0 NaN \n",
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
"4 Has documentation but not in correct spot Owner Investment 2025-09-30 "
|
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]
|
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},
|
|
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|
|
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|
|
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|
}
|
|
],
|
|
"source": [
|
|
"funding_df = pd.read_csv(\"tagged_funding_milestone_data.csv\")\n",
|
|
"\n",
|
|
"funding_df = funding_df.reindex(sorted(funding_df.columns), axis=1)\n",
|
|
"\n",
|
|
"funding_df.head()"
|
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]
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},
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{
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"cell_type": "code",
|
|
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|
|
"id": "2e570f10-959c-4cdc-a4c7-56aed981048d",
|
|
"metadata": {},
|
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"outputs": [
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{
|
|
"data": {
|
|
"text/plain": [
|
|
"Center\n",
|
|
"PennWest University Clarion SBDC 162\n",
|
|
"Kutztown University SBDC 157\n",
|
|
"TE - TEMPLE SBDC 141\n",
|
|
"University of Pittsburgh SBDC 130\n",
|
|
"Bucknell SBDC 116\n",
|
|
"WD - WIDENER SBDC 114\n",
|
|
"SH - SHIPPENSBURG SBDC 112\n",
|
|
"The University of Scranton SBDC 88\n",
|
|
"LE - LEHIGH UNIVERSITY SBDC 68\n",
|
|
"Penn State SBDC 63\n",
|
|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
|
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"execution_count": 103,
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"id": "eee34403-8d9f-47eb-8abc-10b8224ae369",
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"data": {
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"Center\n",
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|
"Clarion 162\n",
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|
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|
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|
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|
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|
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},
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"x": 0.05
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},
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"xaxis": {
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"automargin": true,
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"gridcolor": "white",
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"linecolor": "white",
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"ticks": "",
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"title": {
|
|
"standoff": 15
|
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},
|
|
"zerolinecolor": "white",
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"zerolinewidth": 2
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},
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"yaxis": {
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"automargin": true,
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"gridcolor": "white",
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"linecolor": "white",
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"ticks": "",
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|
|
"zerolinewidth": 2
|
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}
|
|
}
|
|
},
|
|
"title": {
|
|
"text": "Capital Funding Attributions Per Center FY 25"
|
|
},
|
|
"width": 1500,
|
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"xaxis": {
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|
"anchor": "y",
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|
"domain": [
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0,
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1
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],
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"title": {
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"text": "Center"
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}
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},
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"yaxis": {
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"anchor": "x",
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|
"domain": [
|
|
0,
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1
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|
],
|
|
"title": {
