<!DOCTYPE html>
<html lang="en">
<head>
<meta content="text/html; charset=UTF-8" http-equiv="Content-Type">
<style type="text/css">
/*Cambios
    
      -Ancho máximo del contenido 1160px para lectura en pantallas grandes
      -Centrar contenido
      -Margen interior a der y izq del 3%*/
body {
	font-family: "Roboto", sans-serif, "Montserrat", -apple-system, BlinkMacSystemFont, "Segoe UI", "Oxygen-Sans", "Ubuntu", "Cantarell", "Helvetica Neue";
	max-width: 1160px;
	margin: 0% auto;
	padding: 0 3%;
	background-color: #ffffff;
	scroll-margin-top: 100px;
}
/*Fin cambios*/

table {
	border-spacing: 0px;
	border-collapse: collapse;
	margin-bottom: 0px;
	background-color: transparent;
	overflow-x: auto;
	font-size: 12px;
}
th {
	font-weight: bold;
	border: 1px solid #0d7f54;
	padding: 8px;
	color: white;
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td {
	border: 1px solid #0d7f54;
	padding: 8px;
}
tr {
	background-color: transparent;
	border-top: 1px solid #0d7f54;
	border-bottom: 1px solid #0d7f54;
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tr:nth-of-type(2n+1) {
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tr th {
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th, td {
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p {
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	text-align: justify;
	line-height: 20px;
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.box1 p {
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p.address-line {
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ul, ol {
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ul.nav {
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li {
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	font-size: 13px;
	text-align: justify;
	line-height: 20px;
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li > p {
	margin-top: 0em;
	margin-bottom: 0em;
}
a {
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	/*Añadido color de los link*/
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}
a:hover {
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h1 {
	text-align: center;
	/*Cambio de lo color  y tamaño de fuente*/
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	font-weight: bold;
	margin-top: 40px;
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h2 {
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	font-size: 16px;
	/*Cambio de lo color*/  
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	font-weight: bold;
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h3 {
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	font-size: 16px;
	/*Cambio de lo color*/  
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	font-weight: bold;
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h4 {
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	text-align: left;
	font-size: 16px;
	/*Cambio de lo color*/  
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	font-weight: bold;
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	margin-bottom: 1em;
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h5 {
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	/*Cambio de lo color*/  
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	font-size: 13px;
	text-align: center;
	line-height: 20px;
	font-weight: bold;
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	font-size: 12px;
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.aff {
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	font-size: 13px;
	text-align: justify;
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.history {
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	font-size: 13px;
	text-align: justify;
	line-height: 20px;
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p {
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	font-size: 13px;
	text-align: justify;
	line-height: 20px;
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.citation {
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	font-size: 13px;
	text-align: justify;
	line-height: 20px;
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.copyright {
	margin: 10px 0px;
	font-size: 13px;
	text-align: justify;
	line-height: 20px;
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.top {
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	width: 45px;
	text-align: center;
	color: white;
	font-size: 12px;
	background: #0d7f54;
}
.zoom {
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.menulevel1 {
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	display: block;
	font-size: 14px;
	line-height: 20px;
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.menulevel2 {
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	display: block;
	font-size: 14px;
	line-height: 20px;
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.menulevel3 {
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	font-size: 14px;
	line-height: 20px;
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.active {
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	font-size: 10px;
	color: white;
	background: #0d7f54;
	border-radius: 15px;
	text-align: center;
}
.boton_1:hover {
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	text-decoration: none;
}
.box {
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	background: #0d7f54e8;
	margin: 0 0 25px;
	overflow: hidden;
	padding: 8px;
	border-radius: 7px 7px 0px 0px;
	-webkit-border-radius: 7px 7px 0px 0px;
	-moz-border-radius: 7px 7px 0px 0px;
	-o-border-radius: 7px 7px 0px 0px;
	-ms-border-radius: 7px 7px 0px 0px;
	border: 1px solid #0d7f54;
	margin-top: 30px;
	text-align: center;
}
.box1 {
	margin-top: -30px;
	overflow: hidden;
	padding: 10px;/*border-radius: 0px 0px 0px 0px; 
          -moz-border-radius: 0px 0px 0px 0px; 
          -webkit-border-radius: 0px 0px 0px 0px; 
          border: 1px solid #0d7f54;*/
}
.box2 {
	/* margin-top: -10px; */
	overflow: hidden;
	padding: 10px;/*Eliminar borde de todas las cajas y los margenes
      border-radius: 0px 0px 0px 0px; 
          -moz-border-radius: 0px 0px 0px 0px; 
          -webkit-border-radius: 0px 0px 0px 0px; 
          border: 2px solid #0d7f54;
      margin-top: 2em;
      */
}
nav {
	margin-top: 15px;
}
/*Añadido:
      -Borde solo a las cajas del resumen y datos de copyright
      -Poner magen especifico en dichas cajas y la que contiene los agradecimientos y las referencias
      */
      
header .box2 {
	border-radius: 0px 0px 0px 0px;
	-moz-border-radius: 0px 0px 0px 0px;
	-webkit-border-radius: 0px 0px 0px 0px;
	border: 1px solid #0d7f54;
	margin-top: 30px;
	padding: 0px 10px;
}
#article-back {
	margin-top: -20px;
}
/*Fin de añadido*/
    
.tooltip {
	position: static;
	display: inline-block;
}
.tooltip-content {
	display: none;
	position: absolute;
	background-color: #f9f9f9;
	max-width: 50%;
	min-width: auto;
	box-shadow: 5px 5px 16px 20px rgba(0,0,0,0.2);
	padding: 12px 16px;
	border-radius: 15px;
	text-align: justify;
	z-index: 1;
	color: #000000;
}
.outer-centrado {
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	right: 50%;
	position: relative;
}
.inner-centrado {
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	right: -50%;
	position: relative;
}
.clear {
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}
.tooltip-fig {
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	position: relative;
	background-color: #f9f9f9;
	min-width: auto;
	box-shadow: 5px 5px 16px 20px rgba(0,0,0,0.2);
	padding: 12px 16px;
	right: 30%;
}
.tooltip:hover .tooltip-content {
	display: block;
	position: absolute;
}
.tooltip:hover .tooltip-fig {
	display: block;
	position: absolute;
}
div.def-item {
	border-spacing: 0.25em;
	font-size: 14px;
	text-align: left;
}
div.section, div.back-section {
	margin-top: 1em;
	margin-bottom: 0em;
}
div.panel {
	background-color: white;
	font-size: 100%;
	padding-left: 0.5em;
	padding-right: 0.5em;
	padding-top: 0em;
	padding-bottom: 0em;
	margin-top: 0em;
	margin-bottom: 0rem;
	position: relative;
	top: 0px;
	left: 0px;
}
div.blockquote, div.verse, div.speech {
	margin-left: 4em;
	margin-right: 1em;
	margin-top: 1em;
	margin-bottom: 1em;
	background: transparent;
	text-align: justify;
}
div.note {
	margin-top: 0em;
	margin-left: 1em;
	font-size: 85%;
}
div.fig, div.disp-formula, div.table {
	text-align: center;
	margin: 15px 20%;
}
/* Evitar que aumente la altura de linea al usar superindices y subindices */
sup {
	vertical-align: top;
	position: relative;
	top: -0.3em;
}
sub {
	vertical-align: bottom;
	position: relative;
	bottom: -0.3em;
}
/*Poner linea inferior en los encabezados de los apartados*/
h2, h3 {
	display: inline-block;
	padding: 0 0 5px;
	border-bottom: 3px solid #0d7f54;
}
header h2 {
	display: block;
	border: 0;
}
/*Movido al final*/
.textfig {
	display: inline;
	text-align: center;
	font-size: 12px;
}
.orcid {
	text-align: center;
	color: white;
	font-size: 7px;
	vertical-align: middle;
	border-radius: 50%;
	border: 2px solid #8CC657;
	background: #8CC657;
}
</style>
<title>Evaluation of Azutecnia Horizontal Probe in Sugarcane Sampling</title>
<meta content="Sugarcane Sampling, Pay for Quality, Probe Samplermuestreo de caña, pago por calidad, sonda toma muestra" name="keywords">
<meta content="Yoel Betancourt Rodríguez" name="author">
<meta content="Jorge Luis Ponce Salazar" name="author">
<meta content="Yasiel Caballero Jiménez" name="author">
<meta content="Yoel José Moya Pentón" name="author">
<meta content="José Ramón Gómez Pérez" name="author">
<meta content="index, follow" name="robots">
<meta content="This article is under license Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0); URL=https://creativecommons.org/licenses/by-nc/4.0" name="copyright">
<meta content="Cervantes-Producciones Digital; URL=https://www.edicionescervantes.com" name="organization">
<meta content="en" name="lang">
<script type="text/javascript" src='https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-MML-AM_CHTML'></script>
</head>
<body>
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ZYWbneEa%20ww2AGFpmGOO1wd9lsv5geS3o381EK1vl1/jsyX6RFvKvARQBeo5AlbU+rIiWs13BJZ8QwnB/JbKB%20cVUb/LtYeMJS/fGF4eNtdC8TVX/U4+BRMrBHnjoo68MSK1BwCeVmoblRfl2zIPCiDiXCh+7TZjEZ%20FM6D/E8vjtqEGyJTvQLcWWGWRx1eN5EVkyknL7JnPtSPaIGLAYhxQsbUXI+6c0F+1vWQnwZBCyqD%207Q9/LRIQZO+bJOjKKSc+22paYrXOZYFIJeJt/ykSXujnIZ6CUO47MuvQo4qimli5I4Th/gpD/GK8%20Hz6oK1MOfFOkfl3sJSEJQiELe++V+h4IWEdVpSwolR7L8QEzBOTo3iN7uo4u/PnPdt732eUrhw5s%20MqBHYuQkIep9KayS6F0xS5nI1w3GRj46OR2QBSn/E601rbnySX6EERBErkus8Uo9m4fwzE8U9hbd%20b36xPlnrHj8ZyEtskKS38pFfsW3NZv368pJLzZomv3h3Kh/hEAzkwg2zv3t04v2roj145ypCf2HC%20F27AnXCWSSqUxrfywg6q2Ybjd1JiIhzeIm38aix3dyQwqQRFInnlssT9Wr4ytJFTDiINimo6LR2d%203CuMWU2bE6py6gj1jgaM7hqDSXHsylcVKWQfuJlUjWu1XGSnWK/Di/A4oZMDdLzB6H4k1DFQiGam%20uXfwoU9uAxG5KEOAEiUj5bYHDj2sjOVZQ7tzaAgyFngbU6tZUuauJa1jioQ9d4T+0nAlprNfudtl%20GJX/rpj8XLkIkSAwBf7nx8qRf6uOD6vhIBCVefU4P0lxTZKWI/3u14sXZgrdKjFJmXNy8t9QmV/A%20Jg3L7Otex5kLtUm49u9sknSpC8/RDy8SLh1TSZm2hx8MbNkuKcpJa3wu80CIJ0ty/n+S33tvdKDo%20T2qWjMBgut5qv613sgqw544QhvsrTmVixQ75x6HsjSKDmmoo5qDlEnM8aQjic9W7Xu0+SJ3uJrJo%20GSz5G33nJZNDQVNiRDhx6TziN8P5lMUEi0g7A+GwPyVkLAEkS6NdWsGCtMv+9GAgAqE2OdRUGHzN%201NVXs9rlZF/UzXKXnvJFABc4FxhbYAoq1CSgXIamSFobem9HbRqnmkEIw/0VSQBFmDKbvwvKBaOD%20IKtgZmnYFPlzLnAqcDKuWo3vz2sCzOjg699kh0pSoQyTjitx8vTAd5v25t2eV09l3jk5rthbH6W9%20fXCsH7Y/ImSWFQsfmNgzN1vIEOmp7oxfZDMYsRy7RKol4cr3OrIATe1MeFOuYHHh1IuuevkuC0RI%20i95T5ItQGAPe9kNXWxxQXWy4I/SXhxdUXwJcf96Y/p7PSuHA3kOBYF3ZuiUyx5Et6blC0XSgdTA4%20vc1QVhnFMoz10l7NaH6j3t1J9Z3RlCAoIpRdPjyzED6/vPwcN1Xnzr7Guu3bsvb92JTkRN+eufxj%20thfl8VZ3pG0quznUlFcohaIN/dQqXJV1HKlvl9g4DjQJogbqw6FUSTYFl4qnbKCrEtRuj+QXmJOq%20vbih1R7+3vzGI0+u74EQwnB/JXZmNGiNH9or3BWb+vr+bRtrTdgt6Aku1IHoEi6CPwjmj/eGSkAm%20S+zQ0kxHGwwO81/8h9h0OHwQjAs/l58/C+ZPwXRpYvsPA6v2hIetvLvOXHkNkwwwCxCNQrMotlpK%202AvpGFUEt5yD2XN5vM16eLQQ32A7oUD/q6fPucaJqBBJuMW7yKZ/DjclSVdTMVVnj62c6N0irxmL%20EpXxp/+AvG3jrneWwMhhYnEV+rcKgSV2edmXUuSOlpqtWLYjhOH+CmZDcwpGDry+q2S97V1Qfmu2%20swv0QTH7i6o4F3qJFQIhRQQmci/rSy4bm1Na/Eb/XtaZGXjiI7GF42GNKpQZkn87Egw9LjX3SOn2%20puia1fqPbrnrHqP1fcWZbdD7KB3poZmZ2VIZYlukSL2baoEHbhOEO0L1Ysr6+yvpr26L7Q6MtBdr%201jCvQo/o4syhqDIC5Sr78s/r4ACrdvtuk1qzKhHAH2fjkB5iBVzaQMXukCG/L62q/B0LIJOFJ7be%20cNnlDr6xCGG4v+IJUBU3EhPQ2wXBGFy4GobanMdvMycaHO3qYv+jajEri5NSa1HeHSu1fbAwpwmc%20EoSCkGkw9qSlIcmK/lbVB+zBacZujq5k7sia1vM/90+b77yndQB6fwo5XQyPKgstyr80ZuxV4jcn%20R/da/U1mOQ/LJmj2innnfeYfH/zDnbP7Avf/mOtWSSkLPY9K44kSLVG5xZYJWDqsusx9RMoO3phs%20Bqk7brCIk2vXxTa27+dR3mJdej4XbDjSBdSGtpSpyvimInTW4GIdL6l3w2/RWCY8sh+KAdCi8MAf%206HVvYiEFTBeGMrDn30Nt/UGL2G6E9LeU21+j5zZp4kNh/XWZQJLFvp2iGncFHlBAAzJKhMNX1cy6%20Y7iZCrZDCOEykAPUXPC9qZEDAvt6TWOYmo4/7EZifG+dkFlUs+zuYVWlOueGCV49PiU55AsTkzeH%204oMqvTZn19rTvwm3ZGS3zAVXGrg4e+H7zRAHRYX+fvLww+TN72CHdsGyFCxorcxMANhtR+iswdEy%20LyWVKJQ1uPR8KPSSh/4tWB+hscoULnkbHvtWoP0gCf3Lp2o+99nqSaftULj8leqWh+NNTIqLdOGF%207nCDHiNCtUwDnLolOh0pXH7NLv2SXH+JmRbXTTjsWOHrczaD1EI3fXF2oOha3td16AS74U2jK9fs%20HgEmWDQMtEamxCH5paXFiyECtL2kxm+ucv4zOX84INty+y2/FK5Y13SX8uDPRSHoH5JSKa5NSrd/%20XpsZg0WLKsnOMdkRwrYMeibml/Cz60lmf9jsDfxXdmq2ILs6CU5KssztgSF3+dK8Cy2C5AInEjnK%20rep5Vj4HLZ/KHv6ZE+pXOQF9iT7rncXBXcKMS83SkompfTKIvG6FJcqw+x9i2gxn3geK06usicOS%20V+y3rrasArFMUvXp9NFfhINexS5x69LSzOv07DhIS4zxvaGaKImDQik7qGg1AYWPjmqqQA6o237o%20FEX32ARffm9VrlafPUP3J5nBWEcI2zIv8zYLgTMZLkKAUdi0Qdy5Q4BFZvEP4eY9kVSMgMQPGyX4%20RJZuD0iPhRSX5MNO9B25UK174J/jVRfp0Qt1xwRBAEuErgcl+aGI3mAGLy/OngeEwJFOyG/U2k1V%20d3l/XbllvdXcCIUSdD5BpQ1h5pDA6/MtCxmUgQtAXTL5q7BegmVfzHffrgoPhTVbKGqO8vr8RNlu%20vbm6KiZBiXSXnOK1GdpuxXuUc6+yFno/buEbjxCG+8uaw/0ptPzrimeU7xAAZsPvNoGbgNGHFfZA%20SMtIpbX52W8rpycI81K0ROQkGxmDsduDsyWpFHNyrXrDfDcRgXwBVEZDMV5ZbYMTwZ+yRqD+HVI2%20AUpAcMAw/RLbn6SMEUnkzCaZHHiFvKbC0Bjk9kvV46ozKfZUl+deZwa8l1OkWpx5oR+M8MNfjSXG%20lFyDGXtdIdDqNgOsPffUS4ucDrmyAhSOm0QIw/2lToYN22BnF3zq9UDOeDUiwY/ge7eDEa2saFQk%20YoJv+p4mDspwcaFtIQt5YW1APObPSOMRXXAsYE5lskm7EuiVi7TeBogCOCJYbuUyC/FXuNZE4Kb/%20GNcFL/2945Akgir4WyqIICj+YUDwM53kSlxVYTQNo9slvikYfXVx2WVOecrfGLMAzSJcsKwysfuZ%20vUZvY1zYdQza6yEWwXxHCMP9pdmHoU8tr6HCT34NW/bDf3wc/CWN9Kdi64WGF/Uzs6sPDo7CsTR4%20ZbUGJFnL3crqSMcnhvE+S5Kfy8USlLmQZQFCydr2vPfggcm5FpvZWnVXLg97bgyFyqI/o6SXwzax%202o217zNyGW1Sf21c+UNdojgwKWwfiEREI0zNIGVKAHTTf3Kxsg2yBLIC3CEjw96xhDsGLK6HeQ1Q%20V1+ZyZ2/wB311NHL+8hl4R9+CO+5ElYsfmrpj+PPhr17hM4UXlD985HAIf60X1aejA8Ijk66Bxyd%208833iPUJUt/maBFOZAhq8MK60sxPwlmzoCoJw5v9AlwMc68qV0VIxqFshV0emlE3GpLhK480/dS8%200B+qQmRhevIX4dvmtnLdbqeBdbpxl1+hG4SblFXC3SvLXcuP2EJZo8ErivkNWk3xwSOJb2deC0Hv%20iOLI5ex32u9ev8iYytGBscZIYBi4q1tgcK7G/dOFZAAuXvXUSkwv8HTErZxAOAx6B2A6ByPTMDoN%20m3b7px2aAu3NEFT9x3gnEDjpGEJYuZ/lJkw+D3f8RjoITsIUw7cmA4Ywdf1EaKFtfLkqMaWMrc3C%20haXMPvHD73DrGvmZ9KYpZHKwrRN27hGb6ojSaLe1Qufo28XQZQnnbY0puK8zujnT1KAUqoRivVqc%20XWcy7tfy3kc47E/Dq3vFvg3kqao5qIB0fOGNAtRUgSz7LaCDY8FpNzjuhDOG/LaZXbManH1d1ULq%20dnfiLe1Ngwf3Uj4lDufcq9e5HY0Q0F74iYgAU2nY1w153W/9e9VFTQKODMKxaUgocM4cSOf9I4e3%205d7mzWqEGY2Y7whhuJ+9ZO/rIvd9IR4aUNN1pvG26eC4HL+5amB9Ru/QZ9xUa80xStdmSxsCjZtj%20Rp15+VfSLW38TEaVhGDjQ/T+jyfdJmvWh3OrlsH4lJIryPFIoVT2r75yy7+K6+WtS8Dmfo773XPB%20r5G9f/v/SZ8Md5f53XZWGY1OKdi23/j2viN7j6ksCuKdInivS1G8f5BMIdpYm5dkdv8dgnFTnCXt%20D92Uq42/8Jqdgq7Dhj3+2oG0qO0dbK4aGKgHpZ/apTUlskeZldOKxOpKpubNzIdi02UCFy3yDzyY%207whhW+bshHvXE3LkWCCa4DQj7zksmgstfnE21y8YIE3WGMKluaFRaOlVUxrND2j771NbPqKfSbiX%204LxlzPry9IDAOmbCgcNgOyYQs2z4PXdCgYt+2WuViVkiRoE4RWoViasTbhBqU9ElgkuO37cmEEJE%20f3UnqnCucCnAaJALIeaGmBDkVONe4nMXckVwbS7wbFcvBFRYe4W7Mzp92WxIBSt99hdcS4DuwPYt%20QsOWRLQo846pEYnEOwM0ZI3Ulmu7FT4QHG3gFplyH4jm5dTBjtyCNqOmBsMdIQz3s8IB3mRtbs3O%20YUqZutk8RMqQnlfW5oBbBH1hVqNgTJDRqMlNMhS1WyTLT/YzmAuXgxSA2ha2fTeIIkgCEAb5DJkY%20orlhmh8TjDRlBapYVGTeB8SoPz27RCBAqExIkFIViFip3BXv1xO/eKfeKQT3J550Kq/DptyUmKMy%20N+LyhCPUOmqDI6RcKcwME44c9R9c1+KPrjmzwPVOI3IFIiqOd4ZRCBXLCjtYXfT/DAdlU2a74kWr%20xtRlZzwueb8iYwBOUIMQtmXO4l70Gw4/3gBb71BImQaqXHGOVSr5k6643O+W+GV1lhpHFIPwupXm%20p9/Ko9qZjvmT4PZHwQpBOgs7tpHerZI7LqqMVhHBy03ZX/eDKJRU6nMeJtT7JV6aK164gx/xCiEC%20qbRfgBzvz1Agrle7V/6DVAZtenFPXMId4lhQtnmWs3TIzrToyprynPncsmBFNSyeC2d4s5IIhwfg%20e78UjCOy4p0f1NimRUDjQoBTg5g2aC7QsljMUpZw3v4O+8JFZ3SKgBDGEob7ny3fVXhoK/z6cSgp%20wbAMrVXhwuBUeZIl5ie8Qv3AGKkW8rNj/O9f5w8nh1PNhvu8k/1QyOVh2xG/qnUEKFtQyJPsBCmN%20C4VxanmVe14QdCrYftMlTv1R6yKFoB/ulcqdPKNyr5w5kKcrd+5tlE2ZozA36FfuLOlAtUNqHCnp%20qkEuU5BcaEnAijngnxI872nHqY5eCuRy8PVbYZIJ025wSaMAFpvaVwg2SaG6aOd4idquphsfuhIW%20zKkMIUUIYVvmbIY7g3XLobMHjtocSswaKcoGlWUijRtUdWs1sVok15zDpfBzBZZlQ5kBee7Ohgrr%20lvkj0NMFmMrDdJzn63nZZboDuu03ygXmL7pdyhG7QK0CLZchZ1BiEcklAiNejjPdIMz1V/0QgSr+%20YUkMghgCKQJyxL8fyuQgSP7KSgEBQgIkVKgKQlUEYiH/yJTPAX/OZPe+Gwz6F2NPfgBgEE3BZYvh%20nk5vS5gzZgsGicqCnPc2T08wEIKwrB4WzK+cHFC8rQkhDPezhfqjCQcmIaBAKAz9j5TJtOglr2TI%20KqdBlbMQKYTLobnMcaDzoB+aM+pOXtJ+55ti9omAop5WM16o3HdKiD8k3DChZEBB95MwFoVQCATC%20aeWufr81xPyY9T57dfowZ8lr/6amOsm5SyotGlqZkIAcb9G4/plB0Z+9wJ/fhkjgilBg0JMHNwPu%206eWs5Uhi/s6PvKb7T8Pdy/3uPn+TNBWmx52x7lI+L4XKkmCrQQmkADPDdrbKWn8ZdB8Fw4LWlH+c%20wHxHCMP97OzFfX1wOA9VcUg0wjvf6pW9jssdpzLc0L/1n/pTAnj7+mgZGIGpYbg+4Xfkn519XsJO%20S0tGIpL2gm/NJJWAppWuDssAS59wUvFHMue7uTv7vLfPnzPXMp4cbM9PPAPxnsT7YJVDAnvG9yRJ%20cRyLc/58W0Jspm29oxOc7md3mah/2HjwMKQa/O9cdSlwwolg2cxilcGa/q+GyoVdAvvzMD4Fhg3L%205wNORoYQhvtZ2o8CNNf79+O4z2yqkGdnp/dPKvhDaNgpEpJT7kqMSv+3++6FUyevV64zZpklU89b%201guITC/SD+57dNbsZaoWNIziczfcHW6D93Gy7pIX4sk4tDWBdxJDntXXesa+4pVxNZJUeSk4CQFC%20GO5nC4cnC8+TpDZ5ZuXq91L+TK0gIBahkt9kJ5WJwJj0vFX1mdO0wP59Ow4e2FNdFVp/8dsBXMex%20n1WwV44Bp7UFlD59o+xJ9xWp7CiCf1gIYbifXV6B2XkERqKgKn5x+hzHgFIJBKty/+f/6W0jw2D3%20tJesEVGsZo4B4SAsGg5L4pmXuaSC/cnWH/86EeXWWal9W77ac3TOwEDv2nWvnjP3nFIpQwgVRdF1%20XSJS27QoeZ5jlyhCJg1P7PJXf32OA4GX7CXd7+E0zgTMeIQw3M8SG1bNgYAEN2+BeJUf3CeNLa9W%20nZyGRSm4bi1I8v+p20A55CkLXlFmkySe4LoDzoBo9YXlMw13L71N0/RK8YiquowJgkAo9Ypz6n0m%20PG/pPXdtix7JLqoJ5Fr79h8obNooG0Zx/oLzS6VC70B/S1vrpt/fm2ppWLhssWWeutvD/HnT3roG%20fv4gHBrxJ/g91Y7ynsPMww0XQ1MKx7kjhOF+NpsysGAxXG1AVxFaKw3lP+UwGDgMb768MvbjjG7v%20/GNVTEllboApaKrltglqCI5OeKXzk1MOwwtZwVRWFC4KMqV9Pcd23nLLtZ/+jJfsuUymZBippqbh%20wYEjtz6yJNqcHJocmHYuJ99+LP3jVcu379p912Ob8+0dK2zb2fDz353TMKd+uBhevpCx5x/XEozA%209VfCT+6HOfOBn+zhkuSfBq1dDM1tlWGj2HNHCMP9rKEwOQRbuiAYg2N9pyxIJwx4ZAesX3Em4e79%20eNH0+z+268/3W+1K5d8kNi7MKFVc61RXDEcc7o9zZ5XpwCTRv1uVP28fhtInHnpIP3o0sXbN+GP7%20pe70dCZdk6p9+LbbZjy6eeqCtfSyVzlZY6YcqprROFqTjivqte4/3Nfz/Xnz9vaNBjZs+HVr1aKr%20yUxthO9r11pT1a5zGi+Mwb1PQMH15/s96Y7yDl2mCxv2wcwUqBqGO0IY7me1eFckaKmCTAEc/SS5%20DJWBInUhqIqeSVp59XjZhF3L0uks1M9ko0eEZBOr3hidUUciMzjvFksx+3BHhmcFpjBQed1AYNl0%200Bae5ze5riuHQ337upLDgZmBsHXxa8KxCGXsyr/92wNUqH/gwbGuY5na6n/p/+2H6i9dUNVqOKao%20WAuKr7Eb33jlG1blyoXunz94ScuSHWNdo5N9XrLLsng611Rr4zBVBDt7ksuq/rB9DiqBuprKxWdM%20doQw3M8mBpEENNdWObVfjUeVZ3Ununu6OeP1jbOcqVvnz7jjlHMPPE8QA0+6cy90AgJE5tu5CVJ0%20maZAbTX0WeAKLHWBLVu2IIAuQOlm5o8Vf85o9FKYErL8/PNHhqcSB+11yTm/krrlUIDaIDM2/4Z3%209cyf5216fu8+wbBkQt3KuBzDsUpuKRxKMuYU8rlUSRKitKyR9W+8JqQFbPs0GuQcFs2EztL7Glpf%20xdynj4SiKA4PDxeKhVAwLMvynPinpKCFI9wRwnA/+/kOTK5vX1oV1xg7oTuR0yWXscb2pRPmJtcE%20UTmTglQUwB0S0klnmvo3mpq9Yo1A+nNQ6IKozOU0zR0jNOiveM3KJFimhD7/76CyfP/3b8zdty26%20/I22yFdNRx//2T01a+bNaJsRcPmKyy49fLRrQT+/pHp+tRqyXIdUBjxuHD4QHKYdi+a6thMV5Ols%20pq8BljXW2/rpJjEzIZJsbZm90rGKf/yiJEk2jcmZTDSWUFWFTRO8MRUhDPeXSnfGtQ3HJs8Kd9e1%20vFre+5ZX7ZIzGtjn5bTEyaKtycdgindY7iRddl+VovCpMG9uhcEtfPl4aMvdfPzSLKVQdV90YS5k%20hRghzzXc0AtqxzQjM2bWfmTBUUrH9/ZeFmqvy4d33Hpwz9Lh5LxWMsS9rRZrw9WgscoTecW+SqSa%205gaptc5LdkmUJorZY6nyzEvPI9YLu4zg7Q7b0r198vT2ePvJMb195X92nvwSQgjD/WX8JpFRx+lf%20nRMlCISdpmYYpXzi8nTZ4FqQawQydebh5slc2elo8B/fv6DYlyqndyurJsIg8udoy3jhuerCCwVR%20zBZzP91wY8A1zmtdeHFowU333Hdsw/55yRbBca9OtHFZ4E+NayEibSmpPZ0jfM48K1McMDMLr3tt%20Ihy1LRyxiBCGO3ohvAjWOXdmmZYAC+rgkjWwaTs/2GuCDWtWQ1szTE+7edONmXDVer9Uv7ngGHWg%20D1A++vzvsGWaxLIEBudetv6u/7lnRrC6qaquvaYxJgd3jHYtTrXVhOIFy+/yeJthuvajffv7zOmj%20fc4ic61b0EOqJkuSYzv4NiGE4Y5eMH90YMmf9LEcPd7ngcyUn+PeP4CDaUB2yh9b4lXPjIFZholh%20fz7I02xreCW8Iivz5s8Pvzfw+MDU4aOHLq2dfzg75HC3KhB9oHdXR6IhKClevouMdMn5yaRw9Zuv%20FalAVMk1bduwgmHVdXEpPIQw3NEL5OW4psCcWfDwFhgZh/4hWLUE8kX41R2QqoKpDFyyFrbugp/c%204j9SEGDpPNi357T/CERRUBRJlmcvmk9XiF3dx775/bsuis5KBeNbhzsFKuyf6BvMT86ran6s/0DL%20snlz37w2poY442p1VHJJtm80sSyB4Y7QS6sixF3w14H4i3h0D8DFayCTg7WrYGLaHz+zcA7YDlx4%20LmzfA3Nm+jO5x2Mwpx32HjvdMTlesvf39Nx7441PPPRoyTbHJiYye3rWVM1aUjtzbeP813ScUxeK%20l2xjVcPsnunhGTPaBhtIdTDK/AvEbjAeUVOx8p5+08URiwhh5Y5eIAY8Rqn8UDg7vzQgsyXzIJP1%20J2bxauViye+5H+mBma0wnfHnHGYc+sagvFfuGAoQ6fnjnfuddGd6ZKqpt2egt6iU2eWkLlkVmy7l%20JqzCnqne1kDVtbPONVx7RiQ1WJoKzm7wm0SVZk5AUYWOau2xwcnRiYbaOsfBzjtCWLmj0+YCxKmw%20YiSiOZQTONorP7E/NDDkz7DofVg2BANgGLD/sLCzMzI+CbIGtZPqkmKAn8ZQd85YU319oqNdCgZe%20w2aeC/Xd+bHHhw59fu+th84P66vr24M1vHJDlCJJLUoi89gR01/CqbKgNgOpzjvKKKW+cX9FEoQQ%20hvsropVCqSAIkiSJ3ociS5omKhJX/TVLQal8SJXJgk/jsqdXvNsiUxXX5crPDt3yQPnglmPrXduf%20ZDGdhYYUHO6GJwrf+vXwsUd635kIA6Pcpqd1oxQRxQ2/vXX84U2SIB8sjt41M7uxtbSrnV31mXfP%20X75kwfrV9yqD2UxWoxLjXNW0RZPaoSd2y0GtMjMNJYooCaJgsef6ZaTyMqXKS668fK6Bt0MULSBr%20qqx4TyH581CS4/dIIYSwLfMSPFoKgqyqjILNuGEYeqGg5/KD3T2uoRsT+Vzf4PZxUAJUkrii8UAY%20giEIByr9cVJ5N54z3JjLj47Oz9OrwRXtyOuy2UeoDB2tsPcgCFrNFHkTQPWg9eaxyZ8GhdO9BdYx%20zfVv+Bv21rfd99XvxkeEVe95zxJF874uEcHSzVgoMuddlz947+Nt/fn5gTouCnMTTWObj+xWd8yc%20Pyev57P7+ppAdIKidyh55hVVP6WV40u4gmVCsehPZF8uEEsnjgPZNOvOHTaLD1EKYiCgRsJqJBJN%20xEFTRUMTZdnbjU/2jBBCGO5neUcGgKt0ulCYHjw6vfew3nOMjQzS9LRULoULpgSMuKwqSQ7ma/35%20VGIuaMwxAcJMTLiBBru63W5d6lgOPEfx6n+LeKlnevW2y1hdjb+G9YGjsHopPLhdYJWV7Qix6QuZ%20b8srlgOq6p1VtC6dNTI2FgvHbN2f78XiriiLQ0ND2a6hQDK6eeLIzkOdl7UsbY7WrEt0HHh4aHLH%20JtFky/PK/mipbk6r+4yh7t52GrY/XGfgiDR9VCr3SaxMQReoQyoLSFFR5VXGnSX3Dohwx5Us0NxI%20EFKpYjDipFI1ixckW5tbNOLtUiid4fTICGEmof8bxd+LE2Nw8F5h9726NfjheGkiXlVOFUVSkKko%20JD6YY7qQ/mFcqHMiry2kf6QG1hlKu+VOC86EUH4iwEfB3sdHOe/SnAFuzlVOPWUAOd5JCwIDgapT%20GaCSX7nvPwyUEmDhykOChMALam8wxqxSaekVV80pl+1y+fhvp5Smc9n87TvWuLVMcNfK88V54qaB%20A6ooJwORZckZ/ZnxI2JuzyxWvWZVPBR1njFlmKTywV3yI18LRVgk0uzUL7H0TaqbEyLXFOxx0Z0i%20VZ9KT3414UzIoVVlZXZBCGbNo2Lx4REmMqOX5e4NdguJzFJxaj2dt5QlqioLZON4HIQw3P9yO0+B%20w52w7U41/WggqgjzFlhgjBlFreaTufJOIftLlXCe3xas+kSa3h8SW2z9qOwUqLJaF6vd3H/EWYly%20zV9RWwKIex9c6rUcpj5XbyYZHJirfTYUkjV7qyT7KzoVS5CIw1Qhvyz5BYuFNd4lSeDPLMBPcmgQ%20vZqfEFmWJVl2HOePs1f6y40wFtQ07yuVNfVkL9wLfZl4Dqpbqk3mSIwoghhTgrpjCYROFDIbmwqz%20r76gUdaIy50TJ4P0njToCE1UBA28T5G35Wi1k/lJlNQ5+lZNrHYg6jJ/al+SvTuUaHRIA8vcF/Mq%209JrPT7ljUipXah8qT90XPfhIaEedmVpXOvcqq3UGgIFVPEIY7i9+wT6Vh7u+q6TvCdca8oqPZ6wx%20EWJM+xuj9H7N7JHlDosInEhcf0L1PuLvyVpdcuHOEA2z7M8i8RtyqS9NTv9n3NivEJkfD0TuHQrI%20qfsp3HuMuHL2aNj98sxmGBr3+/WKDGOTsGAWTE4X/6b5/+UL/vMkqmHyxPkUpcqVyhxj467T57rs%20WJeoqbFYPBEOM9u2TBMqQxv9SYApLRVLk52dsaYGr3q/6fBDDZGqVDD+qNmf56ZglFbWz/a2ZMzK%20Vy9qTyhB0zBPvrEEHAKCyJ0hcfrb8eTHMvao6OaoOyVI9Q53gOkEbPD2D40xZ5KyPBXrHLHJyd8Z%20Cqww5VfZwkZeKxOYCORuCvz2TqPx9fmr3mKHZSzhETotOFrmjMjQMwg3fTRCf5vsILIqgitzsc1y%20BkV9u8odYh6RpSaHhhgNePkO+V9FA3Ms6sWZF20aD8y1sjfG3TFRmWPx0yhFjw82EQmUy3CwC1Ys%20hd5RqK72b0bt6YfqBGzeDovmwcAERBOQrIIDR/z7m7zH08oPyoQcs+279dImQ+9x3RQh1r/++2Nv%20u/63N7z7Z1/72sGuLiUUFIUnV+ymgjA6NbH5hz/a9K8/EAJK1eVLNkwcKpVLpfMayEUdc2KNlX4+%20V0AsZHNE9n7J8zSAiMbL29Ti/cGqj2adAYkyL/FB0iA43wzMNgUKco3LSwK3idxmg0uibyiAxKa+%20GfcOjY5OocZu+cf00tWseGP1jz8dHM9iQYLQaRG+cAPuhBd8QDRs+PW/hBs6I4Ewd/3lTImbEWJv%20LZS3aLnbI1Tyx5eHzylT1SSRcuGYW0rD1CFxYr+cd6DocqvWZs12cb9c3BCkjIr+1DF+ae0V7QOu%200yxK5MRktxhPmzxr8LFWvWMB27rTX6Z1eBQOHIZUApYvgC07/AkJvC96VXwuD3X1ML5djuUlmwAT%204H69nOdsqawsUdQ2UWoUxQYqNLu8NZPVdu/dc8+9ezPpGUuXhlTVcRyBUkXVxm12sdmSH52MJGMz%20nUgjCfcFjWBNPNSZrg0lHObGldBYV393eaKmuf4kJxuiePiBB+v6B0RJpowQRsqHFKPEp7eoBRvy%20Op/qEosCK3KnMMwcxzQPAhuG6Pm6QKi+LaAuNwt3hTgjoUtL2kpDXWKZY4LUpUqD6oFJd/l6G0fR%20IIRtmRfjgAjDQwDHVC3Ij3eaicyto7LdLwVmOMZ9liEY6T6h9xtNdrKBJFvk9zRM2SaRQq3zFmWH%20br2g/nd2SSgXSWmaFpqNwrigj4h8QlIKYpAfn3vxxI4KI51BY+yKbFgmK9pY96A/A8Hhbhgeg/NX%20Cb3FC3+6qe6c8x7tPdp/8CisWQEug9EJWP7e0r4jZT1Hxu8JXBRV20XJO0MQmeu4Zon5w1oCRJAl%20pVaJ1blOz89u/un+A9d9+d87mpr279z54Fe+sqBqVdXcc5dCtNBTDIdCAie0ZzR03txDof07dtxr%20COyNc9denpi3edPB3uruWXNnP3u+X+K3mfQSTRPXijpCi63Vutxlqb9NB5MsFOSGzh7Lfqi5/SJT%20n8yOZs2pMatlaHigX9o+GpwqNMdZcE5JWcaYxJxxkZumd+x0KI8EYeqAOpktV0ew+Y4QhvufnQv1%20dUBmmPZRGRS/hvSKbpGTiRujk6KTmdOsnrMisWxZQ+vMaHVCC2giIfv37mWu296xeFzZuKAdBMX1%204488+WzlMkxOwWA37dkp6w9L1CHPurPUq1SDtTwg8nQOQgG/PC/r8LrL4NsbPr5t8mvet+882vup%208y/qUPq8xPdvGJUgb3MW45m98rWhYJVIgfOcVdwgRLYnl0yGmzkhyeLwsukDlxjTKSXUGk/E9h78%207cc/ef0Pvq8EAus+8pHx4cnHD3QNBRKDNTxsTilFu1xF25Qgff2aO+B3kfqqzWPD11jtmQh4r5G5%20z14wibhEDzvwhsyiNbRxBqtKVta5Pt4CrLyyQtY7ODXMXb7MdcpAqbc9DmO2aR/YtXvwwP7egz0x%20qzt8z1C0JxCeYwtvLLC8d24DugWBOWZ13N8jCCEM9z83BloI2q4ojxwMVCmEArE5PyjpidYc76ia%20f+V/NDekwHGYZbmuy0olC8AxDOaHl+laDpiVgHtGegdEaGmAllZ2/pXGWAasLX5L+oRf6EJQ8Ydc%20Dk7A3JlwtNf/4u5OyMBVwF3wotea0Ztdl9X7QmEolSEehf4JKPaIF3UnqsJUYO4Tpv6fLddMzX4D%20hOrBH2vOJzjvLE/c1fX79/XcdqEsxaKR8zuP3PJvX/rAN74uA0znMr+8/WO5a1+95g1XG7qul8qz%20FE30R77wxa1tsiPFHXNQnyytTnXU1lpl41l7yDahbYn99isqExTYlSpbP6Gv5e0Eb1dYhuHaT38j%20qCipmqS6akXo0ksYc/KbrhvfUxzcHzp3RCRlKhAyQZ1FV+v+ZQS8porQ88ELqmfEgBXrnEKDITl0%20irl7LFMnXByXpvcHQ7LoeIFeLjuOw08csM6P34EUrNyCL5xwtPATsOwn4EnfD0GAwRF/Gsi2Ztix%20H2bPhEgIFs6GeNz15wkDv1vf3ka9Y0pTPagq9I34i6zWbIo0h6jA2UbL+P8WfXRq4ccgWAtepWwX%20wS75/9CSubkf+Nqyz95tuyJz66LR2gc2PPi//+tttibKi294y8L15wqmq4FYFY5psqJb1p03/fTg%207f8b3T55kdbeLRZq58xwzZNX0V6q+6+oXHlp7MRyQqvshD95qd7xz9tptmFww9BEaeLxoJqVsmV+%20/7+Gpgco9Q4Ts/WlyxmY+PeHEIb7i9aZqamCxlfpXWWnz7EXKcpqrtXsjdKjmhe3pxo+IskwcEz4%20zfdg22aaLlUy7vTYDJrbINUAR4dg9TmwrxtcEabLYDoSEBGI4r2NmTK1KAxnoOhA+1zou0ddraou%20gV6j+N1Z76Ity6/i76b6eOXwcjx9RaE8eiW7QWqY/1/zP3TQLHFCFsnKsV/cnC6XCCHnXnhRNBTx%20Tj68rPdPQZgXrvar3/f++e95y7Hc8J6JHgUks6S/gNuliH8T73gGHttAb/s+5KaIcKrzRsK93yfs%20C9YdipwrabMspbPo9NjOrCvLAQ1w1WyEsC3zYjJhxWXm/b8pXwFhCtwALiqMSM8VPETk7qRY/J/I%207tsCW1Lm/LcULr3aed72sUuhwZQmb456BWvSgMzjkCyBJELa5uvg31azpH8zEIiBX+zlENREUSLk%20IFiLiqos+/2gX0VmlWa96xzpO1++Zu/RW7d08TcB5CvnEYEOcctXXr9v/I4/7Jz59zePPPLF3H5F%20DdQe6dq3fccFa9caun7CaQfnsqKooVB6164xGP+NC+qO3gWveh+l9LQubRL/oPf7n8j9d3hPIbsl%20XZovnLq0IN6vc2TGHWZwGhLofFd5tDZ//ToHDPzLQwjD/UVlw4wWWPEqu3AbScS8UyD+vBUs50AF%20CGk8rFF3PHDHj5zlFxSSoecZ+OECrwOxcVzilcX2WO54z7zSroHthBw/nHCXqxy87eAyIRM6adEk%2076s9trV1wXVgmhIbJZJXaY+CVYRgpXgvFkU+5r3/kjEKrLi7/fWHtu1dJPEWxjsfe4yvX3ey7eeO%20YdSvXj37issConjPTTfVNze6tn2af2jdg7Dhp4GrhYATcDOc28+5v45flSCVU0viehtLLniHFU96%20m41/eQhhuL/YLHj9e4zbrXTPlmCoJIVt4kTJaexxogM/QM2kKeWmSDLKn3dUn/d9Vzzp0G71xP/0%20O0Lek1sCi3kVNXN3qyk71PQv819brw0fGYVPnPuLvRNPfKfv+96x4OMdH5hX1XN0DP52+R8uLuz+%200v5v7Qg0LnYmo7Jsdx7Ol3WVEP4nk9zYtj13/nx/igJKr/vox72jBOP8NP/QCmM0xoQdgr4QZIEQ%20+/kqfUcnZYvmKS9ErKq3Fq99o+138BFCGO4vOgeSYfjbz+l9vXrfISHXyyEbIO4pJxDw8jYgSaOu%20M2YZsyXZtcn0NGnr4Cdm2tODJM+AV+eWGZOAePU7d+1jkQbQ4oUCBOqirQ25/U7MMJ58dl0nQijW%202pgt81hpjIAS7g63OFMjoiiLk9OFQj4YjZ10WdTjX+Suq0rS8RkLTpbMT92URZ7esvQknUPksuju%20sIxq101IEqXkVHW7dyIkrCkojXrHDNY2z21qqoyQwbHtCGG4/8XynbrQ1gJt7S5IULvHLNknmW7X%20SzpJVfOG0Ts4qBK+TFYVQiYNVkhToCe06S2vPC2BxCuTfKngVI4UfoFsEFZpVYgSMNlPVC88qUUc%202w9QLySp6k9k4D2ywJiX7F7KO8xNK1EIN3zrwJfOOfKfr1u04xc7F+4VPwjxoPec3z/2b48fvfGt%20Szfdtr9jq/130JTKqHGLuyolkq5nSuVEImkz9jxtJoCTXlB1/FbKsxWnqHdq0SCIMUL36kaut2cu%2081f/sAzj2cOKuH+Uuva95pwO2890+8SRlAghDPe/BP7UhLTSScZfe9W6pGkGIeN793Z99etz+gaS%200bjNucO5yGhxkj5d2xI/xbJVVv7qKUUGw+HDW5RawwtqGBftmvVGSCVEgL6jRDscCEige4eBOeXW%20Ds4ZFAw+sUWtdSQv5fcyY6Yo+aPvgTtU8AdFRuuTTro2DGG5CMG2OeZPvANRV+RtkXK+NgJRIe0P%20keTMJaJ3/CCCwEzz/s98piEQdNkZDkwxDEGb2QmXPWOHcChPC95mWZx7B7bzorGxX/7mgcNHW65/%20+6yVK1UglvEn+W1UJnPH+5UQwnB/SREEQdS0XLnctWHDwE9uaj7WW+N9VVEs/uRNrYJLSoUTyl5m%20QctstuoCSxJgqgyPHNTOndYI5U9obOU77aakv2DTXTcL1YeVlEonbDZxXv7qt7qOCYPTsH1PcLXu%20ld0kJ9kmuNwGkdCwVQDXBkl+tPSu9P7tu/irwCr8/Xm3Go708W3XbXOvt/c/ss9aDWHFOxAErbxM%20/FtjHcZWdfc3UnrGy13bZTJQXTxhMIwX7lkSZX6zhlUyv0aWE9t3ju3a8/B559S/4XUzly8PBoOC%20IOBfDkIY7i/FIt6LbVmRXVGYmJg8dudd2TvvSnQeXklFL9b/mJVe6LllOlxbft3l5rOKfdfxktFv%20r3ifvbrZrRT03uHA0f2vcMfPatfve4BL/H9bJXAt/4YkXrku6zLQwjxLXWecS1RsLI9tt0sgSIWq%20Vz3uXAoJCUY7g0pZEkUoTBr16x63zwN/+WsTHLOxNOz9iPckhssVrtle0Kt+5c5N4j+1dy6g8sp/%200idHmlNOKrMvcIv4G+Q9QOHHT0QYI1wonfDCGCx/rf7gDq3DVEH1r8L6e0PTGr2TmEc3j295fOPi%20hbWvv47U14nBgCDinyVCGO4voVodqCowWe7u6em5517rgQerh0bmShJogWeWwCInuSKMzixc/bn8%20zI4/czeZcX/ymXKNXRqGqCotKo/8LtsDNQvBMYAEOuybP7jue7ZlcWZ9a9313znwsT7pNcAMEGTI%209i0q9BNJ0k2gs8wZV5l2v5T/fdiL9cCasrrMMDuV0sNBsEnoqoLSbnmhbh5RiveGgHBtqRFYo9uD%20YvEhf4mok18ONmHpSm5/Kf3wl6MtE8FA0DtO+QcGxyvlA4EGzuv27JvevWeoNmWfs7rl4ovrm5uJ%20SvAeO4Qw3M8q2f/ITcOhJ0oDP/inxOF9NflCWFXdUMg9IfyBWNDPHO2a/A3vM6riL8p1QglI9UJn%20ZIsTJuICcFr67u+vXVo5rSAhMp2KW3W1/nic4WErCGnglaa/oFT3P7iclV0SGbOdcIoFazhbbhCv%20chcgcmWJBnlwvS7PsNysEL665OU4Ebm2whSirveP0OVlMckqI9KhcGeIaKcYLlSGVSt53Xezf/hP%20M7Mp2qiAKz45St+PeFWtAqiZzuRvv2PqkU2Pt3cYa6ExCcGIf2DAzjtCGO5/WZIf693HYNvdyvjG%20QGRCWkyeEGTZi/VnxpGXe6LrTulOf5Pwqg9OnXcB91L+RRoBYlswbzFsTeizSpGgHHzdyEPfGrsU%20UkvA0Xcbb7rhV7EPLvmhy+h/7X+/WX8pUB0EDaaPvLb/7oQcZC7prdIXJ4X8Rin0Fjtwju6PalS4%20W/ROSkBbbjKdeP+pb1epyiNthcB5ulfaE4W5BRCiIFa7nBPyHLOtl6EpBe/7kv7g3dbj/13dMaVH%20NdkRhOM/UBnOLwZFMazrTTt2TO+M/uhWtfHi0urL7MbmyvVVB//gEMJw/wsIwtAQbPilmtkQqirI%20M1QCGnNBcE6MdcF2io7dFYsmPvT+GY2Hzl3yc6LDi7fchONCUw3su6jc/+tAS1S4SIB9u7714Nqv%20QSgFWiAYFqukMuMQCEumGvcHchq5c3Z84ypi2jQwXnTdxeaCax3b1a0eaerrSc4h8e5sYJ2u71DS%2034+7BVr10XTk2oIf1I9rU19LBi8pJf8uAwyMg1LhvuDxJQOfi+WvErV2vTtQfX22Wxy75eb6yalw%20IOAKwvEq3vvMKAVNrfEOLGPB7I+13/zerLuyeMkbraoEjolECMP9xW/FPPKAsOO70boptS0Aboi7%20zwhsv9XBOTOtjGNPNjYUz10VX7165fmXjO3qZSWgyou7aY4BF17j/mZToWEqTlX1g+aos+nTjyz/%20BNStmA6sv224jwHNBM4HWYKJI6t2fuPj5R4ihwiDx6G8cl9s5KPU4X7KcuZfTc3+MqKuMHK3Rpxp%20gQZZ+r/i3mvz54rJU221nvxwpnBnyPtH8b6gPSDR0GmMnuTg7YRkODL3g9f3XbbuyG9vH7n3vprx%20yaisEEV2nzrw+ftT4lEJ4rqa+bl60yOliz+ZX7aU43y/CGG4v4jdmMEReOIbsbmG6obYM0t1v7Fu%20O7ppTCpyaeH82BWXLb9w3fjIqGsYZsErjF1CXvSts12oj8Gy95Yf/Zp0CQuBHPyEPb54y6d/V3fB%20QNP6ncpb/ZGYZm/dkZ+9evjhK4ntJbvgkg12af4nC7O2iumNmvd3QRXGOZFn2PH3ZanEkx9Op38U%20Mw8p/hQzRcGfRn6uVf2ZdPGBYOan0cC55UrJfXxwz2ltpOu4VqHQUJNq/NhHR974hu4HN4ze90Cs%20u6fKdRVZcQT6dCEv8GgYIiOhDV8nM3+QjQbwVlWEMNxfJBxkGUKBys1IT5Xq1CWOzSa5nm2oF9ac%20V3/xRcvnz/cvqxrGULnbi0Tyl9o6f4YZHdathh0XFP5wF70qoXFRvVxga8c29I1sGBU0r/BOufoM%20ysJS4P9n706grKrOfIF/+wz3nDtPNVMDVQwi4ABEFAc0oHEgOEVj1KfmpRONaZ/Jet2d5C372Zos%20zUunu1/a2NptTGt8iTFR2yHOIyiiKIiAgAhVQA1Qt6ruUPeee4Z7hv3OqcLXimAQGfJc/9+qVQur%207r11alvrf767zz7ftlmYufSyo3syP74Wka8rmrVgTY+1TvU0JmbdUIc98k/p7PUleYJrrmHBpdQT%20DG6w7PVFc7VSui8RP0sT67zw8WZtq+zslEn8FFNOjm2TbTfX1U246krtqxevfP6FVc+/kHjvvabi%20aEIIizLzBD72LoIEiceiXJIJG6gCINwPGpcyGRJbbLcQZiKXOCtVaTSrFyfK9efdOOekeZlMRnAc%2027IsLWhjyPbUhOsQ1O+To+IwsUd0bZ6iThBkVY5NZzSDj61elyN+xHseDVW9N0L6EdeXj3mpbvC2%20WH3SqfthgclU+WO0cGcqSFKRxDqXjaUqt1j8Yi11RYXXyN4qj/xjWqx3098c1V8Nh2db3tl6/s6U%20EPnUv+l4xMcVpeuomcmONsswq73bdj71D4mtSrqixKPBRoM1h8IddjSKaXcAhPvBrNxlv3Jvd9w1%20QW+YDSGz6+valxbVesoT7M4FqYhoa4e/NW1wo5BHfqyXFWe5ZQqycYStZlwxKgmCynXXG3Hc/ljN%20m2HNrYRPOIV6nyeSuZjxy3NFey5a9zcFNy9Wl4WNVWr6G2VrfcjaGPKL9NTllfxtKWW6FT7GCm5r%20CrrYkPZiVGp0iH2mE1iwE6FperrRmK2LdkxsmfmTKNeWPKK890xsCik2p9REByvfARDuB33uo6HT%202eA6xZrjyd6Rp9qNndSzwqvphquE/3wO0+S8RZTmU2TD+UORKZXtG8XBrYL5djgtCmFLnHWad/S1%20lpNzqmXmBW0Xmb48nPhKxRmQuBWcHux+ufjLpDLVKt2XtDaFQhNtbpP/OTLXrC6NeIYgxLhbFrLX%20FYWEa65TGDsAb1CC6XjDYBa1z6KuQXvTE95az0owsWuii22YABDuB31mJt7mbHZrC+KqqIlLbndm%20/lxj7M/xSB1OlkdNCXbGfPJOcVesdofXpo5SQ47KnWXKEJPS3yqN3FRnb5OZ6pUfjgtRL3qywQ1B%20nWZVIh4b/xuROAtxZUaw1D081zDeUov3JoO9pQrC8K11jT8erjwWLz8aH29RcECIApnD9Obt8RN5%20VJPcl0lf1OriUioAwv0gs2nqFN55pGtvFpSIR93q0KAmHfy2V0wgzvan4bvrBldZuR+PVrDKscb9%20EpzzGrMHRc9kzpAYvK7A/b+I0m+So/cnpWan6afDmWtL2sPRMCPJovAVo7Ez9Nz/rLM2hnatihGD%20k5wzLHo6Cz6bTIgesHCXZOrdRupOhWSvVhGmn+C0teA+JoB9hSnM/a/cswn6Lz8rj8wvlI1ghQjn%20n2GXjX2vZ6X9mZlgH3Rf3w336/I6V4hwIe55NcZNJtU76lGWMt3iHg39OJuYp4cuM5cV2quLWN25%202vBPM+6IqMy01JmW3Or4j/cswa/0/UwXswe4qA6O2Qs2rho2ee2CkStvrqoSdscGQOV+SIr3pgxd%208XfGr78t+1VvYyNtHTnoP5Pv1yP8itz9WHsWv2wPzzJTl5ednJj9y2Lx31NeRUhdNaoebfnf4hbL%20/ziz48HMzacvWDXSVT+lcMuTz7Vur9bfkBezjh+9dq9c+Nc0E3nqylFPY/FzNGdI0peFx1tFHoDR%20daitg4qxWmZa7es/sOQaOswAINwPGYuSMYosqHZN4KQQP+xLsIOpEs727f0Yt1n4ONMtiSM/Tzf9%20dLj+xhE/0IUYL/170hkSs98ttt4ysmp4wqrhLkGyhosN62Y0n/ilFZpExTvS/tPT3yk2/GjY/1ks%20zHPfr09eXImeZOivHLCLya5LkQxNuqIsKFwmJDsAwv0Q0+iSxW6w/tr8zBMRn3lWZ3xTPmHfbhNl%20MtffUMPHGQ03jth9UvGepKcJ6W+Mpq4YDSr3Guu/JVs/zfzC2d0rC1316aGZrw/23pZN/rCUvrq4%20q3K/I+X/w3983Q/zTODFX6UO8DyfQeef65o6YWtsAIT7YRAPj90Q/5nH0vXG9pRmn+0mzH1+Lgtx%208x219Ntk9i+LQzfV2wNBI18/4uVGN9gVpCT6bwJaLhm5deOzW7KZxv5q57n5gQ3Z4Z9kpXrX/2Xd%20gmD3ydxj+Z9nWm7PlR+PVV+JCPEDOinOSfIoFsZUO8CnhguqB4J3gO6JH99x+hAeuJ/vfqAHJ/kG%20R4h4TOFOTjJWK/5nP98bbsxXN6rmPZF56b7wI1RcEm3427wQ9eydkrlW8St3//GC6kmNbtAZWKQD%20Ndv+oeMbGxMkOwAq9/+vHeIZe26y6Gl6+qqSMyjW/SA/fEuwxpG7LHlxOXlJhVtU6wnl/3daSHim%20QI7I9LtSYsJt+NEIk0l7Llq8O8lrTJ7gNPztiFcR4osr3GblR2MHcKk7AKBy/1z8z2CHNuI5CWEe%20XFD9WYYJ5FfuflgnFmnJiyul3yacIclPf24FncL8Rwbr6x3ydMHThOI9yeiCavLSMndYUPtHeP72%209Hi/X+6xw3OmAgBU7gd1nkOUZEmSPe8jZ01RlBjz/K8LgrjXFTU8WMMujq0SCXofHrxDFD4IXkau%20JkiNXnxxlanBohc/rKUWxy0LXlmQGlxrfdB43q/HKUj2ILWdIVFMeuSQs1OSW51gG6aI5xfy0TOq%20codrrNz1W/u/I/tT93OJgihLIcb/szu7NDZ0/liJkv8h4wwBgHD/c3kXxAV3JDfgWYrnfWSeuFQY%208r8yNNhvGGUhtPfMkikkkmmRetDCXRBoeJQKNU9Ug9Uy1sZQ5Ylo4iKt/HDUXKMIqudX4mLcy1xb%20qr4SLt6dlCY46W+VhCj3PxfvTo0+kBAiPH3NKNXIHRH9wr+2JVS6L5H6ell7JqKvUAUl6Gxc46Qk%20g/1X93qCCVGlUhjc2es5+ofCXSqMDI6OjrqOpSih9hAnhr8qAIT74U52q0KFwlDuvUtHPj7XNVbJ%209w8KYcXuG6KO5r1sNyFSXKFSmTLJgzgVkxut12Mxcg0SmVcSS/cnwnMNryw6A1LmumJsoT50S8bN%20S25B8M9BUr2rzqwVfplMX1WW22zr/dDow/HqsrB/Dmi4MZ/5b8XhW7N+Oe/mWfH/JPnYDqv+0zTu%20Zdo+qVFAb46sHb/Y1H/Hbqs/OfefzvUc0zgNtteOaAreZ6B+B0C4H85wz5dpdR9vbDK49/HQDuZA%20/CAbGqW1PdTRupdw59ReT6uHaOrEgzQj49fLFEnNl2bZxuuvsHCYJD9KBeMtNX5+RTnSUo+yRv45%20bawMspuJfFfLMD9b7V27XjM/uT2y+2T/KyN/n6n760LjLUNyq2OuVbnGWDiYnReJFWR71lRvr02+%20BHrzfapKtVh4D7d9ja8E9YfwjS103BQKbiBAuAMg3A9juNfVUUcDdU0hvpele5JIvTuoPUGkjN1v%20+fHMsunIDnpxY7Dg/WCQpeAAWlpOM08Zzb3yYmsk4nhcUDw/ncUkj5xometl/fWwEPF2zYcI5ORF%20a30o/e2SvU22+8euCbBgPofkYI28uT4UPdniNXKLTnA1dWx23rOZ3mJOm0J73uzUf+UwTWqmpECN%202b3+pi6nnYyiqbGzIJZCAiDcDw+R+vvpD0tJytDOXHBFdM91Mwuy7JHXqVCk02btacLBo3Q9ZVXq%20HyQ1fhAOU6DNvY3zzpxjdVVfTSU7bNcRBD+OxZTHxGAxzHitzU0W7LskBUvgnZ1S/o50098PFe9O%201TbLQW1OY3tX22Px77LgWWOvEOS+TSKjQcNrmmemU8G9ux9PdtumZ5+lVX00bVpwptnroYo0UKE7%20/0AXnUr1WWyaCrAfBScciFF8YzM1TqXJE0lVKBrZ80ckTIkYzT2e1hdopLSXsXfp1KNp3XqS5b2d%20IfZzksJ/3zAwSJ56XnNztqOtjU5fMFzVRMFPZ1b6TcJcJ7sjgljvyW12ZJ4hNjpeVQgWw4gULIX0%20S3kx6AYcNAuuCkLCi5xsSG221Oy4RWZtkku/TnhacJ6QXOH9mL7gHGfPZbt/FhyirSbNnbvXURr/%208IdxxhGkNNPbPUQi/sIAULkfFh5Fw9TcQuHQn+4dJslkaHt/mE0zptLLa6i7b8/5LsjkfcpJaE5c%209N81OO6Kdc3zF/yFwDzbchZec80zLy9daJhuSDLXK+ZN9WLCy15XbLx5hCncqzLtmWh1adQZFoMi%20nQfnAD/rhaQXObMaX6RJWc+tMmdIyt1Q7/qP8YIF7zJjPRWn/mvazMlE1b0cDaPWRmqpJ+dPdWb3%2031QoCglFzLkDoHI/XEMokyiTIn3oQw6iWRCDuRdp7D//81tisN6RQmNPZHsu3i/5Iq1+m2yLCWz3%20nP7k5mJs16N2f+WIzN9cLSp1123Y8PYTj/7usd/dsWLZq+rll260LIXT+OVTtyjkbw86f5Ufi5Uf%20iqeu1NTZplcWlKk1IeaFptY8XQhNtjPXlKtLosV7E0KUF/4l7ewIJuL9V/AP1TJoQ0flqqtcsvZy%20cP4j5WAEdhsrcWyg/OEK7TaMYnAyCyoQrIkEQOV+qNUol2NLNzbyHWFJHGvLKDDmmjFnsDnB/dgq%20VSlnJbiacb3g0qAsUm6Qq7WhhTOMYM37x2PLofoGuvB4uuNBZ55ATPzoRAz/5CKduLB7V8gQsR69%202HLst+objnj10V9c8MXJtaS7c2h1ufXk3AXnxx58qC2ZshhncnATk90rRU/VzdWqV6bEBZXwLDM0%20pRa0frysHJ5tyC2up5OYdSLzas5OkZvBiY3GdoYSbeFpoXL5D/Wm9J6aOLLg/Y0zSis3xZYM1DXs%20DNq1+7W5/8uJxnBLVI+pVHNoYFQ0lWaPSd7YaUw3WdrWjmkaTsYwOQOAcD9kFFq+JnrlU1fvcI4w%20jAZGpaQalKxlK+S5KYGGm6JbVdEZ1Ot1exIJtUhIi8he2RJrTvLOHje7pPfS1kduu3TFHvqOGfTF%2046h0Q/WJH0vnuXFx33ukj/Vz90Pz/037qEQ9peKOC847efGXtfUP3fXTr95x8yNrn3jnpif+auuW%207qWzp2+pnk1PPtWeSpn+sww2fGtdbGE1eppe+FXKf7XIXENM+KFPfp3OJCo/HvM0IXFhRV8R1p6K%20edWgOYHoh3tNeLymfenG8vw5e76O6r8d+dp9ZzxX+FJRbyfXVbeUYzLXaoJpJ8hjCWVzvVrU7HBO%209wcqIYqlpGI7nj+SYWKJn2zZ0Smte/jiu6dMdNHVHQDhfvAxKuqh7soxk5vpKyeVzjy2IRUL7tcv%20V2svvjv80Fq5pzLb4UI2bS5qL351bnZiY70kCjXbfXd78bdvai/1TdtSnLDXSrxKF5xFkjz62I94%20TBf2455VP+Il7r6jjzpXXnzZ/7hh2ZN/+NqCruG8Pvzixll5c+nz6y65duF796w86rvfWxJRRh96%20dGY0asuSVwumZSpPR4NJdodVX46k/6IUOcEw31UKd6Y9XfDT3HhL5bWxFTUiVxkrVukFZfS8m7Xz%20z9hTsn9w1tlU7DTYpMXT85cdn5rc0uUPhe24m/pHf/dm6fUdndvsIxXVmd2kXTLLOGnahGhY9jgf%20GTUeXzn06KbUhuGjqpZIDItmABDuh4BLdTH25HcS7U2J9b3FX7862F0ISubODJ01M/6745OmzR2X%20R5VEqWo9syZ/1yuFSk3Ihr2TJyk/+coEMZTY8rbsh6mwt+Cu0OIF1N5YvumfxLq1dNb8YA3Jvsw+%20+7Eelmm0SO9XY5Nu+P65l18oeZ7jWJFwPF+2FMcL++cYzSQmqCGSbfuKG298curUl//1rmNL5Uw0%20ZqvBMnMW4hQKbkoq3ZMqPzS+GIYLUW88qQU1uHzq2cIqrdY7vXzd9605M/ae7ES6RX+zUJkxu17T%205GfX5u9dPjpqUUrlJ3aGbljcooYkveYpEpOE5FvdxX9+bmCgTLJA0xrYOUenrz0zvanbCXFcWQVA%20uB8aAhk17x+e2Tlgld7fGSIvTqEg+17rFn/zlj2psX9mI1Nltr3gvrNDNvVIkJUi98vhJ9dS+uXc%209MbSCWr1klmf+CM0OmYa3f9z955H6K776IR5wSKTsMCUDy6Fs7EbX8dnvaVgvaIneN5InlZ1y4Pa%206Rd9+7vHTD9Sr5RDIaW18+gXXn1+8aKjhc66vmHt9OO6Rrf07SzHj21tkTx+2X/9xvpTTnnl3+6S%20XnhpUtnIqoogy54f34y4zIOCXQw6vfg/VGQkMaFq8bWGva1BP/Yq/XsX8WC7Eu0TZ7BkenHD6C/e%207V03UKtWIyTvGopn3mU/WzI8u8VpTohl01szSAMjEWJxkoM1QUs3Cb98Q58xodwsDP3jfLSaAUC4%20H6ppGb3GXl4fkTLi2dOqF8xOtmUj/pcHCsZj72jPblG6h9TgQaI9rU6/dCEd05EMK2JZt1/bVHxg%20DX9tUyzRJAfXCT/5DkyDwhJ95woa3E6PLaclK3hU17/gRVTHc2xu18itkWVRWTe2V92RSLhX7RK7%20T5wxfdEpk6c8+NBvbnvi90oiFvHYUU3tIa3NfmqbObPl7ao2p+z+6slSrOnIPz7/TNnUo4rS0dJ6%20zn//Xu7yS9c//czG5W/E+wfShhHjpDBhfIkOFwRbUvpr7L2a5k00T/xy7Udn86bG4AiDj08kCrSq%20V1ljhrvqtcvns9ldyUhI1Eznze7S/audpT0x8kRiXixsXP4F7cyjUg3JiOvx7sHqg2/rr/Yl1pUj%20zsmIdoBPk098GQZhf4XotTWpdfSLYybXea7zVk+5Z9jxOO+sk+Z2JSRJ7C9YNcdrSIYyEem9Hdra%20PqNsUV2UfWFitLUuMjAq7dxw5zUn/Edwht2XCQcp+IlGif64gv74Srw4Oj3b2XLEEYoi2aYlGYVs%2044SO+imTOtomJiJxz6t5nrt1S/cND/96Q5NITfVUMdqL3oXZKSp3nl352jcXXfLAplVvSGU7Igd9%20CfLF5Dt9f3fuZYvOXWxzXqhU+rdtG+ru1voHvPKoyAXLEXMVI1fZFo28e87J5cUnUzw5tm2ssy9/%20ZWQadNfKq6cefVFDzN08qL2zXS+ZlI7Q7PZIV2MsV67lK7WIIrZm1Iphv9Vd6Ss5ssimNYZmdcZt%20Lr+zseeLyetnTLFxQRUA4X5owj394I7/1V+Vnn1f0bQMCWMh7bFItHT6JG1Wu6rIYu+I9dxm3jNU%20T1zyi1PiIonGnNb8SZMSbdb9f73wMfpUjQ+FoDeLH6nb+4WVW9p7q/OU+lPbOo9t62iKhiXumJap%2027afz8ErKopilbV7n3rsodz7uYTMJSb0DU/eYVS4kxblzZ0ZKRnlHg9b7jwlc+2CL3d2dZqWxRiT%20ZVlRw0xSNdPbMZgb2P6OPrS0RV5+XEdvZ5sbLH80Pk3LF0Y1k25d8o0R9fSX3tc37qwjHhobCoEE%20a+aE/MLJYnMqVDacN7fXlvYkbDNBgktB82DKJkfOOZLXCcVvTv3B9Mk1hDsAwv3gU+nJ1zJf/v3d%20FBOnppd/bdKL0+t2MuKb8k2/7zltff4k4tGxx7mxcPdFHU+dMuG9pGrmqvGnt816euAsV598VuMd%20T3/vgf3ZgnVsip1EqpWpu5827Ejs0Ge64TmxuqOzjZ2ZTF0sqoYkP6VdQWCqKOYGdvT092mmkUmn%20/+Ol55Z3b7z3r270Y92yTJfzZDTW0trqSpJlObZDVd0qFAv53Nby8DpBX9kcXje9pTS5lZTkWKDb%20+3W0Dh37s+vXVC9UoxsuaH96Qdv6TFgf0aPP9x79eN/ZtVorjZ/ixNG59Uu+0vlaZzpvu8LbuY4H%20es4cqBxH1dzqq68+9sjanrsaAADC/UCSqKdffmxd5zHNgydOLqvpD1LPL1RH6Y3NsbVDrZYrt8aH%2053flmicEzXCDBwSbWdCmrdKSre31Ee3C44c+U9fDD1KeTMoXaXuOeguJYaPdoC5Su0KxtkisMRxN%20R2PJaDSqhPxSPvTKa8v8wnzOrNk123Ycx65ZerVSKef1Ss7S+rixVeXd9er2tmxpYsNY0y51fzP9%20wwfp0X3LJxATTuscaG/3ds1EseBlt/YKy7ZPyFXTMVmf09w/Z5IpxD74LqfyML26Jbt5JH3ZcT0N%20WQ8dxAAQ7ofEeCOB8ezzPjp5In9o2aLz0bnp8UQe68O15zv19/tgxF13DDkGlSpUqFBRo7KharWo%206UZrrup6oWC+xT8XWKbAaiHBVEQ9FqomwkY6yjNxSsdJjtCu8HUPaDtGdfxtDO0+tSJ/6O5T/rGR%20FD8YSQu9fwEQ7sDGTjDCh7oHja8T3+0MxD50BvI++MBycoDPw8wCfC7tS92NKQ6Azy90hQQAQLgD%20AADCHQAAEO4AAIBwBwAAhDsAAMIdAAAQ7gAAgHAHAACEOwAAINwBABDuGAIAAIQ7AAAg3AEAAOEO%20AAAIdwAA2DOJFAwCAMDnLtyr60MYBQCAzxm2PNKOUQAA+JzBnDsAwOeQRAyDAACAyh0AABDuAACA%20cAcAAIQ7AAAg3AEAEO4AAIBwBwAAhDsAACDcAQAA4Q4AgHAHAACEOwAAINwBAADhDgAACHcAAEC4%20AwAg3AEAAOEOAAAIdwAAQLgDAADCHQAA4Q4AAAh3AABAuAMAAMIdAAAQ7gAAgHAHAEC4AwAAwh0A%20ABDuAACAcAcAAIQ7AADCHQAAEO4AAIBwBwAAhDsAACDcAQAA4Q4AgHAHAACEOwAAINwBAADhDgAA%20CHcAAIQ7AAAg3AEAAOEOAAAIdwAAQLgDAADCHQAA4Q4AAAh3AABAuAMAAMIdAAAQ7gAACHcAAEC4%20AwAAwh0AABDuAACAcAcAAIQ7AADCHQAAEO4AAIBwBwAAhDsAACDcAQAQ7gAAgHAHAACEOwAAINwB%20AADhDgAACHcAAIQ7AAAg3AEAAOEOAAAIdwAAQLgDACDcAQAA4Q4AAAh3AABAuAMAwGfxfwUYAG7w%20Fs0d7AWDAAAAAElFTkSuQmCC" height="333" width="500" overflow="visible"> </image>
    </svg>
    </a></div>
  <div class="toctitle">Revista Ciencias Técnicas Agropecuarias Vol. 31, No. 3, July-September, 2022, ISSN:&nbsp;2071-0054</div>
  <div class="toctitle2"><img src="data:image/png;base64,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" id="codigo" alt="Código QR" height="85" width="85"><script>
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  <div class="toctitle2"><b>CU-ID:</b>&nbsp;<a target="_blank" href="https://cu-id.com/2177/v31n3e09">https://cu-id.com/2177/v31n3e09</a></div>
  <div class="toctitle2"><b>ORIGINAL ARTICLE</b></div>
  <h1>Evaluation of Azutecnia Horizontal Probe in Sugarcane Sampling</h1>
  <div>&nbsp;</div>
  <div>
    <p><sup><a href="https://orcid.org/0000-0002-4109-8775" rel="license"><span class="orcid">iD</span></a></sup>Yoel Betancourt Rodríguez<span class="tooltip"><a href="#aff1"><sup>I</sup></a><span class="tooltip-content">Instituto de Investigaciones de la Caña de Azúcar-INICA Villa Clara. Ranchuelo, Villa Clara, Cuba. </span></span><span class="tooltip"><a href="#c1"><sup>*</sup></a><span class="tooltip-content">✉:<a href="mailto:yoel.betancourt@nauta.cu">yoel.betancourt@nauta.cu</a><a href="mailto:yoelbr15@gmail.com">yoelbr15@gmail.com</a></span></span></p>
    <p><sup><a href="https://orcid.org/0000-0003-4266-7754" rel="license"><span class="orcid">iD</span></a></sup>Jorge Luis Ponce Salazar<span class="tooltip"><a href="#aff1"><sup>I</sup></a><span class="tooltip-content">Instituto de Investigaciones de la Caña de Azúcar-INICA Villa Clara. Ranchuelo, Villa Clara, Cuba. </span></span></p>
    <p><sup><a href="https://orcid.org/0000-0001-5053-9416" rel="license"><span class="orcid">iD</span></a></sup>Yasiel Caballero Jiménez<span class="tooltip"><a href="#aff2"><sup>II</sup></a><span class="tooltip-content">Universidad Central “Marta Abreu” de las Villas. Santa Clara, Villa Clara, Cuba.</span></span></p>
    <p><sup><a href="https://orcid.org/0000-0002-7710-2158" rel="license"><span class="orcid">iD</span></a></sup>Yoel José Moya Pentón<span class="tooltip"><a href="#aff1"><sup>I</sup></a><span class="tooltip-content">Instituto de Investigaciones de la Caña de Azúcar-INICA Villa Clara. Ranchuelo, Villa Clara, Cuba. </span></span></p>
    <p><sup><a href="https://orcid.org/0000-0002-5150-5859" rel="license"><span class="orcid">iD</span></a></sup>José Ramón Gómez Pérez<span class="tooltip"><a href="#aff1"><sup>I</sup></a><span class="tooltip-content">Instituto de Investigaciones de la Caña de Azúcar-INICA Villa Clara. Ranchuelo, Villa Clara, Cuba. </span></span></p>
    <br>
    <p id="aff1"><span class="aff"><sup>I</sup>Instituto de Investigaciones de la Caña de Azúcar-INICA Villa Clara. Ranchuelo, Villa Clara, Cuba. </span></p>
    <p id="aff2"><span class="aff"><sup>II</sup>Universidad Central “Marta Abreu” de las Villas. Santa Clara, Villa Clara, Cuba.</span></p>
  </div>
  <div>&nbsp;</div>
  <p id="c1"> <sup>*</sup>Author for correspondence, Yoel Betancourt Rodríguez, e-mail: <a href="mailto:yoel.betancourt@nauta.cu">yoel.betancourt@nauta.cu</a>; <a href="mailto:yoelbr15@gmail.com">yoelbr15@gmail.com</a> </p>
  <div class="titleabstract | box">ABSTRACT</div>
  <div class="box1">
    <p>Improving
      the sugarcane payment to the sugarcane grower, in a differentiated way,
      according to the quality of the raw material, demanded the design by 
      the national industry of the AZUTECNIA Horizontal Sampling Probe, as 
      part of the kit of equipment for that purposes. The objective of the 
      research was to determine the fulfillment of the quality of work and the
      technological and exploitation indices of the probe in the sampling of 
      sugarcane to be ground in the mill under the conditions of the Cuban 
      sugar agroindustry. The research was carried out in the laboratory of 
      “Panchito Gómez Toro” Agro-Industrial Sugar Company, in Villa Clara 
      Province. The standards and evaluation procedures for agricultural 
      machines established by the Institute of Agricultural Engineering in 
      Cuba were taken into account. The results showed that the quality of 
      work was satisfactory, as it complied with the sample weight of 15 kg 
      demanded by the laboratory in cane harvested with strange matter less 
      than 12%. The operating system with the working organ active for a short
      period influenced the marked decrease in the productivity of operating,
      productive and exploitation time, as well as the exploitation 
      coefficients associated with them; however, there is no difficulty in 
      guaranteeing the established 16 daily samples. It showed adequate 
      reliability, with a technical safety coefficient greater than 70%, and 
      average fuel costs based on the number of samples and their weight of 
      0.053 L/sample and 0.004 L/kg, respectively.</p>
    <div class="titlekwd"><i>Keywords</i>:&nbsp; </div>
    <div class="kwd">Sugarcane Sampling, Pay for Quality, Probe Sampler</div>
  </div>
  <div class="box2">
    <p class="history">Received: 13/8/2021; Accepted: 24/6/2022</p>
    <p><i>Yoel Betancourt Rodríguez,</i> Dr., Investigador Titular, Instituto de Investigaciones de la Caña de 
      Azúcar-INICA Villa Clara. Autopista nacional km 246, Ranchuelo, Villa 
      Clara. Profesor Titular adjunto a la UCLV, Cuba. e-mail: <a href="mailto:yoel.betancourt@nauta.cu">yoel.betancourt@nauta.cu</a>; <a href="mailto:yoelbr15@gmail.com">yoelbr15@gmail.com</a> </p>
    <p><i>Jorge Luis Ponce Salazar,</i> Ingeniero Agropecuario, 
      Especialista. Instituto de Investigaciones de la Caña de Azúcar (INICA),
      INICA Villa Clara, Cuba. E-mail: <a href="mailto:jorge.ponce@inicavc.azcuba.cu">jorge.ponce@inicavc.azcuba.cu</a> </p>
    <p><i>Yasiel Caballero Jiménez,</i> Ingeniero Agrícola. Universidad Central “Marta Abreu” de las Villas. e-mail: <a href="mailto:yasielc16@gmail.com">yasielc16@gmail.com</a> </p>
    <p><i>Yoel José Moya Pentón,</i> Técnico en Mecanización Agrícola. Instituto de Investigaciones de la Caña de Azúcar (INICA), INICA Villa Clara, Cuba, e-mail: <a href="mailto:yoeljmp00@gmail.com">yoeljmp00@gmail.com</a> </p>
    <p><i>José Ramón Gómez Pérez</i>, Ingeniero Agrónomo, Instituto de Investigaciones de la Caña de Azúcar (INICA), INICA Villa Clara, Cuba. e-mail: <a href="mailto:joseramon.gomez@inicavc.azcuba.cu">joseramon.gomez@inicavc.azcuba.cu</a> </p>
    <p><b>AUTHOR CONTRIBUTIONS: Conceptualization:</b> Y. Betancourt. Data curation: Y. Betancourt, J. L. Ponce. <b>Formal analysis:</b> Y. Betancourt, J. L. Ponce, J. R. Gómez, <b>Investigation:</b> Y. Betancourt, J. L. <i>Ponce</i>, J. R. Gómez, Y. Caballero, Y. Moya. Methodology: Y. Betancourt, J. L. Ponce. <b>Supervision:</b> Y. Betancourt. Validation: Y. Betancourt, J. L. Ponce, J. R. Gómez, Y. Caballero, Y. Moya. <b>Roles/Writing, original draft:</b> Y. Betancourt. <b>Writing, review &amp; editing:</b> J. L. Ponce, J. R. Gómez.</p>
    <p>The authors of this work declare no conflict of interests.</p>
    <p class="copyright">This article is under license <a target="_blank" href="https://creativecommons.org/licenses/by-nc/4.0/deed.en_EN">Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)</a></p>
  </div>
  <div class="titleabstract | box"><a id="content"></a>CONTENT</div>
  <div class="box1">
    <nav>
      <ul class="nav">
        <li><a href="#id0x967a280"><span class="menulevel1">INTRODUCTION</span></a></li>
        <li><a href="#id0xe6c8000"><span class="menulevel1">MATERIALS AND METHODS</span></a></li>
        <li><a href="#id0xffffffffffd70100"><span class="menulevel1">RESULTS AND DISCUSSION</span></a></li>
        <li><a href="#id0x8b23280"><span class="menulevel1">CONCLUSIONS</span></a></li>
        <li><a href="#id0x4d1f300"><span class="menulevel1">INTRODUCCIÓN</span></a></li>
        <li><a href="#id0x4debd80"><span class="menulevel1">MATERIALES Y MÉTODOS</span></a></li>
        <li><a href="#id0x5390800"><span class="menulevel1">RESULTADOS Y DISCUSIÓN</span></a></li>
        <li><a href="#id0x56e6980"><span class="menulevel1">CONCLUSIONES</span></a></li>
        <li><a href="#ref"><span class="menulevel1">REFERENCIAS BIBLIOGRÁFICAS</span></a></li>
      </ul>
    </nav>
  </div>
</header>
<div id="article-front"></div>
<div class="box2" id="article-body">
  <section>
    <article class="section"><a id="id0x967a280"><!-- named anchor --></a>
      <h3>INTRODUCTION</h3>
      &nbsp;<a href="#content" class="boton_1">⌅</a>
      <p>The harvest is one of the most important stages in the production of sugarcane according to <span class="tooltip"><a href="#B16">Matos et al. (2014)</a><span class="tooltip-content">MATOS,
        N.; IGLESIAS, C.; GARCÍA, E.: “Organización racional del complejo de 
        máquinas en la cosecha - transporte - recepción de la caña de azúcar en 
        la Empresa Azucarera Argentina”, <i>Revista Ciencias Técnicas Agropecuarias</i>, 23(2): 27-33, 2014, ISSN: 1010-2760, e-ISSN: 2071-0054.</span></span> and <span class="tooltip"><a href="#B14">Lopez et al. (2022)</a><span class="tooltip-content">LÓPEZ,
        B.E.; SAUCEDO, L.E.R.; GONZÁLEZ, C.O.; HERRERA, S.M.; BETANCOURT, R.Y.:
        “Efectos de la cosecha mecanizada de la caña de azúcar sobre el suelo”, <i>Revista Ciencias Técnicas Agropecuarias</i>, 31(1): 5-12, 2022, ISSN: 1010-2760, e-ISSN: 2071-0054.</span></span>,
        so it is necessary to meet the established efficiency indicators and 
        ensure the stable supply of clean cane to the industry with the highest 
        quality, supported by the use of work systems that encourage and promote
        the effective development of the process.</p>
      <p>The payment system for 
        sugarcane to be ground in the mill has been a topic of analysis with the
        country's producers for several decades, to increase the quality of the
        raw material, agro-industrial efficiency and achieve fairness in 
        payment. In this sense, methods, procedures and equipment have been 
        established internationally to carry out a differentiated system of 
        payment for quality, through the taking of samples and their processing 
        in the laboratory (<span class="tooltip"><a href="#B8">Estrada, 2012</a><span class="tooltip-content">ESTRADA, M.O.: <i>Comparación de cinco métodos analíticos para determinar la calidad de la caña de azúcar</i>, <i>[en línea]</i>,
        Trabajo de graduación para optar por el título de Ingeniero Químico, 
        Trabajo de graduación para optar por el título de Ingeniero Químico, 
        Guatemala, 172 p., 2012, <i>Disponible en:</i> <a href="https://biblioteca.usac.edu.gt/tesis/08/08_1253_Q.pdf" target="xrefwindow">https://biblioteca.usac.edu.gt/tesis/08/08_1253_Q.pdf</a>, <i>[Consulta: 12 de enero de 2022]</i>.</span></span>; <span class="tooltip"><a href="#B3">Canales, 2014</a><span class="tooltip-content">CANALES, M.C.: <i>Desarrollo de un plan de mantenimiento preventivo basado en la metodología RCM para el departamento de patio de caña</i>,
        Instituto Tecnológico de Costa Rica. Escuela de Ingeniería 
        Electromecánica. Central Azucarera Tempisque S.A. (Catsa), Informe de 
        práctica de especialidad para optar por el título de Ingeniero en 
        Mantenimiento Industrial, Grado Licenciatura, Cartago, Costa Rica, 192 
        p., publisher: Instituto Tecnológico de Costa Rica, 2014.</span></span>; <span class="tooltip"><a href="#B19">Ocampo, 2015</a><span class="tooltip-content">OCAMPO, B.J.E.: <i>Diseño de un equipo para medición de fibra de caña</i>, <i>[en línea]</i>,
        Universidad del Valle, Trabajo de grado presentado como requisito 
        parcial para optar al título de Ingeniero Mecánico, Santiago de Cali, 
        Colombia, 92 p., publisher: Universidad del Valle, 2015, <i>Disponible en:</i> <a href="https://bibliotecadigial.univalle.edu.co/bitstream/handle/10893/16466/0527918.pdf" target="xrefwindow">https://bibliotecadigial.univalle.edu.co/bitstream/handle/10893/16466/0527918.pdf</a>, <i>[Consulta: 10 de enero de 2022]</i>.</span></span>; <span class="tooltip"><a href="#B20">Perdomo, 2015</a><span class="tooltip-content">PERDOMO, T.M.E.: <i>Diseño de un sistema automático para muestreos de caña</i>, <i>[en línea]</i>,
        Universidad del Valle, Facultad de Ingeniería, Escuela de Ingeniería 
        Mecánica, Trabajo de grado presentado para optar por el título de 
        Ingeniero Mecánico, Santiago de Cali, Colombia, 90 p., publisher: 
        Universidad del Valle, 2015, <i>Disponible en:</i> <a href="https://bibliotecadigial.univalle.edu.co/bitstream/handle/10893/16558/0529022.pdf" target="xrefwindow">https://bibliotecadigial.univalle.edu.co/bitstream/handle/10893/16558/0529022.pdf</a>, <i>[Consulta: 11 de enero de 2022]</i>.</span></span>; <span class="tooltip"><a href="#B7">Diaz, 2019</a><span class="tooltip-content">DÍAZ, L.R.: <i>Propuesta
        de un plan de mantenimiento para la disponibilidad del core sampler en 
        un ingenio azucarero, utilizando el diagrama de ishikawa para elevar la 
        confiabilidad del sistema de muestreo</i>, <i>[en línea]</i>, 
        Universidad de San Carlos de Guatemala, Facultad de Ingeniería, Trabajo 
        de graduación para optar por el título de Maestro en Artes en Gestion 
        Industrial, Escuintla, Guatemala, 2019, <i>Disponible en:</i> <a href="https://www.repositorio.usac.edu.gt/12352/1/Luis%2520Rodolfo%2520/D%25C3%25Adaz%2520Jim%25C3%25A9nez.pdf" target="xrefwindow">https://www. Repositorio.usac.edu.gt/12352/1/Luis%2520Rodolfo%2520/D%25C3%25Adaz%2520Jim%25C3%25A9nez.pdf</a>, <i>[Consulta: 13 de febrero de 2022]</i>.</span></span>; <span class="tooltip"><a href="#B24">Santal, 2021</a><span class="tooltip-content">SANTAL: <i>Equipos Agrícolas para la caña de azúcar</i>, <i>[en línea]</i>, Slidetodoc.com, 2021, <i>Disponible en:</i> <a href="http://slidetodoc.com/equipos-agrcolas-para-la-caa-de-azcar-sulcador/" target="xrefwindow">http://slidetodoc.com/equipos-agrcolas-para-la-caa-de-azcar-sulcador/</a>, <i>[Consulta: 20 de julio de 2021]</i>.</span></span>; <span class="tooltip"><a href="#B13">IRBI, 2022</a><span class="tooltip-content">IRBI: <i>Sonda Oblicua IRBI Modelo FB06</i>, <i>[en línea]</i>, IRBI, 2022, <i>Disponible en:</i> <a href="https://www.irbi.com.br/br/noticias/sonda-oblicua-irbi-modelo-fb06" target="xrefwindow">https://www.irbi.com.br/br/noticias/sonda-oblicua-irbi-modelo-fb06</a>, <i>[Consulta: 10 de enero de 2022]</i>.</span></span>).</p>
      <p>Taking
        into consideration the urgent need to begin the implementation of that 
        system in Cuba, a kit of Brazilian origin was purchased by the current 
        Empresa Agroindustrial Azucarera (EAA) “Jesús Rabí”, in Matanzas 
        Province, made up of a Stationary Oblique Probe, a cane stalks shredder 
        and a hydraulic press. Later, a similar kit was incorporated in the EAA 
        “Panchito Gómez Toro” of Villa Clara.</p>
      <p>According to <span class="tooltip"><a href="#B10">González (2020)</a><span class="tooltip-content">GONZÁLEZ, L.J.: “Pago de la caña por su calidad con notables beneficios en Villa Clara”, <i>Agencia Cubana de Noticias</i>, 22 de marzo de 2020, <i>Disponible en:</i> <a href="http://www.acn.cu/economia/62373-pago%20de%20la%20ca%C3%B1a%20por%20su%20calidad%20con%20notables%20beneficios%20en%20villa%20clara" target="xrefwindow">http://www.acn.cu/economia/62373-pago de la caña por su calidad con notables beneficios en villa clara</a>, <i>[Consulta: 11 de mayo de 2021]</i>.</span></span>,
        since this payment strategy began to be applied, a better supply of 
        cane to the mills has been achieved, in addition to reducing the gap due
        to varieties, strain and age, which has made it possible to cut the 
        cane when it has more sugar content.</p>
      <p>In general, the 
        implementation of the system caused the favorable satisfaction of the 
        producers, benefited the agro-industrial efficiency and the stimulation 
        to produce with higher quality (<span class="tooltip"><a href="#B9">Flores et al., 2016</a><span class="tooltip-content">FLORES, M.A.; PALLI, L.R.; HERNÁNDEZ, F.: <i>Diseño de equipamiento para muestreo de la caña para el pago por su calidad</i>, <i>[en línea]</i>, Atamexico, 2016, <i>Disponible en:</i> <a href="https://www.atamexico.com.mx/wp-content/uploads/2017/11/3-ADMINISTRACI%C3%93N-2016.pdf" target="xrefwindow">https://www.atamexico.com.mx/wp-content/uploads/2017/11/3-ADMINISTRACI%C3%93N-2016.pdf</a>, <i>[Consulta: 11 de mayo de 2021]</i>.</span></span>).
        However, the high cost of the equipment in the international market led
        to the search for alternatives based on the design of prototypes by the
        national industry, appropriate to the conditions and available material
        resources.</p>
      <p>One of the equipment was the Sampling Probe, designed 
        and manufactured in “Enrique Villegas” Workshops Division, belonging to 
        AZUTECNIA Company. The probe is coupled to the tractor during the sugar 
        harvest, and later, at the end of the harvest, it can be incorporated 
        into other agricultural tasks without difficulty (<span class="tooltip"><a href="#B1">Azutecnia, 2019</a><span class="tooltip-content">AZUTECNIA: <i>Manual Técnico de Explotación de la Sonda Toma Muestra</i>, Inst. AZUTECNIA-División de Talleres “Enrique Villegas”, Informe técnico, Villa Clara, Cuba, 6 p., 2019.</span></span>). Its introduction began in the previously named “Heriberto Duquezne” Base Business Unit with satisfactory results (<span class="tooltip"><a href="#B15">Machado, 2019</a><span class="tooltip-content">MACHADO, O.L.: “Análisis de la caña y su calidad”, <i>Vanguardia</i>, 2019, ISSN: 0864-098X, e-ISSN:1607-5900, <i>Disponible en:</i> <a href="http://www.vanguardia.cu/villa-clara/15675-analisis-de-la-ca%C3%B1a-y-su-calidad" target="xrefwindow">http://www.vanguardia.cu/villa-clara/15675-analisis-de-la-caña-y-su-calidad</a>, <i>[Consulta: 10 de julio de 2021]</i>.</span></span>).</p>
      <p>The
        construction or acquisition of new and modern equipment requires 
        validation for Cuban conditions according to established standards (<span class="tooltip"><a href="#B6">Cruz and Vázquez, 2014</a><span class="tooltip-content">CRUZ, S.M.; VÁZQUEZ, D.O.: “Procedimiento para la introducción de nuevas tecnologías agrícolas mecanizadas en Cuba”, <i>Revista Ingeniería Agrícola</i>, 4(3): 39-43, 2014, ISSN: 2306-1545, e-ISSN: 2227-8761.</span></span>; <span class="tooltip"><a href="#B12">Herrera and González, 2015</a><span class="tooltip-content">HERRERA, P.J.; GONZÁLEZ, R.F.: “Estudio de las necesidades de agua de los cultivos, una demanda permanente, un nuevo enfoque”, <i>Revista Ingeniería Agrícola</i>, 5(1): 52-57, 2015, ISSN: 2306-1545, e-ISSN: 2227-8761.</span></span>; <span class="tooltip"><a href="#B5">Cruz, 2018</a><span class="tooltip-content">CRUZ, S.M.: “Procedimiento para la introducción de tecnologías agrícolas de mecanización, riego y drenaje en Cuba”, En: <i>Convención Internacional de Ingeniería Agrícola 2018</i>, Ed. IAgric, Varadero, Matanzas, Cuba, p. 13, 2018, ISBN: 978-959-285-061-3.</span></span>; <span class="tooltip"><a href="#B18">Minag-Cuba, 2018</a><span class="tooltip-content">MINAG-CUBA: <i>Procedimiento para la introducción de tecnologías agrícolas de mecanización, riego y drenaje en Cuba</i>, Inst. Ministerio de la Agricultura, Cuba, 13 p., Vigente hasta el 2022, 2018.</span></span>; <span class="tooltip"><a href="#B2">Betancourt et al., 2019</a><span class="tooltip-content">BETANCOURT,
        Y.; PONCE, J.L.; GUILLÉN, S.; GONZÁLEZ, J.C.; GÓMEZ, J.R.: “Parámetros 
        agronómicos de la plantadora de caña de azúcar AZT 6000 en suelos 
        arcillosos pesados”, <i>Revista Ingeniería Agrícola</i>, 9(4): 36-41., 2019, ISSN: 2306-1545, e-ISSN: 2227-8761.</span></span>).
        Throughout this process, the coordination of the work and the results 
        are carried out with the Agricultural Engineering Research Institute 
        (IAgric), as it is the leading center of this activity in the country.</p>
      <p>The
        application of the Procedure for the Introduction of Agricultural 
        Mechanization, Irrigation and Drainage Technologies in Cuba, focuses on 
        obtaining the following results: ensuring that the technologies meet the
        technical and environmental requirements before being introduced into 
        Cuban agricultural production, timely availability of the necessary 
        technical information for decision-making regarding the acquisition of 
        agricultural technologies, anticipating possible effects on the internal
        of the national economy and anticipating the sustainability of the 
        technologies introduced in the import process (<span class="tooltip"><a href="#B18">Minag-Cuba, 2018</a><span class="tooltip-content">MINAG-CUBA: <i>Procedimiento para la introducción de tecnologías agrícolas de mecanización, riego y drenaje en Cuba</i>, Inst. Ministerio de la Agricultura, Cuba, 13 p., Vigente hasta el 2022, 2018.</span></span> ).</p>
      <p>The
        objective of the research was to determine compliance with the quality 
        of the work, the technological and exploitation indices of AZUTECNIA 
        Horizontal Probe in the sampling of sugarcane for the Quality Payment 
        System.</p>
    </article>
    <article class="section"><a id="id0xe6c8000"><!-- named anchor --></a>
      <h3>MATERIALS AND METHODS</h3>
      &nbsp;<a href="#content" class="boton_1">⌅</a>
      <p>AZUTECNIA
        Sample Collection Probe was designed to be coupled to light tractors 
        with an engine power of 56 to 80 hp, especially the Yumz-6 brand (<span class="tooltip"><a href="#f1">Figure 1a</a></span> and <span class="tooltip"><a href="#f1">b</a></span>). The parts and pieces that make up the probe are presented in <span class="tooltip"><a href="#f2">Figure 2</a></span> (<span class="tooltip"><a href="#B1">Azutecnia, 2019</a><span class="tooltip-content">AZUTECNIA: <i>Manual Técnico de Explotación de la Sonda Toma Muestra</i>, Inst. AZUTECNIA-División de Talleres “Enrique Villegas”, Informe técnico, Villa Clara, Cuba, 6 p., 2019.</span></span>).</p>
      <div id="f1" class="fig">
        <div class="zoom">
