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	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8"/>
	<meta name="viewport" content="width=device-width, initial-scale=1.0"/>
	<title>QUASAR — Aurora Intelligence</title>
	<link rel="preconnect" href="https://fonts.googleapis.com">
	<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
	<link href="https://fonts.googleapis.com/css2?family=Inter:ital,opsz,wght@0,14..32,100..900;1,14..32,100..900&display=swap" rel="stylesheet">
	<script src="https://cdnjs.cloudflare.com/ajax/libs/three.js/r128/three.min.js"></script>
	<style>

	/* ════════════════════════════════════════════════════════════════════════════
	TOKENS & DESIGN SYSTEM — QUASAR DEEP NAVY / ELECTRIC CYAN
	Reference: dashboard.html screenshot — deep space blue base, #00d4ff cyan
	════════════════════════════════════════════════════════════════════════════ */
	:root {
	/* Core — deep navy, not pure black */
	--void: #000810;

	/* Aurora Palette — original */
	--aurora-1: rgba(0, 200, 255, 0.4); /* Cyan */
	--aurora-2: rgba(160, 80, 255, 0.4); /* Purple */
	--aurora-3: rgba(0, 223, 138, 0.3); /* Emerald */

	/* Glass — navy-tinted, not neutral grey */
	--glass-bg: linear-gradient(135deg, rgba(0, 20, 50, 0.55) 0%, rgba(0, 10, 30, 0.35) 100%);
	--glass-border: rgba(0, 180, 255, 0.14);
	--glass-edge: rgba(0, 212, 255, 0.30);

	/* Primary accent — the electric cyan from the screenshot logo/signal */
	--cyan: #00d4ff;
	--cyan-dim: #0098c8;
	--cyan-glow: rgba(0, 212, 255, 0.55);
	--cyan-glow2: rgba(0, 212, 255, 0.15);

	/* Status colors — kept readable against navy */
	--green: #00ff88;
	--green-glow: rgba(0, 255, 136, 0.5);
	--red: #ff4466;
	--red-glow: rgba(255, 68, 102, 0.5);
	--amber: #ffaa00;
	--amber-glow: rgba(255, 170, 0, 0.5);

	/* Typography — cool blue-white tones */
	--t0: #ffffff;
	--t1: #cce8ff; /* primary — light ice blue */
	--t2: #7ab4d4; /* secondary — mid blue-grey */
	--t3: #3a6888; /* dim — muted steel blue */
	--t4: #1a3448; /* faint — deep navy */

	/* Type */
	--font: 'Inter', sans-serif;

	/* Geometry */
	--panel-r: 20px;
	--elem-r: 8px;
	--pill-r: 24px;
	--nav-h: 70px;

	/* Spacing */
	--sp-xs: 8px;
	--sp-sm: 12px;
	--sp-md: 20px;
	--sp-lg: 24px;
	--sp-xl: 32px;
	}

	/* ════════════════════════════════════════════════════════════════════════════
	RESET
	════════════════════════════════════════════════════════════════════════════ */
	, ::before, *::after { box-sizing: border-box; margin: 0; padding: 0; }
	html { font-size: 15px; background: #02040a;
	-webkit-font-smoothing: antialiased; font-feature-settings: "cv01","cv02","cv03","cv04","tnum"; }
	body {
	font-family: var(--font);
	background: transparent;
	color: var(--t1);
	min-height: 100vh;
	overflow-x: hidden;
	}

	/* ════════════════════════════════════════════════════════════════════════════
	LAYER 0: ANIMATED AURORA BACKGROUND
	════════════════════════════════════════════════════════════════════════════ */
	#bg-aurora {
	position: fixed; inset: 0; z-index: 0;
	background: transparent;
	overflow: hidden;
	}
	.aurora-blob {
	position: absolute;
	filter: blur(120px);
	border-radius: 50%;
	animation: float-aurora 25s infinite alternate cubic-bezier(0.4, 0, 0.2, 1);
	mix-blend-mode: screen;
	}
	.aurora-blob.c1 {
	width: 60vw; height: 60vh; background: var(--aurora-1);
	top: -10%; left: -10%; animation-delay: 0s;
	}
	.aurora-blob.c2 {
	width: 50vw; height: 50vh; background: var(--aurora-2);
	bottom: -20%; right: -10%; animation-delay: -5s;
	animation-duration: 30s;
	}
	.aurora-blob.c3 {
	width: 45vw; height: 45vh; background: var(--aurora-3);
	top: 40%; left: 30%; animation-delay: -12s;
	animation-duration: 20s; opacity: 0.6;
	}
	@keyframes float-aurora {
	0% { transform: translate(0, 0) scale(1) rotate(0deg); }
	50% { transform: translate(15vw, 10vh) scale(1.2) rotate(45deg); }
	100% { transform: translate(-5vw, 20vh) scale(0.9) rotate(90deg); }
	}

	/* ════════════════════════════════════════════════════════════════════════════
	LAYER 1: OVERLAY & CANVAS
	════════════════════════════════════════════════════════════════════════════ */
	#bg-canvas {
	position: fixed; inset: 0; z-index: 1;
	width: 100%; height: 100%; pointer-events: none; opacity: 0.7;
	}
	/* Three.js neural net — same slot as bg-canvas, transparent so aurora beneath shows */
	#three-canvas {
	position: fixed; inset: 0; z-index: 1;
	width: 100%; height: 100%; pointer-events: none;
	opacity: 1.0; /* full opacity — we want this SEEN */
	mix-blend-mode: screen; /* additive blend: nodes glow INTO the aurora */
	}
	#bg-overlay {
	position: fixed; inset: 0; z-index: 2; pointer-events: none;
	background: radial-gradient(circle at 50% 0%, transparent 20%, rgba(2,4,10,0.85) 90%);
	}
	#scanlines {
	position: fixed; inset: 0; z-index: 3; pointer-events: none; opacity: 0.25;
	background: repeating-linear-gradient(0deg, transparent 0px, transparent 2px, rgba(0,0,0,0.1) 2px, rgba(0,0,0,0.1) 4px);
	}

	/* ════════════════════════════════════════════════════════════════════════════
	LAYOUT SHELL
	════════════════════════════════════════════════════════════════════════════ */
	#shell {
	position: relative; z-index: 10;
	display: flex; flex-direction: column;
	min-height: 100vh;
	}

	/* ════════════════════════════════════════════════════════════════════════════
	LAYER 2 & 3: GLASSMORPHISM NAV
	════════════════════════════════════════════════════════════════════════════ */
	#nav {
	position: sticky; top: 0; z-index: 50;
	display: flex; align-items: stretch;
	height: var(--nav-h);
	background: rgba(2, 4, 10, 0.4);
	backdrop-filter: blur(30px) saturate(150%);
	-webkit-backdrop-filter: blur(30px) saturate(150%);
	border-bottom: 1px solid var(--glass-border);
	box-shadow: 0 10px 30px -10px rgba(0,0,0,0.5);
	}

	#nav-logo {
	display: flex; align-items: center; gap: var(--sp-sm);
	padding: 0 var(--sp-lg);
	border-right: 1px solid rgba(255,255,255,0.05);
	}
	#nav-logo-mark {
	width: 3px; height: 26px;
	background: linear-gradient(180deg, var(--cyan) 0%, var(--amber) 100%);
	border-radius: var(--pill-r);
	box-shadow: 0 0 15px var(--cyan-glow);
	}
	#nav-logo-text {
	font-size: 0.9rem; font-weight: 800; letter-spacing: 0.25em;
	color: var(--t0); white-space: nowrap;
	text-shadow: 0 0 10px rgba(255,255,255,0.2);
	}
	#nav-logo-text em { color: var(--cyan); font-style: normal; text-shadow: 0 0 10px var(--cyan-glow); }

	#nav-links {
	display: flex; align-items: stretch; gap: var(--sp-xs);
	flex: 1; padding: 0 var(--sp-md);
	overflow-x: auto;
	}
	.nav-tab {
	display: flex; align-items: center;
	padding: 0 var(--sp-md);
	font-size: 0.75rem; font-weight: 600; letter-spacing: 0.12em;
	text-transform: uppercase; color: var(--t3);
	cursor: pointer; position: relative;
	transition: all 0.3s cubic-bezier(0.2, 0.8, 0.2, 1);
	border: none; background: none;
	white-space: nowrap;
	}
	.nav-tab:hover { color: var(--t0); text-shadow: 0 0 8px rgba(255,255,255,0.3); }
	.nav-tab.active { color: var(--cyan); text-shadow: 0 0 12px var(--cyan-glow); }
	.nav-tab.active::after {
	content: ''; position: absolute; bottom: 0; left: 15px; right: 15px; height: 3px;
	background: var(--cyan); border-radius: 3px 3px 0 0;
	box-shadow: 0 -2px 15px var(--cyan), 0 0 5px var(--cyan);
	}

	#nav-right {
	display: flex; align-items: center; gap: var(--sp-md);
	padding: 0 var(--sp-lg);
	border-left: 1px solid rgba(255,255,255,0.05);
	}
	.search-wrap { position: relative; }
	#search-input {
	background: rgba(0,0,0,0.4);
	border: 1px solid var(--glass-border);
	border-radius: var(--pill-r);
	padding: 10px 18px 10px 38px;
	color: var(--t1); font-family: var(--font); font-size: 0.75rem;
	width: 200px; outline: none;
	transition: all 0.3s cubic-bezier(0.2, 0.8, 0.2, 1);
	box-shadow: inset 0 2px 5px rgba(0,0,0,0.5);
	}
	#search-input:focus {
	border-color: var(--cyan); width: 260px;
	background: rgba(0,200,255,0.05);
	box-shadow: inset 0 2px 5px rgba(0,0,0,0.5), 0 0 15px rgba(0,200,255,0.2);
	}
	.search-icon {
	position: absolute; left: 14px; top: 50%; transform: translateY(-50%);
	font-size: 14px; color: var(--t3); pointer-events: none;
	}

	#live-pill {
	display: flex; align-items: center; gap: 8px;
	padding: 8px 16px;
	border: 1px solid rgba(255,255,255,0.1);
	border-radius: var(--pill-r);
	background: rgba(0,0,0,0.5);
	box-shadow: inset 0 2px 10px rgba(0,0,0,0.4);
	}
	#live-pill-label {
	font-size: 0.65rem; font-weight: 800; letter-spacing: 0.15em;
	text-transform: uppercase; color: var(--t2);
	}
	.pring { position: relative; width: 8px; height: 8px; flex-shrink: 0; }
	.pring .core { position: absolute; inset: 1px; border-radius: 50%; background: var(--t4); }
	.pring.live .core { background: var(--green); box-shadow: 0 0 8px var(--green); }
	.pring.live::before {
	content: ''; position: absolute; inset: -4px; border-radius: 50%;
	border: 1px solid var(--green); opacity: 0;
	animation: pring 2.5s ease-out infinite;
	}
	@keyframes pring {
	0% { opacity: 0.8; transform: scale(0.5); }
	100% { opacity: 0; transform: scale(2.5); }
	}

	/* ════════════════════════════════════════════════════════════════════════════
	MAIN CONTENT & GLASS PANELS
	════════════════════════════════════════════════════════════════════════════ */
	#main {
	flex: 1; max-width: 1600px; width: 100%; margin: 0 auto;
	padding: var(--sp-xl) var(--sp-xl) 80px;
	display: flex; flex-direction: column; gap: var(--sp-lg);
	}

	.panel {
	background: var(--glass-bg);
	backdrop-filter: blur(24px) saturate(120%);
	-webkit-backdrop-filter: blur(24px) saturate(120%);
	border: 1px solid var(--glass-border);
	border-radius: var(--panel-r);
	position: relative; overflow: hidden;
	box-shadow: 0 15px 35px rgba(0,0,0,0.4), inset 0 1px 0 rgba(255,255,255,0.1);
	transition: all 0.4s cubic-bezier(0.2, 0.8, 0.2, 1);
	}
	.panel:hover {
	border-color: var(--glass-edge);
	box-shadow: 0 20px 40px rgba(0,0,0,0.6), inset 0 1px 15px rgba(0,200,255,0.05);
	transform: translateY(-2px);
	}

	.panel-hd {
	display: flex; align-items: center; justify-content: space-between;
	padding: 16px var(--sp-lg);
	border-bottom: 1px solid rgba(255,255,255,0.05);
	background: rgba(0,0,0,0.3);
	}
	.panel-hd-left { display: flex; align-items: center; gap: var(--sp-sm); }
	.panel-hd-pip {
	width: 4px; height: 16px; background: var(--cyan);
	border-radius: var(--pill-r); box-shadow: 0 0 10px var(--cyan-glow);
	}
	.panel-hd-label {
	font-size: 0.7rem; font-weight: 800; letter-spacing: 0.2em;
	text-transform: uppercase; color: var(--t1);
	}
	.panel-hd-meta { font-size: 0.65rem; font-weight: 500; color: var(--t3); letter-spacing: 0.05em; }

	/* ════════════════════════════════════════════════════════════════════════════
	KPI ROW
	════════════════════════════════════════════════════════════════════════════ */
	#kpi-row { display: grid; grid-template-columns: repeat(4, 1fr); gap: var(--sp-lg); }
	.kpi { padding: var(--sp-xl) var(--sp-lg); display: flex; flex-direction: column; justify-content: center; position: relative; }

	.kpi::before {
	content: ''; position: absolute; left: 0; top: 0; bottom: 0; width: 4px;
	background: var(--cyan); opacity: 0.2; transition: all 0.4s ease;
	}
	.kpi:hover::before { opacity: 1; box-shadow: 0 0 20px var(--cyan); }

	.kpi-k {
	font-size: 0.65rem; font-weight: 800; letter-spacing: 0.15em;
	text-transform: uppercase; color: var(--t2); margin-bottom: 12px;
	}
	.kpi-v {
	font-size: 2.2rem; font-weight: 800; line-height: 1;
	letter-spacing: -0.02em; color: var(--t0); text-shadow: 0 4px 15px rgba(0,0,0,0.5);
	}
	.kpi-v.c-cyan { color: var(--cyan); text-shadow: 0 0 20px rgba(0,200,255,0.3); }
	.kpi-v.c-green { color: #E8720A; text-shadow: 0 0 20px rgba(232,114,10,0.4); }
	.kpi-sub { margin-top: 10px; font-size: 0.7rem; font-weight: 500; color: var(--t3); letter-spacing: 0.02em; }

	#kpi-score-card::before { background: #E8720A; }
	#kpi-upd-card::before { background: var(--t3); }
	#kpi-spaces-card::before { background: #a855f7; }
	#kpi-spaces-card .kpi-v { color: #a855f7; text-shadow: 0 0 20px rgba(168,85,247,0.45); }

	.kpi { animation: rise 0.6s cubic-bezier(0.16, 1, 0.3, 1) both; }
	.kpi:nth-child(1) { animation-delay: 0.1s; }
	.kpi:nth-child(2) { animation-delay: 0.2s; }
	.kpi:nth-child(3) { animation-delay: 0.3s; }
	.kpi:nth-child(4) { animation-delay: 0.4s; }
	@keyframes rise {
	from { opacity: 0; transform: translateY(20px); filter: blur(5px); }
	to { opacity: 1; transform: translateY(0); filter: blur(0); }
	}

	/* ══════════════════════════════════════════════════════════��═════════════════
	TABLE (GLASS LAYER)
	════════════════════════════════════════════════════════════════════════════ */
	table { width: 100%; border-collapse: collapse; }
	thead tr { background: rgba(0,0,0,0.4); }
	th {
	padding: 16px var(--sp-lg);
	font-size: 0.65rem; font-weight: 800; letter-spacing: 0.15em;
	text-transform: uppercase; color: var(--t3); text-align: left;
	border-bottom: 1px solid rgba(255,255,255,0.08); cursor: pointer; transition: color 0.2s;
	}
	th:hover { color: var(--t1); }
	th.sorted { color: var(--cyan); }
	.sa { opacity: 0; margin-left: 4px; font-size: 9px; transition: opacity 0.2s; }
	th:hover .sa { opacity: 1; }
	th.sorted .sa { opacity: 1; color: var(--cyan); }

	tbody tr {
	border-bottom: 1px solid rgba(255,255,255,0.03);
	transition: all 0.2s ease;
	}
	tbody tr:hover { background: rgba(255,255,255,0.04); transform: scale(1.002); }
	tbody tr.sel {
	background: rgba(0,200,255,0.08);
	border-left: 4px solid var(--cyan);
	box-shadow: inset 10px 0 20px -10px rgba(0,200,255,0.3);
	}

	td { padding: 14px var(--sp-lg); font-size: 0.8rem; font-weight: 500; color: var(--t1); }
	td.rc { font-weight: 800; color: var(--t4); text-align: center; }
	tbody tr.r1 td.rc { color: var(--amber); text-shadow: 0 0 10px rgba(255,170,0,0.5); }
	td.nc { font-weight: 700; color: var(--t0); }
	td.num { text-align: right; font-variant-numeric: tabular-nums; }

	/* Neon Badges */
	.sig {
	display: inline-flex; align-items: center; gap: 8px;
	padding: 6px 12px; border-radius: var(--elem-r);
	font-size: 0.65rem; font-weight: 800; letter-spacing: 0.1em;
	box-shadow: inset 0 1px 3px rgba(255,255,255,0.1);
	}
	.sig::before { content: ''; width: 6px; height: 6px; border-radius: 50%; }
	.sig.BUY { color: var(--green); background: rgba(0,223,138,0.1); border: 1px solid rgba(0,223,138,0.3); }
	.sig.BUY::before { background: var(--green); box-shadow: 0 0 10px var(--green); }
	.sig.SELL { color: var(--red); background: rgba(255,61,90,0.1); border: 1px solid rgba(255,61,90,0.3); }
	.sig.SELL::before { background: var(--red); box-shadow: 0 0 10px var(--red); }
	.sig.HOLD, .sig.NEUTRAL { color: var(--t2); background: rgba(255,255,255,0.05); border: 1px solid rgba(255,255,255,0.1); }
	.sig.HOLD::before, .sig.NEUTRAL::before { background: var(--t3); }

	/* Log Level Badges */
	.log-badge {
	display: inline-flex; align-items: center; gap: 6px;
	padding: 4px 10px; border-radius: var(--elem-r);
	font-size: 0.6rem; font-weight: 800; letter-spacing: 0.08em;
	text-transform: uppercase; box-shadow: inset 0 1px 2px rgba(255,255,255,0.05);
	}
	.log-badge::before { content: ''; width: 4px; height: 4px; border-radius: 50%; }
	.log-badge.INFO { color: var(--cyan); background: rgba(0,200,255,0.1); border: 1px solid rgba(0,200,255,0.2); }
	.log-badge.INFO::before { background: var(--cyan); box-shadow: 0 0 6px var(--cyan); }
	.log-badge.DEBUG { color: var(--t2); background: rgba(255,255,255,0.05); border: 1px solid rgba(255,255,255,0.1); }
	.log-badge.DEBUG::before { background: var(--t2); }
	.log-badge.WARNING { color: var(--amber); background: rgba(255,170,0,0.1); border: 1px solid rgba(255,170,0,0.2); }
	.log-badge.WARNING::before { background: var(--amber); box-shadow: 0 0 6px var(--amber); }
	.log-badge.ERROR { color: var(--red); background: rgba(255,61,90,0.1); border: 1px solid rgba(255,61,90,0.2); }
	.log-badge.ERROR::before { background: var(--red); box-shadow: 0 0 6px var(--red); }
	.log-badge.CRITICAL { color: var(--red); background: rgba(255,61,90,0.2); border: 1px solid rgba(255,61,90,0.4); }
	.log-badge.CRITICAL::before { background: var(--red); box-shadow: 0 0 10px var(--red); }

	/* Category Tags */
	.cat-tag {
	display: inline-block;
	padding: 2px 8px; border-radius: 4px;
	font-size: 0.6rem; font-weight: 700; letter-spacing: 0.05em;
	background: rgba(0,200,255,0.1); color: var(--cyan);
	border: 1px solid rgba(0,200,255,0.2);
	}

	/* Inset Detail Panel */
	#detail-panel {
	display: none; background: rgba(0,0,0,0.5); border-top: 1px solid rgba(255,255,255,0.05);
	padding: var(--sp-xl); box-shadow: inset 0 15px 30px rgba(0,0,0,0.5);
	}
	#detail-panel.open { display: grid; grid-template-columns: repeat(3, 1fr); gap: var(--sp-xl); }
	.dc-title {
	font-size: 0.65rem; font-weight: 800; letter-spacing: 0.2em;
	color: var(--cyan); margin-bottom: 16px; padding-bottom: 12px;
	border-bottom: 1px dashed rgba(255,255,255,0.1);
	}
	.dr {
	display: flex; justify-content: space-between; padding: 6px 0; font-size: 0.75rem;
	border-bottom: 1px solid rgba(255,255,255,0.02);
	}
	.dk { color: var(--t2); font-weight: 500; }
	.dv { color: var(--t0); font-weight: 700; }
	.dv.g { color: var(--green); text-shadow: 0 0 8px rgba(0,223,138,0.4); }
	.dv.c { color: var(--cyan); text-shadow: 0 0 8px rgba(0,200,255,0.4); }
	.dv.r { color: var(--red); }

	/* ════════════════════════════════════════════════════════════════════════════
	TAB PANELS
	═══════��════════════════════════════════════════════════════════════════════ */
	.tab-panel {
	display: none;
	}
	.tab-panel.active {
	display: flex;
	flex-direction: column;
	gap: var(--sp-lg);
	}

	/* ════════════════════════════════════════════════════════════════════════════
	BOTTOM GRID (for Rankings & Feed tabs)
	════════════════════════════════════════════════════════════════════════════ */
	#bottom-grid { display: grid; grid-template-columns: 1fr; gap: var(--sp-lg); }
	#charts-col { display: flex; flex-direction: column; gap: var(--sp-lg); }
	.charts-row-2 { display: grid; grid-template-columns: 1fr 1fr; gap: var(--sp-lg); }
	.chart-panel { padding-bottom: var(--sp-md); }
	.chart-panel canvas { width: 100% !important; height: 160px !important; padding: 0 var(--sp-md); }

	#feed-panel { height: 100%; display: flex; flex-direction: column; }
	#feed-body { flex: 1; overflow-y: auto; max-height: 300px; padding-bottom: var(--sp-md); }
	#feed-body::-webkit-scrollbar { width: 4px; }
	#feed-body::-webkit-scrollbar-thumb { background: rgba(255,255,255,0.1); border-radius: 4px; }

	.feed-cols {
	display: grid; grid-template-columns: 1fr 80px 80px; gap: var(--sp-sm);
	padding: 12px var(--sp-lg); font-size: 0.75rem; align-items: center;
	}
	.feed-cols.hd {
	font-size: 0.65rem; font-weight: 800; letter-spacing: 0.15em;
	color: var(--t3); background: rgba(0,0,0,0.3);
	}
	.feed-cols.row { border-bottom: 1px solid rgba(255,255,255,0.02); transition: background 0.2s; }
	.feed-cols.row:hover { background: rgba(255,255,255,0.05); }
	.f-asset { font-weight: 800; color: var(--t0); }
	.f-ts { font-size: 0.65rem; color: var(--t3); }
	.f-dir.L { font-weight: 800; color: #a855f7; text-shadow: 0 0 8px rgba(168,85,247,0.4); }
	.f-dir.S { font-weight: 800; color: var(--red); text-shadow: 0 0 8px rgba(255,61,90,0.3); }
	.f-out { text-align: right; font-weight: 800; }
	.f-out.p { color: #a855f7; }
	.f-out.n { color: var(--red); }

	/* ════════════════════════════════════════════════════════════════════════════
	LOGS PANEL GRID
	════════════════════════════════════════════════════════════════════════════ */
	#logs-grid {
	display: grid;
	grid-template-columns: 1fr;
	gap: var(--sp-lg);
	}

	#logs-filters {
	display: flex;
	gap: var(--sp-md);
	align-items: center;
	padding: var(--sp-md) var(--sp-lg);
	background: rgba(0,0,0,0.3);
	border-radius: var(--elem-r);
	flex-wrap: wrap;
	}

	.filter-btn {
	padding: 8px 16px;
	border: 1px solid rgba(255,255,255,0.1);
	background: rgba(0,0,0,0.5);
	border-radius: var(--pill-r);
	color: var(--t2);
	font-size: 0.7rem;
	font-weight: 600;
	cursor: pointer;
	transition: all 0.3s ease;
	white-space: nowrap;
	}

	.filter-btn:hover,
	.filter-btn.active {
	border-color: var(--cyan);
	background: rgba(0,200,255,0.1);
	color: var(--cyan);
	box-shadow: 0 0 10px rgba(0,200,255,0.3);
	}

	#logs-table {
	width: 100%;
	border-collapse: collapse;
	font-size: 0.75rem;
	}

	#logs-table thead {
	background: rgba(0,0,0,0.4);
	position: sticky;
	top: 0;
	}

	#logs-table th {
	padding: 12px var(--sp-lg);
	text-align: left;
	font-weight: 800;
	font-size: 0.65rem;
	letter-spacing: 0.1em;
	text-transform: uppercase;
	color: var(--t3);
	border-bottom: 1px solid rgba(255,255,255,0.08);
	}

	#logs-table tbody tr {
	border-bottom: 1px solid rgba(255,255,255,0.02);
	transition: all 0.2s ease;
	}

	#logs-table tbody tr:hover {
	background: rgba(255,255,255,0.04);
	}

	#logs-table td {
	padding: 10px var(--sp-lg);
	color: var(--t1);
	}

	.log-time {
	color: var(--t3);
	font-size: 0.7rem;
	font-variant-numeric: tabular-nums;
	}

	.log-asset {
	font-weight: 800;
	color: var(--cyan);
	}

	.log-message {
	color: var(--t1);
	word-break: break-word;
	}

	.log-metadata {
	font-size: 0.65rem;
	color: var(--t3);
	margin-top: 4px;
	padding-top: 4px;
	border-top: 1px solid rgba(255,255,255,0.05);
	}

	/* ════════════════════════════════════════════════════════════════════════════
	STATUS SIDEBAR
	════════════════════════════════════════════════════════════════════════════ */
	#sidebar {
	position: fixed; top: calc(var(--nav-h) + var(--sp-lg)); right: var(--sp-xl);
	z-index: 40; width: 240px;
	}
	#sidebar-inner {
	background: var(--glass-bg); backdrop-filter: blur(40px) saturate(150%);
	border: 1px solid var(--glass-border); border-radius: var(--panel-r);
	padding: var(--sp-lg); box-shadow: 0 20px 40px rgba(0,0,0,0.5), inset 0 1px 0 rgba(255,255,255,0.1);
	}
	.sb-hd {
	font-size: 0.65rem; font-weight: 800; letter-spacing: 0.2em; color: var(--t2);
	padding-bottom: 12px; margin-bottom: 12px; border-bottom: 1px solid rgba(255,255,255,0.05);
	}
	.sb-row { display: flex; justify-content: space-between; align-items: center; padding: 8px 0; font-size: 0.75rem; }
	.sb-k { color: var(--t2); font-weight: 600; }
	.sb-v { color: var(--t0); font-weight: 800; }
	.sb-v.ok { color: #a855f7; text-shadow: 0 0 8px rgba(168,85,247,0.45); }
	.sb-v.err { color: var(--red); text-shadow: 0 0 8px rgba(255,61,90,0.4); }

	/* ════════════════════════════════════════════════════════════════════════════
	RESPONSIVE
	════════════════════════════════════════════════════════════════════════════ */
	@media (max-width: 1024px) {
	#bottom-grid { grid-template-columns: 1fr; }
	#sidebar { position: static; width: auto; margin-top: var(--sp-lg); }
	#kpi-row { grid-template-columns: repeat(2, 1fr); }
	#logs-filters { flex-direction: column; align-items: flex-start; }
	.filter-btn { width: 100%; }
	}

	@media (max-width: 768px) {
	#kpi-row { grid-template-columns: 1fr; }
	.nav-tab { font-size: 0.6rem; padding: 0 var(--sp-sm); }
	#search-input { width: 150px; }
	#search-input:focus { width: 180px; }
	#main { padding: var(--sp-lg) var(--sp-md) 80px; }
	}










	/* ═══════════════════════════════════════════════════════════════════════════
	✦ 40-YEAR POLISH LAYER — QUASAR AURORA INTELLIGENCE
	✦ Author: Senior Principal Frontend, Apple HIG-aligned
	═══════════════════════════════════════════════════════════════════════════ */