|
|
"text": "Attribution Counts"
|
|
}
|
|
}
|
|
}
|
|
}
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
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}
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],
|
|
"source": [
|
|
"funding_agg_df = funding_df.groupby(['Center', 'Documentation Level']).size().reset_index(name='Count')\n",
|
|
"\n",
|
|
"fig = px.bar(\n",
|
|
" funding_agg_df,\n",
|
|
" x='Center',\n",
|
|
" y='Count',\n",
|
|
" color='Documentation Level',\n",
|
|
" text='Count',\n",
|
|
" color_discrete_sequence=['#71bf44', '#ffba31', '#004649']\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.update_traces(\n",
|
|
" textposition='inside',\n",
|
|
" textfont_size=12\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.update_layout(\n",
|
|
" xaxis_title='Center', \n",
|
|
" yaxis_title='Attribution Counts', \n",
|
|
" title='Capital Funding Attributions Per Center FY 25', \n",
|
|
" height=700,\n",
|
|
" width=1500,\n",
|
|
" margin=dict(r=470)\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.add_annotation(x=1.5, y=0.0, xref='paper', yref='paper', showarrow=False, align='left',\n",
|
|
" text=\"<b>NOTE:</b>Documentation levels were determined as follows.<br><br>\"\n",
|
|
" \"<b>Documented:</b>There is a non-blank, non-'Requested on eCenter' <br>attribution source with a value in the affirmation column. If the <br>attribution source is eCenter, then no value is required in the <br>affirmation column as this is a data entry automatically generated <br>by Neoserra.<br><br>\"\n",
|
|
" \"<b>Has documentation but not in correct spot:</b> There is a non-blank, <br>non-'Requested on eCenter' attribution source, but no value in the <br>affirmation column <br><br>\"\n",
|
|
" \"<b>Not Documented</b>:There is a non-blank, non-'Requested on eCenter' <br>attribution source with a value in the affirmation column. If the attribution <br>source is eCenter, then no value is required in the affirmation column.\"\n",
|
|
" )\n",
|
|
"\n",
|
|
"fig.write_image('funding_attribution_count_chart.png')\n",
|
|
"\n",
|
|
"fig.show()"
|
|
]
|
|
},
|
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{
|
|
"cell_type": "code",
|
|
"execution_count": 105,
|
|
"id": "b853216a-9c24-442e-a236-62003a4726d1",
|
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"metadata": {},
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{
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"data": {
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|
|
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|
|
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|
|
" <th></th>\n",
|
|
" <th>Center</th>\n",
|
|
" <th>Total</th>\n",
|
|
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|
|
" <th>Percent Documented</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>Bucknell</td>\n",
|
|
" <td>116</td>\n",
|
|
" <td>32.0</td>\n",
|
|
" <td>0.275862</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>Clarion</td>\n",
|
|
" <td>162</td>\n",
|
|
" <td>157.0</td>\n",
|
|
" <td>0.969136</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>Duquesne</td>\n",
|
|
" <td>59</td>\n",
|
|
" <td>32.0</td>\n",
|
|
" <td>0.542373</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>Gannon</td>\n",
|
|
" <td>63</td>\n",
|
|
" <td>62.0</td>\n",
|
|
" <td>0.984127</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>Kutztown</td>\n",
|
|
" <td>157</td>\n",
|
|
" <td>84.0</td>\n",
|
|
" <td>0.535032</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>Lead Office</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>0.0</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>Lehigh</td>\n",
|
|
" <td>68</td>\n",
|
|
" <td>15.0</td>\n",
|
|
" <td>0.220588</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>Penn State</td>\n",
|
|
" <td>63</td>\n",
|
|
" <td>55.0</td>\n",
|
|
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|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>8</th>\n",
|
|
" <td>Pittsburgh</td>\n",
|
|
" <td>130</td>\n",
|
|
" <td>76.0</td>\n",
|
|
" <td>0.584615</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>9</th>\n",
|
|
" <td>Scranton</td>\n",
|
|
" <td>88</td>\n",
|
|
" <td>34.0</td>\n",
|
|
" <td>0.386364</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>10</th>\n",
|
|
" <td>Shippensburg</td>\n",
|
|
" <td>112</td>\n",
|
|
" <td>13.0</td>\n",
|
|
" <td>0.116071</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11</th>\n",
|
|
" <td>St. Francis</td>\n",
|
|
" <td>41</td>\n",
|
|
" <td>37.0</td>\n",
|
|
" <td>0.902439</td>\n",
|
|
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|
|
" <tr>\n",