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flXgcG7ut%20O19a517zp/bHI52dxz5MyN8WRG7+oVQu2hFSwAVtkOlcPc7Si0dHbbrlfFV+xMkIgQ/xBLlbKl1U%20a/GuVt3qv2OpeBjS5UEEEXvfxXwaR+qmHkNOX5jjeGwn5mfkCKBg2tbYvc5QCI2i5J8BR5jRVOK7%20s5vl+8eE2zHiMA5QH5FgD5MhgIX3nFUsNBpWctzwNFE7rWBqVmXn+MfPskG4tVzAhN2lCR8DXV/n%20lY4vXjewrLymLJizvjO5YnINy32k6dKzlttamsZplc7L7h4jivp9wc/K5ceG18Ia10p2gvLnelu5%20KXQ7j6ka5v1N4uDlsbBjlY+CeMujy2nfG9yfKo0IPjSwR1lPb9U++eb5x+L2rxcGTgRPLZJ59zVu%20gupAXz8Kv2BxquRyz6yZOfLyu7kGNxuQkc73sdpDgyTaAgPWyHwrs2l/Gq9/kZ3Vz0R2zyLB2fw3%20uMLWjChRWnrGnxSuWb/kzVLATchihil+1qruITQrYHyvU8bisNJsmMBpc5HOCsWzivgAo+Y/uq09%20CWJOcF6NIIDj5ttpTi74BoSlnigjdNM8RwxjfI91gAOtO19RI49zHJcr9SO5oeG4tzsfisdwcZQS%20gj/imeW/zfwa3rdrpyC9o7+o/avC8LzHHYuFAQybj3BhksHSxo0ueERf4r9arbnjPw+ZElx52+w+%20+h+Rku5+CHFyGHKZ7jts+5NsgaHfKDqRXF3q/knY6dhWvyOx81Dzs8nIxStwZW/287Q5j3L6r2N1%201T9DXE1LqeeHI2jJJZJvgcB+HhlrnNJkdvDW3Y0EaNUBwBrZKxDHPIYhy8V8NgXNOxehIrTbl0u5%20nOPUrHM+RwJop5Cg9ppG12igILC1e1t7ifmeVuQs/aMEte6jU1rcytVfsZGqpfxX9PGgKr36fQwi%20ttZQLgrb40xJYxyr9be82IIVPJpAVRc+NZ65RppVIz7dyqKLLa4Q3o+A1zryN2KLFx2oVGp/RelL%20xQ8j3jp3wZbZF2bxt3AeIRAAR1qN2N1zLhKxceCZEjpiQSR6nAkqthe2nmLV529c7tvKvYc5UhG8%20AgbUVU/iUJb76mKLsM3zvAI3OSwTVB4G3nRcLiByGfC+tigSx1Nqi7ATdIvqFg0m4W4CE+VxTXKu%20QWEnSIoI0JaC6y6BSqgkXFCqvEZq57lsA4DoQERPSvT7qq5NxEuJ0BeXL+vwB8aVmDN2wTOLrafL%20foAbFT4+NDC7NH40xAc4ILkBLNHn91VawW9oi5h2o5t0J2ohsdV+yni/tr2EsbcpjTZHD57GAgSQ%20yNUG3qCW+w1MnZXr7FRWSj/TricpZ8NrI2uwoIo3likhxITbp0Kml2m5ZvmPutu7/c6TxvCxxwOd%20kRhznE+hzR6VVB9rT1ronuZMobdlX6jafi3HKcYWI0oHAWNhpuBAC6oKI7mBPbL521A/H4iGF5Li%200uubauJSuPed5M69pWjYlKyNCt93HaccoE9V162FNESK7vKFXGykjXVR6rX8E+FUlwFdgZXHqCE3%20BqgkE3IDvAH/AApcBNmwdtBAIAC7DYpa5Q+ZQfHrTbuPqubLqEVAFGhAKADomlwNaGJmC94JAubm%20wU+G7qvQp+hrBJHuRvcGMEIZ+XkLmlUXz/DpSWQJByi5s5CqobD0rqfuqloFwZsKBwvcOAKpu08L%20X6U38Ccm4JJLXgAkXBTVSt9dCtGmQMqrSUTddQgN2k2PRR+s01raq+grCm0kI5drj5ix6X8VqblJ%20B6ls3aFVV8+uuqfdTqq1A2DVNvlPzA+CHp8TencSFWhNVIP7bVLeTRJCjWa63CG/29F8KaY2KNZ8%20CARuW9gB8fwHj4Ur1Vakm5Y1EVNA4FAUT7U/ZQmKwOjaG7Wm/UaItj8Fp3sFjJhUBFU6eKaJ18PP%20pTuI0DCSdu0oqC9w0eK9AbUXHYwWEEqVQlG3sQup06UXBG5agVACCT0UJ+K/jRcLAhAO06DcLjW+%20g/Q0XCyNJA0Ei5Pq8yVUKnj42oTHYSc1V8R1PwT9lUJxEy0tXXX8fCqJasak6dHFPTZfPrRqI1c7%20o71BBu3IrlUeI1oDUD/Ebud8qA9DfSwBvS+Argo3AhCCm0qgOv32oYXNdx6gu0tZVHiFTzotVV8Q%20TEcjJx8XHmyXk7YWPe4gKUZcqFCkEqnnVoGjyPm5JyszIyy33W5E8j2k23Nc4bRrfxvW6VkvoJF/%207QecbtpuU5+0B0k0ki6Malyt9odtH3r401BN81X6EzlYd4X1T4beyPDw5WsJcWF+1oapJCBi2+Gp%20r03F8dfb+tfA8voau8V+lY0Vt4v6o4T5/b/KSM9Syb0YWtIPkPVog1vbpuxn2LlhV9L8S4d10ar+%20XL3VTteuJzo+RwmZEJfsJ2u3KtrHqEQj7K8vf23CVj0dnc643Kp359V+C7XikxYHMzub+VuHEpZE%205PSZX/wgdW61Cjeqr2Gtjj+P3/n53KZs/OyCfMmjf+UkdeKEraGNjV1sbXo3NpvFVnQqMlWpI9kd%20z8hyH1J7ca5IoPzsDWRtRSVK7tBcC1ilWuya23L/ALaqry99dSSPYVcB0nKeQLhlyEoUcfE2UoFV%203hXtwX8TxJvIkMqfHil9kutG9ojcfTcEfZRON1zHCVmR3Bz8VkfT7incvjszYOPxjI7He0Sepjl3%20BCQV/bXL6N71TOqW9k5F3Xz3K50GLyGFw0PD8fybpBiuY50hLQQEebbXHwArJ7dr2NE0b9ndp9+8%201gyZfB8q3FfC7+piF7o5feYgatuo8bfgilFp6Xt7s1VguQ/fA5fHh4xnMtL86J725gkPuOkeCpXd%20ZPs/x3i6quQo5ydk4LurL4rFwcbm4HxcflQNlwp9dsTm7vb9I0bWMlfQpeJccYQ50UWVjOZLjSgO%20ilaVaQb2FS42C19TWTCjLgXta542qUVHBUA600KwhJDjKN7Wl1273aJ8T8aqMXYlySOV/Urn8nku%20TZ2pwjXPkm9MszA0e65rgjdwNo2i7vhWu2sVVcxt2u39i4dkds8d2zx4xYwDmSlv53Lf6vceQAgK%20ByN6A1coGS3ncjfrFw88nA8ZnxzmWbEyHe08pYOB6Dw/wrODs8a1XxLbxnQq30X5GOL6g4LpHNY3%20JWMh3pDHtBJBcSVJahqO8hdJrhXsNdl2xXwPQnJTOmz82CJHtfxzwrCHfxkEFD91cOL+w24XJLip%205ZOPxnPYdxjAKaKLXJv0qybi00rNpjR3qVpLRp53qooTaK9y2HHm+1EVDg4FGhSACiNOldW3NxyY%207kOrDI3lO0cfGgdNBM5zGNLjG8Ft9evwrba7pt2aObd7ZJYKlLyPHsc8HIY14YX7A4B4IKeGilPj%20W27vpRecmW3ttyyV7A7w4jEmycLNyXHIMyxRtYZHBjrsUgfaq+VYdnvScW/cb91sWdZrxLY2J4ja%209CGFPUhTRVHneux2bOSN+BJ8f25mZsJnCRsb8pPiLa/E1ju76i7am23sOaGsnH5EJLXFo8E6F1kI%200unjVLdTr2kONuAn7auNlA9JFgnQKfGtL51JuWXiMs4+2Iusw/0yBruC3CDXU+NcO7G+Tu2ZpYJi%20f2XxghyaENI9QXoPs6Vzo6EmRWVIyMEklVBQnpaydVH7afR7iHLhcajMYQbgjoxfSQD4EBLBKr0n%20chbkWKAvaQXkBo3Fy6NTp10WyaVHT7y+qyAPIIcXEEgOUnQJ0XUkeNLI7YFYw3dtICIgaeoaBYAr%200v8AGnXvEh6JAGIAPA2H7vhU9RaYlGfWpBAvtVD4EA9Ptp3d6r2AhSbKaGkEAB2p87mw6CiD5A2M%203Ojkk2Ef0z6XOIS4uL/bTWhGGxbmY4IeGzAHaY7tzgAiEWAX4+NTuf1NYeJUPpnG12by7mkyLDjD%20ciNCoU0K+X+Vc/a2aqv3Nd7+2S8SP3NARX+NybrbrXQmZWNI2hrS5thc/Ami4JFl4d27AYbau0CD%20XwrGeppDQe1JRVe9iQccghCHAjQ3IX41cdLGe4ysmVjbmwUhB+nhV24GXibucCLongt08CaL86pB%20c33gi9wVCLp9l/Ck4v7DuKCQub7j7tQFAibSTp8elFs4K1F/SCGi7jdUJ62VCljaoqq94iOma3/c%202NbTFkS5W5OtNWsMfCNwIClrbK8oE22C6rVdRNjPsuaBuICfxjQeOpRL6VTYrCjWDS4U+sC+vQr+%20vrSCwbPSdgJaRa9ihHW/SwpNjQqCoXUHRB50FJmrmApbxG2111S46LTuJmWqpXRSi3piQu1TYW8P%20tv1pGkWbsC2W/Tpe9glTcYswWAcoUtvdCSpCgdEOtFwMtkAIJ+IAABQar5FL/wCdIDKqCwlRZALq%20V6kdbmmFzc7S4nqVUeRsu79t/wB5kDFkXcg2hyC2gUDU9APhTuT02G3Kchjcdhy5eW8Nxoj/AF3G%2020O9V18xp0++k2HTyMwZEWXisyYCXY87d8coHzghdyG/y/dVgvAVf/EqOLVPQXvdPhrR5AJuc0kk%20IVChVSyn8T40XA1Vqo0oBdq+fj/hTuPIlISoQEoLeJGui2oIlqJElPSPAoVCg/HrVGdhOGZk0TZI%20pGuifdj2lVTVFX7qd+Nhm1iUJFxZpGi2Fjot6LhYy5CCp9LgdwctgQU0/wAPjSv76r9AsYeLix2m%202upJB/BPspKS4ahZlO+quXPB2Rny40zoC0sYZonBqNuoXo1Na129aqvMmVVXA8zqWxNbo87QGkIp%20uUcvVQqHXoldNr18A5nSuTMmF2Q6MgKIY2gOt65D6rK1S0Hp91rT2zUp+34a/p4eZG6rJ5qq50DF%20iDHgPe3c4Eteoka1oCrIwNevh5a17MVda4wvP/421twxi/Pgbqvf5lwwZ+Lx4BM/kITA1w3BwO3e%20B6trnKFJt62uXW6q3V7is2+VW+ls8mcL2ZNqKrhXhnFrDrmvrBmt4aPheABxYUDZ+ScP6z2k39th%20J2BSnimgFeH3DU5uXBnt9ttuMOniq9vmVDtbtTuTujkTj8NjvyJX7jkZrysTATrJMFB+ZSqk+Vc7%203VlfA6XHJ1btz6bcX283ujKZK3Ml4vBbjMy3NBa3Me1ZTCqptsh1AJqITcp6+dVwFuf1Zzv6YuP/%20AHD7a/n/ALjDuKai1ygPVf317PcRS2nz6f0z9P01ODad5rzPbdfNHsHKs8OGVIQ30kucAoKkON18%20zXtw0R4ctWISMWKYAbkYUcinRFQfdRLSq8fEcdSB7GjD+z8Bjm72OjkaWWIDQ8i6fdRF8Wy9y/Vg%20Y/UjjuR4ntD8xhcaJeNa9ocY2f8AJc5//MCJauXd3Y3SpG21CTV3qa/Snheb5Z0/czMX8hiZzXMn%20x37v6krCB70YIKhAR+qphur2FSguBz/6xxu/uT3PcWPZK5skRJUENGi2Gl/xrodm68q462FtaVyv%205nZeHyIeR7P4vCz8dmRjjDhDWuUEEMF1aR+CKKl7K15kerZtFGmxO7Pp9ly5/C7+R7cmdulxXX9s%20DXd8zt17bfu0olG+pcZ31dfKvfeO3u9eI7gwWZGBO0zbUnxCf6kY1TS4+z76lbV3dk7ja8UVXv7u%20/wDt+GcCB735jm+058R9Ue/5drgvrIVfCtbW0+nwIg7u7r3mnYva0vE4x5PkCX81lxj3A8qIIzcR%20Ai+4j5r63+Om1t21I3ty7sq8C54cUDsgfmRubcE6+IW5K7TS3ZWQtvLE/qM5knZk7g07GyRiJwW1%20wF6IelcjbUlzO1WcTjvaU8fH/UHjA+P3Ymz7GY5cm5rwha1R0cBdFrTeynavGvDxJguNV9jtmdiJ%20ymS6Pg8iBzcR5AimKubv1U2QfgteRZ3wdvDJYO2+Y5MccxmWz5WtMKlSGFSFNlrfbjfUzkyWmyS+%20MFyga7TdfAkG9v08a1UckIZzZAUfwBoDiRZbAL4dKq4OVjSXK/MwnHedzJGpuNnAOF3KacbJ3REl%201LQ879xw9uYvcf8Ab+FdmT5cMjRkZAG/HCeo7lVQhOmiVe9uq109f3/f7ihtviq+IlzOT3bgdxZE%20/EYjpBLtZufD7jtLMYugvcr41zdp3EYRs9Kq+vmbb205O9ZrT9kdA7P7v5jLOLhchwsrC5qZmS4l%20kMW0WN9xIUm3SuhdzFq9/wB68fscz7Zp+B1Di2GPFMLDvY0Euc0gW18yL1EpqTumaxg44tYY8hC3%20a7+mS4Bxc+wIcPHxWt4My3LFO7l7w4zt/EZJlY5mnnD2wY0YR8rmgABeiJqOn21pP+Ns61+xlBdX%20Ake3eabm8Vi8g2B8JyIt7YZGgFp0+PT9lU49SwyVOzJSXlMl7XbRtYRtCfN1F/AnwqFtq+C3utqz%20GOVkTyqHXBsmvUnQ9NRrW0IpGMpYE8aFZg0FHCziAlyAgsv4UbjVggncmouHneGtMpaHAFoRFXUf%2051yS3EdkdskRwh2/81oIIJCkKiBAdbEaVi5I1saji3NDQS1RYFbqCn4pQ2CD2Y4gAHb0VoAOgC1N%207jwaSO2Dc4pe5PmUWk1wQDB8obJezb7763PmUvVq7JkLYce54Acj1A29EtdL/fTdgH3L488HAZij%201OjO3+IevU/FqVjutWwaQ1Kr9M8Nr8zmZy622GMtaSCNgBBQLZHLasO2ZrvXLeTGp6sHiNdfP7K6%20HgzaE3hz3AgagBqaILCldg0WTiQBgsA0UoutRLUuI8qSird7By4pAsA71LZSW/uq4mW4VjYhu9SL%20J9lXcysbCAA3ItqdbH4fp41JSFWMaflYgIuAbm5HxICWFJlWwbGF4cHbgrbElAE6ovnrQwsJh8oY%20G7nLc73BfUPgqqtXYVxkZV7qxkIDG4Lgg/m3HQX8KiRSZLNkeCHDaOjnaKtz5dKNcKq+AhRmQCR6%20XBpuzQqljQ4MDBe0jcSWtRA4i4IUa9delUr6iFGSNQOc3YSVLdCuqnTwNAAx43G6hxUXXUApf70o%20aYG5admhUhSAgJt1NJWG0YATopGniQnVapkiml0v/N1T9DStgtYN2SCzj8filOzvYOpWFWSbCUKI%20LgIP0/fU2KNt3RB8OnRP0NOzEZ3bkNzYgG/UHUedSLQ2CktRSqBt16fvPxAplaGwc4AlupG4W0J9%20Oo89PNCaAWox5t7JMOKN7Q6N2REAXBQ5um11z5FKBDh7W7y0MBaOgOg/GtBGNyEO2AIpIICHVfsW%20p4AalATfQ6aFBVZKAlwANlOn76QjWRoLrk9dEvc/h9tCZLSI7keV4/jWCTLcgAIjA3PcSh6Cq6iG%20iqfTzuObkeKjxYcGaYRSzCbLcQ2MNLiGAj4dKLhYuoc1SL+kaXNv0FDAA8Km4WJaVBF7JrQwE3KQ%20Gj/lOB3yE3vr8KTzVeYeBRvrdI2H6eZABSN08MRKgAK4oFKaJW20rtVwE/iedoIXTZcOOQGmWRjQ%20Q0EN9YYg1JXwP3eG0sLnVeHmCfE6F9SNmPwXH4wID3SI1UV7WBHEdShSn2MP5VXMx33g55GWhzXE%20B7EUqDsTqSQWoirr+xfSn3PTVa50+Zzx2HI1nlycktiVzg0DZGELiQjCAAR6hoo8PKuDe7qcnaL/%20AG/VePtudW1sxirvQ6R9OPopmc/FFy/PyHD4d6+1iR/86YNcHercAA0+OvglcW7JrU2hKMl/E7vj%20Y3EdtcDKzj8aPD43j4nzOhiAaD7bSS956nzNZZZehVp4zg/SrOychWT5cUufkutuMsxBRxJF0HU1%20rst9azqZbv8AVnDfpiv/AHF7ZBTd/cYFdZLLusV1tXudy/8A1y5W+PyzTODa/svM9u18weyc25TG%20ljy5WEq5rtyOABR19SodpofhXr7crpHjzg+pjOSIHehDo9r2ooKljbopVB4/tq/3JSsafRrjN/bm%20NkSI5kLpGAG+4hxA9Sf+7zri3d3+Nl9jt24fyuTM/dfFcr/dOAhZsYMcxgkbUXcxw2FLNLen+Nc6%20TeTZu2CS7MdH/tPi2b124zGBzVDSGjaCnnQ07iTwedPruo7gyg42GSSECeosDQf5h1HhXbs6eyq8%20jF3On9vwSR9vcVu3evEieXIij2wbNS1dEXdHHKNnkekggsJBa+209QPjerZndnK/qJwvGduz4/Oc%20Rlf23ksiRG4sYBY8i5kDPu9On7c5a1VcTr2m2s1+4h2IMLO59/K89kGXknbTgxOaW7ZD80kgPpBI%200UfCs9uavyRe8mo2WaridaiwciWF80UbpIWkrIAT81wm35rVv6seeTiUJa2HXHTw45/qw7pDaQvH%20qQABL+Cms9yN8o125dIx+oXLYmV2qcWQMi/NTsS4bdo3AN6dFrk3NpxarxOvbmpJo4Vysr+P5bAz%20WkxiFzJXNKoXRPHqQA2ActutbrNeV1p8wi8M79273hBzfNNGFkNyg7DLZNg0Lipa9PTurk3YLqsV%20tydskpwc2ZNibg23tMIdY+kFwul+l6I4r96+ZeTXL5TJbkOjhibKwJvmLgWgm6W8qx3N5I0hsSbG%20Uue8vcC4wyPPyE+q4/gJ1augHXXywe9J3sufsrgdse0Vr8KrJGZndPE4rpDmclBC5ri1wdO0u2IU%20dsB3EO8PPxqW5N2vwvX19xstmKrjy9304EBlfVPsLAZ7bMtsjXf1GNgha4a7i0PDSjgh6j9tR6V2%207/2r7lRUVfivv5V7UQWX9euJYEwcGaQFobtmd7ak7XABdR6ivnVraVq+/wC+gPpXkU7nPqp3ByrB%20DJyQw4XAtfBitDUOoWUhpRDer6E1xry4Ml20Yw4DvnneEyBLjcjk5sLnB0mPM++m5Qvkun21o5Pg%20rftXwwZyhzt+/H2fM6Nx/wBaODfHIyeWXEMjSWSTxOlAe8eojbuNEN3cvjN6p/Iwn2kXoQXO8LyX%20dLoeR47uDG5HLwmluI8OEMi2QkKNtx4CtY9wnho55dtKJafp5B3hFvHMB7oduwxzEf03i6xu0exw%20/ZXobW71a1WfoedvRdV+vmX7DxDkSbQdp1LksE0v43qpysTtw6jeTi52yXajR/E0D1AX086Fu3Qe%20h7htNPjccx08szI4WOA9x5RtiE8vsocroahZnOe4/qjyfFcnlZHHZZyMP3GmGFy+pwAbsHUtLjql%20cEsywdSuy+fTvu3uvuCPLfz8WJiRxNa7HbjyNLvV6nbwC67VvTXgWmXGJ8cjne85AwekKpPh0tda%20Vh6jtuNEwGV9gQjQPEqFv+FJhcjs9sLnelyXDgpQW+O5BehZdVVyWNYMWBz23ct1D+iEdE86qTr3%20ha5JDJ4zh243uK+XJeIonJuG46KegvrUPLKSFu6MyE9vZ7d+x/tlvmLooXUVlKLsaw1KZ9OZRCeW%202hAfaZGV9TUaPlSwCu6Vn271qvaVvWRd4PZdC172gBpQqgCmxubHr/lW7bRFjQ5B3HYEJIG5vxAR%20NUQX+ypuLpJnhMvHysLfjuD2MkfE4jTdG7Y4aDqKllx0H9Ioq3ejg12Mdfm9JKCyEH7OqVUTOZW7%20oo1FgESwuKd+FV9yTItuABuPUlyoPgOi9VpWEkKtdYonV243ttPq6r1W1JlIVa9twArWhuiKAQou%20qJRoNobuapVo6gAjTxPilv4a0T5mbsRjmp3VCzaHH8i47EIUbjfwpNDvglA1oeu0kkhbop1ROnwr%20TzJbMhi7QLFRtcCNToDelgVzlmRyfduT9eIMLDyHRcJjtaJcZy+2Y2sG87Us9zjqtPqvrXEu1kda%20DGh5G5Wk6eHqGq9U1qW26r2EocMI2g6goi386hloUB6delBa5An2HpQFkZ2ANQfH9tNA1yMf1Cba%20onh8L0YJszYOdY9Bp5H7afiPJsrwbBLX+ApCybK5Tq0hRp508lGS91vSFVQT8TqvxoEZD3aqSFXw%209VlsvkFSi6BjHkpAPyUe1XyZTWNICnQuJ+4UPxBjvdfwA0RevRKp/GvgIwQoKkodCPEW1+2gLgwH%20eCp9WqFf0saLeAI2CAjxHjdT+go8hmNwAU6+HmKBu4m9oc1wAaXFp2l7Q5LW1FBLKz9PsT8v24Gh%20C508znPsN53G5T41K8QehY9dQqH9utX5EXNCVCOO2yBwBCE2Fv8A1aUMWgABiAuJ6brBV0Xz6Uaj%20OVf+QmY2PgeKwQ4NdNk7w1SAWwtX1NBFh0rbay/jVcyZHC4piHb2na5qFjlcm56DcVv6SR9t61nH%20FlrVVYFhj/kuazMl7sR2WJ8SEsZEZBb3QCC66XN1HX7arZl0589OVP8AQmcLvCImOZ+QQIw3aANr%20zY2KWBHVDr1/GIKW7JRS9tc/2fEqXTCN3qWvt/icSKSOR43lBulQSsaFX0+JJGi2K+Ir1u37Nbdm%203mqweP3Peud0li/j8vE9HdnyiLtyB00rdo3epzmtDQD8npIbbT8a8jvUnPwPS7RNQ/f65GvffIQS%20dvtwcfIjfPyuTFhMayRocWPcPdLSvRi+VcisjqZj6hTYbexOaxYJoi+LFEUbY5GKC3aGgAHqPL7q%2002JJTu3gncUmvE8//S+Kd31D7bc6NzQM+AlQiFdV+C9K9buN+PptX1Vae/5vU5NvYkpLzPblfPnp%20lD5qVkmUZEBYG/K4aFRt3oq+VelsppHmb2WMPYe4iIgj0FrFBd8vp+YgWIXy69a1bRlGL0HH0vkO%20H2Fj7gGmCWZpYD6Wlr0Rf3V50rOR6CdolD725+DF5yTLnjysYRtDXZmGdjjfzFh6rrfw1rSKIS5E%20p9PucmfxmQ1uV+bELhJjxuPtOZC8WIUAlfhSvZjZyf60ZcuZn/nZGmF0kjz+XX1NO0KF06dDXTtN%20KqrgZo6jw/MOOFw+HJ7CvwoDZySWjQWRVI6E9BThuq9kY7kKqnyJTOyYcHGdPkFGNarQlySu0J+N%20bOSVeRjHbvIofb3ZnMd88/ldw5jXS9v40pbgxEDbM9rW+ljfV6GuHqXW9YPcSefbXl8eZ1OEoqyL%20nyf02fzPHMMjBhZ7A1sMzQj7aBwGrQP0SrlvRuZxjLjoROB3r3d2M0cN3BjGeBy/lc/afbJCBdwH%20ncH41zSim7o6I3SLl2VyGF3Vjx5uY2OLLie6KfHaQ0PLVLXALcIhH40epKEbIhbcZSyMvqn23iS9%20tuh46MOynZLC5SbNedqCxsqVz70pzST0NtuMIO5wbuvGliVj3NGTivOPKIiXMaChB2pf1Aa6V3wi%20kqrzITvKxYe2O/e5+Fhik43Cj5POZC5uFiQRghH2cchAu4kaivN3etzt9/edW3CNuXyKvm/U76pt%20Ycl7p8DjmnZE2PHLYidyfOVsCqGn0SaOjb6b17iDzPqd35lRjdy0rohfaSGtN0BVo6AekjzWojtJ%20Zaz4fH33N3uWfAgszneZy5GjMnlyHMUM9x7yWOu7a0t3L4hP3U4xTzxr9NRSm1qIP5Hed82/e8Au%20c+5AUglxv1Aq3F8FVfMXqWqqRiPJicdq7XIC9m3abov49aEmvnVZF1viaySRvAI9L9hTcSXAgbVK%20/ifJaIY0r5+72ENR45EnyRrtcBIW7gQ4FLs9R1PUaa03d8a/fH6CslWptE8GZj2kku2bQqqgQoAF%20ah1vSaxnjVfsNOzsWePFZ7cafysVhJN0VVKeHSufcldnoRh/HI3kx8Rjiz3GgkbXo7aXgeO0t+N6%20Mry8POtRKEG6+wvFl8vjxh2HyuVje01d0cpe3b1O0+PSmpNPC1wY7uzfjf418TuH0X7z7h52efju%20TawxYkDZH5qHdK5dumi9PP7K7Nrdk1n2Hmb/AG8Ys6plHHwcYTZU7YYnAbXyuABHxJun7q168mCi%20locd+psr+QyMVmLkNn48FsbIYnhrXTvRgUk7g2+ul6uW7fFV8smcINFI7e+mmZzmXzvH+/vzuOG7%20CDX+h5ariEI9QQ2Q1jt9KdUipSkTf0j43HfySOacHm+JHuHIafRk47twMbmEpua42NdLcWtXZ1Xy%20Il1XwdviGSx5lLRogYAvXTXon7Kzk09Ck2tReXMztvtlzbtAAsEX7fG1RZFXEoHF7/UHK0i5+b9L%20a0msYC9xaNsWo27QUDh1NgE+3SpsUsC5MHuRbj6g4mN38rkIJH2VFs8y7oZ86DJw2W1CG7DYkgHx%20uOnSs9zEX9y4PJWOwonPfyZ3FoWIPIPq3J+FR27si+4Wa8i6RSSMbtOtl8FHxrRGNxJ+Q1srWruI%20NwviR8StOMQuSP08kMnASuLtx/O5YLiEVJnVDRrHQs9IZVO9yQ7G0IAcSFHiOn2VSM5lZab+kr0a%20iDQ+XnTuSKNKguNgS25BADiUIC6oNaQNGwMijaAp9QLgF11sECedGuRq5Dc33l23w8Tjm5rDIi/l%20WEPe1AXMBAK6olQ5WNFtSa8ChZH114YZgE/uYGHIC7HkY0vLtrgP6jWqnxNQ5N6HTHZglk1/73dm%20R5THuky5HtY5gyg1fQVBb8oUA6lDbRaSUtb14F+nAnOO+r/Z2e50cPOMjcAGRRTs9sl20qSD0DvD%20pS6pRzTz8A9CDLDhd48PPM0R8rgyAlqbZANxX5RtX9PhQ5zV8ZqvuR/ki1dOq/bUY9qYeJFy/Jc1%20LGZOTMxiOQ6QbXMkHyMVAulHqNcKrhqR6F8Kq53LY3Mi3gOjLCURwuBtO0Kmuunh8K0W9z8qrzIf%20bO2BzFPE8Kx4JcLNFut7Hp51pdPJg4tC7SQRu9K9Nfs/CgEzfQFdAl/hTTLsbBE1pXYG1tfDx/Ty%20poAI0Rf8Psqrir5gAFG7TwGqfbRfIGVQXAvYJ8aEIL66k6rdevWhDNg1ybgFIKr8FRSq9KBMjuUa%20fzHGAfL+bapVLhrgF8qYMfKiKTqoAtY+dLqFYwo+C/xfb5+VUmIC8Hoq/frRYF4GC4jUdLDpQw8w%20DiTuIRNF8vAXFHhVXGjI3XKbvSUF72X/ADpDaKj2zznE8f29G7NyG4hdLOSHFXAiQqUC1DmlqCWL%20IVn+o/ZkQJ/uDJHNUO9sFxF/20Peja7YLbbds3HON3h2zkYTMsclC2IguLHu/qNAJQuAuFQ/ZVLe%20jfXXQqPb7jV0htP9Q+yoYy93Kwu2qdsaucb6AeNR68S12e4+Bxz62d28dzvIcW3i53yY2NCTKHNc%201zZHusoJ8BXX21mqryOfe25QdmjmUkhar0CgggE9V19ICXrWcsVWfouRCWcGOMwpOQcWs3CCE7ZH%20tB11DRYfzfoa4tyeqavVVg69uF3rYs73/wBrgZhY3Hslyn/1RlvYS5hcBYg2VeqVUe8klos1VIjc%207WF8yrxEoc7uZkgfDEGNd6nsbGGt0CNa0hVG0Dw+PS5d9uN4/Ws/MhdttqvmbZQ7tycaTEOdN+TJ%20V7S/0kqqIETxsgNcj3ZN31+XgaWhFWIrF4bkoeQjZPIW+kzlwls0om4IfSfH7qqUrq3OvJUxwklk%20nv7bk+56p3aq5HEr5lSFTpeubplqdb72GLIn/p7xj2d+dvy+44pnRB5eHG67k3FfiPKrin1ZZk+8%20Tj0qNr/KvcewK1MTnfeHc3bXbrf7jyryfetBDHd0rm2sPJda6vU6Y2OPoTdyqu/8ge0cd73fk59k%20TQIg3Y57r3B2rcHpWXXc0UfYadmd88NldrM4mGVnvZGVPLM+b0tiifJuaS4auJ6VOb3ZTssFI+p+%20BgPzJX4/LvzeWkLY8uKKbdj+zb23BSNrjcIPHRb1pDcV7cPsGmo9HJ5nGcdkNyMePDyp4oWf1mE+%20ofI0OZtdtvqqVMW+WPd9iH7cFK78kXh8Dc/fukcsrVazcBtcRuJCLYL/AIDs2pa1xIadyQ7czc/k%20MnC9+RsEcbN4ySxQwRt2ghxbojb+IrBzy7c6+P1KcUi28fj5/fPPN4V2YRxGC8HluRDdpLSv9Jly%203e9UNlDa23ZNqvf+xEIJZZ2/HfxfG4MGBgMbFi4zAyCKPRrW6J0rlUHqat8CN5ufJzeIy8WKc4M8%20sR25wv7SIryuiVSdsolo4F3X3HFy+CzFwHzS8RhS+zFlZZc92VkD0vlS6NBs2hT9vkKUf1K72vz2%20TjcjisfJIZ8R4LmRO2gBpBa5qLuZq010Xvla1X0HKK8jrXNfUmPkuJyseHAmfkyMY2GdhDmB28KH%20CxbtW1cu/FtWqq5lQa4nMO+uB5fhOTHH8hkCR00IyXuPq3byCirrc9ERPCuran/FYIdr+JMdg478%20bEj53Cm/Lz8bOfzjI7+9BICHMeLgH1Ei2qVzbs+md2dVrxauTH1oypo/p7i47HpL3BkRRRRuJHoU%20nXcLqir0Var1YyWlc/nWme3tNNtvQq3e3075Dh/ZhcwSww4zJkhYDIXuY0uMpKhQXG6XqFK3ihOe%20Rf6ddkducr3HH27zeK3I9uFuScljpGCdhb6mFwLbt36rTf8AJLi6r6FR3pFwyf8Ax67Dfz0mEZsu%20PGke1mP7bhtYHtPo3bVsl/KklbNkUt5lB7/+i2Hw/evHdsduZZzMvkYn5ZjnH/KjjQK5wsfL02Xw%20pcPGq+XjrCXPSqfMR4D/AMeuX5YOdLycOK71OjY2MytLI37XgkFvjobfdT2ndXJ3ZWdVWop3P/47%20chwfD8bmHkjnyZ8/5cRwxIGGQgtLyS4n+K/lVJZIe4kVsfTDk4p8hzmOlbjSTtie0EK6Al3rUI3c%20WqAbVU9t1VY8yYb8bimNGXvgaZPS9zGukb4l4CbnIB1v4Vw2k3fjXx8j6KdkmkrP6V9DuHE/RD6c%20s5eNzeHdK50Tv6Ekr3AuUneVPgUtau6cEscz5qO9KV78CsfWXs3g+2peMZxOHHgRZEcnuwMcULg7%20cDfd43P76599p1VeZ6nYzelffkSf0a5zi+H7Dz8nKkY135lzxCEbI4pYXo2mop5uc/fN9dV9SF7n%2073n7g5FuTLDIzjYo90OFMhYxxBAcHNKVzT3nMyjC2XcpHJ5UmXjD3ZY2vehaGBEQj5iuo+2pd9ar%206CVkh9i83yGA8SwlzMgMDPfjKEgi9wilEGv3U7uLv5hhrNV+pJY8+ZmT4TohG5zmGQTB20taDucJ%20ZLFRbWq6mr8qrINLgs1WC/fTbu7hcJs3G8hyD35E7zIJXEvhY1oaAxrnEn+IKSa6NvcVzGSw2dEZ%20yOAcs4zZmSZLR6mAqQDppXR1XeCbG4OPI1AQyNEBHp3Jr4WAtTu+IIZSiQyEqrTZrwLIAQgF0AvW%20ytYwzccRthOVA8else8IQQq/botq55PJvDCM89Kx3A5UTyjNl3BNQU8PFK5993i0jXa/sirdjSTx%20/wBzPqkG+MhxQr6fmcnXxqO3tw4lb18FlkzZhuAaGk+RX7x1ArpqvaYXuIxue6Rpcdt9xcSPHW/k%20KbjVV5CbZO/S/Ibkdsvla4Oac3MQtX/9Q/VawZ0pWRbaQyp98n1YoUKj0HW+1PsWqiRMq7Xu3Aqj%20jcA6jVKZnY3Y9tgLqNu2+ll+GtJjNw8FEcCoBIIBapRSfLSkUildw/SDsrln5HITDKxpfbfK9sE7%20hGqFwdtP22XypWXE09ST1PNE88EbMT2XNcIGva5rkHp9xAXDQqzUeNUsPxvwNZZWSe47sXuXLnxJ%2038ZMzAzB7wnKAiFS10uyxaA8eFKf8fB1+/7kpJuzeKr9hn3f2hyvbnKZGPm40oxN7RDnOjSKRQHJ%20uBIGo+6nCSelVr9jSWttLV8scCO4rh8vkuRxeO42P3szMlEWMxpQmykqPJdSEpdKqqwJyd3fFfoe%20g+F7YyZOxOQ7ZxS9r9jpYpGSEZJyowUaJPlHqJW+mtYqOfCv1tqJ7liucD9LPrZjNM45mPjRG18z%20t0pkJLPVt2+q79v2qa09JNeFfIv/AGPhxLb9K3d/c5wbeV5HlmNLMiSB2NJjBsriwIu8aNX9dChm%20/Mnd7hZuq8jo+BLmscMXKc2SeOIPdJGoDlKaO1+K1d7nM1bI9DgVA+C9LfD9tFidDcE+FjpQXcA4%20UBc3Dm2vamlkLg3XrpZKQm8GwXUIDqL+aUw1EDmYI3AzxN2khwMjVG3Vfgl6V+BXS+Qzk7r7YiaX%20P5THKFAQ/ddT9lS96PMa2p8FX0IblPqB2jHk4rm5zZseOTfM6Npc4I0lvygqovbpU+vlJGi7XcfC%20w2yfqv2pC0e23JyJVR0TIy1Ot3ORvTxp/wCpWvYf+J8WkMJPrBxJia/H4/Je4Bpc1+1qlyekX3D4%20kJ9tJ77va1KqRS7JW/svfj3+JHZH1i5BwIw+GBuEfK9wQfgv3UnvysH+SCavNDTM+qndxIOPiY0b%20S1xLLvHzI0q4g6XOlT60/IpbWxxlevgMcj6h9/yzF7ciHGY0lGNibuF+gKfrslDm81kV9hJJdX7k%20dJz/AHw9rRJzE5c8EP8Ab9LbLcFPvqJTfFi9bZWkbVViO9nkZtwyMrIaxCQDIdq39Wnj160dKefG%20q4EPvoPhcRPDbo/VuO1wIPpHzE6XRSuvQ+dHQvEl/kbPFvcZbwViRCpsWmwadx0Ad/KnX7adknYX%20++fFqvLX2EXy3HcqMmOLFAix3OV0m0OVFQgE+Gnxq2k1mq8Ah3c7Y1K5zXvM5KSLILHvDA0vCLe/%20pPmp0/WK9Dt4pR8v3Ofd3ZTy3cbYuDm50vs4sRnkF3sZ/C13pVx6ffWklxJ0udD4/tt3HcfDiAgm%20JqykepPJxAvckLqK82SfDgJ7z1XE3dwz90u2R7hIRsDnemNAm1vxKL99JXJU29RPE4t7Qd0j5HAv%20buQb0cgVwPosDZPFb1Kbx969vLxBu9q08dR27imOJBiaC9SRZFch2i5O30+H7qOmXOs1n6kJteyv%20CveRmDhMm5rOlfEDFjRxwMe1U0V6kEqQ4JYanSqlB8H+lfDHHm+ppYqsEl+SDWDQFWo5qqA0EsRf%205dP8qXQnda1cE6+dfuT3Y+JE3vPhy1gAblxkMFwdpCG4LlBbTjF63qq0CDTadfsem6s7jxN3VzOf%20k8zyEc+S7LEMs20vcHBgY8oGBSOt7rpUp6q5HsKpJLkwNbKYzHG5y2uUBIRjTofO1aK2l6xrXjoI%20khyuZHgQtMhAw2iNjCuwvcnzkXOnjpWbefbXL9BsbQ8nNHPvja5oDgQSEIvtTz06da0SdrXrX2Uu%20BBcW965nJ8T+Y5FhyMmKM4zyHFpIe7cqatDUH6qlyzYajVeI2725THzu2+IyIIWte1xjYNCXNACg%20Egjdt228a6tlO2dLV7iCzMzWZPFcHwvGRtxc4YzWTzOB9DdXzSE38r6rU4TBq/kdl7M4bhuL7b43%20GwGB+KYRNJM0euZ7rl7nIC7S3lTW7cXTZ+JNQthMj3+2GMS4Frnr8abYkrCPIMbncPl4Yi3Mnjki%20kcurS3YAo0qVnXA2zjPcn0l5vF7JwOPwsiPbjTv/ADADAPeZM4bGkADds2JqpocePEadh72h9Icn%20ie5eL5bkZ4pXQMkdktB1e/5AjvPw61cE1e3ElvmO/qf9N+PjwJ+4+Hk/J5sL2PlgaP6chcQGtYmj%20i8j91U9xR1KSd8HL+5cjksrIglzDIeUjYWTjJeS6NAvocUQFoRfD7qtNNc6rj5ELxLH2BxPIT9u8%20nmsIPFyTNMEbHEkvFngNCeoLqetcndr3o6NmedfqOMvLHdX1B7Q7dIEXHcPF784eHHY5iOJ3AHVw%20F3AL5Gstiec6XdV8Tee3aF75x7/adeYzBl5fmXOczJxhhsiELgr/AHdzi4gLoWpXRuZONYHXA9u8%20FiY+Pk42MxmQwvbj5CDcxjyHujBHmOtEWCMB8cOR+ZPqZHnRse0gf0y5p3P+zWnLI0c77Wxoe4fq%2033X3PuJh4+KTjOOLv4nRM9SOUtsK52+aOmS6Yok+z+TiwuX4zDGV7Jmhz/cjaxRIRI3b6j8guoPl%20T2ZJmW4tC38G787BEZ9yRPcFI+Y7yiKnqrsvZHIo3IzlMLEg4/OMLQfeyZzK8ndcQOaHeXq1rKTf%20vNttK68zzfxIacrBdckZEalzS0hZFNiND8PjXntZyfSzkmm07Kx6vhfFjcnjvhAaHRPc5pACEi2n%20jXoyvLU+Zule2pyT6+yPkyOHa9zpHe1NuUhPmuV0+yubunbQ9T8ZlvnX1qxzjhY4Py8cr3OY6Mkv%20DArnNJW4JvotcM5PRGndJdYv+Xdkvkjwy1z5A50bvSj1+ZSCUI8Kxv0u7Ob076aDCbjnYvuufA98%20cw3OjlA2qt9uu3W51rba3Y6Jq6r7ciJbLSEosefIy342HDLPIyMPeGOJOxVcSfD4jwstarpSWlaG%20bXIXhblY8Mpgl2Y8/wDTa5x/jY0BCHEFu5Krp4iutBvxX5zJyzi4zQ2WbdHIAA3YpBLbr42tR0N3%20qv19rJcraHZuyMM9p8O0c0RNy2Y8I2DdLKIn3YqXZr/FXVGVjNq50bAhEkQycluyUkJFZUTUp+Na%20dWBdNhQy4jj64WhgTawEuCW9XVBrQpsbitRnNIHZ7WRxEl0JkPqG0BUIF/CkxDXnnyHh52ENbuY0%20MuEJUGyHSst7+tfE02/7EJ2Rjvibyn9UFjZmB+xwJHoDkB/9SedR2zwX3Go57qy+Ux4OMixZnxTz%208hEyQs9W6Mep7SioC0Fa2dfrXsM4K484vJJZOJkdM6SRCodb1bUPUH7qE0TJWJX6JOD+xmvAQOzs%2074FMl7VA6aVm9TdaF9pDKX9QsqGKTDjfKGPla8MBXxCqh0qome47FbB3I1hO1xTdZFTQoPBNKZnc%20yC9DtKrchAFJvdPEn/KgExRjrHYruigA6BQ49NNKB3Ncx5GDmEoxhgmDiQiK1Tcp9l6TwvIpZweM%20pt5EriCxr3PHrcG6uJ1OpKnSi3tOv/pvVUj1GHyO/JwFxc89sku2NQgAArsPRR6V/GlNXuuZlty6%20c8nVU9uSycfkvpFyjZZG54/t75Ru9Jjfs3MS/pLCbeqp2nryrXH6Gm+7z5nn36aNb/vvt5ULjkhA%20EDk2lPS0BF8P2mrVV8vnybTSqqXI9B9tyvPKybJWsi9zIaoQlx3epltCun6CoUssxatwL8yRvvo4%20kWTXoLqvlpVtYMVqVnsuSOMcjhABv5TIeHNUj5yocTZPmNqmGHaq4HTvL+KkTMuRxmDkT52VmRwu%209gGVsjmgtYy+8tsb+VVKSXkYqLZWc7vHLzXNlgyWcJw7wfy88zDPnZlwhxoGrsYUKOd91Ve6FJWw%20yNl5w8a187+V5qJ5aCcjMx2SQkgfM5jCHAEeCUYvhku4/wAD6vduRwOi5ScHMiQ78RrnxSxn1NkZ%20oVIRWXIqZSSV3oX0sij3V3NnF2dh8qIcVrTMIfbaHhi+hfmS3776V5PeflI7WOLPS2O0jJZrWvYQ%207O4e6M90pZnzbGko6NB7jXHollaqfsp7PeQ3Go3zViO5h6avbFV9rmpwubeW+5mSzSNsHF/Tp6vL%204V1dMr24Vypo4499waqvuZPDZTy1zjIq7nPUn9pXW9P00sJVXL9yX30+ZhvbcJUuYCwOLmtRDuRP%20Qf2mqUfZkh99PSvMXZwEexrNo3WT+FT0UXoUfBGb7qfiZbwjQxXEONigJVUBPiAB8KfTfTFfMh78%20uZu7hYy4lGgBCGAAFel/JBTircWS9x+2vqb/ANpZ/MSVABJKW0BRLXv99FkmCcuZkcawHc1oY5FY%20RqLKuht+yjpVrPKJcjI46Ju6xG+zyLl3gST9ulV0rWwry0MO49jD6QBbaHElUNyqdb/vpWQm7Gow%20YwQUB2gbfEX0HSm0ngTmzLsW5c5m5x1J6kXsl+vS/wC1jTMflABtA1UqSSUUrprTuFxJ+MHbonNB%20IIIBS1wqW1v+6p6VqUpM43zeS2bl86UfKZXoxQCWj0H5T5J+uvRhH+JqrounYGI2Phg5wDZcidxk%20faNwaxRtG1SniT+NbN4vwXt401wZnJ3xXs4+Zc5I/wCoVapcdrXNRFFgE6DSvLuZ3NJYgGnovyWu%205AFIJFJMpMZwxgK1CLlwHS5+wXpR4lPFhQsAQhRtU2sEvc/dVXEQvbzXPw8nKe0B+VkzSL8pLQ4t%20ba+rUsab011WpUuS4EoWFxRzih+dB9xVPLwpMVkTPZbP/wDbuIUI4ZUbiNQu4eIsVFDWo4f2R6Qp%20HceReX7ew8vkMuPHjZC7IynnYCWqRI7VxJup8a5HuVVcTf01VeQjkfTlz5fZy2Px4mAsYjgQQLEq%20P9WoH66r1JaWGthXKu3geOlZKyaVzAyZzQANA11k8DrVLds7kvZbWBs3trBD2luc43UB7Pl/1Wsu%20v7KqO67VVeYnte4lGcVjxcc8wOBmaGtdPo1z3OB3OAJ160nuXuL03F30EO6Uw+3uELnNyXx5L5Pc%20Ta1xG0ohCgLp1rthP+LdUjm6X1M6D2fyfZOJxn5nlpgeTzg2TId7ZLvWFYxmnpYLEL+FcXcTbdjp%2024WLHg928MIpMfB5QRRRj3GMLjH7bBqFTrqaz6pN8v1r9Q6Elpcd43dnITMBh5JpjB2RyvFnJcIb%20KEQU1OVvYKUI6eIm/vbP4yd4my8eYyHcImXI3erQH91P1ZOv1F6URxyPffIZPHHGSIBI54ZIyd+w%20kBR0Knxql3HMl9vmyHeL3piicvyyx+O47JH29z3SU2AC5aEF6r/Uml9heg7lb7p7s/OY/IYhkcJH%20knGZGdzWFgVvuaNCJ1pOfVpWf1NNjaXUsVXI4xlc7zHI8m3+45Dsh0YejwGtaC4ISrfmB6V0dnJp%20tXNu72lrbOKridg+mbmn6cZftPAa2Z/uKgAa0nyGnT76fcL+V34HHB3TsjmHEc4T3Fy3KY8gglme%20cfHlTarWm6FHD1Hx+2uR7jO2adkmXNnf2ZA+GJzmw5pa1rsloLiSFRwFkGlOO++PM5ZbL4ci3dv/%20AFfwcHgpIeVMj8nGcRjNiaS6cotygaHOCVsu4VjJ7cuHEjJ/qTLkY2TicZguycrJyPdE4kOyMPaj%20W3QlzUun66znvqqZ6fbfjZW6pVXtKr2/l8rwDZ48Nsjmn3fel90/8yRfceVahf6k+z7awe91cdTv%203fxjurcNPnWBeHn5Ieaj5AYrxkQSB7Y/dDWN9sEJ6m3JCjSnt7rVnXsMdz8U3hVXuLBjfXnkOLxm%204X9hD2tLnmZ0hPqcdxcCBcNXrpWy7h44GX/EO+pB5/1x5TMhyME8XC0TPeZXb7rIociCyqaT35PT%20QIdgln717Cgw5zYsiBGPaYpmua5xsm+w8fKs01fFzol/Vp6fozvk/wBR2YeRhZXJcZ7Xuw7R7ORF%20I4AoV2KEbeu6O5y+54r7d3syifVvu7jOefx35QPxxBG73GTBu5SQdoLXOuPhXPvTu7I9D8ftJPFf%20euJRuO/JOmD3vQxXkc07tqGzgCRp4VySli4+4g+st3bWLx/J8jLDh5DR/SMkp27SFJaCOmo+6vM/%20Iy9GCdqrl5i7WzbsK89ynF8JyD8OSYTbA108ZHrC3ARCnS9Z9tsy3IKXG1fY13NyMXniMcPuft8S%20tnxZI8adpDXEehznL4pdN33VtKO7BWveuIk9ub0F83+y80173vjEjbSyRFC0n1XB+VxVfGqjvTjr%20evsZz7dPCGvH8HHh5MeVFKybIaQ6KWUJtAADfUvmp6aVpH8i7YIfZriWrtnmZuObl5bnDk+dnIMe%20VIEbGU9LSFAKIteh2m91cMnJ3Oy48S39td2cjnvyI+dhi4/Ix2+4wkqwtHzFbdEX9F7dvcV3Y5ZQ%20ZPMyYMgNdFPHK57Q5pabFNbN/huta9UXexFpCUmVj/nI4nZURlc1zQQ4OIcTdpK2Pl8TTha4pPBn%20lPTxU8peUb8rAdSTcNI6JWfdW6TTYzLUp/bfcXFwcvyHHybo55J4xDG0An2/bCyONhtC1zdq7x8c%20m/cLI5+p/cGdwnHYWbAWPyG5e6B7vU0lsblsD4DxrabtEnaipMlezuQlzu3cfkZgwSzB82TsAaA5%20DuIX+FD1uP1rb0FJXlYtX0WdG/sSF8ZJa/LzHAuJJ9WS83W63vSepoXqkByr60zcQ3M4qDNldDPK%20yUY8gVFDmqqC1upqZbijrxIlFM5/n9048MOFjx5BZ+TAdKT6nldtkT5UcqIvlXO+9WqqvuR6VvYP%20uJ7u/O8Xl5oc/wBmAl7bI64UoqjQfvSvH7z8rvQ3FGNrvwPS7XtYThd6oYcj9QXz8e9mKJcbKc1p%20hmQDbcHe49E8DU7Hd945Wk015WNHsbHBZOa839We+uNnfhM5MvhliIkimja5zQ4n5Hp6V219DBu1%20zHc7eKeEznzI25BkY0tIaSC4H+F51JK3++tL15fAzfKr/M6Mz6vdwtlhyYDHsxcRmBC18al2MLOe%20iXdWbcrPNOtSVFcETnJd8HG7YODiObiRZ+KY3NEZaHNkbsLzpp0Fca35Rl03wjr9CMl1Oq4lb7X7%20ah4+fE5aPK3ZePI2bDQbYiihHbv+I66XrDc/LxjJp8PA0/xtxLtxvOZeLke9MgkEjpnBvqVSpudx%20uqVUPye3VWMJdm7NaF0b9UeN9tolx3qm2UNQIVBJaP5VFq0f5Xa0quRl/gnYiHd4QRc/yOTw0xbN%20yBbtdl7vYjKAPNvFLLYa6VEvye1F3Tqxs+xk4WK13bwnd/cfMHkuWdiHFwGFkfselxY07ibqT4i1%20ca/ObEsXd/I22+xcXnSq8yPye3OfGR+dhMhJaSyf3Htn9oBUcXEjpettv8vst2TzXxMp9lJZEMLh%208ocgwZvLTyQ5Ld755clr9hVfaUlAfUoBumldHrweU/Iy9GfEZ8p2u5nJxew2ZuPFO2KR0jgHEu9R%20dEgKsIVU++n/AKE4t+FVSrb2s54Fwn9rH4P2wrpstxcE/wDpsIRXWKfppXyG5OW5vPwf0qx7EVaK%208iW4DjXN48TSO2ukdv221X06fHQ1i+/lt79uWvwv9ydzZUoEt7LCBt0KkgeOqEDSv0LVJ8z5KSy7%201+xsYQqOFreq7ruvqP1CnJrgiFmvoM8rkuMxMpuJLMPzRA3Y4aS8NGhIA8lpuyVyul3tYwzlePJD%20t3psdNpQkeNreFR6sdXz+g1tSbzobszMNzN28BpXZuCA/AlBp1/dR6sXVffGo1syEBy+E6dsXuNb%20I92xN7FK6FAeqWNCmmwezK1x8WI4tPpLepOlxrWijwM2uZjY3cUACnoCfgFK0WAxsBHnpbRfspWA%20TcwajqdAp+/4UWJYmRdNNAR+2hJAakHyBP7qZIADzHx/GkAhnPZBhZOS4hoihkeXnoGtLjrpprTi%20rtDRwJ0we58jkaHvc97nKvqJ6p/F1WvTSxbWvkb3Ok8G+Xj+1IJoYyMiGEuaA0WklPpCJ4adfOp3%20pdML1yJjHqnhkee7u4i57X2mH+kahullFl8q8R7zO9dnFKyRJ9p8rz2fy80WXI04QiL42hPnBAAK%20fCtNvcb1MO62Yw8Cwsb65VIs5CFVNVsfCtkcj4CHKzHG4zKnPpeyF727AiudYE7blVppZFHLsIcJ%20iHG4fCg2CMiBjnRtAs543OU3XXxNA2x4WF1nD0/s8qAJfsxp/wB18SR/+qiIAGim/SguP9kei6R2%20njnlu8OGPM8hHBi5TmiaVjoiGWlDyC4GwIPlXE4nVFuxFZX1C7i4jHx3PdI3AesbmTNDg47QSAde%20p0q47N8g92z8R7jSwf2fP5J0YczHyvbY1Dd0zS671WwCVMom23u24VX1IKfkXzMEjeKkYyF3uyBf%20SIgUs/1L958qpRE95LQdYObJnRPfj4AY2JBPM9yBxLkAah+Yp4fjRZKq8Rdbb8fjVzbvOGRvBcdF%20kNjbL7j3mNhUhpRLg7Qu3r8a9LZilHNVxPN3JfydhpwreUyhiMxtjI37hCwuKP2ktKH+FQLfoa4N%206Si86fKtOZ27avoWvK7ezzwuLi4UEbuSmeZszIlkBPqP9NsQcQXN2qXfh5eI/wAkut3eP2/avHu/%20zsQHbPcrscGPIhcJF/MNsjTcOTrpQvzGynlk/wCST1GOFwk8IMcuR6E2qwNJQm6veC51q2f5WDyl%20VfuR/kapD7CgyseVhE23GcjPa0AYAiADTaU+UVhufk1qlX66jXZt66fqWOWMcfgSSTziXa724C1r%20WtZvNtyqCg/Tw8qP5Ke7LoStc6/8qSvrYrnI9wY0TIWktxsXLL4ZIgwueSR6U+BN/KvU7Kc3/Z3d%20VzIlBRd14FR4jE452fmjks1uJI1u3Dc5rnRuO9fUB4D9nhXtbfcem00Yd3tOZaJe9cPt7s3O4XCn%20bnZWaXe3ks+WP3bI4BFuU+ynPuPUbbwckO3cPHJD9tZPFN4jH4mcxCSZwMr5Go4SFS7a703GpXWs%20dyT1NWsklLkZ+DlOijwGZ2FjkhmQ9w90PaFKNvuUeSVW3t3V2YTkM8PvJw5UF3HZJxJGFrIBt2iR%20xCPKL6TWktn+Lb5cKrQqDvNLm/gyw8dC3Gw2SEAzAEkjYbvVwAJafWguTcdK4nfJ9TBWis2+GHz4%208MefmbZWUx0QYyVgdsYfaabANJAbornAEH4r8Ka1xX6eHkU4R9v78v1+pFOyY3ySMZIVAuxpcVJ9%20W12trKpP20dVrXqvP9CnaTerX/yvXwwRjpsh2Wx2Pta2MmZpJcCjV1B/l/ZretIrNlVI591XTxrn%209efDmQ8BsS24aNzygATqVI1X8KpyvqyHfOPpkcTHc4uNiRo2/l0N+tWpHJKBU8rOkeZGOax7pS0y%20uLdxSyHcttvlauleVV7TzJwSZJdrxtfjZMoj3O3AKStv+I361jvHT2sLZJaLGjbjSe0wMdIoJB2j%20c6yn9dZ30TL3107bLl9H+M9nluSylDo4ceOJsbih3PIcXbbGyqP3V4P/AOl3JQ24rm/len+jwcv4%203MmV7v2F+T3ryD4XqS5jFax4O4tRw29FaPFDXqfi7/5lXHHszjHsOXvp/wDsZGP7VyJN0ai+3bbq%20T1Qmw6IPjXa5rp8q+/kZR6upHS8rtHjsguxHnbNPisa97QCwywJtKWUL81fLvvJJ3fBnvQ27RtqU%207l+P5FxihxMkYgxoA0uFi4lxBaflBBSvX7NLcjeSOXuZODxzEsWfn8LlcOEcg+JjPbdKWLZrxYEW%20Pia2Uul4M7dSy6+ZYc7mMn83+XfkLiyvHuOKpIAE9KdSnWuiTusnKlZ4LD2RnSAvgfAcTMymhmHk%20OO5wjdZGAaFy3/zrXbfiYzSvcdcp9OvyEmTjDkXwGKH848FQC7chjcNbg6f5V0dTs3VfYx6XyFMD%20vafOjh4WWb3y9oZGWRbHOMZ0UBCBrauTc3201Vjsj29noVfkMnhcbuPKlyMSSfLaQ8SMcG/0wPU0%2061EN2S0KlsqWol3p3jh83w8PGwkfk8RqsABCelELjrrV+pJ4kOGzGOUP+J+p8GDxeBx0Mcr/AGoD%20DM9rbiQAtJKhdKPVmtCfRTO4/QaWOX6Zca9hLgXzq4ghT7zlNwOtdEJNrJlNJPB0GrJOHf8Akhi5%20mTk8LFjOYFjn3tcC4orVdZNPjXF3c+m3LUqMW9LHGRx3IxtMoY+f3SS2VxDY2saA5CLuRHfMlcOH%20j4i6fq9fAlsLk8LC7X5HEfkQDk5nj2ILFzwLesnaB42rk3+zc96E0sRPR2pJbfS8OtKuMG5Mp4+R%202TDG/Il2zPnLlR5BJbZNV8K9H05XVqqkckItS8P1xWCpzHNZl5M5bE6EhrYIJmCQPDm+u/Q2r1Nr%20oad1XkVvKV+JXMdzRmygM9mN4PtRKjdqhT6h+n3VTd3jnVfLJGbZHTGzOD44p2BzSgdIlgTYeo+S%20rrT6vjXu+zWhMar2l39nEm7UY3JaXCCIBwAK+ly+g2uv4V87vTkt5eNeJ7ENv+OdBhx3dT5JsfBw%20ijJTt3ytBcLOcfL9VaT7OF7pB6sXLFVYkW93PPIPjkwpWYACvkA3kPQDQG4sRSf4+IvWimrPA7Pc%20mCySYiOVrYLyPYzcikAhwaE3fC3laudfj9LO1Vn4Gz3dtyxfj9MCEHcEwyjFHgyzK8yMjLPm26i5%20vqPxq93sJSTSdr89TN7i68/clX/U9j4ponce9rmtLSVI2gtRbIqLqDXkr8DJSv1Gv+tWGD+9Jc/g%20ji4OHKzL2tYN6bXN6lpKtvqK3h+IcdzqbvEX+lNY1FOMEzA/3JAQ5wCuaXIERHBPEG6VG5P+S6cN%20eSqvZooJrz8RZkfHkskf7ysPuMjM28Agr/TaoQWQN8q1XcztZr9PfcylspP5k9ncFkySceXvEkWU%200OYLt9ooCiC7ydT00rTurbW16rWWqvX0y25dU3HkI5PPcviZDcHGmjgijRmwNa9jQDtDS7ovn+uv%20O2uzhvLrau/cbTm1gmG958Jx2LE/N5WImIe37LmOEzkHqT+ZVRT5V37fd/kP6wirHBu9v29+qVyQ%204rurgealc3j86FzZvVjwKWvACNd813Ily3p9le5+O3+4cH6y/l8Dz+824L+mce8rHfL4IZuVfK0F%20n5Ap7atKOChCvzOXrXdJW1OHbh/P21WTkeVM1kLZYJXxN2D2x7rkRoLiNQ64+yslbSqry9N3qq+c%20z3hC3F7Q7UgEp/qY02Q6XeWlHyWDlOvqHStFFN2aJb43qveQHak7Je6uJYHu2jIjJR5uWuHpQ+Pi%20BWnQY7idqqvI9MzMPuOsiOO7RAQTp5aeRqnE4mjUgqqEbhuBNzc6hNaMiuaI4qikoXOAHTx/GpsC%20RiRSC4gr6gBqNP10WYuAi4INC0iwHgSmv2UxZMOaRYCw/TzpWYM1Bubjd8V/Gi2QsRXd35iLtfkp%20IopJHCLaBGHE+sgKErTbVpK+g4pnEm4XIE7WYc/uWG325QCF6+m269d9rI2bXDQ6i/Gkg4tsZhkB%209AbE9rmuDWNRSoBGn2Gse8leFk71S+hXaq0r6ZIqXALw54g3KDruC9R4X8q8JJ2yevLcyP8AtBv/%20AFORMYAxgaCpBDtSoDT0rp2otM4e8kpLBM4U8OTJI7HJILiGybHNVwAUt3D/AArdHDKDQ27i92bj%20JMSMpJKWMc23yFzTJ4Ek9f0WqrUmEcjkZOK0nHEjd7A1IwQ0ta232Ar4U3Fj6HqLNPuRF4cBGG+4%206QfKAE8DoFqLoFBkp2TNBN3VxXsSB7fzcYcEFjqdRofhR1JjjFqSuei6DtPCXLNLOd5FsUp9w5cz%207G4cJT1cvj8KxlK+lZZt021Vvsb43avIdz7g/NbDHHIGbZLvc9yB2wHVAhK1rCHV5qrmc59J0nH+%20m2VFwGZxg5GGXIyZ452yNTafaCFR4ih9vxIW+Msn6cd3Skww5OPkRTsaN+8s3KRcsT4VL7VrNy13%20QvL9He+oGbWHEdG4t3e1KEO1COniKyey9TRb8XroQvc/0476l4LGEuIf+ne8TyyyxtAYtkJKEV3b%20TjGNr6nJO7lcdYPG8dw/AYWS7Bjc7DjkbI6Mu/5jj6nerauiafb4/E9z+Qlub7hf+OlVjkfQ7Owl%20Bcx3i42fPhjkYMx250bnNikYN2xAC0EaElvQ3rytzcjGfS1xr7HUovpwUGf6n85HPI3GihkjKj1D%20YBcsLR0+0da+hj+I2bJu96eefjc4ZdzK+NK0N8vN7/PFy8u/AOFjQkOe98BIMTrh7T4Ba6trstpL%20Ga4mcu5ux5HyHLyGKd0sTFa0ugkcGgNfcOBHzhyqPxqZfj9p8Cv9EkiX4l0mZmyiTIikwGncYow5%20Gpfe4kAKjUN+teT+Q2YbK/isv6HVszctWMu5cWfOOEzjG+7mtmBgZEBuJHpNgjQT0/zrX8VGan0t%20EdzOPTe5WOL4yZuZzOLyrWx5RDfy8MjlLnMcVa3Vqpe7h8a+k3drqt4HmR7hvFxly7saPGGG1obK%20Dune1weSXHdo0kIVsNKhbfT5nVt7qarmZdDyWN7T9kORHvjJEQDydwCNa6w3D8KJRVVT8w6+uWPk%20XiLgOYyZI3RQyGQDa1rXhrfUF2629SotEZpewre2rtt1VYIuLtD6sv5uNjMTIPFzyuaJmBjmbAbs%209JVDpWk5q1jDb2Up8vpgtc/Ecp+aELcGXHLQRJg7S5sjGptmZIAm1SfRXG2kvA9ba7m7V/6x8vgR%20WfgcuA9v5Kd0j3XAjKbS4JscAjXDw0T4moTTzXt15cfmd73YvF817VjVZGMseREZGzCSORzNrg5p%20iLmOUgEJuVpCLbWnBVqr8/391wlNNXv9q/e1iPx5Xx5kjvTvbBI15BujwD8yn+FyC/RetXGq5mO9%20ZVWORFxRvUtLXE2a0bQofZQSq+lL/sWmml5foTJJeFta+Q7le4sJ/nC/AorgftSwPn50RtcwcbJu%20q+XtKRlO2udtG1LBxBXaEC/EJ0rug72sePuyuWXt4yu4929oIaDtc02JVSLJotZbup1drJte0s/a%203FjlZo8cPcxpaX7mJba4DS36687u+6ezG6War9zTf2utOLwmjoXa3bTuJdmz4+Q87gIvblbtaCwH%20Y7Z8xB3E2+CrXyf5H8m95xjJaV7LfYO17RbeU8uvb4Fa7m7Vx3SZPKyTudK6UPlia3cGuIN0c5wa%200kKPNfhXrfj/AMlKy21plfFcqscnc/j025V+hGCOFYWyNe0qxsdidyEHaPhpevopS/jd62OXbTvV%20e06G/eeTa4nb7OO7eGofU4hwN7nr0FfDyt0+35VzPei+RR5w575mOjE0UzWnc4oV3Dr1N1869/Y7%20xQ20ji3oXkR+dGxvIPfu3+0G7nm6bWgLY6ACuiM75qrhGONbjnMwGTSYPs7ZY522ja1HQuXUr/Mf%20wrvbTVjhad3cmPyb8XIjOPmiT2i3Y5oQxuBJJ9QQgeQ66Vkv4vN6/XgDTr9Szcj3HLm40YPtZLcm%20IhmTIC10cjSjfQfhfwrXrsmuWK8AW29Su9r8S93cuPDkEGVjXua4eq6o4C2gtr41in1Yqq8t56CH%20dPGnG7iz4vbOVJIY3uaQR7W2waVv06Cn12JS4lWyyyNjUiIO2RvvOCgkG7bLp1rWMh25CWMHMZC+%20KNx2M3e2gR25vqACp08afWLpXE9SfQEEfS7igUXdOqWCmZxP4117X9Tl3X/I6HWhmcH/APJaV0XI%20dvvY/bJsm9r1BvqDma9SvgPjXH3KV03VVydKN0cgi/O5MDZ5HBjo2vfMITuDmj1HcfSvinj41x9K%200f1Nejq14V+5RM0zZ2XkZrz7AmJLH+O6w0/iNdkIJLBSduZPQ965MXHRYEnE4udJGPbGRue2VxB+%20ZwCXH4+dEtuLWWaw3bcMkS7u1k88MD+Jbxr3kj3vWjiNQjrkORK06Gk7Gi7lPhgtXNds8fynbkvL%208N/02RBGPzUB9TA5oUhriATZXEVhDdtKx17/AG6cOqsHPG5H9IzmRIS5DtaHBigJvJB0vrr8K9Bz%20TPHUWkdH4gRZHbLXXcfy7273KgaFJv4B17fbXzPeyfrqy8a5HsbWdvL++Poc+48vZlMO4tKOY9zV%20KW6E/CvWlocS1G55bObhiGGVwZ7r2nIBcHOaPkYXKNP08+qMbnM27slezc/kzLlOblyhrEO3QFxu%20psSUB61nvqx09tZys0dQxIB/tnIz8qUT5TI3Ssf6WuZdR6bfE9elc9m/A6LfyKHz3cU2Xhsx8cNE%20UZ9WTt2yOcBbaQL/AHVpBcWY7+7yWCAg5nk8duMyGUiMva9PUdztyAHxRb3/AH1UoqzMtuTudXYW%20mNXubuc07l9PqDUc4sRSqhBXyE79b8/1Pd27OKqvuN2YUQyHuYwbk3bgQr0X5dPAaJQ91tZ+wdOP%20Emcbmc1uRiyTTCXHxA57L2AHp9Km6LUdxuS3IdLrzM4bSTuUjnuRypuaeGStGIW+7IQit3FXNB+N%20e7+P2VHbWMnB3U7SZXcR45nmHz5cpmcwqGtBYUDk2ldwRBXuJRUdM1XzPMfVc6twz+HxsfEOJxsD%20clh/6aVw/qMJXcW9T4E1Sta9ePmYyhd2dcial5OCSB7s7HiyJCGMe+Qbi9zjoURBV3sZxhnxE/b4%20EtLGcVAWRAkuDG/MgBOmlulOMYjd/E3ys/iBC1uTx8ORFiBseNHJGC0Mf/AwJZDc1SaWBO7Vxrgu%204yYR5LePxopgf6RDWgNcAA4i1hoBTWg2mnYsEXOPke15hO0OLXkH1JbUJp4+H30JJmbVjd3JTCSK%20HarpQdqbfQE1Pgo+81Vh2HbeTlehbG5zQHOjZ6SSQVUk/fSF0g7ksjbvEa+5q4gHcugch6aihAom%20I+TL2+uIuYNwb6RdL+C+NzTsBk8sd7I3RF28ixDdOhKCnZDs9TLuWxoo/cMW0NtvDQSLAbSgF93W%20iwuJhvMBkhYNzJD6nNKaW2lyf6vGizDzMxdxslDpRf1I0loJCWu4BV1pNaq47W4GZebY8hxHrCgN%20IYQEBsPj5GiXIaxk0j5THu4wsaGhNu1gJU2/hOlSoobkzaTk43KxrI2gEXAZfVLp9lFgIbubuCHC%204iVzD7E0thKwNCEtK6p6k86aQWuctZzRL3kuE0pKF8h6qoHhZLim+l+VVpwtxH0pA7lxAwzAbjI4%20Fy33N19TgAlzY/oR2qvhz9wdKEO8u6poezYsDEc6HM5KcOzGscCWwAkMjKDq/roaya4Ovtj2WNUl%20cYfR/m+Yd9S+2IXZkjoZeTx2uhO1XNLk/lKgXW1qnpr2fMto980EHiru/sflMD+6cs7Oxsp7MiWR%202FC8mUsfI4qPHYNRXGpq502dis8fy8uCYZOQx52wybnwPbu3gFVB2oR/KFrSTa/qwUb/ANleqpF8%20wcjiMzh8jksfJzcWHGfGzJik3bmOeSWoPg06eNZPd3EUtqF9BJ3I4zJ4m43OzsfLaOMtJ3DVA4g9%20XaUlvzYnsQ8B5DkdyHLdis5dpkDRJsc9HNXRxGioaf8AokkT/mT4VgR7g5but/bk+FPNviLt7Hlw%20LSQNrk+X40vUk1fNiuiOuLk/xLJJu28KN7i9xxWsJTYoDUKA3Uf518D3D6d+X/8AR7sP6qq8hXEM%20sWJI93r3iWaJFCsI8AoC3KXtWc/5SXsXtL4Hnh7nvynkjcffLgbkfPe96/Q4pJHgtXZ1zmfqnPld%20rP4GGBzMVsHtNMhG1APUEAbqtqqCjxqvbnzNVtWzVfP3HL+a5R/9vgY4NBeFbG4EEMbq0AeoD4Gt%20NqP8sk70/wCNlX2Lx9GsSH+3ZmWGOSaZsT43H3AGoLFxsQFI0r5n/wDR7n84pYZ1fjlhjvuPmZe2%20ecysrD4+FspBfBNMfSVBdtYyM2cHefxrv/AzjLbT1cVVWMO+6oyxpI5pzvMZnIZhzMgsdOD6mndt%20cXKSL6/417y51XM4IKw8yNssORn7oGPkDGtixxuY0FFaiqV0N6xeuTv7f+jdak/HzuLH25iQ+w1h%20wnOZiiMEbZHN9RcWoXf6VvXO79R19cFtfxX8udfAqeVm8o6Q7psgPcjXH3HsQ9QoOvwraLTOCU52%20sxSDlu7nRST4XI55hj/5jhJKWsJ03OXaNVq/4rGhCmyR476hfUrAkh9nk8mYQuMsbJP6g3DVziAp%20ASh7cbWGu4le5ZeK/wDIHvjHfCzO25kTXq5vyOcbelXWO3TTy8axl28OWhou5WrtVVg6R2/9aexO%205jFj8nHHj5eS0CR2Sza56CwMgA9PRa559u0aqcXiLLBn9t9jZUDcl2NGcWbbA6OHc0uau0FoYdy9%20ftpO6dkU1PgzmHP/AEh7o43lhm8KuVwzZA4YjH7po4yCdpBKuCdT+Na+omhbU8rJVsmSGPIeyYGK%20VR/Tc1zXNFw3cNuieVZ9XKvkd6tdXfP71qJHhe18ho9zM25Ljt9sOLlc5S4NOm3w8qfryirrSuAt%203Z2nivnnn5aBG/hcGD8vDlxkbD6nW3ekKfxWru2zPphFYayWHtvlhisbFF6HsO6RzbueFFzqTsap%20olCMo2auc+5HOGdL7a96TFlk3EREPchISzS70lLkmwvXyX5/ajGUUlx5fM17VtJ31IflXCfAmBc5%20rySXbRt3C3zlC4aeI/dr2vZSi4ysmq0J3t3quivY+OyTNhd+cdC9kjNsW4FhIJUrrfr/AIV9Luzi%209t2eTzduLU1xRdHOa3ls1AhGOwONgnU7j1QE/qr4mbbStVM9yLxk53y3Pu42aINxnTSKHbg4j7nN%20Gnjpravf7b8d6kL3w0edv78lNLTUT7gy/wAu3NyXkOlADwz5kd0HRdbLf9vX2+10vp5Dlufx6iR7%20fycXlY2Ni3iYMb70TWk7Tt9IQAJcC2h/X176cHk5Yz6iafhz+y6T3XMVvpMzCHb/AFAh1tfOufqs%209KqrF2EHcPnxcaHMDppPYcRsBJc96ud6zcXHx/XTw3YvqtXIcfSLlsrkO8oYMzFfiugx5S9ytcHO%20Vo2OaWuQda6tvas71XAy3dzBY+f7b5rl+fzZ+BLMiEOEcjpniNHhCW+q7kLghW9YzSbzn4lRdkc7%20777d5PgMXGjzntY+X3HxMbK2S7iNUA2/bV7ckym2a4+Hyo43eIGGOJt3mQNe0SRkk7E0Df8ACk7N%202Y1KzPRv0Bmjl+l3FGMENa6ZpJ1JErlJ+Jrv2VaJx739jolamRSPqLxHF8lPgx5uMzILGvLPcQAK%20Ro4nX9L15/fJ3jXI6e3tZ+w593hwfB4XbmVkQQ48b1awyRbVGioiKnWuGzdjpjG5wqXGh9mP8sA0%20tdtY9wULdHBvXxr0oywYON3cvOHxPcTONiyZYsHlGyt9cnsthmXqY5QGhx/4taxnPiOKWliA7+7c%20HOdvwdwOllw28Q10GTHlhsbrLsbFG2zneO2r2dy2GOSIPsbu3EwWOfmDdjTsDdrgux4sXbRdCLWu%20BRvQzg9Dtu4/g0+XOvcUvMjME/I4mMr8DIkc/wBFmPYSTGbdG9Frpi+Z589vVnRuy3A9t40O5oeW%20PawG7QoIJ2+VfO/kU/VTrgentN+muSrX3UynYHBcjl5zpMWMS+3K5hDXBqbV13aGvSnvxil1Oxxr%20bbbsMc7tfuHAhkOZx00bTI+UqzcHNL/5gCo+P7q7Nvfg1ZSRyz25Zuh72cyNjcp7f6bi5rDE5QhR%20QoI8LUb0njidHbRSvcluVyDHxrzu2lGgvJQE2sdOulZxi+J1zsk+BA5WZNNJKVJWQljXDZtd0IHg%20dL1qkksnmyavcxk8znPhggPqxYUkaPSN6/znT/Cl6eLFRnZ8zqWFM6XFjmDnJOFDW2JRoDgCQAVH%20n+uvjd9Wk0+B7sLdIqjiSzcRCG+lxcXho2lrXkaWBATpWb58S9dKq4hnb/Ze7+JoDg1wDHJIBoAT%20r5/bWm3bqX3Jm7aVVZKHyMDsXKyGOAHuQva0qb+3a/ibV9L20+qKPI342dyL4HJdHkSRKjnBoZcI%20NpVN3j8a9GcrROOKyXfG5h7GwuMgaIysgQNJctidv66y6+Zb2+IuecfKrPdUht2gC3XRCBqPOm95%208A9Fcqr6ig5nLZtb7oMewgDRE1Go+8U/WaJ9FVVcRrlc1ll7drxGxridrSAVDRoin9E0qlvsPSVV%207B1x/PZzMFrVuFIFlCn7aS32hPZTeeY8/v3INgx3M/ouaD7bwAdpeqkHRXKaa3mn5EPYQ6/3RyDc%20jd7exzY00VxV3inTwQVT7gS7b2ire7c3a5I2+prgSSOqm4aPhb41X+kf+XGpiTuzJGE5rAGBrQAR%20YEp4E62/zo/0+Af5uNxaDuzI9lgDWoQvt7tregsPPS6U/wDQiVsYyzLu73Etc9gMgB2J6gAS3cLn%20+IePTwp/6Bf5zE3d8skkDJGBsbXlWAo9Y2ghCU69EoW/i4nsCUfdshnlmexyzCMOa07ha5QEHqeh%20H7x76F6DM4ndXpDyFje8ucvip1KED0i3mtP1rYEtl8BZ3cnuucJyHNjJBBClHD1K3QL4U1vpB6LF%20m9yRlWlxa9qhSAodqFF/NKfr8hLafsNT3BGS0OehahKhLvPVV08qfrxQltSK93rzzDiQxNILXF4e%201oDXDUgjQfwmktxNt1yK9NrwKdhZMwLYohG8tDS8SOcjrK71fd/hTclf7AxTNkgfPshNn7y4K0tP%208KusV2ommtP1EufCq+YlC5IcTkcArZuVfBDj+26OQTkEENIKbAv2p+ysl4VXw9pcldWE+y5+2sj6%20zdpP4CKRmH/coBI15tu3btzBfay6+P6qtNuq/dD6WrnvKpJOY8hBjsme4wQhyl21zA7dcpcr9wte%20vFf9vadyd1kbCHHd64sOEo4e60RhEcpboHXKpR7RNI55zEOPH2z3AI42sYeZHpARWiRgH2IfH7K6%20oLBMtS8u4zhpo43P4/FKsjEcuwAWYF0Nk8a5up8y1Aw3iODf/SHHYkihHFzNXC2o+NqUndFJZOQf%20WPi8OGaEYWNHFjwEiVsaBjCV2kMF/VcL4/Cvd7LMMnm7ztJll454xuJ4KT3Gvx82ByTJsB9iNXp8%20vq+Ar4Pv/wAVJTk075Pf7fulKKxYRk5ADNfx7nNa2f8A5b3klzdzUJ/1XNebHawpnY2UTI+kk0b9%208XMQkSvcPacwre4CISddEvXvx/Opf9LwcS7Nt6muV2LliOQMzmPbEWlzNr2AsJABaoU610L81DH8%20X9fHJrLYbw9CB5fsLlciRhxp49qjeSSP9SIQifBVrrh+Y2+KaOLc7RyzFlx7H41/A8Vi4c7h7+5x%20le1wDGFzyN1r6fBK8D8lvLfm5LRe87+2j6cbDP6i58T/AGiDHK6RWNaXBhDhY7SShXUIa9H/APPp%20xUlWhyfkOl2OY5kjo3OgfGGzKQ31fJewUHwOtfSHlxyhVmNLhtc6dhjcQA0vBLHLdEHwrO9zu21Z%20Er2/xWXyjoIsRkkuRG4uhxgFLi53RfBdfBay3Jq+Tp2dtKN3c6djfTnCyJ4uK5WHIgbiPBy8mJ6i%20aQgO9LXINrfiprKM+TMd/ecrp1VcCbz+2cbjeOn4LtdjYMLJY3+4RSO3mZwIDVc/TqfgtCk9eJzJ%20cR3L2r2dxbcfmP7Yx2diGI+xG7dGZQE2CNyNc2httWEtSh8t2PH3V3R3Dl8ZHFxz45gW4AcrFW6u%20aUHqSy1sty1qqrkuPAq/ef0y5LgOPweRyImxQ5b/AGpi2+xw9V9u5NFtVw3U3auOpEosadp/UPuv%20tSRrDK7OwfSuLM4p6bNDX9ETTSnPaUlg1hvWwdt4L6y9t53FN5I+6/KZI2KWBAJGErdzk2uaNv21%20xz2XGqpHYkp/1G/cfMfTjueJeRwJo8hNzM6EI9qN3AuQI9q6/tqUmq/fw+hThJPDOJchiTYncH5R%208kWTg5Cuw8iJpDHxh1tQocEutdKiunxJi2ppPn5jXkseSOaONp/pvI9SqdwHUeFqNu1tCt7UfR5U%208GW97HAtaWt2nUC2ll+P4CmsJOqrwItiqrQ7J9OsgS9qf3GUuawe6EI9O1pPqC2K+NfI/nO4T347%20aWlvfXkdu1GVm3x+RGt7pxj/AE2KSARE/wBLgjXIgSxJHXw/D6VbScUmea4rVajWLlMnJ5NkcHHx%20NY6SMPc2MOawEjbcBQF/S9cfc9vFp5yuP61y4GUd6cdzpV82r581gtE2YyHkOVeHENZA3UBzWhAQ%20S6yX/hW9eJ6Ds46ZV+f1rxPV6tDlvKjkcznC3GxpJ3mRrVY0uQC2nUrfSvoO3fTt6nLOCckyV5mD%20Iiwsr8xivbsaAWFrjuJIK+N1/S9X2yS3NeJnvtdNhP6MZPccHeEwhwXOhkx5P6U0ZDHEEIpcCFv4%209K7u7knG9VVkcW3HJ33HyGuhc2TEfvaE3MbcPNw7RNoNecjpyI48GLj5WRLj8dmOdkKHkrtcQ3ad%20tihT5SOtPqSzYLeIx7O7X4ji+4ncjix5s2XsmBhlDdh9xwNyFQ/bXT287ySM91NRyMM3NzcbOz3y%20xhhGUXlu5npCIQ0FfHT7a55O1uRpHw1Ob/U2WV2ZiyOYW4z0ZG54AuXgkW628K12HdeI5Fv5LKxI%20+3s6WQRNl/Jgwztga1peGABgcEFinWsXNdVmQnw418PE7B9D2xN+mfD+07c0sc4khPU5yu6N616u%20y/4+/wCZy7mpe61IKP8AUjOwMV+L+bhL2ujefc37AAHNJCnxrzu+tdHV26vc5T3pznHt7YyIcOMC%20Fzi4ku3KQlt4Tr+grhjl2R0LxOROiJY5pduBBA3GwaAVsTqTrXVGTG1j5lj7V4zncfjG8pxfIStY%20XkTYkvrxpHNcFYVVzPiK0m+ZhYmuMiw+ax+S4/KxsjHnlBOTjZfrixg8JvgksrXKv4Vm1ZmnA409%20+Dj8nm4PHpLHFKkbybZBY5HOavyg12pXiLbfS+JZe6mduHj2f2GN2E+TGP5jEkc149/+La4dDWcb%203OlbiUWuY87Di/8As2M+RqvjkdGx5Qi4W/Xp514f5Kb9Sxr2/wDS1cSu8f3LBwnMchjzsdIwSu27%20AmjidDf9Oldu72i3oRZkt1RbLrx/d/EZh9vHzwJC0AxyEh11+Zp3NAHQi1eRP8fuwd0vI6Y7sZYJ%20OaPFyWySz42PKrg6eYsDntJ0ILenqQhDrWce63Y4uy1sK+lrETkdqcVlyNZKHthe8MeGOV1yqBBf%20Un4V0L8nOMb1VeBMtm+t/wBxt3D9O+3ePz2wY+RNmOLQS7bs2OcB6fDSttj8zKcb2xXmY/4OeCu5%20nbOCwvkm3+yxh2tDkJ6B+5HFB4V2bf5ByfmS+0UfAs3GyNMTYmKPabop/lHmq7a8fejlt8f3O+Dx%20mqp8CSLA0iMNLX2a0iwa5QCSFKqTbwWuXXJVs+PnxrgYywXR7UEjybBtgHGzwiaqPKnCyfKsDwm7%20V50yq8zxglkjkIIT5LKW3AKXDUQH9LV63bb9ro5N7bu+RCs7S5rLyWycVH/UcV9kou4EogNj99ek%20+/2o/wB2cH+WbLj2t2Zy8s8R7oMGHgvbtAY4fmHv6D07g3/VS2e72d12iyZw3IcCXl7OwhnSw42S%20HtY0OifIga5SiEjS37q6+hWxLmc/rzTs4iX+yuThxnvl44va15DWY8okkQKfSu1VSo6G1ho09fOb%20iXM9ny4z4oxBkSOkYJHyRM3iIu/gkIPpK+Z+JpKDGt5ca/cjuN4lk2ezBcyeKSUrC2WJ7QQAXEqR%20t+Vp661LjPgipb23FZZOt7Mz43ew/wBVljJILdEIJ6UnCd9GNb23rcTk7az4m+4yMuEVnOcP4V1+%20weP2VN5atDUo4ysV7BKbiuSZEjoyYXf/ADAqFSDdU8VpdVxoRdi5jAVgKBFAHRT4LTU0VyGzmmIF%20pF2kl4RCCbG2lNMXSzAV3W6+kjUA6aLbrpVdQWyaOgY4iRoAEZJ3IvpeosL6UutC6eFV9xQ4zXvI%20ALg4FFQ9F10PiaPVQdKNcbDJICuS7bg2uQL0dYOAu3jz7g2myhCT6VdoOtD3bAoIX/tcpKNkQOGp%20Fk0S3xvU+rkOlCh4mYbS15JaCB5A+Gn6WoW94E9CRC90cbNFHG8OD/c0ebjd53Wtdvc5icFYruNF%20JBOHq4ucNjSLkbrK4XGoP4Vu51VaGPp30HLsCV79xCtfYONwRYhan1LF+nd1S+JVe6sf8tycLC5j%20j7TXJqWkLZyhFreDTRhbgWH6N4eS/wCpva2RDDvjZykAc5gCtAdo5QfSAf0tWjRlJrQ+glIDmfIz%204gne+fZIWEhVc0ggpdfBPP8AUvjy/s8nco4Ei7FdNG1rSxw9foI8d271ADQeX7pBnL+6mlnancv5%20eRrmDlntjcHg7kc2xRDu6rf8a6YK5ElxLTF3PxrcCCEwTvDYYmyiIbTu2Fykuvb9OtR6Vw6x0znM%20CeJgVsJbuAa4qRcKNwN9q0ntcFqC3LZZR/qLxA5KPJyMTe5rAJRHu9J2poSl7C/7RXtdn/8AXaqr%20y4N7+96rAx+noHLcfw3HTtc7E4rKyXShA32oMiMbddHHcleb3+3/ACfG9V7NTr7edtK8RTl+2uYx%20e7IInPM/DQBp5DLYmx8G6zYXetJBuJv+FeT2/wCPi7qXs+p3z7nCtfBPYnBz9zwTZXA5rOLwxO6N%20glHuzvDQGl0oBYIgbBuvinWsv+K2o6r41XEF3cuGTk+f3Z3Fg8xm4c8kI9l7sZ8jQu4/EuN7Wrf/%20AIratozSG/LF2MOU775fA9sNgx3SPTxs0nSx/HpWu3+L284ZO93Di0qqrF6xZHyYsJe31yNa4Nbo%20S4WshsCvXyr5vcilJrkehG7yVTv/AAxPi4cbwDBG5zzKLu9x4JI08q9r8VvWvzOLuoXsUzi+JyH5%20JSaON6F7A8tduAJRQ7VSLfqr6Fu6PLeo5Zh8pyOZJgYbX5GTlSiGBgXZvHpJKaAfGsnJLU6ksHoH%20t7ix2zhe2JWCeJgiJAaNjkAO0gBU01rllFTdVzFGb0bNcruTEjAjaC4PKbnk/MCTYm6OT7qroMoj%20aDuYySvax0Hs7mt2xFXq4qAh87LTti4PkLcdz8GQ57ckBifK8rsAJQFvWiUV+9VqNN8BxhRcfxuP%20K7HjYwO/qSSArI9yqL9fmqVnUMopff3cmdnxYfDZ0AZEycTPZuAc6FpRgel9DbVK020S7PQa9yfS%203GPD53I4WQyOJjfdjxno17QW7iA+w8qI77TK6L1X0Kf2Rx7/AG54y5JsiMzMgRA4NJBGn8qmn3Dy%20a7E7FojweQHuROY5ocC9qOCIbID01/S1YdSOv1M3K7zvHz4jMNxBc5rzsYbhXDa7VEQmrhK2gOV3%20dEFmunkMTmxPG31bCidLIpCfp5HeOSJyGzp4mucbPYwnaG3AQWTw6eX66pR56GMpJI6b2139xGFw%20XHdo8xhZDDyMPsx5OO9PRlkiN5JUg+ofdXg9z+N9Te9VNPoenln2m0d+yUXxL7w/097Ww4PbyGzZ%20Lh6WskkQtAB0cB8LJXJufnI9SfD4+76lf55E2zjRj4jouPkw2JeL3WmR5IB1e0hoPiCF8K8597Ft%20/wAsZ58baY4+409Pwqv1ILI7c7jyMifIZnYjXZLSycD0tRgBRE/iS/j0ro2u927qzxWOOKZTi1wZ%20Fy9s95x4THQTMydp/wCnhx3ta5Vs4KB9mqrratv9UP8Auwq936Z5ktJcCvcv2F9Q+Uj9fHPbHGDK%20CchilhKucWhxJB0ru2O824q/VfnVXOedm7JcudfqiIj+nXecrWuGDmsZcNkLtoIBDf5ggBI0rT/k%20tt6NN1X3EtqztXzG7u3u8oInyE8lEP4tr5XbUAA6+dun66uPeQlpZ1XmV0Wqr/L3CmUO+Ghwn5Hl%20oWMCuY4vaGFpW6gIiin/AKYf+NfYXQrrxHeF3j9QOPUwdwZbG9S9jSSABY72rp0q1vX0XxE9uLWo%201m5nu7Iyjkz8pLkTEl7jK1pHqCF20DRPCplup5a18RraXB1+4ln813HmxsizzBPD7jWu9yMl4Ici%20hxKaarVx3o5sRLasibyZ528bmRu9LA0uG9wUN0DXdDpYffUR/lnnX2OZrh5VTwej/oRG+P6Y8Sx6%20bmh+hUJuPVK9ft3/AAVcTDd1OgVuZnO/qthcZkz8f+ba50m17WAabSQq3+Fed3zyq5HX2ydmcm71%204uDC7Uy245DImOa0ABAHPcEU/Ea1w7durmbu6qvcc/wMWLKzoceWRsYc1zgDa5s0C916JXQgcsXG%20vFZXcXEGXL42Y7Q5zZsB/qhkQ+tRdHC/UV0WMF5Exxfd3Icjny5EbN2IdnuccRtd7u6wJRS3qlRO%20CKWmTnnebOKw+4smLIaZXTPc7IEZAdE9ykNb5t8DXVtZ0M5FaZmTFgh9xI2E7Do/UgqRovhWyiiU%202dL+njiOAj3G/uPBJCID1b/CPl/GvmPy3/2ew9jtG1B1xKZ3Y1x7pzWNaTI6QDaEBGhHn0r2OyX/%20AKY35Hn9wv5sSx43R8wwNAjimRkku0Eo7UfH91byzFma1HnEZufhMyWQZD45Y9vtlpFlUEIfAaBD%209tZT2oblro3huNXTZeOO5/JjwJcvPlaZGuLobbSUQbU6V4/c9ldqMcRquR6EN1KqsQHM/UPl5c8y%20nHa6WUW29FuBqbDp/lXTsfiduMbGE+8k3awyj5rMke7KllY7Ik2g450aQtz5n9OtdD7WMY9K0Gt5%20sXHdzseJ4xISXzvGzfcBDdzXI069OlYy/H9TXU/6j/0W/qvfX2HWBzXGzYsg5PkJYs3JftexgkRr%20B4oUAfa6L1rePZ7aWFoc0+6noOBD3Fk46ca6b8u9Gslykb6gq+2o/XUvtNpO7RcO4m+JNcRxskZ9%207kJPzD7JGdoZtaSjkRHeXwqY9vFaKx2x6lTzxs/usEkPZie8RbY2gEWBRG3O03LfEX+NavajyRST%20tlV++nD2XNyY43f1NzXG7wQvX7VVLn7kNVFrVJVxGnJWa9nlmvffjckcxpa4epxZtIBIb6SWuJd1%20sBYeFGWOKzavYuFtad9AXwq6OR7CHInyAuW9jZvw8ad+ZlKMbWa1+n1+45x+W5WEh7MyRrDexIDx%20tNl8tNdafVwM59rtvhXvHv8Aufm2M3SyiVAA9zwbbQPSv833IKtbjMP8G03j31XEct765CIMEmGx%20Cm55RXBegsASh6Va3pGEvxUM5HMHeuG/1SQua9oUs2rdwXzWqW/4GD/ET/6Whb/c3BTMEchc0ShX%20hzTsB1G4pcmq9WLzm5i/x++uGBw3kuFyw5nuxPa1SSfSh6X1dS6oJ2MvR348DMmLxUwDWsiKgubt%20LdD4UdEHyM3LejwY3fwHEEuDoAXEFQXG4+00/QjqSu63ENH9q8OVaA8BzSG30XW6HpS9CJa72Rzv%20muTyMDmcvj8cNfj4cjWh7l3B2oQNNrretodhFrWqrn0R7yXvJft3Ey+bx8jM90RFjvbZG4KZEA+B%20P6fCspdjYf8AtaJg8FyoFsqKQhrXODkttHn+usH2jL/5GPKqwZ/K86xC5kMjWo8kO2KCCCCtilZv%20snwL/wB0ORtIeU2LJiNJYdGOaVKAtUn76j/JM0j3+2R3MvfPAIpoXRPBDmNIUEgGxS2l18amOxJP%20NV9Slv7btkqskcTS4NKEH5x9njWt2O8XoZzMwmFvst/qRua5CbF2pFKMSvJFd5nC4/MyccSvdC+R%20zh+ZsQA4+nc2yJoNK6drcsuZzbkM3Rf/AKa9q5eL9Qu2ZIQ10UebjvmkZdrtiklwLfA/YlquO91P%20Jg9tR45PaR0rYzOS8t27z35yZ+HyERlc8vjZI1df4bH1AXT1V4M3aT5HoqWCGzOF78biSbG4z5Wt%20N2v2mMooc0LclKFKwNnMG9ndy8QZWyQ5eRPmLJm33MmlN2koEBBAK/ea2nu9Whi4vkWDG5HmsKWE%205cAG1oa3HG4ubt2jZ12i/WsobrWvv+FfAOlrBcMXiOKLnnPi97cNwZDtaAt3PVBc9f8AOtPVw7r3%2019rm67doiOVxe2ePibPlZOTHjhhx4w1rpGuL12gtUuIuhdXVt944vNfsQ/xspOy1qvcUHjxxvFPy%20jHLO52QjZAEDWsB3BASSvQ3qt7uW1m3zyVD8fx86rXgTnHd4ZeZkQYro9sU8oYUu1u61wRcdUrG9%20kXPtrK437m7b7i4XmI+6+H3mBjycqHGcWODAQC58Ru+xBaR+yt1NS4ZONR6aquKKR3XxGDyuc7kO%20GyTkzZTHOy8RrXBxlCby5SSHO+7wtWiVe3gVHca9hS2QSy8jiYcrXDJe6Njd4sSHAhruqenrUzaU%20JNchys5LzOxkGJl/SwgOABQKDtUAfCvh73PetbL+ZW+92NdgxEm0b1GzwcBY2XU9a9P8Y/5M5+40%20KEzExsrkXR5eQcaNse4PDdxJ+a6BQGrrX0cZ4webHZvLJ3HsnEi4jt6DLc9j4pYFY8RgLHpvBIBU%20+J1rCUncqUUsVVYITk+4M/Pzfy+C0PUucVUtA6bitU5qKIjC5Gvw52sJzJJM0xjc4wu9LDex3blv%20++uZ77autDeMVo8Dl8nCtAEhETEu9iAkEWX/AFDr461mtyb1qvoaemtESPH5OFO4xwZhErwGsxno%203cq/KU8vGtYy4mE9vBMRTOxxsIc2FqB66hwKqdR5eFaqRmxP8nxObO6TIxYnzyhXSvJBAaF80ASq%20T5Mh21M9z87xI7PzcbHyGyq1zHbR1ADS1q/y9aUY/wAipLGTmnbWNzULsjP417HjioRkzRT2a4Km%201o/hLtNa3k1oyYotuF3b21yOHFljIbhZSn81hzEpFICV2uQbmFbCuRwkr8jpi+dVWpH9w8n21kcX%20Njv5CJr0JgkBVH+C6FfuqtpT1KclfwOYiXN2uMEahw3SFxXRAoVbeddraZzNsTnhz3FzZsW7h8wC%20gk3A8yaMW1M3c7vxva3A5Ha/D8zkYQh5iLHg/LzvJa5kwQNRvp1OlfHdz+TnHfntrMa8/cevtdum%20k2Wgt7m37g/GdGW3Lmu1KeafhXiyjs3t/Kq+J1ReAe/uBryBjQSgH5/dc3d6SNNF/Cj0du1+p/AS%20mzEuTyrI9xww9ztRHI0rbaDcCykWbUenD/uK6zB5PMbG1z8WUPc4D2YfWeoXy8xS9CLdrr2h1ZEp%20OeigiZLJDksjJUgxOO0HXVNP0tV/5HJ8PePrM/7nxwQ52a9u626QPaSEXqFA2n7vsq/Q3LafqTjk%20KO7wZG2ROQ3XV3qIJcHWIH8V1/zpLtdx4s6Vvlgnp2vCvoORz+VICPfEweS4KRIHNXaoF+rjfoq1%20MozWrdKvcC24ciq8viy8/nvfkZIjkhAEXttYGlqK3bs/hIAuutets7zSbrlXkZyhFYSI93Z25Q6e%20MDbu9Q2oCS4gbQg2rW67t3wr59/3M+iy1z8Pma/7PnhccgSx/wDThziHNRuxg9I19Siy/CtNvvLz%20S52+OpE9r+LsMZOGOZiSRYudIGMd7k+4KgcVcHFEaEKV66bi9NTgcVwPS30Zxo8b6f4EMZJja6XY%20T4bzXq9s7w9/zOXd/sXetzM539VmOkmwY2lquY8bXdQSFQqNp80NeV+S1j7Tp2FdP2HJe9mzjteQ%20KGhkjDvuNzS4r6R6fSVNcW1brefvT+50PHHHyOdyKzKw5I5NsxlAY1tx8doBXVbD7K9FKwSQ2xu5%20MrjOTyffjEnH5Mr3ZsKbXDwc0+rx0q/T95kmYlnwcPuH3+JyQMaSN+RFlD52NAUxuDgu4HRaEr6h%20xyc/5aFxDsqZ7zk5Dy925C8guHqeDfSuuDxbyr5GMmxtExpmDty/xH+Ik9Qn+r9DRXgKKLp2n3Fj%20cdx/sZDZGM91fdZpdwVpAQqleL33aPclda2qvmen2u6lGzI3ul0mVyEmdilMPIeQJGhyv2j+Lr4a%20iuvs4qG30vgc++uuVxvgcdk5E/5qXIGJgRbfekNi8i5bG3Vxv+nXqirowlhiM/IQRZTn4TSrC4sk%20ehcV0K30ojF2yx9Yi3JfO8Okc4xkh0ocVuCq/bS6S4v3mzvb9sNcUKbm+ADxf7j+6hLNVVzUSWNz%200aB6ijSqG90AA/fVaITa4j7GfE4tbGzeC4NFkBPwJ/8AUuv7Mprjxr7G0JxSqq91j4vtThMLMdJz%20MOVmBwLg2Jh2gpcu+Yp5J50/UOJ5eCzZ/cHAwYcDPzhgbDtEeI9qERiwQLYhSalps12J9LZI4MXE%208ixcDloXNkLWwe64ta95uYy8fKQ4A+pFv1rKXUuB3PfzYa8lg5vG5X5fNhdC9fSt2OaPVua7r+nj%20Uqd9TWG4mN2ZAZZAQVa4EoAp0aR+6qK6qr3eQqMpAWANY3oHKdu0Ajw/V5UXG3VezjwRh+WA4Fvp%20LWqfEIUKbb/bTyS3wvVewwMlNCTuRwJ6jVSL3ph1LAuHNb6mN2FC8uBBRSjRfqPvoC/nXzEno30h%20zlaEFkDr6uGoI0oBN8zSKYhoLXAqoaUUdURPDypsq91a5u525xLWbSiI6ynxJ8D0oJ69XVV4CbXg%20vIaE6k2vf76ClNZ41SB80Ydu+U2IQIfxvQS7ctfjXkvDIu3k8pjS2N7l3XUoV+Pw/XTRMu323rHn%20erV8B3D3FnwvaTIXNap9VybINwQbh91aKTbSvxqsnNLsdq17ae72eb8znOZmfmeRyMl7/XNK/wBw%20jwcNbEtJI66V7G3mK5uvoeFufwm7HU/pvxkOR2kJopAwsdJ70TfmD0+Tr89yVPlTnuYfyMmnoA7o%20xX7w9jmPY4rGQF3NT+XUt8PsrzHvO7uqrzO1/jZqzVVqK/33j5EWb1u03At69SifZaj1F5VVXMZd%20luLxFG5uM8bmTN2td8wKFSCCFPX9lHWnxMvRmtYshu5jGMeLIcpdA5wj9s6F8ZCvB1vTVmq86pi2%2073taw+4zDhHHY8MkQc1sQcSRb1HUhPEkVaRMtx3wOXcbxT3FzsWMgm42hL0vTXIPVlzEB27wD/8A%20m4MZdZzlUgkIS2wP30enHghvf3HxLR2NDFD3PxDYGhjDkxA7bbiCBfxSmopIXW5SVz0ZQdZz/Lkx%2025Dh8ocSjbk3cRqPvK6fhXiSWXY70sZMNDS/YNqtcCjulyi/8VqjpRSMxERgK/Uhzd1h+mlNbbBu%204s/DgnBdJHG55u3e0D1BRuJFzZBScBWRBzduZW57WPjIcVbqigrZpsqa0rtVVfDpjvWKN9QcDKhw%20oo59uOJZWuLpCQieAabn9tOEHdWdcvI0jvJKvhXzKFHyXZMrjFyGRltledjZGMaGemwQnXd510x7%20eVreHiYy72kbY8HFzzQjj8p8MjXgOx8wIhDwAS8Kijr1pvakKXd9Sd6wXnt1/cvKDIGBkQcliQl8%20LjGUexyDcwteA7XrcVxzhNO1V7Dl6m7/AA9vMpHe2P8A7f281B7HH80VjyMCKRj3SMBLXENYXeoV%2009pOdul3eMkS+1ypy85xXMcjx2XNHFLJESXABNz3LtLmgWNvBP1V2dzB+m7YuHbu08loPdPESRNh%20lEgnux7yGuc5oAu0Jf71r5JdjuJ3VrHveovaQvdefFlYsDceZsj2OPuhpIBa8G7iCg8b12dhsuMm%205Ky+pjuyusEV2r29wfJdxMxMqZ0k4YHytb/ytrbvBcFX026V7fU+k8+Ts8HQu5O4Y3Yf9vwIyyMN%20bFE7cAGtTawNBQ200qXaJDV3VfPmNMeCDAwxC1u14bvneApBI6n4aVxbk22dMEuRF5bjJM1sV5Ng%20DgiBgBXagsU/S9EIt66+80k0K4fAuLiXjaLI43N7LZV+K1poq87GLmKclicdhNhfkTBn5k7IGvHr%20LuoaSHWJP2VcdpvFtCPULDxMjspv9vy/XmtU4U7nFZdRsc7xt6f0Qi2J2YlHFIHSB7vWSDsIAc0g%20eoFPBPGtrkWTIPn+Hzc+eN8ckcWPCEji3XJ/jcVAHXxq0Q2acTDLidv87loY3SMZh7C1Ff8AOUNk%20LTqKmbu0VA59k8d/9sMkLfdyGhJ4tCNfU0eVXAuTwQ+FlxKPcja5jyjHEBG+LgT1rWSxYiEh9K2G%20IRHHkdK9wIMSbHNACfMP1eNCqqwaXVjGM/Gx2Ok9w5GQbsVdrXGw9I+Y6EUO5HWeieGbLF2VxrMq%20PdL+XhEjH+r1ICFQHR2lfnXeyv3U7Pi6r5HtbP8AVE4S4BhNizUn5iUTd5i9c8F1SzpXy9wcDWRr%20g0rYalg0JQdFVAKcoO1VzCL8DRziCVPqJXcqo0fyn7azlG2PoNZB0ga4tJIIsWiw+H/q8dalYKtc%201D5QSoCgn1J8trn4X0p2toDsazEOYN4BsLEAoAOhppvnVfuTYbT4WFIdz4GPcgCua0m1tT8K0juS%20WjYzWOGDHaWwMELHEFwb6SCouU8KHNy1Y1Epb8x+DyUOYCWwvL2OI9TQGqQE9QQgFU++vd2oKUbP%20w+v6HPNstkDxICWSABxBLm6DcqBSrt7WprbpXFKydmqxXxyxrTAlNiszYTEYxI2ZzWu9JOze9pRL%202R2gKfdbft1/7FesP26rlo8+Mz/qTTOwuOgYWYzi1gRoLyd9rE/6rqlfQONzgudd+n+BHgdsY+JG%20QRE54dt0UuU163aJemrHDvf2LHXSZHOvqvkPim49rIy97w9ocLbVIX1dCei615P5LWL5X/T5a4z8%20n1dusM5F3Zl/mO28+KWba6IRkRhyj0uL2+H8Rugsa4tiTUleuHy8TSTXv8Kz+mmCpNgY7IhypmqY%20iXMLr7XH+IIld0XYbaaKdkcvPA/Kggka3HyXOu4B4JF9UUV0xWDNvJCnZEx/uuVzCHe01w9Yd8t/%20jWi+BDG/9n5jkPzGTjQuyHY4YZfbsRucGNRB/qAp9SE1cXh4eeDKdj5MEkE8BBkxyEeCLixrOU8G%20qjdZJXH7QzcYb58uOPFlTc5gLzF4OcwaLWUpdSuXD+OLkxP9P+7MHG/MRRjLwGo+FrSCHF2itVbh%20UOtZqcbq+CnnQpmczk5pDDK18Dg8ubjvaWbSFBReo0rsja2DnaEcjBx2ANdJskDRua66u63GnhVR%20b04CtxG8kogAiDQWkhx2g+rwv9tFirswM+N6B0bmggKun4mjoaBO+os4klUFgjUI+Z118qEV5Fs7%20bwezocnCm5vl3HGdEX5WNiwudJFNo1ocSjw2xNv1VnJji7aFn5bu3nWZD/yP/T4L2A48+UATvsjk%201umq1jFLiU9trU5xnT5TpppcmNr8qR7vcmUn12JS6InhXRYy6RTjs+bByBKjtoHqhLUZJGf9J08j%20SeQydx4PCZy/b39vkzP7gTCMngp3k7/adq1wN/Q7UGuOSszeE3Yqc2DyuPMY5oGTSj0OMbjGpS4A%20K6jrWtk0a/6GtRp+ZETG74JopHoWvTcwjVPNLG9LoLXcrRmGZGO6QMiljcCllLVITdqGlKfSyv8A%20RH2CjRMXH023XeCSAt/H9Eqek0UleyATI0eohxcfmvdUvppaqasCd9Lib8pyg3dqoB1uR91/31N1%20YavqZblKquQ3LlO0eGtjZPGndgm2KMyQ7dtcS0ts6w2hLeP2rVIblZ5qvsZdKA8WuhfdLFbaeZ/x%20p3DqeL+dfP8AU1OT7djfepH3XQgXv1/ZQO+AbkscLXCjVQQBe/itAm6r3GJsp/tmQOO0AlLXQra2%20pHnV7drrFyN5tRb86/Ypu4e2jgXNBJLtG3Nmr08q96KTsnVeR83OLT5VX3L/APRTl3wcnl8NJKYx%20lj34muRDJH1VSPl8qTTtYzm7ewz3nxhwO4JwiRZX9eIi6e5qPvPWvI7iKTwfQdju9UFfVY9hCmSV%20GguFgjSV0RKxsbp4MNllVoBQqCHC/wBlulKxSyxrl5kjAzdufvKa3J+8VUYmO/BW0H+JzfIsjLBM%204DcHelxQpcX8PhrVdTRK7Xbau1d19/aSMfdOeCd7g9P5moo8ClqHuSM3+O2n9x5D3bKPU+Nj5ChA%20ALTtS6i6kdKr1n7Dnn+LitGyydg9zx5HenC44h9cmXExRdAtrponTyqlu3djGX41xXUnhVXtPUta%20GRRMlkUU7nOPpcivX5XaIOoWvEm/5Ox3JYEIvZJJDzqrnObt+XVtxZoFFykmZ9B2lzwHAguLTt+U%20ot93kq0dQWFHPHQbgSPS709FUXOut/3UrgaB4DjvA2vCvcCQQ0k/vqcBdpHnH6g905XcHcOTJHJ/%200MLzFjBSW7GEg9Uu5b127aSRm7lVlhIeYt903ABAdDa66VrHcQ57TubY+U5gDrv9tS86BzCVVxW5%20HQVbMc3HvF8XyGRymZkcRyLsTLZiSTGJXg5EbGqWMLSPURWbLSKHlgyPdKJHI5196udre5uvjWsU%20glG7Lifpp3DxXFt7ly2xs4ts3sRASLMyUgFpdENAQV1rn3d26xqVtxSYlLE8SNY4epu0P2gldxO9%20Qm3a7d+3pXnJ4qq8T00x1lYPtQb2NJ9t129SCHN3ByO3XPxrHb3rysW42LJ2lyJyHZi4UYjghDo5%20o4w0uKIrXIen6da9CDv5nHvdKRvisil5EyIrIWb7hfV4ddDp/hRvyXTkyhHJnMe9m1zi5Y0lk2u3%20F77BqlE1T8bVy2Tbq3KvidN0OuB4kyo5o3SruehLgSUaCAeui1t0cKrgc82r3Ol8H9L8mWNkmZkN%20xWEDbGLvHVoJKapr0rZpGLlyE+4fotwfIyYkmRmvfJhvM2M0jarrE7kIUDrbzpOVlgLsrfP9rcpx%2039Yt3RNcNuTGQQ2RpKOtp+ysZtMuLuM8oR5IZl7iPzDUnaqD3WAB6f8AEq2raEgcVYilb77S7dI1%206DcNDqo8/uqrCbGHd/OPyY8fBYIofZaFhiXaLgkv/wCLrVJDj4FajxoDLLkFYnQtBa4Ff/Sb9Tb4%20U8iwUzncWHDzPdgG7EyvUw2QO/jZ0Qj9VbQldCnGwtn4pZxOBlMCte1zXeBLr9PhSjK8vE01Qzwd%20v5uAP9LA8F5JULqEtWj0MM3PSfEyOk7O4/3ZBJJLFCFI0cUIt6VQpX513Kv3U7aXdeVvke5t4gvI%20nh6fbaLNsAL2K20It+6slBXuGXVVkT33Ad4K6wGgta+orfpJuYc/cli9Lm4bc+rVOhqd3bxhjjIR%203AK0+m3rT1FCRbW1itcTjZmpruNy4EuT1OPjppRYLBuJsTcG5vqBpbwAoS41Vx2saOdptF0A1NwV%20ctOwI0L2l24XFgtksP8ACqsCKtBiN5HjszGLCZBJujJ2NCoSy/yofD7jXr9bg4vwr7mLSNO3OUkI%20kwMl26eMLBus4PeoLLDV17lUFbb22rXS+v08OPg7E2yT/vSNkx2B7mNkyGxPlRQAtxrbUJS7LbvN%20ez5Un8bkbskkX52JM90oZO0Fo/pPkagLGuHrC/8AD0r3/I886H2u4O4eJzS0sJds2hPStulep2q/%209aOPd/sS1dBmcY/8gpsxuZwjIZXMjc2UyMa7aHlrmFuh6GuTuYJtG+1oziGUyeSKT+hM8vDi1712%20jaLqepXxrCMIpmjXvHDH7uJbmOcD/RJLHdSBsLSenktJx/kPqOdZjmuXYrD/ABN6O3HcijX7b/s6%20eBGBmfbfHulUCP5QLvPg3pp51SYeRM9r5mYIp3CR8UTnMO1hcAdq9fIVM1kqLJTKczJk957S57SC%20ZnKSQ2wFRl6sfyqvqGPL7KyYZ2SR+mdgIQsd8zUvqKSQO6JfheeyeMyn4sM5khH9THgDi5I3/MHd%20BsKEVMoXLUmiF72gE/tcxE7d7srouQjsjZAFab6l7SFpbUrOwSKjPHFJJ8rAWk7QCoG7Q2K9a6V4%20mbVxBzGRlrYiBojdR5dKPMXQTfC9mc/3FMYuKwH50gaXvDRYJr6tKzlupalx21w0L/xX/jv37OIz%20KzFxo5QHh75RIGdR6Wk/hWT3uRdkiu/UbsXO7DyuPw8zLhysjNhM49lWiPa5EuQU3Nq4PqWR41IT%20MzPzXa5myHl+U/LbBGnpYyJrC4lLAq6qjCzxwCe7choIpptrGxmWaUhsTf4nLYBvWqtzMuriKy5+%20USMTIBOTjvLWykgujDSntpogdTSE2dN+l3NNxcaSF/z8fkMyIka4OdDkehzSQCNikFNfvrn3YmkP%20M6BndrZnI5mVk4UJyooysjmkB7QRZAoXX41ntyxlhJormZxs2NOYZYCx7ELi9W9E+yx6VrGVxW5k%20blcRhOYQ+Bj0AbvkHqJHmEtTuO93VVgYScDEwuGNPJAQBtjadzQgPpDXE07iV0NMnA5ZrHA+3kAK%20VcQ15AI1uVtehJFrdloq5DOaQsDffhfAnqQqWjqCop2LW9zExPGPQ6YAm66GwufglFmaLfWo53yt%20buVG2Kj1ArdE1qXHwLU43MGRj0VVubm69dV1osWvM199XlHmwABAt1TXyosUmjHulpcS3X5l6+Iq%20rg5J6mmXMBiy73ABwS6hVCIt79Kvajd2SMO5naDItry6ABAHhu2R3pLWt3N+bcfUWjx6favsWSa5%208DwerkPeHyRxPLYHJsO84kjHqHIgc8teAbfAW0/ClO9foLpVta8zqn1I46LI4jG5THDXNiQyyAIS%202W5JB6brDwrl7pXVzp7CTjK1aeFfM5o6T0gqpTa0EXItr+n2V5/A9luzqv2ExIA6zkF+vTT9P8aA%20TQ0zJQ8xQtN5Fa+5uW2RPjTirpme7mwtHMxQmhKgHoAbj7AppFxwkLtddLgBSWqgtrQXcFX9tv08%20bUhxqvn+xZfpqP8A/oHbxBIb+ehBFtNx63SnHUz32uh31tXv8T2ZXUeIc/zZH/mXtjad49AOvVSh%20BIrxJavzO9YGU0+b73tMAcZNN4VgbopcpR16WBrxMROkhj9icNbKpLGhXh3kSVH+pBSQ/EUgGU9o%2092MRyNdZsLXP2/E9CgstCyPFxLmZDDxWc5S10cEzmOKDa4MO3YPFaqGpLPLTZHMxXTEqSHPCoSVK%20uK+rqa6m8DhjIliyxNYJJm75JGFN6gK64IPVFtRFcjZOLVmaelj2OGrijibBNHKhvY1qjj3Vm3gO%20+G5bM4zk8HkMZ4iyMSYbHhyBERw62pPSwLUm5/plwuRmS5Ts3JlbkSOkcwbWtO5ygFBceCCkpYDJ%20Yp+34M4xQyulyMRpaPyykCR0YSNzj4tX7fsrN2a8ar3lXaN2/TiDLI/LwzY7iS4yOcHIpUj1LYnW%20uaW3HgzWO9Ijub7O5Hi5sSHL2z4ec58bZFADHBpIa5pu5dVrjlsNaPNe46ob91kccVg5vFcVI4NZ%20JhfJizt9Rc06m38qda6u2cn/AG1MN+3Ab4O92LPM4NdDNKBC9LvBQXbckVpvNXwRtriJZ0Uz5JA0%20ANdJFGpuqdbBBYlQV8K54PmzVvBdfppwudm89yz89xZwuLEx3HuaBvZIQbkIf9XhautNW8Tmknct%20mT3xzX53k8bFwHzjjowYdr2NfO7buUt1AKLasru5p6eBTBysPmHx9wz5U0JMAYzGiJRjx8zCDY/b%20r9lGjyQ0LOzxNJLHu9LUO1xC7XKQC02t1XSp6rBZcSrc7w0OPh5U+I1oLHMeYiPSCOoCgtBaTTjL%20I74KLmn2AXCQtCuJ6Ebk08q6YkvPmVJ2M2LKe+BjpJHIoO50m8hdBuNarBLZnLb7EUWPOrN8gdkB%20PUGgr6j1Ss2xopfdscsXJGMFcd26bHNtoDrLbwrfZ0Hu6jzPDJe3sLJjKPjbHcHUom2+vjU56i8d%20JGRQxOxZHvl9vIahjaP4nE2Srk7GWjPR3DxyjsnhxIPclbFiucAOrS02AX76+C7iP/8Ao3H4s9jb%20a6UkTr1UIhUIXk2UeK62riUWnmnaquaOwFxDfQfSSXAG5QJb9PCuiL4kWzYTcSECglwRpKo0onl4%20VV7ja4mj9wBLVaQrR0VU8KxntxavwrmUmI6obElE6omun7K57cC1zMEoQAFOjQEVU89ESmlfIAXD%20bY3NtxIF0IU/tojETZiVGk7QUT1gJqfmstU0rj4ELwzd2DJIGuJa5xG0hxRG2AJRx8Pu613bqyjJ%20DDuTj3408XKYx9e9XAfM16FyCx1upF66O23Lq1V54wJjjKyY8nhjlh59sSN+RqODmtRGgffpXb+P%20j/79OGvHWqZzdzf0yJbzfIMd7jsvIDS4uG9zzbVXNcQENfVKKtVcdDxVJ86q56P+kWXPl9i4WRPJ%207ssj5S6RAFSQgInRNK2gklgTbbuy5VQjjv16l9vL4hASTHMgClUcyyVy9zw9p0bOjOQS5syhzibi%20249dF8baVz4NrWKZyHISQQZGC2X0ueJDjg/xWSxPidFvW3TciTqq5FXyZld7sZJd/E1urSL2v+qr%20RIhI5he0PaC4FWgauVBdaYh1g8jJHA1jkchJJab3QlfupNcgvclIs6WXD955QuKB2tgNbVDVjVGe%20Oy5RM5rGpG0ESFflaUATzQ1Ohp0XWB17seN+UAeBJDNtRoG5zJAFDiFXXrTMbcBxkYMfIyOw19p+%20X6AXnbG2SMq1zz+FCaXkNXYyi+l/Iu5J+Bkcjh4ebHI2MMmlIDnPaXMcxAQhHjTe8lwD029C2cf/%20AOO/MjIOPyXL4mNkf8yONpc8vb/OCQGm/SsZd14FLaOxfS7srG7M4R/HDMbmzzye5kzbfbG8hCxt%20923b4/Gubd3XLLNEi4xMxQWxwNbDa5aCGgi2tibfqqW0yrvzG/I9t9vcxLDLy2BByORjAiOSVgLm%20NIUhCfPSrjKxDOTf+SPF4cXaXDnjIWYkOFl+3LiQxhjDujQEkAF213gutdGxO8s8iHGx58DSm4nZ%20tQhCQWlfm6eAvXVqZ3Zo3FmBc+UEEuDipuuo87+NNyXAEi6diTbcvLY9XRSYobJE4Kw7JARu6t06%20VjurFjTbwz0L9MZ3ZHIcsCF2QYyE9QrwhdfS1h8UrljJp3WpU0rWLpmcVDnxGLOjjljLduxF62O4%20hR8KFInHAqvIfSft6YulxjLiPd/C125gPSx8vFafW0GpVuW+lXOROkfhzR5aXDR6XoqCwBvZfCqU%200KzKpm8VyeBKYs3Ce1wIIke0lhX1WIXRprRNMT0vS8xlJjxylxYT6btaWqQeu9ddAtUpYHoRuRw+%20BLd0R3OXc9tlCqBe9m6U+oloYy9qv278WdwBWxJadVIa7RfOqjYHJ5sMpcbl8JpfKwOhYl3epALL%201PTqKOnBa3bM24uHk+Qfsx8ElrQd0rHN9r5bn1EOQpolHSjWO83qSWTwb+PxzJyInbE9qQjHj912%205LbtAh8qm6Ke8/aRnIx8R/t2NmHj5H9yCGXc4iPa07la30kr9tb7DXVe5y724+myrzICAZ8z24bY%20JXEgvLEAbYFTuPktd09yLeGtHVjjjF20HOHmwThg9wtedynqBdTuN9wUhzk+HjVRk2rr58/nXtco%202Z2LtfmMPlPp1Pj8i8x+wRhi6PG8D2m23fxFKbs7czKEf5pcDmDYspuS/EdFuyIXubJGFVu0eona%20Ton7a814dudY+R7UdxSyN2Tq5u0gsW9wVW4C/ArUNmkXcRknLZWOf6Qy1ulxdeoKf5VS1yZb0rPx%20r2/IVimY4DeoaVLQUsSSn30cbI2i3XIcsezftcqkgnqRfpRbmXky2RoBWzQCQotfz6fZ1paaD41V%20eZZ/ps5fqD2/bTPiQHVVPVDQtTLdutt+VV8D2ZXSeMedeU7s7nxeSnEXIRSsEjmgbTuDA6zVOlte%20teW4Jt3O1T5CP++e4mgFksZBW4aNpKqXBUX9dN7QOWMVXI1H1A7tbua18DJLgO2B5aNVUdeieFD2%20UDlnxqv0EX93dw5TEfmuEZBa5kTdu4BASnVE6WocFx1C7tVfAZZ2RmyROM08shnZ6VJIUtJQhdCA%20bfqq1bhVeHiT1XVcNfE5i2OQ40jJGgOuwK22pFz5USRrCQhnQyT4mHita1ogf/zQigBxcp8UNLqs%20jocG0kqr5muawtLSCWSPcfTb1A/bfx+ytEYb6VxKcvjE26QqHt3I1dENze9qTMkd/k4LhJsXGbFN%20LDL7DBI1NUHzACy6WHnXLKWSornX6DU8PzWIwOw5GvhapY8Oa0LoULredUppg1YZS94cnjuc2V0b%20nNRpcgLQUQEOCi/lQtu43K1VYgu8+8uNyeDlxJGvfnzJHigEBoeSPUUIKNVaS2XcpSsRHaOPLjcB%20kxS5IkkIBcGuRu5ri4o3qStylaSWdBN3RLYYYeIdHG5wfjytO54VQ87nfE1jvf2K2xnlsa1SGN2M%20mDvAkuUEFPBazg3fU0bujpfaOPFJ2rype4sbMSwPDgx4sDt3aBTa9a9VkYptyKtjyMyIm5eR+aMb%20Z3Px3RbjOyNrtgYXtPqS/wBxos72xVcNfA9GUF0rT3/FmvZOdM7lOQzY5JXwMldC3HIRgBC79pK7%20mp6kpTwjimrNWJzE5B7eSa0KQ4GNwchBG7c3/wDFYLWBNuZJZcjZMbIjKua+F9idNrbG51JNOLuB%20zjmmY7MKKTcXNDQ6UlArgGr18a64GT8TTie4YOHxp8lzseKcNSF5ZunD2q3066WOlEr3Ha+pT8p8%20mTM+SYmSTJJ3PdckL4+pXeJppFYIDuiNsWAgcXvxXN9uynbIE2fY6tNp5IkMxE93bEMz5HIZT7cA%20FiDY3IWxq3iRUf6mMvi5osCPKjljmic0ehpVzdP30r5yiHHB6OwWH/bXHtLUHswENI6EAof0+NfC%20byXrz86rmeztS/imSZIaLm4VTc2QWS2tr1EYXBs0chaF0vtsEK/DRBV2xXzEmajqdFsq+PjSGazO%20Y6M9GhUHh0Km+lV1YBRbduI3c4EO/l/hLj0TXW+tefbJsYVCuhBHkUTQ0h2DRqkdSCemt9dw6da0%20iyHg1l3Bjtrd3pJDRZVCANXU1PEa0Nu0eKwsnhYnOyxE8zPJaWvPyENCOGuilfxr6Tb7RSs3XwtX%20Bqxwz3cklk9uce5kkL82NkD2lsjnggEHQkaCnDsLPGtWrj7Bf6Gc3ZxHcL5sri8KJ2XC57SwQkFp%20cHbVadB8VvXpdvsxhlmPcbvUjXNjyOIndBy0TsTK2hz45CT6SuxxHUO216/Vw41XzPM6Uei/ozMy%20bsDBkY7e0vm9SJpIQdPOt1Ym1i70wOO/X3DzJp+Kmg9sxxMl3te4gkkhEQHwrk7mSVrnTscTik2T%20Btd7jkiQu3D1WOoPl0/xrGOTZpr6kFzPDYfJf1oHuhymIC9CV6bj9tXGZLgytT9pcgLmUF5JBcAQ%20FuSSnX761UjPpED2xnKjyUaBuCEBB0P43o6lVVzDpY8h7WyIwryAFFl63sfPSi6EkOHY7oMYw3O1%20TbW5UBCOq1DNIDbDzDiMyHysLsd0rGB4KAANt8R0otk3jOyH+SxgZM1zmguju+yqDbz8CnlQkYN3%20Y4cyaTDbnu3OiY+P1/zFwRdL+dIZJ8RzHJ4s8uQ5mO/IyNge58LZAAwWDdwKD4GplC408Z0Opdu/%20U3hcgQQ9wYjYp8cf0cqJXBpRAUNxcdD+Fc09h+Zoty5an979kSgFucQXXPoddv2a6Las1tysV1C0%20Pc/Akbsfm4kYQGNcRc6+o6IaXQ1wBNEhB3Rwr3f1M3HJchHtyi2oJJXolNeWR2K59XYuN7k+nnKY%20MGXE/KxmjKxkeLyQ+q3qGoBFabUv5K/MzlDieUopWFjmu3DcEcddp6hE8TXe0Y3JXFGE/Bm5HK5Z%20n9xhDWY2A6IyGZml3fKwNaLKKlRzoNsfduRvZ78u/buY2JzFsS97Sdx8hpUbmCoanoj6L45OJzXJ%20oWw5M7YYdztzUxwheE+NczKlmx0VoBb83kp8reNTYLg+EOK/f1/BadhKRkRkaJ1QoqeFHkK5rPjw%20TDbMwSNK+l7d7b+Rt0ovYNSp899N+Az8cNw4hgzgkiaIk2PQt601N8BpIovMfS/uHDa38q050dis%20YAcL6bT4p9nWtFMkqGVxvJY04E0U2PI0IWSMKt6FPt1q+tDXvG7R77Cx38QRq3B6BNPT1p9WQyQu%201reTe1jyz2zo2wQHy++s3NndtqyLBg9y9yYSHGzi1tw9j9r2HaSQFKoLeX7anr8K8vA19KLzbnVZ%2004kzD9Q5ZWhnL8HgchEU3BsbYpCGgXDgHOag+/71q7VUq8iX28bW0HQ5r6Q8ltHJ8PLxEq7RLjl7%201aRqCPS0quot40+t3rFfEx/y8n53wPI/pl9POYxo/wCx8njz7D/TZMWuc5zrkOLdjtPlP2VfrOOt%20Vp8jmn2zV8Wr7mOM+n/O8EXMxOGjlxsieJ+YyOUyMcyIgs9AUtcD0WtP9LcbKv2MXsxvnUu83a/H%205rxku47FhyCXOMjmkSkk7XoGlv2WSspb2Pq6rBcYtO6Oecp9E3ROlfiTwSqd0bQ4N2AmzLk7iKFu%20pYZp1y5HNO4e34eOGRD77jPjXe0ge36Qbbhew6pW8Zu9xtYuyExMuNNyk6Eu9KkIDdQdfhTtzNIz%20t+49bktcGtHpUa3KF1gSidKl+JalcVjkJcXKrPmLnEWAC2A+2/jRdcMlXwWn6ZuX6hduKAv56JAo%20/wAqa1J3n/BtHtCuk8Y8z812nz2Nk5me+JsWMXvd63NBLS/VoHjvWvO6nex2qwywONZl5Ig/rPYi%20ubjs3SW6IBbwpOVqrzBLqrmWbE4nsXGe1ma7K3tKudkt9tpABO1GjxrLqYW4lk42HssbfyMWM93p%202AuUqSSvquq+NR1PgNbfMkJeK4GSQvnw2FS4oFINyFRpHxNLqt7AceRynmu18XD7myMGVv8A0k5M%20kPT0FdyeCdK0U2yovBHZv0nzfckyOMzIX4iB8sc52EBAiu8apbjvoawkk2znXLbIs44yEujcWOIs%20rlWx66fotbQWDHeneVyOx2OnyYYNzgyecNc99gWgoq+PppyfMlZO44eXiciyNh5MBkDRGGY9nNaG%206G976VyuLRadV4jifF4divOTM87Wj2590jCborF1qHJlaobZUGLnOvhtmYBs3sWL5bKEKL8aFN3J%20cblOzMHjMedolfC6Ikubj5A3EWTduahsK6Iyb4EyVjTi28YzlZosFjdk0Tw+Z1/NoaU0BVOtO19Q%20crJk3w8HuwZ+NIUc6L3I2BN3pKpfqnnXPu5yUmITQB4e3Yr5WBdSXAG1j52rOPM0b4F1+nmWzI4X%20Pw5IxLua1z2SB20goza/aN1yK2uY5uV7l8PuTFlGPhJBizsLSxxLTA9Sd7C0gkEaVFzsW9gj+3Mf%20N4jGbkSFwzJzI2UuOpJuSAU61M29DN2eSTyI8h2NLJgu9vMIkdjvI9DJyAQ0geZDf16CsYtXzqJx%20Yt2JJ3d/YXnuZrX8nH721o2kmEAlXpp5V0bnT1fx0MbMrvOSvi46P3mARlm7cNXNXc03Xx+6t4ZJ%20dijzzY8mTvcC3btLXIrgQNQqjpWklcaZtL7sDH5mQwxv0xoXAtRrtEUW11otgabZWu5IZos5jnky%20MfG0x3KOcRfyUGtNt4JmOcR7HYcURc2RWt3MXRPmKJ+qonq7FReLGuQzHhxTtgbGdwa5bpp1X7zU%20rLKtZYPQkQZ/trjwSCz2cc/KStgSB/EpOll+2vjZp+vK3N19/bxPSi10krIwDcELiVaBoSQURNOh%20I/wrT/O069uvnr7dCeq4DeCjdACGuJBG0khbJ8dfOjpdtOHwbeat8wuInZtCoPT/AA2VD1/Xes52%20tVVwGIPLgnRTZSEJ00P7q4t6CN4t2sJnoUQaamyr+oVg3e4zAX7bAAC69RfXXWqsFzUhSgapsg1u%20bJ4J+nwqMeIXNORDY8XMDHbWCN5DiNPSq/8A4aUF/NLxQ74JvtHgMObtjFf7k0T8jcZQxwDd+7ba%204Ww3f519VtzagrKv38Dy9z+xFcq+PIzjx+DNLLFu2Pc/+pFuRXEWXaErohN2zrWCHFJEu7K4js/t%20t3KZDhGWIIo5HbXzZD02rtIIHqAStE7uyIb6dTh/M8jmcznTcpy0nvl7i6VdxAaULWgrZoFhaunb%20l06ZqvDx4nC5OT0PUH0EMZ+mXGmIIwvnLVbssZXFU89a9Lb0JlqdCqxHNPrBzONx0vHe5jMnle2T%202y5u4hC23wrg7yLbVvH9Dq7d63OK8lJFmPJx+NZHIbsfCHkbm9boPP7BXOsHSrEU7DysdzY5I2xy%20pu9u7XAKL6VfVcmzsOx29ycuHLlNj93Fx7PfH62tJFwPE/olCmDu2MTHG5Fb6gigIBe/Q1V2S0hN%207JGggRAAABocnU+XlR1CsV7lmuGQ3eh9xqg6uNyu4n+bzrVO4JWIvIiyMjHGM1xZ7JaWR6h/q9QK%20poulF7F5kheeNu4MLGyFkZBLrIQEBCdLGgzasS+LnYx7ROGSBk/lwCuo2uc5pQWutRbLC+DIkZFo%20gUrIEsQCq+I/x86q7E0S3HcrBJjnCnxG77mPLa7btIujvlal/vpOILzNpcvFxsgvjniyCfnIJLQU%200P2eApLI/PQ3dm4+Qxzy4gSFdjgAhsR4rcU3jgNXTtfInM5gg3Rx7GAkGUiwIUgr59D91LA034jG%20TlZo5XPiYCXEkWO1St7m5K9L0RjYHK6rBQeSxXw5b3CIsxnk2Pq2kIoPxK3reOhk9Qxo2uPWQnSN%20nXwvUtDTLt2Z2hzPP8hHi8bC6SJrt02SQTFGXDVzlu0eFY7kzWOGdy4nsLubjMNmJx3MMihjQiNh%20e1m8qXPLQEUnr41j1IbvVV4j5nE/UiENH5+PJKAOfvTollTSjAXQnyfLd+cTjxz5kkZic4Ne9jWO%20Deug/bRZcPmKytk047vPu3MEjMPHgzXtbuVC0i17B179KHB8waQ7b3d3jGXOn4QbGhS4B4ROuhNS%20l4h/HRmjPqDyjZCJ+EkLVT+mq2XqQlOzHgy76qYbFE3HysKfKXBVOiqBamkybIRm+qHa8i+7FMFc%20F3xMfckqOoPzfGr6HVV7gtwRCdwc59NsjdI7CeZnja98TTE4aevwKJ+N6Iwt5AvgclcMd3JzSY7T%207G8ujbIAXIBZSNym/wCgqWnfJ37dvYO42lxRFLgXNX1naSi3JJS5TVfGpjjx+FcPYaOSvjSvL7Gs%20zVYQBuZc6KjUDf4i5beB/VatCepobSF3oLgpGuq39W6/iT0plNrisUhjI1u5iEtcm30kNK/MLaXP%207KpO1wfEdcX3h3TgH8vicnkMxyS32SdzSCNtmuKaWqkle6M72eTpvZ3cHO8viznOyjK8ODQ8oC4F%20t9yXd0+wVnNZS+mnjw+pSsi0z5IweOyss7y723SOkeNyuhaAQ5bA66/ZeiE14eXt09uP14mcuWHV%20cjz7y+a6bi87KkBM0zHOLdSHEki4P7a64pnNuSKJByTY42mSI7UDVBsQbj7fV0rdRMOsl8PKBLfV%20dyqACAW6KVF/EftqLO1jWM8+I+VqA2vYvcSAQQFv0JTSszZTWuC1fS5w/wC4nbYQqOQh3AkqBdNL%20fZVRVn4VVYncxB864rw9h7broPKOQ/USaUcVKoDWF7Whh0JBUfMRroq2ryG7yfmduhR+zsl7e4MN%20G+t/pO03RxU7ttXPCHFX/f4nTw1mQxxkhE7ru2uLXApoAUTp+6sVqO1yPk7W4aX3DJxzRtQuI3Mc%20CB/A4G6UuofTdjR3aWJC5cLksvC2ucXBku4Bo1LgSNEWi/gGSK7h7J5vNxxLFyzcubHJcyKWMMLi%20DpuJBcu2qUlzDic75PvbkcLHmw82CTGybtZFJGQS5ujgUT7q1hzQXaOV8jmhs8r5iPemJICgkKbk%2031rqisHOyc7O5OHhc93IOxYeQeW+22HIBkY1rkV1gbkdenSoavgET0nI8XmPeXcU7F3Eo/GmfGAS%20bHbYVHTbU0vw4GcHK5jHU4eZI1gu3cQUAB2t9RP8vSm4p6h1Eme5O6IWCJkkZLSg9xoe9D5Dqn3V%20n6avcfWRc+PBPPJNyLnHLcSSWNbG1xsVKeAq0rC6hTBxZOLhOcGxZRZtexjHFrw0kq4fDdpSlL4l%20RZY+HyfyfItn2q0PDj47JQhUeAa6s52auwtwSr5V7rZN2rA7HnhiT3myGXGkCne1wCNtp1rmsirs%20x25wnJ8LzLZdzf7fyDDcbtsclkDk+J8PHrWildCloNe8uSgxeX43GdHI2TktzIsgDfEXx+oRuu7Y%20XFq6eNS4N3aLjIZTCUyPYGj3Y0ey7l2rtUAavQoq+Fct9xXzm3x+PxTNk1jwZlsxd6nFzo2i5cCC%20t1VxurAm3zqnL2VS8yLch7JIcfh+QnPziIwgtAO103o2bQ42Db66Ve1d4dfUmdimd0PkgLYCPeML%20BGQ47QoCXI8x4V3R0MhjwPP8XxeK+WduPkysCY8EjVc1xRCHHWlNMpK/ErnMZ+Xy+S6TJkLsjINw%20R8gC9BprTSKKj3LkwhkMEE2447nNe4EH0qdb6Vvsx1uYzZEb5GlxQsIs5oUa6D9ZrfoXAxTN2yPc%20WsMzg18ga66gXuLdLVPSiozu7HY8DvHv2HK/tmfjGfhcWEPxsoxFithaTG33mjRzgeoryp9ttr+c%20f7ndtbjvYnMX6lZ7QByXGlFcJBGCwofk2h1lIHXwHSuRbKWFXH4G2vEmcXvzgMgvdK50DywPcHBw%20V24uLWqCPlOv7UrJ7a417tP1940neqpkwzk+PntDlNe0FqubtLRvBRrSOp12j9V65J7Hhm3tuuVv%20t4rQpTN8iMxtG9qA2Nt32INClcG7tu9Vk1hJDVLI4gEOuNQT8D4rXBKLRsmak+ne521qq4qCQLFV%20pxTvZKq+IwlaWt6EEekjQqq/f4Gr6ba1+5AhnL+QyPExvDFVSEIB6Uor+aK4Ex20OXzO1sWHEzsO%20CJ8aOieQ2dqkqpGn6Gvq4NJJPlVfqeZKWR9xnbGJxrJMzMf7+PGUZtbtDnD0gAjXRFGprR2kml8G%20R1ZKB31yXLc/yO2TBlx8DEIbjMexRFtuXktCepUtXRtbXE5t18CsRYWHLJklmRPhzxAu2uiRrkQO%20YCfFR91at+6q9pk430welvoft/7c8dtBA3zKHIq+67VABXodv/RWMpJJ2RfK2EUD6scYzOw4WhrT%20NtcI3koRcW8ENcPdys17Tq7bicx7azZOOlfg5DmyHd/Tf/qAU3RK45p6nTHgTXPcDLy0A3Re3PGA%206GZQqbdD9gqVJiKVxnMcl2/kyYu0nH90jJifZEUWUdf21q4t5QlLgxv3PDwD5W5PGF7d7gZ4C0ho%20JQFCt6mCZXiRbCrdjpGuaFRgA1PXcvT/ADqxWIPuSCJ0WNIwAEP2X67wilb61tttmc0QcmNK18WR%20jAPkiJPtqA0td81vH9OtaWCIhkP3gOeAxGHc1flJv08KcURuDeIPZiRja3e8MG7aQpLzbrbrpQ2g%20XMtuFx2Zlq3HaJHNA3EvaxU0N/1Vm5pFtXH2F2vkTy7J5BjO3J7bvUSdwO4dNazlulKPDkXrBxO3%208XDhiyWwmdjb5AjWR4GgQKAKxc3crpRF8p2xwmdI52IHMlcQRI20ZNxtLVpx3ZJZE4XI+KPuztmb%203I3NfjPKPa5jZ4JEP8QIN1JNa3UiOmzyTvF5P0+7hAh5Xjjx2fIFGTjksY56EJc+IVKhqUSySyvo%20RwuVCH4vKPZGRcPa1zSpVFWyULffEThm5FP/APG3A9S8qxj0sWsPzEorr+J1/QN9yJR8Cxdocb3b%202Jxr+OZxjOT4vfv96F7RKxSF9KKQBe9RKd8lKK4lqwO/O38uRsU0j8HIJLTBkN2lfAHqalorpZPx%20ZDJWgxkOaRua5QWlR5VKbE0JyxRyNMUkTHRvYkkfRyoEITSn1gc37h4DM7fzRyPFPkGMCS2SMKY3%20Km1331rGXUhK0eFV9i19r96QctEIZ0h5FguwlGvIsrSfHwqJJhYsDpHSnZ8jttyl0J6KlTJvQEka%20Ow8SVyzQxyuGrnta8qRcEkeFOPiKw2yO3OGy3OdJhwOLxtJ2gGxIKJolVcNCv8l9LO2MlrvYbJiO%20PyiMhzR4ID+00dTDJz/nfo1zWFI+Xj5G5MI9TQwhrm3J+Qm+lV1FKb9hR8/juR4uZ7czGdA9tnh7%20SHEBdaaV9DZbwn+fgVwJcPShDgCE0BLvTp0o6Whx3BCd0ij2zoqAaXHgblKtJGq3EN5HND3NcFtt%20J+F0vRbGBpjSFrfe3FPTck/ynWwpyXAnQ639OsR7eGdK70PyJenq9KBNqX0dp/lXJKV3XOs+eupo%20vkSPf+YMftfMaw+3LlubDHdWmxVCNQB0t+7XZbxnhjwvVcYm8Z4feuftOOPkjLfY3BziLgm2vXw0%20rrOSXKq+Q3dxbXbnBt7hpQaLWnU0cvSiPy24cMgZkSe00ptsRc26AprS1DKHDMCF4HsytcLdQbFN%20fjQ5XNF4lk+mmHkN+ovbSyrEzkIXFg1KO+B6inB5VV+4Sb6X4Htuug4jz93r3Pj8oZMCHHkiMMpD%20pJFO4tKWY0H8a8pKq4HbXyK9xksmFnRZccPvOiVGOBRy6ahVsa1bTTzVeNydKrw8CyO7858b2s4l%20rw4qGnfa+o9PRNFrBbSL6jT/AH73XJIXDiAGtIew+s3Q2A89PC3jcV6S0uHXY3d3d3fP6o+ObGw6%20iOMlzkCr8AtHpx9g72dq/U1dzn1BcwPbx79p9TXe1tI0RL6XpdEeYrjbIm+onJRt97BZMoBDnwBy%20NdYjcSfhS6IpiuVfN+lfKchKcufhYo39XHaxpXqLqav1enAWuKY/0h5ZjXEY8TQGhwV7QD5NCX08%20KHvgoi8X0v5sDY78uPbAX170bpdNNP0FSt5FdAtF9LuWD/62dHDdCAC5yAKOl6PX8CfTH+J9NcFj%20S7I5ba7eWnZH/CTb1E+Nqh7zGtsc/wDbbjJHf0+QfCBtJLwCdoFyAPCku4D0h2/6T9pShkT83Jll%20eQY3NQID/M0a01vsOi2SmQsx8WabCbIHOxpHsdESPcMTSQHOClP3VrCV8j6cF+7R5JmW1mFI1gzY%20BtxXOs2WNSTpYpfyrnnESZbIcIbHN9syQyH+o1fUCFNutTYaYx5XgpgzfFuna9xcHBivYtw7Xco8%20qBxkUvkOJMTHyBHxsajWElAD6n+k3BJsLdBXPON/C/zpG8X8CNHu5Oa3Dw4X5eQ+RHNjDno/UPcU%2027Qf5v3Gjozfjn48K5X4sTsl5jzmMZ0WXBxm5srsAPzOWkZdr8x/yRBAfkaVcvWuzbhZXquBhNt4%20Oe9z8g+eT8vF/XllUNalyehUaeVdCViHnUq8oyg4sGM904JJ9JbtOpXp9tPpSNOq5o6CVgfFuTIl%20YS+b+VgCkAeNF8ieUykHAIsxpdvK73FQSLk3VNa7FIwbBmDNvIaAL3UiwuQh0KeNLqwIWiwclxCs%20ullKFFOvkPClJoVy8duc/wAlg4b+P96STElIMkT3qC5umuifrrCW3fJpGeCxY/ONmUTPIDi1pcRq%20ttQBWT2zVbg6ZFxuWHh0UaAf8zwW4UKCtqze1m5XqtaGh4PjnbJInPx36tKlQC5SQh+6s3svmaR3%202zeIdyYT2fluQMrGuWKF5tYHobkovWsdzt1JWL9VcVVfAXi7t7rxHNdl4jJ42NRyDYCv8RQ2uSU+%2061qx3Oxg731qtDRbq4YHH+/+OmhkxeSwJojIwNcY/USXIpQ7dt7qDWC/HxhK64V7nx58ORTm5IX7%20e5btvHe9see5JC1n9djmdDomgba5K9Kru+39a13Vfv5kZyjqSsuZg8jx04xHxTvIQsa71F3zKGg3%206OABryp9nKG54I1W5jxI/EiypMeMuxngojpGguKomoToP119FBYV+RwSdi9dlnD2Oyc6dwiLSzGx%20i5pb5uLOhalr0nFXJdybm4/EfI3HL2ZDfbBc1jgDIHOQvJILfhf42quozyM8rsnByZsiJzi1sKFh%20cWvG1yo4/Kh3NIQVV8AjpXZ/FY3F8DBh4ye0wucEvdzlN+ter239Ecu5qTVbmZV+9MzFgdAzIkYx%20r2PIDjcga+k615/fao6dhYOPd2ZfAjKjl40tfIXBWR9PNRWETezuLYPfsDcHbLBI4mxYPUVsQd3k%20KiW00CmVnnuTh5LPblthELy0Akmzx8OlvCtFG2BuREqsbQ1jgWtRgaCg29ASmlVz0FoNHYUhnc8E%20vjKH2ig2OVegt+oUnJWEnYZclh5E2JLG/aHkO22REv1NilXCWcA+TKyctpjILixFbIwpdLFpVdK3%20tgzI3Mna6N7tnpe3YA5QjXeXUVSJwxxixiXMhYCkcID5XgLoEaCvwqClkn2AOc0BthoHWsLahCNa%20B6aFw7aysfNiGDyMrm5LLY2TIbJ/qceqjrXNuR4msXoW6KObjQz+4Mjlicf+c0AEk6bviB+grmk2%20WmiVgj43JB2Ma9uh0a1yKQ4kdPxoSeqwPqQw5KfgII348uU1r3BfbjJIclrgkpc9KtJktFQyeMxc%20n/8ApsMr2n5S5p2E9PNDW6ZOj1JHieX7p7bla1pc2I3Mc6FpaSL7grWlFAtUuKeVwH1e0v3C/UTi%20+RDWZX/RTuAABsHOPh1uTpWT2xotUUkcrGva8AW27SCFQi2oqb2ASzeMws2Ix5WKzIaQB6wN3/u1%20qk/ACv5HZMEEhk4rMm4yV49TQ4viCkaKToUo6+ZSkzSKTv3j3f1RFysTQfUEZIgKelo2nXVaLCcl%20YV/3tAB7HMYM2CSUc17d0ZCEuUgfgi0yWkyv8lwXE5Adndu5bJdhLnYTXbXsGhc0klL3rSPiJtok%20u2O93LHhcsHHZ6W5ZHTpv8PjSkrMHwsXkAEKDuBCtKkggXCVOmgCAnJka0va4EHa7U7hY1NxoJMv%200l4eEahcHDxvY2FO7FZIYZnPYWFEZMuZjWtcW7mOCqDdVKAD8aFFiuVPm+/eByAYHYX59vQvaNpJ%20VBdX61agJ2KHyjO3eRcn9qGK5yoYHm5W9iU6qRWqjr4ApciuZPAKSMXcGyE7Wormm5AIOpWq0Bbn%20jWhHz8XnxvQI9nRLOuCSLp5U7o1W6MHQzxgiSJ0bm9LkroEJ0RbUm8Gi3FdXO39t4TMLg8JkLR7g%20iaS1hI9Tl3OVGj5rBa4pW6qqsWzfT1LqqryIjvvtrnOexoYuKkY1kLi+SEkjeSE8kuDar2p2eSN6%20d1VV4nPJuwefwyXZfHyWFpQdzbf6h4J8K7PVRxpCfsZMbtr/AEuBsHBbE+mwuaaaYNGhxo5Aksbd%20riqOQt+3UdVpisxnLwGA8PETTBKS1Cwo4Iv66fUxeJP/AE34nNh+ofbZGQ+Rg5CF7yQLg6AgDy8N%20KqLyTL+tV9T2jXScxQsnF48ZTz+XiKAF6RhNS7yd9teRJtydtTssIy4sftt2xxtaUa1zWMspW4It%20p4UnPigsYiZM2MoWwwi9tS51idq9Ut+ullopIXYZXt9sbnFnoc55G4WBDlGopWCwodxDXsd6mhCC%205QUGhS5K308aSbBpGk8ivLvEbXBOhCoXfh+lmm6qrANsr3kLnt3NCSNbuLWgEEkbtelQ5WKSEYJ8%20gNGS1jBGbOeXFxA1a0KT16Ci47C7HxF39eItKuDWJ6fSh9WvU0mhXNmNjeNzWsjbEVdtb8paLm2v%20qalDQ0JzmVsbmtChQ3YXIp/4RqrfE0dKDiMshuE8Auj2PRw9ILFCoUTw+FS4opNjKXjsWGJoG4kO%20JeRcl3jdTZdaTxkqMroGxWDQSNygkEgkgr6ifVb9tHTVe8LlZ7h7PwMmWTmIh+XyoIXNy8oKk8bR%206g9pOo8RWkZNYJkrlU4fOGI6JZDFGb4cwQObZANv2KfKunVGT8K8Tpfbve7Jme1yrfbmBAGTH8pC%20o1egO4/ppWMo2xYMF4iLXwiSMh7HoQ5dQ661KEaTwYaOlnjjIa1XveG2aAtyegoeNRopvLd44LWz%20YXbLIzPIS2fkWNDYIivqIIH9WQX9IprwwirWeTn/ADnJwYWK6GBSInbnveVe57rve938RPWtowqv%20gRrk51JycQ5B2TJEJ41QMd6T6VJDSD+HWquV0kn3D3vJNjDHwwY43RtWNwb7qhpTcRct8xUqJSS1%20KbNK9kodv/6lxR+hDWuCBD/M41qo3JlJcBuMRrr+2igAgm4U318D1rZMyaNxhho2hrSbC9vMBDoa%20m4WF44Ha7XNIsqa/ofKgLCsA2EaNVFB63HWykrQ2MkMaWwQhAfUdQgPhe9kWoauUmSOPkrKCgcWE%203uL9f2/pepYrkrDyAc9f/mCzFFwoX7kNT08Sr8BwyRjS128nTr01I+Iphccsyy1vqUsaC4E6odLA%20KS6iyDXSuZvO3DyF3ND29AdAnQnWp6EhdRD5XGcGWyTTN9pCtiQXEKEIvU+nwqrlx3WQ54dn5lkn%20H5EsbmlpaGkbg4AJtT0+Sp9lT0LiardqsFo47l+Ww8LYMjIjLysiyblcbpu8EvahbfAjqNDnv3JD%20kEghwf4gkrsJ+ym48xMeYvP8vik7Du9sNHtgnbsuWCw00BSpW2mFzpHF8rkSYkcrXMM8rN0gaVCk%20ILBU/VWErotZR1XtKX3eCgkRoUuCMCCxT9lev2bvtpnDvq02TFdJicd+vePLNl8MGkhgZMvqLQpL%20UXytXL3Cyjo2MJnLIY9kftq1jAUBaEXx1865kjZqq9/AW9jduQq4BQCQNT6QNb6UMVlVeRoccCNN%20WptVymw+K02Wo+JgbQ9rSLIADrooS+mtTqAkcZjHyCNNxKu8DbrU5tcL5yNpMcoQN20opVTYfZpT%20BMrPMdrHLecjHOyZwb7iWa4DQfsrWG5bDM5wZX3dvc3+YDpg1rWO2stvBXT9Va9VyVB6IlcDi3xD%200sAAcN1rqLfsqXzKsTUOFMxoBQOCqTdSbAhKm41zJLjcTGldtfFLPuCRxwbfcKaX6JtBtWbk7j6U%20XXD4/vDKx48fExBjwRBGyZTt0iFQ0bnfwg2rF2yaNmh7K5oF0c+Skrdv9Fp9JJN0I9OnnR1J6ofE%20c8P25hYbiOR4kw5G4h0rjuaQCULiltbmolJvIlcs2GePkh2sk9uIfKGtT/2/L0NMp4zYWyuE43Ij%20LXPBJcSWyeloB0vf4W+NCuJtsqHK9n48Ugfxr/W+3tOBRBoC4ea2PStFPgxXM8Tn92cM9rJA+Nj0%20BheC9i6Ha5NfOjpuhua4l34nvXisrYzLf+WyXFNpIMf/ALlSsnC3iGuhZMdzHtBAAAFgCCPwqlLw%20JkbPY0tRS1PvKeFS37BJiE2PG+D25kkYiHeAR1U/dRpxHfkV3N7G4aaQyQ7sWYXLodVNtxb5pSU+%20Y7vgVrl+xeZx2vlxpG5kDQXEEo9A0FU0J9XjWq3ExXdzHAd3vwYvyvKLJidJb72EBLjUltNwvoO1%20VVyUzfqHwT4nNw1yFF2og1UEA2uDdbVKgJ4wVjlO8+ay9/svGO029GrrXBPmelaLbsKXgVnIy3Sz%20B0xe5zrEm5Qa2HQVasibviJfmi6MtDhIWo0ORCXfb4+VU3ZXr4C41+pvE4uHpUFyNa4BUQX+/W9F%20/hkLXfmDmiS5uCFJNtbnonhTvqKq/QxuAakjS4OsAf5fwpJlNJmolfJuZit9uQ3axjQSvigWodhp%20W0JvH7w5rE2x58DJWtBaN7Cx9ranyNqyltJmqkTGJ9QuKb6pePfG9wCBpBUD5jdPHxqfTJuS8X1R%207UZjhjfcbosbgS25Tr6T+yhQY7DXI5H6fcuQ9z8d0jxfc3Y9b3LgNq2+FNqSXgLpIzM7B7dz4Pd4%20nORxadHNkapv8yr6j5ffrVx3WS4sq2f2B3FiKYovfiCndGdSNLa6Vot5MTgbdgY08Hf3ANmhdE85%20sQLXNLTfXp51tBpszmmk2et67DkKHmTOGUoeAS25JBUqSCVIP41481/J+Z2LQZCSR7dzgXPmcHNA%20CNDgASLakrqetCyxjp8cQEYAsFa6VuoLulzYaafG1FqquAM0dA50Z9wFpDQ0sbZmvzXXxR3jQ7MQ%20riYpQX2tRpRuh1TaLJZP1U2vfXvA3ZBFAPQz1kK1oNwpVBp4fglKwxHMhlfjFsrBkFv/AMsONwSQ%20HDz/AE86lxaBMh3duMbJ7mJLLGhLo4HWYNC5bnwF6ixp1ktDjZL0Ln30Bboq3JctyfHpRYXUQ8/F%20Twyb5M6eUBHMa252gIUQIgsh0NBXUxwcjIcQ2RoLXhrQCEeb/wAOpU/qpoV0LMym+69pa90jg0Kd%20BYa31sgP30SQtBmc+F2zfizOJQh7EagH42XpapayUvMcuZ/S2xxhvufMXFLp6iQbfd+6iwr5EMvC%20jlgfHOBIyQbCArSfEW6mosUpHFO6uB5HtjP/ADcc7eQ4zKeS+GVzd0I02oT8uumnWunbnwdaikk6%208h5w/ceOY3GHJa5gAc+GQ3YW3JuhRDW/TwMuknIubxY2Sx4+XNilx2sOPK6Mm+4Gy1k4cQybHKEk%20Qjys/Jy2OIkAzJi+NpGg2A3sKUYJOq8htsj87ufHjha0SBjWOJYxtgBoo0It0qum3mCi+BQ+Z5mX%20PeolDGPCSOde6+WlVcfR7TPJ9uR42NHO3Oji3sUseVBOpc03tTUgaICJ0DJQYo3SPdd8yIoH8nX+%20LrTuOzNRC0Pe8Xe8qgJIRxVQvX0+NUsGbFmQSA9RZAqKhv8AdTuFjdrXbrIGg3cR1Ov4GmI3apar%20/gFUiw/xpAbyxtbu9u9rEjzNxSuVbJiNpLQ5LAoQVVdfxSiwkLiSVAGHao6WBAQrRa7AcwTalxuD%20oOo6OTVbUrCwLulbjlocQxzmh4Q6gqhsip+P302CNo+QIcPWgUfM3qSSQCQutDBGDzTIiDOWxtQH%20cCUK6W/z+yiwEHy3L8hkZI2TNbBGP6aOCEH+G91t1+ymopZIcjONkTNnR73MAJ9LVAc3QhdRfRFp%20dIdZNnKyDjAul3wuV6k6D4a+Io6TRSHMUkrGAwtIaTtcxPVoAS4i3npUtB1jmOaVoawwMdtBLgCR%20uAB6H+Wp6S+sxjy5LGvc6STdba1T1UOOqdfxqJba1aLUz0p9F3yv+n2AZTucHzDd1IEhRa9DYX8E%20cW87yZeK2MjmX1i7d5rl5+Mdx2HNlthbJ7giFmklqLcVzdxFu2DfZklqc2f2D3wUDOFyHIoaS0BC%20ljcrWLhLkaKcfCvYbwfT7vUtAfxWTYhH7EdfwQ1PpS5D60+Is/6fd5NcAOKyHEIWnaOv29etV6Ur%20gpx5mjfp/wB6G54jI3GxBaL9PEeFT0SfCqq4+uPFmR9Pu70RvE5AT1KWdSenhT9KWcApx0vX6fYw%2076ed3OG0cTkEOB+ZiFPA38v1UvSlyDrhzMN+nfdRkJl4XKc0qbNHh8fKl6UraMa3I8xRn057tyBt%20Zw0sTHWLpWgOQ2VF81Sk9qa4D9SPMZZn0l7rgmLY+MnkT5XRgOaOiC/7acYTtlEda5iY+nHeQY5o%204XKfsuhYEKoCBuJ6eVV6cuVVWQ61zFYOwPqBjZDciDicmOaMja8AEqFAJK363+FJ7La0Gt2PMu3H%20YXf2UxkGRxk2I9oBMhaNvpAC6n1Fax/zz5FLdjzHj+1O5ZGOc9kznlVDUautwvxShbE+XvGt2PMb%20xdrd1Y7ifYyZmBUYgRVAW+77P3UvSnydVWjfqR5j1vbvc2Q0F0LoowVDHxeoEhCPTtoWxPkS5x5m%20w7G5HYDJjGY6G7mdUJ2n4jrer9GfJk+pEye3uXhYduBMzajWBp3p/CvnZPhSezNLQa3I8zf/AG3z%20rofZ9qV0TjvdFJENtwdCqj9dP0p8mS5Lmit8j2R3BHkuMHFzPY/amxoPygDxQa1qtqTWgvUS4muN%20wn1IwRJ+Wx8oNc1I4yxrtoHVVcF/RKl9u3wKW+uJIYL/AKmwzf8AUcbNkREhd0YBHqKoWkdAfwrN%209tJcGWt6DRacGHlciNZePyMd5u9r2Krk1Ums/wDPPkN7keYhlt5eD04vF5MrmpsOxBdqgdPBKpdv%20PkHqx5lU5MfU2U7cPiJ4YiAiNR32lf8AV+3xq128uQPejVV7CvO7M76fK903EZLnbtzkYCCfK6LW%203pNpYM/UinwqvgJv+nvdrn7v7NkDadu5rACnkFFvhS6JLNmLrjZoH9g95qSOHySoQI2+ilVPnVdE%20uVV+4Ocef1r9hu/6bd47rcRk2BJIACpbxpenLkHqLmaf9t++S3b/AGicNDRtsLout/v60/TfInrX%20MB9Ou99yN4jKcF2hrmoDcAElSgSl0T5B1xFW/TvvDcXf2bKa4hTZQbKNT0Sh7chqcRN30272jaSz%20iclxAR3pF18FJo9OT4B6i41VaC3E9md7cbke8e3cqZzRYgAFR01S9J7UmPrjbUOV7N7/AOTyzPLw%20mY1qkBiNT/i1trUx2pLgPrjzGR+nHfG8uHDZZABRu0KSAqqSPhWnRLkT1x5mn/bfvqy8JkkN+UbB%20t1GoUGjolyH6seZsPpv3o5ga/g8p17kxtUovgdDR6cuQepHmJ/8AbXvyMJDxGY0aNQBtjYqjmhbU%20ek3wD1Y8yQxO3Pq5gqYMDMlCkiOWNrgCugV32a1H+e/Ar1o3yW3tSPvw87x/927ZeyP3me5mbWAR%20tBHqKqaIbDUlgU9yLTydpr0TiKNlQsdkOLUVyG4su77Nf08D5EpWb4O/3rH7daQm32o5C2RQXqN4%20A8dd2ljRfFvhVeIIwvuOAiduYhRxB+JNrO3JQtfGvcHE3/KMDyrCVVFKKVJFgt0F/wDCwrWuPibR%20tnaf6ri+QgKWhAR1JX9BSloGTdrQRYeIBCuIJF18b2UffTzmvd4CS4My3Ui+3+XUHqCp0K0k/Cno%20NGP6qnc0NIHzAhSSNCPgnWk7PV6DRrOZQ9kcce5pBV6+lm0W+0rpWY2abnMcxk79z5XOIe1qNRur%20T1+UamjqRQjK72YiYoNzYUcZHEePy3BJsdfhQmCGphzJYnZE0wbGbNYCXEKbAlHHwBFO4WGrcPLb%20NpdgRzQ7TfYBQLGl1DZiZz44iYzvEZVznNO4EqDrr8aEwaGQ53LZvbIWPYxxQI5jnAtRC4/ykA6U%20rpodkLCNvKMaJMOOR4ZuaZGBwaouSSu1fOhtBY5tz30S47MzJJ+O5STB5OQOlix5WkwANKbFAbqn%207K1hvdKsKUblK5Lt36kcE4+9gSZcUahssLd7S3VrwOgTpW0dyL1E00ROL3DyM/vQPZLHIEdLHK1z%20S0r4n8appcwwsWEm8ljTyxNycj29zrPdfZvsttDU2YXwZ5fHj47IfE3OidHtDmEvDjtcPSUC26VU%20YN8BNkMcyPJeGF75o0RgcNrQqIEJ0t0qulh6g+hxZpQ5rCP9S2QGw1+y1CSIuPYsSdjiHMcHNKOA%20CIXE2K/DWhyHlirMcuahCKAnUeKqDS6ikqqv1UdjAXaQLEnVV1slF0K3gatxHrZAgsfhcXCG9J+I%20WMFmwaFQqk+AI/ZRcLCRY57LHaXKA467j9/XxqhXN4z7bRuuVC+IBFNMRsZBdrru63au7S1ulMDR%20rpA2TaQY09W1EsB5UrCsNsvMdBEZCQ9jbm6Hx69RTQZIvlOQc+AAx7WyepshKL4/DwqkRK4hhwmV%20210jWhQHkuFlsUBPTw0pEND2MzODml6zRge3dEBsqDy8aBsdMzG40ZdJJsLTtcvgUoKJfG5PEmeA%20/Na2UqCy53EgepRbp41IXVyXhe2Vu2OQOj+X3AfUpKKQAbUWHcVMgiYGTTuY4/PINChsLePWhK7B%203PSn0c3f7BwQ5FD5hbS0hrp2V/ExnqXatSAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACg%20AoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgBB2BhOXdAwrdC0VHpx5D%206mYPHYJVYGFbH0i4o9OPJDcmbtxMVpVsTR8AnRP20LbitEHUw/KYv/0WW09Ip9KF1MHYuM4I6Jhu%20ug1NHQg6mYGFhjSFn/tFT6UeQ+pmfymKgHsstYekVXRHkHUzBw8UlTEwn4Ck9uL1QKTM/k8VAPZY%20gKgINaPTjyDrfM1ODhkIYWfcKXpR5IOt8zIwsMBBCy3+kUelHkg63zNWcfgsaGsx42tFgA0ACj0o%20ckHW+Zt+Sw//AKLL/wCkUejDkg63zA4WGUWFlv8ASKPRhyQdb5iP9n4lAPycKDQbG9Pso9KPJD63%20zFY8DBjbtZjxtb4BoAvfwo9KPIXWwOBhEgmBihUO0WWj0ockHW+ZsMTFAIELACEPpFxQtqK4IOp8%20xjkdsduZEpln4zFklcEL3wscSCtrjzp+nHkg6nzGbvp92K75u3+OPxxYv/hp9C5B1PmaD6c9gAqO%203eNW9/ysK3/9NPpQrsUHYHYwJI7f44Ki/wDSw9P/AE07BdirOyu0GN2s4XCaNEbBGEW1kH3VPSuQ%20r8TLuzu1HfNw+Gf/ANxH4J4edHRHkO7D/Z3aak/2fDK3KwRlbg+HlR0R5BdmP9l9ogEf2bCQoP8A%20kRrYJYp5UvTjyQXYf7M7S27f7Ph7UTb7EaJp4UenHkPqZj/ZXaCk/wBmwlJ3H+hHcqvhTcI8hJtc%20Q/2T2epJ4XCU2P8AQj00TSjoXILsyOy+0BpwuEE6fl400T+WjpQXND2N2aQh4TC//gRraw6UuiPI%20Op8wPYvZhK/2TCX/APYR/up9C5ApNGP9h9k//wCA4/x//loddD/D16+NHSuQXZp/297EVf8Ab3HA%20nwxYh0To2m0hGf8At92KoP8At/jlGn/Sw9E/0+VFgWDY9h9lEkngsFTqfy8d7AeHlScE+A02jH+w%20uyBuTgeP9dn/APTRXsBf030o6VyC7MN+n3YrQje3+PA0IGNFe639N6fShcLCsfZXaMbQ2PhsJjRo%20BBGEUJ4Uuhch9TNn9m9pvaWu4fDLT09iNLfZTaTBOxJYeDh4OO3Gw4GY8DF2xRNDGhbmwpiFqACg%20AoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAG3IcpxnHRNm5DLhw4nuDGSZEjIml5BIaC8gK%20gNqAK13t3xPxXZOb3P2zFi9wN4/+rPFFkDa6Fl5dj4hKr2tuG0MCa7W7j47uXt7A53jnE4fIQsni%20BI3N3hdr0JRzdCKAJSgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgA%20oAKACgAoAKACgAoAKACgAoAKACgAoAKAGcPM8PPnScfDnY8ufCvvYjJWOmYiLujB3DXqKAFcnkMD%20FkhiycmKCTJdsx2SPax0j/5WBxBcfIUAL63FABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAU%20AFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFAHnb/AMosngHdydrYPIwNycuS%20OeXEi5DM/K8QC0gE5jWpITtJDXNc26BTegaREf8AjNI6PuL6h4kDsOLFjxseSLG4qd8+Ax7mPDnY%2073veSu0Kd3kthQmEtEy4/wDiE/mT9Kg3LjhZxrcyf+1vjJ917S8+77oUokihvl95S0HPU7fTJCgA%20oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACg%20AoAKACgAoA8gsxe8c3/yY7t4/s2bG47m5Z3TO5bIBeYsaJjDLG1nykTOcwO9O61iLqtStIotnd/P%208z9QPpDn89JjQ43fv085OSbJdEdsWLLgy7pXw7y+OX+jGChW+nSn5CWqO+9qc/h9w9t8bzeG5z8X%20kMdk8Tnt2OIcOrelAiVoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAo%20AKACgAoAKACgAoAKACgAoAKACgAoAKACgCF7h7K7R7jfDJz3D4nKPxg5sDsqFkpYHEFwaXAoqCgV%20it9y/TOHG7V5XjPp5hcd25ynMNZj5OfFGccthU7nNdjgPL2hx2DS9CQE39PexeJ7G7Uw+3OLfJJj%20Yoc580pV8ksh3SPPRu5x0FhQPzLHQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFA%20BQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFAHn7lvod9V8X6o8/wB79pc9xuBLzAkjj/MN%20kfIyKVrFCe25ocsYRwosF8WGHfP07yeyfpEzsjhc7L5LvbvPPjdlSRmQvzZla7L9WjIWx/O55uPm%201NA75O+drcBg9vducdwmBGYsTj4GQRRucXkBourjregSJSgAoAKACgAoAKACgAoAKACgAoAKACgA%20oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACg%20AoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAC%20gAoAKACgBKX8p78Pu+3+Y9X5fdt3qnq2Lf5dUoAVoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAo%20AKACgAoAKACgAoA//9k=" height="247" width="665" overflow="visible"> </image>
