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<?xml-stylesheet type="text/xsl" media="screen" href="/~d/styles/rss2enclosuresfull.xsl"?><?xml-stylesheet type="text/css" media="screen" href="http://feeds.feedburner.com/~d/styles/itemcontent.css"?><rss xmlns:atom="http://www.w3.org/2005/Atom" xmlns:openSearch="http://a9.com/-/spec/opensearch/1.1/" xmlns:blogger="http://schemas.google.com/blogger/2008" xmlns:georss="http://www.georss.org/georss" xmlns:gd="http://schemas.google.com/g/2005" xmlns:thr="http://purl.org/syndication/thread/1.0" xmlns:media="http://search.yahoo.com/mrss/" xmlns:itunes="http://www.itunes.com/dtds/podcast-1.0.dtd" version="2.0"><channel><atom:id>tag:blogger.com,1999:blog-7086209542673846414</atom:id><lastBuildDate>Sat, 18 May 2013 15:21:33 +0000</lastBuildDate><category>DBF</category><category>parsimony</category><category>NDM</category><category>conceptos</category><category>Croizat</category><category>Georreferenciación</category><category>insectos</category><category>grados decimales</category><category>monofilia</category><category>manuales</category><category>Conservación</category><category>sistemática</category><category>morfometría</category><category>panbiogeografía</category><category>VIP</category><category>GoogleEarth</category><category>filogenia</category><category>TnT</category><category>cladismo</category><category>GenBank</category><category>filosofía</category><category>landmarks</category><category>parsimonia</category><category>secuencias</category><category>Reunión</category><category>Ontologias</category><category>Culicini</category><category>libros</category><category>evolución</category><category>Andes</category><category>documental</category><category>bibliografía</category><category>PDA</category><category>Latinoamérica</category><category>instalación</category><category>flora</category><category>libro</category><category>Andrés Bello</category><category>Suramerica</category><category>MaxEnt</category><category>conferencias</category><category>biogeografía</category><category>megafilogenias</category><category>méxico</category><category>Farris</category><category>molecular</category><category>árboles</category><category>Modelo</category><category>Darwin</category><category>Amazonas</category><category>Revistas</category><category>datos</category><category>macros</category><category>tutorial</category><category>matrices</category><category>Biografía</category><category>teoría</category><category>programas</category><category>taller</category><category>bibliometría</category><category>Distribución</category><category>Venezuela</category><category>historia</category><category>curso</category><category>SIG</category><category>diversidad</category><category>Hennig</category><category>alineamiento</category><category>pocketpc</category><category>Chile</category><category>fenetica</category><category>geoespacial</category><category>COI</category><category>riqueza</category><category>clase</category><category>thin-plate spline</category><category>biogeografia</category><category>parafilia</category><category>vertebrados</category><category>endemismo</category><category>sensores remotos</category><category>mapas</category><title>Cladística y Biogeografía</title><description>Para entender sobre filogenia y patrones de distribución de la biota</description><link>http://cladisticaybiogeografia.blogspot.com/</link><managingEditor>noreply@blogger.com (Jonathan Liria)</managingEditor><generator>Blogger</generator><openSearch:totalResults>89</openSearch:totalResults><openSearch:startIndex>1</openSearch:startIndex><openSearch:itemsPerPage>25</openSearch:itemsPerPage><atom10:link xmlns:atom10="http://www.w3.org/2005/Atom" rel="self" type="application/rss+xml" href="http://feeds.feedburner.com/cladisticaybiogeografia" /><feedburner:info xmlns:feedburner="http://rssnamespace.org/feedburner/ext/1.0" uri="cladisticaybiogeografia" /><atom10:link xmlns:atom10="http://www.w3.org/2005/Atom" rel="hub" href="http://pubsubhubbub.appspot.com/" /><itunes:owner><itunes:email>noreply@blogger.com</itunes:email></itunes:owner><itunes:explicit>no</itunes:explicit><itunes:subtitle>Para entender sobre filogenia y patrones de distribución de la biota</itunes:subtitle><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-3317866331269241485</guid><pubDate>Wed, 20 Mar 2013 12:00:00 +0000</pubDate><atom:updated>2013-03-20T05:00:39.641-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">NDM</category><category domain="http://www.blogger.com/atom/ns#">biogeografía</category><category domain="http://www.blogger.com/atom/ns#">Latinoamérica</category><category domain="http://www.blogger.com/atom/ns#">curso</category><category domain="http://www.blogger.com/atom/ns#">datos</category><category domain="http://www.blogger.com/atom/ns#">Suramerica</category><category domain="http://www.blogger.com/atom/ns#">endemismo</category><category domain="http://www.blogger.com/atom/ns#">Distribución</category><category domain="http://www.blogger.com/atom/ns#">VIP</category><category domain="http://www.blogger.com/atom/ns#">filogenia</category><category domain="http://www.blogger.com/atom/ns#">conceptos</category><category domain="http://www.blogger.com/atom/ns#">Conservación</category><category domain="http://www.blogger.com/atom/ns#">geoespacial</category><category domain="http://www.blogger.com/atom/ns#">Georreferenciación</category><title>Curso programas de computación para Biogeografía (NDM y VIP)</title><description>CURSO DE POSTGRADO TEÓRICO - PRÁCTICO INTRODUCTORIO&lt;br /&gt;
&lt;br /&gt;
"PROGRAMAS DE COMPUTACIÓN PARA BIOGEOGRAFÍA: FUNDAMENTOS Y APLICACIONES"&lt;br /&gt;
&lt;br /&gt;
DOCENTES RESPONSABLES:&lt;br /&gt;
&lt;br /&gt;
Dra.&amp;nbsp; M.&amp;nbsp; Dolores&amp;nbsp; CASAGRANDA&amp;nbsp; (Inst.&amp;nbsp; Herpetología-FML&amp;nbsp; - Postdoc Carnegie Museum)&lt;br /&gt;
&lt;br /&gt;
Dra. Claudia A. SZUMIK&amp;nbsp; (INSUE; Fac. Cs. Naturales e&amp;nbsp; IML&amp;nbsp; - Inv. Indep. CONICET)&lt;br /&gt;
&lt;br /&gt;
Coordinador:&amp;nbsp; Dr.&amp;nbsp; Diego&amp;nbsp; BALDO.&amp;nbsp; Laboratorio&amp;nbsp; de&amp;nbsp; Genética Evolutiva, Instituto de Biología Subtropical (CONICET-UNaM).&lt;br /&gt;
&lt;br /&gt;
Objetivos del curso: &lt;br /&gt;
&lt;br /&gt;
Brindar a los alumnos fundamentos teóricos y metodológicos de ayuden a abordar algunas preguntas y problemas&amp;nbsp; de&amp;nbsp; la&amp;nbsp; biogeografía&amp;nbsp; histórica;&amp;nbsp; específicamente&amp;nbsp; en&amp;nbsp; el&amp;nbsp; análisis&amp;nbsp; de&amp;nbsp; áreas&amp;nbsp; de&amp;nbsp; endemismo&amp;nbsp; y eventos de vicarianza. Se propone dar a los alumnos herramientas básicas necesarias para desarrollar estudios biogeográficos básicos. De manera que&amp;nbsp; los objetivos de este&amp;nbsp; curso no&amp;nbsp; son&amp;nbsp; sólo mostrar&amp;nbsp; los fundamentos&amp;nbsp; teóricos&amp;nbsp; sino&amp;nbsp; también&amp;nbsp; su&amp;nbsp; aplicación&amp;nbsp; práctica&amp;nbsp; mediante&amp;nbsp; el&amp;nbsp; uso&amp;nbsp; de&amp;nbsp; programas&amp;nbsp; de computación específicamente desarrollados para estos estudios.&lt;br /&gt;
&lt;br /&gt;
Contenidos:&lt;br /&gt;
&lt;br /&gt;
Tema 1. AREAS DE ENDEMISMO. Generalidades. Propuestas&amp;nbsp; formales y no&amp;nbsp; tan&amp;nbsp; formales para&amp;nbsp; la identificación&amp;nbsp; de&amp;nbsp; áreas&amp;nbsp; de&amp;nbsp; endemismo.&amp;nbsp; Areas&amp;nbsp; de&amp;nbsp; endemismo&amp;nbsp; y&amp;nbsp; regionalizaciones&amp;nbsp; biogeográficas Importancia de los métodos cuantitativos y su relación con lo que se pretende evaluar. Introducción a los programas NDM/VNDM parte I.&lt;br /&gt;
&lt;br /&gt;
Tema&amp;nbsp; 2.&amp;nbsp; AREAS&amp;nbsp; DE&amp;nbsp; ENDEMISMO.&amp;nbsp; Criterio&amp;nbsp; de&amp;nbsp; optimalidad&amp;nbsp; en&amp;nbsp; el&amp;nbsp; análisis&amp;nbsp; de&amp;nbsp; endemicidad. Propuestas de renombrar el concepto de a.e. Necesidad de modelo nulo?. Introducción a los programas NDM/VNDM parte II.&lt;br /&gt;
&lt;br /&gt;
Tema 3. EVENTOS DE VICARIANZA. Distinción entre estudios sobre historia de la tierra e historia de los taxones. Críticas y propuestas de Hovenkamp sobre la Biogeografía Histórica. Importancia del componente&amp;nbsp; espacial.&amp;nbsp; Criterio&amp;nbsp; de&amp;nbsp; optimalidad&amp;nbsp; para&amp;nbsp; la&amp;nbsp; identificación&amp;nbsp; de&amp;nbsp; potenciales&amp;nbsp; barreras. Introducción al programa VIP.&lt;br /&gt;
&lt;br /&gt;
Información:&lt;br /&gt;
&lt;br /&gt;
Secretaría del Doctorado en Ciencias Aplicada, Facultad de Ciencias Exactas, Químicas y Naturales.&lt;br /&gt;
&lt;br /&gt;
Calle Félix de Azara 1552 – 1º Piso (3300) Posadas – MisionesTE: 0376-422186 Int. 125 (Martes a Viernes de 16:00 a 18:00 hs.) Email: doctoradoaplicadas@fceqyn.unam.edu.ar/@gmail.com</description><link>http://cladisticaybiogeografia.blogspot.com/2013/03/curso-programas-de-computacion-para.html</link><author>noreply@blogger.com (Jonathan Liria)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-5488857940095360099</guid><pubDate>Wed, 20 Mar 2013 12:00:00 +0000</pubDate><atom:updated>2013-03-26T07:02:28.190-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">biogeografía</category><category domain="http://www.blogger.com/atom/ns#">Latinoamérica</category><category domain="http://www.blogger.com/atom/ns#">programas</category><category domain="http://www.blogger.com/atom/ns#">Modelo</category><category domain="http://www.blogger.com/atom/ns#">Andes</category><category domain="http://www.blogger.com/atom/ns#">endemismo</category><category domain="http://www.blogger.com/atom/ns#">sistemática</category><category domain="http://www.blogger.com/atom/ns#">Amazonas</category><category domain="http://www.blogger.com/atom/ns#">Distribución</category><category domain="http://www.blogger.com/atom/ns#">filogenia</category><category domain="http://www.blogger.com/atom/ns#">conceptos</category><category domain="http://www.blogger.com/atom/ns#">geoespacial</category><category domain="http://www.blogger.com/atom/ns#">evolución</category><category domain="http://www.blogger.com/atom/ns#">filosofía</category><category domain="http://www.blogger.com/atom/ns#">diversidad</category><category domain="http://www.blogger.com/atom/ns#">mapas</category><category domain="http://www.blogger.com/atom/ns#">riqueza</category><title>Creado Grupo Google de discusión Biogeografía</title><description>&lt;div style="color: #eeeeee;"&gt;
&lt;span style="font-size: small;"&gt;Recientemente fue creado un grupo de discusión llamado:&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span class="gwt-InlineLabel GHSP2CYBCYB"&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div class="GHSP2CYBML GHSP2CYBNK" style="color: #eeeeee;"&gt;
&lt;span style="font-size: small;"&gt; &lt;span title="El “Grupo Latinoamericano y Caribeño de Biogeografía” pretende promover el desarrollo y consolidación de una comunidad biogeográfica diversa. Está abierto a la participación de biogeógrafos, ya sean profesores, investigadores, estudiante o aficionados."&gt;&amp;nbsp;&lt;/span&gt;&lt;/span&gt;&lt;br /&gt;
&lt;span style="font-size: small;"&gt;&lt;span title="El “Grupo Latinoamericano y Caribeño de Biogeografía” pretende promover el desarrollo y consolidación de una comunidad biogeográfica diversa. Está abierto a la participación de biogeógrafos, ya sean profesores, investigadores, estudiante o aficionados."&gt;&lt;b&gt;GRUPO LATINOAMERICANO Y CARIBEÑO DE BIOGEOGRAFÍA &lt;/b&gt;&lt;/span&gt;&lt;/span&gt;&lt;br /&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div class="GHSP2CYBML GHSP2CYBNK" style="color: #eeeeee;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span title="El “Grupo Latinoamericano y Caribeño de Biogeografía” pretende promover el desarrollo y consolidación de una comunidad biogeográfica diversa. Está abierto a la participación de biogeógrafos, ya sean profesores, investigadores, estudiante o aficionados."&gt;El
 “Grupo Latinoamericano y Caribeño de Biogeografía” pretende promover el
 desarrollo y consolidación de una comunidad biogeográfica diversa. Está
 abierto a la participación de biogeógrafos, ya sean profesores, 
investigadores, estudiante o aficionados.&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee;"&gt;
&lt;span style="font-size: small;"&gt;&lt;br /&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee;"&gt;
&lt;cite&gt;https://groups.google.com/d/forum/biogeo-la&lt;/cite&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee;"&gt;
&lt;span style="font-size: small;"&gt;&lt;br /&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee;"&gt;
&lt;span style="font-size: small;"&gt;Te invitamos a participar, pero antes las reglas para realizar los comentarios:&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee;"&gt;
&lt;/div&gt;
&lt;div style="color: #eeeeee;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;&lt;b&gt;Normas de uso:&lt;/b&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
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&lt;span style="font-size: small;"&gt;&lt;b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Nombres de usuarios:&amp;nbsp;&lt;/span&gt;&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt;"&gt;
&lt;span style="font-size: small;"&gt;&lt;b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;&amp;nbsp;&lt;/span&gt;&lt;/b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;&lt;br /&gt;
es requisito identificarse con el nombre real.&lt;br /&gt;
&lt;b&gt;&amp;nbsp;&lt;/b&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt;"&gt;
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&lt;span style="font-size: small;"&gt;&lt;b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Normas de estilo&lt;/span&gt;&lt;/b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-left: 41.3pt;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;a.&lt;span style="font-family: 'Times New Roman';"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
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En internet equivale a gritar y es muy desagradable.&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-left: 41.3pt;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;b.&lt;span style="font-family: 'Times New Roman';"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;/span&gt;&lt;/span&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;El idioma a usar es
el español o el portugués. Evitar el lenguaje soez y los localismos.&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt; margin-left: 41.3pt;"&gt;
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manera más correcta posible. &lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
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&lt;span style="font-size: small;"&gt;&lt;b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Normas de contenido&lt;/span&gt;&lt;/b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-left: 41.3pt;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;a.&lt;span style="font-family: 'Times New Roman';"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;/span&gt;&lt;/span&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;No incluir contenidos ilegales, tales como piratería o prácticas de
dudosa ética o legalidad.&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
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&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;b.&lt;span style="font-family: 'Times New Roman';"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;/span&gt;&lt;/span&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;No se permite
contenido racista, xenófobo, homófobo o sexista, así como insultos a otros
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&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;c.&lt;span style="font-family: 'Times New Roman';"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;/span&gt;&lt;/span&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;La crítica
constructiva siempre es bienvenida, no así la destructiva. &lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-left: 41.3pt;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;d.&lt;span style="font-family: 'Times New Roman';"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;/span&gt;&lt;/span&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;No está permitida
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contenidos que se desvíen de la temática general del foro ni aquellos que
carezcan de la debida seriedad.&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
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&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt; text-align: justify;"&gt;
&lt;span style="font-size: small;"&gt;&lt;b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Fuentes de contenidos&lt;/span&gt;&lt;/b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Si se va a publicar contenido de otras personas, &lt;b&gt;siempre &lt;/b&gt;hay que
citar la fuente original. Utilizar siempre las comillas en citas textuales. &lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt;"&gt;
&lt;span style="font-size: small;"&gt;&lt;b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Nomes de usuários: &lt;/span&gt;&lt;/b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;&lt;br /&gt;
é necessário identificar-se com o nome verdadeiro&lt;/span&gt;&lt;b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;&amp;nbsp;&lt;/span&gt;&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
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&lt;span style="font-size: small;"&gt;&lt;b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Eliminação de mensagens:&lt;br /&gt;
&lt;/span&gt;&lt;/b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;serão eliminadas as mensagens fora do tema
(off-topic), anúncios (spam), correntes.&lt;br /&gt;
&lt;/span&gt;&lt;b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;&amp;nbsp;&lt;/span&gt;&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt;"&gt;
&lt;span style="font-size: small;"&gt;&lt;b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Normas de estilo&lt;/span&gt;&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif; line-height: 18px;"&gt;a.&lt;span style="font-family: 'Times New Roman';"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;/span&gt;&lt;/span&gt;&lt;span style="font-family: Arial,sans-serif; line-height: 18px;"&gt;Não utilizar maiúsculas no título nem abusar delas
no conteúdo. Na internet equivale a gritar e é muito desagradável.&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-left: 0cm; text-indent: 0cm;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;b.&lt;span style="font-family: 'Times New Roman';"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;/span&gt;&lt;/span&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Usar o espanhol ou o português. Evitar o
"portunhol".&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt; margin-left: 0cm; text-indent: 0cm;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;c.&lt;span style="font-family: 'Times New Roman';"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;/span&gt;&lt;/span&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Escrever corretamente.&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt;"&gt;
&lt;span style="font-size: small;"&gt;&lt;b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Normas de conteúdo&lt;/span&gt;&lt;/b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-left: 0cm; text-indent: 0cm;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;a.&lt;span style="font-family: 'Times New Roman';"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;/span&gt;&lt;/span&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Não é permitido incluir conteúdos ilegais, tais
como pirataria ou práticas de duvidosa ética ou legalidade.&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-left: 0cm; text-indent: 0cm;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;b.&lt;span style="font-family: 'Times New Roman';"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;/span&gt;&lt;/span&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Não é permitido conteúdo racista, xenófobo,
homófobo ou sexista, assim como insultos a outros usuários ou moderadores.&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-left: 0cm; text-indent: 0cm;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;c.&lt;span style="font-family: 'Times New Roman';"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;/span&gt;&lt;/span&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;A crítica construtiva sempre é bem-vinda. &lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-left: 0cm; text-indent: 0cm;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;d.&lt;span style="font-family: 'Times New Roman';"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;/span&gt;&lt;/span&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Não é permitido a propaganda ou promoção direta de
produtos ou serviços, a menos que totalmente justificado. &lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt; margin-left: 0cm; text-indent: 0cm;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;e.&lt;span style="font-family: 'Times New Roman';"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;/span&gt;&lt;/span&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Não é permitido conteúdos que se desviem da
temática geral do fórum nem aquelas que careçam da devida seriedade.&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt; text-align: justify;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt; text-align: justify;"&gt;
&lt;span style="font-size: small;"&gt;&lt;b&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Fontes de conteúdos&lt;/span&gt;&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="color: #eeeeee; line-height: normal; margin-bottom: 0.0001pt; text-align: justify;"&gt;
&lt;span style="font-size: small;"&gt;&lt;span style="font-family: Arial,sans-serif;"&gt;Se publicar conteúdo de outras pessoas, sempre
citar a fonte original. Sempre utilizar as aspas em citação textual. &lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
</description><link>http://cladisticaybiogeografia.blogspot.com/2013/03/creado-grupo-google-de-discusion.html</link><author>noreply@blogger.com (Jonathan Liria)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-2349933432475627111</guid><pubDate>Wed, 13 Mar 2013 11:26:00 +0000</pubDate><atom:updated>2013-03-13T04:26:17.274-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">Hennig</category><category domain="http://www.blogger.com/atom/ns#">curso</category><category domain="http://www.blogger.com/atom/ns#">árboles</category><category domain="http://www.blogger.com/atom/ns#">parsimony</category><category domain="http://www.blogger.com/atom/ns#">matrices</category><category domain="http://www.blogger.com/atom/ns#">sistemática</category><category domain="http://www.blogger.com/atom/ns#">TnT</category><category domain="http://www.blogger.com/atom/ns#">filogenia</category><category domain="http://www.blogger.com/atom/ns#">conceptos</category><category domain="http://www.blogger.com/atom/ns#">evolución</category><category domain="http://www.blogger.com/atom/ns#">Farris</category><category domain="http://www.blogger.com/atom/ns#">parsimonia</category><category domain="http://www.blogger.com/atom/ns#">cladismo</category><title>Curso Introducción a la teoría y práctica de la metodología cladística</title><description>Esta información fue colocada en el Grupo Clado de Yahoo:&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;div style="text-align: justify;"&gt;
Los invitamos a participar del &lt;b&gt;Curso Introducción a la teoría y práctica de la metodología cladística&lt;/b&gt;, organizado por el PROBIOL (Programa de Posgrado en Biología), Mendoza.&lt;/div&gt;
&lt;br /&gt;
El evento tendrá lugar los días 13 al 17 de Mayo del 2013 en el &lt;a href="http://www.mendoza-conicet.gob.ar/portal/" target="_blank"&gt;CCT-CONICET Mendoza&lt;/a&gt;.&lt;br /&gt;
&lt;br /&gt;
&lt;div class="separator" style="clear: both; text-align: center;"&gt;
&lt;a href="http://www.mendoza-conicet.gob.ar/portal/sites/default/files/CONICET_MENDOZA.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="158" src="http://www.mendoza-conicet.gob.ar/portal/sites/default/files/CONICET_MENDOZA.jpg" width="200" /&gt;&lt;/a&gt;&lt;/div&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;div style="text-align: justify;"&gt;
Este curso está destinado a estudiantes avanzados de carreras de Ciencias Naturales y estudiantes de doctorado que planean utilizar la metodología Cladística en sus proyectos de tesis.&lt;/div&gt;
&lt;br /&gt;
Aquí tienen el &lt;a href="http://www.probiol.uncu.edu.ar/upload/metodologiacladistica6.pdf" target="_blank"&gt;PDF &lt;/a&gt;de el curso. &lt;br /&gt;
&lt;br /&gt;
&lt;div style="text-align: justify;"&gt;
Para mayor información contactar a &lt;a href="http://www.probiol.uncu.edu.ar/paginas/index/cursos" target="_blank"&gt;PROBIOL&lt;/a&gt;: &lt;b&gt;Informes e inscripción para los cursos:&lt;/b&gt; María Eugenia Pozzatto (&lt;a href="mailto:probiol@fca.uncu.edu.ar"&gt;probiol@fca.uncu.edu.ar&lt;/a&gt;; 0261-413-5000, int. 1123).&lt;/div&gt;
</description><link>http://cladisticaybiogeografia.blogspot.com/2013/03/curso-introduccion-la-teoria-y-practica.html</link><author>noreply@blogger.com (Jonathan Liria)</author><thr:total>0</thr:total><enclosure url="http://www.probiol.uncu.edu.ar/upload/metodologiacladistica6.pdf" length="52724" type="application/pdf" /><media:content url="http://www.probiol.uncu.edu.ar/upload/metodologiacladistica6.pdf" fileSize="52724" type="application/pdf" /><itunes:explicit>no</itunes:explicit><itunes:subtitle>Esta información fue colocada en el Grupo Clado de Yahoo: Los invitamos a participar del Curso Introducción a la teoría y práctica de la metodología cladística, organizado por el PROBIOL (Programa de Posgrado en Biología), Mendoza. El evento tendrá lugar </itunes:subtitle><itunes:author>noreply@blogger.com (Jonathan Liria)</itunes:author><itunes:summary>Esta información fue colocada en el Grupo Clado de Yahoo: Los invitamos a participar del Curso Introducción a la teoría y práctica de la metodología cladística, organizado por el PROBIOL (Programa de Posgrado en Biología), Mendoza. El evento tendrá lugar los días 13 al 17 de Mayo del 2013 en el CCT-CONICET Mendoza. Este curso está destinado a estudiantes avanzados de carreras de Ciencias Naturales y estudiantes de doctorado que planean utilizar la metodología Cladística en sus proyectos de tesis. Aquí tienen el PDF de el curso. Para mayor información contactar a PROBIOL: Informes e inscripción para los cursos: María Eugenia Pozzatto (probiol@fca.uncu.edu.ar; 0261-413-5000, int. 1123). </itunes:summary><itunes:keywords>Hennig, curso, árboles, parsimony, matrices, sistemática, TnT, filogenia, conceptos, evolución, Farris, parsimonia, cladismo</itunes:keywords></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-8253948818637709151</guid><pubDate>Sat, 16 Feb 2013 14:50:00 +0000</pubDate><atom:updated>2013-02-16T06:52:11.002-08:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">molecular</category><category domain="http://www.blogger.com/atom/ns#">alineamiento</category><category domain="http://www.blogger.com/atom/ns#">sistemática</category><category domain="http://www.blogger.com/atom/ns#">filogenia</category><category domain="http://www.blogger.com/atom/ns#">GenBank</category><category domain="http://www.blogger.com/atom/ns#">curso</category><category domain="http://www.blogger.com/atom/ns#">Conservación</category><category domain="http://www.blogger.com/atom/ns#">evolución</category><category domain="http://www.blogger.com/atom/ns#">diversidad</category><category domain="http://www.blogger.com/atom/ns#">monofilia</category><category domain="http://www.blogger.com/atom/ns#">árboles</category><title>Taller: Uso de filogenias en macroevolución</title><description>Aquí les dejo la información de un curso ofrecido por &lt;a href="http://www.transmittingscience.org/phylogeny_and_macroevolution.htm" target="_blank"&gt;Transmitting Science&lt;/a&gt;:&lt;br /&gt;
&lt;br /&gt;
&lt;b&gt;THE USE OF PHYLOGENIES IN THE STUDY OF MACROEVOLUTI&lt;/b&gt;ON&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;a href="http://www.transmittingscience.org/index_htm_files/377.png" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img alt="I Have a Phylogeny, and Now What?: Studying Macroevolution" border="0" class="xr_ap" height="143" src="http://www.transmittingscience.org/index_htm_files/377.png" style="left: 28px; top: 292px;" title="" width="400" /&gt;&lt;/a&gt;&lt;br /&gt;
&lt;br /&gt;
&amp;nbsp; &lt;br /&gt;
&lt;div style="text-align: justify;"&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
Evolution leaves its footprint in fossil and living taxa. This signal on the processes of origination of new organisms from ancestral lineages and their extinction can be recovered and depicted in phylogenetic trees. New phylogenetic methods would allow us to draw on the information encapsulated in phylogenetic trees in order to address a wide range of questions on macroevolution. First, this workshop will introduce attendees to the use, modification and representation of phylogenetic trees. Then, we will focus on the use of phylogenetic information to reconstruct ancestral characters and biogeographic histories, learning how to apply phylogenetic comparative methods. The workshop will also tackle the study of the shape of phylogenetic trees and how to estimate the rates of diversification throughout the evolutionary history of groups. Finally, we will learn how to test the phylogenetic signal of a trait of interest. Participants are encouraged to bring their data sets to use in the practical class.&lt;/div&gt;
&lt;br /&gt;
Instructor:&lt;br /&gt;
&lt;br /&gt;
Dr. Juan López-Cantalapiedra&lt;br /&gt;
(Museo Nacional de Ciencias Naturales - CSIC, Spain).&lt;br /&gt;
&lt;br /&gt;
&lt;div style="text-align: justify;"&gt;
Workshop requirements: Graduate or Postgraduate in Biology (including paleontologists no matter the degree), basic knowledge in Statistics, R and personal&amp;nbsp; computers. In case you are not familiar with the R project, an introductory course on R will be offered the week before this workshop: INTRODUCTION TO R - Second Edition. People attending the workshop THE USE OF PHYLOGENIES IN THE STUDY OF MACROEVOLUTION and the course INTRODUCTION TO R - Second Edition will have a 20% off on the last one (see "Fees" section below). Participants should bring their personal laptop (Windows, Mac, Linux) with this software installed:&lt;/div&gt;
&lt;br /&gt;
- Mesquite (free): http://mesquiteproject.org/mesquite/mesquite.html&lt;br /&gt;
- R (free): http://www.r-project.org&lt;br /&gt;
- Python Essentials for running Lagrange (free): http://www.enthought.com/products/epd_free.php&lt;br /&gt;
- FigTree, Tracer and TreeEdit (only Mac) (free): http://tree.bio.ed.ac.uk/software </description><link>http://cladisticaybiogeografia.blogspot.com/2013/02/taller-uso-de-filogenias-en.html</link><author>noreply@blogger.com (Jonathan Liria)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-489384992726903782</guid><pubDate>Tue, 22 Jan 2013 13:31:00 +0000</pubDate><atom:updated>2013-01-22T05:35:10.100-08:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">molecular</category><category domain="http://www.blogger.com/atom/ns#">sistemática</category><category domain="http://www.blogger.com/atom/ns#">biogeografía</category><category domain="http://www.blogger.com/atom/ns#">Latinoamérica</category><category domain="http://www.blogger.com/atom/ns#">filogenia</category><category domain="http://www.blogger.com/atom/ns#">secuencias</category><category domain="http://www.blogger.com/atom/ns#">GenBank</category><category domain="http://www.blogger.com/atom/ns#">Conservación</category><category domain="http://www.blogger.com/atom/ns#">evolución</category><category domain="http://www.blogger.com/atom/ns#">diversidad</category><category domain="http://www.blogger.com/atom/ns#">Suramerica</category><title>Revisión: Filogeografía en Suramérica</title><description>Un colega me envió este artículo,&lt;br /&gt;
&lt;br /&gt;
Me parece interesante y deseo compartirlo con Ustedes:&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;iframe allowfullscreen="" frameborder="0" height="511" marginheight="0" marginwidth="0" mozallowfullscreen="" scrolling="no" src="http://www.slideshare.net/slideshow/embed_code/16116608" style="border-width: 1px 1px 0; border: 1px solid #CCC; margin-bottom: 5px;" webkitallowfullscreen="" width="479"&gt; &lt;/iframe&gt; &lt;br /&gt;
&lt;div style="margin-bottom: 5px;"&gt;
&lt;b&gt; &lt;a href="http://www.slideshare.net/jliria/filogeografia-en-suramerica" target="_blank" title="Filogeografia en Suramerica"&gt;Filogeografia en Suramerica&lt;/a&gt; &lt;/b&gt; from &lt;b&gt;&lt;a href="http://www.slideshare.net/jliria" target="_blank"&gt;jliria&lt;/a&gt;&lt;/b&gt; &lt;/div&gt;
</description><link>http://cladisticaybiogeografia.blogspot.com/2013/01/revision-filogeografia-en-suramerica.html</link><author>noreply@blogger.com (Jonathan Liria)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-7128098873775318949</guid><pubDate>Thu, 17 Jan 2013 14:57:00 +0000</pubDate><atom:updated>2013-03-27T15:24:01.797-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">clase</category><category domain="http://www.blogger.com/atom/ns#">alineamiento</category><category domain="http://www.blogger.com/atom/ns#">biogeografía</category><category domain="http://www.blogger.com/atom/ns#">Latinoamérica</category><category domain="http://www.blogger.com/atom/ns#">secuencias</category><category domain="http://www.blogger.com/atom/ns#">GenBank</category><category domain="http://www.blogger.com/atom/ns#">curso</category><category domain="http://www.blogger.com/atom/ns#">evolución</category><category domain="http://www.blogger.com/atom/ns#">diversidad</category><category domain="http://www.blogger.com/atom/ns#">cladismo</category><title>Curso Técticas moleculares en sistemática</title><description>La &lt;a href="http://www.unc.edu.ar/" target="_blank"&gt;Universidad Nacional de Córdoba&lt;/a&gt; - ARGENTINA invita:&lt;br /&gt;
&lt;br /&gt;
&lt;div align="CENTER" lang="es-AR"&gt;
&lt;span style="font-size: medium;"&gt;&lt;b&gt;CURSO DE POST-GRADO&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div align="CENTER" class="western" lang="es-AR" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="CENTER" lang="es-AR" style="orphans: 0; widows: 0;"&gt;
USO DE
TECNICAS MOLECULARES EN SISTEMATICA  Y GENÉTICA DE POBLACIONES 
&lt;/div&gt;
&lt;div align="CENTER" class="western" lang="es-AR" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="CENTER" class="western" lang="es-AR" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-AR"&gt;&lt;b&gt;Unidad
Académica Organizadora&lt;/b&gt;&lt;/span&gt;&lt;span lang="es-AR"&gt;: Cátedra de
Genética de Poblaciones y Evolución y Doctorado en Ciencias
Biológicas. &lt;a href="http://www.efn.uncor.edu/index1.htm" target="_blank"&gt;Facultad de Ciencias Exactas, Físicas y Naturales&lt;/a&gt;,
Universidad Nacional de Córdoba (Res. 951-T-2012).&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" lang="es-AR" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;h1 class="western" lang="es-ES"&gt;
&lt;span lang="es-AR" style="font-size: small;"&gt;Modalidad:
&lt;/span&gt;&lt;span lang="es-AR" style="font-size: small;"&gt;&lt;b&gt;Teórico-práctico&lt;/b&gt;&lt;/span&gt;&lt;/h1&gt;
&lt;h1 class="western" lang="es-ES"&gt;
&lt;span lang="es-AR" style="font-size: small;"&gt;Duración:&lt;/span&gt;&lt;span lang="es-AR" style="font-size: small;"&gt;&lt;b&gt;
45&lt;/b&gt;&lt;/span&gt;&lt;span lang="es-AR" style="font-size: small;"&gt;&lt;b&gt; hs. &lt;/b&gt;&lt;/span&gt;&lt;span lang="es-AR" style="font-size: small;"&gt;(40
presenciales, 5 no-presenciales).&lt;/span&gt;&lt;/h1&gt;
&lt;div align="LEFT" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-AR"&gt;Fecha
de realización:&lt;/span&gt;&lt;span lang="es-AR"&gt;&lt;b&gt; 11 al 15 de marzo de
2013.&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div align="LEFT" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-AR"&gt;Lugar:
&lt;/span&gt;&lt;span lang="es-AR"&gt;&lt;b&gt;Facultad de Ciencias Exactas, Av. Vélez
Sarsfield 299. Córdoba.&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div align="LEFT" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-AR"&gt;Destinatarios:
&lt;/span&gt;&lt;span lang="es-AR"&gt;&lt;b&gt;alumnos del doctorado en Ciencias
Biológicas, egresados de la carrera de&lt;/b&gt;&lt;/span&gt;&lt;span lang="es-AR"&gt;
&lt;/span&gt;&lt;span lang="es-AR"&gt;&lt;b&gt;Biología y carreras afines (Cs.
Agropecuarias, Lic. en Genética, etc.)&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div align="LEFT" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-AR"&gt;Responsable
académico y administrador de los fondos: &lt;/span&gt;&lt;span lang="es-AR"&gt;&lt;b&gt;C.
N. Gardenal&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
&lt;h2 class="western" lang="es-AR"&gt;
&lt;span style="font-size: small;"&gt;&lt;b&gt;Cupo: 12 alumnos. En lo posible,
traer notebook para llevar a cabo la parte de uso de programas de
análisis de datos.&lt;/b&gt;&lt;/span&gt;&lt;/h2&gt;
&lt;div align="LEFT" class="western" lang="es-AR" style="orphans: 0; widows: 0;"&gt;
&lt;span style="font-size: small;"&gt;&lt;br /&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div align="LEFT" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-AR"&gt;Arancel:
&lt;/span&gt;&lt;span lang="es-AR"&gt;&lt;b&gt;$ 700. Alumnos inscriptos en el
Doctorado en Ciencias Biológicas de la Universidad Nacional de
Córdoba,  $ 560.&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div align="LEFT" class="western" lang="es-AR" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;&lt;u&gt;Docentes
participantes&lt;/u&gt;&lt;/span&gt;&lt;span lang="es-ES"&gt;: Dres. C. Noemí
Gardenal, Marina Chiappero, Beatriz García, Raúl González Ittig,
Paula Rivera y Alicia R. Pérez.&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" lang="es-ES" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" lang="es-ES" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" lang="es-ES" style="orphans: 0; widows: 0;"&gt;
OBJETIVOS&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" lang="es-ES" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;1.&lt;/span&gt;&lt;span lang="es-ES"&gt;
Conocer los principios, aplicaciones y limitaciones de las técnicas
moleculares en Sistemática y en Genética de Poblaciones.&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;2.
Conocer criterios que permitan seleccionar los marcadores más
adecuados para resolver problemas taxonómicos a diferentes niveles
(intra e inter-específico, a nivel de género y taxones superiores).&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;3.
Recibir entrenamiento en la utilización de nuevas herramientas para
el análisis de la biodiversidad, teniendo en cuenta la historia
evolutiva de poblaciones y de especies.&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;4.
Comprender el uso de diferentes programas de computación
corrientemente utilizados para el análisis de datos.&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" lang="es-ES" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" lang="es-ES" style="orphans: 0; widows: 0;"&gt;
PROGRAMA&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" lang="es-ES" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;1.&lt;/span&gt;&lt;span lang="es-ES"&gt;
Toma y conservación de muestras para la aplicación de diferentes
técnicas. Manejo del laboratorio de Biología Molecular. Preparación
y esterilizado de material. Práctica de pipeteo con micropipetas
automáticas.&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;2.
Fundamento de los métodos de extracción de ADN. Aislamiento de ADN
de tejidos animales y vegetales. &lt;/span&gt;
&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;3.
Conceptos teóricos sobre la amplificación de segmentos de ADN
mediante la reacción en cadena de la polimerasa (PCR).&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;4.
Amplificación por PCR utilizando cebadores específicos: a)
amplificación del gen citocromo b del ADN mitocondrial de especies
del género &lt;/span&gt;&lt;span lang="es-ES"&gt;&lt;i&gt;Oligoryzomys&lt;/i&gt;&lt;/span&gt;&lt;span lang="es-ES"&gt;
(Rodentia: Sigmodontinae); b) amplificación de loci microsatélites
(genoma nuclear) de especies de &lt;/span&gt;&lt;span lang="es-ES"&gt;&lt;i&gt;Calomys
&lt;/i&gt;&lt;/span&gt;&lt;span lang="es-ES"&gt;(Rodentia: Sigmodontinae).&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;5.
Conceptos teóricos sobre la amplificación por PCR utilizando
cebadores arbitrarios: ISSR  y AFLP. Amplificación de fragmentos
ISSR en &lt;/span&gt;&lt;span lang="es-ES"&gt;&lt;i&gt;Myrcianthes cisplatensis&lt;/i&gt;&lt;/span&gt;&lt;span lang="es-ES"&gt;
(mato).&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;6.
&lt;/span&gt;&lt;span lang="es-ES"&gt;Polimorfismo de longitud de fragmentos de
restricción (RFLP): conceptos teóricos y análisis de geles.
Digestión del gen cit b de varias especies de roedores sigmodontinos
con enzimas de restricción.&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;7.
Secuenciamiento. Alineación de secuencias.&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;8.
Métodos de análisis. Tratamiento de los distintos tipos de datos.
Construcción de matrices. Uso de programas como PAUP, Mr Bayes,
jModeltest, Arlequin, Genalex y Structure.&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" lang="es-ES" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" lang="es-ES" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
BIBLIOGRAFIA
BASICA&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;ol&gt;
&lt;li&gt;&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
Avise
 J C. 2004. Molecular markers, Natural History and Evolution. Chapman
 &amp;amp; Hall, New York.&lt;/div&gt;
&lt;/li&gt;
&lt;li&gt;&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;De
 Salle, R., Giribert, G. y Wheeler, W. 2002. &lt;/span&gt;Techniques in
 Molecular Systematics and Evolution. Birkhäuser, Basilea.&lt;/div&gt;
&lt;/li&gt;
&lt;li&gt;&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
Hillis
 D M, C. Moritz, B K Mable. 1996. Molecular Systematics. Sinauer
 Ass., Inc. Sunderland, Massachusetts.&lt;/div&gt;
&lt;/li&gt;
&lt;li&gt;&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
Freeland,
 J R. 2011, S D Petersen y H Kirk. 2011. Molecular Ecology.
 Wiley-Blackwell.&lt;/div&gt;
&lt;/li&gt;
&lt;li&gt;&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
Wiley
 E. O. y B S Lieberman. 2011. Phylogenetics: Theory and Practice of
 Phylogenetic Systematics. Wiley-Blackwell. 
 &lt;/div&gt;
&lt;/li&gt;
&lt;li&gt;&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
Yang
 Z. 2006. Computational Molecular Evolution. Oxford Series in Ecology
 and Evolution, Oxford.&lt;/div&gt;
&lt;/li&gt;
&lt;li&gt;&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
Hoelzel,
 A R. 1992. Molecular Genetic Analysis of Populations. A practical
 approach. IRL Press. Oxford.&lt;/div&gt;
&lt;/li&gt;
&lt;/ol&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="LEFT" class="western" lang="es-ES" style="orphans: 2; widows: 2;"&gt;
Trabajos en publicaciones periódicas empleados para Seminarios
durante el curso: se actualizan anualmente.&lt;/div&gt;
&lt;div align="LEFT" class="western" lang="es-ES" style="orphans: 2; widows: 2;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="LEFT" class="western" lang="es-ES" style="orphans: 2; widows: 2;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;&lt;u&gt;Evaluación
final&lt;/u&gt;&lt;/span&gt;&lt;span lang="es-ES"&gt;: &lt;/span&gt;&lt;span lang="es-ES"&gt;&lt;b&gt;escrita&lt;/b&gt;&lt;/span&gt;&lt;span lang="es-ES"&gt;,
a cargo de C.N. Gardenal, R. González Ittig y M. Chiappero.&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" lang="es-ES" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" lang="es-ES" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;&lt;b&gt;Informes
&lt;/b&gt;&lt;/span&gt;&lt;span lang="es-ES"&gt;&lt;b&gt;y pre-inscripciones:&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;&lt;b&gt;vía
e-mail &lt;/b&gt;&lt;/span&gt;&lt;span lang="es-ES"&gt;&lt;b&gt;entre el 1º de febrero hasta
el 1º de marzo de  2013&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;&lt;b&gt;marina.chiappero@gmail.com&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" lang="es-ES" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" lang="es-ES" style="orphans: 0; widows: 0;"&gt;
&lt;b&gt;Requisitos para la pre-inscripción:&lt;/b&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;&lt;b&gt;-
&lt;/b&gt;&lt;/span&gt;&lt;span lang="es-ES"&gt;Curriculum Vitae de&lt;/span&gt;&lt;span lang="es-ES"&gt;&lt;b&gt;
&lt;/b&gt;&lt;/span&gt;&lt;span lang="es-ES"&gt;&lt;u&gt;&lt;b&gt;no más de 5 páginas, &lt;/b&gt;&lt;/u&gt;&lt;/span&gt;
&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;&lt;b&gt;-
&lt;/b&gt;&lt;/span&gt;&lt;span lang="es-ES"&gt;Carta de presentación explicando las
motivaciones que lo llevan a realizar el curso.&lt;/span&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" lang="es-ES" style="orphans: 0; widows: 0;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" class="western" style="orphans: 0; widows: 0;"&gt;
&lt;span lang="es-ES"&gt;Los
alumnos que queden finalmente inscriptos recibirán la comu&lt;/span&gt;&lt;span lang="es-ES"&gt;nicación
a más tardar el lunes 4 de marzo de 2012.&lt;/span&gt;&lt;/div&gt;
</description><link>http://cladisticaybiogeografia.blogspot.com/2013/01/curso-tecticas-moleculares-en.html</link><author>noreply@blogger.com (Jonathan Liria)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-4826935206018419660</guid><pubDate>Thu, 15 Nov 2012 12:11:00 +0000</pubDate><atom:updated>2012-11-15T04:11:37.418-08:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">clase</category><category domain="http://www.blogger.com/atom/ns#">NDM</category><category domain="http://www.blogger.com/atom/ns#">biogeografía</category><category domain="http://www.blogger.com/atom/ns#">programas</category><category domain="http://www.blogger.com/atom/ns#">SIG</category><category domain="http://www.blogger.com/atom/ns#">datos</category><category domain="http://www.blogger.com/atom/ns#">Suramerica</category><category domain="http://www.blogger.com/atom/ns#">Venezuela</category><category domain="http://www.blogger.com/atom/ns#">endemismo</category><category domain="http://www.blogger.com/atom/ns#">Distribución</category><category domain="http://www.blogger.com/atom/ns#">geoespacial</category><category domain="http://www.blogger.com/atom/ns#">tutorial</category><category domain="http://www.blogger.com/atom/ns#">mapas</category><title>NDM ahora exporta a DIVA GIS</title><description>&lt;div class="separator" style="clear: both; text-align: center;"&gt;
&lt;a href="http://2.bp.blogspot.com/-GlG4gO9pnqI/UKTXdkJO8QI/AAAAAAAAAR4/ABV7ilCYy0c/s1600/fig0.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="240" src="http://2.bp.blogspot.com/-GlG4gO9pnqI/UKTXdkJO8QI/AAAAAAAAAR4/ABV7ilCYy0c/s320/fig0.jpg" width="320" /&gt;&lt;/a&gt;&lt;/div&gt;
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&lt;br /&gt;&lt;/div&gt;
&lt;div style="margin-bottom: 0cm; text-align: justify;"&gt;
En esta entrada les traigo buenas
noticias: La última versión de NDM (&lt;a href="http://www.zmuc.dk/public/phylogeny/endemism/VNDM-NDM_Nov_2012.zip" target="_blank"&gt;noviembre 2012&lt;/a&gt;) puede exportar
las áreas y especies endémicas a el programa &lt;a href="http://www.diva-gis.org/" target="_blank"&gt;DIVA-GIS&lt;/a&gt;. Luego estos
archivos son fácilmente transformados (vía DIVA GIS) al formato
&lt;a href="http://es.wikipedia.org/wiki/Shapefile" target="_blank"&gt;shapefile&lt;/a&gt;. Anteriormente se requería el programa &lt;a href="http://www.bluemarblegeo.com/products/global-mapper.php" target="_blank"&gt;GLOBALMAPPER&lt;/a&gt; para
pasar las áreas, desde el formato acf (&lt;a href="http://www.zmuc.dk/public/phylogeny/endemism/Manual_VNDM.pdf" target="_blank"&gt;Area Coordinate file&lt;/a&gt;) a el
formato shp (shapefile).&lt;/div&gt;
&lt;div&gt;
&lt;/div&gt;
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&lt;/div&gt;
&lt;div style="margin-bottom: 0cm; text-align: justify;"&gt;
Acá les dejo un pequeño tutorial de
como realizar este procedimiento. Pero antes actualicen su versión
de NDM y descarguen la última versión de DIVA GIS; en este
paso-a-paso fue utilizado &lt;a href="http://www.diva-gis.org/soft/diva75.zip" target="_blank"&gt;DIVA GIS ver. 7.5&lt;/a&gt;.&lt;/div&gt;
&lt;div style="text-align: justify;"&gt;
&lt;/div&gt;
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&lt;br /&gt;
&lt;/div&gt;
&lt;div style="text-align: justify;"&gt;
&lt;/div&gt;
&lt;div style="margin-bottom: 0cm; text-align: justify;"&gt;
Muy bien, empecemos!&lt;/div&gt;
&lt;div style="text-align: justify;"&gt;
&lt;/div&gt;
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&lt;/div&gt;
&lt;div style="text-align: justify;"&gt;
&lt;/div&gt;
&lt;div style="margin-bottom: 0cm; text-align: justify;"&gt;
Lo primero es abrir un conjunto de
datos, en este caso estos son los datos liecoy.xyd (datos en formato
XYdata) para un grupo hipotético de organismos. 
&lt;/div&gt;
&lt;div style="text-align: justify;"&gt;
&lt;/div&gt;
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&lt;div class="separator" style="clear: both; text-align: center;"&gt;
&lt;a href="http://3.bp.blogspot.com/-1ldCd0ofg3g/UKTYDm00JBI/AAAAAAAAASA/NtwJoZM8Ac4/s1600/fig1.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="225" src="http://3.bp.blogspot.com/-1ldCd0ofg3g/UKTYDm00JBI/AAAAAAAAASA/NtwJoZM8Ac4/s400/fig1.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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&amp;nbsp; &lt;/div&gt;
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&lt;div style="margin-bottom: 0cm; text-align: justify;"&gt;
Fíjense que agregué el comando
“ynegative” para invertir los datos; esto es opcional, pues lo
importante es mostrar como pasar las áreas a formato shapefile.  
&lt;/div&gt;
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&lt;/div&gt;
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&lt;/div&gt;
&lt;div style="text-align: justify;"&gt;
&lt;/div&gt;
&lt;div style="margin-bottom: 0cm; text-align: justify;"&gt;
Ejecutamos NDM y abrimos el archivo
“liecoy.xyd”&lt;/div&gt;
&lt;div style="text-align: justify;"&gt;
&lt;/div&gt;
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&lt;a href="http://1.bp.blogspot.com/-lu3YDBTh4aE/UKTYQrEXq2I/AAAAAAAAASI/xR2515L02pg/s1600/fig2.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="225" src="http://1.bp.blogspot.com/-lu3YDBTh4aE/UKTYQrEXq2I/AAAAAAAAASI/xR2515L02pg/s400/fig2.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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Luego indicamos que deseamos crear una
nueva matriz de datos (cuadriculas o grillas).&lt;/div&gt;
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&lt;/div&gt;
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&lt;a href="http://1.bp.blogspot.com/-Tnwxt-53vG4/UKTYpOfJAfI/AAAAAAAAASQ/tRpfXmGEgCU/s1600/fig3.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="225" src="http://1.bp.blogspot.com/-Tnwxt-53vG4/UKTYpOfJAfI/AAAAAAAAASQ/tRpfXmGEgCU/s400/fig3.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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Realizamos una búsqueda de áreas
endémicas con los parámetros deseados.&lt;/div&gt;
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&lt;/div&gt;
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&lt;a href="http://3.bp.blogspot.com/-T4pyzy73ip0/UKTY37dR8bI/AAAAAAAAASY/3wq8jlnsZQM/s1600/fig4.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="225" src="http://3.bp.blogspot.com/-T4pyzy73ip0/UKTY37dR8bI/AAAAAAAAASY/3wq8jlnsZQM/s400/fig4.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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Seleccionamos una área, en este caso
la primera de las siete encontradas. Y con el comando “v” podemos
mirar las especies endémicas de esa área y la contribución de cada
especie a el score o índice de endemicidad.&lt;/div&gt;
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&lt;a href="http://1.bp.blogspot.com/-qQm7og7DyJ8/UKTZBhR62zI/AAAAAAAAASg/n4TJ9fVxrkM/s1600/fig5.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="225" src="http://1.bp.blogspot.com/-qQm7og7DyJ8/UKTZBhR62zI/AAAAAAAAASg/n4TJ9fVxrkM/s400/fig5.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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Seleccionamos la opción de el menú:
File--&amp;gt;Save coordinates for GIS--&amp;gt;Save for DIVAGIS&lt;/div&gt;
&lt;div style="text-align: justify;"&gt;
&lt;/div&gt;
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&lt;a href="http://1.bp.blogspot.com/--gLltUO18eE/UKTZMfyxlWI/AAAAAAAAASo/i2GLtauRaFw/s1600/fig6.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="225" src="http://1.bp.blogspot.com/--gLltUO18eE/UKTZMfyxlWI/AAAAAAAAASo/i2GLtauRaFw/s400/fig6.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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Durante este proceso se generarán dos
archivos: Uno conteniendo la información de las cuadriculas o
grillas, y el segundo con las especies contenidas en estas.&lt;/div&gt;
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&lt;a href="http://2.bp.blogspot.com/-6kwdFDkpctI/UKTZTOUZM_I/AAAAAAAAASw/VTAanUf0Coo/s1600/fig7.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="225" src="http://2.bp.blogspot.com/-6kwdFDkpctI/UKTZTOUZM_I/AAAAAAAAASw/VTAanUf0Coo/s400/fig7.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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Para que tengan una idea, les muestro
la página de el &lt;a href="http://www.diva-gis.org/docs/DIVA-GIS_manual_7.pdf" target="_blank"&gt;manual de DIVA GIS&lt;/a&gt; donde aparece el formato de los
archivos de texto (.TXT) para polígonos.&lt;/div&gt;
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&lt;a href="http://1.bp.blogspot.com/-j0iLnLY5V5g/UKTZbjU93_I/AAAAAAAAAS4/L6P8sXybSow/s1600/fig8.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="225" src="http://1.bp.blogspot.com/-j0iLnLY5V5g/UKTZbjU93_I/AAAAAAAAAS4/L6P8sXybSow/s400/fig8.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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Ejecutamos DIVA GIS, y seleccionamos la
opción de el menú: Data--&amp;gt;Text to Line or Polygon Shapefile.
Luego elegimos el archivo de entrada (el que contiene la información
de las áreas) y el nombre de el archivo de salida (shapefile).&lt;/div&gt;
&lt;div style="text-align: justify;"&gt;
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&lt;br /&gt;&lt;/div&gt;
&lt;div class="separator" style="clear: both; text-align: center;"&gt;
&lt;a href="http://4.bp.blogspot.com/-Clm5yRZN4qk/UKTZvO4VAjI/AAAAAAAAATA/cNm6zXNAeyU/s1600/fig9.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="225" src="http://4.bp.blogspot.com/-Clm5yRZN4qk/UKTZvO4VAjI/AAAAAAAAATA/cNm6zXNAeyU/s400/fig9.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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Finalmente el archivo con las especies
endémicas, lo importamos con la opción de el menú: Data--&amp;gt;Import
Points to Shapefile--&amp;gt;From text file (.TXT). Luego elegimos el
archivo de entrada (el que contiene la información de las esepcies)
y el nombre de el archivo de salida (shapefile). 
&lt;/div&gt;
&lt;div style="text-align: justify;"&gt;
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La última figura muestra todos los
pasos pero con un conjunto de datos de Venezuela. En este caso es una
matriz con la distribución de 1292 especies (Invertebrados y
Vertebrados); este análisis fue &lt;a href="http://cladisticaybiogeografia.blogspot.com/2012/05/areas-de-endemismo-de-venezuela.html" target="_blank"&gt;mostrado en otra entrada&lt;/a&gt;.&lt;/div&gt;
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&lt;a href="http://4.bp.blogspot.com/-BIY34ptlRTE/UKTaIOLl1DI/AAAAAAAAATQ/fJxhqojS09M/s1600/fig11.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="225" src="http://4.bp.blogspot.com/-BIY34ptlRTE/UKTaIOLl1DI/AAAAAAAAATQ/fJxhqojS09M/s400/fig11.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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</description><link>http://cladisticaybiogeografia.blogspot.com/2012/11/ndm-ahora-exporta-diva-gis.html</link><author>noreply@blogger.com (Jonathan Liria)</author><media:thumbnail url="http://2.bp.blogspot.com/-GlG4gO9pnqI/UKTXdkJO8QI/AAAAAAAAAR4/ABV7ilCYy0c/s72-c/fig0.jpg" height="72" width="72" /><thr:total>4</thr:total><enclosure url="http://www.zmuc.dk/public/phylogeny/endemism/VNDM-NDM_Nov_2012.zip" length="352624" type="application/x-zip-compressed" /><media:content url="http://www.zmuc.dk/public/phylogeny/endemism/VNDM-NDM_Nov_2012.zip" fileSize="352624" type="application/x-zip-compressed" /><itunes:explicit>no</itunes:explicit><itunes:subtitle> En esta entrada les traigo buenas noticias: La última versión de NDM (noviembre 2012) puede exportar las áreas y especies endémicas a el programa DIVA-GIS. Luego estos archivos son fácilmente transformados (vía DIVA GIS) al formato shapefile. Anteriormen</itunes:subtitle><itunes:author>noreply@blogger.com (Jonathan Liria)</itunes:author><itunes:summary> En esta entrada les traigo buenas noticias: La última versión de NDM (noviembre 2012) puede exportar las áreas y especies endémicas a el programa DIVA-GIS. Luego estos archivos son fácilmente transformados (vía DIVA GIS) al formato shapefile. Anteriormente se requería el programa GLOBALMAPPER para pasar las áreas, desde el formato acf (Area Coordinate file) a el formato shp (shapefile). Acá les dejo un pequeño tutorial de como realizar este procedimiento. Pero antes actualicen su versión de NDM y descarguen la última versión de DIVA GIS; en este paso-a-paso fue utilizado DIVA GIS ver. 7.5. Muy bien, empecemos! Lo primero es abrir un conjunto de datos, en este caso estos son los datos liecoy.xyd (datos en formato XYdata) para un grupo hipotético de organismos. &amp;nbsp; Fíjense que agregué el comando “ynegative” para invertir los datos; esto es opcional, pues lo importante es mostrar como pasar las áreas a formato shapefile. Ejecutamos NDM y abrimos el archivo “liecoy.xyd” Luego indicamos que deseamos crear una nueva matriz de datos (cuadriculas o grillas). Realizamos una búsqueda de áreas endémicas con los parámetros deseados. Seleccionamos una área, en este caso la primera de las siete encontradas. Y con el comando “v” podemos mirar las especies endémicas de esa área y la contribución de cada especie a el score o índice de endemicidad. Seleccionamos la opción de el menú: File--&amp;gt;Save coordinates for GIS--&amp;gt;Save for DIVAGIS Durante este proceso se generarán dos archivos: Uno conteniendo la información de las cuadriculas o grillas, y el segundo con las especies contenidas en estas. Para que tengan una idea, les muestro la página de el manual de DIVA GIS donde aparece el formato de los archivos de texto (.TXT) para polígonos. Ejecutamos DIVA GIS, y seleccionamos la opción de el menú: Data--&amp;gt;Text to Line or Polygon Shapefile. Luego elegimos el archivo de entrada (el que contiene la información de las áreas) y el nombre de el archivo de salida (shapefile). Finalmente el archivo con las especies endémicas, lo importamos con la opción de el menú: Data--&amp;gt;Import Points to Shapefile--&amp;gt;From text file (.TXT). Luego elegimos el archivo de entrada (el que contiene la información de las esepcies) y el nombre de el archivo de salida (shapefile). La última figura muestra todos los pasos pero con un conjunto de datos de Venezuela. En este caso es una matriz con la distribución de 1292 especies (Invertebrados y Vertebrados); este análisis fue mostrado en otra entrada. </itunes:summary><itunes:keywords>clase, NDM, biogeografía, programas, SIG, datos, Suramerica, Venezuela, endemismo, Distribución, geoespacial, tutorial, mapas</itunes:keywords></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-2560837306816642865</guid><pubDate>Wed, 07 Nov 2012 12:58:00 +0000</pubDate><atom:updated>2012-11-07T05:08:24.318-08:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">Andrés Bello</category><category domain="http://www.blogger.com/atom/ns#">Chile</category><category domain="http://www.blogger.com/atom/ns#">Darwin</category><category domain="http://www.blogger.com/atom/ns#">evolución</category><category domain="http://www.blogger.com/atom/ns#">Suramerica</category><category domain="http://www.blogger.com/atom/ns#">Biografía</category><title>Andrés Bello y Charles Darwin</title><description>&lt;div style="text-align: justify;"&gt;
Buscando en distintas revistas de divulgación científica, encontré este artículo de &lt;a href="http://www.ciencia.cl/CienciaAlDia/volumen5/numero2/index.shtml" target="_blank"&gt;CIENCIA AL DÍA&lt;/a&gt;, que me gustaria compartir con Ustedes (les coloco el resumen y link para que lo consulten directamente en la página):&lt;/div&gt;
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&lt;a href="http://www.ciencia.cl/CienciaAlDia/volumen1/numero1/articulos/articulo3.html" target="_blank"&gt;&lt;b&gt;Andrés Bello y la Visita de Charles Darwin a Chile&lt;/b&gt;&lt;/a&gt;&lt;/div&gt;
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Por:&amp;nbsp;&lt;/div&gt;
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&lt;span style="font-family: Times New Roman, serif;"&gt;&lt;span style="font-size: small;"&gt;Juan
Bacigalupo &amp;amp; David Yudilevich&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
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&lt;a href="http://www.ciencia.cl/CienciaAlDia/volumen1/numero1/articulos/juan/fig1.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="208" src="http://www.ciencia.cl/CienciaAlDia/volumen1/numero1/articulos/juan/fig1.jpg" width="320" /&gt;&lt;/a&gt;&lt;/div&gt;
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(A la izquierda A. Bello, y a la derecha C. Darwin)&lt;/div&gt;