|
|
" <th>12</th>\n",
|
|
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|
|
" <td>44</td>\n",
|
|
" <td>0.0</td>\n",
|
|
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|
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|
|
" <tr>\n",
|
|
" <th>13</th>\n",
|
|
" <td>Temple</td>\n",
|
|
" <td>141</td>\n",
|
|
" <td>23.0</td>\n",
|
|
" <td>0.163121</td>\n",
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|
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|
|
" <tr>\n",
|
|
" <th>14</th>\n",
|
|
" <td>Widener</td>\n",
|
|
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|
|
" <td>99.0</td>\n",
|
|
" <td>0.868421</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>15</th>\n",
|
|
" <td>Wilkes</td>\n",
|
|
" <td>54</td>\n",
|
|
" <td>19.0</td>\n",
|
|
" <td>0.351852</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>16</th>\n",
|
|
" <td>Network Total</td>\n",
|
|
" <td>753</td>\n",
|
|
" <td>738.0</td>\n",
|
|
" <td>0.521924</td>\n",
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"text/plain": [
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|
" Center Total Documented Count Percent Documented\n",
|
|
"0 Bucknell 116 32.0 0.275862\n",
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|
"1 Clarion 162 157.0 0.969136\n",
|
|
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|
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|
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"source": [
|
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"funding_total = funding_agg_df.groupby('Center')['Count'].sum()\n",
|
|
"\n",
|
|
"funding_documented = funding_agg_df[funding_agg_df['Documentation Level'] == 'Documented'].groupby('Center')['Count'].sum()\n",
|
|
"\n",
|
|
"funding_combined_df = pd.DataFrame({\n",
|
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|
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" 'Documented Count': funding_documented\n",
|
|
"})\n",
|
|
"\n",
|
|
"funding_combined_df['Documented Count'] = funding_combined_df['Documented Count'].fillna(0)\n",
|
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"\n",
|
|
"funding_combined_df['Percent Documented'] = funding_combined_df['Documented Count'] / funding_combined_df['Total']\n",
|
|
"\n",
|
|
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|
|
"\n",
|
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"total_funding_milestones = funding_df.shape[0]\n",
|
|
"funding_total_documented = funding_combined_df['Documented Count'].sum()\n",
|
|
"funding_network_total = funding_total_documented / total_funding_milestones \n",
|
|
"\n",
|
|
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|
|
" 'Total' : [total_nbs_milestones],\n",
|
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" 'Documented Count': [funding_total_documented],\n",
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|
" 'Percent Documented': [funding_network_total]\n",
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|
"})\n",
|
|
"\n",
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|
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|
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"standoff": 15
|
|
},
|
|
"zerolinecolor": "white",
|
|
"zerolinewidth": 2
|
|
}
|
|
}
|
|
},
|
|
"title": {
|
|
"text": "Capital Funding Attribution Rates Per Center FY 25"
|
|
},
|
|
"width": 1500,
|
|
"xaxis": {
|
|
"anchor": "y",
|
|
"domain": [
|
|
0,
|
|
1
|
|
],
|
|
"title": {
|
|
"text": "Center"
|
|
}
|
|
},
|
|
"yaxis": {
|
|
"anchor": "x",
|
|
"domain": [
|
|
0,
|
|
1
|
|
],
|
|
"tickformat": ".0%",
|
|
"title": {
|
|
"text": "Documented Percentage"
|
|
}
|
|
}
|
|
}
|
|
}
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"fig = px.bar(\n",
|
|
" funding_combined_df[funding_combined_df['Center'] != 'Network Total'],\n",
|
|
" x='Center',\n",
|
|
" y='Percent Documented',\n",
|
|
" text='Percent Documented',\n",
|
|
" color_discrete_sequence=['#71bf44']\n",
|
|
")\n",
|
|
"\n",
|
|
"# Network total\n",
|
|
"net_total = funding_combined_df[funding_combined_df['Center'].isin(['Network Total'])]['Percent Documented'].iloc[0]\n",
|
|
"fig.add_hline(y=net_total, \n",
|
|
" line_dash=\"dash\", \n",
|
|
" line_color=\"#004649\", \n",
|
|
" annotation_text=f\"Network Total: {net_total * 100:.2f}%\", \n",
|
|
" annotation_position=\"top left\")\n",
|
|
"\n",
|
|
"fig.update_traces(\n",
|
|
" textposition='inside',\n",
|
|
" textfont_size=12,\n",
|
|
" texttemplate=\"%{text:.0%}\"\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.update_layout(\n",
|
|
" xaxis_title='Center', \n",
|
|
" yaxis_title='Documented Percentage', \n",
|
|