          </svg>
        </div>
      </div>
      <div class="fig"><span class="labelfig">FIGURE 1.&nbsp; </span><span class="textfig">Sampling probe (a) and basket (b) coupled to the Yum-6 tractor.</span></div>
      <div id="f2" class="fig">
        <div class="zoom">
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yOeF89q9xku7BpdC0DTa8VqHNANeyDpmEzuHzePjyOHvI76wkG2O4h+lxpUa6dnKU%20NmzdShNafBBXd5ttD80FUFHNDqV7ahBQRgDUkkigJ1KgNg1oTrr2Op6Hp2U0FsmTaNCQKE7gOnX9%204VZqAdISBQFvRwp/BTNRhZzM4zC2M2Qyd1HZ2MEbnzXEjqbWilT4lJqUQ2+9xspk4WDiGOkn30P3%20t8wxwBjhVjma6169Fw99/sW022k3Vu9mS3FdLTZLCQ39uDzTKyZEQkP+3BEcEbm7Xbg0UcaeP714%20ref7TvM00xUiPZsW4YjVpJeV4PMY+TBcSxkmXhq7fHYglkR2lu5zyWkOa6mizeO8Nvcl3fdWLo9S%206+2IaTkOI5jisLdt5xmX4yD7NzsHJabdZY26QzuoauDelF6/b+A29kzfdbW5g+pd0c0xVpbNtobm%20JjfuJmtdLO6jnuefzE/4q+C5e4yzWbY5QtSFu+45gsjKJLq33yg7myNc7fUnp11rWuinFvMtkUid%20CbGotcXY2nKJ7WzL7a4ngMzbhpJNR2OnRdHLmm7DEz82p26t1BeyMabbItbC6YOax1f5UrCS0ivi%20VzZxxPzWa0/BMSysPIzBAWjrEZLjUz2zXGIko8Qy1H+YhrtO5o7V7Kb75zTXu7cvS71j0lWZo6Xx%20jkUmKMuR9u5zksIXVy+OeN0ls+m8+Qag7RtrSiybTyt+3u7Nz8tf2z0njmrdryds4vzHA8ltvWxd%20x6kjA19xCaiRhNNHA/uXqceS2+KxLG3bQAKONHO+Xc/H+KtyKqlwrUnygVI/3qR5JkDhpXs2v7ta%20fvVai6OisCAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgoWtNa90H%20ieGCWJ8MrGvjlBa+N2ocD1BRCH3WFyvHbn7vjce/FbS++xW+hBbqXQ7t1CW9giW9wfIMZm7L7ywl%209SNuj4yKOY6lC13cFKjaxijaVqg9ICAgIKONOvT/AGILYBJ7ONK+YdzrpXoopIiPuL7n8b4Kyxdm%20nTNkyj3Q2LIWb90raeVx/KPP1UX3Uj4FEA5zk/cq/wALfTty1ti7NsEnqWrI2zhzSKkOlH00b4Lz%20F3+0Y/rRji2dWeMM9UT9nuY4PjfJ5ZstK+OCfFQMjkYHStBaRUOI7nrqvTX322zFZpVink7Bnfa3%202/5Jinyw2MNuXs9aK5tP5QLy3cDIyMjf4kOV7bqq+6E+xHNL3OcjyePEIsrHGQmL0IWsZDJIx/pm%20XawbQSGhQO5trtFTX4qRUgHQ/uQUc7aK0J+SCjpY2gkuoG1qfCn/ABQW98MvmY9r29CQQelDRKCJ%20e5nuBa8G4+crPay3cspdHbxxH8+2rS6vbpUqPcfNX/s33xuLl2Qk5PDbSNNLWzELNjw7zAFpb11A%20NVzs3kbbJiKVWi10W097+Tct9DAYYxcdz8QaMheXlJIpXFtHm3AAr4tUbvyluHD9Sl12lU22apFf%204nj1oA/kNzNlJ4wXTG6kd6dWjc4CMu2bXFtdpXzjJ5zyG6upZdMR6R/JtfTthrMbzfKcpD7Tg+Mk%20uY7dxjfNLS3giaCCB5hQ6eC3tp/qefLPdln9VZy2w3eB9nr69c6bm+WdlHOoYLO3LoWRV8z2vc3a%20XVXtdn4Xa4Y0tirBdkmZdAwHG8Bx+2NrhMbDj7d7i57YIw3cT3cQKnoutpDHNZav3Msba74HnPvI%20Y5tlnM6J0jWu2O2nzN3dD+KRUh8fYa8kscTj7fKChlY0W07da1HcDp2+C8xucUX33TZ05s1tzeAG%20lRoWdRoCNddO651WSrQcinns8vi7q3a1rX7o5HinSugOgP5l0dlS+y+27opLd3Frbyt2Ts3MDvL1%20NHU8R4rQsvujW1LU3WZiwM8EGQkkmgu6CCVjdxBBALT1PfQrbs2/14mbIpNvNWZpzbFrsxZTC/4z%20kf07IO2iVzR/KmYKOEcrBXWvc9lji+y+OzPb3WflPrC2nRO+LZuDkN7K/iDpMDyqzAlzFi522GeQ%20Hzek40Y5u7sB07Klm4zbLW67uwz+3rT4o7Ynk7Fw73VxWcP6dfRyWOUjAjf6raMkkBo7YRQdRWi9%20Pg3uPJGk6sXbKcBsjK/HX4darbiJVe2uLgdzaAjw6+KRNR7UhVAQEBAQEBAQEBAQEBAQEBAQEBAQ%20EBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEDQ/FBQkMbWmg7BJkQvlHE8i7I2ea41cNsLqxmdc5Kzh%20btbkG7aiGQjvXvRBtuN8rxnIrd0lsH288RAuLWYbJWE6EFppXwqg3cZq6oPXqD/uTmLlRStdOtUB%20AQKBB4FKOJaaeB79uiQOCf1WwNnZxWJ9Qx11PV4ANPI3pVa26u7bJla3m49YXvLOONnFhkX3eOum%20bZ8dKS5ji6tTXX8ui85ddt88x32RF0dWW2vRMeD+6PALJr7KXBPwVxM4ML5AJI5HHyksc76W/wBi%205nlvF7zLS63J32x0rSi9s2+jon6NHdRtvOK5iXG7N75jYOE0crm1JZI0nuR+WhXN2Pn91tbuzJE3%20RMxz0+5a7HbMOZexHMrfj3J83d3trLe/ch4lfaje9u2VznVYfMevb5r6PO7stiO6aVatJfUOHzeH%20y9uJcbdxXDWgOe2NwL21b0eBQgjpqti26J5aqzDPZu3eby61FdaU0pXp0SB7eNtDQmlamtOqmRq+%20SZX9KwV7kGxCf7aF8npV67GE9j001UzJEPix2ZzNg777IZe6+2ycu8MjnfC2B0x3BgFakN3darjZ%20NxfkupZNKMtIjm8ch5hyyx4k7F/f/rmGnuPUivLl5dLaveKFod4EeK2cGa7J8t+l0dOdVKJPg/av%20G8kxdtm+HZsyZmxjEt5jL5pdHIdpd6bO+rht3Lh5/Nztsvblx/47p0mGTsr1c2Fjl8tYXwv5BZZb%20D3JkBkq2ZlXEOaxrtp2M+fQLu/WxxSLYrbf1jkpMPrngntJx2fG2eUzOQk5Q6eGKVhuCDDG4t3kt%20aDVwJP5lfD4/DjmttsQib5nR1C0gt4GenBDHBGAKMjAAoBQfSBoBotxVeogqgjHuEC7gvIC5oB+y%20l0IP+E+HyVaph8jY+GKbB2Ynax7XQADdQkOcKVqQBX/YvH5bptyzSerLaY4ZGOSWC+LZImGlrKDV%207mh1AHDx+StuJtmIm3SVmu5xaT3OGY6KT0zBM1xJ0FP9oW34y+Lb6T1RfybyB8UtpBJUSAxsJcOp%200B10HSi0Mtk2XUTEtDzKa8tIMdd2lY7uG7j/AJwAJa2tR1XQ8TfEXzHSiuSYl9Bc19mJMlaWef4m%20Ybe5dbNkyOPA2suHFm4yMDdBIT2Oi6u92Nub2n1YomYcUliivC5oMlrf2wIbMN0c8EjTStNHVB1o%20V5+6L8N1Lv215erJSqb4D3Wh9Gz47z63bKJiyHH52MAuMgFBLMT/ANt/Q7uniudk8RdbdOfaXdtN%20Zt/GkMnd0l16x5bl+M/b2maLsrjLlzY7TJwN3GNlPquD020/MF2PD/7Ji3H+O75b49essd+KkV6J%20+14lY2aF4khkG5rmmoLTqCD0Xp5Yl2tCQa9aDrr8kiQDBu1Oo0GutOuqUBpG7QmnYHxqapUe1IIC%20AgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICDxJU6Cvjp80HtAQeXt3Fp7t1BQUj%20rUlwo4/2BTI9qB5ZG1n06DXT5oI7ybiFnmZLe7hlkscpZkyWt1CQBuBrSVv52V7FKoQO89/7bDch%20ZxzM4xxyf1Pnt5GOidEHBpl69Na7eqJdHwnJsFmrczYy9iniY703dWkE0NKOoUqNkaU2tNW9gf7A%20laC6zdrX6fy+P4pI9dxp+KC2HmlD5iK129eyio4t/Urx7PZKDjt3jLCS8t8fNNJe+iKujaWtAdQa%20nX4LX3OPusmITDi7ZmSl3pv1b9bdWkHStWnUa/NeTvxTZNJhmhSe1trppbcRtc3Xa5zauaQO3xIP%20grY9xdj/AGpq1tlY5fBSG447ezRPdQS27nO2O13VdQ0J/s+S2p3NmWKZrY+5HbPTRLOM+6dhjsjJ%20Nn+OstLi4e1sV7bABsdKbnSAD466rS33jJz2UxZNI9Vrbqc05zmY4DkLeG8t8wY7uMmW0/SnGOWZ%207gHNZIxgo7Xs6i43j58ht76RExb17teP0WyTbOqS+y/urmOUXGTx2XgZBFjdjba4lPpSk/T6crHA%20efvVui+j4cs3Wxyn3jk1Zh1cO3Dztp3B8daLY0lVoPcQRjhuU12j7eU1FP8AAelSFS+NE0q+Mstx%20uHOYOygdIYZIY2OY4a1Jb0Pz8V5zFufoZbutWbtq02D4zyXEPkt4w24s7xvp3LZBVjWEeYivRw8R%20/vXQy7rDfOvOFItmG34ZfTS2rWRSG0u8S9rbZ0bi2Tya+ZtdRp+K0vJWzExM/Nbd+q9l/wBjp+Rl%204p7owDGcpaOP5u3rHjsnDJRs/qtod2gqHU6OK4eH62w+fDP1Mc/ut/409GS6IlNfb73EveIW9rxP%20lmJOJtbIttLLKudWKcMGwSkAeXdSq9dsfKYdzbE2z0+5r3Y5h2q2khkG+F4fG8bmOaQWkEVBBC6K%20q+gII37ihv8AobPA+UOspQX/ADbTXUJRMPjo5KPE4Czl9N87mRAMiBFXEDQE9l5GMM5c10Vpqyxp%20C7g89a5UXAjY6OW3oLiB9DtIBGhHXuFO82s4qe606sjJWEV5YTW0jjtewkOZ0rQ0/iFi291L4mEy%200Pt9jsq3EXWUEcj8VFObYvAMm17fMKgA6ebt+K6nlLrZpbP7qMdusN5fW/3uLuYYnAMkjNXfVSpH%20Y9Fzdvf2Xx7LXRXm+if6d8xZX3t5CLK6+6+1lMM7jWjXAU0qvXVowNv7h+02E5m2Gb1DjslbF0kV%20zC0Ukc4dJRpuFevdY823tvikkS+cczhsnibyfF5ywdbvc98THytoy4aKtJYehbrp3Xmtxtb8F0TH%20JnsvroyOJc7znBYTaOikz/H7l49WCZxdLaxCjf5ZNdzdvRq0N743Fvvmifp5Y9P7p914mbfg7HgM%206MNaSZfiMx5Fi72RpmxrJRI+3LvNVhG5zWsH5KLJ4vzeXBP0t3FNP3T1p/FS6yvJ0vEZ/G5m29bH%20zsnIp6zWHzxuI1a4dQRVezty23cprDBSjYiobQ9D16179lapR7AaDUaV7f3/AMVMQPSAgICAgICA%20gICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgIPLutNenQdeqD0gIBIHU0QEBAPQoNBm+X8c%20xA9PI38cU0jXNawVkeKA6lsdXUNNFjuy2207ppUl8m+1PGMFyX3AujkreS+hubq8LCXybwz1C5rm%20kGooKK0ZIJh0XmXt9zTjV9F9hcyZTDEVs7h1IpoJOux72fkAb1cP71ZPNt/bz3V5LZ2zbfm17ai5%20fc/bG3NGviY4lsDmFtRKH7fh4pX70O4xjcCa6GhaR1I7E06qKD20P6uPboFIp6TKg+CigqGgdCQp%20HPuY+y3C+SzPvHW77XKAOdDdW7hGC8g03tAoRVYsuG2/mmJccz/s37kYQR+jAeQRFpL5oKMla7o1%20oYSa9OtVy8vi7Y1sXjIhss4tpmwXsbrG6d1huWmIuPQ/V9XYLlZtnlt5wyd8UXHtDonRvZ6jZBtL%20HdCOuui1bbpiaxKZiGsx+EixEhuMPO60eJBcNiID2OkaRtGo3AVC3r9/dktm2+KxMU+/mr2UTK05%203Z59mz3Ashhru0cH2V/jgdpcAKyPDHD82oB7LTs207WK7S7ur0unjiif3c3S8d7j8ijtPvcBfWnN%20Ma0gSsB9KeLSuhYHVo0dwt3a+fvtv7N1Z9O7pKs49NG/5N7h8dyPC8i114LK9+2krBcfyXF3pOq1%20m7R1CvQY9xjyxPbMXUYpij5usB/461P/APUwingGjReVzfvmnqzxMsvcQaNpsHUddCTXQ99P20WC%20kTzSg1vjruPkeS9aZsUznevZx9N+opqOldO69FddE4raRWGKmuqQW2ViuA60ykYtbgECj/8AFUBx%20FdAWkdfiuZftZtmuOe6GSL5h0fAe480UDcFyy3jyWEkY23F05lZLeEtDDvJ+rSmo1XD3Xjovu+pi%20nsyR0/5dV6+2iV4nI5v24bBLgXScl4Rd0MkYd6k9lVvlMZqXPj29WnUfvXd8V/sUX3Tj3FLMkfZX%20j7mK7FNNHXeO8pwfIrEXmFvo72BhDJiw1cx3drx1Dl6mrC2rXbwdrjXUU7afJK1Ee9wg4cCz3b/J%20S01p+X9uiiI0KPkXHW7XYa1imaJA+BgcDQnaaUr8R815C/JNuWZj1Z7Y6PGLwWOxdxPcWof61zrO%209x3V1roB418Ez7u/LFLui1Ihs4gAXtf1P1dwR3+a15mk1glq/b/nPMuF32RxtjjIL3ESTfcz2Uw/%20mlryG+pE4nafK3oun5PZ7fc47Zvu7buk8fz0+Klt0xydPu8BxDnNpLnOB3UQyLRTJY+pY0bmlxaW%200bsfWor0K83Zn3G1vizdR8n9t0R+rNSJjRsv6UmX2Ig5Jxq9x0thd284uaTAtcQ/Sg7EDsV9C2u4%20tyWRdbdF0ezVuh30Rg1DqhvYdqdFmjVVqeU8WwfKMe7HZeD1YiSI3N0cxxH1Nd2IUzbF0UnkRo+b%20+be3PI+I3LvXiffYLzGHIMaHFjGjpPTpp1K8/uvGXWfNjZbMiLYPK53iF7Nl+ICIS3QH31jNV8Fw%20BUhw1BD9dCuduMePdWxj3FdOUxzj+S8aTo7LxPl2M5I+TKcWumY3k0UIbf42RopIfqptFN1S36x0%20XMw7vceKu+f5sN3Xj8kzbF3xdI4vy9mXBsr2P7DLxay2clRuH+Nh/MKr3Gz3+Hc292O6LoYLrZhI%20WF461Ap5e/4kLbiqq4CCQakU0IrXt0KtSoAOaKudp+bX4U8FED011dK1NAT+KkVQEBAQEBAQEBAQ%20EBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAIB6iqDxsa2gBo6hDSkyKtPWmoHevfwQa3kF9d%202mHvLuFo/kQSyO8aNYSC3XsokfJfDvdy7xBkuuTYk3L7xpEN9BV08u7/ABveXU/xUFF5jyvj8u5u%20tnHkpMdJ5fd/P8WWy6jV+3d5B/qG4vvvbnG2TZp558mAWPYZjURUIJNOp00K6O43F2HFEWa5NI4/%20j1TERL6BwnuFmofWt8k6DP42RgDDbkNnax4p/OaRQhwH4rW2/nbe3/NbdZKJx+j5/wDcS3xMnuZZ%20XODs3wYt13aB8FwHNkjkMrq7Q5zhtAIpT+xduzJbkjutn5WOkvtVhOxutBsGulfmssclVY3PJJ6k%20U0PTVVhK6rAgtOaDoeoOhGmvbrVKlHsmoBH00qDr/cgjXMvbjh3MmQjkOOju5bUH7WYkh8ZcOrXC%20ndRNsToOKZr+n7m1i+Z+DvI8tZlx9GC6c1sjGVrRrwAPADQrmZ/GY7o+XSV4vogeWtMjhrmO0ztp%20Ni7qc/yYbobfU+MdPqFRSq4+XZZMcaxWGWL4eaeXY7Xc3zM7OBH8VpVmE9zGxlvLh5JLjA3M2FuJ%20GubI62I2uc7/ABNJcDr21Wxkz99IviMke6KM6/5hf5Lj11Zc/tjfzxefE39g1u5hDaUkGvXqSow7%20O2zJF22u7Yn90XfnCKzTVg2QcLK2L6EiKMmg/wCT8P8Aiq5/3Sler5hU1cDtaT0JrWvZYqLIvyMw%20Y7P4y+O577k+kGjr5nA0HX4LsbW+cuK62f7WOdG/yWKsr4k3AIlApHICRT81SO7dOi52HcX4+XJa%20jVwZe9xr222VAfDJRkMjaUIGhNPAimhW5ftbcsd2Pmiqa8P5jl+KStfjCLzEzEG8s3UppSro3djT%20suLu9lj3MUyfLf0uXtuomtkyQmbkns5Pb292Zq8gxEraQznWQ1aRVsutAQr7DzOfYXfT3lZsu/bd%20z5Ivsi79rqnBvcbC8oluLKGKSwztkAb/ABd00sma12m9v+Jhd0cvbYMtmS3usnutnq15iY5s33CL%20jwPPD832U3z1b8C3+1ZrkQ+ScWHDFWe7tE2tOneuo8F4vP8A+Sfiz2sjWn7q/tqsS8yUGulRWv8A%20E66/MqUWtBlMhb4jk9tf3s/pWs9sYW9T5mu/OK9F1sOP6uGbYj5oljnSUiwuRv8AjuU/XOPiCK9l%20o269Qn05oupNARqdKf8AFc+/tyW/Sy62Ms3fe65iOc8f5RkWR4++mxHLoIQ6MPb6frNGoZUikke7%20Qrk22bvxc9+L58F3PrSn5aJmIv8AaXRMHzuF8sGNzw/TswQGtEgpFcPFA4wu6EV6L2/j/KYd3Z3Y%207uXP2q17rJhKjtDQWtoa0La618F0K6KPE0cVzbSW87BNBK10crHdCxwoa/DqFNfUcF9w/ZS7xT48%20hw+0ku8e7d91j91Xxkk0MVfyAdlyt542L9bIpcvbe5K0vuJxksTfS2mVtQ6Fl5CaPZQ19J9a+XcN%20VxpumytmW2tvpLNXu6uh8T9yLLOm3xnPJ2YvkkT6YjI29WMlrQUDqlu8uodp0XKybHNs7vq7Gs45%20/dE8/wCie6ulzruJ53c4pzbHl5Fs8vEFrkgCYrh1TtrQDa5zafCq9V43zmHc20ifnilY9/b1Ybsc%20wmxJJqKiuh08SuzE1YlwebcKkHStOyc0vYpTQU+CkEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBA%20QEBAQEBAQEBAQEBAQEFC6hA8UFPyaN0/w0FUgablI3cXzG0VJs5gKafkd0qo1IfGuIucffYa2iBb%20JsiDHscBUEVqKH59l5PdxfZlmdWWz1VuMJJHJ6mNuHWM28OIrvYaEddSNKLJbvul0VWp6Nvh+X2m%20KYWcvxL78vmbcW95ayekQ9oHlcARXRularHm212aP8V3bSKax0JiI5wzrjCS+4+fnyXHbqB1lHLA%2065Zcj0JWBjifINBoNEw7+PG7b6eWJm+eVNeP6r07nbMbf8twFw9sErs5YvaB9rcy+nJEWkaskf1D%20ugHitDx3+4W6xnr7THHRW7BrokOB9y+O5TKPxZE1hlIx57W4YW1O7aQxx0dqOoXstru8Wa3uxzWG%20CYmEsEkvQjWvcePyWzEoeg8VFCaft2SZFWUOoHl7Hvrqpge0Cg8P2CDyWA9CW/LRRMDV53ifHM9E%20yPM4+G+9MFsbpmBzm167T1CTbE8xyjl39O+7bNxK8baULzJZXJdJG5p+lrCa7NVpZ9hjvjSIiV7b%205hyPl2IzfDpYo+S2L7MT+WCeOk8R3GhLiz6QK91x8niskdV4uiWnys0UuLnfDICwjRzetdp8tR1+%20a1MFvbkpdCZZNmCbG2FdfQZoNNaCmlPGldNVXP8AvmnqtbC6elKjx76/tSqwwmYaDmcL342O4bGJ%20ZbaT1GbdC0tB1J7Lo+OuiLu2eVzHfbDe27hJbxSEkOmY0uc0aVLQPLQdFo5LZi6i0TWWm5PBjnz4%20u+yUb5bG0uGuuYGnV8e9ocNPHt8F0/E3UumI6q5LYo6h7i+yOXxMdryX27gMmGnt2yXuElkIexrx%20vD2GQkCjXUoF2M+yx5ecasUTTWqAcX5bdyvkvuMXb7C/gIF01w0LezHs7jtuXmt7srbZ7MtvfZPJ%20sW5KcnWbW+xPuIXCB83HebY5gfDeRP2F7aeQ1Yf5kZefoNVxceXP4ye+ye/Bdzj046LXW93xbHKe%205eSx3FMzxj3ALLbPSY+R9jfRAOgu2AbKjbt2P3CpafFe38b5XDvLJuxzy5te6ybZcWxuuMtA5vpu%20ELTtPY06k/BeezxPfdPvLNbNIZRBdWg8QR+B/sr+xWKJjqKEjR3WpqPHzfvp+1ETCL8+ZZMt8fd3%20Mfqsjm9MQ0qHB2pND/eur4q6a3Wwx3Ryba3x9xjnF2OcZLCZoldaSOq9u6hq1zvl0WvlvtyaXR88%20dSLdVxjbLLRMuITJDPCaR3DKslieBUFp0J2nVVrkwzMc7evpMLV0dO4H7gxZaKLAc6ax97EGR4zK%20NBBld0Em5msb6EfHuuTufHXWXfV2U9lKzdHJasTzTnCe5t3x/IuwfLHPfEXtZi8kwAtkjH07i2pO%20lPN+9et8f5O3PZFf3U146MF9kxPs6qC2Rgk0ewirHDuDr+4rrqKktDSQKtcBUEdlFYHLPcr2Vts8%20xl9xZttiMs1+66qwtjnadSHNb5Q41+qi1NztLc0RXmmJmHAcvif85Li8zY+lfW9XCOQ6gAkCWF3x%202fNefvxZdtOnVmi6qQcZ91b7Awfp/PWOzeCeWxY67Yxr5Yakj+dXzu+oUfX+5c7ceJjPPftZ+nk/%20ujpPw9FovppLsuHz+a45E++mndnOLTME1rIw1ltYAKg+YbpAWlb3iv8AZrbp+jnibclunxlGTFEa%20xLolpe2t3axXNvL68MrQ6KRncEbh+NOy9bo11/eeho0kH9/8PmrSiDzmgBPQ+bXvqgqWuAoSSAKk%20D4GoA7/BRMfclcHRSCAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICDy5pJqOvz0%20UTAqGgf7vipFHRscCHDcCCCD3B0KCA8p9l/bzOw3DhiobXISRvEN3BWLbIQdriGEDQ/BY7rbZ0kr%20R8oYyy5daZS8x8ttPciylkikha0ucQx1Gy+b8rhouduPGW3cua0TPVft+RYuaR1tcN+1ma7b6Uwo%20C8ilG10/FcnJssuPXnHsyRev3WBsJXCSLdbXMRLmTwvcwB3/ADD8Fjw7u63S7W2egy8Zyb3IxURh%20ZlH3Vq6rgXGr2600NPKQOn7BVv2+yvurNkRd7cfetr6t7x+wwWdu7aa05He23M7FzZYpL8ufDFNo%20NrWnyvG4j83RTO8z7We6LLZw/wDp5o7Yn4uvw+5/LOO2lvFzHFHIula0Ov8AF7XRjZTe97K+XxoF%200Nn/ALLts80ie2Y9VLsUwn+A5Vx7PwmfE3jLkMpva0je001DhWvdd626JiJjlLG3MZNDXTXp4Kw9%20ICAgILc3bwFan56UUTUWbqxsruB0N5Ay5hcNpjkYJPgRrVSOV+4/srwQYG8v8dZnF3MMMj6WjnMa%20+jSfM0fFa+XFZOsxGiay+c7jP2OLx2NN0HPN1HG2ONtAKhorXt+37/Pf9Wc2S7t6fzZ4uozMXlrf%20IOmjijdFPDrJA8ncGjQPqOtT0+KwbnaXYqVR3VXb+J0+PuoWmkksb2tfWlCW6Guix4L+2+J6VXR3%20jN5d4iytbXNTUF4duPmHnjoCRscfymteq62/20ZPnsj3ljtub/Lwtlxl1H6fqy7N0MTj1c2h0/b+%201c3axMZIn3Wl2z2q9z+YniMN/wAnx5v7UMjbBcWTY2GKNsYqJIq16d127/MYbMnZfPbPEMPZM+7n%20Hv6/iOdyGEv+EujsMtJvdezMidCSzykNkbQV1Wzl3GObaz81vHHum2JQPGZ533DcZnGussxDtME7%20HUDw01DmOafqHXVcXcbbSb8XzY+sLxd0l1DBc4xNzYuwXuPG3LWc0oZY3r4g7YH+XY8jpTQh689l%202WS276mznsuiJ7orz+H8GaJiebRct9ueX8LbNkbX/wA3xYF0kYY7+dZ27NWudX6wG66are2XksG9%20+Sf8eeOfpdKk2TDWxt32lreRFslvcwi4heCK+mTo53UsPwKy5cN2OaXxqdwHBwGla/Gmh6UWLlzG%20r5JasuMNK0xtmczzx11oQCagfCoW1s7+3JXkrMaN3Y4PMf6Xscs8NubZ7GNfPER5HubXY8VrXX9q%20LFub7bcs21pVaz1aXN+nDaS5GFxjmgZ6nqM/M1oJo5rfHTt/uz7Skz2XckTbRsLi1uYsbj3Zu0+0%20Zl4RPatlIcyRujTtd0BWTc7LJgu7o/b7KxcycLyPK8eDrbIRv5Bxcjz46ZwdPaMBruge7X6SdP8A%20csGS23NrbP083SY0iZ/9S0TT4OkcU5ZmsFBDl8NfuzXD7lzX+m0OfLbxAA7HBwqHbTRbWz8tdZd9%20LNExfH4/Bj+nSNOTtfHeT4TkVn97jJhNEKeqKEOY5za0cPkvSRdDHRsnENNGgnTQ9/Hr/ckzTQaD%20mXBeN8rtGxZW2D54twtrptWvjeQaedutASovx23xSdYTEvmrmXD8/wALnZByBsclpdOdFa3raOZO%20D/8AkaAdppodF53c+PvxzWzlz+C9uTVqsJneUcUv2z8fuTLi3OH3+JuHOex7Guo5sNfpJboOy0Mu%203wbqztzRS+OV3L72XXo6ni+e4G4x7+TcMyn6e6KUPzOJuAazE+YxBjz5X9mubpqqeOzb3Z5IxZY7%208U/tn2Y802RFZmjqfCPcLj3Mce65xRkbLBQXNtM0sljNdQQ7rQhezx5bb40mrXsyW3xWJqktPKat%20FKdGg9j4LJMLqgBzteop1HTvT8UhEwuIkQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB%20AQEBBbcC0UFS0/HX8CgRvJcRQ961PgUFxBQNpTU6V/igFtST8qf2pAtfZWgkMjYIxI4Ue/Y3cWnq%20CUGg5P7c8P5FbPiyGMt3TEO9K5EbQ+N7h9YpSpB11VbrYmCr5L53xHkHDOTvwOFt77MWxEbxcOhJ%203veXNpUF3h/FaObx+O/VeLqMOfMS4+5EObsZcdM4kM9RpDXOI6kkAafNcrL426yNNV4ubDbb3Eeh%20jlLQNrmHWtdOmq53zWzXkvp1bDDcg5VhrqOSyyk0lk1zXS42Yh7JNpBoXOrTwWLNh2+WPnsju/5f%200XiW5veQ8F5C4QzWl1xPM7wbPKWZJpI40r5SwH8e3VW20brbfNjv+pZ1tmVLoh0fF8u9weKY9kV6%20xnMLRjT/AJ63kDZ444x+ZgB3Oc3VdHZf7Riy3duS2cd1I59WO7H6JbwD3a4tzazlmsnvsLiN22Sy%20vaQzAdKtaeo+IXp7bouisMUwmW+QGvifp69vFIHtshP1CniO4SJFHTNHQjUVGvVJkVIc4h3hTSqU%20HmQVIFCDrRw666JJRoPcSg4dlamn+Wm1Nf8A8bh2PxS4fH36Za5LD2sFyxrmtha6NzgSGu2jpqPB%20eU/7E48kzDYm2rT23BBbXUU8GTlDIi10pLfO9rSDt602rav8rN1sxNvOqn0tUscC/a0Aeby0GtAR%20QjsuTFImrJSjD9quXYLFtz3GM9jDlcRNcFxuNu6SAOq1ztp+JBqCCFv+Vw5MkY8uO7tujpXSVbJj%20WG35JwbOcNtW39vO/kXHbrcY7iIF0lpFTy7mtrva1rh1NVqYN7h3OTt/8WWOn/KePRNKR7IFwa75%20ZZy38eC5JNYyRyuf6EbvUgfGTQEh1aE/JdjyEYZst+rZF0MdmiY8r5Rd5rL4ma/xLLK5t4XRS3lu%20/fHKXGmrQARrqRotDbYLLcd1tt1YmeU9OPtZJu6ywMniMbl7cxXAa/bVsM7dTGT30I6Vr1VMGe7D%20NYJisNBFkcjxcssc0XX9jOawXzddg+na+vw1W9OGzcfPj+W63p/BjmaTq6Zw7nuU4z6pkLs1hbgN%20AtJH1EMQBNY6766flK87v/HY9xMf/jyWzziOc+7ZrRseRezthnQ3kvAck2zbI0z3WKaXFkri71BG%204bz6f+EtCpt/PX4JjDure7pF/wCFWK6zu1hzY8gvGPuo7mDbPHM4XTGAl0JOgh26VAP5l6G/bY74%20tm2aRMaek+6lt8zDeyRRhj43TQyF0TQ4RyNeGeqKBpqa1qtGcV1kxPGjJFJ5JF/TlPHDgM5i7q4Y%20LmC+9WRszwGCPRrXUf01HbTVc3/a8d112O+2Jp200jr9icFNdVznvLfb18UmPx2JbmMg1kkj32tR%20GzoAXPaakErJ4LZbn9+We2335ovuifi6h7VcSust7ZY605fHDfwSwMdjBtBMEbmFoNQG0d5gve9u%20nbLBLlnOfbfkHCXxOmL8pi53lsN3bsJfE0a/zxTp5vq+S4m58Z2fNZy9F7b0bxGQy2AnNxgpWtgm%20/mXOOdT7W5FKlrhQ6LlZJszRTJH2/wB0Msc6w6X7e8hxPJhPPxAy8b5BZyD9SsJRuZKHavG0n6Nx%202h1KrVv3m68dfF18/WxXRoiYi6vSXW+L80ZmZbixubU47JW5pJBMaiTsHRuo0OFfBev2W/x7i3ux%206+rBNsxzSZzG1r3dQuGpGnwW8qx8hjsff2z7W+t47u3dUPjlaHaEfFRToPnXnns5m+Metk8XK7KY%20iWR8slsG0ktYx5qNArubTRcfdeLi75rNJ/NktyTXVyvKYC1yrIrm0kNndNBdHdxClSBVu5umtQud%20h3N+KsXx3W+n4JzRbdFJ1rxq3XE+d5K5yEeOlmfhs7DGBHlbSjo7lrTVzXANbTdtB1HX9yyzgv28%20/Vxftu/tnpXT8/u9Hj9zs82xunLinus1rbPHt8f0+juEe51vmJXYvKQtx2Rija5j3yB0U7QAwu3U%20A3bvy+C62x8hj3ET2845ux43ymPd2z2fut5wnLZX02bS0jt3P4/Fb106ulbNWSpSICAgICAgICAg%20ICAgICAgICAgICAgICAgICAgICAgICAgVH7+iAgIKOaHCh/BBUBAQEFA0h1a6eCAAQTU1B6DwQVd%20WmnVBaoNzXEeZpIDqVNPn8UQxMrgMJl4vTyljBesoWtE8bHlocNQ0kVCiYS4XyH+lgRTTXvFs5Ja%20OL3SCymj3x7RqI27S09dNVr5trbk5pi6jlV/FyTCyOj5BhrmwArtkewkO2HV9W1FNFxc/jbrf26s%20kXPUU9tdRhrHskjfQgOodNNNa6aLmTZdbPpK8Sv4i8yuGuTLib2W1NNronudJEeu7yV1OuinLfbk%20il9sT+aat5mOX8e5PDFY8vxklpIx7TDmsYRDJV2jg91N1NakV7LWwbbNt579tf8A+27Umk84dD41%20k+Vcawb28ezVvyywgrM22unbrprCKiJj2uFfKKAU+a3dv/tF8TFufH2V69ETt6xVKOFe9ODzVu9v%20IbWTi2VbIGDHZAkFzTXa9ri1oIOoXq8OfHkitl0XfCWCYmHQGXLHjdEWPaepYQ7+wq8zRD3HJuOr%20aFvQD91eyuPT/nUa+FPFRI517+84j4h7fz3stob1t4/7PYwhpaZmOAfrX6VF0Vig+brJrosfahzt%20fQYSSaaFoP5jULxuaa3zPu2YXH3Nu1xY6TzHSg6gjqK+FP4KsYb5itNCq4KlwOuh0GnU9q9z0WMm%20NETv8gMNyuMxxBsGSZtvHgEA669ev4/2ru4bIy4KV1tUrSdU+4tyvJ8YlkmxRbe2Nwf8zjpHbmSC%20h3BnYErgbna2Z6Rk0ujld1XqyctwTEXcM/KvbgC4upgP1jjxG0sEjvUJj+nb6Z8vgr4fIXVjDuop%20/wAb/Xp+KZs6wi9lkbW9eCxrobmJ2ye2koxzN31bgdunaq2cuG7HznSdYlWOT2wRSSvDWGJzCOmm%208Anw7aKsxdNtea1WRdFs1WPhEsLwWysIqKanvXqP28aYp7dYnUpRFHYzM8VBucRXJ2MtTLauruia%203UbKHwNei6lt1m7il/y3R19asNJjpolfFuUSWs4y3HbtgfRrp7SpbGT9WyVre/aq526wadma2sdJ%20p+MMttOboOQwvGvdiCC+xs549yjHVEsbQ0GTcPM2QCm9u4ddVxsefL42e26Pq4Lvw/hx7rzZE8ub%20k99xvKWeRngz+Ndh3RNeYZG/y/uHM6SNJO2lezl6rFvcd1kfTu7/ANGtdFeeiH/otzFZXN7Oye+i%20u37AbdxEjCKuHqV+pv7fLo/Xtm6LaxbPHHGqJX8ryZ0cVtJbxMt72KJsEMlkPTbKHD6JG93A9f8A%20Yr/Rm6ZrynivH5qXS+qPZv3k47Pxqxweca/AZXGxRQCO7BDbgkVc6I7fpB+K2PqWU0uj70zDr4ks%20rm38hjura4ZRzQQ+NzT18RSivWEOG8+9i7nHtu8xxJ77qJznT3eIeAXVHma23IpQUPRaG68fZfFY%200mFrb6OPXti27lhube6lx+QtXgsuYCWStcKkxyUINNOi4GPJdimbbrax6TyZ4mrp2C9wMZysDB8x%20pgslaFv6bkmyGMTuFG1a49DqNK6rjXbLJtJ+vtJm6v7rfT7lppPN1fE8wvMbcMxvI5YhbSsb+n5Z%20gIikNNI3/wDPTWo0XqPC+es3ts1jsvjowX45hKcjk8VY20dxe3sVvE/Vkj3gB1RXy/4tF6CNIY0S%20n9xJrm7FnxywkyMbj6cl9L5LWIa0cQaOc3TsuPvvN7fbxrdEz6Rxx1WsxXTD5vv7W0zXOco26k/S%20MnaXZpDGWfbXBc6pbGwUbtNRpU9Vr7ze3XY7cltsXRd+Hxn2cjzHk8m1t+S3vrX7KfDj8m6tcXx7%20jhmmnlhtTI4v9a4cwOpSlGV81Kkjv2XDzZNzuPlpPHHR4fNvNzvbu22Lpr6V/p9vp7IfnPde1nYb%20fEY378a7riZ2yNjm9HM77gehqunsvD3Yp7r7u2fb8v6Ot4//AF6/Fd3339k+kPo7+n/N88y3C3T8%20xi9IxyMjx29jmySW5Y0tkdU+bdXReptnR7WKUdXUrCAgICAgICAgICAgICAgICAgICAgICAgICAg%20ICAgICAgIPLo2lwd3HQ+CD0gICAgICDx6rACXHaB4oPaAgAACg0CAg8GKtDU1GummqQLc9vHNC6G%20eMSwyAskY7WrT416oOQci/pm4leTvvsPd3OKuiXvDA4SR7zU02u0pVYMm3tu5p7nG+R8M9y+Iysj%20zGMde2hB23lq31GD4eT82i5m48ZHO2WSL/Vr7bL4+c/ypw12rXMmIa5tNOjta/3rj5NtksnWF4uX%20LSA2Vy27x8kllOGgtdEaCm6o8ug6rHkyzkt7b/mj3Wn1qlTfci8u4nWHK8XFmrCQAMuoxtmaH1rU%20M1H4dfFaNvi8dnzYLpx3enOERfXpVIOJ3eN4zh7ybgPJmMhIMpxOVcDvla2jG75PMwaBq6ODzm8x%2030zY+6J6266cun3qzZCTcY/qMwk2Pc/lVnLiclE703Mt45LmJ5A8zmyNaW7a6Best3GO7ldDFNsw%20lthzfOchiMvHMTFPaGlL6a6iMWo03RxkyBZZpCrln9T0PLI/biG4z1zaSx/fwtbY2TJGxB207X7n%20n1DTw6KbtYS5ZZ2Vu+ztpCHSF0TSG7iQC5tKbfkKfJeUz7i+LpikW6+jPERRkwwxxt/lMa0ClCzQ%20aEdfj81q35Lrp1mZTPpD2dtCD5iBQU8Ov96oVlGee2Quf064dIG21vNSYk0o3TzVPXqur4u/t7oj%2090wx3wyX213h3GfH7ruynAc8PANCTTy/mpSij6mPNFL/AJb4LdJb/AZ+7tb39TwF6IL9rAxzg0OB%20YT/25GHTzfv7/Fc/NgiI7ckVtqy9yY+nxf3Hn+6ysUeE5ZaMMVs1sm2O5a/6epDXeb8VpTmzbOKW%20/wCXDdzrztTSJ5oVmMZyTjF19ryuBtq2Yf5G+ir6T2nXYXNptcKdP9i6OO7Dntrt57vW3r9yk16j%207iR80c0bmztdRrnNcA1rW182h1KpNsTpOhEVWW3LTI9skbmRtcNkh1DgTo6ooBqpmylO2V2puuKw%20W9w+/wAWw292XF8rGklrgTXp2/Bblu9umOzJyY5tpOjNx2bfdXTZHO+wysBBgdWjiNwNdexPZYsu%203nHGkd1kpifvdRsOV4Xm+Nm437gtitS14+yuY3lglJBaHb/yu1Gi87k2WTaXRm2vzTPO30/ivpdp%20c57m/bu/9vLiWG4dNe8Zvml8GUjaXFjyT5ZNgq3y67jou9h8lZvoibKRlt52zp+fuxTj7fg0t5jO%20LXlpBO8j7eLS3uWP0Bp2poafHwW1ZutxbM2/3elCYhJrb3T5pgRaWF9a2vJMe8CG39WJkMkcIFKN%20dGK129lp3eL2+4rki67HdznWv5pi6YdO4VlILmw/UuD5U2BBaL3C3DC+F9wQSGB0mseo7aLUv81u%20dnd2Zoi+zpPt9iYstv1iU1xHum+FrmcusP0NzKCO5bWSA0+o7qeVte5Xqtn5ja7j9l9tfTl+bFdj%20mOjE9wPanF8uZFm8BOy3yobubNGQ6G4jeakGtQCfGi2dztbM0UnorF1Hz1yLB3FqDi+T46SzlLto%20gmDtT0D43DquBdtsu3vrDZi6JdB9uofctmHvMbdMjdx10bRa3eWY2OSMOGrWsA80bWmoJXD8nm2c%203xdX/NE6xbr9/H4ERd0bGLPcKsYobW5yf+p8taxuitLJjC+KN+unkq1rT2qVO6y77c07v8WGPfWn%206tbNu8GCK33Ua+LnXOr23e7KiDHMeBHb2Fl53AHR0e/92taLWnx+2tuj6Vb5rzu/h/J5Xd/7Hmz1%20t2saRznjX7qfk5VybLYewx8uOscY6K+ie58r7l0jHx3AFA6pNXGoJ+FO69NtMeW+6Lr7qxPKlOX8%20DbbXcRfXPdOvTiP4c/u0WB4ByzlrzLjbG7zt22hmOjYITQmhdo2p+C7OOJ1i2Itt/Pj+Ts4rJ1tt%20t7Lfzdz4Z/Syb60rzWY20ZY0xY2ye1tD3D3ipNOmiz48MWzrNZZsW1tsmtZmfd9DYvG2OMx9vjrJ%20myztY2Rwsr9LGijf7FnbTNQEBAQEBAQEBBy3Ge4+bs+Vcqt826N+JtzN/p8MAY50lqAJLcn8z3uN%20W69EHnifuJy8YeO0ydiMxyqa5vD9rbllvHHbW2x+rnmlQJWt+J+CDKtfdqabJXN46x28Xt8Uy/fc%207m+s2b1nwuiLO59SMsFPn0KFGTce6t5ZRSx3/HrmLKD7SS1x7ZYnulhvpfRjdvB2tLZPK5pQZPMu%20RcksJOKutbN/3l/dmO8xTJIzv/kPd6Zmd5AGuFdyDAHunBthyzoLmOF+PknfjAGO/wAw25ZbtZvp%20Wpe8DcPLRBiWHuHyW0yeXbf4uaa7lylrjcdiBLF/KdPDv3GYeUs01KJZ97z2az5l9reMIY2znfBZ%20QTxTD1bdnqyumDauadpDWojRb5L7hz3GPtosY2SzubmLH37ZnbSPQurtkDojr9XmOqDJxvP72a8G%20NsLObLZGe5u3bZHxW4itrWRkTnbvppukG0dSiV2z9zm3OStWjFyswt7fHFW2UMjCHXYBO30x5th2%20uG7xCITlAQEBAQEBAQEBAQEBAQEBAQa93IcGMq3Em+h/UnAkWge0y6a/SDXog2CAgEgCp0A6lBaY%20IpWb2uD2vFQ5tCD8qIMfIZLG470BeXAt/upWwwbjTfIejR8TRBlOfFCwve4MZXVzjQAk07/FB7BB%20FRqD0KAgxW5THuyTsY2dpv2RCd1vXzCMnbup4VQZSAaU16INJkeWcVsXGG8ydqx9D/li9rnntowE%20u/gopBSXI+Ye3Xtpy55mw3GsichGXUnsovsmGR3m3udcemH7T3CrdjiUw5zmPab3cwdsHssHZKOT%20zep6kcj420J2yNB7dNP4rm5PG47prELReiVrkrW7dK2a6fFcQVjuIgdga8GnVuh8zfwXP3G3nD+2%20yJ95ZLbmf+mWgImawiQEPZMPq8Q6oWn/ANvJyrovSJSfG8/5NaMNleiLN4qcCOeGaNoeyMijg2hG%204UHX+xaGXYYb/miuPJzjWeaYifVIeH3fFreO4tvbzKScayMxD58Xd7iyTadHFru/Y7ex6rPZ5Xfb%20es5Y+pZX90fkp9O2Wp928v7m8h4SOPcowFbv7xlzZ3uPLTC+KJrmvLwTVn111C9DtfN7bcfsu19G%20KcUxzc0weTzseMFxlLFxtInGKKeBoIHp0bsND4LT3O3x3X9tl3z+i9terdWmQsr2rraQPFA50dPN%20qBQkFaGTb34/3QvEsgdaOOrgf7q17/7VhW0a7kNlBdYW6FwCI4YjLp8KOLvAjRbezzTbkiI6ypfF%20YbSKyvm8fx+Udayw4y4gYYZ3FpqaCp2g/uWLLdjjLNkTW+J4/qiIryaDJWDsfGb/AB59FzP/ANho%206OHWq2sGSMnyX6+hdEwu4jL2OWZE57dk8e18Bb5SCD5XMIGnStCm6wX4Zp/bJF8TzdJw3PMRkbCb%20B+5bIr2wkcBj7oxVDdwLfNtqQaHR3w/FefyePvx3xl2dbbo/dFeerLM1jXVq897W2nDnepZuuZuK%20zM9aPIRkSm2eR1mZ1dCBTULseO8th3sduaO3KxX2duscmJd8O5hjcXHkry3Zf4a5Z68GSsavhMJ1%203yDq3QVW/ufFX2zWzVXvQ2/v7iTOYSyw95Q5mZsT5Cd4Ac/a2gB0A70WTZbaclYyxyRNzd+5ntR7%20nYKOC8kx0Etq1xbJkLZwc1oB3N3gnd5qV6fxK3sOzjFE1msIm+rQ2OZjkiFplXCRhoYXgA/SADr3%20NVzMu0u7u7HotEw6hxb3Gfj7ebG8q35bjtzHta97BI6PsA/xZt79l5vc+P7p78E/TzR6aV4/Fm74%20jSWu59wnjeCwdvmuHlk+BuXubd2b5QW1/MYt+odT8nVbXjd9nzX3Y8+mS3ld+Vfb0lgyZIxa/wBv%205cQiv3u+eMW0DpoWgesNBJDToHtNOg/ct/6FsWzN80n802X90aaw3Xt5Hz+xsMpkcZYuyOKkuaE2%201HvjIFavB81AB+X5rY33h43OOyY50ZMV8Wd3unlh7m8Zy8TsfeE38Mw9OfHMYXOI+lzXtoaebQjx%20Xj//AITcY7+6yO2Y6rxlbO1x+dxzRd2eQuOJcejYGyQTvbIXOP8A22xNOjGgO6fh0XWs/wBky4oj%20HbP1sn8FIx26zd8sNLmeY8buo3SYGCTl+Qb/ACn3WRcXwR/9JlLdDt12hVnJus013l/046Rbz/By%20975ba7aIrdrPRHc3zPJmH0ebZmGIS0Fvi7Tc1tAKbjtBceunTosm32dkz3bazXrdPFKezz2581u9%203FMFtLetUNy3PXY+IMwMEGNtns1dK1u97hUDQEtOq6ODxsZNcszfMfFqbbxcXzP1Zuvnjj+jYcfz%20XLsR9vk7W5+4yE22WaK687HB2pDQ76CVXc48F1bKUt5Vjjo9fj2WPFFcdsW3R7fn6uky4r2y92YW%20TG2DOQ40B0kXnj/nubUxy0G17NwC4GDcb3xl2vzYrp+On6Vb1l1mT2nrx/BHsv70c39us5Bi/wDT%20eOwmKeN5tIAwOuQ3rKxzS7q3pVfRNvvLc1sXW8vtYL57ebv3t/7lcR51YvuuP3fryQbDewPaWvie%208dHVHXQ9Fs84TVKQ9vSpoNK+P4fEpWhRdUggo54aQD1caBBQStPj3/glAMrQAddRXogruNR5TSla%20/wC5A3O3EU08UGJJlbGFxZPOyN46gnp8/wB6FFmDP42fJsx0NxHJcuiMxiafNsBpu+VUGpvfbbid%207JG+5tnSOiyYzUZL3aXgFN3/AE/8vRBS+9t+PXW57H3VpcunuLj7q1ndHLW7AE7N2vkftHlQVPtv%20xWsQbA9kLLI42S3a8iKW3JLgJWfmcHEuDutSgt2Xtnxy2jpI+6u5RLbytuLqd0srRZu3wxh519Nr%20tdvfug3uRwlhkLzH3ly1xnxkrp7RzXFoD3MMZqB18rj1QaR3tlxN1qbZ0EhiMElsP5jqhksrZiR/%20zCRgLT2Qesd7c8espWzh1zcXQu4791zcTGSR88TPTaXE9Rt0og8we2nFocu/JNjmc977iX7Z0pdA%20H3jS24IYf/yV11QWLD2o4rZhwBupyWQRMdPO55ZFayiaGNh7Na5o0QZMvtzx8zw3Fu+6s7qGaacX%20NtO6OR33Dg6Vjna1Y5zQdqBZ+3PGrTLsyMLZqRTm7gsXSuNrHcubtM7ITp6lO6gShSCAgICAgICA%20gICAgICAgICDkWR++xnOr9/EopLzI5R73ZLH3dudkErIdrLmK6OjW9PIDr8EiBHp8tnrLA3t7YZH%20LMiNhE7NXN03bLFkX3cbdsLXAecs3gbat6KU/FnMusuLZ5ZeZX/QkuSiE99M1/3ux0DvWGjfU9D1%20C3UNrUKEM7BYzl+XusXa5O6ycdjDZ3j4wT6X3DfVey1+5dSpeI6UGijQlo7C1ztjxjj+Nt5r6wxU%20ZuosrcTeoZYr5oPpAuaxz3MH5aAgnqVInnI7HNT4Th/qufkr2C+tpbu5ZFt3UjdWQsP01JHVIEAv%20m8izllyW3bb5JmPurIXMtlvkdLHcQ3bQ5rJHMjO/02uO1unhVKlG7eeR3PKrO3t8lcWFgyKydx+a%20aOR4mjNfXbK0MoXuoWuD9viFIuXDMxZ4C5vMgMldXOVyt3C5zpXRxWtvDNIIKNaxzxGWtG0AGqgb%20H23gz02exeSzUEwvn8fZFc3MzNrnSNnBo7T6qH4IOooMDNYPG5q0FpkYzNbB4eYw5zKlvSpaWmiC%20zjuK8cxzGss8dBEGU2u2BzhQAfU7c7t4oNqgIInyr2s4LyeONuUxcZdESY5YQInivXVvXx1VLrIm%20Bwf3K9keVcZuYrjhz7rLYoROkvYrgteYQ06BnTd5R9NFpZfHYrulJWi5zaPlNgJfRvopsdI1rXEX%20Ebow/UA7Q/b38VycvjclsafN8GTvq27o7a6IfRrnNFA9pAfTqKObQ01BWhW/HpK8T6t5huZcqwof%20HDduvrOcbX2t0d1G02kRv6irVgu22HJNbraXR1jT7/X8/ROstBhuRWeCvbizv3SxYzISOlsg9gk9%20OR7q+i4jsWnrRb+528Zbe7HTvtik+/urbNG5znEONPjbdtj/AE+4Z52zQP3bmtoW7mA0dUj/AILT%2023kc1Ztunuj0n+K0xHwRN9xyHHNJuIjeRx+eV0dA8sFdNhAGun7VXRsx4Muls9sqRMwyLPMYzLW9%20xBC+sjI3C7hf+UlpG1xNK9CsOTbX4LomYIuq6b7FZq6zvEL+3v4WNhxE/wBtGHAFm1oGpr/sXB/2%20PafTz2XY+d/58TxLJjpMNH7j5z20u4jicfbyXOak3RgWTf5LGlxBLwD4u+pb/iNrvLLpvzfLZHrz%20qjJMTGjnODu7Q4eexzWLlmbZkR2t5bub6lvMGkSeoNNwr5l6+/PimkTPPl8GBdg5RaWlrXIXTZ7a%20RxbBeMBo5w/I5h8wLa9Vzdx4ua1x/ctbf6uhcN59fcaMkUgdlOO3IAls3EOLAQA57Ca6BlAWLgeR%208dbnpWOzLbyu/Kv2s8XUTeyxOXxTIc77Z3kdxx+5aJcrxm5dvjfH9W2Hdu9JxbVu1ZfG/wCxZcF0%204t5E16SxX44nWG+4rg/ZL3GfDyDF4qNmRxE4kmiDTDNDcHzlkkfQlpHhRe4tmKVjlLA6pJFBM0sk%20YJWO+pjwHNoAeoNRopp+KEF5T7J+3XI43OmxUdndeZ0dxbkxESOBoXNbQGjqEhV59KprRwDl/thz%20P23to7vI3IzuHmcWmW2Y4Pid1AdGAdCPwXN3njrLtY0llsv9XPzl85NsmsCWY5pc5ti5wLA4HWUN%20r3AH4/Ja9uPHETZdrPq4283Vl89t1YTKxvcRyS2a+2BsMsGVfKNrWykNoQ/wJc793iaLl5cOTDMz%20d89kzy19ePt+1wbZ3GyurE1x+kems+7a4Sf3FwWNfj8Dkm2kUtx6l+XR7N7aGrY30JNd1d1P4roR%205zFZZGk8fk6V/wDsu1tiJis+1GwscHawySyua1z5HmR7gNtKmv1Dzfx/ivPZvI5csxETTjj3eX3X%20+w7nLfWyZttjoieU9zLE5Z+MyGSu+R2VKRwbAY7baQQ01IEh021quzb4mYt77IjHd1nnX3eg3WPe%207jDFbvp+vv8AweYuWXmVyjY8dZstsZC0uuLc0BkfUfmbo1wA0oP7lgy7Syy2sz888p9P5J8V4PH+%207L/kn8Nfzqm9xxXifuRb04/EzFZ+yY1k7b1pe5zKVbI018wDvBc+PI5NlP8Alj6ll3/Hp8fseojZ%20YojttjtchzOLxvFc7JieUYqVk4Ow3chdJE93R0jAdtN2hC9RbmncY4u290U/Hj2LcUWaUoysfJk7%20TKstMWH5yC9eI7WyhDnemXV2Ve3t+Kw27b60ax23Rzn1Xt+Vm5fDc54pn7KHI3sb8lO4bobeQsdZ%207CKeq8CjmtNB38Vvz47FTtpE/r6sWSK+zI9y87xnKcabjxgZcdyCCYXBypufuROQ0F+15dRgdpRu%201bdmKLIiIikeie1FOLckzuEmbf4TKvwd81hZNMxhc6ahJLS0gt+FVr3Zptn1c67NdZOkd1fenH8n%20YuIf1c3GNcLTl1o/JSUa1lzZABzQ3RznRnrWi2Md/dFaNzFk7o5Udf4h75YjmFhPfcdw9/eW9tII%20pjtja4PIqPLu3eGqyMlW+dn+ekl0fHIzGT5N90Gv29tzduh/FEsa/uPczIxenZ21rhZmkONxLKZ2%20uH+CgaKH4pzGD+je8520zmPoPqPoOqTp8aUTRL1/ob3Eld6k3M5WSP8AM9scLQxriNdg8BU0SslV%206z4Byp1xty3Krm9sNprCxjYpC4n/ABt+FUQz/wD1rhv/APdyHzFy7x+SUTVkM9vOJNYPXsvupB1n%20me90jj8SCERK/jOJcaxWSOQx+PjguvT9F843F2z6qN3E6eKUoN8gIFR+/ogICAgICAgICAgICAgI%20CAgICAgICAgICAgICDHyFlZXlq+C9ibNbEte9jxUVY4PafwLaqJCwv7S+tY7m1k9SCUExu1FQDtJ%20odeoUohkVB6IljXuSs7H0fuZPT9eRsMWhNXuNANEGSHAkgEEjqPBBh5bL4/E46bI30oitIKepJ1p%20ucGD/wC4oMqOWORrXMcCHtD2/Fp6FB6QEBAQEBAQUBr8PgUFHt3d/wADqPxCDQcn4NxLkkcUebxk%20F66IOEEsrAXRkj6gRRR2omXCuVf0r3VvI684vknXLiHMFhcvMbIxQlrmOBp5TTQrDfgifRaLnH77%20H8nwN19plm39jK5zmNuHxbmP2GhI7bfjVc7cbW2OdsLxc2UTL6WGm+3yMDXUMjxqSNSOlAVyr7rI%206TYtErVrfZLFX8WXjtnyCAjbbF4kjIYauBjI2jcdCQFsW47MlnbWPynqn3jmzOQe4g5rbRSxQ2+C%20ljkBvJoQ50sm4eaPvpT9yx4th/1JmNb68q0oiZqsXOLwlyNzGxtnDCWSxupJWlQTt6nTqmLcZomn%205kxCJYCxz1zxjLzW2cubZjblzbi3FWxyaNbvkPx6dV1819lt9tbYnRj7qRzZo5JkcRyO2ktbP7S+%20jt2WckAG+O5LtHyEk+VzjrRVnFZmxazW3mTdOtOa/wAKncLrI3V0XxOlk80EoIaCDq7cfh8VqeRx%20zFttsRWi1uvNlSYDjt3DcOmlZcs3lzpm1/lnU6Ea/vWGzeZ7Yi2IotMNNH9xxW2bfY28OUxdy7Y+%20F9RtI1Jb1roVuzbbuJ7b47b4Ur28pTni3J7y2khy3Hb70d7mTXFnu8sjWmm2Vv5R2JFFw97tImtm%20W2sdJ9PeGa270dMgZh+evbmONXcnFuV46USXHpbWG4fTdtlGgkj3jqRVc3b7zceMmIn/AC47v/t4%20ha6yLnQPb/3UbnMld8fz+NfguQ2YAcyVw9G6odpktn9CKjpXRe+2u6x57O7HNYlq3WzDoDtxDqnQ%20anRZ0LcsMUzXRTRNljeKOY8BzTUa/VWoKiJHAPdT2Clt5Jc9wq2idbNhkdfYM1aK0LvVgNa79T5V%20r59vF/tLT3W1jL1pd6uBXNjITFPYTCG6e4eo36CxzSKte06h1a6U+S58XTZMxfGjk23zjmbb40j+%20bcWPvDNa27rL9PfkL+OkZcX7WAjyg12uND81q5fCW3T3d1I+HHT7mnn/ANbxXz3xd2Wz0aPLXnI8%20/KXZHIS0YKNsLIOLXEk+QiHRx1pqtrBgx49MVnPr/XVvbPbYsUUxWf8AumNfbm6jw/8Apb5dlhb3%2017eRYSwfCx8UbW+pdOa4Ahrxps0Oq6VuGafM62LDMazOq972+12O9ssdYZ7BXLnW9xI2yubWXUue%204E+oXV6VGuipuNrZfFJ0bFs9usOTHmuUtLgGye6e80exzXGN8VDXylp8416H5/LTt8djm2kxoyW5%20qu13PH2+4/FMdkObcksobeECe2s8dSSUSBm0tnJ+nXqFfx/ise1mZs/u/itdd3o3H745J1nc8b4v%20gbHFy2bX21zk7ZoIkjaNjHtcG136V6rbzTMRHTj7iKIzgsNzvC3D71+EueR2V6RG8XzXmYNqHV1J%20dQ07rVt8xg1i66IojsnoinLM63LZ/wBZ9kbaO0Y6NtqxjW+i+ooJPi0Bbl98XW6Tzau4i6lK0ZcU%20b8gIRbmCF5aS4VpQMO41NabnV8ug7LUtx90zMy0cWDumszxxxRl3Nvg73GMlxUZtbyFwZK5w2ue8%20CvmJIBaANCFS7JNvw+PH3f0VyZ+32/h7cfe23EPde64hyKzysEW4H07PIshGxksQePM/Q6gaV+K2%20tvddymWztskzNLn23is3jctax3WPu4bmN7GvPpSNfQOFdadFuN5llxc7y9hru0FFAMNCKHy/Dpro%20NPBRCF1SkQEHlzSeh06EfBBQMcKkUr2HQIHpu2gBxAA/GqCpaa6OPShQUawg+Y7h8fH5IPaCOZzn%203HcJkI8dezOdevb6roIGGV0cVaepIB9LUG1vs3jrOwur6SUOisoXXFw1hBe2Nrd5O3r9Pig92OVs%20b2xjvoJmm3kjZNuJA2te0OG7/Doe6C6byzAYTPGBIKxne3zAeGuqDGymbxuNsL2+uJmmLHwvnums%20Ic9rIwXO8oNeyDJs7uK8tILuGvpXEbZY9wodrxuFR+KC8gICAgICAgICAgICAgICAgICAg8T7vQk%20213bXbdvWtOyDjuOx/J35DjNtfWWTgyFhZSyvyIMjopLtzpW29vOWnZtYDue5w18qmhpLRw2vIvu%20XYuziy1tyC5w1468ZdzPbHNeslaS62Djt6Alrm6UIAUCVRHl+TzM1/bWWQtbB+RxhgjuA6Jxijia%20J3lh+lgePN49U0KtJYcf5tJg8t6k2SZnn2phv7ZjJ2NmmfOCZo7h1Gl7WUDfT7VT8yq9y/iN+318%20YLDK39s2zx0eC9GWWRjXsmDrw3BrTcdCS/r2QZsWJ5aeUwSuhv252PLMdLe7n/p36Q2OhY2h9MVr%209FK7kKuvoCAgICAgEAih1B6hB52Cvh208PBRQV2ChpppTx/tSgo+PdSp08PipmB59HTQnqP4KItG%20PkMTYZK0ktMhBHcwSAt2yMDqVBFRWuuvVTQcZ5N/S5grp/rcey91h52s1hFJInkVIqDSmvcLDkw2%20384j7k1cczGJ9w+NT7c/gJxE4uZFfRAbGxtqNz3CvbXVcnN4iK1snT3W76Qh/DJLu3xk0tlYS5Rk%20sw9VltG58kLAKF8lGu/Gi2d1tbsnKaTCO7Vtc9c2lpjzc2tvE6WctgDANu3e4AuLR5qhzlobbBff%20dS6ZijJN3VtOf+0fOuM4zGSY20kvcZeQsurt2PY8sa4ipLm9Q4B3VdmMWs11qx1c8yDZYMrBNdCW%20+s9zJBA6NzXlof5q1BPzPxVIt+SYiltxV9P2mX4hyLDS2BgtY7WSJp9KGNrT5o6ODqdXiv718yy2%20bnb5u6t0z769fybcXQj8vslirVz3cUvxGyRmy4x90C9jiOkm7sTWlF0P/wCmuvt/z28uUxx7I+np%20M2ue5OS/wjPSzOBks/5myKF7WhkxB6xupT8O1V28FsZtceSLv0+LHdEx8WD7Ze2WZ5nkeU32Cvvs%207/Efz7exa2sU7jUth8BWm34L00YIuxxbd6MFV+wzH3GQ+1yFvLg89ZSbWwyExyCRh12HSoBHRef3%20Oyvwcvmsn2Zrb6uqRciwnuFaOwHNGNxF5bbH4/KQy+m97gBqx7tWur+XuV5y3Bl2F31tvM3xP7rZ%201px+DJMRdon+C5bn+KTQ4zmtzFd4l0YZjuQQscAKENbFcDzeYj83Ret8Z53FuomP23x0YLscw6bD%20dQzxiWOVkkTwC2RjtzD8iOq70e7Gr9HTrWlfjVVmaDlfup7C4TmLxlMfL+j52D1JA+JrfTuHu1An%20bpu83dRdZF0UmFL7LbopLnPC/wCkbL6XnIs6Ld1w71Z7W0j/AJgO47ml7/7lE4o09lLsFt1K9Hfe%20N8D4vxi3EWIxkEZqHOm9NvqFzQNd1KqZ006MtttIb4RUadSK0+A8VasyRFHCv6wYxNwPEwPqWy5O%20NpoG1oQRoTrX5JM0J9XzXL7XclmzYx2Hxl1tDWTvuntoGREUDg89iqX3xbGql0xymdUp5T7WcawV%20raw2ebkOauHBz4i5nouIbWrmt/LvFKmn961P+xSPmhrYNxWadOOI/Dolntbm/b/iWLv7llqZuTOF%20L2zftPqSACrbb/C0vr1Xl/L7bd7m63tupj9fT4/D73Rx58dtlZ9Fid+ct4r7Kx5i9w9peOdc3lsZ%20DOQ1wHkY4k0La9u3yWTFmxX0xzZZfNsRETTrXm8vd/s8X5fp4o56Rr1csi43SIXN7cG1juqziaQh%20zn9SHk6u1K707nWlsVo2/wDu918286cfzXsFBHnRcCW7jtpIQ2JjI2+Z0THU3O1FT41WXPkjHbFd%20WfPktstivHHJkPhnEbbZ7w23YN8cbw2spINCdvwPf5/PX+pbd0/k0rs1t3L+i4cVeZMm2+yZCwN2%20smcCKl/TT8x/N0/uWL/sWWR3V1/hx8GOdzjxR3Vr+nHL+i5YP5bwUNvcNkBayAbLgN3je2NwJ3sP%20XU9wtrb76Mk8m7tPJRlupFs+v3uvcL/qs5lexS/qXEpL+K2iDhPZuMTiRQVcJPKfk1beXdYsel90%20RVt5d9hxTEX3RbPxdG4/72ZjPMc/DcSmuTGG/cRtuojJEHf429Qf+Wi2OfJtRMTETGseyVf+y8cB%205rG9aQNa276Vp00SdEg9y8YaVs7xgqA5zreQNaCdSTToO6ipLMPuRwsEg5OMEdRqpFD7kcKAqcnG%20B079R+CFWe3l3GiGu/UrcNcKgmQA69NCgr/qzjlSBkrY0rX+a3r4KKkNgy9tHNDhNHQirSHtII8V%20Iqbq3p5ZGOPhuHRB6DySCKFnRxGuqiog00XIsBzrM5O2wz8tYZ5loI5oJGNfDJbRmMska/o1w827%20opgRifi/NL/ld7eS4oWbZrbJW0/ovYIpo7iGltvfXc9xdXro09KKBroOCcuOHn/TMXLh447PGQX2%20NMzXm8ktXONxsr5fpI8x+vopNGfc8NvP0/CWLcTf3uLfkJL68dNtjuLRrCDHDCxm3ZHI/V1OyFXj%20IcU5tkOQ5O6GIbaCe1ylrOYXtZDPHMxwtdzvrkc+oJrowoQ61gbeW2wlhbzN2zQ28TJG+DmsAI7d%200GcgICAgICAgICAgICAgICAgICAgICC060tn3LLl0TTcRtLY5SPM1ruoB+KUF1AQEBAQEBAQEBAQ%20EBAQEBB4dQn6wKfLqEqPEsccrDHJslY4bXxvAIINQa6fgmgtWmLxVkxzbO1htmu+sRMaytNddo1Q%20lDue+zPBuYta7JWognaai4t6MeXVDqmnX6VWYgiUzsrVtpZQWcfmjgjZCzfoSGNA108ArVqIXzz2%20k4jy8MluQ7H3jKj7yzoyRzQalrqaEKl1sTpJMuJ89/p/5Lx+W3uuPS3OXhdu9ZtsxsMjQNfOAdrx%2026LSy7KJikRE/Fe29oMb7hckwM7LbN2EsJlDT6pY+MNa01NQ4fVU6rzO98DbOsfdLNGR0rC87wea%20ti289C6ghcB6cpadrqAB2o+H715bP47Ngmtk3WzPoyRdEmI4tjOMZ39U4llIcVfXzavxkoD4ruji%20+gaCXt18tQKrtbH/AGbc2aX2d9sc5jp8eKK3YY51XOWniPuJiDZ8/wAXLxbK2e77XJGjmNc4bTI2%20Rum2uvmXttr5Tb5/2XRP2ta6yYcN5hxXkPHMjbY7k5abUNIwubidWzum/lMhFW7nAChVL9n9OZm3%20+7n/AC4/JMXJt7de6kmJtJrTIxSZPEzSBkgldukgJo00rurHTVeT8t4eMl0TbPZkiOfq2LL02sBk%20vb1k+Y4Lv5ZxzIzB19hhN6jrVzqESW7vNtoNNjqLc8P5++ZnFuo7JiNJ5V6cSpkxxzh2Hi3L8Hyb%20HNu8ROJqUE0Lqtkid3bI0ioIOnRewtviYrE1hgbglzTQAGulB0Hy/cpnkh6iiAAcK18P4KItoAe/%20QE9dA6nU/FTEkrVzOyGP1JXshjB6yuDW0FPFNaofO39WHJ8Lf8Pw9jYXLbySPJxmb09Y2bQR53Dy%20j/eqTfbrETFfxTrSrCyV1eX1nZxZW+jsLZscTg2FwEj3BpdRzyRUamrSP7F5HceTy17bLZr1/L4+%20lHMs7LP7tPu0pPP8o4lyvn2VsnXNiyHFOtILX1AJXkh0zXOJBaQT4VH4/Jb3jsd1Lpuu7pkszWbi%20dJjTSfjxz0aG2xTb2xFx6j2zxEvtzESQC3UEOHQtIr+2u5k3E2zTp1aeXdTbkp0nnx7sjkvPOUNx%201viru3YxgYYZ5YdPUAbtNW0Ar8aVTB47D3TfHx44/nbb+J28Xzfbzau3faT2T3vvGv8ARDAASCQ4%206U8x7GmoWzkxzEt27BS7RI7bAYyOKKR9+7FQAMe2ckTSSvFCXN2Hy0qKE/wWK66YnWK8+OP4sWWy%20bZ1+b+fL+dGTFNgLNwjkx9zK2VgfHcvLZXmOgIcGtPfpTtXqVhusm6vbNOPXp932NX6M5LY1pMfZ%209k9f6L+Nh5NntzLBv6XjwaPubtv81zzXdsDdQO/YaLSzzhwzW+e+7246/q52b/q4Nbru+70ieOfL%208G9wfCMRhB6+QujeTuPndcvDYmltNGh3Trr49VoZvI5M2mO2ke0a/hxXRyNz5nLn+XFb2x7RrKmb%209w7PG7IMVZuyJoW7INGNfTQV00HfRNv4q7Lrmu7fjzTtfB3Zdc9/Z+fHGqK8gu+VXthNk5p24e6s%20wZm/Z7opXuDiaTuaQTtI7/7V2NndZhuiyyt0XcaPQ7DJjwXxZjrd3dZ/T7qvtfgt5PfcLwN5dvD7%20q5sbeSWQ0Jc90YJPTVd56Vv/AE6gh1PhQDogtDH2etYI3VNT5G9R+CVkV+wshSlvECOnkbpT8Pih%20Vr5OIcXke58mKtnPedz3GNtSUqPJ4bxXT/xNqaaCsbelfkg0k/tNxWWaWbbKwyOLtrXkNFewFVFB%204/8AUPFa9Z+tf+67t+KUGZx/29scFmf1Cyv7z0PSMf6e+Qut9x/+TafzKRK0BAQEBAQEBAQEBAQE%20BAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAoPBAIBFP4qKCm0fxqlB52nd8+pA/A6pQeu%20gAOvxUwKPbXpofEKKDxskFQzTrUnuT3/AIpqNBzL2+4xzKzitc/a+syB5kidG4seDSn1D4KJtieZ%20DjPMv6Zp7P8A8nw7ITy37Bt+0nLdpa3UAOBatXJs7Lo7Z5LRfMOZTv8AeGK7ivclxq4gbgHgXd8W%201DYWmrnbdQenULnW+Gsx23xb/fHGrLGSa1dWwvuTgsxauhdLBPFMxrZY3irQH0qHNPShOvRfP9x4%20rNhvrETbNeKcSzWzVdk4Pg7qzvLKwuvUx13Q3GMu/wDMQNcT5TEXlux3ht0XW2P+07jD8ua3ujpx%20qpdiieT59yHFOd8GzDp58RM3D3TzFE6vrsDATtNW6tO3XXVesxb/AG29s+S+JuiP4fqxUm3mm3DO%20b3mBfcXvFpYbu3uXMF5bO+kuHcaja4NPWi4O+2NuWlueJtmOU+i1t1NU35D7j4o29rnOH3QsuV0E%20U2ObED6oaCfTkadoDSdN6y+Dxbna3XW3fNi/5MO73FllvddpDrHB/crFZ6COC8LcdntjDd495oN9%20aOETz9YB06r1eHc2ZJnsmstXb7zFmj5LolLLvK2Fi3de3MdqCCQZnNaXU6hoJ81PgtiZjm2XNOX+%20/WDsIZG8bY3L38dfUhIewNqPK4ENOmhJ+AWvl3Vlkc4192O/LZZ+6Yho89l8DlreO75Plo8zcNaP%20Rx9gQ1sTJNHOc2Mu3OG7vT/Z47eeX319/bZH07PWa68cdGW/cYcVsX33REdKuNe8GcyN5xvH4qPE%20w4bjdveN+3mL90022oaXU27fLrqF0PD7e3Hkm7um/LMfZ9nH4TDSjzOPcTNuPWY9PuYeUfa4t1r5%20H3t9PBEN1w8yMazbWkdWitK1FD1VrYuvrX5YiZ5fr+PR567HmumuTS2KzH8/j/PqjGcvr3JywxPl%20HfzhlBu7+G46UNO63dristmaN3ZbfHZyiiuLklbiJ2NYQ0Vdua6u0atDi0B5A+mviFObHM3VTlxd%2019ea3x6CO+zDRcPYyKFzXPAbrIKgFutRqSK/irbnLOPH8vOjai2mnT1bHnGEwmRuo3Y2J8c4O2QR%20VDXucdOzRofD5rD47Nktt+fl78cfY2O/sidNOK/p6fDRrpsJyHjRjsZ/5sV55xJC31JWNjoTp5iA%20Wu6roXX2XRWOf8V8tsXa2ymfFD7c4yCQWV5ukcBJL9/o9nlPlG7y6gGmi8/vo3l8xWP/AKeOIl5L%20yeDeZbo7uUf8epkvcq+neIuO2Dr/AGHzzygtjYR5dD3BPdUw+Hstj/Nd2/Bg2/gbLf8Az309oQzM%2039pcySTcgyLrm93Oe6xg3MhjeaeVzm18vh/cu3gw9ulltLfXSsvRbXDNkRGGylums86LWF5ZkpT6%20WOjt7eCKjQ92kga2pDjWlaV/4LPf42zJNbpbV/jLL9bpmXq65xb3uJyOOvWhszGujgLBpICerj/v%20Wvb467Hki62dOrUs8T9LLF1k6V+59y+2M9vPwLj4hljlfFj7ZkjY3NfsPpgjdTp06FdedZd6UoEz%20WtAIoQPN18PjRKoevUNBpqToPEU7KJkVY9x6tIr+xCRNR6UggICAg80kANCCdev8EDdJT6anvTog%209ICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICC2+Il24df%207PiooMTLWcWRxV5YTt9RlzDJG6Np2kggt0NdK/NTA5FxT209tuX4Nzvto7bk2NJtsxLYkxOivQKk%20PHR235LFl29l+kwmLpRq74f7scQk/mwDO41zi2KW1aC+INrtMjSRpRea3/8Arll+tjLGX1ZOJ9ze%20P5NklreyMJ3CM2tw3aRLoKEfv+S8nl8XuNvNbKxPrHozxdEuVc+PD8TyAu9vbeV8rY3yZ62ha58E%20Qa7rtIqO9adl6/xmDc58Uxuen7Z6sF9I5Ihb3rslPNkILwOvdvp7m6N2U3bXAreiJwRFtNHF3O7v%20sv5fJPHH9Kzbj3Nra9ntbbMDbf2hY6GX0w1zJmgEOaWgAtFNR4kdKVGpm2HZ/k2809dePy/g4+48%20bNk/U2k8+cV+6n8EsvZeUcikdLyLJMyEENTjyxoa4N0+omgGmlfFaefzN807ax616U4/hq1c3+03%20xEW2x23R+6sMPKZnjPHA39TuGW1xJHubG8l8r2jXWn9ui0Me23GeZpXTj8v59XHtxbzeXd0RN0RO%20np7Off62tLTJibimOZYwva9lxNdVG8EhzXsG6jdQSu/Gwm+yme7un2+HGv5PST4ycmP/APYvm66N%20dKI5zHkl9nvtri4vROyCYMih2hgbrUkNaAHAU6lbmy2dmGJi2KVh1fGbCzDbMRFK8fY6O64w3ILO%20Gw5bSOZkQFhewAMLAWfTrp8x4Lhzdfjum/Fr6xx+fT7WW3JMx80Uj260n9P56RVqeY2uSsYMXa3u%20PZbCwZ6dveRgETijnRlzh1dUiunVdTb7m3LbW3TrPrrpXVH04sppFfz+z045NBiGBthdvc/0jIwx%20kMNAdxJdu06Bv7dVkvml0atDLkpfEQ11rbX+Oc25EVKtbIKUIdGDUOGlNSrX32X6S2JyxMxHHHHN%20IJro2d1iLqeRzmTNMk7ZQWta59atpp17a9tVS6k45izinH4s/dMxSNPfjp/OjL4xn/u87kr6/IbJ%20CwQWr2VaTE49dvmGuhIqtPfYrrcdttvXWWWybYnWff4e9fw9aMXntnjbjPYpzraMBweZRSge3Rwa%20dQB+CnxuS+3FdFeSM+XtxTNtK+zxyzkdvg4orW0HpOeCdjWioqAQa6dqD4H4q2x205Z7rtaOD47Z%20zmum6/p+jQ2Eltd2H22KtPvMjLFuvnkEMY3o57zUAAEr0N1LYertiIpEPd97fwtsYLqyuDbRsZuv%20bq4eGRvoRrDTUgLUjdRN1KVW+Dze8ex15b28PFLG4lmlOy6uLk1LnbRrEBt8tfgp/wCzFn75g7dG%2039s+W8t4xnJLezyd3j7cjZcucWmIPb/iqHAAVUZs13bW2lUUpz5Pqz229yM3kMm/Acyiit8nIz18%20Rc2+sdzanQOeegf4iinb7mzPGnOOaZto6ix4rQA9K0I10W1XWio9shcNp8p1P+xRMSLisCAgICAg%20ICDzNI2KJ8rvpjaXO+QFUEL4n7oWOeyMdjJZTWLrm2fe2cspaWvgieY3OdQ+Qgjo5Bm3/ufwayxN%205lX5WKWzsHxxXT4avLHSu2s0GpBPcINkzl3HH31rYi/j+7vWCS1iNR6jXCo2mlKkdq1Qa3/2JgJO%20T22CtLiK5dIy5fdTMfpbm1ALt9RShrStdChRlw884fNjp8lHlrd1jbPEc8+4hrXO+kGor5u3j2Qb%20izu7a8tYrq2eJbeZofFIKgOaeh1QXkBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEFC5oIB%20IBPQeKCnqxf42/vCD0gpubu21G7rTugqgoXsDg0uAcegrqUDc2u2oqOo7oAc01oQaaGiCnqM37Nw%2039dveiCpc1tKkCvSqCoIPQ1+SDxsdUmutP39UFQ0g/AdlEQItgOGS4bk2XyNq+KKwytZZbaNpDjc%20l1fWdXqduimRKNjmijdR3B71UCEcz9neHcoaZpbOOzybdYr+2BieD23BtA7XxVbsdt37oqmJmHK8%20P/TT7hYJ1zcYrldkMhcvcH3k9o6R7oZBR8bw4ua4H5KluGLZ05U5dCZrzc15hxW39tc3bcc5XDb5%20M5uM3dpd48Og+3mc8xVLTqWDrt79FTPZMx68cUY78Vt+ko9ybjdzj5LKK/2tjuqus7xhb/MYygFK%20EubTwXNw3TFZtlyp22TBNa6fk1jOdcqfG/H2V4LM2+71bxzgS7a2h2t18xGvlW1dscN3zTb83tp+%20Kc3jdvmpddZE3fd9/L8W64h7W8z5aXzY3HvyZa8D7u+f6bYy6vZ2nxWSMV08vlhm+hfdEU+WPZ3/%20AIR/S7xjHE3XK5BmbnY0RwNLmQxE6vG0EbtVs244tblmO22Kc0W/qw4JxTDcKxOTxGJjsbi3u2Qb%207Zu0GIgmjw3Q1poSrdsMkPnKTk+QMwMrg+1kY0bAKhjj9P8A9VB2otX/AKltsafua+TH1jn+jqOA%20y/FH8fDr6K5y+XdDtYJ3yStheAaPaDo0aUHRYrbYt0tiNefLWnHHJisinL7dOfHrxEVwkls2wmdP%205WvkLXkgFpbTzgVpQgeHwWjuO6bop0cXdW3d8U4mrdYvE5HKwA4qxa220a6eYlg2nptqfpZt3UaO%20v4LF20u+aeP5scW3WXVunX2+/wDH3/iyrjg2at7KO0yTRlGgl8f2+1npaeJAJNdNf9y3Meay3lHP%2034/T8W/Zu7YrX0jn9vH9atVj+CckjfK7FRk1NJHXD9hpqTG5pNXdhr0KjLksyc/u9Pf2/VkyZ8V0%209ePT2YPKsbmcblcXJlmNje6OR1u5rg5rnBrSRQUA+r9tFbaW29s9rNhz25rdNeXx+37kcEkF1Hf3%20eSd936bnRwhxAcwjTy9NKAUXRxY4iIpo3dtjtttikU0ZXFcTE+O4dJPNZGNm+WSIk75NdkZpTynu%20sWe+6JiIivo2KVZecz93eyNbPALloIEkkAo1sbNC7YzyaUBWLHi7eU8dDujk6hxDjPDxg8nkcBmT%20fvEAmvWSMMb4nUFdrXdDu67afJeY3+83MZ7bMllO6dKfr9jJERRr8/wae1jyDzaOM94wiJ73eR21%20xcTrQDSqzYPIxMxHd8sey02asHitjftjtL7GZOSHkWNAEc0odNH6IJe6Ha4kNc4ilVv/APyE4r5m%20nyTxVTs0fROO978fa2rDynGXGGdTb9ySJmPc0AFwEf01rXVdTb7/AB5f2zqx9ro+PyFpf2UN7Zze%20tbXEbZYng1q0ivQ/PVbtEMoSeIP4fuUzAp63Xy0+Zp/FV7h7qrCqDyXGmjTU1oPiFFR6UggIPEzH%20Phexp2uc0tDvAkUQcj477P5u1a+3mltsawWF3YT3VkZTLd/cghhla4kBsZIdoa1+CVkZEntjyW+s%20Lh123HWl5b46LG2EVtGfSm9GZk3qTg9N3pUaB0qUSzMvwTmOZ5HY3l3c28ePguLa8bCzc30fSjc1%208TWt+p259WvPREdGuj9pORXMDMfdy2FvaWlnkbKC8gY43M33xDmSSOoPpp5h3NSgy3e2mcys777L%20xWFvI6XHRnH27CYHQY+cTF7wer3FtGeDdOqfAdQa1rWhrQGtHQDQBBVAQEBAQEBAQEBAQEBAQEBA%20QEBAQEBAQEBAQEBAQEBBy2y/TsxznkLuSZOW1vMRdwMxVkLk2wZbljXRuDWkB/qu1J160QR2TPSG%20AZFzKf8Ai70eh6jtjtuRhj376Vr8kqapI3nPKIMq64Jtn4WLLPxEVg0O+4cxtn9wH7tfPuG3aoEV%20k5zyM5GLkj7+xu7r9DvL2ysICQLd3qNa2OZvU7e5PeuilKQZvnPNcVJd2017Yi6wePblLsOYWi9M%20rjtiiDtWsA8u7ru7JWOiKtnza4zV5neEvxlw2wvbt1w93rNcWNral1HMHUtPYoNAPcjKC3/V2x28%20WRucdaNfO95dDFJLcuhc9za/T5Kj4lJHnC5/lcGUvcbYZC0ub/J8hfbXeRG58TYYrSFzvSYKta/x%20HStUolW+9xLu15Jkr2xliyJfYX7bW4czY2N+NNXMaz6i3dUOce/SqaIZfIOYy5i7Fi25idbWV3hL%20hs9u+rt9xIwva4t8tDXog98c5ll7u6xmKs57TDwuZPe3Ek5MnrUujF6UZdSmh8x/xUQ6r+C9xeQ3%20mbxUs0lrLYZq9ubJuIi1urRts4t9WQjU/TV9em4IOpICAgICCN8t9v8Ah3KpIX57FW9/PbNc21uJ%20mBzot3hXtXVKVRXVwqw9iONZTL3XH+RX15b3dk5xsL2TaIZ6u0MBefy7uix24rYjSE3UmKdE64L/%20AEz+3PGBvvLduavNzXslu2to17CXAtb0rqsnarSJdYjjiYKRNawaeRtGgUbQDREvRDtQ07q/2gd/%20miWJmMJjstYy2WQtmXNtKHAscAabhtJFfmg+U+Wf0zX3EMyzK2ds7lPH3vMk1g0elLCdwcdASC3b%20XVVujRS/k2VryC3wVzBbWPAb5trKWk3FnA6eMxlo/OAfHv01ote/DWvHH69Wrl29a8caoLdWWJ4x%20f3V9Li7q8t7gukgx2RtnwlnmJpDQODqU7/BUyYKxHTj7EZdt3x768uK9UowHPcFlYi1w/SJIXDZb%203JEYeHAgGOu2vmPh8Vz8u3utmns5G52d9s0jX0419+STkFurg5wq2jWn8ag6fDv2WpF0xzjjj2aE%20aTxx8D+cBXcCXCjCKmhqQfLpqKjvqptyROnHTrTl6f1R3604+PHVy/3otG3eUwsBdVrhLu26/GtR%200+K6OwvpbM04493Z8bkiLLplyuLCyTyTDeY5Gvc1sNNriNQDTwqOq6ls1jR2cXzW1hmY7krLezFg%20LBgkkiMHrNcaveSQJHDxFVjvxTWteOOKMts0Tj2w4zlcddy30s8UbJI2xxTucXRmuuxxptHToVx/%20J7iL7aRE8enH4rWWxDoWKzuFsL+7jfY28F3eN23s0TQd4cRUuOupNTWui81udvlutj5pm23k2Lac%200r4zyqxGIkssp6c8OOJhBkeBuiaP5Op0LnM1XL3uyunLF9k9vfrp6/3fjomJ6IfgbzMvyF9lsYHx%202w3NZbRQmSkdS5jXgA60FK/Fd6bKWxHOfVjdSs2/qOMilc1kpe1plhBDgwkah+7pSqxfUmOXyzx/%20QabI8UycDQ/jeXuMDcbw8yWh9SJ4BNIwzo1u7U7fFdDa+UyWfLPzfb+Ks2w2UHvw3jf+R5OLe+lh%20IjNzj5RLLtb9Tpo6lwI/bVei2+7i+K0mKsV1rrGC5Jhc7j4L3GXUdzHNG2VoY5pe1rh1c0agivgt%20tVsWuNdBqera9AOilD0HOrqKDuaolXa3TStOhOvX5oKgACg0A6BAQUcSKUFR3QWpryCCGSa4e2GG%20Npc+R7gGgDqanRCWj4ryq55BPdyR4+W0xsB2QXE42unJ1D42/wCAjugkSAgICAgICAgICAgICAgI%20CAgICAgICAgICAgICAgICAgICAgINde8dwd9fQX95Ywz3lsawTvaC9tOmvenaqC5+iYjZs+zh2lr%20mEbB9LnB7h8i4VSRcGLxwduFtHuEv3AO0V9bbs9T/q26V8EGJBxbjlubh0ONt2G7LjcERtO/eQXb%20qjoSOiC5kOP4TIXFvcXtlFcT2h3W8j2glp/bsUGXLaWsssU0kTXywEmF7gCWFw2nae1QaIMZ+Cwz%207d9u6zhMEkfovjLBQx1LtvyqaoKWeAwtmyFlrZQwtgcZIdjANrnDaXA+JCCkPHsFDeS3sVjCy7n3%20erMGDc7f9X/8u/ig8WXGOPWMHoWmOghiL2yFrWAVcx25pP8A0u1CD1ccbwNz9v69hDJ9o8yW1WDy%20OJqS38dUHu3wOGt8jLkoLOKO/n/7tw1oD3V66/HugzXODWknoEFJPUMbvTID6eQnpXtVBasvvfSH%203mz1aeb0/pr8K+KC82tNTUoPJc4mjfmgqWA9evUfA/BBoOW8Qx/JLCKG7DhPZSGexla4jZM0UYT4%20j4JQqweFcudmYLqyvovtcpjZPQu2v8glcNPUj3DoQoJStrTU0FACKHTp4d0Q9CNo7aU7q1Sj0a00%206qErbQ/fuIoe/wAf+CDnEv3Xt3lZJ/52SwWdvA2OFrT/AJF0lPM52o9MuJqdKJMdUOhOjt7kMe6O%20KePQxPoHinYgmvZCjWZzhvGc9ZOs8li4JYXsc0F0bQ9m7Q7HDVp+RShLkN/7Bci456s3EMv99BIX%20O/T8i3c5gINGxygn+IWtk2lt3LRrZdpZdNaQgFjymSCW4tuUY+fj91HK4MNxG5rLjaKEtft2kinY%20/Jc7Ps7o5cnHz+NuiaR83HHtzRn3QnZNnsA6GRlw0MfuMbmubR3lbXbXw/cmLHNmO7oYsE2YLq6c%20V/ViZrBWeTuoywyw3gDjC61jPqPO4aHbWpPg34DxWns82WzS2KtLYbjNZFLIrHFP4a+y7/8A8y82%20vsbeZCxs7iH7ZpmjF2Wh1zoT/La0g/vXfw3ZJ1vij0+3uvuit8UlGcdwrP2cQhkykuGfeNDZ7Wfd%20CRISQfU3EVDRrWn9ypkyRWK2tmNV1ljdmQ4m5vWW0ETvQFzagzvnbU1fvj37QfitLNEx89tnfPPj%201XpHqlmBwUGRvBjY7l1pDJSB0sjvUBIb/KLq6gueQFz77p7Jm7W635o+3nx6r+jqXFuNcjx8/rW+%20Sjxr4mCF42CRs4qRucNAOq5lu4iy75YrE/h146LxFeaMe5PIslDm7axvIxZQsjLp3WBdG6drjtq4%206CmjitjHbbfHdFOnTisq11aLDZjkWQ5FkMTxXMO/To2NbcZG5DpNrHgaNBGko3bd1dCsmWce3xxf%20kjWeVvH6ETWU5w3HeP4K2bFbxs9VrSya/uAHXErq9Xk0q5xPh/Fed3PkM2e6s9ekcl7bYhqeQ4mF%20vIMY20E1jJcmkktm8xOJD2t3Ea6N+NKrp+J32Sy2aTy9Vb7Yl0O39wOc8bY2HJWo5LY/9uN9oPRu%20I6EAB4do74mvZen2vlseTS75ZYZsonvG/cHiWda+O2vWR3cbQ65s5gYnRuPY+oG1OvZdOy+26NJi%20VKJL60Z1DgRStRqP4K49bw3Rx6Hr+FdVAeqz8aVp3UjVZ7kuKw9t6txMPXeCLe2aSXyPpo0NGtSg%200FvxrKcjltMpycut4oXia0xEBLQKncG3NP8AuadQiEw2mmlGsb9I7UHSgRK4wvNdwog9IBNBVB59%20VlK66/D8f70GJlc1i8TZG9yNyy2thQb5DSpPQAdSfgEF6xvrS/tIru0lE1tMN0cjehCC+gw58vjo%20MlbY2WYMvbxr320J6vbGKvI/6e6DMQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB%20AQEBBj3+Qscfavu76dltbR/XLIQ1o/EoFhkLHIWzbqynZcW7/pkjIcNPkgyEBBYu760tBGbmVsQl%20eI4935nu6AILkkkUMT5pHBkbGlz3u0DWgVJJKFGNicvjcvYx3+NnFzZy19OZoIa6mmm4BBdu760t%20BGbmVsQleI4935nu0DR80GnzfDcdlMvZ5gyy2+QstI5InUa5talsjejgUG/Faa9e6AgICCxeW8F3%20bzWc7d0M7HRyA9CHiiCBccyOS4rl3cazkjYcKSGcduSavc2pHpyO1G4dqqB0L1GVIrq3qFIt1q4+%20YgO6dtOuiDDzOBxObs/s8rax3tsaH05QP4Hr2TVDkWR/pL9vJco2+x9zeY6IE1tY3+ozzHUN31LR%20TTRUvs7opKt+OLopLoXC/bTivDYrlmGhcX3cglnmuXepIXAANAc4eUadktxxbGkIsxxbFIhKHGQn%20ya69RQ00V12g5N7e8O5S6GXkONiv3W9fRdJVtN3X6S2v4qKJeOO+3/DONsmiw2Hgt2XDgZm7Q4kt%20H/NVKiK8h9ieNXTsjf4F0mJyl/WWZ7PPE+Vrt7DsJ8tHdNqx3YrbteNeaYlDbC85fawwXORxhuMf%20PEQchaAuMUzKsMMsepBqK1/uXE3XhrZ/YyRf6tfyqXhHIsPcPyTnXlxjo3mGKyr67JC0hu8D8opr%20VaO22WfFfSNInmtN0I1wGK1xfHbP0zUyxGR8rTtJ3vc4NfXpoaLmeUv+rlnTlK9kaaM6SVlm+WbI%2020d7bSaC6BcxzQe9CdfKmC+26ItovPJusZkGW9+Lu0nZkWlrY2Ws7RDJHHUGoLgS8jbT4rLbs7Yi%20aaSpE1nml0d7irglsUuyUiojeSx5odaV8O9Fhutusmowc9xHF5RsJvYWy+m7fA5pc0tLXVqXR7TT%20QLNt99fjnTQm2JeLDNe4HGWbsZc/6htZdv8Akr8tjdGTp5ZQdQ0DuNV6Db+Ytn908ejFONO+Pe6/%20Gsk8W97I7FZFu1skF230mvkpQiF5qHiv4rrY89l/7ZqxTFGbnOVSQn7PAW36tly6kkDCTHCKfXK7%20sKkfNZe06LuD4jFZXj8tfPdf5m4FZ5ZCNkZOpbC2nl1U1Eh2ODt4Gh6+NEgXGijQP2/ggqgIB6IL%20O1znOANKVB7+P9yCKe52OxN5hbY3/wB3HJbXDZrK+s4hO+3naDtkdG6rXN8QQhVz29PML2zt5uQW%20F/b3kmOZ+gxYselEy/8AVeC+aJp2tc8em7a4uaBVBuY8Jy9uaky8z712UZl7KLa13+WNsbRguNkf%200+k6atXdajsokq0GMsc5HlYso7GZW9y9lj8kMw2Y7Yn3Lw4Njt3muwu02bR9KkTb2jbmWOzjLuK4%20ixvrwvxgnEgbtfHWURmUveQH6VLv3IVdDQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB%20AQEBAQEEG954J5uCXIhjMjmTQPcRH621rXgl7o9dwHcIIRxzD5q4ubWwt7m7tsTfZq6nnyVpEbUX%20kIt2ubSP/wCGNshLKtGpFUKrsPI8uOWZK4db5OPDstcg3KWNXyTA29fRMZ6Me/8A+MNpUFBYt7rJ%20swOFGSyuTkw88N7PcXNsHOuGZElptrUupvIYwu2g/U7qo1Etmm5fJw/iUl9G85V17AMkBEC70dso%203SM/IduzcQNCpEZOO5XNjD93dZKcZuyzLMjA86R+g8i12d2Op0p9SaCxHb8ttLnB4luRnxVlb46x%20OHnla+RrpyW+s2UM0e+vl2u6N+SIq2zrflLZJsi+W8nup+Rm3it5WgwxWkbqN9Nrh5WHXzJOqWts%20cjy8yTSW0+RfmH2mQdyG2laTHbzMeG2vo1G1r9tNjW6EaoVdR4Rjrix4xj2XVxcXV5LBFNdS3bt0%20plewF4IoNvm/L2Qb1AQEHiRpdofpPSg79dUGsz/H7HPWTrO/i3MNTFKNHxPpQOYfEdigjvC+UZN9%201eYPkLG22Ss3+lZSP0bcwtO31Gu+gmvYJUTQbKkE9qHr4pVFBu00NNepHWgPTr8kqRD0BqKA6E6k%20/H+9EqCLpU9OlPFRQV27abRr0PxoCkjwC413N0prp1+GqVHoippQnxr80FQ5urgCakapURPEOdh+%20aZLFU22mXb+pWLaaNmFG3Ar4vJDgPgpgYOe9nuEZm5nvRZPxmQuQ6Oe8sHGF8jHVB37dD1KxzbE8%204I0cZynsp7rcavXxYD0cxgmuP2rpHAXTGin1itHE/D8VzN14jHknu/ulkjJMaLWIw2NM0UfLrwsm%20icBFYTNNuwyONS0Cnm8CuTftLsM1ttn4/wA+PtXTy8xHHskwC7tmtc3QTM8sjSRQEeNCO65F92SJ%2005MndHVqr7jOYbKx0BZlLZunpTOpNG2jaGKRorSvXWvyWzGe2I14/QiFsclyNm9sb3G23ENdFkWF%20rSABUMkpr4EkfvUTt7bo44+77kfBu3cgxHpB2SkbYu02umI2vodziC0mpNTpVYp2mSJmLYmafgms%20dWjyOGZzIQsbB6WFhoY55Q315HnVroaj+WPAroW542/Wt34RxxKlKr9hZ8p4wXzcUyIDZGhstnfH%201I3FpO1xcav3Dp16LcwecmZpfrCk2R0Ta095MXbugh5Dj7qwuHkM9djPWgc+lXHczVrRrqV28W8x%20X0pdrKnZKeY/M4vIxepj7qO7ZtDqwuDtD06LaVZJmaDSh0NCo7hVsjSK6gDqT2p1UipcB1/aiBuG%20g7noPkokeIwQ40FB3r/tUi4gx7HI2N/CZrKdlzC1zozJE4Obubo4VGmiDIQEBAQEBAQEBAQEBAQE%20BAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAAAFBoB0CAABUgdeqCm1tKUFK1/FBVAQCAaVFaa%20hAQNrddBr1+KDxJqaVIpqTrTXRBqLXD5O3zctyy8c/GzRbXWkpLnNlr9THdhRBsWRXgd55Gub2Aq%20KIL9djampGgQVD2mlD16f2oDhVpHigjfLeHWfIILed4ezKYtxmxs7HFoEwGgIJ1aT2KEPPE+WRZq%203fZ3BEGbsQG5O1I6O6EtNNQfEIhJWghxAB29QSUS9ICAgICAgjPPbaVmLhzVsP8AN4OUXrfjE0Fs%204p//AInOI+KCQ2d1DeWkF3Caw3EbZYydDte0OH8Cg9vLgPL1/wB6iRHOUcB4py6G0/1DYx3j7Jxk%20tpQS1zHHSrXNIUweyEcn9tOZY+Bk3D71t+Wk+pZ5M1JjAJAZJ13a08y5+bxuK/pReL2guuU2+Hlt%20rXkIlwVzLRsDLyoY+RoHqCKSm0gO7rg7nxOS3lFa8fdxLLFzdSy2N9AI7xjLm2eA6IUq0+B06dfy%20rlzjmyawvM+qLZL26D3l+OvjLGx3qNxN0Q62Y4VIcwCtdNAB0W5i8h2xSYpPr1mPSZUmx7ivslhg%2043sD8OXgn1I2ia2kI1IPdviVj7bb9Y14/ou3dln4ZLQPyDKnaC2eDzw7aEFzXUrQeH/FY5wxXQZj%20WWVzBIbWRlxFIPOG61brXcKEagrFE319+ORzaNvEH4u4fcYG7uMJcO0e61J2Pa07qGJxpQH+C6WD%20y2a3SvdH5KXWeqRYL3Q5FjXelzGybNbGjYslj2mTaAKfz2CrgXnoRovQbfyeLJ7XMM2TCf8AHeV8%20a5CyQ4W+juxHR0wjJ3NDhQVBXQiaq0bY1B0NNTQdB4dlNEAd5QQaj4Gor3+KiiTa/Q0Ip+Uf71I8%20yxvdFJG3XcwgV+IoEkc99lZsfbY7KcdtmiC6wt3JHfwMFGCWV7nkg993f4pUdJQEBAQEBAQEBAQE%20BAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEHmSWOJhkkcGMbq57jQD5koKQTwzxNlhkbLE7%206XsIc0/IhB7QEFuK4t5jI2KRshidslDXA7XgV2up0OqC4gt3Fzb28fqXErYo6gb3kNFToBU9yg9S%20yxQxPlle2OKMFz3uIDWgakklBVrmvaHsIc1wq1w1BB6EFBSRoc01IDaGp7j8UHi0lglga+CVs0Z+%20mRhDmn8RVBdQHEBpJNBTUlBatpYJ4WzQytnidXZIwhzTQ0NCPiEqLqAg0N5xSJ+egzVhcGwu2tcy%206DGNc2ZjtaOBprUdUG9a2nzPX4lBVAQEBAQEFJI2SRuje0OY8FrmnUEHQgoIvwaWSy/UONzmsuIm%20P2241e60nJfC9347m/gglJIAqenwFf7EkUe3cP7ux+aA1tK61qoiBq87xvj+ejZDmcdDfxx7/TZO%20xr9u4UcW16VU8xzzlPtJlobKM+31+3F3Eb9k9re7pbd0Yp9Fa7SAKVC1cuyx5Kd0cfwWtumEeyuT%20yPGxG3ktlNjWPo1tzGRcRue0eZ5LNWtLgKVpouHuPDXVrGvPjj8WWL+jaW2VsL2FsjDHcWkg3soQ%20+M0AqNCe3UfvXGnDdayTdVhXPFMc5lcVM/GzeZzjG4mOpOlY3eXSvRRbkmOcVOfJqpGZrChzri0f%20Cx5q2+sfMHkEkOfH10qs8X23e/H2en5kxTnpxxxDY4nkzprUvlYLyPYWmaAEP6eb+W7a4fVrosV2%20Lu5accdTuiUezXOHZueTD8EkZJkLYl2QyM7AbeBgNDGQ76nk9h2W1OKzaxF+flPKOszx1UrM6QwL%20Hg99ETNcZy5F+XbmT2T/ALZgIFRua0eZtW1o7qFiv/2W6J+SJiOOPZP00u4b7p+4ePlurXPWzeSN%20tj5ZLMNgmY0d3tefNoHVPivQbTzGPJGtbWKccum8X9xOK8oia6xutlxta6W1mrG9hd+V26mq7ETE%20sdEp3bWjefMfDxpUqQEjTQCuvQ0Qcv8Aay3ns+d86iu2GGS7vxc2rHDV8O0N3tP+GvxUDqO4KQ3C%20tK6oDXVDdNSK+I/eoqKqQQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQRD3cDz%207c5xsbHSPMLQ2NtQXVlYNumuvRBDLmzyHDsdcerLJirjkFzvsrPHvL7a0+3gFWunkDtokI3fTqTT%204oUe8RzvPuuONZDL3UzrTI4+MyWNpGTM26MZc+SeAt3ekexB0SiaNZb+4XJnW2Z+1vLh1jSxfFeT%20s3y2rLiYRzPNGtGg/LrTqUhDziMzdWkl7bszktti8hm7z7zlIio93oW8Rhi+nb5ySN9KHbohVI+G%20Zjmmez+KbfX8lrY2+O+8njZDt+8cLqSBj3lw8rZIo2v2jxSBqPcTLZC+z+Rxl3kH2sNlkcTHYYts%20Ze24ilex75dwadQ40qDRtNUIeJOQcvy0HI2Xc0cNoLbKW97iJHH1Y44YHeiYImsqXVPmO6h1p0QS%20PkmZyWN43xCzgun4uwvm28F/lGMq6BjbbcGitdheRSpQavIcxyQ5TjbDHX91eW5ubfHXzZmbI545%204C900TQ0l3QVkq0A1QRvi3KeQ4bBeng79+VmbZZGW4w74Hj7J0DnGJ4NN1C7TvXsiKtte8s5FbcU%20nllz4ZJeXFtFg7qJ4mlE08ZdKLqkYa2KKu4CnaiTCaVZ2U5rlIuYYzG2t5cTgTW9hlI5GUgmZJbv%20c6eFrQXHc5o8+7aOiFUv9qozHwexYQW7ZLoUIof/ANmTqglqAgICAgpvZWlQgqCD0QEBAQEET5NX%20E8jxXIGAi3ld+nZMj6fTl1ilef8A+t4oP+pBLEBAQEFH9KeOlPFBj3FrHdNLLiKOWNwo6ORocKHr%20ofFBz3lns7a5K2hdxS8/0xdRvBlMDd8crAa7XxuO1YcmGy/nGvH8VoumESzLOY8XiY7O4/7mIg/5%207HOdINsdKvkZQbSuLn8LM/tmOP0+/wC1eMjOxuctr21jltpWzRyNa5tPqFSaB7HasNVxL9pNs6xx%20+rNF3ojHunkcHisA68ZG2zyt410VjPESwGYirSaHb+8FZvGWXXZJrytVvnRq8Nax4LCwxWNtHNfF%20nqXx7zzAUdI8nWq528vnPlnunSJpCbKNtjr279GSbIelCwOBj2OP01rQk7dQf27rn5sVtYiytWWY%20nk2XCcfLcx3mTuIGwPuJBHayn6iwa7j10IK6VeyItjopOrMy/E8Tkm/5u2AG4vD4S6N1R5QRsLTQ%20eH9iz4PI345pE8fzVm2FePZXnHFbWWG2vDyCCEEst75+yRgbrsjd3O3x/wCPe23max88c+OOKYrr%20E24x7rcczrhBMJMVfBg9WG9HptDtwaWxvNA7X5LtY8tuSK2yxTFFxpa73Wikbqx2KOx41a4eoOh6%20FZY5CZuBrtDuvauvXUqJiRVjqiupB1B+BSBUHqPBSKoCAgICAgICAgICAgICAgICAgICAgICAgIC%20AgICAgICAgICAgICCjmtc0tcA5p6g6hB4mt7eaMRzRMkjBBDHtDm1HQ0PggoLW1EzZhCz1mN2Ml2%20jcG/4Q6lQPggoyys2MexkEbWSV9RrWNAdu+rcANa90B9jZPt/tnwRut9P5JY0s06eUiiC6I2A7g0%20BwG0EDWnh8kHh1tbumbO6JhnYC1kpaN4B7B3UIKfZ2nrun9CP13t2Ol2t3lv+EupWiD1NbwTRGGa%20NskLhR0b2hzSPiDog8i1tRIJRCz1GgNa/aNwaOgBp0SgrHbW0cjpY4mMkf8AW9rQHH5kdUFoYzHC%20F0AtYfRcdzovTbtLj3IpQlBcFpaB7ZBDGJGtDGvDRUNHRoNOiC41jWN2sAa0dABQIKoCAg8v31qN%20QNad0GFZ2uUhvpnT3YnsXNHoxFtHtfXWrh1FEGcWtPUddSgqgICAgIMDP4mLL4a7xslKXEZa1x6N%20ePMx3/0vAKCuCZk2Ye0jylDkI4msuXtNQ57RQvqP8VKoM5AQEBAQUpR1etf7kHk7jVrgHNcDXTSn%20gaqBCeUe03E8+6OQwyYu7a4SevYH0XPd1Ak20D2g/lOhVb7YmNSJce93/Z73CvsRZwtAzzrCR9zE%20+1YWP0ADWvDj5yadlr49nbjrNundT8Fu71RODmMEcRZcwTW9/bgMuLItc2aN9KFhqKVDtNPgvJ5v%20E5Iup/bXqz99YTHjWGuM9aGTOW7rCyZJvt7MO/mSg673k6BppRauTbRiurE1laJq6LC9npMY0AFr%20QyNgO0Na3o7pp/etXuol72sfTxJBIrXXpp+I+HRJmELT7Vjx5gQXHTbqeleo/wAJ791NuSka8f1T%20MQ1t/hrS5jcyeGKZpa5p3sBoT1AJ13d6rZt3F0T8sq9tUYs8HyLjGXx19xu8N7FB6pntMi58jWNf%200bEQQ4D4L0G28xERS+GKcaccR95hdzXFvy3Fni74SG21zcPrDckaH06CjaUr9S7OHd48mls6sfbL%20pFlksdfRNks7uK5G0EPje141Fa+UrYVqvtIBPTyjsKmnbVRCXr1WUrXSlf71I9VFaV18EBAQEBAQ%20EBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQUke2ONz3fSwF%20x+Q1Qc3w3JOXZXEX3LZL+K1wjHXTYMZFCHStht3ujEhkf/8AIdldv0oKY/m2RlyZjmvX/bzXOMht%20C2JoL23NqZZQ4EabnCte3RJGVae8GPltZLy5xd1aWr7OW+sHv2F1wyGYQFoYDVjnSPaGh3WqDXQe%2052btctlf1DD3ektha47DD0zMZbxrnbhIDt2mmtTpQoNz/wC0rZl+2KbGzsx7LuHGXWSDmujivpmg%20+ltHmc1pdtc8aAoMXkvPclgObXUDrSW+w1riW390yHYPRaJtr5juNXUaPpbqgvM9wnQ39xawQz5a%208uL82ljZMEcRa1sRmc7c7aNrW9zqgxOH+5OSvbfC2F1j573K5C2nvbydoZFHbwsmkY0SVoN3lAp3%206oK4j3NibkMhBftlkuXX9rbwW8bopI4orv8AlxbZI/KfO07mnzBBTPe4Nz+oxmzdJa2No7KW99WM%20Pc+Syty9rmfj2Qo2Nl7ix1nDrSa5x+Ktmz5jM1YxkbvRdKQIvqefIQdvQoMvjXPBl8q3GXmMnxd1%20Pai/sGzOa8T2pIG8Fn0lu9u5rtRVEo5ee517cZ3EyWtrNacdfNeie/k2FlwyyFHbW6vZ5qgVAqUQ%2083Huu/L2ERxDDZXAu8e+ri2YSWV5N6Y1ZXY93dh8wSZTR1BECChJ7BArQakbqdEEb5RwTi/KYo25%20i0Ej4HGWKSI7H1Om7c3r0VZivNFHO8x7c8+4/wDzMHcf6ltZH62l16cEkQ0aNjxSooubufF48kaa%20TC9t1GvtuTxwTm1yLZsVex+WSO9Y6FhINKRPfSrTrRcLd+LvsmsR3Qy23RPs3sGQjdGH+UxuAFG/%20T40p3Pdcz6Guq7NE7TtqRR1NSagUJNa1A7GnbxWGLbY4445LSuNfu8dpANQR4Hx8P28VS+2nxWtm%20ujU8ky2PwuPN5dnc7oy20L5HahoAFa66Ld2W2yZ7qWww5r7ccVumjl/M7+W/wZfyaRslk91LfFtc%20InVc7y1kBrpXUU76L3my8PjwR3Xc9K6/GtOvOHkdx5m/cZfpbf3+bn90fl6xVHriyyXFbsX/ABmd%20+Cjfbl1rKSZnlx19J0by4Nq0d9dP358k28rejqeOs3FK5p+b004+7Rv+E/1bZ7H3Is+cst7yCRrH%20RXtmKkCpDtzY6g+Ko6T6O4bz3h/LrQ3XHcnHfNDA58TSfUjDugew+ZvTulURCRBzNO+3v4fFKFXp%20n0ih3CnXxRKqAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgIC%20AgICAgiEPtlh4JLyO3vb6HF3plfLiWT/AOWElw4ukc1hBpUknr1QZMPt7x+GeKZvrb4ZbaZlZDQO%20tIfQj/8AsOqC0/2z4zJYW9hK2Z9vbWcthG10hJ9OaRspfU/na9gLT2SBbx3tlhLSdt1NdXt/fC4t%207p13dTepI6S0a5sXbQAOOiErknttgX5p2R3ziCS6bkJsbvrauu2CgmLCDr3oDSqDOyvDcRlLq+ub%20n1PUyFkcdcbX0HoF27yimhr3QYFz7b4WV/rQXF3aXbbn7yK6gl2yMeY/Sc0aEbXMNKfigu432647%20j7cQQeu6P7GTGuL5S5zoZXue4l3XeS8+ZBroPaPjkNnPALi7dPKy3iiuzL/NhbaOLrcxkDRzK6nu%20gyIfa3jbLYwPkupy512+SaWYukc++ZsmJNPD6fBBcb7bYVl3cSRz3Mdnewfb5HHtkpb3AEfpB0ja%20fVsOpHVBk8c4LjcHeuvm3NzfXYhFrbzXknquhtmmoij0FB4+NAgwbf2s47DftuXS3UttC64fa46S%20Um2iN5X16M/5iajwQXbP25xcOMZjJru5ubO3nt57OORzf5QtHbomVA8wHeqVEsQEFHOI7VCCgcHV%20Hh4H/YorUU2vp11HavUj+5KDy71Gka1BFKAft4pWRqs/xnjfIYWQZ3Hw38cTi6ATM3bSfzN8FPVD%20n+c9p+Q2Uon4hlCbY9cTfndC0UAHpupuB07/AIrRz7DHfzheMkwjmU5JdcYkt4eUWz8O+6cYreaS%20j4ZZANRG5hdTx1ouFufC3RrbFWWL4lILa/in9OkvqAuFXgVaQTp8a6Lj5tvNsLTMxPHxcr5Rze4v%20+SXI2kW+Bc+O2Y0NcaktBlAeT5gNK06L3PgdrGK3viNaR+X2af01h5rz931aYpnSvw4+HVHRyS7u%20pHXGQbbGaEuOHt5mB4cxob6022po91BtqdFv5ss30jjijL4zxlm3tm63W678mhz/ACvKe4s36Dxi%20zfDZ2zjcXtwHEy3G0mssp7N2+anitWfk149v4OpmzRZb3Ty9UfzPFLOCK4ZZMEpa50EcvloTBQPJ%20Lto1cfnp+/JZW7nGscU+Mfjz+Olbuu6baeldK9fzowPbTlXI+McksJsHkHWT7+4gtbsM13xvlbVr%20h4KZ9HRfo0AAK1rUAlx01okK0XgAAABQeCJEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQE%20BAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQQjm2e5FjeVYC3w8X3guYL59xYueIo3ehG1zHOfR1K%20EmmiDX/+3ZbmyfksZh33eNsLWG7zcxkbG63bMN5ZG0j+a5kfmPTRCWRiueckmZyCe7srOK0x999r%20jJXTlnqsdtLRJRr/ADAO121UdBrrj3YyOT46x+Dxbn5KfH3l5cNdKI22wt6sBDiDucXatFOykXbH%203OyUGItrh2PdfWOMt7BvIco6Rsb2TXUUb3OjiA8+31QXajqiUn4nyjJZ66yTn437TG2d1PaW1y6Q%20OfM+3kMbnbAPK0001RCSICAgICAgEA0r21CAgIKFoPXVBWg/d0QEGDeY6wvYft8jbxXcJqNkzGvG%20vU0dVBzrk/st9xI274flX8euDu9WIh0sDg4ggemT5dR2Wvk2tl/OITF0w+aef8f5XwK/ubTOtdB+%20pyPdb3sby+OYCm91aDZ8B8fms9szbbMRx/Nzdzte++LudHPr/KzPxDpGXLrj0XfbROcKFkZFatcN%20a9v+KmjoRLoPEJMNiuEmbF3Jx1/eOihv8htLjtLQHwgV/OT1HRVtxxdNZmYp/T8vx9NHG3ee6ckW%20xFetPWY5fdMcverT84yUTZLOygijubucMnPpP0ijcdWyObTzebU9ta10K2b7YilsRpxH40W8dgm2%20Jm78evv8Ke8156JP/Th7Qt5bya6zOSia7CY8tlgBr5pzJVm3xDdju6wOxEaPtNtCdtKaCg07advB%20EL46IkQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQE%20BAQEBBo+ScOw3IZbWa+ErLiyEotZ4JXxPYJ2hkgq0iu5opqg1157W8Oun21bV8MNvFFbOt4ZXxxT%20QwmrI5mtPnA+PySBcv8A214tez3k8kMjZL2aK6fsle1rLiHRksba0a7Tsgsze1XDpbO2tDbysitm%20TxExzSMdJHcndMyVzSC4Odrqguy+2fEpL2C6Ns9rYWwtfbNleIJvtmhkJmjrteWNFNevdBvcVh7D%20FQSwWUfpxzTS3MgJJrJO8vedfFxQZqAgICAgICAgICAgGtDTU9kFl+4HUkCpOnfX4fuUTAruYwV6%200FNKDUf8U5DEyOMxmUt2xZKzhu2DoyZgeKnrt3BWV0l89cp/ptwfNbnLTccnjwEdrfGG3AjL4JgG%20D1Tpt6PNG06dFFVnOsr/AEve9GNsvs7P7e/tHy1rBORJ5dQaP+kadvxSVJsiZq3/ABD+kPmM14f9%20TZSCysaslf8Abn1p5C7R8bydtBt0Kmtea1IfU+DwuIwuNt8Zi7WO1tLZgjYxjQzRutdOprqoomrZ%20naASendBUADogICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICA%20gICATQVpX4IArQV0PcICAgICAgICAgICAgICAgICAgoCdainh8UFUBAQEBAoECgrXv4oNRyzP2nH%20ONZLN3JLYLGF0ri1u41+lug6+YhBjcCx8dnxHGAVL7iIXkpdqfUuj67+uv1SIJAgUHh11QU2t8Ag%20qgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgIC%20AgICAgICAgICAgICAgINfm8/iMHZm8ylyy2hqGt3HzPcejWN6ud8Agv47JWOSs47yymbPbS/RI3o%20aaEfgdCgyaitO/ggAgio1B6FBrMnyTEYx0ovZjEIWsdI7a4gCRwYzUA9XGiC/jMvj8pFLLYyiaOC%20V9vI4VoJInbXt/AhBmIFRp8eiDV8j45j+Q44Y/IOmFr6jJXshkdFvMbtwa/b9TKjVp6oNoAAKDQD%20oEBBhy5jHxZWDFSS0vrmN80MVDqyMgONfhVBZvuR4exuDb3c/pS74YgHNdQvuKiMA01rtKDIxmUs%20cnaC7spPVgc+SMPoR5onmN418HNIQZSAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICA%20gICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICCCc+tbu35NxzkLsfJlMXjPuY7y3ha%202R8b7hrBFOI3EV2FpqRqEEY5tPyTKZPHyYXBXdk9gguMfOBteT6xMrHxteGRDb5nF1SQUFvI2vJx%20JyKCyt7y7s5LmK4vMjrFc/bm5BubJgLiHtbCDtc2nl0QWOOZDJ20772xjyE+Ixmfnjmsid88dtJb%20kRNLXEuLdxaAK1HeiD2zCc2usIG3ljdl77C3/kylr3NlbkXSEHXV7Yqd6Up1QroXmGy1vIwZPHX0%20mDfeZR8kNpUONzNIXW8r2tdu2mo2eB6onm3mZsuYs9u+Ow5JlxdSQvt/9SwWzx9zJbjVzdwpXt6m%2034oiGlz2Oysty4WljlWsktbX/R/puoLWVrq3H3ALtHbqF2+tW1QbSz49yaPPQZiQXjsgeQelcvMl%20Yf042w9TZGSAInTN071QZuas8i/3Dmfkra9uLWWCJnHprYn7eGajvUdKA4UdU6k9kqQjDB7gXOOj%20sra1yUV/jMTc215cP2sEt0JDUQuqdz3NrsdT+5TzJZNzxCHNTYmSyx2RtsZb2F+GiR72Si6eKt8z%20ju8zh5exKiCWS3EcyumWf3ttcTPZ+iOcJC3SSB03ruPxa3buUSirUZ7Gcri4/a46zxFzHfsdeT2F%203Fu3tnfkJHtjEbSGsrEd291dCpS7hAZDDGZP+4Wjf/1U1Qe0BAQEBAQEBAQEBAQEBAQEBAQEBAQE%20BAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQWoLS1gfK+%20GJkb53b5nNABe7xcR1QXUBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ%20EBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBB/%20/9k=" height="413" width="665" overflow="visible"> </image>
          </svg>
        </div>
      </div>
      <div class="fig"><span class="labelfig">FIGURE 2.&nbsp; </span><span class="textfig">Main parts of the sampling probe, not including the basket. Source: <span class="tooltip"><a href="#B1">Azutecnia (2019)</a><span class="tooltip-content">AZUTECNIA: <i>Manual Técnico de Explotación de la Sonda Toma Muestra</i>, Inst. AZUTECNIA-División de Talleres “Enrique Villegas”, Informe técnico, Villa Clara, Cuba, 6 p., 2019.</span></span>.</span></div>
      <p>The
        research was carried out at EAA “Panchito Gómez Toro”. The 
        characterization of the research conditions followed the provisions of 
        the Normative Operational Procedure <span class="tooltip"><a href="#B21">PG-CA-042 (2013)</a><span class="tooltip-content">PG-CA-042: <i>Sistema de gestión de la calidad. Pruebas de maquinaria agrícola. Determinación de las condiciones de ensayo</i>, Inst. Instituto de Investigaciones de Ingeniería Agrícola (IAgric), La Habana, Cuba, 10 p., 2013.</span></span> and the following parameters were determined:</p>
      <div class="list"><a id="id0xfffffffffd075600"><!-- named anchor --></a>
        <ul style="list-style-type: none">
          <li>
            <p>•
              Length and diameter of the cane pieces (mm). A 5 m tape measure with 
              appreciation level of 1 mm and a Vernier caliper of 0.1 mm appreciation,
              respectively, were used.</p>
          </li>
          <li>
            <p>•Strange matter (ME) (%). It 
              was determined by separating cane stems from leaves, buds, earth, 
              stones, sticks, among others, in the samples obtained with the probe. 
