{"id":3339,"date":"2026-02-24T20:12:09","date_gmt":"2026-02-24T20:12:09","guid":{"rendered":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/"},"modified":"2026-02-24T20:12:09","modified_gmt":"2026-02-24T20:12:09","slug":"mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model","status":"publish","type":"post","link":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/","title":{"rendered":"Beherrschung der organisatorischen Ausrichtung: Ein umfassender Leitfaden zum McKinsey-7S-Modell"},"content":{"rendered":"<p>In der komplexen Welt der Unternehmensstrategie ist ein brillanter Plan nur die halbe Miete. Die eigentliche Herausforderung liegt oft in der Umsetzung und der Ausrichtung. Organisationen sind lebendige Systeme, bei denen eine Ver\u00e4nderung in einem Bereich sich auf andere auswirkt. Um diese Komplexit\u00e4t zu meistern, st\u00fctzen sich F\u00fchrungskr\u00e4fte auf robuste Rahmenwerke, um sicherzustellen, dass jedes Element ihres Unternehmens in dieselbe Richtung bewegt wird. Unter diesen Werkzeugen ist das McKinsey-7S-Modell eines der dauerhaftesten und effektivsten.<\/p>\n<p><img alt=\"McKinsey 7S Model layout\" decoding=\"async\" src=\"https:\/\/canvas.visual-paradigm.com\/wp-content\/uploads\/2025\/12\/McKinsey-7S-Model-layout-1024x574.png\"\/><\/p>\n<p>Dieser Leitfaden erkundet die Tiefen des McKinsey-7S-Rahmenwerks, eines zentralen Bestandteils des <a href=\"https:\/\/www.archimetric.com\/comprehensive-tutorial-visual-paradigm-model-canvas-tool\/\">Ultimativen Business-Canvas-Tools<\/a>. Wir werden seine zentralen Konzepte analysieren, schrittweise Anleitungen zur Umsetzung bereitstellen und zeigen, wie k\u00fcnstliche Intelligenz (KI) die Art und Weise revolutionieren kann, wie Sie Ihre Organisation analysieren und ausrichten.<\/p>\n<h2>Wichtige Konzepte: Die Entschl\u00fcsselung des 7S-Rahmenwerks<\/h2>\n<p>Das McKinsey-7S-Modell ist ein strategisches Werkzeug, das zur Bewertung der organisatorischen Effektivit\u00e4t dient. Im Gegensatz zu Rahmenwerken, die ausschlie\u00dflich auf externe Faktoren (wie PESTLE) oder Wettbewerbsposition (wie Porter\u2019s Five Forces) abstellen, konzentriert sich das 7S-Modell auf die interne Ausrichtung. Die Grundidee ist einfach: Damit eine Organisation gut funktioniert, m\u00fcssen sieben spezifische Elemente ausgerichtet und wechselseitig st\u00fctzend sein.<\/p>\n<p>Diese sieben Elemente werden in \u201eHarte\u201c und \u201eWeiche\u201c Elemente eingeteilt. Die Unterscheidung ist entscheidend f\u00fcr eine effektive Analyse.<\/p>\n<h3>Die harten Elemente<\/h3>\n<p>Sie sind greifbar, leichter zu identifizieren und direkt durch Managemententscheidungen beeinflussbar.<\/p>\n<ul>\n<li><strong>Strategie:<\/strong> Der Plan, der entwickelt wurde, um einen Wettbewerbsvorteil gegen\u00fcber der Konkurrenz aufzubauen und aufrechtzuerhalten. Er legt die Route fest, die die Organisation einschlagen m\u00f6chte, um ihre Ziele zu erreichen.<\/li>\n<li><strong>Struktur:<\/strong> Die Art und Weise, wie die Organisation strukturiert ist und wer wem berichtet. Dazu geh\u00f6ren das Organigramm und die Hierarchie der Autorit\u00e4t.<\/li>\n<li><strong>Systeme:<\/strong> Die t\u00e4glichen Aktivit\u00e4ten und Verfahren, an denen die Mitarbeiter arbeiten, um ihre Aufgaben zu erf\u00fcllen. Dazu geh\u00f6ren alles von IT-Systemen \u00fcber Finanzprozesse bis hin zu HR-Abl\u00e4ufen.<\/li>\n<\/ul>\n<h3>Die weichen Elemente<\/h3>\n<p>Sie sind immateriell, schwerer zu beschreiben und werden durch die Kultur beeinflusst. Sie sind jedoch oft genauso wichtig wie die harten Elemente f\u00fcr den Erfolg.<\/p>\n<ul>\n<li><strong>Geteilte Werte:<\/strong> Der Kern des Modells. Es handelt sich um die grundlegenden Werte des Unternehmens, die sich in der Unternehmenskultur und der allgemeinen Arbeitsmoral widerspiegeln. Sie verbinden jedes andere Element.<\/li>\n<li><strong>Stil:<\/strong> Der von der F\u00fchrung \u00fcbernommene Stil. Dies umfasst den kulturellen Stil der Organisation und das Verhalten wichtiger Manager bei der Erreichung der Unternehmensziele.<\/li>\n<li><strong>Personal:<\/strong> Die Mitarbeiter und ihre allgemeinen F\u00e4higkeiten. Es geht nicht nur um die Kopfzahl, sondern um Talentmanagement und die Art und Weise, wie die Belegschaft gef\u00f6rdert wird.<\/li>\n<li><strong>F\u00e4higkeiten:<\/strong> Die tats\u00e4chlichen F\u00e4higkeiten und Kompetenzen der Mitarbeiter des Unternehmens. Es beantwortet die Frage: \u201eWas k\u00f6nnen wir am besten?\u201c<\/li>\n<\/ul>\n<h2>Anleitungen: Umsetzung der McKinsey-7S-Analyse<\/h2>\n<p>Die Anwendung des McKinsey-7S-Modells erfordert einen strukturierten Ansatz. Ob Sie ein Gr\u00fcndungsf\u00fchrer sind, der das Business-Canvas-Toolkit nutzt, oder ein Unternehmensstrateg, befolgen Sie diese Anleitungen, um eine gr\u00fcndliche Analyse sicherzustellen.<\/p>\n<h3>Schritt 1: Bewertung des aktuellen Zustands<\/h3>\n<p>Beginnen Sie damit, wie Ihre Organisation derzeit in allen sieben Dimensionen funktioniert, aufzuzeichnen. Seien Sie ehrlich und kritisch. Sind Ihre Systeme veraltet? Hemmt Ihre Struktur Ihre Strategie?<\/p>\n<ul>\n<li><strong><a href=\"https:\/\/circle.visual-paradigm.com\/docs\/impact-analysis\/analysis-diagram\/how-to-use-analysis-diagram-to-visualize-dependencies-between-elements\/\">\u00dcberpr\u00fcfung der Interdependenzen<\/a>:<\/strong> Suchen Sie nach L\u00fccken. Zum Beispiel, passt Ihr <em>Struktur<\/em> (hierarchisch) mit Ihrem <em>Strategie<\/em> (agile Innovation)?<\/li>\n<li><strong>Daten sammeln:<\/strong> Verwenden Sie Umfragen, Interviews und Beobachtungen, um die \u201eweichen\u201c Elemente wie Stil und gemeinsame Werte zu bewerten.<\/li>\n<\/ul>\n<h3>Schritt 2: Definieren des zuk\u00fcnftigen Zustands<\/h3>\n<p>Ermitteln Sie, wo die Organisation sein muss. Wenn Sie ein neues Produkt lancieren oder in einen neuen Markt eintreten, wie m\u00fcssen die sieben Elemente sich \u00e4ndern, um dieses Ziel zu unterst\u00fctzen?<\/p>\n<h3><a href=\"https:\/\/www.visual-paradigm.com\/guide\/bpmn\/business-procses-modeling-and-gap-analysis\/\">Schritt 3: Analyse der L\u00fccken<\/a><\/h3>\n<p>Vergleichen Sie Ihren aktuellen Zustand mit Ihrem gew\u00fcnschten zuk\u00fcnftigen Zustand. Die Abweichungen zeigen die Bereiche auf, die eine Intervention erfordern.<\/p>\n<h3>Schritt 4: Entwicklung eines Aktionsplans<\/h3>\n<p>Erstellen Sie eine Roadmap, um die L\u00fccken zu schlie\u00dfen. Denken Sie daran, dass die \u00c4nderung eines Elements <a href=\"https:\/\/www.visual-paradigm.com\/features\/impact-analysis-tools\/\">andere beeinflusst<\/a>. Wenn Sie neue <em>Systeme<\/em> (z.\u202fB. ein neues CRM), m\u00fcssen Sie m\u00f6glicherweise <em>F\u00e4higkeiten<\/em> (Ausbildung) und passen <em>Struktur<\/em> (IT-Unterst\u00fctzungsrollen).<\/p>\n<h2>VP AI: Wie Visual Paradigm AI die strategische Analyse verbessert<\/h2>\n<p>Traditionelle strategische Analyse kann zeitaufwendig und anf\u00e4llig f\u00fcr Verzerrungen sein.<a href=\"https:\/\/www.archimetric.com\/what-is-the-business-model-canvas-why-use-visual-paradigms-ai-bmc-tool\/\">Das von KI gest\u00fctzte Canvas-Tool von Visual Paradigm<\/a> transformiert das McKinsey-7S-Modell von einer statischen Darstellung in einen dynamischen, intelligenten Arbeitsraum.<\/p>\n<p><img alt=\"\" decoding=\"async\" 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SW0QDnSIVBiWEHW0uRQQlanBLUl04hBAATiiQCZNhm47BEltEA50iFQItxRCN2WQStNlySFYn0OXSKAAAjEBwFp2tLMZY9kjkxfSKyXI+Xrcy5EMuqCAAiMkMDYVJOmLc1ctiBzZPpCYr0cKV+fcyGSURcEQCCmCEjTlmYuFZM5Mn0hsV6OlK\/PuRDJqAsCIBBTBKRpSzOXiskcmZbx0EchVEcvQlajTJlADAIgEE8EQk2bzD80c7hdJgkkx1CLMg05uASBaBBAG2NMINS0yfxDM4erBUkgOYZalGnIwSUIgEAcEAg1bTL\/0Mzh9pQkkBxDLco05OASBEAgDgiEmjaZvyEz3FEIlSYKMqYEBX2aLhFAAATilYDe2GVaxsPtr6wlY1lXn5Y5iKNBAG2AQNQJ6I1dpmU8XEVkLRnLuvq0zEEMAiAQlwT0xi7TMh5uZ2UtGcu6+rTMQQwCIBCXBPTGLtMyps6GOwqh26ZBq2x6F5kgAAITmkB0DDw6rbAJPRJQHgQmLIHoGHh0WpmwgwDFQWBiE4iOgUenlYk9EtAeBCYsbEchIAAAEABJREFUgSEN3PIoxFDTcDlhgUBxEEgAAqPXRYPhGy6HbMdQ3nA5ZHUUAAEQiAMCBsM3XA7ZQUN5w+WQ1VEABEAgDggYDN9wOWQHDeUNl0NWRwEQAIE4IGAwfHlpeRRi1WFZzeou8kFg3Aig4dEjMNZmPtbyR48EJIEACIyQwFib+VjLH2G3UQ0EQGD0CIy1mY+1\/NEjAUkgAAIjJBDezCM9CjH8xMgIdUG1UScAgSAwlgRG1\/BHV9pY9huyQQAERo3A6Br+6EobtU5CEAiAwFgSGF3DH11pY9lvyAYBEBg1AqaGH+lRiKaFqRTtbpQSaAYEQGAsCYy1mY+1\/LFkA9kgAAIRERhrMx9r+RF1EoVAwJTAoN932sfDZ37T+6Ob6feJtnzRaGt0NR9S2lib+VjLH7KDKAACIBAxgREWDG\/mwz4KGaEWqAYCIAACIAACIAACIAACcU6g9+jTbvdKt\/vRpw6etkehr91vPr2GmnM\/vOZ3XVFoDk2AAAhEkQCaGlsCOAoZW76QDgIgMDEJ+LvfPXjwjWPdcfgx28QcEGgNAjFGwNd5+OAbrV2fjb5aUnKnb\/QlQ2IUCPQeeua5d3upoZybf1ieSe9jHjKvWzT\/q05qpnvfM6\/gMIRAIFwIgX7+JaNe3eLH\/xnP8Q9eiNDh1h2b8v7uY28cPPguVnZjg3diSo2ho5DOpmee2UrhQOeYofRH5ZuKF6I+uZt48DUXggB1QSAGCPT+adOazS+++NKv1u04Ns7q9Ha1Nh8+HBLavTq9Bv2+cXFup1tf4U77mVfeHnLT1nlAlHymaewcvA4IkiAwHAKmawPf26+INckrrafNZHW+uO7x7S++9My6TQeGnP1m9a3zVMmPbx5tydZt8jsh+x+emTCvUVuCDh578dV2ju3L31lQzI8neFr\/8vfqN5n6OxeQds64bX5uKgk4dWDHgVP0jjAhCYy30oOnDm52P\/y\/+HeanmsTynzW\/uJjDz9cRzlP7O0WORM46j28ec2vXnrxxc3rnvdM4G5A9dElEM2jkKObKoP\/PVy76rHth3uUg8dT7a2tb1N4b9SduM+zd9PPHqa2H66j+OHan2\/a6xnlpcuFjspn7bufcj\/8H5Xkbnjsfmq3pmHPgcfd\/N\/jr1+YE2rbzqW43duld7tQjVEfBMaFgOZGHn7u3WAFBo89978q5b9NLcG3Qq\/+unuVKLrqd6pZdb0icyp\/9kqnnzmnuOQaNsWWElo7qjmnW199fvv2kPC6OFI41fzMmtqHK\/\/jYTc5t\/94eM3Ww6EfdnT\/TulZ5bq9Bu966vfrBIbKyp\/uVkEMp3O9XW3cabe2dfGPQMPWPPWeKNnablAhbCXcBIGxJBB+bUCzW6xJhprdF7qM6j7wpHg4P3lAsUHXVJeUKeOxJKDIFrudSrH\/qX344VVbD5+y+vh3KM+pCLywt6ObFbekvAWvFS9MtmVtwxK09XkxKO7trZY1zG\/0\/unA0X66ZZ\/xzVlT6V0L\/u7Dz69zi0Uo+Wyive55vbtWH22bjyo1Pju8ST7Rajcd5itWtYACpZKoBElwzvhmoYvX\/ej1MfxEkTcw6q+JKlCdqJvUMYuhjoSbwKoVq1OJv8u10Kl9z7z4btBPzhx7adPBj5Rt2si6F0aT0VycRLRXcrrUlV1K1LzryKihVhQJjOtc8Pee+ujw9p8\/fkD\/8eZod76rcc2jm3Z71AMXxvy9Jz27Nz26pjF2vkTYvfvJp\/a2+7Tvg\/h97Xs3rXlOnlme6\/3Ux\/99OuReIzw6\/9+4FJ\/vbxfk08K3gbsgEDUC\/qNvHNbbRG+zXICOSIHPjm56SnySZsuY8\/3vZNkZy\/3eg\/ffueDuB6puyRmRxDGvRA\/y3ref+X+fb+3uVU160N\/99vY1T4qOmLbfdTB4idx54E+x4wZNNUYmCIwVgQtdG2TN\/\/d\/++cFd9zz0L2zxAZ05Hr2+uQ\/1Z+lzbr\/X0dHcmQ69R5+7imx27E7LyLf5z\/19vZfNirHMkNICPWcQ1QY0W1lrbhudxTdlf8zOSjDXTH1Hn1bfCUkNX\/GV3Wd\/ezoMyvXbG\/uCuwy+31dzdvXrHzmqOkfWA127X5yu4cfqThzv\/u9IrMZRlS4hP+zu0s9t8qaVSL+HMfneTey4dMpiGScERjRBO71dEgby\/pOVf2iAkLS6ekQCwxX0T8\/8lD5Fyhn2CEiTS58cXIuor3S9FsfvP+OBf\/8QNWCrwy7I6gQrwTG4yjkK\/OrVlRVrXhg\/lfEx66DXW+Gfrk69CsMoTm+zoMvPbVGHNyveepF7dsl+qGircJTvxefktqn5n9rwYJbF8y\/PncqPeuZv\/v3TylnDVTB3330d8+se5TLWvXYM4bvjFA7L2rtvKQ\/xWfMd2zv1nWrqN6j67Y3n+p+XfkCx4EeEspatU8VqNhmrikX3q4ud3gR8fLsfV2Ut+cuqPrPRx76bi5XkPUePXSU0THnU6\/LT1FP\/eEJakd8p6N1O6UoPN\/q7zm8\/bFVIjOsMkTvBfF4Zqz9Bar5uNSQMITpOAlXOv7zTXvbe3XdObiJZFD4+Svik2nZi+2cg9u95rdKQyIXEQiMGYG\/HDwYOEX1Nf\/JbOKR9Q7lJRjrPdjwnIfbpTP3n9Q\/7e458PTTL+7esekXTXxN2TqkLX\/WZemOzN1L+ys\/IxOi8EzgRMd74CnKoLDpIP8UUJL7QvlD9YF\/\/1wg3EPqjMI8X\/N\/t3Kt2dSS+x+p\/8n9JReLCh8dbP6rSJhEvsN\/0P29j+eNw2bf\/CdmiuG71zxl8HiDvmO\/f0a4Sn7rlLoEDzRFlYcGHiiOFAiMC4FI1wZSuX7+eT5\/wNGD\/k9iRcHzW1\/8xfbdLz33xAvq9wbMLZ0X5S9z0+g+8OQTr0s\/5n2dP+OfJ2k6ye2v8KUDPVhf1R62pxQ3sfK5Vr5Vpke\/9Vpo8FSr9dqGa8Vfnta\/8Dfn3y+qqX6gPMtF\/wZ83O\/x3HAvM89J5S04tP92jdtN3s39TLPwW1SSqX1x610evyFeOfPFWvF712TxxeJg995G9dN3iyZELXaqbfczj\/Hhcj+67pnfH\/NJN0WrIN64W1kvUdHQHMoUgRz+i4IJrZhepFrqF3bMJYsqatTe\/n950p4\/Yzp\/ly\/6uOu5VnHk4by8ZP6ttBYtL8rkfWKftT63yeTwuvOlTXvFsjDj+nsWFYiSUhLFcgn9o++VCCqsZ+\/v3qZcEdKm56TxxKm\/aN8r5pd4RYMALddpqrjdj7\/e2S6fktr0056bWo5QiKaZqLG9Vd0juGmxHTR0\/u4\/vfjUz3mpNZv3tn8WWPwLAfTZrvnmhSSbTmCllvo2tfgesR2jHVnVD6\/PaH1+1Sti9jJb1951ZCnkneQ3kmiV1Lr90aE3DtQu19W9vdUvfObzrZQTiSbkxSJYnPgtaRD80L0SZQptHn+9m38BkD5372HdTU8\/\/dLu7Zt+caDn1MGN4rb7ceWMtbf1ObENdD828f8SSB1ivEdCYDyOQuxO1xSXa0pmSWGWVNGZKhb38kLGoV9hMOR07V7z6OMvvtHeLQ7uu9sPbv8ZOSB5nClFUHzq4D6xVbBlzLn\/oTuvLyoqLCr51qKH7pffWuw92ij+EFec1j+3r7XLy2Wd+qh19ya39ivc\/IOjx188qLXzxvY17scPyHbo85A1v9r9dtcpquftOvz8qif2dVHS5\/u09xy1ztSj0NbtVOxdrikX\/tSqZ97W1gG8GOv3i0NXkWb2qX9\/17\/zx39V1S357Fzvp9pPAPT3knDxCYXK4v\/uXvfz7Yc\/OsUzwytDNdSPjv1cjNDQrOPubccU5bq4cKXjJz27n6IDF2qfwt\/8rhn5X6CEz3fy6JvvS7XZsT+\/yTn4WM7XYvRTdEVRvMUPga6D2pccvIff\/CikY2ZeYlOLMsHV0v6u3z3xojhFCVp0ngv6hGEIW+5tfWb1uiB39HP1A0xLK8u56itMWFHrUVWlU39+s11kZeTNMPsUkLHPDh54m3sLV+E10229vWfVTtB7atZ37ucLmqoVP5z1\/6Fr8+B\/+4B28nLsz61cVnDBrt+Rhwv2eP97jbJQoPPZp9f8qlG6yu72N7aveurg3\/TVzYA\/\/rp0l\/pySIPA+BKIbG2g6Pi3g5v45\/n8AUcP+h1r3JuPCidCj1VhrvIZbWnpjDHGzExD+qJeX6\/yhdBB8XDm0nSSc3Iyz\/JWulve7JT6nG5T3UROTqq5ZNXounf\/fNUzQWubNbJRKUmNM78kTlF7Pa2dg7RYquL\/bs1X71q9W3hOaw58bcC74mt9UwJkzHtU6csX8s1cnt0p1oozbr5GWSx2d\/MTGusmSNfuxjWrnt7b+hEfLp+3q7XxV2ueFs2pUPl6icpRCM2hTBHI4QetmHx8wC0liypK9Ncu+R2NjC98Scmht3eVj7ucX\/3eQ\/fNLymkteicBQ88tEB+7PXR73bLrwBTSRF6WzZtOsQPw6n8D78lvuch8pVILqG\/PGP+tQqVnr9yKuJu5mWyePfHH4trRNEjoK4ZOl97\/Cn5lBTT79Ent2\/\/P48qz00lRzn8omkmDULbI\/hosa3fgPxu3ZodB9tP8lLd7+5+ajUdmvC08tNgZoYgNy8kOXQCm6Bw0l5MDam0ZwnyRWQp3DvJatw5KRsHUtCwY6qVJkYnM58J9Xztu\/+P8Jmf+SPVhOoOvTixpkHwuecUump7JcoU6ngPP7Nm027PSaG\/trI7N7XklutcXOHOvZtf7Bxknb978SjfBrL8m+ZkCEmIEoTAeByFdL0hfops07qXhPu\/KL\/EcOY9NPtTB3bs5R\/N2Fziux7l+VOoTm\/na88H\/a1Nr6ddLsK\/MqtcPh6oFIXMObPkbv2j92gHdOyVFwOn9d8qyhDn7937ntlNn6x6Dzy\/j7fDpuSX00H+t\/L5X\/D2dr6ygzuyYy89Lz5JZvaLc\/Kvys+52G7xW1i9vam5c26ePydX7m56W\/+7mT\/lSBMZrsjNEePg92x3\/+81mxrf7B4Up0UuO3Nm5n0lQx4U2dN5K1eII38m\/33S3S0\/7mBsCGXSrsjPkq0zV1Z+\/lV59IGE2nFn1jXzF9w6X37C4Pvzr1\/kw3Jq7\/N7pXBnZm7+VbmZF\/X28sWAbNhZdM0MoZXv8MFjPGvw6EGxQ2OZJbOUpzPPxgsExoqAMBlf8xvHhAl0HjjIbV1kqi2eUrwEs0+9qnz+9bnceFmvZ\/tzYl2slvrL80\/t4+tIe+4Ck0WnWkp9t7Dl44fFmasr\/7YHq\/5tQS75kMFu+QFmGCtTv8zM2v90UHzzq7v5z7wTLHXGrEISobape+\/8\/d523l9pZhnTvyKN+tTBx\/+3+7Htr3f6nPR57hSXUxinrp6aJD6D7QffEK31HpanKowy1fvM85ykwexTc6+fU5KjfIVu71bxSyLvvvj8u8IL2KfmXJWfT3eDXJ4KPLxb1tpCIs4JxHD3IlsbqB3w957lj8H83EynMJbedxfIoUcAABAASURBVF98VfnKgFqEHsHKQsL8eWrti5yZX83JoBMNkpSaIc2Kkrow\/ZpvCDM\/7TlGaxL6dPbdY8JNsNzCIicLa3R\/PXpUfLMg8\/oHqlbcMyudpPZ6dh\/g\/o6SgZAx42ti5X\/64C90f20RuG+asvCcYTweC7i8w\/ILfd1\/ahZ9sc+4hvpi2gzP9L\/\/gegHYxkZpGi4Jlj30aOif5lzHlhRdc91VJz1vrv7gEDHZUX2mpqTn8VXlVTalUW+7qu0YopMck+3cK+MPvCjyjJ0etr9PDW1sGyGzrM7i64vEkPr73xf6MzLMHb69ad+LZaWF8+65y59eXlbjQf9nSqV9C\/wbsobGRni90n6e\/vkNeLoExikByQts+kBydv2dx4+fJLRjMq\/Sst5\/cD7\/Jb66u0dmJpD00y5z7r\/+4UDp+mgcC9tQHgZm+p\/zuqW4QGfw5yXl8wP3rxMNZnAXJLh9bfWF8V2TPkPK6bmBPmiK9LIO6k7hylZYuNw6sAm+RVa2p0Uzbk+P\/MiLrK37fnn1E90+DU71a1YLO94iCmJIoaIXGv4xYk3LA1nuL2Sr6dbLFwMTTKWNuuem8Vu8PTBTRs3vfAnvjNzFd81\/\/KQksiIawI0+6Lev9OdrW+3tr7t4f8FnT1zzqLv5eseDhFpQ5+KiE+AXYUL5n9j+vSvFM0vy+eL\/8GuY+IJogg57ZNfO2U2ww8fOp1y5cH8A\/3HjopNDJtSsohO669f8MN77lxApx63Xp\/F\/L633xQH\/K6i784v+sr06d+YX\/5V3g77iNppbZab\/ykl9\/7bPXfecec9P35gjvhoRWk98JZZft+i8mtKyhfdoxTo+uCDwF3GnEWL7ivPEg6F9Xd79m1\/6tGHa588wJuekv+d7+R\/XhT+fP58aiXooMGWMeu+R+rr6xcVDKVM1qw7r1VOgzKvvfPOO76TP0XteM6c7\/1D\/vSv5M+5qVA8Tnvb3+1kPc1HxQqF5cx\/6IFFd96x6IHl38tVoAltvlo+R8jzv3uU9qK9zYc9fIdmz\/2HkqniPiIQGFsCX5kxgyZkf+tROrkbPPYGP120z7gqN9Co6iXYV+b\/yx1zSr616IeLF3DTvvnrU\/sDpU591CWekRnX3RRuLa5WsLBlxcP4Pmg5euxvObc+KL6dcQt9rBrWytLmlBfYueSu1qPkqjoPHv6EX029ds50U8esdJOxr5SUiCPRrJseuLNQnFaQs\/ro8O7N6x7+X6u2y9MKLsnwmjrjKm60XW1HabF+6o2D\/FQlc8YMIUoWPdYivaGr5AcPLfpW+fx7HrpTavjJ0cNdrLX5qFjQ87v33HHnnfc89MD1U2VFHqvAh3DLvGgcv9C1iUAgorVBoCM5N\/PH4J2LHnjoFvk5fu+xNuUrGmqhY8pCwvR5qpqGmS9y5d80P19siJkrfz6ZVanxw4Ssb8j7p461keH2HlV+imJGyVW0bW6T34YzN7pkZhf6ed85eLjLed29wi\/dK78VK26IqKtxzTpxHExX\/pN7H5enIe8fEHuk5\/bKXTzdCw4WnjMsBzZ1TtkMoVJX65+pL50HeczYxdfN0f+sRqAhz3P89xwrH35SHBbbMuZ8awZtAMOhpro2etE2svXgnz92zpLf\/w\/3RTlR2hhlld55DXeWlJ95DQ3KTWIIIpE8OEB1DOHUab7FoswUKYFSMjiccm06cFZ3cNElv1dizy\/\/VqahvKz1rqDyHw8\/\/gYxZCx9znf4bzrIe4jHn4C94M6H7qFl9j0P\/aOyIHH9\/aLgHN8HncqUEOoGHqn3XyceqYOdx97t7daW4Zr\/+Sfpf0QlptralJLQzYv5BJb1dLG\/p72Vb8doR8b\/w4qs0iBfNCuLvFPADvjGgSkOR2wNFpR\/684HflQuDMXv+XOrTjDLuO7+R\/6zvv7uGZFpMnXIxckQNKaE3Ss5cxf8O+2VTH7rxFl8p\/xyVm+7R+y5Su662eiB9f1COi4JmDraMe5pZhHfkNw6v+RyJ\/N37X3MHfjNjghb7lUOvH1\/+pV7pZuH55VvenvVRw6XNMWlLPKND6feXmUvZE9J7VPSmZfJ6e\/MzC8qLKIw\/Qt2rZ3Dm0UrK93b28RegHl9p\/0DfPPPGFVUKGbk5wkvxtvWv1xTFT3EJxp0Z3BASqGkDPasOfdXP1Lzo38uL8x02Xle7\/uvPLVVbkv4pfkrd853Lhel6UwnUmU0SWrH219ZJRk+rnxY5Dt9ip1jUsOpWTlOWcM5I\/9\/yJSMp5YUi8PU\/qMHmk8dbWnnuVOKvjnsL\/jweniBwLAJ2KbPyKfJ7z\/6xuFTzeIHU1PzZ1ypE6Na79QvXybn8NQcbtdFhTPUzyh4YVe68j2wvVsCPz7Hb5i\/LGz5qgXfy+ON+Dx7tz+1yr3y0XXbDnudpF5YK2Ns+rVFLt5Q18EDnZ1\/buWLI1vO9eKTTJ4d\/OqV3WS6T1BtrvxbH3rkJw\/dc+uc3HRqjjH\/qcNPP8G\/0RZcV15N\/cbX+apFtHZA\/GBq5owZep\/Vp3ynNvMy9VOR6V8RZi4+5FG+xk8uT72bcVWeqC7Eq8CHcMuiLCIQGE8CEa0NNAWnXkZrFXHl\/Ea+tAf+lBQ5ahTW0lXTCO+LVFEh71lfF997ZV3vtvkGPcfEH\/PbvzqDH5iqks2NLr38e9\/k3yrtPcnPSd3uR9f81+4PbNwxBdrofHHT7\/lXX51fXfDArflOG6PTkHU\/f+65l17he6RO5xX\/QziWQAUlZeE5w3Kgql+9pkh826LrTwc633+zlT76ZiznH2aJj2HotiHYnaqyzsvn\/POKB8u\/QAXCN5FR\/v05os\/dh3\/3q3XU57VP7e5kqhiqPuIwcslTpwg3z5iyaNRU6OuVBycpkxxaHrs4I8NGV\/7WF54+Kn5ehC6Cgo5K1jf\/uepfyy3oBVXCRdQIfH6q+lS85EsylXKRMgGYmtMX9PWOwAM3c4bySOV7mUFlGR7wP1cp\/kf0pa9XbmRoDyKu9ZsXkTF05MotF9sx+pToOrkDGqKO6nACWwP152nY\/9er+2pT7pxvZ9n5NB5CnnZ7yMUJG4KGJskkMbX4O0Vp5n6M0WfRt2p\/hOYsumV+1nDUNmkMWROQwHiM+ZQcOmgoKiyZf++3xZFp79E\/BZ0m6jH6tKMN+cTQ32NM\/5M\/8rd\/fni97qHgzM3hC3\/G\/nJA\/Vt3Ub9r7wGxc2dfyRcKiMx+1TP5e6lRHqSX4TenliwWH6fIn\/Dg8Q8Df0l2+pQ4madyvR+fUJN0FXlQWuz1Z0yfc+sDVSsWyO9f9Ha2q18xi1jWCJT5ivwVW10HdX8k\/Detc6yzK\/grps7CWfxjecbaD\/xK8sz8+6DvrESsNAqCwEgITC8W5wh\/2f3E77k985\/PMBMzoBycMtbv43Z92qfs90XhlPzv3SOdRs\/ep54O+tMZcT9MpL\/lnHFXzSPVD\/zzt0pyv+yyD\/p97bt\/sVUnzcrK1G+M+9qef\/7P\/CTEftUsi2+nnDp4iHeTTSm6Rv0E1e8TPep1XlZYvujfHnlA+UCp+4P3xTdd9ArK9JTCEv6r6b7DW58+TJsQW05JkVyqydta7DvlVdKdH3WJlN0ZWKsH7vZ+1BXq8oZwy0IcIhAYTwLDWhuwv2nmQI\/BUHsI6oiVpYtC4X2RKGIaZZV8Q9jpR8da\/\/Sm\/AJm\/jem64taGV1m2YPyqLQoJ8Nu89OZyDNP7tbtWJjv\/Q+432FTS75VlFl450N3zeB\/SNhzVHwt1J777XKrjcEQntOSQ9asvxfLstOtz28\/zJtOtfx7QDokmb\/8O\/LPh3t9A5+X35zVum3VRGb5gz955KF7Fswp5N\/29\/d2H94adDpMTwFFhtmqUrll+jaUZF5J3ev61RUlZWbl5tjpjZ1qbtQ9FFjv4X2CAHPlflW3cM2Y88N\/4n9kyXo9zz1pdkD\/lfkP3SRP5Ho\/Hfg8Hy8uXHl1yz\/QsaWIFpVMvMU2Ad0jtVN5pDqcTlVnnf\/5qEv6H\/WWeA+3eREFrKOUTOWj36LCHOFirIsG3\/mbtjXo\/aBLrhacAY2Dy0Z2Feni5G8Bb2xKI7LW9KWO7dqrUu1tPaS3UH0ppOOZwHgchSg7f1\/XoaPKd0yV0z4d6MwvySdD177nDn7k8\/Uce\/G\/PYHbX5ieO4VfnWp5\/dig0+X0Hty6bt1jFDYdDlqYTy25Pp+7k8HuvY+vembf4cPNhw\/+btOqx\/kvfTDmnFFKm47cfL43oA397mfe6PKdbn\/l\/9Tyr5msfPSVdpbxVfnzHqeOvnFs4CLeztO8lXXrnj58ypZzxZe5Dqxr96+2He063X3sd5teDfn7YVFiqOij3evk9zL+31c6\/czf3+eXZ8EOsftwipixU39p7TodtIvTyY1AGYfyuUjXO0e7T\/v8g1rHD77udbouGjj22ycEw3WvdDD2haysVC7e3\/Lrp\/a1d5\/uOvz00wdp78Tz1Jdt+jWF4qhb\/nEsbauuGZYvVeXgfSIRiCVds0qK+J+k0XEAaeXKnxH8qYbqJXx\/ev7Fd7t9PYc3SStbuUn3v7NQRXvmt344P4cSrPfd5574nfpM5BmRvuT\/jPDo2t95C+cv+tG\/zxcuxd\/d7WNhrYyLV79ddbq7m5+9uoquDdrh8CLy5dktf605M3Dg2Hv4OflttVVPN\/voM5O\/9SlLe+dF3O3JesGxs6gwl3L85AHoLWeG8I+UUkLuVwUI1nXg2d3HenxdLc89L\/56lqXmz\/gKy\/kfYg9DLu+\/njv6ka\/73d2bdonTGVlbBT6UW5alEYPAOBKIZG2gqec\/+vwmvg756PAzzyrO47LLL9Nui0RYS1dNw8IXOZU9hPdYK612tB\/\/E3JllPH3hcL22l95VVicq+gabsf0pJ4eZi3kOyT+q7ef\/qo1bc6Cex68t1g8rz\/5WO\/jXJNFJjvV+udO\/yBzfqW8\/Kuq93BO\/\/oValrqERSbes6wHET1qdeU5PCFp6+7hy90+BE2vxT3QqOLSub\/g1hXfHLg+Sa5vAvbhE\/893YrH\/1V29Q5t97z4A9KRPdOfXySsfCrypCmtRXTsZZun8\/PwkjW181ISxeXH3R+IN5F9NU514lcesSsevLFg820Ft27fd2q7R5OgH35OsOHSM6CRYvkYFkc0DuL58u\/tj7VFPwDeay7Sx50XZwhl9CieUQxTqBr769epAcuf6T+Thg4c112uSvj8iw7V9x\/dNtTe9u7feR\/tir+h2cHVhcmmxcqYJzAlBUaemn5pIb+0NshOaor87+9\/Zk\/dfl62vc27JYaZ341zxVSXGZEpAkbYnEyFA3GnJHslaRGuvj9F7f\/mX905BReuPfd558L\/P9WumJIxjWBMI+gMev3X150iz3Jupfa+QRkzvxvyKe6rsX0wiJ50NDb\/uJjbvfPfnUw6AsSWeXfVk7Ntz\/6cOX\/enxvp4\/++bPmlHxBJ4RM46o77\/km\/7Ik859q\/d327c9vf3Gf5xR\/+tgzvnnP93jEezWVAAAQAElEQVSzzqK5c8TXEXvbX1rnXvmU8r\/Mfvlb5fTRa1b5d8SyoPfd7asernz4SaWdy\/6hJIO5Zqm\/gNX95+fWrVzzq32dvSPDefms62Rnew48Tq3QIYz4a5eca8W3Rqdcdpk492HixOS5tqAOqhcRKJOVc5lQz9fy3JqVT+ztVjs+2H3gSWp11fa3TxFDn6NozlV2xqaX3yCWXqy3\/XdPrVm5bnubL+jnFUXD6kfa\/ML602x+d4K\/oH5sEsgo\/IacpYxlhv5eb5biJQa7D25e4\/7Zdvk7Qs5vlM9JM3THWXL794RDYd3\/\/VzQN8gMBS0uc76R7+S\/Q+55ceXDtXX\/e7s4EnVelpVBT3fpXsytjItzqt+u4hcmveDZjD4\/bDrKvWXQgaOz5Dr5o3q9nufdlf\/x8K\/kscWUkuvyZC2z+KqSGeKUk+n\/0EYt6Cz8zhy5ZO\/c+6ufudc9e7Sb+yJn7oL5023MVVou22M9R597zL1m895O\/X9hw1TgvZ7wblltDe8gMG4EnEOvDXS6febh65DHtss\/6OC\/zlBoOCMI\/zxVTcPcF7kuy3Lxxga7dtNq53mzL8mmzcgXrs7fz5cvrqu+rp77qpLNjI6KZfJvjnUffOp\/17prf\/EG\/xIG+\/IVal3eJssryhdd6X798Yf\/o7Ly4VXb27in4fd6W59b99wx07\/R4LfpFeo5w3OgKoyc4iy+xhBpM8ctb2hxRtnN0u107XnxMFcmbBOuGV\/\/sujzG7LPYutoy+R9Tg+\/qtQaVBKXKaddvqPPrnE\/ubc7jGSlhnizTZcfkvn\/4lE+6uPZGeX3fS9ffKul9\/2DLz5Pa9Hdh7sE54vyv7fI+OstVCPr5kWKK373xeeCfpCSblLIKJdUBrt+94L2f4IxdtpzTCyVXTnTcRRCmCZK8J88SA9c\/kgVk8L51e+Uk5Xmln9Lbg1623c\/tcZN\/kdYsNop1RBolR66eWHMOIHVavr3U4eecovtGMVPqD8YpC8QklYdzqCvdcc698+e2v0XoXH6nFuvnxpSWMmIRBNeNOzihA1Bg7GI9kq8ncBrsOuV3wgX4ZzxT1WLSqbQHb9nxzMHuZ+hNEKiELCNb0ftUzKLbv2XO68Sj+IgVabOWnTPnMuVfPvF+QvK+LmFVsRZsOjBRXNy5O9qUK7dlXP9PQ\/dla9UoBw1ZJY9+O+LynPT7WqG3XlJbvmif3+wTKwsKDez\/IH7vhMoYLNnXLXgofvlw8k5464H\/\/n6oHbm3POQonDu9x68oyhD3Ve4cr6zoNTSF1A71mHqrPsfWnBVhlPTMTUj\/9aH7imWvcmaf++C\/EsCN83lDKmMs+jOxXNypmhtMEYd\/9cF+RoZm+i4+nenU6+7\/\/4yteM2e+Y198zPDWk5raRIforMXJafZodUQgYIjBaBqYXixy9oLufNCLU97iXuKFF+fYealF7iNrOvXVw0Y9E9wuQHu\/c+tcn8L7RJglXILP+hNK5Bfy99qCtM6V9uFQ2FtTIuzzb9Gvk\/RDCWU1wS2gtexnvw4F\/4u93w5zO533voHr1RUw\/n3PNA2D92VX5jhbHU\/BmhFm3LLP9X7ou0v\/LlEsnXyt8Ask3\/3oN3Fqkeg2595xYBjavGXxx4ZG6Zl8YLBMaVwNBrA0W9qUU3z8kS+1jKcF4+5577yk1+zzKspXPTsPZFWTf9MGgBQM0Yw9QZeeqKhQV9A45LtjI6cms\/kosHfy\/\/RimZ7Jx7DBtvZ\/6dVEY1at4slbr+nx+6bxb\/iOj00V+FPw2hJgyeMywHLp8+aSkRf9tIF18pKUmjt7DBNn3+t8Q6o9\/z6ivHeNFwTThn3PUvEmagz4vvmcVbGWJVySXrXs6\/v\/Oe63NcygKPboSRTHe14Mr7qhgpX6v6vx+LWxfNuHPFgwsKA48jlurKLFzw4Io7Z6hTS5RTI3LF98m\/le71\/PoJkwP63Pnlgorf86r4X\/94xVPNb3bx96AZwjPwimkCueW35svfP2fMPvWqBf9ylzz9mzrrvvvL1WU4S80ouit4GU6GYLl5YSETeHQQkMPhqw5t82XjG4cH\/x8zl6g2GKkm4RcnbCgaLLK9kqoVvXe99swB\/lv19tzvzp9uz5r\/ffElssH2Fzcp\/4Emw7\/EIGCLYjdnLKo3\/ntkxQMLCpXF\/4y75d1FM6ROF+WU31cjsx758Z1F31RqL1J\/K9uVW35P1SP1j9RUVVNcdc+3cuTJgaytj125cxb92yP1vKiI\/3WR+v\/aKqXsWbN4gf98pKrqkfr\/fIQOOKZqYGyu6d8S7VRX1Yh2ynXtuK5a8OBP6h+prnqE6t4zq+jbDwmFHyoXX04x9oix0BxFA9vUojseJPn1P+Gt1P\/kwTtVLLzAxUV3\/iu\/ScJF91WSdyuoeBnGwitDZZw55feseISE1NcrGtrTi+4kMqQ8kTR0nNmzvik6Thr95yMP3JzJ5NfnUpUvoZFA1us59iF\/j+CjHVEMEQhcKIHgyT9l1gNiQj\/wTeFGCkK8xFXzH6C5HeolvlCu2Oq31A\/PMr8jc+prFvG1aXCBUMs15CjGZWZKYa2McHQf+4v4rCfV+m\/m0+bIbj7y\/elUQR+UdlXnVnVPeU7IwjrjW7JnitVPv004gZ98bzr3chnlPxYEf6z+9p7wRY\/8Z\/0jVWT5FN9TnusKtOjKX0Aeg3j+hN+aVahAe0jFaO2WgwcuIBEpEBg3AuHXBprhLLim\/P5q\/qCnx3DNfSYmJjsQ3tJdVr6IKgujI+HcFPlj3cRYpn5T+gAqUjWfPjGmWmqwNjrGlMXDIzUrSPwjpv6Bl5FGvaJKXU1Nn3r5dx78T2qrvn7F96Y71ZboPdgxUgYzeE7GwnOgKt0ej3B59hnXFOll0y0ZZgSvBp3F9whV6mvUg+xwTagwaWGm9lltJOyq0tAoY86cb91T9RPRsnSPYSRLvUU8Vf0LoIO\/Oyg+MRe5FNkzim7ljyN1mVf1wK1F4kvLdI9CyKBfVLRItv6fD5bz05UZyuONzxAq7yxRqXwvly4ZGzy2u0mchFxcVKL+srW4gWisCATNmVDTiCRHqDa18M6HHqFHKt9KPHRH0VSbyKXInjWHluG0rqBtzk8eXPDVkuA5QMt0681L6AQmgTKoionJrUTiIR6yHmCGWcfrO2krIZdVFIuNgzaNg4DwsvLlNJqSzGZM87Fy0zTE4mQoGtyV6fdKXwhZ5gW3mKls2R5ZJD\/suXx+lYTxozn8IFhVEu9xT0Aa3ETupt3pusgeWQeoaNiSNrtLO+kMkWi\/yOW0qE23tA9RQ+oNMyPVspUIBY1EGZOO+w48Jv4Xu\/\/11EEf\/\/0tn+fVA\/IvAi+9TPsj6VNvvO4R5yM5xRafZkeoNIqBwJgSINOP1EtcmB4mpqQKtLr17t7X+ecSbIi\/mVfFWLxTDy3ck0WFIbPtLmtfRK2lhhVABaIDPKwWuAkCkRGg+Tq0+dCzNbAG6Pf5ek4FbXS1lqwsXRagpsbINMJJtjunBHSXihhjqj7FZb6aGtk60YrD4LG9fzjFW9f9AjS\/HMHLqgkhKmi8RM5oRUNIdhYpv2\/Svtvsb1sYS7V2rRegYtdrL4m\/onTm3yj+tvoCRKHquBCwu1zmWwma5+GdBhWw3ryMVV\/IY0S\/UeoMdTY8DSqDEDEBFCQCI3vEUUWE+CbgKvwH8ddG\/e2vrHuYDkXcyi\/SOmdcV6J+wtJ54E\/iI4gwn2bHNyT0DgQulEDv4TeO8r\/+xxerLpQk6oNA9Ah073vC\/bPd8scgMv+H+EOF6DU+sVvqbT5wVHyCkvn3hl8Lndj90mufUXan+KWPXs8Lzw37zy31giJO97Zseup1fsDkvGrBApM\/OY9YEAqCQAIQQBdBQE8ARyF6GkgHCDivuvNfAn++KPLtU\/Nv\/Rflq5iM9f7pdwfF\/ylzYZ9mC8mIQCAxCXTu3i1+BIR9pWTov5lPTEToNQjELgG7K+c7t5bq\/oIsdlWNEc06d\/9efL\/UllMSx\/\/lnC2z\/P+pqVpRVbXs1pyUaJBPyb71QWpuRU3VHeJDrGi0iTYmGAGoCwIgYEoARyGmWJDJCYg\/X3ykhj9fq+ih\/shPHrqzUPwiA7\/JUvK+R5kUHvx28B8ui7uIQAAEhibwhTkPSPu6y\/xv5oeWgBIgAAJRJ5Bx\/Q\/p2VfzyCNV98wy+QnVqOszYRoczJxzP19OVK1YFOcuz+50TXHxEP5vCUdp5Owu0daQfwY1Ss1NIDGxrGr+rdIWvpcfy1pCNxCIdwI4Con3Eb7Q\/tmd8nE+xfhHjPaL5KN3TP7q9UK1Rn0QmBAEUhUjckVluTwhkEBJEJgABITlDvXzGxOgH9FW0WbnpwO0qBiXXxmIdm\/HrT00PCEIqKtoOJIJMVxQMm4J4CgkbocWHQMBEAABEAABEACBRCCAPoIACIAACIDAcAngKGS4xFAeBEAABEAABEAABMafADQAARAAARAAARAYMQEchYwYHSqCAAiAAAiAAAhEmwDaAwEQAAEQAAEQAIELJ4CjkAtnCAkgAAIgAAIgMLYEIB0EQAAEQAAEQAAEQGAUCeAoZBRhQhQIgAAIgMBoEoAsEAABEAABEAABEAABEBgLAjgKGQuqkAkCIAACIyeAmiAAAiAAAiAAAiAAAiAAAmNKAEchY4oXwkEABCIlgHIgAAIgAAIgAAIgAAIgAAIgEB0COAqJDme0AgLmBJALAiAAAiAAAiAAAiAAAiAAAiAQZQI4CokycDTHCeAFAiAAAiAAAiAAAiAAAiAAAiAAAuNFAEch0SOPlkAABEAABEAABEAABEAABEAABEAABMadwJgfhYx7D6EACIAACIAACIAACIAACIAACIAACIDAmBOYOA3gKGTijBU0BQEQAAEQAAEQAAEQAAEQAAEQiDUC0GcCEsBRyAQcNKgMAiAAAiAAAiAAAiAAAiAAAuNLAK2DwEQmgKOQiTx60B0EQAAEQAAEQAAEQAAEQCCaBNAWCIBAXBDAUUhcDCM6AQIgAAIgAAIgAAIgAAJjRwCSQQAEQCC+COAoJL7GE70BARAAARAAARAAARAYLQKQAwIgAAIgEKcEcBQSpwOLboEACIAACIAACIDAyAigFgiAAAiAAAjEOwEchcT7CKN\/IAACIAACIAACkRBAGRAAARAAARAAgYQhgKOQhBlqdBQEQAAEQAAEQgkgBwRAAARAAARAAAQSjwCOQhJvzNFjEAABEAABEAABEAABEAABEAABEEhgAjgKSeDBR9dBAAQSjQD6CwIgAAIgAAIgAAIgAAIgwBiOQjALQAAE4p0A+gcCIAACIAACIAACIAACIAACOgI4CtHBiHays+nZXW2nw7Xqa93V8IfOcCUiv3dy\/4b6jYdMm\/uwqeHVNl\/koqxK9rVtW7365ffEbW9Lw7q6mrWNPayv7TerV\/+2Q+SOSTSalMZEwXESmtDNelueXVtXu7bx5MSjMOR87vugcePqupqnW8azb6fbKehKaAAAEABJREFUdj3bNDq+KYxrGk4Ph+Q2HGEoCwKjTKDzDw27WkMes17tQTnKzUVBnHmPAg17Y8EJ9+zbUL\/pUAj3gJZRS1k7KKs1klV+1FRGQ6NEwNfZvHtnw7Mv7z\/W449ApL\/Hs\/+3DQ07Gps\/vICZ26dbkBsaNV\/zR8Vgw2hlUFK57LPYQVjlU7Uwt+hulIK1vVsqMJRHtaw44hsjUHI4bQ29yQ2WNm4DNw5HId5966uq6l\/+IJhA2KuWp6tW7+4JW8Ts5ltbqtbQVtzs1ujk9TSuqdry1ohleTta27r6DNWDZPZ1tbV1eA0lhrg82bi6aovZJulzzvSpaZPMans72o6FKGJW0CQvCLLdlZaR5uKlWn67zTOlbNmPytIZs1+k5vI7o\/8KohSp+CDOukpW+boiSMYAgSHcyFsvbzs+teyBH5VdEgO6DlOFoeZzz4Ht+73T766+o2CYgke1OGnZOlzfFFAg2KVbu6ZAjaFTpNGwveXQUlEirgl49\/PlyEujc6YXnhQ9ZkOf9\/oHZfjqMXjXtEcBPaPohIP9SfBDnLxLWlpKQK1xS4VxUIE1UvD6LZA\/blqj4QgIhHcjJxrXrtrc9Mnnsi93dL60duXWNuOqP7iFvre2rFy308Myp138adOv6tfuGf7eRxEYWJArGdobmW7omj9KBmutlaZecCJgBSeDdjeB\/ODydBXmFt2NPAQ7lsjr8ZJh7J3fNnvRsIQ+I8wKjlreCJQcou2gLaHXbJMbTsBoDVy4Nszu2cwyxzSvs+lwl8PR23zIY9mMv8932uc7oxye+s\/4einZ56PMPkoM+n2n+Tvl8zcppZ\/f9fXzC7\/Px\/NJyGcDbDBIFGP+vtO8pH+Ql9S\/SJoiX5ShAiRHClSK8XZ9lK9ckixqaJANfBYskNqlJlTltcJUXDTNVdNlGpPUaF+oTKGS7HVQBaGSz+dnlEsEqFHK8ZGbHeglHXwEi26oIX1Gxa1zcxzqpZRpKCNvkhCqLiDLDMZzuOY6SuIOdVYP2ZFz\/a0VxenMf6aj8yTLuiLXzkfOkTP7tooiOhIRVSgiVUk+aUtpXaC+0xDoCcublM\/blheqJvKK6yMGXVzKwQ2UFZlMKO8LokSDYTp2VvnUTTOFFfl4GwcCYd2Iv6\/j\/W725excWy+fTjTf+GSj6aGbG5RJYyomjzbBlOnE55g6YXjXqCLZuK4uz2RMSuCS5TUvxptTr5QpJy61JviVrCia5pf0ohwuhyQYW+Eq6S2RT9H2zk9cOVek9erKknyD7fCK1AT1xdTGqUXqPm+Umieh5Cd14ijjjE\/zwHQV8F1kC0aBpHaIY9T5Hq7JaeGThc8hRJTDHYPm0gOuSRUl1SP9hXZaRBWpm0JRtaR2L5Dgt0y8pWg9KJ9a0QhQJ31SSSHIpJtUgijpsYiSilgdARIbjIiPjtYXunvap2MrJhJXw0pt2QriMSHQ+YdDfDny5iFPyJIg0J4cMjGCNJRi+qk3dbfULPGuyzdWEfdlFPygpOemjy85gmxWNyu0OUkFhE\/QmYOQp2tUXCuRLMYlywwqxuebvGBB6mlNiJt0i8yNDFZc8YiLIg6kQPAMp3u8sD7T4ISpBAWSf9oXNPmF+fAmSCuSTGX0waQ83ZZMAhZHWun9CWmiX0SlF1TcVi4WPqS2KTcSyYMUK4aX2tX3hd9VXtQWMVEKnZY68IpKF06LEZRlSQhd6lDLbIp1QuiKgrpGIg2D1m9qPhWRIVQmVRGdkve5k1K04hkhDfFMvEadQHg30rZ3f9\/Vdyz7fllxSdnCu2c73zl0lBbppMSZjpYOmaJx6\/Qo6Z4Dez0Z31625KbZhf9QsWx+bk\/zIdOTWt3gqjPQYE0OZUFOTYnAi\/ksJjZVDVo1iQqkVuDRr8tRZnuwwXJ9RA4ZINkIL2NaxagVd0HB5fXPRDI1h7KDoKlubh2iX2RrMvAOqlVIAXIs3AZlGZJGWbpAMqkWr6I1GrhLPdI7FuWGVRV9vlI08EaitLWHSOsWG4FSgVQIQ+WWri7vkQZZl6+U5G9SpSD\/wLOVPRHHIi4tolAdeCs0xFKshGaoSw5KvyXU7tIoEGeqq+WIBBcYlG86cCGjJuqObhT1o5APW9p8uTffUeg81mK6+Oh7q6GubuXaJ9av\/Wld3S+a6DjU89r6xveZ982t659Yv+s4Yz37NqzaumNHfY27fts7tNH1NT9bX1O3mldZWbN2T3PjUyL\/+K71ezrZ6eatT6xf\/xo\/dunraNzgrlv52Pr1j62uqV2981jABzU+XlPz6FqS\/1N3XcNbzdtWbdjXw9pfXV2\/tVktxNjxHas37O8KAOs59OzW5tOsc8\/69U80HPqExqXPs4MkC+UfralZs9NzhjJ56Du2c3VNDW963cqaGl3T\/Kb+FSqTsc9aGupX\/vSJ9WvX1tW4G1pUmb4jDfW1NasfW79+XV3NusbmvRvqt7exTw41\/LrZyzobqdfPHiJ6Aemc27Y2ce3\/sHF9bc3KdevXr19ZV99AvRDZPPIeaVhdW0cw15Oq7g1NJ3imYL65YWv9yp+vJ3p1tURJgDFCbpPoPK8JMns3rBc6tG2v37Bf6DLobX52dY2bo177aA2Nb5dcgA52Na6rqVu7fv0Ta+toaI4L4aJlitpeqF\/7qvIs8P1hQ\/2qx\/Ypf\/XQs+\/J1bvepyLDpMTMOHMxofl9VmPKi+M1XgTCu5Hju7a+SUawb8MTDWSYPfs31D+7Y+eqmrpVYv4PWngMxvhEfbZhrXvl+ifWr11dU\/dkU9cnzVtU66vTLNp8GnsPbKzffFiZup6dK+tXNbQo07ulYdWW5s\/IWXU1\/aKuis\/\/tavrqrT5b9RQo3qi8bGV9Rv\/eMqu5fCp29jJfEe3K26NnWja4K7itkNuraZuw4EuWZb35dc7N7hr6p8iZybzRGyqvO\/QloBZUbHOXY\/Vb2vj5xl+zVc88dM68j+HtxkFsjZp9VRNhJ590gPThb\/T1LWauXQxNEJUw7Nr6x7lrmB1LfnzLhLDg4Uofkv\/svCW5h742M76dbsUz3K6aUN9\/WN7hZuih8zex1a\/1q4XHPpgorvmz5SOXau1oeeFmjevWr+fXJYpeWqL5ueWBlMnT7URxpJAZ8s7vtz5dxROamuhpUVoS9a+gg12mdoyC1MlRL7Jg1Jns5am17Nvw6rNusdx\/bZj3s5XVaupCzgBdqaj8Rd1dT+lBy45nJrVOzzcPUUy7U8Mz6vwz7Hr1+78v9xjKL0MdsKMWT1JufdoeGFDXa26SFDqs8gtLtifGB\/i3LvS0ojEGrmpyxja8H2orogsvRwV6jT1ZvTcIAeo81qcv\/cwf27Qemb1yjoFOylAYdB7aHNd3c\/Wy3VUkLumNVLI+o27ccqnilYAeaek8+SFpDLC4\/e1bFWGfiVNiT8onk0WQjyqBDrDupG+tK9X3PYP2UqL6WkZjD5o4Ve+d5te2vzkyx19zE8P3A3bDrSKP4ax58y6fd7XHbwEvdLT0+jTVkrog+XT0GBN\/FJMBhZwJuuNa35FsNFgmflDUz6jzQyWz9VXD71MK3naWaxbXUMreWWTxdXQ2Ti\/lFpZrV64zerWbFwyWYGldXh20X5HhLVr6+X6RKkS9vFqvodScPC3YMfCcyyrnGhcWyv2TbRNo4Ui97O8vPIKLOQisMoz7WYMw\/gfc5nmWznGAl34+cq6xxs\/CDme4DqH8f+6FTJtPJUdHK8jXsYtIc88sWetyYrO9NlE\/mu78iAwzAEuKOg1yheBnf0oC7YQ1\/lmW2\/+zILsgjxnyx9bQwt17dvddtnNtdWVldXVd+ef2tXYyvJuqbz5CpZWcl9lZWXFlbJKR6etorLOvfBrrGfPhp3vZc57SFZZXnpiV5P8g5IrKyrn57C0Ul7tljzW17Lt6UPOG5fXVlVWVtXW\/iC3fetGUbKv5dmN+\/uLl1RTm5XVVXen7d\/FD04Yy72m0PXeHw9Jaayv+WBLRlFplmyfx+ml995XmsZy5pNeS0rTmffAxi1tGYomNZXz0lu3\/Eq04G3auLU14+ZK3nR1beXNGa1bZdMs5J9RJi\/w8an0u7ly9Kr4smfb9haeebJxw472TCmzqnb5tSd2\/UEoml665AdcqZtJqXtJKV7W+Oprafiv\/QMzlR6vuCOtaY\/sMWMnGze+0J33A2qKBqC2stzZ+Mtt6olV56n0hdWCXuXNl3l+I06JDJDVlvJuUckE69CzZ+POk3mLpfiayrmTGjduF02\/uUcMASldveJGV\/OrB\/TP7YKCXF+HR+T0tR3vdk3xHT8uHhmnPcd9eQVXiFaHRYmlG8ZOiKDImG85plQWYfwIDOFGrqy4rySNXUFGwA2Tq9nRyb5b6XYvLKBHo5XH4OWYt9N\/\/b8JV1C9OP9vu9ava5m2lM\/X6uqlpbbmnXv5xtliGqfPyE\/reE\/unzuPtztdrnbPe0Loe572S\/LypjDP9o27zhQKw6uurVlSeGaXMv+plE5DuuLhTMuWX+5n1y75UXkmv1ReNEVv5n7tB5WVt+SxQc+2X+7qvVqIJLd2b2Hv7o3b1E2dt+NU3n217gfLdN\/IIodpZoNpxTOv8B45zHvH2\/mgpa23oPRqB7lNva+oXpi27zVhsLzQkK8+K9dq5tI1ad4PBq\/\/sRyB+wr9+7a8\/CHdshRF94KCqR+w8sD5BbmftSue5Zine4rL955HeBaf5z1f3lW5OskmDyaCY\/5MmV5c6PI0H1FWQ30tLR2XFJdeakFetmFQ+9e6I3hZAPFYEBDzfGZ+dkG+s+WweLAGt2K5umCWthymSrBsfhX6oAzYbF\/QYzrE9HSP42+nt2xdva3\/5hXCalb842Xdu3eJCdTXsn3zIefc5cKB1dYszn1\/y8YDXjbktB+uVznR+ORvPrjslmULv6bu36hzwU447JPU2+7ljmp5ud5RDcPigv1JusXDnXSioOOmLWOGQE21KPRZeTO6x5g34LUW53tfW7+2ddrSKhqP6tr7S+1v7mzkTkwUPL6vbdqP+Go1xF3z2+mW67ewAHlV4+vEvsZ3Lpsnh\/5uUqlRfgxmLIbrCycwhBtxZF5ZmJ2mNNPX+k77lJxcMdNdVy\/88YKMo5vXrl6zofniimV3FYo\/Lk\/LvjovU7WknrfbvNnTcpTa8m2IqWhiTX1BziRozS9FUhxssMzqoUklmanBihuHm\/w3rTDb6ZhVCetnWOiKyNI68ipo60Bh2bwcG8ssKhR0uT7Ky\/TxarWHUurwt2DHwmh\/ZL7tYqx5935\/yRIy+MrqFXMnN+9qEvsVLoMx\/UIuAqv0mjPsE\/7HZKPKTGVabeWCel29bOaJXX8UO0epqozDjotuhbyk0L9\/i\/optazKTLaEOt\/IV3QNjfSxEC2eTJ9NihT1LXQOqHdG\/T26RyGDnkNv9uYV0BIzq+BKl+eIeF4H9cnl+hz74K39HV4\/s2VXVLpvzw+6rV5kl96Y6+K69xxt9WaX3yZdCOcXCbEAABAASURBVLO5Cv+xLFt+EqsWVd6Pt3guKrzhauFqGLNfWlZ6eVdLK617PS3HnMUVc7PkB6\/2rLnzFWHs0tLiL3a1HRUT5XTzHzuyZ9L+ShEX+tbTfKTLqMnHzc09rOdIc9flZbepTbuuvq3s8q7mIzpTCRWmz7m8eNYXxTX17us5rKebava0tHizDTJFmUgiQjGp+JYb1R5fOvcWVTcu9orSuZdKFsxVNLswpa1FbudYdvF1ypbMVVSQM+j1no6kMX0ZPli5s1TU1B0S\/04L31pNcTlOe5re6vIPMkfJEveyoM0bX7p90tlOO4tBz\/GuvHnfzOk63kZXfcc8Xdm5uTbRxKhT4lItx5TfxGu8CAztRkI0yy6dO03aPp+ERjvVeQxXweyCyaK6PXvm19JYdkGxrGfLnFWSTVtlMmjyOabTOL2gIO1Dct70yPR4PldcMcPVcYwfLnQe63BNy0tjbUfeSglyNRXFKW8dUVaoAQ0Z\/zfY1fiLHV3TF96n2inPDH29c6QlpTjIlotSWg4rIl1fLytNV2xZrcq7b6a8o7CkoLe1hatL27w\/NfdOL+CWZe0rVIFh3q1da5hKzDXjugK5DrRfWlxwsc\/LHXDEokz9gJUHthUUTOvppA\/lqMvkWb59Q84Jj\/AsbZ4TObnT9Fq6TB5MBMf8mZJVWpTZ8dZR8lH0GUzzkY7MvII0ZkVetGJQ2+ulJ5O4gWgMCXgOKfM8qyDPdbw5ZDnCh8zCV1jZcpgqEXXEpdkszS6Lx7QQpHsczyzIHUzLm5ktTd3xtdkzLuo4zp\/aZDWuwhsKxUqJMXtW2bXZXW+3+Yac9sPyKmeObvnlIWf54oXqKkKoZ4jCP0lJyRBHxYZlcYbmwlzquBWpy5ghUEtpBNNiocjv67xW9syCNJbztWIF+xdnFV\/uUw5cGWMXl96sLiPtl86dm+\/X3DXdtA7hAZrVm+xy2T5oOcCX0oyW0nW355mVQt6FExjKjehaONOy7cX2nG+WaR+pOq4ozp\/i855Om3HdDGXC6IqzE41bD7DSGwvlA1G9M8RULLwhxJoimuGqePEedttiarCi2vSyimxFWdfV82Zdou10zKqE9TMssCISkoeO+tq272i7eO7ts9RjJ62K2eOVb3aGuYcKU2Wqy+E91tRyws+Yo\/g+97Ib1NMYw0JusmtoqzRnaD3ok12hMrmqZls5nj9kr8OOi26FnFWcnybXZxpps4TON\/IVnfcEPwqh7tCUCHk2GeoPew4Y6g\/j0jaMshde9HhLG8srmM4FZRVdndbR0ipWi\/xaeblKf7Bs7pS2betqaurWbtknVqnKLf1bilMxt+4eL9MueAlHZsYU\/m549XSfYqcPbazX\/q3d3+Oysz46WTjF7A5Fmqj0pS+qsziteGZ212H+vyR4\/9zSnV9qcEiitBZ193xi0MSZwnp6TrLukz0sVdWXF3c4U1nPyW6ejOQVVFepwLsdlO\/IvETu2JQCYd44ilSHU1ciU+0xF9uxS2NUX9\/QxpwpZN28cBBmnjHsFxff\/qpO\/LNtbJIQfwWdiM\/o27+xrqam\/vGdzZ8Ei7blXpndeZw+6z7u+eDy3LyvF+R2HvcMMs\/xzuzpdKwmCqfqCYscxnh7QfnDoCREWI6puItonAgM7UZCFAtMAz4pgqayI8hj2HWWkULe0Rb4uT0HGTQ\/NOESzKfxJXQw5\/GcZN53jrNpebkFBfb3PD2sx\/Mey\/1qOuvp6h60B7kah8M+2N1FR5ukb0BDumDseNN+34yKBbl6zyRuBEU9f+1mwbbsdNipISnSruuLWs1a+ekFeWebDx1jbNDT8o6z8BpuWWF8hSrQ+p1Xtgf1N+BarWsZvLEsGLkoA0ZRPYwHzp1OnsVDXfa8f1nulYUF06SfIc9yJT8JEtVFZPJg4kqZPlMYS\/tGQWbHkUNe+rT4SMsJeYZuTZ4aMFObshHGkADN82Ms7+t8nrNLi\/ly5G3DcoQPmbmvsLRl6yqR9cSu2iyfXcGmrT2mhSSdXsJH2clZiRuMOR2pjD5UYFyE99B\/BR64a\/fJRQ8LP+2H5VW8h\/d7Lr7+9lnKxySKCsa38E9Se5CXUOoOz+KUSkO\/6biphTmncKhFOV4oWM8gb6a\/lcLHQv\/ckMMhxLD0DHV5ya+nprnYoLLA4teWr\/AAzapNKV38wNypbdvW1tbUrduy32opbVYVecMgMLQbUYX5O3f9YscH2bfcdrVDyTrT8fIvNram37bsnzKP\/tdjuz7UzwR+ir7ll03sH26fKz8KVeowYdf6+caY5VRU6vDJO+QMV8oqb2EemowFt67U4G9pl+j9QFraFOGI+B2TKuH9DBvmM7GvdceOY5nz\/rk05CCEmYrinjqoCUfmUHuoMFWyv7tsYUHfvl\/WVdXWr9\/R7OULRd5t40IuAqtMM2XIhzCYoTboZjK5qmZbOZ4\/VK\/Dj4tdfUKJ7kUS2U3cO++O+bMpSGKQqkF3Rv3CNuoSwwhsOdzi72\/ZUiX+rdvvHez44+GQT7\/s6YW3LK2scVffX8qaNm49bFidGMRnpF\/MfJ\/QklPNP9PVZfZthfQvZLCLCu+u1P4tX\/bDpXeXpLP0zAxb8MFW54dyI0ESHVeXFvQ2Hzre2XTYJ\/cGlGkRQjThn+xlZl3KMi5JZ6fFR5tKTf59isws7VxYyR3WW4jMvq6PQkhaSOQofN5Tmq0y1vmx0mMuNqtsmQbpoeVLf7h0nji6shA2rGyOKKs8IL7ywaVLl86TH1a4ps1e+EB1bc2K27I\/2LnxZfnptCrdkX9lVrvH43nbk0lnH7bcaVmellaPpyMr7yr1oaIW1b\/z7gSRHwYlIYcrHDS71DEVdxGND4GI3IilaiFjauExLAUwLsFiGmcVTPcfP97Z9q6Pn33QyUh\/y9HjnuP9eQWXMhNXQ9MpNTNLvzTWWp1WNu\/Lrds2Hwo8U7VbukSoLZ\/y+uxfMhcp6oVRPrf4amdbi8ff+seWi4tLSWFSmdymha8Q0gIR33opV6SCSIV1raJExNGFiQrxA17vaSY9sOOqvKwOj+e9Fs+X+dmH8CwtHk971pX5Rs9iNz6YOHzTZwp1a0rhzCv4Nwp7DjerZ+hhyFMFhKgToHne72\/ZXCX+rd3\/Ces43Bz8EOVDFuT\/NV8ROiEVW7auMsz+8dkVmelZCuZKugrv1B7nlcsfWLr0zmLyN+GnfWjTp6y9SlrRvOL+xo0vhd9qh2AhXIyvjiyVpxvDsjgqP9IQ2l9tRRQQyWH69Ms4plsoBooNmfq4U7+26TrpNdsohEoZAuCAtpw77dPmMPGruL+ytrb6RyXswKatzeGX0qFtjkPOBGxyaDciOuVr27ZmY8uXbv\/xHQXak6WnpdFz8W0\/vqsg\/Wu3\/3hBRssrgV\/383+4f8PaXb2zlyy7IVPU10XDn4oRzXBdC5QM89Cku1bB+yH\/9rZ6l3+D3enUuqtmq++hWoXxM2oli\/dBz0s72zJvuqN4skWBkOyQDg69OwhXxebKvX7hsura2h\/flt25c8OrqpWHLOSGtEpzhmEHPVQmV9VsK8fzh9oTjea4hGBXMnh3zJ9NSoGov0XxKKSvufm4q\/g+t\/Zv+Q2ZXS1HdMcY1PuOnXVVGw9yZ25Py0y\/iDHVxfvP8EwqERzSZ5Vkd73e0PiBn+f7O\/dv2d+VypPKq\/9Tn5RwZWmx7dCO1zpFOeY70vDT1duO9lOpvNIiZ8tL21q84g45rN+29lK2DDaxPfjtNv5lFrE3kNn6uPcz+YQRmjTtONQj5PR37trceOrK2YVTWPo1xdknD+w4KG4M+jtf29zozZtd5NILMaRVmYbswKWQua9hT6fYgfg7923ef9IeuM16e9VfV9VlqklC4WzZ+Ru1x63bXnpb6TEX+37jtiMStb9z92P1G\/Z3qfUs3zXIliXkDY6oY\/c2Zb1JZ+SP16\/fx8X7\/rChatXODiJnd2SmT7XLIZOVROwoyMtq37OnPTOPn304ZuRnt7++p\/PLeTMs3SyvxrtzMgwlZsVZzecKdzWZjCmXjte4EIjIjYTRTIxpGI8Rpqpyi0swncZ0P6sgz9fycsvfxNkHyyq40n98d4vvyoIsuseEq3ntZflzFH5v85bftKRde734VJrfDnrZ0orvXlx8+uXHtrZI\/xJ0V7sQtrzrtx7h5fzew1u2taaVXmcuUlQKq\/y1xRmtTZsPezILrlY+WhHyTX2FkCajrOwveZv3NEsdevbtaeF+lW6J\/lq5Vsb\/vwwqFFkYQlR4IcIPHDD3wI4ZeV\/u2LO7I1OcfZCfye5o2vNBVl5gvSplmz2YCI75M4WqOApLCrrf3PHSUV+e\/N4BC0eeKiBEl0Bf8xGPq2SJthpxLy\/L\/NiwHOFDZrG6EBPSxJbDVBlm\/2h2WTymIxZESrJDO3epi57mhp\/Vb3ubnrKMhZ\/2oulIvcrknHn33jK1ZeOTu\/mj3EI3gaVpWE\/S4Vqc0Z+oD3ELjfTZor9DeTmCab1Q1EsLn\/6secdLirvuObjxpWNppdeFuuvQ9Zs1wPSsLIenabcY5EFf22tNyjC8t7OueuMhWsrZ7GlfTncOMjHw4ZXD3eESiMSN8J8sXbt6h7dkSeU\/Bn3NM71kyfK7lCeN42u3V96n\/Lqf70jDyl8eSvvHHy8x\/7LV8KdiRDM8qO\/hHppBBYMv3m\/cqux0fJ6Xtu735ZaG2ekIrSL1M4F2Qq2DebZva8mcd8fMsPuBgASeEh0MtzvghcRL23taV\/E1PVlV\/4LYwUzOTE+za\/tWZljIRWKV5gytB91MJlfVbCvH88PuiXiPRzguvKryGnpLSN2xeDYpIqL9Fr2jkL6Wlg5XXsGlgR7ybxGfaGsJOgvJnnvHbP\/e+qqamprqDS1T5s4t4pM7d2aho2UjfXqz5a1AdZlyzLxjcYn90C9r6G5V3bYu+oxCO2SYRtWObqyuqnq6hdmy5v3w9suObaypJtFVqxsHihcpJ4hZNy2puLRzx2ohYV1TRsVc\/W8UZdH24BOvK+gHU2XLFKfPmJntfa2uiuSdZI6Zdy8pZfsfE3LqNnouqfjR9\/O49pOL7753FvtvcaO6ZuOxjIr7bxc3SEJoCJIZelvJmVx8x6JS+x831FDvqNt\/vXreTLXbl8wozvbucldVrWlUvuyh1FHfCMXiiqyPlR6vfSPt5hvUHgtVBxpXC\/5C1cXzssLPET1ktQWrd4FoYA+Jr62pquWIltzEN4muktsqLm3fXEPNVtX99tSM75bxXL0UR17u57u6Pp8ruTmm52ac6HJOk1f6csHpMJSYFeegfKGw2ZgGt4OrqBGIzI2EUyecxwhXL3BPzAqTacxLXDYt+5Ou7pxpcgJnTc\/uPtGdPV1esayblt6e1d6wivuqmrV7BmYuvk\/7m1JeOfhlyyy797bL3t\/2063ylCH4rrwiWya31tFQX00ya9b+ntzafWWXyHvmcTjl04qvvryj4\/3smdryheRb+YqA+LSjUZGGAAAQAElEQVTSf5p32ccvCx3qNnvzCi9W7hlca9pNZaqjYWFculI5+M0gyuClg8uGXAm3ZuGBHXnTXF0nXLnTuatmjrzc9K6uyYqf0QkyezARHIJv9kzhFacXF\/Z3dLDCYvU3R8KR5xXwiiKBvqMt79FyRDFM3nDa1QVf4l\/k4Wn1ZfAV3tIK5ZeDmKUtG6oELUhUsRG90+wa2vSGkCQcjmdjbVUNPXBXc4ej7hYc4aY9NU0TO3KvMrlg4Q9mswMb1soNuZlSYvIz3epIXR2ZFRZ5w7O4YH8S9BAX0sJG1N8g1Bm33Kg5qkBFgwvSe7NAoSFT0+bO9e8Si82atbt9+d9fYnTXFus3S4C23JvvKE6hpaB4AjRl8p\/i41pcMfeOWf7GVbSmqql6siXtxrnFwsPxW3iNFoGI3EjPoV1H+pwp3j9sqVf\/bThgvjYXerXtaexMcbKOF9aqxet3viPuqJFhKg79NDTOcN2aX5VpfA\/30DSW1a7Trr0l772NdTQVq+sb3nGV\/c\/blZMerYQ+QVoNy89QXXPraPnj0T7W8TJvl5q22vhQdX2YHLyHIueu7aF0xYIci6FKYNvlKv3HiqyOzXx3WV33sndGxQ26J4t+IUdebSirTLt2bu47JgwNgx7wP6aWLobPZCtn2QVdn0cwLrraLLItofWzSS8reunw29zR1MMxc7H7oXm6CcLYlNKl7qWzlc8flbYc2WVLqtzuqhXVdbWVi0szhYKOaRXLavjnNwu\/xtglZcvdCwuU4vTmyC5fUl3nrq2pddcuv\/3qvLkPunkxfie3Ylktr3aXKO7K45e11dXVbhJdpv66D53bFX5\/OVWuraF2l8z+fJ+P6b7V9anPZ8u2+sHU9GsXV\/IWlovnmT3ren7JNamrXfb9wjShPCliv3S2uFFbW+euXXa7ulUoWEgfRYXsW\/Qy08uXu6XyJIXC1xa6H1R+UlQBVVNLmi\/\/fmHejVrJ9FLemFsrSfV40HO7uPD2B6ke16f63rLskoBYRVWCRPc1VfV1uSyd5g49ZC0\/vUwbBcYK7nIvL0\/n9ZiCqHpFtVuPyJYmh2DFv9e6a5ZVyG2JqKBGrtL73e77S5XzHj5z3EtnKVcjosT0nNVW+HtwvqJw6JjyonhFnYAjMjeinxL6tNDX0mMUBCYqL2isGLA+ZVYYpzGvlHtbjbv2H9UP+qbdRmZ0m7oZZjZX3i3LuBPgzqpycbnigwwNBS5pj1Htrr6jMPgH1TQr4+0x6dbqamuppcrFmlsz9EUUlVEY5R3Fi93uusWF+kWzla\/Q+4SLixeSHyQV6mqX3zK7QrN91a6lay3LLtY8noVLD+4a07mRYFFGLy16FuAmLllgvJji1riGeg\/My7lmLXW7l5ZO4WnGgv2MzBOx4m+DH0wK\/NBnCq+SNa\/SHfzIMycfRm0uBq+xIMBneuU83QczcuiXXp8W3FqQr6jIZz6f+gcNFrbMWFAV\/YKk4C7tOag1opvhQQ9KUSAS0+MFw1iN4nC4p6JFj+pwqNIQ0z4yrxJwMl8sW0YP9HLlt9hJPoXgia1M\/pAnqUF5qqeEYVlckD9hQQ\/3gBp6l8Ub0TUdhHp2Gq0BHU69F+TFg12Qzpvp5PByQWNKGRoloUlxLn8E1FZX1fKlTr6yhtHKkO769Zsu3wogTbh5S2ntSkvBuuols+aqPlaZh9X\/Xu2moZ8V8ncWpBnCBRKIyI2kl94b+CM1mVoyS66HTZvPU\/4\/FFlUxBXKf52plg+eirqnoWEq6i6DZniZfs2vCmVifoq9ksiyeGjqZIpiQZEto\/iuytq62mpaBVUunq38DwyGKrpLCz9j0KQgsDAL2t2o+SSQ7\/OUl9giqbeMndKvChQPQ4ZDW8db8nTOPdAng2MJqqLfdkm8NStWUMeXVeRO5hICvQgs5IawSq72jYXcAxgZMsNGtSywmjKXqQxfdXU1rQy1rRwjd1G2hLbYNXzBGLxz5DorL5fYLNfRgok7D6tVZaCDSjXxZr4lFLeCVnTmzyZOQOwWzYVLMWMQq5v1MRB9QSJTHfynp4Yjwp5qj6i4zW4PLuj5TU3N5uY+ZrencgF9xzxdU7KylJUx87zR3Jsf\/gdTeS39y1ITannUeafag3ujV2SodBh9wtwaSmok9y0Q2R2TR96bcO2m2i9QroXC4drEvRgncOFjOmIJI65oiTTErVmWVG8MT4dIHIJlGcW1qi2P5D28l45UoqWGkQpgpg+mYcIfHvmIVYvVghNYL9+B9VVrdnUNMmXIPjje4c\/KDvo8R70V0kulSkj+sDMufNIySyWHUGaYE3sIaeL2sLGMhsWJlsNEnm21NVuO8DWgWHb2tR3vcmVlKacUxnqj4M1oQEa81LEEmGo3XeTYx2hNZcSC6+gRGPnTcATOZARVbHaH2ExFSmQM\/MzQTZ9uWl+1etcJxlLt3HAGO4\/\/X3\/W5ZcNXZFKpNp5FUoYAp2Tm98wlGNDW6UlQ0v\/Yy7Tbhc+zaiA0uuQ7KCMqIyLpUMLUmXML2xj3kLMN5D7nVtyP9q5cs3GhmcbGjauXvnbnkLtDzT6mptanYXiP1OI+X5AQRAAARCITwLhvHQs9hg6xQMB17UVs+2H1q9cv4XWBpvX1\/3yaNqNNwd9Zyoeeok+5N5ckfvBCytXb2ygReDGNStf\/qQw6CvuIAQCsUQAT8NRGI0ppRXX2w89Xrd+M1n9lvUrNxz9\/Nybi4xfBRuFhiBiIhDAUQhjkwtuX1G75NsFmS5n+pXzllRXVkxT7aF3asE\/LSwL+hrtRBhV6AgCIAAC0SYwlu2F8dJj2SxkJzQBW2bZA9XLvz972sVO1+Wz73hwxZJrw3yzPaFRTejOO752e3X1knkzMl2T0vO+vaR2eUWuugac0P2C8vFJICafhlnXVsy9yjWBgGfesKz6wTtmT0t3urJmf3\/5CvVnaydQF6DqaBHAUYggabNnTi+cfVNFWUlupv6bXWnZhfmZeCYKRohAAARCCSAnWgSsvHS02kc7CUnAnpadV1xeMe8f8rLTIvv2c0JimvCdTs3MvXr2vFvKiqdn2rEunvDDGe8diL2nIe2W8r44wXZL3LmXlFXcNBvOPd4NZoj+weUPAQi3QQAEQgggAwRAAARAAARAAARAAARAAAQmMAEchUzgwYPq0SWA1kAABEAABEAABEAABEAABEAABOKBAI5C4mEUx7IPkA0CIAACIAACIAACIAACIAACIAACcUUARyGmw4lMEAABEAABEAABEAABEAABEAABEACB+CSgPwoZrx52Nj27q+00td7X9pvVq3\/bQalIw8n9G+o3HuJ1I60xjuV8rbsa\/tA5jgrom+7Zt6F+0yGfPmv80jFFZjwwaCYw7MYTHt2wiY2kQl\/bttWrX35vJFUDdcbGWXX+oWFXa4R2PPJpFujFOKfULozKiIyoLzHlOUfUA1QKR8Dao\/bx9ckLnnCVI7on5AxrnROR2NEo9GFTw6ttEXqTkbVnhjeGgYysk5HWUr1ZaPnTbbuebRrHxaLZMIVqiZxxJxCR7ZgsEsZmNTLuOIQC1mYlblNkAoRyLzB4WxrW1dWsbezhcvo692xcXVez5S1+EaOvvqBl7YiUHBr1iMSOQ6VYOArxdrS2dfXxztsvSstIG9b\/xvQ5Z\/rUtEm87gheLU9Xrd4t5u0IKg+\/Sl9XW1uHd\/j1xqYGkUtLSxkb2cOVGl0yPY1rqoblocZ+ngRMILbRDVe7uClvdw3XM4muB88cMrmROyshzyTydrQp3tPkpiHLq3law41oXL61pWqNXCVcSGtaF0Y4IqFtB49R6P2QHBrGmPGcIcoh40IJWD+MHGlfyMi4eFjrE1WZk42rq7a0qFfDX+eoNcf63dvRdkyuxXQtjY7lKgJN8cYuEEXrMXrzWjpkwtQ6notFal9drA57vTRGsOJH7AUa1PCdiddkkUCPsdFfjUQ+RsN+7EYumnlNzCoYmlcFMgypQxVt+e02z5SyZT8qS6eSJw9s2+fNXVi98Gt0EWGIvqFd+CLKa4I6wu7GWLHoH4X4+077fKd9\/sFQEo6c2bdVFPGJxPp9vjN+xmThPkrJ0n5fcN30GRW3zs1x0E1eksukiqd9vn7KCQr+M7yiEKSUpJxektun5Yvyg37SzXdaFBQZZpEigSupNWRVUebzvugk8Ux9E6pApQi\/JDV4d5Qc8cZrkbb6iiI\/KOJ1eUXiYNDNR71lXGehTHpBxW3lgpyobgQrMnlhginKywzLWOoW3ASvzutylUyQyiq8gKVUdQLoZwuXZt7B0FGTTQRrRT3tG2QDnxHJgFiaDAQ8dNqQZnTLZJ6EzEwqGQgEX98vP00yAZ\/rw4ePZFJzPBWoE5wiCUReG0HtpszXC9duESw+ycNJ1ZWd8EkaR2LIZ4LaFU6ViBFkOeIin2ee9gko6swR+URLOCLljk9WobpiFulqidKOnOtvrSgmz8QL8JlDTfOgGwhdFaUhygmaOQFnJWSSBgZvRjk0grILNPpSJaWseJOjTwWopE92SuSbR1wNUlKPyFCQNKQC+mnPc0i+7GZAASlKsNKLkMUEMSWb5\/BiXM5pnYZkAp8NsME+3pwKLXQEFSHKm65Rqh5QRtzWRkRcUaRrkVcUvVYTOm5UUh+oVtAYyXvUHPFX9ZR5WhzwnCSWl+Gt6P1bSL94Aa4Ph0NDLlyBFMdzFFz8TWaG+BYukAZFucsYrxWR79JqIGFJgAaRxlqPVy1Kc4Omq25cWMbVFRUzM9X74mFKdfkcCOTxlJSp5dN4+eijnoFeKsynsSNHrnOoGL\/kNeQraKCpFpXXG5coxMucDoy+yNNHfLIps5GmsZTPRfF+hPZI1BRVZElxHRSRkCDL5YX5ZCblA9B4prFRKYU3TQ6Tty4z9LHQh26pQOgeieXcdAIpUwtSmlRVKandowSvpehG6DT1qAt0ycVSGV0gCWHyRXWiTfopdYxy1OaU2yxQmCTz5qiArvYZ4iBdIuUHj6C+X6q04HdehWYj713wDX5l1hxffYX2LqQhPgSip1wOvRRRlFIC75RhvRQiRCmakG8aQAJlOkDGfJpFQQYlqZmMryLZQJsuTZ2JFEMxjSCNuxhTajow\/+iWGvh7YDXCm+bzSleRFyA9SQ6fxvyKv6iAuOSK6R\/u\/B5\/6fJVmTybXvxSD4dKmjx2qaASZHmhO6kh7V08Fk30VKowkqlvQs0W70ZoIpMiyqc+KvLpWg3UU8oXnVWzDO9Sw4AV+890dJ5kWVfk2qljJLaj0zslZ9rf9Yo+yLqyii5D36N+4T0MhibrBRdT8kSmWX91rWjoSJ+g5wgvw0k61GUtrSfJO9GcoZIBGryYWRNhUav6Tbj3qB6F9HU0bnDXrXxs\/frHVtfUrt55jNYHQcTattdv2M+\/ptGzf0P9loaG+pU\/fWL92rV1Nau2eT7p3LWubuX69evXra5ZuaHphKjYs2\/Dqm1tPNm2bdWGhmfX1j260yBI4QAAEABJREFUfv0Ta1fX1qzd08Wz6eXvbHy8pubRteufWP9Td13DW81Ucl8P87y2vvF95n1zK+XvOk7lmPdIw+raurVPUBMra9xqE\/yO4SXaemFDXa2irVVF35GG+tqa1Y+tX\/\/zlXWPN35AU01KCqgtr7lAUoku\/B\/uN0Vk1QRVCQ5cVINOt4AO6+pq1jU2791Qv50D44RFgg12Na6rqVu7nrjV0aAcF4My6G1+dnWNm0Nb+2hN3S+aukyOrpSWwzWhH0R3Q8uZkCoGMsp9\/maBwthBKzIWWvUcenZr82nWuYf623DoE8bOdDT+oq7up9TTtavralbv8Ij+cwXkK3Se9B3bubqmhk\/jdStrakymcYCtFPHOtvqnxPDycd\/csLV+5c\/XkwnU1dJsNLRG+5yupl\/UVXHypE9VgPygr21H2BE50fjYyvqNfzxll43GcXyiaYO7is9YciM1dRsOKJbOvcevd25w1yi0LQyfwPg\/bFxfW7NyHc2Bn9bRtDw85ADxWceH8JNDDeQfRFi7pl6aErNoyDhz+OhLZ8VYmC4827DWvZKc0lqaZOsaFbsb9DU\/W19Tt5q809qV5NyaG5+q3\/YOdcU8DOlpraY9Z6hToO7Jpq5PmreofrhuzU6PasLmdsf7aDbDj+9av6eTnW7eSuhe85j7HF1XLAcoUEYdEcqx4M8YL2P+UKBaIhjHiPV5yMpqV3LOj9bU6PorivNIs26e0Pu3VRYPKaHGy398eW0df7jwYdXEclxbd+yor3Ero2nqW9pfXV3\/6xbetnj1HdlMD54uenQP5btEcUQWBAa7zD0tFR\/0HtpcV\/czxUsHeRixPmFWz0dTL01O49fNXtbZSJP\/2UO0vuFWRnI6dq1e1dCiPVj7mjevWr\/\/JDVvsRQxfVLz4srL0mr4NDOzSloBf6h6wvUr6+ob6MmoyNLeDJYrJrN+gWHZKGO+1p3hFlS6B5YChDGjTZFzVh2OxQNdU5QSBnvnjwbvYe69aG2zemVd4OFuPXxWbrbvrYa6OuEWflpHD2UaROle+EOBWuahZ5\/qk3kvnt2xc1VNnVydWjooXu3TDjPPwO8oryGdubE5q96daFxby13QelpRkwsSSw+NvGyMi5LLQnnNQtZLZkKUsrH9NkbacYCvHnqZltC0nKC9CS2hjwmy1N4Js4WK0aCY1fhyybpnMa3e+WLAyplQc8NaJHCfIFcjbduCtk6WVsPnxm+aDpk5RqslEClluowPeexSQSVY+xODnrQKUhZ++tZXuusbjoT8hV8INN4YzWSThZZ3yI2P6Xh5XhPbir0b1pOHp+ZoteM7uu2J9XJrafpYlw5E9aUe48aEqyhfouO6PZ2pAlTUgK75oH5ZK8eaSlHgAoXj0hKMTzbd4tmqiaFRk\/iJGWg9FS3F+1q2PX3IeePy2qrKyqra2h\/ktm\/d2BTm70U+PpV+d3V1ZSW95l3csmXttr6bVtBlZfWK27K6d73WrPobTX\/vB4PX\/1iUqL6v0L9vy8sf0q2+lmc37u8vXkJSSFTV3Wn7d8k\/9s27pfLmK1hayX2VlZUVVzJ2snHjC915P5DlaivLnY2\/3ObRlikkKSh4271599W6l5enW1Y82bhhR3vmzZWiv9XLZp7Y9ccwvRXS+1oa\/mufs1xBVL0go3Xr5qbTF6SbTofa5dee2PWHEB3e3CP4EIbqFTe6ml89QI\/5nj0bd57MWyxh1FTOndS4cbvEJvTUR0HdDGlCN4gVX\/Zs+7UYtaAqFmSsUPCmhwtfr1V66b33laaxnPnU3yWl6X0t2zcfcs5dzntaXVuzOPf9LRsPBCEyzhNv08atrRlyWKtrK2+mMQo7jZnhX+ep9IXVwgQqb77M85utgkigjGf7xl1nCsV0JX2WFJ7ZJcn37NnQ8H6uOiJLiyn\/Bd2v6pxp2fLL\/ezaJT8q131oGZAaR6lBz7Zf7uq9WhAiN3JvYe\/ujdvEUSZ10ttxipvlg2XprM\/K8OlOw3\/tH5gpJJB3WZi2jzbnVFkJYQcovXQJTRwKi652DToKZhYwEhehh1Hk02lX2C50+q\/\/N+nFlhT69295lf\/BOI3+zvcy5z1USzeqq5eXntgVznMO7WnDTXtvQIHF+X\/btX5dy7Slwjyql5bamnfu5fpYOj3eRzOAV1ZUzs9haaXc296Sx8x8Dq8qX33kBsMMkCykxX2WA82LmD4U+A35Mli398DGLW0ZCueaynnprVt+FY400\/m3sA8pb\/NB\/80\/FsNnFNvRaauorHPzb9Ja+Jbcawpdx5tVR9F39K2OzKLSLJp4Q\/ku2UfEpgSsPC0vfHxf27Qf8dEK8TD8Lu3YLZ6PZKcmXpqcxg\/4M+dm8hv3lqZLERRPLy50eZqPKAuZvpaWjkuKSy+1ftxfkNWYWWVfkKGtuCOtaU\/IU95guaQ20z1\/gyVU630pPeWfbc9VF1RLi3p3\/XJn4IkV5oGlsymLNYP+gc4V0r28gUXg4nzva+vXtk5bWsW9Zu39pfY3dzZ+yMtaLW9o+CzcbNe+3W2X3cxnRHX13fmndjW2cjnhXh2d7LuVbvfCArJTiweEqB7GM4j7QztzUSzQHNP3rromsHhr3r3fX7KEWNASeu7k5l1NtNATdcNF6cHrJTYiIeEaiIN73sNN\/ptW8HW+fkFotVAxGFTY8dU9i5coi4H00iU\/MHMm3CltsJi9QzKOyGq4FHPH2Gf5CO4jD2OyozE8drlk+eLlwzz6dXpabfFW3J72h0ajFzODZmDbsIebg5XtSO14bDFeebeo24p7S9OpOXW1w7eWFo91Li3gS3MNhibualGQyzXfR4egM3HmmjyzRGDxbNFH41rXFLWZ5AmRF8WjkOMtnosKb7ha+VNb+6VlpZd3tbSGHOBp2C4vnvVFcWFzFc\/IZVPyZmbLD7wdBdfNcHUcbxc3dZFrxnUFDnFtv7S44GKfl29pPS3HnMUVc7NkVXvW3PmFigaipBb1tLR4ryide6ksx1xFswtT2losfyjRVXhDabooa1WR52eX3ab213X1bWWXa61ZJAjRpMLZRYqCjq\/d\/uPltxdexLioEes2pA5TXI7Tnqa3uvyDzFGyxL2MtpE9R1u9ubNUaDZXIcF4p8XoX0QnuG5hmtANYuHXc5jXS+M9RBUhllmgEDdHET5ND5JW6JJ2YM8quza76+1wvxvXc6S563LDsHY1H+FuVOg2ZJRdfJ1yWuEqKsgZ9HrpqCtQqe3IWylB07WiOOWtI22Mj0j2tWXKNLZllt1fuawsS6lHnxb+YkfX9IX33ajcV\/Lj8u2dIy0pxbeoPbVfOveWopSWw\/yLTtRd19fLFLNkNLIWhs+nVrAE1UhJAmPhB0gUYT2Nz+73fe2226bRpXVDdNM0hO9CweyCyaKaPas4P014MTH65bcpnovs8R\/Lsi1PaRm3nSE8LelsOe1dAQWyZ34tjWUXFEuHZMucVZLte89Dc52bsKVHigCgic9hgX9DDFCgoEhRXywGmt82fSjwG2avnuYjXdkGzh83N1OHzUrzPJ1\/C\/+Qyr2hIlsOKw3fTbMyA2KzS2\/Mlf7H0rdcWlp8SUdLi9gzn24+0pGZNyON8RluOYhcN7zCEbDytKLOxaU3lxBhniYPMzffr3kYniW8sdnzUdiplZcWNYOjrNKizI63jopx9YlxLaBWLY3rgqzGzCqPt3gmFQf50iBPGKxs4IpmneplrSXwXmSXlqkLqswbflT5wA1Z0muFf2DpbGp4awauIbd3ZRGYPZNo5nytWBoX++Ks4st97cJ7WSxvxPAZzF8qzFyuz7EP3trf4fUzW3ZFpfv2fN5YuFd26dxp0m+Gd1DM2jMI8UR4CGcuigWa470wm5xsqsvhPdbUcsLPmKP4PveyGwKHckJERNGoCImopQlUaHpZRbacdMx19bxZl4gFYdinfKBzYcdX9yzWFgOBqsEpPu7Gh5cye4MLmlxFYjWimrljtJ7h1DuzHY2QZRbx8mE8kk7P4W\/xDO0Z2HpPdtFpkoVn0FUlDSOxR10Ny8c6L6PzpfzS6qUrZqUA5Y\/EmQdadGmLZxJl3kfrgQ6ImagpuQWMhvY93afY6UMb67V\/a\/f3uOxMLANM2091Kt6F7qYwZrNTREkeHA77oJ88Ok8HXnZHoIKay1sNzv\/SF02fAN09XtaxS1Ouvr6hjTlTQtpQ5QZkWlXk+am6LjBH5iXy0ajKCHnnyqY6nIF8u2OKy2FnXNSIdRtShysqlt01o2\/\/xrqamvrHdzZ\/Qs3zBttf1cF4to1NMofBi4ZpIugWSeZhiCq8CLNCIW6OHnzejPfQfwV6unZf+EnJuk\/2sKBOOZyprOdkt1AskihFPyeMFXq6ugcDveN3+VTv7urhzIJqprpcZD28BG19m\/b7ZlQsyA2d\/vJ+PMU9f+1mQTbCnGQhPV1yu2rXrIePrD3IIaiGz+8ES8gMcglBmE3R9ezZur+\/+O4FufwuF2feEL9r9oq0C4G6IaPvyMyYErhtSHGNwntaXsJy2ts1hoyl2Mjx6vyuM4WJ1RVXyNIjDQ2QmficQCe4duEGKFCSp3hpu+lA87ss+JbIso66ez5hQdo7qMM9PSeta+hdAXGyfEilffESnZC0NBfzS5JM16C1b0m7uiCz4\/AhL2PeP7d0XTGzmO+Y6YFqOYi6xpA0I9Bj5WlF4fQM\/SJhKg3XoH4pwKe\/2fOR5wfNH72XFoINUdo3aFyPiHE90nIie6Y4f+FSTI0rrNVwOwhnNUF6STWGqiJLhcYBmwojgfdCbx02u2uKy24T0o6HfWDpa4niFBmlWa6mAroxlsKbI6uk+jzwJzV93sPEeiqi4Qu4WVfpD5bNndK2bV1NTd3aLfs6rJetvCX+0nrRQ3aq14ox9UnEi7EwnoHf57XDO3NeijGtOcvesezvLltY0Lfvl3VVtfXrdzR7hSeXtSOPR0VI5M1NiJJpl2Tq9ExLm8JomoV\/ymvlw4+vXfcs1qpYJLiJBBl5YPZa1Ahk23UP0BQLqxGlTR0j74NeQmCG8ztBTknZ0QhZJlFIeRa8NgtuRQrgdYLzg+xLFjKJ7SZsOUMzzxCozluLxB4DNcJvGew68ro6xmSgmJUCPD8ItQGdUWLotV0FwkWZ9pHfsAcpHBnq0LZiMMcWNZ3Sv5DBLiq8u1L7t3zZD5feXaJfcoyBLumZGTbxwaomu\/NDuWvSMmQi45J0llW2TNPuoeVLf7h03nR5M1xsVZHnnxZfTFFq93V95FOS4m1AexSd9skbHFF\/X6+4KyL+uzV9fsZFjVi3sDqIVphr2uyFD1TX1qy4LfuDnRtf7mQZ6RezrPIAjMoHly5dOi9Plg6OuW4RNKGvFEkVKxR6OZTmoszI8PxItOLTw1V4pzbqlcsfWLr0Tv77mCTcNIRI5l\/ryMxSv6Ch1Rkc0JK+03J4tQzrBNcneLp6vb7UzCx6Al3MBnp1C7B+3e8vTiub9+XWbZsPjWxxYwWCYykAABAASURBVK1NLN7hE8PnPaXZDmOnvD77l7KMfiSUpGr4oRI6PzZ1CRbd9zZt++++4n+alyV9p3VDFvVZqALmXQjU5\/bo+4Q2wmrWma6uoC8TqfnincsP72m5zsOb9kJwIOJWYGZ3gRJDpUJ8TqAC1z94iMMNEO+LT+9nmTrQAYmRpkI4k\/WxzKxLI61vXc7b+b7OeE92dzNn6JEopxrktbze09Q89y2uopnZJ9tavD3Nb3YXlBTyQ0\/e8QsaRGttJ8ydkSvK6QVPGxpr7mmFyI87xZ+BiTRjXSe9wQtAPk\/Mno8839JLK8KC36YUzryiq+2ot+dwc3d+qRjXcI\/7UbMaocXwDE1UMURhJPDJ3K97Yg3yH6SnLSKXMPwHFpcWZBrG1RQXG+mLD5PV8Fm6WXt64S1LK2vc1feXsqaNWw8r5qz0iDd9in\/llSeCX6EzLchBDeEZOOHwzjy4NRZm8WZz5V6\/cFl1be2Pb8vu3LnhVXWO69Yqp4Zcq1gJMaqRQNfeD9uV2cA7TR9bcefOB8439EKFFxve+PI2zF58VlvOXrMKI8kzdYzWM5z3zmxHY9U0Lx8MLdyjX0qxbl3eH07MGZp5hoAMruEwxyvEd3m1x3pAbsQpKwV4flh0oftNqza5KNM+jiZqq8bHLV8u56PS\/JWlxbZDO17r9IvWfEcafrp629F+cTGGUV5pkbPlpW0tXtGsr23bb1t7dc35zyjb1PRrirPfb9ym\/OKOv3P3Y\/yn6ajk6bZdz+7vsNbTqiLPP7mvYU+neFj6O\/dt3n\/STvJ4SM\/KcniadgsUg76215q6eC5jV15dMKAh8vcc2Lxy3cvtfsZFjVg3Kx1ki4z5\/rChatXODsJjd2SmT7XzTWb6rJLsjt3bmiUbf+eux+vX7xM6ftjU8ELQF8a5bkM1oTalvEdUxQKFIkJ946LMyPD8sFr1fiYfXjQ92KGdu8RIEIvmhp\/Vb3ubWKgNqO9B8+TkgR0He3ihQX\/na5sbvXna3zTJ4umXZznea9r1IS\/CfG27Dgp08t4QMenjbHntZY8g7\/c2b\/lNS9q11+ey9MKrMwMj4vPsfKx+o\/bTM7a04rsXF59++bGt8jv0Q7QxsW+TG3G27Pqtx8cnqt97eMu21rTS68QXNII6JkiaGr6QsPM3qkto3fbS23qXECQl5MLb9OwuX9Ht8y7T7lg3JIpoM0dciUgoEEEXRGEecXvser2h8QMxo\/yd+7fs70rlN8xfJH8IT0s6RzTtzeUza49kVUHm938qRs3U58gSIib9nS0RDxD1JZyHFxKHiNQxEpybdhwSxs36O3dtbjx15exC6y\/gDCFXd7tjz1ZFrM\/z8rP7fdNLQ8UKr3XA3Lc4Ckvzu5tfeOmIL69AOaCnjl\/QIOq0S8Ak0TP1tALFZ807XlI8TM\/BjS8dM3gYPk8C3jjwfAzrpVlv7xkhPChyFJYUdL+546WjvryvK06MTwOzh5rZk1ona3hWIypGXkW1XFFNF1lLSL+6MFPrxaDP89La+k2HvHK9OfwHFmcS9oGu02nIpOXw0bLHws127Kyr2niQP5XtaZnpFzHxla6s7C95m\/c0C5\/m79m3p8V8lShmmumTSGg6hGcgwkM4cyElEFn1ztf0ZFX9C2KhNzkzPc0uusCyLs\/0HqY+8Pr+nv173hKPGH4V9FLXS6ZC+jr2NbboDuqDaibCxfuNW5UFIc3zrft9uaVFLkYDF2ahohkUFRve+Eqgoc6Ej7vF7JVVRiM2d4zWMzzsMl597OoUIxrDePTLitaty\/uBOBRa4J5IcYZmjl3clBFpOMzxEr7L4rEuZepi1dB0WYaklQKUH4xux5vcX\/Ha6Vnm+01+z+xFosz7aI36TMf+3RPbB8hHkxmOUc+zZc374e2XHdtYU11TU1O1unGgeNEdxZNHvRmjwKybllRc2rljdU0V\/VvXlHZTWY5aJHdmoaNlI2VveYuxycV33ztroHF1FWlXXbPxWEbFYv7Bb9+xQ019n8sMs\/GwqEgC71hUav\/jhppqaqFu21+vnjfTpbRsy735juIUukV3atY2ZRYoiyBb7m33V2QoiGoe+wMr+8HtefQJoEUTkehmqYOiCnOV3FZxafvmGup3Vd1vT834Lv8JCsfMu5eUDuwhGLU1VbUbPZdULLmJfzjZ+WZTpz0jXa3L3ycXD9kEL6Z\/RVLFCoVeDqUtyISDz9JnzMz2vlZXRXPwJMu6aentWZ6NtVU11NPVewZmLr5jJhEn0YEQOk\/Yfz\/G55OcJ\/eLMQoUZ2zazXfMTDn0C16kal1T5teU4dUXsUoLfdobVtHMqKpZy\/W5T\/xNb9qsxYtnqiOyquGDyxfKfEWOLbPs3tsue3\/bT7fKlZmSHYdv0o10NNRXE6Katb8nN3Jfmf6vD9Q+Gww\/o2KuYvgkYXFF1seKS1j7RtrNNyh31KrW7yebD33MfH\/cQG3z8HQLFTU0ZOlhqKgMpAB5wgi6IItT7Jh5x+IS+6FfihlVt62raJ7y+x10LzRI+YoboVlOiIyeVkyzIaZ9qOBAjpXdBUqEpKaRtz26kUbt6RZTnxOoQPqHDFDgbkjKwD8w0CElTTP01i38HtsvjLuqjvu9H32fO2DTisPJTCutyDu+sY7PmfqGNlfZ4u8XGL0MiRNUrXxLbnGh\/70OdnWx5k0udBCpxQQOgl57qKflSKbNnevfJZYMNWt3+\/K\/v8TgYcQ8Ub1xLZ8n8vlo6aUvmVGc7d3lrqpa02j8Btr04sL+jg5WWMx\/eIg3Tg8v06XI6FoNbylCQ9NZLq+lf4WRkFa6eFGxsqCqqW94P2fhvWWBlcNwH1iTg5cZ3tIKbTWl1yeytNXwWbvZ7Ll3zPbvradFUk31hpYpc+cWkfmmlf7TvMs+flk8ieo2e\/MKLzZv3uCg9A8IxtJKb8xtC+MZiDA9LMI6c0OrFr1zlf5jRVbHZr78rq572Tuj4ga+oku79vZ5l3e9XM89U93T3ryr0wzSWNB6yUxIf2vT3v2H3lH3XSH14z4j7dpb8t4TQ1hd3\/COq+x\/3l7gYEwOnOlTXm9QsthwxpdZOBPr2Tt6IzBt7s22PaGO0XKGWy\/j9Y\/dgH5EYziPflnRsnV5W8YW0ORNLbawHe2+OqzDGq+wj3Wd6KCNiS4\/OEmITB0C5Qeju+VGdaVgs9hvBgsOXJEo0yYYs0Ltf7ep8cChNuuvKgeEx2oqikchhMCVV7Gs1l1bXV3trq1cXKb81FDBQvdyudQouEv8nyzkfcuXu+8qoBpK+NpCN\/9fIZQrdknZcv7T3CyQYAEholB62YNu\/pv8dGFLK\/z+cmq1tsbtrlpSll2sNeeYVrGMMt1KSfulsxdX1rpJOyq97Hb5YPMc71K+kEyilGBoi5lWpLKO7LIlVW53TS3JW\/79wrwbA51yZM9bSk3TrbrqJbPmaiqxiwtvJ0Q1K1ZUc0Sl8odjmXkTkehmpUO6Rljls+Lfa901yyqmkxcn3e1Z1wsYpEdd7bLvF6bZKLPH856r+Fr+BKULLQzdhCyqG0SrKrKgEpujGAX46dfyrrnlrLO58m5ZVlvnrqae0qQsVyalooN4M58ntbVUq1adJ6KgFjmyb1rK79bU0pQrvVGdvdq8VQpqfdES5GoVfWqpbpA+juxyrnb1j6vdNCK35MpxCozj5IKF1e7qOwqVX4lTmojHN5dwI3U0ANxGVDfCNO+h9Fmd2NLwZ3++z8e\/uCpu0tR6kIySj2D1vWXZJREPEB9Bd+Cf9FHBDZVZeRhed6Hi1CLrQmBwGY3+kuo6t5gVy2+\/Om+u6t+MvRb9Y1K+tadlFtPeIE2ngJCrM2Fzp6fvI6+hm9iOXO78iR1BU4kF+xxeQXlZDVDAz+skq9JCBlpXhsvVPRT4pfIKtm7F73HOZGWK31NKyjeNiZaQ+UwHh+cEo7BfXLyQHi411bV1ZNWzld83Di5DtRSqNLVprA2+5bJ5lW53pTiSppI8WAwiv4XXkARUenysaUxUzy+GtTiXPxRqq6vEMzFf\/QwjIFOZJ\/ypETRPyE5NvDStaEp5tlsuY4KtLIuP60Pz9I9VZRpUV1eTl9KmgTrPh201xmmmswtLQwt0lektN2CAagFrCfSU552uWiF6UZE7mVcReIUX1D2wNCCBu7ws09sUSVuiraZuyWM+X\/BfLVEFXb\/oihntXWuFsTDDZ+5mldapL9x+SzNtvAEmjZpba+3yW2ZXqD7Z2At14KSD0j0guMJzrxZTI4xncInnndGZCwVEZGzOqndypGpWrKhx1y5ThoPZ0orvIsdUS7rVPlgx+7vKGlUvM12\/XgoVklq4sM695NpQGxHKJUJky+AM62qrCWzl4tmXqt\/+lgMXslAJNihm8bA2rmd0I5IuZkyoMyHnYz57dTNfHY+AT+CTUO6\/xL0wVkP3nWJlG+IYLWc4s9rRBD92SbIa5ATjNuUOWpsZPY9OzzCtq1IZs4LGS+jYWnkGXkx5yWE12qNOHyoXvBhQ\/LnolG7LYCDPggyNhCjBWMxqwnDU+mXtRUp9enNkm+43A5KNM8S8j7Q9Md9N269e6K5bUjqFmpqoQXr06Gpvs9tVXxHFhu321MhaI+0CVDq6eguLlS8kD1U9qKKucKrdsrupdvNb9JA3vRHUxHB0S7WbytNpaXdMNiliT9Vl+tpPXDKzOE1XSZ9MteuK6m9Yp1PtQ1exQmGQarfzX3syZNJlqn3oJqgYY0E9FTlDRFYt6qoNW2YEde1mw6SrN+GTkXZgKDfi+U1NzebmPqYYft8xT9eUrCy9s45gBCNVhpdTGuLJCF9DdSFUzPBmVATyhyfQRCELuwstaZJj7nMCBSMboKEHOiAx0tSFYrFqJ9Vh7qYM5SPruFZprLTVGojrhDW9oean9VNjdLy0+TQYSivzWmGHcARVDPLCSIhwzhsEGi5PN62vWr3rBGOpdv5AH+w8\/n\/9WZcH\/kzRUDzCS6uht8pnpn0J0\/cgPcI+IEwl66tH4Mz1xSlt3gvzBVVY3UiWIZgLMRRKsEub3WG6xYhw4CIsFgFU83GPoGLERaxckPUsGu6EsY9gXWHdesQd0woOzXAE4zWSTmkahSSsFAjTSqqdO88QSZYZVk2oi2rLihPwhm0C6hxNlbPn3jtX\/3FNNNseqq2o6+YqXniH\/GW3oVTD\/WESQPFRJ5D7nVtyP9q5cs3GhmcbGjauXvnbnkLxx1+j3hAEji8BDPT48k+M1jubnt2w6zhLS0vgT7\/HcaSnlFZcbz\/0eN36zQ0Nz25Zv3LD0c\/PvZn\/lco46oSmQQAEQAAE4oEAjkLiYRQnaB+gNgiMIYHJBbevqF3y7YJMlzP9ynlLqisrpsk\/KhrDNiF6HAjE+kBnld4yN0\/\/daRxYIQmL5CAK3Pa1RX31y7G9vsCQY60euYNy6ofvGP2tHSnK2v295evuK808MsjI5WJeiBwgQSyrq2Ye1VCHI+6rppbEfLX8RdID9Vw0800AAAQAElEQVTHkMClpRU35iXE1BwNiDgKGQ2Kw5GBsiAAAlEiYLNnTi+cfVNFWUluuF8+jpI2aGbMCMT0QKdlX52XiVO4MRv8qAimQSzM\/eLwvl8cFcUSqBF7WnZeSVnFTbPzstMwEgk08DHc1bTswrwvJoRzd3wxrzA7LYaHAqoFE6CpeSXWHcFMrK+idBRirQDugAAIgAAIgAAIgAAIgAAIgAAIgAAIxAuBidAPHIVMhFGCjiAAAiAAAiAAAiAAAiAAAiAAArFMALpNKAI4CplQwwVlQQAEQAAEQAAEQAAEQAAEQCB2CEATEJiYBHAUMjHHDVqDAAiAAAiAAAiAAAiAAAiMFwG0CwIgMMEJ4Chkgg8g1AcBEAABEAABEAABEACB6BBAKyAAAiAQLwRwFGI+kr7WXQ1\/6DS\/h1wQAIGEIdD5h4ZdrT7q7lj5BG9Lw7q6mrWNPdQGAgiAAAiAQGwSgFYgAAIgAAJxRwBHIeZD2tfV1tbhNb8XmvvWlqo12MmEckEOCEx4At6OtrauPurG8HwCVYgstPx2m2dK2bIflaVHVh6lQAAEQCB6BNASCIAACIAACMQvgWgehfj7Tvv8g4z1+3ynfb5+I1T\/meB8KnbGrxXy+3x92pW\/z+fTLkQRpTBvwndaV9DHZfJGRSklGvRzBaQEpSJjPJNXJDX4m1KUv1FOkMwzXGZAf1LmswE22Mdl6hTmNenFxZISAW25NNF36hFVMerGdF0gyVJJkkNBitL1jvJ4sMrn9\/ACgfgkYDQfMmS9sTDGCwhD4\/0PtRGeww2d7JG\/8UJBromqB\/LlXbOYqktXQOWtzVn4PaU6N3Bu9aRwP\/Of6eg8ybKuyLX3BlyEiYekwty3UF2ulNIo74Let9Bdck28gNKUfNMXU+SInioCravA1UiAiBOQALoMAiAAAiAAAiCQAASieRTStm3VhoZn19Y9un79E2tX19as3dOlED7T0fiLurqfruX5dTWrd3j4h7DHdtav26X8jcrppg319Y\/tVb5C3rP3sdWvtSt1xVvP\/g31Wxoa6lf+9In1a9fW1aza5vmkc9e6upXr169ft7pm5YamE6IcY74jDfW1Nasfo\/y6mnWNzXs31G9v4\/d69m1YtXXHjvoad\/22d3iG8jrR+NjK+o1\/PGWna1M9j+9av6eTnW7e+sT69a95qFQgnGhcW1u3lvJJpTU7Ra9Y2\/b6Da8eenldTd060mF1Te3qncd4d6mW\/8PG9bU1Kyn\/iZ\/WuRtaDm+rf2qf7LOvdefqWiFq3coad6A73iMNpvkkDQEE4pPAiaYN7qq6tevXP7a6pqZuwwHhRjp2rV7V0EInrbLPfc2bV63ff5JfmNuIwd4Hfc3P1tfUrSZrXbuSXFNz41PBfoBLMnmFMee+jsYN7rqV5GpIz4CZCzf4woa62voN+3s8r21tPs06925Y\/+whbumDXU2\/qKtyS09YVfeLpi7RI+7fnt2xc1VN3apt5K14o882rHWvXP\/E+rWra+qebOr6pHmL6v3qyNWcUVS1cndcoN5hkrfRqsDVKPAS7w09BgEQAAEQAAEQAIFEIhDNoxDi6v1g8PofV1dWVlZX31fo37fl5Q8ps69l++ZDzrnLq+lGdW3N4tz3t2w84GX5BbmftXv4\/oD1HfN0T3H53vPwP9lnPs97vryrcqlmUPj4VPrdQkR15byLW7as3dZ30wqSWFm94ras7l2vNfPzhpONG3a0Z95cWVtVWVlVu\/zaE7v+oP8rmI5OW0VlnXvh11TBZ1q2\/HI\/u3bJj8ozGbPQ88qKyvk5LK30PurWLXlqTf7evHu\/v2SJ1GHu5OZdTaIzjHkPN\/lvWsF1qK6tvDmjdevGJtKir6Xhv\/YPzFzC+0B8Fqbt0w5WSO1n23N\/IO\/ULi3q3fXLnR3UwsnGjS9056n5leXOxl9u84i9E91EAIE4JDDo2fbLXb1XCzOpqq29t7B398ZtxxmbXlzo8jQf4VZOve5raem4pLj0UsbC2UjA3nv2bNj5Xua8h2rJWqurl5ee2MVNkgRFEKzMedvTh5w3LudmTnr+ILddmjkX6G335t1X615enp53y32laSxnfmXlvaXpjHm2b9x1plD0rbq2ZknhmV0bt6unqx2d7LuVbvfCAsb\/eTv91\/8bKUueYnH+33atX9cybSn3D9XVS0ttzTv3ijNk8hth3J3OYVZ82bPt16qHTDRXw3HiBQIgAAIgAAIgAAIgkHAEonwU4ppxXYFDQLZfWlxwsc9LRwDM03LMVXhDoUvqYs8quza76+02n62gYFpPZwff23iOd+V9+4acE542uupr85zIyZ0mpOijy4tnfVFc21zFM3LZlLyZ2fybHIw5Cq6b4eo43s5YT0uLN7vstqtdohxzXX1b2eUyKePs0htzFTUoY7Cr8Rc7uqYvvO\/GLDtdWunJb5m\/proc3mNNLSf8jDmK73Mvu4E2O6Lk9LKKbImBdJg365Ku5iM97HiLZ1LxLUpbzH7p3FtUPYXapWWX2kVllnnDjyofuCFrUHTnitK5ar6raHZhSlvLe7IUYhCIRwLvHGlJCTaTopSWw22MZZUWZXa8dZQ8BGO+5iMdmXkFadLkLW1Es\/eeo63e7PLbCqVjsLkK\/7EsO\/IjRStzvqjwBtWE7ZeWlV7e1dIqznIZubvSdMWa9WPUduStlOKKudLdMHvW3IrilLeOUN94oezSudOkfvzKVTC7YDJPMHv2zK+lseyCYnnTljmrJJtOjenYVfiNMnN3xxjTOczCr+cwr5eUE1XgaogOAgiAAAiAAAiAAAiAQJwTkMcPUeuk3aGcAOha7Ok+xbyH\/qte+7d2X4\/LzmhLkzs9u\/O4hw16PO9flntlYcG0zuP08e\/x453ZV+aGKp7qDMhOYcxmp0hpxuGwD\/rpQKK7x8v0xZgj8xK5gZAFU3QiGDvetN83o2JBriLWWk9ZOTTO\/u6yhQV9+35ZV1Vbv35Hs1fdXKVdkqkrnJY2hfnpXIMwpDqcuhuZX1SOToxq2+yuKS67jfH8jl0at\/r6hjbmTKF+6oQgCQLxRKDnr90s2EycDjvr6aKdf9o3CjI7jhyi01XvkZYT2TNL6CQk2Ea4qehtRLN3bknaBcflyMyYwt8jeVma8+lDG3mL8rV2v+LVSKTdxA1Sdk9X92DwLe64unnf6G5qkHOy61xFCjlDm87bOVOYcDW8V0G1HJl6dxd0ixrgwVgFroZTwQsEQAAEQAAEQAAEQCAOCdAierx7lZ6ZQR\/D3lmp\/Vv+wNKldxbTMYDjqrysDo\/nvRbPl\/nZR+60LE9Li8fTnnVlvnI8MUzdMy5JZ6fFN1GUin1dH9FHocqF8W1a2bwvt27bfEg5wrDW01hRu7a5cq9fuKy6tvbHt2V37tzwqvjWOmPeD9vpoEct1dPdw5xOR\/oXMpjPe0rsYeStzo9pf8eTXO3+3kAV8TuIdHrC87PKlmngHlq+9IdL503nVfACAYVAfL2Fmskpr8\/+pSxyF2xK4cwrutqOensON3fnlxYKHxGZjWSkX8x8n3gDqM50dZ0OXIVPWZrzRYV3a7ZZuXzZD5feXcLVtJTGPYxP756Y1+tLzRR9s6wU5gbve+TuTgjiVeBqBApEIAACIAACIAACIAAC8U0gBo5CWF5pETu0c1en\/DqDr7nhZ\/Xb3hYXjhl5X+7Ys7sjU5x9OArysjua9nyQlVcgdjnDH5n0a4qzT+5r2NNJ5wiM+Tv3bd5\/0uR76opgW1rx3YuLT7\/82NYWcQxhrSdV6P\/UpzvFoAzGfE1PVtW\/0EE9sU\/OTE+zy49q+a33G7ce7KF8NujzvLR1vy+3tMjFriwtdrbs\/E2Ll99gvtZtL73dywszln51Yeb7jduOiFMbXmVt\/aZDXhtLp+5o+dSd3Y\/Vb9jPf0Pyk+bGA51CZykg8WL0OF4JCDPZ9VuPMDe\/9\/CWba1ppdfJXw5yFJYUdL+546WjvryvyxxrGwnikz6rJLvr9YbGD4Tt+Tv3b9nflRpUItyFlTnbDu14TfVqRxp+unrbUe1\/tDEXRx7G2fLay\/Inkfze5i2\/aUm79nqlJ+ZVwuVy\/xC5uxOS4GoEBkQgAAIgAAIgAAIgAALxTyAWjkJY1k1Lb8\/ybKytqqmtqVq9Z2Dm4jtmOgR7R940V9cJV+50cenIy03v6pqcmyeuRIFhRpOL71hUav\/jhprqqqqqum1\/vXreTP0fyIRIs2WW3XvbZe9v++nWZtp6Weo5bWah4+hGkvl0i06Eq\/QfK7I6NtdU19RU173snVFxQ5a8m3btLXnvbawjFarrG95xlf3P2\/nZji1r3uKKrI93rK6hG1Vr30i7+YYcWZ6llS5eVDzQuLqqhv7VN7yfs\/DeMv758uTiu++dpeRX12w8llGxeF6WjXX9cf\/+\/Uf4mYhSH28gEC8EyEx+ePtlHQ31ZG5VNWt\/P1C86L6yS9TeTS8u7O\/oYIXF2m8JWdiIWkF5d8y8Y3GJ\/dAvhe3Vbesqmqf89IZyP9ybpTmTnsc2cvMnr9ZIet5RPDmcHLonPEx7wyruAWrW7iFPeN8N3NDp1kjC5GG6O2oDroYgIIAACIAACIAACIAACCQAgWgehRQsdC8PbFpYetmDbuX\/arG58m5ZVlvnrl5R7a6tXFyu\/qYoY65ZS93upaXK3+27Su93u+8vDTq9EIOUXr7cfVeBSIroawvdD4rDAnHFLilb7l4obzuyy5ZUud01tbXu2uXfL8y7Ua2oK0OVAgInFyysdlffUch\/TtVKT0duxbJaN\/3T60BSLi68\/cFad82KFTXu2mUVudpGyJZRfFdlbV1tNeVXLp6t\/u4pk+VrazmKe8uySwK9ILUXV9a6q1ZUk946UfZLZ\/P86mqRf3vhxdQqy\/z2cnd1RTZP4gUCcUfAlcfNrY7shHuLsoC3oJ5mzat0ux+apxw6UgZjpjai9wmilCO7fEl1nbu2hgxs+e1X581VvVPBXe7l5fw8IuATRIVAZGXOUs9aMk69ntZukCSqHkaoEfCEhqY1lagGBcNdpvN+5DeWmLm78FW4S4GrIbIIIAACIAACIAACIAACMUdg1BSyjZqk0RBkT7X+c5XRkB+QkWq\/kJaGp6fd4TBtzGZ3pAY0CqTsdrvVsKQ6zG+FqRKQixQIxBEBG0364XSHiluZlU7M8ExbV5HZLMx5uHoKmSNXQ1Q3Rql2Uw9kLKa\/hqvR00AaBEAABEAABEAABMaZAJoffQIRbA5Gv1FIBAEQAAEQAAEQAAEQAAEQAAEQAIEwBHALBMaQAI5CxhCuqeisayvmXhX6Jz6mZZEJAiAQ0wRgzjE9PFAOBCwIfNbb333q04+6\/\/bhydMIIAACY0fgr598+umZIX4z3MJMYz37U+FGxgwdXBMIgIBC4K+f+Hxnzo6RR8BRyBiBtRSbll2Y98UR\/+6rpVjcAAEQiD4BmHP0maNFELhAAnQO8lnfwIB\/8Pz58xcoCtVB5BWrqgAAEABJREFUAATCE\/CfGzzTNxDxaUh4YTF0l85BevsGBs4NxpBOUAUE4pSA\/9x5ciNjdBqCo5A4nTXoFgiAAAiAAAiAQAiBz3oH+A4G5yAhZJAxTgTiuVk6cOz3n\/usN96+GEI9OksHIYM4To3n2Yu+xQgBciMD5Eb6BsZCHxyFjAVVyAQBEAABEAABEIhFArQxG8Q5yPiPDDRIFAK0jSGji7Pe0saM+hVnnUJ3QCBmCdBDmz7DGAv1cBQyFlQhEwRAAARAAARAIBYJjOsGJhaBQCcQAIHhEqCN2XCroDwIgEAMEsBRSAwOClQCARAAARAAgbghgI6AAAiAQKIQSEpiSfgXWwQs514SBisp1v5ZDtYY3cBRyBiBhVgQAAEQAIFEJoC+gwAIgAAIJBaBFHvy5yZPmvp558VTJiOMO4GpUybTWFzkTLUnm2x4KXOyI5UKULFxVxUKEAEaCzIfMqJoeg2TmRHN5tEWCIAACIBAHBFAV0BgohJIttkck1I+\/znH37mcCRumfM4x2UELUfPFIX166Jhk\/\/xFk\/7OlXCUiIxzUkqyLcl0fttsSXSXyiQgmb8T9kJ95xtOu\/nMMYUWf5mpKclOR8okMqBkm82WhDDuBJJtScnJNkdqimNSSkrw5KRzEMckOwUqQMXGXVUoQARoLCal2MmIUlPsUfMPCe2zokYZDYEACMQ1AXQOBEBgYhOgRdik1GTazdI6LDUlOWHDpFTaG6RQTPsEw4gGEKXaaZ2aaIiICS3QKU5ONq6ck21JlE+TRzAhOIk4f4iAgyYPzYzgDadhFsX3JZ8AZDkW52Xx3fdY7h33XSnJKfZkvZJ0SbM12WY0Z30ZpKNPwGZLSrUnT0oNGqwxVQMzYEzxQjgIxDEBdA0EQAAE4oQALYtpL5dityWZf+ofJ92MpBu0leMoUowr0WQb\/3A1xZ6clJSgjOzJNk4m2bhyttuT6RTAzidPgpKR84oOiSalJNNhorxMtNhmS7ITAltCz4GYHXQ+MrYgy6WcZFtQTswqn2iK2bgp2ZJtURqdKDWTaKOI\/sYvAfQMBEAABEAg3gjQx7m0Mo63Xo20P\/ZkGwVDbZstKcWe6ItGwhI6T5JttAdOdDJythCchJ0k1HeyEckBcQwSMJxR0WWiHurG4OAYVUpKSrIl0xAZ88fiGr57LKjGn0z0CARAAARAAATilkCyzWZLitLCa0JATGJJBj3pOimJIkN2Yl0mJZkSSKJ\/iQUiXG9NEYWrgHsgAAIgMF4EcBQShjxugQAIgAAIgAAIgAAIgAAIgAAIgAAIxBuB0KOQeOsh+gMCIAACIAACIAACIAACIAACIAACIBBKIGFzcBSSsEOPjoMACIAACIAACIAACIAACIBAIhJAn0EARyGYAyAAAiAAAiAAAiAAAiAAAiAQ\/wTQQxAAAY0AjkI0FEiAAAiAAAiAAAiAAAiAAAjEGwH0BwRAAARCCeAoJJQJckAABEAABEAABEAABEBgYhOA9iAAAiAAAmEI4CgkDBzcAgEQAAEQAAEQAAEQmEgEoCsIgAAIgAAIREIARyGRUEIZEAABEAABEAABEIhdAtAMBEAABEAABEBgWASiehTyaW9\/96lPPzx5GgEEQGBMCfz1E5\/vzNlh+YKJUvgz4UY+6v7bmAKEcBAAgb9+8umnZ\/pj3DNAPRAAARAAARAAARAYGYHoHYXQBuZMX\/\/AucGRKYpaIAACkRPwnzt\/pm8g\/k5DyI181jcw4B88f\/585DRQEgTijEB0uuM\/N0huBKch0aGNVkAABEAABEAABKJMIHpHIZ\/2nqUNzOAgNjBRHmI0l4gE6KSAzO2z3oE46\/xnvf0DdJ6Kc5A4G9fIuoNSUSZAbqTff+7TXnwxJMrg0RwIgAAIgAAIgEA0CETvKKR\/YHAQ5yDRGFO0AQKcAG1jBvzneCqOXv1+8iKJdZwaR6OHrkw8AnHpRibeMEBjEAABEAABEACBMSAQvaOQMVAeIkEABOKTgFWvaGNmdQv5IAACIAACIAACIAACIAACIBAhgZg4CklKSrIhxBIBGhGrCZSUxDBYY0RgZGKTkpIY\/oEACIAACIAACIAACIAACIAACERMYPyPQlJTkl2TU9OmOKdOmYwQCwRoLC5yptqTTeYGZV7kGOXBioUuT1wdaLDIfMiIIjZ5FAQBEAABEAABEAABEAABEACBRCdgst2NJhLawjkmpaTyfbfNZktKnBDLPU222RypdueklBR7sn4y0DmIY5LdMSmFCtgwWLFBINlmI\/OhwZqUatcPVqKlk5NtBGHK5xx\/53ImcHBYHWLSfEhKSnJMsn8+QRE5Jju44yIOocFmS3I6UhJ78vCZk2If5\/VA6NAgBwRAAARAAARAAATGjkBUlz6h3UhNsfNjkCR8wz+UzXjm0N4gNSXZsDJOsSfTeNGt8dQMbYcQsCUlpaTQ0ASdW4WUiueMZFsSnQTRbjaV\/IlAQbM3IYOdDjEp0KmlYbzJbDmiSSl0kpmgZKjv9LBJNj7yktWT34TEwv2G6LidjskcqSnk5A0zB5cgAAIgAAIgAAIgMHICsV3TuC6MprY2WxIt2SmOZqNoK0IC9DG7zRY0PSgn2RaUE6EoFBtrAnQaQqaUbEvQ0aH9G+3wiUBSwp+pkpGmptpTU4znYsliw0+gkpISlJE92eZITU5JNtqI3W6jQyK6m5SUoGSkd6IZkprKT0bkJWIQAAEQAAEQAIGRE0DNCULAuC6Mptq0arfZEnr1GU3aI2jLMDZ0mdibhREgjF6VpKQkWzINUfRajJ2WUlKSk0O2uLGjXpQ1sSfbQmnYbEkpCf\/nD4SFgmE4km38RN6QmZiXyTYbJkliDj16DQIgAAKjQwBSQGCiERjPo5CJxgr6ggAIxCIB2sLZkhL0GMh0PJJYkiGfrpOSKDJkJ9ZlUpIpgST6l1ggwvXWFFG4CrgHAiAAAolOAP0HARCYsARwFDJhhw6KgwAIgAAIgAAIgAAIgED0CaBFEAABEJj4BHAUMvHHED0AARAAARAAARAAARAYawKQDwIgAAIgEEcEcBQSR4OJroAACIAACIAACIDA6BKANBAAARAAARCIRwI4ConHUUWfQAAEQAAEQAAELoQA6oIACIAACIAACMQ1ARyFxPXwonMgAAIgAAIgEDkBlAQBEAABEAABEACBxCCAo5DEGGf0EgRAAARAwIoA8kEABEAABEAABEAABBKMAI5CEmzA0V0QAAEQkAQQgwAIgAAIgAAIgAAIgECiEsBRSKKOPPoNAolJAL0GARAAARAAARAAARAAARBIeAI4Ckn4KQAAiUAAfQQBEAABEAABEAABEAABEAABEFAJ4ChEJYH3+COAHoEACIAACIAACIAACIAACIAACIBACAEchYQgmegZ0B8EQAAEQAAEQAAEQAAEQAAEQAAEQMCaQLwchVj3EHdAAARAAARAAARAAARAAARAAARAAATihcAo9ANHIaMAESJAAARAAARAAARAAARAAARAAARAYCwJQPZoEsBRyGjShCwQAAEQAAEQAAEQAAEQAAEQAIHRIwBJIDAmBHAUMiZYIRQEQAAEQAAEQAAEQAAEQAAERkoA9UAABMaWAI5CxpYvpIMACIAACIAACIAACIAACERGAKVAAARAIEoEcBQSJdBoBgRAAARAAARAAARAAATMCCAPBEAABEAg2gRwFBJt4mgPBEAABEAABEAABECAMTAAARAAARAAgXEjgKOQcUOPhkEABEAABEAABBKPAHoMAiAAAiAAAiAw\/gRwFDL+YwANQAAEQAAEQCDeCaB\/IAACIAACIAACIBBDBHAUEkODAVVAAARAAATiiwB6AwIgAAIgAAIgAAIgEIsEcBQSi6MCnUAABEBgIhOA7iAAAiAAAiAAAiAAAiAQ0wRwFBLTwwPlQAAEJg4BaAoCIAACIAACIAACIAACIDAxCOAoZGKME7QEgVglAL1AAARAAARAAARAAARAAARAYIIRwFHIBBswqBsbBKAFCIAACIAACIAACIAACIAACIDARCWAo5CJOnLjoTfaBAEQAAEQAAEQAAEQAAEQAAEQAIEJTwBHIUMOIQqAAAiAAAiAAAiAAAiAAAiAAAiAAAjEDwGro5D46SF6AgIgAAIgAAIgAAIgAAIgAAIgAAIgYEUgAfNxFJKAg44ugwAIgAAIgAAIgAAIgAAIgECiE0D\/E5kAjkISefTRdxAAARAAARAAARAAARAAgcQigN6CAAgQARyFEAQEEAABEAABEAABEAABEACBeCaAvoEACICAngCOQvQ0kAYBEAABEAABEAABEACB+CGAnoAACIAACJgSwFGIKRZkggAIgAAIgAAIgAAITFQC0BsEQAAEQAAEwhPAUUh4PrgLAiAAAiAAAiAAAhODALQEARAAARAAARCIkACOQiIEhWIgAAIgAAIgAAKxSODCdRocHDx\/\/vyFy4kjCUYadA1EFuNLbCzuJGI2aCTiqKPPIDBBCeAoZIIOHNQGARAAARBIaALo\/CgS6Pef858bHEWBE1rUuXODoTToHCQ0c0J3cwTKE4Fzg8Z5QsdolD8CafFXheAARfwNK3oEAnFMAEchcTy46BoIgAAIxBsB9AcExoLAwMC5\/oFzdASAr4acGzxPKAb8xg0\/wenr9\/vpdqIyOjc4eJYIhJAZOMfzic9YzMwJJHNw8DzZ0dn+cxNIZ6gKAiCQ4ARwFJLgEwDdBwEQmAAEoCIIgMCYEjg3eJ72+b1n+Vaf9rQJG\/znzp3tH+jtHxjwGze0hOjsWX\/vWbrFvzNy7txgQgW\/\/1zfWT9NEjoMMkxF4tB3lqD5B\/znziUYFq2\/\/nP8PIgsiCAY+OASBEAABGKWAI5CYnZooBgIJDoB9B8EQAAEokaANnVn+vq9fzvzyenEDadO9356pt8f8sUHOQqD58\/39g38\/3y9pxIP0am\/9X7W20+TRKIwxHROdKaXJk9vwk4emhK+M2dxDmKYGLgEARCIcQI4ConxAYJ6CUcAHQYBEAABEAABEAABEAABEAABEBhTAjgKGVO8EB4pAZQDARAAARAAARAAARAAARAAARAAgegQwFFIdDibt4JcEAABEAABEAABEAABEAABEAABEACBKBMYh6OQKPcQzYEACIAACIAACIAACIAACIAACIAACIwDgVhtEkchsToy0AsEQAAEQAAEQAAEQAAEQAAEQGAiEoDOMU8ARyExP0RQEARAAARAAARAAARAAARAAARinwA0BIGJQwBHIRNnrKApCIAACIAACIDA2BBITrY5HSlTXM60zydwcDkvcqbak80Xh7akJOeklCmfcyQgor9zOSc7UpJt5mSSbUl09+9ciUhGmQwu5+ecqSn25LGxzokgFTqCAAhMQALmPn0CdgQqgwAIgAAIgAAIgMBICNBW1pFqp30+HQPQdi5xQ0oycXBMstvtxvWhzZY0iRA5UlJTkhOQD\/XaMSnFMclOR2aGGUY5RMYxKdPelFwAABAASURBVCXFbk84MnZ1MqQkT5pkd0ziBAx8cAkCIAACMUvA+KiLWUWhGAiAAAiAAAiAAAiMBYGUlOTUlGQ7nYgkjYX4iSSTNvapKfbUkI\/3k2022ugKRAnKiPo+KcWekmxjwePJ81PtFCclKBgFB80QMiIKyjXeQAAEQCDmCeAoJOaHCAqCAAiAAAiAAAiMJYEUe3JyMlZECmJ7si2Uhs2WRPlKiUR9S7abkEkGGXU+JNtsKSHfJ1Jv4h0EQAAEYo4AHvwxNyRQCARAAARAAARAIJoEaAtnM\/1MP5pKxFJbSSzJoA5dJyVRZMhOrEuL\/ifRv8QCEa63FpDCVcE9EAABEBgfAjgKGR\/uaBUEQAAEQAAEYpQA1AIBEAABEAABEACBeCeAo5B4H2H0DwRAAARAIBICKAMCIAACIAACIAACIJAwBHAUkjBDjY6CAAiAQCgB5IAACIAACIAACIAACIBA4hHAUUjijTl6DAIgAAIgAAIgAAIgAAIgAAIgAAIJTABHIQk8+Oh6ohGI0\/6eOzc4OHg+Tjs37G6dp3\/MSIOuefawhcVVBQsClE144qqnI+7M+ZCZM2JRqAgCIAACIAACIAACMU4ARyExPkBQ74IJQEC8Ezg74PefG4z3XkbaP0Lh9xtpDA4O9g+ci1REnJYb8A8SHEPnKIfyDZmJeclRJPwkScyhR69BAARAAARAIDEJ4CgkTscd3QKBhCFAW7iz\/X7a6p9P7E\/3z58\/P+A\/J1EYBv\/cufN9ZzmiwYRkJMn09fuJj4EMTZ6+swP9A+eojOFWQl0SB5o5Z3EUklCjjs6CAAiAAAiAQGITiK+jkMQeS\/QeBBKTwODg+bMD\/t6zA2fODvT2JXCg7p8dONt\/7txgyLdCzp\/v958709efoHzODpzpo\/MOP00Vg41QDpGhycNDok4egkMT4yyBwLerDPMDlyAAAiAAAiAAAjFN4IKUw1HIBeFDZRAAgVggQBta2sh9duasL4HDp2f6+87Sp\/vGcxA5QOfpNGTg3Ge9\/QmIiMjQ9KBJIlEYYsqnu1QmAcnILn965iydBNHUMZDBJQiAAAiAAAiAQEwSgFKjQwBHIaPDEVJAAARAAARAAARAAARAAARAAATGhgCkgsAoE8BRyCgDhTgQAAEQAAEQAAEQAAEQAAEQGA0CkAECIDBWBHAUMlZkIRcEQAAEQAAEQAAEQAAEQGD4BFADBEAABMacAI5CxhwxGgABEAABEAABEAABEACBoQjgPgiAAAiAQPQI4CgkeqzREgiAAAiAAAiAAAiAQDABXIEACIAACIDAOBDAUcg4QEeTIAACo0sgKSkp2WZLsScneEhOthEKK7Z0M2H5CDLmYJKSGN1NWDKy43ayHwLB8C+aBNAWCIAACIAACIDAeBLAUch40kfbIAACo0KANnKTnSlTXI60zzsTNvydy\/E5Z2qK3ZZkxpS2uk5H6pTPTUpAPkRmsiPFnpxsBoYRGbpLZRKQjOwy9f2iyakpKclROQwxHQRkggAIgAAIgAAIgEC0CeAoJNrE0R4IgMDoErAn25yOFEdqii2xd3JJSUmpKXbnpJSUFOOeP1kgck6y22yJ6POJDE0PJ5GxG8nQAYmcPFRmdKdlsLSYvqK+p9r5zElNsce0olAOBEAABEAABEAABEaPQCIui0ePHiSBAAiMP4HU1OSUZFuS6Xchxl+7qGpAEFLsyal244af8ExKoc\/8o8woqn0P3xiRSU1JTrEbH3n2ZJsgE752\/N8lPnY7RxH\/XUUPQQAEQAAEQAAEQEAQMK4LRSYiEAABEJgwBFKSk2222NnkjzM3QkHBoERSUhJBMmQm2iVhIQ6GXiclMZsNz0FG\/2xJSTYb7IhIIIAACIAACIAACCQEASwBE2KY0UkQGGMC4yk+SfwbTw1irm3jhtZ4HXMKj6NCYKOHDxp6GkiDAAiAAAiAAAjEMwEchcTz6KJvY0wA4kEABEAABEAABEAABBKdwOC5wcHB84lOIYb7bxgbujxPrxhWOJFVO3\/+fNSsCUchiTzTRtZ31AIBEAABEAABEAABEAABEFAInBs8f+7c4CBOQxQesfXGR2ZwUK8T5VDQ5yAdIwQGz5Mp4SgkRkYjoAZSIAACIAACIAACIAACIAACIGBCoH\/g3ID\/3Hl82cCEzXhmDZ4\/L4Ym6CjE7z83MHCObo2nZmg7hACZz4B\/8OyAnxIhN8ckI\/y3QsakSQgFARAAARAAARAAARAAARAAgbghQPu33rMD\/QPnoraLixt0Y9cRGouz\/X4aFzql0rcy4B+kzL6zA1RAn480Y2y8INBYkPn09vXTkEVNBxyFRA01GgIBEAABEAABEAABEAABEIhPArTf9p05e+pvvZ+cPoMQCwRoLD7r7T93LugrIXLynRscPNM3QAWknojHnQCNBZkPGZEcoOjEOAqJDme0AgIgAAIgAAIgAAIgAAIgELcEzp9ng4PnaeM9UUIi6EkjQuMSOucok24lAoEJ1EcaERqX0MEauxwchYwdW0gGARAAARAAARAAARAAARCIIQJQBQRAAAQkARyFSA6IQQAEQAAEQAAEQAAEQCA+CaBXIAACIAACBgI4CjEAwSUIgAAIgAAIgAAIgEA8EEAfQAAEQAAEQMCKAI5CrMggHwRAAARAAARAAAQmHgFoDAIgAAIgAAIgMCQBHIUMiQgFQAAEQAAEQAAEYp0A9AMBEACB8SWQnGyb7Ej5O5dz6pTJCLFAIO3zzoucqfZkkw2vzZbkmITBiqGJSoP1ucmpKfbkaFqxycyIZvNoCwRAAARAAARAYMQEUBEEQAAEQCAWCNA5iCPVTrtr2svR3hshFgjQWPBBSbWTMvpJQucgk1LtdG6VYk+mWwixQIDGwpGa4pyUkpoSvdMQHIXo7QJpEAABEACBCUAAKoIACIAACIBATBGg\/Rvtru3JtqSkmNIr0ZWhI6rUVHtK8HcNaJhSxSEIBium5gcdUZEdpabYo6YVjkKihhoNgQAIgMAFEUBlEAABEAABEACB2CRAm206BolN3RJcKzr4oAMRPYRkm82Qo7+L9DgSsNmSUuw2iqOjA45CosMZrYAACIyQAKqBAAiAAAiAAAiAQIwTsCXxfzGuZMKqZ\/imTlISo5CwNGK840lJSVE7qMJRSIxPBqiXoATQbRAAARAAARAAARAAARAAARAAgTEigKOQMQILsSMhgDogAAIgAAIgAAIgAAIgAAIgAAIgMNYEcBQy1oSHlo8SIAACIAACIAACIAACIAACIAACIAACUSMwbkchUeshGgIBEAABEAABEAABEAABEAABEAABEBg3ArHX8LgehZw\/zyjEHhRoBAITj8B5xihMPL2hMQiAAAiAAAiAAAiAAAjEKQF0K4YJjOdRyIB\/cBBHIbE6Oc7Tv+C9NQ0WhVjVN9H1GmTn\/ecGE50C+g8CIAACIAACIAACIDDuBKAACEwEAuN5FEJ8+gfOYf9GHGIw0Lj4\/UFb69CcGFQ7MVU6d25wYOAcP7xKzP6j1yAAAiAAAiAAAiAw7gSgAAiAwIQiMM5HIWcHzp3t99Mee0JBi3NlaUc94D\/Xd9ZPsb6rdHm2fwBbbj2TWEiT+fT1+8mOYkEZ6AACIAACIAACIJBYBNBbEAABEJiYBMb5KIQ+zaYtXG\/fwJm+AYoRYoLAWT4W\/XTyMRj04xODg+fPDpw7Q3cpYLxig4A0HDIiOhCZmC4IWoMACIAACIDABCQAlUEABEAABCY4gXE+CiF6tIXrPTvw6ZmzPoTYIPDpmf6+fhqWoHMQGikK\/DSk308FMFgxQoAMh8yHRotGBwEEQAAEQAAExpYApIMACIAACIBAvBAY\/6OQeCGJfoAACIAACIAACMQjAfQJBEAABEAABEAg7gjgKCTuhhQdAgEQAAEQAIELJwAJIAACIAACIAACIBC\/BHAUEr9ji56BAAiAAAgMlwDKgwAIgAAIgAAIgAAIJAABHIUkwCCjiyAAAiAQngDuggAIgAAIgAAIgAAIgEAiERj\/oxBbUlKKPdkxKcWJEDMEUlOSbbakUENISkqyJ9swWDE1V2mwks0GK3T4kGMkgGsQAAEQAAEQAAEQAAEQAIGEJDDORyG0tU5JSXY6Uj43OdV10SSEWCBAY0EjQudTtqSg0xC6onMQukUFYkFP6EAEaCwucqampthNj67MfRpyQQAEQAAEQAAEQAAEQAAEQCCxCYzzUQjt4OgDdkeq3bDrTuxBGefeJyUlTUqx07ikpCTrVUm22RyTeL4tKeiIRF8mdtNxqllSUlKKPZnOpyal2uO0i+gWCIAACIAACIAACIAACIAACIwygXE+CqEttz15nHUYZaIxJe4ClEmx21KCh8Zut2GwLoDoGFalcSFTomORMWwDokHg\/8\/e+8BHVZ17vyvDEBPslDd4E9u0Rt9gCTWxocfwEmroQY9QaQUb9HgqWj1eqlj19fJ6qCfeNG\/eNM1LipRy+YiW2hwLSrS0QNW2WMIBTsGCJVaiSUuocCXWWJIrOXSExGQS7m\/ttWfPnj17z59kksxMfnzWrHnW2ms961nftZ61114zGUiABEiABEiABEiABEiABFKFwDgfQ7gmpblc\/IpBIs4mPFcjmC1zpaUhmHMoJw6BtDQxaRJdScT\/HzWSAAmQAAmQAAmQAAmQAAmkHIFxPgpJE2kphzSlO8ThStThTdP+xc06KiIBEiCBiURgcGho6MKFidTjCH29IKw0kL4w4REBgh04gHG4Ylc61fOIItVHmP0jgRQiMM5HISlEkl1JfgLsAQmQAAmQwIQkMOAbHBwcmpBdt+m0b3AolAbOipBvU3oiZQ36bMgMDl0gGTULBoeGBnz0IwWDMQmQQBIQ4FFIEgzS6JpI7SRAAiRAAiQwsQkMDAz2DwzigXbCf+9B4BCkf8DX7xu0zAg85fZ95NMQTdCP\/dH3jwZ8AyFHZjK\/X5GxMJtYScyQfs2PJla32VsSIIFkJjBRj0KSecxoOwmQAAmQAAmQQBwJDA5d6Ov39X400O8bHJjIYWAQHOSRR8hn+0NDFz4Cor6B\/oGJiAi97vtoAGRwVGSZeMgBGVwd8PkGJuzkGRj86CMf+AyEHKJZcDFJAiRAAuNEwKZZHoXYQGEWCZAACZAACZDAhCKAB9revoGz3t6ev03g4O0914vjIPu\/cRi6cAGnRWc\/7JuAiP7T23u+b2BwyJ7M4NAFXP1P70Qko08Gb++Hvf08B5lQayY7myQEaGY4AjwKCUeH10iABEiABEiABEiABEiABEiABJKHAC0lgagI8CgkKkwsRAIkQAIkQAIkQAIkQAIkQAKJSoB2kQAJxEaARyGx8WJpEiABEiABEiABEiABEiCBxCBAK0iABEhgmAR4FDJMcKxGAiRAAiRAAiRAAiRAAuNBgG2SAAmQAAmMlACPQkZKkPVJgARIgARIgARIgARGnwBbIAESIAESIIG4EeBRSNxQUhEJkAAJkAAJkAAFnUJ3AAAQAElEQVQJxJsA9ZEACZAACZAACcSfAI9C4s+UGkmABEiABEiABEZGYKxrT5rkmpKRnvXxKZdMnbhh2tTMj01Jd7u5ORzr6cf2SIAESIAExp4A73Zjz5wtkgAJkAAJkIAtAWaOD4FJrrSMdHfmRW73JBfORCZscE+adFH65Mz0yZPdk8ZnJNgqCZAACZAACYwVAR6FjBVptkMCJEACJGBPgLkkMM4EJk+elD550iSciKSNsyXj3jwYAMVkfjFk3EeCBpAACZAACYwyAR6FjDJgqicBEiABewLMJQESSBQC6e5J7kncEenDgSMh0tBZ8I0ESIAESCB1CfDGn7pjy56RQCISoE0kQAIkkHAEXC5XWtqE\/0JI0LCQRhAOJkiABEiABFKPAI9CUm9M2aMEJECTSIAESIAESIAESIAESIAESIAEEoUAj0ISZSRS0Q72iQRIgARIgARIgARIgARIgARIgAQSjgCPQuI+JFRIAiRAAiRAAiRAAiRAAiRAAiRAAiSQuATidRSSuD2kZSRAAqlN4IL2L7X7GGPvLljKW9OWyxM6STbm4ScNMw3KJEACJEACJEACjgRS4AKPQlJgENkFEpjQBAYGB4eG+AinzwGgQNAT\/jccFoGRPzVB34EFHCydv3BBDA0NWTInZnLowoUh+tHEHHv2mgRIgARIIGoCLJhKBHgUkkqjyb6QwEQk0N8\/ODCI57iJ2HdLn\/FgP+Ab7PcNWvKB56P+wQu4bLkwYZLoev\/A4IDPeurhGxz6aABkJgwIh46Cj88nUThcZzYJkAAJkMCEJsDOk0BKEuBRSEoOKztFAhOIAJ5me\/sG+voHJvhxCE46+gd8vR8NDAyEHIUMDgFR70e+oQn5DQiQwfSQZEIOiXByBDK4ijITyGeCu4q+9\/vkzOkf8AVfYYoESIAEJjQBdp4ESCC1CfAoJLXHl70jgQlBAKch53sHznr7ev7WO2HDf3r7PuzFw6z9HzkMDuE0pP\/shx9NQD4gc74Phx7WEyLlGyCDyYMyE5CM6jL6fu58P07QLvDvzNScYEwCE5sAe08CJEACE4QAj0ImyECzmySQygQuXLiAB1o87E7wMDg4BBROI42LE5aPRsYeDJ7\/B4eGJiwZ1XEcJmLq2ANiLglMDALsJQmQAAmQwEQjwKOQiTbi7C8JkAAJkAAJkAAJSAJ8kQAJkAAJkMCEJcCjkAk79Ow4CZAACZAACUxEAuwzCZAACZAACZAACfAohHOABEiABEiABFKfAHtIAiRAAiRAAiRAAiRgEOBRiIGCAgmQAAmQQKoRYH9IgARIgARIgARIgARIIJQAj0JCmTCHBEiABJKbAK0nARIgARIgARIgARIgARIIQ4BHIWHg8BIJkEByEHC50i5Kd1885SLPBA4fm5KecZF7kourenJMWlpJAiRAAiRAAiRAAiQwjgS4aR5H+GyaBOJAgCpcOAeZ7M68aPKUiyZnZkzggO5fNPmi9EmTXFzY6RYkQAIkQAIkQAIkQAIkEI4Ad8zh6PBawhKgYSRgEHBPcl2U7k6fPCktzcibiEJaWtpk9ySFYiL2n30mARIgARIgARIgARIggagJ8CgkalQJUJAmkAAJhBK4aLLbPYlLmQ4GKNxu0tBp8I0ESIAESIAESIAESIAEbAkkwY7Z1m5mkgAJkIAiIP8gxDWxvxCiQGhxGv4J0tBYMCIBEiABEiABEiABEkg6AmNlMI9Cxoo02yEBEiABEiABEiABEiABEiABEiCBUALMGXMCPAoZc+RskARIgARIgARIgARIgARIgARIgARIYPwI8Chk\/NizZRIgARIgARIgARIgARIggYlGgP0lARJIAAI8CkmAQaAJJEACJEACJEACJEACJJDaBNg7EiABEkgkAjwKSaTRoC0kQAIkQAIkQAIkQAKpRIB9IQESIAESSEgCPApJyGGhUSRAAiRAAiRAAiSQvARoOQmQAAmQAAkkNgEehST2+NA6EiABEiABEiCBZCFAO0mABEiABEiABJKEAI9CkmSgaCYJkAAJkAAJJCYBWkUCJEACJEACJEACyUaARyHJNmK0lwRIgARIIBEI0AYSIAESIAESIAESIIGkJcCjkKQdOhpOAiRAAmNPgC2SAAmQAAmQAAmQAAmQQPIT4FFI8o8he0ACJDDaBKifBEiABEiABEiABEiABEgghQjwKCSFBpNdIYH4EqA2EiABEiABEiABEiABEiABEkhFAjwKScVRZZ9GQoB1SYAESIAESIAESIAESIAESIAEUpoAj0JSenij7xxLkgAJkAAJkAAJkAAJkAAJkAAJkMDEIDCxj0ImxhizlyRAAiRAAiRAAiRAAiRAAiRAAiQwsQkE9Z5HIUE4mCABEiABEiABEiABEiABEiABEiCBVCHAftgT4FGIPRfmkgAJkAAJkAAJkAAJkAAJkAAJJCcBWk0CEQjwKCQCIF4mARIgARIgARIgARIgARIggWQgQBtJgASiJcCjkGhJsRwJkAAJkAAJkAAJkAAJkEDiEaBFJEACJBAzAR6FxIyMFUiABEiABEiABEiABEhgvAmwfRIgARIggeET4FHI8NmxJgmQAAmQAAmQAAmQwNgSYGskQAIkQAIkEAcCPAqJA0SqIAESIAESIAESIIHRJEDdJEACJEACJEAC8STAo5B40qQuEiABEiABEiCB+BGgJhIgARIgARIgARIYFQI8ChkVrFRKAiRAAiRAAsMlwHokQAIkQAIkQAIkQAKjS4BHIaPLl9pJgARIgASiI8BSJEACJEACJEACJEACJDBGBHgUMkag2QwJkAAJ2BFgHgmQAAmQAAmQAAmQAAmQwFgT4FHIWBNneyRAAkKQAQmQAAmQAAmQAAmQAAmQAAmMGwEehYwbejY88QiwxyRAAiRAAiRAAiRAAiRAAiRAAuNPgEch4z8GqW4B+0cCJEACJEACJEACJEACJEACJEACCUSARyGjNBhUSwIkQAIkQAIkQAIkQAIkQAIkQAIkkIgE4nsUkog9pE0kQAIkQAIkQAIkQAIkQAIkQAIkQALxJZDU2ngUktTDR+NJgARIgARIgARIgARIgARIgATGjgBbSg0CPApJjXFkL0iABEiABEiABEiABEiABEhgtAhQLwmkGAEehaTYgLI7JEACJEACJEACJEACJEAC8SFALSRAAqlKgEchqTqy7BcJkAAJkAAJkAAJkAAJDIcA65AACZBAyhPgUUjKDzE7SAIkQAIkQAIkEI7A4NDQ0IUL4UpMsGsXxASlMcHGmd0lARIggQlNgEchE3r42XkSIAESIAESIIH+gcHBwaEJy8HScd\/gEIIlk0kSIAESIAESSDECPApJsQFld0iABEiABEiABCITMJcY8A1+1O8b8PGrIQKHIBLFwKCZD2USIIGIBC7IfxFLscD4ELB8zw1JfhFwfEYiilbhSUNDGKIoio64CI9CRoyQCkiABEiABEggSQjQTFsC2HV91D\/Y+9HARwO+\/oHBCRs+6vf1AUK\/DwcitqCYSQIk4EQAXjN0gV8uc8IznvlY4S8EP1ojB2E8bWLbDgRwDjIIRwoeL4eyccjmUUgcIFIFCZAACZBAIhOgbSQQkcDg0BBOAf72Yd9\/ensnbDj7Yd\/5vgE80UXExQIkQAIWAjhCHZDfLBujT7MtrTPpRACP1v2+wYHBoG+6+QYHceKLS061mD8uBC5cEAO+IbjSmA0Nj0LGZaDZKAmQAAmMOgE2QAIkQAIkQAIkMDYEcIjY2zfQ+5E8DhmbFtlKRAJ4ov6o34dxwdO1ufDg4IXefh9OfgfH6tsH5tYp2xLAYPUP+OTXMz8asC0wGpk8ChkNqtRJAiQwbgTYMAmQAAmQAAmQAAmMPQHf4CCeus96+3r+1suQCAT+09t3zuGbbkNDQ3jqPvshBytR5ioG68Pe\/v6BwbH8YhWPQsZ+nWSLJBB\/AtRIAiRAAiQQDYG0tLRoirEMCZAACTgRcFpFLlwQg0NDA75BhsQhMDg4dAEDEzKWyBsauuDjYCUSAafBChm9uGXwKCRuKKlo7AmwRRIgARIgARKIiUC6e5LL6TkmJkUsTAIkEAWBtLQ0OF0UBZOpyGT3JPQrmSymrSSQzATS0sTkyZNGowc8ChkNqqOrk9pJgARIgARIgASGR+DizMnYUbmwsRpefdYiARKImkBamjwHuTgzPeoayVEQPbpo8iSXi18xS47xopVJTQDLCA4fL86YPBq9SJqjkNHoPHWSAAmQAAmQAAlMKAJ4hsGOarLbhd3VhOo4O0sCY0\/APck1JWPyx6ak2lHIxzLTMzPkmerYI2WLJDCBCGhddU9KwzLimXKRlopzxKOQOAOlOhIgARIgARIggUQmgNOQnGkf+3TOxy+7dCoDCZDA6BH4xCUfS71zELW44TQEy8jooaPmiUuAN6ZgAp+4xDNK5yDwZR6FAAIDCZAACZAACZAACZAACZAACZDAeBBgmyQwHgR4FDIe1NkmCZAACZAACZAACZAACZDARCbAvpMACYwrAR6FjCt+Nk4CJEACJEACJEACJEACE4cAe0oCJEACiUGARyGJMQ60ggRIgARIgARIgARIIFUJsF8kQAIkQAIJRoBHIQk2IDSHBEiABEiABEiABFKDAHtBAiRAAiRAAolKgEchiToytIsESIAESIAESCAZCdBmEiABEiABEiCBhCfAo5CEHyIaSAIkQAIkQAKJT4AWkgAJkAAJkAAJkEDyEOBRSPKMFS0lARKwIzA4NDR04YLdlQmad0GQxhgOPZsiARIgARIgARIgARJIQgI8CknCQaPJJEACJgIDA4ODg0OmjAkt+gaHxoLGhGbMzpMACZAACZAACZAACSQ9gXE+Crkg\/yU9xFTtgOWTZZmUr1TtbnL3C540NDRBh2fAN\/jRwCCOAEb9qyEJP0dwCNLf7+sfGEx4S2kgCZAACZAACZAACZAACYwngXE+CsHTy9AFfpw7njPAqW08V+Pp2nwVOYMT9WHbzCEBZYwUhgYDNCq2JbxS9P2jfl9v30D\/gDwF6B8YnKjB19cvA9bVhB80GkgCJEACJEACJEACJEAC40lgnI9C8MQy4BviZ7njOQXs2saI4JN2BPNFPF\/5Bgfx1G3OTFk5eTqGwcLQwJUm8tAMDg71fjRw9sO+\/\/T2TuDQd663H5MheSYvLSUBEiABEiABEiABEiCB8SEwzkcheNjGZ7l9\/QM8Dhmf8be0qiXxRI3P2M\/3DeDpWsvQIzxt9n3kQz4+hNez+DbeBDBY\/T45KB\/1D4y3LWyfBEiABEiABEiABEiABEiABJKDwDgfhQASPsM83ztw1tvX87fe8QlsN5jAf3r7zvX1Y1wwOpYwOCQ\/e\/\/bhxysRJmrcrDO9w8MDF6YoL8TYpmhTJIACZAACZAACZAACZAACZBAGAL6pfE\/CsHH2njAHvANMiQOgcHBIYyLPkdMb3jeHhq6kDh20hIQwKEVRss0SqkspqWlpXL3j3aWaQAAEABJREFU2DcSIAESIAESIAESIAESGBUCVGolMHZHIemTXS4XH2OsA8A0CYwSgbS0tMnuSaOkfLzUpruxinAZGS\/8bHfCEUjJZWTCjSI7TAIkQAITmgA7TwKOBGI+CrH9soCjetOFj2VeNBmPMTwNMTGhSAKjREB7gHFdnDl5ePqH7eZRNjds\/Rdnpk+ePMmVxtOQKEmzGAkMn0BaWlq6e9LHMtOHp2LYbh5lc6OtP0ozWIwESGD0CIy2m4+2\/tEjE4VmFiEBEpAEwrt5tEch4bXIdiK98AwzJSMdTzGRCvI6CZDASAm4J6VNyZjsmXLRCBWN3PHNBoxcG5aRizMm41AVD2lmzZRJgATiTsA9yYVl5GNThnkUYtgzcsc3VEGIrzYoZCABEkh8AlE7flRdia+2qJpkIRIggfEmYOv40R6FGMaP5AkEHy7lTPvYZZdOZSABEhhVAp+4xDOSc5CRuLmxVoQRRqIfpyFYRj6d8\/FRBUjlJEACn7jkYyM5BxmJm4dZPYxLo63faIgCCSQ8gZQ1cLTdfLT1p+zAsGMkkDwEwru541GIpZolmTzdp6UkQALDJ2BxfEsyol5LeUsyYnUWIAESSAECFse3JCN20FLekoxYnQVSlwB7NoEIWBzfkowIwlLekoxYnQVIgARSgIDF8VXS8SgkTIdVzTAFeIkESCB5CYyNg49NK8k7CrScBJKawNg4+Ni0kmADQXNIYKIQGBsHH5tWJsqYsZ8kkGAEIjp4uKMQVVnFql9mWeUwJgESSEkCZmdXsopj7ayqpWJV1yyrHMYkQAIpScDs7EpWcaydTUuTv5RsrmuWY9XG8iRAAklEwOzsSlZxrF1QtVSs6ppllcOYBEggJQmYnV3JKkZnwx2F4DLChQsXjNJIqoBMJTAmARJIJQKhrg33D82MtcvQAD2WWsi05DBJAiRgIpCsYqhrw\/1DM2PtHjRAj6UWMi05TJIACaQAgVDXhvuHZsbaU2iAHkstZFpymCQBEkgBAqGuDfe3ZEY+CgEIcx2osOQgyUACJJAaBJSzKzdXPVI5Sh5JbNaj9JtzRqKZdVOLAHuT9ASUays3V51ROUoeSWzWo\/Sbc0aimXVJgAQSioBybeXmyjCVo+SRxGY9Sr85ZySaWZcESCChCCjXVm6uDFM5SlZxuKMQVRr1jaDqIDk0NKRkxiRAAqlEAK4NB1c9gmAE5KgFAUJMQdUy9EBQ1SGgLSUzFoIMSCB1CMC14eCqPxCMgBy1IECIKahahh4IqjoEtKVkxiRAAqlEAK4NB1c9gmAE5KgFAUJMQdUy9EBQ1SGgLSUzJgESSCUCcG04uOoRBCMgRy0IEMIdheAy6iBGUBWQREASqhEzkAAJpBgB5dpwcwR0TTk+BJWEMIxg1FXakESAnqEhnqgCAwMJpBoBLiOpNqLsDwmMOQEuI2OOnA2SQKoRiGYZCXcUoh5XFBXICJARu1yuwcFByAwkQAKxE0joGnBtODjcHFYiRoCggllWOdHE5lqQEVALMVpBW5AZSIAEUowAXBsODjdHvxAjQFDBLKucaGJzLcgIqIUYraAtyAwkQAIpRgCuDQeHm6NfiBEgqGCWVU40sbkWZATUQoxW0BZkBhIggRQjANeGg8PN0S\/ECBBUMORwRyGqqIpVBRUjB6cs0A6BgQSiI8BSSUAATg3XVoYqZ1exyhl5rLSpGNrQFlqEwEACJJAyBODUcG3VHeXsKlY5I4+VNhVDG9pCixAYSIAEUoYAnBqurbqjnF3FKmfksdKmYmhDW2gRAgMJkEDKEIBTw7VVd5Szq1jlGHGEoxDjC+0QVH3EKgwMDBhaKDgQYDYJJBMBOLXybsSwG7Hh+BCQM7yg6pq1QVYBLQ5PJ2uRAAkkJgE4tfJuxLAQMVYAxJAhIB5eUHWhBwJiKEGsAlpEkoEESCBlCMCplXcjRqcQG44PATnDC6quWRtkFdDi8HSyFgmQQGISgFMr70YMCxFjBUAMGQJiFSIchaCQqmPEEFTAWUt\/fz8KhARmkAAJJB8BuDOcWnm3itEHCEYMYdjBrAeyEdAi2h22WlYkARJIKAJwZzi14eAQYJ45RnLYwawHshHQItodtlpWJAESSCgCcGc4teHgEGCeOUZy2MGsB7IR0CLaHbZaViQBEkgoAnBnOLXh4BBgnjlGUoUIRyGqDooagpJd2j8ct6AZ5DCQAAkkNQE4MtxZc2uXxdlVv8yZKif62KhrCKgLWTWHdtE6chhIgASSmgAcGe6s\/BoObvTFkA3BuBS9YNQ1BNSFrJpDu2gdOQwkQAJJTQCODHdWfg0HN\/piyIZgXIpeMOoaAupCVs2hXbSOHAYSiJ4ASyYgATgy3Fn5NRzcsNCQDQGXIhyFoMSFCxdUBcShoa+vD+2hGAMJkECSEoALw5FDvRs56BFiLAIQRhKgAXqgAXFoQOuwAVcZSIAEkpQAXBiOHOrdyEGPEGMRgDCSAA3QAw2IQwNahw24ykACJJCkBODCcORQ70YOeoQYiwCEkQRogB5oQBwa0DpswFWG8AR4lQQSlgBcGI4c6t3Igc2IsQhAMELkoxDUUaUhWAKOW5DT29vbz7+UUYwYk0CyEYDzwoXhyMqdIZiD6g1ylDDs2NAAwRJUu7ABlgxbPyuSAAmMIwE4L1wYrq3cGYI5KMOQo4Rhx4YGCJag2oUNsGTY+lmRBEhgHAnAeeHCcG3lzhDMQRmGHCUMOzY0QLAE1S5sgCW2+plJAiSQ4ATgvHBhuLZyZwjmoIxHjhJUHPkoBOWM4xNUNoJqA\/GkSZMGBgZwAINjGBRmIAESSAoCcFi4LZwXLgxHhmurGIIKqheG+6vksGNDj1KuYtUiYtgAS2APrBp2E6xIAiQwxgTgsHBbOC9cGI4Mv1YxBBWUPYb7q+SwY0OPUq5i1SJi2ABLYA+sGnYTrEgCJGAmMAYyHBZuC+eFC8OR4dcqhqCCssFwf5UcdmzoUcpVrFpEDBtgCeyBVcNughVJgATGmAAcFm4L54ULw5Hh1yqGoIKyx3B\/lUQc1VGIWQVkVEOMgDaMMDQ0BAtwEoPzGJ\/Ph2RoY6jIQAIkMF4E4JJwTLgnnBSuCodF0nBhCHBqBJinYiUYMpIjCdCDoDQoATEC2jUC7IFVsA0Wwk4kYbOqwpgESCARCMAl4ZhwTzgpXBUOi6ThwhDg1AgwVcVKMGQkRxKgB0FpUAJiBLRrBNgDq2AbLISdSMJmVYUxCURJgMVGlQBcEo4J94STwlXhsEgaLgwBTo0AG1SsBENGciQBehCUBiUgRkC7RoA9sAq2wULYiSRsVlUYkwAJJAIBuCQcE+4JJ4WrwmGRNFwYApwaAaaqWAmGjKQKUR2FqKJGZSUgNgLaUwElcR7z0UcfnT9\/\/ty5cx9q\/7z8RwIkMK4ENEf88Ny5c3BMuCecFK6qfBax4cgQkK9iswA5XsGiHEkjwBIV0BYshJ2wFjYr48eVHxsnARLwKk+ES8Ix4Z5wUriq8lnEhiNDQL6KzQLkeAWLciSNAEtUQFuwEHbCWtisjOcohifAqyQw2gSUJ8Il4ZhwTzgpXFX5LGLDkSEgX8VmAXK8gkU5kkaAJSqgLVgIO2EtbFbGjzYi6icBEghPQHkiXBKOCfeEk8JVlc8iNhwZAvJVbBYgm0MMRyE4fVE1odTSEpJGUN9LQYygMs0CZAYSIIGxIWDrgMhE64iNAI82AjIhK083XF4l4xIbOtGKaguCCkgaQVmIGEFlmgXIDCRAAmNDwNYBkYnWERtBebGKkQlBrRiGy6tkXGJDJ1pRbUFQAUkjKAsRI6hMswBZBcYkQAKjTcDWAZGJdhEbQXmxipEJQa0YhsurZFxiQydaUW1BUAFJIygLESOoTLMAmYEESGBsCNg6IDLROmIjKC9WMTIhqBXDcHmVNOIYjkIMXaoykpag2kNsBMM4CAhGPgUSIIExIACnQ1ANGYJKwnkhILYE5d0qxiUlxDG26ETSEpRViI1gWA4BwcinQAIkMGwC0VeE0yGo8oagknBeCIgtwbxi4JI5GRfZohNJS1BWITaCYTkEBCOfAgmQwBgQgNMhqIYMQSXhvBAQW4J5rcAlczIuskUnkpagrEJsBMNyCAhGPgUSIIExIACnQ1ANGYJKwnkhILYE81qBS+akIcdwFII60GIEI6naDo1VSeQzkAAJjDsB5Y+IYYltjEzDqSEjIDkaAZqNAP1KDmMVCuAqAwmMnAA1jJAAnFEF6IEQGiPTcGrICEiORoBmI0C\/kkPtUTnGVSQZSIAExpeA8kfEMMM2Rqbh1JARkByNAM1GgH4lh7EKBXCVgQRIYNwJwBlVgCUQQmNkGk4NGQFJ2xDbUUioCqhWAZeUHUhCsARkWoKlAJMkQAJxIWBxNCRD1SITAflwWwgqQB6voAxADANgFQQECJaATEuwFGDSlgAzSSBWAhZHQzJUAzIRkA+3haAC5PEKygDEMABWQUCAYAnItARLASZJgATiQsDiaEiGqkUmAvLhthBUgDxeQRmAGAbAKggIECwBmZZgKcAkCZBAXAhYHA3JULXIREA+3BaCCpCjDCM6CjEag2BYAAFJBENQMpLmgEwGEiCBuBMwe5mSjSaQVLISsEYYgspHztgHo2kIsAcGKAExAnIQqwDZElS+bcxMEiCBYROwOBqShipDVgIc1hBUGeSMfTCahgB7YIASECMgB7EKkC1B5TMmARKILwGLoyFp6DdkJcBhDUGVQc7YB6NpCLAHBigBMQJyEKsA2RJUPmMSIIH4ErA4GpKGfkNWAhzWEFQZ5EQThn8UgmbQwIULFyAgQEZsDshRNpkzKZMACYwegTCa4YxwSUsBIweOrGTEYxlgD5pD6xAQICM2B+TAcnMOZRIggfEiAGeES1paN3LgyEpGPJYB9qA5tA4BATJic0AOLDfnUCYBEhgvAnBGuKSldSMHjqxkxGMZYA+aQ+sQECAjNgfkwHJzDmUSIIHxIgBnhEtaWjdy4MhKRhwxDP8oRKmGERCMJlUSORAQDAEyAwmMEgGqjYaA4YwQEFQVCIbzQh6vAGPQtGGJSiIHAoIhQGYgARIYRwKGM0JAUJZAMJwX8ngFGIOmDUtUEjkQEAwBMgMJkMA4EjCcEQKCsgSC4byQxyvAGDRtWKKSyIGAYAiQGUiABMaRgOGMEBCUJRAM54UcZRjpUYhqxmIBMlUOYsgMo0GAOkkgJgJwRhVULWOxQKbKGfcYliDADGUbBCRVgMxAAiQw7gSUPyJWlihXRRJB5Yx7DEsQYIayDQKSKkBmIAESGHcCyh8RK0uUqyKJoHLGPYYlCDBD2QYBSRUgM5AACYw7AeWPiJUlylWRRFA50cfxOQox2oMFKoTmqHwjNgrEJLAwCZBAeAKGi1kEo5aRb+QkmhBqoZFjERLNctpDAqlBwOJoRtLoXWiOcSlBhFALjRyLkCAG0wwSSDECFkczkkY3Q3OMSwkihFpo5FiEBDGYZn\/Y5pwAABAASURBVJBAihHQHS3kzeimccXIiVWI81FI9M0bplMgARKII4HofTAFSsaRG1WRAAkYBFJgcYi+C0avKZAACcSRQPQ+mAIl48iNqkhAJ8C3tLQxWBzG7ShkDPrGJkiABEiABEiABEiABEiABEiABJKAAE0kgbElwKOQseXN1kiABEiABEiABEiABEiABEhAEWBMAiQwTgR4FDJO4NksCZAACZAACZAACZAACUxMAuw1CZAACYw3AR6FjPcIsH0SIAESIAESIAESIIGJQIB9JAESIAESSBgCPApJmKGgISRAAiRAAiRAAiSQegTYIxIgARIgARJIPAI8Ckm8MaFFJEACJEACJEACyU6A9pMACZAACZAACSQwAR6FJPDg0DQSIAESIAESSC4CtJYESIAESIAESIAEkoEAj0KSYZRoIwmQAAmQQCIToG0kQAIkQAIkQAIkQAJJRYBHIUk1XDSWBEiABBKHAC0hARIgARIgARIgARIggeQkwKOQ5Bw3Wk0CJDBeBNguCZAACZAACZAACZAACZBAkhPgUUiSDyDNJ4GxIcBWSIAESIAESIAESIAESIAESCBVCPAoJFVGkv0YDQLUSQIkQAIkQAIkQAIkQAIkQAIkkHIEeBSSckM68g5RAwmQAAmQAAmQAAmQAAmQAAmQAAmkLgEehfjHlu8kQAIkQAIkQAIkQAIkQAIkQAIkQAKpT0CM21