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El insigne naturalista
inglés Charles Darwin pasó una parte importante de su viaje
alrededor del mundo (1831-1836) recorriendo tierras chilenas. Las
experiencias recogidas y las extensas observaciones que efectuó
durante esa etapa de su periplo a bordo del bergantín HMS Beagle
fueron fundamentales para las ideas que posteriormente Darwin
desarrollara acerca de la evolución de los seres vivos. En aquellos
años quizás la personalidad más influyente en el ambiente
intelectual chileno era el ilustre sabio venezolano Andrés Bello,
radicado en Santiago unos años antes. Bello seguía muy atentamente
los progresos científicos contemporáneos y en 1839 y 40 publicó en
el periódico El Araucano extractos del libro en el que Darwin y
Fitz-Roy relatan su reciente viaje. Bello se interesó en la
descripción que hace Darwin de Tierra del Fuego y la Patagonia,
refiriéndose a sus habitantes, flora, fauna y geología, y además
de la del violento terremoto de Concepción de 1835, de cuyos efectos
Darwin fue testigo. La repercusión de estos artículos en los
círculos políticos e intelectuales y la percepción de su
importancia por parte de Bello pudo haber influido en el subsecuente
establecimiento de la primera base militar chilena en el Estrecho de
Magallanes. Finalmente cavilamos sobre un posible encuentro de ambos
hombres en Santiago. &lt;i&gt;Ciencia al Día, 1998. 1(1):1-11.&lt;/i&gt;&lt;/div&gt;
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&lt;a href="http://www.ciencia.cl/CienciaAlDia/volumen1/numero1/articulos/articulo3.pdf" target="_blank"&gt;&lt;b&gt;Texto Completo&lt;/b&gt;&lt;/a&gt;&lt;/div&gt;
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Dale un vistazo a la portada de el periódico EL ARAUCANO:&lt;br /&gt;
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&lt;a href="http://www.memoriachilena.cl/archivos2/thumb750/MC0016189.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="400" src="http://www.memoriachilena.cl/archivos2/thumb750/MC0016189.jpg" width="257" /&gt;&lt;/a&gt;&lt;/div&gt;
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¿Sabes quien fue Andrés Bello?&amp;nbsp;&lt;/div&gt;
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&lt;i&gt;&lt;b&gt;Andrés Bello, el ilustre
americano&lt;/b&gt;&lt;/i&gt;&lt;/div&gt;
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Andrés Bello, nació en
Caracas, el 29 de noviembre de  1781 y murió en Santiago de Chile,
un 15 de octubre de 1865. Filósofo, poeta, traductor, filólogo,
ensayista, educador - fue maestro del Libertador Simón Bolívar;
político y jurista venezolano-chileno, es uno de los humanistas más
importantes que alguna vez la tierra americana viera.&lt;/div&gt;
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Vivió en Caracas hasta
1810, cuando Integró la primera misión diplomática del joven
gobierno revolucionario de Caracas, en la que junto a  Luis López
Méndez y Simón Bolívar partiera hacia Londres con la finalidad de
establecer contacto con el gobierno inglés para lograr su apoyo en
la lucha independentista en contra del imperio de España. Desde ese entonces
residiría en Londres  hasta 1829 cuando  viajó a Chile y fue
contratado por el gobierno de ese hermano país suramericano. Andrés
Bello desarrolló grandes obras en el campo del derecho y las
humanidades, convirtiéndose en uno de los héroes de la patria
chilena, cuya ciudadanía le fue otorgada  en reconocimiento a su
mérito humanístico en 1832. Andrés Bello fue un
hombre de pensamiento revolucionario, que participó en el proceso de
independencia de Venezuela, en la formación de la República de
Chile con un aporte fundamental para el perfil jurídico y cultural
de las repúblicas que nacían después de la derrota de España.
Padre del Americanismo desarrolló una obra poética en la que exaltó
la naturaleza y los elementos culturales de un “nuevo mundo” que
emergía con características propias. Desempeñó cargos como
senador y profesor; redactó del Código Civil, una de las obras
jurídicas americanas más novedosas e influyentes de su época.
Fundador y primer Rector de la Universidad de Chile. Autor de la
Gramática del idioma castellano (Gramática de la lengua castellana
destinada al uso de los americanos y los esclavos españoles), los
Principios del derecho de gentes, la poesía Silva a la agricultura
de la zona tórrida y el Resumen de la Historia de Venezuela.&lt;/div&gt;
</description><link>http://cladisticaybiogeografia.blogspot.com/2012/11/andres-bello-y-charles-darwin.html</link><author>noreply@blogger.com (Jonathan Liria)</author><thr:total>0</thr:total><enclosure url="http://www.ciencia.cl/CienciaAlDia/volumen1/numero1/articulos/articulo3.pdf" length="1347917" type="application/pdf" /><media:content url="http://www.ciencia.cl/CienciaAlDia/volumen1/numero1/articulos/articulo3.pdf" fileSize="1347917" type="application/pdf" /><itunes:explicit>no</itunes:explicit><itunes:subtitle> Buscando en distintas revistas de divulgación científica, encontré este artículo de CIENCIA AL DÍA, que me gustaria compartir con Ustedes (les coloco el resumen y link para que lo consulten directamente en la página): Andrés Bello y la Visita de Charles </itunes:subtitle><itunes:author>noreply@blogger.com (Jonathan Liria)</itunes:author><itunes:summary> Buscando en distintas revistas de divulgación científica, encontré este artículo de CIENCIA AL DÍA, que me gustaria compartir con Ustedes (les coloco el resumen y link para que lo consulten directamente en la página): Andrés Bello y la Visita de Charles Darwin a Chile Por:&amp;nbsp; Juan Bacigalupo &amp;amp; David Yudilevich (A la izquierda A. Bello, y a la derecha C. Darwin) El insigne naturalista inglés Charles Darwin pasó una parte importante de su viaje alrededor del mundo (1831-1836) recorriendo tierras chilenas. Las experiencias recogidas y las extensas observaciones que efectuó durante esa etapa de su periplo a bordo del bergantín HMS Beagle fueron fundamentales para las ideas que posteriormente Darwin desarrollara acerca de la evolución de los seres vivos. En aquellos años quizás la personalidad más influyente en el ambiente intelectual chileno era el ilustre sabio venezolano Andrés Bello, radicado en Santiago unos años antes. Bello seguía muy atentamente los progresos científicos contemporáneos y en 1839 y 40 publicó en el periódico El Araucano extractos del libro en el que Darwin y Fitz-Roy relatan su reciente viaje. Bello se interesó en la descripción que hace Darwin de Tierra del Fuego y la Patagonia, refiriéndose a sus habitantes, flora, fauna y geología, y además de la del violento terremoto de Concepción de 1835, de cuyos efectos Darwin fue testigo. La repercusión de estos artículos en los círculos políticos e intelectuales y la percepción de su importancia por parte de Bello pudo haber influido en el subsecuente establecimiento de la primera base militar chilena en el Estrecho de Magallanes. Finalmente cavilamos sobre un posible encuentro de ambos hombres en Santiago. Ciencia al Día, 1998. 1(1):1-11. Texto Completo Dale un vistazo a la portada de el periódico EL ARAUCANO: ¿Sabes quien fue Andrés Bello?&amp;nbsp; Andrés Bello, el ilustre americano Andrés Bello, nació en Caracas, el 29 de noviembre de 1781 y murió en Santiago de Chile, un 15 de octubre de 1865. Filósofo, poeta, traductor, filólogo, ensayista, educador - fue maestro del Libertador Simón Bolívar; político y jurista venezolano-chileno, es uno de los humanistas más importantes que alguna vez la tierra americana viera. Vivió en Caracas hasta 1810, cuando Integró la primera misión diplomática del joven gobierno revolucionario de Caracas, en la que junto a Luis López Méndez y Simón Bolívar partiera hacia Londres con la finalidad de establecer contacto con el gobierno inglés para lograr su apoyo en la lucha independentista en contra del imperio de España. Desde ese entonces residiría en Londres hasta 1829 cuando viajó a Chile y fue contratado por el gobierno de ese hermano país suramericano. Andrés Bello desarrolló grandes obras en el campo del derecho y las humanidades, convirtiéndose en uno de los héroes de la patria chilena, cuya ciudadanía le fue otorgada en reconocimiento a su mérito humanístico en 1832. Andrés Bello fue un hombre de pensamiento revolucionario, que participó en el proceso de independencia de Venezuela, en la formación de la República de Chile con un aporte fundamental para el perfil jurídico y cultural de las repúblicas que nacían después de la derrota de España. Padre del Americanismo desarrolló una obra poética en la que exaltó la naturaleza y los elementos culturales de un “nuevo mundo” que emergía con características propias. Desempeñó cargos como senador y profesor; redactó del Código Civil, una de las obras jurídicas americanas más novedosas e influyentes de su época. Fundador y primer Rector de la Universidad de Chile. Autor de la Gramática del idioma castellano (Gramática de la lengua castellana destinada al uso de los americanos y los esclavos españoles), los Principios del derecho de gentes, la poesía Silva a la agricultura de la zona tórrida y el Resumen de la Historia de Venezuela. </itunes:summary><itunes:keywords>Andrés Bello, Chile, Darwin, evolución, Suramerica, Biografía</itunes:keywords></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-618469700148111605</guid><pubDate>Fri, 02 Nov 2012 14:19:00 +0000</pubDate><atom:updated>2012-11-02T07:20:44.008-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">Latinoamérica</category><category domain="http://www.blogger.com/atom/ns#">landmarks</category><category domain="http://www.blogger.com/atom/ns#">méxico</category><category domain="http://www.blogger.com/atom/ns#">curso</category><category domain="http://www.blogger.com/atom/ns#">morfometría</category><title>Curso: Introducción a la Morfometría Geométrica - México</title><description>En esta entrada les traigo información de el Curso (tomado de http://www.filogenetica.org/cursos/Morfometria/):&lt;br /&gt;
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&lt;div class="separator" style="clear: both; text-align: center;"&gt;
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&lt;div style="text-align: justify;"&gt;
&lt;span style="font-size: small;"&gt;&lt;b&gt;Presentación:&lt;/b&gt; Este curso esta dirigido a estudiantes de posgrado, pero tambien se
invita a estudiantes de licenciatura, profesores e
investigadores. El curso contendrá tanto elementos de teoría
(justificaciones teóricas, y argumentos metodológicos) como prácticas
en el uso de programas de computadora para análisis morfométricos,
análisis de matrices de deformación y&amp;nbsp; solución de problemas
comunes.&lt;br /&gt;
            &lt;/span&gt;&lt;/div&gt;
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&lt;div style="text-align: justify;"&gt;
&lt;span style="font-size: small;"&gt;&lt;b&gt;Requisitos: &lt;/b&gt;El  curso es para estudiantes de posgrado, pero también esta abierto a  
investigadores y profesores. &amp;nbsp;Los interesados  deberán estar 
familiarizados con los métodos morfométricos básicos y los  métodos de 
la estadística multivariada, especialmente análisis de varianza,  
regresiones, componentes principales y análisis discriminantes.&lt;/span&gt;&lt;/div&gt;
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&lt;div style="margin-bottom: 0pt; margin-top: 0pt;"&gt;
&lt;span style="font-size: small;"&gt;&lt;b&gt;Formato:&lt;/b&gt; El curso es intensivo, una semana, de Lunes a Viernes.&lt;/span&gt;&lt;/div&gt;
&lt;span style="font-size: small;"&gt;
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&lt;div style="text-align: justify;"&gt;
&lt;span style="font-size: small;"&gt;&lt;b&gt;Objetivos:&lt;/b&gt; El curso provee instruccion teórica y experiencia práctica en los
                métodos para el registro de datos morfométricos (coordenadas de marcas)
                y el análisis estadístico de la variación de la forma y tamaño.&amp;nbsp;&lt;/span&gt;&lt;/div&gt;
&lt;span style="font-size: small;"&gt;&lt;br /&gt;&lt;/span&gt;
                &lt;span style="font-size: small;"&gt;Organizador por:&lt;/span&gt;&lt;br /&gt;
&lt;br /&gt;
&lt;span style="font-size: small;"&gt;Grupo de Investigación de Sistemática y Biogeografía&lt;/span&gt;&lt;br /&gt;
&lt;div class="style2"&gt;
&lt;a href="http://www.uaeh.edu.mx/campus/icbi/investigacion/biologia/index.html" target="_blank"&gt;Centro de Investigaciones Biológicas&lt;/a&gt;,&lt;/div&gt;
&lt;span style="font-size: small;"&gt;
                    Universidad Autónoma del Estado de Hidalgo&lt;/span&gt;&lt;br /&gt;
&lt;span style="font-size: small;"&gt;
                    Pachuca, Hgo. México.&lt;/span&gt;&lt;br /&gt;
&lt;br /&gt;
&lt;span style="font-size: small;"&gt;Contacto:&lt;/span&gt;&lt;br /&gt;
&lt;span style="font-size: small;"&gt;Dr. Julián Bueno-Villegas,&lt;br /&gt;Lab. de Sistemática Animal, &lt;/span&gt;
                  &lt;span style="font-size: small;"&gt;&lt;br /&gt;CIB, UAEH&lt;br /&gt;
                    milpatas@gmail.com&lt;/span&gt;
                   
                  &lt;br /&gt;
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&lt;/div&gt;
&lt;br /&gt;
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&lt;span style="font-size: small;"&gt;&amp;nbsp;&lt;/span&gt;
                 </description><link>http://cladisticaybiogeografia.blogspot.com/2012/11/curso-introduccion-la-morfometria.html</link><author>noreply@blogger.com (Jonathan Liria)</author><media:thumbnail url="http://1.bp.blogspot.com/-z-M1Oa1ks5k/UJPU1RqrSVI/AAAAAAAAARg/wMNTSzR6fQU/s72-c/Sin+t%C3%ADtulo.jpg" height="72" width="72" /><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-6720900520920971104</guid><pubDate>Fri, 12 Oct 2012 20:31:00 +0000</pubDate><atom:updated>2013-03-27T15:23:20.753-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">parsimony</category><category domain="http://www.blogger.com/atom/ns#">TnT</category><category domain="http://www.blogger.com/atom/ns#">taller</category><category domain="http://www.blogger.com/atom/ns#">megafilogenias</category><category domain="http://www.blogger.com/atom/ns#">GenBank</category><category domain="http://www.blogger.com/atom/ns#">curso</category><category domain="http://www.blogger.com/atom/ns#">cladismo</category><title>Taller en Cladística Cuantitativa - España</title><description>&lt;span style="font-size: small;"&gt;En esta entrada les traigo la información (&lt;a href="http://www.4shared.com/office/8Xyg43lB/Flyer_Quantitative_Cladistics_.html" target="_blank"&gt;PDF&lt;/a&gt;) sobre un Workshop en Cladística utilizando TnT:&lt;/span&gt;&lt;br /&gt;
&lt;span style="font-size: small;"&gt;&lt;br /&gt;&lt;/span&gt;
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&lt;span style="font-size: small;"&gt;&lt;a href="http://www.4shared.com/office/8Xyg43lB/Flyer_Quantitative_Cladistics_.html" target="_blank"&gt;&lt;img border="0" height="400" src="http://dc363.4shared.com/img/8Xyg43lB/0.16352506205804884/Flyer_Quantitative_Cladistics_.pdf" width="282" /&gt;&amp;nbsp;&lt;/a&gt;&lt;/span&gt;&lt;br /&gt;
&lt;br /&gt;
&lt;span style="font-size: small;"&gt;&amp;nbsp; &lt;/span&gt;&lt;br /&gt;
&lt;div style="text-align: center;"&gt;
&lt;span style="font-size: small;"&gt;Transmitting Science ---&amp;gt;&lt;/span&gt;&lt;/div&gt;
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&lt;div style="text-align: center;"&gt;
&lt;span style="font-size: small;"&gt;&lt;b&gt;QUANTITATIVE CLADISTICS AND USE OF TNT&amp;nbsp;&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style="text-align: center;"&gt;
&lt;span style="font-size: small;"&gt;&lt;b&gt;June 3-7, 2013&amp;nbsp;&lt;/b&gt;&lt;/span&gt;&lt;/div&gt;
&lt;br /&gt;
&lt;div style="text-align: justify;"&gt;
&lt;span style="font-size: small;"&gt;The workshop will cover the basics of parsimony analysis and character optimization, tree-searches, diagnosing and summarizing results efficiently, and measuring group supports. The course will be informal, with extensive hands-on exercises which will help students get familiar with the main aspects of phylogenetic analysis using TNT. For each of the units in the workshop, there will be a lecture (one to two hours, depending on the topics), then switching to exercises illustrating the points just seen in the lecture. Switches between "lecture" and "hands-on" mode will be dynamic, depending on how students advance on the exercises. The workshop will make extensive use of TNT. There will also be a demonstration and some practice with GB-&amp;gt;TNT, a program to create TNT matrices from GenBank data (in turn, GB-&amp;gt;TNT requires installation of some alignment program, ideally Mafft or Muscle and possibly BioEdit to inspect alignments).&lt;/span&gt;&lt;/div&gt;
</description><link>http://cladisticaybiogeografia.blogspot.com/2012/10/taller-en-cladistica-cuantitativa-espana.html</link><author>noreply@blogger.com (Jonathan Liria)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-5377644370305764027</guid><pubDate>Thu, 04 Oct 2012 23:54:00 +0000</pubDate><atom:updated>2012-10-05T18:56:25.984-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">TnT</category><category domain="http://www.blogger.com/atom/ns#">landmarks</category><category domain="http://www.blogger.com/atom/ns#">thin-plate spline</category><category domain="http://www.blogger.com/atom/ns#">morfometría</category><category domain="http://www.blogger.com/atom/ns#">macros</category><category domain="http://www.blogger.com/atom/ns#">cladismo</category><title>Configuraciones nodo-x-nodo</title><description>Hola:&lt;br /&gt;
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Acá les coloco una animación realizada con &lt;a href="http://microsoft-gif-animator.softonic.com/" target="_blank"&gt;GIFAnimator&lt;/a&gt;. &lt;br /&gt;
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Esta animación se realizó utilizando, uno de los dos árboles más parsimoniosos obtenidos con la matriz de &lt;a href="http://www.scielo.org.mx/scielo.php?pid=S0065-17372011000100007&amp;amp;script=sci_arttext" target="_blank"&gt;Soto-Vivas et al. (2011)&lt;/a&gt;* en &lt;a href="http://www.zmuc.dk/public/phylogeny" target="_blank"&gt;TNT&lt;/a&gt;. Luego se preparó una matriz de Puntos Anatómicos de Referencia o landmarks, para &lt;a href="http://tnt.insectmuseum.org/index.php/Landmark_optimization" target="_blank"&gt;mapaear las configuraciones de los PAR&lt;/a&gt;. Seguidamente se empleó el macro&amp;nbsp;de TNT &lt;a href="http://tnt.insectmuseum.org/index.php/Scripts/export_tps.run" target="_blank"&gt;export_tps.run&lt;/a&gt;&amp;nbsp;para exportar las configuraciones hipotéticas de los nodos, y las configuraciones de los terminales (Taxa). Finalmente este archivo &lt;a href="http://life.bio.sunysb.edu/morph/glossary/gloss1.html" target="_blank"&gt;TPS&lt;/a&gt; se abrió en &lt;a href="http://folk.uio.no/ohammer/past/" target="_blank"&gt;PAST&lt;/a&gt; para utilizar la opción &lt;a href="http://life.bio.sunysb.edu/morph/glossary/gloss1.html" target="_blank"&gt;thin-plate spline&lt;/a&gt; y graficar las deformaciones entre los nodos seleccionados.&lt;br /&gt;
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(*) SOTO-VIVAS, Ana, LIRIA, Jonathan,  &amp;amp; LUNA, Efraín de. (2011). Morfometría geométrica y filogenia en Rhodniini (Hemiptera, Reduviidae) de Venezuela. &lt;i&gt;Acta zoológica mexicana&lt;/i&gt;, &lt;i&gt;27&lt;/i&gt;(1), 87-102.&lt;/div&gt;
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&lt;br /&gt;</description><link>http://cladisticaybiogeografia.blogspot.com/2012/10/configuraciones-nodo-x-nodo.html</link><author>noreply@blogger.com (Jonathan Liria)</author><media:thumbnail url="http://4.bp.blogspot.com/-PxbUzqh6wgs/UG-PELzUehI/AAAAAAAAARI/5OxDFlX4CXo/s72-c/Filogenia_Rhodniini.gif" height="72" width="72" /><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-5794592431241628111</guid><pubDate>Tue, 02 Oct 2012 14:42:00 +0000</pubDate><atom:updated>2012-10-02T07:42:44.091-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">sistemática</category><category domain="http://www.blogger.com/atom/ns#">libro</category><category domain="http://www.blogger.com/atom/ns#">filogenia</category><category domain="http://www.blogger.com/atom/ns#">parsimonia</category><category domain="http://www.blogger.com/atom/ns#">cladismo</category><title>Nuevo Libro "Systematics: A Course of Lectures" - Wheeler</title><description>&lt;br /&gt;
Acá les dejo la información de este libro:&lt;br /&gt;
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XEClzqNSZ/t4fR9AWxTiNyeaPiXBDww6cgJRFApeBCSRkEejOhY1caiJQ3UcyuNQGQ15KIR0CHzBp6HEC6Xe4NMgpkERiOpI1CfgTTo6szFY/F9l6TyNYB0RbR4vRDWygxrFCVJpSKrPkdrTpMpQW3GcKA4T+R4i3aIVr9IKl6hL541yMViM3gJ056KbibepaE1GaxyaIvA6HG9i0JGC7kwM5GC0EKOcyWOcz5WlC5T81RrBT2rhVqVoi1K0ZUywY5S/fZS/fYS3DWt2TF6/a/LmA5N3/jppj8HkI2cn6l/+yPD6JzeMJ941mfLYAuZ2sHUExQkurlOp7l94es6kec3y91kQSFsU5D03wOMLP2d4U+BnC6oFPJ/A4x6oxqDfR9gT/PkMsTZIoyDXC+wACCJQHoeXqXiViaa8xW2s1d2l2wZEe4Ylh4elB4ale0dk+0YFW0cFW8d4G0e5Pw6xFvTlfdDJREcG3qahg4GuTPQyMZiL0XyMFU5WsaaPlcxRlo7/0qzTCrdqhVtVgs0qwebh0p1DJdv72Vu7C9e15yx5nT69JgFl0eAHosADDFukWiDVAqnmSLNEujUy3zvMd0AhBcXO4LiC6w6+J4RekNNQ5ocKOqoC/0b4VxKOfy/H6zRlAZRFULOhLZ2pESzRiH7USjZqJVu0grUa/spxhCrBMrX4R61kI5FuVSv2ayuOkmpDUnuG1JzTVhsqqw3GqvSV5fsGxb90cn5qLphbw4Q0EdxQFPgh2gkB5rA3xmMj3DkNYwPcP4H7x/DoBJ7ow8IQjhfhdgW0Gwi7j1gz5NuB6waxL2R0yANQEYjKIJQHQBEAiS94Hu+rUIoOIcsJxU7gOIPrAoEbJF6ooKMmGC8i0BCNlgS0p+BdOvpzMMr6QMObrxZuHUeoKT9Cqk6Ruguk4SppvEFeXScNl0jtb6ryo8OK/V3C3XUFGyRpi1Mj5tC9PrW0wX2LT+/ZfGviuNicstjGeYml2zIrl6WWzkvsXBc4ui9wpS708JrrTp3j5f09jbY4mD4nwv+jRDoYdOQGoShUV4tWRKMmDi/j8SIBNfGoTEBlBGRBENDA9wKPCq77+5uFB8Q0lAWhJhoNiWjNQE8+hjkzVIIf1aINRPazVr5bI9+nLjtKqk6RF+dI3RlSbUjKDbTyQ0S2m0g3EvFyIlygLf1+rARDbPQXoTcfPUxdRdoSj8YIvAxBUwTaEvAuFX2ZGMrGUBGGizHG+UpZuljJXz3GXz8yfnjbRnjbhku3DpduxZodH2/Y/emWg1N2Hft036nJR89/dPLq5NM3P7714JM/nn701HqSpQPsneDkPMHV7T/jCL285vj7LAj0+T7Qa76/+1c+zhO8HOFlB3dLUB6DcheOt+B2F94PQDdB2DPEWIPhhFwqiukQhqI8BjWJqE2f3pA1t6VgdSdnc1fJ9u7SbV0lm7tKNvexVw+x1wywVwywFvXkTe3MRFsamlPQkoD2ZF3mDGVjNA+qQmhYE0d53yoFi9XCtVrxNiLRIxI9jURPJdmpku5RivaM8HcNcLd1sda25Mx7yUBVEsThYHkjw14nMNUcqRZgWCHzvcM8exQ4gvX+dvQXQoWvDmFNMF6GoCkKb2LQnoiOZHT9A6GqEBoWNGxoSqZo+XPHE08j/kkrWKsVrNYIlqkEy1Si5RrxerV0q1b+i7rikLbqBKn5jdReILXnSc05bc1v2hpDUnlEJT/Sz9v1tnhZYw4qUiGIBDsA8e4IsIbtPdwzwlVDXD+OW0dx9whuH8UfR2FiAOuzoBjB8yoCjRH1BFlWKHICnwqhD8Q0SP0g9YOUBjENAiq4LmA5otgBxQ5gO6KYAhYFLArYTuA4g+8KMRVlvqgKRFUw6sLQFIO2RHSmopeJ4YJPVZyFKsHPSvEOlXSPuuywtsaQ1F0g9ddIw3VSb0TqzmqqTo4pDg7K9rbzd1Rlr+ImzIoOmOXuPMnkOf54PvWezbePHBaZOSwwd5j/3HmxGWWBmeNsS8pse9fvKJ5zXDxnu3jOdvde5OO7IJg+60/6xFg/pPkhJxDFwe8RRqEmBi9iURODyhhURKEsFGI6eFSUuIPjCpYTWE5gu4DjDL4npHSUh6I2Bq9T0JmNvkKM8pepRevUsk0axU6lYq+67DCp1id1Z8nL86TmtLZMXyM7SKS7iOQnIl5ORItI6Y/KkonDbAyw0FeA3iwdwldxeBmKWn80BKM5Gu0JeJeKAQZ68zBQgCEWhtnfDnOXDJesHOIu7y9ZPsjdPH4GOJuwducnG3Z/uvXQtN3Hpx04/fFxoymG1z85c+uTO4+m3Tf71NTmIytH2DuB4oJ/I1z8T4TeDnC3h7M5HB7D6jZsb8D+d7jdhdd9BDxC2DPE2SLdBXle4PpDEgZFDBQJqEr9vJ45vzlvdUvB2paCtS0Fq1sKV3YXLO4pXNJXsLAn/5vxRnBzEl4loCkGLfHoSEFPOgaYGMmFsgDaIozyvh3lL1QJ12rFOzWSPVrpXt3Ft3yPUrF3RLx7ULCjt/SntqJF9cwJVWmQRYHji0wHHcKU57q6NMNKhzDXTodw/HY0jlDmA4Uvyv1QGfA3wpZYtCeiMwVd4+VoDgbzoC6ChgUtB+rSD7X8b7XCHzSidRrxT0Sw7h8IV2klP2lkPxPFLk3lr6TGgNSeJrUXyIsLpPY8qT1NXpwmNfraMv0hwf4uztqmvI+r0yGOQUkwEj0RZAubB7hzCZdP4coxXP8VN4/g98O4eQSPTsDiDBwuwPUKAm4j/DEyzJHvgBJ38KgQeEHkA5EPBF4QUFHqjmIKCu1RZAeWvY5ikSNYFHAo/0YYgAp/1IbgVRRa4vA2CT0ZGMybqmQvVgl+Voq2qaR71GVHtTW/jSPUNFzTvjivrflNXXFsVH6gX6LXWrpNwVxaFP15iM9njnZ48BS3zaYY28555LDIxH7uM5u5jymzTey/fWz/panDl1bOMx3cv3Nyn0Xx+MrVZ76P75wA+td/0ifG+CLVF9kBYAWBHw5pGMoiUBWBqkhUhqM8HIowyIMgoKHEAxxXFDuh0AGFDmBRUExBiRtEPpAHoSoSDUloZ6I7DyO8pSrRKrVsk1q+Y0y+S1m2n1Trk5enycvzpPY9QskvRPITEf1AhHNI6RplydQRDgaL/4WwMQ7VIajyRZ0/XoejNQbvEtCbgq5s9OagvwCDrC+H2AuH2N8PsH/oL/6+n7Nu/PSx12LNzxM3/fLRjoNT9hyffMQQJ85POHt14sWbk/94OuGhOcxsJ1pTPqC4wsV9gjv1Y2/qVB+f+d7ec729F9C9F/n5zPalznB3hpMD3OxAsYDtY1jewfNreH4FNtfgcAPUB6A/QZgF4u3AcEaeJ7i+EAZCGoeyRFSno445+WXO5w05X9fnz23IX/w6d1pr/tT2gg/f5qKFiTfJeB2Phmi8ikJzLFqT0cFATxYG8zA2fvXiLCalPxLBJiLarZHsV0kOKqW/jikOjykOj0iPjIgOjYgODYv0+rgbW3Lm1TMmy6LBC0CuC1ItkGiKJDOkmiPd+n1RaqtrzxQ4guUMtiv4rhC5QUaFwgeVNFT74YU/6gJ05ejbJLxLQ3cmepkYyMVgHkYKMFYENRtq7jRNyZekdBHhrySCDVrBOq1gtUq4RClePCZZoZRu1Mj3qRW/amsMtHWnSP1ZUn9BW39O8/KCsu6i6qURqT9Hak+qFftHRJu72AvrsyBNACcCDF8EO8L6AW5cxHkDnD2K80dw/jAuH8CVg/j9OB6chulF2F+G522EPELME6RZoNARHBdwXcB2QbEbWB4ockIhBQWOKLBHvh0KbXWn2A5se3AcUOIEvitEHpBQIfNBpR9q6KgLxqsotCaiOxOjeZ9pi5arhD8pxT8T2T5SbkCqzpLaS6TuMnlpRKqNiMKQlJ9Sl+t38nfXFW4RZK7Miv7O3evLZzYwfoI7phPum3/x+PlXTy2+sbSZ98R2ziOrWY+svn5u/50lZbaN0xw7l/mO7oup1Hk0r1kBPtNCaYj2RYIvGHQwA1ASCl6Ybj4xzk8cAlEweFSUeoLrBraLLgbHs73YBVxXCLwgpaMyFC/j0cJARxaGWVM0vPlEvI5Itmule7QVh0ndSdJwmtT+RiqPk7L9GtkOtWwTka3XSldoJMuI6Bst/2M1B2NFGMxFNxMtaXidjIZw1ASg0gfVvqgLQH0ommLQloQWBtoz8TYbPfnoY305wJo3wFrUx1rcW7yst3hVH3t1H3s11u3+4OeDk/X0Pzp4dvJxo4kG1yacvzXxkvFk4yeTHj7/xMzuU2uXjxzdp7l6TnWj/seT+jmNtsDHZ5GPzyK69yK693yax1duTqDYg2LzN8JnV/HsMiwvw/oqHK/D9Q5ojxBiikgLpNgjyxVFVJSGQxgFeQLKUlGZjurMidXMj2uyptZl4hUTTVlozsSrNDTG4WXk+6lADFoT0cFANxMDuRgdv3qVLCD8lUS4mYj1tJLDGtlRtfyYulxfU2GgKtNXyY6rZMfHpAcHeds68pe9ypwxjjDHWYcw0RQpz3XtmXGEf7VnCilgOYPvCqE7pJ6Qe+sQ1vrjZSBeRaA5Gu2J/0CYg8FcHUJVMVScCWruNA13rpa3lPDXjiNUC5erxUuV0pUq2dbxG4i2xoC8MCT1Z0nDRdJ4kTReIo3XyOvrpP4CqflNXXZ4VLSth7vkVS4UKSiNBoOOUGfYPMLtSzhviHMncP4oLh2B0WEYHcbVYzA2hMk52BjB8wZC7iHSBMnPkGUHFgUsJxRRUOiMAlfkOyDfAXn2yLdDni0KbHQIWe8dcinguUDoDrEnJFRdNV4dhLoINCWiMxODeZOUrO//nxHWXSQ150nZSVJxUlNh8I6/t65wiyhjDTPqOxf36aaWuG2CO6aT75t/dd/8myfPZplZzHlg8e0fz2Y+fv6Vqc3XFo7f2Th9a+cyx9F9gZfbdzSPr+heU8J9EEVDPA2pvsigozgQ3EAIAiEJgjQQ4kDwA8Cjo8QDXDdwXFHs/B7huENncN3Ap0Lih4oQvIjFmzS8ZWKgEKqSWUS8SivZopHokbJfSa0BeXma1Bj8XwhXayTLtILP1KVQsTFa+DfCV0l4GYpqP1R4o4qG2n/8Wr1JQ1sG2rPQnYeews/7i+b0Fy3oLVrUw1rxN8I1+7Dt1w/2GE46bDTlxNWJBr/jzB2cv4c/nk59ZP7Zc4fP7d1mOlJnOHl/4er9tZvPLJrfQhptMY222NfnB7r3Ii+Pr1wpHzjawtEaDs9h9RjPbsP0Kp4a4ekFPL0Ai8uwuwbX2/B+gCATRJgj2R7pLsj2Q34g2OEojYYwAeIkSFMgT0NlKl4w8JKBhjTUJeJlNF6EozYEjRF4HY2WBLxNQxdTNzVWFkPDna/lrSCCTUSsR6RHtPJj2jJ9TYUBqTyjKT+jVZzWlp1Sy0+M8Pe8K/yxmTlPEatDmGKOhKdINEXyM9218C+EWXbIe++Q5wKBG8SekHujzBfVfngRgLpgNIajKQptCTqEfVkYyMFQ3t8IxzjjDmeoS+dpeUu1gnVawVq1cLlGskotW69RbCdlBzXlxzRVJ7Q1BqTuDKm/QBoukleXSdPvpPkmeXmF1JzWlB9TSnb285Y1F3xYmQ5RApL9EeQM28e4ewUXz+CiPi4cx4Vfcf4ozv2Ky0dx8yQenYH1OXhcQeAthD9EzFOkWyLXFnn2yLVDtgOyKMiyQ46N7uTa/O1Qp9EeLEewnVDi9n57xhtlvqj0R20YXsXpBvejhfOVgg1K0RatdC9RnCCVZ0j1BVJ7kby4QGpOk3IDUqWvrTzZJdhXX7hdlL42K3Khs9sXppYf3nmCO0+n/vH86/vPvn1oNuux2XfGT2cam3xx7+kXJpYzzW2/tbD/0tpxhp3zF+7OX3i5fRpA/SDMG5E+SPRGsg8YNOT7oJAGLg18Xwho4NHA9kaxFziuugwsoujOeKuJ5QyOK3ieEPuiPBi1MWhKRlsG+nIxyoFWuEQrXq+W/kIUh0mVPsT5D9cAACAASURBVKk2JNX6pPLIOEKNfPNfCNV8KEswVoyRQgzmvUeYgNpAVPhA4YkKb9T44UUQGiPwJh5NKWhhoI2Jdznoyp/SWzCzr3B+T+GScYS9xav62Gux9Vfs1P9w35kpv16cduLqFMMbE87excWHePzsv6ZW0ywcP7N3m07x+tLZ52s32lw3+mI//yW+9B9ovkv9aMto3t/7eHzrQplsbwN7C1ibwfIRTO/A5BoeG+H+WfxxGibnYGYEm2ug3IS7MfxMEGaBODskeCDZB5l05IaAFYGSaPDiIUhEWTKqklGbipcpeJGAl9Goi0Bd2N8I21PxLhO92RgqwCgLyuJvNCVLtPyNRLR7PAk1Cn1NxUlSeVFTfk6rOKuRn1HJ9Ef4+zrz1zVlLiiLAz9Qh3C8HE1+hhTzvxEybXU3wzx75FN0TUKxJ6TeUNBQ/g+E40nY9e/5xGghlCyoOVByoeRCzZ2mLv1Ow5uv4a/RCtZqRD9qpWs18s3asl06hJXHtdX6pPY38uIMqTtLGi6R1zf+QqitOK6S6g3yV7cWzajOhDQZjBCEe4Jijsd3cOsKrl/AtTO4YogLBjh7HOeP4bo+7hvC4hzcLyPgJoLv68Iw3QpZVsiwBsMGabbItNGdbGtkWyPXGnk2yH+PsMgORQ5gO4HrohvcS70g90YFHbUhaIxFOwN9ORgt+nqMv35MuFkj2aOVHyPlv5Gq86TmAqk5R2pPayqPkyp9bdWJPuH+hqIdsvSNeZGLqdTZ1nZT7j3F7Sef3DWdMW7vjyfTjR/NvPPgi7uPZzwym2Fq+aWZ1ZRn1hMs7OFCmezhMoHugVAvRHshwQspXkj3Qo4n8jzBpqJkvAtKBcsDRe7v095Rd3QInVHkpEMoGp9VROFVIloYeJeFYRa0/G81oh81op818n2a8mPaiuOk6ldScVir0HuPcJNWulYjWaXiYZSDYRaGCjCQiy4m3iSjPhZVvlB4QuaOMiqqaKj1R30YmmLwKgnNqWjJwFsmOnPRnTe9N39+d8HiHtaKHtaK3uI1fey1OHR60pGzUwzOTzt16T9nrnx68ebk6w8+/OPpR1ZWH9raTrSnTLZ3/djB879O3l+5+i308F/mG7icHrDMj77C12+FH225l+dCV8pnDrawM4eVKcwe4OltPLqOe0a4eQY39HHbAPdO4dFZPL0Ay8twuAXPx/B9jlBnRLojzgcMOnKCURQBbgxK4yBLQEUiqpPxIgkvElAfg/ooNETiVSSaY9GaiPZUdGagJwsDeRguhLL4SzV3kVawbhwhkZ3Qlp3SVpweR6iRn1PLTislJ4dK9nbkrX2dsaA8DvxAZDshxRyJT5FshuRnSH6GNAswrHQDQx1CRxQ4ocT17/URmY+uS1EbopsIvU3+e3d0JA9jfyFk/4Vwkrp0poY3exyhVrx+vCWjVeiRsoPqssPaqhOkWp9UG2prftM1Nhquktc3SN3F8SRUy/YMCda1F39Xx4QiFTmxiA+CrwvszfH8MZ7cw8PbuHcDl87jnCHOncAVAxifwvNzcL0M+i0E3EPYI8SaIsUcDAukWSLZCklWYFgh3RLplsiwQrY1cmx0CMc/8+10/Qy2C7huKPWAaHyBxhdVwaiPQQsDPbkYKpr2rySsOP0PhL+py/VJtb628mS/6EAza1cZcyMrdlkofZ6b8zTTZzA2wV2TD++aTLn9aOKdBx/+fu+T63c/unn343uPPzcxnf70+UfPLWFpC2cHeDjBzxWhHoiiIp6KZE8wqMh2R64Hij3B9USpJzgeKHJDoauuE1NgjwIHFDj8A6ELOK4o9YTQB/IAVEXgVQKaU/EuEwOFUPM+0QiWqEWbtNI94/8XUnGIlO3XyHf/hZDI1mska1Q8jLAxWIjBfPTn4F0mXsejNgIyL4jcIHCBxANlNFT6oyYU9VF4lYDXSWhmoI2Jtznoyv2sJ29eT/4P3UWrelire4vX9LLW4+IVGF3FlSsfXr068fdruHsXj5/A3BzuFHg6g+oOdy94+HzkTvvGk77EM2AFPXiVb+AqWsAqOn2Nn9+PPl7fu7jMtLefYvsMlk9geh+PbuHeddw2wrXTuHQCV4/h+gncPAnjU3hwDs+uwtYYzk/g44AAZ4R5IJ6GdH/kBYMdAV40RDFQxKEiATUJqIlDfSwaotEYg+ZYtCSgLQlv09A5vreRM75P/KWmZMH/QKgp/01bcUFddlYtO62S/jYqPjZYotees7qRMVsejRI6Mu2RaIqEJ0gyRZLZ+5uhBdKt/zEtdAbLFSXvFynHdyllvqj0R00wmiL+J8LhXIzmYSRP53CUPV6RfqIqmfVXEo7P7jWyHeNbwir5QVJ5Qlt1QlNhoC43UFee1FadIXVGpPEaqT1JqvU15YfUsj0jos3vuD+8yp1RlYHiJGREINoHdGdQ7eBoCZunePYIt2/iihGMDHHFEHdOw+wcKFfhfQv0+wh6gEgTxJkh+RkSzZFgjlhzpFnqJqUMCzAskGWJbCtkWyH3r1T8t0O+G0QekHmjPAB1UWhORVc2Bgoxfif8F8Lq86TmnLbqzJjCQFNxUlNh0C/a38L5pTp3Ez9peWrY/GDvz5xsYfocj8zw0BT3THD3Ia7dxpUbuPr7B3eNpz14PO3p04+eWcDSBhQ7uDrAxxlBrohwQ5wbUtzAcEeWG/LcwXIHxwMl7mC7o8gNBS7vBb4/4wjZLihyAdcNPCpENMgDUBmOxng0paAjHYN5UHMnqfkL1cK1aul2rUJPq9AjZfu1Cr1xhFr5diLbQqQbNeL1aj5GORgsxEAe+rLRwUB9FCqCIPGAwAV8Z4jdofDRDVdfRqIxHq8S0ZSG1ky0Z6Mzd3JP3rye/BXjCHuK1vWy1uPJAzx9iGePYP4QFiawN4OrLajOCPVGhB/+DEJ4yMTQ0C8CQub5hSz3DVnjH7KaHrzGL2hNQMB6On29r89Kd9e5To4zbZ/BwgSP7+H+LfxxHbeMcPU0Lp7ApWO4cgLX9XHDALfP4OFlmN+FnQlcbOBpjwBnRHoiyQeZ/igKQUk4hFGQxaA8HtXxqE1AQxxex6MpAa2JaEtCewo6GOhMR1cmerPRn4tR1hQle7aqdJWGv0Ml3K8SHVFKTqrkhiq5wZjUYFR0YkR4fJB/oIe19Q3z+7rk6ZIIFHsjzRqxjxH7CPEmiH+COJO/26RZdrrltWI3cDxQ6gGepw6hxAtSGsr8UR2kS8K/d0eZGMzCcDYGszGci9F8jBRhlPXBWPFUJfdrdek8DX/lOEKteJta+otKqqeS7hmV7FXKDo1JDw5LDg+JDw9Jj4zK9TWVZ7UvLqqqDqsrDqnK9mnku1XSX/oEG9qKFzfmzhKkoTgOzBAk+OJPKoJc4W0PZ0uYmuCPW7h+EdfP4e45mFyA7VW43YKPMej3EfoQ0SaIM0O8GWLNEG2qy//kZ0h5hpRnSH+GjOfINEeWBbItkW2JXGvk2aLAXje0KHYC1xV8T0j9UBGua/F35WOkdM0wb8OYYKdKckQl01crflOVn1aVnxqruDAiM1QrTqrK9PtF+9tKdtYVbpRkLM9PWJgaNiPIe5K7MxwpH9rbT7C0xBNT/H4PV2/h+g3cuj3l/r1PHj6cYPIUzyzgaA1XW3g6gO6IEAqiKEh0RqoLMl2Q7YJCVxS7geMKlivynZHn9I8ktEehA4re7wCxxqe+Xv9GmKxDqOJMUJfOU/JXaCU/kbKfSfm2cYFq+Q4dQvnWcYRawdRRDoYK0J+D3iy0p+BFOGS+ELqh1AmlzhB5QE5DmT+qQlAXpUP4OhUtGX8hXNhb8GN34ZruwjU9Ret6WRvgZgsPO3g5wpsCOgUBbgj3RhQd8UFIjgAjDmmJ/0lKnBsdt+zPqDXBERv9QlfTg9f4Ba6nB20KCNhIo63ydF/gTPna7jnMTWBijHs38cd13LyMy2dwXh/njuL8UVw4BqPjuH4Sdy/gyS1YPoKdBVxs4OOAYFfEe4JBQ34gOCEQRUMeg4p41CaiLgmvEtGciJZktKWgPRUdjL8R9mTpwnCoaMYI+4cx7pbhkl0jvEND/KPDouMj4mNDwiOD/EMDvIO9XL3O/HWNjNlV8RCEoMADSeaIeoCo+4h9hNjHiHmkC0OGFbLskOsIljM4HiihgucJPhV8LwioEHhB4gMFHRWBeBWGpii0JaIjDe/S0ZOBfiYGmOjLxEAWhnMxVIDhQowWfTbK/kbFmasVrCbCdUS0WSveppHoKSV6Y+LdI+LdA/zd/bxdfSV6vaV7enl7B0RHRuUnNZVnxyr3KMv1VGV649+GYcn2rtL1LcUrKrLmShkzOfET8iORGYoE/4l/Uj8IdIGNBZ48wN2r+P0CjM/j0QU8vwKHm/C6C19jBN/Hn48Q8wQxpoh8ivCniDNDoikSniLhKZJMkWSKNFMwzJDxHBnmyLQA0xLZ1si1Q74DChxR5IhiCkrdIPJBWQjq4tGSgY4c9LGW9rFXD3K3DPP2DgkOD4uOD0lODEmOjZZfHJYYjspPKhUn+oT72kt/aSzeImeu4DEWFsbPSQz5LJz+WaDvDJr3Z67OsLOCsQlu3cPvNz+4eWuy8e1PjO/g3gOYmMDOAhQreNqAZocAO/xpj3gKkp2Q7gSmE/JdUOSCYhcUOiOXghxHFDn+7fCfCMefp40jVAT+jbCTgcE8KNlQlcxS8n/QSNaQsi3aiq0a+e73CH9+j3CTRryeCKePvUfYw0RbEmqCIfGCwBWlTih1+hfCFxH/QtiWhc7cyb35i/8nwlgKEtyQ6oUMP2QFIjsEuWHIC0dxHLgJ4KWglDGDzZhfkPx9ZvzytOilkRGL/gxb9GfoD2HhK0JDVwf6r/akLqZQZlNspj9/gvu3ce8GjG/g1iVcPIOzJ3HxBM4dxbmjuKiPK4a4eREPb8HcBNbmsLOCiyN83BDmi5RA5ISiOBz8KMiiUR2Hxji8iUdrPN4mozMVHWnoZKArA11M3XOKDiY6mWjPQnfB4nbm+kHWz705C8ZK1ndzj3Xw72mLjvdw9rxhn2zl6r8t3tKSpNeevL0sDqV+KPRA5AOEP0ToUwRdR7Lxl/H3kPYUyWaIe45kChIckeOJsjCUuCHdD5wA8D0hdp8k9P602AuSEMj8UR+O1zFojUJbPNpi0RG7tDkWbTErB+P39cSvG8id15aFN0y8y57bl/0tEcwg3G2Ev1ErXkMUO8aEekMlB0bFx3q5u3tKdrUyD7UyD7Xmbu0q/HWYc2eAe2VIekCpODamODwqPzSmODim2Dci29Mv2tbN21RZNKe2cE155gZp4nJWxLS8UOSEItwVdAt4m8PkGh5cmHbDAGY38eQCnG9Ntv39K5d7cL+F8AcIvYvg+wh5glDT6TkPEGv8qf9T0J4g5sl3yQ+mJjwAwwSZpmA8npnugBgzJFoi3wVZph8LnSb9aY0s6gdMW5TRNoi9v2DR8CIPMiZeZ89uyl3emLOjlXOuhXuuU/xbQ9HRd8KbLbJrPQKjMd4Wwr/Qx17byTV4VbysLmdJRc5yXuyPnPj1WRHTUkOmx3rNCaAgkAr3h3B7NveP6wvu31p2/9oUc2M8vQ+zJ1PNHeDsCH/bidQ7H/k/mhBHQZgjwt2QYodMe+SMt14oYFFQ6IhcR91tIssOuXbItUOBg275abyoEXj/nYQNsbr3Wd1MDBZhlDtbJVim1r0q3KGu2KYt26FR7NQodmrl2zXyzVrpWrV46Qhv8gAHvfnoZqIjDY2xkNHBcQXPDjxH8CkQuEDsCYUvKkJQHYnqWLxIQGMqmjPRykRbzlcdeYvf5a/uKvixu3BNL2t9P/snMH2R44+CUBRHgRsLfhJEqZAwUJU1qSb3q5qChTUFK8sL1klzNpZkbihOW8eI/z4tbmlS7LKU+FXJ8evjIteEBizz85rr5jDD2uyDx3fx4Cb++B23L+PKWZw7BSMDXDiO88dx6SSuncHtS3h0G+YmsLGAvTVcHEHz+BdCQTTkMaiJx6sEtCS8f6aQpgucvxB2MN8jzEVLLtpZG9pYPzcXrGwpXtGQv6GRdaiJub2+8BcZY/crzu4X2WhM+7485kd2DFh+KA1GiDGCjeF6BaHGCLn5TcBNhNxD8AMU0iZmuaGQikIP5FGQT0GpF1hOyHoOnjtkQWB7QkhFLR0yOmrC8SoSL2PwMgn1KVOqUvGSAVEYZNEoT0B9FhqZ6Cn8T1/27NGCZRreJiLYRESbieSXMf7e4dL9g/x9nayN7TmrG9LWNeWvfsX+5EXO5w1Zu98VHxuR7x6RHhmRHRyVH1KVH1ZXHFGVHxiW6g2Id7QKNzewNtUwN5SnrZIxlnAT5qT4fxbhPj3IBU7P8Md13LiI+zdw6xxunsLDizAzAsUYVlfhem2y29VpQY9BM4bbVQT8Dp/f4fkQ/s8R/gAxxkg2RexDBD5CxBNEmCLSBPFmiDVHzFMk2CDTHnGmyLBCvjWqA9GSjMY41IVOfpOGt8w5jUkrmtN2NaZt78jXa8rY0Vdo0Coy6uZd6mbv7Gdfq8v+uT73QmPBxvbiLS+y18iSN8vSf2YlfJ0RMTsteEuY5+IAKrztYWODe+a4aozHd/H4Bp4/xr0HMH0EezP42IJuBd/n8HsOPzMEWCDNARkOyHVE0fv0y7NDlu3/B8K/ytGKMDTE4nXS/4qQlO/Ulu3SKHZq5buJYheRbyWy9RrJqhH+B8Ns9OThXSZak1EXAak3ip1RaosSe/AcwXeG0B0yH5QFoTIcVTH/G8K13YXrelkb+tmbUBIOfhTECZCnoCIDtVloyEcTCx2clZ3cte9KN7bxtjaXbK9n/VyVt1mRs4mTsZydvrSYsbw4Y21xxoaC5LVp0Uvjgub5unzuYAGzB3h8B/dv4fZVXD0HI0NcOomL+jAywNXT+P0C7l7F4zswN4GtJRxs4UqBryfC/ZAahNwwsCMgjIEiDjXxeJWI1kRdDHYx8C79PcJMdDPRyUQnEx1MvM1GZSKqmbvEmWf5GacFmYdK49dUZ28RZ54ty78pYRiLU3YIElES/ik3Rj8jdlcadXMUBb7G+PP+VK9rcL8Jr3trXY1X0y03h9nMi7BAshW4bhB7T+d6QRKGXCrkCctZod9lBSI7FHkhyPdDHhUV4aiOQkMEhP7gRYIdszkrYnpR5FoWcy0/ays7emlZ8iJFApqZeJc1fTBr8xh/jVq4VSverRTsG+XtGyrd08na2Jy9tCZ1gThmg4SxR5y3m5P6iyz1txb22W7hpn7BvkHRgRHZQVX5UW3VCU3lr8qyQyOyfUNlR9uLt7cV7XiZtaY2b52QsZ4RsL407WKwxy46dYmNDS5ehInxxLuXZ5o/+O7ZfZhfwmMjPDCCza3Nbvd2eD74yvN30G7A1QReT9Z7PF7k8wDuF+FthIC7CDDe7GQ2JcJxPf0hEs2mMCw+DXiEKNslvjYTY62XRNki2/fbZMpnpYH/4fqjPAxvY+eKYvAy5+dq5tFqpoE87cDLAsOGvFMdnPMN+Ude5xjWZu1pLXWs4t5v4DrW5Rx4m7Opla33KvdwbfaO/Jj/xNC+SgnW/9PHwNdtg6/bHBt7mDvD2vE/T+/B4i4cn8PRHiHOm+wffWth/KmP/Tc+NlMp90F/9kEcZXqSFVLf7/rm2yHPHll2ugnTOMIc238hZLv//0M43p7RyPcS+T6i0CPy7US6USNZNcrDIAtd2XjLQHMcKoMgcEehPbjW4NiixB58im7xXR6A8lBURqM2Hg0paMpAK3NCW87XHXlL3+X/2FWwobvwp17Wpn72VkijoIhFZRJeMNDIRGs+3hWjr/SbYcGOEeHOYZHeoHhfn3BfB29XC2dHY/HW6vzVFXkrynNWVeSuUeSsFWeuZiUuzo74Npw61dMW1iZ4cg8P7uDONdw4jyuncfkUjAxw+RSun8UtIxhfg4kxzE1gbw2KPdyd4UfFn3SkhiAvHOwIiONQFo/aBLxOQvt7gd3p6Mr4nwjHX1W2ZuBFwuJ3YhsyUq0ZbupuL+bEGykS9DQjCjL6mnQ2l0Te4MZ+xIrarGmXjg61kkFBIn166HN4G8HxHBxuTmiSxZGhppGeKtJbGOPw31wXlLqA7YACd8RRIGNZkOHmkUHS1jH8trNV2fe6ozFHxrfjBoDjg6pAiIPRKnxEul6S0XqiHBjsrxrqLH8rK3yZ41WepCeIRAsTfbkb+3nfjwq2asRHRkr3D5fs6eZsa2Auq01fKs88VM92Hm4SE3UPGekjPU3a13/W5m/oLdXrF+wblhxWlR3XVp7UVB5XlR8dUxxWSk72sPcPi46+KdhYm7dOmLY9P8ZgtDmJqIffNuX5em8zMgInl0KUgyOddeFB124ewfWTKMgwU/e9IaNv0kMMXX6H0ymUy2iad82krYYdfNXlDFwuINzi+wGFUDncN9pcHvJ8ls9lBF5HqNm0gTouGe1U9bSQ0fbRvs6hrq6ht7yE4BU5YWC4oVIUPNTZONw1ODYyNDrYQ8bGhtta2iq5jZl6DUxDRe6pwTb22Aif9Fa0lt5qzdhUx9hYl77nRdZWYdr80nS9oZZ0MtqgVVaRvnp1X89AV99ob62P/VbKQ1jeRgTtABngE/VbouwlynZVb33vS744w9bx3ieRTxFrhhRzMC2RY4tcW2TZgWmnmzAxbZFjixxb5NvruqN/IRT6QOaPijDUx/y/IdTI9xLZXiLbR+T7iGIvUewg0o1a8SoVDwNF6GSiJQUvo6CgocQJRdbgWOkQ8hx1O7dSOsqCUBGFmjg0pOB1OlqYaM2e+Tb3+3f5P3blb+ou2NxbtLW/eDsqI1Edi7okvGKgLRs9RRgpWaQRrCPSI0T2K1EcJYqjasWvI9Ijg5KD/aL97aUbW7kbmtkbmtmbGlgbanLXSNMWc2NnJvtPDHCCgyme3tch/P0Crp/B1dO4fApXDHHjPG5fwh/XYWIM86dwtIWzI6iu8PdGZADSQpEfAXYUJPEoi0fNOMIUncCeDHSno4uBd2l4l6F7WPg2E23pqIiAgD6xLO13Qt6pCBkYfJfgfymNsrChSU60GjJGShKtI9zADN9HBvuVWtJfn2v7EIHPEfnoS8eLoD1fp+ytJ0Sj0RKiGcj0OZZoDbEvBNQPJJFI9kG53Eap6eklpJcQJdEQDSFE2TNa/SLHsNgHch/kuaKG46TuJ0RDSA8hGkI0hIwR8qa3uyywJBp1mXiXtaybM3+w5CciPjbK2T/A3dlWsFmW8GM182BvSyYZeqcdJWolUQ0RMkrIoOS16Govb8+AcP+o7Fd1+Xij/6SqTF9Vpq+VnhoqOaxRnHzL3vYib5Modff/Ye89g9owt/XfJ06vO73tnX6y4xSnOo4dJ3FcYseOW9x7xQUbCJjejAHTO5jeTRcgCVToiC4EQqIX03vvoC6t/wfw2fv87zl37ty5M3fuzJ15PuiDpJFG+s1a73rXelZ5xkWaLSU5kU5dkHv31HFE+F0nGZGKOjoKDY7h+F60SNNJQySbcTH7yvYUXA+jpDKBlERKyvK/Zrkfdqdgdh6KsU6ZlrSzyyFWH4ZeQcR1BJm9Jh8a1GqJNKRUaZQr347G2Ik/8mOQ7YMykfeSbEyuJjktqWiaSEaq0YHu9Na0H5qYf1bnnFLK+nU0TTpFb6lJT8Y3g7k7B/L/7MrZUpH+Nif+x4X+ElLKlcp50shJQaQmoon7vj85GcL+KgpTrpF6jtS0vECzi1NEWtKQamaoSnD3viWSrcG0A+cO8pyQcxc5LuC4gOf4EEIn5Dmj8C4E7qsQrnSx/1+EkKT/DuF2km6muu80tWvVVZgvxCgXfRloi0WtP8qdUeLwLwir3VchrAtFQySaEtGWip5M9HMwxMNIzt/H8z6fLPj2v0DYkYyuNPSzMMrHTAFkZW/pRN9R3bZVCOsPrHCobTikqT+olh6QSXYsibcu1GyZr906K9oyUr65M3ddU9YHBfGPJfnD2x42t3DLAH9dhcFFGJ7D9XO4chpXTkP/PAz1YHId1rfgaAsPV3i5I9AHEfeQFInsOBQloTwZdQw0pKGNgb4MjLMfEsjDDAdTWZhkr04VTvAxxsVwFnpy0JCEwoiP5dNFSzr5nHomn2mc7vZCYWmShuZJS2Mdad5OqC66SsuTCqIugZu/JcJtcN/6BdPDqM5yJq1KoVlcUqpIRlP13EgL8LzAdUG+HzJ90FsSSEpSy6mtKYt3/69ZUTUtEqlpvi2qJBSNIcjxhKTcXK1TEo3NDNZWFXjViQKJxkhDtNzRINgmTccA851pwT8WBN+RaL+sdNtM6fddOesr034brnZels0TkUY7PTyZMzKQttCbo+nP6BJcXRDtktXtUzUc0jQd0TQee6iT1HxKKTqoqjs6X7V7pPy3Bv6ektSTA7XBCrWCSCuujj52BC63tygnF9Vymlpu1juJ04ceX5ppIw2NdNabXHzR/gKs9qKwPIx0ROrlKK8jBn/C5gqunMbMaPUyLWllgz6mrwVcxL3L8DTA4oRUTVOkGiziOfLS9EszbjbyjuUEIN8dNd6P1BZakWqBZDTSU1maG9SQnzpRyxittpQmrJdk7C/OOjw/2yvTLSnn5HVc/Xbml105v/XnH+7M2yXO+pIbu10+KiEtqTW6xvrg9EyDnMKbgrxjCQEv+JjBxQjJIV+piWRKan1QlcK9WVYbqFNrSEdziqYUGzDswHQA985qCspzRvZd8BzBdwLfGbmODyF0e1gd/TcIm2LRnYK+jP85Ekq3keQ3ku6k+t+ofgtJ1utq1qqq31GVYToXA0w8SEF9OCo9ILiNMnuUOaDM8V8Q1vpDHAJpOJri0ZaM7gz0ZWOI99gw/61VCP89He1IRGcq+tkY42OmCLKK16nmO5Js1db9rq37XVe3Vyvdp5UeWG2Mrj+kbdqnafhDXb9npXa3UPvbWOmPfXnfCtOfYobB3wl2ZjA1hMl1GOvB7DIMLkH/PPTPKBmZKQAAIABJREFUr4ZB05uwtYCLAzzd4OOJQD9EBiM5Cpx4FCWhImUVwta0/wLhNBfT2ZhkY5y5elk/zsNINgZZqGOgKRnlIZhsCdGRTEEqaWVw8C10tpcQzcrnZyZHBNa30FrtScoFokVB+OZEJ0TaIdAEbgZPKgZrSU1NTfy2HgGpiJTLrOC1913A90WB71O5/mjJtyPNPNFEIf+oxVnU3v+L5iZUpJCPFuUEoi0Ced6oLdZXaheIuh6IYsMtXw5wXdPUek+nI9LqJnrdKhLRz3h9vviD2fwvSbhnSbBhrPjzZu6GyoyL2qFypZaIVDWlPinRH/HiXqlJ3jJSfHGoaM+ccOdizR5Z3T6l5JBSckQpOaKuP6lpPE1tJ1SSQ/KaI3Lx0ZnqAx25e6oYB8vSLipoinQ0P9ZseO2Z+IgDpFxSKWiJhizNvjO8sZ40U6SkEnaI/nHY6cFoNypLgkmnVskn4qOMLx14y/ziaw6mX80NdapJplnoczV62u0MPM/B8ToWR8Q6mlqYqg302G2l90SQ8atMZ+T5QuCDQmfUCc6TbpAUs431YVGhfyT6ny5PPJUfhZbMrS2cowL2PuVcn45UukWdiK/fzv+qmb+jk3+oPecPKWdTVuRO2YiUtLSoWkqIOWpv/4W712euDgh1QoQ9gmyQHLxhQaUiHdVWxu74FX9deUY9OUkamlhsTrBBqi0yV2ZBncB1QpYz2E7gOa4Gw1xH5DqhwPl/h1AUtDpV2JX8fwYhSX5dlfQXkm6kui/Uorfllc8tF2GUg+5UNMejNhglzii0RaktSuxR4oAKZ1S5QugFkS9qgiAOQWMcWpPQtVKb4T7ybxD+W2GmKQ5tyehiYpCPiQIslEFVvZbEP2jrd604Q+nq9+vqD1LDIW3DYW3DYWo5pG06qGk8oGk+qGk6LJfsm67aNly8qT7rFV4kgu/itiXMjWF6AxZXYXkVxldhcAk3L8LwMkyuw8IIDtZwd4KXO3w8EeSPqJBVCIuTUZECcRrqU9Gahr70VQhneKsQTrAwlokxNiY5q2FwgIm6NHQxIAp8oYVjR2pSamm2ry7C9OuF4UHSaklDRPNRgcdGmwpomcaHu9LvIM0JaS7wNUZu4h5Sz9MCsZgO99NvkJpoTlZXeN7fAbwg5Li/k2IFUVWkWkNyHbV2pMZ5/zhUxdQR9ZF6pJdz/y6aQiDwhbjIljREOkV3MZ9tuTbQEgUF1ktqkslJvZRbEovxrFcWij6a439GFTvmC9cNFb4n5WwSZVuQckpHKlJOljJucQJeaUv7+2D6+oWirfOl70+Xb52r+m1B9PuSaO+S6MByzSFF3TF1/Ulty35Nw1F57TG19NS08EBH/i4p52B+3B89s60qGZGK7I2+zUk3JI1WLadFWkxMMPFyP0c0S0pFvLf+mT9gdgbXd6ImL46URDoi7bx6fJzUi9rxAVoiUpJ2UuFm+IbzebhfgPP1x5d7hkhBS0QLymH1XCfJBxqZpiFWSA9GtDty8lxJQyoVzepmJuQtpJpVjgnLuftrU7dUp/6eHfOjbKKdSEFyErAuVKS92sTf0cL7s5mztzb7F2bYb8vDEtJp5bRIc820NEOLc51lgVHOuGcJV33wQm+qaZGUNNFYHOXwfWOWKy2RYoz6p8qjTRFv/q92PI4j2E5gPYTwP3tiVyAs9fi/AeFmkv5E0p9Iupmk31PtWqXwpeUKLORhgInWRNRHQxiAgjvIs0SJNYptIbi9GgwrPVDtszpI/X+A8N3xvC8m87//L1cU0lA0RaMrGQMsTOVgWQCd8FWq+YwkG0nyK9XvJumfJD2iqT+iazxGTUd1LUfpwUld1ylVx3F562Fl48Fl8d75yt97+J9VJr6R4Im7VrAwwi0DmN2EuT5uXcdfV2B4CX9dxS19mJvA3hquzvDzRqA/goMRE47UKPBiUZIIYTJqU9GQhvY0DGRg9KGH0hwfM3xM8zCRjRE2hpgYYmKAiQEmWuLRlo7yhMcy4nYqVW1q3fzEoKSI4bSs0hJNkIxIRrm5DkN9DSSjB81unnfB8gHTDv4GGO3iapWknu32uPWyt/lHtDSroTnZtDTEGnkur2T4w8cTHVWOtKxVa2iWZtU0REoiNU3PCYvi3hMF4EEg+E4QFdupaIo02uGCslzzbWHmKOReJC3pZESy4uwwdGVjNnftXNGjVPvpfNGGYcF3NfyPSjjXSUVzRFPq+oyMXzPuoSXzy9bM9b3527uKt00X/jYn2D1XvnuuYtd82cGFshMK4WGVeNey+Ji68ayy+dxS3ZmZ6tNDpaca2HsFkT+1d/DVSiKaz2TbtFbmkJKI1DO6ucq61PuJ/qSTzQxX2xj98/JhWF7EpR2ozeaSiibmJpZpkdREKiLNglam0RHR/KzzzbdcLsL9Mm5fg2ykjTQ0r6Vl7TwpZkglq+f5uJohPQm+7uCVGOtIu7hMS7SgoilSEU3NlKUYNqbtr2Pszk3ctTgwSSoiua6ScaYh6aeWzD+6uaeaMo9LMo5nhe+Tj5SRmrRzpKFlHamIZuqrvENc1vjZw/4WEmP2kYpITqQm0tCySq2iMc28KMnrTIQ+MqyRZAKePVjmKHR+Ns8NHFdw7oD7n3JEzl3ku6PIa7X/qTIAoiCIw9AQg/ZkdKevtlbPFT6nqPhQU/MtiX/Q1f2gq9ugqf9J2/CrVrpFK95Etd9Q7X9ohU/ISjHOwwATLQkQBqHIFTm3kWeFfCvk2CHfAUVOENxdHSAWBUAcjOZotMSjMxV9TAxmPzHK+8dY7ueT+d9PFX43U7xhvvSHxfJNEN9DfTja49GbgTEu5gugKgMJ/66tXaer20CSX0m6SytdHRGipiPUdoK6TlPvWV33aVXHcU3LUblk/0LVzl7+2qqklxO94GoNCxOYGcHcAJY3YX4TJtceEmgIS1PcsYe7C3x8EOiPkBDERiAtGtlxqxCK09CQhg4G+jIwylp1jph9COEkB6NZGGZhiIn+TPRl4EEa2tNQFYeMkA3DfflECtItT/TXkY5aW7O007Mkp4lZqUo2TWotj3EwyRlFvshzAz9s8/R04zKRVqMq57gXZ3mpVJpprXZuobs4/je2PXI9EWkHicBPt7CoIxpdapiaayElaeaptpGTEIocPzQEocT3WUmJu4KmdDTSI46LtXjUywZFRUYaBZGCFMPxFYkYZmGu8OMFwdOa6rVTud8NFX7XmLuumneZFkZomUgz11JsUhD9SG3M8+0J30/xDw5xNk8V/N6f90V34Xv95T8NVe4eLv11uvxXpWj/cs0hZcNJdePZJemp2drToxWnW3kHqhK2CsuCFAuzRIqBkRrV3LRyaqJWxFOTemapp7OzgUjWKsk89ycMTsPyPPR2oqbkPukURBP5hYH+Lgb+TmcSom+o5AMqIs38rIPeq47H4HIadpchn+glHZF8lhlxI859U6bH9xlOL+e4Q+CFPDtUc/VJNU9KGu1h5zD1BIlGnfxrVfGoid9al7GjMH0LLYwRLcrl3dkZ3/MikZ/0bi1noyjjJynzT1bw3oWRPKIpBcnFuXez4s8JmMc5AR9z7oBpjhTLxwWhP6tplmhqbkw6PdKo06qJtM2SVEebN/wuINZ41RIh3XT1HJhuC86d1a70FfGd/wVhmS8q/CEKQm3ovyAcyf4XhGrR1ysd9rq6DSrJjxrJZl3dD9ra73Q1a6nmTWU5FoowyEYXA/XRKPdDnhN4NuBYgG8Ovi1y7VDggCInlLig3BNCP9QEoT4KzXF4kIKeDAxkPTrCe300Z+143lcT+V9OF307V/L9fOkPqPZDbRCaIvEgCYOZmORhoRDqUqiq39SKPtaJv1kZdtTW79I27dM1H6DO09R3kYau0oAe9V6kjpOqhkNL1bv78v4pSns5xQ/u9rA2h6UprG/B2hjWxjA3hJkBLIxgaQpbS9xxhLsHfH0RGISwMNyPQnosOPEQJKAqaRXClXvCMSamsjDNXb2ZmOJikoOxbIywMZiBvnT0MtCagdZUtKWhIPzrptIg0izqiOQKFakpOVGvuzVHs0wKrU6jWibVQErQu0KXdyvckekMSYnehLJzmkhFRMtEKlIRTRPN6nr76/wSLFHmhjw7NDT66FSjGuUEl28VHbJfO9tOWu2Sbqas5IYw/aOaMJTde1Jc4LqsXZxVjLW1s5KCfuOxLyhk7aQiWlxsyT/ZlIT5LMwXv7lU/qamav1s7g/TxZu7C76TZB1SPmDSIpGC5rvEooK/hNkX+vI9lmrdH/A2juVsbeO/1l6+fbYjTN6XOtlwc7Tip4Wy35eE+5WSI5qGE3Lp8UXx6Wnh6e78I/UZu3PTrqjmejSkmV9WkZY6W/LCQ6+TVrssX1paWiJaSo41P74X5ldgr4erv6FAEKiWz5F2zNd536FNOL4dx/ZioLt8VqVVzcw6XXnb5wz8z8NRD0ujPTIVUV9H6O3dvlb/8DF7OtP7pVwP8MxRaf5SdZY5qRZpbqlTmsiIOZ4bc/5B7iUp+6Xa5O/rszbzkr5SzPaoaXFirq+o1KCMd7Q0V79OcKI04/N6zlZu6L6l0TIFjQ/rxrLiz/jc3pjot60o/IccF2Rbg2WDuqjfl2lxWd7f13LfyeLj5fFaWiDd/EJJiR3z7saAq2A4gOWATJvVLDTLYbUffWVAhOMAnhPy3FDoiRJvlPqgwh/Vgf87hBN8zBc8Ii9/RyP8Qlv7tU78jU78pbrmO614vbb2a63oY7XodbUQSwJM5aKXgdYE1ISg2B2822BbgG2KbBNkW4NjA7498u6s5sAr/eLScDTGoC0J3enoZ2GI8/Io7/2JnLVjuZ9OFqxbyUhR4YVqf0hD0BqDnhQMszDNx1IBlOVQVz2pFr2tqV2rFa/X1G+hxt+pZR91nafBKzRqQMMG1H+Nus6rGw8rRL8PFn5Sm/5SWgC8HGFnBRtL2FnC3hy2ZrC+BSsTWJnB1hK2tnByhoc3/P1xLxjhEYiLASMO3AQUJqA0EaJUSNLQloa+DAyzVk3WVvpFJzmYzMZoFoaZGEhHLwPdKWjJREsyhrOebEj4uob1FykGNFpSEdHsRHTI5uJCK9KSTElES4s9qTmhaAx8qiIALD8sjOWqiJZJOThQLustUQ6U9/ZlLxOpSK0cHsjwRo4zCuyRm3+DVMukoK7KsGBH9Egs1YvdpCFS00x9UHU0ysMfaSp0IS1ptLS0oKDFJc2SjFREC6QbETRx/t6XgYk4zAieV1R9SjXbZMVblyt+Gy/+tSFjS3+h/qKqQaclhYamtcopxSJpiZal1ZU/DnK/ac15b7T+LsmJlomG2ePCnRMFGxeFuxTifcr6gyrpMVnd8fma0yMlxzp5Bwpjf1OMlhOpNVoiDeXnOty98w1NT+iIiLSkHbO13Kx/ASaX4XQDl3dAUJWilROpKO7uBYNta/46gLO7MT/QoyKi+VmP6+95HoHXcbjpYXm4Xa3TkooWpvtm5rrlS2Pzk6VJ995h+yHPC0VVAUQqhZpm5HMDk13y5UXd/FhPfbok4/NW/qbchO80k8M6HSnUtDg3pJuaVE3LpntY5ayfpdz1RbEHaLZDp6NZIqK+haX55TkNUQc77pVYL3hbojDpxLyKSE3DNYkWlyBgHaUFFcmItOp5SWCw8UtR5kixA/cusm+DZYt8V2TZr3K4Ip4Tcl1Q4AGBF0q8Ub5yVRiC+mi0J6E7HcNZqxDKyv6uFn6iq/lcK/5UU7tWLVqnq/lcW/uhtvr5lRnC2XyMZ6MzCY1RqAhAzl2wbJFpBqYxsozBtgDHCjwb5Ngh7w6KXFDmhUpfiMNQ/9D/uzcTg1mPDnNfHeO/O5Lz0Xj+J1OFX80Uf4NyT1T5QBKEpgg8iEc/A2PZmOU/dDuvgKr6FXXtWo10IzXupNa92p5LNHSTxkxo9BYN3KSui9qGw/LqXUNFa+syX0wPho8zHOxw2xZ3bOBoDQdr2FrAxgJ2VrC1hf1tOLnCwxd+QQgMQUQk4mORHo/seBTEozQewmSIU9CUhu50DGZgjIkxNsbYGH+oERaGMtHPQE8qupLRykRLAsaY6E79UJR6gBZKtKphIoWms5Ad8w0/czcp+kmrJOrpLbtZHo3aOIgyUJO9jdRLpKC5/jJ+/Dp+MHJCkBX7smq8neREk9RWdJTnj2wP9EojSammGZoujY4yR1H0P+c60mhRSUpabI6RJP5DHP/WQIkLqeSkJtKqSEOk0ZJsZrolQ8rZVBCMcSao6Ie50ueU1et1NTvl5b8qq3fPlv3RwfqxLeuX5hbjgV7hgoyWSSEnBWlJMSkszflulP9tC/+tAbENzRLJSN4TP1T201jON0uVW5U1u5SSPQrpAZnk8GLNscmK40OFhyXpPw/UBpJqaCV1jAnb6WT7+GyHgEihUo+PDBboX3vd8BoML8D6Cq7uR1X1fVIRyZYzvC6ZbIfJbthceIEmB4mmaaorxPgj90PwPIYAQyj6hESzpFASKbQaIg3pliaCPT9J9EPyXQiqHRXUrSaFimRqkhERqbXjPU1SxufdOVvErJ9ppodIRloiWly5mVRPVtTw/mjgbqxIPEJjYlIrVESL8gGlkjQqIhpMjfkgwg+hHqjgnlBoxklBqjp2tBUindBR4i3r7iXFIvUnx1i/E22BJBtkO4FlC4YFsuzBtgPbDln2q+LcWT0WCjxQ4omylVuKhxB2MTCahUku5vMhL31DW/mhVvSxVvSxpuZ9nfBjEn2gE72oroSiHEsCTPMwmI7WOIjDUOIJjgMyrZBphkwTZBqBZQq2GbItwLVGjh3yHVHijnJviEJQF4mmOLQno4uBPiYGsx4dzn5+mP/uaO4Hk4WfTRevQ5kHKr1RF4DGULRHozsZQ0xMZGMpF7JCKEugqoJK9J5a8i01baeWfZreqzRkQGPmNGxKA8bUqadtOCyv/m1E8KWE+UZmMPxc4OSAO/Zwtsddezjexm1b3LaFvT0c7uC2E5w94OWPgKDHg0IREYmYWCTHISsOefEQJKA0HtWJaExGZxoG0jGYuVqGGWNiNBOjmRjMQD8DvanoTkFXMhoz0JqIURaG2O9KGF9ONFsPNQSMSGP7C28J4r8oZ3wzWOsw15k8XOvSyNzQzkB9Cuo5EPPXznXcHa316OQfL/JFlT+qA1Hsj1HBhZFqm4FK5+6ybcXhKPSDMPXQqNCqp+DCWMlOUSiE4Wjif1FfvGdCbDdYvO9B5mstqZ/08K9N1YX2V7uNNdv1Nrh0VFnUsvfVMv/ewEYvFwt8KDkblys/1FRvV1f9vlz1g6J266Lw+FjR/r6iDW2sz5pZ53tLnQabLHskZuOVXpMF1g9Sf5jK29bCQX3OP3uEZkM1jg8E2zr5L4/lfrlQtnG58idlzQ5F3W65ZP9S7dH5qhOTFcf78rc0cm/2SMI6JNHdtVHJwd8FuiMr8SKX78Xh3g4NO3hVD9cuwvwmjC7A+DwCArZmZ7olR910MnrdaA9M9uPWKWSG3chNsSi97+B95Smf0wi4CO9rEESbVGY41CbbCVMNK1Ju1aa4PeA5s11f47uiwhuFCZ8PV/81KHIcrXfrq7EZb3CclNqOCG91Zm0bzNnWmr1usTFiuM23qzm4r91+tCFwtD10pNGutWB/X9HRRubJ0VqPbolXe6PLZF1Ef63PYL1zV6leYdCHWQ7I80JZ+JNtzec6cq36002ybiPGFlEOKIjfK+Gdr004Fm36dLIt0q2RYQXubbBtwbAEy3aVwxVx7oDvjDw3FLtD4IFSH1T5oeYe6qPRloguBkbYmORiPg+ykhfVle+qqt9Ri95WVb9CVe9S1atUBVUZZMWYz8UYEz0JaIyEKAi5LmDaIs0cabeQYYQMQzBMkG6CTFMwzZFlBf5tFNxFiScqAyEKgSQKzfFoT0ZnGvoyMcDEAPfVYf5bY3kfThR8ilJ3VHg99FoOXw2Goyws8LCUC3kRlOVQVb+prftG17CDmg9q+q/RsDGNWdGwFfXdos4r2obDCtH2keKvpax3mCHwd4GzA5wc4OIAVwe4OMHJAQ534OgERxc4usHNGz73EBDydFDYU6FRiI5BYgwyYpEbh+J4FMegMg7SBLSnoPchh4OZGE7HcDoG01ZXKXQnoSsZXcloTkUXA2NZmMh7u5X3Zkv+V43ZPzanbKtnf9ua8cMD5uetzPfauZur4tZ1s94f42OU8X5v5iv1TNSkoyEVHQnoTsDkSjNuLJqiUROLomhUhUMcDKn3Y3leKApDfhjqktCVgp4UNKWgLhNdmSvbRZ7pYLzanb2xmbFeGPViU/LjBdGojn+hi/VmPwsjXExwMZ/3krx0vVr4DdUcVIn2yOu/VTZuX6q7uFBzYaJmy3zhz0Ocn/v52zp461pY7/dlfTfH26HK2zVfsKuP92YjGxIW6pioz8ADNiZyPpgt/GqxZP1y5Y/Kmh0K8V5Z7Z/LomNLotPjldse5FwVsg7y4j8pSdhRkvhrUvDfPFye+cvkRQMjXLmC61ehfxU2ps8ZXsUtfVw7i/PH1+z/ExfOwOgIbl+A0WFc3IWbv8H20Os2R+B8Cm7n4XASdw4+Yb0fdvtx5zC8ziLwNNJMwLRAtjUq3V8u8kJNJEqCUBv3niTpzQfct7p5r4/kfjpW+PtkweYB/svD/LNC1johd6OI/2ILe0tz3o9dxb8NlR2eEJ7rKzrcmfdHHXNjecrnpYGfcQLACADDHcVuENx+QuiL8gDEeYLvgxxbdCa8w7yDTFdEWiDRBnG3EG8KhhXYdki/Ba79k9zbyLQF0wYsW7BswLIB2+5hRroyjeWBUi9U+qLmHqSRqxCueBnP50EheFFV8aZW+Ja2+hVl9dNU/jxVQF2K5ZUVDBwMpKAjCuIQlHkj+zZSzZBohCQDJN9Eij5SDJBigFRDMIyRYYosa+TcQaELin1QFgBRKCRRaIpDWyIepKArDT1Zj/ZznxvmvzWa+wFK3FHuhRpfSAJXHUR6UjCcjoVsLPEhK4S8DErhSw8hPKQduE4jJjRuS8PWKxDqGo8oa3aMFH8nZX7ADEGA678gdLsDNxe4OMHJGXdd4OyGu57w9IN3KAJDnw0KeyokElFRSIhCegxyYlEcj8IolMdAnIC25NVtXgMZGMjAEAODaehPRncyuhLRlbgKYUc6+lkYYGG04Ll+weMdBZgq+Q9F8fpuwbsLgoNT3G9nijCej5HcT+VV30zyIeNgjo3ZnMe7GZjnYSr9zYEMtHPQkYUJJnoSMM/FMAeNAZhOw1AEuuLQGIPGhMdq72EgHnMsDMRjnvfxDAMzLCwWvNbDwnTpW6P8V4YZ7y4yN04VbB5mrFfwtk2nvqPN/1RR9Jms4p+LtW9oRZtIfEIrPUCdmzRdu2QN+gtS/fG6X2bFB4fKdw+XHxsQnBoqOTBRsWms+PPpkvXz+dtm8zdN5n40yEVPJnoyXhxgvzLMx2TuP2cKPlso2yATbZGLf1eIDyrEx5V1Z6drdk5V/tVZvKur/KWGjC9qU7anhr4QF/+Ul/cTZpYws4CBAcxNnzbSX3PL8HHDG7C+jKuncEEP1w1wZs8TFsdfvn0BVqde9D0L37Ov+lyF87k1bnrwuQ7vkwi7iLt6CLVA4A3E3ADDAhmO4PmD5w9RDBrTIEpAF3dDL//H4eJNA/mbZsuOTpRtni/7Vl3zvqLsYk/e+rGKP8fLNi8WX5LVHJ+rOD1VdXa88tB07a6R8p/H8veOZp1syPy0LutjVjRyY5EbiJJA5PkhPxxVoWiIhNgf1d6o9AXrDordX842A8MWHEekmiH3DjKNkWkKhgUYtmDagGmzCiHLFln2q8fCVWP1/xlCueBxVcUrmqo3NMJnNMJnqPQxbRkUxZjPxRQHo5noiUdrCKoDUOSGTGskGiPuBu7rI+E6Eq8iUR9J+kjSR4oB0ozBtADvNvKcUOCBYh9UBaEmDNIoNMWiNQGdSehkoifr0QHuq0P8f6Dcc3XrgCQQjcFoi0RXPAaSMc7AJBPzPMiLoK6Eru4zavxd13ySOi/QkLFuyk4zYU6DV6jzJDUcUIr+GClYJ057NTMIwW7wvAtXZ7g7wccZTu5w9sBdTzh7wNkTbr7wuYfAcNwLe+peOO5FIjwa92ORFgtmFLLCUBKEimBIw1cd1gaSMJCKgVQMJKEvAT1x6H6oB/HoWOkATMfoqgXbm/LizzRlm6hiq0Lwi0Lwi6Jks6Jko1ywYVnw5VLxusWitbKiZ2f4GOdgiosZ/uqKixk+FtiQcaDIwjIT8xmYTcdoKnqT0BONrkh0RqA7CoOJGEvHJBNTbMj4WM6BMudvypy1cv5XMv4XC/yPFvj/kPG+Wc79Ul7wmbz4n7LST2QVnymEX6lrNqjrftVItpJ0J9X/QQ0HqfEINR6lxpNy8UFF3Z/ymj9lVXtklTtVVTvklT8uCb5ZLPpxOvfzcf7bo7wnh7LRz0I/C8PZr0znvTNX+PFy6VdK4c+6mt+14v068SGd+Ohs7YFp0d7R8t/6Cn5q5n9XnfUZL/n1lAh4ub1gZf6YgeGL+kYvXTZac9kE+rdw+QauXsaVS9C7iGsXYHwBludhfxaOZ+B4Hs7n4HoO7ufgcw5+ZxFwDgHnEKKH0CuIuY4EA2SaIfcOSr0gCkRzDDoS0ZeOEc7fpnPXLhT/IC/boarYJ6vavCT8ebnq1+WqbYvCnYvCPQvCfQvCfbKa47Kao/LaY4q6Y4q6wwvCPeOCnwfzvm9lf1if8ZgwHkX3kOeOAjeUeUMUCOk9SO9BEozaexD6ocQDBc7IcUCePfg24FiCbQGWOZgWyDRDhikyzf71gGWBbBvwbiPnDvKdUHgXpZ6o8oU4GM1ReJCIXgZGsjHFxUIe5MXQlEJbBiqDrhRUCiqEgo95NsYZ6EtARzgagsD3QeYd3DdFrBFiDBBxHWFXEaGPqCuIuYbY64i/gQRDpJgi3QosO/BdUeAJgT8q76EqFHWCN9AzAAAgAElEQVRRaEhASwq60tCXiSH2YyOct1YdtVbsJeuD0PLw3z+aiolMzHKwXABVBTS1a7X127XNR6jnIg3/pZmw1AybaLrPU8shlXj3fOVv42WbxeyPGGFrAn3g4g5nN9x1g6c73L0f8/B5wtN3jYcvPHzh5Y+AkEeDo56KiHorLOrFqOhHYuOQHI/MWHCjwAlHbiCKglEVhoZotMWjKwkPUvAgFd0JeJCAjni0x6E1Aa0JaElAczweZKKbjUE+xvMxI8BSxfMK4Qdq0TpF9SdK0VqlaK1S9LGi+iN59Xsy4Tsy4TtLJf+YysUIFyM8TPAxkYMJPqZyML2y3iwHCzzMcDCZjUEWetLRnYLORHTE40ECetMwxMQoB2M8LORjuRByAZYFkBVj8aHkBRtkxRtkpesVFd8pqjYoRBuV4q0a6U5V435V435145+apiPaphO65pPUcoZaziiaTiuaTivrT8nFR+U1f6rEexWi7UsVP04V/304D3189PDRyUFHFh5koYeHodz3xgs+nSn9frF6u0K8TyU9pmk4pW04uyw+tlhzZLp870Dh9lb+phrWOm7CW4kh8PV6zsbmCSPTlw1NX7t669Fr5tA3f+Ka0WNXbj6jd/OxyzfWXLsOw+swuw7bq7h9GXYX4XAJTpfgehmel+CrhwA93LuMkBuINECMMRLNkWEHvivKAiAMQ2MyWhnoysJALsaKMFX21nzl58uiDbLaHXLx78viP5bFe5frDi7XHZXVHV+UHFc0XFY0XFA2XlQ2X1A0nVmUHJuo2j0k2NrMXyfJfqMyGUWh4Hsj1wsCf1QFQxwCcQjqQiEKQWUAir2R5wqeI7h3kG0H5oo5gCVSLJFijmQzpFkj1QqpVkizRrotmA7IvguOy6phQrEXKv0gCl714X6QhoEsjHIwlYv5IshKIC+FqhTKEiiKsJCL6WyMZqI3BW0xqAuB0B8cZ6RbI8EI8TcRe3NNtD6iriPqBsKuIOwKIq4i4iqiriPGAIkrzssO4N5FvgcEvigNRHUI6qLQEIe2ZHQy0MfEAPsVlHmiwhsiH9T6QfJw8UBnDIaTMMrAdBYW86Aog6bmfa10i6ZxL3Wcon593ZilbuQW9V2i9mNa6b4F0e/9go2VGe/dvwcPD9i5wPYu7F1x1x0eHs96ej7v5f2ch+cady94+sAv8Il7Ic9Fhr0bGf56RMTTMZFIiEJaOJjBYAUizQtZPsgPQHkwxOGQRKE+BvUxaI5BY+yqGmLREAtJHCRxaM5AOxvdPAzkY6wY02WPLlS9u1z9mUL8iUL8ibLuU2Xdp8q6LxTiz+U16+Q16xZL3p/IeWowG/+pEQ7GeJjPh6wISgEUxZAVYqkAK6z2pqIraRX+zkT0MTDExHDWqtPUfBEWBVgUYKEYi8VYEkBW8q2ifIOqcpOqerOq5ldV3Q51/T5twyFlyylF80lF80l50wlF80llyyl12xlN+1l1+3lN20VVy3ll/SmV9Jha+qdKvHu5+pfZig/Hip8YyEdvLrpz0MlDLx+DBejP/2SocN1E2cY50c7luoOyhpOKpjOKpvPahvNq6dll0bGpsn19BTvquRsLU/6DEf78XTeYWULfCHpGT581wDlDXDbCef1HTt948eT1509cf/T09UcuX8ONazC5ArPLMD8Py/OwuQCHS3C9BA89eOvBXw9BNxBsgEhj3LdA+m1w3SAIQGUYHjDRyUF/HsYFmK58akH0wbLkW0X9Zrl0j0K6X1l/UFF/WNV4Qt54WtF0Xtl8Qd12Xd12XdN+TdtxRdNxSdZ0errm4Ej571L+p0LW3woTwA0C0wNsN/C8UOAPoT8qA1AViMoACHyQ7wauE7IckGkPhg1SLJFojgQzxJsi7hZiTRBrhhhTxNxCrCniLZBojRR7pN1ZNXfOcUGhB0r9IAqBNBqNCejKRD8bIzyM52G2AHNFmC/EXAEmczDKQV8GOlLQFIfaMJT7ocAD+Q7IsgLDGMkGTybceCb6+uMr4K1AGHIZIRcRfAkRVxFriMRbYFiCZQ/eSs+ANypWzofRqE9GSxoeZKKL/QIqvFHpgxpf1Pqhzh/199Acjo4o9CdiNBVTbCzkQlUKtehtkvyga9hFzYeoR49GTWnEhPr1qP24un7fXPWe/uJvhBlvJ96DtzucXeHkDjdPePrA1+s5f59nA3yfD/B70t8XgYGPhoQ8ERn5Umz0OzExr0fHPBYXjcRoMCJWIWR6g+eDAn8Ig1AXCmkkGqLREI3WmNUNe23xq2GwJQGtiXiQjh4WBrkYz3tmuuithdLPZBUbVFW/qCu/01T9oKn6UVf1i67qV13VNm3FDm3FDl3V58tFr07xMZ6NETaGWRhjYTIbE5lYyIKMCyUXyxwscTDNxggDEwyMpmAwAX2x6I/DUCLGGZjKXD0zy/OhLIa6GJpiaAVv6orXKgUfqso+1las01St11b/pKvZrhX/QZIDmsaTmoYT6vojKunhlVVwKzNKuuaT1HKKGk/pJIe14v0k/kMt2qIo3zCT9+UY94MB1uO9mehOR3c6+jIxwnlrLP+TyaKvpss2LFZvXxb/oaj7Uyk5IpceX6w+uCA8MF22e7Dg13b+xurMT7mxL98PxF1PmNrghumaK6YvnDXGWRPo3XryguHT5wxfO2v44nmDJy8ZPqJvBGMjWBrC9iZuX4HDVThfg+c1+Ojjnj5CbiD0JqIMEX8LKZbIvA2+K0r8UBMGaQxaE9CZigEWxviPzuS/uyD4Wl7+s6pyp7p2u0q8S123RyPZr6k/pK0/oWk8rW06Qy2XqeUytVyktovUckYlPTwn3DlR8ktj7gfirGdK48ENRLYbOC6r0aMuAJJA1AahNgjV/ijzQrErCpyR4wieA1h2yFwJfRZIskCiOe6b4b4Z4k1x3xSJFkixRpod0h9a5hS5oswT1QGQhqElFh3JGGBiNAuTPMzkYakQS4VYKsBiPmZzMMrBQAa6ktEcA3EIyn1Q5AauJdhmyDBCmgESbyJOH5HXEHoVUdcRcRUhl3HvPO6dR6geYm4gwXjVQ4zjiDxXFHmhIgA1oZBEoT4VzeloZaOT8xyqfCH0Q60fxP6QBKD+HprC0B6B/niMJGOSiUU+lCXQVj9Pkm+oYQu1HabeSzRopOu5Ru0nqfGgQrx3qnr3UP6nouSnkvzg4wwXR7g4wd0FPm5wccdKAPTyg5cffAMRFIqwaETEvBgeg7BoREYhLhIJoUgORKov2G7guKPIAxXeqPWHJBCSYEiC0RSIlntoDUdbBJoj0RSBlii0xKA7BX0MDLMwwcU0H/N5Ly0XfqQQfE5VX5LwK6peT8KNVP0TCbeRcDtVbaOKD+X5z09nYzQdAynojUdfAoZSMJcBRTa0fOj4ID6IDxUPC2xMpWA8AUPR6AtDbyj6wzEcg/EEzKdiIR3LbMi5UPKhWXlhzlNU9ipVvUvVX1DtBhL/SnU7SbqPGg5Q6wlqOU5Nh6nxT2r8k5oP0orjaMtRaj1Bzcep/jBJ9lLdTqrZpKv8Wln49WLOB1OcpyeyMZ6FcTamuS8v5X60UPz5Uum3iqrNuprtJN1D9Yeo4RDVH5bXH5BJ98+Jdg2X/tKe/60w+yNOwmPxwbB3hZElrpisuWDytxOGOGmE8yZPnTF4ZiUd1bsJfUOYGMPaBI4mcDGG61W4XYPnNfhdQ+A1hOgjXB8R13HfAGkmYFkhxwECN4j80RiOtlgMpmIsE1M8LOavUZS8q6v8mkRbSLyLJDtIsoOku6hhPzUdpuZj1HKCWs5QxyXquEQd56nj7Mr/R17921zpj02cx8VpKA4DxwMsB/BuI98JRW4Qe6DOE3XeqPOG0BMVrhA4otABfHtwbcG2BNMM6aZgmCDZBEnGSDDCfUPcN8R9AyQYIckEqeZgWIJtAa41CuxRehfVnpAEoiUCXbHoS8TgyqqplcU+2ZhlY4aF0XT0J6MzBi1hqAtApQfyHcGzQZoRUo2RaoREIyQYIdEYsUaIMUTkDYRfR/BlBF5A4AWE6CHqJuJNkGYBpi24Tsh3Q7E3KgNRG4b6GEgZaGKiPRud/Bch9EO1/+q+gVUIQ9Eegb5YDCRhIhMLfCgF0FU/QnWfUf0m6jhE3ed0Pdc0HZeo+Rg1HdA0HV5sPDxU+HVN2ltpAfB3hYsTnJ3g5gwvF7h6wd0HXv7wCYRvEPxDERy1JjzuufCE10ITng+PR3gcomMRF4GkICT5g+mGbHfku6PUczVEV/tDFICGALQEoyMcbVFoi0JrJFpj0B6HHhb6szHMx3g+pgoxK8BCKZbLHpWXQVEOZcUjqsrn1JWvqSvf1VR8oKn4gKq/VZR8OMtfM8pCbyq649Edj/5kDKVhKhPzWZBlQcFZjYcrv8dUBsZSMJSA/hgMxGI4EWMpmMrALBvzPCzxIcuFJh9UACqCrOhZZcnbmvIvNFU/aKu3akU7dDW/a8X7tNJ9Wuk+jWSvum6Pum6PRrJXKz2gqz+okhzQSf7U1h1U1+zVCHdrq7cqyzcsFq2dLXhunI8hzr/S5lEepnIfG+d/OpX79XzRpqXyXxXCXaqaverag+raQwv1B+ck+8eFO7uKfpTy1xVm/CMtCiH+sHKCvhkuGj17xuilIzfXHDPAWZOnThu+eNXwyauGj143xE1jmN7CbVO43IKnCdwN4G0AP0MEGCLEEBGGiDZCjDEyzMC2Qu4dlLihxg/1oWiPRk88OtPQx8QoDzP5mC+BrOJplegjbe06tXCLpnqrqmaHeqV6JDlM0uMkOUmN56jxLDWeosZTmvojspo/pkp+GcpdX89+rCoZeffAcgHLHtl2yHNCkSsq3VDljmpPCL1Q6QGBKwqckHcbPDtkW4NljgwzpN9Cyq1VCGMMEH0TUTcQdR3R+ogxQKwh4o2RbgqWObi2yLuDEjcI/VAfipZodMWjOwn9DIxmYpSFcSZG0zHCQG8iOmPQFIa6e6jyRbErchzAtkaqNRi2SLNBiiWSzJFkjgQzxJkgQh9h1xB8GUEXEXQRoVcRbYAEM6RbgX0b/Lso9ESJH6qCUBeJhjg0MtCaifZsdHGfgtD/v4ewOwp9CRhlYI4LZSGoClT7Pkm/pYbf6cFJ6rlGnXrUcoIa9y+L/xgR7uzI/6kk9ZPYoOfd3GHv+thtt+ccPV686/mqi8/L7v5veN570yv4Te+Q13zDXw2K+UdowrvhyZ+GJn8QlvR2WOIzkXGIjUJCCBICkeoFhjeyvJDrhQIfCHxQ7I9if4gCIAl5ojHqhabY5+pjH5XGoCEOjUnoyEIXF305GMjHUCFGijEueH6y9A1Fw9eKhq9VTRvUzT9oWjZrW37Rtvyibdm6WL19smR9f84HXVkvtqShPh718WhORjcLg1xM8jHHx0IelgsxX4DpPAxmY4CNvkx0pqI9Ae0JeJCErjT0Zq60AmJsZX9wHpYLIS+GSvKjqmG7rvkAtZ+kjkv0QI+6r1LPVV33eV33eV3XRV2XHnVfoe6r1KVP3TfUXTd0PQba7pu6B/radj1qP6dpOiKT7J6s+H5EsHaw6K3B4lcGi18ZKHxrRPD5RNn3c8KDizVHFNIz2uaLurZr1HGTOg3owV/LrVcXmi5Nik/3lR9sKtxZzt3ETv0kOuIlG+enb1g8c/nW2+dN3zlq/LfTt568YPnqJbM39czfvmz22iWz56+bPWFs8YSV5SMO5nA2g7sF3C3gbQk/K4RYI9wG0baPxto8lumALGfkea4pC3hkpbrQFIf2BHTw0J2LIQHGKp+bqv5gQfzNUv0WWcNObcc53YPzus7L1HmNum7quk2ox5R6zWjAmvotqN+CBsx1vX/J269MS08MCw9UsN/MS0JGIJLuIsnumQz7N7OdX+a5P1Lg/kSh55pi70cKfZHvDb4HOK5gO4Ht9Fjm7ccYtkixQbLVmgTrx+5bPhlv8USEOcLNEGryWLDRmmCjNSHGa0JvIdwMsWZr7lutSbN9KvPO41mua/J8IQhGeQQksU83JKI5Fa0Z6MhAezo6UtCW9ERjDCQRqA5BeeCjRb7P5ng8y3Z+Iv32mngbJNqvSbZHohUSLZBsgVQzJJkg4gbC9RF6DcFXEHwNETcRZ4YkG7Dske2EPHcIfFEWBFEopDFoSkQzA+1MdHHQy30OVX7/Skfr/CENRNPKEqwI9MZiJA0z2ZAXQFsBqn2L6r7QiLdT23EauEF9+tRyQlb1azf3i6qU99iRH4Z6PmNpCT0jnDHGmVu4aL5Gz+pJA3P8ZbXGxPaRW3a4ZQdTB1g6w8Z1zW3vN+y8n7Pxgp0nHN3g4gQ3O3hYwdUc7ubwM0OwGcIsEGWBCCtEWiPeHCk2YNxBhhPSnZDqDIYLMt3B9gUnAPx7yA1FfhgKwh8pjnipJOqNwph/FMW+Wxz3XknCh2UJn5QlfFKeuLY8cW1Fyn8Uxb7JDQXTH8nuSHBEohNSXZHuAo4n8rxR7I1yP1QEoeweBP7ID0CeH3K8wXUDywlMR7CdwXEF1wN8LxT4osgfpYGoCkZ1OCRRKIpFSeKLFSkfVTG+qczYWJm5qZz1Y0XWj2WMT8rTP6/I+KoyY31lxg9V6Zur0n+uSv+5KPOnUubWUubWkvQtZYyN5Yz1pUlrC2LfLI76Nj/8k5zQv+eGvZkb9mZu2Pv54Z8Jor8vjv6iJPar8sQNVSk/VjK2VDG2Vqb9Wpa2rYqxVZi6pTR+Iz/8q/TgT2L83/FyedzeBtdNcfoKDl967sDl53ddwK7L+PM6/ry65o8rz+2+8sSey4/su4zDejh/GVcu4toFXL8E/csw1IPpFVhdw+0bcLwB5xvwN0TwLURY4b49UhyReRfZbuB6IMN31S8zL+rZwri3BQlrS5LWl6f+VJa+vjzj+4qMjWWZv5Qzt5WzdlWw/6hg/1HJ3V/J3V/B2VPB+b00a3s+YyM79ovU0Hdj7iHEHe6WcLgOx4tw13vUVx+BxggzQagZwi0QYYUwSwSbwc8YPoa4ZwQ/A3hfh9c1eFyFx1W4XMFdPTjqw+Ea7PVgewk2F2F7CXaXYX8FtudgfwHOl+G2sjnTDGG2iLqN+45IvItkd2R4IdMbmR5IdwHjLlJv474tYq0QZYFQMwQaw+sGXK/A9Qp8byDQEKEGiDJEkikY5mvSzRBtiCiDRyJvImKljHwLSTZIu41sJ/BdUeiD8kBUhqxeUbSmoiMd3Sz0cDDAewEiH9T6QOwLsR+kvmjwR0sQ2kPQF4nRWIzFYI6N2TIsV4IqfqBakOQVGj470e8YydDfcvFrbHganz2CtY/gy2f+f+HLZ7Du6f9e/9Pzv3jqv9f/U+///5b+p+/1/5XP/z/ps5fx5av49hV8/RzWPYHvnsKW197Y877bxU/v2yHeFP+LvfeOlqs8D71/Z8qePXv29Dm9nzNzZnZ5t3ad4iMJg43NxxcnWbnJvTc3dnKT3Ng4jgvYdCG6aDJVyHQhAwIhBAgVegfTO0ICUdQlBGoUUWyY+8cZGa+Ew3eVRZZjf3et549Zs45e7ffd7+99nvdpc9khLDym8+qZXHY0S2epd57GvWfx0Hk8diFPXMQzl7FyPi9fy6s38sbNrF3K+mUFHp3d4vCJn7cgfPECVl3IqjlsmM/WX7JzCbvvZ/c9fHpfqfm43Hzjvz5997f+/O/CdEARvDS6hJ/5/a/OfxLZ1032H/33/9nW4Q/l+SeVAk4OJ4MpU2mjAmYYVxZe5H/+DeceycKZXPVTbjmBO0/lrlO5bzYPnctjc3nqYp69nBfm8/K1vLaI129m3S1sXB7ZuCLHr87gkbN4dDaPz+aJs3n2HF44n5fm8vx5rLuG9dfw9mLevZvtt9F8KNN8avjWO78z/a+gC8w4jQG0BBWFoPP3vTR/sPIHvyn/fzYvU219sGWEhBnBjCJk+sANffufUtefm114JA+ezDNn8+hZrQTupy7l+Xm8eBWr9tZSrL1loh1wfPNtndx/Og+f3kLxsbN48hyeP4+Vc1g5h9cX8MpVbFjAntvYeSvNp/j1417tOz2UQIvyVQ2jgKZQ7UT7fS/NH678sW7WP9Z5mRJCQkg4Ml4KP42fxk3h5xlQ2qdGLzhdWn4aT57B42fy2C94dC5PXMyzV/DClay8mpeu5bVFrLuZdbdM/DpF9M3burn3FO47tYXiI2fxxM95+jyem8PqC1lzNSuvYt3V/GYF767gN8/y7A0VDLCTVJKMKugqhowewVb/wyf/xyp/rJv1j3VebqKlA40YQsZSEXFMha92Uu5klH/6PsvP48kLuH0W91zB4xe1YhIrr+Kla1h1Ha8tYu1NrF/K5uW8dVvirTt6uPMk7jl5L4dn8OjsFoSvXsiqebx0LRuv5dNbeHcFu5/m/OPi6BF0BbtArYtqBiuMEf79L81/HrHVz5c/lPH/0NfnP1q8FLaKKWPEMBKYCkJBxLHb8HrQ5Oo3ue4sHruIW89k+UU8eUkrP64F4QJevZ43FrPxFrau4K07pJ139XP7CdxxIveczL2zeGhv8+BnL2Ddhay8hNUL2XgNH13btns5b73IP/89DLVh59hvBCNGAawI+w0wIv3+V+c/ifxfCP/on99KYqUQaUQaO4OTxEuhh/Cy2O1Zr+3iUzoePp+HzuOOc/Zqwnm8cCUvXMmLV/HyAl69nnU3sWkpb93atuPOTm47nttP4K6TW63aHjmLJ8/jmTlsmctLc1m9kLXz2H1ZaPdydr3Bt7+dphim2omZxpSZ3omIMBiiUfz9r85/Evm/EP5xP7+VxcliF7CzmGl0GT2GKdPooxJBz2Blf3HS6AOzeX4Oj57FIxe2OHzmMp65jGev4MUrW6WMa29k81K23ZrmtuO47XjuPIl7T+G+03jkrNavIj8zl9d+wctX8NYv2XATG5fQ/BUHfA+KYawktooRw0m0VLM1+SKWO6h0ohUQGWwFO4YZR1OohnDDiDh6Bj2HnkFTqcTQVewMbh4jzWiK0SRGEj/92av6V7eLUgazgJXDiGNEEDKGSlGRKgVKOUp59A5EO1YWoWDF8FXcJELFVDFVhIqbxFfRZUoSlRSiE7sbq4CpYk2yY+y9//zfihOjHMHrRM9jFPC7qCRxOiYdx01SUtBSVPO4GUYUigr1NJU8ZgGvHTtHOcWogqbipvDjuApCwYhjxDBlrCROFj+FqVKKUY5ix6jG8eOIOJ5KRUZLYWYxVKwMVgfF7KTvS+TxOvDaERlEGrcdpx0jgynjJHATWBJWDC+Nl0YkcXPoKUoq+sTjqVhJKolJ5zsxpkiiJXBy2AXMDKJApQstj5FExBEqIo2dxf6C58wgMpjp1gehYsTRJUoxKgpGBpHFSiEUbBUngafip3CTmAqlOKMyFRlTwSngZLFTezdYEjuDlUWolGVGZEZkKjJC+aJNbikYOUwZuwOPece3PXAmt5/Hg+fw6Bwen8uTF/HkxTx1KU9fxrPzeG4+q6/ltUVsuJkty+DWGdw6s2WR3ncaD57ZKvB99kJe+wUvzeOtX7LxZjYuofkIX/93QFiP4MUQCsbEpo9jRTHb8BTcBE4KJ4Obw0/jxwkkLAlbxo4hJmLWcZwYrvTZYfm7BNoqXhYvjavgRvDbqEYI4jgxpkaoyrgKroKtYqYxklgKwxHKUSyJQGr9d+UowxH8KE4MS8HOItIYMUQEL4KX+nxxk58vjRAmuEk0BV3Bz2CE8ORJx/EjmFEsiYZMNY4mo0n4Uewktoqj4Mg4Mk4MR8KPoiXQZYw4toqbwE0gkugq+l7vuZPAVbAVjDiVBIGEHcVT8FVEFFPGTqEnJn1fEweTqaDH0GVEfK/vQcZSPvveVDGTGCpuBEdCTEThZSypJZPN14xiqxgyFQlLxVYQUTyZSgIRx5PxI7hhLKkV2Z/0cI+iS9gSroQXw1NwkjgZgg6CPEGKQMGX8SREFDNMMY6ewFWoqlSTBCp+Aj9FOYoWQ8SxFWwFU6YiUYpQTRIoBApVlUDBVTASlL4Ywih2By5XzOS+07ntHB6YzcPn88gcHpvL47/g8V/w5CU8cwXPzW/1fVp/E1uWwdJjWf7bZomzWk1LnzqvBeGqK9l2NZuWsOkWmo/+uyCsSfhhnDbsME4ES0Go6CrlMFoUQ8aUMWQMueX89cOINkywIwQyVQVb/WzT/K4anDi6ajG8MBbYbbghXAk3hhvDj2Ip2BF8cMEIYSRwY3gKXgJPxUniJPFUvASegoggoogoVhRzwtsk4SeoSJ8vRuzzJZAR4EQwQIQJFEQEe5JBKhJOCpHEUggkqlEcCSuMA0EUN4IVwZaoytQUPBkjhpZGVzGTOBPbOo1Q0GRKMUQcP0WQxs5QSaGnEBnsJHaMQCGYcKpFsCXsyX1pXht2CBHCjGBO+ADjLQ2pZ9AyaGmMJIaMiGLHMNtwI/gyjtzi045RlSedr4jiJhFxdBkriSljhPFkrHBrHD+OI332Lr5A+bQOPgU7iphYqyhCwgihtVEBI4wZwYigRxiJU5Yx43gKQaplW+kKtoybIEhRTVNN46t7A4BxHIUgRS1JEMdRMBW0yfe5mUZEcTrw2n4xg7tOZfls7juTB87hwYmSyAt4ZE6r/uu5+axcwCuLWHczm5bCkqNZeiy3nsCdJ3PPLB44g1+dzWPn8dRc1lzM6vm8vYCNS9m0jOZj8tcO2XcItQRmvHVcOTJWCjODUcDoxOrC7cDLY6uY8b2bWEKE0cIIGV/FzaB3JEa7JoXQjSBCmCHMOFqCkkJJxcgxku0ZzlCJ4YMPeohKEjtLXcaNoUsUoxSj6BJujLpMJYM2MZcwVhgzjp5Gy7fu3/9WnOznSymFpuDEcELY4ZamMnKTjqP3oHej5TBl3BhBHE9GRPHCWBLGXqXn5TBy0nAWN4OTxE4iVIwkhoql4igIFSuOo2ClqKQop7BTNLJquZNyEpHETlKOocVwZOzJ0wzr4IEbwldbBqeZxMlidaHnMfLYBYAk9lAAACAASURBVNwMjoQHNSgmsZIECq6MGW/9cTD5fK0JGzuFpWCn0BVKCqJANYQrYybR8uh5RKZ1fZj0cI/iR7FldLU1Xy2NnsEqYGbR0lRSaCoijhejGsVSMeKUYpQVdBU9TTnFSAongZNoqXpzr/FlKxQnjps0ptoyamwVL/X/DaHL3KO57QRuPJ27TuWOs7j7LO6ZzX3n7O34dPleCBey9iY2LQ2x+GhuOpYVx3PHydwzq9WE47cQrrqabdexeTmbl9N8LH/gIfF9hrAoYyRxCtg5tDSagiNRj7ROID+Bm8BWEUmMJHoaO4eRoBLDnDBKJYwkZvtnA/4rc1RXEemWTWtmqaTQEzhJzCRaGitJNU4Qx0ii5THzFFXKCYwEYuJmlaCcoKji5nGyWBP3wBRWCj1FUcZTP18mm++ohJ0iUPAURBwjjlDRpUnHEe2YeTSVchRDwlNxMlQy6CpmFjOPnkDEWzMqqTjgRnAUjCSlFKUUlkI1jq9ixzBUtDTlLGUFK0IDjGRrZEtBT2DkcAqYk5t5bgw7hpskKODnsZNYcRwZO9pSfROXK0fCCeHCaAdmFjeG24Ydwo1hq5jKpPM189gZrAheiEDGlCmlMAdoJLDilGVKKmYap4BdwEhPvukLaCqVKFoES8KJYctYcdwEXgJPxo6iS1QUjDxWN4GEkKmkqKQRWdwMbgIrikhiqHuPb4XKxColsGXcFE4WM0s5TTmFKeNPHgUwFawoTgd223lHtC2dwcKTuPVEls5i2Wncfjp3zua+c3h07mcQrrl+QhOGuOEobjqWZSdw5yncc3qrbfCj5/PkXF65mNXX8NZCNt/K5hU0H+878PvZfYbQzOJk8FRElFKYcghPYnoMK4aQWlaEE8GJYIUx29B7KKfRYtgxnAhmG06IRgwn+a+vhRMoDhcw2/FyeGrrDPMiBFBL4ipYSZx27AK2jB3Ca8MEB6ohGhEaEaohHFpfWmH0GJUkegY7g6tgtyEmEW0SESEaSfw4TgpdpRTHjWEy6TjVCF4bIhzSJMwobgwrQ7mLYh7RiZvDiiGi+BKBhAeViaeNYKnoOSoZRBwvQiBjSlRSmAXMJHoIDQTUwAI7jKtgxXGzOB1oucneV6iYRS9g5BEZLLV12bbAAhfcNqwIItqyO4px9DR2FjeJHcIFH0SE0dCk89UVDAkDXGjEcCU0GbsdP4NQ0SKYYYIIVQUnRyU/2XNKpS4qacxISyHX2nAVRSQxYjgRAgjAAS1EMRUa6aAaxVUQeewcQZwa+ODQeuagjSCCH25dXia+D6AKnoKZR8thxlv3qUkhDON0YHH2T7npKK6eybLjWHwSN53CslnccQb3ncMjc3j6cl6Yz8preeUG1i5h0zL1Mwhvn/VZd9QJCNdcwqoFbF/EltvYcivNJ0a+8c/d+wyh6MZN4UVwIzVb+Yndfq7Xe2Gt98Wa/aRv3OEMX+H3Ht1o//q0FFOhAUYXegIRtoP0oV7nyaLrB3b2TxoZ3NRnHE4QOGE8lLLYKTwJg3ZT+na144hq4TAr+sOgN+tI6BEqGUQeP0KVhhc7q9F3RX14uT/2oKs/6OrL/bEr6sNnNfr+h9G2nxVv3T/LimyqfxEUjqoXZrj5z5Xj3fbPFzvzp1PbsSbuVMlxI/OTeueRZniycf7FT3/PTRxjp06z2//SzeCFsSLoBSp53BTVKHZkulAO87uOrHX8Q1Waa/R/x8xix3Bl3CRWDlPBkPDj6DJaGieDJ2O1fd2QTzO7v9tQDncyx7o9f+F1YMVwQjhJ9Ek3N0UVkcXOokXRY+N+5tCgc5ZInmyqPwzyX/HS6BEqEUQSkaUYx2rrdnM/dgZmie5j7NSh1fQRbvaEcnqy+R7hdMw086eUU6dahUPrfQ0vjRHClXAShpX9mdX+c7v9x17a8RKINJXJNaEAry1Zj/1FLX2Cn19g9T8gtOcs53nXesAdu9YfPKnR9efTckyNE4QQ4Mk4SawcThJHwm0rWaG/NKRLan3zawM31UZvq5dvq5cXV0eurPZfFPT8mSX1OSE8cCIIFSOHULG/oLpF3gthaPahLDyc+cdw4zFcdxyLT2DJKdx6JvedzaMXtiB86TrWLGbdLWxenmLRUdx0LMtP5PZZe/uEn8tjF7QgXH0tb9+wF8InR7/x/b59vxNGMSOqk/hh0P9w3f51zW/64n17cG2tf7Pd847e86k51PT0ndUpL/jmvfYYVg4Rxmk7ot69JbCbut/UzHXuGF4aN/UZhL+14G2VuowPFX5i5F5uOM2a1ywNPVQbHfcjWLQO2lruBK/304r1oV3eY4/ttoq7rOIuq7jbKu6xxz60y023cu8041tfK9HIYkb211N3WUNN1/rIMT5X3nX1z5VmuXKrP9JeBgGecqTX99ZUu1kZnmycpqF9Yow0zbGPPXF1tV+dOL/tGCJONUSNHotLtK53bLPpip1Wf7P29UW+MeYm8CCQCNJYWcoJ/AxGGl3FlamC3/Zzb+jj+lc/cUabhtm0vDsd7StmFAvcti8qlbLbGFeoxdFxK9GLg6FtNatpaE3d3BzYv/BLdjlBOUI1Qy2HkLD5jtfxquU2dadp6W/XxrbVK+/Z2mTzXdcw33G0ZqnU1Kfsqnlz3cGKHsIBO/x9p3u7ZTZNt6mXLtE7Sob6BWaz6sjfqffeNm792nebmtksF3fbpTcalVfqQ9usgWZlpGkYuz1nYU07yMm1Su3MJHoCXUHI37I7ljnGp87UbcHoLrf4oVX8VB/9VB/9QIzusIe3esM7gq9c7VemeXmsKFoMLYGZRnyBspGxw7gdiLYzfsJ1P+PKo1l8NAuOZeFMlpzCrWdw77mfQbhqYQvCLSsy3HAMS2Zy66ncfQYPzOahs3nkHB47jyfOYc3FvHwd665h3e1sv5fmo8Pf+H4/pUjLVWApTKgO+4sWCzenuOHlXlfTK73jDWyzRrbb2rbxKXt0/V2jst0qbXdLb1VLW6sj692e10U7AvxONAWPp4zSe3XtRa/vfdu9ONDQwCmgyy3nQU1BdCGimBlKSQ7IPmeUdto9TwSZ993SN+rtiDb0TixpP096x9F22QObncGtdvtbouddo/ShaX4grN1C2+6N7Bgvvisye0RlXt3GCOPiaok76+W1U0dX1vp2+4Nvm52/1oY3uZV1VqmpFR/4avppQVOMPOcONItWsziy3Rt8pdb/gaU1xfiNtkZVnrByf2R1NA2xQc+t8RKrg963