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R2_new.html
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<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta charset="utf-8">
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<meta name="generator" content="pandoc" />
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="author" content="Meghana Tatineni" />
<meta name="date" content="2019-02-19" />
<title>R2</title>
<style type="text/css">code{white-space: pre;}</style>
<style type="text/css">
div.sourceCode { overflow-x: auto; }
table.sourceCode, tr.sourceCode, td.lineNumbers, td.sourceCode {
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table.sourceCode { width: 100%; line-height: 100%; }
td.lineNumbers { text-align: right; padding-right: 4px; padding-left: 4px; color: #aaaaaa; border-right: 1px solid #aaaaaa; }
td.sourceCode { padding-left: 5px; }
code > span.kw { color: #007020; font-weight: bold; } /* Keyword */
code > span.dt { color: #902000; } /* DataType */
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code > span.bn { color: #40a070; } /* BaseN */
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code > span.st { color: #4070a0; } /* String */
code > span.co { color: #60a0b0; font-style: italic; } /* Comment */
code > span.ot { color: #007020; } /* Other */
code > span.al { color: #ff0000; font-weight: bold; } /* Alert */
code > span.fu { color: #06287e; } /* Function */
code > span.er { color: #ff0000; font-weight: bold; } /* Error */
code > span.wa { color: #60a0b0; font-weight: bold; font-style: italic; } /* Warning */
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code > span.vs { color: #4070a0; } /* VerbatimString */
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code > span.im { } /* Import */
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code > span.pp { color: #bc7a00; } /* Preprocessor */
code > span.at { color: #7d9029; } /* Attribute */
code > span.do { color: #ba2121; font-style: italic; } /* Documentation */
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code > span.in { color: #60a0b0; font-weight: bold; font-style: italic; } /* Information */
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NOjMKhUpWZWHK5LZgl9279229we2OBUX50kuVjv5QDo7PBwnsvrhWJF%2BYDIuVagZDxeFHOF1MEKbsBMEQS%2BKJjOVdXJ1BKw61EH%2BfeqSTzTz3I7ZA3Zuv%2Bwhshy3sDFL2TjctJR6n2SDsfFJ3A0I5ewXfAgugw7s%2B0XQG0SAfFVWHOEsr6TyphSHW5NHFc9J6Wa%2B7B3Dfp42HguHAUINniPlZCpQ%2Fl0CogDIrW%2F8u85iv7sGv8ZzGzYAxjwV%2FMCxTwobJQCTWU8HRPQeruaaXpRqestVdUOXso7dupeF7px4Z8%2Bed3arKFc44AIg51W9ch4kIIiUEocmSk4sBpCcj15oUDRJXYYExl37RmirrkIv55rLASYJJF%2BS3t0nopeptU%2BE%2BmLrLK%2BlPgQyid3mCBU6UP1rVz8R2n770zc%2FXf7x8s%2FNn9fvaFi3rmFHPfmMLWRP4lycho%2FjNPY4W82Os88wiJ34K4tdAIQjAOQkx8YArcM2PaAOjSZBL8uolzAJFFvGDXd8ej67P2AvKpUkOYghcnK7zl300RBcsExwzJ%2Fhbrd7GuYBwhgAIYtbTx%2F3%2Bd4klJ3gtKCQnGIz9InYZEzqG8EkjSzNavCB%2FcXYlcQshhyMsZrI6PYLWc3lOG%2FvlA4rHr%2F3uTFD3r38%2Fr%2B3fMKOke9W4oJ9G566u7au84CpOz%2Fct5R99wF7W6dIYjjnawrHIAh3hlungFOWgXoyzVKbHOr1eD19Il6vISsrrU8kSzbY%2B0QMGpdjgYh60zDTHJKHoyP4404pw27zB4o1o62gq%2BBLL299am8j%2Bzv774zj995%2FdgTOZsOfWr3rnTWPj2h8qGbo1%2FM%2F%2FkYYvmxfms7TtPrM54E7ns4vwBw0rFy%2FaNJjRRVTet31OgCBPABhongUDOCAzuE0h6gnxChToCJ1ulB0iH0jeqvscFBZotflk%2BhMQ5oJDqhrC%2Fl%2F%2FFxmAUlGYeK5Z6Jl5MDec2yJQdc%2Bl5ViNduL1avoZ805eGll04jy6COKheT8S%2BU6kQwdw%2BlW6nPpXF4qtEoBziwAye3mMnRLkqlPRLqZdQlsKxTcLghkqhzjrLL5M%2BWgUwldSkjbL1HPLrCf51d8MHbv66zu%2FmcGl5Kz0YNZ0%2Bmcf759kbEB29qGGrZiYWop2b2R9fYqnKnlWOVzqXqgNfQIB5LtRr8fQLLT7CyT0ZLaL2K0WFzU5e0TcfmojkckcgvcyhJ4pNlr8Bd63VyEhIbiGhfIBFGTq8R9lqcWB2Dl1G79Rn%2F9i8n08OU3L%2F760UX2E369YuvqVUPrI9VryFR8CXc5V%2FrYefbW7svv%2FYNdxUHv%2FOnFVQ1V8yse2Dde0UcAIY%2FzU4L0sA1FEQg3jJT0jVAJFBlqbOOrALk1dCOmkuHNF%2BmpaKOYunHhldNAlZhEyFGpz4R20C%2Bc47Vmu%2B6gqXo9lewuq5TfXrLnZORk9Ink5JjAlNwvYvJBoF8E5N8qd9nN3jrmj7mOx8OPLDXqolpgwv0zZkpuzaeTynf%2BvWjNvnr22b%2BbsfDJR7%2Be%2BcL6dQ1bXlu3CDvOWfHIMytnrhJPHt7x4L7eg%2F48%2B8C5U0euLuu%2Ff8ozr1xteHTRssdGru8V3kwfeHTMsN937%2FzksLEzFdlO5NQpNsMLWdAtnJlizzQYAAQu26AljUvWZbEQlyuJi1Ymcr8Iaal2jjKNg5qJ9Ctqx02jMyDFKHJw8TpUIvjHKhXZQlZ0%2FIwe1eO%2B%2B6%2FRVHpg2mv%2FuPbBuguPMtfKLU%2BtuXfjkIFraEVzg2tlMuZg6O57%2FvXBP1C3kZ3H9od2PPV81RMVE%2FaNAy3HEcaokRS34Ta%2BLAA8XotzQMRiizkRDVfN87X0JXae6NzkVR6Znehb6J8XL%2BY3IKovXMjn0oEDMrkmmc2iXu9yGm0DIkab6hgTZklwj%2FT6FDccpXsmn6Rjlxv%2BknyrTFMR8%2BU%2FcF9%2BDiRwh%2FUCiChwdeXD58cDhSwsRjeikNNcTo83%2F0AtP2DDKLywji1nhxSezMTjgo9eVHOy3LBbJgIQ0OsEsToiIFRHrIjI4wHOlfxEz6a4ZOTXTLq9eTjdTofW1bEH6up%2Bg5GIBDhGEr2BkRNVlMZTa%2FP3HKVyrMMKrF3H%2FKPYUAWjlGsXaRnXrxTIhrJwqp%2FbMtnphFYWIdgGoLWtddqASGuPzdA7YhNaqFZLvVJSEa48LZwUd4YSN4mJ%2Baq%2FctSSXgtmD6gf2emV91%2F9KNj38bHd9l3PX0tq19dMnzFw3OSsgsWjj%2BzqPXn0w4On3e9nZ%2BNJLYFZ1yqkQ2ITFEM5zzwyA%2B1KLJ1kVwpAjsvSTgx3S%2BrQQeiisxv5Ky%2B9kGbnqUmllmSFEhOP6%2FG4ug6C2nJQUPdSt0td36R1IFMgbsUalrqlQAbw4KK1v1BwIH%2FudKqm8NCQbeMHP2LUtVk3rv7Fb4712N3Tt%2FDeaWvZt3%2B8wA7swe6Y%2F5cvjv3I1rHJn%2BAyhLM44ODVn14%2F7bBUDpq%2Fhpxb8c388XfdM%2BrU3veu%2BTws17Pv7O79aFvzMnvxc3aaHRq8sAZX4jgUsP7CfvYntoNhGYquJiAAAKJNPAIyWLjk0ojFqENR0SwqyILNaiG9I0bRYhFECoKD518xh6iplZYz%2B5W8H0OIlBsz%2FtURB6IHmnaT7itJORvb6A94cnbjGZYvHrnSg0zENwfPGTGddQIKJwCEo9xyW8ALGdA7nO0UUg1Wn89iEGQLjwd01iRrUlXEarWAxVcVsTjAWxUBevt4QnM9%2FgxBMbluwe4SAjxpj%2FmcgN0ef3cCt2IAhVVLsR%2F7%2BTIjjZjU9PTeY1ew4I9%2FOvhn8cCeI%2FNf9BnK2Pk3%2FkZ7TF00%2B6HoquhndauXPAGAMIdb09Oqr8gOu6jFpbdQb5IDekccglHi%2FHK2DL%2B4emRymUNIE3%2BRo3WokKfbtNP37Cs0%2F7rxjQ0X2Cvs2Rex%2FNNLuysbxBB7lX3FPmdvl64rwyU44QusOVSzuj8AUTgmDuEc04FdsYcWQQ8COJyiuSoiUsFSFREct4ppwc9rSBlA%2BZuAPZTBx2Az2Uo2CY%2FhIHysic%2F1z59PI%2FdU5CtWz%2BaJB9gi9gKmYebVKZgHgMq89Bc%2Br1GJWSSDAQXQoWAyS%2FreEUlCQsTeEUKRr3B03DZmUZBwxy%2F6S%2FMZmh%2BdTYZHt5OF4oH1LKc%2BeilhJj0UhpMlAKQ6pAbjTRPxSW45Q0CbAac3asPzwaNfrY9LTuyi2ilOhUvnI8SSohNapUJK7wiAaDLZe0dMgujtHRGdt4%2B8%2FHaphRyV9%2Brq5lT1xe9nfPc0a2IrDuKQL%2F%2F9bve3DrL%2Fso%2FQj0kbVrGXCYuWZWXjUhzzD7xn%2F%2BD6GvYau8Q%2BZe8H8LUY7WK6yuVQ2KdHBJ0giCCaTTraO6LTiQaJoshJV81RgnG%2FQbydi5f%2FDYnpjc2ssZGSRrI3Ws1z7dXkYQC8NoLNxfFqVpwaNht1OotVT4GzFDJj9GrpGI15%2BJJiPpxLMg0v6dVv9AONx9jclFWuR6fyFGvI0TNxvRC%2BUjHmnkjBViRGg4Ix0Yn6RGzLWkgJZRVRDKHw1TvRrzc2NpL1J6JN5M0l0dc5snnk4%2BjCBF0QIT1soQCCJCMFzgtw3EBXxTekkO0%2B0aio0pV%2FbIp9V%2BKIgpPrUZJOFCUev%2FJSmsuNBjuVjDK1gKQgp2DnLbuZlRjwuJUAn2MY4nce4COtZjadZSsCntbhh6zRomMm0bbpo%2Bbh4oGrVQLPOume7Uev%2FBCXo1IDsUG7sFsvcaytVpDB7jBS2aqjKCdypaUI4xPzabNJKZdj%2BWvNn%2BtsW4%2FRVB2xkGeEk582NR%2FnE3ZMwaxy2guAqFp99FZ5bu%2BIXqDW3hHqvLVNiOltBiTmueJRtpW9oZgjHIE9sBOOujo9%2Bv1%2Ffvn5h%2F9Eeb77LHuYa%2B94HIt1bArbxs6yU1iIuRjEAnYqZp%2BE8erqdUBRONnA%2Bc75DE6XQaiKGAySLDuqIjKVEtavhpXmSgW%2FmlplYChutYXx7Ay7tLsRZ5PWUePGL949euKoYPr7t1HOh2jK6mdXrVC5wHaoXLBCCp%2BZp8MeAIEa%2BOqmZtns6x0xC7KTL2yZM%2BMtlRs3J6I2pViG8q258sX7OOxndrH0tpz5ki3rzuqxivyf%2FDnN%2BWMCN1SGs8yIxKS3y0aDQdYTwePVm8EMVRGzmVDK5UepkSi6cntnp2Ku8ktw20SOf5bGNm4BcRXyGdhfcfkJ9jQ7%2FVXTzl2vfEZGRLeJB94%2Fzf4%2BLjqZjFi9cuWqJwDVHIFw29ha4V6a0wSQ5BSFrGxTGvV4uH30CFSfoEoJiY4mt0CGlozy8D%2Bo5jgx%2B6jmBbwy4BEI%2B9d3rHnZ0I%2FGN%2B7usnL1ey%2BxM389WLx%2F1%2BINHRbWXfoDLjz%2B6Z07su%2BYN73vyIFFvd959sV3qtf2nfFA35F3FQw8AoDgABCGcv7JvJ7iABSRUp1epgK3CYLmFeJ5qGYSi7k3IEsbWYFQyQrE9PWqJzjM14yPj2OHrLDdhgYZZafDrqOCmQ8UpzGUuFzsLkUnVHMYs4uij%2F2F%2FcJfFxrfee3ld8QDzf2vsC8wo5nuaa44%2BMabh%2BghQAAA4XW1%2FpMcNqJgMuooCJQqiPLlrxWvQhjgF8%2F%2FSgXTwej3O6M%2FNmF1x8zWHdVaFh%2F5uU3bnwXkmg1yXz6aT6km%2BQwpyW6LRdQn2Q0U9TGTotqUGOKqNclWAjJldKcyenwSZ0h8cyc75y5CT3v2xU42u%2BnL9p6UYpSa0Nne7yy%2B1EQ%2F7PaW6%2Fdbm0N88llHNx18ic5qnrv59RXv0YUK93QAQr1q9QNhhyCJ3ORLiskXFJMvtDT5KhocAz63Yu7rj%2FPIY0oTXmKdjuAkfHg%2F60QWROeQZnI4%2Bgq5M9oX4lybrUY5GWGrIBJRpnoDiChTUeOcJmE%2BqKL%2BGCJdcNEhlrSb%2BQ6T8%2BR887zoCZJPFyv1ZQBBscZ6pWKmQyqDLKBgMIoCNwcUdUrMcuuKmVot8AvlzU6qi9roq82%2F0LSFwoaNC69OAIQGdoRMVnSRY2mRUFAYoxcJlTDIOdBSfeJRD5nMSvEEu4B%2BdkS6svyKX6HWC0A%2Bi1c2Kd5c2XRy3h0mgYbo%2F4spg%2FKNEDuCzdrMFFACSacHOUgFevPMXj5rMb9CfMoLfOrSA%2BKF5b9KyigFJCgExOMgQVJYD1TWiQQEwrO%2BG5rpVFUTC3DfaPxsA1vG9pEg3dQ8jnwV9QJea2Zv0k3XKtUKsJLHIlEqwBgjmU%2FLQUfRp9mbCwCxTjhHHZIf9OA8AILRID2BkJ%2Bs1ZoxwDW1OMStBHU83G1fm5MZ0%2B4QzhUdK3f33F8MRKk50lPCUEXzoVc4K1NnTEvz%2BRw6yqMpYkzrFSFGI7jd1ooIt4LJFRHRA24o%2F98LVH4tX7NllapJZ7zS6LZn8QVeLKsVKjrQrxv43GPPvUychyc%2FVveH0F3HR77xCrNs%2FmPDWy89tOWB3js3Y1%2Bb1GPe7Jq5dxTuORZ11TZuHC3LD00fOhwI7OVWtVZygRPSeVUt0%2BD1Wq2mVGqiGX4zmNwOu8HOhccRljzgqoiArYV5DSXF1SDB1sddEk825YBijeRQiVcrvHAqyJ5Pv%2F3%2Bk0l%2F7GwKzGzQ6Wa811i%2FqXFjfb0wlJ1jP%2FDXxwMGLpdcbNHcsTuWvv7ll29fOPPJXwAQpnMOLxWGxbIaK6VuPU3ySmaOmQ0cHDPPzVmNGM9qlJ1DHgNzu6hmOGTcZXYV9f8d8HTbUOn8QrbvuW11Tz3swiw0oRPvyPQu96Sywe9%2B2mlNGRBlVqGU88fB%2BdM97E%2BVvGCx2CV7ht%2FhtgIgmqhez9mjt1FnRYR6bscerSYTkLTqvTcUDPLPA6osi%2BJOiG7ST%2F%2Fn2W%2B%2F%2B%2BTCTLMsNCxmTzdu3Ny4evOmNS9gNlr5647tA%2Frh0V%2B%2Fmfny%2B4Gv3r54%2Bi%2BfxLF0cN44IRk6hdOTDF4jpdzqtkrxGit4uRskyaUyyqIw6paZQyiRZQ632%2B%2BJsUuivNbh53Kb%2Bx%2F2JYp%2Fe%2F%2B7qFl8eecf%2FzBk65bfb7WQLstc2AZl1GMH9v3fJxx%2Fp2pttp%2F%2Bc%2FeGrS8oUksFoBYpHVxK3cVlMjkJ4UaSuj0GvhQMgKIsVkScspUqq0GtY98IAxWmOZS1p2QNgeJSXkPW3DX3mE%2BzrxreeANH3lObN6LH8KHopW83l9G3%2B3TugmsDC9PnPNkLgEKQuYQCzplcKIVu8HC4a56vQ5YpvYtY4ESnSHIzW6Vn%2BQzd72xlLbYWV0R0nXpFDJm6XKvOqvPk5pJekVxrm%2FJekTY2T7teEU9KnHUa%2Bzj%2F8pXd%2BrzbxD1uragaVBdAqDC%2BjaAUkrJv%2FOXKcGMXmJOnbhQXF%2FF3QsHJVnf87VhB3sSqoa%2Fte5X9jf3r7FdPzMgtC%2FccNOnTtwb3ZPb6ZWdOPLzh7amPD50%2F4z8%2F1T4uVE5ICkzt9ewxXYdBbfPqVx54ddvqMauTndXFnYfmBnY%2B2PS66ypEhs2ZFOn5IO08%2FZFvfn4cEPYCCD24nnuUzM5i0nFz7dF7vEkWvcMhVEQcNgOA3q0Y7xjlCatesVT2mALbtRUfM1P06cfm%2F%2BGZhgadoWD%2FjBMnyJuLfn%2Fkk%2BjrfHXnDOow4N5XP4gWAxDYDoDjxAtAwcr9tZ3PJCDa7Ga5MmImVlQ04%2F3EwqZSIqAJJVQc3NDQ1CG3TceObXI7CJWYU1Zc0qFDaSkAubaKudSxTZAEd4Q9TqPRrNP5kj22yognrLcC1z6ISzW5xSTOhATTljhb3v2det7Zv%2FeNGZnLt9g16B6h%2BaqNHZHv0yaP8TSV89QGJTzetxgMRqNOEkSdYHeYAGw2nY7KRje1xiKGfD5zeUyFyuJsRTUiQi0bdclYkzcER73JeuD5E2zOnB07dKSgy2icydpGlxLpQTZOcjW%2FXTo9NjcO5nNT4GQCoiASQHfca2tMVBjHYVRo6SRfJQGoCAfcdruDiz%2BgdwRo66xWHrfb4RPMPm5p0302p1UPDkUPuCLEt534Igi1bHVIVIgEzfAqepHh1bRDypryyOa1DVNmblnVsDhFl79rIuIAXcHhmYdfJicWLNj3cnSLcv%2Fzx9HjQmV99dDDg8e8%2BheuMZq2cnxdUBBOApeiri69x23S22xcWW02g%2FV2ytpSV72Jmrp7m4JG6NDUt95RNPXwJ%2Bq8d0XUSWM2dhSfU9EknsU6wSyDnOwzeLgds1GbYvxvmcVylSHFilGFxE4PYRT74fKaf%2FwOTZcvobX5lZ3PPffii88%2F10Cy2I%2FswyeR%2FAFNmMfeZ1f%2F8rfzH545p1j5vdyW1apU%2B6E8nOEzCrKsS3foHJkBwQhWq7siYrXprboUaHXDzMdZ0GLBqpaeO2hPAhMUr62Y%2BgRHrThpU8Niry7c%2BPBf%2F%2Bf7yzvryabGFc8%2B6xowcMRg1kUqqh9azT5h%2F1GcNr14%2BGTWl29fevfUeYVXHNNSlVexqMKW6qHJyT6bL8OfnOK1pqalecxOp8wtv80MFRHz%2F%2BY2VT5yJ1l63Ul6r3vQ0njtQyL9GzaIW15cvXnjnI8uf%2FfJ57P0SQsajObpM%2Fd9mHXp3YunT59birloRDO2a6z%2F9T38eEzFCzE9okGOpw1ywy6zXm8wEF4DsZrB4FYtg03rc2nRkaE5IY15ZEfvjt4eRQtfaahz6rrsFoaZNlk%2FfTbaJFSenDQjlrnS6XyW1twOtIplrqLzeuZaEfHYJKq%2Frj%2F5t8pdueG5kbsG25Hfpq50%2Bj%2Fe%2F%2BtjA%2FbXzF82%2BdmN88r%2FevSPL3Z6ftEjj7Yds%2BJ13jSzsaHnpjbt7h4Uvrdr2aAH%2ByzaXLm4R1W3O7p2KO71FCCkX%2FuG7BQrwKPWJlwu3jPioEKS1%2BC0OXtFLGGbVeaCkj1xU3kqIVjV5ONWqo52xVGXhtxKNuHyEMcdA5NSJuSy17ZurRiBXdlrw2vN8lyzHQeQZdU9%2F83mRWePngiAsIOvrjKhElx8fh86ZZPJ4DS4PSaz2aZzWdVV7TFqEbMS%2F4daVmW0rJcrhBY127EvX9TPNNQl6UP7Z7zztlAZLeMO6GMSvnpozV2Dj54hp7RcjgiVau%2BHAQ0ms6hHK6jhiJZl%2BNX0NFTicIYQt7ER%2B76ptuiMte%2FtYyP4oI%2F8o0cx9iPtrx6K5UpSgI%2FWinsblz4lNc3rsZipYBZ0yQ7ubnTuxCyYK7c2A1U2Z2Rlk8LhUHSq1BmbsoRPKeSfcBbp2qSdPsY%2B3jNxsk5nLHCcaHqjg0snBF7dzc6QBZ3OvHR%2FdK5QyUaz6j5l%2B4tJbXTp7trW9eRvHClACAIIOpXGzLBdFiVAUWlxQZ3RLaD1pnQ4ngmjmhUfYgteQT9m%2FJktwFVH2Cn27hFSQLxsGO6IfhU9jUdYD0AgfL1LfHw3z%2FsVMqnHK5jB7OBLO0UHfIJCVam1GRJo46KKOdrSUrLvuwFOnfnuS%2FtYTsWfl%2FStKu2xq3cXzuCVn9wf%2Bpn87mrGy5vtC03HtkAsZ6YPCZW3yJl7RUQr6npF0P2%2F5cz0oeZ%2FksHR0%2BTL6D5y31Q6eN685sPxrixetlPl5%2FYlJxu9AFbZRbmnpqlpTq09K3F7TdV%2FbpXcPJZTfEtxCddDvj7d3EK4ZLfHjedrpx794PFH58%2F49MClCxdM44aRZaRxE%2BaPjywnw0Zg4ebdS6Xj7NzZoCl4FhAvMxuZrfluorSo0RSABN%2BtlHzx8nKeJv3cDAiV7Ijaw5Oq4OwWDQ4H8UFqqsXiE2laujso0QScEzYFFXSDxYr7U7DPVNCV5Dj2pcRw4eKhDx%2BZ%2F9jjp45OnvHwVFIePIvB49LSPRvZ%2ByPvJcsjvOq5cRenZNg4zJn2qEvdpyXVQg6tAS%2FXAzu1JvkcpuoIdVglCaojEuTngS3pjfw38rSkOlOZT8nQVNOmbD9lKoU5HFg8t2TMUz2mRrqPyi95omTcisrHK%2FsMJSfuLFn%2FUKvsVinhsvqH%2FRkZSeoOPFuKdcJwrcuYCALV8343AGpSu4xtNPOWXcZcCQNO1%2FXt0PNKk%2FGszp3Ly0IVZPfVC2Lfxb3C5ZVhQDjK7fd5dVemazjNozNTahCARxo62irVJxKnwUz4SzDKgg%2B07k9ljt9sw2apra1KOJCldLR6NAOuqD89OWHNwpPHcdniPisKChY%2BtHv7My8sX%2FFdifTO%2Bxlov4LNXXfvoH7vstCH5z462QkQypUYSDzBpV4Zzk5y6s3mZI%2BdGD1OMS3dlORL6h%2FR%2B3xOcNr6RpxJIPa5uRWkRdPQzZ6Nm29lf5Lfinl2ypuduEqQxqONXTatnD0HG9jQblU05erVU2%2B99f%2FEEzUL%2B%2F1uGTs397MxS%2B7YtDz%2FxwtzsfO%2BU4psZqMkeIVtnHNByAibW0GmBSxtctLd7iwZeNSYn1gJchaVBku9il8r9co82Ja9clCxDnKwNLs0IXQ6VLV4%2BOLx8%2BeOq7t%2FUVXVgmF14%2BYuGrN42MKqeVtnzHh627QZW8mHj01aNmxh794Lhz059ZEFD%2FCHvfj7JZN%2BN2XbM1Onbd8BiscDEJT9Fw8MDrdzWGSj0WYS9URPTS6LW%2FYmGSwW2So5HBScbqsz3UmsTqvThG7JlATlWg%2B33RHrzL7lpjuGUOGj1uaovjBEKnH2HjYCJfY6dmGv72BvYGd%2BARu7j1wgZ5vZ3Ma57Ec08RslQBKsgaxUVYkkUR726QUqUDlmFjgmiYqtbgjFLYRiI5p%2FYebmnxVpXPuF1kupUABdeGdcdiE4pdy0Dj5fmkmCgNS13E07lbRqK%2Fn1%2FmCviN%2Btt%2FWK6OGGznh%2Fs4t9I39VVFmLztSUlwuwZdCiRC2l%2FKk33lG0dHD%2FqprTbw5%2FZmTxqMV9Z8yYvelw%2FcCqjf%2F%2B6K9P9H9t4KLl7R%2BcvmJR99W%2Ff6Ggbs3LPQbRnMF1WW0mD5q1NDW4IJjSKdy5prTH%2BklDl%2BfctXrZxm5rs9r27dWuY8e8oqHTRvWb0MVZPfnuKWXOMUCwWLTQ8eKH6u5TWpiTanKAI8lnpW495N90QCAhzctKeI%2FFxVnZpaXZWcU4pzgrq7Q0K6tYnFrUrl1RYUFBYfwOQGEM7xzvEdt5hxKeSwWDXmrNT0936a1esbSDZAKH1ZRuIuCwOYjJYXKk5AWcoRQByhNPBdhblgFRMxHuG90bnN2obu8KDjc3eYHM1py5DiFU2NqhNXTQOXMWz10weE77sRWvffDZq0880vHB5vXv4PB3les1tv2D02z76xP2YNvdezD3pT3s7N497JOXhMCeTTu3t%2F2dq9X3n575qfMjIXZI%2FQ7b%2Fu6brOGD0zj0rT%2BwD%2F%2BwB3P2xr8GQKCCushU8W1OdzqUhlt5pRQDokeJazP8rQwGh88D1EYJNTvSOakf3feGku9qVGpqG4xTV8ojfbXWGSt18iYUtdZJXEnDlt0%2FedPztWvHjM%2BbtnB%2BHauecmLUlAeov2bk6HHjJkhCcGFoRIcJs1jnI2OaCgRBqd8NhFraSI%2BCBGbICTupxI21YNTrBbMkWKwmUYegHGS5WbPRiyhjVuw2EAfPVEriM1kjLsUhtexzTK9lO0kQ1%2Fdk29mzvXB9yo23qh9EHfeDXhAhJWwiKKAki0J1RCSQr20nattixUJOXfM71Bv9Hhc%2BCdeuaV3LRAIbAAjXdUoX16r7wqGgF3iOLui5Zpn1JodXKu1gsnFoi9Pi0DmtjnQHAR63E4fT4bythikCCP22ZKVVoUS%2Bhp0Bqm51Fnr%2BL2UjHz5YPXLwfRNx36B%2Bl3eeXrwWxYbNVy%2F8n%2BpGrtwd7tNtSfXsNFaLo9jTdPZ89ub%2FpXB47YrkEiRpzW3r%2BoJ09UfBJLnmAoG5dBi5LJ5U83Z%2F2GIGp7L7nGwzHPNQhS3J7yWaAKe27LkytvA6c%2FfPn39g4Oqa%2Bfun195VPX3qwLunC2vmH9i%2FoGZlTdOCgdOm3l0zdZoiv%2FGASic8yQYLAMhwBiA6Q93NqCLLub9OUmpcstOLaHGCwAsItnQvZqjyadHEUVx6cz%2B0JMt%2Bsjy645vIQH91edGont0XbPj9msiaPXiIVI2%2FNHhk35IePbMLh0yeP6V6%2FZPPA4KflKlzBqAsnGkVRaCONIPUOstxn%2FMhJ%2BnrRKMzxUmcTl2yP92s88eVhKvIfTe2KDHRmKtlyd%2F2PpPpA3vsPbRzw4w1sz%2F8snbmA6Or7%2Bw%2BpUPP8mXDl2wVvqx%2BwJu%2F%2FYmVHWb32L5q0oAeXXrkBYa2LZl5056LnkfvwhP6xD0X5YAIN3pyAOvaT85494494cnCD133dnN3O1oEqNZDegiV4IHicLJoMOhs4HS6dC6%2BLeC2ulLMRKks6LWkMWHX6XqfaELKyMnTOhsGs13PNCxJNkz%2BZ%2F0Qg6GhAeewK698pKaNLwyr2caOScrsU1mzMEJygRWCYYcgIoBopDa7TidSq4jaQa%2F8RJkG7MortqVTEvILI6Z9PL1rzacn%2F%2Fov0pY1S3t%2FraYhx5WrKDBA2ED6Yh0dqvitsEECMJuofkCEQsyAJOqq2jzatUOseZR82L1nz%2B7xMwlZzIVNAOBQIge7xQhgUfrILXa7jtog%2F71CzQq3qDNoZYbSkOzBpo31obZtOw24a8BDQx4ubWIXRk7UT9S1Kckrtu%2BbHgSEvqQKP1d3kPleHwFKDSZuX2mGBGlK3sc5EGO7FpnEzw8MXLlQ8pQsvpNv4K4ld9471NP2%2FhFAoDt1kaPi26q3zgo7lONnEnBvHfMfbr3iP964r4XTTjgzJSYsWHJ0V%2F3qF3eu3%2FB8lN07fsKwYRMeGCZM3nHw8LPP7T%2Bw%2FTH%2Bb%2FYjjwCBau4hdsY9BF%2BZRr1AgMrEoJdu5R%2F4fBhELEUxdqM72c5aTGef1%2BIQVnvjPTGxCb3wfhzek01IufGW24c%2BAOIZzq8gnCYLACAbHrsGKMNHNDV6EPR%2FosTBA8ziYuCw7Tjs%2BThseQz2CwV2Ou3PYeV9xMZBVchkAMkvnuAQM34FFf4CxEZ9KD5qXmxUIBBiM2mNMBxSoY3Sba1zpQWwlbVVwCXk5EIqmmhqKj93lzEgkm2zG3tH7IEWecP9w%2B9rGZ4ohslCYnXDUm9MGF2J0ihbnJBfkf59Rs7q4vv9Y9X1ozq9%2BdbRTwPhSMnYbk2zOnXtXqqkXKHH1tZM7NOvw5ip2e0XjzjcWDEhMjB%2FyIz70jFvcU%2FeGRvmVKrdoPJ0bltbq9R1v%2FYaDgTdn4hNzIa84ltA1MLCGETS7SCOQSAGkdoSIv86xGsg3HKMrOsQE6CUQxiaKGmtgtyAkWIwIMNxKIN5QK4xAIk3MIIVnNA%2FfAdPM%2BwIOhPaRNEtuvROycm7kHm7iMHM7wabASUqOtByowkglmHm5an5G8bOiYau9y%2FSAF7vYVQ2zqR5UUeUXdxLDtMT0SMkNXqR9Lhag0cfURpetbZG%2FAvZr2jRHOZSOkc5ztkqzrMIAf55rM9N5VmbON8PqhxBs8aRmyFqoTwG4b4dxLFrV2MQyS0hsq5DTACHylWC%2FhhXgUA%2BgFip9id54Z5wod3t1glmAKcgCUk%2BrogS11erXC6%2FJJ%2BWL8jcIsuyoNfbqiJ6Kri17tNEXW55EDWhHZV7uVhLarxnM5QhVqpNqbM3bcJ9eBf%2Bbn%2F07S9xNlt4lIyKtaWSunqyntWxHSQcba5nhhhNYrmqS%2B3jurSmJdWx7jiVLwUx3sKsmLb5bgdRi4YYhP92EMegKQaR3RIiX4PgeGy65RhZ1yEmwMdxnW4b5z7CQrQJJmEDGMEX1st6ino0mXXgy0%2B0x2rMHLeOu0ewbTh8BHua7RiLw9m2MThS2DCa%2F3fbaLyfPTsaR%2BCIsWwrAOXzv877434CJ6RAQFkZnnRvmsAPExtcAA6rqFMCF0%2Ba32f2945YHTpRoDazQHnjnES1lrm3%2BFq4%2BYgL%2Fygm0lglwc7fxSoM1BZEj3qKzovZ1zsLv1479tEH9ykddGe2jnx04rGmh6Mjpu%2F9zy%2FNwbFk68SdWpPhmOUDNr2FDyl9dMMXV699l61D26bmvgOVZjp2ZRN9qTc7xVdOrI9LlUxpXLoVMfk7Nb7fDFELp2MQKbeDOAZzYhAZLSGyrkNMgA3xlRNMtEfCbHWUTvF5CmKjOFSQeO%2FfrHjvH9%2BpMOtFUbKDBB6vWeALiC8fs96sl2LdkZoVarkRrHVH8v9lCDcaJGexM%2BzzQ42NZ9GHnuYrO3mL5LvvUdvFy4zXWq%2FB6ei%2FV%2B5Y9yQAqv0oW6R0aK94ppxcMTUAXpMJUu25YkGhw5Hbrl12RaQd5LrV3S5tj%2Bvm0xpaZCBL2vZIQjWCo6Q2%2F2lnOTKUqE%2F1UYJv5ZAOKb36Lxv32p%2BOTCrfUnn27ofnjujZq094yVz2TcPf%2Fv7%2B58IPi6dX3OnPyC0L3b917LZdPTcF8w%2F0mVQxcHZN%2BcTisqHF1YMuXO0r7Nv3562c52pXkOTnPL8TACXovgLUVWlXOH6L57V56vN2t3t%2B7FP1eajFc%2FGz689fe%2BUW3xc%2FvP58whegruiOKsCNGRZehzj%2BcwyiTQwCqAIhKbtXOVDENWdkOJQLre3tedlIaF%2BWlJTe3ghi5y4pbYNtKyK%2BAqGgV6RD66BdECyZQU%2BxzqKriLgsNtBaO9R97viBxZsNL1corarUot3Jy%2F%2BqHSkOv7bLFExMz5TiAMaaVIb%2Fwg7NmPnUc0VVb4%2Ba%2F3xO8a6Hj%2F0reqcOO967tWbwurHswpy73lz03Mt7Jg1ZtfPpwzvoK7OWGon8BOY%2F%2ByddrEUqp%2Fie%2B4eMYP%2F9%2ByRWGwjyVpav5k5sXH9%2F5MVNo2XdQ6Sw4ektO5V1zXc4lW4kzreeMU%2BJFaqnVDtxVIn1ikl8vyqRVppEbn5e21993vp2z4%2F9rD7PafGcS1R7PsEQk1d7TaLX%2FgqAo9URXolZHHYXKGOgqI3xIgApTICovZYRgzDHIa79iUMMSoA4xl6IQTg0iG84RDrHQ4OYwA4CqBbHZ9d89VRlx1zyq6euqsJ5fsnUqhXwYN5jsTttkj7YRp9eETFSj91nsfLIR0%2B9LqSttY3QmLJw6%2F3b430QyITiIlAqxdlBMcj%2FlHpUk%2B6gRVqnV4kwil39%2Be%2FsK5T%2F9sUYXdkp9n3vr4YN77ll3OW%2Bpzc8v7NpC3vppe0vPUtC7Ev2FzR%2FcQmlWcInr25%2BcGHXgtrefZ6cNHMlm8b%2BtaaRbXjh4Aku21jXgbraqmOrzaLyJC1RNqNUrt0Vk%2F1HquySb%2Fe8drD6PPN2z4%2Bp45Ngi%2Bd8fu35a9%2Ff4vtcJtrzCSkx3Wh3fS2Ph2YhR9gJVO1CD4WTPAaDTSACKjsZTifKZjMqJ%2FQQ8tX1yhOfG8nPjUN6iccXE96Pp8ejezqVFHXsFCrqot3J8iefZP%2Fq3KW8Y1m4nPwYfwOUY3tEGCUsjvv7PvxEa3orl8vQ6iZn76u47uxt1M%2Bb2Kjnf3P2ZWVxBdGcfXw7QXSpTl4Si1SnX6L2X2yaUjNt%2BDw0Xd40o6Z25NzmV4rxTJ9pvAljfYjl95r63Iuxboyetf0XbEBQGjL6zuy7cMOvu8aRRcWffLRjTHRO6DzXjNjutSq5e2KSf0PVDI8mmZuf107VNOfWz4851OeBFs%2B5ZLXnE%2FyxtZarrfrYDqw6wr2xGWIjpKsAWu%2BI2t%2BVyXex0jOkFJfNZpfsrQMOsKeYPHqqT%2BNdjB7q5euvRZPnb3oYUWsXUUomXo%2FW9JUVbx7J4HugOKR748Sz333%2Fyd8fMwk63mSElTs38OYRzF9LmyID2Efsvwpjn83sV86KdcDaFQ1NOXQi58u3ce%2FZMxo1nF6Nmgn7Y%2FTmxejV%2BpuEyuv9TaJArLfsb%2BIw6gkU6UvxFLggHe4Ot0uSrE5nKpjtqZKY4bc6eDxpBaOR51hGGj%2BVwg8UUAc4b5zk4det2ia1fWVJO2TlvZF9aafq7NnSl1EYN4y9zJ7BYRgeN5RaonxdR8%2BRfs09fmXXEH%2Becs89LqzDiTgeF3ljSZmwlZ1m55QTGn6hNi32qy1yujAU0iAXCmBQuG26zkI8nqx8t7tVlk4oDOW1Mbbh0RHvSCKixdiunWg32pIyxcyKCIieFj7YoVjVRAeseV9R9a0q5rdyvYktTFkxnyvWs%2FNzup6pu8B%2BROnrBae6djz2%2BInL0aAOq4Y%2Fe8%2BQDVf9G154buPm5xvWCb3mrjKRjN%2B7vp4xEwtQh3q8Y%2Ba0KbPYz19MYDO5tw1mkLIPz3985rOPP%2F10x9NP7wBEE68Q7pH8YFF6wGWwWXmN0KJs3CSfKkwsE%2FIgzx1QzhIE0DR3nLfB89CcmUMWLuFF2u%2BWPJGTu3C%2Bt3TBoiIAgpP5iG2lhdp%2BkEMyxSpMejflw753u9KSrHUfcfpp29njxj46a8zY3z3YPRTq3rmsqJu4b9TM2lGjps8c3qFLlw78AkQdn%2Bk78TN1N