" yaxis_tickformat='.0%',\n",
|
|
" title='Capital Funding Attribution Rates Per Center FY 25', \n",
|
|
" height=700,\n",
|
|
" width=1500\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.write_image('funding_attribution_percentage_chart.png')\n",
|
|
"\n",
|
|
"fig.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 107,
|
|
"id": "aa7be3c4-f76e-4fc1-b443-52ba2b58d6a2",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
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|
|
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|
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|
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|
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|
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|
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|
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|
|
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|
|
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|
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|
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|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>Center</th>\n",
|
|
" <th>Documentation_Levels_Combined</th>\n",
|
|
" <th>Documented_Count</th>\n",
|
|
" <th>Grand_Total_Count</th>\n",
|
|
" <th>Percent_Documented</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>Bucknell</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>111</td>\n",
|
|
" <td>116</td>\n",
|
|
" <td>0.956897</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>Clarion</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>160</td>\n",
|
|
" <td>162</td>\n",
|
|
" <td>0.987654</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>Duquesne</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>44</td>\n",
|
|
" <td>59</td>\n",
|
|
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|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>Gannon</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>63</td>\n",
|
|
" <td>63</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>Kutztown</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>138</td>\n",
|
|
" <td>157</td>\n",
|
|
" <td>0.878981</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>Lead Office</td>\n",
|
|
" <td>Has documentation but not in correct spot</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>Lehigh</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>67</td>\n",
|
|
" <td>68</td>\n",
|
|
" <td>0.985294</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>Penn State</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>61</td>\n",
|
|
" <td>63</td>\n",
|
|
" <td>0.968254</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>8</th>\n",
|
|
" <td>Pittsburgh</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>118</td>\n",
|
|
" <td>130</td>\n",
|
|
" <td>0.907692</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>9</th>\n",
|
|
" <td>Scranton</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>83</td>\n",
|
|
" <td>88</td>\n",
|
|
" <td>0.943182</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>10</th>\n",
|
|
" <td>Shippensburg</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>109</td>\n",
|
|
" <td>112</td>\n",
|
|
" <td>0.973214</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11</th>\n",
|
|
" <td>St. Francis</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>41</td>\n",
|
|
" <td>41</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>12</th>\n",
|
|
" <td>St. Vincent</td>\n",
|
|
" <td>Has documentation but not in correct spot</td>\n",
|
|
" <td>44</td>\n",
|
|
" <td>44</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>13</th>\n",
|
|
" <td>Temple</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>140</td>\n",
|
|
" <td>141</td>\n",
|
|
" <td>0.992908</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>14</th>\n",
|
|
" <td>Widener</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>104</td>\n",
|
|
" <td>114</td>\n",
|
|
" <td>0.912281</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>15</th>\n",
|
|
" <td>Wilkes</td>\n",
|
|
" <td>Documented,Has documentation but not in correc...</td>\n",
|
|
" <td>42</td>\n",
|
|
" <td>54</td>\n",
|
|
" <td>0.777778</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>16</th>\n",
|
|
" <td>Network Total</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>1327</td>\n",
|
|
" <td>1414</td>\n",
|
|
" <td>0.938472</td>\n",
|
|
" </tr>\n",
|
|
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|
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"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" Center Documentation_Levels_Combined \\\n",