bb2pTWmWS1uMnk1O/0eO9oE9utXoel8MfVi1FtSHFb8NG9wEtQh6GpGhzh1ecZc99LrTucvT1/sdOy37QLuAHUNXMULYMq6EFacewYWSSrmL8fDamr/NKbxpjb0ZDL5h5Fb7FRpJylnszBdlGgoVu8BonCJTxqM7q9aLWm6PNrCh2r9tuGND1WYaFOMYXRhgh/D4b15ujSmao6JZGt7mDG4JRnY6pV2B2Ch6mmLgAS+xSwxtDsqvTi9+Yve/Nj6w0+5pDvc2R0e3WcbP9e72YggBRvzAIPOJab7htH9g6xdbQ3ghhEy1l4pCCaZGMLoYSjDOt9zkQ9P89RVtz0j/Tq/nzUb3LqvrQ234Q1v/2DZ2WdoHnrmn0r9L67y73rv/hJEpwnhphmGcs4Oe5nD/y9O6t5vZjX7fdmd4j6l/qk/5jWm/65pbaqOvTx1sls1fa/ZfWgomlGM4KaoR9Mk1s67gSJhZ3MjJ/8J1x3DxsSyayaLjWHw8t5zC7adz99k8PJcnLueZq3h5Ea/dyIZlbVtXtHPjMSw9njtP5d4zuO8M7juDB8/i4dk8OptVc1i1gLVXs3YF2+6i+XDfNw/p3XcIuTQof+o5z7v5Z+p971f9+72xQ8YzBx1Q+NZ++W+PZ39WK1xQ7VvSGHt83Fo11cVvI0ih5xDSn07NvquV1+6nbdVG76uZdTeLiGDnMMME4MQop/BVhhL40UP8/meswU3VgQ+qlWv8znZTworh5FSvfV51ZLdXet3qed8xn59u3TA+ekSj80+n5g6alv37euF0v+Nqr3djMLzVca6s+QgFR2qMqtcbxUetkRu90t3+2HVO703W0FV+6X5jrDkq3vQG3q0Of1L1zp86eKtrLHaH508fmTttZLmrX2kN/LPdTaBgS4jw4X7fp763odrbrJtPNcaur5UX+8biamleY2B+fehW31w8Tbu6OrDEHVrhlo91+iOGRDHMSA4/QimFnqYaetgp7bFGNjn9mwPtbbtjq6sf6vfjRjCSmBEsFTuKiONLuKCrmHnqmTe8KbtFfq1feTMY3mQWXqua/eNZKhnsDNbkDoaKgpvCVDE5tt77ZtV82x59rjaw2R96xe3dIyy7oeDFKOUxJoIKiYPqw5dUxQpHvyEY/uW00Wumlhb7Y5cFoyuC/mbNeml84EPLfMzTL5w6/Eu/76rpxcX10VvsgVuCscunm/8zGMqbGZzCpBCaeQyJWgw7xYiEK39zWu9yf2y3XXq/pr0zrr/RGHsoGLqy2nfs1P6/37/vf32t958bXXNqI/c7pQ1TnYcO/srB9W6MtlYk0Gmb3ig84I3sMAberpfW+0PP2OVrguFDpvX4++em7J/52/H2uW7PXebg40H5oYZT37+LxsSSKjghypMs2r+BcOGxLQivn0GrM8jp3H02D134eRDecgy3Hs/ds7jvdO6Zxd2ncu+sVjL3C+fy/Dxem8fapWxeQfO+zEHfy+8rhKVAerFm/8arrHV6V9cq5ziDpXIbdhg3hA0GaG1yJSJE8mC/62/qw4yHsSKYnYgC01hk9zfrzstmfmtgXForYYDfw7BCEMFSGI0SdDEaYlx+Uis/5ffu9ko7xmv7OREqYZwCvvxdb+CDmrfdG1xp9W8I/P39zKghUW5DtOGEcNqwwICvM15NTg96saP4Icpgh6iBiOMq1GEqTIvsF+SesMqPNPqfcft+6Q0yFQJwYRzqYIZxwJKwFTSVivRjt/u9YMrrtc5VbvEQL42397pfBx+sKAJ0KJPVJGyZqkK1gDeEG2FURVPxoyutsQ/EyFZn6Ilq5WOtc61fWlIXBGH0vca5EcOUsBTsGELBi/3QH17jlD4y259s6Fu94TfNzi01ceB4N5qCqeBNvplKcYIUVRU//IRrvuloe1xr9vTO1dX+VdNHm2X9omCE/SKMKBgJghR6BCdCECWAGjSgGsJqGyxJPxLZXY6xxul9Z2RszmjvsCErmowVwm7DhQZ8VaIaQoCrTA5hEiNETaWcRsBXC6/Z3odu5dlqtFnqemd06Ligg2lx3AR6AhHFi6CDGeovR/7KyR0yXrTLeXpiGEnMENOi1wWl98yxdX7/+465eLxEQ8GPY0loUcph9DasNlwOtqRv1/rYP8d4BE1FU7DDmMlJ181I/BbCU37I9TO4ZAbXH/c5ED5+Gc9cxerree1G1i9ly4r83l+QOZm7T+XOk7jjxNbne2fx5Jk8cQmvXMLLN7HuZpp3hg78J3VfIbzY7n7eH3nd7/nUKT/oG4g2imBmKGXQMphpTBUjhojiyAQpaiHKYfwe7G50kgfGm6P667XO9+3+V1zDdBQClZEkVhZPxQxjdlHjcL9nm11+w+9v6lPOnVZBB1vG7saWrrRGm6651s1vtssXjmu4oLdRjFLJIbqwM3hhqmBAEYTEeIz9Ythh9AgmDKgMxTEm4tf8iZbZXbJ+YxWbJefZiokfwpQpRtFVjDjFHD5YEQyVUgZd/ke/Y6drrLdzzWLtolIfWhg9hJFAV6kkKGZwk1gqRoxyBF3CSWAVKBfwwhRVNKXgyWsdbbczvNkbmzc++kml/5XqwOZGFT+EFsNKIpKYEykySYSKFaXKfbb1ijXYtHqum1ZZZ43sFN1vV40f1AbQY2gyweQQlmWCFFM5KEi9b9rv6dprttkYlxdM695d1T7QR9f7HtMlymH0DG6ut6+DcoEJt2QlgpagkqaUQov+d7/j3arYVB3YYxoz9B6sOFaK4RylDFoMIeOm0BOMpHq1vkkh9CSMGKUYFYn902dNqzSHxJsiu9PreE60/6ia4+txGjGG0wyl8SZiDDJ+HAN0sCV0FasLPYdOby3+hqt/bA2tc/vWmeKgeidOCEvCymJ1YHVgZybcNpTAjFKL40UoJakouBLe5ObobyH0pFN/xKLjuGQGC2ew8BhuOI6bT+K207jr5zw4h8cv4+n5rFzEKzeydikbV+RYdAQ3Hs0tM1h63Ge/crrsRFacwgOncN8FPH8hz13LS9fy8XIO+IfYvkJ4g5bb4o7sqA9v8Ea+66UJwlg9+J2YSewsXr4VrDfiGHFMFRGmLFPNYXZSTnIAS4YL70wtv2137NBHr5yq4YMph4pdVFWqIYbSTIusssprqr0fWMVtjtdvx7CjVDMYaTTpAaFtDvpXO5mm6RTrMl5qb65MFjeHkW7lH5p5SilGJhJWIphJjHbcAaYOUO1iapZGCo+6n1obaJsaXb82RpdaIzTAlihF0ScC9BmqMlYGM4uex419e7z7Xd/aqXc2TXGsyLeiBaaKLmPEsJJUewl6cbIICSuKo2DKlCL4USoKQgqq6hZf3+wPvRpU/nF6z05z5NXqULPu/akro0cQGawUVhxPRc9g5LDaCNgt3DVO70fu0BHThlaZQ+9ZvW8H5fO8EUSIcpRg8uuDkcDN0OAir/fXptE0pyxwS7jhv/laqlky1nuDzcD/ByeLBWYGq0A5ga0QyFgRymFK0VbCqogf0uj+uKZtqre/V60cHfThq7jt2AX8DpwEIoIdoTJxKEuTa0Jo5BmMUuIvDhje6ljvlnqfr6q/0Z1/mtbNASH8BJU8Rg4niZVCl7GzTBvEzWK04YZwQuyXQRQw2/7azKx3x7b4nTvNgUeEjg+VBLqKlcLN4Gdwc1hZRAY71EoMtBTKqVa6lTO5Q+t3IDztUG6YySUzuO5YFh7DohncfBIrZnHnbB6cw2OX8tSVvHg9Ly/mjVvYsCLDwiO47nCuOZwFR7DwGK4/riWLT2DFTG45M/Srs3j4ch65hLdvoP637DOETscOb2xHfXSdVzzIkXAZNgaxk62UIhFp5YjpEYwYZpzyRMg1QimD20ElMlxrWxto6/z+nVr/9unVdh/cMCMFPJUgxHDk225ut6ev8tvfN7TZ0zWGoJEliFMOd2mJp3znmfHuV7xcs+LgT6QyteGE8KNYYUohRiR5NEWjHT+DFsaKUAErjlCo5vHylJOYCrrKCAfp8iartE6o26pDNwVDTAU3g57GzlBVqeWxk+g59DS6ihf+2/HOD33nXb1rV3Xsp34aL4yvYuewkjgy1QylEMUolQgW+CF8mapErY0gOmEC/Zd64d3AfNXvW+Xpw9PUJ53RjcHwx0H5YrsDK4yZRSRxI/hxjBx6Boc/CZSm47zuDWwMhhvjhcf0wXf9we3eyE1WCT9MKfZF5qhIImQCXnIrH1jFd4Ip/9wYxFLYP/TxgP5KfeiDauXWygBBBCuOlseNUVOpp3FTGAl0BTdFI0M5fKiX/8gYWmPIb7nDh7sdmG0YaTyVah4niaXgyrgSThuNySEcCPGNPkSUUZa5xU+Nsfvq2bUHlC+1rH6RpgR9idBIB7aMD3aICpTDOFlEHBHCiVACTcLNY0n/oOdW+aU3gq53zaF77TECMGIYEvpemTDsTQlPxVIxFYw4moJQcOQvukubagtCXzr9MBYf34LwuqNZNIObTtwL4fk8eglPzeP561l1I6/ewroVGW44ngVHc+XhzD+Cq2aw4ESuPpH5M7n6OBYeydUnxm47iRXnc9u5rL0a/a/3GcIr670bq+UXva6mIX7hDOJCSUKLYSkIGRHFknBj+PFWvqyZxZcwwYjh5xiSmR4+xel9w6/sEIO/9ioXBV24EYwYIouId9vJ2+3im97QLqv/Xr/UXUtSDFPL4IcxwVLu95zXx0sbvK5PKvqf1pJ4EewIloSbwM20JuIkGFFxcvhx9svjx6nlKUsMSzhJRiT0BGaaMgc7hR2B/bZZ2OoPLdH6MaE8kXysYEXRVMoSWgKhoCsYoe977R/YYqPo2u6WjzBUym0YKiKLEUOPYMSx1EQlFSmnESq6Ig8rjCoICU+iomCFflztanpijdOz0tSocZU/tMMubna7X3c0qhJGHlPBBTeMmcbI4HNB0LvH19cGI497QzSku8yh9xpjW93BX5ka41H0RCtV/XPFSWFGjvZ6dnjGb+zhhxojztQOtBwB9xtjb/mj6/zeHYY+Xs3gS1QKWBHMaCu9bqKuR49hxNEjh9f7m5a5wex8J7CO8nuxQrgZiqBHqIQph7EUbAURwZMnhXBYpd5JVT7IiK92h3a6fU/4nW/XvWneEFYKR8JLY7ZTTuPI7B/FiaCHcLM4CdwYgUJJCpcy+CpaxKlmVjnGB1ZxvT/0ojHG1BCmipOilmY8QyNFkMKayIaPo0noE5GwCJaEncSc/PCagNDI4Etn/JQbT+DS47j2mFaz4BuPZ8Up3HEWD5zHo5fw5BWt5r+v3sLa5SmWnMaCE5h3FFccxS9P4NpZXHUq807k8mOZ/1MuO1a+aQY3zGbRGay6jIG/2mcID62q7/rWS6KzWTReqgYcEMUL4cpoMTQJXUIo2KlWan9RotaNF6IMVagoE+lFqhdZ6zpv26NvlXLv1KbURZwqGO2U0wdO79nc8Ncb7U1j7PivDlICN4kRI2jDAyd2o6l/6E/ZZve+rRcXfNWk0YWVpCxRnljiOELBSmKEJ94TWpq+KG4eL0YtzngKI4afoJ7FDen1rrU1f32p/dcN5169ggaVNFaWagZHoZhCD2Gr1NI4SfTQkaLwviNWB70fV71T9S6KMmaGoBNfxVTQckydCFUrVCcSgJKUMlQzOBIlBTN8ot/TdMw3RPfLZQ2HWUHfe0bpRSvT9AKmxzGzGHFcsEGomBlqbfdWK2/WSuuqo8vdAeqsEIPvTde2OL3PmTpfjWEkvwhCP4fgAdfZ6Zeb5uD5tTT1DKM5NM6YWmxa+rNetul5h/hd1NrQ8jhZzAxaDquAn8PPIJKUE2ihH4wPNy1vqz68x60eZg+gg5tAKPhpHAVHIcjj5tAUKolJIbR7GExgx75X73zhgKFt03o+HupfWxRUI9QjeBJCxpcYj2Kl+nvbqYEdxe3D6EZLYykYIYIUbozhNg6QXzetZsl8curgtmL5f+zXiZ/CTrYy4IsyuoKdws9gp7BjrYJdJ4IZRk9Q+T+F8KYTWxBee9S/gfBinryC5xb+DoS3zWXJOSw6jYWnc+PPufFcbjiba8/glydyxalcdjyXzmT+TOmik0JnXch+34p8llZv/ZvSvs+TvzIGHjOmfFwTu+rdO43cQ97Af2kMYmbRE2gyRhKjwEgnvWnKSRpJRLKVwzlRLOco2FE0DtlvqFm21mupZs282SviQUPGVjda9jprZGOj+HJ5hGkpbCU5nMEJoXcRhAk4wevaUBfrayOv2R2fWIML3MpfaxmKbRgSXgduL1YKM0JRwpio1Yjhpanm8FS0EG4KU8FI4Ccw44Yh7/ar65yO973KCjGCS8tisRVcCaFiRvFUDBURxw7/zGnf1rDetLqafuMkrZtiCCFRTeLLrVTGUgflPHYP5Sx6hmoOuw0HRA9ahAZPVCvv6P273LEF4xUspPHOj3X3xUa2aQ2eXBvCbMNvZ0TCA62TIWmkkdzll14T6qap1vfqvTjJk53OZqP4jJ9qFmtttQKehBHGzVBOYmUYT+FIjMpoKm4MPyN7NIPqxmrXKtFzTK2PgFbtYi29yx3fYxc3BJ2PBUO44HS0Uib02O9sjDhmFCNypNv9kaOt8Ts+FWKG3Y0fwZg0XQ4jflCQagpjrd3+oa1fIkZwQhgJROfEIi+tD7zk5LZU3aZZOTwY2uceNqKLMoUKV3l9HwRilz3wSq3rtQNHD6/1GraMEcKUMfNoeUwJG/Q8Rhw3RBDFUigp6DLB5HdCN4WZxozgtp9yGAuOY+5MrjqcBUdw3VEt38yKM7jzXB6+iMeu4JlrefEGXlnCG8tjPDifOy9m6XksOZcVF7LiIpbN5ebzufYM5s/msllceiKXHRc69zhOPpfg4H2GEIcL3ZGtdXHvAfkHxxPNcuXXleqp0w0OzFFXsSN4EappvE5EGi3S0vgijjZRMBbDkRHhqNW22fPe9IZe8rp21mr7VdPYHGMPvenom8fNXWbp29PSaNFWqYQXxizgZnHbcDk76PvEspqV4iui0BTO83Vz5gEjlf3aMcMMt6FFqRVa1ypbpaRSSeAk8VWE8mVBuMUpzbEK/69Qp1nJcT+tVaOlQBp3cyUXy44O1zOt1FlfxZRxk5jd6BEaPFvVdpsD293SZY0yFgSp54W2qdb9odk3r17GiuKk0GXcMHqOcvQvp/a8VS2/bRZequsHBGlE/HC7/eN66Tk/3SxXh+vdeDHMCJ6KrrYKICyJSgIzjR/Hjx7v9e10Slv93tVe8WA/hdOGmcZS8JSHHet9t7wj6H+pNubU0tiZz3KYWhXG8ZZ8yRAm764Nr3HbN9acpij9r1rfPkPo9qJHEPxJI/NgrdLUtI+K/WuM/Ac15wmnfKrVa/l5Ggr1MN5E+UsSkcZO4sawJbQYRhx/8oyZzyDsPOmnLQh/+TOu+hnXHMnCY7npBJadxh3ncP9F/OoKnr6GF67n5Zt4fWmaZ25M/+oa7r6UOy7mnsu59yrumc+dl7PkQq6by5Vnc8ksLjyWk4/kZ2diHKjsM4RVmB65TvQ3S8aeqZUXp/dsN/s/1Uu73SnLveH/GaTxJ7KWwFaxu7HiOAlsBTOKHmmFLmyZCqeMj24bt38lCk3Xv9MvIXjGFZudwU8CcZczzNdhJEK5QCOJ24YuIfIYEjZmLf2Y7zZdd2Oj+GQ9uabatb1W2loz73DHfmB2txlxRBgPqiEcmdEsw2lEHE9BpL8sCD9yS2v90uuOsaesf1os7qgMwoNcVgAAIABJREFUbCuPfjQ6ZeO0wQ+DysqG9V+9FAJMmZKClcXsQkSpt60MKjvNga1e8Yz6CBZY0nn+4Ef+2NtG96O1KWUni4jiKtgSRhwRnTO1sqE+9qk5eoc3ggu68nciuaM+ttprb2r+1xs9rVRvP9pyPEz4IUQSJzWR2bzJ8Z8TXbv90TsaRWwQYawO3BQmM+2enb65xxrc6I+d3ihjhVuFxbbcysg3Jaw4TvLLhNABM/t4UNpsd22o2u+LoYPqhX2G0EthxrHC1KJ/N96/2pnSrFgflYYfaSTeCvqbnrHFFnPEgGsqeDL1NG4bQkFkcJK4EkLGVL6oDYeT/C2EJx7GVTM4/ziuOIwrDmP+4VxzDItmcvOp3PZz7r2Qhy7lqat47lpW38CrSzKsXjH89OLMQ1dx7zwevJqHruOha1P3X51cMT9xw5VcNZeLzuTcYznmp/xgFgNfS+27JswQtA3b8i1C3+K6b4j+1/XMplpn0xjcXe59Z3Rom2b+3BuiHsIDLYar4CXw1ZYzypRa4zsSAb8KpmwX2qbKwFuiOM9Pr6tpW8yuT0fLX/1aAS+EncXuIVCw2hBtmDLlBHqKWs5qZM+rDWyean9oDa118y/46hY337RKbwr9Kr/07fG+wZKE04YXppKkNOG9jGFKXxaEOyp9693iNt/40Cq+6w68vF/PC/sX143bL7vZZmlorTl2sCXhgB2lnMbpxChgRwfrsbV+5W2nf4NX+nG1GyuMHvl/GvmmI9YbXW/V/O+6vVSgFkeoGCG8yON1+9XqSNM0z3MHJiD8mqVsqFXWej2fmOIHjUH8MLqME8JNIFQqEubEtVzBkaaPx5rCX2V2vlcVP5ra3ToXnA6cFBqOl3ilKj6oDO4wi0/XfSywYi1rxZGxY5hRTPnLhNBsxyFtFFYGle12z/qa/aY9YDeS+w5hG0JFS2NKeInv1PvvDcT7rvep1veym32gkXx1al8zsHaZ7uWVkYO1PGYII4QpIdI4OTwVO4b+BQ6tzyCceRjzZoTOnsHFh3LRoVz6M+YfxbUzWHwyy8/i7gt44GKemM+z1/LSDbxyM7xxl7ty6fDjC6WHF/DY9aHHbyw8vrj/ket77l7Yv2QBCy7m4rM5ZyZH/Yx/OpX2rxf2GUItg1WgmsaR/lzPL65VXp1u7bGL2/y+NX7HK27nLr+8y3du9ipT3QwurXaOtow74RSOteycageCo82BD5zay1bvVtH9a7/0fL3/Y31kmRhgephiBL+ToAMzghbDCeHF0NOUOhBZXLCYYRVeM8Rmy9zult70etf7+deqXevqw1sblV8Wh8edFNUQdhQ9g8jjKIjIlwXhp0K86otH3coz2vBKre950ftqpbi7x1zru82RxhuVr/yZ1U0QwlcpSmhR9DSedHAt86ajbXV7XvVG/srLI2T0CNOVzZa51ur9KLAv8YYpQVXCSmGwfyBv9a3XvaFdjvWPXhcBmOqwG1vVMLe6g3tE5ee1IbwwFRkBQRxToaxgpXBk9BBm9PJpPW+Zox9YY+trNuNtmBHMDG4eO4MRoSEtGTffLQ6/Vx58Nwi+6cXQpZbBMtFJxIxixLCULxfCTr3jFV/fbfeur9kb7d7h8X3va2pHcJKIAsUM5QhOm++lzrQH3rfqbwbuq/XRNdWuTU7nNmtgk1teE4gfu734YWwoxSkXcJN4EYzJS5mcvXW9Xs/Mw7j82PBZx3DBTzj/J8z9KZcfyVUzWHQiS0/nznO5by6PzeOpq3lhEatvhs0PHPDq7c6zN3Y/eUPq2Zs7nltWfH6p+czNUx5ebNx6HdddymXnMefkyDFH8N1ZtH+9fd8hzGF0IToZSjAq8c2keXDPgz3DG239/XH35QPGlo0X1ujdzaL9hC0OPKBAJUoljBbCirVK4EwZM46tIuJdmrLcEzunW294+T3mwMvB0A7X8Q9sZySMFsVM40bQwpTTmBF8FUdp9Tiy4gjwwJH/0em937LesZ333fI2v+9Np7BD5D92g2uqpVItiR9CyBg5rCR+9MuCcKVVPNbL5/0ILtRgKtTBbiOA0XBES+GEqEMjg64ikmgpqtFDqp3vONrGau8qf7TuJDFVjASNxBIxusEb2eWXHgzKViWCF8HJYnBCUNjpjb1pjTzuG5qfwoshkniRR+tihzO00xpcXB3BC1FJoLXhJxAKlQReDjtCGcPKvtGoPGt2Nh13Ya1MDYSK0Y4v42awkkyTjpg2tFUrflAZ3ONbc6pdiInK2mjLhBESuoT55d0JzXYc8nrh5UDb5fSur9lbrX7RSOwzhJUkTgw/gSigpTHDuG14sYpdmOVV1rmNpum8bfS/5OReG+/bdUB59X7u3+/XgQ+jEiMZLAVf+sLQzmcQzjiUS4+RTjuac3/IOT/hvMP4xRHMO5prZnLjqayYzV3n8fClPDaPZ67lhUWw7aGD1931lZVLK8/f0v/SivJLt9kv3dp4cdnUp2+p3329esNl8vw5XDIrdtzRfO80Cl/7d2jCPCUVI4nTiaYyCiZU1bqTuMEuN4XfFNp2Z2hbMLrGL99tD+Jk0WTKIQyp1bDIlDFVdAmnHSv01277pqnW2mr3K6Jzu2Nc1NCYlmAwiqVghrHAjKIXKEstL7MI4Uz0O0vRiFGO4Es0Egc4heuKA9uK5Q/F2LZq/8cNfWtgzglGqaq4YbQERgY//mVB+I5vHOm2Y0cRCnqGssxomBGJuoopY+ewUjgp3CwVCVOmIlOPzQz6PrIqG+vdz/sjg1YMM4OexlMON3Lbasbrfs/rNeO/W1msKF4agztqw1v9oY/M0uX1MdyJqr8MbuieqthtjbxpdT0SjBKE0TNoUYI0IomeptaBDRW+Wx/50C69bve+64j/Vs3ggZFGL+CHsFXMAkF4Sl191Rr7yBxd6w6sqpcJejBUKlGs+O9AKH+5EEaM/HNBeZvdvaFq7xAD0+qZfYcwhSXhTbjfUog0doogw1AYPYKX+H6t97GG9Ukj2OEOP6HLv5mqP9QY+Ue/o9Vox87gJnEn14S2jKH+FsJLjo6cfBRn/wun/5DZP+K8w7jocK48hutPYMksbjuL++fwq4t5fB5PXwNvPfxn6+/af/Uy88VlxdUrxMt31F6+bb+Xlu///LL971vUdeNliWsu5PIzkscfy/dOI3dAdp8hNNuogtmGFqIq4yQp5TCzGGHq1KdJD/h9vxFDW5zeDf5Q050yMH0EN4cmYcRwJiBU0BUsFTdJEBm1oneIzo1B/5pg+H3LH53WHu6L4EnYWWoTxXgqVjvlGCKJiLbaLukSlTT2AL6MiFOW0CVq6b/ef+D+ut7UzGeDRFNUXrPsb9S6qcroCpV0q8fBlxKiENpMM4OQsTswBql0YKnUVJwIGog4lRSlLEaOSgw3SUWmETsr6P/UGltf737GH06KMGYWPYeIH6RLuxr2k35m+7h1mNeLKeGlFYPXG/raanfTNI8dH8SCchYzjc2tVfG+ObLFKqyslamGEO1oCkEOU0HP0ejEJqYxe3+xRxv42K+sskshD+wYmiJVcnhgyFQ6EODyrDP2kV163Mr+xjfbp5ewcpSjrXjSlw5hyzuafaI6tsXpnnDMfLOW32cIgwxmEj2CTcvILHViDhCo1JSJtG+n0namyK8MxpoNa7eZbpqlW5wy9Qz1CN5EqwH+TyA8+jB+cYx8wlHM/gGzfsCZ/8I5P+HCn3H5kSyYwY0ns+w07jmHB+bw6KU8cSW8ddefrL+19sqy8prl5hu3T1//v9l7z3CpynP//zOzp/e29+xepjAzq7HalJ29KYqak8STHBNjEnunEzqbXehSxC4iSNOICKKICIi9xNgrioC9o2LvMWX/X8yYnPM/wetwLq+TeP28ru8bXrH2mvVZ63nu576/39t/9MJth+25ubRrs3H32uTWK/ndhSyfWzd3DqPn0Xh48O8pc//5Cr7hj9f8lSqc4EHyo4YwIxRjJALkggyx5LLWXULy40Lm3ab4H3VlsylQAMFFMozgoxik6CblqDQoGwFkHhZy7+ZzL2sNH+uJnBxDtqM6kH3kvOge8h5yTnQ/OS9iLXIT6SiZIEoAw4kSQPNXOpiLMdptpYyjXxj6birxUnv2A1Na2NFMDgQfgpdS9KAhVG3IPtI+dBemtVeMfWTKL+s1/bLUJ0VR7eSjGA3kgqSqSNvRy+fC4YrFaM5LzoscQojTzh4t9bZW86U+YJ2RQK8qFxXIeWm3PFcw39IbXzMb78mLyDbS9tGl2j/q6TeE6DOH5T26A8WD4UGyIVWNKSU+LWqvyeF9ctOx+XrMKCk3pRBJUKpRq8k6goc6+jOZnWb958bAR0vy6kLtJsl/bd63sjO8VY/frMo3FtPXy+FVgyIvFLJfpbMPFev6zeRDZj1FEOrJNKA56ATNQ67moCEUPP9mhvoV5RWt5gslt1xqQbMiuTCrSHiQw3cUf/C23PSU5ug3C/PFWlIeRB+KE8mG7EavQa4jGSftpuBjkA+z3IocQveiOUiEkMLIbjQHRQ+6l7SdpBvdj1wej6hHDqM4F2n1X+nSV+m2e4clPi0ZR4kOdJAbEH3f6HnjQ7aj1qLZ+ro4r4feLuZPYMY45oxj/gQWTeLCqSzv4YrZrDuLay/g+ovYsZS7V8Jbtx3+yk3G3q0tu7elXri19Modh71wxyF7bi08vVm+c23z5stZfR6XzK6ePYsRc2k8PHLQEOoBtBBqGCWMGCTrIe0gWYUZJBlCjVCwnjA48EIp059L//6Q1L15ibwFyUY2hOhFD5B3kXMdNISl8qSSC8VDzoXoQwuhOCs+X6KVuiraPJgWCvQMbf1EzD5fSv5ZFla3J9BADZDzkvd9WxB+aaQnaV4U0DxoYVQnRQtDHYheBBdlgxnJhmJDr6LgQIhRtD6rpt7W6j43siv1tkqzXvl8r2TZlM98KrW8pTc+nJeChhfZsbgj8YmR+lxovO2QgahVX7uA2pHspxSaPiwab6ixt9WWUwsN6CGEAHoA0YrsR6lBtY0v1n0hpffK/v5M+s/iwP2S8Nds6ksx8YGc7G8TPhMGfiUM+Djb+JzR+L6S+1NKeFZped5s3JtvogBSjEwdipM8KG4ykW8PQjtSGNWzwEh/pCVf0gOf5zN3lWSGRsl7EJ2oDgwbugXFjhpAD2B60ZzknKQ95IKVifgOP+1+VDuCFdleKermAzXpMFkHqgMjgOZERyhxU7H2Kzn1YHv9l5p8puanAGptxZL4myFUalCr+ro4t5fp05k7gb6xzBzPvImcPZkLpnFJD6tm8bt5bDiHjeey5UJuWwpv3DL4hW25pzcHntoSf3aH+vztg569tfT0zcrjm9p2XB7esJIlZ3POjFhPH8Pn/K8gLA8H6FUYVjRb+dgglAyge1E9iHVILko80JntN5SX5LrnCnqVCQoofmQ3ohvdiR44aAgFkCDvoOBBd1HwYfpIWsj4kVyYVlJV4VQYzYPCaLP6j4awy2zoTwvbzAEUQfeS8aAe/BHFASD8Kp+erYdQ7EhBsjFyLjQH7V4EH2UfB8lVqUVpXhQnYoii82VtwNta3Sd6Zr7RjG5F9GJ4kcIUrafno/3Z9Idyy3P5gT8s1WJYtncq72gt/UL6gsHJct9sJcFLcP4oX/NWYeA+veY9IzE134TqQwtXzEHkKpQwRee9ivC2md5fqv1STHwqSp9rRr+ifaIL75hSv1h8t33gX5UBX+Yz+9tzzxWl/brRr2pPHpJ8J5+cYtaiORFqkNwoViQHqdC3BqHmIB9Fd3bqodfzuS+0umfk6McdhdSQJgQHSQtmkPYQarnWAKUwqp+cA9GB9LUfaXmWQrYhuRF8iEFUJ6aVEkhuVBcFK3qAXBQZ8mw1Gr400ruk2F9zQlc+Tt6KGkZ3fVPvqOxHqkDYPd22uJfJ3cycQNd4+iYwZzILp3FuFxd2c+kMVs7kygVctZBrzmHrRfDSdvXp62seWc/DG3nqxuQzO9SdN4mP3dj0h/Wh6y9j1VIWzmNOV83kHs6YRcNhgYOGUIpWOv0VD6oTvWxrbSPjJR9CqCftLqi+x4vi58aAvzTXvFgywgaokPeguki5kF0UowcNYdKO7KDgQ/UgODB9GBESPgQvYhWDHXR6MarRnGQYK8a/MDOPa9X9KfFmLU0HKHZSLiS+LQhfyyfH6gFUO3IIsZpskLSHdADZjx7GDGB6KXgo+NBcZC1Ivnwh+Jo2YJ/W8L4mjDZrMCwIPlQXUhjT7svbvsoJnyuJt3V5WkcLeZ4taa9Ljf2C8Kv2OHIVeqDixp1z5MzAC3n1baPhg3zy3HwC2VXJmlUDyDZ0x7BC9D1JfdNMvtOeuEYMThQ8E+VYjxAaIbl+nQ+elK89OR+ZnvF0mYFePXyaEbhca+lP5J4pNb1bSN5niJggB5E9lcTMnPdbg1B0YnhRfRi29YNT/ZrwfML/hZZeX8gelnWRBtONXkc6QBaKfN2W7CTvocOPHkAJo1WThZSVnA+lDqn26yux0QlFB3kbst+XqkWBEtfpqfe11tez8T9JYlc+jgKyG9NF1nrA61d8SHbkajRbd3dw4Qwm9ri6JzJtPNMnM2Mqc7tY1MXi6ZzXw0U9LJvFyrmsX8y2JbD3xtxjGxz3XMHda3ng2tCjW5IPb26891rnjjVccSHnnceMPromx8dN45SZNA87eAgNF6oPIVSVjTszcYQYSgA1QNqOFCUdRbON6Uy8o8s7lZr9euvtJQUNFCpFi6QL0UWx5qAhlKPk3RRcpKtoAMFKPoZYh1lPqw85ilGLGCPnRLLPHax8bqSf1uP9krRKb6HDimQj6/rfnBMeAMK/yNo8qQ7BgxREi6PVIcZJN5CLI9Uix1FiaGGMchSzB9l1XD72rpZ7U61/WxN+kg9igBBCqkKKofnJ87SS+0RLfaQKlxfb2gv2/UVtn9j4kppJmG5EJ3oE3Y/hJefC8Dxpyvv15o/y6XX5DLK90v+RDaB4MFknJ97RxffV1FuFgb9UPRiQr0KyIoJmwbAhemmzVpwpNQ7TXG+0Ne03al/PN72va+Qt6K6KB7HmRHV+axBKHiQr6TBq1U8G1/xJN75KN78l173aKcwsRcmXx5eCJGvJ1WHEEWoDqVqEKEUPJReSn0wUKUbJj1yF5seoJusn7UeKI0YxA1GhhoyfTIBsLXk7Ha69WnGf3PCJlnq9JJ9oRkiD5KHkI3PgwozsRq5CrkZzdPVUL5jNb2fEpkxm8mSmTaNvOrOnM28686ezcDqLp3NeL8vmsP48dqyAXden7ruKWy/j5hXctZY/XFNz57rAzZdzzUVcOJ/ZZ/HbaYwb1zBqCif20TjMffCFGQeaFRUUkEF2IAWRooiQt2KCbrm5PfulKe+Uavvz+oxiAhUkN/kAmpW0HdGN+b/4EoaRXeR9khqpz9kxoaP8gY3TWFUZvhYc5By/kGNPd7R/oqWeN5tez4un6RE6nIjlNp2Dr44eqDBjGOcqTYg2BCuqjbwVw4bswrCh2BEd5FykfaQCCHHUJhRLn9n4oZ59Q2vap4q5ggsDhCgSSFGkELrl3FLDvnz6M2nA3UZiXqn63Xb5U7H18mIzio1sACVUOTbIeTFt9xniO1rTh/m2O0wJ1VmJdhWCyD4MXlaEl830F1L6ScNsyPsYZKejDi2GEkCKkvEjtiJWY0bJBynYaXdtzDf+uSPzXKH2M0063YxQcGC6UUJorvK59rcDoR4mS7QtjOCg4NiaV9415dfzrV/k6nbmWxd0NkrFYMX5V/aRdVX86hUrJqiEM15/OoTswoiTdWJGGBJHtSOAUkUOJF88GaJsNqX5KYR+m2/pF4buExu/bFduGDogm3eQsSKHKQQri/wDLvqqkGvRnV0z6xfOc42d0zSpyzZpOpO7md7DzB5mdTNnGvOmctY0FnVz0WzWXcQtl8OjG5ruXMXmi7juQrYu46ZV3LicDUtYtYD5PXT1MmICo0YlzphUhtB1sBA+pGZ+pzefnA+6ilCCAuQtGA4KkLfnO8NLhNAbcstHxeTbmeYPdV0t1KBANoIeQbcilBfi4YOH0E/WopuB5e3ZFe3JQ4f46MQiQtFJDgbBIaBbjyxEL9Vr3hGbPpCTrxnpG9sTVgXyAYQoZgDp4M8JDwDhk8WG7nZ/XdGKbq0YyxahAIOhACYUPKhO0iBYKfpQWGokPtOEN7SmVzWJgg0DsjUoVqQ46WoElznEubc9+ZnYukdL3pdvfbGU6BfTxwwNIUG2FjmI5sEMkAuQt9xpiG8pTR8arU/kZUwXkhUhgFGD6B4nh99oF97SWj9T0oulRlRQPOSayUZQPAhB6txkAhW/c7E8xOw4pj3wiS7sLcTfV1P3agMo2jHdKNXIHtSqbw/CAGIV2SBCBNFbyseXDWrZbyY/S9T8RUzuN8RthdYRpdiAdg+mHcFKO+QpZx+crAWulYT5csquOREC7taq48z4OYcle/PBnym2uGmvbCNVyMMg6HAON6u3q03vKs3viIl32weO6QhjgOAjV4Pqx/iG5Wj5mLoWw9s9u3X+osjo+ZmJPeFJvZ6pfb7pfe7uXmvfdGZMY8ZU5kxlXjcXzOGKC7lpDdx/ZXzHUjYs4qpFXHsBm5aw4XzWnM2lM5kxlfFdnDGG4SPSp03kuD4ah9kPFsKnB7Xs7mjb257dWRDvyYtrzexCc8CUfGLS4er9zcqfxR/0q9LeYuydfP2nbS19RzSR9yBDpgaluuKQWW75O1gIDw1QYJBi3atk+lXj+WLuzkJmVy7XVxQvllJLhggXmYn7U5kvix0fd+Y+Frz7c21vqgPOK8XJguojF8fwkv7WCjP9Qs2TesPNxcyThvm6ou/RhUfz4s7iwDcV5QVB2K3p9wz+wVklQcy6EKETVH5npL5Q/wahtTKspFch19JaTdrDMB7rSH4htLyppt5RM08U6vpzmfiwKgQrQhK1vNUsW7Zxi559U6p/X2veaw70FNyokPQxuBXRsVVI7Dx8wJdS8wda+ielICaIwUSiFdHFEAuDvAgOVOgEwULWS6qGrMM6yPGurD5XrNmnNffLJV/RieFFribrR7Z+axDKdlQPehiljmwUg0KH7cNccs+QAa8U2j6Qmv+UbfxcSrxoDripI3PZoPRyc8A9hvSAkbnHaP0or/cXhlyUb8KEoTYkZudDbw3O/kVofEds+UOnuqxd6jaTC9Wmi82mlR2J+wyxP6f3i+ldedt7YvpFQ8iXd0ZylHSctJ3CN4ThuisQmr5pc9sWnV03ZqE4oa9myozI1JnRrpmhnh5/93Rbz1T6pjJrKmf1cM4c1pzP5pXwh5VcvYBlM1k1l9/N43fzWDafs2cxZZJ95LjwiWM5eZR15KjG08dxykzqB4cOFsKH21O727P7CtmP9dRnYtNnUv3nesNnhcb9pbo3jch7Srhfae43lKfz8mS1Li4c+E2TDpGLUIA8D6cG9Kel1/TmPxXbarUmpGoEH8LXUQTlfI9OGwaDTN/1g7Kfl+T+XN1+wft8u//tjvr3zfinYvyrTMNX2eZP5cTbZvrV0oA7Du0YY7Yg2dGsGB7ksqmxAymM6kANkLOT5ijZtU+V+9Niv6qtlsIVc3jJRTqE6KPdixpD9lQ8wrJcKMX7Ve0TueUdvf4f6jOjbY8Rf9tM/NU01hmJigGc0YjivLco79fD/XLd8kNTDLWS82C6yMYQI8i15JxkWao29xv5j6TGv8oN/aq0w8zEDAcipEMI9WhhspAOoDjni8l+Kbtfr35FSx9W8mFEGRJCZmiH9+F8058SNZ91ZreU4ge8/6IDvRohiBKiPUqOXNI67zD51SHN+4X6fcqAZYVWRDBhcAgpjGE7X0s+Ukq+0F77rlI3RXFggHJgCCXbkI7Iq4XMe0r4mc7YRcUYaWivR3VVQiYUD4oPxY8WQg8/KKWfLWb3daTeMqrflF37FPdbZvTtQvxPQu2+Qt3eUvUbSl2/Kr9X6jzHGFDfZsGwkLVMEgNPtGf+3Cl8pFU/q3ueGBz4Sm/4Uq37XK77RG76SGl9T2t7S0u+prddcHjxCK2atAXViR4hFyTrQj9wIIwSo2BDCqM4Rp2nnHVRbtb8gV1nxbvn1vXMa+6b29o3q6mvt7anK9A1zdIzlbnTWTyLFYu5+hK4/VIun8v5vVwym+WzuXQ2i2fRO51xYyxnjIz+ehTHj7CfPrzxxNGc0EvdoIM+orhEq7sm33pfSXipMPB9XfpMFj6TBnwupz/R5P15+dWS8KSRvk6sP10K0+7i8G/oSKhGi9NhpcN1myJ/rJi7irlPCgNtah1yFMGL5EL1VJx5ZDdSLblAVo2N70xuL+VelnJ/EYR+1XihmHwzn/nQEP6oK1/o+jvawD1q7mF1wC+FUHOqiiyoTtRIJYrYdGC4MKzky+bfDCtE/1AY+JqYe7Fj4Jx8LWYVRSdamFwQwfV1SJgVw0vejW7p0ZpeNvUn9NR72sB/qP6M9G4u/akg9mfNG7OZjOBD9HmzLdFC6yOdP3jRaP5KSK1plygEaxMxFD96AN2FEUH3oFh79eZX8sbjWuvTessLurgsn6bdi1mF5EOJUHKRt6LXUQhO0TOvatJz+ZZ9ujGpNMBa5yIXSbZ5LjaFT/L5/tSAV4vKZdqBIVRs6GEyfiQf7TFkayjJCcXmfm3gXxK5z0Vjm6EMyQRQnBTqrJlactYV6dQrkvxXVerPaatyjchlO4wDvWQdx6m1X8pmfyr7J0PeoQ4It1Sh1FcIrDTElL2JA6gBSpYfdoZWl5pfUdL9mVy/IH2lKW8X5H5R78+r+/O5l+XkXim3TZdOVhpIV1GKoviOUCLLzLYn9cwH2XR/VuxX8zvb214uDPhEF/pV9c+q/oYmP2Ckt+qtQ8otlhnQHJUgVMGFduBcRzlKwYYYQraXIZy9QJ0+v65vfnPf/LaZZyVmzG75G4TdU5nbxdkzWb6ItRfADedzcS/zprAOwUjWAAAgAElEQVSgm0VdzJ7K5MmcMo5Tz+T4M6uPGWn99XDfSWe0/mYkx/VYqjtjB12YyYGMYLqPK9TOMpuW6Yn1aup6Jbm1KXOxkjnhkLbkoWHyNnJWck7U0IGXKz4yfmTQ+IkcP16tKRrO36h+lAhyENGN7EbzVG6T5CJZTdaPZqNko8OTKgSPzMdPLbbenk7dLKQ3SQOWGenJxeZD20OWorVieSiCYkerRoqTCSA5KFrLdikoARQ/moUO75Gd9Udr3jFGTYfsRqxC86JHkEKVGCnRScaCXA7Bq2rTw6fkG39m+n6uxP6hfqb5f2C6jtRcw4XQUNGLakGuIhVBdJ6q1h8vWLsSvsPkehQnCQeaBdmP4ED2o3vQrHE9cHKh7sem94ftrt+ooYIaoOjEtJPxk/ajepAhF0G2N4vBE2XPD3XOkKvRw2RA85C2ykbkJDPym5ztkFIQ7cArEc2K6SPrJOukFEP3kLY0SZ6jDN9PJfd/FGu1jjpkG0oVRoC0D4WCEDhSDfzE9J6pxGo0JybIByLcgwya43S15pSc4xcFv5oPkgE9XBkRLkMofc2h7CNtRXPS7k0PCh/VWdNbbFup5K7LSiuU5KV64myzcYpe8xs1pBhB8h7yNrRIZctQsFmKjkGm7zQ93m0krpOSm8TktfKAlXp6WqG5vd1PJwyCjAUJTCtFN1o58tWJ+g1GT2HyVWUIR58/cP7FwpyFWs/ChtmL0rMXDpi9ID1rbtuMvrre6d7pXfRMY950Fs9g6VmsORs2nsv5XfSMZ/pEpo1lwihOG+k46gzP8adyzOnVvxzl+tXI8ElntP56OMf1WOo7aw8aQsFacVVTbaiWSoZOB8hhNFclAUeyILjIhhAO/KbUvAjleS0rmhfTjgE5C4ofuXwB/wlC0YUQQ4ohBxGciDZUJ7oT3UEHFL5OFxLLPaVVZCzkPRgu9BBqDbkIKQ+Sg0J5R+pECCAEEK2YNoq2SspSGlJVCF7UMGoI1YPmRXSRtCK4MAKodkQbkh0JBOs/lmalAAYIViQrBRumm2yoYomrgWjFrKHgQ/cwGBQf6SokF4YX2YpUhWJHgTzkqIReGS4yXkvSh+xBdiHGUD2oLgwwQLYhO9CcFEKIVeSt5EECw0H2wG96DfJuBBcZJ0YQ04doRaxCsSBBwUbJg2xDsqP6yTkpguJEs6BTCUIr2jAOvBwth6KqdrLljAM3EuQjladL/lv6iBvJjehGrUUJIduRQKEyHqmHKdgrZ9Fl93uDssOdpaWOTAzVj2mtVMUMB4qzUh4rWijayNtQ7GStJKhk+pY8lTTLcvipceApCjGEaUUIojhGnz9wwRJx7iK9d1HT7IUDZi8cMGd+dtbctpkzGvq6/T3dlhndLOjlnJksmcuKs2D92SyewpSRTBxpG3eaZfgp1uNODf745JrjTuGXp8WOHun4zQj/SWc0HTuck7tpGRQ9aAgHNdBRTz6K6kNwVcZeynl9ih0RZFAdGB50zzeNihTcFZdb2V8J7ssFo83hr/93dyUXrfJaclO0kw8gB0n5SQTIRsiFSPuQbORsZB1knUg+9Aj5KIUYUpCcD8GD6K0kh8hudA+djnJmEEqArBfJh+ojY6O9nEDoRwqilBerblQfJQeqtWIUK/jIesj5SH4dif7flY0jx5A8FT/ckodiOfczhBHBdKAEkGuRomT9KBZKFjQw7RSCqCFEL6KfTBDFR8pByo0RpFh+1qsoWhC9SDG0CFoYzYVsc6cilrZqUiD6ESIYAUpO9CqUCImGA95/1YLpRfWRcyJ50PzoLnSnKxklFUIIIQfJeSs1KtVBwYrqQQ4ilwNhI2h/29r9I+mOSsZo2o9cjVmN4Ko4I/5nDsWvOTSiKCGyHjLeSoinbEexUQxWmv5VP5oL0UbKXZWMkgkjRVEDyC5kVyUSM+0kZSdtI+dAdqF7MSLoUdRYJX5cdJKpImtHdZH3UPgG39G/QzjmAnXhJdK8s82+s5tnnJWeOT8za96AmbMSM/rqZvQE+3qts3pZNINzZ7FkDpfNgd/NYd5Yxp/OuNMZfSLDj+f4k/jZCc4Tz+C4MyLHjOT4EfYzh9eeMooz+xgwxHfQELYGSYTIBBEjFbffQpRijKwT2YPppujGtKPakGyVLMt/LDu5stWHF8mDEkAKkgr/49552YMOmgW1/BG2Y7gwyud+dWhx1BrUcm5hGMmH4CETJONH9FYCWXUvopuMg7wD+etA82w5pd2L5KMYIR/BDKH97VPsRw+he1CcGC4UP5kgUhAtQCaK4fzHkqtRw5Xg6ErYZdkJM4DgQ/IhBEkHSPpoddFmQ7OiVGE4MINIMdQwRhChBj2KFEIKoUfQyx8QO7qzkk0ru1F8qD5kH0KAXAAVZAfZCJkAohPNiRZBrv+m+696Ks56ghPFjemjUA45DVUKY2U/qHK/mFSF5EIPYUZRv7boTh84iEZwkHFgeFBDaGHyAbLlqux/C6Us/9xJFxknqpN2P4NDFP0oHkQ3YjXZKNkIUgw1hOwnFyQdoWihYEWzIlkRrCh2NBe6E70GpZpcjHSUdIRcENGL6CTjJ+sl60JwobowA+he5APHd4uhynL0v0LYOzfZOzfZNzvRN6Oltyfe2+Pq7WVWL4tmcu4sLp7N8tlwxVwWTGT6GPrG0TOarhGMH8Upoxg5jlNGBY8dy8ljGD+6euxEJs5BO+ygzwkx3ZhuDBeaC9lB1kGbjeYqTCu6E8lPJkDKQ8aB7ML4huVQGMWHHsAMYLoouunw0l6G1ofiQ/ZU9gyqD82P4CTnQQhUbHkLDkw7potMOXHeheLDCGIGMHxo3oottxZA82N4K3OMGTtZT1U6hOpDd5LzIDoxqtBcpENIfjQXWtl4040aIl/+LETRy0HQPkwX7VUVm6B/KMNb8f/TQshhMuXA7SB6ANmNHsbwopZdUgOoMdJusl5UZ8WszXRRsiH4MDzoLlQnigfpa9JyIZQImrfi6WqEyUcouum00uGs0NvqI+GoFDz0byjMhBDKP4S/cuWaH91L0YMZQPSS9aCGUEJkAuFUOJiJIPrRQhgBFDeiGyFI9sBZDkLcmgqTd6G7kB3orlA2ihCpvDv+yze5vIjwVFreVSeaE91BwcWgACk3Oe/fM8wqD4wbw4vqrCxlJQ+yG81F3leJW0w7yHgQAig+DG+l60D2Vf6Z96B5EN3ftFwv7wmlMKrzv0I4oHfugN5Zye7epu7p0eld1u5uZvSwYCaLZ3HxHJbNguvOZeksFs/gorNYMocLZ7FgNj0zmTitaszE2KmTGDmRaRPrpk6nZxGdPzp4CAUvggvRgWRDr8K0k3eQd5EJk/KT9iH5KIQoRtFC5L4hEzxUsQkVfGQcpB0IXgQrsg/Fj/y1WXJ5Br88e6F4EGNodeg1yG5yVeQc6GG0cmu4E9GF5EBwknNiUmleyTkQbEgOVA96edcRpOShs5yo7kK2kwv5W2KIQQoeCjZkG4IXOYgeIedDj9MeRnWSCVDwU3L6Wv9G2n9TeWuqOMkHMMu2sy4KHgwfog3Zj2pHBMWC7kWOV86viw4UuzXlR/dQsIfbfJVQ9XJUteRG82KE0avRQ+hW1CpyNtr8jW01pMoOf1UoTvJRdC95Bx0edOc3/Y5qDRkPkruSxyC4kMuvJNBcZB0ITkp+Ojxo5XW+F82F5kX2kbGRc2B4KB14KLYYQfJRdKA4SVehWlEDlFx/f8P+jcDy69J0o7iRggg1ZGMkAqRCCDEkFwU/7SE0Fzknog+tbDDpQXQiedCj6OV8chdCAC2C5kd3YjjQHCgOBBdZD6oP0YFUhe5Ar0KsIudDOvBKoVwdPTCE03sauqaFpk1l2jR6ujirj7NnctFsls2CG85lx0XcuZx7V/D7y7j9ErZfwA3ncvUi1s5kUS9L+5jbx3kzuesiXL/wkHMge1B8lTV6+b5881zv9/o/ULl3WfahOFD/Ntzc/M+/sP9HJAaRIetH84w4T19wib5w0aCe2U1dM9u6ZzRP66ud0u2fOpUpk5k+he5pnDOT82Zy0Uwu7YO7V3H/lTy5nl0befoaHruKP6zh7pVsu5gbz2bFAtYt5JIFrJ7Pg0tp/uX3EP6rKhUmFyTnQo0h1WEkEKJkvmGP/b2+VYlBFMgF/gbhgoWdZQin9zVN7a2ZPN07+T9BuHgG587gwhks7YUnN7B7Ey9t5fXtvLqV565n53oeXcv9l3HfxVx/IXcsYeOF3HA+ey5DOsbyPYT/otIilGpRY5iNJH0oMYRy6sY/+8L+H5EUQgUhiO4dcd7A+UuUBQvbe2Y3dvU2TO2tmdYdnTbNPmUy0ybRNZmeqZzdxzl9XNjL0l54/gZe3cpbO3j3Zt7ezsvXs3s9O9fy2Ap2XspdS3l8Obcv455LeG017UfzPYT/ouqAPCSt6BEyYIII5oGrkd/r25UUQrMghtC9w89V5l0kzVtgds+KT+mpnjo9MqnLPXkykyYydSJdk+iewqJezu39GsI3tvP2Dj66hU9u4b1tvHYte67iqcvZeRm7L+XBZTy3godW8tgK3rmSzl9+D+G/qnQbIiShEMRooJBAC9Bx4HPX7/XtSoqiWZDC6K4zFguzLkjPnqd0zQxN6QpN6nJPmWKdNJHJ45g6jq5J9E7+rxDu28b+7bx/E+9v463reelq9lzOU6t4fAV7l/PwZby4iifXsOsKPtzA0GO/h/BfVckSWpwOkKG+lkiCVJziN86/fa9vUWIEzYoURnOetijbd27zzLnC1D7rxGlVU6ZYJ05kwngmjmXKWKZPoHcyC7pZ3M353SyZDq9t4fUbeWsL+67ntQ08t5an1rBzJU+sYu9KHlnBi6t4/AqeWcuHG+k4/nsI/1XV1oLUTKmaNhIlBg1D+HEV4vcQ/l9JCKFayjM3Jy9MdJ9d0zsrObmH8VOYNImJE/jtWMaPZvKYCoTzuljUxbldXDQNXt7CK1t4fQuvXc/L1/DcOp65kqev4JHV7F7JQyt4fiWPrmHXWj7YyA+Od3wP4b+oOkAIIMt0cPm1PP80m66t1wrfQ/h/pVwQ1YIYQrGdOL9l+qJYz8zEhG4mT6b8GZwwmgmjmDSarvHMnMScqcyfwuIpXDAFnruWZzeydz17rmbPVexey+617L6Kpy7nxdXsXMkbK9i5kj2X89kmjjgVMvZKSKjsrvTgqb5v6o7/Z0mOkaujADoYEgkHBZAtZGxj5/LVLn4+HNrqyEEBUgqZdoaUJ8phMMgD8JaOGMPmq3nsTu7fxI03cfokaGukrYmh5U7oeoQEeegsd2BDp4pqR60j60CrQfOTg1IzWS+lMEpDKAm6hR8XyUEntlQtmSwtbfwMhHTFFEyvptGKAELKmqolAWoEKUoOOqorrZjJFCbkGxgCqo9BIMHgHA1cuZh7n6BZSaC2MBRUBxk/RScp62G/9P/xUSiFyDlQPaSspGFoFC1EGtRh6CC0kHPR3EapMdhyKBIYVShujGpy9eRBq44f3to7vhwFA4NtNDShw6FxkrhbW2l3YtbTksAU6awjBz8GaQC1TQyNoLVQAgkOC6E4ESGVqzgMpCEbIx9EiKIKdFhIfodeIn50C2I1smvk7Oq5s5gxLfbbaYyfyKSJTJzAhNGMG85vz2DiCKaPonsUs8awcAIXTIHd69m9jqev5Kk1PLWGpy9n91r2XMWutbx0BU+v5rVVPLmK3Wv4eCODT/7uQKh5yNViWlBBa0XwUIJcANFy0w08ejN3bQZRJNFAHnJZMlFUqGtAT5CHVOOMBY7N9zBpEUN/yJHD0j8fizkqhOhA6ERzoFTjcdpSbcgxpBbqGjDiNINqJ+mumI6nfaiQiSFD1kWiCclBO4TBqMEEvYX6AB3ghVwHDZCqYRgUQGtDhBIcARlI1aOKtIDoIOFCryIHrQqxOmvNj8jAT1TqBgbikc3z2XINHleEgI+OA0OoO4iVGDyADBTsJNy44pjQBj8GA0wLSTCryCYRZMIubDGG2WnkP46PvXIHiAI1bjJOmgNIkImQttKQQ3CSgUOgFhpBFhGiwTA0Q9GDaSERoiVOHWQ85H9A0k0mSmsRzU9dFKWaFmjMUfraaOO7IT+6BSn+/4NwwngmjOe3Yxk7mvGjmDC6vC20TR1H73jmTmDRZNh7Nbuu4MlVPL6cx5ezczW717J3PbvX8+o6dq1l35U8tYbdl/PBetqP/e5AmIdcHC2CBIoPzUvBTyL+m2P8e+7k5ydWf/UQHGolW8tQUMCAw9toS6IKJO2FQ2offZAZU0GCxiqyP6HFiQolyBVIM+RnLFjBiGkMG2bxJuPUe0hxTJd80mRINFCAdHX2SNvwOaA3kEP8EfNnxVvl2CV90jmToK0Os1b9KQsvYuk875QRMWt9imExzCoSvtPOVNfO58SxtQzJ0gDtkI6SHogBRTtFaMkmDrGNOYOz53NmF5IQwWdlEOMv5NntPHY/c5dy9AxIHxjCgp+CggSHtdGWqBvEMbP48Rom/1JEhizoIfQf0eY68VgWTqfnfH7dC3V0Hsf2LezfzvFLmTijBtN62iiOmwK6jRJkIvVHBybPh0KQjnTplNaZExo4gu6JjJsBSTtCvOXIxu4prLyEjjOhNcJQUCMIqY5TmbeEWedx9IggBQfNoHf88x+k/6Fk33+GcM5MZkyLje9i0kTGj2PsaEaOZNQIRo1g+AiGj2DsOCZMoGcS86fACxvZu46dq3lsGY8s54lVPLOWZ9ezZyOvX8OeDey/mmfW8vTl7F9H4ZjvDoRFyMWQUwhWJDA8SFES1Vde7F2zHPyhF7bQ1QNSicPBjJCCQ8MIFkRIWOefza57CLsg6SMfwmil1IoBErRaZl3K5ocZfxYzz2Xv48KULkg5MMzzzuK2GyGVogCJ1jPHVj33CA2DkiQ9J0yi/w3WbOPeDfxuEaTC55xT/dJTXHdhw+XnsezqNn4ESU+1XnXXXdxzPTt6ePwOtjyAU4bUQJJ2FNCdtNnoDHhEbr6LDWuZ2dN03jbbkw9RzDfRwdFz2LmZB25lzDyGToLGAQeEcCgUIWl3tuaOP5rn72bXjWxZwPs7m9acDUk/RTshx5ZNPPN49sal9F3G6AuhveXwo5I7rucv9/KzRYztrkViwyo2bQAZSpDkqInx954CoZ7m0K/G8sWLnL+VW+62TVkJCYYcz2MvsONi7u1t+uBRLlvSQnMLMhN72fUYt1/C+bM59xYHv4C029ea+ec/SP9DSZ6/QTh8ZmT2DPqmRn87jcnjGDeG0SMYNYIzR3LGSOtJZ3D8qZxwJqePYPxoesbBGzfwykb2XskTK3lkOY9exhOreeoKdl/D69fw3LW8u5Hd69l9Fe9ejfHL7xSEUhgxh+BEBsVDwkeH6/EnKI2HOi4+J/zizZCLk4HWDDknIijlqerwdXdyzZIUNTKDRDRIw+BqSg6y/mOO4r1niQ8Dl4UEo07n2QfhcKhtue08dm6GhihDoMU16hT+8ggBpZYsvx7Lm7fB0ZBx+FoT6Dz3CMceHyciUAslKFWRtmzYwOp14E3gN6vSbLyDKYud1EvkfAyGZD1ymkTr9uvYuJxYAtrCeP33XMdVl0M6Sty1eTFbLgdvhEbQQgdejoJpI9XkaLNdcRfjZrgDjT4IMIRPnuTwE2qp48w+nrsdBsdpgBSk2iiEcEXGjueVOyFeR8RCOLr1Mm5fA7EYRSttLceenv3rvdCZpjl/2sl8eR+5jrjVF6XBQoe0726OOQaaG3AdfcghNbc8wI9/UU/C/95eTv0pDq9JwoXgqpyvqN8wWvUvpjKEci2S44y+wIweuicFxk5h/CjGjGT0CMaMYvQY+4gxzlOGV51wGiefaR0+gvFjLdPHwzvb2XcDL13D05fz2AoeXs5Dy3hgOY9fxYtXs/sa3ruWvdewex3vrf9OQZgHJUwuVen0F0K02v5jLM/cDfkk9XQcJfY/CceAAFoTRYmMBa2GQWHahHt3sXCSG8mGZKcN9AhJB6140zXrVtr/sBQ8CTok8j5rmOe3R344CUKO+84WnrgemkMUoaX6pBPpfxgUNyn3MWe29O9sQoXBIYQcCcdrj7L0QshDa0d5BVg/uPWzJ5h6GOlimtHUxSxblnjuuQtaod2kCHKYpIP/qP74Tk47QqQ+TgFKA0cNM568C35YRz3XXcLtW6G+Hs2KfuDlaMO/MdhBC785Q7jrVWqPiNKZ5Vc22uPvb6P7PIiFnrstufJMH+lGBjdhglZNEtpyU8/moVtBV5CqqI3uWMPta6EuQoefbOPxZwT+eCeIkI6cNpwPHgAzSs5ApGUcHz9M56FpfgpHOQd2cvNjnDITNGn3bWzdRF0NjmQGIYZYTbuD4oHn9/7VJLorEIqO03o83dOYOs4xaiLjRjO2zOFIRo1g+BmcdCrHn8hJp3Dmqfz2DCaPgPdvZf9NvLGF56/h6St4dAV/WMrvl/DAZexezVNX8dZG9lzD7nXs34D6HVqO6g60EJk6pCpKkG305yzrN7JxdIhoEzFqc543r2ZqL9RFEGNkYiSsSNUYHhqTrzzG2rmQBaOKnIVCkcFNKFbqIlvuYsVkyEGpbELBG7ez5EKwNF5/CY/dDEKcbB2J7K9H8ZddMMhBY+bk04Mf7aAh00xaR4F0/De/sr9618BHHmfzxRx5pETW2/Qf/PVF3tzCprtYeyd3bWfPg1y0EsJQKKKB4EAN8O/0PxCVfwjD/KhNGAweTP9DcGSCNFuWc8tGaLSQh4R8QAgzKrKFFJeN1z59mD3X8uBm9m7l2m28/iRH9UFr44d3MXkENGBN+VFi5EHNU5ca3cdL90AhSgoS1s1XsnUDpKxI0Maxo/j0QVBStNacMIr3HoecBcFBhpkXW798kDtuYMU9rN3Mw+v44EF6JxxOhNwgHnqY93dzzUqEw0CEDK6Wln/+g3RQEEpxBNvJXbZpk5k02nrmWCaMqRo/2jpuNKNHMPp0Rp/OmDMZP5xRpzPqNMadwm9Pgk/u4IPbeOcmXr2BZzfwxGruu5R7Lub3S3hqGU9cwZsb2L2B3et4Z/13CkI1gBEgFUC2MAhy6bTOK7v4aDMztnHhTVywgfcf4IVboS1EB6jlwVArg6HO/txa/nA+pGuRLQwJ0RihEzRIJK98igtmQ8JKEg6JkvS9eB1XLABf9MJV3HktKB5SkK35t9N4//cwyE1LuHscd++GQ6HBRHbRCTKk6n91kv/xjbzxKO2HNZk/qn7uJQ7NKCiWqnSoqu0wMiI6mAFkNxKILSTdtp/R/wIcAkIsJsuk0Y+i/zEoNpKK3rqCLauhzkUHSN9QHYVOgQZmzrfd9hCWlgaMeiQy5VAUo410a/+jcCrkRVQH2QIa5B0kGd3HnptBF8gEaQtfuZQrLwexCSFOInzsSN64GzoDZDh6nP+NB6C5lsFR0izvlh6/g2avguKk4EJoIZEhCYM9ZFKYdPyCa7ez9/n80B/WotVgRv/5D9LBQpiznTStatIExo/k9NGMGWUdN5Jxoxk/ksmj6Z3I/F7PBXNqlp9Xe/FC77mzmDsNvriDT27lwx28s503tvDSBp5aw6OX8tCl7FzK3UvZvZpH1vHQ5bx0BfKxkLUjuf9+WK/+t8HnfxGlBqKA3MwgEIM2rzxzGq/chzyVvinqyLF0jvecPJ+P93D80CQC6JBOUgLJRXTAUdN46SN+noFsnHQIuRa1lbYwGouXRR7aCK4f8CsYEtcabA/fC8Mhq18/hyfXguAhD5mW4072fXUTDLMiMW5E+PkHoWi1tECijR9Z8VgopREtNS759luZvYx6kd27OfHoMA1VmAPI1qDUodSgVaNWkwmg1aF5EXjwWX59jI1kA4dAItlxZuCuu6ETmn+w/lLuuwpnbTNqDAWyVgaDWEvGeehRvPkmZX94lGraW0hXH/4rnniUoQaEBYaB1kIalCOpY+v9zJkP4ToKLtrDiHBENXTOncttj0OjlSFVpMTzz+H+zXhCTto9ZCL/fhr9d0MBspwwMti/A1ScuRoSNiY73noIMWMhEUeHzgRt1UgORIG2BIOhMACH9aZNbLoKQjBk4D//QfofSrZU2tYM1/EjGT+e34yxTBzPyDGhESMto0bQPY5lM7llCU+s5NlVvH4Nb27h+S08uB6+vJPPb+eTW/hwB29v4/VNPHcVu1bx8DJ2XsqdS3jqMh64gvtW8Pxq5F99dyBULIh1iDE6IZGzpsJbH2TBeKj3ePwt9kYbbb5oJvLIdZ7lF0NNG52QrStbKtLa4he9y9fV3vsg/AS0HDUODoFfQR0nnWp7YydnH5/CAT778qk8ekeAgp9AzamT2LcHfh4m4iRVNXI2Hz8KpWrq2kac4H1tNwguWrxkBzKEIR0hMiDz47Yf7NzGnJlkHP+242L/Q78nPqyKRshCRwDTgWqpTEVIoEn12YZNV9hu2RTMZKhtzUT8zrvuZmZvLVmorVu1hpuvhTDItUjN5GwMAbmBVNOPfzjw5ftpyqQsvjpbrpYAJLPNZuON97FmE8E2G03/Rmogh0OH0xfzjxrBM7tbBh4GQhOxJgZZ0Qk35CaN4qFHSWj1NEZo5dhu7ruPwYOhPoYYnXIe793jIe8hxKnTmvsfBgWSLtLVdPLGzU1zzoZDrcRkGuy2wyEBJhzaQAoitU2y9dbtLF+Mt9n6XTonzDpQHMgNGJGTRtomjOE3ZzJxJGNGMnEM3RM5p4erFnL3pexezUtr+GA7X97DVw83vn9/G1/ewRe389ntfHorH+5g/428eS2vXM0Tq9l1GXcu4YlLuXcF91zCs8uRjrZ/dyAEsYVcI+0gSE1H22/Yx9AhA5CbyILiRIFMdsWFvlufhE4Hog3JhRGlHMwWkzNDs2dt4dMn+WA791/MXdtZsbE+UtcU84ZmdvHKvSy7hOu3c9ft/PDnkITOZnKN76zmgZuE1zfFt63jwa30P0htgepoamwfD74AgyHlQGLK/oMAACAASURBVE9wMrdua77uDlat4OWHuOKaIB2QtDQIbLuU5x5l7Xauvp3zNwWLw6mMRwgR2gVaQKWmhi1bzB23cdEStt3C5mtIiknSTvT4OVdz9fWQstIeJ11HMkPBhQQS/34C773Fhhtja7dz52Xceg/HTnCAa9gR3Hs3D9/OjVeyax233QIGpAo2lXMW8v5jTTuv5Z2r2HEj/BQUW+RQ7riDp7awexOxn1oKbbH7VvPHJ3hmC9sWtz27lc9vh0EqtY7jepTnby13IIVQcmQtRx7JTffxwK3sXC69upE/bCbUAcOqXr6Vx278/9h7z6Co0r1v96ITqQkSxIBKHFLDkExjGLMzRhTEMStmgkPOTc4gCAiiomJAFLMiRpIgxjGnGWfMOedEWOcD7OfZe59632+n6uzaU3V9WdVdvbp69bX+d1r3j3OVnD/Mns187wyde9Dv/7wF5v/fsJHjoI3CDCcDr/mSYB/mLSJmCYkR5CRRks2OfKpWcK6YmyXcXcfTnXyuRvitW8uFnnw4zIcjfKzi41HeH+ZNJS/28HQn17dwcyP1K7mwgroiqnO5XojdRPl/jISu0EuKrT0K9bZVIGZLwEILB10GgF0PHMFO87uepuMXgwLMuqKA3t3opYET9NbAqDNWMEr03eLvHRabMRkGgUMXeplijX4fh0F+Nk5e5jjY0VEbZ3AGBztM1Fko/3EmDIJBWHs7MhAG9uhm32fCAhH9+uJkgb05lgzsYzhslPmgGIZ4goUJtmqM6optP7mZiV5/rXneTJyJwygJlmAup893OHXFUs6gEXSF3naYawyf+t28QJvv3aCjCcZ69JTiKLfyYPg0bYx1GSDCEayt6NOBPirYIlKwKJSp8/D0ZdYc+c9xMBAGjMDFDjMU05gYw09zRNh3YlBfHMAMLI27Den2wwLGT1TRngUOEqw6YqohG6bWbwk2U6G/CIU1vbSYgMKH7sN709u4YwQ4dMPawHC8zsK50E+MjQ6mhvTUxbQj5nSZw9hQBk8DFxUsdenthMLSdbb+6FA6jZfi2AMTXX7shtl/TiV01MVJF9su2GssnE9iEFFRrE2mvIjDmzmzW+38Di5s5Ooa/izmXjEv9/LpMK2NmsIZG17s5/UB3h7iwxHeH+LtAV5X8HIvf+3izlZOrOFyEbWFHM3m2nLsJur+x0jYUw8HULhgrYst2OvQRQUFWGrjooZdFwbo0FNGJ1e69cLVGGdT7MSYy+ljih30AlsDzGyw7UcnMIc+WpiDGfSDPh3oLcEBrMHKiF5SnFSx6YwCXMFWTc24B+Zt8UAm2II5WHyPCVhKsIKeYA9mYly74dQBuRa2MoZqtr/UHxw70akzxqbYOWFpgYUh9jLswAmsDBgMw8EZOoOBBa6d6KOBvTq9wF5KV7DogokZ9uAC5mAnorcIZyO698JaSg9jzA2x1sNKDftO2LTdPsCiGxb62OvjpIY9jARXdWxUcIGeUkwVWEJvYwaCcwe66DEQTM0w60Zf6K+Loynm4ADdO2IGtio46GElwhice2BlRHcxA2UowNmJIbp0BUcDHF3pJ8EOBuvQFTqBQs4wY/pBH3D5z9kjx1GKkwRbXZwloYEUJ1GUw8HVNGzhUgW3jnCrguul3Cjm5mpuFfNuP28qeHuA90fgzjbu7eTpPp7v5/l+nu/j2R6e7eHmDu5s5UQxl4uoLeBoNlfz/7MqoTY9dFGYoYA+ciwt6eVAbxG20EMNRxgK9tAL7NRwleIsoqcunaFnV5y7Y2OAvQZDOtPRFIUFdjoo5Cg06GOIowwbMIVepjibYQJDOqIwwkJKH+ijhYUERxts1bCA7lJ6WuLgQh/oCY6dsDPBxRYbNfqq0gssjHDpgAJMuzGgC9ZgZYYzjATHf/QD+8gZaISTJo5yjDWw64mlOf006Q2WEpy1cYHeHVFAHzUcVOllQi9rzMU46uIqw1oXBdiDdTdsaU+GdNano0Ti6ESXTig06KODbSdMzOlsipUEW7AVYd0JZ01MEJmZaZsY0gNsbbA3xNQIS0dsoYu2VvfB2GlhLMVeTm9TBoC5Gi629BbhqIqNDmbquNjh2B1nTVygrxOd9ekCtmCtRXd9rPSwNcAcDStzI0en9oUBLp2w0sDqP2ieEOxBoUN/aWYcu/MpX8WJjZzYxOVd3K7gr+3cKOHmGu6u52Epz3dzfwt/lnJvG5xbzeUSft/Mn+Xc3sqtLdwu43YZl0v5vYT6Ii4WUrOcI0u5mo/NRPX/GAl7qmHbDQdtrMDOCHMNnPXoDi5qWH6PA/QSYWFKP+gHllpYSekjwRocOuBqiYMNlhrtS7F+1MAW7MGhA9ZW6OnhakbPLhiJsZBgq4qFBlYiekkxacuTgcGgcKL7D9h3wVkLM7BSw6kbDiJswQq6wwAT+nzHQFUsO2KFijmSnnqYGuHwA9a6KOQ4aDCwK/0742SAtT4mBiiscdLFHhykGIOLEc7GOOhhZky/zljrYKvWvkzPUYy1Dr264wS2Fjhp46pGz+/oZ4ajmJ52OOjSS0R/cAYL6AF9JDjAcBEO0N+G7gY4dMOuE3ZyhosYLKIfKDSwBDPoq0kvGCxHATbgYsEwXYycsDbF9XtMZDhqYC3BTge7bjjqoVDDRQMz0FWhvwyFGs7fMbgT/UX0AEcD2uIrB7ZtzKGHxSB6OOPwf80D/P8V9lIUImz16KeVmyg5tIK9Kzm1llOlXN3OrV3cKeduGY+28nwXL/fqt42A3tzE/e1Qm8OJ5ZxdxYU1XFrLxTVcKebqGs4Uc3kVNcs5n09VHoezuJKPzcT/nIEZGxH91HCUYGGKrS7DwBRcTXCEvg5Y6GMux9EZGx2cwUoPux+wh95gb4hVW4ZBVxTqWICLDEdVnPSwktFbFXvoBwoRvVXopYurDs7gqo+jBY4yFBYYm+EAP0JP6AOmuvQFZ00suuGijasOffRx7ISFBFMJNioo5PTrgXlH7LozAhzBsjc23bHQwk6GHThDLwkKCfZyXDrgAjam2EtxhEHG2IDCGFtQWOBoRc+uOLalZOpiC07g3I9e3bECM3BWxQpczXESYdkRSy16ybDvgZ0rjp2wB2s9FGLM1XHRoW9bOt93GMuxaJt1tMSpBwPBDrq2xcE70VeEKdiCXXecwVaEsx7WnXDSw16KQpde4ACOcux7MBCcRVh1xKY71uAEfWVYgZUrjqAAOwvMpdhDP22c/nP6hK5GOGhhaYSrdo5S9VA+ewo4vZJrO7m1j/sVPN3D89282c/7Q50+HrW6sp5zq7myhlub4WAqh9OpzqQ2m/qlNGTTkE1jDoez+C1Pszad6hzOpXFOSc0K+k2QYSnFSRc7NRzUsRVhrUJfA+z+3lDob/7L0aU32OtgrbkuRePUJrblcHOj0Z3NPNjJo0oeV/KyktaGXl+PW9zbw1/r+H0111fyRzHsjGZPLPsSqUzkQBKHkziSzNEU9iXTkMLhRCozOZ7E2TiqVtJrLFhIsZdjKcFJC0c5NhJctbH7e2u9v/nvxlkPW7CRY6NdnKZ7ditH1nBjNbdLub2VB/t4foCPVd2Ek/2ajne/v5s7m7i5lj/W8Oc62BbBjih2Kdkbw94Y9sdwII6D8exNpjaOo4lUZlGdqHIqlaNr6TMWbDRx1MNKDQctXHSwlWAva49A+Ju/+a/F1RBzsDfAqcOqNL1Tmzi9mVtF/FnKH6U82MOnapFwordwdlBzg/7Dvdwt5a8Sbq7lrxLYEkF5FLui2a1kj5I9SvbFciCWfWlUR1OXxP4sKpI0GzOoKmHoBLDToqcR9jrYauCgja0MO9n/Lcjlb/7mvwFHLeygpzG9NYozdeoKOb2G+2v4YyN/bOLlfoST3wu/DRZO9fpWy9O93N3EX+u4uYZbJVAaQlkYW8LZFs62cHaEsyuS3dHsTORQKLVx7Eljd6JuXQa165gzGyxEOMhx0WtP83PUwl4Nh7+3W/+b/24U6jjKUMgZwK482fFcanK5XczVNfy1mY9HjIRzPwgnen6rMnpXydPd3NnIX+v4cy13NkJpGKVhlIVRFkZ5GNvC2RHJrkjK4jkYyrFYdiazJ7XLsUxOl5CnBNu2QTZtHLWx08TVEAcNrP4emPmb/3qsRZihmEB9EZfzOLyUcyu4uJI7W2k61k04a/elSvPFbp5t49FW7q/nzlpur+H+etgcTlkEZRGUhVEW/g8Jo9kYz+FwjseyI4H9mSa1aVwu5ugKqfGELpiBnYieethp4qKPkxY2/zmTqn/zN/9f4KKPKTgRGie9uoIbS6nKM6xZzrlVPNhB63Fj4ZTu20oebeVpGU82cX89t9dwew33SmBTaDuloWwKYUsI5WHsiGR9HEciOKakXMnetK5HYjm/nHPr1CdHD2ufbu6ph5W0PVfV8f8c/vg3f/PfQG8jTLAdo7trm/Mfy7icSF3Rd4eKuLSWJ3sQTnYUTvByP4/Keb6Vpxu4V8KtYv5cxa1i2BBGaRibQykPYWswZUGUhlAaypYItivZFce+OPbGcSCZ2hxOrqC2TH/xgrZGqQznjrjqYq+BnS52au356QoDFAbY66PQwV4LhRYKOfZa2Ovi0KarOgpRe/imnSF2BthrYS/H3gD77v8IUpWjkKPQwU4PGwNsO6IwQGGIwgg7I+wMsGs7SwecDHFqS73Wwk6zPdPcQQNnCc4inFVwaZt5F+EixkWGQheFDg5aOGnipImTRnvSvaMIRzEOIhwlOElwkmCvghU4itsPnSQ4qeCkgosIVzE9xfQU4yzGXgUHEa5SektxFeGkipMIZxVc/7Em0wl6SnCUYS/BQYJTWxilCg4qOItxlOEswUWECziDI7iI6a2BkwRnES5inNtOCq7QS4SjYXvQt5MBjnrt64bbUn4d9NpR6GKrg50uig44S3AUYy/GXoJj2+M2MhRS7NSwU0chb/8QhQa2qihk2KvgIG1/m70Uhax99LvtKROFBgqtf6CBQgObTth1QtEBey3s1LBRw1oLG10c9bCVY62BnRb2uih02r9S26GDHvYG2Olhp4etLgp9FB2w08FOHYUMeyn20vbv2Qf6WeFgia2E3iJ66qHQwAVc/pEc7iDDWQNnbZx0cdDCUdx+3Z3+8WO6yHCU/VMwa9sQhrj9Qtvp4CjHRRUXMc4iHNSx18e+C44iHCXYi+mlgYsMBxE9dbBRw1WOvQiFGEcDFN2x7IyVDg5yjJkwl/JVnN7E6SJqs6hdyskVvCmnpRLhCJ/383obz7fytIxHG7i/mnuruLuS2ytgXTgbwigNYUsIZUFsDmRTMBuDKQujPJLtSnZFs0vJ/kSql9JYwLV8GvJICOzYox+Ygh04SDGVYK+BnRxbTaw0sFLDWoKVCGuwVcFGhLUK1mLsJNjJsG3b2VaGlQaWWlioYa2CNViIMJPhIMFejEKEQoy9BDsxNmIsRSgk2ImxFmMlxlqCtQRrMTZirFSwkmAlxVyKiRQTGSaqmKphbIixPt216a5Jd026a2Osj7EhFhpYqGEhxlyEhRgrKTZq2MoxVsVEHQtdLPWw7ohNJ2y7oOiGqRFmnbAwwrwjZoaYGmDeEQsjTLQw1aNHB7rr0qMDZoaY6tFDjlk3zLpgYYR1J6w7YWGIeUcsjbHVxUoDaw1s5djKsVLDSg1bTcxMsDDG0hjLjpjq0EMHEz3MOtGjIyZGmHbGrCOmhpgYYKqHmQHWYK2Cjag9bVchxl6Gg+r/Bg8rJNiKsFXBToRCBRttbLSx1WnHRt6OQoqNFFtVFHLs5NioYiNGIcFSF4t/xUoHKx0UYuylKNSwU8dGFRspdmIUYmzakpulOIixF2EnRiHFXh1rMZYiLEXYitoXddiAnQqWKliLsZVhp4aNrP06WkswM8LUAFMdTOWYa2GuhYUeFh0wA2NNjOR0AQuw0sHMEHMpdrrY6mCjjZUWVlpYyrFUx1KdHh0w08O8A2ZyTHUw18fMkO4GmEkwk2Ehw1IVSznWWu1x4raqKKTt/zpbFazAEizAUg8LQ0x1sTXCUgszdeyM6NEBYzEWEuzVcdDGWgtzMbbgSkqc0d5i3cs7+WMLl0s4uYL6PE4W8nYL3ypoqeTTbl5u5cUWnmzmwbp/kzCCdeFsDGFjEJsD2RDI+kDWB/7LqOn2SPbFcTSDhnz+XMr15TTkGhXHGgd560ycxsBxuA7H9Wdd1591e/6sO2CU7tBxOmPctT2mak+doTl5qszNU32ku9owN7Vh4+U/uWmNdtMcP17eczwuY2Q9x6j3nSAbPJ3hcxk5l+GzJT9NYrg7IycyxhP3aZLJszQ8Z0k9ZojGzmD8FNw8cJ+Ax0QmTZRMnCgd7yYe5sZPHoyZKp4wu5O7l8XYBQ5jFvf6ybffJG97Dx+Fu7e1h4+Vh4+Vp6/dZD+Hyb6O45Y4jFls/dM8k59mGg2fpj9kquHg6V1+nNltxCz9QbP1XWZodpsIw2EwjIDxcpOxqmbj1MzGqZmMVe0+WmI8Stx9tKTHGJnRGMzHS60nqCrGi+3dJDYT1c3GiQ1GYTRYS2+gzGCwxHikmslodeORakZDZUaDVTsN0tUfINccqK0zSFfrRx1Jf01Jf03Vgdp6/TU7DdHs9rOW6RgNs3FS8/Eyq4maNh4dzN07WnoYWXoYmbt37D5et8sYueHPaoY/q+kME2sOUVH5UYV+Inr/o3jag5MIJxGuKvSEXsj6oNOfLgOxGYLDCHqOYcBYBo1j0DiGuzFyIiMmaA8aJ+83WmvA6A4DRncYOFI+fLTmuHFaP7jTdwL9xjFgLAMn0N+Dnh44ujNkrNqw8TrD3fSGjdUbNFpzyFi1ke5qY6Zoj/JgjCfjpjB+qsr4qeIJU9Xcp+tPmmHkMb3jpBlGU2Z1mjq7o8d0tfGejJuM+3Q8Z+pMnm3o6WU8aa7JpLkmnl7Gv8zpOM3LYPxcTbc5Gm5e0glzVccu0B7tbTTK12SEv/noIMeJiwfM9Ok3ep5hp5+hjw59zFR66+Mow0WV3uqifhpq/WWag1S7DtPsMUq7xxgV8wmi79xF5hMwc8PCTWY2Ts14pLTbCO3OQ9V1hmjoDNJR/1FHOkCH3nJcNOgppqcarnJc5LjK6StTHyrrNFqVseiOExmNoZuHVDIBAzd+mC4b7s4Ud2ZNZ9pM3D2ZOpWIEDat02uosXlxQO/dQV7t4tZGLq7lRCEn8rlcxLutfN7F5z283cbzMl6U8XQT99f+q4TFStZFsD6EDcFsDGqXcF0Qm4IpDWmvkOXh7InhSDr1eVwupSaTA3HUZ2rUZ+rsjmZHBAeTqUimIpnDKdRlcjafP9bwcCsvdvFsG/fLuLmOKyu5Usi1Av5Yzp8FvCjgWR4vlvNpHcJehGqEYwh1vD3Ai30828nLPXw6RGsdQgOt9Xyt5fMRPu3n616+7aNpH1/38WEPL6t4V0/TebFw01V4OE54PUf44Cd8Dv7yMfbLR+WXT1FfP0d8+xLV/C22tSlRaE4VPs4QXk9qffhT05/9Pt/o+/lG/89/DPry14h3V6c/vzDpRv3QQ+UmBVnExBCdSEquUWQ+UctFUctFEXmELSN0aTsRBcStlGQUq2WvkeSslWWu0YgtEoXmMT9a5BXB3Ch8kgjIEP2aJl4Ux3wlXkH6swN0Z/jrzw7sOD3Q4Be/DpP8Okz2N5gVyqI4AjLUwnJlyhVqCWu0UjcapW3slrbRIn29Zfp6y6Ris+iCTiHZur+miX2TxF6hlrMCzH/x7jHGy3joZKO+4/VdRup8P0zbZqShYoxBLzfDgR4GP0/VnThbf8bCjl4+RhuC2RbNkSQa0jmVybksLi/j+nIuFHEmj4al1GdRn0VjBueyuJLLgxTuxXNXyf1YHibxMJ3badxM5VQ2Z5dxLo/fcjm7jAsF/F7CvW18ruHbMZrrERoRGhFO6gqnjYWz5kJjd+FUD+GsiXBKv6mWdwf5cJCv1QinDYVz3YRLdsIVV+Hy98IlO+GiiXDBQLg2WLg+RLgxVLj5k3BnovB4lvDaR3gf1CyUfPtWIjSvvPT7JO9kvnfj+7E634/kh4kMmSoePU9zkrfW1ACNueHqfokGIZnGkYXErCZuDbHFKFehXKkSuVwUksOvSV29Yw3nhRvMCtafFtDR3cdw1ByNwVNETiM1rAfLe/TT7trbwHygnsvYDuPmG80N75GQQVYWyzJYuZz8fNYWULNJfHINd1ciHDQQriiE63bCWW2hHqEOoZrP+/mynxc7uFnK2bU05HMun0clvC/n43Y+bOPVFl5u5kUZz0p5sObfJIxhdSTFoawLYsM/aJOwjbIgysPYG8vRDOpzOZpL3TJqUjkcyf5ADgdTE01NPOVR4vIo8c5I9ik5ksDJDC7kcWMFfxWLrq7gt2WczOBkKmdSOJciupgsqk2nKoXqVE7kc6WUuxU8OsjjQ7zexYMybq7m9yJureXhZp5s48k2nu/iaTlPN/F8Ay9KeLGBJyU8XkdTGcIuhCM2wonRwqW5wh/Bwm2lcDdReBQqPAwUHvq2PvBufeAtPPQVHgUJj8OEGwuFK3OEc1OE057C6SnC+dnCVV/hZpBwK1j43bfl7OS/9vXes0ySE0lqNEtTuySmkpSmkpwuTkwRxSWijCMqhqgYYtNIyyI7VyU/n+XLRbn50rQslCn4B6n7LsE3gOAIUVS8RmSMZlC4ZEkQi/1Y4M38xcz3Ye5iZi5kxgJmLcLHTyU4QjMmSTchTTc5S56Rq5+V3zEzz3BpQY/sQvOs5Rap2T1iU4xClfIlwSKfANHshcyYyy8zGOvBiDH0G0qvAbj2waofDgPpNYzBoxk3kV+mMd8L70Vk+lAYzNZo9idwNJH6ZE6kc2YpJ5dJjqVzNInDCaIjcdTEiE7GS88na9QncyyBY7EcS+B4GvVZVGdxKINjSRxPFp1IlTemaDSmcDaHG2u4Vy66v4NHu3m2j1eVHd8c6PH2gPX7Qw4fjzi9rbD7cMD+0yHFh0rjp1u5VcL9jbzYzpdD33096thc16+5fmhT/Y/Nx/o21dq11FgINRZCnZVQbys0ugpnBwhXxgt/zRLuL/7wKrb5RYLwJeaPKz8siaTfaEZ4dBg6kUGjGeWO+0x+mcfMRcwPICCK8CTi00nJJjWX5BySskhIFyuTVMKU+ASz0J/Z3sxcyNQFTJrNuCkMn8CIceIfhkucB6g59tVwHiD9cQxT5xEQKUtVsiyWQiWrUylKoTSNs0XcyOdkLne28qWG1gZaammuQzhG8zFeHeLNQZ5UcGcfV3dxYS03V/J1I5+28bGcd1t5U8arMl5v4eUmHv1bc3RFDEWRrAhmVSAlAWwIYn0g6wLY8A/KgtgWzr5YjqRRl0NjPBcyOZvOgQi2LmFTsPraEFFeAKWJlCayOZ7yRHYnczCD6mXU5XN8OdXLOJLFoQyOplObwfEMTqVxNYPLaVxJ5+ZynmzmUyWtNQjHeFfHkwP8tY0rpVwr488d3K7gXiVPDvC0khcVvNjD810838XT3Tzdw5tKPlXz9ZS85doPwi231gfThMfzhGcLhLtBwp0lwl+LhJvzhN+9hOtewo35wvVFX/8Y8+X6yK9Xh3+9Orzl91HC7UnCYy/hhfe3W1FNt4I/35h/78Tog1sssjIISsA/vVNqqjwtTS8tTS81WT8hXidGKVdGakVHaKak6GRn6hQs61CUp7lquW5RfsdlS/VSUnSiwo1DQ/RDQ7SUSoPExM4JCV2V0Z0iIwyDAjr6+3X41VfPz8/Ix8dgwcIO8xfoL1zUMShQO0bZNTW1R1p654zMrjnLzJblmi/N7pG+zCwj1zx9mXVK5nfKRJOQSONfg438/A3mLxbNXiCaNgePKaJRbirDfhYNGCr64Uexy2Bpn2HiH0dJRrrhNpkZs1m4SOznL1GGkh7F6njKk9iXzMEUDqdyNJ3aFRzOpSKLinQqUzmUTF0yJ9K5GsGVcK6Fcz2aG3FcT+RiEqcTObqU6qVUL+VoJlXZNKzg/Gau7+FOJQ8O8bSKl7W8qZO8qZO8qZO/Pab9qkb6tk7y7hivqni0jzvbeVzB+yo+NvD5hMHnM999+e37T7/ZfjrT+etpvp7ic6Pi68nvm067fDvb9/OFoZ+uuX29Naf5gY/wuUR4Wyy8zbx8fLjfEoaMkA8f3aPPIH4eo+3mYTB9Zqc58w0WLNb0DZSGKuVxSR1TM3Qylupm5RikZ2mnpOslpxjGxRlGRugv8ddZ7Kc9f5H6vPnac+YZzphlNGma/oRJOj+PYcgIfhwuGTxSbcgo0U8TmDEX/1AiM0jIUk/N0Ehf1iFxKTlLqSymsYi6Yi7v5FktX07RdFrn60np+3qe1/L8OM+quVfBrQruHuL2bp5s+l8J32/h7RbebOZVKS828vTfmqN5SnLDyQug0J9i/3YD1/pTsoSSJaz3Z3Ngu4SHU6lZyq088YkkdgdR4k3RQlGRj2FJpOHWNO29seyLpTKGg3EcSaAqiboU6tKoTaQ6niNxHI2nNoHGRE4nci6BqliqlFTH0ZjB5dXc28Wbo3yu5/NB3u7hQSl/FfPHKv5cx51S7m/h0Vael/O27aZSystNvCrjVTkvj/KuvsOn865fboxtujO9+f6c1odzhUdzhTvThVuThZsThBujhWs/t14dJVwdK1yb8PXGlC/Xf/ly3fPLdc9Pf0z9dHvux3t+Hx8Ffnsa+e1pQMsDr1fXfmo8ZLJiJWGZ+C4lIY3EdJLSSEhBGU9ENKERhIQTn056Nrl5LF9OYSGFK1iaR1IWITH4R+AfQUgsEYmEJxAaR0gMfoG63kt0FvvqLvLTX+Bt4LVAb+Z8g1kLDH1DCE8gLkMUl0nCUtLy1dLzdZOyNZXZxOSgXCqLSJcGxot8I5gfxDx/ps3H04sJ01VGufPjGPoMVXEaiEM/vh8ocR4k6TNCNHCcyk+TVNxmiacvks5ZohmnJDOG4li2J3AogZpEahI5mkhjNnUZMm49XAAAIABJREFUVCVTk0RNPPVKTio5H0NjBGciORfDuQTOJXEqlYY0atI5mcaJVI4ncTyZkxlcLODmJu7v4G0lHw/RVN1NqLMV6hyEWkVLtW1z9XcfDxh9PNjhQ6XszW6ebObxRt5tQ6ik5Yhxa7V1a13vlmP9m4/1baqzaa01bK3hzVnz9+etP11SfL7s9PHaD+//+OnTvcmfn3q1vFkrvFnX8jitak9/r7kMG9V9tIf14DEMHCkfNl5nwhTDX+boz1qksyBA7h+tH5nYOS6TxGyScojLRJlKZCIhMfiHs9BXz8vHYNYi/elz9Txn6btP1x8zRXeUp66bu2iMO2M91cbP0HSfKfacg7c/UfEaEfkkFBCXT9JKovJIzGXHOo6s4lQ+V9bwbBetNQjHERoQ6mk5zovjvK7m2V4e7uLxAZ7s53k5n7bweQsftvJhK++38GYzLzfyrOT/JWF2NNkhLF1Cvg+r/Fjrz1p/iv1Y68s6P0qWUBpAeRh7YziUQlUme2L1tilZF0ruIrJnUDiNrYs4FM7uVHansjuF3SnsSWJXAjvj2ZHA7gR2xbMznj0JVCZxJImqBGrj2qmL53g6F4q4Xc7Lg3w+xteTvK/lcSU3y7mynoslnNvEhc38Wc79XbzYQ/uag3Ke7OTpPlqPSIVaM+FUH+H8aOGyh3DZQ7g8Xrg8Rrjs0XxpfNOFUV/PDf/y27Cv535qujC2+YKbcO4X4ZyncH6ycGmKcGW6cGNu85/e3/7yF+6nCn+GCVe9Pp8ceWWnxZYc0hOISVKLz5QkZKknZurEpmlHJWmGxUiCIlUCI4jLkKZkS5fmkZNPbgF5KzSzluslZWuFJOgFxMh+jSEwgZBkQpLEwYmy0GSNACXeESwOZ3EY80PxCmBGADMD+TWGqHStuGX6MdmayqVqCXlGCcs6KzMNQ5cSmiUJztD4NUltcbTGnCDRND/xlMWiiXNk42bJRk2TDfeQDRgn6zNS6jhU5jBY9fvBcufh8r5jtH901x45o8OERQbTgrt5RZoFJsij4kXZ8ZQksiuF/ansT6UimcM5VGayP439aRxI4mAs1UoaYmgM4nQ4F6Oll+I4n8jpJOqTqUuhNouadKrTqM2gMY+LJfyxgzuVPKnk5WHdD3WWXxocvzS4fKxTvKu2eFPV422d8Zsa/ZeHxE/2cmcrd0p5vosvh/l63OJbo2PTqR+/nhr65eTALye+/3Kix9eT6l+OOTcddxFO9RfO/Cj8NkK4NEH4Y5Zwz+fN66XC56JvL6J3bDUZPwnXwQz1kA/xZJinyk/TVdy88FzMjADmReATT1AKkWma0Vny6Cx5eIpqcKJ6UJzOksgOi4I1p/sw1Y8pPnguwm0e47wY48XYuUyf29Fzjra7l3zSQg3PBUxZgG+IKC7VOGcphbnahTl6RQWds3JYsZSq1fy2ghO5/LaSB9tpqUU4idDAtwa+neTjMYQGhMN8rOBVJY8rebqT97v4VManMj6W82Err0t5XsLTNTz5tz5hnJKIYCK8iV1Ilg9FfiprfFmzmBU+FHqz2pcNQWwJZ2cUFfFUpXIgmW3RrPImeTLR40mZQrEv25WUJ7M3nYp0diewO4Z9seyPpSKGw0r2K9kdxW4lFXEcjKM6hqpojkVRFUWVkpokTuRyvZTnB/nUwLeGTh9qeH2Qp7u5u5lrq7i4issl3N/Co2083cHznbzYxqtyXm/j/XY+HaKpCqFeJDQaCI3dhQYz4bi10GgjnNIXTn8nnOklnBnZcnZc0/kJzZfdW6+7t5wf1XphtHBxfOsl99ZLHq2XPIWr04XrM1tv+wl/zhduTPn227BrFd+VrSA2jYBU4tNU4lKJTyc+TUWZREgUAaEEhomjkknJli4rkOUVkltAdgGZ+dKUXHFUsn5wjMg/kqBYwhJVwpPE4UniiGRpUIRmQKSOb5TOwiitBeHyBSEy70Cpn78kMo7YZJKyVJJztJJydOKW6ccu04/OM4xNF0enE5LMEqX24mCj+T66XvPxmsvkyVqek7XcJkt/nigaOJpew3D+UcWpv8R1oEr/EZLhE2RjpoonzpFN9daYG9zJO9IkMNYsNNYoNpbcBNYnsz2ViiT2J3AkjqMpHEpjbzIV8VTHUB8uavAXHQ/mVDjnlJxL4EwSjSnUpHEknbo06lKoTaI+jVN5XC7h1g4eVvDsMM+PqL8+Zvn5pOvHRte3VeavDnX8cET3XRWvK3m5k8dlPCjjyQ5eHeBDtehjrVnrKWfhVL+WE/1aT/7wtcHu07HOTae6fD3p2nyyZ+vpPsJvA1svjmz9fWLLnZnCg0XCu3ThzYo3L5bk5ePpLv9prMaIyQyZoDfKU9N9us6UuTozFmvO85csDhOHxkmVqbpRSSpxGdK4TNXIFJF/LH6RLAxVmRuo4rmIKQuYNBeP2XjOYvJs0fQ5sllztWbOZ6433ktk3v6iRX74+BMcIYuO00/LobBQVlQgL8jXzFshLSxkawF1q6nN5XQhf5Xx8RDCMVrqaaqjuZ5Px3hfw7sq3h3l9QGe7uHpbl5W8H4L77fwrq0MbuJxCQ/Xcq+YO6u4s4rbK7lVBJHRhAcRupioBaR6k+dHoQ9Fi1i+iIL5rFzEej+2BLM9jIpoDiWwS0lZGEWLSJxE8Ciix7NsHhtC2RbPrmT2JLEjhu0R7IpibzR7o6mIYHc428LYFs7OSPZFURnJwXCqwjgczoFIDifQkM2VEh5X8L6W1hOdPx/j3VFeVnB/CzeKubiai2u5vYl7ZTzexrMdvNjGs6282MLLrXyo4ONBvh6lqYqv1Xw9ytcamupobtBqbjRpOeksnB7acnZs0/kJTZcmtFyd0HJhZOuF0cLFMc2XxrdcnNh6yaP1yhTh2rSmP72FP+YK1yZ/Pjv0SoVFaQExqfinkJAu/h8JoxMJjsQ/hIBQlahkUrLJLVBpkzC3gIzlopRccXRKh5BYcUAUIbEqbfpFJEsjU1Rj4kWRcYTEqvjHsiSGJVEq/uH4hxCRiDKVhCxZco5qUrY0JZvUHNJzVVLSiU8mJAbvULX5fl1mLegyfY7GlFlMmqY7YbLmGHeNoeNl/UfJeg0XOw0WfT9Q9MNw8eAxqj9P0nCbqe45X226r/b80K6+0eZLYswCY4xiYmWZ8axJojyZ3QlUxHMwjiPJHExlbxIV8VQpqQulfgmNIZyO4JySc/GcTuR4MtUpHE6jNpXaZGqTaEjndD5X1nN7J4/28/wwL47K39R/988Svj+s9fYoryp5sYNHm7m/mSc7eH2AjzVaH2vNWk+5/KuEXf9NQuHST603PFrvzhYeLhbepAhvVzy+vzA5GXc3yc/j5CM9Ge7ZJqF86jzdmd5q/yNhdIpOVJIsNk0tNkMjPEm8RIl3OPOCRLN88ZjP5Ll4ejFpDr94MW2eZPYCNa9FmvN9VbwDpf6hGr+GqPkF8WswYVHSmAS9NglXFmoX5GvmF6mtWMHWAqqLqcvj5HJurOd1JUI9wgmERlqO862RT8f4UMPHWt4d5cV+nuzm6e52Cd+W/a+EbUOj/yJhdDQRIYT4EulNki85/uT6ketNwXzyvFjuxeqFrPdh0xLKQ9gdxaYQSgLIm49yIn5D8R1OzGSyF7MhlM0RbI5gYwjrAygLZnsYu8PZE8H2cLaGsjWUbeHsDmdfOBVhVAaxP5i9YVQoqU3n/Gru7eL1EVobNZvr+VLDu4M83cGf67m6hktrub6WWxu5v4XH23iyjadlPN3E4w283MbrXbzdw9t9vNrL6wreHuDDYT7XSL8c69zU6Nh6alDzmZ+bz41rOj+++dL45vPDWy6MbL34U/PF0c0Xx7VcnNhyZZJwbfLX3xc2X58tXJn08fSgS3tNNy0nLoWgZBLSxfFpKm0SRiUQFMGvwfwajDKJ9KXkFqgUFFLQVgzzRWnLJMpU/bB41SAloXHiyCTNyBTVyBTV6FRJUipxSYTFExxHYAIBcQQpCYgiMFU/IkMvMVsrbZlkaS4FeRQXUrKS4jzyMomLxS8QrwV6U2Z2mThVf/wU1bEzJD97yoaOlw0YpfXDCHnv4RouI1QdR4iGjpf95KExfobmpHmaUxfrzA4wWBje3U9p4Rtj7RfbPTxWNyWO5YlsTGB7PLti2RfH/mT2p1KRRGUshyOpDqLGj+PhnIziTAxn4zmVQENSu4TVydQkUZtEQyZnC7heyt3dPKnk5VH5q+qubxtsP5/s/eG4y9sq85eHtN8cUHl9hBf7ebKNB5t4UMrTHbw5yOeaTp/qrFpPubSe/KG58YfWkz98O27/ub5b06keXxp7/bOEwu+TWu94CY+8W18kCx8Lfr861T8INzdGu+mM9GT0NN0xUzXcZ6pPnac101ttfoDMO1zSJmFEgqoyRSc6RSckVuwbIVoYJJ3lK566QDRhtsRjtsqkOSJPL6bNZ9ZiyQI/1cUBct8QWUCkZmi0bnCUmn84geGEKVEmaqYtpaBAsrqgQ0GBet5KlRVFlK2geg0N+RzP5+JKnuyi+RjCKYQTNDfQ1Mjnej7W8amOD9XtxfDRTt6WtRv4ehPPN/B0LQ/WtDdE7xRxp4jbKyAmnqgoIkKICiI1hKxQskPICmT5InK8yJ5B9gxyZ7Hci+JFbAigyIdCb5bOEYWNw2sgMwfgO4bw6SybR858cuaTPZ9l8yhaRIl/+/TG1lC2hFAWTFkQW4PZHsSOYHYFsDOQHcHsjORoCmeKuLOdFwf4Wk/TMZrq+HKE1xU8LOePjVxdz5XV/F7C3c08KudpOU8282A999fweANPN/G8jGflPNvGs128ruDDQd5XqX6p7dLU6NB6aqBwZmTL2dFNv41qPjem6dywNg//SUIP4drkb9fmtV6b1XLF4+2pgb/t7l6ST1wKoami/5EwLpWoBALDWRL0vxLmFYoLV1BQSF5hm4TEphuEJ7RJKI1M0opO0VGmyWLSxYkZUmUqYYkEJ8qCkzQDkgx+TTDwjdX1T+kcmdExOUcrP5+1K9hRzJGN1G2hejN711KcS1w03ouYOl3Nc4r65Okyt5mMn8LoCaLho2T9h6v/MELaZ6xa3wmyMVO0x8/QnDRPZ+pinVn+OvNCjLwjTZbEWPrGKvzizIPjusTGaWTGsTKWjTFsjWFHLHsS2ZdMRQIV0RwI5Yg/1b4cj+BkNKdjOBNHYxzHEjiaxNEUqpKoTmyX8LdCbmzmwV6eHeBNVde3tRYfjjt+OtHnw3GXd9UWLw+pvtzP8wM82cPDLdxbz4NSnu3k7UG+1Jp9qVcIp/q0nOjT3PiDcKpfU6PD53rT5pPmXxp7NZ/s03q6n/DbYOHSKOH3ScLducJD35anScKX3DPHx83yYrw7Y9y1f5qkMnYG46ZreMxSmzJfbaaPbH6AyDdCFhonjUrWiohTi07UDk9QD4xSWxwim+unOm2hqscs6ZipYrdpkokzRJ5ezFgomrtE5BOkuiRMIyBSFqyUh8dqhipFAZEEhhMSRUQsiUtZvlx11XLdFcs1ClZKVhSxqYjDa6nLpyGXs4XcK+PT4fbZ0W91NDXy+Rjva/hQy4ca3h7heUW7hG8287qUFxt5VsKTNTxazcN/SHh7RZuEyaKYeFF0NLFRJCvJiGVpDJnR5PuTsYD46UR7EuVOtAeJ08icS+pcUr2IncqS0cwcwOQ+zBjKgnGETiRoAoHuBLoTMom4aSydyyofSgIoCWC9PxuXsMGPjb5s8GWDL1uXUO7HlgC2hVGZyOlC/iznWSXf6mipRzhGUzXvK3mym1tl3Cjh8mp+X8tfpTzYyqOtPNrMg3XcLeb+ah6s5ckmnm7hyTZe7OZtJZ8O87FG/9uxbs0nvhfO9BfODBXODGs+O7LpzPCmc8Oaz4/4VwknCdcmt1xb0Cbh61P9T+/qui6P+FQi0qWJGdJ/q4RtEkYnk55NQQErV7BiBQWFZOeTmkNcZofwBNXAaIJjZOEJ2lHJWso0WUymKDrDICrdICLFMCy1U2Raj5A0E//k7r4J3UIStGPT1Jbmsq6IPetoKOP6Lu7t588DXKmgeisly0gMI2Ah/gsJ8cXbG19v/BbgNZ2JbgwfyxB3hkwVu8/RbquBM5doeQXpLQxva4ta/hqv+DXeJiDeMiyuU2yMeraSwmjWKtkcxbYYdiVQkUBFFPuDOLCEo34ci6IhmuNKjitpiKE2liOJHEniaCJVCdQkUZ/Bb4X8vpmH+3hxkPc1332ot//Y2PtTY78Px13e1Zi9OCh5to/HFTzYwf1N3C3h4WZe7ObdIdUvNd99rW9ri/ZpOt5LONWn+YTTl/rvmk9afz3xQ8upvsKZ/sK5IcLl0cLvvwh3FwgPfVufpAifUg5XDvKYwvgpjPXQGTNJw20mbrNknnPUpi6QzfJVXRAo9ouUhMZpRCZphsfKIuM1QuM0fg0XLQgUz/FR+2WezG2a+KdJkrGekgnTJZ5ekpmLxPMDRH6hav4R6sFKeVhch8h4nbAYSWAUgeEERxGqJC6T5XlqK/O12iRcvpL1RVSUUJ1D3TLOFPDnJt5U0tqAcJKW4winaG7k87F2Cd8d5WUlj3fxeguvyni5iecbeLKGx6t4tJKHRdxfwf0V3CvkbgHEpMpjktSUiZoJidopKTqZaWqZqWQlkxtNSgARcwmciu9EFruxxIPgaYTNIWQG/h4sGsOcocwYwvQRzBrN7BFMHYbHMDyG4zmCuaMJ8iBhJssXsXIx63xEG3xY7816H9b5sNaX9YtYt4h1PmwKZE8sx/P4fTOP9/GllpZ6hAZaa/h4iOd7ub2F6+u4sppra/ljPXdLeVDGw1LuruPuam6v4t46Hm/m6Xae7+LVfj4e4kuV+HNNp6Z685aTTsLpvsKZQcLpIa2nh7aeHtF87ueW86NaL4xrvuDWfGFiy8VJLZd/Ea5OF64tbL02q/my+9MTfRq26xfnkJhCbIZGYoY0IV2ckEFCuvh/+oT+IcQlkbGUwkJWrqSoiMIV5OSTkUN8lnZ4gqp/JP4RkpBYtfAE1ehUSWyWJDKFmHS1pEydlKV6qVlGiel6ManyqGSt1GRyMllfwL41NJZyfSdP9vPuEK+qeV7FXwc4vonypayNY108pWkUJ1GSxvo0iuKIC2ThPH6ZydgZTFmkNdVbY4af+pwg+YJwA5+obktizH6NtQqJtw1MsA2ItwmMNQuJMoyNEGWEkx3BmjA2RLG9rV0aSUUAB5ZQtYTaKOoiaYikPoq6SKqVHI1vl/BoPFUJ1KVxtpAbpTzax6vDuh/rFJ+P9/58YsCnxn7vG5zf11o8P8Dj3dzbyZ0t3F3P3XU83sKrvbw/LPpcY9J0vK9wamBzY+82CVtOOn9tsGs5ad90qn/rqYHCmUHCueHCpXHC77+03pkvPFwiPM1sfh20dZOT2wQmTmOsh9xtsv6EWbh7qU6eK526QDTLV7wwSLokShoapxGRqBkeK4uIUwuOES0JU1kQKJ7jo+E5R23cFNEID/GYSeIJ0yWT50pne8sWBIp/DZcHRMrC4jpEJBhEJ+pFxmuEKkUhUYREEaZEmUZ2rvrqXHlRnnh5EctXUryS3evER7KpzeFEPr+X8Go/LQ0Ip2k9gXAG4TQtJ/lSz6c63le1S/iijOebebGRp+t4UtxuYJuE9wr/IWFipk5Chl5iRufULOPsHLNluebLlnXPyemck6maGk9UMIGL8Z6N11S8prJgJkvms3gmiybhO5FfJxEwGT9PFnowcQQ/DebHgfTvT/9+DOuPxzAWjiPJk4zpLJ8jWjNPsmYBaxawchFF3hR4UTiHwnkU+7A9gtosrq7n3k7eHuRbFUI1zVV8PsSrSh7s5M9Srq3hajG/r+WP9dzZxL2N3F3HrWJuruFuKY+382IfLyp5c5B3R+Wfqrt+rOr86ViPpka71lMuwun+wukfhTPDhNMjW86Pbb3gJlyc2HLRveXipNaLU1qvzBSuzW6T8Oslt4cNPWu3aBRmEZ9EfLrmP0sYk0xoNIFhBIaJ2yQsKqR4JauLKCpslzBhqWZoAr5h+IaIAiJloXHSyBRis8hYSkEeG1dRXkz5SkqXU5JHcS7rl7FtBYdKOF3O9V083MvbSj4d4lsVn6p4cZBbu7m4nrNFnCvi4mrOruXSZq7t4MJ2Dq6lKI3gIGbMZeYSrVn+WnOC5PPDtBdHGS6JMfWPswyIt4mMNw+Lt/aPtfOO/s4nrOuvIWoRwcSHUhBEcShl0eyNZX84+/w54EdVgORIBNXh1EZQE051BEejOBLL4cR2CY/GU5PCqXyub+LhXl4d6vL5WM+vJwZ8Ofnjp8YB7xt6vq+1eHaABzu4Xc5fpdxey70SnpbzpoIPR/lc06nl+ADh9I/NjT98a3D+Jwmdmk8PEE7/KJwdLJwfIVwa13rjl9bbc4UHvsKznLcPZhflGf88mrFTGTFR1XO6yaR5eMyV/jJPPG2heJaveFGwpE3C8AT1sDjC4sRBSnzDWBCoMsdH7Rcv9XFTRD97isZNEbnPVJ0yXzLHR21RsKZ/hHZglFZ4vFFEQqfoxI6R8fphMeqh0YRGE6YkIoWl2Zorc1RX5Kos/3/4uqvots7lb8A/S7KM4TRJ0waatmnTnKQNNw1z4thOzDEzy44tMzMzW5KxZmaZmZk5zOBwzLL2d2E3bc/6zn+tudDSrdajmT0z77ujEcIAg4HseGpNCOqC0BiEASZeFWCxAZxGfKjCfB24LeC2rdSln2vwlo3nOSt7ai+S8CIOz5l4Go3nUXgeiaeReBKBx+F4HA54BH/lEfy1d9BO/7A9IRG/hkf/Fs7YFxb9S2jkBt/AVS7u/FZ2gkYmFG0dqGtAU4uHZgA9dejJw1QR9lpw0eex04GpGsREcP4CDp7CvuP45QgOHsT545C6iNsXYSsCL0mEyCFMEaHKCFFFiDqCFBGkjBBVROkgxRIV3hiIwYMsvCjAJzY4FVioxFwlPlViqhiPszEUi+EYDMVgNA53E/AwEQ/icC8G4wm4n47nBXhdijflmKrEu0qBjzVb3ld99bl253zTz5zWX4n234mOM0TnJaLrGrdHguiVJPpkuAOy3H55br8iMaRGjGgQI7rEsOpsn/ij+gMVqaQwHzi7/Y3QzQ9uvryOHrBygJk1zG2oywgZUf8fhBYuMLCAgRmMrXjMHUnLCP9koSAFjXnoKURPDtrSUJ+M+mSwY1CbjJ4cjBfhMRuv2PjIxiwbS1VfzVfgQxmmivAyFy8y8DIFL5LxMhfv2Jiuw+dWPKpFRZqQnwevPg3q9LXqZsKaFkK6Nqtpjl/fdtlJd/3JzG2vo9N3Nk4/3nbco2O7W8P8Gx1TYVNTWJkh1BRMc6Taocjhb4S1ZnwV1qi2Qo0Vqi1RZYVKW1Q4otIVNW6ockGlM2o80BaKkSQ8LcS7iu1zjccXW8/MtZ2fbj75qenIp7qdr0rxOBt303AnEfdi8SgBr7LwoQSfqzBdu4HbcpZoP7+CsOMIt/3QfNO+pbaDS51niM6z/0aoQzw2JF6HvJyUDvBaffkKRGRx8SZFQW23oi5ktKi3tMiKejxqRjx65pTb9nz/QIgvCDVognKavOLypOvypJuKFBk1qqIun6aRsL7FKhPrtWb2G6yct1i7bLV13mzjvG4ZoYUdLO1h5Q4/f2p0IG9kMMKiEByN6GhkJPA2RfHWBqPOH90ReJ6N2Rp8qsDjPLwuxOdKcJqw0Iy5RkzX4h0bL3LxKh2vUvD8TzyPXUmDz6PwLAJPIv6B0Dv0e+/Q733CfgqM/DU85nhU/Jmo+DORsWciYk8FRR31DNzr4PmdheMmYytBPVNoG8HUADR90AxgQ4OvMUJN4WsMJ2OoKkFEBMdPU/YfX/vtYeqWo6RvjlE3H+Y9fQqSl6AjBitxuEjARxY+snCTgocMnG7ATQIRmsiwQoU3WiLQG4vxVDzOw+tSvKvExyp8LMebAjzLwL1UjMVimImJGNyLw/043IvFvTjcT8HDTLwswIfSrz5X7pyu3va+6qu3FYLTVWtm6r6aa9rBaf0Pp+0Ip+MUp+sit1t0sVeK0yfNGZDl9MssDNziDClwJ1SJe1rEXRoxpsztv3qvcl9OrKB/EDwD4eIDJx+4+ME1AK4BcPKBrRssHUhmtjxObvALRDQDLBYYDEREIiiU7BdECfTY4ehE1TODmjF06BtNzQU83fBnDLpzcLcCrxp+nqrZ97xS+EUVHpXiTgFGszCRg/sFeFGC96X4VIrPxfiUj/cl+MjGRzY+FuBdLt5k430uPuZjphzc6nVE/Umi+RK3/fTD2j2FcfCwxW0LIZq5gIn12tt2mw3ttpm6/2ztc8TYbZ+653Zdj+1GzjtoNlt1TNdrGK5Vo61VMV5nagx7E4RbIMsBJfYoNEOBCQrNUWWGajoqzVBOB9sMpZaosEWFI8qcUOGKCldUuqMpEMOJeFok8KZi7buGgzOt5xbaxOcbRWfqzn2s+uklG4/y8CAZYyyMxeBROl7mY6oIn8rBqecnWs8vNf4+13BwoXn/YuuBxdYDnLYj3K5TS83niB5Rovcap/cyZ+gmd0SBmNQmnloQrx2fD9KNjAXO3sRNJYhJQF17razKGlVtqqIWRVGXT4kmqGkhRLMTpLvwWrnxWDlSbJz5LZz4ja14tU2pqvpUGTVBMVmKiNzyAyGU9EmaxiRdM14jCyET67UWdrusnb6zc91h67bJxm2tpbOgmQOFbk+yciY7esE7CIFhCA9BdCg5PhLJLNRFoj4UzYHoCcODVLwtwqNM9EVhMhb3EvEiDzM14LRgth7vyzBVgnsZeJCCB3F4Er1CbjkehOPBX5/hH/mzX8RP/pF7QxiHouJPspIvsJIvMBMvRiecDWUe9wn51cXnRxvXb8wdNprYrDay5Leh89LpMKHDyRwhloi2QoglvCyhqYEb4jh1gfzbKeGdhymbD2LTIcr6fZR9h3D6BCTOQf08jC7DXBTmN2C67gdDAAAgAElEQVQiBoubMLsOSzH4qeBPM5S4oSEEnQz0MTGajEe5eFGMd6X4WIb3JZjKw/00jMVjmIlxFu7G4m4M7sbgXhwepOJxNl4X4UPpms9V30xXb/tQvfl91ZpP1atna7fMN/+w0PbrYvvxpc5zS91XOT3/QDgguzgovzSsuIJw0oAYVpjvuTpetjeNCZ9AuAfB3R8uf61BuQfBxQ/2nrByhoU9XDzgH/Q3wsgohITx+gVR/Hy+tnMhaZtBxRA6puttrElRASjLwcNavO/YOdd3Yrbz6Oe272ba+adb8K4WryrwsgyvSvGuFB/LMc3GdBGm8/AqF69z8ToXU5l4lY7XmXiXhQ95mC4Ftw5E2x9Erxh3WORt75lO9vfZTKql01qaDem2vbCp82ZT5y109+/MvX42dtlp7LyDZr9T2/IbDdNvVYy+UjZaq0TjUzQiGxjDygiB5kizR5EdCk1RaAw2nbeSjgo6Kugop6OEDrYF2DYod0CZEypcVhA2B2EkCS/Y5Pe1a6fbTs+3X5hrvTLXdG624fh03U9vS/EoF/cTMRGLiVg8TMHTTDzNxOt8TJeDaD3DaTg6W79/oXn/QtuvywiXOk8S7ZeJrmtEz1WiX5QYlyEmVIi7usRTOvHKvK9GRkcX5yVwU5EsIQMVDT5ZVV5lTbKCJllBh/oFoakz2dIVlg4kayequSP1C0JpVf4vCG9pkVUMqVomlGWEt61W022+NrfbYum02dJprbmDsKkt1diKl2ZBpdvAzhVe/ggIQWgQIoIQE4EkJqpDUROEej90BGEyAS9ycC8VveEYi8ZkHJ5k4k0JZmowXYv3ZXhV9DfCx1F4HI5HYSvx4C+Hj8KAYOa+YOa+ENaByLjjMSnnEzKuJWRci0+7xkw6Hx5zwjf0N1ff3Xbu261dtlo6bbZw3GRvI2RuC0sbuNgi0g5xDoh2RLAjjGmQk8Pl65Rj54V+PEbacgibfyOv20PZ8At++A1HD+PyMYifgtwFKF3BrWvQEIOGCPTF4KwIpgnyXVEfgLZwtIWgl4GxRNxPx/M8vCnB+xK8LcLDDEwkYoSFMSbGWZhk4g4L9+LwOANPczFVjA9llE+Vaz9Xrf9Qve5D9bpP1avn6rYuNO/htB1Z6jyznAa5feKcPumlfhnOgCxnQJ4zpMAdUSUmNIk72kvj2kuDtz52nO8t/DEuHO7+8AwW9AoiuQfBMwTeYSSvULgFwtEbtu6wdoGrNwJCwGAiJgYsFqIZCIng8Q/h8Qgg23hAywyKumQD4zWejsiNwVANPnTuWhg8Tgyf5/QeW+jatdS9g9u9Z6ntANG+baFh5ZVYMxWYLcN0MT7l4mkqnqbiSTKe/Ylnf+JFKt5m4mMuZkuwVAei+xgxLrP0QGX+ntzzrrOj5f/xChG2dYedBzwDN3oFbfIK+tor6Gt3/6/83bbZ222h0TcpGm2Qp30lb7xGyZiiYgQdI9w2ghcdiXbItUWhKYppKDehlJui3BRlpig1QbEpSsxRYo1SO5Q5odwZ5S4od0VjAIYS8awEb2sw13pptvXcXMuJ+dZji60HZht+fl3MfzcVI5EYCsdwBMaiMBKJ4SjcS8LrfHCbji42/Drb8Mtiy/7F9t8WWw9w2n7ndJwiekSJrktL3ZeIwRvEuBwxqUjc0yIeGRGPNbLidiuo4qoEJBX45RXJ8qqQUYOCGm6pQ16b8k+EFi6wdCBZOVK+IFQz4JdW5ReVIYvIUSSVeRV0qGpGAjp0Pj1zKs1cwMhCyNhy1W1rYVNbIVNbIWMrXgMzko4RWcuQomcEM1u4+MA3AAEBCPEDIxTxDFSGojoQtT5oDsAICw/SMZmE7ggMhWGcgbsJeJSOqWJMV+NDOV4UrCC8H4vHUXgUhoehK3E/7O9AeNzBsNgD4XFHGIkn49IuJmWLJueIJ2WJs5IvLCN08fnR1m2btctWK+ctVs5bHBzWmtvBzBYutoiwR4ITWC4Id4WtJTQ1ICFNPicqvPcMaedRbDtI2fwzFXuwfi92/Yb9h/D77zh7BpcvQ0QEcpKQvQlNSVirIoKOXDfUB6AtBM2B6AxDHwMjcbibiuc5mCrA63w8ycGdZIzGYIyJUQbGozHJxL04PMnEszxMleB9Gd6X40MF9V2lwIfq1dPVG2cadiy2/MZtP010XeJ2iy73Y5Y7opwB2aVBhaVhZWJUg5jQIu7ocCd0Fgdl37ScbcraGh4EZz94hq3yCeFZFugbQfUJp7gHwckX9p6w84CnH4LCwGQhJgYxMWAwERbFGxBKdgqApSe06HyKWvzGNN5QN9Sm4Xkr5ruPcwfOE/1nFjt/nmtbu9i+ldt+kGg5R3TtJZrWzlTjcwUWKsGpwEwJPuXiSTIeJeBBHB7F4HEcnifhTTreZ2O+AJxKzHcdnp9QWXpqSjylLYxKf2g5kZ2K2HDERyI3dV1B+jd5qVvyUrdkJ68qjCTHB8LFBXpWZEU6n7wJv7IJVcuEomxC0jWGIx0MO2TYosAExQaoMCKXmaDMGKUmKDJGgTHy6SiyRLENyp1R7oxSR5Q6odYHfbF4UICXFfjUcH66+eRc68HF9n0LzXs+lu94kMo/GIEuP3T6otMHHV5o80R3AO4m4G0ROI375uv2zNT/tNC8b7H9t8XWw5zWE5yOs8SAKNF5kdtzjRi6SQzJECNyxKQq8UDn2eBVN3vckMF1aX4Z2TVqqoJySpBRxy0VyKmtINSyXLWM0NwZFvawdCDR7UnGVrw6dL5lhNelSSJyFCkVPkVdPg2TVXrmQvoW/DRzAZq5AM2CZGRJplmAZkHSp/No03jVdChK6lQlDRKNTnZw5/H0ha83/LwQFoiYSFSFoSoI9X5oCcQgE3dTMJ6IvigMhmIsCuMsjMfgaRY+VeBTBV4U4G4a7ifjfiweReJhKB4E40EwHoTgXijuheJeCO6EAlGJRyLiD0XEH/0vhLGplyPjTvuFHVhGaOW8nLI32zivM3OAiQ0crBFuhwQnxLohygPOtjDQhbwi+bqkwOGLPD+fxPeHeb/dy8f7H8qqfeTNv5F3Hca+4zh8Bn9cxlkxiMlBUhZqcrDSQIQ58t1Q54+WIDQHoi0EXeHoi8BoDB6l4UUuXubiaS7upWEsfgXhWBQmmbgfh6dZeJaP1yV4w8ZrNt6w8aYC76uEP9Vumm34kdP2O9F5kdstvtyPWVppikpxBmS5Q4rEqBoxpklM6hITBsQd/YUBmSf1J8pT1vv7wzkAPpEb/MJ4vcPgG0H1jxLyjRD2COZx9oOjDxx94B2A4PC/ETJZCItCQCis/WHuCS36WhUNPnMaYr3RkYl3reD2nSP6zxO9fyx2/DDXSl1sWcNt2Us0niTady81rJutxmw1FmrBqcZnNt7l4Gnyyl1A9xl4GIMn8XiVgql0cPIxX4rPrfvnxlWJ57bEcztiXIXbfnaiHJ2Z6MnCZMWW+zXf363acady+3jZxuEiNGUhnQVPX9y2g5YZtE0E9cy+UqGv1jKBtTnC7ZBii2w6ivRRYYBSI7CNUWKEAhryjZBrglxzFFqB7YBSR7AdwHZEjRd6Wbifi+dl+Nx4dqbh+Mf6X95Vff2sUPBOInpD0OaNJk80uaPRDY1uaPbCQCRe5GGxcd1Cw49zdbum63YtNO/5gnCp/TzRL7LYeYHbd50YluL03SRGZIl7asRdlQb2r9oauCqBG7JrZOXWamqsuaUMWY3/idDcDhb2MLXjMbIk65oJqBsKSqvyi0jhC0JN0zVfEBqa8dEsYGgOAzPo06FrTNHQ41NU45dTosoqUnQMKFYOJFcPuLnDyw2BvogIRUU4qoJQG4CWIPRFYTQeI7EYiMJABEYYGGFiiIG7KXjDxvtyPCvE3TTcS8S9GDyMwIMQ3A/CvUDcC8TdYNwNxmQIxkMBZvLvkQmHlxHGpl5IzBT5M+v6n5li8elXoxPOBkQccvP7abkcXXZo47rF1FHIxHYFYaIzOdldKNZL2N0BpoZQUyNJyPOdFMWBc9h7nPz9ft51BygbD1C2HKB8d4T3p+Pk/adx9CLPaVGSiBzfTTmSsgLMNBBqhlx31Pqh0Q/1AWgJQmsw2kPQH407yXiWhRe5eJaH++mYSMRELMaYK5nwQTye5+BFIV6XYIqNF8V4WYKpcryvJk/Xb59t3sttP0t0iRM90kSvNKdPeql/eWlbmjMgSwyrEmOaxIQeMWFATNC4d7Q/9UpMlh/MiRV094VzsLAv62v/SKpvBDUgen0QY6t/5NeewWtc/ODsBxd/+AYhJAIMJlgsxMSAFYOwKPiHwM4P1p7CuvSNqhqwNkVSIPqy8b4eRM/vRM8JouvYUvuPiy3k+UbM1fEvVO2Yr1s/U4OPVZipwXw95mrwsQxTBXiRjifJuB+HByw8jMHTBLxIwqtULBZgjo3ppm2LI+LEEzPiiSUxpkh0/jHbjLcVeF+NxfZfOJ2H5joPzXT+9qFlz5tmPK5DXwkKExEeCAdHmFiuMjTfrmX5jZ65kJUlgh3wpz3SzZBniFIDlBitCMwzRJYhsoyQY4pcCxTZosQebDuU2KPGE70M3MvBUzY+1x2bKt/7KG/9WCJ6wtDkiTonNDqizgm1jqhzRpMnekLwIAWfyjcQ7bsXGr6bqdn0uW7zXNOu+db9i62HOa2nuR2XuT2X5jrPEYM3iBE5Tt9NYkKBeKA83y/KDNooI4NrUpBUXC0vz6ejwaesCln1/1mOmtvB3A4mtjCyJOuZC2nQhKVV+a9J4posabkc/a9MaGRJNjSHPh16ptAx4lPXFZRXEZCWo0jKUFS0eIwtYe0IBwe4OK44ZAejNAA1fmgORGc4+qPRy0BPFIaiMcLECBPDDEwm4FkuXhXjWSHupOJeIu6y8CAc94NwN2Al7gRhIggTwRgPAVgpxxlJxyITjkUnnIhNvZCQcS0xUyQxQzQu7UpU/JllhPYeO2xcv1lGaO2+08TpKxNb2FsjxA5JLsJpXl8l+G4KdOOxpcNAV1BeffUlKRy/hoNnKXuO8n5/hGfnIZ5dh0m/HKPuO0799SSOnec5I0K5IsUvLkNWlAddHSF05Lqjxh8NvqgPQGMQmgPREoCeMIzH4X46nmTiWT4eZOBOMu7EYyIGEwzcjcGjRLzIw6tiTJXiNRvPi/GiGFPl+FBDnWn8bqHlN6LzItErSfQqLPUpcHrlFvoliUGZvxGOaxEThsSkETFuvDimPtV2rbdwd1IEXHzgGrEhMH5HQBS/f+RXwcwdoTHfB0d/7xPytVuAkFsA2SOYxy8YIRGIZoDJ/DsT+ofAxR+O3htp9E0amnCwRE4ExvLxqRYLHbs5HQc5HQeX2ncvNONzLT6U4U0xXhbhRTFelGCqHB+q8KkGHyrxrgxTeXiRhaepeJqE5yl4mYY3GXibifkiTJdhrhFE7z5iVIIYlSf6znM7dhMt4DSAaPuR6D9NDIgQI+LEqNhc/0VO12/zHbveNlLvsFGfioRQuLhsMLb+lma3m2a1ycaaFOCEeEckmyPTEIX6KKahgIZ8Q+QaINMAGYbINEW2GQptUGyHYhsU26DCBe2hGE7EZCbu56wajkd7GBp8UOOMSltUWaHWBlV2qHZAgye6wnA3FW/YmKvbzmn6eb7xm+naDR9r1s00fDPX8p+FlqNLbeeIzmtLfZfnuy4QQ5LEsOxi7w3ijgIxInGn+DtzA9INSYjIQVp5laIidNSgoUG6pU75X40ZM1uY2eK2zQpCTaPV0qr8VyVwVYbnpiJZXpvyX8+ERhZCBmYkXRPoGEGbxqumw39LmU9ShkdUCvKq0DOCiSWsLGFvDVd7eLgiPxAlfqjyQ3Mg2kPREY7OcHSFY4CJAQYGmRhiYSQWk8l4kIVHebiTirsJuMPE/TDcC8Qd/5UYD8R4IMaCMRoKxKadYCb/HpX4OyPx5HJjJjFTJCFdhJV8ISL2lF/YAVff3f9G+L2J02aaDcnOCiG2PH86r0rz2vyn77YI3zXO1nymxhs0dTeIKpDP3MDxS5QDJ/mXx4a/HCHtP0799QTfwZOUE+dI56/xi0gISUrxKcuBro5QM+R7ojYAjQFoDEZTMJoD0eSHziAMMzGZhPspeJqHh5m4m4J7iZiMxSRzBeGrArwuwZuyvxCW4E0FPtVRZpp2LbYeJrquEr2yRJ/SCsJeqX8j1CUmacSkCTFuPDuk9LTxXGvWTlYIHH3gFr01JOmHIMaqwOgtoTHfR8btDWXu8Qvb4Rm40SOIzyuU+k+ELNYKQr9geAbC1We7sdlXOlpwtUUxC3eKMF3LO9++ZbH9F6LjENG5d6mVOlODN2y8LMBYKsbTcScHD4vwohzvq/CpBp9r8ZGNt4V4mY3XGXiThfe5+JSHT3n4XIzpciw0gNsOonPPUtvB2Zad0y3g1IPbuIroPkwMiRJDcsQ9beKR1ty4ArdLhui6RLT/Z75x3aMylCcLhvhvNnX4mu64h27zta0tNdAZcc5IskCGIfIMUGSAfEPkGyJHHxn6yDBEhgmy6CiyXUFYaIUSe9T5oCMSPSy0hKPKGyWOKHNAtQOqbFFliSpL1DqsbnBFZxAmk/GuDAtNGzhN383W/DDfuGm6dtWH6tXT9V/PNu9dQdh1nRi8stB9kRiSJAal57vFiIlbn9vP10dBRRoS0hBTFJZRE1RUhKYqtLWp8uqr/9eI4n8hvCyNGwo8t7TIqjQ+bVPqF4Q081X6phQdI2jTeLQMKaraVDkl0k0pXJeErBI09GBoCjod1mawt4KTHfICUOKHan80B6E9FO1h6AhDVzj6meiLRn80hpkYYmEoBuPJuJ/9F0LG3wgn/TDph7GAfyBMTDsek3KEkXiYkfA7K/l0fPql2IxrsRkiUclnQ2NP+UYccgvc6+iz29Zzl5Xbd5auO829dpi7rDO3g60tPB0R7imYGLAlNXhnhP+37o5CNFOoGkJWhyKqQD4jimMX8OsJ8v7jpP0nsP8Efj2JQ2dx/BLlpAj1wg3qtRtQkAFdA0HmyHBDlS8aA1Dvh1o/1Pqh0R9NAWgLxVAc7ufgUR6eFOBhFu4kYzIeY9EYZeJxOl4X420p3pdhio3nxXjJxlQ53pZvWmr8nei4QPRKLvUpLPUrLw0rLw0qLPRLLvReXxqSIUaUiRF1YlSLmNQl7uhwxzXnuqUe1V/Jj9nm7Q7voDVBjB2BjB2RCXvC4/eFx++LiN0TwtrlH/m1byi/dzDFKwi+4aSgSEQzEBeH+HiwYhESDZ8w+AfB3hPG1rAyB8sNrQl4UYFPrSDafiI6thBdJKJTiGhbu1CH96V4UYh7aZhIwmAyRjPwsBivKvChCp+r8KEc70rxphhvCvA+H58KMFOCRTZm2ZgvA6cCRDWIGhDVWKoEpwIL1eA08XJ6fyfG5YlHhsRzM+Kh/sK4AjEgSvScJToPcDr2vmz8sTH/28hIYRsPmHh8Z+75g4XjencXxPghyR5J+ig05M80QIY+MvSRpos0XaTrIdMA2cbIMEGuBQqsUWCNQhsUO6LEBcXOYDv+Fct50gol1mDboNIdrSEYT8bzojWfK/4zV3NgsW7vYsO2xYbNc7VrP1XzfardNN+8n9NxlugQXWyXILr1OX0niYnjxJj80rDyzIRod/FuLxpuyENKDjKyuKXAo6RCVtSiKOiQbunxyOkIyukI3tIjqxsL6VmuMbJfa+Kw2sRBgG7Hb2JDMbCGvgVViy6spLdKSkXgmiz1hiyPhDxJRgXKumQdOh/NWtjIlmJkC5oF1dCcom9K0TWmaOpTVbR4bqlASg43lSChDBkVKGuSdfXIJsYkczNYWoDlgCJfNAagLQDtYWgNQ1soBiLRHYUeJvpZ6GdhgIkBJkZjMB6HsQRMxONuDO5FYiIIQz4Y8MagH8YDMRKIwRAMhgF/pv/xT4RxaRdj0q/GpF+LTr4QFnfaP+qoR/A+F/9fHH1223r+aOPxg6XPLku3LRb2sLNbQfhn4Nb00O+jg3Z6uay7bU7SpvEo6QncVKVekMCJKzh0mnroNPXAadJvp3gOnMbhczh+iXLyGv+5G1SRmzzLCIPNkO6Kcm/U+6LOF9U+qPFFvS8a/NAShMFY3M3Cozw8LcSj7L8RjrHwOB2vi/CuDO/L8LoEz4q+INw633iU236e6JHg9Mpz+pSWBpU4A7KcPsnZHvHlNMgdViNGtYhxXWJMkzui+rHjxkjZidSINV5u8AleF8jYEcT8gZG4/wvCYOZ3fhFbfEKElxH6hCEwAtEMxMb+C2FAMI+jNw/dDg42+NMbXal4XY3pdhAdu4mO9csbhtw2gcV6fCzH6xLcT8N4EvpjMZCA8Uw8KcIUG+/YeF+Gd6V4x8b7YnwqwWc25thYKMMcG3NszJdioQwLZVgsx2I5OBVYrMFSMz+3/wQxqUA8MSaemxKP9JbG5YneC0TXMaJrP7f7l6mWPc0FWxmRZHtPWHh85eKz3dV7Y7APb3Igkh2RbIB8fUrOchWqj3Q9pOkiVQ9p+kg3QJoRcsyRb4VsK2RZItcGecuzDVsU2qLoryRZZIliK7BtUO6MpgAMx+NJAT6Wb5ur3Ttfu3u+dvt8vfBMDeljFeVT7abZ5r2cjlNE5zVOx835bjFi8AbRL0X0SS6NXL3XvCshEIYKkFYmySryyCtCUZmkqkFR1uFX0uOV16f8E6GuxaovCM3sBU1sKHqWPDp0HjUjXnltfgkl6mVp8k05XkkFXllVXhVdQW0TQQNLQZoN1cD6nwgFviCUXrnBkUdSgXxLGWqaPLp6MDKCiTEi7FDgvYKwLRQtoWgNQX8kOqPQzfgbYT8Dw0yMxmA0HuNxmGRiMgyj/hj0Rr8XBrxX0uBIOMaigaSME7GpR5lJR/6JkJV2lZFyKTz+TCDjd5/wQx7Bv7oG7Hf2+4+jzx4H319sPHZYOPHb2MPDCeGewkmB2zLDf4wJ3ePnsdnSkqxvSlGjCUtrCojI4fxN/HFZ+PeLAkfPUw+dJR0+Rzp6nuf4Jcofl3nPivNeuQlZ2RWEac4o80K1D2q8UO2FKm/UeqPOG00B6GNiIh2P8/GsCI9zcDflL4RMPMnAVPHfCJ8W4nkxXpWuIFxqvcDtvrnQLbfQI88ZkOcOSHP7bs73y61MJka0iDF9YkKfGNPg9is+bbnanLM30g8u7vAO/SqQsTuY9XNMypHw+H3h8XvDY34OYuzwDd/kHSzoFUTyCiJ5ByMwDJFRiIlBXNwKQt9wBATzuPqQbV3g5YKcEIzk4F0D5rpIRMcubrswtx3c5RNoDZipwcdyPM7GRDL6mOiKxkA8JtPxKBfP8vGajbfslXWF6XLMlf9Fjo35YswVYbYQc0VYKAGHDW4ZFqrBbVlPDJwk7igST42J5ybEQy1i/NZS11FOx69E1x6i55e3rT92FH4VHw0Pb7j58oaFb41jfJvBWl3EQL4H0o2RpYscg5VCNF0PqbpI1kaiNhK0EK+PNBNkmSPTDOlmyDBHhjnSzZBpgVwL5Fki1wJ5Fsi3RJElSqzBtl3p39zPwfty8mztt3M1381W75ipwecqfKjCp9oNs80/czpOEF1Xl7rEZoYPEgOqRIc2MSTBGT9UlgIjHcgrUm+pUxTVKMpqPGqavJo6VFV9qrI+VcGA+gWhmpGArsUqmt0aE4fVt+356Hb8t61JOubQNIayAUVWgyImS7l4k3xTVkBSgV9WRUBZR1jTaLWe2Vp9C359C6qRJb+hGZ++Kb+OEZ+mPlVFiyKvQpJRgJgsRVSGLCZNkpThkVXkUVbj0dSCljb8LZHtiUZ/tAWgPWQFYV8EOiLRFf0vhANRGIzCUAxGYzAehbFgDPmg3wN9nuj3wogfRoMwFonxWCAp40Rc2rEvCGNTL7DSrjBTr0QnX4hIOBvMOukfdcwn/KhX6GH3wEOu/gecAw7Yeu22dtls6UBydkaIp2BS4Lbc8J8SIvcHeX9jYyNgaManYbJKSU9ASoUsLo/zYqvPXhc6dYXvj0uU4xfJf1win7xMOXmZckaMckkc0tIw1kTAXwhrvFHtiSpPVHqhxhO1Xmj0Ry8D42n/QjgRh5FIjDLwNHMF4YdyvCrC43w8LcRLNt6Ufb3QcJzbdonbfXOhW2ax5xa3X54YkCJ6xRcGbi0NKxMjmsSILjGuR4xrE4Mqi52Sk3XnC+K3+LjBxQM+4d/6MXaHxuyPTT0eHr83NPbnYOZ3/pHfeIWs8wzk/SvgH4KISLBYiI39G6FfINz84OqJMB9UMPGwCJ+bMN+1jmjfxm0Dpw3cFhAt4DZisR6zNXhTgkdZGIpDVyS6ozAQh7EU3MvA8wK8LMJbNj6WYaYC8xUrDpf5zRRgOh8zBX87nKvCUvMaYuAkcUeeeKxPPNUn7qtyR8S4Xfu5HbuXOnctdf30rmlXT9GazBhEBCKeiZzkzRVZ25tzvmpLQ30oCq2QroUsXWTqIE0XqbpI0cGfWojRAEMVERqIM0CKGdLMkGKKVDpS6Ug1RQYdmX8dE802Q6458ixQaIUCc2q5MzrCMZmJN2WYrt0wV7Ntpmrbh0p8qMD7SnysWbeCsPsi0SvCGT+50KlAtKsSYxceNnwd5AApWcgarlbUoqhoUdS1yJq6ZB0DfnVDfhUDfgUDwVu6wv+F8La9sLEdr4kNxdiKV8ccWiZQNqDIqFGvS5POiEJMivemHK+MsoCi1ip1gzXaJmt0zQR0zQRoFlQDOq+eCVWbxquhx/cFoYiskIgU31UJishNipgUr7QcRU6JpKAMZyMku6LBH+3+aAtGcwhagtH1F8I+JgZiMMhCfzT6wtEbhkEWRmMwFonhAPR7oM99BWG/Fwb8MRKJsf8T4aXIxAthcWeCWacDGSf9I0/6hB33CjnmFnjM0W+/tft2S2dBRxdSoMeqPwO+zQnbnRp9KNRnl72NkLE5VYfOp0rju6VFllbjuSaz5rKk0Hlx3jOipDOipLPXqWdEKKevkf8Q5U5UC/wAACAASURBVDkrDkkp0NThT0eKE4o9UemzgrDKEzWeqPFEgx96ojCWgsd5eFaEx9m4k4yxGAyFYSR6BeH78hWED3PxOA8vSvCm7JvFxhNE+2WiR4LbI8vplSP65Yi+G0TP1cU+ac6A/NKgEjGsTozqEqOaiz233jdea2MfSwgXdHaCkw+8Inb6M38Ki/2VmXQoNPbHYNauwOjt3qEb3AOF3Hx53f34PALIbr68PoEICwOTidhYMFkrCH0D4