              The result was expressed as a percentage of weight of the stems with 
              respect to the total weight of the sample.</p>
          </li>
        </ul>
      </div>
      <p>The determination of the quality of the work considered the following parameters:</p>
      <div class="list"><a id="id0xfffffffffd075f80"><!-- named anchor --></a>
        <ol style="list-style-type: decimal">
          <li>
            <p>Mass
              of the sample released by the dumper (kg): Mass displaced by the dumper
              and collected in the vessel without the manual action of the auxiliary 
              worker.</p>
          </li>
          <li>
            <p>Mass of the sample left inside the probe (kg): 
              Mass of the material left inside the probe and removed manually by the 
              auxiliary worker.</p>
          </li>
          <li>
            <p>Total mass of the sample (kg): Sum of the masses of the sample released by the plunger and collected manually.</p>
          </li>
          <li>
            <p>Mass
              of the spilled cane (kg): Mass of the cane fallen from the means of 
              transport through the entrance or exit of the probe, or spilled from 
              inside the probe.</p>
          </li>
        </ol>
      </div>
      <p>In all cases, a 1g appreciation digital scale was used to determine the mass of the samples.</p>
      <p>The
        influence of the harvest-transport system on the sample mass of cane 
        stems taken by the Horizontal Sampling Probe was determined from the 
        effect of the content of foreign matter on the sample mass taken by the 
        probe. The system composed by the CASE A8800 series combine and the 
        transport with Sinotruck (20t) and 20t trailers was evaluated, compared 
        to that of the combined KTP 2M and the Zil 130 (6 t) with 6 t trailers.</p>
      <p>The exploitation indices were evaluated according to what is established in the Normative Operational Procedure <span class="tooltip"><a href="#B22">PG-CA-043 (2013)</a><span class="tooltip-content">PG-CA-043: <i>Sistema de gestión de la calidad. Pruebas de maquinaria agrícola. Evaluación tecnológica y de explotación</i>, Inst. Instituto de Investigaciones de Ingeniería Agrícola (IAgric), Norma cubana, La Habana, Cuba, 13 p., 2013.</span></span>. For a penetration depth of 1.30 m and a rotation speed of 155.00 rpm in the probe, the following indicators were determined:</p>
      <div class="list"><a id="id0xffffffffffd6f400"><!-- named anchor --></a>
        <ol style="list-style-type: decimal">
          <li>
            <p>Time
              in taking the sample (s). By means of a digital chronometer of 1s 
              appreciation, the time in the operations of the working day was 
              determined.</p>
          </li>
          <li>
            <p>Productivity rates (kg/minutes): Productivity
              in clean, operational, productive and exploitation times. In addition, 
              the operating coefficients for technical maintenance, technical safety, 
              use of productive time and use of operating time.</p>
          </li>
          <li>
            <p>Determination
              of fuel consumption. The measurement was made with a Flowmeter of 1mL 
              appreciation. It did not include that required for the transfer of the 
              equipment from the parking lot to the work area or vice versa, however, 
              it did take into account the movement from the parking area to the cane 
              transportation means. Fuel expenditure was determined based on the 
              number of samples (L/sample) and the weight of the sample (L/kg).</p>
          </li>
        </ol>
      </div>
      <p>The
        size of the sample of the variables under study and the data obtained 
        in the different investigations was automatically processed using the 
        statistical package STATGRAPHICS plus 5.1. The t-Students test for an 
        independent sample was used as a criterion to estimate the differences 
        between the means of the samples, at a 95% probability, in determining 
        the weight of the sample based on the harvest-transport equipment used.</p>
    </article>
    <article class="section"><a id="id0xffffffffffd70100"><!-- named anchor --></a>
      <h3>RESULTS AND DISCUSSION</h3>
      &nbsp;<a href="#content" class="boton_1">⌅</a>
      <p>The characterization of the harvested cane showed that the diameter of the piece corresponds to the values reported by <span class="tooltip"><a href="#B17">Mesa et al. (2016)</a><span class="tooltip-content">MESA,
        J.M.; ACOSTA, R.M.; RODRÍGUEZ, M.; HERNÁNDEZ, G.A.; JIMÉNEZ, A.L.; 
        GARCÍA, H.: “XXIV Reunión Nacional de Variedades, Semilla y Sanidad 
        Vegetal”, <i>Revista Cuba &amp; Caña</i>, Suplemento especial: 50, Publicado en La Hsbana, Cuba, 2016, ISSN: 1028-6527.</span></span> for the varieties of Cuba, with an average of 24 mm (<span class="tooltip"><a href="#t1">Table 1</a></span>). The average length of 163 mm is related to the dimensions reported by <span class="tooltip"><a href="#B23">Placeres (2015)</a><span class="tooltip-content">PLACERES,
        Y.: “Evaluación de los índices tecnológicos-explotativos y económicos 
        de la cosechadora cañera Case ih Austoft a 8000 en la UEB Perucho 
        Figueredo”, 2015.</span></span> in the mechanized harvest for direct shot to the central tipper.</p>
      <div class="table" id="t1"><span class="labelfig">TABLE 1.&nbsp; </span><span class="textfig">Characterization of the cane piece</span></div>
      <div class="contenedor">
        <div class="outer-centrado">
          <div style="max-width: 1160px;" class="inner-centrado">
            <table>
              <colgroup>
              <col>
              <col>
              <col>
              <col>
              </colgroup>
              <thead>
                <tr>
                  <th align="center">Parameter</th>
                  <th align="center">Mean*, mm</th>
                  <th align="center">Standard deviation, mm</th>
                  <th align="center">Coefficient of variation, %</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="center">Diameter</td>
                  <td align="center">24,07</td>
                  <td align="center">4,56</td>
                  <td align="center">18,93</td>
                </tr>
                <tr>
                  <td align="center">Length </td>
                  <td align="center">163,46</td>
                  <td align="center">31,56</td>
                  <td align="center">19,31</td>
                </tr>
                <tr>
                  <td colspan="4" align="justify"><i>*n=21</i></td>
                </tr>
              </tbody>
            </table>
          </div>
        </div>
      </div>
      <div class="clear"></div>
      <p>The
        evaluation of the quality of the work showed an average mass of the 
        sample 1.31 kg lower than that recommended for processing in the 
        laboratory (15 kg) (<span class="tooltip"><a href="#t2">Table 2</a></span>),
        according to Instruction No. 3 of the Sugar Mill "Panchito Gómez Toro” 
        (2019), which was associated with the high percentage of foreign matter 
        (15%) and the harvest medium used.</p>
      <p>The mass of the sample 
        remaining in the probe, after the material was discharged, represented 
        12% of the total value of the sample, due to the fact that the plunger 
        did not reach the end of the probe, remaining 15 cm away from the tip of
        the blade (<span class="tooltip"><a href="#f3">Figure 3a</a></span>). The cane remaining inside the tube was extracted manually (<span class="tooltip"><a href="#f3">Figure 3b</a></span>).</p>
      <div class="table" id="t2"><span class="labelfig">TABLE 2.&nbsp; </span><span class="textfig">Evaluation of the parameters associated with the sampling</span></div>
      <div class="contenedor">
        <div class="outer-centrado">
          <div style="max-width: 1160px;" class="inner-centrado">
            <table>
              <colgroup>
              <col>
              <col>
              <col>
              <col>
              </colgroup>
              <thead>
                <tr>
                  <th align="center">Parameter</th>
                  <th align="center">Mean *</th>
                  <th align="center">Standard deviation</th>
                  <th align="center">Coefficient of variation, %</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="left">Mass of the sample released by the dumper , kg</td>
                  <td align="center">12,09</td>
                  <td align="center">4,61</td>
                  <td align="center">38,09</td>
                </tr>
                <tr>
                  <td align="left">Mass of the cane left in the probe , kg</td>
                  <td align="center">1,60</td>
                  <td align="center">0,79</td>
                  <td align="center">49,48</td>
                </tr>
                <tr>
                  <td align="left">Total sample mass , kg</td>
                  <td align="center">13,69</td>
                  <td align="center">4,81</td>
                  <td align="center">35,08</td>
                </tr>
                <tr>
                  <td align="left">Mass of cane spilled, kg</td>
                  <td align="center">5,11</td>
                  <td align="center">2,41</td>
                  <td align="center">47,26</td>
                </tr>
                <tr>
                  <td align="left">Strange matter , %</td>
                  <td align="center">15,07</td>
                  <td align="center">5,29</td>
                  <td align="center">35,09</td>
                </tr>
                <tr>
                  <td colspan="4" align="justify"><i>*n=21</i></td>
                </tr>
              </tbody>
            </table>
          </div>
        </div>
      </div>
      <div class="clear"></div>
      <div id="f3" class="fig">
        <div class="zoom">
          <svg xml:space="preserve" enable-background="new 0 0 500 211.278" viewBox="0 0 500 211.278" height="211.278px" width="500px" y="0px" x="0px"  version="1.1">
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VyZ0Cc4La%20xKlL/iQHpcrQCqG5gAcCoAduKr/Vrf6v5U5EKF0CaqO5Ol7a9KJCAixocEQJYL/SL/8A4bIaW4EF%20GBtDWgXICG2liqrtRV/nRuG0OR+W4hDtB0BVVJBGq9VoBLqSI8WN6pogIBsAqL7B21LuZWzqOsx2%20NeWEhS1DcdhRQVP2dvvW4aQ7sY5wDUUghu0m+7tsNOv0FKWG0x/ze9OD1B8uOYwHXkjjGREbEjy3%20bidR/SdRTVyQ9Dnv+1Yx4vF8zx+/fPJJHkpoocNnTra9+w073IJHb5HsDwS3sAUdGlUUWuL++hZE%20isZ4cgQOd0XqqC2vS3s99K4Leg8CEQITYlQe46doIJ/jUmkhOI23Gg6HcL69irb+C00TdDQy6APT%20QuCDcBrdBr7a03GUEf8ARkqhvq1Usl0UdEqtxIoYoDQq2uB95pSggznzEgLeEwECkclhk7kuBIOn%208KW4u01z2MBJRAiImtg4e9Af4WrPcynahuXQnRy+/t6+1L/ypECC4ru3e3rVQIDXFoB0Tr1sV0v3%20UNBIouaAQQfDYdbIdNeiVKQB79QumvT2fT2UQEh7gAOwoAlxfRKBCmtAClCPd0IJ+n7Kls0ts6h7%20CLgKAoJSx0snf94+skewUGgD/CvxNARCiuVff/KlJSSEkGwIs4kADtRLKl0+r/w0yWgb3KOhN1Hf%203f8AiB/iaIDcHuUAkJ71DRc2sfwr9NFBSuD3EE22kIb9CLoDayH7D7aAkChU6E3sQD0+Eaog+7Wi%20AkQXtQtXTU9ftHeffrrTSFvSCcfEe3W/aST/APmP0tTSIbBucR3HUnT9/WiBbgRuPmNS7hcKb+9P%20br/GgEyfUm4KABQBTZ0rxkyNaHEBwCalSAFAuSPF+ykJjEc7yoAUt1sTqg7R1NOH1FPQcdkzIPAQ%20E2oCLlbtVTp7aSQBOynBAGtQ2G4gNPTtCdOtNDkNuS5xBO4FyFxQpdAqix+JKYkOK03I0uUGgclr%20bvZSTHnmIdEHNIPhd0Kdi/ypq4loacxFchIUkKQOhuSuie+qklIUZGAbuiXDrEqnutpRmVBLx3wu%20iF7ED6iW3vUtjAsa7m6g2aFBJJWxokW0U2aLaFJRAgQg6G9+tEOQkQ4QuIBRpKm3aR7QbKdKpMIG%20XNG7cHaA2N0It3VUigWjQpDjYqL3sVHUUSEht8tEUOA63UnTU6JUyPIeEjNpR4b0JsRogsQqAd/7%206gqRozMBQuCkkoejRpZdL6U4GKL2X3KXbS0t66guJJ7e2kAUjxqRooBII7kt7aQkRJ3NWxVVHVAA%20ENu3XWqTBkaSYtCMaXTH/LZc3uVPWxVb1ci2mf8AUnrfguBx9k+VG/NDQPJj8Tt10JDdBaxqXcNJ%20sy3/AHn9PxE5ea1zgDshx2XLn6PIb/SAhVdKlXofltmM9V/PXls+Z2DwLRgwPaY3ZZ2nIevRurWj%20ShspWEr0R8rvXL83H9QcnkReYHeY1uessxVCqE+H2LVqpNzjI7XBA+GMRpHqj3NCXah061Zkcw9c%20/MfM9P8AKcrx3HYx/u0j2EZLwrWMuSgUKSLCsOTkg34uFXG49F+suH9T8LDl4eUw5LQ1mXCHFrmz%20IjgFQkKmmtXZcmRfa7WaPa9xVzkJ70TV3fVpGY55D0G4qdTtHdoCaFcG1BiMCxUuAuNNCifX9VEs%20W0PY1qWDwu3Wy3/d2WphAAzwkauAvb3Lf299MYJXtYjnloYvUoF6XJH1VKgRUZvqT07hg/q+QgiC%20gEOfck3Ip3XJD2tmbz/m/wCisUODMl2Q9urWtI6rc9FvY1LvSLXDc8jMZvz6YXEcdxr3hQA6UgC5%20VXALqtS+Toa2elnNnEvVnM5HMeoczkZwGyzSH8sX292vbXqcKbtqcN8JspXKnh+Lp2D21o+5Mjco%20LopGgBmovcH606WpXJuNRpnuj0QE9AcGHN147G3Nt1iav9NeRdmdWaqR1jb5i3IQveFAAS+0aBU+%20qrkzQtAAjijTu3ObYHp227taKhmGW6nchC3sLlyKuvTsoGgKdw6lzkJ0FjdR7ToPtpBIbHMCOLVK%20L7tQUHhH7zQ2FcgPkJcCF3LdqdwIF6aFCQBM5u0kptKDcNUS106n30oGPOywLOIW+pOpUE63uEpQ%20UpM96n+Zfpj0yRHn5IOQ8OLIIz4jsQkbtAdNalou1N1Oac789W5cj44OUh4+Jw8Lce5AB/E4ggke%20+hWXGqtUFO/5px5cTsT/AFGZWTja6BzxtJK2RPhcui2oVjG4fuxiSX6e5M8NhyZXHPHGS79j5QjQ%205jrjc6w22pxJFlqbhlpD6+9SucreaMg3IRuBUEAEEr1GlKumMY6F+XY8fj7KYUiP1/6wRjmcjHIC%203XY1wXUrcWSyUPcV5duPlj5Fg35oerw9ge/Hc15IIMIvYmyH4iDepqD4reo/H82PUg3HIxMd7EDg%20PhJumiFdToaKruJ8M/IssL5txEgchxuxrT+Y6N6kIpCtRrdKe9kPgg3HF87w/LQtkwMhs6k7mqjg%20QVc3aQtkKnvKdlCMbrWs0S3lApOnWx1Qn61++qRkzL/MQN/smE0KE5TE0KaSDoUJ17KbLtNW4hQo%20+ACyHQALr9L/AFyhXOWNy/Ch1PXtOp+/6dKtJY1qiA3JK6m+nsqyBQb4FCL0NKRgSxDei/b30CDE%20chClqC4IOvcO7WlKCGLbGShJBUBLhLqB07eyk7i1YxbSdgAAToqBOq9mnZ+wrBrY6ClADieqldSL%20B3xLqjbUFBkEuO5F623dPFY9P2e5AQSkAm6oLqDYWVSO5RQEA2sIQAFrejUXQhAOi6Du+wkMwHrb%20Xs7Tfste/b9lAwbQXINHFS7uJQakDr7/AK1JFtEkalP+LuX29PFc/X1VyS7RLrKLgAFPeo091NVM%20nQIgkoNFpyIIQo0PNmjUusEHb0stOR7SK/kuHglayfOhY952tYHtc4uVPhvSd2hVtjLuoNgUACgC%20g5R7W5cpJRSAnU+H9tUkQRhKQdoLgFLWBCAoF0Ts0+yhKApApjyQ1XbQSSCeik3IJ1UUJBJRY/P+%20oc3IzY+N9Pvy8bDmMLso5ccW9zbna14W3bpXO+a5txb8YPX/APbuG2y18nLtdymNjce0kjO9bAEH%200vYqEbnwfsHYKPN5P7fiR/hel/7/AP8ATY8eX9Z7XL6XsFLieRxlGm5Vb/Klv5P7fiP/AA/S/wDf%20/wD0XB/3b1oP/wDVAF1B5CBCiC4OoWh33/2/FD/xPTf9/wD+ncR8z1R6h4848vJemzi4087Md2Sz%20MjmLXPsDsYrnXB0pPlutibaeJa/j+G9PZzbrlbMbGsu7oi8e2SOUlUJRFHRCqEalK680eK8Y6BRP%20kXo7QleywuR3CgekklkrtgBKghSLuC6qV19tTA2NkkuAGnUqnUBNR20xTqAPdtQgCxuNT7tetMBZ%20fueSQFVSATe5/fQEigxRuQI3Xt+FNT2gUmMbLHELZBqosvSgBRLj8ICoen7KQ1Oo1KJNrnNa1zmt%20JY0odxQo0+09v8aBSUHob1fH6m43Iyv0xwp8LIfiz4rjue10RI1b9dSqml6hwXmTn4eJtblZMePu%20BLN7tqgIpuvb9lAkpMb6n+ZPE8O0wYjhyfKSEpCwh0TW+E75HhL3pboVCthzH1D8xvWvJGSGLLgw%20GEFi49nlrQibiQhsbCpfJOY1xowT8x0Xm+IeYdwdK4rI7t3F3etKC4Qxw0mJxUj+Y5TB/XxY7Uij%20eCGuyCnlhw127tb1rZVk3uEdA4X158rJIpos301bKY2R7GK4QyNQvLZE+FQvdatHaYq4WPm/xvC5%20wd6dnypMM3l4vkVcwnaAsc3xNHUdKW255IUrU6Bx3zs9C5HGxZOdkPw82RBNhIXkbrq0jpRNyzBW%20oy/q+Dg/WUWdyfDzs/uuGd0UT1aZIRcsBcgsvXpXPyrcu5txXbXDyOc8VyGRgSjKxJHwzxuEsckf%20xCSO4XSx+H2VgrqpnZcpxjEno30J60wvVHBszd7Y82BGZsAciPHUdztV7K7OO9XI4OSyGWuZ6i4P%20BYuZmxRNBAk3ORVO3RT2GtJI2voZvkPnD6KxgGx5ByihTygoNz1AKhaTvgu3iuZmuR+fsTS4YHGl%205LtkbpTtUpa6LapfJ0NF6Zv4+0y3J/OH1vlvDYXsxIju8TG3Fjq4kaCk7maW+lt1x2716eJmuS9R%20epcwbMrk5pHSNc1rfMc0kiygtujTdAKy9Rc1Zc50+knofxnFx3eosT1f1930+J26D5Eehs7j8SXK%20dlSF0UZe4yuvubvO4K7qVv8AXUW8EaucsYXgO/8AmL7b3FnGq/2rGJHI/kF6Bj2nbktQ6eab7tQb%20lTuPfT8hd+uMfUj/AN55M9vH/p6Bs+QPoNu5q5XiCL5oCEFN3/Etz9veLgS1fvx7suw3/NXv+jj/%20ANI27/bz8uHP3uiyHn8ZMpG4X+JET3D9tUuNxG673mb/AJS5/wBHHP8AurHvk4x88fQvp/0jy+Dh%208LG9jJ4TNL5hLjuB2g3v8NdXoW1y7W3G36wT63byejXLtttvXJtlUptb8M9TmRAKeEKB4Sm3+X1V%206jzPAVD3N6Lt6B4QhWpx+MRoq+W09a8q/wDczqT+0Yu2TwPDWhUI8W3sKghF7KZmJa0hjdtlIazq%20AC7qVKk9yUDkWzaSAyzW3Z2gIrGgjpbSlIMNHbCU2kBC4ahyaddFXS1MAOMoJ2ILkIVRAFX7VW9C%20Cgm6C5LU0JDd3VTbVe2gExbPMDgHBA2yBHEhCC7qnZQFByGRwe16IQ4OACKvXtJs5aICKnHfXXy6%205T1j6bgPDxRyZWHn5Ln405LHTNc4X8zuAT7qINbLoOS5/wAi/mcJpHQ+niGB25rIphK1rD0BNyna%20aqQ3t9zK8R6flyc+LDmb5UrJi2WwDmuZfaECL9PYNjdTqfqjjp830XysRY6LyGNlicCHeZ5VkICC%20pVsEzU4pEMkt/LdIQE3BpP1EdK0hGjvY7Dm8jEvkZc7CUDtr3Af4TY91G1D3sfxuR5906YuXlPn0%20DY3Pc5CENh20bV1B8kGp4nF+bU8e/j48rIAV5Y5HPDTY2d4rl1DtSE+fro8Y9xIPqT5oYm79Xilz%20tHF8Q0BQ7i1E6a1L40P/ACEnjHU1HoPK+avqnLa/hOMiibE5rZOUeHxxM22u8qDZSgqLrEhvkTR6%20G4zL9WcVh4sfqB0Ga1zmwPz8co7c9PiYT4tL0tTGEN/MZkjeDxQTu28nibidLyDp+2nJKNS9x3Fo%200CWBA79EoSJYRUghPE5d2tz1+rrQiWghE7r3EEdoCpRuCBxg2kKNyey/s6X/AGjtqWxq0U0AoVBA%20Pie1E1aD7LE/fSbKSQrsQBt+0L8QsAe/aAv2aUjSAKAiIEAQDolgiLa+i6H6wYCBtUDRENrGyd3U%20fZQS6CfM6jTVe5D1QG2z2+2nBO4BLjbsNyioVOgH2ez6yA3CmkErYXBAClB4VRPpp3UilcGAXaKq%20AdShJF+zrp2UFBF20K47OwuNh2ap9v76BFbnepPT+GD+p5CCN2u0vBNwdO3T6qMmUrW8jOcj84PR%20eGCI5ZsiRg3ObFGSQ1SNy9q/TWkq5Gi4LmZnlfnsxrP+ncWGNKhjsh4AO02QNHYnu91NSw/x5Uuh%20ms35z+qskP8ALyMfEbcAwgu0CW3qvRV+paqH7Q8rjt1l4x49UZPkPW/MZhIz+WyZVb4hHIWNJAQp%20sQdCL1Wx1jHjjxKt5OK2qq9Jx8SJw+fv9QYBMb5XvyYA2RxL3EB7dwCknREt9d6flwo7Y8en0ki7%201Vkwln7664/M9hVkZgoAFAGb5RyZ2QFIsjgNA0geI66/QVSIuZDf43OPwueSdqX+K7V7etMlsWxw%20MhKgbiCDcKFUkEqVFvtoCKEf0Api5opb+4SothpdCewBNT7unLwa+J7H8l/R/wCHbjEe3M1ZS41+%20iVueYKLXhFsmhPQ0oAR7kICpcH7CvU9fvpgZf5jBeFxA0K79fj7QO46bfEov1FYc+S8T0/4p/wDU%20u/3LvkWWRLvkfrtUKCul9SVXxIldOh5IhsoXcCoKua4lWpqoATt++/YxIcOUFuiAXItqFFtffTiA%20XYJ0pJKgIihrh10Q9et/bTBiWyIANxJItuUX0uUHdRAm5HWPWyLray9ndrSaGmPtftIcoG0a3RKk%20pMJ8zS9HG5VFvrYak+xaIFIk5UbRqAPxDomoGt+6jayp6EXI5XDxmtkmlYxu4hpcinoABclTQE9D%20iPNesZvRfr3lpuHAn4/m2tldESNjJRYyMHUki61lc4Zvx8e62pmvUnOSc9yWRyHIZ4kmY0RuZCCI%202McNB0GlZbnnqWrCryc7FxMcCCUYwc0bnoTIUtZL7iHHrQlLDJVID8+Nknk4UDpiQHuyJlBRBoLI%20idD+2rjqDbxjxI3H4GI/MhZymQyE5nij8yweF6a9lU5zQndBofUPDPfiY+NCwhj3bmBrC7cQmnXT%20r99Tx3wK9J9wcEzCw9/H4uOByL49r/NZu1BBFwWntIpu+6Zfhj3E7LUszPv9Hc5JGRBlR5cYe4lw%20YW7FUlrUCprW3ndiHx9SBnelcjjeTjM84a1zQ+UjwncHKAB2JoRQ+eg/KZcYXqmTCjmwYc5446du%202fFLA4OJF3B5PhJTWsne2WrEV8vIwRAeWJP073DY6QEEdgUW7qx2G6vSxoTuP5XGhc50eQ+Fz7Et%20O0J/Se3olOGLcmoJM0sGa57nTPlka8bGuP4XBOp7k91aysytyUY/X8xuQ/p2hskfluTcO1BcnuRL%20JV2Wp1M+X1e2ioskMjJcB+ULFSWuR1k7gAi/TStElk8Y/HQ5b/5CuM/xr7fEjyTZrp9oLhEPiVPC%20pICdbJVJJaY/Q5n6q67LGM6/iLMEib32YoL3uXbucvxE2cD2fdWPqH9jSx8vbkdv8RzbvV8S/wBr%208MZ+B7N4vc3i8EOG17caG2hXyxZE7e7s10qbHNqYc377vFkX1J6m4P0zxUnKcvkjFw4gACFc51vh%20jjapdr+H+VT1Mx/hOZwOb4jD5fjnufg50YnxXuaWOLHfD4HAFUH2d9AEy20dWiwHuHf9PetAHnD/%20AHRuX1DxI3FW47kaE/rReuqVp6Nf9f8A4Pqd/N//AJ//AJy/7DOJtaF0UAG3S9endVniTQ9y+jCT%206D4RbH+34wKq3/0mjTWvL5P3PxOm39pFJ8Tt5VocSLBSpNkOp60yQnPRu7cpLQS65VzSi91AQBQq%20tdoh1ABJKolksh7hQxSDeS1QgDQpcWko03Uqgd+6hjgMOkLgSvRFCElT162+GmJhN3M8RIIb8SIV%20tdNLWXp16UCdQ2hoBbuBawXABKg9V1ChLj91ED3C/MYzxE7A0ECQhdoT4r9B3mmJoi8Zgx8dhnFh%20cSA90rnlTukkJNu6gbJsT3CQK51jYAp4R4SACfp30MR5R4zy/wDVGdE0h0h5acBNQryguv8A4r1D%20zU+J6Cjy2nnh4qdMxON4/kjPxeWxz8TkHCCdjXbTsIK7XD4SoJQfVWhwug/6t+TPyV9PcLNyWbFm%20YsDUZHFDO58s0jnHy4omlS4uVBUy0NGGn+R3E8bxmVzHO5h4aN7Q/E4UO8/NR3wNkB0dZTV2y3CE%20+SChwcjjOJi8jiogx/UhPNeHD8S3sq91ddvGc91zJI5mfwSgTNBLh5gLw5A0nxNSy3RvWqfEk4pO%20Magn0Hf7vmSI05UrAw/EHAlwHiNvsvfWjbatJxjFRS8zW+mfXfPemJohKSOPlY2SPEkLXRuYSu9p%20u5rj7L2WsruJPLMe91OvZ/Kwcr6ZxOR44unilmhLWRhXNO7a5qDQNW9ct1pvbdIfzGtwGO5zwn9z%20wlICL+bpeocF26mslCO0UhoVrlAT93YEpohjbQCXIdepGoTaNL0xSONKgD4rFF631OvtNJoBRcAC%20o3NI0JFw4Ht+3vqIK3QBr2HUg+1eqgp10+nioaBXDm/vNwbjtcSqJZFTT79UW7kESEde6aAW7gAL%20H7unVaB7g37STuuD1NylzY97SfoKEDGy47rpuK938dfotUYthBpQEA2AuBoiH7xQKTAes/mPzHCc%20zNxGDxgnfHG2RshD3ktK9Gh7RoNaNTq4uO15uDBcr86vUHnGGXK/TSsI3xxx7XIi+EG/xIEpKxxW%20hW7jXfHsMnyfrfms1fOyc2ZpBYGGRyAXUqgIVP41a4iLvWWLJZY9pDdnctI5zhitG+zmOAJQEjtd%20dUuv3VWy1Y9+MjN/yHR9emtc66e0WcbmJ3HfIQ74S0K7QaWKu+KqVqRhd6xvH45ZYkTH6cyZg575%20XudIN79wJ2ligho7R9dVtjShjf6i/SZ+mPoyVF6XaA5x8abgjl6deq63orqZu+MpxiF7iaz06wAt%20LWhoQqikp+76WppTQzdz/qf64+hZcNwcbOWw37QAMmJ522JG5CFCKENhSaSQWwn7vg8Yqemq5T2A%20UACgDNcpC53IT7UIcgKWSwuRc/TvvadDK7MZ2tuXA3VVCWKB31ddKEhNBiFrpGjVxcSQCD1X6m9v%20WiR7SJ8vwBFzTlG08hKighUCFT1+s+7py8Oviex/JP8A+3/4duMfm9RPEZYJYt7o/NaWeY1N7VG1%20Wn+ptbnmHJuK4LE4P5xcdxfpXLy8hkGFPL6xGRM6eENkA/TOeXbg2Zzt9glqFmOp1ywUG3auuotd%20R/P6wRlvmK1zuFw26g8hjhwve/Z4v/wn9+HqMl4o9P8AinHJd/uXfLHQmvY4SIVDrtCIQC5xJd/F%20a7KHjxUbRx2GyatIBQPud3Xp4U7++hsQbGOQNDW7SEAVQAR8JH9JWiAFI4IVXw2eU1P+LoL/AMzQ%20wTFEgDxIAnivYC3aCtk9tDBCXPLCRIQ0oSY1S1wdUX2CgehnfUfzB9PcBE8TzHIzWjw4kKulcOhO%20iL9NKl3QWrZRUj5iZ3I4sc3G8cYWSN3edkuRu4AhWAXdVJMm6Eyv5T1TkRYZl5LLEUT9zTiAoHdH%20NaDfuF6e0W5vxOd+ofmBmZmS2CHaQLwgu3ODQfi1t3VPImlQviq6mN5f1ThGF7J5BNMHb2OBO9rj%20r4ra63rmXDc2de+1KEZ9nqLGa7aWPLLDe1BuFlKdF9laLhemYnyljiNj5OKSbGc7zYwGxFx3Fpcq%20hqgUq2sVGnGY5nclLxUONiygpKwbnFxUo5NpJ6dt+lFtu6RXOCn5Dlos7K/WT+V5yGJsbg57WAaC%20MAj61rZWGe4mY/PP8pomz5Gta0P2tcQFNyl1+2pdklbniAsvl8WVwXOeyRqHzGu6Kt+i9O+i2xoT%20uY5i+oMfGe17MyVz2I5rCpCrYWRqdydaT4mNXNaic71Ri588uRlPdNO++8A2UA7W9LdKFxPQW6Uk%20wM9R8UPKhbh+UyL4ZW3c1Ou0qD23q1ZqJ3PqWeX8wsd2N+mMf6uBxBMD2NAQKiIhH10eX8MY1Erp%20ZnP1eFkSu8oeRI5VG5RfQNJuL9KzfG0bK5DmPyE2FIA9dzCBdVLLE9q0bZEnBsOL5Hjs+PI/UZBE%20kRYIHOafFG8bUsmntqbbtumOhjz8O9ewuMfi8WUsbGfOa9qoxWgf1Lr8JHZV2ck9cUOXk4Ha5bJE%20PDscWtjaXuIREcrj7+qC3uFbUSlnHffE1ose3TFBWVhAYr3ucAGeJzwdpb1JJIOjm++s/VP/AKd3%20hih6f8K49Zxpf3rv8PbTrB6h4suPFYZdYnGhLlQC7ASE+g+45WJwpzN+al78WRvU2AM7geQhbjty%20p3Y84xoy1j3b3x22qQA69kP76ozKz5ZcbyHGfL30/wAdyMLsbOxsRkeTjyIXMeSiOS1ASaa5Q/iW%20y9Tb9qe+gDzh/uiH/X+JO0bXYzgHLq3dpt7Ao6fXWno0/P8A+H6nfzP/APQ/85f9lnFWhGuPUAkp%20Xq6nhzQ9xejA3/QXCjVn9ux9Lq3ym9gHSvJv/c/E6rf2kJXBxUq567kHaD4gTqT2BKcEOAmyEAOB%20VUKHQbB2A9SftoCAibbOzwtUog1AvZep76A+You3G5c1znK1y3UIAfEmifbQABIFc8dA4jql1uLr%202d1ACt+1ykg7PE0E6/ChAC3vY0wzDXY0KfDGBuJCIp7iVHaDRoKRRXc0C5Liim6Os4A20+2gIoE1%20xIDhdUDXXF0KWICLoQDTBjkbmiUEqFIFypJDdLKT9lIGjyZj578T1jyL9rrcnMAQGuAc5yd5U6da%20SzR2W3Rb3j547fQ6nx8rcTLbOZdkEMofI56BvhJF3FbJ9FtVs5WkQf8AUHN/MH16ZvT7WeXgeHis%20qZu/HwoidsnIOapDpnk/lCpkGoMr83D6c4D1BDweNLPlZrIxLynITvdLkzzSK/c8ggBHAEAJ1ro4%20nGZm1ORiv1THR+ewh8by5xRSPF/V2kbkPdXSs8YgiNB9vJ5TMKTC83diTPEs+O5LuYEDnOu63Zof%20dSgExrz2hw2jy3kPaXAoSdUJs7s6/wAbT6MCQckvKRSuEjwBGCShe1yBdxO1U+rWlMeGMUJVtO50%2075VfMyTg8Cfi8yB2S5koMcdow0uKORwUWCkdtc/PZLk0teh1T1nn4eV6YwMjFlZJFJyGEWlrrhZB%20YobEKiVytNmiak2b7vJ10BGlmjs6fTsoQmxUbm2FwCdbEm10Ve2puBIOZ8bGlzpGxgAlS4NC9Tcg%20Jp7kpIcEXDzMfNb5mJJ5sIftErF2bhdGki5C61YiQyMHQqtuouotSbFINjrO3r3oNAFGp7KKALaD%20tG3Qi3Z39PbSGVPNerfS/DNXleUx8VfwvkG4rbQXXt/jSjUeZg+b/wBwfpPFVnFsdnzOB2klrGFX%20KPb7v5puASqc19TfOP1bzL5PKzhxMLUAhxyNyAhVLlvQm5iBu2FXGMVMQ7neXiyZMuDnc45co2yT%20g7nOGgVztx6XArROoslBfekOFnzcU5nIOkycl8riZJgrnbgCEP1m/bV2tHLz3uYNhFwUMTQWjRdt%20gSd4J18Wp07KcPUw3N464xBJHFY7E8sN2saNoa0ojRY/VuT66cYx7BS4xj8Y6ZPjDjat3WAQWFra%203GgK6d1OJG9XjGX4ihiMbchNiEjTS5ACNuQOz30QsfiRGMRUP9KhI2EI0K0dQB0QOP7NaeO+Mag1%20GPyx7wnRNO4IpJDbqEsnRetu/pTiFjGdcVUaeBL4yPdyOM5gB3TRFn9Kr2BSt9BpSjosY/Qu1VXS%20mMe87xXGewCgAUAU+ed2VIDoCCW96ALr3VDFBByIWISCgd4XOaFQO63I/ZV2voQ7WR2PduDbAOcw%20bUIActwQOpA/hVi3LMY+X48HNKNq8jISblWhNv8AJT2Wrl4dfFnr/wAl/wDj/wDDtNLlRzyYc8eP%20L+nyJI3thnADzG8ts8NNjtVb6/fuzzTA+g/l16w9K5I8z1JFn4ks8mVyZOO1uTlSPO/fLNdygEAK%20UAtpRANnRCCCidba/FbQnqb/AENAQZX5i+LhcMW3HkMdBrck6i69bbftrDnyXij0/wCKf/Uu/wBy%2075FzkSMkLw6x1auqAblHUpXQpk8q6tCF5ZapVAAgGo8Ngbdt7e2rTIY5uRdquIW/UgaXPb076MwS%20I2fznH4R/PmG4lGxtvJc9ALppSgcGc5H123GhM8cQYxztsTyHbnFxTa1jVJJ0FvfT2sUoyPLZ/qL%20lmNlErsZsZcWtKbyST4l/D2pTdkiXJoUWHHxGHkBjpRyPJuDv1Bd+YRvVQfibusVLr0KxZDd0krP%205XF4WBsGNE1kYafKhuWtNkDiqNF9AlaJTnqRFDlXrH1Tk5eWY3v81wRHuuASNGNsBbolUoxjGRUG%20NyspzHq9xdK5Q6Qk7kCgrdfrpOuZSZDknLxYIAB4ibkJotKBzIldEKBNe63bTaFJcenfPbJLLHvc%20qNMbSrXL2nVRrWPIlBpxlzz2ZlwuEuTixZ/GtDWPaQBLEugJCkL21nxqcqGvI/aZXPnwZpmuwsU4%20sYb4mlxed3Uqb1vbb1MLo9hFC6XH9V7LVu1EvuDQX01AAKqut6IBOQ1bcjTXttSAG51huK9D/LtS%20iJAAcV631C9ye+iAkSCQQq36+ymEhoLe+/s/lS2jks8TlS3H8rJj89jHDa9xu0e/21lfx1mYNVf1%20Lfj84xu8+FvxtHgc0P3NW9qyipdzcSjpnpscRPhOkwn+WZSd0chJLQgFlRzAK6LF0PL9Tfc5lwvk%20Xj4vNLWPiIa5Q9gIKD8F9RZUFNI5U2nMkbN2yxfp43ATzNLoYDIWSFxGoJT4fsSsue77Xan97xjx%20PU/ibHZy2811r8qy5b7oojo+H84ZIcPHx3enp3ujjZGSMiENswNXalgU6aX9/Lb5lqS2One35yet%20yWeidzf+Rb/o5P8AlHf+85S/pvI7x+oh1VEJ9hJXT31W7l/sfvX4keX6J/8A8m3/AEcn/KNZnz0h%20wseTKyfT+S2GIF0jv1ETrBEsi3UIPuprzW4Vj99v4h5Xo9PUW/6OT/lKUf7ofTQb/wDo2VbskZ0B%20A/D7K08vl/sfw/Et+n9J/wD2Lf8ARyfhj3xyv5vfMTjvW/KYedhYsmIMeIxPZK7cXK5dwQAD6d9d%20HouDkXK7rrdqiPj2F67m4bfSrh4+TzH5m6ltyhQ1/UkYRQGvU6D6/dXpJVPCZ7V4NHfK7A3T/pQe%20JiXJ08s+QPH7ta8jk/c/E6raI4tjerfWWFnnCZzEWa2KZsWPkDY5kjXDwkKLnt7DUS1mTOpvM35i%20+n+NjjHJzCPJcpeyL8xCLgnX8S66rVbhUI+J82fReVkvYch+PEGl/mTAhrkchaPb3opShciYQaPi%20+c4flWPdgZkWU2Pb5/luUIQCE9o19lUnIET1D6qxOHOyeOWWZ4Vr4mb2gEADeBu6UrroGloZvK+Z%20WVCx8sbIiXANjAILQ9wJ/NX4HW26pU7tOgi34b13jS8cMrlY24UzHOZt3AukIA+Fti7cOymrwgf5%20v1ezF9Ps5fimjM86QRMDjc9xXcim5rL1HOuO2Wa8PEr7o0OJ+s/nP64xvU738Xk/pGOiaw4haHt3%20BSHI7dc/sqvT8jvUs25OC22hGwvnp8xnYmTnTchjCfGA8kuiAjKgh24Dr0FXdc00R5dsCsfBwH8b%20/ed3mZ3JSDJncUTzHHcdmigGvN9R6m63LGO528fFNHOMVDzMjOzMPIxp5nuxZ/8AOARq6A+IAaqK%205v8APvVJLXpbR3gua5r0xiS43p+ZuKyZ2+ZoY1xe4BArj0S3ZVW+vvE/R2swvrfP5Xk/UmRy2YRL%20kZm18hARCAWbdvcAK93gm+xM8vlStbt6FFi5UkEo+IMKh4aNVCKSlb2XNE3JMtP1HhHVwW57xeuj%20ckY7QOmdoCAET6r9KbuBWkhrt7At95UC4AKfsFKYCCdx+VN5jfMmLoIgjGEE2X8Ka/spblkswh5s%20v+P5/Ix52PaXB7ZGTNau5rjEhuG+GzlqbrVGMY0C1Qzuno/5mT8myd/N4X6KNkYkjyWtc2N5Au3x%20ANXsSvK4ed3XNRkdfJw7UmnmYL13/uVGDyZ4/wBOQNyfL8E079Nx6tOhT6Xrodr0M7EjnOX84eYm%205WWXkXyZ8aBjmOeREbEEeWNrTbtrPyncbqFkOR/PH1VjSh2EJI8EBolii8IIFzb8JWn5TiJqS2jp%20Hy8/3G43KcljcTzjjhOneGMzHACMhwQNkIFr9ara1mQ0tDpHqTm/mdHJOPT3BYk2Kwb2chPkM2vY%20iktC92ppMzg4hL63+b3qzPnwYostz4XbZ8XDHl7WhRvLmo5Nw1oaCUZf1P6e5jh+TbHzuCwZs+15%20e94llK6FSDc/XQkxbpoUONj4z5XzOx3yGIDwQuaUX4rDWw9lVL0ErkzSt9M5EONjvdw0zcfJaHR5%20ChC0L2KouVFRdc+uZSj3DzfTGQxmPnz8LkvimmaI3uKEkHVoNr6X7qnc3qOEszfcJxORg4h/U4r8%20GWVxm/SzoXNEgsXAf8IN66ePtjEnDz/uxj8i78rXcLKqEC5IcBfqrkUp/G1DXTGPcZ/X2Yfjn7xf%20lBVADrgOaVRV6Gy6WP7Kbda0xin1BT01x+Xs0yQY27doUODTuJGqNT4R0U6aUd/0z+hMPGMu3jnQ%20qfUvODhcVuX+mOSXvLWNajEO0uaqA/iHd20Q8fqDWnf6zqsZKqM5/wBwp3xB/wDb4cPGs1zsiYAE%203I2js3Ku61Q7uuO5dnCmsdcR28WNT/MDLY4tkz+Px5HhQGkuaTZWm/cin+cb/bjHQ3/xVjGF2JOH%206tyRlcVkz8tH+lz8qJmOWRktkPmNa4AOBPUX99J8jx8MdB2+mSc+B6srE7gUACgChz8hozpWhxsQ%20CNUst79U/ZUtBJGMrCwBRtKIR3OCp9RpxUGRS8BHfDZHNVdV0VSK0M5/HGNSlwsb1Txk+b/bMrEb%20jZczsgtmj3O8QRylqWGnb77VyrivtbhqG8Y+R7d3qvTcltq5Fdutt20fTx/QnO5D17c/reNJBuPL%20fqttfbTjl7Gafo+nJ77fwKz1D6k+ZXD4ozWjDzsNjicswRFz42W/MDdw3NvfrWXJfy2qaPrjCp3O%2030XpvQ892xu+y7+mWob6ZUJvH816x5DBiz8Lk+Jmw5W7opmxvDSLjqiaIV0q7Lr7lKa+Jz8/D6bi%20vdl9vLbdbmpX4CeSwfVvLfp8PlMzDGGyZk7hBE4SExnQB3/F9NKHx33ZxnjD/MXH6r03FN1iu3bW%20qtRXwNB5yv3HoC/a5bGwHUfb0NdZ4r6DWVyGHgweZmS7Om0n8wqgsF6p2UgpNDJ8z6qmnaY4D+ix%20l1t5rmhFRurfYlWrWQ2jKZXI+N4hacnPLnFrXPuB8Qc8+JGuHQVdtupNPEjT8hj4xdlZMvnSuuWg%20A7bojGqgA6lac69BbJKHI5TkeRnbCybyIAPGGLuKj4lGn1++luzLViBBPBxeMYuKxgGndJM+dd9w%20pdIT4lTSpboUlUxnqjMz5JAMSZYyA6aV6Xcvwgkrusf40WX0KutazOfZ8znyOZu3Ifidqt7XrRti%20gjlr3blJcTZXa6aE0JoQkxFAo17+3v8AfVSmG1hBpQqdO02oBKps/ReJ+RiscwPflyGVdSjCA0EI%20qKFFcvNdU34aFPzXLZOP6k5J0bxJG95hkjeN8bmgIAi6jtq+O2UjO51KKyFPp2dPZWpmE5VJcLC4%20PUVQII6dgITVOqd3ZQCYYJcbdoBXqnxadlKASCU2U63TroF9tAVgAQp4eoCdB9DQHtBtG0IT2kdq%200B4gHagUqAehAtQOR+OZ7Iztv0ANwnX3GoY1CLvBkdFxks0BTIYxQ4lAAAvh92lYXKbq5G6dO+Mf%20oSfTfq7Lw+SgMf5URO3YCu9ziAjjbVK12xU577N1DrUfNz5wZDx0KZCA5E5vHET8Td2jzew+6uW7%201L5Pt4off+lfn8Dv4f4Xj4LPO9a3bZ/TYv335/6V4+wmcfwuPiFz3OM+XIFlyZB43Kml1aLCy1vx%20cCs+51v1fzzyx1OH+R/mOT1K2Wry+C39vHbktJf9z8esk0RgqCVCj2oCt0t161u6YxjoeTuxjtPb%202CTG0AXUn4STZT2a9lORq7GMe8oPWzms9P5A8I3kNaD1Q3CqqgVrxKWirXU5WQPw6aA6fTWuw6BA%20CEf1JYHW/dRVjHE8Lj0uWg9v20rVUTPYc73RfI4vagLOBBA6WxhbpXjctWzssyPJuNlB4b5LnCQJ%20ZjifGRdOntK/wxeMdSKjs2Q6WRoeTIS4FzhcAAC90uV6a9yUq56iFfr8UPb5UmyTdtDSQdriAU8X%20b2npU9QJ3G8xkYBXAyTDbxOB2OKqoshJ2/bQ7nM4xkHYmZfqvn8qB0eRlyva5u1r1Jftap2HqQEA%2009veO5jTZWzZ7jLKwS7S7x7ioJsLqRuNj9LChvXMSoHJzGbIMfHMh8uEeDxAIF3au6qbnqlOICKE%20r0/ymZORhuduj3K5gXxv/rPxC2nirl9XZutUHX6RtX4/UxnqrKaPUE23xxhwabhSnSypXoeljYjX%20mu+5l1iYvDTcJlyZeM/Fa7Z5xicHqxlg4Nch1va1Vz8e1qtTHj5NyYrB9XDG4iPjXkOZj+DHlAId%205dzuLTZfp21w+o9Kr2dXFekqjU3qyVkpja50g1YfiDY9V+H22RNaxX8cnr+uPoVf6iHRj+Lz2TlR%20l86xMsBtVQCjlFiWjXuqX6KHRm1vI7s6FJy07osw7dskCkBzbHw2Nylex6W7bYl0PK5rVc5Kz9RI%20ZXjbuaQnaQNDqUtXQ+TUx2jzc5yAmEr2uIHYCKb5fcNWEmKR0jgxoaC7aFcTYu0tapfPCxjHtKt4%20ZyL7D4YxyxHkJWte5C2IXC7RYp17qx/yG6KmMYg3fptuk4xjPa+lfT2DmefPyAXEjb5cbWHa8vUA%20X1AWsYd+Q7/+nQ0UHpH0liZn6uPjXNfE8OaHFzo9zAoc0EeILXV5lzUScW1aFJ6+9T8xlY7+PxiY%208uSPd1b7dv8A4e7WsbrkmbW2SuxyWL07klrXOc4Bw/NJaQjibhT+2jzStrHOP4fAy893HCUwSPVk%20IevikWwXv0A+uk+Rq1MFbLzLPD9OZORuhZE6JCXSPJbsf5dvLU99/sqHyCXGzPZ3E8gOQbHHivZI%20/RgCXHt0Wt1empkh2NHXfR3zM9ZcdxnH8e/kdg41xMkZcHExNX8vdYI0dPtrHlvVuRF9rVX2LmP5%20qZXFesOW9Q4mO155WOKLaSAWeX8LdETctN8lEzFXfc8dSq9Z8vj+oM1nJzQmJ0pe55c8uDWKiN7L%20grWC5tye3GKR1Lma48Hh9ikxIOOxclksbWxPZtc17ArCFBAftVQi3PvpXcjuT1xj9AlPTHQ0Tefl%20lhlljWCdsqbAUbI5xAlDEVu0qb9ntSuS77nDeNJWPgLc7vt8I7d3l7uulGwTcxl48LNojyC15dDi%20NXZGGq5rkcdxIs4FALUW3VmWsY65jdziW65fKn01itZNZwvMZfNYEHJZgDcmVQ9hUhW2IVxB6KfZ%20Xs8P7e+MI5OW6rxppT6E9SG7m3cGlF6kO7rWOtbNT44+ZLnLCw/wgDWjaUVoO0FAAhFtB+FAE6Ut%20VOPz+QopEL6U9lNNPCQnDzG7Qvi0cUIUixBHQqSoPvFNNqviJxDaxTtn8/kZb1+UxMN6eDzSXMc4%20hxaikBTfdp9dJLQjkairmvsz18Pg+iOY+ssKF8fDtAIHkPLkJUqR3m1uyovcZHZ6VNqZKWXjuHOS%200R472QjaJfGpJA8TdK51dSh1pQbd+Jxz5/l7hTRuZgh3nFzSdwd5zQCtvxAdPfVu6LRpSz2ZWZYK%20ABQBmOWeW8hkbtxarSLpfaETXvppE3MhnYHIinRxCXb07ieymkRMg3m5JXYtwUJGh++iByBuqoFs%20hIJCaGyXBcbUyQw0qAb6XuFaPEW9PotA2xbHTAtdfe0OVVBUqbg69vZ29aIBXRjH4mSzuD5Dgcx/%20Mel2tkhlJdynBEhkc34XyY40a9Ontrku4ruN7uP/AE9fe6fU+i4fXcXqrFw+qcXL9vJm12u62l1w%20/qfieX492bhzOcATFPBKNksUjSRskYqh+vi6/VW/DzLkt3I8r13oOX01+zkWdU1lcuqZE5b1dBgw%20lojD5wCsYcm0izQ69jfrWqUnC37zET+oOX5DN82Qs/TlyCR4Jc4FFDWj4et6tIWnYiZfIGScR47g%20/KYHLOgIhBcniUuRwQIDVK2EKSG7KixgWRPE0jipawFrpJC1DJI431v2DpSmpfcaytz4ZGzv8ySR%20BI2PsJNlOgavbRAbsY+ZUSnjeMiHhcZHDcyIq4gjR5KovZRAk20VmDnvynZU2T42gmIAODi6Q3cT%20Yfurn5mzo47KmK9R8zHNmGCH8yCFro2AE+ElNxCdfoKviUKtBX1Zn5AXuLlu5y9l+laNwTECmgpb%20tVNei/VUt1xjHuA9hI8VtvU/S5onGMfIIDLPCQFXQADu7dfp3UbhwWGRzU4a2PDBx2tx2wBw+IEE%20lxb1RxNSrVqVJSvj3guerpCpcbklb6n663TMnUbcCCqr3/fTJaEghwCInTQ2NAgKoCfvoGE43QlC%20o6H7aAQbWnargg0/h9lDFEBuvZEC3H360DC+K6IShVKQJhAlXNKBO0di/spgKJUdtvvtSY4Lfj3u%20kmlxIRu87HLCQAge0KVPebVz83JbYtzeWPednpPS3+ovXHxrdc/hjvoMiTG460W3JzR4XSH/ACoy%20LEN/qdrXPtv5qv7bPiz19/p/46lscvqF/V/RZ4f3Pvpoav0J6vmw5/z5HSBrlnjSxjcUVG7dErpS%20VkJUWMfM8D1Tv9Q3fyPdyPXGnhodkhkilx48iJ++OVm5jwQAQ7vTsP0uK3TxjHsZ41yjPGMRkKLA%20oI6Os5UCj+VNfHGMIetcdcT+ATmgFNUS+ulLGP1Jrjwx8UZX5hvEfBtYCjnygISNADcagkVvwfuN%20LHXtjGIOYEqxfs7Prrsg3lyDR1k116dlJjzB+F5uCWoCCB7vsWmDbPY0ji35JE6f9CAUX/8Apkrx%20OZfczstVDyazIhYXR7Wtd4QHFNVUDdZpBcev7K5XLRFCUyUGPxMBfYSJduwgANKAo4e0/XUPdOMV%20wxewNsELCyQvZFuaHPjc1wLDooVCoXRe/spy5cjihFbiYEmU4+aWR7Q1p2gEgKQb28P2mmnQNorz%208XExyPPeGMRGoQULSEC2HxJ7b0834igTJNvcYxGyPHB+J1nBR4doOqoPZQlOoKrL7GzeKGA3zWY/%206gA7GyACQqFu0dHa61pYpVcfM7eLjTVemMfIhScrhwSkwyQ45B0agsl2hSddFND4lcqo3Vtlrzr2%20qVk2Lx+URkmJkk1gS1qOcQ5AbLr0J+utVKoivKTcvX6/SlH7HIiZsn6DOiDUjjiG1h0JCkoUBN3a%201nzXzE6/j8yXwK1UpjGKmc66ElOnZdQD9tBzkyTmTh8fHDGBJI86bQS3oim/SnakwucOepP51z8G%20THhMhjf+lbLksZq55FgP/NrRapNLnCoR58MP4vEm2kOFmgnprYWX6LVp6aGbt3VITMQvN1VpVwT4%20if5095K45JkfCZDgQDuCXc5ACdSSvupPkxj6l+U2PYuE2PPhieAZGq5xIuXBEaU+K5B7qzuvbRvx%202JXKcVNDkYn6YCHKY05TSS8gAlyFAdTpYftrJ3arI6mpqzoHpHN4vjOHibkyRtneS+TcFKEjap+1%20UrqsmKnk87m6mmPyJnM+uuLjxmx47/Mc51nhiBAhVCRWiuMXbJz3+65PIDNmcB5uPkGRu8B35Eh2%20kBvaCn7q5eS5SdFicGfzZsaTPeJJ5H70D2B5BeW//wBsEad9QrqSa7ZxjCLTi8bAfLBM3HvEVgPx%20Palld1VRrRdc9TTjsTUl62PFDXz5EEj4H+GcsJBQ+Iue3VLKUrNXRSTV2QVmVmTTh8Mk643mBsU8%20KOlMKop6rrV2te0wdi0KvE4zmW5u/EZFNAH7RLZr3A/1MWy9at3pquZndZoWuRF5rg2YfpcyBrvL%20O78t6ruDRf7f5xc20loc9/p7G3/tfHxIUOx58hj0Yxu50IaHXIHiXXXp/Kl4mbpUhTzzYsb5i8ub%20JdpJBUlEOhKKNDot6rPxxjuQ2SH8iyGIBm5oI8cryr2aEDqNPqPW1p8uXX8sfP2j3Q5eMe4mPyJn%20OcQ5wMuku7cH+LdtKDTrb76yXGlnjTXHsItpHb4HT/RjpX+mcV0pJcQUkc3aXbSQD2Kor1OBbbev%20hjDOblo29F88/wBIepelA1r1JIJRfh8BKBCDp/i0rbNxGOpDXTN9vZ7csUA4ICh8JO4BwJuSUaXJ%20a/7uyi11xkG5aPPLHt+QlyHcChN1HduQqqjSm7ms8sY+VQShvVe+aL86JVMl67LT+hLnNbse5xaC%20jiS3YC0tK/8AhA76cQ4xjDMuWcpdZxlGWXX2nN/XYc3I4uD8LMUbWKjir0JQ3sb3H3VjyZ1O/wBN%20+2Uox7TLYu9khLSu8uJF9rm/vulZOp1Sbv1AxsfIfL6EOG6JuO9zf/iZDen8KbdBI9pVmWCgAUAZ%20DkczHl5bNZA4OlxnNbMyxIcWg3U6Brlppoi4bcGbiDru8TirSnf9L0yZgAJRztCocSoKFQF66fXT%20Yo6h/q4Y0BO4gk7QUtu0HYmv2UmiupFk5JgBau4nw/0kDvbpTEyOeQc4bkchCPFttu091EidcyHN%20yUpChjSQCQiqCLqCndVJDmDF+qXuxuTPI8ZI6Hly0nLLfgla3RsrNFufEiiubl9NdO+xxd8Gez6P%20+V4/L8j1K38Gj/qsfW3t8CkwuddnmTePLy2nbPFIFc3Qn/iBRF7K24Oe29NZXLNHH/Jfxd3prk53%208V9bL1lcvo+qE5eY6OVuJjkuy3hzSH/CxmhJTsrqZ5ls5rMVHH5aQAEwWkdILPe9Nri72dKTr4jV%203uIhDWzy+WXGSUnzHArtam4NaL9BUsaumCLl5seLHJKXeZ4gIoz1cLbQLAIulPxEsY6foZTkM3On%20zPJDRvnsZXFXPJ6BgJRjftrN0xj4G0zQd9QTQcTxsrYyX5JYI4nktH5jrvcjdK5J3XHX+23xOfFt%20xuUusSSt3HvrpkxE7C6wTcNBroDe1OYEANDQAAE0F1KO0pTQaFi5J0QE2XWlUEGivAIILgSO391K%20YAS5CPC47QNdAh6e+nIoEID1SykIO1E9tOQEOY1Du63AB7dUSrlksjPjI9i2XRKsTQTSoIN+q6L9%20AaCRVh0B7HH6a0SE1EuJKWUnpohoGFYCwTs92iCgQDZQF2rb2UMGGEJRUA7P50SEkzEwHyR/qp3C%20DEbd0jiVcBqGNTxHpXLzeqVr22rdf0/E9f0P8Rdy2edyvy+D+569rVq/hQPI5LdAcfCa7HxdXEp5%20j+9xFRx+ml7+R7rvh7Df1X8varPJ9MvL4df7r+9z+kkRoDdBrZO2/wCw12QeG+jLPjc10E0HlRje%200gOkcACjiQWrp8NK6GOdToHon1fDxc0mLnTFnHyhxjhDS8xPLl/CN3tpW98Yk5ufjnI6Xj52Fmxu%20kxcls7AXDc1C4fEUKlV7e/3LaXVdMU/U4rrWse3H5KX3iTc0XLgS0WNi4kE3F1Hb/JJrGMeIRXHV%204+JiPmbKBgYsTiRFK5QqkORttEKDsv7+nX6ZVxj2l8c4x1k509pBLirnBCSSp1Isfxaa11JybQE+%20z/C5dyo49gsCSFbfolDQZIK/lITr01VP2Ug1PY+1rvkk0OcQ13AtIcCAb4oIKqPvrxOZVZ2W/tPK%20DocXaocZtgDTMCWrcJ4U1QJ9tcUtD2ipMvionNkl3M3At8wFzwXXHi0IXvH1Cmk8Y+pIsS8ZlO2M%20D2uc4h1yhcvxAkITdNO0a0tsaeAR0Fni9gIyHtYwADegCE7WoALns/nQ7g2aCv7CyXK86TL8gNYX%20RPDQ8B4GoAubjp7QK0tbx+GPEasWpWjjeQ3MjyXtkcw7od35bl0Xr4iPd+ypS0gcOCVl8TyboI5J%20YYpfLBax8Z3u2lAjnDTpartvSNUmZ3meCeY2TF7IG3Dg5+pKu8LR4r3rS24RI4OUNwvLc4l2O8iG%20Ut/qFtoI3dfhqblU7/S3faXDm7sLktylzYHBSBtDV3eFLkiublcZY9ptypQzKNALQE9/bWrzPOFm%20CHJyOPg1eZGtd2AB25L2si1draTBw2W3qV82X6gyzE1800Zija2MO7mgW0t3UWwi+SZgthjy4+NH%20jzC4Yd7SAu4aghe/6dM73qb8NiiuPhI0fIjIBY0WRyNUkEA2+xfZU50NFCzwswCfHau2VrEIKuKE%209gXVRbvpSxtaRT8RGVGHSsc5gE7HB0N0YQFs1xKAnsonoNLUmxPMxMkhJLvxPXcpCAFbFP59KVqR%20ly8g8cuEBwaA9LILusrkXQLWu+hxu1SJnzvOY0NFy5bA6gX0XSnMk7SqZ+rxPVEMLJQ2KdhJcxOp%20sV/p3N76htO2oXt20RY8xgynFn5WDxmEEZsJ1MilHBouF1XqtY2XVh54x7CbeREr0rPFLgMe1yyP%20CrYKUQogC/dWl9p6HHcoTL4skkEcZAfC9WuY47VaFtu11P0NRt6l7zN8lyvE8S6SDDxf0z5VG3eX%20F70Tw9gt1o2XOJOW96Dnp2ON+JNLIYQyNr0MpUglfFqoQ9orS5w0O10H54MkNijzmMjaWB0cgJLC%203o5pC9e2l5juULQ57uFK5tvMZbhYu9WEOe60kh8TVAUlovu3a/S+aujGPYQ0IkZivjcxg8uR4LAH%20EptAQOV2o938LqvhjH6y0Mxw4X+Q5/lBwLXSFPFtI2ntuez9lG9vQmEPR4eHA/yY53SMYAXtkV7X%20NaQoBKeJouhsvWsbr7nbj34ykKxKWOuKnTfTnI4WNxPE4Mk4/W5sMpgjTwo0l7TuGm7brr316PHf%20FmOhz+U7riJ6E9ZQeoubdjZ6skAc6LGjCNc9pJ8RAJ2o3t/ZV38jhFW8EXVzJXI+pM6T1PLicbjs%20ljb/AMrJA542MexrtzjtDjtNvZSsf21yI5behY8Zy8ObM3ClaYOUCl2GVJbG0NcHEhdtjbdVrlx+%20X4GfkuKZ/D5+FKfMpfWxkL8QKmoLSEaRuKqW+zsTol62UHJypNKF9HOeJjxTM/zHy9n9SjCyo+Tx%20sPyYBj+Xkna5VRQ3S4rG49D07+2aFfB8kOcc/dHzGFM1LkOLyh/4Sq1nB0JmmzvlXy/Jcv6cmjzc%20eNnEMxopmvN3PikDyWr/AFaaVT+AKT1FWRoCgAUAcumwJeO9d8/yMk4fBnmMtx1I27YmMJN9fDU2%20WNXN9Q5LpSRLk5KZzBtaGADXVV63XsrUyGTM9wG9XOVCL23Fe/6qBdxl86DbGxA6wKW709tA4kY3%20OVhkcXDq0XAchQL++qgRHmymgqACSHDcTcBegFkSrgUsrs3NMDSW2kIcWs/DaznKFRFRUoFBnMhd%20xduBLiTqq3BuL6NT21aJ7lTy+Mx7WZMcn6fMb4ceVhG8r+FOt/Ehrm5+BXvcntvWv0+ntPV/j/5J%208Fr4r15nBdna+vW3o/D2jXGZEjZsiHJYYORlAMm5C2RhPh8oqqAfxpcXqNz23rbf8+6NP5L+MXHY%20ubge/wBPdl1t/wBm/o++vYPLyZ97WwvZta9HRlS47m9XDsXuvXUu/Q8XGMe8EQ3BzASCG+NFJc0E%20q8k/Xrp0pSOJzKHNlx5cvImlemLiR7w74Q5OiXWzVolmiUlR6cijmzZeWmcS5HHBDrHd26+FoS2v%203Vzc/Jojp4bdSh9S50mdnO8RkEDneIalzzqL+6p41BV7rQqi3bdVW1ghumt+2tDIKJTIAhA6KERb%20oehC9tLIeQt0JABXU6hFIsQQDRIB48ZLwhQi669FH76m5wNLRD8mO3/M2gG5sLEOJKC4Oo6VCumg%209sEJwa1xJIJUaaIbWSydlaJtk0AGgkXAOi3Ouh99OYzCJG3MUWARLAdp7FUr2pVJqgu43JGAStgU%20uAhQadxvTV1CYGZIyFcgQW7LVpmTtEAi4J9ml+yiQQSCyDS6W6FKBRASm9/5UA0Ka1z3BrG7nOs1%20Lk/ZSbSUsqzjd1yttTbehPdj4vHgOzAJsmxZiNIIYvWQ/sFcT5buallLf7uvgfQr0XF6GLvURyc0%20U41kv9//AJURMnLycuXzJ3bnCzWizGgf0jSunh4LeNQjyvX/AMhy+qv3cjnotEuy0GRtBA9lj9fZ%20WpxIUS7QdidNKBp6hteW3BIB1C1MBDJ+PnuQq0ncQrl8RQ2v2dtA/Es+M5eRmQCyV0EpIBc1yFdS%20RpfspNtZCfGmdK4n1pycbd+QmTG8/ELSbGtDvChQlW/TSmrqQ8YlnNyelTyIPrXPbzLMN2K5yxtJ%20mhCtQvG4WFvwoAmtdvp7kp7mS4nbRZYxiDITRPjlLHsc0r4lG3d4jrdE6eGutNPLIp49ncjPcBuF%209PEQDqmnTsogIlCnBI0Fgh2grrYaexPqpeIOrPaHGYjMv5SYeLKrmTcPExyAqQ6ACwF68L1D/d7T%20u4k6HCYvlvwcYZ5D3tQeEtJ0A8J63215vmPqdb4lkK/7c8WI2tY52xCQBtcPEVPTVTS3vQHxJht+%20XWJsZtlaxzdPDtS3t19po3MnyUshmb5dB7Xj9Vtvua69nKqqv7KFc9Q8lQQj8q8pgeIOTcwG6X1B%20Lgg0Fzfvq95P+ONy/LrkMaKWV/ICaJrd5kkQbWtCo1QdE6i9X5kh5MIzg45uLC3JwZS3cC4yxEOa%20dSdyr2pXSmSyJlxSZA83KjgibHuE2a43LR0aB1H12oUKgaVKXDy4HZckeKHMaWFwyJDtuLoiOt7e%20zpWl1uTZt6a6HBovT/EcjzEmZBh47nRPg2Nc8JEy3hc83T29lc3Na3CTk6+XkUOWPY/y94zHYP1u%20aciVqr5HhY4AaBRf9taq1nClPsx+RrOM9KemYvSGTyOPx0cuZBlsjE0hMhjalwbj/wAwptJZFW1u%207Y0ILg1s0j4WBj5DulkDdpc46u3G/WuZXU6HdsWpCkx9zi4DaXbRq5R4UK/zShXuaYx+horSNJis%20aQgaWorUu26OuncfspzOYQogfjwsZzQyRocT4oy4KQBfxAEHt+qiWxND3HfL/J5SQw4T4sdgDnvd%20P/ktaSpe4o5HILd31Vdj3OiMeW/YjOQ8FyGTy444ZcMbZpjBHmqsZeQQCUFlNq0t49Dkd01jEk/I%209F8xi5kmHl5kMGTA4MkAJQhChXv1HupOEx28bamKE+P0Vlywny+Qglc8gbCCwN2g2Bt3/fWc6lPi%20Y3m+lsvi4X5pjMz2SRthDb+FxVyELa3UVhdc24Mna0U3qyd+BvjiMvn5DdwjiaSx8RCFrk0ASteN%20SzO6zbcSvRWOw4nmFjo44yQA5pa7cfwkITofd9laXM6uN6Y0Njvikb+YNoHiVzSURDp2tKaVkzbZ%20oZT1ZwsWXnxStIx8olS9CW7wE3Ent6iqtv2mT45cjHE4GFiZofLlw4Ec3/zMmSr2OU6bRqNKL/uM%20nbC7mg5F3piXjZMPBkyM6JwL4JIwRHGb7jGvi2p0rNKKi2SoZQT8TO0smwMnz2Tta8YrmODgfxOV%20CF91aK/Qy8uGR/OmxjH5uPLKHEOjEbVVb9nhunuptJmbtcQWMUDJ2tLofAV3Rlm7Y6ylPZ261DT1%20xjDDYS8SKF7lfF5cgIETkRtiEa3R3U9Kl+JaRIPqPGyY2YrmOi/TnyoNwRzyzsPhteyd/v3U5nXw%208dsT1I3ET8f6T9RYPOua48fIXR5JQrGX2cUJWxuapXu5QR6jg1J3FczyPA+oc3kMdozoHlzIn7vB%20slc0iQuClw/bWjUqMjzk2rsiu5fkM2X1fkF2XJhTSvL25ESX2gBrWqvh6dOymmtqBNzUnY3rHI9S%204kUs7WwZ+KHMyBG7aA1t2vQqqhoX/i9tdXH2R5/rLbU65eGXxX5x1M1622jnseJT4sRgABLRcnU7%20uorLkbTO309bUVUofi4sr2TyRx7SoZI8XCaX1tXPbczrdtDY+o82QeuPTB8ydoEGABse4A75ApPw%20qSqFau7cK1I9lUgBQAKAObepHxN9RZgeVcXtO1bpsA6nuqlBLTIYnAAKIW3F7r3jrTkjaRcnLYWh%207bhVLWkfaneRSkrbUTE/zG+YVbuBQL0+y/sqpgUSJnmAeWuO1NLgKNev1USFENPn2M8x7Uc0Kyw+%20FetNCbMnm8k/LmL43uigY5Q643bVNum3u7/qvxCJIn6gmZZG7DJ8LrC7lGosOh7fto3CcakcTNys%20x87l/T4asx2lPE9y7n92zpeqyQoiozyePDPEBIwula4Fkrdu6N1ipXQH6u2sebgtvVaPrqdv8d/J%20cnpbm7Iusupda8rl38NH7Csiyjjytx8mPc8ghs7bNeCqK8+EORax4/UO25cfJR6Pr+Z6Xq/47j5u%20N+o9JWxfvs/qs6+NvfMZ5vImwONcyKTZkZB+FzvEGNubO7b1273J4EGJlmzcqb+1YcbnPz5B5wAL%20nBtk0Tr1Ss3dCk0tUmsy8Pj8DjzDAhdixOMuSDdzwEepBTWuF3O5nWlttMHjtMuIycM8ARskrQV3%20ArfS9vZXVdBziY4Hlp0cwIoFyCCt6TYxyJj5HDa0opO43CkBSpt7f21DuQQKOOdik+06Ke3p07an%20cOCMG/nbm2CHcBfqbBLoQgvVt6BA6/eI0Q7WoSVIF9D21mkVu7kOWSNx3NshIcB0B7au1EsJyakA%20Cxa3sHYo+3vqkCEuc0ECxLSSdLJZfr7KX1EkBwRqAhB0RVXuCdapXVkO4Rit4rEXLbkk26+yhXia%20IEnheu3a09ChRb1smRcJUHr2F1MQ/iYWTlvLY9oYxHSSPs1veSetY83qLeNS8zu9D/HcvqrmrKWr%20O50SXiPuzoMQGLjbynwvzXDxHtEYI8I7/wCFc64ruWvJl/b+J6l/8jxejTs9JW958rz/AOBPJd8/%20gVwBVSSXEq55u4ntNdyofPO53NvVigSLad/7qCQza1kuE99AZB9UTr2+6h9xoMFtidepSpUDDa7a%20F6i416aaUqC1JALHkobWDgdEW31GihaLHCzcmFDE9C4+JlwHFpUKO6kNVLjH9RK0NyIwQdquC7iW%20fD8N/hJvrpTknaWUc+JNLC1GZEU4fErruY4jcwhw8dtydlbcfK1STO+yhSzxyhsrHhDGQ16aWKXu%20dXV6Sc1RytJMUWjySpJdt8RA+FoVFI7d1OcYx1CcYx8T2lwLm/8Aa3jy1A1vExIiIA2AJpXg89Gz%20v48kctjcgTctjYK0oPrTVa8dHoNCPOeZCH+A/g8XiKG9rpQSK3OBIOq2BvYjqtrm9MYbWxgBCjh1%20IUfat+2lQAb4y4dQCNyk9TdfcOlUoEReUkb/AGzNaCp8l9+5L6k61SVcY/AV2Rx6KOfjJGyQP2Fx%20DnwO8TXtPcVGulq9CJOduCLkHEyXxeXBIZnEf8qVMcbgt1OvsoiJHM01LXgfTEWZluyMt6YmK8Ca%20Rh2izgkYOimnuSRdlrn7TZ85yLOO9L4+NhRx47eRld5obZYoSCL31qrW4rjHzC+XdE/lWce0yD+S%20le0uUgKN3RwKDVju0WqmghdMfhhGg9B85hw5+VwvIuA47l4xHHIFSOQfCe7pQ1KhEXUczjGJJOdw%20eXx+c7EzGpJCQfNcbOaLNcCoXcK4b006np8fIrlKdSI7ym7QgBQISAL3Ro9g++og2cezGKkKYgO8%20wAuLFJjCAhBcO9hsn76tKBE3icGeedmNAwy5EhDGRhu47SSA5OgTouulKNzyId0VZaeteZx+C4we%20nOMmD8uYeZzOUxwAG0H8kEEI5NVrsssSUSedfyO9y8sdOhz95cxr9oIkYjo1B2EhTuRCfedBWlHj%20TGMhRrj3nTvV+JBlclhci6/6nCikKWIMbdWqbrf31ycyhpM6/RubaYxjoVUOVDG4OcVDWjbI4gWI%20VOiIHE3P7EyutcJOmK/L4HU1TGNP0HmcgISGRE7GNG4Luah7iQDrp2dAiUO6tXj3fEi7inPGPoSI%20eSjleCMeJ7x1LWqRcIPw9mvUpTmk6Tj3mfkrUPIzoEY0Na15aVIabgjbZwCWVevcKLrpTY7eKJXh%207CC5zGb3sKkEqCUCOJRHf8LffTmWLbLpqMOlWdj44vMMLtvlqjlQeEe51S8g2odl9M4GblY+XLCH%20Fjt4heLF4GjgQqGkrs0iXboWMJ5DG5TNnx8FpjmY3y2MYPKjLWKETUdtXyN3JQpOCdrchR5nOf3M%20sixZGBjQsZjBapC+FyKoTT66zdt2PoJc6lEjJyOaeGuZgBsbQTKSzZ4goPiPeOy9J7ulCFzT0a/T%20t+RWyv5qSDezHeJy5SwMAeW6t7FHiHZS23dCVyua/D69BnIl5pjTkfoUixvHKRGA0kXLnFToTbtq%20rFWWnGMYq+O93NJ4WNChz5sbn3pLGcdxasbowhbI0qQ1CiV07tqpj8T1NiapjPHiHkxtiwZ4Myb9%20Z4S3eWgk7RbS37/vluTS21wZj03nepOHklx8VjHca95LWzAHaBfwqtu0Vrffa1TM82709zcrIss7%20mOBk9Q5ufls24z4WNOM4jzIXn/M2JZXdKbV22EY7Um5LHjJuOzJ45+L45+Dw+Njux8Z0qmTJcSHF%20zx1A7ftro4Vdqzz/AF8bdUprGJ93uKr5gysj58SA7vKx4Y3MChXBUXV2povUs6ODIpclr8iN0DmI%20JQE0KhVA17O+ue22GdU0Nh6waGfMT09jK4ugbx0bh0Dg9p6dvWtWkTbMSe0agAUACgDk3q7Mij9T%208g143tDmqL/+2LKF6mrSIllYeQkLVY2xUg9mp60mCkTumMpuX7SC83LFF0UVUMSTHQyeIGZ8gVwK%20xhdSSU6ad1JD1GnF4Dmgqxjt1rIV66EUSEFPz/IwxkQKHRkh8gCBriDZoXsQWNVaxFMfMcDuRq7m%20uc1ACvRF0uRemmLb1xj4jGQ+UYu1g/NyCGxgG4OifVTBOvYXDixQt8uNxEcbdm2/iIa1XfiUqAt6%20eRMTSSHmJIZCUId4tjh4XNsip269nvoTHJEdjxnG8vIjD4y1TGgs5wJJDit0NTyW2327Xlj5HT6T%201XLwci5ON7bliH2ZmORgyJ8lsOVM5mLZjHuO6zbodvXQX7K4bPUXcP231t0u/Hqe/wAnoOP19r5P%20TrbzKt3H172ZeO38hfpN+NNzckuBETx+A0l+Y4eOV/QFxHb3j92nK6HiWJJ5Fvmb+RxeQxoUc8w/%205zjZXElxUntNYJ1NXbQx/F8MyBzsUuMsjgj5GkNCju0tXYrt2RxtQQ8kPwsqWJ427D4CEDHAXNu7%20SlEjgaEjyr40a0i7nIpJ069CetTkOUOMkV7gHElVBNzt9oS6/VWeReY3Ixqm1upGgCBLlTc61SYe%20IJGG/hDnvaXAg6EG49mqUp1F2IssLZHlwBRqoT0GunuWnvgbtG5fNJJYNzCblPchqk1qTARjeQLo%20SSSBYA9tJsQPELaADwk6ftoGJNla0KFRxC/V31SqKKEGdoCDo2xW/Wym9b2kND8WBHBG3I5FxiiN%2044G/5r07G9NetcvJ6l3Pbx1fXRHten/ibeO1cvq3s43lav33eC0Xj+Azm8jPlDywBBiNP5eKwAN7%20i4j4jV8Pp1a9zrd1Ob138tyc9vl2ry+FZWL65S+7IvtHtFdUnl5hXTtNEg+4NfZregIFLYi6CgEg%20wST2N7E+qkw+YYNlOmpW/voGw0e0hx16d9DQOBcTi0nRU1TQfZUwGpIhcji14ug01IchGtJlpk5j%20m+FPFuUBAFPXrUgiZjwTtDcmP8uQI+EdFbduv1Ut9YKgsOUy2Z4iy/KMWQfBO62x7ghDmNCdNbWr%201eB3banHerZhDGQPC0FqEN8LbBLKUH/i1H7a3rjGPgY2s9lYDph8osZ0LgyYcPGYnOsA7yBt1NeF%20z53HocehxHA5bk/JYcjxkgBpIa3ctmkgFQK8t2o6kyXHy7XN8UDwCAS0ISNCQ6/fRCZe5ofx8jjt%20m2OQxl43ENBJuVVV9tFAlEj8gPY/evw/C4q4oNV+21KLchyONycUDxgtLl8s7ksVN9P5U010EQ+Y%20zGPwMlQhMDxG9SEJFtBY/wAKdtWJ5M5A3McIo8fPeXtc7bHkFFalgCQo1CLXoJVOd4x8R2HD5PKy%2048CAsjbJ/n5jbkRITZx+E9i1KjMat0NXugxsaPExAG4mONrG3ZYC7nHxbib6/wA5rqd/HxQiP64l%202s4OIAAx4bnKEG0vN1B2A2+qt7MpOO5/dDx4eBl9zn7gLhgQbydR4nEqgRuraqRLGPmNt2lp3o0E%20gbnEq4C4AXQ3psF8TZcZ8w2DCHG+o8c52IwH9PlsQTRtVNpalx0v/KLrVcKx3WVTxj8CZ+n4rNLZ%20+M5aGSEoXQ5B8t7QVsV7Og+g57uGh2W+rzkeZxGJE1r8/lcOBg8IeJA4hoQkkAk6dt1pf47eYrvV%202sjZvr7g+Fgdjel2fqeSkBE3LTI0Aa/lt7bWPvvXTZarTnvvuudcsfpkYN05leZCXSvkL3vnkJLi%20v4y46dhq1OPwJtj2/nn38PaHPI8slapeqNfYC4FiAC4q51zRATljGKnVPU+U3HlwMHaHvxcWESE3%20JKbi1xCgA+z3Vxc11cjv9GntnxM1mTl3jLz5jRZxVSpRC6yDwpWFtPA6ogax5H7nMJOwFGpp2IUG%20oOv2WomgT3x+RZQzMDNjy0MXqNzUNiU966UqpysyI1GpsloBkJB3AFeii9k7qaU+IR0K+Xk1cgcN%20pU7lBKhLi+qA+2qpqKULxv1mZDI44s2TEGFrHwBwDX6N7NwHUKPZSudDn5+TapRc8TJyuFCMiaGf%20IhbtDFY4uQJq3ao2helZpzUmzklVzL/i+WxM5jBjuJldpFoblO9blUqrW05WY+WxQ5NNyvF8xj4X%206jGacqINHmwj42O/E4AHxBp6a12XppdTyW60MT+r596skxpY5Jy0RN2P8JK3cje4eE9e6uK/mvWm%20KY7/ADlu7PO3w8Pfr4Dn945Jrd+RjzRSlrYwS1w3EIDoLIepIFV/k3Wqq/DGOg3uUp2+7H0fgQs3%201Jkw8XyEYbIX5bA1o02gg7i86q4E/V31XFzt0eMY1NOCG1Onu7wYtrYI3tk8zchBeATr79PoK23d%20D1bXr1J2GZ8jJEOJC6eVw2iNjdxuQNxRU6J2VKTY3yJKWXX+mPVL4crEweEa7kccJFPJtMACXVwI%208TRfWtLeJvN6mN/q7VlmczzvRfreDk2uzsFxnlfvdkbmmI3+PcpRK6qJJHntu9zmdVzMfk4cTAx8%20uQZOTHGGzOgXY1bNa1tjuB2j39lXxu1anm+p47rnLtpjP2SsmVHOfLrlvUOW7Ows3Hg8yNkbsSdW%20vaWFbkjqT0qbup08T2qHminyPlD68jLS6GLJa17UMcrTtDSu5CbgDoKk6N5a+r+C9Ru+Y2Bk4/Gz%20SYDJsBZo2bmtDXt3qQCiJQ2CZ7HqBgoAFAHHfWUcjPVvIvtsc5gddLeW2/t6VoqohuCrZkSNJcGq%20Rdi6qe1frWm0TMC8Nz42Xd+b+NwH4h0RTUu2o9zFSZIe9znORoJ2AnQC/RKUArhiLPjex8zHPc1g%20JDwviRERddKeQGR5CJubG+PKG4yv3q1xa4uJUhpVbBKpqopAN0bmua4mJjS1rQRZoaG9CAL/AEWh%20IG0IbJE/ki6R6x4zC1rXW8bxucRr3JTG3kh6V4CMCNOwvIPUBDY69q0SpJqVgmKhpKgK10hBA2gg%209Rf6qcDmMiFkch5ED52jcgAhaniJ7bWt20rqpjVHjHuOf+oszIbyOK0zvY14G5gUbXE2cn4kXqKw%20ttTtadTpXLfx3232vbcsmszWYAl4+EYxY7yp2xz5LmgtcztUC1xcpXm3K7jr+6z5H01q4v5Bacfq%20o/4eT8Lvh9JHK58DcHMfjbmCVzY3zN1c55LkUaCuixp1R4fJZdY3bdS62VBB4Hj34+92RF5ce0Et%20cFcwkLcdSVWtW+hzXWuSy5/h4srbkRRiVhH5e0IEHQGzvENa6Ha2px4GC6GHzIY4jvjdtbvIcoKs%20d2O7ulZZZmqT0H/0U/lzSSBzYgwSOlIA3MVAQlQnUaXYZ2+IbihIO4akN7ksiVLfyGuw2+IAoQW9%20AR+I6I3sHSm8wQzMZELXAtc9DIOn+G1zTT9wkNtY1qNBRyEqO+5F/upyFEHI5jWBPEenQ9UUdaST%20HNBtqOJCaiwd1NAo01AyGSQmKNqyPs1vZ7SOzrRdyK1Tdkjb0/peTmvVnHa7rnp+PRBOfBhfAG5W%20c2wcbxxk/VuNZfdzf7NnxZ7O70/8e6beb1K1/os/5n8iozDM+d0s7jJK/wCJ51t0/hXfx2W2qLcj%205/1HPyc17v5Huuerx8BtQRe1aI54CNEhEhHpZUNu6gYPp7KQBjUdBTkICIINAJil0PXtpAG43Lip%20XXtoBAbdwPvU9/spNASA8uYA34h+LqvS1JjzoW2BJBFFdJZHoGxKCezs61ldJqrS1lM+10TmI8AA%20tN/H+FttV7q9H0/AlV5nLy8kuNBp7ASAAocdwaQlundXZkc8i5mkb7kAIHEtS5CgItjqKm1hB7Ix%202u/7Pwjb4v7Kzwqn/wBONLD3V4vqc7vad3GqI85NGS2BGsc15Rr3KoRfgAKfiFeTMVnI2aJMEn5z%20XyOMTtimQKCAA620WI6jSqkpOCXgSSzZBhkJcPjV3hKW2r33v7KINUX2+JoDSzwkAOKpdAVQUsjR%20WvMN0gcXKweIWJt7Lr3UAV3JKzjspwUlsR2j8RO3poPebU7c0K90OXZMjcpm+MgtaAXxaEHb093d%20Xfa+py3dcItuFY7D4wbnvkfkkFpdoWAgJ4Ru+uouulnX6eyKssF80EJuDz4kKEW1F00PTt+vNdDr%20I/r2Tdz0eKu5uNiQRhqL+HcUdp9Y9tdljojy5rRxjH0gz28uBJaLltwVUA2vbr0/kWCyxQZc8vcN%20riEeGMegcD9fZ7arx8cY0FNPp1x7AzPGWtY8J4WgkBHADwnRB8NJp5lKuVXOPZ8+1SJNDNDI4gbo%20yqsNwRawPfTnGMdSElpiZCYzj5pAb48xJaR8QOvb08PaaTepSRJOOWNWORj2u+IJ4rFLA21pt4zB%20Y69saBsIuXAbjr1G65G64S/b/GjGOvsCcZY/PxJ3GxtyOW4/GRTJkwgkguRrntFtVCG9LEA6Uxrn%203xkdD9WlsnqHMLDv2vDB3BrABpoUWvN5bvuZ6fprfsRQvxm4wMr3lnltVznEohUqQbpftrJNujrj%20PxNXco7DLc+Mu2xtchVCEDtNSXE6Dr21cJVEr1I5+oyX3jgIaCp3EAgFbnXu+hpTbrjUxfPYlQi5%20QmkOyXxSEW2EIAAqnt8RFG/ocvL63phjGHlw484kdCC9jwWxuUiwO4k6WcgFk76jzMY7e0536q55%20YwqnQOM+Y+HjRsZktEIBtHBtA8HsCAqOt/detLeacljGpkuWa48fDCLTB9Z8OyFmzJLjI/xGWznP%20dr4e4d3Stbb1juW70yL6Whw4/V02Y10bGyNccJjAE3kDeoIO3uvXSuJJyQvU3NO19TofGcjiYyxt%20kc6VpDkahcD8XehdWuZiIyZ25scszZziGIAucW6OdZXAgIoN6zdi0oVbejO5nIc5hwGfMMeRiNAQ%20gNRrQtz8WqL0qHxxqaSnQqncziTyRHIwP1Di1GMY1Sihd4bb8VR5c4x4lbtSlj9Cxc1kT8hkRvx4%20Q8tjx8YeJ3VXKoQBK08kp+ocGv4Dh+PwpTjxufjtc5WQMi2IC3RzyrrN761VhzXcl1zL79G/EhIw%20AJImlxfA8ku3uuu5TarITZTclh4nJ8fkwz4jsSZ5QB1mbwpMg7b/AGU2jTh5HbdJzaYT4zHRhWzQ%20uc17VRu6wDgQnRoA/wDFa1ZXWzV5Yfj4zktT37YvrE4r7+9RsZ+QJfypXOaNx2OsPEShPQn7vYam%20I7ZdtJ/RapZE+RY0qKnbGGLx/UPKROjHmlAVLw24CBCUO5NUFqHNWYXei4muhd8B6u5MclixDeIn%20SxhA46Pla1HKo/EtVuc5qcY1+Rhf6K1ZXanp2g4wUACgDkPrYr6kzmgjxSMBRFDfLap16VaoZspW%20OD5S4k2G62gSy/VeqAUZGoSFO5RYIQvTpRKJXYYlXZtCaFjgSCUVV94N6JAhci5sOKyBjdu9UTw7%20GNIIBQ6GmmgM/MwvdKYW7yAdzAhI3eJfZ7rJRLCQSOMTC9vhLYy4BwRpAHhv29FoWY2HhwGPGaQS%200uDpHPOiuCihVQDGW0sbYhzVAL1FyAt/u8NOQUYx+RBe5rWkAAEANC6qSntSh0xj8gq6alH6jyMu%20CXGOO5odtJa0hSpG1UF29Relc0lUpZlYzhZuQ5zjnZHghjG7JmIBHgKhqjtSuZ8jShZnS+Ntlv6j%205CR0krIY9jZwyOSUgF20dR2NNc9pupUNUjXp+Zmv+akx5MNszoy5wLJzoXNuA49Si9nZrWNyfE9y%20/bqvwPf4eW3+QS4OWnP/AE8nXtf18fA1mFyM+XyEMA2jGjIJY+5cxg2hpVR1Fqjh51yNk/zH8G/R%208dl07ppd/vdu34GkxVn49XIwsL2gAJ1Nk8JS6V6/C5tR8pyKGZH1Jw2HjTN5MoYnSiLOxrBY/wAT%20mEfib176jkS2yOx1gm8xxz/9GNbjrLBDte6UBJHRlS0IUNlAQ1wq77jrutpjGOhjo228XhL2oxwF%20lIA+4Duq2TjHxI8r2hhfK7bIXBQ3oAVUWRSRVIVw1FjvDmv0uEVbr1odyExD4wbsO8m+2y9vSyUJ%20j2jD3HTo6/0NWkS6ZlnhcU2XD3vdtfJ4o3AXaBpqmtedz+savpkj7r+I/wDjdnL6RvklX8lV1tWn%20vz8CFlTbRJjY7PIjUskI+N3buOqHsXtrp4uPd91zl/I8L1/r/wDHV3puBeXZb9tz/qv6y9PDxIZa%20AQQAB0CIEPW2ldUnz6t0IebF+WHjpZU6Io+oVtxszuWpEY7oVTpatSYA4n9tEhkJJ+5RSkeQZPZr%20TTEwA9OztokbDXS1AhTV0X6zQggDiiiiR5htK2N0HvSkJkyJr4o3PDC92qAA9NU99Tc0zSYDwYcq%20aUvgLWStC+NyKSvuFNWO6gldtqXGHl5cZdi5LHOa0qwEkAOCo6N4Nrql/wBlVby8nE65FOyzkUon%20OgZvhLH/AJcjz4ZEaFaUQkahD+Guqz1drVaMwu9NemCaCWMu3t8LdXBSwIA1WoQ1XIFt9Vda5Fdk%20czTR7Fx2r8nYWsaP/wBFYgFv/px3NSvD9R/V7Tu4qwedYW55YxcQgvcocbXIQB34QATXl6QbJMdf%20gciTseWARt3KSSgduDr9/wBOtOZzKgltacYtc8iZwUsJO0W1aDoqjrrSnoUoLXEc5zUeD3N+I7lK%20Be0UbuhqksYxAp5ftIB2tQgnW+ocfZQmU11ZF5QvPD5JKj8ooQCANFXr7fqqrWtxLRyR5kbOxkBJ%20mVA0AoWk3UC3srulHMajIiLYGgt2uam4EXB+g6/vrnuPS41FtCZwMTcjk8SJwGx7hvsVIb4yfYET%207qFUd90WyZr1FyZz+bzsxVa+VwjKghrWktG0g9g99d9q0x8DzV0xjT5Z0rzKS5xDg3TwgWQ2t/5a%20JnP8wlY1/P8AKBl0xYQgO3Rp111VbU0gl9cfXqsIExd5Z/MRNqFSgFh95/kaNJxIn3WK/L6UDhyT%20JEQiFUQ6BD0BpxGbBxPfGPyE7Uuupsv1VMYxhC07IQ0EOXfuCNaAoFyUUr7aOxU9cY0/AkxuuS07%20T0a6wI0QqlvvonJCbz/LHXw8GXXoqMy+suJaBuLsmPct16uU/Xeh/iFypKyxj599xyTzJy2Y9u1r%20/OLGSOLgilGuCEDwpf8AlXkcjrXH6nr8cbe0GN9RcgZcyLGZKTDjH8yJpQufZzQU6X0SujisVTl9%20VyOYF8FlMdK+R7zuDSSFO7amn4j0TSlzKlFjFTg5LnE4+hLy+b4+GVmI6aNs0rjE9rmueIy5CQ9i%20KNUupt2JXNx8Vzrj34Xbpla51fw+nv8ABj+N/bzDkRTMMWYxpM7QhEjTo6Oym6aXrW7jaVcfQvZC%208BvJxWtWbeInyEDwHc0KQC26pbQ9axutuSrWhm7IWciGSY8bWteSRGFYQC4Bu5fiRO+y9/VC14x7%20vkK26HXOfpjOApouKmibO17I52qfPJcriB/T4U26fwq07piMY+pSyyyxJN4r1DPxjXGXFe979xjn%20BQWHXS/iCqPvrpXM6ZUI44TiZxiDXYLs7JxmclxHKOxmuXzWNCvY7R29r/pa1ddt0qcY/UHDLXiO%20T5+ZkvD8m4F8rnGDLcWhRc7Hp9nZVpiaoanjsD9DhmB7WEFdp3BwL3lF6qutO4mBiIRjIyt0jCxk%20bUYGhrm3JKO+I67qzV2hTD4PMa7Ed50Zb5W7yCAG7mh3QW3L2mrbqJSTsjKxY8ePMijEhuyQn4gv%20QmlKFGpAy+fdDiumxI1c8N8DxZh/9twFNMIF4vJx5QEj2vMM1ywqHRvAJKA9tUODnPrfDgxufndB%20L4JR5xaLOIIuSp1XQJesrlP4/HE/p7PpLm7I9nYovy2bmhn+YGOEbzqQLODb9Lg2/fKdZ7V+cU93%20idLa7vvlTGOkdxQb9xLfEQVW7k0Gmnb7dKaVK4nKvWevtJT8JyJ3DBw5rj3NYFGRC1oF3EeaHE2W%203iJomcfDLP5kX3/b4nrumeQCgAUAcM9f8w2H1pyUTXgva5rQw+FC6JhN0PRKu1IzdGUreVhc50e5%20NqBt0AKfiKlV3adKpQwyJLs/GJGyQbQDJusAQbC9xZVpQAl2XDuZG97Q5dpC22goL27FI6U2EFZz%20k0Ls4xl6+VGNpYbEqpRSETan8qQQU7ZJG7Hxy+W5iua9ocoJO4tv9dK9SORjKly5TLJNMXefshEe%20jWNaRuQdFA6UW2xqKdSwdIY5nFzg1zFbtBABQAjd161UpvGQRjuR8kBxadu4IAGG6lw3OKAjXrQm%20EELIc3zWuepa0flMAsb9pTs/jVJ+4IMxl5LRyYdM8Njmd5e4/CE0Qj/GUWs+T9ppxfuTLAMzcCWV%20qru3BQjggvofoa4W0zrqI4ljpcx8mV+cWq1oddSNAAPr1qb30NLe+vyJr+GgdNDGQQx0yHo7xA9Q%20ug6ofZWb41yUdDs9H6/k9Jd5nHE9yfxHpiWHlhJ5gEUcg8uJ/iMkZ+JSAACOyiz0Gy9NOfZpkel6%20v/5Q/Venu4uTjq1+5PWZy8P9onxYsuLlZk2NI7LfOgZBIdrGbSCRbcu0d/216dtmxOGfIu6TNeqJ%20o8XjIV2yyOIdGx+m/tIS6GydankW1QVx3J3NlzhcgzG9GTwsIkkhx1lXUGV+hXSvMuT3HYlCMH5T%20Hws/TFS0NSN5uD00N60ROpXT/pxkNjO1ri1SHAhDchW+2tEnHYlrqKe9zmNLAgcu8t6DRL6i1KdC%20kkDZvIMbVYg8SaqQtk0GqClIoQjOgha3y13ZFtpOpDjoV9tFlzfgERD7/Ebdn57gAJbKABE0NIHT%20+odO/uqF6bjVY957PL/8k9bco3K2NLUl+JDma4PLy4veXBrnO/EO1U7K6LFSEePz8t/Jc7r3uufU%20EkEjWh7QDYpZPoKauTcGVylEJ5Lody7i4EgaWAVe+1q2tdTF5FeqEhb9PsrdEQAqDY+5NaACUdPf%20QASItgPbYe4+2lIMUO1PedaY5FGgBO4NUm46CiQyFByBSPeegFCYokJj3LuAvpSkak1no+aTj+Sx%20M2BwEu7cHyBWlNQ6x+nZUtOfAukVHuf4mCfksmeKNsRdI4ujBQDqdjShGoVK7H6f7ZtOezmhxcP8%20bgT5cASQB0fh8QV4Kk9QF9tc3+Q7aXKToXCrqqgrN4PMLRFkRP2X8UJRSBqKq3yr8syX5lndEFkW%20VA0Nxpi5zA4GGcW8OoC9vurR+nvtydBPmtuzVT2jhSvb8oMWR4aHjhYi4aNX9OFRdtq4eWYc5l2w%203TI89uzWOjcWlzdzrveSoCq0IFVAfZ215bbxjHbTaR12Wjlhe1zi4gBCA4A7vCCqFy9R+ypup2RS%20u6CIch7pi8bXxuO4tJaGXCAgnU7kXtPVBRNcY/DoWnoibiSP8lpdI/c5DtQEr1Rev8fdUmtJyHpH%20gNcFHmKGtOoc4uUNI0JAC05GoI3JzSO4rM2kO2xOMjWAoq31S21V9lO11QrkYmB5b6fjZ5bHOjyQ%20XSaSgOuBoRtHtrqubVTGxaomyPc9jnHxWuq3OtrfT2Vm6HesUE8VyBwcPlM8PHm4WO5sTibmSQAN%20P4U66GtOJS0c3Pd9sGJilQNEhuqhxJFlUO+6uxnGuqAJQXE3IALnNVUC9RZCE0ptaBtpj4C11YXE%20qEDhYqAvuoHmIhmDVaSNrbf0hobb8V16UR2CAn72EFADYuFiASoHZTtYLoO7WvbuFmHUkX+lqAxj%20H4hSRxBp3PO0ntS6d+tu2kE9sYxQUwxNO1h3uTcU9n1DuoTx7Svl+ePaX3orLGP6u4iVybW5LdwU%20BqHw3X3Uogi6qrjFfqbf1E9uHy2cHEh0Usj2gE2LgSHBPrry7rKxB63FyJ2yjneScjJ87Jaxn6sO%20tISGlwudqfYb+yuuw8+5TUr8LmeVw8xpLA0lyGJAWKvQH6lNO6xXKMe8zuzmIGeUzmnLOEx3hDy/%20KvuLpX3JXsYKq22KkOhp+H5MuwsXJf8AmOwnCGS3ia1fjUlHeysORTdHUbdS4yptwdHMC5sn/LyP%20QeLaQ5ltQLUX2JrGGF1qghPw82NjWRtM8btxJ2oQU8ZABTQ2vp0rlUTj2fL8zmdjVWsaY+Ik4mbu%20GS87ZXBznOJ3OBA6lHL8XadL9Edq0xj2eHdbHERTHfsJZBKm14bueCBvBQfhCL1Nj+6qXVUHcn0e%20K4+pO4TKzePzz5TpHwtbumZFqApKWAXwjoNa14+SIhZlW1r1Ohx8vxzcYyZwc2NFZHIrZNQEQjTT%20T7q67WmpDaXfEZUsn5GK6y7kF0BW9z2UwaYnkMDx+RFlsblSTeb5RJLnNAPh3A6LRao1IdcY9ovK%20iazAmxI37ZJYSxhLj4XOcp77GrmXUQxwEEn6Sfj8/KdI6R3mMDXEI4C6O1umlLeioFY+MWZWdFGX%20ObsEjg9y/mIRu0N091EpjgPiM3E/tCSBzJInGIscrd0gNtp9lUyIpUzvrTFP6LD5FrNmxzoJHF9y%20167SACbhFB6C9Z3rVnoei5a7epjZ5HMjc0bSd5aBoXbrpuBO1fomlZz8j0U59w26V6kNcVZZpFw7%20TQoi/X1tVUWdCZcTnPyLv0ZM6P1Hx0uNifqJ3ysad8hbGwF7TvPhurVQVO7RmHqL6O2cfkes61PN%20BQAKAPM3zSyJB8w+Y3BWNli2i/SCPX7aa7iaMwMqIXe0BiHxW6X7ftpz7RO2BQzG+JpKAWAJQKQq%20n3UxROQ/Dlo673BqjehKkDp06Us+zAp+S5mZjnhri4BynrqqjboNVobqMaHNy6uChxCuU3uaUiUD%202PyLpJ4w9oIjVzio62Fj7arwHmTXchC9wJO9wQgEhbaHvFqfbUUEYcmx6lpJcCCVBUElevZ1oVAa%206CJsgyBfNBuXEkFO0rfQgGhMfwMvyGVJMsE8YO1u4MaQFcu5rwR2KlDdAtTk02+bK4vFzYiqMaXL%20ZHs8LrdR7K865Rc0eja5UoKIOizcd8jQ0vLQQDbxfV1SpblDSqW+XHM3Mx8diMMk4Wb4i1rdUGn2%20VXApZHM/tNBnYkskjHRTCBrGB0M4/wAIJdvCJoTXds3OcoOHfCKmfkm4zCciZhQjzJXHwkLYghP4%20VoqImJMN6r5Z+Xmwx48J8hrGiKd9w5yC4AULa1cvLfuOjjtaoy/4vCfLxvO4kjiJBgMl8TVUtPw3%20ttQ3/lXE4k6J95hRLjsK5AEb3DfGG7iXEaomgXQ1vtd2RDujUZdmDNgldLGH5GMQTOB+B1gD0KLW%20m1oh3bmMh48w+XGXhuvQlvUoKGozBXJ4xJPgkeyMOdCA5rd5d1FrfZrXNcpNkQpj5r3SBXOv8Vl6%209TatkooQ6jf5gIcAfFYgJ1qqEsBefGzaC4/iCK1aBNMbE8rovJEZBFnFypbRb++iBdoI8rGh3iB2%20uvcnUdK1tfRkNVKpwAeVNtADYr1rdGQCgFh9VUwEEdC2wRCLKaTAJxaFJAJCho0UID+ygaTBuudT%20qq6ikTA4D4TdD30wEbwHIoVQDfqRaiRjjGgnXu+i00g9oXXtSkBo/S8TZMfznP2bZEiiCOc9wv8A%20CdAvWlMDzoXGU5gyJAA7wu8DH3cx2pFw62530vXr8T3JN9DjuVY6fT8A8bMlxn72NDw60gPhsgKa%20khNxQk1PNwK9dCrOR2+Ba4nKuyS9jUYW+JsRIUkdhTtry+X07sZ12c25ZEDkJWZbZp8eMGOEBsgc%20PGC4DxEt7NtdvDa7aNnPyuanr3jonSfKTFjYFc7h4wALEkwD76831Fd3tN+PQ88jieY+CPGeo8JC%20dWEn8S23XryfLUzjHxOjawn4XLMDmvxZA1pI8Qd1KW8R3XuPro2xGP0x0K2OAoON5Pz2yOG14Kvu%20rgVTWjbBVvHD6lr5E6F7wGgIHhwuvUXUdLU0jVOBQbG5Va5wiBDngBqAHUErdq9tNoqSNmQibDmB%20YB5kTy0k9rfcSnt+ymrSbnoYQT5L+IZE1xghErdsYbd7FVxJ6XFdN2Rjb4k4SFD4igUbftUIe0VG%20p3rIzvPZD2NdCHJHMQMgFbgXao0Nq24czm51SpTNT43t1tcJYW+2urGOpyChrYlRcbddFXr2miQg%20kNb1KEFXlTYXUfzokKEWcljw5N/4ivZp2fCtC7FS9cYwx0uegc1u9pu4ajc7tBU+yglBbxG7e27G%20gd1iim/soHj6DjJ4pOhBKtCJ1Otx3ChgL/UsDfhvpsKAgp4QQtHgCD89zJGPbIWStR0Kf1tcCCh7%20+lDevcFjudRy+T/1Vw0HPcTj/qebiEeJy3Hx/EWkgb2gkdK5rrPuxoacfI7U0cw5Dj3Qcjl4rZyP%20KlfE0i6NadXHTw6U9A3SQ5kweQhlbIXxEhxevUFCB00qrakt1x7islMQycl8bvObvJifcEhxJRCD%2011qlRKhF2bNZw2VFJxb8Ju6KeNhkaUCOKHaFum2ufY3dIJF87LcMQzjcXoJAihHNQa1SqNM6JxHp%20vh+R4nEzdzt+QwOcx4LS1LXITt6e2ud2otW0JI9Hca1qNmk8slHOsVO5S0BNLde6krVkOMfIjD0h%20gREuO6RoKBrrhF1ppWi2DLuEwsWQviieHFXFwJa5q9AddFt7KaUZEu0XPitmYWZkjpPL3OjMoQAj%20/E0jolaJ64/MTtCh5qbCwTicfNDjZMjF8yQB0lggJDUGnU9laLkuehm7EN8IcjFzjlOhGROiOmmc%20NURz7gusNL/ZRa64/QLkiZl83HIybF89HoS+Q2JVVAddPfVy4I2yyPF6obDeQBWtaWyD/MJH4Gt6%20lFvQ3j5AXDc3PyMKTKgDhltkBc4jwtZcoTZbfV7qTZKSJkzuPfGyA5AiyM074ZHElZAACmlaW/Ai%205dSp9ePI4LHwo4WtDngyIgu0IfYqLSvf2nX6N/fOMYRztzZI3uc0OQgjamjVUJ3W1+2ssz1pWMSN%20OLi1UAc1FQqjgLD7KcCnGFiprfl/tPIQEvb+XOwNLrAEuCHt69Ki5/cjj50eqq6DhBQAKAPMHzWm%20I+YnNMBG4yxAC1lgjF791ZspIy7ZYnXB+tOosKptvMICBaXEblK21sQDamm8xAZJ4gtiQTZeh91O%20eoQZ7LLHTucwB1ze50TQaG1CuBojGxAkBabbwPhUaLTkUEzFMm1XMNmpuOutwfvokQ+ZCxhI2hFI%20f0Q9LdqmgdRl072vc0DdcBpPaQoaU++jJZEyKlyWmOYyMVobtBUEgkFF2k2W1U8xplDlZTImyTCE%20tlY7Y/IcpG4pp9L1TYWo1voeV0vB+S781+8nVbG1k9qAV5nqI3Seh6d/aTcmEiVqtUtdZxBFgff9%20RrPQvoPeoBKcfjgwfG5HIUHhPiUa2C1rwOrkz58ibyXqTH47AdG5/mZDVZsaLgKCUFuvZ/LvuvSV%20ThVjeRhPUOdPlY0TpNXFxbCCoaG+zS/061y+ZJ0eWlGJK3F5SXGmhgeQ4MIe6J4DmjYCbH31Ls6U%20Gr14m64HlsbKweTzWuLsg4r8XMxT8RVwLC3t1uWn765Lk08Y0NppjpjCMjyHDRyxxyzlsJABCFSW%20XIRK14uZqhlyWSVUkckOKxmNuEEm4vB+J5s3c7/8tdL5E8yFbGRI4yMLG56FxJAOvhA6kdax5XnB%20fGpLWRrHAtN2mx6LXFu1N8ylyUGYjm7QCiCxKJf2122P7TFqoUoEbrBWPLkGgQ6pbs7aE5AZdGQS%200DSx7ul1v1q5JhDUjS6Tc1zmtOjAfCV0X2JTkhoanc10ZKIAgt2dymmhNyU0xScgDt091diMHmJc%20Sg7evs60wEOcEcVBsdT0XtpSPwCUtIUdSiKT0F9aASkIHQlEsS4qRc3F6QQPMTxA6p9oRVpphUZc%204tO0G/4TbRxt30SAuJyEAKNQF6p9tCkSTFOcFHaqdBRIF5wQb5T3Hc8u/LDWfEA4XPf+yhqSk4Lx%20sZZAx53JsEccrSgVSu7TVHDX+Hp+nvTsicsfn7Pfyctr3ZAO4q0HeB4AGj8RBARNSgI71KLrW/gZ%20ZDQJaSriqDag1I09lTetGX9CVLkGHKlYQPzI/LyWf1gDxL3rWPlyi9zzPZfp8NPyw44WY08VCOgC%20eSNdNeteVz53e06bKwc4dFDGm8lsjUaSdAQevXv99eckdjunwK/KeC8HzSWMbtaT3n9h60oQ9xFa%20/D2PY0AB5BcQEJPeVVKItFukamlw3pIhI2kmVSidLDU376p2hu+OMfAQJMN7bNaG3ajiQoaEBv7r%20/upK0bZH5BnHNx8h74GgNY9+5QpsQSvb399C0Bs5Zx7ct+G2MPb5Ech32Vziqo3sFdNxNlWTidUG%20ug6iuaTvzM1z5JlCggKdQnW172ro4exzc1cYx7CE8Bw8wNQNAXoBZdPurq9pyOQNDg6xUEnUdyHU%206pTAcil2vDTe7SNWlTqlr0nkNhTgFgsEaVaRZydiW7PspsII+O9u8RP+F6gO636js0FNv4BUfkLm%20DYbAhIygIv3m1qUdQcEd7gCC0DVT0RUFiNaIADZZCqEqBcNuFBUanXrQAnfKw3QoBvaRoe793bTT%20C4fx8jJxZXZEEsuNIGmMPjcRuDum5v3VD8QlCfMLXuA8LXElz1JLlN9U3HtrMc0LHmOAzoeAxObh%20Hmce4mOYn4o5DoUPxNctTY6wO9djMl4EZc4KSRtHebG/atad9SIcGh9NSvL27ZAwuY5riQCXEXQF%20LEpU39gWRfYkjv0ewkeKJ4aECBzegTp1qYgMzrny+yxN6SwXqji13jCqocdoTonb/Kua5QzTPvjG%20Kl7NKxh8UTnhy3ZdoBQ/RalrqUp0xj4imvDySSqkFwd3d/xCnHUSxjIRI2IsO9m4uBBkP1m/sKU8%20swU6Ffl48ccJlYQBGQQw/wDEAQNe6qtz8CL3STLOZjy8w50jGbQw7ZGu12jcj9QgQ610K2IXTGPx%20MG5CxYsOTNGRi5DvC1wfjHwkly2v2JZKTt64xjoLdJPx+MxPKewEYriFe9o3kpctv3CnZ0xj5A7p%20InHyRjKfklNjjsbJIFO5yI1vRtuw1pdb/aszGVk37jW8TyeC7Oi42OQSsym7YrkhQNxCIftoVrGo%20I3I8LPkyS4DHsifE8TYhcVcx7buaBqiaU04zBe/GKGe9bclyHJx42Pjyfp3RI+ZupDxYtde1utRe%204pqb8D1Mi/J5OEkZGOJ2gbdzCgANiB1H0NQ4Oxcrx1CZn8ZO5rXEwzAABrwgBVRuCDWh2vMtcluu%20MfOhp/RYjg5GANdub+piLQAu7c9PEO4dal6Mnlaaf6nq+tzhBQAKAPKnzakH/cfn2k3bLEiqUHkR%20Gw+usbnUtGTDlDmvGuiEko5QTpSlzAJCmyJ1dodEFx2LdSetUFRyKVzQWqu4ElSmgJNiuuqUJ9ah%20BS5MjWzFbvDldeyqfwnu+qrQpEqCWsagBJb29yfbQhkiKRu4M8zwbB4NpQWFyeuqmhCgeeIwC5xc%20GlpLdvQ+/t76bBJEBhcrgi7rkG6gdqdn2VUkwxqZ7mMmaHODks5b7Q4Ag+6mrm1I3E5FbO6XJY5v%20nCCOIGQbvEHu6hAOwUNiRb/LzIhjmOMu9r4A4MaUb8akE67rVxepTO308RQ3vIxGQlzHbmootucS%20QOvTUaW+6uU3IXK5EkfpvKmiI87Gc10bkUNCAK331pxXRcRy2yjGYUf90kYHEh8r2ukD3JuIcp2u%2091a3t5mNqUk/1THi43MHE2l0ULGCNx0Uggt3Ii/vrLjTzHdjGpncRY4JclkbGFh2MBBeQ0nxdb2r%20Z3TQUQ6lnx3J42JNEZS5+K94bJJCjShHT2Vm02VbQsvU/DZGFJFlYzw/jpQXY2gL1ujib2Ws7WpK%20vqZ7Kgmhjim3jzmNIcw31CEt061rY17zK5C+PRg2sFi0O29b63J99Z8qnMq3MnAO3Eu10AGiCuV/%20E1REmJcqljmNb4nhFJXs7K3sIZHfuk6tABCgaKgKhOh+z7tFdBLGliBLQSUb8bgD7AU7Fq6iyIjg%20j72jPxae0WPbVpk3EaV0j4347g1FUAiyEIQSPfWtsJmTyKedpEp8RTqo69orpMWgOII1IugTtHtp%20hIlzrgogCpb3FL0gzEMI2gINoC93sSgH3CQEDrbUHsPfp20QVGg7CUcXJcAq2+pCqVVNOtNPUUUE%20yOAcpKNbdztUIslIUC/CT4uhQgaoPZ160BA5Ps3lo8LUUD8Q6+82ptjL/gIZ4sCfLZDuxg9rTOwk%20uYiLtFu2pufuGmi6gdM1jf0sjgrd0e9CNpIX4l7OyvQ9PCsUnNyqLhUmOx/mPmDmyMK7mAIjnE+E%20EglVBVa183LKCNukDGO5sLyXFWxuaU7XBbKndU3cidIzK2PMEodIyaRwB3OcSt0CXS9abqT4E7We%20z+Bcf+2HHOAU/wBqgIaf/gt7CPvrx+dzMdzrsWRyuSXLaCXDaWrqUaV69fqWvKrmd7IJicSA/wDM%20eAiBAEHQdOq08hQtRuaF0UZbGLkHc7UroCSLXaK0nrjHQUQU80uVM/VIzawUoehS4AS3WjJjSHGl%20pYQ1wVoXxanaEQaILe+hIQ1mtkeGs3NDZCROFO7aew2TuFNMIgwXGwtwxksma9jmyvbEXFBtJItW%20tzQ+FOQzNC6NxbIPCFLmFSEUrbsSsZOxMzXOOJmc1oF3FTcaFEN9a6OI5uf4iXB0bWtjfuY0A7ie%20un32rddzmaGnOa4qUKkaqVA6/vqshBo0g+JdUbcL1QfTrTCoTZGkINQQAqWaq60QwgZmjUBwDide%20mirf6rd1BKHoMhrgIZhuBJ2i4HsJopElNBTYha7dH4luUGoFvoaKiERwyPcBsJAQOICFF76UgyTH%20A1jPEVQ3aUIXsT32ozYpGfLkzMyKCFtiW95UlFt7aToijZcb8toW5LZcyYz7zu8snRx0QlB++uO/%20lnI2t4l0ND68w2zehstjCG+U6N4AQNcF2hrkQdez2DSo439yC5UaOKGKea7UU/EF7tUJrunRnPBd%20+m2TRvDWgOkaXBjSbXCFSfsqbh22waHALv0bXFHBjJSLrfQ1ndBddcY7HVvlu53+lcVzC1sau2hn%20YCviPhQgjvvWF7+5lpUqacvySUBBDiFAGt+ut6mWKEEXzBvjcSoUEalpJRU9p+upqOgh87mxPe+Z%20rWtUPe7uKusT1v7jVaBKM3zHKw8hjPixJCJIJotqhASV8JUooRavjUMy5HKImLx00mRPvj8LF8sP%20Bcfi32Q3tr16V1JOaM5pG4/Szp5TJHkiKRo8TGi5BKlq9dK0giSTJx2XlAQgPYGIjWix6IQoFkF7%20a6VnCzWeOwS0S3cNBOwMy55InBA6NQACCm/b2uq9wTQscXiY2NdlcKWNma3a90zUkAYCPy+xx7a0%20lTUUSxmPlYnsGXK936vBO2eYN3eFdHAdfER94qbggpOYyYc/MdOxnlscALodwdtcqLbctct+cI7e%20LIrvKBedrz4T4XdFPQW7KmTVkTJ4zHljSaMS70WyHcUvre9NOCSHif3XhuXwZeIa4HJy4IssubuD%20YzK3dtF+nX7apOR9T2dWxygoAFAHkz5vyBvzQ506bZoVPW+PEF0Nu32VlcqlpGVJAc1+4uXwOBS5%200W/sqSto60vGhLiPE13Ue89aUY+AoFAtVb3A1sCNdO4mqCCozV3hDcEkfWe2qtERZHOF9UK9VsE/%20bVSIlYriRuYzxNBFtTtKoQfdQ5AVNkx+W2PeCHNLhEbeEWKEJ2paiKgR2uIf4bodzRr3oje005ER%20sqd8cMpBBa/ab9HfCNEUd1UBX8icRkjG4szpIdu2YofEVUqt0Wm0CcFh6NhGPyME5DhK95bEwKwB%20osrugH/FXLzuUdPCjqMpG1u5XluyMA6AAnd3DXQ1wo6xoYT54syJrgcaVj4tFJUeEtOp2mkm5C6q%20h5mX+XPENzOfDMlodFhRPc4tATduQfaBXRyOTmVCt5fn3YufM10DczFMzw3FmNjECVST4m0cfHIO%209Ibfj8NyJMnDSyx5kTVdx0g8Ya7Xy3fi29lN2XIUrIp2tAxWxz7gIHFclrU2vBOrfbTlijqar0rz%20P69n9hzIvMxMjcI5P/aegLX9zV6VjfbGppb00M3mEDlJIB4smOQxNX/LO0m7V18N7VcfaZwpjH4E%20oQRPyHSkkyMRq9EF7D21i7qQaK0PI/UPaQ3wNcB+HxDVe7SpthZltsS/HfuD9HNcqtN/u6rVbkRD%20I0gypHI4COMWaRd27RbHuqk17WIjytK7i0NdtBRosoKXBTWtbWSMSsDQdyG6EWsh61aZL6jBcDG5%20gaVddeqjs9xrRTmZt0KbLT9U94QnRzlUWF66bWZXZjZJDF1Xrpa6d2tUIbK3unsVF+vWiRzATiA0%20qCAoJ6FAEpDSeQVyQ0qVKOAtqLqNCo1pigdxmFwchG4BA7260IUDcgIlPiKqDqgJS1io99DdRv3j%20rgwEbToUK2JUU3GgqEjFzH4sjntjDpXNLI3OW27qKm5SOYLHhZ8qPdjMdII5pATEwuQkXVwGpTpT%20ajIcpSaZzIZGOma4sjIaHNRSx3TcDcL+/uXu9Pd9sHLyqo3I6MOO2w2gsBUgkuRykp2fQ10K3qQ6%20UGS0DHlUGz2lrdWhNQetcfJbN0m9t8KCRkOYY37UKgAuQIfDa6e2t9kqphuqeyuDD/8Atfx4sHf2%20qEIQo/yQEICa15fKszssazOUSSSEFgCu1LtRa3aOleUk2doy+QtQuKAHQBVCX+qmlDBkfImndGQC%203sDmqQt7G+lVbjGJD2lVlSSBxTwKb7bEomp62oUQNorneW4lr3ua5qbj8KhRfsRUv++rkHIuLGgj%20aQ17i55JeSVtYDcVvTliky/q5sfmuLnBrCwbEJUn9h7Kq3H1HZdDzr8iogcjS4gGJVJQbrEobC6u%20TqTSa9+MdDqtupPYouZcXSi5abI65KlL3AGhHTSt+PI5eatEJCNja0u3lShVUB63vrW8SjnGw5yo%20V2uULre+q2S/WmJsSpAbscHCxBsbX+yjxGNOk8ZW6qQNNb/Z300xZElkgkVHK/qCVJsPClEe4IEv%20a0/AVukjRa+gX3UnKBUEw5r4W7TdpG5CUQDuHWmEk2PLikbqQbg27NUoY2M5MwNt217dWghB2LbV%20adRmi9A4An5SR7BuONHvJJCFbeJeoNc3O/tK4/gb3ycmFpcWFzR8J+E3+LvADbaVwnQK5drc/wBO%208lC1iyvgejEAJLfEqqAD7TV2qGS6VOHxQsMZAHjLdqjUIE6f4lruOVZFlw7XRv8AMIILWklzRoSt%20ynab0mMssWZseENSI43yIhDVcqIah5jR1T0I3Ix/TfHplBsO1znwkDUuUoUtXNyXVNEjXxPkYxyS%20EmQKQpA7EtSWXQHE+A43KYfFv2ubZQUBIsEd2qTrVp64x3JjQp+Wws7My2/ppmDHeNsjHFPGLi/e%20lCzyG0ollHncbNguhnDmfpV2vab+MXa/+olTVpJ5k30Q5mZ+Vjhs7i98ZDXEnwxggC7gOtz9ldUV%20zONsl8fmPli/WjwAlZGsV9wQjfbVpr2ERFI9ix7KE6XmCyRz8aVGM273StO1rtqp2kFKT7oEh3Fe%203OLJpCX5MjWmWFgVunxM9i6VntQQ5xjxLXhsnBmy/K89vnBqGBw2AjcoQdCNt6uEJQtAsb02zCzM%20rJxntdNKFGOnh2r1JOpXWmyoMnz2E+HkZmsPhUbnAJtGiD2VzcmZ2cToVUbmgMa0udYNDtev4j3J%20UQa+JJEEbwStiACCdp0OhNIVBWKG43K4LpCQz9TAxDdqmRob7xVKoNSmeqa6TlBQAKAPIXzkkI+a%20vPtDwPzItp1DXfpouy6oKzug1tyMkx4JLLLJpdFOh3AHUpU9ximZBDhdAbXKoQmiWpRGQ4ZNjne5%20ui6EXsHAkG9vhSl8xEHNaHybihcb2CWd8PbVpihNkV8DiTtcNzfCtuzTram31FtxigvFic1ilwUP%20sw9et+6nMCgXKXFjGAK9q7CniKmwKdnZQgZHhbF5wLl2Krg3qll1qsyYGJz4XvcNrW+MDU2IDUt2%20U7RMgwYk2RlhrH7Hhxkao8Lbq7d3ntpXXQi7bZLz0ZkQzZWdKUABbFG7Uja5Fvotc/OqHTwuh0kw%20Yr8EvJc2QNbvAsCUuOzR2qd1ckVN9zgawBHFkthKtDjtRQGuLrmwBVF+gvSbGUfoLJjw8j1G9/h/%20TslaLbQNbbnd3WrdDBmIy58GeIea4OVRYLt6qmvTUVVltyyC5dQF8G9pd+S9wBx8hqhy6DsI76r7%20tCYRcOxo/UhiGGTFzpGyaIEBs7Abut4WvanbUq6MxxJLzMfH4rE/tPFS7+Raf+eyyVaCLljFXpqT%20WTvWbyLaePkZzyxFKIXuaZHuUOUW62XUknWtN05ExWuZLmeI5Bco8gWC3rCDR5gDhGwtUukCbQDo%20TcL3VLVRZDTM0uDmua1j2nY11yC69yO7sq3w+0Tvgbie9wcx7QXMBa9zV2qAQq9tqd1qXgTJHmDG%20iRzASXfF0O0gko4+xSlWmJg/TY7oo/ORrdu4J4SewJ1tVS5JdaFTyTWxFkLfFC9u8yNUAAe/w6V0%208TnMyveMfMpd+56hU0TqAE6V1JmICXbQHKmgCgouuvttTkBt24qipY9tx4qB+IlBdbkXPX6160hO%20vtEoB0UA2Cm6/dpTkc/UlQMaInbym5+5pQ2FrlF60LIFkR2o55JBHU+zoCAb91INCVFBvDn+ECPx%20AKb30HfeqhCQIo3T5LAPjLhtDrAldTQCZY4j81/IOkjP/MsJG5hAUuKW7lpJD1k1UWTK+R0M0geH%20MuT8O4kJcIB0r0dlNyOWdAnsJkexXFybWIWlxAKgW6eEr7uwVsrqYxrQyiKDbiwxsK/5jnPDW3ae%20zqOrayttg1d0DMr/AAI1AoG8EXWtFakTMntPhgG/K/BCW/tMQS4QGAeyvF5KpydlqiIORkn8APhF%20rDW3RydK81T0xj8DsbbGZPMcSjWuBQhxRb+/pamkC6kOcObGfOF7hzmIB3ICTZbVWoIjbVJKo4uu%20ll2jqdbCkUJe1iNaAAQPCAS4Am4sFPWmCqNTsQKoB0upKJZfq1oSCWY31htbuLgF2KCQ5VaFBHZW%20vGRdXGMambbukxGSgo9zdugc4kAtUBB22p3dDfjvkg5cYncwr4Sri5hKFCpNlKlb1px50M+Zkd8D%20JWl21qi8i3UnsN66TlGzBksJIaUujVug1B7lvRI1QcZBJIy7EYNNwRUT33pSA3NAArhdPE7QahF7%20KYSNRySREqbdO4HqvWmJUJriydu+8bzZo6XVb+wdlJKBsT5cEQ8yVyuOjARuK/vpVG2MOkklIDAY%202grtbZ+ttBTkUimRvCNABcemoGov30SFJN18u3PgmznxkB5Y0F9kLnITdF6aVz86k0sZrJuUmjJC%20oVUNaCRe56VzO1FyMjlISomjc4uB8y7S1TZFBHbalsG7qHIc3C8nkJYgSx0cj9eoJtb312J0MXnk%20TMZ3kwSSEObuGy3aAiOFrLSeYkSZN/6cQNQucGwgAfidci/sqJL8TtnCYrcTiMPGIUxxNLlIsUW7%20ilczdSpLWOSFrztam1CA07raIAFpSUhxk58Ie0FFu5QCDcDrboaqa1xjInbQbJ3MUAJ0cDqoBpt0%20GlUqPVUUMnDSvcrpsdzXw7ygD9waSigGxOtXY5ZnfRUHG4OO1jRPtfHlRggFqK7YEG0bTbb2d9dq%207HG25GPT7ORwZcmB48CCVmwhzrnRwHVe02+uijRLrQQP1OZmfkxh083hIDjG7Y0Ao53+HedO32VM%20JPHYTyrjH1Zop8Z+Fx0j+PBG8ETaeBu3UKQbpbsp2RNQdZGuHzhMwGTAMbpFdFI74iGhAAU1svvp%20XUGXkMs8bHzMCzOCEN/COxL9opW5iaoUPMRtzhHlND4pGExZTCACH9HWsDfpU86pNDp4Lupn8nEy%20GucGtD0/EiEkBFH7a5pOlIi7U/8ASdYaKhsNfdenIaEDPeTm8Q0uKOz8YAdFErSLEG2tVauhVmT8%20D15XScQKABQB49+dcX/7p8+Q4kmWEloKf/TMGorK7M2tyxj5GQDnAN7kIBRF/jUlMU4AuAb8GqHt%207h7aU0oNokNa5zWOc4kgAkk/Vru6/TWmxQJy9xjDnXLSGuHYo+nWhA1jH6ELe74SQNbjRLoVKCmS%20kSMYF7ZHD42eJqjo2/hSgB1A6RrS4hy+B2tjb6d1AIYmiAmIaQWgoE7Ozr0qkxNETIY6TzGqm4fd%20rppanJLKuPkHw5jcoxF7XN2OHURaE+0laq62VGJC1wzU+iI8eHOzsdrSWPj8waALYMQlSiDurDkq%20pOjjlG34zM34p/MILijQAA5WjQNO7b7b1x3dzp75EXz2R5cTwNzY9quXxEddR9NFSoqUytbCcXE5%20bGDi7+5ZW0PHRgaXHrodlbLqYXKrOfucpe+IrC0uDexAUtrXRGhiqFjgYjsuRGMBc4o3ddgRfens%20rK5pF22tl+3OxeBx5cTjSP1R/wDmeR0d4fwNPSsG3caNpe0Y3Y/JtfkQl39ziYDNERtbKy43j/EO%20z7KGmNNMgeQNscjkfIwHY8otRupAo1Fb2vYFam3oRddakeY3OImxODTtDvCEsrlQBO1aq1uQaIcU%20MUkjvxF1yL7r/ZWrvoZwORg4+PJuftY4iMkEAIqDsQfQVLe64H1GBudt3OLm/GDqS8ptS4Xb3VeQ%20hObEWtEj7vaibrjr7AafG6kXOhQclK5oLdwG8gho7wqn4Urs40Y3srmhB8KtbZEIQdPfXQqEdwyA%200AFV1XSwKLfr1pMEhKG4A1sT+9VogIrIgtUgm7UuqIfdotqArAlrHEbxo0/Fr1/dR3G+pMJDMfa7%20/MUFR2/Q0NwIY8voniJBUp2gBdKaBIkPZJExzZG7THYgnqEXTsprIUB4jPE50igbHBpT8ZRPdRA4%20L7g4n4s0rpscgvafJRUJaEDw63ZWnDbuuI5LoVSwIY0na0OY3qhcb/1Bp+n3+oci+Ic+S6RoLgXP%20aNq2CtS1u3W9K1QV4k7FixZcNr0JDRsJJUBzrtcNoGmp7qzcyJjmUxnlLtUFpLtyblCtDiXbfxWa%20KduWPaEaI9f8U8j5X4b5FX+0xF4Gv+QLdNa8fnip22OYORuysdznOBcgBJ6dfb215krU7JGmS424%20bQ7xCyklQgLlX21TqL2EWSYJoEcQjTexCJ00FA5cENXE3OxSCAAFQIiKndTaHQKzWbW+EuADi34v%20ELdiITah9wREllJUlASSSAFcUB+iCnAszH+s3scxgY9NsW1zmhVdonW1aWPUm6pmsWcDHxXAg+Bw%20A/4STYBOutXcs0xWXZwQp54xG2VjQXOcA5riEBFtv11rxqGPkvoRnThry8KYnajrr36aVvDMWyQy%20CQta6HIJBQgLYaW0/ZUtjkTI7kSquBA2q4IqDqlOQbIwjyC7bq8EloBW7TqfbpTWQpjUeiw3OBJA%20RQL3BGunvpNgiQ7HxsdnmPKDcXBxcQutjRVDZDdIZiHLtW7SR9QDUphPuHWOj3EMBcFvr2pf3ipg%20B+Fha5rnDxkElCCgPWgJZt/Q2If0eZMQWh8ottUFAni9in665+a7I0tRoMjHb8RdJp8R0Fheydmi%20a1iUU+di5QDzGdPiup00UdVpphmzHcxxma3JkyWjf/UQ1EA66arW1t1DJqCq89u5sUrHNijR8riC%20jz/SOqoKbGsY+JrvRnp2fm+SGZKCMPFdvfE8EOdIigN/wo331hfdBrbj3nVts7TYIVViIddSNLgd%20NKyiAFM/VgbTLtaAm7aFVETRNV6e6iMYx3DaLSYBxa8lR92hF+tERkLaHG7JYgkPmWR52hoPRLrQ%201WjByiLzWSJMODG2gebkRRvVqhdxNzog21pZVwRe6dws7Fm/ukYgc0PERa1p8LALtaBe2nRLV3aH%20D4ljgYORhFfLXziZJ9o1cQLj39KlJBdlULjuShyshseVjsgyYw4RPcniBN16guS1U7YUoGupZ5bo%20f0koax75Ubta1ybiHdmtTY4zGQYuYbAP0WdMXZMbWknaCq9gF0b1vQ1LJroXvp7LOdgv/VObEGSO%20jjkFgQQAHBa0SgLidPiYMuPLjyK2UCyKdxW10vSutlDsuc0MhLhAPczcCWktIJ9puh00rz2lMYx+%20fiejbcmkyFmRRNDg2yn4kVwJCfDbt7KFGMdB9jN83jkclxO0fFnwHYhskzQUI7AOy/dVJjsyZ63r%20rOIFAAoA8mfN7j5cj5n8+YSS4SwktHUjHjJ7dB9Vc/JfDqdFmRiHReUQyXwvuC02AtqoVbUk5LU5%20Yx1HWsbtc1VYqtdoqD4hc0TBKWMY+YqOJyACwK3FwFGosiLdNKGAuSAyRvAaQunUgr2qbUkx7She%2016utuI8bh0sVBAU9a0SmhmmP4eVL5rg2we1w6hwKE27VNJoJoSohE5kfmKzc34ha4KAob3vpTVRj%20T9peq2U2NlXTTSmmGQzNA7c1FO0ABt1UhFsVNNE3LGKFNOBvZE8FgDdniBW5UFTV2vVEQaX0Hk5D%203vilI2xEDzSpJa4/Cidv1Vz81qOnibNj6e34/I5uC8kMgneI2kBAHNBCdR1rlvqb8YTo4oXOcAVj%20cNpfoQAVVO8dtZNwaSI5RciPFLd4fCXzGQp4vCQ4Eotm/i7qu1wZ8ieMe0546Fr4AVZuG9HEgFHO%20PurqV9TlaRM4zKlxo5GxuHiaN8h8Lg3RfYg+nTK8047mqCY5XzyAeXt3NJM7TZT+HvNvdUOhpmKg%20lkZltMate0qNpI2Ae8VLjMSLH9OJvKdIu0ueToGscFPbb+o1yPkq2aUyePfr88iNPjRt2OkAU3RE%20NzZfbWtt8sLlBEkU5DHAta0EtC9SnePi6eytbciHAIXu2OjjYlwBISpI7h77rSaqSNyxBC1N24gi%20ygdB109/2VVrEwMkPmCR1mE/FcohQfZ3e+jSRNaEfMlciuZ5hKtLOq6hEWtOO0zuu9xlc2cPkRUI%20Up3qlv3LXoWo52wbC0NT4nLuHQk30NWwgbc9FCAd1ggtUzmhdhLnaq2wIB7KKlQxL5AhsvVCL6oD%20fQUwa0HGEv2MsWtCgKov99NVE1IqZxc/e5XdQ5t7CyA0MJA94e5rmRlj0CIbFOqa0VBj0jgHAvJe%20Sp3E3XX66bATFIf1EbXFFcVsqAkL4aSQzbeVHPjS5DC50LGsbGxPCDYu1/Z1rq9Nctxly2tWkUL+%20LRwAToQBuK6dmh+2vTOVvpoMvsqBV+JyIpUlfZTbAl8Jl7ZREHDc9AEXdvA8JKeLW3srO62sjboW%20L2IZArHOY3a+QtClrV3uahDXfEOqhKzWSFcevePaG/KvFaRsH9pjsDoDCOpAryOd1u1O6zQ42WkB%20Cdh0FwFITULXmnZQD4XBUKf+4FF72LiepphQbe1xaVuC67wVK3JF+lKA8Bp0EexNqkBLnsOn20Da%20I3kpOHAgC4DSEQkr7PZRNAI80bSHOEYaAbFLDoQ1e1PF/KgM6GL9cwsiHmhxaHAgm/xG9ya242Q0%20YvFym+Rj7XXAc1vaNyhe41rFWSmoGH5ETWiNx2tILWkBdxLgVXp7q6bTJuBYi3BxiPmR3LmAjdu7%20e5NKUAgv088BO1w2Czo1AKEpe/fTkpSGXC/mTJ3ArqT2e2nXoKRuTksSMFJHPeSC0BEU9f5USpJT%20Qj+4Z8vgx2CEC24hRZe1en8qGUmw2YuQ93mTHfJYguJLQia0pDxHT5cbR5pDS25YLuOoQ0R0B3CD%20kw6bVCqS0dAl79KIgN3Qeile5zWRxBpPwvddLJ0621NFMx+J1r0JFD/p+JFa8uO9rSbEdCe49lef%20z5nRY6GhGDivATQ33WQnUi576x3FsYdx0W2zfDcBACACRb3dae56kQkRZOJxXHxRKoJJTotgU6+2%20nuePmPIJnBcY0h5gY55KjcNwXVN34daPMYbUWuCyPFDQyNjOh2tsUUfXZKHc5qKCxa4SaNS4JUAB%20Vvr30T1xmOoppGgG0jQHS3sNJ1EK81ETvDnW1H4UT305CBieaJsZe921o2776FRYJ++jNwxTBSZb%20n5fFZWUpjZHJD+nF127x4umvfW/GoxjIz5HQsZ5sVkzYZMaUyFoYJS1S1z3AgW8IB6V351k4IqXe%20PFmNw2NmkaA8BrthURu/pd1X20ogn4iR6WwckjMi3TvDgfLc7wW+E6uHhv8ADRchpdBLuIfkZUE8%20rJo5YW32Pts/EAvaoVAvvrOY9o/ZIWbwnEiRhx8cGWD/ACwCviOpevxWJNFtz1G4qOu46SaHcQ4t%20haDBCfFGi7nAO/qcnX99apkwop+Q9w+aMlroJJXOdEC4Pc6+8hD4XaAfsoakIrDKDksrIhzsiNg0%20sxxKFDYO9gNcHIq4x4HfxzCxj8SvkzXtvtIJcEC32kJr2e6p2495fiVmZmibleKjY3XNhdtPxEh7%20Q1FtoUqrbVNXj5+41syfc9a11HACgAUAeYvmDDjy/M71IJZYoWiWI75XAa40QNiRprXLzKWb2ZGd%209V8ezjfT784va8EEQNZ4zvdfpci171lZbUt/AwXG8+1zmsn/ACzZoK+Ea6gaItdDsZCuZo4o4p2N%20kY6NygkkITu7Qe+skWhxzHNa4tUsdoAvutQnA1TMrZoWRRzlrQPOIV/UhVQHqb1W6RNQirdAWre4%20QsTt7ADperoQOxOa5oDXA+HwgXCa9oXWhugNBkjy2MsrR4HDvv29/WnUHOoUp3xBb7SHA9i9aYMr%20c1GBzOrn7mghToi3NUTJY+kc3JxuYx8eR24St2sagsjgdyAdEIBJqORSpL43obYTGL1py2OQrXRx%20SF24NKloKjvaW/wrjvVEzo43XGMZkrlA5vmZCh7yGo1zSGnW6Ak3SyX7r1j4UNlJDCOEE5JY+Lex%20wsUiLTuUf+Jdadt3xFdac+zwxk8sM0TQ4uLhIwoC1dU61225UOF0zF4scJlG17nvXa8OBFgD019l%20RyOhVhYQQSN8EaqSpt29netct10nRahbowXeJviCOaU6EKq+6s90lBY+Ttx9g2jd4kKLtYewrbSp%20vsCaBDzJG7pT43BXNdcKb31v76dEA3OwFgaCpahQk3vZfeKpXEtB7Wxq5CCSASD8S/UhpyIZkka2%20Ty9w3kFGlU6LroK0tUogiTSPDXOT8w2QklqtHTTW4FaW2keDK3keTe2FzWkFrugS7u5F61vx8akx%20d9JSKSBrXyF8jwNSVJQ3JOtdSVDOQ5CHgu/qs0i1l8NvdQ6hIw47Sm4DuHb239tNjQRFwrfEOy3h%209lAqVCI/CCjW9twP30ZjzJGOImtlMyEuaGxkLb3gLp+yhuBbhOx795IRrQSSugTuSmkCQ9hta5r5%20CbBL6m/QlBTTAtOIHFTZvk8jKcfHcCI5gAXNeVDVABVpNRfMSsyrGpqPf2ifieRysXPDWbXBgLWh%20zTG4FzXsLbFQLIahXK7Jl7GjRo7DwMYwEBpO7xX3A6a3QV1em4Ve/DUnmvdtq6sgBS7c7xvPxaAk%20KD8SFy69K9dKh5zq+ixiozO38tSjnFN1iEW5QEd66Xpp1EMwvcCACQQu06Fuo7Oyi5JodrNBGkrR%20IBtZOC5p1a120l5UodzUtpqey2bTrlSmIznGYnjTH1PX3EsY/wCVuGxqta7iYwOpvAOwD7q8b1Gd%203tO+zQ42WM3FwJVqmxTvuqrXmI7GgmGRzy5rUJab3J+tdelJIG2LMYc5xNyAhd1DSOqkfT6qMdwi%20AnMLgjhYFHN3X0t+00A3qNGFSA4hy2Lltbv0/DR3KnqMOw43NBLQB/h6HTt0vRIFbyXAY+ZAcfIa%20JYnkFH2ANrj69Kdt0VFDMrm+h+BxA+YxNb5ILiHlACllcvXsNa23twTdasznskJMsj4gNr3FzWdy%20pbtruRzuFkNHFv4Fid+Eg7gEFtU+ynu6BC0GZY8lu7zI/MGrXA7ST3oaM8hOfEYL8YHx4zyR+Ir/%20AD99EdgimQ5FnY0YO3H2otxYH+X302G5jreSmIVkPZuBAGnstSjsDbB+qy3BDGgQg2A7OxadZyHU%20cD273ebFte2zi34tNe6lFAkca1mt9qWLvD7dKdchj0cZkADZdpGgGh26aUBlodX+XbXD060uBc90%20rgQDcGxGgF0tevP519x02NwapgUMcEK3uL2OiN9tjXOU5QGwOc0kqFO1r0C3Nj7AO6nPQF9B04gR%20xsE0F7BPwqUpymJCP0T2qAWo7RV6DrTgAAPZ8TQOhulnA6/VSyBXTjFRW6QoU3K7xBupI8KFv01p%20QJRjGY+3e4pYBELiD0PtXrR21DxEy5MWMjXFznFA2NqFxCpbSqSrRCbgqcnJbLI10kjXbVKAeBov%202ruNapQS1JacJA7kvSuaHjY6eVzIQB4trUIe72HXoa0tSgm7MqJvVbMGP9FymNJsYzypXsaDvY3w%20gqrTft+h3V8aHLdbUpcT1lxEchm4eWT9O5WBkrNz2E3cEBQ9vtrotsuuXY57+S23OhocP1lxMDG5%20TcuSEkFzsfa5xUa9ClkT99Hl3dDJ81iecEh3rxr3P/TyvDmgODCxrgrgXtj+JqflhSV+umuG5kXe%20s47Vr+nTr0Fw+r8eEOZPjzNBcfOY1HMDgN5LH9QioKa9Lc6Zmf8A7hZpOP0Hsn1rx8cUvkYMkDXP%20WUOcXlBbcyMIdpLUtrrV2+nTrc8Y9xD9dc19lsvHs+WsZQUeNy/IRzmPjZhA7PLYwZAbtb8RjAJT%20Vbio5XZaqKuMe7I6uDj5m/udOmPp+b0kmGAApL0QHcd5XVXE+2w0FeTycjucnscfHbaoK3J4+II/%20YFsttQmvRNKhto0hECHi43czgF6O2ZEXiIurZAUvp26VVl9QuUJtHqWu44gUACgDxL8+M7/92/Uj%20Hb98csOwgoF/Sxonab1DVTVOhiJPU/KQYv6cSkxNB2Nku0Egt3AdoFTsTLd7RURF7VduAkcVavUH%20sA7C5auYM8ukl1gcjPjls2PJtewjelxaxKJUXWlKUbjDzm5GKyfcrJAhPUHQlO2sWqmqYrJxocqA%20+S4NCq06gHSkqUFBnJIgHP8AAhaQpdcKNbd2taJg9Ambi8hSrPwr/V1d9VqEiYHHscWvBaTtsdSh%20WmnUGhtg3OcpR91N1INlTt91AZDOREEa8jaWtAJHiUtNrHUprT8BMHCwTP5vEzYozth2tnc8qAoX%20cASpWlc1DHZmbXkn47vXLch4LXz4gIJJDrja66nQC33Vzcj+1dDosncWfKw/qy2SN6gkP2NQtRq3%20JCFUC/yrmeRurdCly8qV2LMwgmRm3fK0ILpoqkgC1UlLldReBjOSnMjC17WSbJPA5tyOlzp00rr4%20X3OHlBxbWvyS94Vx/wAtxKeLQn2FfdU87+2A47qlu9zbNYCjmpIuhKr0rghnXI0ydpDo93ieV0uC%20B2dPZTdopDcwhqFxN0ciFelv501cDQnzGMad5SNiKRZEAstOJCRuQyb9wJDA3xFAShPZTVsCYJ8y%20KDHfM4pG02+sDra5otsbcIl3JFVBkGfKkzvLLIw3y4t3aSTuGg0N663x7VtMFdMsLJlBx97SiWae%20691NzpRZa5qO65NGdyJZJ3bkBijW4B1NhauyxQc1zkbbowkkgktcbdq1bGIkcqhxQpdydtqUghIJ%20PQWOlvb30CEt2tAcLnoncmg1qhuR2DHlmJDApYPEVuAfr1Wkw2yOSshBZseXSLtc1wtYEar9tNuW%20DYqTH8mJC5okcQXRtUoE6pRp3E11zCjf5Q2tQ30HQHW/vtTCRcZ2zmV7C9rV299rIiAotJgnBueI%204iblOMiP6szccxxdG3wmRhW8QcioDesdjqzS3kSoTeaEJZjYwYBFCwNSwcR+LaCnU++u30E1bD18%20UaK9+BOXFzrl1txKkkn23NkrtfqK5HDsoRcuLYjWtACeEqXFQABcr2LW1t8kRBCd4VUGxLrp27tN%20frrQRZ4Mo8t8byAGgu3KVBTUdB7RfoL1m+uuMfMGezeODW/K3EDvhHERL4enkDpavE5s3H4ndZoc%20ZMkZJBNtDazgttSq15iSpJ2NdBUUlwhc5247mgoFIWmmGQr9RGQhCXBUdtkXp1+uiRNDcrghO47i%20AXdAEUOBQW1paQXFZEEKgaSt0OoBXTRKGwgQyN7kDQdxsvxXFj1BcnVaTCAnF27cu0EEuUKL9e22%20pogIKX1eGw+nc10jjEwsa1gJsrkA07V7a04q3LUm5HEXPlBG0EEoFBVEHT9+tenkc0ChlZI1dayr%20Y+E2RKKClgblylo3RbrL4XG6KD99KAUijk2HmQakq51ySgAQmmkG4bMhLvAWuJB8JaLp9q3olZj3%20SH+pKgOLBqAUQAkfiNLInd3DM73MJajluUBUXuU6U4RVcxsz5IaQ2MtUFXC5B7vdTicxVYmKDKyp%20Ws3PLtSpQN/xEjSk2kFtsljhcDNLE2QZkcLDZokch09hsutPITaTOkfL7mOA4jjDg8pykf6ueUkG%20MF7QxBsU6XW1cvPxO5ybWcseJ05uDjtaCCrHJZtiQUGqG1ccI13BnBiDj4S5RckjW3REpQhsQY3R%20uQNDmsHjJ/qKdiUp7DJTWWJQOJ+JL360xMSYY7bWgKEPahU/XTQSRnwSMegI8sADcoJVfr6UeOMS%20NkeYSxxlsYa15BAJcCGkW6nomlPa9cYx3l3FVPKIHls7TJKCB5hS6BUYFt21atgVz1K6WF2zzJkJ%20eT5MQWwUo4m10076qBJ9DYejZg3iGsKOd5xczogUBHfS9XYReq4xhEz1J6bxc3FfvjDpGHcHtHaV%20I/nW5g+xyXA9MT8Z6uysRxLceaH9RECpChd1guhq7cybrZUs2DOOx3htm+JwapVdwIIuTfTp9Va7%20jF8NkRFCTNg40cULWxNc8ljGhpCEqq9pC3NVOYOyx6FuOPwmF0rsdjT4Q9xBLrAi51KXSlvuyl5i%20fDbnCInPYnHiCMRQNbE4EiQ+EBqhQAPEe+p0qbKxTQqONYHTtzN7ZWhvlwMeEIFyQ0691q5Oa95H%20Rx2ewtYs6J4Ld20nTc0htwq3TpXG9TaRP6jHRyEgOO5vUa27P50xxGMZisRzHcjiPkHh89gBFreY%20KLVLQN0cnouvQOMFAAoA8S/P6R0Xza9QyPgc5hmgaJHNO22LDYONtKycN5nRY4tyObZbwWoCChuF%206oU79aqBNEaJvmOLz/UjHgjX9lJhGrJuK5m7aBtYCia+/wBlPQUGr9NZuLDjSY0h8bj+U0Ak31sB%20pUX21Ha0idxDpFlx2KHscSXHwkA6+5ulQ1QpPGOo9Jhyuj/UOR+2znoB4v8AFfaUpJFJkN+O6wOq%202DexFX66VQaTG2lzwXPaN6koL2C/spzoGoh8Vw5rkcLKOyqEkCWImNxA3IhDbbzfULZaJ9wR7xjD%20nezK8t3hie3aGtHh1OqpRdkK1KZQ76oz5G5nHPNpoohjwgeBvlg3LibKVqbEmoK5KXSb1mxuNBJH%20ICwtcXPJ8JUDoVKiyhFIrz3RtzXU7UtCpz+V4vGyMhoc2QSAxuDGpcjqqoLEa1Vs9SLr0ZGd8MsZ%20wy0guJAS4tdf31tZK+45WpRFhaI85sDdzH7SHOUdL2rW9zbJFtGXhGMu5z9jWg+K249lgbdP315l%20TrkH/LujAD/GQCTdB0QIuuq0bnNRqGxMkEckZIn2PDSRtGjnWGqaL0+2mr6iYz8AY18gI/EXIrq0%203dCQg4sjkAChSDuTTVb05JIOXC3OxxEZSwruDutl6EDtrosu2uSLyC90RDoWRH9NDYSWBc4ixS/9%20NbS3XVmTcUKvJyxKPIDjsBBkIsHp0b9ddFiWZlc5GnZDBHthbtcSPD1G21ayKSJK4XAK7Qh+3X30%20m6gNkgKCewEpYrqf2UhNoIkEbrIgKG3WmPsGpCG4AuOupTqVNNQBIiErIPC4hjyCQLDw9ei0RAaB%20D4i9xUG4JUk+7rRQQbmkx+YUcSdQeun39KqsSIJ4KbmIQSrVtf6u2k2MkY2JJN5h8wRxRKriviKk%20hov1S1TkOC79Ocjk8cWLIRhTSfmQAK5W/ja0joHVUig6XyvDN5XizlY4jLWhroySplUK4v6u70Hs%207a34L2mRelBlZFiY6ORuwsagY4XB2OcAXNsqjr09tdqtlnNXUi5AIDIyjlJSNpKkgbQSDpqgGtqq%203qDeiI78axNmlo7VJ947SK0dykn5BNjdCXBws0I7vC6E9b9tLeDUntHjy3/tbjOPw/2qNx0bbyQS%20dUrxfUf1e07uPQ4u1pB+FT+IpoLlfdpXmpHaK8s7QNhJ0QqCg6K1DQ0xBCKVxUeEDqbWdcq1bWtS%20KQf6ctP4UVVv3NJJ91J0CkCwCCHElxBBAFzr2+1NKH3D9Aw5WBrgAAUQdSE0XdQkCYzO7HjcxpcW%20l7iGE33HUAe69JIJ8cY8DO/MYxD04WbXnfKNS1SB8Xv9tdXp03cY8t0I5dJxGe5xAhLjt3DQgg9/%20f19lej5bz6nL5iCHB8k9u8xRgXCvcGhAEcL9lJWOR+Yht3DZr52wCKN75Fa3a4Kq9qmhWti8xaiZ%20fT3JNlmjbiOkML/Lk2EXelwliKIcD8xBf6U5NCBgPBvu6nUIi/XS9g99ug2703yLGlzsV7W6lHaD%20vC09sArrdC0Hy99Vlu/9G9jSGv8AMUIhuCVTWsHzI1XE2IyfQXqKCIvnjTtLnNJ7NAaF6i0fktZl%20JhOnwxksTbJIBE8k3AaVde/vrVQ1JK+1vqEHueQ9xXeSh1KDpRugzkEYL5Ym3O6RiEaXcPq1oueY%2040PU0O3Hgx4gGjZDGwq3b+D+lK8y5o6UqAe+N0hkZISChFwGoL229tTQpJYqNvkeu9w2oFYQSgQX%20P1VLTGrRiSZ0QIK+FBtXo391TGMY0KgMSOcGlSjblpRbjVDZTRGPnjsDDk3FGtO5w0Xov4r9K1ss%203ZYx+pF10ZETLljxYJJZCdyoNoRSFs1pIV1q6NitWMY9plM+BVgSvlGTkIHzGzFPgBA8IUC47fqq%20W5fb3jSI+WGySIGhGJY6AgqLd1TBaUIvPSshdhZTC/8AyXMc1w1BcV/eKrjJvN9+bJHaQN33dGlg%200hNda6TnMj6p4nzYIuTxsf8APw3fnY56xk+JPvoTHcirhdE//JZteB4GlG+HWxVV2/VWzp4GUUoR%20vMnMcYc4AMkBa5iNO3cp1Xp1Sm8xlxjTZsUMsUHlzvY5HY0ngIJTTW3XrRIRoRH8lGIHxSxywOcX%20eaCd1zeyqRuWoue1TmO21tlc2Ys3eZdtgWEAAgEW7Dbt7q887UhZyw9Q5zihG4m/UKR1NKAgAkJa%20pbtO4EgFWlw6EHsAT7aPAEiXxkn/AFXEDiQ4TxtZvIt4mjxAfEVX76EqoTyZ6RruOQFAAoA8z/PX%20Bdm8l6jx9gehjkjTao/JZuv7q5brvvOmxJ2nm2R2+MEHeSDtIsqnqi/wrcgGOHsjIFkQFBYn6u+k%20xio5PLcHBAAVJQmyUQDdKGk4LMdi8jHI5gLHtDHWCqRbp1qbgTqX8j2x8vFNH4RO0xuaQijQWPZU%20eI3msYknoXyzwMkLGJucU0Psv2UPqCUkdnH5Tsd00IOUzHUySMCbWiwKG5HWs9xaSRFc2N+50IO9%20lxa3sAqgqAxMLWuYlwV/4gD/ABozHrjGoyyVjxJG27YCjiAhWyJZTrTrIJdeojN46GGaB2WTC+Rw%20IhIS2o3DpRvEuuEN+oMBmU1k72l7GkohuLgtJJSy0rLoHfbQDPUvJ8twxxJZf05jd5Tg1bkXa7rY%2091ZXcatulBvbUCNwigYHK55IErwA0krtXvtWOb6BNCXDG15aQGtLvCHkgAJ+ysLrmXEjOZCyafHL%20Hp5LT4UAsTcIp+utOK+E+4rrehEdA8PaQ4jYVfe/huewdU0rR3qB1Joa1jfC7wsaiFSiCsLmmyqi%20nAEAdRcHsPuqEUNuiQlzCjiSSo3XKBQOmlXJLQ2XRNjcp3wAEOJIIUWI9lqpZkuSt5Lk4omEatsC%20WkC/Zbr91dPFxt1Zjfft8TP52RLO8OarYWBWgKLaoPurt4+Mwuukaa0sYS1o3L1GnfWvgTAlwRWM%20J3EoDqCV0pSsgGiqhQhICe7r1RaOw/EQPFZLv2hNbD+VAQ9AAq4tFng7nNI7OhoBkyHAdFDFlTtL%20Y5l2Rp4i1oRfZfsoRTtiJF5M0cjFcXOEYADbJb8KEAJem2iW+o0IXeWS+M7S5Avt7RVeIvEU5Oh2%20tapMYVCQQbDrSpoNDbQx7XeZdrPhb7ToiaGpXUmSdA1yF2rgiW3NptlKha4eEGo8/GAC1bkX1060%200J3Gs9J863C5GNs6nGejGFN2wuCO2tStEqENuS+5/iGzRvysTy98aseGoQF8Ra0n4igVzyNbV02X%20rJmNy1MTkGzWIqXMvalgVt2BunTWuq1yiGOgs2vaXBzULHNCEIHbi3TsP00oliWlYx+Q1I0yRSbS%20S67nqpsAfFond3Un3BHsvh3bflZhO6DiIl1NvIFrV5HPnd7Ts49DkLMhtzd5FtwKXKn4Qa81adDt%20nGPoMT70+M+YdEG3oEOnb3VI46jbMiUqC0NLSLm5RFAU+41WQtoB5rnDd4V8IYCNLai3i/dQlFBt%20TUMtDEDn3NiQhubAG6XF6mAkLftc7cOiE9U7L/099PMGCTcFYCpK6J2fd3ikNmO9fZT2uwGAgxFX%20v6W+E/8AmHdXf6K37m9Tl9S3EGex3Y7SY3SGFSsMoKBB8LDcgIep1r0lfqcBOjmzIRuL2TAEOdIQ%20CmitK62VB0pN9UG2R1mVjPlZKyFnmREowANIIF9vu6UrrqdB226ZkbDhim8yWOd7XSP8xGuRFtt7%2071cpIRJdG9jQw5UjwRq/QgEItr1N3egWjE7UicGSbXFNpeTdCNVGo6Gp8dSkaBnqDBEEbC6TzWRN%20UNuSiaJb2V5/+LfmekvVWrxIHJ81juxC52+7bF5RABrpodKv/DeZL9Ylkcyzpg+aSVkbo2b3FU8L%20iR31u+NrIy3q6upFxoy8tjb4WF6CYqjVKKUul6VYIXQ6dw/ynhbmY2VnZ7JMZrmyCOFvhcDdviPQ%20pe1cd3qDo8qTqZmikAc1u5pHgAKNAAtpXOjXuRJJvImARhxwN25U2m+49bVM1oDfUejy3kFvmAxg%20AAhQje1SAoXrS1BUAx7SGlw3aAmzm2t1+papPWByKaXuBDAriqLoEFxVWWNxjHf9AucELOyGccx3%20mMMkzgS2NgJkdbsv2VulFDBuSHszpJGZuad8ieCELsjahIchJC/4qTubCAstsO1rtpuQBH/U5uoX%20t6r7aHbFC05yxjEkUNe07HnbEbGVoQjdfaSutLaJXGo9J4EbOKyJyAx8srBGSNRH4htCjsq7VCJu%20dTZ4wcWrIA2RUKXv06XrZSZITPADFtIDrJIDq4EXCDSh2hNDn+VjP4jlXYez/lnDzISPwtLr7j+L%20burS3H4EsjShZRMxwaC8MkehcBtKWvVyKKFlkRuMUbgHEyK6MgncjiCRuCre3Z9VJOsBBC5XIyxh%20+VLtJc7cVaA4NYbbnWG6ufnaSob8WZUtD7udp3oQvv8AsrjOlkiKMOG5rlaimyp3dvsv3UggW6N6%20kPc4EjxOUOF1JN6JxjGofIkcc5reTw2FXOM0W0FV8TwevsqrW5JuVH4Hpeu44wUACgDzb85m5R5n%201M3GJ81wYdAieSwHU9R0rjvcXnVZ+080SSRIU+IHxN6rf2da6UQ2hEEouXkoSfEb9n2Umugk+olm%20VE1wLwZLE7PaNfZ1Whoau1fxLjAyW+TjytKBpB2hSQiW/ilDnImDS5uYZXQSsjdGGvAR4ue8hRr2%20Gs5KeMY9qLWCaVmaWODQZYyQGr0VEX9lJrqCLL0FnmPmZIXjaW7mNaUcC1VO63b31F66UHbcSPUP%20p58HMNdhQgHJBd5DE0UWHVO+od0ZmlSmjhjbPLAGPjnsGwkAP36AbTdENXMiTihbScZj8DsneyOb%20m8jxxwPQxxNsA94/E4qlG6c5GjN5AOU/dLJ5kkkm57nE7i7qV6juNDgJgjcfzHHvy5uKzI3ebI58%20TFAIXadqJ3j6dXsio9+jKaSKfj25b3lpyhM3zGalGuVXduug0rWN1DCNtYJzYn5UMc0aGRzQSo7E%20dbqlq4b1scaFq6UCbHnnnaWTyQsjBJcxPiGgIOoPfSV9qWRW1kpsrjskaBdyPW1hZdL/ALa52upr%20mIBjmSUOsLFQgI10NVlQGxx0rd4YD16onUJUaD7AcYHI1gLSSHE6BEuh9tKoPMZn5INlfilj2yQg%20HdsJJDvYCTtTrWtnC2p0ZD5UVmfnOicS2OZkTFWVyo5xCAi9hXVxcJldyJFC90kzGyvJUHwxlEAR%20VJPavbXdbbBzyJAeqbtvaLJ0VKtsQgPYF6E9SNbG16lsY3uQWsLgntU2JIolwMViYeRmZTMfGjLp%20JFARVA1JKLZdaTuhVyHapcC/zMDNaYXt86B6B9iFGqdtGagMmXeLk8XycXk8liMhfjuMk+XEjdwH%20RwGl+yoh29zRXznjqQ+Uyf1c75I3tRyNiIsyOMBGsAN6u1UIbnIrtronDxbWhGktOhNgbVcIhDrg%20ImuaHFxBQE3Pu7qG4VBDUkgIG4goUKBD7U9tDAexsZzirmghSX20A/bTBFpx8TZZmXDWA+C5AsoK%20XShuB6FsNyt23GrQShXRAlVaQyVjYr2kOMYY1LEq0IT1HYe3rV5CLrjuSkZi5EEcjRiQgfqpXeJW%20g+CJPhtqOtWnUlqhnc/IGRPLIxh2PNx0DUDR70rrV6to39xntbroPRyOGx7rlT5L1I9+7t6CqbTM%204YnbujIdpZHKosuu3so3IIPZnGOLPlZhkHaRxEV9dYBoqa9F+2vH5tTt43lJxYPBJJDiER/aevUX%2091edmdr+IjcVKjddS4lfEENuxbaU8YxUUYxj2inWYjh4bhdNO11DG5fzE/lt2qdqWACoi9lvbRHU%20FQDpGIHtBcn4etkvYpddKXiMIuY0lif4nuTTrcUBOYRaHCwJ3A7utk7kUXNAJHO/WWUc7mZY4pNr%20o2hkId8G4NQ6XBr1PTLbacHM5uKLDzGPeYMhYZ2fEx1yEs43CEJ2Vu1WhkvgS3vy4Gh3m7Y3BAAQ%204XVAQdyWNTLiA2oaGWBk/nTOaHDVrQL2ALi1LACi7kbWRSsQjj+SMd4y1wDiwF6iwcUP7UNqp8mp%20Plluz1AqB8EYB+IBy39vd1AqFyC8p6Dg5Zsq7BE1ANGEq3UOSq81guMW+aSR4cZS1tmJtDLaICUT%20u61avbQtiVAmQYhgdK8N2N1kkJchUdvW1OrdWFFkjPZeFJmPklYCI4tySIA0AEjd7e4Vf2qhMtsh%20YuIXZIY5L+BpFwpPXpt/ZVbUG47lg/lYuOHMAayJrUaOgCdnZXz16q4PVsoiwhkBADXLYuWw16J2%20kUSCSWgcrY3tD3ABoRwJSwPRbr2UokaaEgODdrXloaCqn4dwoYNuAMat2g7T8alQQLBw79CtXba2%205Fc9BWRnw4TkaEc4bWPXxOQaX7e8/fW6oqYx+Zhdc3jH5kebIwsVgyslzWSjaBIWq4kgKAqkDupz%20jGPaGQxkchjeS58RVUDBYtK6FKTjHxGkyJPMXRAOAbI8eN9wgFkQIepuKaUPOGXRyMZGZ5TWh7TJ%20A921z/iSynVLChUxj8yWdM43ChxONwIi3wv6oosDb3DSrShGbdSwa5rbE6aOJKhB262qnApCimMm%20521qJr1TvI7aYkZz1Xxk0+GZYgXS4jvOjctyLDaQvUL0oThlGTbLEWxfl7ZXSNDoxvOnxNC/8Jv9%209bLH0x9TNovIWs2PMD3qSQ7GlVoadUtpa1HiJlLzrd+a6EOa0xHdJEepd2kapXD6h1hHXwqEQo4y%20H+NzXRNDW3FwbGyap21zs2H43tDy5wTsAsEJOg1vfvpAqB+cSxdq23EIEBRVpwIdwRCeVwy0bfz2%20IBpZ7Sl+6mgdF7z01XecQKABQB53+ZJkd665ljmpG6SNoNju/Ij11QXSuLlf3M7OP9qLf5S+h/SH%20Kwc1LynC4mW9s0Ox0sQJaDGbX0AN7VtwwzPmuaaOgt+WHy53g/6awA4In5TS5RcXTT+Na7UYK5lV%206n9IfKj03weTzXJemcNvH4IDp3xY+4sYShdtAVAEWnCHufUssH0F8tMnCx8zC4Lj5cPJY2fHmjY0%20te1w3BzXewrQ7V0E2zlf+5bguD4v0/xDsDCgxC6aVj/JYGq0N8LU7PdeovSLscyccc+R36OVW71G%201zhqUS/trPMtzoT/AE2yQesGtA81z9u4NHQkkH2BaLshqjOmmNh5WfJaGujjAYJHJ4TddvcgrB9t%20ClRSIdx+L+oOfEyJnIOYWx5EgCNUa2PZ1pjn3mE57jOX47K87LlOUycr54+5O5NKG0PwKqQQPBeG%20k71JlVD9+q1Q56md53Ec6WPOhbumika5x2jcdpt4Wpf2VVjUeJm8iXy+JNyJgyYowxswMuU5bmQt%20ALS00WXpeCLus3VQvC4/NOQ3GfA6GFzVx3hN42hdDZHVV+y5SY/dYxbW8U2SLBmnyIsiZ+4scxwY%20S2/xG37ENc13C9CXze8uW+nsRzNjpXPBRpV43EkeF1g0BfcnW6Cse6WMYipD9TdOMeHVDrfTeIxu%204eOMLIXbUUbfCXFQAbJYm/uFDbyjHz76aGf+RdDr0U/P8cogR+g4hjfMla0IU279pOu5CT291XE6%20Y8CvMumMY9vgQMjm+FwWpJ5cgIcd7SZCly0ORr7DaD9Fq1wuKYxjoRN2eO/QpH+pnPmdPi4bBCC7%2082Yhsd1ajQBucNvd99a+QoNIbeMe0pcvks3LcGy5DZYFTy4wWsBXw7ibofqPWt7bEholf6dz8iLz%20cd7Jnhoe2FviAb7O331L5Uszby51KSfzYXuhkBY9ti0oUIsh/fWk6mTpQZddwBALeiFPv7KJBiHW%20UaDQ2KJTmoNwaLgOSw+I9P5+Zv8A+pZX/L4zbFzWfjceyodrbXQ0taS7sRjcDJxvHN5Tloz+oyGr%20xuD+N6/+tI38MY6dtVTQlJqpXT5QbC/GDvMfKjsl5B+IdAmoBNCUCGhKWOaXAuYxfCeqjqtU0IQH%2047hIPKAfruVGqqodetCQm6DYJDyUUNJIKbrr30xQSo8OaWQNhhQtO0N9yop7AKYQWsfDzhjG5B8v%20cWHQj4gvX6GlLzGaHi+Bw48dj537nhrXeWB4g9xABXVDrST6jgnskhiErYsQpHvewyMFnAI1C7VV%20JNPeoDY3oSX8bI+KVo25EUzYWMYoKsjCuuE1d2VW6tM8e4SRRZXG8hi4LsFjXNjfK6Z7hq63hDib%202Ra24ea21yyOSy5jcfEcjLxb5wGkPUbCVc0AaEGsefkV3InodHDNtjK/EzT5wCo0KrOx1gqEDq6u%20xNt4wjkptJzpmuY4keIqe61beGMdDOD2dxdvlRhpYjiIzZP/AGB7BXmc/wDVPc6ePQ4k528NcQ9C%20hF+jrnW+orzZO1F/6b9E83zuE7NwZImxRPMR89xDgQA46e6tbON3KUQ77VmWw+VHqhgJLoSnVzj7%20Oz60qvIZPmIB+VHql1mvxn7RoZCCqkaob0nwMa5bQj8qfVrrh2K5Ev5h9qKnYlJ+nuDzk82UHqD0%20zyfp3Igx+Qax752vkjfC4uA2m+466utaovsduZdt6eRneQzP0XHZWbIQXQxulAGiAFNCvWlapaQ7%202oOVTyZE8TJnXlcGuKqPzHDcVRdSlevbCoee85DjP6lmxzWSPZ8LHjUm3hoVs5E5BiSaGN5ZEA8H%208tFs8f0m1KslSoC3tfJGS0bmm23QuKEp9dDdMewkisje2Z7BZocSTYgrbp2LY1UahJPxMfGMbQ8O%20bPucDK4B0e5VBI699LdA8yY7I5CFoijwYslziS2SORB3OQ3FPeiWmKx4uVyJ/M5B8OPHr+nYSXJZ%20V+mlPcCtUDmVmcXv2ta/Lc2zYwdkLS0orkS9VLoRtIeXlzZLHF0eyNo2xRMO2O2riEC2NWkpx7gb%20oJ4jDlyOSxo44w8ukaD13AXKd9Plui0LF9x1lrdjNpcJACl7D3jsAr551Z7ECo5H7Wixf4TvW57x%207etBMMeZO8bmo9QFc5SQUF0Cr+6gNpLxo5J1ebMFnqL3tYW/D1+6tLLGzNuhIe1rwwM8DE1RNO21%20be0lsqYTDPNLIpej/A1wKBwCEI4pb207lOf6fHHwITx1F8jh/qcV7T43jxRElAxx16m1J98fgDSM%207x2ZJJAzGlDWvaUjIbsG1UaE/fSVR2snfrI2ylgcR1BCiy+G9ioCfaO8WksYx8C2x7GhyJsrExoY%20w7GkeI5z+IhyAoBbRFPbTM20dMzA5jMJrXARucjrIAgTbc61bJ08ReYUMaNXeUa3q+xQDvSncJIP%20Ga9rB49yhSvxdhNqEgbFzxskHjuCCFPS3Z2dKbQpOf8ANRjAzhDkFxgkf5kDQod4SS5qdQUq7egm%20tSyE8MrxJivZK1zUjcCGlqGzXfi10QXWqgRn8/jCeQkyD4HvHiJFwQbjWwtpXF6htM6uFqBvaUDW%20sACbQhGnv1+mlc8QaCfCXOLgB3i3cqBemlEFSIkQObuCg9CRdwGpRdR2Uh0H+LeP7phkAbjkRjeL%206vaV0RfEAfortzFdMPwPT9egcIKABQB50+Y8zT8wOXjcDsEkYKFSnkMJPs6Vxcs7mdfGvtRufkoG%20/wBu5chy/nxuJHhChqLoU0tW3p3RmfPmV3zs9QT4vKcRxUXq2bgmZO/z+J4rFOXymWXoWGMI7Y1r%20gb1uYFR8kfUfP+tvRXrPg/U2RNyDMOafj4JsxgiyPJfGQY5mjbtd4b9l+ygC7/2x8tmch8o8FmS7%20zHcdkz4MLytooiNgUdgclAFJ/upEjvT/AAjWRl5fkTWH4SGhCQDqf2VF7Sg0sdDhuM4+TjKHNDQC%20HK5VJQnt0Fc7uNIyJnDZGQz1SySIPa6MAtcG2uEJUjsctDiBrOh0LjswyZEmCW7Djq8MLlLw8ruI%20PhN9b1naXdb7i1RsjS4AFqOsVALUVT77005xj2EtRnAH4zZg2OSIOAIDWlF9tqnvjH6DroZTn+N4%20CPzJIsmOHNDSZsaIh7XAIPEBpbSk3AZGO/R/oIi7AgcW5LtxzMgOeWkEn8toKJ0v3Une7swttnGM%20e0bw5OQ/QZEPnbstjtzd4Aa5o9iWTsqdqmYOhUWMfIht9RPx3/p8+ItjIHlyMd42BSLHp2dfup22%20SqGbh0x8R6V3MZUTmY3JNzcWINf5EsaTw37EVO01pY10qYXcMin+ocDMkHHGSbjeSaANsLS5oedp%20HbqvZ7qd1sV0xoYu2boIPqmD1LiY8s0WZMYYSxssbB4SoPiB7EX2VVlyZT4mk2ZBk0roy6bIdISj%20tgO4lyancutdMQSrV4kkcjsgc2GRzFUSvsjv+Jo++lBSfQhbjJIXSgvJX4nFb9VvTZL7kt2PL+lZ%20lhv5UhLBo1CCtyU16JS3VLSGMefIxJvMxZnREghyH+oJotDSegshhxQEyFVKvJKFSnU9aapkIbUo%20C1vh+FSFul0+qm50E0ORYOZMCQx2xQHSkIAO1V99NIbTJeMGYcolaWSTxlQHq5itHS6H7qIFlVD2%20VzuZkTT5ckhmzspBuWzWAaAaezspbegSyDGroVN3B2oKle9ftpoQTC584Y8tj3OQF6WvoSmlENC8%20SVFgQ/ppZsh/lyMckcSqSO091VFew4oO8bjumyTiMeGue7wyEAt2ArrSuvaHbbLLDy1ZNJBv8mIO%20JNruJRGkarWHmG3k46mi4PCE/NQ/3R3nYrNpkaz4A1zUR4S20VndytqEa2cNaHQ+B4HExcd8zYWe%20bkFrnNcjg1rT4NqqQnYpqVe2VsSpGMfkWMuHjSBwkaC0ou5iAdvhK7V9tCfeHjCK2ysiFJ6e4xzE%20iY6GQ2jMbiCE/wAPei1VtzSUMm7jTzK/M4DMa1I3NmGha8I4a23dTaq87qR5KKOaM47TFPjmFfCH%20xjcCT2/y061aaZDsunKSjHpzAyD5sE0bngklo8JanaK2V9yoZO1TUYn9OckyN4gJlOwhoCqqWAs5%20dFrez1i1xjwZm+DoexcBpj+UuM14Qt4aNRp/9OK5uVymx2KqRwuJ8m5pe8IVaXOs1bqiXXvFcJ2f%20M7N8pIwPTMrR4gMkr2ptACkD6a108FbTn5czA8j86nemfnV6k4v1FnzyencbCidxvF4sHmyPyX+W%205zow3xLtc9xVyJetzKC89a/MtnM/KqT116A5IlvCZUeVlROaA6SNjx5+NMx4dtVrw77qAOj8BzOJ%20znBcbzeM3/leSx4suFrkcQ17Wv2qUU99AHN/nMz/AKpxbVVjYJA5D4nAFqaG+nYt65PUvI6ODJnH%20/XmSI/TWW1tppXNhDkT4/eutwDT9LbN6HzURgYVfiRloIDow1QEJ2i+0J39QK9K62pwp6iDC8OL2%20uBkabnUhenQ3qUnoOUPGd8gbHJuAJKsdoE77WQVVomug+wxF8bQQNx+L33uLX1NPbShMkZhidlSK%20p/MBN0tbcAiLVLIGSonRPxXtc5CXBy/hG7S3abrSay6DI8vIYETvLhHnzBXEDtKrcWt+yoha5DSe%20gN+TKEkWGM6Qt+IgFHKUtr0pqFoJomQYpiAa8NYDZqJrZbHXtK+6qXInrjGRO1icmJpAS+7xOJsA%20NxBCimmDRf8Aysxon+sIp8h4ZFA0mJpCAybS3rqajm5El4lWWydPmwYsgyS4zm+F6O2Fbtu7r07K%208u7jUSjvV5BZGXvZ+XtLrkpcIqg36aGs1a5NHclnjGhJg4mR6B/ga5CjtXWBI11Q1pZxTmS74LOO%20IxsLVJe4FQQNpIAHt0roVsGLvTc9Bmfa2ygxKAB0P86Owl1KzKge2f8AVwOG8eF8aqHtHTWyE1Dt%20xjHccjE3KYnliN+1jnuIAUh3VbaU01msx54/UzvOh8OS/KEyRSn80xtVwt4dxv0APupQS5WYePJH%20kQhzAVcAHF1nN9xBJpsq240Po7F3c3iQ+YXiJXq7WzfuWqioNs3+fkueIBIdqPa1yBBqbWptszX0%20JcpY5oBRG6O6dh0PXtq8yWFteWBfAUCWH3ChIGILsnfukaL3RpHiB1TspAUvqHjpMnHEzIt0+O8O%20YLbjfsK3vTTCCnEcEspM+OMaUNG9yagpt/MsPEUt21suxm5Kff4ZN42lkhJuSSFACr3u0Vf28/ql%20STo4HDGpGMDSAUYQjmBSSAB29EuK4qnSIMTdyogBDSO8AImmpNEiTYT2uLChQoCq3REBH36UDmRf%20FMd/c8J6FwM8WgAAIeLJp36U7VWCXk2eoa7jkBQAKAPNXzRja35gczLuHxxEBzVALYWdVUnu6a1w%208re9nZx/tyxj3mx+TPOcRgcRy7eQzosJrZ2bHZUgjUMju4F23cATe/vWtfT3LUz5020xn1pwXoT1%20B6wwfWHDev8AG9P89iwfpZJ8ebHna+AKdgZI4BpF+n7K6ZMIZVYUPoX5W+j/AFjyPE+sWc3l8pHJ%20PHDJLBLO7LcwgIYzucXud4j+6iQagvvknm+ivSHy14jh8v1Bx0ee5pys6L9VB4J5SHPaXNcnh+H3%20d1KUEMqfn16r9P5HFcLLgcpj5bI5pd4gkZK1CGoXo5B3W1rl9VbvhJ+404pOW8VnNyMzbHhOfmFx%20/Kf4omjQuLQE29i6VyLhSqblnlZgnjkZBkQjKDmwZEkUdwD4SI3Dr31cDS96G8v0/NFHJmYudIZY%20nbGGQqSyzS43uiLbU1jtchtQxyuL6swponMnleWA/AjmO2lVe6xBQilLXcW2lCvy+V9TZDDuZIwT%20ACIN3Nd4QpsEBTQddEqN9cY/QiHr1KCR+Jhyl0rX4jnSGR0L3OUSoo3BSt7a/VWtjuu13fqK65/L%20HyNBx3qnFxIpcZsUUkeQgcCSjXhQoaQ3ce3rQm41FbyXZQUPIGHHzY+TbMdloZoCCUYSm5qKqELW%201t8mtvLXGPkROW47Lnyj+niifNjo1sLyVdu7VG32VVl1sdi7+zgRlyTYDYuQysWSHIYm6bGJcGLo%2019xamlOot0aULnAy+N5VrsifEG9wBhythjkabAOChTc2Ssb07Ncy7brXj4lnxvLSbn4ea39Q2PwC%20Z7QGzt01RN3iJtft6VCta/Ad1EZ3lvQ2Jl53/TXR43meMROcTEFuintRK7eK9wc3JaUHL+jee41v%20mzYzpIiEEsXjaCD0LVCL2eytt0UMoTqikD4GsVxIeSR5Z+Idi9EPVDQEofyspjMZuJGCWbBIXH+p%20yF3QWulJW1FokiI0zuB2NLkOrQShOoUDrVASIuKnb48qMxxO8LC47XKgOmtOPeA61nH4UgMpdkPF%20ywWaFPXt7eymn7AlIbm9QZIdJsDWtdbyw3wAIlmEoSetLwJzK9+VLJudKVLU3gotrBKcTqEe8Xis%20ych22KMukQDuAP8AV2dlPxHtehYTsigxGGQxjIaELGFXOW+5+2wQdaJCI8SE+UvcwOdYo1dEBBNM%20nMn4kE7sR0JDjA925rg1C4C91ulqGlJS+BP4fiJZ8iUHzYsQtu4Wa5rrIHdl6w5b4N+OzrkaPH4d%20oxBEQWMiafENAAqaJe/RK5ndWrOu3j6lq2FkHFue2P8APku55RX/AIR7U69fsFJI0tUWlzj8rmwH%20ax5DGMA22LRtPTchH1VaSRo+NZFjj+qEIbkMF+jen9S9n2VSVCHxdC0h5PAySHY7wVKXUG40Id4r%2091LLP2k7Ghz9Q1pK7mXawOcEUm6DoemhpadZ+ItrY0WQvb+ZF8XhvqSoH/F3rRtiqYNTQhZnDcHl%20sIlgaLuJczwEOU3JBKoRfT9tPc7fDuZ3cSeZTZfp7PwQH4eeSwAhsMrVadw0KElAO6tFyTmjJ8PQ%209M4wk/7Ywh4ST+1MDgL38kd3WtbodlOhyNNXV6nDYMRz4nB52vIu1lh193Zc1wO6tDtodh+VTWN9%20OShio3IcASOu0Ig09y/fXZ6f9py82fsOVZHqTG9G/wC5H1R6h5ris2Xh38eyH+5QY0kzIHFkTg4l%20jXfF5ZZr9lbmbZU+nuNzsf5SfNf1Vl4MnG8Xz7pJOLxpmuY8sJQShrhuAe6QUs0Js7T8mMDIwvlR%206YgnBEjsGOS5KhsjQ9re5GlE+gYGd+dMjW8jxu5rk8l7fMtYE3rj9Tmjo9PkziPzAklbwLG9HTtY%204qu+6t6/4lrT0Ti8PU1tMZxrt7fJJYp/yzqHFE06LXp3purOFIklm5+9RtOoOiIQvZes5Ag58b2x%20sc3aTvBQBV2u7B9ZNNPGPgNBSZox3tllJY0fA7q4A2aO/rTdEJIp8nnIYXSSMaXucVAufr++lvY0%20pJeMzM5JoeTtjUNEUYKuIClTQp1Y3KyLnC40wMDGxNBA/EFJUamyuuelPasYoZtyT4nyMI/KbGin%20eTu2i/iJXxI39ndTVqHuYJMmNC3/ADNnhQoRuRLBRt17P30OxYxj2DV7IWc8+UWgpK9xZIAfwgAg%20AXsDV2WwQ7jUejcJkWLNy0riI4JEY5wso0cU1TrXH6y9ppI6OC3U33p3PbNF5srWRzTyb4WRkjeB%20+Mqh79FFcnH41N7lBopPKY5TF4bB7w1DuHbf76vKosewSZB4XOaJLK8KSECOXpdOtabhbffjEDWR%20j+SVZIZGn4GE+DaPiOvfQHwIGRLFG7a923zHbCxwVxBCKACAKmBzDkrMvLdFkEuQvF/LHiPhX2ik%203OWPzGrXqUPMTRySRzQ7v1DXbw0gjcwEgC3uFGo0o8CPBkfqcVnmO3ggtcC0quq9OlSwI0eQ3jxI%20+JZ3TAkPJRoFlQdu02qlj8MfiQrYoa75ZTtzs/JkTcceNzXONj4iiN7jVqWO5nQM9jhtjJ3MsCXh%20RZEB6Ea60dCV8SUm6wKtBBG4agJrca00QPrqSt/wnvFvvqgY1MC6J20NJT4St0+ugCLFOZgRIxHA%20hrutiAd3dqmtSmxtLMoMji4osxz5RJMyQh0TNxIuVRt9O6trbiLlqsYx0M3M3/qObG9rgzeoa9uh%207iNb1n6j9prwfuFPYXHwkNcPgAslrXF685PsdcIaeyRwB0QrGLEr3E091AEhvwt7SSnZZFvfvvTk%20UD3GBeVxCfEWzxA7r/jBS9/sprMluh6bruOQFAAoA80/NGVg+YfLhwO8SxbSfh2iCM2Hcpri5J3d%20jq4/2oyWVHj5OPJjSOaGvb5RS6NI6E+LTWoSNNxx/MwfIyJYAxvm47yQNuoW1x9OtdSyOdqrjHYL%20HmhlLnmJrdy7joVI6oidaboVa6C442FyeWwPCKbfFra1CJb1NJxfHHLhjwnMbixv+OYEeJrksBYL%20btrO5xUtVhYxjuX3J8pJixQ8Vxx8rEc9rZpGo57g0dXe6/bWdq11Laii1I3pueVnqPIZAGhrkPlp%204UF+ulm6p0p35KRJ1zOkxvhmwHsILXTMIkQAEOcnRUX9tYXIpsfw5pH4cW9xb+WPM1COAK9Tant0%20EQeVw8lxjOO5gdtSYyW2nVpF7JuqLrRqxGYz+Vy8U7XQGZocWA+UpUKCWyPHU9vupK3tU02KKEnE%20weNyw7ImlgbI1u17HNKm6aW+nvoYO1RiMin5v0tjzEwRkRukaXF0JOxSVC3NO3kSclPjnIr4eG5P%20lMdmPE//AKhjN2gOHjezqAvxWC1bvnMV1j9pFzcvl8Jm3JxXSsAIe1pcoAsAWFFS6VFqtbzgxdjV%20cYYfH8zHnFDkGLHiAErpmFGMABFgOpA76OTi61JSbHNzMpoLcgSNYSWuLgWbiqmxChL+33VEO3Ql%20tqmMfAl42W5r2w5Hjx5HNEYeNviKFEGq9K0t5JK3yqlby3q71BwPJzYuBKMvj/C+THnbvI6oHWFq%207uLklGV9qmdCfBz3y79TxuHI439r5FoG4OIDC78Ra7wr/wAJStHZToSrmnUHOfL+bKdDk8V5EwlY%200MijV247VBLh8JTuqLZQ7nORis0cjHI5jmPx3xJG5gCEbLAKBdU7a0TFdLqQHPnler5HySO0LiSQ%20B92l6CYYDxk8ku2BriEVjnjaDZUvbpShZjivYaPGzhpeoa1l3OWwAvVxXOoq5aiWjDhQqZXj4Toj%20uvU0nC7iyH5cmeRz97PKa4keUFatkK0QynI3BgOe5oex7I3Bd2vd20RAO3V5l5henZC+Jrw6TzUd%20A9niVxuRsGtutS7y1bXqX+HwUkDnfqw4PJ2+Q+5bGNBrq6sL+Wcjfj4JqzQY2JGcM47mbWKdjdAC%201LnubtrBnbbaojQU4vlyf00B2MjO5w7Om09DUNkuGx7Nj3zY8d3FztxYDdBo76qtJlbh1weE8LiQ%20vjQlLEhAbatCXppmu6BGx7trwEuiG6bujh11K9b0ToFCM6PYjo1YQN4cvQ+zvPZfuqpY2P43Mcpi%20lI5g9jAfC4B2g7NDfrTTWeO5F1hc43quAA/qscseAgLCQNTu1Bp+0xusu0LaHL4zLDvJm2vBJ8t2%205qakaixuvWltSMrtyzDngDTcgByqh8OnRNAU0X91LMU9jvccZHy/ZGAhHHgAD/4fRQK6f6PYcd37%20/acQcXsAQbgBaQdE/D23J1rhSOmXjGINJ6d9d5nAce7EhhZMC4yAklQXNA6AqiaVfHzbVEEX8e5l%20qfmxkuEgODCGuQODyLhotu8KIPuq/wDKupQnyV1M76z9WQ+sOGPBctjvbx4lilkjxZfKL/JJc2OQ%20bSsbiigXtah+pfQFwrqXbPm1ybI2MZgRRMjRkTGhWtYLbE7EFH+W+gLhRlvVPqif1XNDNkMZB+mY%20+KIN1duIO53YprLk5HczWy1IxPrLBb/pjIkBLjG5khfZW7dUGntFb+kufmIy9QptyOXYknlTbUIJ%20AUdhBAChOteo4g4VUlTzPLgha8ldbKeht3dKXhjHxGhl+V4XF4CtNz1JadLp0APetICvzniVoY9q%20lnha4kqbWJHelCqEFbBhmaYtaF2eJxOvYutO2yWFzNVwjWQiKDIDmtVC8WaHaKp7fp2VrseRm7kz%20QfpJHB++4HjeQhD1GlvYCq/vqZaXsCAnmV7HCclwaQDHZqqbBNR2X6U3XGMfAgce6LGw3SmJkLEH%20idc2+EBRcgGphuZCYxjGZnm7nyGS+ngb/hFutr66Vqox1E2zrXA8UB6S47DheGSZIdNMHNLgQSpF%2001Fq8v1F266EdfFbFuRHGQ3AzDIQIseG/l2Bc/tYHf0gnb765l7zd1Nnx2fDkQseqF7RtY7VLqq9%20p0ra1yqYx+pGvYTkT+UzfuIYSWLZAo8KadetNt6CTrIMbksfLf8Ap3AxyEFzHlAHIdvhSy+2i2+a%20g0VPIQzGdIy5kqbXSAnxa/ApNwhWm1poPdmU75IfPcY3+OMX7h2LSmTSCJND43zSPQkbXPsABoOu%20qfXUwKJKPPycZvIkecGyOarmNPh+GxHYe2nMZiToRvMgGZG8AzwtAdsBA8feSLapSzGkjpHyjbHN%20FyOU1nilmETtxCWAcSCLWVKq0zuVIN/ksM+QWBw8qNCRqdwVE/nWmZLcEtsSNAY3uKAm4qhDbi0X%20BuUPWkIaaXgvUjy1TcDcHrSTCAn+Jvm7ENySCBcFU7rCnIQQsyFs7AnxM8Ubmmwt0ShPoGeZkeT2%20s5nzHFGTtHhvbba6E6ovSq5a20HZO6pGkljY5H6FA78Sqfb7a8xHdqNucdytBcqkvNkuhW1IFbAw%206WVzXuPhZtKtce+9vsvVUDb7x7i55zyuI1BaeMSJoUeCQv107WpQXqjPT1egcAKABQB5e+bczo/m%20Fzbm3PmRX1H/AMvH3qOyuW/9x08aojIyTN2kPkUA2aUHhF+9AOiVEdizCeqoBHyYnZ/lSBXFtwHA%20i6Huraxmd6KRrYHufKTtaXK1D3ar76omVmScYNEYPag+q9xQ0CcltmSSR4TIpHB5cLIUNj1PW1Ql%20WSpJkbvHjxFwVrQ95ACgAIv0/jUvIotPRxczOk5IRCaUP8vHa5LhdTY9OlK/oO1P2HR3ZTmyEhGA%207i4AWXqBoEstZKC4FHJmJAYwaHYTbuS4HSlQf1AyNxHiKomqkAdoXr7aVAnqDIa+WAxuKs8Sh2lv%20bZanagqitzPS/FZhHnxOAJ8ZjeWEoNbaeIUh72QW+khjMaYcowx3Di4Da0AW11FTdbOPeWuSMqEa%20P0V6gxZ2TYWWySYEOaXHaQAW7Rr0FFAoTuc4vleUwo48rBa3OieHTZLXAMcxoUE7dfZRQadMzP8A%20I+k+ddJ/y2K0xQEgx7d4lQLvc2zk9lUmmDXgUmb6TxXzse8ScVPK1Y2uKxkAkWQjvprma7keWplk%20CXiOdwpGhqZeCXBvnteHlrgAm5LhPZ+1Lm27xJfHDoMyZPKlwGTHuezw7nhrwd19So6/vpLYsjPZ%20FcMiZ3NQORmfx8SO8L3hoG4XsOoPTWtbbXozO5tZ4x8xnD5DlOJnOTwWY+OOHxDGmIIDU8QaHeE9%20nbW9vI8mTtnIuMf1zgclOyLncY4cxAH6yIb2k2QuY4Vpck6vMlSi/wA/01xPLyul4rKZ57Yw+wDS%20UsTb9lQrYyqi3dHZmO5ThObgc+ORkvltJ2yhxESAfEXLYJ9VVBLbY1BxXqJ0nlCVjVHmOjc9qAaK%20neKbtTEpWoIMHjocmZ2fKH5DNrjHCgjAsXKRYoCapKBFlt4eFmNPHB+okyGlzg1xcATYE69Og7Km%20V1HtZawei/U/JOjL4RjwFoLXykANY7UNaPEqaVjdy2o0tscG84Tg8DhMU42OXTyDXIks9E+Fruxe%20+sHdJrakUvLsDs9xALiQUIS5B/pFwNelJHbaqAg8vyiVLHv8DbdqlpGv4T20mFzhDjI8eF5Md3FG%20ve7xFdwB3AKhoSErXqOQuEuW6RUZGBE3tVxJRO8n9laKlSbqDxcwtfuu1ES+twANRrqEvSSGRp5X%20MCF7NgQBgUr00GgVV+rvoTT0LQN0cnjc0AOIAJIA0vuXuSmhyQw4OeSSSCU3WUeEhqk9vWh/E1TY%20y4t2hxIJAIFtNL9t0ATsApUkLVQQ5xYd7H7SUAcLXKW17aFlEEXVqLZ6izcNzlm3tjG4RPFtPCQS%20vvqk5I2J56nrPBkEvy2x5HDy/N4yMuH9Kwjp3V0P9nsPIf7/AGnGpHgtc9jgXhSQFc4NBQp0WuE6%20MyE8tlJLQWuCbmmwdbp2AnW1J3Mu1CGq4EB28X3qoK9E7qUgOtZu+FOhBVABbrSG3QN0MrGuDuw7%20xZLlUJH7acA6kd74IXXAa5FQDXs+2iAXQg+ocmGLhORlmIEflmx7SiFqaX+nbrwpu5RmZ8uRxnJD%20mHe1QWHdqLB3xL7717t2cnlJizMDt/wtIcVvtN0XpfqOv11m1QuRiWSQRg/ECPxIFS/cSl6mIGQs%20ickHUk3cSbn6/ZSuUFdjR+g/Tb+T4vl+TQl+IWMx2p8S3k/w6Vk+fZckW+LdbJaYR81oTJEYIVyt%20aVKlG7uhKa133LM5FCHmYeKGObNnXVoZE3whQVcg9vSox7x7uhJDsCIDywXv1jfJclrlVx7U1PdT%20T11DxyM/yfISZUj9jgjEYxqEEuJXQ2utJ4xj4DXUc4/FdlZWNgxpunkYxiEKXFyalEU1Te1N6qQS%20lncnxMxoseMtQY8Za1ApKDsFr3rx+RvdOPwO61JZfgVHJ8Nh5mM3IniLfLu1yI5o+IlyjtF6yahZ%20Fp6lfDycuG/fuDGRgaG1wm32lOlUsymi6/usc2PBI5vlOlc0hov+K7Q1Qnaf2021BDlkWOSAvljk%20JaxkxduBKxkiwaWhVN+tJTMDzRKje57JGPLhLGwOhQI7aibwv9XULW1j6Y/T8hXYxjqV7ceKF08r%203fmMckjHhQ13bfUEHUU4FJU8nPDLhzeJroGggKQhKm4QqDf+NDykowPksDHvz4XSwyEkz3DmtWyj%207qiIKkqMjJGE57cOUvjb41NiGkodw7fDaglwejflRx7eL9DYeU4bPPD8lxsrg+7SXFBohubVdtFJ%20ndLuNbgsRvnPAZu+MW/FcdlUqEyTmloAIPiboD2nrVJCYk7HagKb+w/YmtKZyAjTuIfEwAAvvuQE%20eHobdV7PtokBTogWPYHg9C1B8KWt3CxokZGlUrtB2gAoCthYAdFpQOeuP1Ml6k498S5rJNwiP5oI%20B6WJU6dfbr0qbn9rktVZSxZ0DmM8QR/Zop1O6uBo60mLyJdoQORwC2sHAG5Cjs6UhqozI0yBr27f%20MIUWsVuCB8XdeiWPJ1D4aVOYwo3seGCeMkEanzA0a27NRVW3VQro2vGh6kr0jzgUACgCnzvR3pbP%20ypMvM4vHnyZiDLM+MFziGhtyf8ISpdqY9zyIh+XPoQhDweGRb/0h00o2roPe+ozN8rfl1M3bL6ew%20XtvZ0TTrT2oUsa/7R/LHbt/0zx6dnkNo2oFc0KPym+WhcXH01x5J1WBtCtQSKPyq+W5IJ9OYCg7h%20+S3Xt+2ltQbmLPyx+XpcXf6fwdxCE+S3Tso2roEsdx/l16FxmhmPweHE1t2hkTQidiUOxdClyXLU%20kf6L9Kf/AGrH/wDIKXl29EG99Qx6M9KgqOLxwVX4BqOtPaugt7Ff6Q9Mf/bYO34KNq6D8y7qD/SH%20pj/7ZAnZsCXodq6Cd76gPpH0wdeMx/8AyDpT2roG+7qJl9GelZYnQycXjvifZ7CwEFe0UbV0De+o%20r/SPpkInGwBERGppU+Xb0QbmL/0t6dQD+3QIAgGwaUvKt6BufUI+lPTZVeOguNpRgFuyjyregb7u%20oxN6G9HzxNim4fFkjZZjXxNcAO5aflW9CvNu6kTH+WHy9x3SOg9P4UbpgkpbE0bhrejy7eglyXLJ%20jf8A2p+W21zf9N4CPKuHktvYj9tPYugebd1YHfKf5auYGO9N4BaAAAYW6DSl5dvQW99RH/aL5Ylu%200+meP2qqeQ2nsQbmK/7TfLRAP9NcegCD8hmn1UbUDvfUch+Vvy7hLTF6ewWFnwkQtp7ULcx9/wAv%20fRD4jE/hMR0bviaYmkGnFIERP+0vy1Xd/pvB3Ii+UFT20D3MD/lN8tHu3P8ATWA5yIphaaUBLJeH%208vfQ+GxzMXg8OFjtWshaBb3UnamG5kp3pH0y6zuNgNk+HpT2oauaEu9GelXEl3F45JsTsFJ2W9AV%2076jLvQPot0gkdwuIZGncHmJqgqqg0vLt6F+df1YbPQXoxgRnDYjQVFomjXWkuK2IgXnX9Qf6C9Gf%20/Z8X/wDxtp+Xb0Dzr+oQ9A+iwCBw2KFVUjHXWnst6C8y7qH/AKD9Gon9mxU1TyxRsXQPNu6hf9v/%20AEV/9lxDdbxNN/fRsXQfnX9QD5f+imonC4gQIEiaLUbF0Dzr+ol3y89DuJJ4TEJIIJ8oKh6LS8u3%20oHnX9WGfl96JOvC4h9sTTrY0eWug/Pv6sR/259CX/wChYRXUmFp0K9lPYhedf1YHfLf0E7XgcI9n%205LaWxA+a96stsricaXh5OKgAxsZ0Jx42sFmM27QGjuFU1KgiayYaP5M4TNv/AFSVxCbljHiCIV8V%20c/8Ajrqa+d2A75M8eTuHIvDupEYvdb+Kj/G7jXN2Cd8l8ItT+6Sgom4RNVT1+LtpL03cPO7DkPye%20w4mgf3KRx0LvLAJsl0dT/wAbuJ87egZ+T+Eq/wBykXxX8sfiXXxdFofpkC5mMzfJXjZSC7kHqCq+%20UF62Xd30f4/cPOZXc7/t+weV4p3Hjm58ZryN8rImklovt+IWrTi4tjkm/k3KDNu/2l8U5F9SZCgk%20qMdgN/8Ax12PnfQ5vLI3/wDx9xIaAPU+SEBbbFj0PT4+2p8zsNcYb/8AZ9w7mp/qXIHaf0sS9Ou/%20uo8wPLrmMyf7NuHeCP8AVGU29iMaP/8Anpbxq2Mjben/AJAcPwnAx8PjclK6NjHtkmMTWue56q9y%20O1v21y38W5zJuuSFEGdg/wBqXExsAPqLJcUILvIjUjv8RrsXM0c740xxv+1fiBd3P5BIKj8hgC94%2033peaw8scyf9r/HTRhjfUWSxPxeRGTtVQLOGhp+d2F5SIbP9pnDtcw/6iydrBYfp49URfip+ewfF%20M9yy4X/bJw3G8lBmyc1Pk+S7eITBGxpKJ0cTSv5ncoGuOGbLJ+VuFkPD3Z0m4AtUsBO0hEuT0tXK%207OhrIh/yqwHxhn654AUfACERAEJ6UvKK3lRnfIji8t8Z/ucrGMuWCII4oBfxDRLUnwoa5BpvyEwx%20MyQ81MdikDym69vx0PiDzByH5DcdEqctMS55e4mJtzb/ABd1V5YbwZPyKxpZN7eamYjtzPyWlD73%20ULjDzOwcnyKwpNpfy8pkCjf5LVLT+H4qpWi30gjTf7euJe4FnKyxNDQ3y2ws2lOqbqNobyuy/wDb%20JxmS3YeeyGRrdogYu1EQHdap8sFeVWT/ALReIyHPLvUmSj9f+XjKf/x0eWPzKQdO4/5bYeFxWJxz%20Mxz48SGOBrywAuEfVyOS9UrUlBDfQn/6LxgSW5BBRGjbYHqU3VQUFN9HwtIIySnXw/8A9VABn0fj%20n/1yvc2330SISfRsBcHfqCCARZvaEtelA5En0XEZA/8AVG34dlu9fFRASIPofHO7/mnITbw6D69e%20+nAiJk/LXDyI3xy5bnMkXcCzo7pZw7Km62UUrmmUo+R/GiNrG8k8BuixNNlP+LssK536bua+f2Hv%20+y/GIQ7Oe5dHGMK21kv0NH+N3Dz30G2/JTDbpy0wupIjb11GtH+N3Dz30HIPkzhxZMM/9ze58T2S%20XhZcscD/AFdUQ016eHmPz+x0auk5wUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUA%20CgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUAC%20gAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACg%20AUACgAUACgAUAf/Z" height="281" width="665" overflow="visible"> </image>
          </svg>
        </div>
      </div>
      <div class="fig"><span class="labelfig">FIGURE 3.&nbsp; </span><span class="textfig">Position of the dumper (1) with 
        respect to the end of the blades (2) (a) and conclusion of the manual 
        extraction of the cane (b).</span></div>
      <p>The results obtained also 
        show the possibilities offered by the use of the horizontal probe in the
        determination of the content of strange matter, which is one of the 
        indicators of efficiency in the harvest of sugarcane according to <span class="tooltip"><a href="#B16">Matos et al. (2014)</a><span class="tooltip-content">MATOS,
        N.; IGLESIAS, C.; GARCÍA, E.: “Organización racional del complejo de 
        máquinas en la cosecha - transporte - recepción de la caña de azúcar en 
        la Empresa Azucarera Argentina”, <i>Revista Ciencias Técnicas Agropecuarias</i>, 23(2): 27-33, 2014, ISSN: 1010-2760, e-ISSN: 2071-0054.</span></span> and the variables to consider in the payment system to the sugarcane producer.</p>
      <p>The
        evaluation of the effect of the harvest-transport equipment on the 
        quality of the work of the probe showed significant differences in 7.23 
        kg in the variant with CASE 8800 and Sinotruck (20 t) with 20 t Trailer 
        with respect to the KTP 2M and the ZIL130 (6 t) with the 6 t trailer, at
        the 95% confidence level (<span class="tooltip"><a href="#t3">Table 3</a></span>). The strange matter obtained in the CASE combines was between 10 and 12% and in the KTP between 15 and 20%.</p>
      <div class="table" id="t3"><span class="labelfig">TABLE 3.&nbsp; </span><span class="textfig">Mass of the sample depending on the transport harvest system</span></div>
      <div class="contenedor">
        <div class="outer-centrado">
          <div style="max-width: 1160px;" class="inner-centrado">
            <table>
              <colgroup>
              <col>
              <col>
              <col>
              <col>
              </colgroup>
              <thead>
                <tr>
                  <th align="center">Variant</th>
                  <th align="center">Mass*, kg</th>
                  <th align="center">Standard error</th>
                  <th align="center">Value P</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="center">CASE 8800 and Sinotruck (20t)+Remolque (20t)</td>
                  <td align="center">18,69a</td>
                  <td align="center">±1,15</td>
                  <td rowspan="2" align="center">0,0011</td>
                </tr>
                <tr>
                  <td align="center">KTP 2M and ZIL130(10t)+Remolque 10t</td>
                  <td align="center">11,46b</td>
                  <td align="center">±1,27</td>
                </tr>
                <tr>
                  <td colspan="4" align="justify"><i>*n=7</i></td>
                </tr>
              </tbody>
            </table>
          </div>
        </div>
      </div>
      <div class="clear"></div>
      <p>The
        harvest of cane left and lodged shoots influenced the high percentage 
        of strange matter. However, the particularities of the technological 
        process of the CASE harvesters that cut the cane into smaller pieces, 
        together with the use of extractors, achieved greater efficiency in 
        cleaning the cane compared to the KTP harvesters, coinciding with what <span class="tooltip"><a href="#B23">Placeres (2015)</a><span class="tooltip-content">PLACERES,
        Y.: “Evaluación de los índices tecnológicos-explotativos y económicos 
        de la cosechadora cañera Case ih Austoft a 8000 en la UEB Perucho 
        Figueredo”, 2015.</span></span> stated. </p>
      <p>For conditions where the 
        harvested cane has a high content of strange matter, greater than 12%, 
        and the established weight is not met, it is recommended to carry out 
        several samples in the transport means until the established mass is 
        completed.</p>
      <p>The Probe showed a clean time productivity of 15.15 kg/minute (<span class="tooltip"><a href="#t4">Table 4</a></span>).