HIBf4jARIYBQITYNUKdHEU+FElCZDAhYCPTQCJ400CJDAaBCbA4hHo4mgApE4SGDUCSaM44GOjJsX5KMRAaxhs5FgEowAFEiCBOBKwOJqRNJoIzTEuJYgQaqGRYxESxGCaQQIpRsDiaEbS6GZojnEpQYRQC40ci5AgBtMMEkgxAhZHM5JGN0NzjEsJIoRaaORYhAQxmGaEJcCLyUfA4mhG0uhJaI5xKUohPkchyg40mZaWhhhB5SCGzEACJDDuBOCMKihL0tKkq5pzVP44xoYxaWnSNliichBDZiABEhh3AnBGFZQlaWnSVc05Kn8cY8OYtDRpGyxROYghM5AACYw7ATijCsqStDTpquYclT+OsWFMWpq0DZaoHMSQky3QXhJIQQJwRhVU39LSpKuac1R+NPFIj0LQKppJS7NagHwEXELMQAIkMO4EDGeEgKDsgZCWpjsv5PEKMAZNp6XplqgkciAgGAJkBhIggXEkYDgjBARlCYS0NN15IY9XgDFoOi1Nt0QlkQMBwRAgM5AACYwjAcMZISAoSyCkpenOC3nEYZgKYAxqpqXplqgkciAgGAJkBhIggXEkYDgjBARlCYS0NN15IUcZhn8UglbRRlpaGgQEyIjNATlDQ0PmHMokQALjRWBoaAguaWndyIEjKxnxWAbYg+bQOgQEyIjNATmw3JxDmQRIYLwIwBnhkpbWjRw4spIRj2WAPWgOrUNAgIzYHJADy805lEkgFQkkR5\/gjHBJi61GDhxZyYjHMsAeNIfWISBARmwOyIHl5hzKJEAC40UAzgiXtLRu5MCRlYw4Yhj+UQhUKwuUYNgEQeUbApKQLQGZDCRAAnEnYHE0JI0mDFkJ8FxDUGWQM\/bBaBoC7IEBSkCMgBzEKkC2BJXPmARIIL4ELI6GpKHfkJUAhzUEVQY5Yx+MpiHAHhigBMQIyEGsAmRLUPmMk5YADU9QAhZHQ9Iw1JCVAIc1BFUGOWMfjKYhwB4YoATECMhBrAJkS1D5jEmABOJLwOJoSBr6DVkJcFhDUGWQE00Y0VEIGlCNIYasLIAMwRKQaQmWAkySAAnEhYDF0ZAMVYtMBOTDbSGoAHm8gjIAMQyAVRAQIFgCMi3BUoBJEiCBuBCwOBqSoWqRiYB8uC0EFSCPV1AGIIYBsAoCAgRLQKYlWAokSZJmkkCiE7A4GpKhFiMTAflwWwgqQB6voAxADANgFQQECJaATEuwFGCSBEggLgQsjoZkqFpkIiAfbgtBBchRhtiOQpR2FaMBJaBtCKExMhGQz0ACJDDuBOCMKsASCKExMg2nhoyA5GgEaDYC9Cs51B6VY1xFkoEESGB8CSh\/RAwzbGNkGk4NGQHJ+IWAJmg2AnKVHMYqFMBVBhIggXEnAGdUAZZACI2RaTg1ZAQkRyNAsxGgX8mh9qgc4yqSDCRAAuNLQPkjYphhGyPTcGrICEjahhiOQixakLQEwxoIKgwODhqCIascxiRAAqNNAE6HoFoxBJWE80JAbAnmZQKXzMm4yBadSFqCsgqxEQzLISAY+RRIYGIQGOdewukQlBGGoJJwXgiILcG8VuCSORkX2aITSUtQViE2gmE5BAQjnwIJkMAYEIDTIaiGDEEl4bwQEFuCea3AJXMyLrJFJ5KWoKxCbATDcggIRj4FEiCBMSAAp0NQDRmCSsJ5ISC2BPNagUvmpCHHcBSifoMENaHL0h6SRlDGIUZQmWYBMgMJkMDYELB1QGSidcRGgEcbAZmQ4eYIhstDjlcwdKIV1RYEFZA0grIQMYLKNAuQGVKdAPuXKARsHRCZsA+xEZQXqxiZENSiYbi8SsYlNnSiFdUWBBWQNIKyEDGCyjQLkBlIgATGhoCtAyITrSM2gvJiFSMTgloxDJdXybjEhk60otqCoAKSRlAWIkZQmWYBMgMJkMDYELB1QGSidcRGUF6sYmRCUCuG4fIqacQxHIUYupSA2AhoSQXonTx58kUXXTRlypSLL774Y9o\/D\/+RAAmMKwHNET8Gl5wyZQrcE04KV1U+i9hwZAjIV7FZgByvYFGOpBFgiQpoCxbCTlgLm5Xx48pvzBpnQySQuASUJ8Il4ZhwTzgpXFX5LGLDkSEgX8VmAXK8gkU5kkaAJSqgLVgIO2EtbFbGJy5cWkYCE4OA8kS4JBwT7gknhasqn0VsODIE5KvYLECOV7AoR9IIsEQFtAULYSeshc3K+IkxUOwlCSQuAeWJcEk4JtwTTgpXVT6L2HBkCMhXsVmAbA5RHYVAC4KqpgTECGjPCC6XKyMjIzMzMz093e12I+l0+qL0MCYBEhhjAnBJOCbcE04KV83IyEDScGEIcGoEWKViJRgykiMJ0IOgNCgBMcLQEFrWA+yBVbANFsJOJGGzqsKYBEggEQjAJeGYcE84KVwVDouk7sDaG5waAaaqWAmGjORIAvQgKA1KQIygtaxHsAdWwTZYCDuRhM2qCmMSIIFEIACXhGPCPeGkcFU4LJK6A2tvcGoEmKpiJRgykiMJ0IOgNCgBMYLWsh7BHlgF22Ah7EQSNqsqjEmABBKBAFwSjgn3hJPCVeGwSOoOrL3BqRFgqoqVYMhIqhDVUQgaU6VR3whoBTLiwcFBnMfAgkmTJqlijEmABCIRGP\/rcFi4LZwXLgxHVu6M2AjKRMP9VXLYsaHH0A\/BaBc2wBLYA6uG3QQrkgAJjDEBOCzcFs4LFzbcGa5tBGWP4f4qOezY0GPoh2C0CxtgCeyBVcNughVJgATGmAAcFm4L54ULG+4M1zaCssdwf5UcdmzoMfRDMNqFDbAE9sCqYTfBiiRAAmNMAA4Lt4XzwoUNd4ZrG0HZY7i\/SiKOfBQCFSiHAMESVEs4icF5DAowkEAkAryecATgvHBhuLZyZwjmoMxFjhKGHRsaIFiCahc2wJJh62dFEiCBcSQA54ULw7WVO0MwB2UYcpQw7NjQAMESVLuwAZYMWz8rkgAJjCMBOC9cGK6t3BmCOSjDkKOEYceGBgiWoNqFDbBk2PpZkQRIYBwJwHnhwnBt5c4QzEEZhhwlqDjyUQiOT1QdxKEBBzA4hlG6GDsQYDYJJDQBuDAcOdS7kQO7EWMRgDCSAA3QAw2IQwNahw24ykACJJCkBODCcORQ70YOeoQYiwCEkQRogB5oQBwa0DpswFUGEiCBJCUAF4Yjh3o3ctAjxFgEIIwkQAP0QAPi0IDWYQOuMpAACSQpAbgwHDnUu5GDHiHGIgDBCBGOQlBBFTUEJCHjrAVh8uTJaA85doF5JEACSUMAjgx3hlMjwMENuw3ZEIxL0QtGXUNAXchoCwHtonXkMJAACSQ1ATgy3BlOjQAHN\/piyIZgXIpeMOoaAupCRlsIaBetI4eBBEggqQnAkeHOcGoEOLjRF0M2BONS9IJR1xBQFzLaQkC7aB05DCRAAsMmkAgV4chwZzg1AhzcMMmQDQGXIhyFoIQqbcQQVEAz6enpKMBAAiSQAgTgznBq5d0qRqcgGDGEYQezHshGQItod9hqWZEESCChCMCd4dSGg0OAeeYYyWEHsx7IRkCLaHfYalmRBEggoQjAneHUhoNDgHnmGMlhB7MeyEZAi2h32GpZcYITYPcTjQDcGU5tODgEWGiOkVQhwlGI+g4JakJAjDqIVcBxC5IMJEACKUMATq28GzE6hdhwfAjIGV5Qdc3aIKuAFoenk7VIgAQSkwCcWnk3YliIGCsAYsgQEA8vqLrQAwExlCBWAS0iyUACJJAyBODUyrsRo1OIDceHgJzhBVXXrA2yCmhxeDonci32nQQSmQCcWnk3YtiJGCsAYsgQEKsQ4ShEFUKsaqoYSZfLhbMWCAwkQAIpQwBO7XLpa4JydhXHq4NKm4qhE22hRQgMJEACKUMATg3XVt1Rzq5ilTPyWGlTMbShLbQIgYEESCBlCMCp4dqqO8rZVaxyRh4rbSqGNrSFFiFEE1iGBEggKQjAqeHaylTl7CpWOUasP\/YYabNgrgAZAVcRDw0NQTtkBhIggRQjANeGg8PN0S\/ECBBUMMsqJ5rYXAsyAmohRitoCzIDCZBAihGAa8PB4eboF2IECCqYZZUTTWyuBRkBtRCjFbQFmYEESGBUCYy9crg2HBxujqYRI0BQwSyrnGhicy3ICKiFGK2gLcgMJEACKUYArg0Hh5ujX4gRIKhgyOGOQlDUKKe+SYIkAvKNUxbIDCRAAilDQLk23BwBnVKOD0ElIQwjGHWVNiQRoEe1BYGBBEgglQgo14abI6BfyvEhqCSEYQSjrtKGJAL0qLYgMJBA3AlQ4TgSUK4NN0eAGcrxIagkhGEEo67ShiQC9Ki2IDCQAAmkEgHl2nBzBPRLOT4ElYSAEO4oRFVAaSOgAgKSSjVkBhIggVQiANeGg6seQTACctSCACGmoGoZeiCo6hDQlpIZkwAJpBIBuDYcXPUIghGQoxYECDEFVcvQA0FVh4C2lMw4XgSohwQSgQBcGw6uLIFgBOSoBQFCTEHVMvRAUNUhoC0lMyYBEkglAnBtOLjqEQQjIEctCBDCHYXgsgpGaSShBbE5B0kGEiCB1CCgXFu5ueqRylHySGKzHqXfnDMSzaxLAiSQUASUays3V4apHCWPJDbrUfrNOSPRzLokQAIJRUC5tnJzZZjKUfJIYrMepd+cMxLNrEsCJJBQBJRrKzdXhqkcJas48lEI6phVqGrIVAJjEiCBVCIQ6tpw\/9DMWLsMDdBjqYVMSw6TJEACY0lglNoKdW24f2hmrK1DA\/RYaiHTksMkCZBAChAIdW2jnp+QAAAQAElEQVS4f2hmrD2FBuix1EKmJYdJEiCBFCAQ6tpwf0tmuKMQlAYFFUNAMMtIMpAACaQqAbOzK1nFsfZX1VKxqmuWVQ5jEhhLAmxrzAiYnV3JKo7VAFVLxaquWVY5jEmABFKSgNnZlaziWDuraqlY1TXLKocxCZBAShIwO7uSVYzOhjsKwWXbYFS2vcpMEiCBpCYwNg4+Nq0k9UDE13hqI4GxJDA2Dj42rYwlN7ZFAiRgEBgbBx+bVoxOUSABEhhLAhEd3PEoxFLTkhzLPrAtEiCB8SJgcXxLMqJVlvKWZMTqIy9ADSRAAuNOwOL4lmRE8yzlLcmI1VmABEggBQhYHN+SjNhBS3lLMmJ1FiABEkgBAhbHV0nHoxCnDqtqTleZTwIkMO4ERm7AaLv5aOsfOQFqIAESGCGB0Xbz0dY\/wu6zOgmQwMgJjLabj7b+kROgBhIggRESCO\/m0R6FWH5iZIQ2sToJxJ0AFY4Ggfg6fny1jUZ\/qZMESCDuBOLr+PHVFvfOUiEJkMBoEIiv48dX22j0lzpJgATiTsDW8aM9CjGssdViXKUwxgTYHAmMBoHRdvPR1j8aTKiTBEggJgKj7eajrT+mzrIwCZDAaBAYbTcfbf2jwYQ6SYAEYiIQ3s1jPgqJqe1RKky1JEACJEACJEACJEACJEACJEACJEACqU9gdHqYGEchvq5jvzt06E9dvtHpJLXaE\/B2HPndodYOr\/1V5pIACYw9AS6GY8+cLZLAmBPwnfN6z3p9Q0bDvt6zXq93vDdB3BUYA0KBBEiABBKBAG0YZQKJcBTSe2Tzup+89OKLmzf8vH3Uunu29Vdbn3tu63O\/eotP\/gpyx4tPPLn9pRefe\/KZA2dVDmMSIIHxJTAmi+H4dpGtk8AEJ3DuxItPfPvbtXV1q5\/a2yVZ9J54ccP\/\/HbN6rq6H6oMmTkeL+4KxoM62yQBEgglwBwSGCsCY3kUcvSZipB\/m48KkenxZGr9nTx59Mzp7Wx7q7X1rda2zl6trYSLun6zRqezYe+ZYOvO\/PsG\/dLju7WNU\/Dl0FTb9jrt3\/a20GtGzsemeTTZ5dbeGJFAUhCwLiPfrl33zL8f8wY+XI2xF90HntSc5cnfRuVbtto7f62cd8PeHtvroZnWXmgOvmb3X0dhMfzrbmWc1oQRPYOVN9Ss8c8ZOtP60tN1\/9Nv5\/+s2\/DzI\/y64PiPS+pacOz5b+uzbYP1zjtKnT720jOH\/mL69sfQsRc3H+rst2nt6GbdtG8\/f8xyOWC23ERZLtoluSuwo8I8EhgJAb+Hxu9+Gr01\/jv7mt8Eti5mezp\/s04tHzXbjNWja\/fjKm\/NrzptWjrT9uLTq\/3r4f\/97bonth\/pNq1UNjWYRQKpQGD0zh5ioDPz1kceuOOWf3648pbPxFArZYt2HjrQYe5cx4Hf2y1a5iIW2fc3r\/bvb+EWsWnz7n\/kn2+9895v3TdvqqU+kySQNAR857ram36y7tmjwzzjHOz9UHOWD4dZX4J677R2evmZuXOzZHIkrwm9GJ479sL31jz3uxNe47Gw39vZvH3d6ueOnhsJVNYlAQcCQ8eO\/smnX+tsbv6rLo7mW0f7Sa1Fz+x\/\/u6jCz8hREf7CW3Ce0r++bvfWphj17bvrQNHzAtU75EDb2lK7Arb53FXYM+FuQlAgCaMAoHcBV+7Plvq7f3DT1\/QvnHfe\/jFvR\/IHE\/p176SKwXTq\/fYtro1zx46cda\/sAz5vH85sv0Hdc+1mJceUw2KJJAqBMbjKOQzN1c+VqmHW4tAsuvgs8++tHv7Mz860I2UEPhg8DfPbfie\/Kx2zRPP7W03\/0mLr6tl93NPrJHXvrfhOdOnwa0\/l3l1ddtbvcf2bl6HhKx7ItSH+7p+\/+LTP8D1dU+\/dOSM+cNkX9fR39i029m0AaXr6p4+pP6Q5M8vrtHSdT9v1cz1HmrQ0luPakuIz8nCrt\/qHz8f+Kv32L8\/s+6HBwJnuZoif+Q98uoxvyxE+++OqHYDWUAEDcrUNfjU9MxfTZ9st22v+8UJVfbEL2DYk5Jqd6CAt33vMz+Qma2\/eHr7b1584ckXW8UZvQt1T+5Wpy69rS9o\/OueGN\/v66p+MCaBEAJqGfmXf56rbvZ\/2n3A\/xjj7Tj04tNyBairkz4e+E5BqBe0H3jy6d9qxxjizKtPwVv8X6Ry9OLAOuPrOvLzDWvkItDRKb3GPesLs9XX28KuYMEdUb3Q18NvXp8jTIuh99AzsAjhucBTUPt2tfhs+He1eDjaGdyMTE0rvVdfdWVzX5MrL7J99osertj1FNnCES8u4tpLBvoXgz5QCreqoyZC76HGnxzV1jr3JUULb73lliXXF1yifWftXOsLjYf0pXzIeekTIrDGdmqjA3g\/ePrFZjXCUfAMqxwmnmnbbXv3wSWGpCTw1qGj2jGEZvyZI783fQoRWC46u36\/XduQrLPsGcLMB7iC3SrUdeCHzxxRO5re1u3fe\/JA+4EnN\/sz2rZ\/z2lXMHTi0O\/UNJaWeo8cOmHeusi8mHcFAWcxbUgCu4L+Ey9+H\/5TV\/c9\/0HkX\/eqHUzd863aVke1yni4BFgvlQn4nB4E0Glf9xF9cfjBM3tP9AZutbgmWrdrbofnC22vjsSaDVv3nhjGhwGu3IW3X58jH\/J6j77wwrFzR1\/4tfZokDnrliV5sinTq\/fwcz\/5g7YwuacVfemWW269+frPTpN336He1p8+d0hv3ed\/eqpbtxkmBUyVmsIumN7Dz9Rp\/55r1u\/kYujY9qCnjLDKhej9i8O+TrbNFwmMiID0khEpGEZld6ZnqkcPF0tfE8bnsoNQ17X7B2ue29fa2SM\/qz3zl9bdz6x7Rj+V7D36bN265\/e2\/uWMvNbT2dr0k7rvwcNRS8gfIZO5rdvX\/WT3n7ogyrpPr3nuLb\/jyVLib4efWbfj0InTuN514nfb1\/xgt3qkEOeOPlO37oV95nbrap6VHzXn5uX0orj3xAltm9T553atea+3XWW8d+qUvDz5\/8h1i3AW+rvZc2Trup80tXd5gwzTrNMj80dAx\/4Quu1AK9CgTD2DT03XbNrbKU3wyk+28eFPr75R8Um7P+wF1UEdcc+R59Y9s7v9tMz0E\/ubT0ybu\/SLnnNQ0bF384sdQ6LjNy8elfxF0U14OtOt4hsJJBABtYxkz1w4V93Uz7x3WlrX+Zt1dU++eOiEXAG8Xunj6\/7XOv2AL9QLBno\/PKc7i+iX3gJnwD03inXmxO7\/Z9325s4zqH4WC4AQU2d\/4bPSADyPO69gqoApVr3wr4durMe6p8JDPUXTPfBJr7f1qH8RO9byhrb4iMs\/gw+PsQ44roemNvxipn\/Vlc1lypXXedFDHf\/6YOqpEJ1N675nwVv3zNFzKI5ru+W13xnoD23\/ft2Tv5WnRFEx+euBA9o+TWRf\/8C\/3Hl9yezZX1h4z7\/cN+9Sj\/zXdeyo3Kehy85LH6zQ6XXufVobHeA7feLQz9esa8IyHw3PcMq7mtateXav+e4z\/O8iwVSG8SfQe6RZ+7TUU1DwaWmNt+0N7SYvZeFfLjr3Pb1uxxFtQyLXE2PPEGY+hFmFer3m2\/OHvViCzBnOu4LO3xvfFj1z5KhyK81OPQrrGra7At1ZeswbEr\/X\/82XPv3mm6b74EE96iCy99DLuzuQPJdz\/ZIiuXro7cb4xuIkkPoE4IzOt+bO3Rt+sF3fopxu3\/30mu1t8CsEbfch4KuQvd627dpeHfKZzrd2P732uVbHJwZnoLkLv\/b32CrITc1zq3\/eLo99M4uW3jwTO42gSl363deVc\/0Dj9553ezZJXMX3v3ofWU58uZ7cdcx7TcWO3+zwf\/05O36E0zCB88wz+vFLgjawi6Yns9eqe9mWvz9+PPRN+RThlfkXQkTwyvvfeu5NU8E7+v+n92docfBMIOBBGInYHWI2DXEXqPzd89pv2D63NZftWqfAQap+OvRo90yI\/e6hysfu3ee\/Mi3t3239gWK9hdfbJOLQWbe3JtvveXmL+TJz2DPHv3pr47JCvqrtze94PolN19foH4Jo7f1P5rlFlq\/Kny9Iqdk4S1fmp0jKwvR\/du9ci905sAzL7RL3SIzd\/b11xXlXiwr9Lb9\/IWWXvGZmdM1Tp3vYv\/hPXHS\/+GM99Qp2N\/dof2VLzZTOSIqC71d3VpLsgW7F9oa8n8EZHwPFplG2T+9+PM\/aRrc06ZfXVQ0fZq717+ZQpmsK4vyVN+FJ6+o6OrCXNVTXBLC292l1dQS5ihr3r1LpsuMs4eeaXjmF7+XzDylX7\/5CpnHFwkkKAHfmaPt8EpYN+1TlwrR\/sLT+\/DQK4R7WsF118+Fa+CKr2vvVv+JJ5JmL8jILfxMjtrWu7OnF11ddGUWlESzzpzp0pYpqc8z957HKisf\/oo6khFhVjBZOvgVWAwPBJ7B\/EU8s2drPilO\/EkuUvKb9H\/2yYuXzJbnP+3R2CmLq9ffWl\/UF95ftkr3FmEXPVVHxqae9hz4+T7tSzbygyP\/Gtvb\/vOf48j4zIEde+U1l0f7TGlhkfyzu96OV35+oEdEw6T3nVNqYS34+4W5LtmwfLnyvvI\/KrV\/98zFqvansEufrKBecpmf\/aVbFpboy3zXgb24SUTgGUF519Gj2tTKvf7hxyrv\/SI2b6LX9F0k1TDjZCLQ23pUO33zFP7DrZ\/Tvi9+tvWNd6w9kJPJZs\/gPB9CVyGo1FehzNzP+m\/PU\/OKcHf+L7mF\/gx5v\/6s+XaNav4Ajzh75Hd\/0pIdBw5hzUOOltKj8LM33K7AeUNS8LV7SuF1Qpx48elnntutsZq+5M652u5Ib5dvJEACFgLtYW7NZ\/b+fG+X9gyfmVtQdHVB7sW9vbab8t5ed8H1Ny+5vkDeSXGW0bpX\/\/aYpbEISePPZHw+uXlwF3z5lqtNjwSqdu+JU9ofzojPzFuoLYQqO++mR7Sbb6VcB3r24u4v813S8KKC3MyP7A23XzCnlvh3M63tWvc7\/nRCGiSmzf5veSKS8vY\/aAconqKv\/UvlI0sLZAe69\/7mLWkOXyQwcgKW2+nIFUah4WxH61vyF0xb37L7DdNJQj2Z9Pzx0JHOzC\/ep\/0pzX3zpglxrEVzBjH9+n+6vugzM4v+\/qYSeVAiev\/cbnqKyF14\/z0LvzB34T33Xn+JZkznqVPau4rcxf\/0yK3Xz77ulke+WqDl+Do7usTZtjf+oqWm3\/zow7cs\/NKdDz+kFgQfPFC4Cmb+V3n1zOn3xNCJt7ELETgqRU7n238W4tR7coOcPr3giigtFJmfveXR79bX2\/9V8LRZV8ulqLPtKB4MzvxO+x5s7qxZeEJDg1pobVZ\/ieOZ+41H773jzjvvffTh64BHu4Yob96d10oNEHOvvfPOO76iPZMgpYXMglv+FW1rf6KsZRhRZumdtxS4kew90S5PW6fO\/XrIl+hwlYEEEoLAn16QP\/\/17TUvtmv300\/PLfmE4YDSNe75DdDziQAAEABJREFU0sKb7330zmI5pcUHR49It\/UbbnjBlUVf+UrRx7XsjxfdfOcdd87LM5SEX2dEzhcf+O7\/rq+\/e5ZwueV33NQX3KDKeQXDRWsILIZvw9+tVzNnzVI\/n3Ti2DHsHt55Q51h5P5dCR7Eo1sPAyp93Sda1cL7p0659Qq\/6AXqBXrqfesNuTIIMX3Jf7\/zOqyx37z31ltuwan01dN8fm2ekltu\/ruZMz8z++YF2kfHQ53HcMYcBRPvWRyZoNVpOfrqBdkaIix9geLuWbc9cst1s6+\/9ZGb1Vd1+js7cHSVGY5nZOUurYGe1kN\/eC9znvpro2\/O+z+0TEahBBI+x\/9nJp6iWXn+YzLk4dAsyHT7PQOKOMwHv2ParkKeopu+oE\/w3C\/Iu\/Oni75ivl\/fVKSdPUC7ORTMuhrrmK\/1qLTt2Kvykch99awCU5EIszfsriDMhiRvyT3ztH1UZ\/sJuWhMv\/nOUvkYYmqZIgmQQBAB\/wpgt4Xobta\/0SWfNe658457Hl71tYL0oOp6InfhN+9ZOPcLC++553q1v+8MepTRS0V+c+Vef4N2L5ZFc790q\/\/PeGXS\/zrr1e++l37Kn2V97zIMX\/Low\/fceec9Dz\/6T9oDg7WgcFgwM2cVT5dlh04ck5\/sdLzRpn0ik1uCnVtE5fILs6h87tQbfzjmnX7rI\/jw6bHKW9XNHfkMJDAyAupmPjIdsdbOnY3dsxa+HPSUrvRkL\/zaP8jPaXtPH9m9eUNd3ffW\/dvuU65MbAT69K8+nPjV43V1qxHkD17ISt4zpqcIz7QsmSdETg4eFyAODWiPSpBk+Pg0taoIcemnlOTDM0Zvb5+8KKblTdfv81kzpys9\/19Pl8jECai83tnZ0XFKPgxcMvuLn4FF4sTJY53q0+HpM2cKEZ2F0+Z+abb2R3hSZehr2t99Xm6VOg8d6NB\/MDV31ixlqiosDZZS7uX+r2zkXF1oLiAvOrymlX5ldpa03O565uxbvySbltcyZy+9Oc8lJb5IIKEJuDNzrr7l0QfkaanfAQOuMfMz2t1XnFFuqjoS1gui9OKC67+cp9+elVIjdl7BjCIBQX4yXFR0NcKVdi6cWXS1Zn9\/69E\/i672drV3KPo7Wdbf2fDrYaAp9bUX2dZntU+eIyx6RsVAT40al2tfyBNi2vSS2bMR\/i7P47\/m\/f1PtMW5ru7n+l\/29Zz1iiiYeKaqBfdMl\/nQyrBCE6Je+j7uvwuI3E9IVkL4xCBUhOMZSXnOwtuvz8Ha2dt15Dc\/kXem9U\/v7hDyzgTFRqCQNATOHFEPJZ6iz+NOmjmrSHM135+OymNHUy\/s9wzCcT74HTPCKmRqIbI48+\/kw4z8y9ke9YOp7qK\/w44jUDHS7A2UDJHCbkhcuV9ZYjw75X7la3MzQ+ozgwRIwEzAvwLY3ZoHcSuSZQPPGlh5tI9aZa75NXWaunWJT+Ron\/kKMWR+lDEXDcgDeJwJpDRpqPM3u\/V7sRCde3fJ41Ttgima6tHvvvi415QdJOqtT7v8Cn0NyLxaLZlBpZBwWDBF5tWztO\/X+1rfOib+ekzfzRRqTzeRlBct\/VrRxSDgbd+3\/Wk8AH5\/wwvNPZm2R0iwgIEEYiQwHg+7U6fL3TM20CVF2pbcanLugke++51H7731+tnTc9wuH85Envuh+fvt02\/WTgRtfgLQqinm9N+MQ5XeU53qmDQzE37vmTFTrkreU2+8eQpPI57PzJyXL\/dNvlPtR947g2amF5g\/oRmZhVNL5sqPgr1Htj4rfzDVNX3ubNk4WgkO3jPKQiF6\/9IpjQi+PIzUsV17O\/Vqva2Hj8pPgfQk30ggwQh89mv16t93qx+5Y\/a0oJUs4Bodf1Ez2p2ZEav9w\/fiSCuYyRL5yfCdd96BMC\/PlG2ImSWzC2TXfCf+dOjom5qXf\/rzs9W2RS8UrZ3qay+yreBPnp0WPV29zduAfnKMAwav13vW6z2rn1KjbPCPs8rv9H3zOnkmHZFJ5hWXq2Wu\/T9MfwM81Ln7Se3H1uqeOYSVFw3IEBjfWJe+KHg6K89d+Mh3vvvovbdcXzI9J134cCay9and\/h\/rlXbxlUQEeo62qrXBe+jJCvyreVH7AxDRf\/RQlN+7jjAfAhNpBKuQH2jBF2ZPxZPAid0\/3H0CTztTZ3\/BvOPwlxIi0GisrhHQESSdOdBk\/Gpz55HfKWRBJZggARKwIxDu1hy47YqOzpHdRAbOGbdG9QvuQlzyKf+HmqKz6YUD8o9f3PJJBg8L\/v9NJsjgzOmXa1\/+En8+oP+wmna5s8l\/9z1sNPE347lD\/EX7vXitZFRR5uzZ2qrl+3P7oRb5tXchcj9fom77SoGz8otn3Vn13eqH\/nnhFwpyPW7R7z3R9KNnW\/iMorgxHikBucseqY5Y6\/t6td2ztodWP7dj0uA9rP3O8OM\/ac26\/pZ7H7lP\/anqB+\/hDlzwWXn6IMSJQ6\/2ZHoyB9pffOqJDRsQ1K8im5TELH5ipvp7PN9b25\/7fae3+8TeRvWHsSL3s4UeqEMB+dZ56DAMEbn\/NU985kq51nxw5Mi7uJw787OZeIuThZmzS+SC4TvrlYfA02cVSd1Qr4fp\/1W2jPPd3f\/2wtG\/yJ8vemaX2sTpBUSG\/lFl5x+PdkEJdk7+K+He33lx+x\/kyqId\/ojeP\/38BeOnnsNV4zUSSBQCfgfsPPD87mPd3s6WF36u\/eqNSC+a9RkHIzP1Q5Izf27tPCt\/0tCvJNI646AvzArmUCNstmvWXPndeOH9w69+Kzc0YnpJiVyKhBihnQJrGh6ucJzhtOiF2JXzWfULTN5D218E3q7fa2v16rq6zYf+5td2puW3x4awPPcc2qotzk88c+SMiIrJJ+bNUwt8994nv\/\/c3uYjR5r3Pvf9J\/fKn2r0enNmzvKIyEtfiM3WDGeeEZR7tf\/PZ\/X3ftI27fpb733kG3O1UTijfqzX2grTCU+g6\/fN8l5uZ2d7s\/Hwb3dZ5TnPB79jxrIKKZ3h4ry52nfBsHdCKU\/h5\/PwZgoRZi9KDmtX0Ht4+6\/k3w7rz1Fd+577lRM1NMFAAiQQ\/tb8iby8dMnI1\/LTp\/ed6DrbeeTZZ\/X\/m1Jmx\/L6xHT1JXZv83NPvnToSPOhF3+of2CQ+V+ny88foOyvu1\/4D\/kX\/OLTX\/rmvab\/Tcb6UJCj332HuvY+uea5fbj5Htm7dc2T\/67dfc\/lzLzak3NFnhsKhe\/otqf3nujy\/uXIc1sPGQck8koUr1n\/bZZU4j3yq1e1z3Wmzy7RNiGRlJ\/41ffr5J8I\/HvP7Jvuefhfb9Z2Cr7uv8bafhQmssiEJDAeRyF\/flH\/BjX20PK\/ogwC77n687nyV8u7Dj39v2rqan70O22uf\/pK3PgzS76i\/pfsrt8++e3\/+9trdrTK\/0zhXObs64qkdwWpiTWRt\/DL2i\/xDHlbd2yo+\/7Tu\/8sDwVE9vW3XqfOLPOmwwJolSvI9JkzhJh6+eVyL+zz9QtxyUx1kpIZLwuvnjtLWy6FcAf+h060rgVP2cJZmZrUffSFJ+R\/atXxkZY0orzpl7tkwtvywrrVT0X13+EOdf7qZ9q6ljnrnyrvmSuXJ1\/7DuP\/0JLa+CIBkdgIDAfs7dj7k+\/XbXj+qPb7ZJkFt4T+ZLq\/J3BkOduF+MvuDavrXmgThpLhrTNhVjB\/k7G9z5xVJNe3fu1Hz1zTZxUr5x+pnUJEXPRC7Mxb+BXtzFd0HwLedTvatVUyc9aXrp9maOtt3\/69b1f8T\/0Iw5d3\/dxPiOiYZM5d9s+zpspGfR+07v759u0\/3936gTwNFhcXfW3ZXHQ78tIna0d4OfGMoNwz6\/Of1u5Mv1N3Jm21dOXKO1OEBnk5AQl0HPqDthf3zH1AfblMxtVqiy1OHFU\/SxbObuf5kOnfBsSwCoVrSb+W899K1GcgQuTODfkOWYTZCx3D2BWcO\/KC+pzp01\/676tu1r7cfuaA9n\/MQR8DCZCAn0C79tNlFfi35jddxgpgt4WYufAG5ce9J37z9LrVG7a3eYW2Xferiv59+pe\/qh5bejt+9+L2n7946B11Qy64eZF2ViDOHPj5Xm0LNG3e0nk5pv9N5qc\/t\/6ZTGbpnf\/8dx7Ztu9M629w892++60z8u7ryiz6J+2XkgsWfunT8rroPbH76XV1T2xXv1ymZUUdFcwqko822nOTENOL9UcZEUH59M8XZXrx708v1v2vmprvbNc++83Mu0I\/8Im6eRYkAXsCw3RBe2Vxyb141j0P3VJ0aaZb+LT\/ds7tmX79vffIHwIQrtyF\/9cjt1ydY\/yJvju76JZ\/eWThJ+LQcGbxPY\/ee\/10j3zokOpc7pyrb3nk\/1qY6yc0Xf\/RASEuuVw7i82bnicL4uX5zEzdI+NloUvfrstPs+UXRNCIKbhmfu2RO2dn66YC0FeWanyMIpmz71x+\/fSpegEjO4zQ+cpz6kt0BV+9eaY77+bbtc88h068+IxaScWE\/sfOJwsBOOD\/eDRoicDycc8j9\/iPD+z6kXfzfWrB8V+EkpGsM2FWMH8Lsb3ruwetkvk7YiO0U4iIi57WpDnKnPX1R+78gvyCqsrF4nP9vY9+rUCmoO2Re0xLKK5dd++jX9e+0xYlk4tnfu1fH73zC9M9crckdYp0T27JLY88duesi7VkxKVPKxUhcuQZfl3NnPX1\/46plWm+My2\/d15WhNZ4OREJnDii\/vc6z9Xmr1dkzlI\/zTN04tDvtIOScKY7zwc4ZsyrULiW9GtZsz+vHkVyi8w\/o65fjegaMe8Keo9se1H73zenXX\/rvGkXz71zifZ8dfbQMz89Jp+R9Ib5RgIkEEwAK4DzFmLaFx94YMF0\/VHD5c4p+eebC4KrR52y3nOh7bML7111j7pd+r\/SJTL\/bslXtOMX43+T6f3DT1\/4k8WJM2feVvno1+cGHhxcbs+nZ9\/yPyrv1LdP0+bd\/8BCv+EiPWf212M3HI82n3Xr\/cPnOoH\/yyaC8twvffPe67SNQX9vLz5+Ts8puvW\/q42Hro1vJDACAv4H\/RGoiLrqrHvkBy\/Br7tnoXrOlx7Vcv3\/rckls+\/8H9Xfrf9u9WMyrrx34XS1D0ZRd87sOx757v+u\/25lpYz\/5c7ZlyBXhll3azrq75EaZYYIyvnEQr2NL+mnFiIkJ3P6wnsrZbPQXf+\/v\/vIHbPlj+RpqhBllt6rGjD+55eir+sZlV\/1H4qgnLOF1m6isClYrs687btS+3e+NlMOUc7Cb8mU0bTw4AxIM\/U7QHHvvJKvWHon+\/LYd7U6GtWQzqJlM5\/cLysF39UfGq+4uVKrXP+Q+k4dijOQQCIQ8C8j2tJhY5BrmrFE6MuH+qsOFLXzAmQLfcGRM\/6eYpkhnL3Y7DVaUbtIV2i3gunFHXthWQdkcTzkfEfaJl\/LZ2fKLP\/L2U5\/CRG60AUuCSEXCodFz76nLk\/RkodljapKHa92MKx0egr8S2jVd+XC9CXTtdgEQFsAABAASURBVMhMNB2uaUVL7q38juyrfH2n8uFbg9bh8EtfKL3QHBGGZ\/h1VZtastd2fdesZ5QkBKbfUimnV33lEtO9G+7gv8s\/\/A\/TbBzHsoCEmQ\/aJblFqfS7ibEKiRDfL9Z3RvriY0IY7IOeeQ9pRj98vfZV1RA94WcveocdjmlXYOMaQphazJx9j2kLgep+ONW3z3SbjKRIAhOWgN9fNMfUokfVI0a4W7M77x+0Rw2sDXjQuHXm3KCHlxC\/Dl0xTLj1ey4el3DPhba7rzcel4xnlurb\/D+x7Mpd+C+alfXVXzOOJEzaphXefK++RNTjIajyoVuMz1xlKXfe9TD8f3+3Em1955FbPjtXX7nUZuwTkR+yoGTm7WpVgf57g3Yz4ZVjq\/IlbWPwnUq5PfjOI3cG\/cgIFDOQwPAJyOfs4dce3ZruzKmZTndct8djfDcknlZAlzvTox\/YIjH8MIoWGkbBVOPjUyOTAgmQgBBwQMflI2o+UDKCdSbcCha1CVEVHJmdgJXpiXHRc1\/sccSLdelix5U7zKoeVVdVITQxektfJOXh+q7MYzyRCISZD3BMRzcZJUSRZu8oNUu1JEACoQSwAjhtIdzOt9BQPZFy3JmO99xIVWO97nJ7Rq+tiMrTPYEvjcZqOcuTgAMBl8zniwRIgARIgARIgARIgARIgARIgARIIPUJsIeSAI9CJAW+SIAESIAESIAESIAESIAESIAEUpcAe0YCQQR4FBKEgwkSIAESIAESIAESIAESIAESSBUC7AcJkIA9AR6F2HNhLgmQAAmQAAmQAAmQAAmQQHISoNUkQAIkEIEAj0IiAOJlEiABEiABEiABEiABEkgGArSRBEiABEggWgI8ComWFMuRAAmQAAmQAAmQAAkkHgFaRAIkQAIkQAIxE+BRSMzIWIEESIAESIAESIAExpsA2ycBEiABEiABEhg+AR6FDJ8da5IACZAACZAACYwtAbZGAiRAAiRAAiRAAnEgwKOQOECkChIgARIgARIYTQLUTQIkQAIkQAIkQAIkEE8CPAqJJ03qIgESIAESiB8BaiIBEiABEiABEiABEiCBUSHAo5BRwUqlJEACJDBcAqxHAiRAAiRAAiRAAiRAAiQwugR4FDK6fKmdBEggOgIsRQIkQAIkQAIkQAIkQAIkQAJjRIBHIWMEms2QgB0B5pEACZAACZAACZAACZAACZAACYw1AR6FjDVxticEGZAACZAACZAACZAACZAACZAACZDAuBHgUciYoWdDJEACJEACJEACJEACJEACJEACJEAC409gtI9Cxr+HtIAESIAESIAESIAESIAESIAESIAESGC0CSSRfh6FJNFg0VQSIAESIAESIAESIAESIAESIIHEIkBrkpEAj0KScdRoMwmQAAmQAAmQAAmQAAmQAAmMJwG2TQJJTYBHIUk9fDSeBEiABEiABEiABEiABEhg7AiwJRIggdQgwKOQ1BhH9oIESIAESIAESIAESIAERosA9ZIACZBAihHgUUiKDSi7QwIkQAIkQAIkQAIkEB8C1EICJEACJJCqBHgUkqojy36RAAmQAAmQAAmQwHAIsA4JkAAJkAAJpDwBHoWk\/BCzgyRAAiRAAiRAApEJsAQJkAAJkAAJkMDEIcCjkIkz1uwpCZAACZAACVgJME0CJEACJEACJEACE5AAj0Im4KCzyyRAAiQw0Qmw\/yRAAiRAAiRAAiRAAhOZAI9CJvLos+8kQAITiwB7SwIkQAIkQAIkQAIkQAIkAAIpdRTibd3V+GoHejWy0Nf2s7Vrf3kyBiWn92+qbzh81lqje9+m+mcOe63ZMaVjN8ZefV\/Hnoa1tdVb3rS\/nNC5Z9t2PX8w3Lj2tDRuqK1e39Sd0N0wGecwYWSJvrZta9e+\/LYU+RoBgZ6W59fX1qxvOi11JNcr4jrWd6pJOvOzLePer4imWi0cnekdsxkmszpebdzVOrJF2qRNRFyszIWFSJyhDLaLqQQjMDqO49DJjoPP72oL2c8kzlyN2d\/HlJ4DVH92jMbbj4Vf2TDf47E1HWbTE7Ja6m6\/Y7zfjWD0g3Z0EdaiIZ\/3rNfbP5zWYnRPNGH20CAjcS00xK4\/VIeRY27ayAwnxHm3E66pJLs2DkchPfs2VlbWv3zKgdSbWyrXDfOZtq+zre1kj4PeGLLdF2flZHliqCA+lpk9Lesi1OhuWlcZOG5AdlbWZGTHFE43ra3cYjzlxG6MXWOnD2zb11NwV9Vdn7O7muB5GNfWcOPa8stt7VMXrHxoQXaCdyRgHmaGmjCBLL\/k9sQ6+\/w1Le+pnYy0jLy87fi0BQ8\/tODS5MOA+R52Hes+sH1\/z8y7q+4oHve+RTI11MB4Te+glTZ2MwKG9Zxsa+vsC6RHKMGUsItVsPoEGspgwyZMqme\/3I68FO6k3cpieFuU4Nu6VWfkdEyOE+QdkXVbS\/ScbA31iQSaq3CysCuktT9CxEQvtHo8c2I03nYsRmwPNiDD2JqOuNmUVRB+GUnh7Tdmcwz3O4fxj2ZtfNO8o3Nei86fbGqor66qrl9TX19TWb1uy8F3fQ6tGtlBqyU6FOPaYvLQICMN\/aLl2cq1u\/UPamPXDz1BFiLtD6am\/Vnh33tGvtuJZrDCG5GQV11jblXHwSOdGRm9zYfbbZr29XnPDYihPnmkd96Ywb4+nPCd7ZNpFPDKd1XX5\/WipG9IpYJi33lc0qoY2fKkUMuBEigM6Bei3+uVSTSEAhnT599WPtv0WB1a3q8KraCCyJ5Vfuui6RkC9vQNiYFzaNoLq7KLy29biGyBYrDTCLikGyX1oA9aj5QNyPFiXz7Qe1blx2YMmpD26Nr9b9B5sqNn6vQZ\/6VXXkVSgwmrZFKVkpmqRYOGIQALehQoi26ioUAvzBo0zSoDxQJ1pP5ACk0HjmxD8QrZotQPJpaTXa1wQJEA25Mdp0XelQXuXolRNS0HFADNdaEqMMR6KdObbNFrMh6XdCNheWDKmYrBkkC+ECiGFlWO3pYjQGPC6HaiohZkvzKmX3dreak2+wIG4KrSDLOMgFaQr\/UxCLVRIJWFCMvIyXe6xKfzC1y9+iwKHXo7eg7ATYNuRqo0SM0qVxaTzflTXtOQBQ2QqqgNnCorp4HUAw1yCuiZ2ps0yTItvSc6PvBMvzJLc2atELwAvntWrjl6GjnntU9FMC1NZhhXZYshk0e2BatQBZdCa5nz0QVpsKEPlnuDTId3wGwUgyp\/kAUC01tWkbhUGbRrKFOCKT+InnZV5phWWi0PkdRp8WLk6r4Je2Qi0ku1a\/ROdcRUSVIyriomUWqWqrzajUZX57MbSv0a38aEQMerh+V25I3D7Xa7CGmCGmLDHTCIQVsUOeX0aWzMYXMVTCfMFuQE3dalYrzkXDqr+SkSpqDypb8Yt8KA4+jlVJnAbVTPlm\/23gHL0RaMkUXML9kFG68xF8F6YjdX0ZBlJyCtAgfZX9Pt2FCFfNigYCoyuKQLDmbYVkEtGWQVjZJMyJfsY58PCtGKP8gCJnoBC1FAWSJr+l+qLroguxy8pvmL6OuJqovyCqkuSJNsYKpeqJKGnoAga8lZpIopzYGrZkmW1PWjs3pJmSmrwwZ0SjNe1XHqrLE11foiCcmSZ0P7KzWHNKd0Mw4QCLeMYEwjbr9NAwefkuMB3ciUE8Y0BMjUpqXF6WQ2WsHQB+5EspacEvIa6vR59aki04EmkMIsQkXZEBJakKqkCZgS8k3L0yOtsDVTXdMume5u0oCgkrJAUIaqZxujafQxsLj5+sw7Osf7Zl9b4\/cbXs+44aGaOvmvtmLZjDNNP3qi6X1TI9IMr8lO61Obv6i0X5\/5\/iztXeUH7bW0fAnZbKSeiezzXvloghE4a\/YvpScUiCkfpmqjJsfLZrdjtKA9aJx1vI8EMJpqyB2gNugKtdUONA2FWgFzJblcjPBGpgGRJslphm2rcZswddxo0lrGuBB\/YcyPQt5tafMWLLmjJPNYi83m4\/iujXs6xNnmrU9t3PiKPCvxvdu0saZ69YaNG596vLauseXItvqn98njtaHOpg3VteuRv762Zu3O4zg+MNF5v+mJ1fUNr51xm\/JE975Na7YdfG1Lbd3jG59av3Z1de2PDnZqG6Du\/Zvqn9+xc0117ZptbUK0ba\/ftF82IkRf+4611TWr1z+1cf33qqvX7Ww\/r2mUqrbu2FFfXVe\/7Y9CaW4T3Yef39p8VnTsgVWNhz8QUu126BPtryBHC0+srV+zSeuA8L7eWF9TvfaJjRs31FZvaGreu6kehT843PjT5h7R0QQCzx+GEdEYs2nN5sat9at\/sHHjE2tra2ob3wymAZ2g6j267amNu44ra03GCwdLUBBYtjQ21q9+\/KmN69fXVq\/Z1v5Bx64Ntas3wua11as3HfQvMT2vN66tqQWljRtWV9fp+W2\/qF\/\/a\/3TNu+rm+rXPLFP\/2uF7n0\/XLvrHZDss8cr2rat2dT4i021NcZAoDCOGzqbnqitf+bwGdO0bX9FY75308bnJS4x1HnwR7WVdevlENdWOg2xpk6P+o7tXFtdvfoJdGp1dfXancd0epL8T3duqqtWU85xKkYPEBM4MH\/kTOt+rXEjBlqG9WvXaHNJ67uaIdKA5xvX161GmfUwcUOTmq5iyNv8fH117VoAX7+6ev2e5qanVV29R6n\/FmkZ2foGfGjfpqf8bmjy7jD0LMBrf3iw84PmLf75X2u4\/1BP8\/Nrq+Uc27j+e8Yy0nOgoX7zEX3ytO9cXb+msUVbXsRQS+OaLc3n5ASObXLarGNYZJo6hPfodn2FFO8f3FRXKVfCJzBFajcd6FSjL\/timr0qU8bOk0dWsZ1vzjNcKpQv7+Fn69e\/ojs7MiSLHa1\/DTe9NR9\/fn3t9zZKV63BNO5ERRmcLZRX5QsQNK\/3r7Qy71xLYKUyHE0I26VJlg992Q6r9\/CWwMKFOh27nqjf1ibv3zFotr+PoBfBQwn1DGNKoKPlj96Cm+8ouaitBXfG0Kbfb1qv7mu4\/cH94dzWLYo2jU23qihv6wKfXv6otvZxdZ+qXrujHbpl+76Opierq7+H\/I2P1+FW3oxboXY7kA1pAvaSHftt68r6eGFeWbyjz+E+K5zufdASHKAzeK7Guuw4ryFym2TeZpic1x5mwDJv7MuOtruzXeUiLzuyYSeTourFD1bXPtl0ynRUITXKlxzcl197eX2t3ETJez0mm9oqyKv6y\/euw2ZY2zM0Pm+zljot6dJa7DahuHuf0+7RuTlUYzATCLuMhN9+O886OUZmv1gT0\/a7J\/JuRDgsC3JKBD0g6F3FM1fI9ltd6nkt9KnK3jfljVPVcYptF8bju0w7upC1yK+qY8\/LbbmLV95Rkq0e\/FyegpvuX\/b3OT3HT2rt2vYX2iyrpRAOe4m+k02b6mrlkwL2Wnjq9D8p6O0HGann4Q1Pf03viJ43tmIbL5+\/kOWg32fv4HYWQok\/vL\/HxvEd7y8i4vC\/AAAQAElEQVT+WnJ2\/ezg4c21td\/fqB4bja1j35uNtbXaM+\/jtbU\/OoiHUH8lITCZfxr0fOrYkOONzLoC1zpts0NvvgE74i+Zninjr9xGY8cbbb1Fc4rziwszW15rDSlwVXnFzdNFVtn9FRUVSwtFX0vjv+0fmLOiqgrpqqq7sva9Is9HZLU39uzvL12h5T92o6f51wcCA3a+ZcuP94trVzy0MFeWDHq172ud8ZBUV1VTvaLk\/K6G7X6FJzvEVyvq6u4yf+m850DDlracxY\/WoJ2q6orF2a1bfnLQ\/xc4Jztc5RW1daY\/Ockuu+\/+siwx\/WZYu6JM+2BfaP8KlyIHYeXiK9ziU6UllwpxumnTjhO5SypqKisqKmtWXfv+rlc1xdllK74hdSxB8fvMOkRYYzrOZN9VpamqWHJ5+8+2NusbK6156PRTLb9KyxEm450sUQXfO5N9t8arqmLxJS1b1m\/ru+kx0Kioeuy2vK5dr2jtnG5q+EVX4TdksYqqmoqFmU0\/3oZzruLiAu\/Jdm1c+tqOd3mmeo8f1\/4m\/2z7cW9h8ZXhe9Rzoqfw\/pq6VQsNjn0tWxv2i7IVDy3INU3bwqV+5hqu9u0Nu86XaDOmKpohFj0HG7a25qiBgPFLclq3Nhhj3HPyjDTikQXZYaZi1ADLP92+7acaMcVWiOx5KzDOCMtLPL6M4jlF\/gv+954O33X\/ovGuWlHi279FO1rq3rNp59u5+rSsWlX2\/i7DYH+9FH+PuIzcPzdLXAkf8ruhybvD0zMBX170t10bN7TMeFBO7KqqB8tczTv3yqf97j0NO08XLpfZFVgWFl3UpC0j2bOKsk6+fUJD33H8RKbHc6L9bS31dvuJSwsLp4rYJqf9OpZddt8SuUR+Q1shh9q3\/XhX7zXafK+sqbmvpHd3wzb\/Q11g9mpWqCjq7gfmm+NipTTKOKt0Tr73deOj9Y6DR7qK55Z8OsL07jk1dN231Oy+v8S3b8vL70pd4S2UJQQg+L2+wj\/EppVKOtr2FlnSYWmSl0Je9sOKnl3Z8\/oROe6yxqmWtt7ismsywMR20ZNlQl4OSzd6YRrKkFrMGHUC2mjOKcovLspsOaJNmOAmm3fv983VdxmLpjTvwrbQskWR5U23Kqd7Qbbltt7Xsn3z4cxFq+QagvvU8oJ3tjQcwAagr+X5hv1yY6N5ReXdWft3+TcosiXtJcvsu8hf97GlOW1bNr+q3Vi1y7irWPYhDtMPx4Th7n26Mv0te4TLDvzFfsOj9FucV90lnWCqKjKGcw5j2RGmRT6wykWx7Dhv26QxQkTuRdXKOe\/veg0DrSqY457mQ74l37LdamrF+pw3w\/K6\/VqKK7adRb4p2O0eIzRnqk0x\/DKSXbbCefsdYdaZZlSM2+\/IuxHHZUEOqOkBQSbxst9+44IQtk9V9r6ZoVVwjhwWxqvKTTu67KC1KKCrG88VBbNKg5vIKLhh2W1\/n4+zEYf+Qlt0e4m+lm3PHs68cZV6ZKv5RsGJrYEnBWlFkJEyQ73w9LfkSpE1Vz7U6s9fpmEN7FUcPc7OQqVaxhbHb2ySnzc7YJTlTa\/j+9pmPCRXnKCtY+e+3W2XL5HZVVV3F53Z1WR+Ts+Oz43MtCg5brNtbr4m20W8ZdMzZbxV2+gbaj\/8Rm9hcYEQecVXedpfD3ostCl\/vKX9otKlN+ZhHuOq+7JFS6\/x\/4THVE\/G2faDb3b6hkTG3BV1K\/2\/E4GTyx\/t6Jx51\/3+WqhoClllN5VmqU678xbdWOx783X5tQ2UyC9bNMOvHEkZuptf78xfeFuJynZ5Sv5xQf57zc3aw70Q+WU3FniUKlk48quvdceOY9MW3Y6TDtHd0tKTv+A2f3c819y24IrwGiIYU\/pF\/dzHM7t4+lBPT8hvngVrDxgfwZIrSud9Uqvq8pTOKhBTC+fIVQU5GcVfnOU5eRxPflLDlWWLLlOjJDyz55dMbmvBQ2BRccEHHSdwKDPUfryzcPE\/TO883oZU37H2zvyCAlf4HnlKbijL1lWiOdG5+4c73i+4675F+myQeaGvttffnFxa7i+DIS4vnRxuiEX3682dV1gGorP5dX2MPZ9foBvhPBVl98MMpQlgyeeni54e86ZV78Dppq3\/4S3+p9sKQqaTp3h+8RStlDuvtCjL24NdVPfR1h7rtFTfPtAKpn4U6zICIvmGd0egZwKeP+dzWSK\/uFR3\/9x5c\/O9b+NoT2oomOefY1gWMN\/\/2IInluzi4qx3ceiCHXN7+8dKy+Efx+QjdMexk54ZhVkilskZYR0T+r8\/vt4yOXiFnD255Yi+pAVmr14ab9L4MJPH1H1jvkW1WGVcU1Ys\/B+tHz\/cLEpKZ6I5LZx2mt6eWV8sVhsX92WlxZdos1tEsFDTaBdZHK27Cz4sfdN2abJRINu1G9aMkrnFva0tciCx6ft9c+\/MYvhpTJrD3kdsTGHW2BBoP6yPZl5xoed4c+h2ZJono+fYwZb38ZliRun9dStvMM7lzQYGblVyVoS5FwQqtbccQ60Sff\/gzltwbX7nW21egfzMoPvXzSVq+QlU1cqUzPfXnVK87F8qln0+01TAIjreZ8Pf+yxagpIxLzsiAhmL82p3yQhVNIOGtewIu1VOun+YhVFrbbR6oZQX3FCer+71Lk\/JTfNyA1tN7brzDkS7bLuWyit2nZX5ple+ze4xQnOm2hNejLiMhBDKL9OfHSLNOpNfxLr9jrQbcVwWNGsNC7WUCL\/9tn+qCuebutbQNyyAtgtjaMnQnM73PxBC\/2nG7oM\/qjf929kmwvc3WJsJu9y0a3sJAY+4uOQG\/yOb+7IFZVd0trTabOeDddmlnPQ7Pe0aOmwEi+P3vC+PQqLDeEnZkrlZSiUerhcV+Vrk1tHj+Zg49eb+kz0+4covr6hbVqSK2MZODSE\/3I3MtCg5bbNFdDdfW6uGk+kaTqVh1zne0iYKi7Utct7sa7JOtrTiydhZW3fXGZGeYb7J537Svxe5snzl12f17W+ora6uf3Jn8wd+LccP7vfOKr+lQO2w\/bnGe07OpYYsRFaWZ8iHbY7MSs\/MkG\/mV1f3B2KyOTsjc7Lo7pZTDcWCriAdIfS17djZlnvTcnkQIkRXd48IajEj99KQPU+QxrgaY+pWBEvMRmKVcbkR6XZlZLg1elLDyV2mdaexTWROBlZXwVX5HcfxGfXx9lNXFBR+vrig43j7kGg\/3pE\/E8dh4Xvkzggaj\/aD\/+Gd9dXbCtReQbcg5K27s2souKI0sqsTT0Uom24eS6Rl6DrdbRmIzHTRfbpLXhPC7Z99Yaai7H6Q5uChDLqktFri7qbn9\/fNvvu2GZZ8mTQMkAn9JRsMmnwZuTlT9WsT4i3GZUQyCYxCBHpm4JNdQrhM8x3eL4+cpIYTvzbN9+fbxEVyvotLccDX3n5a9PzxuJhRWFBc7NaOTtrfFgWfzRYxTc4I65jsE17df+0SwStkZoYbDan5bu4LCmtBGh9m8thViW6xchWUXpPZcqgZK3r7G205s8vytPaECDO93cE+ripEsFAVsokDQxy4KHXZLk2BIoYky9oP68ziwo+aDx8TYqi95Y+ZJV\/A2qUxiV5zuPuIYQCFsSWA0TwmCj8vR1NcViq3I29h8gbZkP\/VlXcV9+37cW1lTf3GHc090v2DCmiJwDSWcyhoHmbY39bl7aTn8L\/VG\/\/W7+v2uEWfzA9ok8o\/Zex4ZEq+Qsq4p3g8U0wfGshC5pfjfTb8vc+swiLHvuxo\/hKGTNAlvbWoYA5n2Qnc1vWW5JtsLczCKIuIUeuF1J71ScvWVPiEab7JYQ9e6gObYVk9eNrIHP3l9u9h9LTNW1C\/1fVIzalSjIW8KURaRkIwGcAjzTqzX2AnEtP2O\/xuBHM53F3JsFDZHn77nWP\/VOXom0qnXSynXcjCiIXRrmxInnSIgV61hmeX3Veh\/1ua33uuV\/puuP4GKzNj91+Rpp093GAs2fXr92trtv96LO9O+sM5uJN+t80mStoaBcbsHP\/jtFQ+LcsjhvDY5in7xspFU9u2baiurl2\/Zd9JBVSWCH114xHdriGZH2xY8I3MbVqUHLbZIrqbb6hNw8zBZn+YNYdRreVIi6+\/ZUul9m\/D\/p6hk68dCXeolv2JHOHtOWO6H3S8pzb5snHPjPl3PVxVU\/3Ybfmndja8rD61EzMWLP5067bNhx12LZ0d5v+55vT7Pek2E0lql6+c7EuE94MeKaqX\/LAiN+8ylYgtbn95R1vu4jvm6M\/3OZdmi7PyI36\/lr7Ov4RDIUQ8jfE3Kt9jt0TWMr+khrwFK\/WFp6Li0VUPfvPBxfLAK6PoqrwT7e3tb7Xn4uzDVTAjr72ltb39ZF7h1eAQU48KFizJbf1pw2HjzMtsgSFn5+a4vGas8lsY6bl5Zo83CmuCND5oIOQXanLz\/M9xWhlEYaZiiIaIQwl9gdBzYNv+\/tJlN1lbDJSwSiHcznd2RvgSkFVFUqdjXUaCOztyelJD3sLAfK945MEHH1xcKJvJK57pO368o+1PXnn2gb1If8vR4+3H+wuLsWhkxzI5Z4Rfx2RjeIVOyzM9Xvenws1365oWxeSJcobnXVua+\/ZrzaebD\/4xb47\/04bxnd7ScvulCfAsIcywylOetpZ2X+trLZeUlmEosRxjAY9Fc7zuIxajmRw+AYxmv69ls7YbqVy\/\/wNx8kiz9R7s8hRcd9fKqpqab92W37Fzk\/b3iWFalPMt6G7icC+QS4Gn5E7jllmx6uEHH7yzNFvmB9+\/Ot4N7HhUw7KMr8+0P\/Wd95p\/BVCVMsVyYttOvxBre3rOitB7n0mVLsa+7IiQthzI6C3ItyirjOWyE6VJ0nr\/K+oqPR3vmAb1dFeXyMzELsmvJ5S5eTPsLxW39zFuLm52j72iaJYRR6tCfPO8fy\/nWMV6QU4w+ztR2N1IbA8UBWG3345PVba+6e9Az8nX2zotP4gjFze7hdFfJ+x79qyrsk6+uk\/\/QT2h\/vW1vNaGz6Wmx9ZfVTcolh5xccndpjV75TcfvHuu86NFUO3ICanf6\/i0G7m+uUSUGN\/r0J+atbqdp3vc6mnYnV2y9MGK6rqqB8rEwYatR0zrklYyEDk1JPO9QQ9ioTeygBYHKcabr4OWaLPH8Cikr7n5uKf0\/jrj36obcjtbXjedNPiN7v\/Qq44\/riorzWzZ+bOWHp+85G3d9tJbON7T5Fc3Va7ZeRL57ozc7GluVR5XXFmldy8vPfvyE1tb7AbQ2\/ziy+3afsfXfbjhxfasuddpnwqhZmjInjc3v\/PgjsPdaEaI\/o5dm5vOXDW\/JNIn8L3nQlo+vm3bm7mLby81bm3ZXyjNP72vcU+HT1ru69i3ef9p8wc7vb2WNUIM05jQXllyIlliKW6TlBreadr2uoZV+Dp2P1G\/aX+nVjCjuDDvxJ49J3IL5dlHxqyi\/BO\/3dPx6cJZEkRsPcqas3z5HO\/LT25psZLRWtKjwrLZRH9fwwAAEABJREFUmS2v+Ie4p3nLz1qyrg0zxEIaf\/rAjkPaGA\/5Ol7Z3NRTOH92yDd0nKeipiHMUOqW2b\/1HGzc7S39p8V5MTiixu23jU2ntGnp69i\/ZX9nur36FMyNfhmx7\/zI6UkNJ3dv0x+bfB27nqzfuE\/Nd5FXXOhtebnlb9rZB1JX+Y7vbvFeVZwnjYllckZYx6Q6+dKm5a5ftmsLpq\/nyJZtrVllX3Re0tQyEuPkiXaGZ5XOubLz8Nb9J68oLpIOLn+MYFSnt81KK6EEXtJyh6UpUEiXwg7rtaU5rQc3H2nPLb5GfaM0Vs3DuI\/odvFtVAj0Nb\/e7pm7wtiN1K1akPueZTviPfjDyvpfaLuMKbnZWe7Ap\/TGFiXYNjkrorqtYykQh3fu6tCWcOFtbvx+\/ba3kEB+ZstL2\/w7nrZtv2zVdzyBhgqv+dyAUdfXfXDz4+tfljYGSijJ7x1yYttOP83aKO59Sp05jnnZUffZ2O6SmnlRVBnDZSdak0ysoq9ycs9WfavpbX\/5+f3emWVBW02Nue1m2NRa\/MQxbk4ZnnxxNMtImF5pvhnj7diiTk4wh3tc2N2I1vTBaJ9uwm6\/nZ+qQn0zYL3vxH80Nv5Wbpy8He979c+ksQDaLoyBamGk7BuWzXcdbPhRU7t6Yuzvaf\/lD3e8M33pLcUZaufj3F\/\/aumsHh7hOrzjFf+a\/Xrj42u3He13Lh98xXdePR8F55pT0O\/wtKtKRbZQlZNxdBjPNe94Sd86dh9qeOmY2jqe3Flb2XBIWuvOys2+WATuelKzehnPp04NIT\/ijUypcoqdb75ONUaW7xpZ9Rhq97W0nPQUFmsfqalqWX9XnPt+W4vlLGTGnJKMow1VlZXPtghX3uLl5Xnv7VhbXYl\/63+XteSG6aquZ+5t5Zed2FxdWV1dWfvLM7O+ukB72NAuunIX3Hfb5e9se3xrs\/aEoGXqUcGim8SedVBWWb1hl7dw2Qr7v\/7VS2fMuXtFmdj\/hNZ8bUP7peUP3V6oNvl6Cetb9qw5+T2v1FZWrm06HbjW8lpL39DJl+tku\/qlKaV33FPmfm1TdRUya7f99ZrFc\/yP35fOKs3v2YXC65rMnwjFbkzAgHBSGEvCVTNdm1J6933zBprWYjCqq6objuWUL\/c\/22cUFny8s\/PjBYpaxsyCnPc7M2eolIi1R7kL77\/tilPbftCoP4WaTDDEvJseXJZ3onENqFZWr98zMGf5\/WGHWGjGi\/\/QxrhKM\/6BZbp9hlII1qmYs\/RGfSpCg+NQomLY0H3kcOeQ9\/CPpLV4bXkzbGn\/xYw5dyyf6z78YzUtt\/WUleu\/Z+EvkMLv0S4jzggs9DpnL46VnjZvB\/ZgvtdUV9bIZWHFTf7l5\/IZ+R90dk2fodJ5M\/O73u\/Kn6lSIrbJGW4d83cP0\/Kbyy4\/2Vgvl5Hq9f8+UHrP\/QvMX7T2FzTeh9P9aJeIjJK5xd4PvMVzS9QiOZrT236lNbqpC5p32y9NeonAW7hhzSq95oqTJ9\/Jn2McksasOab7SMAqSqNCoO9oy9vYjuiOKZvIuqb4U51tR83bEU\/ZP5bnndyMm1p1Ve3LPbPKb9DKm7cosqbpFcZTgm\/r2lLQ3lBTWY01ZO0e3KfUN0bzblpRflmHvuPZcDCnfJH\/NhNopeCWh8ov1etWP3FQXL98mX70aJQJ8g5tYttNP20OR773GVoNIfZlZzh3yTAwDUukMIbLTrQmSbP0V8QqermssvLC4w212AZU1je2eRYsvx3Pb\/o1+QbmDptheTXuL2tzpg1P3NtKXoVRLSPhujec27FFn+bF9ve4sLsRx2XBot+fdN5+Fyxa6Nu1Ts7ckKcqq2\/6leE9e8Ht8zNf24hq9b\/smvVPS9QHOE4LIypEDtgyPaT9ccd6tTdev\/N04bKVd6mf23Pub9Bq6dgKPAJ7rWMN8nZQjQc87LXuKA3\/B\/t+XQV4qG1pQE\/D7fCh39HBo7PQ3xzeo8I4Y9ES1x7t4bp6\/W5v0e0rtK1j\/qI75vv21mtPc5tapi5aNFvt5qBVC8O6kWXdtCD0Rqapc4ocbr5OxUecP3ZHIRlzltc9uljbSvitnlr2YN2D89WnbP48kVFQvrJGflbz9WKZd0nJskdq6mpqamrrqu5bkD\/3rrpHtF9IdWWV3L4KFx7715q66pXlM+VoZS9cVadqTSm+q6qu6o4S\/WfJpCL9lZm\/+MHquprKqprampVLC1WBQEWtVPHX6\/z\/cYk777rlFWimuqYO5W8vyVLALl2wqs70f82YktnXyvJ1+IzpUmGohULZI\/21SptwIiN\/wYrKurrqGqhfdXtJ4Y1+40V2mdKh9RR1YzNGFN+lta51xR997i6dGzJM1iKF4GSJYT\/KyGBWgrRJj\/uy+dLkqqoqdGblspJLcFkFT9kDdXUPlOnHPHLE6x6cp6eEcMBr6UKgoYzir1fVVS4L\/im57AWP1AX+Hx+Xp3DpSsyWGgxZTcXyhflyZojAWCizzLFuvDbHakzGF3\/dmAZa8aCpOD+rzysyMpXymAH6eyQJ67NCvmm9CAyfxQBZWE1vkZG\/cEVVbZ3Wx1XlRcLr1b\/aphmaylFGdMuIiVXo0AfRW3ZN4SL\/\/HEGriENzH993lY9VhW0LMhSBbdheflHdVsXYsZtcIjAr8BENzkDxtuvY4EZIhv0FMoFsxbTtw7zfYE+34WlL7Kk\/hpO96Oc4X1er29q4AdTZUfkvNZfwdM7uBfC7MVBFjpN72y7lVbvYmCkhO7dNkuTXtYEKsywZpQur6urXa6f8WhV7TX7XVsrYkS6Zumw5vuIZaEzilMYbQJyPCsWX2ZuRt6qHrwuy5wl1Jpf\/dhjcOqV5QVTtItBWxTLNMbSvGBFFLd14V8KqrCGwG\/99ynh39jUVNfVVa6Y\/3HcZjK124ypIVkG97iax75VJX1+Xq5mVlBk9g7n+6zfO7B44G4SuPeZ2gpoDc70xLrsBJMxbXjkKqHf17TGTM47CsuOdWE0tR7VshOlSSKKXmi9DUTuS0rvwl6zugpb04rl8\/0\/D2\/CrmajNlhBm2HrMhJYS02Lm2zI6KwhCOt65dTcfPOGR+riCwSiXEZMkyEEeNCsM+9GAmOEhhDMSpA0DZz9nQhlRNjdiNP226RZ6ggk7bbf2tXSmeUrsUJWVmHqGk9Vsq4Qli2BytTjTy7As5jcHNSsUk9wMt9hYQymYZqlso7p5c4uuX0lHkOk2losrAsKjKcNp\/4KYV4tgxsSZkcWatGrwWZCrrv+vVbAGGtdv10ZMyQfmIQtkLWMeVgdHTzIQr9WvAeaRgL9CDwKOWAMXhAy8296EENWVak9RBfppPQlrvKxKgmwLNel6Q5EQc+nUd7IFuSXGo+lwTaE7M8NIIpGdfDNN2BGnCVrL+OsPl7q3G63vaXujCnmvyuJtj33lIyYqrnTYyoerRmyXLo7VtWjZUy6O1ZLpP3ml9tpmMyFbOTR6FHMOiMY376tpnrL631CL9bXdrzTk5enLx6qT+nukQJUeiLF3gMbK9ft6hwSeh9PHT\/py8sPOmWMpILXhZ\/eCFDo\/GPXMOyKjk25MC8dL9peGI4N6e6wM7zn8Gsnc2eXjXAmjsr0Bh6XLQabzNjIjJ5mG9OYNR4EcM4cdt7b2JTutqlhU866CrX\/rLp6c7O8zWh\/8yj\/t7WpeXn2f5Mb8+bHcWLHMoeDOhH7siPS3VGSCTSU7g5bZTyWnXR3WJMCtgekdHdUVdIzHPa6fk3DHiy\/gujeo9jwRKeIpaIh4Oib0VRWZYY7MeLQtGaA3VPV8H0zXlZppgVFI9U8jEUvqP1IieGOo63eKDrrcB+JuBAFt+fQkNut3ciCy8aSGsbNNxb1Rtmot4dGDQokMBEJFCwpLzj1i9VrGxobn29sWLf65Q9K9O9LjzkNz7Xl892HN67euOX5xsbNG2t\/fDTrxiXmz6vH3CI2SAJCvHvw8Ol84wdTh02E03vY6BKxIm2KhUDBV5YW\/GXn6nUNuMs0Nqxd\/cvuEvMf\/8aiaqKU5bIzKiOdQBueUekflY4BgTj55hhYyiYmOIGJdBQytXDR0pF+YjnBp8tE7n7G55ZVVa1YPCvXc1F24ZdX1KwqL1B\/HjP2UFy5Cx6uWnX7\/BmXZHqumH\/HI4+tuDZuP2Q99r1hi6lBoM+df8PdS+NwJJcC0zs1RpS9GHsCU4qXPVaz4svFuZ7M7KsWr6iqKJ8xXreZse\/8cFpMiWUnr2zpokL77\/4Mh0lc6iTQhicu\/aGSMScQN98cc8tTvkHP1YvKrx3h93dTCtJEOgrJyC28Jj\/4T4FTaizZmVEnkJ5bcM38xUsXlM7MjfAt1lE3xZ2VX1i6sHzx3xfmZ0X1xdtRt4gNTGwCGZ8sLLkyXusrp\/fEnkwTufcud+7Mkvk3lS+YW5A7wm8XTwCMGamw7GTlX1OYm4BHXgm04ZkAUznluhhX30w5OuPaITk0fBo2DcFEOgoxdZsiCZAACcSBAFWQAAmQAAmQAAmQAAmQAAkkIQEehSThoNFkEhhfAmydBEiABEiABEiABEiABEiABJKZAI9Cknn0aPtYEmBbJEACJEACJEACJEACJEACJEACKUGARyEpMYyj1wlqJgESIAESIAESIAESIAESIAESIIHUIsCjELvxZB4JkAAJkAAJkAAJkAAJkAAJkAAJkECKEjAdhSR2DztebdzV6o3JxmFUiUl\/6hR+92Djr9uC4fa1\/Wzt2l+eTJ0+sickMLoEnFzGKT++1ji10nHw+V1tZ23a6t63qf6Zw8Feb1MsDll9bdvWrn357Zg0edt+3Xjw3ZiqJERhb+uuxlc7gk1xHILgYpFSw8EYSSevjxUBu4kxVm0Po504TLa+jj0Na2urt7w5jOajq3K2bdfzBy3OFl3NoFJjtxIGNctEShKIYrXvaWncUFu9vqlbiLjMvTitLX3Jtud3Rh2nlWFsJmg8hs9AEWYQw++phtfXMW5ueEZGVWtMj0Janq1cuxvuH5VllkI9J9vaOvssmeGTw6gSXmHKXgWpY1a47ouzcrI8Y9vl7qZ1laO4cxrbzrC11Cdwumlt5ZYWfz8DLuOU7y85Gu+B1t\/cUrlObrO0VnpOtjosnB\/LzM7KmqwVGuXI7Yl5LenrPNZ2sid2u4L6Hnv1Edfo62wLsdt5CGJrbhgYY2uApeNKIOh2ZjcxomptmLum4CUoqpaCCo14sp0+sG1fT8FdVXd9LkhvPBNg2jqcRcJqw9ithNaWmU45ApFX+5ZfbmufumDlQwuy0fl4zD34QchNB6pjDoEtRMxVx6WCM2oQiWplGBezrY3C2BEPXwCF8yBGtaeK9XYzwuasLMYvPXZHIb7z3l6fEH1e71lvHwTV5yEfkl6vlu73es9rAi6Z85EMDj4v\/ukloRYaAgqDS6qULH\/W6xtSKSGT\/bos37S2jKv+HLNKX59e3S\/A1IAGmek9q5X3oXu6YX496K92SR3mj8kAABAASURBVKaFkG3JpJPZKt\/rVx7Z1IBaPxPYpjDqgsk8VViPtXxFXs8xv2VMn39b+Wy5VkuTYI+03N+ELKhVV72WyUDXBCCc9QaGUl1FHJovdeo08IbO9g2JgXMgFhgsgV6c9SogsoBG18EktKEFVUVB0DL0yClfv8y3JCKgpp9pnvhtxyTBgmB2Z4fZojRg3vlr+mej4wS2zB+U9+JwdqAX81P6kd9lnPL97ZintJ6HKporSVPPmpZH\/bKQJskm9LQsBpdUKb2uv3V42bkBMdQHCEE+qIw3agmRXVx+28LpGVCCS9JZQoDgUnCQ7ermycIKssyEWmmGeX0w1cyYft2t5aVyLRERCsMSXX+gul7FyEAZaa2WtjRq7bvfSFTpj2LZ11RqS7S\/I6io2tIFqVBf6lVhFSszVEmVYxurYqZxlOOq31n0Cpi9gRmJ7mBqGWpjxBg0+lBv07ps3zpPUHIiBTm79CknB1eb0n4Bg46JrdOQmeahDxopydY0buflDUsWCL2dwZMxppqz64otb8GDDvOCdk3+hpAfaE9mBs9Y5AQtTXobqCWHO9CpoHxNoeymhGCabKqQfd1ga1VJGcOAkx09U6fP+C+9mlqZJ2dbSN+lWtiD8kF+ocoL81IpeWp3f\/8103uoGRg7w3FQEAVM+qEKHGQ3ccm8EsIMbWikVfqs0Er4I5WvdiP+PNktaLO4mypp6nugOKXUI6CG25hRpg5Kh8L0MC75zp\/sOC3yrixwS8eO\/i5s1WNqIiAqM8yzTubAv4wi0i\/8XiRnu3\/dkAUypvv3\/NLvpPuoRs36ZDn9Fql5ipbWI9lWiNdYfE0vKt+kconFakbgUQIKA23DhbF6SKtk5aBXqIagy0jItsyjIJ32rLZ7BBCoNRDZtmKbCa1GMClBf3WbkSmtVU3reUYNnaEsEMgzJCgJWmS0DkpWWglgQV80jVK5ka9dNA2ilpZDGTIo6kqoHuTIWYmnWHMVrXXzvU9V1+KYmwvql6YCjdp2x5SvlRvlaOyOQtpf2dj0juh5Y+vGpzbuOi675X29sb6meu0TGzduqK3e0NS8d1P99jZ54f2m9TW165\/auHF9bfW6ne143JC5+qvvzS2r69fv\/H\/hz30tW2trH1+\/8an1q2trN71q932T8yde3lBduwFNrK2uWbvzmNR14tdr67c2S0mpPL5j7ab9nWYS3fs2rdmmmaJKtG1bs2mfVC+Fxl9sqq2p37Rfpn3vNm2sqV4N\/U89XlvX2HJkW\/3TWkEhel5vXFuj9WLD6uq6TQff11RJzZsbt9av\/sHGjU+sra2pbXzTb4ivY\/+PalV31tZWr90h+x3ZVCGcMHbv31S\/pbGxfvXjT21cD5Iw77xmA5YBw+yNq2vrG5vtvj\/ftl3voxSeb1xftxoDt35tde0PD3Z+0LzFr7YWA6TUyq5tO\/jaltq6xzEia1dX1\/7oYKd+\/NTXvgP8V2NM13+vWo5poMrWHTvqq+vqt\/2x+\/DzW2FJx56NG59qPPwBFkRv8\/P11bVrZa3V1ev3NDc9jWKyCxaTMHn0hoa8bWioDlNiIxoKGDDU0\/z82urQfKmMryQj4Ht3\/6a62tVPbIQHGU4t+\/D+wU11lbXrtfzq2k0HOmWmEJbZUjuMCWw7fz443PjT5h7R0fTUxo3PH8ZyIBvCsuCUD2uGOg\/+qLZSzsP1a2srA\/NT+s5m+2UBtRA+OLCpfvNhfalo3\/F4ff1PW5AtQ2sjVrNe1U20fnzXxj0d4mzzVlj1SrssIMT7e9bXfm+j9Moa+JGORa4P2norBYeFQlWXsa+j6cnq6u9Jz3q8DqtWs39JtOINOKOspl5y2VTLokRkWkwChYcCzv746tqNu0\/pfTX6pTQJIa3VzBahtwlr32W7xnI9SmtpYPn9weraJ5tOGZsqv8Hq\/cOTL6+vlbeD9WtNC6CQFioyWrHuff4lru\/NxtpabcF8vLb2Rwcxu0AiMnPbiQrVoazwqYRNEyg6YYLjlJaDYkwb4Og7thODJhcc3Mqr9V1E2y\/q1\/9a\/+MM76ub6tc8se80yiJ07\/vh2l3vhNzOcOVci+3tGFdUCB10666pGzsT444pKwWmn3kTFbIEifMnm0J2F7J+WAj6zHSoG2qtVKheMACrkPfotqf0zZ4tQ5SVC8JPd26qqzY2TsiUwbQgrA+++8urpleP3ZYjsEqokn\/0b8yGOpuwIcQ94qn1tdgQHpfLTKCwxOuwDscAoS\/yvlRZxXjsCIxaSyYPWl1X3\/h64E9O+042hW5U2l\/Rdrl7N6k9gzH3pOBwF7bVY+3PUM\/hzbW135ebHzxWBG1+sCvwl5atON09cYPZru\/5ZTEHY+yfa4TdnLfzNb8heJfL7Muv2d0WpRuaV7k++8cH6BDC4caqXdMiB3qy9cbnjX2R3C72HNmCxxq5TVpdq56\/oCDcKofLzstUGIaBRdthzyD3KsYGD3fq1zdjYOQjqmmyPR68DYMtKsgVVY24yTbLnko46LHebpweY1VLWhxVcw6Lp5MZ6PHYL6HmAwCtZ6MWFS6tWHKlyJp7f0VFRflVQpxu2rTjRO6SiprKiorKmlXXvr\/rVf370M279\/vmrqhCuarHFk1p3qX2gcqw95t++LNTly9dedfnMsT7+5r+ePniKhSsqrm7qOeVJtPhhSoteo4c9N30mGyiqqZiSU7r1oaDPaLgCyWet187rLfW13yoJWd2WZ5eI+Jbz4mewvtr6lYtzIb7N\/7b\/oE5K6QJFVVVd2Xte0V\/9kDvGn7RVfgNdaWmYmFm04+3tevnAh1nsu+q0npdseTy9p+pU5m+lucb9l20aJWsUVXz2NKcti2bX\/VGNtUZo+zJe2ey79Y0VlWUf7p920+1A6C+FrPZj92RdXCP32xZx+bV0+G77l\/AGZ1cXvS3XRs3tMx4UKl9sMzVvHOvviMUon1f64yHtCs11StKzu9q2C419xxo2NKWs\/jRGqioqq5YnN265ScYB9XQyQ5XeUVt3V2fyy677\/6yLDH9Zgz8irJs0b1n0863c\/VaVavK3t9l1BFw0YBJK0p8+7dou1JUaXynYLk0oKKq+sFSGPAL+XMn3Xsadp4u9OdXLLqoSRkGPQxJRkDO3n2ZC1dJp66sqbolp3Xr5oM4yxtq3\/bjXb3XaM5YWVNzX0nv7oZt2pErOjjCCWw\/f7LLVnxDTtglmLD3YcKiHS045cM9tjfsOl+imVhldhCtmu2yoF1BdOms4ktOnlQ\/t3Hq+MlMj+dku3Qt6Gw\/kfvZwsBfsl1VXnHzdJFVJtfZpYVC\/us5NXTdt+B7cN\/7S3z7Gpv0ZzZ5TX\/ZLhT6Nbz1YXXa31+qWV5RVXl31v5dqnVcQzDhDTgj8m2DbWF4bsDZK1fOOb3rsL4+2+qQmTa3Cbu+n+jRl+tRWUuDlt+qlXPe3\/Ward09zYd8S75luwDKvoS8Ovftbrt8iVa+6u6iM7uaWq1FHDDaL3Q2rETkJqxNplQ6\/JQ23eV7DjZsbc1RG5WqwC6iuLjAe7JdO6Lqazve5ZnqPX5cewo6237cW1h8ZbbldibhWbxsu\/80U17Dy2ZErLsmlBLGHdN5E5VtWZr6WrZvPpzp311ULy94Z0vDAUzU8BBkY3JXal\/XxlpVQcYwwL8Kyc2eA0NZErfyk2ekiz6i\/b2AysKJZ9i7v78U3u23HLhgH97Ys1+uY1iyqx670dP86wPaCJrL2q7DTgDtIESxLzW3N5oydY82gWAPemxZ1qtN+p2xr2Xbs4czb9Q3KjXfKDihPX0ULvXvcs17BmWmZX3wb9dt9agagfj4vrYZD8kbRsjmJ1DGJNndEUyXIdoac7rJ\/rnGds5H9rUwt8XAKhf28SGMBvRBrl7O9Ez7ouV4fty4vnXGg5XYJ1XVPFDmfmNn07vQYOfgyPaHoH1LyEOKcGBoevK13zPIvcrxZu1pDS31HX3zZK58RA2ebCHbMBQ1hyDbgvZUjnqstxun4TY345fDNWd\/B3E0I5pHe3+zcXsfu6MQi8ndLS09+Qtuu0bfw3uuuW3BFXqRaZ6MnmMHW973CZFRen\/dyhu0r1bj4vmjW358OHPh8rtUrSkej+tUy4GTPSiYX15Ru0xt\/FEwEGYuKM\/PUEnPNYvnXdrZ\/Hq3uKys9JOdbUexFRD4+PS1k\/lz5mapMlHEnpIbyrLdWsHjLe0XlS69MU+l3JctWqoMw40cvbuybNFl6orwzJ5fMrmtRT3JiPzSL+Zq9ZFfPH2opwcPcqK95VhmyfwSjxqQKcXL\/qVi2eczI5oaBqNs4orSeZ+U78LlKfn8dNHTIzdrzmZrRW0iT\/H84ilavjt\/zueyRH5xqRo3V+68ufnet9WOUAiRVXZTaZbqgjtv0Y3FvjdfbxPdza935i+8rUSv4in5xwX57zU363uQ\/LIbC\/ReQ0EgdB9t7bHW0s+SZCGTSXmlRVneHoymVuXaBfp4uHIXPFCxcgHOuGR+wbxF\/nwPOE\/+Y4t+x5LK+EoeAnL2lsyfrSaTyPjcsm+tWlZysRB\/fL1lcmmQM86e3HJEPx01zZbhTGBMxXjMn7bX35xcWu6fh3CQ8tLJ0kEUfNtlQV1CnD2rKKvjpDxz7G5v98wuv8Zz8vgp5HccP+GZcVX45csz64vFGSgrhPuy0uJLet4PPQqxXSi0KlokV6cgy2\/WvVm7Kkx4DWdUV2xiu8LSQ8M4u40WIRxvE0GlTct1pGV\/GGtphComSwpuKM9XS6jLU3LTvNzAAmgqFBA9no+JU2\/ul\/c2V355Rd2yosA1JTlhtJ2odqwiN6EaStE4\/JQOTJvu15s7r1hwm\/\/Orm1UtF1EUXHBBx0n+oQYaj\/eWbj4H6Z3Hm9Dqu9Ye2d+QYHLDpvFy7q79HugXjbKEQncMaOefugselSi32fdeQuuze98q82r7TrC+LVml1PdKK2VOhwZyovC8\/kF\/h2VlpZR9AtC6JbjdX3Rl3pCXlM9GWfbD77Z6RsSGXNX1K0MOn\/RStuuw7FAmOKJvC\/VWmKU\/AQwMTLtPQgblYtLbvCvG+7LFpRd0dnSKjfgjr22rA\/Gdj0aPZeULZmrbwPwJLKoyGdsfmybs7sjBBe0M0YuOLbPNVM8NnM+sq8J59uiscqFf3wIo0HrTrhRMO2L8ucUZ4npnyvVV8hPziu9wntCPtZ4wt6IIy1TTgwdnnyF8Q97lUtPtrTgfiIfUV8\/mVs4C4PrPNmMigEhjG3R6nEc7kArhhS+uRjvPlM8NtPJaGp0BNs79ug0Fay1q7tHpGeqDbp2JSP3Uv3xJv+rK+8q7tv349rKmvqNO5p7\/A\/APUf2t19y3bJ5uVp5IaaWLX940bS2betrqms3bNl\/Ups3+jX9LetSf2GZkZU1VeAWKERW6Zz8ziPyt8d7\/tDSVVRWkiEvR\/dyZ\/gLd3edEekZmaZquZ\/UT21k707uqg\/8a2wTmZNxZCMLTzZ3W2bgJXUFNCPDPcXjmYIN\/u0pAAAQAElEQVSTlAimyobSzfoCGKFEBF2SGXjJphzMxlXb4Db1cjKmjCvwY4sZmZOFf4CEyMm51KQgK8sz5POJru4PRFCfZZ3ubv15LOiKqbLsWdC1jNycqYHrZpP8uSFV0j0eDxjK\/BO\/DgxG\/fNt4iL\/aPgr8z0pCITMXnfGVE+GW3T\/tUsEz+pMmdupHjbMs2U4E7hHxGH+dHd2DbmN1UPSzshwD3XpJga7iLwa\/Mr+bIGQZ449bcfFjKsKZhW523GrPt3e7iooMDtdcC0tFdyolmWN7BaKQBkJPVjJp\/wrnVbIbVoftIxwkV1h6aFhnN1WXb7DbSK4sNsEPKs07LIvjQjikJHrvyVJnUGXZAZeEaqghB6yPmkeIyyMwmdaNvVCpjdP2TdWLpratm1DdXXt+i37bO5tbhvm0hzbiWrHKnITJntSTuzGzdttmhtCBE3pwKWu090iaOgzMtNF9+ku4Sq4Kr\/j+HEhjrefuqKg8PPFBR3H24dE+\/GO\/JkF9ryC9IQWiXJEAo4ix1vXqbQFz1iVh1h2tufwvwXugOv3dePG2CfzAz1FwWAIMkPIMnZ1RZTWSiWODOVF4XaYyYF+olhG0N0fGf6QY7fl8F8Mfb+yfOXXZ\/Xtb6itrq5\/cmfzB6ElgprVL8cEIYp9qa6Wb8lOQE4Mt+0yIq+cPdxg8rn9ms+F63GQL+sFo9WTnaM\/e2j1pmV5xJD+vKFlWCO7O0JwGTtj5IJj+1xjO+cj+1qY26LhhuEfH8JokN0JS888cJPdeK4xP9akq0fF8Kuc5GEYKtuzLFNODIPyM4K2GVILXlnXFOeePHK4Rwg8onZeOacUJyGyM2abLfcs1DIHZ9ui1iNV2A63uR1dlmXtUcjm7O4gMt+hO7bTSW9otN4w\/qOlOrzenEuzxVn5Ub6\/WF\/nX\/wnpi5PwXV3rayqqfnWbfkdOzdpf\/uAYlmzF5f2NzW8FNgXurNLyh+oqKmpemiuOPDM1uaQw5Ced+XHNqirBfkpTKZ2bpBxTVlxb\/Ph4x0Hj3hLvmC\/cRkwnvDPev2WaWr8UfYncoS354xRTIiO97rVRdm7vAUrK\/z\/Hl314DcfXDxTXbSLs3NzXL4+k\/3yN2POy7UsvKmyISeMdu0gL4zZuDqy0NkhP6n26zj9fk86bhM52ZcI7wdwan++PO3OzbvMn7R\/D6l1vrNTfn3GvrSWK6sM9Jog9qsfhZL5eQsDo1HxyIMPPrjY5jtEmhZGiUxAzt7+vt6AifKHo\/p8QuYHO+OZHq\/7U3nm\/UGgkqPkOIHjMH+kj3vNS578llZ6brQmXlZc2H+8\/d22tvPy7CO7oMDXerT9+HHfzOI8x+7E6UKo5R3v6itdfFqQHhq0RFicfWjAaOfMWf9i7HCbMEqGCnFfS6Nefns63jGtS6e7uoS6EUkbtdN5KQiBOasEIdzZJUsfrKiuq3qgTBxs2HrEVN1fJORdYrSfqLashtNESJvjmTGCtqOe0iFD3NNzVuTmwecyiq7KO9He3v5Wey7OPlwFM\/LaW1rb20\/mFV7t\/7QkVgNjHJEQ20ybKHPTsrOekjv9u5GKilUPP\/jgnaXZMj94RQr1a1nGri70R21tiJ0GQ2ixDXImh1sQApVsV2ztsmnR8BqLhhCeGfPveriqpvqx2\/JP7Wx4WX7RTiseLooRAsCE35eGa4vXkoiAnBj2HiQ3JBeX3G3yuZXffPDuuTHuR4S2sYlGz3sd5pncebon8JRpcoSR3D0xLNKRHZ5rbOd8JF8Ld1tEc1oIWQqCHh8iaIjDKKBjjjfiENss+xatA5ZIMozikc0ze07+6baWnu7mN7qK55bIO4rzZLM0oSWdbYtajzTVYbi1JsxR+Obs7iBhzQD1MV5CXebejIHsO69vZLO\/UJp\/el\/jng5tI+jr2Ld5\/2l8gA8TvAd\/WFn\/i5M+IdxTcrOz3IFPz6ZMX3zf0mktDT\/c3Yly4u2dtVUNh6HP5c76dHbmED5ok9lBr3eath7qhiox5G1\/aet+b0HZbI8s4CoovSaz7Zfb2kRhcegzeXZeXkb7wd0dqmLbKwe19mS9oNdVZaWZLTt\/1iL\/QkcIb+u2l97Sn9Gy0bt3mrbpP6Hk69j9hPzZm6DKlkThNZ8bOLxzl9ak8HUf3Pz4+pclA4FPn0qdTZUN2WO06Dclnc02FRqe6G1+8eV2jIhAFw43vNieNfe6ApE9b25+58Edh7VxEP0duzY3nblqfonpKx7mxnrPqU2\/Vuu3jU2n5CAIX8f+Lfs7080FQ+XskmtyT+7e1qwZILztO5+ob5B\/ui9VBfJ9HbuerN+4Tw5pz+tNB0+p5kK1MSchCVx1TfHA4R2v+B3lwObVG14+gTmizepdv2z3yqNJX8+RLdtas8q+aH\/K6dwxxwlsO380Pb2957V3axSaX1g2O7PlFb+D9DRv+VlL1rVwEGtNh3Re8VXelhdbvOrs43J5MrKnxVtYjKeykBr9H2ocQvKHmaFZ\/tI2\/0rXtu2XrfpKN0yFlmrSQzsdnD3vityeI3uUU\/u69+95E4ON6s63iTB9D7vsD2Mtjb7KyT1b9QXQ2\/7y8\/u9M8u0BTAv\/1M9zeicNmm79+1p6UfXEE7urK1sOCQXMndWbvbFInATFLjqFCRGu4lqy2p4TTg1nXT50U5pbYgP7NB3Eb6OVzY39RSqP9DLKC7MO7Fnz4ncQnn2kTGrKP\/Eb\/d0fLpwlty36kD8tzM9GfbNcUSMXZOlumab7SZKFTSWIHRWHPbvLoS3ufH79dvegh8hP7Mlgl+jjG1dR2tV2+ZYs9OeobmYSZYz2WlBMBWDaLtii+wr8jLePrjrXfQRO7O2XYfk7V6WfnVT5ZqdcmPlzsjNnuaWfofsiCEWCLb70g+amw50cKsREXSyFcDEcPAgbEhcxkZFeF9vfHzttqP68h5LL6PUc655x0v65qf7UMNLx\/TNT8x3z7CmSUe2fa6xm\/PeKHzN4bZoNkJbCg46Pj5E0BAlPXODQXL4VU6zzWHfEqTGlJAMo3lkyygpK+pq\/sVLr2OLp3+I7jzZTPr9YhjbIugxbjfSVNvh9rdheg\/fnO0dxNkMu+lkamtURNeoaHVQWjCnJKOlobKycsubQkwpveOeMvdrm6qrkFG77a\/XLJ6jHVIIT9k\/lued3FxdVV1dVftyz6zyG\/IC+qYU3\/WN+eLApvU4p7hy0R3zfE1rKqurqyt\/2JJ146JS0xZEVcm6dlHBHxtq0UJVfeMfPQv+z2X6H80LkXdtac4HPR75azSqrCl2FSy5o3QybEPF6vUHc4vtn6hceYuXl+e9t2NtNcpVrv9dztIbp+tappTefd+8gaa10riq6oZjOeXLF+eFhV1wy0Pll7Y31FRW11RXP3FQXL98WZHen3CmOmLUDbF5s5qdteQGv9k2pWPKKlh0k9izTtKo3rDLW7hsxQ3yFDxjzt0rysT+JzRMtQ3tl5Y\/dHuh3rcg9dmz5uT3vFJbWbm26bTImHPH8rnuwz9WtbZ1zl6s\/0BJUJWgRNa85cvnDOxZKxlWrmk8dcVd9wcM8OfXSANW3IRJ1Xl43\/59r+ubpCBFTCQsAVfBbQ+U5xxrkOsDHOVVseAby+Rkwqz+5rLLTzbWy\/Wkev2\/D5Tec\/8C818lRNWjMBM4dP4Icems0vyeXXWVleuagr4l4ZCfd9ODy\/JONK7RHGT9noE5y9X8jMo0LFkz87ve78qfiamLGnkzpnd1fpA\/43LIwWEG1tmjDeDwbEvwheGn8m5aUX5Zh77SbTiYddOCeC0ZyqYwzp517bLFV3S+XC+h1T7bU3hNllbF4TYRqe9xXkujXX6zym4saNNuRJX1jW2eBctvL9YWwKyyf1p8+Xsva5O2dnNPYcklWudE\/qI75vv21mu3j00tUxctmq0VVxedY22lDZ2otqyG2YRz40l2xTKlc8oX2U9p7VYu\/kO7e6lb+QPagoPuZhQWfLyz8+MFcv0RImNmQc77nZkzVAqXg25nSEcK9iNSAG82dk0WFWGmX\/ASpK08+u6icq1cee6YI2dUNBAc6tpbazFQT4ZhqJewvoVZEIKLFixa6Nu1Ti4O1aYth5ix5I45kw\/\/SNs8bDiY+zl9B+eZe1v5ZSc2V8OxKmt\/eWbWVxeoxTRYp00qBgh2+9LO1\/bv38+thg3YZM+yeFDgzqg2JPpGBTtabEjuKJ0Se3ej1DNj0SLfLu1JpHr9bm\/R7SvU5ie2u2dE6zRHtnmusZvzUfhaVll54XGb22KQHdpNzenxwenG6tcQJT1\/8ZD3CKtc1MuUSXGYRdtUCmJBaYnv7ZPimlJ98cIOMJZtWBjbHCetEEG3G6fhhnEhIWxz2PdGvvsEfMduOoU0GOeMsE\/ncW5LZMwoX1ldh393fU6qzshfsKKyrq66pqauZtXtJYU3rqr7erG8cEnJskdq6qofe6y6rmZleYG2fBR\/vU7+py24\/MkFK2trVi7Mc4uM\/IUrqmrrqv61qq6mYrnxGyJC\/yer3FhStryipramCqoqls+\/zK1fw9uHXq8r3+kHUzPyFz9YrdlWW7Vi3qK76lZpK0uxX0B9LShTa2pqYMZ987P6vCIjU24xhHBfNh8t11VVVaF7K5fpe9xLF6yqu0vrpFZdmBS6skpuXwlTH\/tWlbU7EUxdYIsxe6Gfp2rqc3fVGT\/SHmT2gvy5pkuqsBCS3kJ5kGEI6ko4tUJkatxqKqvQkZVLC\/VfIRLuvOskjJrqmjqM3e0l+k+rWmmI7GtlsTqdtj6+slbNqmXXFC56pE7NHGeTUEVqqAJDNLS0QI0FRkMZUPVYlcmA3EWr6qqW5qt+MU4aApi9K7X1QXOUsk\/6DfcUliO\/Ft4oHWiB\/\/eSnWeLVtHsF5EmcPD8QfVsubxgRdM8y9SQQ77LU7gUPl6nTemK5Qv9JlodQS0L0B8cZtyGteS2GXpmwT8Cwm3GbTLQekaB5ACr5HJqUZW9wO9EhiMbgq43GIieKVenVWi9prqurnLFgvxSYyUMtKsVtWqTmQEbnAvDc+VirpEJcnbhyir9eoVquuaR8vlf9S9rmAYhtwkRru\/SFBHvtdTxLqa1pkWy+4uu0WZKtVwYcSPC3Uu7JMQlpXdpncOCuWrp\/HL\/6OhqKx+rqsW9rSzXheJSj3YbCizOyEUwMddXWutEtWNl1wSUTZgQPKXnfxw370zt5h3grFjot3KsK7V1NcatXF7zlD1QV\/dAmfoMR0wte7Cu7sF5egrXs023M9MY4YoQdl5mOyJBuybrQoE9kP3dX4igJUj4Vx45MTChjJUnGggOdW2t1fqmRcEddGJY\/HX\/vk6rZIqcFwSjkEajdGY5dpUhW46M\/JsexK5MrieVK8puvEvf\/Pj7+9i\/YvFcWT5TbhACQ6MpdNieeQq1pdsC0A6Cbrl5X5r7ZWw1yrnVMIYudQT\/jAq9Mwq1IanBM4B5QxK4BQOCMfcMAZkymN3HXo8spV5a3dIC+JjoLQAAEABJREFUOT9rqiq1iV3kX4ViuXsazqgpNPmByRjdkdEn3JIDi6HNnMeNu+R2uWcw+5oy2Ijd6vZnuS1a3VC\/qUlfxq7eeHzQnp7sb6xmDfb0LIt80KDAPAOFnYPjuhH0jkvbgh9SwjDUdVbXAGHQk6+hVQmXL66oq6u4yXRa6zjZAt0xLBe4OSx03FOpoQmdtEG3G+HwGKvM0+LomrNfPI0ZEmKGTtW8hGqtjWLkGkXdUapOd7ttS7ozMuwvWEu7p0Qq53JnhPxtRfvvmnuLIv1garo7rOr2bTXVW17vE263\/NEd0dd2vNOTl+dfhDQ79UuaHFXkzgjpTjxMtWs7ZtvslNjluafYD507PSxOO1XIG0YtpykxDFUwgGEMCUTdlNP64HKHd9poGojvBA5tMWnnodsdspCG9m4kOc5kHJp2mgYORozWWprujmppS8\/Q7hQhxmHO2t6KncqHKLBk2GO0ZTXcJiwtJl2y\/WfV1Zub5c1bm9Lyf36Zmpc31bkfTmPkXGOYV4YxIunuqKafEJaJERMES129dzFZGztD+0b1tgNvMa7YNrusgK6wkr09dhCcNiFh1fNikhJwuD2hN\/HYkECNiEqP08R2MM\/2jiAbi\/RycGS7Oe9kkqkJO\/cxXdZFe9dTFyNqiIqe0mUXR9IfzjY7fTIv3R3loi0LB70cRjOoTCDhbFvUehyGO9CGSXJuznr38VdyNMNuOvkrxfvdFW+FSaKvr\/lga2aJww+mRt2HgiXlBad+sXptQ2Pj840N61a\/\/EFJ0J\/zRK0oXMH4mBquBV4bbwJsnwRIYPQJcC0dfcbJ0kLBV5YW\/GXn6nUNuHc3Nqxd\/cvukqj\/XCJZ+hjRTkKIiIgFSIAESIAEUpvARD0K6Z1W\/E93LbhspIOb8bllVVUrFs\/K9VyUXfjlFTWryo0\/yRipaqN+nEw19I2WMLVw0dIy03e5IrbDAiSQSAQ4gRNpNEbFlmRZS0el81QaTGBK8bLHalZ8uTjXk5l91eIVVRXlM+SfSwQXSvUUIaT6CLN\/JJCQBPLKli4qDPMtvIQ0mkalKoGJehSSlV9SlBufjU96bsE18xcvXVA6M9f+y89Bcyf2RBxNjb3xGGpk5BZek58VQwUWJYFEIsAJnEijMSq2JMtaOiqdp9IQAi537syS+TeVL5hbkKv9mUxIiQmQQQgTYJDZRRJIMAJZ+dcUxukZLMF6RnOSkMDYHIUkIRiaTAIkQAIkQAIkQAIkQAIkQAIkQAIkECOBpCjOo5CkGCYaSQIkQAIkQAIkQAIkQAIkQAIkkLgEaFlyEeBRSHKNF60lARIgARIgARIgARIgARIggUQhQDtIIEkJ8CgkSQeOZpMACZAACZAACZAACZAACYwPAbZKAiSQ7AR4FJLsI0j7SYAESIAESIAESIAESGAsCLANOwIdB5\/f1XbW7sqo5XlbdzW+2jFq6oMVn96\/qb7h8Nh2MNgCpkhgVAjwKGRUsFIpCZDAGBLoblpXueXN2Bt8c0vluqbu2OuxBgmQAAmQwIQiwM6SgJVA0Bai52RrW2eftciopvs629pO9kRoIsjICGUtl1uerVy729gifSwze1rWRZYiTJJA0hPgUUjSDyE7QAITjYDvvNd71tvn0\/vt83r7hsTAOZnpGxKi3+s9j2u+vrNGES3zrNfbL6vI8tp177kBMdQHVVp5eUkI1PLrURl6rPI1hb4+r1erfzZggyyFfHOLMosvEiABEkhiAjSdBEjAngDu+DZbiKDNhqoodyzYewxh64Gdg8qzKebfuvgLQL\/cafiTqI49jMrRNzn+S\/q+RdufGHlKgBIbI9V+xiv3S6qYilEYTcjtk0zD7F7Yi\/2O2upkzyq\/ddH0DFyS1WVdmIHy6BryTAEVsa3SrPGXNF2lSAKJRoBHIYk2IrSHBEggDIG+lq21tY+v3\/jU+tW1tZtexecV3Yef39p8VnTs2bjxqcbDH4ju\/Zvqn9+xc0117ZptbdA05G1+vr66du36pzauX129fk9z09P12\/4oxPFdG\/d0iLPNW5\/auPGVdhTsO9m0qa529RMbNz6xtrpm7c5j+uc7vnebNtZUr96wceNTj9fWNbYc2Vb\/9L5u4T38bP36VwLfTe050FC\/oxU7B6hiIAESSF4CtJwESIAEIhAI2UKg\/Pt71td+D1uF9WtrsNnoRA5C2\/b6TT\/duamuWts5CDHUefBHtZV1chuztray9kcHO\/ERjtC2LtvlngVVZPij2mlI0ft6Y31N9donNm7cUFu9oal576Z6o+S5lsb61Y8\/tXH9+tpq7E\/Oy\/KBV4iRTvucvjcba2tXy23S47UwCVur9lc2Nr0jet7YuvGpjbuOw759m9SeSrRtW7Op8XmbngpfR9OT1dXfQ9c2Pl5X2\/hmM0pitxSwhxIJJB4BHoUk3pjQIhIgAScC7+9r+uPli6uqKiqqau4u6nmlqU1kl913f1mWmH5zRUXFirJsIf+d7BBfrairu6sYt+89m3a+nbv40RpZp2pV2fu7Dqrvk15VXnHzdJFVdj\/qLS0UfS3bnj2ceeOqmsqKisqamm8UnNjaIEv2tTT+2\/6BOStkmxVVVXdl7dPOTYTIKp2T7339cLu2iRGi4+CRruK5JRmyeb5IIPkI0GISIAESIIFoCVi2ELJaz6mh676FrQa2CveX+PY1Np2WuXj1nDxTeH9N3SMLsENp396w63yJtqWoqqleUXJ+V8N2+WEMitmH002bdpzIXVKhNierrn1\/16tqE6MVf+9M9t1ye4JX+afbt21v0XL9kcXIPod9jujct7vt8iVqm3R30ZldTa2icGnFkitF1ly5RSq\/yq9Qf7f0dMvL7+JCX8vzDfv7S7WuVVRV3p21f1fYjqEKAwmMPwEehYz\/GNACEiCBaAlM8Xhcp1oOnOzxCZFfXlG7rNC2Zn7Zohke7Ur30dae\/IW3laiUy1Pyjwvy9cML7boRHW9pv7jkhmtUOeG+bEHZFZ0trV6B\/ItKl96Y59ZKui9btNRfJuOasmLR1oJPS3Dp+OFmUVI6ExJDMhGgrSRAAiRAAiQQDwKeWV8sVh+HuC8rLb6k533\/UYjn8wvKstUmou31NyeXli\/ybynyFpWXTn7zddO3QayGdLe09OQvuM2\/8fBcc9uCK0xlriid90kt6fKUfH666O7q1lL2EfYztvsc4fF8TJx6c7\/cWrmwtapbVmSvwJ9r6am3Rx7OtLccywzq2s0l+o7KX43vJJCABHgUkoCDQpNIgAQcCEwtW\/7womlt29bXVNdu2LL\/pP43LNbS6ZlqOyJEV3ePmGykUC4jN2cq3qyhu+uMOHu4od74t35\/t8ct+mR+ekamqXjuJ\/G5jpZ2FZRek9lyqBlGtL\/RljO7LE\/LTvyIFpIACZAACZAACcSVgDvDv\/OwqHUbm4juzq4hd1CxjAz3UFen8wGG3MQEtjRQnJF7qemEIegSroYLcj9jt88RwlP2jZWLprZt21BdXbt+yz6nrZWhPLgLKrsbu6jg\/E8ZuyVVgjEJJCIBHoUk4qjQJhIgAScC7uyS8gcqamqqHporDjyzVZ5DOBWV+TnZlwjvB\/IDC5nC63xnp93\/Bpf9iRxxccndFca\/VSu\/+eDdc7NlvrfnjOmLJB3vBfYsedeW5r79WvPp5oN\/zJszNwvqGUiABEiABEiABEjAhkB2bo7Lq32Hwn+xp8ebnpunPmEZGvDnCu9Zr5JzLs0WZ801+jr\/ol9SBaKP5X7Gbp8jNbizS5Y+WFFdV\/VAmTjYsPUIPuKR2TG8QrvW8W5gtxSDIhYlgTElwKOQMcXNxkhgjAmkWnNv76ytajiMbYDLnfXp7Mwh4fP3sPec7Z07e97c\/M7fNjad0gr6OvZv2d+Z7q+D9\/4PveqY46qyUtfhHa90aOWE9\/XGx9duO9ovBPIzW3b+rEX+SY4Q3tZtL73Vi3p6yCqdc2Xn4a37T15RXKQ+Djp\/cv\/uFtPRi16QbyRAAiRAAiRAAilFwNhCRNurwrLZmS2vvNyObYwQvp7mLT9rybr2ugIhsq\/Iy3j74K53tT2It23XoU6lMvsLpfmn9zXu6ZD\/aYvwdezbvP+0+lsbdT2K2DAS+xnbfY44ubO2suGQtMmdlZt9sRBqXwQLz8vMKNpAEa1rL23z75batv2yVd8tcV8EPAyJSoBHIYk6MrRrBARYNWUJXLnojnm+pjWV1dXVlT9sybpxUak8gMieNSe\/55Xaysq1xq+UGQQy5tyxfK778I+rK\/Gvdlvn7MWlxndLZ8wpyTjaUFVZ+WyLcOUt\/uayy481VFdJ3WubBkrvuaN0ipD5y8vz3tuxVlOw\/nc5S2+cbigXIqNkbrH3A6\/xg6m+Px1sOnC4ze6LJ6ZaFEmABEiABEiABJKZgHkLEXU\/8m56cFneicY12JFUVq\/fMzBn+f03ZMvaM5bcMWfy4R9pW40NB3M\/h+MRmS2mlN5xT5n7tU3V2KtU1m7rKSufY2xitALhI7ORTvsckb\/ojvm+vfVya1W1qWXqokWz5daqAFuklgYYuuXN8G3oV\/NuWlF+WYe+W9pwMKd8kdotcV+kA+JbQhLgUUhCDsuwjGIlEpgABDLyF66oqq2r+tequpqK5fNyVZezr11eUVNXV7dqwaUie+Gquq8Xq3wt1qvUVNfU1axadk3hokfq7vqculJQvlJW08t7CmWypqpK070gX24FZLlLSpY9gro1NWj3vvlZfV6REfj1kT6v1zc18IOp7mvuqqtdUWb3cyRSFV8kQAIkQAIkQAIpQCDDvIUovkvbgfi7lb3Av9Mo\/nrdqoXaYYe65vIULl2J7YS2J6lYvtDYamTk3\/Sgnl+5ouzGu9T\/OINKGfkLVlTW1VXXYCOyammh8HrVb3JYdzufC1RBLT0EGSmEx36fozdR+VhVLbZWZbna02HGjPKV1dhZaVumSxesqpP\/K58Qjj0VrqyS21fByBrUqlwx\/+PYLWVit8R9kT4WfEtIAtpkT0jLojSKxUiABCYgAfcUd6y9dqdHV8XldgcVbN9WU73l9T6BbLle9rUd7\/Tk5fk\/lOk5\/NrJXP5gaqyDwfIkQAIkQAIkMIEJOO1JrPlnD26sXLvrfSHS3XJvMtRx\/P\/15V1x+YjIWfc5fmXpGW65z\/EnY3xv\/1l19eZmuVtKlzX7jrV3Ts3L4ydDEgZf8SYQP30jmPLxM4KaSIAESCBRCRQsKS849YvVaxsaG59vbFi3+uUPSspv8P9fMe8ePHw6nz+YmqhjR7tIgARIgARIIJkJTC0rv859+MnajZuxCdmycfWmox9ftET7A5ZE61XBV5YW\/GXn6nUN2Cw1Nqxd\/cvukq8u8O+WEs3Y5LSHVo8CgTE9Cvmwt7\/rzIfvnj7LQAIkMKoE\/vqB13v+o1FYMSaiyozPLauqWrF4Vq7nouzCL6+oWVVe4P\/TmT53\/g13Ly3xJyciHfaZBJKQAHcjo3oDonISMAhwNzLyBfTkO1oAABAASURBVDL3hpVVj9wxf0Z2pidv\/u2rHru\/zPT3NiNXHz8NU4qXPVaz4svFuZ7M7KsWr6iqKJ8Rj+1R\/AykJhIIJTB2RyHYefT2DQwM+n+VONQW5pAACcSJgG\/wwvm+AZ6GxAmnEOm5BdfMX7x0QenMXPPXRzM+WVhyZVbcWqEiEiCB0SfA3cjoM2YLJKAT4G5EBxHrW3B5d1Z+4dwF5TfNL8zPkn8mE3w1gVIud+7Mkvk3lS+YW5Cr\/ZlMAtlGU0jAjsDYHYWc6+3\/CAchQxfszGAeCZBAPAlcuHBhwDd4rm8gnkqpiwRIgASSnwB3I8k\/huxB0hCIbTeSNN2ioSRAAilCYOyOQvBghgUxRbCxGySQ8AQuXBADA4MJbyYNJAESIIExJcDdyJjiZmMRCaR6Ae5GUn2E2T8SSGICY3cUgqUwiTnRdBIgARIgARIggeQnwN1IQowhjSABEiABEiCB8SYwdkchYXqalibS+C+xCDgOVxoHKy3R\/jkOFi+QAAmQAAlETyBttG9wafwXKwHH0UvjYKUl2j\/HweIFEiABEkhMAuN\/FDLZPeljUy6a9vHMS6ZOYRh3AtOmTsFYXJyZ7p5kMzeQOSUjHQVQbNxNpQEggLGA+8CJEnN9oVUkQAIkIJIEARZSLKdYVLG0Mow7AWwzMBbcjYz7QERpAAYL7gMnShJ3p5kkQAIkIAnYPO7K7LF6pU+elJkx+SKsnZNcLlcaw7gTmORKmzTJlZE+OeOiyZPdQdMD5yAZF7kRUADFxt1UGgACGIuLJrvhROmTE\/o3xcdqRWE7JJAwBGhIUhFI527ElVh7MGwzcIPjbgQ3+qQIGCzuRpJqzaOxJEACkkDQs67MGNsXNh\/y6weutLFtlq1FIID77kWTJ012TzKXQxLP25Nc4zxnzCZRBgGXKw1OdFF60GAhn4EExoEAmySB5CTA3UhijhtucNyNJObQhFqFweJuJBQLc0iABBKZwHg+1mLRdOMYmecgCTlB5Mi4gqYHcia5gnIS0vCJaJTLleae5Jrk4uiM0+izWRIggWQm4JJL6CQXdyMJOYjYe7hcQXc35ExyBeUkpOET0SiXdCXuRibi0LPPJJCkBMbzXoKbGRbNJAU3Ecy2fFcHyTS8JkLPk7CPaWlprkljOzxJSIkmkwAJkEAogUmT8KzN9TMUTKLkWMYGyTS8EsU62hFEII27kSAeTJAACSQ0gfE8CkloMDSOBGwJMJMESIAESIAESIAESIAESIAESCDJCfAoJMkHcGzMZyskQAIkQAIkQAIkQAIkQAIk8P+zc69djaNHAoDRFcN0T8\/k\/\/+7\/bK75ySbSfcAvslbwIS4hQFjW5dXejgKY+ta71OSVSrTIUBgKgJaIVPJpHEQIECAAAECBAgQINCFgH0SIDA5Aa2QyaXUgAgQIECAAAECBAicL2APBAgQmK6AVsh0c2tkBAgQIECAAAECnxWwPgECBAjMQEArZAZJNkQCBAgQIECAwPsClhIgQIAAgTkJaIXMKdvGSoAAAQIECOwLeE2AAAECBAjMUkArZJZpN2gCBAgQmLOAsRMgQIAAAQIE5i2gFTLv\/Bs9AQIE5iNgpAQIECBAgAABAgSeBLRCnhj8IkAgEYEf96v\/\/ceP\/\/qfP0zHCrAicJLAf\/\/9+\/e7ZSIfDMIkQIBArwKqEUUIgX4EOq1GtEJ6\/dx0MAIEzhH4835197Bab5uPd2INAgTOE9hsd3cPa92Q8xRtTYDABAVUIxNMqiGNVaDTakQrZKxpFxeBEwSmvsmP++V60zTNbuoDNT4Cwwvsdru43P68Xw8figgIECAwJoEfqpExpUMs0xbotBrRCpn2yTOP0RnlbARW66bRB5lNug10cIGn+mM7eBgCIECAwKgEVCOjSodgJi\/QXTWiFZLsySNwAgQIECBAgAABAgQIECBA4PMCqbVCPj9CWxAgMAeBLLvKs8xEgMAJAlmWXfkhQIAAAQIECIxOoMOAtEI6xLVrAgT6ESiK7GZR\/\/brzd++3ZoIEPiUwO\/fbr7e1nVV9HO1OgoBAgQIECDwkYDlfQhohfSh7BgECHQnkOfZoq5urquiyPM8MxEg8CmBIs\/rulxcV7oh3X1M2TMBAnMQiDokqpFvXxa\/fb2Z8bT45aYui8PPmFmWLa7LX98kmrbb4nZRxT334LWQ59nNopr3yfN45lTl4TPnINr5M3s92Pnh2gMBAgRaAnG\/jUe4Is+y1gJvCRA4TiCunqfrqDxudWsRIECAQFsg6pDruoyn2boqoyz5zFRMa+VyUT9Or7sh8bT\/SHRdxbdX0xrykRksFzH2uN0W7QfwIs8DLfpos2R50QufclFXVdnfn6m2M9G+rL0nQIDAuAXiXpvn2iDjTpLoRi8QF1FZuI5GnycBEpiOwNRGEs9v8YQfNYlvZooir+vHflArx8XTA39AZdlMbzdxeizqonrVCinLPJpEsTTLZirzfKrEGVLXRV1phTx7+E2AAIEPBbIsu8o+XMsKBAh8JOA6+kjIcgLnCth+sgJVVRSvHnEnO9qPBlYW+WuNPM+qfv\/5w0dhDrA8WGJqHbjIsxBrzZzn2yLP+zxJ\/FXIPE8zoyZAgAABAgQI9CPgKASmLxCPcHl8NTP9gR47wuwqa60a77MsfrVmz+ttlh0UyOJnXhDvjfYg0XsbnLxMK+RkOhsSIECAAAECBN4SMJ8AAQIECBAYr4BWyHhzIzICBAgQIJCagHgJECBAgAABAgkIaIUkkCQhEiBAgMC4BURHgAABAgQIECCQkoBWSErZEisBAgTGJCAWAgQIECBAgAABAkkKaIUkmTZBEyAwnIAjEyBAgAABAgQIECCQtoBWSNr5Ez2BvgQchwABAgQIECBAgAABAhMR0AqZSCINoxsBeyVAgAABAgQIECBAgACBqQlohUwto5cYj30QIECAAAECBAgQIECAAIHJCmiFvKTWCwIECBAgQIAAAQIECBAgQGD6Aloh08+xERIgQIAAAQIECBAgQIAAAQIvAlohLxReECBAgAABAgQIECBAgMDUBIyHwGsBrZDXJuYQIECAAAECBAgQIEAgbQHREyDwjoBWyDs4FhEgQIAAAQIECBAgkJKAWAkQIHCMgFbIMUrWIUCAAAECBAgQIDBeAZERIECAwKcEtEI+xWVlAgQIECBAgACBsQiIgwABAgQInCagFXKam60IECBAgAABAsMIOCoBAgQIECBwpoBWyJmANidAgAABAgT6EHAMAgQIECBAgMClBLRCLiVpPwQIECBA4PIC9kiAAAECBAgQIHBxAa2Qi5PaIQECBAicK2B7AgQIECBAgAABAt0JaIV0Z2vPBAgQ+JyAtQkQIECAAAECBAgQ6EFAK6QHZIcgQOA9AcsIECBAgAABAgQIECDQp4BWSJ\/ajkXgPwJeESBAgAABAgQIECBAgMAgAlohg7DP96BGToAAAQIECBAgQIAAAQIEhhXQCunD3zEIECBAgAABAgQIECBAgACBkQh02AoZyQiFQYAAAQIECBAgQIAAAQIECHQokNqutUJSy5h4CRAgQIAAAQIECBAgQGAMAmJIVkArJNnUCZwAAQIECBAgQIAAAQL9CzgigfQFtELSz6ERECBAgAABAgQIECDQtYD9EyAwIQGtkAkl01AIECBAgAABAgQIXFbA3ggQIDBFAa2QKWbVmAgQIECAAAECBM4RsC0BAgQITFpAK2TS6TU4AgQIECBAgMDxAtYkQIAAAQLzENAKmUeejZIAAQIECBB4S8B8AgQIECBAYGYCWiEzS7jhEiBAgACBZwG\/CRAgQIAAAQJzFdAKmWvmjZsAAQLzFDBqAgQIECBAgACB2Qtohcz+FABAgMAcBIyRAAECBAgQIECAAIF\/C2iF\/FvCfwkQmJ6AEREgQIAAAQIECBAgQOCVgFbIKxIzCKQuIH4CBAgQIECAAAECBAgQeFtAK+RtG0vSEhAtAQIECBAgQIAAAQIECBA4QkAr5AikMa8iNgIECBAgQIAAAQIECBAgQOAzAmm2Qj4zQusSIECAAAECBAgQIECAAAECaQp0ErVWSCesdkqAAAECBAgQIECAAAECBE4VsF23Aloh3fraOwECBAgQIECAAAECBAgcJ2AtAj0JaIX0BO0wBAgQIECAAAECBAgQOCRgHgECfQtohfQt7ngECBAgQIAAAQIECFxdMSBAgMBgAlohg9E7MAECBAgQIECAwPwEjJgAAQIEhhfQChk+ByIgQIAAAQIECExdwPgIECBAgMCIBLRCRpQMoRAgQIAAAQLTEjAaAgQIECBAYIwCWiFjzIqYCBAgQIBAygJiJ0CAAAECBAiMWkArZNTpERwBAgQIpCMgUgIECBAgQIAAgTQEtELSyJMoCRAgMFYBcREgQIAAAQIECBBITEArJLGECZcAgXEIiIIAAQIECBAgQIAAgVQFtEJSzZy4CQwh4JgECBAgQIAAAQIECBBIXkArJPkUGkD3Ao5AgAABAgQIECBAgAABAtMR0AqZTi4vPRL7I0CAAAECBAgQIECAAAECExTQCmkl1VsCBAgQIECAAAECBAh8QmC7bZpm94kNJr3qLn6uaByf4\/DC9RfXrscz57kV8teB\/YcAAQLJCTzdPdw\/ksubgEco4DoaYVKERIBAGgLL9WazbdKItfsog2KzoXEsdHCte+c6Nrh+13ukWG97O6ZWSG\/UDkSAQCcC6812u\/UI14mtnc5HIL7OVIfNJ91GSoDAxQU222a52qzW2928S5L4gioKs2eKiyOfv8Nx7iFOnoflevV48sz67AmHOHOWWiHjPE1FRYDACAXia4fVehNPcTMvPkaYGiGlIhB9kNVqu+qx+EhFRpwECBA4UqBpdsv15n65vluu7x\/GNfUaTwx\/uV6utnFnOZLOanHyrDbbOHkep7mePHdPA18GRI9\/XeWvQlx9BAikLdDsdg+rx+JjtX78Nma1fnyi85sAgaMFNg\/LzcNqvd709yepaX\/oiJ4AgRQE+o8xHmjjQe7Pu+X3GU8\/7lZxT9EH+ezp93zyhN5sT54fd8voBG167INEjrRCAsFEgEDaAnH\/eFiu\/\/jx8M\/v9yYCBD4p8PDn\/WrtXymn\/SkoegJ\/CfgPAQIECBwpoBVyJJTVCBAgQIAAAQIExiggJgIECBAg8FkBrZDPilmfAAECBAgQIDC8gAgIECBAgACBkwW0Qk6msyEBAgQIECDQt4DjESBAgAABAgTOF9AKOd\/QHggQIECAQLcC9k6AAAECBAgQIHBBAa2QC2LaFQECwwhkWVbkeVUWM5+KIg+Kt3IQC5PzuVTATzKHYbLsKpZe6kCJ7qeM6ycgrvwQIECAwOkCmWrkqRKLu2pQnO44yy2zTDVS9F+NaIVc+SFAIHWB+Oi8vam+fV38\/uvNBKbThvDb18WXm7oq8+xQOuNR92ZRf\/tyfdrOk94qZG4XVVkUh2CuQiaWxjpJj\/Gc4GPsv9zWVVVEHXbrmsatAAAM3klEQVSQyEwCBAgQOEagLHLVSNxT3qlGjmGc5zqqkThz+q9GtELmebkZNYHRCZwcUFQeN4tqUVf5vJ\/ksiyrq\/Lmuqqq9jN\/fD8TRDfXZZ7P8TM\/ZOL0uAmZsi0TDZKQiaWxzslnYOobxtjr8vHMqasy9bGInwABAkMJlEX+fEPJs4NfSQwVV9\/HzbI3q5G+Q0nneFVZPJ88oZdO1BeONMZe916NzLEsvnDe7I7AGQI2PV+grouqyLNZFx5\/KQZCVRZ12X7gD57rKr7zn69RyNRVUZXtW15Z5E8yfwHO9j\/hU5aPFLMVMHACBAicKaAaeQGMe0pVHqhGXlbwoiWgGnkGiTOn52qkXRc+x+E3gU4F7JzABQWqosjz+T7ktySDIqbWzCzLAqk1c25vgyUcWqPOsqs8dx+8ip88y\/LcdRQSJgIECJwioBrZV4sbSkz7c7x+R0A18oKT91uNKAFf5Dt\/4QAECHQhkD39dLHnZPfZfqBtv092YB0EzmYflca+htcECBD4hMBTMeJTdF+Mxr7G+69Z7fv0p9F5K2R\/WK3XzbZpml1rprfjEWjlJt7u4n\/jiU8kewK73c7VtOfhJQECBI4VUI0cKzXQeq3SI96qRgZKxceH3e1UIx8rWYPAxAXSGd6QrZBts9tum0Y3ZJSny2NmmmY\/tJgT0\/4cr0ci0OziUlJ8jCQbwiBAIDGBrWpkxBnbNo8\/+wHGnJj253g9EoFmpxoZSSqEMYSAYyYoMGQrJLhW6+16s91p74fFmKZmt3tKzU+tkM1mu15vY9GYIhXLVVw+602zXG\/iBQ4CBAgQOEHg6Za39Sl6Al2nm0TJ8ZQa1UinzJfZeVw+a9XIZSyT2otgCaQsMHArJJ7f7pfr1Vr9MaKTKG5my9Um8hJdqv2w4g4XMx+W61hhf77XAwpELuLyuX9YRcoGDMOhCRAgkLSAamSE6YsbXNzaovBQjYwwO62QIlnzqkZa4\/eWAIE0BQZuhQRa3OG+3y3\/8a\/7v\/9xZxqDQOTiz\/vVdvvTlzCRqZi2TXP3sI4VxhCnGEIgchGXT1xEkR0TAQIECJwsEB+k8XEaH6rx0Woag0DkQjUyhkT8J4a3C\/VIVlw+cRGdfAHakAABAv0LDN8K2e2ummYXD96m8QhERiIvr0\/HmBmLxhOnSEIgMhJ5eZ0scwgQIEDgeIH4II2P0\/hQNY1HIDISeXmdxJgZi3qKc9s40DECkZHIy+tkmUOAAIHRCgzfChktjcAIECBAgAABAnMUMGYCBAgQIDB1Aa2QqWfY+AgQIECAAIFjBKxDgAABAgQIzEZAK2Q2qTZQAgQIECDwWsAcAgQIECBAgMD8BLRC5pdzIyZAgAABAgQIECBAgAABAjMWGL4VUhT57aL67evN377dmsYg8PuvN7\/c1GVx4NzI82xxLVkjOlEjWV9u66osZvwhZuifEbAuAQJvCKhGxlCB7McQNzjVyD7ImF9HslQjb3y0mE2AwHgFDjzu9hlsVB6Luoyn63iWi2dv0xgEIhePSanLCGb\/ZIg+yHVdRt+qKotYZBqDQORiUVc311Vd6Ybsn60\/v\/aOAAEC7wqoRsoiH9v0dIMrF7VqZHSpeX2qVGWxUI28+yFjIQECIxQYuBUSz2\/xdB0fqVk2Qpz5hhRFYV2X1c9\/axBpqp+aIJI1qjMjWlRxHdVV2Y7KewIECBA4TiA+RVUjx1H1upZqpFfu8w6mGjnPz9YECAwgMHArJB62i1wXZIDEf3jIaHxECbK\/WpHnrTn7S8fyepZx5HlWlXn8nuXoDZoAAQLnClRl3N9UI+cydrF9WbRrjyJvz+niuPZ5gkCuGjlBzSYECAwnMHArJM8ef4Yb\/lSO3M04WlVhll3F1M2h7PVcgSzLopA\/dy+2J0CAwCwFVCNjTnv2c3BZdhXTz\/O8G4tAlqlGxpILcRAg8KHAwK2QD+N7bwXLCBAgQIAAAQIECBAgQIAAgekLXHiEWiEXBrU7AgQIECBAgAABAgQIECBwCQH76EpAK6QrWfslQIAAAQIECBAgQIAAgc8L2IJA5wJaIZ0TOwABAgQIECBAgAABAgQ+ErCcAIH+BLRC+rN2JAIECBAgQIAAAQIEfhbwjgABAgMIaIUMgO6QBAgQIECAAAEC8xYwegIECBAYUkArZEh9xyZAgAABAgQIzEnAWAkQIECAwCgEtEJGkQZBECBAgAABAtMVMDICBAgQIEBgXAJaIePKh2gIECBAgMBUBIyDAAECBAgQIDBSAa2QkSZGWAQIECCQpoCoCRAgQIAAAQIExi6gFTL2DImPAAECKQiIkQABAgQIECBAgEAyAlohyaRKoAQIjE9ARAQIECBAgAABAgQIpCegFZJezkRMYGgBxydAgAABAgQIECBAgEDCAlohCSdP6P0KOBoBAgQIECBAgAABAgQITEFAK2QKWexyDPZNgAABAgQIECBAgAABAgQmJaAVcjCdZhIgQIAAAQIECBAgQIAAAQLTFNhvhUxzhEZFgAABAgQIECBAgAABAgQI7AvM\/LVWyMxPAMMnQIAAAQIECBAgQIDAXASMk8CzgFbIs4PfBAgQIECAAAECBAgQmKaAUREg0BLQCmmBeEuAAAECBAgQIECAwBQEjIEAAQJvCWiFvCVjPgECBAgQIECAAIH0BERMgAABAh8KaIV8SGQFAgQIECBAgACBsQuIjwABAgQIHC+gFXK8lTUJECBAgAABAuMSEA0BAgQIECBwgoBWyAloNiFAgAABAgSGFHBsAgQIECBAgMA5Aloh5+jZlgABAgQI9CfgSAQIECBAgAABAhcR0Aq5CKOdECBAgEBXAvZLgAABAgQIECBA4LICWiGX9bQ3AgQIXEbAXggQIECAAAECBAgQ6EhAK6QjWLslQOAUAdsQIECAAAECBAgQIECgawGtkK6F7Z\/AxwLWIECAAAECBAgQIECAAIHeBLRCeqN2oLaA9wQIECBAgAABAgQIECBAoH8BrZC+zR2PAAECBAgQIECAAAECBAgQGFCgp1bIgCN0aAIECBAgQIAAAQIECBAgQKAngRQOoxWSQpbESIAAAQIECBAgQIAAAQJjFhBbUgJaIUmlS7AECBAgQIAAAQIECBAYj4BICKQpoBWSZt5ETYAAAQIECBAgQIDAUAKOS4BA4gJaIYknUPgECBAgQIAAAQIE+hFwFAIECExFQCtkKpk0DgIECBAgQIAAgS4E7JMAAQIEJiegFTK5lBoQAQIECBAgQOB8AXsgQIAAAQLTFdAKmW5ujYzAPAR2Tz\/zGOuRo9y11mu\/by2e9Vs2++mn8aThFwECBD4v8FSM+BTdh2trtN\/vrzv312z2z4D+NLRC9t29JkAgPYH1dts0\/X1ojhwoKGJqBRn1WRi1Zs7tbbCEQ2vUu91V0zStmfN82+x2jetonrk3agIELiGgGtlXjBtKTPtz4vVut1ONBEs4hMb+pBp50Wh2vVYjWiEv8l4QIJCkwGq1XW\/jkzPJ4C8bdNxK15vtarNt7TZ4lqvtLha3FszmbQx9td6uN+2ux2bbLNchMxuINwYaPpvNI8Uby80mQIAAgQ8EVCMvQHFPUY28aOy\/CBnVyD5I63X49FyNaIW0UuAtAQKJCWy2zf3D+mG1nnk7JDodq\/Xmfrler1+1Qp6I7peb5vkvIBLL8LnhhkycHo8yr5pEUas9nzyxzrmHSXb7GPtq83jmrNabZAchcAIECAwsoBp5TsDjPUU18mzx8++QUY38TPLTu\/DpvxrRCvkpB94QIJCiQNQfd\/frP74\/\/N+\/7t+cpr7on98fftzHw+zhf+SwbaJhtPrjx3KGPiFz9xBNj3aH6PlUD5k4eWKdGco8DznG\/ufdKjpo8W3Ms4nfBAgQIHCCgGokbitxT1GNhMPrKWRUI69ZXuaET\/\/ViFbICR90NiGQjsA8It3tHv\/1aTzsznzabpugeCvnsXC2Pk8yh2Hi+X\/bNLOVeR54lO9x6hwGMpcAAQIEjhOIW7AbStxWnu65b\/6fuG2bXawzz+lJ5vDJpBqJU6L\/akQr5PDpaG7aAqInQIAAAQIECBAgQIAAAQJvCGiFvAGT4mwxEyBAgAABAgQIECBAgAABAh8JpN8K+WiElhMgQIAAAQIECBAgQIAAAQLpC1xsBFohF6O0IwIECBAgQIAAAQIECBAgcGkB+7u8gFbI5U3tkQCBngXyPFtcV9++LH77emMiQOCTAotfbuqqVA\/0\/LnlcAQIECDwoYAVCHQooPTpENeuCRDoQSDPskVd3lxXdVXWVWEiQOCTAuXiulzUVVUWPVywDkGAAIGpCsQXM9d1+cvt9ddzp4T38OW2jntKkR9+xsyyrK6K6L\/PkChk4vTI8+zg+R\/zY2msM0OZ5yF\/ub2OYr4sDp85B9HOn\/n\/AAAA\/\/+TLomhAAAABklEQVQDALkbj94bG124AAAAAElFTkSuQmCC\"\/><\/p>\n<h3>Automatisierte Canvas-Erstellung<\/h3>\n<p>Von einer leeren Seite auszugehen, ist oft der schwierigste Teil der strategischen Planung. Mit Visual Paradigm AI k\u00f6nnen Sie einen kompletten 7S-Canvas aus einem einzigen Prompt generieren. Zum Beispiel, indem Sie \u201eMcKinsey-7S-Analyse f\u00fcr moderne Live-Unterhaltung\u201c eingeben, erstellt die KI sofort alle sieben Elemente basierend auf Branchenstandards und spart Stunden an Anfangsarbeit.<\/p>\n<h3>KI-gest\u00fctzte Ideenfindung und Erkenntnisse<\/h3>\n<p>Blockaden in der Kreativit\u00e4t k\u00f6nnen die Analyse behindern. Wenn Sie unsicher sind, wie Sie \u201egeteilte Werte\u201c definieren oder kritische \u201eF\u00e4higkeiten\u201c f\u00fcr eine Nischenbranche identifizieren sollen, k\u00f6nnen die KI-Funktionen unterst\u00fctzen. Durch die \u00dcberpr\u00fcfung des organisatorischen Kontexts und Branchenmuster liefert die KI handlungsorientierte Vorschl\u00e4ge \u00fcber alle sieben Dimensionen hinweg und stellt sicher, dass Ihr Modell umfassend ist.