B0AnwAkhKE5Gc9LMdOM2Y71RNsmTisWm7HYDG4TiGYsNYJTj+kqvC7EZDJ6GeiKQHcU+lkYjsO9dDzKwotCvCvFpwpMl2OmFNNsTOdiOhczeZjNx1wB5guxUIzFEsxWYql5DdF3ghiXIe6pEw/UiQlJzuAlovfnpc5d3LYdC+3fv2nYMVS8pjwFmUzU5Ag25W/oL9k6yhYYyUd/HCpc8KcG0rWQpolkTSRp4U8txKgjUgVhivCVR4Q24o2RSMef9L8Q/uVwOTJNkWmKXDryzZFjArYD2sNwJwtTpfhcIzhTvXG6cvPbUrwrw7sKfKzZMNP0y2L7caL7ItF7ZWlYfK5TktN/9Xnz1owAGKmskVH5SsQQStpUNR2Spi50DKBHI2vQeFUM+OX1Bf6JUMdcyNB2lbGdoJEt5bY1n5ElWd+CqmsmoErjk1XnvyaJUyIQkYC4DFlKkaKgKaSqJ6RBE9Q2EdSh831Jg1oG/Oq6vCoafLeUKTIKuCYjeEWK/7I49ZIY72Vx6nUJqpg0SVwGdC3EOaDeD21+6AhCcwiaQ9EZjo5IdEahj4l+FgaZ6I9Gbxi6gzHIxCgLY5EY8kWvG/rc0e+Jfi/0eqDfHyORGIn7v8rRy9HJlyITL0UkXAyPuxQacyGIcdY/8oxPyDm3wGN2Pj9auW+ydxXw9xRO9N+aHfpDOvNIuO/3Drarblvw65lTtYwFlA0oSjqQUVkjocAvKkMVkSJfl+a9Ls1/VYJy+Qbp9A3SuRuQlIK+KjyN8ac9Ct1R7olqT1S6o9ID1R6odke9D7oiMJKER7l4VojH2ZhMwggTAyEYjlopR9+X42MFXhbifjYe5uBZEd6UfTPXeHyp/SLRI0H0yhG9ckSvJNF9jeg4v3zLE9EvvXzVGjGqPtMp/aL6XGHqf/y9YeMAOz9B94gdvqyfwuP3RsbtDY7ZGcDc5hu+ySNolbMvydkLLt48br68Lt5kLz+EhCA6emVEERINvwj4BcIvGKFhyGChNwtTlZhpxnTLZqJVcKkZ841YbMRSE4hGEE1YasBsLd6y8SALA/HoYqAzCp1R6I7CaDwmU1bWYt+z8ZGNDyX4VISPGfichZmcvwQWYaEIC8WYrcRi81dE7x/ckZvEhDwxIUeMXOP0HSd6fiQ6tnPbvue0/fih6ecH5Tu6CzY0ZfMNl/KPswUelAs+LsODAoynockPSXrI0ESqBhLVEK8KlhpPpAqC5OErDQcx+CqBoY9YY8SbINEEKSZIMUGy8cqHNBOkGiPdeGWkkUtHhSt6GXiQi7el+FAp8LGc70PZylrF+3J8rNky07Bvoe0Et+sC0XuF6JdfGrz+pvdAURyM1aCpuFOL9sNlDSjpkNT1oGUAPSMYmEDLhKJqKCivt+q/EBrYCBnZ8hvZUoyteI0s+ZcRqtGEZdWFRaTIp0RwXRI3ZCGjQlbQ5FPR41U35NcyFtCh8xnQeXWNKVqGFA09XlVtqqIaRU6JJKNAvirNf0mCel6c9+x16jlRvvPivBdukC/cIGkpINwGVT5o80N7IFpD0ByCzgh0RqErGr0M9LMwxMIAA31h6A5G//L8MAz9Xuh2QZ87BrzQ74keb/QHYZiB0fj/3ZiJSRdlpV1npl5jpYiyUkQZSSIR8ddCYy4HRFz1DjvjGPSrre82R6+1/t4b4wO254b8mBNzIirgJyf7taaWVCNLfj1zqpYJRYPGq6grfEtDQEqFLKnMK6XCJ6UiIKFEFZfjPSPDf0mKJCUNPRW4GYJlgxxnsN1Q6YZyV5S7odINla6o8URHGIYS8DAHTwvwKAvjCRiKRl8QBiPwOA1TxfjwBWEmHmThaSHesLfP1B/jtF3gdt/k9kgtdUsSnWLc9vMLTccWWw8vtvyx2Hp+oUOU0ys30yP7rO7ySOFvzLBvnexBt4Ot3xrH8G/9Yn6MTPo5hLUtiLXDL3qrd+gGFz+Kgxcc3OHkCRdvspMnxdMXwcGIjlwZUYREwy8SAcE8QWFgMFGchNECfKzBfBM+Nm4imsFpwlwj5hvBaVq523+pAXM1+FiOp0UYz8RAEnpj0c1AVzT6ozESh3tpeJqHqWK8LcG7IrwtwPs0fEjHp8z/djhXDU7LZqL3j6XB60sjMsSoBDF4YbHnCNG5k2j/jmj7ieg8sNhx6E3zbw9r99yp/vlRpcCTCrytJr8qx6M8PMxCXzTyLJGljVQNxKsgRglRSgiSh5ckXMVgfAFOkgjWRLQBmAaIMUCCARL0Ea+HBH0kGiLZEEk0pNFWRhqFNqj3xWginhXhLVvgDZs6VYypErwqxlQJ3peTP1Z/N1N/eKFleVJ/jei+OdWypyoDDhZQUICy1noNmvAtDSjrkjT0oUuDAR00OnTofGo0YQX9DV8QqtL4viCk2ZCWjxnomvFqGpOU9HilVfmvS/OeEYW4HKSVIa9BUtYlq+pT1A0pmsYkbVOSnglVx4isoc+jpkNR1iQrqJJlFXmk5UmXJXkv3qScFaOcEaGcus536jrl1HXSietQlESQBSq90eqDjr96M12R6IpeOfPZtzyiYKA/HD3B6I3EMANDIehxR7sDelzQ74led/T6YjAEI0yMxv3vEUVcpnhshlhshlh8xs34jJuxaRLMZLHIBJHgKDG/yAuuYUdtA35w8tkU4LMpIXBHbsjPeXGnGUF73BzW0634blsLG1gK6prxaptS1WjCSnoCt7TIcpq8ClqrFLRWyaoLS6nwXVRYfUWWKi0DXWW46INhhUwHFLig3AVlLih1QbkLyp1R5Y62EAzE4UH2CsKJeAxGoTcQg2H/jfBeBu5nriD8XHt4oeXcUpf4UrfkUqcEt/36Ysvp+dpD70rXT5V+PVX6y+uKI1N155/VnBvI/602fou/xzq6BW7bwNJ3vX3o136xu6KSfwpkbAxgbvOJ3OwZvMbJB3YesHeDowecvUiOHiQPHwQF/Y0wlAG/SASFUkMjER+LyjTcLcF0Heab8KFhI7cJi42Ya8BcAzgN4DaC2wiiHnO1+FyF16V4UITxbAylYCAO/Sx0R2CIhckUPM7Bq0K8LcK7QrwtwPsUvE/BxzR8zsRsDhbysViEpRIs1ILb9g3R+wdnQIQzLLE0LModOMPtOUi0byFathPt/yF6/yD6z8x1nnrXduxV25GX1UJvqvhnG/ChCk9z8SQX40modEOOLildE/EqYCggXB5+MnATh90V6J2ElTj8VBGqg3AdROuAqYMYbURrI0YbcbqI18ef+kiiIcMYWXSwHdEagnsZeMVe9Y69+VUR74v8lQfdqRK8L+P/WPXTdN2R+eazKwhbDvdmwc0cCgqQ19kiqQNZVZjo71bRI2saQM8IhmYwsoCeOVXTeI2iwcZ/ItQ2E/iC0NR2jZElv5YJVPV55LUhpcJ3XZr3wg2qtDJuqUNZl6xmQFUzIKnRoGEELRPoGlO0abzqumQVLR4lDZK8Cq+sIkVKDhckcF6c54wo6aQI+aQI9Y9rpONXcPQKpMTgb/ovhK1h6Ipc+ev8gnCYicFI9IagJwKDURgMRqcLWm3R5YQ+D/S4/RthSvrhmMRDjNijMQln4pPPJqYdT8r+Nb1wf3nuyeLcUwU557OzRZKzJeIyZSLSZEJTZL1SZAOTrnsH7w32XZMb+3V18qoyFipZSIwWjIv42ddzr5XN1ya20LWGthlo1ut16HyaxiQVI6gYQsmYomgsdMtgvZzuBlFVHjFFiqw8r7Yq7AwRaYUsRxQ7o9gVBQ4ocECxM0qdUeqCBn90M3A3DQ8ycT8DI7HoCka7P/ojMZ6AJ4V4XYapcjwuwGQGJjPwMA/PivGu4vSnmtMLzSeX2g/Nt/70oU74JRuPCzCZjd4YjCXhWf6m+/nb+/N2VaVsiQ3C8hkzU0che9+NPuHfBjG/C47ZGcza5Ru+ySdc0C2Yz95LwNxhrYX1Wns7spszbJxh7wH3QARFIpyFSCbCohAUSg4KR1QUsuLRmIW7bLytwUw9FuvBqcdiPRbqMF+H+TosLH/ZAKIBM1V4y8arQjwvwKNsjCajLwZ9DPQxMRy74vB5EV4U41URpvLxJgsf0zCfgcUszOVirgTzlXhfK7DQ8QsxcIEYvLE0eJMYEOH2nSZ6ji12UBbatnA6fiW6zxO94ktd1xc6Ly32XJpu2jbTtGm6Dm/K8aQAdzIwkYLxZBTZIcUQEQrwvSnkc3ODx02KnRjMr8DwNHR+h604/FUFw7QFY/QEojQQpYZQDcQYIkodkSrIoCGJhkRDFDpvaAhBXSj60/GsAi9K8TgfT/LxuAAPCvC0GK+Wt5rqv19sPsptPUe0XO7MQ1oI7OlQ1YaEJsQ0IaEHeRPQjNbq6kFHHzQ6aNbCWpbrbpluumnyjaqekIquoIoeWZvGq2smYGApqG8toGXNd8tKWNVyjYqxkKo+VUNPSE6Nel2eJK66SlRbWNForaYpVYsGbRMYWEPLmk/BBLr0jZpGq5V1+BU0ybfU+WWU+W7KkcSkSeeu46IYLouTz4pRTl8jH79IOnaJ9PtF8tVLcNBBiTdPsw86gtAVieYg9EegNxy9keiPxgADAwz0RaEnAt2hGIxErz863NHljC4ndDqi0xkdbmj1Q3coBpkYSwCiMo5FpPzKSPglKfHH7OTtRcnry9NRm43x2j/uNpwfb7zaXXm1Ku9cftq5nPSLOVkijGyRuPSTiUm/lGbuGqz46W7t9skyyngJKlJJmdFbg712ObjsMnfbYmALHQuYOnxtbE41MgNteTfPGNo0aBqQNPWpEppkCTX+W8p8OmqwM0SEFTIdUOSEQmfk2iPXBoX2KLZHsQOqvNERjpF4jCdhLAF9EWj2QYMHOgIxwMDdLDwpxLNi3MvGcBKGEjGWgjsZeJzP/7xk9avSNa/LhJ6X4EE2xpLQz0LjchEfhd4YtMWiPEYo1h+O5lAzIOnQySYOAnY+673DtgZEbw9gbvNnfOsTttEzWNDRD3QXkrGVoImZgKU1XBxh7QQHd7gFIDDib4QhYbwBoYiMREYM6tIxWoRXFfhci/llgfWYq8NsLWZrMVeHhQYsNoBowEIVPrLxtgRvSvA8H/czMJaIPgZ6GRhgYjQBD5abpSWYKsGbArzNxqd0zGdgIROzOZgvxkIVppu2cnsOEsPXiGHJZYRLvWeWug4vtQkstG3htv9K9Jwleq8tdV9a6D7P6T0/0/jdbOM30w2Cb6vxnI0HebibhckMjCSQKtwQpQaP63C+xuNyXcD6EkzOQOsE1I/h9iW4yMBfFYGq8JaDryzCdBCsgnBVxGsjQQuxOkgyRoYl6oLQGIHRTDxm434uJlIwnoaxFEwm42EmnubiSQ4eZ+N5Hu+nip2cxn2zbcdeNZy4Uy3SXCzOCDxoogNdZVgZkkLcwApAQijCfOBiBzodejRo6EPeUPiWgeAtgzXyhsIqxkI6dL7bFhRLS9w2h6EJ1HWhoUNS1xWUUcE1GYjIQl0PusYUIwuh29Z8y2FsuYpmLqBtsk7NgF9RiyKnRpJRIUspUm7IUkSlcFEMl8RIl8XJZ0RJp66sCDx+iXLxPKw1UOjO0+CLtgB0hKMpEH3h6A1HX8S/EPaGozsUfWHo9EWrM9od0emIdke0OqPddQXhEAsTSUBYxqGo5O9jkwRzklGVjJZE9CZgLAkDKbibj5f1P831X5wblnzeJtKdf6g8ZmdhwdGcjJ3V+d9O1H//qu2bt62YqsOzMjyt5GlKWx3mSaJbCxi5br3tvk3fbp2h5UZzG6q5DdXcFpbWMLOAmRnMzGBOJ8vrC8hrCimq8etqwsEIkdZId0SBI3IckWW98sruXBvk2KDMFQ2BGIjCMBNDDHQFockd9c5o9UFvGEbTcT8XjwowkYH+OHQz0cNELwsjyRhLwUQaxlMxHI/uCDT7o9YT+fao80d9KMoCURiCOF/YmUFNGUr6JA0Tym174WWE/lHbAqK+8YvY4hO8zi2AbO0BAxto03h0DECnw9YWVg6wd4ObHwIjEMb8F8KICKQyUJGAvmw8LsHbCnysxmwNpqvxqRIfyvGhYmVje64OnGrMVWC6FB/Z+FCKNyV4kYv7GehnoScavVEYZOFOCp7k4lUx3rLxrhAfcvA5A7OZmM3EdC5m2ZivwWL7PqL/DDEmQYzIEYMyRL8o0X16qf0Qt3Ujp+Vbom0f0XWS6D1HdJ9e7Dm21Pf7bMOPs80/zLV+N9209X3t2tcVpBdsPCvBm4pNdzJ56/0QpwcXUdz+HToHofUbSfUIVI9A/RjoV+ClAF8leCsgUI0UqAEXSYQqU+K114bKg6WFAicUuKIlAu1R6E/EZCbuZOJhDu5moicWw9EYZWGUhWHGym96NwXPckE0nyb6xIknesQzo0dVF3K9kGqH6sCNXckYzsFQNloSUMUCm4EkP/hZQ80ItwxwQ59HzGidPH2zjvkGYxpMdGFlAGNtaGlCVZukpEFSUoeRIdwc1jubw8IEt81h7rDR1GHTbQshuinVxnKNurGQkh7v8us9biqSxeVJ16VJ1yRxSYx0SYx0VoxySgS/X8axS6Tjlyi/X+E9fRpGCshxRb0vGv3RGoLGAHSGoScMveHoi8IAA/3R6ItCTxi6Q9EZgFYPNDmg1R7t/4+t937L8srCtk862GJJMb1NJsmkx4wao7EgqBTpGEBBEcSK9N57lyJgpUQQARUQxYZK772DFBF7r3TY3w8yM+/7Ht9xXH/B89znfa+99lrX5UaFG6XulHtTGkxtNG0JdB+H9JQvTiTLZyWTn0JFCk1JdCbQm0BbAm1J9J7gwUVGq36YqF8+WLn8acHimvM/FmXIt56b/qz8w9dlvC7g1VUe5TF0ldsXyT4s6ebGLpeZ1gFfOPp96ejxkZ372zau8jbOWDlj44S1I7a2WFtjbDl94/aZxqZy283wsCLehXRPTntyyoM0J1LtOeFEhgPpDmS7cSmQ6khqo6mNpiyEK57ku1HoS0UYjUm0n6Azg+ZkKmIpiqAgjKshlEZMbWOU76MolHw/8tzJdSLDgfxQzkeQHkRiCAGumG5B14ANFpJbLGX3uM1wC3k3eP9H4fEfh8bOD41+Jzhyjncodl5stcbIHBNzdlpi74SDGy7e+IQQvv9/EEbuJyJGMm4/KfGcO0p5Ch2Z9GdzN5eH57ify51sbp3mdhb3zvAojyfnGczjxTme5075WTzN42E2t0/RmkjjYerjaDhARyL9Gdw7w+NzPMudgnAwncF0Xp9m+DzjRUzWLhIta0XHBtFuIJr130A4VvnzZPnbk6UfTZZ/Jap/ETULx6t+Gq3613jNt6OlP4yV/zJe/e+x2iXDNb+9rvjpVfE3zwv+8bL40+eFH909P6PhKJnOBOix90/Mf0P/ewx/QPNLNv+IvRJO6yTc1OTcNd9y1MJ5PQH60pGGxGzkpCMVcdQk0phEZRzl+2k8zECW5FDx9y+u/qP9OG1xNEVTv4/GKFr20xxLUyxNsXQn0J/G40u8LpW/k0ftIaqj6TzCo5M8y+ZpDs9zeHWBF1foy6EygSNh+LpjZonOTnSt5hnbfGS+a/a2rVLbzNhsxiaLORu2zdIzwnI76bGfXb+qlHlofrgvtg5Yeijs9f5gp/MsK1s5VycFUyv5jTskdTejYSihri/9po2/Tlty1XrJFeoSbwhcuFpikaLkQiWpRcpyC5dhqsNxdwpDKQyleB/F4VRFUxs9BWHjARoPUB9HXQw1UZQFU+xFgQulzpS7Uu5KqTtlXhQHUhNFWwK9J6AikbKjVByl9hhNKTQn0nqU9gTak+hN53YOt3O5fZZHlxXGqxeIzrUPSn7vOfvhw8vviMqPRSkTRVNXXoN5DBXTk//emdRPIsI+cfZ838Xrg+Dwr1wCPnfwnW/jOdPGW8bOV8HJR8HeU97KWdrcVmHzTvnNW2V2mONlQ5wbad5ke5PpQaojf9ty3I7jdhx7k47oxRUfrvpz1Z+LHuTYkWXNOScue1EYTfkBqg5SFMmFAHI8OOVMpiNn7Mh14pwLua6cceGkIydsSbEixZ40LxI9iPUkxJ0dFqjqst5ozgYLGROrmZbuc91DPgze/2l4/Mfh++eHRM0LipzmFSJp48Hm3eibYmAqY76bvU7YOUs6e+IdTHg00Qf/B2FkrER8LCnxnDlIwWEqE2hOpu0Y11PoTKY9kdYE2hLpSqH3BDcyuH+K+6d4cJpH2TzJ5Ukuj3J4kEVXKi0JNMRTH0fbYXpSGTjJvSyeneZZJi9PMJjOqwxenWboEmNljNf9KVpURftfos1INOuLJlVR+8dExQ+i7G1RMnui5IPJii/HK74cKf1ksHT+cPmHoyW/TlQsHa9XnmjWnGjVGm9SGa1dMVL1+0jFL4PFnz8r4FE+/WcoPkCCPb4G7FWVdNbEahUuagRtwFcXD112KbJlOTYq2Cvjq8FJR5naQ++2HKc9k8ZjVMZRGkFNDDczmKhcIOpXPsj/ofMILfE07actjo542uPoOED3EdoS6Uzhega9WfRn05dB51GaY7h7iMdJDGcicpk4x0geQxcZusLDC9SmkxCOtQO629E0l/5r+/smu79UNZ+7dsscre3z9cymbzQixImOs9+LPu3u6rWnU+d7+2Hjg03grL1+M609ptt5yJrbKhjvktXdLLHeQPLNFZqKjpyKjtSq9ZJ/qkouVubfivy2il9XsUBR6rfV0r8ul/pLlSOOXH0z4byP0n1URlEbTV0MDbE0xP+vFq2OpCSAax5cc6LIiTIXil0pdqfEk6IAqiNpS6AvHW4k0H2EziN0JNOeQnMy9UlTHnudx7mfx/MCnhfw+BIP8rifJzVetezltW+Hr80XRVKTVxi9zGTBlCn/YCGPrzFQ9E3NuSVH933q7YKfn4Sn79su3tMcvaQcfSVcAuRcgmY7Bbxl7zNrp8M0813Ttpiz0wJvW+I9SPPhtDdpbiTactSSJCsSLTm6iyRL0hw55USWC6ddSLfj2G7+3kGaFScdOefLpUAuB3HWi5OOpNmQuofknRy3mHVip3yapXSaDam2JNuQYMnh3RywJdKaACu8bdm7G11DlHRYb/Ke/vbpJlZv7XGb5xb8flDMJ2FxH4bFvBsWOSNwn5xnMDZumOyW0t8y4y/TmVt2Se92xNZJ2tEdzyDCov5vCPdzII7UeLLjuLifghhKo6mIpmI/5TGURVIWSXkUlbHUHqT+CL3J9B3jRspU4s2909zL4l4W3Wm0JdF4YKq99sb4eOAEj07wKI1nxxk8wat0XmQznM9klfR4w3LRvE606osWfdGkIxrXipqFE+WfixIZUcREseRk2dyxsrcGi2cOFs8cLJs7Vvr7eIXiWL3WWJvJZOfWiU7jN0EdE5WrRst+HixReFnMw3zaTnE5lhQ/Yh047s8pP67GUBDLpWhywnE3QWchJiswX0bgRioPfdp/5quGY9QeofIwVfHU76cumpbDPL70rmhcPdGo3Z9BdwqdCbQdoimW1gPcSpcavPTF80uLhoqXjVesHK9YOVG5arJizYv8pQMnv711lL54Bg7wNIWhU4zmMnERUYgoYKyAgTzOHsLHBZOt6Bmja/ruKlM5xY0YmmG5Ha9dnI/mVekC0a04dtOkpXBR2iFCA/EPwjMYez/5Pe6S5o7TNlpKa2+RXKcvuUZHfo2O/BodOWVdqVXrZZaqsEhpisBfV0n+rCj10yqZBStmqq4i2pLLwVwNoSiKkkjK91ET9f9CWBNFdSTX/LjiRr4jhY4UO1PsTKELRe4U+lO1j9Yj9KTB3VT6k+hNoC+Z7hTaUmhJpeUE14/RmUx3KrezeHqBl1d4fp5HObwu+Hq06PPhS7w4x6s8XpzjZR5DVxAtH42U8CCPZ5d5Wby4Le/P3ORvjx19PyX+4+T49w7HzomJlPAPwt0bRw/sPbB0eWu7layZOXu24WVDnDsp3qR7kuhE3B5itnNgOwe2E7uV+G0c2U3SbqlkK5KsOLKTeFPitnDInMRdpNqQ4UimI6nWJO0kcQcJFhzdRoLFlLlwoiVHLYnfRbQF4eYE7sLVDHtzLM0ljYxQ1UPFSFbNZLaOxayNlnN2uL7jEvhBQNSHYTHzw6PmhUdMDwyVdA/Exo3NexR0Td/6y/StLbvkLeyxdpB1cMMz4P+CMCpWIiKauP2kxJETS14kl0K5FES+P1eCuRI4pWvBFIRRvI/SaBpiaYilKZ7mQ7Qn0p1CXxo30ulIpfnoVFXTGEvbIToS6Unm7jEe/s2TFF6k8TKDFzkMX2WiZs5E44qJlnWiVXuySWeyQVXUr5ys+ma0ZJ4oZrKQ8UImSxgvkxopkRgpURgue3uyfLmoUhtv2DjRuVP02ojeXaLLWLTpTNauF/UrRc23rwvoz6YygfPRZIaT4MXFeGpTuXt5xp1L0+4VfDFQ+NNBd7QWorUAS1XSfGhOf7stnZrDVB+i/BA1B2g5QEsMDbH0ZzFWt1J0b3l5efbASVoOTz2v7YncO8NwsezTy3MHC7+eKP9DVKuKxr9Es4moNxyp0H2a/82t0zM6jtJ9mMfpTJxn8hJDeYzmIa4yWcLji5QncdQbx52Yb2L3Hux2EeXCMQ+yfejORDQtEc1LRY/xUINq99nPz8eSHEhcEH5+EtaubHOZvslKVmuz9Fo96dWa8qs15ZW0ZJW0pFesl1mmKr1Ymd9WS/y2WvKX1dK/rJb/aZXMLyvfXvUHgds4G8ClJGhGwwAAIABJREFUIIqiKI2iJIyayKmKtD7uf7VoVQT5Xlx05pIdV+wpfOMl6cQ1Fwp8qQyn+RDXU+BWBjdS6U2mN4W+VLqP051GTwZ9idxIYSCNuyd5lMPL80zkIwq5f4bBK9Nf5vEom9fnGbrEq8uMl/GscMZkDSPXeHKKV3nviAadob5tD2+ZD3Vtft1lcrdZp+7asqzjH8RGEhpIcCD2HnN32c4w3zYFYYwbf3uS5s4hW6J3EGFKzFZiTIk0JtKEOHOit7DfjGgzIkwIMSBYn/CNU5E1By04tJ1YU6JNiN1MvCnxpsSZE7eNuB3s30GkBcFb8TXGyxD7Lew2YqcJJkbSKuqo6EhpbJ6lZIj2ttmGu2dZOM918n/Pb9/8kKh3wiLnhIXL+wfjFoC1q8Tm3TN0Tefpms4z3iW7ze5/EIZGEnWA2INvICR0H7ExpMRxej+5EZwLJM+Hs15cfDOE4MMlX/L9uRpIQQiF4ZSEUhJKaTgVkdTE0nSQ9kQ6k2lJouHQ1H/ZEEPLAdoO03mEgQTuJfD42BSEL88wWIComz/ZtHyyVWWyRWO8SWOiYY2oWzxe8eVIIZOFjF9jrJDJUsbLGC+RGSt9Z7LiU1GzRtRpixbTyW47MeAiBhzFjR2i21h0GImGdZPl3w9emX4nl4ZjnA0jwYMMf8qPvHMj66vx8j8GSxaKFm3Ra3Y6XEp7seya73E3oTT5/Zo0rkZREU/nCWqSqT1IUxxtsbQc5FYu4/WrRK+5qFp68+S8sghKwmk8TNcJ+rK5lcfLqzzJ41Eer6+8P16xeKJ29XjzWtG5/nXboteNvz7Kn3s9la4j3Evn5Rme5zB0heHLjF9C5PPqEp0nOB1CmA3J/uSG0nCEjgM07OP+GUTrihdNy0STgegyEFV/9KVyJYT0YKIDpd3cplm4yr+BcI2OnKKGrKKG7GpN6dWaUqs05f9Uk120TmKRsuQiZekFynK/Kin8rCj7s+L8PxbitYUcXy4EUBRJSSRFIVTv+8+xMJaG2P9BeNmTC05csOGyLdfsyLfjsgMXnSjwoSKM5gN0JsP9BAaOcDuRe2ncSacvhd5j9B+nO4Xrx7h+jL407mTx6DxPL/PsCmNXeXCWm7ncLfjgRfWPL6v++ap43mCB/LNiRst4XcS9Czy/imjeLXrshq7/MdhrIQZ2ils7xIC56Nlyr0oz79hXwW642WNswYY9Ept2EGhHmjdHHUn2J84eV1P2GOO4BR9jAjcRYIzXRvw34r8RL328dQkwkPTRwUMDPz0pfz1CNhJpQvhGwoyI2ESUMVHGkge3cmgrcVuJMMHTEGt9zDZgbIDeFnQ3S2htlF6nL7laW0JRW3rtBjm1jTM1zeQN9yhsc51nFzjfY9/73lHv+EbM9AqV8w3Ay1fCzmXmll3Sf5mxyULSzEp6t72svdNsexdpN08CQ4mOk4o/LLn/IDH7CYwiZj/J+zm1n3P7OB9Eni9nvbn0HwjfcHjZjytvBtYDp6ZkrwVSFExpGDWR1MVQE0tN7FSHre4Nh/F0HaQ/gVtHeJDAk1SeZfM6n/FyWVH703jj2vFG1bFmjfEmlcmGlaL6W1EqP1nIcCWjFYwWMVGEqECUzh0p+U5UrRlv1p1o3TTWtWu831Hc9Zy47z5232H0vrW4YTrZpj1Zu2S8eP7dXKoOkhVEig85+2jOfPf2xSWi0Vg0mIiWzaJnc8mx2aZKkrtUOWhNYSQ1sfSe4MlFBnLoSaQ5lrZDNB2kJoo72R+IhnWibm1/Kl2HaNhHdTiN++lKpD+TWzncy+JhNo/P8vwirwoYKvtkpPaPsQYV0WYhuneIev17OV9eP8yNRJ5mMpTFxJtlrnxGrvL4DF0J1MdTf5SqFHov8KiQ2xe5m8dgEaLqHVH29ljdoskOdXHd9X7horJoqiOpjCfDkUhHLHehZiKhtEFBU0tBQ1VupZrcL5rTlbXlVmtKLddgmTpL1CR+Xyfz22rpn1bJ/6gk98NSDHQ57CKb70dlAFURXAujbD+VMVRGUx5FZTTVsdREUR7CeQfOO3Denjw7LtpO2UletuGaOzURtCdwPRUe/839RO4mcT91Ks/xZio3j9OVTGcSnUn0HGfg5JSFxOOLjBXw4grPCz96VbNgqH7RYOX3Q2XvT1bOHiybLmp/m6j+4vFVHl5hrFpddGwZ6lox2GU22b9b3LISt6zEHTsxYPWgeXNzkerxA9/s2YP2Zix247WHJA+OeZHoTYwdDqZsN8LKBGcjPA3x3ISTIa4b8DDEWQ9HDRw12KvE7lU4quKsiacePgZ4bsBDHx99/Azw0yd4I8Eb8TfEXR8bHSx0MNHDwADdzeiYoGkktVZPQklL+n8Qmku/gdA24D33iPlekfN8wqd7hsj4+uHmi63z9C27pA3MMdkhvcNa2tJRxtZJwc5Z0skT/2AiYyXiDhFzgIgYgqKJ2U9CLKdiyN1HXjB5AZz3m8LvgjcXvLnow2U/8gO4GkR+AFf8yffjij8FgRSHUBVBTRRVb1a2o6iOpGYfdVE0xdIeR/8Rbh3hXhKPT/DiLEPXGK2YJ2oWTTauGW9SG2/SEI0aE/XLJ6v+OVHCWAGvixgrZvQa44WI8mljpR+MlP4majXHGw3HWszGr1tN3HQXd33FAz/x0F08cBV39ojuTZMNiiOln9zOpfIA2YGkeXMuhuvnvn1WulZ0mImmLaJ9q7i5ve7UPyy1pV0MyfSi9Rh96TzK48UVbmbTk0hjDM3xNMdTF8vtrLdHSxY9v/x952GaY6gJpTyY2kjaD9N9nBuZ9J3gdiYPs3max8tLvC5guOyrkaqFg9VaotdM9JuKyj/vZtBzhDtJPEvn5WkmLiGKeJHHjVS6EunP4H4eT4u/GatfLFr+HK9fPFa3SDSvFE0rxqv+GK9fLLpUxE3PVzWraw9RtY+aQ+T5SmSHsN9X2ngnf2qhqCqlqiqrpC7/p/aMNTpyytoyilqs0JT4c73EEhXZhUqyC1bK/LBK/sdl6Gqyz5qLPlQEUh5KQQSl0VTGUBE1BWFVDFURlAZxzo5zdpy15ZwtF2y48B9b16tuVIfTkUT3cXj8N4/+5kEi9//m4XEeZXAvnYEUetPpOUHvCfozuZ3DgzyeXOJZPi8v8fIqwxVfjzcsH61d8bLsu8GyueM1jFcvFi1GovWv15Vf3iniceXPI206kz1GEze2izu24oHnxD2fiXs+4pGPeOQm7trcqNp8MOzzTRtxsMZ9O0fcSQ8mwZsoJ2y3stWIHcbYbMRlE86bsTLGZiOOxtgasFuLnSpsXsbGRZivZKcKVlrY6WGjg5UW1trYaGOthbU2e7TYuR4zVYxU0ddARxctA0mtTWga8SYhZLWmlKK29DoDBXXj6VrbZA33KJi7zLHxf8c17B3P8Le9Qmd4BMt7+eHqLWnlrGC6W2aThZTp7ilnWFsnaVtnHD3wCyIiRnL/AcmoWMIiCYwiIppDMRyP5mQEucHkBXDOfwq/816c9+KC91RReiWAy/7k+3HZl3w/rvlRGET5m8ngfZTvo2oflRFUhVOzj/poWvfTd4CBozw4zrMsXl5iqIjxiq9EteJk4xrRqCYatUW9lqheMV723lgRw9d4fY2xIsYKpMcL35ko+WCo6Kuh4j9E/YbJRovJtr2ix0UM+Ir7oeJRkHgSIB75iseO4uaOyTbNkYqfbp+l7CDZgaT5cDaGnssLhup1RafFeOMW0WkhbuxoPvOdvR6BppwPoz9b+nHe1K5gfyY9idTH0LCf5niaDjKQyaOzb18/TnMMdeFUBlIWQHU4zfG0J9KVQmcyPanczuDBaZ7mMniJ8RIZUfXJaO1q0aouWtcOFf3rZirtsQwk8PI0z04ydoHRy9zNpCuBgXRe5c8dr/posvF30awoWrRFh6no3S0G7MTAHtG7TdQvEV2LxG1X0abVdozKMGrjKQyXbT5EUdIcPy+U9FmqxlrNmWs0ZJR1pdbpy67Vk1bWlVqtI7lKS3qpuswiZekFK2W+WyH/y0pJFRU8tnLGk5IgCoIoiKAkioqo/wvCijAKfTljPaVcK85ac8GGi7ZcsiPfhaowOpLoTYcnKTxL4WkKT1N4lcmrHJ6e4lYqN05y4yT9pxjI4m4uj87z7DIvrnA/j0cXeFnw0UjV0pGalYOVPw2VzxqpZLR6iWjZLLpsJtv1nzb89LRxwVjXRtHvLG7tEo/cxLOw8WeRI48iJu77idtO4sYe8cS7KV/XZQduu/Gx5Igv6WH87UOUG9YWbDbB3JS9pjhuw3knVjtw2I7jDqxM2bkBCw2MlqP9GwaLMV6HmSbb9DDXxVSLLdps1mKTBobqbFiHthKqiiivRkkVJR3JtRvk1hugvgFVXcnV2hKKGpKrdWTWGSisN5n5Xwit/d5zCXnXPfQdj+CZboEKrj44ekntdZLbukdu807ZbTZyNs7Sju6Sdq5Sti44eeIZRHg0UXFS+/YTug/fCIIjiY7kaDgpIWQGkOPLOV/OenHWi1xPcr04602eL+f9uODPZX8u/3da3ZeCQMpCKA+lNJzScCrDqQynKpzqCOqiaImhN55bCTzI5Pl5XhcyViY1UblAVKlMQdigLWrURPm/J4olhwsYvMroNUTp3MmSf06U/DBW9uOr4h9eFa8QdQYT9TtFi5XodBY3vMSAr7jjK+56i3vu4pG9uLlTdP41Uvv7rQuUHSYrmHRfzsZz4+qiwea/xtu3jjabiu4d4rpZa853gaYcsqU0jltneJDHg1zunKYzic6jNOynYT9N8bQcpDeFG8dpjKMxkrowqoKoCKImjMYYmg/RepT2NzYQydxK41k2I5cQxYgKXpf86+GlD25mS/Sm0XWErgPcSuBpBi+zeHZ66gB1K4Nn5xkr/URUfjVe8+1QxaLXlWoTzdtFn4e45y8e+4pnXqJu2UjTbNG7S7Tr9KRREUBNFOVR3DzErZxpJw+9ZbIdRT2ptXpz12nLaOigYTBt/QYZlQ3SKhuklXRlV2rILlkns0BR6oflCr8qzVixmp36HHeeOkoU7KMkkvI3iqIqhspoSoO46kGO5ZTOWJJrxbk34QJ2XHSkMpSOZPoy4NlxnqfxIo3hTMZyGDvLkywGjtN1guvpdGfSc5IbWdw6w708HpznXh63crmXx8uib8br/hBNi8frPh+tnj5c891YwxrRuUP02Y71bRrsWj/ZuVV0+YkeU3HbRjwJnHwRI57vF8/CxH03cdNKPPcSA55HvObbbiLAniMhJAeS4U+UJ3u3s8mErVulrCwkHS1xcpSwdpBwsMfRhr3b2GnCTgM2KqGxAI1f0FXBUJON+hjpoa+DvhbamqxXR1UV5TUsW8WSFSxWlFiqIrVKS1pZT15NHzV9VHSklLSk30CoYjhNY/Msne0KRpbTzV3mWPm+6xT0rlvI2+6Bs139Z7p44+ghvdtphpmlwtY9crvtZe3dcPbE0UPa3gNHb7yDCY6SiIxVCI+WCo7AJxy/CMLCiA7msD/HfDjpQ44vuZ6c8ZhSruf/OLzsx2UfLnlPQVgYQGkQ5aGUhP0fEIZNfQnfQHgziUc5vLjCSCnjFV+KquWiSmWiYY2oVxF1a0XV0omSz0evMXyNwatMFM0RFd+Lij8mK1dMVC9/XbbodclqUW84WbV1ss5CNO8Zb9872mk51rVLdO8SvbvG+7eP95hNdvw12qh4N/+d8iTOhJHhz7VE+gv+/apZd7R982SnuejdOdawoTnjszRnLgXTeoxbOdw8SXfqVFpB2yGa4qbUGkvnYToP07Sfxkjqw6kJoSqEmjDqIqfuuFsTaD3C9QRuH+d5NkN5vMrj+Vk6j1N/mPp4OhO4cYzeo/Qcpu8o90/Qd5SuIwyk8+Q8r68xUvzuZNl343VfjdQsGKvXEJ07RL/T5C2XsfvOE48dRf3yFzWIFj3RrNF3gko/qkIo28eNSJ7kUH1iprsTaw1YrjNrra68/ga0jaZpGklrGkmrGUqt05dV1JZZpiq9eLXUT6vk/608d9EqiQ1qRFuS50O+PwVhFP13OCSSqhgqIiny44IjObvJ2k3WbrL3kGPJGStyrTlrQ54dZUG0J9KbCY9P8CiVpykMZTB8micZ3EylK5mO43Sm0XWC6xl0Z9J3moEc7p7j1jluZNFzmnvnGSr/SjT8Otnw3Wj1Z6M1n7yo+eJ163ox4CXu+o33bBlrNhD1e4bb9ce6t44P2IgHPuJZqHgeLp4Fice+k3dsxLOQy/GLt2vi60hcGAk+ZPsT5cHebRgYYbxFcqeFlJO1tKOrzF43SVsnBTs76V3b2bmV3SaYqKK6AOXvUV+HtjYbNqCnj6Yuqtqs0UBRDUVV/ljDwlUSCxSlFilLL1WXUdSWUdaVUtVDVVdSRUdOSUt2taa0kq6s6kZ5zS2z9XbKb7J+a5vrvDcQuga/7RYwx8VvppM39p5Su51mmFtNM7eW3esk5+wp5eGNk4+cgw9OPngEERQpHRozPShSOiAEzzBp71D8ggj2J9qLI54c9+S0JzmeZHv8T2e8OOvDOV8u+nDJm4teXPLmig8F/lMQFodQEkplOFURVIdTGzkFYd9BBo7zMI+XxYxWfjpevXiyRlFUrx6rVZ+oVRLVS0T5l+OFDF9h+CrD1xgv+UZULRfV6yZr1UT9muGKP4eKl4lqjckKvYlq/bG6v0bqdAfr1w/Xr59o1hStWiOtemMtuqJZd6JB+f7VjyuOcTaCU0GUptCb/6/ndSpDzX+Jji2ibdODS79XxnPei5IImhLoTuV6Cu0JdB2lJ5HWg7QepDmelv207KftP6oPpy6MmhAqg6kMpiqM6n3URFETR+MBOhO4fZxHJ7mfTk8izXFUR1MTRVM83Qn0JHL9ENcP05dI5wHa4+hJ4uEZnufzPJ+hwrmi6vex6u8mGn4XHVqi31QM7Jrs3z7aZzp0Y7NoUn5Sw3C9oqhd13uCKl9qAqXLImgP43YqnSeI90XHgN81pNYazNIzltLdKK9jJK1pJKVhKKGyQVpZW2almtySdTK/rJZesOatBStl1irhbkKGy1SPrTCU4jevzggqIimL4KoHZ6zI2knWTk7t4NQOMnaSuYvMXZzcTa4Vpf60HqU3E16c4fEJnh5n8CQvM7iZSOsRWpPpPEFXOl2ZdGVy/RQ9p+k/w+08bmbTd5ruTHqzuXeBF8VzRiq/H65eMFHz9dMKnjb+W9wKFg8SRO/ekcblkzXLRjp1xq8biD5TcctS3HMWD73Fs6DJ5+Ej923F44DmHF1LbTwc2RdKkh85vsS6Y23GBgOMjNluLm1rLWnnKrXbDWvHWbYOM62ssNrBXnO2qKP+b9R+RFUFbR30jSS0jVDTR1mXVVrSf6pJLl3HYmUWKEr8qiS7SGX6So1p67Ql1XVR05NS05NV1ZX/L4RqmxS0TGdu2D3D2Ga2hdvbVr7vOgV94Bo03y3gHRe/uQ4+2HvK73aaYWYzw8JWwdZF1sUbbx9c/KY7+uLgg3sgfvsIipzmH6bgFYhboLRLgKSrD17uBDoT7UiSI2nOZLuT5UaW+5RyPMn15qwPeZ6c9+C8Bxc8yffimh8lgZQFUxhEcQgVYVSGUx0+1Ztpjqb/CLfTeXyR16XyY1ULxmvWiBqlydolY9Xak1WKovIbUcLIVUbzGb/KeCFjlUsna9UmavVG67Qn6lWGShc9u/z98JWFI1eXDBcsfl208GnB94+vffGk8MvBsq/Hq74brV01XrNmsm7daM3yO5ffK0/mTCSnw6g9wY2LX7yoURxu1BSthsMVKm3H5l4N4IonZcHURtN4kM4kepLoTuRmMq0Hpz6GzTG07aclipYI2iKpDaU2lJoQKoIoD6biP42osmhqYmk7RPcRrh+mNZbqSMpCp6bb2uPpOEDbAToP0pvArVRaD3D9KLfTuZ/Lows8v8JI8RxRuXykcsVknbJoURPtGuK6jujdILr1Jju1RdOaZ7UM1yyaqFzdnUK5F7X+88ojadhHRzz9aZyLYutmlmhKKG16R91YTm+TnO5GWW0jNAwl1DegrCulqCG7QlV24Rp+VJL7YdX0FSvYsZ4EKy77kufJlUCuBVIQRFEopeEUBXPBiUwLTllwchsZ20g3J9WclP8oexdF3jQfpjcdRNHHr88xmMX4WV5ncSOJtgS6M6b8MLsy6cygM5Prp7iRw8BZbuYwkEP/GXqz6Mvh3kVeln03XrdSVC98Usajhn+JW+Hi0UnRZzfe8i/RJD325oe4aSxubRO394p7LqPPgkZfxYohL3Hf73bRdkdj3J0ID+HvYHK9iXfH2gwDfTZulLAwk7KxwtZFYpcr1g7vOrq84+Q429lmmu0OaTMttH9HZyFqaujq8dcmOd2NsmqGUmv0ZVdqKyxbL7tEmYWr+Wm1xAJluaVq05S0FNR1JbV1UNeXV9efrqYzTVlbTklLVllP/g2Ef+2ZZWI718LtbWu/D/8Hoe+7Tj5yNp7yu51mmdnIbbeTtXOV9/DGyxdnfxlHXxx8cQvAJ0wiIELGJ1jK3Q9bH2l7TwlbNxwd8bAhxIoD1iTbkOVGlhun3TjtRpb71Mcw15uz7pxz45wbee5c8uCqL8X+lAZREEhRMOUhVIRRFUZ1BLWRNEVxM5G7J3lyiddl741WrZqoWS9qlET9b6OVehOVqyYrPpwoYfQKo5cZv4IoZKJhjWjUHa83HKnTHatd++La9w/OvPMo+5MHWe/ez5l3O0euP4u+09zI4WEez/OZqFw4UbFcVCmOVvwxcGFOWRK5UWRH0HKa21e+Gm5QnmjTE21/vShcURdHvidVwdTvoz6G5gP0pHIjhe7DdB+egrBhP01RdMTSHkVjKM3h1Ib9B8IQKkKoCqMmkvr9lEZRvZ/6OOqiqQilNJiycKqipRojaImibT+d/4kf606k4wjdKdzK4PYpBk5xL4/BIibK3x8v+l00bhLN+pMNqiM1yycaV4gOFdGpLVrXiwalZ3WM1CwYK13ZlUi5GzV+71VGUhUt3xDJ3TRqk+bY72aFvrzi5vmrDGX1NsnpbJTQMmS9wZuXu9RqTemVanIL1/C1osS3itP/+JNNihzYziUfyTPOXPSdanFfC6IohGsBnLXluCmZ5mSYccKM46b8bUrSFhI3c3QLp3dQ6EXTQXpOwGi96lid0our3909RX8qXUdpT6Avne7jtCVyI4Nb2XSn0ZfBnTP0n+J2Lr0nuZPLvXN0Hqcng1eFb01UfyLqNoomA1GnIeq1xXVT0WMiWlaPNPw02rRetOuIHmPRbyFu7hK3bcRdZ/HAfexVoni1/2XN5iBTfPYQ4j0tJXr2qUj+DsDNgr/UUdWS1LPA3AErJ1wdcHL9p4fPt55eX3m4fOS8552tOmgvQ/t3tFQw0OGvTdI6xlLqRtLrDBTW6MgrasguWTd3kdK031ZLL1kns1JDdp3eNFUDBVUDGXUjaTVDWZUNckpa0qvWS6zWlli/cZre1jmmVjO32c3b4zLf1vN9R9+PXf3ec/Wf5+I318pH0tJDerez7E6HaZaO0+xcpZy88fDHw2+mq7eksxduvngFSnoFyrp4ydi54Ok028VF1tpVYruDhMV2qb2mBFhwyJZUx6mR9DfGgWfcyPHgtCuXnTjsQoaffJ33vGIHTniTG0FjAPWBso0hlIVwKYwLMRRG0xLBg/C5d49w5xydl2SfVy8Q9cqiQkm0ruur+W2glfHud0XxhyJJRsRJiQRG8hhslRB1fww1KIo+o5dVa0X12ld5X948Tnca7SdoSaL9CD1J3EilL52bWdzN40GR3Ejt76P1qo9KlrTmcvEgp0LJjaIjV+Fe0edDTSqixXysXuPRFbn6g1xwpCaYgb/pPEBzNN2HuH6QniNcP0xvPB2xtEXRGklzJC37aNxHQzi1kVSEUhxCRSS18dQfpimR5lQaE6neT6E/DRG0RFMVRGUYpWFUhdAYRddBrh+kPZaOWG4c5E6CdPdx+k4wcIJ7p3iax1jxp+NVPw1V/SxKfxAV/xbVy0XNGlG7brJxrWhXF90aouVfL4qYqJkjKr+qDKMqkAp/agJp2kfbPsmuZJrP4WE7S89YSssc9Q3vqxtJqxlKqWyQXqcvqaors05bRllDcrWaxA/LZ/6wavo/V8p//YfEsqVs0ybWihw/zjpz3oPL/2l6X/Qiy55UC5JNSd5KwlaJg1ukozcSYUTEJsJMyLCZdtaVymi6kuFx8a8vS359mv/xvRxunaQ7hbZErqfSlTK1TnrnDDdPM5DFnTP/2cs8za0cbp+hO53eTB5fYqh07ljV2sk6peHKP0YqV4gWfdGxQTQpj9b/OtasJtq1RLeR6N8qBnaK21birp247zz8LEa8DBtp2XjQgUh3DgSRFk1mCIn+eO5ks66Mrt5M/W2Y2mLrIuHt/pmTxzdeft95+3zt6fqxi+W7ZrpTEOqoYaTPxi3T9LfIrzeRVTGSVdKVXbVeZpHSrH8ryv+2WnqpiqyiloLqhplqhtPUDGXVjaTVjeRVNsgpa8soakgq6UhqbJqubzb3vxDaeX3g5PeJc8BHb1Ij30C4x0V+l+OMvU4z7Fzlnbxx9cfFV9rRCwdPnH1x85d08ZW2d2OPPfa2CnvtJLfZsXmPxEZTthrhtJnQnSTZkepIpuOUQeAZF7LdOOVCqQd/u3LEgQs2FDpzMZB8TyrMqNg4o2QTDfaSzUEUBlMQQnUEdcH0HufxWZ5fYrzh55d1i+4V/CoadcR1c3FWQ5zSfuW2oOlPKj6n5hdums+YPLhUVKwXzXovqteONKpNVCx/fHpGdyJdKbQfpyWJjqP0JNGXQl86t3N4dJGnJV8MV68YrlF7XPpn2xnZ8/GcCuViPN15H90r+nqkab3o2DNWr3E7j9p4Cr1pjeZOKh3xtMTQfYiOODoPcP0wnXF0xXI9jo44WqNpiqI+growSt/U2FFURVMWSXkMLcn0n+H/xkmAAAAgAElEQVTuhY/7T79Vs5+qMCpCKA2kNprKKBqOTN1hvJmj7DnGQDoPsujPpDeNG6ncPcnL84wUfzhS/vVI5feTpUxWIKo/E3W/iIY/JxvXTDSrilZ10fT1y2JE3fyJ0i8qQqnwp8Kf2iAaI2jdR3cKXRcIcJqlsxH1Law3+FDdSF7VQGadvuRaPek3Vher1SRWqfCvpbJfL5P5bKnk54skFiyS0FbCzYRDduQ6cs6FPHcuepPvxwVPMi05YkK8IXFGxBixz4AQPYL1CTIk1JjE7WTYUhJGy1HoPcvti3L38rh7jofnGDhFZzJtx+hK5cZJBrKmMo/u507t4AxkcTeH21kMnOTWKW6e5E42z/MZLP5quPzTlyXzXxZ/OVG/SjSrTTQojjcuHm9eO9mmLrr1xA1jcdNM3N4h7lqK+7aDT0LEYKC4Y375MBcSuJjKtWTJy7EcC8VnD5t10NFhw1YJc2tJW5cPPNx/dvP5wTfwJz//73w8Pnezfn+7LrpL0VuMrjqGhhibSRuYy2tskV5nKKOoLf2nmuSClTILVsosVJJapiqnpDNDzWDW+o3T1I3k/08IV2tKKetKaRrP/Mv8bWPLmVvt5lm6fmDv85mz/6fOAR85+L7t6D3DykvK0kN6j/OsNxDauMo7eMk4+Uk5emHvgb0Hjl44+0g6eijstZfevoftu+XMd0sY7ELLnPUG6GhhtgGnzcTtItGWtDfOuQ5kO3HahVPO5NuS7sxhe07aUexDsbtcni7Z33D2Q+kzH9Ok8uEj+596nN9p9aUrnoZ4WjN5nsfwOQZLP3rVvWb0uok4/9czj58bFn9V++NnhW/PLZWZ3vPW/PsffzrwzYd9//5wJE1ZtOweq9YUHVovi765nUl7Ai1HaDv2H3PoJHqP0Z/JgzxeXnv3dcXS4dp1Q9Uaj0v/bM2ZnRvNqXAKE2UHLv/0qHTBeKue6LIeqVXvy6EyllJ/OuK4d4KOAzRH03WA1mjaY+k6SFsU7dG0R9McReM+6vfREEljFM2HaT1C8xHq4imJpHgfDUfoO83riqUvihd0HqciisoImg/z8Nz3j/N+vXuBx1dmvS79YrTim6Gyz55f5d55Bs5y8yRdyVxP5N4phi4zWvjOcMnHIxVfDlcwWsl4FRP174jGn0Xj8omGNaP160TDP16Xyov6zwevflgWRJkvFf7Uh9AQSksY/ce5eWV6lO90HQPWGqFmOP9NufSGwFVa0ivWyyxVkVqszLd/yHy+SOL9RZIf/1v+mwXyfyzEUAUHY47vIc2KdDuynbjgznlXifRdHDYkQpdwHYK18NPAZz0+mvjpEWhAnAnJO7nsR10ctGbSfYa+Mwyc5eEF7p6jN5PeTG6c5N5Z+k/Rn8mzi1JPznPzJP2Z3DjJ/VxunqT3BHeyGThF7wnu5vLoMi+KeFLI80Iman4TTcqTDSsnGv+YaFkj2tREp6bo3SD6N4tbW8VdC3Fv9+C9APE6QLyw7b32TX/BV7eLfx3IX9CV801+2qw4H3Ybs3EDWy3YYz/d3vUzF4+f3AN+DQz7d1Dwz/7eX3nafbxDT2LDUnQXoaWOoSGbtslv2DZtvYnsan2JP9dLLFbmpz8lf1kpuVBJarm63Br96es3ztTYNF1jk9z/L4QG297ZtGfGVrt3drl+bO/zmVPA528gtPV6y8pL3spdYY/zrN1Os3Y7zbJ0nWbtIWvjLWPvgZ079h44eOLoIW3rPH2XtbTZdonNO2YabZfQNEfZREpRW1pZDX1NzA0JMCVqN0l2pNqTbsdpB045c8qJ02acdOSYG5keXPGmwJTzv0gUvjurZNpb2RISF6ZJV305o/pniXoVbjrwOHZObxaDBfKTZf8YLv91pFxjPPuvfvNfs2aQB/lSUmXy09pmzL47Z96jObPuvKdw69PpDaYfiXObRddO0a7+IP+9O7lcP0brIdoT6UiiJ5GeJPpSuXWKp5cVRst+HqvXGavXeV2j9rBkWf3pt06FcyqM0nSFBwV/vqpZLdo3iTbLoWq1W3nUHqTIj/pwHmbSl0xTNK0xtETREUd7LB3RNO2jLoz6cBpj6DhEVzLdKdzN5UYGrck0HKIylrJoquKoP8rjot+flyzqyZSvjKUmjlvZH4hmTdFuNFq7WjRqiPZNomub6DAVDRqvSn9+eOX9O9l0JtFxhPunGL7M0DWGi2aNVnw8WsFIBcOVjNXOFo0/iKYlE40rRmtXTdR8OVwxWzT883HezGJ/SrypDKA+jPoQWiK4c5IHxR8mRU7T2YCiLiob5q4zUFijr6CkK79KU/5PDfk/VOUWKUsvUJT6bpn8Zwt57zepjxbO/OyX2f/8XmLp7+itJ2IT0aYcsCBhD2m2ZNpxYpdkognBugRo4qmG6xqclHFVxV0TL12ijDhsRq47JWHQcpzOTDpP0p3F7fPcPc/ts9zP4/FFnl3m1mn6M3mTgHs7ixsZ9Gdw/wz96VML0QOZdKdyM5N7Z3l+hReFvCpB1H0vmldONqycbFoqmtdMtq4VnetFt47o3yhumYrbZuKu+chNL/EkQLzyedGiNdS0RrRpjTVseFqh31+xpCD9kwMB+Dhgb4eNo5STx/ue/t97hS4MiFwcHL4g0P8bL/tPduhJ6P+Bzm9oqWOwEWOLWX9ZzFY1kV2lK/O7Kr+tlvjxT35ZKbl4jfRKjWlrN8xcv3GmpvFMTWOF/6ccVdaV0tg0/S/ztw13zzKxnbvT5SMrny8c/D918P/E3uddW6+3rD2mW7nPsnR5a6fzrB1OM3Y6T9/tOm2P2wxbd2zdsfPA3lPKzkN2r9MMC0uFLRZSRuazdMwkVDaz0kDm9/XTlirLKKuhq4etAb5m7LckwYZjtqQ7kOlEphPZe8iy4Zg9yW7k2JG/jtpv5z35eVn7vLdrZs4ulJWvmTaza+6Mtndp/YXbG+SGjn/68PQ/h2vURY3ZQ9/FZz8hHZre/UfrvLcrZslVzJVqmi/dM19i4EPJ+9/IP1gwp2r53Aduv4tW27HatU9L/vnoskJ3Ml2JtB7lehK9yfQeoz+Nu7m8KvxiskZRtJhNNBsO1q27W/hr5Qmp9CAyI6jOmvu4aM1Yk5boNJts2DVSq/W67L3udAp9KfXlxZl5j7JojaVxH63RdMbRFElbDM2RNEXSeZBbJ3iYy5M8HufxII+BLDrTaEmi9iAV+6mIpjKO61lf38r7V0syZdFURtOTITNRvVI0qIh6lbFa9dEqrdFKvYmav0S9rmhUm2xc/fLau7dO05PMrRM8yuZpHkPXEDUfiqr5oxXzRsrfG6v6bLLue9H0m2haMtHw+3j1F6NVH4iGfw1kUuRHsRfVwdSHUR9GRwxPcnlZ/mlWgqz+RlZpSSvrTVujP32KwPUzFqkp/LZmxo+KCt+tkP/2D/kPfpN4d4Hk/IVvzf9l7kffyf2wkFXrsNbGxRDfLQSbEWVOvAWHt3HIHG8t3NWwV8Z6JdarsFfGSR1XTcI2ELuZDFvOe0JjAq3HaUyjKZ3uXAbyuJPH4ysMFTFYyOM87p/hVf57wwUfPM7j5mluZnL79FRAUn86/Rn0HKc3jXuneXGJVwUMliDqvhaNSycb/hTNy0SLqmhRFa3qoktH9BmJgS3itqm4tVXcdhaP/MSr8Mm+vaLDRPRtE907Bzv3vu7Qv1u9run8otzEz2MCJF0ccHKb4Rv6D9+IJSH7l4VFLgoO/M7b4bNdehL6i9H+lfXqGBhJGW+fp79t7rqNM5Zqyy1eI/PbKtmfV7BAUWKJiuwqTfk1+grqRvKaxgpam/9Xjv63MaNuJK+3dc5fO6dtsppn5vT+Hs9PrH0/s/f72NbnXWuvedYes/e6zXgD4XbHaWYO8m9k7SJr7Sph4yZp6y5t7SK7x366haWC6XYZ/S3yGsYoGbJUW/q3NfK/rZq2bI3MGk1MdbAyxs+CyD0csuKYHakOpNiT4SSdZkGCBQmOnN7FtT9o+vCt+18tbJ09ven9uR1ffvbg238Nf/7147mzb3wge+PXOeVrGD+kLC7uqtr61YnZVMtPa5H/8BpzKmZ+eFZK+tJMqbZv595f+P7TZZ/dX/XV9RWfC+Nl7Rs+EpfNRZPhWNPqJ1c/bDlCdyLtR+hJpO8Yvce4lcHjPEZKf5msXS9ad4g2o1f1q3rzvypM4kQgWdE0nvvgSfHayVY90WU+Ub9bNBmKll/u5soU+1LkzvPsj55ly3fE0xRJazTt+6kNoS6UxkiuH+bBKV7nvzVWPO3VNR5f5MklHl/kXh59J2k4MrVdWR1PxUGJuiMy5ZGUhlMZQcNB7ufNe37145HK+cPlHw6Wfzxc8eVwzXfjDT+LpsWi+XfRtGCo8L2H2QykcTOVuycZzEfUzhZVv4uqf09W/jpR/fNk3U+i4VfRtFg0LRmv/mK8+gtR+31HIkU+lHhTE0JdKM0R9B5h8CIjlV9dOYmxKUqas5drSypqKazUkF2qprBQVe6XNdP+tXrGP5crfLpM/ouFCu/9KvH2L5Jzf5327o+zPv5Z7sdl0svUMdFhlzH25jib4b4F3y0EmxNmhosW9qpYKrLzT3YtZ68idmtwUCNAm9ANJFiQbgNVMTQcoTaJ2lRas+g6Q99ZHubzuoDX12YOF3zw+srHLy7NHyx459U17uYycJL+DPoz6D1OVzJ9J7iZSc9x7qTz/Dyv8nl1jbHKD0TtwvH6xaJlmWhRE82qky0aokNb9BqK/s1iYIsYMBUPdoiHLuJlhLjtJTr2iJuWon/vqwEH0bV3smP7YLNRf5F6fspvsUEf+vq87Rvymff/R9Z9tjWdde/DPwkhCSGB0AR07Dp2RVRE6X3oVZAiIKB0pIPSBHsfdcapTh8dC6DSe++9N0F6UxAFaQnZ9wOZ67r+v/s49oPkBXyOvb9r73WuuyrXv1O/ef/IjWt74sM3elvDWhHm8jA0gLUdxd5dwvwkR8NGWNGIJq9N26dGV9CiKOoKKhvRPyM0tqeZnaD/H4QaJtAyh5GdkKULy8aT7uDHcQ1b5R297kzc2oD4NcHxq4PipAOiJM9EivudFfWKYLmHMVxDhJ2CmE5BTJ9wlm8Ey+8cw+8cw/cszTOE5uZPcfGmHXOhGTtC5xhUTQUP64oe0GQd0aVrmVKOW+KUA0LdcMkLd/3xUwgeBuNHf3wfil+c8LsrfgtlPHdF6UG0yQm3ya5+Lc4pFae37F0/cHBrm5jQkDhj4fCOcfWd3YfxRl1syGB71bZVuaIilWzJUiGRKgYrhyadyxRr2f7F+JFNPbvF2vdwBkz2T5w2JB6GjVoin340Il2BvGariexNHb+h6yG6fkbPr+j7DX1/YSgR73OwVKFMam1I02nScXy2UbEjnZX9Ix5dRdr3aMlaN1NhxG89RjrdSdMZ0upCGg/0JyAvBnkRGPhVov83tH6D1vtovI2mO6i7gerraHuAsSeYzVq1XLJ6qZT6MQ9v0zGVhbfpGHyJ149R9yNK76DkNsruIec68q8i+zyqr6PuNqrvoPcfjKXjQw5mC7FUCV4dSCP4DTL82h28GnnSfJDU7V4uYn5IwehTjCdgLgukAqRakdQqkrqDpF6B1O0n9QdJ/VHSoMar/nK5ZjOp3tH4AEXxKI1feTPQfo82/AgkH9yqL8tS4emJryxWK5tC1YiiZEhR1BWU16Zt02JuUmeuV2bKKjFk99Ol9lMk5CniuwVl9wp/eYR91JChayNg4wo3L5pvIDMoAOF+iPJFnDfOeyDGHuFW8DeAtwY81eGjAT8t+OsgyggXLPDgJH73Boquo+YBqh+i8i80PEdzIrpeYDgd05n4mMPil23jFe9+ny4xkys6X4TxNIwmoP8xhp9i4DE6fkbf3xhLQt8jjD/GhxTMZGI6G3Mlq3hVCvxaRdJylLSYkybT5WYT0m5FehxIvwsZdCWDrmTMdmnEm/f+6vJQPGn1Jm98lvs8p4aDSHc86Y4g3Wf47T4DxU6Zf+s9uLPv0rUN8fdUr3+nfuubo/9FeBCWe6CrDTNLWJ9gGzmwjppT5bUFd6oI7TxMO6hDVdIXUjER0jJn6B1jGNkJ/R+EOuaC6sbQNIOhLdXCmWnlKWznw3IJkfSIXON//ov/g9DnHNsrguUWSjsRLOQYQLMLYHiFsr3DxHzCmd4RVK9wQY9gips/5aQP1daFZu4IvWPQMBVS0hM7qCmmpM/QNKNZWzOcHaj+JxHjgRt++C4I3wfgGx/cDMJP9nh0kvLQV/QPa9Qp4t1euQH5L3tEVuWz6BOWquS0UdsmZv9G5qKBQp2C9NsDzE/bJZY3b24WEk0VFM6Wlc4RpVaLUMrZ0rkMwZbNzGlV2Q/K4m911rw/qfwu1IzobC3ajdcx8qT77FSZ4UT2jpEkvP4N3Q//i3DkBT7mC/OqNEi1Hbfemd9pOdMg35yK9Af45zoyH6Ijb8t8jflyqwVpdyUtQaTZaa5sW+svSA9DZhAab6L2Bupvoe0+6m6g7gaa7qDpHvp/x0ya7HLJRn6ZzHwRPuZhOgcDSWj/HZUPUHkfld+i4h6KbyLvOnKvISMWGRGovy7WeJtSdhktP2PwJcYTMPEK0xn4mIdPReCWSpNKJVJryC3fRhr2kYYvSQlm0jCdgk/Z4BWBV72J1G0jzTtI817SsI9fq8iv0SA1uss12/i1W/lVu2ruoigeZRdQdxPV19DxLWviGUgJuFVfVmfB1w9GlpuUjPC5nXePFnZoULaq0dcrM2UO06UP0qTlGasO0KT2U0R3Q3Y/fZ8mR9tazNSZZuXHcg6R9IqUDomWiooSiz8nEh+CGH9cOoW4Ewg1h68uvDThoQ5PVXiqIkIPcSb41lngd28q8m+i8DbK7qP6OzT+go7H6EvEcArGUvE2G58KwSvcx807MJeLTzlYyl0z/gIjzzH4DwYe481feP0b+v7GWAL6/sZoAubz8SET3EosVHBIqwavyZC0mpM2U9JuSjrNSJcl6bHh9zvxh90WR0PIh0jyLpT0niZdLqTLjXS6kx5v3mAoGQglvcGkK+Bjk2dXoc2rx4fv31597e6+ez+o3rindOueQniIiL0xnDVhshXmRxB8iuXp+YWRneReQ8ZaDcp6DdoGTbqSJvWoLlXNQFDbTFDPWtDIjmJyAmZOFLMTdBMH1lfWTE0zppoxTc1CQNcexi6U4x4cey8xJ39x91Bp76hVfuel/eMk/ePEgqOYZ6Lo/pFC3ucE3MKFXIKYDv4idj4c9wApN38xd3/hU4EUryABryABTz+c8oH7SRxzElS3oSgaCR7VpmloMzT06KpGdHVHydNWUrFuWz2CpPxC8WMovvcTOOOL79zxnT2+dsSdk7SnxqLV20Rfb5R7c3BXmaRsA41VsVOWRDoO710zqLR5yt1oQvvw/KH1b0x39hxa28dh1UqyUmjUVqkvCgSZ+SKratj0T/tl5jVXt6lIjDip8kJshy1VFhREezUEK05RyUDEWIv1bK3hh6cbpm/gzT2M/4XBJ+j9B2/TOPNFO7lle0ntblJjQCpWvStCexqeXEHiTfHyf7a8Lty0WGtBelxI02nSGEDajk9koeY+0oPpOedQEouaS2i6iuZrqL+G2huovoWquxhPFF7IW/spH0tFWCrBXBbeJ6P6W1TeR/ldlN5B6W2U3ELxTRTdQPbFlRaT3EsovIaSW6i6h8Yf0PM33vyDwaTPxVvwS0EqJUn1l0s165ZrNpOaHaR6OymXIUVYzMZMGpaqwa/dSmqVSY0mqTtKGhRJ3UFehcJC9V7SsGcmm1NzA2VRqI2XKj+Ppq8x8DMWX4FkgZTq9hWzQ7xpOuaMw8b0PTq03Zr0rRr09aoMuSNMjiKTc1CMeVD0i71UiV0CIjvBkcdWVaibUK0dGa5uYh5BEmfOrg2N3RoWvyP84vbwi5sDz8v4RAp6h8LfB/E++DYcd/0RZAaLw9A4AOtD8DegXHJg3HHCytvT0s9Fqp/R9jd6n2PgJcZSMZ6Jj3ngFu5Yyt/xObFvPltoKhWfHQ49Qf8jvPkLA48x+hx9f2PkOT7l4EMmliqwULGKtKj9PwjbTUmXGf/1seW+E2TQdXEkkLw/S8YDl1878dvs+W32/DZH0unM6/Hh9/qS1/7kdSDpCnrX6NWQdyw1Qe27XzSu31GKv7Tv+o1DcedkPa1xXBn6a/HkJvXD6/CiDFdDEyhqCexWo8vJQ0Fb9LCWwFFdqrohVcec+tUxqpEdxdiRYnICJg5UIzthPUu6ugldxVBQ1VRAx0bA0EnwmLvIcQ+Wo6+oa7CE5zlJnxgJv/PifufZwefFgmLZAdHCvlFC7hF0lyCmvZ/wcW8xF1+Oiy/L3V/4dJCgTwjVJ4TqE0j18oenL+u4O03Pjq5mxlA1FFYxYCiZMA5a0Pc6ws4OAR4U5xB4heB+EL4LRFQIQv1w2Q53zfCdpVCCDqdqs2innNTrLZvKaSJvmOJNm1ZNHVMe2ik7Y66yEOPWY6E2p7O/89jBYb39bzesrZWVeE5BLYNdz5KulZB8s0l6fL9Uv7L0kJX8UtCx+VPGHYprRxTEu5VYoy6bSW4Y+cN0/MK2Lg/K20CJ2asS/TfQ/i1a7mLwGzpJVyeNlm9L9pIafdKovNS4qz9P8u+L+OciKv9ZO1WjPld1jHSeJE2nSVsoaTDreobi68gPl8iKQHEMqi+ujN37D8KyW+j5Gx8zmTO5mM3BbB7ep2H4nxWBJbdRfHOFX+F1FFxD1oUVhDkXVt5/ld5C1T20/YKu39H3FKMpmM4BtxikHKSCza1cxav6glRtIpVfkoq1pARLBVjIwXwF+LVbSYMKqdMgtYqkdh+p3cevOcit3ksads7miTfcRmk0Gi6I1lxG5wNMJ4Jkg+SBlKq2F8D7NDRMhfYbCh7QFNqvTtulSvvyCH3tYZrMQZqEAl18P0NmD0N8txBnj4CsImWPjqC+jcgJdwlPHwmfMKmgqA0h578Mi98RFr8j+NLWM3FrvaM5XhHUoADxKxHU3y/hh0iEWcHkAJR3wGAXbA8gUBc37ICCmyi8hZKvUXkftT+g+fMg8kSMpmAsDe+zMJ8nulQot1iI2Rx8zMCnHEylYiwJI88x9BQDjzH0BCPPVhB+zMTHLCyVYbFiLWlW5TUZ8tvMSZspaTMhbYakw5R0W5A39mTAeWnwDJkMJcPeS2023GYzbrPZUqM5r9WK13mS3+lG2j1JxxnSGbjUHjhU5daYZ/3wT81rtw58c0fj2xtHYwOYATaIdsDPoatLfgWv72RDnr2aIg4fxhFNsV0HoKonflhL4KiuoIYRTdeCZmBDM7KjGDkIGDng86N4HXOGqhFdSY9yxAgaVtBzELA8yTzmLmLvJeYcIHYqXMIrUtwnRsI3lhMSJx18XvJMrIhvJNMjjOYcSLX3ptl6CDl5s5196e4BVM8Q6pkI+pkI1plQhl8w/VQA87i7oKEttC2Ej5gyDxjT9plTFWwYyh6CJ7xo3sEU51j4xuJKKK76IdAbFuG4YIu/NPFMg5WqKFm+RqyZJdYmtqpekD4sItG1RuLNntX9m6SmjI9yr/oOBNlNWWuNRNiTwBMD69flidDSGbR6hlg9Q6xFnDYuv2ZMc2Of2d5JL9MZD8sJPYXh3VKDR9a372D17WEvGXzZt1+kabdgwyGRJQ+NQTOJ8XM7SYrN/M+qDbZ4f24TqT75/o3jTNVXvBbb5U6nd5VaL+8g+TZankt+qjTmNZ0ibSe5DadIdzBpNmp7jKLLKAyTywxHYRQq49BwGQ2XUXd1BWHFHbT8hHep+JSPyUzMZON9Gnp+R9kdlNxagfd55V1B7mVkxq8gzIr7t7vyMoquo+4+mn5A118YeoHpDHzeV5eLwSsDv1yUVKwhFRtJxUZ+uRSvDNwyfCoDv3YraVIn9WrL1fLLNTtI3X5Sr8Sr2U0adi7kc5rvojwKjZcobbcx+icW00HyQPKwXKJQlwXXkzhqTN2pJ7BPmb7nCG3nYdrmg0JrFair9gqK7xYU20UR3c4Q3UmTkBfccETwkCHVxIHh7CniE8A+Eykecn51RPzWsPgdoXHbg+K/9Itd53lOxt5P2M2DExOCh1fxUywibGB1CFp7oLsLhjtwWhVfOwP511B4A0W3UX4XVQ/Q+Cs6H6M3ASPJGEnB2zTM5GKhCEtF+JSL6QxwC/EpE+9eYiwBo88w8hQjTzH8D/r+xvAzTKVhNhuLJeBWbeE3qC03G/0XYasBaTMgnaakx4b0O3IHvcnbIDLgutRstlSvt1Svt1inu9hoyGux5bc4kBYX0upFOs6Qdv+pOtf+4mOPnih+/2DftzcUonyF7kUL171Ua3ypWPxw3XDhjvQf2I/v7zXQwCElKGkyj+jS96vjsBaO6gqqG1P0LOmGtnQjOyEjO4qhPYzsKAY2NG0zmrI+XUlH8LCBgLq5oK6tkNkJupUr67gHx8lf3C1E0uOshE+0lN956cDzMoHnJc/EcPyiWJ7hdLdAmr031daD4uzDPOkv4hEs7BvBCopkB0eJBUWIBoQxTwQL2Z+mWDlQv7JmHDGl7TGCoilFw0bYxJpl7yZidxo2ITgdwwmKWns2clNAmJxLkMCvZrTKA6KVu6Xyt0oWSnKqaSK1NLFmBvO1mGi/nOTAGonB1RLNW6SnfawXr52Z9Dg+fNWPH+XbJCWTShXMF2c3MzhtIpJ9ctTBPWIjRjvf+5h/DDgxaKT2Zqfs3C6pvp1SPZvYw5vFe2RoQ9tWTanse6O856ONQftW8Td2O7nf2i5d1O3TFl48vZ0Uuo+Oey4PepGhGDJ8jQwG9OUxB/MwU7aLVB8jXX7cNteZGhfSFUhaTXqTUHkNmd6c9FDkn0N5LGrjUXcRNZdQcx01N1F5HzX3Mfgc77P+7UdNQ9dDlNxC0Q3kX0XelZX1OVjgPx3PmeeReR5Z8ci5gNyLKL6O2ntofYj+p3ibgg9ZmMvDYiFIKUgpSBousLUAACAASURBVLkoKV9DyteTyo2kcu1y9bpPlViu30kaVUj90eXavby67aRhH6lXInX7Sc2mxTy03EXZObRcRd/3+PACixngZYKfC16JSmUGnJ0FVE3Edukyv1RkfKnI2HiI8cVBxqr9dI68EH2PkNBuqvAWIfEd1PUHBBW0KDqWAo6u8PVHaCjOnReKvSwTf3XT+Stbz17aEhq/2T9S5nSIiOVplo2TcKAP7l7At9EIs4WDCqyVYaOGE+o4Z40/gynIu7oS/lV6B5XfouEhOh6hNwFDLzH8EhMpeJ+NuSJwizCfhw+Z4BZiLgdTqZhIwlgCxp5j5CkGH6P/EUae4+0rzOdisURguWbHcr06v8WYtFuQNlPSakya9UmzPmkzIN0WpNd2edCLTPiSPqfFRsPFOl1evS63TpfboM9rMOc32ZBmF9LqSboDSPeZpWbXyUrrVy+33b+Gn6/LJX6/oyNbZ6nH/n291nDxgf7y40GO8DnJ0NMTOKgptFeTomxB26sHJW2o6AlomFD1LOkGNjQjOyFDWxjawsiOYnCMqW3KVNanH9YWOqxHVTUV1LZmmDgwLJyZtqdFHX0kTgZJnI6Q8omWPRO32j9O5ky8bFCcdECshG+kmEcYwzWA4ezDdPMXcw9ieYcxz0SxQmMkQmMkQs6xA8NZJ8IE3PzoLu5ixvbMo+YCSoYw0xc4ZcC47CR9/+KWC1cQGg+vGNiGCbhHSvpGiN6zoZWriE5sWdW9TrZYRjKfyS6jsSqYnAqOSJUMe3Djmrey0uOrZcqFBIZU9y0EOixH+bXFug25WddLyRSIstNotFIB6tC6zTM7JXv3sofMds/4WU06WfYrKwxslh6XExxdxxjaxBxVWNWxV3zmmDL/tMWYhebkMaOuzTIt2hvbTuzsN9kwqShB7LeTV7bv5yLITBx5d4eMfEsmwj81ruG3gjRsImW6pNVxufX4XJMb6QpbbDLtSUbN10jzFEwLQW44SqNRfR41cai6gKorqL6BynsovI7mhxhKRO8zjLzA2Eu0/IDimyi8/i/Cy8j7N90jLRbp51d6SjJikXkeOXHIiUPuJZTeRNN3eP0XRhMwmYrZLMzngZSAlIGUg5SLkrJ1/IrN/KrtpGbXUs06Ur+f1KuQOiVSv5807SWNB0idEmlU4JdLzWWi/R4qo9B9G5N/rUwd56aDnw9SYVyZxnSyo6sbcParC245IrjliOB6JeqawzSZQwzWATpTnk6Vp8ntFNiqIHBEHSbmcD+J8CBcjMGNi7h1Dd/cEfvum7Xf3t925+vNl66tjYil+YXCzodl70wL8sK9i/g2GmE2cFaHsw78bXHeDT9FIPUykH8NBddRcBMlt1BxD3U/of0vvH6KgSQMJ2HsJd5lYrYQvGIsFWA2B4t5WMjBTDomX2IiARMJGH+K4UcrX4bjL7BUgMVicVK3f7lenbSZknYr0m5BWoxIkx5p0iYtX5EuM9JjyR9wI2MepMd+se4rbp0uqTfk1RnzG0xJ8zHS5kDaXEnbadLhSdpc5+os3pVqZSWKvfhVuC1Xd7nPk7xxnm7QnmnWJ9O+X0dvN1SFrjaUtAXUrSQVjCiHjKFsjiM6UDGAhglV14JmcIxpaEv/3CVtZCf0lTVDy4RxRJd+UFPooA5V2YiuYUE3tKWanRA55i5m7yXpHCDpHirtE70mIH594IW1QZe+CLokF3pRLihO1i9K0idMyiNIwj2IczqE4xPOOhPFColmhcaIhpxjB0UIu4TDO4jpdpppaAtVc5gaUQJVBa7uQV305plyy5EWzea87Qm/rgo7j7CziPdCriK1fytrSk6qRVI8n80qpIlUMMSKxDm5TKGcNaIDW9aNS0qNr5PrYNBG10n3qe8g0Wcmrp8ZP2lVzxYvFedkiNBLBGktkrLj21e9U9s856D83kb99aFd/Vs2jm2R6VklMLmRM7CV1akg3qwhO3RCcdhFZdRRgwTaf7JWnz+t985OflBRcnA99fUhobc/aBJyd3n6Mn/8Jum7SHqdJ/IwWwJeCXh5qxZqDvM7TEhfABm7Ot98vPsVGn5EwVlqahBywlByDpUxqIpFRRwqLqHyGqq+QcFVVN1fGTzcn4D+x2j8BkU3UHBtxV7upf8fwhikRSItcgVh9nlkX0DhNVTfXynFjyfiQxoWssErBr8UpAykFMulYryyL0jFNlKzl9ewh9+ozG/Q5tUpLzccIi0KpEmJV6dGmvYvFuJjKrq/RdMFjH6PuQTwMrGQjvlU8PNAKq1KkuBgAX1dqKjhsDYUtXBAE/vUsV0FGw9j3UHIKGD/Qaiqw8oMPi64EIh7sfjtBh7dxaNvkfAT49Xva179ueWfXzY8/E769g3ExcHFC04OCPTAtxfwXQzCbOCuCQ9jxPvgp2i8uonc20DR7ZVVcgvld1HzPVp/Recj9CViKAFjLzGegel8cAuo/MIvFgvxKRsLeZjPxodUvHuBt4mYSMDov+/ZxxLAK2QsFq8ijUrL9Vqkw4LfYb2CsFGL36BJmrVJhxF5bcHrP0GGXUi39VKN/nLtV6TegtRbkvrjpM2BtLuQNlfS4kqanXmNxz5WaY0XKbRk7+a+diJDvrwW26VmMzJyiv/6VNWTw25Wgg5msLKi61kKGTmIa5gKqelCXRvK+lA1hIaJgK4FTd+KbmBD+4zQwIaiZymkYSR8WJtxQI2moEFV0hdSM2XpWlGM7WlWJ0WPe3AcfUVdgyW9o1YHxK8PuLQx8PL6kCvrQ658EXJBNjB6lW+EhGcwxy1QzD2I5RlC8z1LC4pkBEcxQyIZwWdFToXBL5h+0l1Q1wZf2dKDbWV/UxV/JYvX7jKkyJLUKS+k7en/Sf5l7MbkkDW5x9C9TWh8A7tHlpMryUpliZQLsWoZ7FwOq0SQnrFKtHvt2lExid41kn0SjAkpVttu8Wlb/aWbgQuuVvVURjGTniMqUsMWz6QKdW6QmTM4tGB1eOjgFz1yogOSnP51Ym92ir7eKTehsn1Me8cnO8Up2/39pttHbPYteuqRWGcSbDZjvGdiO2dknUi3itTYN7rk0w3y8TZ5f52MhZBew7c5mCsAKQEpwkKF8GLDPtLvS6Z/XOzwanuF+l9QegmfERafRUUUKqJRFouyCyi/jKr7KL6Jstto+QX9z/DmCVp+Qs1tFFxF3mXkXPx/1ueWvIw4pMUgOQLJEUiPQlYMMqKRGY/8Kyi/jcYH6PoZw48w/QLzGZgrwGIxlkvBLcNSCXglbFK+mVTvWm5QIs06pNmYNOosNyjxGxVJkwqp1yONCp+yMfMKQz+j52vMPsJSMhbTsJCOmWTw80CqzMoT4WEHNwe4OuC0E047wdUBjjawNoeRIfS0oakBCyM4WSPYFdcD8VM0nlzBq3vI+A65D1HyN8qfiZY+X533RCr5Lzz6Hj/eQWAwPJwR4YYHMXgQgVAreOgiyBb3Q/FnPNJuIO8WUHp35R1t6W2UfY2qB2h+iI4/8SZhBeFYOqZywS2QIEXbecWYycRCHhbzMJuBqVeYfIG3iRh/iqEnKwj5xZKLxWtIk8pyvRbptFxB2GxAGrX4DWqkSZu065MuU26vHRl0JB2Wi1U6yzVGpN6K1NmS+hOk+Ti/xYnf5MJrdlluPcFvt1lq1v9Yq0h6nciYP2l3Iq32/Fab6SrLmica5x3gYgwXK1hbwtQSarrQ0YWViYSBOl3FAGpGFA0TAR1zwX8R0g1tqXrW0LWgqhsyDmoK7Veh7lOjKOrSlI3oOuaChrZ0C2emzSmOvZeYSyDH8+zqM3EbzlzcEHBpXfDldcGXVwfFSZ+JFPcKZXsFslz8hE/6U04FwjNMIOAsNSiS8Rmh71lKUKiI22maoYOAvYfcA79DlUY7OmQYLbpr33+rWXeZUumMSmvxZNMtxYbbqjZRp3aITGwRr14v9liO8VyUWUsTqxdipYtQmyisNBajTXzVKFu6cRWzQ4w6JUkfVllbt2v1sLfZsL5SsyCtnCWSKEQpZ3Py2aw3u3d91FPqlZdqEcfMOunZ1bKdsow+RblOLYUlR6MFo6N8g4PD8lI9e9mDOmvfGGyscTncZb77ndKGD5ukB9aIdWtvnHnoQKbv89/dJuMxZMiZ9B6ZzsFSIUghFnOwWI6pQiw22pGpn7ndAY2vUP4jcuKQFryCsDwS5VEojUFpPMouoew2Cq8h/ypqH+D1E3T+jopbKLyI/CvI/U+szr/hOln/htClRuNFGJJCkXoOGVFIO4eMeORdRskN1HyNtgfo/w1TCVhIw3QuZguxWIql0s9zV4VI+XpStXO5XoW0mpAOa9JsxKtX4tUfJo1apMmINMjPpmMmGRN/YuwHcBNB0vApGYs5mE0DKQFpMm/OQLQvrkYK3YnHgxh8G4XbEbgajFhvRLjC3wHeNghwF4zywd1w/BGHF9eQ+TXyHqDoR5T/htp/0JRIqU8UrkykFD5Fyp94+gPu3UJcEC764PsY3AtGsCk89RHhgp8j8SgWry4h7zowW2HU+KtUzgVUX0fTXVRcR+ltNPzCHP2T2v0Ak4lYLMBUJmZLQVoUP5SpLRfjUzbmcrGYj49peJ+Ed08x+geG/8F4AiaSsVAm9aFQht+mxW83Wm6zJO36pFWLNKuShiP8RmXSqku6jEmPJb/HgfTYkVZLXrUBqTEizTakxZ5Xb8urdyOtbqTNgd9uw++wXWy0XWh0Ia+DSas+mXCca9eerNWar3N4cWWTszpcTWFvR7GzxTEbAXMripEF7fNAOQ0j2mEDHDGCqqmAhrmglgVF14piYEMzshPWsaJoWVDUjGmKuoL71QV3qVP2aQkd0KNrmArpWtOMTwhZuwnZe1PdApm+Z2WCYtefPb/+XNzas/GyZ+OlIuJFg6OpfmHwCoKzl4CTN1x84ROCoEhGeIxoaKRYYDgrMFjGP0DSOoBy0BG/Rsv3ntj/TmlTEQc5oqy+gwezxcVf0mjpopx/BAWTWZwEhkiBKCtXUjRTRixTgpXDpOfRaLkMRo6oSC6NWcFkt7Il34hJDHE4w1KiY+vE326VnjyyeWTvuiYZVhlNqJLJLGWK5NJoeSz6wPoNPWz2IJsxuV6qezWjdbPosPLW9h0yHz0MPjpqfNDfO3Vg9dhW0aEtogO7pPsVvni3W2rwkFSfkuzgDql3m1b1H+TwfzImE2FkzJvfd46MR/Ca975PAz8D/DzM5oNbiPelmK09SqZ/JEOePVnMrIvIiUJGOLLPouAsiiJQeBaFkSg8j+JLK9cPRTdW4h7K76DwGnIuIucC8i8j9yIyYpEWi6wLyLqAjDikRSM1Ci/PIjEMSeFIO4u8KBRGISsO2bHIiUPpJTTdxZtfMZGA6RR8SMdcLnhFIKUgZViuAK/qC37tTn6DJr/bhjfoxu+xJI2HSO0OfpPKbKclqcJ8FqYTMZeIpReYT8BcIrgpICngZWGmaBu3WbMnDalfI/MnZP2Owt9Q8Csyf0LC1/j9An6IxHdn8f1Z/ByGXyLwVwwSLyHjDkq/R/VvaPwbLc/RmYQ3KTJ9qZLdr9DyHPWPUfMXkn5A8j08isf3Z3EtGL428DLE5RP4IxbP4pFyGXlXAdLlOFtytP+ZSO9DDP6OqaeYfI63z/H2Fd4lC0+lYerzRUUpSLUcqVQjpZjPxXweuIWYzcCHl5h8hrG/VhBOpmGumP2pdNNyqybpNOW3W5FOE9KuR5o0SJMKaVYlLTr8dgNeuxEZtCOd5vwGI1JnQhosSeNx0nSCNDuTNnfS6UmaTy7WHuc12ZAOa9JpRLr1SYfhcP7e8UqNgXztP84i1AR+FnAwhZ0d7OxwzEbAwhpGFhRdE4q6MUXVEIr6UDKEiglF3YyiYS6ga0H9nGP3OcFOzZh2UIeyT42yU01gryZVQZembkLVsRIydBC0cqUe9xRwDWB4R6wKiF4bGb/pPwjDYjmB52g+IdTT/rA/TXE8jRNecA+Af7hQ4DmRwHCWf4iwd4C4h6egrZ+AthsSrym3mm0c2iHRtEqohCM6rLC/RIKTxaDnibJfUKlZbHYag5FNo6WxGGkckXQ2M5fBKKAxClisPHHRXIZImQi7ni3ezhbvYLM6OKxOGdGudZzXO+W6t8g2SLLLGYxKEXYpUySXIZTPotczGH2SklOrpSc3y3RvZHXtXzVrfGhaX2HUSGFMd/e48voxeenR7WJDW0T7t4r3bZUc3ybVv39V70GZvq3i77ZID6qIL/9mTEb9yaArvzeUjIYuNuycTAUvDcvZmM0HtwAz5eC16pN397hvTnRkCubeQEY0MsKRFYG8COR/XudQeB5FF/9bfSm4iuIbKLqO3EvIjFuJtMqKQ0YssuKQfxUF15B7GUWXkRGLFxFICsers0g/h6wIZIch8zyyY5F3HqWX0HAHPQ8x/hRTrzCdhtlsLBVguRjLJeCVgVf1Bb9mL79BjddpyetzIr1WpFmV1OxeblRb7DQnFZjLXEG4mITFBMwnYelfhJ9KdvJatEdzRSseoikBbWm09lS0JqM2EcV/Iv07JN3Gsxt4fhNP4pF4EclXkXkbxd+i+iGa/kTbY7Qn4vUL9KewhtKE+9LwOhltCWh5hqJHKP4F6bfwZxxuhMDPBr4muOFK/TsWz+Lw8gKyLwKk15m0my2U732bgpEneP8E80+x+ARDyeBVbF+uUJjOlflQgE+F4JWwSZMqqcBiPhYLwCvCp0x8fIWp5xj9E0OPMZ6Aj1n4kEfjVu/iNquTLkt+uxXpNue3G/CbtEijOmlRI+26pMOIdBqRXmN+k9ZijTaptyDNdssN9rwGR9Luzm9xIq0nlxudF2tseQ3mpFOb2751pg5DaVvflmh0ZWr8GccKMYSXFjzMcMxsBaGNLSxtYGQJXVMBVUMc1YOiLkVJn3rUmKpuQlU3o+iYC+paUfSsBbUtBbQsqKpG1APagntUsF0FnzdDNWOKtiX1fxF6hUsFRK8Ni98QFr82NG51SJx0YAzHJ5zpHgAnbxx3p9m6CTicgosvfIJXJk56+9Nc/IScXGHnA3MP5H1jWKUu0buKOraG1SDJnti7o1FKtIxFrxJnFTBoFRx2iQgjW4iRzmCkMBgZDGYhg1XGYBeKiOWJcnJFmEUsdgVbrIYlVslklokwSznCpVKsCkl2tYxkpRinlMmqZnHKRFgFDFoRm94iwhhZLTsgxe7fIP5WZdsHs4MLtupThgpvdsm82SXVt1NiaBdnZJfEyDbxgfWcN7KssY3Sw3vl+vbLvdkkPr591ZCONPfRVwv9J/k9DsuvA8ig31y13LuXWErG0ufbuXx8qgDptSEjV2a6repfIe8uUqORdhaZZ5Ebjtww5IUj/xzyzqPg0soFYM6/1Ze8y8i+gPRYZP6LMCt2Jd4q4zxSopB3ASmReBGB5HNIjUJKOFJDkRmOrBhkxSA3FiUXUXcLXZ9zrhIxmYKZdMznYqkA3CLwS8GvWM+v2b/coMRt1+f22pF+O9Kuz689zGtQIV1mpBTzGZhNwnwCuIlYfI6FRCwlYzkZi9lYKN/Lb1KfzBXtfo632cIfy+SnynZNlm0bKVrTm4mmRFT8jeJfUfQLcr9G7j0Uf4vy71H3Mxp/R/vf6PwHrxPRm4TBVxhNw2gGhtPR9wo9SWhPQuszVP2ElzdwOxh+VjhjjtunGI/j8PQ8XsYiNRogo+Fk2J8MOZNO7ZkC1vg/+PgXSBLeJ2I+F0uV65cb1Ui7LWk5tlyvQpp2/S/CuSzMJGPqOUb+wPAjvHuBuTxMZYM0HuA2a5JuK36HLbfLbKnVYOnzTtimSTp1SKc+6TBYrJFfrFLkVmuTekt+owOvwZHb5MxvdSFN9vwm6+VmE26z5qc6hU81O6bL14zmCg5nK841O2R8vyfIFBFmCLWErS5sbGHvCAcHHHeAlS0+D1hV1oeSDg7qUA/rUZWN6OomdA1TIW0ziq4FVdeKom1J1TAXVDGkKWhRdivjyyPYoUrZq0lVM6boWAkZOVL/cxz9vBOGnF8bHCsXHCsTGC3ld5bjESzs4k1zOIVjLixrZyEbVzh5Cp4OZPmGsL0CWaf96Da+go4nccIDlu4o/M68+LBwJwuza6S6ZFiTO9f3yHJaOYx2CXYDm94myW5kM0sZYnkMViZTJJ/BqmCIVTDEChmsDAYzk8XIFRUpYLHyRURymIx0Jj2VJZIqysqm0YrY4sUiEsUMTrmIeCmTVcygVXJEeiXFJ9avbhMT6t22atFGbeGExrjxvt4j60bXiw9sYPduZvXtEhvdKzWxQ2Z8veSoFGtsy+qJvetH5Fe/2SQ+Ji87ZC639I/uTNcxXqclv8uHvDk1U0afeInFV+CmYaEAvHzMlIAMupOx+Ik2vew/kX4bL+KQFom0s8iKQE44ciOQF43ceORdRtGNlRrM5yro5+/AzDikxSArDjkXkBOHrBhkxa78zYxCcgReRiA1CsnnkBiC1FDkRyMnCjlRyItBcTyqr6H1W/T+huEnmHyJD2lYyAI3F9wCLJeAVG4kNYr8RkVumya/14oMu5Be26VG7eV6FdKuxy/AQho+Ja4gXErAYhIWX2HhFRZywK1SWKo58jaLNvYKCwXr+JVqvBrtpVqNhZrDH8u3jebSu5PR/Ax1j1DxI2p+RN3PaPwFzb+h7U90fJ7gkoCe53iTgKFkjKRhNAODKehLQm8S+hPR+Ri59/B1IHwsEGSF216UJxfwPBYJ5/AqHCBTt3jvr5OZ6+RjLOl1/FSwbS4R5DnIS0z8hal8kGE7MvUd+fAHmQgZa9lIKrGQt3Ic/Yxw8hmGf8PwI0ynYKFAYDJTkLQcXW7VIV3W/A7b+TZDXqsBadUibZqkVZU0KC6W75wt3DqRJblQeYg0my03HOfWnyAtLqTNhdtsQ9rsl2o15hq//NTEHi/DWNHGDxX6M2V2pNcn/3f5eC8EWsHPAKe04WgKOwc4OsHhBOwcYWULI0toG+GILhQ1cUBTSFFH+KihiLoJU8NUSMec+hmhlgVFw1ToqIGQggZ11xGBL49guwpltwZN1YiibUn9X4Re4VJnotaciZL1j5byi5L0OSfmEco+6S9id4ph7SxkZMs2shMydxC0dRNy8Wa4+7NdfVknPYQMfQVc3ARc3GHqiJc3tHOPiLaxKTNyUgOr2ZNbVg+t4fStYvZJsXslmH1SnNcckXpxqXI2p4ApUsFkN7IkGlkSpUxWOoOWyWJkshiZLGYmi5nKZL5iMV+wWM9FWak04XyWeD5LMo8hXiwiUcIQKWcyGiXZnWza2FrpLln2hMp2cspwwupg1xG5/kOrPm5eNbGJM7CV1buDNbxbamKHzOSGVZOykiNbvhjfs250j1zfFs7E4TXDtl/wEvSXuqyX2wxJhxvptJ8uxPtXWE4GNxW8InAL8CEXZMiXTF7srj38+008Oo+Ei0iLQVo0ss4h+xxyo5B3HrmXkHsFRdf/i/A/JdDsC3j5OQPi/IrAkito+wlDz+nND1B8BcmRSApHUhiSQpESjtxoZJ1DbhTyo1F4HmWX0XAHHT/izZ+YeIYPLzGXgaUccAvBLwGpXEtqDiw3H+a3aZHeY2TkNBk6ze2w4Dcqk0Z5XjYWUzCfgMXnWEr4H4QvsZgDUqc0V64wloapNHCLvyRV2ss1pqTOjDQakzqN+fIdE9noeYG2p2j8FU2/oeV3tP2F9r/R8QivH+H1I/Q+x5un6HuGwSSMpmI8DaMpGHqBvgQMJ2IgCeU/4F4A/C1xzg7f+CPxIp7H4lkYEgIB7sRl3vu7Sx9/4n34nkxeIT3OvFy5yT9BnmLyHyw2riOfIhff/7E8nUAW73wcNyKVjIU8zOViqQBzWZhNwVTCCsL5LCwUMKZzWKTlKOn8irRb8DtsFz439bZrkdajpHrHQjZnJBGv/8JIhsxyrQ7pOkGaT/IanEiHK2k/vlSrtVyvNVmwbqIYI2UYKMRkrRb/dThpv176XDPWE6csEWAj4KoOZw142cDGCo5OcHSErR0srPGVKUVDH4qaOKCKvao0BQ36YV2mqqGwugld20zw84lUw1xQw1RIWZ++glCJskOVsluDpmIILQvKfxB+Po76R672Oyftc07M+6yoRyjbNYDt4MGycqKb2gppmTC0TCk6lgJm9gK2bkInTjMcT9GOn4T2aZq7O/vkCeja4G7E3kRV8Vpx6qiM5Mg60bENEmPrxAfl2MMy7BFZ0RFZTp8Es0VCsprNKmMwakVYrznSPZIydeKcLBYtQ4SeIUJPYzHSWIxUFiOZzXjJFnnBYqYxaLkcTpaIWBaDVSAiVsIQqWAw2iRE34jT+2XZTasYEzr7iZ/VW2vF14ekhvZyZvasfrdz1eB20f7t7IFtYiNbV41vkH63Vm5gm9zwLrmRXTKD2yXH1dYPnlhPEgxI93HSrE86XJebzd9m40MySBqWUrBcBF4ePuSADISQqbjiDJkrofgmEP9cQHIsUqORHonsaOTGIu8Cci4j8wryr/xXYPYFZH0+gsYhJRop0UiJREoEMiNRdQvDz8AvluQWre1/gsJrSIpAUjiSzyH1HF6FIussciKRF4WCWBRfQOUNND1Ax0MM/4V3T/EpBUvZWM7HcjFIBYdU7eQ3qZA2HdJ7jIx4kbEAXp8Tv1GRlIGbhsVXWEoE9xl4z8FNxMJLLCRjMRmL+SBNKu8KtvS+wHQmFkt2kRrd5WprUmdNmqxJsxG/9vDHQunhNPQk/U8e7xN0P8Hrpys/up/j9TP0PEP/CwymYCQNY2kYS8PQS4wkYzwNdb/jmyAE2eCCG34IQ9JlJMTgaSie+QHk7RkydWH54w9k/hH5+ID0nlouEv+UiPdPwC2TJ+9jyeLDiclvPkxeJbPxZCqIVLEW/i3MLOTgUxqmkzDyF4YfgV/ImM8Xmi2QJg1HSI8Ft9mMdNrxWvVJiyapP7Rcsn42De+eYvhPDPyKmbKjvCYz0u7Gb/HgN7mRFrvleq25dUJpdQAAIABJREFUsm0fikRHsjGRv3q0eN9QmeZ8t8fHzuDaNKszTvBwhLs9XM3gpgsfQ5wyh40xHB1hbw/rYzAxo+gYUJQ1oaBC2acksEORskdF6KAW86geQ9WIrmFC1Taj6JgLapgLqpvQPyPcrUzddkRwlyptnxZD3YSqa00zdWbYnmae8BM+FSzqe1YmMGad3zlp37OSnmFi7kEsJ2/GMRea8TFBPTPKUT0hFT0BNSPoWcPKiX7cVfj4SeoxJ0EVF8pJF46zrZCeLfzd5L4/LJwpLtglIz28QWxgrejYBomRdZwBWfb4GolROYl+SVaHlHgdm1HBoLaIMIakpAblZBulRPNFqZksRoYIPVWElipCS2PRU9n0VDY9VYSaxqRmckTSWIw0BqOAxSoTYVUxGK1ioiOy7IE1Yo1yzBGtPdzTRm+tDg4pyo5uY47Iyw7LSw3vFh/aITa4lTO0WXJ4k8zoerl++TWDu6VGdkmN7JIa19j42u4L3mM90mZPmjVJm8NSrc5YKmZSQTKwlIzlAixkY75IkAyeJWORjx8i3A1XPZh/xOFlNJIjkRqFzBjkxiP3ErIvIf3f3e8zwv8I/HwVkRqN1ChkxaLoMuq/wfAzzOeCVFOWikT7n1GLbyE5Ei8jkByBlyHICUfeWeT9uxmWXkHdXbT+gP4fMfYXPiRhIRO8fHCLwCsDv2LNcqMGaTcgPTZkyIc3Ec4bOc1r3LWYjsVXWHqBpQRwn4H7DNwkLLzE/CtwU7GYB169Uk+qSM3vGEzBZP6G2UqtxSr9pRp9Uq/Pb9Dk1cjPFkuOZ2EgFT3P0ZuAnkT0JOJ1Arqfr8SCtj1GxxO8fobeJPQnYzgNE1mYypZ4m4WJLLzLRe3fuBuEUDtc88bvUXh5GQmxeB6C534AGTTlvnEhb2+QhUe8oWujuUcnEkDSMJ4NMuBHPiS/f//8PfcWn4SQSX/SEUaqWIt5mM8DrwiLeZjPwMeXGHuE4UcgpRJzeZT54rWk7jDps15oMCKddqRDn9+ovFCy6f0rjPyFkd/x/gnmX4K0mi83H+c1uS03ey43u/PqTOfL9n7MF54swHQha65af6b65HSd/1zP2eocvQh/eDrByR5uzjhtj5M6cFaDqwEcTeHgAFtbWFrC0FhAQ0dASVVgn5LAnkOUrQoCOw9T96vTlHRoRw2E1IwoGibQMhX4D8IDmozPCHer0eW12NoWwgZ2bEs3MUcfCddgic8fhKHxm32iZT3PSZ4KF3UJYh73pJucoGpbQMUASjo0JR1BVUPoWlEsTwgddxW2Ock45iR4yAEuDhxHK0E9JyFbW+ErB2hP2ZQmWZnBDeI9csyxTVKj6yT7Zdnj61aNykkMSLF7ZCWbOcI1DGqbCGNESmpktWyTFDuPLZjJYmaIMP5FKJTBoqaLCKYzKK+YAumi1GSmUBqDViDKLmexaxiMVhFWnwR9avsXI/s3jusrDJkd7FBdN6wgMbtbslOe82a/xLC8+NhuybEdksNbpIc2yQxs+mLkyMZhBenR3ZKje1eNamxos5T69FCNNBwjTRqkxXahQn04GXMpIBngvgQvH7MZWC6XI4MxSwOh967C3xEX3SV+jUVSNJIikRK5gjDnItIvIfnfEM7/bobxKys1BilRyIpD+U20fI/e3zGcgMlUTGeAVDH4lfu6/1mTcR7PgvEiDKnnkB2GvLMojER+NApiUXoJNXfQ/B16vsXwL3ifgPk0LOWCW4DFEnDLxLh1mqTNgHQfI/2ei2/P8Se8uA1fziZhMQmLSeA9B/cZuM/BTcLCK8wlYzkNC7mYrz5Q9wQ599DyFP1pnNECpY9Vip8qFeeqDs1V7psr2/C+COPZGEhDbxJ6k/DmBXqT0JOIrgR0PEP7UzT8iZZH6HiC7gT0vMJAGiayMZ2/abpk/VQ+3hWi+hFu+yPYFrd98XsMXl39H4SzPT5k8iwZ8yQVu2deYu4FuClYeoWuNofZ99GE94A7+8381G3+x6tkOmJuxJ00fG4sBL8EHwrwIRtLr7DwC8Zy8LEUU/kgtWzSfJg06JNeO26HBanVmXiFyUS8+wMTv2D0EXqfYKH4y+U2S9J4ijQEkUZnbpXC20IM5WG0YMd4tcVUvfV4ldmHZvtPHd5FCVrxfvCwhb0729lZ4JQ9fKzhboTjWrDRgY0JxcEB1pYw0IemBu2oCu3AYew4iM37IXeItu4ItmpgtzYUDKBiIqRuTlO3pBhoS+voSitriytoMHeoUnaqCcjrUpSN6NoWMDlBPe7BcvJnu4eJ+0SvCTi/OeD85sDoVf7nxD3CaC5+ArZuMLSFlqmQqj79oA71sDblqAF0zAXN7OiWJ+iW9gzTY4KbHGFtQTtuIbLXCep2uKiKpDVCKQxGv4TEkJTUqKzM+GqZ8fVSo2s5/XLCPTK0NvFVzWLsNnHhN2tEBzdJda+VrBNjldBoOUxGJvO/Z9FkEXqqCD2dSU9n0NJYjDQ2K40tliEiUswQqWOwWxisdxzhwd0yQ1YKI7YHBpRXj8tLTCrK9CqIDu6gj8uLvz0gOy6/ZnC7ZP9m9uh2sck90iO7pPoVxKflpUf3Sg0Z73xnsoXcM3rX5UWajEirKbds71Qqpj+XH7OxlIkPySB1x8lkeFeFQYTHZneTraeP4f4lZMUhPQavziE5EinnkX4BafFIiUfh1ZVvv4IrlMx4pMQgPQ7pF5BzCdkXUP8Dxl/i7SsMPcHwPxh/Cn7Sqo9FmKzCQkdEVdrqH8ORHMasvID6hN0l95Efi8IY5MUgOx55V1B8Hf0PMPErZp9hKQXLWVjOA78Y/HKphUpl0m5Geu3JgCsZ9SLdFvP5QjNPsZiEhUTMJ+BTIj4lYv4FFpKxlIpPL0DqxfrSkXEfmTeR/zUq/0ZdGvqzMFGAj0WYKaDO5jE/5lOm8jCejaEMDGdiJAuDmehNQVcimp+g6RGqH6LmVzQ8QkcSelPRn46RLMpk/hf8EsVPRQfGK1HyHLd9qJHH8HUg/ozHy4v45ywe+eKJN0BGPUi3w3KFyqd0zLzEQjL46SCZIJOXyewdMv8Nf/ommb5MZi+Q6RAy4kbKwM3BUjaWCvAxD5MZmE7GzBN8yGDMF0p8yMFS5WbSqkNaTUi38adK+fnM9aNPMfEP3v+N8T8x8Bgjr7BcqU/az5BWT1JnPVdyYDyPNporOFEsP11hOF55bLjEZLrJYa7LqybN8FaMqKcTXBzg4M444SLg7ghPa7gbw0EXxw1wwkLA1BLGZtAzoqrqiR7SYG9XYm44SFurQF2zW2zTfuaXSoJ7VWkH1IQVNcWO6Egc1RXTM6JqG9GO6gnt1aRsV8EOVRzSZqgYi351DBYuDAcf1skgjsdZaf/z64PivwyK/zIoZs2ZSEnPcOZ/EGqYUJV1GAe1aIe1KUf0BbTNKIa2dDM7uokN1ciCstkO5mYMKzOmvCM0HXBRE8/X018w6Xn/H2F3+Rb1/vUN/w0MwzjMwNAIJshWFNjSIGFs1G23bnNjYGAhKnYHtliAgCgGrYDA0N0dEiIgOUF3TX3uB/o7z+u67vu87uNYD+YfeB3rO2t91lqsSdlKkwpV6NUaio2arNbJLK6mAledWaeiXqek0KDCbNFSaJuh/AthBpX2PyKk/0YYy5CPl5fPpjPKmIrfFVkcZVqntU7Pblv+DvM22yl8I6VOU5UWc+V2g0l8Y6VOEw2+4eR2fdU2PRZ3LqvbQJVvOLl5vnKvkTp3vmb7GqPO9frk1foh3jlSu5dUrhrLUB6IxXgcxAkYZ2M8AT2xID8cCe9Ywiec2olrB6ReXUb0axS/Qv4zZD5BxkOkPESiO2JuIOLy793+ybeQeAOxV5B2HxVvpL4H0sp9UPMWvEj0xYH/Ba2B4ASi7SPGgtGfhLEyLTLgIWl1insM9gWMfTUS1e8Yyv+r/LVU3EUk30DqHaTfQdkzVD7DzzfoDsNwNMbYGEuCJBukGBOFtqR2FWnYQpodCe8Iadw4kcEYCf8fEY7GghTSKsMR+QBf3ZH0CJl+yAnFj69oiUNnIroT0JeIvmR0J4OXBH4COhLBT0R7AppiUPMZFUEo+4ACHxT6oeQDqsNR/xXNbPCS0ZupPZFlOpazoKuAkhaIBwelr2zDizP4eAuxdymfLyL4BEKOAKTKfjhpRmcY+r9gjI2JOJBMkFIT0vOY8G+SVjdh20nScZJ0nyDcA5KGfyRxICmQZPx+PjuYjI5I8CNB4nQlqbNGUqaKiqxI7TpSu46UmnXFgvcJnYHoeo+BIPAD0RCE/pTppPQY+XaRlG7ry5zZloCWJHRmW/QVb+orcewtduwu3CVuPtNddfjt45l7d+CfndixX37HAex2xP6dOLAJjquxazn+XYv9m7FjF2XTNixbC9NFmGkOjfky6kYsdWOtmfPk55gy/rRRMl3EslisaLFY0c5BefEKDevlsFqO+UsxdzH+sIfRYrkFK5SXbpi8epf0VifGvy4qB89pHrs6xfX2LLe7887emXv2xvRTV9SPnGfsPSG9bb/Uym2UhSsp1ktkzRbKWSyhWC+nLForu3yT3N+bacvXyzislpqzQWr56klr1jAstkuv2C19fSXto96kMDrNhyUTwKKEsajxSrRcJXqNskKTihJPRaVRVblJVblVk8nRUuBOVf6prVbGYv1fEP6q1sQy5Nny8gl0+Wx5+QolhUZV5Xot+tAqk1GnpZ1bTNvtpnINWbz5LI6VGseYyTdW4hmp8gw0OXPVOXOUefOU+QYqHQZTfhqqdRho8M1mtG0w79xsSF5uFA7fJa3XRLXrhtMxGgPCBmFjPBaDCehNA2k9TjgHkz/g0z0keqM4CN/D8CMEtYGoCkC5P0p8kfUSSQ8Qcxtx15B0C2nuSL6NtHuo9qd2snW74mbWB6I5DF2x6GGjMwp90eiLBjcQPf4QpYCUGZK2s6TrZuMXg7QbEMTpEY4j6TvWk2mb/gS/Tl8kXUTpY/mWMHTFYiwFE6kYTsRQAsbTIS6AoNia1PxNvq8jjTsJ9whp2iLMUvrVoP8/EE7EQBALUSJG0pHxGgFXEXYD0XeQ9BwJ3ij5iKrQ360/fgw64tGVDH4yepIZPcnoSgE3EY0xqA5H2Qfkv0HuK+R4osAXZZ9QE47GaPCS0ZetPppuMFGwqCNvcqwfbu7DtR3wPIfA2/hyCcGnEHgYIU7AMBvdYegLgzAWgngMx0GSpUK+LyHVOwWla4fLlk18X0WaNpHGzaR2G6neJkozk+RrD+ZgJA0kE8I4dH5BVyxIkoYkRUOQOZVULCTfN5CiRcNxNM5HtPlhMASdb9EThJZA1AZiLNeBVFwjFUdGs63bE8BJQnfO4oEix+5iR17xhpFKZ3HjGeHPM4WxK2+6YfcubN8nvekAa68T9u7Dvl3Yvxl718NpI1x24vx+3DiLS6dw1Akbt8J+Of60hZ6JlPZcqpY+tAwx01zmD1vKnIXQXwiTv7BghazlUlgukzZdJmf01yTDJfKmy+hL1iqu2qKxcS91xxHF/WfUjlzSdLmpc+6e/oX7Rufv/Xn+tu7pa1OcLyjsc6H9c0BmxVZpu+XSZvZSJnY000UUKwcZu1WUxeuoi9bK2q+QWbAU85ZL2a+gLV7NsN1CXb2bcmGDvI8h/ZO87DMV6ktlqo+S7HsmJZwhm8ig5TGYpYpKjapKbVqqHdrKfC1FrjarSUutQlk5i0b/nxDGylOj5eViGfJxDEaKPD2LLlemSK/XUK6fpzax1WZs719tq/TbrLV4RkocQybfSoNnzuKaKHEMlDhz1bn66ry5qjwDFa6hSue8qY3zNPjzNDus/2jZYsnfbiJ6skY88Zh0viRNu0dyMBoNEg0SBwEb/fEY/6ZPmlxJvWNDAvjZ4KeiKx4D0bLNUWiKRMMX1H9GbQi+fUTRG+R6IfkO4q4j4SbS7qHgGeo+4Gcwvr1BYxDqPqAxGNwI9LExnoqxBPDD0PcJQ1EYSqQPpJiS2oMTWQuLnoMXjMGyTWT4Cul0/f51bvI9JFxGvjsa/NQmCnUkpQakYj4pnjeRpT6cipF0jGdDXGxBqhaRqr9FdZsJ5wBp2iLJUhF8wfiX/0Y4GoHxqN8ISTraoxF6F89PI+ASvtxA7ENEPkLmK+T7oOoD6kPRFgleHDqT0ZWGwYy5AxkzetOY3GQ0sVEdhqIA5Hgj/RlSPZDxErm+KP2Ems9oiUdXlvRA+ixB8Yr2LN2wp7i8E1d3w/sCAm8j9CyCjiHwIEIOSGHoM0YjIGGDJGMiEYPxGEsDKTKeyNMYzVUeK9YW1ZqIvy8UVi4nNf+Qn0dJ0xnSvLOrRJuXACEbJBIjERhJgSQdI8kYz5Mm30xJme1QnB73Hbj+4PpjNAyd/uB9QnMwmr5AUrqVVJ0nRQuGM6Z1pU8ZLPh7pORkT8HpzuLdnTUrRA2nxM1n6jM2hLyccv8STh3Frr3454DMkYM47IQjjji4A8e249IBPD4Nv6sIf4jPTxH2HO+ewuMOLp3Cjg1YaAldY0w3gJYhbbI5bYotptlj3iJYLKUucmAsXKZms1zdYrmm+TJlm1WTHDbJrt4hs+0gfc8JppOb+tEr2qfv6Fx8aHjpofGF+/Mv3Zlz9sb0YxdU9p+ib3eirdwmZ7uMYmIrbWRNNbGjmS2WtV5KWbBCdsEyWTMHaePF0n8uhMVSqu1qhcUbZdfsppzYNumpBf2dAsVHaZKvMt1LaZKXgqwPgxIgTw1VoEWxGJXKjJapap0z1PjaDN5khTZttWp1lRy6/P+E8Cud+pVOjWMwUlisNHl6Bo1SzKTWaSg0288a3bqgb4P5T+sprWbqPBOV9vkKHRbqPEsVrqly+zwWZ44qV1+dZ6DGM1LlzFftmjulcZ4G33Byl51+6zbrrl3mg9cXCvvvkt5npOOoqExzOBriKJA4COPQxwZp2klaLpGanb3ZmqRiWn8aRpJBkufyE8CNQzsbTTH4GYX6CNSFoTYYle9Q8Aql3vjxET8+ou4dqnxR/BKNQajxR2MgOr6iKwY9X9EdBW4YRiLR4IO2IPTFgRQtIEULuBHojoWo3JH03iXClx0l/yQ/QcET9MdgPFtHVGYmLrci5fakxJ4UWUsK55GCqaRARVxiTKrsyTcHUe060raXNK6XZDEF/0mDo+EY/vzfCIVsSLJQHQjPs3B3hs85hFxF9D1E3EXiI6Q/Q4kvvgehNQJcNrpT0JeFsZwFw1lzu9OVeSloZqP6MwrfItsLyY+R+BCJD5H2DDneKPmAuki0JaErjTVW/PePJL03t3BhG27shc9lhN3F5/MIccGngwjeL4vRSIxHQRgLQRzGkzGejvFMCLI1xb92iVdoSKqNJyqsx0uWke+7Cf8M6b5P+m6Mtf87VjqHpIKwIUrEcBZGCqf0ZEFQyhIVThlOVOcHotETXe/R+Q6DweC+R9NHtH3GYLIFqdgtqdzUnYKuNNZQ/uKJ8mPDJRe7Ck4OVO+XcHcN1R9sK9qY8mlG6DMEv2Q9uIITTnA7hdMHcdIJRx1xcAdO78EDFwTeQeJzVL5DbQh+RKEuRurbV5WMj6z3d3D7CBwWw9xYbpYeS89QRd+GYrIINoux5C/WcgcsXSqzaJncgmUMq+Wy9uukV+yQ2rgfO4/S9rqyDl/UOHF9ipu73pUn8688Nr34wPiK+7xzN3SPX1Tbf0pxx0H6ym1yC5bKzLeGoQXVyJpqYidrtljWZIm0ySLKvIWUufYyZlYwXE43W89ctlF2wy6pfXtkby+S81eXfk+nvWPS/ZTonizaCwXqSybVlzXpvYpCJlOubpoaV1edq83gaclzp6vUTVbJY/6Pn6NfGXK/EKaxFDLk5bNolFIWtWGaUsdq4741xjz7WY0GSm2GSnxTNb6ZCtdUmWOj2mamzDFQap+twputyp2nypmvyjVV58/TapqvyZ+v2Wk3u3Wr1eBui+7T88fbz4s6L5LOE6R25XAqfTju97HOsQSIf54gPbdI+w5StYCU2YxkQJwPkms/loPBLPSkgZeAFjaavqIhCo2R4LDREo3uBIWB5Omtoah+jVo/NAXg+zvUBYDzBd2xaAnFjwC0hIAXAW4oWj5hiI3RRIwlgZRYkGLLrmSQ6n9J62UiejvBu/49UqcjCuSblrBSU1JsLC42k5QsEJXak/IlpGIRqbAl5VbiYn3yzZJU2QuqV5LmneT7KlGa9EQ4xj7/nwgFsRCyIclAnjfuH8b1Q3h5Fu8vIeouom4j3h0pj1Dkje9BaP81S5SKoWzmeK71QPacrnQKJwkNbFSFI+8dMryR+Bjs+4hxR9wDJHkg8zVKgvA9GpwU9OYuKo7U9LiA8ztw5yD8riHiAQLPwf8IvHfh9Xag9wv6vqAvCsPxGE3GWAZEWSB5dJInTQqmkjIr8m2FoGL9WPk6yfd/SMs+0nKCdN4kfbfJz60kCyQNkhL9wdrtY81OE3VryQ+78RT5zo/gv0GLJzo/oes9+O/BDULjJ/TEqpKSQ6R4Y38uuPHozZw7XLRloPRwX5lTf+WBgcoDvaX7ChNM0sKmJL6TzgikpX9ihD6B11W8voHbrrhxAm5OOLELbo54dQaxD1Hgg/ZIdMehP5nRlzalN0OPm6pbFYF0H1x2guMq/G2Ovxdi8xbs24uj+3DKEcec4LQPO3Zh9SYsWY+/NmOdI+0fZ8U9J5i/9qy53Jx+4YH+9Wdm155aXHpocsXd8NwN3eMXNQ+4snYeYqzaPmnBUpk/raSMzGhGlnJ/2sga2VGM7Cj6dtL6NrJ/2MpaW8Jw1SSLLcprN1M378aOA7i2UubdNOn3NOo7Jv2NMsNLhf6SJfeSSfVj0t6zGF9plJJpaq16mm3TGO3atI6ZSg3TFItZsv8Twmgl+leGHFtePl2BmS4vl02nVGvSefpafRssefaz2g0122crtesr8k3Vuqw0OSZKbTaq7eYqXEMVzhxVrp4KZ64K11iNa67ZZajVZq7RYazOtZ7WttlE4Gjd4/yH4MdJCXcH4RwjP09KataPFqKDjT42SDbErZdI10nSZEFaHEjFFnHJdFIFUmRLChVF+RjJRU86OpLQFoc2Ntpi8TMa7fHoT5fqjqfU+KPYA9Wv0OCLH29+tyXafx2T+ID2cHA+4+cHDCVCkoZRNnrYIIVWpOZkTyZIsenYj33ikddk1FdY40jy55Iyrb4SWVI0j5TMJWUGokoDUbkhKbMiZfakbImwcBapMiPV9qLqFeLGbeJqh4lkjIb8fyMUsSHMQKoHru3D1YN46oo35xBxG5G3wL6N5Aco9MKPYPBi0BGP3hT54exZQ7kGvZka3GT8jEddDMrCkPcW6V5I8kDcA8S4I/Ye4h8i+Tly/VEWivp4tKUYpr7DfRdc2o2HxxFwC7HPpL66I8AVz3fh0QaAH46uCAzFYSINw8noZmMoESQXkuy5JNeGFK8l1XvJdyfR990TNRvGa1eSmvXihlOk7c542bruKAwlQtS8aXTIhwz7kv47hHtgJIbR9hJdfmj3Ae8TOj+i7Q144WgMxlCSMam5Jsj5uyURg7k6E6Urh0v28PI3d1WsGqzb3JK+Jctnhc8jvPdAegjKY1WyApDsg2RvhN6D3228uiblfgYXnXD1IPwvINUDlf5oj8RgMkOcb0yK7UjJ4rFCE07SpG9hyPyAgBu4fQR3z+K1B0LfIfYjkt/hgx88X+D6DTgdxYbdWLkD6xxp244o7XVlHTyveuzqZNfb0y49mnfzhcWNZ1ZXHptfvffnfyHcdZC1ahtzwVKKkSUMTeUMLaiGVpR51jKzbaRmW8vo2VBm29BsrGC0jmm1U33TVuoWR2w9jEvrZD7MkvajU/yVaP7qjNfqTE8WzUee+o4uF0SnB1Flcqaq/Zyt3TJNsV2b1qWr1DKDVaok8z8hZKswo5m0ODo9lSGfRZfLZcjWT1fqN9Md2GTdYqbdpqfcM0eVo6/IN1XrsdH6jdBSlWekyputypml3K6vzDFR41hO7jbW4lhrdhirtllqtm4wJPttew7NFNc4E+4y0nyEtN4lHecF9bOaf9VFy+aS/nvD9Wu+p0Fc9ae4YKegxExQg7EyS0n+dHG+iiAXQ9nozUBnKjpS0JmMFjY60zCcja54/PiAel80vkHtK7QFoS0IrYH4/gY1b9AeDl4Evr8F57PMQBK6wyGIhzAH4nRzUnaXfNcnuRhv2DQ28JyMvifcS6R44UjulP5KXZLFJPksUsoSlsmPFCuMFM4QFZmTkiWCAl1SZUKqF4lrVgrrNwkqF40mYDT4t8D/N0JBOpIe4/IeXDko/fAUvM4g/AYib4J9G0n3UeSFhlDwY9AVj75kteEsw4HsWV3plJZE1LNRE4WSUOT6I90LKc+R8Aix7oi5C/Z9JDxB5msUfUJNLOridGO8cfsorjjisSs+uiPRc1J58MyER5P8nfFsG9AVju4I9LExlIj+ePSwMZo8leTakLzNokIbUm5PKreT8nWC4mkTJUxRmZmwcBX56UgqVg6zpUWfMRaG8XQt0ussHH4rGH0v6X8lqd7X5IXe1+gLRN1H9LzDUAg479AXoUPKdo/nr6xPAKcE/ZVO3YW7xkt2k+9O/aV7k0NsLl+S2eaIazfx1hPpYfgWhZpwVAShNBD5Qch9g8RXeHcVj47iqQveXkbCU9R8Aica3XEYTlcT55uQIlthnuVw+uyelMmNX1Afjrpg1Aaj6Su1O2XOQLblQLZ1d/bfDTGzioOkAp/A+TDW7MHmI9RtztKOp1Sd3LRPXNU5e2fexQfzLz8yufzI5NJD4wt39c7cmO58Xnn38Ukb91IdNslaLZM2tpeebSalbyGtbyGtay6lY4aZltCzkZltJzt9OZauZ+7eorRpJ2XlQcrOo7RLOyn3F8GPCl/WJG9NTU9NVS+lST4MGT+GnL+Ckr+C3GcluYqZalw9da42o3u6WudM7WoWI0OekSJPj5WnfmVQvzJ4wNUpAAAgAElEQVQp0QxKPJ2aQKOm0mghNJkAFiVGlZlHp1XSqE1ztXo3WQ3+pdNkwKjTpbbNVeYYqHJMlLnWqq02TI41s8NicofhNM4s9fZZClwDRa7J5HbzGT2GavVWf7Sb6fbZTOVssuzdv5F30oaU7xjh7CdNe0nLAcK7T/h3BLnojAapP0b6z3QV2FQGoz4E7ZEYSlMhtcvE5cslpVMlBSak2JYUzhrNxEAG+jPQkzy1PxmjGSCFivxIfPNGgx8afFDvjea3aH6LOl/88EdLCJpDUfMBtR8xEISBBAhyQbIWS5LMx7JAvluQzjeCyumkfDNpOj0x5jkx5Cn4ZirIASmdS4rkST5LkqssypUR5UGSD1KgSQoMSQZI5UJSu3OibhGp1SNprOEQjIZgNByDQRgMxFgYRiMwEonROIjT0ZcJ/0u47IQrx3HHGT4ulA8XEXwbX24g5SnK3+JHGFqj0ZGAnhT0pIKXgHY2Gr+iLgwVn1Dgj2wvpLxE3AOw7yPmLmJvgX0XyY+R44lCP9R+QWOsfMQDXNqNWwfwyg2fH6L2K3qLjFpStfMCEHoL6PqCnkgMsDGUiMF4DCRgIk2HFFhJcpcI82aLiwxJ6WpS+vdEscZYEVVcYiwoWEW+bxfk2/dHYiwMQ6EYTGaQ1m1k4LFo2JuMeJFm15a36PRB93v8fAeuD3qDwA9Df5yUuGjxQM7fvHSbwW8Oo7U7+8q2DZT925K5I9DDwHETVi/Hnn2KVy/B9znSg1Edhfov+BGG6nB8+4yqYBT5I/wOnrvghSs+3kDKC9R8QmsEeNHoScRQmtZwht5wht5Q+qyB9Fn9yYzeFIXuZI2e1D+G86yE31ZLareKa7YKanb25dm3Jc9N+6h54wr2HJXe5cLc5ULf66p+8NyUE1d13O4a/EJ48cH8Cw8Mztya6nJN47Cb4s6jtA2ONIdNstZLKSYLZeZaUgysKAZWFD1LaV1zKR0rqT9sKXPsqXNXY/Um+r87FLbvkV17GHtOyF/cS7m/AgFK0r4sOU8VJU91FS8VuidD2otB9VVSeseU+6wkV6St2KKj2jlDtWeGOk9bo06JmclgpTLk2QzaV4ZclIJcNFMuXp4WT5NLkaeHM2RDleQSlRWKaPRqlny7hd6w41+Df+k0GzLr9Sa1z1NpN1LhmqpwrVU5NgocaybfXJNvMPV/RdhmNr3bQLXe6g+uud6g3XTuZqu+A5u5x61JybYJriNp/Jf83Ev4d0nvQ1IhNZAM0uJGek9x0uZ/C0T1B9S8RXsUREVW5Mcm8nMpqbIjpcaSEvWJPIzlY6IYE8UaQykYTQXJl+2NRq0P6n1Q742fvmh+iTZfcN6g8yP6vzC6Q6VbA9DyDv3h6EnAUDYkeQtJ3gJBESaqjUnjo/EqPVK+mTSdnBjzFAx7iaqtBDkQFemQQhopYIhzaMIc/EaYr07y9URpICVmpG67sGGxuHyygC09GIiBTxgJw1AwRgMhCMP4F4x8hSAeJANNCfA8j7MHcP4obh2G93Gp924Iuo7IW0j1QPlbfA9BcwS4seDFgxuP1hg0RaIuDOWBKHmLPB9kvkKqB9j3EXsP0Xd+I0z9D8Kaz6iJQuAdXNyFm07wuoCox6j9CnHV8tFSG07K1OowoDMCPV8x+OsPcSJzPElZlKlLCuaLs+aMZUGQA1JoTYptRUXK4wUQFhiKizaQ8o3DqYadoRgMxkA4+uIxUWNHeC6S3ttkzJv03G7/PJPniy5/8N6B+xYdweiNxXg2RGWWgrKtY2VOwirXrnz7ttxl8Z8sXJ2wyAY21lixgr5urer50/B+iJSPqI1ASyQ4UWiPRlss+FFoCEX8Y7xyhecZhLsj2xPfAtAYhJbPaIsCNwYcNjriMZA6dThrriDHSJhnJiq0E5avJHXbSasz4Z4ibS6k9Yikduto6bKqOGPPp8rHzkrvdqHuPj5pr6vyofPaLtf1zrkbXHpofPGh4fn7c93c55y8qnr0ouIBV8Y/h+XW7ZZbsoFivZRiak/900bOyEbOyEbO0Jr6h5XMH1Yys+2oBosZNhuktu2gO+2R370fW49h35lJbkekb29F4AxZL2WZFwyat4qytyrjBZPyTJ7iraQUIE/9wqKlq8h911bomaXVN1OjXV2hWZWVy1BMl1eMYzCimPKRCvJfFX5352Pl5SKZctFK9Awmo5RG+66uyFs8b+ToisG/dNqMlZrmynPmq7YZK7Wbq/Bs1Dg2Su1WDL65Jm/elHZdtV8IeaZabWbT+fPUftjM5lnqDi2c3rXVesBpI9fZkuRtHGv7h9TuJD92iXjXSL8HqTcfLgDhXSftTtWf1So/4dtblHiiOgB89mRSt5E0OQpqHEbKZ4nKNEnZNFHx5IlCjBb83pFJcjDCRpM/fnjjuyea3qDNCx1vwPMD1xdd78B/D+47dAVijI3+NAznQJg7X5SpO5qHscrZpP7iRJURKd9Mmp3Hx1+IRn1J3SJRNibylEgBRZwHYQ6EORDlQpwHSZ6CJFdZkAxBrg6p2yKptx/KQn84+t+j7x2GQjEcgvGQ3w9HBTEQJ4FkIS8C991w6hDOHsMtZ7w+LvXeFYGX8PUO0jxQ6oeaT6gPRWMEfkbhRxS+h6I6ECXvUOCLHE+kP0fKEyQ9Qow7YtwRewexd5Dg/hthiS+qwlAcBL8rOL8Lt5zx5hoSXuFnPMi31eSbAym1HMufDn4EuqMxHI+J5MnCFD1Rqi7JnEpypoizMJaB0QyQXH1SZCUqUhAUMET5JqRyOyleMcTW7PiE3hD0R6InGWOls8n3FRMth8nIEzL0hBtrwvNDlz/6PqEzFO3B6GFDVDSHVP1N6vcJqo+0Z+2siTF5fR2bVsDQBH+Yw8hGbpEDa/06zVPOeH4byf748Rm8KPTEYiAefckYiAHnM1Ifw9MFr07jy33keKHcD3UBaAhEQxjqw/EjHM1R6EyQGczQE2XbSgqWkNI1kqrtpNGZcC+QzmvCjuuEe5z83Eu+bW5NsQ55rX7mIvYcx65j9H2nVQ6d13a5rnvO3eDig/nn7889fUfP5abO0YvMQ240x+Oym/fLrt5BXbRW1spBxmShjLEtxdiWYmIn+6e9nKGtrL4NxXAh3Wyp8uqt2LVH/sj+SfsOYtcJ7D8ne/oU9dIBBJnSvCfLPKdRfFis1+rMJyzKQybllTLrHV02jCUXLS9drErvnDO1W0ejRYXB02DlMxUzGcwEBiOSwYhUYEUqMKMZzFiGfCRdNppJS2DQM6i0IlnZ2smKvKUGA84Og4tmck1VWuezeGYqbWbK7ZbKfFv1Xwh5ZhrcuVq/EPIMWf8rQr6V7oj91K6tZgNO6zmHzUnG6pGfa8m3raTun3H+GdL/iDStG634g/S4k++bs1+j3B9VASh5jTI/VLzFaJ4V4d+WtOwZqzETVhqQb0tJ+TJxsa6oHKQQw0mQpEOYgM5gNL9BvSea/fEzALwwcELQFIDmD2j6gKYP4IZhhI2xTIiLQfK0xWkYScNEAUj1DkGNFancQpoOj415iEffkh/LRdkYzwbJk5bkQJQNcTYk2SA5FEk2xNmYSMZYBoPUrpHUWfDj0P4W3W/R9Q4DwRgJ/f1wVBQFcRzEqRCnI+oTrl+Ay3GcdcEdF7xxlXvvKhV0EV9vI/UpirxR4Y+qT6gJQVUoyoNR5If818h6iVSP322JhHuId0fM7d8C4+8g8R7SniDfEyW+qAxBhh9euOHMHtw5LvP+tky6PzrSJpFiO1K6gJQYiIumoSMKvbEYTVAQpuhJ0vVJpq4ogyZKgyT7d7uC5OqTYmtJ8QxRkY6k+C9Ss4Pk2Q1FouMDOkLQE4OBdAgKFUmpoaBuG+m/RQYftsWYtfqgww+9n9AahuYQDCSZk5J/hGU7xqq2t+ctSQ+m+1xW2b8OxvMxy4KiZ6+uaylnaI0ly3BkHx5cAdsH38PQEYVBNkaSMJaG0RjwwpH0CC+P45Uboh4hzxOVr1Hth7oA1AXhexBqgvEjDJwYdCcri7LtSMEyUrZRXL2b/DxJOq6S3vuk94GYf4q0HCFVO7oyFiZ8Ur95A4dc4HRKff8ZlcMXtFyu67q5zzl/f+6Zu7NP3ph67Orkw+fo+09Rdx6SWf8v9e8tlIVrKJZLpU0XwWwhTBZKmS2WtvyLZrKIYmRHmf/XpAWrNbfulNq3T9b5kNwBZ+w/gcNuUifPUlyO4/1ShqeO9Aua9BsGw09d6Yky5QGT8orFeCMv90lBLpQmncKiNM/S4uhotKrS+ZqKZYqMPAYzhc6IpitGMBUjmIqRDPpXhly4vFysAiNFnp5JoRbQKN91lDlL53Tttui1nco1VeZYqPJs1NotlbnWSp12alxrpXYrBtdUnaM/uU1HtX2WAt9IiWeq1Wo6jT9Ps952Ds9SZ8hOrXPz/IEDazlOxpLEFSM//iIVW0jjjvHOo+Luu6TJUVi7hPTfFZWuSH2MvJeo8EeZH8rfIOcFWiLlSedT0nFmvO7vwSIrcfEaUrJeUmxGvmmSUq2BOIwnQpSI4Sh0BuPnG7R+wI8QdCVTRnJ0hrNnDWVN70lRaI1DWwIm4jGRAUkBSL4UyQRJgTAFE+lagprFpGobad03Nv6YjLwnP9ZJcjCaBZIDUfavPWuQZEuRbJYoCxMZEKZiPF2KfPtLVDWX8xXNr9H5Bl3v0R+E0TCIwiH6DGEMBEkYTEZHPPx8cOWy9KlzjNNnce8s3rrJBJzGp0uIuYmkB8h9jkJvlL5BaQCKPyDXHynPkfIECQ/Adgf77m94sbcQfQsxtxF/BwnuSH6ILA8UeKHEDxUhYL/EQxe47sLVQ9Jel5Hhi840aVI8nxQbkEIdSa4G+uIwmCA3nqQsSNEWp08hWUxRBsZSIMnCeCbGs0HyTUiRg7jESFhqTso2ksoNknT90XB0fkB7CPhxGM6CuACkRFdUu0bSfZF0XmkN123yBtcPnE9oDEcnewYp3kUqXHrzdjRnLCmI0vzwFE5bZDYulzK3ok43ktM0mjTDTNrQDtZL8O8u3DyHiFeoCAL3CwZiMZaI8TSMstESgth7eOYCrwv4+hgFnqh+jW8+qPFHdQCqP6DqE76HoDkK3DiMZZgJ8xYKS1YKv20XNTgT/iXSe4/0P5joOE1aT5CK3f0ZC/PC1R7dw5FTcD6t5eSm7nxxyslrOqfv6J2+o+dyc/qv+YlfE0xb91FWbZdeuoFiv1ZqwQpYLYPNcixYBrvl0nar5KwcZIwXw3KZ3JINajv+ldnnRDl0lHr4OI664MQZ6eNuMgfPwHMT7dV8GS+mjL88w1eV9USV+pgl+5JJ92XIBSjQPsrLRDEoxdqKTTpq7dos/mSF76xJZYr0DHn5eDrzq7xiJIPxlSH3VV42kkGPU2CmyNNTaLL5qvRGIy3u4lnc5TodFhqtpko8G7XORRrtdopcW2W+vRrHSqXdisExUWubrdE6U5mjx/ovhF2GWg12+hyLab1Witz1+oN7V3P2GYnjlg39WEjK/yHNO8a7dwu7bpCWk6RhE+m/MZZlk/YIafdR6Ilib5T6IO8FKt5isPYU6b5EuIdI9XpSs5FUrxEVmQpLpktK5nbFYjgOwkSMxqI3Ci2BaAoGJ9FAULaK1O0hP5xI43HSeExSf0DUeIDUWIpLjIaztMdSQH5FMgQJENYuJzU7SPv+0bEHkuEPpG4jycZYFiRZEGVBkAlRFkiWNMlUFaZjNBWSNAgy5UjpInGZTk8sWn3B9UHnJ/QHYSIUonAIvkDAxnAaWhNR8hnPn8tcvjn93NXpZy7gwQW8uQi/0/C/gqhriL+DjIfIeorcF8jxQoYXkl8i+h6i7yLqFiJvIvoGYm4i5iZiriP6Bti3kHAXSb9WaT9HkTfK/FARjK9PcOsYju7AiZ2464zYp+DFg5TMJsU6JF9bnKMIQYa+MENvLFV9LAnjqRBnQpKBiVSIMjGWBUEuSOFCUrRGUGw9XraYVO4VFv01kagi+IzBEPA+g5+AsRwGyQUpmyOqXUU4LuSnc9MHSosX2gPQHAoOGyM5C0j1XmG5IyfT4Rvb8Otr5sMz2LZdwdgM2rqYY0rXN1PQ1IOuMRavo2/ajPOnEOiB4o9oDUdfNEYTMJ6KfjZqAxFyG49OwesKoh4h/zlqPVHhjcrXqPDFtzeoCkBdMJoi0cJGX9KMkUzj8aJFE5XrxT/2Ea4b6b5Jeu6M914gHDdS8e9Y1qIq9pTXHjjmiiOuUw6e0zxySfP4tWkuN3Vcbk4/dnXy4YuKB9xo/x5V2O5E27CLumyzzF/rpBeuw6L1WLQeDhullqzH0g0Uh01ydqukTR1gvUJ26WbVPfvkHJ1pTi70o6cop1wop09LHzlL3esm82A3XlpT/FWp7+kMP2WFZ5ryHspyr2hy3iyajwL1HVM2SF4mnkWpm6ncpafB0ZzUqjqpTolexGSkyjPZ8sxYhnw0gxrLkImSp8UxGPE0uXiGbMFM5WZb3a6FM9qMWe1GKi0mLL69WpeDJmcRi2PP4turtVmw2q0YbcaqrXrqLTOUOHqsjvnKPFOtFpMpnfO1G+z028y1usyorat1+3cv4+41FMU6DP1YQEq2kYYNIx3rJvjnSdt58nMX6T7LjZiW+QjJd5H/HPkvUfAKxd4o8ERDhjnpPE56XEntOlJjR2r1Jwq1RgpnTBSbdSbIjKZiIgn9Mej4jB8f8T0Q3Sl6orKlpGYnqT5IfroR3g3SdYf03yN9Z0n7yeHqnQO5emOpv4+0iDMxXruK1O0iPMfRcXfRwAdSs5VkQ5gDcSYEGRjPhDATJItKMjQm0jCYDHEySDZLUrJAUjp1PA38D2jzBv8jBgIxEQ5ROMYiMJGIvix8Y8tEv8Vjj6k375ldvmt08SoeXYX/dbw+D/+b+HIZMTeQdAcp7kh5iJQnYD9CxD2E38Tn6wi/hi/XEXED0b/iGmKuI+42Et2R9hBZHsh/iRIflL9B6UeE3sP1Q3Dagn3r4LYLke7gsSHJ1xXnTRblKYnzqCAFC0mu6US6xnAiRpMhygTJhjAdgkyF8SxM5MuSwuXios3jRYvGypaTqqMjuZbjcZBEYTwSHdHoSKVO5GmQPJBSA2HNaknzIVK7q8kP7a/BD8bPCPSkzxovWjxWuqYj16YhQ784etZHd40L2zHbBoa2mGeB2YbSf8yj6JvS5llI/2GOlRvgegzvnyD3HX6Goefrb4S9bFQE4MN1PHSF5xV8uY+sx6h+jnJvlHmixBNl3qj0R10wmqLQwkZnospght548QJR1RrS8C/huZLua6TnunjkBum+RqoPkcKVzWmzPnrD9SxOnJ5+8LzqkUuax65OOXF9+vFrWs6X1Q+eZ+w/S915iLHFkb5mK8VhvcyStVJLNsBhC5Ztw/qdlJXbsGq77Krtkxatl7JcCutVWLpV2fGAvOMx1sEzrBNnJp1zoZ5xlTt2ZpLjebnre/FisWyAFu09Xd5Xifl8MvOVyiQvKtWTRfNSkHujIhfAkA6l4dsM5R6Dqc3qcp2ajCbVSeUs+UwGM5HJjGPS45jUeIZ0BJUaQ6PFUGW/Mil5+hqcJfpdtlNadGSa5io0zWd2LFTvWqbJXazMXaj8f0fYbTy10X5uq5km35jStGJq366lHEcDYYzDYJ01KdhEalYOtS+Z4J4i7VfIzz0i7tFKH2Q9ROo9FHsi9wWyn6PMF1keSA/GUKXDWPH62lBaTSh+xqKJDX6KzFiZbX/6NGGO2kQqOiPQEoSKN6h4hx9h6E/HRImBoGIZqd9J2pzFbUdE3KMjXbfIoBcZfk54u8RlcuMpGEnGaCYmataSH7tJx7+j4+6C/gBSvYXkQJQLUQYEmRjLhDDrF8Ip46kYSIYoCSR3MimyJWXTSD4GgtH8Ctz/HeFoMrqzkRfDCPCCh8e8B08c7jy2vXgLT27j7R14XYafO8IvIuoK4q4j/gbibiPWHV9uI/A6gq8i+CrCruLzVUTe+E8a/A/C1HtIf4TsZyh4hVJfVPij8A0Cb+KKEw5slt25Cqe2INIdXYnSY1kzBdlTRXl0cQFAKk6Q8lVjWRhOgiQDJIcmzMFYHgRpkyQ5OpJCc3GJg6R8LalYJyldMZ6/kKTIjMaiKwI9XzEcj/E0dVHWVHHeZJLNIpVrhT9dO7JWVbxE1ye0hKI9y1pQsHkoy3ogXW00Dy3xSH8L3xtyB9fBfrX0nwsx01xG11xhuglTWx/6hrBdiIXr