|
|
"0 Bucknell Documented,Has documentation but not in correc... \n",
|
|
"1 Clarion Documented,Has documentation but not in correc... \n",
|
|
"2 Duquesne Documented,Has documentation but not in correc... \n",
|
|
"3 Gannon Documented,Has documentation but not in correc... \n",
|
|
"4 Kutztown Documented,Has documentation but not in correc... \n",
|
|
"5 Lead Office Has documentation but not in correct spot \n",
|
|
"6 Lehigh Documented,Has documentation but not in correc... \n",
|
|
"7 Penn State Documented,Has documentation but not in correc... \n",
|
|
"8 Pittsburgh Documented,Has documentation but not in correc... \n",
|
|
"9 Scranton Documented,Has documentation but not in correc... \n",
|
|
"10 Shippensburg Documented,Has documentation but not in correc... \n",
|
|
"11 St. Francis Documented,Has documentation but not in correc... \n",
|
|
"12 St. Vincent Has documentation but not in correct spot \n",
|
|
"13 Temple Documented,Has documentation but not in correc... \n",
|
|
"14 Widener Documented,Has documentation but not in correc... \n",
|
|
"15 Wilkes Documented,Has documentation but not in correc... \n",
|
|
"16 Network Total NaN \n",
|
|
"\n",
|
|
" Documented_Count Grand_Total_Count Percent_Documented \n",
|
|
"0 111 116 0.956897 \n",
|
|
"1 160 162 0.987654 \n",
|
|
"2 44 59 0.745763 \n",
|
|
"3 63 63 1.000000 \n",
|
|
"4 138 157 0.878981 \n",
|
|
"5 2 2 1.000000 \n",
|
|
"6 67 68 0.985294 \n",
|
|
"7 61 63 0.968254 \n",
|
|
"8 118 130 0.907692 \n",
|
|
"9 83 88 0.943182 \n",
|
|
"10 109 112 0.973214 \n",
|
|
"11 41 41 1.000000 \n",
|
|
"12 44 44 1.000000 \n",
|
|
"13 140 141 0.992908 \n",
|
|
"14 104 114 0.912281 \n",
|
|
"15 42 54 0.777778 \n",
|
|
"16 1327 1414 0.938472 "
|
|
]
|
|
},
|
|
"execution_count": 107,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"funding_temp_agg = funding_df.groupby(['Center', 'Documentation Level']).size().reset_index(name='Count')\n",
|
|
"\n",
|
|
"funding_combined_and_wrong_spot_df = funding_temp_agg[funding_temp_agg['Documentation Level'].isin(\n",
|
|
" ['Documented', 'Has documentation but not in correct spot']\n",
|
|
")]\n",
|
|
"\n",
|
|
"funding_documented_agg_df = funding_combined_and_wrong_spot_df.groupby('Center').agg(\n",
|
|
" Documentation_Levels_Combined=('Documentation Level', ','.join), \n",
|
|
" Documented_Count=('Count', 'sum')\n",
|
|
").reset_index()\n",
|
|
"\n",
|
|
"funding_total_agg_df = funding_temp_agg.groupby('Center').agg(\n",
|
|
" Grand_Total_Count=('Count', 'sum')\n",
|
|
").reset_index()\n",
|
|
"\n",
|
|
"funding_final_df = pd.merge(\n",
|
|
" funding_documented_agg_df, \n",
|
|
" funding_total_agg_df, \n",
|
|
" on='Center', \n",
|
|
" how='outer' \n",
|
|
")\n",
|
|
"\n",
|
|
"funding_final_df['Documented_Count'] = funding_final_df['Documented_Count'].fillna(0).astype(int)\n",
|
|
"funding_final_df['Documentation_Levels_Combined'] = funding_final_df['Documentation_Levels_Combined'].fillna(0)\n",
|
|
"\n",
|
|
"funding_final_df['Percent_Documented'] = funding_final_df['Documented_Count'] / funding_final_df['Grand_Total_Count']\n",
|
|
"\n",
|
|
"total_funding_milestones = funding_df.shape[0]\n",
|
|
"funding_total_group = funding_final_df['Documented_Count'].sum()\n",
|
|
"funding_network_total = funding_total_group / total_funding_milestones\n",
|
|
"\n",
|
|
"funding_network_total_count = pd.DataFrame({\n",
|
|
" 'Center': [\"Network Total\"],\n",
|
|
" 'Grand_Total_Count' : [total_funding_milestones],\n",
|
|
" 'Documented_Count': [funding_total_group],\n",
|
|
" 'Percent_Documented': [funding_network_total]\n",
|
|
"})\n",
|
|
"\n",
|
|
"funding_final_df = pd.concat([funding_final_df, funding_network_total_count], ignore_index=True)\n",
|
|
"\n",
|
|
"funding_final_df.head(20)"
|
|
]
|
|
},
|
|
{
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"cell_type": "code",
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"title": {
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" title='Documented Percentage if All Funding Milestones With an Attribution Source had an Affirmation FY 25', \n",
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" width=1500\n",
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"\n",
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"\n",
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]
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},
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|
|
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|
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|
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|
|