5wPn%2BSzg2gC%2FnKrZc73En4mKLYb3o4vKU6BwvQ0olRTQpJEXXkDB%2FTOLAxZRpmn39tucP%2FKjIL21tHmqcL5rLZZnbvMquO3Tl1n1aldEci5Ff%2FFEyCCePMvngykw%2BK%2FeMIh5f8VUtYgffQ49lB7%2BR0HUNTpQenhP6WBBkscHEs5y%2BQZ1WF29yx63DMUTVyicNM3RdTpRZly061Rq55Od5RisXIk%2FbGKDPGARzmLjqmfcouq%2Fe4LkcAKAEQZizSpY1khOWwS0KwXbHbQUZP2M1%2Bx3pUgbyrhA%2FvjeGG9tcNjs9M6maNnb2B4FnXTeR1Tw7TF6DZldL0ZRcHuMIs2WRn9LW10DWe%2Fei9JQJ4ELUkjOsxJ7m6%2BQYbnXvbTY2Ow6D6FHh%2F7lTTBZZSVLOtqB8g4iCCHzeZK%2BdC1Y38ymWJ3vb5SBnteXszG7cAfyXB6EYzgPBD%2FURrIP3Wr6u%2BOqQ9OmDF94qRp5JtZj%2F9u9sx5C%2Ficym8TiHvgB8gGOwAEwU4c%2FM4nELJA1RaoJelK5ZPTbBAIlYikk0WuCInpvPM3e2CJ%2B16ASv2UpGqjUBAIkMRRWhRNSeqtK6QAyGYBkJXxUyYgEkE7ZYLxAQJIVjbPWkkXx4%2BZIJRzr1gnnuT0TQ2Xp3rTPZ5kI5Hl5NZ2wZDslYJtjN4kb%2F%2BILklMTUvtHyFp1rT0tPw0qqdJaUlpzsxM6BvJlJ0W3iDhg5ZN3bwwdMsfKruRW2ZQbuRlt9evdcorVpPyolGwuJT%2FdUDsCHUKOz4AWfRHQvA065Z1snHLxtW7%2FoddaNewgZANO4LY%2Bn9OPN%2BrQSxmD80rC7ed1%2FRm9%2FpuaEacl3tH9TwUsfXIpYPVzprl6o4iBXdYT0AUtDAtYc3y%2BEuJtrjkUwGEVlI650ylKvE%2B5ABA%2FHNTwuf9lc%2BBgItUcf0%2FAgZwQedwuks0ypTyaYjSqY%2BiqLe60l3E5aIWOZ1mxPuV70toergeGwR4g0v8V2eKi0otVJZJ05xV7GHcsHQO%2B0ESk9LSjDup6913x%2FKzVKdeX9THFGzb1v5TDDfpQ45bECoJ9%2B43cBcf0nCXXr%2FF8%2F43notvxJ6rVEnqc1TWG05X9cp%2BAAQRKWiHl2Knck80KgqljCAC4Aq1QvJpPHP6XaxCImp1FiUv6pwAUXstt2Ud9NrbHGJCAsQx9ufEKktsFtJBzroOMYF9EK%2FV%2BGK1mv8PflNJUQAAAAABAAAAARmahXJJOF8PPPUACQgAAAAAAMk1MYsAAAAAyehMTPua%2FdUJoghiAAAACQACAAAAAAAAeAFjYGRg4Oj9u4KBgXPN71n%2FqjkXAUVQwU0Ap6sHhAB4AW2SA6wYQRRF786%2B2d3atm3b9ldQ27atsG6D2mFt2zaC2ra2d%2FYbSU7u6C3OG7mIowAgGQFlKIBldiXM1CVQQRZiurMEffRtDLVOYqbqhBBSS%2Fohgnt9rG%2BooxYiTOXDMvUBGbnWixwgPUgnUoLMJCOj5n1IP3Oe1ImajzZpD0YOtxzG6rSALoOzOiUm6ps4K8NJPs6vc%2F4cZ1UBv4u85FoRnHWr4azjkRqYKFej8hP3eqCfDER61uyT44DbBzlkBTwZD8h8%2FsMabOD3ZmFWkAiUs5f4f2SFNZfv6iTPscW%2BjOHynEzEcLULuaQbivCdW5SDNcrx50uFYLzFHYotZl1umvNM1tgNWX%2BV%2F3gdebi3ThTgVEMWKYci4kHZhxBie3TYx3rHbGr%2BPdo7x4dIHTKe5DFn%2BO%2Fj%2BW2VnE3ooW6isf0LIUENvZs1gf%2FLHojJwdpplCP5gn%2F5gi26FoYa19ZVFOJ6Sxuoz%2Fq2Ti20IKVJdnqvYJwnhfPH%2F2f6YHoQF30aZaK9J8T026RxH5fA%2FWPW%2F8IW4zkpnIfoFLifGB86v0ffm5nbyRs5iaHR3hNBD0HSfTzoPugRM%2BhdN0x052KoHLBS0tdgpidAiEesDsgWYO73RWQz2LWIwjqnMe%2FuYISQtlbyf2NlT9Q9PoBcBnrO6I5ELoMeyHkNnIXGdv809H%2FDXNOTeAEc0jWMJFcQxvFnto%2F5LjEvHrdbmh2Kji9aPL4839TcKPNAa6mlZUyOmZk6lzbPJ3bo56%2F%2FCz%2BVaqqrat5rY8x7xnzxl3nvo%2B27jFnz8c%2FmI9Nmh2XBdMsilrBitsnD9rI8aiN5DI%2FjSftC9mIf9pMfIB4kHiI%2BhWfQY5aPAYYYYYwpcyfpMMX0aZzBWZzDeVygchGXcBlX8ApexWt4HW%2FgLbzNbnfwLt7DJ%2Fp0TX4%2BUucji1hCnY%2FU%2BcijVB7D46jzkb3Yh%2F3kB4gHiYeIT%2BEZ9JjlY4AhRhhjytxJOkwxfRpncBbncB4XqFzEJVzGFbyCV%2FEaXscbeAtvs9sdvIv3cjmftWavuWs2mg6byt3ooIsFOyx77Kos2kiWsIK%2FUVPDOjawiQmO4CgdxnAcJzClz2PVbNKsy2ZzvoncjQ66qE2kNpHaRJawgr9RU8M6NrCJCY6gNpFjOI4TmNIn36TNfGSH5RrssKtyN%2B59b410iF0sUFO0l2UJtY%2F8jU9rWMcGNjHBEUypf0z8mm7vZLvZaC%2FLzdhmV2XBvpBF25IlLJOvEFfRI%2BNjgCFGGGNK5Rs6Z7Ij%2F45yNzro4m9Ywzo2sIkJjuBj2ZnvLDdjGxntLLWzLGGZfIW4ih4ZHwMMMcIYUyq1s8xkl97bH0y3JkZyM36j%2F%2B58rvTQxwBDjDDGNzyVyX35Ccjd6KCLv2EN69jAJiY4go%2Flfr05F%2BUa7CCzGx10sYA9tiWLxCWs2BfyN%2BIa1rGBTUxwBEfpMIbjOIEpfdjHvGaTd9LJb0duRp2S1O1I3Y4sYZl8hbiKHhkfAwwxwhhTKt%2FQOZPfmY3%2F%2FSs3Y5tNpTpL9ZQeGR8DDDHCGN%2FwbCbdfHO5GbW51OZSm8sSlslXiKvokfExwBAjjDGlUpvLTBY0K5KbiDcT672SbXZY6k7lbnTQxQI1h%2B1FeZTKY3gcT2KvTWUf9pMZIB4kHiI%2BxcQzxGfpfA7P4wW8yG4eT%2FkYYIgRxvgb9TWsYwObmOAITlI%2Fxf7TOIOzOIfzuEDlIi7hMq7gFbyK1%2FA63sBbeJtvdwfv4j28zyaP8QmVL%2FimL%2FENJ5PJHt3RqtyMbbYlPfQxwBAjjPEN9ZksqkMqN6PuV7bZy7LDtuRudNDFwzx1FI%2FhcTzJp73Yh%2F3kB4gHiYeIT%2BEZ9JjlY4AhRhjjb1TWsI4NbGKCIzjJlCmcxhmcxTmcxwVcxCVcxhW8glfxGl7HG3gLbzPxDt7Fe%2FgY%2F%2Begvq0YCAEoCNa1n%2BKVyTUl3Q0uIhoe%2B3DnRfV7nXGOc5zjHOc4xznO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Z9A7%2BtETl5RXdNNZGDm%2BvXYXWjgLDRzEhoLBAYv0%2F0NHAAAAAADBQ8CvAAFAAgFmgUzAAABHwWaBTMAAAPRAGYB%2FAgCAgsIBgMFBAICBOAAAu9AACBbAAAAKAAAAAAxQVNDACAAIP%2F9Bh%2F%2BFACECI0CWCAAAZ8AAAAABF4FtgAAACAAA3gBY2BgYGRgBmIGBh4GFoYDQFqHQYGBBcjzYPBkqGM4zXCe4T%2BjIWMw0zGmW0x3FEQUpBTkFJQU1BSsFFwUShTWKAn9%2Fw%2FUpQBU7cWwgOEMwwWg6iCoamEFCQUZsGpLhOr%2Fjxn6%2Fz%2F6f5CB9%2F%2Fe%2Fz3%2Fc%2F7%2B%2Bvv877MHGx6sfbDmwcoHyx5MedD9IOGByr39QHeRAABARzfieAFjE2EQZ2Bg3QYkS1m3sZ5lQAEscUDxagaG%2F29APAT5TwRIgnSJ%2Fpny%2F%2FW%2F%2Fv8P%2Fu0Bigj9C2MgC3BAqKcM3xgZGLUZLjNsYmQCsoGY4S3DfYZNDAyMIQAKyCHTAAAAeAGNVEd320YQ3oUaqwO66gUpi6wpN9K9V4QEYCquKnxvoTRA7VE5%2BZLemEvKyvkvA%2BtC%2BeRj6m9Iv0VH5%2BrMLEiml1XhzPdNn3n0rj6%2FEKn2%2FNzszO1bN29cv%2FbcdOtqGPjNxrPelcuXLl44f%2B7smdOnjh09crhe279vqrpXPuM%2BPbmzYj%2B2rVws5HMT42OjIxZnNQE8DmCkKiphIgOZtOo1EUx2%2FHotkGEMIhGAH6NTstUykExAxAKmEqSGMFl6aLn6J0svs%2FSGltwWF9lFSiEFfO1L0eMLMwrlT30ZCdgy8g2S0cMoZVRcFz1MVVStCCB8raOD2Md4abHQlM2VQr3G0kIRxSJKsF%2FeSfn%2By9wI1v7gfGqxXBmDUKdBsgy3Z1TgO64b1WvTsE36hmJNExLGmzBhQoo1Kp2ti7T2QN%2Ft2WwxPlRalsvJCwpGEvTVI4HWH0HlEByQPhx468dJ7HwFatIP4BBFvTY7zHPtt5Qcxqq2FPohw3bk1s9%2FRJI%2BMl61HzISwWoCn1UuPSfEWWsdShHqWCe9R91FKWyp01JJ3wlw3Oy2Ao74%2FXUHwrsR2HGHn4%2F6rYez12DHzPMKrGooOgki%2BHtFumcdtzK0uf1PNMOxwDhN2HVpDOs9jy2iAt0ZlemCLTr3mHfkUARWTMyDAbOrTUx3wAzdY%2BniaOaUhtHq9LIMcOLrCXQXQSSv0GKkDdt%2BcVypt1fEuSORsRUwgrZrAsamYJy8fu%2BAd0Mu2iYFhexjy9FIVLaLcxLDUJxABnH%2F97XOJAYQOOjWoewQ5hV4Pgpe0t9YkB49gh5JjAtb880y4Yi8AztlY7hdKitYm1PGpe8GO5vA4qW%2BFxwJfMosAk2X9n9X2cVVfnA36pzHNHJGbbITj75NTwpn4wQ7ySKfAu9u4kVOBVotr8LTsbMMIl4VynHBizBEJNVKBAfMNA9867j0InNX8%2BranLw2s6DOmqIHBIbDfQR%2FCiOVk4XBY4VcNSeU5YxEaGgjIEIUZOMi%2FoeJag4mEB3PUOweCaG4wwbWWAYcEMGKn9mR%2FsegY3R6zdYg2jipGKfZctzINQ%2FvxkJa9BOjR44W0OpTKAskcnjLTcKyuU%2FSVIWSKzKSHQHebYW9mfGYjfSHYfbT3%2Bv877XhsIwGzEUaleEwITyE2u%2F0q0Yfqq0%2F0dMDWuicvDanKbjsB2RY%2BTQwOnfvbMUhiNPFyDCRwhZhdjE69Ty6FjoOoeX0spZz6qKxxu%2Bed523KNd2do1fm2%2FUa6nFGqnkH8%2BkHv94bkFt2oyJj%2BfVPYtbzbgRpXuRU5uCMc%2BgFqEIGkWQQpFmUckZe2fTY6xr2FEDGH2px5nBcgOMs6WelWF2lmiKEiFjITOaMd7AehSxXIZ1DWZeymhkXmHMy3l5r2SVLSflBN1D5D5nLM%2FZRomXuZOi16yBe7yb5j0ns%2BiihRdlFbd%2FS91eUBslhm7mPyZq0MNzmezgspUUgVimQ3kn6ug48mntu3E1%2BMuBy8u4JnkZCxkvQUGuNKAoG4RfIfxKho8TPoEnyndzdO%2Fi7m8Dpwt4XrnSBvH45462t2hTEX4Bafun%2Bq8jIzK%2FAAEAAgAIAAr%2F%2FwAPeAF8egd8lFXW9zn3PmX6PNMnPZNJMRRDMkzmDYgZMRRDCEmMMUPJIgZEepHlRYyIiNhRUdYuS4ksy9reLDYsdOmLLC%2FLy7L2CgKrrCJkLt%2B9T2YyYPl%2BD8804J5zT%2Fn%2FzznPBQKbACSTvAEoqJAdtUhUJpQYjBJVAUrKSkIOJ1ZUOEKOUGkfV8ARiPB7E72m87WJZF58ibzhXPVE6QsAAnMufI4H9XXsUBh1UpOJSJLmQNWqNsasLkKhsrKnA%2FT1HCF9PQzSAPYtD5V5PW4lmFeIK86EcCRbObLp2lGjGxpH4%2Bf0wLkjjU3NDSNGxYSMxbSdDkzomhE1SypQalCISvniob1lDuTL7injC1O%2BMr%2FxmeJtxeRt%2FiJviJ8mmrjFOr0BJCZ3QAbkQFu0ypCZ45HcRqNJQkiT%2FLKsOO02s2Ryudze7CxVUnw%2Bv9%2BtmKTcgEEymzPRlgN2e5rHaeOXyeeiisnJFagMOSsqSkr45kL8Tr450SfM5%2Fy1V66pGvBwTV1BcYcDEX67QjQkbo8cigTplyVI2OHh%2F6zdXHO4%2BiR6SjoxMPzo8O21h2tPx7O2lmylNV%2FtY5Nwubj3fXUA%2F8BuFveBr74CoNB84V6pSnFCLhRCL7g7OijfR7Oy3FalR49AcXYRFBnsQUcgkAYO6H15j6wiAGu%2BI%2BAo6pleFDAWKJZMX%2BaImNunWOpiskIVH796ewAqEzvV9gqX9nQ4Qd8S%2F1V%2FScSM%2FrmsTP9FfNUNIvzuVlRPMFxY5PB6fY6iwsJw3%2FJIOOTx%2BlT%2BWzaR%2BxYWecrR7fWFFanqi%2F33nnn9%2Bv%2BMvXr7mk933%2Fv5Gy3PrN6yZjg7WFV1D5s2oGoh7nx%2Bk2vvTrkeDT0HKlieXvvakkfecj%2F5uKnhm6iNHRk27a6bevTL%2BclH3ulVkX3cBTJUXjip%2FCDvBiO4wQ95PB6qo%2Flen0%2BWTRpofo8nLa04mB3UgpeX5PbMLEzzKz4%2FtapOlXt5a1llpXhN7FF7r8zJ37o%2FiN15Q2XhvsE8RdajOqwFyrwFGETXr%2F0F9u9dNnZsWW9869X1azow9qe%2Fkpc7D52mPRf%2F%2FHcJFrR1npvf9sWX336EO7%2F9x7lqeUMn6frt8y%2B%2F%2FZD%2FJjzecOGEAnxvWdzjpTAzWtHbGjRhlhdMXqvLVZSWnl5kpSoChLJVtcwXSPea8vNLSrT0dEnTegyPaZIUqIlJLnSKhAV%2FpfBuhb9EbE53bYVIM%2F3S45hfiZ%2B7th8IFPHN5QuXcscms1vF8kiAZ2qBsEEEFQX7FnJDeNy%2B8nIF2JLZ7%2F77DPtk3rJhVV9vefPD%2B57CzCF98cr82%2Bs631s4%2FvbxrKPf1XjT0Iqrh%2F%2BuafTMxR%2B9e%2B%2BmxqZnxzzx5l8embstxo7PeX0Ju3DjoqYJA7C611hyd3hAtH%2FzpD5jAAVm4DM6Zjj5C5WIAIu9DuxCIB0kuvEBAKGBbSTz%2BL%2B3Qm7UZjaZqCSBqtrN%2BVQgmAMTua3joeaMhBTicTt9wULS8PSj5x58eNk9Z5c9RUrRiPte3MTKzvyHRd5Yh9vFygP4yq3JlfmyfHG%2Bso1LyP%2F5yqgRNVjuDPclRSGvk7Q%2B%2FejZJY89%2FOA5sTT7ifVb%2Bzru%2FOEM7tv0EisFhErSJGUpbrBBOOo3ms0ypVZUVc0umUyqilarYrDxpN1aJrKQuykJwvwz%2FyPMUOCTXSqlRa6CiEzJy8U4J8DWf%2FjpM%2FeeOMZeLMKpxYqbPTyx088Oz8MKtnMuFqefm4gzAKEZPpUqpG1g5qivGRSjkSKAxWo2giJRKOFCysqS4vjNhQXCAa4Bxz1HEI%2ByNlx0FBextqOk9SjezW49yhaIHbGzuBtOggKe1wgFWVapDCXbdSNt5ghfoNCgMxLA3X1v%2B%2BdV%2Beg%2FvIsdR9MJYWVcS5rISqDg%2BCuVQQLkSiTc7QoHPANIGq49dw6wi7GwgmvujZoUrrSRNsaMLqjsmfjnkYu4aU6SlJZ28xECNyqt0mMrM2pBricBidueiNS5iDcRA0ir4h%2By4yQgGJP%2FDwLVF05IQ%2BW9XLoPLou6LYoTFPCnGT0jYkaV2kfEaBok8y%2B1kkYCeeDQnIEyQI2nUrlDE3kkDT3PzsfZhXMoxZHGw2OmTRl7w%2BSpLeQoW8gexttwNi7C6ewO9hD7%2FusTaELr8eOAMA%2BA1nJtTNAj6jJKAAZEs8WgqihJRgX9wJHOkYoXkf8iwR2RiKKqRRiitWw3lYdnr30cDzNae%2F8Tw%2F1L3sS5gFALINXpKDQgmp1pQxW86M3O8aoqMTlNtTGnSjATM2tjXEgCYfS3hKyuCkFHkzBeScI6WKhFVxLuD%2BEQLt4TkOo6CU5f1drrhvrrVly%2FdspDayfe%2B8EtQx7fuJG0HcbZLyyc1r%2B5qXbojtE1xa0dt4x%2F5c31r9hA6MYtP5DrVgijoiV5Po6KKs3MBOCVStFlgez8bG57v8%2Fvq4tZ%2FGilfr8pX7VqJm1EzJQGeg3j5%2FxX8ruWMbrG4oduFyXxMEFyQlkpkMeJTvhKbCMY1j%2Fo2ykPlEmSr335KxvYPvbZydev29P65KNrX58%2Bc92zfxv6%2BKil76PnU1Sl6fe%2Bl694%2F%2FzIweMjUO1ZPnH2TU3fxqa09%2Bl%2F6OHXAQgEAaSZuhddMDiaZ1epkRAzpTKAxyVzrnGh7JLreGi7qF1VqO5WvoGQ0DwF584uo3cpz4sCBzc9T9SAQPKgoqI082X2QfxhshCzXmZ5Jmoo6MvOYAk7gCWH6cudN5%2B98oSroZZNBoRWbuEw1ygDmqI9OZ36aJrbbTPYqIFmZrldRpdFA27ONADF4%2FHXxjyKYhkRU9LgYsIJ6e%2BpgHAkGUjkgUhLSBg2N9w3IMwpylMaKScT%2Fn6efcC%2BPLN8xActmMGOhu%2B4bH6EpsV%2FyAgOoO0n9%2F%2BHnR2B5h7hr455LAPJ1%2Bwc%2B1i1AYGhXOs6eQf4IR%2BuigYUp8WSlweZTnAWFNpz6mJ2u4d60kbEPGnUwENEvUTbVJbqTCjIAQJlPo8IXEUNdQEJcCAhMvd%2Fgvy8Q3E6TmsbErv%2B%2BZ2tRuuN%2F7f1X%2BzsNyv%2FvYhoN066sbVlcRuZiq%2FiWvuP7rEb%2F7LuhyPfsFPLMffdxfMnz7%2B1fu5qEc0RPdM6QIHLo14FgCDKRFYNMiWU1MaoAsLfupYpQwobhpDby4OfkoJ4iZQWPyy9jNLm8wLSdEtUyzvBB3lwOVwbLXYqnl6U%2Bo3%2BQo%2FHnp1ttBtL%2BihOZyBQXGwBS0Z9zJIGwfoYXGwTYYlLnVeWdKFwoCSqAj0%2FLqoW8qk7kShFiku3kK9cfCPVHyDedt%2FqpeyLL06zk4uXtU1DyfXfE2fPmrng0Ccjbhg%2Bflxtq7zz3ZUzXhrU%2FO6sjqN73mrbXD2iY%2FKzm89vbBp7Y%2F3VcwaOI3vqq674XdnlYysH1Ym8GajvcgekQQFURnOzZJfFEgyCCwqLtNy6mKZRrzd9RMyrUkMdR%2BNfdbfu7DIBzCIaw0J5kS16edcXuNOdBXwbyU1J1ewxtvTOqxtHP%2F3%2BJIOl3xOz3v0nmr9Y%2Bf2d8VNjp4xrbbm7jQ5mdazJdtYzasufW2r%2B83%2FH0fEE%2B3DTXbdNum1%2BHfd4stOSZuvMURh1OXnyAPjtnsaYXeumMPAnaOwXTOb4NVYT72PqU%2BxG7xcf6mPNQAQX6%2FIUcHKmcllV1UUlBRXFZdIaYyZNUjgzJ6Rpm8u6mKrApzM0vUgYbrTrbF2SFHbS18Xa5GhSmF5P7JYqZODSiqKajIK%2FVYNEqQIEZRigFxShVFwJURhGD6JU0ZlDP443kvW7ccNSPH2abWFfCns140peoYDeNeZHHSqlRgkMcp00ViJSV30QKhkjagSue7JMQH4304%2FFkrTgKC9Tjh69VLueUScBrhFPNVAUJJTKEur6Ce0u1dCFuorNZH28UayJb2IaDjjNtKWsWmioXPicrpB365FYFc3LTU9PA%2BB2dlqdhUV2QCMFCAazGmNBl900ImaXkg7mVCR4KJVkyfpRJFR5F86oRckaXOFoe0m%2F7W6YevPVY5uWvzf1w3P7vm99YGyIHU4139VjH6ob1tLvqqpxR9u2r5m2onVI9RVXsHUX9eMTLkxQdnCc6AuVEIv2VCsq3G5XOGzt77rMZaWBtEDvNOgN0au8hkhEMg3QTPzqkVUq5feAklS7rOucMleiPU7ivc6kQtuiYCqrfNTdlVF8fxLxCKgtj3iUQC44%2BjrzOa06UfyDSESH3x2j106vnpWmTXnhlT1o%2BUfT%2Fqt9NdGau79%2FZhf73%2BexCP2T2Pz%2FZefZXez6I%2FgIyv%2FEkRs7Yf3IFpM1FG27n5x%2B%2BNQ9Q%2FotPPTGQSQBH%2FPd%2F9Yf%2Fvjjne1sx152gh0p6f3eKHwYW3%2FEZZ93sA627uCCpcfMzwj7AIC8WN4IKljh6miAWKkBQZHNZgqip6CSZLOSmpjVSs0yBZocIpTouZRiZWGortKL8gsDiITjI5Uik%2BLHJ7FXiYTziRJnywoMgWdwNFstbzxXRcbikdvy72CqiPvXAaQznI%2Ft4Idczsm9VLdbktKzzeY83vfZ7QGDlqalDY9ZNLRSTbODPb0mZneCvyYG9BLcSxY9KQVDSTe5ArmSp7voCQYwWfE4HPqnwOu4AyOYNn%2FC%2FfPZh2fjx7C84%2FaZ8xev2nXHraxT3vDKpkVrHaacdQ%2B%2B%2FxGdXTuy8Zr4NrZo3PgNgDCXI%2FUBnh9eKI36VZeLN%2BNWnxscUBNzSKpskmtiJleyNBOvSfVEKuQRD2%2B0Iw4l2BUdoTI%2BZiikBS%2B9h9OfOtrxL7aJvdiOkQOHDrc2tEs72U%2FHmW846xyGi3DSZ3j9azd1FvUDImwoz%2BE2NIBd1OtGAIdVkjTZUhOTqWTlLbMzaamUcEELnGVzAbVA0BHKleew8ew2Ng534wR8gL3Dxq5ZjO%2FxGuQP7A55A7ubrcHDnUMBdY8RLs0Mg6L5BgnAqphMiBbFWBOzKNxLAnII3zehaKqJofOXXkp5iCsitPAkbol0bqDV8RN4ijmIm4tl7zK2BLqkUsalGqFvNN1AqVkBQDQJoSl5QlZS0MVSLhaCX7P9dHD8OHKMEwKWxLu8KBdxL6ZDTbQo3e8nNquVEFemy2DIsGlmjQdbOr9BNkt%2Br%2BzlsmTu1FB3wd0z5VlnstgW8BBwKLpv9YJL5RlPdMKNOALkU1L14E93sr%2ByVfg43vTxgZtW%2FGXnd1vevKGVHafhuOnyAlyMU3AcPjDybB377rOT591Y2mUHeYJu%2FUg004jIzW%2BQJFm2GGhNrMaABoNsUijK3QmbMnfKFN2XPIHtjr%2FNdmE5uRrDZG78Xj5t2EIGAOCFiawBT%2BozgRw%2BbSAGXiPLwM0MRsr79e4NCw4Rxa5IJL6kRnJurq0bOKEZy79hDV4k7gVL5JHn1l4AdgYS%2BtfxVS0wMJpjIcRkNiOAzUBl2cq%2FUrNZoXwP3VtwpgBXF1eWAOXEQAdVfSMRDKBcx1awhYvEZm7FB7CZETKxJf4D39CN6%2FHf8XkJ6VIlly6LPUkqBVCQArccJKJUl6GXoPq6r3PD1MsbzldfSPxvRcyR3dAvmukGo9nI1bbxUPHKisdJjEQxq9QGilBcN36X0mUp6hA6Y9DpEYujXuXykscVRBpkK4wudhzbcaSC07GdfUgtRrZEms9Wzok3cw1WSi3nqklH6R3oPr8kYcedOm6WR9NMYETFagVwUFlRVM1MVW5RVLtHv11adI%2FEnAKwL1KEcM%2FJO9nv43fpSiwh81U7%2BqQGdrQtXseFv4FZvycdQPQ8%2BVKfDHgE0jgAfBZF8RpdNTGjRO01Mer6daQROSBexQQy16Hxpkj%2Bkj3BXubXE3gz1vNr%2FPlDb76Bs9nSNzaSY%2BxxdivejVP5tZCj0mP%2FOYvf4smfoAvtpHU62rkEFkhGowdsNrvdbQXBV3ZNM9TENGr%2FTSzoRn%2FZLXHoEyAo4ckJSx%2Bau%2BBBspEdYacX8yA6iCb0UGXmlKkTd504Fz8rb%2FgchAXYat0CdkjjEZynUFmSCDVIJg9AhmYypVOVEwBXRFK5UWSV22N7Ev4uHU92T9OQe%2BLX7PPaKziWzWZnfL9pJMZW1bO5OPS3LSUP1S3lg9poocvnk0ySppm8njQw8cTzu4wWMA6PAZgtFm40C%2FWaRcikzJbSWfPzuXKqQ0sxKLdfgl3BF0A82brsgaXLW7gB12EPzH7oTqxuZWvZKtp73M0Tm%2BPz4vvlDUeOLdxZwVwPk1KRVS2cQX0ce4s4n%2BRlpKcHICC7LeCGy4rdAbAELNlGX3ZNzCdRYyq%2BuhvwVHHWrRpn%2BIvGGoVFl%2FMhDadWMcJP9LZen9cr%2Bdin7JuOx%2FZeN2FqnzFL7767DtWvZu2f2TrnyermlsJrn977BC7f%2Flkz5g4srx3e8%2Borqypveeqmzf8qL%2F13n8KGgcUDKqrHbRP6FwNIYiqrimdLCgBFNBhVKlHOuxSdv3y2lARgcoLtYrOlOn53IGEMEF7k%2BdXC13JCQdThQHSbDQaX08hRhsdSYuuXVBAOtyLx4BHI6%2B6CYLnlEXbyLfYFex%2FD9zz7BAf0ztqVZ%2B7EwHn6YufCPz33%2FDraBqjXfyHBI2K%2BRonRKAOiVZYkC3BDJ%2Bq9VNpUJOaj%2BsXtVx6h57CC2dmLTMMKdPlKFXO0a4DY%2BdTwvZeN%2FqJLhrqRy8gSsx%2BT0e52yQh%2Bv2ynlszMrKwci9mcnemSzdRvt6NJiOSi%2BEtCbgo1UyM3WkiKOMKJUtMlGvCIi78nPihD2fPbzWFJ6WPdxqngfix9q9Sr9HQdwoJDth5mUy%2Fnm1hKoRixV%2FmpUJxwVT85trLi1EAa6twb%2BaS%2B9uuhNBsStmnSbVMVzTXLnPpUo6oYTYpJ0C2VLGYDkWXJqFCUkhDL9evG%2BooUZ3VpjZj8Izex59h6fnXg56wfNmF%2FDGMtC5Pi%2BGHyHdka%2F47Y4j27dJCYyF2B7wZVlZEQEERvNFFF4QqiSgVDdslOjEH5Z65AarLLowIDZAGWchEZbA%2FLwDo6mozsXBTfQUqoXleVJiZ0RugfzTJISFUVEExmlYuSRP1I0IAGUcZdOgxNpl1qFqqPbALSzPPvkbfjTVJ6vIrs30m%2FRXi%2F0ykkLWUbyWw9T7KjVgXRIIFRJlTBfN2EuvH0BNZX4iUpmc0y8bOPPmIblXMHz60Xa1gA6MDkVFt%2FZIKYnGpfnBa6sUmAHY9%2FmJhqI4S4fJ%2BQL55xoKIY%2BVYNoOZTiaaCvQtCfCFHMMy1CH34IX7GMmfKjQd%2FUoR8AzFIA%2BR3QIHeUTdBWVYkSTznFd6SVJko0DW%2BxLKLeyTRZYcwiGjADQ%2FjqVO8uP6KGOiGzmqyKN4maq1OtpHWXhja9SRIRonoRhEaJZ5K0NrOFyl%2F%2FvMAAGKNdIQ%2BqATAwK1gBjVKRVTIdwCUpB%2FrioP0XWLww7EvHPD6PGRL5ZkqbKpcLx3ptW2gZ%2Fz7GYIdmjju9pfm6E8Zq6OFTovBQvLy%2FP78LIMhaEkbFrNYZLfbPjjm5jWdnDM4JnvBk0Az%2Fy%2BZVYSeXlcUJWdMvMcN9%2B1u8h0omny9N6YT%2BhuGr1r0xzd%2BOr%2F5xbv%2FOn7T8Y9PswO%2FX3znY5MWPHHDsNfXvfono1K6rn7f%2BK3vx32E27h55MJbxwOBFVznDsUNTsjh7BvIojRg1Mw2n89szrWA2WPUFFDSh8QUL7iGxEC7mCz83SHi7H5mUeZ0aISzRVANCgTlw1AfH9d2D8WobftHX%2B7YNsMT%2BhpLLZbJM2ZOJJNvaZk%2BQ5rNdrPv2XH2t6XzFTdbPuiJ9jP3rwh0PPOXNWvWAMLoCyfoMWk2eDi6esRYymclxCubh8RkDexcM%2B%2BlZZJuOTk32SdwmnJoYkjgUBQyIf4DZqJx81Mjh9525cmTzcuHVf%2FBTQZgFvauOZFVwBH49ZIydr4kH4iQK81M2CcaDRi9Gi%2BobTZhqFy7xwIOIyi6fTTdPt5ft4%2BoT4Q%2BecShOXlPGioU%2FBLkji3iOnVPiAnZ9vHnOw9ON%2Fmw7Jv%2B1omT5kyVp7dNmDnLjWVoRx7zq9vG4YSfTjyy5vt7ViWNk9BynD61y%2BDMEKROSUpzOLKcJlOm3%2BOkzuoYFVUUVMesmuoZHFNTel5aloiry3bI3RbgrbNeR4XKwOMJ6AVAxMMtOP2GaQZcT2aVs%2B%2FY3zDt7LdoiJfID985vmNc3Qb61PyZM%2Bd3NmAPdGAahth3Jx%2B789Eel5%2B4rCjB7nSOkgMeuCKa7SZElSn1%2BqwAPhndyHVz283akJgZqJ4bgp8v7QVDiRwWFgxH9KfOeieocBWpiZ1l%2B9eu3bj%2Fufm1o2uv6ocGOq9zCZ23rKHh3ZdLPsoafsVgoKAwtzSV26sYyiEKd0SrzFlZAwZIfRwOUqzmSkGUpIHpPXr4fJFg8Kp0K1jRqlj7qv2GxYy5Eke5wr7FpDpWXFxYWDksVqi5e1fH3BkXz%2Bn4pxIOWz79gRHv0LneqJs2FQ76ewKfPao%2BpSsqEvmsj%2BykQFfCF6ZeRcGFyUQK8v26El%2F4WGzqS33OfxjpXbL2ndc3sTfYvm9%2BvP3WksHVg5tvOnmsZKGTFc2buvrNabOfa5w5%2Fdrrmura10otT%2FceNqZjJ5Xzew187smt%2F1i1bPw9We5Roeh1xYVrZ732vkM6L1UOHVlb2WcEHT5q0qRRuwBhBYC0lmeDB8LRdATw2Y0Wg8Fo9Nolp1MaEnNqJkCjR6D%2FJfU5336yUOPaKqJJEuCQeFQirWX7O%2B6YxfZjqapqE%2F61bQ958LsXt8S%2F40CwpeDekav%2Fvh0ILAPAD7lsA1jEZFcyGsFksprtJg9Rr4kR6DJ%2FZWoO7uobKtNnnyJUlrW3X3ttO14phMgLHn98yIjzPqkFgFxoY259XSt4oSTqd%2FL0JgaDT%2FNcE9PAaBctOk%2FsjOTEKYEwCRGJxwB6tajQpMDBcxoHXzN8CJbum6GLZe60066mRmnd%2BeJXN6mThXRIWPMH%2FUn%2BNdGgxLmTUKrIsmYzWa0Gg8lkN4P41WCzUcXkofbu2oTf3cjSZdpuokXRuGOyi1dx22KswGZWhYd5AffOIrF9jYxdh40sI74Et93MVivueDXr0gYPcG0ouF4DRIkAevQioLvExgPivyvuhO7qQJ5BQRgeLXS7XPrsKDMzI6PAajSaTPkuq9WRKzu46XwOzWzPRJNH7%2BG7krl7%2BOC8ePqbjJDCRIiEfKFykdziVfBd8q%2Bke9n%2B%2BuvnTGL7vy529F437Xwso%2FdL097ZwvbVXz9jOnlw3rz12%2BLfSS1Lh1%2B%2FurZpy%2BF4kfhtxYuQjGCut1tMFxHAq6vrscoOoatQFU0Xx29SyV%2FXLRG8TS0ierkyof%2BZtWWXEPbn7boC9dce3JHE5yf0pzhpostXLJYMcLnSvcYhMa9mp0Nidu8vu%2FxUrvPeVQMOCCQs6MzrxGVT5986ecr8W6dQmX3ELvzxh7swGyl%2FI6Xt6%2F70Qnv7mhfYKbbnQTS8jE7s8wA7B4LrOep1cC1ckMMn1Hl%2BRVFNlKpZmqrlcuQEq9U9hBOEwa5mQEaKzBKmSBWoSQVlTvPepDFCnPndRKFJtuemosq2GZrG9p%2FtaZv8wfaPbt58TGf7vePdSx%2Fwsv5K9SPtbB87%2FT%2Fs7H10mU722JDgM67pTN1euaIq8dIsyh%2BTpOUZ%2Bfg6PcNnz%2FZanE5V4I0FhsQsv8m6iSfIBUmS5S2dL8HBXl8ook%2BLIkFBaLdMkafPPzxZ2v7R5zsmPXeFIQMJ22e1lq48uri9oOMZ9uLa9lNYiho3Z9%2B6xqU%2FbcBDAybXN3ZFFJ3LddVEh0mcejw5BCxZZVnUS7wGFxqlMrTMRy%2BJIqpdWewrCD%2B6iu3%2Fsre97yvSbCP7xLR8SXyH1LKxZTYkqp%2F1XIZ4dpmjpLktAEU5bnchWNw5lhxTli9rcMynUdPgGPX%2BvJ2%2F2BgiqPTHK2HB5clePsGgXCkPt082oetPnbx1%2FbDrDtW395oycuG8yJd%2F3%2FXu6MZHa5Zcv2zRrf2wZn1HILfzsvKx%2Bb0rCstHz73%2B8VXN%2F8y%2F%2FJriK%2FqHR%2F%2B30LeE6xuRa8AjToRYDHa7y2UyEIfB4fWZnHbn4JjVYrfL3HVyQt3QpktOVnRhgnBcxKOXvoLpIyFPwCO6cjK3bsas9tdeeHRt8xasYDuu%2BTD4aeiNN0jGwgknTn4e%2F%2FyqK4UOT%2FGc4zM%2BcENZ1E8cDrfby3t%2Fj9NoJ7JNtumyPcmJ1sVDgItr7tQYgH%2BgrxdrpR2zt72PpSLjsXRp7XUHt5Mj8dki4Ynt%2FEpI9JkPcrlm6BV1m0GWiYgIK0G0GNEuC5llKWndDU1X%2Fx0SbTfiOtaElf%2FINyryZYexkjVJLfFF86aMXUzaumS4AZRtXEaWOMsoSyaOIVng81ETVTMyMjNzVEXJ9plMVLbbMxQ7yDqidR3RdPz2LIDSIO1WQ8wBsin%2FpGskRZpuUfew19lm7LMwJ1eRcrT7sG6R5NCsqBgvN92NPdk7uARPdt4vtTDH4m9q1lxH%2FPGvvE03jMkcer4XnuKKI5gApOW6bWqi%2BYoMaKSUSAQlGWWzQVWtfIZmMSoUAA1mj4T2S2cBqaROkYZeq3KlhdkClOu%2FmD2BI48cxZHsMWxja46fYO2kPwmyZ7A1fiy%2BDRewhcJLzK17ycs1KTC73ZrXK0koahm%2FJgob%2FpNT8no0p9XJMTHDAFyVskQJkKKvhBlTUzxHyokifvTqgNsSaw9mmBRz7n4cwoqu%2BvcfR9RErqqfl%2Bfkfr2%2FYcZNo8ic866XXnR8Z72xNZI450HXce2MIn%2BoKqkIYDYgmvQhAm8c7YR%2FMwyOoefSIULSSMJGySlCWEwR6LrOB4nC0uhAZiCmDrLp6%2B3xekDI4T38Id7D54ipCHUbcnIcfn%2BuNTMzIFGXy8qjKd9qSbTzYosp2hbbF7bnuBrm%2BREWRw08Coc18VTQ4xFQ6%2BEJhDmL2m6%2Fc%2FOZG4cpn31T3XpmM9quH32qucGAVz7Z9jEdXMUObcyzBF8xskNVg%2BknbU8BIO5gJWSlYgMK7tcIpZJMAaCyhONDYlbqCOKOo0cV29lA1ylOauB7yBN7yOHlOmgGQ75bkoI52TabW3Z7qCzl%2F3%2F2IIuHzuFynuSi2BZnlftyiBSnzxyCyzwcrImh4e0Xbhz2%2B9mfKtWtL7xTP39x26LeM2aFPyFVQ7CnuWmyw5K3EXsOrqIfh2dPY5tNjY2nGm7QTxGQIqmCtoEHIlG%2FAg4zmKnd7qNeu82mSJSaHQ5QoCRU1lYi9ElBdqqp5pwa1sv%2FRAMmELwQB0baym968pqFwxaOC99ePv7pgf89chFZcXX5l1NzcyPRii%2Bnphf8lzhBwpbiQanl0rP6Dg26zurbad4v56mukCugE0Wi7Vh7JsTasSV5lIO0dJbKBcljHAhLOdJqfN6cwad7QYchPV3OyCA%2Bn4mYMrPSXCNiBtuIGMiGNH4pGWmKygXqpwH4S8%2BePzvOII575nOCTh4R15lS69q26gmSEBt94OCr7YtF6z7vlm8b7mpdcN%2BrL%2FfHcyhjZk77c8arjmflv%2FBn9kZObzbAuFFEB4A0ST%2Bd2BztZXeaidFqTfd6iV%2FzO51ado7Fn%2BavjxnT0sDFqcleG3P6QR7xs%2BNNXUfUIJTSVqjbjT%2BpBpRfbpXXFSKawsFwiBuQbNyyZcyzs2sbcS679w9k3%2Fmvbhr%2B6qufy7sbvojGrt10dOm6WtZ5ttes1keObtl5BAjMBCYFpHXcnkW8R87TLC6j7EsnBrDZ8jIhM%2FOyYp9LSycWo2xQPZ4ctYBHz%2FYyHc11H2qb9S%2BiA4oURXyC3SM%2B0WGqPrVIoJJaFCmMXFRdbixfuGzBqEk3j1qwfGE43Pbogt%2BNn93Y9siC8v1T6%2BqnzxxRO50cnPC7BcsWhCMLly6MTZs8uu2RtlBo%2FiNtYyYOnz6ttm7aDBHpCoDEp%2BPghZnR%2F7I53U6Plce2UaYyMYkJqxeRED%2FHBp%2FidDkbYkCRuuwmm93WEFPtdgt6FMsl5xX