4HwY3reR9ALV/uj4guE4jCShKQp5/gi8Ad/L8LuCsDvIfoWcZyj2QKUnKn1R7oPyN6gNRH04GiLAj9PoT5szkvFnf8r8nlTr0bK1hHuEDF8U9t0mfe7CNrfRyg0tiTOivXD1Eva5KZ24RHe5rHrqkvbJSyouVyadvCx35Cxzr7Pyhn+V1+xgOWyStVkL+w1Sa3bS/nFk7PhXZuc+pb0H1PY4KuzYRdmyQ2bpetitgcNWmqMz7cgpxsmztFNuOOWGk+eknF1l9x2XcnakX1+Ozxb4SKe8pyl6Kkt7TZ70iKrqwaC+UKD5sBgBSoxQGjWZRqlVVejX0e7QUmzVZH5XZ+Yr0BNp1Bgqlc1UTFJVT6AzE5nMRCY9UYFSMI3eYT1r0F6vZQ6TZ6bWZqHSasNqXazMdVDrWKLZaafZYaHON1flGSm1zlJomc5o11XhG07mmWq1mGp0mE/psNBvM5vSZj6pZ/GM8Z0rm/YZkE9WwqqlpHIZqV5NGnaS7jMjzQdJ37HxKofcp8h4gCR3pNxHhgeyXyDrOVI9kPYMaU+Q8ghpT1DghapPaItBVzJa2BAVmZJvi3uTZnfE6nCippS/RoknqoPQHIXeVEzkTyWlxqTSjnz7m1StJg2HCPc86X8oGn4qGrhOOLtFpTOHEkBKbAh3mbj7DBl+SfqOjZXZCjN0xNkgqb+neUgOSDaEqRAmQJwAkgNJupYwbwmpmC/KQ08Y2vzAeYeuLxgIhSgMJA7jaahNwOdgy2fe21/42D/1tL3vYer+aO7D+9pP78m8cscrdwTdQtANhF9D+FVEXMGXywi7jNArCL6EkMsIu4rwa/h8/XdWDL+GmBtg30KKOzIeI/cFir1R/gaVb1H0BkG3cGQjHDfRdq2Gy0bkeGEgDuNpEGdDkgNhFiAuP0QqVgpz5UaTIckAyZIWZGI0B5KcGaI8A1G+1UTBInHxKlKxnpStIoV/kWQMxqI7En0xGE2EIGOyMGeaOG8yydcltZvFzafbUpZUeILzES1f0JphOZi7glSvJVWWpGzaSK5Ga5JOTsD0x8dhaAQLO+gaQWU2ZlmrTbdkMPWhaQTbFdi7F88vI+4xvvmiPRj8z2gPQUMUCt7h3RX4nke4O9gPkfMSxa9Q7IHCJyh4jlIvlPmhwh8/QtAWi/7kOd/eIv0B0u4j4R4SnuIH+0/Sto8M3xF3XBmpOzxatqYjY3aSP25dw8HzrP8V4a+roIfPyDseUVq7i7lqG3PJBmnbdViyWXajI2uPk+q+gwr7jmgdPjb10GH1ffsVdzrSVm7GwvVYum3SL4QubtRTbnA9h5PnpJxPS+87LnXIkX57LYIt8ElBLoCp5KNJfTmZ9oCm/AuhlxLjrRIjSF6WTaeUqdDbZqj1aivzJivWqTKLFWkpdNlYGjWWIc9WVk5mMBMYdDaNmsSiVMxS45nP7DSb0j6PxTdXb7dUbbNValuiwluq8f+LsNVIjWv6B89yBtdGoe8vvbEdK+r36ks+mgm+LSeVy0jtOtK4h3ScErWfIF3O/Azj9PtIvovEu0i+h9THyPBAylMkPkKqB5IeI+nB72pEsQ+qA9HwGd/D0J/1h7BkQdNnjSIvlHgh5ynynqHcHz9CwIvDUBaERRqkdC4ptyaViyTf15Cfu8Sck8LOS6TnCul0JT+3km92pGKlqMFhrP0kGXlKOnaP5OgIUlRF/0EoTockC+JMCFIgTIQ4ESQLojRNYd5CUmkkyUFvCLi+4PhjIBiDQRBEQJSIjgRkhysEBlh5+W/xfLPk+etFj19aPvSY//jJjGcPFV89wOv7+HATgTcRfBWhl/D5EsIvIvQSQi4j+NJvh6FXEHb1vyP6GmJvIsEd6Y/+N4Q53vhwFc6bcGAL4991cNuOAl/0szGSDEEGRFkYTwcExTtJxUpR4QxBBsSZEGXQRtNpo9mTRIV/igtMBfn2goLlpHgtKd1A8pYKUy0ESRiMRXc0+uMwlgZB9lRx3kxR4RSSZ0y+byctZxpjzav80PIJfDbaM006M21I7SpSZiXK1yWls0mp8XCeUV2kytv7ZjtW4885mGuEqYbSivOkWRZ0ZVumhR22b8KdE/hyGyVeaAsCJxTNn5Dvizx/fL2PyPtIfo7kx8h7hsKXqHiFvEfIeojCF8h/iaynKPREXTDqAijZj5BxH+XeKPZGwgNkeKORbUC6z5Dey6TtuLB8ZWfatKyPeHQTh05LH79IO3lJ5dQl7RMXlU5ckj1+keJ0irr7IGPlNrllG2Xt18JuPZbvYGw/qHnw+LSjLtrOrnqu5/RdXHWOHtM+cFh1/U6ZJZuwfAdt71HakVM0Fzeq6zm4nofLeelfCPc6Mh7vRIAlAjWYAcpKb3XozyZTHsgrPWPKvVCgeSoz/JTo75myn+mUNGVqhZZC7zQ1vpbKT1WFUqZcFl02QV4uliEfxWSmMBVTFZixNNk0ZWrdvClthtots5U7DDQ6LNS51qrchWpcB7VfCPm26v83hPOV28102y2ncW0Uev7SG97xd8MBfRJiIahcRSpXkvotpGEPaTtBOs+S9oMVQfIJt5B4G/F3kXgPiQ+R9AgJDxD7APGPkfAA8e5g30XiPaQ8QvYz5L1Cnh/a4iYLiuyqA5V+jdUn30HaPeQ9Q5kfGj6jIxED2RjLh6h4GikzHK8yEdTaC+rWChv2EI4L6b5G+m6Snuuk0WmgbtVwywky6E6abPuTMJEKQQ5IOqYZerEAACAASURBVCQpEKZCmP77POh4IgRJEGZhPFNVUGRHKmeLMzEQCL43+H6Y+IDRUIyy0ZWMkkidUD9DX98Fb4NW+71b5uW/9PnrRR6vLJ4/N/T0mOz1GD6P8P423t/Ax6sIuoig8wg6j+ALCPpPBF9E8EWE/Edj6BVEXUPMDcTfQcpD5DxHoRfKfFHhjyQPeLvBeRP2bZLdvQYXdiHXG5wIdMdhIBnDaRhIBkZz/yZly0ixqThHTZTNFGYpjWRojOVOExZaCIrshEVLxcVrSOlGUrhKlGTe+1l7LBEDbPSwMZCM8UwFQa6euGCuuHj2RMFC0rCftJxojDFo/gxeFIZztHoKLCaql5L6VeN5fwqzdEnutMF49MVjOBX96YvbE5a/OoO/DGFiiD+MwJiNyebKixZi3yaZe0elQ64i5wlq3qD+HWp8kfYS2V5I80TWK6Q9Q4kPfnySznqE8lcofIrcJyh8jpynSLuPzEco9EL+IxQ8RuET5Hsg5ykyHiP1MdKfoi11AWk5RDpdJRXLOXGMzAA8d8fRM/ivTPgL4bEL0gdcKDsP0H7VY2xXw36D1Ko9ynuOTj925g/Xc7Nczs+9cGX++YsGp8/qOp+YusWRvnSr1N876XuP0pxd6S5uVNfzvxDi6BnKvuPYtU/a10X14yIETlf0U1d6q894MlnqPp3poSDrwZR7pUT3Vqb7K8h9lJeOYlGSNahd09Q7tFWbVZk1TLkiBjVDgR7HpH+hyyXQ5fMna6YrK2QqT6qbM6VhlnrdVPnueVM6LFX4tur8xaq8pRr8ZZr8xRo8G02+uTrPTIVryGrRZTZPk2/XVekw0uKbabeaaXZYaHAsdFrMtNusFLsc9Ib3rGp0NiRRC4Tf1pHKtaRhK/mxS9x4mPReIfX7sp8j7jbiboN9F/HuiL0H9n2w7yPuAWLvIcYd0XcQdet3lSLmBmJugv0YNSHMkdwl1YHTwi8g4jISboJ9DSl3kfUUZe/Q9BW8ZPRkYCQXoiLliSojYaWRuNyKVC4jDbsJ/zzpfygZfkV6rw+0O05wzpGeS5Jyeh8bkiyM54JkQJICcTKEqRhPwXgixpMwkYrxLIzmaApLFpCKaeI0DH5Elxc634J8xEQUOhJQEisf8cHSx2upt5/Du2D7tx9X+r1b4fnG4aW33QsvM+8Xs7w8FL0f4+1dBNzCh6v4eAEf3fDpLD6dQ+B5fHL7/eO/NP5yGHEFUdfAvoXkB8h8hgJPlPii7A1iH+PxCThtwM412OaAC7uQ+RJ1AWiNAD8W3fHoZAODmRakxIGU2Ivy/pTk6U3kTBvP1hEWzBcXLRQW/SUs/FtUtIaUrCf5ywTxhj1hCqOJGIhDTzyG0jCRM02U96e4yFRSajJesZ60OZOGAxy2Xk8iehMxUag1UGg4XGIsLLfoTZrSF6c8HI/2EPDCMBQHUkwluaojaUaZryafXo+/DGFlCH1drLfDic14dgJhV5H6AMWvUOGNkpcofotsL5S8Rbk/0p+gNXqmpHRFrhfyHqH4GUpeoegF8p8jzwN5Hsj2QMFjlL5C8Uuk3UOKO3I9kO+BNHckPMHPWMOJ8vWCkkUdSWrpb/HcHW7X6ScvM05dUT99ZZrLZdWTl+WOXZDef0J6x365ZZtlFq3BgpVYuFF63V71fS66Lufnnr881+3K/Ks3Ta9e+/P8Rf2TZ2Zs36/493as2EXbe5Ti7Cp78pyU63mcvvALIfafwHYnRDzUj9wo91GX7jOZ+XbeJA9tqXt0+Scs2cdM6jMFmpcSw5cl94YhHcSUjlCmNGmptWurtWooNrBoVYpyhUqMFAX5CBo1lkqt0JlZMmNKlgq9YprK96nKdZqTumZpdliq8G1VO5ao85dp8pdp8hZO5v8/jN1lWNTb1zfwr0iMMDPAgJTtseuoKKKI0qiEil3HOrZykO7uHhi6RcBuunOG7lJRabuVmNjPC/Ccf9z38zzXtV7M23nxudbaa+29fhsVX69X+N8Qvts4fWD93JfrZwyoMz4b/j56ZvcL0zUkc5OgZQ9pNSTdJqRjD7frOPlgN1JnUuSPbC9keuCBO+674b4b7rvjkRee+OCeB+67454b7rngjiNu2eOOHW7b4pYbyiLw4qFyVbR8hiXu2uOJM+7Z44krcn3AjkD7Tbx4jKFsfCzCzyqMNf3Oq1tBapeS+nWkXZ/38tjIW4uvn13JzyDeVxvy3psMXP1Zji+ZIJUYrQApg6AQ3ILJZSsjuRjNx2gxflZglD2D27CWNEhxc/EpCW+i8TYVgpv48QSdmbifrhAVvZUVty8+xTjxumpi6va4pG1R8foRsboRUZsiWRPJkJLkhyRvpLgixR7XrXHdGtetkGaNVEtct0KazaTAiTR42xn3HPHAGY89kO+HkhBURKA2BvVxuBMAz3M4sxsHd2CfFjz/BDsGnSnoTEfPHfQ9RO8D4GvpQlKnSep3CKo1+LXK3OplY+xVpHYzqdcltfo89vbxSj0+W49Ua5HSVeM5M77nU7/k4lM+vpeCW7WcX72RX7uVNG7+2XqYvDo/xtHrvy/0LgtvsvCpCB8K8KlY4UfZnFd30ZGI7mQM3sZoAbilIEXg5+LLA3zPm913b1X4WVzWQ4TlvIZ7Wi/ztn0o0/9QuHboseKLG2hOQFUYKiLRch3fy5d8L53fnIRPJarkjcXzbN2qADSEoyES1UxUhqAqBJXBKA5AoRfKAlDJRFUYqsLAZqI6CFX+KAhCMQsdt+Z+Z6t+ZS8rSIa/Gxw85c1dGJauSlYu8yxcFK86S1yxF55AuH2/6ARC7X2ie8/OOmc1wW+Ng+c6T99Nnl4qTq4rLGwXHj0rtePIVIM/JE5dFrloLmJmK2RhBws7mNtNIjx+AdU3N3PMZqQuFEqYRUlYIhwxRyiQIhHAEPWnCQfRRCPo4nFS0xKpwqm0qTelhJtkaD1KjEFFxoCMeI/0tA4GvZJOz6RQskVFWubNbZ0/t0qGWiMj3sKgPpcVfz1Hbng9fXiz1BstuTf6isO68sNbFYdUFV6vmzGkzBhcIfkfCPvXKw2vp/cpz+5Tnf1Od+bPvRu4F/c9M/+dZKnwWnaSVgPStp207BjvOEgG/xrK2lDsjYfuuOeCm/a4bot0O6Q74IYTbjoj3QHpDsiwx42Jss0K6ZZIs0CqLe66oiBY9o4j4i8hzQq3rHHHDg+d8cQNxcFoTETnDfTcw+tMfCvGz8qZPyvkBJUzSe0i0rye363zo3f/19cnyVcPMuJCPjJJr/XncnzMBCmbyisDvxzjxRjPB78AvHyM5uFnIcZKMV6GMfYMXsMSHgffHuFtDIaj8ToD727j2R0UpIrFRs0PjNwalbQnMdUoIWFTXJJuTIJuVPy2iFg9VrQGi7U2IvS3iMDpcf5I8EGiG1IccM0aqZa4ZoEUC6SYI9US6ba46fBPe+aOG2474q4LHnsgxwfFwSgLR1UUamOQ4SNkfwpn9uKwIQ7pItwSTRnCT2+gORkdGXh6G103gR8Vs0i9Fqk3ITWGpH4Lr271GGedoEab1OqSGn0+W2+8QptbtYWwN5HKlaR05s8CxS/5+FKAn+Uy41WreRxNXp0+adT73nacPDvx9uHs3nQM3cPAIww+wrtMkJolo2WK/XfRnYrWeDxLw8dcvM3CxywM3kJ/OgZuoD8DvTfRlUblxEzpvEV59UhqMEt08AleZ+JTwfQvJQveFy5sSqF8KVpFuvVJu/qbvAXf64zJR68vTx2bItDIQk0YOKGoCEZZIKpCwWGBHY6KcJSGo5iJwkAUeKHMG2w/1ESjmImyaDzLnN1XoJiTCC93WLpJW7nL2XjMtnVfaOU208JV8i9HsT/NhA+fFttxQEzDCGoG0DskfujSb1fsf3f02ODlt9EraGsQU8s/SM3DW9nGafHxC7KGx4SNTtBPXRa5aCFkZou/EV62wmlTnL6K/jKD/sDfry9B8jyx2IVIXiAaQqH6y4j60Kb6SwizaJQEOjVFQjSVKnxTSqSYKtKqIDk0i/FWgT4sS30hI90gLVVIkSgQp1TKMKoVpnNkpNg00Uaq6HMG9bXi9AFlypAa/Y2W7Gs9uWEdxaEtSoMbFP9HhG/Wz+xfr9S/flrf+pkDavPe6c7+snvtt7O7nlmuIqVbxhu3k1Z90rhF0KTNa99Duo81JUqVeOKuK2444JolEi2QbIVkGyRZI8ESiVZItEKCJZIskGSBFHOkmCPlKpIskWyJa9aIuYC4S0izQMpV3HHEA2c8cEaeL6oj0ZKEjuvovYcPOfhciK+FGC0DqZMnzasEbRt5Xdr8F4Zk8BL5YkM+RpHXviOtSp9zQfKFSKkwrxxjReDlgxSAFIBbgNEijJdhvATcSqXxGqUfJXh/A/0s9EZh4AbqbiAzColB8mGha8Ji1CITtsbFayfFb4+N04qO14mM04+I1YuI0Q6PUAkLXRIeODPKD7HeiHNDoiOSrJFkgUQzJJohyQzXLJFhhzsuuO+O+56454F7HrjtiLvOeOCOHB/kB6I0DBURqIpGvCvMDuPsHhwzwlF9xDmi7RajKx2NiWi9jo4MtF4HxtgzSJMWaThIaneTBl1Bvcp49Xp+tQ6p0CAcPcLZzqvS5Vapk6o1vPI5Y0WiI8VzvxZQvxThe/mM0SoVHkePV2tImgzGus+RZ6cG0tB/Ha/v4U0Whh/jRy5G80QHbuLlDXwtwLscvLiLoSd4eRcNSXh+C8/S0J2IV2noSUNnMp7fRN89vLyFjmQ0xqD9Ol5n41vV4pFaZdK6l3SbcKtWfyv6baxmM3lxlnwO5b+P6YxHfRiqQlAbjhoWOGFoTUDv/Rlfy1S4DTq85m1fqtQGs1Y8v6nYFi1UHYCSQJSGozAcJVFgp+JJHPz9YepEt/ZQsPOaZ++52MZjtpU7w8xp2pmrokf+pBgcmqZlPGWzIbYflTxmtsTcZb2br3pAiEZQxLbwqO0hYZo+/qr2rstPXpI3Pi5qfIp66sqUS5bC/43wvCW+tu7/kaietgzXFojEzkf6EolwCs1XRtSLPtVPXDhCQiyRRr1GFcugCd+ii2SKCjXK0V7Pkf2kxHgnRxuQlW6RZpRTJErotGxRkUIJCkdGqppKqRUVfiZFG1aQ7VsjOriR9lpT5rWe3JC2wqC64v+I8O3qGRMIh1Spg6pzBzbPH9wqP6i76M0xvRc2a0i94UidNmnWFtSt4zdu5nXuHGvZXRyEYjfcdkK6LZLNkWiBFCskWSPWHFGXEWuGGFNEX0HsFcReQcIVJJoiyRTx5kg0Q/wVRJ7HdUtk2CLJFA9cJ9v92Z5gM9EYg7Z4PM/A2yf4mIfP+fhZBn6dOGleTppVSOtW0q3Df3qQvDflv48hnyPJgPrXIvCzRUiFErcMo0XgFkxer+EVYqwY3DJwi8ArVxitkvxcgKEU9ISiJxKvbiE7FTE+8HVSZAZvik5QC4tdERGlei1uT0ysZlScdmScfkTsNlaMNitSNTx0RVjQnHA/RHoh1hUJDkiynvwvcZeRaIZrlrhhj7uueOiJh9544IX7XrjjNIkwyxv5gShmopyFikiw7HHRBGdMcMQAh3QR64CmdEpjHJqS0Hod7eloSQZ+cETGq1eTRhPSeoI0HxLUbBNUaRCO9kjlBkH1Fj5n88/SdSOla/hsVVK5YaRwJbdMfqRIZrxsIY+9Zoy9gdegKWjWGa3bRJ5dGqvQbYtHTzI+3sOXB+AXTP/6QPrVDfSkYugORooWCSqV32crdqaghoU2Ftqi0RGL1mh0peBD1sL32Yu6UtGVhu4UdCejJx39D/C+AGM1G0nroR89JqTPj9Rpvs0DaVjH51zgDhmSz7EfHs0o8hAtZKGMBU4YqqPxtfIo6f2L/95M8NGW/96R+8ZS8Po8GTjCb9v7vWLbqyTUspAVgPxw5McgOQAurrDwlXJ0X+nms9rDf4Wzz3w7dwVzB+nzZkInzmHPAWzbBZ1dU3f9oXTG8ndbr83eoVphUdpBEbrMmB0hsdu9mVut3Faeuqq4/wzF5KTQnivUSzbitrawsoKVI0ydGOcspp27jGhvmb6K+aR+Q6Yxrs2Ri5enpi+hh8gI+dNEg+gSTGk6S5oeRZOIp4qlUkVu0UXu0UQqGeIv5STfKUq9myHTr8ToZNCbRMUL6FNzJMQKaZI1Uox2qngnRaSDSutSmDW0VObNeslhTWq/Hn1AT/G1zm/v1Ga/WcsY2ig7sJQxMENqeI704HJ671qp/vVKw+sXflBZ1LVU+JOuwitVhSH9dQPH1d6zNpIGnRG2Ab911Xi9DKnfQlr2/ajcfNsZ91yRZo80e1y3wzVrJFsi0RwJV5FwFQlX/on4y/9EojmSriLRDIlXkHgFKWZIt8ZNOzxxRKYTclxR4IHyQNRGoeM6nt/Gy7sYeozPBRitAL8WpGEOad5KWoxJywnSv1bw1pi8jSLDwV8bJT7ng5Su4paAXwx+MXhF4BaBWwR+CQTF+FIIUgNShf44vAjGq9ipldG4FgQ7B7i7y3r7LQkMWh8StiU8WicyTo8ZpxUepRkWqREeoRkeoRkWqRHK2hgUtiYgdEV4kGyon0iIJ0KcEWILpgVCryD0AiIvIsUKd5zwxA053ijwR74/Hnvjjg/uueGRB3K8kO+DCibYkSgKgc8VnD2MvbtgrIXLhki3mVIRioY4NCegKwPt6WhJBX5WS/Fq15OmPaTtBGk+wK/W4lVtImx1frWWoFqDz9k6XrmRV7VBwNkkqFQeLV7OK581UjyTX7GS1G7mVm/m1moKmvW5DZqk/ejXApWnKRi4iW9Z+J6Fb1m0t/epjZEYvo+x4vnjpavGS9Z8L1rZe1uiOgz1YWhkoZGFhij031cg9Vo/y9fXx6IjFV3JvxDex4dCjNduIm2Hx58dI8/tBA26wwUgjUb8xssj/Rrkc+yP0hXsCLSkKnKi6GURaL2NkaZTpNd2bNiffIgkn2PIO+/xQVPSf4r0nyKvzpJ6vf4ni0sikB2M/AjcZMLNC2dcRF28Vnn6r/UO+t3df5GD52xLJ9lLFmKnLmD3UWG9vdDdK7r71Kwz1mvsvNX9w7RYMbphsQYRCcbhicb+ETq2nmvOWM46dJ6297TIgcuTCK2tYeEkfMVR6qz5lIumSA4Qe1+/jDQrd1rOTppPi1cUT1ssGSor7EcVCaCJB0tRw6RoLJr43whvSwhXSE97KSf5VkHyjaJUvxKjW1a6XUKygC6cIyFWQKXVSDE6Jand4qKdVIl2GYX++VKv19DfaFAHdOkDeorD2vNfq88eXicztFF2cJnM3wj7lKUHVGa8Vlk0vGH+y7USgxslPmrNe2Oo3HdS+ed1LdKoPVatzW1QGq8V4rLXkea9Lx/MvuOC27/Ofn87TLFCsiWSLJB8dTKSzJBkhkTTX2GOpKtIMv1PhI8d8MRx8ttMxT7ghKEpHp1peHYTffcm3meDWwV+nTRpXEeatUijCelV5w8aCwZcSL/9z+ZF34pBiuS4ReAVgVf4D0JeEQTFGCvHeBXeZqEzCm1M1IZSr7nB3Qa29nBzk5lEGK4eHq0TEasbHq0VFqnBjNgaxtIIY2kwI7b+jZAZKB/iJ+HviUAnBNgiyBzBlxB8DqzzSLbEXWdkeSDPF0WBk28pHvrivjuyPJHng0I/VIWDHYmCILiew58HsHcXjDRhuhM3HVEVhtpYtCTi6U103URbGjBaPYtXq0qa9pC2o4KmXeMctbGKlfyKVaR+O5+tPV6pzmNvEXA2jVesHS9dNl66jF+5dKxkMZ+tShr0BDXa3Fpd0ryDtBmSxu0DD2Z3JKE7Gb038fIWmuLRnISeDLx9Am75Im6l8vvMxW2JYIeiIgjlQWAzURkGNgu99+VIi94IZ1NtPNqT0JmEp0l4noaBB/hUJMqt1yDtx0jXOdJ6nNthPMwWJZ1m5JnF12fLyPuob5wtVfEYrzAlDWbPc9HwEINVJuSzD/l4j3x+TL7eJ+9ixgbtxvvPk8GzZPASGbrC7Tzam72mKhrZfkjzhZff1Ateip7+a31D1vkz13kHrXDx/c3WTcnUmnbm8pRdJ6nbjojrH6buPTP7gu1aB1/1QJZWVLx+dPLu2NQ9UakmwTHbnP1ULtjOP3qJsf8M5cBlsSvWFFtbWNvB0ln0ij3lojnMzHGTiQ+1s0ntgrHUrddWTY1UFE5dzIhUovhKCPvTRANo4sE0iXAqJY4qdo0mcoMukk4RKpWSeCHHeCNPH1Kgv1KUfCbPeCbNKKAL50hQciUkOZLS3dL0F5ISnVSJJgmplwr0waXUt+rUIT3JAT3Ffq25g5tnDapOH1abPrhMZmgW4/VcxtAKyf51jMENM99sWNyjOmtQTfbVKuHR7UteGy4d+kuZZO8cb1Efr177sxrf2RgpX0FqjErDcNMFNx2R4YgMx38cptoi1XayYzER134dCCdMJk78MEOSKZKu4NpV3LTCHbtfu7odke2MfA+UBaAmHI0xaE9BTwaGH+JLLn6WgcsGv34GafpdUK9CnunyX+z+0X2A33NA0LV1tEp2JA/jheBOdEcLMV6I8cJJhISDkUpGYzKyvPHAFbFWMD+Ds6awtBNycpvu4780IEQllLWFFa3FitEOi9IMZamFsraEhKszw7f+jdCfudQ3SMHHX9LHE77O8LWBnyl8z8HnNAJPIdYMt52Q6TU5Fy0MRmEwHgfgngeeuCPXG8UBKGehjIUsH9iewPF92L0bhlq4YoJ7bkLsSHBi0JaIF7fRcwddGcAoZzGvRp007ietR3gN20eq1vwsXTxeupTUGYxXaI+WqXOr1MfKVb7kL/xR8JugcrWgWnm0QpnUaJFmY1JnwKvdTlp2k84934oXNcWjNgLlQagIRnkYMn1RFoP3uXibhQ85iq+fzGuORaYzHjhM3mIpCUElC2VMsGPQ+2Te67zFHTdFm+PQHo/uRDxLRf99fClhCBp0SftJ0mY60riD++Lol879ZCCMDLt8bJtO+r2+NZxm3wDp8iQfQj+303srNHvZB8gnM/LjCfn6kHy6ST7GkPee5J0lv/8i9/lFMmxHhi1H2w49vS1T4IebPmCGiFkEzvEJXh0Qtj4wfJ1vyO8e/ksdPeZa2MtcNBfZeZax/QTV8LjU4QtzTB1WufqrhUbrxSUbJKTvTbqxPy5jLzN+u3uQ6mXH346byRw8L3bEdNoV66nWtrCxg6Wz6GU7oSsWcLDFAxa6svA+F6RIP3Pn1CBFXFssEz9Pypsq7EMV8aGK+FMpoRJikVRKIl0slS56nSJULC3+TJ4xJEcbkBN/IU97IcfokWXk0UWyqJRMcWoZnd4pS++Voz+TpNaJiHfRqH3zqW820N7qMAZ0FHo1ZvRvnjmwWfFfEQ6vlBpYLzOkOuut6pJu1enD6nJDypTvenNfGit+DdhCKo1HWlS5lUo/qvCxDGOcNR/yttxxQao9Uu0my9G/i9K/HaZZ47oVrlv9m8O/I/kqkk2RbIq0q7hhidu2eGiHR/Z44ohsR+S6otALFQHghKIpFp1JeHUT7x7jWz5Gy8GtBb9RcrxuNuk0Jp27vzUvHe1cS3r2kkbNDwUYK8B4/q9l8L8Q8otAKvGjctEDf/ieg80xnN2HPQdwykbBwnaak+tM74BlASHKoSy18ChNVqR2GEsjOGxjcNjG4LDNIeHqIeGbQljrg8JW+TOXegQpufsz3DynujvCzRpul+H6Jxz/gPsxhJxHqg3uuyHTCzl+yA9EXgge+OGOGx65ItsT+X4oCUNeCG65wuIIju+BiQkMdWC6Bw89KdXRYEeiLREv7+LlPXTfALg1yqROlzQdIq1H+I07RtlrR8qW8cpXktrt4xXaY+VbuVVbfhSveZ8190fBYlK3WVCnPs5RI3W6pGmnoN6YNOwkLbtJk8GzdJQGoSwYeT7I8ka2Px77ofo6eu5gOBO996bVsJDrgXwvFAWg0B85fsgLQGkYSsKQF4gyFpqvo/3G1PootMaiKwFPUyYQThc06JG2k6Tl8s9GLdJ3UTBkRz4mkM8+n5ropPsc6Yt5WQbSup/U7huunU8+ho/2O39+qUE+h5KPTPI2iLz1Iu9tyTsL8tqKDDqRT97kvYvgxbnXub9XRyInDMkscWc/mh/z96AI5eAIFX/mGq/A5a4+C21dlP6yoR+4LLXnjOi+PyVOX1Eyd17qGbiRGacXn74r+ebBlFuH4m/sC0808ArdbOa65JSF/JFL1KPmUycQWjvCypl+2QYW1vBzQXEcyuPQkQZSur7RjhE4DwkLpZIXSvnShX1owt4Swn4SYkE0MRaNEk+jJNJFrosLFzPoTxUYg/K0XhlKj9y0Hll6D0M6iyrygCp+X4KWSxVvlqP1zWD0MKTqRCmtovRnShJDayXeakq91lLo3aLUp6Y0sFlxohz9b4RP1RhDG2W/qskPazC6D0uR+ztJrc7PxpXjJRitwvtCCOrUW9KWXLdDvDWu2f5KfTb/FilW/2smnPh97SpSzHDdFGlXcdMSt63x8FdFmu2IHBfku6PUG+X+qItASwyepWLoDj5k4mcRxtjgNWC8Xoa07iTN277WYbSZRl4cIU+PfqxijOVjPB+8fIznYyx/MjFOfJHibcFKn8s4ZABDbRgbwfgQTtotMreVcnCb5eW3IiBEOSR8U1ikBoulFRa2NYi5PjB0Q2DoxiDmpuCwjUFhawNCV/iG/OYcKO/sR3PwFLV3gp0VLC/i6gn8dRjWB+B2EhFmuOaAu66454GH3njih9teyHDELUfcd8Vjb2QH4b4/Eh3w1yEc2429JjDSxZU9uOUmUs5CeQTa4tF/FwMP8fwmQOq3kEZj0vIHaT0uaNrFrd7Mq9pAOFv41To89lY+R1NQrTVWqvold9V4yQbSqMet1xiv0RA0bCcNRoJ6Y9K8i1en/zZvTQ0LpUEoY6IoaHLfRqY/OLFojENDHKojUBKIHG/k+Uxe9s0POvwbYQAAIABJREFURtbE6v/wyRvA5WGoiUJNOFpi0BmPriT03cHXYiVBw3bScpI0/znWosd/fpW8cyYfg8kH329Ni0iLHvl092vrdFIvN1ax5E29Ohm7QT6E898YjQ5f5g2bkUFzwatzo517f7abkBfnyBt38tmbfPYmn11Hm3c1JCA7CHfDERMK/7BlwZFrQ6JUgljr/UKVvQKXO3vNt3aRP2dFO20q9OclYVMLhqPrIr/gDWHxenE3dqfc3n/tzoGEm3sjkg18w9UtPZedtVE8biZ50kLoijWsbGDrKDaB0MEWUX6oS0JhMDiReJ8p3Bc3K04V0QtEry0W85ee6ksX9qQKe0uIBtDFwumUaClKPF00RUI0n0HrkJMekKP3yU57IS/eI0t/Lk2/R516i07JoEo8EBfhyE7rnSv9QpHRIE6pE5ZqkxV/tYLyWl3ytabswGbFPlXFITXFQVWZicbMRDn6N8KXG+lvNsh815jRoyve6zCXcHaP1ahwaxaM5WOkFF/K8LNKLT+YlmSHeGsk2iDZ6lf8mkb820ziX/hNxDVzpFrgujnSzJB2FTd+IXxg+ysTOv/6bL0nSr3BZqIuAh1xeHUdb+7iSw5GysGvBr9xEWnQIw2bRqsxUgfSs5/0XfraqsktAL8A/AmHBZMIeYUglWi/M++PHdi6Gepa2H1o6oETQn9cUTCzlbd3+83Td7lf0Jog5vpw1lYWS4vJ1AwMXRcYui4gRCUwdEMQc30gc7VvyCLvoHmuAVQnX1F7j2nWjrCwwKXzOHkMf+zDORP8dQAup8A0Rbw1Em2RbI9UJyQ5Id4KydZItcN1J9zwQIobwizx1wEc3oXdJjDUx/mdSLJCvj/KmGiLx8ADDD1Gzy2ANGiR+l2k8RhpOS5o2M3jaAvY2qTGYJyjxmNvEVRrkFodwtHiVWiQSi1Su32kZvNYnSZp1BfUG5IGI9K681Pxuvp4sENRG4EyJkqYyA1Glg9KAlEagNooFPoh2wvFQSgKwiN3PHRHThCKgiar6tIQlAWjPARVoSgLBIeJlih0xKIjAa9u4UvRLH6dAWn8Q9B8iNtq+KPuEum7SPovkD7PsbZN3NZ5go8R/HZjUgPSNPNnxw7yxZs3FEY+W5L+c6TvAnl1lnTvG2nQ+MJRHWvaSZ6fI0M25I0jGQkkw2Ztd2Zm+yE3FI8j4M9aGBK1mhmjGhK5IYi1wZ+5zitombPPfHtXiq2tkJUFHGzpHu7z/YPXMRN0ozJ2X7tz4NqdA4m39kWlGgVEatj5rb7sOPe05fTTNiKmNlPMbWDtRDV3YZjawNUR18LQEI2KYBQFoSkFQ7cUso7QIxYIpa0QCpYV9ZcW8aYJe9NEAmjiYVISkVIS0VKUZHGRbLpEC4P2SpbWp0DtnUF9IU97Ji2eITH1Ol08kUq5ThEqkRHt+Y3xcq5cE4PKEZFrkBZ/tlhkSJX6bqvM642KgxsUh1RnDGxg9C+R6leSHJ4j/feZ8K3qkiFV2qcNcm/UGC8PyI/c0OI26Y/ULiVlsrwcfMsFvxYDj5ffckKiLZKdkGD9j71E839aoxNzsySzf+M3mQPNkWqBDAukmyPDDBnmuGmJW1a4b42Hdv+C0B1FHijxQnkg2CFojsDzOAxk4ONj/CjEaAVIkxqpViM1SwTVGGGDdOwgQ2bcV+f4RRBM3OEu+HeEtULlibLaG6CqKb5JV3jfYRw/iXPnp5rbzrZ3XeTut8w38PfgkHVh4WqR4RoRoZqBoesCQpQDQlQCQlQCQpT9Q1b5BC/0DJjt6i/k7DvFzl3M0oFy0VzkxDnsPwrjvdi3A4d34Pxu2B+Dz1kEnEfgeQRfRIgZgi4g5CJYV8A0BcsaIVZwuwCzQzhgBKOdMNDFye1gnsUDJxQFoSMBbx7hXRb67gCCOm1Su5PUHSUNx7i1u8Yr9UjVdlK9Z7RKZbxKhcdWI3U6pMGQ1BkRtgGp2PajWmW8XkPQvI1fv400GZDWnYNZCzO9wQ5BUyyKglDMnJyPN8aAE4iyQJQGo9AfWR7I8kZhMHKD8dAHeX7I9UaBP4r9UOSDqlDUsVAVjKoQNEeiPQbt8Xh5E58LZ/Bqt5P6E9y2vfy2vZ+KzpGuvaRzB+l2IF36Ix348c6OPLPgF+NbHt7VbSRjl8jbKPLKg/Sbk+dXSPcZ0n2IdOmS1s2CZh3Supf0/fW98wL/jRN57zhUrFYdi4owZPsjIGJxSMzv4XGbmNGbQ6PUgiM2+jF/9whYEOBD93QVcbOf4uko6eM51z94bWi8DitjZ+rdg6l3Dybd3h+Ttis4RtsxUPkvlwVnbRTP24hNILRxppu7MP6yhYcrbkShMgicUJlcHxSFo/82qi0XsBYjYzVC5MT8ZUQnEPrRxUOlxVlS06LoYnEU0UwqpVFa/KUMdVCJPjBH6pWi5DNp8VRxoWtS0+JplCTKlFzpqU8XMHoXyLfKS7FFFaulJDp+Ex5QmfZ+i8ybjQpD6xWGVRQHNjD6Fkv2KdKHZksNLqf/3Zh5r0L9vlHxxRrxwXPzSfUfn5vURusXkkIxkoOPj0Fap7ekKqZYIcYS6W7/hdAMCaaTkWj6bw4nBVr8G8IbV5FhjhsWuGuFu5a4b43HDshyQo4rct1Q4IEiL5T4oSIQDUx0RaEvBW/vTX7jhTTpc6tWEY4C4WC0HIKWrWTYlAw7khKQIpAiCAonezOTCJsYhTFS6uuwdfuMDdpChjtx9jhsTGFmN9/edZGb7wqfwOVBwcoTCCOZOoHMNROZcAKhX/AKr8D5Hv6Kbn5w8Yadu5C5A+Wsudjhs0IGR6CzB9s0sWML9mnh3E5YH4LDEdgfhuNRuJyG8wl4nYT3abiehucFuF2E1QmYHsE+AxgaYrs2jmrB+wjSrFDgj85EvHuCDznovw+MNxqM1G0br9tOGo1JnQGvQkNQrk6qdXgVm0mtDmkw4tUZc2uNBPXGpGaHgK09Uq5Bmkx4TXvHG0y4jbtJg1F1ONihqI0CJwyVISgPRKk/in1RFgg2EwX+yPdFrjeyPZHlgSwPZLkj2wM5Xsj1RoE3inxR6o/yQFQGgx0CNhMcFqrCwA5Heyre58qMVi0dqVwyXq0/zpnFY4NbI8lv3UWeniddxoLmGWTIg7QZjU08RG4EeWfFe2cx+s6TDJ0Y7TxIOk+QnhOkw3ikQYPbaijoOkh694x27ie9V8lb+9HuY+wUcCJQFoCbEVQWUz4oTiUkZUdIjHZMnHps/DLPQNx0RbobEp2Q6IgMN6T6yMRFrE24uTc5fff1W/uu3dkfn76LmaDrFbbRxnPJRfuZFxwlL9jAzBaWzqJXHabY2yDeA2VRKGWhiImCYDx0R0MUPqUtSdVA7AJayJKpnjJTfGgSPtJSDuJCngzRKFlGxFRqpIRwhLRohRR9mEF7Pku0d474K4XpWQxGgoTwDQYtRUIiRYqeSBXNUaANrV7wSk6sWES0mkrpnkN7s2r6BxXZ1+tlB1TkBtRmf1g9Z3CB3MBs2T4l2ZezGIOrZrxVX9CnPoe/emGvmljzUYzcUiPsvaRSizSv/FSC71kgtYrDmQse+SLFBcnOiLPCNTtcs8Q1y3/Kzr+nEUlm/3OkWeGaOa6ZI8MCGRbIMEeGOW5Z4YEtHtrhiQOynJDnjAI3FLqj0B0cX1T7oTYAzaHoisXQLXzLA68CpIYiqAC3BLxS8KvBb91Eeq+Q90zSe/FDAUgJSDa+P8LPKvysALcApHP+7YCZOqpQUYfKVuzaI3T8pNQFU1jayTu5zff0XekXpBwYupEZsTU8QjOMpRHOXMcMWRccoBwQqBIYtN4veJWn/0I3XyVHb1i744ojzlvjpKno3tPT9PZR1A2E12ymrNggvFRFSFldRFt76j59/GmIv3bh6h5c2IXLJri0B6eNcWY3Lv2Byydx4igO7cQeQ+zQh9ZWHDZExGUUeaMzEW8e423WBMIG47F6I269kaDeUFCjx63awq/cQqq1BFUapNaANO6eQMivMyI1+gK2Jqk1Io0mpO0AaT1Inh7ruTOvNgKVwaiJBJuJiuB/QRgAThhyvZHjNSkw0x1ZHsj2mEQ4sTug2A9lASgPRFUwqoLBZoIThqowcFhoScLAI3wtVhqpmjvK0RrnzOJWgVsjyWsxJF2nSacRv2k26XclHSZjFRgvxkgdyBsLwQdz3ntPMnB8pOMAv/0YeX6cdBiPNWnx2gwEnQfIi128roPk5RUybMXrOV6XDjYLFUF4EE6JD5MJS1wfmqYXEqORELUuIXIu0xc3nJDhhusuSHVEhiMSnRAVtCApw3ACYcrtffHpu8IS9X1YavY+Ky47zr7oJHXRFuZ2sHQWNXcUcrBFohfKo1EUguIg5Pkh3w8cJl7FyJackQqciyQVOQ8pIcepUz2oNBe6qIe0CJNBjRSnxVKFWVIixTRqvyS1R0lkaLZEr7xsFkMqQUL4pgw9QVw8gSoRJyF6X2ba86Wzh2fLFFEopVTRJoVpL5ZSh9ZKD65l9K2d3rdeaXg54/ks0d4Z4u8Wyr9ZotC/Qr5PRf6V6vQPa+Q7t+Cz3yJSoEsajEntps9ZGCvBaB74ZeJdadQbzkh0RJITEmyQ5ohUK1z71X35eyr4f4k0C1wzR8rV/xlhpv2/ISx2+3eE0ehPx6cn+FkIbjnGijFWBG4ZeByMN87jP91HBmzIWxd+4zJSDpKLkSyMlGG0HCQfpHNxsoeCujLWb4aqJkxMhP44JnbuMixs5Rxd53n6rvQNXBvE3MSM2DrRHWWFqU4g9A9Y6x+w2jtgqZuvkpO3pK3nVAsXXLTDaXMcuSRqclJcZ4+Y6g6hJeuFZq2GwnLMW43VytDagD2bcVwT53bgpB7+NMBpAxzSwlF9nN6PM4dx7AAOGMHEANt0sVUN+/XBPI98d7TH4/UjvM/GwAOAX29CGk1Iw87xav3xqi18zlbC0STVW0i1AanbRRpN+PW7uPVG/DoDUqsjqNYgzXtI817SvJc8+4PfuLM4GJwwVIWiOhxVoSgPnERY4ofyQHDCJu09cZuMzIk06Ilc90mEpX4oD0RlICqDUBkEdgjYIeCEoi4CTbHoSsObLIxUKoxWbeRWThdUYpwjw2vUE3QcFrRv4zXME7xyIt37xivBLcS3KpABU/LJirxzIX0HR9p281sPk2cnSOdOXqsuv91Q0L5P8NSAPDtCnl8g/X+RvtOtt0SqWOAwkROCa0zRyMTl4elbIuJVroUtTg+kpnjgtjPueeCuB+674Z4zku0Q5UWLS9qSmG6UfGNnQoZxTOqOsEQdv0g1R78Vl51nXnJmXLYT+huhkz2SfVAejdIAlPgj0x1FgSj0Q0MgepnKzHVIWCPtxxBxFxb1FJd0oVHcpIQDGKLhVEo8VSyULpIjIfGCSn2pSHk3R6pPXvaRNC2WOjVNjh5LEWOJi0bSRFOoU2tnTx9eOqeITiumirGlhDtmiPYtlhxYLjWwTK5/heLAgmkvlYReKYj2z5AYmEN7vVL+3eaZw5sVu9dNfXNuBnmyjVurO96widTM//wI/Fx8z8ObxygNQbI1UhyR6owEG1x3QKoVUq1wzeL/1+F1c6SYIcUM6ebIsED61UmEj2zw2BaZ9shxRJ4zilxR4o4Sd7B9wPFFbQCagtERiVfJeH0HHx/jay6+ZWM0D/wScCsxUoPxVhXy9AD5GEL6DgjKwc8GPx8/C8EvASmA4Nn6UBv6hhVYvxHqOti9e8qRw1P/vIir1jL2zrM9fFZMIAyL1GBFaodHaEaEbQ4LUQ3yX+vrt9Lbb4m73wxHL5qdu5C1q4iZPc5Y4Phl7D8rbHhsmtYuiqq+yLz1UxVWQnwxGAsxZynWLIfuWuxRxXENHNXEcR0c0YTxBphswVFjnNyHg3tgYgCTHdimjY0bsEsDfqeR64ymaAw+xPscDDwC+PX7SNMB0rBzrFJjpHITqdEitdp8zlZSu480HCANe0nDbn6dEa9On1enI6jT5tfvIu0H+fW7SNehpzdnlQSiOADV4ZNpsCwAZQEo9ZvMhOxQZLsi2xVZLsh0RpbL5NKOXPdJhMU+KPVDRcAkQnYA2METxyfUR6KWhbpovLiD76WUHxXLxiup/ApwqyTH6zV4rXtIi56gfulYjyPpOTJWibF8fC0DeXmWfL5K3jiSF7vGmg15zQfJ0+Oka4+gfYegw4jftpfbqU9e/EGenSEvzpHB0913RdnhqGehwA83gxAVIxuZsiwpdll6kPwdN9xzxD033PPAfTdkeiDPE7ddEes7NTrm95jkbXGpOyKTt4Un6ITEafpFqjn5rzR1nXPZRcbUQcTCfhKhiyNSfFEejaogFPsgxw25Xsj2RKEX3lxXuXcawfMRqiQcIs3wpkg7ios5SQl7M0T8qVPjqWIBdOGH4hLdVMleRYn3s6VeyTIyaMLhNKEEBRqLJhpAEw6REQmXwGMZyosVCyvlZEtolFKKUJO0yKtZ9NfzZV/Pm/563vT+GRKvZ1DfKEn2SlN6GKLvV8h/2Tyvbz2j0wQkfTup2P65bsOnurk/SkFKMX4PXwrQmYYHrki0QLoL0lyRYI1k60mEqf+SDP+1KP3vuPZrQphu/k9v5pYVHtvisS2y7CYRFruh1ANlnqjy/QdhWziexaA3BYM38PE+Pj3A98cYzcNoEUYrwK+fQ9p1yKA/eWf+vVTyexZIMbi5IMUgxRjv0XG9ILxqMdaoQFMHu4xw6AD+vIirFlL2jrM8vZb7B6wNZW6OiNSMjNRhsbQiwrYwgzcE+q/y8l3k4TPLxVvGzl3M2gVX7SXPWwqfuIxDZ2ByUnz7IZq6kbiKzrQ5qmLSq6aILoTYfCjMx/LF0FoDk404roFjmjihi0NbYaCMXWo4thOn9mHfTuzejt07oK+LDethoA6f43jigNoI9D3Am1y8egiQ+oOkcT+/zmC0YvNI5SZBnTap1xNUa5HGw6ThEGnYSxpNBPWGvDp9fv02fpM+t3EP6ThMOg68zV1XEggOC0X+qGSiMgRlASj1R6kfSnxR5I0SP1QGI8ftH4RPnCYpZrkgzx0Fnij2QZkfKgLACQQnEOwA1ASDHYDaEDSxUMcEJxTdqfiUh6+l8uNlEJSDWyU5VrduvGWboEWL1P8+9sKFvDo5Uo7xAnwpBek8RD5cIUMWpFtvvHG7oGU/eXqcdJnwO3YIOoz4rbvG2nVJz1Hy9DTp/oO8Otx9GxwWGiNR4ou7fogJRmyEdCpTOsMdt+3w2BHsRLmyGEamP7Jcke+Jx35ICqJERi2PiNeMStQOT9Rixm8NjNnsG7HBJXCluec8Uzd5M6dplg4wdxQydxRydcI1P5RFoSoIBZ4o9METZ+R5I8cN9WESVd7CURsQMg+e4sJuohJONKqtlLATbYqvtHCchKinlMgNGrVdUrpXif55hsxzBjWeCn/ZKUxF4QAFYXc5IVelqZ7SiKYLVS6dxVFUKqZJFIsK1UmIvpSXGpolP6Q0vV9B5pWMzEspqSFZudeK018p0l4upg9slOndKvM1cA4p3z1WrfGmZtHnanzPB8nHz7sYr53blo7bTrhmiXQXpDkj0QZJVv9kwn89Fv5fEKaYIekKkq4g7SrSzZFuihtXcdsST2yQaYssO+TZo9AJxW6o8ESlF6p8wfFHTSAag9DCRGcEnsfhZSLe3MDbG/hwG18nltAWQFAtR9rUx3ocyXvnr1XKX3JBKkByQApAyvC5e9uVo1j+G1YpY6sWdu3Akf348yLMzOl2DjP+GyGLqR4SuN7fd4W713xXT0UHdykbZ2FLB5wzp5+6LH7oDHafEDY4StHaQ9+oT1ulIa64VlhiGYTmQmg2GHOxZAE012CvGk5q4ZQuTm/HEU0YrsOeLThlgjOHsNsYu3bAxADb9KaoqMBAHZ7H8dge1RF4dR9DWei5D5D6PaTOmF+tM1qlNsbeRGp1SL0hqTEkLcdI08GJTEjqDXm123kNhoKWPaT9GGk9SNoPVEegxA9VYSibmPIFosQPxT6TAvM9Jl/05boixwVZTsh0nIwsJ2Q7TyIs8UKZH9j+kwirA1AbAk4gakPQGI7aUHBC0J6A4Yf4VIyRUgjKwa+UHK1dNd6iQZq3kgbV8X5v0nfqWzF4RfhRBtJsQob/JL1XSJu6oEGXtB0iz06Qzj3ctm2CNkN+6y5upz55dpB0/0E6DpN2o87rqI+aRPjID0k+SPRFmifSrHHPEWUssdHuc5+b/+h4uK4oCNkeuO+N6AAh79C5IZGbwmO3hCVohMSq+0dt8mGpuAX/buu3xMxD0dyFZumAqw5TzOzh6oQUXxSzUOKPHHeU+E++Ls9xwwNblAcg6/zUSBVYicBGeKqrvIwVXdicAl9Z8QhxUUdp4Vi6RLWk1DMF2nslqecytGgGPObBdTZc5k+xmoO/5sJqFjwYSJsnWTBDIZMunikqXEqltMgxupRkO+Skm6Wp7bIzS4SEq0RFns6XbV9KqVuL/sPTiZsKKVYdzV/LbdzytXrezzL8yMVABkbyRUjHlvbbMvfccN168n5Mqi2u2/6vjZn/LZJNkXgZiZdx3QxpV5Fuigwz3LbEE2tk2iLTFnn2KHBGqSsqPFHlDbbfL4TBaA5FBwtPo9ETh/4U9Kdg8Dpe38Dru/icCX65EGlW5j6/SN67j7fu/lYCUgaSB34extjo5mw9sANLf5uyYjW2boWhHg7vw58XYX6V6ugww8dzeXCAcnjo5ugIzegI7chwjfDQzcEByj5eS5zdZjm4TLdykLxqI2ZqKXr8vOTBP0VNjgkZHBLS2yeubkRdrUVbvFFMbpWI+OIpQnMhPBtyc7F8MXTX4aAGTuvgT32cNcARTexUwUEt/LkPZw7BZCd27cBOQ+hvx0Y1GGvC6wQe2oLNwrNbePkQHTcAUr+bX60/xlbnVm/m124V1OiR2p2kfr+g7QivaS9p2E0ajUmDEb/OiNe0l7QfJZ0nx+p3D2WuKfBCZQhKAlEUhLwAlAWg2BdF3ijyRoEnct2Q544ib+Q4IdvxH4RZTshxQY4LCjwnB0SlvqjyAzsANYGoCUR9KGqDUReMhlDUh6AhDB1xeJmB94X4WQJSBn7l9JHapWPNG0mrOmnazH8dQPpOv8sHKcV4Jbg120jfUfL8DGlSJg1apOMweX6S1757rEWP32pAWoz53TtI117SfZS07+NWb2xKQGMMGiOR54tMf9z0xA0X3LXDbRsUs8T7K7eTn4FkPHi0+0Jt6qz77khxg783rP1m+ASvDo7YGByzOSBS1ZOp7Bb8u0vgSjv/pVc9Z1i4Slo64C87/GUHVyck+6AwDHl+eOyBbE/kuiPLGQWeuG+DXHeUeePuH/CaD3MKbKQkrtLF/qIIOUtNCxUXsZISDqVRiijUZgblrQK9R0kycc5UN+Up5r/BajnOLMThebi4GFZK8FFC2gzJJCnRFHGhe1KUfEVGiaJULkMskyacw5C6R5maqyhavZ5aqQnOYQwHzSS5WjzOb+9y5AU167lls74+xOf7GH6A8Xqt95y1tSlS992RYYd0W1y3Q5o9Um2QYoEUi3+rQv/1/cR/R9IVJFxCwqXJ6zJ/I8y0mZJjgxwb5NmjyAll7mB7otoHHH9UB6A2CI3BaGaiPRxPo9ETjxcJeJGAl4l4kYKXaRi8ix8FINVyvOd7ybA9eXHu20Q/phBjBRhtRMGDxZrrsWSByIrV2LIFRjo4sh+nzv8nwiiWRhRLi8XcEhaiFui3xsN9oZ2jgqWNlKkF/fxlsTPnp+09Ttl1RHjbvinaJsJbdlKU9cSXqonMURZVWCpGXSBEmTeFNg8z52P1MmxXwTEtnNHDmR04a4CjWtithqN6OHsAp/fDZCeMt8PQAHr6UFPHTh14ncRdW5QEoiUJbamoiQZIvdF41ZaRyg28GjVSr8mt1eXVmJD6I4K2I7wmE9Kw8xdCY17jAdJxitd8+GeNUYE/SgNQGYLSgMnpX6k/inxQ6IVCL+S7I9sFOa4o8ESWw2T8LTDXFfnuKPJAsSeKPVHujcpfpUhtEOqZqAtBbdCkw+YIdMShOxnv8jFaNIlwvGbRWMs60raFNGuRdyGk7/SbXJBy8NgYZeuSF/tJ93HSsIY0aJGuo6TnDLfNZLRpEiF5Zijo2EW6j5G2vT9KV0zckmuIwCMvZAXgvifuOeCRDZ44ofXe7+SLzbchZ8JlkWH75jur7nog1hmeXrjqP8vVZ6FvyO/+Eeu9maudA5c4+i9y8Fto67fQ3GumpZv0BEJTW7g4Iskb+aHIDcAjL9xxRLYH7lqizIde7IMnzsjyBtt9xi0jhatUnBeeYsmgWtEoFqLCweLCplJTfahimRRKHU10WIHWM082eZmE+xbhiwvx12ocWQrjeTi9EpfnwUYOYTMowQwhJl0oUZZye5bkbSVaqszUBNqUCFE8+I1eqzu/bq982QnUuOP5LWpPnvjLLPyonD1WspibLfk6HgOJIM1bxzqOND+QyQ/DbVfcccZNB9xwQJo9kiyQbI5k8/8UGH/5/40w9co/CG9ZIMf6PxFyvFDj+58IOyLwNAY98eiKQ1csnsWhKwmdyXh5Ax+ywC/D+FNN8uIv0vfX13KMZ4FMbJppR0aC1JolWLKAsnLNFA11GOng2D6cOvM/IIwM1/gboZvrfGs7GTNz+vnL1FNnKH+cEDc+IGKwV0h7N7YYT9m0Q/R3LcoCFWGFlVOmL5hKnyskMRuSc6A0DysXY/taHNmKs/o4azCJcK86jhvg3CGc2o9du7BjO3Zsh952qGpgtx48TuK2NbK9UBWBykjkBwKkbgO3avV41Wp+nQqvQXOsRodXt5u0HR/lGJLW/aTZZLxuO79xJ69uD2k4Qp6bjZZptMZTCrxQ5IMin8kVWmUBKPJGsQ+KfVDohTw3ZDsjy2kyAU78mIh/ClEflPigwgeVv+qQuhA0haA+DLWhqGOiKQLN0WiKQksMOhKqQkXWAAAgAElEQVTwIWve13LwSiW5JVTCWUsaDUbb6eTZYfI5id+r8b4MpAykaA6vdDp5rs3vPjpat460G5FnJ3hdx362Go226gu6jEj33m/NJrz2feTlUdJh9P6JYls0WiLREYtCf8mHTnjigCwXxF1Gbsw88tH3x6dg8s6B23WS9J3vebIi2QlBzrC0h5nXbCvPWU4Bi1yDlzn4zbX1krf3UXLwneHgq2DvybB3lrCzEza3nWZqI+7ggFhPPAlGjjeyPPHEDY+ckemMrIlwwj0XlAagyFWapSN8njLlquh0F2nFS1PgTBWylxWxZUwNEBHKFJ3WJa/UOk8pby7tgjIurRbaTsee2TixAjtlpxxSFPpjHpzX0s/LwH72FLfllGANJT8tacuFsJ2PK3OnJh6YWeKqVOCFHE/URuPlQwxlYzR7CmEv/nhPqImF3rszflTvIO+sOrI2347A3SDccZ9cFXPDFtftkGiDZMvJeX3C1X8m9Qmm/+t7wolIuITEy0g2xfVfbdKJC9xZDsh1RJEzytzA8UatH+r80RiEpmA0BKI5FB0R6P4/pN1nUJZX9+jhHw9FNBo1MbH3GEs09o4VFOkdpPdepPfeO9J7k2ZBsABiwRp7RVCk2E1iEk00xQrc5wOP8c17cs7MOf+Z9eEZPzJzudbe91p75dORT08h3QXi6Mqnp4SntfzZjND6tdCqK9wxeXWad4cRWnh3COEq7o5fz/uKuVORW8TaFagpifR1sbEVubuODAmcFh8zPyVxaVry8oy01Znb5TK3y2WnrUmKmx8TOSUkcKS7m5St8wgj6y836cpu1JRdqypaqSS9ePOgb+UHT5OT/mIBMjMYNhXZqchMZugERk9i/mzUV2Auj60STuo4KmK+FpMN2GhgY4CZLlu0pFRV0VBEWQHFDegrEmJOtT+H48VxJA76Lix8f+7bt+e/7b289P3V9e+vKgvXdYU2M+Hm1neXVPuuawhtuu8uqfZd1RPaLITrZh1lX55O4lgMZ5I5nfSRYkuMuBb9nyO8ks7VjI8I2wroKOGPIyv+OM2r47w/hXBpnnBt45tbY4Uec+G3rDedy389jXASoWV875mJwp31QrdZ7/UV/a1bhFsmQpd1f7dhb4fa+zbV3psafV1bhXvGwh2t349/013BnSI6CrmQxuEI9vmzy5P6EGpC+PnCVuGX0L5nYcJdW+EHF+GhzfGCodv9SIvGOxDPiDEe4aP9YycHxk/2ix7rFf65d8RIn8jPvCNG+oWP9AuS9vCVcPOWcfYa5O9HfgQNyTTH0hjFgXD2h3AglMYQcRyOYX8gtwom3kiaGzQLXfAcMtZ3yGRXycEOskOdPhkePWRk3YjR58aObhovnf8lpjMxnjJUadhQhZESa4YwC5aA0jAC5fFcQvwGEhVkA9dJOi3AfDzes6QSNlNtLzoSwdFojifSWsyjfRLfHxS9PTrtfikXU/hx73ihw+D9Dd13XdatjSvLU9gRS2UoNf7s9KHKh3Jfiv9jgPD/gvB/11jiQqmreIqixoud3uIG7n8gjPkHwusptG6nI5euAjoL6czjTi4dOXRk05FDZyFPdvKikffXxvVeURRuab0+xbujCM28P87v5zDV/XLWZOZNY9Vi1q5ATRk9PayscXcdGRwwJS762+SEJalJyzLSVmelr8lKX5ORJpcY+210xOQg/08dXbC0H6JrOnKtqmilosQyBYlFG0XfrJOasVpq3BLJT+YgmsaQychMRmoSn4xnzGSWzEFzNVaK2KvgrIGzCuYbMJPHTgtbQ8z0PiJU2cSWjegrEmpBtT9NseKn6w7HwuszU9+dm/Huwvy3F5a8v7yh/4am0GrY32oqtBu8vqAotGoLrdp/frdJuG0udFg/3Lf8WDSHwjgey3fJ4juY47EcjviI8Fg0h8P//xFeS+fqdq5ncjOHtlzacrlVQFcpfWf1/zrLyyO8O4lwdXr/tUVvbs0R7jkLz8JfXpv+xxn6jiMck+0/O633hpzw0FK4vkpoVRZumQpdtsIdk95bWr3tmsJtA+HBVqFd5c9T8+/u5EaueGnzuRQOBbDPj9pAKvz5rvQr4Scf4Qd34YmL0KkpPDR9dF4xN5boEJKSRrv64Bkk6xY0xCN0hGfYZ9uCRjr7DXH2G+LiP9Qp4JNtwUO3+Um4eGDvJmXjNtjLi8xQ6j+8VrY/jP0h7A+hIVgczSGfNYRwMZOH1WO+CxsXMgcdMGGkqaSEkayUyTAZJ1nJKBnKx3NIntM2sgaTREuRmInEtxKskJVaIT1qqWiw/Aj0F2O5mG0rsV+C6WLcFYnVG7LTee6ReI7EcTCcA8Eci6E1nwe7Rj2tm3g+jRt59FRPEi5pCj949nfb/HrT+FjV1zmxFEZSFsauIHYFUONHZQDlgf+CsMiVov/zmbDQiSJnip0pdRV/LdzpzS4fMcJDwf+N8HIC15L/ibCI7hI68+nI4XY2t7O4nc2dPB5W8mwfr87z9sIS4fratyd538LrZvouDLt9gHUrmTKOuV+xeokYoYEBFta4u44M8p8cEzk3MW5hatKyzO1y2Rlrs9LXpKeuio+dExk2wc9viL0DJpYyW3RlF29gwRrmyfHNSomvlokmLBSNmIPMdERTEE1AcgKSE5CdwNgpLPsG7TXYK+OohqsWLqpYymO5GXtdbI0w0kNRU1JVFU0l1BRRVmCrshiheJ1TDM0x8LLl0zffTXt3Yf6bc8veXdoo3NQR2ozfXzN8d0Wp77qacFPnzcUtby4oCw/s+67qHU/mSDRHojmRwIkEDkdxLJaTiRyJ5li0+ED4P0R4PYNr6bRm055Hex5tedwupLsModXt/aWvnx3m7UmEa+PeXpve27lO+N5f+N76+ekhb07S20L/MYQLc/66sl54bNV/dbnQoSP02Au3LN/c0HnXpiF0Ggp3rYT2DT81j+2qoqOUWwXcKuBmPpezOBFAcwiHE0Wlgfx0UUd46Cg8sha6DIRulQcnluwvG5cQS1zyuOikSU6ebPPBwVvK0UfG0UfG3kvayl3Kyl3Kyl3W2mOIo/9QR08JexfMHaVMHWVc3EgJZHes+GXO/WHUh7AvWBwHg2gIkjwaTUM4V3N5cWjJ5YSvI5bjNBYNSTRk0RkhbfGprOtQUdhE8jeL9rmOd1s+ZpUUCyVYIsuGUZLyn42dJylaPQrjlaJgzS+SjT/NtKMkhMu1i27vX3y75uuWDBrj2R9GUyRnkjifyrlETkfzXbrk7yeUhDu2Qrer0OPWe9f1xxtGu/M/S4kmI4LiMKrD2B1MTQCV/lQE/zfCAYFFrhS7/HsUOlHo9O8I/7scjeFyAhfjuJrE9RSupXAjjds5dJdwt4yeUjqL6MznTh4dudwp5GE1P9fzxwnenZsiXPr61WH6W3hznNdXxu9KY84Mpozj21msWsqaFSgrsdVIjDDQb1J0xJyE2AUDCHMy12Wlr0lPXR4XMyMsbLSvr6ytHbqmovVqEjOX8/VSZi0VTVsiFjjoK6SmITEVJsAEJMZ/QDgP/XU4qOCkjps2rmpYKWCphIMe1obo67BZQ6SigrYKmsqoKWKkSrjlPxAeioZfj8i8Oj357flv355f9f7yJuGmjnBz69srOm8vKQg3Nd9dUX17UUXoNBe6LO7vW7QvnJOJtMRxPJ6jMTSFcyyWU0kcjuJolNjh0aiPCA+F/j8jvJlBWya3ssV/9Fu5dBZyvxyhO1i4uf7nAYRXp7+5/oVwX0/4JUzoXPXiMO+P03eMdy0IF+e/ubpZeGL17spKoctQuOvQ12r6rlVb6NYXurcKN7SfNo3oKKc1n84iOgu5XcDNXM5v50wIJ6LZH0Xj9kHCY6d3nUZCj6FwU/mni2sbi4fkpg9Oy5oWkfqVf8xod3/c3LFzxdYFG2csnGRMHKSN7QdttR9q5Djc3H24hZOMuS2GtrL6trJ2TiT4Ux3JgWj2RVIbQl0wdUHUB1EfSH0gRyNpDqcllsvZPNgt+qVx0p2yoYeCCV871Hm2xNbRmH4pchgr7TRRwm0m7kvw34zVAtzWYCuHxixWDOVbWYzWUR6qWOMnl2oweLsphe6cLxt6eye3i6mPpsydbHOKbDkYzNVsnu6d/KZlpXDLUrjvJvR4CHd9hB7PN/fdu85r1OQPiY4gLoTMQEqCqQmk0pcyb8r9xU9aDDRw/42w0EWc8QbiXxEOnAmr3MXl6N9ta81BtIRwKpzz0VyK50LsR4TX07iVS08pD6p4VMO9crqL6S6ks5CuYh5U8XQvL44iXJQSvhv8qpG+o/Rf5MGpCT7WTJrEjGnMnc3yxaxegeImjI2x+YAwKnx2QuyCtOTlWelrsjPWZm6XS01bEhv9VUjIKA/vwZa2aBtJr1ISTVvI1G+ZvEA0cZ5o9ByJT2YgNQ2mwBQJJsAkRBOQncCkqaych+FaXFRxUsdDC1c1rDdjoYqtPmaGaGqySV1CRQUdVXTU0FTGRJ0Iq4/l6N8IR/x5YsrbswvfX1zXd3VL/w3Nvusary+r9LdueXtJ4c+zG4Q2feGe7bNj606n0xTLkTiaPrRfN0VxJI6j8RwMF9M6Fv0/RdiWSXuW+EjQkc+tXLqKeFiFcNdfuKP1SwvvT0oJ1xa9vjFSeGwr/BIqXOXVYXqP0NvC2+P0X1zc167X98D47Y2NQsdW4Y5Vf7uZ0G0oPNAXrq1/emBiWyEdRXSXcCePtmw6i7mRx+FIToRxPIZKb+42LhJ+sOt7YPbrFaUfz244vHteee74wsI5mQXf+seM9gsfGRgx3NUNW0eRpS2m1hhaSetZDNEwHaRhOlzT/DNt6+G65tJ6ZpJaFrJaVkOtHInyoTyCfVHURVAbwu4g9gaKoy6AA6G0xHAyjgtpdFfz/X4e7+OHfTyqndxW9OmZJI5HSRwKlarzk97lLdrlLZNnT6kzNf6U+xJmgPJUFKYR4sDh3BX1kV9n6FPjMqLGk8OxouORnA2n2p+6UKmzqQvu79r4e8uadxeXCtfWC226wj17ocdJuO0i3A8QHvgLP/i3nd6yI4uIaMmIIBL9KAigIlBs72+E4iee3D4IdKHAURwD6v7WKEboKHZY4UqlG1Xu1Pmyz5+GAJoCOBrEiVDORnIhhgux4iuZgdvRjgIeVPFkF0/quL+T7gq6SrlTTEcJ3RU83M3vzQjnEY7zvoG+Q7y/THMJSnJMnMLMmcyYyZLFrF3DZgXMjbG3wd11ZIDvxAGE21NWDBwIt6esSEqdHx41xS9ouJuHlLk1GoaDVm6SGjePsXMYM5tRs/hkBjLTYQpMgPEwXpwM/0ZotI5tqrip46mNswZWSliqYWuEqSGq6iiooaKCnjp6GuioYab5EeHHTPji6LjfW6a/ObNMuKwgXFd+d0Xp7SWFV5c3vL+m8OLMijcXNwvtBi9PKVwuGN4US3MCzTEcCKMpiqPx4qmIQ9FihAPJ8H+OcCANdhd+QFjMo2r67tgIXTq/nqbvu6nCtY1vb44RHnu8+dH/7Sn6j9HfhHCc96fou7hY6LZ+06Pz+rbSu9v6QoeF0GkpdOkIV1c+bxjaXcztfHqKuF9KVx7tmdzO50omTaE0h0k2hXI8nv4bKsLDra+7DK40LTt9YHle0YqSinX5ZSvScuZGxI8LjvosIFzW0QNruyGmFhL6xhLaRtKqejIKmlIbNIbIa41Q0Bm0WVtaWUdSyXCwurmshT3hPpREsC+KveHsDmFXILs+IKwNoNaPk3E0h3EmiZ/282Q3NzJ5VMHjvfx+GOEiwhWet9Cxm0u5XErjQhZtxZ+dSeO7TPZFDLddhtpMfC04Wblqb9R07xVEKhCnTmOYxM0cfqzgjzNy788bCNcchDYToU2ut/Wb3mtrhetbn11Qen/bXOhxER7699/1FH4OvnF8Q34yIXGfBwYS7km6L2WBVPixw5eKAPGP/x1hnj159uQ7/DfFjwgdKXam3JkdLlS4steHOh8O+NHoz+EAjofwXQTno7mcQGsa7Zm0ZdCWSVcxT3bxtJ6nDTyp414NPZV0ltFRQlcF93fyZzPCaYTDCM30NfHyNLFezJ4uGjuFr2czaQqLFyG/gc3ymBlJ2ttIbXMZMYAwKX5xeuqq7Iy1GWmrUxKXxqd8Exw+2tNP0tEFY0vU9GVXKMiMm8eY2YyawYjpyE5HZjoMFKJjYByMg/HIjmfyNFYvwGwjHpq4a+Klg6sWNipYaWFngpGhSFkDeVVUVNDXwEALPQ0stIi0ptqfxqgPEQkvj019eXTG69MrhKtKwg2Vt5cU/rog99eVNb+fXfb85BKhTev9Zc0rhV80xXIsif2RHI2nIYJD0eIf+0JojORQtBjhQDSH/U8RdubTXcidAm7n0V3Co2r+bNUTunRenkU4t0C4pvzq5kThse/vD93/PIJwnL4mhBP0nqb3wlLhkfNfnRpvO9XfdOgL3TbCA9u+G/I/HKS7hLuFPK6kM5euPB4U05nLte2cS+F4LAfDhtX68/TAt0KPjnBX68nFjY3Vs6rL5mVUapbXGaTlLktImZaVPScufoy7P47eWFt/YmQipa0noaYjvVldRm6z1AoFmZWbhqxQlJJTQkFVYpOujLKZtImDGGF9JHvD2RUsRlgbII7DEdT7cSKaWwXcq+DHPfy8c9DDnPFPa3hVT38Tbw7x437uVHAjg6sxtETSmsPhcL7bzqmUyR5rJPS/IcyKoxU6TclqXivwXEaoChcKxvx8iJ/303tlgXBdRWjdKlzf/NfV8X9eHfb++lqh1UL43kq4a9HbYS088uu/6yk88TrftLgoGd+oUR5e+DiQ4EqhDyU+lHlT5vvvCAucybUj107scIDiAD+xRgeKHChyosyJcmfKnan1Yq83+3xp8OOwPy3BnAnnXBRXk2hLpyOHW1nczuFuGT/W8uwgzw7xwwEe7eH+B4fdldzfxZ/NvDtGbyPCyS/6mvjxMLbaTBwzfOxUps5m9ATmL2KzApvlMTWQtrMa+p8IM9JWZ2esTU9dlRS/ODpxZmDoqG3e2DliaI6qnswyhcHjvmHsHEbOZNh0ZKcz6CskpsMEGA2jxRRlxzNlOusXYamAvzae2vjo4aaNnRo2OtibYmQipfofCLdqS+hrYqktRjiw4ndgdQevjvFbMy9aFvRe0em7bvb6rNqrFrn3xxe/OLqw/8KmVyfXtpd81hLHkTiOxLEv5OM8xEBn9uEPcSSCIxHi3wMIB6I5mENB4mgO5kjYh+mVaE7Ecjaec4lcSORiMlfSxNdid/LozKeriO5iekq5W8bdMt5dmC/ct/7xDMJpVeG82vNHk4VfEvvalr85iHCC/hbeHOX3w0P6Lq4UHhj1dqi8vLpVuGsjPDIRrq78cR8dReILngcVXEniQcmI9kw687mZwfkYTvrT6D36bNwYoVVP+MG4+9S3+2omFxYurao3Kq1SLKncnF+yLj1nWWLaN1EJ0/1DR7n6YGcna2yGujbrFVm0bugsuRHT5GSnrmf2mpEz1n8+Q/7zb5SGKejL2jtIJvhREEJTCPtDqA1hdzA7A9kVwB5/av1oChEdDKIxlIuZPNjFg53cLqSzkMcV/FLP6yO8PcZPddzM51waZ9JpSeBUIufSOBHH1ezxiQaYLCRYd2hz1vprZcaBa8hW5YwvT8t4UccfB3l7dopwWU64rtV7Q/ttq/L79k197Uq9rSpv21X779n3PQp53x0k/BItfO9+cv+cjAxCQz91dsfMCjsbAlyl07wp9KHChwIv8jzJdSfXjQI3cSGaa0+OA9n25DhQ4Cw+KOY5kW1PrjO5zhQ4U/DPrFjpTI07VZ7s9qEhQKbRjxOBXEvgVia3s+jI4k42XXk8LOfnOl428ecRXhzmpyYe1NNVQ0859yt4WMmrOt41ITTSu4/3x7hQyvJpjJosMXEyEyczYwbLFiO/XqShipERtla4Ow3395oQE7EgNXV9RpZ8cvqqqMTZwXHTfKInbgv63NlrqKW9tJ6RpJqO7FolmdnLmDlPNGUmY6bx2XQ+nYbEZJgEk2AsjIPRfPIlM6agsBRLRTy0CdQmQAdPHZx0sDPCxgxDA9TVkVeRVNMQ6Wmgo4WeDiY6BFuwI4B9kR8Xe/B4Hy9aJr+9uO71hU2/nVz787H5vxyb/vzEhNen5H46OPtGvsSRaBrDaI7hSBzNMf9vCJtCPgoUI/wwQnY86h8IL6X8C8KeErHAu2W8ODFYuO/62wWEcxuEi4q/P14q/BT3/ur0903i5eZvj/HmxBjhygbhgcn72+pv2kyEe1ZCh8az5vGd5dwppquUjiLultKWwYMS7hZyI42LcVyJljjh+WmRKb8eUBC+d/v5jNzRys/2Vs4qKpPLq9QYQFhQuiEzb0Vy+oLoxBkBYV9s85GydxhkbIGaFms3MX+F7LTFsuOWSI5dzrTFgyYvHzJ1zdA5CjIKOiJHexL8KQihIYR9wewJZmcgNQHU+LHbjz2+1PtyIJAjUVzN50Etd6u5kcW1DG7n8KSGv5r56yjf7+ZqFqeT+C7145jYiTiu543LtMB6CQFanzSmr7lZZR6rTIEWZ3z5vphfa/l9P2/PThIurxSuq/fe0H7bqvq+TamvTaWvVbv3ltYAwt67gcIv0cIj12N7v0pNJTBQxtkdS1usrHGzJ8yZ7R4U+VLoTZEXhR4UuFPgRok7pR6Ue1LsRqELeU7kOYnJ5TmR60iOEzlOH/7dkQJHcVbc4UilO1We1HhS70ujH6dDuJbE7Sw6srmTQ2cu3QU8rBQjfHWE34/x6xEeH6Cnmq5SHlTy027e7OXNfvoO0NfEXy3sjWfhJEZNZtIUJk1h5kyWLUF+PQMI7azxdh8Z5D85PmZBWppceua6xPTlYYkz/aMnuYWPsfeVtXWRMLNBzwhNA+nN6jKL1jB7gWjybEZP57PpDJoGk2Dch2Q4BsYwbAxfT2fLMmyV8dIlWJcgPbz1cNHDzggrE/R1UVZmozKqGmhroquNrh5megRasSPgw16dAYS3d/L8+Jz3F+VetMx51DDqcfPIRy2fdDXzYPeUixkcCqc5kmOx4oNfYyQHw8QhnksK++jw7/gHwkCaAmgKpCmQQ0EcDuHo38kwlu/iODfQr5TK1e20ZYgRdhXQXSxGeK+ce+X80IRwN+DVtTHCxTnC5TVvvtcUHoe/PkP/EXoP81cj71roPT1duLpZ6DZ906oh9FgI3cZ/nFnRUc71LLrLuFfJrQI6i7hbRHceDwu4mURrDGc8JSs12OuGcMda6LE/XjyxKnPUnpq1lbUaeTu1i6sUi6sU88vkMwtXpWQvjk2dFRA5Zpv/ICfnoSaWqGmxWp7Zi2XGzJIaNYvPv2XaPMlpiwd9tULmW3k26+LiSHIQhZHUh7AnhF3B4p7MKj92+rDTh51e1AVyJJrL2XRW0J7P+SQuxHMpgXsl/N7EqyM82cXVdE7FcypJPDB9Io7TsdzIHVvsjKMc3qpS+5KX3t5tmWv8eak+p314mM+znfy+nzfnRvVfWSLcUOm9of3upnpvu1r/TZ2+Vr3+Owb995x6Hwb03w8Snke9u+fQUDMxIRFPP0kndywdMLXGzAJnS0KdSPalyItib4q9xA/CF7lS6sUOX3Z4i0o9KHAmx4EcB3IdxfCyHcl2JNeRXEdxpVpoT6E9ZXZUuFLtSaU7u9xp8ONMJNeTuZ0lFtiVz91iHlbycz2/NfH6yLBXx3nZwg8H6Kqkq5hHVTyr5+1e3u2mrw7hOE+PE2nLjLEMm8zEyUyayszZLF+K/AbU1TA2xsEWH++RoUFTYuPmpaatTM1YGZsyPyBmqmfol/YBX5i7SBrZYGSBgSl6poPUDQavVmTeCqnpCyXGzGbkTKT+RjgePocvkRjNyDF88xUqq3FQw9+AUCOCjPExxsMEJ1MsjNHVRkmJdUqoqaGtia4uBoaYGhJgTel/IKwLh4cHxz8/MuP54SmP6kT3arm3X7JtD6eKOJUgbsI+nczpJBoiqA/mYDgHQsUxMJHU/M/4T4fic2AATQE0+n9EeCSUY+G0RHI85h8Ir6XTnvkhExbSXSwWeL+C+xU8OYjQE/ru+lLhIsLVlcKPNsJdpz+bEVroPczvDbw/Tt+ZGcLFzUKnydtWXeGu0burCo/2fX49hxvZ3K/gURUdRdwp4EEptzLpyqAnja6EYVXq5MjxonmhcMeko25p7fYpu0pXVVQrVdbpl9ZvLarcUlylXFixKad43fa85Qnp84NjJnsEfuLqNszcGg0dVssze4HUmGkSo6YzZh7zFg/6dvmg+WulVmxGwxAPd9IjKUtidxg7Q6kJpiqQKr8PK+982OVLXRAHwmiJ41wapxNoieRsDN9F01nIy0ZeH+WnvbTlciaRE3G0xHEillMxnI7lStagSm/cN+KpKNqTMKdjj0Wl47QSPU568TCXZzt5uY8352X6rywUbij13tB+16rZ26YjtG3tbzUV7pj23XXufRggPAwSfg37q9N6T/no6HhcvXB0w9xRysRWxtgSMwucHQjwIMuLPB+KfCj2IM+JHEdynClwp8xDqtiVAidy7cmxI8eOPAfyHcUI8xzIc/gHwmIbiXJnKr2pdKfcmQM+nI3mSqIYYVcePYXcK+FxjRjhm+MTX5+Q/u0Ij+vpLKOrmCeVvNzLm1reVyHU03+B9kMYKDBxtOxnkxg/gYlTmDmbZctQ2IimBmZmuDjK+HiPDAudHBc/NzF1UXzaorDEOd7h4xz9h1p4fqljg44ZW80wNMfESqRvLq2ozXJ52XlyoimLGT0XmRkw4UMh+hmMQnY0X4xj7izU1+CoSYAhEaaEmhFggZcVLlZYmKKtzRZl1iqiqoqmJjq66BtjaoSfNQV+1IV/DB43jrtXO+R2JTdLuVnC1VxRSyL7Q8VXLMeiORpNcwQHPiwiHei6Gmi8agr9ePYbuHT52+HH8SX/j9H0YZ76aJg4E56NF89PXEnjesHryWwAACAASURBVIYYYUc+nYX0lIgFPqjkYRU/NiL0BP91dVX/OYTrG4Qfnftub3m9H+GoOBP2naD/uznCJWWhx1LoMH5/TeGnpuntxdzMpauIe2XcLaW7mO5ieoroyqZnO3eTOevJdjmuhywQHlnePbiwPIpd+Uvq92jllygV79Yp2qWdX7WloFopr1Ixq3R9WsGq+MyFIfHTPUJGuXl9ZmWHtj4bN/PNIsnx0xk/k5lLJNasG7ROXna9okhRA2MLAn3JiWdHOtWRVEZQGUJVINX+4pV3FT7U+FE7sGIylCNRNIfRGMzxCOnT0dwu4NlBXh3h1wN0lXIxhZZojkRxIpZTUZyJ5VwKe/zxVcRjk1RV1JRbe4z3es0t1KbFnUd5PN/Fy/qPCPtadd7f1Olr1xPajIVWC+GOTW/3tt6HAcL3QcKvwb+0GVYWjgyLx8lLZOsiYe4oZer4iYnDYBM7kbU99i7EuJPiRY43+Z7kOZNlR6YDGU7kf5CWY0e2Ldm2Yor/J4RF1pJFDlT7UuVDmRO1npyK4Hw0bekfxpeKuF/Ok50828+LJvrOzHhzYsTzZh7upbuCeyX8WMXL3fy5i75qkXCQV+c4UMbieYweK/vlBEaPZfxk5nzDypVs3oyODpZWuLt+6uc7Kix8WnzCvPjk+THJ3wbHfb0teLy1xxBdh1GqJiI1IwzNMbHE3FZkbCOlZcQG1UHLN4nmrWHKYobNhkkwBsYi+hzpMYyYwMQpLJqL1gactQg0IsycYHP8rfCxwdUac2O0tCQGEKqooKGOtg56RhgY4GFBpjd1YewNFQfnCySPZXEwk6a8zxozv9wXI30gmOZg0bEojkbSHEZDCIfCaY6hMZJ9IR8z4UDr49/Xnv85JPFfCBv8xNEU8DEZHo/iZNw/EIozYT53CugqoqeUe+VigY+q+fUQQqfHn1eWvbuIcF1DeGj952UZoY7eJnqbeXOI/pMI5+YK19WE+1a9t/SeNo29Vc7VLDryuV9Cz0AzfjH3yujM52EBj7K5HkqVDjWmCDc8f2iWq44g2Y/qsnXluzRzylR21BqUVGoUVKoUVqnmVSpmlmxMK1iVkLU4LHGmd/gYD98vbR1F+iYoqkksWSGaOouvFrBkg0hFWaShIdLSY6spTk5EhpKdRGn6h/XLYR8zYYUP5b5U+LAnhL2h4qaWxhAO+tMcwqkI2nL4aR9/HOa3Bh5WcTWD47EcjeFULGciORvD6UQOhBOsgcdG6ZKQEbf2GB4NX1mk+wHhTl7U8ebc8IFytK9VT4yw3US4aSnccezv3Nb7MED4IUD4yfv+RdW8DMmQOGw9ZMycRaaOMhYuI6xcR1q5DDF3xtoJD3eCvEjwJtuLHDdynMlyJMORTGuybD7AsyXLRhyZ9mR+yI25tuTakmdLni35NuTaUhNAXRjlLtQ4cTSQ4yFcS+JmGndy6CnkQQU/7Ob5AX5vRjj31dtTQ58d4kEt98p5UMLTHbys4XkNwq7BQhOPDxEbwISpfDlBNGU848YzZTrzF7FhI6rqGBhgYyvy8vjML2ByZNTsAYFhiXN8o2Y6+ozZ6jBoi+Fn6zUllHUxNBOZWWJpi7ktuuaoakspqLFyE/PlmPAtQ6YiMR7GM2wyXw78hzuHNUsx3IS7HkGmhFoQbIG/FV62OFphYoC6OgpKoo2bUVFBTRUNDTT0JXR0cTImyfWjwNoQ2Ld9WmnKpKyMOVn5y3NyFhUljt0dwbGIj+e65giORtMczYEwagPEB8IBhA3BNAR9jMbgf0H4t8CBkepDgWKEf08SXkjmUrK4HG3L+Ijwbhn3K8QCH9XwWxPCHcs/b8wTriNct3jdof7TKYQ63jXS38ybJvpOIJybK9xQFm4bPD0l117OjQJu5tJdwN1COvPoyuduKXdLeVDC/Vzub+e0J7vMuV86V7imVhFCgitZiZOKKzZklsoX7dKorjWoqNLKr1bNr1bNqVBKL16fnC8Xn7M0NHmWd9RE74Bxdq6DjCxQ1ZZasUZi9lzmLWOtCrqaGBpiZY2LC8H+JMeSl0pxGsUxlESyI0S8frnChzIfinwo82Z3MLtD2BPMwQgOhFLvx4FADofQ+h8IH++kPY9LaZxK4Fw8p8M5G8OpBFoSidVj23rJbG869m69lKa4w5jjHjzI4ZdqXtTy5txY4fIy4br6AML+W3rCLSOhzVy449rf6dH3yL//e7/3j52ut6xJTsA3EjO3T4ycpEwdZaxchtq4DbNzHWTnioMHVr64+hDiRZIHGa7kOJHlQIY9GVZihNm2ZFqTYSVmmW5L+geT2dZkW5NjTY41BbZkWrMriKYEyUp3ymw56MkhHy7FcC2JW5lihD/u4bcG/mzm3amxf57glyYe7KKziLu5/FDIbxU8raR/r4zQyMVS9JUYNl5izGS+GcfUacz6hpVyKKmgo4uJCfYOkt6eowIDp0fGzI9PXhSZMM8/cua2oCkmzp+pmoiWKMouU5DYrC5pZPqJmaXI3BpzO4yt2GokoaWHkgbrFZkvx+Rv+WImn81i6lxmLGLOUpYtQ2k9Vhr4mhBpTbQ94TYE2uPrgJM1BgaoqLFJWVJeUUJFGVUlVFVR0ZJRV8dKjyh7akM+Bg1l6oWFStGFKoFlGhHlm7Znz9wRw+5A8STEAMLGUOoCORDK0fiPCAf6jxsDaQigIYCDgTQGcyj0HwgbgsT8Dvp+RDhQkQ4gHJip/xvhzfR/Q1jD4528aEDo0H3dPle4NVq44fzy+tqHRxD28b4R4TBvmnh3jP7v5ghXNv11afONPZ9fyqGtkK4iugvozKU7n3vF3K+gp4gfq+lIoz2a4+6cjfxSaDc8nE6qM9sDBu+qXJNbuSapaHVprWZppWpVqfrfCLcPPGORszQsZY5P9CS/oCkO7kNMrFDXk5RbxzcLmL+ajZro62BhjqsrAf7ERZOZQkE6RdvJj6YggpIQKvyp8KHcixIvCr3Z4UtNMFV+VPqwN4j6IGr9ORBIUyCtOTw7yJ9H+bWR73fTVUpbHue3cyGRk6F8F83ZRL7LINEY5zWkutFZb3S7UHe31eCTXtzL4qdKftvDm+8mCpdXCte1+m5s/Yiw3Vy4s20AYd8Tr1f3rc81LoqMwDMUI9fBRk4yZk6yVi5DbF2kbV0kHDxw9ZU0DRls4y/y9iLSlVQnMu1JtyHN6mP9mWVDuiVpFmKWadakWZNhRYYVmZZkWpJlSZYlhfakW7I7hGNpw2u8KLJkjwsH3TkfydV42tPpLuBRBU9redHAX4f5/TAvjvJTE3erac/iViqPsnlewpNyeut530hTMgtnIRor+nIKC8YxczbzF7Fuo0hDW2KrEWYWODhKeXuOCgiYFRG9MDZxUUjUHM/gKfZeY3Wshm7UZI6c9NzVyKtIGpoMMzWXHkiGpjaYm2NkIqFnJKmqPWjdJql5KyS+XszXi6XmLGehHMvXsXY9mko46BNsSawdiW5EORPmQqAzLrYYGqKqLqGoOlhBSVpFWaSsyBZlNqtLKqthoUW49T8RFpQo5uVvzMzdkJKnmJq/JS9zRXXs53VBNIbSFMLhEJqDxd+46kPYE8r+D/3H9UHUB1EXSF0AdQEcDORgkPhR18MRHI7gSBjNIR8OhB8oNgbQHMLRcI5GcTz24wMzF1PEFentTO6X0FNOZzndVfRU8qCCn3YN3I5avbyE0KYotLv3nuH1foRGhIP0N/F7Ey+PIlza2H9B8fv64a0FXMulNYeb+dwuoKuIe8U8KOFhKa930pPBnYzPW9O4msLrE2Oulk7OcBqSECzKTp5RVLC2oESpqFy9vEZ7R41aablCbqVidvmmjJKN24vWpRSsic9eHpE6Pyh+lk/ol27eg+3spY2NUVRkyQoWrpZYpfSFrgk2Tnj5EBxAXDS5GWRnkpxIuD8RHuyIoSaYcg92+lLsRrEn5Z5U+1EdQIUflb7s9mWvN7vcOBpCWy7P9vHnIX7dz/c76a7gThk9+dzM51QqJxM4EUtjBMUeuClIpTlzumR96x69cnvRYVcepUv+sZunO3l1GKFV4+1V4zetqkKHjnDdSrjp0Ntt2tthIXR7Cw9ihMe+T2+plRaQlCryCZxg4ISRPRaOOLnh6omLBy5uuHhKb/MY6uwua+8mZeeKsyNetkTYkGxLkglZVmRayqSYSySYE2FClDlpzqRakmJBsjnJ5qRYkGIpjjxriWwLyjxojKchkTIfsuwocPj8QBDHIriZzr0iHpbzdB/PWviphden+fkQjw9ws5DDQZwP43H60O9T+CUH4ZjUtcp5VtpMmsL4CUyfzNeTWb6Q9XKoqqCnh6EZFjY4un7q4T0uKGxeUMSsgPAJHiGjHAJHm7hPWGfy5ddKsuOWjJi4dPDcDYPkdWX1LWXNbLGyxcEOaxssLDAykdLUEW1RZo08KzawfD1r17JxIwoKbNmErhqOJgQ7EuNGmocowY1ITwI9cbRFS5sNKqxXQ0mRzUpsVEZehU2bUdmEkRYOplR5URdIQzD7fCGvSDE3b0NGzvqUvE0peYo56St2xI6sDRQjbPqAsCGE+hBqQz9OAIgRBojjwIetV3+/rDyA8O/b0YO+/42wJYZT8R8RXt3OtXQ6srhfQncZneX0VNNTyf1ynu7i+TGEO1tfXERoUxGuWL1q4c1BhIMIzbzZz1/NvDk99s2Z1fd2Tu0o40oWrTnczKV9YAijmPulPCzlURnPSunJojOPm9n8vFfyQbXoYCzJDsSFyeSkzCwqWJtfvKWwTLWsWqu8WrW4QiG3UjGrTCG9eH1a4drkfLm4rGXhKd8Gxc/yDRu9zecTewdJMzPU1FixhoWrJZbKf6phiLU9Xl6EBJIQK0aYlIC/u8jdgnRfKoLZ4UmVD2UelPtQ5kGlD5X+VPhR5cceP+p8qPWkJYz2PJ7v/wfCjlLuFtJRyvlszqdxLoUTSezww0WBRDuOF629VW9Y4zq0wZHuRJ5X8mQnfx5CaNV4f9307U11McI2p74es3e3TIVOT+FehPDI5/b51YXZxCWJPHy/NHASGdlj6YCjqxihq7vIxVPaxU3k4CJp7SQyc8DSCgczfMyJsCHBgmQLUiyk0m2GZzkMS7YgyoAYI7abk2ZGkhlJZmKHAyyzzNluSrEzB6JpjKfcl2xbcm0+2enBQX8ux9Odw5NSfqnntyP82MzPTTw7REclzRHs8+RUEN3JPMvlr1qe1A4qCZbevILR4/hyAl9NZcFs1qxg00Y01DEwECN0cBnq7jXWO3C6d+Bkz4AvnHyHm7sPV7P5bLHG0HFyolELh325WGbWWsl1mjLaptImVljaYmOPrR3WNhImZpK6uiIVNTYoslaBNfJs3MimTSgqoaqEgSZO5oQ6E+dBmoco0Z0oL4K8/oFQVUVSSZUtaiioorgJpY3oqWClR54nNYHsDaM2AHIKNuXkrs/MXZeWuyklTzEzfXlhzPDKQPHMW2Mwh4JoDOZgEPUh7Pk3gXv92evP/g9br8QIwzk80C4T+BHhAR8a/GkO/gfCMwMVaRpXt3M9gzu53Cump4Sucu7X8KCK++X8sJvX56YIrVt+P4dwS63/5JaXTbxrRGhAOMofdbw+inBt6fOm+S2xXMvhciatObTmcSufriLulfCwlMcV/FjBz8U8KKSrnK5yhHMbW2LIdSfJnaToLzPSvinMX5NXpFBQqlxcpVpWpVJULp9bsTmrVH574drUfLnk3FXxmUsjU74NiZ/lGzba3XeYk7OUtbWknr7EOnkWrmbuaqktWhLGFrKu7lLB/iTGkpdJVgYJcXg5jjRVI8yG0hDKfCjzpNyTCh9K3NjhRYXfR4T1vtT7cCqa2wU8388fTTzfx5Oajwh7qrhayJVsWnO4nEddBO6bibbgWMHa7kaL/YETDjhwK5qnxTyp4WUjQqtGX6v5uzYN4ba2cM1SaHcW7ln0tZsLHW7C/eDeB9uO75+ank50nJSz1wg9e2lDOyzscXT5iNDVS9rZVcLWEVN7kYG1hLYxenrYmOBpKxVlR5g5wYaEGZJgQpqpKMWIFH3SzP4R281JtyDDkmxTMk0ocaAhkqOJ1AZT4kiBFWWOolp3zkSI7mTwpIQXdfxxiKcNPG/mr5PcKmGfH41+nAjhbCgdKdyvnbQnGjNFpk/hswmMnsrXs1i1hM0bUFNGTwdDE4wtMLfDwfVTV6/Rbv7j3fxHO/l8bu0xXN/usw0Gw2dsHCKzSGLYN4NGLJCcvFq0VFmkbIC+ORY22Dpg74SNA+ZWGBiiroWSCopKyCuipIiyqoS6mpSGOma6eFoR6UqyF9u9SPYk1odgbxxt0dJigwrrVFFXk1JTQ1kDVVWUFNiyDo2NGCgTa0eej2x1ODtDIbtgsxhhvnxC7uaU9KW5MV8UB1EfxIFAGgcIBXJwQF2QmN9/Caz1Y58f+/w48OFk2BwmLmUPBXIo8D8Q+okR/t1Benrglac08RjhwBMGA7Nkj2t4VMODKp7WIlzf0Hd58auzY4R2zT+a5j7bT28zQiNCMy/38eoIQodKV9WExlBu5HHz7zRYQHcxD8p4XMGPVfxUw69VPKnhfi1PG+k7o7LLkww30kJJjJ+Ynj4/N18ut1A+v3hTYYVyYcWm/PIN2WUb0ovWpOStSMpZlpC1OGb7/PCk2cFxX/mFj/HwG+riJnJwlDIxG6SoJrFIjq+XslJBUl13iLW9pJ8vSXHkfEDo7jhOQx4XfQqDKQ2k0J1SD0rdZUvcKPdkhy87fKnwYac3e72p9+FsAneKeb6f35t4Vv8RYU8hd2u4VsyVHNoLuV1BcxJ+6oSacjh3dc8hq+Nx3zS5ciuGx0X8UMOvBxBaNYQ2y3dtGsItLeGapXDLRbhvKdyyFjrdhPveL7tsqwpFqamExA6xcZfStpHVt8LMBnsnXN1FLh64euLmLePiJrJ1FBnbSGlZyG7RY5MmuobY2o0IcCXckxg3Qi0I1iXeiAwTUaoucYbEG5FkRJIRycakmJBmQro5mWakG1Foy/5QjiVxMJxKN4ptyLGWqHDieIjUzRTu5fHLLl428vNBHu7l3h6+S6bCiWIrKuw56MvFZEojxjnr8u1MRo9j7FdMm83CBayXQ1MJbU0MDTExx9QaMwdJG7fhjt6jHXw/t/f5wsZ9pKHDSGXTkUtUPh29XJrZEpJzpIbNkxy3QnLBJpG8tpS2qcjMBltHkaMbts5Y2mJogrYOamqoKItUlKXU1NDSktDWZqsOVkZ42xHrQaoP6d6k+ZLgT7A3DjZoaUlsUGGtCppqEpoaaGqiroaqvMSWdSKldahvwEOLRHtKg9kdAdkFm3PzNuTkrk/N2xiXK5+wfWlazOjckA+DNoE0BNDoT0MA+wOoC/h4Dvyb30DU+35YuBP0T4RB/43wUBBHQjkSwbFoTsR+RDgwTT/whbC7hPvlfL+TRzU82cWvjQjtum8vfv7uwlyhTedZvejXeoSjCI28a+RVE38dnSC0651N40Q8twtpy6X9Qxq8X8rjCp5W8/NOnu/i1138UMv3TfReXvxg98IdXmQHkhxBbNLXKdsXZOWsyM1bl1e0sbB0U36ZfG7J+uyitel5q5IzlyRsXxCfNj8m+ZuI+K9DY6b5R4zzChixzVPa2UXa0kZGTUd66XpmLGHeCskNSpKG5nh6k5RAXrZEbgZJ8Xi4jNPajKkqKb6SRSHkeVHqRbHLkBI3cV1a7kO5F5Xu7PagzpuLKXSX8fwALxvFCHsq6SjjTgEdVVwu4GI2twvpqeZ0JtGGBBtRn774ToPxd+lLmz24E8+jAvEQ+gDCtzfVhXbNAYT9d82FO45Cl0vfPZd7V7UzU0lMFQXFDLdwQd1cVttU2sgCO3uRixsDCLf5SDm5iyztJbdayqoZD12vKbFGhS16bLX/3N2T5JRPq0on5MdLhloRYUC8ESGqBGkTrkOELlG6ROkSq0e8ASlGpBqTqE+mGdXeNEXTEE6NJyW2pJqSZ0tDABfjaNvO40qeNfC0ge8bhn+XQY2PKMmQbWvxV6LQSaYufKSxGquXMH0qE6YxeTZzFyC3ki0b0FVnqw7GxphZYmEnsnCSsXEfae39hbmHrInLEAO7T1VNRq5UHzpNTlY0V4LpEsyRklkgNWaFzFx56bUa0mrGUsY2UlYO0o5u2LtgZYeRKbq6qKuhpoyakkhDA109DAwwNcLegkAnErzY7kOGHxkBJAUS4oW9JZqabFRmrQoaqmhqoKuJjioaCqisk9qyRmKzHGZrCNAjz4PdIZCVr5iTK5+dsy45Z1101rqI1CVJMaMzwtjpT20A+/w46E+DHwf92e9PXcC/CNzjyx5f6nyo82GfPwcDxR/u/xPh3xVpg9+HT/YRHP3w5OH5JC5v50YW7Xl0FNFTyt1iHlTw/U6e7ORpPa+OI9w0fH0Z4eIK4Zr60128rEc4Rl8Tfzbxqhnh9Or3p9WbwjibSns+1zK4lU9nvjgNfl/Fzzv5dTcvavllDz/U8/vpqUKn3pn0oTsCyAgmKoSI5FnxafO3Zy/LyVudX7g2v2R9TvG69KI1mYWrUnOWxm+fF5MyJyppZkTCjJDYqUHRkwIix/sEDXf3wcUNa3tJLcNBqzZJzVkhmrVUtFJBZGCClw+pyRTlDynMkcxIxt13iKE+2psItiUniDw/Sn0pdZUe2GdU7sMOX8q92OHKLnfqfbiSTncFz/bzooFf6vh+J3er6KygM59bFVzK50o2HUXcreZ8DmlW+BqwM3FO6z79y3mrmz1oj+duDvfKeLYP4YZ6/02L1zdUhHZN4bqV0O78rtNIuOMqdNm97rH8rmlxXBzRqcN8o0YZO7DF4BM1fSl9Y6xtJBxdcPHAzQt3XxkHdxljW3SMZVT1hqxXk1qhyAZttG1knbxIypba3zRzR+mXPjY4qOGrK/LWxleDAG2CdQnVIUybcB1iDUgwJsGYGH2SDCl0Yk8QB8LY7UuFE8nm5NhS78vpGK5sp7uCx/u5t5/jeaMTrXCWx24tVuvw0P4kxGqksw6rlzHvG2bNYeYcvp7FssWoyKOpiIE2xvqYmWFmI2HuKGPuPMTMbZip++eGLoN07YaqmQ7fqDVi/oZhXyySYo4UsySZKyW7eMgXcp/M3DhkuergLQaD9C1lTexEdk7YOGBpi4kZenroaKClgpYyOloYGGBqipUl2+wIcyfZlww/sgLIDiYlmGBPbM3R0BDJq7BeDQ1VdDUx0EJfFe1NqG0QKa5l42rUFmGlQJgxWc6Qmbc5M3dDZtaq5PRVoWkrAxMXREePTwyjxo89/tT7csBPjPCAH/v8xPz+S+AeX/YO1FF+/0B4KOhD1+gHh+IPFUHihw9PRHMyjnOJXN5Oaza38mkvoqtUnL5+rOHJTn5poP/iUOGy3qurCJfWC+cVf6ji9X6EI/Q28OowLw4iXNd9sleuMZQzKVzP4VqGuAH1bhGPynhazS+7eFHLy3p+PcjzJoRrGkKb1cF4ioOJ9yMidFRo0tyo1LkpGYuyc1flF67NLVqbWSCXmr8yI3d5SsbCuOQ5kfEzwmOnhcVMDYmaFBQxISByvG/wCA9fnN2xtkfHWGa9yuCF6wbPXi29SkmkZ4FPEFkZsuUlo8oKP81NlwmMxtlFWn0j1hokepHtS4kfJa78jbDCjx3eVLixx5PGQK5miRH+dpBf6vhhF/eq6aqku5Bb5VwppK1I/BTnxRzyHPDRpyp+1s3/Rdl9RTW5he+ifwghIAoWBLsue0OlKkiXJr2DIYTQWwISEkhCSEiooffepYN0RVQUEXvvfS3LUteyd+x+52K593/vM8a5OGM8N/P++435zXeWd8DncqPlvlhcycCdEtxr+I3wxyX/TxfsiKsuxKVg4krEp2texDXW9xsBL697dNQrS9MgzZkTm6zuHgJLd4XtbnLu3ggMRAQTLDZ2chHLJ0Vwp/oGy7tRFZ08p9k4U4xsYekOjxA5JhfJ2WgdXLCrY1lEIKz04GYCuqNcuB2iHRHnjHhnxDuC7wSxG1K9kOyFJDeI3ZDlh9potAvQGo9dLBQEy5UEYxcLw0IckeFcJc7W4VAZ4jwRYgsvE3iaIcAVkQHqdJ+pZmYwNsKmDdDWgp4utDfC0hg7nEB1BNUbdF8EBCAgjMyImOobpbwjStkrSsk9XNHJX9HKfaqBzfTlW5SV18tjLQmaZGxQkN88bZ7J9BUWKjp2StaeSi7+Cp4BCAiWCwgBIxh0BmhU+HjC2wVezvDwAI2G0CBEhSM+GmkJKBCgVIDyJFRKUCCGIBZBfnBxVrBylNvmLOfpjB1uoLnDxxGe1nC1gI0ZjA1hqgfbLfA2R6gdUFBhXVRmVli0JSt/izB3M1+2ITl1boYYbXx0JWA3D4MJGIrHUDwGE/4/EXbFo4fz/0b434Jwr+A3wv/tcC8fewX/PxC+HgZxaeH3426TF0CctSKObnvcgq+DIPbj2yC+HsSz3SDuRFyr0RpJx2EZLpbjWjluV+FONf6qw99NeNaO111414NPffhyGJ/HFhLXoz6fCurPRJUQIjZk6ZqC7LXS3A25RdplFQZVNSblNcbFVUY5VQaFZfo5hZvSsldLMpaJ0/74T2CiZL4gZQFPrBrHAzMWQWHw9KNYOqvoW6pu2DbV1EXBNwSCZFRUqLY2L2ium1dTNj2lEImSOY6WcLeANApFXNRwUcP8jXBXAtoEaElAKxu98dgvJl0ow70WvOjH68HfCO+3424r/qzDzRZcrMftZjxq+42wlokEH7Rnr7uxl3azw34oFpdScbsYfzbi1QCIi07fLvh9PL/9P4S/Lod/uOxOXI78fIX29JJ9WT7EKUjK1mAJZzoyYO6sYO0s5+oJBgMRkXLM2N8II3mzfcMoblRFN69ZDq5TLR1h7wnPULAT1Pgp2DXwR8+IKZM5e+1SrF6ALZrYYQSaKQIsELINwWaIMEOMFTh2iHXATmvEWIJnjyw6MZkrRQAAIABJREFUKpmoYaIiFPmBlFwayhloY2IwESMZ6ElDGQcJQWgv2dheZSjizKBRYeOArZYwcYKt9RRdLWhvhIkBLAzhZgWGO/wcQaOC4YfAIASGK9Ajp1Ijp7iHy7uGwt5ffpsnycCWvM6YoqYph2XACkBTHhvlyVtUNMzUVprP0LJRMndTdPSVd/WDHwP0APgHwT8A/nT4ecPXE1R3eHqCTkdEGGKYEMQhm4+yJFQJUSlGlfQ3wgAanJ3IVo5yli4kb1c5Xw8wPODrCE9ruGyDtSkMDaFvAB1taK+H0VqguMq8tGabrERfkqOZkrdRkrlGIFrET1xUm6BSy0JLDPo56OOgLwH9SegUop2HDgGaudjFRY8QPXx0xaInFj0CUhsbPfwpQyL0CnEgBWNp6I37fdKtPwl9PPRyMcDFcDyG4zGSjIOpv9eEp3JxvhhXK3CzBjfq8GcjnrTiaSee7sY/Q/hydB5xxYGYAHFsPnHZdvLA2n924esAfo3g4x682IcvR2cTlz3GMkmj6RjPxpUaXKnCxRrcrsOjBrzchbedeD+I1/vwZD8ej5oR16jEXca3My6tycjgQCpVi02eI05flpazLrtIu6BUv7jCoKLKuLzSqKRsS26RlixvvTRzRVLKIkHyPL54Hk80lyeam5Q8XySazeMpREcjJBR+/vL2rnJbtkHPYrqlGwIjkJKC2qoZuzt02tq31jdszi9Wl6Qu9fObZmwEd3vIOGgQozwSNSzUxqIpHu18tPLQHo9eIUYycLIUVxvwqAv/9uJZD/7pxt8duNeCa2241YqbtbjXgvtduNmB4yWoCYXYk1QpxtUhzwc97GEu5YwEt4twtxovhvH5+Hrikjtxxff7Jc+vl1y+n3X6etKFuLLj7RXa7vb1mQWKKVkKAonKTsEiO+oUczeypTt5uxc8GAiKUGDFKcTGk+PjSTt5qiFR02n+Kj6+FE8qPKjwocM/aLpfJJIz0NahvntgPZOnvFQL85di9Ur5VWuhqwsLC7g6guoCP1f4uYDhDD8bMOzhuw1UU4TZYacbOD5ICsZOZ+x0BZeGFCayuFNTOSQpB5IEdLRgYtz44EGneKH6dlfYu5ItrGGyDdtMYWEIM33YGMDZHD5OoHmB7ougIIXgYPmgMJJ/BPwiSR6hFAeGgq2vgo3b0i1285YbqSrrULBWHstJWEqiLKdgI5T1sMBMbpUN1jtB1x1bqfImDIqPL8XXjxzkh2A/BPmA4Q26D/x95YOpCPUFKxCJUUiPRW4cynmoFZHqhaiVIC8ZbDbcfGFiD0NbsqkjydcR/m7wc4e3E5xsYWcJS2Ns1Ye5Hoy1YbgBW9YDBSVb88uMUvM3ibNWpeWsS5GtShYvlIoWScLRla10tU33ctWKvfHojsAgG4Nc9ArRl4QOLtri0M1FZxw6YzCYoLyLhV1M9PEV9yahX4ARCY6kYZiPrjh0c7AnCYdSyCMi7I5DTyz28n8XUUelOJL5PwhvVONWA/5qwuNWPOnE8wG8PYifJ5cSF62J4/hx4g/iovWHfUt/I9yHyWG82AviuumvE05DQhzKwLE8nCnB1WrcqMO9evzTjJftePvfHe39eDGGr5f/66wY8OGEU7MYGRwkJlJiRLNFaUtTs9fKCjblFesUlm0uq9haWm5QVKKfW6SVmbsuOX1pomQ+T6TBE2nwRHMTkjQSRXOFwpnx8SQWCyGhoNFJ9q5kA0sY2qo5UBUi2cjKQlP93L5u/c5O48Ymg7LytVm56yOjNKwt4WAGDh3FbFSwURWBmig0sdGagPZ4tMWhi4fBJBzLx5VaPOzE814878Gz3XjSiYetuNGKe624XYcHbXjYi796cKkO7VwI3VEmxPl+twc97CEu5XgybuTjThVeHcD3k3q/zjt/OuXy5ZwTcd2buOw5ecyRuO579YBxeYmSOBPiTAiS5SNjptt4wtxNcZsb2cYT7nRSYLg8K04hjifP4YOTpMZkzwoMnU0LmEZlwNsfVAYYwSpUJkRpaGlT69ujw0lSW6WDhcuguZK8cjW0dGG1De6u8KcilI4IOpj+CPZEmA9CPBDgAIYlyUMfDppw1wfdDNEeEIVCHAleGHiRECcgU4r2Zhw9ajQ66swTzXV2h6M72doB1jawNIeVCWxM4GQBH3v4ucOfCoYf/hMYEEaih5O8w8guAUo2VEVTTwVTB1VNc8ocHSitA1bKYQWwkqS8VmGWluo8/VkrTTU0rdT17NSMnGdaeM229tVwp6n60qcGBJBCAhBMA8MbVA/4uCPED5EM7AyFIBKSWOTEo1SIajHqRaiWIl2EqBh40MhWrkqWLhQrV7KvExjuCPCErxvcHOBkDSsTmOjBVB9GOtiyEfqaQH6xYU6xfnL2usSMZcmy5RLJXGECRcpTyODgSCu+X3Ukrnv/OmjxulPvSs6cnnDsikEbG20x2B1L7ufO6I5BOwt9CdgjQls0ejg4lIZRKQZ5GIzHcILy/iQMxqOHgyE+hoUYFPzezBjiY48QB5IxloEz+bhU9rueeasBD1rwuB3/dOPtMH6cBHFu5a8zBj9O4eup5cR5i3fD81+0/r7N+XkYr/eBeOT/tHdrRwwOZeBUEU4U4kb97935f9vwpg+vB/FsL16O4t3pucTDyO8XvIk7of8c2l7JQ1ocuFzsFKoJU5ZIZatkeZo5hVoFxXolZVuKSzcXFejkFmzKyFqTnLIkUTSXl6jGS1TjC9X5QvX4RBU+X5HDASsKQcGg0uTtXOS3WsPEYbYnQ4mdiMJCtDQt6unW7+wyrW8xrK40KirbJEia6+4KM114GINHR2kCKkJRE44GJtrYpDY2WmLQHI3WWOyX4Fwh7jfh32683I0XXfi3E4/b8Wcb7rfjr0Y86cLjfjzsx8027JFC6I4iPs70OD/o4+4TTJmQ4Go+btfg9cFZk8c2fz1lP3nC/vMp258XnYjLHsR5n3fXfXbXz5ZkIDEDyTJI05TCmRR7T5i6KJm6KFi6y7nS4B8hH81R5AooCUkQpMyOE6hHRs8NiZgZEA56CPxDERCmRGNSeBI0Nk0dHN6clL5EcwuWLsOGlaTV66ClD3Mruf86BAYxEMpAOAMhfghnINwPge6KbsZKm+djowpMFoNuCTYd4mjEhyPSHzvDIBIgMx3NLZiYMD485iJInufqCQ9vkpMrHJyx3QYONnC3Bc0ZQT4IZSA0CEHBCImQC4wAPZy0I0TeLUDJhqpo5EbRtydrWmD+ZkxdB6wmYSUZK+WxVh6a8upaSgv0py03nbXOcqaujaqRwxQLF4qth5KNp6qDj4o3jUyjwZ+KAB8wvMDwQjANzCDEhiEuFIlMZPFRlIzSZNQko0yKZCGCIuDoDUsXeSsnWDqA7opALwR5g+6JHc5wsYWNCUz1YKoPY93/hbCwaEtuoV5qtqYkc6U0c6lYpJjMQRYPx1twqQtPhvDxwHzipAFx1evXEYdrlUsPZmOvFJ2xaI9EP5s8EI8+PvZJcbIEF8rxZ9OMV/0r3+1d+6Rr8ancKX1sHEjEaBL28NDNxm4uhkQYTEJHPIb42CPAATHGM3CuEFcqcL0K16txow5/d+BZD14OYHIUxNmpxPnVk8dWfT2j9OXc+h8XTN8Oq73rwK9BfBvC5B78OmFK3Ao8mb+kLQb7U3CmFOcrcKcZjxrwpBEvuvFuGO/24/l+vDm27NtVW+J++Jfz3sRfrCs9xmmRSIoFmw2uUF0oXSTNXCnL08zJ35RfpFtWsrm0WL8wXys/d0NW5ipJ8kJhorpAoPpfEhOnx/HkuVzExiIqAgEB8PYhbXciG9vImdhP8Qok8cQoKUVz49zOdq2WNqO6JqPqCquSik3STHV/+lTjjQoGy7DDCiIWysNQGY7aKDRHozkaTUzURqAyDF0sHJLiajketuBZB5534nkHnrbhUTuedOBRM/7pxt99uN+LW504kAWxt1xBAk732D8e5o9K1SdScKkAt5vw8uDiV4e0Ph2z/nbGcfKk5fsJ4+9nnYjboRcPW2RnIjEDSdkQZyJdNjUyiuLkiS2OU4ydFMxd5RxocvRwEiueEp+kkChREKZPjxdr7IyfHxWrFhaNICaCoxAcSfGNosQJUVunODKyRZa3xtACK1djwwqs1YT2ZphZwtkNPlTQ6Qigg+GHADoY/vCngeau4GhM0lsI02UI2EaJD56aEElKYIEdgehwxEaDL0RyKppbcOyYyZFxN5F0roc3vHzh7gEPN3i4wtsVdE+E0RAdgp1R5J3R8pExCI9BCJNMD5f/r6mgkauKtq3yenOKuqm8vI4c1ihgjSrWzMJKFaymQJOiogcNI/xhSVrtIL/JCZtdYeYBK29sp6rbUVWdqSRPKui+CKYhgg6WP8JoiA1BXATYIRBEITcRFamUMimqJChPh0gEWjhsvGDlLrfdFQ7OCPZBCBXBPvD3AtUFHnZwMIPVFlgY/J4MDbWAwnzdrDzt1Oy1qTmrM7IXp4mRm4iGdLzoxYNG/FWDx014Mwji7Gbiridxe8ePyw7/DuuNy9AZiYFYjKXgdDGuNuKv3fgxMffnkYWP2/G8B8TxDV9GDW5UL+2KwhAXI0IMC9HPR1c8Orlo52IgHkN87Bdh/H/PhFW4Xo2btfhnN94N4/0Ivh4GcXoacXrR+3H1D2emf72g/fOi2cd90z/sxq9BfO7Dl2EQd4I/HHTqSUC/AP0inCrGzXrcbcSTBjxtwYs+vD+A92N4Oz7t0zlz4jaDuB5AXAsiHiaMVGpy6OBEgR1L/h+EOZo5+ZuKCnRKi/VLivSKcjflZq/LTF+RLF6QmDidz5/G5ysKBFMEAnJsPNhssFiICAOdDnd3krW9/FZreVM7eWowhCkoK0djvUpL07q65i1VjQa1Vbbl5Zsyc+dERc0y2zxtlQYM12GHM7JCUBSGyijUsdDEQiMTleEoC0Z1AHbH4XgmblbgYSP+6cC//wvh00783YZ/e/F3D+5041o7RvKQ7EPK4uB4l+2TA0ljsvnjqThbiFtt+Hf/kleHdN6Pm7+fsHh/0uzDWcsPZ10/nNpRU6rB4UOQhcQc8CSQpkwLCVe0dZXXs52mZ6dg4izvQCXRwuWjE5T4yRRhGiUxbSpPoh7HXxjNUY9kkyPYCI9FKEvBJ0x5Jx+VVdh/QL+wYr2DO/T1YbABG3SgbwhzG7h4wJcORiACgxAcAD8/0GjwpsLDE3bbYLYRO7YhLXpmpmAVP2ZKXCS4MeCwwWaDI4AoAy2tOHHCfOKYuyRtnpcvqH7w9gbVG/6+CPRFqD+ig8FlyfM4qpyE6bEJyhFcSnD0NGqokqOfioX7NB27aavMpvxhqAQDdWyYhhUUrJyG5cpYQsZyMklTeY4eFhuTVlpPW+00e5PrLD3XqSYeCpZe8o5+M539lD38FX0DwAhEZACiAxAbgJhA8KLIQiaZF4ZkJgqFclWpU6ulqBahIh2pEvhHwcUfviEqESxFJhOsYET4I5gKhgdoLvC2g6slnMxgawJrI1hshqkeUJivlZ23MSVrjTRrWVq6WiofFSLsLSP/U4fHVXjbjp/D+HIAH46QJy9qf7tjRbyMJO74Pe5dO5GOk+m4W4NnvXi9D5/H8eMoXvbgZjGul+BRG97vX0acdjiTN2cvH+0s9CdgRIR+HrrY2M1BDxv9CdgvwlgGTuXhfCmu1eBWAx6249UeTI7i82F8PYzvE8rfjqm9P4oPp9R+XNxCXLT4MKzysQc/B/F5AD/G5hL3mJdrNjYxsVeq2JOI4wW41YCbtb8/3Fd78XYUHybw+YzWz8sexM0I4pIf8WfMl+s7KyXqkb5ghSI6lhzHnyGSLEpJX5GZvS4/d2NhvlZZoV5Jvk5+9oaczLWZacul4gWixJlC/pREAVnAh4CP2ATExoIZibBg+FJJTk6wsIaBpZylAwIjkCZDRSXqaig1tcsq67TL6w0bau0qK/VyCpfF8xba2Sj9MR8LNbBxPSJdIaAhJwQV/+vd+KoIlIagyB8NERjiYyID18t+t6193I4HLXjcib878bQf97pwtQlnGjCYDTEVadEYb9v27LBoPG/JaBpOFOBmB54ML357RO/F6Ob7e1c/m9D/dN35/lG7fTXr+RwwOeBlqidkUmIFYCdQaCEqZk7KGy1VtK2UtjqSt1Pl/SIUWPxp/JQpogxyYtpUvnQ+N3FJNEc9Kk4hioPIOLmwaEWPkOksLkrLMLxvQ1XjupAoJW9Pkpsd7Bzg6AIvb/gxEByC4BAEBYLhD39f+PrCwxtOLrC0gJkO6DaQsZHBX57AkueyIOCCGwcmE3F8pOdOaWnFyZMWx0+6p2bOp9HhHwCGHwLpCA9ARCBiQhDPJCXFTxcmzklI0uAK1SMS1IKiVT0CVS09p+nbKa83V15ioDhHTwHrZmCFvOJqzNPEEk0sXYk1mti8hWS0mWRoqGxgoaFntUDHeu5mW3Vz+1m2jmoOrnDxgrcfGMGIisDOCLBDwQlCXBh4TFISE8kRyGSihI9GCXZJ0SJGfTrSRAiMADUUbOESWe7S/AKVhBgyKxShNDC84O8KqgO8beFtA1dLOJnD3gTbjYCSfJ3/jTA1bUaOGL2FuLt3w9v+mX834Z9deNeNV9142Yd3o/h0TOPTrSDiMZO47Ppvp8rDWrzdjW8j+H4YvybUPgzjVQc+9uDrEB634u9O/Dxp+X3C+2GXwRHZlF4u+hOwLwl7eOhioSsa/Qk4KMG4DKfzcakSd5rwqBvvRxZ8OojPh/FlDF8O4fOYwufxaZ9O4NOJOcRFA+K86dtB0sdufB/A5DCIi2aTE157JAoN0RiSoF+M40W4VoPb9bjfhOd9eDuCt4fw6fgy4qINcZVGXA4lLvkR99g3h10EwQjzQ3AQWNGKnITpQvECadryjKy1udma+bkbi/O0i3I35crW56avzkpZni5eKE1UkySqiPhI4kHIA5v3G2FoEHZ4k+xsYWyBzRbY7iYXFg1ZHiqrUVWBklKNgvK1RVW69bUWleUG+cUbxdIl3j5YsRazZmKOBslAE55m4HoiOwDloagKR3kIigJQEITSYNSFoTsGY1JcLcefzfizDX+24mEXHnThYQ+uNGK8GPvyUMeHhCaXysKhNtMXEyknileNZuB4AW704MHgjCf7lv89vPLO4KK7o6uvHdbta1gujUdECJicGaE8VWaiEpODgBA402bq2k5fazZlo4XiVnuKna8CjakUI1QWpE4RySiiTDVh2uKEpOUx3LlRcQpMLiLZ5FCmslvQTCYHBYUY2LOssVNTkrFEIFzGi1GPi5vH5szhxKvxeTP4vBmcOEVWFMKDEcQAnQFPH9g7wtIYljpgWEMWiZS4eXwWElgQxIHPJrNjwBMgTSa3qwUnTlqcPO2ZnbOQEYSIMESEIDoMMRHgREHAJqcK5sikf2SkrRCnLOdKFkVw5/gxZzn6qRg7TllvTlliQNbQJatqk9RXyK/aCDs7RAUgIQQ7fcD1hJgOHhWxVIT4kKkeCq6u8p7u8PNBmJ8cww90P9ADEBwOFgvcGAhZEDLBjkICC+IYZHFQzkeLFIPZ2F+I89UzD1ZMLZQiJBT0SIhky8tqV9bUKoj4UzhMRAUglIZgbwS6wt8RDCf42sPbBh6WcLMA8nM0M7PXpWStSc9bnZ+/cFex6uXBjcR9+qfjxs/2qj3vwbtuvG3Hh90gRkAcwsvzocQbKfEv6/PI0icNeNcN4gCIoyBObCSOrH7dgofl+LQbvw7iy6FVXycsiItBxKME4pz/8bw5LZEYjMd+PtrD0BWLIT7G0nA8D2eLca0WD7vwchjECa3v4/h8GJOH8GUUnw5hchyfT+HTMQ3iogFxxvh1H9514OsAvh5QI+543m7XbYvDrjh0CbEnBWfKcbkS91twvwXPh/B+lPz20JzPJ7SJK27EVcaPMwzikh9xLWKkcgPDGeEMBDHAZClwEqYLkuYmp/why1idLVubl6VZkLMxP3tDXsaanLRVMumydPHC1CQNqVA5WUBK4iMxAWwedrIRFYHQIJKPl5ytNbaaQc8M9h6IjJPLLkBFFYpLkJc/NatwWWbp+qoqg/LSLYVFW6SZK/xCsUEfs+Zg1sw5s5ShuxIMK4h9UBCA0iAUM5Dri7xQ5AUgj4oqP/SxcSoH1+twqxl/tuPBbvzVjXtdOFmJvjTsSoIsBKn+CmnRGOswf3My43Tl2rEsHC/GnQHc68ONLtztnfPgwOrL+xZ1VCNZgIgwhPiTIlhz3ILgx0RgFJw8YOZEXmU2bY3xlPXmSvr2ZDtfBT+W8s6kaYlpU0UyOUn2nOSMFXzxyp3x86PilJlcciRbKSRKyS1AjclGbh56+9Xae9YWV22oKNtSkr02P3dDfu6G/Pw1xYVrigpW5WYtT0/5I1k4P5ZJYUbK+dLh6IjtZnA2RLQzuSx2cTp3gShanhsFDhOCOIUkwYwkoTxfiP8Qnj7rnZu3JDgM0UxERyE+GtwYJMbJpQrV81JXFOdszM/VTs3UFKSuCubO9Y3U2O6jomujuNKIrKFLUtGSU94A7fVwtUU2T2G0YdbZNkwU42A6xtLk92ejNxM1yUhPgJCNpDikCVCYDJlYVSIgceIQHYPYGPDZSOYghQseB4kcZPFRnYLuHBwoxdl63OjC96NWf+3Rby5QZkYihIm03GXV9X9UViMlaVoCG9HBiGQggoZQTwS6IsQFgY5g2INmDaolUFVqlJq2obhQtzSTfKwFV9vxYGAxcYNBXA/8czfu9eDT6NZP+0z/bsOTDhDHQZxxJF6nEh8KPp1zfNeFXwMgJjTenbYkzhs+6MCjDvzbhg+tIAbxohP3WnG7BsTZ9cTd7Q971vYnUNrDyHuY2BeNhijykAhjKTiThTtVuNeABz14fwI/J/DxIF7vx4fD+HgE70bx4RC+Tix4c2odcdWaOKLztAWT+/BqBN/OOvy4krhXjK54NMaglYO9qThZiut1uN2IJ/vwYBDPRuZNnjD6fsbh53l34jKVuLTjxzW/R2NePAZoLggJhRcN0bGkOLYSTzhdIpmbmb4iK3PVfwgLszTz0tYVZizOkczPTJqbIZwvE82TiWelCiHhIzEe0UyEhoIRCA+3qUYmCnoGMDSDs6cyN1ElrwglZSgtRVqmqiB1Rkrx0vIa47Jq4+Jyo4ycdeExZHNLLP8D82ZingaWLYDOSmzXQ5gDxH6UdD9IPJHhgVwfcpGvQjEVZXS0R2M8CzcbptyoxKN23GnClWa5I2VyVRyk+iLBkSSiQxaDPQ3r7+9n3Gq2OJaH4+U41zTvfAPOtOBYC0Ya0FyCrBSwYxEcAl+GvE8AxcN/iiN1hqX7TF17ldXmyktMlJYYkDUtlLc4Ktr4kGgRcrGJSMqANAuJsqmJslnxKRosnkZotBojYrp/+Ey/sBku9KnBMUjJRlv78sEBg12NBsUVBtVNdk21tk21tk21VrvqLJtqt9VUGpUUbsrLXi0ULRUkzQ2LRBADXg7YrgeWGyoEf0i4ajGB4ISDHwtxgryID14cMiTTm1sxMWF8+gytqHxtZAzi4sHlII6NpHhIE8n5qUur83SrCw3ycrSksrVJ2as8EtVsGRQrR0UDE/J8bczWl1ugP2vWMmVvA5QlYKwap6pxqRoXyqeNF+JQGU4UY6IAYzk4mIkDGRiVYSwH43m4UoGz1RgoRE4ieDFI4kIiIIniUc5BswhDWThUjJNluFKNe634pwfEEaMnR5VLshAQrMASILMY1bXriso0k4RKPC5lZwQi/RHmgzAPhLghxAV+9vC1xQ4reG8DMgs0M3PXF+atGevQutGjcqsVz4YXE7f83gyvvFyJO614f3gucVLn19j693vwdRTEGf23xywfH9n2bGTRh92Y7MKXQ/h23Ym4av1y/5o3h1d93Kf0oQff+vG8E/fb8bwXDzrx7jCIP92Iy8G3aw2H4tHPxu5Y8ogIR9NxJh93avGwE/8O4vVBfDyAN8N4NYz3o3h/CK/34+1+fBjTeHNkLXHVfHLftBedeDuEz2MLiRuM6x1WXQlojkFdJFrisCcFJ0txvQF3m/GwH5MnVr8aXf5kePXPc07EZZ9Px+2+nnd7f8F/l1SNYQeaO4KDQA9ARAR43KkCgapYrJGWtjgzfUWObE1+9oYC2frc9NUFaX/kSBZlJs3NEM6RiTRkYtX/EAoTEMNCaCgYDLi6KG01JusZwMiC5E2dwhOr5hWhpASFhUiWKHGSlEV5iytqTcprTEorTWQFm6Ljp9s6Yu1KzJ+FubOxbD42LoeFFqjbsNMDfG8kuEPgjGRXpLgj1QWpLsinoTkGg8m4VIy7zbjUgON16MqA2BcxtmBaKSX6IoWJPQ3rHx2KuNXudDAb/ZnozkaLDC3Z2JWH8lzI0sDmITACHgy4ecHRA7au8sb20LWUX22isGgLeZ4+edEW8npzpS2Oitup8n6RJLZQ7j+EIhlFkKnKlc5kJswOjJpODZ7qFaDsFaBs503yj4IkE80dy/YNm3Z2W9Y1W+/a7dna7tba7tba7tzW4dLa4djUYltda1pWYZCbt0WWo5kgmBUbrUr3gJMBdnqiQrBExJ7FYiA6+L+fTAi4SIhDarJSSxsmJozPnPUrrdoQwwVfCAEf8VyI+MhOm1eRp11bvLWq1LSk1CS9UJsnW0XnrXANnGfpOGeDyXRVbZA2QkMbKzeSEqnozCQfr8PJcpwuwqlCTBRgohzHCjFRgPE8HMnFkVyM5+FoPiYKcLEcl5pxthvDTajJRk4ickWozMSADCP5OFKGUxU4X4XrdfizFU+78WV4+b39yEsFI3BGtACZxaioWZZXukgqniPkz+IylVjB8mE0hHghxA1BLmDYg277v2ZCScXKnMoNtSWrXp52ebdf4+8WPB/C5Gmzhy24Woy7zXg5AuLMdOKS8/fRdU97QRzG0y7cbMKzHnztxeRufDmiRDzwJf5k/LrpQzxp/0RDAAAgAElEQVTwJ65Zfz2s+mUYb3rxrB/3m/FuHz6M4f24OnHXi3gpfHnIqSUBvZEYjscxGc6V4Wo1/mzDs17804eXw3ixF29G8GEM7w/hxQhe7sf7sSkfDmsRl7WeduNFL970gzjlSFwL70hEQyxqIlETjqZYDKbgWBmuNeFuB96Ornw+/MfDvgWvRg2ISx6fTtu/HLf8cdlrot3U3wo7rBFMhZ8PosLBCkVS3DQeT1kkmi2Vzk9P+SMrY2WBbH2BbH1expqCtOX/IcxMmp2VrCaTKKUlQSKAkIed0QgLg78/nBzJW4ygZwBTa9AClIRS5fxiFBUhNxt8PokVT+HL5hdXG5ZUm5ZUm+aW6PHE87xp0NPFsvlYOg+r/oDOGpjrwtUcAS5geSHGGzEu2OmCWCfE2IK1DTGW4DpA5Ia2aLX9ORivxdFmNEkRZQ1Pbfjog+8DSSSG6jY9ORp3p8dvIEOxhAspC2IOknmQiCCSIC4JIXGKnmFKDgyKrau8pQO2WkPLHKuN5Jbqyy/Uo8zRoyzcTFpvTjFwUrCnydOjEJdESkonSWVyomwI0sEWUyK4U2nh09z8KHbeJBtPeStXeVooklLR2Lp4/z6L/kG71m6ntkGfzgFq5wC1a9C3e4jaPURt7/Nq6nSsa7WtqtleVmWWmbteKl4RTldwNwWXhqqkxSL2LFYQYkKwMxRxLPDiwImDRCLf1o6JCeOz5+iVddrxQoilJLGInCggSyTqhYUb6qvMqivNyivMy6u3ZRbrcVIWBEcvdqPO3Ww2Y9GW2dg8HRuxeCNMTdCQgEOlpLONOFmKU3k4novj+ThWhomC3zlW+DvHi3C8CBcrcLkZ9/bj4cTSM30a3floz8JIJY6X40QFzlbhfBUu/3fAqxkP2vCyH5cGkC4EnTGHLYSsBKWVc3ILFVNTlolFi3lx82LDpjH9FUK9EeAGfyf42/0fCNPqFxdULx1u30BcdiTGVD7sxps9eHZo+b8tuF2Ov5rwVzdeHgRxfuuPo7ov9+BLNz504X03JnfjWxe+DuDXybXEX4HEw0jiWQLxPoX4h/Xr/Navo/gwhNeDeN2HyQN4NYy/evDp1AbiDZv4O+7msO3BeAzFYTwLl+twqRrX6/CkC89249lePB/Gq/14cxCv9uOfYTwbwZvD+D6u//P49NtNeD6AyRE94jzz2V7PomDUsn6/qNfExmAKjpfjRiv+2o1Ph/TPl+NO+7wvp7e/mbB+MWH7+ozT3REDCRP2BgjzpUT6q/i4IzYS8ZEQRcvzeApJSdNTkuelSRfmpK0okK0tlq0vzFhXkLYqV7pEJtLISlbLkc7MlipkJCNFCCEPsTEIDwedDns7eb0t0DOCpYN8SLhicrpyUTEK85GRiuhYclC0HDttQV6ZblGlcWmNWWGFgTRzRWjEFEsLrF2O9cuhsw6m+thuBk970D0RTgczEDv9EUMHiwqmB8IdEWgDhgXoZoizkssJQbUQbRnICVf01oHTBvhaQkSHJBIDdRufHOPdHQrvzlogZSHMH9FM8s44RY5garx4VkzizMC4WZ6hMxzpU8zslQytydoWpDXGpGWbyQv1KPP0lebrTf0PoaEzxZFOZrDkOSJyUrqSJJMkygYvFdGJ5KBYJe9AJRtPeRMnGNvD3FnBJxg8CWrr5w8Nm/QP2jV22jZ0O7UOUtuGfDv2+nUO0zuH6W1Dvs39Po09nrVNrlX1dgXlW7Nz9FlBKt7bIGSgLnlhqmBhPFMpnqkUGwkuCwnxiOdCIkFbO44eNTp7jlbTqJ0oQWqGYmqKqlQ8OzVrVUnZlto6q5pay6pqi9IqQ1nBKp50Gpcl5+sFHQPM0VdWMp6roiW3URfB7hjIwLFyXKzHuUqcLcTJAhzPx0QhxgtxpOD/ynghxgtxphRnKnCzB/+Oz3l8aOXFNtLxSpypxYVKXCzHxXJcrsL1OtxtxYMOPOrCP/04uRuiBPj5z48VqWaVoLhCNbsAqWmrxckr+PGLYqNmRwUoB3uD7gaqA/ytQLcEzQK+5kBmKSoqlO4fs/11WpcYw8+9+DqKT6c2PW/EjXLcqsONevzZhQ9H8fPkIuKU5ecO/OoF0Yfvnfjchi8D+Hbc8Nf1oM+3QomXkl/v878/F/284fXlyPz3e/GyB5/24k0fXvbh4wF8O7vi5y1n4u8E4lXh351GR2QYzcDFSlypwrVKPGrDs1483YOne/DPXvy9B/f78VcfHu3F81F8GdV8sQe3WvH6AIU4S/1xjLVHuqwgAKURKAtFeSia2BjOwOla3N6N+wOqf3Usut4048mwzvMxi7vDho8nHK/tMysTYocDdjggjKYa6qvM8AYrGAksiGKQyFNMTpqRKpkjky7KSVtaLFtfkqVZmLGmIG15rnRhVrJatmR6buqU3FRypuT/QkijwcaSpK2HzSawc1dgxZDSZZTiEuRlQyoih4Ur+IaRoiVLMou1CqpNSuq3FVcZyfLWxMaruzpBRxN662Cih+0W8HAE1QP+vggNBCscvFjwYpEQDR6TxAkjsfwR6o0gNzCsEGYPhjmCzeCjRdr2Bxh2yOCrpoeRU5jorV73eCLh3jCrO29dMhsBAZTwcGVW9Ax2glqcYBaLq+IfoeDiK2fjAm0z+U2m5LVG5GWbyUt05edqk9W1KOpaSou2kDdsUzJ2V3QJJAfGkDgicmLqFFEqRShDnBjhHBI9kuLsp2zmRNazktO1lDNzUvYOInOSUFo1q2/QYPfg9ro2i9Jmi5pe77r+HY1DtF176bv20pv2+DUM+tb176hto1a3uJQ12BSVmTFDp/lYITlErl4yP0eyVpqwSCpYImDPjudMESZS4vkQSdDSivGxrWfO+ta2aCelIi1zSkba7IzUxbICnYISg4oai4Ymq6Z647rKDZXFCysK1WrSkc6Fnw8MbLDMUGXRWriaozp+5slynK7A+WpcrMLZUpwuwslCHM3HkQKM5WM0BwezcSALB7MxmoNDuRjPxng+zlbhZhfu96jdaZ1ytRaXq3C1HFfKcK0St+rwZzse9eLJIJ7uwfN9ONEDPgdU/0Vs0WxZMQpLZ8jykJy6IlG8gstdEBOpEcZQYXjBxwletthhgR0W8DGHtxnQUIT9rRq/7u34PrHk1wi+78WPMRCXzZ634GoZbtbgRjWuN+DRHrw/DOK0DTE663sfvjTjWysmO/FuAJ+PGhDXAj5dDyDeZk2+Lfn4Ivfnw9gfZ4y+HsCrbjzvxPteTA7h8358mcDXa6a/nvCItzXEU+HNPq0DGTguw7ViXC/DjXrcbsfjAfzdjwe7cbcLtztwuxsPBvF0H/7tw59teDyIyRMmPy8G3+hwyvFFgT9kQchioCgQu+JwMBcXm3Gzj3RnQP1a6/RnB7T/OWR478CWe2M2J3q3FokRTQPNHYHecLOGvzuiAhDki7gIiOLk+Tw5sWhahmSOLGV+fvqy4qw1xVlrCtNX56XOy5bMzEymyCTyuanknBRShhhSAQTxiI1BRBh8qSRLc2zSgaEFXKjKsfHIziEXFSM7E0nxU2l0kjudFJq4MLVoQ0GNaUWTXVmtaU7xukTRPBoN5gYw1sE2QzjbwMcNfj4IpCIiEDHhSGCDFwchB6L4qSKOKj+GEheB6GAEU+FrA7OlMJ0Luz/grgdJ9JS2Os2sWEpKLLqrlj6aiLs/zOwt3CBJkA8KUw8JV4xgTWPGqkSylRiRZA8/OSsnGFlilbHCSiPyCgPKoi2U+boUdR2y2kaFWRvIfxgqbbKaaual5BYsHxwnxxGRBRIlQbI8X6rA5MI/Al4ByjZeyltsyOvNSOvNyIZ2yq4M+Rg+CkpUuvsN+/ba1XZaFjcaV3S5Vfd41Q9QG4f8Gof8GgZpDQP+DQP+Db3BdZ3eDZ2uVXXbWWGqPlaQhpHqpepFMu3c1I2FmbqpotWSpMUpKXMTRRBJsasZRw4bnj1Hq2vVEaYgNUNRljEnR7Ymp9igsNSwuta0rdW8u1m3r27ZgeZ5p3YvPduBQ3VozER8JGzNYayJZDquNmo+6MWlOpytwLlKnCjGsSIcK8GRfIzm4UAO9smwNwN70rEnHcOZ2CfDcCoO5+JYGU6W4mQJzpbiQjkuVeBSGa5U4GY9/mzD3314OoR/9uKfvXgzuuhYD7hx8GEsjEuelVGInPxZqZkQpiyJT1oUw9YIC5nlT1X0doGbNRzN4Wr2P8FEJe4Pr5k8b/rhCPnTfnwdwbexKT/OmL/oxrVSXKvA9SpcrsO9Tjzpw+QBEnFW/+uw8mQrvrThUzdeD+HDUU3iuvf3GwziU+Hkh7pPb6qJ5xnENS9ifPnHHnwYxIsWvG0HsR+/juHd6blf7gYTnxoJouLV9YCLjTPPynA7G1fzcbYMZ5twtwU3mnG1DpeqcakW15txuwt/9uJeC+604M2Y2fuTPnf2WjcKFSSeyKJNk9Ag9UVBAFrjMVaI86240IGzzbjapfDXvuWXB/441bfiaJ9+SbpymB8iGQjyBc0NzuYI8Pg9jIkAn01OjIdUqJwhUcuWzs9LW1yYubIwfUWudEm2VDlDjLQkZCRDJoVMglQhJAngc38j3OFNMjfBBm0YWcKTocxPRE4+iguRkYL4aAV3d1h7gM5RF2Ytz6k0qmiyK68zKyjflJ61PIY5w9MZtqaw2wZPe/h5IMgHIb6ICgAnDDymKp81Q8iekRSnKmQr82IQF4noMAQFgeYC23Xw0EKMM8ThqMyZtrtBN4ujkByLzop5j4+yHg5H9BesknIQFDzdL5RCD1Oihct7hMg5+MPMnaRtQ1pvRl5uMmWpkeISA/L8zQpz9BQ0dMnqOmR1HfIy46k6dtMsqSqeYeQQDilOqJQgIsULEcdXDY6CJx1O3krmztM2WpBXGsmvNqHobaM4+spHcJBZQOrs3dw7bF/XZZFbv7mkzamiy62m16d+wLe+n17fT28YCGgaCmrsD6vtpu3q21HX7MQKU/W2QmqEXGPq7PK8LeV5W2vKrIpzt+Zmb8zPX5OSriBNx65GHDlsePYCtb5NO1EKaRqyMucW5W/KK91aWbttV7N5V5PeUMPSk20aD4YWvDu0/K9+3GzDuXr0yiDxB98TwzJ8H1/2ar/i5XqcLMXJSowX43AhxoowkoWRTIxk/k/Lzv+dPek4lIsjxRgrxOFsHMnF8SKcLsfpSlxqwJ1OPBnE8314uQ8v/qtiHNQe70JMDLwZc9hS5dQ8yDLURUnK8SkanES