<\/p>\n<h3>Tiefe strategische Analyse und Empfehlungen<\/h3>\n<p><a href=\"https:\/\/www.visual-paradigm.com\/features\/visual-modeling-tool\/\">Tools von Visual Paradigm<\/a>gehen \u00fcber einfache Kartierung hinaus. Das System kann eine tiefgehende Analyse durchf\u00fchren, um m\u00f6gliche Missalignments zu identifizieren und Empfehlungen zu geben. Es k\u00f6nnte darauf hinweisen, dass Ihre aktuelle<em>Personal<\/em>Kapazit\u00e4t ist f\u00fcr Ihre aggressive<em>Strategie<\/em>, sodass Sie Risiken proaktiv angehen k\u00f6nnen.<\/p>\n<h3>Professionelle Berichterstattung<\/h3>\n<p>Sobald die Analyse abgeschlossen ist, erleichtert das Tool die Kommunikation. Sie k\u00f6nnen Ihre Karte und die von der KI generierten Erkenntnisse in professionelle Formate wie PDF oder Word exportieren. Dies ist entscheidend f\u00fcr die Ausrichtung der Stakeholder und stellt sicher, dass die gewonnenen Erkenntnisse klar an die F\u00fchrungsebene weitergegeben werden.<\/p>\n<h2>Tipps und Tricks f\u00fcr den Erfolg<\/h2>\n<p>Um das Maximum aus dem McKinsey-7S-Modell und dem<a href=\"https:\/\/online.visual-paradigm.com\/knowledge\/business-model-canvas\/business-model-canvas-guide-with-examples\/\">Business-Canvas-Toolkit<\/a>zu ziehen, beachten Sie diese praktischen Tipps:<\/p>\n<ul>\n<li><strong>Beginnen Sie mit geteilten Werten:<\/strong>Weil sie im Zentrum des Modells stehen, beeinflussen geteilte Werte jedes andere Element. Wenn sie unklar sind, wird der Rest des Modells Schwierigkeiten haben, sich auszurichten.<\/li>\n<li><strong>Untersch\u00e4tzen Sie die \u201eweichen S\u201c nicht:<\/strong>Es ist leicht, sich auf Strategie und Struktur zu konzentrieren, da sie greifbar sind. Doch die meisten Ver\u00e4nderungsinitiativen scheitern aufgrund von Stil, Personal, F\u00e4higkeiten oder Werten.<\/li>\n<li><strong>Nutzen Sie mehrere Ansichten:<\/strong>Wenn Sie digitale Tools verwenden, wechseln Sie zwischen einer ganzheitlichen Ansicht der Karte, um das Gesamtbild zu sehen, und einer fokussierten Ansicht, um tief in bestimmte Abschnitte (wie Systeme) einzusteigen, ohne Ablenkungen.<\/li>\n<li><strong>Iterieren Sie regelm\u00e4\u00dfig:<\/strong>Das 7S-Modell stellt einen Zeitpunkt dar. Wenn sich der Markt ver\u00e4ndert (externe Faktoren), muss auch Ihre interne Ausrichtung sich weiterentwickeln. Behandeln Sie dies als lebendiges Dokument, kein einziges Einzelereignis.<\/li>\n<li><strong>Nutzen Sie das gesamte Toolset:<\/strong>Das McKinsey-7S-Modell ist m\u00e4chtig, aber am besten in Kombination mit anderen Tools. Nutzen Sie eine<em>SWOT-Analyse-Karte<\/em>um die externe Umgebung zu verstehen, bevor Sie 7S nutzen, um Ihre internen Ressourcen an die Herausforderungen anzupassen.<\/li>\n<\/ul>\n<div>\n<div class=\"cl-preview-section\" style='color: rgba(0, 0, 0, 0.75); font-family: Lato, \"Helvetica Neue\", Helvetica, sans-serif; font-size: 18px; font-variant-ligatures: common-ligatures; background-color: rgb(243, 243, 243);'>\n<h2 id=\"resource\" style=\"margin-top: 0px; margin-bottom: 1.8em; line-height: 1.33;\">Ressource<\/h2>\n<\/div>\n<div class=\"cl-preview-section\" style='color: rgba(0, 0, 0, 0.75); font-family: Lato, \"Helvetica Neue\", Helvetica, sans-serif; font-size: 18px; font-variant-ligatures: common-ligatures; background-color: rgb(243, 243, 243);'>\n<ul style=\"margin-top: 1.2em; margin-bottom: 1.2em; margin-left: 0px;\">\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/www.archimetric.com\/what-is-the-business-model-canvas-why-use-visual-paradigms-ai-bmc-tool\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Was ist die Business Model Canvas? Warum Visual Paradigmen und KI-Tools nutzen?<\/a>: Dieser umfassende Leitfaden erkl\u00e4rt die Business Model Canvas, ihre Kernkomponenten und wie visuelle Paradigmen und KI-gest\u00fctzte Tools die strategische Planung und Unternehmensinnovation verbessern.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/ai.visual-paradigm.com\/business-model-canvas-builder\/editor\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">KI-gest\u00fctzter Builder f\u00fcr die Business Model Canvas \u2013 Sofortige Strategiegestaltung<\/a>: Ein k\u00fcnstlich-intelligente Werkzeug, das die Erstellung von Gesch\u00e4ftsmodell-Canvas automatisiert und intelligente Vorschl\u00e4ge sowie Echtzeit-Einblicke bietet, um das Gesch\u00e4ftsplanung beschleunigen.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/ai-toolbox.visual-paradigm.com\/app\/canvas\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">AI-Canvas-Tool \u2013 Intelligente Gestaltung f\u00fcr Gesch\u00e4ftsrahmen<\/a>: Eine AI-gest\u00fctzte Canvas-Anwendung, die Nutzern bei der Erstellung und Feinabstimmung von Gesch\u00e4ftsmodellen, Wertvorschl\u00e4gen und Strategie-Rahmen mit intelligenten Vorschl\u00e4gen und Automatisierung unterst\u00fctzt.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/www.visual-paradigm.com\/solution\/ai-business-model-canvas-tool\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">AI-Gesch\u00e4ftsmodell-Canvas-Tool \u2013 Intelligente Strategieentwicklung<\/a>: Eine umfassende, k\u00fcnstlich-intelligente L\u00f6sung zur Erstellung und Verbesserung von Gesch\u00e4ftsmodellen mit intelligenten Einblicken, Echtzeit-Feedback und kooperativen Funktionen.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/updates.visual-paradigm.com\/releases\/ai-canvas-editor\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">AI-Canvas-Editor-Release-Update<\/a>: Einf\u00fchrung eines k\u00fcnstlich-intelligenten Canvas-Editors, der die Diagrammerstellung durch intelligente Vorschl\u00e4ge und automatisierte Layout-Optimierung verbessert.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/guides.visual-paradigm.com\/ai-powered-business-model-canvas-tool\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Leitfaden zum k\u00fcnstlich-intelligenten Gesch\u00e4ftsmodell-Canvas-Tool<\/a>: Ein Schritt-f\u00fcr-Schritt-Leitfaden zur Nutzung eines k\u00fcnstlich-intelligenten Tools zur Erstellung und Feinabstimmung von Gesch\u00e4ftsmodell-Canvas mit intelligentem Eingabedesign und Echtzeit-Empfehlungen.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/canvas.visual-paradigm.com\/mission-model-canvas\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Mission-Modell-Canvas | K\u00fcnstlich-intelligentes Strategie-Tool von VP<\/a>: 28. Oktober 2025 \u2013 Koordinieren Sie Live-Sitzungen mit Ihrem Team mit Hilfe des integrierten Timers und exportieren Sie Ihren endg\u00fcltigen Canvas oder Berichte in professionelle Formate wie Word, Markdown oder CSV. \u2026 Der Mission-Modell-Canvas ist speziell f\u00fcr Nicht-Profits, Regierungsbeh\u00f6rden, soziale Unternehmen und alle Organisationen konzipiert, deren prim\u00e4res Ziel die Erreichung der Mission ist, nicht der Gewinn.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/www.cybermedian.com\/comprehensive-tutorial-ai-powered-business-canvas-toolkit-with-visual-paradigm\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Umfassender Leitfaden: K\u00fcnstlich-intelligente Business-Canvas-Toolkit mit Visual Paradigm<\/a>: Diese Seite bietet einen detaillierten Leitfaden zur Nutzung eines k\u00fcnstlich-intelligenten Business-Model-Canvas-Tools, das mit Visual Paradigm integriert ist, um die automatisierte Entwicklung von Gesch\u00e4ftsstrategien zu erm\u00f6glichen.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/ai.visual-paradigm.com\/tool\/canvas-tool\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">AI-Canvas-Tool \u2013 Visual Paradigm<\/a>: Ein k\u00fcnstlich-intelligente Werkzeug innerhalb von Visual Paradigm, das Nutzern erm\u00f6glicht, Gesch\u00e4fts-Canvas durch intelligente Automatisierung und Eingabe \u00fcber nat\u00fcrliche Sprache zu erstellen und zu verfeinern.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/www.diagrams-ai.com\/blog\/mastering-the-business-model-canvas-with-ai-a-step-by-step-guide-using-visual-paradigm\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Beherrschen des Gesch\u00e4ftsmodell-Canvas mit KI: Schritt-f\u00fcr-Schritt-Leitfaden mit Visual Paradigm<\/a>: Dieser Blogbeitrag bietet eine strukturierte Anleitung zur Nutzung der KI-Funktionen in Visual Paradigm, um Gesch\u00e4ftsmodell-Canvas effizient zu erstellen, anzupassen und zu optimieren.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/ai.visual-paradigm.com\/tool\/business-model-canvas-builder\/how-it-works\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">So funktioniert der KI-gest\u00fctzte Gesch\u00e4ftsmodell-Canvas-Generator \u2013 Visual Paradigm<\/a>: Diese Seite erkl\u00e4rt die Funktionalit\u00e4t des k\u00fcnstlich-intelligenten Gesch\u00e4ftsmodell-Canvas-Generators und zeigt, wie maschinelles Lernen die Erstellung von Canvas und die Generierung strategischer Einblicke automatisiert.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/online.visual-paradigm.com\/diagrams\/templates\/analysis-canvas\/strategy-tools\/deep-learning-ai-canvas\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Deep-Learning-KI-Canvas | Vorlage f\u00fcr Analyse-Canvas von Strategie-Tools<\/a>: Bearbeiten Sie die lokalisierte Version: Deep-Learning KI-Canvas (TW) | Deep Learning KI-Canvas (CN) Diese Seite anzeigen in: EN TW CN \u00b7 Visual Paradigm Online (VP Online) ist eine Online-Diagramm-Software, die Analyse-Canvas, verschiedene Diagramme, UML, Flussdiagramme, Rack-Diagramme, Organigramme, Familienb\u00e4ume, ERD, Grundrisse usw. unterst\u00fctzt.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/canvas.visual-paradigm.com\/product-canvas\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Produkt-Canvas | K\u00fcnstlich-intelligentes Strategie-Tool von VP<\/a>: Erstellen Sie Produkte, die Menschen lieben. Kombinieren Sie Strategie, Design und Feedback in einem visuellen Raum mit unserem k\u00fcnstlich-intelligenten Produkt-Canvas, um Ideen schneller auf den Markt zu bringen.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/canvas.visual-paradigm.com\/lean-ux-canvas\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Lean-UX-Canvas | K\u00fcnstlich-intelligentes Strategie-Tool von VP<\/a>: 28. Oktober 2025 \u2013 Erstellen Sie innerhalb von Momenten ein vollst\u00e4ndiges Strategie-Rahmenwerk. Beschreiben Sie einfach Ihre Vision, und der KI-Canvas-Generator verwandelt sie in einen strukturierten, reichhaltigen Einblick-Canvas, der Ihnen hilft, Ihre n\u00e4chste gro\u00dfe Idee zu visualisieren, zu planen und zu verfeinern.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/canvas.visual-paradigm.com\/lean-canvas\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Lean-Canvas \u2013 Visual Paradigm<\/a>: 28. Oktober 2025 \u2013 Unsere Anwendung ist als strategischer Partner konzipiert, der intelligente Werkzeuge bereitstellt, um jeden Schritt Ihres Planungsprozesses f\u00fcr den Gesch\u00e4ftsmodell-Canvas zu verbessern. \u2026 Haben Sie eine Startup-Idee? Geben Sie einfach \u201eeine Mobile-App f\u00fcr die Lieferung von hausgemachten Mahlzeiten vor Ort\u201c ein und lassen Sie unsere KI einen vollst\u00e4ndigen Lean-Canvas erstellen, der das Problem, die L\u00f6sung und die wichtigsten Kennzahlen darstellt.<\/p>\n<\/li>\n<\/ul>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>In der komplexen Welt der Unternehmensstrategie ist ein brillanter Plan nur die halbe Miete. Die eigentliche Herausforderung liegt oft in der Umsetzung und der Ausrichtung. Organisationen sind lebendige Systeme, bei denen eine Ver\u00e4nderung in einem Bereich sich auf andere auswirkt. Um diese Komplexit\u00e4t zu meistern, st\u00fctzen sich F\u00fchrungskr\u00e4fte auf robuste Rahmenwerke, um sicherzustellen, dass jedes Element ihres Unternehmens in dieselbe Richtung bewegt wird. Unter diesen Werkzeugen ist das McKinsey-7S-Modell eines der dauerhaftesten und effektivsten. Dieser Leitfaden erkundet die Tiefen des McKinsey-7S-Rahmenwerks, eines zentralen Bestandteils des Ultimativen Business-Canvas-Tools. Wir werden seine zentralen Konzepte analysieren, schrittweise Anleitungen zur Umsetzung bereitstellen und zeigen, wie k\u00fcnstliche Intelligenz (KI) die Art und Weise revolutionieren kann, wie Sie Ihre Organisation analysieren und ausrichten. Wichtige Konzepte: Die Entschl\u00fcsselung des 7S-Rahmenwerks Das McKinsey-7S-Modell ist ein strategisches Werkzeug, das zur Bewertung der organisatorischen Effektivit\u00e4t dient. Im Gegensatz zu Rahmenwerken, die ausschlie\u00dflich auf externe Faktoren (wie PESTLE) oder Wettbewerbsposition (wie Porter\u2019s Five Forces) abstellen, konzentriert sich das 7S-Modell auf die interne Ausrichtung. Die Grundidee ist einfach: Damit eine Organisation gut funktioniert, m\u00fcssen sieben spezifische Elemente ausgerichtet und wechselseitig st\u00fctzend sein. Diese sieben Elemente werden in \u201eHarte\u201c und \u201eWeiche\u201c Elemente eingeteilt. Die Unterscheidung ist entscheidend f\u00fcr eine effektive Analyse. Die harten Elemente Sie sind greifbar, leichter zu identifizieren und direkt durch Managemententscheidungen beeinflussbar. Strategie: Der Plan, der entwickelt wurde, um einen Wettbewerbsvorteil gegen\u00fcber der Konkurrenz aufzubauen und aufrechtzuerhalten. Er legt die Route fest, die die Organisation einschlagen m\u00f6chte, um ihre Ziele zu erreichen. Struktur: Die Art und Weise, wie die Organisation strukturiert ist und wer wem berichtet. Dazu geh\u00f6ren das Organigramm und die Hierarchie der Autorit\u00e4t. Systeme: Die t\u00e4glichen Aktivit\u00e4ten und Verfahren, an denen die Mitarbeiter arbeiten, um ihre Aufgaben zu erf\u00fcllen. Dazu geh\u00f6ren alles von IT-Systemen \u00fcber Finanzprozesse bis hin zu HR-Abl\u00e4ufen. Die weichen Elemente Sie sind immateriell, schwerer zu beschreiben und werden durch die Kultur beeinflusst. Sie sind jedoch oft genauso wichtig wie die harten Elemente f\u00fcr den Erfolg. Geteilte Werte: Der Kern des Modells. Es handelt sich um die grundlegenden Werte des Unternehmens, die sich in der Unternehmenskultur und der allgemeinen Arbeitsmoral widerspiegeln. Sie verbinden jedes andere Element. Stil: Der von der F\u00fchrung \u00fcbernommene Stil. Dies umfasst den kulturellen Stil der Organisation und das Verhalten wichtiger Manager bei der Erreichung der Unternehmensziele. Personal: Die Mitarbeiter und ihre allgemeinen F\u00e4higkeiten. Es geht nicht nur um die Kopfzahl, sondern um Talentmanagement und die Art und Weise, wie die Belegschaft gef\u00f6rdert wird. F\u00e4higkeiten: Die tats\u00e4chlichen F\u00e4higkeiten und Kompetenzen der Mitarbeiter des Unternehmens. Es beantwortet die Frage: \u201eWas k\u00f6nnen wir am besten?\u201c Anleitungen: Umsetzung der McKinsey-7S-Analyse Die Anwendung des McKinsey-7S-Modells erfordert einen strukturierten Ansatz. Ob Sie ein Gr\u00fcndungsf\u00fchrer sind, der das Business-Canvas-Toolkit nutzt, oder ein Unternehmensstrateg, befolgen Sie diese Anleitungen, um eine gr\u00fcndliche Analyse sicherzustellen. Schritt 1: Bewertung des aktuellen Zustands Beginnen Sie damit, wie Ihre Organisation derzeit in allen sieben Dimensionen funktioniert, aufzuzeichnen. Seien Sie ehrlich und kritisch. Sind Ihre Systeme veraltet? Hemmt Ihre Struktur Ihre Strategie? \u00dcberpr\u00fcfung der Interdependenzen: Suchen Sie nach L\u00fccken. Zum Beispiel, passt Ihr Struktur (hierarchisch) mit Ihrem Strategie (agile Innovation)? Daten sammeln: Verwenden Sie Umfragen, Interviews und Beobachtungen, um die \u201eweichen\u201c Elemente wie Stil und gemeinsame Werte zu bewerten. Schritt 2: Definieren des zuk\u00fcnftigen Zustands Ermitteln Sie, wo die Organisation sein muss. Wenn Sie ein neues Produkt lancieren oder in einen neuen Markt eintreten, wie m\u00fcssen die sieben Elemente sich \u00e4ndern, um dieses Ziel zu unterst\u00fctzen? Schritt 3: Analyse der L\u00fccken Vergleichen Sie Ihren aktuellen Zustand mit Ihrem gew\u00fcnschten zuk\u00fcnftigen Zustand. Die Abweichungen zeigen die Bereiche auf, die eine Intervention erfordern. Schritt 4: Entwicklung eines Aktionsplans Erstellen Sie eine Roadmap, um die L\u00fccken zu schlie\u00dfen. Denken Sie daran, dass die \u00c4nderung eines Elements andere beeinflusst. Wenn Sie neue Systeme (z.\u202fB. ein neues CRM), m\u00fcssen Sie m\u00f6glicherweise F\u00e4higkeiten (Ausbildung) und passen Struktur (IT-Unterst\u00fctzungsrollen). VP AI: Wie Visual Paradigm AI die strategische Analyse verbessert Traditionelle strategische Analyse kann zeitaufwendig und anf\u00e4llig f\u00fcr Verzerrungen sein.Das von KI gest\u00fctzte Canvas-Tool von Visual Paradigm transformiert das McKinsey-7S-Modell von einer statischen Darstellung in einen dynamischen, intelligenten Arbeitsraum. Automatisierte Canvas-Erstellung Von einer leeren Seite auszugehen, ist oft der schwierigste Teil der strategischen Planung. Mit Visual Paradigm AI k\u00f6nnen Sie einen kompletten 7S-Canvas aus einem einzigen Prompt generieren. Zum Beispiel, indem Sie \u201eMcKinsey-7S-Analyse f\u00fcr moderne Live-Unterhaltung\u201c eingeben, erstellt die KI sofort alle sieben Elemente basierend auf Branchenstandards und spart Stunden an Anfangsarbeit. KI-gest\u00fctzte Ideenfindung und Erkenntnisse Blockaden in der Kreativit\u00e4t k\u00f6nnen die Analyse behindern. Wenn Sie unsicher sind, wie Sie \u201egeteilte Werte\u201c definieren oder kritische \u201eF\u00e4higkeiten\u201c f\u00fcr eine Nischenbranche identifizieren sollen, k\u00f6nnen die KI-Funktionen unterst\u00fctzen. Durch die \u00dcberpr\u00fcfung des organisatorischen Kontexts und Branchenmuster liefert die KI handlungsorientierte Vorschl\u00e4ge \u00fcber alle sieben Dimensionen hinweg und stellt sicher, dass Ihr Modell umfassend ist. Tiefe strategische Analyse und Empfehlungen Tools von Visual Paradigmgehen \u00fcber einfache Kartierung hinaus. Das System kann eine tiefgehende Analyse durchf\u00fchren, um m\u00f6gliche Missalignments zu identifizieren und Empfehlungen zu geben. Es k\u00f6nnte darauf hinweisen, dass Ihre aktuellePersonalKapazit\u00e4t ist f\u00fcr Ihre aggressiveStrategie, sodass Sie Risiken proaktiv angehen k\u00f6nnen. Professionelle Berichterstattung Sobald die Analyse abgeschlossen ist, erleichtert das Tool die Kommunikation. Sie k\u00f6nnen Ihre Karte und die von der KI generierten Erkenntnisse in professionelle Formate wie PDF oder Word exportieren. Dies ist entscheidend f\u00fcr die Ausrichtung der Stakeholder und stellt sicher, dass die gewonnenen Erkenntnisse klar an die F\u00fchrungsebene weitergegeben werden. Tipps und Tricks f\u00fcr den Erfolg Um das Maximum aus dem McKinsey-7S-Modell und demBusiness-Canvas-Toolkitzu ziehen, beachten Sie diese praktischen Tipps: Beginnen Sie mit geteilten Werten:Weil sie im Zentrum des Modells stehen, beeinflussen geteilte Werte jedes andere Element. Wenn sie unklar sind, wird der Rest des Modells Schwierigkeiten haben, sich auszurichten. Untersch\u00e4tzen Sie die \u201eweichen S\u201c nicht:Es ist leicht, sich auf Strategie und Struktur zu konzentrieren, da sie greifbar sind. Doch die meisten Ver\u00e4nderungsinitiativen scheitern aufgrund von Stil, Personal, F\u00e4higkeiten oder Werten. Nutzen Sie mehrere Ansichten:Wenn Sie digitale Tools verwenden, wechseln Sie zwischen einer ganzheitlichen Ansicht der Karte, um das Gesamtbild zu sehen, und einer fokussierten Ansicht, um tief in bestimmte Abschnitte (wie Systeme) einzusteigen, ohne Ablenkungen. Iterieren Sie regelm\u00e4\u00dfig:Das 7S-Modell stellt einen Zeitpunkt dar.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_yoast_wpseo_title":"Der ultimative Leitfaden zur McKinsey-7S-Modell-Analyse | Visual Paradigm","_yoast_wpseo_metadesc":"Beherrschen Sie die organisationale Ausrichtung mit dem McKinsey-7S-Modell. Lernen Sie die wichtigsten Konzepte, Schritt-f\u00fcr-Schritt-Anleitungen und die Nutzung von Visual Paradigm AI f\u00fcr strategische Analyse.","fifu_image_url":"","fifu_image_alt":"","footnotes":""},"categories":[1],"tags":[],"class_list":["post-3339","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.1.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Der ultimative Leitfaden zur McKinsey-7S-Modell-Analyse | Visual Paradigm<\/title>\n<meta name=\"description\" content=\"Beherrschen Sie die organisationale Ausrichtung mit dem McKinsey-7S-Modell. 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