	/* ── 0. Space Wallpaper ──────────────────────────────────────────────────── */
	body::before {
	content: '';
	position: fixed;
	inset: -50px;
	z-index: -1;
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EKY8khgynOFUDTPJMhJgJOynGcoIEDkphvrUzplrR63iUnt6KQc4AgbIaN7tRmIUcQgAkKToxp2hDSM4ShShMDOUSREYSUy3xQBiFDSCFINhSeBCppDB2UXKTRHNRdvPNCwgJSIgqQ2lRdvgIyeOoUFKEoQJCEIBCEicoGhCEChMtBbCEIACFOm+GvZAOob9FW4wmDjZFRGCnq8E2tBBJKRAjeUXRBAQmgEIhPkjWiCEBMIuqAYMoJJROIhSZsi6EeKkhEbdJUQCeuEKdSC86fixhQhF0AmAgGDKCMyo1p0PwQ4dlG9oBe0XB1fuhbT+MifjR0XO1ZgJCm0O1AZTPxiqSCCiFKcIG5CbSzv2RhEKTtoRsi6iMIjxTk9EHZCQi1wAJa4Nd8UkYKIHQrRWuq9W0oW1R006AOgRtO6pJnkjVRIJSOFMBJyrJBEOloaHEuIAgTJ6ICspVq1GpSqUajqb6TxUY4btcDIKilVZVoVqtvWpvp1aTtNRj2w5p6EHZVrTxG7u+I8RueI31Z1xd3VQ1K1V273HmVTCFRORBCjp8VNESiWIQiFOIS5oaiBAB5oLQVOAUihpXA5JTJAwASAT0CnjogAFE1WjiNva0bvRZ3Hf0w0S8iM81mc0c0wCNih2FCq4CFMnCTt56qTbNiCTpG4UwfU0x7UnkkZ5K6Z0ggoCTvsWdIREoWmzsbq7s+IXdClqo2DG1K7pAgOMDzWYqeRO0oVbu9o2duNVas4NYNs+aOKWtSx4lXsKr2PqUHaXOYZbPgVCm91Gsyqxxa9uxHJQAEHJJO5K1pKiRCCIBPRLURyV1ekaVMEuBLgCAFm6RUTKid00upQRUXetumSkgjEJOBJwplJDSssxuhjWuJGrZTJULcND3d5MclUocAOagrSQWkgR0VcJ2ZsIpEQJTOCouMqJNgIcRG4SnwVtWmGgHUDInCNM+knmkWwrEETuqzqKik4ZhTeAFZbW1W41d0wu0t1OzsFYinT4oKsLCS1rQSTsAFEth2k7jdCxBN/JIhSdsoRCFF4zC0VHh9JjIjSr+FULOvdlt/cG3otYTqAmXRge9Zulkc92yiG+KvZTFRxBe1o8VUcSp7L4QjKkoblTKlKR2UZVgyoOEJ2IUGJUo8UpxsjV4Kd2p+YREhEptOciQoqJCE6g9bGySECtcG90CN1SVNjgAZym0qBU4GgnmFCckonEKAKQEpkykooQhCATbhMiU1GdhCEIgSATUXFRYc+CCUkEwq1oEwkSkTKS527AhCFBJCBkwhaAhCEAoqSQ3UoAmmYJwkgEIQihKESiVQ+RCcw3xUZSKlAUkIXNQhCEDbupOcXAAkwNlBCbAhCFkCEIQCEIQCEIQCEIQCEIQCEIQCEIQCJQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhB7vfCGjJU1EGSV9N3vgtPikcKagBKyySIBMKaCJTQWkJncIIlSAyFQVo9UKgEgyFqumFjgDusxUxWiSRlBCEEYmUtZqJEbIIBGUElGTuFdkJ2Ak0yipjdAB36oUGScKMKRBGZUTnMq7QojZHIjkUi4lLIU2aP4oA3Ck6oSFAkyCTCnVaWvieSbjOiQoJkkp1KZOYRq8EAQd0OlU0ThJwm4U9LS2Zj1p6pjEEBNUipEKyB0UFqKm0BoEIDyyQ3E7pNUjlZoYCZwk3Cm8RkbKrpBMDMpiCcoO+NlU0ZdHJMnZIBWU263QhoASEiFOm0nZWV6OgNzkiYhVVGQlMkBShMNxJQkJ2DIQCkhCwzumkjPJCQ0pUi0xISAJMbIaRSLZVj2OYYduoEKM2IkYwokQYVkJEZVTSCipEZQRCIhCD7fYpFSpnQ/VuYQUt5ohaLa1NyKzm1GM7tmsh2JyqdMKISk3GqRySLSgjxKpoPgRCiXElKFLTndFMM9aHYSc3SYQ4+t5JEyZKLDJlJAQd5RdBAQpIaRCJgwphuN0tJ6qNSEGk8kKaaG0AJUwEbqTRlLV0jCakSCcbIGJwosRTA5pJySAOSaXQa4g4wicp+xKJVXQKSmRCiRChokNUkIujgaZCWEJBVkFATUiTySLr8EZShTIGMzIyopClCeOYlCYVXpLSEQOispxqyJSA0ag4apGPBQmPZCB0QnB8VMASJCHSrGUZBjmmRBRE7IaDQCMqJCcZQiaRUXSpndJRdKwFZ6mjE6kw0EeKNIa3bPNVNK2lMiUGI2SKIichBGVJLkonSIVbgRuplKJHNSs2IBJw5qUkbJFWXbNiPeVGsfSDiGVANQBwY6pQApEA5UYKmk0ThzUFYdwk7ZRFZEofJCaZYXCQlTSNRukA9Qoqw5gHkkd4Q0qDC44RpVgloMGFB26zTSBEJKZUEngKNXgkVM4CRwiIEBGkJxuiEorIBVbhBV+nxSLAVJTSgBMEq7R6vKVW8Q0q7RWUSgbpvwqiLjkKVJ7mBwa4jUIMHkoGJElOYRFtOtUpNmnAdEA9FG2pipV9d4bJySoFAnTAVE7ltIGaTnOZMetuqYhaLk2xZTFuKgMevrPPwVIKm9lgiPaomZg7KYSmUFSC06VY5oPgh2GEKaRQGiVa23qut3XAYe6a4NLvHooqba9Vtu6gHnu3O1FvInqsVZe/dTsUnCRKk7dKDCHughSgdFECVrbQ5IBhabo0XNYaQDTpAcPHqszlg7BCIRAHNDYa0EFKE5gpFCCEQmNlq4ZZ3PEr+jY2dI1biu8MpsH5xOwU0lrGgq+/ta9ld1bW5pmnWpOLHtO4I3CoUWBCEIJoQhRkIQoGQYClulhkyooSWLdtSJT4JEykhNgQhCgE4SQgkAgbwhAVAlKaMcwgOQKQTQgEicJpGEqkCmUlIAeaRUUKWOiigEFxIhJCxctgQhCgEIQoBCEKAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCD3ztvFQdPUBTUHcl9KvQA7qouMlIpgDmVGKiFKEgmos7pASAmzJSZkKymCTjdajS67MiT0ACxwujf0DTtqDy4EvErnlpUiZTVRQmMBKFGEtUUi0BQ0kKRSmCi7Vv8k31nvawO/M2RVzlQChUnmXEqdpbXV4+oy0oPrGkzXV0/mt6lUuGVJlSpTDzTe5mtul0GNQ6FaZqIgc1FycANMrXc0LNnDuHV7e5qVbirSJuqbmwKT5wB1EJ5GM7QkSSZKkCAIlIrISFKg/urinV0h4Y4EtOzvBX39SpeXbrp4a0vOGtEADkAmhQ3mnMbQirTfTdpe0tPQhFJzBTqNcwOc4DS4n4qsugwZUXAyI2CGiOcprfkQQpoVnYJuyfNAPVSGSD0Te1nkNwVIyThLcpwVWzTG60UbtlLh1zZOtKbn1y0iuT6zI5BUIa/AHKAFIDqgN5nZF0sozqgGDyK992l7Q9kX/AAR8C7PcE4WK3GqL+84vxN7CHCpJ002noQfoXggHMIyPML0192tNx8Hdj2Mbwu1pMtrn0h92xoFSq7xMTCTyzcLa8uATlAHNWHAUSFpqQhhEKUAjKSHSTht5wEOGl7qZBD2mHNOCCpDD6bx8am9r2+BBkLZxviV7xnibuI8RqCrcuaGlwYG48giSMajHgpndT7o6S4OaQPFF0oeS52pxyo4U3xsoaSjCLzpbq5JBwIwVMgRpcNTTuFo4pfXF+6gK+gMt26aTWtAAH3qbZsY55KJECVZCThKrKtPQSC5o23QBCk0DS46iPLmgqAPNTGyClImJRDcYZK9i3sXa/wDweqduqnGKTbocSZZ07OR8Rwy4+K8c74sQuvxDiF1xHs5w/hVvZ91a2Acbio1xIqPLiQ5w5EDC7cfT03bhyzO5YzHxvv8ARz7kWYp0vRTUL4/G6xifBUQngABIjqYXGu8QcMSkApmDgKEQSEdJ3CcSgDCbOalUkwE5TB64RdF0TCCIQ3ZRRsQmjmmVdBJgkA+KSnTaXyBE+KGqgAhSIgkFAElRtFTIhKEKsp020jJqOIxiOviomAcJJEw0kmIRrRkphTuba5tnMbXovpOe3U0OEah1CrghECEQeiIV01IEFPMQiPFNGiKFN0ETCGiVE0gmrNKirI30kACPFDgpBNU0gFICUw3O8KwRsRhRcYgGkCSMILiRB2CmZLY5JEIXFUWlKFe1h0yDKjCJ0qoPJI+qCThWkKJbq9U80LIvveG8TsrOyvbywr29rfhxtKr2w2sG7lvWFkWu4ubmva21tWuqtWja6u4puOKerePNZnAbBSsaRiAk7ZS23RpMKCBUywmmHlpAUDspte/SBMjoqzVbxzG6iJU1EiSiTuSiVIjMqJEolOJVbh6xU2u0ggc0OGyyyrIS0lWOyhzhCbRVHPoYWjiNjecOuvRr62qW9bSHBrxBIOxVGCNsq2pWrPqvqVKr6j3jSS9xcY9qzUsUkIGCmkMrLKD2kukKCtJGZVZHitKBlsJRInohCGk7ilSaGOp1C6W+sI2KohTMHYpkSYIypUUweiZBVhGIUXt+xSppWkE0KID0WqrYXFPg1Dijiz0as5zGwcggxlZUi0u9Uudo/RnCC2tb1KDaZqMLRUbqaTzCzPHrYyrq9WpU0h7i4MENnkq3KbFThIwq4KvIUHBXaaVKJaYlXNAnJT1Na3aYOyXLZpncC3MzKkw80nwTsojaB1V2i0EJeSrSBPJNosGB1UQBByJ80pxCRCbLFzW6sAOJ6ASoOB2GQF6L4OO1972K7T0uO2Nna3delTextO5YHM9ZpBMHzXDv6r7i5rXVSBUqvL3BogAnOAul1pnTIYlBQZKS41QUi4gQmU8EHOUIjvskBBU6caskgeCiU21Ki7dJNIqLIQkpkQpN2UXboXRJiSQAMlHkgOIIPREhgaSdQhTpVX03h9NxY4bEGCFW52rzShRancVH1X6nuLj1JyotEkCYlRT9qmjZvEOiZTYxz3aWiSo4U6dRzHam4KCJAwlsmUpUU1F3JSUXLOXgRU1BCzLooQhCgEKRKW6uglJRTnwSBpBNAQMpFCFQIQhAhumhCihIpody8kEUJHdCxbtQhCFAIQhAIQhQSc2GapUU5KSUCEIUAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEHvzsoESrSJCrlfS8vRVbsFImTKk8ZSDZ5qMXuITIhJWIuIbgQraIzk7qoBW08kDxVbjXxF00bdhHxWLnkyV0uLgA0hONK5pBD4UMu4ICgBKmVH4qOaKRiE3mREJs9X1iFKulTjIhQIhN3xikVIuiAxlCIhEdFdsUESgO0s0gCCjJEwonIUQkISKmwSpB5BaQTLTIyoplILa9WpcVTVquLnbSqwY5JTAKYPqkQtbEgZS1eCGBhJ1O09MbpASOiuw9XgpNc2MqEeKYEHdVZ2WvYCGlpmRlR0kKewAmUklbDdoUgon40+CkFrZ7pYQAkN1Npxsq0bVJ4hqbcCEzlGpEQ4n2bKWYlDWq2kxorUH1GF9EVQazAYLmcwCtNaVOTa0lauL1LG44xdVuGWr7OxJb3FBz9TmADMnnnKpAKJJ3QDS0kFAU9ygDKFxRc3SQCoqx4c5wkYSOOUKs6JgBcJTqMjLcBNoEjCm4yIOyJZ2UEKJbKtcMKAUZqEDmVEtJOFMhRM+SJVbhBiUoype9RlE0IxCgBB3KuJgKE9QonShpkzsrn1HVKdOgWthhkEDPtKglPrSEZDmkGFLvarKD6Lajm0qjg5zRzIUSSTlEqpooiM45qL8y7VAHNSeSeRhQcNVItOxwoshkFh0uBBIDoIgwdiiFr4vfVuJ3VO4uG02vZRZRGhsDS0QPasiNgCEohNKcoaprodn6nB2Xzjxy3q1rQMMd2fWDuR8VzgUwSjRtH4sSckk7RAnH0I0oBROYUakPlKmHN0xGVApQipAJ7dUgIT3KBEygGFr4ZYO4jcG2p16NF+gvDqrw1pgTErKwzTBiChO4SCkpAZVXpQOInmhzQ5pa4SCIK6nBrqztW8TF3ZC69IsH0beXR3VUnD/YueGRTYJkhgk9TCpYtu7y5u61KrdVnVTSp92yeTVS3fITDQghO9XSM7ohS0pJGpChXNZ3j202Al7sNAG6rEld7shxkcCub+6PD6N86vamixtT+iM/HHiqWOA71XQ46cxlTDS1wK28NvRZ2d/RfbU6xu6JpB7hJpyZ1DxWQS1oB5BXS4xAmXEpnaIhMZM+KCEbsABiEwExun7EqaRcBKYCcSphplRqRBEyIVugJ92OSGldMljg4bhRJzJG6uLOig5uYiUSxAwThRMDcwrC2BtCusnso12130W1msPxHbFTTNmmQwdsjqoASd1fXf3lWpULQ3U4kNGw8AoFE6VYZvlJwxKnJJiMIRNKnbKKscEnjEBRjKK+aUbq0RpyMqDgomtIqOnyUwEj0RNK9DnOhokp6eR5bqyS31gcqDnEOkc91NM3FEj1MbKBEq1zpbphRAhTTNiLgkVJohImVLGUHbJB0CFJ2VEhZCdkykRATCRKCtBarI6qLldmlZUiZIJTInZIhGUTupFrTA5uEjxUXCRC6F7xi+veCWHCrk23o3D5Fv3dANqQTPrPGSpTTmlpacp1nNJ9VgYApEzvlVuEyozSaWzEoK3VbqhU4ZaWYs2srUC4vrg5qAmQCPBZXMEEg+Sl0aUQgqWlI4UNIqL2yZU2j1girBcSMhTZpS7yUSFY4SlCbRS5oUSwxurnNjmoSrs0rEdEjA5q4AbQoOaOiu00rTUnDAgJacTKJoapSc6U9PiiPFXaUhp0qBjkpHZRhRCxzQd04ScgSEIAJkxhWrCdskAtABfQjQ2GbnnlUEROVlr3J+DhKPFCkBlEvlEiOairHDKrUpApAyooRTSTO0JIBA3QgbqCToBgIBlMgREJAQoUyokSpKMypSVBCELmoThJOUBCZQUiqEmkpbqAQhC0BCEIBAQhS7AhEZhTNNwwQQeiCCTgpOaWmColSrEUIKFhQhCEAhCFKBOUkKAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCD35JGyipP2wlsvox3vhB/JRVhQmmUXbhSRCQEKkukwVbQgPBOyrYJCsZuq6Olx2kadKwa5oBdbz55XIeMrudpx+NsA0kgWoj3rjkLMS1UQoPVh3Ki6YwqeVTsiOaiZCvptDzkAQq6wBd6uwWalVKJO0kDxKb1ZQq9zWZWNNlUNMljxIKghUbpMSDHMKIPMK25e2rXq1GMFNj3ktYPzR0VQGEYpEwlMpgyk4kGFKgAk4SeIMJtMZSJJMlBEpock4EDdAyhRElSQAwUy4gpTCRMqizdAOYUWmCpeSu12mAm0qDSSYlTbuVZ3bngAypBIbqYGVqNSGBlTDYOAkBCkwrcdJEgCVIDCBlSaMI1MRCspvDYBGEtPiSp6cCQq3MUNI1kxvsnAIITDM4VpDdJbHtTSTFS9oAEZUWgq6EiFdLo3QWgAgqot8VYiJV0liNNoJGFaab3FzGMc4in3jtImGzElDG6Z8RC9Fc9pbw9geH9maFjaUWW1eal3TpgVrhkH1Hu5ieSa7OOcvs8o7KrcCtFbDiAMSqCspqxApHx2UiJShEVuHinp6KSgZHVEsJyiE027omkITAGPpQdyEwJwN+iIjCBum7BjooomjBwVEpoUXRIhNI7ptJClJPxTSN6KEbIOAoyUXSaFE5TCKkUIbumN1FkNNEJkQrpdFAUokbJBMt8UakKFIAyMFOFaHDue70jVM6uaq6VtEIB8EIydkNGQg4KiJHNNNLo+UqAPJSEocFYugArWmGkDEqsBSGysNbSScSTnKFNgJkgSq1IrgdEQpFEQi6RhTa3UgTOVYGgcypTQaAFKEZUhEFNNTEs9DCcK2k5rqLmOMHljdQhNNdMRGFF7ZVo0jJEhRdGokbFEuKkzEbykAVYQjT4oz0qi3cqA3VxG6iWgZUZ1VUZlBABU4SIUSxWd1GFMiCnp9SZEzsjNimoQXYCiZJVxa2JUQ3KjnZpUQYS5ytAaCfWMKl7Y5yozpAqMSAYUgholERIAaFArs8NteBVey/Gru+4u+34xb93+DrIUSRcy6Hy7YQ3K5T2tAwcqbZV7oOykox4qbZ0g8EHCiVYRKjErNZVRCbRLwCdInJUyBpKiN06hKvpa7Sw6gOfVUuCseokJoEgjxUXDEpwE91LNJYrQgphMoIuBBjoowVZULXbe1QWdmkdlJjhnCClKhonbqMJuBOyUeKgUJKUeKTxpMEg+SCBMCSk9pBIIII5FOAXt1bAyp3VV9a5qVTp9c8hAUYsUkKL2gcirIQILYhU0o2z0Sdkyr6jWgR71CozSAZBByIKoq2STcEgiBRdhSQhYgQolWqJRiwiAKYxkqtynyhLSXOgDKIgE2v0tLcweiIIOUFUga5wBAODuonZNEIu0SIS3UiJQIA+1RUTJRp8VbVNOPUaQqkBp8URCaEEXJKyJG6jzKlCDUhuhTImFNgSJhNCiIgwmmohSqCJS0qSFNLKrQhCwoQhCATCSEEkJSiVdhlKUFJNiWOYQhCostqvcXNKtpD+7eHaTsYMwuv2y45T49xypxOjY0rEPAHdUviyOa4iMcwpo0bnF5k7pOCHYMKKzasCSaSyoQhCAQhCmwIQhQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQe+MHcIzEIgoXvdBE80aQcyhDdimzZQmArDTJa4j80Au8J2VTcrUom3mtFHJaNJMuDYHMkwqGjddbs7aVL7jVjY061Kg+4uKdMVKnxWS4CfYpldN7dHttZ3Fpe07a5pNo1KFMUy0cuf3rzT919e/ynuDcH7Ods+H8F4RfV780rAG6uKrw9zqs8zzMEeWy+RubhYxu5DqmXhU4YlRVhUCuk7LAFW4YMBTgqLoB3hWjO4IBiBgkkAR1KseJKiBkY2MrKJX1vXtLk0LhobUAmAZVR2VlZxfU1ucXO5k5VZ3JUYtiLRiUnclInCjEc1KiKEyokKAKEikhtIGB4pGYykAmVUhtOE0NIDIO8oMncqqY3UlECVKfeoujKbTBVtq5o7wupteSwtE/m+PmqxIGcrcdJDG6lskFIArc8umMWMCnE4SZCmwKx2xibBGFYGcgVAK1gWo1ImYIA5hSgRCA1ShV0kR0ohShMNkoSK90ROFbUZpICiQVqaqXFCJ8gp6DEhMNKm1pI6JeyXEmglMyGEThTY2ZypVWN9B1gQ4vhTbFx7MDmySVXUaAVocDjCrqA80Y0yubOyQaQtlu2horOrl0ime7A5u5Ss2hwaNREwppi4qzvCCAU9PVEKMWK3NhIqw7qJEqiGymxvxnTHgjT4pAHMZCM6QcowpOB6KbSAwg7oWKiIUdQmNQnorWyCStLLmh+AavDncOtnXLq7ajLyPxjWjds9FEYwJ5oIhN4gqKmkKMocJTJ6pQo1EdPiiI2EqUIhGiCYTAhX2Fpc394LS0aH1i0uDZAwPEptqYqQiEyHNc5jsOaSCPEJBTTQap845KIU2q7VIQgJSpI1IEwjdJs7qtpQkApgJtAIgq6TSBCWkqYwkiQN3U3hpbgZUYhTmTsq1pCFKEwJUwByQ0iGyApU/VMhSAhNVqRAiSjSpoVJEYCCMqUSlCnhqYmExvKAI3Uxnmq3II9bATA8FOJG2U4RrpQLSUiFaB0SLeqiaVmNJwoEK0hRIVSxXpBRp5FTgrTbW1Orw68ual3So1KBYKVFwOqtJzHl4qJcVLqPD/wAEWdShdOPEnXD23VFzTpZS/McD1OVGg20p0L83Je6q1oFsG7EzmfYoFo3iD1US3KmmfCo0/VB6qtwMrQ7LY2VThkxso5ZTSuEtICmgo52IOCrViWyiaUOaQlCvgAqBAiU0zcVfKOhkKLhMKZg4kSkVGLFZBhIKzKUCcqaTSv2qLugCsgKJEFTTOkRHNRwThTOJxMhQAysWJYCIGVGASpvMhRaFEkVvbJ3QAYVsDmomFdrUISITBQSIyUZVn70lM7KBEKUByFFSKULIRXQr8GvKPZe07Q1KlD0W7ualtTYKg7wFgBJLd4zuueUgxu8ZQ8HTdoqtfpa7SZ0uEg+BUrqqbi5qVzTp0u8dOim2Gt8gowg+ajKLmxlLSZjknMmCm7wUEHAKOOasIUHCUCDtBbU0h+kg6TsfBbe0fEaHFuKemW9hRsKfcsZ3NIQ0OAgn2rFhRchv2VObzAUSCDlXKqoDqVjCMHdJWB0NiFAgyqpIQQUIgbjkhr3MrNqgCW7IQ5p0F3JGaqedTy4wJMqBCtUIIOyJpHZIhTdnYJFERGEjurabA45Ki4QSPFKu0Z9WISlMjKICKSIAThJECBuShIKVTQhCygQhCASMc05SKgEIQoIJKZS0+KzpuVFClp8URCaCKSZSUAhCEAmRCAmUCKAkmMKhoKEwpaEkU5lClVEhIBSKAsqUIhMlJEJCZ3SUqhCEKAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCD6AQRuokQplwO5woOGd17V6iQ5pLHNG5ELRWp06Yb3dUVJ38FWcFDbfxy+o3bLGnb2dKh6PRDKlRnxqx/reXJc8boDZUtJVjWzAytdpoaS6o0ubpIjzWWMhaKROggbRJS92r3j1Hb2hRt7XstQpMew0uCtFTUZLnF5M/SvKOb4r1fbru3UeA1WNPeVODtcT1GpeUqBL2rl6e745VZCg8ACVYQovGCFp6FWCYBEpOELrXVxwl3ZzhttbcPdT4pSe83ty7aoJ9UD2SubWguJGysozvw72JAS0lTdlVuRmouEqAicqwqDhiVmOdRhRJlSCCEsWVApJlJTRsghI4hNQLZEiJzHWMIcCWkAweq3cRvzcWlraU7elSo27d2j1nu5klUYU5SThTaybNuSrBuqxurUaIk8inumI5phajUSCm1uN0hKtaF0jpikwK0BQYCrmrcd8YbGSrWABJuysY2cqu2MNSY0kKxrcSU9J5Jt1mCAapBoVrWDRkZQ1ghNtdCsjGygAVpLcYChpI3CFxVtBVjWn3oB0qxpVZ6S7rJEiRyWirRb+BWuIE99g+zZSsaT61w2lTpuqVHmA0bld+4sh/wDDC+c62Lbi07SGg6odw3up0pbpw5flnd4l4A9ipqCTK0PaZdKpLcrTCo43youkmVcQolimksUkKBbJ2V78NUVNMXFniElc5ohVwdlHOxGmAHZyEnOIOFKVF2SqzpFxlAEiUNEpTBI5KVKOcJpJjIJRlF4zKTRhTUXOgwoDR6heThRhMOMRySCjUEJKSRWbW5CT5H1nNkRIMJFMZUjRAACAITAQApAKzssiTdlKPFDW43Uiq1IWOaYRCYwq0jPgpAGEmiSc8sLbe2ltQseE3FtfMual7bOrXFJs6rV4cW6HeMCVZpqMzRPVOEMw5OMqkhQjSVYxNWIiG+KkAAmUhkoa2MJtCSk2Cq3IM9FZSDQ1+sxjHmiIymcqNxFpaGERJPMqHJTggTyShWGkR8YBTLQDgpBTDZCNSEGk7KwANQ0QYUhlyNyGzZSDSTAQ0dFZTw4HojSDmkfGx0lGkyMLU91GrRpl0940QVSRCbW4qXMyTsolpC0RO6g5vvRm4qQ2dkObO4V5btCRaUZmLORhQcFpI5Kt7QGozlGZwxCGNBcATAO5VhGVE7EEI52M5AmJ2S5K0tgJFoGyjlVLhzUXDEq9zVWWGCVE0qUSIVjpBUXCSjNhiq2lwu+oCzoVql01rW1niX0NJmWdCdio3TKTDSFJ2qaYLj0PREHqkNlKxcVZChCscYydlKrRqMptqubDHfFPVTTNxUQkQp8ykRCmmdIE4jkq4zgq0hLTmRhZsTSIZqwAQUPpvYJcIlTLzvhXWtSgO9N1SdV9WGQdippnTEVEqcHzQ8GMqKgWEqBEK0GDskR6+QoyrPrCEEAESpEQog6nZ5KGkXhJ0RhTfhVpo0imMlNMghRNIkQUipHZRIxKJpEJoQRCiaRShTSOENKyMykCpkKMc1ERI8VEgEZUzJ5JQeiJpCIEdUnMIExKsMJcoVNKiMKBVjhySjMFVlBEwNKkWJEQoVFGmUFWsIgg802mlDm4Sa0c1YTEghIptNIGQZbgqDtRcSTKtUdPVXaWK0irCIUETvEgdLSImeaihBQ2RSiFJIg9FK1ClCNPihZAhCEQihACDhQCEIUAhCEAlKaEUiVGFNIqaNoJwgiEQstGAeSAhCU2Etk0KeAIQhQCEIKASKJTRUUIQs1SKEyiECQnCIUCQhCAQhCAQhCAQUIKAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCD38CQjDfBSUKw2K9+9s+BKcqLdlNXUhLsMMKwGcQqgDJjkVNu6ysqavoS0Eg7gj6FURhW0my2fCVY3ctR7H4QqQpU+yVMYP+bYLo5nvCvHvHNe1+EdrfROxVdpJFbswH/wC8K8Y/YK8k1dPL6LPq49/nf7q1W7J81ZCiVI+hEXCAolh0T9CnEvgqwsEFwCuxhOCoOVj51lRcJV9mbECMKsq12FW5Zc1RMqLlcWjScBQIA2V8oqQnCSXsIlBUyksIGoQmEWeSAlHNCYR0lDVYEgFJFACvaPxU4CqAUwtabnZJsgbK6kBGygMhWMGy3K6YpswrmjKi1uQrWBdHpxhtC0UxsosAWik0aUr08ch6YT0+KsUmN9aSEd+lWmArdAJJKkKeFV6FBCFcaR6KOmBkIz0qS2TKmynhWNbMqdJklFmKVo6pSf3lFxZUblrhuF6nh/Fbqv8ABbxrgrrWlU77jH4Tr3jj6+rQG6AF5+hSAku6Lt2IaOwXEfWLfyzEDfAwVM/Dy+qx7Yz848a+mYEqiowAroVmjQstRoHitSs3Bj0icpFolaC0dFEj1it9memM72FVhpBytZbKqcFIzZIzETKRbAVzhBUOcKac7FJaVW9mZhaHBRIwpXOxS1pc4CIylVaG1HAGY6K2I2UHBRjSlNohWAdQgNU2zYrmEiCVbpBS0+KEikoAKmW80afFQQKWVNwzCiQs5OkRTCAmm9NwKTTGd0bpgQo1IsdoLWlpydwjZRGE0laSQhoU2kgLWyTaITDRMxnqpQeim0zuq1MUWjMqTQpCCpABaVFMeKkApASrs0hBRCt04UQ1U0WkQmGwFPTgIAyFGojCkBKm1onKtLWtEDmjcisgC1c0fGLwfIKpWESU9A6K7XSpoypnAEYUtI6JuBKiwh6ykGgbKVOmIMlT0xujpIiNlY2eanSYC0YVuhnRVuYizthXbcE1GN7mn3mTv4KrRzHNXNAaTA3EHxRA6EJpddlBaQOoUHCTMrSR60qDhlRFOkoDStDWQ3KUBE6VBESCqnha3DqFU4DeMIzliyQQoOC0ubnCqe2DlVxuKogHbChCtIUCMo59KvZJw5SpnKHCFGLGZwyolsLQQOigRmFGFKlSpVK1QUqVNz3ukgNHTJUi0dFdZ3Fexu2XNs/RVYHAHzEFDsxNcHUuRBQ8kta0kkDbKmKbadFtNpw0RlQaMkKMVURBQrICRA5KMaVKJVukJFqlYsVIVmkKJCmkQMBRLsRCshQc3KaEMdEKwAHdGAdpCzYKC5rnaWmSN1EeS7PEeLG54Bwvgw4fQt28Pa4d+z49wXOJl3lMLmw3pyWEUETulAVpAUQFEvZCByQciFOIKUDkptNqyICgTIjkrnCRCiWgjoVRVCRCtawJPZGZRNFQFMVC6qNTYMDxSrODwIYGR0QEoU0aqACi7dWOSUZ0rQVJwQB4oIOaPJRiFZBQQm0RZTdUnQ0mMlR0weRWy1tbyrb1q9tSqPpU/wCdc0Yb5rO4CIKiaUkdFB4yrtHikWwrKligiCpGlUNv3wYSwGC7xVxY0t2UZOjRJ0zMK7TSmJZ4qGkjdXx9KgRBRECYEKDjKtIlRcBKgi7DRjKgQFd8YAHkowrtFZaR5KJC6bOI12cCrcI7ukaNSs2trLfXBAiAeiw93+LDpSU0raMpkSVJzC0wUISKiIQrIUNKlVGElOEoUTyQMFBAJTUSYU0EcFCYgogKBIT9iCEQkJwkUAhCilulBQhCwoQhCAQhBQCEQmFNLskEIchNBQgJoU0EkpJQppSQpJHdNBITSUNghIJoCaNkUJohNKSE4QAmk2SEzsgKKSE0IEhNCBITKSAQhCAQhCAQhAQCEFCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCD6A7EeaTjJQSSgAnZfRk0527IbqSiUJZsl0Gk5VgIUDHVJkA7pJs20sIPgr6WGHyI96yg4EdVoojU5jJjU8D6Vrjx3WeXPpxte4+E4Cjadi7YH/R+zTaZ/wBoSvFfmjC978NFv6PxrglCI7vhDGfTK8I+NS6eow6a8H2Ry/E4Jfr/AHVAQolN/LzSIleaXT7eN7AhWknutEKoDK69rVtzwKpQfTDrl78OjYBK1O7g1GquPVV9aA8joVQVUqBEpKaiUcqg/Kg5ulWgKLyNRlLdIpjCrKtfEqsmTAWU2NJ06lBSOx6KKJTTCQwFMCdswjUpJtGZQUAo2sQgJgZGEbSGysZsojdTAjbZbjSbVazcKtqtY3IWsXXCLqeQQVoohobBGVRRGVpaScRhbr04m3BhamSYhU02y5a6DZCPVxQw1WASpBsq1rAq9eMV92YDirBTxlXBnqiFLRLoKOnSzuaoETg7LW+nEKgiTKqXDuqc3MAK+gzISAzsr7ds8kXHGLqDQDtK6tKmG9jeJ0S8aTcd6BGxiFit6cgldKpTI7J3wgCawH0KZJ6jg6pNPG1BLQVnqt9bC3PbAhU1GiSVqPHlh7MZaeii5uVoLBMqLg3cqueWGmVzTKi5pVzhlRKrnYzlqrLRyKvIyohhLZxARzuKghRc1XEKJClc7FLgokKwsQcDZZ8OdilwwtPCKFjccTo2/EburaWrzFStTZqLfYqSouBUrnZ3KqxrK1VjKneMbUc1j/0mg4KjCmxpc4NaCSTACT2lriHCCMEdFEVuGyRGZW3hL7ajxOjWvrc3NswzUoh2nWOk8lDiVS3r39xXtLQ2lvUeXUrc1NfdjpqO6uuzEvfTHUUCCeSmRCCsV3xm1aYUiCU2g5WLXWTR0aVWtUZSo0zUqvcGsY0SXE8gtF/Y3fDrx1lf29S3uWNBfTeIc2eqroVqtvcUq9GoWVabg5jhyIVl9e3V/eVLu9rvr3FQ+vUeZJSrIzwVYEkAkJvbchhT3woKxgkKgarA0QotEBWUxqdExKoGjKlGYRGcFSedTiYhbiwkxsmBhSaCOS00BskRndMeSAqhQpsAJym0SpwiyGGZEK+jTD3NpyAXOA1HYDqoMy5WQYhV1xi3ilnRsbx9Gnc07mnALajNjIWAtBkkq8hQLfBRVQEtClpMBWBgkK+2tbq6qGlaW9WvUALi2m0uMDc45KKz0wWuVoahgPMqxgG+6NRJlNwpa5EExE5V1Cn3lRtMODS8wCdh5oAloU6MB4xMI9EifErOtw+9qWdw+k+rSMOdScHNPkVRA6K+t6xJJyVURhCYq9OdpCKjWlwIGOasAxlQAhGbj3IygtCm0ZVrWtPmm9NTHbM5uCIVD2FdCq0aBA2WZwgq7Yzx0ynaIVFRhiQtVRpOyrhI45YqWtBbLt1W5vtWuvT0CmZadYn1cx5qhzcptxsUEQokK0hIhGLNKS3KicbhX6eqg5pKjFkUECUnCFeQoPGE0xYzkE7IcFYFFzVKxVcYUSFNCjNivT4plSOEoRmxU4ZUCJVzhAUC1RhW1upwaNyYTq03MeWOiRgwmMGRyTcS4yclRVUeKUK80QaHfh4kO0lvPzVaRIgo55BWOCjELGUSoOEqMSd1NwlI5PRYTaOyRCaESoOGFENypkE8kEQozpBG6cImMSM9VVlQLAlA6hTUdM8k2VVGZVwqAWrqJYCSQQ7mFXpPRIg9FE2g4ZSKmQQkVNIggKSFEsOm+pTa5rKjmtd8ZoOD5qB80zMJaSptCQgRzTVCJxCrhWwlpSM1THgolucq6JIQ8Eq7Z0qbTJDi1shokxyUFc0uaHAY1YKjpCgrQVIgSlAV2IESmBHVMCDMJuElRESZzOVA4KmRCCgrhRIM7KwNgyUwgpOyFNIhFQKgVJ+FBNojEcygHKkk0EIJuwlCSYWQkJlEIIndRUjupNid1LNitCnUUFLNAQhCihCEIBCEIGEnckIRDCSEHClaCEIUAhCAgFFSQgihMpKAQhCAQhCAQhCKEIQpoCEIQgSUkkUkJoKgSEQiEAhEIhAIRCIQCEQiEAhEIQCEEQnCBIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhB9AAzKkzB8Ck2SYhONJgnI3X07i88rd2hq8LrcVq1eC2lxaWGlgp0q9QPqA6RqJI6umPCFziNynj/qgnACsx12W5I80xlLIMaZUwM7LXSxtJuAVptzpex/6LgT71naATuryQKb8/mrfHNWOXPd4WPp3+UCNHangzeZ4ZTd7zC+eX9vVtb2ta126KtF5pvaeThyXvv8oKsKvabhFRpEDhtJk+Ie0kLy/whlp7e9oSzDfwncAex5/cu3qJ+L5X2Ly/wcNeLtwHCY8EozCGxq6hT3BC+dX6THJAAdFtt2n0Zro3c4e6P3rKG9F0LUTYUjyNaqNujaZ+9J5buWo5Fdv45w8VS4QfFarkDv6mPzis7lU6lblBwIOxVp+lE0+5DBS/GayTU1H1mwIbp2EEEzzmOSaYuSqIyq3ZdjKujChGZ28Vuzsz1M9ZpaASFU0Q6V0OIVras21bQsmWppW7KVUtqvea9QFxdWOr4pcC0aW4GnxKwOMclj2XfdBziSUoSJTlTSbOmeStpiJVIwVYDhWYrtYYJhIhShOBEQpY1KApIA8VMBI6ym1pIkbKYBKi0581Y0LUblNoVzB4qLWjOCtFOk5unvGOZqbqbqaRqbmCJ3GCJHQrWLthUmNWhgUGtxEq6mMjC29WKymJ3Wy2YYCzU25MAyt9s3y8kezhm0wyDnmrWsBUnNiJ6ZKvosBiAMqvZMdUmUjoB5EEj2KRYNQMHIBXSvKLWcL4O9o/nrJ9V0bGbio0fQ0LMaZD24BjHhgBJdvRJuSslw0AR7VmLc9F0Llh0TzhY3NiFduXJNVVAGScASfBabYQlQL6VVtSm4sqMcHNc0wWnqCr7dkAADAROPy127Ypu8QvTUremfgs4xcPaHOp3cNdz3pD/mXnrdst3G67bL6uOw/GeGaKQoFhui4D1gTc2zQPKJ+lSTd7vJ9s9U9PjljfGUeDqt2Wd4JHkttUZIgx4qkUy5zhqptDWOeS9+kENBMDq4xAHM4XS1vKarE4RuqntnZansztCiGJtxsZtIHiqnNWp7OXOf4+5VvblHKxlLYUSFe4BQcMlHOxToLnBrQS5xgAcyouplri1wLS0kOBGQVMicRySEgZUc7FThCrcFe4AnCrcFKxYqOeagrSMqJCy43FXkZBII2ISADiS4kkqbgk1oM6naYGMTPgo5ilSq1qzaNCm+rVeYaxjS5zvIDJVcgtDgZBEgq5zHCm2q5jwx8hrtJAdG8HYxzjZUPM77qbSTdR0l7g0RJMZMBQcC1xaYkEgwZHvUgZlJ5Wb5ejCaICVJojmlEJlYrpPLXd0rJlnZvtrypXr1GON1TdR0Cg4OhrQfz5EGeWyx6cqQf1TSdmtERKkEk0VLkpMGJUQpjYKiQTGEm7qQWsaiQKaiDlMFdIsTlSa4gQoDKYVi7qxJqaYaMaXBxIkgTjzWqmzZurBsk0c4PnCmwSEbxWU25VwCqZurxsj0YxQ7dDA0vAdOmcxum/4yA3xUZs7kRJxgLVYXd1Y1TUs7irQquYWF1NxaS07iRyWbTndS5Jpdb8g+SnTUWtnmB5q1oiEai1jcKbB6yKe2ysY0EzIR6cSLUi2eauIlQODG6ndvSpzCoaSr41N5KOnxREWD1srU6o6pTpU3BumlOmBG/XqqGjMFWjEEnCaXGTauq31SVmc2ZOy6N1Rq0XOpVqb6VRsBzHtLXNkAiQdsEH2rC5uCeXkk7s56veMpEbqt2AtDhklQc2Qq8+UUOAg+KrcyMlWuGd0nH1ThHCxQQoR4FW4S9yrnYq04lRc3JWggjBEFVvGyjNihwzCg5XuaJMKtw3CVzyUncJQrCFFxiFnTFilwhRhWuB5wowjOkCiFPSiFNM1SQlEKxyiUc6rjBwoQVYUQI3WfCK4AKm6lpoNramFrnlkB/rAgA5G4Gd+eUaWnIKROIIUv5HdAhQcruSr3KaFWyIUi3plKY5LnYyDkqKsgZlwbgkEjc9PaolRFSCpEeKUeKCMKVKo+kahZoPeUzTdqbqgdR0Pim/TrOjVp5at1GENK4CspValEVO60/jGFjpE4KjCSlYVnZRdyV9SjUYym+oxzG1Gl9MuaQHtBIlp5iQRI5ghVkZhQVIhWR4pESgrKSnI6JIJ0KjKbnmpSFQOYQ2TGk9VVzUkBTSVW4IjCsKnTNIUarX0Q+o7T3dQvI7uDJxs6RjOyVKz8k4UyEoQ0jSLqdRtRp9ZpBGOYRXe+tXqVnwX1HFxgQJPgiFKgaIc812VHDu3aAxwEPj1SZBkA7hGbFLvJQO6tqZOBGVWRlWM6QIRGFOEk0IhqREKaFBWUQpOCXJBEjKipHdRRKjCC3xThBUNoPbtlVkQVa/CgBKRKrKIUoQQqb7oKSUIKaAUBJMKaC0oCkoqAKiVJJAiEQpbohTUVBBUkJo2ihMYKZMDZQRQhCihCEIAJykhAIQhNAQhCGwhCENhCEIbCEIQ2EIQhsFBCYQVNKiAiFKElNBQiE0JoKEQmhNKSSklCmjZJohNNGySUkFNG0UKSE0bRQnCITRsJKSCmjaMIhCFNGxCBhCFFM58EoQhAQiEIQEJFNCBIQUIHCSaIQJOEQhAQkU0FAk4RCECQnCSAQhCAQhCBwiE0lQQiEIUH0BpLYMiUy7U4udKTsnKQ23X2ul4eunEyUtPXqpAjGClIJPuU0u0cz/ABhT8ZUT4ptO87qyJam0zMlXNB7l8CfVKoC00QHgs21CAt4uXJe1e6+GyoX8d4YObaZ5zjU2FwO27g/tpx5+08TuD76hXT+FKqa3GuGkn1jaMqmd/WeP3Lmdr89q+NEmZ4jXE+VR37l15/NfI+xJrh45+TiO3IzCmwCcIcPWkkHKcROy+dlj3fpcak7DcFdK0aDwmiR/4ivEcvUo/vXLEkQurZ6fwMzmRc1yD/coKSd2sr2cS8n0ioQTOs/aqgREHdW3R/HVN/jlUnqt3FiZOtbdm+J3nZXiHaa3pUTw3h1anQuqjq7Q9r6mnTDD6zgdQyMZ8DHEqS3lsVN1Qkj1cjEz0n95UXGSFMcb7mVmg0kjIVRjUrhsVW8esQuvS59XdFjxQrU63dsqGm9r9FQamPgzDhzadiOYWV25kf4LRWlxJIAPgFndIMESsdPdvaBUQI3Uvalz9idC7SY0OMKwAZPxQMknYDxUW4Kta3WxzTTLmEet6sgDx6KXHRLtbcW9a2qmlcUn0aggllRpa4AiRg5yMqC28a4pxDjF86/4tfXPELt9NjHV7moXvLWNDWiTyAWLfbErGq6SpN5YCmM80MaJW29sRaULKoL2yuTd2ouNFvV1ut5cW93VEDQ/E6c4IUvZuVjAhXUtpg9Np3wEUGtL4cQAeZ5KdMAZzvIIMQdwVdu2PjbXfcPvuG3lWx4lZ17K7ou01aFdhY+mYBAIPUEHyIUWSSA4l0CBJ2HQK2/vr3iV7VvuI3lzfXdY6qtxcVTUqVCAGglxycADyAUGCYK3jHfBcB0VzRHNVgzCtZzW9PVGq2eGF/4ulUL6bmDvNX4smPXbBHrDYTIycHC2WwPUHw5rBSEELp2I5HIOwTXu9XBdVpc3ABONPuVtIaYMH40Cdl07Ph7rj0udTTbcMZcAbgl91Rpx7qsquvTY3hT6oHrjijmB3MsNOY8MiU33e7rlzuM9tf8Abc+39J4XwuP6DgtBwA5l10QR9eVTc2vd0bZwiajqZOIy61oVT7JqLocOM2dpPxRwq2Z4Yvh/goX+bKzgmddqJ8+HWn7lymVmUj18XaYYuJfU9NOmTs5sg+0rA4QYk5+hdbiAb3NINEeoDtH5zxlcx4hxPKSus7sepms0AI5habcSQs7BLlstx1BCrjxd612zfV5HOF2LdrR2Y4417QTUsMHoW3Nuf3rlWzd4OCZldhv/APbXGAeVi8xGCe+oR96zldT+jv6vCZ8GUv5f3jxVcNaHlxAbImT1VD2kE8oWysXNqnS4tcJAI6EQfoJCzVBGOa6e7yZzuyuGSMqtwgxC0Pb0UHN67quNi6pxO/PAafBPS6n4OpXT7tlvA0trOaWuf1+KXCDj1j7OYQCCtLmyqi3MdVJNOdxmtRlcwqJWhw5KlwhVxymlb2gZG+ZHTp96r09Va8AHxUHbqVz0qcIJUT15K1wnKg4QozYpcFAyrXear2OVHPLFWcqPq6o1DV0VjtyChznml3Wpxph5eG8g4gAn3ALNcbiqf4KpwJyVbV0yNAcBpGqXAyfDG3gqzuswxiOAJMAcyouAIBBwchTa91N7XsMOa4OaehBkFNz3VHue8y5xJcepJkqWu0iEpHB2Tjoh2+yw2REJt3SEjmp4CtUKynTc/VpY52hut0cmjc/SFACTCtqUntDRVpPZLQ9mthGppmHCdwYMEYwoIjeEwoGQVIzodB0kjBiYKJbpZ6w2UhulcVGVK1SpSoNoMc6W0muc5rB0BcST7U2ZK3PKQ0BGwCD7V0NpBTAjoTGMqtpwFMOIVi7X1RT7wii6o6ngtL2hrjgbgE85UGuJMBIEwpsAPJVZ3TBMK2mVW0KxgVdcYtYJdlamsEbclnpzII3Wps+9R6uORlqgF2FDngK55IdIJnqoQCYRjXcsqQAhOAQI1AR+cRM89uSaKUZVrBJCgwS6AJ8FazBCLJt0+DWT7++tbJj6TKlzWbRYar9LQXTBJ6Y9pIHNT4rYVOGcUu+H1iw1rWs6lULDLdQ6H3e9Z6Tj3RaQC04LTkFSJLySZJJJJOSSTJJ8SVvtomHJ8WZb+XXj80YKiRPkrSDHVQAzA3WHs9kNOBCjlWkEiZwoJpmgDKtYMiVFo+xSYM7o3hE7gktz1kkmSfasTxv4rbWGPFYqoIcQkmk5Z+ClwyVUVa/KrLSFfZ5soqqMk7KDmxk7K6MIY7Q6dFN50ubFRuoes0tmOomQeRAKjz2aZiCDg+1RgT5q7T1Ki4KuekGy4nMHqcqVyWOqaqdI0mQ0BjqmsyGjUZgbukgcgYzCbfAKLoMj3KaZs7M7xEkKt2y0OB5gxy8VU8CUcrGdwJUXYhXPGyrhKyrQrWwGvBYxxc2AXT6uQZEc8R7SoOGfNRnasnKCITdk80wjNVwoEQry1QeI5LNcqqIPPCQJYQQSCDII5FScS45KbWPc1zg1xawAuIGGgmM+0wpWVbi5z3Pc4uc4ySTJJUdI6KyEgCghpEbKsgtKuIkKtwjmhVRylCmAiFixlBEKwNTZTaWPLn6SCA1sZdP0ACOfURzU1oUECVAq12AVAhZRWkdlYRKg4ZUESkpQkVEsDXFrmmZ0nAOR1iOirOXQrA0GZeGwCcg58McyokQYTRIUKJCkhCxWRKl3X4oVO8p5cW6J9YQBkjoZx5FSVZkHdSxLNIpbJoKIAhAQiUEKKkn6pYfjawcdIURWcBQ2KsKQk42KRKgcqK0PNLuqbWUqjaonvHOqAtfn1dIgaYG+TPgqT06Ksq0QpFRRCQrrikyn3ZZXZW1Uw52lrh3biT6hkZIgGRIz5qkoBR+xSQRIImMbpRWowr7uo2tXdVbQp0Gu2p050t8pJKqKgilCcJKVkiBzUHCNlYoVBmUghEpFSCDgSqaQ5KJUyondVEUZTKSipBKEwhZEUJlJABCEICEkycRCQCBJ77oQmgiISTAlPSOiwqKFLSFFFCEIQCEIQCEIQCEIQCEIQCEIQCEIQCJQhA5QUoRCAKEKSaVFCZSUAhCFAIQhAIQhAIQhAIQhAIQhAFKE0IEUkykpQIQhRQhCaRSQhBQBSKYQoBCEIBCEIBCEIBCUolA0k0kAhCEAhCEEkJIVQIQgqK+gkFRaPLJVhGYIKiMFfcfNlS08pEkSBzhRgDHvXSo8XvqXAa3BG3B/B9a5ZdVKGkQ6qwFrXTvgOOJhc1+STynbopN+7VQfl2NhuiJOCm2PanJyVWbe6bFu4YGuvLdrtjVbPvWFmcLdw86bik7Yte13slbxjly35a9L8Ipb+EuECAdHBbZx9pJXP7Yn/wCb+PA8uKXX/Fcuh8I408Zs2mPV4JbNyOY1A/YsHbIh3a7jbm5DuJXDp8DUcfvWuad3zvsmz4XHZ/4/rHFdMjmptE7xlJ4kieQTHqt/jK8dm33scjA9YxOy6dpJ4O0f+ZrA/wCzo/uXLyQcLtcLpuf2equAJDbsA+bg2B9Q+5STvG7d41526EV6mD8Yqh2xErTd4uHg76iVnPMrrY5SoHxKSkBjKRJk9Ami1Jo9WPvUdRaSYnlkA49qtoiduYUHwHZK1rsxMu7PUBxhUvaVpqkRIKoOVnTW1MZlEDwUiD0ShNNbAHRW0aj2tewPeGPA1NDoDoMiesKDBAVjBus2NSpzI28EnGCQmk4ZWLHWXstaMCd1LUYhVsJhWArFjpKk1TjqogSd1Y0DMHbdZdJVrBhaKfxVRTB2Wim3InZdZ+L0cdXTthWNzmMpOaAB5SpMcY5bLb177rqUznkurYZafCFy6cGJMFdXh4HduyZIBPvVenhvd7vh9s0/h9rDDW8KtaIztN7ZTv7V54O1dnxoAIHEWkNBgH8S4z4L0/ApfxPjTXGdVlaNkiRAv7MfuXmGTU7NWzjkG5pYe4EwaTgQYPms4+/8m8cteq5p+bqcHaO5t2g72NH2/llP9ynXl/C7V4H59rz68NtT9xUODkm3syDGrhtEGcE/ljThW1BPAbUiP52zEj//AFtL9y55ffj6mN+5/JyuJQGsnkNOD1Lj965TwSd8nK7PFaZFOSMNFNpPTUHH7lyXfo8shdonqcpcuysN9YescFarYYO3XCzt3gRnqV0eE0m1hckuP4u3dUEcyCB96mXZz4fLo2FEO4fXqkAuZe0WNHMtdSrEx4S0LpNpx2S4sSf+41Nv7Wh/gsXC/wDsq5OMX9EY/sbjZdICeyvFG4g2jm77TUpfuXLK9v5x6PUW/Ay+s/R4e4EV3x5EKis3nyW28pOp3T2PbpcCCfaAfvVFQQF3vl59S92JwCgQYjJ8Vc4AunxSLYxzlRysUuaIx0VD2nK1Rnqd1XUbjZGLix1Gqlwla3jfcLO4YV24ZxQQYlQI67rQGkhxAJDRLiBIA6noFA7+SbcpFDgk4SFcYUSR0WadLM4Qo6nMa8AiHs0PBaDI1AxnbLRkZwrXDkq3NRxyih2PFJ1SGPp6aZ1x6xpgubH6JOWzzjcYTc0hQiVK5XFWdh0ShSeDgqJWKkiPNDd0wkZlYrpJ2TJb3QZoaHBznF+oyQQIbExAgmYnPkqjnmmQSkAJhJ2aKCFIboQN8z7FLRY3mcGN1Ive4t1Pc7SA1upxMNGwE7DwVt7fV7ynbNrmlFrbttqQp0WU/UBJBdpA1ukmXGSVlB8Uk2zupEyZQN1E+BTCvslTCsp4Kg3ZTpkTAK1CeT5omW5mZ6clEz7E9iuhtIRCk1REneMYUwtQ90xHUlWtCpG6upDKrpFrRjdX0KdSo4U6bHPcdg0SSoMYdOyta0aYiUr0Y46TpD1h05LYym7RIaSs9MetMrrUy30cAAbbqPZwYTLy49VvrHoq4ytNctGsGmx0xDzMsg8s8/GVQInOyPPfICcKRA3TCBBvUwrWbiVXIkKxoko1i1sjThSpSSVCkCGQVbRwSUemJxM5SiDPPkpnAUmVC2jUpltM95p9ZzZc2DPq9J5pXSz8FVQNAGkOGMyZk+GFWBkq4mW7qoYRMobR4YU2A6kuasomXBGsDqj1Fhqgh2eq6dZo0ZWCrupDlZy0dQqXDKucNlU9plV5KqIyoOGFa7Y4lVlHKxA7KDROFaQEiAOaOSIzsoPGcK5u6rqD1iqzVb3PLAwvcWtnSC4kNneBy2CocFeRhVPEZCacsoqeFW4QrlB4yjkpKIlWtpuNN1QAaWuDSZEyZjG/I/wQoaVE91eJiRPROFcKjxRNEvd3Rdq0T6uqI1R1gwqoHIoyrdhKJVjwNIgzgHyPRVrLnYgRKUCQS2YUyIUSJUYRIymwUzrL3ObDTo0t1S7GDkQN858ky0pQOqIi4YVbmyriFW4espoUhvRBaZyrYScFEVwiBywrYHNR0jlhNChw5oaGlzderTI1ad48FNwzlRcICxYyqjmVFwHULR3NV9J9ZlKo6lSLRUeGktZqMNk8pIgJUX91UbUbTo1C0/Fq09bDg7g77rFS3TMkQpFsANBJjqcqJRNokJGVN2yichF8IoTKChKSWlNCKTxLVWQRurSJCgWdFKliCE9LuiHCFGKSEw0lJAillSQERZb+jdxcd+a/ehre4FNrS1ztQ1B5JkDTMQDmFRGDifDmVJwPJRSRnSdzTo067qdG5FxTAEVAwt1SM4ORBwoUWNqVWMLmUw5waXvJ0tkxJjkFAiEJpE7im2lWq0W1adUMeWB9MktfBjUJAMGJEgYWcqRycpYBiRKRCSKZQgiRgJKRShAlOla1ri2ua9I09NuA6oDUAdBIGAcu35KByotAaZIB800gjKqepkjyUHBZEQgpweilCogASYwoPGlxCtcTGFW7KumUCkpHBSKWACaQSWVSQiEKBFJSSKBIQhAIOyEHZBEptQhLFNQG6kolTREjkQooQooQBKEKBkQkhCAQhCAQmRBhJAIQhAIQhAIKEIBCEIABSUUBF2ZQEjlCIEIQsqEIQgEIQgEIQgEIQgEIQgEFCECQU0igSEIUAhCEUIQhQCEIUAhCFQIQhRTSQhECSaSKEIQgEIQgEIQgaEIQBSTKSD6I4QkBsAVN28KO5X6Czs+VKRwkcpuCRxK56rVqOdkAeKAJIEwttraMq2d1Xdd29J9AMLKNTVrr6nBpDIES2ZMkYV8J5Z6Yg9VtsGl1ywDcvaPpCyAGYxhbeHnTcUiMTUZ9LguuMcOfLWFr1Pwp09HHKAPxvweW42xUeAuP2pIPaTikyD6Y8kEycmV674deGusO0tgH7V7N5Ejl6Q4D6F47tFnjfEHgATdVDH98j7leT5u8fO+ydzi45f8Ax/w57zt5Ij1fbyTLcsB/RClEUwB1XlsfdxqIlrSAvWdkLY3HZ+/DGyRxPh7R19c1x9wXlDt7F9F+BunTr072g/8AP4nwgR//ADL2n9sLnn2m/o7Y3e/pXznitO1Hoz7a5719Wjrrs7os7h+pw0SSdeA06hA9aOSwGCBBWmuTgHfSPcsz955rvJ2efqQPTZJo5KXhCA3KsXa62bufBVVcrTbDJCqrfHM/Yt67OUy+ZlqNgKkgrVVEtiFneCORXOx2lQhQ0kZVhEpOELLSMY5q6mMKDGyVexuFK1ESCMdUECdlY4eCRasV1iIbClsU58ENMrOm5U2mcK5stBIBdAkAbu8FW1kHJG04Mq1nKTlYsbldrj3DbHhta0p2HHbHjLK9jSualW1a4No1Hg6qLp/OaR4YIwFipqlrjAByr6QzC1j4enCxpqiIEchv5KIHVOrs1DSRvsuj1XLuuZuF1bA+o8eX2hcmmcrq8PILHez7VXbiy7vovZgA8Z4mDuaFoNt/5QtMLytGf817R+D+UUzJ3/mnwF63sp63GuIzuaVoY/8A5+1K8rRAHZK3lxMXNLflNF539i5zz/R0t/8AW8v7946PBpNmxsT3VlRAzEfltMfetTQBwKyLhgXdsDB5N4bS/esXCHRY3EmfyGnAOD/ptFbbuWdl6Dj6hFVh3x/2ZbwVbP4kfVxu+jX77NHayiynacRYGhrm2fBnnT+k+nVLivHPHqif0j9y9x20c0Hi9MNh9S24LE/otpVpH2Lw9UxTB3mo77Atcf3Xg9PnleOdX5f2QBkjMLqcEJAvZH/c6g38WLltyV0+CkflpgwbR4x+sxXKdnr4cvndPhIjg9zM/wCn0Bt0o110LwaewnHXs1S22a1sbyXNP/KufwUj8G1m4l19SOego1s/SuxcgO7C8baZDvyMbfpvqf8A6rjlO3849fJf4ff/AMsf7x5/t5Tt2dreJU7RjKdFtSkKbWYaG+j0TAHmSuJVbDdWMLdxy5N3xW4uM+sacz/VpMZ/yrJWHqyRkBdsZrGSvJ6btw4y/hGTTJ5eGE6jKeqWB2ktEh5BMwJyOUzHhCZEkGDCk4AkeeUsWTbMWeYMbqt7fKVqDeZyY2OyhXJdTbsGsmAGic7yeam2rj2YKu5WZzcnaFrrDKoqD6VXlzndRAEGNlHTknqpndEI5a7qHDkk6k8Na8tcGPnQ4jDowY8uaudHRVuAycTzPVZq1Q4QVW/ZXVPFUnPKFHDKKiyQTiBvnr9uyhgESA6Mw4SPcrDiVU7qpXLLFVp0tiVCOmVacqVFhc+WNadPrHURpxmDODMfF57QVjJlUWkbhVrSfxpqPLabZLnaabA1gk7NaMAdANlncOajprU2XLchTq1qlTR3lR79FMUmanE6GCYaOgEnHiq0ESpYhIQjlKAiUtkA5KHFanZnaTYDgSJ+9SGQDBE8t1AKxgGmCrYlScxzXFrgQ4GCCIIPSFOmIcPNRGSSckmSepKmzcKyJ7p0nCnWa91GnWa0madSdL8EZgg85weSrJwBJJAyTuUOPrFIRMxK3pdd02KxrSSoM+1Ws3W54XSbW8+isYFYO59FDe6ea+ue87z1dEfF0xvOZnbEJNBnGeiku3SNTDNJojIO8qdPxUWU6ncCtp/FF/dhwcPjRqiJnbnEcpnCbYR7Jltazb2rfRce7AWBp9TOPWC20TDBzR34r3Yrj4xPiqo5qyu4l/L3QoAZzsq4XylEqRgDCcQMo5KLYGlwY5ocWhwh3jkH7QFJmDCiBJBVjdwhGyiPUGFOkDqPVFBhdSVlFpLiCj14zwZECFWcgStD2QqiOoR2qMYUTBcAFafiz4KuJdhGakG81bRbDwoM6Qr6IzKWtYzulct/FY5hcyqPWXYuWkU4K5NUZKkOZQ4coVT8lXFs7FVuEA5VeTJTCg7eFbCrI9Yo4VBIqRBRBRiwm4Ki5uVaBKg4GVWddlDhiVU9uVpe0aT5ql4MptyyikqBCsIjKgjjcURgqMQrPYiAox4VFszCrVtTCTAcobVqD2qycwk4KOdUlpOyRgKZBBhQicqM1IuaYhkKKlEefMdEmjKjMIiBKqdutDx6qpcMwiVUEwJTIUmDBRNERmOaiQtFw6m5wNGgKLQxjS0PL5cGw58nbUcxsNgqYUTyrKi5sqxwUSs1mqHb8/Lkq3AK9zYCqc3xWLGRTLGOJfSbVGlwDS4tAJBh0jmDBjY81S7krDhVlSwRKIRCYUWIlICVMpQhpApKSceqXQYmFE2ggqThhKEVApOEqTmyoEQYTSaNNtNzzDGPcc4aJOBJx4AE+QKIWlnptk6jXYbm0dWouNKo0lhfScHMdBG7SNbTyOQowxkQJlJWnSKcBsGQZnlBxHu9yqIIRQkRKaFUVnCirIUSjKEKTqr+5NEPcKZeHlnIuAIB9xKC3Cgmk0icpQpqJ2RKSipKz8T6ORpf3xOCD6sKChI5UiEiqzVZaVZ3DvQ3XPe0tLagp92XevkEzHTCi50KJaCZ5pYbRO6aI8UKa0Iv2UCpl2NlBWJSIUTgqaiUojCQUkipoSlBUQYUmmVDwSEyksqihOEkAhOEkAQlCaECKRTO6UIqSgpTCHbLIihCFFCEIQCYSQgZMpIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgcJBOUiooQgoQCEIUAhCEAhCEAhCECKSkUipQghCEAhCFNroITSQCE0kAhCFFCEIQCEIQBSThEIEhOEigEIQgEIQgaEIQBSTKSD6O4eqoK8gARhVRK/RPjyoGEASdvNTjEHmowppoiAeakHZwUoHuTG+ySFpskmV0eGCbqjI2e0jwyMrDTElb+HR6TTjm9o+kKx5/Uf7dfW/8qWkGdpuzzmj1ncMc4wP9YF8x4+GniVxUAhrqjnbfpOJH2r6j/lR6T2k7PuGSOH1GO9ndn/mXzjtPbmlXcefc2752B1B3XyXPjvyRyw1OTt7OJXHrt8GBbq1nUpcEtOJOH4q6ua1BhkZNNrC7HT8Y36VkuQBUbJ/o2/srVXqvd2dtaRJLKV7V0icDXTpzj+4FnLG9nvwyYH4yvofwNVxQHEa2wp3vCnggbH0smfoC+dkSCvefBPA4fxkl0flXC9+X5S5Z5J8vf8AGf3bmerfpf7PBXLYe05+I37AsrmjeFuvB67DH9DTJz1YFQ6jV7p1ZtOoaLXBjn6ToDiCQ0uiASASATJAMbLr21HPG2xnDQchMN28U45KYbjJ5JWo18KtqlzVe2kzU6nTNRw6NBAJ+lVVLdos6V0a9BxfUew0Q/8AGt0hp1ObGGnXDTOdLtoXrvgmt23PHeI0nMDx+BblwnrLBP0rxzW/k9J04fTDhnaVqXbyY5/xcsfw0pqMIG3JZKjfWwAujUbFJrvEiAPJYX/GIWa9WFU+1OoGSCx5cCBMtiHRkeU7Hn0CHCBKgfFYsdttNmKGp4rOqAd2dBYAfX5AyRjqVppU6ZovqOrBrwW6KegnWCTq9afViAc7ysFOQ4ZW1n2rnlNOuNliNQAc9lUenirqu+3sVRCjRhp96TQAZV5ruNk230N0tqF+sN9bYCJ6fvVDjJwFnu3lqa1Uw8jkFawyqAps3hNEybASr6MkDqlZVLRlO4Fza+kOdQe2ie/dT7qofi1DAOqN9JwVJhBeAMQs+7042SRpqiWtIzDdlBjs7KdSdLZMYlVjBGVt2uXddTIJzsupw4+o/P6O/muWz2LqcOxG3xhy8VY7+ny3m+k9lfW7QcQH9S0yD/5y1XmKYDeyFHfN1QIMGP8AR6nNeo7KY7S35JkD0UZ/9Xary1Mg9lKDYE+k22c5/EVd1mT5r/J6bl/6zmv78xt4MZsbp2SBYNJgbfldKPuXQ4m0HsrTBxFxQHgZ4ZbfuXN4Qf5N4g0QB+D8jyu7f94XWvgHdlMxIuLQx58PpD/lV/8Adn1fUwv3Pr+kavhI0Nu6haAHucKLpOYpVHBvuBheGqZpM8XvHkYava/CQ6eI1RM6biqJA/rtXjK38xSOwNR5+hqvDd8crx43XHj9FQ93mulwfAvQP/CPj5zVzmgua8j81pcujwWTUuRIH5HVxO/xSfoBW8vDfDn88dTgABtax/NFanPTLagXWu5p9jOPkkt0U7BwnkW+kPPt+Kub2XDX8Pu5EfjrfH95w+8rr1qba/Ab21eGnv3ta8TyZaVnN88hefkuv+ns58r8L6av9O7xvGKPccbvrYf0V1Upx5PI/cleW7qdlQrujTXpl7PIVHM+1pULus67v614+NdxXfVMf1nk/eF0OLAfgPg3X0OqTn/zVZd8tyyPPw53oxn78VwYMmfNWuB1NkfGMqpzmsa57yA1oLiTyC18Vtq9pXdbVWllWm9zHAjZzcEK6MeSd4zlpLi2Dq1RCz1CNAdO67VvZm44422YzD7hkDwfA+0rjvaTY2FaCO/tu8aSRka3tnG3xeeVl0uXsyVBk5kLLW29q2126WE7gxHtErFVO/gjjmq5GUoTOQhok7fSljHug8ZUIl0c1e5qrIgrK6Z6gOfBUnZaKuC7E5VLyS0AgCBG2/mpXLOM7t0nsc2JaRIkSNx1U43xzUHRyzKzk4WIva3QI165M7adMCI5zM+EQqxIDhqcGujU0OIDo2kc45TspPUVhgU/iVT/AFfvCqdlWtk06s8gOXiqpPIo3l92IwDgHxScI6nHJW639y2j6ugVHVB+LbqlzQ0+tEkQ0erMAydyo1Bhp6ifpKjGyqMaxwaKtOoNLXaqZJEkA6cgQRMHxByVEtSJgwm0kmOqa7JKjjokVMg9VEhaxDaFNu4SZsmMEJtFjsKVM5hBEFNm66Q8VAn1kipPbBiIIwUQqsSZsrWmDO6rp7FWDda9ljRRdoqNfpa+HA6XCWug7HwKtqPa+o5wa2mHOLgxs6WAmdInMDYKhnxY2VjUbjZQa57mspUy6o4hrQ0ZPQBTbBYD1H3YVVISIPNWM+NE4j7ldPTisH80TGdTAB7HfuWumT3eyzNE03mI9dn2PW2k090HQq9HFHPqj1ucKLD6wU6vxnDeEmAZClcfdYWktEe1Mt0jM5VkjuaOlrWlrSXOBJLvWO42GIGFK5wGnxd+0VHWzttQMFSblwUArAco5x2rJrfwfU9VvrQASNoIOPHCjZAGs4GfCfNWWJjhpkTBnyVVk4ekn2hTXl9Ga1F920CoQMALGcla7okuncrId0hle6f9GofnYVkRTlQbkqpUmDeVopD1gBhVMGY5LTaiXgGN8KV0xmltcTSzkx0XHr+C9FXpljG1GtBIIIBGDB+kLhXUvr1HENBe8uIa2GiTMAcgOQWMctsZ3bG7wUHjGVcWqp8xAW3nyilwMF3j0Vc+tHVWVJyJMYJChGVXnsI8oRGZTTjG/NGSaBOFB/xirqY9ZRqAakW49lbmNFJrtTSXEgtAMtiIPSDJ26LNVABWqp8WFnftKOOcUOA6KsjKtOVEquNioymASpAJgQjFm1bgCMhAEKTt5QFHPXdnfh5UeatqjJKrgxKM2K3AhICDKmRIUYU0xYlUe5zWNJbFMENhoByZMn87O07DAUI6qcYUQFNaZ1pIgEBUPHrFaSPVCpqbpUqmFfaWtxcuey3o1KrmU31XBjZ0sYJc49ABklVEKdMkAiSJBBgxIO48lKiBGAeqSscEgFNopeFCFa8RuokQFGFTxIVRBV5CqO6liKnAkbKBaFa9pOygRCzpFRSCsiVFwWdCKEzjcpHBUXYhEDpKChCInJ8EEKQCChpBRV1Wm+no1tLdbA9vi0kifoKrAUSqzgpxvGJTKIRKlTa12rW/TDSR6s6iBge3qq3ASgIjEKMoOA5JKZUTy8kCUVJRViWEQokAKaCJVZVFRhWPEbKJQQISJU0o9UHlMKVKiouCkkUSoQouMGAppQqyrJ8EKThIShSqg/ZQVqrIVSklCZQgRUU+SFNCMIbumkDCyJFJAyhSqEIQoEdklJIoEhCEAl7E0kUuabtkJQpYEgp7IKmuwSFICQoqKEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEFCEAhMJFSqEIQoBCEIBCEIBCEIBBQhAoRGE0igISQhRQhCFAIQhUCEIUpAhCFFCEIQCEIQCAhCAhIpoQJCE0AhCEAUk0FB9NqNnE81VpK21G0u4Dm1S6oahBZowGwIOqdySREcpkysr2EZX6J8aVQ4boAxupkeSjsjURTGycSmMbbKibMbytdsD3jTOxCyU91ttcVAZwkcOf8A26+vf5To/l7gLxzta5mP9XQXkO3tENpMeRk8O4e73tevX/5TdQv4twN07ULgeX4q3K8t8IB9S3aefC+GgfNqLz8fjCOWHnK/v3eLvhpNPxpMP1VocAOzneAYHEC0n/2h+5V8RbD6J62tEj2tWotB7GV376eLUp9tF37l18yPRtyS5e4+C5+iw4vMybzhY/39ReEOV6zsNcdzwrjJ16SK1g4HxbUqlZ5ZvGfWf3dZfP0v9nnqoDoByBasPuYFkdUeaRptc4MLg5zQcEgQDHUAlbPz3N/8oZ9lNYMxvE+C6XH2c8M+xtEmAIhWOHqsx1lRphx2Ctq/zdP2/cs2Ou3svgdcGdprySfX4XVZ76lIfevGAfkVmYiLduPaV634Ij/860qYEmtbVabRjcAPG/ixeTJ/JLcbRRb9rlrGPDO3qM/5GRNpIAIDj5yWrm1QJJHtXbtKYfwy9cRIZTJjyYTK41QRy5KZTT08OW8svyZz4pOAOxVpIhVgAHZYenZ0/jBbKYmFlpmHZC1Utws5R0xpviYKzuOSAtFYZWd8jCxpvYDiRAlNmDlJpT9u6zYsqToAwhhJKR8U2CCjW2miTvuFqoyTMrHTMNMFa7Q4g7So6Y3Ta8TTZkfFUKZaDLmasGAftwp1Y0MjopU6dI0KrzXaKzHM7uiaTiazSTqcHD1WaAASDvOApvT0W9yZ4ldXh/Ix+cJK5TTGBv1XS4fM5ncZWsa9Hp8tZx9L7OY7RcQIx/op/wDq7VeUB/8AlxjGlsC6ozGwik8fevUcAeB2j4jyHc2zvdd2i81fDurF1OcC6aPcxwhXG/Nf5PXlP/U81/flp4KSbPiLefoJwCMH0q2XWqSezbhGBVsHe+zj7lxuCuLaHEmgH/QcDr+VWy7WPwBVGSNPD3N//p6jfuUy+/8A0fSwz+TH6z9F3wjgDiVwBP8ApNxnyqNXjK8+jUdJ3qVN/Jq9p8JTh+EquB/P1yf9o0/evF1/9Fo8galTn+qrwf7ceXO/Jj9Ba/ErzAig77lr4Gfy9zZ3t67T7aL1jtTDLnH/AHap9y08GdHEWwQJbVGf7J63UwyvVh+/d3uyLotbkxM17fbr3kfeu0yPwe55AEVKx65FjXH3ridkZFtWMk/jqR84qsXcdpFg4Akt765AnnFhVP3rzc3Z9Hmv8G/T9K+f0cMpQdmtz7l1OKQ7hHBmjH5FVM+VzVXJpEd3TzuGrp8QOrhvCDOBY1R/9RVXpz72PHx59v6/2riVWGrQr025c+k8D5pP3L03wh02M7VcSDBht088/wA5lN33rzlB4Y9zn4DWVCfLu3L0Xb9xPaa+DoB71sx/6eh/im9ZyPDu9Vv5X++LTwqk5va3hxAB1VrBxaBO9do+8LyFqzVZW8RB9WY5y8/8q9rwJuvtHwd5wY4aYiZ/KqYOTtuvK2DB6DTBOz6Y95qysTta+jct52z8P1Zb2nFkx/jSEedAFcqoIMFdriQ02LR1dRI9lIj7guM/fPmrj4a5Zq6VOkZx+9MwT6rQwQBickDJyTk79M4AGEPxB3nwSZ9yljnPJGJ3lQIyBKscPsUDuFltTWA7x36xVDs+Z2V9WdbvMqoOczWGmA9ul2NxIPsy0ZGfeVK45+azOEBVlWvGRAQ8A0hAALRBIJ9bJM+6BHgs1x1tnfiYCrDt+Sm/moFrg0OLXBrp0uIw6N4POFmxxqYINKsQ1jPVYIExIgE5J3gk+JxjCpBwJUh/M1BzlqrOSotvaJa/Ua3QwaQRIEF0kmSeZzHkAFOp/RfqD7SqwJyrKgLTTzsB9soY+ENMvcI5EqHNXU47ypJ/Mf8AYVAN8UQEGFEBXvZpDfESoFp0zGxhCzVRieSlpcI1NIkahI3HX6E2AkHwTJqGA57nBjdDA4zpbJMCdhJJjqSrGasLfUFQvYJcGaS4att4304ydgU67O6r1KXeUqndvLC+k/Ux8GJa7mOhRUJLWA/oBRIkrpC+VYUoPRTdScx2l4LT0cIKI9Yc8qtCnhWA5Tqt0VXsHIwhu601rXZawCFY1VswMqbeiNxrpCSM4UxgZCKI9UzjED6FaW+u/oHOH0pt6cZ2TYPyd5/1lMfVeu1TpBlkYie7cDInZcos/IK7m4i4pgf7OoV6MW82NZ/6NC5qGP6hCWvVw9tvLXAAr1IGNR3VQw5dTitk6hT9JJEPu7mhHTungfeuY4Z8Fp48eTHO3S8Eu0Z5qdwfUYepefrFOjSc91m0f0r4af74b9qd+xzG0RO4qEeyo4H7Fjfd6MpZiyTk9FYzcKB29kpsh0OaQQRuq4Su9ak/g5wjZS4U5ui+cWg6bdhBjIPpFFv2OKnw6373gNzXDhFOGxzkN1fcqeEmad/O3cU//uaH7kvfG6dOTnmUmON8Wb/rE7ww6CFkJ6QtF78cjmsRwZR68smkEaRukwiUmn8WkPjeCjUyXszsVqtgTWpgD84LJT3WyzzcMAP5wUyvZ19nbuGDumzDgSce1eXuAA7liF6a6eBSo+JI+9eYuHEPBwDA2XHh93nxvy1q7RcKdwi/FnUuKFZ/dMqF1F0gahMLj1Qr3ukf4qipsuuO9d2JL06t2oeof9FY4GJUHDELblUYCY2ShT/NUZ0dES8QlUa4k6C0OIOku2nkpUDD5SfGvdGv+KV42gatR1q2syhjuxWc11T4omS0AH1tUeELDVjmVsqY+5ZKol6Ts4ZY6mmciFFWu3UCCBkKuNVwm0E9AmcpiIRjSDxlDWyFN/0oaCVdpruoqDKqeCeS0VBBKrIkFHPKd1EeCUFWDEykclZcqTUtKm1hKZA1boWFpws7xlbSz1JWV/xilTOaisCE0exMCSsuZHAlRCsIBaogIK6m5UDhhBbLiRDp2645q0jCi4YWWNKXjkqnCFeRCg4EhIypIUDsrCk4Yws2IqIUHDxVsZSI9ilPJ0Rc06T69E1WUzNF9RhIHrAgtJHUThUFWFomSBPVEdFnRtWmVJROU0sqJEJKyEKKqgICkRKPNE0hCSlCFNJpCEipwkQERApFScMJKIrd8ZJT9yso0KtcvbQovquYx1RwY0khjRLneQAJJ5BEUnIUFc4RiFB4ICu2EFFwypJOEqisqZe8W3c6vU1648YUHYMJIIkYUXBTOUFTRpXyKScGSkRCM1EqKnKUKsoJQpEJKeFVuSU3Z2UFUpJpEJoInZRKkk4SpYIpwiEwsmzCXNSJlJTQSEIUUJFBSQCSaEUkIOyEQikpIUsXYbsopgwFLksiCEQUQeiKEITIhAkIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQpVgQhCgEIQgEIQgEIQgEISKBJhJCgEJwkgEIQppdhCaSihCEIBCEIBCEIAITJnkkgEFCCgEJIQNBQkgEIQg+rlhnHVU1BgxlbjSgHnEqivTLZ8JH0r9HXw8cmIgAHChGVa8HIGMqLsFR0QLY5pNEqZMoA5+xDaTGxlaaIzIVDCOfVXUzgnpurHLlm8K+vf5ShB4jwEhsB1CvPn3NuvIdunhxsdP53CLFwjw7yV6r/KHPeVezlU/nW9Qx/7FuV4ztnUl3CBiXcDtMDbDqoXHjnbFx4t2Vw+KfztsIz6DQ/YW2i0O7CcQdB9Xi1t9NKoo1OHX3EKtMcPs7q7dQ4XSr1m0KLn91Saz1qjo2aOpV1uAOwfFROBxO1fg4PqP/eFu3tPrP7vRJ37vPDwXY4BWFKzvmYHe9zB8Wvn7yuQdpWqwcKeueYB38Vqza29k9P5SWwTNq4D/AGZXO6c11dP8p0Bga6DBjxorlDZp6rVu7WMFlMYHkrKg/E0zPX7kWg1VXN6U3u9wlFQzTaCciVj3dZXqfgkn/wCIHCQBOp9RvvpuC81UZpp02/o04Psc5el+CEE/CTwBon1rwN94IXJ4rbGnUvWQJtjUa4tyIFQ/vVxvzWflP1eS/wC9v8VnBqIf2f4udM6GjPQGlUn7F5qqPWMle47LWwf2Z7SOJzSpsxtvRqleIq5OVrOdovpct8nJPzn9ozkZ3SABM5VhHJQAXPT3y6DfjCAtVJpD46rOz4whbGNJePFZydMKVcYjmstQGVtrtc3lKyvw5YjpUACSITzq3TYBJCtIBIIk9VmrIr2GyBvCseICkxrSxxLjqBbpGnBBmSTOIgcjM+CyqVMHuyOhWm0HrzOFRT+Ic/4LTZNmSns64t1UHuW+QVTXEbGM9VortAt2Gd2/esvko9GfarWHVyAg9V0rBxBb4uC5tNdGxw9vmFZ5dPTX+JH0Lhcjj9+AQD6FSJn/ANVbLicb0tFanyF9Vn2YC7NgdPaLiAj/APhzDnnFxbH7lxePsLLm4g49MrRywcrWM+a/SPo8n+76j6xHhNSBc09y+2DBzP8APUjj3LvjPZt7m7udYMjcj1KrftXl+HVu7uWHBGtkz01t/cvU2jS/sy7UCfy/h1J2YI9Z4x7HApnO8v5x6fT5y8f9P7xb8JBDrx1QTDriuJmZINOfNeQrR+D7bH59b7Wr1fbt2uw4ZXLiXV3XlV88j6QWf8gXlLlx/B1rnd9b9pqnF2wkc+W9tT2/yrtT6lwCN6Dh9i1cGJ/CdLTnUXNcJ3BYRH0rJbE/jgOdB/2LTwR8cYsxuDcMGfFwC6e1csMtXD6/q73ZB5NpJHxq7Zx0qMXaJnh9YbEXd4CJjawqDkuD2OH5I0GSZLvKKtMSu41xNjcQMG7vjnl+RvXl5pv9/V9Tl3eD+X6V8/oO9SjnENldG5qfyTwyQC5ttUz/AO/V/wAFymnTTptnIaFbXrarW2ac6GVGb/6xx+9evLvdvmcfJ2rJXd+T3IG5o1c9PUcvR9ujr7UcQqA4c+iR/wD01FeZruPc1gIP4t8fNK7va1+vjld2YdStnbbza0chZ/5y/X9HKd5b+X6x6LgInjvBXtIJczh+/hdMP3Ly3DhqtabSQS+pQ25S+ou/wGvpvuEVHbsp2Zxz03jNvGCFxbGmKdemyBFOtSbE7xXcFzt739+724Zbz/lGTisfgyi4CAYAn+qCFw6hk4wvRcXYP837M7n0u5Hjju/3rzrt1cL2d+e/Mg4SUMbHNBJmFOj8fInkrXLC7qDhOypdJjKtfjAVRWK61VUyT4qh2MSrnjO8KioY8VK8+V7qqhzhL+iOeYSQcUj5qVzl7s7yS72qtxkhWPEexVjBKzXntMn8WQDzCrCkct9qjKybP80rRfQLhzRyj7As/wCYVou59JeT4fYEax+7ahRA7w5+MCPeFEc8KdETVZ+sExpNNoh3eaiXGRp0wIjnMz4RCRLeyyu3FM/6sfYq/wCjPg4fetdZhNpQeRu1w+mPuWcNim6P0h9hWtOmc1UaDSRUP+rcUc1Zb/0n9k/7FA7kdEnZzynyw6n5n6oUGlTecNPgqwukL5TBmYHipvY1tV7W1A8BxDXtBAdncA596rEg7qwdRiChPK66h11VIP5xUWBSuR+UVP1iikPXaOpVbv3qYBVrRlRAhxHirKYzCrca6Z/FmPFX1BD6g/ru+0Kii2abidgCfsWyu095VxkVHg+8LO3rk7RYR+SXLRzu6f8Awnr19JjKnBrp/qiOH3biXGCdT3CB1jmvK02SHNdzv6I9hY9eitnuPCA0zB4Zc4P9of3rHL93bpN6uvyc3tQQbJg2B4txJwEf61oXncTPRd/tU4eiWzRt6dxM/wD1RXA2ldp92Pmek7dX1rr8N0i44DIDpuWSCMEG6iPcs/Ff5i1JMkm5/wCMVdw135XwLP8AT08f/wA279yp4uZt7Tzuf+OVz/5Pp8t7MIGADH7lbXqvr3FStVfrq1Hl73QBJJk4GB7FQ3bCYklbeTb2HBAB2Uu/VHxnSYz/ADL1z+CsdUoXoYCXObbNHtuaYWng9XR2U4iw4JY8iPCi4rPwd4p2/ESRIAoEjwFww/csf+f1jjxTWef/AO0/Qr6TVfOIcQZ81gcYWqu7YAexZHn1iOa1J2fTtsXsM08cgk0mYnKbf5klJhz7VXWtFIGZ5Lbw5hfdU4J062zA6mAsluJdsVv4USOJ2wBwazJk9DIWMvDdy1jXQv3AW1GpmILj9cfcvN8QaWXDmnduF6KvUaeE0C6kH/kVR7ZcRpcHPAODnfYrh8YLX3tQtAA8Fw4rvs8/HbZZf33YSZGxRcs0hoO7mhw8iJVrAO4c/GKjWe8E/cpcUjTbEYm1o/sBdrl3b9nPJiFW7OBCm8ZxsoEkmVtwtR5qf5vt+4KKtaJpOPQ/uQhUQC6FF2KntVtoNVZrevJRcDrkbKL7IES0zyWWqM+xbH7FZao5k7JtyzUFJ0RzV1enUpVX06rCyow6XNPI+xUuyUeeq8dVJonJThNoV2yrd8ZTYISeMqxogKpruoePWPmq4VtTLohQJ5Ks5RQ9uVFqsdtsk1qy4VYWs7tha/U8g626SNBkgDxwAZ8YVYEuVjQCFEiD+5DXu2VKVD8Gtrd+fSDX09x3RxT0z3muY+NjTE81y6o9Yro6iaZB5LBViTCU5ceyqIUmgkYRE5UmBZcIWkwogbq6NQ8VFrcFVqxQfjFRiVY8Q5ILNYsUlpKgVoKrc3ooyzOaVHkVc4ZUCMK7ZqqROQkRIU4ISAWbBWQNkoE81YRCULKaVlslRLfFWwUIvhU2DyQRCtczSJChHgpppWMIIhWJEHopUVhIqw45KMJo7olIplEbyozpDBEgyCoEZV9xVfWrPrVXF1R7i5zjuSdyqlGVcJuAIggHM5TIyUtPiohOVlrb1Lqu2hS0a3SRreGDAJOSQBgH7FBR5HEhEsRIBgjYiVE4KsyQB0UCJKsRWW5UIVrsFQelRBIqUJFUQOClKk4KLgpoQIymnAQU2zYgRhRKsIwoQiKyMpGJVjgq3j1lpEUFCFAoSKkkQgiEEJ7JFZACAE1E7qQUBCRUkioEkU0iopIQhAjshMhKEgEIhCATUZhOfBZu1NBEhKfBNRCw1ByEOE80wIRS0+KipOdHJRQCEInGyKEIQgEIQgEIQgEIQgEIQgEIQgEIQgEwUkIBCEKKEIQoBCEIBCEIBCEIBCEIBCEIEUkykpQ0kIWWghCEAhCEAhCEAhCEAgoQUCQhCBpFNJABBQhB9uFLU18Bpy4Z5bDHthZOJsLHukATUqbeDyPuXoOz9NtXjPD6T4dTqXLGPB/ODqtMR7pXI7RMa27eGxivcg56V3r9Fb82n5zitt24jxBVbh7Vc8DUCqnbSrp6kD1hIDCkQMSEYkAqAb0V9IjQZ/RKpbutDObYgQVWOT7tfVvh7dNv2YcRtSqNnzt7Y/evC9qXh7+CE5/kS3HuqVQva/Dm7Vwzss/GabiTzn0W2Xhe0TtdLgZ5jhFMHltVqrlxXtPrXLhnyfv8VVxfXtoLd1nd17Y1uGUqNU0qhb3lMjLHRu0xkHGFdZmewnGARtf20eWly5t8dTLM6trOl/zBdGwI/wAyeLtLvWN7bmI/quWrJMf5z+7tO+ThFWU3aR4kQq3blSbsD0XSF8OzWpj/ADh4ZTyQ+3tiZ8aIXAbljfIFeo4kNPaDgJEy7h9geuTSj7l5dgmkw/1R9izjdxMZpq4eAatWfkKv7BVTiSxueSv4a2a9QAgTb1v2CqD8QCOSSd2nqvgmc5nwicBe0SW3gP1Sr+01r3fFO1dJoBNM3Jbj/WrD8G7xS7Z8KrOghlxMEf1HL1fay1jtx23tzDhoungxz1hw+grn1dPJfpP7uFx6s5Pzn9nN7GMns/2rZJINNp/3FRfO3bCM8l9N7DWzz2Z43c6SKdSaRgfnNoVDHhhfM92AjpK77lxjn6WWcvJv3s/sqIUSFMk80uaxY+iiweuD0XVZSAq0gObQT7VzaY9f2r0osnMpWt2Yc0w3GcrnyPRwzcu2apbNj1gYXFrMLSZ5L1d1RcxlMlpGpgI9681XbL3jcTAXLGvRz4dPmKG7QcqwiDKdqwPqhvJW1qemsW9CmVc5Lrap4wICiCJ2z0Wqs1oogwssQZlMfC5TS6n8Q9FpsuaqtWg06k8lo4eJ1T4KV0w9m+7H4ln6s/SsoW+8pkUWuAxoXNMhjSDlR358bjl3WsORHWF0rMsApPDnklsvDmABrtRwDJkRBmBkkZiVyabjqXSsCS9rRmCPYmj09+ePodmZ7U3TSd+Hxj+1tyuP2izeXRmR6ZVXZ4e1zu1deQY9Cd/xLdcXtHIrXJ/89VTG7zv0fT5f931H1/Vy6Zh25HkvX2TyOztxpOfwjQcPNls54+xeNaZyvYcH9bgQBjS/izWGeQ9Af+9azupGfS5W7/fvC7cO/I+F0tu7F0Nv0q/eT9deauY/B9r+vWn5zV3O19c1aHD3EEF7a2oHJBD2j7lwbkj8H23jUq89stTCaxj0c86dz8v1Qtjmr07h/wBgWjg5a3itq92wuaRj/wBxqyW7v5+QMW9T7lZYuLbuidor08/3wtPPj5w+r0fZAEVmszIZcACN4qMd9y7OoG3uGySRXuTHXVaP/wAVyuywP4UthMB1e+ZPkyV0WEBt2RiO9ORz9HqD71w5O8fZu7w36fpXz4GGNz+aFW5+wJ5n2c0i6GNB6BVF0L0V+ZvL3TeZDgNyxw+hdLjdwK9+KrTM21p9FtSB+kFcuk2rWqFtGnUqPa1z4ptLjpaCXOgcgASTyAJUg/U1smcAA9Ry+hRvHm7WPV8GdqrcNY10SxjR4ltyx33LDbkm+djAuGbf+pcfvT7L1tXE+DNLgR6eKLgeYdUZjw/eqaTibgvOT6Sw+0XDj9ixZq39+76XHlvKX8ZP7RPjAP8Am7QduRxC5ZI8qUrzTzlek4zpZwpzXguY3ilcu0u0uLdcOAJkTDDBjpMrzBnTnJiCevimHh6fU/eMQTsmz43kosiCgGHDkrXLC6pPO6qfgkSDDokc1a6MQqnjosuu1NQwTn3rNVJWivhxBwQYVDhJysuGd7qvARPiok/i3eY+9SJABbsCcqLj+Kf+sPvWfdw2zuOThRe17XuY9hY5pgg8lM7SokADA2UsckAEoUnYRCmiU6bS4wAT4BX3w/LHwZ2z7Aq6YhzYJGeS0cQj0yp7PsCjrPuX6qKAmq0eISafWHuVlBp76n+uPtSHKAkTXZ0azZ4Vau8x9LlhE908/wBZv2FdSq3TwS19/wBNRc+Pxb/1h9jlt6efHVn0n9kbZuX/ANmR74CVdmiq7zKstPzz0aJ+cFK/bpuqrTyc77Sjlcd8e2V4JDfL71HZWPHqt32Va24ptg8oUhuk34wnAVj6bqb9L2lrhEg8uY+iEax8rLrF3VB/SKdEfjmfrD7UXcemVv1yrLVgFzbSSQ57SfnQq6THeaP559qubg4ynUphtzXbHxHPGfAlSogOIJn+Ajdmq2UGuda1CB+YT9IXTdRDnXUzIdXPtDmH71k4e0OtXAjennGPjhdik1rnXR3l9wPqtI+xYt1X0uLCdMrJSb+NkH/vNq7Pixy7NnDeHsycWN03f+u0j71yaA9djjn17HHj64+5dmi0C0ps1CTQrsPtn9yznd4ueXbKuN2nM0raf/FcR/8AunLiue00m0xSp62vLnVM6nAgQ3eIEE7TJXW7SmaNIdL3iH/3BXDHiV284x8vgnTv63+7q2BIvOCxyfTMf/zT1Hip/EWngbn/AI5RaEel8IIMEGnn/wDmXpcZEUbUdHXP/HKx/wAo+jn4/f5sDHE+Cm3dUglWMMiStvK9Jwp4HZu9Gcis3PX0Z/7is3DSfR+Kwd6LI/2zFZw0x2au3H5Z7ffa1wqeEHU2/b1os/4zFzxv32uKfNfrP0SuCS2Y3WJx9ZbbyRSp45Pn2PI+5YD8ddJ3enL8WmmZp6VKk1znO0Mc4tBcQ0TA5k+CLZmqjVcHsaWAGHHLpIEN8cznkEUvjkT4Hks29+zpLuNtt1GStfDXTxa1cDP45vLxWCifXK2cM/7Rt4MxVHhzWcvFazvy36OlgcLpQfi2ce+q/wDcvOXbia7+frFekhp4Y7MH0On9NWovM3R/G1CM5K58Pu5cV31fVJkiweCJJrtP1D+9W8QDR6E9wDqbaVpqEYOASPcCpcUYKNtb6SYfTa8x1iFVePLrDJ/m6VqDGwhjgftV3vV+rUss39XMeSXukaRqPq9PBRU6hhxBPMqLi3RMO1at5GktjpEzPNdbdOVmiaMq2jPcvHX/AAVIiVcMUz5n7Ai4reHAC8pE7F2fcUOpF106k2dXeaQPdCrtnAVmun4pn6V1qFIDtDUbALWXzAegBeAs5XVblmnJqUzqeN9IJPsWRwyeq6zWa765ZGO5rfQ0lc0NJFUcxTJ9xH70lc88d3TOQGiAAB0AVbgFY8SVAiFqPLYipNE7pQRupMVRU4DUrabSQMJPEc1vsLY1KWo7BzARHV0JtcMOrLTl1AQ+MKtwMLTcM013jOHuHuJVTwYwq55TuzubyURhWuGVEjwhHCxKmMFJwhW02+rKQHrAeMKNdPZYGjujjkufVbJ64XdqWpbad8RDSQPeHEfslcWoMpe7XqMOmRS1uFZTblIYCspblR5cZ3LTueQQ0YKsyWuACKWx8lXTp7xkqgalBWvEuKWlZcbO6o+Sid1a4ZVZ3U0xZpQ/clQIV7gCqyERXCiQrCFGFEsVgIcJU3NlQIgwmtoicFPT4p6ZQpIAiRBUdAViRQVaUtsKzT4o0+KzoVEA7pK3QFUQljSJxyUYU4jqgrKKyDzUCIVp3UCJCjNiB8lEhWvdqDQKbGaW6SWz6xkmTPPMexVlRnSDkoxCsUHYwoiKUHdTIkexFaoH1C4U2U5j1WCGiAB9O/mVWapduokKb95USqitIqTlEqFRKgTKmVWqGEk3Y5pKIDsoFSdukUjNRcYVbsqb9lFxWkVoUiFFQCRTSKBFJNCgSkAEkalECEpkplRSKRTQsqihSUUAhCEBCRTQgSE0kC5qSSUKWKkhIJrKAiUtITQgghTUSMIuyQhBRQhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAUIQooQhCgEIQgEIQgEIQgEIQgClCaEEUKRShTSkhNJQ2EIQooQhCAQUIKAlIoQgEIQgaSaCgRQhCD9GdmqDmdu+GWjpJ/DFKlnnFVq4HaYAX1RoJn0i5B/2zl7ipSFH4a7a3Ag0+0gYB/79L/FcP4VuGs4Zx8UQTDrm/EHlountH0L7/xN5Y/nH57DHp7fnf0eJfvCriTjqrXDMhRAO3iujvtBwx4KCuqDSfLkq8dUhvYburWbexVhSHxXeLSiZTcfTPhlqB/Cuy8OmaQMT/5W3XiuNkdxwSCT/JbZ/wBrVXqfhUq95wTstB3t2uGOtrbwfoXkuLPDrXg5HKw0+6rU/euWHifWufp5/D7/AL7st5/M2fhbAA+T3rbZE/5qcUAO95b+31SsF0ZpWk4iif8AiPWu1Mdnr4Dnc0T9DlrLw7Sd3LflybeijADR4JtyfsXWM5eHpeKEfhjs28jH4N4f+y4SvLU/5tuNgF6LjTnNv+z7iQQOFWUEeGsc152mIYPJYx8JPLdwkA3VQ/8Alq3/AAysozC18IxeGf8Aw9b/AIZWRp9UeQ+xWXvW/Z6T4PGl3a/hjAYJuIHta4fevZdrDq+ETtkIHr06mYnekwwvJfBmf/njhGCR6QAY8ivVdqHavhO7UA7Gi8gTy9HaQvPnfnv0v94xhP4n9P1T7EkHsFxaYaDeVCMwP9GfPulfIxBptj9EQvpPY++7rs/XtQ4h1Z9eoCPCi4feV81b/NU/1R9i9GM1tz4f93K/RHnB6pjeClzTmOqleypsGZXtGPb/AJu2knDSHT5OheKpwXAr11OT2ctneH/5Qmt2bbmVxwy1+X93a47bsbwayeANXcET1glfP7wgV6nL1ivpPGmOPZ6zfAgU3QfaV82v/wDS6udnFeTj7vtfaP8Awuvaf2PhkelN96ne/wCmP81Xw3Fy0j2Kd/8A6Y8LWU7vDL/D/mldx3DVjG8ytN6QKdONowsxMmBuExjOd7tluJp1TnAWjhmA7Chaj8VW5eqFbwsTjZT3d+PHvi7XEWRaNkQRQz71w6g/J9X9aF6HjI/J/H0f7yvPVHD0SP8AWFI9vr8enk1+SumfW3yutw4kFp56guNTMOwutYOjQ45yFfd5PT3+JH07gAD+21VsnNk/6HUCvPdqD61dw53r956L0PZc/wDz65vI2VU5Gx10MfSuB2rnRXIOPwg8D5srGM1yX6R9Tlu+T1P1/Vwmu+xeu4Y5x4GGMcA48YpkE7ZsXrxzXYnovXcA9a1tqWow7jVtynDrWq3/AJVrk8OHpMvvfv3Ye1NYP9HDZAFa6jyNaR9ELk1n/kVCc/jKv/KtHGKoqFpPLSfIuaDssVUj0aiDuH1P+Vb9nq9Vnvkz+n6wWhGqqN5ovH0Ky0qflNIkfntP0hZrcltU9DTeD7kU3EVGkYyD9KV5pn936/4e17KAHi1jBmb2/af9m1bQfye7Iz6tScf6l/7wsPZN4/DttrHqtvb2o4AgY7tpgHbkV0uIttmu4qbXvDb/AIx9EvMO0mmN/pXHO99fvy+3hnvjsfMqr8mIyqe8zEYUa5AMcwqQeXMr267Px2WV3V/eQ8gPc2QQYMYIgj2qbahMIvmsbQsnNEF9HU49TrcPsAUARpJ5Aws9MdLvG6djs1WNPjFgJ+LfUqvl64laqQ016gJjTVJ36VSuZwV4bxizDjA76mTHTWF1yNLrl36L6gM+D3H7lxz7X+T6/oLc8tfh/gdovV4fWaIxxG422/nKhXmHCRuvW9q2Ftrcsn4vFK4G36dReYpNmo0by6IWcL8r6Xq++ck/BlMhNp2TfggHfS36RKTMOVeXxdJPIHTChWbpY0EEHW5pHkGn/mU7xpaCT+cwO+1W3wmu0DE3Th/u6Kw9UmtsfFhp4hWGNwfeAfvWFxXQ41Hp7jka6dJ3+6Yua7faUefn7Z2KyDBKj/Ru8wpVPjQCkR+Ld5hZrzqSlAOokgQJAjfKtFIuoVawqUg2lo1NdVa17tRgaWky7xiYGThVc4UtciIxlSafxXd+rBdrPqDVIEfG3jw25pbgwn6ha3R3mqTr1ERviPZvKgk0A6SBBETmc84Wq+0jiDw9uoBzdTQYkQJE8uazsHxfMfaruImL6t5j7FNdnfGfJfrP1Jvdm9D6THU6Tq002OdqLG6sAmBJAxMCVW0ZTadL2uHIgobufHkpEnh2qgngNoMZnPtqLkgepUdvsf49660TwSyO2T+1UWGybbOvaTLt1dlqSO/dRaHVGskFxaHQCQAcHda3p7PUzvPpFNrID/ED9oK/jTNF/V6l7j9Yqujp7xwadVNxDQXNElusEGORwJjqVq7QD8udtJc/b9dyS7Zkl4LXNqCA3yUTlSqZgeCjC6PFQDCk0aWkKuR1U1Vnlqu4N3VPV5V1MxWs439X9sqi5zc1PNXMJFS0/u/tlR6MPv2/vy0V/wDtC9/Xq/aVXQIDmzyP3K97Q7il60Dd9wM/qvP3LPTH40DwbHuBRvP2+tdjhWaIb1ZH12rr2Rk3EGPx1f6aLguTwggMaJj1CPrtXQsHzUrkiPXquj/23Lnl5fQxv8P+SNExTc5wxFkT0xVcF3bMAvsmkadVfQfCX1BC4JP5M+BB7m2/45/eu5ReBXsecXgcPH8Y9ZyvaOOf37+/Z5bjlRtSjbkGT3944+2uSFy3ZVty5xJ1EmHuI8JMlZw7wXf2eG49Ns+rqWpAueFSedL/AO4enxvNtZO/S9Ij/blVW5/KOGdQWf8AHer+Igvt+Ftbu81258a7gsb1Xsvefv8ACuS7CutRSdVIr1jRp6HO1hmslwaS1seJgTyVD9HeOFOoajPzXFmmfZJ+1MDZa8x5LNPQ8PcR2Vvh8VzbikY/WpVW/esvB3gOrhxgOptGf7Vh+5QtbgN4NeUZ/nXUzH6rv8VltnltXBgE5PtlSTz+btO1/f5OxfH8UzqDUE/+4VznZccrdeEupsPV1Q+9wP3rA9pDvatY+HTP8Gq2IDVKl/OypW1OaIfnLXY8iB96romavgldZe0aaXxpyIW3hRjiVB3R4mfNZKXxo+0LTZCbp0/msc7HgFjK/LUyvy11Xg+g1WExos6U/wC1qn7l5m4J1O8yvb29sK9fiNuCWh1pSYCBOmX18/SvC1Hl0OOJGVx4b2rz+l5erq/fs38YP5NYY3th9qoGbC+PIWzR7tP7yreKkus7CCRFuZ9jgsusNtrpkn1raD9Vax+7HTG34c/n/dnqti3L/wA7vCCs33LSTNlUB/NePpKzzGr9Ujzwusq5XYbGQQrm/wA2T4kfQFRjqrWmKfQyf2VWZRJg8sLvUJdx28PS8pOj/wBwLz7SSCP6pXdt3Rxe9jcO1+ems0rnyeF3vHX79lPDwHcZumxvTuYH9xy5TiBUr89VMtHvB+5dfhwDe0b2nZzrhnn6tQLjTIPWFJ5a333+/dQ7c7Kt3sKm4ZSXR5agpUml23VMxzWvh9IVKsIY49VZKrSCuzwoaLGtqiTSFQT4VKUftFU9oLMWnE6lFolrQ13zmB0eyV0H0m07WgWiBUoWTD462tcfpYpllvGac+PlnxdY+7z/ABBmm9uADtWePrFUaHaSQNiFr4h/p9x/bVP2iqh/MVCRyH2rUb6d5d2B48FGFbUjluq+arzVbS2RtVb4GVKj1SeYqg+KNWfK9DXb3nAWgfGFNjsD9Dvpn5zV5aoJcdl6a1a59jVb8lRuSQd/5thH3rzThv45WZ2dfWeIoLfFWUsCVGArKQlwaBMrT588pAS1xUWDcK5jPVeIgj6FGgxztU8keiTvGWqPWSjEqdYQ49VFrSQjjruiRuqH7rUGnpuQFVVYQ9w5BxCzpjLFme2TukW9FY4QVFwxKjnpAgdVFwTIQAhpWQogQrSMqEIiGnxUkc0KIR2SU4UHAqaKClB5JhCIUHookQppFQVEQoFWvA0woaSDsixFVFWuGFByzUtVlRhTKisskchRKmouU0mkSo8pUiEjsoiB3Ki7kpOBVarNhH4xUCFYVEiU0ishRcFYRCiRzQRV1ClRqUrh9asaTqbAaTdM944nbwVOeYS0+KoiQkmUpU8M2EVB7TqxlWJFWVnwhCrUnfGPmowmlI7KMpwhEIpKRShQJCkoOKgHDEpN3SQoqRQhvNNTSEhCFFRQpKKAQhCASlNCAOyU5TKECdhDUbJhZUIQlKiGhCEAoKfJRgosJCDuhFCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEJhTS7JCEKAQhCAQhCAQhCASKaEEVJCEEUKRUVLAIQhRYEIQooQhCAKSZSKAQhCBoKEkAhCEH6n4k/T/lBAY0t7T08+damqf8oVgp9rKAAgOr8Sf7716jxl4Z8PFZ+Yb2jpkif9fTWn/KSZo7W2hnd/EB/wDWv/evseOXj/8A1fCw7zP/APavlZOPYgQMSk7MdSk4hrCfBetb4WXbdFVzSII/cs3713e19g7h/G723cABRuBSMbT3bHHf9ZcI4KS77mF3D6ke5SElrh4FVkqTJ3Rqx7b4Rqodw3ss0DawonfrbUf3LzHEHTa8OjMW7hj+0cut2zuhc2fZ8NMinw63B8+5Y37lw7p80LT+rTd+25Yk8OPpr/D/AH+KFd007efzaZH1ytNs4Dgt63BmpSI8PjLA90taJ2Wmi/8Ak25b/WZ9pVynZ6cfLNMps6KsFSaYMytxiu12jeP5EcAPV4Pan6ai4jsYXT7QvBHCx+jwqgwex1Rco9VnxDHw3cLd+V+dOo33sKyMO3SArLFwFy3bZ32FVMMNHkFZ5b9nrPgtGrt5wZsxN0M+wr0nah2n4Ru0T9RINmXHGTNpTP3/AELy/wAFxH/xA4E2Y1XrGz5mF1O1V5p7Z8arAy6pZU2zP/lmN/evLnN8ln4y/wB4uGOrv6fq5HC7oUafDWyRqpXROerCPuXlQfUZ+qOfguk6uadLh7h+bSqfS4hcxxAgRsIXq2xhjrLYicpt2IOCUFwIURjfbmo6rWYdvIXtKdIf5rWxxlzSOvxv3rxTQAZBPkveuYW9hbeuJIDmRHmJ+1Yz9nTGyY3b094xjuxdAwCRQ+2SvkvEgPTa0fplfWLqrPYq3MgRazAHmvk3ETF7WEz65Xl4/d+h+1+849fhEuG/6YzoSjiY03tTzT4Tm/pcsp8YP5fX/WXT3fKs/g7/AD/RVekGhQz+aszTLhyVly6aNOdw0qhpkjMStzw5ZXd27FEfiqxn8wKfB3RUHWYVVvPcVtviBS4Q4d7vmQfpWI9fHfmxem42fxFLG1qB55K8s8/knj3n3L0nGXAUKY3/ACYfaV5gkmxjpUn6FJt6/tPLfNfog3Lo2XXtHAMp7ThcVrgDuuramGt6Qt2PBwZazj6h2WcT28Ok72VTbxdQXH7Y+rSucZHFKo+qV1uwre97eNGQTw9x/wCCfuXH7cEd3dCT/wBr1/sP7lmz+JPo+lyZ/wAX1U/fl5y2lz46g7+S9b2WcRS4Xg+txXh/0i5avIWTvxwzgA/YV6js1UAteGO5Di3C/pqXP71eSfK4+nvyW/l+scfibxmJ/o4k5H4sLDVdNCm2ZIfU/wCVX8Sfkk5MUv8Ahhc5zyCByBJHtj9ys8OnrM+nlyn78r6TyHTzgj6E2mTy9qzCpLtyB4qbXSjyY5vX9laxdxJrxiBcv+dSP7l3Ks/g7iB62lQ+5n+C872MOq8dPyNf9hd8unhnEC2YNlV9mFw5fMfo/S579Pa+X3Dj3hzPkqpMzyRcGXnwKhJA8yvovyFvl0uKiLXhxI+Nagj57lXTZrsHOG/ehv2rRxnHDuEOjezb9pVND/sqRzuR7MLl1dnryw/iWfl+kdA02UL/AIdUaGgGnQcfE6xK7FUaX8QaRtXrAjy77/BcrjJIdw/fFlSInfZdO4rajxap/rqx/wBzWP3Lz8nePsejwmPNfr+jT2sbNvduA/8A4tXH1qi89YW/fVhjAewHw1PAC9N2t/mOIbgN41XA+dUXK4JSitctABDa9vH/APUEfuXPHLWD6XR154/T9HnLxsXGnGGt/ZCizc52E/f9ylf/AOlO/VZ+yFFrJtqtU7AafaQ5dJezx5TfLZPzaeM0zReGOEFtvTPvBP3p3sNvqQgz6YTHmygtva9n5VcR6umlSbA8Gn9yy8Qzxa2aOdyzJxvTtysS7ezlx1llPo5/HMXjR/qKP/Daua7ddLtBjiIHIUaY+oFy3O5I8Xq+3Ll9VbzJUmwGPLpOWkCfHIVbjlSYWkP1h0FuNJjPJSx5d91TnbDeOaKbmsqMe6kKzWvDnUy8tDwDlsjIkYkbKLySot3U12YWVC01XubTFNrnFzWBxIYCcNk5MDEndA5FRc3ToOtjtbdQDXTHgehxspBS9oRc0T3Q6n7wp8QP5ZWP9b7ggCTa+J/5lG6Oqu907klS+Hq8Ya+n9lYOQpM+MoBSb7VI5u7v2ftT0cR9NRcukYqf3HfYV0wf/l21j5R32vXLoia8dQ77Er3c/nD6QUT+MZBzI+1bO0H+nHzf/wARyx0cVG/rD7Vs4+IvTv8An/8AEcrHOX+Bl9Y5lRQJU6u8c1VBnwXWPFRuQrOR8VADKmRiZ2RN92isZru8VqgF/D5xMA/7RyyVmvZXeyqx9Oo0w9j2lrmnoQchauXDiOo/4hR347u39+7Ywg8XugTP46sPe2oFmBioD/VZ+yFopn+W7kdbmqP+IsrT+NaMfEp/sBV15L8k+tdng/xG4xp2P64W7hxH5SeQbVPt0/4rHwXIZn8wY/8AcWnhcvoXHPUCPeWj71xy8vdjfkkTqBrbfGRotR/viuq5xZVsxtNYOB5/HeVzKmaE4kmxE+dWVvrOh1kcDDHfVn71MvEcvOd/fs8dVJMqhpypkgtHkPsVUwV1teTPvlXQtXflPDoOxb/x3LY5wL+DAk4LyfbcOWCyM3XD9o1Cf9q4rUSRU4TJn8U13ve8rPu9WP7/AKOSw+o3yWm8Gk0gOdJpWSn8Rh/qj7Fs4h/QHpQZ96u+7jNWZNFq3Xw+oTsHNn5wCppfzoZ/WI+larI/ybdCREU/+KxUUhHFAyf+8R9dWXy6ZSax/f4PU21syrcUabhI1tj+9j7lyLmgBbW9Wf5xjJ8+6Y7/AJivQWekXVs783vKQPznLlCh3tg0wNTG2TR46qDAuOGd69PPeaddlaOF24qUren8oyoAR11NK5lm3W1zxtE/SvRcBYH1OHACC6mXjyOo/wDKuJwxv5O7yDfpCuGfeu2PJvKxfo0lo/jcj7lOwdFzVn5Kp9ituKRbDiMAx73OIHuhVWYPpbx/VqD6Arct41q57wunr+EieMXbetKhI/v1f3r527AHP1V9C4SY47Xg4dRoR/tKgXgHNmm93MUC73VAPvXLg815PR5fPnPp/ZfeuP4N4aSZmnUyf11mvgW0wAfjU4PlqA+5XXpP4J4ecfErAf7QKviRllH+