1iGhVOkPJ0x1O1rAxgfkW2BrC1hDbjWBnDNytxvsDm2514cVBTB4BcRw/j82fPGr8bx8uF+BC/uwLZbhSi/vteNyJF0N4c3LTl8OLfg1hshMv2/HvIN6NL/xxwfTXDV/ia/Hk+/qPb5qIV4XENQZxdMPHbjzvxGQ/fg7h+x58GQNxVZ14Gkq8Lv7wq/T72+Q3E9YPKxTu5+BqDk6W4FQ7ThfjZAGO5WIiGycKcK4cF2txuR43m/Bnt9rkCf9nR/33li3gUZEZhHSfuWJfSH2QF4B2Ho6W4GwzjtfhQCmON+BYM460oKsYmXxwoxAdhiAGaO7wsoW/G8JoCPJBeCB2RmMnCwIuJIlK6cmzsqXzc1MXFaavyE9dmp28MEOMVCFShEgTISMZGWKk8CHigMfBzmhEhMHHS87MGJpaMLHCjqDpiSLkFqCoAGkSxIaTHBxg5gQf1owY6Zz0Yr3SeuvyOrOSau38Yk2x8I+wgFnuDnCzxw5nBHgixBcRNLADIYhQFLFWi2NWJLOXiGPn8WNUOJHYGYboENCDQXMnuW4mRzggNx7VuWitQEu5bnocxDHoqFB9fDTi0XBwX94ScQzodJJLINkpANv9YUKFrjvW2csv3aa82HT6EhOlhYbkefpkdR25WVqYpUVS1SbN0CGtNFXVc1C18p3mFa4QwgE7kcIVynP4iI6bRg+Gsxes3ShGtoprTUjLDEjLjJW0zSh23giNRWoO2rp1eobtajrMZNXaxU325W3ONd1e9b20+l5aQ69/Y1/groGQhr7wyi7qrr4d9S2uzNBp3lbIYMntSp9TXWRcX2bZ2uBWW25bXmJSWamXnTc7LVduVyPGx7aev+TX0K6TKEVyCrJl88sK9QrKjZvb7HZ323TVa+6tUrnSOeX9gbnE0QV3WnCpDNercLESgxIMSfGgG8QFvNiHc1U4VoQzVThcigOFGMlDrxRDqdibjuEM7Jdhv+x/QB7Iw75s7M/B4SIcLcJ4IY4WYaIcJxtwuQOP9uD1IflP43M+j82dHJ338YDGqxGD0XawWPBmzGBLFaQ5SJXMEcTPjE+ZFZM4PZSp7OtHdnWCrTlMN2OrFox0YKQH080w2wJcbcWtNqUrFbhVgw/D+DWBr4fxY2LJ+2E8bMW1Ulwrwc0yXKvEnSY87sXnoyDOrf96YPWrFnxox5chfDyMzxe3fr/LJd63TH7ue/+54euL3O8XYr6P67wbwcdBfBjCx2F8OwjiuBJx0Yi47U78RSP+8vt80/LjRb0vFy2Ia34/L/o/3r/1TAuqYnAsA7+OOX+5yZtoMj4kxaUSnGjEpS48Paj77qj/cIaO1B18FzBtsNNhKsdaleeM/Ci0Z6InF7tz0VOAnkK0V6M0H4kiBMaAFgFGJCU0jBzKQLA3qI7wsQfdA6E0hPmDFYr4WHC5EPBJyWLVrNTZuelzctJmZ0umy8RTJYlIFiBZCIkIKckQicDnyXHYpIRosJmICIGnO4wNoaWLbfYkaph6aio5LwtluRCL4eUPPSuY2MOXQQnmKYhylufXGhTXby2tNSytMszIWstNmE2nwscdXi7wc0eQDyJocqxAUlwYRRANHhPxkeBGgBsBThjYIdgZhCgGaC7wMEesC+o5CoPZKrtLZ7XXz8+Lk5PEoqty/l/jrNtD4QMl2mkJyr6eJHt/eWsfBTNXir6dso6l6kbz6etMp68xVllnTFm2mbxElzJPR0lDW1ldizJbV2neFuX15somTtNc/VUCoijRCUo7kxRjhMrhCUoB0VPc/MjWTkpm9lO2WpM3GWOtHtbokFeawNiJ5BulnJQ5paJlbu9+o85B24KSrVk1lkUtjpXdnlXdPjU9fvX9gbsGw5sGwpuHIhv6wpu6QprbGOGBFD97yFjoyFxYUWHd1OZc1bi9osG5stGzss6upHqjOBPVtRg9pH/pkldH2yaxGJLkqVkZS8qKN1ZW6jW0bNu923ZPy8axGtzpwIs9+HsQl6txsQoXajBRhtEiXGjFmzE14rzu3wO40oBjRTiSj0O52JOB/nQMZqNPioFU7Pk/Osj/lyO5vzcMjxXiWBEmCnG8GKfLcbYO1+rwdwve7cXniUWfTm36eGT1u/0az49iuBqcKASGQpg8SywGJw58ngYvUY2bMDciQs3bQ8F2G0wNsEUbWuugo4nNWjDQgYkucL4eV+twvhhXSvGyH9/G8HUM348u+HgAjztwqxLXS3GjDNcqcbsRj3bj1QiIk8u/HVz5ohXvWvF5AJOH8e2Cyfd7LOJj968v+79ONhL/in6d8yHGln3fB+KQ/K9D+HEY34/gxzGFn6d1v1+w+nbFgbhoQ1w1I26YELdciHuRxNNk4rWEeBs/XqV1rgTEOUfirezTDfZoKg4mY6wKD8dMznUbtkvWxNhihz6CrcGwgqcRgi0QaY+kAMj+H6ru+q3KtHsb+Mlms0HEdsQOFERApEO6pWEDm+5OaVDp7u5GunvTjXTY7eg46jwz49hJ3e8POs/zfY9j/QufY13XfV9rnb6I9USUK6LcEe4CVxs42sLKDiYOjJauO+w9tzs5w94GtoY/EdoYwMECTlZws4ePO4L8SZcvkaNDt8dH/pIYtTs+YkdcCHPMZXJIEEKCEBqMsCsIv4LLl+DnAy93XHSBhyPsrKCrg/PiEBCGshaDuRt7dBwpPQXZqQgJgY4xeKUhpgA9YyYzD/hHH0nIE84slSyokC2uUMjKEYuOOe3ntdXJDuZGsDKEvSlcLUjuNgxe9gy+TvBx/Lcc4G0PL1t4WMPZAmbaMJSHty7K/SndyXtacvfUlR5N8yNF+qCx6PCv4x6Pely7coWjA1hoelAygqw+g4QGSUCJ8azcFl4ZltNSLFySzFzSTP8HIfMefqa9wpQDkqznFNjkdLfpW7PaebB6BjL6XmHxCGZz9CdbuJJ0TEkK6ozSqkziigxnJcEtDG4h8ilpSGiA5kQOjmLOrTjY0ne+vkM1NVM0vlAhvVIjt84gv8GosMmstM2mssPpB8LKDueqZqeqemsXO2YrLSR5oSHhSFHRhap6g9Iq7eJqakmNSUmlTkG5eHQyikowOCS8smJYWy8cEcEYGbErIfZoVpZAaalMVb1aS4t6V9XZgTzcKMPTetypwvUCLOVhsQDT+ZjKw4MmfJnaRyzxP2nGcjHG0zCcjMEkdMWiLQbtiWiPQmcMun4cQWN+xr/3xWI8GaOJPx2Op2E8DdeysViE+QLcKseLZrwbPPh5TuzTgvS3qbOrw+wvh9GaC09nWDtS/C7v8QmCiwd8Aw75B+308dvj5LTTQI+sKAtJYQjxgZ8bgrwQPgtxQUgLAQsFWMrHXBoWM/GiAZ8HsTqGzck930bwZzsel+F+Hu7m4m4e7pXh1zq87MDGzBFiiv9jC97V4Fs71kf3ry3Jf3lkQ3xqI77NEZ+qiZcuxJwoMcxI9IEYwuYw1sawPon1afb1BdHv11W+31QlllWJO2rEPTXilv6323bfnl5ZfZdAfM8g/kr6Oi5HLMtvvvIk3kTMZW0fjcP1ZtWuQhU/IwaJQ1Djh6nKz5evGvLwtYWvHfyc4GABPWWoyUBVmiwjDgVZqKmxaBjuodoctnQ74ui9y94VVlaw+RehNRWOZj//B/i44HIAOSSIOfIKa2zoztiwrdEhzFHBpIhAXPJHsB+C/XE5EEGB8PeDpxucHeHuAHtrmBlDQw3i4hAWgzqV5OhzIDaRMTMN2akICoSyNk4I4IwYVDWZ9WzhHHwgIpU/rVCisFKuolatqFwhI1M8PpY70HevgxUsaD/vhE7mcLGEsyWcLeFiBVdruNnAzQbOFnA0g70xTLX+h5Ceyt6a90ttyZF0f3KULxqL9v867vaw14VeIB7tv01HEzI6DBIaJGElBl45Eo800xkpMqcU4ylJ0g+EB4UpB4QovwhQdgsw7hMmH5XcKqzKqmS4w9B+m70ns1cQk89lilsgi6MPycQB6lTIKJHE5RlF5MAjDi4hcAuRT0pBVBX6Ngx+ocgs2dNEF6/vUErNEorKlUouVcmq1sutM8pvMCttsatod6xod7za6Xy106Wmzam6wcbVfou9HlJ9GRqTDpWUaNc20Spq9cvrTSsbbK7W00qqZePTmQuL0T8gtLhiXN8oFh2zMypqf0wCR3qWUEmF3NV69ZYW9dZKHnoWZnNwoxhzeZjPw2wW5rMxn4PFQjxvxfo4CzF9/GYVpnMwmIT+BNAT0BmDthh0xKEz5ifC7hh0RYMejb5Y9MdjIgVjSRhNxFgKxtMwlYXFItypxtOWbX/3nvg8Lb56S/fLPfMvt/RWpwU2hnY8H0BdKpztYe6418Wf3c4dto7wDjjt47/Vy3uPg/0ufR2SrCSEz4L/NPhO/a8ZnhcAFgqxkIvpNMxl4FEVPvRhfQKbU0xrE3hPx/NaPCjA3RzcycX9Ijwux29NWJ3aQywIfKezfqjFt1ZsjBxbnZX684EB8aGd+HideHd181fa98ldxAAIOlZ78W0Q30exdg0bi2c2ryts3FbfuKtBLBsQ1w2IGwbELRPisTvxRyjxNn71XTzxOpm4rf1t9vTr+5rEu0sP60Uq3BBjf8BF++jZfThIgbfDubJCvZh4ruR0zpKK81dL+fPyjsfEb7e2x3k5nBOlCMns55Vkl1TeJa+5T9XwiLbVIRPnw3aeu+xdYWsLKyOY6YCmCUt92BvDzRJe9ghwxRU/UmgAJSKYLery1qjLWyMukSICEeaPID8E+MDPE95e8PaEhxucHWFnC3sbWJqBqgdlRYiLQkwSOqYk16D9sYlIT0dGEry8IKkA9lM4wQtZeZYLprDy/CUglicuRyi7XKq8/kJZtWpekXxutlh0FKe353YnG9iYw5YGayPY0mBjCBtD2NHgaAZni58C7WiwosJEE0YKuKiDcv+tfekH2gsO1xQfSvUnR/ujueTQowmXR33OfUWSEQG7LqhAQoMkpsIorMDEK0fmlaHwylBOy5A4ZXBCivmwGNMPhOwC5N0CjAdEycdkWCS0WdVNt5s7s7n6sFwMJnlfIrv7k+08GQxtoKIDSTkIy0BQGmfEwCWEM8KUU5IQVoKmOYNHEFILtjXSxRo6FTNyhcIyRRKKFDIqdbJraPl15iXNtuVtDuUddpUdTtXdbrXtzlX11q72TE4GyAggN6ccLSnVq202Kas3KG+wuNpsX9loWlqrEJexI78Q3f3nFpZpTa3SccmHohI44pJ50nNEi0vlymvUaptUWirO9GRiKgtL+ZjOwkw2JtJwLQ2zmVjJx4tGfKTjcw+m8zGSip449MSiKxYd0WiNRlvMT4SdMeiMQmcUeqLQH4/BREylYCIJE8m4lo6ZbCwV4WE9XvXg+5Q4sXyBeGxFvPRd++PS6lOnjQW5zYFtzwdQnghHO9Acj5q7H6TZwsqBISD4rK8Py0WPnQ42bFRNRjkxCJ/BuZM4d/InQhF+nBcAFguwkI3ZDEyn43YJ3vRgcxIbE1ifxOd+/NGIh0W4nYU7P+I7i/CwGu8GQcxzrQ/s+1iPby3YHDryfersn090iI8NxPvp9dd53x5c+DC65Ws/PtOx1o9vw/g+ibW5fcSyxOZ1zbVbuqs3NVfvuK3fcd245UTctiEe2RPPXYnn7uuP3VYf+hGPdD9Osr59oLjxp+dfA3rhWhDYDT42HKPg1B64Op3LLdXKq5KubFeoaVNqbDlfXHU2KuWAqUx3LVAAACAASURBVBPOKYBLmolXhZ1bdY+ACsQ0GaWpzKqmrPp226zcdjq4sTg6wdYU5lSYaMNCDw5GuGiFQCeEeDCE+FBCfZnD/SkRASyRQUwRgYyhAaQr/gjyhZ8n3F3g4ghnRzjZw8EWltYwN4eBPtTUICcNEWGIS0HPHO6Xd0QmIjUVSXFwdgS/JLYdxUFOiEkyy+sxGjjs9Qg5GZ5yNqNEoqxOubJBq7xao6xCOTdbLC7mVFDgXjcnkqUxzPRgpgcTHZjqwoIKayPYm8LeFHbGsDaCue5PhF7aKPPbMpB5vKPwaFXhwVR/clwQmisOP5pwvNfn1FdyPjLgF2VFiKuSRZTJQvJkPllmPlnm/yI8IsV0UIzpgCjloDAzuwCZXYDxiDj5tDyrvD6zttVWK7dtHgEU30tk30tkNz+SnSuoliQlLYhLQ1CKQVAKZ8TALQweEQqnFKOQIkmdRnLxQXwWpa5LqKlHIadYKCTjXEy+TGqZRlYlLbfGrLjJprTNpqzdurTNpqrLpbbdqaLG1NmW5GKEnEtbW9OOlZYZ1jSZldQYlNZZVDY6VDSYFVcrRKduzcpHB51vbpnW1KWUkn0mMUMgLlM4rUCuqFyhtEattkmluYqnOwtTmVjIx3Q2prIwkYLJH+uks/GkEi/q8LQcQ6noTUBHDDpi0BGN9ii0RKElCh1R6IhGR/RPhPQYDCRgOBlTqZhKxXQG5nKxVIQ7VXjRhfdjbKvTYsSSKvHAevNl8OY/8cSfIcQ9Q2KK67cBFMfB0oZB1+aonu1OfQs4OZPCws76eJPdXZhsLEh66pAVheBpnD3xP4T/dsLcnwKvpWIpF390YH0Cq8PYHMfqIP5uxqNC3MzAnWzcz8OdfDyswh9d+HptNzFx5Hsb1toZiJFDG1PHvj9WIN6lEa/LiZfBG3dkv44e/j60+8MQvtLxdRDfJrG2wEvc0Nq8bbV522r9tvHas2DiWSjxJIC4Zb26qLY6L782f2FtzpD4PZh4qPZmGJ8eK3/+1e7zNct0S5LEUcjthuReqAiSgvyFcyuUc2rFcutE82rECsq5k3L2+0Ux69nirByOi+GoLA7Kg08ZQpqQ1ccFU1BtKZauO2zcWGydmZysYGsKKypsqXAzha8trrgwhHkyhnoyhnmRw70pIT6kEB9SiC8u+eCSD3y84OEKJzvYWsHWClZWP8dSqVSoq0NGDuKiOCcISWkYWsIjhCkqCYmpiI2EjSXOCGPrIbCfhKAI6bwqk4bZTlvvQ36xnIn5QkV1SjUterWtBtV1mqXlCtm5Yglxp/18t1ubwUAbeuowUIOhOmiaMNODpQGsDGFpAAsqzHRgqgWaIjw1UOrDOph1oqv4+NWC/Yl+iL2MluqD9yfs79Dt+kulogL3qSgyiCiThBRJgnIUXhkKrwwLjzQTlzTplCQOS5J/IDwgyrJfkLxfmMQlzSSgskPJiEK1ZbX3ZPMKYvK7zOB7iezuQ7Zxhq4Zg4I6xKQgKMX4fxCST0kyCsmTVQxIdq6ISMLVVr5mumxxtVhwCk9kzvmkYvX0MoOsSuOCesuiZsviFouiZsurnc7VrQ7F5Yb2lnA1RmHo9vYMjrIq46pmy8Iaw4Ia8+J6+9I6s7xKhYhktoxctHXzzS3T2vu0ckrE0otkkgvkM8rVy6u1Kuq1a1rUW6p5uzIxko7ZLExlYCoL48m4loL5NCxl4nYh7hRiLg09CeiK+ymwIxotUWiORFME2iLQHon2KHREojMKvbEYSsJoKq6lYzoL83lYKcHNCtyvw4sevB/Ht6mzGwvSxC3DzSdexF8xxNt44rkbcV3t10HkRsPYgnTB+ICqMcnUApf8kZvE4+sNV0dY0KCjAjlRiJyGAAcEOf6HUJIfmMvAVAqm0zGViplMvGzD+gRWB7E+grUBvG3BwwLcSsOdbNzLxZ1sPK/Dry14Nwpiat9aB+PXZmz04uswvo6DuK1N3DDcXBInpk6s0w+s9jO/G8LbVryn4+MYVhckiDsWxIOLxENv4oHb2n1b4pEn8cCLuGm2saJIXFck7poQDzy+33RYnzj9eRTEc62Pdy3eDlGLXffInILhQVw4CGd11vRYsauNSqUtkjlVglfb1MrqziTn7g+O2mLlzCqrTjkrSeGRZuKWg4gyg4wmWYnKpGFMNrRmMndmtnJhtHCCuwNcbeBkDhdzXLRCkD1DmDMp1AVh7pRQD4Yr7rjijiB3BLrBzw1+bnBzhpM97KxgbfFzIJVGg4EBNLWhqARJSQiJQEiEJKMIU3v4RTFHpSIxFRGhMDYFlwAoh7CPA9xCOCfLLK/DZuCw0+Uye0Ta6ZwK6apmrfp2WmOLXnWdekmFXF6OWHQUx0XXbZZGMNSGjiJ0FKGnDAM10DRhog0THZjowEQbZtowVoKbGoq9KIOZnN3FpyrzD8X7kOKuoK3u2P1J21s9lj2l56OCDykrk0WUGYQUISjHyCfLzCvDwiO9hVOKzCHBsF+CkV2c6aAYy0ExloPClOMiJF55FjHNParGJEP7LY7erL6XyAGXyX7BZDdvko0ztGiQVfkRPvUTIacguIVIHGJkQTmKsh7Zwh7BUSht4Gymy1Y0nA9IPBmaIRyXr5JcpJtWapRTbZpXb5rfYJRXb1reYVfZZJtXpGVlCldjFIfv7sw6VVVvXdfuUFxjkl9tVlRnV1JrnluhEJ60Iz0HLZ08Myum3UP6hbWKeVXqGeXquXUGVfX6ZY06NS3qzVU8LekYSMREGkZSMJqGkQRMJmE+DfPpWMjBdBZ6Y9AR97PaY9EWg5YotISjOQwtYWgNR1skuiLRFY3+eAwnYywNi3lYKcStctyrxt1q3KvBb+34qx8fJ49tzp0jrisSd82J34OIN3HEXyGbT52eDiM3BsYWFCXqHnUDuDihIJ7UUcwTFAg3Z1gYQ08dKlI4zw9Rbohy49yZn99mJM4CsxmYTMZ0Oq6l/URIXMPaENaGfiJ8kIebqbiXhXu5uJ2F53W4W4OXdKyOkj4343UF3jTiVSv+KMGXNvzTgjet+NKCrzX40oa/u/C2DW/p+DTOsrokT9yxJx4EEg8CiXsXiZsaxAqNWDDenNPcXJQhbilt3DJbW3EnHjgTEyeJRfbVh2qvZjR/bZarCzosfxZRSkgy2l0VKVmaIV5cIVjbKVtcI1FWp1xWfTwmhcErEOY2LPIKrILCW4UkdorIsYnJ7ZRR3q2ssVVNl0nflGRmz2jlTrLyhJczPBzhYQcvW/jbM15yJIc44oo9It0ooW7kK24IdoGfM3ydcNEJXo5wsIWdFazMYWUGM1OSCQ1UKrR0oK4JBUWISUJUjCQuQVFWZ7Jxo1xO2BmbgcQUhF2BEQ0cAmA5jJ0c4BIAnwRZQo1Jy3KLjc+O4LhjyQXCRbWqVU167XTT5jZqdcOF8mrFvBzxqHDuiy77HCy3qclCTRYX5KCpCB1V6Gv8LBNtmOvAWAmuqij0YPwvwjhvxIegvfHo/Unb693m3SWS0cHHVFWZxdQgoswgrMB0Vm4Lnywbr8xWLknmk+JM/xfhIVEyhxj5rOJWKR32C6YwcqA4+TL7XiIHhsD/EsXNm2TrCA1DyChDWBwCkiQBSXCL4pQAuAQYTogynZNlVtQhmdjALxQF1Ucb6eevNkn6xB27kiYQk6sUn6+VXETNrKBl1xjk1FJzao1L22zKGyyy89UtaHA1RknEnq5sroZmx8Yu59I6s4Iaq+I6p5Ja87xKpfCkHWnZaOzknlkx7R2llTVq5NVrZ1Xr5TebVdUblNXrVjWpNpRzNaWiLx5jKRhORl88+n+EQKdgKgXXMjGahrYItMehIx5d/yJsjUZLOJpC0RSC5lC0RqArEt0xGEjASArGM3CzDHcq8agBT5rwoA73avG4CS+78Ucfvo6zE7PniGUN4pEb8Vcs8TaeeB362xgK4mFqwapE3aVpiEAfNBawTjfyhobCywNWZjDUhqYCFMUgdRbn+cDP/bMZivMBwykYT8V0GmaSsJiC32rwbQhrYyAmsTGI9214WY57WbiVittpuJOFu8V4WIXfmvCGjrWBox9b2V5X4G0V/rmK93V4V4s3NXhdh1dX8bIGH7vwtg0f6Pg+xk4snCduaRN3TDZv0taWaauLkuvLCpvLqmvLyhs35DdvaxE3zTaWHIhbyu8HRIi7tM37GjN0zA+dTfaHIS889JBrxtoQwFOaI1NYr9bUcKGpVi6vXiy7+HRw1HYHr21GVjskVElnxHFGiolPgU1QAWIqjDKazCp623RNtxtbs1o5szq6s3q44aIr/F1w2ZkU5sQW5rQzxGVXqOuOUCdSqBMpyBF+tvC0grsF3C3gagUXKzhZwN4Y9sawpcHSADRdUDWhp05SU4GCIqSUIK9G0jaGox+uJCApC2Hx8Lu0k2rAfIITe47iGB/YeXBckoVPgVnOYLuxG7t72ImQdKG0KuXidmpLj2kb3by526S6Wbe4QiktWyQ86rhvwDYLc7KaCs4LQ04UmrLQUwBVBaaasNCCsQaMVOGsjnRHDGaeGS7hLYhDhDsSotBUyfl0OmChXaG/gic1XOCCCsQUySIKJEE5RkE5Cp8sM4805bQk80lxpj0i2CXMwC7CdFiE5bgImUuCJKbCqGjAqmlBNnRisfFlcrsM3xD4XoKrB2ztQNWDkjykJCEpjrNCOCMIbmFwnAWPIIlLCOdVWXSsKQ4BSC9mb+2VbO8SD8k66ZvA7Z8sFZavFVOsmVSmnlVNza6kFbbRksudijtc4jJE7agINkdZHFpypVrbXeranOo7XSra3IsaXMrqbPNKlaOT2bOy0djGOXlNa3zStK3DtKLGuLiOWtSsW95gXdRgWt6kXVPO15gKejyGEtEbg/EkjMZgIgrzsZhPwFg8+uLRkYC2KHTEoDOGoS0KTRFoikBDGBqusLZeRtsVtISiMxZDyeiLw1AMFjIY7pTj12Y8bsHDGjyuwdNqPK3Dyza8oePbCIhZTmJJlrhtRPzmRbwOJ97Gv5iXTImFjjWUaSy6RkgNwVzLnod0JETB0x6u5gy2ehRDJWhLQ1kY6mKQEsB5fkjwQZwXGE3DeCqmUjAVj5kkPKvC10FsjGFtBF/78b4dL6rxqAB3sn+eSG8X4G4ZHtXgP+34RP/lfTPzX+V4cxXva/ChHm+q8Xc1/q7Fq2q8qsOHbnyg41Mfvo5sX53mIBbENq8rESs6Gyu63xcF1pcVNpfV15Y0Nq6rbd7WJW6ZbKzYrC0rEIuaxH3z19OSnZXobtgW6wVDAVw0QIHl1uZgnvI8ueJG9ZYmjZYG+fwG8fR8joBwFlt3FkPLXf8XoYA8hJUYpNVZlHRYtYxYDayYLRwpNm4UD0/4eiDYA+Hu26Pd98Z47I/0/CXc65dQJ8olR3KgHXyt4G4GF1M4GMPRFC7mcDD7idDOGLY0mBnAWA9UTUYtdSirQFEVKtpMhhYUz0CEpyA5C1FxuBiwVUuH4ehJ7DuM4zw4dAYnRJm4pMlimhRtm+32AQcDEs4klMjkNqrXdZm00i3ae62au81qm/SLy1XS0kUiozi9vQ+YmZIuKEJFCurSUJeGjgKM1GCqBiNVGKnCUQNpDuhP4+nN584MR4Q7EqPRUs39bCZwvk2uv4InLeKcmjLEFMnCCkw/nmvzylB4pCmnJCgcYuQ9ItgjQmIXoRwR3XJClOkHQgXqFm0rZiNnVls/ZrfLDF5XGLyCGBzdYWkNXR3Iy0NSEmKS4BfGGUFwCeE4Lzh4cJIfEspbNC3INj6Iz9nZ0CXURT+fmHP4UtzhkHjBqGyl2EKllDK13Br9omrTvFat5Aqbgnab2IyzjjSE2aEqGe1F5+tb7KpbrCrb7cvbHAvr7QvrLTLL5SJT9qTnoKnj5Pi05tC4WVOHZUWDRXmTaUmrQWG9SV4DtahBpbKMqzYFPXEYSUBvNOhR6AvHSARmYjEbh9F4DCSgLxV98eiKRlsomsPRGQt6ItqiUBuMzhB0hqEtBO1R6E9AbyxGE3G9EPdq8HsHnnfhSTOeNeBpHX6txe8t+KsTX4ZATB8lFsSImzrEEyfiP1eIN9Evls6nxkHHGmpmLCbmyI3Bra5jv/Yzp8bD2wluFrA3YDRRh4ES1MWhKQFFcSiIQk4YskLAeCrGkjCRhLF4TCfiaRW+DmJ9HJvjWBvGRzr+bsZvlXhQgFu5uJGNm3m4VYDbpXjWgLedO/9uYHxVjn+q8K4a7+vw+ir+KMefNXhVgz8a8ZGOryOnvozs+zRCej+Gz1P4PntiY1GSWFH9tsS5vixLLOtvLBkRK9TN2/rELcONG0bfFxWIh1bf5/RmavcUp6E0DxEeMBaEnylK7Xe0h5yrLJIva9HqaNNtb1YuaBRLyDh0MZhk6cxINd9+XpWJV5KBR5qJT4GNVw5CiiQJNSY5bVY1AxY9c7KpHZOlM6OnF3y8ccWHNdqPPc7vcJzfsVjfg1G+By47bQ922OpnzehuBgcDWOnBRh+2VDgYw54Ge9q/u+v+/UppokvS1YGWFtR1oWNIMXdg8Qslx2YwJGchMgbuHqyqyjh6HAcPgeMMjvOAU5DCJQx+Wcjrkw2ct7uFHg3L4k+vlKts0W/oMWsftO0asGujWza0GpVUqGbmno9LEvD1PWBmStLTgIYCLkhBSxZUFRipgKoKmiqcNZHpSO5N4enMOpUYjAh3JMeio57vt9mg6Sap/gqezGghVSWIKFKE5Mn/FcglzfQD4S9ipL2iTP9FeFqKQUyFpEBl0rFmoblstfVjdg0me14mewRQ7FwZTC2gqQFpWUhI/ETILYBTAjjMjYMcOMoDYVmKiiGjmSvCkklVLbw9vVIFRQdj4/aERHNFpoiHZ0nGFcinlmmnlxlmNsonVpjmtpqEJR+3pyHcAZXJaC+SqGm0qmw0vdpqUdZiV9hgW9Bonl4hH5q2NyUTjZ2co7NavWOmdR2WVS0O5a02pS3GOQ2G6fW62fUqxSUcNYnoisFwLPoi0R2J3nAMR2EuHovJWEjDXC6Wi7GQi+ksjKdhOAXjGZjIwUAy2iLQ/i/Ctgj0xaEvDiNJWC7C/Tr83o1XPXjaimeNeFyDB1X4tR6vWvGhH+tT2zbneddXVDYeWBAvLhKvQ5+vSCXHg2oFTQsWO0dczaQ8Hub+ffhQbgoCXeFlCVcjBjsdWGmAKguqDNQkoCoOZVEoiQAjSRiOx2g8xuMwnYSHZXjXg8/9+EDHuy78/SOUqwx3C3AzB8vZWMnC9VzcKMSTWvzVwfpXI+lFGf6+ir/L8aEOb2rwqgKvavB7Lf5qxddBrE4rfJ0892kcH0bxYRSfJrExx0UsSX5fPrmxIkesmBDLlsSy6eZNw41bemvXtVdX1IlHDg9bJa/GITMZOZkIcYexCIKtcdV1V3eEYHWpUmW7XneXbkeLYl6DQGTiXldfmNhC13T7eVUmPikSrwyFT4GVV47Er0AWU6HIaDIr67HoGDMZ2VDMHeHhAR8vhPrtjA88mhR0KjGQIy7gSLTfwVCXvcH22zzNYa8HU00Yq8NMCxa6sDGAjQFsDWFHg70xHM1gbw4HM1gbwJgKKhUGxjC12uLoznopijkxG6kZiIimODiSZKTBcQxHj4LrDLh5wSNI5uQHlygEVKBmxmThuzcwnjMmX7ikXqumg9bab909aP/DYX2LYXm1Rk6hZEwCr6/vAQcbNhNd6ClDWwH6iqAqQl8ZNHW46SDDhbkvlb8942SsPyI9kBoPeovQs7nA8Xrh/sozufHi/0XII8vII830r0DKYTEmdnGm/yI8Kc7MLU0SVyUpGjDrWLOYOLPZ+rG5BDG7BpOd/bZYOFIMTUkqKoxikhARh6gkzomAWwCn+HCQE/uP4+Ap8IgyyGqRTBwRHIOS2hNdveKl5Ucj4/f4hx27FC8SnC4VkqcQU6ITW2KUUSuXVmWd12YaFn/M0RARDqhKQleRdG2dWW2dSW2zSVWzdVmdbVGDZUal8uXMw/FpaOg8MTKnQ5+wrOmxq2p3Lm+1KWyg5tSZpNZQs6ovlBbw1MSjOxIj0egPQ3ckeiIxEouFVNzLx/1SPKrG4wY8qMCvtXhUj5vlWCrEYiGu5WEsCz1xoMegPQxt4RiIJw8mYiwFC/l42ICXdLyi41krnjThUQ3uVeJxHX5vxhs6vk9iY45zben8+h194jcX4q/AJ4vC8dHQMYeuJbOnJzpKmF5Onns1crIoA5fccNESHjQ4U+GoB1MlmChAUxIa4lAXwwVRYCgBgzEYicN4HKbicT0XT6rwpAb3C3A3F7eycTMLK1m4no3r2VjJwXIGruf8i7CN7Y968rMy/HEVf1bhcxs+d+J1M/5owssm/N2JL2NYndddnZX9em3/5wl8GsOXCazO7t9cFFy/wUvcVCVuWBLLtptLpuvXqes3dNaua6/e0CMeuMzXiKUGIzUZ8UnwdYKFDEIcUOu5szdGuKZMubJdr6dbr71ZIavmTEj0dgcPGFlBx3iblBrzWWkSrwyFV57ljBz5nCKLkMqW8xosCrqs6jSKgRWjiQOjiwd8vEhh/r/EXTqefJkr6RJnfODRyID9Ye7sgQ7b3IxhpgWqIvSUYKQGM23Y6MJWD7ZU2BrCngYHUziZw9kSjuawMoWlGcxtYO9E8fLbHhZLSstGSjoiIlltrXBeFKc5wM0BvjMQOAshIRK3ALiEwCMLSV1GPYdt7leOhKVw51WpV7QYNtOt2/vtOwYcOvvtW3os69tNiqrks/IlYhLOBgVxuDjsNtGHnjI05aCjAF1FGKnBRRsZLsz0lLPN6RyRfojyQloSBjpFns0FDlby9VeeKU6VVlOGgNIWfgVmnh+DS5KMxyTIh8WYDomS2cWZfxGhsAuxHBHdckqChUeWQUKDpGjIpGvJbOzEau3DYh9AcQqg2HptpdmyaRoySSswCYhCQBQiEuARAZcATvLiIAcOnMSBkzjBCzFFBpodAiKRW3qggy5UVi8QknjE/coxz1gh39Tzl3PkIou0YooNM8vlCmqcS9tsomI5LhojxR2tGQzj1SodtQatNTrt9dTmOuOaasurdVa5lRqhGdwJiahvPTAyp9M3Y9vY73y1w6m0gZZToZxbbZJRbphVeqE4h7cmGr0RGI3GQCjaQ9EbiakU3C/Hq2b82YJn9XhUjSfleFaPZw14VIP7NXjcyPSgHouVmCnBRA66YtAcht4YxqEETKViJR+PW/HnAP7qZ3zegV+bcb8Wd6vxaz2eN+LPHnwZw9rcwc0lsfXbmsQTO+IP3xtTHBGh0DGGoTXTpUAM1uH17LlXQ9ylGbjsCh8LeNHgYQgPQ9iqw1oFhvIwkIO+DPSkgKEEDPxIro7DcBSmEjCfjulULCZjIRHTCZhJxFwyFtKxmIGlTFxPw/Uc3CjAw0r83kR+XoXHxXhRjf804Ws/69rI/o8D297Qt7zuIb/u3f11gnN1Xn9jTnFjjmvtGtYm8G0K32YOrS3wb1yXIG5pETfNiWXz9UX9tRXdjRvU9euGqzeNiKf+D/toqVcQEQP/MDhbwk4ZES5o8t81EC9SW65ytUO/p1uvtVE6tfxYcPhWWxcYWECXtkNanY1fhswrQ+GWpZyRY+ZTYBVU3iqhxiKnzaxmwKxtSabZkV084ONNCQ1gjws+mXLldNIlzuigoxH+7CHuewMcWJxNYaoJXUVoy0NfGQZqsNSEtTZs9WBjADsjOJjBxQpuNvCwhYstHO3g6AIPT2b/S1tj4snp2UhKRUQEo7kpJIXAzw2BMxDkg6gQJEQgIARuYXBJkASVyco0FkuPPf5hx1IK5QpqNKs7TFroNu399t2Djl0DDh19dleb1EtqVHIL5ZKSRUMvn3Sz32GsB10l6ClBWxlUNThqIdmJ1J18uin9WIQ/YnyQmYLhHomns349xRz9lZxXc5TV1SCgtIVPnsIlTT4lyXhE/F+BIkz7xbbsFabsE2Q+IrqFS5KVX4F8XotBmUbWt2Y1cd5p7b3N1o/Z2ofF1GWblhlFXptBVGYrjxDOCINfHGeEfyI8dBIHT+HASRzmhIAMg6E1k/dlpOWxtfcI1tKVI9JOOwUdcL1y6mIUZ1ACV3SqUFK6ZGbB+eJyu7I6k5iwnVcsUXEZw8VYaVEca1AcrpcabpAdqFNuq9JsraWWVyonZHGlxqOhYffIjObwgn37kHNli2VepUpmwbniUo3cItX8ArmKDM6mWAzHYiYJY7EYiMJUKh5W4l0fy9rkrg8D+L0Z9yvwtAqPK3G3HA+r8Rf95Pdrim9GeR+043EX7jRgNBMtEWgLRXckxhNxPZ/pcSv+Gtjz98DxF5143IK7NbhZjnvVeNaIPzrwYQgbMweIFZGNW5rEIxvid5/pIbaQS9AzhoUjJSoc19rxbuncy0GekhRccYafObyNcNEQ3kZw1oKzJsyUYaoEYwUYyQIj8eiPwlAMRmIxHIXRGEwkYiQOiymYT8JsAmaSMZeKmXTMpONaKm6k43o2VvJwswQPy3GnEHcL8KIavzXgXT/j19HDn8c4v00Jf5mS/Dgp/eWa4uqcBjGvRMyJEtc4NiZ2fZ/c93WG89uS8MaSMnFDj7hhsrmsv7qotnZdg7hlRNyyXrtnQfwn8uON4NTw3f5h8A2DrSlsVBDrhfZLv4wki9VXqlV1Uuk9+q2N0kll+4PCtts4g2oOXdoOGY1t52TJPNJMXNJkbllmXnmWcwpsQipbzmtQFPVJWmaM+jZkR3dc9GS87LsvJvBEYhBnfOCJCP+DoX57gp1Zve0ZXMxgqQsDVegoQFsBOoowV4GVOmx0YU+FPQ0u5vC0g7czAl1JPi7wcIO3N3yDmEND2RISkZ2D+CSEhzOY0yApBHF+SAlCnB/SwjgvAhFhnBHBKTEypxSDmBp0LZmdvfddSuRPLJAvaaDWdVu19Tl0D7v2jLjRB12ae2j17QZX6zXyixVSUkXDQ7i8XHbZSy4YVgAAIABJREFUmMNEGwZaMNKEow6SndCZytmcfSwmGDE+yErFKP38k2mfttwDA1Wn64rUtDQhoLSFV56FS5rMIUE6LEb6IXCfMJldlGW3EPMvApQjomynpVgElCgyOoyqpsyGdjvMXPfY+Oyw8WW18GDWt2dWopJFlSAguY2TH5yC4BMFtxC4BHCKD4dPYT8HDpzEoZPgEyfpmjE6+SAuDW3dfD0j6okZHJ5+zD7+W8JCmTPi2SqzTzTn85WWiVZWmZVXqsSEItkdvSlYbsC9Lv5bdJ6VriPLHcfnW/jG6iUHmpRbGyTyC/fnJqGplmV0UmViwb5z0LGkVi+zQDAr53B1qVh5oUhF4dmG3H29aZjLwq0iLOXhdj6e1OBdHzZmt23Osb0fwot2PG3Ei3o8q8X9KjxuxKcxaeKmzeqi2tM+vBnlfjvG96R932QBehPQGYWReKzk43E73gxzfhwV+7PvyPMO3K3D9VLcLsOzRrxoxZterE7tIZZFiFuaxH0r4lfPkV5cDoKRJbOzx/aMeCz34fMNof/0nytKwmUn+JnDh4aLhvChwU0XHnoMdho/W6KFIjAch96InyllwzGYTMB0KiaTcC0WUzGYjMd0EmbSMZeJ2UxcS/+JcDEbi3lYKcByFm7l4vda3KnCiw687t/zYZxnY0mFuG7wbYH6Zc7w+6wqMa9EzEoRUwKbY5xfJzg/z579uCyyvqBOXDcgrhuvL2utLimu37hA3LYg7roRjx2J1wnrT+PjwnZfvILgOGZbS5jLI8EXXaH7xtPON1Zr1HQb9tINWpokE0p+CQrdbe0Eqjn0jHfKam7/gZBTivGkDOWnQ0UmCTWynC5Jwxi6ViQ7F3i4kYK8doX5HY7yPx7hezjEe2+w17afg0KWsDWCieaPZGNckIGpEizVYK0DeyocjOFm/WMHM654swR6wt8b/oG4fHlrRCRbYgpychGXiLAwmBlBSgiyQpATw3lByIhCSggiwuAVBocw+Zgo+GWhYkCyct7lEXI0NFU4r0qzusPsB0L6qHv3sGvHkE0b3byujVpRe6GwSCEzTTwmjDvI96C1MZOFIcz04KKPVFd0p3O25R2PD0WsL7JSMdYr+fjaxZbsfQNVpxtLNXS0wa+0jVeehVOKfESc4bAY6cC/CH8RoewSpPwiwHJElI1beougMousLpOaGYuJ415LD3Zb393WPizGbmRtKyZpLZyTBr/4tlNnGU7y44wITgv+D+G+4zh4CodOgleMpGlIsnZBeALae84ODiumpu7280SYP/Ji0Vm4+3rrued9ih1tsu2tlnW1MqnRKA3BQhWe0PFs4OCLMbanQ/i1H3d6di20nZnukuzvEKiq3F6aiuZqyuio4sS8TduAVWGFUmbWqczsbU1lXFUlHPVlx7uKMZaPO2V42oAHtfijHm+7sDqG9Wl8HMXLbjzvwMtuvGzAi1b81obnbfgwrEAs2X2e03o2sG9tTpe4Y7x5XfPFAOdSBYbSMJ6KG8X4vZfhy4wEsaD+ZUrsnyGWX9twuwp3y/GsAc+b8Xc3vk1s/4nwng3xyGOwB0GXYGq7/aIve24abg3j6y3BPwcEC+MR4ogAc/jTSL6G8Kfhoj58DVg9qXDXg4s2nDSB4VgMxWAwCkORGI7CWBQmYjEVj2uxuBaL6TjMJGI26d9Kxnw6FjIwl4rpRMyn4Ho27ubhTj5+K2Z7XoM/6Pg6K0KsUD+PynzsxeY1rM3xECsqxIL62hj/x0F8GcfGHA+xoPRtxXT9pilxg7qxdGFj6QJxw4C4Y0Pcdvj8TxDxOfbtU/+IYERG7vEP2uloBnMFpPiiNJazKl2mtZba1W3U2HWhvEE2JpPbIXivsTNJywLaZjuV9HfyyTMekyCdkN1yQpZ8QoZ8UpbEJ88orkqW12FSNWTUMIaNDcXViRToRQnz3RvheyTM++glz10BnvBxg6cDHC1hbQQzPRiqQ0cB6tLQUwBVCeaasDOAkzFczOFliyBnXPFGiD85KBAXA+B/BbGJSMtkSMtCUhr8fGGuD20FaMlCQxpqElATgYII5IWgIAZ5cYgI47Qg+BSYpY2O09zhGXUkqVCxtMG0qd2xp9d1YNBtYNBxYMSDPuDc1evQ1m1T12xcUqGZmSuXnC4REX7YzZnZ1hAeekhzQG8qR3cBd9wVRPqiOAcTPQZPZ72rkjFWL9xaQtXRAb8CM5/sFi5JVg6RLQeFWdmFWNhFKL+IUPYKU/aKMh0QJR+TIPEoQFQLKsYkXVsy1R42HmxO/nvsPbcb2bAqU7cLy2/jENnyiwBlHz/pMD9O8oOLHyf5cYwPh87g+DGwn8BOHhwRh7AqK82aPTqOra4BS4MaM22yI2WcY/m4VY1/uvG9C98bQMxdIG7YvJ2wpWccqI3BcgP+6DvyduDc5wnGz1P7Pk1yvxsXfD0m++eI/G/9svc6RceaMNmGxRHBlVnzvk6tvMw9OaloqkRfGQbLMVqJ6UosV+NBI/7owrs+/DNC+jixa3368PrUtq/D+NCH9/14P4hPg/g8hPf9eNOPD8P4qxfPO/AHHevzesR1C+K+A/HQ8fsNw38mRV92s/3ahPWZcxsrcsR9Q+KR1bfrBn8NnXtah/tFeFKL35vxDx1fJ0AsCBLXtYm7JsQDq5561kAf2LogJB6VJbg7yPNxRfa3EeTEItQFXsbwoJE8DRgvGpCCaVsvG+7yNqRcNGDy1Cd56DFgKAaD0eiPwGAEBiMwHIXxGEzEYirmX4Tx/5/DuSwsZ2MpE3MpmE/BSibu5OJOLu5k424pHjXj9cih1XnFT6OC/9DxcRifpw9vzosSiyrEjOC3SXycwJdrh7/PiK8uGa0v6qwvqK8tqKwvqK+tGBC3bYj77qv/pBOf8h/PuV72Q3A4xfvSFgcLWKojywc18Rx16eKtVerdXdr17XKltcJJWSfsg/YZO5O0LaFtzqakv41PnvGoJMMxGRYOOcopOcoZOWYBpS2S6qzyOiyqVKYLRmRzczjY4qILgt1Zr3iwX3Y/EOi2zd8dvi7wcoCLJexosNSDsQb0FKAhDW056CmApg4rfdgbw8kcXrbw/y9Cf9LFAASEIC4J6VmM6dlISUGwD6wNYKAMqiL0FX5evi9IQVUCahJQkYS4CHgFcFqK4ZzGHm1b2AXuC0sTyy5Tv9ps3E637x92Gx7xHBrzGhjx6Bty7el3auu2qW2ilVRo5hWpJKfzBgft87Rj8jNGuiN6ko935XMlhCImAKV5mKQbPpryqEjAaJ1Qe5mhnh7Oym3hkaacFGc+LsxyQIjlFyHyPmEKuwjTLyKUA6KUQ+KUE1Lkc4okGR3GC+YUfTs2Y9ctVl7b7Ly3WbpS9K1ZFfV38siy7effsvssee9Z0pGzOMmPUwI4JYBjfDjCg/0cYDuILUdxVBDSqmRLSySGo7EUM814NaFI3PInFize9eI/TXhTh891+DKyb2NW7v2YxnjeFnoa7nfizciuT2OHv0xyf7/G/33m/NdZxS/zGp+WtP6ZU3s1IXe9G0t03BoTvX1Nf6hdqjwTlZnoq8FEJWaqMV+L63W434jfO/B2AN/Hye+mDn6bPbmxeIaY41ydwJdhfB7ClxF8HcbqBL6N4sMQ3g3iZRd+a8N/erF6TZpYUCNu04gnDsRvzsSvVpt3tb9dlyVuqm7e1dt8bEu88CB+c/m8dOH39u23i/GoGs/+i3BegFhRJ24bEfeM26oR4A1HD4bIFNRV4P4Iz8cV2adDyIrEFRd4msHLlMnNEB5U+FCZfHVZfIzYfIzYvA1ZvQ1Z0R+Fvkj0haM3DAPhGIzAUDTGYzARg4lYTMZhKh7XEjGdhJlkzCRjNhPzP6YuEnEtAfMpWMrAUgYWM7BYgBvVeEbHxxnBz1O8f/Xj7z68md76efYsMS9HLIqtzrF9uoaPs0e+LZ4nVvRX59TWZhTXF9XWl3VWV0zW7zsTz4OIt3XEu9qhZn0/X/hGMnmGMtvZwk4HJQHoyeDqyJHsrFKj9+jUtp7PKeOMT99n47/H2JlJ14qkY7FNmbqdX4F0VJLhqDSFQ5qJQ5qJW5aZX55NVGmrtDqLnDZZSZfRhAZrC7jawdcRQY7bgxx3B7hsCXCFnzO87eFhDScz2BnAXBtGqtBXgKYctORBVYOZHqxpsDeHmy28nUmXvUgh/luC/Ele/ggMRXwyMnKQkYP0RFz2hZMRLNVh8d8Fr4qgqkBHHtpy0JKDrCTOCYFbGKclGRX1SYaOu73COGOzxAqq1Ro6jHsGnAeHLw6NeQ2Oeg6MePQPu/UOunTQ7epbTCpr9XMLBcOjjgd4bA+yRLoTupMOdeVzJUcgPhgVhbjWZ3RnxKk0FqN1Qp01plQqfjyROSHKdFSQwi5A/vFW+6AII7sI02ExpuOSFG5ZirAqswJ1i7bVVkPHneY+uy28t5m7sxg6kjQtWCS1tp+QYGPhprDwkLbzkNj5cIIfnILgFATHWRzhAeMJsJxg2HWM6QQH5KUQYI/aRFyrwGI5/ugGMaVOTOqtD5z72IV/mvFHLf7Tgg90/EM/OpeHsSw868Q/Q/gwgq8TEmszcusL6hsruhu3jTbvGX+/a/D+hsbvE5xPRngejUvcH5ebaD3RkoOOXMzW43o1btbiXgMeNuG3dvxNx5dxbM7s/boouLYiQdyUJlYk1mdPfp/E2jjWJvBtAsQceXN2y9cJvBvEi3Y8a8Nf/fg8tOPT6PFvc1LEXRrxwot4HUi8uUS8DiJ+s9t45rz+0o94G0m8jySe2f1n4PRyMe5X4lkT/u7Ft0lsLgoSNy5s3tZdu6tVXQZfX7gGbEvOJTfX4cEo79sFyQd0pIbjkht87eBny+ZpzuhuBE99uGnCz2iHP22nP21ngPHunwjp4egNQ2/Yz2Y4HIPx6P/jMOEnwtkUzOdgNhOTyRiLxng0phOxkIr5FCxlYakIKxV41IEP186szQt9GN/xfhjv5o+/vyb4/Zr8xpzk1+kD7ybxae7s+k0t4obOxozS6rQCsay9eZP27ZbF+hNv4nU08bFl88+ionQBr0D4xO3yimR3sIKDJor80JN9prNIob1Rt2fI5GqnXFrpyfD03RZeu2iOLHrWjLqWW5WpW88pko5JkY5KU7ikmU5LsXBLb+GVYRGSZxVXZZbV2qKox2JEY7A0g5M1vGwRaMsabL8r2Hn7JVeSvwP8HeBrh4tW8DCHkxFs9WCpBX1V6KnAQB1merCgwdocDjZwc0KwBy75kP194eWPoDAkpiIrDxm5yEpAlB+8LOCkDxc9OOvBSRP26rDQgbk6aKowVIGmIs6L45wQuIUgobzlguF2K8/9wbGnUookyho1m3psunrdewdd+oZc+4fdBkY8BkY8egddWrusaxqNMosFr0Qe9nIl+Vsgwxn0lKM9hXxpEUyxl3G1GNcGTZb7LQtjMFh/jt5gqW8ILomfaywOCTAe5CcdFiQdFyGdEGc4Icp4UpyJR5rCr8B8XoNF1YhVz3ansesua/89Vr7bTT2Y9O0hb0zmVWHeLcSMk0w4TaJwM+zmxQl+cAmBUxAn+XGUF4w82M3NeuDANs79sFRFUzxu1eBOGX6twpMqPK7Bn60gxjWIFVdiQfmfEfzZgPcd+KcDy7mYycTTFvxJxz99+Dh2anVaeHNRaWNFm7hlQtyzXL1r/uUm7eP8hb+nZF5OCj8Z4VlqwXA+Jgtwux4PqvC4Dk8b8awFr9p/5oJtzmz/fkNu/ZYKcVeLuKVOLEutz55cn8bmDFanjxPLp4lFjo3ZPV/G8WcPnrfhTzo+0PG+H5/HD3xfVNh8aE28CibexBPvM4l/Qtb/Dvn+Oob4lEp8SyX+4/Vq7Nx8CW6U4WkjXvfhyySFWBIjbmlu3tP8fkexuBC+vrh4hT2rZHtHMx6M8v5nWmyxBfEhuOKFYHfKJU92P0c2b2sGH2OSmw7J22iXD223n+kvAebsoEejJwr0cNDD0BuG/n8Rjv634jAWj4lETKXgWirm8zCTibH4n1xnkrCQjoV0zGdhpQDXS/GoGe/HTq3PCq1eO7s2c/rLsujXWcW1ac3NWZXvM/wfJ/8fVXcZFfX3/YH+zcwwhKLY3V1YGCgpJd0gA0N3SXeXIIgoISqCfAFpaRARREU6xAITEUVSQAWk5twH8rv/e9c6Dz7PP+u19jn77H32lj/1Z+dfMEi7zFy9yEydGGlXIa90pt8Yz39xJqOXyPSdoS6PEN9Fjt4U+/ANDr4bTBmwkkScM3Ku7chMPJd7X/P+I53EQvGIxF3u4Yu0LJepG3OpGnIr63FJqnMekaRsE6JtFqTvE+E4KMx1QIjzgBDnIRGukxJcwoqLJTSWqalRdTRhrAtbPTjpU931edyNeTzNuN2N4GEMb1N4mVDdjeCsB3sG7LSgpwyGAi4oQEcF+v/G4jFhYgxnC7hYUxztYecMD39ERnPE3EB0HGIvIdgFToa4qAU7Ldipw1oFloowV4OJMowUYaiIC3KQO4ezp8F/HEdO0wWl2JWYHObu6wKuHoy9K5GSdyGzxKTkgemDR5YPq20qH9tWPblY+dg2v8QgNVMtLO6wo8dyYyNcZCDaGpXXt5XdOhTuyRbqhZQkNDzWbijRTAjCo6wjD/MNVDSw/SR9Kz9t41HapkOUzXxsW4+z7TrFtleQckiQwifEdkyUdlKSKqLAIaPNpWaylGGz3MCZx8CZh+nAqW5GE1THDmGwH6RhByd2UbCHsnQfNh3CrqPYfQw7+LD1AJbxYe1WbF8NheO46Yz3uUv68vHyGl7Hbnt1G2/S8OU+Jp4cJq9tyAeHmU7duYeYeYSJcnTdQUc8enPQX4ihMow9wsRT6lzTAdIqTDpUyWt98spwpl1/qllu7LlQf82+noc8b3LRnIi2W/iQhu40fM3Et2x8z0N/AX6WYaoK88/wt11s7qU8eavJ6row91p5ru3sfMse0rR8rvk4aT/BauFjtewgTWvHH+F7Pr4V4GcZfj/E9BPaTMPh6RdK059s/g6Fzv6+QcYvz49F/h2/Nvsnlvy5PPfd6vtjvuY7eHEHH3MwWIHJp+tIswB5LT/3Rvr3K4G4GFx0gLPPyoTkpcX38a7mcE/tyccZCPCCpwt83ZYHeGz3dFztarnIyXDxRXXufwgdtVY4M1ajNBAl/ij2Q6kPynxR4Y/KIDwKRnXQ/1YIHofiaThqI/D8CuqiUXcVT8JR6Y8KX9QEoj4CTVFojkZHAl4n4XMOhh9gvGrNVPVu0igy3yFM2hVJuzZpVyGtAnNNx2aaJFituqRZYrb+3FyDFKtNjfVab7bTbP6LExkKIBPBrY/kvdzgHLDYLni1oxePmz7CtJF9GcU3t+WnCBUWqmaXKNzJOh6VsNHFE6rGPKqG3KqG3Cr63FIanMelKTuEKVuEOPcLU/+View7S9srSOETo5yUowupLFJWpl5Qg74WLBmw14aLDt1db5GHIaeXEbuvKXeg5bIgq6WBljy+pnQvI3gawlYLZmr/u6/XgL4mjBgw0oOtAezNcNEGdk7wCkRUDHtsAqLjEB3CGeJMczNmc9SDExP2DFzUgK3qwl2tlRqsVGGsCm15yIvjnDAOnaAcE8I5RbYL5rwOAbuDY8/GpincyWMUl5s8eGRZ+dj2UY1d1ZOLFVVW2fmMW0kyXmEHTOyWMnRxkYFYOzyK31V8Y1+gEy75IS2F1vhUtzpf/noAKjMPVpeYqWhhKz990zHahiPUTYcoW49S9p6g8AmxHTtHOSVJOS1FOS0FQVlIKFMVmDRtSy5DR14LNw5Ldy5zV05dGw4pbepOETaeQ1Ts4sYuCnZRF+3F2kPYfmQhEm47iPVbsG8HtM8hwWlJ441VnXfxOgEvr6M2Ci1xeJmIN2noLsXvln3kkxP5mkRahUnDwelny3py0JmMb9nozcGPQgyX4VcVZuuopHkfaRcjr5RIhzppV5+o4x+p2TlQwf21BO+z8DIZrxPxLgVfM/AtCz/y8CMfA4X4WYa/jzD3BDMtInMdiqSTST6Ysz6YsDo1516Lz784QV6Jkw6R+RZ+0naQvNj99yn6C9Cbg96ChZps1vOtMy0is136swP+8xMxrLHIuV8x079jJ39dmx0NmP5i0FezsyMVL1PRk4/RR/j7bPd8sxh5qfj3tcTP9qMJMXBygIfPktvJi0sL0Pn0eNdTgfwU+HvDxwNB/ptCAvf5em70clrhYbXSSX/5RW3ei9q89oxlDjorUBKAYj8U+qDQByXeKPNDRQAeBuJRECqDFkBWhaAmHM8i8TwKVeFouI7WOO5nl1Hhi3JfPAlHyzW8vomPKejNwXAxRkrRm4v+fLCenJqq3zXfIEjqpVm1gnO1O+cadpFmUdKsMdVwbrpJeq5Fkby4QF7pk3eWpMeB/PCY6rPOvrXJ0xVuweusfbm8/HDTB08j0JGFuvS1NZknq0ukCvNO52fvL0pff90fivo8KvrcqobcKgac0pr0E7KUXaK0bcJcfMI4KkLlE6MdFKXvF2Y7KIajUjipwKYgT1FRAVMD5lqw04SjJt2Vwe3GZPczWhpktirMZv1lu01hNmuCLXgCzGj+phRXXcpFdVgow1QFJmowVIehBowYMGPA2hA2lrBzgk8wW3QcV2wCrsbicgB3gCO3qym3kxG7sxEc9OHIgL0mm4MWxUETDlq4qAUbDRir4oIClKVxQhTHhHBaArKaiwxsNzsGHw6KF45Olc4tZBaXm5Q9NP+3CkoN76TIh0WeMHXeqmHArakJGwbi7FEZt7MgdpevHaJCcC9jSdMzZlmG+BVvlGfse/bQWlMPW47TNx+lb+Sjbeaj7j5OOXiWdvIcTUCaJq1MlVKinFNkO6eM8xpQNaQwbblM3ZbY+3A5elNsPWlmzotUjBYfleZYfZSDsocTe9ixh0bfy7b6ALbxYecR7ODD9kM4uQsGckjywfNbaL2B55dRF4G2G2hLxIsEvIph77yJviLMvwDpMSFfb5DXhvPt52Za1/aV41Muvt3Hpwx8yV44K87WYP45J6thC2neN9d0YLpx7/gT2uBD9BbiUw660tGZjLdJeHsX3VnoycH3++gvwGARxsowVQXWE7AahUm7IukyJl+cyVc38sWGfNCZ71Ik7xTIW6m59tOsFj7SvvdvDfrz0ZeDj3noL8LkQ5Cn3KTpCOlUmf9+kTXmP/fzCutXzMzv2OmxK3M/fee/MEeebvlwD1/yMfwI0883zzeeJG0K5LXG31fSI22HM5Lg6wn/AO7ku+ylBeioOdFSJZh0A0GBCAzkiAjfFxF5NCRoh5/Xen+Xze4WG531VjkxVzoxVzrqrkChHwp9UOCNfC8Ue6HUFw/8URGAysAFhJVB/z+Ej8PxMpH3c8a+V7e2PAlFhT9qI9FxC72ZGCrAxAP8rcbPMny4i08pmCzf0VeG4fI1w8Xb+nLY+vLxqwpz9YdZDdJ/GiWmWxVIhxZ5ySRvjchnO9LrQr67DLw1iPKHlyvdI2SbrQ8lJBQPbmG8An3F6EhDfebOllKhx/cPtpYf6Kk58eQm5HQ5lZgc/4KhlBblpBx1txj7dhHuk5JUARm6oPyS03K8/NKcR6XY+OVwUgGKCjQ1FehpLiB01qS7anO569CCjdeFW2yMstsS7bDtiu36MMulwaacQSZUTz12Bw1YKsNcCaYqMP5Xv6YFY01Y6MHaAnZO8A2hXItfHJuAqBhc8lnsbc/jZLrY2YjLxYTN2QgOTNjr0Jy0qU7acGbAUQt2mrBQh54qLihARJ5y6hxOiEJMnkPVcK2p6y63y0dCbgqkZannFOjmlxjcL9bPLWSmZ2tExwp7+OxQM1wmpU5VUYWNNq7b4cH1LfkxO33tcD0cWVk8TbU6BXcFw9xQdm9vXZWdjhG2HOPYdIR9Mx9tyxHaHn7qUUGagCRNVI5LUYtdXoMqqwYZNcgyoG4KA0d2S++lXoGLXX0ozl5UG/clOlYrzyovXX+Si3MXF/Zw/EO4aj+2HsIOvgWE5rKrY12XVt1AbRyeR6IlGk0xeHIFDXFoj0XndfTcxK/7IM+3kxfnWK3K5K39zMvzf9+sHHqO7+XoK8WnTHzMwkAGxgsxVYHpakzWYPIpxp/g52MMP8L3MnzJwfs0dCbjTTLe3sWbVLzPwKdsfL2Pvv8hnH4E1hOQ+jOkXZF8sCTfvEh/AOnzIF8tyWdd0q1B3ivOd5ydaznCatkxWY3BfPzIxZciDJT9Q0glLQdJpwz5ajgzYMcaiWSNX5/7FTs/FklGfUiv7p/aTZ8zMfQQf+s3kPZjpF2SvNQkXczZt/Ij7UfLcxAVjLCw5Slp1JJ8NFcdrynjv3IFly4jLGLV1evHrseeDA3fGxKwPdh7t6/dTnejNW6Gq130VzjrLUeRPwp8ke+F+54o9kKpz0KSZuHDHw8D8CgYNSGouYQnYai9hidXeH+UqY8+lf+Yt7c9fs2LaAwVYOr5TtKwf6p69WT5Ytbjjb8quL/l4VsRvuagvwCDJfhdibnaFVOPMVaByWr8rd3EauEnL5VIpzH57EK++ZGv3uSj851geoALfAOX23kudXXFg4wdfTWc3+7jQzre5KKrgtqRQ+suxJ8aDJVgqkLU3JBiYsJparlCz2KFgh6HiDJEFCCpQtNjwswYhnpgaEBDDecVKULS7EIKS6WVoaYOE23Ya8NJC86aFDcdXne9NSEm68Mttly13XXdYV+03c5Im01hFitCzXj9DbZ6MjkcNGGhDFNZGMvCVB4WSjDSgLEWTPXh4IDgMMTcQPwNRF+Bv8syJzNY68HOcCHd+q/MzUgf1oZw0l/uyljvxljvorPCWgsGyrggByVpSIpDWBLiSnQ1k5VWnls9L+2+FHs28Z5CZoFaSsb5+Dsi4fGnbf23y5tBXJ1TUYOqrwFnXVy2QUXisZSINQG2uBaF/Gy+l01GsVeWR4QgP5uvulTdyZSXfoSyhI+2go8pbNFYAAAgAElEQVR90zHa/lO00+IUKSUoakCDyaGmQ1NlsGswOS4YgmkOcyeKox+nsz/cg+EZBCcfmLnQVYx4DkmwcewDDqzATrYt27FuI9bsxbpjnHsPQOI07rmiPATPrqEuBnXRqI9GczSar6LtGtpi8CoBXzMwXoHZxvXkxTHy8gxpUyHtgnMtm/88x9BD/ChETx56ctCXj4FiDJdjvBK/HuFXBX6WYrgY33PwNQOfU9B1B52J6ExEZxK67uJdCroz0Xcfw4UYLcH4A0xUYbLmfwi7jFk9bmQgmIyGkGF38t2G9NmQDxfIS0HSvos0cU5VY6AAXzPRn4exUsw8BqnnJi375juEp98q/v2gzRqIJAO25Ksc+ShPPl8k3a5T7bK9FWA1SJJ2FdLJnP1gMvPJlHwyJe8ZrNcqnWXryxKREovku8gv351dwnflBmdEzKKwqzuuJRxOSD4TnyR8Nf5MYORRt4C9du4b7ax5bcy4rQxhqQcU+iHfB3meuO+BfE+UeKPUF2V+KPVBqc8CwsogPA5GzaUFhxVB+Jx3jLy1Ii+Y/SU7f+SD1G0kr06Spv1/ytkH8zCcj5/FGK/ATO0KUn9i7unJv1UnSZ0Eea1E2oT/PFozUorBEoxX4u+z/fMNYvMtCqw2tYkW+dHnEomeuOKMUD94esLXFU+yd/xtOdCXj0/J6EjFyzy8zEZ3Hn49wmQNWM/POzlQnJwo9q7cli48DBs2ZUOo6kHLmM3CDLbWNAtTGDChqYXzihRBKbazcjwyqtDUhBkDTjpsrtoUNwbdg7nczXBdqOnacIuNkTabouy2RNltvmK7PtJ2VaTtskjbvUFWy90NYKMOYzkYSkNfFgZyMFCBkSbMjODsjEsRiE1AbByuXIav0xIHE1jqwkIPFnow0oSuGvQ0wNSGmS5s9ZY66q500VnhoMttpQ0DNTCVoSYPaUmIiENYjiLP4GbarLDxWO8ReuBy7Jm4RLF/f841aA/TfrUEE1JaPCraVCMG3PQR5YCHScfuXl4d4ICYaBTfP/6iXj8qhPNSAPKz+Z6Ua7haLOM8SuE9wr7qCH0rP/2QAF1QiiajSlFlUDX12dWZFHUmRVOfXduIomcBC2eag+8i92Cq9yWadwjF1Z9q5bFI23rlKSX6Gn7g4FJsxeodWL8Lqw7S1x6gHDoAhgzy/VAZjmfX8Pwanl9F/VU0RaHxClqi0XodrxLw6R5GyjBZyzvXsm+unZ+0y5C2UzNNq8afor8c3/PRk4cveejNx4/ChYFcYxX4WYbhYgwVoDcLX9Lx/n8Iu+7g3V28T8WHNHzJwsB9jBRhtAS/HmCyCn+fgtVwhrTLzncZsXpcyEAwGb1ERvzID2fyw4F8ZM6+EiFte1hNtIlH6C9ATwa+5WKsFLNPQBo3keZDc+3nWJ1arG6zmd7QmQ9GE62nfjcIszqtSV8Q6Tb61bafdKiRLib5Ykl67ee/O5DvdqTHmHzQ+fpkx+N7yLiF/9KQV7YntWB/WDQtNIo94vqe2NvHbqWKJtwVjbopGHKV3zN4/0WvrXbWvJZmdFN9mDKBAl/c90auB/Lccd8DxV4o8UaJDwp9FoLhg4CFk+G/YNh4iasyGC13MN9uTN6ZT9Ztna5fQxrOkbqdv8sog3kYyEJfBoYLMFMD0gTyin+uYe/PMt6RMvrs0w2zzyhjlRh5gIkH+FOO0WJ8y8WXLHzJxdcC9BShr1TwZfaegljEBOCSA2qTF5PXYiOF6PsPncnoSMXnPPTl488jkBb6ZI2wvw98feEVCPdAjou+sHCFlRNsXCh2DnRnp8V2NuymRmDossko4ZQkBGTo8mrQ1oK1Hpeb3iJP5iIP5lJPw9VeJutDLFdfsl4Vbrvqsv2KSMeVV13WXndfF+e1KcH3cJT7Bj8r2OvAUAG6UmBIgykPhiL0NWBhAndPREQj7iZiryEiBF4O3BdNYaYLYx0YakNTGSpyUJGFmgIYajBl0K106Fa6FCtdmDKgrwGGOtSUIC0NoXM4IwkJZaqyHpe2BY+p61pHv+2ewftd/XdbO29gWK5Q0OMQ14Asc5mmHpcpE17GiHWjPkg6did8eYATYmPxoORs0zNmkA/8fXA/m6+2StvdZgX3Meqyo/R/CA8Lc/zbiGoZ0LUMoKEHDT1oG1F0zSj6lmxmjlQ7z6WeoRy+4Zw+l+AeTHXyX2rqukGaueygONiPcmAr6DtAO8DJcYh72U6cPAQ3HVReRk0Unl3Ds6uojUJdFJqi0BCJxmtoi8ObRHzOwGAxfldjumHbfCsfaROda9775zkGK9FbhM+5+JKDL7n4eh/fCvGjFINlGCzDUDH6C/AjD58z8DEN75PRdQddd/AuCe9T8PFfn3s2BvMxUoSxUvyuwMRjzDynzTcKzLfLznUx57odyUAAGQ0nP0PJgDcZ8GB1G8+8lZp9sX++EROPMFSA3kz05mC0DHO17KRxL6vp7FybIukyJF8dyEAE66Pp7wbhn7Xis12OZPQaGfGa/qRM3uuRr1ak34UMeZNhHzLsTvpsSY/xYPOB+nzkpSA9A1ml+5Nz9gdG0oMjlkbfOHQj+cyde+K308Sv3xENjxHwCjvk4LvN2obb1AxG+tDTAXJ9kO2FHHdkuyHXDfc9kO+FIk8UeKPQB0W+KPdfqPCuCkF1KF5EcNdFoCoC3YV7/jSem20/TDoFZ2vOTD5A3z303cNwHr5loD8HUw8x/Riz9ZiowWA+vqVhIAND2RjJxUQJ5sowUYyhbHQno/MWOm/jfSq6szBadOBbwfrmJNQmovgyOlIopONcfxaGU/EpBa/uYqiMd6oKpBHk9bYPubv9vOEfAP9LCIpY6hvO4x7I5exFdXTDRUd2R5dF1rZsJqYUHSZFSgknJXBClqaqCX0d2kWjpd7Gy32Nl/sYLfM0XellsTrYmjfUZskle+5wR+4o9yVxfusSQ7f/F7k/MeJQTOCGAEfY6kFfAZpS0JKBjiIuKMBQEzbm8PJF5DXcSMC1KIQFwNOOftEUFnow0QVTC2pKUJCGnCRkxaAsAy0V6GqCqQWmFnQ0wdCAsjJk5SEhCUExnDkHYTnKeQ2aEpODYUVn2vKaOqw2tl2vYbJUVosmpU6V1uRSMlyhbcRlpgdvc8R7sxcl8sUF0wNcER+PqgditVXani7w80JezqH6Gl1PuxXcx+i8R9hX8LFv5acfE+UWV+RW0aUzjDm0jaFhAE1DMEzANKfoWVCNbTksnBe5BXB4hfD4hNJ8Qmkeoats/TarW6w8o8y2U4BK3wvsoWEPB/ZSNu+FsiCu2+LJdTyNRs2/9xmi0BCNlmg0X0VLAl4m4n0avuagvwijD/Gnlmemeeds4/7JuuUj1egtwcdsdKXjXQY+ZONzHr7ko6cIfcXoK8aPQnzPx7c8fM7C53v4kIr3yXifjE938TkF3anoyUJf7v8h/FWBvzWYfb5+tlFgrl1q5u2F2Y9WrD4P8jOU/AwjA8FkyHe+12rmncLcy4OzTbS/j/GzFP256C/AWAVmateyGo+TZunZtgvkrSX57EIGLpNPdjNtSpPN6qxub/L7Bhm/NPnVmNVjQX44kmEvMuJHRvzIsDur33b2q9FQ67bnhchNxb0srpzSw3ezj4RcWX756oaY2ydupQolZUjcTJeMSRIJjz/tc/mQk/8OC3u6kSWbjh40tYEcb2R54p4rMp2R5YJcN+S5I88D970WHBb74UHA/zlsDMOTIDwIxvtCTHYcIF0K5LP2XO22uUr2HxkYyMJYMfpz8SMb46WYqMDfasxVYaYYfzMxk4npVIwn4vcdDKZiKA1DGRjJxEAGvt9Dbxp60jFdtvVXGffHNHTn4mUiPtwFaTr9q4x76C66U/DxHqZrD5GOI+TNkvHm7QURHO7u8A2gBIWvDonc6H95g6f/GkeXRXY2sLCFjR3FzBz6htDShYQCjkvgpBxdUxtGehQnU15/87UBZiv8THi9zHndrHi8LWk+Nmz+9gh2QYQ3e2zIquSru+/FH026tjf20ho/F1jqLtSyqUpCUwHaStBnwNYaPv6IuI64eERfRpgX3C3YFo6CTBhrQ0sVyrKQkYa4EJu4GKSlIacAOWUoqEBZGaqqlPMKkJaFuMQCwrPSEFVmk9akqxpSlI0oqsY8KkY8sjp0CVW28+qcyrorVI2XM4w5THThZYZ4X668m/sifeHvjhs38bjqfGWZsrM9fH2Qlb2/4ZmulzMv/QiN5xB1+SHaVn7acTFOSRUuNT0OHVNoG0PTcAGhrhlFxxQ6JjQ98yWWblQXP06f0KUB4bwBEetcQ7Yw7VdLaVOPi1JWH6dhPyc2s3HuhaQI3LSRF4gn11EThaoIPLmC+mtoicPLG3h1C6/S8C4TX3Lx/X/7zLEq/KnlmXi6bLQa38vwMQevU/DiDl7exZs0vMvG+xx8/EexAL35C6snD1+y8TkTn9LRnYruVHxJRU8avmejPxfDBfhZhNEy/K7AZA3vTN2u2UaB2TaJ2VdKc+/0WF8vkkEfMhREfgSSQR/yzYa8V5p7eZDVhNlnmHyI0RKMluHXI0w92zbbKDLfqsp6oU9eWZE3tvPv3cgbS1brhb8turMf3cnYNfIrfPqHI+ubFRlwIsNerGFvMuhBBp3Id8vpL8yv9ctqcpGTgozs5dllJ+9kHw2+ujYydmfcnTMJ6WK3M6RvpkteSxYJjz/tcfmgnf8WE0cOphVNQw+KGkCWF+65I90Fac4LDrPdkOOKPE/c90K+N4p8UeKPikA8DEJlMB4Ho9IfzQnL/7TvJt+EyGsl0iz6pxo/89GThsH7IE83kdr1vx5gtAS/yjD1FH+r8asAf+6B5IBkYzIZY7cxlI6BVPSnYSgDA1n4kYHv6ei9B9JxkjTvHCnEjwy8v4m3cfhTvnS2ZvFkHn7kYKicjbxSIO8UxurWVabA1xxubmze/kv9wjZ5X9ruErDR3n2NjS2vhSnN1BKmltA3BIMJNS0IyuCoGE7JLrrAgJkBXMx5A63WBFms9DXncLdgc7WCvRmcrODuAB93hPghKoz3RvSuO/F8t69vjgrj9XSCkSYUxSAtgPMiUJSBljIM9eDgAP9gRMUgJhYRwQhyhqsBHPVwUQ/WTJgxoKcOdQUoyUFclCIkhNNCOHMOZ6QgIgNxeZxXpEgoQFIO4tIQlYCIOESkIKzIJqJKkdGFrA7beR26NINTQpMmpUFTYXBqG/KqmSzVM6EZMuBphnhfrszY7cEeCPBCYhKePJYtypO2t0aAL+5l7G54pu3vsZx2iMJ9gLLsIHXbCfYT4pxSqhxqelSGCRgm0DSEhgG0jaFtRNHQo6oy2FUZnPqWbHauPN5BywPCVgeGb3AL2mzktEZRn35GkrrpNAf207ERR0/BzRDJHqi+huqrqIpAVSRqo9F8Ay8T8S4FnzPxKR9fCvG9EH0FCw4HSjFYgdGHGCxDdwHepqPtNppvoPUm2hPxMg2v7+FtJt5l40Muuu+jpwA9BfhaiJ4C9OShJxu9mfiWgW8Z6LuHHzkYzMfPIoyX4nc5fldi+snWmbojrEZhVov4/Avp2deqrI+G5Jsj+eE53+tBep3JFyPSJc1q2zbfANZzTFfjdznGKvG7GpPP9s40Ss+1a5MOY9JhOt9uPPvWjryxJG260006k29t5wYDyFggGXQlfWZkwJYMOpI+B/LtIvlmwerRnf6k8q4aZelIT0Z6ztqcMoHEzGNBUcuvxG2PTRZJSBO/dU8qPl3yWrJI6I3THpf32fiuM3RarG3JJa9LkVShIdMT99yR6ow0R6Q5ItMZmS7IdEGux4LD/28wfBiERyGou47xp0Kk9wL5LDvTcHiwCP15+HAHnbfRk4G52r2kQ2CyallfDgby8Kv16GTTzvEKjOTgz31M5uNXLn7lYaJk8WAWPifh0x10J+PLXXSn4us9/CjEdDX+lGEoA/2p+HgLH5IxUAZStW6oBFNNR0ivFXmn25iNAAeYMNntXOHiu9zZf62N1zJTJy5T+6XWtsusrXlNrblNLelMA1xgQFGDKiCJwyI4IbtcWwdmRvC05AmyXhloyeNrTnG1gIMVTM1gaYuLLnD1gU8wgi7zXL665cq1vdFXeEMC4WANbSVICEDkOCSEIC8NLWUYG8DRjRoSjug4XL+OcF94WcFNB+66cNODox7FShcm2tBVhboiZKQpZ4Rw6CQOCFCPinDxn6OflqIIy0FIASLyFAkZipQUTVya7ZwsRJQgqgZJTUhpU8W02YU12ES1aPJMdm3jRUyzxeqmvPqmFH0tuJgi1o+aen2zryuC/JF6j/NpjVxWmqi1KQJ88V/q1vparbDA9ZSDbP8Qbj9JPyXJfV6dU92ATdsYDGOqhgHU9aFlAE19diVNmowiu5Qch5ouTK25XbxWePjzuPvxOnmuMLZbqmpIF5Wjrz9NxV62JTuho4C7XuwloXh0DY+u4NFl1FxF0w103EFnGnry0F+Kvkf4UYn+cgz8v3vLQnwvRH8Jvhfhcw5ep6AlAU2xaIhD4w00JaL5Dl4k41U6OjPxIRef/yEsQW8RvhXiez5+5KE/F0O5GMrFQB5GCvCrDBMPMFWJqcfs07UH5urPkgYx0iTCahGda5cknWqk25R8tZ3ttiPvjEiXOmk/PVdPn6vF/FNMP8ZEBUYfYLwaU3VHZ1rkZ9sZcy8M5tv1SJv2/Fsr8taSdBizWnX/dlqw+t0Wsqzf9UmfCflmRrpNyUd98kmbvFea7TzXVITcW7h7E2lZm3LLhW5lHw2+uvRKwub4FLGb6ZIJGVJxaeJRySKhN056XN5n5beO6bBY3YxTSptDSJGODA+ku+E/J/zngDRHZDghwwkZzsjyXEBY4ItiP5T8fxB25YD0qZIe2+lGud/P8C0PvWn4mo6uZLxOxPcinsmn+/vy8fo2vt7Dn1eepNuHvDMlDSLzlWt+FWHwPkaKMJSPL2l4l4iPyehJx6d0fEjF+xT0PwBpW09qefv/Q/9dfEnC29sYrgSp2fytCPMdomTIg3QZF8TDWAe2dgctnGDlDgs3qo4dNMyhZ02xdVrl4r7Fyn6FuRWPniHlAoNNQY391DkcEsJx6eUMJqyM4WnJFWTDG2jJ5W0OB3NctICpJazsYe8ON3/4XELgZZ6QK+svRW2/FAwfT5ib4N8z5oLHICkMJTmoK8PEEC6enKFRiEnA9esI8YSHCbwY8GFSvA1o7gYUe31Y6sJQAwwVyCtSzwpj73Hs4Ofcd3YZn+hifgmagDTOyFCEZagSMuwyMnRZWZqUIlVCjSKpRZHQgJQ2VVSLdladKqbNrmrMo2fFY2zJpWG+RN+UoqcJZxPE+bP/d22TtzNCApGWu6TmqfzdJAFjI/j44k7yxtparcuXtv2LhMsP0Xae5hSQ5pHVXKRhSNE2BsOYQ1MfGnrQ1GdT16XLqdDFpWki52iyKmAaU+2clji40m1dYOXIrm9JV9dnF1PiXnOCDTux/SBcmSgJ5iwPQVE4KiNRFYFn19F2G2/T8CEL34vwsxJjdRh9hpEqDJdjqBg/CtFbgK/5Cx+fsv+HMAb1MaiPxfN41N9E4+0Fh++y8Skf3UX4WoqvxfhajL4iDBRiuBAjBfhZiOF8jBXj779JJ9WYebJqtu7IXJMoaRAjjSKkSZDVIjT/WoZ8YLC6zaY/ms13aJAXMnNNB/4+xXQNZp/gbzUmKjBUirEqTDXwz7QpzbTpzrTpzrVrkw6t8SZt0mpA2vRJmx7roykZciKD9qxuM9KjRXp1yRc90qXNeqNB3ijMvxGbeSXwOAOp13A7FmlZm3IfCN/OORZ4nTc6ceuN1HMJGVI3M8/Hp0v+Q+gWsdvKbxXDnkfZhEdcnfOkHAdS/JHuiTRn3HXALSfccUW6C+7bI9uFM9cDWd7I8EaOD0r8uUsDUOKL9hR0F4K8FyftZ2dq9sw9Xt+XjbFS9N3D57v4dAef7+LjXbxJxItEvErGUNUW8kqOfDQjby3JWyPSJvm7HN/vLWw+u5LxOgnv0/E+Be9u4uNtTBeD1BwkHxjDDdt6K8BqOs1qVZ7rUBx/jokSkLqdZDR77qdPReKiQEs4mpxlWsLAlk1RH8qG3LpmvIbm3C7Oy3y9VgR57fTx2K1tuESasfiIDGXTCfBLLz0lu/yCJkwN4WpH83Ra7GhPs7aEiQWMLelWjrB3h5sPPP0REEwNC+MMC2cPCUWgN2ytoayFU+LYf4Jy4Bj1jBCbtAxklbj/NY9FxOBqNGIi6eHeHI6GcNSGqy7F04D7X9bHVZd2UR2WymAo4rw4jhzH1kPYfJS+W4DjuBi7gATExdmkpSmSshCXh7gSRVKLS1KLS0iNKqjOLai+RERtiZQWr6rxciPbJcaOMLCDgS2Xujq7nibcrBEdhGuBq/3dERGJ0vyVDc+1IqP59Uzg44PUu1ua6/VCLx1gP8jFfYC69iiNT4xDTIlHQZNTg8mhb8yla0S5wISmDpsqg1NRg0dMfvFxYfreExTBs2xqaiuNTNfrmi5hGFN1zBdrGy9V0ubYJbpizQnuVftx9AiCbZAbhMrLKA/Hw3BUhqMhFh/S8S0PffkYKsNkDe/U8zMTdRvHazFcjf5S9N1Hfy4G8tCbj6/30Z2Nrnt4lYyWBDTGoC4aDXFoiENjPFpuov0OXqbiTQa6svElF70F6CtG/7+saTlGyzH2AL8q8LsCvx/izyNMPd7499nBuTr++UaB+QYxVos4aRWebxckL0XJW1nyRoF0yJO2M6yGHbNP8bcaM1WYrsSfBxgrxUgJRsvZ/zzm/1svM9eiONuuMt+iNd/MJC0MVqvuXIfJbKfF/CdrVrfZ7GeduY8qc10y5IMyeadEupTmXojMvxEmH4V6HrMnXMHVCETHIbVoW26VaELm4UuxvBE3ua8nnYlPFYlLO3ctWSTylkBQ7DH38F22fmsMHFaqGi8VUll0QJIb//ngnjsynJBij0RH3HZGmiPyHJDtQrvnhnteyPZBjhfyPPEwGHXReJ+JL/cx17Bjsnr1RNVK0rzvdyVma2j9WehOwcdEfEzCuyR0JKAtAS8T0VuCP/X7/raLT7YqzHdokBcKs08P/imj991DTzre3sHLJHSl4k0i3sbjUyLGijBde4Z8d5zpvjDx/jwZcCKDgWTEh7w59D0L882byfDt+V/e3xvELznAxniLEpNDzXCZtCaXlAa3gianoSnvpeADsVcOR1/a5e+zQ890lZAc7ZAEfddZNn7pxcfFqdraMDWCvTXdyY5uaw0zS5hYw8SOy84Vzl7w9Gf3DuQKCOYMDeUOC+YMDkCgK2zNoaQKfhHsOkbdfYT9mCBFTAZyypzGVhSfMETEIOoqoi5RAp1howMnxv8PoRuT3UETtmrQU4GSNM6cxa6j2MzHtuME21FhCEhARoZ6XoF2XoEmqUARVWY7p84upsp+RplNQIkqqEqT1GJX1KfrWC+2cF5k4cpmbg+mFU1VjYOpAScrRAUgyn+Fvzsir6A4Z1ld/QXfkL36xvD2RkrSxqY65uWII8v4uJfw0TacoB2V4BRX4VLS5tAyoOib0nWNwDCAhh5VlcEpp8olJM1x+Cx193Ec44eoOLusCoeCJk2BSVPW45LV4hBVYNsmtHTlcc41ByFwChHOuB+CijCUXsLDcDyKQGMcPt5DXz4GijBWgelnG6ae80/Vrftdi9FqDJThR/4Cwh+F+Fa44LAzHa/u/N+mtD4W9bFoiEPzTbTdQUcKXqXjQxa+5P7f7cXQP4EP8acSE5WYfISp6hUzT/bN1J6YqxdmNYrONYmyWsRJqxhpFWO9ECOvJEiHyGzrGdK4g1XLPlOFqQf4W46/ZfhditFiDJZgpAzjj45MPpeca1Ek7eqsVm3SZMBq0WK16s51GM51Wc5/smB1G89/0pp5r8TqkiXvFclbWdIlM98h/PeVwMTro6/LcCUI4SGIisF/+dvzKkTi0g8GX+MKi6dfu3My9q5gTIpQdJJg5K3TAbGH3cJ22Piu1rNbpmy4WECRe5/4IiR6Is0VOQ7IsEeSPW7Z464DshxxzxX/OSLNFVleyHBDjhueROBzBn7k4msORh/gez7GKkHeHCZNu+ca9v4sRG8GPiXjYzI6E9EWh6YYtCfgQyb6H2CwesmPx1t/NwmRF3KkRZ40yIwWoy8bnUl4cwfvUvD6Jl7HojsJgyWYajhHBi+RsSAyFkAmElm/7v6djCf9LqOPNk294Ca/rs9P+5ERh4womOtDSW2DrNIaKZnFsko8mpqcDjZrIgJ2eNrhajDd04nD1GLDMRG2vYJcu87SjohTT4hDS5eib8hpbsFhaUUxs4SRNUwdKBZu3M5e8PDn9AlaEhC4JChwSWjgkmB/7gBPBNjASh/ycjh8FtsOUjcdZD94lnZaFgpq7OZ2NP8IRFzHlSsI84eHFUxV4aAFZwbc9Ti8DXm9DXk99DlddNgctWGmAR1FnBfH8VPYfwz7T+CEKESlIa3AJqNElVZiP6dIEVVkF1XhEFGmCyhRBeUhpQ5lQzBtYOEKB0/6RReahS0umEBJma6rDkdLRPgiwmeJnzuuRiM/e/nz5wxbp1X6ZvDyQnLiuoZanevRJ1Yfp687Qd8tSDspxyGtyaWuz65rRjG2ohiYw8CMwjBepMJYfE6B8+Q52sF/IwePYO8x8AnglCREFdmFlThPSVEOi2CzwKJlR+kbjlDFxRDjzZ3/vxljZeGoikTTDXzOxGAxhsvxp5p7tn7HdD3f37qlf55jtBpD5RgoxEAeBvIwUIz+IvQVo7cAn3IX4mF7IppvojEe9bGoi0F9LJoS0JqI9iR0puF9Jj7n4Vsh+ssw/ACjlfhVjYlKTFZh5jHX7JNdrNqTrDpRVoM0q0F2rkmItEqQFknSLMFqESXtZ+Zb9083riXPMVuNv2WYLMBEPiby8asAo/noL0J/KX5WHPz99NxsswJ5oUFadUiT0bZ3jVEAACAASURBVHyz5myb9vwrE/LOknyyIp+MWB80p7vkyFt50ilHXomSN6J/O07+bN7X/XRNZQp8nRHgi8gYpBbszy47G5282zuSHnyN6/KNw1dv80fdORF5+9ilG4d8ovc6hmw09+Jh2KyS01vKL8exQ5QTCR5IcUG2PbLskGyLBFvcsUOaI1JdkOKI/5yQ5oJMZ5T6oeMmBkswkI3+HIwU4UsmBspAXmxntfDN1B2f/nf7mYEvaXiXhJYYNFxDaxzeJqEnB90F+FyC4SebZ5rPkFYZ8kKN1O37WcrxPgWdSfiYgs6beB2PrykYLMZUkyj5Fs4au05+xc2Np4+PpPeN3yAjieSb0chLGpmJn5kKJmOhrfd36ytCTZpH5RybvAg0JGGihsSwrS8eqjQXi0f5wdYYxsar+QRou08v3XaCyicMUQWoMDgvGCw2NOc2taSYWsPEHhZuHFY+vC5+VK/AxX4hywIDVwYGrAj1XxHoucjPheJtAkstyEpgPz/W7qUt20ffKkA/KktV1qLYuiwKvILL1xAZiUBP2BvAUAE2qrioDidtuDG5PPR5PPQ53fXYXZmw0YaRGlRlIS6KM0I4KwZxabbzCjRJRUgpUcSVqGLyHMLydCFFurASu4gy/bwKTVOf3cQe9t5wCYCLL2yd2E1MoagPOQUaQ53iYIFQb4R5cvq5IzoOhXk7qh9rM4ypRhbsnp5IvLmy/umFG3ECm07RtgpS+CRpoiocynpcuhbsJvY0a2ealT0sHTj1rZfL6y4TlOc6KkI9eAr7+LH7CHXLPmw8gL0ncUCEsk+IsusU204B6maBRbxH2Dcdo52XQoL/soJLKAlGSSjKwlF5BU0J+JiNwTKMP8Lk03Xzjftn6rbP1GGiFr8eY/gBhooxUIDBfPSXoL8EA6X4UYJvhQsO36TgZRJeJC5ExcYYNMYtJE5fJuLtXbzPQE8e+ooxWI6xR/hdg4lH+FuNmSerWM/5WPUipPE8aZBnNSrNN4uQVgnScp40SrEahUnzIVbj4ql/AssxkY8/Wfidgd9Z+JWL0Tx8K8T3IgyU7RmvEZlpkift6qRVhzQYzjSpzLZdYL0xIh/MyWdz8lGf9U51tlOavJIjb2Vn209Pv+Qfaz34rnJ5dRZuXoKTNby9cS1+cWYRX3aZcPTtXe6hHJ6XKf5Xtgdf2xsStzc4do9/9Ha3y5ts/FYYOdPULVZK6vAekubeKMiFWD/ORDek/w9hnBXirZFkjzuOSHFCsj0lyRa57qiPxtcMjBRiIAOj9zFajO4MfMnG7xradP3++caTpBa/yzGUj4H76E5HWxzqotAcg9exeHcHb1PRlY1vFRitXT3RsJ+8OEs6xWee7vqSic4kfE5B1228TUBPCn4Wg7QKk0++rMHLZDyWjP73d+y/sakbcz+zyC/vkff75yZvToyFkrFr7wvOXhCE1lnYqyDYFKGmCDBAfhR+v2aQHrMHqZs9LKGhhgMnKQeEVuw5y3lYGPIaVBkGu4oBp545t5kth6Ujm4Urm40Xt63/Mhc/qnfQkoCQNUFB60L914T4rA1xXelnz+3BhIkKpEWx9whW7KQu3kPfdJb9iDyHOpPi5L00+CouX0VkONXHCZZaMJSHiRwsFGCrCkctiqsup7seh7seu7s+mzUDhqrQlIOsNGTkIKtEl1flkFeliatAVJkqosAhJMdxRob9tCxFSJEqqkK7oLPY3GaJqx+vbzjVLxxu/lQre4qeIeW8FiRlqQx16kULBHkgyIPm64m4WygrOZZdJK+sA0NrblcP3LrB+/ypxu2bgrvOsh0Upwgo0mV16BcsOEyduC56L3bx43TyhqMXj5HTGnnmylOyiw6K0g8JUg6ewh5+9s0HsG4P1h/CRj6s2o+1h9i283NtOs29/BjHluN0aUnE+y75FwlLL6Eo7P8QDpXhz2NMPV8727R7rpZnuhYTTzFejfEKjJRisHCh42GoBAOlGChFXwl6C/AlB+8z0XUPr1PQfhtN8WiMWXDYFI+WBLxIxNtUfMjCl3z0l2G4EmOPMfEIE48x+3QN6zkfaRAjTfKkSZnVoDLbLDbfKklaJFmNoqSBnzRsmK/F1GNMlOFPIX5nYzwd46kYS8dIFoZz0FOA3iL0l+36WS08VS/DalUmzVqkQXemSWmuXYu8MSQfzcgnM/JBh/VWYe61OHmpRrpUJttO/Go79LV226Ms3L4Cb0dYmlE8vSnRCbxZxYezSgUux2296IuLvnANWusVtsHnymafK+u9IjY4ha4x9+Jh2lMUTFaJaPLuEV+04jQ3Ii9vuO7DleyAdBsk2SDWEtctkWCDG3ZIdESSHe7aozQInckYyMNAJoayMV6A4Xx0p6IzGd/u40/NRtJ8gjzHRAXGSjFehr77eHlzYfpv6xW0x6A1Hh3J6C7Ajwr8fILZtvWkS4rVeKy/EJ/u4mMS3t9C1w10J+NnGcg7JdLjzerzIqOBZCiajMXPT0VNTeWTkYD5YebkWOrUWAiZiviQvcNHk/487UzPY5Xf7czxZtXuh2cH6mRIvy35bjP90S4pbKuMBA6exhHxFaflVpyWgpImm5wuRc2IZmjNae3EYe9Kd/CkO/gucghY6urP7h20PCBkQ3DAxks+m0I91gc7rPaxXOrEgJ4yzolgNx+W76As2cuxRYjzuBK3thHFI3BlSDTbpUiEhVBcrWCoCAM56EvCWAZWSrDXgDOD3VWX5qpLcWXCWBNMFWgoQVUZqppQ0aYqaNKk1HFOjUNEmUtQnltAhvuUFO2kNISUIalFMbVc7ey5JThye1jM5qCo1a5+vGa2HNp6FDFVSMiwX9DgvGgBXzcEuLH5eeFWMioqxaIT+GW0oW+9xNkNCXGL659o3LktfOgczsjTpLS5VU049R04bb0Xu4Zwe4Yt8gmGS+ASI+e1kjorjkhxHhLhOixMO3qW7cBJys4j2LQfG/ZhxU4s3YZVe7D5KH3DKa5V/FxbjtPFRHHVnZIfigeXUBKKwlCUR6IuAe8y0V+G8RpMPOecqls3+xTTTzBRg9/V+PUQo2UYLsFAIQYKMViE4VIMlKG/BN+L0VuAnvt4n4OujIXnsRvj0HAd9TGoj0FTPFpvLrz5+TEb3woxWI7hSoxW4lcVJp9gpm7XfKMAq0mK1Sg/26g003x+vlWS1SI633CU9XwjeYqZKkyU4WcuRrMwmo6f/2H4LoZTMZCB/ix056G3kNpXdnCkSujPc4npBhlWoxJp0Jhpkp97oU46DclHU/LRmLy7wHojS16Jk1cXyIcL460C3+p2NpevSroGb3eYmcHQFC7eiL61NLPoQGbh8dBrG8xdYOwIG/fljr6rXUPXuF1a5Rq64mLgSlO3JTrWdCn95fzKizaJ0DmPcyPoxr7LQStvOCLZdgFhtDliLRBvjRvWSLRBpgdqr+FzBoayMHgXP7IxmIdvGehOQddtvEtCfwHGK7lmqzFWitESTFRiuARvElEXhYZo1F9dGELaEo939/DlPn6UY7KOOtsqRNpOTVSt/J6Jz3fwPgHvEtCdjP4ykO/G5Efg335HMupE+n3ISNjcuP+f6Wwyeo2M+c38Kpr+5Ux6zg9XoilZmIz6kgk/MmBHvpqTXmsy7EumYsnIVTIZV33v/HkxnDyHI1Ls4lprJVXoSpo0VWPoWlIs7On2rnRnD7qbF7urD4eLH6dbAId36KrA0I3BAVtCvDaEumzys17lZcxjy4CuEkRFsPMIlu+gLNtH3yXMcVZtsb4lzS98XUg0W8AlBPlR7QxxQQJ60jCQWkB4UR3/2pccteCgBaY69DTA1IKODrT1ocqknNeGuDpElLnOynGdllp8WmrxKSmOM/JsUtpUVTNeR+9t/pf5riScjrzJH3hlv733WqY5VUkbQooQlWLX1uS6aAUfV/i6IcAHielcVY9lnDxXnNem6lrw2DviRix3w1PN5ESR07IQV+dUMeLRsV5s6sbtFMTlFcHtc4UeEA6XYE6mw9Kzapy7xdj3CnP8Q8h3Cvv5sfMItu7Huj1YtxMb92LTIerq47Q1J7i3neAUPIvLTsgPRUUYCoNQGIzyy3gej7fp6CvFaDV+PcPvZ5h+jKlq/K7C+CP8eoixcoyUYrAIw/9DOFyKgVL0l6CvGN+L8CV/oWPw1R20J6A5Fk0xaLyOhng030T7bby6i650fM7D12IMlGHkIcYe4fdjTD5bMVN3ZLZRZKZJYrZJbrZZYb5Vcr6Ff75+3dwzzFRhohgjOej/b2FYw1AyBpLRdxff0tB7D59y0VvE21/OP1IlOvZE5E+t0FydJGmQn2mRn+/QIF365KMpea9HutTJ6/PkpejcC13yntFXf6ztwbKCNPh6wsgCuqZLdM3g7IvoxEWZJbszi46GRW82dQDTCobWnBbOi2y8ll70W3TRb5Gl1zJ9ex5NM9r/w9ddBlXZdv3j/+5kswFBUAEFERAFQaRDUBqkG6S7Q7o7N53SCF4mAoKgG7sLUOxWBCzE7kLO3wu3z3U/9zz//8wxDMMMvOKz17HWOs+19Fz4FCwYAlpU0mo6sreoFBULV8ejPRLtUagPQ2UQqkNQH4m6ELRGYl8+LrficRde7MDMFjzZjSe7MNGJJ9vwqB03G/BgCx5vx2c2XvXjzQC+HcM7Nm6343wVLlThYj3O1+JMOUZqcLsd93Ziqh8fT5A/nF5DXNEhhmXf7sPjLbjfhActmNyKO/tAvIicmyn8NLOJ+BhNvE4n3rN+f8yY/tBJ/Nzx60UB8fXop7dej4ZA3AQx7vfzWTTxPoV4EU28jCc+FBMf62c/bn37opN4vfnyPndrM+hbY7UJTNwXWbkJuLjyuYdT/aLJEQnU+BRqaio1NZ2UksGVnMWdms+TWSz8B2FBmnh+vHh2iFCqD1+kB9ztoG8AGWUILacIreKS12fqO/EHRPHmlS8trCZlFSA7HaEecFgPD2P4myPYEpH2iHFGnCs5zhWbnBDtBA9n+Hoi0A+BQfAKgI0PTN1g4AwNSy4VE7qSEbeGMa+2OVPfnss2gM8nYXF2yeryBt3NHabVbYbZ5SoRyUuc/WDmCF1r6JvS3F35N4UhMwmZScjORsdugSMnLD1CsMGN4h7IFx2DhjrG8BmXzvb1623Jlh68riFCPjF8EWl8CUXMzApGVhU5twwJ+STXSC5lW5rEOuoKXZriOuoaLahqY40WFNSxQhGS8pBSgKQCeekq0nxFkogGr5QGt7YmimPQV4TDJdibg735YJfg7Gbc2o6ng3hzDO9P4c0pfDuGL8fw8Sg+HsXHw/hw8F+Ebwbwej9e/31W++UBTB/Ak/2Y2odH3biznePw0maM1uNiA0aaMNaC6x3/Xkqf7MfMIbw6jA/H8fkUvp2T/XlR6+eI4a9Rk9lLjnNj5nOXFH9dwPeT+HYQ73rx8h9MteJpG6bbMb0FzzrwtAMT2zCxHY+68XRgycwhrbfHDd6eWPv5pObPs/rERfOfl6x+X3Mk7voQD/yJ+97EHUfihhlxw+DbmMfP2xsfnpA/1ovWWoSEw9kbG4OkPMOQmIuadlIXW6r7gEpprWRwHMUtAhv94BNGCkqghiZTwlKoAYk87uF0Ox+KhiPXShMKU40EORrK6pRLi2SLExaXhqAmCE2hqPdDqQvK/KlV3tgSgpFKPN2BiU5MbsXUDjzvwZPdGN+GB1twrxV3m3C7ATfrcaMJt9pwtxPP+/HxKPVFP65uxtkSXKzASBVGqjBcidFa3GrHZC9m2Hh9Er9GxYhLip+OYbofz7vw/B9MNeIzew0xEUy8y557nz37OuXndCLxsXjuaw3xivX1hjTxxI34WPf5keXMHTliOpx4lfTrQ+2P9w0/vmz79X3Pt0/bfr1vJN5XEK9ziCdJXaxldlYwcODWs6NscINfjIhTKCkilhwZR4lOIMekkBPSGclZ3Kk5jLRcZmKBeEahRF6uRF6KcF60UF64cHbA4jQvkUgP+FjDbB1WK5N4VtHJylRZUy5b7wWRqfTcMq6SSmQWIySRz8wW+jrwMIe7KXwsEGKLMDsE2yPACQFu8PNGuC9CfBDoDR8fmrsXj50Ln6kNfZ0ZbbkBVhpSFY341Ezmr7fhs/cRDEhYGJ+3pKLJsLrNuLZdv7xOIylHxidsgZkLXdcaSvowdeBxdiH5eyM1DtkZKC7Hlt3i/QetLO3E9Z2wMRDx0aLNDZSDhza071hr4Q7XEFpgzPywRL74DGZuCU9RDaWoGpXlyM6DZyifmjFVTJkqqcKlqE1X0cVqXfJqXdoqTepKNYqUEnmZPFlSgSKpQFuqjMWqTAkVLnVtpIahtxy9RegvxkA2BvNxug539+AZGy8O4tUxfD6DHyfw+Qg+HMRbNl4fxOshvGRjms2Jfi8GMTOAV4N4x8aHIXw6hJcH8GIfJv+0EHfgVgeuNmN0M4brcLGecym9tgW3d+B+Nx71cao7r/4US0/h27nlc8PriUuWxFkn4pwBcU7sxwm8H8LLXrzYhqdbMNWGqRY8a8HzVky349kWTGzBo3bc34up/eIzR7TeHFv36qjq2yOrPx9V/XVS7+N509mrDsQ9d+K+J3FnI3HblbjtQdzxJG5Hv7iw/vQgmpoQn4iN7jQXN5pvMMM3BGkFPC3bl/awlXb1a7KqpMNiqT4RcHSFs4eAm5/YxhAhlwg4hMDGh2HhIqZmJr5Mez5NgRsy3GBVyBbnryyME87zR7EXKv1RGYhKP3qRN6XEC1sjcakaU9vwuAMT2/B0Fyb3YHwX7nXidjtuteBGI65txpU6XKnH5XqMNeDBDrwdwhs2/V4nRqpwoRzDFRiuwMVyjFbjegvGd+P5AF4cxdfzFGJU7seZRR+G8KYfMzsx2YLpfhATrsTbxK/TKbMzacT7bOJD7uzEJuIq+fkRfBzhJ54mEs/ifs1sIj41EW/6fr8vIT7XEd9av7yqIz41ET9bZp+m/p6MIa6GlMXA2grGzkxTN6ZzII9XGN03lj86gb4pkRqTRI9LpSZmMFOyedLzBDLy52UWLc0pkirIkcxPXloYtbggTDgrQDDFmyfcDd5WsNKDihoWrCYzVMnKZlR7n3mxWTz5FYzSKqQXkAKi+Q0soacJJ2NsNIeXOXwtEWCDYEeEuCHQE/7e8PeErxe8vODhxe3oxmdiz61pQl6ji5VGpNXGFGUzLk0rLjMXHveQRVGZy7PKFCvaTGvaTapb1xdXKsWmS7gF8BjaQ8MMigZkQxuaoyMCfZESj6x0lFRiW6/srn2m64wFtWywMRCxkcKN9Th02HzLzvV2fvCMZIYmLYpKFUjOmZ9fxs+qY7BqUVqKlCy4BtAUDaiLFCniSlzLNajyGpDVJcvpUFdqU5ZrkJcpk5cqUsRXk5cqUsWVOAjVtJASgp4ydBdgbyEH4ala3NqFiQFMsvHiIN6ewLfj+HwE7w/h3RBeH8Srg5gZ+m+Er/dzEH48iBk2pvfjeT+m9uJxF+deerUZw5s5FZrRRlxpw81tuNuFB7143o8Xg3+bFsfx6bTwj3OKsxd0fp9Y9/OEwvejjI9svNyLqR2YasdECyZbMdmMp8141oIXbXjajsfteNSOO7vxeJ/Qy8Nqr49pvjyiMHNI4sNh+e/HNL6OWM5ddyTuuRP3PIk7G4k7G4k7nsQdz+9X3B6eUBrciVIWgsPg6EJ3caP5BJH9w5BewNOyfWkvW2Vnn0Yua7FvJLwj6Bv9YO9GsXHms/Hks/KBmTvW25PWWwmtNBTiVadCFpAGWCzp4uzluVEL0zyR6IAUZ6R7IctvYaIjMl2xPQGXN+NxB8bbMbENT3djfBcebMOdLbjVghtNHIFjNbhcg+FKnCvHWAOe9uL9Qf6nvbjaiIvluFjOmVk6XImxzbjbiYk9mGTj3Un8GpYgLsj8Pj3/6yG82osnnZjZD+KRyex0+JfnScTLVGImkphw/35e4+dJvBvC92EqMRFETFcR7yqIj5uJmSHiVSbxNp94m/95IoF4lUW8z/lxL5CYCr/atyHYERvsYOkt6Og3LyhmvncQNqULb0rh3ZTCFZPKHZvGk5DJm5wzPy1/UUbRwvxi8eLC5SVZK0sSpIuixfNDF2QEUBI9EegKX1s4GkN/HaTVSeJa0LUmuwfwxOXS8spJxeVIzIJbAM9aQ2ipwU4PjmZwMoGrGXysEeSCUC8Ee8PPCx7ecPWEvRvFyplpZMPUMqPJ65GXa0HRhEvFnKZtCyNXOAbRg5PF0svUyxuNazrN6zpMKpp0slgKIXEL7Dyoay2gpA9FA6quKcnGHiEBSE1AajrKa7Br/5rmnXoK6jQVc3iEUDZFCjbU49hxm87d+m4RCEmcvylDJC5rUXqhUHHVovJ6vpI6FJUhIRO23uQV68EvTxZcTRdVoYopY4U2VuqQVmpTVmhRpNUpy5TJEkrkpYoUMUWIqjD+RMKUEHSXYk8uuvPQl4PBfByvxlgn7nbj4V5MDmD6ID4exodDePv3MZeZv5HwT4vixSBeDeL1frw9gPdsfDyId0N4+5fo835MduPBdtzZgrFGXG7Apc24tJmzRP7uDjzowlQPnu79013Aq8N4fwyfTgh9ObX0y1H+j4fwbj+mezCxDY/aMN6E8SZMtGCiCU8aOQ6ftGG8DQ9acXMrxnuYL4ZWvTyi8GxI8Bkbr4eEvx6TnR2zIm46c/jd9iDueRH3vIg7Hi/Pr7+0X7yzDnFxcHaHtT2fowfTOwiBEUjLpzZvE+07qLa9Vy0pW8jFH26hfD5hJFsXGFrAyJJuaEPWssAaY9IaQ4bQOl4oAVLAMqCkSKo4UzI7XDjeFSFW8DODlyk8zGnuhoi0xo40XG3B/TY8asdEJ6Z24sE23O3A7VaOwKv1GKvB5WqM1WCkEufLcKESt7dgZhAzg7jTidEqXCzHhVJcLMNwBS7V4Hoz7m/Do0G8PIwfZ7mJYVnigszsCbwfxLMu/DhLIh6YfZ8MnptOJp6EEJc0iNP4dQifj4A4p0vcdSSmQokJ1q/HkV+mbH89SSGeRP+eCP1x35sY9yUeeMzedCUe+hITIU35S+2sYO4CxxAh73C+qDjekEgkZiyKTeOJTeP5i1AgOWdhesGSrGIxVtHi0nzpkozlrHgpVpR4frhgij82ucPXCd528LCEhQlU9EgKBjB1ogRF8CYV0vLLUFiCmBSytQev2nrKWk3YGMDcENbGcLGEjwOCPRDiA39v+HjCxY/X2oNhbEfVNqOqGtDk9Rny+syV+kwVE25NK6qRK2yD4ZfETCqWLWowqO103rzDurLDuKhOKylHyieU39QJqsaQ1cVqPW5VfVjaICwEqYlIy0DFZu7eg2vLmrUkFciK5vCMZMZECTXU48RJu23dxkEJ1OjMBUl5S9LyF+WyFpXVClc2zK+sIxdXIT4Tlh6Q1gGfHIlnFX2eInW+IklaHTKapJXalJXa1OUa1GWqJAklsoQSWUwRi1WZy1QZ6tpIDcWeEuzOxu4s9GahPw9HKzDcguvbcHsXHvTg6eC/EY9zDuD5fjz/j5/8J8IPQ3g/hPdD/1J83o/JPXi4E9fbcLWZ4/ByA6614tZW3N2Bx7sx0Y2pPjwf5LyP/+4w3h/Bu8N4zcbLvXiyHQ9bcb8RjxrwuAnjTXjciKkGPGnC02ZMteBhC+634EY7Hnbh2aDoU7bA+H5MDuL1Qeq348t/X7GYu2lP3HT+fWMjcceLeBhAPPD+ccv13nHJw7uorDy4+8DYisvYVsDRk9c7CCHR1NQ8cvM20f4jqlu71cISGeZucApa6BEKJy+YWpLX6lFU19GU9bhXrqNLaFGhPg+yJEgAEkBFgWRR6rKcEJEkT2qEHdyMYKqJtYrQV4KrHrZn42o7bjdhvB0Pt+DhdtzbittbcL0ZVxtxdTOu1ONyLS7VYKwGw+UYrsCFcozWYnIP3rAx2Y0rdRip/IuwHCOVuNKA2+0Y78eLA/h0HMQFCeKi7Owp/o9szAyAuKxDPPacfRxCPPYjrup8ZOPrIGYP4sVREJeCiftxxEM/4k7Cz+s2324KEvd15x74Evc2fh01IB5a/xoz+HZpA/Es4tFBgxAf2LnAxofuFSMaEMUVHo34VJ7IlHnR6cyoNEZUGiM6nRmbJZCYuzi1UCKjWKokfwkrR6wkTawoXqw4RjQvghnvhyAXONvAwwaetnCwgrYJ1Exg606KiluQWcEorEBhCSIT6Sb29DU6FF0dWBnB1Aj2lvB2Qag3wnwR6A0vL7h5wsyFW9+eS8uM9mdR2cp1dDlDPgVTfi0zmqE91dYPPgnkTQVL8urUqtqtG7e71+20LG83zKlQjkoT2+jPbWhDUjbASm2KrC63og7MbBEZTk5KRGYW6loX9h1bn8JavWQVXckKbhG8UVFC9bU4ctRqxx7j8DRSQu78lELhjKKFBeWilZuX1DYIVdaRy+poCVlkW3cs1wLvStBlyJRVZLICaYkKlqmRpTVp0po0KQ2qhCpFTJkspkwWV4KYGmOZKkNDBykh6GJhVxZ2ZaIrA325OFiGM5s5j1/f2YnxXkz2YqoPT/o53fBngxyBzwf+G+E7Nt6z8YGND+x/Kb4axIteTO75X/9vVxpwvRm32nG3Ew93Yvzv+4rTA5hh4xUbr4cww8aLQTzvweRWPGjGg4a/CBsx3oDJzZhqwNMmTDbjYQvuNeFWOx7sxGQfHg3gwQAmDuDNUfw4Kz97xYS4bjN33XH22kbirh/xOGj2nvebMZtRNmV3E+JiscGepGXKr2+z0NaLxzMYoTHktHy0bBfuP6revkfZP4aqbw9rbxFnP7gFMezduHTWQ06JLK3GLaLKZKwCZJhYSsZiQIKEkmyJ/Hjx7GDhLL/5iR4UbysYa0JZFquXw1QT/xTg6hZcr+XE7jsduN2Om6242ogr9Rirw1gdLtfiUjVGK3G2mOPwXCnuduDtEF4ewI0mXKrGhTIOwovluFyLm6143IMnpqAB5AAAIABJREFU/Xh3BHPneYgLMr9OCn4+jM9HMHvJnngSQTz0+DWi+u0QPvfh50F8O47Xl/Djqh1xw4+440jc8SKuuxBja4kr6r9uuBAPXH5f0iaua/8a0yTuOH684V+fBgcHuPhTnUL5/RIXhsWRImKQmCUYmMT3PwJjMoTis4WT88XTiqSySlaU5EmxcsSK0oWKUrgLkpjpMdQIP7jbw9QcdlZwt4ODHXTNoWkBOx9KXLJIfjVXfhlyCxEUCU0TrFCHpg7MDOBoCy83hAVQokJpIYEUDy+ynSvZypmuYghFI856Frl1PCv0uFcZcyuY041sKZZuNLcw7vCMxRkVq0pa1tdttW/c6V67w6KkRTedJR8ct8Dek6prgVXrKVIaVCkNbjlNWNgjIpKWmIisPDRuW9p3TN8vfvFied41dnAKpkZECFRV4yDbZGf3huhMJBYwMouFslmCrAqR6kbx+ibhqnpqVT01NRsuPlBeDxE50KWB5YAshBWwRIkioUpfpkaXUKWLq1DFlKlLlChLlSGmxviTEyYFYWcBdqRjRxp2pqInG+wSnKjG2ToMN2CsDbe24e5OPOjCeA8m+vCkD0/3YXoA0/vxfIDj8D8RvmPj0wF8OoAPbHxk4/0Q3h7Ay3140Yvx3XiwA3c6cKMF15txvRk3W3F7Cx5s5zic3IOne/FyH+cPPh/E03483YPJrf9GwvHG/0+Et1vxYDvGe/B4Hx7vx7ND+HRamBjW+jVmMHdtw+9rDrPXNhL3A4mJ0E83XcdPrT+6GzVF8PSGrgVd1UxorZ2gtQfDK4QcHkNOLyC17FrYd0ylbbeKdzTPWisYOolYuMI9kM89gMfIDKtUsGQVgy5DxVJAlAQRYCl4ZGgoSl2cGyWSEyiaG7gw048Z4gBrPegoYaUMxUAd24ox2o5L5XjUirttuNGBay2c8vFIHYZrMFzDaQaOVuFEHi6UYqQCp4twrQkz+/HyAG614VINzpXgQikulOF8KUarcaMFj3ZishtvD2FuGMTI0t8nF38/jtkz+H3Li3jk/WtE5fsR/B7Ejz78PIHvw+LEDcyNKcxdtiNuWREP1hE33InLfsQVrR+X7YlbNsR13Z/npX5f1f503XFfq2KQOzZ6w9Gf6hknHJDIH5WI+FSEJzH8U4XDU+kRaYyoDN6Y7IUJ+UtSi6UySuSyyhRKixTLCiSLcxiFWcjPRGoC2d8H1lbQNoGFBVwd4OgEfRvo2sIliJGSLVlQQ8kpRXY+AsKhboSVOjAwh40NAn0RGojIEISFwNsPdq5kPWuqqinXn1xrlS73Kh0+uXU8qw0ZKuY0DRuyjSfdKYDPL0YkNlcup1qrst28YYdTS5db1Q7TgiatuILlvpG85i7QMIaMJklchSqqwpDVgI0TPTKKKzYBuYVo272i98g6K1+GmPIiVWdYByAyUrC6BgcGDfb0WcXkIKkIWSV8eaWCpTWiDS2SDS2L6zZz12wm5RXSgsMZppbUFapk3pUgSQMyEJClCMqTFynSRJS5hJXowkr0RYo0YSW6uBJEVejiSrQ1aojzw7Zc/JOCf5LxTxK6s3CgGAfLcKQcJypxrhYXN2OsFdc7cGcnHuzG465/X7F/tu+/Ef5x+AfhpwP4yManIbxn491+vN6HJz2Y6MLD7bi3BbdbOedOG+5txb2tuL8dj3bgyd9RF68G8KwPz/rwvAdPduJxBx42Y/yvw8eb/zfCZtxvxp0W3O/Aoz2Y3I/nh/HmFH5cWEmMGM2O6RDXN8xdd/x1w4N4EDQ3HvJi1OrSoFxPIzJiscEaSqaMNZYL1Oz4zN1pXsG8YdHILEbrbuG9R5Wau5R9YwU0LCla1iLGtvx2HlS3ADi7Q8uAukiOiiUkLAaWgi6NJUqU1doM5CWJZocLZwcIFwQsyvRjRjrByQgbtLFKjl9PE/+UYrgVF1l42Iw7rbi+BVeacLmBsxPmz+bQ85U4V4GxWhzLxTkWRitxqhBjdXi2F8/7cbsdo9U4y+JslfmzCfh6Mx524vFuvDkEYgTEJVHitMTsKX5iGMSToJ83jF8exCwbxBC+9+LrcYlfN9yI8yBOCRLnbIgblj/u8ny7YvZzLPTbHflvI/a/Ro2Im/qfTiz6fW39w+OGCYEI8kFw+AIrT/glifonUGNSkJHH6xWJgMyl4WmkyHTmpiyBuFyRpEKJ9BKZrDKF7PLVFaUaZSyZkiJycQHycpGcBG9vygZTaJjB1AauznB1oxg6QtcJbhEC6YWyJQ3zCipRWEKJiOddZ0PRtOBx8prvH4D4CGwKRWQQAvzh5gkje6wxJEtokRV0qHI6NFkt5kpNXjkdhpIRfa0tQ9+d6R7I5xO2ICxheXyean6NYfUWm6bdTm09Gyu3m+Q3asbkSXmG0owdoKKPZaoQVSALr2bIasDGlTsymhwTj/xidHSv6j6ko+cCKY2lWh5UK39ExS2oq8eBQYO+/Q6xuUgrQnYpM7+Mv6xWuKlNuqVNvL6Bt6EBJSU8sfFCLq6C6ut4ROTJXMsBGfDJUARkaQvkGQsVuBcq0Bcq0IVXM4RXM8QUIaJMXbyaoqCETV7ozEJHIjoTsTUZ3VkYKAabhYPFOFSM46U4WYHz9RhtxLUtuPWHyi5M7sHTXjzbh2f7/hvh2wP4egBfD+DTAXxm49MQPrHxkY13+/GsD0968Xg3HmzjDFzjOOzAnQ7c7cD9rZjYgWddmO7Fqz4878PzPkzvxfM9mNqBx+2YaOZEwokGTDXgSeP/RtiIe1vwaA+esfH6JD5fIM+OqBCjG35f0SVumBM3nH7f8iIehs0+DJo6Z3Jq98KOCkT6Y60hVhlzK9oKKdnTTV3JXsECoVHIYpHauhf9QegfL6xhybXGTEjPYoGJDVy84RtMtrCfJ6pAxWISpKj88liqBjUDmoklH3IixPLDxQpCRAsCRHN9Fya68fmYw0YbqkrQUkNJOo604HwZ7tUy7jeRR9txrYGTB47+nTD5Z7rWhVKcKcLxHJwvwbkSDFdyJvw83IGRKpwuwLlinGPhQhnnF+9vx+MuvGHj1ykQ56g/T4t/Oyf/fVSZuGpCnBT+NYhf+/B1Hz4M4ceILvEobe6S86eL+DgMYmw1cdWZGDWaHdUirtgTFw2JEaO5MdMfd10fjTjkZSM8Hh5RFL9oBMYhLJmyKYN3U5ZAdOa8kHRGcBo9PJsSlTM/IVciIVcmKUcqtVAit0q8ePOykgpZVsXSwnLevFKk5SAiiuTiQt1gQjU1hZ0TXH3JDn50K3eKkw8tPImZWy5UVIPSesGCsiXxSXxhIQgNRmgoQoMRH4GYMAQGkV3caHpWZAV9SOiQxbTJ8voMOR2anA5DeT1TzYCmYwZzRzj7kf1CEBgpGJwgH5mlnlypW9RpUrXHdvMe581bdUpqFOJSF3r6k83soGZAW6ZGny9HF5MXXKkNa29ExAtEJaKkAdv3yXfsMlQzY6zRwwZnftcQmnsYiqqZfWyj3n6j1HxkFdPzSvnyyumsOtS0CW3ukK1vVdncsqq8XCYjfUl4CNPaCXJ6wGpAigEZKmTIDBkIymLhKsxTAFYBKwE5UFdikTKXpBLs7MFKZtbFYlsCdiRiZxJ6s8EuwVAp9hWhrwADhThegROVOFOFC/W49KfVvgN3uzDRjSe9eD6AV/vxZj/e78eXA/jKxpu/RZrPB/H5IL6w8ZmNT2y83o+ZAUzvxVQ3Hv+9mt5sw612ztfbW3BvKx7t4oxsm+7HdD9m+vCyB9M78WwLJpowuRkPmzHZgieNmKrDs3pMt2K6HU9b8LgdE9vwvAczbHw8he/DIr/G1GevGBI3TX5ctvl9I5h4GPvjYeCLaxaXj8j0dyI1YYmTM1SNIGvMu8KUX8WGae3N4xPKExnFlccSaNq+dO/RtW09Wpsyltj7MPWtoW5B17Wg2LhyB4QIePpDzxzyKlghT9XQIesYkA3MKcZWJORGLi6MWlIUIV4QIpoTIJziyRdoC2cDqClBUxHZsWA34GwZblbgej2GW/4VOPJ3wuSfDsQ5Fs4U4UQuLpTiLOv/QHie9S/CkSrc3oLxXXh9AN+PgzhHnbsoPTuy5teo/K+jeDeAj3tBHJhHHOb7eBw/LoMY9yXu+H4do366CGJUjhhzIC4Z/7yk/fuKBXHJhBgx+jpqNj1suaOeLzsdvmHwi+cNj0dYMqLSqDGZ3DE5fJuyecIzucIyaFF53DH5gvF5S+JzxBNyFqcULskqFy6uFS2vXlFataSogieXRUrIRGAoycaGpKcLc3PYO8HFj+HgR7f2om4MpESn0wqr55c38lS3iJXXi2flCcYlc8UmcEfHUiPDERwGP384ucHEhqRpQpbXo0rokMU1STI6lBVaZDkdmqoBr44Z08iW7OBF9gqjB4TDP2KBf8yK0DTlhDLt/HbD8l1WNTvta9o1citXRifNd/EhGVtDaR1piRKFT4YiJr9ARhP2/giL5Y1OQmkjug6oN7XrqFtQVQxh7jbPPZjuEY7imvl9bKO9+wxT85FRSM4q5s0pJRfXorp1/uaOFZvblJu3KlfVrc7JltwUKbjRi6prBRENMmSokACkyXRZMOXAlAN1JSADSAOyoCnQRVR5F8vB2ATZ0aiNwZZobI/DziT0ZGJ/MQZL0FeA3jz05+NQMQ6zcLQUpypwrgYjDRhrxbUtnKg41YMXfZjZxxkS8+XAvxWaT0MchF+G8JmNNwc44w+f9HLqpXc7cXsLbrXjVjtutuJWO+504MEOzqX3PxG+3IVnnZhswXgDHjZjqgVPm/C0Ds/qMdOCl+141oqprXi2EzN9eHcQn8/g5+jy2TEd4ooZcdPy9zVn4nYY8TDq8x2vqUvG5wclt9UiKIhpbAUFA8gaz5MxmadkxWXpyfAMokdFcxeULmjZKdl/fN2WvVqxOSIbQ3gt3cjrbXjXWVLNHWgegYzACKqzNwzMSerreNYZUQzMKWa2NAtHLuRGLymOW1YaL1UaI1UQtjjdf36EM8nbAmvVoCaP+AD01eBsBcZYGKvEcBMnCTxXwVnSdLYcZ8pwuhQninCqCMfzca4UJ4txrhLj3Xg2iAfbMVKFM4UchOdLOXpvtGB8J17uw/shfD8NYnT53MiKL2cX/2Dj7SC+HARxzocY8fpyHp9GQNxWIx6Hzl5X+HQRPy/KEpfMiTGTX5fX/b5qRlyxmB01/3bF4WzPmpRIJKUgOBoRafyxafT4DGZCJm98Dn9C7vy4PIHYXP7YXP6kIv6EAoG43IVxWYvisgVT83lyyngLauaV14mVVM8vrKBkFCEmBZ7+MDGFhhpMTChWDlQHL5qdD93Wm+wZRo7Po7Ia6NUtYnXty6pbxAqr+DMK+ZIzBSMT5vuHcjn4Mc1dyGvNoaQPuXVkOR3acm2KmAaWa2GlDklZj77WlGFkw7R2oW4MpARGcwdFknzDFniGSvnGrYoqVMluXlfWaVrWsaGsSSmTJR0cy+vgAT1TyGligSwokhCTXyClio2hlKAIZlwqypupfYfXl1Wv0bWFrhXsvAXcgqg+YRyEewYMU/ORmkdOy+fOYpGKav4glG7Yoti8Q62mSbkwf0V87KLAEF4HD6aqAW2RHLAUkCRhJbj+CJQGJAFpQBpc8jwLVeYLL8daHSQHoy4W7VHojMX2JHRnYV8RBoqxNx/dOejNwUAOBnOwPxdDBThWjBNlOFeFCzW40oxb7bi/HRNdeNGLV/14N4gPf8sz79mcnPALG1+H8HWI8+T3n2DIyQ934t423OnArTZOteZmK6de+rgLz/ow3YfpPrzci+kuvNiGJ22YaMLjZky14HkjntXjeQNmWvGyHS/aMbMTr7vxfhBfjuLnOd7fo6vnrhoRV21/37IhbnsRDyKJB+Hvrrk+OLfu8E6h6izYO0HTCKsMyCvNBFaY8qtYUi08KB5BiIqhFpcLt++R2ndSZ8tejfi8Rb6x/BtDuUxdBQxs6SY2JCcvBMfyhicKuQXMN7VhmliTzR1oNq7cDh5MZMWIspKlKjJkK1PlWPFSmaEim9wpATYw1oW6AkJdsKccF2owXIThMpxvwsVqnK/k2DtbjjOlOFOKUywcK8DJQpwowNkSnCjC2QpMdOPpPtzbiuFKnCnEhRLOvtGRSoxU4nojxnfiWR+eD+DDERAjIrPnhd8cxCwbPw5i7uwq4vom4lb4j8tyX0dAjAoSj4KJ6/o/RqR+Da8mRo2IUePfl43nrpkRV61nrzq8GLavz0dcFKLiEJfOF5M6LylbIClbICVXKCl/QXLBopRC4aQi4aQi4RSWYEKBQEwmd1QadVMGOaWAklNBL6zlKanhLaqkZbGQmIvwOJqTJ13XkKSghLW6VEMLqqkTxdQV1l7wjSIlF5NLm1HTKlXbtrS8eUF+NVdKEVdEGp9nKJ+tG5eOvYCqBbecHlVKiyypTpHSoEtr0pZrU+TWQUWf+mdNook91dad5BYAnwj4htM9ggQd/UU3hkuF5SplNuiWbDEuaTUqqF+VlLfEL4Jh4wxNQ0gpg3s5SBIchF5RvAFh3IkZzOrW+QPHjLMKJE3dYOVO8Qha4BEEnzCwahf2HjDoHtRPzUdSNik5i5peQCqsRnUbT33H4s0dsrWdytVNygWFsonxomHhTB8/XhMLiqwKIE2GFCAFLAdkAClAEpAElgDSDH55/sXy0NZBlDeqo9EYifZodCZgdyb6CtBfyEHYk4W+DPRloD8dAxmcQWFHCnG0COeqMFKHa62cOfYvevF637810ndsfGTjI5uD8NtBvGfjHRuvBzEzgOk+PO3FRBfGd3FaFzdacK0J15txqw33tuLhDjzt5Tj8Ewxf7MCTdkw2Y6IFUy143owXjZhpwEwrZrbgVSfedONjP74cxM+T+H1Bkri0lrhmRVzf+PO2C/EwmJiI+X0vaGbU+vZRje5mruxImNpC3QiKJlyKFgtWmfKrWpEtPcleIZToWGpx5YKOHpl9J3Xa9qrE588LTGL4xtHsfBaaO/PqW8PSGX7R9NhM0ZC4BU6eDCsX2LiRHby4nH2ZSI0UyE9eWpEjV5WrWJEhmx8tHu9NC7GFlSHWKsLdAlsLcKYWZ/NxtgRn6nG+CmcrcLrs33OqFCdLcDgPxwpxtACnSnCsCOeqMN6DyX7casOFMs519M++0eEKDJfj6mY82I6JXkz24e1hzA0LzJ6lvWbjy17MDUkT5+2Ia1a/b1sQN12IK5bEJTnipsvcVZvZMYPfl9R+X9L+NbJhdsxm9roFcc2RuOd/dLtyZBCi4xESg4RMgU3JpNQcvrRc/rQCwYyihZnFwukskT8nuUAwNosnLBkRSYhNR1oRubCKr3QzL6uamluGtHzEpFK9wxkbnBgquuRlq6CkStbQI6+zJOvbwdKTHBjHlVPGVdGC+jbZ6hbJ4voFqSW08Ewuj2geM3fGWgv6cmPe5QZ8kut4JTSZYmp0SXXaSm0uhfXcygbQNKWut+I2sqWbO5Bt3eDsC69AuAXB3odp5SnkFLQ0OEshu25tSathSZNBTrXMpqxF7sH0DfYklXUQkQddEpDAklUCK7XhG8vvH0pLyxWq7xDZe0gvNVPcLRi+kQIhMWKewWTfMLBqF3YfWNezXz8lD/EZiEtFah65sJpU1cqo27KobotYaevK4nr5rELZmESR8Ahe3wCarR1lnS4YinRIAqKAGCcAYhmwDJAASYLCL8dcocHQMYC/KwpCUeyPzWFoi8P2TPTkoa8Ae/OxNwfdGdibjr3p6E1FXxqHIjsLQzk4WoRTpRiuwZUm3O3E492Y3otXg/9WaD4c+F8IPw3hHRtvD+DNwF+HezG5Bw934N5W3GrD9WZca8KNFk5yONmNp7143o/pfkz34vlOPN2CyVZMtuBZC1604HUTXjXjVTNed+Dtdnzox2c2vh/D73MLf4+qElfMiBvOxG3fn/cDiPEoYjL2123fJ2eNLu+X/6eSnOALc1usNYW2OVPDUkjRhEvdCtbeNK8welQcWFWCHT0y/SfWtvSsic1l+idR/OLJTv781u4CxnZUYwe4hyA6c0Fs+pLASEFHH9h7kuw9SU4+DEQHIjmaryBjWXm+fEWeQkmKdFrwvChnOFtAXw12eqhPxYlqHMvDGRZOVONsBc6Uc+CdKsWpUpwqwUkWDuXiWCEO5+JEMY4X40INxnsw3otrTThTjFP5OFeM00U4XYSL5Rgux1gN7nbiYTce9+P1UcwNCxDneT4P4dMAiKOmxEXv71dkv92UIe5EELfjiGuG3y8bE2NuxDUn4qr23GWN2VFrYszt9w1r4p7nx+te5WkIDoRfBCM0SSgqiZKUgZRsnrRc/qzChVkskewS0YwS0bRi4dSihZsyeMOSKUHxiEhCYjYpr5SPVStUWi9YXMWVxSLFZ1KDYpj2Psx1llwyalgkBSkF8motiqoRtC1h6ckISVyYV7GgvJla2yJTUi+RXrIgPFPAPXKeqTefhjVTzoghpsu9THfeMl0BSS0+SXWGlAZdfh1DyZBPzQS6FhR9G5qRLXmDPexcsdGL6u5DcfSBtQfD3F3ILkg8OEshq1a7tNmgrEE/tVwiPHWesx/ZyBIKWlggA4oEsAyiqxjKxvCJZQRFkrIKFzbtWLxzQD01e3F4ChJzJeLSV/oGU33DUFIjume/bi97fUou4lIRnYTUHEZRDaWiBdVttKoW/sIG8ayyZXEZ4pFxiwLDGZ5+dHsHmpkZQ1yLSV4OiACLAWlABiRpUCSxSA4LV9IWy3PLr+NZZwpfT+TEkFM9URGAzZHYmoKdOejJR18BB2F3BrrT0ZuKnhT0pXAo/tm9dzgfJ1m4UIWxRtztxOQePO/H60G8HuSUaj4cwGc2vrDxhY1PQ/jI5kxkerOfkx8+34vHXZz88GYrrjfjRgtuteFOx3908Pvxci9e7MZUJyZbMdWKZy2YacWbVrxtxqsWvO7Ax134uB/fDuP3aebc8BpizIS44Uzc9SMehv2ejCEmY4nH0d9ubHx8TPP0LvHGPES6wdEe5uYwtKDqmjNUjaBtBSsfklsYdVMCWFX8HT0y+06sb+tRj8sTCEik+8bRXANotl48Zo4MIweqgx85LHlBYq5EaraMTwTTxR/2niRHby74uiE8AElxArmZy8rz5Sty5ArjFmf4Mb3sYaELKx2Ux+NwFY4W4nQpjlXidBlOluAEC8eLceLvOV6Ew3k4WoChLBwrxAkWRurxuBcP9mCsDicLcCIXZwpxsgCnCnGhDMNlGKvBrXY82IOJQbw+gtmzfMRp5reDeH8Uc2fUiRHr35dX/by2mrjlRdwN+3Xb6usV3d9XvImr3sRVHeKqOnFlI3Et6Nd1R+KO5+mdCrEhCInk3RjOH5AgFB6PtAykZtMz8nhzihfml4rmlolmFgul5vPE5dKC47hCohEWh9h0UmYRf3HVopJqoeJKvlwWIyWbHhHP5RbEMHfmVTOkiymCdxmWrCStUCWvWg91U2xw5QmJF81iLSiqAataOLNYKDJFcGOIkJGbgIqVwEojvmV6TCldhqQOU0KTKaXBLa3JJadDU9Rnqphwa1tC345i6sBlbEcxs4ONM8XFjdvVnWnpAQt3pqWnqEOIVHCWQlaNVnGTLmuzblLJkoBEHjsP6JhhhQr4JQExkKWwSI6sYwPPaITGkHNLFrTuXtK2e3lWwbJMFr2kRiG7UNE/lMs/FCU1orsH1nazdVJysSkZUfFIzWEU1/BWtKCiBWVNyK0V3pTN4xtF8wrj8QzldvSmmDvQTK3mrdZjCq4GSRLk5eBRoPLLk/nlILoK0opYocKQVGKs0WXoWSEuQaSlRjkripLvgYpQtCbgn3TsyeFEwj3p2JOOrjTsTsGeJOxJ4kx2/7NkYV8mhnJwrBDnKnC1Efe3Y3IPZvrwqh+vB/9F+PlP83AIH9h4/zdOcvLDfkz04HEXp1j6PxWaW+14uAOPu/CkF0/78XwvnnVhqhPjrZhqxfMWzLTiQxveteBNM9514HMXPg/hxwkQwzLEFQPipjNx129uPJyYiiGm0+cmE4kH4Z+u2N9lr2a38JYnIdQe3vawt4C1BUwsKNomWGcNa1+ySyhXTBJKa4S27l25/7RxZ59eSpFkcLKIbyy/WzAcvblNHHmN7LmtvGj+UfNSsiXzi9dEp0l4hfE4eJGdfJhwtYO3O8JDkZoizCqQrS1cU5EmUxS50N8VDkaw1EFpDA7X4HgxzlXiWBVOlOBYMY4Wca74//P9n6mkB7JwOB/HWRhpxHgv7uzGaDWO5+FYNk4X4GQBThbgQimGy3ClFrfacXcPJgYxcwhfj+PHEdK3A3h6GG+P4dfpVbPn1/4eNZi9tuHHXeuv961+3NQhrgUQV4PmrukQN9SIG77E9ahfV50+jVqXRiAmBD4R89yjFjuFksLikJiI1Gx6Zv68XNaigrIluWWiGUXzE7MpMWnwDyMFhCMsjpSYzSgoFy2tXVpcKZBXQkvOoWxKJgWEkx28uAzt+JX1uBcrgk8SIlIUSUXSCm0oGMDYgScganFq3oIsFtILEZMG7xDmBmd+NZP50uvnienyCa9nyulxL9eiS6hSxFXIMpo0hfXcysY8KibchvZUMxduCxeeDfbUDTZkKwcuR6d5zo7zzN1g4c609l7iHL4iImtNZrVmYcPaorq18UXCvnE0KxdoGkJaEQwJYAnIUlggC0MXuEUiPB75ZULtexZv3rowjyVVWCtQ16peVKYaFMr9XwijkxAZR0nN4fuDsKwZJQ3IrOYNSICND+x9SY5BdAsPkqENWd9inqbJvOUaZMHVmK9MFVZniihTJZSoK1SpK+ShpMFYocIlr00ydiCVVGqy97tVF67McEFJABpj0JGCXZnozUNvNrrSsDsNu1KwMxldSehKRFcSupPQk4KeFPSmYjADQzk4wcJIHW5vwaNdmO7ldNv/IOQ07vfjM5uD8I/DN38RTu3FRA+rLSCGAAAgAElEQVQe/U0O/6djcXcHxndjci8H4dPdmOzAeCuet+F5C1614UMb3rfhTTPed+LLHnw9jJ+nQVxSJG5YEnc8iYdhxFQM8SKZeFM4N5n8417I+0vWNwal+2pQGIUAOwTZw80SjpawtiIbmcHYAfYBXM7hjNhklNbO+6dPbuic+Y79GzJK5MLTlvnFLfIOhaM3l7EDj749zwZXLvdgZnyqeH7xmpTCVUGxi5x8aM6+vPA0gYcl/F0REUZKTluYl7uMlSPDypSJD+F1MYOrEfLC0F3GZFfiUDFOl+FYGQ6zcLAQh4pwtARHWBgqwGAO9mfiaCFnZcXxYlxpxrNBjPditApni3Eij3MjvVCK4XKMVmGkDjc78XgPJvfiDRs/T8/7fpL09gC+HMDXQ/h5CnPDAsQVHeKG7dxN29mblsQtx18jlr+uOBK3/IhRd+Je6LcRe2IyYHerRFYyvHzgFTLfM3KJUwC3VwhiUrlT8ualFfBlsRbkV4gVVC7LKBTblDwvMAJewYyAKK6oNEYmi6ekXqS8cVl+xeLUHIZfvPDGcH5rb5qxC2m9LU3JiL5MlbRwJUTkIKZMlVRnyOhQda1pbmHc0emkxGxsyhNxj1yo5yi02mT+cgOm5Hq6lC5DWmeeqDaVcyPVZizXpsjrkdXMKfr2XKbOVBMnur49j7YNU8eSS9+aaulEc3GjWXiQ9O1h6SEQFLs6KV+3sMqopGF9Qa1SQr6ITySXkT2U1pHEV4F7KajLILAKCuo0Eyf4RAiGxM3LKseuQc3SylU5BWisN2xsUy6plgmLEvEORF45afeA4sAB07QCvuBohEYhLZe/uIpc1YDqRlTWIpe1yDcEFo4US+cF5i4Cpk4UMzsYWUHNgKy8nrxaiyqnSl+hRFuhRFupTJdVocqrUGTUuZfrCixWhL0rT1OT6cGjYdUtJlExC4K8kR2BllR0ZWNfPrrS0ZWBnSn/9+lJQ286+tLR/8dhGUaacKMTT3fjRQ+m+/D6z4TffXg7gHd/A+NHNj4cwPv9eDeAdwN4P4iZQUz341k3Hu3EvU7cbcfNVtxo4fQMn/TgZT9e9eHlHjzZhqk2PG/Ei1a8+gdvt+NNO9624FMnfnfjyzH8urCSuGZB3PX7PR77+1na3EzG7Kt0Yib790T891ter88ZXuoS3ZqD7ADEuSLUDsH28LaHsw2sbGDjAEdvLq+QhbHJKKkW2t6vdPi8zY79G/Jr1sQVSPrGkTwCGY7e3KYOXOssuQxsmQ6+AqFJi5LylqSVqsXmynlGCNp6A76m8LaArxOC/REbQ89IFynIkSzNXZGWtMjfHZ62yAzGPwVgV+JYOc6U4mgpDhdzEB5h/YvwTwwcysHRApwqxY12PBvE/S6MVOJ0IY7n4GQezhb9dViB4Rrc6uAgfPsX4Z/i2KdD+H4SsxeYxGVt4prV3E372ZuWxA3Huat2v646zV3zIK76EFe8iFtery7ZlOciMRY+AXAL4HENEXIL4w6KJcem0VNyhTKKFuaVLy2oFM8uEU3MEgyNIfsEIzCaOzJlXnKBYEGVSOlmcVbd0vRCoehkkmuIkJ0f09ydZOhEW2/LUDZmSKtTROSwSB7CStTFqlxiGjRVUy5bX2ZQLD0sAV6xDAsvbhVzXml93mV6THE9usQ6xnJdAVFtriU6DAkdppQuQ3Y9XdmYqmVNM3TkMnGiGzjQtKwZauY0TVPyekuypT3ZyZVq6Uk1ciBZewmGxCsmF+gUVq8vrtfOrZKPzhR0DybrWWG1NsRkwSsGPkkIKZCUNBgW7vCJmBcSNy+vGrv2aeUXLc8qRGO9YUOrEqtKOjRS2DsQuWXYPaA4yDZLyeMOikJgJFJz+IqruMobUdOEys1IL+R3C4CRLdnIXsDAgVfPlqxvTTIwpygZ0RUNuOR0aDLqdClVLilVLmk1how6XVaFLKnOkF7HK6kOr0Dhzk7bQ8fCK5uNAkPnuzsjzg9VMehMRU82dqf+/yHck8LZsNCXjoEsHCvG+TpcbsWjHZj46/BVP+e87ue8if92EG8G/vocwNtBTjx83sN5mObeFtxq4/QqHuzAVDem9+JlL6a7OAinm/GyHW+24/0OvOvEu3Z83YG5Pnw9Nv/XsBJx04F4GEZMJREvc+fe5My9ySKmM388jP4w5vL4sPrxZmpdAlI8sMkJkfaIcETwn8WStnBwhJs32TtkfnwqymqFd+xTPnTOevugWUGtUkLR8oBEHo9AqqM3t7Ej