9mtiW3kNfypcpEhAfkgPKkCfoEXdAGF7cGCBD0YAVbOGWH374gX38448%2FvsOW4BViZBv3vHrfq8eO8RdyHMhFiKNCMGoniiKGmUaJSlTVsUcEbCpFdAhyJGBIAFHnAbag8wAAgUm89lnw%2F0o5D7g2jvTvPzOzu9KCJNSFaAKEBMYHAokSuQpiY04OODjYsWxCcjbkNaluuPdyiXuaS0jHpPfeE0N68fVO%2FObSe%2B8uy39mVlqEzr76oeyi%2BbG7U3bK83yfkUZBGZwCMyKlaRaXRRTLC6E4JyfkAld4DKmpsbkrK0ttpSafxzc15nHqTVNjepQycUvmivi5NiuyMYtA0qyNo3NOVr9OFfZJmt75WUW7VMhOWtE4fsubj9zRP33SzuaW6LxFB3rWTJj4xSuvXdHyYsOAb%2Fbpj257c%2BOS5s4tvmrim7appHXPputbn8kPlVdURssit194%2FxklXdGr7p3261Hh7uKKUGH0uu2nzi8Pxya1V5qmAUYu4UfygiRwVi0%2FYrQaWIvIdGcQ4pBB7dzU9snCdpLZJF%2FSOXJNjdRPPa0uMhVd2TKurqk5Mq5FXFPXEB0%2F7ucNExvqGieOb6wDIIw7lSbR99oBPqhmvm9ikm0mm7%2Fc7yzPc%2BbV1IrpYEmnX1mlhbZglpActKMVbEo36zBrHWyifBGnSASrw44ZvIhr6bwgFCxiuH4R45HIul%2Bc91p4c3j55tf%2FfvilPddGFx5b8zJqf5X9DCi9v%2Fm10vvcrj6U09uHsg%2F0Ke%2F29invHSBfX7VJ%2BTAv99nwkcNvfNd82xjlI%2F4%2FSu%2BrLyi3%2FObXaPaLTJb0b6xlBfCX%2BDHKMLqgAOoieZk65HLlmXXU56PLK%2FRmGI2e9HQbys4GEGweShSEA0F1mAtak3BQbR1SPGxVVo3K6irbp3YM1ToJV3pGr452r7n58XnrWi6tr79h3tY9yqTy%2FKbYvMvxsYvGRLrPu%2FBCWegef0l%2BcNcmpeGP%2FqIz6oqkNPas06Fd6BEEkMAIbZHRaUaDTKd2RMKCgERqGDdkGNkrBpBGCE4XBIMoIpOMsR4lWko4kLBqJI%2BK5j8Faab66Q897w8yR4ALIR3yqYfpaPGg8hFyDSo70RG06A12%2FoayC49HL1E%2Fs9K3DL2QNXzKGb8fhTCZCCJkRZgzSkcQkogAAdYJoQTf6LXQWZQQHjx2hLz1I7pgEIaGErEHWAIzAAhaezTEW%2BS5kUqBYFHUgcViJEbamxB9uT%2FROLFE8QLBIegdsp5%2BnaSN8spKbara53ErgY4FlFnoIwadmhP5X7VaYcvuz5QHAu8h%2FcO3K%2Bs89eFTJuceP%2Bdft9utd0xUFqDpyj3kqh3K1%2BH6uhrlzX%2FZctHQEckuSNLhJG8MjPTGCNLRbwWDZH%2BFr%2F6Jm7D5hAmyIDMiQ0ZGTrbVkMkqRQ3FUq17vL06HSowmDyctbXd2N5201ln3XjW5a88G6uvnz2nLjJHWMg%2B7W0766bZL10emd02YWJ7G%2BNFAYSwiCGdcx%2BZGTqdRB35BoSomd9sMRrSZYQkAYOKeoYC8S5MM5WnxriwyfZwnAs9I2%2Fh3kG0RVlFY12UNylYiiCAo%2FgZTriVRKwOA5LAgiyuTNnkwQ4Hyucer4lJXb96j39EPHUF%2BJnjK%2F5%2BbriipGXeqiuf3np9%2B4YudA6O3jbYEQv6S2bt37Cle8be7rMBwVgcxo%2BIr4APJkRy7enY7QbIl%2FLTzVK65C8mdrvDIed4PSa5IIE5pbQ8dlABTRX6S6xu1DgHrezj3QjuuaN9%2Fn1P7N541ards5oXtJ3REgwFWsOdE%2Fb9v3W9wlu7a432i6at2N7wzOzzq6tvrAr76ePuDExYn%2BqLI0JEDyCnCdwXdyjui3uFjR%2FVNMjMIUk6ao6YiGZWHZ0i%2FDX75U5H1aEgAOK2LmrkhkxmMUmXJFnOsjrBQR%2FdrXNlOGl7yiCq4Y2Z%2BzTTkbYwT8qwtv73xo0CxS6XhZtDZ7WvpVaAD0ZnlC6fNWF%2Bvigy%2Byj67YoVdz%2FPrAF7Z8wo%2F9mM65SDUhQQLFSOCbslO2RAIOJINwsiAoTMFr0emUykKWYSWc8XiHtk4gMlbe5qgAb7UsMIa0IFwu6bbumd0PqX1%2F72IW5Tjkmn%2F3QfCVmPHEWCwiKd8Cj0e7KGEUURmUU6Ebk1RiCQCHSypSLhfEr%2F%2B2Eqe2hQsaNeALBCVcRlNjI7Fh1Y7Gaz0W60ySYW9pXNXt9QQI0EXB1%2F3PjAIiZPQYprQ3RWgnr3Xd88KXuOu%2FGW5v7s6Kwj6xc5btOZJpzh7hmf2cktXDiKGxPRSYI8MjopD%2BWfMDoJeePRSb4QbvyciNkVzReismdxFD2z4Oyi0vHr6MwOwnTUfEt8ic9KPBFjIvYqgzhkDw%2FxTGK3kxc9YlKPgt969IarH3%2FwwP4nFG9dY%2BPEiY2NdULbnf0v3Hr7wAu3dHR2dnTMm5cy6s2OlKZTy49OL2AW1Ib01FNiGh70BD7YIdHEB79%2FOej1B9UBL%2B6NL0aoFonqQehRdg4ip%2FLxIFqsSMPn2KuMXYbaUNsyJZw1fMrGrnIA6Qpa2n5Y%2BTuAYvg1fgUA6eAP5Nrjj4L8IMFW%2BuJUVye0D51Au5h8T7W6B7CZSZlyNlXeJ75ClUs8XEnM8as%2BEb9qmXpVwDBeWUH%2BLLTzNU5DpKiQug4YJk0jh0pMoyDbnI1lQp0JPk9rzJdhoRy8xZvKwaN4g9Cm5HHsnddbrUub3bCVWHLF4ldiF1wYPjM27aFzzp37w3lvHP3F7rOrUcnw6jY6d1dT86yJ4eiY0sOnTO6%2F%2FYLru%2Bj0cyyamXhHhoZU2lu3GPuhiOexHiQ0HfQPYqfoh9HVJ1B0w2%2F%2FheIgzFQV2SMV52iKgYTCOlIxU1N0cUXaQwR7uWRYkxbXSNDfPYvXhpfEa4MpdD7OPtrg4sg4yUbMNmIRLCjNZEJsvgbgEETRbiYUvqb4syENGQkj%2FJFkkzkxTAQrMmlscsKiQLvUAAeUNb8G7yQ062PCs0QKkEYsI9rR6nzH9imOvcoLeLew9%2FghbKIUT%2BhoLlq5jiPvcYqZDnXNrC6WKXZGjNP8%2BVlGYAXOBfY556p5%2BZaodTT0KC89ZE%2BUXqqiG9pSFPdShT1JcXDoO1XhHnmNmZqia%2BgnXgMYFag1wGbucZ7cAJnQGCmivUCW3ep0GlBamtthAIqVWwGovcRJi9eKLYy8TgmP0%2BBgddahWmkscQqUlpiPo4MhBwPPA1tV5FzFz7cKwm9%2Bd%2BCzzzahATIdd1Du%2FG5GoOPWnR9%2BofQoyl1qHsRXeDuriLez36eUA%2BdUeTlUxtt7N1fgvJMpulHDv1AchOdUhXek4hxNMZBQZI1UzNQUXVzB2vvoeGkj2IAMglnogXTIjaRLBGTZYORGZXcgqMUn8260FqnLBlSM7lL%2BuB%2BVocqr6Rhetkf5tfL7vfj3qKxH%2BSMavZf%2B%2BVuaSiUAhD7DLeIHkgA2yIZCCEdyXJ4cuz0tB9LAW%2BTMK3Ab3QxXJQWpdOWImbyK8arGGFaJqpEG2V2IO%2FyqihEFV1Wm94Xts3tnv8iA1RevaL1x1sDRP56CjrR2UWL1%2FZBiOG0%2BWqzyvXWXXHDpANrEwNWGNfM3DSi%2FfHYJ%2Frbsp%2B8e6j5uKR4aUmlIXgO18Vocrdaz1uOkKrqR6V8oDkKPqsgfqZipKbq4gr0RJcl9kqDwq4yNv3kb1KtYuCSJSmbrqZpIDiOjjbIoSpJTMDbFZEdTTJAFWdIRyZowKGrdjOZBjePIDroW0tZGwh2UUz1yNcPaH1CQ4fikjst3rbt0NcHv%2FagMUij5c2Vc18rz5%2FNZJM3JfMkD1dAaGU3tegXFxQDlWSZTbXkgUGPKKtBBcbEui2SWhkqnxEIQcFgyozFLwnGq7ZUx0g03TH%2FaTYLqcnOkuuX8iaFL8zhXsVAn4a3SSDRSWl1%2FRVfoo3fmXTau%2BubIbfnTo2vnNjQ0TVjXsWQjbb4%2BhL9FfuGvkV%2BcNqai1JldVTJn7srmu%2B7JLfy6KLhqVGhcaeOylsh5lbWnl49r6TrnKPVMv%2FLO%2FazH5ASbVEBr5VQ%2BUtQfAPb2jbbEazY1vfvCE6Xna%2BkHfxhi6RUj001a%2BkAasPTikemClt4lAX%2B3T%2BGCYcUDmqJ%2FlKrwqwogTCEpQjeUQBBOgS2RydU1JDM%2FP2g3GoNBuabG7%2FGMKZPlsC%2FfW50fjVVXsyDp7OxQNJZtNo6aSoF3p%2BS0NFDHPHgbYiBJgQZGv%2FERLZmZ0t5q6wkJKnqMhzBz8MufZG0ZXsZRzHYYrWJk1TDShwoZfiVWbn2rce4L19%2F03NdfPRtr2nHzvKc%2Femdx%2Fd3LDyM4XkaJq%2Bcfm%2FbY8bqFq1fv6FyOvX%2B1oHvwefbOru7Y0zcz5q91cn3Tq52bInXKZx9RCGvWp8UlOEsQzpxD6T%2F05acLVrNap952xtZhP0xWx0%2B0iY%2BfnCrjtT1FbQ2389oqStRWanr34n%2BeflDP00eNTBe09C6rWpeVidoeugYAvcGv8LTaXynTgF0DGRLXuBwA%2Fy5J0T00eaRi6JdU8UmS4qDyuqqwJBTvUMXlkqApuriC9Vdu9UkSBIfk5fPVpZGx4MYuV46oJ%2BkEY0tOTnr6qEKLpcQNmZh%2BSJ2ImdjppB56CnnSKS02%2BRpiJifBU2MEnYC8izsQ2clwI9I%2B1YYLf3Gtkw8SVgdtm4XAwyNdtX46hDAvXCL2GCmnN3ZetuitjjuuvUr5%2F0PfKX9DwuFDDfpT17zfga0rz19x8fIFq84TXdXF99Wdtr1n%2Fm5lz4fKh8pLyPrJR8gyV%2Bhdtuva4%2FMv2Lj1ih27%2Blg74MwMf2tPV9%2FaEPAZUHI97ucl3KK2k5t4PReeOJ319ZfAyRW8pRiS%2BgUt3aSlD6jpeSPTBS29y6C2pIDWK8yCw0JYeIl7wbKhNGJ1pqWZBQEIyYUcNwVKAXHz0vPBYdBQiw8WTxJRTWOGj2%2BK1tf%2FPFpXNzVaf2ojO%2BKOwcEvTpva%2FPOG6c1EmNrUMqWhpRkIfcaHKAN0OZ81eEfOGnzxWQOjb0jBFAZx%2FC%2BzhmCNsJ9hQWsvOLVn0n5GBm1eUrt%2FzK5jR21o%2FOiJKy9AhwzKa%2F6alefjSoYJlXV2dVyL7IwUqpp%2BQes1ytH2RjTouvnWlnFKMOP2oSGVpeD1c2ZST4ByefGmpvMavgVOruA1XMnTC0emC1p6V0B9A0u1np977PkV5qi9zXh%2BBQ8XJOgmziYWsLhqD%2B1vHQZzli2Dxi8VWsCcbXDIRM6dEpOdxEnL%2BCQocxLLTDtnDWdWTT4Wyh0nAU7ot8Herhf%2F%2FuZLf5xv0ulUfvGjOONEDrXMYEgzK%2BCtE9qVsXpQVixvbB7mnLQ8CVqeut5Qc%2F0zNdcJKk9oH6byMk5M5VGJGk2mO108BE7wQmekxuJwGFF%2Bvs6WAeDL0umKLHa6drMgI7HQX0YznaWSNBddcwhCLotpRQ5tBcd%2BThplmiAy%2BBMMx2M6XcOLuERnVGvx%2B3WnH9vn31Wm9Cv3oTPQhPGbvaRDW9Q9dstdd%2FXVrfR7t8jpaBvqQuejTSZZXeCR145%2B8%2B1PDivZbnPyN%2BhT3SphMXhgNARhQWRMoMKEHQ6%2FX19RkWu3V%2BXr9aEchzvgiMYCATCbfxaNmc3YJNDOmfLEZnDT4VwQvFNiQupwHj45Cp00iOdT56kG4bniI7dDo6KTeT2fSk%2BLtyhf7dl5pPfHLSgb4QUvT7nsi2%2BR%2BbhTt2fL%2BU90tDx99FwN5Pu4fbWMBnC3%2FZprdiD9%2FciByqY1XcvYaf26naXlbOCeHGf7BhavuJhFHD0h%2FFXwSAVgZP0Zi5ozAMh6jE0ZWF4vsh39sg5pyx2NKqQzEZ2XGU%2BdFNAgrdc1Ne977elTUafn6kbhr2ed0XJ29tMLqh5sYBENqFX4M4lKD8Q9ehmS1eqmkUWyR8ay7CDxvRTYHVKNZ7qk8YhEdy1YcOklCy%2B67Pqa0tKaiorSGvGlCzavv%2BiCDZu7ykKhsrKqKkDwa%2BHPgkEygQuqIm4KNEUEQjLdBhvobPTrYvM6MzavFyCQ9fpZmoNENQebXw6qkISXvbF5mNVHiE23yjF6xRM27knfvXTUtKZoET%2B%2FfAk7F%2Buray7vKyjOr%2BKHAr4bGHqI3IN7%2BG5S%2BAS7SU0nbeih999Xlbp%2FqtQllG7Sj%2Fp4jIw7kiaIOqTTySBou5KZB5gLq7jGWhvCumKTs7N6sN5L%2Bp1zkG2h8t3HkHQFCVwRmQhIknSCRC8wvD8WUrffQHtNwbWDkz3iI84XlPdRySFI3luLeVIwEfnuWhIEtNuffHstwOzeZBl%2F%2BgzwRczUIGsiggSSZNFlkHRtI0Z%2BoT8E%2BbOoWSnwxY%2FoUzVPdILhSZyRP8ezp2Vz%2BE4SGJn%2FndpNDXwrMFMaMYjsRi%2BqN9Luoz60qB5QH885cqO31JNM8Ua1DBJFgVlJkOt5SRihMGIaeQcIpN7Ap91gROGgt0eWkkvbi2wunXrfKIyCdLA9wszuRplAgHssUq3uc6%2FavnXvvku37cGf9hzou3r%2FLbcAELbTizQXhfm75mXsYF6m6kEvys4gbKuXAofMQuS5LUhtbJnmP9AJy8gdX3yp56m7v%2BAps89kZzPacGPqPmctKUf%2BVkA7vpHbtCsijrgDV9RLQAg9pa0JI9VZmsxW0W%2FVN5vqlE12xKZeO24nRzp2bfoHPRPEf7z2SBs4vvHEBm8ApCxj83oe25YVSSeAEcaCFtqW8B8j5EX48mN%2F%2FIKMjge2AeK7BW0S%2B6EYdkQaJaL3%2BXI8RW5ntmywWIrSafaLika5cnP12dklBpdLzpRy83Knx0heRt66PJxOMvMy82yFPiiEabFCndlkMzXHbNp2YiNNoxZenyxzKUghO%2FCtQOhvro%2FH5DgKdA420DrVfS4oWELdb%2F7qWvq7BuL7XXhXXu9CVyrtGKN5yj0hZNq9ecn93ynPj9q6VMBLtvjQpG%2Be6ps7ebnwys5f3ucNFDzwTXgIxqK0Tx5wFVff9zVyT%2F%2FQ4%2BXsWgfzjp%2B0n6MTYDbdHRriMbs%2FSh7wQyNfQ04lboD45x8nfd7MPgcMBhzF34tPQRpYGbthFXUmWnBEBixim90k62TJikTRaiW6PJLPDTwBLSYu4RpNwn%2B8DhpfWI1CfA%2BzWrZnHP5%2BzefKBrTh0zXKHkmuzliH39q3rwfXHT%2FUN3Nu1gWuZ9Wn05u0pyuGRuJWn14KAMTT4QTpzcPp0q6k3PF0dS8BvtMDAcsjIIiIQGKXQLYPAt8FgTU2uvZ8EQDruB3sL%2FEV7krVDmZIWNNupYoPkxTdQ3NGKoYYgS4mKQ4q76sKS0JxHADfqZupKbq4gq9wuaT6%2FwCVeR0IAAAAAQAAAAEZmiehT9dfDzz1AAkIAAAAAADJQhegAAAAAMnoSqH7DP2oCo0IjQABAAkAAgAAAAAAAHgBY2BkYODo%2FbuCgYGr9zfPv0quXqAIKrgJAJZXBsIAeAFtkQOsGEEQhv%2Fbnd272rZtG0Ft27ZtW1G9dYMiamrbZlgrqN17M89K8uVfTna%2FoRs4AwCUGVBCU0zQl7DAlEIZWoPOfhXUs0BbVQAL1CG0ZepQd9STPdUW9dQ61FGN%2BU5LpOW1pswUpmU0hZj%2BTGOmWnQ2lPNyV2rEoO%2FA%2BmUw0CwATG8cNjkwyXzEYZrG9Of5NUyy%2BXBY7Q4Hm9a8tgCH%2FWU4bOcwPfmsjc7GvDcYPWk7StjU2G8qAf5xwHQE6D%2BzHRXUbqzi96bmrEQNEeim4V965jWnB%2Bho0sNRHnTn7E5H0V3nQAlaAGsawqkxWKfGhDPoO2Ts%2FGdwsk5fIecd011vh9O%2FOaegHO9toBWAfYLM5JBSxvoNquliyEeDvUucbeXvMd55vIqRtTGMJTnzAkP5bdnsXvTX6VGOPkbfYe%2ByRgh%2F6xHoLms6QDmmlvyFPThTB2PEtbczfMbr3XUu1JD7fmqUjaYre68jzpPD3wJIH6QH0RyQ5L6Ui%2FGeGFqDOZLiPj7iXnpkDsKJ5%2BTwO3LmEe8JYecb2fcazoXMC%2FEd4z0J7EFS3MdH3EuPJJX07gom%2Bff4%2FDMcpS1ee85bBLQNGO84cgiqPerpVcghUBEeK%2FS1jzBBfUZbwUv5X%2F7bkOlslqCEwJ5TBw4lBFsBJdRuHA4vYk%2Fown8RLYvLrQAAeAEc0jWMJFcQxvFnto%2F5LjEvHrdbmh2Kji9aPL4839TcKPNAa6mlZUyOmZk6lzbPJ3bo56%2F%2FCz%2BVaqqrat5rY8x7xnzxl3nvo%2B27jFnz8c%2FmI9Nmh2XBdMsilrBitsnD9rI8aiN5DI%2FjSftC9mIf9pMfIB4kHiI%2BhWfQY5aPAYYYYYwpcyfpMMX0aZzBWZzDeVygchGXcBlX8ApexWt4HW%2FgLbzNbnfwLt7DJ%2Fp0TX4%2BUucji1hCnY%2FU%2BcijVB7D46jzkb3Yh%2F3kB4gHiYeIT%2BEZ9JjlY4AhRhhjytxJOkwxfRpncBbncB4XqFzEJVzGFbyCV%2FEaXscbeAtvs9sdvIv3cjmftWavuWs2mg6byt3ooIsFOyx77Kos2kiWsIK%2FUVPDOjawiQmO4CgdxnAcJzClz2PVbNKsy2ZzvoncjQ66qE2kNpHaRJawgr9RU8M6NrCJCY6gNpFjOI4TmNIn36TNfGSH5RrssKtyN%2B59b410iF0sUFO0l2UJtY%2F8jU9rWMcGNjHBEUypf0z8mm7vZLvZaC%2FLzdhmV2XBvpBF25IlLJOvEFfRI%2BNjgCFGGGNK5Rs6Z7Ij%2F45yNzro4m9Ywzo2sIkJjuBj2ZnvLDdjGxntLLWzLGGZfIW4ih4ZHwMMMcIYUyq1s8xkl97bH0y3JkZyM36j%2F%2B58rvTQxwBDjDDGNzyVyX35Ccjd6KCLv2EN69jAJiY4go%2Flfr05F%2BUa7CCzGx10sYA9tiWLxCWs2BfyN%2BIa1rGBTUxwBEfpMIbjOIEpfdjHvGaTd9LJb0duRp2S1O1I3Y4sYZl8hbiKHhkfAwwxwhhTKt%2FQOZPfmY3%2F%2FSs3Y5tNpTpL9ZQeGR8DDDHCGN%2FwbCbdfHO5GbW51OZSm8sSlslXiKvokfExwBAjjDGlUpvLTBY0K5KbiDcT672SbXZY6k7lbnTQxQI1h%2B1FeZTKY3gcT2KvTWUf9pMZIB4kHiI%2BxcQzxGfpfA7P4wW8yG4eT%2FkYYIgRxvgb9TWsYwObmOAITlI%2Fxf7TOIOzOIfzuEDlIi7hMq7gFbyK1%2FA63sBbeJtvdwfv4j28zyaP8QmVL%2FimL%2FENJ5PJHt3RqtyMbbYlPfQxwBAjjPEN9ZksqkMqN6PuV7bZy7LDtuRudNDFwzx1FI%2FhcTzJp73Yh%2F3kB4gHiYeIT%2BEZ9JjlY4AhRhjjb1TWsI4NbGKCIzjJlCmcxhmcxTmcxwVcxCVcxhW8glfxGl7HG3gLbzPxDt7Fe%2FgY%2F%2Begvq0YCAEoCNa1n%2BKVyTUl3Q0uIhoe%2B3DnRfV7nXGOc5zjHOc4xznOcY5znOMc5zjHOc5xjnOc4xznOMc5znGOc5zjHOc4xznOcY5znOMc5zjHOc5xjnOc4xznOMc5znGOc5zjHOc4xznOcY5znOM8XZouTZemS1OAKcAUYAowBZgCTAHm3x31O7p3vNf5c1iXeBkEAQDFcbsJX0IqFBwK7tyEgkPC3R0K7hrXzsIhePPK%2F7c77jPM1yxSPua0WmuDzNcuNmuLtmq7sbyfsUu7De%2Fxu9fvvvDNfN3ioN9j5pq0ximd1hmd1TmlX7iky7qiq7qmG3pgXYd6pMd6oqd6pud6oZd6pdd6p%2Ff6oI%2F6pC%2FKSxvf9F0%2F1LFl1naRcwwzrAu7AHNarbW6oEu6rCu6qmu6ob9Y7xu%2BkbfHH1ZopCk25RVrhXKn4LCO6KiOGfvpd%2BR3is15xXmVWKGRptgaysQKpUwc1hEdVcpEysTI7xTbKHMcKzTSFDtCmVihkab4z0FdI0QQBAEUbRz6XLh3Lc7VcI%2FWN54IuxXFS97oH58%2BMBoclE1usbHHW77wlW985wcHHHLEMSecsUuPXMNRqfzib3pcllj5xd%2B0lSVW5nNIL3nF6389h%2BY5NG3Thja0oQ1taEMb2tCGNrQn%2BQwjrcwxM93gJre4Y89mvsdb3vGeD3zkE5%2F5wle%2B8Z0fHHDIEceccMaOX67wNz3747gObCQAQhCKdjlRzBVD5be7rwAmfOMQsUvPLj279OzSYBks49Ibl97In%2FHCuNDGO%2BNOW6qlWqqlWqqlWqqlWqqYUkwpphTzifnEfII92IM92IM92IM92IM92IM92I%2FD4%2FA4PA6Pw%2BPwODwOj8M%2Ff7kaaDXQyt7K3mqglcCVwNVAq4FWA60GWglZCVkJWQlZCVkJWQlZDbQyqhpoNdAPh3NAwCAAwwDM%2B7b2sg8kCjIO4zAO4zAO4zAO4zAO4zAO4zAO4zAO4zAO4zAO4zAO47AO67AO67AO67AO67AO67AO67AO67AO67AO67AO67AO63AO53AO53AO53AO53AO53AO53AO53AO53AO53AO53AO5xCHOMQhDnGIQxziEIc4xCEOcYhDHOIQhzjEIQ5xiEMd6lCHOtShDnWoQx3qUIc61KEOdahDHepQhzrUoQ6%2Fh%2BP6RpIjiKEoyOPvCARUoK9LctP5ZqXTop7q%2F6H%2F0H%2B4P9yfPz82bdm2Y9ee%2FT355bS3%2FdivDW9reFtDb4beDL0ZejP0ZujN0JuhN0Nvht4MvRl6M%2FRm6M3w1of3PVnJSlaykpWsZCUrWclKVrKSlaxkJStZySpWsYpVrGIVq1jFKlaxilWsYhWrWMUqVrGa1axmNatZzWpWs5rVrGY1q1nNalazmtWsYQ1rWMMa1rCGNaxhDWtYwxrWsIY1rGENa1nLWtaylrWsZS1rWcta1rKWtaxlLWtZyzrWsY51rGMd61jHOtaxjnWsYx3rWMc61rEeTf1o6kdTP%2F84rpMqCKAYhmH8Cfy2JjuLCPiYPDH1Y%2BrH1I%2BpH1M%2Fpn5M%2FZh6FEZhFEZhFEZhFEZhFEZhFFZhFVZhFVZhFVZhFVZhFVbhFE7hFE7hFE7hFE7hFE7hFCKgCChPHQFlc7I52ZxsTgQUAUVAEVAEFAFFQBFQBBQBRUARUAQUAUVAEVAEFAFFQBFQti5bl63L1mXrsnXZuggoAoqAIqAIKAKKgCKgCCgCioAioAgoAoqAIqAIKAKKgCKgCCgCyt5GQBFQBPTlwD7OEIaBKAxSOrmJVZa2TsJcwJ6r0%2F%2B9sBOGnTDshOF%2BDndyXG7k7vfh9%2Bn35fft978Thp2wKuqqqKtarmq58cYbb7zzzjvvfPDBBx988sknn3zxxRdfPHnyVPip8FPhp8JPhZ8KP78czLdxBDAMAMFc%2FbdAk4AERoMS5CpQOW82uWyPHexkJzvZyU52spOd7GQnu9jFLnaxi13sYhe72MVudrOb3exmN7vZzW52s8EGG2ywwQYbbLDBBnvZy172spe97GUve9nLJptssskmm2yyySabbLHFFltsscUWW2yxxX6%2B7P%2BrH%2Fqtf6%2B2Z3u2Z3u2Z3u2Z3u2Z3s%2BO66jKoYBGASA%2FiUFeLO2tqfgvhIgVkOshvj%2F8f%2FjF8VqiL8dqyG%2Bd4klllhiiSWWWGKJJY444ogjjjjiiCOO%2BPua0gPv7paRAHgBLcEDlNxQAADArI3Ydv7Vtm3btm3btm3btm3bD7VvBoIgLXVVqCf0ztXT9dzd3j3cvcX90CN5Snmae%2Fp45np2e356gbeH94HP8Q3x3feH%2FX38NwJwoHigQ2Ba4GBQCK4NfgxVDE0OnQr7w1nCI8P7wi8jdqR4ZGzkRDQSLRmdH%2F0UqxTrEVsbux%2FPHe8b3xh%2FlgglzESJRJfE6MS6ZChZJzkj%2BRouCA9GJKQuMhI5hsZRHR2A7kZ%2FYZWxldhtPDPeFd%2BIPybyE0OIy2SIrEy2IneSX8mvFKB6UpfodPQYeiOTjmnK3GOzsCPYpexaLjdXiRvBHeJ%2B8BX5Lvxe%2FqOACmWEnsJ60SsyYjqxiLhE3CoeE6%2BLL8RvUlRqJXWThkszpJXSbjkq83JaOZ9cXm4gd5IXKZACK4qSSSmiVFWmq0lVUtOr%2BdXyagO1oxbRSM3UsmnFtOpaC62nNkqbo7M60HPppfXaemu9j77X4IwUI49RxqhrtDWOGzeM92Y985lFWWWtcdZia4d10%2FpiU3YZu6%2B91j7rME5xp5szGVAgDcgBioDhYDpYDjaDE%2BAmeAW%2Bp8R%2FA5ajfCcAAAABAAAA3QCKABYAWAAFAAIAEAAvAFwAAAEAAQsAAwABeAF9jgNuRAEYhL%2FaDGoc4DluVNtug5pr8xh7jj3jTpK18pszwBDP9NHTP0IPs1DOexlmtpz3sc9iOe9nmddyPsA8%2BXI%2BqI1COZ%2FkliIXhPkiyDo3vCnG2CaEn0%2B2lH%2BgmfIvotowZa3769ULZST4K%2BcujqTb%2Fj36S4w%2FQmgDF0tWvalemNWLX%2BKSMBvYkhQSLG2FZR%2BafmERIsqPpn7%2ByvxjfMlsTjlihz3OuZE38bTtlAAa%2FTAFAHgBbMEDjJYBAADQ9%2F3nu2zbtm3b5p9t17JdQ7Zt21zmvGXXvJrZe0LA37Cw%2F3lDEBISIVKUaDFixYmXIJHEkkgqmeRSSCmV1NJIK530Msgok8yyyCqb7HLIKZfc8sgrn%2FwKKKiwIooqprgSSiqltDLKKqe8CiqqpLIqqqqmuhpqqqW2Ouqqp74GGmqksSaaaqa5FlpqpbU22mqnvQ466qSzLrrqprs9NpthprNWeWeWReZba6ctQYR5QaTplvvhp4VWm%2BOyt75bZ5fffvljk71uum6fHnpaopfbervhlvfCHnngof36%2BGappx57oq%2BPPpurv34GGGSgwTYYYpihhhthlJFGG%2BODscYbZ4JJJjphoykmm2qaT7445ZkDDnrujRcOOeyY46444qirZtvtnPPOBFG%2BBtFBTBAbxAXxQYJC7rvjrnv%2FxpJXmpPDXpqXaWDg6MKZX5ZaVJycX5TK4lpalA8SdnMyMITSRjxp%2BaVFxaUFqUWZ%2BUVQQWMobcKUlgYAHQ14sAAAeAFFSzVCLEEQ7fpjH113V1ybGPd1KRyiibEhxt1vsj3ZngE9AIfgBmMR5fVk8qElsRjHOHAYW%2BQwyumxct4bKxXkWDEvx7JjdszQNAZcekzi9Zho8oV8NCbnIT%2FfEXNRJwqmlaemnQMbN8E1OE7Mzb%2FP%2F8xzKZrEMA2hl3rQATa0Uxs2bN%2B2f8M2AEpwj5yQBvklvJ3AqRcEaMKrWq%2F19eWakl7NsZbyJoNblqlZc7KywcRbRnBjc00FeF6%2Fenoi05EcG62tsXhkPcdk87BHVC%2BZXleUPrOsUHaUI2tb4y%2F8OwbsTEAJAA%3D%3D%29%20format%28%22woff%22%29%7D%2A%7Bmargin%3A0%3Bpadding%3A0%3Bborder%3A0%7Darticle%2Caside%2Cdetails%2Cfigcaption%2Cfigure%2Cfooter%2Cheader%2Chgroup%2Cmenu%2Cnav%2Csection%7Bdisplay%3Ablock%7Dblockquote%2Cq%7Bquotes%3Anone%7Dblockquote%3Abefore%2Cblockquote%3Aafter%2Cq%3Abefore%2Cq%3Aafter%7Bcontent%3A%27%27%3Bcontent%3Anone%7Dtable%7Bborder%2Dcollapse%3Acollapse%3Bborder%2Dspacing%3A0%7Dbody%7Bfont%2Dsize%3A16px%3Bline%2Dheight%3A1%2E5%3Bbackground%3A%23e7e7e7%20url%28data%3Aimage%2Fpng%3Bbase64%2CiVBORw0KGgoAAAANSUhEUgAAAIYAAACGCAIAAACXG2XGAAAAGXRFWHRTb2Z0d2FyZQBBZG9iZSBJbWFnZVJlYWR5ccllPAAAA09pVFh0WE1MOmNvbS5hZG9iZS54bXAAAAAAADw%2FeHBhY2tldCBiZWdpbj0i77u%2FIiBpZD0iVzVNME1wQ2VoaUh6cmVTek5UY3prYzlkIj8%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%2FPsPnF3EAAB7iSURBVHja5N3rmiPFlYVhWtMY3%2F8dGhsDd4BtBk%2Bov%2Bq3lxNmPMMgVQH6UY9KSmVG7NixD2sf4t0333zznx9e%2F%2FHhdd68e%2Ffudrv98MMP%2F%2FznP%2Fvk%2Ffv3n3322fm3y7r%2BXHY%2B%2Bfzzz7%2F%2F%2FvsuOG%2F64fnqfHL%2BPR%2Bef8815%2FO%2F%2F%2F3v5835%2B4c%2F%2FOH8%2FHx%2Brjl36LJz2%2FO3e%2Fag85Pz4bnsvDnXnF%2Bdb7%2F77rsvvvjiH%2F%2F4R4PsPu8%2BvBrt%2BXs%2B71aNpw977vnwfNX788PPPrzOBee2vj33%2FOfHVwN2wzPgJ9Dq3V%2F%2F%2BtemfV7nZ%2BeKM4hzUSTrl%2Bfq8%2FcQ4vygZ3Q9SkXZSNNl52%2Fjbtp921NbiW7emwhx%2Fu368%2Fdc%2FLe%2F%2Fe084nx7bhUFz8XN9nzYBefK86sWKaqdV8OL4ufN%2BaQJdqs%2BtE7n2zNaTGCF%2FvjHPzaeKNv7c9kTaHVfkqZ6PuqKCNcP4sRodD5siIb%2B2cdX3OrD829bocmcN%2BfD80lDiaaNrHs2q%2BjYzSN9y4CbYrco2Mx705RMsp%2FEvxH9PPp8aHbdvMsamw163mCRxnZeZ%2B3tqifQ6hb7tObnGefx54u4Kb4433aNoUeLf3x8dd%2FPP7xQLdK0DxpljBaHYurD4D39%2FLBHJ1jiuAh3Lu7pZ%2Bj9ttueibWocV%2F3RDIL08xRsN9GAswR6SNfU9iZtgP69wm0uln880Xs0H0PXZKq3eV8FVmbVXwdZyWau2%2BTb3BN2%2FiaTNzdJ%2FF7s0oWNdDz9%2Fx7bnt%2Bft63ov22R1vFqHPkTG9Iwpj0vLeKCRO6pyn31bnmPMuyWc5znzNrC3%2B%2BfQ6t3n355Zckb0PpRTK0mFEtjusx6Nt8zmRW08bm%2F3v1EE27LGkQEYmUWD46RqBWdMWglWtDpJ%2FORiQxaJp9XHKvYSRzWozmEnFaJzr5obR699VXXxkHGvXjHr%2FKs19GhVV9LS8bhgTo86ZHr2YvJXAof8ZMD%2B3f%2BDeRwoBBvtZsv2pbxM5Js8y8BmaantjTz%2FDOHNM6tkh3W7ug6T%2BBVi9b5ocPL9ZexkyTjygt9f0HHx7Q5o39m0CLnNjtbs0kiRQDUoOeaANFglbibgh%2B%2FIQd2WXNM2a8qNzz%2FphJ2Zr0AfV7%2Fp4PD8m%2B%2F%2FBqpnEo9ZANSm20wyJ9tslzaHXfJW%2FBjmQXPl9QvDWb%2B332MoPEOttQaebWtvXsqWvbsKbOm0wIFqo16FYkGAke33Xbdjo%2FhvA5nyRbknsZpki8bmPLSXNmp5FsPb0Rtk4EaS5bI%2BefMoh3tR5OK45bv0wZtrvZzv0s0d%2B0sQnjOn5prD40FG5qQ6ROcNC5OCJ2MRfyTJsCj3Ct6BlMhlmPoKsZxOeaM5fuFoEafJrGc%2FsJI7h7EoYRAb8%2Fh1Z3iytW6u4XSOBsqKgJV%2BBMJZ1xX3Nm4ZFUVAVzqEdwO1LjvbmgLH3ecxPNmDdqng8bTzssgROb2wH9qouzFxq%2FjYsPCB%2BqCx%2F00Ij7aFrdvfe3API07oi4yiZqZjjhQa7cbxIQe2GoM%2FREB3XXdj5vzuIDIZBvYQksQIFzU7sslyq52XAvLoJli%2FRm1RM9jrdvkGv5tMPyLs99UtdNZAES1%2FctWc8lOoNMb0WQ2KiVfg6t7oIrVoo6DKT1hzMr16GL3TJp4oKEJnOw2aYJSAPCF6HBQd4koxoAOb4by0xSrV3MW4Zuce%2FT56zqptOC2Y7UALeU95OZlHo%2F759Aq7vgIiIbInqBOZtPRn1vFnpiafQTSiKWZG419EQTStn1Paj5J%2F3ja0RszXA67z1JeD6hKqwBFABWxs9w2wbGJ9gdGelXtdgcD6XVu2%2B%2B%2Babv7DIa0qYG0cTmGaDt6Iumalic56ydzM1EUzNvZKwOZiK%2FrGl4ikkS2fugbh7t8ulWYjQ7eAE7ojvvnrAJFi%2FA73u3h9LqLri4pt3Fbk0Kt8JJeXs2uiRVKahI3wyTJ8bdV9GOGKFUYatAPVhLaAcubtoJhMRxFCQMQfecUACJHbYWlGjHuZgnwU5LAy%2Fe8wRavfvzn%2F%2F8ijESdldT%2Bt3GSJZWL7skEckpZS3w7EDivNm1IGFEP1sZ4Ee3SjH0N1nRt%2BeTtk4UhxAv0Zm5bLnLDlgjB4jQkNpbO0fOeaR8NK1ubT36sL9JN3GFM%2F%2BICPAQconKoWztx9afswo8IMH6FVG%2B3GQ%2FUddN%2FtwwSkWy8%2Fc4Bz98fDFSYRs89u7GjdhoCncVyNhDF9fZXdXdnkCrWyPOQbNDmRYWH7TA2zQmYPg6Ys0tWdmzYwqubCTjaWNbKoGgy1JqXzeGsD8oQEQBoTex5dOUU9TnH6RLQVLEoFBS65EJJ2vgCbR6wYqx0iLP4mKxFbwByTyAFR87rP%2FRz2lvwDgjJ7Ku7m3CENZkFKyFaiH3W0vbceFkdElwt1ScHiHe9cOjKfceaHbcwOfQ6gVo2%2BXaaGuzzaNeQ5AQIJfpYcgatOM85tx5oV8ot8kQBWz2ppHp0m8RiydPQLWZaHX4BCSYsWDytp1AU3xq2zExhLaeQ6tb%2B66%2F0aj55EzCBD2et9ld%2FvbhBXkuk4GmSho020RN3JHQYNVwUAQWaYUel8kYURaBYDus%2Fxw1e7Va3ECfg3MAGyEotp2wvMeh0qNp9d7y%2Fthx7Wo%2F63mMkywf%2BCUzTtQhC321xcrorgGsLsAAAXN9SyhClcXFVMswW6MLTnX%2BMrfAukiwsituWOsjHo8bLOoTaHX3S55s7%2F4k%2BPH7tHd%2Fklbvvv7667cQVHhOmuuvIgDzfoGmTdsRFmV7bEiS4SRg3lRhiLZ2PM7xJgpikIhlJmGlgnSioYts811WPeQHGLnMKIA%2FKwu%2FUyfs4C8%2BvNYcZ4Ylcy7e%2B4NodWP%2FdVNgMnMQTNQW66axj8QywHh2XullsUDKnHhpSpITEwvpWIA5W0gAroHFtvBtd6Yw6YneAxCF91tUJIaqbZhdigUDjGH2JFp9%2BeWXjW%2F9VSb2KiJoq%2FidINIl1nR5bXYBN6qNn2Hubvyy9jKVKH%2BlPb1CLMUIMoKAwV%2FFKw31U8bUBwpe0pFJRctMT7BBHkurJrP79MyQD7E4qNs1T05s8%2B9fWXS2fzJhPQN7%2FDy6KYUbGrFN4ALu5CaXcKFtQStHJDaL5si8lIT3%2FuML%2BLiQTFtqnb7n0OoeL3kLUZ0e%2FVqg55uKgL379ttvU6qwZWqQ6SIS0LJjcxJz60gu5hP3TfDKrM4MIwRab%2FIjHbCZ1LxlMk2mhNQ0oYiNsqyFRnZZpK32yKfrVtEO%2BXrcw2l1%2FBKm976EIS81HwaXAI33N7esocRo5%2FPvvvtubx7XkNeNTMoBdIg%2Bd70EuC5rAaSpsbKgGlLWDSZK%2FTjYZR%2FjeiTjul4g0YfS6sa%2BBFWK%2FMQFOcBstSUBcx6yu%2FmMWRdRByEqD8CwqRamOu3Kk1hEy50Xxu%2BHUW0xAjogOWl4dBUM3xMbTEYHQHdTkJ9Dq3s6hPQk2YLsSHtWemsbebM3VWNsPi5V4dkLngt0Yxbh69dN4GfybqJJdhQM5uG0%2Bstf%2FuJhft%2BToDeCENJz8SBvyCfiARKiuWMcJbZ8TAR2RcdGCaIXJ4%2FFssTAJMQaqU2dbFJ2lL0EMNY85YfvSuQwtdX4NA%2Bl1Ut9yauX0sRxmzzImtz5M0CxZDpAipQQmYQVYK2d5KEmKBvxTZQdff3118JnwvqshYsHq3BveU00VF4hQ0iuSZcxGelz6c%2Bb34XNl7VbvwQIlF40bGHazUT1nsO4fqXsIUIsoAzvC51Zv2fQ6uySTxXXH7N4Gis4DAtcCHFJ7PxxoZvSY4UtsYzNu5jg%2F0n32BbQX6jJpXKZSSrHNUnIFm%2BF%2BB%2BrFRZxIOseTasbppBnRh%2BG5RkNIGEtRZg2K7ZH7q1EwtU%2B2df4i%2F3DKDoqtGcllFVSdU0yes0bmd2B6u28FrgQE9Nu6976q4yYRUTVLXL1HFq9BIehgTsmQU3Lyw%2BQqGBK7BwBV0kOyrnBuuvH8SIJCrpB0PRoIPhx3ET%2FKw7yPitWmv2lCGg1f5gKhcRToW%2FUNlrdJ9DqX1oRSB%2BGBMjv25Sf5ikctpnniUUa%2ByKy5YLStwwe5WivlZSsimcT8jJGCEC8%2F1Ba3QAGYePJa6g4%2F4Dglo0oJirNCRwd1eQwrBGFAWnyZEgbwqP%2F%2FuGV52UOkmuSZglrz41Dq7xqhzFJuTuCVFkQe3OBSCGZDIFiLSb4BFrdYccnq6%2BfVPVd8PPczN%2Baqq%2FT0NpzPIB%2BEFstPOXW7Eu%2BUjpKlFSaFrgC23bDYMdMYUkIaRq8H0XENihMzCtosbm5KnRXMDbONuV6J%2BvNMUOwzsJZT6DV3S9Z0ryWZ%2FAGSfNv2ehBtLr7JW8hmXwzGdI3NHl3i8r0YbmHv83mRBt3bHomsM0yFGEsbAWq8hhFylgA%2BLzpioryYysx1GjBrFTr3k5K2sSMWzVyfpvnUY3IGq9AM9pCJp9l6Lbci20cwXkStH8GrY7gUnfDFhK9ETrFoZeUZ61zqLIF8jaVr8FFO1HbbSgmNZRtinbqaBCXBWU3bEj%2Fkki3nT7UUGkRsoXChQ43dUbB0aLFD6XVfUneQmnlZtCy7rcMjlbY2i0LwxxSq%2FDrLUO9fSok%2FWhfZ9qHWMDDP%2F%2F4YnrmWOGywM5LeGqLELGSBjUSOPJCIkqasGlzGyU%2F1AhrNX9Si9Hcc1MPykrIos1HAW9Ei2ZNXVPsXMg0%2FxNodeMxtevj0%2B2WJCCoL1j06t8dnzzlLbRhaEYmHA2X7so8L2bPZqGVu8UuUtnO3xSDUjN%2FiStHmnygTZ3ugu8%2FvnA38WWojItn0Ir1JuC1rrX6fuG8dcRIdogQVuUJiqHyBOn57sbPUAJSyIi40D1mPc1LnxnpXuKMyQqZbYo5SD%2FmGXklZLB5MwSp6O%2BjafXuT3%2F601swLoUQ9pMFepPa8Sm5ryiWSY000nMwBGnGD0gZbErcGzHEb7wh3LodGFXc0JwYgTFe5aDUTSSOplpRBuoh9FaTbJ%2BE7aIk0bRCxdI1hSBhX20%2BziarjOLhtXH3ln%2BznqGiYDQCivP0BFrdAZW3AARtWPvVczNeFzS7bQMPERum3uaWawWzOYab3aMQXzXRZhqszE0IUDCsFKPn4UOltsUo%2F1mEeLsRLPQrGUdto83HD98GA%2Bu0UsUvkaXbk2j10o%2FrOUlj%2F0OC3adowe8%2Bwe4uuDYeuYF%2Bv%2B8W1JpopQtMG7DjAvbr9qdcryrO5ZyDFDcLC3wk7Hixf0Ad%2Fm7m6vY1FRfR2UVFa%2F9KpJNClryql%2BcTaHW3uBiO8osFrrPQCY3LZlRfu6nH%2FA%2FRw7pUnY1C1UtVWTOD7IZMCAKKra5Pzg3uQ2vDoLz0VeQ62I6sie1EIS1%2FI4M88CfQ6uaOftMk4xGGIJBKBr8MhO00oHiSlusn27lFGlwxu%2B2eAgck0DYLrUdktgmJy47YCCO1DIHeRGn15xzGzRbfEjeEEyB4Aq1uqp4JNYK1%2FF0G6%2FZgYeS06dakSTJIdlIMl55kzGCQ5nMp%2BSGUY1Uh3vU6dR3KhFWaTgk3ErPVj8KvFIbJzIfQHForadgMzSfQ6kXzbBfQbXnfmJQqaxOyCdQyaGGIcpnjR%2BAgxGIb%2FUrLVFCq5mNzCeEQqRbU1Icp6sumjCjbXAPOZoeRZg043aP4kYom4p5Dq3sxA%2B8soa%2BMcyvDUGphq6QQF29LBRWmxsIQb%2FtA7d5WzcqI0LYLNmwZTCZ2K58o0oBSiD5kpT919Mys2NTLppMztJPdmNsTaPXSte7VS5IlDb3Nk3eeWr791VdfbW%2BERWlkj%2Bst40QJqXKSGXbyOiRtKrCE6C3u29K3V7H0tibvEpYXfdJM1UZ8KK3e4y8OsMAqSbq1yWKfPVgwyoku8T7Df8%2BQkWZAUEgOll4eAyrzhVdqiKJFY2JtU0klGctz3PoVuIWsrY0DMvk8zu6BBhF9D6XVjaG5LcZC96B%2B2alr%2F1FHZCvYOZYkQ9RMbsOAH2d4dofslpUhOFRAHmKRYodGOD0GatmmpIc2jcHW5L2rX1GAmtkNadez%2FNG0eilm%2BNkx818w2%2BrXHjP%2FpWj1Ly2nID8x3aVPUh8K7fGVPjVL%2F8h9oGzsKda252LtsRSgEQOAOa7zjNlhutujLobVMluGqly67RS9WdJZX22siJDWhe2TLc%2BgVbWKr57NdqlRe5Vt%2BkaSIu8Y1yu6I%2Fur37k7glb38lHlcgxT%2BRnGJCwj0KbirQs0sEpcZMLK2yAusGGgxXZ%2BfCMt3%2F837fEfSquX%2BpJX16iXc3nski3VIQQWyXeBMKXqDeHFX1fG3o3bpefHCnEHC8pS0Ck9d4zf1OSl1QirXbhV4C%2BX2AFW4j%2BxzwbAqeKIK0KeKs6%2BbBU3eQ5qoBOADjmbhLDnz%2F3nx5cVkgejbc4TaHXb7Nh%2BtlG8bbRGSWoWeonuURvCEnvKD8YhTCEW%2BQctlY5m3DT1czrpbtC75SzPSKvVjb9qXsl1X5hZB1QxcN7fNo7QOPoJtLo5jXR91BgqIYim0r%2BBg6RHXtU%2BOJng2E%2F6EGyAuWDdVI7sjUu3GXjqpQ3QZiZkaDokkehYUGsxrs0yaTBbWrf5NC32E2j1Xovu3UHZM8kKDLt9UC5d4hcjIjH3vLetQtsOTLh1ESeJ%2FtJz99zcy8l47DSlm4W5OhnPBVv5sV1rd4E3e2%2F9jJ88jfpxtPrUa1XzczYGlbXHMTLMdWAEFm0X7ItA147XxcIeGgluJtw2apI3BUXe80VEA%2FuJgJicsc0RsWbhTlv%2FCD5pmjJ69nyR59Dq7pe8BVP9Zx8U%2F9uLsrwnMfiiTVV0jFG0SiyJnHWkcaZTvYTTIX0d3ibautlD2%2BNcgDrmTaPShFsBxWgxeW2115gRNdmzaCTSrdkqB478tFlBhPjjobT6VD76ukc870m3v%2Fq%2BNP8%2FWt18sT0speMJucgWKHlAnM5hmzacgMymmDQHLZSUIugyxneJlZIDEt0jUJpD%2F0f0Zeo4AwGkyNLVFnatAGmMXDb2lRaCWoFt19OH0uq2HdScS9jWy7C7tOxdwQde3WMBcRwziUXBCiR5t6WufBTHQ8mHT45vszp%2B%2BBbLcHq2SqgJ0xPJK94AsUn6bdeIqE9FPYdW74HYMO1L6S0qGLp8nHWvtgcgAbLjw57UO1MdFqIPrE4ywNoYfDv1RlzdU6TnqHKTvMqDkeyzXguYVlUD74%2FkMccn0OolAfXV2%2Bg5S0GAYfsBATbIq99wy8E77MiUpvqUbW%2BnJY0noDe8p3SvRL%2BlF8jvkostNiVJd8PjMobb7yu1pF1JhGDe7En3l8avAhjHDK2t1PYnUpy4NerbOsV8n0CrG9HJNlCIzsrUq2pLMXkJavFjIjG%2BDUaVQrgrsT2vBdUzlNWNmbn8AWko7FqVhprYEOh5zuiy1Vyu3Eq1BRBpfpuDlfFoWr0Xnd%2Fm6uLP7D9iYQ9gcaLL9r8GHDFPbZTtDk58OZpINS3IXSBvD7nkBvMHdcQQf7007hMuXEthk%2FnsrXVUgdCbA%2F8EWt00YCNVs1Cl7QSvGqggJebdE6J6ak7QwuN7nD0eZGI6R0x99OZu7dnQfD348fb05ZoJ2LG%2B5FbBXIG%2BexwUvhY%2Fl2QEM340re665C2c%2BLxd%2FhTy%2Fj7bEnyqL%2FmxRw3E3UMAGRsYTT6gqudtMCUk55S4BbjUYm0I9g161P8WffgFaXVPQCWjtS%2Fc2lY9jS7s4CAFD4Dfcaq3oe8FA77g1UpDHt0jmuxGIxHoHe22aN4D7Z5Aq9sWrfZjYQwHHTgIvPfZRXumyr7JbBXAWOMkLMEuSeeLTGwhbMADhyChnJ9cWPdTNcbH7rw6X2T%2FlIKVvUvgeHTW3a7NOqGkjQ4EWYzPodV7KwyUDlxaMcrGJ4s3NctvubVkMW4ScJVAtkeMryQFyK95Kr%2BdKON1Cgtyu2QGwy516KRvLjp%2FT30VYaS30EE1yUNpdWOTCK1IX0MvdLxUaQoaS9EoELQtLfa40ct5k0zPtWdYXwLjiKhKKruFBl5oEmMy8OD%2F0iqsnKq17napN9iK3gLAz6HVbduBbEe7TFUUTFwkZ%2FpKeIMLJldcDdyeoCI5HIQVfRdwVeW2Mt0ZvWrUl6a3eaFUORXbh5gTt3URala1Ld1yKYYZ9OE5tLqnab%2BRxqGveT7FW%2BoX8RLCevUqJlAo1F1Pgs1DKDq5iV5rdMIrmQ98jp4bQ0h%2FfZsVXy%2BwI7RALexmbGy7v%2F8uY0MC488LoTt0%2FRf0dS6p35uiYJ30ANqeoGW3CFZKviKvHkqrf2lw%2Fku1M90ArVrjZNHGoCQbLM76W2tn%2Bn%2Bn1Y2%2Barbn8dUmq%2BB3tIKhw9rE91niqCYLbXuQOQsUU1dGpTSk%2FUsPbxi1Re2327BMjBJabOQQXzg%2Fuw7A09MVTe%2FprmYqEeI5tPqEIuh9p95gm%2FuEQzixi4G%2FRUobbXVKrvEt%2FMAGc2pBsmhPtHc4w7ZxWO%2BEoXnkzKJnoC1heYmEdM%2Blkji%2FRH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jYB8rAUAgICAgQCAgIEBQBoCAgECAgIBAgECAgICAgICAgICAgICAIAgIAAgIAAgIAAAIAAmgAAAPoAAQGWBMDLyBSAOPUAugCAMxyBPpIGX%2FQBt9FgAjQAfGQM4WMgD%2FhAEwnUfgAlOvqAJ5a1uABp03nXYAa0kDNzWfRAZxcQ%2BalAOtNRvqBhqter%2FACBVHXfgDLt4q40cgHc5mKrTIA2plL%2BPEgL7ob%2BsaPkDPdDUY%2BWqzgAtwlENSBlLd44mgKKmcxX0AnO3yU9XyA5TWFo%2Bq2AmpanyXAEolrCefMB7Zf469AFNO8rWvUB%2BXydTGW3xsBOZadJxc7cga7VjMT%2FPIClDuudK%2FADOvj7AM%2BejWgDPxab3m8AMvafCA1rQEkkk88gaWnoAuoTcbMDUpVh8ICU%2FH3gBV3qBqOPJgMrxkBVcaAat%2BLAU9gFWtgHxACgFSAoBmX9wHXqAgKAQIDQEAgICBAQGgICAQICAQIBAgICAgICAgICAgICAgICAgIAAoAgACAAICAyBAQAwBgAEAMAAAAAeQCgBgD8MAmKANADN6gDWy8gBteMgZxxoAX4yAJvQAynotABqY%2BnABUxjfzAL67oDMp3la0ANy66yBl5abhMASmMxP88gSUZrnSvwANzfiwMtvGVh7ADcO7ubwwBt7T4QF%2F04txHhgZ%2FVJPOzrCAnpvjzXUDPdWXGz%2B4B8l21h6JLbzALfb1uK9cWBZczbfmtAL%2FOPUB%2FTOkwngCmFVzxv5gPbdYf330A0pTdKetsBUtSvVSwJdzuLWt2Aqe6XbugNfsm3ruqmAL%2FACmvNeYGk7ddM4AW4xWviQH4x7wgFQ%2Ft5gNaZ0WQGbWwGmqnK5oBmXEelgNrIDLdagah3sArd6WAvhAKA0lP2AsYA1WQJPYBWwCqmgFAaTAlLsBsBwAoBAYAUBAIEAoBAgECAgECAQICAgICAgGAKAKAKAKAKACAICAgICAgACAAICAAIA6AAEBAAAAOQDQAAmBlr%2BgIAoA%2BgGXuAMCYGW35gUO6oDLn0sAb2XkAe4BE%2FZgZdfkAfxyATtYBmsAZtN0p6gFtSvYA%2BW38gZty8zgBfyTnXipgDLS7U15rzAJz7ZAG4iK18SBl9sL1hAEp0961pgVKlnRZsAbbfFQwM9yqf9LmgCZaUdGnIE21lu8LC9WBd3c3WG9F9gK4T%2F6W2ujAIVTDc6acAavuhPn%2BAJRD6SlgDSUfq1P1u6kCbccvXgDXCp6%2BYDmtFkCS1TuYQCk0ucgat15eYCmrjTTHICsY8gFL08UBrtrHmA44kB5Wl9QH232oBWZf5A1MWwLrkBj0A0p8cgPIGtQGPUBAcgKAVswEBAQIBA0BAKAQECAQECAQICAQIBAgICAgGAGAICAgICAgICAgCAACAgICAAIAAgIAAgBgAEBAZYABADAAAAAAAAe4A%2F7AOXoAOgMv3AGvRAF%2BOQDqAPPAA5zqBlrewJy6YGW1HlMYAIinYGX9dQJ8VuBl3WmoGY1TuYQBaXOXkCcsAlXGnkAaY6rkDMXH%2FOk9cAXbWMa1OgFzhvowMPdaQ3m5AI0wtdnAEnLbacLTMZAp%2BMtgUqFqncu2AuZlZ5dSALucJ5ipfUBiWp%2FFgaVwmsVHkA0u1NZbwqx57AMPKXIFPxVxWL8gNW1PcvuBZ0l58gNppPP9dQG8p1vYElD1c2gNKHO2sANpq%2FuApuI2%2FAClF6%2FeQFJOOdUBqnKytAGGgFW40AcfcBVXj8AaXGQGNNgHQB%2BoCnUgPUBAUAgID1AUAgICgECAgFAIEAgQCBIBAgICAgGAECAgICAgICAgICAgIAgAAgICAAIAAgIAAmBkCAgAA6gABQAAYYF4oDLyAcAABCcAGZ1AHKAOFgAdfcApXj8AGnIGWprbABUb6zkAfGeoGZah%2B7AHbU%2BGAZiVgApJPV6KgBp5XUDMxnTAA02p7vpKAMu1LUvyAKTyAOVLT87AIh6ubS3eQKnOiy4rzAxLTVzmsyAy4%2BOi%2FAGMWlbro5gAXam0qvVAUrulK1bU3X9gEdyvxHoAzE905%2FsCzc9V44AkrzvKSeNgNdtN6K3M64A03DpVh%2BYFSUtOcXgBe7vTxgBXSXpzACoxqBrLvEWuQHDSxywK4pxhzigGLjcDS2b8wGIdvzAYpdZSA0mkt3sBKXnOGBpbLoAqNLAaXQDS1ikApY1AV46AMAK3AY%2FkBQGlrtuA68AQCBpASgDX0AgEBAQIBQCBAIEAgQCBAQEBQBoCAgICAgICAgICAgICAgIAaAAICAgACAAIAAgBgAEAAAABAZAGgJgD6%2BYGWBacgZ6gQGQB%2B24Fo4wBmMagZ8eQA07%2BgBiwBqdeqAIvPlYBhvRZnnAB3OHSrUDLhKX04AO7kA8pYGVGNaAnblwlFrkAeUvcDNxTjWcUBlq2tX6gTejfnqANXb5b4vgCafxWrTpYxpYBKSu2tPcDFvKc4cZAlDbS6cgC4Uvbf0AW6TWVaT0cgStbPE7yA9sOalv1gB7VLT6xwA9sQnnueLlALSUrtzlt%2Bd%2BwCsdanYBaVpf64AZxzhANPy1A1awpucgD2ajadJ6gbTW%2B8MCVOIlZA1G9r8AazFROugFH%2BVjzA1UTpmAEDWeIAln6AKa%2BwGoAb%2FDAVkB5WVoBpYAUArcCUeYGunqAgP1AgNAIEAgIEBoCAgECAQIBAgIBQCBAQEBAQEBAQEBAQEBAQEBAQA0AAQEBAAABAQABAZAgBgDAMgQGWBAHAB1AGARhADjyAGAMDOv0AJ%2FABF0AOdujAyonYAe6zlIAytgCtp%2BoBFp%2BEBlJQtwBqJjOrfjgA09gMtZjIA3jnC58wJw7zEX4yAOVpPmBju28KQKVvGYewGZhxFZAnTtytuEAu4hROumAMPt%2FysLqAP4tT%2FzmPcAczdLT3UgVPLhKtscAUvML%2BWBUlKjZceYD5x1dIDXbDiaeugD%2BkfGM58eQFF%2FF0sxFSBJPGNkBuXSwuc0BKYlgKbiVPQDXbo1MaThASr%2FqsbAaVacR0AVs60A0vRLYBWbxhoB%2FWm1nYBV2lYDGGs7ga7VtYCp9QFSnACsrPDAYq348wNfUBQCgEBXICowAgMAICgECQGkAgQCgECoBAgECAQICAgNAQEBAQEBAQEBAQEBAQEBAQEBAQGQICAgACAAIAAgB5AAIAAAAA8wAA6gAA%2F7AKyAO7QA1tkAgAYA6cAZedeABqlfjzAM9dQBt5AKSroAPxwBmnEqHrNAH6xEZyANXDx0qQMw%2BmyAHNaL8AFxPEAZlwmpxjRgCWGpjRPCAMa16AGNOIfAB16AW%2BiWq%2BoBreMdyywB%2FGE2pmXQGXDnuSvfNqtQMvtw1lu3hgPaomLnD0nn0AJ%2BSnCcATTcukomtgNRapxhrjyA0lCiJSeiAf1Sdzc%2BeAJLu7Xre%2BvoArMNNdvlAGmomur2kAuOcQBpKa0A2q92tmBSppVbkBbWM%2FwAAMTIGkt8vIClhvM6gMLWnPqwNROPPzAU3G8YYCsT9QHDqgJa8UgNpXXoA112AVADM8AMAaS9AKAFQA3ICs4oDQEAgICAgQCgECAQIBAgECAgFAIEBAQEBAQEBAIEBAAEBAQEBAQEAMAAgICAAACAAIAYABADAIAgMuABgDAIAmtQMgDvABcbsC0Ay64Ay%2FwCEBNbegBXXYDNMDLcrYCamXoANemqAzEaSp0AP1SdzqAQ0%2Buj1ANYhpeQA6mvPqBhzGbxGM0BQn03XjUCx7tbMDLjyuwM9zSpKenAA1M%2B4FFuctXGwBFpvKdys9ABpf9U582wM9yltdudY5AJ7onLWGApVPs89AMNdyTVdHfOQNPu%2BP5AkpvObA6dt7%2FyuQC5jfKh6gK%2F09W%2FsBpd3V86ATmbtZU%2BOAFPRPoBpJJRNa9F0Ald4VLrwAtOeUBqOIgBUy5A1M1zgCVcT4wBprbG4Dpt7YA1MdNAGar3AVXXcBSm%2FcDXu2A6AKArA1gBAUAgaWQFMCAQGAFAICBIBQCAgQEAgIEBAQGgICAgICAgECAQICAgCAACAgICAgICAGAAQEAAAEBAAEwMgQAAQAADAGAWBNyBkAYFpfiACQBvbQDL9wDIA%2FVsAcxvoBlIDLTSAm4Ay1NgX2%2BoGIeNwL%2Fp7gE%2BfIGXm8ZAJ09IAISUTTmVxzABnjCAy58wB9r0UQBlTLn2zIE3Nc4AMcTMfaoAu9bTGZAy8NutJxgA%2BUJOYTtKvoAtuH8ZUaN7AGc3frxGAJqcVlLboAqpVwuoGu3Fq8zsBpJRCrrdJyAavt1rCzADScvP4AcKE756gMJfdsBTjhxCYGoTma93H2ApTczpp%2FIGk%2BZ4A0l9cgMQpnp44AfDz0A1CnEcAL39gHM86gKio9gFX0Al%2FAG05XADXqArGQHICAgKA0sAPADqBAaAgEBAQIDQEAgQCBAIEBAKAQICAgICAgNQBAQEBAQEBQAAAEBAQEBADAAICAAIAAgACAyBADAGBOwMgQAAAAA8gDAGBmqANwM%2F0BTK4Ay4U8gE1mADIAwB%2BwGfLmdgKKhUBmrXTCzAA4TnUDLpQsgZaSx5vqAJxxUJ9AFpPNe7gDDiZ%2BgFOzniQCF5zE%2FaQMtRafR%2BNgB593nOAFpTMQ9uoGe%2Bpbhp6R5AZpy93n2AFDhp0rrFoBay1KWwE32z1hbAaUt1SaVgKbdzCXH4AI6rl7egGknE2gNVjXGmuoFhvWb8eoGtOdYyAzK%2FtgKjKqfICX7axvPkBrWONANYlOwFOU0vEANrOtAPW99AFLxwBrq35gOV9gNK9oAk78IDS%2BoDPoArDbaAQGgNWwJWA%2BLA1oAoBAQIDSAgEBAQIBAgECAQICA0gICAgICAgFAIEBAQEBAQEAAAEBAQEBAQGQICAGBAAEAAQAwACYA8AAGXYEwAA0YA5AywIAYAwDIGZ5r0APuAN81sBnCbcY9wB1gAbQA5b4YGZb4Ay14e3oBQ4m0AfXAGXTAHjnWABuV06vAFKyqnyAw7qY3nyAnFpZjT6AGJTtgZmu5JT%2FAA%2Fks5de3kBOcNt5nT2hgYj%2BsUBYptuN9OQJ2mtMRz4YGWm7Twpx1A11q99wNJOKac58wNdttrx5ADpJdrcaMBTUOMbK66oBUY038MBzwsfwBpRhx0AVVxKdR0A0nrc77yAKnvxqBpqJ42AUmq0A2s58vsA4vbEZAYw9dAJAa8IB6dAFb%2B%2BwGsr2kBT4AfPAGlaAumgGlyA%2B%2B4CgHGGAgKgBQCBLcDSAkAgSA0BAIEAgIEBAQGgICAgICAQECAgICAgICAgIAYABAQEBAQGWBAQAwIAAgACAGAAQAAAAAwDAAAADAzIE8gD4Az9dwB31xIFPFgZfWkBm2gBp5WiAOoB5zuAawBl0oTrRgEpT9P6AKxpuBl30wAcOOgBi4lOo6AU63O%2B8gYw98vkA7qTxxFgEd3bWn5nYCec%2BX2AHKUvTEOwFpU5vKh5A5TP2n8ADamddM9QHlKG6t39wJpxLmrfkAQ1%2Bq1332A12ynd%2B%2BIA2lntbmn%2FAGBVhQmsfYBbuZlcqQJvMqbVbpgKXVrXUDS39wH4%2Be8ga4m82BJJuLejbA0kBRbXmA276SBtaXgBpQ3sArqA6dMgNSA35sDSVcbAaQF5ygFIDXIFgDSlZAVsA0AgIEgNIBAUAgQCAgQCAgQCgICAkBoCAgICAgEBAgICAgICAgICAGAMCAgICAgBgAEBMAAAIAAgBgAEAAAAAAABbAACsgGgAwBwBlzrkCj0AAMv1TAI%2FAGWql6ADlVv9QCGsgG6d0wMuMKJXhATd5roBl6zuq4AznprqAXM%2B4A157gTxE3mwMwm4zo2wCHvwBl9ttXVgH7O%2BnqBXV4%2B4E%2Fio7nGNdgM4Tv0uwMz%2BrjTML1sAcS8xOVT99gLtUaW4n0AYaisU3z6Aa7YzIGk0lDVZj31Au35OZfRgSzPc22pgDSSmVXEZ8gFNLmHn2AVE1jcBSqXp9F0AY3YC176ZAYnK6gazn0Abi6fjyA1tx7AM7efIDe8ANRGwDjLlIBrD9GBoDUAKQEv7AV%2FYGl%2FYCgFAKn%2BQHlgK3AV9AFAKAUAgQCsgICBAQCAgQEBAaAgICAgIBQCBAQEBAQEBAQEAMAAgICAgIAYABAQAAAQABADAAIAAOoAwBgAB1AAB8ADncAcYAHQA4x7MDLAmtgMx41Az77gGPPIBf5APMApZ6gCl69GBnFty1MAEKZVcbgEx1Tz7AZpOsbgCVS6jypdAKMywMtb66ZAy1OV1As2%2BkYAy5hTT8eQDtx7J9AM9zv9aeXOH4gA7l3LVpbAZ%2FWPjEwvf6ATS7Ylylr%2FADIA1hvDqsAPyb1lzkDWn%2Bvlv5Aa7ax1awAQnLS6rWgNKEnxUrcCiLfk7zgDURm2%2FIBlTaAflKzEgLhTGucaAa49gHPnIEq119wNK9Y0gB1l9ZA03o%2FUBSi%2FSAGNPHsApXHqAyvIDUrTOAGE5AQNIC2A1LAdMyAqgHyAVgBAV7gNAQGgECAUAgQCBAICBAQEgNAQEBAQEAoBAgICAgICAgICAGAMCAgICAgBgAEBMAAAIAAgBgAEAADAABgAAAAD5AAB5gAj%2BQBtAZn1wAZkAANdwMvTYAbfW8gDxmf4AE4x1aAzEy0uu4FhdNVAGWtX40AGozl%2BQGW1NgDc3MSAOFMa5iNAJ7ewA7URmQMJxrbcNcyBKXlwsQBnWX1lgPc6S7rnWQMNReNo5AGm3C80%2FXQCSlxcLPUBiVShfbTcAeVNJYfHqBrtacPQBcx8U5lQvHkA6ppeXlNQBJSlxqrWwGsO6WEwJb%2FwBr31AY0URjb7AaSwutAXV142AVtGPoBu05y%2FsBJqYnp6AaqFDhrQCV59egGkAxCcZAaf0A14gBXvv1AVyA6Z8wHn1A0gHXxgBTVAXGQNAOgCAoBAgNIBAgFZAUAgQEAgIEBAQGgICAgICAQECAgICAgICAgIAYABAQEBAQGWBAQEAAAEAAQA8gAEAMAAAAAAAAA8SAADWwA7AH4QGfrv1AOuQDTbkDLcOddQL2QGX6c8AVOGBh7JzOAB8ADUpTpqsADp3jQA5Ay%2FVZewA1oojAFCpewGXrLrxsBlRiMfQBhpt5eutewGZUxMZj0AqhQ4aWPcDKuZ2hPpVAZl7LoAfGE4ytwCU6VadAHWJtLPmBNrEcrUCT0eZiegG1b6TPKgB%2BPxaTzotaW4FbSWmZ8wNV7Zx9UBROEkn4sDSxVL8gPxUxmnC%2B4D%2B2cIBmpfr9gGdfLqBpY32Apxt5gaWOtQBpKfGkgKeHnUBWsgIClcvwgNRu7QCphQArZgakCXuBoCXICgNYAcoBAQFAQGkAgQCgECAQJAIEAgQEBpAQEBAQEBAaAgICAgICAgIAAAICAgICAgMgQEAAQABAAEAMAAgBgABoANgAGWBAEAE6gAA%2BgGdZYA1mdADRQAcMDM3uAa87gDa2Az9cSBZfr6ADUO86eQGbaS85AHHtnAGWpwqYBpVfyAfFJxmnH5An8vIDLdNtgDescdQDSrqUkBlu5VJ04lAHTVpRtoA%2FGfGkgZmIavWtfIDMO%2FlqryBU6hSBOqn%2F8AT22AphcPHDyBrtT0wsYn6AKzSvV5hTsBQ%2B%2F9sKpYDDh5S52AecZ6%2BQDhOejYGl7cAOLhYSvSQGJuMPDAphaTrO%2BAN1nTUBU%2BYDN1n2kDTpQ8egFLjGdANJNdQG5sB%2BgDN7MDSxyArZr0AVQCr0AePUBwBpSBLIGs2A6AIFgDSAQFAQCBAaAgECAQIBAgIBQCBAQEBAQCAgQEBAQEBAQAAAQEBAQEAMAAgIAAgACAAIDLAgIAYAAMAYB9QB8AD5wBlyBQBnUAYA%2FcCeAMvlAGAMzNfQAe3qwBuFwAQ%2FTG4GdazvkAvuv1YA04eUuQB%2BgGXU%2BjANeOAB1aSiIvSQKNdnqBhuFpP3wBNLLxr5AZtv8A%2BgJtt%2Frn2kA7lCh49PwAN93xSimqXkBl9rW8zvoAY7rvHUAjCysQsX1AWpXxblRV6AXao9JafGwCqzp5ejA0tIUrCcgKXcu3GLSWvqBNzmJ0WmtgXyraH5AbeidbdoFtYGk%2Bb0aTpANOn2xvt6gSh428bAaU1cPkBjXgDWb86vIGtazsBJOVCwBq%2FwCQLnSQNJ5%2BoCuP4AV1A0nxQEo82BpcYAeNAFf2BpASA0pgCAUBoC2AQEBAQIDSAgECAgEBAgICQGgICAgICAgECAQICApAAIAAgICAgICAGAAQEAAQABAAEBkCAABgABkCAywJgHiAM2BX%2FIGfoAbgDgA8MAnigMuM6sA50AHtNQAKvuAOs6eQBtU7MDMdyWPLcAd9dFprYGZ9n5AT2foBh6XQFPq8U6QA4dPtjfy5AzTxt42AlO8PnnIGWpvdZ9gJqb85SnOACphZ%2FwDM5rbQAh1CwAd0rpn5Z0yBiYcpVOdQHtbuOsvKkCahXfN4AG3HxcOH1wBq6SV6LSdQNdrdNQ7cJ37gSTfk8AKa%2BWqeIYGkopK9c%2BNQGHosSBKI%2B4CqUOWsPYDfbjMtONIAo7tcgMVQDMS1pvkDSy2l0fICsqMTQDdJeUAOF9wNU0tVuAroA7SBayBpZ9mBq9MAKAQHgB%2BugCgFSBpZAgEBAQFAICBAKAQIBAgECAQICAUAgQEBAQEBAQCBAQEAAQEBAQEBAQAwACAgIAAAIAAgBgAEAAAEBlyAADANwBgD0AHyAZW6AgMvkDLyAPP1AnMUBnwgB0gMt6UBP306gZU01D2kAhvongAlTqtIAMUl1yANPTQDEqPuAYUOYw4iAJYzLwAP5ADVAZbhtr3mXsAatpXo1uAaqMTTx1AnMJLya%2FAGXScreGuQKmk25SqX9AJXlcRjIGE0lb%2FbnZAbUebqeoFN0nnMgaV771VeYE%2B5tNN3psBqn3QlCTvlgKSmVIC4dLOI26%2BoEkojbKgDXa9Y%2FbYBnyleVgU39fMBcz%2B3mBpNOdgNVp0hAKb10c%2BgDLWNdOOAFNZd4A0ktcsBhJQ%2FcC1nC3yA489QNr2QDICp%2FIEnHUDSgBkBAZAdQFLUBAUAr3AQECAQEBAgECAQIBAgICA0BAQEBAQEBAQEBAQEBAQEBAQEBAZYEBAQAAAQEAAQA8gAEAAH1AABgD5AJkAAJAHQBKyAVABhWBl76eoA68wJ%2ByAzIBLj6gYmFyA15gZb29QDP1qqAy%2B5tNNgVTGidgEaqQM90aZAzCa3i2oAk3bj9sJAD%2Bq%2BoGW%2F5Az3zK%2BXmBJpztnygCcaXpC4AJzNRe6oA7m%2B3E3prHAGW1fc7xEAEKLzupAYS7YdaXpNAZ7kmqVN%2B%2F1Au6d4%2BlAKjXOqrHmBrtedvsAxU91KqrcBuZytFvIDcw346AVNfLHroA3lqmBtdzy6SQF%2FnF%2BMagLj5NRPGcAarCVz7gK159QJPfGoGsV%2BMAacvruA7pOwG4rTUB438wG8IBTjrAGs%2BQGpp%2BwEozADHFMBA0uQFAK3dAICA8gQGpAcAQCAgQCAgQCBAIEgECAgFMBAgICAgICAgICAgICAgICAgIAbAAICAgAAAgACAgMgQAAMCkAYAwCgDfkDP0AGBMAesZAGAP6gZc4QAnDAHfIA3n2AzWYAGtlkAYB1yALXb7AZeJdLYCvOVouoGbmPHoBl4nAGXOWqYD8nFuEl9eoGX%2BuLAHmIn3An8XSVzXUDMO%2Ba5AzN3jXjIE4WPtgC7pb53Aw9Un%2B2ZzoBOUnGlN6sA4f%2FAFK1fuA4dq%2FGoC5vWfcAcS7vNZsDSfaqnogNLva0rSZyBatuUnmOgDfRbRuA5rTSXmQF78KNwGItegGk4m6euQB1c6VUAavXGwGlePwA6c7gNXfQDU%2F%2Bb6cAUyo8SBpe%2BbAcdQFAKUgPAGs9QJTppqBrGcgaAgNUBJgaAgEBAcAICAgIEAoBAgECAQIBAgICAUAgQEBAQEBAQEBAQEBAQEBADYABAQEAAAEBAAEANgAEAADAAIDLAmAAGgGaAp2AG5oA%2BoA3HUDO4BCfQA4AHetgZu4wtQDGQJgZetgZpa9EAfJrT1nIA8zcPMADny%2FIGXfT6yAd274jcAa%2BKn2Apidt8gYdXPTQCc64Wi%2FABnGmmAJzDetXv6gZq3OFWnoAN%2F8AlTtHAGX3PuUdMTkCT2mc39gKWue5aYAH3JVq85AWm3mXO20wBKJmJePT8gPbinegCoSlz5qbA1EJqI7vuAqYn7%2BYE8zq68wNTKhOOAJTjAG%2B2at7p%2F0Adnv0mgNcvGKwApzOzygFc6yBqFUewDl3a3oBUemeoGtawA7pgKeAG85AUufIBekga%2FpdAKdPUDWeoCoAUA0gNICvIDqAgK2AUBIDQEAgQGgIBAgIBAgECAgICTA0BAQEBAQEBAQEBAQEBADYABAQEAATAAICAAIDIEBADAADgAAEAfQAmQAAekADAPsAPNAD1QBMADnOQDzAy9JAHjrSAy3FeoE87gFbSBlUvoBmkpvzWoFo1h%2FcAcxIGe7M64AJlQn5ACTtKq92BXV9H%2FQGO3P8TQBOW4hKK4AJmbzlAERM6z6sCaVR7AHcpamWtHT4AxXpmdwFzMLH0sCu01Xr9OgB94SwBJwnUaw9gFNd1NKsSoAe1zPcrlNx%2BANNNw24erWAFr%2FmY8ohe4EpmU7nogFVhQ9nUoBXDUbgOVr1f5A0ojW4meALOlaaOQNNziugFKzAG5h%2FxowGojE7AaUuEsNSBJbv7gOmQHyn3AU%2BnAGttXssAK23AZvkBThYAQFOE9ANJzQCnqA3QDwA%2FUBQCgIDQEAgIDIEApgKAgECAgECAQICAgIBkBAgICAgICAgICAJAAICAgIAAgIAAgACAGwACAAAAAGBAAAAcwANgDj1AHPkAADAH0kDPhAU414AzwAN7ZAyqWMgABNPTgAlOo9QCZl5y46ADTptw9YAHtP2Azc8%2BiAzi0r51QEsqGo3Ay8a623ldQJxH54Aw7eK03kCbnFNrTIGe5qZj%2BAF90P7xcOsgTaiMfK3GaQA23CSUNSBhLLbxxNAEVM5ivoBOdvkp6vkBymsLR9VsBNS1PkuAJRLWE8%2BYGu2f45AU07yta38wL5fJ1O7b42AXMtOk4125Ae1TGc%2FzyAqs%2BulAKevj7Aal6Xo1oAz8XLu5vDAZe0%2BEA61YCoSTzs%2BgGlp6ALcZccgMpVh8IBUte8AKu9fcBj%2BmAprxkDSccaAMt%2BLAU%2FMBVrZbgPiAFAaAZkCmWA69QNICQCAyAgICBAIEBpMCAgECAgECkBAgICAgIBkCkCkBkClAEgUgUgAEBAQEBAAEAAQEAAQEBkCAJAmAAAA2ASAMCfQAYGa%2FkCAHz6gDcfwBm49wDN6gUceQGZAG440AHL8WASAZTWFoBlqY%2BnABUxjfzArf4AxKdzK1oAbl11b6AZeWnU6yBJT0n%2BQBVn10r8ADad%2BL9AMt%2BenAA38XL3m8MAbe0v%2BgJ23FvHhgZ%2FVJPOzrCAXpvj06gZ73FNxs39fcDPyXbWHoktvMAt9vW4r1xYFlzNt%2Ba0Av849QH9M6TCeAKYVXPG%2FmA9t1hz9s6AKlN0p62BpS1K9VLAl3O4ta3YCp7pdu6Af2TnXdVMAP%2BU15rzA0nb9s4AZiIrxyBPtj3hAaTTr0Aaws6IBlzxoAvE5XNAMy4j0sBbaA023WoDDh7AK3elgM7LyA0mAqwFUA0AzsAqwFa1YCrQCmAgNgOAEBAgEBAQICkDQEAgQEAgQEAgQEBAQEBAQEBAQEBAQEBAQFIABAAEBAAEBUASAAQAASAATkAYBIAAR%2FQBIB0AGwB4nQAbkAbgAbb6gDw6pgHL0sAb29AD3gDMT9mAYAH8c6aAEwqsAzWAM2m6UgFtSgD5Zi17gZvul25wBP5Jt6%2BkwAP8AVP1XmBmc10yBNxEVr4kDL7YXrCAE065rWmBUqWdFmwB90viaYGe7E5XNAEy0o6NOQJtrLd4WF6sC7u5usN6L7AVwn%2F0ttdGAQqmG5004A1fdCfP8AEqPKUsAaSimp%2FnqAt1y9eAHhU9QGZrTUC5TuYQCqXOQNW68gNJq408uQFYVdUBLPGk86Aa7ax5gK9JAuVpD6gaW2%2BdqAU5bbWPMDUxkC41YDfkgNJsCW4G5vgB%2BvAF7gayAyoAVsA%2FcBAeAJAKAQFAICBIBAQIBQCBfUCAQICAQIBApAgICAgICAgICAgICAgACAgACAgACAvqAMAAgAAbAgAA5AABgQAAfQAQAwB8AH018gM6gWAMv3AH7IAlgZAm7AHvqtgMxibsCcumBltR5TABw7Ay3XLAnxW4GZmtFkA5TuYQGbS5zqBOXXl5gEq408uQDTHVcgEXH%2FM1Os6AXbWMa1OgGXV4nowMu3K0t5uQKPJa7OAJOW204WmYyBT8ZbApULVO5dsBczKzy6kDK7mknMxUvqAu2p%2FFgKuE1j8AbULtTWW8KqXnsBNN%2Ft2rZ7gSfxV6YvyA1lT3fSQKZ0u35AaTUgMu2n52ApQ9XNpbvIGk050WsfUCTaav7gaTeNF%2BAJVpmn1kBSThb7AamZSvUBUoBTbpY1AcfcBVcfgDSdKMgOa20AU1HG4D9eoCn%2FYD1AVYCscgPKAU4AQHICAgIEAgMgQCBAICBAQCBAQCBAQEAgQEBAQEBAQEBAAEBAQABAQABAQBIABADAgCgAAwBdQAAkAAALxQGW4YFOgGeQCE4AHDnXYAtAE3CwBluL9QDHAFNKMgD%2BmAMyo4zIA5ys8sA%2BUJPMVL6gHdcT4YGc5QBSUrL0QA08rqAT8VcVi%2FIActT3K%2BkgZdu1Lt%2BQFKlT9PuAObadXdgEQ9XNpbvIFTnRZcVnUDMtNX95