        However, the work regime with the organs of the equipment active for a 
        short period, with respect to the total in which the sample is taken, 
        determined that the remaining productivity indices of operative, 
        productive and exploitation times were much lower with respect to the 
        clean time, in 29, 21 and 15%, respectively. However, in practice, 16 
        daily samples were established by <span class="tooltip"><a href="#B11">AZCUBA Business Group (2018)</a><span class="tooltip-content">GRUPO EMPRESARIAL AZCUBA: <i>Resolución
        202/2018. Procedimiento para la aplicación de las “instrucciones 
        metodológicas para el control y aplicación del sistema de precios de la 
        caña por su calidad (SPCC)”</i>, Inst. Grupo Empresarial AZCUBA, Resolición ministerial, La Habana, Cuba, 18 p., 2018.</span></span>, for which the Probe easily meets the demand for a working day.</p>
      <div class="table" id="t4"><span class="labelfig">TABLE 4.&nbsp; </span><span class="textfig">Probe operation indicators</span></div>
      <div class="contenedor">
        <div class="outer-centrado">
          <div style="max-width: 1160px;" class="inner-centrado">
            <table>
              <colgroup>
              <col>
              <col>
              </colgroup>
              <thead>
                <tr>
                  <th align="center">Parameter</th>
                  <th align="center">Value</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="justify">Productivity in clean time, kg/minutes</td>
                  <td align="center">15,15</td>
                </tr>
                <tr>
                  <td align="justify">Productivity in operating time, kg/minutes</td>
                  <td align="center">4,33</td>
                </tr>
                <tr>
                  <td align="justify">Productivity in productive time, kg/minutes</td>
                  <td align="center">3,10</td>
                </tr>
                <tr>
                  <td align="justify">Productivity in exploitation time, kg/minutes</td>
                  <td align="center">2,21</td>
                </tr>
                <tr>
                  <td align="justify">Technical maintenance coefficient</td>
                  <td align="center">0,97</td>
                </tr>
                <tr>
                  <td align="justify">Technical safety factor</td>
                  <td align="center">0,74</td>
                </tr>
                <tr>
                  <td align="justify">Productive time utilization ratio</td>
                  <td align="center">0,20</td>
                </tr>
                <tr>
                  <td align="justify">Operating time utilization ratio</td>
                  <td align="center">0,10</td>
                </tr>
              </tbody>
            </table>
          </div>
        </div>
      </div>
      <div class="clear"></div>
      <p>The
        equipment achieved a technical safety coefficient of over 70%. The 
        fundamental problem was found in the breakage of the blades of the cap, 
        mainly caused by the inadequate dimensioning of the hole to take the 
        sample in the transport means, which is why it is considered strange to 
        the machine. However, it should be noted that there were no spare parts 
        to replace the cap, despite being a fast-wearing component. Another 
        problem of less incidence was the leaks in the hoses of the hydraulic 
        system. In general, it is considered that the Sampling Probe presented 
        adequate reliability. On the other hand, the coefficients of use of 
        productive time and exploitation time are low as a result of the 
        equipment work regime explained above.</p>
      <p>Fuel costs based on the number and weight of the sample are low (<span class="tooltip"><a href="#t5">Table 5</a></span>),
        with an average of 0.053 L/sample and 0.004 L/kg, respectively; which 
        was due to the discontinuous regime and the short time of operation with
        the motor running in the sampling. </p>
      <div class="table" id="t5"><span class="labelfig">TABLE 5.&nbsp; </span><span class="textfig">Determination of fuel cost</span></div>
      <div class="contenedor">
        <div class="outer-centrado">
          <div style="max-width: 1160px;" class="inner-centrado">
            <table>
              <colgroup>
              <col>
              <col>
              <col>
              <col>
              <col>
              </colgroup>
              <thead>
                <tr>
                  <th align="center">Parameter</th>
                  <th align="center">UM</th>
                  <th align="center">Mean *</th>
                  <th align="center">Standard deviation</th>
                  <th align="center">Coefficient of variation, %</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="center">Fuel cost per sample</td>
                  <td align="center">L/sample</td>
                  <td align="center">0,053</td>
                  <td align="center">0,019</td>
                  <td align="center">35,951</td>
                </tr>
                <tr>
                  <td align="center">Fuel cost per sample weight</td>
                  <td align="center">L/kg</td>
                  <td align="center">0,004</td>
                  <td align="center">0,002</td>
                  <td align="center">39,717</td>
                </tr>
                <tr>
                  <td colspan="5" align="justify"><i>*n=9</i></td>
                </tr>
              </tbody>
            </table>
          </div>
        </div>
      </div>
      <div class="clear"></div>
      <p>In
        general, the use of the Horizontal Probe in the Sugar Agroindustry of 
        other countries such as Guatemala, Costa Rica and Brazil has also 
        provided satisfactory results in the sampling of sugarcane to evaluate 
        the quality of the raw material that goes to the industry differentiated
        by producer (<span class="tooltip"><a href="#B8">Estrada, 2012</a><span class="tooltip-content">ESTRADA, M.O.: <i>Comparación de cinco métodos analíticos para determinar la calidad de la caña de azúcar</i>, <i>[en línea]</i>,
        Trabajo de graduación para optar por el título de Ingeniero Químico, 
        Trabajo de graduación para optar por el título de Ingeniero Químico, 
        Guatemala, 172 p., 2012, <i>Disponible en:</i> <a href="https://biblioteca.usac.edu.gt/tesis/08/08_1253_Q.pdf" target="xrefwindow">https://biblioteca.usac.edu.gt/tesis/08/08_1253_Q.pdf</a>, <i>[Consulta: 12 de enero de 2022]</i>.</span></span>; <span class="tooltip"><a href="#B3">Canales, 2014</a><span class="tooltip-content">CANALES, M.C.: <i>Desarrollo de un plan de mantenimiento preventivo basado en la metodología RCM para el departamento de patio de caña</i>,
        Instituto Tecnológico de Costa Rica. Escuela de Ingeniería 
        Electromecánica. Central Azucarera Tempisque S.A. (Catsa), Informe de 
        práctica de especialidad para optar por el título de Ingeniero en 
        Mantenimiento Industrial, Grado Licenciatura, Cartago, Costa Rica, 192 
        p., publisher: Instituto Tecnológico de Costa Rica, 2014.</span></span>; <span class="tooltip"><a href="#B13">IRBI, 2022</a><span class="tooltip-content">IRBI: <i>Sonda Oblicua IRBI Modelo FB06</i>, <i>[en línea]</i>, IRBI, 2022, <i>Disponible en:</i> <a href="https://www.irbi.com.br/br/noticias/sonda-oblicua-irbi-modelo-fb06" target="xrefwindow">https://www.irbi.com.br/br/noticias/sonda-oblicua-irbi-modelo-fb06</a>, <i>[Consulta: 10 de enero de 2022]</i>.</span></span>).</p>
    </article>
    <article class="section"><a id="id0x8b23280"><!-- named anchor --></a>
      <h3>CONCLUSIONS</h3>
      &nbsp;<a href="#content" class="boton_1">⌅</a>
      <p>The evaluation of the AZUTECNIA Horizontal Probe in the sampling of sugarcane for the Quality Payment System showed:</p>
      <div class="list"><a id="id0x8b23780"><!-- named anchor --></a>
        <ul>
          <li>
            <p>Satisfactory
              quality of work, by complying with the 15 kg for analysis in 
              laboratories in cane harvested with strange matter less than 12%.</p>
          </li>
          <li>
            <p>Productivity in clean time of 15 kg/minute, satisfactorily fulfilling the 16 daily samples established for the laboratory.</p>
          </li>
          <li>
            <p>Decrease
              in the productivity of operating, productive and exploitation time with
              respect to clean time by 29, 21 and 15%, respectively; as well as the 
              exploitation coefficients associated with these due to the operating 
              regime with the active work organs for a short period.</p>
          </li>
          <li>
            <p>Technical
              safety coefficient greater than 70%, which showed adequate reliability,
              being necessary to make available to the customer spare parts such as 
              the cap with blades.</p>
          </li>
          <li>
            <p>Average fuel costs based on the number of samples taken and their weight of 0.053 L/sample and 0.004 L/kg, respectively. </p>
          </li>
        </ul>
      </div>
    </article>
  </section>
</div>
<div class="box2" id="article-back">
  <section>
    <article><a id="ref"></a>
      <h3>REFERENCIAS BIBLIOGRÁFICAS</h3>
      &nbsp;<a href="#content" class="boton_1">⌅</a>
      <p id="B1">AZUTECNIA: <i>Manual Técnico de Explotación de la Sonda Toma Muestra</i>, Inst. AZUTECNIA-División de Talleres “Enrique Villegas”, Informe técnico, Villa Clara, Cuba, 6 p., 2019.</p>
      <p id="B2">BETANCOURT,
        Y.; PONCE, J.L.; GUILLÉN, S.; GONZÁLEZ, J.C.; GÓMEZ, J.R.: “Parámetros 
        agronómicos de la plantadora de caña de azúcar AZT 6000 en suelos 
        arcillosos pesados”, <i>Revista Ingeniería Agrícola</i>, 9(4): 36-41., 2019, ISSN: 2306-1545, e-ISSN: 2227-8761.</p>
      <p id="B3">CANALES, M.C.: <i>Desarrollo de un plan de mantenimiento preventivo basado en la metodología RCM para el departamento de patio de caña</i>,
        Instituto Tecnológico de Costa Rica. Escuela de Ingeniería 
        Electromecánica. Central Azucarera Tempisque S.A. (Catsa), Informe de 
        práctica de especialidad para optar por el título de Ingeniero en 
        Mantenimiento Industrial, Grado Licenciatura, Cartago, Costa Rica, 192 
        p., publisher: Instituto Tecnológico de Costa Rica, 2014.</p>
      <p id="B4">CENTRAL AZUCARERO “PANCHITO GÓMEZ TORO”,: <i>Realización de los análisis de Laboratorio a la Materia Prima Caña. Versión: 001.19</i>, Inst. UEB Central Azucarero “Panchito Gómez Toro”, Instrucción 3, Villa Clara, Cuba, Fecha de Aprobación: 26/12/2018, 2019.</p>
      <p id="B5">CRUZ, S.M.: “Procedimiento para la introducción de tecnologías agrícolas de mecanización, riego y drenaje en Cuba”, En: <i>Convención Internacional de Ingeniería Agrícola 2018</i>, Ed. IAgric, Varadero, Matanzas, Cuba, p. 13, 2018, ISBN: 978-959-285-061-3.</p>
      <p id="B6">CRUZ, S.M.; VÁZQUEZ, D.O.: “Procedimiento para la introducción de nuevas tecnologías agrícolas mecanizadas en Cuba”, <i>Revista Ingeniería Agrícola</i>, 4(3): 39-43, 2014, ISSN: 2306-1545, e-ISSN: 2227-8761.</p>
      <p id="B7">DÍAZ, L.R.: <i>Propuesta
        de un plan de mantenimiento para la disponibilidad del core sampler en 
        un ingenio azucarero, utilizando el diagrama de ishikawa para elevar la 
        confiabilidad del sistema de muestreo</i>, <i>[en línea]</i>, 
        Universidad de San Carlos de Guatemala, Facultad de Ingeniería, Trabajo 
        de graduación para optar por el título de Maestro en Artes en Gestion 
        Industrial, Escuintla, Guatemala, 2019, <i>Disponible en:</i> <a href="https://www.repositorio.usac.edu.gt/12352/1/Luis%2520Rodolfo%2520/D%25C3%25Adaz%2520Jim%25C3%25A9nez.pdf" target="xrefwindow">https://www. Repositorio.usac.edu.gt/12352/1/Luis%2520Rodolfo%2520/D%25C3%25Adaz%2520Jim%25C3%25A9nez.pdf</a>, <i>[Consulta: 13 de febrero de 2022]</i>.</p>
      <p id="B8">ESTRADA, M.O.: <i>Comparación de cinco métodos analíticos para determinar la calidad de la caña de azúcar</i>, <i>[en línea]</i>,
        Trabajo de graduación para optar por el título de Ingeniero Químico, 
        Trabajo de graduación para optar por el título de Ingeniero Químico, 
        Guatemala, 172 p., 2012, <i>Disponible en:</i> <a href="https://biblioteca.usac.edu.gt/tesis/08/08_1253_Q.pdf" target="xrefwindow">https://biblioteca.usac.edu.gt/tesis/08/08_1253_Q.pdf</a>, <i>[Consulta: 12 de enero de 2022]</i>.</p>
      <p id="B9">FLORES, M.A.; PALLI, L.R.; HERNÁNDEZ, F.: <i>Diseño de equipamiento para muestreo de la caña para el pago por su calidad</i>, <i>[en línea]</i>, Atamexico, 2016, <i>Disponible en:</i> <a href="https://www.atamexico.com.mx/wp-content/uploads/2017/11/3-ADMINISTRACI%C3%93N-2016.pdf" target="xrefwindow">https://www.atamexico.com.mx/wp-content/uploads/2017/11/3-ADMINISTRACI%C3%93N-2016.pdf</a>, <i>[Consulta: 11 de mayo de 2021]</i>.</p>
      <p id="B10">GONZÁLEZ, L.J.: “Pago de la caña por su calidad con notables beneficios en Villa Clara”, <i>Agencia Cubana de Noticias</i>, 22 de marzo de 2020, <i>Disponible en:</i> <a href="http://www.acn.cu/economia/62373-pago%20de%20la%20ca%C3%B1a%20por%20su%20calidad%20con%20notables%20beneficios%20en%20villa%20clara" target="xrefwindow">http://www.acn.cu/economia/62373-pago de la caña por su calidad con notables beneficios en villa clara</a>, <i>[Consulta: 11 de mayo de 2021]</i>.</p>
      <p id="B11">GRUPO EMPRESARIAL AZCUBA: <i>Resolución
        202/2018. Procedimiento para la aplicación de las “instrucciones 
        metodológicas para el control y aplicación del sistema de precios de la 
        caña por su calidad (SPCC)”</i>, Inst. Grupo Empresarial AZCUBA, Resolición ministerial, La Habana, Cuba, 18 p., 2018.</p>
      <p id="B12">HERRERA, P.J.; GONZÁLEZ, R.F.: “Estudio de las necesidades de agua de los cultivos, una demanda permanente, un nuevo enfoque”, <i>Revista Ingeniería Agrícola</i>, 5(1): 52-57, 2015, ISSN: 2306-1545, e-ISSN: 2227-8761.</p>
      <p id="B13">IRBI: <i>Sonda Oblicua IRBI Modelo FB06</i>, <i>[en línea]</i>, IRBI, 2022, <i>Disponible en:</i> <a href="https://www.irbi.com.br/br/noticias/sonda-oblicua-irbi-modelo-fb06" target="xrefwindow">https://www.irbi.com.br/br/noticias/sonda-oblicua-irbi-modelo-fb06</a>, <i>[Consulta: 10 de enero de 2022]</i>.</p>
      <p id="B14">LÓPEZ,
        B.E.; SAUCEDO, L.E.R.; GONZÁLEZ, C.O.; HERRERA, S.M.; BETANCOURT, R.Y.:
        “Efectos de la cosecha mecanizada de la caña de azúcar sobre el suelo”, <i>Revista Ciencias Técnicas Agropecuarias</i>, 31(1): 5-12, 2022, ISSN: 1010-2760, e-ISSN: 2071-0054.</p>
      <p id="B15">MACHADO, O.L.: “Análisis de la caña y su calidad”, <i>Vanguardia</i>, 2019, ISSN: 0864-098X, e-ISSN:1607-5900, <i>Disponible en:</i> <a href="http://www.vanguardia.cu/villa-clara/15675-analisis-de-la-ca%C3%B1a-y-su-calidad" target="xrefwindow">http://www.vanguardia.cu/villa-clara/15675-analisis-de-la-caña-y-su-calidad</a>, <i>[Consulta: 10 de julio de 2021]</i>.</p>
      <p id="B16">MATOS,
        N.; IGLESIAS, C.; GARCÍA, E.: “Organización racional del complejo de 
        máquinas en la cosecha - transporte - recepción de la caña de azúcar en 
        la Empresa Azucarera Argentina”, <i>Revista Ciencias Técnicas Agropecuarias</i>, 23(2): 27-33, 2014, ISSN: 1010-2760, e-ISSN: 2071-0054.</p>
      <p id="B17">MESA,
        J.M.; ACOSTA, R.M.; RODRÍGUEZ, M.; HERNÁNDEZ, G.A.; JIMÉNEZ, A.L.; 
        GARCÍA, H.: “XXIV Reunión Nacional de Variedades, Semilla y Sanidad 
        Vegetal”, <i>Revista Cuba &amp; Caña</i>, Suplemento especial: 50, Publicado en La Hsbana, Cuba, 2016, ISSN: 1028-6527.</p>
      <p id="B18">MINAG-CUBA: <i>Procedimiento para la introducción de tecnologías agrícolas de mecanización, riego y drenaje en Cuba</i>, Inst. Ministerio de la Agricultura, Cuba, 13 p., Vigente hasta el 2022, 2018.</p>
      <p id="B19">OCAMPO, B.J.E.: <i>Diseño de un equipo para medición de fibra de caña</i>, <i>[en línea]</i>,
        Universidad del Valle, Trabajo de grado presentado como requisito 
        parcial para optar al título de Ingeniero Mecánico, Santiago de Cali, 
        Colombia, 92 p., publisher: Universidad del Valle, 2015, <i>Disponible en:</i> <a href="https://bibliotecadigial.univalle.edu.co/bitstream/handle/10893/16466/0527918.pdf" target="xrefwindow">https://bibliotecadigial.univalle.edu.co/bitstream/handle/10893/16466/0527918.pdf</a>, <i>[Consulta: 10 de enero de 2022]</i>.</p>
      <p id="B20">PERDOMO, T.M.E.: <i>Diseño de un sistema automático para muestreos de caña</i>, <i>[en línea]</i>,
        Universidad del Valle, Facultad de Ingeniería, Escuela de Ingeniería 
        Mecánica, Trabajo de grado presentado para optar por el título de 
        Ingeniero Mecánico, Santiago de Cali, Colombia, 90 p., publisher: 
        Universidad del Valle, 2015, <i>Disponible en:</i> <a href="https://bibliotecadigial.univalle.edu.co/bitstream/handle/10893/16558/0529022.pdf" target="xrefwindow">https://bibliotecadigial.univalle.edu.co/bitstream/handle/10893/16558/0529022.pdf</a>, <i>[Consulta: 11 de enero de 2022]</i>.</p>
      <p id="B21">PG-CA-042: <i>Sistema de gestión de la calidad. Pruebas de maquinaria agrícola. Determinación de las condiciones de ensayo</i>, Inst. Instituto de Investigaciones de Ingeniería Agrícola (IAgric), La Habana, Cuba, 10 p., 2013.</p>
      <p id="B22">PG-CA-043: <i>Sistema de gestión de la calidad. Pruebas de maquinaria agrícola. Evaluación tecnológica y de explotación</i>, Inst. Instituto de Investigaciones de Ingeniería Agrícola (IAgric), Norma cubana, La Habana, Cuba, 13 p., 2013.</p>
      <p id="B23">PLACERES,
        Y.: “Evaluación de los índices tecnológicos-explotativos y económicos 
        de la cosechadora cañera Case ih Austoft a 8000 en la UEB Perucho 
        Figueredo”, 2015.</p>
      <p id="B24">SANTAL: <i>Equipos Agrícolas para la caña de azúcar</i>, <i>[en línea]</i>, Slidetodoc.com, 2021, <i>Disponible en:</i> <a href="http://slidetodoc.com/equipos-agrcolas-para-la-caa-de-azcar-sulcador/" target="xrefwindow">http://slidetodoc.com/equipos-agrcolas-para-la-caa-de-azcar-sulcador/</a>, <i>[Consulta: 20 de julio de 2021]</i>.</p>
    </article>
  </section>
</div>
<div id="article-footer"></div>
<div id="s1-front"><a id="id2"></a>
  <div class="toctitle">Revista Ciencias Técnicas Agropecuarias Vol. 31, No. 3, July-September, 2022, ISSN:&nbsp;2071-0054</div>
  <div>&nbsp;</div>
  <div class="toctitle2"><b>ARTÍCULO ORIGINAL</b></div>
  <h1>Evaluación de la sonda horizontal Azutecnia en el muestreo de caña de azúcar</h1>
  <div>&nbsp;</div>
  <div>
    <p><sup><a href="https://orcid.org/0000-0002-4109-8775" rel="license"><span class="orcid">iD</span></a></sup>Yoel Betancourt Rodríguez<span class="tooltip"><a href="#aff3"><sup>I</sup></a><span class="tooltip-content">Instituto de Investigaciones de la Caña de Azúcar-INICA Villa Clara. Ranchuelo, Villa Clara, Cuba. </span></span><span class="tooltip"><a href="#c2"><sup>*</sup></a><span class="tooltip-content">✉:<a href="mailto:yoel.betancourt@nauta.cu">yoel.betancourt@nauta.cu</a><a href="mailto:yoelbr15@gmail.com">yoelbr15@gmail.com</a></span></span></p>
    <p><sup><a href="https://orcid.org/0000-0003-4266-7754" rel="license"><span class="orcid">iD</span></a></sup>Jorge Luis Ponce Salazar<span class="tooltip"><a href="#aff3"><sup>I</sup></a><span class="tooltip-content">Instituto de Investigaciones de la Caña de Azúcar-INICA Villa Clara. Ranchuelo, Villa Clara, Cuba. </span></span></p>
    <p><sup><a href="https://orcid.org/0000-0001-5053-9416" rel="license"><span class="orcid">iD</span></a></sup>Yasiel Caballero Jiménez<span class="tooltip"><a href="#aff4"><sup>II</sup></a><span class="tooltip-content">Universidad Central “Marta Abreu” de las Villas. Santa Clara, Villa Clara, Cuba.</span></span></p>
    <p><sup><a href="https://orcid.org/0000-0002-7710-2158" rel="license"><span class="orcid">iD</span></a></sup>Yoel José Moya Pentón<span class="tooltip"><a href="#aff3"><sup>I</sup></a><span class="tooltip-content">Instituto de Investigaciones de la Caña de Azúcar-INICA Villa Clara. Ranchuelo, Villa Clara, Cuba. </span></span></p>
    <p><sup><a href="https://orcid.org/0000-0002-5150-5859" rel="license"><span class="orcid">iD</span></a></sup>José Ramón Gómez Pérez<span class="tooltip"><a href="#aff3"><sup>I</sup></a><span class="tooltip-content">Instituto de Investigaciones de la Caña de Azúcar-INICA Villa Clara. Ranchuelo, Villa Clara, Cuba. </span></span></p>
    <br>
    <p id="aff3"><span class="aff"><sup>I</sup>Instituto de Investigaciones de la Caña de Azúcar-INICA Villa Clara. Ranchuelo, Villa Clara, Cuba. </span></p>
    <p id="aff4"><span class="aff"><sup>II</sup>Universidad Central “Marta Abreu” de las Villas. Santa Clara, Villa Clara, Cuba.</span></p>
  </div>
  <div>&nbsp;</div>
  <p id="c2"> <sup>*</sup>Autor para correspondencia, Yoel Betancourt Rodríguez, e-mail: <a href="mailto:yoel.betancourt@nauta.cu">yoel.betancourt@nauta.cu</a>; <a href="mailto:yoelbr15@gmail.com">yoelbr15@gmail.com</a> </p>
  <div class="titleabstract | box">RESUMEN</div>
  <div class="box1">
    <p>Perfeccionar
      el pago de la caña de azúcar a los productores, de forma diferenciada, 
      según la calidad de la materia prima demandó del diseñó por la industria
      nacional de la Sonda Horizontal Toma Muestra AZUTECNIA, formando parte 
      del Kit de equipos para esos fines. El objetivo de la investigación 
      consistió en determinar el cumplimiento de la calidad del trabajo, los 
      índices tecnológicos y de explotación de la Sonda en el muestreo de caña
      de azúcar a moler en el ingenio en la agroindustria azucarera cubana. 
      La investigación se desarrolló en el laboratorio de la Empresa 
      Agroindustrial Azucarera Panchito Gómez Toro de la provincia de Villa 
      Clara. Se tomó en cuenta las normas y procedimientos de evaluación de 
      máquinas agrícolas establecidos por el Instituto de Ingeniería Agrícola 
      en Cuba. Los resultados mostraron que la calidad del trabajo fue 
      satisfactoria, al cumplir con el peso de la muestra de 15 kg demandado 
      por el laboratorio en caña cosechada con materias extrañas inferiores al
      12%. El régimen de operación con los órganos de trabajo del equipo 
      activos por un período corto influyó en la disminución marcada de la 
      productividad de tiempo operativo, productivo y de explotación; así como
      de los coeficientes de explotación asociados a estos; sin embargo, no 
      existen dificultad para garantizar las 16 muestras diarias establecidas.
      Mostró una adecuada fiabilidad, con un coeficiente de seguridad técnica
      superior al 70%, y gastos de combustible promedios en función del 
      número de muestras y de su peso de 0,053 L/muestra y 0,004 L/kg 
      respectivamente.</p>
    <div class="titlekwd"><i>Palabras clave</i>:&nbsp; </div>
    <div class="kwd">muestreo de caña, pago por calidad, sonda toma muestra</div>
  </div>
</div>
<div class="box2" id="s1-body">
  <section>
    <article class="section"><a id="id0x4d1f300"><!-- named anchor --></a>
      <h3>INTRODUCCIÓN</h3>
      &nbsp;<a href="#content" class="boton_1">⌅</a>
      <p>El
        sistema de pago de la caña de azúcar a moler en el ingenio ha sido un 
        tema de análisis con los productores del país desde hace varias décadas,
        para aumentar la calidad de la materia prima, la eficiencia 
        agroindustrial y lograr justeza en el pago. En ese sentido, 
        internacionalmente se han establecido métodos, procedimientos y 
        equipamientos para realizar un sistema diferenciado de pago por calidad,
        mediante la toma de muestras y su procesamiento en el laboratorio (<span class="tooltip"><a href="#B8">Estrada, 2012</a><span class="tooltip-content">ESTRADA, M.O.: <i>Comparación de cinco métodos analíticos para determinar la calidad de la caña de azúcar</i>, <i>[en línea]</i>,
        Trabajo de graduación para optar por el título de Ingeniero Químico, 
        Trabajo de graduación para optar por el título de Ingeniero Químico, 
        Guatemala, 172 p., 2012, <i>Disponible en:</i> <a href="https://biblioteca.usac.edu.gt/tesis/08/08_1253_Q.pdf" target="xrefwindow">https://biblioteca.usac.edu.gt/tesis/08/08_1253_Q.pdf</a>, <i>[Consulta: 12 de enero de 2022]</i>.</span></span>; <span class="tooltip"><a href="#B3">Canales, 2014</a><span class="tooltip-content">CANALES, M.C.: <i>Desarrollo de un plan de mantenimiento preventivo basado en la metodología RCM para el departamento de patio de caña</i>,
        Instituto Tecnológico de Costa Rica. Escuela de Ingeniería 
        Electromecánica. Central Azucarera Tempisque S.A. (Catsa), Informe de 
        práctica de especialidad para optar por el título de Ingeniero en 
        Mantenimiento Industrial, Grado Licenciatura, Cartago, Costa Rica, 192 
        p., publisher: Instituto Tecnológico de Costa Rica, 2014.</span></span>; <span class="tooltip"><a href="#B19">Ocampo, 2015</a><span class="tooltip-content">OCAMPO, B.J.E.: <i>Diseño de un equipo para medición de fibra de caña</i>, <i>[en línea]</i>,
        Universidad del Valle, Trabajo de grado presentado como requisito 
        parcial para optar al título de Ingeniero Mecánico, Santiago de Cali, 
        Colombia, 92 p., publisher: Universidad del Valle, 2015, <i>Disponible en:</i> <a href="https://bibliotecadigial.univalle.edu.co/bitstream/handle/10893/16466/0527918.pdf" target="xrefwindow">https://bibliotecadigial.univalle.edu.co/bitstream/handle/10893/16466/0527918.pdf</a>, <i>[Consulta: 10 de enero de 2022]</i>.</span></span>; <span class="tooltip"><a href="#B20">Perdomo, 2015</a><span class="tooltip-content">PERDOMO, T.M.E.: <i>Diseño de un sistema automático para muestreos de caña</i>, <i>[en línea]</i>,
        Universidad del Valle, Facultad de Ingeniería, Escuela de Ingeniería 
        Mecánica, Trabajo de grado presentado para optar por el título de 
        Ingeniero Mecánico, Santiago de Cali, Colombia, 90 p., publisher: 
        Universidad del Valle, 2015, <i>Disponible en:</i> <a href="https://bibliotecadigial.univalle.edu.co/bitstream/handle/10893/16558/0529022.pdf" target="xrefwindow">https://bibliotecadigial.univalle.edu.co/bitstream/handle/10893/16558/0529022.pdf</a>, <i>[Consulta: 11 de enero de 2022]</i>.</span></span>; <span class="tooltip"><a href="#B7">Díaz, 2019</a><span class="tooltip-content">DÍAZ, L.R.: <i>Propuesta
        de un plan de mantenimiento para la disponibilidad del core sampler en 
        un ingenio azucarero, utilizando el diagrama de ishikawa para elevar la 
        confiabilidad del sistema de muestreo</i>, <i>[en línea]</i>, 
        Universidad de San Carlos de Guatemala, Facultad de Ingeniería, Trabajo 
        de graduación para optar por el título de Maestro en Artes en Gestion 
        Industrial, Escuintla, Guatemala, 2019, <i>Disponible en:</i> <a href="https://www.repositorio.usac.edu.gt/12352/1/Luis%2520Rodolfo%2520/D%25C3%25Adaz%2520Jim%25C3%25A9nez.pdf" target="xrefwindow">https://www. Repositorio.usac.edu.gt/12352/1/Luis%2520Rodolfo%2520/D%25C3%25Adaz%2520Jim%25C3%25A9nez.pdf</a>, <i>[Consulta: 13 de febrero de 2022]</i>.</span></span>; <span class="tooltip"><a href="#B24">Santal, 2021</a><span class="tooltip-content">SANTAL: <i>Equipos Agrícolas para la caña de azúcar</i>, <i>[en línea]</i>, Slidetodoc.com, 2021, <i>Disponible en:</i> <a href="http://slidetodoc.com/equipos-agrcolas-para-la-caa-de-azcar-sulcador/" target="xrefwindow">http://slidetodoc.com/equipos-agrcolas-para-la-caa-de-azcar-sulcador/</a>, <i>[Consulta: 20 de julio de 2021]</i>.</span></span>; <span class="tooltip"><a href="#B13">IRBI, 2022</a><span class="tooltip-content">IRBI: <i>Sonda Oblicua IRBI Modelo FB06</i>, <i>[en línea]</i>, IRBI, 2022, <i>Disponible en:</i> <a href="https://www.irbi.com.br/br/noticias/sonda-oblicua-irbi-modelo-fb06" target="xrefwindow">https://www.irbi.com.br/br/noticias/sonda-oblicua-irbi-modelo-fb06</a>, <i>[Consulta: 10 de enero de 2022]</i>.</span></span>).</p>
      <p>Tomando
        en consideración la necesidad imperiosa de comenzar la implementación 
        de dicho sistema en Cuba, se adquirió en la actual Empresa 
        Agroindustrial Azucarera (EAA) Jesús Rabí, de la provincia de Matanzas, 
        un kit de procedencia brasileña, conformados por Sonda Oblicua 
        Estacionaria, Desfibradora de los tallos de caña y Prensa hidráulica. 
        Posteriormente, se incorporó un kit similar en la EAA Panchito Gómez 
        Toro de Villa Clara. </p>
      <p>Según <span class="tooltip"><a href="#B10">González (2020)</a><span class="tooltip-content">GONZÁLEZ, L.J.: “Pago de la caña por su calidad con notables beneficios en Villa Clara”, <i>Agencia Cubana de Noticias</i>, 22 de marzo de 2020, <i>Disponible en:</i> <a href="http://www.acn.cu/economia/62373-pago%20de%20la%20ca%C3%B1a%20por%20su%20calidad%20con%20notables%20beneficios%20en%20villa%20clara" target="xrefwindow">http://www.acn.cu/economia/62373-pago de la caña por su calidad con notables beneficios en villa clara</a>, <i>[Consulta: 11 de mayo de 2021]</i>.</span></span>,
        desde que comenzó a aplicarse dicha estrategia de pago se logró mejor 
        abastecimiento de caña a los centrales, además de disminuir el desfase 
        por variedades, cepa y edad, lo que ha permitido cortar la caña en el 
        momento que tiene más contenido azucarero. </p>
      <p>En general, la 
        implementación del sistema causó la satisfacción favorable de los 
        productores, benefició la eficiencia agroindustrial y la estimulación a 
        producir con mayor calidad (<span class="tooltip"><a href="#B9">Flores <i>et al.</i>, 2016</a><span class="tooltip-content">FLORES, M.A.; PALLI, L.R.; HERNÁNDEZ, F.: <i>Diseño de equipamiento para muestreo de la caña para el pago por su calidad</i>, <i>[en línea]</i>, Atamexico, 2016, <i>Disponible en:</i> <a href="https://www.atamexico.com.mx/wp-content/uploads/2017/11/3-ADMINISTRACI%C3%93N-2016.pdf" target="xrefwindow">https://www.atamexico.com.mx/wp-content/uploads/2017/11/3-ADMINISTRACI%C3%93N-2016.pdf</a>, <i>[Consulta: 11 de mayo de 2021]</i>.</span></span>).
        Sin embargo, el alto costo de los equipos en el mercado internacional 
        condujo a la búsqueda de alternativas basadas en el diseño de prototipos
        por la industria nacional adecuado a las condiciones y recursos 
        materiales disponibles. </p>
      <p>Uno de los equipos lo constituyó la Sonda
        Toma Muestra, diseñada y fabricada en la División de Talleres “Enrique 
        Villegas”, perteneciente a la empresa AZUTECNIA. La Sonda se acopla al 
        tractor durante la zafra azucarera, y posteriormente al concluir la 
        cosecha se puede incorporar a otras labores agrícolas sin dificultad (<span class="tooltip"><a href="#B1">Azutecnia, 2019</a><span class="tooltip-content">AZUTECNIA: <i>Manual Técnico de Explotación de la Sonda Toma Muestra</i>, Inst. AZUTECNIA-División de Talleres “Enrique Villegas”, Informe técnico, Villa Clara, Cuba, 6 p., 2019.</span></span>).
        Su introducción se inició en la anteriormente nombrada Unidad 
        Empresarial de Base Heriberto Duquezne con resultados satisfactorios (<span class="tooltip"><a href="#B15">Machado, 2019</a><span class="tooltip-content">MACHADO, O.L.: “Análisis de la caña y su calidad”, <i>Vanguardia</i>, 2019, ISSN: 0864-098X, e-ISSN:1607-5900, <i>Disponible en:</i> <a href="http://www.vanguardia.cu/villa-clara/15675-analisis-de-la-ca%C3%B1a-y-su-calidad" target="xrefwindow">http://www.vanguardia.cu/villa-clara/15675-analisis-de-la-caña-y-su-calidad</a>, <i>[Consulta: 10 de julio de 2021]</i>.</span></span>).</p>
      <p>La
        construcción o adquisición de nuevos y modernos equipos requiere de la 
        validación para las condiciones de Cuba según las normas establecidas (<span class="tooltip"><a href="#B6">Cruz y Vázquez, 2014</a><span class="tooltip-content">CRUZ, S.M.; VÁZQUEZ, D.O.: “Procedimiento para la introducción de nuevas tecnologías agrícolas mecanizadas en Cuba”, <i>Revista Ingeniería Agrícola</i>, 4(3): 39-43, 2014, ISSN: 2306-1545, e-ISSN: 2227-8761.</span></span>; <span class="tooltip"><a href="#B12">Herrera y González, 2015</a><span class="tooltip-content">HERRERA, P.J.; GONZÁLEZ, R.F.: “Estudio de las necesidades de agua de los cultivos, una demanda permanente, un nuevo enfoque”, <i>Revista Ingeniería Agrícola</i>, 5(1): 52-57, 2015, ISSN: 2306-1545, e-ISSN: 2227-8761.</span></span>; <span class="tooltip"><a href="#B5">Cruz, 2018</a><span class="tooltip-content">CRUZ, S.M.: “Procedimiento para la introducción de tecnologías agrícolas de mecanización, riego y drenaje en Cuba”, En: <i>Convención Internacional de Ingeniería Agrícola 2018</i>, Ed. IAgric, Varadero, Matanzas, Cuba, p. 13, 2018, ISBN: 978-959-285-061-3.</span></span>; <span class="tooltip"><a href="#B18">Minag-Cuba, 2018</a><span class="tooltip-content">MINAG-CUBA: <i>Procedimiento para la introducción de tecnologías agrícolas de mecanización, riego y drenaje en Cuba</i>, Inst. Ministerio de la Agricultura, Cuba, 13 p., Vigente hasta el 2022, 2018.</span></span>).
        En todo este proceso la concertación de los trabajos y de los 
        resultados se realizan con el Instituto de Investigaciones de Ingeniería
        Agrícola (IAgric), por ser el centro rector de esta actividad en el 
        país.</p>
      <p>La aplicación del Procedimiento para la Introducción de 
        Tecnologías Agrícolas de Mecanización, Riego y Drenaje en Cuba, se 
        enfoca a la obtención de los siguientes resultados: asegurar que las 
        tecnologías cumplan con los requisitos técnicos y medioambientales antes
        de ser introducidas en la producción agrícola cubana, disponer 
        oportunamente con la información técnica necesaria para la toma de 
        decisiones en cuanto a la adquisición de tecnologías agrícolas, prever 
        posibles afectaciones a lo interno de la economía nacional y prever en 
        el proceso de importación la sostenibilidad de las tecnologías 
        introducidas (<span class="tooltip"><a href="#B18">Minag-Cuba, 2018</a><span class="tooltip-content">MINAG-CUBA: <i>Procedimiento para la introducción de tecnologías agrícolas de mecanización, riego y drenaje en Cuba</i>, Inst. Ministerio de la Agricultura, Cuba, 13 p., Vigente hasta el 2022, 2018.</span></span>). </p>
      <p>El
        objetivo de la investigación fue determinar el cumplimiento de la 
        calidad del trabajo, los índices tecnológicos y de explotación de la 
        Sonda Horizontal AZUTECNIA en el muestreo de caña de azúcar para el 
        Sistema de Pago por Calidad.</p>
    </article>
    <article class="section"><a id="id0x4debd80"><!-- named anchor --></a>
      <h3>MATERIALES Y MÉTODOS</h3>
      &nbsp;<a href="#content" class="boton_1">⌅</a>
      <p>La
        Sonda Toma Muestra AZUTECNIA se diseñó para acoplarse a los tractores 
        ligeros con una potencia en el motor de 56 a 80 hp, especialmente de la 
        marca Yumz-6 (<span class="tooltip"><a href="#f4">Figura 1 a</a></span> y <span class="tooltip"><a href="#f4">b</a></span>). Las partes y piezas que conforman la sonda se presentan en la <span class="tooltip"><a href="#f5">Figura 2</a></span> (<span class="tooltip"><a href="#B1">Azutecnia, 2019</a><span class="tooltip-content">AZUTECNIA: <i>Manual Técnico de Explotación de la Sonda Toma Muestra</i>, Inst. AZUTECNIA-División de Talleres “Enrique Villegas”, Informe técnico, Villa Clara, Cuba, 6 p., 2019.</span></span>).</p>
      <div id="f4" class="fig">
        <div class="zoom">
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6GuHudvpa%20xxOjtt12nLGP0Jg2QEFVcgHWykXWx/GuXOcY/Q6lpkYsEJUEEEXK38V8GkfuoDyGnLcxxvDYT8zP%20yBFA0I0WL3OCAtjaLknwp+Y0VTiu7OZ5fvHhS2Y8RguygP0TAHSZDAi+871Jp0RKztuZaGirjGPa%20d1rA1KzNz3Gun2SDcW+pgQm7eo+FdS7e0HF69ZFpeUxZMWd8Z3LE42cv5SdOlZ222jWt0yudmdw8%20PxX0+4SflMuPDY+ENa6Uho3lzvS3clJ0cj6ka531L4yDlsbBjla+GeMvjy2+tjymijQ/GlkR1lPb%209U++Oa5yTF7W4uHJwYXlsk8xLQTo26kXNVwyQYx8Dlf1kyM+Xld3IMbjZ73OM0DTuDHoBY9bIfCu%203aWWMe8zlHojtrkWDtDh/cYWtGFDtBaVQxp5GuWz+5mqWQT8hiBil6N1UhNL2X76njIoGsuTGNu5%20yPcpaTYlfAf+I1aJYk5w8A0hFPilrChPgECUs8UEbppniOGMb5HuKAAdarpnUSOPczyXLfUbuWHh%20uMLoOKx3BzpAbCPR00hb/V+St2ozBZjr6jdrcJwvL8di4MP9ubAcGGREdLGjS59kX81+tVS+WePE%20i1fjiB/9D8jKdzsMOLktdksMjts+5NsjWh3yg3JHSuHvV9ycHTsKJ5HYuah5yaTkIpm4Mrf8eUa5%20ryvqvYrfw/Y1xtW6teHI2VkkTfA8fJhYZY9zS6R28NZdjQR+RQHAGtkoIY55DEOXivhsC4HZu6OT%207q027dLkzvXqUHM+RwJoppSg9tpAB0UC1q9ra3E45nlblGmMEte6jU1rJlGMfoZGqpfxX9vGgMY9%20+n7GEVtrKBcFbfGmJLLLlj6x7zYghU8mkBVFz41nrmjTTGEZ9u5VFFltcIb0fAa548jdiixcdqFR%20qf2XpS8UPMe8dO6DLEm7ZuG3elr2RAftNRuVnxLpaC48EyFHTFCSEc4X187aJ1Feduyd22vAdZTy%20A8BAiKqdVUW+K1NUWkMnzvAI3OSwTVB4G3nRISIHIYfLzsUCWPWpzxjHMBJ8m5XDRpNwDdoQnW1x%20QsfIINHSAKD0Vvqsug1uCRe9CGaOc5bAOA1BAQAj0qdPupkpiRepNi8uX8Sui+NEOAN2wTOW2ny3%20WwBQEE+PjQ0GYm/FmIDiPTcgJZo6r9gqkoCBJzSGoQmtiENvP7KfEljXlMWXI4fPYwECSF7dwNvU%20Et99K7hYxBVVmUj6ecVll0+IGRtdhwRMc5qkhxNtv2FTU9peJK7rbbf6nSON4WOPHL8hgcXk+ktC%20NVUH2tNdF93Mxptxj9RtkcW45TzCzawoHNCjppuVBqtFdzIT2i+dt478fiYoXkktLrnzca495zY6%209pRUlKyNCud3FHY5QfmQr1KDSmiLFc3+kkuIRVGuqj1Wv8KpLgTLM+8SdQQm4CxKm6B3gv8ApSjI%20GzIdtaUKALsNihS+vmUHx6025Dqk2XUIqAKNCAUAHRNLga0MGYc94UC5uRZT4buq9ClVkSR7zt7g%20xwiN/TSbm3S3j56dKSAkCoKmzkKgobBWg6m/lVLQJMjaoDgVKg/+Y2PS1+lMnM2C/K5BqrT4qVv8%20DrQ8swNtxQnRUK2BXaSngNKa1jGP2E0b7SQjlLSfMWPS/itTJSzM33FAngV6+f7aUYxjUINgAeit%20NyDayeFVIkKMb43B/jUt5miSFGs1RbhDfyXovhTTH5ijWW6FCNy3sAPj+A8fClOMY1JNyxqIqaBz%20SgKJ9qfwoTFBl0bQ3a031I0RbH4LTmAgDCoCKCdPFNE6+Hn0okDQMJJ27SioL3DR4r4G1EhAFhU3%20VDZtyhC6nTpTbBG5agVAC0krZbfiv40SEGEIBQ6DcLhVvoP2K0SEGkjQFRT8y9SVUKnj42oTxjHM%20cCTmqviNF+CfwqxdIm5pb46/j4UyWoNXE28T0/fQJGHOGmqaiwJWw8NaAAizlVyqAh6G/lS8sYyF%20IH51tdE89aANF11dcADqo8bp504BMRycmDFx58l5OyBj3uS/y3KhblaaBo8kZuScnNyMotEgnme4%20ONtwLhtC/jeuhKEp+n0JTL/2g/8ATdstynP2AF8z3roxqXINy3cgt5r401RN80K1oHeH9UuGD2RY%20eHK1h3OYXbWhqkuCBi2+Gpr03V8dfb9ceyDy+hqXlj6Yy0Vt4v6o4T5zH+kkjuTJuIYWgg+IF9PT%20r4dFxv2LtljE8S6d106/25e7GMr1xWfFyOGzIg37CS1wcqqChW40T7K8ve23S0Ho7O511kqnfX1V%204HteJ+NC5udzPytxIlLInIgMjwqAf061mqzljGORpByDH7/zs7k8zI514ny5Y3nFkcpihK/9FjGr%20rY2vT3NpvLGPA0rZY1JDsjufP5D6kdtsKRQ/rYGtjaApKlV01GlWuya23b/tIfcKVVHsGuA6TlPI%20EjLlJQ+ool+ptqdUr26L7UeJZ5if6qeCOX2S5RG9oY4+lSCE6m9K9ZQ6Whkbwc/FT/T7incvjszY%20MDGMjsd7RIrmOXcEJBWub0Zl8DqtuwzkfdfPcpnQYufhcPFxHH8mXjFdGXPJaCAj/wClx8AKye3E%20miaNuzu1O/OawZMvhOUbjPhd/cxfcdHL7zEDSfiPG38E656THuzCSI73/wAvjQcazmGGTOhe9uZ7%20h9x0j1uq2St6vGMchVzzOycF3TlcViYONzUD4cDJgbLhznRsTmqGKNQ2sLLkUvEuGM2LOhjysd7J%20saQb4pmEFpGqgDxtSdYYPPU1lwoi4FzWueNqlFQhUHjTUigQkgxy4b2tL7t3OC28rea1dauCXZI5%20Z9Se4MnkuTZ2rwgLpZhtmljABlcCPRuGkbRd1XtqRt6t/wAFw7I7a47trjxisAdmSlv6zLdfe8hE%20BQORvQVpahkt5yRn1i4eeTgeMz45zJLiZDhG5yWDgeg6Cs6ZPLXGPiW3lmVb6L8jHH9QMF0jmsbk%20qxHekNe0EkKSVJCGs+8pKTXDHs/U12XGU49h6F5GV02fmwRlrw/jnhWEO1eQVQ/dXFx9htwkkeKm%20kfx+MXN9RjaClwoCXJv0qyZF5pWbSxHeqxLRofG9qaQm0V3l8OLNEUZUOa4WaLoqek6V17d3XMx3%20NvqyZHcr2lBjQvmgmc5rAXujcC2+pT7q22u6dnDRzbnbJLIqMnIcexzwchjXtYZNgcA8EFPDRSnx%20rbd30qvPMy29pu2ZXsHvDh8SbIws3Jccgzf2mMY6R2x12KQPC+vlWHZ7tnVv3G/dbEPGPeWxkT/b%20a9CGFDu0FgqjzvXY4bOSs8CU4/tzLzYXThImM+UnxFtfjWO7vqrjU229jrQ0k47JiJa4tGqbehNk%20I80qluJkuscBP21cbKB6SLBOgU+NaTnqRJZuJyzAkRd8h/tlulx1t1/GuHdq3md2zZLImJxE9gRx%20BCENI9QXw+waVzo6EiJynsjDiXXsUJshSyWW1Po9xDsNhlscp3Aj+klQQCuhFrCq9JkrcTFFcCC4%20gAKXLoE6L5dE0qI95SsYDyHBxJBQOv4J08SRSzCMhZgaDtIBA9KHRGgWAv0vTx7wQ8EoDCABolwP%205VPUWhOMpIpBS+1UPgQDTl4x8AQpNlNDS0gAOOvgbmw6Cij5CbGbiySTYQrHWc4jqLi/201oTlIr%20zUcEPDZgBVIDucgS4sAo86nc/qa7fiVH6Zwrm8u8HfuixxuIQAlCnWubtYjI13nnmXiV+5oCK8dd%20ShW3XxrpTMoE42hrC5ttT8Cf9aJBIs3EO3YDCiXOluvhWN3maU0HlSUVXvVyHHTqHAjQ3T76uujM%209wrXutF1IAJAA/BKuOBlPE2LlCWAPRUKaoTRPPGEEigeDrcXCE6fZe1utJp/wVJv7hLd77hASLJt%20JOnx6UozyHMi42ghou7VftsqEaG1TjGPeIjpg3/c2NbTFkS5XXrTURmMf+24O+YtGpeUAG2w+PjV%20dRMB7LmgbiAn5xoPHUol9KpsUCjGgqLjo8KpC9Cv7+opBAGNGkNaU6BbFD43+FJsaFWu6i4OhHxo%20KTNXNBQp4jbYbl16inImZaoJXRbff9lMSF23UaeH4Hr0pGlRRgBIC3P70NglTIxZmgDlBJbfoSVI%20BA6IdRRIGWyAEE26hAAUGq/FL/8AGkAKoLCVFkAupXqR1uaYSbnaXE9SqjyNid3h53/mZgYSyg2I%20BACdAoCKUsnwo6iekb8nn43HYcuXluDceMj33G20Ov18xp0++hsOkIMiLLxWZMBLsedu+OUD5wQu%205DfT7qsEKv8AzKjiFd0F73T4a0eQI0LgpLSCdQSqWU263NEhBoNqo0oBdunXx605GJym42gm1h1S%2050OhoM7aiRNrDoqIb6+NUiIE4Z45omSxSNfG/wCV7TqmqU/GBmUB1QKLAi3gLfbRIGTtR17EFQ4a%20Aqi0p94QYeB5obIupJXxWyfZSVkEMp/1VzMnH7JzpseV0JDmNM0bg30qVC9G+Na7ebyJtjGOB5nQ%20sjDU9XpAbopvZ3ReqdfKunXD9wLizpHJl+F2Q6MgEiGNoBt6pD6rK1S0HUfda09s1a/t+Gv08PMn%20dUJ54xjnQsWIMeA57dzgSHqJGtACkvYGvXw8ta9mqla5ZLz/APjGscMsp5+e3jHvLfgTcZBAJXch%20C6BrhuBaU3gera5yhSbetrvG6q3V7iht8sR+0Z8mcL2rSqrHDHhnlEDvmvq/mt4aPhOAXFhTZPyT%20h/ec0m/ttJO0KU8U0AFeH3DV7u3Bnt9ttutOnisfy/aVDtjtXuTufkTjcNjyZMjy4z5rysTATq+U%20KvzKVufKud7qz+R0uuZ1Xtz6bcX28O58lkrc2bi8FuOzLc1Wsy3tJlMIOgbZHahTU0u7Xz44/kW4%20vtZzv6YuP/uH21/X/kYdxTUWuUB6r/OvY7iqW0+fT9M/2+mpwbTm68z23XzR7ByvPB/VSFPSSS0F%20DfcbqPOvbpojw7asbyMWKYAbjsKORToi2+6i2mMePiOupA9jMa/tDAYW7mPjkaWEggNDyDcJ8KKP%20mXuTOQx+pHH8hxPaH6jC44S8Y17Q50bP+k4v+cJ08a5d3cqmlH7G21SzUvU1+lXDc1yzsjuaPE/Q%204ma0snxnl39yVm0e7GCtiAR+6ppur2FW21wOf/WKN3+Se97ixzZXCSIkqCGjRbdP510OG8eWPaLb%200Oy8NPDyPZ/F4WfA3Ixxhw7WuUEEMF1an4a1L2U8+ZPqw4KPLi929gZUmdw5dyHbsrlkxXer2wDf%20d8zg5dC37qLVnUqt51eMY53ft7vbiO4MBk+DO1021J8Qn+5Et00uPNKmu1Lli3G0Vbv7u/8AQYbs%20GBz35jm+258R9TPc+Xa4KN5CqmladMaGdHLl495p2N2tLxOMeS5Al/NZUYD91xDGSoiBCHcR83nf%20467W3GpG9uS4WPAueFFA/IH6kBwupRfEE3J0pbtoQtvNif1GdHJ2ZM4NPttkjbGQSE9QCr0P8a45%20asuZ2rOrOO9ozs4/6gcYJI/dhbPsZjkpuDwm1pI03AXRa13s04x448PEnbXHjjHwO2ZuIRymSWcH%20kQEYjykUxUgP+ZTZB/GvIhp5HaojMsHbfMckONYzMZ8rWmEEqQw3Cmy1tt1nUys4JabJLoxuBA1Q%203U9CnlWyWZKGcuQLBQzaAVFugC+H5bVQO0aCcuV+ohOO87mSNTcbOAcLuU1VYTkiy6loeee44e3M%20TuEcfwzsybLhlaJ8hC/H/qIcqqACdNDVb+4oyev64/UW3tuc1j4iPM5XdWB3Dk5HEYr5PcRm6SES%20H5flYXaDxNc3ab9aVh6fPHPU23tp2crGOX7HQOzu7+WzDi4XI8NMxQmZlElkMW0a33LqbLauhdyn%20nP64x4HM+2a4HT+MYY8UxRnfG0Euc0gW18yL1FrqzmTWu265RAx5GFha7+2rvU5zggII8VrejZlu%20QU7uTu/jeAxWyZUBmyJtwgxox65XNFr9P5fbWl/tjPUyp93Ake3uabm8Vi8iyB0P6iPe2GRqFnRC%20fs6VTqraMlXglZeUyHNdtG1pAaE+bqOiIT4VK2kW91tQxhlZM8wLXXaSiajxNtE6VrSqRlaxpBCT%20MGj0nRxAQeQsq0XagVE5JuLh53hoMmwOHpGirqK5Lbh11oSA4Ulg/utBaihSCUTQ62PSsXZG0Gg4%20otDQS0nQFb2KfilJsEHsxxD5g/oEK6KKTcjyNZHbAriB4k6XOq0oyhAR7pA16mzV/ueZVfMC+lXm%20SxbDj3PABR9gG9EtdL/eKbgQ+5fHng4DMUep0ZDTqPXqfi1Kx3bKMjWmpVfpnhMdmczOSgLYWOa1%20QfQAQUHRD0rDtnjHHmbb0lwWJTZWDqRrrqhroeRlAk9XuBDbkABNEFglLMGiycSAMFgGl0WotqXU%20eVJRVu9g5cUgWAd6lspLf5VdTLcKx7e0qXX6fdVyZQbCADVwUa2Wx+H7eNSUhVjGkelqDq0EqdQf%20MgJYUmVGRsYntO5ULbElAES6L5602EGm+QN27nWU7yLKP3qtVApGXur3Tjae2zBcqdHbiLa+FRbj%20zKTJZsjwQ4bQbBztFW58ulGuSxj4CN2ZAKelwafl0KpY+PjQ6MDG9hG4ktZpuS4IUa9daoQoyRiA%20luxTduhXVTp4GgDLXBV1Dirb2QjS/wB6UNMDbadvW9zoCbJcikoG0ACXRSNPE28zVMk3BS6X0Xyp%20QWhRsgsT8Toh8EUU4cwHUhRkmxUsALgIL+f7a1MFG27og+HTon7GnDEZ3bkNzYgG/UHUedSLQ3ap%20LUUqgb16afj8QKZWhsHOQlupG4FNHfLqNb6eaGkAw5x8cmHFG9odG7IiA3XDm6I78ClMQ5eAHkNY%20CB4HQJ9taCNd6EODACLkEBCir9i1IQYKAkLodNLaVWYw9QANlN/GlAGj2AuJLj10S+v4fbQmS0iP%205DleP41oky3ooIY0AucSh6Cq6iGiqfTzuSbkeJjxYcGWURSyiXLcQ2MNLkYoPlqKUhBdA4KdbC+p%20psDIeFQkWKFVHw/fQAm5Xelf7Zad0hKHzt0pMCjfWx4h+n2QAUjdPDEbgAK4oOlvT1rbazjHAUe8%208648Lp8uHHI2mWRgCNBDRvDLak/A/dW1slzxjw8wT4nQvqPsg4LAx1R7noFTc9rAhI6kApT7Gk2x%20jmY79sjnsSBwc4Ne25KrtTqpBaiLXpX7lVxjXPT5nNXZdjWaXIyS2IEuDUDWC7iQjSABtKgdQOlc%20G93N7OKv9PqvH4nXtbNaqXodH+nH0Wze4IouW56Q4XEO/wCniRj+9MGkFHKAjT1Ovwri3G1qb0vW%2039Tu+LjcP21wMzePxmYnHYET5nRRjaD7bSS956nzNZZsrQq+Qw4X0qz8nIVs+XFLnZLwACZJSLEq%20LoOta7M9az1Mtz+rOG/TD/8A6J2yD845CD1WSyrYrr5V7ndP/wBduUfH5Z4ZwbX9ke3K+YPZOb8p%20jSR5cjCVcHbgH2KOv8xsa9bbsnVM8e9H1MZSxAiQqDHtcNQh2suB1TzrQlKNDT6N8aX9uY+RIA6O%20EyMAKkPIcR8yf/F51xbu79qS/g7dumcsmsjuvi+W/wApwMTNrRA6NSNpCqxysKWBb0/1rnSbzNm+%20BI9mlg7U4uMuUtxmMBALR6RtFvOhrMSaaPOv12BHcGSHGwyS6w0cW7Qb30B8q7dn6Yx5GL5HTu34%20Hx9vcVu3HdiROL0uR7YJ9KWroq5Rx3rDHpILSwlWvCFpuoF9DerZEs5Z9ROE43tyfH5ziMk8byU8%20iDEiCseRrIG/d6dP452OrbbazG/Yows3n38pz0/u8k7acGJzSNsp1kePlBI0H3Vnt3U8ljElbyar%20lmdaiwciWF80cbpIWkrIAT81wm35rVv6teZxqluQ647Ihx/+rFukcElL/m2gC1x0Ws71nNGu2+kY%20/UPlsTK7WOM8NjGTOzabNu0KA3p0X4Vybm26tHZtXVk0cL5SV/H8rg5rSYxC5kjg5fmiePVtC2DX%20LbrW6zx5StPmKryZ37t3vDH5vmmjCyG5Qdhlkntj5S4qWvT07q5d2i6oK27OMyT4KbLmxd4ao9pi%20OKH0jcBpfpekklxxjHEvNmMvlMluQY4YmyMF3TFytU3S1Zbm8kaU7ezGU2e/eQSYpHn5Sb3H5CdW%20r0HXWud71nMfx7Dtr2aSkjMzujisTe7M5GCAtcWu3TtLtqEh2xVId4Dx8aluzcTwnH7+42WzVYxG%20X7cCv5X1P7D49hYzKa9p9bWwQtLVLtxbuDSA4Ieo/jUenMz/AGx/JSVVlk1/Plj2og8z68cTH/8A%20I4U0oIDSJTsudpAC6i5WrW0ox4+328QcIp/N/VTuHlYxC/kW4cLgWvgxWhpBOiyuDSl71p0Jrjjy%204Mlxxx7yP7f7653hMgS43IZObA4h0mPM+4tuDgp1RdPtq3Z8FGMeSIvTnD+v6fM6PgfWjg5I5GZE%200uIZGktknjdKA9wuQW7j4fGnTd3FpnOMP5HPftavQgud4Xk+53Q5+Bz+NyOTggjEeHCGRbISFCae%20FaLuJ1Rz27V1xj2ln+nkPd8e9vL73QbdhZMixvbdY3aPY4eB8K9Da3erU87eo8Y+pf8ADxDkP2g7%20OpcRYf61V7QRt0k3k4rIa/5fQPzMAKgX08/30LdTH6PuG0s2Px7TPLK1kTXAB7iQFBCeV/Ch2lAq%20Qc57i+qHJcXymTkcdmHIw/ca6KFw+ZzfTsHi0uIulee87ZHWpZfPp33d3X3BHmO56LFxGwta6AQS%20NJ9VzuALtFvVLwLTLjE5j3O95yBo9PUny0tSgeo6bjQtHuvsERoHVbLek2Esjs9sLnK1yBQdUH4q%20mtCzeMYkTGsGLA57bustndEI8vOqbFEkm3J4zh243uHdLkPEUTk3ep2inoL61DzKSFe6MuI9vZ7Q%20/Y/2iPMXRQuorK9XBrSWymfTmVsJ5YtAAd7TWH8wRo0SyX6VHbvUreLxj+y6JkjmptKFSNSgVTr1%20/wCFatmcGhySXHYEJKb2/EIANUtf7KUh0kzwuZj5eGZIHb2MkfE4i3qjO1w0HUVLLroPqRRV+9HB%20pxjr83pJTRCvwHVKqpncrV0UaiwCJYXFOeGMfySZag3AA3HqS+h/n1pQKBUOsUTq7cboNpC9V6ra%20kykKte24AVrQ3TaoBCi6olGg2hBzS5yi+gDvHqbdP/DWi8TJwRbmkd0xNLdx/Qn0of6il7ik0VOR%20KgAPXaSV1XbdFTy+FaeZLZkNVAqEmzgmp0+5elLIUnLMjle7sn67QYOHkPi4THY0S47l9sxtaC/0%209HucdafUnqX0wjrQY3eVdZxNvD1DVevjUttkoXYRtB1BRFv51DLQoD060FrkCW0QnSgIM7AAg+P8%20aaBrkY/uE21RB0+F6JJhmwLrHoNPjTXMZsrwbBLX+ApCzNlIJ1CKNEp5lGS91rXshOtydVoEZ3P1%20UloK+Hq62UfalEhIx5KQD9FHtV0mU1jXAKdC4/uofiDHe7zQDRFH2EfGqz9uPgICLFVQ6EeItQAM%20B3AqUd4X+P4GiPAEbCyfxup/YUeQzXcADdT5eVA8zSRoc1wAbuLShc0OQ7ba0eBLKx9P8T9P24Gh%20C500znPCAPO43Kaa1K8QehY0tcLf+P8ACrxjHzIk11ahUWQEAi5t/GhiAN2elSfF2muimgZyv/uE%20zGx8DxeFuR0+QXlpJQtiap3NHQVtszPxxjmRb4HCopju9xp2vaha8kpueQNx+BI+37K1uuCGtcx/%20yfN5eTI7Efle/iwljYi8W9wNILr3U3Xx+2q2bdOfnpjxJtSdCJZK6c7WBqAel1xpay6/z/GaK27Z%20VSx+5dunbrL1LVwHFYscjJZB7jvzS7RKxqkfL8SLBbEHyNer2/Zrbht54xkeN3XevclJZT4/LxPR%203Z8oi7bgdNK3aC71OLWhoB+T0kNtp5615Hew7ytD0u0UUx9cxt31nQycA3Bx543zcrkRYbAyRqlj%203D3SCD0Z9lcihHVJr9QZcNvYnN4sE8RfFie1G2ORqgt2gAAHw8vurTYvVXl6E3VmoWpwH6YQzH6h%20dtl0bgmfAXKEDb6rXrdxv1e21Oqx+v11OTb2bKyyyk9tV8+emUTm5GSZRfYtA+VwNj0Lvtr0thQj%20zN7NjD2HlwjRCWnZYu0AGpAsb1q2jOteA4+l8n6TsLGVGiGWZu0GzUfp/wADXm2zsd6mtSh968/D%20jc5Jl5DMrGbGA12ZiHY4qfAiwv6lv4a1pVe8hLkyU+n/ADszuNyGtyv1YhcJceIn2yyF/wApCgEr%205ihOMhs5P9Z8qXM5D9bK0xOkkeTjqrmktCjw6eNdO00sYxwMzqPDcwTg8PhSGBXYUCeoh/8A0wlj%201I6U6bqmEZblMYx4EpnZUGDivyMgoxrVAsCSSQB1+NbOyRhXbbZQu3uzeY7557K7gzGmXgMaXbgx%20kemZ7Gt9LG+r0NcPUut6we4k8/bjy+J1OlqrLGNS58n9Nn8zxzDIwYWewNbDM0I+2gcBq0D9kq7b%201ZIrW3EieP717u7GYOG7gxjPA5f0uft9CgIu4dPFfjXNeqblG9ZSLl2XyGF3Vjx5uY2OLMjc6KbH%20aQ0PLVLXALcIiUeo6VhELaVrZjP6p9uYsvbZh45gdlnJjJUn0te7agsbKlc+9a90k9DbbpSjk4N3%20VjSxrHI5oycZ5x5hESWgFCCiX9Q613UqksY8zNObQWDtjv3ubhYIpOOwo+Sz44XNw8WCMEEPsXZC%20XDlGorzt3rd4x7zr26VjljHgVjM+qH1RDHZDnT4GAw7ImRwFsfzf1kmwuhp9Dg6dvpTITM+pvfeV%20Gh5OQxr8qhrSVsVaD0+U/GortpZtZ4k2e5DIHK5/mMqRn6ueXIcw/wBv3HvJjJ9SNRQb3tVVqteO%20PpqJ3aEH8hvO6b3C9wVzn36lVJ+AqofDGPqJbhhmRE6wcjkBcNqa/wCt6Ia8OOMZi63xNZZI3XCB%20+03eSXBLKfH91FMsY9xDSxj6CT3xbtpAf8wcCCEVtzY+I0puXxx+v8CyNo5N0rHgklxbtAKgpY2H%20yp++k1l5jq8yzR4rPbjT+lisJJuiqpTw6Vz7lpZ6FafbmIPx8RjywSNDiNr9rtpcBe+0t+NGanl4%20eeNRdFG88fQcQ5vMY7Guw+VyccxNUOZKXtDf/CfwpqzTyXgYbuzPGTt30Y7z7h56efjuTawx4kDZ%20H5qHdI7cnwXX9hXZtbtms/Yedv8Ab1qzquV+nwcb3sqdkMTgNrpHAA/AmteuWc6qlocd+p00mfkY%200eNkNm48ERthieGh87yGjd1Db/Crtup8sY9hnSjRSO3/AKbZvOZfOcf7+/N45u7Da1yMeQC52o9Q%20TwNY7fSnjCKtaxN/SPjoH8iGvBwua4lZffafRkY79wMbmOtua46jpXTNebh4x8iLdU5Hb4W5LHmY%20tAUIguBfSx6J/Cs21wK6mtReTMzdojLghaAgsirbWs+lFSIwEverw5WkIT83S34XNDWWQdUi0TIz%20cbUBsRoUSpgrQXJg9yLcfU1xMbv6XIQSB8KiM+ZcoZ88DJw2U1CG7TYkgHxKjp0rPcyrhl0eZWew%204nyP5IqWtWLeRZxcn7Co7bJF9ws8eRc4pZWN2k+C+Cj41pBjIm/IaJWtVUIULe5H2r4U61E2SP08%20kMnAyuLtx/WZQ3IipM6oepsizUhlU73JDsbqAHE3HiOlUjO5WWm/pK9Gog0Pl505JFRoXaAkXNkc%20ShF9bUgaMgyKNoufUC4BddUAQJ50a5jU8CI5rvHt3h4S7NzGb0/+XYQ97QAS0ID46VDtBotp28ig%20z/XPhhmAT+5g4kiuxpGNLtxa4D+41pW6a+dR1N6HTXZ20szUfW3stmSyR0uVJI1jmDJAJ9BVWkbb%20gHqmmi0krazjwL9OmhOcd9X+zc8ujh5tkZaAyGOdntku2m5B6B3h0pTaqnDz+AehRlhw+8eHnlYI%20+UwpWq0AtkA3EE+kAKnT9hQ73U5Z4x/JH+SrUp4xiRh2rh4sXL8lzUrDLyXve0ZnSDaWP/KxUvpQ%20rxwxjhqR6E5LGOZbW5ke8AxuYehFwNvpunx+74Vot7mQ+1cZDmKaN4VjgS4BA21+uugrSUzB1aFm%20kgjd6V6a/Z+FHkCYoCbroPsplwbA21pSBmyL4eIpoWMe4yiga/E9KchBgAKNwt4dfxpzmBkKAbeV%20vjp+NEiM3VdSdSbr1oQzIa5FAUi4I8l1KrQ2IjuTB/UcYnyjLF1T8jrfCmgY+LkRSTdQBax86XUK%20DG4fAn8xv+/yqkxAXg9FX79aIBeAFxH3WoYeYB5VTb4/yojgNAA65TcdpTW9j+xoG0VLtrm+K4/t%206N2bO3ELppl3FXA+4VNlrN2jUOGQrkfUXsyEOJ5Br3NUEMBJH/Gj1qxmL03MJZjnH7v7Znw2ZQ5G%20FsSF+x7/AO40AkAuAv0NUt6r9pde33GpSG0/1B7Lgic53KQvDSSWsBc43NgPFaj16lrtNx8IOOfW%20zu3jucz+Mbxk7pcfGiJlDmua5sj3WVT4DWuvtossY8jn3tu1HmjmMj0G8D1AhyEoFX/l0rW9ssYx%207CUs8g4zCl5BxYwOEEJ2ve0FF1DfMnd+xri3LxMqTq26JvWCzOeOLgjwsbj2TZTgJW5bmEligelD%20Zdx1Sqr3lktFnjGERudrSc7CcOd3IyQPhhDGuQvY2MBugCBpFk2gfzq7d9uWw8Z/MhdttrHzN8o9%2025GO/F/WzDEJVzC8IXEqg0T7LVyPdbtLzNEqVUETicRycPIRsllc07TOom+V2m5qFG+dU7SvPHli%20R0slmT3+Oyi9HZDkVXI4lfMqQqfGubptryOt97Tgif8Ap5xr2d+dvy+45wbnRBxeHO9XzfOV6aeV%20Wk+rNmb71OvSqxPyx7j1/Wpgc87w7m7a7eZ/keVeT7qiCGO7pXNtYJ0XWun1elQcfRLkqr/r/wBp%20Y8r3HEnDIw1sW3a5zgTfTRD0rPrkutfCDTszvnh8rtdnFQSgz5GTNNK+ZWtihc8Oadw/MdQKmXMl%20uNCkfU7AwXZckkHLPzOVkcI8qOOXdj+z+RzSSEcdEHjot60ruKY4fwEcx63k8vjOPyG5MDMPKnii%20Z/eYSjggY0OYji2+ulTVvllj3Ev5FJ78k3cPgBzw9ZHbpGq1u8BHEbiQngv+g7NpvMyackj23l8h%20yGThe68Qxxs3tyCxdojG0EOIsCB9tYO6l+eMe8q1VEFtwMfP7451nDPyyOHwnh3K8iBtJbdYmXLd%2079D1Da23W2se/wDQmlEs2dvgdxfG4MOBgMbDi4zAyGKPRoboAlq5VRmrtwRGc3Pk53D5eNFOcGaW%20IgZwCiIjV5XRKpOM0SzgfdnccXMYTcbAfNNxOFL7UeVluLzk5ACPl26BoNmihX9orV+pXe2OeyMb%20kcRrpJDNiPBLInbQA0gtLUs5vQ10TOa1xj9gdeeR1rmvqRHyPFZMEGBNJkyNYIpoyHsDt4UORC1F%20tXLv1bUaF0a4nL++uB5fhOTGByGR7jpoRkOc71bg4qlj8xXw0Twrq2rfapRDiciZ7Bgkx8SPncOY%20wT8bOf1jGX96CQFrmP1APqJFtUrm3L9N5eMcTqiatSS/1nyZo/p7iwMekvPzxRxRu/pU9VVVIVft%20qvVrZaYxJnt7TTbfAqvev075Hh/ZgcwSQw4zJgIGAvL3MaXGUmytLj8ajqjxQnfMcfTrsjt3lu4m%20dvc3itm2RNyjkxvewTsLfU3cCLt3a02upc3jH7FV3bFvyf8At57Ffz0mE6fLZjSPayD2yNrA5pO3%20ciqNt6SUZpIpbzKF3/8ARbF4fvTj+2e3co5mXyMTsosmCe0xllc4W00t+FLhjGMvHWlp1EeA/wC3%20vmuWa50nJw4rke+NgjMjSyN+14JBHjof4UbT6lJO7eHjGNRTub/t35Lg+G43MdyRz5M+f9O2KGJA%20wyEFpkJJJ6r8KtLMj1Eit/8AtjycU873sfIMeSdsT2ghXQEu/uKEbuIUA2p2o9NMY+HmTTfrIpjx%20l74GmSz3MY548S8BNzrDre1q4os3PHHx8j6K8JNJQ/2x+x3Difoh9OmcvGRxLpnOjcTDJK8tLypL%203KfPTSu7col7T5qu9a0yVj6ydm8H21LxjeJxGYMWRHIJYGFQXA7gbr9v+tc++08Yx5nqdjuPTH8k%20p9Guc4zh+xM/JypGNd+pc8Q2bI61hRtNVq85Ofvm+uMY+pC90d7Tdwcg3JkhkZx0cZdDhzIWMcWk%20BwIsb1zX3nYyrWM2Unk8p+XjgySxse5C0MCIh/MfEVMvV/XGELJIe4vN5+C8SwlzMkNDPfiKFCL3%20CKdqDX4JT6mnPmGTWZJY8+XmT4T4xG57mOeJg7aWtB3OEsi9EGtV1tTrjHEGlw1L99Nu7OFw2T8d%20yGe+TIyHmQSuJfAwANAYwuK9bmujb3czGyyZ0NnI4BzDitmZJktHqYCpaDppXR1S8iYFA6CQEA7Y%200sVQuI1+xLU5fESyGUwkdIVKtK7XAWsE9LboBetlEGMuReNsJycdwGxse9QQQq/bopSuezzN66Ge%20emjdwOVG4owsu5RqPs8UrDfl1aRrtf2RVuxpMiP/ACZ9UgL4yHFCvpuSnXyrPt495W/ORZZMycbh%20sDSfIrp4jqBXTjHtMJkRic90rS47b7i5fA638hTdVjGPATJ36YZAyO2XytIc05uYhC//AMw/VawZ%200pQi20hlT75PqxQoVHoOt9qfYtVUi5V2vduBVHG4B1GqUzODeN7bAXtt2ldLLr8aTHIoHaeoFQ3c%20oVqkddPKkNFJ7h+kHZfLPyOQmGVjS+2+V7YJ3CNULt20/wA6ULia+o3qeacmWCJmIIS1wga9jg5B%206fcsvQq3UU1l5ya2zRO8d2P3Nlz4sz+NmjwMz+82cgAiFdrpNh0aHhNL0X+3weP1+ciSUw9Bp3d2%20lyvbnJzwZuNJ+lD2thzXRkRSWBTcLAXFOlk9C7QnCyI7i+Iy+S5HF47jo/ey8yQRY7GlC4opKjyW%205pdKxjGQnZ8Weg+F7ZyZOxs/tnFc9j9jpYpGPIyDkxizRILD1Eg301rFVzxjPLUXqxoVvgfpf9bc%20dpnbzMfGhjHynfIZCSwbk23u9PxrR7Sflj5ZF/63wLf9LX9+c7wg5XkOVjZsyJIHY8mPtlJZZd3R%20q/v0pKimeZG73CzlY8jo2BLmNcMbKLZJ44g98kahrlKaO/nWkyc7XEeNd0HSyjT8NKcE6CgcQlrH%20SgqQDqBybbmm6qOtCWYSZbc9VI/jS8BN5GwX5rA66+aUwxjGogczDG5Z4m7FDgXttt1X4JSngV0v%20kM5O6u2Ymuc/lMexQEP3XU9NKl71eZS2r8sfsQ3Kd/8AaUeTiuGcJseOTfM5jXOcEadvyi6+VT6/%20IuvbXfgNsn6r9pxBuxuTPIqOjZGWp8XORv40/wDSomB/4nxaQxk+sHEGJr8fAyXuRpcx+1t3flud%2033j8aT33MRhYwiv8a/7l78vf4kbkfWLPcD+i4YIXIJJXmwP76T37RjH7h/kotbjTM+qvdZLXY+Jj%20sahLo7uBugu4g6X6ffU+tfyK9LY4vH0GOR9Q+/ZJjI3Jhx2A2Y2Nu4Kemn7/APRO7c4zFOwlCT/U%20j39w98PDRJzE7nPBD/bO1qeI8vGla74sXq7K0rHzxyIz2eSmDhPlZDWISN0h2k3C6ePXrbWp6Zzy%201xjgR/uo08pETw26P1Bx2uBBsPmJFrpddeh86fQvEl/kYeUGw4NASIgTYtNg0hxVEd4J1+2nknEC%20/wB9+LWPmRfLcfyn6mKPGAixy5S/buBRUIBPhp8appNZ4x4BTvLxlrj2Fb5r3mcjJHkFr5Axrd4T%20rex+06fvr0e3qlXy/U593dtfN5jbFwc3Ok9rEiM0oCuY38ocdoJ8PvrSy4i0mDofH9tnjuPixLEx%20NWUj1J5OIF7khdRXm2T4cCXvcUbu4Z5dLtke8SEbA53pjQEbW/EotSkyVez1NMTi3tB3SPkcC9u5%20BuRyBXA+iwIRPFb0k3jPHt5Z6hMxjT4jp3FMcSDEAXqSLIrkO0XJ2+nw/lR02xj5/uQm17MeGPeR%20mDhMm5rOkdGDFjRxwNkau02V5VbkOCWGvSqtTLJ4w+enHm+ppZPGIJL9EGsGgKt2uau4AAliLf06%20fj0pdCcrXEgnj5k/2PiRt7y4gtYGhuXGQwdUITUbvy061es4+WPIKNNpnpqrO48Ud18zn5PM58U+%20ScsQyzFpe4EMDHGzFJHW6GpT1zIKlJNkQtErozFG5yhLlFI9LSChrWsc8Za48dBEm3lstmDC0vLR%20igMZHfaXOv6kKnT7qybz9o2hrFyc8c+9jXNRwIKXF0+3Tp1WtEnETjX2Z/pwILkO9cvk+K9/kWnI%20yImHGeQ4tJDzuVPyhqCpds4Gq4x4jbvXk8bO7c4nJgiYxwcY2N0O5oAUAo6+0CuraWXhBHgWWPNb%20lcVwfDcbE3EzhjNZPKRdjdZJpTr5X1WpcL+RtTnwOy9mcLw3F9t8djYDA/FMImkmaPXK92r3OQF2%20lvKmtySemGTULYfcc/2w1iKQPHx+NOzyEkI8g1udw+XhCLcyeKSGRyorS3YASNKlZ65DZxruT6T8%207i9lYGBh5Ee3Gnf+oGwD3WTOVjUAC7E+2i1ePEacDzs/6Q5XFdy8Zy3ITxSugbI7JYDq9ye2EJ8T%2099XRNe0TfMd/U76b8fHgT9x8RJ+kzIXsfLA0f25C4gNa1PlcXkVT3FXUcOcjl/cuRyWTkwSZZkPK%20RsMc4yHkuj2hfQ4ogIGv/CrTTXPGOOpERqWPsDieRn7e5PNYh4uSVroY2uJLngI8bbXHn1rk7te9%20G+1fxHOZlDun6g9o9vBIeO4iH38jeCdhaQ51xuCkpc/gay2L556SzovtxSZz+p12NmDNy/MuLmZO%20N+jZEIDd/uqS5GroWoK6Nz7jiWQ74Ht3gsPHx8nHxmMyGF7cfIRu5jHkPdGCPMdaKsaNd7Ycn9U7%201sjz2Mc0gf2yWkOcF/ppvMEc87Wxoe4Pq33V3NvLoMCKTjePJX1PiZ6triS2w1rnfijqsumqJPs/%20k4cLluMw25Xte7Fn+4xrFEhEjdg3fkHX7KezacuJjdaMt/Bn9bBEZ1LY3uCuGp3kDVPVauyYXicq%20rJF8rhYkHH55hYD7+VkGV5O64gcAVOnq1rGzfvNttKUecOKAOVhO1IyYy4lu1FkvYjQ+X21wNS8z%206W7UNpwox8j1dC+LG5LGfENm6J5cCAEJHl416NptqfM6TByT6+yPkyOJD3F7jFMHKQnzKbn91c3d%20OND1Pxuba4nOOFjg/TRyPe5jmEukawK54VbglCmtcO5Z8DTulNxwcd+S+SPEc1z5WuMZt61+ZSuv%20lWMw5fA5ntzoMJuPOL7rnwueyUbnRygIq9Ndvmda32t1aJ6Y/jkRbZaWgjHBNPlvxsOGWeRjGvcG%20uU7F9RJXT4/vrRdMLTGhm1yHELcrHhmMEmzHn9DXONtzAAh3EEbkqunjjmKVoNuL/WZGWcbGaGTT%20bo5GtAGxSCW3+NrUdDxj+fayXZrQ7P2RiO7U4do5oiblct4IZATJIInXYvVi/wDNXVW0GbUnRcGE%20SQjKyR7chISOyonVPHrWnULpgUMuIT64Who+VqqE/q+HShXYOq1Gk0gdntYyInfCZD6xtAVCB99J%20gNOefIeHnYdrdzAGXsSoNk6Vlvf1x8TXb/sQnZOO+JnJkSgsbKwPLHAp6Q5BfX1J51HbPIruNR13%20Tl8pjwcbHizPinmz4mSbfVuj+Z7TqgLVrZ4+pnRJjzjMlWT+6jpXSSIVBt6kQ6EGhMmyglfom8P7%20HDh1zs3wS2Q8aDTSs3qbrQvlIZTPqFkwxSYcb5QySRsgYCviFW4tVVM9xwVoHcjWF21x+ayL4WHg%20mlMykzuchLStl2oACTe/xX/hSgaYox1js9fSw8AoJ0SmOTXNeW4GYSjWmCYEmwCtXU0nkiq5uDxn%20OCRK4q1j3vBLnbfzE6nVVojU6/8Apk9Rtc9ww4S4l57aVxaC0oEPyeHgtK6mVzMqW6XPJmeSyMfk%20vpJybZpG5w/QPlDnBDE/Zual7bDpeo2nq+Hz+BpvWm/M8+/TVjP99dvlAv6kHUBybSnpCIvh/GtF%20yxjkOGkehO3JHnlXhkrWR+5OCmrju9TbGx0T9hUJ5swa8OBfWPb7wBJBIQX8Lrr00q2sjJalZ7Lk%20ijHIYTfScTIeHNKi7yocTZLONqnbycYxwOneX2qxNS5HG4WRPm5WZHC72QZWSOaC1rL7yLH7hVtp%20GKq3oVnO7xycx7XwZLOF4l4PsZEzDNmZdwn6eBt2s1RzqcyhOsEbLzh40PnfynMxuLQXT5eOySEk%20DUtaQ5CPCiVzJckhgfVvt2OB0XKTg5kKHfiNL4pWG7ZGKhU2Vt0qLWSUsvockUe6+5c1zs3D5URY%20rQZhD7bQ4M/IuqKn8b6V5Xd/lFtZcWelsdpW0SiGb3F3TnvmLM+YNaVDmJ6wTdNB6VSns95TcaU5%204gjuaLaUxKxj+JNTh808tMmZLM9oQFzzp09Q8PhXV020zSxjxONd9waxj+TLuGyZC1zjIq7i5Sf3%20G+t6fppZJYxjUl99fmat7biN3NBYHEtaiFUT0H49TVKvsz+BD72+mPMXZwEexrdo3FP+VT0UXoVf%20AzfdXeeZs3hWhhLiCShQEqqAnxCD4U+idMsfMh9xbmbO4Ziko0CxDAAL2IC+SCnVRxE9xm/+JZ/U%20SVABJKINAdLXv99EJMSduZn/ABsYO5rQx9ywjUWXwNv4UdKiHmS7Gf8AHRN3WI32eRdzvAkm/jpT%206VrAptoYdx7GH0gC20OJKoblU63/AJ0QhNwajBjBBQHaBt8RfQdKbSeQndmXYty5zNzjqT1IvZL9%20el/4saZj9IANoGqlSSSildNachIk/GDt0TmgkEEApa4VLa3/AJVPStSlZnG+byWTctnTD5HSPAZY%20Etb6TofJK9GlftNFkXXsHEEfDhz0E2RO4yPUMcGsBG0bVKeJ/fWzeU8F7eOGuDIs5yx7OPmXJ8fr%20coUk7WluiiwCdBpXltkSaSxANPRfktdyAKQSKSY0xnDGArUIuXAdLn7BelXiU8oFCwBCFG1TawS9%20z91VIiF7faX4eVlPAD8rJmf/AEkgOLBa+o8ab011RVuS4EoWFxRzih+dB9xVPLwpMUImeymf/wC3%20cQTZ36qMkBTfcPu0oa1HT+yPSFI7jyLy/b2Hl8hlsx42QvyMp52j0q4PcLuJN1PjXI9zGMcTf01j%20HkI5H05c+X2ctj8eJgLGI4EECxKj/m1A/fVepbSBrYUlYbwXHyskZLM9gZM5otoA5LLodapbsMl7%20LayGze2sJsjS3Nct03MuPPwqq7rgl7RKR8Xjxcc4wuBnY1jX5GjS8uB3OAJ/bzpPcmQ9N1cjfunb%20hdvcK57mzviyZJDIQgcm0oiWC120tNWc3Q+po6F2hyPZWJxpyuXnDuTzkkyHe2S71AFjWFR6WjUL%2008K4t+7bhLGMzp26QWPB7r4gRvxsLkvbij9ccZcYzG0ahUKrrWfVZzwxj3h0JLSR3i92chMwOh5I%20OiB2MleAjkKhD1CIKatYTpX4icne2dxk7xPlY8rpDubGy5G71KgNqfrWePqL0qjjku+s/J444yRA%20JHPFJGu8MJH2XPjVLuOLJfb55DzF7zxhMX5ZY+AnbK9AZBIvygArtFr1X+pOP4J9DMrXdPdn6vG5%20DFL3B7yTjtjO5jCwK33NBak79WPH6muxtrqWRxjK53mOS5Jv+QyHTujD/WA1oBcEKlvzA9K6Ozs0%202pNu721x1yOwfTR276c5ZY9tpne4bAbR/L40+4S6pfgcVHKcI5hw/OH/AHHyvK48ghlmecfHkPpV%20rTcKjh6j41yu7O+6cJMubO/c2F8MTiIc0hrXZLQXOJCoUsBRXf5nLbZLd2/9XsHC4OSLlXSOycZx%20GO2JpLpyi+ooAHEItbLuFBi9u3AjJ/qTLkYuRicbguyMnJyPdbOH+mPc1GtvtLnN6p++s7764Y+Z%206fbfjXHVYqvb+XynAsnjw2yvH9z3pfcJ/uSfO4q1C8ByKnT7aw9bq46nfu/jHKjhp88ZC8XcEkPN%20R8h+leJ4Hh7Y/cDWNEYTaVbcm40p7e61xMdz8U3kiwY316z+Lxm4Z4APa0vf7pkJRzjvLgQLhq9a%202XcPyxyMv+HcrMgs/wCuHJ5kORgnjIWNmkeZnbrgyLuT4qaT37PTQKdglmUKDObFk45DHtMUzHtc%204qE32Cf61CanKTot/VprL9Tvc31GZiT4WVyXG+17sOz+1kRyOCix2KEHnXbXc4L2eJ4r7fOCifVv%20u3i+edx36MPxxDG73GTBm5SQdo2l1x8K5960uD0Ow2knlj+Sj8d+jdKJHOR0R/uOadyJo4AkaeFc%20jeUj7ij6y29tYmByXISRYWQ0JGZJDtQhfSCOmo+6vM/I39GicYxyF2iUtIW53k+M4XkH4ckwl2hr%20po3WcFuAARboN1Z9vs23KK3HGINtzcrXUY4fc3ANkbPiyR40zUa4j0uc5epTzT4Vs67tFEzjiSnt%2024C+b/heaa973xtkH/VkiKEE3uD8pK/Faqu9eus4/gzv26eQ14/g48PKZkxTMnyWkPiklCbQAA26%20+anpWtfyDjIzfZriWntnmZ+Pbl5biOT5ycrFlSBGxlLNIUByIq139pvdWcZnL3Gy68S4dtd2chnS%20ZEXOQx4GRA33Gq70OYPm9VvJbV27e4pZy2o+CJ1mVBkNa6KeOUvG5u06pdbdLmtVarmCIsJPycf9%20ZHGcmN0rmOaocCjibtJW3S3xvTrE48ws/E25T08VPKXn02awEXU+oBNKz7pLpL2JdtSn9t9w8ZDy%203IYEm6KaSeMQxNQn29gWRxsNoWuXtnNfHM37hZjn6m8/m8Lx2FmwFj52ZW6B7rsJDHDQH+Nb7loq%20TtLqZKdncjJndvQcjNsbJMHy5O0AAFDuRfyp43H71t6CtWbQWr6Lujf2LC+Ndj8rMc1V65Dz1+NJ%206mheqQHK/rRNxIzOKgzJXQzzMkGO8KihzVVNPjU23K11ItVMoGf3Vjww4UMeQWfpBulJVz3Klk/p%20RwPj5VzW7xcCHtZZcB7xPdzc3i8vMa9/swEuaQPUbLZVH5f515He/lN6m4q1iX4e7HE9Ltu0panU%201mhhyP1BfNxz2YjZsfJe0GGYtaNt13OOg+B/4rY7vvHaLQ15QaPY2OCzxjI5tzf1Z7443IfhN5P3%20IJIyJIpY2ueASfkcnpVK+go3EmO5sVTyOeMiGQZGDajSQ46+l51Ure2taJ48vgZ2XDEnR4/q7z7Z%20YcmAxhuNiNwIQ6Nd2MAjnebqzfVDzwxKq4InOS74OP2wcLFczFhz8UxuaGJuEjdpedPl6CuKu/al%20ungdPoVsuplb7X7Zi4/IxeWjyt2XjyNlw9o2xHojl+PXSsb/AJetbNcvA1/xt1hl24zm8rFyfemA%20EgkMzg07l3FTcqbqlVT8nt4xBhbs3DLoz6ocb7bfdx37vlla1AjrEloT5VFav8rtaYxyMv8ABeCJ%20d3hDF3ByGTw0pbNyBaWHL3CCMojjbxSx066Vlb8ltVzTxGMZGz7G7pH8lZ7s4bvDuLmHclyr8Q4m%20CwsYIFa4saVJupde4tXIvzmzbKXOMew22+ydXnpjHmR2T2/z7cj9bC6T1NJZOJXtnMYGjiT4Vtt/%20ltmzhMy3Oyus+Ahh8TljPYM3lZ3w5ADn5EmSx+wqvtKSgPqVNUro9ejzT8jL0LzmM+U7Xezk4v04%20mbjxzCKR0jgHFxvujQXY4akU/wDQulse3tZ5lxnMePwfthXy5bi4J0jaQLu8P20r5Dcu9zefg/2x%20B7NV01XkSvAccW8d70hAdI7eW+a20Tx61k+/tt78ctf0/cnc2VahLeyy23QqUHjrcDSv0HVJ8z5K%202rnGPabGEAo4WQeq7ruvqP4fzptrgiFmNMvkeNxMpuLNMBkkBccAlwaNCbeVNwiulzEGGcpgEh26%202pttKFD18PCo9WvEpbVm89DdmXhuZu3ANK7NwQH4E2060erV4x/OQLZsNxy2E6ZsfuNa97tg9bVJ%20PWx6+NHUmwezbUfFiOLT6S3qTpca1oq8DNrmY2N3FAAp6An4BStEAY2Ajz0tov2UoATcwajqdAp+%20/wCFEEsTIummgI/jQkgNSD5An+VMkAB5j4/jSARznshw8jIcdvtRSPLj02tJ66fGnVZoaOBPmEj3%20yPIG9xc5zlVHHxTr1WvTSyjU3k6Rwb5eO7UhmhjIyIYS5qNFpJT6QieGnXxqd63TSccURWvVfJjA%2093dwFz2vtMNBtA0bpa1lrxHvM9BdnVKEiS7U5Xnc/l5ost7ThiIviAT5wQAHAfCtNvcb1MO52a08%20Cwsb65VIs5CFVNVsfCtkcj4CHKzHG4zKnPpeyF727AiudYE7blVppZirm4EeFxDjcRhQBntpAxxY%201LOeNzlN1186ByOywus4en+HlQBL9ltP+6uKcEtlREAdFd0tQXX+yPRdI7Tx1zHeHDHmeRjhxsp7%20RLK10RDLSh5G5psCNdK4nU6k3BFZX1C7h4jHgc90jcB6xlkzQ4OO1SAdRc9KuuzOYPdaY9xpcf8A%20w+dyTow5mPk+2xqEq6Zpdd2tgEpWqbbe5GMY1IKfkHzMEg4qRkcLvdeAVaIwU9Liqr/wpqonurgO%20cHNfnRPfBghgiDfelc5A4lyANQ/MfFP9CEsY8RdbbNu8opGcFx0U4jZL7j3mNhUhpTwsFSvS2axX%20M83cf3OBtwreUyhiMxhGyN4cImFxR21WlCF2qBauDesqvPQ7dtToWnJ7ezjwuLi4UDDyUzzLmTyP%20BsT/AG2xByK3aSXV4j/JLrzf2r6fod3+doRHbXcrsZvt5ETg/wD67SiNRQ5EvppQvzGzV5sj/JZj%20DD4WeEGOXI9CbdzQC5Cer3guNq3f5Wj0I/yNefsH2FDlQSs/vbMZ3p9vpt6hBohT5RXPufk1qlj6%206lLs29ckWOWMcfgSSTziba724S1oa1m91t2qoLftbyq/kr7tuhKJOv8AypZ6wV3ke4MeJkIJGNi5%20RdDJGGlzyURidbE/dXqdle7/ALOXjHMi1FVyvAqPD4vHOz81vJZjcWRrduG5zXuY47ybgHpXtbfc%20em00Yd3tO8lol71wu3uzc3hcKdudlZpPt5LLNj90IhHxt9lVbuPUbnI5dvtnTxzIftrJ4pvE4/FT%20mISykGV8gRzZD8202uNb1huN6mllnoSUuTnYWU6NmC3OwsckNyHEGQOaFKN/Oo8kqtvblSzC1ocD%20PD7yd/lQXcfkOxJGFjIBt2iQkJJb8prS2z9rfhjHsKo5ulzZYOOhbjYbJCAZgCSRsN3q4AEtPrQX%20JuOlcTnM+pooqs4+GT58eGXn5m2VlMdEGMlYHbGH2mmwDSQG6K5wBB+K/CmtcsfTw8inSvt/Xl9f%203Ip2TG+SRjJCoF2NLipPq2u1tZVJ+2jqiJxjz+hTizerX/ynHwyIx0+Q7LY/H2NbGTKCdwKNXUO/%20p/hretKLOFjCOfeUp5a5/Xnw5kPDoS24DdzygQN6lUsV/Cqdp1ZDnPL9s8aDiY7nFxsSNG38uhv1%20q1Y5LUKrlZ0ry9rgx7pS0yPLVKWQ7h4eRrpXksY8zzL0SJDtiNrsfJkDNx3AAm6j/wAR+NY7x09r%20WMyWixom40ntRhjnqHEHaNxsp/fWbeiZe+unbZc/o/xns8tyOV80cWPHE2N5Qq8g7ttiU6fyrwf/%20ANLuWrt1XN/KcP6M5fxudmV7v2F+T3pyD4XqpYwbWPB3bdrht1HpB63r1Pxaf+dTjPL2Z5Zew5O+%20v/7GRb+1Z5N0ai6bbLcnqh0HRB8a7XddPlj+fIzr1dSOl5XaPHZBdiPO2afFY172gFhlgTaUsoX5%20q+XfeWTl8Ge9SjSS1Kfy+ByTjFDiZIxW40AaSAhcS4gjRoIclev2dVuV6rI5e5u6PISxcjn8LlcO%20EZ74mM9t0zmBLPCodD41srdLyM2upZvDLDnczk/qv08k64srgHuOkgA/L8UvXRZyszlSzLD2TnvB%20kgdC7Fy8puzEnJ3OEblA2gJdy3rXab55mN0pkc8p9PHYEuRjDkpIHRRfrXKoBduR0ZGt1reXDeMf%20wY9D5CuB3rPnRQ8LLN7zntDGFsWwuMfSwuBrXLu9w2njI7K9uk9Cr8hk8LjdxZUuRiyT5TSH743b%20f7YHqBBWs6btloVbaVtRPvXvDE5viYeOhQYmGPQgK/KgUnXWtPUu1DHXZrXMfcT9T8fA4vA46GOS%20QR45hle0aSIQpt4Xo9W6yRPoVfA7h9B5Y5fppxr2HcC+dXIQp91ym/nXRSzazM7pJ5HQasg4f/3H%204uZk5HDRYzmXjm3tcC4orVKDoK4e8vEctSq1b0OMjjuQjb7oY+YSFzhKUDAwDchFztR3zVxSn58x%20dPl5/AlsLlMTC7X5DFfkQf5OVwEEBI3PDUHqVAB1tXHv9m771LpfbX9z0NqyW30vJ40/UYDJlPHy%20OyYY35Eu2V8xcqOIKtPxXwr0fTt1KDlrVq3h9csZFSn/AFbczJnc2IwODWQwzM3hwIV69QbV6u0q%20NOUVuq08Su4xb+ulaGeyx4/txAo3ao13D/hVPN5c8Y+WZnDjMdMbM7fHDMwEW3vsg8PUftXWn1cO%20ePdh8BV+Rd/axJu1WDJaXCCIBwAK2P5Da6/hXzu9dreXjjxPYpt/bnoR/Hd1Pkmx8HCKMlO0PlaC%204Wc4200+FaX7OkykHq1dssYgkm92vPIvjfhSNwQFe8DeQ9ALgG4pP8fUXr1TUPIdnuTCbJMkczRB%20eR7GbkBKEOa224eVvK1c6/HaQ4x4/P4G73dt2y0xAhBz8wyjFHhSyq/3GRFmu3UXN9R+NVu9haya%20XHnr4GfqLrJV/wBTo3RTROwHhzGkKpG0FqeAX768r/gbK0q2MYzNf9agYP7zkz+COLg4crcra1jS%205Nrmg3LSVAXUCt6fiHXd6m5rrj6i/wBCayN+MEzA/wByQEOcArmlyBERwTxBulRuX+5dOTXksY9l%20qia8/EXYzjy5kj/eBYfcZH7u8Agr/baoAFkDfKtV3N4hr6e+TK2yk/mTudweRJJx5e8SR5LQ5rVL%20faNiBtF3ql+ladzG1teq1nZYkx27dV3XkI5PP8ti5DcLHmjhjjO0s2B7Whdobu6L515212dN6vW1%20L930N73ayRMt7z4XAxY35vKRF0Y2e0WOErreq35l0U+Vd+33ff8A9aVXScG52/bz1WkkOL7o4Hmp%20S3j82BzJjux4VIeAEa75rlEuRXt/jt/uHRreX3fDHmef3m3Rf0zy9/6FY74fBBPykkrRs/QW2KPm%20Cj/zO8677KNTh26rr9uMZnJMmdrIWywyvjbtBYPcdoASmoNZJrSD08yY7viGL2j2tCJXf3MaWd8o%20eQT7khs5TrcVoqpvQh+eMe8ge1Z2y91cS0PcjciPcd5u4OHpv4+KVp0Iy3E4xjHkel5mH3HWRHHd%20ogIJ08tPI1TqcTRqQVVCNw3Am5udQmtGYpNEcVRSULnADp4/jUwCRiRSC4gr6gBqNP30QxcBFwQa%20FpFgPAlNfspizMOaRYCw/bzpQwZqDc3G74r+NEZhBFd3fqIu2OSkjifI72toEYcT6yAoStNtRZSO%20qZxJuFnudtZhT+4UAb7cqIvVG2W9674hGzfLQ6i/Gkg4tsZhkB9AbE9rmuDWNRSoBGn2Gse8tNIT%20K7VNWnTPHvIqXA3BzxBusddwXqPt8q8NJxmevbczH/aLf/U5EpgDWBoJJBDkUqADrXRs1aOHvLKy%20yJrDniyJJHY5JBcdr9jmq4IpbuH+ldBw2o0Nu4TLNxkmLGUklLGuaEswuaZPAqev7K4XHHzJpVzK%20HAycVpOOJG72BqRghpa1tvsBXwpurH0PUWB3xF4cBGG+46QfKAE8DoFqW0Co3oSnZE+PN3VxXsSC%20Rv6pgI8DqTfofhS6pGqNWUnoug7TwnyzXM5zkGxykPOXM70nQiQ2U/H4VjZybdPNQbY/a/I9zbt+%20Y2FkUgYGSH+457rO2A6pYmtdunV7CL36TpWN9N8uLgczjW8jDLkZM8c7ZGptPtBDbxFD7ec/AyW+%20MMj6cd3SLDDkY+RFMwAOD9m7S+xPhUvtms5NK9yOJfo931js2s/SGMlu725RfaFAPTWsnsM0W/V6%20kL3P9Oe+peCxvexCuO94nllkjADFshVCK7tp1rWOeMe85LS7SOsDjeO4jgcLJOCx7sOOQSOj3WkJ%209Tr7V0T+Pj8T3P5C25vuk/bpjGXI+h2O3VaKVmO8TGz58MchBmOLnxuc2GRg3bEAICaElvjevK3N%20ylb9LXHXHyOpV+2Sh5H1P5qKeVmLFDJGfSS70hp+UtHTyUV9DX8RstJuZw8+ftOF9zZOFjyM5eb3%208eLm5Z2AcPGhIL5Hwkt9t197PILXVt9lt18ccfoZ27qR5HyHLSGGd0sLVDS+B7g0Br7hwP51W341%20Nvx23yK/0WSJjiXy5mZKJMiN+C1HGKPdtAF97iUv6U1ryfyGzTZS6Vmzq2bu2rGPcuLPnHCbxjfd%20zWzAwMiA3EixsEaCen/GtfxSur9LRHc3r0ymVni+NmbmcxjcoGx5RDf08UrlLnMcVDdQvW5Hxr6P%20d2urp8DzK9w3lIy5c48eMMNrQ2UFZntIcS5x3IQ1Ql7dBUrb6fPGP3Orb3ZQOh5HH9l2yGePfGXe%20233D6kRrXaFzfwp2qsYx7Q61e37F4j4HmMmSN0cMjpE2gNeGt9d9utjuVFpVul7C97alt4xjQi4u%200fqw/m2MZi5H+Lmlc33mbHM2A3Z6SqHStL3UQc+1spXxwyx7y1z8Ryn6kQtwZYC0ESYIaXNkY1Ns%20zJETapPorjbSXgettdzLTf8AWvl8CKz8DlwHt/RTuke64EZTaXBNjgEa4eGifE1CaeePbry4/M73%20u1eU549qy1WYyljyYjK2YSRvcza4OaYi5jlIBCblaQi21p0WNVPP9fdIXumpn+MfrEEdjyuZmSOO%203e3Hka8jVHgH5lPRyC/nV1xjmY78LHx8uRFxRuUtLXONmsG0LvsoJVfSl/4LTTSxwJskvCNcfIeS%20ucWLrvCpa1lcD9qWHx86KxJg6wm8Y+XtKPlO2vcGhEKB6EEtCDd8QnSu6jmIPH3bSWXt4yu49xe1%20pDQQ1zDZVJIsmlZb2p1drZtFn7X4z/KzMxw5zAWl+5qW2uA8v3153d916NZSzxj9TTf2utOryTR0%20LtXtt3EOzJ8fIc4ODYvbkbta3YCWu2fMQVJt8Na+U/I/k3vOtbLTHw/gO17Rbeaebx/BWu5u1sd0%20mRykk7nSmUSSxNbuDSQbhrnEBpdf4/dXq/j/AMlaFtrTT5csQcnc/j027LHyI1scO6EPa9rlYIwh%20O5CPSPFPOvor2+2Xqcu2nOMe06E/ceTa4nb7OO7cGofU4hw1ufuFfD2a6X5/LHM96vgUfIDnyTMd%20GJopw07nFL7v33Xzr39ju1TbSOLerNiPzo2M5B7g7f7IbuebptGtiqACuhXnPGJBVyiZHWZgtmfg%20+1tlZO20bWo6F27Ur/V+6u9xEHC05ZMfpH4s8bsfMEntbQxwF2OBJJuDYeQ61kn0viDq8fUs3I9x%20y5mNGD7WT+ojLW5Mih0crSg9Ph41r1wo9mPAFRzJXO1+Jc7uXHhyCssbXOa4I66+oDwAJGtYp9WR%20vfQQ7p4443cOdF7RyZJNjnNII9rbbaVuv2U+uBJFWzCyNjUiIO17fecLEg3bZdOta1sEchLGD2sh%20fExysZu2IEdub6gAqfjT65J6UuB6k+ga/wDthxaou6dU0X3XV17P9Tm3f7HQ60MzhH/cpK6LkOAe%20x+2TZN7Vw31BzDc+dcfdJSm8YxyKVZRx+L9bkwNnkeGuja98whO5Wj1HcfSvw/fXH0rR/ua9HVrj%20GZRc0zZ2ZkZj3CATOLmPTVbDTqa7aUSWRSccydi71ni46LBl4nGzZYm+23ID3tkcQV3PAS4oe2ms%202a03Y4EU7uxk88MEnEt45ziR73rRzhqPVchyJrV9DScGn+lPhkWnmu2eP5TtyXl+G/8ATZEDAcqB%203qYHNCkNcQCbK4isK70Wg6t/tk6SsQc8bkD2jP7n9ku9W1qhqi29fC+uvwr0HdM8hVaR0fiBFkds%20tddx/TvbvcqBoUm/gHXt9tfM97Z+uoXjjkextZ7eb/nL9jn+AXMymlSCjmOc1SG26E+QNetbQ4lq%20Nzy+c3CEMMrgwSuaZw5wcW/lYSo0rrrWTmlyyU7Nz+TMmW5uXKGsQp0LjdTYk7Qay31B09tnbM6h%20iwN/2zkZ+VKJ8pkb5WSelrmXUWt8TXPDfgdERYofP9wzZeGzHxw32oyFydu2RzgPyka/dWlFxZjv%207vJEDBzPJ44xmRS/294eB6juduQL4op61dqqGZbbcnVmFpjV7m7nNO5fT6g1HOLEUqoQV8feet+f%201Pd24dVjH8jdmHEMh7mMBcm7cCFeihW6eA0Si262sw6cvEmsbmcxs+LJLMJMfEDntC2AHp9Km+tR%203G5bcp0vHmZ02krSUfnuRypuZcGStGJt92UhAW7jucwH417v4/ZVNtczg7q8WZXsWT/Ncw+fLlMz%20muUNCtKAptKqESvcVaKuSzPMbsdW4V/D42Pivw+OhZksKY8pHrYXA7i0ddEJq1ESjG1ZcMmpeTx5%20YHuzseLIkIax75Ape5xsCiIKvRszrRe0SMXAlpY3i4CyIE7g1q7rKfgo6U6qo234m+Vm8P7LW5XH%20w5EWKGx40b2K0Mdq2MJZNTTlITl5jXAPFTCPKbx+NFMD/aIa0BrmgAkW9I6U1oNprIsMXNukc1/t%20OQOLXofUgTXy8aEpM2mjZ3Izb44tqukBRNvoCanwUfjVQOB23k5XoWxlzQHGNnpKkFVJP30hdOYO%205LI27xGvuauIB3LoHIemooQKpiPky9vriLmDcG+kXS/gvjc04AyeWO9kboi7eRYhunQlBThDh6mX%20ctjRR+4YtobbeGhRYDaUAvu60QJamBy4ZJtRzJD6nNKaW2lyefjRDDzMxdxRyLKL+pG7mhxHxcOu%20tD4qStOBmTm2PIJHrCgBwYQEGgPVfI0rZguZpHymPdxhY0NCbdrASpt+U6VKqhuzNpOTjcrGsjaA%20RcBl9Uun2UQBDdzdwQ4XESuYfYmlsJWBoQlpXX8yL1ppBEnLmc0S95LhLKbb5D1VW/uuKb6XppjG%20nCBqqMO5hsDPeA3mRwLgUJcDf1OAsFNj+xHGMYfuH0oR7y7pmg7NjwMNzoMzkpw7KDHAlsAJDIzt%20HV/XQ1k1weMfI0SUjH6P87zDvqV2zC7Me6GXksdr4jtu0lE+W4Fyal1xjHiW0e96CDxX3f2RyeAe%20U5Y52NlPZkTSOwoXl0pY6RxUeJYNRXGrps6YcFa47mZMF0MmfjzthfufC+PdvAS4O1CPC9XZuPtY%20umdS94GRxOXw+RyWPk5mLDjOjjyonh25jnqWo3yAOlZvd3EWtqkiR5LGjmiGNzk7HSFI4yCdy3sf%20iaS37sT2KeA8hye5P1ZxWcs0yNaJNj3kOAOjiNFQ/dTfcNIl9snwEef5fup/bmRhTzboydzJC4Fp%20ICOQFKXqWangUtta5ST/ABLJJu28Jkjt7v0zGudt2KjUO0Hr0/fXwPcNV3rf/wBY/X6Hu7f9VjHk%20KYpkixJHu9QeJZo0UKwjwunilZ3i1l7EXwPPD3OflvJBKZBd1KDfe+lfodISPCamx13mvqpNldqv%204KKBzMcQ+00vI2onqsg1W1VRV44x8zVbUZnLua5V/wDj4IyGtLx6WOFwwagAeofYa02q/dmRu3+1%20LGEXn6N4sX+OzctrSkswjdG47wGoOpsQFTSvmf8A9HuffVLI6vxy+1jvuHmpO2ucycrD4+ISfPBL%20NZpUE7WNYbODuv316H4G9bbaerqvMw73qrbLSxzTneXzM/L/AFmQWunBVw9W0lwUi9z517uMfU4K%20KB5kBskWRnl0LHvDGNixwrWgorEJUk6GsW88zv7dfY8cSfi53Fi7dxIfYaw4LnNxWxg+mRzfVuRC%205ei3rmafUdfXRbf2r7sYRU8nO5R0qumnDyjSRI9qHq0IUWt6w/I4L2voxSDl+73RPnwuRzzDH/1H%20CSQtYSUG4/KNevSriqy0IW4yR476hfUrAkhEPJZErYSZY45EkCi5c4gbjpRalYjGIHXuLTOpZeL/%20AO4HvfGdAzNDcyNr1cPkc4ropCemwrG2xT3Gi7lcYyOkdv8A1n7D7ndHj8hHHj5eS1JHZLdrngWa%20N4AsPGue/btGq3KvRwT+f232PlQDJONGcabbA6OIFpc35W7Qw7vP7aTlOCn188jmHP8A0j7o4zlm%205nDA5XDiQOGKx+6aOMhdt7u+Na9aaFtXcqWVfKkhjyHtmBhlJH9tzS1zQpA3DbongKz6uR3qMpfP%20+caiJ4XtfIaC/M25BO322uJVzlLg06bfDyp+vaqlaY4C3dnaeWPnnz8tDMTuGwoBjw5cbmhhRzuv%20pBP71q5bZn0Uqsmsyw9t8uMZrIY0Y9h3Pc35nBRc+TW3otStqw1Jz7qzyZ0rtv3pMWWQOIjIe4Ak%20IUaXekoVJNhevkvz+1WtqpLjy+Zr2raWepEcq4T4EwLnMcSS4NAG4FE9wpuCAeX8te17K1HW0Ssa%20Eb+6rSsY/bmV2CBsmdCf1hhcx7dsW4FhIJUqQt+v4aV9Ju3q9tw8zzturV1xUl0c5reVzOhbAzeQ%20A1LKdx62X91fFXbaTWMM9xNQc85Xnv8AGzxBuM6Z6h24Ej7nAaeI8697tvxz3KTOTR5+/vtXS01x%209RLuDK/TjNyXkOlDd4j+ZHeHRdbL/wAezY21V9PIL7n2ySXAZWLysTRGZBOGNM0bW7tpSwsnXpXX%20v1dHmctb9RMvw5/ZdJ7rmKz0mZhDt6lQba21rn6oLgQPEZ0PGhzA6aX2HFuxpO57gS69kv8AbVau%20MY+BfUxz9I+WyeQ7xigy8STFdDjyFzla4OKtbsc0tNq6dvahyjLdvkWLn+3OZ5bns3I4IsnhDhHI%20+Z4jG8ISL/Mi2K1juJN55lVyRzvvrtzlOAxcaPNc1j5fcfExsjZCriNUA2r51e20ym3xNYMPkxxu%2072GGONqlxeGuaHxru2IqAf6UnDY1aGejvoFNFL9L+LdGCGh0zb6kiVwJ+0137Kipx739jodamRSP%20qNxHF8lNhR5uMzIcxrzH7iAC40cTY2/415/epzXHI6e3hppnPu8OD4PB7cyp4YMeN6taZYi1R4om%20qLXC03B01rJwuXGibFH+mRpY9GPIUKFQ7evjXpVtkc7rLkvGHxPcTONiyZYcHk2ysRz/AGWwzf8A%208ORqNcf/ABa1je3uKquDRAd/duN5zgIefdLJhs4lroMlmWBE4ouxsUbbF3imtVs7kZMdkQnY3duL%20hMdJmDdjTt27XBdsgsXbRdC23iBT3tvPI9Dtu4+xp8uZSsyMwZHIYmMd+BkSOerLMewkmN1ujdRX%20Snlmeffb1Z0bstwPbeNDuaHlj2sBu0KCCdvlXzv5FP1U8cD09pv01yWNfdhlOweC5LLznSY0Yl2S%20uYQ1wAG1dd2hr0r79apdTg41tttwMc3tjuDAhkOZx8zGmR8hVm4Fpdruaqj412U3qNQrI5b7ds5Q%2097ObGxuU9v8AbduawxFQhRQoQdLUb1nlxOjtqpTJL8pO6PjZDuLSjQXqgJCWP+tZ1q+J13hJkBlZ%20ks0kpUkmRWMeNm1yWIHgdL1qkkszzbNTLDI5fOdDBA6+LCkjQdo3k29R0/0qfT4FVtDOo4UzpcWO%20YOck4UNbYlGgOAJABUef76+O31FmnwPdpHSKo4ks3EQhvpcXF4aNpa15GlgQE6Vm+fEvXTGJEM7f%207L3fmaA4NcAxySAaAE6+f21ptx1L+SbuNMYxmUTkYX42VkMcAPcie1lzf27adTavpe23OqqPI36w%2051Ivgcl7MmSP8zg3ZcI3aVRfH416NrRU46rMu+NzLmNicZNuwgyDQqtlI1rHr5lvayF3c5JKrA9U%20bcAeN0T7ap7z4B6K5Cg5nKj2N9xpj2EDyTUG/wC6mt5on0KjXL5rKL27XCNgPytIBUAaJf8AZKpb%207D0ljHsHXH89mtwWtJQhSBZRf7daS3nUT2ZefMef57kGwQOjWFzQfbeADt3qpB8XLTW+0yP86Y6H%20dOcMjcI9jhGACiuKu8QPwtVf6BLt58hVvd2WjvQ31NcCp6otw37LfGq/0of+XIxJ3ZkDCLWAMRqA%20iylPA9bdKP8AT4B/m4yLQ92ZAhYAGmy+3u2t8Cg/C6U/9Ckn0ObMu7v9TXPYC9Ds6gAlq9fzDx6U%2013BP+cxL3e+R2O2Rm2MPKtBIcsbQQhKdelC7jKQewJRd2SGeWZ7XLK2MOa31AJcjTxPQ/wCo99C9%20Bozid0+kO2kse8l2611IuQo0/jT9aMheixZ3chkcfeKhhKgi9x6vTp8RT9dB6LYsO44zZzi1zQQC%20RfdqLX80qvWXAXpP2Gv+fjOwFyEISourvFV0o9eqEtuxXu9edacOKJpBaS7e0Da4KpBFgBpQt1Nt%2045FLbZTsPJlBEUTWPIDS4PJR1ldf7qHZSDFM2SF8+yE2duLgrSDdFdYqmmlP1EueMYYlWSQ4mfgt%20zZ+UfBDjiN0cvvFQdpB+QL18Kyxjz+HtLtXIT7LyO2sj6zdpO4COSPE/yUAeHm27duVguQ29XM4x%20+o1VqT3jUknMeQx8dk0hdBCHXcGuY0re1/Hy868V/wBn5ncnOo2EGI9HxYUJAcPdAjGjrt0BvRnz%20DI55y8GPH213AI42MaeYBLQLEe4wD8K6aaEW1LyeL4WaONz+PxSrIxHLsAFmhetk8a53Z8y1TmYb%20w/Byf2v8fivUI4uZqRbUeelKzyKSzOQfWPjMSCaH9HjMix4SWyNjsxh6IwXO64Wvd7LOmfE87etF%20mWXjpG43E8HIJGPx82BxbKmwH2GK9Bb1fAV8H3/4q3XZpzme92/dJ1WUCMnIAZj+Pc5rWzj+295J%20c3c1Cf8Amua82u1krnY2UTI+ks0b98XMQESPcPacwre4CIrvm8L179fzqX/S8jiXZuZk1yuxcsRy%20NZnRvbEWl7Nj2AsLgAWqFNdC/NUy+1/v4mlthvJvIguX7D5WeSM4s0SAq5xUJZUAIIT4LXXX8xt8%20U0ce52jt/Vlx7H41/A8VjYk7h74LjK9rkYwueQHWvp8ErwPyW8t+7stEd/bV9OsDP6i50LzCVjkd%20IrGtLgwh4sdpNipFkNeh/wDn06qy4fscn5CHBzDLeYy6B8W2clAFHp8ASDX0uZ5izFW40uG1zp2G%20NxAa0vCsct0t8Kz1O3bUIlu3+LzOVfBFiNklyI3Ew4wCl24+fh41le6nM6dnbSrLk6bjfTjCyJou%20K5WGeAYjwcvJif6ZpCAfSHINrfvNY1u1ozHf3naU8YxwJvO7YxuM47I4PtiNsOHksH6+KR24zOBA%20aC5+nX7Fpqz14nMkPJO1OzuLGPzB4xjs3EMR9iNyxmUBNgjcjS2htxqJZsoXK9js7o7m5/K4uOLj%20nxygtwVWNT5qgO7otbLchYxjMl1Kv3p9M+R4Hj8LPyIWxw5Tvbl2erY4eoKm5Kum6m8fEh1Y27U+%20ondfa0ojMrs7BULiyucitKNDX9ETSi+0mjWm9GR2zg/rH21n8SOTJlflNkbFLAgbI0lbuICFoA16%201yX2XXGMI7ElfQb9x8t9Ou5ot3IYE0WVdzc6L0vbbcCUCPaovUpQU6vg5x/BxLkMSbE7g/SOkiyc%20HIV2HkRtRj4wbagEOCXWulVTr4k1s1dJ8/Ma8jjvjmjjaf7byL6ncB1HhajbjkVvaj2PLngy3vaQ%20WtLW7TYgINOvx/CmsknjGJIjLGMaHZPp1ke72qORlc4MHujafl2tJ9Q6Gvkfzm+nv120paj3s7Nq%20rht8fkRze6cZNjfUQoicEIRpQAJYnzr6VbU1SZ57rxQ0h5TIyOSjjgwIgwyRB7mxhzWtKbbgWv8A%20teuPue3q089MTjlwMa7167kLjH74z0LRNmxw8hyrw4gMgbqA5oCAhXWS/TrXieg4dfFTz/fHier1%20aHLeVHI5nNluNjPnd7jWqxpO0C2lga+g7Z9NNTlvVNpkrzONkQ4WUMjEe3Y0NLCHFSqra6Ff2vVd%20qv8A2a8TLfa6YNPoxk9yQd4TCLBc6KTHk/tTMOxyEISXfGu/u7J1nGMZHHtrOJO+Y+Q10LmyYj97%20Qm5jVO43DtE2ivOR05iOPj4uPlZEsHHZhdkKHkrtcQNp2qCn/KnWn1JZwEeIx7P7X4ni+4n8jix5%20kuWWS7oJA3Y7e4WJCoa6di82SM91RXMY5uZnY2bnvljDCMovc3c30tRCGgr1OmnWue7SjkaVj2nN%20/qZLK/NxJXtIxnoyMvAFy4FLdbVrsNWT5jtkW7ksnFj7fzZHtiEv6QezM2FrWl4aBsDgBpasXddW%20ZCfDjjEnYPogIh9NOH9olzSxziSE9RKnoK9XZf2+/wCZy7n9i91qQUf6jZuBjSYgy4d4cx5EgftQ%20BzVH2153fxK9p1dusmcq705vj29sTw4cYbE924lztykInqCJf9hXDV55HQvE5C6MlhaXKoICmwaA%20d3XUnWuqtmmNrL5lj7V43nsfjG8pxefI1heWzYkvrxpHNcFYdXM+IrSz5/EwgmuMiw+ax+S4/Kxs%20jHnlBOTjZfrixg8JvgksrXKv4Vm1DNDjbnYWPyWbg8eRLHFL/be42yCxyOLVTaDXalNcxbb6WWXu%20mPt08dGeBjfhvkxT+oxJHNe33/zbSOlZ1mTpW4lVrmO+xIv/AKNive1XxvdGx5Qi4W/Xp4mvD/JX%20fqQa9v8A0jHEr3H9ywcJzGfjZDC9gmchaEQBy6G9du72i3qVZkt1VbRdeP7v4jMSPHzwH7Q325CQ%20evzA7mgBbGvIv+P3aOUuOR013VbIkpo8XJbJLPjY8oLg6eYsDnNJNiC3pcAhDrWde63a5Sy1sqdI%20gisjtTist7WSh7YXvDHtY5XBSqAAX1X4V0L8netZxjHgTbZnWf1GvcP077d4/PbBj5E2Y4tBJTZs%20c4D0+FhW2x+Ztesxl44Zj/g55FdzO2cFjnyTb/ZYw7GB1z0D9yOKBdK7Nv8AIOz8yH2ir4Fm42Rp%20ibExR7TdFP8ASPNV214+9XNt8f1PQo8s8Yw+BJFgaRGGlr7NaRYNcoBJClVJt4LXLrmVGfj58ccD%20GWC6PagkeTYNsA42eETVR5U6QnyxkPJNxjzwyq8zxglfHIQQnyWUtuAUuGogN/8AhXrdtvxKOXdp%20L5EKztLmcvKbJxUfrcV9lQu4E6LY/fXpPv8Aar/dnn/5bvMuPa/ZnLyzRnud0GFhPajWscuQ5/QE%20N3AJ+als95s7raqyb0vXgS8vZ2EM6WHGyQ9rGh0T3oGuUohI0tXX0KP7HP69086iY7K5KLGe+Xji%205rXo1mPKJJOp9K7V0rPobWTRp6+eciPM9oSYr4o/Zne+SMSPkjZvbGTfY8gnaftPxoVGUt6vHH6o%20juO4kTZzMIsmjllJMDZYntaQASfURt+Vp61Lrbgh23dtLNk63s3Pjf7LvVZYiSrfAg+H76Tpfkx+%20rt8zSXtvPjb7jGFwiCOeQPlB1+warU/dyK6q80IzcVyTIgHRrC8f9QKhUg3VPFaXVIIRdiZjQVgK%20BFAHRT4L+3lTV0VyGzmmIFpF2kl4RCCbG2lNMXSzGpBGoRE18tFquoIzNXQtcRI1EjJJcQvpfbS+%20lLr4i6Dc47XuIALg7RSPBdUQ0eoHQjGNiEkBXJduhtdBejrYnQXbx7vcCG1gC4+lToOutD3YH0IW%20HGSqjZdocPmI6aJb43qfVDpFDxU3pc15JaCB5A+Gn7WoW9zQuhIhe6ONmijjfuEgfo439X3+Va7e%205mS6ZFexYpIJw9SXEbGkXI3IFcPiDW/WY+nOg4dgyvduIVrwQDqCqEfuqfUgr05ZVe6cb9NyULHP%20Y53tNcRqWkL8yhFrejTRjHAsX0axMl31M7Wnhh3RN5SAOcwBWjdo5QfSBWjqZXa0PoHSA5pyU+K2%20d759khZ19TSCClwf9f5+Pb+zzO5VyEi7FdOxrQ5jx6/QR8dx3INAvT+U5BBy/uppZ2r3J7D2ub/l%20XhhDgVIc302S/VUNdNCLLiWiHubjRgQQ+xO8NhibI2IbTvLSVJdewqPS5h1jpnO4GREwBzYtq7QS%20upBTcDfatJ7XBagrxmyj/UXiByTMrJxN5axokDFAa7amhKeA/wCIr2uz/wDrjHux+nBvf3kZ/T5O%20W4/h+Pna44vF5OS6YfL7cGRGNuujiSleb3+3m/E6+3u1j4m3L9t8xi91wROe6bhYADn5bULHwbgj%20YHK5JApVa8nt/wAfVyrcdP3x7jvv3OkcCfxeDn7mhlyeBzGcbiCZ0cYkSad+0AOdKPSI+ia+NZf8%20VtV1XxxjwCvd24ZnJ8/uzuHB5nNwp5IQYXuxnytBIcVTUu1tatv+K2o0Nab9spYw5PvrlsH29sGO%2057kXyaTYWNbbf4zazcMje7h1hLGMIvOLI+TFhL2+uRrXBrdCXC1kNgV6+VfN7lUrNcj0Ky8yqd/Y%20YnxcSN4WCNxeZRc+48EkKmmte1+K3onmcXdUmCm8VxGTJknbKyN6F7dxa4OANla7VUr6FvI8txI4%20Zh8pyOZJgYbX5GTlSiGBgXZvHpJKaAfGsnZLU6ksj0D2/wAWO2cH2hIwTxMERKNGwoAdpsqaa1y2%20qrvGOZKu9GzXJ7jxIwI2tL95Tc8mzgSVBN0cnwSr6DNCEPc5lme1pgMJIbtiIL1cVAQ/ctEKJB8h%20Tj+fgyHOZktDEXa8rsQlFHWi1V+uMajTfAcYUPHcbjyux42x7v7kkgvI8qo9XX5qlOdQzkpnf3cu%20dnxYXC5uOGxsnbM9m4bnQgowOS6ppWu2s5JbQ07k+l2N/h87kcPJayKNvux4z0D27gpAco+FKm+0%204KdJRT+yePfsnjLiJsiMzMhIQODSQen9Kmn3DzNdi7RaI8HkB7kTmOaHAvajgiGyA/b+1qw6kdfq%20ZyV3nOPnxGYbi0vc1x2MN7uADtURCfKrpbkDtLkgs05Ehic2J42+rYUTpZFIT9vI71zIvaRs+eIF%20zkD2NJ2BtwECgDw6fteqVc89DG1kkdP7Z7+4nC4Pju0uXwshjuRh9mPIx3BCzKJ2Puv9X4V4Pc/j%20fU3vVmeh+WmftNqdxCSfEvfD/TztbDg9vIbNkuFmsfIhaADo4D4dK5Nz85XqT4fHHtK/z2JtvGfp%20sR0XHyYbER0XutMjyQDq9pDV8QQvhXnPvatv7ss+fGNMuPuNPT8MY+pBZHbnceRkT5DM7Ea7JaWT%20gelqMAKIn5kv49K6NrvduVDyxlxywynVrgyMl7Z70jw2mCaPJ2uSCDHe1rtwNnBR06fHW1bf6qf9%202Sx7vpnzJhLgV3mOwvqFykfr457WMBlBOQxSwlS4tDiSDoK7tjvNuqnqnnjEnPdpuF4c8fVERH9O%20+83sDhg5rI77ZFRQCG9HWAJS1af8jtvSybxj+QW1DjHzEHcB3lBE6ReRhA+YtdI7aiDx86uveUs8%20oeMeYdKxj9l7BTKPfDQRNyPKxRMG4scXtDEuFsERRT/0V0+2cfoHSpXiO8LvL6gcevs8/ltHUvY1%20SABY7mqiXqlvTos/MT26ta+I1m5nu3IyXZM/KSzzOJeTI0EesAF20DRKVtxPNrUa2lwYln833Hmx%20sjzzBPF7jQ4vjJeCHIoKoqarV03qqYIttKCbyZ528ZmRus0NLhvILg3QNd0On86iq6vHGIOZrhpp%20jDyPR/0JjfF9MuKY9FaH6FfzGvX7dzRY4mG65sX+tzM539VcLjMmfj/1bXOk2vbGBohIVa87vnms%20cjr7bRnJu9OLhwu1cpuO7ZDG5rQALAvcEJKeI1SuGkdRu5WMe45/gYsWTnRY8kjYwWuc0G1zZoF7%20k9K6EJ2ykbcVldxcOZsrjZjsDnNmwHq6KRD6lHRw+yuiDFExxfdvIcjny5EbA7FPt+5xp9LvdWwJ%20129UqL0RS0zOed5t4vC7iyY8hplfK9zpxG4B0T3KQ1qdWnoa6tpSjK3gVlmbOWeyZD7bCfbOjxcg%20qRoqVsqISbOl/T15/wBvxqb+48EkFUK3b+UafjXzH5b/AOz2Hsdm2qPHEpvdjHnunNYGH3HPA2gB%20Usnmlq9jsv8A6azyPP7hfexLHifHzLA1vtxSo2SUtBKO1B863tnVma1HnEZ2fhMyWQZDmTRFpYQ7%20RbEIfAaD8DWV9qm5DaN6bjWTZd+O5/JjwJcvPlaZQ4uhttJRBtTp++vH7jsparXKuMcj0NvdSxiC%20A5n6icvLnmU47XTSi23otwNTYdP+FdOx+J261gwv3lmxnHzWXK92VJIx08iA45uGkHU+aLXQ+1rW%20sLQa3mxZvd5x43DFhLnzvG3foE1cxyN69OlY2/H9TXU/6lf6Y/qh3x/N8bNiv/yefJFnZD0exgkR%20rBe6WAfbotb17PbS00OW/dX0HAh7hycdONdN+ncjWS5XpvdRGo/f51L7TaTlouncX5kzxHHSRn3e%20Qk/UPskZ2hm1pKORCHeIqa9vVaKDtr1LDz4w8LIkh7MT3iLbG0AiwKI252m5b4i/xrV7VeSKScZr%20H66cPZJuTHG7+5ua43eCF6/aqpc/chvVVa1SWOI07KGvZ5Z4988ZHujaWuF3Fm0gEgelWlXdbAae%20FGbHVZx8/ouEa4c6bnwqY5HMIcifKC7rrZv86bZlatYhrGX74Q5xuX5WAh7MyQNN9SA8IbL5afGn%201cDO/a7b0WPePf8Ac/MsYr5BKgAe6QGxCelR+b7rVa3GYf4Ntv64xoOWd88hGGB+Gy4BdIUVwX8o%200BKeFWt6xhb8VTPMcwd6YT7yROa9oBLEW7gvnVLf8DB/ib/9LQt/ubg5miOQuAkG57XNOwEXG61z%20T9WrzzMX2G+vLzx4DhvJcLltLfdie0KST6UPS+po6qJwZejv14GZMXipQGtbEVBczaW6Hw+yjoo+%20WPkZu29Xgxu/gOIJcHQAuIKguNx9pp+hXUld1uIaP7V4cq0B4DmkNvoo+0C1J7FS699Y55zPJ5PH%208xlYGO0Ox8N4aJHbtwPRA3TretqdhWy1xjHPor3tiW7cxcrm8fIy/dERY/22xkKZEA+BNZX7GCv9%20sEyeC5QC2VFIQ1rnByW2jz/fWD7Rlf8AI15Gf0vONIJZDIGo8kO2KCCEvY1D7J6Gi76nIy88mWBz%208Rp2HRjm3sC1SfvrP/Jcuvf7ZHcy9+RAIpoXRPBDmNIUEhbFPK61Ndi1XnjH7lLf23GZVpI4mlwa%20UIPzgeY8a1ljmr0DLzCYWmFv9yNzXITYu1IpVqPyRXuZw+OzMiATPdFJK5w/UBCAD8u4dL26V07W%205C5nPuUzlF/+mna+Zi/ULtmSENdDHm47ppIydrtmpcET5TonSrrvdTMbbaqtT2idK2Mjk3Ldv89+%20smfichE6Rz3PYyVq2P5bG4F09VeBdw2egm4IXM4fvtuJJ7bcZ0zWn5XoYyAoc0LclNKatA2zmLez%20+5eIMrJYcrImzFkzb7mSyk7musEBBC/v1rbc3urQxdXyJ/F5HmcOSF2VAPS1rRCNxcE2jb1QX61l%20Tda/XGOQKsZFwxeJ4suec+P3g5u5scJa0NBu56oPmW//ABrT1cs1jHuk3XbsieVxe2sCJs2Tk5Me%20OGGCMBpka4uBQEElxFzeurb7x1eeP0If412cLUoHH/43iX5Rilnc6dBIiANY07ggKlehvVb3ctrO%20PnnJdPx/HzxjXgTvHd4ZeZkQYro9sU0oYUu1u61wR6h1SsZyKv20KRt3N253FwnLs7o4gPOKx5OV%20DjOLXBoIBc6I3kCH0mt1uKy8TjVenGMeJSe7OIweVznZ/D5P6mfKYXZeI1rg4yBC4uU2c77vsrRL%20H6e0qu5HsKUyCWXkcTDlDm5T3xsbvBQncCA7qnp61N2lWzXIdodl5nYyDG2/pYQHAAoFB2qAOlq+%20InqPeiM38yt97sa7BiJNo3qNng4Cxsup616X4x/czn7jQoTcXGyuRMeXkHGjbHuEgbuJOt0ChrfG%20vo63yPNrszbM7j2TiR8T2/j5bnsfFLAsbxGAsegeCQCrvE61hazkq9UssYxkQvJ9wZ+fmHHwWh67%20nOBUtHRu4qlU7KqzIrRsjX4mQ1hOY9+aY2hzjC5GsPmqrf8AnXM95tStDetVo8hy9/DNHrIiYl3x%20oCQRZf8AmB/nWa3LvXI09PgSOBk4U7jHBlkSP9LMd6N3KD8pI8vGta3evEwvtkvFM7HGwhzYWoHr%20qHAqp1Hl4VqrGbExh8VmzufkYsT8iUK6V5IIDb9FQBKpPxIcam3c3OcW3tDMxsfIbIdrmO2jqgaj%20SfCpqvuKtpmcz7axuZhdkZ/GvY//ABcQyJop/S1wUDY0flcdNa6LNcSaot2F3X21yWHFltyG4WSS%20f1OHMT/bkBK7XW3MvauO1Gp5HTV8yP7h5LtrJ4uXHfyMTHFTDIHKj/4rVbSvqU7KfA5gJs4sd7MY%20Ic1ZC4roQFCr1613SjlbYnPDnu3NmxbuFnAKCtx99BDk7xx3avBZHbHD8xkYQi5mHHg9idxIcyYI%20GkN9OtfHdz+TvXfvtrOuPP3Hr7Wwmkyzlvc27cH4zmEXLmvW/hdK8W1dmY+7M6U3Bl7+fa9yYsEg%20Bs/3HN3ek9DoaPR24nqDrMS5XJsZudhiRzrJHID0QG4FlI0qPTp/3IrryNf8lltY1z8WXe5wHswo%208povgNLil6FW4le0GxKTnWQxNlfDksYoO0xuO1fj4Xq/8rs+HvGrybf7mxwQ45j2B1lkDmnaijUK%20m0/d9lX6G5Gn1Jhckbu7vbE16cgt/US4glwNiB+bVaS7bceUPCj5ZE9O14Doc9lSNI94TNcS66SB%20wUtXr/Ub9FWpavXVvCjHkC268iq8xizc9nvfkZIjkhAEQja1rS0BQmz8pAF11r1tnfarOOXl/Bna%20lVkkRx7OVQ6eMDYvq9KAq4gbf6Sa3XduclOfv/kzdMtc/h8zX/Z88Ljk+7H/AOn3OIc1BsYPSNfU%20q6/CtNvvJuk+P1Ittfa40GMnDfrMSSLGzpA1jt8wcASA4q4Ot6RtKaV66bq9DgdVwPS30axmY3YG%20BEwlzGul2lyabz4V6vbOaI5d3+xd63Mznf1VY6SXCY0t3OjeEdZQXD5Stj515X5LWvtOnYUpnJu9%20RMO15RZu2RiP0LmlxX0j0+kqa4tqOvGOJ0PKM8jnUisysSRkm2b3Rta3TXVEPjXoqoWQ3xu48njO%20TyffYJePyJXOzIkRw8HN18dKv0/eZJmJZsLD7gM/E5QGNJG6eLKHzsaAvtuDh8wPjTSbWYcTn/Lx%20FzXZUz3/AKnIeXHcheQXfM8Hyrp29I8jG0jWGNrpg7fYeoqdyu6219VPHgKqLr2p3Di8dx/s5DZG%20M91TIzS7gNpAQ6V4vfdo9y0rWMY+Z6fa7yVYZGd0ukys9+bilMPIeQJGgq/aPzdfDUV19nVU2+l8%20Dn3112kb8fxuVkz/AKqScYvHxJ70hsXEXLWN1cb/ALdemqTRhbJiORyEEWS6TBaVYTtkfdxXQk30%20p1q4zY+sSbkyTvD5HuLCQ6VT1BVftqegutveZfs9sBxum5vgA4X+wf6UKueMYk1Eljc/a0AbijSt%2073RAP51eiE2uI/xnxOLGxt3tLgxvQE/An/zLr/DK648cfwbUvVLGMe6xcV2nwmFlul5iLJzNw3Bs%20TDtBS5d8xTyPxp+o/acTzeRZ87nuBgw4GfrDC2EtEeK4IRGLBB46mpdXwNNi/S2yRwYOK5Fi4HKw%20ubJtEPuuLWvc7WMvHyo4D5kX41lbqXA73v5wNOSwc3jcr9PmwuheSdq+pjmj1bmu6/t41KvOprTc%20TEGZDWKECFWOBKAKdARp91UV1Yx7vIUGUACwBrG6N3EnbtAItb91EjnGPZ7kYdltBBaNpa1SOrUK%20FNt9etPMlvhOMeww3I8CXbkcCeo1Ui9MOpZC4c1vqY3YULy4EFFKNF+o++gJ88fMSejfSHOVoQWQ%20Ovq4agjSgE3zNYZkaC1wKrtKKOoCJ4eVNlTKiTZztziWs2lEAdZT4k+B6UC6tXjGPA0a8F5ACE3J%20KdClA1ZeYOmYHbgSxwQ2CHy1vRBLSfD98eS8MxdvKZbGlrJH63uhVV1P7XprIm3b7b1rzxpjXwHc%20PcfIRPaTIXNatnXsiDcLbh91aKzbieOMZnNbsdqJjTGXmc4zMwZPIZGQ96STSu9w9fUtyhRSPsr2%20NvOq5nh7n2XcHU/pxxkOR2mJ4pQ0tdJ70Y+YPSzP/MFJX4U73yfyMWm3BlvdGK8vD2Oa9jisZAXc%20EH5f6T0OiV5j3nLnGPadr/G3SlYxqKDnMCRFm9btFBb11NqfqLyMbdluIUGbjPCsmBDTZwKFSoIU%20/wAqTunxMns3WtWQ/cxjGPFkOXdA53t7DoZGIrgdb9aa0x54wxbct8h7xmJCOOx4pIt7WxBziRb1%20HUhPEkVaRNtxzkOXcbxT3FzsWN17gtCUvTXIPVvzEf8AbnAP/wCphxk6lQTfw6rR0V5De/uPiWjs%20aGKLujiGQMDGHIiHpsqOCKSLpbSmqwhdbtZTmei6DrKBmSQNyXD5V0bcqdxF0SvEslLg9BZrM1Aa%20ZNgQ7SCQfD8q/Gp6UNG0REYCnUhwJsE8/tShbbCRR2HjzjdLFG6Q3buaFDhZSRfwpOgsiEm7cytz%202tfGQ4q3VFBUI3RSNaJaxjHw6a70FG+oGBkxYUUc+3GEszXF0hIROqNNz/GilHKh45eXyNK7ySjH%20sx8yhxcj2TK4xchPlCZ6sa9jGhnpsCFud3nXTXt7RHhjHMxt3v00RtjwcZNPAOPynQyNeFx8wIhD%20wAS8Ki+PWm9qwrd31J44F57df3LyYyG4ORByOJCXwkxuR7HINzS14DtetxXHfbunBy9bc/D9ykd6%20Y47fDOagEGBzKmOfj45GPMjQS1xDWOd6vxro7TcvEPkRYqcvN8Xy/IcflzRxSyRFXBE3PKoS0Cx/%20byrt7mr9NpZSHbuL5lnPdHEyRNilEgnux7yGucWBACAn8Vr5FdjuJyog971V7SF7rz4crFhbBKJX%20scfcDSQC14N3EFPO9dvYbNq2bahY0Md20rIi+1u3uD5PuJmLkzOfkNaHytaQI0bd43BVtavb6n0n%20ntw8jofcfcEZwxgYEZZGGtijO9A1oG1gAtpppUuEQ1LxjEjLHggwMMQtbteG753gKQSOp+GlcW5d%20tnTRLkReW4yTNbFeTYA4IgYAV2oLFP2vRSreuvvNLNC2HwL3OWQIAiONzey2VfvrTTHtgxdxTkcT%20j8JsT8iYRjJdsgDwC8uuoaSup+6qrtN+wjrLDxMjspv+PzBuzWhcKYlDKlvbefG1qdW/YJwxJkMj%20TJvd6yhLCLtP5gU8ErZMzhMguf4jMz543RvZFjwhI4t1yfzOuPPxq0yWzTiopcTt/ncraWGRjMQx%20lqK/5zc9W9am8Njoc/yeOd/jXSQtM2Q1qTxaOFydzQdUq6mlnkQ2FlxKPcja5jyjHEBBbUGtbLKC%20KWH0rYYhGceR0rnggxJsc1oCXcP2WhM0ygMV2LjtdJ7hyZzdmu1pNhbq7RKHJCueiOGZLH2TxrMl%20hdIMeESNeVvYhU6btK/O+9tPdXh8XjHyPa2f6onCXIwmxai/1Epr5iuamds9PfiPgHA1ka4NK2Gp%20YNCUHRVQCnajjGOYVfgaOchKn1EruVUb/wAp+2s7VjL9hrMHSBri0kgixaLD4f8Am8dalZFRJqHy%20glQFBPqT5bXPwvpTiNAcGsxDmDeAbCxAKADoaab54x+pMDafCwpDufAx7kAVzWk2tqfhWldyy0bG%20axwwY7S2BghY4guDfSQVFynhQ7u2rGqlMflvweShyw7bE9z43H5mgNKgbb2QFf317m1TqpD8P3+h%20zXbLXA4PaXRvAa8glzdBuWylTva0tN/hXHaE4axlj45speAlNiMzYjEWCRkxDXHaXbd72lE8L6Ap%2091b9uv8A2KcZP2/s8/Gb6E03sLjYGFmO4tYAAC8nfbU/811SvoHWTgOvdgYEWB2zj4sZBEbngpop%20cpr1u0S9NQcO/wD2LFXSZHOvqvkPin49rGFz3h7Q4W2qQp3dCei615P5LWr5T9P55nV26yfA5H3Z%20mDI7dzopZi18Xtu2ByhQS4eGrjdNDrXFsWfVnjh8jSzXlPhjP6aZFRbAx2RDlTBTES5hcF2uP5gi%20a13JwNtNFPyOXyIH5UEEgbBkOddwDgdDqiiumqM28yF9MTHmRwJYQfaBs/cm2/xrRa+BDQ3/AMRy%20+ecjKxoX5LoNpl9uxG4hjUTzcKfUvYJqRaHhsiDKdjZOPJBPAdz8dw2vUBRY/Gs7Xyxj6mirlmSu%20P2hm4w3z5cceLKiuYC8xaI5zBotZWt1KTSn25STE/YHdmBje/FGMvAaj4WtIIdu0UL1CoazVqtqc%20irZ6FMzm8lNJ7UjXwkPLm47xs2kWt59K7axGRztCM+DjNAa+QxyBo3B11d1uNPCqq5yFHEQllGO0%20RAAtJa47RZ3QePjSgpMwM+N9nRloQH1afC5o6GgTkWcXKqdEaifM6/2aUIryLZ23gdnw5WHNzXLO%20OM6IvysbFhcZIpgoa3cSjwEBP+lZ2cDq4LNy/dnOMyH/AKJIMF7AcfIyWhxLtA5Nb/GsapcSnt2W%20pzjPnynTSy5UTH5cjne5Mq+uxKXRE8K6IMungKcdnzYM4lR20D1QlqMkjPkdD4HxpPMMzuXCYTOX%207fPHy5n68mEZPBTyE7/adq1w19DtQa47LM3pdwVObA5THmcyWBksoOxxjcY1KXABXUda1hNGv+hr%20UafqBExu6CWORyEOTcwjVPNLG9LoLXcLRmGTwOkEcUkbgUspapCbtQClN1K9eoo0TFx9NlCvBJAX%207f2Sk6s0VlMIPfG3UhxP5vFUv8LU2oBW5CT8pyghXaqAddR91/51MoanUy3KXVyG5crtoTTUobJ4%2005BWbFWZIcu1xLS30usNoS3Q/atUhu0PPGP4MumAePEgvulittPM05DqeU+ePn9TU5PtlDfepH3X%20QgXv1/hQOcjDcljha4UaqCAL38VoE3jHuMTZb/bMgcdoBKWuhW1tT8avbiVlJG82qt+eP0KaHf20%20c0uatyLNvoF6V71Usk8Y8j5u9Gnyxj+ToH0V5d8HJZfDyS7G5Y9+IOADTJGddU+XqlS1Kgz3HHsD%20vTjDgc/OESLK/vxEXTfqPDU9a8nuKpPI+g7Hd6qKdVl7CFMkqNBeLBGkk+CfxrGDdWyMMllVoDiC%20tnC/2W6UoKWbG2XmSsDN25+8prqdPGrqjHfoo0H2JznIsYWCVwCh3pJQ+H2fDWm7MldrttS1Lx/P%20t98lH3Tngne4PQaFqA/FFo9Sxk/x20x3D3a8BXxsfI4AhA5p2pdQFuEtV+s/YYX/ABdVoyy9g9zx%20ZHefC44hO+XLiaoulynTwP4U1uy4Zjb8a0uqcljHtPUlaGRRcpkcc7nPPpcnqUekqiN6ha8S7zZ3%20JZDeH2SSQ86q4uaW/KPluLNAokpSbHZ6SXAFQSQdtgUUE7uia0dUhBu6QdG7gTZjvTbVbLrrelIG%20rXgE7wNrwr3BQQ0n/WpiRy0jzj9Qu6cnuDuHIkZIRhQvMWO0l23YxQmqXK3rt20qoycsqksJDzFv%20um4AWOhtddK1ruId9pzkb4+U5gDvVJsJMhT5mE/mPUjpVsxzke8VxnIZHKZmRxHIuxMtmLJO6JXL%20kRsaCWN2n5krNlJFDyw6R5lErvU785JdrdSbqOta1S4jtWWW8/TTuHiuLb3Llsjj4xs3sRtEizNl%20cAWl0Y6EFda593dlONStuqTkTkheJGscm5u3egVVJ3qE2kOX+PSvOVsj00x1lYPtQF7Wk+2fl6kE%20ObuDkO65+NYbe9NoLdYLJ2lyByHZn/oo2xwQh0c0cYaXORFa5DZP2616NXPmce90paG+KyKXkTIi%20shZvuF9WqddDp/pT37LpzMqVzM5j3s2lxcsaTSI4uL32DVKJqn42rkybeI5Y+J0yh3wPEulAe0bp%20fnchLgVsrR1NbdPA57NSdL4T6X5M0ccmZkNxWOASMXeOrQV26p9lbQjF2nQS7h+i3C8lJhyT5r3y%20YbzLjtIRXEKVQhQPIUneFkEsrXPdr8nxw90t3RBytyIyCGvaSjraVjdpl1Y0yvayQzL3EfqGpkBU%20HusAD0/8Wtq2pYGlBFK332l26Rr0G4aHVR5/dVQJsYd384/Jjx8Fgii9lqGCJdoupL/N3WmkNeBW%2048aEyy5BBY6FoLXAr0PpPxNvhVZiTXEpnO4sOHmiaAbsTK9TPAO/O2+hB/CtqOUK9YFeQxTHxOBk%20tarXtc1y2BLrjT4UVtNvE01Q0wE/WQNf6WB4LiSEXolqt6GHE9JcTI6Ts/j/AHZA98scIBI0cUS1%20lQpX5z3CnurxzePd8j3NvKi8ieCt9to+VQACqgrbr+yVmqKZDNie+4DvBXWA0FrX1Fb9JMmHP3JY%20vS5uG3Pq1Toand28smOthHcArT6betPUUJFtbWK1xOsM1NdxuXAlyepx8dNKICA3E2JuDc31A0t4%20AUJccYkcQaOdptF0A1NwVctOARoXtLtwuLBbJYf6VUAirwYbeQ47LxnMPuCTdGXbGhblviL+H3V6%20/qOjT8MfyYupp25ychD8HJcszAsG5Q7e7VluruhKoK23ttRKX745cfDIniT3vSCTHYHuYJJxE+VF%20AavqGttQlLstubr2fLCfxkz3bJIv7sWZ7pNk7RtH9p8gQbWH5kPwr3+GRwI6F2u4O4eJzSCwl2za%20ECLb416nar/1o493+xLV0GZxn/uBmzGZXCsglfHE5spka123cQ5u3TwNcnc0Tak22tGcQymzyxyL%20BM8uDke8lAg6k9V8awrSqZq1HmOGPXiRmuIP9k7muVCQNhatJ1zKk51mODgdnp/qb0duO5FGv23r%20p4GeQz/tvj3SqBH8rRd/kOmnnVJi8iY7WzMwRTuEjo4nuYdrNwB2qNfIVN0XVkrlOZlPEz2l72kE%20zOUuIaSgJqNdR/IMeX2SZMQ7JGemdgIILHfME8xSSE5RL8Nz+TxmVJiwzmSELJBAHFyRv+YFbego%20RUXpJorNEJ3rAJva5iJ273ZXRchGg2tkA9JQ6l7TentWhwFs8YxBUZ44pJPlYC0naAVA3aGxXrXQ%20vEzakRLGMLGxOAFg1puB4eVAukm+G7N53uKYxcVgOzpGt3vDbAJYndpWdt1LUum2uBfeK/7eO/Jx%20GZWYuNHKNwe+YSBnUDa0n8Kye9yLhIr31G7Fz+w8rj8TNy4crIzoXTj2VaGFrk2lSCitrSj6lnj9%20BqNSFzMv9V2u6bJeXZbstsEYHpYyJjS4kBACrqdaw8gvuyQ2PFNNtY2MyzTENiZ1K2Ab1qonUy6u%20IpLn5JIxMgE5OO8tbKSC+NrSntppZ1NLiJs6d9L+abi4skTz68DJbkRIHBzocj0OBsfQpBA1rn3a%20mlPMv+d2vmcjmZWThRHKijcPcc0gPaCPSg66/Go27ZZsLRwK5l8bNjTmGWAsexC4vVvRPs16VpW0%20igjcricNzCHQNciN9x/zEjzA/dT6uITIxk4ONpcMfIkhICtjadwCagBxWnIKUNMjB5VrXBwZkNFy%20SdjrdD0NqFBa3baIZyyFm33oXwEXS5aD4qKcGi3uYm2aOzDMFddflNhc36JRDLW+tRwHytbuX02J%20I9QKlUTWpdfAtWrJh0jHkKq3Nzdeuq60RmWvM199XlHmwABAt1TXyogpNGPdLS4luvzL18RVSDsn%20qa5UoGLLvcACEKqpUJre/Sr2lLhIw7m8UZFNcXQAIPcA2vPpRrdzUJVNxA/D7a9eEoPC6uWg94bJ%20/wATy2DyUZ3OxZI3KHbQGueQ8A210FrVavj9iehNanVfqPx0WRw+PyeOGlsaGWQBFEtySD03KB4V%20y90pUnT2F3W0Y08DmjpAWtKqU2t3C5HmlefwPZbh4x+gmHhrrOtdSPDT9v8AWgExpmSh5jhBQyK1%209zcjolOqkz3XjHsFo5WKPioHgAbj7AtI0pohZrrpcAKS1UFtaCpBV/jb9vG1IdcY+f6Fl+mrV+oH%20b5C7f10IS2m49bpVVI32uhzrGPf4nsyuk8MoGbK/9S9kbTv+TcL+ZQi1eJbV+Z3jGafN932mAEyC%20weFZtVF3KUdepyGvEIpJIWGGYBkqksaFeHDRHH8aFmPxFIBkvH91gjkaSjYWl+34nxQULMBHmZPY%204rOcpa6PHmc1xQbXBh27B4rVUzYmeWxI+PGfMSHFHOUgEkkqSt+prqbyHTLMRxZIWsEkzd8kjSm9%20WhXXBB6otqKo2TTUM09LHMcEVxQk2CaFU+NarQ491Zx4DzhuVyuN5TAz8d4inxJhseqADQjrZKT0%20gFqTU/0z4WfMlynZmTI3IkdI6MbWtO5yoUGnglJWyDMsU3AQ5xihlfLPiNIH6ZSPcdGEjc4/8v41%20m4a8cY95UtG7fpxBlkfp4ZsdziSZHOBRSpHqWxOtc1tuvBmtd6xHc12dyPFzYsOXtnxM1zo2yKEY%20Q0+lwPzL41x27dp/a88e46qb8rMccVg5vFcVI4NZJhfJizt9StOun9Kda6u2dn/bVmG/HAQwd78X%20IlcGmGaUCJ51eCgu03Iq95qciNvQRzo5nySbQGtdJFGpupHWwQWJVVrGj5s16i6/TThc3O5/ln5z%20vb4bGjbJgOaBvbIVuRfzrqTSXic1ky2ZHfHM/reSxcbAdMOOjBhIewPndtW4NwCi2rKWaenkKYOV%20icw+PuGfKlhWAMZjRKQxwXc0+N+h1p6PxIdRZ2e2aSWPcC1t9pIXa4EgIfTbqunlUdUAoKtzvCw4%20+Hkz4rWgtcx5iI9IIS7QoLQWkrTq8x8CjZxMALg8tariehaHWsnSumuZDzKm7GbFlvfA10sjkUXd%20JvIUW9RrVOBNmMtvsRRY84czfIH5A0cGgr6jqUrNsaKZ3bHLFyRjaVgdumxyg2gOsv2Vvs6D3dR3%20nhkvb2HkxlHxNjuDrZEvr4rU59ReXSRkUMTsWR75fbyG7TG0fmcTZPCrs4ZlxR6P4dkzeyuIEg9y%20URYrnAdSC02AX76+B7iq/wBG4/Fnsbdl0onHLqEKhC8myjxXW1caq088OMYk0cAXEN9B9JJcAblA%20lv28K6KviRGcCbiQgUEuCNJVGlE8vCqmRtcTR+4AlqtIVo6KqeFY326tTwxzKTEdUNiSidUTXT+F%20c8cC1zMEoQAFOjQEVU89ESmlOYAXDbY3NtxIF0IU/wAaK1E2YlRpO0FE9YCan5rLVNKR8CF4Zm7B%20kkAJLXuILStkboCfUfD7utd26s0ZIY9x8e/Gmj5TGJ3h6vaBdr0Lk0OpVSL10dtuSoeMeOWQmOMr%20IjyeHOWHf2w9vyNRwc1qI0D9yV2/j6/+/Thr7f4ObuZ9MiWc3yDH+47LnALi4by421VzXIL19Uq1%20jQ8VWfM9HfSPLny+xsKeeT3ZHvlV6AKPcKadEraiSWQm5zLlVCOO/XqX28riSGlx9ubQL+Ztcvc8%20Do2OJyCXNmVXEoQUU2118a58jaEU3kOQkghyMFsqhzxIccH83SxPnWyrJFnjGORVsmZX+5GVd+Zr%20fykXsp/dVokQkcwvYHtG5pJaBq5fFaYh3hcjJHjtY71alQR1uf3UNcgmSTizpZsP3nlC47Q7Wya1%20m1BqjPH5comc1jUjC+65flBQBPMqtSadErIde9FjnEG4NkhlI2tTc5kgvuI1+3rVQYxwHGRgx8g8%204a+0/L9ALyjGyMKtL6SaXkNS2M4vpdyLuSfg5HI4eJmxyNjDJpSA5z27mOYgRCPGh7yD029C18f/%20ANvHMicwcly+LjZB9ccY3PLmj84JAaQvSsrd14FLaOxfS7smDszhH8acxubPPJ7mRLtDAHH8jb7t%20qeNc25u9Tk0qi4xR4rSI4A2G19oLRbxKqbfuqW0ym35jfku2u3uYmgm5bAh5DIxwWxyStBc1puQh%20OnlV1tGhLOTf9yHF4UXafEHi4mYkOFle3LiQxhjSHMIBKBSQ4dK6Nm82z5GbrB58DShcTs2oQhQt%20K/MNPAXrqiTOWaDFlBc+QEEkOKm66hfjT6kCRdOxJtuXlscSYpMXbIwhWnZICN3hpWO6si6anoX6%20ZTOyOQ5YELsgxkJ6hXAN3X0/1SuWtmtC9xLQumZxMGfE6LOijljcNuxF6qPUlCtjGPmJxwKpyH0n%204CYmTGMuK92jQ4OaD01/jT62g1Kvy30r5yEyPxJo8rqAPS5F/wBKtXQoZVc3iuSwJTHmYT2uBtI5%20pLSt7OC6NNXKYnksZDGTHjkcS0khvqa0tBv13ePRapWyAjcjh8GQEmL1OXc9pQkageNgKfUyWhlL%202s7buxpyAVF3FpN7gO0XzqlAdT4DKbG5fCaZJWB0LervUiW+PS60RkWt2GZ4yHkeQfsgwjtaDukY%204e3pc3IclvCjpRrXebJLJ4J/HwGTkRM2J7UhGPH7rtxFt2gQ1Mop7z9pG8jHxP8At2NmJjz/AOSC%20GXe5I9rSpLWnaa32I6pk5d7ct0wiAgGdM8YbYZHEgv2EANsCpXxSu6+5WdUcdauNB1iZkM7W+sse%20dynqBe667gpV1vKqrac1wx7ce12rDOw9r8xg8n9Op8fkHlnsEYQPyvG8f2m23H5ilN5xzMqVfXHA%205g2LKbkvxHRbp4XOZIwKSNvzGx6ba815OOeMj2q7nUN2zeobSCwG/wBugX4Fahs0TkRknLZWudYM%209KDpcXW6gpVJ55mW7Zz449r+ApHMxwG8EBSWg9CTb76OMI2rbHgOY3s37Xrcgu8RfofGiOZeZlkg%20HkBdqjx8+n2ddKWmg8Y/f9S0fTV5P1A7f8BnRWOqr+6hamW7lR+R7LrpPGPO/K92dzYvJziLPhmY%20JHNAQlwaHFGqRZOt68t7ctydqvyEP99dwtA2SMKrcAIbqXXRf30PZxjHzB2XA1b9QO62q0PgZJcb%20tgeWjVVC36U3tITt7xF/d3cGUxHZrmsI2vbENoI0JT7KOhDlsZZ2TnSwu96eSQzxna5SnyqhC6VS%20S4Yx+pPVKOYtjkONIyRu112hWqNTqadka0twG+dFJNiYeM1rWiB//UCKAHFynxvS6oR0OrahGua0%20tLSFY97rtQXBt4/slaJmG+lIlMXMbMHyFQ9u9Aum3XW9qTkyR3+TguFmxcZsU0sMhgYJGJqgRUFl%208q5bWKqkNjw/NYbQcSRr4mbtj9waAdChP31XWmEQMZO7+Tx3uZM5jnNs5yAgWRQRb7qFtyN2IPvL%20vHjsnhJcWVr358xEeKAQGB50cUQ+kUlsZlKzIftKCbG4DIimyRLKQN21xDdzXE2b1JW5rSyz0E3J%20L4gYeJdHE5wfjyghzhqHnc74msd7+w9sZZbWtUhrSxkzXa3JcoIKeC1nRvmatyjpnaMEUvavKGRx%20Y2Y+2HNcGOFlRfyqQgWteqEYpzYq2PIzIjblz/qjGydz4HRbjM2NrtgYXtPq6/caIcxljHD4Ho2o%20ulaY4vC9pr2TnSu5PkM1kkj4GSuhbjmzEIXeh/M1PVSvkjiuoaJzF5GRvJtbcqDG4OuC3dub1/qt%20esJJgkcuRsmNkR3cHwvsSiI0+q5N1NNOQOc8yzHZgxSbi9m1rpCUHqCLrXXUyafE04nuDH4fHnyX%20Ox45tqQvLd0wePTbU2HlRZORxOpT8t8mTM6SY+4/IJV5uUXxCqaaKyIDuiNsWAQHFz8Rzfbsp2yB%20Ng+Dq02nLItmMhE93bEMz5HIZj7cAGoNjc+Bq3lYqv8AUMvi5YsFmVFLHNCR8jSNw0pTnDIayPRu%20DGf9tce0tQezAgToQCh/b418JvJevfzxjmeztW+1MkyQ0XNwqm5sgsltbXqK0kGzRyFoXS+2wQr8%20NEFXGWPmJM1HU6LZV8fGkM1mcx0Z6NCoPDoVN9KrqyBVbccRB5HqXToSfAa15/E2NVQroQR5FE0N%20IcBo1SOpBPTW+u4dOtaVZDyNZFDHI1TtJa0dVCADzqeI1ob9pcVh5PCxPdlCJ5meXMLHflIARwN7%20hb/jX0m32ask3j4Y9hw33c8iRye3MB7JIX5sbYXtLZHPBCg6EjQUU7CH44jHH2C9c5u3iO4HS5XG%20YUbsqAvaWCFCC4FNzT0+3WvT7fZrTNmPcbvWa5seRxExg5aN2JlbQXRyX9N9pIS4clex18Jzxj5n%20mdOh6M+jUzJuwcGRj/caXyo74SEVsogmC7UwOO/XzDy5p+Kmh9sxwxy+415RxUhNvjpXJ3Nkok6e%203WpxWbIgLTvckZBcoR1jqvl0/wBaxWZs0/5ILmeFw+S/vQOdDlMQF6EqB+Y/berrcl0ZWp+0s8BT%20KryquAQE3JNutaqxn0iB7YzdyPJIaAHAAgW6H8b0dSQQx5D2tkRhXogIUL+B86JQoY4djux8Ywkl%20WkkprcqAhHVahmlBrh5hxGZD5WF2O6VjA8FABt8TqOlEZm1bwiQyWMEczHOa0vZd9lUG2oWhKDCZ%20fgOC2aTEbyBV0bHx+sfmLggNKSiS4jmOSxciXIc3HknyNge58TZAGsFg3cCg+FTakjTyzOqdu/Uz%20hMgQQ8/iNimgH9nKj9QadFAKpp41zX2GaLcktLu9OypQC3NQu19BCj9gtZrbsPqFoe5uBI3Q81H6%20SjGvICnW5QhD1pdD5AmmSEHc/CSO/uZuOS649uQW1Ckr5U8+WZUFb+rkPG9yfT3k8HHy4pMrGaMr%20GR4u+H1FAvgorTat9yTM7UjM8pRSMLHNduAcEc7VD4InjXe0YySuIMN+BNyOVyzP8jCGsxsB8RkM%20zNPms1m1osoqVXPQbcj7tyN0fvybtpc1sTmLqXvaTu16VG5kVQ9EfRfHJxOZ5MAiHJnbDCp3NSAI%20XAjrdK5mVbgdFACXOlrr0tU5AD4g4qnxH+lOBKxlse3QA+B8KPIUms+NjzBJoxKCtnjcL+RtRIFT%20576b9v58AGHEMKcEn3olNjqC3rTVnwGkuJROY+mHcOGG/pWOzY7OWMDcL6bfGtFcmCpZfG8jjTgS%20wzY8jQhZIwktPXW2qLV9aGveNwBO0tcB6gjQbg9OienrT6gUkIjWcm9sbyz2zo21gfL76zd2d22s%20kWHB7l7jwkOPnbW3D2PDZGFCSApVBby/jU9fhjy8DX0qvVc8Yz04kxB9QXSAM5bg8HkIT821gjeQ%20L7gQC5o1/ZVqWsYRL2FEaDocz9IeS2jkuIl4ma7RJjl7xtQ3BHpB6+rTxp9bnGRj/l5PznIdx/TD%206fcvjMHB8njTbCQyOYtL3PfchxYWO00rRb7rjGNDmv2z5YxJnjOwOb4IuZi8PHLi5E8T8xscpkY5%20kRBZ6LkFfOr/ANFumDF7NZzLrN2vx+a9uQePxosglzjI4ESEuIa5A0t/lWVt7LT54gutWsznvJ/R%20N0bpH4s8MoJ3RtDg0sDjZlyVIoW9GTNeqxzXuHt6DjhkQ++4z413tIHt+kf1DwHVK3rd6g1o2QmH%20mMA3BxKlSbKQg1UdVpxzNK3j9R43IY4NaLKPOxdoqeVS/EtWkWZIS4nVouS4jQXsB9t6MipLR9M3%20r9Qu3AgX9dEl/P7qddSd5/a8Yx5HtCuk8Y80c32pzuNlZmc+FsWMZJCr3AEtL7FoCa7lrzupzB2o%20ZYHHx5eS3HPvPYhJbA3dJboB060naMY8wjqxhllxOI7FxnBua7K3tu52S322kBfT6R/GsuphHEsv%20GwdmANODFjPd6doLlIKkr6rr8ah3Y+gfycRwEkm6XCYSSSGtCg3RUaaXUHTyOU8z2vi4nc2RhStT%20EyD7sPT0FdyaonStFZsqpHZv0nzfcfkcZlwvxEDpI5jsICdXePWqW4zXbtDbOdctsizTjIS6NxY4%20iyuW6H/Wt6LIx3rzaSPx2GfJhg3OEc84a577AtFlX/yiixKO44mXicjHHGeSDWQNEYbjoHhrWnXx%20vXM6tcC0xxPi8MxXnImedrUjmLntJunpXWs3ZlajXKgxc518NszQ3ZvYsXy2UJ6Vpqzkl19xT83B%2043Hnb7r4nQqS3HyBuIUIu9padK3rZvgKyjzE+LbxjOVlhwmt9uaJ+6U+rzAb5ap1pxIm4TJvh8f3%20YM7GkO1zovcY0fMNpVEPXb5+Fc+7nmUmIS47XteNivlYA7xO24F/BazRbfAu309y48nhc/DkiEu9%20rXOZIDtKo3a7aFCpW0syzkrvLYfcmJKMfCSDFnYRscS32HqTvYWkFzSNFNRJ2LeyGHbuPm8RjtyH%207hmTmRspcdSTckAp1qbtxBm4bkkshmQ7GlkwXe3mEPOO4j0snIBAP2lKxrE+ImhfsWXu3/Av/wBz%20Ma7k4/e2gbSTCASr/wCFdG509X26GKT4ld5yZ0fHR+6xoYW7lGrgu5pv/KuihLKPPNjSZG9wI2o5%20pRXAgdFUdKuykabMy+7AyTMnYY32GPC4EI12iLprrRwGm2VruSGaLOY55MjHxtMdyjnEX8lBrTbe%20RNxziPY7DiiLmyEtYrB0SziiVN9WVVwoNZ2QQ4p2wNi9QDluLea/jULNlRCyPQkAb/tvjwCNnsY9%200NxtCgfmU/tevjdxP17RzeP5/U9KryJWSNNwALlVoAsVBRPDof2Faf52nj26+f10J65D1go3QAhp%20JB9JJatk+OvnR0uNOHwc54gJETs2hUHp/LZUPX996zvEYxjgMReXaJ1sSiLp+1q4t6iN6txAkehR%20BpqbKv7hWDcyMwF+2wAAuvUX111qoCTUhSgapsg1ubJ4J+3wqteISacg1seNmBhRojeWlNFav/3a%20VV9y8xzkTfaPAYc3bOI/3Zon5G50oY4Bu/cBa4Ww3f8AGvqduzVVCxjgeXuakXyr48jOPH4M0ssS%20hjy/1xFyeoi3yiuml3GeuMiHVJEucniez+23crkO2Fg/tRyEtfLO5Nq7boF0rROXCIbVTh/M8jmc%20znTcnysnv+4S6VdxAaULWgrZoFhXTt26fHGPDx4nA7Oz0PT/ANBTEfpnxvtBI985b6dtjK4qlejt%206CtqdCrQRzT6v8xjcdLx3u4zMiR7ZDGS3cQhb49K4e8q21HidXbuJOLcnJFmPP6bjWRyG7XwhxG5%20upvbz+yuZZHSoIp2JlY7mxyRNjlTcY/lcATfp1q5TJhwOh2/yUuJNktj93Fx03uj9YBI6eJoV8wz%20bGRjicnpu1LBLLfolVLJhCT2Pa0hsQAAQbrqp8qOrxFBX+Wa4Tt3Id7VB1JvdfjWqciWRFZEU+RB%20+ma8s9ktLIzff6rgr4LpQ3BedkOJ2N3BhY1+xhBc6wBAQEJ9tEkNQS+LnYp7S/RlBkewAQdQGuc4%20FPNanpzCcjLZGRCyXvJZQUuviP28acsloluO5SCTHOHPiN33MeU123aRf1aNIv8AfSdSkstTMuXi%2042QXx5Ec51cWkkApofs8KSDzFHZuPO1z9xDXldhsBoQPO4pvLgNSnHETle0Q742bYwoMpBIBFwV8%20+nwpQoHLGMvLTse58bdxKkKCilb63JoVYB2lFB5PFfFlyPEZZjPJKELtIRQfiVvW9TJ6hixtebq8%20lEYxb+F0qYGmXbsztHmef5CPF46F0kTXLNkIsTCRcuct2gdPGsdy5rVQzuPE9idz8ZhMw+P5dkcM%20aIxhe1m4rueQmpNY9SG5H0fGfUiBrQM6LJdbc7clwE60ZA2acly3fXE48c+ZJGYnODXyMaxwat7g%20fCiFwFCNeO707rzA6PDxoc2RrdxIBaU62B/Ch0fMGkOm93d4RlxyOE9AC7mh4RPipqY8Q+00Z9QO%20TbIRPwshaqejcvXqQRTh6hl4mXfVPBZabAmYerdwW9hqBTSYoQjN9Te1pR/cilBJQl8bHdfl6jqE%20Sr6GBB9wc39NsgOkOE8yvtI+JhicP+bwKJ+N6K0gEcleMc8pPJjtJg3kxtkA3IAjdFU3/YVLmczv%2024HcTdxQhS4FzR852kot1VLlNV8amuXj8McPYaOynLTHl/BiZoLHbQrblE3I1A38xPQdPvtVaE9T%20Q2lLlaXC4UuuVQ+rdfxJ6UFNpxKywhg9jS5qEtdtT0naV+YW0uatOBMd8Z3j3Tgn9Pi8nkMgcSDE%20TuaQRt+Vy9KpJJyiJh5o6b2f3DznMYs5zsoyvDgNyALuF9yXdoPsrKyzSXxy08eH7lVyLRPk/oeO%20ycs+4XGN0jnuG7c6FoCO6A66/ZenS68I5e3T5fXiZ25ZPGOR5+5fNM3F52U9TLMxziNSHEk6i4+y%20uuqZzbjKHByTY42+5CQEDVBQEXP3+rpW6qYdZL4eU1yeu5VQhAI0uCCviP41EOINa3zH6hAQiGxc%20SUIIufI+VZmyuvDH1LV9LnD/ANxO3AQdw5CFQSV1KXFtKqqh+GMfpwncyo8fHyPbVdB5RyL6iSyD%20ipPSGtLw0NOhLSo+YjXSvIbmzO0o3Z+U9vP4aBHOs7abgEqdyGrvkh1TZ0/YzIY/3IBO67ix+1wt%20oBZLpesVqOJI+Xtbh5TIZOOaNt3EbmOBA/KQelKRxI1PaWNE5cLkcvD2vO4Nk3ANVDuDiBTTDMie%204eyeczoBLHyozJcZXsikYGucRcjcULvlpq6A53yXe/I4WPPh5sMmLkXayKRhBLho5UQ/ZWtNZQS0%20cs5HN2zyvmcDNKpFwSFNy6+tdS0OdyTfZ3J4/C5zs5+LDyD3N9tsM4L2ta5FdYOufH7qh1kET8nI%208XmOeXcW7F3Gz8aZ8YBJUHbYdKjpg06uC0M4OVzECnEy5AwabyDa+1vqJpuqeodRJ/7m7mijEbHx%20uIKAyAPeQfLxrP0lI+sip8eCeaSXkXOOW4kksa1jXaXKBNKtKCZFcHGk4yI5u2LKLNr2MY4teAVV%203/2qVrfEurLHw+T+j5Bs6K0Pa4jr7couo8A11Z2hrMI4JFrm7Wgdjzww/wDWbIZcaQKd7XBdoA01%20K1zIuQ7c4XlOG5lsh2/47PYfU3dtjfazkve/hVq2RNkNe8uSx8Xl+OxnRyCXkdzIp03xF8fqDHa7%20SS1dPGk6PNouthjKJDI9gaskaPbdyhq7QQBq5Cmtcs7i93xx4M2XTl4GzZdw3OLnRtCuLgQVuquN%201YE21TZMDx7zj8Pnzk/3BH7ALQDtdMduzaHHRt9a025epF4Kb3Q+SDbAR73tRiPaSGjROninhXbU%20yYw4HnuM4vFfLO3HyZWBMeB7FcxxQggnWlZNlJSVzmOQy+XyDJkPLsnIN1Clg+A0ppFFS7lyogyG%20CGUOMDnMe4EH0XrfZrzMbshzJI0uKOYRZzQo10Hl41v0LgY1YoJHuLWGVwa94a+6tBW4t0tU9KKr%20eXB2LB7x78iy/wDGZ+MZuFxoQ/GyjEWKIQXRs95o0LgeteVbtttPrX9zu2t1yTuJ9SsxrWt5LjiE%20LhJ7Q2lPybQ4poPwrjWylktMP4G2MfAmsbv3gcjeZnOhfsD3NcHD1kklrVH9J1VPwrO22uOPdp9f%20eNIlmcnx89oMpkjRtUtIIG4Wa0g6nXaP4LXJfYfLOPbPhH8eK0KVxTIidG0b2oNDbdrZEGhSuDd2%208zWtkNECEEgeo21C/A+K1wWq0bJmpPp3udtaquKgkCxVadU5hLGPiMJWlrehBHpI0Kqv3+Bq+mNc%20fqQIZq/oJz4sfsVSSEQHpSqvvRXAme2/8vm9q4sGJn4cET2EOheds7FJVSNCf2NfV0aSSfLGPqeX%20a2Y943tnE46OTMzHe/jxlGbW7Q5w9IAIVdEtqa0cWTS+DJlyUDvrk+U5/kiJMKSDBxDtx2PYojLb%20l5LR+Zel66Nva4nNuPhwKzFg4csmQ5k8+JNGC4NdGjXJYtBPjb7q1bx/Bk6zmsj0r9EC0/Tnjy1p%20aN81iir7rvC1eh2/9EZNJPIvlbCKB9WOLZnYcIDW+8GuEbyUIUj7ENcPd2hr2nV23E5j21mScfI/%20ByHNkK/23/8AMNbolcd1xOmr0Jrn+Bl5aBu6L28hnqimUKiaFfKpVmJlL43mOS7fyZMUtPse4mVG%208AXvoCOo0rV1bzQlbgxt3PBwD5G5PGF7d5BmhLTtBKAoVpUTKyItpJaGPeHAKGsAA1W6rVEwiD7k%20gidFjSMF9+y46uCX61tttkXRBy48rXxZGMA+SMkiMkIWOs77a0CvIRyHBwBeA1GEuC/Kt+ngtOqI%20uN4WvbiRgNbveGBdqKS82+HWhsFzLZh8dmZajHY15aBuJe1lhob/ALqzd0i2pH2H2vkZEmyeRuMd%2020xu9RJUXHTWs7bo1XhyL1g4nb2LhwxZLIffY2+QI1keAbBAoArF3cl9JGcp2zwubI5+JuZK42kb%20ZhKmxatOu7ZLMTpJHRR919tS72FrsZ1nNLGzQSIfzWN1U1qnW3mR0NMneMn+n3cIEPKce7j8+S4y%20ICWNc7QC/ndKhq1SySyvoRw+VGHYnKPbGQR6mhzSrlT7KFvtai6MyJk/7b8H1E8oxj0sWMJuqKVP%204033Iq08Cx9ocb3Z2Jxz+OZxjeT4wPL/AHoXgSNUgGyKQB41FrTmV0palr4/vrt/MkbFLI/ByCdp%20gyW7CvgDpUtFdLJ6HIilaDG4OaRuBBBBB61KbE0JzRRysdHJE10bm7Xx9HA2AI8KfXzGc47g4DN7%20fzByHFvkbjKS2SMH+2VTa7xrWtuolRXgWvtfvKHl4hDMkPIMHqYtnkWVpPjU2kIRPukdKdnyOTUi%206HwXxqbNrIEkaOwsOVyzQxyuFi57Q8qdbkULxAa5HbnDZjnOkw4XFw2koAbFLILJVyLQgOS+lvbO%20S13siTFc6zQw7mgdLGl1OAg5/wA79G+bwnum494yIR6hsO0i/wDSt6rqLV/cUfO43keMnc3Lx3QP%20Fnh7driB4014Gq3hP9dCrgrgrUIcA4JoCTbRbUdLRVdwRmc/SM6KgGlx4G9qtI0V1I3kc0SOBHRF%20XwulEZZAmNIWt97cU9Kkk6bTranZcBaHWvp1iPbwzpXEsfkS2/N6UCbUvo7T/hXJa0vHPGfnrqaV%20jUke/sxuP2vmNYfbly3CFhVWkIVQjUAdLfy12W8s+HunGOMXeWfDGOftOOPkjLfZUOJGhNvgfurr%20OS3IQPFscHENQ3DLDRfCr6mjldUyOy24cMgjyZPaaU2Egi5soRU1omQUjhuBC8D2ZQ4W8DYprQ3J%20onzLL9M8TJb9Re2j7qxM5CElvWx008r06PMLN9J7aroOI8/97dzY/JukwIoXx+zKd8sl920pZgH7%2068tLGOB2le4yWXBzosqOL33Rr/bcCh8FUagitG1ZYx8SdCxu78531tZxQcHFQ077eYO3y0rBbSK6%20jH+/e6pJCW8QAAQ5h9ZuhsBfVE8Kr0lpI1eDZ/dvd0/qZxrY2npHGS4nVfgKOivsCc4NHc73+5ge%203j3bXHc0+0hHwvS6KhI2yJvqFyTG+9hMlUA7nwByB2o3Emp6KoUlXzvpXyWfMcufhYo5LEkoxpXr%20rWi3enIfTJvj/SLl42uLceJoDQWje0A+TbX08KHviVBxF9MObTY447diL6y70/ZppUreRXSLxfS7%20lhJ/ezo4QqEAFzkAUaC60ev4E9A+xPpphtas/K7Xbtrtka+kmxBJvUveGtsc/wDtvxsjvRyD4gNp%20JeATtAUkAaJUrf0B7UeQ6f8ASjtOUMikzcmSV6FjmoEB8QKa32Hp8SmwxwYss2G2QOdiyPY6Mke5%207QJAc5CU8vKtKWkfTkX7tHkmZbGYcoYM2AbcVzrCWMG4tY7b+VYXqElshwm7HN9syQyH+438wIXT%20rUwCYx5Xgpfb3xh08biXAhgL2qpB1Vei0DrYpnI8UY2vkG18bGoGqUv6n+k3BJsLdK57Vn24+hvV%20ka33snOGHhRPysh70c1gLkf0e4/LtB8en2UdGc+f8Y5SJwl54+Q85fHMGTBxm4SHBD8vlXx/I/Lc%20EZEqaMaq+ddm3SMzC9m3Bz3ufkXzyexEffllXaLAqOq9PKuhZEalWlblB2wY73Tgkn0oh1Pl9tV0%20pGnVJo6CVm+Ld/6iVhL5v6WAKQPOknmTqmUg4BvsG7eVL3FQUuTfTWuxWMWzLMCbeQ0ABbqemtul%20vGp6hC0WBkucBt6W6HXw8B4UWaEXftvn+SwcN/H+/I/EkIMkT3qCW6a6J++sHtzmaVvCLHBzbJgW%20zPRS0biNVUaoKye2arcHTIuNyt+6GNAP+p4LcWUFbVm9riV6rRoeE49wY6Nz4H2LSpVNykhD91Z+%20izRbzk3j/wBy4b2fpuQMrWuWOJ5sUU3BuSi1judurKC1urkOIu7u6sRzXZeI2eNrSHW2KTq4ofEr%20+yVjudhVy3qaLdT8Bf8A3/x00MuLyGBPD7jA1zo/USXa2OwN8VBrnXYVpaVwx/PwLd3ZDjt7mO3c%20dzgzkHESFrR+oa5vipCaBqC5vV912/rRLxjHOa3tXUlJczC5DjcgYckU7yELGu9TnaqGrfo4AGvK%20v2dq7ngjZbmRH4kWS/HjJx3qiOkALiqJqAPCvoqaZ8jgbgvPZZxPbdkZ0zxCWluNjFwLEFnOLOha%20dL0nWskuSbn47DkkbjueydvtglsZDS9SnuElWr4XqlYzGmT2RgZM+RCXFohQsc4teNrvzE+lCrel%20VOQI6T2fxWNxfAwYeN/0WFxbdfmKm9er239Ecu7/AGJqtzMq/emXiwmFmRIxjXMeQHEKUsRtOute%20f32qOnt0ce7sy+BGVFNxpY95cPRHdE+FYUNs5xjwF8HvyAYO2WF5OhYqldQdxvUW2mvMauVjnuTi%205LPGWIhBIW7XEld4S1rpWlawh9REqSxqMcCB6A0FPSdAvhVC0GjsOQzueCXxlCIiisdre3lSdsgT%20GfJYc82LKx+3cQ5LIidb6GrrbMT0Kz+rGwjcW7VbI210sQVvat4ykzIzMnaWPcG2c3Y1VCNPl1FU%20icmOcSMS5kLAf7cKPkcAugRoPxSo4FcCfjG5zUaUGi2sLC401oAuHbWVj50YweQkc3JZbGyJDZB/%20U49QnWubcqbVekluijn40M/yEccsLj/12hCp03WNiB+wrmtZ8C08iVx4+NyAfbY14sOjQ5FIco6f%20jRD8iupEfyU3AQRPx5MlrXEf9KMkgoEQgkp9lWkyGloVDJ4zGyP/AOmwyvaflLgSwnpfXrW6ZPEk%20uJ5jujtyVrWl7YTrFN8paSPzBWj7qTqnmhqxfuE+oXGci1seV/6OYgAA6FxHTwBOgrF7cDTUlpif%20HIxr2uABTbtIIVEtqKmYASzeMws2IsysVmQ0gD1gbv8A4qpPwAgMjsqCCTfxeZLxsrgrmAl0SKAR%20r8KHfPMpWZpFL35x7klEXKxNBG5qNksboAnWiBNqBT/euOP7HL4M2ESUc1zS5hCKVIH4a0yWkyv8%20lwXEzh2d29lNlDCXuwmOIkYNC5pJJ860qJtok+2e93LHg8sqs9LcshbXTemnxpWWYMvAALQQdwRW%20lSQRqEqdFkAiJiXhpe1w6OT82njUyNGJMobC8PCNQuDh4+dhTlihIY5fO4OHGZMqZrQ1xbuYRuUe%20K6J+NCTF1FT5vvzgMgOgfhfr2+L2+n8Vd51aoxNooXKx9u8g4j/FDFc5UdA83K9ASmhUitVXUFYr%20uTwQv+n3bHk7Wn5m6oCpvrVAtzxI+fi+QidtCPZ5Wd1UXSnKNVujB0ORGC18Zjc3QaldBfoi2qW8%20jRbinM7f25hx4PCYTIGD3BG0lrSR6nKrtALuQBa4rf2xjGUZzp6koh++u2uc57Fii4qRjWROL5In%20EjeSE8kuNK02rw8yN28o57N2F3BhK/LwJLC0o9TfP1Dw+6u31UcaQmIMiN4Y/wBLgbBwWxPpsL0J%20p5g0JnGjkafdjbtcVAchb9vTzpiaYzk4HBeHiJpgkJCFhRwTw+KU5YiwfTbi8yL6h9tkZD5Ixnwv%20eSAVBOhAHlVVeaFaIeMfqe0K6TlKFk4vHjKef08Rsr0jaR1Pk4V5Fs7ODsEZcWIxt2xsY0o0ODGW%20Ur6gdNPCk78UODETJWxlCyGEeAuXGxO1eqW/fSzaGhdnuPaIwriz0Oe4jcCgIK2UUoGKIdrXMd8g%20QgFQdtgCiL46UpYnBrPJ/cLlU/K4J0N0J/Cmm8YxHIBtkicNL3NLmhJGNXawBOpqHaCkhDHmyA0T%20tawRn0ueXbiAqgAknr4UNhHIXY+Jx/vxkFXBjEVvpQ+rXqaTA2Yxjhua1kYiKuAHylouba3CUNDQ%20nOZmxuaxDcN2EpfVdo8vGjpQcRnkMwpEJi2OIcAGK1QqWTwqXVFJsYycdiQxNALtwcS8i5Lr3ups%20utJ5Z4x8Cq2kGxGzQ5zd6qWkhSCvqOoT+NHTjHvCSs9w9nYOTLJzMbTj5UMLhlZQ+WaNo9Qe1UUe%20Na1u1kTZJlV4fP8A0joy6QxRkriThA5vREP8a6NUZPwOl9ud8RzsEPKN9uUH/wCYYCWkKg8gVrC1%20WuAZF4iLXxCRjg5jkIcCLg36a0kITmgxCHSTxxkAet7w35R4k0NxqNMp3Ld44LGzYXbTIzO8pPyD%20GBsEZX1EED+7IL2FNeGSKjmc/wCc5OHDxTDApMble9xV7nuu97nWJcutbVqTEnO5OVjHIOyZI/fY%20qbXek+m6NP7LTDpJHuDvZ82KMfE9Ebo2gxkASkhtlIuW+dJVLSWpTZpXslDi/wD9S6zwqhrTYJ/z%20OrVVkm11wG4xWuv7e0EIQTe5vr++tlYyaFBhho2hoJKA9PMBDU9QdItHA7Xa5pCi4F1/bwokIFYB%20tISwKKDqg87Kq0NjJDGl8HBPzHVqfzsi1DUjkksfJWUFA4sJ8QnjUuQklYc8OeDbeLN3agEfuqen%20iORdkjGua73Cb+Nk1T4g0xyOmZRA9RVoBKk3TQWAW9EIJnHvNp2YWQDuaHi6L0ToTrU9CQuriRGV%20xvCFr55W+0l/SbkhQPGoe1wLrushzxDRkskwMiWNzXBzA1AQ4AIiIB4fwpdC4mq3WWfjuY5bDwtj%20cidhef7iyKrjdN3gg6fbQtvgR1Gpz3hyRZBIIO8eBJJ2HxFN1yzE9R5i9wcxjOVpUxhvoBJbsuWi%203TRUqVtpgdI4zlcmXDjla5hmlZukDUI3EIFRU0+FYXTRazOqdpSmXgoJCGgncPSEFinX4V6/Zudt%20M4d9RdkxXSYnHfr3jyTZfDhri1gZNuQkXJammtcvcao6NjRnLYmFrNihrFQEWJ8da5kjYW/Tl25P%20U4BQqDX5QNbolD+AlGpp+nDYkHyptU3sPippstLxMBN4BFiPjpZPKpASOM1jpPbA3EqR0IqQnPMb%20S45QgbtpIUgqbA9AnjTCSscx2sct5nxzsmcB7iWa4IgH8K1puRkzO9GQDu3+a/UB0wa1rDtYE3C+%20hrXqTJVHoiVwOLkiCNYBcbkHqJFv4VLfEqCZiwpmtAIAddSbqdFCVPUNcyT43ExpHbXxSzl3/Tjg%20T3CfsNkTpWbs5H0oumHgd35WOyDExG48MWkmS4OkIuGjcei2rFtFyansvmlfHPk7ZWkf2G/LrcA/%20L49aOpPgVA44ft3Dw3EcjxRin3EGRx3NIBKEuS2t6i1nqCLNhnj3w7GSe3ELNDWp/wDCidDTHpnA%20tlcJxuRGWueCS5S2T0tAOl/wt8TQshNyVDlez8eKQP45/reo9pwKILAFw8116Vor8Ak24rP7s4d4%20bIHsY4gGKQF7VCj0u8U60dKaE7pal34rvPi8otZlP/TZBJG0oWW81rLpjXMJkscDmPaCAAALIQR+%20FUreArGz2NTUjX9hUtiTEJ8eOSHZOkjUPzAIt70acSp5Fdzux+HnkMsIdiSqu6HVfHbpekr8HmGZ%20WuW7G5nHa+XFlbmY7AXOCo+wUFOpvWqumIzwHeL8CP8ATcmsmKB6ZSu+MgJcanbRak6Dhknm/UPg%203RkYa5BIuxNvWxQ2uvwpKmYmVjlO9OZyt/suEDTb06u8lGinpVrbgVvArOTmOmm3TF7nGxJKnzsK%200UImXxEv1RcxA4PRAHDUuB8/Gqby0FxNonFwsCC70hw1CC/363okIkC0SXIUEKXG2t00SnIYx7TG%204BoErS4OsAfD99KRwjUSySBzMVvtyIoaxoJJ8SAtS4GlGhN4/eHM4e2LPgbKGgtBezY9BaxI8Das%20bbSZorEzh/ULimjdLx743kDQqo1J/FanoEmS8X1O7Ubjhjd7VTcxwUXKL8aFRhA1yM/6f8uRI52O%2058g0c3Y9Qty4Dav+tD6kg6SLzOwO3c6H3OKzUcW3RzXtU3RVJv8AD760W6yekq2f2B3HiqY4hPEF%20JdGdSNLa1pXeTE6s37AxsiHv7gWzROiecyMFrmlpRb9POtqNNmd00metq7DkKHmzkZRcHAFFKkXK%20k3VK8e6+5+Z2KYGfuPeFd6nSu3N2hG7gFI8SSup60LNjHTmRtEYGgVrpGqocbJf+HxtRAMTML3R+%20tWuAALG2Zr83X4HxocMSYtiYpQXDWgNJDdDqm0WIslNr3gbNhihuxnrIVoBuFKoNPD8KUDEcyCR+%20PtlYJyNWA6hSA4edT0tAmQ7u3GNk9zElljQudHA6zBoXE38heog06yWhx8p+0vfdAGltwo6ly/j0%20ogXURE/FzQSb35s8qI6NouQAEItZPDxoiSpHByJiQ2RoLXhrQCEeb9EU3ppCkVbkj3Xsc15eQ0K7%20ppqFXyB++hpANDnwO2b8SZxKEPaWhAPxsvS1S0NDhzD7REUYYXlXbil/zEgn91ECnMQy8KOWF8Uw%20ErJBtcArSepFvGoKVjivdfBcl2xyH6uOYchxmS9XQyFodCNNoHh8K6du/BiaTHnEdxQFjjDkNc2z%20nQvN2EXOvStoRl0k5FzeNGyWPHy58UuO1px5XRk3UaLWbpIs0bOy/dhEeZn5OYx59wDMmL2NN7bQ%20b+dKu2kxtsj87ueCKFrRJsDHOLGNs0A2Vv8AKq6feNV5FC5rmZc56iYMa+0jnXuvXqL61Uj6faZ5%20PttmNjMnGdFFvYDseVBPVzTe1NWBrIgInwMlBiY6Rzl3y6KB0j69afUODAhaHveArnlbEkIb2X4e%20NUlBnxFWwS+YsgVFuFpyEG7WO3WQNF3EhbnW3woEKMJLVf8AC9xYeNAQbSxsG72wvUH4k6UpKjMx%20G0loKaG4Kr4/ilECQ4EkqDYdqjpYEWJNESwHEE2pcbgrbqNNyarSgWQ4dKMctDjtL2h4Q6i6Gyaf%20jTYSbR8gQ4erqPmb1JJIUhdaTCTB5pkRBnLY2oDuUoV0/b91OAIPl+Xz8jJGyZrIYwfb9QQj+m/W%201PpSzId+RnGyZmzo97mAKrWghrm6ELf7KXSHWTX6rJOOFlL4XK5SdPs18qXSaK8DqOSRjFhaQ0na%205ierQD1EffpSakOtjmOWVoa39Ox20EuAJAdY9P8AlqYLVzGPLlMa9zpJA78rFKpo46ol6h0WrRau%20ek/ow+V30/wTKVfvlCnUgPKLXoduvsRxbzmzLxWxkcy+sXbvNcvNxh47Dmy2xNk90RCwJLUW4rn3%206NxCNtqyUyc3f2D3wU28LkO1DSWgXSx1rB0tyNeuvgbQfT/vUtSTismxHq2I6/hel6dlwH6ifFC7%20vp/3m1yDishxsQdo628afpW5AtyvMSb9P+9D6jxGRu6gtF0suo8Knos+A+uvFm4+n/d5ADeJyQlw%20S3zSy6U/StnkHqV54x9DB+nnd7gjeKyCCD8zP338qXpW5B105mrfp33UZCZeFynNKmzR/PypelaN%20BrcrzFI/pz3ZkDazhpYWusXytRyfBfwpPauuA/UrzGWZ9Ju7IZdrOMnl0R0bQ5osiBSv401S8aEd%20deZp/wC3HeQY5o4XKdtvdlitim41Xp25YxjMOuvMVx+wO/8AGyGT4/E5MUzCNjg0WN0W9/8AhSe0%202tBrcrzLrx2H39lMZDkcXNiPaATKWjbYC+p9SGsf89+RS3a8x4/tXuWRji9k7n39LQG+Oi260lsX%205e/3D9WvMbw9r91Y7j/YyZWBUYjUVQFvu+z+VHo35PGMaN+pXmPm9udzZDQXwuijuQx0XqBIQ/Kl%20NbF50Jd68zI7H5HYC/FMpsDdzfInafj43qls7nJk+pU2Pb3LQsIZgTM27WsAR/l+4fZSezdLQa3F%20zNh23zb4va9mR0TjvdFJEEuDYFVH7LT9K/IXVXmit8h2R3BHkuMHFzOY5E2NBsEXqg1rVbVmtCXu%20JcTGNwv1Hwfc/T4+VtLSImbGuQDqpJv+yVD7dvgUt9cSQwX/AFLhm/8AUcZNkRFFDowCLlULT4D9%201Q+2suZS3qNFowoeUniWXj8iB5u9r2L6k1Ums/8APfkU9yvMRzG8vDbG4vJlcPlOxBdqgHTwS9Uu%203vyD1a8yqcp/7mTenE4ieKM3XaN323/5v2vVrt7ToD3qldd2Z3y+V7puHyXOXc4hoIJ+CotbLabS%20yM/UqnwNH/T3u17if8NkjaUUNAP76XRZZwLrroYk7C7zUkcPkXCBGIdFKqfOq6LcsY/UHevMQf8A%20TbvHdbh8mwJJAAVLeNL07cg9RcxM/TfvgtLf8RkABo22F0XW/wC69Nbb5YyJ61zMj6d97KQ3h8ot%20XaGuagIFlJW1qXRfkHWuYo36d94FxceGymuIUgNBBsvj0oe3YavUTd9Nu9mNJZxOSSAjhtF//Dc0%20enbkHqVF+I7L7147JEru3cqYgWcAARfTVKT2rMfXXmY5Xs3v7k8ozzcJltBKBiNTwXW2tTXasuA3%20evMZH6cd8bt3+FyiALNDbqBqpNadFuRPXXma/wDtv31ZeEyTt+UbBt1GoUGhUtyH6teZkfTbvRzQ%20H8HlOQ3VjVKfApR0W5B6teZoPpt37GNsPEZjQLNQbUBt0Io9J8g9WpIYfbn1bwiTDx+XIFJ2Ssa4%20fYrqj/PPAr1qzmWztOPvs87x/wDlu2Xsj95nuZm1gEbQfmKqaKdu1ZZCvuVaeZ2mvROIo+VC05Di%20ANzkJ3Cyh2h01/bwPkO0N8MY5fp1pCTfajeRIo3W3gBblV3eR8qU5R8MY8QRg+twEbtzQD6iD8Tp%208ypTWvjj3BxN/wBKwPuwlV2klFKkjRboP26CiB8TeNs7f+q4veUBLQgIOpK/sKVtAzN2ix2hNQCF%20cQSgKjrfr+NPWce7wFHMyENr7Snp1B6qCdKSccBqTX+4p3NDSBqCFJTQj4edJw9XoNGs5kD2Rsj3%20Agq9fSzaLfetZjZruc0sjneXPlc472j0o3Vp8kGtHUuJQjIfZi3RQKIipkcRqq7bqftoVgQ0MOXJ%20EZ5Zg2I2DGkuIXxKHytTkIY2bh5jZtPksW7tC47QFSxpdQ3BrM6SOIlh3CM+ouaQ5ruuvWiQa8Bm%20Ocy2b2yOY6JjiEAcxzlaibvIhfspTkEIVETeUjaJMOOR+zcwyMDmt3D1Ek6LQ2hwc2576JcfmZkk%20/HcpLg8lIssUEzVgAbbYo2+Fa03oUcBOs8Cl8j279R+Cf/fwJMuKNQ2WFu9pbq14HQJW1dyr1Bpr%20MicXuDkp/dhfHLHJ80kcrXNLSq6mqaROSygRZyWNPLE3IyPb3OQPdfZvsttKlpjnIzy+PHx2Q+Ju%20bEY9oLCXgnaR6bBbdKqtW+AmyHOZHkPDS980YCNa70tuLBCdE8KrpYPcH0OLNKHNYR/zKURQg+FC%20jUhvmPI8SdjiHMcHNKEaISTY28taVrDUizccuajmooHmPFVBpdRSxjH67uxgNCFuTqq62+FEoUeB%20qMR6qECCx+FxcIb/ALdKH4hBgs2i4KhVPkCP4UJhAkWuc0IUJUAnq4+OvUdaomTeM+20brlQvkCK%20aYeJsZBdrru63au7S1ulMDQOkDZNpBjT1FqJYClAogb5WY6GL3LPYLm6G96aDPQi+U5AvgDTHtbJ%206myEhq+Pw8KpIztmIYUBldtdI1oUB5LgvqCEgHw8KRLHkZmcHNL1mjA9u6IDZUHl40DeQ7jzG40Z%20dJJsLTtevhQMl8bksWd+12Y1sx1ZcqSB6lFunjUjkloHtlbtjkDo/lLw4blXqB0ogbYt7ntBrJZ3%20RuX1SDSxtpQlI2ek/o3uHYOCHJuD5VTT/qGurajpyMLvMu1aEBQAUAFABQAUAFABQAUAFABQAUAF%20ABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFACDsDC%20cu6BhW6FoqPTryH1MweOwSqwMK2PpFxR6deSG7M3bh4rfliaPgE6J/GmqVXAXU4gP0uN/wDkmf8A%20wijoXIOpg7FxnBHRNN10Gpo6EHUzAwsMaQs/+EVPpV5D6mZ/SYqAeyy1h6RVdFeQdTMHDxSVMTCf%20gKT26vVArMz+jxUA9liAqAg1o9OvIOt8zU4OGQhhZ9wpelXkg63zMjCxAEELEH/KKPSryQdb5mrO%20PwWNDWY8bWiwAaABR6VOSDrfM2/RYf8A+RZf/lFHo05IOt8wOFhlFhZb/lFHo05IOt8xH/DcSgH6%20OFBoNjf5UelXkh9b5irOPwWBGY8bRqgaAP3UelXkLrfMHcfguIJgjJGh2iy0ejTkg63zNhiYoBAh%20YAQh9IuKFtVXBB1PmMZ+1+3MiV003GYskrwjnuhY4keain6VeSDqfMZO+n3Yrgju3+PPxxovh/TT%206FyDqfM1H047ABUdu8cp6/pYl/8A0afShSzYfT7sUKnb/HhUVMaLp/5aIQKzFm9ldoNCN4XCaOgE%20EYT4IKXSglmzuzu1HLu4fDK//mI/BPCjoryCWH+ze0r/AP0fDuVP9iP+VHQuQSzH+yu0UI/w2Hf/%20APMR+Xl5UuivJBLD/ZnaSbf8Ph7RYD2I/BPCj068h9TMHsns8/8A9lwrlSkEYv8AdTdK8hJtB/sn%20s/cXf4XC3Hr7EfX7KOhcg6nzAdk9ngIOFwgNEEEfgnh4UdKCWYPY/Zp14TCK6n2I1/dS9OvIOpmD%202L2YSv8AhMJf/wBxH/Kn0LkCs0Y/2F2T/wD4HA1X/wCWi1Ov5etHSuQdT5mn/t52Iqjt/jwfEY0X%20gn9NOEIP/b3sWx/2/wAeo0P6aLy8W+VEIE4Nz2H2USSeCwVOp/Tx3sB4eVJ0T4DTaMf7B7I9X/0H%20A9fz/wDp4r2Av6b6UdC5BLNR9PexAEHb/HgGxTGiCr4+mnCELM7K7RjaGx8NhtaFAAgjCKE8KXQu%20Q+pmz+ze03t2u4fDLfD2I0+5KbSYJwSWHg4eFjtxsOBmPAxdsUbQ1oW5sKYhagAoAKACgAoAKACg%20AoAKACgAoAKACgAoAKACgAoAKACgBtn8nxvHQibkMuHDhc4MbJPI2JpcbhoLyAtqAK33t3tPxXZe%20d3L21Djc+OP/ALk8Mc/pdEy8oY+ISrI1pUNoYIme1u4+O7l7ewOd45xdh8hCyeIFNzd4Xa9CUc3Q%20igCUoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA%20KACgAoAKACgAoAKACgBpFzHEzZ0mBDm48mfFeXEZKx0zE/qjB3DXqKAFMnPwMWSGPJyYoJMh3t47%20JHtY6R/9LA4jcfIUAL63FABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUA%20FABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFAHnb/uhyO33dx9rYPJQNycqRk8uJFn5n6XiFYQHH%20Ma1JFQkNc1zb2XpQNIiP+2aQx9w/UPEgOJDiR40EkOLxU758Bj3MeHOx3ve9xXaFK626ChMLaIuP%20/aG7mT9Kg3LihZxrcuf/ABckZWR7S8+6ZQpRJFDfKktB21O30yQoAKACgAoAKACgAoAKACgAoAKA%20CgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAPIUeP3nm/9y/d%20vH9mzY3Hc1JOZn8tkAv9rGiYwyRBh9JEznM3endaxF1Q+CLZ3dz/ADPf/wBIs7nn40ON399PeUkl%20yXwuLYcaXCl3Suh3l7JVhYCjlvTkDvnanP4fcPbfG83huc/F5DHZPE57djiHDq3pQIlaACgAoAKA%20CgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAK%20ACgAoAhe4eyu0e43wyc9w+Jyj8YObA7KhZKWBxBcGlwKKgoFBW+5PppDi9q8pxn09wuP7d5TmGsx%208jOijOOWQqdzwYAHF7Q47RpQkBN/T7sXiex+1MPtzi3SSY2KC580pV8krzukeejdziqCwoGWOgAo%20AKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgA%20oAKACgAoAKAPP3L/AEO+q2N9Uef737S57jcCTlxJHH+obI+RkUrWAhPbc0OWMIRQgnKBj3z9O8rs%20r6RN7J4XPy+S727zz43ZUkZkLs2azsu+jIWx/MXm4+bU0LIc5ne+1uAwe3u3OO4TBjMWJx+OyCKN%20zi8gNF1cdb0CJSgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKA%20CgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAK%20ACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgBKX9J78Pu+3+o9X6fdt3qnq2%20Lf5dUoAVoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA//9k=" height="247" width="665" overflow="visible"> </image>
          </svg>
        </div>
      </div>
      <div class="fig"><span class="labelfig">FIGURA 1.&nbsp; </span><span class="textfig">Sonda Toma muestra (a) y cesto (b) acoplados al tractor YUM-6.</span></div>
      <div id="f5" class="fig">
        <div class="zoom">
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yOeF89q9xku7BpdC0DTa8VqHNANeyDpmEzuHzePjyOHvI76wkG2O4h+lxpUa6dnKU%20NmzdShNafBBXd5ttD80FUFHNDqV7ahBQRgDUkkigJ1KgNg1oTrr2Op6Hp2U0FsmTaNCQKE7gOnX9%204VZqAdISBQFvRwp/BTNRhZzM4zC2M2Qyd1HZ2MEbnzXEjqbWilT4lJqUQ2+9xspk4WDiGOkn30P3%20t8wxwBjhVjma6169Fw99/sW022k3Vu9mS3FdLTZLCQ39uDzTKyZEQkP+3BEcEbm7Xbg0UcaeP714%20ref7TvM00xUiPZsW4YjVpJeV4PMY+TBcSxkmXhq7fHYglkR2lu5zyWkOa6mizeO8Nvcl3fdWLo9S%206+2IaTkOI5jisLdt5xmX4yD7NzsHJabdZY26QzuoauDelF6/b+A29kzfdbW5g+pd0c0xVpbNtobm%20JjfuJmtdLO6jnuefzE/4q+C5e4yzWbY5QtSFu+45gsjKJLq33yg7myNc7fUnp11rWuinFvMtkUid%20CbGotcXY2nKJ7WzL7a4ngMzbhpJNR2OnRdHLmm7DEz82p26t1BeyMabbItbC6YOax1f5UrCS0ivi%20VzZxxPzWa0/BMSysPIzBAWjrEZLjUz2zXGIko8Qy1H+YhrtO5o7V7Kb75zTXu7cvS71j0lWZo6Xx%20jkUmKMuR9u5zksIXVy+OeN0ls+m8+Qag7RtrSiybTyt+3u7Nz8tf2z0njmrdryds4vzHA8ltvWxd%20x6kjA19xCaiRhNNHA/uXqceS2+KxLG3bQAKONHO+Xc/H+KtyKqlwrUnygVI/3qR5JkDhpXs2v7ta%20fvVai6OisCAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgoWtNa90H%20ieGCWJ8MrGvjlBa+N2ocD1BRCH3WFyvHbn7vjce/FbS++xW+hBbqXQ7t1CW9giW9wfIMZm7L7ywl%209SNuj4yKOY6lC13cFKjaxijaVqg9ICAgIKONOvT/AGILYBJ7ONK+YdzrpXoopIiPuL7n8b4Kyxdm%20nTNkyj3Q2LIWb90raeVx/KPP1UX3Uj4FEA5zk/cq/wALfTty1ti7NsEnqWrI2zhzSKkOlH00b4Lz%20F3+0Y/rRji2dWeMM9UT9nuY4PjfJ5ZstK+OCfFQMjkYHStBaRUOI7nrqvTX322zFZpVink7Bnfa3%202/5Jinyw2MNuXs9aK5tP5QLy3cDIyMjf4kOV7bqq+6E+xHNL3OcjyePEIsrHGQmL0IWsZDJIx/pm%20XawbQSGhQO5trtFTX4qRUgHQ/uQUc7aK0J+SCjpY2gkuoG1qfCn/ABQW98MvmY9r29CQQelDRKCJ%20e5nuBa8G4+crPay3cspdHbxxH8+2rS6vbpUqPcfNX/s33xuLl2Qk5PDbSNNLWzELNjw7zAFpb11A%20NVzs3kbbJiKVWi10W097+Tct9DAYYxcdz8QaMheXlJIpXFtHm3AAr4tUbvyluHD9Sl12lU22apFf%204nj1oA/kNzNlJ4wXTG6kd6dWjc4CMu2bXFtdpXzjJ5zyG6upZdMR6R/JtfTthrMbzfKcpD7Tg+Mk%20uY7dxjfNLS3giaCCB5hQ6eC3tp/qefLPdln9VZy2w3eB9nr69c6bm+WdlHOoYLO3LoWRV8z2vc3a%20XVXtdn4Xa4Y0tirBdkmZdAwHG8Bx+2NrhMbDj7d7i57YIw3cT3cQKnoutpDHNZav3Msba74HnPvI%20Y5tlnM6J0jWu2O2nzN3dD+KRUh8fYa8kscTj7fKChlY0W07da1HcDp2+C8xucUX33TZ05s1tzeAG%20lRoWdRoCNddO651WSrQcinns8vi7q3a1rX7o5HinSugOgP5l0dlS+y+27opLd3Frbyt2Ts3MDvL1%20NHU8R4rQsvujW1LU3WZiwM8EGQkkmgu6CCVjdxBBALT1PfQrbs2/14mbIpNvNWZpzbFrsxZTC/4z%20kf07IO2iVzR/KmYKOEcrBXWvc9lji+y+OzPb3WflPrC2nRO+LZuDkN7K/iDpMDyqzAlzFi522GeQ%20Hzek40Y5u7sB07Klm4zbLW67uwz+3rT4o7Ynk7Fw73VxWcP6dfRyWOUjAjf6raMkkBo7YRQdRWi9%20Pg3uPJGk6sXbKcBsjK/HX4darbiJVe2uLgdzaAjw6+KRNR7UhVAQEBAQEBAQEBAQEBAQEBAQEBAQ%20EBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEDQ/FBQkMbWmg7BJkQvlHE8i7I2ea41cNsLqxmdc5Kzh%20btbkG7aiGQjvXvRBtuN8rxnIrd0lsH288RAuLWYbJWE6EFppXwqg3cZq6oPXqD/uTmLlRStdOtUB%20AQKBB4FKOJaaeB79uiQOCf1WwNnZxWJ9Qx11PV4ANPI3pVa26u7bJla3m49YXvLOONnFhkX3eOum%20bZ8dKS5ji6tTXX8ui85ddt88x32RF0dWW2vRMeD+6PALJr7KXBPwVxM4ML5AJI5HHyksc76W/wBi%205nlvF7zLS63J32x0rSi9s2+jon6NHdRtvOK5iXG7N75jYOE0crm1JZI0nuR+WhXN2Pn91tbuzJE3%20RMxz0+5a7HbMOZexHMrfj3J83d3trLe/ch4lfaje9u2VznVYfMevb5r6PO7stiO6aVatJfUOHzeH%20y9uJcbdxXDWgOe2NwL21b0eBQgjpqti26J5aqzDPZu3eby61FdaU0pXp0SB7eNtDQmlamtOqmRq+%20SZX9KwV7kGxCf7aF8npV67GE9j001UzJEPix2ZzNg777IZe6+2ycu8MjnfC2B0x3BgFakN3darjZ%20NxfkupZNKMtIjm8ch5hyyx4k7F/f/rmGnuPUivLl5dLaveKFod4EeK2cGa7J8t+l0dOdVKJPg/av%20G8kxdtm+HZsyZmxjEt5jL5pdHIdpd6bO+rht3Lh5/Nztsvblx/47p0mGTsr1c2Fjl8tYXwv5BZZb%20D3JkBkq2ZlXEOaxrtp2M+fQLu/WxxSLYrbf1jkpMPrngntJx2fG2eUzOQk5Q6eGKVhuCDDG4t3kt%20aDVwJP5lfD4/DjmttsQib5nR1C0gt4GenBDHBGAKMjAAoBQfSBoBotxVeogqgjHuEC7gvIC5oB+y%20l0IP+E+HyVaph8jY+GKbB2Ynax7XQADdQkOcKVqQBX/YvH5bptyzSerLaY4ZGOSWC+LZImGlrKDV%207mh1AHDx+StuJtmIm3SVmu5xaT3OGY6KT0zBM1xJ0FP9oW34y+Lb6T1RfybyB8UtpBJUSAxsJcOp%200B10HSi0Mtk2XUTEtDzKa8tIMdd2lY7uG7j/AJwAJa2tR1XQ8TfEXzHSiuSYl9Bc19mJMlaWef4m%20Ybe5dbNkyOPA2suHFm4yMDdBIT2Oi6u92Nub2n1YomYcUliivC5oMlrf2wIbMN0c8EjTStNHVB1o%20V5+6L8N1Lv215erJSqb4D3Wh9Gz47z63bKJiyHH52MAuMgFBLMT/ANt/Q7uniudk8RdbdOfaXdtN%20Zt/GkMnd0l16x5bl+M/b2maLsrjLlzY7TJwN3GNlPquD020/MF2PD/7Ji3H+O75b49essd+KkV6J%20+14lY2aF4khkG5rmmoLTqCD0Xp5Yl2tCQa9aDrr8kiQDBu1Oo0GutOuqUBpG7QmnYHxqapUe1IIC%20AgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICDxJU6Cvjp80HtAQeXt3Fp7t1BQUj%20rUlwo4/2BTI9qB5ZG1n06DXT5oI7ybiFnmZLe7hlkscpZkyWt1CQBuBrSVv52V7FKoQO89/7bDch%20ZxzM4xxyf1Pnt5GOidEHBpl69Na7eqJdHwnJsFmrczYy9iniY703dWkE0NKOoUqNkaU2tNW9gf7A%20laC6zdrX6fy+P4pI9dxp+KC2HmlD5iK129eyio4t/Urx7PZKDjt3jLCS8t8fNNJe+iKujaWtAdQa%20nX4LX3OPusmITDi7ZmSl3pv1b9bdWkHStWnUa/NeTvxTZNJhmhSe1trppbcRtc3Xa5zauaQO3xIP%20grY9xdj/AGpq1tlY5fBSG447ezRPdQS27nO2O13VdQ0J/s+S2p3NmWKZrY+5HbPTRLOM+6dhjsjJ%20Nn+OstLi4e1sV7bABsdKbnSAD466rS33jJz2UxZNI9Vrbqc05zmY4DkLeG8t8wY7uMmW0/SnGOWZ%207gHNZIxgo7Xs6i43j58ht76RExb17teP0WyTbOqS+y/urmOUXGTx2XgZBFjdjba4lPpSk/T6crHA%20efvVui+j4cs3Wxyn3jk1Zh1cO3Dztp3B8daLY0lVoPcQRjhuU12j7eU1FP8AAelSFS+NE0q+Mstx%20uHOYOygdIYZIY2OY4a1Jb0Pz8V5zFufoZbutWbtq02D4zyXEPkt4w24s7xvp3LZBVjWEeYivRw8R%20/vXQy7rDfOvOFItmG34ZfTS2rWRSG0u8S9rbZ0bi2Tya+ZtdRp+K0vJWzExM/Nbd+q9l/wBjp+Rl%204p7owDGcpaOP5u3rHjsnDJRs/qtod2gqHU6OK4eH62w+fDP1Mc/ut/409GS6IlNfb73EveIW9rxP%20lmJOJtbIttLLKudWKcMGwSkAeXdSq9dsfKYdzbE2z0+5r3Y5h2q2khkG+F4fG8bmOaQWkEVBBC6K%20q+gII37ihv8AobPA+UOspQX/ADbTXUJRMPjo5KPE4Czl9N87mRAMiBFXEDQE9l5GMM5c10Vpqyxp%20C7g89a5UXAjY6OW3oLiB9DtIBGhHXuFO82s4qe606sjJWEV5YTW0jjtewkOZ0rQ0/iFi291L4mEy%200Pt9jsq3EXWUEcj8VFObYvAMm17fMKgA6ebt+K6nlLrZpbP7qMdusN5fW/3uLuYYnAMkjNXfVSpH%20Y9Fzdvf2Xx7LXRXm+if6d8xZX3t5CLK6+6+1lMM7jWjXAU0qvXVowNv7h+02E5m2Gb1DjslbF0kV%20zC0Ukc4dJRpuFevdY823tvikkS+cczhsnibyfF5ywdbvc98THytoy4aKtJYehbrp3Xmtxtb8F0TH%20JnsvroyOJc7znBYTaOikz/H7l49WCZxdLaxCjf5ZNdzdvRq0N743Fvvmifp5Y9P7p914mbfg7HgM%206MNaSZfiMx5Fi72RpmxrJRI+3LvNVhG5zWsH5KLJ4vzeXBP0t3FNP3T1p/FS6yvJ0vEZ/G5m29bH%20zsnIp6zWHzxuI1a4dQRVezty23cprDBSjYiobQ9D16179lapR7AaDUaV7f3/AMVMQPSAgICAgICA%20gICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgIPLutNenQdeqD0gIBIHU0QEBAPQoNBm+X8c%20xA9PI38cU0jXNawVkeKA6lsdXUNNFjuy2207ppUl8m+1PGMFyX3AujkreS+hubq8LCXybwz1C5rm%20kGooKK0ZIJh0XmXt9zTjV9F9hcyZTDEVs7h1IpoJOux72fkAb1cP71ZPNt/bz3V5LZ2zbfm17ai5%20fc/bG3NGviY4lsDmFtRKH7fh4pX70O4xjcCa6GhaR1I7E06qKD20P6uPboFIp6TKg+CigqGgdCQp%20HPuY+y3C+SzPvHW77XKAOdDdW7hGC8g03tAoRVYsuG2/mmJccz/s37kYQR+jAeQRFpL5oKMla7o1%20oYSa9OtVy8vi7Y1sXjIhss4tpmwXsbrG6d1huWmIuPQ/V9XYLlZtnlt5wyd8UXHtDonRvZ6jZBtL%20HdCOuui1bbpiaxKZiGsx+EixEhuMPO60eJBcNiID2OkaRtGo3AVC3r9/dktm2+KxMU+/mr2UTK05%203Z59mz3Ashhru0cH2V/jgdpcAKyPDHD82oB7LTs207WK7S7ur0unjiif3c3S8d7j8ijtPvcBfWnN%20Ma0gSsB9KeLSuhYHVo0dwt3a+fvtv7N1Z9O7pKs49NG/5N7h8dyPC8i114LK9+2krBcfyXF3pOq1%20m7R1CvQY9xjyxPbMXUYpij5usB/461P/APUwingGjReVzfvmnqzxMsvcQaNpsHUddCTXQ99P20WC%20kTzSg1vjruPkeS9aZsUznevZx9N+opqOldO69FddE4raRWGKmuqQW2ViuA60ykYtbgECj/8AFUBx%20FdAWkdfiuZftZtmuOe6GSL5h0fAe480UDcFyy3jyWEkY23F05lZLeEtDDvJ+rSmo1XD3Xjovu+pi%20nsyR0/5dV6+2iV4nI5v24bBLgXScl4Rd0MkYd6k9lVvlMZqXPj29WnUfvXd8V/sUX3Tj3FLMkfZX%20j7mK7FNNHXeO8pwfIrEXmFvo72BhDJiw1cx3drx1Dl6mrC2rXbwdrjXUU7afJK1Ee9wg4cCz3b/J%20S01p+X9uiiI0KPkXHW7XYa1imaJA+BgcDQnaaUr8R815C/JNuWZj1Z7Y6PGLwWOxdxPcWof61zrO%209x3V1roB418Ez7u/LFLui1Ihs4gAXtf1P1dwR3+a15mk1glq/b/nPMuF32RxtjjIL3ESTfcz2Uw/%20mlryG+pE4nafK3oun5PZ7fc47Zvu7buk8fz0+Klt0xydPu8BxDnNpLnOB3UQyLRTJY+pY0bmlxaW%200bsfWor0K83Zn3G1vizdR8n9t0R+rNSJjRsv6UmX2Ig5Jxq9x0thd284uaTAtcQ/Sg7EDsV9C2u4%20tyWRdbdF0ezVuh30Rg1DqhvYdqdFmjVVqeU8WwfKMe7HZeD1YiSI3N0cxxH1Nd2IUzbF0UnkRo+b%20+be3PI+I3LvXiffYLzGHIMaHFjGjpPTpp1K8/uvGXWfNjZbMiLYPK53iF7Nl+ICIS3QH31jNV8Fw%20BUhw1BD9dCuduMePdWxj3FdOUxzj+S8aTo7LxPl2M5I+TKcWumY3k0UIbf42RopIfqptFN1S36x0%20XMw7vceKu+f5sN3Xj8kzbF3xdI4vy9mXBsr2P7DLxay2clRuH+Nh/MKr3Gz3+Hc292O6LoYLrZhI%20WF461Ap5e/4kLbiqq4CCQakU0IrXt0KtSoAOaKudp+bX4U8FED011dK1NAT+KkVQEBAQEBAQEBAQ%20EBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAIB6iqDxsa2gBo6hDSkyKtPWmoHevfwQa3kF9d%202mHvLuFo/kQSyO8aNYSC3XsokfJfDvdy7xBkuuTYk3L7xpEN9BV08u7/ABveXU/xUFF5jyvj8u5u%20tnHkpMdJ5fd/P8WWy6jV+3d5B/qG4vvvbnG2TZp558mAWPYZjURUIJNOp00K6O43F2HFEWa5NI4/%20j1TERL6BwnuFmofWt8k6DP42RgDDbkNnax4p/OaRQhwH4rW2/nbe3/NbdZKJx+j5/wDcS3xMnuZZ%20XODs3wYt13aB8FwHNkjkMrq7Q5zhtAIpT+xduzJbkjutn5WOkvtVhOxutBsGulfmssclVY3PJJ6k%20U0PTVVhK6rAgtOaDoeoOhGmvbrVKlHsmoBH00qDr/cgjXMvbjh3MmQjkOOju5bUH7WYkh8ZcOrXC%20ndRNsToOKZr+n7m1i+Z+DvI8tZlx9GC6c1sjGVrRrwAPADQrmZ/GY7o+XSV4vogeWtMjhrmO0ztp%20Ni7qc/yYbobfU+MdPqFRSq4+XZZMcaxWGWL4eaeXY7Xc3zM7OBH8VpVmE9zGxlvLh5JLjA3M2FuJ%20GubI62I2uc7/ABNJcDr21Wxkz99IviMke6KM6/5hf5Lj11Zc/tjfzxefE39g1u5hDaUkGvXqSow7%20O2zJF22u7Yn90XfnCKzTVg2QcLK2L6EiKMmg/wCT8P8Aiq5/3Sler5hU1cDtaT0JrWvZYqLIvyMw%20Y7P4y+O577k+kGjr5nA0HX4LsbW+cuK62f7WOdG/yWKsr4k3AIlApHICRT81SO7dOi52HcX4+XJa%20jVwZe9xr222VAfDJRkMjaUIGhNPAimhW5ftbcsd2Pmiqa8P5jl+KStfjCLzEzEG8s3UppSro3djT%20suLu9lj3MUyfLf0uXtuomtkyQmbkns5Pb292Zq8gxEraQznWQ1aRVsutAQr7DzOfYXfT3lZsu/bd%20z5Ivsi79rqnBvcbC8oluLKGKSwztkAb/ABd00sma12m9v+Jhd0cvbYMtmS3usnutnq15iY5s33CL%20jwPPD832U3z1b8C3+1ZrkQ+ScWHDFWe7tE2tOneuo8F4vP8A+Sfiz2sjWn7q/tqsS8yUGulRWv8A%20E66/MqUWtBlMhb4jk9tf3s/pWs9sYW9T5mu/OK9F1sOP6uGbYj5oljnSUiwuRv8AjuU/XOPiCK9l%20o269Qn05oupNARqdKf8AFc+/tyW/Sy62Ms3fe65iOc8f5RkWR4++mxHLoIQ6MPb6frNGoZUikke7%20Qrk22bvxc9+L58F3PrSn5aJmIv8AaXRMHzuF8sGNzw/TswQGtEgpFcPFA4wu6EV6L2/j/KYd3Z3Y%207uXP2q17rJhKjtDQWtoa0La618F0K6KPE0cVzbSW87BNBK10crHdCxwoa/DqFNfUcF9w/ZS7xT48%20hw+0ku8e7d91j91Xxkk0MVfyAdlyt542L9bIpcvbe5K0vuJxksTfS2mVtQ6Fl5CaPZQ19J9a+XcN%20VxpumytmW2tvpLNXu6uh8T9yLLOm3xnPJ2YvkkT6YjI29WMlrQUDqlu8uodp0XKybHNs7vq7Gs45%20/dE8/wCie6ulzruJ53c4pzbHl5Fs8vEFrkgCYrh1TtrQDa5zafCq9V43zmHc20ifnilY9/b1Ybsc%20wmxJJqKiuh08SuzE1YlwebcKkHStOyc0vYpTQU+CkEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBA%20QEBAQEBAQEBAQEBAQEFC6hA8UFPyaN0/w0FUgablI3cXzG0VJs5gKafkd0qo1IfGuIucffYa2iBb%20JsiDHscBUEVqKH59l5PdxfZlmdWWz1VuMJJHJ6mNuHWM28OIrvYaEddSNKLJbvul0VWp6Nvh+X2m%20KYWcvxL78vmbcW95ayekQ9oHlcARXRularHm212aP8V3bSKax0JiI5wzrjCS+4+fnyXHbqB1lHLA%2065Zcj0JWBjifINBoNEw7+PG7b6eWJm+eVNeP6r07nbMbf8twFw9sErs5YvaB9rcy+nJEWkaskf1D%20ugHitDx3+4W6xnr7THHRW7BrokOB9y+O5TKPxZE1hlIx57W4YW1O7aQxx0dqOoXstru8Wa3uxzWG%20CYmEsEkvQjWvcePyWzEoeg8VFCaft2SZFWUOoHl7Hvrqpge0Cg8P2CDyWA9CW/LRRMDV53ifHM9E%20yPM4+G+9MFsbpmBzm167T1CTbE8xyjl39O+7bNxK8baULzJZXJdJG5p+lrCa7NVpZ9hjvjSIiV7b%205hyPl2IzfDpYo+S2L7MT+WCeOk8R3GhLiz6QK91x8niskdV4uiWnys0UuLnfDICwjRzetdp8tR1+%20a1MFvbkpdCZZNmCbG2FdfQZoNNaCmlPGldNVXP8AvmnqtbC6elKjx76/tSqwwmYaDmcL342O4bGJ%20ZbaT1GbdC0tB1J7Lo+OuiLu2eVzHfbDe27hJbxSEkOmY0uc0aVLQPLQdFo5LZi6i0TWWm5PBjnz4%20u+yUb5bG0uGuuYGnV8e9ocNPHt8F0/E3UumI6q5LYo6h7i+yOXxMdryX27gMmGnt2yXuElkIexrx%20vD2GQkCjXUoF2M+yx5ecasUTTWqAcX5bdyvkvuMXb7C/gIF01w0LezHs7jtuXmt7srbZ7MtvfZPJ%20sW5KcnWbW+xPuIXCB83HebY5gfDeRP2F7aeQ1Yf5kZefoNVxceXP4ye+ye/Bdzj046LXW93xbHKe%205eSx3FMzxj3ALLbPSY+R9jfRAOgu2AbKjbt2P3CpafFe38b5XDvLJuxzy5te6ybZcWxuuMtA5vpu%20ELTtPY06k/BeezxPfdPvLNbNIZRBdWg8QR+B/sr+xWKJjqKEjR3WpqPHzfvp+1ETCL8+ZZMt8fd3%20Mfqsjm9MQ0qHB2pND/eur4q6a3Wwx3Ryba3x9xjnF2OcZLCZoldaSOq9u6hq1zvl0WvlvtyaXR88%20dSLdVxjbLLRMuITJDPCaR3DKslieBUFp0J2nVVrkwzMc7evpMLV0dO4H7gxZaKLAc6ax97EGR4zK%20NBBld0Em5msb6EfHuuTufHXWXfV2U9lKzdHJasTzTnCe5t3x/IuwfLHPfEXtZi8kwAtkjH07i2pO%20lPN+9et8f5O3PZFf3U146MF9kxPs6qC2Rgk0ewirHDuDr+4rrqKktDSQKtcBUEdlFYHLPcr2Vts8%20xl9xZttiMs1+66qwtjnadSHNb5Q41+qi1NztLc0RXmmJmHAcvif85Li8zY+lfW9XCOQ6gAkCWF3x%202fNefvxZdtOnVmi6qQcZ91b7Awfp/PWOzeCeWxY67Yxr5Yakj+dXzu+oUfX+5c7ceJjPPftZ+nk/%20ujpPw9FovppLsuHz+a45E++mndnOLTME1rIw1ltYAKg+YbpAWlb3iv8AZrbp+jnibclunxlGTFEa%20xLolpe2t3axXNvL68MrQ6KRncEbh+NOy9bo11/eeho0kH9/8PmrSiDzmgBPQ+bXvqgqWuAoSSAKk%20D4GoA7/BRMfclcHRSCAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICDy5pJqOvz0%20UTAqGgf7vipFHRscCHDcCCCD3B0KCA8p9l/bzOw3DhiobXISRvEN3BWLbIQdriGEDQ/BY7rbZ0kr%20R8oYyy5daZS8x8ttPciylkikha0ucQx1Gy+b8rhouduPGW3cua0TPVft+RYuaR1tcN+1ma7b6Uwo%20C8ilG10/FcnJssuPXnHsyRev3WBsJXCSLdbXMRLmTwvcwB3/ADD8Fjw7u63S7W2egy8Zyb3IxURh%20ZlH3Vq6rgXGr2600NPKQOn7BVv2+yvurNkRd7cfetr6t7x+wwWdu7aa05He23M7FzZYpL8ufDFNo%20NrWnyvG4j83RTO8z7We6LLZw/wDp5o7Yn4uvw+5/LOO2lvFzHFHIula0Ov8AF7XRjZTe97K+XxoF%200Nn/ALLts80ie2Y9VLsUwn+A5Vx7PwmfE3jLkMpva0je001DhWvdd626JiJjlLG3MZNDXTXp4Kw9%20ICAgILc3bwFan56UUTUWbqxsruB0N5Ay5hcNpjkYJPgRrVSOV+4/srwQYG8v8dZnF3MMMj6WjnMa%20+jSfM0fFa+XFZOsxGiay+c7jP2OLx2NN0HPN1HG2ONtAKhorXt+37/Pf9Wc2S7t6fzZ4uozMXlrf%20IOmjijdFPDrJA8ncGjQPqOtT0+KwbnaXYqVR3VXb+J0+PuoWmkksb2tfWlCW6Guix4L+2+J6VXR3%20jN5d4iytbXNTUF4duPmHnjoCRscfymteq62/20ZPnsj3ljtub/Lwtlxl1H6fqy7N0MTj1c2h0/b+%201c3axMZIn3Wl2z2q9z+YniMN/wAnx5v7UMjbBcWTY2GKNsYqJIq16d127/MYbMnZfPbPEMPZM+7n%20Hv6/iOdyGEv+EujsMtJvdezMidCSzykNkbQV1Wzl3GObaz81vHHum2JQPGZ533DcZnGussxDtME7%20HUDw01DmOafqHXVcXcbbSb8XzY+sLxd0l1DBc4xNzYuwXuPG3LWc0oZY3r4g7YH+XY8jpTQh689l%202WS276mznsuiJ7orz+H8GaJiebRct9ueX8LbNkbX/wA3xYF0kYY7+dZ27NWudX6wG66are2XksG9%20+Sf8eeOfpdKk2TDWxt32lreRFslvcwi4heCK+mTo53UsPwKy5cN2OaXxqdwHBwGla/Gmh6UWLlzG%20r5JasuMNK0xtmczzx11oQCagfCoW1s7+3JXkrMaN3Y4PMf6Xscs8NubZ7GNfPER5HubXY8VrXX9q%20LFub7bcs21pVaz1aXN+nDaS5GFxjmgZ6nqM/M1oJo5rfHTt/uz7Skz2XckTbRsLi1uYsbj3Zu0+0%20Zl4RPatlIcyRujTtd0BWTc7LJgu7o/b7KxcycLyPK8eDrbIRv5Bxcjz46ZwdPaMBruge7X6SdP8A%20csGS23NrbP083SY0iZ/9S0TT4OkcU5ZmsFBDl8NfuzXD7lzX+m0OfLbxAA7HBwqHbTRbWz8tdZd9%20LNExfH4/Bj+nSNOTtfHeT4TkVn97jJhNEKeqKEOY5za0cPkvSRdDHRsnENNGgnTQ9/Hr/ckzTQaD%20mXBeN8rtGxZW2D54twtrptWvjeQaedutASovx23xSdYTEvmrmXD8/wALnZByBsclpdOdFa3raOZO%20D/8AkaAdppodF53c+PvxzWzlz+C9uTVqsJneUcUv2z8fuTLi3OH3+JuHOex7Guo5sNfpJboOy0Mu%203wbqztzRS+OV3L72XXo6ni+e4G4x7+TcMyn6e6KUPzOJuAazE+YxBjz5X9mubpqqeOzb3Z5IxZY7%208U/tn2Y802RFZmjqfCPcLj3Mce65xRkbLBQXNtM0sljNdQQ7rQhezx5bb40mrXsyW3xWJqktPKat%20FKdGg9j4LJMLqgBzteop1HTvT8UhEwuIkQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB%20AQEBBbcC0UFS0/HX8CgRvJcRQ961PgUFxBQNpTU6V/igFtST8qf2pAtfZWgkMjYIxI4Ue/Y3cWnq%20CUGg5P7c8P5FbPiyGMt3TEO9K5EbQ+N7h9YpSpB11VbrYmCr5L53xHkHDOTvwOFt77MWxEbxcOhJ%203veXNpUF3h/FaObx+O/VeLqMOfMS4+5EObsZcdM4kM9RpDXOI6kkAafNcrL426yNNV4ubDbb3Eeh%20jlLQNrmHWtdOmq53zWzXkvp1bDDcg5VhrqOSyyk0lk1zXS42Yh7JNpBoXOrTwWLNh2+WPnsju/5f%200XiW5veQ8F5C4QzWl1xPM7wbPKWZJpI40r5SwH8e3VW20brbfNjv+pZ1tmVLoh0fF8u9weKY9kV6%20xnMLRjT/AJ63kDZ444x+ZgB3Oc3VdHZf7Riy3duS2cd1I59WO7H6JbwD3a4tzazlmsnvsLiN22Sy%20vaQzAdKtaeo+IXp7bouisMUwmW+QGvifp69vFIHtshP1CniO4SJFHTNHQjUVGvVJkVIc4h3hTSqU%20HmQVIFCDrRw666JJRoPcSg4dlamn+Wm1Nf8A8bh2PxS4fH36Za5LD2sFyxrmtha6NzgSGu2jpqPB%20eU/7E48kzDYm2rT23BBbXUU8GTlDIi10pLfO9rSDt602rav8rN1sxNvOqn0tUscC/a0Aeby0GtAR%20QjsuTFImrJSjD9quXYLFtz3GM9jDlcRNcFxuNu6SAOq1ztp+JBqCCFv+Vw5MkY8uO7tujpXSVbJj%20WG35JwbOcNtW39vO/kXHbrcY7iIF0lpFTy7mtrva1rh1NVqYN7h3OTt/8WWOn/KePRNKR7IFwa75%20ZZy38eC5JNYyRyuf6EbvUgfGTQEh1aE/JdjyEYZst+rZF0MdmiY8r5Rd5rL4ma/xLLK5t4XRS3lu%20/fHKXGmrQARrqRotDbYLLcd1tt1YmeU9OPtZJu6ywMniMbl7cxXAa/bVsM7dTGT30I6Vr1VMGe7D%20NYJisNBFkcjxcssc0XX9jOawXzddg+na+vw1W9OGzcfPj+W63p/BjmaTq6Zw7nuU4z6pkLs1hbgN%20AtJH1EMQBNY6766flK87v/HY9xMf/jyWzziOc+7ZrRseRezthnQ3kvAck2zbI0z3WKaXFkri71BG%204bz6f+EtCpt/PX4JjDure7pF/wCFWK6zu1hzY8gvGPuo7mDbPHM4XTGAl0JOgh26VAP5l6G/bY74%20tm2aRMaek+6lt8zDeyRRhj43TQyF0TQ4RyNeGeqKBpqa1qtGcV1kxPGjJFJ5JF/TlPHDgM5i7q4Y%20LmC+9WRszwGCPRrXUf01HbTVc3/a8d112O+2Jp200jr9icFNdVznvLfb18UmPx2JbmMg1kkj32tR%20GzoAXPaakErJ4LZbn9+We2335ovuifi6h7VcSust7ZY605fHDfwSwMdjBtBMEbmFoNQG0d5gve9u%20nbLBLlnOfbfkHCXxOmL8pi53lsN3bsJfE0a/zxTp5vq+S4m58Z2fNZy9F7b0bxGQy2AnNxgpWtgm%20/mXOOdT7W5FKlrhQ6LlZJszRTJH2/wB0Msc6w6X7e8hxPJhPPxAy8b5BZyD9SsJRuZKHavG0n6Nx%202h1KrVv3m68dfF18/WxXRoiYi6vSXW+L80ZmZbixubU47JW5pJBMaiTsHRuo0OFfBev2W/x7i3ux%206+rBNsxzSZzG1r3dQuGpGnwW8qx8hjsff2z7W+t47u3dUPjlaHaEfFRToPnXnns5m+Metk8XK7KY%20iWR8slsG0ktYx5qNArubTRcfdeLi75rNJ/NktyTXVyvKYC1yrIrm0kNndNBdHdxClSBVu5umtQud%20h3N+KsXx3W+n4JzRbdFJ1rxq3XE+d5K5yEeOlmfhs7DGBHlbSjo7lrTVzXANbTdtB1HX9yyzgv28%20/Vxftu/tnpXT8/u9Hj9zs82xunLinus1rbPHt8f0+juEe51vmJXYvKQtx2Rija5j3yB0U7QAwu3U%20A3bvy+C62x8hj3ET2845ux43ymPd2z2fut5wnLZX02bS0jt3P4/Fb106ulbNWSpSICAgICAgICAg%20ICAgICAgICAgICAgICAgICAgICAgICAgVH7+iAgIKOaHCh/BBUBAQEFA0h1a6eCAAQTU1B6DwQVd%20WmnVBaoNzXEeZpIDqVNPn8UQxMrgMJl4vTyljBesoWtE8bHlocNQ0kVCiYS4XyH+lgRTTXvFs5Ja%20OL3SCymj3x7RqI27S09dNVr5trbk5pi6jlV/FyTCyOj5BhrmwArtkewkO2HV9W1FNFxc/jbrf26s%20kXPUU9tdRhrHskjfQgOodNNNa6aLmTZdbPpK8Sv4i8yuGuTLib2W1NNronudJEeu7yV1OuinLfbk%20il9sT+aat5mOX8e5PDFY8vxklpIx7TDmsYRDJV2jg91N1NakV7LWwbbNt579tf8A+27Umk84dD41%20k+Vcawb28ezVvyywgrM22unbrprCKiJj2uFfKKAU+a3dv/tF8TFufH2V69ETt6xVKOFe9ODzVu9v%20IbWTi2VbIGDHZAkFzTXa9ri1oIOoXq8OfHkitl0XfCWCYmHQGXLHjdEWPaepYQ7+wq8zRD3HJuOr%20aFvQD91eyuPT/nUa+FPFRI517+84j4h7fz3stob1t4/7PYwhpaZmOAfrX6VF0Vig+brJrosfahzt%20fQYSSaaFoP5jULxuaa3zPu2YXH3Nu1xY6TzHSg6gjqK+FP4KsYb5itNCq4KlwOuh0GnU9q9z0WMm%20NETv8gMNyuMxxBsGSZtvHgEA669ev4/2ru4bIy4KV1tUrSdU+4tyvJ8YlkmxRbe2Nwf8zjpHbmSC%20h3BnYErgbna2Z6Rk0ujld1XqyctwTEXcM/KvbgC4upgP1jjxG0sEjvUJj+nb6Z8vgr4fIXVjDuop%20/wAb/Xp+KZs6wi9lkbW9eCxrobmJ2ye2koxzN31bgdunaq2cuG7HznSdYlWOT2wRSSvDWGJzCOmm%208Anw7aKsxdNtea1WRdFs1WPhEsLwWysIqKanvXqP28aYp7dYnUpRFHYzM8VBucRXJ2MtTLauruia%203UbKHwNei6lt1m7il/y3R19asNJjpolfFuUSWs4y3HbtgfRrp7SpbGT9WyVre/aq526wadma2sdJ%20p+MMttOboOQwvGvdiCC+xs549yjHVEsbQ0GTcPM2QCm9u4ddVxsefL42e26Pq4Lvw/hx7rzZE8ub%20k99xvKWeRngz+Ndh3RNeYZG/y/uHM6SNJO2lezl6rFvcd1kfTu7/ANGtdFeeiH/otzFZXN7Oye+i%20u37AbdxEjCKuHqV+pv7fLo/Xtm6LaxbPHHGqJX8ryZ0cVtJbxMt72KJsEMlkPTbKHD6JG93A9f8A%20Yr/Rm6ZrynivH5qXS+qPZv3k47Pxqxweca/AZXGxRQCO7BDbgkVc6I7fpB+K2PqWU0uj70zDr4ks%20rm38hjura4ZRzQQ+NzT18RSivWEOG8+9i7nHtu8xxJ77qJznT3eIeAXVHma23IpQUPRaG68fZfFY%200mFrb6OPXti27lhube6lx+QtXgsuYCWStcKkxyUINNOi4GPJdimbbrax6TyZ4mrp2C9wMZysDB8x%20pgslaFv6bkmyGMTuFG1a49DqNK6rjXbLJtJ+vtJm6v7rfT7lppPN1fE8wvMbcMxvI5YhbSsb+n5Z%20gIikNNI3/wDPTWo0XqPC+es3ts1jsvjowX45hKcjk8VY20dxe3sVvE/Vkj3gB1RXy/4tF6CNIY0S%20n9xJrm7FnxywkyMbj6cl9L5LWIa0cQaOc3TsuPvvN7fbxrdEz6Rxx1WsxXTD5vv7W0zXOco26k/S%20MnaXZpDGWfbXBc6pbGwUbtNRpU9Vr7ze3XY7cltsXRd+Hxn2cjzHk8m1t+S3vrX7KfDj8m6tcXx7%20jhmmnlhtTI4v9a4cwOpSlGV81Kkjv2XDzZNzuPlpPHHR4fNvNzvbu22Lpr6V/p9vp7IfnPde1nYb%20fEY378a7riZ2yNjm9HM77gehqunsvD3Yp7r7u2fb8v6Ot4//AF6/Fd3339k+kPo7+n/N88y3C3T8%20xi9IxyMjx29jmySW5Y0tkdU+bdXReptnR7WKUdXUrCAgICAgICAgICAgICAgICAgICAgICAgICAg%20ICAgICAgIPLo2lwd3HQ+CD0gICAgICDx6rACXHaB4oPaAgAACg0CAg8GKtDU1GummqQLc9vHNC6G%20eMSwyAskY7WrT416oOQci/pm4leTvvsPd3OKuiXvDA4SR7zU02u0pVYMm3tu5p7nG+R8M9y+Iysj%20zGMde2hB23lq31GD4eT82i5m48ZHO2WSL/Vr7bL4+c/ypw12rXMmIa5tNOjta/3rj5NtksnWF4uX%20LSA2Vy27x8kllOGgtdEaCm6o8ug6rHkyzkt7b/mj3Wn1qlTfci8u4nWHK8XFmrCQAMuoxtmaH1rU%20M1H4dfFaNvi8dnzYLpx3enOERfXpVIOJ3eN4zh7ybgPJmMhIMpxOVcDvla2jG75PMwaBq6ODzm8x%2030zY+6J6266cun3qzZCTcY/qMwk2Pc/lVnLiclE703Mt45LmJ5A8zmyNaW7a6Best3GO7ldDFNsw%20lthzfOchiMvHMTFPaGlL6a6iMWo03RxkyBZZpCrln9T0PLI/biG4z1zaSx/fwtbY2TJGxB207X7n%20n1DTw6KbtYS5ZZ2Vu+ztpCHSF0TSG7iQC5tKbfkKfJeUz7i+LpikW6+jPERRkwwxxt/lMa0ClCzQ%20aEdfj81q35Lrp1mZTPpD2dtCD5iBQU8Ov96oVlGee2Quf064dIG21vNSYk0o3TzVPXqur4u/t7oj%2090wx3wyX213h3GfH7ruynAc8PANCTTy/mpSij6mPNFL/AJb4LdJb/AZ+7tb39TwF6IL9rAxzg0OB%20YT/25GHTzfv7/Fc/NgiI7ckVtqy9yY+nxf3Hn+6ysUeE5ZaMMVs1sm2O5a/6epDXeb8VpTmzbOKW%20/wCXDdzrztTSJ5oVmMZyTjF19ryuBtq2Yf5G+ir6T2nXYXNptcKdP9i6OO7Dntrt57vW3r9yk16j%207iR80c0bmztdRrnNcA1rW182h1KpNsTpOhEVWW3LTI9skbmRtcNkh1DgTo6ooBqpmylO2V2puuKw%20W9w+/wAWw292XF8rGklrgTXp2/Bblu9umOzJyY5tpOjNx2bfdXTZHO+wysBBgdWjiNwNdexPZYsu%203nHGkd1kpifvdRsOV4Xm+Nm437gtitS14+yuY3lglJBaHb/yu1Gi87k2WTaXRm2vzTPO30/ivpdp%20c57m/bu/9vLiWG4dNe8Zvml8GUjaXFjyT5ZNgq3y67jou9h8lZvoibKRlt52zp+fuxTj7fg0t5jO%20LXlpBO8j7eLS3uWP0Bp2poafHwW1ZutxbM2/3elCYhJrb3T5pgRaWF9a2vJMe8CG39WJkMkcIFKN%20dGK129lp3eL2+4rki67HdznWv5pi6YdO4VlILmw/UuD5U2BBaL3C3DC+F9wQSGB0mseo7aLUv81u%20dnd2Zoi+zpPt9iYstv1iU1xHum+FrmcusP0NzKCO5bWSA0+o7qeVte5Xqtn5ja7j9l9tfTl+bFdj%20mOjE9wPanF8uZFm8BOy3yobubNGQ6G4jeakGtQCfGi2dztbM0UnorF1Hz1yLB3FqDi+T46SzlLto%20gmDtT0D43DquBdtsu3vrDZi6JdB9uofctmHvMbdMjdx10bRa3eWY2OSMOGrWsA80bWmoJXD8nm2c%203xdX/NE6xbr9/H4ERd0bGLPcKsYobW5yf+p8taxuitLJjC+KN+unkq1rT2qVO6y77c07v8WGPfWn%206tbNu8GCK33Ua+LnXOr23e7KiDHMeBHb2Fl53AHR0e/92taLWnx+2tuj6Vb5rzu/h/J5Xd/7Hmz1%20t2saRznjX7qfk5VybLYewx8uOscY6K+ie58r7l0jHx3AFA6pNXGoJ+FO69NtMeW+6Lr7qxPKlOX8%20DbbXcRfXPdOvTiP4c/u0WB4ByzlrzLjbG7zt22hmOjYITQmhdo2p+C7OOJ1i2Itt/Pj+Ts4rJ1tt%20t7Lfzdz4Z/Syb60rzWY20ZY0xY2ye1tD3D3ipNOmiz48MWzrNZZsW1tsmtZmfd9DYvG2OMx9vjrJ%20myztY2Rwsr9LGijf7FnbTNQEBAQEBAQEBBy3Ge4+bs+Vcqt826N+JtzN/p8MAY50lqAJLcn8z3uN%20W69EHnifuJy8YeO0ydiMxyqa5vD9rbllvHHbW2x+rnmlQJWt+J+CDKtfdqabJXN46x28Xt8Uy/fc%207m+s2b1nwuiLO59SMsFPn0KFGTce6t5ZRSx3/HrmLKD7SS1x7ZYnulhvpfRjdvB2tLZPK5pQZPMu%20RcksJOKutbN/3l/dmO8xTJIzv/kPd6Zmd5AGuFdyDAHunBthyzoLmOF+PknfjAGO/wAw25ZbtZvp%20Wpe8DcPLRBiWHuHyW0yeXbf4uaa7lylrjcdiBLF/KdPDv3GYeUs01KJZ97z2az5l9reMIY2znfBZ%20QTxTD1bdnqyumDauadpDWojRb5L7hz3GPtosY2SzubmLH37ZnbSPQurtkDojr9XmOqDJxvP72a8G%20NsLObLZGe5u3bZHxW4itrWRkTnbvppukG0dSiV2z9zm3OStWjFyswt7fHFW2UMjCHXYBO30x5th2%20uG7xCITlAQEBAQEBAQEBAQEBAQEBAQa93IcGMq3Em+h/UnAkWge0y6a/SDXog2CAgEgCp0A6lBaY%20IpWb2uD2vFQ5tCD8qIMfIZLG470BeXAt/upWwwbjTfIejR8TRBlOfFCwve4MZXVzjQAk07/FB7BB%20FRqD0KAgxW5THuyTsY2dpv2RCd1vXzCMnbup4VQZSAaU16INJkeWcVsXGG8ydqx9D/li9rnntowE%20u/gopBSXI+Ye3Xtpy55mw3GsichGXUnsovsmGR3m3udcemH7T3CrdjiUw5zmPab3cwdsHssHZKOT%20zep6kcj420J2yNB7dNP4rm5PG47prELReiVrkrW7dK2a6fFcQVjuIgdga8GnVuh8zfwXP3G3nD+2%20yJ95ZLbmf+mWgImawiQEPZMPq8Q6oWn/ANvJyrovSJSfG8/5NaMNleiLN4qcCOeGaNoeyMijg2hG%204UHX+xaGXYYb/miuPJzjWeaYifVIeH3fFreO4tvbzKScayMxD58Xd7iyTadHFru/Y7ex6rPZ5Xfb%20es5Y+pZX90fkp9O2Wp928v7m8h4SOPcowFbv7xlzZ3uPLTC+KJrmvLwTVn111C9DtfN7bcfsu19G%20KcUxzc0weTzseMFxlLFxtInGKKeBoIHp0bsND4LT3O3x3X9tl3z+i9terdWmQsr2rraQPFA50dPN%20qBQkFaGTb34/3QvEsgdaOOrgf7q17/7VhW0a7kNlBdYW6FwCI4YjLp8KOLvAjRbezzTbkiI6ypfF%20YbSKyvm8fx+Udayw4y4gYYZ3FpqaCp2g/uWLLdjjLNkTW+J4/qiIryaDJWDsfGb/AB59FzP/ANho%206OHWq2sGSMnyX6+hdEwu4jL2OWZE57dk8e18Bb5SCD5XMIGnStCm6wX4Zp/bJF8TzdJw3PMRkbCb%20B+5bIr2wkcBj7oxVDdwLfNtqQaHR3w/FefyePvx3xl2dbbo/dFeerLM1jXVq897W2nDnepZuuZuK%20zM9aPIRkSm2eR1mZ1dCBTULseO8th3sduaO3KxX2duscmJd8O5hjcXHkry3Zf4a5Z68GSsavhMJ1%203yDq3QVW/ufFX2zWzVXvQ2/v7iTOYSyw95Q5mZsT5Cd4Ac/a2gB0A70WTZbaclYyxyRNzd+5ntR7%20nYKOC8kx0Etq1xbJkLZwc1oB3N3gnd5qV6fxK3sOzjFE1msIm+rQ2OZjkiFplXCRhoYXgA/SADr3%20NVzMu0u7u7HotEw6hxb3Gfj7ebG8q35bjtzHta97BI6PsA/xZt79l5vc+P7p78E/TzR6aV4/Fm74%20jSWu59wnjeCwdvmuHlk+BuXubd2b5QW1/MYt+odT8nVbXjd9nzX3Y8+mS3ld+Vfb0lgyZIxa/wBv%205cQiv3u+eMW0DpoWgesNBJDToHtNOg/ct/6FsWzN80n802X90aaw3Xt5Hz+xsMpkcZYuyOKkuaE2%201HvjIFavB81AB+X5rY33h43OOyY50ZMV8Wd3unlh7m8Zy8TsfeE38Mw9OfHMYXOI+lzXtoaebQjx%20Xj//AITcY7+6yO2Y6rxlbO1x+dxzRd2eQuOJcejYGyQTvbIXOP8A22xNOjGgO6fh0XWs/wBky4oj%20HbP1sn8FIx26zd8sNLmeY8buo3SYGCTl+Qb/ACn3WRcXwR/9JlLdDt12hVnJus013l/046Rbz/By%20975ba7aIrdrPRHc3zPJmH0ebZmGIS0Fvi7Tc1tAKbjtBceunTosm32dkz3bazXrdPFKezz2581u9%203FMFtLetUNy3PXY+IMwMEGNtns1dK1u97hUDQEtOq6ODxsZNcszfMfFqbbxcXzP1Zuvnjj+jYcfz%20XLsR9vk7W5+4yE22WaK687HB2pDQ76CVXc48F1bKUt5Vjjo9fj2WPFFcdsW3R7fn6uky4r2y92YW%20TG2DOQ40B0kXnj/nubUxy0G17NwC4GDcb3xl2vzYrp+On6Vb1l1mT2nrx/BHsv70c39us5Bi/wDT%20eOwmKeN5tIAwOuQ3rKxzS7q3pVfRNvvLc1sXW8vtYL57ebv3t/7lcR51YvuuP3fryQbDewPaWvie%208dHVHXQ9Fs84TVKQ9vSpoNK+P4fEpWhRdUggo54aQD1caBBQStPj3/glAMrQAddRXogruNR5TSla%20/wC5A3O3EU08UGJJlbGFxZPOyN46gnp8/wB6FFmDP42fJsx0NxHJcuiMxiafNsBpu+VUGpvfbbid%207JG+5tnSOiyYzUZL3aXgFN3/AE/8vRBS+9t+PXW57H3VpcunuLj7q1ndHLW7AE7N2vkftHlQVPtv%20xWsQbA9kLLI42S3a8iKW3JLgJWfmcHEuDutSgt2Xtnxy2jpI+6u5RLbytuLqd0srRZu3wxh519Nr%20tdvfug3uRwlhkLzH3ly1xnxkrp7RzXFoD3MMZqB18rj1QaR3tlxN1qbZ0EhiMElsP5jqhksrZiR/%20zCRgLT2Qesd7c8espWzh1zcXQu4791zcTGSR88TPTaXE9Rt0og8we2nFocu/JNjmc977iX7Z0pdA%20H3jS24IYf/yV11QWLD2o4rZhwBupyWQRMdPO55ZFayiaGNh7Na5o0QZMvtzx8zw3Fu+6s7qGaacX%20NtO6OR33Dg6Vjna1Y5zQdqBZ+3PGrTLsyMLZqRTm7gsXSuNrHcubtM7ITp6lO6gShSCAgICAgICA%20gICAgICAgICDkWR++xnOr9/EopLzI5R73ZLH3dudkErIdrLmK6OjW9PIDr8EiBHp8tnrLA3t7YZH%20LMiNhE7NXN03bLFkX3cbdsLXAecs3gbat6KU/FnMusuLZ5ZeZX/QkuSiE99M1/3ux0DvWGjfU9D1%20C3UNrUKEM7BYzl+XusXa5O6ycdjDZ3j4wT6X3DfVey1+5dSpeI6UGijQlo7C1ztjxjj+Nt5r6wxU%20ZuosrcTeoZYr5oPpAuaxz3MH5aAgnqVInnI7HNT4Th/qufkr2C+tpbu5ZFt3UjdWQsP01JHVIEAv%20m8izllyW3bb5JmPurIXMtlvkdLHcQ3bQ5rJHMjO/02uO1unhVKlG7eeR3PKrO3t8lcWFgyKydx+a%20aOR4mjNfXbK0MoXuoWuD9viFIuXDMxZ4C5vMgMldXOVyt3C5zpXRxWtvDNIIKNaxzxGWtG0AGqgb%20H23gz02exeSzUEwvn8fZFc3MzNrnSNnBo7T6qH4IOooMDNYPG5q0FpkYzNbB4eYw5zKlvSpaWmiC%20zjuK8cxzGss8dBEGU2u2BzhQAfU7c7t4oNqgIInyr2s4LyeONuUxcZdESY5YQInivXVvXx1VLrIm%20Bwf3K9keVcZuYrjhz7rLYoROkvYrgteYQ06BnTd5R9NFpZfHYrulJWi5zaPlNgJfRvopsdI1rXEX%20Ebow/UA7Q/b38VycvjclsafN8GTvq27o7a6IfRrnNFA9pAfTqKObQ01BWhW/HpK8T6t5huZcqwof%20HDduvrOcbX2t0d1G02kRv6irVgu22HJNbraXR1jT7/X8/ROstBhuRWeCvbizv3SxYzISOlsg9gk9%20OR7q+i4jsWnrRb+528Zbe7HTvtik+/urbNG5znEONPjbdtj/AE+4Z52zQP3bmtoW7mA0dUj/AILT%2023kc1Ztunuj0n+K0xHwRN9xyHHNJuIjeRx+eV0dA8sFdNhAGun7VXRsx4Muls9sqRMwyLPMYzLW9%20xBC+sjI3C7hf+UlpG1xNK9CsOTbX4LomYIuq6b7FZq6zvEL+3v4WNhxE/wBtGHAFm1oGpr/sXB/2%20PafTz2XY+d/58TxLJjpMNH7j5z20u4jicfbyXOak3RgWTf5LGlxBLwD4u+pb/iNrvLLpvzfLZHrz%20qjJMTGjnODu7Q4eexzWLlmbZkR2t5bub6lvMGkSeoNNwr5l6+/PimkTPPl8GBdg5RaWlrXIXTZ7a%20RxbBeMBo5w/I5h8wLa9Vzdx4ua1x/ctbf6uhcN59fcaMkUgdlOO3IAls3EOLAQA57Ca6BlAWLgeR%208dbnpWOzLbyu/Kv2s8XUTeyxOXxTIc77Z3kdxx+5aJcrxm5dvjfH9W2Hdu9JxbVu1ZfG/wCxZcF0%204t5E16SxX44nWG+4rg/ZL3GfDyDF4qNmRxE4kmiDTDNDcHzlkkfQlpHhRe4tmKVjlLA6pJFBM0sk%20YJWO+pjwHNoAeoNRopp+KEF5T7J+3XI43OmxUdndeZ0dxbkxESOBoXNbQGjqEhV59KprRwDl/thz%20P23to7vI3IzuHmcWmW2Y4Pid1AdGAdCPwXN3njrLtY0llsv9XPzl85NsmsCWY5pc5ti5wLA4HWUN%20r3AH4/Ja9uPHETZdrPq4283Vl89t1YTKxvcRyS2a+2BsMsGVfKNrWykNoQ/wJc793iaLl5cOTDMz%20d89kzy19ePt+1wbZ3GyurE1x+kems+7a4Sf3FwWNfj8Dkm2kUtx6l+XR7N7aGrY30JNd1d1P4roR%205zFZZGk8fk6V/wDsu1tiJis+1GwscHawySyua1z5HmR7gNtKmv1Dzfx/ivPZvI5csxETTjj3eX3X%20+w7nLfWyZttjoieU9zLE5Z+MyGSu+R2VKRwbAY7baQQ01IEh021quzb4mYt77IjHd1nnX3eg3WPe%207jDFbvp+vv8AweYuWXmVyjY8dZstsZC0uuLc0BkfUfmbo1wA0oP7lgy7Syy2sz888p9P5J8V4PH+%207L/kn8Nfzqm9xxXifuRb04/EzFZ+yY1k7b1pe5zKVbI018wDvBc+PI5NlP8Alj6ll3/Hp8fseojZ%20YojttjtchzOLxvFc7JieUYqVk4Ow3chdJE93R0jAdtN2hC9RbmncY4u290U/Hj2LcUWaUoysfJk7%20TKstMWH5yC9eI7WyhDnemXV2Ve3t+Kw27b60ax23Rzn1Xt+Vm5fDc54pn7KHI3sb8lO4bobeQsdZ%207CKeq8CjmtNB38Vvz47FTtpE/r6sWSK+zI9y87xnKcabjxgZcdyCCYXBypufuROQ0F+15dRgdpRu%201bdmKLIiIikeie1FOLckzuEmbf4TKvwd81hZNMxhc6ahJLS0gt+FVr3Zptn1c67NdZOkd1fenH8n%20YuIf1c3GNcLTl1o/JSUa1lzZABzQ3RznRnrWi2Md/dFaNzFk7o5Udf4h75YjmFhPfcdw9/eW9tII%20pjtja4PIqPLu3eGqyMlW+dn+ekl0fHIzGT5N90Gv29tzduh/FEsa/uPczIxenZ21rhZmkONxLKZ2%20uH+CgaKH4pzGD+je8520zmPoPqPoOqTp8aUTRL1/ob3Eld6k3M5WSP8AM9scLQxriNdg8BU0SslV%206z4Byp1xty3Krm9sNprCxjYpC4n/ABt+FUQz/wD1rhv/APdyHzFy7x+SUTVkM9vOJNYPXsvupB1n%20me90jj8SCERK/jOJcaxWSOQx+PjguvT9F843F2z6qN3E6eKUoN8gIFR+/ogICAgICAgICAgICAgI%20CAgICAgICAgICAgICDHyFlZXlq+C9ibNbEte9jxUVY4PafwLaqJCwv7S+tY7m1k9SCUExu1FQDtJ%20odeoUohkVB6IljXuSs7H0fuZPT9eRsMWhNXuNANEGSHAkgEEjqPBBh5bL4/E46bI30oitIKepJ1p%20ucGD/wC4oMqOWORrXMcCHtD2/Fp6FB6QEBAQEBAQUBr8PgUFHt3d/wADqPxCDQcn4NxLkkcUebxk%20F66IOEEsrAXRkj6gRRR2omXCuVf0r3VvI684vknXLiHMFhcvMbIxQlrmOBp5TTQrDfgifRaLnH77%20H8nwN19plm39jK5zmNuHxbmP2GhI7bfjVc7cbW2OdsLxc2UTL6WGm+3yMDXUMjxqSNSOlAVyr7rI%206TYtErVrfZLFX8WXjtnyCAjbbF4kjIYauBjI2jcdCQFsW47MlnbWPynqn3jmzOQe4g5rbRSxQ2+C%20ljkBvJoQ50sm4eaPvpT9yx4th/1JmNb68q0oiZqsXOLwlyNzGxtnDCWSxupJWlQTt6nTqmLcZomn%205kxCJYCxz1zxjLzW2cubZjblzbi3FWxyaNbvkPx6dV1819lt9tbYnRj7qRzZo5JkcRyO2ktbP7S+%20jt2WckAG+O5LtHyEk+VzjrRVnFZmxazW3mTdOtOa/wAKncLrI3V0XxOlk80EoIaCDq7cfh8VqeRx%20zFttsRWi1uvNlSYDjt3DcOmlZcs3lzpm1/lnU6Ea/vWGzeZ7Yi2IotMNNH9xxW2bfY28OUxdy7Y+%20F9RtI1Jb1roVuzbbuJ7b47b4Ur28pTni3J7y2khy3Hb70d7mTXFnu8sjWmm2Vv5R2JFFw97tImtm%20W2sdJ9PeGa270dMgZh+evbmONXcnFuV46USXHpbWG4fTdtlGgkj3jqRVc3b7zceMmIn/AC47v/t4%20ha6yLnQPb/3UbnMld8fz+NfguQ2YAcyVw9G6odpktn9CKjpXRe+2u6x57O7HNYlq3WzDoDtxDqnQ%20anRZ0LcsMUzXRTRNljeKOY8BzTUa/VWoKiJHAPdT2Clt5Jc9wq2idbNhkdfYM1aK0LvVgNa79T5V%20r59vF/tLT3W1jL1pd6uBXNjITFPYTCG6e4eo36CxzSKte06h1a6U+S58XTZMxfGjk23zjmbb40j+%20bcWPvDNa27rL9PfkL+OkZcX7WAjyg12uND81q5fCW3T3d1I+HHT7mnn/ANbxXz3xd2Wz0aPLXnI8%20/KXZHIS0YKNsLIOLXEk+QiHRx1pqtrBgx49MVnPr/XVvbPbYsUUxWf8AumNfbm6jw/8Apb5dlhb3%2017eRYSwfCx8UbW+pdOa4Ahrxps0Oq6VuGafM62LDMazOq972+12O9ssdYZ7BXLnW9xI2yubWXUue%204E+oXV6VGuipuNrZfFJ0bFs9usOTHmuUtLgGye6e80exzXGN8VDXylp8416H5/LTt8djm2kxoyW5%20qu13PH2+4/FMdkObcksobeECe2s8dSSUSBm0tnJ+nXqFfx/ise1mZs/u/itdd3o3H745J1nc8b4v%20gbHFy2bX21zk7ZoIkjaNjHtcG136V6rbzTMRHTj7iKIzgsNzvC3D71+EueR2V6RG8XzXmYNqHV1J%20dQ07rVt8xg1i66IojsnoinLM63LZ/wBZ9kbaO0Y6NtqxjW+i+ooJPi0Bbl98XW6Tzau4i6lK0ZcU%20b8gIRbmCF5aS4VpQMO41NabnV8ug7LUtx90zMy0cWDumszxxxRl3Nvg73GMlxUZtbyFwZK5w2ue8%20CvmJIBaANCFS7JNvw+PH3f0VyZ+32/h7cfe23EPde64hyKzysEW4H07PIshGxksQePM/Q6gaV+K2%20tvddymWztskzNLn23is3jctax3WPu4bmN7GvPpSNfQOFdadFuN5llxc7y9hru0FFAMNCKHy/Dpro%20NPBRCF1SkQEHlzSeh06EfBBQMcKkUr2HQIHpu2gBxAA/GqCpaa6OPShQUawg+Y7h8fH5IPaCOZzn%203HcJkI8dezOdevb6roIGGV0cVaepIB9LUG1vs3jrOwur6SUOisoXXFw1hBe2Nrd5O3r9Pig92OVs%20b2xjvoJmm3kjZNuJA2te0OG7/Doe6C6byzAYTPGBIKxne3zAeGuqDGymbxuNsL2+uJmmLHwvnums%20Ic9rIwXO8oNeyDJs7uK8tILuGvpXEbZY9wodrxuFR+KC8gICAgICAgICAgICAgICAgICAg8T7vQk%20213bXbdvWtOyDjuOx/J35DjNtfWWTgyFhZSyvyIMjopLtzpW29vOWnZtYDue5w18qmhpLRw2vIvu%20XYuziy1tyC5w1468ZdzPbHNeslaS62Djt6Alrm6UIAUCVRHl+TzM1/bWWQtbB+RxhgjuA6Jxijia%20J3lh+lgePN49U0KtJYcf5tJg8t6k2SZnn2phv7ZjJ2NmmfOCZo7h1Gl7WUDfT7VT8yq9y/iN+318%20YLDK39s2zx0eC9GWWRjXsmDrw3BrTcdCS/r2QZsWJ5aeUwSuhv252PLMdLe7n/p36Q2OhY2h9MVr%209FK7kKuvoCAgICAgEAih1B6hB52Cvh208PBRQV2ChpppTx/tSgo+PdSp08PipmB59HTQnqP4KItG%20PkMTYZK0ktMhBHcwSAt2yMDqVBFRWuuvVTQcZ5N/S5grp/rcey91h52s1hFJInkVIqDSmvcLDkw2%20384j7k1cczGJ9w+NT7c/gJxE4uZFfRAbGxtqNz3CvbXVcnN4iK1snT3W76Qh/DJLu3xk0tlYS5Rk%20sw9VltG58kLAKF8lGu/Gi2d1tbsnKaTCO7Vtc9c2lpjzc2tvE6WctgDANu3e4AuLR5qhzlobbBff%20dS6ZijJN3VtOf+0fOuM4zGSY20kvcZeQsurt2PY8sa4ipLm9Q4B3VdmMWs11qx1c8yDZYMrBNdCW%20+s9zJBA6NzXlof5q1BPzPxVIt+SYiltxV9P2mX4hyLDS2BgtY7WSJp9KGNrT5o6ODqdXiv718yy2%20bnb5u6t0z769fybcXQj8vslirVz3cUvxGyRmy4x90C9jiOkm7sTWlF0P/wCmuvt/z28uUxx7I+np%20M2ue5OS/wjPSzOBks/5myKF7WhkxB6xupT8O1V28FsZtceSLv0+LHdEx8WD7Ze2WZ5nkeU32Cvvs%207/Efz7exa2sU7jUth8BWm34L00YIuxxbd6MFV+wzH3GQ+1yFvLg89ZSbWwyExyCRh12HSoBHRef3%20Oyvwcvmsn2Zrb6uqRciwnuFaOwHNGNxF5bbH4/KQy+m97gBqx7tWur+XuV5y3Bl2F31tvM3xP7rZ%201px+DJMRdon+C5bn+KTQ4zmtzFd4l0YZjuQQscAKENbFcDzeYj83Ret8Z53FuomP23x0YLscw6bD%20dQzxiWOVkkTwC2RjtzD8iOq70e7Gr9HTrWlfjVVmaDlfup7C4TmLxlMfL+j52D1JA+JrfTuHu1An%20bpu83dRdZF0UmFL7LbopLnPC/wCkbL6XnIs6Ld1w71Z7W0j/AJgO47ml7/7lE4o09lLsFt1K9Hfe%20N8D4vxi3EWIxkEZqHOm9NvqFzQNd1KqZ006MtttIb4RUadSK0+A8VasyRFHCv6wYxNwPEwPqWy5O%20NpoG1oQRoTrX5JM0J9XzXL7XclmzYx2Hxl1tDWTvuntoGREUDg89iqX3xbGql0xymdUp5T7WcawV%20raw2ebkOauHBz4i5nouIbWrmt/LvFKmn961P+xSPmhrYNxWadOOI/Dolntbm/b/iWLv7llqZuTOF%20L2zftPqSACrbb/C0vr1Xl/L7bd7m63tupj9fT4/D73Rx58dtlZ9Fid+ct4r7Kx5i9w9peOdc3lsZ%20DOQ1wHkY4k0La9u3yWTFmxX0xzZZfNsRETTrXm8vd/s8X5fp4o56Rr1csi43SIXN7cG1juqziaQh%20zn9SHk6u1K707nWlsVo2/wDu918286cfzXsFBHnRcCW7jtpIQ2JjI2+Z0THU3O1FT41WXPkjHbFd%20WfPktstivHHJkPhnEbbZ7w23YN8cbw2spINCdvwPf5/PX+pbd0/k0rs1t3L+i4cVeZMm2+yZCwN2%20smcCKl/TT8x/N0/uWL/sWWR3V1/hx8GOdzjxR3Vr+nHL+i5YP5bwUNvcNkBayAbLgN3je2NwJ3sP%20XU9wtrb76Mk8m7tPJRlupFs+v3uvcL/qs5lexS/qXEpL+K2iDhPZuMTiRQVcJPKfk1beXdYsel90%20RVt5d9hxTEX3RbPxdG4/72ZjPMc/DcSmuTGG/cRtuojJEHf429Qf+Wi2OfJtRMTETGseyVf+y8cB%205rG9aQNa276Vp00SdEg9y8YaVs7xgqA5zreQNaCdSTToO6ipLMPuRwsEg5OMEdRqpFD7kcKAqcnG%20B079R+CFWe3l3GiGu/UrcNcKgmQA69NCgr/qzjlSBkrY0rX+a3r4KKkNgy9tHNDhNHQirSHtII8V%20Iqbq3p5ZGOPhuHRB6DySCKFnRxGuqiog00XIsBzrM5O2wz8tYZ5loI5oJGNfDJbRmMska/o1w827%20opgRifi/NL/ld7eS4oWbZrbJW0/ovYIpo7iGltvfXc9xdXro09KKBroOCcuOHn/TMXLh447PGQX2%20NMzXm8ktXONxsr5fpI8x+vopNGfc8NvP0/CWLcTf3uLfkJL68dNtjuLRrCDHDCxm3ZHI/V1OyFXj%20IcU5tkOQ5O6GIbaCe1ylrOYXtZDPHMxwtdzvrkc+oJrowoQ61gbeW2wlhbzN2zQ28TJG+DmsAI7d%200GcgICAgICAgICAgICAgICAgICAgICC060tn3LLl0TTcRtLY5SPM1ruoB+KUF1AQEBAQEBAQEBAQ%20EBAQEBB4dQn6wKfLqEqPEsccrDHJslY4bXxvAIINQa6fgmgtWmLxVkxzbO1htmu+sRMaytNddo1Q%20lDue+zPBuYta7JWognaai4t6MeXVDqmnX6VWYgiUzsrVtpZQWcfmjgjZCzfoSGNA108ArVqIXzz2%20k4jy8MluQ7H3jKj7yzoyRzQalrqaEKl1sTpJMuJ89/p/5Lx+W3uuPS3OXhdu9ZtsxsMjQNfOAdrx%2026LSy7KJikRE/Fe29oMb7hckwM7LbN2EsJlDT6pY+MNa01NQ4fVU6rzO98DbOsfdLNGR0rC87wea%20ti289C6ghcB6cpadrqAB2o+H715bP47Ngmtk3WzPoyRdEmI4tjOMZ39U4llIcVfXzavxkoD4ruji%20+gaCXt18tQKrtbH/AGbc2aX2d9sc5jp8eKK3YY51XOWniPuJiDZ8/wAXLxbK2e77XJGjmNc4bTI2%20Rum2uvmXttr5Tb5/2XRP2ta6yYcN5hxXkPHMjbY7k5abUNIwubidWzum/lMhFW7nAChVL9n9OZm3%20+7n/AC4/JMXJt7de6kmJtJrTIxSZPEzSBkgldukgJo00rurHTVeT8t4eMl0TbPZkiOfq2LL02sBk%20vb1k+Y4Lv5ZxzIzB19hhN6jrVzqESW7vNtoNNjqLc8P5++ZnFuo7JiNJ5V6cSpkxxzh2Hi3L8Hyb%20HNu8ROJqUE0Lqtkid3bI0ioIOnRewtviYrE1hgbglzTQAGulB0Hy/cpnkh6iiAAcK18P4KItoAe/%20QE9dA6nU/FTEkrVzOyGP1JXshjB6yuDW0FPFNaofO39WHJ8Lf8Pw9jYXLbySPJxmb09Y2bQR53Dy%20j/eqTfbrETFfxTrSrCyV1eX1nZxZW+jsLZscTg2FwEj3BpdRzyRUamrSP7F5HceTy17bLZr1/L4+%20lHMs7LP7tPu0pPP8o4lyvn2VsnXNiyHFOtILX1AJXkh0zXOJBaQT4VH4/Jb3jsd1Lpuu7pkszWbi%20dJjTSfjxz0aG2xTb2xFx6j2zxEvtzESQC3UEOHQtIr+2u5k3E2zTp1aeXdTbkp0nnx7sjkvPOUNx%201viru3YxgYYZ5YdPUAbtNW0Ar8aVTB47D3TfHx44/nbb+J28Xzfbzau3faT2T3vvGv8ARDAASCQ4%206U8x7GmoWzkxzEt27BS7RI7bAYyOKKR9+7FQAMe2ckTSSvFCXN2Hy0qKE/wWK66YnWK8+OP4sWWy%20bZ1+b+fL+dGTFNgLNwjkx9zK2VgfHcvLZXmOgIcGtPfpTtXqVhusm6vbNOPXp932NX6M5LY1pMfZ%209k9f6L+Nh5NntzLBv6XjwaPubtv81zzXdsDdQO/YaLSzzhwzW+e+7246/q52b/q4Nbru+70ieOfL%208G9wfCMRhB6+QujeTuPndcvDYmltNGh3Trr49VoZvI5M2mO2ke0a/hxXRyNz5nLn+XFb2x7RrKmb%209w7PG7IMVZuyJoW7INGNfTQV00HfRNv4q7Lrmu7fjzTtfB3Zdc9/Z+fHGqK8gu+VXthNk5p24e6s%20wZm/Z7opXuDiaTuaQTtI7/7V2NndZhuiyyt0XcaPQ7DJjwXxZjrd3dZ/T7qvtfgt5PfcLwN5dvD7%20q5sbeSWQ0Jc90YJPTVd56Vv/AE6gh1PhQDogtDH2etYI3VNT5G9R+CVkV+wshSlvECOnkbpT8Pih%20Vr5OIcXke58mKtnPedz3GNtSUqPJ4bxXT/xNqaaCsbelfkg0k/tNxWWaWbbKwyOLtrXkNFewFVFB%204/8AUPFa9Z+tf+67t+KUGZx/29scFmf1Cyv7z0PSMf6e+Qut9x/+TafzKRK0BAQEBAQEBAQEBAQE%20BAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAoPBAIBFP4qKCm0fxqlB52nd8+pA/A6pQeu%20gAOvxUwKPbXpofEKKDxskFQzTrUnuT3/AIpqNBzL2+4xzKzitc/a+syB5kidG4seDSn1D4KJtieZ%20DjPMv6Zp7P8A8nw7ITy37Bt+0nLdpa3UAOBatXJs7Lo7Z5LRfMOZTv8AeGK7ivclxq4gbgHgXd8W%201DYWmrnbdQenULnW+Gsx23xb/fHGrLGSa1dWwvuTgsxauhdLBPFMxrZY3irQH0qHNPShOvRfP9x4%20rNhvrETbNeKcSzWzVdk4Pg7qzvLKwuvUx13Q3GMu/wDMQNcT5TEXlux3ht0XW2P+07jD8ua3ujpx%20qpdiieT59yHFOd8GzDp58RM3D3TzFE6vrsDATtNW6tO3XXVesxb/AG29s+S+JuiP4fqxUm3mm3DO%20b3mBfcXvFpYbu3uXMF5bO+kuHcaja4NPWi4O+2NuWlueJtmOU+i1t1NU35D7j4o29rnOH3QsuV0E%20U2ObED6oaCfTkadoDSdN6y+Dxbna3XW3fNi/5MO73FllvddpDrHB/crFZ6COC8LcdntjDd495oN9%20aOETz9YB06r1eHc2ZJnsmstXb7zFmj5LolLLvK2Fi3de3MdqCCQZnNaXU6hoJ81PgtiZjm2XNOX+%20/WDsIZG8bY3L38dfUhIewNqPK4ENOmhJ+AWvl3Vlkc4192O/LZZ+6Yho89l8DlreO75Plo8zcNaP%20Rx9gQ1sTJNHOc2Mu3OG7vT/Z47eeX319/bZH07PWa68cdGW/cYcVsX33REdKuNe8GcyN5xvH4qPE%20w4bjdveN+3mL90022oaXU27fLrqF0PD7e3Hkm7um/LMfZ9nH4TDSjzOPcTNuPWY9PuYeUfa4t1r5%20H3t9PBEN1w8yMazbWkdWitK1FD1VrYuvrX5YiZ5fr+PR567HmumuTS2KzH8/j/PqjGcvr3JywxPl%20HfzhlBu7+G46UNO63dristmaN3ZbfHZyiiuLklbiJ2NYQ0Vdua6u0atDi0B5A+mviFObHM3VTlxd%2019ea3x6CO+zDRcPYyKFzXPAbrIKgFutRqSK/irbnLOPH8vOjai2mnT1bHnGEwmRuo3Y2J8c4O2QR%20VDXucdOzRofD5rD47Nktt+fl78cfY2O/sidNOK/p6fDRrpsJyHjRjsZ/5sV55xJC31JWNjoTp5iA%20Wu6roXX2XRWOf8V8tsXa2ymfFD7c4yCQWV5ukcBJL9/o9nlPlG7y6gGmi8/vo3l8xWP/AKeOIl5L%20yeDeZbo7uUf8epkvcq+neIuO2Dr/AGHzzygtjYR5dD3BPdUw+Hstj/Nd2/Bg2/gbLf8Az309oQzM%2039pcySTcgyLrm93Oe6xg3MhjeaeVzm18vh/cu3gw9ulltLfXSsvRbXDNkRGGylums86LWF5ZkpT6%20WOjt7eCKjQ92kga2pDjWlaV/4LPf42zJNbpbV/jLL9bpmXq65xb3uJyOOvWhszGujgLBpICerj/v%20Wvb467Hki62dOrUs8T9LLF1k6V+59y+2M9vPwLj4hljlfFj7ZkjY3NfsPpgjdTp06FdedZd6UoEz%20WtAIoQPN18PjRKoevUNBpqToPEU7KJkVY9x6tIr+xCRNR6UggICAg80kANCCdev8EDdJT6anvTog%209ICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICC2+Il24df%207PiooMTLWcWRxV5YTt9RlzDJG6Np2kggt0NdK/NTA5FxT209tuX4Nzvto7bk2NJtsxLYkxOivQKk%20PHR235LFl29l+kwmLpRq74f7scQk/mwDO41zi2KW1aC+INrtMjSRpRea3/8Arll+tjLGX1ZOJ9ze%20P5NklreyMJ3CM2tw3aRLoKEfv+S8nl8XuNvNbKxPrHozxdEuVc+PD8TyAu9vbeV8rY3yZ62ha58E%20Qa7rtIqO9adl6/xmDc58Uxuen7Z6sF9I5Ihb3rslPNkILwOvdvp7m6N2U3bXAreiJwRFtNHF3O7v%20sv5fJPHH9Kzbj3Nra9ntbbMDbf2hY6GX0w1zJmgEOaWgAtFNR4kdKVGpm2HZ/k2809dePy/g4+48%20bNk/U2k8+cV+6n8EsvZeUcikdLyLJMyEENTjyxoa4N0+omgGmlfFaefzN807ax616U4/hq1c3+03%20xEW2x23R+6sMPKZnjPHA39TuGW1xJHubG8l8r2jXWn9ui0Me23GeZpXTj8v59XHtxbzeXd0RN0RO%20np7Off62tLTJibimOZYwva9lxNdVG8EhzXsG6jdQSu/Gwm+yme7un2+HGv5PST4ycmP/APYvm66N%20dKI5zHkl9nvtri4vROyCYMih2hgbrUkNaAHAU6lbmy2dmGJi2KVh1fGbCzDbMRFK8fY6O64w3ILO%20Gw5bSOZkQFhewAMLAWfTrp8x4Lhzdfjum/Fr6xx+fT7WW3JMx80Uj260n9P56RVqeY2uSsYMXa3u%20PZbCwZ6dveRgETijnRlzh1dUiunVdTb7m3LbW3TrPrrpXVH04sppFfz+z045NBiGBthdvc/0jIwx%20kMNAdxJdu06Bv7dVkvml0atDLkpfEQ11rbX+Oc25EVKtbIKUIdGDUOGlNSrX32X6S2JyxMxHHHHN%20IJro2d1iLqeRzmTNMk7ZQWta59atpp17a9tVS6k45izinH4s/dMxSNPfjp/OjL4xn/u87kr6/IbJ%20CwQWr2VaTE49dvmGuhIqtPfYrrcdttvXWWWybYnWff4e9fw9aMXntnjbjPYpzraMBweZRSge3Rwa%20dQB+CnxuS+3FdFeSM+XtxTNtK+zxyzkdvg4orW0HpOeCdjWioqAQa6dqD4H4q2x205Z7rtaOD47Z%20zmum6/p+jQ2Eltd2H22KtPvMjLFuvnkEMY3o57zUAAEr0N1LYertiIpEPd97fwtsYLqyuDbRsZuv%20bq4eGRvoRrDTUgLUjdRN1KVW+Dze8ex15b28PFLG4lmlOy6uLk1LnbRrEBt8tfgp/wCzFn75g7dG%2039s+W8t4xnJLezyd3j7cjZcucWmIPb/iqHAAVUZs13bW2lUUpz5Pqz229yM3kMm/Acyiit8nIz18%20Rc2+sdzanQOeegf4iinb7mzPGnOOaZto6ix4rQA9K0I10W1XWio9shcNp8p1P+xRMSLisCAgICAg%20ICDzNI2KJ8rvpjaXO+QFUEL4n7oWOeyMdjJZTWLrm2fe2cspaWvgieY3OdQ+Qgjo5Bm3/ufwayxN%205lX5WKWzsHxxXT4avLHSu2s0GpBPcINkzl3HH31rYi/j+7vWCS1iNR6jXCo2mlKkdq1Qa3/2JgJO%20T22CtLiK5dIy5fdTMfpbm1ALt9RShrStdChRlw884fNjp8lHlrd1jbPEc8+4hrXO+kGor5u3j2Qb%20izu7a8tYrq2eJbeZofFIKgOaeh1QXkBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEFC5oIB%20IBPQeKCnqxf42/vCD0gpubu21G7rTugqgoXsDg0uAcegrqUDc2u2oqOo7oAc01oQaaGiCnqM37Nw%2039dveiCpc1tKkCvSqCoIPQ1+SDxsdUmutP39UFQ0g/AdlEQItgOGS4bk2XyNq+KKwytZZbaNpDjc%20l1fWdXqduimRKNjmijdR3B71UCEcz9neHcoaZpbOOzybdYr+2BieD23BtA7XxVbsdt37oqmJmHK8%20P/TT7hYJ1zcYrldkMhcvcH3k9o6R7oZBR8bw4ua4H5KluGLZ05U5dCZrzc15hxW39tc3bcc5XDb5%20M5uM3dpd48Og+3mc8xVLTqWDrt79FTPZMx68cUY78Vt+ko9ybjdzj5LKK/2tjuqus7xhb/MYygFK%20EubTwXNw3TFZtlyp22TBNa6fk1jOdcqfG/H2V4LM2+71bxzgS7a2h2t18xGvlW1dscN3zTb83tp+%20Kc3jdvmpddZE3fd9/L8W64h7W8z5aXzY3HvyZa8D7u+f6bYy6vZ2nxWSMV08vlhm+hfdEU+WPZ3/%20AIR/S7xjHE3XK5BmbnY0RwNLmQxE6vG0EbtVs244tblmO22Kc0W/qw4JxTDcKxOTxGJjsbi3u2Qb%207Zu0GIgmjw3Q1poSrdsMkPnKTk+QMwMrg+1kY0bAKhjj9P8A9VB2otX/AKltsafua+TH1jn+jqOA%20y/FH8fDr6K5y+XdDtYJ3yStheAaPaDo0aUHRYrbYt0tiNefLWnHHJisinL7dOfHrxEVwkls2wmdP%205WvkLXkgFpbTzgVpQgeHwWjuO6bop0cXdW3d8U4mrdYvE5HKwA4qxa220a6eYlg2nptqfpZt3UaO%20v4LF20u+aeP5scW3WXVunX2+/wDH3/iyrjg2at7KO0yTRlGgl8f2+1npaeJAJNdNf9y3Meay3lHP%2034/T8W/Zu7YrX0jn9vH9atVj+CckjfK7FRk1NJHXD9hpqTG5pNXdhr0KjLksyc/u9Pf2/VkyZ8V0%209ePT2YPKsbmcblcXJlmNje6OR1u5rg5rnBrSRQUA+r9tFbaW29s9rNhz25rdNeXx+37kcEkF1Hf3%20eSd936bnRwhxAcwjTy9NKAUXRxY4iIpo3dtjtttikU0ZXFcTE+O4dJPNZGNm+WSIk75NdkZpTynu%20sWe+6JiIivo2KVZecz93eyNbPALloIEkkAo1sbNC7YzyaUBWLHi7eU8dDujk6hxDjPDxg8nkcBmT%20fvEAmvWSMMb4nUFdrXdDu67afJeY3+83MZ7bMllO6dKfr9jJERRr8/wae1jyDzaOM94wiJ73eR21%20xcTrQDSqzYPIxMxHd8sey02asHitjftjtL7GZOSHkWNAEc0odNH6IJe6Ha4kNc4ilVv/APyE4r5m%20nyTxVTs0fROO978fa2rDynGXGGdTb9ySJmPc0AFwEf01rXVdTb7/AB5f2zqx9ro+PyFpf2UN7Zze%20tbXEbZYng1q0ivQ/PVbtEMoSeIP4fuUzAp63Xy0+Zp/FV7h7qrCqDyXGmjTU1oPiFFR6UggIPEzH%20Phexp2uc0tDvAkUQcj477P5u1a+3mltsawWF3YT3VkZTLd/cghhla4kBsZIdoa1+CVkZEntjyW+s%20Lh123HWl5b46LG2EVtGfSm9GZk3qTg9N3pUaB0qUSzMvwTmOZ5HY3l3c28ePguLa8bCzc30fSjc1%208TWt+p259WvPREdGuj9pORXMDMfdy2FvaWlnkbKC8gY43M33xDmSSOoPpp5h3NSgy3e2mcys777L%20xWFvI6XHRnH27CYHQY+cTF7wer3FtGeDdOqfAdQa1rWhrQGtHQDQBBVAQEBAQEBAQEBAQEBAQEBA%20QEBAQEBAQEBAQEBAQEBBy2y/TsxznkLuSZOW1vMRdwMxVkLk2wZbljXRuDWkB/qu1J160QR2TPSG%20AZFzKf8Ai70eh6jtjtuRhj376Vr8kqapI3nPKIMq64Jtn4WLLPxEVg0O+4cxtn9wH7tfPuG3aoEV%20k5zyM5GLkj7+xu7r9DvL2ysICQLd3qNa2OZvU7e5PeuilKQZvnPNcVJd2017Yi6wePblLsOYWi9M%20rjtiiDtWsA8u7ru7JWOiKtnza4zV5neEvxlw2wvbt1w93rNcWNral1HMHUtPYoNAPcjKC3/V2x28%20WRucdaNfO95dDFJLcuhc9za/T5Kj4lJHnC5/lcGUvcbYZC0ub/J8hfbXeRG58TYYrSFzvSYKta/x%20HStUolW+9xLu15Jkr2xliyJfYX7bW4czY2N+NNXMaz6i3dUOce/SqaIZfIOYy5i7Fi25idbWV3hL%20hs9u+rt9xIwva4t8tDXog98c5ll7u6xmKs57TDwuZPe3Ek5MnrUujF6UZdSmh8x/xUQ6r+C9xeQ3%20mbxUs0lrLYZq9ubJuIi1urRts4t9WQjU/TV9em4IOpICAgICCN8t9v8Ah3KpIX57FW9/PbNc21uJ%20mBzot3hXtXVKVRXVwqw9iONZTL3XH+RX15b3dk5xsL2TaIZ6u0MBefy7uix24rYjSE3UmKdE64L/%20AEz+3PGBvvLduavNzXslu2to17CXAtb0rqsnarSJdYjjiYKRNawaeRtGgUbQDREvRDtQ07q/2gd/%20miWJmMJjstYy2WQtmXNtKHAscAabhtJFfmg+U+Wf0zX3EMyzK2ds7lPH3vMk1g0elLCdwcdASC3b%20XVVujRS/k2VryC3wVzBbWPAb5trKWk3FnA6eMxlo/OAfHv01ote/DWvHH69Wrl29a8caoLdWWJ4x%20f3V9Li7q8t7gukgx2RtnwlnmJpDQODqU7/BUyYKxHTj7EZdt3x768uK9UowHPcFlYi1w/SJIXDZb%203JEYeHAgGOu2vmPh8Vz8u3utmns5G52d9s0jX0419+STkFurg5wq2jWn8ag6fDv2WpF0xzjjj2aE%20aTxx8D+cBXcCXCjCKmhqQfLpqKjvqptyROnHTrTl6f1R3604+PHVy/3otG3eUwsBdVrhLu26/GtR%200+K6OwvpbM04493Z8bkiLLplyuLCyTyTDeY5Gvc1sNNriNQDTwqOq6ls1jR2cXzW1hmY7krLezFg%20LBgkkiMHrNcaveSQJHDxFVjvxTWteOOKMts0Tj2w4zlcddy30s8UbJI2xxTucXRmuuxxptHToVx/%20J7iL7aRE8enH4rWWxDoWKzuFsL+7jfY28F3eN23s0TQd4cRUuOupNTWui81udvlutj5pm23k2Lac%200r4zyqxGIkssp6c8OOJhBkeBuiaP5Op0LnM1XL3uyunLF9k9vfrp6/3fjomJ6IfgbzMvyF9lsYHx%202w3NZbRQmSkdS5jXgA60FK/Fd6bKWxHOfVjdSs2/qOMilc1kpe1plhBDgwkah+7pSqxfUmOXyzx/%20QabI8UycDQ/jeXuMDcbw8yWh9SJ4BNIwzo1u7U7fFdDa+UyWfLPzfb+Ks2w2UHvw3jf+R5OLe+lh%20IjNzj5RLLtb9Tpo6lwI/bVei2+7i+K0mKsV1rrGC5Jhc7j4L3GXUdzHNG2VoY5pe1rh1c0agivgt%20tVsWuNdBqera9AOilD0HOrqKDuaolXa3TStOhOvX5oKgACg0A6BAQUcSKUFR3QWpryCCGSa4e2GG%20Npc+R7gGgDqanRCWj4ryq55BPdyR4+W0xsB2QXE42unJ1D42/wCAjugkSAgICAgICAgICAgICAgI%20CAgICAgICAgICAgICAgICAgICAgINde8dwd9fQX95Ywz3lsawTvaC9tOmvenaqC5+iYjZs+zh2lr%20mEbB9LnB7h8i4VSRcGLxwduFtHuEv3AO0V9bbs9T/q26V8EGJBxbjlubh0ONt2G7LjcERtO/eQXb%20qjoSOiC5kOP4TIXFvcXtlFcT2h3W8j2glp/bsUGXLaWsssU0kTXywEmF7gCWFw2nae1QaIMZ+Cwz%207d9u6zhMEkfovjLBQx1LtvyqaoKWeAwtmyFlrZQwtgcZIdjANrnDaXA+JCCkPHsFDeS3sVjCy7n3%20erMGDc7f9X/8u/ig8WXGOPWMHoWmOghiL2yFrWAVcx25pP8A0u1CD1ccbwNz9v69hDJ9o8yW1WDy%20OJqS38dUHu3wOGt8jLkoLOKO/n/7tw1oD3V66/HugzXODWknoEFJPUMbvTID6eQnpXtVBasvvfSH%203mz1aeb0/pr8K+KC82tNTUoPJc4mjfmgqWA9evUfA/BBoOW8Qx/JLCKG7DhPZSGexla4jZM0UYT4%20j4JQqweFcudmYLqyvovtcpjZPQu2v8glcNPUj3DoQoJStrTU0FACKHTp4d0Q9CNo7aU7q1Sj0a00%206qErbQ/fuIoe/wAf+CDnEv3Xt3lZJ/52SwWdvA2OFrT/AJF0lPM52o9MuJqdKJMdUOhOjt7kMe6O%20KePQxPoHinYgmvZCjWZzhvGc9ZOs8li4JYXsc0F0bQ9m7Q7HDVp+RShLkN/7Bci456s3EMv99BIX%20O/T8i3c5gINGxygn+IWtk2lt3LRrZdpZdNaQgFjymSCW4tuUY+fj91HK4MNxG5rLjaKEtft2kinY%20/Jc7Ps7o5cnHz+NuiaR83HHtzRn3QnZNnsA6GRlw0MfuMbmubR3lbXbXw/cmLHNmO7oYsE2YLq6c%20V/ViZrBWeTuoywyw3gDjC61jPqPO4aHbWpPg34DxWns82WzS2KtLYbjNZFLIrHFP4a+y7/8A8y82%20vsbeZCxs7iH7ZpmjF2Wh1zoT/La0g/vXfw3ZJ1vij0+3uvuit8UlGcdwrP2cQhkykuGfeNDZ7Wfd%20CRISQfU3EVDRrWn9ypkyRWK2tmNV1ljdmQ4m5vWW0ETvQFzagzvnbU1fvj37QfitLNEx89tnfPPj%201XpHqlmBwUGRvBjY7l1pDJSB0sjvUBIb/KLq6gueQFz77p7Jm7W635o+3nx6r+jqXFuNcjx8/rW+%20Sjxr4mCF42CRs4qRucNAOq5lu4iy75YrE/h146LxFeaMe5PIslDm7axvIxZQsjLp3WBdG6drjtq4%206CmjitjHbbfHdFOnTisq11aLDZjkWQ5FkMTxXMO/To2NbcZG5DpNrHgaNBGko3bd1dCsmWce3xxf%20kjWeVvH6ETWU5w3HeP4K2bFbxs9VrSya/uAHXErq9Xk0q5xPh/Fed3PkM2e6s9ekcl7bYhqeQ4mF%20vIMY20E1jJcmkktm8xOJD2t3Ea6N+NKrp+J32Sy2aTy9Vb7Yl0O39wOc8bY2HJWo5LY/9uN9oPRu%20I6EAB4do74mvZen2vlseTS75ZYZsonvG/cHiWda+O2vWR3cbQ65s5gYnRuPY+oG1OvZdOy+26NJi%20VKJL60Z1DgRStRqP4K49bw3Rx6Hr+FdVAeqz8aVp3UjVZ7kuKw9t6txMPXeCLe2aSXyPpo0NGtSg%200FvxrKcjltMpycut4oXia0xEBLQKncG3NP8AuadQiEw2mmlGsb9I7UHSgRK4wvNdwog9IBNBVB59%20VlK66/D8f70GJlc1i8TZG9yNyy2thQb5DSpPQAdSfgEF6xvrS/tIru0lE1tMN0cjehCC+gw58vjo%20MlbY2WYMvbxr320J6vbGKvI/6e6DMQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB%20AQEBBj3+Qscfavu76dltbR/XLIQ1o/EoFhkLHIWzbqynZcW7/pkjIcNPkgyEBBYu760tBGbmVsQl%20eI4935nu6AILkkkUMT5pHBkbGlz3u0DWgVJJKFGNicvjcvYx3+NnFzZy19OZoIa6mmm4BBdu760t%20BGbmVsQleI4935nu0DR80GnzfDcdlMvZ5gyy2+QstI5InUa5talsjejgUG/Faa9e6AgICCxeW8F3%20bzWc7d0M7HRyA9CHiiCBccyOS4rl3cazkjYcKSGcduSavc2pHpyO1G4dqqB0L1GVIrq3qFIt1q4+%20YgO6dtOuiDDzOBxObs/s8rax3tsaH05QP4Hr2TVDkWR/pL9vJco2+x9zeY6IE1tY3+ozzHUN31LR%20TTRUvs7opKt+OLopLoXC/bTivDYrlmGhcX3cglnmuXepIXAANAc4eUadktxxbGkIsxxbFIhKHGQn%20ya69RQ00V12g5N7e8O5S6GXkONiv3W9fRdJVtN3X6S2v4qKJeOO+3/DONsmiw2Hgt2XDgZm7Q4kt%20H/NVKiK8h9ieNXTsjf4F0mJyl/WWZ7PPE+Vrt7DsJ8tHdNqx3YrbteNeaYlDbC85fawwXORxhuMf%20PEQchaAuMUzKsMMsepBqK1/uXE3XhrZ/YyRf6tfyqXhHIsPcPyTnXlxjo3mGKyr67JC0hu8D8opr%20VaO22WfFfSNInmtN0I1wGK1xfHbP0zUyxGR8rTtJ3vc4NfXpoaLmeUv+rlnTlK9kaaM6SVlm+WbI%2020d7bSaC6BcxzQe9CdfKmC+26ItovPJusZkGW9+Lu0nZkWlrY2Ws7RDJHHUGoLgS8jbT4rLbs7Yi%20aaSpE1nml0d7irglsUuyUiojeSx5odaV8O9Fhutusmowc9xHF5RsJvYWy+m7fA5pc0tLXVqXR7TT%20QLNt99fjnTQm2JeLDNe4HGWbsZc/6htZdv8Akr8tjdGTp5ZQdQ0DuNV6Db+Ytn908ejFONO+Pe6/%20Gsk8W97I7FZFu1skF230mvkpQiF5qHiv4rrY89l/7ZqxTFGbnOVSQn7PAW36tly6kkDCTHCKfXK7%20sKkfNZe06LuD4jFZXj8tfPdf5m4FZ5ZCNkZOpbC2nl1U1Eh2ODt4Gh6+NEgXGijQP2/ggqgIB6IL%20O1znOANKVB7+P9yCKe52OxN5hbY3/wB3HJbXDZrK+s4hO+3naDtkdG6rXN8QQhVz29PML2zt5uQW%20F/b3kmOZ+gxYselEy/8AVeC+aJp2tc8em7a4uaBVBuY8Jy9uaky8z712UZl7KLa13+WNsbRguNkf%200+k6atXdajsokq0GMsc5HlYso7GZW9y9lj8kMw2Y7Yn3Lw4Njt3muwu02bR9KkTb2jbmWOzjLuK4%20ixvrwvxgnEgbtfHWURmUveQH6VLv3IVdDQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB%20AQEBAQEEG954J5uCXIhjMjmTQPcRH621rXgl7o9dwHcIIRxzD5q4ubWwt7m7tsTfZq6nnyVpEbUX%20kIt2ubSP/wCGNshLKtGpFUKrsPI8uOWZK4db5OPDstcg3KWNXyTA29fRMZ6Me/8A+MNpUFBYt7rJ%20swOFGSyuTkw88N7PcXNsHOuGZElptrUupvIYwu2g/U7qo1Etmm5fJw/iUl9G85V17AMkBEC70dso%203SM/IduzcQNCpEZOO5XNjD93dZKcZuyzLMjA86R+g8i12d2Op0p9SaCxHb8ttLnB4luRnxVlb46x%20OHnla+RrpyW+s2UM0e+vl2u6N+SIq2zrflLZJsi+W8nup+Rm3it5WgwxWkbqN9Nrh5WHXzJOqWts%20cjy8yTSW0+RfmH2mQdyG2laTHbzMeG2vo1G1r9tNjW6EaoVdR4Rjrix4xj2XVxcXV5LBFNdS3bt0%20plewF4IoNvm/L2Qb1AQEHiRpdofpPSg79dUGsz/H7HPWTrO/i3MNTFKNHxPpQOYfEdigjvC+UZN9%201eYPkLG22Ss3+lZSP0bcwtO31Gu+gmvYJUTQbKkE9qHr4pVFBu00NNepHWgPTr8kqRD0BqKA6E6k%20/H+9EqCLpU9OlPFRQV27abRr0PxoCkjwC413N0prp1+GqVHoippQnxr80FQ5urgCakapURPEOdh+%20aZLFU22mXb+pWLaaNmFG3Ar4vJDgPgpgYOe9nuEZm5nvRZPxmQuQ6Oe8sHGF8jHVB37dD1KxzbE8%204I0cZynsp7rcavXxYD0cxgmuP2rpHAXTGin1itHE/D8VzN14jHknu/ulkjJMaLWIw2NM0UfLrwsm%20icBFYTNNuwyONS0Cnm8CuTftLsM1ttn4/wA+PtXTy8xHHskwC7tmtc3QTM8sjSRQEeNCO65F92SJ%2005MndHVqr7jOYbKx0BZlLZunpTOpNG2jaGKRorSvXWvyWzGe2I14/QiFsclyNm9sb3G23ENdFkWF%20rSABUMkpr4EkfvUTt7bo44+77kfBu3cgxHpB2SkbYu02umI2vodziC0mpNTpVYp2mSJmLYmafgms%20dWjyOGZzIQsbB6WFhoY55Q315HnVroaj+WPAroW542/Wt34RxxKlKr9hZ8p4wXzcUyIDZGhstnfH%201I3FpO1xcav3Dp16LcwecmZpfrCk2R0Ta095MXbugh5Dj7qwuHkM9djPWgc+lXHczVrRrqV28W8x%20X0pdrKnZKeY/M4vIxepj7qO7ZtDqwuDtD06LaVZJmaDSh0NCo7hVsjSK6gDqT2p1UipcB1/aiBuG%20g7noPkokeIwQ40FB3r/tUi4gx7HI2N/CZrKdlzC1zozJE4Obubo4VGmiDIQEBAQEBAQEBAQEBAQE%20BAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAAAFBoB0CAABUgdeqCm1tKUFK1/FBVAQCAaVFaa%20hAQNrddBr1+KDxJqaVIpqTrTXRBqLXD5O3zctyy8c/GzRbXWkpLnNlr9THdhRBsWRXgd55Gub2Aq%20KIL9djampGgQVD2mlD16f2oDhVpHigjfLeHWfIILed4ezKYtxmxs7HFoEwGgIJ1aT2KEPPE+WRZq%203fZ3BEGbsQG5O1I6O6EtNNQfEIhJWghxAB29QSUS9ICAgICAgjPPbaVmLhzVsP8AN4OUXrfjE0Fs%204p//AInOI+KCQ2d1DeWkF3Caw3EbZYydDte0OH8Cg9vLgPL1/wB6iRHOUcB4py6G0/1DYx3j7Jxk%20tpQS1zHHSrXNIUweyEcn9tOZY+Bk3D71t+Wk+pZ5M1JjAJAZJ13a08y5+bxuK/pReL2guuU2+Hlt%20rXkIlwVzLRsDLyoY+RoHqCKSm0gO7rg7nxOS3lFa8fdxLLFzdSy2N9AI7xjLm2eA6IUq0+B06dfy%20rlzjmyawvM+qLZL26D3l+OvjLGx3qNxN0Q62Y4VIcwCtdNAB0W5i8h2xSYpPr1mPSZUmx7ivslhg%2043sD8OXgn1I2ia2kI1IPdviVj7bb9Y14/ou3dln4ZLQPyDKnaC2eDzw7aEFzXUrQeH/FY5wxXQZj%20WWVzBIbWRlxFIPOG61brXcKEagrFE319+ORzaNvEH4u4fcYG7uMJcO0e61J2Pa07qGJxpQH+C6WD%20y2a3SvdH5KXWeqRYL3Q5FjXelzGybNbGjYslj2mTaAKfz2CrgXnoRovQbfyeLJ7XMM2TCf8AHeV8%20a5CyQ4W+juxHR0wjJ3NDhQVBXQiaq0bY1B0NNTQdB4dlNEAd5QQaj4Gor3+KiiTa/Q0Ip+Uf71I8%20yxvdFJG3XcwgV+IoEkc99lZsfbY7KcdtmiC6wt3JHfwMFGCWV7nkg993f4pUdJQEBAQEBAQEBAQE%20BAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEHmSWOJhkkcGMbq57jQD5koKQTwzxNlhkbLE7%206XsIc0/IhB7QEFuK4t5jI2KRshidslDXA7XgV2up0OqC4gt3Fzb28fqXErYo6gb3kNFToBU9yg9S%20yxQxPlle2OKMFz3uIDWgakklBVrmvaHsIc1wq1w1BB6EFBSRoc01IDaGp7j8UHi0lglga+CVs0Z+%20mRhDmn8RVBdQHEBpJNBTUlBatpYJ4WzQytnidXZIwhzTQ0NCPiEqLqAg0N5xSJ+egzVhcGwu2tcy%206DGNc2ZjtaOBprUdUG9a2nzPX4lBVAQEBAQEFJI2SRuje0OY8FrmnUEHQgoIvwaWSy/UONzmsuIm%20P2241e60nJfC9347m/gglJIAqenwFf7EkUe3cP7ux+aA1tK61qoiBq87xvj+ejZDmcdDfxx7/TZO%20xr9u4UcW16VU8xzzlPtJlobKM+31+3F3Eb9k9re7pbd0Yp9Fa7SAKVC1cuyx5Kd0cfwWtumEeyuT%20yPGxG3ktlNjWPo1tzGRcRue0eZ5LNWtLgKVpouHuPDXVrGvPjj8WWL+jaW2VsL2FsjDHcWkg3soQ%20+M0AqNCe3UfvXGnDdayTdVhXPFMc5lcVM/GzeZzjG4mOpOlY3eXSvRRbkmOcVOfJqpGZrChzri0f%20Cx5q2+sfMHkEkOfH10qs8X23e/H2en5kxTnpxxxDY4nkzprUvlYLyPYWmaAEP6eb+W7a4fVrosV2%20Lu5accdTuiUezXOHZueTD8EkZJkLYl2QyM7AbeBgNDGQ76nk9h2W1OKzaxF+flPKOszx1UrM6QwL%20Hg99ETNcZy5F+XbmT2T/ALZgIFRua0eZtW1o7qFiv/2W6J+SJiOOPZP00u4b7p+4ePlurXPWzeSN%20tj5ZLMNgmY0d3tefNoHVPivQbTzGPJGtbWKccum8X9xOK8oia6xutlxta6W1mrG9hd+V26mq7ETE%20sdEp3bWjefMfDxpUqQEjTQCuvQ0Qcv8Aay3ns+d86iu2GGS7vxc2rHDV8O0N3tP+GvxUDqO4KQ3C%20tK6oDXVDdNSK+I/eoqKqQQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQRD3cDz%207c5xsbHSPMLQ2NtQXVlYNumuvRBDLmzyHDsdcerLJirjkFzvsrPHvL7a0+3gFWunkDtokI3fTqTT%204oUe8RzvPuuONZDL3UzrTI4+MyWNpGTM26MZc+SeAt3ekexB0SiaNZb+4XJnW2Z+1vLh1jSxfFeT%20s3y2rLiYRzPNGtGg/LrTqUhDziMzdWkl7bszktti8hm7z7zlIio93oW8Rhi+nb5ySN9KHbohVI+G%20Zjmmez+KbfX8lrY2+O+8njZDt+8cLqSBj3lw8rZIo2v2jxSBqPcTLZC+z+Rxl3kH2sNlkcTHYYts%20Ze24ilex75dwadQ40qDRtNUIeJOQcvy0HI2Xc0cNoLbKW97iJHH1Y44YHeiYImsqXVPmO6h1p0QS%20PkmZyWN43xCzgun4uwvm28F/lGMq6BjbbcGitdheRSpQavIcxyQ5TjbDHX91eW5ubfHXzZmbI545%204C900TQ0l3QVkq0A1QRvi3KeQ4bBeng79+VmbZZGW4w74Hj7J0DnGJ4NN1C7TvXsiKtte8s5FbcU%20nllz4ZJeXFtFg7qJ4mlE08ZdKLqkYa2KKu4CnaiTCaVZ2U5rlIuYYzG2t5cTgTW9hlI5GUgmZJbv%20c6eFrQXHc5o8+7aOiFUv9qozHwexYQW7ZLoUIof/ANmTqglqAgICAgpvZWlQgqCD0QEBAQEET5NX%20E8jxXIGAi3ld+nZMj6fTl1ilef8A+t4oP+pBLEBAQEFH9KeOlPFBj3FrHdNLLiKOWNwo6ORocKHr%20ofFBz3lns7a5K2hdxS8/0xdRvBlMDd8crAa7XxuO1YcmGy/nGvH8VoumESzLOY8XiY7O4/7mIg/5%207HOdINsdKvkZQbSuLn8LM/tmOP0+/wC1eMjOxuctr21jltpWzRyNa5tPqFSaB7HasNVxL9pNs6xx%20+rNF3ojHunkcHisA68ZG2zyt410VjPESwGYirSaHb+8FZvGWXXZJrytVvnRq8Nax4LCwxWNtHNfF%20nqXx7zzAUdI8nWq528vnPlnunSJpCbKNtjr279GSbIelCwOBj2OP01rQk7dQf27rn5sVtYiytWWY%20nk2XCcfLcx3mTuIGwPuJBHayn6iwa7j10IK6VeyItjopOrMy/E8Tkm/5u2AG4vD4S6N1R5QRsLTQ%20eH9iz4PI345pE8fzVm2FePZXnHFbWWG2vDyCCEEst75+yRgbrsjd3O3x/wCPe23max88c+OOKYrr%20E24x7rcczrhBMJMVfBg9WG9HptDtwaWxvNA7X5LtY8tuSK2yxTFFxpa73Wikbqx2KOx41a4eoOh6%20FZY5CZuBrtDuvauvXUqJiRVjqiupB1B+BSBUHqPBSKoCAgICAgICAgICAgICAgICAgICAgICAgIC%20AgICAgICAgICAgICCjmtc0tcA5p6g6hB4mt7eaMRzRMkjBBDHtDm1HQ0PggoLW1EzZhCz1mN2Ml2%20jcG/4Q6lQPggoyys2MexkEbWSV9RrWNAdu+rcANa90B9jZPt/tnwRut9P5JY0s06eUiiC6I2A7g0%20BwG0EDWnh8kHh1tbumbO6JhnYC1kpaN4B7B3UIKfZ2nrun9CP13t2Ol2t3lv+EupWiD1NbwTRGGa%20NskLhR0b2hzSPiDog8i1tRIJRCz1GgNa/aNwaOgBp0SgrHbW0cjpY4mMkf8AW9rQHH5kdUFoYzHC%20F0AtYfRcdzovTbtLj3IpQlBcFpaB7ZBDGJGtDGvDRUNHRoNOiC41jWN2sAa0dABQIKoCAg8v31qN%20QNad0GFZ2uUhvpnT3YnsXNHoxFtHtfXWrh1FEGcWtPUddSgqgICAgIMDP4mLL4a7xslKXEZa1x6N%20ePMx3/0vAKCuCZk2Ye0jylDkI4msuXtNQ57RQvqP8VKoM5AQEBAQUpR1etf7kHk7jVrgHNcDXTSn%20gaqBCeUe03E8+6OQwyYu7a4SevYH0XPd1Ak20D2g/lOhVb7YmNSJce93/Z73CvsRZwtAzzrCR9zE%20+1YWP0ADWvDj5yadlr49nbjrNundT8Fu71RODmMEcRZcwTW9/bgMuLItc2aN9KFhqKVDtNPgvJ5v%20E5Iup/bXqz99YTHjWGuM9aGTOW7rCyZJvt7MO/mSg673k6BppRauTbRiurE1laJq6LC9npMY0AFr%20QyNgO0Na3o7pp/etXuol72sfTxJBIrXXpp+I+HRJmELT7Vjx5gQXHTbqeleo/wAJ791NuSka8f1T%20MQ1t/hrS5jcyeGKZpa5p3sBoT1AJ13d6rZt3F0T8sq9tUYs8HyLjGXx19xu8N7FB6pntMi58jWNf%200bEQQ4D4L0G28xERS+GKcaccR95hdzXFvy3Fni74SG21zcPrDckaH06CjaUr9S7OHd48mls6sfbL%20pFlksdfRNks7uK5G0EPje141Fa+UrYVqvtIBPTyjsKmnbVRCXr1WUrXSlf71I9VFaV18EBAQEBAQ%20EBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQUke2ONz3fSwF%20x+Q1Qc3w3JOXZXEX3LZL+K1wjHXTYMZFCHStht3ujEhkf/8AIdldv0oKY/m2RlyZjmvX/bzXOMht%20C2JoL23NqZZQ4EabnCte3RJGVae8GPltZLy5xd1aWr7OW+sHv2F1wyGYQFoYDVjnSPaGh3WqDXQe%2052btctlf1DD3ektha47DD0zMZbxrnbhIDt2mmtTpQoNz/wC0rZl+2KbGzsx7LuHGXWSDmujivpmg%20+ltHmc1pdtc8aAoMXkvPclgObXUDrSW+w1riW390yHYPRaJtr5juNXUaPpbqgvM9wnQ39xawQz5a%208uL82ljZMEcRa1sRmc7c7aNrW9zqgxOH+5OSvbfC2F1j573K5C2nvbydoZFHbwsmkY0SVoN3lAp3%206oK4j3NibkMhBftlkuXX9rbwW8bopI4orv8AlxbZI/KfO07mnzBBTPe4Nz+oxmzdJa2No7KW99WM%20Pc+Syty9rmfj2Qo2Nl7ix1nDrSa5x+Ktmz5jM1YxkbvRdKQIvqefIQdvQoMvjXPBl8q3GXmMnxd1%20Pai/sGzOa8T2pIG8Fn0lu9u5rtRVEo5ee517cZ3EyWtrNacdfNeie/k2FlwyyFHbW6vZ5qgVAqUQ%2083Huu/L2ERxDDZXAu8e+ri2YSWV5N6Y1ZXY93dh8wSZTR1BECChJ7BArQakbqdEEb5RwTi/KYo25%20i0Ej4HGWKSI7H1Om7c3r0VZivNFHO8x7c8+4/wDzMHcf6ltZH62l16cEkQ0aNjxSooubufF48kaa%20TC9t1GvtuTxwTm1yLZsVex+WSO9Y6FhINKRPfSrTrRcLd+LvsmsR3Qy23RPs3sGQjdGH+UxuAFG/%20T40p3Pdcz6Guq7NE7TtqRR1NSagUJNa1A7GnbxWGLbY4445LSuNfu8dpANQR4Hx8P28VS+2nxWtm%20ujU8ky2PwuPN5dnc7oy20L5HahoAFa66Ld2W2yZ7qWww5r7ccVumjl/M7+W/wZfyaRslk91LfFtc%20InVc7y1kBrpXUU76L3my8PjwR3Xc9K6/GtOvOHkdx5m/cZfpbf3+bn90fl6xVHriyyXFbsX/ABmd%20+Cjfbl1rKSZnlx19J0by4Nq0d9dP358k28rejqeOs3FK5p+b004+7Rv+E/1bZ7H3Is+cst7yCRrH%20RXtmKkCpDtzY6g+Ko6T6O4bz3h/LrQ3XHcnHfNDA58TSfUjDugew+ZvTulURCRBzNO+3v4fFKFXp%20n0ih3CnXxRKqAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgIC%20AgICAgiEPtlh4JLyO3vb6HF3plfLiWT/AOWElw4ukc1hBpUknr1QZMPt7x+GeKZvrb4ZbaZlZDQO%20tIfQj/8AsOqC0/2z4zJYW9hK2Z9vbWcthG10hJ9OaRspfU/na9gLT2SBbx3tlhLSdt1NdXt/fC4t%207p13dTepI6S0a5sXbQAOOiErknttgX5p2R3ziCS6bkJsbvrauu2CgmLCDr3oDSqDOyvDcRlLq+ub%20n1PUyFkcdcbX0HoF27yimhr3QYFz7b4WV/rQXF3aXbbn7yK6gl2yMeY/Sc0aEbXMNKfigu432647%20j7cQQeu6P7GTGuL5S5zoZXue4l3XeS8+ZBroPaPjkNnPALi7dPKy3iiuzL/NhbaOLrcxkDRzK6nu%20gyIfa3jbLYwPkupy512+SaWYukc++ZsmJNPD6fBBcb7bYVl3cSRz3Mdnewfb5HHtkpb3AEfpB0ja%20fVsOpHVBk8c4LjcHeuvm3NzfXYhFrbzXknquhtmmoij0FB4+NAgwbf2s47DftuXS3UttC64fa46S%20Um2iN5X16M/5iajwQXbP25xcOMZjJru5ubO3nt57OORzf5QtHbomVA8wHeqVEsQEFHOI7VCCgcHV%20Hh4H/YorUU2vp11HavUj+5KDy71Gka1BFKAft4pWRqs/xnjfIYWQZ3Hw38cTi6ATM3bSfzN8FPVD%20n+c9p+Q2Uon4hlCbY9cTfndC0UAHpupuB07/AIrRz7DHfzheMkwjmU5JdcYkt4eUWz8O+6cYreaS%20j4ZZANRG5hdTx1ouFufC3RrbFWWL4lILa/in9OkvqAuFXgVaQTp8a6Lj5tvNsLTMxPHxcr5Rze4v%20+SXI2kW+Bc+O2Y0NcaktBlAeT5gNK06L3PgdrGK3viNaR+X2af01h5rz931aYpnSvw4+HVHRyS7u%20pHXGQbbGaEuOHt5mB4cxob6022po91BtqdFv5ss30jjijL4zxlm3tm63W678mhz/ACvKe4s36Dxi%20zfDZ2zjcXtwHEy3G0mssp7N2+anitWfk149v4OpmzRZb3Ty9UfzPFLOCK4ZZMEpa50EcvloTBQPJ%20Lto1cfnp+/JZW7nGscU+Mfjz+Olbuu6baeldK9fzowPbTlXI+McksJsHkHWT7+4gtbsM13xvlbVr%20h4KZ9HRfo0AAK1rUAlx01okK0XgAAABQeCJEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQE%20BAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQQjm2e5FjeVYC3w8X3guYL59xYueIo3ehG1zHOfR1K%20EmmiDX/+3ZbmyfksZh33eNsLWG7zcxkbG63bMN5ZG0j+a5kfmPTRCWRiueckmZyCe7srOK0x999r%20jJXTlnqsdtLRJRr/ADAO121UdBrrj3YyOT46x+Dxbn5KfH3l5cNdKI22wt6sBDiDucXatFOykXbH%203OyUGItrh2PdfWOMt7BvIco6Rsb2TXUUb3OjiA8+31QXajqiUn4nyjJZ66yTn437TG2d1PaW1y6Q%20OfM+3kMbnbAPK0001RCSICAgICAgEA0r21CAgIKFoPXVBWg/d0QEGDeY6wvYft8jbxXcJqNkzGvG%20vU0dVBzrk/st9xI274flX8euDu9WIh0sDg4ggemT5dR2Wvk2tl/OITF0w+aef8f5XwK/ubTOtdB+%20pyPdb3sby+OYCm91aDZ8B8fms9szbbMRx/Nzdzte++LudHPr/KzPxDpGXLrj0XfbROcKFkZFatcN%20a9v+KmjoRLoPEJMNiuEmbF3Jx1/eOihv8htLjtLQHwgV/OT1HRVtxxdNZmYp/T8vx9NHG3ee6ckW%20xFetPWY5fdMcverT84yUTZLOygijubucMnPpP0ijcdWyObTzebU9ta10K2b7YilsRpxH40W8dgm2%20Jm78evv8Ke8156JP/Th7Qt5bya6zOSia7CY8tlgBr5pzJVm3xDdju6wOxEaPtNtCdtKaCg07advB%20EL46IkQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQE%20BAQEBBo+ScOw3IZbWa+ErLiyEotZ4JXxPYJ2hkgq0iu5opqg1157W8Oun21bV8MNvFFbOt4ZXxxT%20QwmrI5mtPnA+PySBcv8A214tez3k8kMjZL2aK6fsle1rLiHRksba0a7Tsgsze1XDpbO2tDbysitm%20TxExzSMdJHcndMyVzSC4Odrqguy+2fEpL2C6Ns9rYWwtfbNleIJvtmhkJmjrteWNFNevdBvcVh7D%20FQSwWUfpxzTS3MgJJrJO8vedfFxQZqAgICAgICAgICAgGtDTU9kFl+4HUkCpOnfX4fuUTAruYwV6%200FNKDUf8U5DEyOMxmUt2xZKzhu2DoyZgeKnrt3BWV0l89cp/ptwfNbnLTccnjwEdrfGG3AjL4JgG%20D1Tpt6PNG06dFFVnOsr/AEve9GNsvs7P7e/tHy1rBORJ5dQaP+kadvxSVJsiZq3/ABD+kPmM14f9%20TZSCysaslf8Abn1p5C7R8bydtBt0Kmtea1IfU+DwuIwuNt8Zi7WO1tLZgjYxjQzRutdOprqoomrZ%20naASendBUADogICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICA%20gICATQVpX4IArQV0PcICAgICAgICAgICAgICAgICAgoCdainh8UFUBAQEBAoECgrXv4oNRyzP2nH%20ONZLN3JLYLGF0ri1u41+lug6+YhBjcCx8dnxHGAVL7iIXkpdqfUuj67+uv1SIJAgUHh11QU2t8Ag%20qgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgIC%20AgICAgICAgICAgICAgINfm8/iMHZm8ylyy2hqGt3HzPcejWN6ud8Agv47JWOSs47yymbPbS/RI3o%20aaEfgdCgyaitO/ggAgio1B6FBrMnyTEYx0ovZjEIWsdI7a4gCRwYzUA9XGiC/jMvj8pFLLYyiaOC%20V9vI4VoJInbXt/AhBmIFRp8eiDV8j45j+Q44Y/IOmFr6jJXshkdFvMbtwa/b9TKjVp6oNoAAKDQD%20oEBBhy5jHxZWDFSS0vrmN80MVDqyMgONfhVBZvuR4exuDb3c/pS74YgHNdQvuKiMA01rtKDIxmUs%20cnaC7spPVgc+SMPoR5onmN418HNIQZSAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICA%20gICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICCCc+tbu35NxzkLsfJlMXjPuY7y3ha%202R8b7hrBFOI3EV2FpqRqEEY5tPyTKZPHyYXBXdk9gguMfOBteT6xMrHxteGRDb5nF1SQUFvI2vJx%20JyKCyt7y7s5LmK4vMjrFc/bm5BubJgLiHtbCDtc2nl0QWOOZDJ20772xjyE+Ixmfnjmsid88dtJb%20kRNLXEuLdxaAK1HeiD2zCc2usIG3ljdl77C3/kylr3NlbkXSEHXV7Yqd6Up1QroXmGy1vIwZPHX0%20mDfeZR8kNpUONzNIXW8r2tdu2mo2eB6onm3mZsuYs9u+Ow5JlxdSQvt/9SwWzx9zJbjVzdwpXt6m%2034oiGlz2Oysty4WljlWsktbX/R/puoLWVrq3H3ALtHbqF2+tW1QbSz49yaPPQZiQXjsgeQelcvMl%20Yf042w9TZGSAInTN071QZuas8i/3Dmfkra9uLWWCJnHprYn7eGajvUdKA4UdU6k9kqQjDB7gXOOj%20sra1yUV/jMTc215cP2sEt0JDUQuqdz3NrsdT+5TzJZNzxCHNTYmSyx2RtsZb2F+GiR72Si6eKt8z%20ju8zh5exKiCWS3EcyumWf3ttcTPZ+iOcJC3SSB03ruPxa3buUSirUZ7Gcri4/a46zxFzHfsdeT2F%203Fu3tnfkJHtjEbSGsrEd291dCpS7hAZDDGZP+4Wjf/1U1Qe0BAQEBAQEBAQEBAQEBAQEBAQEBAQE%20BAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQWoLS1gfK+%20GJkb53b5nNABe7xcR1QXUBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ%20EBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBB/%20/9k=" height="413" width="665" overflow="visible"> </image>
          </svg>
        </div>
      </div>
      <div class="fig"><span class="labelfig">FIGURA 2.&nbsp; </span><span class="textfig">Partes principales de la sonda toma muestra sin incluir el cesto. Fuente: <span class="tooltip"><a href="#B1">Azutecnia (2019)</a><span class="tooltip-content">AZUTECNIA: <i>Manual Técnico de Explotación de la Sonda Toma Muestra</i>, Inst. AZUTECNIA-División de Talleres “Enrique Villegas”, Informe técnico, Villa Clara, Cuba, 6 p., 2019.</span></span>.</span></div>
      <p>La
        investigación se realizó en la EAA Panchito Gómez Toro. La 
        caracterización de las condiciones de investigación siguió lo 
        establecido en el Procedimiento Normativo Operacional <span class="tooltip"><a href="#B21">PG-CA-042 (2013)</a><span class="tooltip-content">PG-CA-042: <i>Sistema de gestión de la calidad. Pruebas de maquinaria agrícola. Determinación de las condiciones de ensayo</i>, Inst. Instituto de Investigaciones de Ingeniería Agrícola (IAgric), La Habana, Cuba, 10 p., 2013.</span></span> y se determinaron los siguientes parámetros:</p>
      <div class="list"><a id="id0x4dedc80"><!-- named anchor --></a>
        <ul>
          <li>
            <p>Longitud
              y diámetro de los trozos de caña (mm). Se empleó una cinta métrica de 5
              m con nivel de apreciación 1mm y un pie de rey de 0,1 mm de 
              apreciación, respectivamente.</p>
          </li>
          <li>
            <p>Materias extrañas (ME) 
              (%).Se determinó mediante la separación de los tallos de caña de las 
              hojas, cogollo, tierra, piedras, palos entre otros en las muestras 
              obtenidas con la sonda. El resultado se expresó en porcentaje del peso 
              de los tallos respecto al peso total de la muestra.</p>
          </li>
        </ul>
      </div>
      <p>La determinación de la calidad del trabajo consideró los siguientes parámetros:</p>
      <div class="list"><a id="id0x4dee580"><!-- named anchor --></a>
        <ol style="list-style-type: decimal">
          <li>
            <p>Masa
              de la muestra liberada por el botador (kg): Es la masa desplazada por 
              el botador y colectada en la vasija sin la acción manual del obrero 
              auxiliar.</p>
          </li>
          <li>
            <p>Masa de la muestra quedada en el interior de la
              sonda (kg): Masa del material quedado en el interior de la sonda y 
              retirado manualmente por el obrero auxiliar.</p>
          </li>
          <li>
            <p>Masa total de la muestra (kg): Suma de las masas de la muestra liberada por el botador y la recogida manualmente. </p>
          </li>
          <li>
            <p>Masa
              de la caña derramada (kg): Es la masa de la caña caída del medio de 
              transporte por la entrada o salida de la sonda, o la derramada desde el 
              interior de la sonda.</p>
          </li>
        </ol>
      </div>
      <p>En todos los casos se utilizó para la determinación de la masa de las muestras una balanza digital de apreciación 1 g.</p>
      <p>A
        partir del efecto del contenido de materias extrañas sobre la masa de 
        la muestra tomada por la sonda, se determinó la influencia del sistema 
        cosecha-transporte sobre la masa de la muestra de tallos de caña tomada 
        por la Sonda Toma Muestra Horizontal. Se evaluó el sistema compuesto por
        la cosechadora CASE serie A8800 y el transporte con Sinotruck (20t) y 
        remolques de 20t, respecto al de la combinada KTP 2M y el Zil 130 (6 t) 
        con remolques de 6 t.</p>
      <p>Los índices de explotación se evaluaron según lo establecido en el Procedimiento Normativo Operacional <span class="tooltip"><a href="#B22">PG-CA-043 (2013)</a><span class="tooltip-content">PG-CA-043: <i>Sistema de gestión de la calidad. Pruebas de maquinaria agrícola. Evaluación tecnológica y de explotación</i>, Inst. Instituto de Investigaciones de Ingeniería Agrícola (IAgric), Norma cubana, La Habana, Cuba, 13 p., 2013.</span></span>.
        Para una profundidad de penetración de 1,30 m y una velocidad de 
        rotación de 155,00 rpm en la sonda se determinaron los siguientes 
        indicadores:</p>
      <div class="list"><a id="id0x538fb00"><!-- named anchor --></a>
        <ol style="list-style-type: decimal">
          <li>
            <p>Tiempo
              en la toma de la muestra (s). Mediante un cronómetro digital de 
              apreciación 1s se determinó el tiempo en las operaciones de la jornada 
              de trabajo. </p>
          </li>
          <li>
            <p>Índices de productividad (kg/min): 
              Productividad en el tiempo limpio, operativo, productivo y de 
              explotación. Además, los coeficientes de explotación de mantenimiento 
              técnico, de seguridad técnica, de utilización del tiempo productivo y de
              utilización del tiempo de explotación.</p>
          </li>
          <li>
            <p>Determinación del
              gasto de combustible. La medición se realizó con un Flujómetro, de 
              apreciación 1 mL. No incluyó el requerido para el traslado del equipo 
              del parqueo hacia el área de trabajo o viceversa, sin embargo, sí tuvo 
              en cuenta el del movimiento del área de parqueo hasta ubicarse en el 
              medio de transporte de caña. Se determinó el gasto de combustible en 
              función del número de muestras (L/muestra) y del peso de la muestra 
              (L/kg). </p>
          </li>
        </ol>
      </div>
      <p>El tamaño de la muestra de las variables 
        en estudio y los datos obtenidos en las diferentes investigaciones se 
        procesó automáticamente empleando el paquete estadístico STATGRAPHICS 
        plus 5.1. Se utilizó la prueba t-Students para muestra independiente 
        como criterio para estimar las diferencias entre las medias de las 
        muestras, a un 95% de probabilidad, en la determinación del peso de la 
        muestra en función del equipamiento cosecha-transporte utilizado.</p>
    </article>
    <article class="section"><a id="id0x5390800"><!-- named anchor --></a>
      <h3>RESULTADOS Y DISCUSIÓN</h3>
      &nbsp;<a href="#content" class="boton_1">⌅</a>
      <p>La caracterización de la caña cosechada mostró que el diámetro del trozo se corresponde con los valores reportado por <span class="tooltip"><a href="#B17">Mesa <i>et al.</i> (2016)</a><span class="tooltip-content">MESA,
        J.M.; ACOSTA, R.M.; RODRÍGUEZ, M.; HERNÁNDEZ, G.A.; JIMÉNEZ, A.L.; 
        GARCÍA, H.: “XXIV Reunión Nacional de Variedades, Semilla y Sanidad 
        Vegetal”, <i>Revista Cuba &amp; Caña</i>, Suplemento especial: 50, Publicado en La Hsbana, Cuba, 2016, ISSN: 1028-6527.</span></span> para las variedades de Cuba, con una media de 24 mm (<span class="tooltip"><a href="#t6">Tabla 1</a></span>). El largo promedio de 163 mm se encuentra en relación con las dimensiones reportadas por <span class="tooltip"><a href="#B23">Placeres (2015)</a><span class="tooltip-content">PLACERES,
        Y.: “Evaluación de los índices tecnológicos-explotativos y económicos 
        de la cosechadora cañera Case ih Austoft a 8000 en la UEB Perucho 
        Figueredo”, 2015.</span></span> en la cosecha mecanizada para tiro directo al basculador del central.</p>
      <div class="table" id="t6"><span class="labelfig">TABLA 1.&nbsp; </span><span class="textfig">Caracterización del trozo de caña</span></div>
      <div class="contenedor">
        <div class="outer-centrado">
          <div style="max-width: 1160px;" class="inner-centrado">
            <table>
              <colgroup>
              <col>
              <col>
              <col>
              <col>
              </colgroup>
              <thead>
                <tr>
                  <th align="center">Parámetro</th>
                  <th align="center">Media*, mm</th>
                  <th align="center">Desviación estándar, mm</th>
                  <th align="center">Coeficiente de Variación, %</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="center">Diámetro</td>
                  <td align="center">24,07</td>
                  <td align="center">4,56</td>
                  <td align="center">18,93</td>
                </tr>
                <tr>
                  <td align="center">Largo</td>
                  <td align="center">163,46</td>
                  <td align="center">31,56</td>
                  <td align="center">19,31</td>
                </tr>
                <tr>
                  <td colspan="4" align="justify"><i>*n=21</i></td>
                </tr>
              </tbody>
            </table>
          </div>
        </div>
      </div>
      <div class="clear"></div>
      <p>La
        evaluación de la calidad del trabajo mostró un promedio de la masa de 
        la muestra inferior en 1,31 kg a lo recomendado para procesar en el 
        laboratorio (15 kg) (<span class="tooltip"><a href="#t7">Tabla 2</a></span>),
        según Instrucción No. 3 del Central Azucarero “Panchito Gómez Toro” 
        (2019), lo que estuvo asociado al alto porcentaje de materias extrañas 
        (15%) y al medio de cosecha utilizado.</p>
      <p>La masa de la muestra 
        quedada en la sonda, después de descargado el material, representó el 
        12% del valor total de la muestra, debido a que el recorrido del botador
        no llegó al extremo de la sonda, permaneciendo retirado 15 cm respecto a
        la punta de la cuchilla (<span class="tooltip"><a href="#f6">Figura 3a</a></span>). La caña quedada dentro del tubo se extrajo manualmente (<span class="tooltip"><a href="#f6">Figura 3b</a></span>). </p>
      <div class="table" id="t7"><span class="labelfig">TABLA 2.&nbsp; </span><span class="textfig">Evaluación de los parámetros asociados a la toma de la muestra</span></div>
      <div class="contenedor">
        <div class="outer-centrado">
          <div style="max-width: 1160px;" class="inner-centrado">
            <table>
              <colgroup>
              <col>
              <col>
              <col>
              <col>
              </colgroup>
              <thead>
                <tr>
                  <th align="center">Parámetro</th>
                  <th align="center">Media*</th>
                  <th align="center">Desviación estándar</th>
                  <th align="center">Coeficiente de Variación, %</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="left">Masa de la muestra liberada por el botador, kg</td>
                  <td align="center">12,09</td>
                  <td align="center">4,61</td>
                  <td align="center">38,09</td>
                </tr>
                <tr>
                  <td align="left">Masa de la caña quedada en la sonda, kg</td>
                  <td align="center">1,60</td>
                  <td align="center">0,79</td>
                  <td align="center">49,48</td>
                </tr>
                <tr>
                  <td align="left">Masa total de la muestra, kg</td>
                  <td align="center">13,69</td>
                  <td align="center">4,81</td>
                  <td align="center">35,08</td>
                </tr>
                <tr>
                  <td align="left">Masa de la caña derramada, kg</td>
                  <td align="center">5,11</td>
                  <td align="center">2,41</td>
                  <td align="center">47,26</td>
                </tr>
                <tr>
                  <td align="left">Materias extrañas, %</td>
                  <td align="center">15,07</td>
                  <td align="center">5,29</td>
                  <td align="center">35,09</td>
                </tr>
                <tr>
                  <td colspan="4" align="justify"><i>*n=21</i></td>
                </tr>
              </tbody>
            </table>
          </div>
        </div>
      </div>
      <div class="clear"></div>
      <div id="f6" class="fig">
        <div class="zoom">
          <svg xml:space="preserve" enable-background="new 0 0 500 211.278" viewBox="0 0 500 211.278" height="211.278px" width="500px" y="0px" x="0px"  version="1.1">
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P2d6l2aHt%207jrMdjX7V8xH4payffS3Dgd2NLgG6uBDUsq9TYUtzHBj/q97c/r/ANOeYwHXkZGJ4iikbHBxOo6A%206ihWSCMjnv8A2rGLF4vl+P8AU3TSPZklbWPlOngO9VdyG07dJI0PChdNqiyC/wAL66UJZEisd4cN%20tiSPvH+H7a1NhofB/t+CkHT7/wDGkXIlxG24X4Fdf7bfhpQibQMugD0IQuCeYDW6DX41ruMoI/6M%20lSPi1Usl0UDRKrcSKGKA0KtrgfvNKUEGc+ocBHC4HVOSwyS5NBINB4/CluLpqa97IwTZE0t4B33o%20P8LVnuZbqhqVEJ0cv29+vx6/4UjPqILiu7d8evxqoEBry0DoB99iulDQhZeGgi/l0+46VMDBv1vp%20r0/b/CiAkNfGx7XF9EoELYwIFQ9vsIP7f4VLZpWncPYl9Usbai37ftckewMNAHYX8wHwv4fw+ApS%20UkgiCbflNggTohQH9vupktBbnEhCh1UePh/7S0QLcxQdZT5R+AstvsX9tFBasDcQL2IQi/X4/A/v%20oDcBQqdDrYgdtPsFvs1ogJQn1AideqL/AB+37acC3oJzvMe/j0Knv8aaRDsFuJF9D16ftf8AxogW%204ONx9Rqa6i9/2vrQCZOqTcFAAoAp8+V4yZAAUUWt2AXr3pCZHjmeVAapGvgqDv3NOH3F5DrsmS3l%20IttAB1PUKppJAmJdlOAA2AgLt3FAfu0ppDkU3Ic4qVG5Nx6Xsqj4pQShZ2rcXb8wTRUtZfhQmOZ1%20EPiDmkHyu6FOy/4U1YUDTmopuik3+BuU6VUiSFb2IvhcOsbofhYd6NRwTMd0RjToR+BLbqalsaAT%20Gu5tyDZoUEklbH8KJDaKbNEWi5RB0Q6a/GiHIpG3CF2pDSQTbuR9hspqkwgaczzKChQ2PQ/hTkUC%20kaFIcbXFytio6im2AphYABuBDeqlT8CdEqJGPNkZtKEBNSeyILEKlSVIyZmqhcNVQjRo0sunhTgB%20Rey+5S4NLdt11G4r40hhSSDshCi4I8ET/wBqkJEWYtJsV1HgAiG3eqTBkWSVzR5Gl0p/02XI3XN+%20tut6uegtpQe5Pe3BcFj7Z8qN2YgAiYVduuhIH76l2Gk2ZY/Wb29ETl5gc4BWQY7LuL9HEN7AEdal%20XQ9jMZ7s+u3K50zsHgGDBgeDG7KKGd69G6houKHYpUXUleyPph75kzcf3ByWREJA7e1mcskp0O5C%20UH31aUk2caHa8eB8MfppHqj3NCXah061Rkcw98fUfM4DleV47jcdOWkczbkvHla03KBQpIsKx5OS%20Dfi4U8zcey/ePEe5+Ghy8LJaclrWsyoV2vbMAjrHW/bWrpZMzvR1NGj3Xc5Dp2TV1WkSL9ByBT4n%20aPDQE0KwoQYjaLFS4C4+Fk+/7qJYQGGNG2zXBdutlv8A2drUwgDWeUt1cBe32L+K9aYaAkeGIXlo%20YvUoPA3T7qlQIqcz3H7ewwTlZ8EQ0c0vUk6le1FrJFbZM3n/AFe9lYqhuS7Je03axpHj263tSd0s%20i1w2eZmM368sLiOO41z7gNdKQAVKqR41L5OxrT2s6nEvdvM5HMe4cvkpgGyzPX0xfb4a969ThTdT%20gvk2UjlTy/N07D41o/EmRuQLFIAAw+YXuD9/3Umnl1Gme6PZDR/yDwYc2x47H3N+MTV/y15FtTq1%20Qwdg3p5jbe4WCJfaNAoq5M0LCAeYo07txagB7BP3a0ZhqAix8wDr3sEJcmuvTtSBA3HcEHzuIXRE%20N1736D8aEEimFoRxatl+zXpb7KGOHoB0h3WCuX5QPgRemhZAbM4bSfykgKFVEJHQ60mhjxykCEBQ%20vfsb+NxSgctGd9zfUr2x7aIZnZIM71LIYzfyoSN2gPxqWjSibzOa859dWZUjmQcnFx8RFmwFSgP5%20nIijwWnsfZ4x8TVVUFO/6px5cTsU+4/VbM3Y6Bz0aSVCafK7stCo/HGOw2q/T44+JL9vcmeGxJMr%20jnDjJt+x8oRocx1xucUG21ESRSqbh4xjMtIff/uZzgW8yZL3B2kEECxK9Rp/ZSz6F+nRrH3/AAxp%20Ij+oHu9GPZyEbwQoIY12hDitxZLUZlenXGPv+hPZ9T/dwdGHvx3NcSCDECtibIfmvephg+KvfGPy%20JEf1Z9xgOdPh47moCBdpPmI7FdelGa8RPgnEllhfVyDcP1/G+mGnzmN6oilSEaKe4l8EYxJuOL5z%20iOVhbJgZDJ1+ZoKOB1ILSFtdf2FCzMLVa1RKeUapOnWx1Qn71/fVIzZl/qGAeFwwFCcpi9U0kHTU%2069qbKqatxvcfIACEPQBdf2v98is5Y3L8qHU9e51P7/26VUljWqIDckrqb6fCrIFBvkUIvQ0pGBLE%20N6L+PjQIUI5SA4tI1BB18B4a0pQQxTYiUJIJOlwR+y0nYtUY4wq0dBrdAmhXt1/brBrVilCL0Kke%20GjtVoKAQNxVF1/gUX9v4AAU6nW19f2SgQEBagChLol7EWH7qA1AUv4rp436+NAwENJPYkqfAnxTx%20/voFAkjrr3vp9/YH9urJdRDrLqAhRPFRofhTWZm8giCSg0WnJIXoo3e6zRqTYIPwstOR7SM/keIg%20layfOhY952tYHtLi5U+W9J26F1oy6qDUFAAoAoOTcG5cpJRSB43ba9UkSyMJXbi3cbq1o0CgX01T%20SklAshbHrt3OQKS0myKSig6lVppAUOPz3uPNnzI+N4B2Xj4cxgdlHLii3uZco14W3fSuf1rNuK/W%20D1//AG7hrWr5OXbaymNjcfFEoZ/vZqr7XTwGfB3+HYUeryf6fqT/AIftf/P/APxse/qvvNCP+VrB%20VXkMZfH8vhS33/0/Uf8Ah+2/8/8A/hYP+q+9R/8A8oB3B5CBCncdaHe/+n6h/ie2/wDP/wDx2I+b%207n9xYDsaTkvbZxcaedmO7JZmRzFrn2B2NVztOlL1bKJrl5lr+P4bp7ObdZVbjY1p4svJGvZIe9ks%20vQ6eKV19DxXkFG+Td0NwT8LdvCgfiSWSu2AblBF9SF1UrrUwPzGiSXADTqVTqAmo70xT1AHu2oQB%20Y3Gp+zXrTAXvV6kBVUgfEp++gJFNZuaqBG69/lTx6CkxiCxxClLC/wAbJ1oBBkvOgAKG6W7mkNPu%20NyCTa9zWhzmtcWNRdxAJAP20CkoPY/u+H3LxuRkjHOFPhZD8WfFcdz2uiJAu376lZl3UF3k52HiI%203LyY8fc0lm9yAiynr1/dQJKTH+5/qRxPEM9DEcOT5OQlImEOiaCnmkeE70naNC9pzD3D9RfenJl8%20MOXBgMLdhOPZ5a0IQD000AqXySNcaMFJmPYJXF4Mjg4OmcVkctvMXX70oLgj8NLi8U9/McrgnPgx%202lsUT1DXTuT0w7rtJ1Q1rTNomzhHQeF99fSySOaPN9to3JYJXsYNwhkAG8tf0B18K0dTHcLH1e43%20hs9rvb2Rkvwz/rcZyCuYSWhDHN8w8L0treiFK0Z0HjvrV7HyONiyM7Idh5siNmwkL3BbqCOlE2QK%20qkyvvCDgveUWbyXETs/qmGQ+KF6tMkOpYC5Bbx6Vhyrd5m3Fba4ehzrieQnwZRlYsjoJ2OEscjPm%20bJHoqIUKJ8K51bQ7LKcYxJ6M9ie9ML3RwbM3e1mdAjM3HDkR46jwdqvauzjvuRwclIZbZnuDg8Bm%207MzYomiz9zkBUpop6CtJREPsZvkPq/7KxRtjyDlELaMWNyt7rc1LuXXitJmuR+vkTS9uBxrpCTtj%20dI4BbWTrak79jRe2bMvyX1h97ZcmyF0eJEd3ma0qNdXHsBSdn0NK+1SWePDx+BmuR9ye5c1pZlcl%20NI6QOa1nqObfS21T5SNAKy9xZqlnOi+6T0P4zi47e4onGduvn8vpH1O1w/Qn2PncdiS5TsqQuhjc%204mVwXcN1wSet1P31FeCOrnTXH3eQ7/zF63cU41n/AKVjEjsf0B9gsLUGSE/+abrqDc7rmn6C8e/x%20xjUj/wB55Jnbx/8AL2Db9AfYbQWg5XmAv6qaFN3+8Tcn7/EXAl1fzx8tPAp/zV/9HH/yjbv+3n6c%20PfvdFkOd+dZSC4XsUT8B/GqXG0o3W+Zk/wCUt/o45/3Vj5nGfrj7G4D2jy+Bh8LG5jJ4TLL6ji87%20gdoKn/Zrq9i2uXa242/eT73bye0XLtrW65NsrLLa2cxIBAUCwO1Lf4fdXqPU8BZHuf2Xb2DwhCg/%200/GI0BX0mn99eVf9zOpftI9w8hjgGhUI8waPiCE3dqZmEAdjdtlLWsRCArupXU+FED3CmEEjYfK2%207V1uFY1R8NKQnApDtVACLFwsdyKieCrpamN5gcZAoai3BBVEF1/FVoTATcAXUAfmO3ct1NtVWgEL%20bvBRwHl6BHWuC7r8KAyFwvIe1yIWkOaLap95saIBJScd99fTzlfePtuB3ERxPycPPyS/GnOx0zS4%20X9S3QURma1vByXkPoZ9ThNI6H28WsDtzWRSiVrWHoFuU7mq3BvMtxHt+XJz4sOYGKZkxbMoAc1zL%20ltgi/t8B2Gzqfufjp832Zykex0Rha2WJwIdvMVkIFSqwTJxSH9SWrG6QgISGqU+7StIRo7sdhzuS%20iB9DLnYSgdte4afKbHwpQh72P43I886fbiZWU+bQNY5znJpoO609q7i9SDU8Vj/VmZm/Ajypw1X7%20XEF23Q2errl1DqkD5u/fGPkSD7k+p2Lu/V4ji5UcXxDQFPMWoBUvjQ/8hJ4x3NR7DzPqr7ny2v4P%20jIohEQ2Tk3b44WbbFXk7Xd0qLUQ3yJo9DcZl+6+Lw8aP3C6DNaXNhfn45R25yJuYvm0vS6mMIb+o%20zJG8JigldvJYm49LvHQ0SSjUPcdxb0CWBA8dKEiQjcEJ5nLu1uev3daaJaCELuvgQncBUo3BA61o%20aR+ZPgV/b+zvUtlKopoBKg26uanhp+P7JSZSSFdkQaaJ3Fgv2JSNIAoAUIqBPs07/d40BIRQBWrb%20Q21KJ+8f3UCtkJ39emv2IeqL+SnBG4Mlxt9hsqEkj9v2UgNwbXLfRSD1KaGyfH91IpWDAJ6fdQUE%20Ttb5nBni4hF+1KBFdne5OAwgf1PIQROGjS8KqHTv+32klKrehnOR+r/szD3COWXIlYFLYoyUaqLu%20pLPQ0XBZ/EzPK/XeNrf+A4wBpUNfkPCEtPZo7AfZ9lNJh/jypZms360e6skO9LIx8Rtx/KG75QhT%20d9irVQ/iP0uOvWXjHn4GT5D3xzOZbO5XJkG3zCOQsBIF02IO4qtmo68vFXNZvpOPqROH5AP9wYBc%20x8r35UIEriXuQPavzFf7PG9V6cZeGPPt+ZNvd0mEtfmewaxMgUACgDN8q5M6e5AsHDUAIPMRfUmq%20RFmQ3eZzr7S8k7UK/Ndq9+tMmRcbgZDcAuIINwoW5BKlRb8aAgj/AE/J9HmiRb+oSp20WxPZE1P2%20Vy8HXzPY/kv/AA//AE64x+ZqyEtW55gotcNQg7+NACU7/b370AZb6jBeEw0Cu/X46DVb6bbrr2rD%20n0Xmj0/4r/vLf7lvsLOeXc956LcFdCupv1rpPJeohsgXcDa5aTcIbqlMVRw5PU6Aa6DRRbX7acQC%208AnSqeiahrh10Q9brQAkPRBuubDcuvxt4UQKUOMetvm1tZe3hrQ0NMfEm0hyjyjUqiVJSYT5mb0J%20RdAb6/E/YtEMJEnKjA1CfnHS9wD3o2sE+xFyOUw8ZrZJ5WMaXENLkU9gBdVoHPY4nzPvKb2X795W%20bhw2fj+bayR0bj5GSizpGgalRdays4ZvTj3IzPuTnpOd5KfkOQzw+dgDC2AEMaw9h06VlubzLVOh%20VZOdi4mOkEgx2uaA56Fzz8B/mQ96azYaIgPz2MkMWFA6VzgHuyZrH7rAGq29wlkbj8DFfmQs5TIZ%20C7L80YkKBwWwHQVTnoJuDQ+4eHc/Egx4WkMe7cwNYXhxan8O9Tx3jGYrpPxD4OPBw/UwMWAf1B8e%202T1WbuhBVQWnvTd7TL8idijUz0ns7m5GEQZUWVGHuO7YWlqlS1qDQXrb1vAh8cakDO9q5HG8lEZ5%20w1jmh8pBAO5VQDsmhFD58oH6TLnD90vwmT4MWc/+nZDUnxS0OBcl3NcdCU1rJ3bLVEiul5GCINEe%20/wDTucNjntLSF0CgIU0rHb3NleGT+O5bHgc5zMmSJ8ljtO0Ef5Tovh/fThilNQSZ5YMxz3OmfLI1%20w2tcfykJ1PYJWsrUvcksYf5jcn/DAMki2OTcD4C5PgiWSrpVPMz5vd7clktEMfqnBPTCAgktKO6X%207BF/d8K0SWjxj8ehy39/njX8c/j5keSbNdOGDcIm/MvRSRbrZKaSXTH9DnfunbNYx2f4jnoS3e/5%20FDnvddu46lxNnAp/hWXuP2NLH2fd952fxHNu93xL/a+L0xqezeKVvFYKja8Y0KjQqI0Q1NHNUw5v%203282RfcfubhPbXFScnzGSMXEjCbkc57iOjGNVzvgKozge4TmcDmuIxOX455fg50YmxnlpYSw2FiA%20RpQBN6DsNKAPOH/dE7//ACDihuKjGKNTQF+vXVK09mv+3/4fvO/nX/8An/8A3l/9DOJsahsPlBNt%20L/316ds2jxJyPcvssk+xOE6f/b8ddyt0ibrXmX/c/M6V+0iE+Z275QSbgKVKJ0U9fDrQSBz0G7cp%20LQS7uWFL9qAgBKXDtEIKgAqVRLJ0NtBQxSDc4tUINtyUVGm58D/ZQAA55IJXom6xcVNl1NvlpgwN%20LmK4oQ3UC62umlrLRAtQDahbuBawXACqCdV1ChLj+yiByL9RoO6zdoKPQWCa/AeJSmJkbjMFnHYf%206aJ5KPdK55UkySEm3h9lCGybE8iUXcgNgCnlHlIAJ8f8aBI8ocb6f/M+bECHP/qs4B6hXFNf/eqH%20r9T0FHptdYOm4nG4HImfjMthficg8QTsa7adhF9pHylQv8K0OFj3uv6MfRb2/wANNyObFmY0DUZH%20FDM50s0jnHZHG25cXaCpljRhZ/ofxPHcXk8xzmYeGjewPw+FDvXzdrvkbIv5upq6y3CE7lFg5HGc%20VEYOKjDH3UhPVeCPzLeyr4V114zntZkpvMzI2UCUAlwL1eHABpPmb0UqjetU+JJxlOMdQTjQcHL5%20ciNdlSsDLbg5S4C5Kf231o217TjGMxS9TXe2PfXPe2ZoWylwwJWNkixHlro3MJXe3VzXH4XstZW4%2009NSt7zOvZ/Kwcr7ZxOR44umhmmhLWxglzTu2uag+VFvXLaucG1bSH9RbcDjOc5R/UsNUCC0ul/C%20ocF16mrkCGwU7RZxICW/DtTRDENAUoQvcjUJtHjTFItjiQAL2KL1vqdfiaTQC94ap6JZSOo8fx8a%20iBq0Aa9pFyCovr1Vf2/tptDVoFlwP2jUdz2RRqmn76kvcgFyhyG6aa2PTsdaByG4i4dddVva/X4E%200AxouKqeq20/v1/ZaoxkADkBANhqBpof3iiBSYD3p9R+X4TmJeJweME72RtkbIQ95LSOzQ4DprRn%20J1cXHVqW4MHyv1q9wCUwSZQxpGu87I49j0IWwKGxtpSVHGeRW7jXjj4GT5L3xzWdv9bJzJmkEBhk%20dtsqpZpC1a4ibe8otFpj4kJ2dy0jnOGMxJEDmOAJQHxJuHJdarYlj5mT/kNI8frnr5fEUcfmZ3Hf%20IQ42LQCbppYqdbVSqkYW9433x56aYkTH7cyJg575XuMg3v3A+UsUENHcU9sdDG3uL9Jn7sfcyVF7%20XaA5x8/zBHL069V1vTz6mbvGk4xC+RNZ7dYAWlrQ0IVRSU/s/a1NKcjN2f8Ac/64+4s+F4ONnLYb%20toA/UxOO2xI3XC2UIbVLSSCsJ/JfJ4/Hqema5j2AUACgDN8pA93IToiOTQEJYXIvVJ5GVtRgNb1a%20VPQhLOQOGvTrTE0KbC1z26ElxJuupX8Pxoke0h/T4fyeaI0PISoUIVAh+P3n7K5eHr5nsfyX/h/+%20nXGPzeoni9WCWLc6P1GuZ6jU3t3AhWnu2tzzDlHF8Ji8J9YeN4z2tl5k7IcKeX3gMiZ00AbIB+lc%208uUNmc/fZqWoWozrX4fHWgRl/qK0u4TDb0PIY4I73+39xrD3Gi80en/FOOS3+5b7Ca+NwkQgtepC%20WQFz1Lv2NdmR47Q2hO0gjuCBo7Xd1+CUMQbGPQABoBCNCqLjQ+BWiAgUA4Idy2+a2p1K9LGhhIpR%201tZDfQW7qvT40MBLpAyzyBYksVFGh11oAzvuP6g+3uBjeJ5/XzQFbiQq6Q+J02rUu0GirKzKn/qJ%20mchism43jzEyRu71spwa1QPyAKXfGqSJu0mV/Ke6cmPDMvJ5YihcSDjCwd3DRr8L09otzZzv3B9Q%20MzMyBBDtLReIF25wAPza28KnkULIviSbzMbzHunCdA9mRIJpg7fG4E72u6+awrmXC2zr31SyM+z3%20HjNdtLH7LDe224FFKa1ouFifIWGI2Pk4pJcV7vVjRsW4qWkqCGr4GlDq8xa6ajufyUvFw4+LKv8A%20OaN7i4glCgafCitd0ibgp+R5aLOyv1c/pGX/AEhG4Oc1gboIwCPvrZUM93YmY/PSCJomz5GNa0OL%20WuIC6lLr+NS6FbmFl8viyP8A/rXskah9Rrumvm7mitGhOzHMX3DBjSB7c2Vz2o4MN1cttEBHhSfE%204BWjqIz/AHPjZ00s+VI6aZ9917EgHa3pbQU1xPoG6cg2e5eLBjhbhiNkR8srbuBHXaVB0WqVOpLs%20yyy/qDjuxv05j/VwOKmB7GgeCIh/Gj0kCtmZ39XhZErvSH6d71Vu5RfQNW/2Vm+NmyshyDkJcKQB%20+7c0gXX5LE6KtLbIk4NhxfIcfyEU5yMgiSIsEDnNKmNw2pZPlHjU1tt6Y7GPPw718C3g4vFlLGxn%201mvaqMVoH+ZdflI6CtKck98ZHLycDWbZIh4dji1sbS9xCIjlcft6oLfYK2ySlnHe8TnksfHpjIVl%20YTRjPe9wAYrnPCgt6qpXRzf7qz91/wB3adIxken/AArj3nGl/rXj8Ijxy7weoeKJPF4RdZzseEu0%20GsY6ft/CsqzCnU35v3282Rvc+A3O4DkIRjNyp3Y836aMta93qOj/ACLo6/Q/21Rmys+mXHchxv0+%204DA5GF2NnY+I1mRjyJuY5SSHJ1oBmm6g/voA84f90Q/+/wDFEtCOxXN3Lqj7gg9BWns1/wBv/wAP%203nfzP/8Aof8A3l/9LOLMHleV+VpJP4JXq5SeHOR7g9mhv/IPDDVn9Ox9Oo9JvYDpXk3/AHPzOqv7%20SISQ83Jc5dxA7gofj4CnBDEtkIAcCqoUOg2DsDqSfxoCAjbyj/dapRBqBcovfxSmApztxuXNc4qC%20qFQg0cnQfjSDQAkHmeBoHEdUuuhVe1ACt4a5SQdvmaCdV2oQFN72NMHmGuxoU+WMDcSERT4EqO4N%20HQUiiu5o1JcU3G6GzgCU0/GgIyA0khRfTa7S6ECxRF0KHpTCByNzRICVuUKlSSGollX8KQNdDyZj%20578P3hyTkdbk5gCAHDc5yDuV6UuqO2tor8Ptx5/YdS46UYuW2cybIYpRJIXptG03VxPareZxtEI+%204ea+oPvwy8A1npYHl4vKlbvx8OInbJnuaSjpnn/SFIbyMr9W3e3vb/Pw8JBNkZeayMS8pnTuMuRP%20M9Xbn3ACOAIAArficambrJiv1THRiZha+NxJO1dpLv8AMDqfMh8K6VqRHQfZymWzCkwvV3YkzxJP%20jki7mBA4u+ay6aH7KUAmNfqQHBBseQ9pcChJ1Qmzu37C9p9mBJOSXnbHMRK8AMBJu5riLqSi9PCl%20MeRKr8zpv0r+pb+DwJ+LzMd+S5soMcZIZtLrORwsg1FYc1JcmlX0Oqe887EyvbOBkYsrJYZOQwy0%20tde8nVNCDZK5LGieZsnkOcXakovT5QOn7fhQhNsXG5qoRqfvKX1+P7qmw0gTPjY0ue9sQClS4NHV%20blAn8EpII7EXDzMbMZ6mJJ6sO4tErF2bhdG2ulWLMktjB0PzW6i6gpSdhA2OF9y+KdAFGp7UZAKa%20FAI06duq/wAaQFVzPu32vwzF5TlMfFsobJIN3b5Rde/99LxKWZhOb/7gvaWIrOMa/PlcPISQxhva%2051obBI5p7m+snuzmHyCHOHEwNAAhgI3ICFUlbpSTc6DahGIdz3MRZUmZBzmccuXyyZC7nO7XO7to%20K0TFoi99o8LPnYv6vkHSZGU+VyyTBXO3BQh+/XvV1aOXns5g2EXBQxtBaNF26EneCdfNr07U4fU5%205bx3xiCSOKx2IGBu1jRtDWlEaLH7tyffTjLGOwdMY/GO2j4w42rd1gEFha2txoCunhTiRvq8Y0/E%20UMRjbkJsQkaaXIARtyB2+2iFj8SIxiMw/wBKhI2EI0K0dQB0QOP8NaePHGOoNRj8sfMJ0TTuCKSQ%2026hLAdCUvbx6U4SWMa54zUdPLGPtJnGR7uRxnMbu3TRFg6LuTS53X0GlEdljH1Kqs12xj7zu9cR7%20IKABQBT553ZUjToEJHigC/hUsUEGeFiEggB3lc5oVFW90106VVX2JdWR2PO8AkI4sG0qACDcEAdh%20/dVE7uoz9PwfS5olu1eRlIPcIE18PE/ZXNw9fNnsfyX/AIf/AKdTS5cc8mLPHjy/p55GOZDOgd6b%20yEa/addpvetzzDAew/p17x9rZA9T3JFn4k078nky7HaMnKkeVLpJbuUKAOwogDoifdoKAMt9RgDw%20uEFG88hjoDdSp6XX4Iaw59F5o9P+K/7y3+5b7C4yZGSF62S7VFwEVe9q6FKZ5VuxDDC1STZoNhf5%20bA273/Grkhjm4KUVxH5upHx+376NQSgi5/N8fhn+fMNxPljahk16AXTSlBRnOS99sxoTMyIMYXbW%20PK7iXWQMbdT8Ke1kz8TI8tyHuHlmNlEjsdsZJa0pvJJJ3L+XulN0EuRdCjxI+Jw5gx0o5Lknbv1J%20d/MPmVQfmG6xUm9ColkN2bJWfy2Nw0Ihx42tYGkxwqS0O7OcqNF9K0SnUiMjlXvH3Tk5eUWPd6ru%20j3XDSmjGmwt0SqUYxjQqDGZeW5r1e4ulcu55J3ABQeqp2Wk1JSZDkn3AoERPMTchNFoaHLYnd0VB%20qo0ShoUlx7dM7ZJJI97tGljSrXLop1Ua1jyJRBpxyXPPZmXA8S5OLFyHGtAY9pQSRLoCRcL0NZ8a%20nTI15MvEyufkYUs7XYOMcWMNu0uL1I1ua6K17mFoIoLhbT/NcItXBL8QKlzp2AK0QGoe5tyNNe9q%20UAHvdZHfA/t3pRISAOK9b6hacCkRuIIXr1+FA5D7ftp/hRAFpicpsx/TyYzOxrhte43aPBaxvx56%20myv3Lfj80xv9eFvztCNcA7c1b2rKP1F2eUo6X7bHEz4TpMJ/pmQndHISS0IBbRzAK6KLLI8v3N7P%20VwvsLx8XqlrHxENcoewEFB+S+osqCmkcqbTmSPm7ZYv08bgJ5ml0EBkLJC4jUKht46JWXO/0uqf6%20n92Pqep/E0dOWvNar9KllvtGSOjYX1glhw8fHd7eme6ONkZIyIALMAXb0B8P8eaq5K1S2PLxr+J6%203JX2Ts3/AJFf+Tk/6R7/AKzuRT7byFRSP1MOqga/j2+2qnl/0P51/Ej0/Z//ALNf+Tk/6RnN+uUO%20HjyZOR7fyWwxAmR/6iJ1rIgAUqth96U16reVH86/iHpez6e4r/yX/wCkpv8A+5/22h/+zZK+ErPH%20w+FXs5f9D+hX+P7T/wDYr/ycn/Tj7OV/V76h8d735PEzsPFkxRjRek5kjg4uJdu3BAB3/Za6PZcH%20IuV2tXaoj6+Ae+5uGvtVw8fJ6j9TdlWyhRH9yRg1G16nQff9leklmeEz2rwaO+l2Bun/AEoPExLk%206emfQHn7W1ryOT9z8zrrkjjGP7u954XIOwhy8Wa2KZsWPONrmSMd8pv+PY1ExqQnjHc3eb9RPb3H%20RxjkpxHkOUvZGr7i4J1/N31WrVhZEfE+rHsvKyXsOS/HjDS/1JgQ110LR+1zSXImEGj4zm+I5Rj3%20YGZFlNj2+uGOBsQD37a/CqWYQRPcHunE4fyTxyyzPCtfEzeAEAbvF9RStaBpdDN5X1KyoY5JWMiV%20wa2MAq3e4E/zV+V1kqd3QRb8N76xpuOGVykTcGZrnMLdymQgAeUancO1UrDiR/mvd7MXgI+X4poz%20BNIImAlSnYqpHc1j7jnXHVtmnDxK9o6HE/ef1n9743uaR/F5H6Rpiaw4pbvaHBSHIVQnr8Kr2/I7%2013PI25OCtciNhfXX6iuxMnOmz8cTY/8AoudEAw7gQ7cANbIKq9mmifTq0Hj4WA/jf6yHepnclL+p%20nc5EL3XOxUUA9q873HurV0xjxOzj4pyYrMyc7Mwp8aeV7saf/WSy3Q+YDqorm/z76SWvaVHeC5vm%20vbGJLjcBM3GZK7fM0Na4vcAgV3ZLdqqvv75Zifs6MwnvjP5Xk/cmRy2Wkk+WGvkICIQC0t2/Cvd4%20JvRM8vlSrZ1KLEypMeVuoYVDwAqqEUlK3pZolpMtTkDYLK8Lc+ISujckY7QnTO0BACJ91+lN2BVJ%20DXB7AHBd5UBSACl/uFKYCCfx+VN6g9SUuhYEaxF/8Ka/wpblotQh6sv+P9wZWPOxzXODmSNmY1dz%20HGJDcN8tnVNqqMYx0BKHB3X2h9TJuTjnfzWF+ijZGJI8kNc2N5H5bjbu7JXlcPO7WajQ6+XhVUmn%20Jgfff/cp+g5M8d7dxxk7P5c00iIHHVzTooroafQzpVHOcv6xczNyssvIOk5CPbsMbnkRKhH+mEBK%20Vn6U5ybqEOR/XL3Viyg4QkZgAD1Io/L5Uug/LT9JxEktrqjpP08/7jcbleSx+J5t36J079jMt4Aj%20Q2DZHAW+NVtfUiyXQ6N7k5z6mxvnHt/gcSbGYC6PkJ8hm17EVWhfDrSZmcSm99fV33Zn5GFDDll0%20Lts2LiD09jbjcXNRyFw1NDQSjLe5+A5rh+TbHz2EwZs+15c9/qyFdLkOuaEmG6cihxsbGfM+V2O6%20QxADZC5pRfm01CCqlkqyZpG+2smDGx3nh5mY+S0OjyFCEBb2W3cVFrP5lKPkPs9sZDGY+fkcLkvi%20mmaI3uKEkHVoPfT7qW5scJam94TisjCxT+pxX4MsrjN+lnQuaHixd/4Qb10cc9MYk4ef92MfkXno%202O4WVUICkkED4q5FKf32oa7Yx8jOfr8MPz/EV6QVQA64DmlUVehsulj/AApt555Yxl94Ke3XH5fD%20pogxt27QocGncSNUanyjop00o8f6a/cTDxjTw89ciq9yc43hcVuWcY5O95axrNrSChcFQdx3HeiH%20jt8wa6dZ++dWsaLNSZz/AKgzPh9T9BFh49mk5EoAJufKO24nW1Q7d8eJdOFNZdfxxH5san+oGQ15%20ZJnYED3gkBp3A9wQqdEqN8+Jv/irLGMIk4Xu7Ibk8VlT8rGMbPyYmY5ZGSJD6jQQA4E9dftpO7x9%20B19tWZ8j1XWJ3AoAFAFFnztGdK0ONiARqll79UqWgki+qwtAXylEI1sQqfbTjPH2g2RS8AhybVCO%20aSvU2Cq4VoZv8ymwsX3TxmRmf0zKw2Y2XOcksmjVyvsVLejfiv22rlXFercNQ3jH2Ht2917bkrX1%20FbdWsZPt5k05/v4ApmcaSFt6T9emtOOXwM0/Z9uT51/ArfcPuL6lcPijNa3DzsSNx/WehEXPiZb+%20YG7gXN7pesuW/LVTk++MaHb7L23see2ybVt/bLUN9pjIm8fzXvLkcGLOwuT4mfEmbuimbG9Dr3RD%20a66VVLXspTr9Tn5+H23Fd0vXlrauqlfgI5HA928t+nxOUzMMYbJ2Tu9CJwkJjugDvj+2lN8d7axr%20jD/MXF7r23FL41bc6tZtRn5Gh9Ul4PVC7aVsdBXUeIM5XIYeHB6uXJs6BpPnIQLtH2UDynIynNe6%205p2mOF36PGUku1kcAQqDUVaqyG0ZTK5DzvETTk5xLi1rnXA+YOebo13YVdV1Jy8yNPnwY27KypfV%20ldcgBdvRGN0Cd1pz17C2NlBk8ryHIzCFk3oQAefYVcQRqo0/a9LcWqoOGeDi8cxcXjgDzPnkm+c2%20UueTde1TZ5FJZmN90ZmfI8fpZljcN0srurtdrSSu6il5TZVqNHPc+dz5HM3F+0/M7Vb2vWjsSyM5%20rnly7nE2V2vwJolAJMRQKNfHv4/bVSmG1hBpQqdO5tQCWZtPZeJ/w+M17N7suQyqilGEAAjsoUJX%20LzWzN+HIpub5bJx/cfJGN4kY95hkjeN7HNAQBPDvV8dZRnZ5lEQ26ft2rUzQTlUlwsLg9RVAgjp2%20BCap1Tw7UAmGCXG3cAr1T5tO1KASCU2U63TroF+NAZwAIU8vUBOg/Y0B8QbRtCE9yO60B5gHdApU%20A9CBagckiOZ7GHbfpe9utuxqWNNIu8GR0XGSzQHbkRs+dUAAC2+zSueym2ehunl4kn237vy8PkYD%20GkcRO3Yq73OIs5wTWttsHNem7I6yzm584Mh42L/iEByJ3KY4ifmbu0eb/L+6uS3uXyfp4ofj/asf%20I9Dh/hePgp63vW60/tov331/5V5/AmYHC4+KXPc4z5cgWXJkHncqaXVosLLW/FwKn6nnfq/t10x3%20OH+R/mOT3K2VXp8Ff28ddF4v/U/PvJNEYKglQo+KArdLdetbvLGMdjyd2MeE+HwEmNoAupPykmyn%20tr2pyNWxjHzKH3s5rPb+RoNxDWg9gbglVUCteJS0VVuTlRDfyi2gKp2/trsOgSgDtb9B1v4UZsY4%20LBzuhBIB7/jSqlJLPYc73RfRAvYLs4EEDpbGFq8blzbO2mh5MxskPDfSc4SAhGscT5iLp/Er/di8%20Y7kZjs2Q6V7Q9xkJcC5wUgBBe/W/TXwSlnr1+8Qr9djFwETy167dhR20kAod3fuelTIE/jOayePd%20uwMowkXL2nY5SbhOp20O2ch4EzL91+4MqB0c+XK5rm7WvUl4a1TtJ1ICAaf3jsxpuSsn5B5llYJU%20LvOHuUO0F1I3Gx/bSieuolkHLzObI3Hx3SH04R5PMiN+ZFd1vc+FOICMiZ7f5XNyP+Dc7dEHKWKf%20O/8Az9Rbxrl93XdXsdftG1fH9TFe6soD3BNtV8ahp0Up8NK7/axsRrzW/Uy7xcXhpuDy5MzGfiMf%20s9UxP3+RtmuDXX1vV89NrWeZjx33JisH3cMfiGcdIQ5mP5ceUNO4s13OBsv7d64fce1V2dXFdJZs%20am91yMmMbXOkbYsJG4BlnLYW62RKxX8en2Kv7iHkx/G53Iyo3Pm3RMsAAqgEhygodoIXwqX7GHkz%20avI7a5FHy87oczy7XwGwcNbW1KV7HtbbaJdjyuaqbbRWfqHmV427gQi6kDQ6lLV0Pk6mO1jzc1wA%20JiK9yU8DTfKOtCVFI6RwY0NBcgUk2LtLWqXzwsYx8Sq8U6F7h8MY5Iv6hK1rnbS2IXau0WKdRWP+%20Q3kssYxBu/bbek4xjXa+1fb2DmetPyA3YjG+nG1h2uL1AF9QFrGHfQd/+zyNHB7S9pYeZ+rj45wf%20E/c1rnF0e5oUENIuK6/Us1DZxQuhR+//AHPy+Vjycfiksy5I9w/Lbrt+zwrC1kmbVpOc5HJovbmS%205rXOc4B4/mktIRxNwv8AbR6pW1i+P4fAy893HCYwSPVkAevmkWwXx0A++k+RqqYKsvUtMP25k5G6%20FkTokJdI8lux/p29NT43/CofIJcbM7ncVyLeQbHHivZI/RgCXHx0rdXTWpDozr3s76me8uP4zA49%20/IFg4538yMuDiYhcx7j2HT8ax5bqumMY8IvVrNlzH9VMniveHLe4MTHDjyscUW0oCz0z5Qeiblpv%20kyTMa2/VjxKn3ny+Pz+azkpYDE6Yvc/c8uDWKm1p6XBWsFzbk4xjKO5cznjyKTEg47FyWSxtbE9m%2017XsCsIJBAftVQi3P20rcjsn1xj+gSn0x2NG3n5ZYZZYyYJ2ypsBIbI5xAlayxbtKn7Pilclv1OH%20jtKx9BS7fpntHh4vT5d+mTYUvM5ePEzaI8gscXQYjV2xBquaUJ3EizgUAorbOZjGO43bKW89Psy+%207rGecmt4XmMrmsGDkssBuTKoe0qQrbEK4g9L/CvZ4Z256nJy2zeOnT+nwJykN3Nu4NKL1Id4Wsda%202anzx9pLnTCw/wAIA1o2lFaDtBQAIRbQflQBOlLqpx+f2CjKIX3ZfDLp08pCcPUbtC+bRxQhSLEE%20dCpKg/aKabWfmJxDaxl4a/b9hlvf5TExHkKz1CXNc8g7bEgKb7tPvpJdCOTTNzn5r4+T+vY5j7zw%20oXR8O0C3oPc5Cb3HiUFu1RdxodntVKbnHyKWXj+HdktEeO9sQ2iTzqSQPMNFrBXfQ61WDbuxOOfP%209PsKVjmYLXeqS0+ZfWYBe2rgOlU7NVGlmezKzLBQAKAMxy0hbyE+7dtVqXAvtCJ+KU0ibMiHaCAi%20nRxtdvTwJ7U0iJC3m5JXYtwUJGh/fRA5DbqqAkohIJtobAXBcbUxBhrrA30K3CtFyEKUA3qKjfO0%20tdfc3d4FXKbg/BaICTJ53B8hwOXJzHtdjXwyuLuT4IkMjmFg+XHGjHp0+NcluK3G93H/AMvf5vL7%20z6Hh97xe6ouH3TiyX6eTqvC3epc8P7o4rmOPdm4cxcA4xzwSjZLFICRskZq12t/7q34eZcldyPL9%2097Dl9tfZyLXNNaWXdMi8t7ux8GItDA+cAqwOTaRZu6+t+tapScTZh5/cHLchm+rJsMG5BI9SXA6h%20rRp1vVwJ6EXL5AvnEWO4OyWArOgIiBcnmUkBwGgNUq5E+ZCdlQ425kLxK9xUtaCHyPIQvkcb636A%20dKTeZcDWSHSQyCd4kkk8r2xjoSfKp0AXvRGQbioldxvFxBA71CNzIiSS0i28kFF7UQJNtFbhZ0mU%20cmbI8zQTE0BwcXSG7ibDxrn5mdHHTMxXuTmY5s0wQ+eCFro2BSrTYONuvx+yr4lCFfNmekBe4uW7%20nE/boK0bjGMeJDQpoKWvdU16L42vUt54xj5OA9hI81tvU/tc0TjGPsCAyzykBV0AA8O+v7eFG4cF%20hkc1OGtjwwcdrcdsAcPmBBJcWnVHE1NaLqOSmfGHgucSXldxKklb3J++tkzN5jTmuBVV8aoloII5%20ACE6dbGgQSlAnW6m9qBhON7lLjp++gEKa123c5qN0/u/CgWgHXsiBbj9+tAwvmuiEoVSkCYQJVzS%20gTuOy/wpgKJJH2fvtSY4Ljj3ukllxIgpmx9i9A5oJ18TXPzclaLdZ6HZ7T2t/cXXHxrdZ/QYEmNx%201oduRmjyukP+lGmob/mNYRfm1/Tx/Vnr7/b/AMdlWOX3C/u/sp5f6n49OhrfYnu6bEnSeVz2tcDN%20GlixxQlBt0SulKtISyR8/wC6d/cN35G7XfXHTy6HYoZIpYI8iJ++OVu5j2kAEO8U7H9tK2q5xjHg%20zx7VjXGMRoKLAoI6Os5UCj/CmvrjGEPrnjvifwCc0ApqiX10pYx/UnPHlj6oyv1Dk9Pg2sBAe+UB%20CRoAbjUEit/b/uNK6+GMYg5i5Ni2+A0H312Qby5C0NiNdenakx6hj5HnQlpaCCPBR+C6Uwb6HsWR%20+36JFxsnBDS//wCrJXi8y/UzsqsjycyeFhdGWta/ygEobqoG6zSC49f4VyZtEZElkoMfmYC+wkS7%20dhAAaUBRw+J++oe6cYzwxfANsELCyQvZFuaHPjc1wLDooVCoXRfHtTly5HGRFbiYEmS4+qWR7Q1p%202gFApBANrfjTTyDaK9fFxYC313hjEQIQU2m17D5k+N6erFtEvm3uMYjZHjg/M6zgo8qA6qg+FCU9%20QWbL7GzeJGA31WY/6gA7GyACQqFu0dHa61pRSs8fadvFxprPGMQQpOVxIJnGGSHHv8rUCBLtGutN%208SstDdUpV65/PGJK2bE4/KIyTEySZEJY1HEgoD9vc1ayUIr0k3L6/f8A0y+TkbmbJ+gzow1Io4ht%20YdCQqoUBN3a1HPduJ6/j9pD4FRZYxjuZy/YldfEJcA0GBNk5j9FgRwxhr5XnTaCW+Cm/SnVJhZw5%207k/nXSYMmNB6hjd+mbLkRs6vcFQf+LWlVSaWtCUEafDDuLxJthDgoaHHUG9hZf3d60VvkZ7d2ZCZ%20iF5uqtKuCfMT/jT3k145JkfCZLwQPMEu5yAE6qfwpeoX6TY9iYbY8+CJyGRhc9xOpeEsf82oNZ2u%202jbjolbPH5GinxDjJDksacppJeQhLkKLr0sP41lu6rQ62pzZ0D2jncXxvDxNyJI2TyLI/eFKFCAS%20V+NdVJjM8nnc2y6Y/Imcz764uPGayCT1C9yhwYgICFdRWm4xdZOejlcnPGdMU9XHyC9m8An0XlCG%20t7gpXLyWUydFFkZ/Olxpc+QSTyP3oHsDiC8jT+XbTxFQrdTXbOMYRZ8ZjYDpIJW494isBu57Usru%20qqNaLWfU046J5l62LGDXzZEEj4ZPLOWFDe5c5uvTpWatBq6Rj7ytysyaf1IZJ1xfUDYp4hul9FUU%209d2taVsviYOk6FVicZzLczfisilgEhY2WzXuH+0xevWqd511M7ULbIh9VwbMP0uZC1xjJd/LfruD%20VX8amzbUdDnv7ejb/wBr6kGLa/8AkMejGN3OiDQ65A8y669P8KnrmZvLMhTTy4rHSl+5j0RxIKkp%20e4JRRodFvVRPn/XHiQ2yS/kGQwgRlzV+eVxV7FQgG6aeH22tOyXn+WPt+I90OXjHyJj8iZznEOcs%20uku5Q8ru2lBp1t++s1xpa46dcfAiuUeH0On+zXSP9tYrpSri2z3N27tpKHVFUV6ft1trnnjHxOXl%20ybfRfbr/AEz6l4UDWvUkglF+XyEoEIOn+1pW2riMdyWu2r8Ph8dMZAcEBQ+UncA4E3JKNLktf+zt%20RV540Dcuj10x8fsEuQ7gUJuo8NyFVUaU3ZrXTGPszBKG+q+c5L88kszJ++i1wwSS0Fj3OLQUcTt2%20gt2nd9gHjTiHHQy5Z0l5zjSNNPzOb++g5uRxkCKGYzS1qo4q8g2N7G9x+6suTxO/237ZSjHxMri7%202SEtK7y4kX2ub/bdKxeZ1Sbzn2tj5D6fQ7/NEyB7mj/5mQ3p/dTbyFU9o1mWCgAUAZLkcvHl5XMj%20heHSYzmiVmpDi0G69mmmmiLDLgzcQdd3mcVaU8f2vTJmAAlHO0KhxKgoVF+un30MID/VwRoC7cQS%20S0Ei25UHZNfwoaGRpeSjALVUny9kHi3SmhMjnkHOBIDkIRwslu/woBuSHPyUpVGAkKQiqCLqClUk%20OYMX7oe7G5M8hxcjoOYLf+L2lI5WN0bK3Rb/ADIo+yubl9tad9HFvoz2fZ/ytHT0PcrfwdH/AHUf%20euIKTC5455k3j08tpLciKQK5psSncFNe1b8PuK3T6WWqOL+S/i7e2snO/ivnS60t+DXVCMvMdHK3%20ExyXZbw5pD/lYzRxKdq6GeZWemoqNnp/yACYLSOkFnvem1xd8OlDz8xz8iIQBPL6ZcZJT/McD8rU%203BrR8BUsatMEXKzY8WOSUuD/ADARRlbuH5QAgCKLU/MVcY7f0MryGbm5GZ6IaPVnsZXFS8noGAkB%20jai2WMfQ21yHPcE0HE8dM2Ml2QWiONytH8x3zuQaWrjndY69K+Zz4tuNyl1iSVu4+NdMmInYXWCb%20hoNdAb2pzAgw0NQABOnUo7SlI0KFySqICbLrSzBBorwCCpBI7/2UpgAihHlcdoGqoEPT7acigbQH%20U9FIROqJ/dTkBJaLr1uAvf4VcslkZ7E+C2J07VaE0E0qL+bUg6L3/CgkVYAWX/aNEhOYhxJI6k/Y%20hFABKALBO32aIKYBkkEgaL+FIGAISioB2/xokJJmJgPki/VTuEGI0q6RxKuHUManmPSuXm90qvav%201X7fiev7H+Ity09blfp8H+p9fCi6v6ZB5HIrCcbCa7GxtXEp6kh/2yKnj9tL38j3W+i8jf3X8vVU%209H2yfHw9f9V/Gz+6SK1BoPBL9664PDfiWXHZhgmg9KMb2kB0jgAUcSoXTSlaGNM6D7J93xcZLJiZ%200xZgSBzo4dpeY3Egpa6WvSr44xJz8/FOaOlQZuFmRukxsls8YLhuaQXCxKEkqt7+P2LaXddsZf1O%20G1WsfHH5KX3iTc0XLgS0WNi4kE3F1Hf/AASaxjHmEZ47vH1MT9TJSMDFiJIjlcoUEhyNCaXQdv39%20Ov21c8Y+JfHOMd5OdSBwJJUuCEk3dqRY/m0ua6k5NoEvID/K65VHG9hYEuCtv0ShoNEEF9Ign5hp%20qqfwpB1PY5a130UaHEtaeCbcFCFxh1WvE5dWdlf2nlB0GMWqHGbYNpmBIW4TykaoE+F64paHtFPy%20+Kjc2SUuj3NI9RS4F1x5rghfGmpxj7yRYk4zKdsYHtc5x3XNyvzAmxP2d6W2OnkG3sLPFloIyHtY%200NTegCHyhABc9v8AGh2Db0Ff0FkuV60mWINrC6KQNDwHAagC5uOn2CtKt4/DHmNUXUrhx3IbmR5L%20mvcwh0O7+W5dPHzFPh/CpXaAjIlZfE8o+CN8sMc3phGOjO920gAK4LpV1skbQzOcxwTzE2dz2Y7f%20MHbnam58rR5rmtK3JJHByhuF6ZcS+B5EMpb/AJhbaCN32VNz0Pav9JcuBdhciHXLYHAkgJtu4bUu%20orm5Wlpj4m3KlDMm0AtAT7e9avU84WYIcnI4+HV5kDXFLALuS9rVdW0mGTZb+5HzZfuDLMTHzTRm%20JjWxh3QbQLaW8KKwi+SZgtW48uPjx48zSS1h9Rrh+ZbghfHpWd31x95vw0S1Gz6MRCsaLI9GqSE6%20d/H4VMmiSx8wCfHb8sjWIhJcblAiLqotQpG18hvKjD5WOe0CeNwMJVGuRUDSbAmlPYaUE2J5mPqS%20EklD5j5l0R3wpVSMuXkgfOXEGuaAHfC5tfXpWm843UTNmmdoDQLuVQCLgfbpT3Nk7SqZ+rxfc8ML%20JA2KdilzPG4P+6oHepcOuYXbrkix5jBldizcrB5zDu/WQnUyKUcGi4XVeq1jS2cPXGPgTXkRK9rT%20xS4DHNd/Me0FVAUohRAFrS9T0OO6hF6WSSCOMgPheS1zXHarQtt2up/Y1G3uXvM3yPK8TxT5IMTF%20/TPlUIXlxe/Ty9hbrS2Wepy2fQc9uxxvxJpZDCGsY5DKVLVVHX0Q9xWrtDQ08iRNBkJFFnMZGCwO%20ieHKwt6OaR28aXqtpLsc9uFKzbeow3Cxd25hDnutI8+ZqgKS0X3btf2vmrRjHwIaESMxHxuY0enI%208bAHEptFg5Xaj7P7rzX0xj+stDMcOFeBzxEHAtdIU820jaR1ue38KN7fQmB6PDxIX+jHO6RjEMjX%20q5rmghQFS7R0Nl61ja9nXHzxoEPVLHf+mZ0725yOHjcTxWE+cfrcyKUwxp5UaS9pXpuTX8a9HjvF%20Dn9J2sRPYnvKD3DzbsfOBZI0OdFjsCNc9hJQkBdqDvaqvyOEilwJWckrkPcmc/3RJicdjsljH/Cy%20QFwLWOa125xQOO02+FFH+mWRy17FjxnLQ5szMOUGHlLk4jiSQxoa5SR8tj1q1y4/L8DP0bdNfp9u%20PmUvvUvL8QaagtNmpuupHwTROiXrZQcnIk0oX3OdcTHmmZ7mPp7P7lGFlR8njYfowDH9PJO1yqig%20aXFY2PQ9u/0zkV8H0Q5tz90fL4UzUuQ4vKH/AHSq1m0dCZp876WcvyPLe3Jo83HjbxMeNFMHm7nx%20SB5LQf8AN8Kp/QFJ6hrI0BQAKAOXTYEvHe++f5GScPgzzGW46kBu2JjFPj5e9TSjVm+4clpSRMk5%20KUsGxoaALE3163XstamQyZnvA3klxsQAQi96Yp6jD8joxnzdf3p8aBxIzucrDI8uCfKLgOQoF/tp%20wIjTZQ3KBuc7cNxNwF6AeFXApZX5mYYGkts8glrR8vZzlC6Ki0Cj4GbyV3FyruK6qtxqL9Eq0T4l%20Ty+Mx7GZMb/0+YzywSsI3lfypoQt0Nc/P7dXcp7brr9x6v8AH/yT4KviuvU4La1ffvXs/L4jfGZL%202zZEOSwwcjKjpC5C2Rh0ERVUAqeH3G57brbf7fFGn8l/GLjoubge/wBvbTvX/Zv2fj18A8vJmMjW%20wvZta9HMKlxUdSOy+FdSz10PFygKJu7dGChDRuS+5oVXFx+/X7KUjjuUWZNDNl5Esr0xcSPeDYAp%20ZEv0C0SWlJUe24o5s2XlpnElHHCDrHd1OvlAS2tc3PyOIOrhr1KH3LnSZ2afN6ggJCt6uefy3+yl%20xqCuR5lSW7bqq2sEN01v3qzIKJTIAhA6KERboehC96Wg9BboSACup1CKRYggGiQDx4yXhDtIuv2K%203T76m2Q0uiH5IG/PtANyQBY7ibC4Oo6VCtOQ9pCc1rXEqCVCAaJpZLJ2rRNsnJ6ADQSEIVUW510P%20205jUIkQ5hIKAIgQDueyqV7pTTWQstRuSMAkGw7onW3gapWyJgYkjIVyBB9lq01J2iARcHrpYX+F%20EggEDUAd0t0tQLQSpvf/AAoBoU1rnuDWN3OdZqXJ/Ck2kpZVON2sq1TbfQnnHxuPAdlgTZKAsxGk%20EMXrIf4CuJ8tubKmVe/fyPoV7Lh9jFvcxyc0Zca0X+//ANKIuTl5OXL6k7lcLNaLMaP9kaV08PBX%20jUVPK9//ACHL7q+7kc9q9EvBdBkEBPs1+/tWpxIUS7Qdk+AoGn1Da8tKglDqKkUMnY+e4Aggncm5%20y+axte9rUFT3LTi+ZmjyAY5XQSEoS1yX1JHRbWpWfYT408jpXFe9OSjbvyAMmN5+YWk2NYHDbe5V%20tNWyh4xJzcntU9MiD72zmcyzDOK4oxpM0SFqF43Cwt+VAE1rt4LJT4mVeJ100xjEGPnifFKWPY5p%20VXWTcrjrdE6eWutNPTQp4+HiR3us4Kf9ogHtpcDtRARKDISIDQEHaCuqAeA0T7qXmGbZ7Q43Fjy/%20pLiYsm5zJ+HiY5AS4h0AGgvXhe4f7vid3H0OFR/TfhI9vove0jRCRoPKet0rzfUfc6/SQZ+nPG+m%201rXO2AK0Da75ip6aqaFdg+JMNv07xBGzbK1jm6eXagT46/bS3Mj0UtBmb6dB7XD9Vtvua69nKqqv%208KFZ9Q9FQQj9LMtu4Q8o5oPS+oJIQaDxq9/cX+OhuX6dchjRSyv5Bs0TW7y+VAjWhUGuidav1JD0%20ctTOjjW4sLcjCmLQ/c4yxOVpUqdy/dXSmSyHlxS5A9XLZBE2Pd62a43LQdGtHX+yhQsh+ZS4eXju%20y5IsUOaC0ubkSeXQ9kdb4/hWll1Zr7a2cGi4Dh+R5iTMgw8dzonwbGl9o2Ws55ummvaubmq3CTk6%20uW6hyx6D6e8ZjsH67NORK0uX0PKxwA0aov8AxrVVZxJT8MfkazjPavtmH2jk8jj8dHJmwZTI/WkJ%20e6NpHdfxptJLIqudsyCQxksj4WCN0h3SyNbtJPdSp61zq2R2+mupClxg8kptJ2i6qEF/2WkrOcYx%20kapQRpMVjSLNLUVoF23Q3TwP4U9zeoQojoPx4WO5myRocvmjLgpAF/MAQe9EtiaHuO+n+Tychhwn%20xY7AHPkdP/otabl7ijkda3h91XR7nkjHlvsRnIeC5DJ5ZvGjLha2WYwR5hJdGXlQCUFgTWlePocj%20tOcFhkey+XxMyTDy8yGHJgdseASQiEgr2Oo+ylkmOvG2pjInR+y8uWEiLPglc8gbCCwN2jQG16zn%20qU+Kw3me1svi4X5pYZnsfG2Frb+VxVyEKUt1FYWs24MrVaKb3ZO/BL44jL6+S1RHE0lj4iELXItg%20la8almdqRYley4GHE9QtdHHGSAHAtduPQhD0/bpWljr4+xsd8Ujf5g2geZXNJREOndpTSsma7Ohl%20fdfCxZefFK0jHylUuAJaXgIq316irrbaZPjlyMcTgYWJmB82XDgMmT9TJkq+NwJ/yjUaUr/qMnWE%20X/In2zLxsmFgvyM6NyvhkjBEcZvuMZPm2p0qEozkSpKhlDPxUzSybByfWZO0PGM6NwcD+Yrov2Va%20uZPjjQj+rNjemZoJJA47ogxpK9egO26U2kzN1cQWEUDJ2tJi8hXdGWbtjrKSPh31qGn1xjDDYS8S%20KF7hvi2SAj0nJ5dQgbo7qelSy1UkH3DjZTGYxY6P9OfRx1COcW9AfLZTZPH7ehSdfDx1ie5H4ifj%20/afuHC55zXfoJC6PJKOWMvsShK2JU01d2UEe44OuMYZN4rmeQ4L3Dm8hA0ZuO8uZG8OVmyVzT6hI%20u4fxrRqVGjPOTas8iv5bkc2X3hkF2XJhzSPL2zxJcMQNa1dW9OnammtqBNzmTsb3jke5cOKWdrYM%207FDmZAjO0NaFLXeZVUNv8fjXVx+R5/vKpeXlp9f6x3M172RvO40auG7EYAAS0anru1I61lyNpnZ7%20fOiKqQSYuNK9k8kbA0qGSPAUIbX8K562Z2OmRsfcWbIPe/tj+ZO0ehggBryAd8gJJ0udCtXfcKqR%207JpACgAUAc39yOiHuLM3lXFzCGrdNgHfwqkSyH64RUQgqEPXuRpTkjaRcnLBaHtUtuS1pH8OxNKR%207cxET/Ub6hVu4FAvT8L/AAqpgIkKaYNeWusUtcBRr1okQy+fYz1HtRzQrLD5V600DZk83kjlTF8T%20zHCwrv0UNvb/AGfCrCCJ66zLINhku12gVyjXT+NG6BOOow2ZmVmOnev6fEWPHBRC8rukUabKvoJq%20Mxnk8aGeJokYXStcDHI1N0ZtcroD91Yc3AuTXJ9+p2/x38lye1s3SLVtlar0svHpl0fwKyLKdBK3%20HyYtzyobO1A2QFUVx8oci1jx+4asuPkyfR9/zPR93/HcfLxv3HtM6L99P7qd/OvjqMc1kTYHGuZF%20JtnyHfK53mEbTf5u9xXbucyeCkYqabMyphxWHGXPz3j1kBLmtCAdvvrN2hSaVrJrMvCwMDjzBCAX%20YsRMuQHIXPRHKVTWuF23M60ttTBY4MuIycM8gRskrAfmBW6pe3wrptBzsTHA8tOjmBFAuQQVvQ2M%20ciY+Rw2tKKTuNwpAUqbfH+NQ7IIFHHOxSfidFPfp071O4cEYN/nbm2CHcBfqbBLoQgvVt9AgdfvE%20aIdrUJKkC+h71mkVu8SJK9jiHNshIIHQGrSJYlyakAabW9h2Ufj41SBBOICBAdpU6WS3TqD2pTIo%20CIAFiEHTuvYWqt2chrmAxWVwQgqW/MSban4UKwrIgSDa9du1p6a2N62TIsJVevZe9MQ9iYWTlvLY%209oY3zSSPs1viSetY83uK8al6nd7H+O5fdWapklrZ5JLzJBzoMQGLjbyHyvzXDzHuIwR5R4/3Vzrh%20ty58mn+n8e56d/5Hi9nV09p+q715Xr/wLovHX6FddVcSXG5dq4nuTXcstD592dm31YakINKBBkoU%20UIVB++gWga3Qjr306UMaDBAQnXuRUjFNdt63F/uoEPgteSQbWDgdEW33GkWixws7Kh2mKRCT5mXR%20xaVCqthSGsy4x/cW5rW5EYIOxXBVJZ8vy3+Um9OSdpZx5GJNJExGZEWQHxEuu5jiA5hBB3W3J2rb%20j5WspM70yKSeOUNljeEMZDXpYWIF7k3NeknOaOVpJiy0egriSS25A+VoVLi99yU57CnH4fI9o8E4%20f9LsAhAG8TF2skIrwefJuD0ONaHLmOG2xJsfKDtNiv8AGvHPRaG/Vf6hDxt/y+a5Q3+2jxIF7iCQ%20TdbDXUeNtaeQwBsQAQobotxpbVftpZADfGSOoXzBT1N166DpVKBEblJAOMzBckQvBJv8dT1qq6it%20ocdjjn4x7XwPMZcQ58LvMHtPxUa6Wr0Ik53aCNknEynxenA8zuP/ANKVMUbhqVNjREdRzPmWvA+2%20YsvLORlSJiYrwJZGlB8wSIE2U96e5JZl8dXP6TZ85yDOO9r4+NhRx47eSkd6obZYoja99SL1VW4z%206YgLy7RjXH1Mg/kpXNLgoFtxOoKAXYe+lU1AR4Y/DCND7D53Dhz8rhuRf/8Ab+XYGMkukcrV2nsO%20lDrKgi2TmcYxI/ncHl8fnOxMxqSQkH1XGzmiwcCoXcK4bpp5np8fIrKU8yI70m7QgBshIAvdGj4D%2099RBs4+GMZkOUgP3opYqssCE1DvgbJ2+NWk0Im8Vgz5E8eNjsMuRIQxsQG6xUbraD7fxojc9CXaM%202WfvTmcfgeMHtzjJQ/Mm/mcxksKAbQf5IINnJYrXXSiSiTzb8ju5ehgHFzWnavqNIdGoOxRcOCX+%209a0yx2xjQUHTfd+JDlcjhcg9T+pwo5CLAgsbq291v9tcnMknDOv2bmuTxjHQqocqGNwc4qGtG2Rx%20AsQqdEQOJuf4JlarhJ47/Z9Dqayxjp/QeZyAhIZETsY0bh8zUPgSAddO3QIlDtLzePl9SLcU64x9%20xIh5KOV6/ponvCXLWqdbDp217pVTlPTH2/cZ+iuoc+bAjQGsa4tIJDTcEJYoltevwpO0ywrxRK8v%20gQXOYze9h3EEqCUCOJRHd9rR8acyw2y8uow6VZ2Pji9Qwu2+mqOVB5R9jql6BtQ5L7ZwMzKx8qWE%20OLDvEMg8pcAnmBGhT4UlZ5pEuvQsoDyGNyeZNj4DSyZjfTY1g9KMtYoREUVXI3ZKMzgna3IUeZzf%209T2RYsjAxoWMxgtUgnyu1UJp99Q62JXOuhJycjmX7SzBAjaCZSWbPMFVXHTQdL0mrdFkSueezX9P%20D8islk5p8G9mO8TkjyBgD9urdUUFR2pbbdiVyOc/p5dew1kS8yxpyP0CRY3nkIYAFFyXG+hNu9VR%20OZayxjGb47OzSeMdig5CbG555bJGYHFqxvjahbI0r5eiV07tqxhnp7E9Ma48xWTGyLBnx8yY5flL%20d5aCTtVNLf29KluTRVcGY9t53uTiJZcfFYx3HPeS1swHlS/lVbeGla3vVrLU8+3t7NytCxzuY4GT%203Dm5+XHsxnwsacZxG+F//mbEsrulN1tthGG1J5llxk/H5k8c/Fcc/B4jGx3Y+K6VTJkuJDi546gf%20sa6OFW6s8/38R1WecYn5fIqfqDKyPnxIu70seGNzAoVwVF1dqf3UXUnRwaFLktfkRmBzUEibRYrd%20dfhXPSsM6pyNh7vY1n1E9v43mLoG8dG4dnB7Stu/WtWkTWYPaNQAKABQByf3dmRR+5uQa/ztDmq2%20/wD8NtlHiatIiWVn9QkLVayxUtPbXvSYlIjdMZTcv2kF5uWKLooqoYJMdDciJpmfIFIP8sKilSl0%2008KSHGY08vaC0OJYw7rWQqNdCKJCCo5/kooyId25hO+UAgBxWzb9k0NVViRSkyOb5toHmBLUAv0T%20tc6005FHcYyHytxdrB/NyCGxgG4OifdTBP5DkWNHC0xxvIjjbt23RxDWq7rdfGmshRORCzNshkJQ%20h3m2EeVzbIqd9e320JhJFfjxOx/SniD4nNUxkCxcCSQ4rdDUcla3rttpj7Dp9p7rl4ORcnG9tliH%204My/IwZE2S2HKnc3FKMa4lbNuh2/m0FcVPcW4f03c16W/E9/k9jx+/q+X2628yztx9/Gmnnt/IX7%20Tfizc1JLgRLx+A0l+Y4D1JX9Ap/2q15XkeJSqT0LjM38hi8hiwIXmH/WdYK4kuJJ+Nc85mrrkY7i%20+HZA52KXGSRwR72naLeHhXYrbtDjagiZIfhZUsTxtLD5SEDHJc/dpSiRwMiR5V8aNaRdzkUk6deh%20PWp0HKHGSK9wDiSqgm52/EJdfurPQvUbkY1Ta3UjQBAlypudapMPMEjDfyhz3tLgQdCDcfDVKU9R%20eBGlhbI8uAKNVCVsNf4LT3wOBuUSkksu0m5T7ENUmupMSEY3EDRSSSBYDxFJgEjh4ADyk6fxoASb%20AhoUaOIW/h4005FGRCnDQg6Cym/Wyn8K6KkND0OBHBGMjkXGKI3jgb/qvTsOmvWuXk9y7Pbx5vv0%20R7Xt/wCJrx1XL7t7ON6VX77/AA6fH8BrN5GfKHpgCDEaVjxmAbe4LkHmNXw+3VXuedu5ze+/luTn%20r6dV6fCtKL79JfiyJ2UdlFdJ5eoLgLqf21pg/ECfDuFpBAfQjoLigEgwST2b2T7qGH2hg2JOmpW/%2020DYYD2kF2vTxoaBwOROQlTdOo0qYDqSIXI7a4XTpqVQjWkyk+5NY4eVPNvUBAFPXrSGiZjwZDEy%20Y/5cjUdCBorbt/sqd/QfiWHKZbOQEOX6RjyT/LnP5HuF1Y1V/C1erwO23M5LqswhnIarWt2o4N8r%20bBOpsPF2v9tb4xjx8DFM9lce6YfSPGdC4NmHDxmNx6O9AJXhc+tjv4+hxHB5bkfSacgbygAJRu4m%20wNjpXluqOtWJcfLsc3zwvRArQQSPjQ0mUrND0E/HbNrJCxzwHENBOpXvRkVJI/kAxv37tFRx8xQa%20r9i2pQgHRk4oCPbtLv8ATO5FBXX4000BC5jMY7ByVsfQeI3qQhIsbDr8O1VVyyXochGY4Rsxs95e%200u2x5NgQiICQvwWu9JnOOw4nJ5WXHgQFkbZf9fMbciJFs4/Ke1JRqNV6Gq3Y+Njx4mIAzEx27WNu%20zQHzOPm3E3X9ljPVnfx8UIj++JNrOEiAA9PDc5bBC89QdnQ/Z3remhx3/dHQzG9z9w1DAQNxKKLu%20JXo3UVUxoJYx9o2zYWncjQSBuJKuAuAF0N+tN6gvqbLjPqGz9EON9x45zcRg/wCHy2IJo2qm1zSP%20MOl6i1VZBR2pmmTP03F5pbPxnLRSRFC6HIPpvaD0v26Vz24cjrr7vuPM4jEia1+dymHBGLbw8OcG%20gAuJAU6d+tL/AB29RW93VkbN9+cHwuO/G9sM/U8lICJuWmRoaP8A5Y7hLGuildpzXva2umP6GDdk%20GV5kJMj5C9755CS4k/nLjcdjWinH4eIKPjjEBzyPLJW7i/o9QAhAKEAE3edaI7BKyxjGZ1P3PlNx%205ePwdoe/FxYRITckpuLHEAgD7K4ua36tDu9mntnzM3mTOer9zvUaCQ4qpUpd1kHlrCuXkdUQNQPf%20uc0klgKNTS1kIA6HX8LUbshJ4x2LGGZgZseWhi9RuahsSn2rpSzTlakx1GpsloBkJB3AFeii9k8K%20aU+YR2IEvJglNwQqdyglQin42NVl1FI5i/q8uJ7v0s2REGlrHwAtAcqBD1+FK7yOfn5NqlFxxMvK%204cLciaCaeJqNarCXIvUbbIF6Vms8ya8krPUv+M5bEzmNEDyZXWEWhuU+1Teqq2nkPloocml5Xi+Y%20x8L9RjNOVEGj1oW/Ox35nBD5g3767LppdzyW8/0mKOXzz1ZJiyRyzloibsedpK3cjT2HlPXwritz%20XXTGWMZy7W11r5eXz6+QscvyTWbsjHmilLWxhxa4FyID0sh6utVf5NqrT8MY7BbcpW3Pwx9z8iFm%20e5MmLjM9m2Qvy2Bo6bQQVLj3cCbfwNVxc70ZrwQ2p6fLxgxjRBHIJBJvRC4AlF+3S9bbl0PWq3qT%20cMz5GQIcWF08rvK2NjdxulyAqaBO1Sk2D5ElLLr/AJY90yQ5WJg8K13I44SKeTaYAEurgR5mi+ta%20V4m9X1MeT3dVpqczzfZfveDlGuzsF3ryv3uyNzTGb/PvUgJXV+lJLoee27uUdVy4OThxMDHy5G5W%20SyMNmdAuxq2a1rQh3A7R9var43VdTzfc8drOXXLGvwlaFRzn065b3DluzsLNx4PUjZGcSdWvaWFb%20lOq9Km3c6eJ7VD1RT5H0h9+RFpdDHkNa5qGKVp2gH5kJuAOgqfI6N5be7+D9xu+o2BkwcbM/AbLg%20LNGzc1oa9u5SNEShsEexqgYKABQBx73kyRvuzkZLbHvZuulhG2+mvStFmiG4ZVMyHtVwapF2Lqp7%20r9602iZgXiPfGxN38xfO4Dr2qXWWPcKkyQ97nOcjQTsBOgF+iUoBWGY86NzXytc8hgPmC3RE1+FP%20QDI8hG3Na9mSNxlfvBa7aVVSGlegSqazFIQL2EODiYmNIABHyhobqoAU/stCQNoQySF/JOMr1jxm%20FrQ5Qd7xucRr4JTG3oh+V4ADGgNIYXOB6pex17rR1JzKz1ioBKgK1zyobtUHrr91OAmNOhCyOQ/T%20wPnaNxAAgACuce9kH20WzTKWTOf+4s2dvI4jTM9geBvjCja5bOQfNXPWqdWnmdK5L8d63q9tlo+p%20rMAS8fEMbYfTyGRz5LmgtezoVA7i9ebZW48/3U+w+mquL+QXTj91H/DyfhbHk/ymfjswct2NuZ6x%20bG6Vuri7zID0FdFWnmjw+SlqN1tlas5ELgePkgDnZEXpxBgJa4K5luo6qErVvsctq5ljz/Dw5WzI%20ijErE/loECD8oNneYa10OranHkYrsYfLhjiO+J21u8hygqx3Z3h0rLTU1SfQf/RZAjnkkDmxNYJH%20yuAG5qoCEqE8xpeAzt8w3FCQdw1Ib4JZEqW/sGvAbfEAUILegI/MdEb2HSm9QQzMZELXAtc9DIOn%20+za5pp/ISG2sa1Ggo5CVH3p/dTkMkHI5jWBPMenQ9UUdaSTHOQ21HEhNRYO6mgUdOoI4ZJHGKNqy%20PsG9vifCi3IqqXobe39ryc11TjTtZ9Px7IDnwYVmbcrNbbcbxxk/duNZfq5v9mn1Z7O72/8AHvLb%20ze5XX+yn/U/sKjMdM6d0s7jJK75nnW1krv46VqorofP+45+Tmu78j3WfV4+g2CCLoK0OeAjr/jp9%20tEhEiT06oSnhSGDvQAbShGg+NOQgDrH7b0gQoOuD2oBgcdS66696AkME7lP3mkwHw8lo2/ME82h8%20KTHMlvgPgjjCpLI9A2JQfDt1rK0mqqWspnDXRujR4AG06b/yiyqvhXo+34ElL1OXl5JcdBl7Q5wQ%20KHHcGkJbpdTXZoc8jk7XNL/BNziEKkEgWNuo61NWEHsfHa4fR+EJf+ist8uuOPhXi+5/unxO7jWS%20POTRkNgIaxweUa9yqEWzALfmFeTMZzobtEqCQ+q18jzC7apeFaQAHD5QNp7jSqQ04JeBJLLkmF7i%20R86u8pTovj3oNUX29jfKWWQbie6Dp2paGiXUDpA8kOYu4J46260AV/JEs47KdrticQEuTt6af2VV%20dUKzyOXZMjMmMvYhDAN8WhDkSu6rOV55ltwrHYnGgOe6R+QQWk6bB0t5utRa0nX7ekZlh/qhwTcH%20oHbShuFtdPu/xzWcHVJG9+Sbueixgdwx8SGMNQG20EodOvUfGuyjyWMYzPM69sY+4z+5QSWi5bcF%20VANr269P8CwWmMhhzt7hsJs8MY9A5fv7fGq88Y+4U5Z/1xHgGZ4y1rHjb5WgkKHAaH/3aTTKSnTN%20zjHXwIs0U8EriBuYV8hKgixsbU5xjHclR0xMiWN4+aQFTjyk7SPmB179LdylJ9xpEk47mt3RyMe1%203zBPNYpYG2qU3jqCx92OgphFy4Dd16guum64S/f++ljHf4BONCdxsbcjl+Px03GTJiBJUo1zgLaq%20L0YgHllj4nQvdpbJ7hzCwh+14aNFAa0AaaFDXm8tv1M9P2y/QpKJ+M3H/mOO1zGqXElLrqD0Kg61%20km3k88ams/IYZmsLtkbSVXaiBx6X3E6C9W0kpF6iHf1GQ9SyEhoKuLihQ9f2/jSmvXHUxfPRLIi5%20ImeQyU7pCLemQgAHXRVJFG/LI5Ob3vbDGMPLgx5xI+AGRjmlsbiSLLuLibWcgFk8azfIYP3VnpjC%20zOgcZ9RsPGjYzJAhAdaOBAPL8BYr9v2XrWvNOSxjv8pM1yznjz8sIs8L3lw7IWFmTuMj/N61nOe7%20Xy+A8Ola1uindMje1ocOP3dPmNdG1jw44bGAFHkDcqgonxrpXEk5IXubNOryzOhcZyOLjfyxI4yt%20IcA1C4H5vFC6tdTERlTtzWSzNnOI6K7nFoQOdZXAgag1m+NdMiq3RnczkOcxITPllmRiNS7QEaAt%20zqfGofHHU0lQVTuYw55Izk4P6h+1GMa1SgcFLg235qj05KdupTRexouZyZeQnjfBCHlrMfHHmf8A%207yqEATStPSKfuMsjX8Bw+BhSnHjc/Ha4+WBkWxBt0c+5sNb1qqHNbktZl7+jfiQkYAEkTS4vgeSX%20b3XXcptVkJspuSwsTk+PyIZ8R2JM8gAOszeFWRve/wCFNo04eR0tJzacT4zHRXZNC5zXtVG7rAOB%20CdAE/wDatasrKc3ph+fnOi6s9+sXziev4/PxzEDOyfVBilc4eY7XaeYlCb3P7vhUxHhp4eOv2Lql%20oT6NGlksvDGGKxvcHKROiHqlAbvDUIBAQm6pqgtQ5zeMY6mFvZcTXYvOA93cm3ksWLziJ0sYQOOj%205GjzKo/MtVuaebU4wtfhkYX9lVaW6npyg4wUACgDkXvY7vcma0H5nsDkTT02qdelWsjOxSMIfMSS%20VF7GwSy/denIpFGRqEhTuUWCEL06U5Ql4DEq7NoTQscCQSiqv2g3okCFyDmw4rIGDaXqBYDawEWP%20hTTQGfnYXmR0bdxRC0AFN1/49rUSOQSOdFGXs8pbGXAOCAgBR8CllprUGHiQmPHaVLS4Oe55sFIU%20LS1QDOW0sZYhzdw3PUXLQoX93lpgsYwiA9zWtICAgBoXVSU+KUaYx+QZvLqUfuOfKglxzjubuQkD%20XUFq2061LaSKWpWM4SbkOc492T5IYxuyZiAR5Coao/zJXO+RpZanS+NyXHuLkZXSSxwsLGThsckp%20ALtoCKOzTXPU3U1hrKOvb8zNH9VLjy4bJnRlzhsmNw5zboT1KL27XrFp8T3L9vVfge/w8tf5BLg5%20cuf+3k7+F+/n5GrwuRny+QhgG0Y0ZBLH3LmMG0NKqOotUcPOuRsn+Y/g37Pjpad05W/3vDw/A0mK%20TPx5LkYWF7QAEupsnlKXSvX4XNUfJ8ihmR9ycPh40reSN4XSiLNxlAWP8zmEfmb18ajkS2yVRy4J%20vMcc8+zGtx1lgh2yOlASR0ZUtCFDZQENcKt+o67VyMdG23m8pe1GOAspAH7gPCrZOMfUjyvaGF8r%20tshcFDegBVRZFJFUhWGosd4c1+lwirdetDshMQ+MG7DvJvtsvfpZKEx7Rh7jp0df9jVpEvLUs8Pi%20mS4e97kfJ5o3gXaBpr3rzuf3jV8tEfdfxH/xunL7RvklX5M0+tV0+evkQ8qbaJMaBnoxqWSEHzu7%207jqh6Ba6eLj3fqs5Z4Xv/f8A+Ore24F6dK/ps/7r95fTyIRaFBAAb0CIEPVBpXUfPqpEzYjsDhqC%20ht4KPuFbcbM7IiMdZCvcWrUmAip/jRIaBElfsUUpHoAuTTWhMTDB6dqcjYZNhQINqmy/j2+NCCAE%207VCfdRI1mHG69+g1+FITJsTXxROcGF7uwC9O321NmjSQ8KLKmkL4S1krAo3uAUn8PCmqO2QKyrmX%20GHl5cZdi5LHOAKsa4kDcFR0bwbX0/wAKqvLycTz0G6U5FKJzoI98JZINkjz5ZEAVvQkai/5a6qe7%20q1nkzC3troKWGSJzt7QjdSLtsjVahDfOlyn3V1rkVtDmtVo9i47T/wBHoWsaP/5KxALC0A+FeH7h%20/u+J3cXQ86wszi1g/SEFzlDyouiAH8oCmvL6QbJMdfg8iTtfsHpt3biSUa7cDf8Ab99PXUpIlsac%20ctc8iZwUsJO0W1aDoqjrrSnsUoLbEc5zfOCCtm/MVVQPiFo3GqgU4vDbO2ggr1HgT8KJKfiyLyhe%20eHyXFU9I3aLBUW/wqqv9RL0ORv8AUZOxkCmRU2gFHNJuoFrdK7pRzI1GREWwNBbtc1NwIuD+w6/2%201z2PS41FciZwMTcjk8SJwG17xv1uG+dx/BP3UId7RWTN+4uT/Xc5nZakh0zhHceVoO0IQewrvS6Y%20+h5qnGMdNcq50pJJBDezQLIbW+4UTOv5hKxjXX7hky7CEHluh111VbU0gl4xn3X07BzFxYUebbUK%20lEsP46URlOJFbxXl9fs+7IOHJMkRG1CqIdAh6AiiI1YOJ8cY/IRtAuupUL+NKMYwhZR4CWAhy79w%20RrQFAuTqV+NHgVPfGOhIidclhAOgadD0QqlDeix5hOv5Y7+Xky69lRmb3jxLAN5dkx7lKql3Kfs1%20oYraStMY+3x3HJvMvL5kjdrZPWLGSOLgi2a4bSB5Uuf7q8jkeeeP6nr8cbfCDHe4+Q9XLixmSrFj%20n+bC03c83a0+F66OKupy+65HMC+CyWukfK9x3BpUKdyJ8o+bsmlLmWWR5/JZwS8vmuPhlZivljZL%20K4xva5rniMuKkPYQo7XU27VzU4rPPHzwvAzq56v6fd8/JxA9jDAMORFMwxZjGn1gNpD2u0dHZdU0%20K1rbjhZlqkLyG8jFa1ZtwjfIU8h3NGgLbqltD1rG1bJZ55GbpC1kQyTHja1rySIwrCAXAN3L8yJ4%202Xx6oVeMfL7BVtDz1n7sawCaHi5oRO1zI523/UFzlJRU2+VCNP7q0TekFRlktMSTeJ9wy8YHGbGe%205z1LJwUFhr0v5hY10LmeWmRHHCes4xma7BdnZONHyPEcmcdrl9ZrbvYfzb2vrrrbcpG4LTieT56Z%20kvEcm4F8riYMpxaFFztelr9O1aJolrI1XH4H6HDMEgYVUN8wcC51lS60WJgYiEQyMrdIwtYxoEYa%20GubckndqVXdWafQbBweY12I71mFvpbvQIAbuaHdG/mXuatvMFJOyMrFjx48yKMSatkJTcF/KTSlC%20jqQMvnjDiumxWeZ+3yPFmH/I4CmmEC8Xk2ZYEj2SGGa7mFQ6N41QHvTHBzn3vhwY3PZBgk8kv87a%20LPQi5KnVdAl6zsp/H64n+ns+0s3SPh4FF/LZuAZ/qBjvTcdSBZwbf8twf7LynnPhn9sZfLzOmV4+%20emWMdo7ig37iR5iCHL83YaG3f404yzxOmfee/wASU/wJ/CtI5vj3NYFGRCGgFXEeqHE2W3mJomfl%20haEXutr8cfYeuqZ5AKABQBw339y7IfefIwh43Ncxgb8pG6NhN0q6xBDyZSt5aFxdGu3agaSUAt+Y%20313JVKGEEl2djkjY8IFkBsAQbC9xakkKBLsmHcyN72h3ykdEB+z4mm2EFZzk8Ds3096+lGNuzQlV%20ci7U0pBBTNlkaWvjl9NzQS17QdwU7tvilK6kcjOVNlyukknmLvX2QCPQMaCNyDp4pRSsdRT1LB0m%20yVznODXNVoaCACgDgvU69KqZCCPkgOLTt3DaAGm6lwUlAR9tCYYx9pByHM9Vrng7Wj+U0Cxv4iqT%20+QQZnLyWjkmulcAyV3p7nfKE0Qj/AGyi1nyL9JpxfuTJ4Zm8fLK1d27cFCOCC+h/Y1wtpnWpE8Sw%20y5j5Mr+cWq1oddU0AH8Km7jQ0r49SY/hoHTQxkEMdKhGjvMvULcDrf4Vm+NcmTyOz2fv+T2lvU44%20nxJ/Ee2JYeWEgkAijkHpxP8AMZIz8ykAAEdqKew2XTTn4dND0vd//KH7r29uLk482v3J9ZnTy/2i%20fHizYuRmy40jsqSe0cLzta3ahI/Mu0V6labE4Z8i7SzN+6Jo8XjIdzRLIXBzI3ab73IS6G3jUcq2%20qCuOybkucLkG4vs2eFpEkkOOsq6gyv0KoleZZPcdiWRg/SY+JpxyrgiRvKIeiIb1oicitn/TjIbG%20drXFqkOBCG5Ct+NaJOPAlruKe9zmNLAgcu8t6DRL6i1KehSSDDN5WNp2IPMALkkLbsOwpNiEZ8ML%20WGPdunHym1wToaKWb8giIY2/Pz3eUSEIQA1jQ0p26/tpUL21Fmezy/8AyT3tlG5VjpVJfj2IcwcH%20l5cXSFwDnO/MB1X4V0USiEePzct+Szte26zBJBI1oe0KEPRKasm4MbVlEF5LoVXcXBQNNBr49q2q%20/wBRm9CvVHG6Hp+FbozgMlCgP4a0AJUdPtokJCRFUAfgPv8AjRIMV4podTrQMVf7utABbtpvcaAG%20iQD32Uj7T0AoTFEgY9wKgUpGpNZ7QmfgcliZsLgJN24PkbuaQLEOCH9u1S058i3G3Md5/iIJuRyc%20iJjYi6RznRgoB18gKEXIVK7H7f8ATNTnpzQ4sSONwJ8uEASDcxGo4ecXJ7X+Nc3+Q65WUnQuJWzW%20QebwmYWiOeJ3p/5oSikDUVVfSvpkxf8AaU8UQWRZcDduLMXuaHAwzgBvl1Fz1rR+3vXR5Evmrb9y%20PaOFI5v0hxpHAAjhY3OBsP8A6cHwrh5ZhzqXWJy0PPjsxpjc5u5geU9R5Nr+UAX3ID8K8tt4xjw6%20bz3HHZaEGF7XOLiAEIBAO4bVW7lTT+FTbLwQ1bsJiyHumLgA9pIJaU2lbKCdTuRe5TpROeMadOn2%20Wn0JuLK/0WEyO3OvtRSSRe56/wB9UzXLsPSPABU/zAQ0di4uUNTTcAKcsZF5OaR3F5m1wcWxO3ta%20CBuJvqmrVWnV5oVkYqB5HARN9NjnR5ILpDaXabhvbaPjXVZtZmFO6Jr3OfG5x8xQKStzra3j+wrN%20noLGQnic/wDQ4fKZ+8erhY5bG4m5fIgaeiddK04lmjn9xb9MGIilRrQ83VQ4kiyqCK7HocXigxL5%20ib2VzgqoF66IRTa6BAtdWFxKhARYggLQPURDNtVpI2tso8oaBa+669KGggS/ewgoAbFwsQCVA7U0%20C7Du1r27hZh1KX/a1A8Yx+IUkUIB3PIaT3S6f2d6QhbDGCQ07nEAlL9B91CcDfnjH1L32VlDH93c%20RM9Njclu5UDUNrr9lLQm2azxj+pt/cLxh8tnNJO+OWRzGjo5wUOCffXl3pnEHrcfInWUc7yfXyfW%20yWsZ+qDrPLg0uCk7U/A/hXXTI8+ynMgYXMcrh5jSYw0lyGJAWqvQH4opp2orKMfMiwxyeaw5Zwo3%20KN5flFd26V9yVP8AkFVWsKTNmn4jky7CxcmT+Y7CcIZLeZrSfnVfN8Kw5FNo7jbzLnKmLgY5gXNk%20XHkcg8yI5niBai9E1jDFZJogvw86NoZG0zsO5Tt2kFPOQ1U62vp0rlUTj4fZ+ZzujWbWOgk4mbuG%20U87ZXBznOJ3OBA6lHL83c6X6I616RjHh5eK2OIjLHj4CWQSptftV4IG8OQflCL10P9lUu6yxj8x2%20T7PGP6k/g8rN4/PPoufJCGrNHEQoFylkXyjtrWvHyRELGNCq559GdDj5bj24xkzQRGQscciteCoG%201E00/wAK6001IbS64jLlkHoYzrfMgvtBW9z2piaYXIYJ3+hHlsblyTet6TiS5zQPlLge9FVBLzxj%204ismJrMCbFjk2ySQljCXHyuc5XJ1saucwQxwEEhxJ8DPyXSF7vUYGONnAX82t00pPkUjgXj4xZk5%200TC9zdgkIe5f5iEbtDdKJTAPiM7E/pCPa6N8TjEWOtueD5drk7VTJiFmZ33piuOFick1pbsc6CRx%20epLXqhsTcar0rO66s9D2XJ/b3MbNI5rC0bfnLQOrtyHUEov7JcVnJ6Uz8hp0jlIDirbNc24dppZN%201k6/CqyWuREuJ1n7C89mTmP3Fx02NiDInfM1p3vLY2DeDvTbexKVO7uYc9omsnrKtTzQUACgDzN9%20UsiQfUPmFCtbLEGi/wD8GP8Avql4iaMyMqMIXtAYnzfC/eifiJ1DGY07mkolkJQKbqfsp5ijsSIc%20sB13u2lN6G5A8bdKU/ACn5LmZmPftc5wDlPX7EHxobzGMjm5NXBQ5Fd3uaJFkP4/IuknjD2giNXu%20K97C320/IepNdyELngrvcLhSFt18RT8OoQRhyjXK5rjuBBJQqCT/AA60CjsNzZO8KZAdSSQUXUk3%200QUIfkZfkMl8ywTMB2t3BjSGq5dzXgj4pQ3KCqaZpjJNlcZi5sZ3IxpctkkZ5XW6j4V51lFmj0au%20aygoQ6HNgfI3aXlqtB8oJ+7rUtyhpZlxmMmbmY+OxGF84Hq6lrW6oO/2VXApZHM/0mgzsSV8jHRT%20CBrGB0M4PYEu3hE0JrudNznSDh3wipn5JuOwnImYUcPUkcfKQTYtNv7q0WSJiTDe7OWfl5sMePCf%20RY0COZ+jnIAoAstrVy8t9x08dI1L/i8J8vG87iPc5srcCOW41c13yqbIhv8A4VxOJOgwglx2FcgC%20N7hvjDV8xGqJ49a3VXbQzdkuo0/MbmwSukjD8jGIWdPyGwB6WWtNrRG7cxgPHqH04y8N16Et6lBQ%201GoKyeMST4JHsjDnQgOa0vLuotb8Na5rKTZEOZ3qvc8eZ10Wy9ept8K2SjIh5jX8wEOAPmsQE61W%20RLAXnzs2guP5gitWgTTECeUxeiGEEWcXKltFvRAn2I8jGr5gjTfzHqOlaVcaENZlS60hvbQDxW9d%20CMoA4AC3ToKpgII6EFAiEWWkwCcWhVAJCho0UID1+FA0mDdc6nVV1FImB1rvIQpBPemA3vAcihVA%20N+pFqBjsbQT46fstEC+Iki9AzSe14hJAJnP2bXpFEPM55H+ydB40pgZb5TmjIk2h3ld5GPu5jtSq%207rbnftevX4nuSnscdlnHb8MeQeNmS4z97Gh4cokB8tkXxI2qUJJqebhV1MFU5NvkW2JyzskvY1GF%20vmbE4jVvYnxry+X27o4OunNuWhAz5WZYmnxmB0UI2yBw843NHmKJoldvDV1ybOflc5nrzjonP+km%20LGwK53DxgAWJJgH4mvN9xnu+JvxvQ89DieXJ2R4z1HlITQtJNty23Xrydixj8zo2sJ+FyrGua/Fk%20DQTdwcNSiDzea9wtG1LGPuK2MTDxvJfqGyOG14cryquBVKFWCq8bnuWv6fIQveA0BA8Obdeouo6W%20ppGqcCg2Nyq1zhECHPADUAOoJW7V702ipI2XCJsOZWBvqRPLSTorfsNvj+FNVRLcGF/UZL+IjiaT%20BEJWhsYb87FVxJ6XFdNoiTGrfcmiQgHzWFtt/wDeUfaKz6netDPc/kyMa6EHbHMQMgaAgXao0Nq3%204dTm51kUrf8AO9utrhLC3411HIKGtiVFxt10Vevc0SEEhrUvYgq83sASv7GiQI0xLHhybvzOXtp2%200WheBUvqOFz0Dmt3tN3Dpud3BU/CglA3iN29t2NA8LFFN6B4+4WyeKTUEEqLIlzrceAoYdBz9Q0N%20+W+m0oCD+UELRHYEGJ3MkY9r9krUdD/vNKgp8elDfXxBHUcvkz7q4aDnOJg/U83GI8XluPj+ctUN%203tBI6VzXp+rHQ04+R1TRzDkOPdj8jl4zZ/8ASlfG1L7WtOrjp5dKfQN0kKUjB5CCVshfErXb16go%20R91UnJLZWSmIZOS5jvWZvJif1IJJ0K9dapZJEW1ZreFyYpeLkwxuinjaZGlAjjfa1dRtSufY3aRJ%20F6cotxDM1d9pRtBCOb49taazKTOi8R7b4jkOJxM0OduyGBzo3ggt6KSo79PjXO0tC1XIkj2dxzGo%202aUMUKbFSqkAIiU0kOCL/wAoYMSudukANmuuE1oSqLYNO4PDxZS+OJ7XFX7gXBwB6A66L+FNKCXV%20Cp8VszCzLkMnplzo/VGhH+0COiVoreInUEPNzYWCcTj5osfJexRLIA56IikC2nftWm+2iRm6Ia4R%202Ri5v6l0X6iZNpllcNbhz7qbfGirzCyRNyubZIyXGE6SXL3ohPcA3/GrlwRtI0PuhkQWQDc1rS14%20H8wkflaOpRb0NoC5bm52RhyZUAcMtsgc9xCNazs42Bt932UmyciXMcB8TIDkCKfMO+KRxJ/mgAED%20StKkWXcqvfj3DgsfDihDWuesiIEICH4LrSu/0nX7N/rnGMI504PjcS1pRCNv+yqg/D+NZHrZYxI2%204uI0DXBFPYgWHfpR4inGFjM1n0/2/wBQx3F7T6U7Npd3LglrarSs/wBSOPnR6qrc4QUACgDzB9Vp%20iPqJzUYRXSwgWFlhj8fCs2UkZds0TtDr3I6iy022/MIA1zS5w3eA1sQKpNzIgo3EkFCPgqKD9lOe%204QZ/MLXTuLApBIJuflTpobUKwOpGd5SA+xKbwB5VFgtORQTMUybVc02am4/G4P20pEPmQsYU2gtU%207+iHp+Jp+QZjLp3Nkc1CQoDT4kKGlP30aLQQqXJY6KYys8obtaVUgkIFA8bXqnqNFBlZbIxJN6Lh%20Ix2ySdykbigsf2WqbYJGt9kSul4MQu/mv3k6rrZR96AV5nuI3Seh7d/pJuRD/Nbuapa6ziCLD9ut%20Z9C+w9zwmMHHBij1Cj9pQHb8yjWteB5mfPoTeS9x43HceWPkEk7QW7WjRqglBbr2/wAO+10lmcKo%203oYX3Dmz5WLE6XVxJbCDZoHXwrl9STo9NLGpW4vKS480WO8h2w73ROAc0bAtifjUunVDV15m64Hl%20sbKweUzmOL5zivxczGPzHc4emWrrrciuWyaZtOWOxkOQ4aOWNkk5bAWgGxVxbdESr4uZrIyvSSrl%20ikgxWx46iF+4yA/M82bud/Cul8iepCrGg/xkY/luehcpAP8AsgDUjrWXK9YL41JayNY4Fp8zTY9F%20ri3dToKXJQZiObtAKILEol/jXbR/pMGswpQI3WCseXINAh1S3bvQnIDLoyCWgaWPh0ut+tXJMIak%20aXP3NLmtOjAbFdF+CU5IaG5nNdGqIAgt0HgtNCbkpZrTlPGuxGHUS5UH49k60wEOIAJUGx1I0XvS%20GFoQE0UtRSbWvSCAA3Collfci5uAtMB6O6tPbt1CKvehMMxhzi07Qbj5TbR2njRIC4nIUCgXAXqn%2040ZigU51x8U6CnIF7wQb6T3lXl38trY/mAcLnx/hSakpOC8bGY4GPO4jYI45RYKpUO0N0I1/u9P2%20906ROmPz+ByctXu0CO4qA4yfkt/mIICIilARfVSi61v5GSyGgXBxVx3INu0IpFhppU3XRmk5+KJc%20mT6OVI0gH1Y/TyWf5wBdfGsVSUVuep7K9vhp+mPHCzGnioR0AT0Rrpr1ryufW3xOmnSDnDo4WFXK%202RoDXE6Ar16ol/trzl2OtufIgZTw5zUlJaxu0E9FP9vWlCyHJFa7D2uY0NAeQXoELj8e1EVB2kal%20lw3lshBIRTISUI6KOuvjVbQ3T8RDX4b22a0N+UtcSCQ0ABKSqNtkbPjwBjzudAAjHuBW5sQSo60L%20oDZy3jxlyYbWBzf08ch32V7juJQdhXTYmmbJpOqDXQdRXNJ36mb58kyhQQASpIT4Xvb7a6OHwObm%20zxjHwITwCN4agABPQCy6furq+JyOQmhwdYqCTqPBDqdUphkORS7XhpvdpGrSp1S16T0GwpwCwWCN%20KtIs5OyW7fhTYQR8d7d4if8AK9QHdb9R20FNv6BmPvLmDYbAhIyii/ie1LzBwMPcAQWgaqeiKgsd%20TRABNlkKoSoFw24UFRqdetDALfKw9HIBuB6Hw/s7005Bsfx8nIxZXZEEkuM8N2b43Fu4Hpub+6oe%20moZCDIWuI+VpUufclxJ8fmPes/IbeRZczwGdDwOLzUQL+PcTHMXfNG8qAUOoctTR9B2MwXgRl7gp%20JG0eJsb960+0iHBovbUry9u2QML2Oa4kBXEdAe5SpuCL3Fkd+j2Eg7onhoAsHN6W6damIDU679P8%20oT+0sF+5CWnzjVQ6zU8O9c9lDNNekl7NIxh80ZeHLdnygWP7LUNFKegbXh5JJVSC4O8PH5hTjuJY%20xoJe2ParmKSCPU/E38BanMagp0RX5ePHHCZWFoEaEMd/vIU18KquvkRfSTKuZjzcu5z2MADDse0q%20u0Kj9RZK6FWIRg2FixYcmaJ8TId5WuDsU2JJW1+3Sk65Z4xjsG4sIOMxTG9qjGcVL3tG9x0JbfwH%20WigmyHxz2DLflEDY47WySITuKI1vRtu1a3r2Wpi2ozeMdTXcVyeE7Oi42OQSsym7Y9SFDdxCIb/F%20KFVjIvIcLPkyS4LHshkif62ISVcx4u5oGqJpTTjUF88YyM9715LP5KPGx4JP07okfM3U7xZzXfZ1%20qLuMjo4H1MlJk8nCUyMYTtaNu9hsAbEDtUODrXKwmZ3HTOa15MMwAADwgVVChAq0bXqWuWvXGPty%20NN7KDIOSgDH7gMmItACruenmHgmtS+jJ5XKZ6vrc4QUACgDyr9W3g/Ufn2k6SxAKpQGCI2H31jbX%20HYtZGTDyVa8X6ISShULpSl6AhQkTvodEFwPHqT1qgzFxTFtlUkE3KXAJKKuuqUJ98wKXJka2Yg/M%20HK6/idQfCrQSES0lrGkAEkd/BPxoQD8L27gwSeTYPIQUAQFSeuq0IUD0gjAJcXBpadpbdD9tNgki%20Awu3EITuQkG6gd07fhVSKBuZ7mMmZucHAWct9ocAQfspqzakHrmisndLksc31hBHEDIN3mD3dQgH%20YUNiRcfTzIhZM7HLt4fDuDGlG/MpBP8AmtXF7lM7eA3nIxGQlzHbmootucSQOvTUaW/dXKbkPlMi%20SL25lTREetjOa6NyKGggNVv21pxWixHLWUYzDj/qkrQXOD5Xtc/e5NxVTtdWt29TGqUk/wB0RYmN%20zBxNhfHCxojdZASLt3IlZcacSO+mMMzuIscEuSyNjCw7GAgvIaT5ut7Vs7TkKIeZZ8byWNizRGVz%20n4r3tbJJEjSQ7t8KzabKrkWXufhp8KSPKxnB/HzAuxXH8y3Rx1stZVakdnJnsuCaKOKfeBKxpDmG%20+oQlunWtqNfMzspFcejBtYLFodt6311v41nyqdSq6k4Byku10AGiCuV/U1RFmJcqljmNb5n9SQe3%20at6EMjP3SdWgAhQNFQFQnQ/h+7RWgljSxAkC4DV3lD8AU7LVZi0Ijgj72jPzafEWPetEybEeR0j4%203QENRdwB7EJcj7a1rCZk9CmnaRKhJ8VC3710mMAJVqgnVAmqj40xyE4oVIQDRAPgaQDbB5QECBCP%20G+ifbQDQViBobIoPY+OlEDjoPQHa4uIRBdvcnqfuoT6iESu2uUlGi5drcdKAgWELhu7he5A100oA%20dn2b0HlYigfmH99NsC/4GHIjwJ8tsO7GD2tdOwkuYmu0W71NhpouccyhjP0sjgrd0ZehG0kL8y9u%201eh7eFTM5uRfq6C5II3+o+cObIwruYiI519oJUqoKr/CtfV07E7ekDGO9sLyXFWxuaU08w8U8Km3%20Knl3GqPUEgMjJpHtB3Oeu66Wun4VpuynyJ2s9ncC4/8ATDjnAKf6VAQ0/wD6FvYj99ePzuZg66LQ%205ZJLlgElu0hUU+U+NlryszuZBdE5xHqfzHAWCoE7fjTiBQhuaJ0cRazUqC43K91HgK0CIKeeXKmc%20nyxm1rlPFLgWo0Y0hbS0sIa4K0L5tTtCINEFvtoSENZjXvAYXNDZCRMATuQ9tE+FNMIgwXGwtwxk%20sma9pbK9sW4oNpJFr1rZofEsxRnhMbi148oUuaQSEW9u1YydkmZ51xMzg0C7ipuBayG+vitdHEc3%20P9RLg6NrWxv3MaAdxPXT99q3XiczQ05zXFShUjVSoHX+2q0EGjSD5l1RtwvVB+3WmGYTZGkINQQA%20qWaq60QwgZmjUBwDidemirf7reFBKHoJ2kCGYbgVLRcDrYmiFElQFNiFrt0fmW9hqBb9jRmIRHDI%209wBYSAgcQNpRfGlIMksgDGK8qQVcDcL2T7bUasBn0pMzMighbYkHVSp6/saTyQzZcZ9NoRkiTMmO%20RvO/0ydCex8PxrjvzG1eJGh994Qm9i5TGENMRjeA0ANcAQ0A/f2qON/q8wssoOKGKea7UUqXBb6d%20ia7p6HO1Jee22TRyBrQHSAuDWuNtEKk1NhpGgwCf0bXFCGslIut9DWdoRa8cY8Dq304c8e1cVzS1%20kauQN7Arc2QrXPd/qZaWRpzJkEoCCHG4A1v1Um9KWKEEXygedxKhQlyWqUVPifvqcx5CXzvax73S%20hrWqHOcvxNiet/sNWLIzfMctByGM6PDkcJIZotpIQOJ/KVstVRNMzu8s9SHi8fNJkT74/KxfTDwX%20FN28IhvbXr0rqUzqc0jcXtZ08pkZkCKRo8zGi5BKlq2XStGiJglScdl5IbAA9gYiNaFBAshuBZBe%201ZpRmG5kp3CwTsDMueSNwQOYoABBTft7uq9wdCyxOKiY12Xw2wTNbteZgjwGAj+Wmjj3rRtC1YzF%20ykL2DLle45WEds0wap2j/MB/vEVNgSKPmcmLOzXTsZsY8DW+4OQqi2WuW+sHbxaFd6QLjtcTtPld%200XsLdqmYNWRMnjMeViTRiXeijqvexpq0EtEPE/qvDctgycSxy5OXBFlEtLwyMyt3bddR1qk5H3PZ%201bHKCgAUAeTfq/I0fVDnTptlhU6G+PGOxtWVlmWkZQkBzX7iV8jgUub3/CpKgdaXiwJJHmDtSPtP%20WlGPoKBStsb3A1sCNdPA1QQVGau8Ibgkj7z3qqiIsjnC+qFeq2CfxqpESsVxI3MZ5mgi2p2lUIP2%20UOQFz5DPTawOG1w3CPSwtYj7rdFojMCM1xD/AC3Q7mjXxRG9zTkRHyp3shlLULXbXJ2Og01HhVAV%203IuxGSMGLK6SLaGzFD5jqVW6U2mCcFh7Nhbj8jBOQ4SvcWxtCtAaLK7o0f71cvO5R08PidRlI2t3%20K8t2RgHQAE7vAa6GuFHWNDCfPFmRNcDjSsfFopKjylp1O00k3IWzUPUzH054huZ7g2ZLA6PCie9x%20AHzbkb+IFdHI5OZZFby/Puxs6Zr8duZiGd4bizKhjBPyyfM0/bRx0b6g7pDUmPw3Iky8NLLHmRNV%203HSfOGnX03fm29qbo0KVBUNZ/wAM2KbcBA4rktCFr16t117U2xNGp9q8z+vZ/QcyL1cTI3Bkn/wn%20oC1/gF6VjesdTSr+RnMwpykkA82RHIYwv+kdpN2rr5b2rSP0kQtMfgSRBE/IdKSTIxG+CC+nxrB2%20ygtVDyP1D2kN8jXAfl8w1Xw0qawtS22E/HeXB+jmuVWm/wC7qtVuRMMiyDKkd5gI49GkXdu0Wx8K%20pNfFksjytK7i0NdtBRosoKXBTWtaskZlYADvQ3Qi1kPWrT7EvuR9w9NzA0kuuviOn3HvWiT1M28i%20ny0OU5wQu0c5VA7101MrajZswHUu66Wun41TENO66jxHfv8AEUDmNQnEAFQUsUNja1IcPQBUnbdC%20bgW18DYrTFA7jMLg7aiiwd370IBt4PqlXaEKRYEp4rROYP5jrgwEBp8CtiVFPLoIfxct+LK6RsYd%20K5pYxzltu6ipspHMFjws+VHux2OkEc0gLomFyOIupA1t0ptRoOUpk0zmQyMMzSY4yGhzUJLXLbc0%203v8A2+C93t7TWDl5VDkQ8tD3bbDaNgKkEko5SU7fsVrpVe5DyyGC0DHmW6PBY3VttQetcXJWbSb1%20vlBJnewxv23VqFyBCrbXH21tslZmO7M9k8EHD6X4AsHf0qIJqP8ARAQ6V5nKtTro5zOUSSPILEU6%20l2ulu/avKSZ3DL5CwgucgB6XWmlAmyPkTTOjIBamgc1UXsTVJYxhh8SqynyBxTyKbhtiUTU/ChQN%20oryGFWve4EWcdFCrVyGYqPHgY07XuLnklxJW1kW9MUmX93Ni9R25wawsGxCQpX8D2qq4+8dLw9c/%20sKjHcQ0uIBjUKUG5QTewv5k6k0mvnjHY6lbKfAo+ZcXSgrtNkNyVPxAGhHTSt+M5eYQAGxtaXb3A%20lPAHre+tbxJzjYc5UK7XKF1vfVbJfrTE2JUgN2ODhYg2Nr/hR5jGnSecrdVIGmt/w8aaYtCSyQSK%20jlf1BKk2HlSiPkECXtabsK3SRotfQL9lGaAKDNfCNpu0jchKIB4DrR5gmTIsuKRupBuCo7apQxsa%20yZwbbtr2/lBCDsttVp5jNF7BwGzcm97BuONHvJJCEkp5l6iubneRXH36G99DIhaSWlzBoT5fjbUA%20DwrhOgPl2sz/AG5yUIYTK+B+1lhcebdV1WZLyOHxwtLCAPOW7VGoQJ08a7jm6FlxAdG/1CCHNaSX%20NGmtync0mGpZ40zWYQuSGRvkNiArlRDUPUaOp+xBPj+3OPDckNi2uL4SAu4uvtPjXNyPM1SNfG97%20GOAkJLwqLbsltaES9R1uSwndv2ub1FgUCBHfadapPGPtFHQpuVw87Ly2/ppmDHkG2RjinmHj4p2o%20UzoNpRLKTN42bCdDPuZ+mXa9rr+cXa+/mJU1aSepPJkheXn5UAZMd8jSGuPRgIS7mjrc11RnqcjZ%20M4/LfNF+saNilZGs89wQjfjVpoziMoJsvLlj3PxpUY1NxkarWnaD8SKTfdCS6juK9uc5s0hL8l7W%20mWFgVunzMTsulZ7UOHOMeLLXhsjBmyvS9dvrBqGBw2AjcoQdCEvV5CWXQLG9ttwszKycV4fNMF/T%20ordqrck3J70MqDJ87hvh5GZrSrFG5wCINECdq5+TU7ON5FWxwAaAS6wAP2/m+CVEGvmSBBG8Erqg%20Icdp0Oi9KQshWIG43LYL3lG/qYWBflUvAH21SzBqUz1TXScoKABQB5D+skhH1V59odrJEhOgP6eJ%20dL6Cs7amtTJMlV2xfns1SmgQ7gDqaiOo4DZkncLoDbuhAAtqKGhwybHO8tNiSEIvYOBT/wB1KQiF%20msa+TcUU3sEs6wSrTFEsiPgKna4bm+VbJpp8KbfcW3GMheLE5rFLgofZh69b+FOYFAuUuLGMABe1%20dhQ7ipsClrJQgYxC2IzAuXYvmA6pZdaomBic+V73Da1nmANzYgNS3anUGQIMSbIyw1j9jw4yNUeV%20t1du8T3pWtCKrWS99mZEU2VmyFAGubHG7UjaUW9worn51lmdPCdJdBivwS/c5rg0bgiBeo+461yb%20czeWM4IjiyWwkloedqKA0k+ABVP271LY0UnsLJjw8j3E93l/TxytCjaAiqNx8K0eRgzEZc2FPGBK%204OJtou1Tr36VVFZaA/EIug3NLv5LiAcfIaocp0vY9b1X6uhKSLh2LH7kMQxFi5wjZNCCA2dgN3WV%20rXtTvUq23UrbJLzMfH4rE/pPFy7+Raf+Oyz8oIuWMXS2pNZPkWr0KaePsM76YjlET3NdK51nFLDW%20y9Setabu2hMZ56kuV+yQXs8gFAt6wg0eoGuEbC1S6QAbUOhNwvhUtZhmhluZuDmuDWPadjXXILr6%20jw7VT4fiS7wIje9wc1zfM1WuI+VQEVe9VaqRMkeZrGh7mKS4eYddpCnzH4KUq0xNBfpsd0UfrI1u%203cE8pPYJ1tVS5JeeRU8kxsZZC3zQubv9Rtgn320rp4nOplfwxjuUu7c9QvZLKAErqTMQ3EoAVTRo%20VdfjTTBZDZ3X2roCPiPN1oga0E7QApulydenVfjSFqIRCbAhQgX+PSnI/wAyVBG0ROL1aXOUFEAH%20cotC0BEdqOeVCLcqiotgQNfCgCVFDva6QoPT8wCm5VCB43p5CkOJjp8lgHzl1txsvjRqCZY4r8x/%20IOkicf1DHEbmEBSSlvBTQkM1UWVI+QwzSB4cy5PyqSE0sLoK9DZluRyz0CewmR7PMXJtZtLS5FUC%203Tylfs7CtlbLGOuRnpkNuLDEwraRxeGtu3946isq1g0dmMyu8iAgEtG4EX+ztWqrBEye0uHRv0ww%20Qlv6VECCosYB8K8TlzTk7aqGjkpJ/KPl8PHsa81JnY8yPJ6riUa1wtcoq9telNJ6B4kTIDmxn1Re%204c5hCeCBT8KoERdqklUcSVSy7e51tSgr7BL2sRrQACB5QCXAE3Fgp60wWY1OxAqgHS6koll+7WhI%20JZjfd4a3cXNaSGKCQdRcJ2rXjIeMY8zOAmTEZKCj3t2qQHOJu1Qovr3p2NuO0qCDlx+q9pOh3FxY%20Tcg3PUre9aceuRHKyM+BkrS7a1ReRbqT2N66TlGzBksJIaUujVug1B8FvRI1kOMgkkZdiMGm4IqJ%209t6UgNzQAK4XTzO0GoRe1MJGo5JIiV06fA9V60xLImuLJm77xvNgOlyVv8B2pRBTE+nBEDJKVcdG%20AguK/wBtLMGxhz5JCA0GNqrtb8+ttBTkUimRuBDQFcdOoFyPN40SGRuvp26SCXOcwo8saC+xBc5F%20ui1z86TNKODWy8nMwkKhVQ1oJF7npXO6otMZHKQkH1mFxcDvREKjRVH+al6Y3bI5Dm4Xo8hLEpY+%20OR4v+YEqFH211p5GD10JeM70YJJCHN3DZbuAiOFrLSeoIkvD/wBOIGoXODYQAPzO1F/hUSX5nbeD%20xmYnE4eK4KY4mk3FidblNK5m8ypLSOSIOVrQEITaQSh6UpGOMn+UPaCnUkoQeh8KrdnIoEOO5i7Q%20DoXA976fCm3kCWZT+6o4pOHkkcrpsdzZIg6w37kJQp0Jq6OWRfJZDjcGBsbRPtdHkxggFv5tgQbQ%20hsnbxrtXgcbkY9vx5+DJkwPA9NBIwMRzkKhHAdV8bUZNEvMS39Tl5f8AJYHTzFCNxYdjUUOd4bjp%203+FTCTE9DQzYrsLjpHYAPmBbNp5W7dQt+lu1OkTmA1w+c2ZgMmAY3SK6KR2pDQm1pTWxP20rZDLy%20GWeNjpWNWZwQ7fyjsl9FGlKuomsih5mJuaI8podHIwmLKYQAQ82DrWW/Sp56vwOngt3M/k4mQ1zg%201geB+ZENgij+Nc0o6UiLtT/ynWGipoNfsvTkOhBz3k5vEtLlDs7GAHiJWpYiqquxVNGeu66TiBQA%20KAPH31rjX6pc8QSplhJAKf8A6tH1rK2ptTQyAc4AeFwCLfxqStBTmguAaoZ2PfwHxpTlkNokMDi1%20pc4kgAqfwVV6/trQyYkTlhzo2uchLUDvt/bvTQ2iD6jvlVNbjt8TamSkScZXNkcPmZ5mqNQ2/lSm%20A5Z0jWkkOXyuF7G33fwpCQxNEBMQ0gtBQJ27delUmDRFyGOk3hULhb7NdPCnJLKuPkHQ5jckx72O%20bsd/+i0J+JK1VlKgKuGan2QzHhzc+BrCWvjEgsBe21CVslYcmaOjjlG34zMD8U/zCC87WAIHK0aB%20vm21x21zOnxIgyGRZcTwNzGbVctyOuo/bulQU13K5sJxsPlsUOJHJZWwPHRgBefsO2tlrJhZZs5+%208kue6MrCwua34AkeNb5aGOhYYGI7LkRjQXOPl3XYEX7U+FZ2aRdatl+3OxuBx5cTjSP1R/8AqeRF%20nI38jO1YNuxpKXxGFx+Ta/JiLv6lEwGaI2bKy43gf5vCk5GrJkD0Btjkcj5GA7HlFqd2UCjqK3te%20wK1NvQi661I9REwjETw07Q6wSyuW1qqrzBkOKKJ8jvzOdc67r/BAK1dsjOBca48Dy521jiGKEaEV%20PuqW9zBrqMDc8N3uLhd4OpLim1NF21eghObEWtEj7vaibrjr8AafG8yLPIoeSlc0FqgbyoaOi33H%20SuzjRjdla1qBEUNt1CA6V0LIgUQ0ALrqTogXWkwSEkFCAPAn+1VogcZyILFKm7QPMqJ91AmIaxxb%20vGjT8322+NqPEb7k1xDMfY4fzFBtqtDcCGNh7I5xBunwFMF5D745I2ua9paWWIPcHw7U+gNB4jPM%2050lhsIaU/OUTxSiAgvuCifiTyOmxz5gfRRUVos8O+NacNd1iLuEWJ2tXa0PY3QoXG/8AmDT8NP8A%20H1DkX1BPlOkaC4K9o2rYK1FFu5velVQUT8WPFkw2PTcGjadxUBzrtcNoGmp8KzcpiY5ksb6fy2LS%20St3E3aHEnb1s0fGnXTHxDw/E9fcS8j6YYTpNf6TFuAtrALdErx+eMzto5g5G7Jx3uc5u5AFNkuvx%20715kr4nZI02XGUbQ646r1AJUGq1F10I0s4RECEgBpvY2HbQUQOXBCVziVOzcQ4BoCoERFTwptDyA%20HbGbWHbuA3EXd5h9nU2ofiCIckpKkoCSSURSgNOBGP8Aeb43MaGOQCJC4XV2idbVpR9SbZmaxcgD%20HxXKHDY8AIui9P31dlqhVt2IU87PTbLG0FznI5pIsltv33rXjUMfJfIjOnDXl4UxO1HXXx00reGY%20tkhkEha10OQSChAWw0tp/CpbHImR3IkFXAgbVcE0HVKchJGEc+7bq8EloBW7TqfjpTWgpjqPRYbn%20AlAigXuCNdPtpNgkSHY2Njs9R5Qbi4OLiF1saWZTIjpDMQ4+Xq1x/ABqU5CRxjo9xDAXBbm/dL/a%20KUQIfhYWua5w85BJQgoD1oCWbj2Niu/RZkpBAfKAm1QUCeb765+a2hpVF/kY7T5i6Qf7R6WHZKxK%20KfOxcoB/pnSxKqdNFFNPINWY7mOMzW5EmS0b/wDMQ1EA66arW1bGTUFUZ27mxSsLYo0fK4gjee3d%20bUxrGPqa/wBme3Zua5MZkoP6LFd6j43qHOk1G0f5QBWFrQa1Oq7Jm20OrUANzqnwFZRA/AUz9UAh%20kDWgXIA+CaJr4UxbRZE7VLXlU18R2v1oaFH1DjdksIDyH9yBt+y9LrkwckbmckPw4cbY0erPFG9W%20qNSVJ7WrSilwRyPLMTm40w5ONsDmh4iLWtPlYBdrUv4dEtXd0OHzLLAwsnDK+nuEpL5toKFxHQ/H%20pUpIVnlmFx/JQ5U7Y8mBkOTGHCJ7gPMF1PYuS1U6wpQ2u5ZZbof0koax75Ubta1ybiHdtamjjUZC%20i5hsAOHmzE5DGhTtBJB8G3RvW9ESyYfQvfb2Yc7Bf+pc2IMkdHHIAACCiOC1aUBYmzYmDLjy48it%20mGiKVOoQpei1JQ6Wc5GRlww15aTdpIIXsD2rz2ocHo1smpIWXDE3c0BFPzIp0TRKEMzXNY5byXFI%20ELs6DyobJK0HTw8KpNDpoz1vXWcQKABQB5M+r3Hy5H1O58wkkiWIluikY8ZPfQVz8l0nmdFNNTEu%20Z6REco2uIILSLDxUKtqSclZ6Yx3HWsbtLVVmrTpoNWmiYEljGPtFRRkINApTqAoH4de1JjFSQGSN%20wDTdL6kHxKmmmG0onh4LkuR5nD4HoFrRKcjOR/Dyn+q4A7Q9rgo1B1t8amyAlRek5jHOWPc3UWNi%20gKHvemsxjTg10irYE2Nl7U0wQzPA8OCL5Qm25KoluppomyKWcDeyJ4LAG7PMCtyoKn7qur6oiDTe%20xMmd7nxyEJEg9Qqpa/Rui6/dXPzJHVxWZsfb5fj8jnYLy7ZDO8MBATztBCdR1rkvmbcYl0cULnOA%20KxuG0v0IAKqniO9ZtwaSI5RZ48Ut3h8RfN6p6naQ4Ei9m/m8KurSM+RSc8dC18AKs3NL0cSAUc4/%20YK6lbM5WkTOLypcaORsbgpaNzz5XBui/BBWd8zTjs1kJjlfPImzbuapnabKfy+On2Vm1BpqKglkZ%20lgxnbIwqNpI2Bb9RUuBFkIPW9Iyk7C55KIGsdcqi27nSuR8mbZp4PHzw9CNPjRt9Nz0U3RCCFNlt%2011rWt5YNESW+RG5WhqoF7p4jWtavIhgiefTLI2JdN5KkjwH23Wk1mSNyxN+UjcCQU1CaDrpTqxWC%20Y8+p6jrNWzrki6D8KYn2I+ZK6xcz1CVaW9VNwiLWnHUztb5GWzpt8papG1beK9/4V6FUc7YNpaG6%207najoSb6GrYQNOeijTwsEqZ1QhLnKqhU+0eFBUMJ8iBQFHjrqi38KYeAuMufsjsQ0Kij4fbTQmLl%20cXP3OO7qHC9h2oYTmB0ge5rmM2PsiGxtqlGfUB2RwBBeS9xU7ibk6r8abAKKQnJja4oS69lQE38t%20JIZthHHPjyZDC58LAwRxpYGxdr/DrXV7ay3GXLVqpEC/mPzABNWkAB11Ttofxr0zlb7dBl9lQKvz%20OQhSpK/Cm3LF0JnCZe2QRAjc9AEXdvAKEpfWx8KzvXOSm8iwe1DIFa4taWvkQXDV3uahDXfMOqhK%20zSyQrZnr3jmhv0sxWpsH9Jj8ougMI7i/3V5HO87HdToccLS0BpO26DzAXAGoBrzTsyA+J19tv84U%20Kb6knvT0DLqNPa4tO4KC75wVPUkX6GlHcEuw07HYGJtW1lPY6fjQNoj+ikwcCG6gNLUQm/w+FEgR%205mg7nhgbdQU0KoQCf/eoDXIxXvmJkQ9UOLQ4ISFHmN7k1txshr5mLxckehj7T0c1hGoJUL4GtYzZ%20KiBl88TWiNx2tIIaQF3K4FV6fZXTUybgUItwcYj6kdy5gI3bu/gmlKAQX6eeAna4bBZ0agFCUvfx%20pyUpDLhf1Jk8AV1J7fGnn2FI3JyOLGCj3PeSNoCIp6/4USpJTE/1HOk8uMxsQFlIUBPjQyk2BmLk%20Pd6kx3yaguKtGmppSGmo6THG0eqQC25aLuOoR1OOwOwg5MJ/KoVSWjoOt+lKIDd2HopXucxrIg0n%205Xuv4dOttaPEZ1r2JFCPb8KEh5c71GtJsRZCe1ef7jU6KaGh/Q4zwE0dfdZCdSLnxrGX1LYw7jok%20IDfLcWAQAkW+zrT3PqRCIsnE4rj5olUEkp0WwKdfjT3MegTOC4xpDzAxzze43eKLoNaN7Dai1wY4%208VoDY2s6HaCnX8bJQ7OcxbSyDw/5VBJBUhAvUXob7hmKaQeiEFEP91IBXqIiC6Hc79w/sptgMZE0%20QjL3FGBNxXS/RKNXmIpMpz8vjMrJBLGRSRDH1XbuF7d9L1vxqMY0M7vIsZpsZkrYZMaUyFoYJXC4%20c9ygW8oB6V3a5ycEZl1jxZjcNjZpGgPAa7YVEbv8ruq/GiIJ+oQ9r4WQf1kJfNICDsLvJ4dXC19K%20LIaXYS7iX5GVDNI2aOSJqna6238wC91ulZzA8/MLN4TivUYcfHBlg/0wCt+pevzak0Vs+o21mOu4%206SaHcQ4thaDDCfNGi7nAO/zOTr/bWqZMKMvyHuHzW5IdBJK5xiBeHud5t5CHyu0A/hQ1IRnDKDks%20nIhzp4mtFvlcShIOht0Brg5Fm8Y8Dv4tE8Y+8rpM14uWkEuFluh6r2NTGPmXpqVuZm+tyvFRMb/+%20uQvLT8xIe3ai20KVVarq8fb8jWmj8UetK6jgBQAKAPMf1Bhx5fqb7jbJLHEBLES6RwGuPGNCRpXL%20zKWb00zM57r4+PjeAkzS9sjSogDPP5j2IColZUrmW9DBcbzzS5rMj+WflBXyj4gaa10OjJVjSQxR%20TtbIx0blUlEJ3LqvjWSKkW5jmtcWqWO0AX7LUJwNZalbPCyGOfa1PWIVx1RVQHveq3SJqEVhgcxS%20CjghYnfqADpV5EdRyMhzQARp5QNE/BaG8ggMkemxllaPI4eN+/j1p5g56hSnfEFuAQ7d2XrpTBlb%20nIzcwXLn7mhCToi3qiZLH2jm5ONzEGPI7cJGhrGoLI4HcgHRLFajkUqS+N9DbCYxe8+WxyFa5kUm%207cGm4BUfAj+6uTkWSZ0cbzJXKAtL8iz3ENRpBAOt0Bdqlkv4XrDxWRspIbfP+nnJc2SLewizv5Za%20dyj/ANrvTrb6itU5/wAgGMnlhliAcXbhI0oC1e3Wu2umRwvLUVixwGQI9znrtcHAiwB6a1HI8iqM%20sMeCVo2RqSqnqi9vFTXLa0nRVdhx0Q3+Zvns4HwIBVfsrPfJSCgyduPsG0bvMhRdrD4rbSptQJyE%20j1JG7pSj3BXNde+t/H7aeSARM0GPaCpaigk3U2/GqViWgbWxq5CCSASD8y99L05FoMySNbJs3AvI%20s0/Yuugq0pRGhEnkcA935zYAqR5R/G4Fa1qR5MreQ5N4hcxrgWu6BLu8E8a3pxqTJ3yyRSQNa+Qv%20kcO51Q3JOtdSWRlIqQh6u6us06FFCW+yh5hIw4httyHqB3t3psaC7K1HDXpbTS9AshJ/yqjW97pp%20RqPUk44ja2UykEloEetvt1NqbcIUiNj37yQjWBVXpQkOB/DDXtfItgn4/wCNNMRacQ3iZs4QcjKc%20fHcojmABc15UN3BCrSai8xKKrE5jv9In4rkMrGzw1hBa0Fo3AxuG5r2EKLioVlbRlbGjSAOw+Pxz%20AQGk7ldfcCqa3tXV7biV35dRc13Wq8SvuXF7vO8k7tASFB1Qu79K9dLI85w32WMZjM7f5YJRziih%20CEW5QH49r008xDMLnAgAkG+06Fuo7dqLJQOrNBGWytbIAWsnBc0r5WuQl5U33N6aantbNp56ZZY7%20zjUTx0x956+4ljH/AEtw2NVrXcTGB1N4B2A/dXje41t8Tv4+hxx0ce4uaSrb2IF9euteYjraCY+V%20zy5rUKFNTp/G9JDcizEC5yooG0u6hqDW4oCAnNJs7oUcN19LfxNPMG+o0YQoDiq6uJtbx06Up6jn%20uR3YcbmgkAD/AGbIdPuvRI9Su5PgYMyA487RJG7o6wWwUffTraBQZXM9j8Fih8xiDfRaXEOKAECy%20leta1u3BNq9TnksKyyOiA2ucXNZ4Klu9dyOd5aDZxb+RYnDQg7gEFu1PcEDEseQ3dvj9Qagg7ST9%20ho10BjBkxgUfjvcR1K9KH5C+A5Fm40YVsG1F+WwP+H76bDcx1vJTEKyHsqgDT4WpR4A5YP1OU5qO%20jRqEEAJ2/sqs50GOh7d7vVi2vbZxb8ypr4UoyCRbWx/Nfali7y/HSn4DHo43SABsu0jQDQ7b9KQP%20LodY+njXD24HEFznSuDkuRoRp16Xrz+f9x00eRqWNVrHBCtwuqg6ID9xrDQphtgcQpVqkBrkHXQ/%20AfCiewJ/YOnECO0BCIADb/dulVqSIGE4Lt2odF8O4+2gYA1zChaAqDxIcOo+yloG4UHSkhyFyuCp%20qSLIRSFkPt3ORtkARxutj8fGmHmIlyYcdA4kko1sbdStrdaaQnkVWVktmka6SRpRSgB2N/8AzGta%20pLUlqSz4WA8j7VzA4bXTyuZC0BTtam1500q1EEPUqZvdbMGMYXJ40uxjBFK9jQS5jbbgVBv3/Y9C%20u10Oa1SlxPeXExSGbiJZDju8oZKwlzDqQgN+9dFa2svA578la64x9DQ4fvLisdjMluW+ElpLsfaX%20Fev4IlGy3YzfNRPWCQ/32HucMeV4c1HCMsa4XBe2O5ankCm9qa4rMzt7ylV16/QXD7uxoQ5s2PM1%20pcfWY1CwOTeSx/UItqa9tZ5amf8A7hScpePyHsn3rx7IpBj4MkDXP/mb37igtuawIdpLUXrV19um%20ps8sY8CH7+zX6Ky8fD7PDSCjxuX5CObZx0wgOeWsBeD8rfmMYB8VqOV0qslnjHy0Org4+Zv9Ty7Y%20+783o5MMBo3K9AA7c7e7d4k/GyV5XJybnJ7FONVUFdk4EQR+wAkiyKEA+xKzdmjSEV8HGMdzGAXk%20O2ZMVyLq2QFPDvVUvmFlCZ6lruOIFAAoA8TfXjOP/Vv3JG4ybo5YQwgkAf8ACxfeb2qGszVPIxD/%20AHRysGL+nExMTWnax/yhbKBpU7EW7tFREZG+cuSRxBavY9k8TVyRp5lzgcjPjls0EmxzCN6XFrEo%20nWotWRrLwNxhZzcjFZPuVkjUJW4IsSne9YtZmiYvJxocqA+i4AKrTqAdKSyyBIzb4gHP8iFpCl1x%20bW3gi1omD7BMDtyAnyWDV79XfwoQhx7HFrwWk7bHUoVpp5iaEMG4uBID7qbqht99AaDOREEbIQGl%20rQpHmUtNrHUprT8hMLhceV/N4mbHGQ2HaJ3PcrQt9wUqVotmmOmptuSfA73wMhytfPhi5Ja5CEdd%20egHj8K5bv9K7G9P3FlykP6stkjeoJD9jULUatybFUC/4VzPTI6EuhS5mVK7FmYQTIxN0jQgCp3VU%20FqpKXKfUXTIxvJzuewte1j9j/I4BSPj06V18L8Th5AcW1r8gvc1XfkeSnmNj9hX7Knnf6Q43mW73%20Ms1gKOYkm7QlfCuCH1OuRlk7SHR7vM8rpcEDt0puoSG5hDULibo5EK9LU1YGhPqsY07z/LaikdEH%20enEhI3IZN+4Ehgb5igJQntTVYJbBPmRQ475nFI2mx+0Dr40Vo24RLskVcGR6+VJnbCyMN9OPd3JJ%203DQaG611um1bdTDdMsTkyrj7mlEs0+F7qbnSilXOY7WTRnciWSdyoDFGDdDqa7KVg57ORA0apsSj%20igPVbVb0EIkcSXbincp3pSMQpPQWOhT40QJiWbQhGvT7E0FUNyPQY80xOwKWC5W4B+/vSYQ2Lljh%20aWbXl0i7SCOwPXrTbl6AxUmOYYk3NEjiFjbdB4pR08Qa+YI3+mNrUN9B07/vpikXGdkxke0vaLtT%20raydKWoJxmbjiOHn5TjIj+r9bj2OLo22MjCt4w7VAb1jseqNK8kZMm802JzcfHLP5cLA1LByW3bQ%20U6ntXZ7BvNsPfw4aIDsGfeXOQr+YlSST++yJXc/cZ6HDsyIuXCGWa0AJ5SpcVAACkr2Wtq3kiIIL%20vKqg2JddO+7TX760EWmBMPSfE8gBoJ3XBB26hNNddeg1rN9+uMfaDPZvGgD6XYgdoOJi/L/8gdLV%204nNq/wCp206HGTJGSVKJYkAIQtvEV5qWkna12FRyEEIXOcquAsFcFoAV+ojITaRcKV62SiROrG5X%202J3HcQC7oFuHL2qfApLORBvZhK9OvXTRKbY4ENY9yBoO5fjfQ9QvitJ+IQJcSu5dqqXLcX69/E0Q%20MpfdwbF7dzTKTGwsDWAoilANPj3rTizsiLqDiLnyghAQSUUFdAtv7a9PQ5YYoZWSNXdlWx8psiUZ%20BLDGXIQA6LdZShN0UFfvpQgUijlWG+DUnc43JKABCfhTSDcNGQl3kLXEg+UtF0/FaJQbpFDJcSAS%20wdAUS5HU0g3eIZne5hLUcoU7QVHiQdKcDz1GjPkBp2xlqqp1IP8AhTidQzCigycqZrA5243Kmzeq%20k9KTcAqtlhhcFLNE2QZkcLTZoe5Hfu708yW0mdJ+n/L8BxHGfoeV5Rn6qeUkGNXNDSPIp0vXLz8T%20s5NqcseZ01uDjtAcPM1wHy2JXxQ2rjhamu4M4UW4o0uUdSNbdCKQxJjMbrMDmNu8knXwSk/IZJDA%20hKBxPzIBqiGmLMIwxkWaAoT4KpsO9ORSRZIJGSaj00F16k9qChiYSsZtjAD0IFxY/b2SntZLsVWR%20N6UhE7fUlCAyEapdGAm1Wqk2fbGOxWzRODN8qK8n0owoQKUcTa/aqYk5Nh7NmA4hrCjnesXM6IFA%20R2v996uhN1njGETPcntvFzcV++IOkZ5g5o7lU/xrbwMepyXA9sTcX7uysR5LMeaH14gVIJ/Nouhr%20SupFqypZsGcbA8AoPM4Akqu4EEXPw6VtuMfRpERkSZcDGjiha2Nr3uLGtDSEJVV7kLrTnUHx0fQt%2028fhMc6R2Oxvyh7iCXWBFzqUv99LfbSWJ8NdYRE57F44QxiOFojeCRIfL5VC6XNxep6ZmyopyKjj%20ow6dmZ6jZGgenC14QgXJDT+Fq5Oa+qOnjpBbR50bgW7kXuCika3rkZrIkZMKOQkAncOvX7NaAgPD%20c1/I4j5Qg9djQRa3qBL0JS0NvJnouvQOMFAAoA8S/X6R0X1Z9wvfC5zDNA31HNIb/wDSwlA420rJ%20w3qdFNNDm2W9pagIKHReqFPHWqgTRGiZ6ji8/wCZGPBGtJhHVk3FczftHlYCia/bTFBrPbWdiw40%20mNIf5jj/ACghJvY2HSovUdXBN4hz/wCdAwEPjcpcTtIBF9egqGsikx+TDkdH+ocj9tnOQa+P5Sne%20kkUmQn45sDr0A7Iqr8aSkGkxDVeCXNG+5sFsF/hTnoHUbfFcOa5HCyjtVCSBLETG4oqIQPzm+oHe%20hMGn8RnDnczK9Mq2N7doa0eXU6ql+lFtBVSmUO+6OQlGdxzyds0UQghA8oEYNy4lb3qaJNMrkycm%208jDG48D43gsLXFzyfKSQNQVKiyhFIrz7ZNuTtRVZ/K8ZjT5DQ5sjZAYyGtS5HiqaEarVKerItZGQ%20nfBLGcQtI3EgJpa6/wBtbUy/UcrUoiwtEec2Bu5j9pDnKOl7VrdzWSK5MvD+m1c7Y1q+e249rLb/%20ABvXmZnXIEx3xgB6PI3ElUHRAim+q0bmMKSCKSMkT7X7SUa3RzrBFTRf8aavmSxj5A1r3ghPMXIr%20q03dhBBxZHIAFCkHcmmq3pySyFlwtzccQmUtK7g7roehA6GujjttcmdsyC90RDoGxH9NDZshQFzj%20oUv1FbJt59WZaZFXk5YlHoh/lBBkIsHJ0FdFEtTNuRl+QwR7YRteSm3QjbatZzFJFlcLtaVACH8b%20n7aTeYZjZQa9UGlj3P8ACkJtCSWoCURAdvbxpj8A1QA3CXA11KdTTUQBIiEseOrXIx58QEaNaIAI%20fMXuKg3BOpoyEw3NJZ6hup1B+yqlxIAeLbm3aT5VCFR4fGk2A/jYkkwkPqCOKEFXFfMVs0fHpUvI%20cF37c5HJ44sWQjCnk/mQC7lb+drSOm6qkUHS+V4ZvK8WcrH9MtaA6MkqZFHmL7Kf2St+C7ViORKD%20LSAxMdG9uwsbtDHAWOwuAJbZV79PjXaqy2c2ZFnBAZGgeq/ywqkhu1SDoioBraqr3YN9ER34gQkE%20BzRoqk26HxNaOynIkJkZhJDh8oR3wXQrrfvS3SOJPaPHFp+l2M4/KeJY46D/AMkE2Fq8X3Gtjt4+%20hxYNIJVpJS5TQd/s0rzUdor0ztA2lTZNCgHhQ0JAbFK4g/Kh1NrG5VvS1Aw/Qc3UtF1B+5pJqWx5%20CmghHE7iDYBCe+vxShoNRQcCxocEAcnlv20F6SQDM5x43Na5xaXOIZb5uqD7L0JCnzM59RTH/wAu%20lm13nkFlCkD5vt+NdXt03Yz5LQjl0nE8g53liLiW7hoQQT38evwr0dj1OT1EF/Q+Sc3eYowLhXuA%20CAI4fYlJUcj9RDbuGzXztgEUb3yK1u1wVV7qaFVsXqLqJl9vck2WaNuI6QwvEcmwi70uEsRRDgfq%20IIe1eUQgYDwb7r31CIv30vgPfUQ725yLGlzsR7WpdCLDxBNPbAK60LNv0+90ubvGI5gIDt+4adyq%20Vg+ZGq42IyfYXuKGIvmj2hbkuaSmmi0f5FR+k+pSYbsjDGSwjbJIkb1NwAVde9arNSSv0t9wt7nk%20OdfeSQdSgFDsQCMF8sTSvmkYhHi4fdTs9Qjoep4UgggjRrdsTGEuCfkHSvLbR0oJ74zI6Rki2HVA%20g7J91SNJYzEOfJu3FpaUVpU2Qf2VLTKSI8kz4gVJtbb4NP8ACkVAoSucl9Llp6Ki+F6AYJCfkadx%20FgD0B63rTjpu0ItaNCLlzMxYJJZTdUCBFI6NB/NXRsVUZTPkVQbI+QZE6B8psxSNoTQKBfufuqW5%20eY0hjKDXyI1tmdDoDqieFTBaWRd+1ZC7DyWF6iBzHNd1Bc5fj3q+Mm5vv5skaiQN33dGlg0hNda6%20DnMl7p4n1sePksbH/n4bv50B6xk+YA9utCY7Iq4XRyf6TNr0VgKNKG+qqu37q2bjyMoyyZFD5yyN%20pIGyQbCxA5FU+P4U2MucabMjhkigEc7muvjyeQhT01t1H+NEh4EOTk4xA+KWOWBzl9QEh2vZbjct%20Re23PUdatsrmTGPdv+UIrCAAUOnY27+FefqdqFfqw4ISSGoCT8RcdTSCBXqqF27TuVAVG4dweoAT%208aXkCSJXGSD+q4bXEgieNrNxCjzNHmF1Kr++mlmhPQ9I13HICgAUAeZ/rrguzeR9x4+wPQxyRogc%20EhYTf7K5bW/WdNEmkebpXb4wQd24eU6Kp6/tatyGFjh7IyBZEBQWJ+7xpMYuJ/pva6wAIJKLZP40%20QDeWRo+CzHY3IRyOaCx7Qx1gqkIPvSpsCeZfyPZHy8c0flE7TG5pCKEQWPao8xvVE+75Z4GSFjE3%20OKaEff2oYJSyOzj8p2O6aEHKZjqXyMCbWiwKG5HWs3YtJIiubE/c6EHey4tb4CqDMBhaQ1zNSCvx%20T/GgfUZZMx4kjbcQEgkBCttOtPMEvtE5vGxQzQuyyYnvcHCFEt03Doq0t4l3GufwGZLW5D2l7Wko%20huLq0qUstFLQO9cg2+5OT5Xhzhyy/pnRu9J4b/mF2u66+FZX4lW0rQN7agb3+lAxrlc8kCR4G0kq%20i9VtWOryCciXDG15aQGtLvKHkgAJ/CsLWZcSNZkLZpscsfaJqbUSxNxqet604rwmK1CI+F4c0hxG%20y7+pRtz+9NK0d1A4ZMRrRZyNYETVErCzTZUZCiAQB1BUHx+yoRQ26JCXMKOJJK+a5S4HTSrklob3%20RtYQTvhAIJKG7bJ+FPqQyt5Hk44mkC4CAlqC66W/YV1cXG3mzK9tvmZ/NyJZ3NLVbC0KBcWTp9td%20vHx9TC1pG2gtYSGjcvXpW3kSIIRWMXcbDsT0FTK0DQaKkhQmiWo8Bx3ENG4gIrn7RtF7D/CgIfQA%20KuLRZ4O5zSO3Q0SDJsOA6KGLJnBbHMuyNPMWtsuul6EW6xEisiWORt3Od6YAA6L/AJUQBL020Q33%20GhC7Yro/KXI3p171SELciWO1rbmMKijsOtLLoNDbdrgd5VrLtbpcldEqUSTYGuQu62223N/DrTb6%20DWRa4eEAjyPOAC1bkXt0poGzWe0+dGFyEbZyTjORjT8wYT821qXrRLIlzJfc/wAQ2dj8nE9PfGrX%20NahF/MQ0nUoFc4jW1dNLrRmFl1MVkGzWIqXMuiooBW3+UN0W2tdVXJDHRt2vaXBwTYWhDbduLdOx%20/bSiWJdM4x+Q1I0yRSI4koS/VyID5tE8KT8QR7K4dwb9LMJx0HERLqf/ACB2ryPca2+J2cfQ5Cyd%20qlPMWkDcCl/ALXmp4/A7ZGZzIgO8+p0Gnbp8aSH5jbMiQqC3aQQp1OigKfspgqhAyOLd3lHyhijT%204W839lHgDUhkbEDn3OpamujQb9RSgchbwC5e2vXb/dQJgkUKwFSeydB+7xpDZj/f2U9pwGggxOJf%20J3/yk/aD2rv9lWXPU5PcvKDPY78dpMbpPRCrDICgQaMNzoep1r0lfqcLJsc2ZCNxe2UAgukIBI0V%20pXW2g6Um+6DbI6zKx3yskjiZ6kRKMADSC0X2/Z0pWtl2HWvTUj4UUcokkjyHtc95kRrkI3W231vV%20ykhEh0b2NDDlSPBGr9CAQi2vU28cgqMztSJ2yTa4ohedUI1UajoanzKRoGc/hCCNpfJ6rYm2Fz5U%2006fCvP8A8W+p6K9zVQV/J8zjnFLn77tsXlEQa/A1f+G9WT/mJaHMs6Zr5pJWRujj3uIKWJI8a39N%20rQz3p59SNjR7y2NvlYXoJSoDVKKU6XpZkLsdN4f6URNzMbKzs9j8ZrmyhkLbO6t8x6WvauO3uDoX%20EdTM0T2hzW7mojEPlAS2nwrnNSLLMYJw3awwAbtxNwVK/YKnOcg8x1mW4tID90QAAICIPEkXC0gW%20QbHjylwDiCAbAgHTS1VMAG3e7ysB3FbG40U2/sqqUbHa0EPOyWccw+owvmcFZE273fZet0oyMG5I%20RbmyyMzMw75E/lwj5I2gKDcm/wDtUpbHAWW2Hax203KCP/M4ahe/VfjQ6xkUnOmMYkihr2+R52xG%20xkaEI3X2k96W0Ssaj2lgNZxWTOfI+WVgjJHRlxtCitKqETZmzxg4tWQBsioUvfp0vWqkyQnIxx6W%20wgOttkB/MCPNpQ6hORz/ACsV/Eco7D2pjOG+E9ml2hP5tq1pXxx4EsjShZROxwaC8MkehcBtKWvV%20yKMiyyI3GNjgHEyeaMtJDkcQo3BQb9dPupJ5wEELlcnLGF6Mu1xc7crmgOaxh8u51gtc/O0lkbcW%20pUtD0JcFHcoQD9v4VxnUyRFGHDc1ytRTZU8O/wAL+FIIFmN92uc4EjzOUOF1JN6JxjHUPsJHHPaz%20k8NpVzvWi2qq3eD1+FVXUmyyfeD0vXccYKABQB5u+soyv6z7lGOT6pDCFAIA9Fi61x3cXOqi/SeZ%205JIkKfMD5m9Vvf766URZoRBMLuedXLu1/YUmuwvMSzKha5XtdJqdnx6/DxoaHuwy5wMkeljytNmk%20Hbdell/jRaRNGlzcwyuglZG5jQ9tnBF+I8aznuNlpDPKzNcwtaDLGSA1ToqITSa7giz9h57o+XfA%20/wAu3cwNKOBCqd1v41F0Orgke4fb8kPLtdhRD/iVd6DNeigDVPGomNTRT1KaOFgnlg2vjnsGwkDd%206h0G03utWJOMi1k4yDgQzIeyOfmp/NHA5DHE2yPePzOK0TOsjRm8gHLfvlk9SR8m5znfMXdSv9tD%20gJgj8fzHHOzJuLzGO9Z7nRMUAhUsieIpunUN/RlK+GbjmZTnlpyhM31IwejDq7vroK2jdkzGIzJ7%20Y35UMc0aF7mhxtYpe3gK4brY46GitIU0E087dk74WRgkuZ/mH5SD0qVeqWaHtZKbK7yPaBdyPXws%20ul71ztdzXUQDHMkodYWKhARroarQbeY46Vu8MDuvVES4So6AG847yjAWFxDrWCJ0Opv+FJSDGZ+Q%202yuxixzXxAHfsJUOt0BJ2p1rSnE2p7kPlRWZ+c6J3lZM2Ji/zXWBeQgI8K6+LhMrciRQyOklYJHk%20q1yNZ4C6k+Nd1awc4gB6ou3uLFO6JVtgIEjAvQnuDex71LYDe5BawuCe6mxJFEuBi8TDyM7KZj40%20ZfLIrWgKo7qnSk7Qs9ASlwhfnwM1roXt9aFybrFqjUAdaMrKBvJl3i5PF8nF6PJYbYZMd3qzZUYD%20dwFkcB/Coho0Vp1IfKZP6ud8kb2o5GxEKGRsARrAtWlkQyt2mF/z7WhGktOhNgbVcIhDrkia5u7c%20WlATc0NpLIUDcjxbcQSChQIfj21ocAh7GxnOKub1Jeo0A1+2mCks+PibLKy4awHyXIHUFLpQ3GQ1%20p4FsFVu241ClCulkqqkslY2K8EOLAxqWJVoQnqOx79asku+P5KRmNkQse0YsTR+qld5laD5Y0+W2%20verq8yWsjO5+SMieWRjDsfqLANCBo/CupXVYT/cZ7W8+g8yRyMc69z6TlNx3Xulh+6rbREMSisId%20oRZyqLLrt7UbkKGey+Lds+luG4FE4iO9j/5A79/GvH5ep28fQ4sH3JuQnmTXVa89Ha38xO4qbKhu%207W4v9lGMYzDGMfUUdwYNzfKAfCwPV2tAPMR/LYRfalgioi9rUAgOkZ87AXAWT4dbILrpSgJCLmNJ%20Yn+09yadbigc6hOAcNCdwO7rZPBFFEgkc895ZX67mJI437TG0NhDvkJDUNxcGvT9sttTg5nLKHEz%20GPeYJ1hnZ8zXXISzihCInauhrPIyX0Jb35cDQfU2xmwAIcL6AghyBDUy4Dahv9WBkj1pnNDhYtal%20+m4joEotyNrQpUQ3gckWXjLXI4sDnqLBxT+1NKp8nVk+mW7PcCoHwRgH5gHLf4+HUVC5Bek+g4OW%20bKoYIm7UsGEq3UOSq9Vh6Yt8skjwfULW2YgaGW0QE6fvq1dtC2JZBNgxDA6Z4btbrJIS5Co7/Cnm%203mwyWiM/l4T8uSSVgIii3JIgAABTd8fAVf6VkTLZCxMQuyWscUJ8jS24Un937qranqG47jgfysbH%20D2ANbE0IB0Travn7r9Tg9WuVSxhkaQEcvVTbXonelIRHQOVkTwHOAAs4EgIBayhVFKJHKEDcGbQ4%20taAdeihNaAzgDWE/K0hos9dD0X4+NXWjYrWFz58OG4NZZzhtY9bu0sh6muhZaGFrNkeWfDxWDKyX%20NZIdoD3BXEkIgVTbtRITAxkchjei50ZXQMFi2+hRaTgalkSWfdG3e0Mkd87yoQDwHxN6cR5lZORj%20Iy/TDQ9pkgedrn/MllOqWo0xj8yWdM43CixeOwIy3yuuXIoVDa/VKtLIh2zzJ7S1tiRYKHElQg76%202qnBMgimMm47QQlz1ROqaLTBGb918bNPhmWIbpcR3qxu6kWG036iirzGZRskJbH/AC0kc8B0YLjZ%20LtCn/ZNbIhl3C1mx/oPeCSWuxpVAafmS2lrWo8xMpeeb6ma6JrmtMJBkiJ1c7qSNUrh9w88jr4VC%20IccJDvO9rowGtQ9NCETVPGuc2Ho3NDyXBF6CwQqbDXv40Asg/WJYu1bbkACAoq0QIdwBCeVwy0J/%20PYgGlntPX9tKaB5L5npqu84gUACgDzx9SS8++eYaQkZkjC6qkEdzY2vXDyP9TOzjyqi2+kvsf2hy%20sPMy8nwuJlSMmhEbpY1LQYzYL8OlbcMNGfM2mdBb9L/p0oP/AC3gKPl/khV1rfajBNlV7n9n/Sf2%205wWTzXJe2sT+n4QDsh8cG4sYUVxaAqCy0Qglllg+wPppk4cGXhcFgS4mQxs0ErI2lrmvG5rgR8aI%20QSzln/crwXB8XwHEvwMKHDc+WVrjC3aSA0ILVF0i6uZOOOkkd+jlBHqL5XGy2T43rPUtz0J/tpjx%207vaz/Uc8tLmtCC5JBTtRYayZ0x0bTyk+SAHRRgMEjkQFSuxUsgrDyKWQl3H436h2dFHHHyDmbGZE%20gCNJVD8fhTHPfUwnPcZy3H5frZcn6mOcl3rD/wDCngmlDaGvAqpBA4GQNXfcyqn23Oq1UQPzM7zm%20KTLHnQs3yxSNc5B5iGm3lb1qq2UeZmyVy+JNyJgyYowxswMuU5UJkLQCC00UvHki7U3ZoXhYGach%20uM+B0MLmrjvCbxtBOmiGqvsspMf1UYto4oSRYM088WRK5S1zHBhLb/OUH9xrmtwNaEvn+ZdN9vYr%20m7XSueCUPnClR5D01+xOt0FY+MYxiMyH7m2Pr+Xcdb7cxGjcPNGFfu22QjyklQBcJYm/2US9Izx8%20fHp0M/8AItDz7fn5/KIGxg8RG31ZWNBBTbvDSRfdqe/hVxPTHkP1LTGMYRByOb4bBaknpyAh3maX%20SFEJaHI19htB/ZapcLjLGMdiZs88fcUb/cznzOyMXDYIQSssxDY0crbADcQnh++tvQT8zRJvMpsv%20kc3LeGy5DZIFTZGEYCtlJvW1eNVY0iT/AMu5+RF6uO5kzw0PEAuA34JrS9ZdTbZOclJkCWF7oZAW%20PbYtKG4shrSepk00MvQuAKEdEKfv7USDEOUKNBoQh+5KrqDZo+A5HE4j2/n5m7/7llfyMZurmsFn%20uPas3VtrsaVaS8RGNwMnGcc3leVYf1OQ1eNwvzvJH+tI1fKwdO9VkyEnqVs+UGQPxQd75SH5LyD8%203YdwDQlADTZSwt3N3MYvlPVR1WqaFIkPx3B49MNfc7lQa6GhITeQ2HEPJRQCSqKPCmIkx4c8sgEM%20KOBQNPdF1PYUwgtY+HnDGjIPp7ixFt8wXrSbeoGi4zgcOLHY+Z+5wa13pAeYPc4AFdU60k+5UE9k%20kMXqsixHAR73MMjBZwG1qE6qpJp71AbG+hJfxsj45W+WeKZsTGMF/wCXGFd/71XuzyJSgocrjuQx%20cF2CxrmxvldM8jV1vLuJugRa14eatXLJ5KWY3Hw/IycY/IaGkPUBpKuaANCD99Y8/IrcifQ34ZrR%20or8TNWUBUAVWdA6wJunV1dibbOXKCeZmlrinmJJ8Lf3VtjH4GbR7N4q30pwyLJxER07QDsleXz/3%20T4nTx9DiTjv2khyFC2/Q3P7q86TtRoPbnsjm+cwnZ2FJE2KJ5i/nkhwIRx0+ytK8bayId6rItR9K%20PdDQVfCUVC55+Hb91X6DJ9RBn6Ue6SLOxnJa8hBW/VNe9J8DGuagk/Sn3Y64din/APeH4oqHolJ8%20DD1l1ZQe4PbPJ+3ciDH5BrHvna6SN8Li4DbruOuptaovR11LrdPQz3IZYw+OysyQ+aGN0liLICml%20+tFVLgd3ByrJlyMiNszryODXEFR/MI3HTvavWrCyPOfcEZ/VM2FrZHs+VjxqdPLRtnQNGKEk0Mch%20ZEA8HyItnj/KbLSzkcqBO5r5IyWjc0226FxQlPvobyx8CSMyN4mewWaHEk2IK26dlsarxCSfiQYx%20jYHhzZ9zgZXAGPcqgubZfGlMD1JZyOQhaIo8GLJLiS2SOTaD2KG4p70TDF48XK5Exkz3w48ev6dp%20VydVp7pBVUDmVmcXvDQHZZaobGDtha5pRXJ1qpeRG0hZeXNkRuc6MMjaNsUTDtj7FxCdqtJTj5A3%20kFw+HLkcljRxsDy6QA9dwFyh70ctoqFFNjrDW7GbHO3hvl1QeNuwFfPtyz2IFMkcQ0IN5Q7lv8R/%20fQxQPtneC4I5bFxVVQFUutEi2krGjknVzjtYEElr3PQW6VpSjZDeRIe1jtmzyt2m6JoPDWt0iJKq%20L0J5pZFL0f5GuFg4AqEJ6fGhqdf6fUhB8jhDJxXhC9480RJTa4j7bUmgaRn+PzHywMxpWhr2lGHb%20tG38oT+2kh1t3J/6uJs3ph3QeYKPh2Ngn4irSXQpsdxoZ58rFxoYw7HkcI5j+ZHIqDTRF0vTglvu%20dLzAWMw2BwEbijrIAgTbfrVmfTzHMxR6aNJ36AauF0ROtOyBagxmvDQd27cCT/m7HShIUi542SDz%203BBCnpbt26U2gk5/zMQ4/PEOQXGCR++BoXda7mp1FquvYTXVFn+oileJcWRkzXNAjcCGlqGzXfm1%200QXqoEZ7P4xxznznyOcPMSNCD5uthbSuL3DasdXC1A3tKBrWABNoQjT7df20rniDQT5C5xcAPEW8%20FQL00ogqRMiAt3NUL1OpA1KLqO1IFA/xbh/VMMtahdPGj9VV4K6ALdD+yldQejPT1eicIKABQB51%20+o8zT9QOXjeDtD49CpI9FhJ/hXFy/uZ2ceiNx9FE/p3LEO3D141QJ+U9E8O9a+3eTMufUr/rX7gy%20MTk+I4uL3dNwTMjd6/FcZinL5TLJuwxhHBjWka10MwKf6Je4/cHvb2X704P3Lky8g3CmnwIJ8xjY%20sgwujIMczQm11r9tOlEgXf8A2yctl8h9JMFmS71Hcdkz4MLyv+lCRsCg9A6gCk/7qBK7gOEZHGXl%2008umgO0XT91RdpQ2aU6nDsdzvSxg4OAaAj1cqrc9+lc7saJaEzhsjIZ7pjkia9rmAFrg0JcFpKp2%20K0OIGtcjoPHZhkyJMIt2HGO8MJUyB5XcQbG+t6zWZdqlsWh4JQIjrGwITX+NOZxjIlrvAT8Zk+1j%204g4AhGlPv/Gp8R5mV9wcbwEe+WLJjhzGtWXGjO8OHXcBpbSk8g0Mb+kOBEXYOO4syXbv1mQHPLSC%20v8ttgnxpOztqFazjGPiIw5OQ/QZEPrbstjtzd4Aa5o7p0TtU7VMwdCyWMfYQm+4pMd/6fPhLYyB6%20cjHedoXo7pqnX91OtJWRm2nlj6j0ruYyonMxuRbm4sQa/wBCSNMiLwQpbxWtKWSzjMwtwyLd7gwM%20uVvHmSbjeSYANsTS5u8kJ3+b9hTtRrPVY6GLrLIHuiH3LiY8s0WZMYIixsrGDylQfODqiL8Kqjqy%20nwtJmRZPM9hdNkOeqHaDuK+KrXTEEqqJA5HZA4QyOYoIlfZHf7zaIKnsQw8ySF0gL16F3fqtDJZK%20djy/pWZQb/KeSwaAggrc0pzKSGcefIxJvUxpnREggof8yjShpPoOYI7iQCXnct3k69OpprLQgbVw%20ALWo3RTe/gnwp59Aeg7FgZkwJEbgywdKQgA7qulNIbRKxhHhyiRpbJPGVAeCWK0dF1ogWmg9lc7m%20ZE02XLIZs3KQbls1gGjRp8KW1dAkgxq6FTdwdqCpXxX8aaEEwufOGPLWAlAXpb4ntRDQeZKiwIRj%20SzZD9kjHJHFqT4nwqo+QdB3jcZ02ScRjw1z3eV5ALdgK2NK12h1rLLD01ZNJBv8ARhDiTa7iURpG%20q1h6hsuHHc0fB4IyOai/qjvWxY9rpGss0Nc1EeCPyhKztzNqEa04c8joXA8Dh4uO+VsDfWyCHuaU%20cGtB8m1VRO16lXkrYlkWMuHjSBzZGhCiq1AO9j8q014OC4lTBDf7e4t0f8pjoZCUjMbiCE8PG9Ot%20mkoZFuNPUrszgcxrUje2YdWyBCNbbuptVPm7kegiknZ+na6OfHdD+UPjG4En9u321aaZDpadJKP/%20AJbwJz6sE0bnNJJaPKWkdwtbK7WRi655kef25yMcbxCTJ5SAAq6WC3Wt6e8U5mb4Ox7F49ro/pNi%20teEczh41GmkArm5XKbKos0jhkb5N4LnjaVaXOIDVuqJdfEVwHY/kdm+kbA32zK0HcmSQv5rNACkC%20ur2/7Tn5dTBch9ane2vrT7k4r3DnTv8AbuLhQnjeMxYPWkfkP9NxcwN867XOcVKda3MoLv3t9Sm8%20x9K5PfXsLkinCZMeTlRFoa58UbgJ8aZjg7YrXg/dQB0jgeZxec4Pj+axh/w3JY8eVE03IbI1rtpP%20U+NAHNvrMxeT4wfkEMm8A+YhWoLfDtXJ7l5o6ODqcf8AfmUI/bWWxg2yyubCHIhR9/jc6Cn7Ws3Q%20+bKpgYQX4sZaDtLA1UQnaLoE8etejauZwp9RswvDt7XAyN1dqQvTprSU9B5D3rvkDY5NwaSVY5EC%20eNrIKqomuxIaYi+MAgbj8323v46mntyJkisMTsuTU/zATdLW3AJ+CU1oDZLifC/Ge15TzBxJ+Ubt%20PtN1oa07DI0mfgQuEcQ9eYEuIGq9bi1v4VELroUquMgb8iW0u6GMqkLfmIFnKen2U1C6EtEyDF9I%20Bjw2MGzUTXrY6+K/ZVLkT64xoTtYnJiaWhNHeZxJRLkEKPhTT7A0aD6WY0T/AHhFPkODIoGkxNdY%20b9paDfrUc3IkvP8AEqlTp82DDOZJschWvRwabq25T4V5duNRKO9XIDIi57Vj2l1yU6ffWSq3kaO0%20Yx8CVBxMriGyeRpuh/MUBI17Gta8UkWvBZRxGNpapUgghwBBS2ngK6FWDF2Tc9hmba2wcPSUAXsS%20i9KJDzKzJge2b9VAQotJGCoe0fbY+NQ6jmBmflMXZ6byGOe5Gi4fpcJTT69RwZznQ+HJflCYCKQ/%20zjG1XaWU/cfspQS8tRWO9k8Ic0FXAA7rOb9huabKqzQezsXdzeJCX7xEr9ztQg6+C1UZg2zf5+S5%204gEh2o5rCgQfMbWNNtma+4lyljmgFEbo7p2Oh696uJJYW15YF8hQJYfuFCQMQXZG/dI0X8xa0jzA%206pSDzKX3Dx0mTjiZkW6fHeHMFtxv2K3vTTCCobHBNKfWx/00oaN7kRRZDvtqU0rdeBm5KfcC1+8b%20Cx5Lrkk3CKD/AL3f+/m90spOngcMZkYwNIBRhCOaFJIAHfwKiuLM6BBiC6IAdp0VUACaamkJNhPD%20ttjdASVuiICP2WmOZHOKY88phPu4OnivYX3ix/fTqs4Jeh6gruOQFAAoA81fVKJrff8AzMu5DvjK%20EWCQx9dSa4eR/rOzi/abL6Mc5xODxPLjkM6LDaJ2bXZL2xqGsuVdtW9a+3tCM+dNtDPvTgfY3P8A%20vDC94cP7+xvb/PYsH6WSeCbHma+AE+UNkcACFNdJhD6lVhQ+xvpd7P8AeHI8V7vZzmXykcmRHA+S%20CSd+W5pFjGS5xe4qf7qNyDa10L/6KZvs32j9NeI4jL5/jo897DlZ0ZyoSWTTeZzSWuTy/LSlBDKj%2069e6/b+RxXDS4HJwZbY5pd4gkZK0AhqF6FB4eNcvuqboSZpxJnLOKzW5GYWx4Tn5hcR6b/NE3u4t%20RNtrLpXIuFLM3gs8nNEzJGwZEIyg5sE8kUegJ2kRuA1q4aGl80N5ft+aKOXMxc6T1onemwyFSWWa%20Sb+ZEXxNYurkNqGOUxfdmFLG5s8r9gKbPMw7XKrnWIKGlNl4ijsV+Vy3ubIbdkjBKAImt3Nd5Qps%20AAU0HXRKjfnjH9CIfXuUMj8XFkL5WvxHOkMjoXFwIl2qNwUr16+Nq0pZ267v6kuz+wv+O90YuJFL%20jNiikjyE3gqjXXChpDd2t+tOrcBXkekFFnmGDNj5Jkx9MkQywEaMJTc1NUIWtq3k1rykTluOy58o%20/p4onzQI1sLyVdu7qNvwqqWqaX8GN5b5sBsXIZOLJDkM+abGJdsXRr0It8aaU9Sd0ZxkXXH5fG8o%2012TPigvcAYcoMMcjToCFG43KBKxunTrqXW1Xj6lnxvLybpMPOaJ2R+UTOaA2dpsATpuC9L96hVa/%20AdlCM5y3sbEy87/7a6PG9RXtiLiYgt0U90Su3iu9Gc3JUoOW9m89xzfVmxnSREIJY0e0EHoWqE+F%20bTGRlCehSh8DGkuJ3KRsPzeC+BoCUP5WUxmM3EjBLAwPJP8Amdd3QWvSVcw8CG0zOB2NLk0LQShO%20twOtWIkRcVkBH5Ubo43eVhcdrlQHTWnHzDsOtZx+FIDKTkP6xizQp69/3UJgNze4MkOk9MNa11gw%20DyAIlmGxJ60nDyROpXyZUshcZCu1N6620SnE9Q+0XiMycl22KMueAAU0APf91UPa+hYzRxwYjTIY%2025DQQ5jT5nLfc/bbSlIojLqQXyF7mhzrWC9gfGmTkT8SCc4joSHGB53Bwam5O/VABQ0pLX0J/D8R%20NPkSr6seKW3cLNc11gN3a9YcvJBvx07mkx+GH6URoY2RAoRoNU+OvSuZuXmzrXGupaNhZBxbntj/%20AJ8t3PKK7oPinXr+AqUjSqhFzj8tnwFGSHa1gG3UBDcjcVGqaVokkaPiWhZY/ulCG5DRro3omqjp%20VJZEPi7FnDyeBkkHHeHKUurXBQuh816Tyxj7ydrWo4cgNJBBYVaxXBCSeg6fcaHp5iVZgaLIXt/m%20RfN5b6k2H+94rS2xmmDU5ELM4XhMth9SFrSpJczykG4JJBuiXpy1+ZnbjTyZTZXt7PwUfh552AI2%20KVu4HcNDdbVouRPVGVuHsemcYSf9MYQ8JJ/SmBwF7+iPDrWtodMuxytNWz7nDoMRz4iJCWuIu1tg%20NV8O19a4G88jsyOwfSoMb7clDCSG5BCnodoRBXZ7b9py82pyrI9x4vs//uQ9z8/zXF5snEPwI4Ry%20UGNJOyBxbG4OO1rrO9Mst+6tzNsqfbvG5sH0j+q3ujKwX8dxfPOll4zEma5jiwlBJsd5gHueKNUE%20navozgZGF9KfbEE6+o7Bjl8yqBI0OaP/AAu0oEZz60yNbyHGlzXJ6L27wlgT3rj9zqjo9voziPv+%20SZvAsb0dO1jiq7wDub1/2lrT2WVw9znUxnGv3t9Elin/AEzYhxIT7Fr07pvNnCkSSzc/eo2mxB0R%20CF1S9ZyBCz43tjY5u0neEACrtd2H40088Y8hiZM39O8SyksaLtd1IBsB++m8kJFRk85DC6SRjS9z%20ioAvpov76W8aUkvGZl8k1r12sUNEUY+Y6lTQp6sblaFzhcb6DAxsTQQNCFJUakorlXpT2p4xBDck%206N0jL+k2MhTuXdtA6kr5kb/DwpqqBWYcmTGhbaTaNpBQhdNFtr+2tDoh72Qs55ERaCBLI4skAKEN%20CIAOyirpWCHY0/szCZFizctK4iOCRGEiyjqe/jXH7y8NI6OBdTf+3s9ssJlkayOaaTfExhI3gfmP%20XxrkpHc3soNDJ6TCpi8tg+QNQ7h3v4Vpj4ix8AjIPK5zBJZXjcSE+ZV76Vck7fmNZEBhKxyF4/I1%20fJtHzHW2tA/oQJ5I43o4gb3bSx4BciIoCoKkc5lZl5jop/Om8XMYAcUap+FJudBqr6lBy80cj454%20F/UNdvDSLuZcDT7rUdUOI8hiDIGRiM9R+4EFrgW37roulSDI0WQzjxI+NZ3TBxDyUA0GndDaqXhj%20wx+JCUZGu+mWQ3Oz8mRA4wROa4mx8xQBvgapNsdmdAzmubtj3K213BQCNAehFBK+pJTdYFWggjcN%20QE1uNapED+4Bdb/lN9dD+NUDkamaXRHaBcIhW6UARYsj1gWvYQQQ141snzeFimtJMbRQZPFxR5jp%20JWyTNkIdEzcUuQUbfSta2IsuqxjHYzkzU5DNY9jtm9Q14+Ujsmt6z5/2mvD+4ORhcfIQ1w+QCyW7%20i9ecnodcIaeyRwB0QrGLEr4E09wCQ35W9ySnayLe/jenIoH+MC8riEq4tniB3X/OCl7/AIVSJeh6%20artOQFAAoA81fVGVo+oXLhylwliQn5QPQYbDwvXHyfuOrj/ajJZUePk478aRzQ17fSJF0aR0cfN8%20azSNNxx/MwfQyJYWtHq4zyQNut7XFdS0OdrPILHnhlV3pNbuHmKAFU6npQ1BSeWMeQuOOPenpsDh%20qbfNra1CJfc0nF8ecqCLBc0Y0b0L5vL5mk6AafjUWcZlrOC+5PlZMSKHiuNPpYjnNbNI1HSODR1c%20Phes6r5ltRkiN7byJm+48hkIG1yERn5UF+v+7qlO+mYk8zpEb4ZsB7C07pWOD0AF3aWXwrBopj+J%20NI/Di3uIPpj1NQA4C/e1Pb0EQuVw8hxjdjOZuILZjJq0j5SL2TdU2qOtEZfkOUy8V218HrgOLA70%20g4rdS2Rw6nv/AG0kvDM0VFGRJxMHjssOyJpYGva3a9jmlTdNLft9tJg0oxGhT837Wx5SYYnCN0jN%20xdCTsUlQqk068iTkp8c6ECHh+T5OBmPE9c/GG0NcPM9nX/esF1qnaZkm1H8SJm5XL4TNuTjOlYAW%20va0uUDQAsKKnSpqqt6wZOjWeMMPA5mLOKHIMUEQAldLGQGMABFgO4HjRfifXMlJscVuSAROJAxxL%20SXK3cVU6hQl/j9lZw69BNtEvGy3Ne2LI88Ejm+mHDb50BQAar0rWvJI986ldy/u3n+B5ObFwZG5n%20HeV78fIbuI62dbSu7i5JRnaq+BOg536ee543DkMb+mci0DcHIGl3VzXeVfgUrR08YIVmtQ+c+n82%20S6HJ4v0JRKxrWRxq8OO2xLhoU6VNU0OzTMVmjkI5HMex2O+JGOjARC23QXv2NWmJp6kB0k8z1fI+%20SR2jnEk7f2FEkwE7jJ5JSMdrtqFzHOBA7pe3TSkkhwNu43IALl2hpUnoAL1UZ6izEhuHD5ldK4aH%20RHdepocLxB5D82TO8v3MMTXEj02kgmyHS9G1jcjcPHuc5oex0bHBVRbHr8KIgGn1LzC9uuMkbXB0%20vqoYHM8xLjdNo18am1y1UvsPgpIXOOUCHOIaIH32xjQa6urC/LOhvx8E5s0GNiMOGcct2svsboAW%20pc+A2pWDO6tco6Cnb5cj9PAQyOMhzh26bT3qGyHDcD+ZFvlx47ne5SwHUNFnadqtJlOyHXNeEO1y%2038yG1lCA2RWhL0JmqtA36b3BrwCCqIboHDR33let6c9AyI72GMgtVhaN6koUI8OxqpGPY3M8piki%20OYOY1p8pAcLeGhv1pprXHiRahc43uyAL+qx9j9AWEgand0pyY247dHjHzLeHL4zLB9Gba8FfTcrU%20NyLkWN160tqRlZWWoJ4Ax1yNrl0Pl06AaApotLUU+B3tkZHsBsYFxx4AA8Ivsrp/s+Bxv9/xOIvM%20jRuHmH/xB0/2e+tcKR0mk9ve+8zgePdiQwMmBcZFJKhWgdAdNulacfNtUQRam5lofqtO8SNOBCGv%20Rrw5Lp/msiCq/wAqyjIn0V3M77z92Q+8OFPBctjuZx4lilkjxZPSL/RO5kcnlP8ALcUUDtah+5fY%20FxLuXbPq1yTI2Rx4EUUbEZGxt2ta221OgAFH+U+w1woy/un3RN7rnhmyGMg/TNfFG1mp3OB3Fe5F%20ZcnI7M0pVVyRiPeOE3/lnIeHOc5jmvL7KNuqA2+Irb2ln6iMvcKa6HL8ST05ttwSBbshQWTrXrWO%20FEqeZxcEIeSutlI0P3dKkaGX5Xlc54u03PUlugunQL4rSArs54kbte1SzyglV0sSvdKEEdythwzN%20MWtC7PM4nXstUqJsLM1XCMbF6UE4cGqhfo0OGhU9+3+Fa7GZuyZoBiyO377gedzgAQ5Rpb4C/X8a%20iXHwCAnmV7XCdxcAQDGEaqmwTUdr9KbzxjH0IHHujx8N0piZAxArnXNvlFxchamG5kJjGMamfbuf%20IX3s3yN/2RbU2vrpWqjHcUuDrXA8UB7S47DheGyZIdLLuG4EG6X7jy15fuLbrQjr4qwpIwyG4GYZ%20SGxY8KkR2Bc//YB7A2rmXzN2bTj8+KeFj12h7fKw9tSvxrarlEdfDGPuEZE/pNMm47CSxeg/y9uv%20WnL6CQMbkcbKeYD5JCCWPKAFDt8vRRRW85jaKnkYZjOQwlkp8rpAqEp+RVuL02vkG4p3yxeu4xv8%208Y+4dlpI0gizxed80j0JG0vsABoOuqVMQKJKPPysZvIlomDZHN87Gny/LZOx705jUSeRF9WAZbHh%20ZomgODQfz9Fso1pDSOkfSNscsPIZLG3mmEbtxCeUblUdlSrrmZ3R0DJYZ8gsDv5UaEjUqNE/xq9S%20WSmxANRg8CgsoU697VRI24tFwblD1pANtLhvBI2L8wNwetJBAlyOb6u0t1JcCBcFU8NKJCCHlwtn%20YE+dt4y02HwTvTT7A1OpkeTDGcx6jijJ2jy3Xy26d0Wq5c65YxI6TuzIsksbD57AoHHVVNeYvA7o%20z0EOcSdzQqqrzYgiylRSBVgjuklcx7idrdpVrj0W/wDYlVIbR/i55/6rhtQWmj9RPB4JCmnVqUFl%20kz07XoHACgAUAeX/AKtzOj+ofNOZc74gtkH8iOuW/wC46aL9KMhJMEO+RQDobeXXW6DslZx4FmE9%201QCPk/XZ/pSBXOGgcEuh8K342Z3RSsZE9z5CdoU7UPhr+NV4EySMYNEYK6oD9l70NAnJbZskrMFk%20b3Bxdohv9p61mlnJTZMjd58eIuCtaHvIAUABF/b++k9Ci09mlzM6XkfS9aUP2QNcl06n+yld9B1X%20yOkPyS2RxHkXcXACyp5mjS3WslBcBnJmJGxg67HGxH7ulGQ327gZG4jzFdNVQDuF1PxqcgnuDIa+%20WAxuKs8ytOlut1FLan0B5Fbme1uKzCPXicAT5zG8sJQKttLipge9kFvtL9M1phyjCy4duARoAsb6%20iptScfMtXjQjReyvcGLMybCy2STghzS47SAC3aNe1GXQconc5xfK8phRx5WC1udE8OmyWuAY5jRY%20lNfhRkCeWpn+Q9p845//AA+KHRQEgxhu8SoF3ubZyfCqTkGvIpM32nivnY9/qcVPKFjDisRAJFkT%20xprma8SHxrVkGXiedw5GoG5eC5wb67Hh5Y4AIqXCfD+KXNbeZLpDyGH5PKl4/Ux7nxnaHSBr2ndf%20UqP2vSW1aGexoiZvNQORmfx0aO8r3taBuCnSyg9Na1rV/wBrM231xj7RnC5DleJnORwOY+OOK4xZ%20nK0NTzABx2n99b15HoyYkuMf31g8lO2Lncc4cpAH6yIb2kqELmOFaWSeb1JWRf5/trieXkdLxeUz%2012xh6AAKlibeHaoVWtNC3aNcmY7k+E5uB7o3sk9NpO2QE+kgHzKth+6rgltsag4n3C6T0hJG3y73%20Rue1AERSvcUNJhL7hwYHHQ5Mrs+UPyGI704UEYFi5UsUvpVLIX2ljs4eFmNPHB+okyGlzg1xcATY%20E69Og7VMruG1lrj+y/c/JOjL4RjwFoLXyEANY7UNaPMoFY25KrqaVo4N7wnBYHB4hx8cunkCrPIj%20ZL6taey1g7NmtV3KXl2B+c4hSSDtRPMQT0GgpKDtqlAIBH6RIOx7/I0p3UtI6/KU1pMLOELZFjxS%20Ex3cUa97it9wBUBb9qEhKr6jkThLlukVGMAib38xVE1uT/CtFlmTbIeLmbXElW6DVVCpt8V8L0Jd%20BkaeQsahewtCAR3+Gg6KCv3Uk0+haC3RSfzHNADiACSANL7l8EsKaHJF3B0h3ElSm+yjykDzL160%20mapjLtqAkglCAvS4uuvQDsgFAV0EFxYd7HFpT5m2uf7KFoRbuLZ7hzcNVlL2xgkRvbYlPKhK/bVJ%20yRtT1PWWFJ6302x5HeT1OMjLvDdEK6H+z4HkP93xONSSAtc9hBeApAUkNBQi1lrh7HQsyG8tkKtU%20OCbmmwNvwB62pOxaXQQ1XAgO3C+9VBXonhSkY41hd8qdCOiC3WkDYp0UjWu3WCedqhNVufGnAEZ7%20oIHXAa5NANU0/GiAXYhe4MqCHhORlmIEfpm3xRCE6rWvCm7KDLl0OMZIc0lzVBYVVQgDtV6/Cvde%20p5aYszg7bfKEJJuhumtr/j99ZtZFyMSyPEYPzNI/MgVL+BKXqYgZCychxBVST8xJUlfj8KGoH4Gk%209h+25OS4vl+TuXYhayBqfN1fbTSsnz7LJGj4t1ZLTDSZieu2NrgrwWgqVsNxFie9d1lqcihDzMPG%20DXCbOVxI2RN8oUXcgHj0qNcdx7uxJacCJPTBe/WN8lyWuVSe6a/Cmn16h5mf5PkJMp79jhtjRjGo%20QS4kHr3pPGMfQa7jnH4rsrKx8JiLM9jG31JKalEWqb2pvqpBKWdxfEzGix4y1BjRlrUCkoOwtevH%205H+qTuoktCp5PhsTLx25E8e0Mu09QEUk1k6wi1JXQcpLhvL9wayNNCqW0T/MU6VSyKaLv+qsmxoJ%20XD03SuaQ0FTr8oFkptohrMislgL5I5CWsZMXFzSmwuCgNLb3pKU4GnJKje+Rr2vc71Y2rEQEciJv%20v36itqPs8fl+QnjGO5XNgiiM0r3fzGFJGuChrv8AN4gg604FJVclNDJhSncHQAEC4QldVB1v/fSe%20hRgfRa1r358TpYZCpnvua1bKKmIKkp58n9E57cOZz42+cHQgEodw72oiROD0d9J+PHGex8LJd5PX%20D8lxQKQ+7SvwQ1dVCMrNtmswWI31njZu+cLe+naqrloSTgQ0Ag+ZugN7nrrVJCkS7a/UAk/gdPBK%20UzoCRHmcjo2ADc/QoCLdDbxokA3Rgtc0PXQFttEtbw0okbI8ocQdoO0AGxWzbIOlIc98f1Mj7jwJ%20Ij+sjeXekUlBQ/ab6VNnFXJdVLyKWLNhc1oX5+g76krXA0daWXgOTy7UAPmCHtuAN0UdulTkPUZe%20DIGvbt9QhUSxsSCg83henLDQPhpk5jCjcx4aJ4jpqfUQahF01p1eYP8Aa8dD1HXpnnAoAFAFPnez%20fa2flSZeZxePPkzEGWV7AXOIbsCk/wCzapdUylZoiH6c+xCEPB4ZFv8Ayh00o2rsG99xmb6WfTqZ%20u2X27gvAVA6Fp1p7UKWNf9I/piif8s8en/6BtG1ArNCj9JvpoXFx9tYCnX+S2hVQSKP0q+nBIJ9u%20YBLSCP5LbEUtqDcxZ+mP09Li7/l/B3EIT6LdO1G1dgljuP8ATr2LjNDMfg8OJrbtDImhE7JQ6LsU%20uSy6kj/kv2p/6Vj/APgFL069kG99wx7M9qgqOLxwVX5BqOtPYuwt7Ff8oe2f/TYP/DRtXYe+3cH/%20ACj7Z/8ATYPgWBKHRdhO77g/5Q9sf+mwf+AU9q7D9S3cTJ7N9qyROik4vHdG/wCZhYENLauwt77i%20v+UfbIRONgCaI1NKXp17BuYv/lb26gH9OgQBANg0pelXsG59wj7U9tlV46C42lGAW7UelXsG+3cY%20n9jez54mxTcPiyRssxr4muAHgtHpV7D9W3ciY/0w+nuO6R0Ht/CjdMElLYmjcNb0/Tr2Bclloxv/%20AKU/Tba5v/LeAjyrh6Lb2I/jT2LsHq27sDvpP9NXMDHe28AtAAAMLdBpS9OvYW99xH/SL6Ylu0+2%20eP2qqeg2nsQbmK/6T/TRAP8Alrj0ARPQZpRsQO77jkP0t+ncJaYvb2Cws+UiJoSntQtzH3/T32Q+%20IxP4TEdG75mmJpBpxlAiJ/0l+mq7v+W8HciL6QVPjQPcwP8ApN9NHu3P9tYDnIimFppQEsl4f099%20j4bHMxeDw4WO1ayFoFvspOqYbmSne0PbLvm42A2T5elPahq7Eu9me1XLu4vHJIQksGlLYuwb33GX%20ewfZbpBI7hcQyNO4PMTVBVVBpenXsX61+7DZ7C9mMCM4bEaCotE0a60lxViIF61+4P8AkL2Z/wCj%204v8A/DbT9OvYPWv3CHsH2WAQOGxQqqkY6609lewvUt3D/wCQ/ZqJ/RsVNU9MUbF2D1bdxP8A0/8A%20ZP8A6LiG63jBuKNi7D9a/cMewPZQKjhcRdP9NtGxdg9a/cS76eex3Ek8JiEkEE+k1UPjS9OvYPWv%203YP+nvsk68LiH4xNOtj0o9Ndh+vfuxP/AE59iHXgsM/GJtPYhetfuwO+m/sJ2vA4R7fyW0tiB813%201ZbZPE40nDv4qADHxjD+njbGEDGbdoDQE0FU1Kgic5MNH9GcNhaRykpLUU+mASE/3q5/8ddzX1vA%20Dvozx5O4cg9rupEYvfr5vCl/jeI1z+ATvoxhFqf1SUFE3CJqqevzd6F7Zdw9d9hyH6PYcTQP6lI4%206F3pgE2S6Oo/xvET52+go/SDD/8AUZPzJ/LH5v8A2u1P/GQLmYzL9FuNkILuQeqqT6TSetvm8aH7%20fxD1mVvO/wDb/g8rxTuPHNT47Xkb5GQtJLRfb8wtWnFxqjkm/JuUGbd/2l8S5F9x5CgkqMdi3/8A%20brtfP4HN6ZH/AP7P+KDQB7nyQgI/+lj0PT56j1QXGB//AGf8O4IPcuQOi/pY1/8Ax0eqP0xmT/s2%204h7U/wCaMoHoRjR//npbytsG29v/AEA4fhOBi4fG5KR0bGObJMYmtc9z187gHa371y34tzmTZckK%20IM7B/wBqXFRsAPuLJcUILv08akePmNdi5mjnfGmxxv8A2r8QCCefyCQVH8hgC+I30vVYLjHMn/tf%204+aIMHuLIYR+b0IyUVUs4aGn63gL0iI3/tM4ZrmH/mHJRgsP08eqIvzU/XYPimfEseE/7ZOH43ko%20M2Tmpsn0XbxCYGMaSidHE0r8zsoGuNJmyyfpdhzva92dJvao3bATtIRLuOgtXK6djWREn0qwXRCP%209a9ACB5AiJYa9KXpFb2VGd9COMynxn+pyMYwqWCJqOKJfzDTpSfChrkY036CYYmZIeamOxSB6Tde%20/wA1D4g9Qch+g/HRqnLTEueXuJibfT/a8Kr0xbwZH0LxpZN7eamYjtzB6LSh/wDFQuMfqeAcn0Kw%205Npfy8peCRv9Fqlp6fN0qlUW/KCNN/298XI/c3lZI27Q0sbC3aU6puo2hvK7L/7ZONyW7Dz07I+r%20RCw20QHdap9MFcqsn/tF4jIMhd7kyUk1H6eM+H+ej0xvkyg6dx/02xMLisTjm5jnx4kMcDXlgBcI%20+rkd1qlVJQQ2T/8AkvGBJE5BRGjbYd7LVCFN9oQtNsgp/ulf/wAVAwz7PxyLznd329vtoEJPs2Au%20Dv1BDgCLNTUJa9Icif8AkuEyB/6k26bAnRetEBIg+x8c7v8AinITby6D79fGnAiJk/TXDyY3xy5Z%20cx67gY+h+Dh2qbVlFKzTKb/ohxojaxvIvDW6D0mnqe7u1q537bxNfW8B3/oxxhBDs57lUBxjarbW%20S/Q0f43iHrvsNt+imG3TlphdSRG24Oo1o/xl3H677DmP9GsOHJhyP6m9z4nsfeFoUsK9HdUpr20d%20RPn8Do1dJgCgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUAC%20gAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACg%20AUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgAUACgD/2Q==" height="281" width="665" overflow="visible"> </image>
          </svg>
        </div>
      </div>
      <div class="fig"><span class="labelfig">FIGURA 3.&nbsp; </span><span class="textfig">Posición del botador (1) respecto al 
        extremo de las cuchillas (2) (a) y conclusión de la extracción de la 
        caña de forma manual (b).</span></div>
      <p>La evaluación del efecto de los
        equipos de cosecha-transporte en la calidad del trabajo de la sonda 
        mostró diferencias significativas en 7,23 kg en la variante con CASE 
        8800 y Sinotruck (20 t) con Remolque de 20 t respecto a la KTP 2M y el 
        ZIL130 (6 t) con el Remolque 6 t, al nivel de confianza del 95% (<span class="tooltip"><a href="#t8">Tabla 3</a></span>). Las materias extrañas obtenidas en las cosechadoras CASE se encontraron entre 10 y 12% y en las KTP entre 15 y 20%.</p>
      <div class="table" id="t8"><span class="labelfig">TABLA 3.&nbsp; </span><span class="textfig">Masa de la muestra en función del sistema cosecha transporte</span></div>
      <div class="contenedor">
        <div class="outer-centrado">
          <div style="max-width: 1160px;" class="inner-centrado">
            <table>
              <colgroup>
              <col>
              <col>
              <col>
              <col>
              </colgroup>
              <thead>
                <tr>
                  <th align="center">Variante</th>
                  <th align="center">Masa*, kg</th>
                  <th align="center">Error estándar</th>
                  <th align="center">Valor P</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="center">CASE 8800 y Sinotruck (20t)+Remolque (20t)</td>
                  <td align="center">18,69a</td>
                  <td align="center">±1,15</td>
                  <td rowspan="2" align="center">0,0011</td>
                </tr>
                <tr>
                  <td align="center">KTP 2M y ZIL130(10t)+Remolque 10t</td>
                  <td align="center">11,46b</td>
                  <td align="center">±1,27</td>
                </tr>
                <tr>
                  <td colspan="4" align="justify"><i>*n=7</i></td>
                </tr>
              </tbody>
            </table>
          </div>
        </div>
      </div>
      <div class="clear"></div>
      <p>La
        cosecha de caña requedada y de retoños acamados influyó en el alto 
        porcentaje de materias extraña. Sin embargo, las particularidades del 
        proceso tecnológico de las cosechadoras CASE que cortan la caña en 
        trozos de menor tamaño, de conjunto con el empleo de extractores logran 
        mayor eficiencia en la limpieza de la caña respecto a las cosechadoras 
        KTP, coincidiendo con lo planteado por <span class="tooltip"><a href="#B23">Placeres (2015)</a><span class="tooltip-content">PLACERES,
        Y.: “Evaluación de los índices tecnológicos-explotativos y económicos 
        de la cosechadora cañera Case ih Austoft a 8000 en la UEB Perucho 
        Figueredo”, 2015.</span></span>. </p>
      <p>Para las condiciones donde la 
        caña cosechada cuente con alto contenido de materias extrañas, 
        superiores al 12% y no se satisfaga el peso establecido, se recomienda 
        realizar varias muestras en el medio de transporte hasta completar la 
        masa establecida.</p>
      <p>La Sonda mostró una productividad en el tiempo limpio de 15,15 kg/minutos (<span class="tooltip"><a href="#t9">Tabla 4</a></span>).
        Sin embargo, el régimen de trabajo con los órganos del equipo activos 
        por un período corto, respecto al total en que se toma la muestra, 
        determinó que los restantes índices de productividad de tiempo 
        operativo, productivo y de explotación sean muy inferiores respecto al 
        del tiempo limpio, en 29, 21 y 15%, respectivamente. No obstante, en la 
        práctica se estableció 16 muestras diarias por el <span class="tooltip"><a href="#B11">Grupo Empresarial AZCUBA (2018)</a><span class="tooltip-content">GRUPO EMPRESARIAL AZCUBA: <i>Resolución
        202/2018. Procedimiento para la aplicación de las “instrucciones 
        metodológicas para el control y aplicación del sistema de precios de la 
        caña por su calidad (SPCC)”</i>, Inst. Grupo Empresarial AZCUBA, Resolición ministerial, La Habana, Cuba, 18 p., 2018.</span></span>, para lo cual la Sonda satisface sin dificultad la demanda para una jornada de trabajo.</p>
      <div class="table" id="t9"><span class="labelfig">TABLA 4.&nbsp; </span><span class="textfig">Indicadores de explotación de la Sonda</span></div>
      <div class="contenedor">
        <div class="outer-centrado">
          <div style="max-width: 1160px;" class="inner-centrado">
            <table>
              <colgroup>
              <col>
              <col>
              </colgroup>
              <thead>
                <tr>
                  <th align="center">Parámetro</th>
                  <th align="center">Valor</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="justify">Productividad en el tiempo limpio, kg/minutos</td>
                  <td align="center">15,15</td>
                </tr>
                <tr>
                  <td align="justify">Productividad en el tiempo operativo, kg/minutos</td>
                  <td align="center">4,33</td>
                </tr>
                <tr>
                  <td align="justify">Productividad en el tiempo productivo, kg/minutos</td>
                  <td align="center">3,10</td>
                </tr>
                <tr>
                  <td align="justify">Productividad en el tiempo de explotación, kg/minutos</td>
                  <td align="center">2,21</td>
                </tr>
                <tr>
                  <td align="justify">Coeficiente de mantenimiento técnico</td>
                  <td align="center">0,97</td>
                </tr>
                <tr>
                  <td align="justify">Coeficiente de seguridad técnica</td>
                  <td align="center">0,74</td>
                </tr>
                <tr>
                  <td align="justify">Coeficiente de utilización del tiempo productivo</td>
                  <td align="center">0,20</td>
                </tr>
                <tr>
                  <td align="justify">Coeficiente de utilización del tiempo de explotación</td>
                  <td align="center">0,10</td>
                </tr>
              </tbody>
            </table>
          </div>
        </div>
      </div>
      <div class="clear"></div>
      <p>El
        equipo logró un coeficiente de seguridad técnica superior al 70%. El 
        problema fundamental se encontró en las roturas de las cuchillas del 
        Casquillo, causado principalmente por el inadecuado dimensionamiento del
        orificio para tomar la muestra en el medio de transporte, por lo que se
        considera ajena a la máquina. No obstante, se debe señalar que no se 
        contaba con repuestos para el remplazo del casquillo a pesar de ser un 
        componente de rápido desgaste. Otro problema de menor incidencia fueron 
        los salideros en las mangueras del sistema hidráulico. En general se 
        considera que la Sonda Toma Muestra presentó una adecuada fiabilidad. 
        Por otra parte, los coeficientes de utilización del tiempo productivo y 
        del tiempo de explotación son bajos como resultado del propio régimen de
        trabajo del equipo explicado anteriormente.</p>
      <p>Los gastos de combustible en función del número y peso de la muestra son bajos (<span class="tooltip"><a href="#t10">Tabla 5</a></span>),con
        promedio de 0,053 L/muestra y 0,004 L/kg, respectivamente; lo cual se 
        debió al régimen discontinuo y de corto tiempo de operación con el motor
        funcionando en la toma de la muestra. </p>
      <div class="table" id="t10"><span class="labelfig">TABLA 5.&nbsp; </span><span class="textfig">Determinación del gasto de combustible</span></div>
      <div class="contenedor">
        <div class="outer-centrado">
          <div style="max-width: 1160px;" class="inner-centrado">
            <table>
              <colgroup>
              <col>
              <col>
              <col>
              <col>
              <col>
              </colgroup>
              <thead>
                <tr>
                  <th align="center">Parámetro</th>
                  <th align="center">UM</th>
                  <th align="center">Media*</th>
                  <th align="center">Desviación estándar</th>
                  <th align="center">Coeficiente de Variación, %</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="center">Gasto de combustible por muestra</td>
                  <td align="center">L/muestra</td>
                  <td align="center">0,053</td>
                  <td align="center">0,019</td>
                  <td align="center">35,951</td>
                </tr>
                <tr>
                  <td align="center">Gasto combustible por peso de la muestra</td>
                  <td align="center">L/kg</td>
                  <td align="center">0,004</td>
                  <td align="center">0,002</td>
                  <td align="center">39,717</td>
                </tr>
                <tr>
                  <td colspan="5" align="justify"><i>*n=9</i></td>
                </tr>
              </tbody>
            </table>
          </div>
        </div>
      </div>
      <div class="clear"></div>
      <p>En
        sentido general, el empleo de la Sonda Horizontal en la Agroindustria 
        Azucarera de otros países como: Guatemala, Costa Rica y Brasil ha 
        brindado igualmente resultados satisfactorios en el muestreo de caña de 
        azúcar para evaluar la calidad de la materia prima que va a la industria
        de forma diferenciada por productor (<span class="tooltip"><a href="#B8">Estrada, 2012</a><span class="tooltip-content">ESTRADA, M.O.: <i>Comparación de cinco métodos analíticos para determinar la calidad de la caña de azúcar</i>, <i>[en línea]</i>,
        Trabajo de graduación para optar por el título de Ingeniero Químico, 
        Trabajo de graduación para optar por el título de Ingeniero Químico, 
        Guatemala, 172 p., 2012, <i>Disponible en:</i> <a href="https://biblioteca.usac.edu.gt/tesis/08/08_1253_Q.pdf" target="xrefwindow">https://biblioteca.usac.edu.gt/tesis/08/08_1253_Q.pdf</a>, <i>[Consulta: 12 de enero de 2022]</i>.</span></span>; <span class="tooltip"><a href="#B3">Canales, 2014</a><span class="tooltip-content">CANALES, M.C.: <i>Desarrollo de un plan de mantenimiento preventivo basado en la metodología RCM para el departamento de patio de caña</i>,
        Instituto Tecnológico de Costa Rica. Escuela de Ingeniería 
        Electromecánica. Central Azucarera Tempisque S.A. (Catsa), Informe de 
        práctica de especialidad para optar por el título de Ingeniero en 
        Mantenimiento Industrial, Grado Licenciatura, Cartago, Costa Rica, 192 
        p., publisher: Instituto Tecnológico de Costa Rica, 2014.</span></span>; <span class="tooltip"><a href="#B13">IRBI, 2022</a><span class="tooltip-content">IRBI: <i>Sonda Oblicua IRBI Modelo FB06</i>, <i>[en línea]</i>, IRBI, 2022, <i>Disponible en:</i> <a href="https://www.irbi.com.br/br/noticias/sonda-oblicua-irbi-modelo-fb06" target="xrefwindow">https://www.irbi.com.br/br/noticias/sonda-oblicua-irbi-modelo-fb06</a>, <i>[Consulta: 10 de enero de 2022]</i>.</span></span>).</p>
    </article>
    <article class="section"><a id="id0x56e6980"><!-- named anchor --></a>
      <h3>CONCLUSIONES</h3>
      &nbsp;<a href="#content" class="boton_1">⌅</a>
      <p>La evaluación de la Sonda Horizontal AZUTECNIA en el muestreo de caña de azúcar para el Sistema de Pago por Calidad mostró:</p>
      <div class="list"><a id="id0x56e6e80"><!-- named anchor --></a>
        <ul>
          <li>
            <p>Calidad
              del trabajo satisfactoria, al cumplir con los 15 kg para los análisis 
              en los laboratorios en caña cosechada con materias extrañas inferiores 
              al 12%.</p>
          </li>
          <li>
            <p>Productividad en el tiempo limpio de 15 
              kg/minutos, cumpliendo satisfactoriamente las 16 muestras diarias 
              establecidas para el laboratorio.</p>
          </li>
          <li>
            <p>Disminución de la 
              productividad de tiempo operativo, productivo y de explotación respecto a
              la de tiempo limpio en 29, 21 y 15%, respectivamente; así como de los 
              coeficientes de explotación asociados a estos debido al régimen de 
              operación con los órganos de trabajo activos por un período corto.</p>
          </li>
          <li>
            <p>Coeficiente
              de seguridad técnica superior al 70%, lo cual mostró una adecuada 
              fiabilidad; siendo necesario poner a disposición del cliente repuestos 
              como el Casquillo con Cuchillas. </p>
          </li>
          <li>
            <p>Gastos de combustible 
              promedios en función del número de muestras tomadas y de su peso de 
              0,053 L/muestra y 0,004 L/kg, respectivamente.</p>
          </li>
        </ul>
      </div>
    </article>
  </section>
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