11oL+lorqrk7zTeSd1O6UE61TmaFZkS6lFsoH4LMEGgJf3sEuiM0CHFxpKysRUUF0jn5y2Li5oX7IT4ItenoL8PpSpwrwREWDhVxEB4uxqEiHMjDQDYGsnAoF/szcSgPZ8pxowPPBnB7O86V43ghjuTgWB5OFuJkIU6xcKYUwzW4uQXjXZjqw1s2fpyifj+J92y8H8KHw/h0Al/PYXZUnbhqOXfdce6m7dxVG+K2y+xN15+XXYlbAcSoO3E/+GK3bHw4YqIREkHeGEhxDqT7xPBFpDHiMpCcszCrWKyoUqagXColVygigeofBu9AhCaREnLn51aJF9VLFNZJprNEIpKZnqEwd+Mzc+E2dqQZONDW2/CqmHCv0KIsUYCgPFlIkUtIkWuBMlV2Pd3QkensS3cPhJU/1tqRVuhxi+vME17PXKRHFV/HEF/HI6rNFNdiSugwV+hxK5sxtW2Yho5cxi5UQ0emtg1d1YyqaEBWMYSuOSzsSI6usHCfZ+rMcPATDU9STinULqzWLaxTziiVDEjksfOBlhlkVSG6HHwSEJDGYkWymi7DxR8+EfOC47hKm8jb92olponkFNP/ICyulAqNFPb0R3YJdu1bfWDIIiWPOzAS/mFIyuTNK6ezalFaj+IaxGXzOfpAxxJrLTifC2tNadqGjJWGdBl9LkkdrqUa3ItVuRarcomp0cXVGdLKJHEVqoQOU1YXm+JWdHW7Dh0NK2kydvMTMjeHnx1y/NAYg91p2JHMWXDyf56uJOxJRncKelPQl46DuThZjvN1uLcFD7ZhogvPe/CiF8978KIHL7rxogfTvXi5F9O9nPMne/yD8EUv/h9f5xnVZPqt/SvJk0IIELqigoBIR3qR3oXQq3QIvUpNIBAIvQkiVaQI0sVeECt2x97L2HX633FGxxkdy5j3A8yZc973zLvW9eH5/Kz1W/u+733tfT2bwuMxPBhe6BzeHcSDETydxHfT+GEa34/jm2F8M4CfBvDzEH4dx28TeDuK30bwfhvE+/HnCY2/LjmK78eInxeJf6wWv2oQv24U/1Ir/qn8w+Osny7639yjt6sZjWkoCkdeGHJDkBeK7FAkhyA2CJHhiIlHQiq1qBQtnYvG95rMnvEZ2ete22FS0mSQXqoYkYzAeIZ7CMPGi2buRnLwQzCXSC6Qq9hgU9ftXNpskcZXR6Y3MnyRHojkECTFIC0N+XxKaZVCacOislq1Ir5SXiZqCzBRjaNNOFWHQw2YrcdMHWbqMFuHmRrsq8TucuwR4kAl9ggxW4njDbjej2/24M44zjTjeC2OVuJYFeZqMFeDuTqcasRXbbjZvwDhqxm8n8O7E3gzP9w5vzvkND5eMP1yxUd8M/jL7cBPNwM/3Qv/dC/i0/UI8W2u+E7K28tRo83Iy0RBATILWLGZtMgMIonHyCkn1pWDL1KsaFhe27KivH5pbolEUia46aSkDMa6EpTVydR2qNd2aJQ1LssUyESlUnwj4ezPdPanuQZKOAexHP2lzDyY2jYUNdOFgVdZA4acIbHchrHaW9IrlBkYQXGLpln40jUdpJXtZJUcZeQd6fL2ZHlbuqqNpKoNQ9NeYpWb5Gp/KfcwGY8Ipkc42T6Qbc6R1HMmr7Qj6zvC3pPMCSQHh2NNuJRnmGRYsmpOqZmgYXXNRuvqjYb8+kXRWUzvKJK5C9SNoKQB6eVQ1IaaKexdmDEZREImI7VAon1o0cCUWXq2REWDXE+nS9dmo7oW9dRMxagECOsxscdwZpZTUi3JzUR8KvKLpQXVRHkjyhshqEF6Mcs7Epbu5FUuDB1Hkp4DycRRYpWd5BJ7YrENoWhJkzMlZE1osiYE25Qsa0ZRMyYrGZEXW5FXOaK0wmzXntj9h1KqOx0DopXtHRHohsJQtKRhayGGizDx7xCO8xZ2SU/zsaMYe4SYrcXJZtzYhDsDeDCCpxN4NoUXE3g+jmdjeDaG5+N4MYEXE3gxueDV/nEnftqNH3f9Y2ebH7K7twV3B3F/CI9G8WIC307g21G8GMI3A3g5hFdb8WYc7ybx+zjeTODdLohn8e6Uifiqr/hxqvh7kfjnZvHrNvHr9eJfG8Q/CN8/TH1x1v3M2PJBIURxKAhBfjiKw1ESgaII5IUjPRTJkUhKQFIaiS/Ehh7liX2mM6e8hne71XWaCluNc0RqUWmkoASaRyjTxotm4ky2cod3OGIz2Lwq3cZOh4YOR361IXL9URCI3FBkhiMlEmkJyM5GbjEKayRFrXqV6w2Ly9iiIvQJcaAWc3X/EHiwFjM12F+1ELi9swwHKrG3HPsqcKgaX3Xh2U7cn8DJJhyrxeEqHK3GsZqFkMOTTTi/ATf68GgCL3bh5wP4/SjeHsObWfxyCL8cwS9zeHua/PGCxZcrfuLrweJbIV/uhb+/Ffrx60jx3XjxjTjx04IrO1c3lKCwhJbLo2UWEilFtFQeI6OEtq6ClFdNCOtUq5vV58tgej4SMpCcRcopVOZXk6paFGo7NMqbl+eUKkekS3hHwskPTn4M10Ap92C2a4iMo7+UqbuEri2hYQ4FQ7K8EVXeiKpkRtO2p632lvQMZviFUlwiaeYcSXV7mUW2CkqO7L8hJNTtWZr2EtouNAsflkuYHCda3juS6R5GMvdT1HeXVrcl1KzJ+o5kO28KJ5AcGkbyCJFeEy4Vma6RV25S2mhZs9FC1KqXVykTmirtEUqYOEBVH4rqUFTHYj1omMPTW5KbTYrPIGfwmN1jqj0jRtFclNUpdnc4dWwyqF2vNg9hWR3GdxvMHvYtrZHkZiI2GZkFrPxSRmE5CoRYV0yOzJJzCqYYOROa9rSlllhiBU0r+gozlqIlWcGCImdKsI2p0kY0aSOCbUyRNiGrmVEUTMiLLGHujvpm2/0zCTtmuOXtdp6Rama28HRAZgDqudicg/58jJb+K4QTfEwWY6oE03xMF2NXKfaLMFuDr+azDftxbwvuD+Hrwb8T6vsXAnrvb8HXQ3g4iqeTeDGNH3Ys6Nv/Ziudf6S5P4SHI3g6iuej+GYEL4bw7Rb8uBU/j+DNGP6YwNsJ/DaFP/dCfAwfzjp9uRkmfl4gfln35fVG8ZsO8esW8S/1n5/zf70VfeeIxb4uWmsWCoOQ44fcEJRGQRhNEkaTBJHIi0JmLFKSkJQGvhAbe1Um9pnuP+G5ZadLfadl5UbrwhqdqGxKUBLhHi5h5S1p4EQxdoJLIDk0UTaTv6S2zaZlk0t162oUhDB44VLFUayiKFpOFLLikJGKnFzkVkDUqtfU41jXYlAjQkcZtlfjeD321y1oXy32VGNXJXZUYLsQ0yXYJ8JuIfaWY28FzrTh4TbcHMFcPY5UL0B4tBpHqnGsFicbca4V13rxcAzPd+A/+/F6Fm8O49cZvD6CX47jzQn8cUbl0wW7L1cCxNdDxTeDxXej3t0M+XQvWvwgSXwj/q9bKSOtUvxCFFews3lIKUS2gDHvEc2vYhU3yNW0Lq9pXS5qUi6qoKQVICUH2UWS/PKlNa1LG9o1K1u188qXRGWyfKMIpwCSnTfcgiTXhMqsCZdyC5Wy96MZu1J07MiaFiQ1M4qaGWWpJVnbnmrqTnP1p/mHEaGRFPdwsrkXVd2WqWIto+wgreRILLEnltrRVjozdF0Zpl5UhyCWd5QsJ1bOK0LKLZiq7ymn4chcbEEssSDrOxL2HDonkBwcAvcQBieKHZujXlBlVtpsUdlqKmjQTOPTfeKkHANo+jakxdqQV4OSBpYbQteK5BckHZ+F2AysK5XfNKG5sc8wLAqC6sWdGx02duvWrldLy1KOSoCgBqM7dWcP+5bVSiVlIJqL1CzptAJ2aoFEcq5MfLqsd4yUuRdVw46xzJopa0aSM4WKGX2ZIUvWjDJfA9nGdLYxXdaEJmdKyJsTqpYSChaUpTYkR1+iq8dj9lDi+L5oXputXaiqjgVcbJHkj6pYdGSgJwtbS/69EhZjogRTJZgqwTY+tpdgtxD7RTjZhDMt+Kp9YZPF/JzqvK524FonrnXjxibcnnfGjOObSXw7he+349udC7bSxxN4OIr7Q/h6GA+G8WQYT4fxfAueb8F3Q/hxZAHC9xP4fRJvd+DDQYhPLv58yUd8P0H8vUD8S9OnNx1ffusQv14v/rnu06Oin64GX9itMVQPUQKyfZDji/wwlEUTwhhqRQy9PIZcHEdax0VayvxpHxt7lSYPmOyb8xjY7tTQZVXTac+vN+AWEqGpVI8IpjVHysCJZmgHO2+KX5RsUj67Yr3p+h7n5m4n8KKVSqKVS2MWCaLl+TEShfHITUVuBnIFENRp1HY5rO91bl6vuqEcI+U42IB9tf9AuLsKO0XYLsR0GbYVY085dpZibzn2V+JMG+6O4WIvjlTjUCVmK3CkCkeqcEiEozU40YBzLbi6CQ/m4+z24tUMXs3g1QG8OSb9+gTp7Wnm+/O6ny65iq+GiG+Ei28Gi29G/nUn6sONcPF9rvhO8p3djg1C5AqQV07LKSXllJLyK6n8GrmiWll+/aLiZtWq9SqiJqWSWmp+OdaVIL+MLKheXN2kW79Rq7ZFu6hSLT6LzYkguwQSjgESDn5Sa8Lp3pFM70imayhttQ/J0AXatiQtK7KBLaFrTzZwoph7UVwCCb8IckQUYmPhHQMbDrRtGUusmEvtJJY6EOoONE17lq47xcibsA5guEZIcWLlOFFs9xCGix9V3UlG2YrONqYomZENHSUcfCS8A0gBgfAMo/nHSycWriiqMRM0mZc3mxSI1OOy4BbKtPGiaplDUR0yS6CsCU0TGNmQw8Ll4tKQkIbiCpXOcfXGnpX+ESgUqbRvsGvr0qlpVs3IWRzNRUk1RnbozB72rWxkp2YhMh4JyeyYFNZarkRwNMsnWNqSQ9eyJRZbMBTMGIQxpIyhYELI6zHZxhS2MZVtTJc1YsoZsxTMJBXNaYqWNBVLhqIloWZPeIZJDg75zR6O37w9MLPJ1MRXWc0Iq62R4IuyKDQnYWMGtvw7hKM8jBdjUoDJEozzsY2PHQLsFuJQFY7WLThATjXiZANONuBMPU434HQTzjTjbAvOt+FSJ65vxu1BPB3B83F8N41vd+LbnXixHU+n8HgCD0bwYAQPhvF4CE+34NngAoQ/jOPVKP4Yw58TeD+N93vw8QjE503FN0LET9LEL8v/er3+w2/tn95uFL9uEr+s/vPr/KdfeR8apbXykR+MNHdk+aMwEvwYCUEMXRQrWRnHLEtg5iVRUtMocZkoLF2AcO9x9/5px4au1bVdDsUNq9LLZNZm0lwjmBY+LH0nhrYtydKF5B4oEZ9B41eurGuzXt/tBH7c0pK4pcKYZWWxKmVxcgIulZ+Kggys4yO/fEnFBpu2Po/WdoOmCmwuxf76/xvCHeUL9ohxPnaWYnsJ9pTjYA3OtOPWEE614WAlDlRgpgKzlZitxEERDlXjeAPOrsfVHjwYxbPt+GEPXu7HywN4uQ9vji/77aTyH2dUPny16q8ra8TX1i5AeDVCfD/u3dVg8e048cOMXRvkhMXIrkC2EPlV9OI6VnEdS9AgJ2haLGzWLG5eUVYnU1xDKRQhvxxFlRDWy9dvWNnSZVLXvLKsVi29UDEohuzkBwcfmkugnGuoincUhRNNcKIZLiFka2/oO0HblrTSmmLuTLV0Iaw9CZdAghNBDY1FbDwSuQhKhEsgYeBAV7dmqdky1eypmvY0LQdpfU+yhS9hF0rziJbhxMp4R0q7B0o4cWhLbaTkTAlJAyiaUvSdmA4cSS9/+PjBK5IalCiTwl/JqzUtaTQubTDMKV22NhmrAwgzV5K6EeRUIa2CxZrQMYOxPSkiSiE6GfHpKK1S6xhbXte5wj8M+eVLNrbabujUrmlWzcxdEpOIkmps3b7y4CGf2ha5jFxExCE6TjokmuEVRHb2olg6EjoOlEUmhLwRk2lMJxmCMAbbmCKjy5A1oMgaUGUNGPJGTEVjlrKppLI5bbEFTdaMImVJXu5I9o6U3joWNDMb2zHmnVitt9JDRlEPVhaI44AfgfoEtKZi4N/L4EgRxviYKMFEMcZ4mCzCdDF2CHCgHAdFOFS1cG46IsIREY5W4ngV5mpwohYn6nGqCefbcLkL1zfj8RCejeHbbfhmF77djW/+TtV+NIaHo3g4gkdb8GTwHwh/nMAvY3g3hg+T+LQdH/biy3F58QUn8b1o8TfZ4l+qP71t/fP3jo9vN3553Sj+WfT2dvbdOcfpLlSkguuOWAeke6MoDLwYKUGMZEWsjCieJeSy8lOYyenk2ExygWABwj3H3Pq2OTR0ra7rdixpNM4UKa7NlnCNYFr4sHUdJVZYwsgB9hxiLRdZ/MXlDasaO+zBS5AVxKuWx2tXcTVFibKliSjgIjcekdkoFLIqG5bVbzDYuMmuUqBcEYu91dhbjQN12FeDvdXYXYkxHobzsEO48Ft3VZD2irC3Cl914epmHKleqIQHK3BAiJlyzIpwuBJHq3GmGZc6cXMQz6fx0z58ux3Pp/ByP/44Zfn+vP3HS/YfLzp9vOT+5WrglxtRf12L/XQ77d2VcPH9CPGj+EfHfJtLUCeSySgAv5JaWE4urpUvbVYtbVwubFGvbF1e2rCotFGhqIayrgKFlRA1szZ0G3T02G1od6haL5FfKhWRKOkSIGnuRpi7kZwC4B9LDoljhMRIccJlnHylzV2YenZULVtCy5awdKHZetJd/KhrAklBUYhOpiVlMJLSSGFJcAmGoQvUbemqNpIadpK6rgwzb5qNO+EaKMUJl+JEUH0iaV6RbBt/KS0nMsOCCiMy2YCkbE41cGbacuhuQSROKLyjlGOyNAuEBoIavdJanaJKHW6hqn+ilEMQW9+JxtADVAFVMLWhbkUydSFHJ9PWxrPiMiFoRs/EKr7I0NMfBSL5rjbnDZ1aVesXp+UtWRvPKhBiYEpr/1GP8lb22iTEpsl7hTK9wtg2fjRdJ7KOs4yGucwSUyllQ4a8Hl1WlyatR5sHT9IATH0yQ48saUAoGtOUzamLLMmLLLHYQmGxKbHSAuv4uv3jgSO7IzbtWBuWv1jTQVVBH6udEOeNMj+0RpPquGgpxlY+xvgLjpmpIozzMMbDaDHGef+75k02O8uwS4g9woXHhZlyHBHiWAWOV+N4LebqcLIBZ1txoX0hzOvJJJ7vwIudeL4Dz7bj2TY8HMHDETwYxdfD+HoIjwfwoh/fDeLXcbydwIdt+LAD7/fi3SH8dVZXfCX48+NM8Y+lX36pE//e8elN+5c37eI/Ov78Rvj77bhbM5b91cgMRrgtouyQ7o11ISgOoVVESNTHSdVzWRWJ1NwUJKWRIrNIeQJs7FfcccRwx1HLLVN2bT32TRusq1sN1lWtjM5X9o6RWu3PMHalrbQjq9sT2i5M51CEpMlkV68oazdBcaKCkLu8kqtTxdWs4MoUc5EXh6wYBHKRkk8pEclWNmqs7zAvK5IpDMKWHOypwp4q7KzALhF2V2JKgLEiTM8H3/OwQ4g9FdhbhQvduLoZhypxsPwfzVbgkAiHq3CkGqebcbkLNwfxaBu+342nk3g8hh9247d5CC86zUMovhb05UbUl+tx4rvpX27Hiu+Gv78ZObfFtCgJhQUSyXnIE0hmldCKqpTKmzXL1qtVbNCs2qBR2qggqJHkV1KLKiGsZ7d26WwetusfdOrqthPUSCXlEl5hZBt3wtyFaeVBuASSOVGkkDiGXzTTK1TG3lvC1ImubUNoWlFX2tAt3Wn23hKu/jT3YHJgNBGTwkjOoiZlIiqNtCYcFh7QcaBr2rNWOrKMPRiWfgx7DuERyvSJZHIiqN7hdNcQGVMvlqoNiWpChz6ZpE9abEEzcGau9qa5BVDWhMIvbnFC7sqCCn1BjV5J9co8oWZUtrJXNMPGj6VuTxDawFJADVL60LahrPagzkMYn4XS9egeNyoo01kTgPxypc4NLq0dKyqblf87hAeOrRE2KwbGIDRWxtmHbu/LNHYnL7OGmhVT0ZghZ0iT0adL69GkdKmSejRpAwbbUIJmTDCN6bImDFkThoKZpLI5TdmcssiSrGjMWGFDsfaAoNpseDp0cGd407C/ezJTxVJ+qRGcnZHsjcoQtMSRauKxnocB3gKH8xCOFWG0CCP8f4VwsgSTJf+0EHeXYXcZ9ggxK1zobx2vxfHafyC83Y/7Q3gyiefTfxM4jWfb8GgUj0bxcAwPRv4HhD+P4c0EPmzD+x14tw/vjuLz+VXia2FfnmaL/yMU/1o/D+Hn163iNy1/PBO8vOx3bkqrtQhcTwSaIcwKiR7IDEBhCMoiqbXxrIZEqYpEan4yUlIRl4mSMmwakNt91GDPUYuRaZtNm+3aOy1bNhqWNmplFC8O5tJdAgljV4q2PVXLgantynb0RWA8kcJfXFi3AoIEeSF3WVWibnWSekUSmxePzGgkhcMvmhabRsnmUXgV7MpGrcIsUqYPurjYVYXpckyWYrocO0SYLsdECcZ4C5nb2wTYJcS+SlzswdXNOFSF/SU4IMCMEAfLcUiEw5U4XIXDVTjVhIuduN6PryfwfBpfD+PuFryY/gfCPy85f7y05vP1EPHNGPGNePHNBPG9+M83Qn+9Ft1bqRzph/B4WkgKKzZDKi6Tua5kcUmtelnjclGLWsWGZcUNcnwRpUTEENYor28zGBxyHdvmNTzs3Nm5KqtYLiSeZOMOQzuymSKUF6QAACAASURBVJOUnTfbLZjuHY6AWAnfKJZroISVB13XltC0oKhbUDStqOZuxGoPqoMPzS2A4h9JikoikjKJlGxKQibDP5Zs50s2cpUwcGYZuUqZc+j2gZKuQYR3JNMvWso7nO4WTLf2ZWo50RVMSDBiQp+QMqSoWdONXSUcfCQ8gqicCGpIsmpSkU5RpZ6gRpsn0sjkLwlJZjsFw9yTscQC0ACWAOokWSOSkTPhEiAZlUSsjWcl5kDYiu5xo6wizTUByC1TaGt1a2zTKGtSSstTjUiQzi9D/+SKmeNewiZVjyC4BUmaOVMNnOlqtmQlE5KiMY2iR8yLrEtQ9AhCn0Y1oFENaGQjKtOYLmUqxTKRZBtKyBkSCiZkZXPKEguylbekb4xMdavV0I6QTdPBZR0u1hFgG5IMLODvikwOmmKIDYlUUTQac9BdiL4ibOVhjI9xHkZ5GOVh698f/6/GeBjnL9wS57uI817TA2U4WL7gTD5Wh5MNONeKi+24tRn3tizMED6bxrNpPJ3C0yk8GceT8YVHmgfDeDKIF/34dgAvR/FmAu+m8eduvJ/Bhzl8uWgtvrlW/G2e+OcK8esG8R+df73e+PmXFvGvTW8f5j87u/pgn6wwAcGWWKOLABNSrBNSvJEXCEEE6hKYdcnSlckMXgoy05CaiboqbB2SPXxY/+hRsz07TCeGLLf2mQ726Le0LS6tkEpMBScIlm7QsSOr2zLV7WXtXeETjJgUVnqhMoqiWSVxi0WJWtUpmqJkuYI4JIUj2h8B0cpRXJnUHKQUIquYlZaEdf4YSJPYW8OYKsV4CbYJMVWGyVKM8TGcj1EehvMxVYJdZdhfhcu9uDGIIzXYX7LA4fzfnK3AoUocrsJcPb5qx9U+3BvDw0ncHcStfjyZxJtTpu/O2b6/6PThotufl33+uhH65Xas+Fbcp0tB4rtr318LeXMrrTqP7eYMBx/a6iBpj1AmJ4Iaky6TI1AsrFQU1CuXNi8pqpUtLEWJSLamfmVXt+PYROC2Kb/eXov6hkUxqYoeQdRVdtCxIEwcpO285T2DWZwICb9opneYpJMfw8yZusKSvNQEi8zISy2phvYwdoKlG8neG15BCI1FbBolNYdIzWKFJ1LdgqnmXlQjd7qpF2O1P8M1hOEVSfKPofvHSHqFMh38WMbuLFUbhpQhBYZSVAMJRVNCx4Fu48V0CWBwwqUC4+SisjXSSnT51XoltSsKRctSCxT945l2/jBylZAzBZYDS4EVJAUzWHkQ3mFSUUlEeBwzJZ8i2kjqGluVkKHkHYjsEvnm9a5V61WLa+VT8lQjEmXyStE3oXlwzlPYpLfaC9aejJU29GXWdCUzsqwRWc5QArpU6FOgT4EBAX0CBpT/EmHMYBoz2YYSMvoE25C0xIJQt6VbeRC+MQqx2YtqNlr0TvttHPfLqbc2DABbC/b2iHZHoT/WJ0nVcckFoahMxvo8tBegn4eRYozxMcpb2Ar1bxCOFGGkCGM8jPH+bujzMM3DXgEOlOOQCEeqcbQGcw0424KL7bjZu9CXfzyBJ5P/6OkEnk4sXA7/B4Rb8Xoc77bjw158PIRPp2X/uuYivhsj/p4n/qVS/LpR/Efnlzdt4l+axK8a3t7PeXTKcPsGItsPHlpwVoOPPnmtLRI8sS4AxeGoTpBuSFaoTWEKU1CUCV4ONrdg7wT93BG9C0cMTuzRPjSldXBUe98W9fF+6e71JCEPCfHw9oWFE/SsCA1LCQsnOPvQA6LlI1IUkR2Mogi2MF6tKkVdmMxeF4vYIAR6wzNYKTCSFZNKiUlFdApiI5AXhNG8xUdadCYFtNESTIswXoZhHrbyMJC3AOG24gUIr2zG7WHMNWJWiINl2F+KfQLsL8WMELMiHK7C4Wqc3oArm3F3DA8nFzIin0zi1ZzRb2dt/rzg+u6i95+XAz7fWPvlduyXm7Gfr/r9dTvk9ZXg3+4XFGcp2thAz46q4Ug3cqabu5G8wxGfQcssJPLKJQtrFLIq2Dk88IVy9c1Gm/vcxieDRsZ8NrQYFRfTvUJlbNwJHQuyuilNx5pp4Srp5s/yC5fgRLE8Qpm2HLq+I6FmikWGUDIiLzYl1C2gYwl9O1i4wtEHvuGISkZSjkRqJi0yke4dTtj5Ui28iXlnjGcYzSeGCIiV8IuWcg9mrfaW1HZiLrKUIIxp0GVRDSSWWTDMXWguflSvUGZALDssRZnL08oq1ymu1SupVc8vX5KUq+AbS7f3I2k7MdmGgBqwHGRd8lJL2HAowdGseQjTixjVnfTOEZPwOCYnkJZeKFvd5CSoV8mvYiXmL49IlM0UoHd86eyJNRVNpqscoW1PUzSXkDJl0owJaSMa25AFfRoMaDCgwZAKw3n8QNInUQ0IhhFN2ogma0BRMCSpW1BWuTBsfKQ54VLRmYszBMtquiw3TQc0bPGN4BlouGKRDnxdkcOBKBT1qYrZkYj3R340KjPQlIvOIgwWY6QYI8XYysNWHoaL/nfNQzjKw1gRxoowxVvQjhLsLlt42DtS/Q+ENzb9Y1J7NL6gx+P/Xwgn8MdOfDyAT8fw5byB+IaP+Os48Q/8BQjfdYjfbBS/ahD/XP377bR7x3QGaxDrBLslWL0ErjoIskKsKzL9URyOKq5MY4pyfZpUdQbq8tBYjN2bcGYH5fYxrbtH1a/NKF3ZK3V5u/RXE4onJin7BjDYhMoipCXA3w+2TjCxxCo72LjT3YLlOdFKSA9AXiirJFqlLF6pMI6WEo5wX3DcYedNc/MhBUfRAqIonFAE+yMvEKN5Sue7PEYLFbfkYUcVJoUYKsJWHrYUYGshhvMxXULbWYq9Ilzuxd1RnN2A43U4UoXZChwo+xvCChyuxGwlTrXi6gC+nsTjadzZguv9eLQNPx3R/fWUxe8X3N5d5Px5Jfjzjci/bkV/vBn55W7A7zc4P1wOePWouDBL1cAEamY0JTPaUnPaShu4+JFiEpGcjRw+M7tMnsuTTc6j5ZYp1LUYdA84Do2v6elzFlbqpKQwrN0k9G0oasbkpUaEpjl1lQPZ0YfsE0rxipjHhqFnR11qQpbTh7wBSc6YomoCVROstMAqW4q1K8nDHyFxVG4WKzEVsUlEQBThEkh28Ke6BNO9IiR8oxgBcTT/GDonXMrJj2HiJqluy5SxkIApE9oMqgFthQ1ltRfZOxiB0URYMjsme1l6mU5OpRa/RpNfrbquVDkuU9o7iubgT1W3ZzH1geXACjLDhFC3JzkFkNZyJSKTEBZHzSqWruuR7hg29g2Bb6BESh67vN6xoEops1yCm6sekSibxkfP6KIjc17CFqsVllAyI1ONWDBgwJBKN2RI6jFgwIABA4YMGFJhQCEbkJj6ZIYemPpkaT2ynD5pkSG0zGHmDFd/ik8kLTpRNqNAhVe9orbXqnNbgKDD3TluqZwFVpoixhPl/mhNkC5LlPP1gZcnYkNQmARhGprz0MPDEP8fAocK/3f9vxxOFmKycKGHsbccB0U4XIXj9QsQXu9ZOJHOLz58MIqHo3g4+u/H0SH8Mol3u/HpIP46gS8Xbb/cCfvyKEH8A1/8SiT+tV78e9uX1+vFL2vFP5a9uca9sHt5exGCzbF6MVarwk0PQVaIcUWmP4rCUZUgX5+i0pgm05KLrlIM1OL0OG4dwIu5pS+OyT6ZxaODeLQP93fi6jacHcP+HgzUojYfufGI9IWXE0xtYO0Ee284+9OQE4zcEGZhGLsgXDIjDDGBCPCChzPs/Wh2XvD2p7lyaI4epEBvFIRjoljh0uaormTF5liMlZLGKzDIxxYe+vMxlL8A4Q4BdpXhQjfujeGrzoUx/LkGHK3BoUrMijBbgdkKHKjCmTbcGMLD7Xi2E7eHcWMAD6fw4vDylydN337l+u6S/4er4Z+vR3+8Gfnn9bVvb7i9OGv17JLPz88qeEX6KwywzJiuaEyTNWFoWJNd/SlxybT0HGQVSqQUyq/NYMZks9aVLRG1arf0m7T1W1Q2G6dnLwkMohpYE8tNyIv0ySqGFC0rqokz2dEHnFB4hkk4B0nYeDH17KhLjElsPUjrkWUNKIsMoaKPZYbQNqessqXYuMMnDBHJDG4i4hNJYXFUrzCyewjNK0IiIFYiII4WGMf0i2Z6BjNsPel6dlRlcwrFlIApDTpMhgmh50x2DyRCYsiRiZT4HKXUEq3sKt3c6pVFNaqFokWZfHZkCs0zjGbnS1a1kaTpAGqADpVtydBzJruHUOLSJOchzBHINvQqdQybufvCL0gyKUemuNYhs1wuqZQal6sWwpVJKULXFoUjc15VbQ7LzCBlTIIRC/p06JFJhjSyLg26DOjRoEeDPkHoU5j6ZGkDyBuQFAzJKoaU5SZkPWtYu4IThMh4JKRScnKXFpVqlDboVHVb1g2uSRRZ63hLSZuQrR2QykFjCHrSl2XFyunbwdQVXv6U1Gjkc1GVjo356CvCYBGG8jGUj8Gi/13zKG4twNYCjBRi9G+N8zAlwG4h9s03t+pxtgVX2nG9a2GrxYLDZhgPRvBw9N8fZrbi1yn8sRefDuHLaXnxZfcvd6M/P04S/1Ai/rnir1e14jctX141fvq+XPyc9/NXaw8PKlWnwN8ETupw14OPOUIdkOiNLH/wIqiihMV1yUua0qU6i7C1FrvacXMPnh3By5Ny/5nDj8fw41H8cBDf7cHtbbgxibND2LcRQ9XYUIiyRGSHIswH4b4I9UOwP5AfTs4LZeUFs7KCyIn+COPA1w0ezuBEyzv6wMWbWO1Is7anBXGIsnjS7iqliz3chnApgQ8GCzEuxCAfg0XozcFgLobyMF0iMc3H9hKc68DdMVzqwVftOL8RZ1txqhnH63CkGrMVmBFiphpnOnB7BE924cVu3BnBtX48nMKzg0t+mjP+7Zz7u0uBH66s/Xgj6sP1yHdXw745Y3pzRvP+hTWvvq8pL7fW1Ie6MWORkYSCiZS6Ld0jRDo5k52dz8oukknKVQhKlIrKVs4ULilrW17Tq1ndoZFXrhoaI+XgTNa1pC4zJCvpYqkRoWvLsPIgXP3JPmFwD5N0DmJZeDH17GhLjCkyupDSJcnok5X0oayDRbrQMKTomMHEDm6+CIohJ3ARn0ham8DwiaSsCaf7xkoGJ0iHJbAC45i+USy3AIaVK1XLiiRrBBgBJmToS7ItGSaedP9ISlQyEjIZKfyl6yoNcmsN8mt1CquX5ZcrpRVKhidS3YLJNhyKiiUDWoAaoE9XsJE0cie8wwluFmsewnWl8o2bF7UPmTh7wS9IOilLjldtl1IqxS0hx+aohnBlkgrQOSh35IRHTZerqjloxmSYyMJAAvoEjOnQoUCLCm0C2lToUBh6ZBl9srwBabEBeYUlS8daythewsGTFRAmFZ8kmZnLyOPRSku1hZU6ZY26glYDXputf47OEntCxkzS1QMZvtgYShrM1eJGsmXNoOYEe2+JuFBkxECYjOZsdOWjLw+DuRjM/VcItxQsaDgfw/nY+rdGeZgsxq4y7BNhtup/QDh/Il1YQPpfHP5Li+KneQj34fMRiM+oiK94fb4X//G/IHxZ89fr5k//qfn4ouTTo5zvT/ntameXxcHfGO568LNCsCOiPZDhT8kKBC9cSpSwtC5ZtTlDprcYU82Y3YzHB/HDHN6ckv71BF7N4fUcfjmCl/vweBce78btbTg3iAMdmGpAnwCtWRClQZgMXjyyI4HKSPnSSHZ6ANZyEOQDT0+4uoHDoW1ptyng6S+zhZ6HjJkt4gMhjMeuZt25Yf+ccBkfB3CD0S3EUCm28tCXgYEsDGZjp4CY5mM0FyebcW8cl3pxvA2nN+J8Jy5040IHTjXjWC2OiSjHqyX3l+NaP344yLo/hcuDuDGGS0N4vlvy5azubyed3p3z/fNS6Kfr4e+v+/9yye3sTuyYwJlLax59W9K6wcZYH8s1sdKUvtwSq31IIcnklEJk8ZFRgIRUanicVGyOZKZQobx1aWW7SlGVXHQyzcuLttqKrm2OlcZYYQgdU5jaw5kD33AEx4ETB7cg2LhQV1mxNU0U5AwloA/ogq0BFS1oGEDbECuNscocDu7wCpWJiEJcAiOOS6yNRUQcYlIp8RmM2FRmfJa8jRfM/RSVnaVgCugBjnToAQaybGu6hT8C4sDNZPMqDAQNFtkV2gWNi/PqVbKrFiWXKEZmSfvFMVyDqPYcupI16CvAVCeWGcoY2BL2vghKoMWkS/pFKYUmIk+E1l7N9R2WHn7w8EdkulJBmX4OXy21QDE6Szo8kZqYTW/t1pw96TKw2V3FnARDwIBYorZkmQod2oAOU1JHkq7Pho4kdOiEIZOpDzlDrLRBdBSjVGDo64uwMMRxkZrB5hXrlgpNBSKdsjKz8nqz/I3qfmUq6v7KKmZ0fVPE+aEkAL1c2e6CVbbOYFhAzZps78j0DWZERzHyU2hV2WjOw8Z8dBahm4++QvQVYnMB+vPRn4+BAgwWYrAQfXnoy8OWPAzmYygPQ3kYzsNwHsZ52MbHjhLsF+JwFc424lIrrrXjxqaFFU+3Ni+M1d8dxL0hPBvD42F8PYSvh/H1IL7uxYMePOvFy0G83oZ3B/HpFD5e0PrruueXu9Hih0ni7/LE3xWIfyoX/1z35Qlf/LRQ/DT33ox9X710eiACTMHRg78xopwQ74GcEDI/UEoUq1IZr1iVQLTnYlyE4xtxYwgvZvFyDr+dxu8n8PYY3hzBq0P4zwy+34sXO/FwCrdHcLkPJ9txqBn7azFdi/EKDPDRlQsUBmFdMDWOAx9XuLnByRkuXgiMoO+fDCwtN9d0giGHbemA+EBUcLG/bdVcn1dagISLFdxdUJCMtnyMCDCYiy28hd1bWwswXYbT3bg1gXP9uDWAa7240IFz7bjYjcvdONGEvaU4UIZ9Zbg+gO8PyN4ewVfduL4Fl7fg/gR+Oqz9xzmX3855/Xbe//fLgT+ddXk4azzVhtFNOHXO7fGzwr5Ntn4usLeGuS3svOAXQU7NIXhl4AuRUwBuMhEVK5WcR8srZ1c0KpXXs/N44MYhzB+BHgh0R4AbAt0R6o2YYKTFIicZeRlIz0N8EgKD4OAAPUOoaIGlDaoe2JqQ04SCFpboQt0AeuawdcWaAFpEFOITqQmp1NgkRCUjPoOWkMmMSqV7hsE7SlbPjcU2plDNaDCnQYtC1pWGkfRSO5pDCDUiXSKHr1bVZFPb4SJotihqXp5buzS9XCG+UGpthoxvrKSzP83Gk5A1A6EBpjqhaiS1yoFwCyZHpEsk5siExC+NTEVBFTZsXtGwwdTDD54BiEyXzy/Vy+SrcgvkY7LZ4anUlHxKa6/a7Gn77k22mlZU6AEGsLLWdHCQU7EE9BUZWhKEriRZm0bRIxTMaEstoW8Hew69rNSor8+vstIoOU0iJ09pXb6KsNyQX6LHL19cJDAsLDfkipStUxjy9ixVI8LcGpkhqIrAcNay2hSNVbYgLLDMlmrjLOPkSwSGUJLjwE9FVQaas9GWh64C9BWhv+Bv5WMwH1vyMJSPvjz05/8vEI4VYapoAcIj1TjbiMsb/oHwv1D8Lw6fjOD+FtwZWAhNuduN+9141Isf+/HrFN7O4M9T+HRx5edrHl9uR4i/5n55kiF+li/+QSD+qfLTw9zPj3M/Pky/usd8gwAJnvA3gbcB/M0Q5YQ4d2QEIS8AwmiZilg5UTytIxdT1TjehRsT+PYwfj6Bd6fxx0n8fhy/HcWbQ3g5g5/24Yc9eLELj7fj3iRujuBqP85vwsleHO3A/mZsrwO4voj1g78bHO1gZQcrR7gGITpL+tzRNEGlpZYLTDjSds5ICEJNKo72rT7Xy4n3JJuYkbRM4OqKnBhs4qEvFxsy0JaJTbnYUoTxUuyuw7EenB/G5Tbc7MH1zbjci0ub8VUv5lqwR4jt+dgrwLU+PN0hf7kXpzbg8mZc34Kbk/ju0LJfTlv/fMLxl9Nrfj3PeTBjcWwTub8aIz04f9b5+bOcfRMOgmTkxCAuFPFRSOeiJB91IlSVIScL8TGIiqTlFKCklFQpYlYKSIJsFCahJBHlqdiYjfYcdBVgUwkGRdhai5F6jNSjrRbN5RBkIyEErrZYpQc1LSzVokrrgKEJaQ0oaEFVHyvNYO4IVw5lbRTiU4i0XGZqDpGUSyTnMuMymWuTKI7BsA+UXGSIxaYMJROmiok0RYWkZqDCNGZqOBPeMRLpRUtKa1a1dntsGPCt6XIqadHJqV7C5bMis+khKSxOFMvRlzB3hoIJmaZJktKkapgwzVxJnChSQo5kcoF0UKxyRAryK9Hau1JUr+PmA/cArE1l5RbrpRUui89jR2dJh6UgMR/rexftP2XZPWChbcuALknREsHhy7lcBVsOJPVUGJqEjC5DRp9QNiXpOxJW7vDwR2Qcs67eemp79OR0RGHJMn7pcl7J8soak5JSvdwKUlbRcm6u5ppU6aXeoOgRmvoULxeURKAlARPFBpkBEppGgBlZwUbS2EXWzJNw9aeERyAjASVJqElHSzbac7G5AJvz0V+AwXkCcxc0XwkHc7El728Ic7E1HyMFmCzEdj72C3G0BueacKUN1zsXlqwtRIN148Ym3OrDnYGF3L6bvQuBatfacacDD7vxzQD+M4W3B/HhND5f1P98zeOv26Hie1Hv7yX99Shb/KJQ/G3xu3up7x6kv74df2xMszgVIbZYowcvPQSYItIRUa5I8UN6AIqiKCXRTFE8syufuqMeZ/pxZxf+cxRvTuH9Wfx5Cu+O44+jC8Xw1xm8msHPB/DTAfywH9/sxdOdeLwdt6ZwdQwXBnGqFwjzQYA3nB1gZoVVdrB0h08csipUL5/OzS3W03GEOUfSyQMpoWjKopwac78+GLjWCTqmdEkDYqkR1rhAwMX6dDRw0ZaOTdmUwQKMl2BaiKOtuDWF61243Yd7Y7g3jksDONqMMR66UzCWhR3FONuBm4PEmTbMNePyJtwawv1deDRDezGr+eKwyQ/HVj8/ZHt+UGlMhOkW7BnApVO23z6IPb979aAQ3aVoLUZdHmpzsb4EPdXYIERJxkImWUUxqkrRIMB6PjYUoqcYI1XY1YwDDZhpxGwLjrXjxCac2Iy5Xhzvxc5O7OrCVAs6BCiKQ6g77Iygp05m60FSCxIrIKNLUtGHujFW2cLRA6FRSEyn5fBks4pZmXxWapFsbAYjOA42gRJatiRlA6ib0pfpwdJZyt5V2dSavdiUMHRBIJeVJ9SsbrHc2O/TNuhX3ekoaFmVVaEancsMSSECuSxOFNvBh2biACUTuow2sUiXqWVBs/ZAQAIS82hJuYRvFCsiBQVVaB/QL6te6eEHr2CsTaNnFGmnFiyNy5Vfm8EM5CI2G009ivtPWQ5sd1xhSVY0Jaz9yPFJcjk5CIyEmpa8jDZ5qRFN04KyyoHs6AOfYETGIDOLWVFrNLotbP+h1LpmM0H5CoFQq6xCRyjSTREiOlPRN3aJSYAEwwp0DZqxMTXGF9VR6EyjDpet8rGFgg5gypSxkVrpLGfkxbLxY3qH02NjkZ2I0lTUpqMpC9256MnD5vz/BmE2tmRjc+4/98Z/IMzDcC4mCrCdjwPlOFaLr9bjWjtudi8sWbvetRANNp+aNn9FvLUZV3twsRPnW3G+GVdbcKcdz/rwwyTezOLDGdJfl4zF1zzFt0LEd8P+vM0VP8wQP8sWP8n87WbM23uJ314Jn+xkcwPhrA9bdTiqw10PgdYIdkCCFxIDkBsBfiStIoa+KZ+6Zz0ujOLRDF6dwO9n8eE8PpzG+zm8O463x/DbYfx+GH8cwm+H8Nth/HoYrw7h5UF8fwBP9+LRTtydwq0xwIsDVzeY2UDfEiaOFHs/Ulgms6RF5+rZ/NQcNV0XWPsyvXyQGYn1Bazz2zg3h8ICrKBlQiObyTP1KbrGCPeFIB2NiWiIR00kGiPRm45txZitw8VuXO/HlT5cHcKNMZzupmwTSHYlkZpjMJSBqcKFgc5j9TjRiEtduLkFd7bj7nZ8vYf+eJ/6vWmNc73MvfWYKsexHswO4uKM5vfXve/s19/XiH1N2NWKHc2YqMVkPXaux1gD2otRn4eGInRWobscPUIMVWC6Foc24KvNuDaMS4O4vAWXhnF1DFencH07rk7jyjZcGMPlSXw1hkM92FqD2jQkeMDdAEt0IacJ2RWQN6AsMiQtN8Qqazh5kkMiEZ9ByxHI5pcr5Qjl0njy4SnMNeHQdJFeZs1aYSmjqg8bN8SkqBQIjOITlVfZUqw9EZ5ILRBp1rXZbOzza+33EbXZ8hqNUgRLw9LoAVxyQAKLEyVrz6GvsoOSEVVWl1hqRJu/EIanIqVQMj4LftHMmAwUN1A2j1qWiDS8A+EbjrVplNR8zYTcJTG58mszZAITEZ+Dpt6lM2fthmbc1Y1g5sxam6ywNhYJqYhPgZGBxHITspEt3cqV6u5LDo2kRMSCm4zcIqKi0XDr9rC9R1K3TgaX1+iXiVbmFi0SlmtEFGBNlLSFh9wyR4JsQiiukHK2oGUFoTUGmwuUW4t0zIwhowuKuZy8rZyWq/wqjoJ5ANs9TDI4lp7ARXYiSpJQloz16diQifYcbJqve7kYzMFgFnqz0ZuNgRwM5CzUxuFcDOdiSzbG8jDNw4FyHK/DxVbc6MLtTbg7gFubcb1rYdzpWufC9tHbg7i2CRc7cKYVc/U4Xo1zdbjWgq/78c0kfp3FuzPshf2iNwPEdwI+3EkQP0oRP0n6dC/65ytBr+7EPDgf0lUDX0cYL4WhPFYpwFIFbnrgmCPcCbHeyAxGUSgqozBQgNkNuDaBZ4fw+jT+PI+/vsLn0/jzON4fw7vj+O0oPh7Du6N4fwzvj+P9HH6fw5vj+PUIfp7FTzN4sQdPdwL2LrByhJ4VDGxh7kV1D5fg8lXre+0vnS/iZi0x5ZDtAyX9/JATgza+3LlpzrlNQR4mWGkKCaAAKAAAIABJREFUWTN5BUMZVT3YOyE7R6KdT9lSpbS1UqUtEzVRaEvEZAn21eBcP65N4eZOnNyEviyU+aAiABuTJLekY7IIu4XYK8JsFU404mI7bvTh0gCuDeP+NtzfxjjbiV1C7BJibj0u9ODMIC7vofx4wfq7g5qXenBhE8714/wgzvTgVBfO9OBYB/Y2YaIek03YsQE71mNnEw624mwPro/g6wk83IYne/BkDx7tw6MZPDmEJ0fw9CieHMWTg6wnB6lf78O1bTgziO3NaMpEjj+MjaGuhUUaUNLHfEzfKju4eDH8IxCfwVhXqpwnUs4uk+cWyAfGM5z8oOIgr2zOXmxAmNjRCsosuVmsrELZTQNr/IOUfEPIUcnIL1tW1WLZ0uPd0O1e0miaVa4Tl6ccwCX7xBB+cVKcCHk7L4aRLeT0SYv0KRpmdBNneISCm8vILpHnZjH9omkxWShppPaP2+QWK68JgE8YgpMRl7UsKkNhbYZMeIZcaKp0fJ5MQ7fWzqP2m3d76FnBN4SVlLvIOxAh0UjNhYcr1dyZ7MSR8Amih0UR8YmkhGQkZyK/VLa4Uad/yndqJn7P4ZTmNhthpU5eAZtfstg9FiZukipmdIYZaMaEhp50gD1VEI6eJMpwuU42V0nNAGxDCRkLZRU7xeUe0kY+sib+cg6hMl7RrJA4amw80mKRGY3yeFQnoTENbVnozkZvDvqy0JeJnkz0ZKIvC/3ZGMjCYA6GcjCUg4FMjOZimoeZCszV49IG3OzGnd6Ftb/XOnF5Iy614fJGXOvEjW5c78XFTpxuweE6zJRjfymOVeCrBtzZjMcT+HEGb0/Jfrxg+vmym/g6R3yL8/FulPhB7Jc7oW8ve/5w1u3lrdgbJ4KFRbDXhzoLy2lQo5I0aDBbBEdN+JgixB4p3igMQmMcJktxuhP3pvHdIfxxlvHxwt8QzuH9cbw7jj/m2TuGP+fw4SQ+nMHHc/hwFn+cwZtjeHUIP+7Ht7sBc2uY2JKM7WHpTrYPpvonsHOrjHunQs+fyY9NU7INpDkG0Pz9kB+LDoHyme0+sxs4HiYwMMFiA0LViK1hACMHJPAWd7Urzh3iPLiZeWiba1U2REno4WETn7R/A3F+XOncmMIAD+kOWKuHbBdUx2JLNrYLsbcK+0Q4XINTzbjQjpubcXETrvbj1hZc68PJZsxU4FgdrnTj5mbcHsetXfj22OL/HFR8OoGnU7gzibuTuDuGu6O4PYQbg7jSh7ObMNeD030404fz/bg6jHtTeLIDz3fjxW58tw/f7cd3M/hhFj8dp708sfynk3r/OWHyy3mLX86b/nRS8/mswoP9Cpen2Lvb0MVHmBdsTaGhiWV6UDOjaVpQTOwIe0+6fxji0mSyBYvWlSulCeRjstmcCAkrd8jbSzP1KfLa8I/ULa1ydvOHgxdaenyL+ZZp6cqJGeRMPptXpVvZbFfaaJlZqhGfpxaWIseJJntHUXyipbzC2Ks9qAbWWGSIZaaEnh3N2pvsG4N0PjuvdEliupRvDBGTheIGSt+YdWaeHCcIwXGIykZkupJ/AuEVBz8uKyhJISqDXVCltGGzeuuIk1cQkjJkYlOZTt4KnHC51AJyTDzJM4AS9H+4uquwKPutDeA3wzAMXYodgEgjpYh0KiEd0t1gABbYgYGKgEjXS0pIDykIFiapIN2pYIHN8x047vfb+7rWEcf8Zj3/Wrcd1daJydkNXn5kzwAm3xCe4IvCBy+uj8nenVNuV9ngl5RueOKMUOiJDf6BkDVg3CTHwSZMgTSo8iQJeU4nHfIVF2QErvwnfIe+PrhFQZVk55DhXa/EIaTLvM2AQ86YQ8mSR9uBy8iZw8qJ0d4ejjY4YIUQO5xyRbg3bvjhpj9i/XDLF7G+iPVFvB8S/ZHsj5QApAYgLRDJfsjcT0d4/wpeRKEzDt3J6ExEWxxeRuNZJJ5ex9PrdIqPo9F0HTXhKDuFgiMoDAEtDM0X8Soe3VkYL8P8PbbFh9I/n6j/eqGz3Kb9tcvsx+u9X56qTzbIDN1TnG6ze1pncdAbkpuwkhGrGBhXgHEFsJUKWT6oC8BIGm5aOGGFBF/UXUVXJoZL8a4OX59wLj8jE0/xsxlfG+i1eA9fG/G1Ad/u4/sD/HzM/KNl9Y+W1d9a+P8gnCzHaDEgJUuSU6Io6JDVTSl77FltvPnCrijlV/g0NwbaunMpm1FU9pKMDBHsjNsn1z2+a1YcsXvPDmxTwBohCIlTRWTJomqwOb459AZKm/cMzYQ2PbA9f5LlSABOBMLdHKcccS0QFzzhowUXBYSZ8N30YY4MRFYQKi6S6iNQE477V/H4Ol5GozMJ7SlojcfTaDy8jseReBWD9li0x6I7CQOFeF2EvmKMF2GqELPl6CvEwF2MlGCsGKMFGMlHfz7eZONVGloz0JGD1wXoL8FQBcYrMUnDLA1f6/CtHt/uU38+2vjrmRzxUnP5pdHv52afWvWX2vcsvtJceCI32yw6XLf+SS6KI3HUld9ME5Ji2CwB4e0sIkrM0qrkXdoUYys4+fAFHF974MRqz6O8dr58elZUeU1ABmQpCClz7/PYqW/BL6cEUXmY2ArFR5mFhYn7BjJ5HqL4H10XckoqIGyrYyD3Ph9+Exeqng322DIa2nPrWfIo6TKLK2KTPMOWnRRZHTZ1E5KZGwKO8x0M3eDiwWXmQnY9iLAI1rQ7KvtDVlk5Mrvv5w84tcbGi1fPFqpm0LUhGTrxmjmzOvrB7zguJal4BmwICeWxdoC6npCRrZhLEJPPIZjbMTm4srq4M3h4wieA2esQu3/YhuPX5Y9cFUooMMyvc69s8Mu7a3v85OYz5wUcnCGsxrpSnJcsSIUUWBUgq8jlbch82wdZQRsyryhLbgdJEGQxNjZRzjXbqUJakDfgkDfh2mHFo+G4Yo/rShMXVgsHWNrAwwT+FjjsgDPuuOqN63647otIb9zywS0fxPki3g9Jfkj2R2oAUgOQ5It/ApB/GLTTaLqKl9Hoikd3Mtri8CoWL6LooWBPItByDU9voPEa6i6h/AwKjyPnEPIOouIYms7jWRw6MzBUgrlayqcm8W8PVX4/1fr1SnOxbffXNu25pm0DtI29VdITr+wfVZv7uEKYHxwAN5g4QGEFNjBAhIrt/NAXgYcG6aIdso/geRxG7+JdFT43/ovwVzO+1+N7PR3h0n18bcJSE749wLfHa348Fvz2RODr482fGugIR+4CcupQ0WPQNeXWt2I3tIfjQcrFWJW8Ks+yCgcHr5W7TKiqe2FjCV87JIdvel7hXBSuqCsJCUnSKils3Q5ZBSYVTXgcxNkLKKuVHp4819px/OgpXDgLDwtWPVnoCfAorYLyWjhpINwbUcGIO4Y7l1EYibfVWj/bjk3QzO5HoTkKHWnoSkZrCtpS0ZmC9iT6BvTrRPSkoDcD/VkYy8NkIWb+DoqdL6PPwHtXgXeVmK7AeClGizFYhPG7GCnCUCmGKzFSjuFSzJTjcxU+N2CxmfXrE4FvLxS+tWr+bttNtBsRnSZEpxXRY0t0Oy51WH96Zf6hxWCUJt+ZvbrwIg6YQkMaW0VJm2VJAjshogh1fW59Wzj6sgWGrt4ftsrlELeRM992A95Nypy8wiQhRWZpPV5JHd4Nilz8sqzrFFkFtFj3OuLkZfmTlyQ8/OEWyOAWzGfty2Piu8rAkUfPlnmPDbOhPbuhLZ/GXk5FDarMToqcOru8BknTEGZ28PBH0Kl1B06ss/Mimdtzeh7B8WsM0enqnocobr6IjllxN0/L05OirMO5YTtV2ojB2pdfz5zJ2Jmy7zDiojdF35Y/cEpyx14GOUOSnhX1yImtwUe47Lzh6EX18Fnt5bfCK5DZK4jR/+S6o5dlT11RSMzVLqM5VdKCa2oPXI8VPniSbGxLWi3NslqCwiVCYhVh4JOEmhqCbJDoi/zLYqH7BXnEAHESxEgcCkwCaiyC6qyyeqSdxrzKlmtVbHl1nKnGbkwmdoz6hjDSg6U+vMxwwAJnXRARgIteuBGC256I98ZtDyQHMCT4It4H6UGI9kBSAFICkH0Q5UfReB7Pb+DlbbQmoPs2Om6hNZLUchUPr6D5Cpoi0HQdtHOoOIG7R1AYhJJgVIfh4QU8u0bpSMLbdAznY6oCc7X40Mjy8ZHExxblL480vzxRHqle0V1Jbi1fM9hi3Fpv7+sAAXZGdoAbWAnGNWBcA2wAFHlJehsRoIkkf9y7itcpmCrGl3r8eAjiCYiH+NWE7430NeFiHb7UYrEOS/X41oDv9/GzCb8e4vdD/H6IhTrM0TBZhrEiQEUfWsZMuqbceyyp5q4k37DVV+I1UorsCu9a73Pj2mVCVTeBnQ0CnZB6WfB5hXP2mW1qohASJ/GJY7M8ZORYVTVIrvtJZy6gqFpmcPx0x5ujZy7hwhkmNxMuTXEo8UFjPUxlEGKO6GAkhuGfc6iIRm0iemnbvjxxnKhSf5GK9nQMFKAvB6+z8CYb3Vl4k47XyXidQh+G15uBgey/CO/SR6b/yQ/5WIkPNHyswkIVZmmYKcd0GWZKMF6KsTKMVmCkHOOlmKnEpxp8aaIuPVr/9ZnUz1a1n227f3WYEJ2WRJcV0eNA9LsTA54/e1y/v3Fc6rB+16zRXyreGIdwL1hoQFYagjIQ2A4hBShpUQ2tYOdF8TnC53uU2yGAc7cdu7Q2B788ZbUEZasSq6QO91Z1dn5ZZk5x8gpZ8loVkpwubLz5vIPXuPhRXP2p9t7MBo7QtYOeFauWGUnDlEHXkqJrwa6+l1VRmyqnSpXXZFfUJu02hbUrfA5Sgk+v2R+21toLfxCGXmeMTlcJPM559BSy80TqKvfuc6VKKVF4pchb9WDlvVrfit3Uld0qGKmp0lG35b2OCckZQlKfpGHBeOCYQNAxbkc/OPuwefis9vZf6XOQ1fcwNfD0xqOXZc9dV07NN6ht8n/0KPzR41Npd9QOnGDWNQaPJBOXBJlDjIlNlLRBBnraCHVAWiAKImQC3fhXSQGijBAjU2XJG3Yyb1ShyPxFqGrHp+vCauzGZGzDpGsANQ3oasHaEK5GOOyAS3646Ifo40g6hNt+uO6KGC/EeiLaDYl+iHRBrCfivJDuh5IQ3DuLFzfRnoiuVHQnoysBbbfw7AYeXMX9S2gIx72L9AEOf15dNF1GSxR9jltPGvqyMVqIqXLMVWG+AR8ebP38eNeXh7pfnqiO1m7upXF30ARHnlm23XPY7wghVgYuYAWwGqQ1wDpgPbCDG/ukEWqC3GNouYX+XLyrxNcG/HoI4iF+N+NH47/8/gzw/1iFz1VYrMFiPb7ew7f7+NaI7/fxvhozlZgoxmgBsMeSqmfOpmvKYWDD7BjIffSyWESi1q1M86wcU0tHDiVjVi0zkpMjgtyQEbHlRaVjQqjYji3YLMrAKoJ1cpCW51LWYHYJZDl5nu0ObVvv6NHXfUcjonEmlOysx6O2Bcp8sJFFiBki/fHPGeSFo+QaGhPwKB0d+RitkBgs4X+dg94CjJdi6A76CtFXiL48vM1BbybeZqA/C4M56M/GYC5G8jFZiKlizJVhgYaP1fT4ni/VWKzBp2p8rMIHGj5UYq4M02WYLMdkOUb/Ivxci28PBb+3bPvZqvaz0+j3G+vlN3ZEtxPR40wMeBIjfsTY/t/DfsuDfst97osvzWcaNDoKOTNO44ANNBQhLg3R7RCVh6IG1cgadu6M3kG8XiF8+7y5tSxYBVWYOMVJG2XZtuxkF1Zj3qBI4ZIgUYVJnJJYuYMkqQNlM5KRI4uZC9nCGeb2MLaFiR2DriVV3YSkuhcapoxaplRVQ2ZFbSY5dUYFLVal3eS9NnD2JfsdYQ0+vcbvGK+5OywdeXyO4+RNcmTqjqDTHBExTJU1Cg8bjU2deVfLkklilE1asPBcbWa70tyF2/wg/snbdSlaxtqXX1wPYvqkneYkr6Prj5xc7XaQ6urH5eGzwieQLyCEY38o18Fzgkcvy16J2ZNRZHb/UXDry6inzy6U1e7bH8qjrA2qOMOf94ec4iRxBdjo47IHco+Rcq/IWRhipQwgTIIYhUOKaZ0iy2YVNhk9kpIJ9y6rVap2fHqu7CbubIa2LJr6jOI7sW0n1NVhoAl3S5z0wbn9uHUO/5xligvBeSdEuCLSHRFOiPLAdRfcdMYtN6T6oDgYDefxKhqv0/A2B305eJuFrhS0xuHJTTRfwb0LqDuHe+FouoqWaLQn4k0m+vIxVIThYgzlYiQfE0WYLsUsDe9r8alJ+MujHV+fGC4+05u6JzVcJ9Rds23yhV3nfZcgVwiyYQWwkRFbGElbSRBlhAQFuzfhoA5uuqPqCjqzMFGOj3X40YTlh1h+gB+NWKrHl2p6gs18Gd7/HSX+oYLeJz5W41MNPtVgphJTpfTERRjYcWqaUDSMmUxdub3DNoRFSl9J0orOMk9LNzKzo+7cS9UwZXB2wmFPZN0QfUlzjgwRkhHEBjFGsgjWyUBanldFk93Jjxp6li+nXOLN8MHe4WOxCeTjgXBUY9UXgY00wiwQH8SccwZlV1EVifoYtCThVTpeJuN1Bvry0HsHI8WYLsNYIYZLMViMgQL05tFvx/dnYSAbg3+TlieKMVOKd5X4WI3FeixWYbGKnuDzhYYPFVgox3wZ3pdhrgTTxZgswUQxJooxS8One/jeovDjhfqvDiOix2G534Po9yUG/YmhgOWRAGIiiJg88ns8mBg7SAz5fOu0/9BiMELjp0Xhkj/MNLFdFvLbsW0ng7IO559RF16HuL0O8Vp5cCkZUzYokpnFSEIKfII7WNZtJ/HLMrCJkpi3kLgkSKsUSZJ67NsMWTQsuQzsWI2sYWILa3sGCxsYWHPomJLVTUhaplQtUzYVA4qsJqTVsE2LaacBydiB4h7I7neENfAEn1sIh4kLrJx4A0/iXCzX1QSpwFDcTGSpvif/sFHf1GcTtwwTxKkbNWHqtsLCfpWZM69ZANLv7Dp+SVDdGsLaDFv1qbssGD2OrDt+cZNnMKerH5eHD4/vfp4Dx9gPneIOurDl6GWFiHjjtELz6nsBTx5daWgIrW12P3BinYI6GCQYIEmGOIVDAoqK8DVFbCBz4dnV6Rdk1XaATxIQIEGMlVOaslmFU0x7haQ+o4Ipt7rVai07Hj1XqpE7h641m5IuM58CebU8SUyRQX4HzAyx3xMngxB3BQXRqxLP4qQLzjojwoN80QERzrjqhOsOiHFFhj8qjqP5Cjri0JONgQKMFGOoCP0F6MlBRypexOLJDfpL8dYEdGdhqAgTFZikYZqGKRqmSjFTitlSzJVhnoaP9Vh6IPrtqfKPlzY/W83ePdw13Sw/eH/XbJvT2wceod4Q5cEGJkiwQYaTQZEHWqthJARfNdIlW2QdxpN4DBbjXQ0WG/HzAZYf4mcTvjVgsQYfaVgox/tSzN3FTCFmCjFbhLm7/2/dVIF3FZgq/Zu1mAPstmZTMYCGKaNj4Lqgi8KhN8QvJ2omFNglp+ib2LLu3EtVN4GzE456IzdarLXKKdx3jeQmbBAhMwhhtQRkZTnV1RjtPXH8JGdWyebOPo/h4cPpKasOu8Bdjey6E2eskBqMskvkygg0RuFRHJ4loDUZrzPQkYiedPp4gskyvKvCbAUmaBgtx9Bd9OWjLwd92ejPRn8WhgvooeSTJZgqx3saPtbg8z18rqL3/U8V+FCC+bt4V4C5fLwrwkw+Ju9g4g4m8jFVhHc0fGnA96cav14ZLb+xIwa9iZEDxFgIMXGEmDxKTBwmpo4S06HE1HFiIogY9v3Z7bD40nS6dvXjFKSehLcJ9BShooQdyiQVfS4bBzh7Unz383gErDR14pDfTV6lwMgoThJXXiu0nZVfFrwSYBVhYNlC5pIgrdxBXqNIEtFiVbXg13NYYWDHau7IbG1PNjKGsQ2LrhlZ24RR24xDy5RLSZ+yTR1bVSCrQ91lRDZ1YnEL5PQMZvE+zOO0n2OvCywdefafwpWUVRdubXEPwrXbqKiRaG7UswrcwiHFQJVm2aIJE0dmK7uVZs685oFIy1MOOr1JTh9CWkwiu7mULaiuwatCL23wDOZ19eNy82HzOch68DhL8BmukPAtx65svxxrnHzHpKDStaY2tJQWSGvyOHZBQlYZbJKAFBViVG5x6Coj1BYpR7nzwwWTL8jt3A5ucWAzE1mMjU+aWViVR2r3GmmDPwhXatpz6rtQDVw51cy5JTVZqfKsrDLM/PIUQVlo6MDZFSFBiL6OkmzRtOg1Jzxx2B7nXMmnrHHGGuescdUW0S7IOojq02i5iTcp6LuD4WLM0DhmaJTpKkxWYrQU/XfQnYHOFPRkYiAPY8WYpWG+Bh/q8L4e7+owX4V3VVioog/X/NJE/d6y7dcrzeUuJ6LbYemV/qfnupMPtd91uAy1eIYfosiugzA75Hixix96G7FPCj6quGBHSfRFxTm0p2OyAh/rsdSEnw/wqxnfG7FUj89VWCjH+xLM3cVsAabvYCoX03cwk4/pQswUYbqYHug9VoiRfAxkYyATUDMhKRlijy2n+1HBkKsixyJFLyWrJ911jovTNbKiKBqxqJvAxRmhfsiPlWyrdTrpwie+ChuESAybsFYM22WZtdTg7IbQE/ingO1Vh+Vw36HCdMEjtjhigPM2+OcIqq7gfhTuR+F5IjrT6Hf8elPRnYz+P2G9JZihYaGO5X0N81wdpqowWoqBQgzewUAeBrLRn4X+fDrC8VJMlmGmEgtV+FiDj39CJMvxrhRzhZi+g+kcTGVjJheTWRjPwEQmJnIwXYh5Gr4248cL/eUOS6LXnRjbT0wdJWbCiNkTxOwJYuY4MRtKzJ4gZkOJyRBi2JfocfjdbvHx/pbuO6DdwDk32GtCTxmKylAzYrFxhJMH2dOf29GLW8eCaasaOGVJZBmqnJbwlh3sfNLglQCHGBPLFjKHGAOPPMO67SRRTXb5vTxKZhy61mymThz2LuxOLqwmdgz65tAyZtA0YVU3YlfUYxZXw1YlyOpxKhqxGDlwOPpyOfqRnf1Z7f24TV1ZLRzYA07hWvr6c9FbnPwREYvyaumWB6Y2B9fxSmGjEpu8ASwdYefAZ+7CZxHEmF2gefj0FjltiGqyi+pwKluwOwZyh11Y5xnM6+bP7e7L4XuIGhRGPXyO9+jlrSeu7zobpZdQYJxbaltZFVJK8y9rcAq/rb5NBSukSJBkgTjbaimYa+GSG1LD+JIuCqRFKOnvBpcYIERmFaOukCILqlAldvNKGpF3mHGqWfHq2HHqu1D1nDnlTdgFlFkpclSyDJVXhp1PkkFGA5aO8D+EK9dQXqaYky513A++5jhsixBzHDNDqDmu2iPWA3mHUX8BL2LxNgNDRRgvx7s6wfl7wh/vC39pEv7YsPpdDSbKMVKCkSKMl2CmEu9r8OkeFhs5Fps2LjUJfWjEpwZ8vocvDVi8j6+PN/94obTcvnv5jTPR5/L7tdn3DuOZJ9oLnc7jr7xvnuRUEYHsKuxaA411MBWFjyrCjBHrg4KjaLqOnhxMV+JDHRYb8b0JX5vw9R6+1OJDJb0HzhZgOg9TuZjIxmQOpnIxkYfJfEwU0OtP3nB/FvozgJ0G0LZkt/Le6BUmdOiK4IkYqatp2rF5tpGRanvMyDsMmbXMSO5uOHUQRfFSbbVOoTa8YnzYJEhm3YTN4lDdzrRXBz5eOHUaGTl48khzpDOwOkvmrD1u2OPOUVRfweNYPE/A83h0paMvE30p6EtBdxK6UzGUj8lyTFbiXR0+Nq9438C60IiZGoyXY7AIg3cwkEtH+DYXfXfoDsdKMFGKqXLMVGK6AtNlmCzGZAEm8jD2Z+hyBibSMZaMiSRMpWA6EzOF+FSL709W/W43J97YE0M+xGQwMRtGzJ0k5k4uvztBzBwhZo4TM8eJmSPExCFiyJPotiU6zb49lhwpw9NkJB/GQTOYakBFBRqmjPvs4exG9vDhsXXlVjUkbVQApzSJQ4FXTktYUIGdSwLc4uCSYOYUZeYUJ3PLQVyFIq3NIaJFltQnaVhz7LFhtnJhDT4maufOaGLHsNsUmkbMuwzYZLRZxNUYhZUZZHR5FHZT9axYTZ0pZo4wdYaFB7eJK5+1K6f/SVxLX382SsjRD9djWcpo8s8f2XocXim8Hbv2rjS0Z3B2h7Mzt4Urj2kwU0mx4elzkgpakNTgEtHg0DLjdvPnPnVxjUcQt0cAr3cAZ0AIS8gpytELvGHXJM5Ga52L1ssot8wusyms8C+u8rtTbZGYb6moxbZWgoFBgh0S3JvlGTwMEeOHhBPsl0+uSY9RdXVbyyEGiJBZxZhWSDFsViEJ72aV2sv0B6G2LetuZ4qOI5uUIcdKBQpFhsQkSWGV4uAQYxJRpRjaMnkG4kIEc3GVWl6BcnAg7PThb4pgC4TZ4KwDEv3xTwjKzqD5Gl7Foy8bo6WYpmGukXuhWfjrI8Ufj9V+PFJavC88X4eZasyWYa4cczTM1+DjPSzex9IDvm8PN315wLf4iGvpIcvSQ5alR+uXnkouvVL+3r77Z6ctMeBEvLX6+cZ45onWfKftXKdnyuUVurLYJQAtQewVgcsOhBnjqhMyDqPuIl7exkgB3lfiUw0+38OX+1i8jy+1+ETDfBld4MwdTOViMgdjmRjPwngWxnIw9p95/rkYysNADn3HETt2w9h5jWuwhGeo4P7wjWcSZK5n6l1PM718WVFnL3YYMutYMPl44VwIihNl2uscQy15JHixZQuFRwBiUtBToVgb4lAALp5Daiaa67YPvfRrzlW65oI0XzREoDkGr5LRnorONAzmYCgTfYnoS8TbVPRmYqwUU9WYrcOnR+TFZ+vfNzN+aGSZqcFYKQYKMZCH/hz0ZaIvHW8y8TaH3g9HijBWRB84OVSCkSIM52MoF8OZGEzHcBqG0jCWgpFEjMVjMgnT/+B9ERbruZafbSVmElFnAAAgAElEQVS6rIleJ2LUn5g5vPzuxO93J3/Nnfg1F0ZMBBOTwcRUCDEZQowFEv0uxBsbotPkd4vcVCU6slF4HicdYaMDdXXoWjLaOsDFncnLm8fGmWOnHtbKgluGiV95jbTa5vXSFFYRcImBV4qFV4KdV4rCp0DeIg9RFZKwKmT3Mu92Xq1uDh1z7D8q7HWI286d2dCSSdOIeaceu7QGq4gqZasKk7Qm9zYtJvW9ZD1L6JlBzwp7ndgMnXgdvFb6n0RE2tozN4Ud/XDj9sqS8u1Pmx2CT/DJa8DUaZOzD5uPP9zd+Mxd2I2DUVmy98KFbTs0sU2dV1SFQ9eCz3f/yotXNnse4vUM5PPdz3PgKOfh04zHLvKdvCF98bbelXijO3UOmWUWOcXuhZUeGaWGeVVuGob8m8TAJM4OSR5xRXKgORIPIjaM8eQRnoxbygeCxFhFQBKjcIgxrpWGgCqDqAHLX4Rcerasek5M2g4cEvocrHIUTklQxUkcEmzMIhQBZVZdazZnf5y9wlZE08i7q3kgAGZa8DLGcVuEu+GGLwpPM5ZeQH0EnsSgNQl9ORgtxXQ1Zpqx8JB/6cnO3y0Gy48Nvjbv/Fi/7l0NFirwvhLzNLyvxkI9PjXiYxM+NWHp8ZavTwS+twh8bxH41iKy+FTmy0uNxbbdX1stiT57otfiR7fJ9GPN+c59893eWTfXGCtCUwSG4rCRxQEdXHVCvB8KT+HhDbxOxkQR5ivxqRqf7+FzIz7exycaFirwrgQzhZjJpwscz8ZoBkYzMJaJkSyMZGE4C8NZGMrEYC76s/8i1DKFpSevfcgG11Mb/S+JRuTsOX9bJfWuzbFTompGJDkjPhUT+B/E6WDcv6PVWeNtr0NR2IztQtBXhqEqHAxxwhOXAhAVjuRItFTv6H6kXxnPm3YCtCt4chvtiehIxtsMDOZiMAdvU/EmCW+T0JuCiXzMVmCuCh/u4esT4e9PJT88XLt4Dx+qMVOOsSIM5aE/G2//JBOkoScdvVnoz/l30N3oXYzk0/NA+tPRm4K+JPQloT8ZfQkYScBUImbTsJCPz1X48UiaeGlNdDsRA97EZDDx/iQxf4p4F0bMhBCTB4lpb2LCa3nUfXnUnRhzI4YdiLcmROfun23ic/UYyMeLWPxziNXPkLR3Nwwd4OPKbucMS1/scoCoAQufNBPjJijq82/dQd0gReIVBvNmrJbn+jNJnms7i5Ay92p5kqgaRcGQTdWMU9mURdGIvNt6ld+JtSGnpPTNmXaqQdWAQ1SFtEqBUVCdT05rtZgGSdmCXUyXUUyVU1ZzlZGDgIE9o4vvioPnSJEZwieuCnseIl28iSKaSPNj/RPhXKaWcPMR8j7M4R6EY+E79tgyuoTwldcbhF0RElSBuA5lkzJJz4bPN2j9xcuip0I2Bvpxefuzeh9e6XtiY9g1pfDbBmER6uFxurnV/v9UuCcUmsUXGcYVGuRUeToGCEGcBBFGXjlWJR1GZwtEha5KvCDhboJTpymxsbrS8mATp0CSBGUyuyJkNUkKhpw7jKmqFkw6Dqy7XfiUbPjWa1NJsgwkMQpZih3CTBAjsStily2ziStCL/MWVmtfjtzs5gxbIxywQcRBpJ1C1nk0XMf9KDyJxctEdKVjIBfjRZgtxftqfGrA0mPer8+kFp9t+/BA6H09+1w1FqroJ8YzNMzQMFmF2QZ8eoyl51I/Xip8f6Gw9FTm25NtP59LL78UX34p9uOF0nKb5u9W9aVnctNNmz+3ayx1Oz7NVzviCmcdWMvBRx0XrcnxfrgTipo/qabpGCv6uzFRjc81+FyFhTK8L8FMIabyMJGNiWxMZGEiC0Np/9ZwOkYyMJqJsSwMZ2Iog/53GNiQbX1XOR/d6HlO6ECE1JWsPeHx6ukldoeOCKoYMMrv5vqD8NwRNBXpdtR4uxlQtSWxWwFOe0luxjhgi0sHcfMwkq8h4yaaSkXaa5WqEil3L6H5Fl4moisVXal4m4GBHPRnoScFb5LQm4iBdEwVYo6G9zX41Ej60SL687n05ydCi434WIvZCozfpevqTUPP3xzWP3Ef/6E4dAdDuRjIRl8m+lLpCPuT0Z+EgSSMJmIqGe8z8eEulurxq2U70WpDRzhxkJgLXX4XSsweIaYOEhP7iSkvYtydjnDUlRja9wch0S7zqQmTZehKRuExHLGEpQEMLGFjCidXOO1n22UBXhlwijILbedUNV4nvJ2yQYq0dSfXKikqlwSZKk5avYMdYuCXJolqcompk8U0oGTMqu+4Vttm1dYdMLJeuc+bz8Yd+takXbortsrzb1Tg2qzOKqLILqzMKKAGMW3qFhXuDVIwcxE0cWG1duA5cVUgMl3m0Ekhv+C1V25tulOm8Py584VILls3lv0hMgY28AwhH7+k5OC/xjmERGuwiExU3bEb0vq8QqoselarvPavu3RV/OgRHDgE/yPYfwqHI9aE3hQKi5S4kqJ2M80ys9z3ZpplYpF1bL5+arlFWqmT9zFJ1p2MZBlQNkFvN8L8kXKJ+/rplRZ7cS5809XL6orKVDZhJogwQoZxkw63oi6nvAHH9r3MKuZkHTt2HUceBQvu1RoUSAGiJEizQ5gJIiRWBWjYcJm44PAp3siUbWFnV3u4w9MWJz2REIr8cJRcxcNYPI7Di0S0paArHX3ZGMnHxF3MlWO+Ch8b8OkB/6fmNe8bWN/9eb9XiqliTN7FZBkmyjBVgdlafGrGlxbhb8+lf7xU+PpM5luL+Penwt9a+Jces316tPXrM5mfz+QWW8TH73HOPZH+0G7eWqJ68yjCHHHICKctEeOFzGCUncP9G3gWg9dpGC3EZAnmKrBAwwcaPlbSN2Nm8ukIx7MwnonxTAynYzj9fx2OZPyLcDAVsHLncdq/wT1MKOCyRHCkXHi67tVknX/KnN181+zQJUlpUdVNcOAQLp3A47I97dVe/ibYpwI3fYS6sJ5yxyV/JIYh9RTu3ER+FOozmR/l89fF4V4M2lLRkYo3mXidgbcZ6MtCXzreJOF1Ah3hZCHmaJivxef7+NEi+vOp1NLjLUtN+FiPWRodYV8melLwJhGtt9EW9++zsf9MNOjPQF863qaiNwVvk9CXiP4kDCRjNAVjyZhOwXwuFivwo5lz+YUq0W5D9LgS/Z7EeAAxHUTMBhNT+4mJAGLMlxh3J0Zd6TXiQkfYtYd4pfDjMT7WYOwO7l9DVAACHLHPDiEBAh4eHCZ20LHgE1FauUacXVqNb5cBdbM8g6A8mUMAgko8fNLMPLIUbAL3TuZNO0kiWqyCSpDSYdhuQN6mg517qbKa2Km52tSV2/cEk4kLJHaQRKTWbZLh4ZHF1h2sW5WYRTXZN6pQuKXAIQx9O34TF6qjN+lUFHt0gfChCyucAnH+JkNu+ZbGhwZXk3g8D/HvP7LD0AquQdx+x8XM3eFzBnl3taOTteV1IKrJJabFp2+7ztWP/9zFLSHBCDlOOnya0S0YQZdXXE7ZcSpa+kaaZupdj4xS3+gMm4QCm6QS05Qys38qHc9EaTJJM6ySYVwvAHdLXNuPuJOkEH+qvjmTTwDz7dumHj7buUUZIccJBU4hrRXiimRpfXZ5A8pOU7KmDYuGDde2vey8SoyQAEQYIMUCYSYIMTBJM2jbrjFxYvI5yBpwlN//IDXAF2H+iDmGgkuovYmGW3j+9xJVRxq60tGbhaE8jBViqhAzpZilYa4ac9WYrsIMDVMVmC7EZD7G8+kJatNlWKjGYiMWHqxefLr1+0vJn89Fvz3dsPSY8dMDvGvAbD0+NLF/ebD680O+sWqM1bO/e6r+lrar8CaSwxDjh5T9yD2K0lO4dwXPbuH5LXSmYDAPY0X08+r5csyXYbYIM4WYvkMXOJaJsQyM/fGW/l/98A/F/+AcTAXs/Va5BK3xOCV48Nq2Y7cUzydpRaYbpRc7WzlyKOiQRdUoWmYIOoSIM3hKM3hW6RJkDl8DHLHBtUCGmCAkHEPmOdy5iJJIlN5EbQIaklF/C08S8DoDXSnoycabTPSkoycdPSnojENnHN4moDcFw3fo1xc+3cO3h5u+P9ry9cG6pWZ8vIeZSowV0ZOQ3yShK/7fdB46xUR0JaMrGT0p9ACtt0l4m0QXOJCMsVSMp2DqH8wX4mstfrWIEq16yx2WxFs3ot+TGPUlJgOIyQBi3IcY8SZGPIhRJ2LEkRh2Wh5xIYadiEEb4q0p8VqfeL5juYXlWyNmy9CahLxzOOMLb0fYm8HDFXvNoKZPEZVnXS1KVt+7Yq8Lp6QaO68QeIVBEcAGRV7SFnBIMTBIgVsKAqpkCQ3KVjVIa5JUzbi1rFepm3Bt0+SW1ICxG9xCOEwd+IQVwLkZYqpsIoosvKJYu4MFG0HaAjFtNiPHFUYOcPKnBFxATKHYqShJB19cjOauuq/Z/NjqeiZv4EmBfW5CJo7MLvv5Qy+pGDnC/ywams2KaDbyelilACFVipY1r6Mv5XT4qrCwLf6BPH6HV9n7U/xObg6P0z1zU/tmskVKsVNSgUtKscv1NL2E4t2RuYrpNLOYHEMZPbG1YkzyEjjuyJVylLskZrufz3r53Xz2nkhOt/INlCSvAUmSgWE7K488g4w2i7Q++zZDyk5TspoNi5I1l/BuZvJ2BogCooA0C0Qp2MwAMWhYrzexZXVwhrU9PDwRdgiRJ5ATjtooPI7H82S0p6E9A53p6MzA6wz0ZmEwD8OF9GOnmRL6lYyJMkxWYLICM0WYLsJkISbvYqYU7yro58nvmqifnqz7/mzj1xb+xUf4/BAL9zFbh8lqzNRitgYfGjFZhREa5h5sHamVfZCCqhsoPovyM6CdR/1FPLyGV7fp+W1/fgvG8zH15/7WXUzfwVQeJnPpAkczMJqO0fT/QjiY+m/9B+RgKuAYwOcSxO9xatPBa9Kht5XPJGjFZFvE59rvMSMraFG27iTpWSIoCNEX0FK1p6nU5pgNQm1w2QPxh5EehuzTKLyE4qsov47qaDTE41487t3CswR0pKIrCW8y6ccSr5PRFY+2W2i7he44dCejPxvjdzFLw0ItFhs5lu5zLzYyfW7EfC2myjF8h94Gu+LRcft/U7L+UOxIwOu/9TbhX4SDKRhPwUQapnMwX4ZvjfzLz3YS7Ua/uyyJXnei35MY9iJGPYgxN2LElRhyIYZciCEbYtiOGHYghp2IIUdiwJp4a0q8MSJeqRLP1/xsxnwlujNQfhURh3DACQHuiI1WCDrMsV0VG0SwTZnJ0J5HyRjiyhyrxbBRlrpCgoKNYJMkr1fixkZs2knmkcRWFSZRNYqsDpuiAZuwMmQ0sFkFsnrQs+F28F/pdYzdwAmb5bFWgiSrziKizLlFfTNZigtbwC6NvU4rrdx5nLzXHbqw4mqGbPBFGTtf/uPha/4pUKprdL6RL+h9XFDThEPLFN5HBK/cNtrnw+h6DHcr5Ipoxor62KQMcR12NUtWWy8cP89y+dp2F2/4HOELuii8/8LW49fkLsRqJ+U7pZfbp5U6pZc5R2bo3cpXTyzTTinXTy0317EV4hOAmQHOeiE2BOUp21y8yAK6sPEmnbkqe+joJiVdrFQArwob3w7sMmGXMuSQMWJWMmPRsOHaacEtqM3CKEeCGBnigCSFjlAQ6ubr91pQLSxgYYH93rh+Av9cRvkNNN3Gq2S0p6EjHZ0Z6MpEVybeZKEnB/35GCrCxJ+IwmJMFWO8BBOlmKzABA2zFZipxFw5ZsswV4F5Gj5U40MN3jXgwwN8ekT+2ISF+/jQhPf3MduAyWrMVmGyDAu1eF+LySq8a6JO1W1+lYXHcXh4Aw9v4OF1PLyGp1FoT8CreLQl4k0q+jIxkoOxXEzcwUw+JnP/7YF/BP5JZfsPwsFUDKT8W/+fIpz28zgH83qe2XQgQupEvOrZeN24XPvLsYZKOpDR4hBUgJE1Dh/C7ct4VrOntsD0pDMueSE2CJknUXgedy+h+CoqIlF1A/duoTEB9+NxPw5P49CagNeJ6EhGawLa4tB+G20xeHkTr6Lw+hbeJKI3AyMFmK7AQjU+1eJzHT7VY772/7XBVLxOQGcc2mPxMurvG+pbaItFW9zflhiHrni8TkBPInqT6QKHUjGZhKl/MFuET9X49mDrrxc6yx0Wy90WRJ8HMehBjLgSIy7EsAMxaE8M2hMDTsSAJTFoTQztI4YdiEE7ot+KeGtKdO9dblf+/Vzw1wMs1mG8BC0pyItYH31aIvzE5oykHdExItb2EJWEqjbjPo8N6uZYJYot8uyrRCkcwkzrFVaSBElYgxWK3GvlmVfJkMVVeEVVuMVVWLZpUWV0SXpWK3mVIKvHs0NzrY45j10gnENg7s4ho8QtoQKB7VSsJUOMF+JkrIWx8xozO/Z9fjifxH4pk9s9DF6hDGdikJTP/qTdMiJXysCRRc2QU9sSB89JuR8SNnWG32nGimr5inozlb0QUiMLq3HK7yZbe1KPXVwXFEb1DIZnKAIuUDxPMxy4uCo8bkdEslpCoVV8vu2trH03M4wj0tSyaiyuZ6inldnZBXBulIWjM8IO4vYF5KfzO/lAUB+aVvA+vDIuSdM9cANpHTilSUIaVEkdSBlySO1l3mHBqmrHTV8QyjBBnAJxQIwRwmQIkLAZysYrjMzJpqbwdMLpYKRfQnkkGmLQkoT2dLRlojMDb7LQnY2eHPTk0E+qBgownI/RAowVYfIuxkswWY4pGqZrMFeLd/WYr8W7Gryvxnwt/fnsdD3mGvG+AbN1mKnBXD3eNeD9PcxU4101pooxT8Pne3hXhw+NmK3B23x0ZaItGe0JaI3Hyzi0xqMrGe1JaEtEZxLepv6NQMzCZA79HIL+IZr5tw2m/a/A/mR60f9R/yB0OcTtfpTf57zQ/quSpxI1ziXoxeU6HLuoIqUCaQ32DTIwtSEdDULiNbysN6LdMTjjgehgpJ9G/kVUXEP5dZReR3kUqiNRH4PaW2i4jeZ4PIxFyy10JeBFLJ7F4GUUXkXjZSSeXcOLSHTGoPM2upMxkIOJYsxWYL4SCzQsVNFvtQ7l0T9E/whsu0UX+Afhq1i03qZXx210xuN1It4moS/l31+XqWTM5WKhAl8a8e2J3K9XxsuvrYleC2LQixjyJEZciGE7YtCaGLAiBmyIQXui14QYsCSG9hFD9v8i7DH+3bnr57OtPx/wEA8oXxtXj9BkWov3PrrrXpxpk3Jre2OtZWqyuro61LXIVi5C21QgKMshIMO5UoQKdqyVX4W1DNjEwC7LySfOumk7P8cmkqACl4wGv6Qas4bFKjltbNXhWSVF3SjBYeumaOnGb2SLAye2WTgJiChhhRgooiuwnh0ijOvVGC09t9i6bvIM2Xzy9oaIHFHno0xGbjgXy1XcsKPxiXHA5Q0KhlAz5jF35zh6Vcb3qKST/6bA02sfPNhdUmUlowEp9TVy+pLq5qL2PlsDjwhcu6V1OUbV8RBX4LmtEWkG529pRaVYpt9xT8x3iUpzLKg6GZ/rlVnum1TkEJ1hXfng/KEwKT1LRmevtccOryvO0UyOlXT35dC24dNzWuvozXMrXiPwoNBOHV5h1Y2bdnJLaFAkDTglDajbzVlUbHnlTblXqjBBigni7BAFBIAtJGwhYRN2GnKYWsDGEqH+iDmF4kg0xuJZPNrT0ZGHtlz05qE/HwMF6M9H3x1056E7Bz256M5Gbx6G8jFaiLESTFZiugYzDZSF+9SPzZwfm7DQiA+N+HIfC3WYptE/O6drMEHDWAUmaJipxnQVZmn4XIfZUnyoxNI9fKzDpwbMVGOsAkN30ZeH3lx056AzAx1p6ExDZwraEtEej+5k9KdiMBXD6Zj4a+9fh38/R4dSMZhCXyL1J/1XDSRjKBXD6YBbMK9X6Fq/i4L7r0qeTtI8n6gfl+sQGConogBJNfa1UnSEyZF41WhYnqd/1hNxx5B9AcURqIoC7SZKr6PsJmpuouYmKm6gOhpN8WiKwaNItMXjaRSeROLZDbyIxMvreBqB5zfQEY3WKHTGoefP65JiTJdgpgwz5ZgswWgB+rPQnUz/EG27hdaYfxG+isGr2H8ddsShK+Evwr8tfjAd0yl4f+dPG8TPp0o/Wy2W39gRA9bEkDcx7EWMuBBDNsSgBdFvQfRbEQO2xFtjot+CGLQmhuyJAVuiz/IPwuVe1e8vZH4/2ko8EVl+JDPXqNl3z7W36WRpupubNRJixMtKzGOjTd68zm3vKjC2ESyqSSmqTjt0yju/LpcqwFr1ghZ/N9YswPzl4FPfME9B2VVFdRlPX1dqmgts0yIpGTLm3yt51P3o9fCTnqH7WTlnK6qvjM4UBp2V0zRHwCnzx0Ovdvs5gh3cCthtvSo1K3Dx0+fRmWe/iKGHT6sPHnYrp0V8+XLvSXOsphN2mbAr7eYwciEdi5Cqe3IuJtXRyY+jhqbd0Oh7/Nze+pbKyaXZ0YW3LR052fkBS0utT55m7D+mX1Rz7fNyV/3DtNqG1KWl3ntPrxfQzn3+1d7Ykji6UJ1bcbTp5e2FH89ycs6+6qDNfxpYmH9FfGkpzQmpKY+aft/nflTPyI41PFyhsNB/av7l+ZhzfJIcYlp8W/XZJfQpCqZsyjbcMsYcvEp/Qi/YsYUecQNhEjZDSZ/J3BoO9rh0BGnhqLmFx/FoTcHrHHQVoDUfw8X019jDd9FbgDe5eJ2Frky0p6MrEz05GCzAaDEmaJiqY5pu2vzhwdbPjyW+tAgvPtq49Gj110fsH+9jugpjNExW0y9FDpdivAwT5Rgvx1QFlhrwoQIfKrFUj0+1+HgPc9V4V4dpGkZKMHQXfUV4k4f2LLSl4XUa2hLRFofuJPSl0CH9D8LxLPquzGg6BlPoCP+H338QjmQA7oco+8+Iep2VDI5VC47beTFNJ6PAyc6Bb40i1opxCYowODoj7BiSozk77tvQcmRv70dGGO6cR8U11MWi5iYqIlB7HdU3UH0DdTdw/wYeXMeja2iJwJOreHYZTy/h6SU8uoQnV9ByDc9u4MVNvLiJ1lvoSkBPGvqz/5435NN3RF8noz0erbfwKgYvovAiCm2R/1Z7FDqi0XULXbfwJh498ehN/FvJ6E/DQAbGcjBXjC917N8fSf94qfOzw+xnt+33Xidi2IUYciYGHZb77Zb79xF9+4gBa6Lfmhi0Wh4w/z1g9WPA5seg1e9+0+XePb97tIkOSaJH+9tzTqLDnWgPbqPhRblYT4NxJe2MozfcPbhLCk/FxO+svu9OEMPmxspHztktE59fdXZE3oph5qW8/z7t6GchobL+B7HgEWwDNtx7WjH1eXitFHW7EfeGnXjWen90usfdz+xCpOeFaIfj4ea/iJErN49rO6D5eVpb+xvwAZsYGXew7LLH8dO7iR9EWqHV0+fZP358isrUup3pSRA/j1wVltAiK2nJbdfDPh+GyERd4gfRO/zY4Qjy6qSe9oR//L7w5E2LVYi0c7B209PCY1fEf34jSmuvnbtp/JOYed5GO35V6UrinvefX4+Pj1+Js5z5Vra4ND822R2VafZ2Knd6buj0dfH3I70T3f/cuLCu9aH/nWzDipLI38vzBnablA1x9Kxsar7Bt49fL18Pw1rwqUNEd7WMEesuC6hYQsaImV+VHRJkbAYEACESNjFiPQPEIacFa2t4OyM2DP+EozIGj1PRkYWefAwXY7wc45XkyUpMVmK8DAP5eJOFznR0pKEjGe0p6ExDdzYGCjBRgblaLDRg4aHgYsu278+Uvj9T+flU5UfLzi8PxBfqN8xVYaIC/XfxugCd+XhdgN4i9N/FWDGmKvCuCgt1+FSPL3VYqsXXOszX4X0tZqswXonhUvQVovcOenLRk47uNHQn43Ui3iShNwX9aRjMRH82hrMxnI2RHIxmY+Qvy+FUDKVgMBkDif9Vb+PRl4SBNAxnAo4HSf9BeCxe+XLm7tg0K8O95NU7sFqUU0iU5OSCsGNIvcXb1exQkSV7KwDpobhzHiURqItBzU2UX0HNNdCuoeYa6q+j4Rqar+HBVTy+gsdX6AhbwvHoEh5fpiN8HokXN/EqBp3xeJOC3kz0/4316M3AmxR0JODV3xk+L6LwPBIvb9LrVRRaY9B2C+2x6LiNjtvoisebRPQk420qejPoj55mCvGhAt8a+X8/lSdad//usvz91mG5z4UYciaGnIkhR2LQgRh0IAbtiAE7YsCOGLQiBqx/D1gtD9ouD1oTg+ZEnyHxVu/nY32iW+/jo/VE9w1iuOJnt0/rvRXEVPfoAC34sPCpU7tolWeLKz0OnxaYe/+gvqpMQAZjEwNfFn/wCTDv89TtHnnLuZlX01bsMzG/P8wDFCTlxcx9HZdW2yiuSRLWQHl1/suOB+wrsFkKuwzYzF1FGp5mzHzsDjqr9unHU99Ae5AADkAEOp44e86c+EHE3qVUPvAilonTVw0zy/YvLs07eqkJKEPXeouWMZeZO+4/jF368oEgfmSUBCQXKiwsvewfG1DYLckpCXEVXlXDFT4h2wjic0d348uO6tkPbQdPKx++InguVoXWdPP7r49ZpcfKm0O/Lv5+/LLw1p09k+86HrUnhscpTww/bn18MfKsdG2x9YULKCkO+v31m74dv4YZfA+vjkySJYgf4TeCIAgJc3YhrRXSBlQVK7K2LaucMQevEhXiZAiRIAQIMf4H4Q5dkoMDDnni9glkhaMqFk/S8ToP/XcxXo7pKszVrXxXxzRbg6kKDBWiOxsdaWhLQVsi2hLRnoKudPTmYaQY0zTM1eLTA/6lx5t/PJP6+Uz+1/Odv18oLbZsm28SnqvCeDneFqA9Gy8z0ZaFrhy8ycNA4V+H1fhYi8+1dIQf7+F9PeZqMfOneRajrxB9+ejNpO/zv0miXzvpS0V/Goay6AhHszGa/e/icDj1r8Ok/0LYl4iBFAxnYiwHcNhPDjgr6nVWMjhaKSxJLclMDacAACAASURBVCrH+Mx13e1KWCGPlVtYhcRJrh44GYp/4td3P3IuSdt2ww/Jocg9h7tXUH0TVTdQeRnVEaiMQNVV1Eag/io9dvzhJTwOx/NwtPytx5fRchVPr9MdvoxG+210JeFNCn2YeXc6upLQHo+X/2+Azx+Er6L+rdbo/0XYnUQXOJCDkQKM38V8OT7X4EfzBuK5EtGmT3RaEj0ORJ8LMWBPDDoQw07EiAsx7EqMuBIjrsSwCzFsRwztI4bsiGF7YngfMWhB9BkSPXrLHSr/V9l9hmPB/v8Df9uS1Z53Qzslo0GRykqIkEJlJFG4KXtfLnuTveK2I3vPkKwUJU0qu0RGqTtx/h9cl7rv7+/7+x/H7zjeDy6XnvTg5Ryf8/yc5C2+tDOQt8Fz3ddID/V+CUhP4+jbWmW5tTFR2lHR2qk5ptpXmQqqKWSeaOjwFhZkT0/+ACtKGqOTszPBxCCguOQH+X7B6DzLSobEu7Hd/Z18IiuEZJesOYDSyryfZDr1bmTHq1ItY8F9kjC2kflCXvb2dTzuTrhpdzzmjktRY11c8a1TxrCyOUX+Jj9Iw8zUh+6OPlE5JBeYETKneHYPvwxEFLH3IOd1+90/Zz/Ut9weGxt7+eZRXrna95mBgvJUjl3YK/3HkTMr5bSgb7pr5PMjQmYJIZ6BV6x8tlNi+OwC+G8la/0gQ50vS+Izb5CfpLY5Luee0djYWHyhfEDqic+fu36MP/zypoOMPwwJYSguMiN/E4nT6yUVeS8abKIGHCBzxCfQmXUD41rRJXzHl+2RZRc/yyp3cekB5WVc+1mwkxG7WMEH8DFhAyPWArsgKosrOrC7hmgHpHuhKgLtKXh1F31F+FiOiWp8ub/1S8PqiVqMlqIvF89T0ZmA9hi0R6A9Ao+i0BmLZ0l4cwd9eRgqxlgVpuow07j6e/OW2TaBH+0HZ1qFJxv5x8rRV4jnmWhJwINoPIhGaxw6bqObtrbMwVARPpZgohzTFfhajakaTNVgvBqjFRgqRX8R3uehJwc96XiditeJ9PI1bU/+Vdx/QUgLfXvmf4yHb2LRm4D3KRhIBy6Ys5pQdhq57rIMPkSJOxF+55yp3YHt/OAVxFI+9u17mAyuwsUR6fFbXrcYZkXv9b1Krw1meaEkECX+KPJCiQ89FT6o9cE9b9z3QqMHGj3QupBmT7R4odkXLX5o9f9Xh6wn0QuJweMwtIeiLRitQQsIg/EwGI9o+YXwFh3h00g8i8aLeLxMxJsUvMvEYC6GC/G5DF+r8ePBNtImNv9Idq5Tdf6ZBnlxgbzSJG+0ybtLpP8yGTQig0ZkwJgMGJF+fdKnR97rkT4d8v4C6T1LXiqRbumfHarfnm6ce6pE3lcPtoG8vzv57NbUi/gfI/ciPA3TUgwsrPnSciwM7Hht/QQnJsYbGkMftlQQMhsUZv/kXfURuYMsa9mPnhX+QWYVNRWxGHfLMt8MP/9jL+9h5fUrhVBdX/Smr8vV07KiIUlNf+dpnfWqelsyij3IT3LR8A9LZ76IpGtm9o5XnS+JqMDH8yL5QdoepTU3lszNfW3o9I5Juzky+vai6br9CovF1bHnAEfgLbP5+aH2l+GfJl+QOVJebUHIu9L6uGUCEFTkEJSH7AVYOO388nVs7PPQ1JfhyoaEa/a7LX1XOYZudwkVe9pT8O3Hp9ZH1YTM9gxXvRkuetnT5Ju8OyhL+sOn7rfPS1qKw3oeBrh7ID1Vf36KKOjt3C/NeO7y+lsJkj+/T8cney7bzcwnuWaX3Fp+GTZRFWYZrZX7T6/mEGTDFgbsYsUm2qOLDFgD5l04LIurOnA0QowD7niiNhKP09Cbi5ESTFTjS8Oy2Za9fzetm6nD5woM5eFNGr2n+8Nwetoj0BmL7mS8zsTbuxgpwlg5Ptdgqh7fmjd+f8j/tZV/vGnXpyr0F6ErAw+iURWKmmA0hKE1Eo/j8DQRL9PRexcD+fhQgskK+onQqVpM1WK8Gp8qMVyGgWL0F+FdNt7eQc+CQ9oi6EUM3i6cDu1LpR9bG0rBUAqG/sJgIgYS0B+Pvji8j6Xn10g4kAFcsuIyo+42puy2DDjgHicVeUdby2Dblh3g2gvuTUw7BZiMTEBxRXby7t626ymhOygGiLBBEgUZ7sj1RZEvCjxQ5oUSH5R7o9IHNd6oW0DY5I4WN7S4o8UdrR5o8UKr94LDBWP00l8YHoX/HgBbAun/oD2EHhrFh8F4GPKPwn04uhZavr5MRg+tjFuADyWYrmabqV832yI4//DY/CPZucdKc09VSLcaeaFOXmmSt7pkwJAMm5ARczJiTkZukBFTMmJCBk3IoDHp1ye9WuTl6bkuub8fnfzeLj/btZ+8yhnrxuwrCvlYMNHjPPYs7POLDCvz1cami/LKLHVtoWeHksrkmS9vhz40dD4rnZoeraor4NoMhlUQV5Sa+HtK1+QS2JFWmPRm+DnjUmzaz7pTEnUPip+9auNazsi1BrtFoXBhpbgSo3+M3tQEUdZiumYLPTM+MIJtK6PCVVDcNMg3Epy63jYQ74bqP35+mpYT+GH8hZTyslW7GfglFqvr7Bkeep+RZy2tBq1ra758mZn61D46Xv3h89OTZ49hJbaKQ+ncGt1ra8kPUloTn1pgSchQVuEtvZur3GN3J+RrphbYzM3PfP9KWrqSv8z2/Jj9mt/wp2/c8aC7Jz59etvSGGx7E9HRoPoiNdmMfCciiuDZBRUdVvfQ9YQMxWWaM23EthOLhZT59spxCSswHlXl3Se3km0vOzYzYCsjNgCbGbCRARvAxY/jcrh+Cc6GiLNHlifuRaIzHe8K8LEck3XM3x5smm3Z/XfTqpl6fK7AcCHe3sGzJHTEoT0CD8PRFoa2MDyKxJM4dCfjRRre36WfABmrwuR9fGlZOdWyceLB+rFq9JWgKwP10SgLQIkfqgJQH4zmcLRFozMBz1Pw9g4G8vGxBOMVmKrCdDUmazBZQ3f4sRRDJRgsoHcV603DmyS8ScDreLyKw/ukfwkc/pVkDCdjMBEDt//l8E0cfSQczAR07FeZePCbuAvYBx7yipUKT9U6cZpn805w8INrI+NuIUYTC7hRkJe+7/0j8wTfLY66CLHGbQqS3XDXGwVeyKeixB1lXijzQoUXar1Q54lGDzyg4gEVzRS0uKGVilYPtHmi1RttPmjz+c3s15yTxq8tCK2BC03sgn4LbAv6nX86/IXwVQp6MtCXg5EifCrFzP3ts01CpE2ctEuThzLzj2RJ50nSpUCeqZKXZ0mvDhkwJMNm5IMlGbUho/ZkzI58siWjNuTjTTJsSt5fnn+tMd+tNPdsJ+k6N9GB+UdXyIBKX9vOTy+Vp3qoL0o076WcMlCHn9/hoEg5PVsY2MHZW4WQ6fR8GzMHye+zE4mpwXJaLEu24rDEoa/kq46JFjiQWhD7fvyNttEZS3e9c9fEKuvv9A52aOkqGd9QC00w0zDkk1RhSsj5c/zr50vX12sZwj9Wjl9y2+YjKyT1YOl0ipAfjQ+DGpuSyDwpLo+9FXvz59z3qIg4j1BHZz8zz1tnx8b67D0FdC14lQxQVptAZmc6niYSMjk08sPRx8orxLyuPu+vFJvvU6SmNVDZAA1taYRMR2dcsfbfHJGhEZJ4tqe/ZXxs2jNKvHf4/ujoaHD2xqAEDd/kHeNDQz8/ve6ovfWyNSYh8nx8vCshH31jPf0jKbG3Keb2ewj50fW6ysn7z9DEcBGVrXvleAVlGQ/Ic+w4xsvMz45NDNgEbAT4GLCJEZuxQhDyCrDQg7sxEu2R64m6KHRn4H0hRiswXb/k76Ydsy0bfzQyz9RhuhKfitF/F2/S6FuUj6PRHoG2MDwMx+No+j5Nbwbe52C4CB/K8fkeppsw3YTx+/hQjb4SPM1CQwxKA1HkhXJv1PjhXhDqQ9ASgUcx6EpEbyb68+i3VSfKMFmJiWpMLKwPR8swUoLhIgzloT8b7zIWrkQk4X0S+hIxkILBVHxIxUgaPqbiI+3zwnjYn4C+ePTFoy8Ob2/jXTIG0jGcBeg7rTPx4L/hJeRyS8I3Vi4w/uweUfyxjZF9NxZvYNyzn/FPS3hQUXhHpO/RzWj3TdaXEGSFBFckueKOB/I9kU9FMRXFHih1R6UHqj1QR0UDFY1uuE9BM2XB4QJCWloC0RJIXx/+R1oC0Oz/e+lIY/lgIU1BaA5GSwhaQ9F2C48i0RGDJwnoTsHrTPTl4UMJxivx/YHYbIvk/EMp0iY913Z8rk2SPBYnT8TJk9OkW428uUjeXyXD5mTUhow7k8+uZMKNTHiQCQr57ELGbMmIGXl/mfRok84jpPXiTOvOHw8VyXvPmU7D6VfG5EPzVNO5DG8keu9JDNW+asJt5gpj20W619aU30/QvbFD8/qm5ifpVpSTV+1WKF6ErqHk0NTbC9dVNolwJxdE9nzsfvS66dXHNq8o87zy6N7B9nfDTz5MPksr9BA8gVPaS1KKrLpHawysd53X5wpNPXXw9B/LRdgl9BGffXNkpP3r1NDcNHn18vl5g802VIXBkTcjHwfHZvtza8Iikq80Po40sd2oqAO5iwhK0PgyXv+6Lz403rj6fs3k96nBzw/bnyWnptt8nOh60h+paYb8ao/XgxW9n+6EpSuHpWiGpp/Mq3GqbY639F2XV+NSei/MJ3V5aKrSnUqlgbeNP8fbyddRMjIZc8siPN6qd+Je9+Dbdx8GyytzHKkn3r56Ofn1xdBET9f73p2ya/bI8gjJsQnLcG4W5WLcwYqNjFgHbAQ2AxsZsRFrBKGkBOsr8DVDsiMKvdEUgxd30F+MsSp8vb92tkVwtmXljweYqcd0NT6XYagAbzPxIpX+oCXNIW1S2hGDjjj6vPRdLgaK8bECE/cwWYexagxV4l0JurJxPxalgSjwQLEHyjxR5oMKP9QGoDEEbZHoSsCrDLy/i9ECfCrGeAkmK/C5Cp8r8akSn8oxWoaPpfhYhOF8DOZg8A76M9GXQa8KDiRjJAUfUvExFaNpGE3HaBo+pmIkGcN/YTABA/EYiEd/HN7epi8Ih7MAXad1Jh78Vj773SKO+cbK+USp/LEL6/kY2XeDYz2DwEFmC2t4eKA4+0D/Y8sIykariwi0RCwFtynIdEeeB/LcUOSGQipKqKhwRyUVtRTUUdDgikYXtLrQEba5o83zt8NfCP9naJ0kfzmkffPgf3H4MByPotAZj2dJeJ2J/nyMlmKiiuf7ffHZphNzLdJzLdI/mo/+aBb92SYy/0iYdCqSZ6rktTZ5Z0iGb5BRe/LZlUxQyZQfmfQlk77zUx5kgkLGrMnwddJnQHp4vjayk46Ls134+mgf6faae+NF3t7+u0Wlr25Heazcn1r7L+rC1BE2rnvNbNfLXOKVvcSlef0PLZMVclq4as1qYrPG4PoffCIrV/Ozrt3LtFdy3Xr+pXxCawWPbVovxCypuOnQsY0iRzYLHFq57yjbYUVm7evbVPTWnzJbrWy42vCGYOidk+Laa5aLLVa355E8y2lgJOIQDu80XLVbcVSOR1KRd5swRGUZhaU2bRWHotZacw+eP22FtMyhb7nhvClupwt2vLppF7Bqw0FsF14vf4FTRguWDgLaFoxG9lsuW269Yr3NxHmna7CUS5BsRqlFVI7srQyZmLuq/olHg1JkvOMkgtIPhmVLhMTKxsaddPFBfCxrfJSEqh6Ur+PU5UObT2CvNBOfCAxsYWy6x853uzFl92oRbDjKwy/DvV9hsZD04j8OLGLYxoYNDFgLrAc2AOuAtVixB6cVYH8FwRbIcEKxL1ri8OouhkswXo2ZxvU/W4V/tnHPNmGmHl9qMVGOkSK8y8ardHTTHMbiUSQdIe1AWWcCulPxKgtv8zBYgvFKjFditAz9ZXhTgqdZqI9DaSBy3ekzuCIPlHii0gf3/NEUgvZoPEvCq3SM3MXHfHwqxkQ5Plfic+XCKZwK0K5r0ByO5GAoGwPZ/4mQLnAB4YeUfyEcoJ0qSUJfKgYzgSuOy2/6bL/htdU3+oRvpNIlU+FFm7B4CxZtBesaCEsymNmD6oPaYtn+h1a3bDmdDRFgg0gn3HbBHU/keiKXgnwqSt1R6o4KKqrdULsgsNEFjU544IxmV7RQ/zUdbfanM/unvWZ/tPuh3Q+t/mj992/vB+B+ABoD0RiEB8F4EIymEDSF4EEwmsPwMBodCehOxbtcjFYwTtev+dZ09O8WydkWsdkmoe8N27/fW/u9fs3PhtWkTZo8OkWeaZAePTJoQkatyIQzmXQhEz5kOoBMB5DJADLhSz77kFE3MuxA3qj9fCb97dGeHw/55h5vJ0/2k84T849kv7bvf5aHRBfoKUHhDKuGJQyd4eK9SfHi2kPK0LixRs5okZw+11F1FhU9XiObrZbXcFAE67awrjnEB0E27ACLCOPGI2t3H8cuSWa+g8zrhRh3SLCKqy6X010mq8d6znDDyXNwDRAoqDTS1lt36ATOXF4qrY/rlvCKWh6cekD2HK/giSX75VmEpSAmx7tfgfugEpR0YUHZ9qfDFvXLLJrXOS/d4EhKEmh/fjU0QXq3OMvuozwnNKBvyWxgxmXsuFbLlEnPiudPNz4zyiY7f4GgJNmIzNPh6Wej7mhGZKgHJ58KuC0dmHw8JE0qNF06IPX4rSjEe3HWFoh4+G8UU2DSusZ85cpqMUXuzSc4Nsnzimlx61svt3Fa6uUnckaVBRKL+KQWiSpwCUotYhRixDZgM7AG2MCILcByiB3HFU3eK2fgZYoAS9x1Rbk/WuPRnY2+IoxW4Fs9SPM60sw7+wAz9ZiqxecqjJZiMB/v79C7LrxMRkccHkagOQytEXhEO04cj1fJeJtJrz18LMVoGd4X4k0uulLRHI3qQBR7I98T+Z4o9kSRO0qoKKGiyhMNQXgYg6eJeJ2Kd1kYzsdoCSbKMFWOr+X4Wo7JCkxWYLISkxUYL8HHQgznYjALIxn0w2vDyfiQitFMfL6Dz1kYy8SnjN8IBxMwEIfBeLyPRX88hv7Ch1TA2GWNuSefnb+AZ8Tx4LizJ8+t4eQD60awbwHHWogcw58OcPdFXYn8QLt1iC2n41X4WyPSCQnOyPRAjgdyXFHkRv9vlLuhivJ/QPjL4a8f6b/1RbMvvbNykx/u+9MR3g9AY9Bvhw+C0RiEphC0RqA9Bk+T0JONkVJM3lvxtVH8W5PE302HvjXyf61b86WGY6YGM/cw33yYtB0jTxXIS03y3pCMmJMxWzLhTCa8yLQ/+RI4PxkwP+FPJnzJmAcZcSFvdcgL5Z8dYnPtu+c7+EnnwbnHkj8fSo3W8XQXID8I1zRw7DgUdWFoz+rlf+C8Ed+R01C5tlzVZPUZ4/Uy2twntVlP67Ba3lhuZLxFXHbFaiG2taI8TMIM2AnOA5x7pZn2nmDfKsr6hzDjdnGWwypLZS7xyugyq+qtUL/M4hclkVtqdNVkm8QpqBosl9HFn7aM3tErA5NFpNQ590py7ZdnEZGG+KllIqe4xJShos9oQdluYrtRVY/1/DWOixac8fG72p8bhCac2HeUec9RzlOXmAys2Q0tll6xW6FtxqxvvcSMssnCfatzyP7gZLnQ1FP/G8KglBNh0fgrcGVN4X4Xjw2HZJnPX2c1vLZW4gzvTmnOddKLhdXYL1rw3LTjdfcW1NZfDjHWXTLconLse46xch5io8HDBmAZwI0N4jC33eNqvdXyEqjXEWqHHArK/dESh647eFeAkTJ8uYe5Rva5JtYfjfhah6laTFTjUxlGijCYi/d38PYOXqfiWTweRaEtHG2ReBSFjkg8jcXz2+hJx7tsDORjuAgjJXibj1d38TQFTVF0hHkeyPNAsSeKPVBMRbEbSt1R44vGULRG4eltvE7F+7sYKcJ4CSbLFtpqVmG6mp6pKkyU4VMRPhb8vkk4koKPafh0B5+z8DkL43fwKQMfU/8xEsZhII6OcDARIymAidsff3psdQ455BUuHRKvuUsM3FvBuBYcm8GxFgePw8IJ3gG4X6442GkXYr+YhjDcEXFOyHBHrhvuuqCQgmI3FLuhjIIqCmpc0eCM+8647/wvhL82SFu9fwOj2fv14wNvehp90OiD+l/xQ4M/Pb8oNgbhfiAeBKPpFloi8DgOLzMwVIzx6sXTDeIz98VmGgW/1PFNVGO8HJ8rMFGJn/e3zrYIzj0WJ8+UyGtt0mdMPliRTw5kgkqmfcnXwPmpwPnJADLpTyZ8yCiV9JuSnktzXfJzHaKk4wDpODDbfvhHm8TYPbwuRF0c7HUhLgYZDVyzXUr1FLlmL3BYCVLazGeM16td3yivv0xOi/2wItR1V5vY7blguELkKLaLMK4Q5MQeJoiyCcqyCEgt2i7GtlGEadsRZtHTPNIXeeT02RS1mK5ab0rIUs8o0rdyPiBzhlnFgEfmEm46cvjGrvFPFJRUYeWXWCwix7xfBkcVV4qc4hJXZVY3ZDd33WZk+YfSRWgYLb5gzhUZvb39ucGtpOMiUkx7jrKpG/EY2nJevbniss3KSze4L9usvO688abnbvdIiZAUhYDbsuHpZyMzz/83hDKRcbgTtamqUMzccTX/Mdaz15iNTdfJaCzdc4p7mSTzLnkGDSO26zfZHCg7Ta12Lj3Kult6kbAkA78E63IxbmwAuAE+YB2wCZfMNgSHHXG0XGSpA+p1RDsh1w3l/miKQWc63uRgsASTNfjegNlGfG/4jXC8gj4VHMxFfzZ6M/AiCR1xeBSF9gg8jKK/VfgsHi+T6Q778zCQj55cvMjCk2Q0RaE66DfCkl8IKShyRbkbqr1Q64eWcHTG4sW/HU5X0FtFzdRhpg4ztEd5yzFRho93MZKF4Qx8SMfHDDrCiWyMZ+JTOj6mYjiRjrA/Fv2xeB+LvjgMJGDoL8Dck8/Sd7dLqFhArDI1UGnFVnDygXEtFm0C71qISTPddIFfMBprTo902YU4cDkaw88W4Y6IdUS6G3IoyHVCoQuKKCiioNQVla6odkG9038ibHajI6Q5bPTBA188WBjuaJ8bffDAEw88cd+LnjrvhfjSU+/3G+SvsZHm8GE0ulPRX4DRCsbp2oNf6oS/3NsxWc09TpvEl2C8FH/XYbZxxVzb3vknkuT56fkeHdJvSoatyLgzmaSSL75zU35zU35kOoBM+pJxDzJoQ94ak+fnyBNZ0nGEdIiRR6I/2kRnW7e/L0RLAryMoCiF8/r405Hzpu1KW28hidMQkoPMxRUnDdYqGKxQ0F925DSEFZedvMBoZM1zxYhrnxB4NzEsPcALSTZBWZa9J9hpCLeKMR1Q5JS+yKNwhfO0Jij+h3MrrqUV6LsGHpfXYlDWZVfQYbBy5vaJWe2bICBxmolfYvF+eZb9MhA/tUxYnl3yLOs5Yy4zZ77LZitPaUHdkFPLhDsojK/tmX5UupT4KVbhE4w6Fsuv2C3Sv7lKz2qZruUSXcsll21W3vDY6RV9LDj5lG+cVFia+i+E/glSAUnHQtKkQtKkbiUrRCegMHlvWYH4JbMlm8TYzxgvNrq5QkF7iZAC91Jxxq3SUNFnMTRlumn3hw1lv+Dp5QJHISyBg9KcSw9xYj2wEtiMJesgr7bEM1jU23+zkR7+vAj/G4h2QA4VZX64H4HHyXiVjf4ifK7CTD3m7mO2Ad9+PX9biYkyfC7BSAH9mPHrVHQnoGOhfE+75vb0HxvmtGaZr7LQnYHOJDRFoyYYJT7I80CuOwo9UeiJEncUuaHQBYUuKHZDORX1/mgOxZM4vEyjb7l/LsVkJaZpzaPq8L0B3+rxtRZTVZiqwFg+RnMxkoWPGRjN/MdImIlP6fiQjKHbdIF9MeiLQW8seuPwNh7vEoAb3tscQw86B4ndun3+irkw1wawbwTTeizegKXrcUyWxdYNgbfQUq86/Nwx2HmRoyn87BHhjBgnpFOQ7YJcBxQ5osAZBc4ocUG5E6qdUO+EBkc0OP4LYYs7vWTfsmCs0ft3aN80eNJzz4ue2n/kng/u+fynRvrAGIKWcDxNxNscWql391TN1sma1eOV+FiC4UJ8KMDHIsxU095qXU0eC5GnUuSFKunVI/3XyYebZMyOTFDmJqhk0pdM+5MpHzLhSQbtybs/ycuLpEuRPDlGOo6Qx6Kzjw6RhzIDBXiUiAhL6KpB34TFxBnXrWHvt0P2HHZJQkJtpeSFZacMeJUurzmqzrFHeeO+U9AzB8Vth5rK0rUbwb4NOMIoJMcmILVop/iizQdY+EQZBWVZjmlxnDJYrH0F4YkqRfXWyQVXvKPllPWgcAln9LksnTi9o1f6xO85qsyyV5LrwClWYSkckuEWlmeX0uTQvM5r4rhJx3i5vAbUDHjOX+PxDt7Q2HkxJV9RWoX5qOIiXcsletZM+hZr9KxW6FmtuGDOddGCx5y6wz1S0j9Bzi9ehoYwPF0tKEmehjA49URImlRkskpsIkv5XdGCvCNKutzLhbgUjRZftVqidGmxoCLbSgnWHTKsCheYr5iwXL2x9KabkIoBn8gxSMkxKJzbtFaUBxuAtcBSbFgHZ+cDIRGHnKjcpkYw1UawFWJskeuOUl/U3cLDBDzPwPsCjFXgyz3MNmC2Ad/r8fUepqoxWYGJst+TQFr7hZfJ6IpDRyQehv++8/0sHi8S8ToVPel4ewfPM/AsHZ1JaI5BbQhK/JDviTwPFHig0AOFHiimopCCQhcUuaKYgipP3PNHaxiexqMnHX059DaKtGHwewP+vk93SP/rsNBq7VMWRjMxmomxTIxl4lMaPqZg5C8MJvwWSEe4ENz02e4accQl+FhAzNkTStxLNoJ9Pdg2gXcDVm2A9KlFDh4IiUDrA7WRVw5BTmzONxDohHAKYp2RTkG2E+7aodAB+U7Id0KxM8ocUeWIOsd/IWxy+Y2QFpq0XyPeL3717vTc88A9D9R40lO98LnWC7XedI33fP5BMRBNt9ARjzdZPN/FUwAAGqdJREFU6C/CaNni0QrWsXKmsRKMFND7jozkYroc32sx38xA2jeTjgPkqRR5oUZ6tUm/PhkxIaNW8+MOZIJCpr3JtDeZ8CBDdqTPjLzWId1nyFNpGsL59oM/6mUHCtGVgdvOuKLJcu4ydCxx3QG23is1jZYIH2M+rLxOXHOp1GUuWZ2lEme496r8IaDIIKECY9PVltb7RY+zsazFUkEIybHtk168+ygn30HWzYcY+E8wHFFnktVjtaFsSSvQz6+2TikyDkxW0DRhOamNs5eX0xB6x/EfVWYROMZzUIFNWAr7T3AIy7NLa3FqXue9arvhgiGvvAajmgHv2avcFJ/llU2qdytVT59bpKjJe8Gc9eJN6Fis07Vcpme1QtOETct0kTl1ByXsiHfMicBE+bA09YgMjf+JMDpVPS6Ru7pI/M7dw+KqbMz8vHKGnJetWFX1OEQUWTcf49yrwCt9FpdNOfVNOIxt+a7ZCiqpQ1N7ieaV3ZskeekIl0BDBVFRsm4+Oy1s2Myu47IqAkyR6oxcd5T4oDYYzdHoSkLvXVorWvrLDT/q8P0evlZjqhyTZZj81dApD33Z6E3Di0Q8jaHfqvn1in13Al4m4XUq3qShOxVdaehMQkss6sJQFoACL+R7ItcdeR4o9EABbTCkoMgNJW4ooaLcC3UBaA3Dkzi8SaPXD6er8bUW3xvwoxE/GvH3fXyrw8w9fCnDZDHG8ukIP2bQN0U/JNMnov2xeB/9O/+8VIGbPttdbh32CJd38ZXfIYQlG7FoA9g2YclGrNkM2dMcTl4IicbD5rMfXjv6OYFijUAKItwQ50JHmGuDIjvkOSLPEUWOdIT3HFDvgHqH/0TY5EFPvQfqPX6Pew2e9G/uuaGGSk+VO6rcUemBSg/652qPf2j0Rq03arzoY2ODPx4Eoz0Gz9PQm0t/C22kBMOFGLiLwSwM3cFwFv3GynwjSNvyuYc75tsPkidSpPsUeaNB+i6RYWPywYKMO5IpKpl2JxMU8tGaDJqRXh3yXJk8lSaPD8+3H5xrF/paJzpUiq4sJDhDV51FUgnSWtCzXmnjxXjdfttBad79cqtF1XiP63FIai46cmaZgCK3kCz37iM4dprF0HK7ttGGfaJYvxW7j4P/GOtO8UU0hLuP44g608nLi+JT5QorzdIKTdPKzCKyVQ2dVipoQ+vyemsXXu/olV6xu8WVGAWO8RxSXERDKHJqkYw29/lrPAZWa7UMeE+dY1a/skL1Mpe1K0tupXRxg6b6BfZLVzecM4G2BXRu/qFzc6mu5bLz11kv3eC18t7rHCLqFi4enKxwK1XtF0K/+BM0hMGpJ+LTNOMSuetKjydnie2RZ8XOlVKGnHpW0LzCLqzAuENmqYjyOgklXDFfomPCpm26zNFD5IblZsOrq1W01244uohWlmAXQZD/ocjY4xYO6zQv46ImrpxBwDXcpSLfC8XeqArA/Vt4HIsXqejLwXAhpivwtQrf7+H7PczUYLqS/pbDdAV9PPyQh/5s9KbheQKeRONJ5D8cxtE7g71MwrMUPE1BZxLa4tEQgfJAFPmgwAt5VOS7I88DBe7IW0BYTEU+BYVUlHvhnj+aw/AkAa8z0Z+Lz6WYrMCXGnyrx9/38eM+/m7A93p8q8R0CcbzMZaFjxn4kIqRZAwlYigBA3F0ge+ifofG73UMXkcDN7y3OQQd9Is5be4otpoPvBvAtRmsG7FsA9ZvxkkVLmdvhMagvUWDhpBqh2AqotzpCLMckWuDQlvkOiDXAYUOKHVApcN/R9hM/Y2wzp2u7p+pc0e12+9UUlFJRQUVFQsg/8NhjReqPFDjSXfYGIS2KHQl41UW3hVgoBADhRjIQ18W+tIxkI7BDIwVYLoCPxtAWjh/tq7/2cr/8/Eh0ilJniuQXg3Sr0+GTcknKzLpTKYoZMKFjN4kw9fJu0vkxRnyRIo8Ev35UHC2TWCmZd9IDdozEWED7dMswhLYIwXVqxvtfGDnIXxIagm/JK+IMscxXXZxTQ7Js+sOqy7eJ8277/hqYZlFstowddyhZ7B74xrwiYFPFFsOsfAdZOUTZdwjxXj0HNtpoyVFVToV9VZxmQbp5X9GFpw1996keBFal9fbUpb5xKz2iN4hpoA9RzlpI+EBqcX7FRbLaHOfM+bSv7lK8zKPguYi9SsrzuhzWTggvUi0ovnCOV3Wq+bbNIxw3gJ6Vpt0LJbr3lipeZ3zstVae78DzkFiriHioSkq/4HQP1EyKOV4cOqJhLQLcYncteUnktLFtkkxYdvKY1c4LlrigtGi/fIM/PIrD575Q1QOhhZLdUzY1A2ZPf1E/AMOGRsvPyKH1UcYsQ7YDAmtXQlxklSfnUbWKxU1oKwIK132WxbIdESBN0p8UOmP+mA8jEBXInoy0JeN8RJMleNbLb7fw7dafKnCl0p8qcRMNaYr8LkUnwoxnIe+O3iThK5YdEagM4LeeOGXw+e36QifJONhAu5HoiIIxb7/QphPRZ4b8ikocEORO/JckU9BsRuqPNEQgLYodCejJwsfCujFwy81+FaHvxvo+V6FL7TGh1n4mIbhhUXgPwW+jcTbyAWEMXgdjdfReBUFGPtvtg8WikjUOHaKm2cjONaDZw327YWhATRUcEoRvqHcYdG8rff1h3qcAt3h44wQV0S4IYGCVBdk2uOuLfJskG+LfFsU2qLMFhW2qLHDPTvU26PZCS3Ov0v2zQuhHWproKKBintuuOeGWgpqKfR6I63g8SvFbijzQJkH/be/QiuK0JV6otYPD27hURy6kvEmC7138TYH77LRQ+s3noKeVIzkYrwEMzWYawRpxfzDdfOPhGcfHyXPZckrRdJ7lvTrk+Hr5OMNMu5AJlzmx26QDxbz741/vtCee6pEnhyebd840wTSzDtchLZkxHvj3FlsE8buAxwnZPkMLRf7Rh7WvIK94hCX5zx2evXxs8uPa7JIq6zYJwlRBV6B44ybhaFlsM3KQVRCEoICOCDKtkGIfYkA1+qDPLulOQ/JIjBKqaTJOqlQNyFPJ7XEMLn46hUbPlUDdjUDHgcPhKdsoISIiSty75GCgAzzEQU+ARkcPI3TV5afvLRU02znKd2VoqeharxG+gKjvglLcJzovUdXTZ3Yzl6G8iWWc4ZL9S3W61ou0bNadukG92WbpTc9dzgG76OEH/C7fexW0pmwNNXA9DNeyfIeiTLeyTIBSVKBt49HZO5LTlSor5f1juPl2r8UfBv3a7Lp2+CcCe/xc4v2SLHskmI/osaroM+jYcSjZbzsqhVXQKyy4oU/dkks5jvIvGIH+MXg5C3iFyF1zfqPS0bLTp3CGRk46CPEFOnOKPFEmRcqfVDth4ZgtESi4zaepeF9DoYK6Yuxb7X4Vo2/K/G9Al8r8bUcX8owXozRPAxk4m0y3tzGszg8jUFnFP1iQFcsnsXjWTz9FmLHbTxOQEssGsJQE4BSb2R7IssDd91/z0uLqShyQ5E7itxQTEEJFdVeuB+C9jg8S0FPBt7fxUgxxssxUUUfEmlFlIkqfCrCUBb6kvA+Du9i8C4K7yLwLgJvw9ETgZ4IvIr8L4FJ4E73aMmgyDP7jzJxrgfLWizbCDk5loCA3fbW2zS1QfVDZBzvs8emI2/dfF3h60KfjiZQkOyMDAdk2yDX+v+MsNENjW5ocEM95bfAarf/wo+W/7D3K+Vu9FS4o8YbDUFoi0JHAroXOiO8zsTr1N+vOw3lYawYXysx24C5ZvxsWzrXLjDbfnju2XHyQo70qJL3F8mAIflgQcbsyGdnMm5NPlqTfrP515dJtwbpkp5/tOdrM9d0Nfpy8TAJid64qIWdB7BFiFHgENsFQwTEHHP0EpJRYzwkxXLo1NKjqrxHzzEfU1kmKMUkIstx6NRiwWM4qsh44coGE9OdoqLYuQcbhbFZlGuzBM9KAchpLErLM8yuNkkq1E0s0Pmr6HLg7dPapquUdBnVrnA4eCAidZNrsOgRBa690hCQYRaT3yggA1EVKBkslbu4RNNsp4Le6oNKOGO0WvoCo44xs1eoYNE9bRMHDi1DRlU9jnOGS3XNVmqbLbpgzqFlyqZnxXPTc4d94B7nUCGvWPHojPORmWeDMlS9kuXdb0t7JUkHJksHJUrdSt2XlqL84L6ST8xy3v2c4FsnqMauZ4XzpkukNDkEZNh2SS0WO8Mlp8Nx9iq39jXe81fg4CMmpc7DL8m87zjnPkloX1sVmiBnZs9neGOt2iU2cUkoS8HRAJHWSHdGscdvhzUBaAxFWzQeJ6A3E305+FiCqQr6E38zVfi7EjNVmKnAlzJ8LsGnfAxm4X0qepPQHU+/DUebkf7qyvfk9m+ErXFojMC9IFT5It8buZ7I8UAOFflU+sqwyA0FbiikoJCCIleUeeCeP5oj0B73u344WIAPxfhUhqkqfK3FVA0+V+JTEYaz6Qh7o9Abgbfh9PRE4E04XkbQ8y+EpoGCwUkqru4yO3aDZw1Y1+CPHbh6bVNo6G4//4PGJrB3R9RtnhfPLUfeUQOo8HZlD6IwhrkhxhUJTkizwx0bZFshzwZ5NiiwQak1ym3+O8JmCprd0ERBE4XOr55C51e1kP+wV+xGL378T5Z0nK70lFFQ4U4fDFsj0RGPp4l4noLnKXiZhJdJeJWM3jQM5uJTEabL8Xct5hox17zoZ9v2uYf75zqPzD07Tl4qkN5z9EnpqBUZdyCfHMgnBzJsQ96ZkR598lLtZ4fY15btE1UYyENnIlLcoauN/UeZdh7Erv1QVIVXiFjS3fOGljuFjkNQiumQMuthTSax05wHlbj3SjPtV1h8WJVb4BiOKcHB7bC9vYicIuOug1gvhC2HsFEQFs6HCirNk4v1k4v1U0sM4nMvmbvtVTVgV7gEDSMeR09Epm12DjwoJs8hIAMBGeaDMusFZXFYFQr6y6S1ODXNdipdXntAEcqGq6UvsGrqM1pRNkamnTC4yahpvEhNj/usAY+WydIL5ly0XHVY5xAoQgk75BYu5hd/Ij77Qkz2+eBMNc8kOWqC1C+EoSn7s+6caao/4xG8hFMAWMPNr8Stb82kacYjrcUpKMO5W5rzoBKHlDazuiHnJdMVp3Vw001I/fL6fZI4JMuoqreaeusoJVT4rB6jgdkGmdMQFIaSDByvIsEJaU4ockcx7TynByq8UeuHhmA0heFFInrSMZiDjyWYLMeXSnyrxvcazFRhpgpfyzFZivFCjOSgPwPvUvAiEd0JeBpDvxz3NAZdsXgai84Eejpu43E8mqPRGIa6YBQHoNAbue6464Y8N+S5IZ+KIjfkuSLfBQWu9KIFbbP0fgjawtARg+5EvEnDuywM5OFDCcbK8amSfpBgKBvvU9ATizfheBmCnlvouYXXYXgdhhfh9DyP+K3xZQRwI+DQreTzV4z2rVgF3rXgWI8d+0FxFzC3RkCgiJP7KkcfRCazdT+zGHhDCfZh8aWsCnLjvuXGGOmCOHv8ZYM0a9yxRq41cq1RYIMSK5TboNoW9+xQZ4cW5wWErmh2pQt84Ip6Cupc6QJrXFG5kH/Co6XQFYWuKPpHaPUcelXHGcXOKHZCsTNKXVHpgVo/3KedZYtCRxy9BfiLRLxOQU8aBnLwsQCTpZipxo96zDZitmXtz1b+2UcH5jqPzHfLkFcqpPcCGbhCPvxJxmzImDMZcyWjzmTInvRbkF69uacKM62iM3UYKcLjONy2h8FZyMiwHpXB4ROQloat44aC8sveodISShCQwl4FiGowi57mPHKGd6c0425ZhmPnVogpQFQW2garIqLkbBwElNRYBA5iswBOnGaIT7+UV2maUqRzp/xKZplheOqZC9eXnjVgVb4ELeNlTl6IztjqFHDgkCybkBwEZJhFpNYIyeGEOqOiDq+0BrOOxS51wz/EFHHm8ko5LXbVi4z65lx2ntvUr+CswWJlXW4VPY5zxosumi+7aL7s0g1eM8o2t3Bx75jj3jHHg5Lk47MvRGedC8pQ9UySo01HA5OlA28fD0sRz8tVu1+j7uK5jH0PsJJpywnuKzbcWuZcMtrcInI8u6W49yuwSWowqhow61osVzOAqeMOc9cDh2RxTAU33ER8oo6fvwYVHeiYbBGWAD8/1JXoCP9yRL47/VA17SZAmQcqfXDPF+0ReBKHN6kYzMGnIkyVY6aK/g4ZbTCcKsd4MT7kYSgL/Rl4lYIXieiK+42QDjIOT+LQEf9vhxGoCkFZAAo9keeGXApyKXSKd12Q44oCVxS4osiVviCq8UaDP5qC8TACnTHoSsSbNPTl0g/lDBdjqICO8E00noei2x8vQ+h5cQsvbqE7jJ6X/wgsA48ExJxVOLWUmxMr1jGs3IKD0ggIFdI1hLe/sG/IdkoQEu4s73r+Z89z+yBvdl/qlgDqmiAK2y1nRNkh3hrJVki1Qo4VcqyQb4USK5RZo9oGtbaot/2NsMkFza54sBCavV/8KlxQ5oIyl//CjFaB/PWBFlpFJN8JhQ7/Ct2hD+oC0BiKhxF4HIun8ehKxItUvM3EwF18yMfnEnypxPdazNbjZxPHz9ZNPx/umX10YP6J5Pxz+fnX6qRPjwxfJ6M3yJgz+Uwhn93JJ3fywZH0/0mea39vl//WuHq0GJ2xSLHFjXO4eIZBWwPn1XBeCebGKCw6m5ajoXV15SF5CMjigCrjMfXlBxQX7ZHCHnmmI2qcJ9TYjp2GjBKMTRe5eeyzstqic4nr6FGY3tiSW3otr/J6eol+VoVhcuElSoi46mVoGfOo6EDLmMfZmyH2zg4HP+GDMqwHFCEoyyJ0fNV+BcicW3TqItcJdcbLVvya1zeJKUJZb5mcFqeKNvN5A9aLpovktaCsy6Gsy616meucCdv5azznr/Fom/KaOG9zvXXYPVLSPVIyMFE+OuN8RIY6bU3olSznmyoXmCztHy8ZlCReUKjcUnshIGDHjhPARoa1ojyXbnBoWXBIX+AQkuXeLbVE5NSiI2o4c5lJ78bSCyYcGobMDj5iZ3VZ9U1We4VLm7tuk9GAphGXuu6aDTuxfRe0NWB/DVH2+MsR+VQUeqDIE8Ue9MOcpe4o90RjAFpD0RWLnlQM3MWnIkxXYObXSFiJ6QpMlGC0ECM5GMpCTzpepaA7AV2xv8fDzih0xi4kAU9uo/M2HsejPRb3I1AbgnJfFLnTEdIc5rjSP/yalBZTUOqOKk/U+qAhAA+C0BqGzli8SEPvXbzLR38e+vPQl4V3KXgVjWfB6PTD8yA8D8KzYHSHoCsUXaF4dgtdYXSTtMA2SMLVT36/EHg4sWIt47pdUNRASPieS/qwddji4r3J1hu3c9Y8f3Wj94VDgBerP5Xf321LIGVJsBMibBFrhURLpFjhriXuWiLPEsWWKLVClfV/QdjkggcLZ0prXFHtgmoXusBSZ3r+Ce8/vNFCq4X8Sr4dCuzpK9J8u98Oq31QH4jmcLRHoyOefjS+Nxt9ORjOx3gxvpThexVm6/DzAUjr6p9tO+faBeY7xeaeSc+/VCa9F8iAIflgSj45kM8UMuFNJrzIOJWM2JIew9mOc7OtIlMVXO8yUOuHW+ZwuQqXa3C8CjsD2BkjN1OypkbHiSogpcx4QBYiilDQXn9QhnGfNIPYaQ6J06ySilBUg5oGo+YlUNx2uNpvcbBYZ3qZLSZSprDMMK/qak7Fleyyy7Hpqtdt1mno47LZsjMXoX2V09mbIS5rp72v0H5pZjFlCMuzCx1fJaYMeU3uU1rc0mqM1+wF9G5sk1CC8qXlJ89xKWpxqOlzntFlkD4LxQtcKvrLNYyXaFlwaBjxaBjxaF7nve60g7Y1Sg2TDE5WiEo/F56uFpCm4pUs751y0i/tZECSlG+sRMDtw8Wlp57cN0hJklK6ysgkzLxSiOvcNWjfYDuhxSoow7NHesV+Be4jalDRZ9S7wWvsuOGkJixdt9u783sEHHb1E1PQxqmL0DZdJaHAtnQNduyCjjaczRFui2Rn+r5IkSeKvBbOkVFR4oZqTzT4ou0WnsWhJxUjOfhcgmnaxkzlAsJSfCrCSC6G7+LtHbxJw4tE+g4NTSBtp/RXW5qniXiaiM7b6FhYH9YEoMQTRW6/x8O7bvRVYj6V7rCQgpKF7YnKBY0PgvEoFs9S8CYLPdl4l413mXibjJdReBKEDl88DaDnSRCeBuNJCJ6E4Gkonv8jsA+RsHIW3cGH9cvBu5JhAz8uXl1yK2r3+Yu4YrjMxnmNjReS8tZ3v7TofeEQ5LPYz0PYn7rLj7Iq2AEh1oiwxO2bSLZE9k1k30TuTRTdRKnlPxA6ocUJrc50hDSB951R44xKF1Q4o2KBH21i+f+3RyuE0JJjjxx75NnSl6P0Rak9ip1RRqFXeGhn2Tri8SwFrzPxltZdKx9jRZgqw0wVftSBPABp5SFtO8mjPXMdB8jTY/MvlEiPJunTJ0PGZNSGTLiSSc/5KW8y4UVGnck7s7kuHfJY7u+6LRPFeJGIfHfE2CDGBnHWCL4Jn5vIS9z+8MHFsPAjp88yHVVkPCTPoHB21VHFRYdkGMVPsZ5QYpc5zaCsyqBzicvYlNvfZ7+30zYLXfg4bi7L0yoo0csp1curuppVqh+WKK+hjwtGLFdvrjmtjYvGi118mBLu8tv5CIpIMUmoMe1XWCx8YrWEGouC9hJ5Ta4TajBzFrxqu+uoMpQuLpXTWHxSnV1dn0dBm0H6LBS0eVUN1p6/vlzTnPm80fJzxku0TVeZOPM7Bhx2CjxCDZMMT1eLz74QdUfj10jol3YyMFnaL+5ocJpkWYVUV+OV4lzVa24r1x7jWLaHS8MY2jfYjmuyCEhx7ZFafUhxuYQak4o+dG9wXHPadN6I4eoN7uBIifAYWSOLdYdkoH557flrS/eIYvl67N4LnQvwtEOoHf5yRA4Fue7I90SRFwo8UEill+zKKaj2RGMAOsLxMgH9GQsTmQp66AiL8SEfIzl4l43eTLxMxrP4BYQR6AinFw/pCG+jK+n3fmlbNOpDUOWDUg/kU5FLQY4rsinIoSKHSmdZ4IpCCoqpKKSi2A0lVBRTUEFFrR9aw9ARhxepeJWB3kz0pqMnEc+j6Qg7/fDEH0/80RmIzkB0LjjsXsjzUPw/eIMeLynyTGAAAAAASUVORK5CYII=" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"&gt;&lt;/a&gt;&lt;/div&gt;
&lt;a href="http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470671696,subjectCd-LS41,descCd-description.html#.UGr6kOJ8BJM.blogger"&gt;Wiley: Systematics: A Course of Lectures&lt;/a&gt;&lt;br /&gt;
&lt;br /&gt;
&lt;div style="text-align: justify;"&gt;
&lt;i&gt;Systematics: A Course of Lectures&lt;/i&gt; is designed for use in an 
advanced undergraduate or introductory graduate level course in 
systematics and is meant to present core systematic concepts and 
literature. The book covers topics such as the history of systematic 
thinking and fundamental concepts in the field including species 
concepts, homology, and hypothesis testing. Analytical methods are 
covered in detail with chapters devoted to sequence alignment, 
optimality criteria, and methods such as distance, parsimony, maximum 
likelihood and Bayesian approaches. Trees and tree searching, consensus 
and super-tree methods, support measures, and other relevant topics are 
each covered in their own sections.