AG3DWi%2FAGFTlK3T0uY8gFdqcKr1QFK7pStW1N1%2FYBHcr8R6AMxPdOf7As3PVeOABK86uUk8bAKpuaVuZ1wAvuh0qwBqUlLT2vAC93eml%2FQCXSX9YAVGNaA1l3GLXIFsvcDSmKcazwBRlb%2BoDOjfmAxdvqwNaLea0A0mkrytAJS8zOGwNK3C6cgS9eANUum4GlhxjQCjzYCvHQBh6%2BgGk9QHwwJAaVTsAzdYAsAaAkBpbagOoEAgICBAICmBAIEAgIEBAIEBAQCBAQEBAQEBAQEBSBAQEAAQEBAQABADAOQICAABsAAmAAH1AsgZewF48gMsCAHm35gDx9AKVHIGM%2FQCzSAyBP23ANHGAM%2B74APHkAO%2FwBmcsCdrPVAZ1zy0pwAYb2tzzgA7ndYAy4SvpwAPnx9AJbxL%2BoBWNQB27xFrkDLylhvVgGlONZxQA1pq%2FUCnRuozqAdyh2%2Br9QMuYWrmUsY0sClJXbWnWwMpt5TnDapgKhtpdOQBcKXtv6ALdJrKtJ6OQJWtnid5Au2HNS36wBJS0%2BscOQLsiE9Xi5QG8SlnLb%2BvsA6dXE7ATStL%2FQFOOcIDUpqcxF%2BMgNrSdcgT2dfb1A2mozEzD2AE4cJSs%2BqA1h25X4A1qoqddAKF%2Bq%2B4Gqif%2BcwA3OwDTy6QCsgKf4A0A302Au1qdgNTqtLgBUtbAKjq%2FcBQCo8wHpkBTAfqAyA5AQIBTAQHrgBAtgGgECAgGQHoBAQEAgQEBAQEAgQEBAACAAQEBAQEAAQEBADYABAQAAAAE%2BAAAYA2BOAAAYBKAJ9ADqBMDOyAnEcZgDLzwAU%2FIA1%2BgGZV%2BgF0yAOXpGsgZUTsAN6rKtIAytn9QBNbS36gGWmBlRC39QB6xnLfjoAe2nQAaVpf64%2BgA3h76ADh%2BWoA5WFNzkDPdiH76T1AZW8Zh7AZmHCU9sT6oCdO3K%2FAGe62oUTrpgDML9VhdfoBp%2FFqf%2BcwAOZulp7qQKnlwlW2OAKXmF%2FLAqSlRsuPMBeMx1dIAUOJUPWawBfpiM58eQGkpaTxtFSApOIxsgNOaWFzmgBTEvRQwFNtSpxjRgPbo1Mc4QCq1rGwGlWnk%2BAHh1pICtdEtvqArN%2Ba1AV8YTfUBV2le%2FIDGGsznDA128XOugEm%2FUDWHADqk54YDpnx5gKvl6gMvYDSiJ8gHxwAqKmmAqMRkBWwEgNbbAVgKYCt0A%2BYCgIBAQKgHkBAQICAgGQECAgECAgICAgICAgICAgICAgIAAgIAbAAICAAIAYEAUAAAEwDkAAOUAeYEAAE%2B2wB9NQCssAp2Bl6R6gV6XyBmQCYYBqk54YA8Q348wDPXDAJ1jwwColRsuAB%2Bn0QBVTnXQDP6xEZAIlw8dNQMw4jGyAW3SwvegM3E8AZlxKnoALRqY0TwgDGe6sbAWNOIfGALh1pP1AN9EtV9QMa3aw1qBfpCbUzLoCpz3JXic2uoA%2B3DWW7eGA9qiYucPSefQAn5KcJwBNNy6Sia2A1HDjDXHkARCiE0ncIC%2FVJ3Nz54AV8u1rnR6%2BgGlbhppeUAaaiXHV7SBm4ypxGM1twBqJrTgDSrpbWzApWmLcgalKon%2BAKJnVvM6QBpK3OYuOQGMN5m5AVGtOfUBy68wGXE5awwNLH2f0AnTqo%2FsBX0pAaXHoA112AU0BTKnEgazL0A19NUBR53oA1G4DaYCvYBAgEDSAsAMgIDAEAgIEgFOgICAQIBkCmQECAgICAQIAAQICAgACAgICAgIAbAAICAgCQACAAACtAAAANsCAJAHAA2sAD1AIzIB9ZAK1zIE7wBmXE5e4BpIA3D2Ay9eKQFEddgBtPnYAr%2BOoGW5WyYA03LwuACPTVcADUKIlToAfqk9dQD9k%2Bum4BrDTXb5QAOprz6gYcxziPYChPpuvGoFMe7WzAy2k8QrcgTaVJT03TAHc6zmQBrM5avoBmLTeU7lZ6AUL%2FAKpz5tgTUuO3OscgU90TlrDAUqn2eegGGu5JqujvnIGn3fH8gETec2Aq5zS91yAXMb5UPUBT%2FZ6vMdANruXLe%2BEAudbWfG%2BACf8AlOVolQGkklE1qvzAErvCpdeAFzPKA1GyiALtm236ZkDXyTrnAEq4nH9AaftmQHRzXtgDXyjWEAy9KjR8AWLw87gaVvbn%2BwH3bAbgBQFaX2A3MAXiQNICA0s8gKfmBdQGdPQBAUwIBAVIDIEAgIFIDOwEmA5AQICAgGYApAUBAWoEBAQEBAQEBAUgQEwCQKQACAgIAAgMuQKQICkDIEASANgU6egAAADAGAXcgDcgGAJ%2B24GXh6fwBTC2QGW8xpvwAc6gGXMx9AB%2BrYA8ewAl4nEgY7k0vsAvugDLu88gE%2BOnIGbxqwKf23f4Avl1b30Ay3d4ygMzonOwFCSiacyum8AZzxhfwANOeV5AT7dlEPrCAFMuXPTMgZ7u6XHOADHEzH2qAHu4mMzYBo265xgB%2BUJOYTtKvoAtuH8ZUaN7AGc3frxGAJqcVlLboAYlW0sZAVrKvLezAUlEKut0nIBNvt1rCzFgNJy3f4A1jthO9J6gTSURtbfO4EnFYqE%2BgGoTma5y4ApTczpp6ZYGk%2BZ4A0o2uQKIuem%2Fn0Adfd5zgDVTMQAupfsA5nnUBUU1jNAKhy3jRcgXHkBqa4AaXmAp0rAcgPQB%2BiA0vDAVsqAZ0AakCwgGgFMByBSBqQFUBAPhgIEAgQCBSAyBAIEBAQEAgUgUoCAQICAJAZAKApApAAICAgIAApAGBTyAAQAAAQABOJAPqAMAkCd5AzkCn%2BgADIA%2F7An6ADq%2FYAdzzqBmqj2AM9AD%2BgKZ6AZcKVOeACVGWgDObAHwAPXZdQM9fN7AMVCrr6gZlS%2B18TCzFgDiZqQMulE2ANJY82%2FuBlOKw4hPoAtJzNe7j7AYlNzOjxXGWBqdm3x9gMwurmJ%2FkDERc9P56ATz7vOcAMKZah7dQLupNuGnpHkBU5e7z7AChw06V1i0AtZalLYCb7Z6wtgL9u51SaVgCbdzCXH4AI6rl7egGoaU2un3AVGFnHrqApw9HN9QNPGf2w2suAJuV%2FLeAFNZVT5AV91TGjnV0BqsLMafQBnKdgKcruS%2FuOgC%2Fks614wBXre%2BgCvCxQGuHPnoAu01psBpOdoAk7z54AVnreANT%2FQFhNuJgDXKAZQDbdYYCm84AvF7AaW%2BAEBAfqBSBoCyAgIEnkBsCAQEBAgIBAZAgECAgICAgICAgICAgICAgICAgIAAgCQIAkC5AmANgGQKQAAAgBuwBgU0AT5AZzQEATmbAJz4wAOVnUAfruBkC6z56ADtP6AGegBN%2BEBnW9eAJvmnoBnCbcOo84wBPdTAGW1IA5brWACW7mF42AzHly9vQCuJtdPuAdOgGW4b9QJ4zeHGWANyv7YAmsqp1wAX3VMaOdcATiWlmNPoBluJTt6ACddyS%2FlLoAP5LOXXt5ATnVt5mK9oYElf2xC9AHFNtxvpyBO01piOfDAy03aeFOOoGutXvuBJOMpznz0Albfb689AB0ku1uNGAyoceiutpQEo%2FwA6b%2BwGlecY%2FgDSjDiP%2FIBi4lOo6bgaT69d5AFKcK8uNQNNQnMcQAqU40A0s58vsAuremIyAxhzekagCfPr%2BANSpn0A10qfHIEtHPnsBqmqy6bAU%2BHOeQHa6QCpakBvKeAFPfcDSnruArYCxh%2BYDICox7gKAVs%2FQBXTyAUwJUAsBUqgHzAgECTAZAQIBAgIBAgGQIBAgICAgICAgICAgICAgACkAkCAgACYBIABAQAAN7YApAOAAC8QBnmPICkAwAOvsAWgLzAHV7YgAej10AxIE3r6AD3QBzPnsAO%2BrqQCeLXqAd2lwlgAtqfHqBl8aWBTu4sAved%2FMAVtrx5AZdJJNxowKVDj0X8AZrGm4BnNLH8AC2bX%2FwCQDFxKxHQBT1ud95Ayp7XCczLjUA7lCeOIAx%2Bycab%2BuwDrE4ePtAE5Sl6Yh2Awqc%2FtlRqBlNPL6T%2BNQJtTOun1AeUobq3f3AmnEuat%2BQBDX6rXffYBSabm%2FfEASWe1uXD%2FALAqwoTWPsAt3MyuVIA3mVNqFumBdtqpaedfoBvtdz6MB%2BPnvIDpE3mwJJNxb0bYDDq%2BPwBRbXmA276AaurwBr9VHc4xrsBJws%2BlgM10zQDXOcgN7W88gaSlcLTyAVXHQB85TAkvwBrCkCtVv9QFSmArZucgMrCgDU3mgHxAF4YCtwEB4AkBoCAryBrYCxYDIFNAIF9QEBAgIC5AgGwKQGQKQICAgIBAAICAgKQCQICAGBfUCAgAAAuQDgCwAAVaADYB4gAAgBgXnYGcgUAZgAcuwLYApQ3sASAN10yBlxP3AL1ywKKvGwBj0AHy5T0AI%2FAGWqkDLqlr9QK07AEspuXD%2FsAbWFErH2Au53muQMt5lTargDOatrXUCUtz7gD7fPcB0ibzYGYTcW9G2ANYvj8AYfbbV1YF%2B3dfRPqA3V4%2B4F%2BqjucY12AVSdryu%2BQCf1fGYXrYA4l5icqn77AXao0txPoAw1FYpvn0AlEzPj6gVJQ1WY4zqBdvycy%2BjAMP5dzbamANQplVxGfIATSxb7Xn2A0omsb5AUp7ZdR5UugDG7AWsTrpmwCJprr%2FAGBvNv0wBXF0%2FHkBrbj6ALd%2FrTducPxAC5WrS2Al8YjMIDVduXPIDUQ%2FR%2BoFLr8WBqNJi5j2AUlp%2FIEvVagaVeeQG1FdQFAKaiH1Ae2d%2BjAlu3MAaUZAU48gFRNASxID1YD1AgNAXUBAp2AXIFUQA4ApAQECAgFAQEAgQEBAUgQEBAQEBAQEAPgBcgFYAsAAFIEAAHuBAQABAF7%2BYBywKsgE%2BwB0AOoB1An41Az5AXiAB80AP6ADe3uAOdGAVERoAP8AXWQBxDT9H6gDeI86sAdUnFzABG2vqBnnK10AFXnkCvbGeoAszIBSUPEzHvqAL5PL6MDPLcxgChS2q4jPkASliW%2B159gCk6xvkAVqXptsugFGZYGe5Ymp0yBhqaa6%2FwBgazb0lRgDLmF8qeun8Aa249k%2BgA3f603mcPxAF3Lu07mlqgKO2PjEwl4zAE0u2Jcpa%2FzIA1hvDqsAPyb1lzkCeP8AXy36IC7ax1awAQnLS6rWgFQk9YqVGQCIvu8nczgBiFdt3GAGVNrOoGvlKzAE4UxrmI0AYmvawNZUbyAJxrbcNcyBpNvLhYgC1l9ZA03KSdzr4gCiHMJPSMWBp24SjdP%2BAFKXGmvUBlROgCmsLOAGnMugFP6Z%2FoDSyBbPRgMt%2FkB0zO4Cv7Asy4%2FIGlS6AOM%2BoCvdgMqbApmwHGAEBAkwFXwA8gXUBAcgQDIFIFT1AQECApAfMCQEBAXUCAgICAQIAAgICb3AAICApAJAKApAgBgUgD6gQB5AQGeoFjqwBtADfkAOgLP4AniOoGZh5AL3jgA1l%2BoA%2BfUAxeOgE8wvHoBnNeoA2o4YBKwsuvQAcOZdAE77AWu4GHpswCX1c5Au61%2Fr5b9EBKqXVoDFOXH5AqSfGwGYi35O84AsK7b8gBvtbtVhsAfdKzEgTjtmPPGgA7r2AHajedfoBlONbbhrmQFS8uE6iQDWX1lgPc5SXdc6z%2FQBENOEnpGHIC1LhKN0%2FXQCSlxcLPUBiVShfbTcAeVNJYfHqA9r7X8XpH3Ay5j4p%2FJNQvHkA6ppeXlNQARKUqlqrV0AunDxhMCSm%2F4AscrOydga4URgDSUwutAVXLrnpwBdrWI%2FoDVpt5esXXsBJrEw7j0A1UKHDWgErmeif4AU3VKdgFKJjKAZTpf0A%2BIAc2879QFZl5xQDpMxyAypnXWNANK1svsAz5LR8AKapgWkK5AegDmAHGcaAK3AZ%2FIDenQCQDICtvEAOOoEmAyBZ%2FICA4ApAQIBXuBAUgIEBSgKdAGQICkBAAIBApAAEAkCAPEgUgQEBAAEAAXIEASASqAHtkCkAyBNwAcgD%2FkA6dALxABPIBOkf0BY5YGZWPQC844AzmZ9QCf6AIhOMgDadICfhAZzMxL16gCzLziv6AtE5jkDLcOdVmNAKJW34AHlaLR8ASacPSPuBh4%2BKc6AD4AGpXC1Vq6AnTh4wmAZsAeN1l6J2ANaKIxt9gKqXsBhtXLrn%2BABRiP6A1DTbiXrF17ACaxMO49AGoUOGlj3AyrmdoT6VQFLqlrCT%2BwD8YTjK3AJTpVp0AdYm0s%2BYE2sRytQDhu5iegDl9G11UAXx%2BLSedFrS3AraS0zN5kCrbTOPqgCJmEkn%2FdgOFVLyw%2BqAV2pd0Zpx%2BQNT3ZmgFum271ajXQCnWIyuoCsVeqgCnDVJ1UqQFPbeI2A0lPjSQHtcQ1etagK1%2BWqnUCp4VgKzLX9AajMuIAVMKAFN4bAZt66RsBLMTa1A1PAEnvnEgK8dANRD50AraXqA%2FgBzikwFYrH5AYUwA2AzUgUgKwBT6APQB8eQCmBLkCAdZYCBdAKQGQKQJsCkBAsAQEBAQEA2BSASBAQEBAUgAEBagAEBSANgAE2ASBAGGBS2gD8AGegBpsBRcZAG2AN1PuAN%2FjqATX2Ay36AX5iAKJ8aSATj7AG87AZcPSwKLl5%2BwA1mXDXQAuFABLw31AG866AZy4m0sgTaxHKAzOjzMT0Av59IAI%2BL50XQAtpLTM3kAce2cfUAiZhJJ%2F3YFEKqXlh9UAPtScZpx%2BQMt92swAN023erUa6ATesRldQJYq6lJADdpqk6qVMgXTVpRtoArtnxpIEnENWrda%2BQFDv5aq8gVOoUgTqp%2F8A09tgKYXDxw8gKXdphYpJ%2FQDK%2FwBfqr1eYU7AUPv%2FAGwqlgTT%2BLylzsAvfGfCAMJyuG%2Fp9QFU%2BM0vetwJ1aVQlekgaW8YeGAzCwp1nfADCy6WvlyBKW9u4BmX%2BufaQNOlDx6fgAlwqpqkBpJreZ30AVTu8dQKMJ2sVi9gGb2az1A1NcgKzDUaUA48a7gKc1HoA4r1ewDMLjQBU%2BSxuBJ3WfUBt2A3D0XIDOoDMTPRgKfoA9MfQBApjr9wHnTUBvzAZl0BY6AMuAKIAZsCAfqAgUgWAGZAgKYAbAvqBZAgICnIFIDPAEASAgAFL0AnyBTQEATYEBN%2BoBIFIABTIE%2F7AJhAVgE3WQC3YBowKQCYn3AteABvbGADnYAbhc%2FcArPqAZ6gDcusgT2ePQDLbjFPQChrr9gDDvIGXtle1gTd7NAGn5wATpERVADrxqBmZqPQCdVN%2FwDT2Am4XDtLZ5AL8ljEgZ1rOrzqBm%2B64jdgTmHlLnYAbm5jPhAGE5XDf0%2BoDh5rNL3rcDPc4tKoi9ACJcxh4YGZhYU6zuqkBhZdLXy5AlLe3d4%2FIE22%2FwBc%2B0sC7lCh49PwAT3fFKKapeQD8Wt5nfTqBY7rvHUAjCysQsX1AWpXxblRV6AXao9JafGwFEZmvL0YEtIUrCcgSXcu3GLSWvqBNzmJ0WmtgHyraHPAGnonW3brfQDLuLcU5i2Az6vDSdICUNpd3bG%2F9gaTTiHcLxoBpfKrhxrzkAaTvdZ9gNZvzq84AdYWdpz%2BAJJyoWJA1az1%2BQEnDnSfMDXa25jOZeVIEo0e%2FRgSnflgaTxVdMAUpKdXMgaUq020A5UTUUA9tfVp8AOM6eXoArTVaMCUxjyAZnrovUBn6%2BQD4gC2sDSfroAqHlRuBJzgDSnewDkDXP0AdedgK9FgBtfkCkBTyBSBIBnigKvMC%2BgDxIEv7AQLYCuAKQKQEAApApnIFOwDLAAIC8QBdALxIBIFIEAAU%2BgBSAumALNSAAXUA215ALjHkBMDM%2FXyAXz6AZegFPqAU8qAMynhgUvewBrXgCe%2F0ANazsAXULAA5X5Ay3crE51Ak8%2FV8gFaP8AHnywCeJT4wBme1KdWv5ArVpt9uQJ2vi3UVegGVX3XQCxn8ejANoUrCcgZS7l2xGLha%2BoB3PRxOi9bAPlW0PyA09E627evQDDeLcZnUAn10aTwAU2l3dsb7eoBTw3MLw8AK%2BVXHdGvOQBpO91n2A05d%2BdKc4AKmFn%2FAMzmttAKO6VCVN6gT%2BS%2BvyzpkAmHKVTnUB7W7jrLypAmoV3zeABtx8XDh9cALmklei0nUCTdNQ7cJ37gCTfk8AKa%2BWqeIevqBRFJXrE14kBh6LE%2BcAZnth9M%2BXO4BhQ5aw8NAb7cZlpxpAD%2B2sbbgaSqgCYba03mX4gBTttK9GlqAp2oxNMClwkvKPwA4TldGgNU0nlLUBXKAsR8vvvAE8zisbTsArOzwwN3p7gS58gF0rAZqKceYDOkXotJ1AVNNQ8wgJS%2FUDSd7PYB6KwEAlR9wFY9mBrt9wGwHoBTba9wFZYFtGNAGX%2BAHC%2B4FTS1QCugF1Apv7AOv1AegEBAU6AIEmBKwKb%2BwEAgE0BAKArAgCQKcgU%2FwAS6AgLIEBdQB5AtQJzoAATAG9KAp%2FgAnYAv0Ak71XABikBWBmVDAML6gS62AOQLTgDLcNte4FNuv7AzNqMTTApdL0gAdK%2FVAVNJzKVSAeQGXUSBlu5xWALXbRgTmP1xz%2FABF6VgA7qVgZbqHFeYE9Elei0nUDKbpqHbhO%2FcCt%2BTxkATXyy08Q9QKIpK9YmvEgTWyxPnAGG1D3jPlyBnSHLWHhoDXbjMtONIAGu7WJmFqBRVY8fgAmG2tN5l%2BIAU7bSvRpagGqjE08dQL9oSXk1%2BAGITlZmGsQA00m3KVS%2FoBK8riMZAwmkrf7c7IDajzdT1AG3onnMgOd96qvMDL7m003emwDTcJQk75YCu1TKmuuPMA7odLNKNuvqAQmozFtRyBJty4%2FfCXiAGfdeTbAm7%2Br6%2BYC2218vMDSac6rPqgNONOiS4AE96i98AMvtxN6ccAK7lfc7xEAMKLzupA1hQ%2FcA1nC3yAunj%2FWsAanSP1WLgCnWQFNxxqBJpK3YG1H8gU7J5zIDn60BfKU5dgaqY2dgK3UgLa0yBVHTQBT9QHx6gTf8AIE29fMDSaYDP4AZ%2FIFMeYFKznADWoDhQwLnHuBY8wGfQCAk3%2BQKY6gaoCkCApkC8MC5AnAEBJ%2BoFIFIE51ApkCApApgCnXIFWoBhAGsgTrzAm%2FQCkAl%2FkAn1AqApAM%2FUAmU5AqbheYBrKAG9FkA0%2BqAE9dQLx6gDYA5m%2FMAlMCfF6QATvpYA2%2B3E3oASv9O8RABC1zwBUlDrSwMvM4XqBl156gLfH6qYuACdW61mr8MATccYcgYmFeeeANV5upAy25pPOZAnf1qgMvubTTd6AVNwlCTvlgSSmVPjqAdzTmFe23UDEJqNrajkATblx%2B%2BEvEAM%2B68m2AN36pvr5gXdLa%2BXmBJpt6rK80Bpxp0SXABOZqL3VATb7cSpeNY4ApV9zvEQBQovO6kBhLth1pek0BnuSapU37%2FUC7p3j6UBVr%2FraseYD24e23ABEKe6lVVuA3M5Wi3kAuYb26egFTXyx66ATnPcqa8dAH5OLcJL69QCPjhT4xqBOPk1E8Zx7aAa%2FV0lc%2B4D268095Ap3xrwAuFj7YA05b530AsSk%2F238gFyk40pvcC43lb%2B4GrdIB7X8dLiwFqYUy0sUBTT9n9gFNRMdAFxFYb9wFzvACucroA9rzttwA6S64AecrRAVzDAU5U4Aby8AMuLqgLADNxEgNe4EteQGd%2FMBwAuX13Ad0nYF9tQL7gPCAk4AfsBTkCT4AaAmBfUBTAuXQFPpsBAU6gQDIABNqQGgACn0AJAXP8AIB0dgT4Ap03ALwgJOAL7AE0wKVsAPjAEwDrkCTz4oA5dcAU652QBcwwCakAvLwBfLyoAwAN3ieAJxjX7gZ1fIBOrxrwANxj7YAXL%2FIGW8pO8gDm4013AHtvK3ALdKwBdz7XzEsCamplpYoAbp10f2AJWYAO5VSpv3Az3T050oCrLytK%2B4Am72%2BwFFT3UqqtwLWcrRbyAOZhv8egGG1Hyx66ADnPcqa8dAH5OLcJL69QCPjhT4xqBOPk1E8Zx7aAP6ukrmuoAk7xbjkAnfGvAC4WPtgBabfO%2BgE9UnPdmc6ATlJxpTerAOH%2F1K1fuA4dq%2FGoC5vWfcAeXd5rNgE9qqc0kA%2FNq4rSZyBatuUnmOgE56LaNwLNaTU6yAPdvRRv5gTXxUr0AU4nZ6qwMulM9KgDX7a2lovwBpOVWmmAG45q9%2FUCq3OFWnoAyv%2BZa0jgB%2BT7lH03AU9pnN%2FYClrlrTACtdX4yAqHWUA8ZaA03LzfQDPa3cOks4A1MZyBq%2BsgTi7vgBlKvRAK7mtI6zkBTuXMcAMvotuoFmtPrIC3r6AOAFOOm4BMa9NANXqAzIDp9wKVbnoAytLApboBn15ArXUBu9wJQwIBmdbAk9tAGYAgJ9QGV%2BAL5eGBeoFPoBfQC59AICAgICAgKUBTtYA3NAU%2BvIFPqBbgGegAAty%2BQMpvTTUBxnIB7gDeQKVieiAPk1p0AJ1uNQKfQAbnoAN6%2BgA1FoBmJ2Aw3GvQCvXGwFM%2BQA5i%2FX%2BwCrc9ACdr28gJttR4kAnrPIGZjrtgCu7l%2BMgZSTcW0rAt1loCbl5sDEu4eNQKYznxqBOb1kA7su745AJ7VU5pIC%2BbVxWkzkAm23MPMdABt%2BUY6gZ%2F1Wmk6yAPdvRRv5gTXxUr0AU4nZ6qwMulM9KgDTnW0tF%2BALMxpbWEBXDetXv6gFW5wq09AGV%2Fym9o4An3PuXx6YnIEntM5v7AUtc9y0wAPuSrV5yAtNvMudtpgCUZiXEdY%2FIF2qFTnbDlAFJS5XVTYDEJqI7vuBXE%2BefN6gDzOrUeYDMqE44QAk3PbhxXVgaU1b4f9AZ7M88qaAp1cfFKKxXIEnM31WgGlrOs%2BrA1CcR7ALUtTLWjp8AFeSzO4GpusAO6ePX6dALtcROlTyBXnOoG1lXWwF3PE73ngB0hRLULowB9yVa65A1l5mwFRnICsfQCUJT9QNLEYf3AZcT9wJ55deYDM0mBKcAaWl%2BYF26%2F3QDOunAEnM%2FQBx5gNVAE%2FVAMr0%2BoDrWALcCTgB5yA%2BdATeJAgKdAHIEoAkBUgHHUCmpAnnkCnRAS2AV1AEwLnQCmZAvuBPSAJ2AT7ATdgW6AE4yBPfIFe4A9JAp26IAbWAJ2AV1AEAaSBcYf3ApcT9wB55Apml6AHGALz8wM9r8RNADeumK4AJmfdAWJnWQBxUADtqcb0AV6b7gTzCwAObTVev06AZTi30kCc%2FwCs6oCi8%2BXQDPc8e4A8Qol0ujAH3JVq8uwJ28y5%2BmABQ7iXEeOoF2qFTnbDlAZpKb81qBYTWH9wMtuJ9b89wB5nVqPMBmVCccIASbntw4rqwNKat8P%2BgM9meeVNAU6uPilFYrkCT%2BU3nK0AoiZ1n1YE0nEewC1LUy1o6fABXpmdwFzMLH0sCu01Xr9OgB94SwBJwnUaw9gFNd1NKsSoAk5nuVym46bATXc4baT1awBNf8yl5RC9wK5lO56KdgBVaUPZ1KAVTUNfHfUAdrXW28rGQGoubiZWwBl4q40cgTczFNrTIE2plL%2BPEgPzju%2B8XD5A1KajHy2zSA2m3CUQ1O0gCW7xxNAWkzmK%2BgD5Sp6vkCnZqv8AL%2FgBTdavZY3AVtowGds6APbCWKa1wBT7wlgBThOo1jgBTTqMbgKeXnLgBc035gPEgVzm%2FRdAFONI4xKAU7VqNwLK%2B7YGq9QLIDM8PgClTMAPyhgLa6TsAy%2FICXXAF55AZ80BT%2FADONeAJAM%2BoEmowBT74Ak86AKadASeoE5zqA8AXTPoBTwBT6AHiQEAkBbAG%2BAGbApXrsBW60AEBeIAnPUA8ICnGr2AgBvbIAnCwBT70gCaYFKdNACeWusATmm%2FMAe0gWtZ9EATGFD%2BwBPNADtfdgXiwMu3w%2FWQJueG1oANqZgCfdD8YAG1G07dAKW4WkAZXXABpnOgE%2BnyU9XyATtH%2FwAv%2BABt1OdlgA4uwBu6tvFACaSxla4AG%2FelgAmE6jWHsApruppViVAEnnuVym46bAZ7vk4bzrsAP%2FzP2he4Bcync9FOwAqtKHs6lAKpqGvjvqAO1rrbeVjIDUXNxMrYAy8VcaOQJuZim1pkCbUyl%2FHiQF90P7xcOsgTaajHy2zSAbcJJQ1PUDKW7xxNAUVM5ivoBOdvkp6vkBymsLR9VsBNS1PkuAJRLWE8%2BYCpf469AMpp3la1jfUC%2BXydTu2%2BNgJ5abhOLnbkB7VMZhv015AkozXOlfgClO1fTn0Avk8K1hp4Am2nLu5vDApe06%2FT7gOe5xbiPDAz%2BqSednWEBpPHo%2FLqBpuMuHo9%2BfcB%2BS7aw9Elt5gFvt63FeuLAsuZt%2Bq0A01WN1DAfkks%2FkBmKxoBS34sBXdtYCnKawtH1QDExONE9gJRLWE%2FuBpS%2FwAASad5WtAPyl169ALVrEgK8fUBVZ%2FigGdfFgPyemMAUw7%2FAIAZ4AdaAqha8gPj0Am4y45AZSr6AVte8AUzrkBjZeTAZgCn8AMt%2BLAk9gKaemwDnPpwBSugCgCfTWgKZdeoFrGJAVYEufUCkClgUwwKeJAtaAKifcBAm4y%2FMA%2BSVa8IClx7wATLzYE%2BnkBSgCfwBNt%2BLAE9rApprGzANvpwBa7fyBeIAJTvK1oA%2BUuusgDy%2BQJWAYz66UBTqvYA%2BT0vTgAbh3fXAE29gDLcAZpKc88ICn8ADcZcbMC%2BSVYeyX8gFvt63H35AJlzNv1WgA1x5MCbSWfyANxxoAS2p%2FsAXdtf3AJlNY2fVUBNS1PkuAJRLWE8%2BYFLfO65YGJTvK1r1Az8vk6ndt8bATy03CcXO3ID2qYzDfpryBJRmudK%2FAFKdq%2BnPoBfJ4VrDTwBNtOXdzeGBS9p1%2Bn3Ac9zi3EeGBn9Uk87OsIB29PNdQLucU3D07t%2FEgXyXbWHoktvMAt9vW4r1xYFlzNt%2Ba0Av849QH9M6TCeAKYVXPG%2FmBK6mHOF0zoBKU3SnrbAlLUr1UsCXe7i1rdgSnul25dAT%2BSbeu6qYAv8przXVgSbTdRGITwBNxEVr19QJ9sKesICTTp71rTYFSpZ0WbApbfFJMBeJyuaA1MtKPNOQFtrLcvTC9WBd3c3WG9F9gGHcKnXWgK3b0tALeYUxlP3AU%2FPUBV%2FZgUxj1A1%2BufR4AvlCq543AVdTDnH30Ak2m6U9bAVLU%2FkBXdnVdbAlLl52AbTnX6wA%2F5T9vMBTcuumcAMxivHIF8Y%2ByAk1j0AZSxnRZAZvjQCeJyuQGbj6ATbQDLfUBjOwF10sCb2XkAz5wBZApj8gNZQFOwErApjSwK9AFd22PcCmZ12ApczqBTE%2BoFOQKdgJ19kBJrHoASljOwFN8aATxOVyBTLj6ADbQE%2B5vGQJ67AV5eloAb%2FAJQFPmAZ%2BwBMfkBrOnoATVASusAEw3QBbVAXyd7e4BbnXYCfymdfqAYTXmvMAmG%2FboBNxigBqF9EASnXoAUsZ2yANueNGAd2JyuaAm5aUVo05Am2st3hYXuBnu7m614AmnDhUwC8vS0AN24UxlP3Ap80rAEn3etPgDP%2BceoD%2BmdJhPAB8qq54AJmsOftkDMtN0m%2BtgSlqV6qWBLvdxa1uwJT3S7cugJ%2FJNvXdVMAX%2BU15rqwJNpuojEJ4Am4iK16%2BoE%2B2FPWEBJp0961psCpUs6LNgUtvikmBdyqcrmgKZaUdGnIE21lu8LC9WBd3c3WG9F9gK4T%2FwCltrowCFUw3OmnAGr7oT5%2FgDMqH0lLAClE9rU%2FW7qQBtxy9eAHhU9QKZrRZAOU7mEBWlpOXkBcuuq8wJNXGmmOQJYx1XPhAUXH%2FM1OsvAF21jGtToBYt1PCYA8ytIbzcgaV8LXZwAp22060zAGp%2BMtgEYT%2FwBNwBQ9%2FwBFgDSbnjdcgWLf54A1N3hagV09VsA7Tdgal90JgEqH0mMAKUfq1P131Am6nfXgDXSnqBTNaagPKdzCArS5AXLrxIDKuPwArp1QCs8afgC7XGPMC53AeVpYD4e1AU3LAZi2BfV0BXvQCm%2FHIFiwGbvAFtuBdbAbeQCa8sAPDApfqBSBTppqBcregK11yBOwKdgKf5QFrx4oCT%2FkC9pAG9VoA%2BHtQBO%2BgFMSwD6sCvegJNgHUCm7wBX5oAAnLAJUe8AHDAm3HL1AnxT1AJmtFkA5TuaALS5yBOWBSrgA8uqANY0089ABVjz9ADl1PCYA8ytIbzcgPtOdnAGZm3p5gTcWBl7f9NwAQ5zPYsASb8cgGLfjQBn9lKlLXzAHMJ%2F9LbXRgDiptz6cADlwnnxAGJUN8SlgBSie1qfrd1IA245evADwqeoFM1osgHKdzCArS0nLyAuXXVeYEmrjTTHIEsY6rnwgKLj%2FAJmp1l4Au2sY1qdALFup4TAHmVpDeblAMeS12cAScttpwtMxkCn4y2BSoWqdy7YC5mVnl1IGV3NJOZipfUCdtT%2BLAswmsaeWQGl2prLeFWPPYCab%2FbtWz3Ap%2BKuKxfkBOWp7lbrEoAy7Uu35AMqVLxOmmlgTm2nSm7Aoh6ubS3eQGnOiy4rOoGZaauc1mQGXD7dF%2BABVaVunpDmPIBSThVeqAU13SlatrUDS%2BS8fwAy2%2Fil%2BuscgDcfetgFUk4hdNPQBTpQ78bAMN1OMICTULVO5yBpz59QJd0JP3YC7an8WBK4TWNPLIDS7Z1bwqx%2FADeUuQKYXTADlS%2FyBJzp%2FQGpUgUvKfnYCoT13SAZTn1r6gSbTzPuAy4jRfgAW8f3ICknHOwDKcxayBWgGZcJVqBTH3AVWkfgCmluBZqcAMqPeQJ%2B%2FUCTqQJ3kCmcgMqFu9gJ7rqBTCsC5YFM6f0BStwKdn9QLD%2BiApT%2B8AEtNWAzpoAT756gSigKU51WgBaAZbcLABj7gSrj8AU0twB35YApUcZkAfv1AJw9gJ21P4sAzXjAFSUrL0VADl2uoFMK9MADtS%2FyAZdq8%2BQFKAG4ua3sAiHq5tAUpztrFeYBLTSmdtZApcPt0X4AyqtZdPrMASScYvYAlOUrWUAfsrApbfxS%2FXWABuPvWwAoVxC6aASdKH%2B3jYCabqcWlsASoWqzLtgHdKcrPWpAyu5wnmKl9QB21P4sCzCaxp5ZAaXamst4VY89gJpv9u1bPcCn4q4rF%2BQE5anuVusSgDLtS7fkAypUvE6aaWBObadKbsCiHq5tLd5Aac6LLis6gZlpq5zWZAZcPt0X4AFVpW6ekOY8gFdqcKr1QFK7pStW1N1%2FYBHcr8R6AMxPdOf7As3PVeOABK86uUk8bAKpuaVuZ1wBd3dDpVh%2BYBSUtPa8AL3d6aX9AJbxL05gCUYr5UAu3cRFrmAB5SiHuwK4pxhzigBq2tX6gM6N1GdQBq7fLfrwAw4WrTpYxpYDKSu2tOtgZTbynOG1TAU020uFyBJ4i3t%2FQG5S2iJnIGphOIS06rABGNXrAEnr5%2BQC1My%2FKfqBJxPdPjIDlTPVeOAFdfK8AKpvbMzqAvuusagUpKWnteAF7vpp%2FAEt4l6cgKjGtAMy7xFrkC1%2B4DNU454AuNwGdG%2FMCfL5bAbhauaX9gaTSV29gBNvKvACmm4XTkCXrx%2FQC3HTfIDNOMAXuwKfHAE7%2FAABTrID59UBLr5ASpvbfkBbusAEwr%2FgCbAUBVjUCy%2BNVyBAU1tr5AH3AZ0b8wB5t%2BYFp50AykrzsAS9c4ApWF%2FIBIFS6bgMwnGADbV8AE%2BOAJz%2FABMXoBZ16oAWc9c4AphvRZnnAF3O6VagEpK%2BnAA%2BbQF4XIBWNQJuXe1rkAfhsAuMxzigBq41YFOjdRb1AGrt8t%2BoA8LVp1%2BAGVF5AxLeU5w4ApTbS6cgHlL2%2FoCcLpmcgUwnEJaPnQAjGr1gAT18%2FICady9cT9QMzE90gGbnqvHAAledXKSeNgFU3NK3M64Au7uh0qw%2FMApKWnteAF7u9NL%2BgEt4l6cwBKMV8qAXbuIi1zAA8pRD3YFcU4w5xQA1bWr9QGdG6jOoA1dvlv14AYcLVp0sY0sBlJXbWnWwMpt5TnDapgKhtpdOQBcKXtv6ALdJrKtJ6OQJWtnid5Au2HNS36wBJS0%2BscOQDtiE89zxcoBaSlductvzv2AtOridgBpWl%2FpgM4t3hc%2BYE4a3iL8ZAnKwpucgZ7lUNQtJ0nqBpNRmJmHsATDhKe2J9UAunblbcIBdxCiddMcAZhfqsLr9ANP4tT%2FzmABzN0tPdSBU8uEq2xwAp3mop9AFdyu%2BLA1FuM04kCt3ERaf9AHbE7cQAt1KyrSejkBVrZ4neQNdsOal%2B8ASVp%2BEBdsQt%2FUBxMZ1fjoAp17TsBPVL%2FQDOLzhc%2BYFKfMa%2BMgatcvOQB7PxIGk1vvDAph4oBw7tfgB6VOoBC%2FVfcDVRP%2FOYArnYCp5pICTv6AK7s3xYFrQDLzHmAJqdgFvVdYAsrZgKfnPqBLMgSiFuAuLjOrAp%2FAA9d2BTjkBz%2BQK1pIAwGfvDAJhxFAXVygF%2FXUA2QE48swBXIFXSACbAPl%2BAHp1ALzEbMATU7ATaysq0tnIFMrZ%2FUCTT0n6gCtp%2BEAdsQt%2FVATqYzqwCfwAPVLIE3jnQAbT8tQJytJ1yBnu2a9dJ6gKa0cZh7AZmHCX659QJxra26AT9J10AzH%2BVhdQF%2FFqf%2BcwAOZ2WnupAKeXCVegAneyap9AJdyh3xev0AotxmnEgDbekRaYGU1OwA3UrKtJ6OQJWtnid5Au2HNS36wBJS0%2BscOQDtiE89zxcoBaSlductvzv2AtOridgBpWl%2FpgM4t3hc%2BYE4a3iL8ZAnKwpucgZ7lUNQtJ0nqBpNRmJmHsATDhKe2J9UAunblbcIBdxCiddMcAZhfqsLr9ANP4tT%2FzmABzN0tPdSBU8uEq2xwBS8wv5YFSUqNlx5gLxmOrpAChxKh6zWAL9I%2BMZz48gKJfxeMxFSALteMbIDTmlhc5oAtqeIYAm2k1OMaMB7dH2zGk4QAq%2F6rD0AcacQ%2BMAXDrSfqA76Jar6gGt4x3LLAv0hNqZl0BU57krxObXUAfbhrLdvDAe1RMXOHpPPoBS%2FWZVfcBlpx4r6gKdpOaw9eUAtUk3ET4sBzrLw2BS8wv5YDKiVGy4AXjMLl0gJQ4mnrpgCntxGcgOsPHSpAkn02QG5dLC%2FAApieIe4Em2pU4xoA9ujUxzhAScf9VjYBVacR0AU9%2BgCn5JaoCm7xqtQH9YTd6gVO0r3Aow1nV6gK1i51ApfrIFLTgBm0nPD16AWkN%2BPMBzy8NgUvbwwKoqNlwAt%2BXXCAqcJ09QCViMgOsP6AXtsgGcaL8AF5ApqVIEtGgKY1AsAU79AGfbYAm7xhoC%2FWmwCZtZAmsNZ3wBLi510ApfqANw4AptZ4evQCeEm%2FHmBTPLw2AS8wBUlUbLgCfjZAFOJp66AE9uIyBaw8dKkDMaY2QC260X4ALieACXEqcYAu3RqY5wgBOP%2BpWHoBTGnEdMAE79AKc7LYA1vGGtQD9ITamZdAFOe5K982gBrDWXl4YEk7i5w9J8IClvzmVX3AG2nHH0AJtJzOj15QA6STcZ8WAZ1l4bApeYX8sCpKVGy48wF4zHV0gBQ4lQ9ZrAF%2BkfGM58eQFEv4vGYipAF2vGNkBpzSwuc0AW1PEMATbSanGNGA9uj7ZjScIAVf8AVYegDjTiHxgC4daT9QHfRLVfUA1vGO5ZYF%2BkJtTMugKnPcleJza6gD7cNZbt4YD2qJi5w9J59ACfkpwnAE03LpKJrYDUcOMNceQBEKITSdwgL9Unc3PngCju7WudHr6AWsNNdvlAC1EuOr2kDFxlTiMK624AYTrTdfh7gaVe7WzAG%2B1YUK3P1Am0qSnpumANTOreZyoAfjbnLVxGGBRabyncrPQChf8AVOfNsCalx251jkCnuictYYClU%2Bzz0Ay6dfrFfcC34pAaVYzONo8wNSnzqvcBT7Xn06gE%2FJThOAGG5dJRNbAMcOMNceQFEKIlTogFfFJ3Nz54Av2T66PX0AdYhpeUALrTz2kAlxziOoGoTrCAU493wwJtTircgTaVK%2Bm6AszvrPAGo3zqBRhvM3IFWtOfVgOXXtyBS4nL3AVideQJ06qKAt%2BKTAYjGdugDK67ASaf46gE%2FJThMBzLwuAHbbVcAWFESk9AL9UncgX7J9QLWHS8gF1p1e0gZuM3iPYBj0AZj6rZgDa8rsCbWM%2FwAZn76QAxmfOAKMN5m5Aq1pz6sCdtx5%2BYBLicvRgOk%2FUDLcPaP7AN3tSAYjGZxtADK67AEr%2BOoGZlbSBNTLwgF%2B2GuAM4URKnQClQ9dQL9k%2BvuATcNNLyAnUtrq9pAzcZvEYzX2AoTbWm6%2FkBmPdrYAbWlK3IA2lSv%2BAMu5950gBi3OYuNmARhvKdyAV%2F1TnzbAmpcdudY5AJ7onLWGApVPs89AMunX6xX3Ay9eKQFjGZx08wKU%2BdVPmAJ9r89OsgE%2FJThOAJpuXSUTWwGo4cYa48gCIUQmk7hAX6pO5ufPAFHd2tc6PX0AtYaa7fKAFqJcdXtIGLjKnEYV1twAwnWm6%2FD3A0q92tmAN9qwoVufqBNpUlPTdMAamdW8zlQA%2FG3OWriMMCi03lO5WegFC%2F6pz5tgTUuO3OscgU90TlrDAUqn2eegGGu5JqujvnIGn3fH8gETec2Aq5zS91yAXMb5UPUBX%2Bnr3fgCXd1b3wvFATmbtZU%2BLwAT%2FynK0SrkBSSUTVyuFu0AK7wqXXgCac8ryAn27KIfWEBKZ7p9syAvuTrnH9AGOJmPtUAPdxMZmwDRt1zjAD8oScwnaVfQBbcP4yo0b2Azi8d2ZzwAwu5ptxzle9gDfm2tZA1aT10f4AV0nmZgAaaUV0d85A2%2B74%2FkAibzmwNK96%2Bq5ALmN80BpP9nqwJd3VvfC8UBNubxkCnROdoA0kkomtV%2FQEnPSkAuZ5WAJrZRD6wgJTLn2zID8prnCAscT4VAL4xmQKac17YAflCzCAZelRo%2BAKddQJQ2rj3XuBN%2BbaAbv0YEvF4AGmlp0YGvlABnnkDSfX%2BuQC8b5oBn9uQL5eb30Am9HayBTon0AkklE1qunQCTm8aATn0AmtlEPrAAm5fhyBPuTrnAFjifGALu9sgWjlx7YAvlCzCApqqjfgAmLw9wL%2FAE024917gDfm2gG49mALxcgZcpR7ALcAGeeQJOd6%2Bq5ALxvxuAz%2B0Zf4Avl1b3wgBtzdrPjfABOidaRQBCSia8bAEz0wBOZ5QA09FEP0AFMufbMgT7k65wAY4nH2oC7uMZmwDRt1zjAD8oScwnaVfQCbcP4yo0fAGJi8PM54Aq7mm3HOV7gZbXVtayA3D10f4AEuJ2czCYA13JNV0d85A0%2B74%2FkAibzmwFXOaXuuQC5jfKh6gK%2F09e78AS7ure%2BF4oCczdrKnxeACf8AlOVolXICkkomrlcLdoAV3hUuvAE055XkBPt2UQ%2BsICUz3T7ZkBfcnXOP6AMcTMfaoAe7iYzNgGjbrnGAH5Qk5hO0q%2BgC24fxlRo3sAZzd%2BvEYAmpxWUtugBiVbSxkBWsq8t7MBSUQq63ScgFS%2B3pMLMWBOE5cT90AYUJ3pPUCaSiNrb53Ak44cQn0AWl3TNe7j7AZlNzOjxXGWBqdnPE%2BwFC2TcxP2kAiLT6P89AJ593nOAGFMtQ9uoF3Um3DT0jyAqcvd59gBQ4adK6xaAlDbbwsLkA6K4iNYA1Mr%2F52xQA12qVOVt9EBLuSStp9d5wBvObv142AenK46AW6tpYyArWVeW9mApKIVdbqZAJUvt1qYWYsBpOan8AWFCd6N9QJwoja3%2BQJOOKheQGqcz%2FADABMuZ00A1PM8AKja5AsKU%2BnjgCefrnOANVNqHt1Au6pbiHpHkBU5b1eQJQ4afNASh28AX1xAD8p6bcALhefAAnWWBrPNgXT%2BALfbzAli87gKVQq6gE5XTCzAE4makCwom9wJwvu2BJxw4hMBcPPhAEy540%2FLAZ5ngC8rnIBjXoBTf1z0AamYj%2BQDuq3EbAVOedQCqj2AqecaIA6dAH5em3AA4WueABOssCz6gT45AHU5hdQJayrzOwCkohV1vWQCVfa%2BJhZiwBwnNT%2BADCib0AHH5YBMcVCYC4cz%2BaAzKbmdNK4ywGdnPE10AK2uYn%2BQDCmenjgAefd5zgDUKZah7dQDupNuGnpHkBOHL3eQM04adZrkDNNucLHUDPRXERqBqZX%2FztigBrtUqcrb6ICTUL9mvPrhAOc3frxGAJqcVlLboAYlW0sZAVrKvLezAUlEKut0nIBUvt6TCzFgThOXE%2FdAGFCd6T1Amkoja2%2BdwJOOHEJ9AFpd0zXu4%2BwGZTczo8VxlganZzxPsBQtk3MT9pAIi0%2Bj%2FPQCefd5zgBhTLUPbqBd1Jtw09I8gKnL3efYAUOGnSusWgFrLUpbATfbPWFsBft3OqTSsATbuYS4%2FABHVcvb0A1DSm10%2B4FWmcaa6gEw3Sc318SAvGf2w2suABuV%2FLeAFNZVT5fUAvuqY0c64AXDbSzFx9AKYlO3psBJ13JL%2BUugA%2Fks5de3kBOdW3mYr2hgSV%2FbEL0AcU23G%2BnIE7TWmI58MCX7bQ%2Fv8AUATh5rfCAqmHreAF93NTint1AIhN9zTcRb1jAC5UtSlsAvuU9YWwGpbdUmlYEu5uHMLWvwAR1XL29ANQ0ptdPuBUsZxpqBTD6gLxm8OM0BNyv5bwAprKcT5AU%2FLWNHPkAysLMafQBmJTsCTppeIAm%2B5Z18cALnVt76fZgSV%2FbFegDw2630kCdp%2FTnwwFOdo%2FIAnfG%2BAGbvW8AXy5qcAWE22sfbAC%2FOAJtetAMtvhwALubuYAvEvb0AdJtAXToBTDAnjnWAKZXhgSazj2Ap%2BVTG4FWNY0ApiU72Appx4gCbazrQA3u530Al4WKAuH7gTufoBJztABN5%2BwFN3reAJ90dNvEgGE22nXvGAJzbUpbATfbPWFsBfs3VJpWAJt3MLp%2BAD16vb0AribQF9cADcPcCdLnWMsAbleGBJrKr2AzfdUxo51wBOHKWY0%2BgFMSnb02Ak67kl%2FKXQAfyWcuvbyAny28zp7QwDX7YoAfLdb6ADtP0jnwwJfttD%2B%2FwBQBOHmt8ICqYet4AX3c1OKe3UAiE33NNxFvWMALWWpS2Am%2B2esLYC%2FbudUmlYAm3cwlx%2BACOq5e3oBqGlNrp9wKtM4011AJhuk5vr4kBeM%2FthtZcADcr%2BW8AKayqny%2BoBfdUxo51wAuG2lmLj6AUxKdvTYCTruSX8pdAB%2FJZy69vICc6tvMxXtDAkr%2B2IXoA4ptuN9OQJ2mtMRz4YGWm7Twpx1A11q99wJJxlOc%2BegErb7fXnoAOkl2txowGVDj0V1tKAFEfHTf23Asu6WP4AVs2o%2F8gGLiU6jpuBpPW533kDKntcJzMuNfcC7lCeOI8fcCS7u2tN%2Bs7AOsTh4%2B0ATlKXpiHYDCpz%2B2VGoGU08vpP41Am1M66fUB5Shurd%2FcAxDlddo0AWk1GrptY82BTw5Xq%2F6Au7S4Sw%2BAJT3KfrzmwMtN2nhTjqBq9avfVgKndOc%2BYD222vD6ATcJJOtHoAyocei22oCUR8dN%2FbcBy7pY%2FgCWzaj%2FyBYuKdR0A0m86%2FWQBT2urmXGvuAupmKxAFfbXjUDWsTjT7ATlKX7ZAdnN5UACe79fwAtqZ10%2BoDytat39wDZz57ANNcum1jzAvlw5V8%2BEBPS4SwwFS1P1AM4eAGd6v6gPmnv5gSy0ANxh1owKVceiAk1jTcCznp%2FACno2ugFMXFYjoAp6gZTh5nNagLqQC1QDrny%2BwE5Sl6bZAtnN6QBlPd%2Bv4AW1M66AXRZ8cgGznz2AnDXLqVjzApezlXz4QF3aXCWGBKe5T9eeQMtN2nhTjqBqd6vcAveZz5gScuAMtwqdaMClQ49P6AKx7gWc0sfwBKMOI%2FwDIBi4lOo6AU6679QMptOFeXGoF3KE8cR4%2B4El3dtab9Z2AdYnXH2gAcpS9MQ7Ano5vKS1AxKeX0n8ADamddPqA8pQ3Vu%2FuAYhyuu0aALSajV02sebAp4cr1f8AQF3aXCWHwBKe5T9ec2Blpu08KcdQNdavfcCScZTnPnoBK2%2B3156ADpJdrcaMBlQ49FdbSgBRHx039twLLulj%2BAFbNqP%2FACAYuJTqOm4Gk9bnfeQMqe1wnMy419wLuUJ44jx9wJLu7a036zsA6xOHj7QBOUpemIdgMKnP7ZUagZTTy%2Bk%2FjUCbUzrp9QHlKG6t39wJpxLmrfkAQ1%2Bq1332AUmm5v3xAElntblw%2FwCwKsKE1j7ALdzMrlSAN5lTahbpgCU4lp5mwFS2n7gXx895AdIm82BlJNpW9G2Aw6vivbAA%2B22rqwL9u6%2BifUBurx9wL9VHc4xrsAqk7Xld8gE%2Fq%2BMwvWwBxLzE5VP32Arm1bzOoDFcLTDwBJQ9q01AnGW5T03Al20nOa8sATTiXNW%2FIAhr9VrvvsApNNzfviAJa9rcuH%2FYDKwolY%2BwGn3XmVygJvMqbVcMCVqpaeZsBUtp%2B4F8fPeQGdJvNgChtK3o2wGOfQCi2npYF%2Bzvon1Adr81yA0ob2AU4Tv0sCmumaAG1PnkBl7W88gOVwtMaAKp7VcagTjVynpuBJVnNeQE04l6Z8gCGqWv12AVKdueM4gBWqbmn%2FYBKwolY%2BwC3ea5UgDcTK1ULhgWVq99QFNzPuBR57gM6TebAyobS8m2Aw6AItq9wL9nfRAV1ePuA0objGoEqTv0uwCf1fGYXqANqdYnOOdQK5xbzOoDErhaYeAJVxVxqANrVynpuBJeuPIAcxL0ALVLX6gSlZAt03NP%2BwCVSUSsfYBbuZrlSBlvM3ardMAzSlp5mwFZn3AGvPcB0ibzYGUk2lb0bYDGL4r2wANW81YA%2Fk76T1AJxePuBT2qO5xjXYCVJ2vK75AJ%2FV8ZhetgDiXmJyqfvsBXNq3mdQGK4WmHgCSh7VpqBOMtynpuBLtpOc15YAmnEuat%2BQBDX6rXffYBSabm%2FfEASWe1uXD%2FALAqwoTWPsAt3MyuVIA3mVNqFumAJTiWnmbAVLafuBfHz3kB0ibzYGUk2lb0bYDDq%2BK9sAD7baurAv27r6J9QG6vH3Av1UdzjGuwCqTteV3yAT%2Br4zC9bAHEvMTlU%2FfYC7VGluJ9AGGorFN8%2BgEomZ8fUCpKGqzHGdQLt%2BTmX0YBh%2FLubbUwBqFMquIz5ACaWJb7Xn2AqTrG%2BV4UACUqXUbVS6AMbsCaxNTpm%2FFAZiaa6%2F2BvNvSVGAMuYXyp66fwBrbj2T6ADd%2FrTeZw%2FEAXcu7TuaWqAo7Y%2BMTCXjMATS7Ylylr%2FMgTiGnpo35gTmoetyrAmrhOLTSfosgSS011mGAQs5WHUAXao0txPoAw1FYpvn0AlEzPj6gVJQ1WY4zqBdvycy%2BjAlT%2BXc5amANJKZVbqMgKcYt9rz7AKiaxvkAV9suo2ql0AY3YE1ianTN%2BKAM011%2FsDWbfSMAVxdPx5AO3D9EwLubn9XD1nDAe75LDaWwB%2BsfHMIBf65cpAUqGnpo%2FUCnn2sB6OLkBXGvqAVnO9QAqtM5YFaiur5AVEzNgSaSh4mY9wLt%2BTmX0eoBj9u5txMAahTKriM%2BQAmliW%2B159gKpp1urXigJWpdRtsugFC1YE1ianTN%2BKAM011%2FsDWbeMRgDNwpp66fwBrbj2T6AZ7nf6uHrOGA906NpbAH6x8YmEBOO3LmAJtRD9G%2FMAbfhWBecXIF45AOcrWgJV55Arqur5AFludQJNJQ8ZjjOoF2%2FJzL6MAw57nLUwBQplVxGfIAlaW%2B159gKpp1vleFAElKl1G1UugFG7AmsTU6ZvxQGXdNdQKZt8qMAZcwpp%2Bn8AL049k%2BgA3f603mcPxAF3Lu07mlqgKO2PjEwl4zAE0u2Jcpa%2FzIE4hp6aN%2BYE5qHrcqwJq4Ti00n6LIEktNdZhgELOVh1AF2qNLcT6AMNRWKb59AJRMz4%2BoFSUNVmOM6gXb8nMvowDD%2BXc22pgDUKZVcRnyAE0sS32vPsBUnWN8rwoAEpUuo2ql0AY3YE1ianTN%2BKAzE011%2FsDebekqMAZcwvlT10%2FgDW3Hsn0AG7%2FWm8zh%2BIAu5d2nc0tUBR2x8YmEvGYAml2xLlLX%2BZAGsN4dVgB%2BTesucgTx%2Fr5b9EBdtY6tYAITlpdVrQCoSesVKjIBEX3eTuZwAxCu27jAA32zarDYE%2B6VmJAnCmNcxGgDE17WAu1EZnwgMpxrbcNcyAqXlwnUSAay%2BssB7nKS7rnWf6AIhpwk9Iw5AWpcJRun66ASUuLhZ6gUqG9HrPiACVhK3UbQBQu6ZcryApzO2f6A0qeJb%2FoDLWG8OqwA%2FJvWXOQJ4%2F18t%2BiAu2sdWsAEJy0uq1oBUJPWKlRkAiL7vJ3nAGlWbbuMAT7u2bTvUB%2BUrMTQC4Uta5iNAGJr2sBdqIzPhAZTjW24a5kBTby4TqJAtZfWQFuVDudQKIadJ6RyAu3CrdPG%2BgElLjRZ6gUqJinqBfJYWXUbQBU5lgM56Z%2FoBWdwB6PRgPyfW8gTxmd%2FICTjHVrAFTmF%2BQFOF01QBy%2FGgDhcvyAm1NrzAn3TrEgGJjXONAHNewC3KjeQMpxrc2uZAU29YWIANZfWQJuVDvkCw59IAnmF6f0AZcevUB%2BSzoBn5aLLqAKnMsCnM7Z%2FoBVPeQMvRvDoC%2BTesucgTtf6nfogJVjq1gAzLS6rUCVJ6pVKjIBEX3eTuZwAxCu27jAE32zarDYA%2B6dYkAcKY88aAWsewE3KjeQMJta23DXMgKl5cJ1EgGsvrLAe5yku651n%2BgCIacJPSMOQFqXCUbp%2BugElLi4WeoFKhvR6z4gAlYSt1G0AULumXK8gKcztn%2BgNKniW%2FwCgMtYbw6rAD8m9Zc5Anj%2FXy36IC7ax1awAQnLS6rWgFQk9YqVGQCIvu8nczgBiFdt3GABvtm1WGwJ90rMSBOFMa5iNAGJr2sBdqIzPhAZTjW24a5kBUvLhOokA1l9ZYD3OUl3XOs%2F0ARDThJ6RhyAtS4SjdP10AkpcXCz1AYlUoX203AHlTSWHx6gPa%2B1%2FF6R9wMuY%2BKfyTULx5AOqaXl5TUAESlKpaq1dALpw8YTAkpv%2BAJ43WXonYA1oojG32AUlS60BVcuuenAAoxH9AahptxL1i69gBNYmHcegDUKHDSx7gZVzO0J9KoCl1S1hJ%2FYB%2BMJxlbgEp0q06AajHrCsAy23EvDzkCScy6eKn0wBaJzE6%2BIAG0nOqzGgGolUoX203AHlTSWHx6gPa%2B1%2FF6R9wMuY%2BKfyTULx5AOqaXl5TUAESlKpaq1dALpw8YTAkpv%2BALC3WXonYFwsY2%2BwGlFL2AZzLrxsBdrTqP6A1abcS9YuvYATWJh3HoA1Chw0se4GVcztCfSqAU3suiYFETGVuBSnXl0A1t6wAatuJeucgSzLp4qfwA6JzE6%2BIAm0nOqzGgDErEL7abgTyppaPgCTThzQA3UJzOAHoBZ8tVgCbh3jRgSuwKfNZ4ArwugCtvYAnd142Ak1iP6AbTer%2BwAmsTDuPQC0UOGtABXM%2BT6bAUvZcJAURMZApTpdOgD%2FAHCAMy3EvD6gCzLzip9MAWicxz4gCbU%2FLXWNAHKxC%2B2m4A3DU0lh8ASacPSPuBlzHxT%2BUqF48gHVNLy8pqACJSlUtVaugF04eMJgS3%2FgAb81nrYGXsojG32Atl1oAlWm65%2FhgCjEf0BqGm3EvWLr2AE1iYdx6ANQocNLHuBlXM7Qn0qgKXVLWEn9gH4wnGVuASnSrToBqMesKwDLbcS8POQJJzLp4qfTAFonMTr4gAbSc6rMaAaiVShfbTcAeVNJYfHqA9r7X8XpH3Ay5j4p%2FJNQvHkA6ppeXlNQARKUqlqrV0AunDxhMCSm%2FwCAJ43WXonYA1oojG32AUlS60BVcuuenAAoxH9AahptxL1i69gBNYmHcegDUKHDSx7gZVzO0J9KoCl1S1hJ%2FYB%2BMJxlbgEp0q06AOsTaWfMCbWI5WoBw3cxPQBy%2Bja6qAL4%2FFpPOi1pbgVtJaZm8yBVtpnH1QBEzCST%2FuwGIVUvLD6oC%2BKXdGacfkC%2FbOgE3Tbd6tRroBN6xGV1AlirqUkAN2mqTqpUyBdNWlG2gCu2fGkgScQ1at1r5AUO%2FlqryBU6hSBRfyav3SVcgT7Zltw10qQJJwvjPibApeG%2BoFNum9I21ygLWJtLPmBNrEcrUA4buYnoA5fRtdVAF8fi0nnRa0twK2ktMzeZAq20zj6oAiZhJJ%2F3YDEKqXlh9UBfFLujNOPyBftnQB%2BVS359dAL5axGV1A0nVXUpAE4apOqmwGVpq4jbQBXbPjSQJOIatW618gKHfy1V5AqeEpfjqBRctXtqkvUBjLbhrpqBKYUT4mwKXhvqBTby9I21ygKbibSyAtrEcgZnRu5iegGsvo2uqgCj4tTnRa0twKW0lpmeQJxtpnH1QFE4SSf92BYVUvLD8gKEnGaf9gU92XgCbptvq1zoBTrEZXUCTqrqUkAN2mqTqpUgU11cRsArtnxpIEnENWs1q%2BgBd%2FLVXkCp6ICi5av3SVcgTUy24a6agSmFHjkAl4b6gT7reXpG2uUBLMTaWQJtYjlagHDdzE9AHL6NrqoAoXa7zp5LcAltJaZmwJte2cfVAZd4SSf92BaVS8sPyAPik4zTiPqBftnQCbptu9Wo10Am9YjK6gSxV1KSAG7TVJ1UqZAumrSjbQBXbPjSQJOIatW618gKHfy1V5AqdQpAov5NX7pKuQJ9sy24a6VIEk4XxnxNgUvDfUCm3Tekba5QFrE2lnzAm1iOVqAcN3MT0Acvo2uqgC%2BPxaTzotaW4FbSWmZvMgVbaZx9UARMwkk%2F7sBiFVLyw%2BqAvil3RmnH5Av2zoBN023erUa6ATesRldQJYq6lJADdpqk6qVMgXTVpRtoArtnxpIEnENWrda%2BQFDv5aq8gVOoUgTqp%2F8A09tgKYXDxw8gKXdphYpJ%2FQDK%2FwBfqr1eYU7AUPv%2FAGwqlgTT%2BLylzsAvfGfCAMJyuG%2Fp9QFU%2BM0vetwJ1aSiEr0ncCi5jDwwCYWFOs7qpAYWXS18uQJS3t3ePyBNtv8AXPtLAu5QoePT8AE93xSimqXkA%2FFreZ306gWO67x1AIwsrELF9QFuXt3JXw9wLR784sC1hqIqgKPjCePvvngCTmVELjkCdVP%2FAOntsBTC4eOHkBS7tMLFJP6AZX%2Bv1V6vMKdgKH3%2FALYVSwJp%2FF5S52AXvjPhAGE5XDf0%2BoCqfGaXvW4E6tJRCV6TuBRcxh4YBMLCnWd1UgNZdLXy5Ak23t3ePyA%2FKX%2BufaQF0oePT8AXycJRlUvIBiN5nfQBw7vHUAjCysQsX1AW5e3clfD3AdHvziwDWGoiqAo%2BMJ4%2B%2B%2BeAJOaiFxyBOqn%2FAPT2AZhXh44eQJTphYpT9ABO6zq8xYFfdeFqwFzDylzsBTriJ8ICmJno2BJ3xml7%2BYE3FpaRegDlzs8MA%2BULSdZ3wA1l418gBS%2BoE3LrPtIF3UoePT8AHycJRTVIChreZ30Aph3x1AuMrFYsCbl7dyV8PMgOj35xYBrDURVAUfGE8fffPAEnMqIXHIE6qb%2F6ewFMLjTh5AlOmFilP0AzP7VnV5qdgC%2B6%2FcCcw8pc7ADc3tPhAGE56N%2FT6gKp8Zpe9bgTq0lEJXpO4FFzGHhgEwsKdZ3VSAwsulr5cgSlvbu8fkCbbf659pYF3KFDx6fgAnu%2BKUU1S8gH4tbzO%2BnUCx3XeOoBGFlYhYvqAty9u5K%2BHuBaPfnFgWsNRFUBR8YTx9988AScyohccgTqp%2F8A09tgKYXDxw8gKXdphYpJ%2FQDK%2FwBfqr1eYU7AUPv%2FAGwqlgTT%2BLylzsAvfGfCAMJyuG%2Fp9QFU%2BM0vetwJ1aSiEr0ncCi5jDwwCYWFOs7qpAYWXS18uQJS3t3ePyBNtv8AXPtLAu5QoePT8AE93xSimqXkA%2FFreZ306gWO67x1AIwsrELF9QFqV8W5UVegF2qPSWnxsBRGZry9GBLSFKwnIEl3Ltxi0lr6gTc5idFprYB8q2hzwBp6J1t2630Ay7i3FOYtgM%2Brw0nSAqbS7u2N9vUAp4bmF4eAFfKrjujXnIA0ne6z7Aacu%2FOlOcAFTCz%2FAOZzW2gFHdKhKm9QJ%2FJfX5Z0yATDlKpzqA9rdx1l5UgShYej6OABSteXn7AMzFN9rrGPIA%2FVKdWnK97yBKVabfbkBalfFuVFXoBdqj0lp8bAURma8vRgS0hSsJyBJdy7cYtJa%2BoE3OYnRaa2AfKtoc8Aaeidbdut9AMu4txTmLYDPq8NJ0gKm0u7tjfb1AKeG5heHgBXyq47o15yANJ3us%2BwGnLvzpTnAFrCz%2F5nNbaAC%2BUqFhgalqvP5Z0yATcpVOdQNdvc3PFy8qQJNZT36OAJdeWAyqqe18Y8gCe1KdWnK97yAqVabfbkCalfFuVFXoBdqj6tPjYCiMzXl6MCWkKVhOQJLvXbjFwtfUCbnadFprYB8q6PyA09E6%2F%2BevQDO11mYsBn1eITpAVNpPtjfb1AJXdhuYXjQBXy3hxrzkAam91n2A05d%2BdKc4ANUln%2FAMzmttAKO6VCw3qBP5L6%2FLOmQCYcpVOdQHtbuOsvKkCULD0fRwAKteXn7AMqqntfGPIDM9qU6tX9byAqVabfarAna%2BM1FXcACr6tPjYCxnTy9GAbRawnIAl3rtxi4WvqBNzmJ0WmtgHyraHPAGnonW3brfQDLuLcU5i2Az6vDSdICptLu7Y329QCnhuYXh4AV8quO6NecgDSd7rPsBpy786U5wAVMLP%2FAJnNbaAUd0qEqb1An8l9flnTIBMOUqnOoD2t3HWXlSBKFh6Po4AFK15efsAzMU32usY8gD9Up1acr3vIEpVpt9uQFqV8W5UVegF2qPSWnxsBRGZry9GBLSFKwnIEl3Ltxi0lr6gTc5idFprYB8q2hzwBp6J1t2630Ay7i3FOYtgM%2Brw0nSAqbS7u2N9vUAp4bmF4eAFfKrjujXnIA0ne6z7Aacu%2FOlOcAFTCz%2F5nNbaAUd0qEqb1An8l9flnTIBMOUqnOoD2t3HWXlSBNQrvm8ADbj4uHD64AXNJK9FpOoEm6ah24Tv3AEm%2FJ4AU18tU8Q9fUCiKSvWJrxIDD0WJ84AzPbD6Z8udwDChy1h4aA324zLTjSABru1iZhagUVWPH4AJhtrTeZfiAFO20r0aWoBqoxNPHUC%2FaEl5NfgBiE5WZhrEANNJtylUv6ASvK4jGQM4j5ffeAJ201VYxDewEv8AWzw5gDTTj9caz%2FAAldw4daYAmoV3zeABtx8XDh9cALmklei0nUCTdNQ7cJ37gCTfk8AKa%2BWqeIevqBRFJXrE14kBh6LE%2BcAZnth9M%2BXO4BhQ5aw8NAb7cZlpxpAA13axMwtQKKrHj8AEw21pvMvxACnbaV6NLUA1UYmnjqBftCS8mvwAxCcrMw1iAGmk5lKpf0AlOq4jGeAKYj5ffeAKbTxWNugEnezw8AbuP1xz%2FAAuYcY8gJwld%2FgCfdXxcOPMBbwkr0Wk6gCbpqHbhO%2FcCSb8ngBTXyy03Ub%2BoFEUlesTXiQGHosT5wBme2H0z5c7gGFDlrDw0BvtxmWnGkADXdrEzC1AoqsePwATDbWm8y%2FEAKdtpXo0tQCbUYmnjqBS4SXk1%2BAHCcrMw1sBSmk25SqWBTOVxGMgGI%2BXi4Ay3cqqxj0Ap%2FbZ4cwBpzH645%2FgDN6w4x5ADpOb9cADbj4uHHngBc0kr0Wk6gSbpqHbhO%2FcASb8ngBTXy1TxD19QKIpK9YmvEgMPRYnzgDM9sPpny53AMKHLWHhoDfbjMtONIAGu7WJmFqBRVY8fgAmG2tN5l%2BIAU7bSvRpagGqjE08dQL9oSXk1%2BAGITlZmGsQA00m3KVS%2FoBK8riMZAziPl994AnbTVVjEN7AS%2F1s8OYA004%2FXGs%2FwAJXcOHWmAJqFd83gAbcfFw4fXAC5pJXotJ1Ak3TUO3Cd%2B4Ak35PACmvlqniHr6gURSV6xNeJAYeixPnAGZ7YfTPlzuAYUOWsPDQG%2B3GZacaQANd2sTMLUCiqx4%2FABMNtabzL8QAp22lejS1ANVGJp46gX7QkvJr8AMQnKzMNYgBppNuUql%2FQCV5XEYyBjtmF%2F6rOwG1EPePPIFc0nPWwJx76AXd8o7vl%2FGQB%2FGVGJvwwJfH5VOKzEAPdEOOI2i8gY%2FX43ETxuBpTLn%2FAHp4QFv0c5ibAnMveHuAd%2FylfLmY2Ad5%2FwAzXoA1piugEpjzr%2BABTfxmJvpGgDXyfy4jwgM%2FrDmflxsBpR8OIqdvMDLj5%2Bdb%2B4FX7RGf28dANOI%2F%2BdM7AV6%2BfvsAL5RWIUz57gZ7Zhf%2BqzsBtRD3jzyBXNJz1sCce%2BgF3fKO75fxkAfxlRib8MCXx%2BVTisxAD3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<h1 class="title toc-ignore">R2</h1>
<h2 class="subtitle">Predicting Diabetes in Pima Indian Population</h2>
<h3 class="author">Meghana Tatineni</h3>
<h3 class="date">02/19/2019</h3>
</header>
<hr>
<div id="introduction-to-machine-learning-in-r" class="section level3">
<h3>Introduction to Machine Learning in R</h3>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co">#install.packages(c("dplyr","ggplot2","caret","reshape","kernlab"))</span>
<span class="co">#Data Manipulation</span>
<span class="kw">library</span>(dplyr)
<span class="co">#Visulization </span>
<span class="kw">library</span>(ggplot2)
<span class="co">#Machine Learning </span>
<span class="kw">library</span>(caret)
<span class="co">#Data Manipulation </span>
<span class="kw">library</span>(reshape)
<span class="co">#Machine Learning </span>
<span class="kw">library</span>(kernlab)</code></pre></div>
<p>The dataset is originally from National Institute of Diabetes and Digestive and Kidney Diseases. The purpose of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. This datset is restricted to females at least 21 years old of Pima Indian heritage.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co">#Read in Data </span>
<span class="co">#Set Working Directory </span>
diab<-<span class="kw">read.csv</span>(<span class="st">"diabetes.csv"</span>)</code></pre></div>
</div>
<div id="exploratory-data-analysis" class="section level1">
<h1>Exploratory Data Analysis</h1>
<p>After loading our data, we are performing Exploratory Data Analysis to get a sense of what we are working with and how much data cleansing and wrangling we have to do. Usually 80% of the data science work is preparing the data for analysis and 20% is modeling our data. Thankfully, this data set is already clean so we won’t be doing much data prep. This will never be the case when working on a real data science project.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co">#Looking at Data </span>
<span class="kw">head</span>(diab)</code></pre></div>
<pre><code>## Pregnancies Glucose BloodPressure SkinThickness Insulin BMI
## 1 6 148 72 35 0 33.6
## 2 1 85 66 29 0 26.6
## 3 8 183 64 0 0 23.3
## 4 1 89 66 23 94 28.1
## 5 0 137 40 35 168 43.1
## 6 5 116 74 0 0 25.6
## DiabetesPedigreeFunction Age Outcome
## 1 0.627 50 1
## 2 0.351 31 0
## 3 0.672 32 1
## 4 0.167 21 0
## 5 2.288 33 1
## 6 0.201 30 0</code></pre>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">str</span>(diab)</code></pre></div>
<pre><code>## 'data.frame': 768 obs. of 9 variables:
## $ Pregnancies : int 6 1 8 1 0 5 3 10 2 8 ...
## $ Glucose : int 148 85 183 89 137 116 78 115 197 125 ...
## $ BloodPressure : int 72 66 64 66 40 74 50 0 70 96 ...
## $ SkinThickness : int 35 29 0 23 35 0 32 0 45 0 ...
## $ Insulin : int 0 0 0 94 168 0 88 0 543 0 ...
## $ BMI : num 33.6 26.6 23.3 28.1 43.1 25.6 31 35.3 30.5 0 ...
## $ DiabetesPedigreeFunction: num 0.627 0.351 0.672 0.167 2.288 ...
## $ Age : int 50 31 32 21 33 30 26 29 53 54 ...
## $ Outcome : int 1 0 1 0 1 0 1 0 1 1 ...</code></pre>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co">#Change Outcome to Factor</span>
diab<span class="op">$</span>Outcome<-<span class="st"> </span><span class="kw">as.factor</span>(diab<span class="op">$</span>Outcome)
<span class="co">#number of missing values </span>
<span class="kw">sum</span>(<span class="kw">is.na.data.frame</span>(diab))</code></pre></div>
<pre><code>## [1] 0</code></pre>
<p>There are no NA values in this dataset so we must have no missing data. Wrong! Looking at the first couple of rows, there are 0 values for Skin Thickness, Insulin, and Glucose which does not make sense. Let’s return the number of 0 values for each column to get an idea of how much of our data is missing.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co">#number of 0 values </span>
<span class="kw">colSums</span>(diab <span class="op">==</span><span class="st"> </span><span class="dv">0</span>)</code></pre></div>
<pre><code>## Pregnancies Glucose BloodPressure
## 111 5 35
## SkinThickness Insulin BMI
## 227 374 11
## DiabetesPedigreeFunction Age Outcome
## 0 0 500</code></pre>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">colSums</span>(diab <span class="op">==</span><span class="st"> </span><span class="dv">0</span>)<span class="op">/</span><span class="dv">768</span></code></pre></div>
<pre><code>## Pregnancies Glucose BloodPressure
## 0.144531250 0.006510417 0.045572917
## SkinThickness Insulin BMI
## 0.295572917 0.486979167 0.014322917
## DiabetesPedigreeFunction Age Outcome
## 0.000000000 0.000000000 0.651041667</code></pre>
</div>
<div id="cleaning-data" class="section level1">
<h1>Cleaning Data</h1>
<p>Since over 40% of the variable Insulin and 30% of SkinThickness is missing, we will remove these varibles from our dataset. We are also going to replace the 0 values with NA.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co">#Replace 0 with NA</span>
<span class="co">#remove Insulin and Skin Thickness</span>
diab<-<span class="st"> </span>diab <span class="op">%>%</span><span class="st"> </span><span class="kw">select</span>(<span class="op">-</span>Insulin, <span class="op">-</span>SkinThickness) <span class="op">%>%</span><span class="st"> </span>
<span class="st"> </span><span class="kw">mutate_each</span>(<span class="kw">funs</span>(<span class="kw">replace</span>(.,.<span class="op">==</span><span class="dv">0</span>,<span class="ot">NA</span>)),<span class="op">-</span>Outcome,<span class="op">-</span>Pregnancies) </code></pre></div>