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|
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|
|
" <th>0</th>\n",
|
|
" <td>Bucknell</td>\n",
|
|
" <td>116</td>\n",
|
|
" <td>32.0</td>\n",
|
|
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|
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|
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|
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|
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|
|
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|
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|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
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|
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|
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|
|
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|
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|
|
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|
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|
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|
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|
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|
|
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|
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|
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|
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|
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|
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|
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|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
|
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|
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|
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|
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
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|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
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|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
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|
|
" <th>16</th>\n",
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|
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"tickformat": ".0%",
|
|
"title": {
|
|
"text": "Percent of Director Confirmed Attributions"
|
|
}
|
|
}
|
|
}
|
|
}
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"fig = px.bar(\n",
|
|
" funding_director_combined_df,\n",
|
|
" x='Center',\n",
|
|
" y='Percent Director',\n",
|
|
" text='Percent Director',\n",
|
|
" color_discrete_sequence=['#ffba31']\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.update_traces(\n",
|
|
" textposition='inside',\n",
|
|
" textfont_size=12,\n",
|
|
" texttemplate=\"%{text:.0%}\"\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.update_layout(\n",
|
|
" xaxis_title='Center', \n",
|
|
" yaxis_title='Percent of Director Confirmed Attributions', \n",
|
|
" yaxis_tickformat='.0%',\n",
|
|
" title='Percentage of Director Confirmed Capital Funding Attributions Per Center FY 25', \n",
|
|
" height=700,\n",
|
|
" width=1500\n",
|
|
")\n",
|
|
"\n",
|
|
"fig.write_image('funding_director_attribution_percentage_chart.png')\n",
|
|
"\n",
|
|
"fig.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "aad0bbb0-8ef0-4ace-8344-2cd07c86d1c8",
|
|
"metadata": {},
|
|
"source": [
|
|
"# Word Document Functions\n",
|
|
"---\n",
|
|
"Now we need to make the word document functions to pass into the document builder library"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 111,
|
|
"id": "3d9e1238-d696-43d1-9aac-48f671c8fc2e",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"builder = WordDocumentBuilder()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 112,
|
|
"id": "3e964ead-85ab-4de0-8943-d991c9933058",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def capital_aquisition(builder: WordDocumentBuilder, funding_overview_graph:str = \"funding_attribution_count_chart.png\", funding_attribution_chart:str = \"funding_attribution_percentage_chart.png\", funding_attribution_potential_chart:str = \"funding_documented_not_documented_chart.png\", funding_director_attribution:str = \"funding_director_attribution_percentage_chart.png\"):\n",
|
|
" for section in builder.doc.sections:\n",
|
|
" section.top_margin = Inches(0.5)\n",
|
|
" section.bottom_margin = Inches(0.5)\n",
|
|
" section.left_margin = Inches(0.5)\n",
|
|
" section.right_margin = Inches(0.5)\n",
|
|
"\n",
|
|
" \n",
|
|
" title_paragraph = builder.doc.add_paragraph()\n",
|
|
"\n",
|
|
" # TODO: Change this to use section number in script\n",