&lt;/div&gt;
&lt;br /&gt;
&lt;br /&gt;
Tabla de contenido:&lt;br /&gt;
&lt;br /&gt;
&lt;div class="productDetail-richDataText"&gt;
&lt;b&gt;Preface xv&lt;/b&gt;
Using these notes xv&lt;br /&gt;
Acknowledgments&amp;nbsp; xvi&lt;br /&gt;
&lt;b&gt;List of algorithms xix&lt;/b&gt;&lt;br /&gt;
&lt;b&gt;I Fundamentals 1&lt;/b&gt;&lt;br /&gt;
&lt;b&gt;1 History 2&lt;/b&gt;&lt;br /&gt;
1.1 Aristotle&amp;nbsp; 2&lt;br /&gt;
1.2 Theophrastus 3&lt;br /&gt;
1.3 Pierre Belon 4&lt;br /&gt;
1.4 Carolus Linnaeus 4&lt;br /&gt;
1.5 Georges Louis Leclerc, Comte de Buffon&amp;nbsp; 6&lt;br /&gt;
1.6 Jean-Baptiste Lamarck 7&lt;br /&gt;
1.7 Georges Cuvier&amp;nbsp; 8&lt;br /&gt;
1.8 ´Etienne Geoffroy Saint-Hilaire&amp;nbsp; 8&lt;br /&gt;
1.9 JohannWolfgang von Goethe 8&lt;br /&gt;
1.10 Lorenz Oken 9&lt;br /&gt;
1.11 Richard Owen 9&lt;br /&gt;
1.12 Charles Darwin&amp;nbsp; 9&lt;br /&gt;
1.13 Stammb¨aume&amp;nbsp; 12&lt;br /&gt;
1.14 Evolutionary Taxonomy 14&lt;br /&gt;
1.15 Phenetics 15&lt;br /&gt;
1.16 Phylogenetic Systematics&amp;nbsp; 16&lt;br /&gt;
1.16.1 Hennig’s Three Questions 16&lt;br /&gt;
1.17 Molecules and Morphology&amp;nbsp; 18&lt;br /&gt;
1.18 We are all Cladists 18&lt;br /&gt;
1.19 Exercises 19&lt;br /&gt;
&lt;b&gt;2 Fundamental Concepts 20&lt;/b&gt;&lt;br /&gt;
2.1 Characters 20&lt;br /&gt;
2.1.1 Classes of Characters and Total Evidence&amp;nbsp; 22&lt;br /&gt;
2.1.2 Ontogeny, Tokogeny, and Phylogeny&amp;nbsp; 23&lt;br /&gt;
2.1.3 Characters and Character States 23&lt;br /&gt;
2.2 Taxa 26&lt;br /&gt;
2.3 Graphs, Trees, and Networks 28&lt;br /&gt;
2.3.1 Graphs and Trees 30&lt;br /&gt;
2.3.2 Enumeration 31&lt;br /&gt;
2.3.3 Networks&amp;nbsp; 33&lt;br /&gt;
2.3.4 Mono-, Para-, and Polyphyly 33&lt;br /&gt;
2.3.5 Splits and Convexity&amp;nbsp; 38&lt;br /&gt;
2.3.6 Apomorphy, Plesiomorphy, and Homoplasy&amp;nbsp; 39&lt;br /&gt;
2.3.7 Gene Trees and Species Trees 41&lt;br /&gt;
2.4 Polarity and Rooting 43&lt;br /&gt;
2.4.1 Stratigraphy&amp;nbsp; 43&lt;br /&gt;
2.4.2 Ontogeny&amp;nbsp; 43&lt;br /&gt;
2.4.3 Outgroups&amp;nbsp; 45&lt;br /&gt;
2.5 Optimality 49&lt;br /&gt;
2.6 Homology&amp;nbsp; 49&lt;br /&gt;
2.7 Exercises&amp;nbsp; 50&lt;br /&gt;
&lt;b&gt;3 Species Concepts, Definitions, and Issues 53&lt;/b&gt;&lt;br /&gt;
3.1 Typological or Taxonomic Species Concept&amp;nbsp; 54&lt;br /&gt;
3.2 Biological Species Concept&amp;nbsp; 54&lt;br /&gt;
3.2.1 Criticisms of the BSC 55&lt;br /&gt;
3.3 Phylogenetic Species Concept(s) 56&lt;br /&gt;
3.3.1 Autapomorphic/Monophyletic Species Concept 56&lt;br /&gt;
3.3.2 Diagnostic/Phylogenetic Species Concept&amp;nbsp; 58&lt;br /&gt;
3.4 Lineage Species Concepts&amp;nbsp; 59&lt;br /&gt;
3.4.1 Hennigian Species&amp;nbsp; 59&lt;br /&gt;
3.4.2 Evolutionary Species&amp;nbsp; 60&lt;br /&gt;
3.4.3 Criticisms of Lineage-Based Species&amp;nbsp; 61&lt;br /&gt;
3.5 Species as Individuals or Classes&amp;nbsp; 62&lt;br /&gt;
3.6 Monoism and Pluralism&amp;nbsp; 63&lt;br /&gt;
3.7 Pattern and Process&amp;nbsp; 63&lt;br /&gt;
3.8 Species Nominalism&amp;nbsp; 64&lt;br /&gt;
3.9 Do Species Concepts Matter?&amp;nbsp; 65&lt;br /&gt;
3.10 Exercises&amp;nbsp; 65&lt;br /&gt;
&lt;b&gt;4 Hypothesis Testing and the Philosophy of Science 67&lt;/b&gt;&lt;br /&gt;
4.1 Forms of Scientific Reasoning 67&lt;br /&gt;
4.1.1 The Ancients&amp;nbsp; 67&lt;br /&gt;
4.1.2 Ockham’s Razor&amp;nbsp; 68&lt;br /&gt;
4.1.3 Modes of Scientific Inference&amp;nbsp; 69&lt;br /&gt;
4.1.4 Induction 69&lt;br /&gt;
4.1.5 Deduction 69&lt;br /&gt;
4.1.6 Abduction 70&lt;br /&gt;
4.1.7 Hypothetico-Deduction&amp;nbsp; 71&lt;br /&gt;
4.2 Other Philosophical Issues 75&lt;br /&gt;
4.2.1 Minimization, Transformation, and Weighting 75&lt;br /&gt;
4.3 Quotidian Importance&amp;nbsp; 76&lt;br /&gt;
4.4 Exercises&amp;nbsp; 76&lt;br /&gt;
&lt;b&gt;5 Computational Concepts 77&lt;/b&gt;&lt;br /&gt;
5.1 Problems, Algorithms, and Complexity 77&lt;br /&gt;
5.1.1 Computer Science Basics&amp;nbsp; 77&lt;br /&gt;
5.1.2 Algorithms&amp;nbsp; 79&lt;br /&gt;
5.1.3 Asymptotic Notation 79&lt;br /&gt;
5.1.4 Complexity&amp;nbsp; 80&lt;br /&gt;
5.1.5 Non-Deterministic Complexity&amp;nbsp; 82&lt;br /&gt;
5.1.6 Complexity Classes: &lt;i&gt;P&lt;/i&gt; and &lt;i&gt;NP&amp;nbsp;&lt;/i&gt; 82&lt;br /&gt;
5.2 An Example: The Traveling Salesman Problem&amp;nbsp; 84&lt;br /&gt;
5.3 Heuristic Solutions&amp;nbsp; 85&lt;br /&gt;
5.4 Metricity, and Untrametricity&amp;nbsp; 86&lt;br /&gt;
5.5 NP–Complete Problems in Systematics&amp;nbsp; 87&lt;br /&gt;
5.6 Exercises 88&lt;br /&gt;
&lt;b&gt;6 Statistical and Mathematical Basics 89&lt;/b&gt;&lt;br /&gt;
6.1 Theory of Statistics&amp;nbsp; 89&lt;br /&gt;
6.1.1 Probability&amp;nbsp; 89&lt;br /&gt;
6.1.2 Conditional Probability&amp;nbsp; 91&lt;br /&gt;
6.1.3 Distributions 92&lt;br /&gt;
6.1.4 Statistical Inference&amp;nbsp; 98&lt;br /&gt;
6.1.5 Prior and Posterior Distributions&amp;nbsp; 99&lt;br /&gt;
6.1.6 Bayes Estimators 100&lt;br /&gt;
6.1.7 Maximum Likelihood Estimators&amp;nbsp; 101&lt;br /&gt;
6.1.8 Properties of Estimators 101&lt;br /&gt;
6.2 Matrix Algebra, Differential Equations, and Markov Models 102&lt;br /&gt;
6.2.1 Basics&amp;nbsp; 102&lt;br /&gt;
6.2.2 Gaussian Elimination 102&lt;br /&gt;
6.2.3 Differential Equations&amp;nbsp; 104&lt;br /&gt;
6.2.4 Determining Eigenvalues&amp;nbsp; 105&lt;br /&gt;
6.2.5 MarkovMatrices&amp;nbsp; 106&lt;br /&gt;
6.3 Exercises&amp;nbsp; 107&lt;br /&gt;
&lt;b&gt;II Homology 109&lt;/b&gt;&lt;br /&gt;
&lt;b&gt;7 Homology 110&lt;/b&gt;&lt;br /&gt;
7.1 Pre-Evolutionary Concepts110&lt;br /&gt;
7.1.1 Aristotle&amp;nbsp; 110&lt;br /&gt;
7.1.2 Pierre Belon&amp;nbsp; 110&lt;br /&gt;
7.1.3 ´Etienne Geoffroy Saint-Hilaire&amp;nbsp; 111&lt;br /&gt;
7.1.4 Richard Owen 112&lt;br /&gt;
7.2 Charles Darwin&amp;nbsp; 113&lt;br /&gt;
7.3 E. Ray Lankester&amp;nbsp; 114&lt;br /&gt;
7.4 Adolf Remane&amp;nbsp; 114&lt;br /&gt;
7.5 Four Types of Homology&amp;nbsp; 115&lt;br /&gt;
7.5.1 Classical View&amp;nbsp; 115&lt;br /&gt;
7.5.2 Evolutionary Taxonomy&amp;nbsp; 115&lt;br /&gt;
7.5.3 Phenetic Homology&amp;nbsp; 116&lt;br /&gt;
7.5.4 Cladistic Homology&amp;nbsp; 116&lt;br /&gt;
7.5.5 Types of Homology&amp;nbsp; 117&lt;br /&gt;
7.6 Dynamic and Static Homology&amp;nbsp; 118&lt;br /&gt;
7.7 Exercises&amp;nbsp; 120&lt;br /&gt;
&lt;b&gt;8 Sequence Alignment 121&lt;/b&gt;&lt;br /&gt;
8.1 Background&amp;nbsp; 121&lt;br /&gt;
8.2 “Informal” Alignment&amp;nbsp; 121&lt;br /&gt;
8.3 Sequences&amp;nbsp; 121&lt;br /&gt;
8.3.1 Alphabets&amp;nbsp; 122&lt;br /&gt;
8.3.2 Transformations&amp;nbsp; 123&lt;br /&gt;
8.3.3 Distances&amp;nbsp; 123&lt;br /&gt;
8.4 Pairwise StringMatching 123&lt;br /&gt;
8.4.1 An Example&amp;nbsp; 127&lt;br /&gt;
8.4.2 Reducing Complexity&amp;nbsp; 129&lt;br /&gt;
8.4.3 Other Indel Weights&amp;nbsp; 130&lt;br /&gt;
8.5 Multiple Sequence Alignment&amp;nbsp; 131&lt;br /&gt;
8.5.1 The Tree Alignment Problem&amp;nbsp; 133&lt;br /&gt;
8.5.2 Trees and Alignment&amp;nbsp; 133&lt;br /&gt;
8.5.3 Exact Solutions 134&lt;br /&gt;
8.5.4 Polynomial Time Approximate Schemes&amp;nbsp; 134&lt;br /&gt;
8.5.5 Heuristic Multiple Sequence Alignment&amp;nbsp; 134&lt;br /&gt;
8.5.6 Implementations&amp;nbsp; 135&lt;br /&gt;
8.5.7 Structural Alignment&amp;nbsp; 139&lt;br /&gt;
8.6 Exercises 145&lt;br /&gt;
&lt;b&gt;III Optimality Criteria 147&lt;/b&gt;&lt;br /&gt;
&lt;b&gt;9 Optimality Criteria&lt;/b&gt;&lt;i&gt;−&lt;/i&gt;&lt;b&gt;Distance 148&lt;/b&gt;&lt;br /&gt;
9.1 Why Distance? 148&lt;br /&gt;
9.1.1 Benefits&amp;nbsp; 149&lt;br /&gt;
9.1.2 Drawbacks 149&lt;br /&gt;
9.2 Distance Functions&amp;nbsp; 150&lt;br /&gt;
9.2.1 Metricity&amp;nbsp; 150&lt;br /&gt;
9.3 Ultrametric Trees&amp;nbsp; 150&lt;br /&gt;
9.4 Additive Trees&amp;nbsp; 152&lt;br /&gt;
9.4.1 Farris Transform&amp;nbsp; 153&lt;br /&gt;
9.4.2 Buneman Trees&amp;nbsp; 154&lt;br /&gt;
9.5 General Distances&amp;nbsp; 156&lt;br /&gt;
9.5.1 Phenetic Clustering 157&lt;br /&gt;
9.5.2 Percent Standard Deviation 160&lt;br /&gt;
9.5.3 Minimizing Length&amp;nbsp; 163&lt;br /&gt;
9.6 Comparisons 170&lt;br /&gt;
9.7 Exercises&amp;nbsp; 171&lt;br /&gt;
&lt;b&gt;10 Optimality Criteria&lt;/b&gt;&lt;i&gt;−&lt;/i&gt;&lt;b&gt;Parsimony 173&lt;/b&gt;&lt;br /&gt;
10.1 Perfect Phylogeny&amp;nbsp; 174&lt;br /&gt;
10.2 Static Homology Characters&amp;nbsp; 174&lt;br /&gt;
10.2.1 Additive Characters&amp;nbsp; 175&lt;br /&gt;
10.2.2 Non-Additive Characters&amp;nbsp; 179&lt;br /&gt;
10.2.3 Matrix Characters&amp;nbsp; 182&lt;br /&gt;
10.3 Missing Data&amp;nbsp; 184&lt;br /&gt;
10.4 Edge Transformation Assignments&amp;nbsp; 187&lt;br /&gt;
10.5 Collapsing Branches&amp;nbsp; 188&lt;br /&gt;
10.6 Dynamic Homology&amp;nbsp; 188&lt;br /&gt;
10.7 Dynamic and Static Homology&amp;nbsp; 189&lt;br /&gt;
10.8 Sequences as Characters 190&lt;br /&gt;
10.9 The Tree Alignment Problem on Trees&amp;nbsp; 191&lt;br /&gt;
10.9.1 Exact Solutions&amp;nbsp; 191&lt;br /&gt;
10.9.2 Heuristic Solutions 191&lt;br /&gt;
10.9.3 Lifted Alignments, Fixed-States, and Search-Based Heuristics&amp;nbsp; 193&lt;br /&gt;
10.9.4 Iterative Improvement&amp;nbsp; 197&lt;br /&gt;
10.10 Performance of Heuristic Solutions 198&lt;br /&gt;
10.11 Parameter Sensitivity&amp;nbsp; 198&lt;br /&gt;
10.11.1 Sensitivity Analysis&amp;nbsp; 199&lt;br /&gt;
10.12 Implied Alignment&amp;nbsp; 199&lt;br /&gt;
10.13 Rearrangement&amp;nbsp; 204&lt;br /&gt;
10.13.1 Sequence Characters with Moves&amp;nbsp; 204&lt;br /&gt;
10.13.2Gene Order Rearrangement 205&lt;br /&gt;
10.13.3Median Evaluation&amp;nbsp; 207&lt;br /&gt;
10.13.4Combination ofMethods 207&lt;br /&gt;
10.14 Horizontal Gene Transfer, Hybridization, and Phylogenetic Networks&amp;nbsp; 209&lt;br /&gt;
10.15 Exercises&amp;nbsp; 210&lt;br /&gt;
&lt;b&gt;11 Optimality Criteria&lt;/b&gt;&lt;i&gt;−&lt;/i&gt;&lt;b&gt;Likelihood 213&lt;/b&gt;&lt;br /&gt;
11.1 Motivation&amp;nbsp; 213&lt;br /&gt;
11.1.1 Felsenstein’s Example&amp;nbsp; 213&lt;br /&gt;
11.2 Maximum Likelihood and Trees&amp;nbsp; 216&lt;br /&gt;
11.2.1 Nuisance Parameters&amp;nbsp; 216&lt;br /&gt;
11.3 Types of Likelihood&amp;nbsp; 217&lt;br /&gt;
11.3.1 Flavors ofMaximum Relative Likelihood 217&lt;br /&gt;
11.4 Static-Homology Characters&amp;nbsp; 218&lt;br /&gt;
11.4.1 Models&amp;nbsp; 218&lt;br /&gt;
11.4.2 Rate Variation&amp;nbsp; 219&lt;br /&gt;
11.4.3 Calculating &lt;i&gt;p&lt;/i&gt;(&lt;i&gt;D|T, θ&lt;/i&gt;)&amp;nbsp; 221&lt;br /&gt;
11.4.4 Links Between Likelihood and Parsimony&amp;nbsp; 222&lt;br /&gt;
11.4.5 A Note onMissing Data 224&lt;br /&gt;
11.5 Dynamic-Homology Characters&amp;nbsp; 224&lt;br /&gt;
11.5.1 Sequence Characters&amp;nbsp; 225&lt;br /&gt;
11.5.2 CalculatingML Pairwise Alignment&amp;nbsp; 227&lt;br /&gt;
11.5.3 MLMultiple Alignment&amp;nbsp; 230&lt;br /&gt;
11.5.4 Maximum Likelihood Tree Alignment Problem 230&lt;br /&gt;
11.5.5 Genomic Rearrangement&amp;nbsp; 232&lt;br /&gt;
11.5.6 Phylogenetic Networks&amp;nbsp; 234&lt;br /&gt;
11.6 Hypothesis Testing&amp;nbsp; 234&lt;br /&gt;
11.6.1 Likelihood Ratios&amp;nbsp; 234&lt;br /&gt;
11.6.2 Parameters and Fit&amp;nbsp; 236&lt;br /&gt;
11.7 Exercises&amp;nbsp; 238&lt;br /&gt;
&lt;b&gt;12 Optimality Criteria&lt;/b&gt;&lt;i&gt;−&lt;/i&gt;&lt;b&gt;Posterior Probability 240&lt;/b&gt;&lt;br /&gt;
12.1 Bayes in Systematics&amp;nbsp; 240&lt;br /&gt;
12.2 Priors&amp;nbsp; 241&lt;br /&gt;
12.2.1 Trees&amp;nbsp; 241&lt;br /&gt;
12.2.2 Nuisance Parameters&amp;nbsp; 242&lt;br /&gt;
12.3 Techniques 246&lt;br /&gt;
12.3.1 Markov ChainMonte Carlo&amp;nbsp; 246&lt;br /&gt;
12.3.2 Metropolis–Hastings Algorithm 246&lt;br /&gt;
12.3.3 Single Component 248&lt;br /&gt;
12.3.4 Gibbs Sampler&amp;nbsp; 249&lt;br /&gt;
12.3.5 Bayesian MC3 249&lt;br /&gt;
12.3.6 Summary of Posterior&amp;nbsp; 250&lt;br /&gt;
12.4 Topologies and Clades&amp;nbsp; 252&lt;br /&gt;
12.5 Optimality versus Support&amp;nbsp; 254&lt;br /&gt;
12.6 Dynamic Homology&amp;nbsp; 254&lt;br /&gt;
12.6.1 Hidden Markov Models&amp;nbsp; 255&lt;br /&gt;
12.6.2 An Example 256&lt;br /&gt;
12.6.3 Three Questions—Three Algorithms&amp;nbsp; 258&lt;br /&gt;
12.6.4 HMMAlignment&amp;nbsp; 262&lt;br /&gt;
12.6.5 Bayesian Tree Alignment&amp;nbsp; 264&lt;br /&gt;
12.6.6 Implementations&amp;nbsp; 264&lt;br /&gt;
12.7 Rearrangement&amp;nbsp; 266&lt;br /&gt;
12.8 Criticisms of BayesianMethods&amp;nbsp; 267&lt;br /&gt;
12.9 Exercises&amp;nbsp; 267&lt;br /&gt;
&lt;b&gt;13 Comparison of Optimality Criteria 269&lt;/b&gt;&lt;br /&gt;
13.1 Distance and CharacterMethods&amp;nbsp; 269&lt;br /&gt;
13.2 Epistemology 270&lt;br /&gt;
13.2.1 Ockham’s Razor and Popperian Argumentation&amp;nbsp; 271&lt;br /&gt;
13.2.2 Parsimony and the Evolutionary Process&amp;nbsp; 272&lt;br /&gt;
13.2.3 Induction and Statistical Estimation&amp;nbsp; 272&lt;br /&gt;
13.2.4 Hypothesis Testing and Optimality Criteria&amp;nbsp; 272&lt;br /&gt;
13.3 Statistical Behavior&amp;nbsp; 273&lt;br /&gt;
13.3.1 Probability&amp;nbsp; 273&lt;br /&gt;
13.3.2 Consistency&amp;nbsp; 274&lt;br /&gt;
13.3.3 Efficiency&amp;nbsp; 281&lt;br /&gt;
13.3.4 Robustness&amp;nbsp; 282&lt;br /&gt;
13.4 Performance 282&lt;br /&gt;
13.4.1 Long-Branch Attraction 283&lt;br /&gt;
13.4.2 Congruence&amp;nbsp; 285&lt;br /&gt;
13.5 Convergence&amp;nbsp; 285&lt;br /&gt;
13.6 CanWe Argue Optimality Criteria? 286&lt;br /&gt;
13.7 Exercises 287&lt;br /&gt;
&lt;b&gt;IV Trees 289&lt;/b&gt;&lt;br /&gt;
&lt;b&gt;14 Tree Searching 290&lt;/b&gt;&lt;br /&gt;
14.1 Exact Solutions&amp;nbsp; 290&lt;br /&gt;
14.1.1 Explicit Enumeration 290&lt;br /&gt;
14.1.2 Implicit Enumeration—Branch-and-Bound&amp;nbsp; 292&lt;br /&gt;
14.2 Heuristic Solutions 294&lt;br /&gt;
14.2.1 Local versus Global Optima 294&lt;br /&gt;
14.3 Trajectory Search 296&lt;br /&gt;
14.3.1 Wagner Algorithm 296&lt;br /&gt;
14.3.2 Branch-Swapping Refinement&amp;nbsp; 298&lt;br /&gt;
14.3.3 Swapping as Distance 301&lt;br /&gt;
14.3.4 Depth-First versus Breadth-First Searching&amp;nbsp; 302&lt;br /&gt;
14.4 Randomization&amp;nbsp; 304&lt;br /&gt;
14.5 Perturbation&amp;nbsp; 305&lt;br /&gt;
14.6 Sectorial Searches and Disc-Covering Methods&amp;nbsp; 309&lt;br /&gt;
14.6.1 Sectorial Searches&amp;nbsp; 309&lt;br /&gt;
14.6.2 Disc-CoveringMethods&amp;nbsp; 310&lt;br /&gt;
14.7 Simulated Annealing&amp;nbsp; 312&lt;br /&gt;
14.8 Genetic Algorithm&amp;nbsp; 316&lt;br /&gt;
14.9 Synthesis and Stopping 318&lt;br /&gt;
14.10 Empirical Examples&amp;nbsp; 319&lt;br /&gt;
14.11 Exercises 323&lt;br /&gt;
&lt;b&gt;15 Support 324&lt;/b&gt;&lt;br /&gt;
15.1 ResamplingMeasures 324&lt;br /&gt;
15.1.1 Bootstrap&amp;nbsp; 325&lt;br /&gt;
15.1.2 Criticisms of the Bootstrap&amp;nbsp; 326&lt;br /&gt;
15.1.3 Jackknife&amp;nbsp; 328&lt;br /&gt;
15.1.4 Resampling and Dynamic Homology Characters&amp;nbsp; 329&lt;br /&gt;
15.2 Optimality-BasedMeasures&amp;nbsp; 329&lt;br /&gt;
15.2.1 Parsimony&amp;nbsp; 330&lt;br /&gt;
15.2.2 Likelihood 332&lt;br /&gt;
15.2.3 Bayesian Posterior Probability&amp;nbsp; 334&lt;br /&gt;
15.2.4 Strengths of Optimality-Based Support&amp;nbsp; 335&lt;br /&gt;
15.3 Parameter-BasedMeasures 336&lt;br /&gt;
15.4 Comparison of Support Measures—Optimal and Average&amp;nbsp; 336&lt;br /&gt;
15.5 Which to Choose?&amp;nbsp; 339&lt;br /&gt;
15.6 Exercises&amp;nbsp; 339&lt;br /&gt;
&lt;b&gt;16 Consensus, Congruence, and Supertrees 341&lt;/b&gt;&lt;br /&gt;
16.1 Consensus TreeMethods&amp;nbsp; 341&lt;br /&gt;
16.1.1 Motivations&amp;nbsp; 341&lt;br /&gt;
16.1.2 Adams I and II&amp;nbsp; 341&lt;br /&gt;
16.1.3 Gareth Nelson&amp;nbsp; 344&lt;br /&gt;
16.1.4 Majority Rule&amp;nbsp; 347&lt;br /&gt;
16.1.5 Strict&amp;nbsp; 347&lt;br /&gt;
16.1.6 Semi-Strict/Combinable Components&amp;nbsp; 348&lt;br /&gt;
16.1.7 Minimally Pruned 348&lt;br /&gt;
16.1.8 When to UseWhat?&amp;nbsp; 350&lt;br /&gt;
16.2 Supertrees 350&lt;br /&gt;
16.2.1 Overview&amp;nbsp; 350&lt;br /&gt;
16.2.2 The Impossibility of the Reasonable&amp;nbsp; 350&lt;br /&gt;
16.2.3 Graph-BasedMethods 353&lt;br /&gt;
16.2.4 Strict Consensus Supertree&amp;nbsp; 355&lt;br /&gt;
16.2.5 MR-Based&amp;nbsp; 355&lt;br /&gt;
16.2.6 Distance-Based Method&amp;nbsp; 358&lt;br /&gt;
16.2.7 Supertrees or Supermatrices?&amp;nbsp; 360&lt;br /&gt;
16.3 Exercises&amp;nbsp; 361&lt;br /&gt;
&lt;b&gt;V Applications 363&lt;/b&gt;&lt;br /&gt;
&lt;b&gt;17 Clocks and Rates 364&lt;/b&gt;&lt;br /&gt;
17.1 The Molecular Clock&amp;nbsp; 364&lt;br /&gt;
17.2 Dating&amp;nbsp; 365&lt;br /&gt;
17.3 Testing Clocks&amp;nbsp; 365&lt;br /&gt;
17.3.1 Langley–Fitch&amp;nbsp; 365&lt;br /&gt;
17.3.2 Farris&amp;nbsp; 366&lt;br /&gt;
17.3.3 Felsenstein&amp;nbsp; 367&lt;br /&gt;
17.4 Relaxed ClockModels&amp;nbsp; 368&lt;br /&gt;
17.4.1 Local Clocks&amp;nbsp; 368&lt;br /&gt;
17.4.2 Rate Smoothing&amp;nbsp; 368&lt;br /&gt;
17.4.3 Bayesian Clock&amp;nbsp; 369&lt;br /&gt;
17.5 Implementations&amp;nbsp; 369&lt;br /&gt;
17.5.1 r8s&amp;nbsp; 369&lt;br /&gt;
17.5.2 MULTIDIVTIME 370&lt;br /&gt;
17.5.3 BEAST&amp;nbsp; 370&lt;br /&gt;
17.6 Criticisms&amp;nbsp; 370&lt;br /&gt;
17.7 Molecular Dates?&amp;nbsp; 373&lt;br /&gt;
17.8 Exercises&amp;nbsp; 373&lt;br /&gt;
&lt;b&gt;A Mathematical Notation 374&lt;/b&gt;&lt;br /&gt;
&lt;b&gt;Bibliography 376&lt;/b&gt;&lt;br /&gt;
&lt;b&gt;Index 415&lt;/b&gt;&lt;br /&gt;
&lt;i&gt;Color plate section between pp. 76 and 77&lt;/i&gt;&lt;/div&gt;
</description><link>http://cladisticaybiogeografia.blogspot.com/2012/10/nuevo-libro-systematics-course-of.html</link><author>noreply@blogger.com (Jonathan Liria)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-386501427852785102</guid><pubDate>Thu, 27 Sep 2012 15:12:00 +0000</pubDate><atom:updated>2012-09-27T08:12:10.010-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">Distribución</category><category domain="http://www.blogger.com/atom/ns#">biogeografía</category><category domain="http://www.blogger.com/atom/ns#">curso</category><category domain="http://www.blogger.com/atom/ns#">Conservación</category><category domain="http://www.blogger.com/atom/ns#">Modelo</category><title>Curso: Modelos de distribución de especies...</title><description>&lt;div style="text-align: justify;"&gt;
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&lt;i&gt;&lt;b&gt;Uso de bases de datos de biodiversidad en los Modelos de distribución de especies e índices evolutivos para la Conservación.&lt;/b&gt;&lt;/i&gt;&lt;/div&gt;
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...y aca les coloco el afiche:&lt;/div&gt;
&lt;br /&gt;
&lt;a href="http://www.4shared.com/office/IjbpvNJx/AficheCursoModeladoSNDB.html" target="_blank"&gt;&lt;img border="0" height="400" src="http://dc523.4shared.com/img/IjbpvNJx/AficheCursoModeladoSNDB.pdf" width="281" /&gt;&lt;/a&gt;</description><link>http://cladisticaybiogeografia.blogspot.com/2012/09/curso-modelos-de-distribucion-de.html</link><author>noreply@blogger.com (Jonathan Liria)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-7568047143036437725</guid><pubDate>Sun, 16 Sep 2012 12:38:00 +0000</pubDate><atom:updated>2012-09-16T05:47:30.009-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">molecular</category><category domain="http://www.blogger.com/atom/ns#">alineamiento</category><category domain="http://www.blogger.com/atom/ns#">TnT</category><category domain="http://www.blogger.com/atom/ns#">Culicini</category><category domain="http://www.blogger.com/atom/ns#">parafilia</category><category domain="http://www.blogger.com/atom/ns#">secuencias</category><category domain="http://www.blogger.com/atom/ns#">megafilogenias</category><category domain="http://www.blogger.com/atom/ns#">COI</category><category domain="http://www.blogger.com/atom/ns#">GenBank</category><category domain="http://www.blogger.com/atom/ns#">monofilia</category><category domain="http://www.blogger.com/atom/ns#">parsimonia</category><category domain="http://www.blogger.com/atom/ns#">cladismo</category><title>Filogenia molecular en Culicini a partir de tres marcadores moleculares</title><description>&lt;br /&gt;
&lt;div align="CENTER" style="margin-bottom: 0cm;"&gt;
&lt;b&gt;FILOGENIA MOLECULAR EN
CULICINI (DIPTERA: CULICIDAE): UN ANÁLISIS UTILIZANDO GenBank-to-TNT
Y PARSIMONIA CON TNT&lt;/b&gt;.&lt;/div&gt;
&lt;div align="CENTER" style="margin-bottom: 0cm;"&gt;
&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="CENTER" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="CENTER" style="margin-bottom: 0cm;"&gt;
&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;b&gt;Introducción&lt;/b&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Culicini contiene
algunos de los vectores más importantes en cuanto a la transmisión
de distintos patógenos, como: Encefalitis Equina Venezolana,
Encefalitis Equina de Este, filarias, entre otros. Esta tribu incluye
a 789 especies clasificadas en cuatro géneros: &lt;a href="http://www.mosquitocatalog.org/taxon_descr.aspx?ID=101"&gt;&lt;i&gt;Culex&lt;/i&gt;&lt;/a&gt;
(amplia distribución), &lt;a href="http://www.mosquitocatalog.org/taxon_descr.aspx?ID=26"&gt;&lt;i&gt;Deinocerites&lt;/i&gt;&lt;/a&gt;
(Neotropical) y &lt;a href="http://www.mosquitocatalog.org/taxon_descr.aspx?ID=29"&gt;&lt;i&gt;Galindomyia&lt;/i&gt;&lt;/a&gt;
(Neotropical)&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Estudios previos han
indicado que &lt;i&gt;Deinocerites&lt;/i&gt; es un grupo incluido en el género
&lt;i&gt;Culex&lt;/i&gt; (Mallampalli 1995; Liria y Navarro 2000). En este
sentido, Liria y Navarro (2000) propusieron la inclusión de este
taxa como un subgénero: &lt;i&gt;Culex (Deinocerites)&lt;/i&gt;. Sin embargo
esta propuesta no fue acogida entre los taxónomos de Culicidae,
debido a las siguientes consideraciones:  
&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
“&lt;i&gt;Navarro &amp;amp; Liria
(2000) formally reduced genus Deinocerites to subgeneric
status in genus &lt;/i&gt;&lt;i&gt;Culex, but this action has not been widely
accepted because this group of species is diagnosed by many unique
(autapomorphic) features in the immature and adult stages.
Autapomorphic features are normally excluded from phylogenetic
studies because they are uninformative in the context of cladistic
analyses. This does not mean, however, that autapomorphies should be
disregarded as denotations of taxonomic rank, providing that doing so
does not conflict with the principle of recognizing only monophyletic
groups in classifications. Autapomorphies are a measure of (often
rapid) divergence and adaptive radiation, which traditional
taxonomists have intuitively taken into consideration when defining
genera. In this case, an alternative action would be to retain genus
&lt;/i&gt;&lt;i&gt;Deinocerites and afford equivalent rank to the monophyletic
subgenera of &lt;/i&gt;&lt;i&gt;Culex. It should be borne in mind that the
majority of taxa (14) currently regarded as subgenera of &lt;/i&gt;&lt;i&gt;Culex
were originally recognized as genera&lt;/i&gt;.” (Harbach 2007:622-623 )&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Según la afirmación
anterior: Un género, debe permanecer como tal, porque posee
suficientes autapomorfias (=caracteres apomórficos no compartidos).
No obstante en el alegato no se indican las numerosas sinapomorfías
(=caracteres apomórficos compartidos) que se encuentran en el clado
donde se incluye &lt;i&gt;Deinocerites&lt;/i&gt;, así como la posición derivada
de este. Algo similar a lo señalado por los seguidores de la
Sistemática Evolutiva: “mientra es mayor el grado de diferencia,
entonces la jerarquía debe aumentar”. 
&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Simultáneamente se ha
indicado que el trabajo de Navarro y Liria (2000) carece de soporte
debido a que solo incluyeron caracteres de las piezas bucales (maxila
y mandíbula) de las larvas. Este alegato puede rebatirse debido a:
1) Se obtiene una topología similar a la de Mallampalli (1995) quien
utilizó caracteres de todas las fases de vida, y 2) los caracteres
de las piezas bucales han sido empleados ampliamente en otros
Culicidae (Sabethini y Anophelinae).&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Tanaka (2003) eleva el
subgénero &lt;i&gt;Lutzia&lt;/i&gt; de &lt;i&gt;Culex&lt;/i&gt; a una categoría genérica a
partir de un estudio morfológico y sin emplear métodos
explícitos:&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
“&lt;i&gt;Tanaka et al,  1979, 
expressed  their  view  that  its morphological modifications  were
more  distinct  than  in the  other  subgenera  of Culex,  and
 it was  more reasonable  to consider  &lt;/i&gt;&lt;i&gt;Lutzia as a genus.  In 
this  paper,  following  the suggestion  of Tanaka  et al, 1979,  I 
treat  &lt;/i&gt;&lt;i&gt;Lutzia as  an  independent  genus&lt;/i&gt;.” (Tanaka 2003:
159)&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Recientemente, St John
(2007: citado por Harbach 2007) realiza su Tesis de Maestría en
filogenia de &lt;i&gt;Culex&lt;/i&gt;.  
&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
“&lt;i&gt;St John (2007)
explored the generic and subgeneric relationships within Culicini
using morphological characters of larvae, pupae and adults.
Sixty-four characters were scored for 41 exemplar species
representing 26 generic-level taxa of Culicini, and three outgroup
species of genera Mansonia, &lt;/i&gt;&lt;i&gt;Orthopodomyia and
&lt;/i&gt;&lt;i&gt;Maorigoeldia. Characters from Mallampalli (1995) and Harbach &amp;amp;
Kitching (1998) were included along with several novel characters.
Characters were chosen to contain maximum phylogenetic information
about subgeneric relationships within &lt;/i&gt;&lt;i&gt;Culex. Characters that
were internally polymorphic for subgenera were discarded. Maximum
parsimony analysis of the data set under equal weighting yielded
eight most parsimonious trees (MPTs). The strict consensus of these
MPTs (Fig. 23) indicates that genus &lt;/i&gt;&lt;i&gt;Culex is not monophyletic
because genus &lt;/i&gt;&lt;i&gt;Deinocerites is embedded within the clade that
includes all subgenera of &lt;/i&gt;&lt;i&gt;Culex (clade A in Fig. 23).
&lt;/i&gt;&lt;i&gt;Deinocerites is placed as the sister group to subgenus
&lt;/i&gt;&lt;i&gt;Belkinomyia, and genus &lt;/i&gt;&lt;i&gt;Lutzia is placed in an ancestral
relationship to genus &lt;/i&gt;&lt;i&gt;Culex, which is polyphyletic relative to
genus &lt;/i&gt;&lt;i&gt;Deinocerites&lt;/i&gt;.” (Harbach 2007: 621)&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Rossi y Harbach (2008)
en la descripción del subgénero &lt;i&gt;Phytotelmatomyia&lt;/i&gt; de &lt;i&gt;Culex&lt;/i&gt;,
muestran un árbol reducido con la posición de este nuevo taxa
respecto a otros Culicini; no obstante al realizar un acercamiento al
árbol completo, se observa a &lt;i&gt;De. cancer&lt;/i&gt; + &lt;i&gt;De. mathesoni&lt;/i&gt;
como grupo hermano de &lt;i&gt;Cx. (Belkinomyia) eldriegi&lt;/i&gt;&lt;span style="font-style: normal;"&gt;,
tal como fue reportado en el estudio de St John (2007)&lt;/span&gt;.
Paralelamente, en la discusión filogenética sobre &lt;i&gt;Phytotelmatomyia&lt;/i&gt;,
se hace mención al trabajo de Navarro y Liria (2000):&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
“&lt;i&gt;Navarro and Liria
(2000) proposed subgeneric status for genus Deinocerites
Theobald based on morphological features of larval mouthparts, but
this action has not been accepted because it is not supported by the
numerous unique characters that distinguish the adults, larvae, and
pupae from &lt;/i&gt;&lt;i&gt;Culex&lt;/i&gt; (Harbach, 2007).“ (Rossi y Harbach 2008:
12)&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Finalmente, Harbach
(2011) muestra la clasificación más reciente en &lt;i&gt;Culex&lt;/i&gt;,
resaltando los principales aspectos que deben cubrirse en los
próximos estudios taxonómicos y filogenéticos:&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
“&lt;i&gt;The  current 
classiﬁcation  is  based  almost  entirely on external adult
characters, especially features of the male genitalia.  Larval  and 
pupal  characters  have  been  largely  neglected, but  are  likely 
to  be  of  value  in  arriving  at  a  natural  classiﬁcation
(Belkin, 1962). DNA sequence data are proving indispensable for
resolving  the  phylogenetic  relationships  of  numerous  groups  of
organisms,  but  so  far  sequences  are  publicly  available  for 
only  75 named  species  representing  11  subgenera  of  Culex,
 including  39 from subgenus &lt;/i&gt;&lt;i&gt;Culex and 16 from subgenus
&lt;/i&gt;&lt;i&gt;Melanoconion,..&lt;/i&gt;” (Harbach 2011: 6)&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Por ello el presente
estudio pretende utilizar la información disponible en GenBank con
el fin obtener una hipótesis filogenética para Culicini, donde se
discuta la posición de los géneros &lt;i&gt;Deinocerites&lt;/i&gt; y &lt;i&gt;Lutzia&lt;/i&gt;.
Para ello se utilizarán los algoritmos que permiten compilar y
alinear secuencias, así como los métodos de nuevas búsquedas de
soluciones óptimas.&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;b&gt;Materiales y métodos&lt;/b&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
A partir de GenBank se
obtuvieron secuencias que incluyen especies de &lt;i&gt;Culex&lt;/i&gt;,
&lt;i&gt;Deinocerites&lt;/i&gt;, &lt;i&gt;Lutzia,&lt;/i&gt; y como grupos externos &lt;i&gt;Aedes&lt;/i&gt;
y &lt;i&gt;Eretmapodides&lt;/i&gt;. Se utilizaron los siguientes marcadores
moleculares:&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;a href="http://en.wikipedia.org/wiki/White_%28mutation%29"&gt;White&lt;/a&gt;
(Besansky y Fahey 1997; Reidenbach et al. 2009): &lt;i&gt;Aedes&lt;/i&gt; (678 secuencias), &lt;i&gt;Eretmapodites&lt;/i&gt; (1 secuencia),
&lt;i&gt;Culex&lt;/i&gt; (2 secuencias) y &lt;i&gt;Deinocerites&lt;/i&gt; (1 secuencia).&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;a href="http://es.wikipedia.org/wiki/Citocromo_c_oxidasa"&gt;COI&lt;/a&gt;
(Cook et al. 2010; Demari-Silva et al. 2011) : &lt;i&gt;Aedes&lt;/i&gt; (108 secuencias), &lt;i&gt;Eretmapodites&lt;/i&gt; (3 secuencias),
&lt;i&gt;Culex&lt;/i&gt; (487 secuencias [y 37 secuencias para especies de
Brasil]) y &lt;i&gt;Lutzia&lt;/i&gt; (14 secuencias).&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;a href="http://en.wikipedia.org/wiki/Actin"&gt;Actin&lt;/a&gt;
(Staley et al. 2010): &lt;i&gt;Culex&lt;/i&gt; (106 secuencias) y &lt;i&gt;Deinocerites&lt;/i&gt; (1 secuencia).&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
A partir de estos datos,
se utilizó el programa &lt;a href="http://www.zmuc.dk/public/phylogeny/TNT/GenBank-to-TNT.zip"&gt;Gb-2-TnT&lt;/a&gt;
(Goloboff y Catalano, 2012) para extraer aquellas secuencias únicas
por especies, filtrando duplicados y conteniendo los genes y
productos especificados.&lt;br /&gt;
&lt;br /&gt;
Seguidamente se prepararon dos matrices con
Gb-2-TnT:&lt;br /&gt;
&lt;br /&gt;
(1) Bloque uno “White
 gene” (Con cuatro especies), Bloque dos “Citochrome Oxidase C
 Subunit I” (46 especies), y Bloque tres “Actin gene” (10 especies).&lt;br /&gt;
&lt;br /&gt;
(2) Bloque uno “White
 gene” (Con cuatro especies), Bloque dos “Citochrome Oxidase C
 Subunit I” (59 especies [que incluyen a las especies de
 Brasil]), y Bloque tres “Actin gene” (10 especies).&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;
Luego las secuencias se 
alinearon con el programa &lt;a href="http://www.drive5.com/muscle/"&gt;Muscle&lt;/a&gt;
(Edgar 2004), obteniendo las siguientes matrices: 1) con 6202
caracteres y 45 taxa, y 2) 6141 caracteres y 56 taxa.&lt;br /&gt;
&lt;br /&gt;
Tambien se incluyeron datos morfológicos (quetotaxia larval y piezas bucales) para algunas de las especies, a partir de los trabajos de Navarro y Liria (2000) y Foote (1954). Estos caracteres fueron incluidos a la matriz 2, para conformar un set de datos combinados:&lt;br /&gt;
&lt;br /&gt;
(3) Bloque uno "Quetotaxia larval"&amp;nbsp; con 17 caracteres, Bloque dos "Piezas bucales" con&amp;nbsp; 30 caracteres, Bloque tres "White
 gene” con 1215 caracteres, Bloque cuatro “Citochrome Oxidase C
 Subunit I” con 1542 caracteres, y Bloque&amp;nbsp; cinco “Actin gene” con 3384 caracteres. &lt;br /&gt;
&lt;br /&gt;
Todas las matrices fueron analizadas con &lt;a href="http://www.zmuc.dk/public/phylogeny/tnt/"&gt;TNT&lt;/a&gt;
(Goloboff et al., 2003; 2008), utilizando rondas de &lt;a href="http://www3.interscience.wiley.com/journal/119079712/abstract"&gt;TreeFusing&lt;/a&gt;,
&lt;a href="http://tnt.insectmuseum.org/index.php/Ratchet" target="_blank"&gt;Ratchet&lt;/a&gt;, &lt;a href="http://www3.interscience.wiley.com/journal/119079712/abstract"&gt;Sectorial
Search&lt;/a&gt;. &lt;a href="http://www3.interscience.wiley.com/journal/119079712/abstract"&gt;TreeDrifting&lt;/a&gt;. Simultáneamente los datos fueron analizados mediante &lt;a href="http://tnt.insectmuseum.org/index.php/Implied_weighting" target="_blank"&gt;pesos implícitos&lt;/a&gt; con concavidad K=8.&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;b&gt;Resultados&lt;/b&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;
En líneas generales, los analisis realizados a las matrices moleculares (Figura 1, para la Matriz "1") y (Figura 2, Matriz "2"), como la combinacion de datos morfológicos (Figura 3, Matriz "3"), muestran la inclusión de&amp;nbsp; &lt;i&gt;Lutzia &lt;/i&gt;y &lt;i&gt;Deinocerites &lt;/i&gt;en el género&lt;i&gt; Culex&lt;/i&gt;. Los resultados de la Matriz "2" muestran monofilia de algunos subgéneros de &lt;i&gt;Culex&lt;/i&gt;: &lt;a href="http://www.mosquitocatalog.org/taxon_descr.aspx?ID=140" target="_blank"&gt;&lt;i&gt;Lophoceraomyia&lt;/i&gt;&lt;/a&gt;, &lt;a href="http://www.mosquitocatalog.org/taxon_descr.aspx?ID=103" target="_blank"&gt;&lt;i&gt;Culiciomyia&lt;/i&gt;&lt;/a&gt;, &lt;a href="http://www.mosquitocatalog.org/taxon_descr.aspx?ID=187" target="_blank"&gt;&lt;i&gt;Phenacomyia&lt;/i&gt;&lt;/a&gt;, &lt;a href="http://www.mosquitocatalog.org/taxon_descr.aspx?ID=91" target="_blank"&gt;&lt;i&gt;Carrollia&lt;/i&gt;&lt;/a&gt;, &lt;a href="http://www.mosquitocatalog.org/taxon_descr.aspx?ID=159" target="_blank"&gt;&lt;i&gt;Neoculex&lt;/i&gt;&lt;/a&gt;, y &lt;a href="http://www.mosquitocatalog.org/taxon_descr.aspx?ID=83" target="_blank"&gt;&lt;i&gt;Barraudius&lt;/i&gt;&lt;/a&gt;. Otros taxa se presentan como parafiléticos: &lt;i&gt;&lt;a href="http://www.mosquitocatalog.org/taxon_descr.aspx?ID=101" target="_blank"&gt;Culex&lt;/a&gt; &lt;/i&gt;y &lt;a href="http://www.mosquitocatalog.org/taxon_descr.aspx?ID=150" target="_blank"&gt;&lt;i&gt;Melanoconion&lt;/i&gt;&lt;/a&gt;. &amp;nbsp; &lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;b&gt;A&lt;/b&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;a href="http://2.bp.blogspot.com/-lUNchY6l79c/T8K9OumH6_I/AAAAAAAAAOo/0DXc4Gco1W0/s1600/Culicini_K8.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="237" src="http://2.bp.blogspot.com/-lUNchY6l79c/T8K9OumH6_I/AAAAAAAAAOo/0DXc4Gco1W0/s400/Culicini_K8.jpg" width="400" /&gt;&lt;/a&gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div style="text-align: justify;"&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
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&lt;b&gt;B&lt;/b&gt;&amp;nbsp; &lt;br /&gt;
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Figura 1. A) Cladograma más parsimonioso obtenido luego de utilizar pesos 
implícitos (K=8) a la matriz&amp;nbsp; "1"&amp;nbsp; (6202
caracteres y 45 taxa) con base en tres marcadorexs moleculares (actin, 
white gene COI). Las flechas indican la posición de los géneros &lt;i&gt;Deinocerites &lt;/i&gt;y &lt;i&gt;Lutzia&lt;/i&gt;. B) Cladograma con ramas a color muestran la taxonomia de los taxa.&lt;br /&gt;
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Figura 2. A) Cladograma de consenso estricto a partir de seis árboles más parsimoniosos obtenidos luego de utilizar pesos 
implicitos (K=8) a la matriz&amp;nbsp; "2" (6141 caracteres y 56 taxa) con base en tres marcadores moleculares (actin, 
white gene, COI). Las flechas indican la posición de los géneros &lt;i&gt;Deinocerites &lt;/i&gt;y &lt;i&gt;Lutzia&lt;/i&gt;. B) Cladograma con ramas a color muestran la taxonomia de los taxa.&lt;br /&gt;
&lt;br /&gt;
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&lt;div class="separator" style="clear: both; text-align: center;"&gt;
&lt;a href="http://3.bp.blogspot.com/-hEp1otBWZxg/T8yieYV0WNI/AAAAAAAAAO8/BnevP7cXmKU/s1600/Culex_comb2_K8_Consenso.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="237" src="http://3.bp.blogspot.com/-hEp1otBWZxg/T8yieYV0WNI/AAAAAAAAAO8/BnevP7cXmKU/s400/Culex_comb2_K8_Consenso.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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Figura 3. Cladograma de consenso estricto a partir de cinco árboles más parsimoniosos obtenidos luego de utilizar pesos 
implicitos (K=8) a la matriz&amp;nbsp; "3" (6188 caracteres y 56 taxa) con base en tres marcadores moleculares (actin, 
white gene, COI) y dos morfológicos (quetotaxia larval y piezas bucales). Las flechas indican la posición de los géneros &lt;i&gt;Deinocerites &lt;/i&gt;y &lt;i&gt;Lutzia&lt;/i&gt;.&amp;nbsp;&lt;b&gt; &lt;/b&gt;&lt;br /&gt;
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&lt;b&gt;Bibliografía&lt;/b&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Belkin, J. N. 1962. The
Mosquitoes of South PaciÞc (Diptera: Culicidae). University of
California, Berkeley, CA&lt;/div&gt;
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&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Besansky, N.J. Fahey,
G.T. 1997. Utility of the white gene in estimating phylogenetic
relationships       among mosquitoes (Diptera: Aedini). Mol. Biol.
Evol. 14(4), 442-454.&lt;br /&gt;
&lt;br /&gt;
Cook,S., Lien,N.G., McAlister,E. and Harbach,R.E. 2010. Bothaella manhi, a new species of tribe Aedini (Diptera: Aedini) from the Cuc Phuong National Park of Vietnam based on morphology and DNA sequence&lt;br /&gt;
Zootaxa 2661: 33-46. &lt;/div&gt;
&lt;br /&gt;
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Demari-Silva, B.,
Vesgueiro, F., Sallum, M.A., Marrelli, M. 2011. Taxonomic and
Phylogenetic Relationships between Species of the Genus &lt;i&gt;Culex&lt;/i&gt;
(Diptera: Culicidae) from Brazil Inferred from the Cytochrome c
Oxidase I Mitochondrial Gene. J. Med. Entomol. 48(2): 272-279.&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Edgar, R.C., 2004.
MUSCLE: a multiple sequence alignment method with reduced time and
space complexity. BMC Bioinformatics 5, 1–19.&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Goloboﬀ, P.A., Farris,
J.S., Nixon, K. 2003. Tree analysis using new technology Version 1.1.
Available from http://www.zmuc.dk/public/phylogeny/TNT.&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Goloboﬀ, P., Farris,
J., Nixon, K., 2008. TNT: a free program for phylogenetic analysis.
Cladistics 24, 774–786.&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Goloboﬀ, P.A.,
Catalano, S.A., Mirande, J.M., Szumik, C.A., Arias, J.S., Kallersjo,
M., Farris, J.S., 2009. Phylogenetic analysis of 73 060 taxa
corroborates major eukaryotic groups. Cladistics 25, 211–230.&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Goloboff, P.A., Catalano,
S.A. 2012. GB-to-TNT: facilitating creation of matrices from GenBank
and diagnosis of results in
TNT. Cladistics. 1-12. 
&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Harbach, R. E.. 2007. The
Culicidae (Diptera): a review of taxonomy, classification and
phylogeny. Zootaxa 1668: 591-638.&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Harbach, R. E. 2011.
Review: Classiﬁcation  within  the  cosmopolitan  genus  &lt;i&gt;Culex&lt;/i&gt;
 (Diptera:  Culicidae): The  foundation  for  molecular  systematics 
and  phylogenetic  research. Acta Tropica&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Mallampalli,  V.L., 
1995.  Phylogenetic  relationships  among  taxa  in  the  genus 
&lt;i&gt;Culex&lt;/i&gt;, and  the  phylogenetic  relationships  of  vectors  of 
New  World  alphaviruses  in  the subgenus  &lt;i&gt;Melanoconion&lt;/i&gt; 
(Diptera:  Culicidae).  PhD  thesis,  University  of  Maryland,
College Park.&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Navarro, J.-C., and J.
Liria. 2000. Phylogenetic relationships between eighteen Neotropical
Culicini species. J. Am. Mosq. Control Assoc. 16: 75-85.&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Reidenbach K.R., Cook S.,
Bertone, M.A, Harbach, R.E., Wiegmann R., Besansky N.J. 2009.
Phylogenetic analysis and temporal diversification of mosquitoes
(Diptera: Culicidae) based on nuclear genes and morphology. BMC
Evolutionary Biology.&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Rossi, G.C., Harbach,
R.E., 2008. &lt;i&gt;Phytotelmatomyia&lt;/i&gt;, a new Neotropical subgenus of
&lt;i&gt;Culex&lt;/i&gt; (Diptera: Culicidae). Zootaxa 1879, 1–17.&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Savage, H.M. 2005.
Classification of mosquitoes in tribe Aedini (Diptera: Culicidae):
paraphylophobia, and classification versus cladistic analysis. J.
Med. Entomol. 42(6): 923-927.&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Staley,M., Dorman,K.S.,
Bartholomay, L.C., Fernandez-Salas,I., Farfan-Ale, J.A., Lorono-Pino,
M.A., Garcia-Rejon, J.E., Ibarra-Juarez, L. Blitvich, B.J. 2010.
Universal primers for the amplification and sequence analysis of
actin-1 from diverse mosquito species. J. Am. Mosq. Control Assoc. 26
(2), 214-218.&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
St John, O. (2007)
Phylogeny of the genus Culex (Diptera: Culicidae). MRes thesis,
Imperial College, London.&lt;/div&gt;
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&lt;br /&gt;&lt;/div&gt;
&lt;div align="JUSTIFY" style="margin-bottom: 0cm;"&gt;
Tanaka,K. 2003. Studies
on the pupal mosquitoes of Japan genus &lt;i&gt;Lutzia&lt;/i&gt;, with
establishment of two 
&lt;/div&gt;
</description><link>http://cladisticaybiogeografia.blogspot.com/2012/09/filogenia-molecular-en-culicini-partir.html</link><author>noreply@blogger.com (Jonathan Liria)</author><media:thumbnail url="http://2.bp.blogspot.com/-lUNchY6l79c/T8K9OumH6_I/AAAAAAAAAOo/0DXc4Gco1W0/s72-c/Culicini_K8.jpg" height="72" width="72" /><thr:total>0</thr:total><enclosure url="http://www.zmuc.dk/public/phylogeny/TNT/GenBank-to-TNT.zip" length="4804250" type="application/x-zip-compressed" /><media:content url="http://www.zmuc.dk/public/phylogeny/TNT/GenBank-to-TNT.zip" fileSize="4804250" type="application/x-zip-compressed" /><itunes:explicit>no</itunes:explicit><itunes:subtitle> FILOGENIA MOLECULAR EN CULICINI (DIPTERA: CULICIDAE): UN ANÁLISIS UTILIZANDO GenBank-to-TNT Y PARSIMONIA CON TNT. Introducción Culicini contiene algunos de los vectores más importantes en cuanto a la transmisión de distintos patógenos, como: Encefalitis </itunes:subtitle><itunes:author>noreply@blogger.com (Jonathan Liria)</itunes:author><itunes:summary> FILOGENIA MOLECULAR EN CULICINI (DIPTERA: CULICIDAE): UN ANÁLISIS UTILIZANDO GenBank-to-TNT Y PARSIMONIA CON TNT. Introducción Culicini contiene algunos de los vectores más importantes en cuanto a la transmisión de distintos patógenos, como: Encefalitis Equina Venezolana, Encefalitis Equina de Este, filarias, entre otros. Esta tribu incluye a 789 especies clasificadas en cuatro géneros: Culex (amplia distribución), Deinocerites (Neotropical) y Galindomyia (Neotropical) Estudios previos han indicado que Deinocerites es un grupo incluido en el género Culex (Mallampalli 1995; Liria y Navarro 2000). En este sentido, Liria y Navarro (2000) propusieron la inclusión de este taxa como un subgénero: Culex (Deinocerites). Sin embargo esta propuesta no fue acogida entre los taxónomos de Culicidae, debido a las siguientes consideraciones: “Navarro &amp;amp; Liria (2000) formally reduced genus Deinocerites to subgeneric status in genus Culex, but this action has not been widely accepted because this group of species is diagnosed by many unique (autapomorphic) features in the immature and adult stages. Autapomorphic features are normally excluded from phylogenetic studies because they are uninformative in the context of cladistic analyses. This does not mean, however, that autapomorphies should be disregarded as denotations of taxonomic rank, providing that doing so does not conflict with the principle of recognizing only monophyletic groups in classifications. Autapomorphies are a measure of (often rapid) divergence and adaptive radiation, which traditional taxonomists have intuitively taken into consideration when defining genera. In this case, an alternative action would be to retain genus Deinocerites and afford equivalent rank to the monophyletic subgenera of Culex. It should be borne in mind that the majority of taxa (14) currently regarded as subgenera of Culex were originally recognized as genera.” (Harbach 2007:622-623 ) Según la afirmación anterior: Un género, debe permanecer como tal, porque posee suficientes autapomorfias (=caracteres apomórficos no compartidos). No obstante en el alegato no se indican las numerosas sinapomorfías (=caracteres apomórficos compartidos) que se encuentran en el clado donde se incluye Deinocerites, así como la posición derivada de este. Algo similar a lo señalado por los seguidores de la Sistemática Evolutiva: “mientra es mayor el grado de diferencia, entonces la jerarquía debe aumentar”. Simultáneamente se ha indicado que el trabajo de Navarro y Liria (2000) carece de soporte debido a que solo incluyeron caracteres de las piezas bucales (maxila y mandíbula) de las larvas. Este alegato puede rebatirse debido a: 1) Se obtiene una topología similar a la de Mallampalli (1995) quien utilizó caracteres de todas las fases de vida, y 2) los caracteres de las piezas bucales han sido empleados ampliamente en otros Culicidae (Sabethini y Anophelinae). Tanaka (2003) eleva el subgénero Lutzia de Culex a una categoría genérica a partir de un estudio morfológico y sin emplear métodos explícitos: “Tanaka et al, 1979, expressed their view that its morphological modifications were more distinct than in the other subgenera of Culex, and it was more reasonable to consider Lutzia as a genus. In this paper, following the suggestion of Tanaka et al, 1979, I treat Lutzia as an independent genus.” (Tanaka 2003: 159) Recientemente, St John (2007: citado por Harbach 2007) realiza su Tesis de Maestría en filogenia de Culex. “St John (2007) explored the generic and subgeneric relationships within Culicini using morphological characters of larvae, pupae and adults. Sixty-four characters were scored for 41 exemplar species representing 26 generic-level taxa of Culicini, and three outgroup species of genera Mansonia, Orthopodomyia and Maorigoeldia. Characters from Mallampalli (1995) and Harbach &amp;amp; Kitching (1998) were included along with several novel characters. Characters were chosen to contain maximum phylogenetic information a</itunes:summary><itunes:keywords>molecular, alineamiento, TnT, Culicini, parafilia, secuencias, megafilogenias, COI, GenBank, monofilia, parsimonia, cladismo</itunes:keywords></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-4146625716757363180</guid><pubDate>Wed, 12 Sep 2012 01:49:00 +0000</pubDate><atom:updated>2012-09-11T18:49:54.962-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">clase</category><category domain="http://www.blogger.com/atom/ns#">sistemática</category><category domain="http://www.blogger.com/atom/ns#">NDM</category><category domain="http://www.blogger.com/atom/ns#">TnT</category><category domain="http://www.blogger.com/atom/ns#">biogeografía</category><category domain="http://www.blogger.com/atom/ns#">VIP</category><category domain="http://www.blogger.com/atom/ns#">teoría</category><category domain="http://www.blogger.com/atom/ns#">Latinoamérica</category><category domain="http://www.blogger.com/atom/ns#">conceptos</category><category domain="http://www.blogger.com/atom/ns#">Suramerica</category><category domain="http://www.blogger.com/atom/ns#">cladismo</category><title>Curso: Cladística y Biogeografía</title><description>&lt;div style="text-align: center;"&gt;
&lt;b&gt;&lt;span style="font-size: small;"&gt;&lt;a href="http://cebioperu.org/courses/cladistic_biogeography.php" target="_blank"&gt;CURSO INTERNACIONAL: CLADISTICA Y BIOGEOGRAFIA&lt;/a&gt;&lt;/span&gt;&lt;/b&gt;&lt;/div&gt;
&lt;div style="text-align: center;"&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div style="text-align: center;"&gt;
14 – 23 de Enero de 2013&lt;br /&gt;
Lima – Perú&lt;/div&gt;
&lt;div style="text-align: center;"&gt;
Fecha Limite de Inscripción: 1 de octubre de 2012&lt;br /&gt;
Resultados: 5 de Octubre de 2012 &lt;/div&gt;
&lt;br /&gt;
&lt;b&gt;CLADÍSTICA: MÉTODOS CUANTITATIVOS  DE CLASIFICACIÓN: &lt;/b&gt;&lt;br /&gt;
&lt;br /&gt;
14 al 18 de Enero de 2013.&lt;br /&gt;
&lt;br /&gt;
Modalidad del Curso&lt;br /&gt;
&lt;div style="text-align: justify;"&gt;
&lt;br /&gt;
Curso teórico/práctico, con fuerte énfasis en los aspectos prácticos.
  Las clases teóricas se usan para introducir la problemática general en
 cada tema, y los prácticos se utilizan para ilustrar y terminar de 
entender los temas vistos en las clases teóricas.  La dinámica del curso
 es bastante informal, pasando de modalidad "teórico" a modalidad 
"práctico" rápidamente y a requerimiento de los participantes. &lt;/div&gt;
&lt;br /&gt;
Las clases serán diarias, de 9:30 a 18:30 hs. aprox.&lt;br /&gt;
&lt;br /&gt;
Duración: 40 horas aprox. &lt;br /&gt;
&lt;br /&gt;
&lt;b&gt;BIOGEOGRAFIA: NDM/VNDM/VIP - PROGRAMAS DE COMPUTACIÓN PARA BIOGEOGRAFÍA, FUNDAMENTOS Y APLICACIONES: &lt;/b&gt;&lt;br /&gt;
&lt;br /&gt;
21 al 23 de Enero de 2013.&lt;br /&gt;
&lt;br /&gt;
Objetivos:&lt;br /&gt;
&lt;div style="text-align: justify;"&gt;
&lt;br /&gt;
Brindar a los alumnos los fundamentos teóricos y metodológicos de 
algunas preguntas y problemas de la biogeogeografía histórica. Se 
propone dar a los alumnos herramientas básicas sumamente necesarias para
 desarrollar estudios biogeográficos. De manera que los objetivos de 
este curso no son sólo mostrar los fundamentos teóricos sino también su 
aplicación práctica mediante el uso de programas de computación 
específicamente desarrollados para estos estudios.&lt;/div&gt;
&lt;br /&gt;
Organización general:&lt;br /&gt;
&lt;div style="text-align: justify;"&gt;
&lt;br /&gt;
El curso constará de clases teóricas (3hs) y prácticas (5hs) durante 3
 días, un total de 24 horas. Dado el énfasis en la aplicación práctica 
de la metodología biogeográfica se necesita obligadamente del uso de 
computadoras, idealmente UN alumno por computador.&lt;/div&gt;
Las clases serán diarias, de 9:30 a 18:30 horas. aprox.&lt;br /&gt;
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&lt;b&gt;INSTRUCTORES:&lt;/b&gt;&lt;br /&gt;
&lt;br /&gt;
Cladística: Métodos Cuantitativos  de Clasificación &lt;br /&gt;
&lt;ul&gt;
&lt;li&gt;Responsable: &lt;b&gt;Dr. Pablo Goloboff&lt;/b&gt; (Inv. Ppal CONICET)&lt;/li&gt;
&lt;li&gt;Colaboradora: &lt;b&gt;Dra. Claudia Szumik&lt;/b&gt; (Inv. Indep. CONICET)&lt;/li&gt;
&lt;/ul&gt;
NDM/VNDM/VIP: Programas de Computación para Biogeografía: Fundamentos y Aplicaciones&lt;br /&gt;
&lt;ul&gt;
&lt;li&gt;Responsable: &lt;b&gt;Dra. Claudia A. Szumik&lt;/b&gt; (Inv. Indep. CONICET)&lt;/li&gt;
&lt;li&gt;Colaborador: &lt;b&gt;Dr. Pablo Goloboff&lt;/b&gt; (Inv. Ppal CONICET)&lt;/li&gt;
&lt;/ul&gt;
</description><link>http://cladisticaybiogeografia.blogspot.com/2012/09/curso-cladistica-y-biogeografia.html</link><author>noreply@blogger.com (Jonathan Liria)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-2344892945866883143</guid><pubDate>Wed, 13 Jun 2012 13:03:00 +0000</pubDate><atom:updated>2012-06-15T07:17:01.697-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">matrices</category><category domain="http://www.blogger.com/atom/ns#">TnT</category><category domain="http://www.blogger.com/atom/ns#">filogenia</category><category domain="http://www.blogger.com/atom/ns#">morfometría</category><category domain="http://www.blogger.com/atom/ns#">parsimonia</category><category domain="http://www.blogger.com/atom/ns#">árboles</category><category domain="http://www.blogger.com/atom/ns#">cladismo</category><title>Matrices morfométricas 2D y 3D</title><description>&lt;div style="text-align: justify;"&gt;
En esta entrada les traigo unas matrices para que puedan practicar los análisis filogenéticos (utilizando parsimonia) de datos &lt;a href="http://tnt.insectmuseum.org/index.php/Continuous_characters" target="_blank"&gt;continuos&lt;/a&gt;, particularmente puntos anatómicos de referencia (=&lt;a href="http://tnt.insectmuseum.org/index.php/Landmark_optimization" target="_blank"&gt;landmarks&lt;/a&gt;).&lt;/div&gt;
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El programa &lt;a href="http://tnt.insectmuseum.org/index.php/Main_Page" target="_blank"&gt;TNT &lt;/a&gt;admite matrices de landmarks en dos (X,Y) y en tres (X,Y,Z) dimensiones:&lt;/div&gt;
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Esta es una &lt;a href="https://www.dropbox.com/s/81vyn6j9oteokb1/Sneath.tnt"&gt;matriz&lt;/a&gt; 2D (Sneath.tnt), para cuatro géneros de &lt;a href="http://es.wikipedia.org/wiki/Hominidae" target="_blank"&gt;Hominidos&lt;/a&gt;:&lt;br /&gt;
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&lt;a href="http://3.bp.blogspot.com/-xVCIqDBLOyk/T9XvRgbMoBI/AAAAAAAAAPU/Qkn9ye5r2XU/s1600/AUSTRALOP.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="245" src="http://3.bp.blogspot.com/-xVCIqDBLOyk/T9XvRgbMoBI/AAAAAAAAAPU/Qkn9ye5r2XU/s400/AUSTRALOP.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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Esta es la filogenia obtenida con el macro &lt;a href="http://tnt.insectmuseum.org/index.php/Scripts/Landsch.run"&gt;landsch.run&lt;/a&gt; &lt;br /&gt;
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&lt;a href="http://3.bp.blogspot.com/-zNia6tRKozY/T9XwA6_ixbI/AAAAAAAAAPs/VMlenfkOOYs/s1600/Sneath_tree.png" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="400" src="http://3.bp.blogspot.com/-zNia6tRKozY/T9XwA6_ixbI/AAAAAAAAAPs/VMlenfkOOYs/s400/Sneath_tree.png" width="398" /&gt;&lt;/a&gt;&lt;br /&gt;
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Esta es una &lt;a href="https://www.dropbox.com/s/25dwm6ugoivck4q/Caiman_3D.tnt"&gt;matriz&lt;/a&gt; 3D (Caiman_3D.tnt), basada en un &lt;a href="http://www.jstor.org/discover/10.2307/3893243?uid=3739296&amp;amp;uid=2129&amp;amp;uid=2&amp;amp;uid=70&amp;amp;uid=4&amp;amp;sid=21100851061641" target="_blank"&gt;articulo sobre ontogenia en Cocodrilia&lt;/a&gt;:&lt;br /&gt;
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&lt;a href="http://3.bp.blogspot.com/-W16_8Winv0c/T9XvSK9OilI/AAAAAAAAAPc/4Acu03jc5mc/s1600/CAMAN.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="246" src="http://3.bp.blogspot.com/-W16_8Winv0c/T9XvSK9OilI/AAAAAAAAAPc/4Acu03jc5mc/s400/CAMAN.jpg" width="400" /&gt;&lt;/a&gt;&lt;br /&gt;
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Esta es la filogenia obtenida con el macro &lt;a href="http://tnt.insectmuseum.org/index.php/Scripts/Landsch.run"&gt;landsch.run&lt;/a&gt;&lt;br /&gt;
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&lt;a href="http://1.bp.blogspot.com/-aDhr059Ksxw/T9h668QNzxI/AAAAAAAAAQM/MvdVAxmmWH8/s1600/Caimn_tree.png" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="300" src="http://1.bp.blogspot.com/-aDhr059Ksxw/T9h668QNzxI/AAAAAAAAAQM/MvdVAxmmWH8/s400/Caimn_tree.png" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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Esta es una &lt;a href="https://www.dropbox.com/s/3f6mht9c2pd7vx4/Cercocebus_3D.tnt"&gt;matriz&lt;/a&gt; 3D (Cercocebus_3D.tnt), basada en un articulo sobre dimorfismo en &lt;a href="http://es.wikipedia.org/wiki/Cercocebus" target="_blank"&gt;Cercocebus&lt;/a&gt;:&lt;br /&gt;
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&lt;a href="http://2.bp.blogspot.com/-wRp63aql6KY/T9h5HjSif4I/AAAAAAAAAQE/JccLv5kamLc/s1600/Cercocebus.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="328" src="http://2.bp.blogspot.com/-wRp63aql6KY/T9h5HjSif4I/AAAAAAAAAQE/JccLv5kamLc/s400/Cercocebus.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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Esta es la filogenia obtenida con el macro &lt;a href="http://tnt.insectmuseum.org/index.php/Scripts/Landsch.run"&gt;landsch.run&lt;/a&gt;&lt;br /&gt;
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&lt;a href="http://4.bp.blogspot.com/-JhMd-HGgkAE/T9s_eyImZ8I/AAAAAAAAAQg/nWTzGWl5ebA/s1600/Gorila_tree.emf.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="640" src="http://4.bp.blogspot.com/-JhMd-HGgkAE/T9s_eyImZ8I/AAAAAAAAAQg/nWTzGWl5ebA/s640/Gorila_tree.emf.jpg" width="403" /&gt;&lt;/a&gt;&lt;/div&gt;
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&lt;br /&gt;</description><link>http://cladisticaybiogeografia.blogspot.com/2012/06/matrices-morfometricas-2d-y-3d.html</link><author>noreply@blogger.com (Jonathan Liria)</author><media:thumbnail url="http://3.bp.blogspot.com/-xVCIqDBLOyk/T9XvRgbMoBI/AAAAAAAAAPU/Qkn9ye5r2XU/s72-c/AUSTRALOP.jpg" height="72" width="72" /><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-7267169110058985394</guid><pubDate>Tue, 05 Jun 2012 01:26:00 +0000</pubDate><atom:updated>2012-06-04T18:26:20.416-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">vertebrados</category><category domain="http://www.blogger.com/atom/ns#">Distribución</category><category domain="http://www.blogger.com/atom/ns#">biogeografía</category><category domain="http://www.blogger.com/atom/ns#">Amazonas</category><category domain="http://www.blogger.com/atom/ns#">VIP</category><category domain="http://www.blogger.com/atom/ns#">Latinoamérica</category><category domain="http://www.blogger.com/atom/ns#">Georreferenciación</category><category domain="http://www.blogger.com/atom/ns#">geoespacial</category><category domain="http://www.blogger.com/atom/ns#">Modelo</category><category domain="http://www.blogger.com/atom/ns#">Andes</category><title>Dos Latinos galardonados con el premio GBIF "E. Nielsen"</title><description>&lt;div class="separator" style="clear: both; text-align: center;"&gt;
&lt;a href="http://4.bp.blogspot.com/-CXYn6IYJL0o/T81d2nA9PKI/AAAAAAAAAPI/-BpvuTjgtG8/s1600/GBIF+prize.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="342" src="http://4.bp.blogspot.com/-CXYn6IYJL0o/T81d2nA9PKI/AAAAAAAAAPI/-BpvuTjgtG8/s400/GBIF+prize.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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Aquí les coloco parte de la información tomada de la página (&lt;a href="http://www.gbif.org/communications/news-and-events/showsingle/article/awards-target-novel-research-on-species-distributions/" target="_blank"&gt;GBIF&lt;/a&gt;):&lt;br /&gt;
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&lt;i&gt;Two biogeographers were selected to receive the €4,000 &lt;a class="external-link-new-window" href="http://www.gbif.org/communications/news-and-events/young-researchers-award/" target="_blank" title="Opens external link in new window"&gt;Young Researchers Award&lt;/a&gt;&lt;span&gt;, presented annually to biodiversity informatics students enrolled in a master’s or doctoral programme at universities in countries which are GBIF Participants. &lt;/span&gt;&lt;br /&gt;&lt;br /&gt;&lt;span&gt;Salvador Arias, a PhD student at the Universidad Nacional de Tucumán in Argentina, developed the Vicariance Inference Programme (VIP), which uses georeferenced data to explore the splitting of the geographical ranges of groups of organisms because of barriers to gene flow or species movemen&lt;span&gt;t. Arias plans to process GBIF-mediated data through the VIP to formulate hypotheses on how species distributions have changed over time. &lt;/span&gt;&lt;/span&gt;&lt;br /&gt;&lt;br /&gt;&lt;span&gt;Elkin Tenorio Moreno is a master’s student at the Department of Biological Scien&lt;span&gt;ces, Universidad de los Andes in Colombia. He plans to use the award to analyse dispersal patterns of Amazonian and Andean birds across climatic and geographic barriers, g&lt;/span&gt;enerating climatic niche models for over 500 bird species using GBIF-mediated data from natural history collections. &lt;/span&gt;&lt;br /&gt;&lt;br /&gt;&lt;span&gt;Leonard Krishtalka added, “Salvador Arias’ and Elkin Tenorio’s
 investigations embody the innovation and originality called for in the 
GBIF Young Researchers Award. Arias’ doctoral research project will 
affect biodiversity scien&lt;span&gt;ce worldwide in developing an analytical tool for modelling the spatial distribution of animals and plants using GBIF-served biodiversity data. T&lt;/span&gt;enorio, the first master’s student to receive the YRA, will investigate how the dispersal ability of birds affects their numbers of species and evolutionary potential.”&lt;/span&gt;&lt;/i&gt;&lt;/div&gt;
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&lt;i&gt;&lt;span&gt;&amp;nbsp;&lt;/span&gt;&lt;/i&gt;&lt;/div&gt;
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&lt;i&gt;&lt;span&gt;&amp;nbsp;&lt;/span&gt;&lt;/i&gt;&lt;/div&gt;
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&lt;b&gt;&lt;span&gt;Felicitaciones a Salvador y Elkin... &lt;/span&gt;!!!&lt;/b&gt;&lt;i&gt;&lt;br /&gt;&lt;/i&gt;&lt;/div&gt;
&lt;br /&gt;&lt;span&gt;&lt;/span&gt;</description><link>http://cladisticaybiogeografia.blogspot.com/2012/06/dos-latinos-galardonados-con-el-premio.html</link><author>noreply@blogger.com (Jonathan Liria)</author><media:thumbnail url="http://4.bp.blogspot.com/-CXYn6IYJL0o/T81d2nA9PKI/AAAAAAAAAPI/-BpvuTjgtG8/s72-c/GBIF+prize.jpg" height="72" width="72" /><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-3398357106785379428</guid><pubDate>Sat, 26 May 2012 09:51:00 +0000</pubDate><atom:updated>2012-05-26T02:51:18.859-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">endemismo</category><category domain="http://www.blogger.com/atom/ns#">insectos</category><category domain="http://www.blogger.com/atom/ns#">vertebrados</category><category domain="http://www.blogger.com/atom/ns#">NDM</category><category domain="http://www.blogger.com/atom/ns#">biogeografía</category><category domain="http://www.blogger.com/atom/ns#">mapas</category><category domain="http://www.blogger.com/atom/ns#">Venezuela</category><title>Áreas de Endemismo de Venezuela</title><description>Esta entrada fue inspirada en este trabajo:&lt;br /&gt;
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&lt;a href="http://2.bp.blogspot.com/-mnrHRfzENa0/T8Ao49ysgXI/AAAAAAAAANM/ljnKuhoFtyI/s1600/Fig0_Szumik_etal2011_Endemismo_Argentina.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="343" src="http://2.bp.blogspot.com/-mnrHRfzENa0/T8Ao49ysgXI/AAAAAAAAANM/ljnKuhoFtyI/s400/Fig0_Szumik_etal2011_Endemismo_Argentina.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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Szumik et al. 2011. &lt;span class="st"&gt;&lt;b&gt;Detecting areas of endeminm&lt;em&gt;&lt;/em&gt; with a taxonomically diverse data set: plants, mammals, reptiles, amphibians, birds, and insects from Argentina&lt;/b&gt;. Cladistics &lt;/span&gt;1-13.&lt;/div&gt;
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En Venezuela existen varias propuestas de áreas de Endemismo, sin embargo en cada caso han sido postuladas para grupos particulares: Peces, Reptiles, Mamíferos o Insectos. Por ello, el presente estudio (preliminar) pretende realizar un análisis con datos de diversos grupos taxonómicos.&lt;/div&gt;
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La matriz realizada contempla &lt;b&gt;8964 &lt;/b&gt;bioregistros y &lt;b&gt;1292 &lt;/b&gt;especies de: &lt;b&gt;Anfibios&lt;/b&gt;, &lt;b&gt;Reptiles&lt;/b&gt;, &lt;b&gt;Mamíferos&lt;/b&gt;, &lt;b&gt;Aves &lt;/b&gt;e &lt;b&gt;Insectos&lt;/b&gt;:&lt;/div&gt;
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&lt;a href="http://3.bp.blogspot.com/-o7nluXzGCVk/T8Ch4wtyCvI/AAAAAAAAANY/IAO0OJHtbg0/s1600/Fig1_Venezuela_Datos_Endemismo.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="392" src="http://3.bp.blogspot.com/-o7nluXzGCVk/T8Ch4wtyCvI/AAAAAAAAANY/IAO0OJHtbg0/s640/Fig1_Venezuela_Datos_Endemismo.jpg" width="640" /&gt;&lt;/a&gt;&lt;/div&gt;
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&amp;nbsp;En &lt;a href="http://www.zmuc.dk/public/phylogeny/endemism/" target="_blank"&gt;NDM&lt;/a&gt;, se utilizó la opción AUTO para construir cuadriculas de 0,58° x 0,58°; también fue considerado el relleno especial. Posteriormente se generó la matriz: &lt;/div&gt;
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&lt;a href="http://2.bp.blogspot.com/-36N3kRbKnG8/T8Ch6NpwKBI/AAAAAAAAANg/PVB0Lx4Gdc8/s1600/Fig2_Venezuela_Matriz_NDM.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="392" src="http://2.bp.blogspot.com/-36N3kRbKnG8/T8Ch6NpwKBI/AAAAAAAAANg/PVB0Lx4Gdc8/s640/Fig2_Venezuela_Matriz_NDM.jpg" width="640" /&gt;&lt;/a&gt;&lt;/div&gt;
Para este tamaño de cuadriculas, se obtuvieron 194 áreas. Aquí les muestro algunas de ellas:&lt;br /&gt;
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&lt;a href="http://1.bp.blogspot.com/-xskO--Z4yxg/T8Ch7oMc5II/AAAAAAAAANo/LcY5WCxTQ4k/s1600/Fig3_Resultados_NDM_set_1-194.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="392" src="http://1.bp.blogspot.com/-xskO--Z4yxg/T8Ch7oMc5II/AAAAAAAAANo/LcY5WCxTQ4k/s640/Fig3_Resultados_NDM_set_1-194.jpg" width="640" /&gt;&lt;/a&gt;&lt;/div&gt;
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&lt;a href="http://4.bp.blogspot.com/-3bsgnI_YMX0/T8Ch89lkd9I/AAAAAAAAANw/odnfcUx9Mf0/s1600/Fig3a_Resultados_NDM_set_5-194.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="392" src="http://4.bp.blogspot.com/-3bsgnI_YMX0/T8Ch89lkd9I/AAAAAAAAANw/odnfcUx9Mf0/s640/Fig3a_Resultados_NDM_set_5-194.jpg" width="640" /&gt;&lt;/a&gt;&lt;/div&gt;
En este caso se presenta el Consenso a partir del 70% de similaridad de especies que integran el área.&lt;br /&gt;
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&lt;a href="http://4.bp.blogspot.com/-hkwZWOXaXw8/T8Ch-GotvrI/AAAAAAAAAN4/G-aNzOz6qxg/s1600/Fig4_Resultados_NDM_Consenso_14-133.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="392" src="http://4.bp.blogspot.com/-hkwZWOXaXw8/T8Ch-GotvrI/AAAAAAAAAN4/G-aNzOz6qxg/s640/Fig4_Resultados_NDM_Consenso_14-133.jpg" width="640" /&gt;&lt;/a&gt;&lt;/div&gt;
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En lineas generales, existen áreas con elevados índices de endemicidad: Andes y Cordillera Central de La Costa. Un análisis posterior con cuadriculas más pequeñas reveló áreas de endemismo similares, pero con mayor índice de endemicidad para las áreas al Sur del país.&amp;nbsp;&lt;/div&gt;
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En una próxima entrada tratare de disponer de bioregistros de grupos de plantas.&lt;/div&gt;</description><link>http://cladisticaybiogeografia.blogspot.com/2012/05/areas-de-endemismo-de-venezuela.html</link><author>noreply@blogger.com (Jonathan Liria)</author><media:thumbnail url="http://2.bp.blogspot.com/-mnrHRfzENa0/T8Ao49ysgXI/AAAAAAAAANM/ljnKuhoFtyI/s72-c/Fig0_Szumik_etal2011_Endemismo_Argentina.jpg" height="72" width="72" /><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-8353434251152737341</guid><pubDate>Mon, 21 May 2012 16:04:00 +0000</pubDate><atom:updated>2012-05-21T09:04:11.507-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">sistemática</category><category domain="http://www.blogger.com/atom/ns#">matrices</category><category domain="http://www.blogger.com/atom/ns#">TnT</category><category domain="http://www.blogger.com/atom/ns#">filogenia</category><category domain="http://www.blogger.com/atom/ns#">megafilogenias</category><category domain="http://www.blogger.com/atom/ns#">GenBank</category><category domain="http://www.blogger.com/atom/ns#">conferencias</category><category domain="http://www.blogger.com/atom/ns#">cladismo</category><title>Megafilogenias: ¿Quién y cómo lo hicieron?</title><description>&lt;div style="text-align: justify;"&gt;
¿Existe un record para la filogenia de mayores dimensiones posible?&lt;/div&gt;
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Imaginen el Record Mundial Guinnes para la filogenia que contemple el mayor número de taxa posibles (Megafilogenia):&lt;/div&gt;
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&lt;a href="http://3.bp.blogspot.com/--BFVYO1MCl0/T7pSVD78_CI/AAAAAAAAAMw/CBKGIRX1Dy8/s1600/Dibujo_Guinness1.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="193" src="http://3.bp.blogspot.com/--BFVYO1MCl0/T7pSVD78_CI/AAAAAAAAAMw/CBKGIRX1Dy8/s200/Dibujo_Guinness1.jpg" width="200" /&gt;&lt;/a&gt;&lt;/div&gt;
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Ya existe un record:&lt;/div&gt;
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&lt;div style="text-align: justify;"&gt;
Goloboﬀ, P.A.,
Catalano, S.A., Mirande, J.M., Szumik, C.A., Arias, J.S., Kallersjo,
M., Farris, J.S., 2009. Phylogenetic analysis of 73 060 taxa
corroborates major eukaryotic groups. Cladistics 25, 211–
230.&lt;/div&gt;
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&lt;a href="http://2.bp.blogspot.com/-XjKqXuynUgY/T7pTFJe-U9I/AAAAAAAAAM4/pZzDLHcfqGg/s1600/Goloboff_etal2009_73600+taxa.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="342" src="http://2.bp.blogspot.com/-XjKqXuynUgY/T7pTFJe-U9I/AAAAAAAAAM4/pZzDLHcfqGg/s400/Goloboff_etal2009_73600+taxa.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;
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Esto no implica que hasta el 2009 no se realizaran megafilogenias. Sin&amp;nbsp; embargo, este es el estudio de mayores dimensiones (taxa y caracteres) conocido hasta el momento.&amp;nbsp;&lt;/div&gt;
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Recientemente, Goloboff y Catalano (2012) publicaron un articulo donde se explica como puede prepararse una matriz de tales dimensiones:&lt;/div&gt;
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&amp;nbsp;&lt;a href="http://3.bp.blogspot.com/-kDLNHt3Qu48/T7pU-9zR_nI/AAAAAAAAANA/jhhR7q6knro/s1600/Goloboff&amp;amp;Catalano2012_Gb-2-TnT.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="342" src="http://3.bp.blogspot.com/-kDLNHt3Qu48/T7pU-9zR_nI/AAAAAAAAANA/jhhR7q6knro/s400/Goloboff&amp;amp;Catalano2012_Gb-2-TnT.jpg" width="400" /&gt;&lt;/a&gt;
&lt;span style="display: block; margin: 12px 0pt 4px;"&gt;&amp;nbsp;&lt;/span&gt;&lt;span style="display: block; margin: 12px 0pt 4px;"&gt;&amp;nbsp;&lt;/span&gt;&lt;span style="display: block; margin: 12px 0pt 4px;"&gt;&amp;nbsp;&lt;/span&gt;&lt;span style="display: block; margin: 12px 0pt 4px;"&gt;&amp;nbsp;&lt;/span&gt;&lt;span style="display: block; margin: 12px 0pt 4px;"&gt;&amp;nbsp;&lt;/span&gt;&lt;span style="display: block; margin: 12px 0pt 4px;"&gt;&amp;nbsp;&lt;/span&gt;&lt;span style="display: block; margin: 12px 0pt 4px;"&gt;&amp;nbsp;&lt;/span&gt;&lt;span style="display: block; margin: 12px 0pt 4px;"&gt;&amp;nbsp;&lt;/span&gt;&lt;span style="display: block; margin: 12px 0pt 4px;"&gt;&amp;nbsp;&lt;/span&gt;&lt;span style="display: block; margin: 12px 0pt 4px;"&gt;&amp;nbsp;&lt;/span&gt;&lt;span style="display: block; margin: 12px 0pt 4px;"&gt;&amp;nbsp;&lt;/span&gt;&lt;span style="display: block; margin: 12px 0pt 4px;"&gt;&amp;nbsp;&lt;/span&gt;&lt;span style="display: block; margin: 12px 0pt 4px;"&gt;Este es el manual de GB-to-TnT:&lt;/span&gt;&lt;b style="display: block; margin: 12px 0pt 4px;"&gt; &lt;/b&gt;&lt;b style="display: block; margin: 12px 0pt 4px;"&gt;&lt;a href="http://www.slideshare.net/jliria/gb2tntmanualpdf" target="_blank" title="GB2TNT_MANUAL.pdf"&gt;GB2TNT_MANUAL.pdf&lt;/a&gt;&lt;/b&gt;&lt;b style="display: block; margin: 12px 0pt 4px;"&gt;&amp;nbsp;&lt;/b&gt; &lt;iframe frameborder="0" height="510" marginheight="0" marginwidth="0" scrolling="no" src="http://www.slideshare.net/slideshow/embed_code/13014432" width="477"&gt;&lt;/iframe&gt; &lt;/div&gt;
&lt;div style="padding: 5px 0pt 12px;"&gt;
View more &lt;a href="http://www.slideshare.net/" target="_blank"&gt;documents&lt;/a&gt; from &lt;a href="http://www.slideshare.net/jliria" target="_blank"&gt;jliria&lt;/a&gt; &lt;/div&gt;
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El año pasado, tuvimos la visita del Dr. Pablo Goloboff, durante el Congreso Venezolano de Entomología. En su Charla nos mostró algunos de los avances que permitieron realizar esta Megafilogenia. Aquí les dejo la presentación:&lt;/div&gt;
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&lt;div id="__ss_13014437" style="text-align: justify; width: 425px;"&gt;
&lt;b style="display: block; margin: 12px 0pt 4px;"&gt;&lt;a href="http://www.slideshare.net/jliria/venezuela2011ppt" target="_blank" title="Venezuela_2011.ppt"&gt;Venezuela_2011.ppt&lt;/a&gt;&lt;/b&gt; &lt;iframe frameborder="0" height="355" marginheight="0" marginwidth="0" scrolling="no" src="http://www.slideshare.net/slideshow/embed_code/13014437" width="425"&gt;&lt;/iframe&gt; &lt;br /&gt;
&lt;div style="padding: 5px 0pt 12px;"&gt;
View more &lt;a href="http://www.slideshare.net/thecroaker/death-by-powerpoint" target="_blank"&gt;PowerPoint&lt;/a&gt; from &lt;a href="http://www.slideshare.net/jliria" target="_blank"&gt;jliria&lt;/a&gt; &lt;/div&gt;
&lt;/div&gt;
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&lt;br /&gt;</description><link>http://cladisticaybiogeografia.blogspot.com/2012/05/megafilogenias-quien-y-como-lo-hicieron.html</link><author>noreply@blogger.com (Jonathan Liria)</author><media:thumbnail url="http://3.bp.blogspot.com/--BFVYO1MCl0/T7pSVD78_CI/AAAAAAAAAMw/CBKGIRX1Dy8/s72-c/Dibujo_Guinness1.jpg" height="72" width="72" /><thr:total>2</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-3042056785847491807</guid><pubDate>Thu, 26 Apr 2012 21:00:00 +0000</pubDate><atom:updated>2012-04-26T14:14:12.834-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">endemismo</category><category domain="http://www.blogger.com/atom/ns#">NDM</category><category domain="http://www.blogger.com/atom/ns#">biogeografía</category><category domain="http://www.blogger.com/atom/ns#">mapas</category><title>Mapas base para NDM (8)</title><description>Esta entrada contempla un mapa base del Neártico y Neotrópico. Es uno de los primeros que hice... pero hasta el momento no lo había colocado en el blog.&lt;br /&gt;
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&lt;a href="http://3.bp.blogspot.com/-7Bw-XzrgU7Q/T5m1TvajcRI/AAAAAAAAAMY/cXx8y5-7q9Q/s1600/Neartico-Neotropico.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="400" src="http://3.bp.blogspot.com/-7Bw-XzrgU7Q/T5m1TvajcRI/AAAAAAAAAMY/cXx8y5-7q9Q/s400/Neartico-Neotropico.jpg" width="356" /&gt;&lt;/a&gt;&lt;/div&gt;
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Este es el vínculo para el archivo &lt;a href="https://www.box.com/s/cfa83b21af907ff51df6" target="_blank"&gt;XYD&lt;/a&gt;.&lt;br /&gt;
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Espero les sirva!</description><link>http://cladisticaybiogeografia.blogspot.com/2012/04/mapas-base-para-ndm-8.html</link><author>noreply@blogger.com (Jonathan Liria)</author><media:thumbnail url="http://3.bp.blogspot.com/-7Bw-XzrgU7Q/T5m1TvajcRI/AAAAAAAAAMY/cXx8y5-7q9Q/s72-c/Neartico-Neotropico.jpg" height="72" width="72" /><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-2566910205926785344</guid><pubDate>Thu, 19 Apr 2012 21:50:00 +0000</pubDate><atom:updated>2012-04-19T14:50:09.258-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">endemismo</category><category domain="http://www.blogger.com/atom/ns#">NDM</category><category domain="http://www.blogger.com/atom/ns#">biogeografia</category><category domain="http://www.blogger.com/atom/ns#">mapas</category><title>Mapas base para NDM (7)</title><description>Esta entrada contiene el mapa base (map line) para &lt;a href="http://www.zmuc.dk/public/phylogeny/endemism/" target="_blank"&gt;NDM &lt;/a&gt;del Continente Africano&lt;br /&gt;
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&lt;a href="http://1.bp.blogspot.com/-9b43YJT4FPY/T5B4vet-K_I/AAAAAAAAAMI/SPuoh2CRrQw/s1600/Africa.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="320" src="http://1.bp.blogspot.com/-9b43YJT4FPY/T5B4vet-K_I/AAAAAAAAAMI/SPuoh2CRrQw/s320/Africa.jpg" width="310" /&gt;&lt;/a&gt;&lt;/div&gt;
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&lt;a href="http://www.box.com/s/479e9f724ff07488ce93" target="_blank"&gt;Formato xyd (xyData)&lt;/a&gt;&lt;br /&gt;
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Formato shp (Shapefile)&lt;br /&gt;
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Les recuerdo (tomado del &lt;a href="http://www.zmuc.dk/public/phylogeny/endemism/Manual_VNDM.pdf" target="_blank"&gt;Manual de NDM&lt;/a&gt;) en que consiste el comando "map line":&lt;br /&gt;
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&lt;div style="text-align: justify;"&gt;
"&lt;i&gt;En este tipo de matrices VNDM permite poner de fondo los límites de un mapa. Esto se logra incluyendo al final del archivo&lt;/i&gt;:&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;/div&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; map&amp;nbsp; &lt;br /&gt;
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&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 66.167 21.800 &lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 66.117 21.817 &lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 66.067 21.833 &lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 66.050 21.850 &lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 66.050 21.867 &lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 66.050 21.883 &lt;br /&gt;
&lt;br /&gt;
&lt;div style="text-align: justify;"&gt;
&lt;i&gt;Cada línea (máximo 300 líneas) del mapa puede tener&amp;nbsp; hasta 5000 referencias planas. Nótese que si se termina de definir la península de Yucatán y se pasa a la costa occidental de México debe definirse una nueva línea, sino ese salto aparecerá dibujado también en el mapa. También es posible editar las líneas en modo gráfico y salvar posteriormente las coordenadas resultantes."&lt;/i&gt;&lt;/div&gt;
&lt;div style="text-align: justify;"&gt;
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Ahora que el mapa base esta disponible, sería interesante realizar un analisis de endemismo con NDM para el Continente Africano. Asi podrían compararse los resultados con otros estudios.&lt;/div&gt;</description><link>http://cladisticaybiogeografia.blogspot.com/2012/04/mapas-base-para-ndm-7.html</link><author>noreply@blogger.com (Jonathan Liria)</author><media:thumbnail url="http://1.bp.blogspot.com/-9b43YJT4FPY/T5B4vet-K_I/AAAAAAAAAMI/SPuoh2CRrQw/s72-c/Africa.jpg" height="72" width="72" /><thr:total>2</thr:total><enclosure url="http://www.zmuc.dk/public/phylogeny/endemism/Manual_VNDM.pdf" length="485557" type="application/pdf" /><media:content url="http://www.zmuc.dk/public/phylogeny/endemism/Manual_VNDM.pdf" fileSize="485557" type="application/pdf" /><itunes:explicit>no</itunes:explicit><itunes:subtitle>Esta entrada contiene el mapa base (map line) para NDM del Continente Africano Formato xyd (xyData) Formato shp (Shapefile) Les recuerdo (tomado del Manual de NDM) en que consiste el comando "map line": "En este tipo de matrices VNDM permite poner de fond</itunes:subtitle><itunes:author>noreply@blogger.com (Jonathan Liria)</itunes:author><itunes:summary>Esta entrada contiene el mapa base (map line) para NDM del Continente Africano Formato xyd (xyData) Formato shp (Shapefile) Les recuerdo (tomado del Manual de NDM) en que consiste el comando "map line": "En este tipo de matrices VNDM permite poner de fondo los límites de un mapa. Esto se logra incluyendo al final del archivo:&amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; map&amp;nbsp; &amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; line&amp;nbsp; &amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 66.217 21.767 &amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 66.183 21.783 &amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 66.167 21.800 &amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 66.117 21.817 &amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 66.067 21.833 &amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 66.050 21.850 &amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 66.050 21.867 &amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 66.050 21.883 Cada línea (máximo 300 líneas) del mapa puede tener&amp;nbsp; hasta 5000 referencias planas. Nótese que si se termina de definir la península de Yucatán y se pasa a la costa occidental de México debe definirse una nueva línea, sino ese salto aparecerá dibujado también en el mapa. También es posible editar las líneas en modo gráfico y salvar posteriormente las coordenadas resultantes." Ahora que el mapa base esta disponible, sería interesante realizar un analisis de endemismo con NDM para el Continente Africano. Asi podrían compararse los resultados con otros estudios.</itunes:summary><itunes:keywords>endemismo, NDM, biogeografia, mapas</itunes:keywords></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-1564101991433961749</guid><pubDate>Wed, 18 Apr 2012 20:03:00 +0000</pubDate><atom:updated>2012-04-18T13:06:32.433-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">MaxEnt</category><category domain="http://www.blogger.com/atom/ns#">Distribución</category><category domain="http://www.blogger.com/atom/ns#">Conservación</category><category domain="http://www.blogger.com/atom/ns#">Modelo</category><title>Modelo de Nicho y especies amenazadas</title><description>&lt;div style="text-align: justify;"&gt;Encontré un articulo interesante sobre el uso de los modelos de distribución y su aplicación en el monitoreo de especies amenazadas. En este caso se utilizó &lt;a href="http://www.cs.princeton.edu/%7Eschapire/maxent/"&gt;MaxEnt&lt;/a&gt; para predecir la distribución potencial de &lt;a href="http://www.floravascular.com/index.php?spp=Astragalus%20oxyglottis"&gt;Astragalus oxyglottis&lt;/a&gt;.&lt;/div&gt;&lt;br /&gt;
&lt;a href="http://es.scribd.com/doc/21597011/Los-modelos-de-distribucion-en-el-trabajo-de-campo-localizacion-de-nuevas-poblaciones-de-especies-amenazadas" style="display: block; font: 14px Helvetica,Arial,Sans-serif; margin: 12px auto 6px; text-decoration: underline;" title="View Los modelos de distribución en el trabajo de campo: localización de nuevas poblaciones de especies amenazadas on Scribd"&gt;Los modelos de distribución en el trabajo de campo: localización de nuevas poblaciones de especies amenazadas&lt;/a&gt;&lt;iframe class="scribd_iframe_embed" data-aspect-ratio="" data-auto-height="true" frameborder="0" height="600" id="doc_16803" scrolling="no" src="http://www.scribd.com/embeds/21597011/content?start_page=1&amp;amp;view_mode=list&amp;amp;access_key=key-1laauyeydanfymin3klb" width="100%"&gt;&lt;/iframe&gt;&lt;br /&gt;
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Tambien si desean profundizar más sobre el estudio de caso para esta especie, consulten:&lt;br /&gt;
&lt;br /&gt;
&lt;a href="http://ide.ugr.es/blasbenito/tesis/CAPITULO_7/GB/Astragalus_oxyglottis.html"&gt;Informe de resultados de Astragalus oxyglottis&lt;/a&gt;&lt;br /&gt;
&lt;br /&gt;
&lt;div class="separator" style="clear: both; text-align: center;"&gt;&lt;a href="http://ide.ugr.es/blasbenito/tesis/CAPITULO_7/GB/Astragalus_oxyglottis/8_ME_previa.png" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="205" src="http://ide.ugr.es/blasbenito/tesis/CAPITULO_7/GB/Astragalus_oxyglottis/8_ME_previa.png" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;</description><link>http://cladisticaybiogeografia.blogspot.com/2012/04/modelo-de-nicho-y-especies-amenazadas.html</link><author>noreply@blogger.com (Jonathan Liria)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-5599831947786115578</guid><pubDate>Sat, 14 Apr 2012 12:25:00 +0000</pubDate><atom:updated>2012-04-14T05:25:06.910-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">panbiogeografía</category><category domain="http://www.blogger.com/atom/ns#">biogeografía</category><category domain="http://www.blogger.com/atom/ns#">libro</category><category domain="http://www.blogger.com/atom/ns#">Croizat</category><title>Libro "Manual of Phytogeography"</title><description>Aqui les dejo este clásico:&lt;br /&gt;
&lt;br /&gt;
&lt;a href="http://www.4shared.com/file/FDXLvXib/Lon_Croizat-Manual_of_Phytogeo.html" target="_blank"&gt;Léon_Croizat-Manual_of_Phytogeography__An_Account_of_Plant-Dispersal_Throughout_the_World__-Uitgeverij_Dr._W._Junk(1952).djvu&lt;/a&gt;&lt;br /&gt;
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&lt;div class="separator" style="clear: both; text-align: center;"&gt;&lt;a href="http://3.bp.blogspot.com/-tdR8u8Q-yoY/T4lq7FwfZnI/AAAAAAAAAMA/o61MiitAI2I/s1600/Manual_Phytogeography.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="400" src="http://3.bp.blogspot.com/-tdR8u8Q-yoY/T4lq7FwfZnI/AAAAAAAAAMA/o61MiitAI2I/s400/Manual_Phytogeography.jpg" width="291" /&gt;&lt;/a&gt;&lt;/div&gt;&lt;br /&gt;
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Esta en formato &lt;a href="http://es.wikipedia.org/wiki/DjVu" target="_blank"&gt;djvu&lt;/a&gt;. Si no poseen un visor para este tipo de archivos, esta es una buena opción:&lt;br /&gt;
&lt;br /&gt;
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&lt;div class="separator" style="clear: both; text-align: center;"&gt;&lt;a href="http://djvu.sourceforge.net/images/front-banner.gif" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="31" src="http://djvu.sourceforge.net/images/front-banner.gif" width="200" /&gt;&lt;/a&gt;&lt;/div&gt;&lt;br /&gt;
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http://djvu.sourceforge.net/</description><link>http://cladisticaybiogeografia.blogspot.com/2012/04/libro-manual-of-phytogeography.html</link><author>noreply@blogger.com (Jonathan Liria)</author><media:thumbnail url="http://3.bp.blogspot.com/-tdR8u8Q-yoY/T4lq7FwfZnI/AAAAAAAAAMA/o61MiitAI2I/s72-c/Manual_Phytogeography.jpg" height="72" width="72" /><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-780979980571814558</guid><pubDate>Sun, 01 Apr 2012 23:17:00 +0000</pubDate><atom:updated>2012-04-04T17:11:54.851-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">vertebrados</category><category domain="http://www.blogger.com/atom/ns#">diversidad</category><category domain="http://www.blogger.com/atom/ns#">SIG</category><category domain="http://www.blogger.com/atom/ns#">Venezuela</category><category domain="http://www.blogger.com/atom/ns#">riqueza</category><title>Vertebrados de Venezuela</title><description>&lt;div style="text-align: justify;"&gt;En esta entrada les mostraré los resultados preliminares de un analisis realizado con base en 1349 especies de Mamíferos, Reptiles, Anfibios y Aves registradas en Venezuela. La base de datos consta de 7607 bioregistros.&lt;/div&gt;&lt;div style="text-align: justify;"&gt;&lt;br /&gt;
&lt;/div&gt;&lt;div style="text-align: justify;"&gt;A partir de estas especies y bioregistros se calculó en &lt;a href="http://www.diva-gis.org/" target="_blank"&gt;DIVA-GIS&lt;/a&gt;:&lt;/div&gt;&lt;div style="text-align: justify;"&gt;&lt;br /&gt;
&lt;/div&gt;&lt;div style="text-align: justify;"&gt;Riqueza: cuenta las clases diferentes de una variable (por ejemplo, los nombres de especies en un conjunto de datos que cubren un pool génico) que están presentes en una celda de una cuadrícula.&lt;br /&gt;
&lt;br /&gt;
&lt;/div&gt;&lt;div style="text-align: justify;"&gt;Abundancia: calcula el número de puntos presentes en cada celda de la cuadrícula.&amp;nbsp;&lt;/div&gt;&lt;div style="text-align: justify;"&gt;&lt;br /&gt;
&lt;br /&gt;
&lt;/div&gt;&lt;div style="text-align: justify;"&gt;Diversidad: calcula el índice de diversidad de &lt;a href="http://es.wikipedia.org/wiki/%C3%8Dndice_de_Shannon" target="_blank"&gt;Shannon-Wiener&lt;/a&gt; para cada celda de la cuadrícula.&lt;/div&gt;&lt;div style="text-align: justify;"&gt;&lt;br /&gt;
&lt;/div&gt;&lt;div style="text-align: justify;"&gt;Finalmente, las salidas en formato GRID (cuadrículas de 1° x 1°) fueron exportadas a capas (=SHAPEFILE) para generar la vista en &lt;a href="http://www.qgis.org/" target="_blank"&gt;QUANTUM-GIS&lt;/a&gt;:&amp;nbsp; &lt;/div&gt;&lt;div style="text-align: justify;"&gt;&lt;/div&gt;&lt;br /&gt;
&lt;div class="separator" style="clear: both; text-align: center;"&gt;&lt;a href="http://3.bp.blogspot.com/-6v5CCDa_oYM/T3jd-vrLQCI/AAAAAAAAALc/-jBqO4HycQg/s1600/fig1.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="250" src="http://3.bp.blogspot.com/-6v5CCDa_oYM/T3jd-vrLQCI/AAAAAAAAALc/-jBqO4HycQg/s400/fig1.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;&lt;div style="text-align: center;"&gt;&lt;br /&gt;
&lt;/div&gt;&lt;div style="text-align: center;"&gt;Figura 1. Vista de los registros de Vertebrados de Venezuela &lt;/div&gt;&lt;br /&gt;
&lt;br /&gt;
&lt;div class="separator" style="clear: both; text-align: center;"&gt;&lt;a href="http://3.bp.blogspot.com/-TlDMdt5o2Ck/T3jeFZOuPcI/AAAAAAAAALk/YIu5CwN85I0/s1600/fig2.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="250" src="http://3.bp.blogspot.com/-TlDMdt5o2Ck/T3jeFZOuPcI/AAAAAAAAALk/YIu5CwN85I0/s400/fig2.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;&lt;div style="text-align: center;"&gt;&lt;br /&gt;
&lt;/div&gt;&lt;div style="text-align: center;"&gt;Figura 2. Abundancia de bioregistros &lt;/div&gt;&amp;nbsp; &lt;br /&gt;
&lt;br /&gt;
&lt;div class="separator" style="clear: both; text-align: center;"&gt;&lt;a href="http://4.bp.blogspot.com/-neAp8xXTEZ4/T3jeKSu3EvI/AAAAAAAAALs/xVDzzH8FAmg/s1600/fig3.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="250" src="http://4.bp.blogspot.com/-neAp8xXTEZ4/T3jeKSu3EvI/AAAAAAAAALs/xVDzzH8FAmg/s400/fig3.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;&lt;br /&gt;
&lt;div style="text-align: center;"&gt;Figura 3. Número de especies de Vertebrados&lt;/div&gt;&lt;div style="text-align: center;"&gt;&lt;/div&gt;&lt;br /&gt;
&lt;div class="separator" style="clear: both; text-align: center;"&gt;&lt;a href="http://3.bp.blogspot.com/-rUoD9qwtKAE/T3jeMyTSytI/AAAAAAAAAL0/58QQlmPlW80/s1600/fig4.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="250" src="http://3.bp.blogspot.com/-rUoD9qwtKAE/T3jeMyTSytI/AAAAAAAAAL0/58QQlmPlW80/s400/fig4.jpg" width="400" /&gt;&lt;/a&gt;&lt;/div&gt;&lt;br /&gt;
&lt;div style="text-align: center;"&gt;Figura 4. Diversidad de Vertebrados de Venezuela&lt;/div&gt;</description><link>http://cladisticaybiogeografia.blogspot.com/2012/04/vertebrados-de-venezuela.html</link><author>noreply@blogger.com (Jonathan Liria)</author><media:thumbnail url="http://3.bp.blogspot.com/-6v5CCDa_oYM/T3jd-vrLQCI/AAAAAAAAALc/-jBqO4HycQg/s72-c/fig1.jpg" height="72" width="72" /><thr:total>2</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-7086209542673846414.post-8114358519957773864</guid><pubDate>Sun, 01 Apr 2012 15:58:00 +0000</pubDate><atom:updated>2012-04-01T09:00:47.629-07:00</atom:updated><category domain="http://www.blogger.com/atom/ns#">endemismo</category><category domain="http://www.blogger.com/atom/ns#">NDM</category><category domain="http://www.blogger.com/atom/ns#">mapas</category><title>Mapas base para NDM (6)</title><description>Aquí les coloco el mapa base de Australia para incluirse en &lt;a href="http://www.zmuc.dk/public/phylogeny/endemism/" target="_blank"&gt;NDM&lt;/a&gt;:&lt;br /&gt;
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&lt;div class="separator" style="clear: both; text-align: center;"&gt;&lt;a href="http://2.bp.blogspot.com/-4x3JmO9Eong/TayFt8B8k9I/AAAAAAAAISU/cnr8MCq94e8/s1600/australia+map+outline.GIF" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"&gt;&lt;img border="0" height="296" src="http://2.bp.blogspot.com/-4x3JmO9Eong/TayFt8B8k9I/AAAAAAAAISU/cnr8MCq94e8/s320/australia+map+outline.GIF" width="320" /&gt;&lt;/a&gt;&lt;/div&gt;&lt;br /&gt;
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&lt;div class="separator" style="clear: both; text-align: center;"&gt;&lt;/div&gt;Archivos en formato &lt;a href="http://www.box.com/s/33dc8470a6c11e734d3d" target="_blank"&gt;XYD &lt;/a&gt;y capa (&lt;a href="http://www.box.com/s/0e5b44aab2de0685fae2" target="_blank"&gt;SHP&lt;/a&gt;)&lt;br /&gt;
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En otras entradas trataré de colocar nuevos mapas...</description><link>http://cladisticaybiogeografia.blogspot.com/2012/04/mapas-base-para-ndm-6.html</link><author>noreply@blogger.com (Jonathan Liria)</author><media:thumbnail url="http://2.bp.blogspot.com/-4x3JmO9Eong/TayFt8B8k9I/AAAAAAAAISU/cnr8MCq94e8/s72-c/australia+map+outline.GIF" height="72" width="72" /><thr:total>0</thr:total></item><language>en-us</language><media:rating>nonadult</media:rating></channel></rss>