<pre><code>## Warning: funs() is soft deprecated as of dplyr 0.8.0
## please use list() instead
##
## # Before:
## funs(name = f(.)
##
## # After:
## list(name = ~f(.))
## This warning is displayed once per session.</code></pre>
<div id="imputation-with-mean" class="section level2">
<h2>Imputation with mean</h2>
<p>To deal with the zero values, we will use Imputation.Imputation is just replacing missing values with substituted values.We will replace the missing values with the mean of each feature.</p>
<p>Read more here:<a href="https://towardsdatascience.com/how-to-handle-missing-data-8646b18db0d4" class="uri">https://towardsdatascience.com/how-to-handle-missing-data-8646b18db0d4</a></p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co">#Replace missing values with Mean </span>
<span class="cf">for</span>(i <span class="cf">in</span> <span class="dv">1</span><span class="op">:</span><span class="dv">5</span>) {
diab[<span class="kw">is.na</span>(diab[,i]),i] <-<span class="st"> </span><span class="kw">mean</span>(diab[,i], <span class="dt">na.rm =</span> T)
}</code></pre></div>
</div>
</div>
<div id="lets-do-some-visualization" class="section level1">
<h1>Lets do some Visualization!</h1>
<p>Now that we fixed the missing values, lets graph the distributions of all variables for diabetics and non diabetics.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co">#Distribution for All Variables</span>
<span class="kw">library</span>(ggplot2)
<span class="kw">library</span>(reshape)
diab_melt<-<span class="kw">melt</span>(diab,<span class="dt">id.vars =</span> <span class="st">"Outcome"</span>)
<span class="kw">ggplot</span>(diab_melt, <span class="kw">aes</span>(value,<span class="dt">fill=</span><span class="kw">factor</span>(Outcome)))<span class="op">+</span>
<span class="st"> </span><span class="kw">facet_wrap</span>(<span class="op">~</span>variable, <span class="dt">scales=</span><span class="st">"free"</span>) <span class="op">+</span>
<span class="st"> </span><span class="kw">geom_density</span>()<span class="op">+</span>
<span class="st"> </span><span class="kw">scale_fill_manual</span>(<span class="dt">values=</span><span class="kw">c</span>(<span class="st">"green"</span>, <span class="st">"red"</span>)) <span class="op">+</span>
<span class="st"> </span><span class="kw">labs</span>(<span class="dt">title=</span><span class="st">"Distribution of Variables for Diabetics and Non Diabetics"</span>)</code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co">#Box Plot</span>
<span class="kw">ggplot</span>(diab, <span class="kw">aes</span>(<span class="dt">x=</span>Outcome, <span class="dt">y=</span>DiabetesPedigreeFunction,<span class="dt">color=</span>Outcome))<span class="op">+</span>
<span class="st"> </span><span class="kw">geom_boxplot</span>()<span class="op">+</span>
<span class="st"> </span><span class="kw">theme_bw</span>()<span class="op">+</span>
<span class="st"> </span><span class="kw">scale_colour_brewer</span>(<span class="dt">palette =</span> <span class="st">"Set2"</span>,<span class="dt">name =</span> <span class="st">"Diabetes"</span>)<span class="op">+</span>
<span class="st"> </span><span class="kw">labs</span>(<span class="dt">title=</span><span class="st">"Box Plots of Diabetes Pedigree Function"</span>)</code></pre></div>
<p><img 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" /><!-- --></p>
</div>
<div id="lets-start-modeling" class="section level1">
<h1>Lets Start Modeling</h1>
<p>Before we start modeling, we need to split our data into a testing and training set.The purpose of this is to prevent overfitting. Here we are randomly splitting our data into 75% traning set and 25% testing set. We use the training set to train our model and the testing set to determine the accuracy of the model.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co">#Simple Train and Test Split </span>
<span class="kw">library</span>(caret)
train.rows<-<span class="st"> </span><span class="kw">createDataPartition</span>(<span class="dt">y=</span> diab<span class="op">$</span>Outcome, <span class="dt">p=</span><span class="fl">0.75</span>, <span class="dt">list =</span> <span class="ot">FALSE</span>)
train<-<span class="st"> </span>diab[train.rows,]
test<-<span class="st"> </span>diab[<span class="op">-</span>train.rows,] </code></pre></div>
<p>We can finally start the modeling our data using statistical methods and machine learning!</p>
<p>We will be comparing four different classification technquies by using supervised Machine Learning algorithms. Supervised learning means be already know the outcome of our data. For this data, we already know the person is either diabetic or not.</p>
<p>We are using four Machine Learning models 1.Logistic Regression 2.K Nearest Neighbors 3.Support Vector Machine</p>
<div id="logistic-regression" class="section level2">
<h2>Logistic Regression</h2>
<p>Logistic regression is a simple statistical model which predicts a binary response (ex.YES/NO). For this data, we are predicting whether a woman is diabetic or not.</p>
<p>Read more here:<a href="https://towardsdatascience.com/logistic-regression-detailed-overview-46c4da4303bc" class="uri">https://towardsdatascience.com/logistic-regression-detailed-overview-46c4da4303bc</a></p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">fit_log<-<span class="kw">glm</span>(train<span class="op">$</span>Outcome<span class="op">~</span>BMI<span class="op">+</span>Glucose<span class="op">+</span>Pregnancies, <span class="dt">data=</span>train, <span class="dt">family=</span><span class="st">"binomial"</span>)
<span class="kw">summary</span>(fit_log)</code></pre></div>
<pre><code>##
## Call:
## glm(formula = train$Outcome ~ BMI + Glucose + Pregnancies, family = "binomial",
## data = train)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.3001 -0.7251 -0.3997 0.7363 2.3220
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -9.276670 0.815670 -11.373 < 2e-16 ***
## BMI 0.113705 0.017643 6.445 1.16e-10 ***
## Glucose 0.035460 0.003966 8.942 < 2e-16 ***
## Pregnancies 0.120009 0.032597 3.682 0.000232 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 745.11 on 575 degrees of freedom
## Residual deviance: 540.80 on 572 degrees of freedom
## AIC: 548.8
##
## Number of Fisher Scoring iterations: 5</code></pre>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">predict_log<-<span class="kw">predict</span>(fit_log, test, <span class="dt">type=</span><span class="st">"response"</span>)
predict_log1<-<span class="kw">as.factor</span>(<span class="kw">ifelse</span>(predict_log <span class="op"><</span>.<span class="dv">5</span>, <span class="st">"0"</span>,<span class="st">"1"</span>))
<span class="kw">confusionMatrix</span>(<span class="dt">data =</span> predict_log1, <span class="dt">reference =</span> test<span class="op">$</span>Outcome, <span class="dt">positive =</span> <span class="st">"1"</span>,
<span class="dt">dnn =</span> <span class="kw">c</span>(<span class="st">"Algorithm predicted values"</span>, <span class="st">"Actual Test Values"</span>)) </code></pre></div>
<pre><code>## Confusion Matrix and Statistics
##
## Actual Test Values
## Algorithm predicted values 0 1
## 0 108 26
## 1 17 41
##
## Accuracy : 0.776
## 95% CI : (0.7104, 0.8329)
## No Information Rate : 0.651
## P-Value [Acc > NIR] : 0.0001183
##
## Kappa : 0.4912
## Mcnemar's Test P-Value : 0.2224692
##
## Sensitivity : 0.6119
## Specificity : 0.8640
## Pos Pred Value : 0.7069
## Neg Pred Value : 0.8060
## Prevalence : 0.3490
## Detection Rate : 0.2135
## Detection Prevalence : 0.3021
## Balanced Accuracy : 0.7380
##
## 'Positive' Class : 1
## </code></pre>
</div>
<div id="k-nearest-neighbors" class="section level2">
<h2>K-nearest neighbors</h2>
<p>For each test data point, we would be looking at the K nearest training data points and take the most frequently occurring classes and assign that class to the test data.</p>
<p>Read more here:<a href="https://medium.com/@adi.bronshtein/a-quick-introduction-to-k-nearest-neighbors-algorithm-62214cea29c7" class="uri">https://medium.com/@adi.bronshtein/a-quick-introduction-to-k-nearest-neighbors-algorithm-62214cea29c7</a></p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">knnFit<-<span class="kw">train</span>(Outcome<span class="op">~</span>BMI<span class="op">+</span>Glucose<span class="op">+</span>Pregnancies, <span class="dt">data=</span>train, <span class="dt">method=</span><span class="st">"knn"</span>,
<span class="dt">preProcess=</span><span class="kw">c</span>(<span class="st">"center"</span>,<span class="st">"scale"</span>))
predict_data<-<span class="kw">predict</span>(knnFit, <span class="dt">newdata=</span>test)
<span class="kw">confusionMatrix</span>(<span class="dt">data =</span> predict_data, <span class="dt">reference =</span> test<span class="op">$</span>Outcome, <span class="dt">positive =</span> <span class="st">"1"</span>,
<span class="dt">dnn =</span> <span class="kw">c</span>(<span class="st">"Algorithm predicted values"</span>, <span class="st">"Actual Test Values"</span>)) </code></pre></div>
<pre><code>## Confusion Matrix and Statistics
##
## Actual Test Values
## Algorithm predicted values 0 1
## 0 100 22
## 1 25 45
##
## Accuracy : 0.7552
## 95% CI : (0.6881, 0.8143)
## No Information Rate : 0.651
## P-Value [Acc > NIR] : 0.001235
##
## Kappa : 0.4668
## Mcnemar's Test P-Value : 0.770493
##
## Sensitivity : 0.6716
## Specificity : 0.8000
## Pos Pred Value : 0.6429
## Neg Pred Value : 0.8197
## Prevalence : 0.3490
## Detection Rate : 0.2344
## Detection Prevalence : 0.3646
## Balanced Accuracy : 0.7358
##
## 'Positive' Class : 1
## </code></pre>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co">#plotting different number of neighbors and accuracy</span>
<span class="kw">plot</span>(knnFit)</code></pre></div>
<p><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAqAAAAHgCAYAAAB6jN80AAAEGWlDQ1BrQ0dDb2xvclNwYWNlR2VuZXJpY1JHQgAAOI2NVV1oHFUUPrtzZyMkzlNsNIV0qD8NJQ2TVjShtLp/3d02bpZJNtoi6GT27s6Yyc44M7v9oU9FUHwx6psUxL+3gCAo9Q/bPrQvlQol2tQgKD60+INQ6Ium65k7M5lpurHeZe58853vnnvuuWfvBei5qliWkRQBFpquLRcy4nOHj4g9K5CEh6AXBqFXUR0rXalMAjZPC3e1W99Dwntf2dXd/p+tt0YdFSBxH2Kz5qgLiI8B8KdVy3YBevqRHz/qWh72Yui3MUDEL3q44WPXw3M+fo1pZuQs4tOIBVVTaoiXEI/MxfhGDPsxsNZfoE1q66ro5aJim3XdoLFw72H+n23BaIXzbcOnz5mfPoTvYVz7KzUl5+FRxEuqkp9G/Ajia219thzg25abkRE/BpDc3pqvphHvRFys2weqvp+krbWKIX7nhDbzLOItiM8358pTwdirqpPFnMF2xLc1WvLyOwTAibpbmvHHcvttU57y5+XqNZrLe3lE/Pq8eUj2fXKfOe3pfOjzhJYtB/yll5SDFcSDiH+hRkH25+L+sdxKEAMZahrlSX8ukqMOWy/jXW2m6M9LDBc31B9LFuv6gVKg/0Szi3KAr1kGq1GMjU/aLbnq6/lRxc4XfJ98hTargX++DbMJBSiYMIe9Ck1YAxFkKEAG3xbYaKmDDgYyFK0UGYpfoWYXG+fAPPI6tJnNwb7ClP7IyF+D+bjOtCpkhz6CFrIa/I6sFtNl8auFXGMTP34sNwI/JhkgEtmDz14ySfaRcTIBInmKPE32kxyyE2Tv+thKbEVePDfW/byMM1Kmm0XdObS7oGD/MypMXFPXrCwOtoYjyyn7BV29/MZfsVzpLDdRtuIZnbpXzvlf+ev8MvYr/Gqk4H/kV/G3csdazLuyTMPsbFhzd1UabQbjFvDRmcWJxR3zcfHkVw9GfpbJmeev9F08WW8uDkaslwX6avlWGU6NRKz0g/SHtCy9J30o/ca9zX3Kfc19zn3BXQKRO8ud477hLnAfc1/G9mrzGlrfexZ5GLdn6ZZrrEohI2wVHhZywjbhUWEy8icMCGNCUdiBlq3r+xafL549HQ5jH+an+1y+LlYBifuxAvRN/lVVVOlwlCkdVm9NOL5BE4wkQ2SMlDZU97hX86EilU/lUmkQUztTE6mx1EEPh7OmdqBtAvv8HdWpbrJS6tJj3n0CWdM6busNzRV3S9KTYhqvNiqWmuroiKgYhshMjmhTh9ptWhsF7970j/SbMrsPE1suR5z7DMC+P/Hs+y7ijrQAlhyAgccjbhjPygfeBTjzhNqy28EdkUh8C+DU9+z2v/oyeH791OncxHOs5y2AtTc7nb/f73TWPkD/qwBnjX8BoJ98VQNcC+8AAEAASURBVHgB7N0JvE3l/sfxr3meQuYxSqFIGmQoGqhoIgndVGgeabj9b90GpTmhuma5DYZQyRBXKSKliJAyZCZkyDz912+d9nHms885e1h77c/zeh1n77XXXs/zvNd2zu88Y67jThIJAQQQQAABBBBAAIEICeSOUD5kgwACCCCAAAIIIICAK0AAygcBAQQQQAABBBBAIKICBKAR5SYzBBBAAAEEEEAAAQJQPgMIIIAAAggggAACERUgAI0oN5khgAACCCCAAAIIEIDyGUAAAQQQQAABBBCIqAABaES5yQwBBBBAAAEEEECAAJTPAAIIIIAAAggggEBEBQhAI8pNZggggAACCCCAAAIEoHwGEEAAAQQQQAABBCIqQAAaUW4yQwABBBBAAAEEECAA5TOAAAIIIIAAAgggEFEBAtCIcpMZAggggAACCCCAAAEonwEEEEAAAQQQQACBiAoQgEaUm8wQQAABBBBAAAEECED5DCCAAAIIIIAAAghEVIAANKLcZIYAAggggAACCCBAAMpnAAEEEEAAAQQQQCCiAgSgEeUmMwQQQAABBBBAAAECUD4DCCCAAAIIIIAAAhEVIACNKDeZIYAAAggggAACCBCA8hlAAAEEEEAAAQQQiKgAAWhEuckMAQQQQAABBBBAgACUzwACCCCAAAIIIIBARAUIQCPKTWYIIIAAAggggAACBKB8BhBAAAEEEEAAAQQiKkAAGlFuMkMAAQQQQAABBBAgAOUzgAACCCCAAAIIIBBRAQLQiHKTGQIIIIAAAggggAABKJ8BBBBAAAEEEEAAgYgKEIBGlJvMEEAAAQQQQAABBAhA+QwggAACCCCAAAIIRFSAADSi3GSGAAIIIIAAAgggQADKZwABBBBAAAEEEEAgogIEoBHlJjMEEEAAAQQQQAABAlA+AwgggAACCCCAAAIRFSAAjSg3mSGAAAIIIIAAAggQgProM7Bo0SL9+OOPPqoRVUkpMHv2bP32228pD/PcRwJTpkzRli1bfFQjqpJSYMyYMdq3b1/Kwzz3icDx48c1cuRIn9QmfNUgAA2fbcSv/PHHH2vixIkRz5cMIycwZMgQzZkzJ3IZklPEBfr27asVK1ZEPF8yjJzAww8/rB07dkQuQ3KKqMCRI0fUvXv3iOYZi5kRgMbiXaPMCCCAAAIIIIBADAsQgMbwzaPoCCCAAAIIIIBALAoQgMbiXaPMCCCAAAIIIIBADAsQgMbwzaPoCCCAAAIIIIBALAoQgMbiXaPMCCCAAAIIIIBADAsQgMbwzaPoCCCAAAIIIIBALArkctarOh6LBfdSmTds2KDGjRurdOnSUS3Wtm3bZLezbNmyUS0HmYdPYPPmzSpYsKBKliwZvky4clQF1q9fr1KlSqlIkSJRLQeZh09gzZo1qlixovLnzx++TLhy1ASOHTsmu8c1a9aMWhks4927d6tz5856/vnno1qO9DInAE1PJgvHbVHhUaNGRf0mBxavLleuXBZKz6mxJLBp0yb3l1a0/9iJJbNYK6v9QVusWDEVL1481opOeYMUsHtsDQUEoEGCxdhp1hC0ceNGVapUKaol37t3r7p166Zly5ZFtRzpZZ43vRc4njWBQoUKqX79+ll7U4jPrlKlintFWsdCDOuhy1WoUMFtAS1atKiHSkVRQilggYn9H7aWbpI/BayFu3z58sqbl1/BfrzDFoCWKFFC1apVi2r1Fi9e7OnPGGNAo/rxIHMEEEAAAQQQQCD+BAhA4++eU2MEEEAAAQQQQCCqAgSgUeUncwQQQAABBBBAIP4ECEDj755TYwQQQAABBBBAIKoCBKBR5SdzBBBAAAEEEEAg/gQIQOPvnlNjBBBAAAEEEEAgqgIEoFHlJ3MEEEAAAQQQQCD+BAhA4++eU2MEEEAAAQQQQCCqAgSgUeUncwQQQAABBBBAIP4ECEDj755TYwQQQAABBBBAIKoCBKBR5SdzBBBAAAEEEEAg/gQIQOPvnlNjBBBAAAEEEEAgqgIEoFHlJ3MEEEAAAQQQQCD+BAhA4++eU2MEEEAAAQQQQCCqAgSgUeUncwQQQAABBBBAIP4ECEDj755TYwQQQAABBBBAIKoCeaOaO5kjgAACCCCAAAI+Edj2l/ThPGn52pKqW13q2kQqWtAnlQtxNWgBDTEol0MAAQQQQACB+BPYsVeq0Uv6dqVUtuhR/XeuVP5+6Y898WcRTI0JQINR4hwEEEAAAQQQQCAdgUNHpKoPSbc1l97tId1y3h7NeULq1ky66nXp8NF03hjHhwlA4/jmU3UEEEAAAQQQyLnAqj+kk4tLb9wkbd3tdMFvyedetH8XabvTLb9pZ87z8NsVCED9dkepDwIIIIAAAghEVOCndQnZXdRXOvspaeOuE1NsCueX9hyIaHFiIrMTQjFRXAqJAAIIIIAAAghEV+CI06U++1dp8iLpM+fr2HFp5z7pibYJE482bdjvFvCrXyRrHa11cnTL68XcCUC9eFcoEwIIIIAAAgh4SmCXE1NOW5wQdH7+s1S7nHTlWdLou6V6laQJC5zgc5CU1+lbrl44r75aL935rvR5b6lAQo+8p+oT7cIQgEb7DpA/AggggAACCHhSYM22hBZOa+n8fo3U/LSEoPPFjlI5Z8xn0nRtI2nqw9Jzn0jrtp+s6mWlTx+QmtRKehaPAwIEoAEJviOAAAIIIIBAXAscd7rSLdC0bnULOm0JpTZnSne1klqeLhVyxnNmlJqeKk1xgtC1azeqWrVqGZ0a968RgMb9RwAABBBAAAEE4ldg/yHpi2VO0PmTEzw6QWfpotIVTtf6gK5S4xpSrlzxaxPOmhOAhlOXayOAAAIIIICA5wS2OEslTXUCTmvptIlCZ1d3gk6npbNXa2cxeafrnBR+AQLQ8BuTAwIIIIAAAghEWWDpRifgXJjQ0vnrZumSutL1jaVB3aSShaNcuDjMngA0Dm86VUYAAQQQQMDvAmktlXRVA+mpqyUbq5kvj98FvF0/AlBv3x9KhwACCCCAAAJBCthSSZ8v+XupJOd7rRRLJQV5GU6LgAABaASQyQIBBBBAAAEEwiPwuy2V5IzndJdKWp3Qumnrc/bt4CyVVCI8eXLVnAsQgObckCsggAACCCCAQIQEAkslWcA52Qk8be/11vWlOy52lkpyFoW3rS9J3hcgAPX+PaKECCCAAAIIxLXAgcPSzKUJLZ2BpZLaOK2cb3ZOWCopt7P7ECm2BAhAY+t+UVoEEEAAAQTiQiDpUkmznKWSGlVnqSQ/3XgCUD/dTeqCAAIIIIBADAvYUknWtW7rc65gqaQYvpOZF50ANHMjzkAAAQQQQACBMAjYUklzfjsRdB49lrDX+r+cpZKasVRSGMS9c0kCUO/cC0qCAAIIIICA7wV2O0slTXOWSJriTCCyJZNqOjsP2az1D+6U6lf2ffWp4N8CBKB8FBBAAAEEEEAgrAJrt0uTbNa68/Wds1SStW7a1pfPt5fKs1RSWO29enECUK/eGcqFAAIIIIBAjArYUkkL1iSM5bSlkrbskto4AactlTSGpZJi9K6GttgEoKH15GoIIIAAAgjEpYAtlfTFshNB50lFnFZOlkqKy89CMJUmAA1GiXMQQAABBBBAIJWALQI/dXFC0DlrudSwWkLQ+VDrhLGdqd7AAQT+FiAA5aOAAAIIIIAAAkELLHOWSrJlkqxrffkm6ZIzpGsbSe/8QyrltHqSEAhGgAA0GCXOQQABBBBAIE4FUi6VdMRZKukqp2v9ibZS89OkfHniFIZq50iAADRHfLwZAQQQQAAB/wnYUkm2RJK1crJUkv/urxdqRADqhbtAGRBAAAEEEIiygC2V5HatO93r852lkpo6SyVdyVJJUb4r/s2eANS/95aaIYAAAgggkK6ALZX0w+8ngs7NzlJJrZ2As4ezVNJolkpK140XQiNAABoaR66CAAIIIICA5wVSLpVUqnDCrPU3Okvn1pBy5/Z8FSigTwQIQH1yI6kGAggggAACaQn8sSdh20vrXmeppLSEOBYNAQLQaKiTJwIIIIAAAmEUsKWSbAKRBZ32+NK6LJUURm4unQ0BAtBsoPEWBBBAAAEEvCRgSyV981vCXuufOYHnYee5TSBiqSQv3SXKklSAADSpBo8RQAABBBCIEQFbKmn6zwlBpy2VVL2sE3Q663O+31OqXyVGKkEx41aAADRubz0VRwABBBCINYF1O6RJCxOCTlsq6cLaCUHnc9dLFUrGWm0obzwLEIDG892n7ggggAACnhZIuVTSJmeppDYsleTpe0bhghPwbAC6evVqValSRXnzpl3EAwcO6OhRZ5BLilSoUCFnGYmEdSQOHz6s7du3q3z58snOOnToULL35sqVSwULFkx2Dk8QQAABBBCIhoAtlfTl8hP7rZcsxFJJ0bgP5BleAc+t+PX111+rZs2aatWqlUqXLq2pU6emKdCuXTsVLVo01deiRYt03PmTsXv37u51LrroIjVv3lzz5s1LvM65556rwoULJ341bNgw8TUeIIAAAgggEGkBWypp1BzpxrelGr2kN6ZJtcs522A6jxc8LT17nXT+KazTGen7Qn7hE0i7eTF8+WV4ZWvVvPXWW/XCCy+oY8eOGjdunLp06aL169enaqGcNGlSslbM3r17a8WKFWrQoIHstW+//VbLli1zA9TXXntNTzzxhP73v//JWj+XLl2qNWvW6OSTT3bLYy2gJAQQQAABBCIpsHzT37PWbakk53GrM6SrnfaQt26WTioSyZKQFwKRF/BUAGqtlwcPHnSDT6No3769nnzySU2fPl1t27ZNppM/f/7E57Nnz9bo0aO1cOFCWTB57Ngx9e3b1w0+7aTLL79cvXr1kgW4FpRa4FmtWjVZF32+fPkSr8MDBBBAAAEEwiVw9Jg051dnm8s5JTRrZZ6EpZKcWev/dH69NXP2Xc/vqd/I4VLguggkCHjq426tkhYYJk1Vq1Z1W0CTHkv62ILN22+/XX369FGlSpXcl66++uqkp2jEiBE677zz3FZUC1JtjGizZs00f/581alTR8OHD9fZZ5+d7D0pn0ycOFH79u1Ledh9bt37f/75p/bu3Zvm65E6aAG1DT+IdjkiVd94zOfIkSPuH2m02vv37tvY9vTGuPu31v6t2Z4D0szleTRtSV7NWJZH1UsfU/NTjmlw1706s8qJ3rfDB521O50vUuwL2O9hS9H+Xbxjxw7t2rVL77//frqo559/vjtcMd0TwviCpwLQTZs2qUSJEsmqW7x4cTe4S3YwyZMZM2Zo69at6tq1a5KjJx6OHDlSQ4cO1VdffeUetA/GhRdeqH79+rnP//nPf+raa691u+8LFChw4o0pHlk+FmSmlX7//XflyZMn3QA1rfeE41ggAE0vUA5HnlwzsgIWgNpn2P7wIvlTwO6tBaD2/5kUmwIbdubWjOX5nYCzgH5cl1eNqx/WJXX2q/clh1Su+DHt379f9vtm3z7PTcOITXCPlToQgEb7d7H9HLEyfPbZZ+kKVa5cmQDUdGzS0e7du5NB2fOKFSsmO5b0yeDBg9WtWzfZ7PeUybrhLdCcOXOm6tWr575sY0ztK5CefvpptwV0yZIlatSoUeBwqu8DBgxIdSxwYMyYMe541bJlnVWAo5h27tzp5l6yJIvBRfE2hDXrbdu2uS35NgGP5E+BzZs3y/4PszJH7Nxfa/D68Xdn1rqzA5FtfbnJ+VHcur5016UJ4zqLuI0bJxo4bF6D/b5Lb5WX2Kk5JU1LwALQtWvXKtoxgcVOFSpU0HvvvZdWMaN+zFMtoNbdvsbphk+abDmmGjVqJD2U+Niatz/++GN37Gfiwb8fPPLIIxo/frxsVn2tWrUSX7bzS5Uq5c6Mt4PWlWmtl5Y3CQEEEEAAgWAEDqZYKqm4LZXkrM/5eifpvJrMVg/GkHPiW8BTAWjTpk3dvwgHDRrkLqM0atQoWZejLZtkySYb2dqggXGiy5cvdycR2TjOpMnGfNp7rdvcWhKs1cjSSSed5LawPvbYY+74T+sCeeWVV9SiRYuo/6WStPw8RgABBBDwnsC2v6QpTguntXR+uUw6y2m3uMKZRDT1YamWs2QSCQEEghfwVABqLZHDhg1zZ8Hb7HcLGC2YDHSv9+jRww1MH3zwQbeGtpzSGWeckbjwfKDatoyTdWMFut0Dx9etW6ebbrrJXRO0fv367jgcm7hkXegkBBBAAAEEUgokXSpp6UbpkroslZTSiOcIZEfAUwGoVcAWjrfg0SYWlSuX/E9KCziTJpt4lNbko19++SXpaakeDxw40B0bamMmy5Qpk+p1DiCAAAIIxKeALZX0zW8n1uc8eCRhr3WWSorPzwO1Dp+A5wJQq6qNy0wZfIaawAZ/E3yGWpXrIYAAArEnYEslTf85Ieictliq5rRLXOl0rf+3p5ylkmKvPpQYgVgQ8GQAGgtwlBEBBBBAIHYF1u9ImLFu4zm/XSk1qZUQdD5zrVSxVOzWi5IjECsCBKCxcqcoJwIIIIBAjgR+WHNiqaSNzrLOrZ1Z67c1kz64QypyYpWkHOXBmxFAIDgBAtDgnDgLAQQQQCDGBJIulWQtnSVYKinG7iDF9bMAAaif7y51QwABBOJMwJZKmvr3gvBfJFkqaRpLJcXZJ4Hqel2AANTrd4jyIYAAAghkKPDL5hOz1n/ekLD7ULuG0sCbnfWfi2T4Vl5EAIEoCRCARgmebBFAAAEEsicQWCppyt8tnfsPJUwgeuxKqflpUn5+s2UPlnchEEEB/ptGEJusEEAAAQSyJ/CXs1TS5ymWSrKtL9/tnrAjUfauyrsQQCBaAgSg0ZInXwQQQACBDAWSLpU0z1kc/sLaLJWUIRgvIhBDAgSgMXSzKCoCCCDgd4Eff/97fc5F0gaWSvL77aZ+cSxAABrHN5+qI4AAAtEWsKWSZjm7J3/mBJz2VaygdIWzC9GrnaTza0q5c0e7hOSPAALhECAADYcq10QAAQQQSFcgsFTSZGcSkS2VVL9yQtf6FGeppNrl0n0bLyCAgI8ECEB9dDOpCgIIIOBVgRXOUkmBVs7AUklXOS2d/btIpYt6tdSUCwEEwiVAABouWa6LAAIIxLGALZU015k4ZK2cFnjuc5ZKsoCTpZLi+ENB1RFIIkAAmgSDhwgggAAC2RewpZKmO0slWcA5bbFUtYzTtc5SSdkH5Z0I+FiAANTHN5eqIYAAAuEWsJnqga71eSulC2qxVFK4zbk+An4QIAD1w12kDggggEAEBQJLJVn3uq3VeXl9qVsz6b2eUlFnFjsJAQQQyEyAADQzIV5HAAEE4lzg0BHpy+UnWjoDSyW93NFZKukUKQ9LJcX5J4TqI5B1AQLQrJvxDgQQQMD3ArZUko3jtO71mUulM6uwVJLvbzoVRCCCAgSgEcQmKwQQQMDLArZU0mQn4PzM6Vpfsl5qeXrCzHWWSvLyXaNsCMSmAAFobN43So0AAgjkWMCWSrKJQ9bKaYHnXmeppCudpZIeaSO1qCPl5zdEjo25AAIIpC3Aj5e0XTiKAAII+FIg5VJJVUonBJ0juksNqvqyylQKAQQ8KEAA6sGbQpEQQACBUApsdJZKmmRd684XSyWFUpZrIYBAdgUIQLMrx/sQQAABDwssXJsQcFrQuW671NpZEJ6lkjx8wygaAnEmQAAaZzec6iKAgD8FbKmkWbZU0t9bXxbJL13hjOdkqSR/3m9qhUCsCxCAxvodpPwIIBC3AtuTLpW0TKpX2RnP6bR0fvagdGr5uGWh4gggEAMCBKAxcJMoIgII+F/gu9XSE+Ok79eU00lFpAcuk+65JHW9f93iBJgLE1o6F69zlko6I2ESUb8uUpmiqc/nCAIIIOBFAQJQL94VyoQAAnElsNYZo3lxX6lfZ+k/HbfoUJ5SavRMAf22VXr1xuRLJf110FmbswFLJcXVB4TKIuBDAQJQH95UqoQAArEl0G2I9O9rpNuaS5udxeCLFTquUT2ku9+VRn8r1SjLUkmxdUcpLQIIZCZAAJqZEK8jgAACYRZYvF76+H7p+HHplndLafbK/GrldK2f5azL2bS20zXfLswF4PIIIIBAhAVyRzg/skMAAQQQSCFQ2hm7uXGn1Pk/0qIN+bT6xYNuQJovj1Tz5BQn8xQBBBDwgQABqA9uIlVAAIHYFmjfWGr2vHTA2Qrz295bVaygNHiWNNOZ2W4toSQEEEDAbwJ0wfvtjlIfBBCIKYFjzn7sm5zWzwLOT+PPf5b6FC6uPYfzaa6zR/vPfaSTi8dUdSgsAgggEJQAAWhQTJyEAAIIhF7AxnzePSqh+/0XZxb8T86ySl/8dESVy+ZVvy55VLZY6PPkiggggIAXBAhAvXAXKAMCCMSlwP3vSSudpZYm3CcVcnYuOu8UqVqRfSpZMr8KOt3wJAQQQMCvAgSgfr2z1AsBBDwt0OtDacmGhNnvRQp4uqgUDgEEEAi5AAFoyEm5IAIIIJCxwD+dHY/mr5I+dbbMtAlHJAQQQCDeBAhA4+2OU18EEIiqwFMTpC+XJ+zXXqJQVItC5ggggEDUBAhAo0ZPxgggEG8Cz38qTfnJ+XpYKuXs905CAAEE4lWAADRe7zz1RgCBiAq8MkX66PuE4NMWnichgAAC8SxAABrPd5+6I4BARAT6TZdGfeOs89mLdT0jAk4mCCDgeQECUM/fIgqIAAKxLPD2TGnQF9KMR6RyJWK5JpQdAQQQCJ0AAWjoLLkSAgggkExgiLOd5ptO6+f03lKFksle4gkCCCAQ1wJZCkC3bt2q7777TkuWLNHPP/+sbdu2qVy5cqpTp46uvPJK1atXL64xqTwCCCAQEBg5W3rZGfdp3e6VTwoc5TsCCCCAgAnkDoZh9+7devzxx1WtWjW1a9dOAwYM0G+//ab9+/fr888/12OPPab69eurcePGmj3b+alLQgABBOJY4P250nM2492Z7V6tTBxDUHUEEEAgHYEMA9DDhw+rf//+Ouuss7RlyxaNHz/eDTrXrVunb775Rl988YU2bNigXbt2af78+WrZsqWuuuoqdezYUb///ns6WXIYAQQQ8K/AmPnSk85an585i8zXLOvfelIzBBBAICcCGQag1rr566+/usHlsGHD1KZNG+XP72xYnCIVL17cbf188cUX3cCzYcOGeu6551KcxVMEEEDA3wITFkiPjXV2OHpAOrW8v+tK7RBAAIGcCGQ4BtTGddpXVlKJEiXcLvmsvIdzEUAAgVgXmLRQevgDZ293J/g8vWKs14byI4AAAuEVyLAFNL2sjx8/rpUrV2rx4sU6cuRIeqdxHAEEEIgLgWmLpXtGSRPuk+pXjosqU0kEEEAgRwJZCkAt8HzmmWdUsmRJ1apVS2eeeaaKFSum9u3ba8+ePTkqCG9GAAEEYlHgf0ulHiOcXY7ulc6qGos1oMwIIIBA5AUy7IJPWZwHHnhAI0eO1HXXXafLLrtM1atX1y+//KJXX31VF154ob7//vs0x4imvA7PEUAAAT8IzPpFunWoNOYuqVF1P9SIOiCAAAKREQg6AD127Jjef/99vfTSS+rRo0di6S644AJddNFFOvXUU/XVV1/pkksuSXyNBwgggIBfBeb8Kt08SHr/Dum8U/xaS+qFAAIIhEcg6C74HTt2yL46d+6cqiTWEnr++edr4UJnFD4JAQQQ8LnAtyulzu9II7tLF9b2eWWpHgIIIBAGgaAD0DJlyqhu3bp67733UhXDuuFtXdBmzZqleo0DCCCAgJ8EFqyROr4lDb1NuqiOn2pGXRBAAIHICQTdBW9F6tq1q+68804NHDhQrVu3dgPSVatWafDgwTrttNM0a9Ys98vObdKkiZo2bWoPSQgggIAvBBatldoPkN65RWp1hi+qRCUQQACBqAhkKQB95ZVXVLRoUa1Zs0bvvOP0PyVJf/31l/r06ZN4pHfv3gSgiRo8QACBWBdYskG65k2pfxepdf1Yrw3lRwABBKIrkKUA1LbjJCGAAALxJrBso9TuDem1TtJVDeKt9tQXAQQQCL1A0GNAM8v66NGjrAWaGRKvI4BAzAn86vzdfZUTfPbtIF3bKOaKT4ERQAABTwpkqQV0/fr1evbZZ7VixQodPHjQrZAtz3To0CGtXbtWb7/9tjp0cH5KkxBAAAEfCKz6Q7riNenZa6UbzvVBhagCAggg4BGBLLWA3nzzzRoxYoQKFCigRYsWueNBc+XKpSVLlqhFixaM+fTITaUYCCCQc4Hft0ltXpX+r6100wU5vx5XQAABBBA4IRB0AGqtnDbLffjw4Zo6daq75JLNip87d64mTpzo7gtfokSJE1fmEQIIIBCjAut3OBONnOCzdxvpHyzmEaN3kWIjgICXBYIOQLdu3Srrbg/sdFS/fn3NmTPHrdsVV1yhcuXKafLkyV6uK2VDAAEEMhXYtDMh+Lz3Uun2FpmezgkIIIAAAtkQCDoArVChgrvP++rVq91s6tSpkxiA2gELQG1NUBICCCAQqwJbdiV0u3d3As+7WsZqLSg3Aggg4H2BoAPQPHnyuK2fPXv21Pz5892tN5cuXaoPP/xQM2fO1IwZMxgD6v37TQkRQCAdgT/2JEw46uyM97z/snRO4jACCCCAQEgEgg5ALTeb5W4TkKZMmeLugmRjQDt16qRWrVqpZs2ablAaklJxEQQQQCCCAtv/cpZael267hxn3OcVEcyYrBBAAIE4FcjSMkzz5s3T+PHjVapUKZfLJiTZzPjjx4+7QWicGlJtBBCIYYGd+6QrneCzzZnSE86MdxICCCCAQPgFgm4Bta02rcVz7NixKly4sFsyW4KpZcuWBJ/hv0/kgAACYRDYvT+h5bPl6dK/rwlDBlwSAQQQQCBNgaADUOt6L168uHbudKaIkhBAAIEYF/jrgLO9Zj/pglrS8+1jvDIUHwEEEIgxgaC74PPly6f/+7//0+OPP66FCxfKlmEKdMUH6ty2bVvVrl078JTvCCCAgCcF9h2SrnlTOquK9HJHTxaRQiGAAAK+Fgg6ADUF24bTut2nT5/ufqWUqVGjBgFoShSeI4CApwT2O8Hn9f2lU8tLb9zkqaJRGAQQQCBuBLIUgP7www+qWLGi8uZN/TbbmrNs2bJxA0dFEUAg9gQOHnb2dB8oVT5JGtBFzh/UsVcHSowAAgj4QSDoMaBWWVt8ft26dWnW+/LLL9enn36a5mscRAABBKItcOiIdOPbUpli0jv/kHJn6adftEtP/ggggIC/BFI3Zaao38svv6wvvvjCPXrw4EHdeuutKlSoULKzduzYoS1btqhatWrJjvMEAQQQ8ILAkaNS5/9IRQpIg7tJeQg+vXBbKAMCCMSxQKYBaLt27ZJtuWmTkfLnz59IZmNCLfC8/vrrZa2gJAQQQMBLAkePSV0HOS2eTnf7iNulvHm8VDrKggACCMSnQKYB6GmnnaaJEye6OldffbUGDRrk7vsen1zUGgEEYknAgs9bh0qHnBbQD+4g+Iyle0dZEUDA3wKZBqBJq//xxx+7T23nI2v5tC75r7/+WieddJLOPvvspKfyGAEEEIiqwDEn+Ow5QvrT2elo7F1S/iz9tItq0ckcAQQQ8L1AlkZC2Uz3Bg0a6Msvv9Qx56f7VVddpUsvvVSNGjVSjx49fI9FBRFAIDYEnL+RddcoaZOzb8boO6UC+WKj3JQSAQQQiBeBLAWgNgHJxn9WqVLFnZg0Y8YMvfHGG5o0aZJsX/i5c+eGzG316tU6csSZtppOOnDggPbu3ZvqywLjQDp8+LA2b94ceJrsu7Xerl27NtkxniCAgD8E7ntPWrXVafm8Ryp0Ysi6PypHLRBAAAEfCAQdgO7bt08//vijhgwZolq1arlLLpUuXVr33nuvrrzySp1//vn67rvvckxiXfo1a9Z095e360+dOjXNa9rkqKJFi6b6slZaGyLQvXt39zoXXXSRmjdvrnnz5iVe55lnnlHlypV1wQUXuK23NoOfhAAC/hB4+APp5w3S+HulwgSf/rip1AIBBHwnEHQAanvAW2B38sknuwhTpkxxu99z/72YnrVIlihRIkdAdg1rZX3hhRe0atUqDR06VF26dJEdT5ms1dWC4sDX3Xff7ZbHhgjYa99++62WLVum5cuX65prrtETTzzhXmLOnDluEL1gwQKtXLnS3VL00UcfTXl5niOAQAwKPD5W+m61NPE+qWjBGKwARUYAAQTiRCDoALRChQruTkdvvfWWRo8erRUrVshaIS0oHTdunCygs/GgOUnWemld4x07JmzO3L59ezfgta0/UyYbCmDrkdqX5W1lsmEANjnKuuH79u3rto7a+2x5KFvL1ALZCRMmqEOHDqpataoKFiyoXr16acyYMW49UubBcwQQiB2BJydIs36RPnlAKp58qeLYqQQlRQABBOJEIOh5oRbYvf7667rlllvcsZmtWrWSBYjWRX7jjTfqrrvucrfpzInbmjVrUi1mb4Hi+vXr072sBZu33367+vTpo0qVKrnn2XJRSdOIESN03nnnuQGnjS21bvlAsjVM9+/fr+3bt6tMmTKBw6m+WxC7daszqCyN9Oeff6p69erauHFjGq9G7tDRo85aM06yVmGSPwVsXLT9IbV7925/VjCbtXrzy2L6fFlBjfrHNu3bedz5yuaFPPA2u8fbtm1zdmoKun3AA6WmCFkRsJ/VNvTLfq+S/CdgDXOWoh0TbNiwwZ3r0rBhw3SRn376abcxMd0TwvhC0AGolaFz58665JJL3Ik9Z555pvufx2bAW8tl3bp1c1zMTZs2perGL168uCzASy/ZRCgLDLt27ZrmKSNHjnS78r/66iv3dZuUZNcMJBtHasnyyCgAfe2112STmtJKn3/+uWbNmpXh+9N6X6iP7dmzx71ksWLOXoMkXwrYUBhr/S9cuLAv65edSr02Lbc+X55Hkx447GyzWTo7l/DUe+yPYfs/nHTDD08VkMLkWMCCT1u+ME8edkXIMaYHL2ABqMUaGcUUkSh2yZIl3Z5r6x1OL1kjX7RSlgJQmzVesWLFZAvR25hQ+7IgtGzZsjlqBbVJRylbduy55ZleGjx4sLp165Zqe1A737rh+/Xrp5kzZ6pevXruJSyPQKBmBwKPM8rDzssowLbhCN9//33Uf2EEfpjxi8vumD+TtYrlzZs36p81r+j2+1z6cL40rZdUroQ/ZhxZqxj32CufsPCUw+6x7Spo95nkP4FAC2i0fxcXKVLEjY1sbowXU5b6eOrUqaN169alWQ/rov7000/TfC3YgxaJWzd80mRd5jVq1Eh6KPGxLcNki+PfdttticcCDx555BF3spHNqk+Kb3nYNQPJHlvgbDeKhAACsSPw1kxnX/dZ0pSHLfiMnXJTUgQQQAABZ2e6zBBefvlldwKPnWcThGyWuk38SZp27Njhjmex8ZQ5SU2bNnX/IrTtPm0ZpVGjRrnjTc8991z3srNnz3bXIA3kYzPc7a9IC4yTJhvzae+17nlrgrbxVJasy8O66q+77jq31dTGbVorqY1hJSGAQOwIDHECz/7O3MTpvaUKJWOn3JQUAQQQQCBBINMWUJvpbs3IgaZkC/gCz+17gQIF3IlDL730kjvbPCew1oU8bNgw/etf/5LNurfg0ILJQMBruy2NHz8+MYulS5fqjDPOSDVY35ZxsvEX1u1urZuBLxsQbJORLIg+55xzVLt2bdmYuueffz7xmjxAAAFvC4ycLb08RZrqtHxWPsnbZaV0CCCAAAJpC+RyxiokTNdK+/VkR212ubVOlitXLtnxUD+xItnEonDmYzOJ7ctaSHOabBknW4rKvkczWTBtKRR1imY9yDt9AWvNt+XDApPn0j/Tn6+872y29tTEhDGfNcv6s472x7P9H7b7TPKngK3sUr58ecaA+vP2uss62pyZQG9ttKq5ePFi3XTTTbLvXkyZdsEnLbSNt7S0a9