yP7bl0x9nsx8T+f6s4n0Styy0/Ss/U9QtTIPDbk7kOot95d+5ZqMGo0ctQXSe6IHBVoP4sfrfcqnO9Ygqx2KQ8SPsTe0idDLn7YpPP0L0FpT1ccvmaTllRo9pBH2LgWf9M6dqD/3fevUPbo7S1mNMAwABzllP95XPmumc8tYX6X9HNtSR2rpgiJuKwjzFT965NBhfRe/fRSDz72j711aJ/8Am+kNpvKgjzDwufYZtLwDf0Jp/wB5T/ervs6Tx/KfqwnmEhtyTO6QlajjSOF0eDf6SADu5mP74C5xg7rdwl/dXAqHEFh/3jVb4OP7zo9qajKnFKjmOJkU4Ph3NMq6u+bC0IMw3h591JwXJ4m8uq0jOfRqGfHuKf7l0TJ4RSM729qQfIVR9yxrWGLx8OFx5cd/h/hyOKNjiVwP9c/9oqkmKL8zgfatvE2/y1XbG9V2PaSsWDRJ5R966SvdZrKsVXdVjdW1AMnoqoVePJqoEaBChWEHKlb/ABVGuc55KtW/K9NavBpcSpim2e5rv1kmQBTI0xt0zvheRcBA8l6/hze8ZxPwt7ifa1//AOq8hUGBHQLGPmt+r8RAKykSHAjcQqwFbT2J6CVp4sfvNzmf6XMmA6B/eCfCKHe1Q0jeoxp9pKue0tfet/XH1pRwlwpsq1D+bWoH6xUle7jxnXj/ADceu06zI5opN1B/9USr+JM7u5qMOS1xbPkUWYBo3QIyKBj5zVXCY/xLL+bODHsc37VbRpms2qA2Sbmk353e/uCrjPtC6fZ9gJuDn1K9k7ad6zgT7ipa573ZHnX5MqJHipuOZhROyPPfKBSCkQfYlCCBwoqbt0hsozYhCUKSUIyIUSrIUHYKKgARKEyYSGSSogQUykSoWIuCiBKsOySiKaghVESr6vJUxClhfxVlRhSKSwlJIpoREXKKm5QI2URB+ygrHCQq1ERIzCRCmVHdaZQckmWwkoiJyoqUKLh4qwQIkbwlEKREKLtkDkHZRcfWKbUiFGarIkkykRCbspEytIidioxCkUiohIQhBFDjyQg5KyIITjKCooaYUlBTCJRCRTTKmhFIqRCiVFJCcIKBIQhAIQhAFJqaUKVTS0+KaFlAhCEAhCECLczKipqBRYEIQihCEIBCEIBCEIBCEIBCEIBCEIBCEIBCEIA5QMIQEAUIAQVFCEIUAhCEAhCEAhCEAkUyopQIQhZqwIQhRQhCEAgoQUCQhCBpFNBQJCcJFB+juP3A/wDjReVGn4vaIZnpcN/cV6D/ACmQ0dpbBwMk1uJAjp+WFeM4/VA+E7itWZI49Uj2XP8AgvY/5Sj2v45ZPBJi94u3P9W9j96+1nNcnF9Hw+PvM/r+r5O52+FCr/NunwTBBbnlzVVyfxVQgmQ0r07LOz3Pwt0xT47xeAJbx1zZ5keiMP3LwpOZXvPheqMdxzixa6dXHXfRZ0x9pXgCVy4b8kak71IlNpjKr1eIQD0XVW69rF9K1BM93SDQOQVNV006Q5aD+0f3qp7pDR0Uaj5a3Ow+9KmM1NHuSr6LiLWsCdyz71kkkbq5hPozxPMSpW4jMckbhV6oOVNpViadHjnxeHCT/wBn0hvP5z1zHOmF0eNn8Xw5072NMD59RcwmRsrUwnZbSeW1GkEApDYDKgDAnYoa4lZ239HqPgwdHwi9nIn/ALSojHmq+1deO0l65pA1U2MMfqAKfwX6W/CJ2cM4/CdD9sLl9pqhPHLtxP5wnxgLhf8Ae/k6T7tY6zpp0mg4Y1w95lUPgmEi6TKrLsrttlOUmZOSYUJSBPVDy2OqU3inppNpQwNdpcSHOG7jJwT0GML27Lof/DukzUQRUOI3HqgD6F8/Y7qvTU67h2XtKGrHfPJ8c4SfiZy5TUe1FUO7GMaXTFtnPgvmPEXD0qqf65Xv7eof813Mnah9EL55fGbip+uV5cZ3r9B9oZ9WHFfyXcKeBfU5ONSOMvniFaD+cqLFxF1T/WCXEXTfVDtJW5PmfOuf8Lp/NGs8uY3wCqa6HShzsCVAFb04uvaVNVOqDHxFLhT4rdMrFZVPVqZ3aruGvmrjzXOzTvhl3j0vFapNs12cWw+0rzr3H0Qx+mupWqarV4M/Ege9chx/Iyf9Z9yR6PVcnxMupW059q61o4GM+C4zD60Lp2riA0CJK1k8vFdV9a+C13e9vqE4nhjyfmt2+hcLt+7TTrubg/hev9jl2fgkIPwgWcHB4U/7AuH8ITgKVWefF6/2H96zf92fT9Xsyy/jep/fvHmbJ34+P6p+wr0nZ2oPwVauB+JxbhP/ABa/715fhxm/ptJwSR9Urv8AZ9w/A2oH4vEeFH/f1P3rfJ4/ozwZaxv8/wBGHjp0VHNLh8Wjt/ZrkPdHNdTtGYru6llAjy0FcNz/AFsq4TcX1uX8bJdrkzKupOlxlYy/orKTzqycK2PLMntewbh+FHSJ/E1MdfVXbpku4Len/wAlXAx+iGfvXnvg/dPFawPKg/nPIBd2gZ4FxBwPrehXRB8m0l5uTy/Tehu/Tfv83zKqZO++6qDjGdlKs6HwqwZnM4XtflcvNei7QAN4ZwMEYFkz7SslDHB2bCbrf2Bae0zj+CeB5/7iw+2SsbCRwOkZx6QSfcuMvyvp8s1zX6T+0dLjbjq4eM/6FS28lqNUei8UOc1Kzo//AJWr+9YO0DtFWxaJH5HS+xWWZ1215SHNtU//AE9Vc8vD6Xp7r1Nn5/o9D2lcX23EgfzePOHvLz9hWTgn89cOIAm5pDptdnClxau2tw3iLjJLuK0Kp8dTHFHBQXU6pJMuuGkCdz6cz/8AZcb9x9Tjvf6T/Dyd8fx7iT+j+yFazT+BbonlVp/SHKi8INcwZwD9Csa7+Rr4Ts6ifrOC6ezw4X+Pl/N3O1rJ4hfNzj7qdQrn8QaBxm1B29LobeNC2XT7TkO4txGAB6+n/dvC5vFp/DtsAYi9oR/sLdc49/P9236OX2iP8pePdUv2AuU8jZdXtMA3imkcqNL9gLkO3JW3yvWX+Nl9ai7dA+JU8B96R3SB9Wp+r96beVW6OaQTO6FnbBNKsDi50mBiMCFWBCbDIKXu21sd+Nth4gfWVdZ3rmMooOmrR3w775SqfGPisu9y3jv9+Cwps3VYUwozt3WD/wCXrb+1d9r1yrf+cB8HfYV1KR/kC0j5Uz73Lk0D+Naf6p/ZKPdzf8PpP0FD47T/AFm/aFu7QZvfPX/xHLnUzDh5j7V0e0IIuGuiAS+P9o5WeXPC74cv5OW8+soNyQOqbz6xUWH8Y3zXV4Le5nBUmOEEQDyUHuh2ylT0nUXOLfVJbDZl3IHIgeOY6KM291oeXElxJ8SZK20jLuGdO90/71c+RyW+z9apw0Qf9Jj67VXo4b3v79402zieM1j/AOZqO/4ipc3TWg7hlOfmBSs3fym905NV8+3Wi5j0iodgNOP7gR2ym+OfV2uCj1ZG4ZSHvc4/cruBO/EHHxjTA9tRqp4aWsL2wY0s+im4qfATDKQJ3qW/7Z/cuWXl78fEaqYBt7eScvsfoc79wWq6IDbAgnLac/7IFYrR2qlYAgGfRiferLqq1tnYHVBAZPsotWL7M2fPv83lHOGgeQ+xV6j1TcTpGeQVc5XXbxZeW60P5VZeBH7blrq4q2Rb+bRpjHXS8rBaui5t/wCqCceblsruh9tBJhlMY/Ucs16uP7rmMPqtb0C28Qdi3/8ATt+1y57T6rZnYLVevnuQTtQaPpJWr5ebG/LWy0eRw66z8n/xWlAdHFz4XZ/bKyseBw+u2fjEAexwKv1D8KkxBNcO+mVJ2dre0/f4PZUj/omMk0/26n7lRwtodaZiO+4YD4Asoj71MAhnDh+kGn3OqKPCP9C3P+kcL/ZoLzb+e187kl6rf35jp9m6Q9K4UP8AyDXg+TXg/thcDhZ/JauMhur6wXo+DEsq8FaDn0CuD4+pRK85w8hoqt/Tp6R71ri7yuvDbcr+/wAXcuKc0qojAvKTAen5KXfauTYmbs+WfeF3+Haa/Cb+q6ZbXNUR4UQPvXn7HF07oKc/WCYdpZU4c7rLD8HqeEuB428Ax+Kt5/21VeHJilU2za1eXSu1ez4M6eO1R/ZDbpcVV4qofxT9/wDR64/37U4fdn0t+fP+SV8Z4Lwx/LXctPz2qm/fNGg7mWOj57lZdkHs/wAOM/8AebofTT/es14ZtbR3VtT/AIjl2x9nu3/1v9TpO/km8E71bePrrPS/nmfrD7U6Th6HXYebqZHsLv3qFAj0mnJ/PH2rX4rvv+/yD4FQ+ZV9UfiQTy0fS1UmO8PmtFYfij+rQ/YKS6PxK1aC2uOZpQPa9gXqXkP7UPgjIY4Sf6tILzXDWaq43h2hp9tVgXd70f5wMqzDXUaZ2znuh9y5cvf9/Rx5PuX6X9GC3P8A84W8n/v7hjzcsXDyfRLxw/8A8efoq0Vrq+p2wpxgMv8AJ9p/es3CwPRLnEg8MrYjm2pSP3LV8f0dpe39HPO+yAOphSDCQ92po0wYJ3k8gmWkVC3mJW3OogEmN1otA7Q+MeqPP4wVPxYIOJd+zK38Np66BdnLW7/rs/eFbdRce17st4ZrNE7U6bfcwD7l6Czo9/wOwDIk2Ix+rWqt+9ebuD+OC9R2feDwywbvpt6rTP8AVrOP/MFjm7Yx5+S6y3PxcTiTD/nFUZIBNYt9sFc1g/JyYiR1XX4mI7VERveOE+0/4LDb0C7h9eryY0H60Ky6j167uZU3KhhSqfGUV0eDLyvt8CVG4H4wiegV9mAYnGcqu7bpuqg6R9ibay+7K9RwoRS4q7n6PXJj9WqF42pEwOi9lwx7nN4pqGX2tc4GNqi8a7JB3wueH3sl9RflRiVJo9R55aT9iR6rRaUjU7xoJ/mav7BH3re3jxveOrVb+UXwO4qPEf3QfvWayP4ms2f6WkfP1l3q9DU7izQ3Y06mcERaBx+krg2ZHc1zOGuY79pSXcun0OOy5SfhtV2gaBxWuG/pvPn65H3LPYwTcDrbVPuWvtFP4Re8xLg53ve5ZOH/AM9Vnb0er+ytTwxl/uq3CbCk/mKrgTH9UFdPsqA6pcsOdVeyH+8efuXOB/k1zTEtuOXiz/BbOzFYU+JNpmPxte3I/uOcfvWcu87PPyT8PweepkOpMI5tB+hCVH+Yp/qj7FM7JHnRKi5WMEuA6mEqgIAnm0FVddtqXKJwpJOnmURGUQkUSppLATgpJn4qEqVAoUnBQAhGTSJU1Ej1lKqKRUikoyrqDqFS5X1BhUlZpfCBEqBVigs1ESkmdklEIqJU1EhSppWFF4A2VhVTlEJIgJoVLESq+SsdyUXCUZRUSApJFEIiVBwEbKag7kqIoKTkAKaREjKSkd0lWFTjIUSpndJXSoxiUkz4JKIEipFJZEUFMpIFjoiY2TKYGECGyEykogOySZ2SUrUCEIUChEIlEoEhCkgihCZTYSAhRKlipIQhZQFLV4JoQLV4KKmoIsCEIRQhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAE90kwgSEHKFFCEIUAhCEAhCEAoqRSKUJCELNWBCEKKEIQgEFCCgSEIQNCEIBBQgoPt3G6hd8IvE3TI/Dtw7P/AKpy9p/lEGeK2ZJmeJcc/wD+g5fP72s2v2u4hcB0tfxC5rDPLvnuH2L2/wDlA1g/iHDnTIdfcbcD58Rcvs53efH9P0fHxmuuPmWqN1XcP/J6mP6N32FQqOlVVnfk9UD5N32L0exp7f4Ta4qcb4hmf5Yqn/6aiF41zoXa7a3guOP8QLDLXXhqtPWaTG/cuC5w2lTCaxkSe9MlMFQlGorW2kyQPBBOOqgTIklEoukpVrXRRM7SFn1QYBU9UsIUXRFxlTaYjxVQwVJpyFd9y+Ha462OG8HrbA2RbjqKrlxtUHB5LrcaqauB8HZj1aLx/vHLiOJGVzxu2s8ZjdLQ4wgFVagmXeOFpl3exd16J2u4Nckw2lf0Hk+VQLHxw/yjXkR623RU8JqGnxK2e0wW1Wn6U+0D54nWM/nLnfv7dZPkY3OUS4yoF+cKJOV02xpaSnIVWqQJgIDjOSFNtRcD1K7FOpHCLeDtUeuJqC6FOofwaxoOzyVqUe2snl3Zt886B+xeDuXTUJJG/Ve1sHz2deCc+j/cvDVyNRkZXmx8vseu7cfF9Erd0VmGfzhlK/cTdVPNUUXRUaf6wVlyQ66cQZBK6eK+d5iFQmG+SgCQVdcgN055KglWXsjbaOGh4PMK7h5ArjwKyWplrvJW2jh3u43WK3jXcc6bV3TSVy3n8jcf9YPsK2scTbPz+bhc9zh6GRP9IPsKzi653atpyPNdS2PqtgrkMJ1LqWximzput5Vz4vL6t8Ej47d2B68Lf9q4vwiw1tWT/wDxW43/AFV1PgmMdteGyIP4LqfaFxfhHqSawDjnitz7lm/7s+j03/d9R+/ePM8KdPEreIy4/YV2eB1gOA1pzF1w47dLj/FcLhR/lK1j9M/YV0uDVGs7PXhMkMqWDzHQXTQftWuTx/Rnivyf1/RPtYC27I2AbTbEzsHj7lwHOyZXoO3Te74vUpkyW6RPsd95XmnOg9VvC/K163/eqYMFXWpJqBobJKznDA47Ex7Vq4SQ69YCcEO+wrTzYTeUn4vV/B4Z4xcEEZoPHuhehsnH8BcRnlaXwnlgUP3rzXwePDeJ1TInuHj3wvRWbo4FxEZP5JxKR5ejheblfpvs/wD+2/f5vmVSNTsjdQOAcyensSqOGonqVWHwQV6tvzFj0XaZ38j8Ej/wTftKzAR2fokne4dPuCs7RPH4L4OOlmwfSVTUqRwKg2cd44/YuPs+rya+Jnf/AIz9G7tM6K9mc4tKeI2wnwZ0iq3V6xZU/wDt6oVHaSpN1amdrWmN/BU8KrmndsE/HJGdo7uoPvWJ+D0Y5zH1Vrp3FyTwO6JJGqpZuONz3JXW4W80zUJ+L6eGiPC7YT9gXmWVC/glZsnLbMnz7shdi3uC22BA+NfucB4d81w+5c858un1vTckt3f33efvjFw5s7GI9qKR/k6/aT+bSP8AvFHiekXtwJyKrx9Yqtj4s73oaTCfY8K3w8GOf8e/zen48dfFeIjBIuCPP1ag+5c/jTg3j1AdLq3cfD8VRH3BbOJP1cc4rMYugNvCsuX2gfHHQ5xw2pbu8/UprnPL6PqMvlv1jJ2nJHFnA7d1T/YC47tyut2qgcWdBkdzS/YC4rpXTb5nq7PjZfU0mn1X+X3pEylPqnyj6Vnbyb7oFIKUeKiN1lNmm3B3UZTBCb0sq6kYqCDmUnGHHKiw+u2OqC6c7KXu6b7JsMlNpgpU8vCARuoTxHetzPALYTtWP7Tlybf+db5H7F1bY/yDbdO+/wCZy5NufxzPAH7Fa+hz3vh9J+iLTlvmF1u0bYFN07uf+279y44O3hC7HaKe6ZnZxPvdUSeXPju+HNw3opH8Y3zSfulTPrt8wum+75++6TjCUqJwAlPgm02uYd5W3h1T8rs2nGm4Yfe5v7lztS02L/y22/t2ftBXbrxX5o3Wp/lE4/Pd9pU7w/lNSOej9kKmzk8RAG5e4DzkqV28OqBwOHMpEfMBT3euf7f83csn/jamf6MH/cuS4I+KNuZ/paJ/3hWe1f68Yzbg+3RUH3J8JefRaXUPpn/eLlXvxvdva8tPD2Tj0ek+D1BhZuM1S2yot6VCPZ3cfcnWcG1rIg5FpT+8rHxuvI0ACBUJ+oP3rPuly+W5OW92SVXOUnOz4KDnZmcLfh825Nls8ekUthAI+3963VXerQO5DWHJ6UXFcm3eBWaR/GF0XPkUhOYYMf2B/epXq4Mt4uc0w1omYgLTdn1aX9kyPcsjXDEmThX1XzToAmYpf8zk288y+Wrmu/Jy3q4n6Ar6Jm8aQclzI+hY2uBox/W+4K+0dN3S662farXTHLfT/J7qs5uvhkbQJ99RR4MPyTSTnvuGn3Mo/uVdR/5Rwtg/Qc76a37lZwUxTLZ/PsD/ALukvJXkz+9f37urat0XnAGjnYXH/Corzlv6tRokYM/SvSW7tV/wAgyPwbXPvpUf3rzzWH0uiwDLi2PaVvg8J6XLe/p+tdzhNZrLK+oTl/euj/25+5cOxP5U/wDs/wDmauvdUxa8XqUwfjtc2P1qFT/9VxLI/lpE/wBH/wAzVqd5avBlM5nlPd6jgx/lomd3D6Lit+9eLujNOrGIoXEeP5Q1ex4R/wBptc48qjp66bg//svF3rtDKsbdxX/+6aE4vdn0uX8TMrp5HA7JvS5uf/xqm7/7NsjM5uB/vB+9K6fPCrNo5V7n/kSunH8E8PH9e5/bau0e3f7/AKqKR/F1B4N+0qNI/jWmchwPuRbTpqxuKZKra4Bw6q+7W/FaGmazZ/SyttxihWI+MG230tK58nWx3Iu+yP3roXRDaVxGIp2x9whLPC29r+/wW8GbJ1cg+j/xmBaqlQ0723dMRRoD2SxZ+z5mhXMmBUo/TXppcZqaaluZgOtKDvc0fuXLLvlYzZu2fl/gcTcW9qKzh+ZeF3uyquEuAt6wxJsLkfQ133JcbqB3aG8e04N07ZU8LJ1vGBNtcj/crpr5YuOXaT8mV7pY884K11APTXnyP0D96wk+q7yW1+bupH6NOPaGLVXG96URTcYEA1Dz/RaPvXS4QQ20oAx67qQj2sP3LnO/ma520h8e6mtdo/RQsA057xg+z9ymXeE73Tn3oi5qNH5riPpXpOzzweHUBPxad4Ppon7yvOcVhvFbpgOG13ieuV2eAv08N1A5DLyPPTSP/KVOf7jz35rVfGvV4++tORd1DPkxhVVJrWcKvuRNJp/3oCfaMzfXDxt31Yz/AHGD7lfV0ixug3nZaj7KtA/efem/lj045bk/k8xWGfFQyBGynUy5QaepXXb5+d71rsz6pPRQv8XlQbw4fYFK1HqOPmfcJUOJGLysOev7k92+S/wo9FwZ7tVdpOX21w2AfF68lJLW5nC9XwjFw0k707kbb5f+9eTbHdMg/mj7Fmeaz6i7n9DXX7OMD69UmMUX+3LB9648rudmWz6Q8fm0iPfUoqZeHitslsegsqZr1OKMZnW0NB6/kTAvL2oi2vMxFAn3L1nY8Gte37Zw2qAfbbNC8mwhrblsTrtXj/drOE6cssb+Tr6PnuV6h2hM3rXH86nq+u5Y7ID0g43o1h9QrVx1wNS1cDJNt/8AkesliZugDzp1R/u3Lo9eV/iz+Spp/J6u+zXR7Y+9WcJdo4vaPPKqPvVVGDTrDkKAI+c1OwMcQtj0rN+1HCX7u/33YAIpsA6BEKTuXuQEcvdbw9odxC2b+lWaPpULlgFKkZ3otP0K6w9XiFqY2rs/aCLxv4uiOlFv2u/cjv0/w7+/wYQkRmE0nckeZW7dJB3KFESjCRGysI9Rp5uSeAHETs6PJKtxqp28JK24Z3dV9M7tMH2KkqbYs76TUecKUS0JYG4SiBSTKSjNIjCocIK0kYCoqDMqVfCsqBUohCzplBQKkUiFkpJFNIpUQKi5TdsoOUiKyhCEoTlFTUSCThIzYg4JKaglZJ2yiVI5CiQUgi7koGVNwKREKiBBlNMmFEwjNm0XCQoN3Vh2VSrMJyQUkFNFRSUiouWagQUISqUJKSRUCzyRnmmE5wptEUFCEUkJlJZUIQhBFMIKSBlJCEC3TQolTSpIQhZQIQhAIQoIoQnpQQUCQgiEIoQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCyoQhCAQhCASTUUoEIQooQhCyoQhCAQUIKISEIRTQhCAKSaRQfTbOoTWqOkD8TV3/VK998OVbvGcAqA/HqcWfHPN+V8zpvMO3yxw94Xt/hUu6d1wbsnUY6XPtb6sfJ94XN+9fb5J82Ov35fHn3/5X9Hii9QcdbXNmJaQqi7G6WvqV06m9Nl7WNa5qVju8gn3AKjUBscqIa40nVQRpaQHSQDk4gbn2KBMDcJ1aJFurOSUEk7FUajMJyQnVBcHckF3JVat0F0iE2LNUHKkCYVGpXURqp1HH80Slul1stWMlMGD4KkmM7ptcBKSmnT4hWLuH2Lf0GO+lxXPc6TOwVlxUDrW3zs08/FZp5rOPZvLumSnr6KrV1RrHRXaabLN+m6puHJ4U+LuJvXkmZjPsWazd+UMEfnD7VdxZ35XUx0+xZ38zWvl0yZAmRCTioudKRK0SJSiVXKYKbXS1rs5W6k8+iRO7pXNBkjktlJ0Ww/WKmyR7Ph9SOCvBOe4j6F4u4cRUcu9aXMWBYT+Z18F5yrl5yuWHmvoeq5Jnhhr2hAwQmXE1JUOSG/GW3i2vuXF2kzyVKdd0+5Q3KRdtNs6A6OittCA+ZKy0zE+SttXeupksrs0nTa1DP5pWBzvxGjmXSVppv8AyVw/qlYHO96xHXOpN3XUtnfiqZHSFyGuyurROmmxW1eKPp/wUEnttwsCM8Oq/aFwfhCdPeS4H+Vrldb4Laxp9ueDEZLrGoBOObf3rz/bd+qlP6XELhw9olN/xZfyevk4rM+fL6fp/hwuGE/hG2k/0mPcuhwwk9neJNA/MtIHj6ZT/wAFzeEjVxO0g57z7lt4UQ/g/E2ZbNtQIjlF3SWsrHHDH+H/AF/tHS+ESPw/XgyHCm75zC77CF5So7kvVfCIdfaGvMD8TaHG2bZh+9eTuWllUtIyCnHflh6z/ct+i0mbVk/KH7Ar+Emb6l5u+wrISPQm/wBsfsV3CnfllI+J+xdN9nnw7Z4/yeo7DvDb2q4n+jcPfC9LZ1I4PxBsmfRuJCek+jleS7IPi4qmY9Zv3r0fDanecO4k2dqXEG+UiifuXDkfqPs//Yxn793zmo7lvhV6t4SrOyPJVtduu9r8ta7/AB908O4YA7a2aNuhKqqv/kagCB8Z32qHF6oPD+HRGKIH0lVvqg8KoMO4c/7lytfRzy+fL6T9GzjdQvq0CT/QM+xZLeqG1WuJOEuIVJdSM/0TcexZhUEjcLJnn/EuTfbVPySo3o+3afGCR9kLXTudNrR9Y/z4P0s/cuRTq6aTxzJY4DydKkap7rQ07PLv2f3J2evh9R0T+S7iD5u6rpmar/2nKFNxNret60J9z2rLUqOdUc92SST71dbODqN3HyH/ADtWLXPDPfLcvr/avSVqravF79zfz61N3vFb965naGoPwy/OB3B/3bFPh9YP4lWcZgvo5nwqfvWTtA934WqeAo8/9WxZnl9Ll5Orh3fx/wAodpnzxIkH+ho/8Nq5RJK38dfN9JP9BR/4TVzZS14PU5b5cr+dMlQJxCCkp5ebdOUkkpClNhMEck6cHV+qSoalV8Ta1hIqN80KAOZQSo11dtLaB/GBNm8SqmOhwPRNjsqNdXbT0Nsf5Bof2v8AzuXJtT+Np43n7F0bVxPAqRnaqP2yuXZkm4ZPVX3fQ57u4fSFqmYXd7RfzLYOJafrVV56RpPku/x//RGGOVL7aqRjgv8ABzjgOMShhhzfByi90DOEEtFQgODgHEBwmHDqJzlX3fOt7k50AeScepqkbxHNQO+8oBIG5jortNpBXWzouKR6VWR84LNqhTY/SQ4bgyFPDeOWq6ti9v4aZB2rEfSoPcTRo5z3VIfUCr4fUB4rTf8ApVpn2ql1XVSpgD+jp8/6q3Hsmfy6/N3aD/xm+9Fo+mqE+FPAoMHRzP2ws1B+SZ/o2D6axS4S6Qxsz6zf2gueT2Y5/NG+6qxXthyFrTP1CuZxOqXXNTM+t9y03dUG5owIAs6X/CB+9cm6f+OfnAcVmMcuesP5ovfKRcOqqLiokrVeK5L2O0mV0G1BqpD/AFjBj+xK5LXQVo70922T+d9lOPvUdOLk6UQ7AVpqYb4Nj6SfvWXUYEKwn1G+SOcvlrpu/FwY+N9yutHxc0f7Rk/OWKm78XH9ZWWziK9Eg/nt/aTbpjl3xe7dUP4Y4bTmfydxjx111o4UdgDuyx//ABNXNa+e1fCqer49s6B4mpXWvg1QltFxODTt5z+jXprlcWMp82X793Usqpc/g7wT6nDXN8pFuFzqbwOMWrZ/NalTue6trd7MuZw6oY/rB9AR9VYqlcDtHQEw1tVjMhXCalc+HC43L6PTcUM8fbPyrR7O5uF52wMcRe0z6rSPrNXb4hUP+cFPoax+incrg2pH4aq+ZP1leOfLfo5egvbKPU8IcDxG2H6Tbse64YvD37iWVZP9BU/+7/wXs+CuJ4lw8bz6d9Fdq8LePmi/+yf/APdO/crxT9/za9Nf4mf1n6oV6uq1t2/o1a30lqLh+rhlkNUkPuP22LLVeYa2di4++FE1D3TGThpcY/WIP3Ltp7bm02rhFbf+ad9iomCVO0OKg/1L/sVM5U92rl2jTJ7ul01P+xq6l8wijdGN6NuZjx/xC5OomhTz+e77Gr019TBtq0wIbbt8xNH/APZTLLVjh6jl6JPqydmyDSuGznvKB/3zFRx4yyxd+lZUvsU+zrvXridzQ9v4+mquNk+i8NJ3NjTP2qf+69Mvf9/gy3dXVeVXmfWeXe9T4WfyiJx3Ncf7orJcmKrvZ9iu4WT6WB/qq3/DK3fDnjbtnaSWkz+ZP0LeXReOA5sZ9DGFc5vxD+p9y6MRxYMP6P2U2p5dML5PTNhcOE71BP8AdprUW6GcKGxqVQfcs9DPCKnIzV3/AFaa0yTU7Ph0H1v+cj7lnflqdqwcbxxq+P8A5mp+0uz2Zb3lvRpbl9zUZ86i7HvAXE44f5Zvv/U1P2iup2Uq6a9EAk6b+39gcXNP2q8k+R5be2X0U8ZcH0qlXJmtdZ6xp/etdwYsq0Gf5Mqe+LYrDdOD+C06uZNe6n2hpW65lti7Yk8Jqmf7lv8AuWPaPTvV08zUdDsqpxkmPNSrfzh81AbzC7PnZ5d3U4U3U0gwMvJ8hTcfuUOKUwLm6qGrTDhcGmKR+ORE6hy0iIOdytnBaUWzK0ghzqw8gKZb9rwsfF5PE7obRXePeVJe7pld8cdrhX8+w5Bi7b7nryVP+bZ+qPsXr+Ff6awDID70bcta8ez+bb+qPsWcbu1Oedv6JAxiV3uzBildHowf8SkuBOV2ezzwLe+zsymY/wDdYD9yXw8d7436V6LsNWax/F36tLmXlF3rcwSyl9pHvXlH1CC9uZ7usyfY5q6ljXdY1eJ76XXtNr/Jl60/8i4dV0VHgQYc6faT+9dM5Pi2/vw4+hlxwm1/GXA+hlvO3/8AyPWWwP5bS8dY+o5W8TcDSsiCP9H/APyPVPDvWvqA/rEfUcpPD6dv8WfyV259Sr/6dx+lqVkfy+h/bM/aCVsZ1D/UP/Zn7lG1dF5RP+vZ+0FNue+0U1hpqPb+i4j6VEFW3Yi6rt6VHD6xVIwq5Zdsq02ZLbug7pUYfrBWXx/E0f7Jv2vVNE6X0yN9U/SEVn6qTMDAg+8/vT3d8ctYWMvMocMSpNEuA6lFduhxbM6XFqm3n1dbZzumN0juUA5T2T2XfmU/A/epXQitUaN9bgo1JFNviJVl5i7q42e4qVv2/mr4j/ptf+0d9qzrVxMab+4HSo77VlRjP71X02TbF3Qn7v3qqCZMYmFtt2A8Lc6cgv8Atp/vVVBrSxs5BuKTT7SVXW8e+mfiyEZSKvum6Lms0bNqOHuKrPxQ7xWHGzVsQOypfzWg/FBhUVBBPilZqpwkKKsI9UqBxhRKgR4qJUzsoHCzUR5JFSOyiVKiJyq3KwqDlEqvmhHNCAKRKZUUjNpKOnxUkKsoJFSdyUSpBEqLuSkVH4yoiRKgRCmoHcolCgW+Kmk5GECISUjlRVUnKJ3UyJUDulQIKcIhQIJFNBQKFFTUOZWaAbpobunClQkQhCKSE0lFCRTQoEUkygoEkQmhAg7wTBlKEAwppUikjV4IWQJAZTQiFqCAZS0+KbRCKHclFSdySAlAkIQihCEIBCEIBCEyZQJCEIBCEIBCEIBCEIBCEIBOUkIBCcpFTShCEKAQhCAUVJRSgTSQsqEIQooQhCAQUIKBIQhA0IQgCkUykUHt2vyCHTsuz2muDW4XwHU4nu+Hupj2Vnrz4MLpcVqF3DuGiR6tJ7R4euT96+zb4fOwm5XPDoG4TkYVJcdW8I1Tj3re2GjUAo6pVIcTMuAxP+CNXPIURdrg5QX+SpDjJkyjVGFV0v1GUHDQSd+ip19DCc+5IsiZIK02ropVhP5qzVqb6byx3qkbjClSeWtdncI1AXe1R1TupV+4D2+j1KtRpY0uNSmGEOj1gAHGQDIBxIzA2Vc9SkpVz3/iGN6SqtXgguwAQokiYSKerCJVZdmEyfVwmxptXhtdsj84ZVl88vrOcTJKx0HRUHVXV3euSSs77tTwrdB8FGQguJCjOZV6k0nARglQ15xz3RMJ1GlnNXsf+JDfGVlklWscNI80206dKqRTifzYXOe7Kt7whsDpusziJ3Wce1byy3NJTkKTnQYO0KsOggpvPryrthOoZb7FBh8UnO+lIlXYvpRyVtuQHkFZ2O9inTd628LNajq0yfRneSwOMSVopvPcOydlmIyQViO17hjoK69EmGHlzXHEAjC6lNwDWg9ErXH5e07L8R/B3avg11mKNBxIHMRqIPzVzu1dYPDQ10tNy6oDHJzJCy39TueJ25Dvi02hvhIcPvWLitXvKdqAZ/EtkxzGofx5KT7231PVWY3lwv5f9HwV5bxS2MiRU+5aeFVIsL5skzas25/lFMrncMP5dRPPvAtPDnkWXEIMH0UfRVaVp4cL8k+t/R2u3J1dpapdBHo9ljw9EorzfFXTfVCB0+xdztk//wCYK7jsLSxP/wBHQK89xNxN049Q0/Qpheycl3xf0/UifyBv9r9yv4U4emU/b9hWNx/If/d+5XcKdF5T/jkuu3nxnzz+Tvdmqha+tEbNP1l6PgdWbLiTTJBbdxjkWUui8lwWqGMqu29QH6wXd4JXm1v2Oye7rEe1jBP0Lnl3j9B6DkkmGP1eJc+WtJOYSacqBcMFRDiNl02/O+zp37ybS1zIawAfSo1HD0OgPElVXrj6PRH9Qfeis4eh05HIrnXot71bdvBbSzswKokDZKu6KVOc+qFUTjdSm+60uzko1nkVTPrGU5hYrfUmX5yr7Z0UrkA70QPrtWQu8MhWU3RTqwd2feFHTjy1k6XDasXNV0iPUPuDlDjtQO4nVE4il9FNiy2VQ6n5zAI/j2pcWqa7+oWkwQw/UaPuT83tvJv0+vz/AMoX1bvawf0pU27dGgLNKVRxlVyjy5Z3K21Y4pgSxx6QqS7rKsa78XU8h9qbJZtGUpkYUS7okSealrG4upSNZ6MKhKlRMtqzyZ94VRJlRu3tE5HVAd7VCUFwV3E2nqUmnKqBmQAmzmVkjv2tSOBU5Mfjf+dcy0d+PYc7rZbP/kNk/wDiCB7wVz7Z345qbe/mz74fSIFwLTuvRcfqTZUhPKn+1VXmC4gYXf42+bekN/Upk+U1ionBn/DzjiuPVFJ7e8YXsL2Bw1NDoLhzE8vNQcfV9qiDqLVXh909XrEgQ2TAJyApub+IFTXTy8t0avWEAGSOmcHwKoc6SiTo9qQiYOpwGM8ycJ7Hl7CqdSJwrabb+HP/AC6h01hVtfLGGYmm37FXYui6pOOweoseA1gJ2aB9CsrpMtR2LeoDScZHxR9lUqXDHwdM51tj3rFaVAaDwT+af2Kqnw15FVon85v2FSvZhyfNi23VUC4aBysqX/CauZUcXOMDcrTdOBrAzE2lOP8AZNWSjHpNIHbWJ96zE5M9yT80HOUdR6oqn13eZVZdAlXby3LV0mXGN1YXwwZ5n7As2ud0y8Js6tLtXTZT1+oMrM0jZWA+qEWZeWqm78Wf1lZbvHfU/B4P0rKxw0HwKnQeO+pmJ9YfajeOXePYtq6e2vBDgRRaD7alZarGt3dm4k7MEeGmrTK41esR2q4Y8Y00mif79Vbi4N4XWd0o1fLFWkpfD1ybyy+qV9caReU5g07Ss0eEvasj7gu422oHbXIz/eVHFa35RxT1o9R7frNWZtQjiMz/AN4b+2FudozlZLHvbypq4pQq7+u948tFz+9cy+aKHaBrW4FWhSqAfrNEq9j+8vrVnKagHWdFysPF6/8ALts/GbO3A8fUBWcZqPmcF6fVXGPS9n3j8I8MPIuvx7e+C8Hck+j053dQcf8A6l69r2efFfhz5mH33L/XBeHvnfiLaIH5KDA/tnlMPP7/ABrv6b/c5L+bJVkRPMAoB9Uu6Iuj61PxptUQfxFT2faulemzWVi60dmp/ZO+xVajOFO0z3v9k/7FTqhynu1fuxrmbdkfpP8AsavTcTqEWd+QCNNOg4ex1uF5V5i0a47aqn2NXa4vVk3QBHrW4mOZ7xv7gs5TvHPl4/iWT6f2R7PP03NUDpRPurUyVDjDvyThoP8A4Gn96q4IYuanjS+x7T9ylxgk2vDjGBbMb7i5Mv8AceuTtv8AfhiuSe9cP6yu4UQb5jZyWVR/uyqb8FlwfHIT4Y4+nUjI2qfsFdL4cZ25NVSx0s8Cz7l1rlv8r1CDhtOsfcAFxqbsDO7V2rmfwhcPnajcyf74Czb4awvy36nb/wDY7un4wz/dpqym4d9wE7+sJ/2z1TbkDgb8/K/s006bgH8GPR7forPWPxb33/f4MnGyfwzfZ/7zU/bK29ma2i+YwwA66tTPOe+A/wCZYeOn+W7/AP8AVVf2yocOrijd0XkmG1qTo8qjXfculm8Xlt+az8WxziezNOPjC7qtPiDTaujcPDuGBwnPCKu3L8XbrmOJHAYn4t79BpD9y213n8C0XR6p4U9