|
|
" title_run = title_paragraph.add_run(\"1.5 Capital Funding Milestone Attribution Analysis\")\n",
|
|
" title_run.font.name = 'Futera'\n",
|
|
" title_run.font.size = Pt(12)\n",
|
|
" title_run.font.color.rgb = RGBColor(113, 191, 68)\n",
|
|
"\n",
|
|
" title_paragraph.alignment = WD_ALIGN_PARAGRAPH.LEFT\n",
|
|
"\n",
|
|
" overview_graph = builder.doc.add_picture(funding_overview_graph, width=Inches(7))\n",
|
|
" last_pg = builder.doc.paragraphs[-1]\n",
|
|
" last_pg.alignment = WD_ALIGN_PARAGRAPH.CENTER\n",
|
|
" \n",
|
|
" overview_chart_note_paragraph = builder.doc.add_paragraph() \n",
|
|
" # TODO: Change this to use section number and prefix in script\n",
|
|
" overview_note_run = overview_chart_note_paragraph.add_run(f\"Figure {\"1.5\"}.{builder.figure_number + 1} shows the counts of milestones in each documentation level per center.\")\n",
|
|
" overview_note_run.font.name = 'Futera'\n",
|
|
" overview_note_run.font.size = Pt(9)\n",
|
|
" overview_note_run.font.color.rgb = RGBColor(15, 27, 38)\n",
|
|
" overview_note_run.bold = True\n",
|
|
" \n",
|
|
" builder.figure_number += 1\n",
|
|
" \n",
|
|
"\n",
|
|
" \n",
|
|
"\n",
|
|
" # Add comparisons between actual documentation counts and what it would be with proper documentation\n",
|
|
" picture_table = builder.doc.add_table(rows=2, cols=2)\n",
|
|
"\n",
|
|
" row1_cells = picture_table.rows[0].cells\n",
|
|
" row2_cells = picture_table.rows[1].cells\n",
|
|
"\n",
|
|
" attribution_chart_paragrah = row1_cells[0].paragraphs[0]\n",
|
|
" attribution_chart_run = attribution_chart_paragrah.add_run()\n",
|
|
" attribution_chart_run.add_picture(funding_attribution_chart, width=Inches(4))\n",
|
|
"\n",
|
|
" attribution_chart_note_paragraph = row2_cells[0].paragraphs[0]\n",
|
|
" # TODO: Change this to use section number and prefix in script\n",
|
|
" attribution_note_run = attribution_chart_note_paragraph.add_run(f\"Figure {\"1.5\"}.{builder.figure_number + 1} shows the percentage of funding attribution milestones had documentation per center.\")\n",
|
|
" attribution_note_run.font.name = 'Futera'\n",
|
|
" attribution_note_run.font.size = Pt(9)\n",
|
|
" attribution_note_run.font.color.rgb = RGBColor(15, 27, 38)\n",
|
|
" attribution_note_run.bold = True\n",
|
|
" \n",
|
|
" builder.figure_number += 1\n",
|
|
"\n",
|
|
" attribution_chart_paragrah = row1_cells[1].paragraphs[0]\n",
|
|
" attribution_chart_run = attribution_chart_paragrah.add_run()\n",
|
|
" attribution_chart_run.add_picture(funding_attribution_potential_chart, width=Inches(4))\n",
|
|
"\n",
|
|
" attribution_chart_note_paragraph = row2_cells[1].paragraphs[0]\n",
|
|
" attribution_note_run = attribution_chart_note_paragraph.add_run(f\"Figure {\"1.5\"}.{builder.figure_number + 1} shows what the attribution rate would be if all milestones were properly documented.\")\n",
|
|
" attribution_note_run.font.name = 'Futera'\n",
|
|
" attribution_note_run.font.size = Pt(9)\n",
|
|
" attribution_note_run.font.color.rgb = RGBColor(15, 27, 38)\n",
|
|
" attribution_note_run.bold = True\n",
|
|
" \n",
|
|
" builder.figure_number += 1\n",
|
|
"\n",
|
|
" # Add the director chart\n",
|
|
" director_chart = builder.doc.add_picture(funding_director_attribution, width=Inches(7), height=Inches(2.5))\n",
|
|
" last_pg = builder.doc.paragraphs[-1]\n",
|
|
" last_pg.alignment = WD_ALIGN_PARAGRAPH.CENTER\n",
|
|
"\n",
|
|
" director_chart_note_pg = builder.doc.add_paragraph()\n",
|
|
" director_chart_note_run = director_chart_note_pg.add_run(f\"\\t\\tFigure {\"1.5\"}.{builder.figure_number + 1} shows the percentage of milestones that were director confirmed.\")\n",
|
|
" director_chart_note_run .font.name = 'Futera'\n",
|
|
" director_chart_note_run .font.size = Pt(9)\n",
|
|
" director_chart_note_run .font.color.rgb = RGBColor(15, 27, 38)\n",
|
|
" director_chart_note_run .bold = True\n",
|
|
" builder.figure_number += 1\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 113,
|
|
"id": "8850b388-264e-4d9a-b766-5dc272b5c3f2",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def nbs(builder: WordDocumentBuilder, nbs_overview_graph:str = \"nbs_attribution_count_chart.png\", nbs_attribution_chart:str = \"nbs_attribution_percentage_chart.png\", nbs_attribution_potential_chart:str = \"nbs_documented_not_documented_chart.png\", nbs_director_attribution:str = \"nbs_director_attribution_percentage_chart.png\"):\n",
|
|
" for section in builder.doc.sections:\n",
|
|
" section.top_margin = Inches(0.5)\n",
|
|
" section.bottom_margin = Inches(0.5)\n",
|
|
" section.left_margin = Inches(0.5)\n",
|
|
" section.right_margin = Inches(0.5)\n",
|
|
"\n",