cud4F3CxRtNnyoZ+TaAO1wBp9WB/vhzg94kyAhEBsCY5zJRrbW5+SHJL8Gn7FxJyglAgggkHOBTLvgk2ZhyxDZ5B5bWsC23rStLG25kCZNmrhjQJOey2MEEEAgVAITFkiPObscffqAdGr5UF2V6yCAAAIIREsgSwGoLVg6cOBAt0l37Nix7t7w7733nmw2+sUXX+xOUopWRcgXAQT8KTBpofSQs7+77XB0evorsvmz8tQKAQQQ8KlA0F3w1t1ua2ra1pUWiAaSLXHUuHFjnXrqqZo3b55atGgReInvCCCAQI4EpjpDl+79b8Le7vUSNjrL0fV4MwIIIICANwSCbgG1GeR//fWXuxVnyqKfcsopatasmb799tuUL/EcAQQQyJbA/5ZKd4yQxt0jnRW9zTqyVXbehAACCCCQsUDQAajtdmS7NkyaNCnVFW3GugWfgb3YU53AAQQQQCALAl8ul24bKo2+S2pUPQtv5FQEEEAAgZgQCDoAtfU/bTq/rbE5ceJEdyb8oUOH3On9thORLQtz2WWXxUSlKSQCCHhXYM6v0j8GS+/dIZ13infLSckQQAABBLIvEPQYUMvi9ddfd7e9vPbaa90cbbkkGxtapUoVjR492l3wPftF4Z0IIBDvAt+ulG56R3q3h3Rh7XjXoP4IIICAfwWyFIDaVpYTJkzQwoUL9fPPP7u7CNWqVcsd/xnqtUD9S07NEEAgLYEFa6Qb3pKG3Sa1OC2tMziGAAIIIOAXgSwFoIFK16hRw11yKVwL0Qfy4TsCCMSHwKK10vX9pUG3SK3OiI86U0sEEEAgngWCHgNqSCxEH88fFeqOQHgEFq+Xrn1TGtBVurx+ePLgqggggAAC3hLIUgDKQvTeunmUBoFYF1i2Ubq6n/RqJ+mqBrFeG8qPAAIIIBCsQNBd8CxEHywp5yGAQDACKzZLbd+Q+nZwWkAbBfMOzkEAAQQQ8ItA0C2gLETvl1tOPRCIvsCqP6QrX5eecRbUuOHc6JeHEiCAAAIIRFYg6ACUhegje2PIDQG/Cvy+TWrzqvR/bZ0lly7way2pFwIIIIBARgJBB6AsRJ8RI68hgEAwAut3SK2d4LN3G2ex+abBvINzEEAAAQT8KBD0GFCrPAvR+/EjQJ0QiIzApp0Jwee9l0q3t4hMnuSCAAIIIOBNgSwFoCxE782bSKkQ8LrAll0JwWf3i6S7Wnq9tJQPAQQQQCDcAkF3wS9btkzbt293y9OgQQOVLFlSs2fP1ptvvqkRI0a4W3KGu7BcHwEEYk9g627pitekrk2k+53WTxICCCCAAAKZtoBu3rxZLVu2lAWguXPn1pNPPqnLLrtM7dq1U/ny5VWwYEFNnjxZS5Ys0VtvOfvokRBAAIG/Bbb/5azv6cx2v/4cqZcz7pOEAAIIIICACWTaAnrLLbdo165dGjVqlIYOHeq2eF599dXq3r271q9fr5UrV+qJJ57QkCFD9McfztoqJAQQQMAR+HNvwlJLV54l/dOZ8U5CAAEEEEAgIJBpAPrNN9/o3//+t7p06SILRnv16uUGmnfffbdy5crlXueee+5xt+lcsWJF4Lp8RwCBOBbYtT9hkXnb1/2pa+IYgqojgAACCKQpkGEAat3ve/bsUdWqVRPffMopp7iPK1eunHjMJidZ2rJlS+IxHiCAQHwK7DmQsL1mk1pSn+vj04BaI4AAAghkLJBhAHro0CH33UWLFk28io35tJQ/f/7EYzY21NLRo0cTj/EAAQTiT2DvQWdbzTelBs7frC91jL/6U2MEEEAAgeAEMgxAg7sEZyGAAALSfufv1ev7S6dVcNYM7oQIAggggAAC6QtkOgve3vr4448r0M1u3fKWbrzxRuXJk8d9fPz4cfc7/yCAQHwKHDwsdRgoVS0j9e8sZ3x4fDpQawQQQACB4AQyDEBt+8169erpzz//dL8Cl7Rja9asCTx1v9uxEiVKJDvGEwQQ8L/AoSNSx7elssWkd252ltagX8X/N50aIoAAAjkUyDAArVChghYvXpzDLHg7Agj4VeCwM+y783+kogWkIbcSfPr1PlMvBBBAINQCtFWEWpTrIRAnAkec4PMfg52g0+luH3G7lIefJnFy56kmAgggkHOBDH9lfPfdd+4uR1nNZuHChXr7badPjoQAAr4UOHpMum2YdNDpfh/VQ8qbMBzcl3WlUggggAACoRfIMACtWLGiu73mRRddpLFjx2rfvn0ZluCLL75Q69atdeWVV6pcuXIZnsuLCCAQmwLHnOCz5whnpyPnx8H7PZ0l2TIcyBObdaTUCCCAAALhFcjwV0elSpU0adIkzZw5U71793Z3QrrwwgtVrVo1ValSRQUKFJDtfrR8+XL3ywLUhx9+WOPGjVPStUPDWwWujgACkRKwBS/uGiVt2imNu0cqkC9SOZMPAggggICfBDIMQAMVbdmypb7//ns3sPzqq6+0ZMkSffzxx9qxY4fKli2r0047zV2qqWPHjm5gGngf3xFAwF8C970nrdoqTbxfKnRiLwp/VZLaIIAAAgiEXSCoANRKYfu+d+jQwf0KlOqY0xcX2AUpcIzvCCDgT4GHPpCWbpA+doLPwgSf/rzJ1AoBBBCIkEDQAWha5SH4TEuFYwj4T+CxMdKCNdKnDzhLLiXsxuu/SlIjBBBAAIGICeQoAI1YKckIAQSiJvCv8dLXv0qfPSgVLxS1YpAxAggggICPBAhAfXQzqQoCoRZ47hPp8yXSlIelkoVDfXWuhwACCCAQrwIEoPF656k3ApkIvDxZmrBAmtpLOqlIJifzMgIIIIAAAlkQyHAd0JTX6dSpkzv7/fDhwylf4jkCCPhI4I1p0ntzpclOy6ft8U5CAAEEEEAglAJZCkD37t2r66+/XrY+6AMPPCDb8YiEAAL+Ehj4P2no1wnd7uWK+6tu1AYBBBBAwBsCWQpAP/nkE61fv16PPvqobNejhg0bqkGDBnr99de1dauzOCAJAQRiWmDwLMkC0CkPSRVKxnRVKDwCCCCAgIcFshSAWj3Kly/v7na0aNEi2Vfbtm31zjvvuK2i11xzjbtz0nHbLoWEAAIxJTBitvTq1ITgs/JJMVV0CosAAgggEGMCWQ5AA/Xbs2ePfvjhB/3444/6/fff3R2RbGH69u3bq3nz5tq2bVvgVL4jgIDHBWy85/OfOmM+nZbPamU8XliKhwACCCAQ8wJZCkBt8pHtDX/jjTeqXLly6tmzpwoWLKiPPvpI69atk3XRr169WitXrtQrr7wS8zhUAIF4EBgzX3pygrPOpxN81iwbDzWmjggggAAC0RbI0jJMNWrU0IYNG9xxn3379lXnzp1VunTpZHWoUKGC+/qWLVuSHecJAgh4T8CWWXpsbMIi87XLea98lAgBBBBAwJ8CWQpALeC0pZhs4lFGafjw4TrpJAaRZWTEawhEW2CSs4iF7e/+qbPD0ekVo10a8kcAAQQQiCeBLHXBv/jii8qTJ48mTHD66/5OAwYMSPbcDlv3fL58+QKn8B0BBDwmMHWxdO9/pYn3SfUqeaxwFAcBBBBAwPcCWQpAbba7Lb00d64zY+HvZGuD2pjQiy++WDYJiYQAAt4W+N9S6Y4R0rh7pLOqeruslA4BBBBAwJ8CWQ5AbeznSy+9lKhha4KuWLFC33zzjbtLUuILPEAAAc8JfLlcum2oNPouqVF1zxWPAiGAAAIIxIlA0AHo9u3b3XU/b7rpplQ01apVU9OmTbVs2bJUr3EAAQS8ITDnV+nmQdL7d0rnneKNMlEKBBBAAIH4FAg6ALVJRWXLlnWXXEpJZcHpvHnzZIEoCQEEvCcwb6V00zvSf3tKTWp5r3yUCAEEEEAgvgSCngWfK1cud5H5Pn36qFixYmrSpIkKFy6sVatW6YUXXnCPtW7dOr70qC0CMSDw/WrpxrekYbdJzU+LgQJTRAQQQAAB3wsEHYCaRP/+/d2JRrfeequSbrdZp04ddyZ8yjVBfa9HBRHwuMDCtVL7AdKgblKrMzxeWIqHAAIIIBA3AlkKQG0JJpsJb5OQbB/4rVu3qmbNmqpfv77y5s3SpeIGmIoiEC2Bxeula9+UBt4sXVYvWqUgXwQQQAABBFILZCtqLF68uJo1a5bsakePHtW+ffvcrvhkL/AEAQQiLrB0o3R1P+l1Z87glWdFPHsyRAABBBBAIEOBLAWg69ev17PPPusuu3Tw4EH3wrb256FDh7R27Vq9/fbb6tChQ4YZ8iICCIRXYMVmqe0b0os3SNecHd68uDoCCCCAAALZEQh6Frxd/Oabb9aIESNUoEABtwu+aNGisslJS5YsUYsWLdylmLJTCN6DAAKhEVi51WnxfF167jqpQ+PQXJOrIIAAAgggEGqBoANQa+WcNWuWbJ/3qVOnul3wXbt2dXdFmjhxohYvXqwSJUqEunxcDwEEghRYs0264jXpX+2kTucH+SZOQwABBBBAIAoCQQegNuHIutsvueQSt5g28WjOnDnu4yuuuMLd/33y5MlRqAJZIoDAuh1Sm1elR65weiouxAMBBBBAAAFvCwQdgFaoUEH58+fX6tXOooJOsqWXAgGoPS9Xrpy7Jqg9JiGAQOQENv6ZEHzed6mzzWbzyOVLTggggAACCGRXIOgA1JZgstbPnj17av78+Tr//PO1dOlSffjhh5o5c6ZmzJjBGNDs3gXeh0A2BbbscoJPp9u9+0XSnS2zeRHehgACCCCAQIQFgg5ArVw2y90mIE2ZMkV169aVjQHt1KmTWrVq5a4HakEpCQEEIiOwdXfCmM+uTaT7ndZPEgIIIIAAArEikKVlmGy/9/Hjx6tUqVJu/WxCks2Mt12RLAglIYBAZAS2/yVd5cx2v/4cqVebyORJLggggAACCIRKIOgW0L/++stt8Rw7dqy7B7wVwJZgatmyJcFnqO4G10EgCIGd+xKWWrIF5v/ZNog3cAoCCCCAAAIeEwg6ALWud9sBaefOnR6rAsVBIH4Edh/IpRv+U8jd1/2pa+Kn3tQUAQQQQMBfAkF3wefLl0//93//p8cff1wLFy50938PdMUHSNq2bavatWsHnvIdAQRCKLDngNR1eHGdV+Oo+lyfJ4RX5lIIIIAAAghEViDoANSKZdtwWrf79OnT3a+URa1RowYBaEoUniMQAoG9zs631zh7u59Z6Yieveaoc8X8Ibgql0AAAQQQQCA6AlkKQLdtc7ZaISGAQEQF9h+SrusvnV5Reqr1XifvghHNn8wQQAABBBAItUDQY0BDnTHXQwCBzAUOHHb2dB8oVSsj9e9iE/8yfw9nIIAAAggg4HWBLLWAtm7dWgcOOAPR0klPP/20WrRokc6rHEYAgawIHDoidXxLOrm49M7NBJ9ZseNcBBBAAAFvC2QpALXtNg8dcvoD/06HDx/WmjVr9NNPP8kmIJUp4zTTkBBAIMcCh51hnje9IxUvJA3uJuWmryLHplwAAQQQQMA7AlkKQEeOHJlmyf/3v//plltuUdmyZdN8nYMIIBC8wBEn+Lx5kJTXmeg+/DYpD8Fn8HiciQACCCAQEwIh+dVmuyCVL19eU6dOjYlKU0gEvCpw9Jh061DJWkDf7Z4QhHq1rJQLAQQQQACB7ApkqQU0vUxsK86tW7dq+/bt6Z3CcQQQyETgmBN89hgu7dovjbnLWWgpJP87M8mUlxFAAAEEEIiCQJZ+xb399tuycZ9Jk23RaS2f69ev18UXX5z0JR4jgECQAs7fcLrzXWnzLumje6UC+YJ8I6chgAACCCAQgwJZCkBtF6T9+53mmSTJdkiqXLmyhgwZogYNGiR5hYcIIBCswL3/ldY4y+xOuM9Z5ZPgM1g2zkMAAQQQiFGBLAWgkdwHfvXq1apSpYry5k27iLYc1NGjzkC5FKlQoULOjOETQ1ttWICdd/LJJyeeaTP5k77XdncqWJDFvROBeBBRgYc+kJZtlD6+XyrMBkcRtSczBBBAAIHoCJyI1ILMf/HixZowYULi2QMGDEj2PPGFbD74+uuvVbNmTdnEptKlS6c7saldu3YqWrRoqq9FixYl5rx37161bNlSH3zg/IZPks4991wVLlw48athw4ZJXuUhApETeGyMtGBNQstnUf4Gihw8OSGAAAIIRFUgSwHoO++8IwvW5s6dm1hoC/JuvPFGd/znMZtFkYNkrZq33nqrXnjhBa1atUpDhw5Vly5d0lz8ftKkSdq3b1/i1913361LL700cRjAggUL1KRJEy1btixZiaz1c+nSpe76pYH3//jjj8nO4QkCkRD413jp618TWj5tvU8SAggggAAC8SKQ5QC0b9++eumllxJ9Hn30Ua1YsULffPONPv7448Tj2XlgrZcHDx5Ux44d3be3b9/e7TqfPn16qsvlz59f1t1uXxZsjh49WsOHD3e2KkzYq7BTp06644471KZNm2Tv/fnnn91rVqtWze3et/fT/Z6MiCcREHjuE+nzJdKnD0glC0cgQ7JAAAEEEEDAQwJpD7BMo4A2ltICxMmTJ6d61YK5pk2buq2N1157barXgz1guyrZtZKmqlWrujPskx5L+thaXW+//Xb16dNHlSpVSnzJymrB5bRp0xKP2YOFCxe6Y0SbNWum+fPnq06dOm7gevbZZyc7L+WT2bNnu8FxyuP23IYl7N69O9UErbTODeexI0eOyJbESjlRLJx5cu2sC7w+Pa8++j6PPrn3oAo5fwKmmNeX4QVt7LK14nOPM2SK6RftZ5r9IW7/l0n+FLB7az1+efI4u02QfCcQ+L8b7Z/TFpfYSkW2WVB66YwzzlCFChXSezmsx4MOQE866SR3p6OPPvpI997rrBOTJFlwOm/ePLf7PMnhLD/ctGmTSpQokex9xYsX159//pnsWNInM2bMcNcg7dq1a9LDbvCZ7MDfT+yDceGFF6pfv37ukX/+85+yoNlacQsUKJDWW9xjNtZ12zZnmnIaacuWLTIfu9nRTIEANKdDIaJZB7/nPWh2YY1ekE+jb9uu/E6gkdWPTGACXcrl0PzuFk/1s//HNjzIAhSSPwXsZ7QFBoEeO3/WMn5rFQhAox0T7NmzRzZ53IY1ppd69+7t/QDU/qNYl7i1NBYrVswdX2kTeWysplXOjrVu3Tq9OgZ13CYdpbxh9rxixYrpvn/w4MHq1q1bugFnyjfaGFP7CqSnn37abQFdsmSJGjVqFDic6vuHH36Y6ljgwJgxYzRu3DiVK1cucCgq3wOrFJQsWTIq+ZNpxgIDZjgLzDvDjWc8KpUvkb1ta+2PIBsyYhPwSP4U2Lx5s+z/MEOD/Hl/rVa2bnaZMmXSXeXFvzWPj5pZALp27dqoxwTWK2zLZFpDnRdT0C2gVvj+/fvL/nKzAC4Q4dtx68a2mfEWQOYkWXe7dcMnTbYcU40aNZIeSnxsE6Bs3Kl1qweb7PxSpUqpefPm7lsssLZuEMubhEC4BAZ9Kb01U5re24LPcOXCdRFAAAEEEIgNgSxNQrJAzWbCW0vbV1995bb6/fDDD+4YyAsuuCDHNbZxpLbu56BBg9wA991335V1R9mySZZsHObvv/+emM/y5ctlC+FbABxsshbVnj17ypqmrTvzlVdeUYsWLdzhBcFeg/MQyIrA8K+l15yhyFMfliqVyso7ORcBBBBAAAF/CmSpBdQIbMLNb7/95o6btOc2NtJaLXMy+ciuY8kC3GHDhrmz4J988kl3XOWIESMSu9d79Oih7t2768EHH3TPt+WUbABt0oXn3Rcy+Oemm25yx6vWr1/fnchhTdTWhU5CIBwC782Vnp/kzHjvJVXNWQdBOIrHNRFAAAEEEIiKQJYCUGv9vOeee/TQQw8lBpyBdUBtzU2baZWVYDCtGl900UWyMVBbt25NNX7CAs6kySYepZx8lPR1ezxx4sRkhyzIHThwoDsJyVpybRwOCYFwCIyeLz01QZritHzWyN6Qz3AUi2sigAACCCAQdYEsdcFbABrOdUADGjYuM9wTeqzxyvbEAAAm9UlEQVSrn+AzIM73UAuMXyA9Plaa5DTW147u3LRQV43rIYAAAgggkGOBoAPQwDqg1oWdMiVdBzTlazxHIN4EPnXmxD38QcIi83Wis7xavJFTXwQQQACBGBMIOgBNug5oyjoG1gFNuYh8yvN4joDfBab8JN3334TtNeue2BfB79WmfggggAACCGRJIOgxoJFYBzRLJedkBDwmMONn6c6R0nhnn4Yzq3iscBQHAQQQQAABDwkEHYBamcO9DqiHXCgKAlkS+HK5dNswaezd0tnVs/RWTkYAAQQQQCDuBLIUgAbWAX3ppZfcfeFtpnrNmjVlSxrZpB4SAvEoMHuF9I/B0gd3SufWjEcB6owAAggggEDWBLIVNdr+7M2aNUvM6eDBg+5amrVr11bjxo0Tj/MAAb8LzFspdf6PNKqH1KSW32tL/RBAAAEEEAiNQNCTkNLKzvaBf/TRR1WlShV17tw51Taaab2HYwj4ReD71dKNb0nDbpOan+aXWlEPBBBAAAEEwi+Q5RbQo0eP6rPPPtPbb7+tadOc/QWd1LJlS3d/+LZt24a/xOSAgAcEFq6V2g+QBnWTWp3hgQJRBAQQQAABBGJIIOgAdNOmTRoyZIgGDx6sdevWudtjli1b1t3WskaNGjFUZYqKQM4EFq+Xrn1TGnizdFm9nF2LdyOAAAIIIBCPApl2wc+cOVMdOnRQ1apV3V2QWrRooRkzZuitt95S0aJFRfAZjx+b+K3z0o3S1W9Ibzj7MVx5Vvw6UHMEEEAAAQRyIpBhALp27Vq1atXK3Zd9xIgR7h7to0aNco/ldM/3nBSa9yIQDYFfNkttneDzpY5OEHp2NEpAnggggAACCPhDIMMu+CJFiqhWrVr65ptv3Npu3rzZnWxUvnx5f9SeWiAQpMDKrU6L52vSc9c5Yz9Z6CFINU5DAAEEEEAgbYEMW0BLly6tFStWuF3u1atX15NPPunOeL/qqqv0xRdfpH1FjiLgM4E126Q2r0pPXS11Ot9nlaM6CCCAAAIIREEgwwDUymNbcNq4z5EjR8omIg0cOFDbtm2TdcmvX79et912m7788ksdP348CsUnSwTCK7BuR0Lw+eiVUtcLw5sXV0cAAQQQQCBeBDINQJNC2AL0PXr0cGe+L1myRPfcc48mTZqkiy++WNZC+u233yY9nccIxLTAxj+l1q9I91/mbLPZPKarQuERQAABBBDwlECWAtCkJa9bt65effVVtxV0/PjxOvPMM7VxozNFmISADwQ273JaPp0xnz0vlu5wvkgIIIAAAgggEDqBDCchBZNNvnz5dO2117pfwZzPOQh4XWDrbukKJ/i82elyv+9Sr5eW8iGAAAIIIBB7AtluAY29qlJiBDIX2P5Xwmz3Ds5M94dbZ34+ZyCAAAIIIIBA1gUIQLNuxjt8KvDn3oTgs21D6fGrfFpJqoUAAggggIAHBAhAPXATKEL0BXbtl65yFpm/pK70pLPcEgkBBBBAAAEEwidAABo+W64cIwJ7DkjtnOCzaW1nofnrY6TQFBMBBBBAAIEYFiAAjeGbR9FzLrD3oHRNP+nsatKLN+T8elwBAQQQQAABBDIXIADN3IgzfCqw/5B0XX/p9IrSa518WkmqhQACCCCAgAcFCEA9eFMoUvgFDhyWOgyUqpWR+nexHb/Cnyc5IIAAAggggECCAAEon4S4Ezh0ROr4lnRycemdmwk+4+4DQIURQAABBKIuQAAa9VtAASIpcPio1OkdqUQhaXA3KTf/AyLJT14IIIAAAgi4Avz65YMQNwJHnOCz6yApfx5p2G1SHj79cXPvqSgCCCCAgLcEcrwVp7eqQ2kQSFvg6DGp21DJgtAP7pTyOkEoCQEEEEAAAQSiI0AAGh13co2gwDEn+Ow+XLL1Pkc7wWc+gs8I6pMVAggggAACqQUIQFObcMRHAsePS3e8K23dLY27RyqQz0eVoyoIIIAAAgjEqAABaIzeOIqduYAFn/f+V1q7TRp/n1SQ4DNzNM5AAAEEEEAgAgIEoBFAJovoCDz0gbR8kzTRCT4L549OGcgVAQQQQAABBFILEICmNuGIDwQeHSP9uFb65H6paEEfVIgqIIAAAggg4CMBAlAf3UyqkiDwfx9Jc36VJj0oFXfW+yQhgAACCCCAgLcECEC9dT8oTQ4Fnv1EmvGzNPlhqWThHF6MtyOAAAIIIIBAWAQIQMPCykWjIfDSZGe85wJpWm/ppCLRKAF5IoAAAggggEAwAgSgwShxjucFXp/mLDA/T5raSypT1PPFpYAIIIAAAgjEtQABaFzffn9UfsAMZ2vNr6XpTstnueL+qBO1QAABBBBAwM8CBKB+vrtxULdBX0pvzUwIPsuXiIMKU0UEEEAAAQR8IEAA6oObGK9VGO60er7mdL1/7nS7VyoVrwrUGwEEEEAAgdgTIACNvXtGiR2B9+ZKz09KCD6rloYEAQQQQAABBGJJgAA0lu4WZXUFRs+XnpzgzHZ3llqqURYUBBBAAAEEEIg1gdyxVmDKG98CH30vPT7WWefzIalWufi2oPYIIIAAAgjEqgABaKzeuTgs9yc/Sr0/lD59QDqtfBwCUGUEEEAAAQR8IkAXvE9upN+rMeUn6f73pI+dvd3rVvJ7bakfAggggAAC/hagBdTf99cXtZu+RLpzpDT+XunMKr6oEpVAAAEEEEAgrgVoAY3r2+/9yn+xTLp9uDTuHqlhNe+XlxIigAACCCCAQOYCtIBmbsQZURL4eoV0yxDpwzulxjWiVAiyRQABBBBAAIGQCxCAhpyUC4ZCYO5vUtf/SKN6SBfUCsUVuQYCCCCAAAIIeEWAANQrd4JyJAp8t1rq9Lazv/vtUvPTEg/zAAEEEEAAAQR8IkAA6pMb6Zdq/Pi71GGANLib1PJ0v9SKeiCAAAIIIIBAUgEC0KQaPI6qwOJ10nX9pbduli6tF9WikDkCCCCAAAIIhFGAADSMuFw6eIGlG6Wr+0lv3CRdcVbw7+NMBBBAAAEEEIg9AQLQ2LtnvivxL5ultm9IL3V0gtCzfVc9KoQAAggggAACKQQIQFOA8DSyAiu3Sle+Jj13ndS+cWTzJjcEEEAAAQQQiI4AAWh03MnVEVizTWrzqvTU1c6s9/MhQQABBBBAAIF4ESAAjZc77bF6rtuREHw+eqWz3ueFHiscxUEAAQQQQACBsAoQgIaVl4unJbDxT+nyV6QHLpNua57WGRxDAAEEEEAAAT8LEID6+e56sG6bd0mtnW73O1tKPS/2YAEpEgIIIIAAAgiEXYAANOzEZBAQ2Lo7odv9lqbSvZcEjvIdAQQQQAABBOJNgAA03u54lOq77a+E2e4dz5Meah2lQpAtAggggAACCHhCgADUE7fB34XYsVe6yllqqZ2zxudjzqQjEgIIIIAAAgjEtwABaHzf/7DXftd+J/h8PWFrzX+1C3t2ZIAAAggggAACMSBAABoDNylWi7jngLPDkRN8Nj9VetZZaJ6EAAIIIIAAAgiYAAEon4OwCOw9mLC3+zk1pL43hCULLooAAggggAACMSpAABqjN87Lxd53SLquv1S3kvTqjV4uKWVDAAEEEEAAgWgIEIBGQ93HeR44LHUYIFUvI73ZWcqVy8eVpWoIIIAAAgggkC0BAtBssfGmtAQOHZFueEsqX0J6+2aCz7SMOIYAAggggAACjAHlMxAigcNHpU7vSCULSYO6OR8s/rQJkSyXQQABBBBAwH8ChAn+u6cRr9ERJ/jsOkjKn0cadpuUh09VxO8BGSKAAAIIIBBLAnljqbCU1XsCR49J3YZKFoR+cKeU1wlCSQgggAACCCCAQEYCBKAZ6fBahgLHnOCz+3DJ1vsc7QSf+Qg+M/TiRQQQQAABBBBIECAA5ZOQLYHjx6U73pW27pbG3SMVyJety/AmBBBAAAEEEIhDAQLQOLzpOa2yBZ/3/Fdat1366F6pIMFnTkl5PwIIIIAAAnElQAAaV7c7NJV98APpl03Sx/dLhfOH5ppcBQEEEEAAAQTiR4AANH7udUhq+shoaeFa6dMHpCIFQnJJLoIAAggggAACcSbg2QVzVq9erSNHnJXN00kHDhzQ3r17U30ds5kxSdL27du1devWJEcSHh48eFBr1zqRFClogSc+kr75LaHls1jBoN/GiQgggAACCCCAQDIBzwWgX3/9tWrWrKlWrVqpdOnSmjp1arICB560a9dORYsWTfW1aNGiwClucNqyZUt98IHTZ5wkPfPMM6pcubIuuOACNWrUSFu2bEnyKg/TEnh6ojRzqfSJ0/JZolBaZ3AMAQQQQAABBBAITsBTAai1at5666164YUXtGrVKg0dOlRdunSRHU+ZJk2apH379iV+3X333br00kvVoEED99QFCxaoSZMmWrZsWbK3zpkzR0OGDJG9vnLlStWvX1+PPvposnN4klyg72fSpIVOt/uD0klFkr/GMwQQQAABBBBAIKsCngpArfXSusY7duzo1qN9+/Y6+eSTNX369FT1yp8/vwoVKuR+WTA5evRoDR8+XLly5XLP7dSpk+644w61adMm2XsnTJigDh06qGrVqipYsKB69eqlMWPG6LhN7SalEnjNaYAe/a302UNSmaKpXuYAAggggAACCCCQZQFPTUJas2aNqlWrlqwSFiiuX78+2bGkT2zM5+23364+ffqoUqVKiS9ZMGsB6rRp0xKP2QMbW3rRRRclHrP89u/fLxsrWqZMmcTjKR907tzZPSflcXu+efNmlShRIupd+TZm1gJpC+JDkYZ9U1j/nV9IH972p47vP6Yt+0NxVa6RE4FDhw7Jvmz8M8mfAnZ///zzT+XO7an2AX9iR6lWR48e1bZt2xIbTKJUDLINk0CgQSvaw/s2bNgg+2rdunW6NX344Yfd3uN0TwjjC54KQDdt2uQGcknrW7x4cfeHcdJjSR/PmDHDnWTUtWvXpIfd4DPZgb+fWLBo1wwkG0dqyX7gZxSA9ujRI82hAPbeWbNmuV36Sa9rxyOdLCixD36gTjnJf+jXeTRqfl59et9BVSxJ02dOLEP53t27dytfvnzpfr5DmRfXio6A/SwqXLiwrJeH5E8B+yPDfk7nycP2cX68w/Z7+I8//kgWa0SjnvYZs8axBx90xs+lk84444x0Xgn/YU8FoDbpyH7BJk32vGLFikkPJXs8ePBgdevWLehfyJbHnj17Eq8ReJxRHnZyixYtEt+T8sGuXbv022+/BV2GlO8P1fNAy6e1/OYkDftKGviFNK2XVLV0zq6Vk3Lw3tQC9kdGYPhJ6lc54gcB+3lSoEABd4iQH+pDHVIL2FAxGwKWN6+nfgWnLihHsiUQaAHN6e/ibGWe5E0WfFoQevnllyc56p2Hnvr0W3e7dcMnTdZlXqNGjaSHEh/bL+OPP/5YCxc6M2SCTJaHXTOQ7HHZsmVVpAiza8zkv99INukoIfgMKPEdAQQQQAABBBAInYCnBhk1bdrU/Ytw0KBBblfyu+++664Feu6557o1nj17tn7//ffE2i9fvtztjqxTp07iscweWFf9hx9+qCVLluivv/5S3759deONN2b2trh4/UNnstG/J0qTnQlHNcrGRZWpJAIIIIAAAghEQcBTAaiNhxk2bJj+9a9/qUKFCm5wOGLEiMSubRuHOX78+ESmpUuXysYvZGWw/nnnnecu9XTOOeeodu3a2rlzp55//vnEa8brg4++l/45LmG2e61y8apAvRFAAAEEEEAgEgKe6oK3CtsMdZsoZLsXlSuXPBKygDNpstbMlJOPkr5ujydOdJr0UqRnn31WTzzxhDupqGTJkilejb+nn/wo9f4wYZ3P08rHX/2pMQIIIIAAAghEVsBzAahV3wZopww+Q81iA8DtK97TlJ+k+99L2F6z7olVrOKdhfojgAACCCCAQBgFPNUFH8Z6cuk0BKYvke4cKY2/VzqzShoncAgBBBBAAAEEEAiDgCdbQMNQTy6ZQuCLZdLtw6Vx90gNq6V4kacIIIAAAggggEAYBWgBDSOuVy/91S9StyHSh3dKjdNe4cqrRadcCCCAAAIIIOADAVpAfXATs1KFub9JXQc56332lC6olZV3ci4CCCCAAAIIIBAaAVpAQ+MYE1f5zll//8a3pRG3S81OjYkiU0gEEEAAAQQQ8KEAAagPb2paVfrRWb+/wwBpSDfp4tPTOoNjCCCAAAIIIIBAZAQIQCPjHNVcflonXddfevsf0qX1oloUMkcAAQQQQAABBEQA6vMPwc8bpGv6Sf06S23O9HllqR4CCCCAAAIIxIQAAWhM3KbsFfKXzVLbN6SXna3u2zXM3jV4FwIIIIAAAgggEGoBZsGHWjRK17Nu9s8X5Xdzv9Rp6SxSQLryNen59tL150SpUGSLAAIIIIAAAgikIUAAmgZKrB16b670wPvODPdz8ujYcenCPlKJQtKLNzjHzou12lBeBBBAAAEEEPC7AAFojN9h206z5whp5UtSgeP7tf7PXJq+rIA27pROLh7jlaP4CCCAAAIIIOBLAQLQGL+tHy2QXnHGeJYrIS1dk0sd/lNUD7d2gtF80tjvpMuY9R7jd5jiI4AAAggg4D8BJiHF+D3dtkeqWDKhEtv35taEu/5Sz4ulssWkP5zXSAgggAACCCCAgNcECEC9dkeyWJ7zakqjvkl4U/1KR1W+uDMI1EmPjnG22jwl4Tj/IoAAAggggAACXhIgAPXS3chGWe5oKU35Sar1iJxxn7ncrxsGSmu2SQ9eno0L8hYEEEAAAQQQQCDMAowBDTNwuC9frKC08y3p1qHS1W85/e5OOs9p+dzgrP+Zn7sbbn6ujwACCCCAAALZECBEyQaa196SN4/0bg8nEN252y1ayZJ/Dwr1WkEpDwIIIIAAAggg4AjQBc/HAAEEEEAAAQQQQCCiAgSgEeUmMwQQQAABBBBAAAECUD4DCCCAAAIIIIAAAhEVIACNKDeZIYAAAggggAACCBCA8hlAAAEEEEAAAQQQiKgAAWhEuckMAQQQQAABBBBAgACUzwACCCCAAAIIIIBARAUIQCPKTWYIIIAAAggggAACBKB8BhBAAAEEEEAAAQQiKkAAGlFuMkMAAQQQQAABBBAgAOUzgAACCCCAAAIIIBBRAQLQiHKTGQIIIIAAAggggAABKJ8BBBBAAAEEEEAAgYgKEIBGlJvMEEAAAQQQQAABBAhA+QwggAACCCCAAAIIRFSAADSi3GSGAAIIIIAAAgggQADKZwABBBBAAAEEEEAgogJ5I5qbTzOrWLGixo4dq8aNG0e1hjt37nTzL1myZFTLQebhE9ixY4fy5s2r4sWLhy8TrhxVAbvHBQsWVOHChaNaDjIPn4Dd42LFiilfvnzhy4QrR03g+PHjst/HpUqViloZLOMDBw7o6NGjUS1DRpnncqCOZ3QCrwUnsGTJEu3fvz+4k8N01pAhQ9wPW8+ePcOUA5eNtsDTTz+tRo0a6aqrrop2Ucg/TAL2//eOO+5Qw4YNw5QDl422gP3/HTp0qMqVKxftopB/GASOHDmiZs2aae7cuWG4etYuWbt2bXm1UYoW0Kzdy3TPrlevXrqvReqFKVOmuAFotFtiI1XfeMynTJkyqlmzZtRb2+PRPlJ1tpax008/nXscKfAo5JM/f341aNBAlStXjkLuZBlugcOHDyt37tz8H84EmjGgmQDxMgIIIIAAAggggEBoBQhAQ+vJ1RBAAAEEEEAAAQQyESAAzQSIlxFAAAEEEEAAAQRCK0AAGlpProYAAggggAACCCCQiQABaCZAvIwAAggggAACCCAQWgFmwYfWM6pXq1q1qqfX/Ioqjk8yP/XUU3XyySf7pDZUIy2B+vXrq0SJEmm9xDGfCNhKJQUKFPBJbahGSgGbAd+kSZOUh3meQoB1QFOA8BQBBBBAAAEEEEAgvAJ0wYfXl6sjgAACCCCAAAIIpBAgAE0BwlMEEEAAAQQQQACB8AoQgIbXl6sjgAACCCCAAAIIpBAgAE0BwlMEEEAAAQQQQACB8AoQgIbXl6sjgAACCCCAAAIIpBBgGaYUILH6dP/+/cmKni9fPuXNy+1NhhLjT44fP641a9aocuXKsvtL8o/AkSNHdPDgwVQVsvucP3/+VMc5ENsC69evd/8fx3YtKH16Alu2bJEtxVS2bNn0TuG4I0ALqA8+BitWrFDhwoWTfT3zzDM+qBlVCAj88MMPqlmzpq6++mrZeq8vv/xy4CW++0BgxIgRKlq0aKqvf//73z6oHVUICEyePFn16tXTFVdcobp162rChAmBl/juA4EDBw7ouuuuU7Vq1XT++eerZcuW2r17tw9qFp4qsA5oeFwjetUxY8aof//++vzzzxPzpQU0kSLmH1jLp/2yuv/++9WzZ0+tXbtWZ511lpYsWaJKlSrFfP2ogNwNJA4dOpRIMWfOHHXo0EE//vijqlevnnicB7EtYJsM2B8V119/vaZNm6Y777xTv/32m9taFts1o/Qm0KdPHw0bNkz2/9c2DHnkkUfcXqtx48YBlIYAfbRpoMTaoYULF+qcc85RoUKFdPjwYbpnY+0GZlLeWbNmyYZYWPBpyVpAFy9erNKlS2fyTl6OFYE8efK4/3+tvHav77rrLvXr14/gM1ZuYBDltNaxX3/91e3JsNNPP/10NzjZsWOHypQpE8QVOMXrAl988YW6dOmi8uXLu0Xt0aOHGjZsKGtEyJUrl9eLH/Hy0QUfcfLQZ2itJPPnz5dt02jdeDfddJP27NkT+oy4YlQEVq5cqdNOO81tOaldu7bOPvtst/WzYMGCUSkPmYZX4LnnnnP/yLj55pvDmxFXj6iA/X999tlndcstt8iGSFlX7aOPPkrwGdG7EN7M7Of0rl27EjPZtGmT9u3bJxvzS0otQACa2iTmjthfz9dcc43bKjZ37lwtWrRIjz/+eMzVgwKnLWA/xKwVdOvWrfrkk0/cPzA6deoka1Eh+UvAuuEHDRrkDrfwV82ojbWC2f21MYE2mXDbtm3uBLOjR4+C4xOBrl276t1339XQoUPdn9n2h4ZNIty5c6dPahjaajAGNLSenrjam2++qTfeeEOrVq3yRHkoRM4E7H4++eST2rx5swKtnjYG9IknntANN9yQs4vzbk8J2HhuaxWzVm+bRUvyj4A1DlxyySXauHGjSpQo4f4BaStaWMBik5JI/hCw+Rg2DtSGSNn/ZZs4arPiixUr5o8KhrAW/IQLIWY0LmVjPl999VX3r+lA/jbWxGZMk/whYGM+7RdWIPi0WpUsWVJ//PGHPypILRIF3n//ff3jH/8g+EwU8c+DBQsWqHHjxu7/ZauV/X9u0qSJvvvuO/9UMs5rYoFm+/bt3cmDM2bMUJUqVdzAk+Az7Q8GAWjaLjFz1Ga7W/fsCy+84A50tu5aa/7v2LFjzNSBgmYs0Lp1a3dy2dixY90TbUmmb7/9Vq1atcr4jbwacwI//fSTO6Ew5gpOgTMVsGDT/u/aPba0fPlyTZ8+XRdeeGGm7+WE2BD4+uuv3eFwNqzi2LFj7rh9W+mAlLYAXfBpu8TU0aVLl6p3795atmyZ29Rvk5AGDBigAgUKxFQ9KGz6ArasR+fOnd3NBWyQu7V6M0klfa9YfMVmvxcpUsTtfq9Ro0YsVoEyZyLwn//8xx2fb0v02HJqTz31lNtNm8nbeDlGBCzotB4MC0Stccj+6LDueFvlgpRagAA0tUnMHrHAxILOpF21MVsZCp6mgI0DtV9ejA9Mk4eDCHhewFrHbByoLdVjQQrJfwJ79+51GwtoBMr43hKAZuzDqwgggAACCCCAAAIhFmAMaIhBuRwCCCCAAAIIIIBAxgIEoBn78CoCCCCAAAIIIIBAiAUIQEMMyuUQQAABBBBAAAEEMhYgAM3Yh1cRQAABBBBAAAEEQixAABpiUC6HAAIIIIAAAgggkLEAAWjGPryKAAIIIIAAAgggEGIBAtAQg3I5BBBAAAEEEEAAgYwFCEAz9uFVBBBAAAEEEEAAgRALEICGGJTLIYAAAggggAACCGQsQACasQ+vIoAAAggggAACCIRYgAA0xKBcDgEEEEAAAQQQQCBjAQLQjH14FQEEEEAAAQQQQCDEAgSgIQblcgggEBsChw4d0pIlS3T8+HG3wFu3btW6detio/CUEgEEEIhxAQLQGL+BFB8BBLInMHv2bLVq1Uq5cuVyL/DII4/ojTfecB9bIGrHW7RokRigJs2ld+/eKl++fNJDmT4uVaqUXnzx/9s7rxApligMH3UNmDFizjlhzqIPomLOYsSACUQfBBMmBPUaURRzRDFhQMwJVFAfzGJ4UFExIOasGPrWf6DqzszO7uqMF3q2/4Klq6qreqq+Bu9/T6j+J81xdsCwYcOkfv36thn1OmTIEGnYsGHUe+wkARIgAT8ToAD189vh2kiABP43ApcuXZK6deu650e2cePMmTOydu1aNyaeSp8+faR69erxPIJzSYAESCDdEKAATTevkhshARL4EwIXL16UevXq6ZTPnz/L7du3Xds+p1ChQgLL6LNnz2xXzNcVK1ZI+/btY57PiSRAAiSQnghQgKant8m9kAAJpErg/v37KjIhPA8ePCibN2/WdoMGDeTnz58CK+WhQ4fcM6ZOnSoZM2aUMWPGuL6UKuvWrZPatWtLrly5BM/bv39/2NCWLVvKxo0bXd+DBw8EbvaiRYuqZXT79u3Sv39/WbNmjRuDypYtW6RGjRqSP39+6dSpkzx9+jTsPhrLli2TsmXL6rOGDx8unz59Chtz9uxZadGiheTJk0cqVKggEyZMkG/fvrkxzZo10/U2btxYypUrJ4cPH5Z3797J4MGDNdQgX7580qpVK7lw4YKbwwoJkAAJxEMgKZ7JnEsCJEACiUQAAgwi78OHDwKX+8SJEyVnzpxy6tQp+fHjhwwcOFCFnN0TLKDz58+XoUOHyr59+6RLly72VtgVYyZPniy9evWSGTNmyOnTp3Xsrl27pHv37jr22rVr8vz5c61D/KH/+/fvsmTJEnn9+rWKXAjHihUrumdfv35dpk2bJmPHjlVBuHTpUp13/vx5N+bKlSvy6tUrmTNnjgpPiEuI22PHjukY7BPiEdZXCO6HDx/qM5GABRGOgmeMGjVKypcvL9WqVVMhC9GNEATsp0CBAgILLmJiIYAhhllIgARIIC4CJgOUhQRIgAQCRcAIK88kBbk9G0ukZwSXaz969Aip8d6OHTu0z1gvvWLFinnGKqjt8ePHe4ULF9b6mzdvvNy5c3vGWujmo9K7d2/PCDrXlzdvXm/u3LnaNhZLff6tW7fc/Q0bNmjfzJkztc+IXs8kQnkmNMCNMSLXy5Qpk2cy+LUPv4l1moQqN8ZYXrXPWCu1r3nz5p6x+Hq/fv1yY4yVVcccP35c+7Jnz+7VqVPHM1ZgN6ZUqVLepEmTXNsITw9runnzputjhQRIgARiJUAXfFzynZNJgAQSkQAsfnCX23L58mUxAsw2k11XrVolL1++VNd15M2rV6/K+/fvpVatWnLu3Dn3B1f33bt35cWLF5FT1PpavHhxqVKlirvXpk0bV7eVIkWKSOXKlW1T4CpHqMDjx49dH6y6jRo1cu0OHTpIlixZBFZS8x8GQaxr3759XbY/BrZt21bHY7224NkIN7AF2fULFy6U0aNHy9GjR9XqiYSsqlWr2iG8kgAJkEDMBOiCjxkdJ5IACSQaAbjAFy1aJCdPnlSXO9zVKHBHG2ugJiIhDhQu59ACt/iUKVNk+vTp0q9fv9Bb6tJGx7hx48L6bQPu8IIFC9qmXu/cuZPs+CSITcRxhhbEh4aWrFmzahPhArYgbtNYRW1ThSZCB+Aqx36/fPmiLnU3wFQgfvFbofGkJUqUCB2isahJSUmC2Fa4342VV0aOHCmzZ88O+72wSWyQAAmQwG8S+O9/d39zAoeRAAmQQKISQOylcSGLcX2rlRB1xDnCUoikG7Tfvn0bdXsQq7BYIsknNIEHCTooSNAxbu5kf9HO8oRANK77ZL+T0m8nGxjSgQP1IwtiQiFosTZYNRFjGlk+fvyoCUe2P1TEog+Cc+vWrRpfunv3boGFdt68ebJ48WI7hVcSIAESiJkABWjM6DiRBEgg0QiULFlS9uzZo9ZPZKQfOHBARowYITVr1tQ62kjYiVbg1l69erXAerlp0yY3BEk7OLTexIvqFXX8rVy5Unr27Clfv351Y22lSZMmKljh1rcF7vBoQtHeT+mK8IFQQQzXO6ye2BPWjFCAEydOhE1HQhS+/IQx0QrW3LlzZ9m5c6cmaXXr1k3ryJBH+AILCZAACcRLgAI0XoKcTwIkkFAE4G7PnDmzVKpUSdcdGQ+a2maaNm2qFlDEfNoCV7ZJOJL169fLggUL1O2NjHmTqKTxktmyZbND3RWubHtcE0TtrFmzpGPHjipc3aDfrMBqOmjQID2rFJZdWGgRv4mvPKEgO3/v3r0aegAr740bN3Q8Yl4R9xmtYM0IG0DYAcIVYK2FNRTHWCETnoUESIAE4iVAARovQc4nARJIKAKwGMLyZ13OaSUgRW4On9OEezu0IEmpa9euYrLG9dxMJO4gVhTtaAXubVgqkWCEo6C2bdsmy5cvV2ujyUiPNiXFvnbt2mliksnS1yOUEL8KK68tAwYMULc5jlMymfh6Rik+I3rkyBHJkSOHHZbsinhXcOrRo4e68iFssVacXcpCAiRAAvESyID0+XgfwvkkQAIkkCgE8FUjuJjLlCmjS0bcJxJwIArjLYjHfPLkiZQuXTpVa+a9e/c0VhTucVvwNSZYRWFJhUXzTwviPvHPeWQClX0O7uEMUIhnm8xk76V2Rda9OZZKzLFMYVnyqc3hPRIgARJIiwAFaFqEeJ8ESIAE/jIBZJYj9hRxn/hqEmI44bJHP2JMEavKQgIkQALpmQAFaHp+u9wbCZCALwlAcNrPfsIdjoQgHHkE13nr1q19uWYuigRIgAT+JgEK0L9Jk88iARIggT8ggE9v4jvtOJYJ8ZYQoSwkQAIkEAQCFKBBeMvcIwmQAAmQAAmQAAn4iACz4H30MrgUEiABEiABEiABEggCAQrQILxl7pEESIAESIAESIAEfESAAtRHL4NLIQESIAESIAESIIEgEKAADcJb5h5JgARIgARIgARIwEcEKEB99DK4FBIgARIgARIgARIIAgEK0CC8Ze6RBEiABEiABEiABHxEgALURy+DSyEBEiABEiABEiCBIBCgAA3CW+YeSYAESIAESIAESMBHBChAffQyuBQSIAESIAESIAESCAIBCtAgvGXukQRIgARIgARIgAR8RIAC1Ecvg0shARIgARIgARIggSAQ+BffIW5PVCbpoQAAAABJRU5ErkJggg==" /><!-- --></p>
</div>
<div id="support-vector-machine" class="section level2">
<h2>Support Vector Machine</h2>
<p>Support vector machines attempt to pass a linearly separable hyperplane through a dataset to classify the data into two groups.</p>
<p>Read more here:<a href="https://towardsdatascience.com/support-vector-machines-a-brief-overview-37e018ae310f" class="uri">https://towardsdatascience.com/support-vector-machines-a-brief-overview-37e018ae310f</a></p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">svmfit<-<span class="kw">train</span>(Outcome<span class="op">~</span>BMI<span class="op">+</span>Glucose<span class="op">+</span>Pregnancies, <span class="dt">data=</span>train, <span class="dt">method=</span><span class="st">"svmLinear"</span>,
<span class="dt">preProcess=</span><span class="kw">c</span>(<span class="st">"center"</span>,<span class="st">"scale"</span>))
predict_data<-<span class="kw">predict</span>(svmfit, <span class="dt">newdata=</span>test)
<span class="kw">confusionMatrix</span>(<span class="dt">data =</span> predict_data, <span class="dt">reference =</span> test<span class="op">$</span>Outcome,
<span class="dt">dnn =</span> <span class="kw">c</span>(<span class="st">"Algorithm predicted values"</span>, <span class="st">"Actual Test Values"</span>))</code></pre></div>
<pre><code>## Confusion Matrix and Statistics
##
## Actual Test Values
## Algorithm predicted values 0 1
## 0 108 27
## 1 17 40
##
## Accuracy : 0.7708
## 95% CI : (0.7048, 0.8283)
## No Information Rate : 0.651
## P-Value [Acc > NIR] : 0.0002216
##
## Kappa : 0.4776
## Mcnemar's Test P-Value : 0.1748444
##
## Sensitivity : 0.8640
## Specificity : 0.5970
## Pos Pred Value : 0.8000
## Neg Pred Value : 0.7018
## Prevalence : 0.6510
## Detection Rate : 0.5625
## Detection Prevalence : 0.7031
## Balanced Accuracy : 0.7305
##
## 'Positive' Class : 0
## </code></pre>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co">#Tuning Paramter c with Grid Search</span>
grid <-<span class="st"> </span><span class="kw">expand.grid</span>(<span class="dt">C =</span> <span class="kw">c</span>(<span class="fl">0.01</span>,<span class="fl">0.1</span>,<span class="fl">0.5</span>, <span class="fl">0.75</span>, <span class="dv">1</span>, <span class="fl">1.5</span>, <span class="fl">1.75</span>, <span class="dv">2</span>,<span class="dv">5</span>))
svm_Linear_Grid <-<span class="st"> </span><span class="kw">train</span>(Outcome <span class="op">~</span>., <span class="dt">data =</span> train, <span class="dt">method =</span> <span class="st">"svmLinear"</span>,
<span class="dt">preProcess =</span> <span class="kw">c</span>(<span class="st">"center"</span>, <span class="st">"scale"</span>),
<span class="dt">tuneGrid =</span> grid)
svm_Linear_Grid</code></pre></div>
<pre><code>## Support Vector Machines with Linear Kernel
##
## 576 samples
## 6 predictor
## 2 classes: '0', '1'
##
## Pre-processing: centered (6), scaled (6)
## Resampling: Bootstrapped (25 reps)
## Summary of sample sizes: 576, 576, 576, 576, 576, 576, ...
## Resampling results across tuning parameters:
##
## C Accuracy Kappa
## 0.01 0.7723559 0.4510140
## 0.10 0.7727495 0.4652853
## 0.50 0.7724287 0.4673078
## 0.75 0.7727984 0.4684634
## 1.00 0.7726218 0.4678846
## 1.50 0.7724519 0.4676467
## 1.75 0.7718493 0.4665505
## 2.00 0.7718396 0.4666305
## 5.00 0.7722605 0.4680404
##
## Accuracy was used to select the optimal model using the largest value.
## The final value used for the model was C = 0.75.</code></pre>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">plot</span>(svm_Linear_Grid)</code></pre></div>
<p><img 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" /><!-- --></p>
<p>To increase our classification rate, we can try tuning our parameters for each classification algorithm and try other classification algorithms such as random forests and neural networks.</p>
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