|
|
" \n",
|
|
" title_paragraph = builder.doc.add_paragraph()\n",
|
|
"\n",
|
|
" # TODO: Change this to use section number in script\n",
|
|
" title_run = title_paragraph.add_run(\"New Business Start Milestone Attribution Analysis\")\n",
|
|
" title_run.font.name = 'Futera'\n",
|
|
" title_run.font.size = Pt(12)\n",
|
|
" title_run.font.color.rgb = RGBColor(113, 191, 68)\n",
|
|
"\n",
|
|
" title_paragraph.alignment = WD_ALIGN_PARAGRAPH.LEFT\n",
|
|
"\n",
|
|
" overview_graph = builder.doc.add_picture(nbs_overview_graph, width=Inches(7))\n",
|
|
"\n",
|
|
" last_pg = builder.doc.paragraphs[-1]\n",
|
|
" last_pg.alignment = WD_ALIGN_PARAGRAPH.CENTER\n",
|
|
"\n",
|
|
" overview_chart_note_paragraph = builder.doc.add_paragraph() \n",
|
|
" # TODO: Change this to use section number and prefix in script\n",
|
|
" overview_note_run = overview_chart_note_paragraph.add_run(f\"Figure {\"1.5\"}.{builder.figure_number + 1} shows the counts of milestones in each documentation level per center.\")\n",
|
|
" overview_note_run.font.name = 'Futera'\n",
|
|
" overview_note_run.font.size = Pt(9)\n",
|
|
" overview_note_run.font.color.rgb = RGBColor(15, 27, 38)\n",
|
|
" overview_note_run.bold = True\n",
|
|
" \n",
|
|
" builder.figure_number += 1\n",
|
|
"\n",
|
|
" # Add comparisons between actual documentation counts and what it would be with proper documentation\n",
|
|
" picture_table = builder.doc.add_table(rows=2, cols=2)\n",
|
|
"\n",
|
|
" row1_cells = picture_table.rows[0].cells\n",
|
|
" row2_cells = picture_table.rows[1].cells\n",
|
|
"\n",
|
|
" attribution_chart_paragrah = row1_cells[0].paragraphs[0]\n",
|
|
" attribution_chart_run = attribution_chart_paragrah.add_run()\n",
|
|
" attribution_chart_run.add_picture(nbs_attribution_chart, width=Inches(4))\n",
|
|
"\n",
|
|
" attribution_chart_note_paragraph = row2_cells[0].paragraphs[0]\n",
|
|
" # TODO: Change this to use section number and prefix in script\n",
|
|
" attribution_note_run = attribution_chart_note_paragraph.add_run(f\"Figure {\"1.5\"}.{builder.figure_number + 1} shows the percentage of NBS attribution milestones had documentation per center.\")\n",
|
|
" attribution_note_run.font.name = 'Futera'\n",
|
|
" attribution_note_run.font.size = Pt(9)\n",
|
|
" attribution_note_run.font.color.rgb = RGBColor(15, 27, 38)\n",
|
|
" attribution_note_run.bold = True\n",
|
|
" \n",
|
|
" builder.figure_number += 1\n",
|
|
"\n",
|
|
" attribution_chart_paragrah = row1_cells[1].paragraphs[0]\n",
|
|
" attribution_chart_run = attribution_chart_paragrah.add_run()\n",
|
|
" attribution_chart_run.add_picture(nbs_attribution_potential_chart, width=Inches(4))\n",
|
|
"\n",
|
|
" attribution_chart_note_paragraph = row2_cells[1].paragraphs[0]\n",
|
|
" attribution_note_run = attribution_chart_note_paragraph.add_run(f\"Figure {\"1.5\"}.{builder.figure_number + 1} shows what the attribution rate would be if all milestones were properly documented.\")\n",
|
|
" attribution_note_run.font.name = 'Futera'\n",
|
|
" attribution_note_run.font.size = Pt(9)\n",
|
|
" attribution_note_run.font.color.rgb = RGBColor(15, 27, 38)\n",
|
|
" attribution_note_run.bold = True\n",
|
|
" \n",
|
|
" builder.figure_number += 1\n",
|
|
"\n",
|
|
" # Add the director chart\n",
|
|
" director_chart = builder.doc.add_picture(nbs_director_attribution, width=Inches(7), height=Inches(2.5))\n",
|
|
" last_pg = builder.doc.paragraphs[-1]\n",
|
|
" last_pg.alignment = WD_ALIGN_PARAGRAPH.CENTER\n",
|
|
"\n",
|
|
" director_chart_note_pg = builder.doc.add_paragraph()\n",
|
|
" director_chart_note_run = director_chart_note_pg.add_run(f\"\\t\\tFigure {\"1.5\"}.{builder.figure_number + 1} shows the percentage of milestones that were director confirmed.\")\n",
|
|
" director_chart_note_run .font.name = 'Futera'\n",
|
|
" director_chart_note_run .font.size = Pt(9)\n",
|
|
" director_chart_note_run .font.color.rgb = RGBColor(15, 27, 38)\n",
|
|
" director_chart_note_run .bold = True\n",
|
|
" builder.figure_number += 1\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 114,
|
|
"id": "87091175-a9f5-461c-9c4d-b21bcb5e0d07",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"pages = [\n",
|
|
" PageConfig(capital_aquisition),\n",
|
|
" PageConfig(nbs)\n",
|
|
"]\n",
|
|
"\n",
|
|
"doc = builder.create_document(\n",
|
|
" pages,\n",
|
|
" \"section1_5.docx\"\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "634609a4-580c-4ce6-8ad3-ec0867401334",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "c343e248-63cc-40f3-814b-6da05a81dc9b",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.13.7"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|