sxz7qh+5Yz7f1d97rztU/jHeaQOYSquiq7nkoadiulfMzy7vUdnmB9tbMIEHvf+JSlc65Afxtx/SuS7P63+C6XZUlzbJm2av/ABKa5rDq4vQ2E1X5/vOXPC969OPfD+bqcGcHXNAzhz7sn21F5Bhmm3yC9bwAA17OTnVczz/pF5Fh9VvktTzT1H3UhldXhB0WPFH59W1aRHMio0/cVyGyuvwVs8N4qYz3Dh7BTqP/AORL4eXCbul/aGada/Y2RrvriPZcPI+1cYkkHJyuz2pMVav/AKq4PnNUn71wpMHPMLU792sMOiSfk0Xp/EWR/wBQf+I9HDf+0reNy8/sOVd06be08KJ/4j1LhJnidtPyh/Zcl8O0v8WfyZ7dwz429Qf7spUnBt1SPLvWftBQpHS2RzpEe9pH3qJMODujgfpRjfeRdxIxxC5/tn/tFZwVp4r/ANo3X9s/9orK05UZ5PvVeN6Q8fvQ/wDmSf6yG/GoDyn3lD80HH+uFY37X9+ypnxmn+sPtTvBNWqf9a77SotPrDpI+1TvY7yvHy5+0pHOd8b+/ZjO6QTO6TUY9mqv/MW5/wBUT9YovY9Jeep+5Fx/olsd/wAU79oqN9PpDunqn6oUrtye9+n9kb+p3l1Uqxh7y5UDJQ4k7pKON71ttXgWdemehPvLP/1Ubd4aWNn/ALzTPuP+KhR+JV/U/wCYKLDpId0e0/Srt2md+VK+zf3Q6V6n7RVTv5hn6zvtCtv/APT7r/1FT9oqt38wzwcfuUc8/v5fz/uif5h3gq649f2D7AraeaNXw0/ao3I/GR/Vb9ib7M3wzPEEhVvEZVtfFZ/gVWVms2IHZRhTKgs1lE9EokKRUThRFblF3JTO6gVlFaEIQIpJlJaYoKSaSIi7kolTdsoHZQJRUkiqK0nDZNKZQpOESFFymVBykYqJwJUVMqJWoEoFTSIEFKlRCYMjISTAhRAUlJIopKHMqaipQN3UjsoIJwpUNCTU1FCiVJEKUJCZCSihIppFAkIQgEoTTalVEpjZSUHY2U8hoSCaygQohxPJNxwinEhAEJMTRED8YoU1BFgTAkpIzyRQhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAEykgIQITCSihCEKBFJMpKAQhCAQhCml2EIQooQUIKBIQhA0IQgCkmUkHqtQWy+cDZ2kcg77VzGuWu4qarWiJnSDK+ta8OM0q1IBlV6s5KYPIK72zpZKDkZVYPMwBKZ8VrZpMFNp5qqcJknSJ5iU2aWB0onOVXKeocym00smOe2VJr8OzuFSXeKA71SQfBXYmXAIDvsVRcYgJEmTPuWeprS7XBmJjkk50k8lVOESTsnUaWT6qQlII1N5fYm10spOh4JUq7x3hVEjkUnn1iptZE9QS1CROFCcgJptdJSZQHFQ1RjdMFNqmHe9WMf6m6oBUwVdjSXDTuqXmTum8ifYqi7ogsDj7ky6eeVVr6ZQXYOUTSwuOyYcqpnYqbmlji10SN4KGlrHdVKmfFUAgKbXAFVY30KsNIlW311b1m2oo2dG0dTtm0qppvc70ioCZqu1fFcZEgYxhYG1D1US8Fc+l0mXZcXLXSqgsg8lzgVZScZVsWZar0XF7hr7wODiR3bfZhZLurrFATtTLY/vH96xPrFxBLthCKlXUGQdpUnl6OfnvLnllfd0eCuB4pbNdsarQfer+HnTQvgT/AEH/AORqwcKdp4jbOJgd6CtFo8hty2fjUiPrApa1x6uEn53+zs9siRxq5J39DsPZ+RUF568f+NAI/o2Z9i6/aS47/iNzUzm2s2x+ra0W/cuHemX0z1ptUw8Mcn3UpPoH/u/cp8NcPTGHxVLf9BP9p9ynw4/lVP8AWC3vs4yd46fDXfz0EfE+8Lp8IrEG60mJoPz7lzuGU8V4gRSk+xbOEx+VZ/7s930BZfU9NhlMsP5vNA+oPJAODsqySGt8ghrhMTErpb3fI12dnjNq+1tLB7iJr0e8HgFirOPolMc5Ku4rdGvRswY/FURTMc4G6xVKpNJrcYWO72ep6JyXo8dv7La9X1WADYbqvUIiVU6oTE8lHV6wSvPKvDxyJT1k9T7FVIKC+NysN7WTJUqbsuH9QqkEEYKTHnUf1TClal1Wq3eW6yJywwnxFwdcuIdiG+31QqKLvWMc2kfQo3b/AMeRvhv2BZ32d+v+H0okyokpEjqoFwU25bS1eCnTd+LqeQ+1VSpsP4up7PtU2uF7ok80p8CoyogklGdr6boa8Hm2PpUScqE9CouIxlRbltfRy/2H7FAHCLdwD8nkfsVRO3kjW+0X0z6x8inqjooWzXPqOA/QcfcCoSi26jtUXgcCaT/4g/YFis3Dvh+q4/VJWimf5CaP9efsCp4azU+uT/R0Hn2kEKvdlOrPCflGQHEexdfidQvo0yDINvSP01VxNe0rpXD9bGN6WzPsekceDL5cmEk6Pb9yTD6w80nH8WfP7lCk7126jzCjz7TLskJ6joHmqXkFxUi78WPMosvlKehS1KqcJh2NkRqt3RVYfFQa6QM8lXRd+Mb5qLTARd9nQtHgMqCc6T+w9W8PdFxTBj44+9YKLz68/on9lw+9X2L2NvaIqP0U+8Gp0TpHWOau3bHPVjVdVPXYf/KsH+6CzUX/AJTT/Xb9oRcu/GaQ6YotaDETFMCVRbvi5Z+u37VNrlnuxJ5Ot2eZSe8uidOwAhoH2faq3u9Z2eZUZKOVvdMFOVXKJV2m1gOVaTIkLPqU2uOgQm2pV7HHQ/wCdJ0VWfrD7VVTJ0P8h9oUmEhzSf0h9qu25fD0F1U/+YbJzT+Y2fnvXUuX6eEXjZyLasf96xcC6qH8MWxGNLWftOXVvqsWfEhMhtvA9r2FZe7jy+9fzYOIVdVa8k5cDP1VS2pNyHTvWafrhU3lSa1Xy/cq2O9dpnZ7T9YLVu3nyz3lH0CwqkcasyNu+aCPP0gLkcZqaeI27+Xods6P/ZYVs4dVDuNWzgZBqWxEeL64+9cbjj9N7RaXGW2Vq33UWj7lr8Po8W+n1ed/OvY9mq2qzsqswY4g7/f4XkOIuD30Wg59HaP969dvspXJ4TatBy0XIydya4K8/dYvWN3iiG+6o8/epL81e30+FnXlfe/5ZrtxIoknekI+cUqRmjWnkwfthRrmbe1P+q/5io0j+JrD+qP2gr5dMr/Ev79m3hTvxlfMTb1h9QrODkeat4QYq1Bknuav/DKzApvuv/GNdZs2FEnY1KrfqtW+/rGtb0qpImpbif8AaOH/ACrBWP8AJdE/69/7IUGVC60LZnSWgeAlx+9NN71f5fo28JeReR+kxw+ifuVvFXzw6ynlR+9ywcOeRes/UePqOV147XwqyJ3bTA+glZy+86YZfJ/VLjJi5bEZaf2iquHO/LKfL4w97SFLi5/GUzzh32z96p4a+b+j4vAW54cs7/G/oqaYZ/dXcrT39w7cG3uJ/wBof3Lz5d+KMfofcvSVWyLh4MRbVifCXuH3qfgcV3v9/ipou/kJ0yJNVv1GKo1McLM4Bn/euT1fyCx0j1qtQnrnSFjq1YpWLpw1rif9o5JOzVutVdx8/wAuX5H/AIqr+0Vjou01mH+sPtWjjjieM3x/8zUP1isbXEGehlbnh4+S6ydEE/gBkna5bP8Asit9d4HZ63YPzrWJ6zbs/cuUKn8kFs7XQ/4R/ctV88t4DYicuYxpHgbdqzlNu+OXvfwcmoZe4+KAdlW4ySTzQDj6EtfPteu7Hn1rGdgK/wC2xcmi+OK2cmfxoJ9ryfvW7spVFMUXO+Kzvtv1qX71ynE0+J0wcFtVu/mFnH3enDL5L9Y7nZ4H0iyAIH4y6nP+theTafVbG0L1nZ8xxGgJECvdAf8A9QF5E4AmFqea36j7iRO+V2ezg1W9+yASabwPP0W4XDJzuu12WqinVr6j+c2RHI0a7f8AmUyvZ5uP7yztM7V3bsQ5z3SOckFcMn1cdQujx1+q3ss705+gLk6luXs681+fs0XL/wAVbgEGKX/O5S4Sf5Utef40fslZXukN8Gx9J/eruFH+U7X+2apWZd5z+ShjhoH6o+xRe71HHwUafxG/qhFX+af+qVPZm/e22cTGq/uiNhUeT85ZBut3EDF7ficy79oLCcmFWuXtldfjWmy9a8t2GMvA+lM5tCf9YEuHD+UrUEx+Naphp9AfG2sJG+Obw/r/AGjIDknx+9W8QxVufCv/APsqHyGlaOID8Zcxzqgj6yrnhflrCgIIko0lTbntpu8WVoTt3b/2ioX/APPb/mt/YCnc/wDZ1r+rUH1lXeGagJ+TZ+wFHXPxfpP7MxTSKAYVc/ZfT+JU/U/5goExTd5hSpkd3V8Gj9oKmocFC+I08R/7RuT1rPP1iqXfzIz+efsCu4gP5QuP7Z32qj+jd+sPsUXO/Nf5pUc0q4/qA/WCjXH4yf6rfsU7YA07kdKU/WCjUE1I6tH2KJZ8srPXzVd+sqnjPkrXfzig/wCMfNRmq1F42UiMqKzWEeSR2TOyRUFbt1EqwqtyjCtwzKRTdukoeyKFYk7ZaYQQdkJIIlJOEiMIIpFTiAooIESoq1ReMIKgcpOThMozYrSiVIpIiCE4SVCOyQTdsohKhlRKkUlAIQhBFJTOygVNBFSbskmPirNEpAbEbqKJQgDskmgqUiJSUkKKihSUUAgoQgBhJ+8pqKimE0gms0oQhCIEIQgFBTUSEWEhCEUIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQghRSCaSaBJJlJZAhCYQCSkooBCELLQQUIQIoTSQNCEIApJlJB6A4yrC+aTRtEqgOGwwpAr6u3i0kmAeZUA4BMOnKJp0uz/FbngvFKPEbRlB9WlOltamHsMiMg7rE9xc4k5JJJjqqZjnlOT1V2aTPITskSSkTkFAQSGEyVEeaCT1TYYb4wgTKiXn+AgukJs0lyQXTvuoF3hhPSQwPIIaZgkbqLoyQN8J6lWTGyU+IRdL3ghrXEOAdJaesKsOIPmo6jESgoJgpuiZCqa5SlNiUpavcokEGDunEDfPRNhgqU4UI6p4HNNqkPFHMKMgo5wmxa5wkHKhqClBO2VAj2K7DTJgSlElNNiZaBSa/W0lxILeYiN/OfoQ0y5QdgJNPLZNixxym3JUOak2ME5VlFoMGEicqIOMpKbaTBU2PVMptKm1jVr8E+8WbUFIOgK2yK3WVT8ppGdnBaLSo7vnjqIWG0eBcMJ6hX0HkVneZWLXXC9nQvahearyclrAfY0D7liu3/zf9mFOq+adRZ7kzonk0KYtZXslrJtCAfzx9inYu03VMg7OB+lUAj0cxn1vuTtHRcM81rbnPMrt2twabamSC5hGPGVr4HVb+V9TaP8AuXF1w52StPCqxbVrgkQ6i4D3Kb2+hwc9nJjv225UnSz9UJAwol0ATyEIJnK2+a03L5YwdAqS6Rk+alVy1pH6KpJ8VFttW1YZVewPa8NcWh7fiuzuJzBUATKRBLHOGwifBVl+VVi/UB4qLjKhI5JTCy0upFnesFUvZTkanMEuA5kAkSVFrsTOesQqyUteIhYtGhjwDzRcGamr+qPsCqpmXDzUrgzB5wPsCztvfZE4MqDhJmVEmGlRDjMJtna7UBumw+pU8vvVBKmxw0OWWpdGXwkHBV6ilKM7Wz1UXGVCUFF2to/HCjKKImr7/sUQYCjXtF1B5DjB/NcPoUCTMqLHEE+SUou+zq0XTwP/AN8/YFHhjjovP7E/aoMd/IxG34/7gnw3NK8jlS+9V78ct54fT9GEnZdGyIrVtJmBQI9zSuXK6fBfWuN/zHfYkcPTd+SRkcZtz+t9yoYfXHmpz+If4VY+1VN+MFHG+YZPrJkxSbn84/YFAnKkTNJvmfsCJPctSNSgTCJKm6bWMMGUEqtrkydldm19N4BdPOR9CTHnW2TzVMqTDlNrtsrv/GnONDf2AqWVIqNPQgqt9SX55NA+qFWHQU2tvdbUJLjPVGpVl0pSmza3WOievwVRQE3Da9plMEjxVLXQpFx5ps210DNGt4MH2hRacieoStXfi64jen94VYdLlXTK9o6dzUJvqThvA+0rr8VeW2vEiMAuZTz+rTK8+Hk39HO7mj6V2OM1ZtLtgOTdt/4Q/cleziy3jnf34cuq/VVPjH2BNrsSeWVmDpJMwptOCN1dvHvu9pwKoHcWsZO/oR+u7/8AZc3tESOJj/01Ee5gCh2XuC/tBw1rjANe3p/NeIUe0r54mCNjQpfsreXt9Hn5Lv1OWX5/3d3sYZ4Wc5ZUePfVlcO4qTxFsk4D/bBcV2exWbCuBt37R73rzlxVHpZfy9Ye+f3rE7Wvr35eP+n9hXd+S2+2GkfYfvUaZIpVY/Rb+0Eqh/IqU8nOH1WpUjNCuf1B9YKuWX3+34fo3cGk3NXO1CqP925ZWuzEc1q4HmvWA+Rq/wDDcsDHAOmeivlr/hi33To4Rbxia9T7AqKDvxFX+79qdy8O4TagfLVf+VVUCO6qjwB+lXZnfm1+X6NXD3H0tniHD6pVtw+eGU4PxdA+oVl4c78tpjxP2EKdR88Mcemg/UcpfxdOLL5P6/o1cZJD6TvFw9wYfvWK2q93csqD81wP0rbxwjTRM47yp+zTXKBgGFZXHmuuTf0W1SG94BOA4L09R2m0vjn/AEZ301B+9eVujD6w6SvT3ZLbW9AxNuf22LNdOG/fYtQ/zfp52ruafcCufWf+IAH9Gx0e8lXud/IDcx+Vu/YCxOP5PcHpRJXTHwxnl3k/Jt427+V7sk71Sffn71iDyTlbOPY4tc/rN/YaucDJUebl+/W0PHoDmz/3kGP/AG3LbxIzwKwM/J/8ALn2ze8dTou/PrsHvx966HFgWcFs2ndpYD/sSPuRvG7wv0jjvcUAyYUD1QDCPJt6Hgr4sGwT61SvTEcj3bH/APKVhq1DWvqdTbvH0z7y1Pg9UsphoPxazngedJwVFN0NsHTvpn2OCa09M/23o+BO/lOgBibm4IH/APNN/evJP3I8V6bgLz+FaWdP5ZVb7TdsXlnOO+CVJ5dOe/JP37JExzW3g9fua1Zx5hh3/rQT7nFc6ZU6ToJO04P2qvHMtVt4o8vt7L+zdPseR9gWOB3AqdXlvtAn71O6fqtrPwbU/wCIVA/6Az+3fj+61X2d8vmyt/L/AArmVdw3HErX+1b9qzTnOFfYuHp9rHyzPtCjGF+afVSCQxsdE3N1McBuWlQmA3yC18O0uqVieVtVI8wwlXem8MerORbxQgcRv/13AfOWJgytnGccSvpz+Nd9LlhBhs9ApPC8l+e/W/3dV1FtDtDb0m7CvT+kBRpNnhlZw5Pcfc5v71bxIlvaumelxS+wIaI4TcjEa6oHhFSmEleuSdWU/PL+zlPEkj2K6sdVGo4762fY5UxNTdWvP5GT1c36NSs28PH7/S/2ZDupOaQ1jp+M2fpI+5ICcrRVj0e2MbsP7TllnGblpV88Ptv1qg+z96oujLm/2bB9UK+uf5MoeFxVH1WLI9xMT0hVvP8ASf2RKSEKsrqfxavi0faFU/4rvJSa4NY+eYj6VW/4jvEKeyWtXET+X3H9q77VT+bHUyrL7N9X/tCoFvqtPh96jWX3qusmwy5MzNs4+57VB8Cu2fAfQr7cCnQ1fpWtQn/atCrum6a7ZEEVS0+yFfZ0zw1hHPqfGKTlKrh5HiUniAD1UcKrKiVI9FErLmgVEqURKRWS1EqBOFNyrcVKxVbt0lI5KQQ2CYCHNkBHUqTgYBVRUhCEQkiZUoUIhAnbKKkVFAJOEhNCCkiBKirKmBKrRNaIpKSAEZV809PimkgiQS0qBEK3wUS2eaCHsQgiChEKE0IQBSITQgjCRUyouUETupSFEoG6yJIKEFAkimUisqSE4RCBIQhAIahMKVSQhxgoWUCEIQCEIQCEnOjkmgghCEaCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEICAOEHKDlAQCER4oUWFCITQoFsmlumEAoqSipVCEIWVCEIQByZSTRCAQhCAKSZSQdv2oJiAoAnSSeQla+K21O04hXtaV3b3jKTy1te3JNOoP0mlwBjzAX0up5FAI5JgxjkoNwPBPxEK7RMQTlMn2quVIEHefYVdiTTKmwCDJjGPFVNmdlIGBMgJtEgczAUnAfanWpVqFapRuKT6NWm4sfTe0tc1wMEEHIIPJRqnAKppU4x7EajCWCjHRTakDCmXktiTjYSohSa1zzDGku5AJsRJPVBOE4EYSnJ2VBPPdAdvKDuTzS3OyKnTDXVCHuDREymBpJURhMFQOcpzuVExyQoGXHn7UHKRCIHRUAMKTT1UYTbPNBdq9UGYKrJgoO0JN2QTY8sIe2AZkKTSH6nOcARnPM9FSTBUpxsimSISkAyFGSmm0icynKgECYUtaWtI05SmVFEwpKukpTBUCfBIGE2ulh+1TDoEKkulAKeRroOiq0+Kvov/ABzs5JKx0iZBVtFxNUz1UbjZVqRTdHOAq67pDfJRqOlhHiqqrjDfJTemr3TLiKeDicqVs6KzXYgHmqv6I45rbwLiNzwu/F1ZvYyt3b6UvpNeCx7S1wh0jIPmFbl27JjJubIud3jhJ3VlpU01HZj1SFnGlhIEwMZKlRID5HRTbXiqXHMbp0naKrHiJaZEiRhVjMkGVCVvbnru2VLqq59V5cAapJdpAAyZOBgexUAiVUXeKAcJuQqZcIUA4Sk49FGVLVi4FBKbO7Ns95qkVWvAFPQfWaQZM7YMY8VU52Vi5NJF3go6lGU1Ni6iTrHn9yLgwR+qPsVTHkPmVKucj9UKKhKUpSiUQ5Ta46SOqKNUU36+7p1IB9V7ZBkRt9PmoTAA6IJc1KoA1o8QqpUqhljZ6IolMGVWptLdER60zqnlG0Iiyg6Koxy+5QJHWEqZOuZUSYKi77JtPrJk9Aq5hyZKL7N9Nx/Bhby7/wC5X8JI7i9nnSH2rFTfNm4f6wH6CtPCT+KvP7P71Xu4b8+P0/SsLvjFdLgbgLqP6p+xcxxl62cIJF0c/mlZ93P091yxQSPR63hVH3qgHIVszbVv7Rv3rPOYVrlle8E5VjiO7b5n7lVG/mpvPqA9CVNsxDWVEmTKExEJsIYKscYaFEKTi00mHOqTq6eEKbCDiZTac9FFAU2JlwJlInMKJQrsSlHtUZQSmxL2qUhVB0mEyYTarWkFE5UOnirHtDYg7tB+hFjTaH8Xcf2R+0KkO9ZXWI1Urs9KE/SFmByrtvL7uLfaHXxC2B+WYPrBbuMvPdvzGq4Dv92uXw538o2v/qKf7QXS7QkB+kRGph/3as8vRxX+Dlfzc4EHZSa5UgwpNMhV5dux2aqx2i4VuB6dQB8jUar+PvBvaZ621E/VXK4fWNG+t6w/o61N/ucD9y18WqB96IPqikxnuJCu9xiz59vV9hHTY1unpdL9teSrP1PM+P2r1HYR59DrD/zNL9teSc7Y+1J5fU5rrix/l/ZqqO/k6nGPxzx9Vqc0xTuu6Dm09TdAe4F0asSRAlVF02FP+3f+y1Km6beuPBn7QRy3rL+X6OpwD49d3Pu6gP8AsnrlB23iul2fd6l2QMhjv+FUXILvVB8Ela5L/Dw/fu11ak2dCn0fUPv0pUHfi636o/aCzF5LRlWUXQyoMZb94VcpnvLf78NVk+Lqk4ERrH7lIO1WFVonGkH2Ej71lo1SCxoDYFTVOnPv6eC0NIbQuWg+tn/iNV26ceep/X+zfxok0aPTvKh+qz9y5ZdAK6HGT+T0iPlXj3hv7lyXOJByonqe3Jpp4g78dc+Gr7F6S9cDYXLpj8mOP71NeYvzNWuOZ1fYvQ3z/wCRalQEQ+m0D292fuR04P8An+/xc57v5FpNP5128+5g/esmo9xdD/y71N7j+DrcTjvqp+hn71Uwg0Loj5B32hal7ONy7z6NvHHF3E67vFv7DVhJAWvjJ/L3u6x+y1c9zpTbnzffrbw1xPEbMf8AmaX/ABGrq9oRHD7cdKrf+G5cfhp/lOy/9VR/4jV2O0R/k2j4VmfTTf8AuWL96Lx/7eX8nALo5KOrwUXmSkt7eZ0uEkl9SD+YSPcVCkSafDROHOgfPCu4A2Rd1Sf5umCPaHBZ7f8AmeFmOYOf7RXfZ6J2wl+v947XBakcUoknA4g8/wD1bV5xpls55/auvwmp/KFLMH01xx/6sLiBx0ckObLeE/ftEy4IDoVWrqguR49ralSaVEA/E1j3uJT1k0NOPjl30R9yo1NTlVr4lSccK2zMXtuT8qz7Qs+pToP/ACilE/zjftU7rhlrKEIc1vktVgYqVGjnb1x/unfuWNrvUb5LVYuBvKbZjU2o3303BTz2d+HL+Lj9U7+qK13XqcnvBHtJKzGO7d+qkHaqTHdWj7Ep9R36pT8nO59V27HGXBvaLWeVWkfoarao08NuxEBtxXH+/aPuWXtA8fhEVQRllF8+bWlar0gWnE2CPVu6v015+5PZ9C3WfJPzv9q5LM1HeDHH6CtLmB3D6buur6NR+5ZaJJqvE7UXn6pW8D+TbfbLXke6oFXn4fu36frHL5BaamLK1P8AVP7T1kk4ytlf/s21P9Uif7z1lz452y+iurnhVM9Lqp+xTWMrU94/BQaNxdu+mmz9yxkkbKxc7uy/kaFHUeqkMrVY2kWnu9XjCjyVn/dgf9Z9yrULdLKztVV7v0jP0JvxTp+LT9pVQBO2VJx1MaP0Z+2VDfna1lQihWE4bbuA9tRhWnigi8eDyuqn/KsIcRQuR1oOH1mLbxZ35XWP/mXn6Gqx2l3g5twIrPH9YpPP4to5iZVvEQBe1o5OVDjJWXDLtlYgoOVhHqA9TCiRCjHhWcqKmRCgdllm1F26qdsrHEzuq4Rio/nJRkwpoCiIhuYlWVRGnoWyouV1Vs91/ZBVWQ7pKT1FEMbpVBDoTCsumaHgHeEXTOVAqZCi5EJCEIIVRhVK8iVU8AbIliKAhMBGKjAUYUyMpIpBI4UuSQnmggQoHBV0BLSFUVIUyADsomVAkIyhAgk7dMoAlQRUVMpKAacppJqAKSaFAkIQoqKEykgEwkhAoSBTO6FKpoQhZQIQhAiAd00KOooHCipnZQRYEIQihCEIBCEIBCEIBCEIBCEIBCEIBCEIBCEIBBQhAbISTUUgUJIWQ0BCYVgEkFJSrAhCFlQhCEAhCEAgoQUCKEIQddpT1erCgDgKQXujy6SB2UiZMJPc59R1R5lzjJMKIHuVlRIGVMBQOqcbJyBC2iZRgc5SzzRzVFr6j6j3Pe5z3OJLnOMkk8yovmBjkk07qwFrXtcWh4DpLSSA4DlhBSducJu23CsrOa+vUeymKbXPJawHDQTgCeiq57IEExIMypkDTM56JAoI5QZmNlY8UzTpluqdPrztMnbwiPpVZGUE2ua0klocdJGeR6qGyBPNWUBSNemK7nNpF4FRzRJDZyQOZhFV8k/4hTqBoJDCS2SASIJE4MJaHaNWl2mYmMT0RDawljnSPVjBOVFIyITGMjKKlGJhKFN1QlgZGGqEKgeMYS803EnfZEQUDxEKJ+9WOqF1JlMgerMernPiqypsA3SEzHipggIZEyRITaxE7JZ6qcZmN1FwhTewBPKEwTyMK2rpJLZMbb5SAkSsVopTBQlyKwqSEg4xEpjZVE2GXLQGlr8iFlaY9iuZULnSXEpWoud8UqpxkSp1HerA5qvBG6RqpzFH2qFF5FQJyO7jxUWkk5TY0PdEyd0rd8GSoVNx5KNJ2T5Ivuupx3VSTEfSqCYUgSGOVRViVIulKZSUSYcVazamkVAuPLCRJO5TarQcoByVGl8ZIfGKzSJ6kAwopSo0kCm8yfYoShxwgZKUpAygmEDnKJSkKLiJQWJ1DDW+SraepUnkd2JRSBlBMKEpIm19IyVEkyihOoIcQHHfdT3X2BOE58CoSFIn1Sou17HRbvHVwWrhbop3Yj+j+9YWH1IPmtVg6G1x1p4Tb0cOXzxlcfXWrhdQC5IJ/NKxVPjLRw4gXBP9UonFfniP9BWjm9v3rOrSfxVQf1m/eqTPNS1zpyTupzDBHUqsKx7mmkwBsETJn42d1khESwHmoFWExTCgIB33UtSmEyT3bfMqL8Qm8/i2+1IsRBRsklsibTBQHKITERum12lKiUY6pSmxIFNRT9m6ShgzhWudlv6oVKk7MeQVWNtgfxF9/Yf8wWUHEq6xd+KvBzNA/tBZw7Cu2878mP8ANpsXRfWxj+np/tBdXtN6t7Ub0cwf7sLj2Rm8to37+n+0F1+1RnitbpqafqBWV6OP/wC2y+rkgqTXQqpTBVjyNFN41tJ5GVqvHh1wXAzgR7ysDXBW65dvyAV2vu9p2HIFjV9b/vNL9sLyTXHS3O4Xpuxbo4dWJO1VhHsevKU3/i2ddITb6HqP9nD9+zbqHoTBP9M8/VaiiR3NbIn1Y+cFm1zR0zs8n3gfuQ10NcOsfatPPc+8+n6O52eM07yDHqH/AIdVcWfijwXX7Omad5B/MP8Awqq4rTj2K7dOS/wsP5/3TTDoUJROVeqPNtcx2R5hbSS59ZjC0Oe4sGpwAyeZ5Bc9m4K0PdNSodpcftUdsMna7QUzStNBLXFl2WS1wcD+KadxgjO64U7rs8edqszkYvBt/YNXEJlZnhv1V/iNFw4GvUPKT9i7146OzNMzGWN+q0rzbyJdHT7l3eIP/wDleyB3c8fRTaq1wZanJ9HLe78koiY9eoffp/cnTI9Huef4h2PaFQXTTY3oSVNj4o1xP9C77WrUrh1bs+n6NvFz+VT4Z9zFh1LZxgAXDSDuyd/6lIrnyptfUffrZw938o2e/wDpVHb+0auz2lxw5gkn8dS/Yq/uXB4c7+ULMdLqj/xGrudpXh3D9MyW3NNv1Kyl8xrin8LJ55xkpDcqLnRgJajMla28ddvs84C04rkCLYH6T+9YWOLbfhZODk/76Fo4C/8AEcVb/wCTH7YH3rLWd+I4aScCk0/75x+5WPVlf4WP0v8AeNFk8t4izOfTc/8A9T/gucTDequ7wi8dkgNuHGR/akqmvU7yq5/d06YMAMpiAIEfTv5q7ebPLeOilRKRI5EFLV4LTkkU1XrbzKTnCCmkWNIP+KlRcG3DJcDDh9qyaipNcQZ6K2J1LS/TAg7Ky2raLinUP5s/SCFkLpjMo1CE6Sclxu40MqEU2tzgQrNXquxyWTXnCmHGU6TqdXjjwX0njnbUT7mgLZxKrA4m0/n3ZI/2jiuXxR34m3O/5Iz6BH3K/iri6veAO/70T57lZ12e7Pl1lnfx/wAVVamK1Qnbuan2Lbn8G2RBiWOJ/wB6udbOGuuTMC3fHmS0feug8xwe1diW2tM+Zf3w+5TWjgu8b9P1jmFa7gzwq38Hx9L1inoVsqmeDUj/AK6Pocozw3cy+jIXfiHNj+lDvqx9yrCmTNI+Y+9VMIG6Oe00ijUOqJHNUWtk2zQASTXIA6nSq1rsoc+yE/8A8QYPeGrI747v1j9qlbynyyrbUS6oP9U/7FQDhXWX85UH+pqfsqkIl+7Ez/NVB+kwt+kfuWi/druav9oT9AWY/wA37VbdfztY/wBf7gq1vWKN/wD6ZV/WWZ608RxcuPUA+8LMSFmscn3qB8Vv6yrMwVaMskD88fZ/gqj8UozfCJUCpnDc9VUcklYrnai74yiU3ESolECEIREXc1rbkUZ501mOy00j6lA+BCLGOod/NVq5wglRAA3QR0wJWniAlwd/VCrILmwFZcSaDHEbiEWXtWIhRcpnZVoxboihNRx1ROoO2lVqbshRhEtR5KKkRCRRD5IShNDRJKSEECiFOELO+6yIKOlWqLmmJTa6Vu+KotxMqTTJhOoIb7U2mlblEqUKJRKNwoqQ2USEAmkhoUoaE0kAkmohSkNIppFRSQmUkAgICeodVKpIQJPJCygQhCAQhCAOyggzzCEWBCEIoQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCBBNIIJlRTSKPbEJlSiKYQUBQMqKZSUqwIQhRQhCEAkmkgaChBQJCEIOtz8ED2px4o5L2vN5MZymSdOmecqI2lTxGQrGSz1UsylALfFPktwSTHmo9MqQ81UEbq2aQty0sqGtrbocHDSGwdQIiSZ0wZEQcGcRqNY1lMsqay5suERpMnH3+1RnwQIzKAMqRMhR5oGBOFfYUqNa9t6NxcNtaD6rW1axYXikwkBzy0ZMCTA3hUsCkd8J7DVxy3sbTi15a8Nv/AMI2NG4fTt7zuTS9IpgwH6Dls9CsUSU3ZTMc1YCMifeokEFarFlq65psvalWnbk/jH0m6ntHgCRKoIzCCONiFZ3j+57rW7u9WsMnExEx5KLmwYQEQgJTGRG6tayibZz+9f32sBtMNwWwZM+GMeKQcGgjSCYEHmEXyqjKMYUkRKuxEFWU6bqgcRphokyYwkxgJyYwmRpaTPuUJVcAbFE+CZyfFSZTc4EtaSAJMCYCLtADrsmdIcQDI5FPGQkVVaqF46lYXFp3VN3fxL3D1mwZwVjfkoOfFBWbDYA5pndNh08gcIjMrKrHaxSZLIDiS10bhRDZaSXNERgnJUZMxKCFKsLmluU4wp0WB1QNPMqdmorITGydQAPICiN1NtfVbHqAEb5BTp4duq5OAeQU2ukgQhFj3HdXXl7dXbLdletrbbURQojQBpYCSBgZyTk5WYwZEpbIt2lyTBgqIMhSpMNSoGAtBPUwEOyR+1Lmg4bPRQBkSipT6pVZUnfFKr2RnI0zukChXbOje0tMEifAqMoSTazUTpmHI/PdKVP4yJyo1DJhLV4J9ZBwJKi7dFBcYhEk8lCU0TYKRKCiENmCOaCUoRCBqx4lrWqtTqGBhSkR0n2JFbBUsRwd9N1vcniBuGllUVB3TaOky0t31F2Z6LEclNrYtoGCk/4xRR+NChU+Oc81nfdfY1IiQoalJrxqEiUpEgSI8FpsXZq/qFZS7wV9mYdU/UUldeK6zilxzsr7J0V/YVmcIKusyBWz0Ke5h96IE+o4dSPvUE3fneajKzUoTJ9QKJKk8+oAokMn8WPNRlNx9Ro81FPAnV/N/VCR+KPNDzMHwSLvUGNpVLe5FChr8Ea/BZ2JoChr8FIGQScQrsSlJa+K8OueGV6NG6FLXWoMuGinUDoY8S2Y2MclkQMKWokAEkgCBnZRlJF2mcpbBKUSncabMw24zk0T9oVJwVO22r/2R+5QGcLS5X5YvsP9NtfCvT/bC6XaY6uLVB0DP2Audw4E8QtY3FxTP1gtfaN38q1SObGfshXb04XXpsvrGCZRKgFKVZXl2mFMHoqg4THVTbuqPWdl6mjgNy/o8H/eBeZYRob4CF6DgT9HZW/ePzRP+8H715xrhloIkbqx7/U3+Hx/RYCCcFTBVQdCerwVeN3OzzvxN7mPUP8Awqq48mB5LqdnnTRvv7P/APHVXJ2jyR6eW/wsP5/3SlPUOqghHmXU3A7K6q6HVT4uWWmc+0Kyu7+ePg770dJdR3ONOm0dsPywf8Bq4zTBXS4q+bV4J/72P+AxciVZ4b9RfnXSu1xQkdmOFDmTP+7YuCDmV2+MGOznCG/1f+Rim2uG/Jn9P1cqcBNp/nR1pkfYqC7ZNpiT4FWPPLp1OKuzTJxLBn/26K5+/gtnFXyaQ/1YPvp0lgLsqyx15rvOtNg+L+1O35RSP1wu12icPRawHK8pg/7OquBaH8ttf/UUv2wuvx93qXOf++sH1KqTy3x3+Fk48zlCryOaJPVHjdTgri1vEXAgfkf/AORqzVye4tBO1ER/tHlT4WfxXEf/AERP12Km6MULPMTbNP1nqyutv8Ofv3Rq1JqvcP0yR71S9wJQ8zlVqzTzWpFBeBiDhRJ6JTlaQyRkyDnadkiU6lVz2U6TnktpghogCATqOeeTz2UC4bBam0OUkgUOMQtMAnOEktSWpETk8irGGSqNfgphxRGy7c51vbjrbgCfMqd1WL7iq4GQ9+oe5VXjmllqxhEttmh3gZOFn1mUduW6ysarV511f7F37TV1rl0cBtuptLb9u5XDtnxrMxLCPpH7luu6/wDJtlTB3s6P0VK3/wCyxk7+nz1jl9P1ZtS2uP8AIdKf/Efc5c7VK26ieBAbxctj5rlmnDfvfSs2r1C2N1WhyJWe7MoQgoCK3WGHWnhxCmf2VlqGHuH9Y/arrQxUtv8A1tM/YqHes93mlbt+VbaGHVY+RqfsqrmrbbDqg/1FT9kqkc0TK/LFrmzbtd1qFv0BWXg/G1xv+MKQ/wBAZj/vDvsap3MGpcu/rz9JWm7Pl/p/ZHieK7XQc0mH6oWT8wHxK2cRz6OetvT+wj7lkP8AMNP9d33LNZ5ZrOil8R/gWn7VD1Jfq1berHXxU6Xxah8B9oVTtj5qOV8IPIIVJ2VkeqSq3GJClYQdukmVEqICQjUFFAEoLGCXQtLMW1IjqVmpmKrZWkmLe28XkfSqsZqol581E/epv+OUR6qaQ8QIKlVcH2TST8VxCW6gQBaV5PxXNPvKewoqEERKqPnKbjJlIK6ZtAEp6TvGEpV1B9MUy15g8lNJ4ZnZKUeCseJeTyQUh7KjlLTPNWOCjBG6aRWUwmRlMt6KGihLT4qSFKsiJwISU1HSo0SDlMjwSWRAMgzOyVb4o81ND2y3KChKFOoAIhRAlWJUSkWlSdkpEqso6Sm1EoCVKCkmUlCBJNB2UUkIQooSjKcwglBFKCmjV4JVSSKCYSJWQIQhRAowpIQKQVFNwhJFCEIRQhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCECClCiFNSLbpFCEKAKAhIlAFJCFmrAhCFFCEIQBRCIRKAQUIKBIQhB2oCWnxV5YJ2R3Y8F9HoePqUQRsmAS2FcKYUtB9iTE2o0nxUgtDPVY9ga06oBJbtzx0Q63c2m2odMO2zlXSWqB0gQhWFuMBGg4lXRtEDHVKMK4hxABzGyiWqatNoQUNHVWsY550tbJJxAUu6jcQZytaNqwOibWkq3u290fjd5q9mmPtUqcsLXAgEEHIkYPMJpNtNHgvEKvBL3jTKE2FlWpUbiq57W6H1NWgaSdRnS7IBAjK5zgZIPJdzj3EbztP2jq8QrW1sy6uYa2lb0hTY2BADR4x9K5D2EY5pIu4qDYUmgkHmpNbmBsraDhTdqABxzV0bZiJ/6IiFaWiTG6jp6qaCaN0KbWnKNBTQjGCOiA0nYbqwNExKC0tMTtzCCFRhY4tcYIMGFAjxKsOZnmkAoulcKTXPbOhzhIgwdwrKrGCCMyqzE4REUzGjxUmAE52ScMqruqwIHtRzTIKFF2bHAPDi0OA3HVTdBcSABOQOirGN1dUc1x9QaRp28VPK7VY3PVDoB9UkjxUSiDKxWomwNLHlztJAlojdNh0vBCiUMILt9lloP9Z5JSgKWS4gc0nyJCCPNSGCoJhxCHhY1jnHS1pcd4CigE8k2tLnBrRJ5KNlyT3cZCk2lUe2o5jS4UxqdHISoJtFjj6irDoTnEckh7FS0akjB3QfJJCzYG8ImEIQ0JTEc1FBOENLGzOBKBv/ABKi0mY2U6VGrWe9tGm95a1z3Bo2a0ST5ABZ2rsXXEeEv7K2vDaPCGUuJU65qV76Qe9b68DaRhzQRt6oK4b903YONlEmSs4yY+G+TkuethEYlKUSt7YBRKRyYJQ4DkUtDlEqOyJU2mzUtRUEKG0yTjJ6pEqJMoKLKspO9ZRefXPmnSPrKLz6xUaKUwcqEqTRJ35JaibcnJAwraJgmDygqjZWUTJIJ5LMbl1SeZcVOg6KmdlAObrJcA7BETHtTpn18IsuqD8Vx5qvUpE7qCiVLmmfiNKgN5UnH1QITaG8+qPNQOlMn1QopV2nqBA8EHLQCoFWEwwiAsispITCoSkHEeSRSQWCAZASdnnylQCEom10mFJVt3TecptU0FJpkSpBNi22/pc/0R+5RELXw2pa0qN424tTXqVaBZQcKpZ3L5nUQPjCJwsg2lW+Gr4jRwuDxWy8bimPrBWcZeX8Qc45ljD9UKnhX/atmelxT/aCLwl1ZrutNn7IVdZl/As/OKUxtKTnCfVBjxSBVcFgqPFJ1IOIpuc1zm9SJg9cSU2uVYUmQXNnbUB9KK9Hwx+jsdxLOdQH++Z+9cR1V7mU6bnamU9WgQBGoyc7nbmutZuA7KcQbz78t/3tNcQnK1t6vUXthPyTlAKhKAVrbzbdzs64dzfDrS//AB1VyNU5K6XZ90MvM47s/wDCqrlyrt6OTL+Hh/P+6YMIDiEg/SCfV2IyJUSYRx2vY7KKr/UeTzaVQCnUd+Kd+qfsRN9nY4m/8VVaN/S//wALFzdQWjiVQ99XZM/j9X+7YFhlTw682W8mhrgV2uNv/kHgg60S76jF55pXc427+Q+A4/7r/wArE8tcN+TP6T+7lapRrjHgVUTnogmAT4KuDp8ScJpjeKbP+FTWIEEq3iDvyiBsKNL/AITVknxRvku862Wh/LLbP/eKX7YXV4++XXzRMNvmDP6lRcS0cfTLY/6+n+2F0+PPPpPEpP8A/EG/s1ArK3hf4WX1n9q5ernCkCqdQITBjmo8roWFQNo8R/8ARH/iMWatU1UrcSZZS0H5zj96dq8No3087cD67VSXLUreWXySfvybnQFEv8FFzsKJMquKwlRLiDChMIlamUD1JJiOahK3MomkmnKbiCoSgJ1JpJKEBAIWtys6JMGEIREnPJSBPNQKYQXtdC0V3fk1kOlq37SViBgrRVdNC0/9O371K64XUpStLKgHC6tPpcUyPmuWHUVbTcO6qN/Sc0+6f3rNjeGfTb+aUolVzyhDDJUsZ2sJTlQ1BNZq7bbcBtXh5/SrteR5PIH2LPMCd8SrbZ0VuHE/m5/3rllHxG+SV1zsk1+/EX0HjW/xpPH1SqgcpUjDj+qR9CU+so529mtpi0pg/LuP1WqdQyyv4hjveSqKh/JmAnao8/VCvr4Fbl+TUCt2O1u/6T+yN1U10KG0sphh8wXfvVLx+R6oyKv3JPI7v2oEmyqCf6Zo+qVjyzcuq7RomRW8GD9oKt3xXeAn6VZa57/+xJ9xCgwaqVY9KU/WCVz12iofzblQ4yT5q/8AMf4BZ9yfNRgFRIlMlJ2Gk+CmgiBCQ3VZcTzRqPVWYm1oMOHVaq7osqBG4eYWKmTrytdz/oVDzKuu4qcZcSmzFMnxVRcVcwAW581bEl2anTj0W8pkAyKbvcSk0SyVCRNUYALBHjlYrUY6hDiIEAKKdTeFFajBoQhLdISZKFWTlZNJgyjSSk3mm10Gd0908DQ6JhCuZVafVe6AoVtBaIWrOyb7qeRSUgkVzvluEhCk0AjKioqJGVewNByoVdJcS0Y6LNogRhRIhSKSkEXNlVPEK8qBEyFRQd0lZpA5Ks4WmEeSAUIKBgygpNTKie5IKEIpITISWVCRTSKBIQhAigpuCUKbUAppR0QFA0IQogSgJpOOEUnCEuUpgpOyihCEIBCEIBCEIBCEIBCEIBCEIBCEIBCEIBCEIEFKUkKKEJFBU2CUkIUAhCFGoEIQoBCEIBJNJA0FCECQgoQetNKBsgUiOW67jrCThqXoJ6fQv0PwY+P8RwzS5kJmmIADdh712XWJ5CT4hM2cNmD4p8GHxXFFPMgYSNMxsuv6G6I08kvQjzB8FPgr8VyXUnbj/oo90ekea7PorgCDJlQ9Dd0hPgnxXKNMg7SmaZ35LqC0PQq2hYhziCHEdAp8E+I5HdnVACkKepd4cPaKgBP0KFSx0PMjyT4R8Ri4PwXiXGLwWPC7KteXJY6oKVFupxa1pc4x4AE+xY3UtJiIC7NJlWhVFSi99N4mHNJBHXI8FTXtyfW2PgFPhE5HKcw+1Is65W51AjP3JtoEkTpErPwq18Rz+76fQp3DjVLSWNbpYG+qImBGfFbn25a84HsVT6DxhzSB4qfDq/EjCGqTW9QtJpu6IFIzup8OxrrjNol3mrKduXEiR7eau7qBMlNrXYLcqdFOuMZZkjKNEDoujSthUJJdpwtljf1bCxvbZlChUbeUwx7qjJczxaeRS4Ume3A0lGla6bWGoNQwovpg1DpGCVmxuZKm0w5hcTkKrSAZWl7dOADKrcz1o26rOl6lJHuSIx1WhoAORKdzocQKbA0famjbI4dEmCFaWGQpUqep4GRKmqu4oc1SaBp8V3m9nbh1ky71s0PHqz16HouNUpmm8sO4wR4q3GwmcqiFF5OkN5b7K18zAMKLmmPJcrG1Q85TynG5Q4yAIGPBZalAbqeGlwbPMnAQ8Q6NQMHfqkRKNB0k4wouzdp0DSTqkz08IUEbIWWh5FSOMSFA5SzzTS7WApEpAoUE4MSogc5XT4Q7gvcuHExdmpr9XuiNOmPtlcyoWydE6ZMTvC1vRYc9SkNlGCpBZtUSpu0GmIDtc5ziEOcXhlPS0aREgQT5qNRpY0Ex702IoSlJTYk0+sg5J3nwSG4Q1xa4kGCgCZKXNE+KJTYQI6JqMoTabMboKAgkRKbAhA8F6LsL2R4p2w4lXseFvtmPo0e9qPrv0tAmABzJJMJO6Xs86ouytvFbGtw7id1w+40d9a1n0amkyNTSQYPmFjKUn4kgFCFGomx7Q1wLZJ2M7KBySUc0IoTbuoFEqbHbsvwGOA3brt7/AMIgxRbkDlG2Ou65dI7kqiZU6ZiU21bvSTkmH1kn5PgoxlRNrg1zidIJjJgKIgHInwRTcQTBIkQfFWXdA0KpYajH4BBYZCCHqlu7tc+yFHkMpE4wk6eZUqng7FBgIYG6ecyk7kpsPlKD0UEJsSbHIqSrQmxMpQmDKabAlCaE2IoQgqtBSp81FCDRRMPcf6rvsKH/AM3T9v2qND879R32JuP4pnm77lrZvstsnBl9bOOzazD9YIrn1qcmfxTPsVTHaajHdHAqVT8yfk2qRqX5LCdyUUSOqJSMpAq5j31K9EPe58OYxsmYaCIHsVLTC2cKtK95c/k9MvFACvVyBpptcJdk53GBJV2uPfKNzXxwHjNMna9AHjLgf+VcgnbC3GpFnxVhO920583rnklXbry3fTPy/WgGFOfBVyeqAfFXbk6fDqxpUa5BjUNPvp1B96w6sKwipSt/XaRrexzZG4h0FZgJWmsruSL2VHsqNex0OaZBiVEYAG8KuCkRCMrgUOd+Ld+qVUCRsmDIIQbb583dUzIJafqgKhKo8OeTO8fYAo6upSrle6wc12eNvB4L2fb1sdX7I+5cu2ptqUK7zvS0R7SR9yv4hX7zhfBW/J2JbHlUePuVjrhvHDLfvP1ZmwSZMQCVB59R3ko0nZMn80/Yh2QR4I4b3GziLvypw/qUx/u2rNKK9Q1Krn9Y+gAfcq5PRNrllu2r6LtNxQPStTP1wurx959P4qwxjiH31FxO80Fr8eq9pPsIXS47VB4txXM6r0uHiJd/+yvs6S/w79f0rChQlGpRxXU6mhlUR8dmn6QfuUA4qGrEpSE2lqwu8FGVEmEE+Cu2UpTUDnkperoDi719RbpjlAMz5yI8FdgJRPgoE5wIQ3CbEkpQEStSmgSmCoGUQtbZqyUlFEqymkkwogk7EJgynUmkuR6hW16ge2kB+bTDVSEtSvUs7JFAMHmlKJU2LNXglPRVhCba2slSLvV2VYKalGvVpbavG7af/O8queSKp00aOdqf/M4qsk7qTu1lVkonBPQKuTCQd4JZqo23QikRyDiPbAWi6yKx/wDJ2/2hZ7wfk7nf67/lCuuHHTVxGqyo/Q4K+zrL5/f4sn5h8wp082Vb+3p/Y4KsH1SFZb+ta1qY+MXtcB5BxWYzh50LQDv69Pn6PV+gSoW4mjd+FvP1mrQGBvFrlg+SrgfMcs9tHdXgPO2/52rWmta1/NT+bU8gs53Wqk2W1+opk/SsjslZ043t3Uv+MUgVKpuoFKzskIQDCInS5rZXH8mW5594+ViDpWqq6eHUmzkVDhX3WVnC0MH5I49DCz7haW44Zq61CFqmPudvlh8lncZMyNlfZ7O/VKyVCQCs5RZeyp5yhBzlJRk1FCCgiTKScIhY0pHCEQhGQ4HBUhndI/FKSNRImEkBMI1oBNCFBNolpKiU1FYogU2CSgmU2O0yVFVuBDjKSm8y4qIRlTUadZKiRgq4jKpqD1ieSsRXB6JZ6KSFpkggp/mlRUqBCEIpITOySihIppFQJCEIAJO5IJwksyKYQEs9E2q0NCELKBRBlSOygiwJwhpA3T1DqgQCCIT1Dqk4oEhCEUJkQkhAIQdyhAIQhAIQhAIQhAIQhAIQhAISTUVFClpSIhZ0EhSSKaCQhCy0EIQgEIQgRQmhAIQhAIKCkg+4eit3AA8kNtmRkkwr4ccAeGN1MYIbO88iIwV+i3Xx9RG/4M+zNAVnUC6tRbWZ3T2vGl0xJBwcGWmCFkdZMn4gnkOa3aTmNgJOPuUQHaSB+bjCTKnTGL0NmwaJ8kvQW8wJ2wOa6DRJMH2qRbgO2Pkr1J0uZ6A09PsUXWA3gfeF045kqUH1Z9nir1M3FyW8P1bCVopcODRMY8srezn06hWMI0kcletOlltLOk+6otrerSL2io4ZIbIk+wL33wmdmOyfDbGieFVW1a9QCe6fqEafjExicY8TjC8WDDp2P2qx1Vzmd2T6rTIk7LOW7ZZSTtZp56vYFrgSJGRhRu6da5LDWlxpsFNp/qjAC7dWlqBk6tO0dfFQfQGdhBwum4xqvMutfXyCRyWi8s7NlOh6I64LzSBuO9a0BtSTIZBMtjTkwZJwu262B1GNsJG0YcwBOAE7U7vN+jEfGbHVOrTfUHrS6AAJ8F3zZifinaVE2TciCtWRN1502hJJj6EjauH5ueeF6ccPaQRpyOREqY4eP0BvgKai9VeVNpLXEggyqfR4OxXsHWTSDDRCw1eHQ4lgxyTph1VwO5IBwqjRJO2F3/QXTOnA5JHh5j4vmp0RZnXm3W7gT9ygaLp5r0LuHmMDqVA2LoPq7brN4Ys5dOA6nmchNlP1tj4LruszPxD7lH0UgyQFn4Mb+K5VW2cDIaY3lUmmZy0rv1GnToIWR9DMwQFm8ManK5BZqOSVoFCkylRqMrB1UuOunpI0ARGec526Lb6MwA481QaDhMCFj4WmpybXuvbijaBrK003AgNmYPXwXHqAueTJJ5krd3DiI5DZUuoEGOSmWFXHOMbmyei32XCKl1btqh4aHGOseaqfSMSBlDX1KYPd1HMn9EwuV43XrjFXp93VcydWkkSFDS0tJJIOIELS6m4ieSrNMBc7hW5kzn1ZRutVG1r1y4UaL6pa0vcGtkho3PkqQwjrlY6WpkoLYKt0UTQkOf305Eerp/epVGhxkgDHJVkeCzca3MlUQUFWEKVRjA71CSI5rNiyqFIuljW6WjTORufNMtPJAbCml2I9UFQW+jYXVWaVFveFtI1i1pn1QMrEQeiWEpao5FDTJwrHUmig14qtLy4ju4yAOaqbhZsa2kXQlqnmnULXBpaIxBVbjHJTQklq8Eg+eSIxKndUmGXJPMEp02mSeQSe0GT7VBHV4JSm4RHiFFE0cqbI1etMc4VaabNJOiUiVFJNmkgYXV7Pce4x2fvH3vBOI17C4qUnUXVKREuY7cGfILkBMJLos2tqPc+o6o57nvcS5znZJJ5lVucTDTsFFOU2aEptzKiEwYKm2jSO6k52oyo81LQRKZaBTLy5uCBHNJBCmwAKbSQ0+PUKIQSDsrKCeSk9zqh1EyVEK2jp1evMRyV2K4hBJMrr8F7PcZ433p4Twy5vRREvNFk6R4/uXNq0nUnuY9rmuaSC1wgg9CFrSTKVS1NxgI80Fc7GtltzSQVGVDaRTx1UUKbVLHVGOqQGYRCuwIQphon1iQOcIIKxQKSeBIIST1HoFeqLsFKUJKbotpYLv1D9ik934tuPznfciiGaKrnvLXBnqNDZ1kkAieWJM+Cg/wDm2/rO+5aUw4OOJVjnSGzMgRuqQYKZdPJBNtQtkCcqOqepUSSUkRcNlZbH8po4Eiqw7f1gs2p3VXsDqddge1zHNe2Q4QRkKtY3VlXV3nvbtk/HrF3ucf3rPzUrl03FUj9N32qrV4K7MrupoUQmm0WsMUiP6wP0KEoD4bHiopsSlNQCYV2bSSlJEq9RtJOTzUJQDlN0dPhRDqN4wx6zaf0Fyz1Xh1nYsG9Oi9h/2rz96XD6hZUeP0m/ZP71QXEMa3eB9uVY65Zfw5P352m3ElEyZVYQq4p6gnIVaEVN+WFvVaL2qat1Xq5/GVC/3rK3fKuuH0TSod0xzX93FYudIc/U6COg0lojqE2m/ZDV1RPl71WhBOUT4qCM9USxZKAZVeeqckc1UTkdUiROFEGRJKc+KIkESokhKR1VE5QFCcpoJhAKiCnOECOTg+xAnzUmvADhpa6REnl4jxUcrcySw5Ug4HYqotjmohxCu9ppoGEHKqD+qfedU2iacqIcOqNQOyptKUwZUJ9YZTQlMpgqJKAUNtNZ4NKkB+jke0qrUFAmQElGtrNQTBkqsbqbPjBDbfc/6OQD+e0/7sK26mWgH41pT+1VVodQJB/OYf8AdhTuD+MtwN3WzB9JV9uzr9Py/Vka7cLTwoauI02n4pbVn2UnlYW5d0Wi0qClfMdOzan003j7ws60cWWs5XQqNH4dqNH51OqfnUj+9YKM93dk/wDhj+01baNQVO0FJwwHN2/uELDQGqnd4/7uR9Zqu3Xku7ufjSoH1bgnH4tyxEgDKv1QyrBy4x9qyl0GFXkt7RCocqKbhJlRlTTJSgoKSqm1WappgHkZVROnxlMGQjNTa4eK3NBPBgeldx+xc4CF0qR/kJ39sVb7N4e6uy/nH/q4WOqcStlnitHVpCxP2jxUy8p7IBOEiEi6EkNiEiUwolZyEeSEzsks2aTqMolJCgCoqSRCBgqQVakCjUpkpgYUSpA4UVIJJhRJgSsVTIkJaPFGvwQ5/gstK8yUpUjHRQduUjNByqnBTBhVuPrFajKLhCSm9QC2ykxjnuDGAucTAAGSi4pVKNU06rCx43B3CnbVn0K7K1I6XsMtPQqN3cVLiu6tVcXvcZJPNXWOvzZ3dqkIGQhYaCChIqUgSKCgqKSEIQB2STSQGpAMoRss6U0IQogOygppafFFiKFLT4pOQJCEIoQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhGxQEQnukhRQiUIKUgSKaUKBITSWGghCEAhCEA74xSThJA0IQgCkmUkH39tPMmZ3yrBTkRkhonAydo9ys7qQ71Zjf3KzQRBIkdV9vqfM0pY0tnQSNQIPiOYSbRZJM4O/KR0WlgyQNpj3HKkxocZgE8wE6zp2zCi3pqgdYlbKXDSaJqkAiBsfb+5SNIx6rfWycK1ldwGguJG46J1nQ5ptiwnHmUxbkjIgQDg46rYQDuc4O26lT9V+PVgynxKvQzusKoaHaCAYgnY9Va7hxbSDyWtn4s8/Fdm+4s+vwmhY923TQB9ad8/uP0Llurh8zkDAkbKfEqdEYH0P0Qd8eKj6O+RLSM5wuiws2LfI+O/sSLm6pAgE48VbyHw4os6Ia8OfBzpmJKlxC3papp4BggCcdVeC3Vu7qCDBlWfiyD8WMGBsCk5T4bld0QMCBGFHTBAjwhdo29N8iAAfp/jCz1aAa9wy1wPlkfYrObaXh05uk6RttuR4qXdZ1GQRiD7YC1mm0D1QMDCk2m1p0g4HKN1v4jHw2dtI6ZG38ThOI3GREThagCXaXdMZ/iFK4o0vR6bw/U54Ic0tjTERmcz9EKzkifDrCWjSQcDM7yo9zMziZmdgY+9aajNThAgHfMqQpAgGDB3Mq9adCihZNqDABMefOJSrWIbiIIBiOXJdnh1u99TTLG4BOrAH8clVdNfUqa3AzsRGwlT402vwrpyfQw86QzVmI048FI8OLWHUyOUFeg4T3NG4Dq1PUCCP4Kt43Xt3MAoAQYyMn2/xyWpyM/DeNrWLA4nMzv1VJ4fTdkHM4XZqtIl0E9MKoQDEHyPLyWuupMI4lThwLjLcbBUVOGuM6RHmvR6QXnE+Ebp9zJn3YT4mj4bgW/A6lwCQdIG5WK64U+i4tMGOi91YB1NsSIO8LFVt2OdJG+Snxdnw3iPQXiSG7KmpZHfTk4XtatnTcBAgxjHXx+5UVLKkRHh0yQnXidFjxVS0dGG+wql1mY+L9C9o+wYWwRkeCoq8OaRAH0pvGrqx459s4CIVD7U9PoXsfwa0mC05wqKnC9nBpgjCnTivVk8oxtakXd299MlpaS0xIO48k7eyfcVhTY2CfDZekfw3OxhRp2VSjV1U3AO8sqfDxq9djzl/YG3cASCc8lidRPRequrWrVfqq+s4iMjkszuHY2KzlwxZy2PN9yZSdTd0ld99gdtJHionhryR6vlnCxeCOk5XB0RmFHSV263DnMcQR7VQ+zIdsfcsXganM51NvrjU4tEbjdJtLW8MbzMBbXWrp2SbRex4dGQVj4NX4qi+s32zw0mQeayFshdi5JqsJfl0LAaW5iFnk4O/ZrHlZTTJyNlW9i2hpAPRQNIzsFyvFXScjGWEJhbXUG6J59FS5gB2KxeOtTOUm1qoomiH6aZdqIjcrebi84fbVbWrZUqZuKekVK1vFQN5lrj7vJc4sBBBGCIXU4zxzinFbW2t72s17KA9UhsF3KT4rncK7YZ46u73cZ4yo+xXQeai4c06WNoafVmcqKsgogqdJtBDmxHitNrbd93n4xrHNbLWkH1z0VLmnmnSu0WMcTABJOwCC0gwVJjiNgZScSU0K0hJPgnugSFlSOyjKkchLSkDaU/jeCUI2Pkpo2erwRq8FAhSDSQYEwJKaXaQMoKiAZAGZ5J1A5ri1wIcDBHRNJsTlTmIKryeqeYiU8D6X8Evwj0OxfDr6yuOGVLttes2ux1J4aQQ2CDO422XhuNcQfxPid3xGu1jKt1WfVeGD1QXGYC5wd1QXTzWtszGS7aatSi+2pU20tNRsl7x+cszjlBJCgs27bS1eCRyUkIHKaimCs2LtKUJIWFNS1eCiMmOZU6jHU3FrtxuqIkykhCbAmkmCRkKybWAiEwPFISpN2C0sNvIKTssb5n7lEYKf5o80a0rKAm7ZRVZSQkSiSs9SbEqYcceYKhKkrLs2tuD+Of8ArFUpkkzPNIqhyiVEoGybNLJH6RRI6lQQgnjkUA9VGUSrsT1DqiQoSgJsTgJqCRKu1X0n6H6tsH7FEmVUE5TaVIOhPUoIV2bT1KwadDiSdWIAGFRJT1GE2iYOU5xCqBhPUqJyiVXKJTa7We5CrlMEqym05SBUELTKyUSoavBGrwTaJypY/SKrlEqiZjqUpSJwohBOU2uwogpFBZqRq8FBCCRMp6B1UJQEEo0lIlAPgmYmYV2lgDkw4BQTlXbOlusJB4HNVyiVdndYXauYQYBgBVymCQm0WtIAgqSolS1lXZFqckBQDpK0WjG1K2h2RoeceDSR9iNSbump/wDo7vDu/wDhq0EG74bJ3psB95CpaC60LuvcyfOmVGs8tfZukjTTaR7yrj2jvPlu7+X92Un1lbWJFb2A/QqKh9YxtKm92vT+pB8U81w26Vo0t4xw0HBqU2P94IU+C0xVurqm4CO5P7YTp/8AbHA3RE0aI+lwU+BY4nct/wBSf2glfR48J8TGe3Vf7Rx7kaXvAMQ8hZCtnEh+VVoEfjD96xOKr5uc1lYi8xMJT0ScSoJpgyUApJygMlMOIMKMkbIB6oJlxBjC6VN4PAXCf6fouZut1B08Hrtj4tYH3pa3hfJWbwLlh8CPoKz1m6XuB6ooOiqw/wBYKV8CLqoPI/QmXknhne6FCZTKSMUSgpISwElxhCBuhYqkU1FCzSHKSElFMJhRTagkpNEhQCkCeRWa0lMFJ/xUphIklZqhJ2yZUVGtgxzUDkqTlCUjOy6BUkwVdzlUuGfatMkTKSEclUEoGVEptMhKJRCSElkEoQhRSKSZSQCEIQCSZ2ScJhFCSAmECGFJKAUlkSQmEFRCQRKEIIkQkm7dJFCEIRQhCEAhCEAhCEAhCEAhCEAhCAgJhCEIBOFEqRUNiEFJCLsJFNBUEUIQsrAhCFFCEIQCIQhAIQhEBSTKSK/UFjbU3P8AXGBuCfoWri9426ZSoU2U6dOk0AEMAdgQZO/mOeSr7G1p3NsDTfNSZhrsjw8d1nqUQKmkkOM/x9y+rHirnmjTDG8nEAhrQIHXKVKlL8nz5Y6BdG8oCiRr9V0ZmMScDHsWWm5sgjkdyOalvYmK9lMAkNAPKCMHfPh5+Cy1aBaSIMzER9C32lXuqzHBgkEEA8vBdij2eveIcJPErajqpiQWgwXACCemEhlqPLd2ZAx/H2pFpcQS0gnyxzW8tZLZbMD80b43Wujwl1XhlxfNewMoENcJ9YzkH7lU24jaR0yI3jOCQh1vE4ON4yPNdvgNvYv4paUuI1/R7V9Zja9Ubsplw1OB5Q3Ps8Fv+ES17PcP7U1rTszeG94bTa0NqioHjWcuAcANQiM9Z6LNy76WR5JzHNMn40knMzndIUzqGJzmZyB5clofGoT7EqbtNQwYcMYPOFqUsiju3MgE5AORsUi5wgZgiMdFoe4OM8+pSkQTG45oaVd4/OPfzQXGYOw5bZWltBpod4KjC7VlhOT/AIYUO7BAbk49vmnY1VQOJI36JtdviAd8far2sDwCSBI8gc/x7VS8aT6sAAyMq7Z6dJNgtzKCWyW7T1woN1ACRM5PL2K0tcGknAEf9Fdmja1oyCADhWM0TBECVleXNwOmM+9IOefWztMTuodnT1sptBkAOGTEy4pmoxxnc7T1XMc53IzDcSVFziypLZnkZ3Cz0tdTqS0NIBEHPgPBZ6zC9uJjMn2rM2u7rgddz4q1ldumSdhv4Fam4l1Se10BukSJ3H2+CzmkfjNbIiRlXurNc/wn+MexSFVsTsfdlamdY6IztbobETzB8v4CiyNWo+Oy0EMBIwGxA8eaYa1xMnbEytdSdIpVoAG7QJ33wBH0Kd1UpuZ6oyI5ZKqDRqkiCeiejEEcxy5dVOpOlldvI68xzQYyCST5LQ6i4gRtmFU+m8N1apEYWpTSpwyNtoTFNpcRgAnCkG89pwShp9XAMkcuibNB1s3L4JPLxW+oyxHB20WUvyrUXOfjA6BY3PcQIwAqxUPXO/sUtq9lFS2ZMwBIkgCEOsKRpmoSBHJXFx5n2JTJ+lbmVjNkYXWQB0yACeapNhMjT0weS6pdA1T4+eUSBA6J106I5DuHNPKPIJC0lugNgbyuzMmIE9AFEtacn3BT4lXojh+gsJmo0OE5HX2qriVhavuajrSm5lGZY15lwHQnmu+aLQ4eoPuCi62YWzuQOW6s5E+G8o7hwds0T5Kqpw4BoIaM7wF6t1q2DBPj+9QNoNiDnZanLE6HkH8PwYbJ6Kirwx49Y08HbG69gbTo3mq6trgAjbYJ8SJ0V4x3D3RhsKl9g/J0r2T7Npk6Ynmot4cHVA07lXqxNV4s2L429gVT7N/JjvcvfXXCG2lyGP0VCIJjaOi9Rc0+x9Tg2ltq9lQUy0Um6tYdHImR7ZUvSbyj4m61M/FhQfQcCTC9fX4cxzsMzOTKy1OHQSNBS8WNWZ15Y0T0R3bO5cw0peSCH6thzEL0L7Dq1UOsYB9Qe5Y+BGvi1wHUioOpHVzXbfYnGFU+ydOAud9O3OZygHARnKC0yBC6TrQgbKHo7muDg2YM7LF4GvisPo7y6GsJMwPNaeL8Ju+GVKbLtrAajNbdLgcbK13eF+vZ0yCORUb6rcXdXvLmq+q8CA5xnCzeFZyOcdWgMxEzsoFvVa3UvBOgymC7vqZeCwhsOiHciuV4q6TOMgaHEA4lRqCDDTzWjQeYUCzwWLx1ZmohEdBCtLCg0yBlZ6GplFUIHTKsjxSIU6V6or5ym4SZJkqwNypd0XvDWAuJMADclOmnUjXq94GNDA3SIxzVR2gLRXt61Coadam+m9uC17SCqiCOqlxsJlKhB6IyppTOIWdKidoUYlarOxurxz22tF9ZzG6nBvIKhzSN0XaBQpJjp/ARdoJjdTcADG6QClCQmiFnS7ATSTIxKypIQhAIQhWAQhTa0re41KcCB1TUUGAptrYfCghTpP7uo2oGtJaZhwkJvTNqA2QjE9JKCsMkiUHZJUSlEqdB1ENrd6xzyaZFPS6NLpw7xHgq5nnJVl1AEpyolJXZtOUSoyUSU2u0ghRlEptEkxHWFCUwVdiWOsox1USQiU6hIlIpTKOUqzuJtMplV7IV2LJRKrQmxMnCQPjPsUCUT0Ku02mDCbj4KuSpNOIU2JyiVAuPJR1HqtbRbKJVYceakHAqyiQQVEuQTCbEpTx1+hKUSrsOY2KEApT4q7EnckwZ5KE+1HsTYlPgUKPsSBhXaLJQVHVjZKT0Ta7TapSqs9ESrs2sQoSpSgJRqQThIIiYMolRlEqiUolRkolE0k05W3hn+nMb1ZU/YcsUrXwkg8Soid9Q97SrKuPax0LeBYgnkbYj20ysnEHDVQjlSH2lareDwwEnYWx+o8fcudemX0z/AKpv3rUrry/dn0/VU45UtZjZVF0o3VeV3nE/hLgR/wBVR/bKnwwlvFbyB/RvH1gqC6bjgZ5hlIH2VCtFoY43xBu0Mf8AttUvevr8d3yS/wDyn9nL4uIvq7doqfcue7qulxyBfVvNv7IXLcYWny+btnfqiTKSJHVRRgykmkm10EIKEQwVqt6gFpc05HraSskhSa45A5pZuEuqmx2hwd0cD9K2ccaKd3pH6AWCZI8wul2k/wBNJ8B9inJdWN435a5ZSTmAFEuCS7YoKSEK0OUFInBUZWTZoSJQs2KYKElAlZVYhu6iDzTkIJhNQBCJHVSrKmoFE+KWoRMrLRplQDp3Tc4QogcZUCkTBUXnmro2T8GFApqKaZ3uiSlBTbumVdogU27JoUUJJpKUgQhCikUkykgEIQgEIQgYCIUhCm3JUtVVpUgxa6VJpC1izbErNyakcwMRoHJbH0Q10FLQ1ZuS6YnMIVZwtdQZhZqgO0LUZsRUFOCN1CEQIQhFCEIQCY+N7Ek/FAFqXsVrdkyCs9S6UweQThXUW+tLsBOowak6jXZnIhCsc0yoFpC1tNEhOEgEIApJbIKLokIQVIBCEFVAkU0oWVJCELKhCEKKEIQgEIIQgEIQibBSTKSK/S1nd1qLwaby0zOCc45/Z7lofxCoaweCJGRI59fNRdaEPiRIMifPEqp1s8fGaQQY3ifFfQnJK8947F3E+KXF9cvuLq5fVqvJLnVHajnqVjbWI9Z2qDgieauFECkYBL5kdI5/x4qt1s8N+IZGxiZV64nRU6Vw4OA1SRzJ5hezte3L7Dsizg9lTis4VWVKjgPV1GQ5viJOcLwwpOjmMzMbKZZ60tPqxk9VqZRjLCtYuNTySGgcsH2Baabbqu19OgypUIaXPDJ+KN5jl542XNDS31jAkbhabPiN1Ymq62qOpPq0yxxYcwdx9CdX4GvxN1UtY6HEg7gHMRCoNTU0DVtsQIhUvOqN/FAJEwJ2GBuqLJIBdtv/ANPPyVzR+LMmIxP8dFBzS1jKhbEYifDmoGRPjPPb2ptDGxgEzBwN1J4Gj1ZONkmAaszHirXUo+PtjwPiqKNRGrS7nB809WoZONh5BDmnVkbzuZ8kg0gTABAxKGmm2dS0nUYdgN0gY8+qhhxGwLtx0/jwVOlxiJ8lFpqBzQ3yxn3JoamsbAO25APXmpOe2YyAJgrOwvcDJxpPuyk6o4NyPNXSbXNbMwJkqTacFukEwSSs1J5DocY9+VqoXFLvwCRpLhqIGyrO4TqB1E523VTrd5IALhmYiff4Lt9qL7hA4hVt+DvqVbFtT8VVqM0vIgTM53n3ri+lNOZPh4qd17IdwdJiCOvRI0SHETJ+lWi6aSAdoM+PgmLhhySHAeG6vc1GY0icGc7KTGuYQIIPiVpp1qWYjO5+9Sc6m5h9WJO3702dLHUkwI3OylSJAEkgkLbbW4uquhpio4w2Tif8ZH0quszu6jgTlpgjByE2aUetjzWyyrU2MqU6lAVHvaAx5MFh1AyOuxEdCqho1bDKmwNBBmSJ57eKmzpe27L9hrztBwO94rZ16UWzjTNEyXPOmcR4Lx9xQEAsg6hgDyXa4HxziXDbS7trG+q2tK7b3dZrHfHYJx4fGIkdVKjRovJIAB6DYeC45ctxvd1w4up5l9GJkHbkOSpdRcJP8ea9LxC0pMaSzeCfLw8P8VyHsZrjmTgjcreHL1Jnx3G6rmmkRy/xS7p0436Lp0wyckCParDasdIEHmcLdz7ufS5tsLdtKr6TSq1A5jhTDH6YdHquM8p6ZVJpST6w85XTdbQXERE7feq322SHA+SdZ0ac7unQeY2xt7Ewwlw3JP2rc6i7Xsd52T7t07b8gYV6qdEc4sdkzJJRyGMj3FbjSAnHu2UDTAjGPJTZ0sUnr54Ug7PPHVaTRBBMbDruouou3jlCoz6pOJ1JgD4uD0zgf4qx1DJGCOqfdev1IwmxEUgSACCYmOYUatDSfWEGNlcxrmuBIBzPuVt081XSYDpk43Kmxz30GzyPPyUe6AM5wtTxyx7VDB36ps0z1KXevBqOLjPMroWdjad1Nd4zmPCfes7sAgnAnE4Ceo+q0zkf9VqZM3FgvbSm2vUDBLQT71jNrJyOa7bmYmecbKt9IAkaRg5kbq/Ep0OHUtJwW7Kl1k2RDRnqvQmgDkgAkKDqOlpAE9PNX4lLht5ypZDk2T5Kp9jg+rhekdatDjgDnqGQVS6i0n1hA6KzkrNwebdw8HkqqnDmxABnYgr0jqA26KBtS44MwtfEToeWqcPAmBhZ6nDyeRXr/RCJxk+CqNrg+ofNa64lxrx1Th5mQJ8FU+ycPzCvYusQ45EYVLuHtzEkpvGp3jyDrR22lVOs3/or17+HjOCqH8P5wcJ041erKPJm3ImZVb6Bg5K9TU4eSdlnqcPMbFZvFKs5LHme6I5JGkRyXoXcPP6Mqh9kQfihY+BK3OVxO7PRbuA3ruFcas+JMo06zrWq2qKdQeq+DsVc6zcDsVB1qRsFj4Gmvi7dn4Te1NHtdx2hf2/DBw+lRtm0AwvD3OIJJcSAJ3jbYLyRB5FdB1uQNlUaB6LF4KuPJJ2jFo8VHSQtxo42Cg+idgFyvFXSch8N4hd8PfUfaVNDqjdLsThYiOpknmtBpRukafgsXjrcyiiI5I+xWlvgkW4ysXCr1RXjmhTLCFHQs9NalD9JedAIb0JlIKRaUlnVa3ESE+WSpDKSlmzZRlKD0UwpFYs00rDUafFSKECAhaLZ9BrKja1MvkeqQYIKoTa0nZRZdIlQV1Sm5ji1wIcNweSqW5YEhTLAGzOZUFm3dR1+zvAbnjZuhQuLSh6PTDy65q920kzDZjBMHeB4rkH4oJEE8lJr3AOaHODXjS4A4I6FJx1IqBSKcJKoEIQgEIQgEIQgSEIQCAkUEwgcIlGoKOpBMJgwoApakF1R+p0gBuNlBIFEoGicQlKhOVYlTRGJUreq2nXp1HU21GteHFjtngGYPgdlq4zeUuIcVur2hY0OH0a9Vz6drQnRRadmieQWkY5jqiSkUgcKndOUpSlJBImUwVEHKUqiwJKCYOE0JJqOpEp3FmrwRq8FDdEym6LAZTUARzwlK1KLZUVAKUptEtPiiI5qEpq7Q5TCiUBXapylKipafFNmzkckApafFBCu0tOZTlNzIY1xcPWnAOfaoEeKqGCnvzUAYCmxpcHQPit1HyVNnmVs4MZ4taDrVAWIHK18HJHF7Ijf0hn2pezWOtx1aDQ3gzSelD25rBcq/MVmN6Umrq0p/AjZ5Oo/8SsuTxRwF2RvDWhXF29R2k+n+VCYKrlNpWnk26xeJ4SZjSQP94unTgdoOINgQaLsf3mlcIVQRZj9B/8AzLuj1u01YERrp59wKkvd9L0+W9X/AOU/tXL7QCbmq8CAe6PvpNK49Q8l3OPQRUcDPq2h99u1cJ5krUu3i9TP4lRBTlRKCcKuO0gUFQTlSrKcoJUTlAwrEtOUThJCu0OfWHmF1+0n+lT5fYFxojPRdztN/pB/u/shYz72OnH92uK9whR1BJ07yoF2JWows1N5lRLxG6qQmjaRcm0yoKTeaUhoQhRQhCQKgae6jKJWKsqcQhQDvBSDp5KGzBhQIkzKQJzzRPiVOlepIqLiEjsomTzV1o2biDsooKEAlCaUrIBugpNOUypUJCaSKJSThJSrCCaEKASKaRQJCE4QJNNR1KbXRjCspOgqspjCUaW1C12Fcy8cGxKxtKYErF/NqNbq+pRFUeJVAkc055KaipOMuJUXBAQVYlipzJ3VcQrnmAqjlX2SoafFBEKSREom0U4TjKsDRClumpNqdJKtDThWtpiN1LAGyzcmpirg9CnB6FWNJ2T8sKNzDaotISKuOTlItCsh0VUQovEhXObhRIUZuKgsIUTI5LQRhRKu6mlJSiVdAVbt1d7TRAQiEBBVQQkU0T4IaJCIQoIoTKSgEIQstBBQgoCUJFNAIQhEBSTKSK/YLrACGicHHMrPUtgNWIkchuvX3PZ/iDASKToiQAFxL2yuabiXUngGYdGFyw9Rjl4r7PL6O4ecXH9GY12YWy24bSqiXRnbKqeHsdziBlSp3L2OwffyXa5W+Hlxwwl7xZc8Johpc0id5XM9BBe4gbZJOVsrXtZ7YJMYEHnB5q/gHE6Fhxe0vrq3bcUaVTU+kRIcI9hxMjIzC1hcpO7lzTjt7Rnp8Er1KZYaXMOBOVzuK8IrWr3amkDwMwF6vjHaihX4pcV7a17m1qPJpskEtEAmfauNxLiRu/is0jY+76VrDPPbHJx8HR28vL1GlrhkdY5Ip4fMDwzC6NS2e44p7bABUVLZzCS5pHTmCvXOSPBeOxCpWc6iKUDQ1xMRG/jzVMOJ9V2fBXkENaC1ulgLWiOUkx45JUWsJyJAiBnkt43bNivMbnGPIK92rAcM+a9P2M7J1u0d2+0oVWU6oAI1tOkZyT0AwsnaXs5d8DvX2d5pFZpGRmQRIM/xuqxvvpww0GQBBJ5K1rA3BEEjf+Pao6S1wIDgAd4wB0RUrh+GwMY8VLtraYFOCZjAkhOlSa4iQA7EyNisdRzm7b/mg5SZdFjmycgGMKaqzKe7pOaKbT6oMtxPJZGinq9YkcoBUa99qZpEDnHsWcViTgmdvJXGVnOxdVph1SGNAzsM/wABJlrVeCWAkRIwtfDGMruAJAE5yvZ8K4PRfQDyMkZM7clz5eecbvwely5vD5/Vs6rGjUC3n0Wd1J4PjMr3vGLG3ovJDGyBjPJebuKbSTAMT090rXH6jqjPN6b4d04rqL2uJGoJFrw09QQfBdN4ZmRsfcoAU3AiAc+tnlvt7JXWZ7ee4MTXOME5mBPVaKQc4QDsZiJU20WESCBO0Ynr96up66AL2PLZETA26+SuzSllQsdEkFpBB5jmjWXGczkkkZ9v2qegZxidyrPRw6mXa4dIIBaI9/KFFZaroBz05c1Q66LTk/StJt3ZbBJGM8uqprWj3Ek/x4qyJ3OhxEg7kCdui32/GdIjXtn+PoXFq2VSYa12/LkqfRq45OjZS8eOROTLF6erxbvWlrnT1jcrFWqhxLd8ZHVcNouGbg/xyVor1cS0iImVJxSeFvLcvLp03Fjt5G08vNdC2ugxsHcgR/1XEbcuOMyRI5+9aKdbJGkgcgcq3EmTrOrgZMmR+/75Um1mOPrGCeZGy44qHUADjcqYqEEwZzzWehrqdd5puA09I887rZSoWjrJ7tZ72Zxsf42Xn21Xua0yQeXiFY6pVA1NzBG2/wDinSdTomhTLg1mxUqtiQC4Bcqnf1G1AHzjod10GcXpmmGjlvI5rnlMpezeNxs7qnUnNBbkmeaiaUtnYxiNsqFa/Zyz4FUm+yQDvj+PBbm2LpaaQ1EkEk+PRAaAZIHP3rM275k46hWi5aBJI5Aea0i6o0vyQAFU6iTmY+5bbd1N9I1GkAjkM5UC5kkiI5KbpGcW5PqhuqT/AAU7zhdzbtY+4t6tIVBNMvYWh46jrkLbbvpteHyCA6fpXre3fawdp7exp+hUrUWzMtYdzGfZ0Cx1Xa6fOjTIyRJ5hQLDHiNyurUoCAJ3VJt8bArUyNMIbPrGDy803iGiBBAwujSs2kE9MmVmr0C1xAbB+xXcTTEZk8uRSLZwJHhKvdSces/uUCC0yRBIQ0qeMeWDlUuZ+9ai0aTO/wBqgW5IgxyVhpl0Rv05paYMT5rUaZ6KIYCOe/NXaMv27I0Q2AtPdATDRCg5kDA/xWts2KXMBIMKBpiCI+laNJJ0o0A+Ij3IMppNmYmOSQoAyCIWvT6x3z0Sc07AK9RpidZgkiFS+y3IXUGkcwPNRcGl2HNOOqTLSalch1i2Pi5VT+HjfuwMLtFgmABCbqREyJBCvXTpecfYN20hZn8PbJxEdF6d1BszpAjGyqdbgyQAQVqZsXB5arw/AIz7FS/h5AgNXq3WrZOxlUvtf6o6rXWnRXlXWH9VUVLEwYbsvVPtQTkgeEZVT7RpxCu4aryLrR36KrfZkL1lSybO26pfZNj4qny1d5R5U25HIq1mpthVthSYW1HhxeRkQu++w/qj3KmrZEAgRnfCl48b4OuvNOowcqJpgDAXoX2HVoWepYwdlzvBK6TlcM0z0TDGlnius6zM7Aql9q4H4i5307U5XMLCEtC6DrZwMaVWbdw3aud4K3OViAKcGVqdR8FHuyud4K6TljPoI3S0gc1foHQpaOq5XhsbnJFBHRIkjC0BgHJQcwzhZ+GvVFZJcSSST4qGnKtIPRKB4LNwa2A1pa+XEED1YG+VWGdVM7bopkscHwDBBgjBU6KbQLRyUCrXnU9zoDdRJgbDwQwgBwLWukRnl4hTpNqSlCnpyowmjaKkwAzLg2BOefgnB5qMKbUkJwkkAhCjJlWTabNCAgopFRJlN/JRCsibCEI9qujYJhIFI+KNlBJrwN1LUqygGEsFmpRSJzKDlSVT2TBKiSeaRWpeyJlKEiUJPBThEIQqhymFFCuxJBUUQmxJCigEjcymxOUgYSkpFXabTmU5woBMFU2kTlE9UpSQTBnmmqwpY6oJNITUAQifFBNPUeaghO4sygEdYUJKArsT1eMpzhVkwogxzVlRbqOqITnlGOiqBMrRUoV6VGlVq0KtOlXaXUajmENqAGCWn84A4xzW5YyrmMrXwpw/CdoTyuKZ+sFhlaeGmOIW39sz9oK7WeY7LSW8Fg/KUx7qtX965XEz+V1AeRj3Lc6pHCXcpqtn/aPWG4HfXjhrYydR1PdAxJSV257vU/fuzO5JNOU559VGVvbzbX0zD2Ho4H6V6JtQf500/wCsGj2Fq8xqIaTsQu6Kob2htak5/FH3tCj0cGfTP5z9UONfzJzJ7q0+igB9y4T12uNGKbgc/i7bPlSj7lxCmN7M+p18S6QJRPgh26QV3XnOfBDjKjukrKqWrogOjdQ1HmkTKbFsolUyeRUg6TBVTSxx9U+S7vaZw02zhB10mn6AuCuzxgF3DOG1CZLqH2EhZy8xvC/LXFqOVRVj5lRaJVjJBEJnBUZV2gKk0qKbYPNS1UtXgjUkU1NhykhQJlTYmFElJu6ahDBndBSQSZUWBKUSjkimgpJFTZoFJCRMKbU1FOUgVA4RumdlFRAhCR3UU0kShFgSKaRUAUkJhAk5SQs7AcohCFA0bpIKu1Sa7opqpTa5SrKtQoyOSkstHKjUKHclAqxm1GocQlKHbpLSbCEIJhREmtzlWAQq2E5lWBYvl1xTBwEboBHNSJA2Ce7rjSAyphqGQVNSusiIahSSOyi2KnbpSpJHK0xlNo6fFJ4gwphSDCdwjlYoUYla+68FXUpwcKJYzhqNIVpYQNktB6JtnSuEnDEKyEQgq0Ic2VbEpQm6Ki2Ui2FdCUJs0oKStc1QiOSa/ARQmRCRUAUICEAgoQiQihMpIr+jNn2q4NcsbNZonbVj/opcQuOFXdJ2l9GoXSMEHzyviBuoy2o4Hw3/AI/chnFbqnDW16gnxI+leCfZXTd41+gn21hPvYve8WsbF1V5aRBwIK4NxbUmSGiOZHiuAeNXJID6hPt930BRPGXz62eRwvbx+mzx93k5fX8PJ7N1djZI8vcsr2Q5oBztE8/BZncRBJkwOcHz/wAEvTC8bEiJI3HthemYWPn5c2N8NbWQ4c+mYU6baQYS7A36dF2uwNlZ8a4/bcOvS9tOvUNMlrg2MGMwRvHv3V3wn9mB2U4vTtGV6rmVafeNbVPrUwDEHlkiZ/crMfZwucjgsqU2u9aesIuX04n1RI6brjNrEtyNxy5IdcajqkF07SBzW+ireXcXvIkZggiHAKtrHgZAiMY2UO8yAQNuf7vaF7f4LOFcF4z2noWPG3u7ipTeWsDiC9wb6rZG0rrj28vNnk4nZ7tDxbs/eOv+GXdS2rAEOc0AyDvIIIPtCz8Z4xfcV4jVvL+vUr16rpqPcBJMeH2L6nxzsh2btL2raUrptCh3Qc0PrB7mZOZGQOU5PVfH7ruxcubQfqYHnQXHJEmCunby543ddvhvB339MV5MTGBkwudxrhdfhuh9QEMqAaTGDmD7V0+zXH/wXTc19BtZod8QkCTG/wDHguZxziFxxCq99dwnoABPXzzzK4YZZdWnpzww6JZ5cau90uD3mcZ8FnJOdp+3+MqdRpB9USOWZwq92kT0np7fDC9UeawOIgQQ7Eg7SkDE+9Mggztz2USBMSASRMff4LWmWy0uH0KgczzXpbLtFWp02sDtyfEZ+9eQaMjAicqbS7fV0k9Vx5OHHPy7cfPnx/dr015xd9wSXGSVztfeD1ZgjchYGOcMbQdyvcfBRwSz4/2z4Zwm+qvbRuaj9ZYQHQ1jnQMbkt6bLMwx44Z8uWd7vJV6bgAQOUkRn2rE4uiJMZM9fBfov4dOwPZfgPZSlxLhNqbKp3zaGhri5j5kySZION1+frgNDzEmeog+5b4s5nNxyy3L3Ze8fjJ6zOyYvakBjnYG2fP3JucwzpAPOQk2gapDWjx6LrpnadO8AJaTk42XQt7yk6B6snfouPUtXNc4A5Eqosq03YaYx7FLisyr1NOpQfBAaYPPKnVpUHguJaDpnrjmvIm6uKThBIaApfhWqwCSTBU6KvXHpalOlgRI26KsNouMkjfcrz/4UqOaPWOBCR4gQYmTHjlWY1LlHoHW9EjIidx0UX2VGpGBnGQuGOKPaNU484V9DjBBBe7Yp006pXTdwsEHSW85gzzyonhxa4NAbk7jr4+Kqo8ZpFzRMwc+P8SrfwvSEAu1RjJU3V7AWDuYk84wB5KBsnAEFpzkhbKXEKL4OpuRtMBXsuaJwS2Tsp1VemOYaDhMgjrCsAe0EAT/AB/gt5uLXeBvBOyGutnk+s0k+Km1041a2JMgHzIVT6D2zzPKF6E29F4gRvJzCrqWXMTpnf7k2mnnHU3k7gHqE+6c45BA5LuPsxq9YROyQsgRgSQVraarj0qJIMgwMrRUtoZqDhM8117bhTqhDWgS7LYC2v7O3JoF40kAnE/xsuWXLjL5dcOLLKdo8gX1actpvcJ5zCi26qagS72Rld2+4JcsLgacwfOCufX4ZWZ6xpuI5w3ZameOUYuGWKhl87SACPYtFG+cCC4mCT/1WepZ1GEHS4ezboqxQIMwR0V1DddajdB0atytDKrDE4G3muM0OZmAOYVgfUAIMz9KzcYvU+k9hezdr2ho3jqt76OaLJAiZPvXl72jRp3dSmHB8OIkYmMLl0LyvSokse5od8aHET5ws9S6qGXE8swuUwy6q6XLHpjeRTHMYPWfNUGkwnYY57LI+tUIJB9u4TFZwPMQuurpja42wj1Mg4EKh9BzYJ8iCr6dctDsmdjlRq15yHR0MSs917MxbkhxzyCkxnrGOuFGo4l0k8pJCnTq6XSXQFvfZnS+nauMbE+SZsXEyWhSZxGlS9UuHjhaqXErd8S9ufBZ6quo5tWyc18BpzyVTqTmyS3bK9FTuLSo2dTCJ9q51/fUaJJpANI2PNXHK114vT3kvbwxMszHe3Dxb0zkSJcR4D98KFa54dbCKdHvT+lVdJ9wgLkcV4s8vcQ+ZXAuuIvLjL+SZcsj3Y8XFxztN383q6vHzTJFKnbs/Vot/cs7u09wBpd3D2nk+gwj7F4utxAgn1istTiBJ+MVyvPW7yV7xvH7V5ivw+3/AFqP4sj2DH0LRSura4AFrcNeT/R1oY/yDvin6F86HESN3LVZXzqlVrGEueTAaBJKTn7uWWOGfmR7+pTgkPY9juYIUCyMDmuNwntPa235HxK5bVpDBDCXOpHqHNmPEZHgvQMdb3NFlzZ3VK7tnyGVaWxO+lw3a8Tlp8xhd5lLNx5Ob0/ROrHvGY0pkxzUXUxPxSVr0EDbCRZIzsm3n0wut5nHt+5VvtgDMYC6BZJ5wmylynHNWZJcXINDMwoutwQuy6gDsJIVZoAyr1J0uK63IyFW+hAnC7j6IzInO6qdbNI6+CvWlxrhOtx+jgJ0Le279vpFOo6lPrtY4NcR0BMgH2Fdh1qD/gqX22/XkFqZs3FxKlq0nYGOYwqHWgMjSu6bZ3iq3UHGcRGy31s9LgusQSTHuVL7IRsSvQmjEyAVW6iNiM8k6tnS84+wgYCqdYkCdK9G+hygKJtxHSE3Kd3l3WZ20wqnWzoPq/QvUVLURiD7FSbQOGyaxqy5PMuoHoqzQK9K6yE7SqqliM4CzePFZnk84+jB2VZpiV6B1lIjT9CzVbIt/NWPgytfFscbuxGygWwus+zdGypfaEfmrF9O6TmctzSUBpC3utnTkKo0CDC5Xgrc5YyEFRIWo0HBLuidwud4a3OSMsZyggHwV5pmUiwhc7x1rrjOWpRKuLSo6Oqz8NepU/bZQgq/TlLQEmOi3atu6aenoggnfHms3FZUHtkqBBB2Wm3omvXZQY5gfUcGt1ODRJ2knAVVRpa4gwYMYMpC1UmN1JBWtGyqN0PLSQSMSDIVcKbsKO6hsIThJAinlCFLNqCSkU0KdJsgmhC0gQhCAQhCAQhCATSQgaClKEBCI8UIlXaWHCISQN1GT5qUqJ2S8wrKqUjqnKhPggEKyiaYKhI6okdVTacpgqEpopvnEJZ6IBQT0VQ2la7m/vLm2tba4u69ahaUzTtqb6hc2iwuLi1gPxQXEnHMrFJKcqppNW2ZDbyg44DajT7iFmlSYcrW0das8jhbgcevO2/ruP3rn1Ha3SrrmqTbNY04dJPzisuOqRrLLaSRSlCrKQ2Pkt9WuPTaFQHZtPPSAFz+RU3vmOgEKykdTjbyZAx6lPbw1rju3ldLiriYPVrfteuapteS9WW0CUgSDspOgJHIhXbnoiQUFRwNylIVQOM8kkwQU1rYim3dNIpsTnwXavX6uAcPzOkvC4YXSe6eA02z8SsZHmEy9lxrC4qCbjhRcRzUlAd0KJM8lFTZraxRckiCptdAGFIkKEolNmjQkUSeqi6NCihTYkkUk5TagJpSkgcpIQVEIzylKCnsnKbEUtk5lCm1CaUoJlQCSEgoujQlKSCSihMoAICAmpViJ3Qmd01kRQmUkQIQhAIQhBMOhMPlVomE8rKunMqDjyUWmBBQSml2QQhCMowYSUnRCiiw2mFYHdVUpM3Us21KuVjDlVSmCsx0xq7PJTa5VMIhOZ2KtjvKtlBOFDVCjrKzIuzecqIQBKbVpE6bcwttChqG0qi3A1Bdi1Y0ALG3OTbH6Odg1Z61Eg7LvBreYWG/p5kbJsuOnGc2CowtFdsclSUZQcMKGkq0boVNKg2VINjxU0Js0qc3OAVDSVfImJSkdUNKdJUCFechVkKJpQWqJEK47KBRLFaEIRAhSDfBDm9AgikU0IP0J6e6TDiMe9W+mSTL8dfvVdbh7mtgGeY8cLK+2rMMjmII3X0pqvJ3dVtYEkGd4IHjy8VMgOJA3GY+0+C5NHvG4MmQVroVoIaRykD7VdLK192ZJDiM/mjko6XAwGuk7ADPmtVs6nDSDJjnHt+1a/RmvZgydxjdY3PdqY32YLe5q0XaqbiOY6+EH3KziHEb2+qd5c3Ve4fGnVWqOe47mJcT1+1W1bF7GiG43A2Bj+Cs1Sg5piDzJnmU3jtLjVMz6w2OcJjMy6AYU3U2NggnO/l4BQxt1+jqVRKC0tgzEQBn+P8AotNnc1baq2rScQ9hBaZ2IODKzNPiMDdSBkgZHX+OqSlm3T4lxW74hXfXr1Hve7dz3uc4+1c9wMjkNlfQbSJAO7h038F0PR6TmFzSTzO2/RZy5PZrDh3OzmB5kDVHjGAiqAQYJmZGZTuqYY8nJ5gnByqO80gasD6Y8FZq90u52qm4YQS0ZjczzVBBGTJjAJWv4wAIG045f4bquqA0TzjbmukrnYoZqB0mNOwBCk0erkkY6Hyz/GyTn7kZnE9Emk+AMdFrbOlrGt0jODtndMw2RIHP2KDKhJAGBPNb6dk99AVdRiNlLlI1Md+GZrgDMQDMLfwriNWwuad1a1n0atIipSe10OY4GQQRzVVlw+6u6zmWtM1XtEmOgWN34t+CAR4pdWaTT1Pa7ttx/tI2geM8Rq3Qt26aTXBrWjAkwAJcY3Oei4NBgrB4cYLXRqxOYWJ74LswfLCVN5a4lpcDEeeUxkxnZL3OqAyoQ12G9Nv8VdaVKbZNV2NhjnKocdUEgY6bIOlzfWzq2wt9SdKyvcaqpIiJmOY8EOqNc2d8LOc7nJMZQ8jlIke7GPuV2mlzmMeIc2CQNlndascNueJH8QpFx3GI3AO6kCYIOeXmr1JYy1LQahJ3xHioPtSHAcuUDkujTAcYcRq+392V6z4M+zlv2n7WWPB61V1OncOPePaMta1pcfeB9Kl5OmbOjb5++1fGBtg+KpdQqNiARlfe/ht+Dfg3ZThFnxHhld4FasaRo1TnYkOBHIAQfML4/UoRDiMbeSuHLjnNxm4WOA5tbly2UH1agn422V3nW9ItyIgKFWypkCWyfELfas6scSnd12SA8iYK2W99WmXOP3rVV4ewZwzG0Kv0EN9Zx1T06LNkalqQvHucADPTw/xTfdV6Yw90TIkyoi2DNpbB96VVkt07b5AWLi6ba7Li1cOhziQDBXZteKs0hzjIiDH3ry4p6cwB6qlLg4DYj9yXEmWnqn8TpdZUGcRp7h08s9V5Oo+oMk53Q2s8DB2MwP4yp0HW97Y8XpU6rC6DH0L0VDj9s+k0A+viI8F8iZXqB0h2JWuje1GkAO8Jlcc/TzLu7cfqMsPD6dcX1rVcXQCSJiFGmbd7dhH0r5/S4hUkkk+xbvw1TZaUnU6lTXnWCYGNsLHwbPC3m6vL09xw63c4hkZ2K59XhgEObBkTAXLt+0c6Q5zvfzXTocapVi0AiYzJW9ZRi3Gsz+HaZgSPARPgo1LICckjYYgldQXVKo0eO0oeWPaJHjPirunZw61u5o05geCzGg6fHkvROoNcfZAwqzaQY0AkZ2+lXek08+6nzyTGUaDMzJ23XdfYgkkMiOp3Vb7HS6BMeKdUXTjFvg7r+8KLmRuTO+Oa61W0IB/grK+gZMNJE5hWZGmBzTExCre1w6wVvdSIG2+yiaW+Nk2ONdU3wSJWBxq03EyV6SpTHv3lYqtG31aqxhoy5alZ6LldIcMfVpUKle4cQ6Ia3oOq5XFb9xc4aitXFLioyiNQcHQX1Cdg45K8lxDiNsKjpuqRP64K4cmen1sZOPCYRK9vDJ9bmuRc3Z1HJUbi8oP+LXafIrBVeHTD59q8ty2xckq1w4ncqh1c7kqmo50qhz48Fz7uVtae/wDHC2Vrh1uDbNOms4flDhu0H+jHT+t1ONgsFqRQDr17QdBik0jD6nL2Dc+wc1QXucZc4uMySTJJ6ptJXc4fcBkBpgeAXsOzHEWUboa3aGVQGvcBnwJ6gTz6lfO6FUtIMrt8NuyCMr0cWWq78eU932N1PGQNUwROxVT2Qdlg7KcQ9N4e2lvVojSRG7fzT7Nvcum9jwMtK9OW5Xj5uL4eWp4UxnOyIElN0jcQo6xO6u3HScY3S0+tiPPom17eqlIO2VOoVvZJVZbEbeK1BkkkOx4pOZBwCQr1Iy92DIAmcKLqYnGenktTWFpkggJgAZImMQrs0wuoCZj2Qq30PViF0QATI6KLmNkzKu06XKfbjnAVbrcb5XVcwCRA8FB1KfWx7VrqZuLkOt+W/sUTQGcLq1KUmCJVfdJ1GnN7gEKDqAGF1DTG+lJ1LGAr1L0uQaEeardb52K7JpCIgKBoAnngck606XFdbTlUvtR0XcfQE7SoGgDiFZmzcXAdaidlUbKV6B1uOirNAdFv4idDzdayzgKl1iei9K62Bkwq3WwJ+Kr1yp015epYnoqaloQ04O69S+2EbKh1piI3TUp3eWfanOFS63MfFXqatk3OFnq2IA9USnRjTrseZNCOSg6jC9C+yJGyzvs3NJBas3hxq/FscM0XKJphdh1q79FVOtc45Lnl6duczkmn0RpK3utnajhQNFw3XK+nbnLGFzB0VbmSVvNCOSh3JmFzy4bG5yRiDYKiW+tIWp1M7RyUSwrncLG5lGVzFAMOStZYYUNBhTpOpn0worQWDqommQJUsWWK4SMTup6Ui3IICz0tdRJQpxuUvJNG0CEKZEb7ojzUWIITISRnYQgJwjW4SEFCG4EIQRiUTYQhCLsIQhGbQhCEQIyhCAQhCAhJShJ0TgzCKJQHDxQhXYYd1Q4golQ38FZRZqHVKZQ1uRlBbpcQVpDhNuDKEKs7WPfLGjoCPplVyEiJRpSLuCVKVGEpVPoslOTywoRKeybRsvX62scDjSB9J/esZMFTqv1MaCqtSbLe4KJCiTKjq8E2gekgunkohXa6SQDHJLZIq7NJ6vBJKUSm00mHeC1Mqk2NSkdi4OCxK2k6GOamzSOoQB0USZQkU2SGhKER71NqaUpIQ0EIKUqKaAhKUDQlKYRClEohJNiSUplRU2HKZUUphNmkikUSkptdHOUpQlKi6BRCaRQBQUFJAIQhAIQhAJhEICiiEgcRCkoBRUpQEkwogKSChECEIQCTk1EukbIoaespyPFRQhpKR4okeKQE80kNBAQhFB3KlGFFCCRcQpBxVacJo2uBkKbTlUMcptcOazezrM+y4lIKsOTDzCm2+tZMBNvVUlybXKMXLu2W7oMldS2rCBlcZj5V9OoQpVmWnoKdVrvBV3bmFkSJXMp3Lxu5Dq5MklTTfVuI1mzKy1IBjKuNTeFRUM5lVLpAkRhIY8VGUSrpEy5AcoBBTRo3AkyEhhMOxsgoE7ZVqZEe1QURFRLeinCidkKqcCCoqxzZzKiG+KMJT60IeYHtRHrTKVTb2oqCEIRH6Rbc8ngEchKZfTe0EkE9eeFznva5zgNuczn/AKqAqOaCS6R1Iz5eS98cK3VGN5Kh9MiSHRJnfZViseZzMTyHmp06wOmS7MYO+xg/SFrdZ7JMqupu+NJyR1PX/r4rs8Huphr3YOZPPC5VMtc0M2Me8K2kDTHqkx5/Z4Lnn3jpx2Y16/VQNAGZkE4Pl/h71y7ot1wANok4Bn7FyvSqsaS5xE77GFMV3OJDpGcA9Fxxwynl6suXDKdosqBrxiGkTPmq+5cecDbeN0tQa2AdxzOfEqJrwCCAI5noukt9nnuvcPZAMuyMiBkeSp1BhkA5JwApVLh5cQI0kYVJdj40E533/wAFuMWT2XCuQ4QRty54mVpF+8Mg5A8dj/H2LnZEwSMe2PuSec5EdZGQmpVmVjdUuXVZcYOfaqSd5Ik525KprvMDVy+hSaTEE+2PFJ2S9/KTXOBMb7/4eSHNc4H1fGf49yB8bIXc4PRt3sPehoO/j/Eq5cnSuHF13Tzz6ZJ3EDIIVptqoo97pcKQJJdpOkFdjjdrQpvDm6NRHrlokHriJ9o3ysV/cOpsqWIuTXoNfIMYLti4TkBbxz6o5ZYdOWq57ANUmMGN4IK6lDiTqdo63DQXGBrHIdPGcLkz1aMc4QDLZBIGytkvlJbPDfRu6lF5fSqvaS3Tqa4gxHVUVSS+cxvk7oDNXSI2VjqThOpu8+xO0KzkNMxGmfvQ4H4pySSSt9tZvqOJIMZO/P8AenW4c5rfWk4jxWbnPDU475c0CdzmYz1VrBT1euDE5z+7n4qdagQ4nadx49FUabh1jGFuVNB5aCY64UXAATBgQDPVSY09fPH0IjMRGJV2zpFuQC6euCpRHv8AoUqGgVJeJpyNQa4CR0BOxMb5U7k0nV39wxzKJe402vdqc0TgEiJIEZiDlNmlcFphwB6R06rocI4je8PvGXdlcVKFeiZp1KbtLgfArDpMAnEgNgmMfuRqDWkmc4EnZS6vY09B2s7Ycf7TV2VeM39a7dTHqghrWt8g0AczyXAFV+kguOnIjqFW4gtGnBIzASkZxgZmFceyXvQ1xGP4hSLy0kDcqJaQJB38YiUyC4Sdic46LXUz0m55OJ+nI8PoSD8knJI2wlA5jpKbYOCJE5Hh0V6jpJxkRgmcYwoESQIxtI5K9tIuktO593ghzC0kE58vBOuJ0smj1fX9WRBE7fxlRLCRBAzuDy6LWWzzx4obTkyGz4rXV2S4udUouxMnxP0qk0ngbR4Sux3RcILTJ28VNlt3mQwnyCTOJ0uC9tUD1vJVhzw7b3r2Fx2evaFrTua1lXZReAQ80yGu8ZXLq2DWu2yfD9631ys9N9mG1uAKL2uZqc7AJ5ZWas+qHETIldR1nBdpyPoUfQ5MxPX96zuRdWudb0qz3EgnCvNSpbGC5wA8V1LW30MI0k8yAJws99ZurPLg0QTiFjq3dOnTqI2/FnUx8aANpK61pxpp+O7Ld5PJcelwpz24mTySqcPq0gXNaQN1LIkuUeuteJtqQJxvj/qttO9pu9WRA6Lw9vWuKGRkO9WY8FNt5WDiZd0hYvG3M30CnUpVGxLY29pVwt2VW4iTt1Xh7fitYDDyMTPs6LpWnH3NbEjz/wAFyywynh1xzxdytb6T4ROVifbjJgefNY6nHQ6SDEjkVBnGGF2lzZnmpMaW4tD6ADzA8h1VJoxUhxgea22TxdGQIC1XllopawBt/ilz1dNTDc24dakYOCQOi8/2jZf0zbHh9OjUe4uDxVfpDGkQH+MEOkL09XDHAbxJXke3dQ09NN4ID6LWxtggk/arb2deHDeW/wAHjeM31pc3ZpipW4tXnEgNp9PVYJ98E+K5rn1AyPRzQcDD2aQNJ5jK2V7qq2g21pv7m2a3T3dEaGu5EujLydyXErlVoGAAANl5su701VcmcazO8CD9KwO1T8YFaagqPnSMASdgsdQHcLm51BxcDklQLgfjNB+1TcXFuZPsz71XEIxUqlR1V41GGtEMaNmhRHxoAwiFJm+yiJMMZXS4eXlw0Mc6CJgSsFBjn1G02iXOIAHUr0XbLhtjwG8bwW1umXV3bsAvrm3r6qRrHJpsIMFrPizzIdyhejh47Z1PRx4W49T03Y68NtxGiCdMnQ4HGCvpgbRqS5jgQea+HcDuaj2UHmqBVpHQSd3N3a7zG3lHRfR33l1RqmHmMEeREr254XPCZM+r7YY5V6ata03AhYLmwqD1m59qwUeNVWxqOfErXT4015AqaQD0XDpyjw9WNZatGuzJEBV9/UZkyun6Za1Wn1mx4rJXbRcTpKTK+50z2RpXo5rRTu2OMF2SuZWoOEluFld3jScmQtSbZvZ6MVWOBkyIRLCCea84y4qNxJVzL54BklXSbjt93PmhzIXNpcR9X42fFaW3rTu9qd1mmkUz+ioFmCCAIPVOnd0nH1iPDKubUpuMy0+KbNMxp4lVuZn4vuW+WOGSJUSxrjATqTTC1hTNKPJbvR4khuEnWzk6l0wGmBMqOiFuNE9OeUGliITayOYaZyd1Hu8y4BdB1LBAAmVAsAxHNXqSxhdRGqYUHUfaug6njGVW+kWgkptNObUp5gKPd4W80p5KLqQWtppgdSEbZVTqQJ2XRNKAZ9iqdTAxGVepOlz30ARJVTqEiC1dN1LE4wqqjCDgLcyZuLmut8ZCoqUJnC6pZIyoGmOi1Mmbi4rrQTMFVOs/ALuOogqs0AtzNm4PPvs5JgKmpYneF6F9vHJVuodArMtp0vOVLI5kKh9ppOy9M+36hU1bZsHCvap3jzJtp5KipRgwBhekfawJAVVSzBHxVLhjTrrzZo+Ch3YgrvusZ5KmrZdAs3gxrXxa4j6Xgq3UyAutVtHtOyqdbO6Lnl6aNzmcs0/BQ7srpvtnDkqnW5HJcr6exv4sYCwwlp0+K290eiiaM8lzy4K3OWMoc3Q5pY06ohx3b5KDxOQtDqXgoGlvhc7xWNTPbOiPBWuYQcIcxZuDXUzhSIKmWYKcuLWtcZDdvBZ6V3FUHonCnCWk8ippdxGFs4tdUb2pTfS4fa2IZQp0nMty/S9zWwah1OPrO3MQJ2CywVEg9VLjtfCJQmDJQQohIThEIhIRCECAhNMpIDHNCEIBCEIEDKaEIBIiU0IBphJz5MmSfFNQWpRMOlBJjdQQqmk2uJQHHooIkzlVNJhxQcqEnqmSQhFmyJCjqJwjPQIiZyApPoubSZUc2GvnSesbquUpHOFQHCgnq8EkESgIKCq0ChKUIGhRQgmCJyiYKgpBENxJSBSKE2JZ6IJTpPYGu1Akx6qgTKmw0KLiYwgFTZpKEoSJQCYV2aqSMdEpSJQCEkpMqbXSRSlCEXQlBKRTUAhCUoGhKUSgaipKKBygpJlAkwkgoHCIQ1NTalCCowmFNhyhqSE2HOUkIUQJNM8k1E42RUkKEnqnqQ0ZMHZNCjqKBk+CihCKEIQgEIQgEIQgEIQgE5SQgEApykgYJQHFJCaNnJndTY/kVWhNQ20MqNG6vZUBWCVJr3Dms3FduiHAqUjqsDa7gMypd+7qVjVamTVWqNAKoa4kwVmdVfO6kKsFXS9TShVB/imHElGtplEKIcpAym1BEJTCZMKtNiZMieiiTPJJHJRAFEhWUym5gRLVDkgpvCrKIZ3KREjKkdpSQVJkypP5KCI/QDWuYQcTImTyUHMAzk+ByupVtpA0kjoRjZZ6tvAMmG5XsmbGXHYw8yGQTsOikQ4k6SYHU7fx4K17CZHPHPdOnSLiWn2dVrqYkVte4ZyfFaKdV/ItiIAHSdlA0HB8SQCMfx9yZbDQCJJ3BM+eOau4ml4qet15npE/epagQSTDifaqq1Rpos0Ug17Q7U6Z1T+6FQ1x0ggnac9EGtlURggCPAqJIOPoJWXU5rZJIMe6doS72o12nd3nOU0bbDBO8gdTuf3ck+7GowfWn3/4LKK5wASDMeR3P8FSbdEDAABHLn13Sm2ptOXASZ354AymaToHqwG5geKopXbtQJn38/3rXQuWwAQHY5/xup4WaRbRfMDJGOuQrDQLxqLSB9BWm3uqbnaQ3EgE4weX/VbqFWi7IETkSsXKumOMrmMt3iPVHjjH/RSaatJgEwIgyevRejo29CpERmZ8Z/iFC8sA7WQ2I+Kehj/oFz+JPd3+BdbjzF7XrVSGkuJHvWWTqmCeY6QvQ1uGtLjiPzjJlc+6se5wI23M9fLK645x5s+PLzXMY0xkk4kZ/iEAQA4DMYgbrQ+mAXDwwc/9UMpajybIlders59Ok7esWkAifHl/H+Cu1tJ9XBPP7J8FD0csAfH5vLzW/h9JtV4a5oE40zusZZSd28cbldL7Ks1jQS31dirLq4pvmOmTGZXo+D8EtbhmqpBJnY4HsS4x2et6LC5nIyN+X/ReL4+PVp9T/Rcs49vHV26nF3IYgcx/gsj2O0kkQYE+f8SV26lkGOOT4yq6tBurSQCByMzPmvTjm8GXHXDdTgnERMf4qDuRgxI8fauhVpDk7J3MeKg6g4Aw2dR9pwuuOUcLjdufBkRgHl1ynqMbycbFa3WtTSXOaRG5iVXUoPaHbkjcAbLfVKz0p2xZoLXRkbHqqKxBcZBmZ290KQY6Q1owB7/FQeHCMETsSJ/jmp7re8QBhuDz32TYCJJOcySjJAEE4ggDZDXFsesAZyP8eq3GGt1q4Uu9cYkbKl7cHnnpv5Kx1zUfS0OMtBift8fYqdekSZ8ZPJX6JCg78t8HkgRzlSJEjck/vKnAMGDpPhv5KWjRavpNABHmYVFwZqk42kwcT+5SptJIIGSduik6lt63LeVmalb9mX1jImPLorBOrx5KbaRO0iQN8+X3JijpMn4pxB6c5/jmt9UY0bIJI5jlMrp8CrUbfiVC4uaIqUqVRr3MIHrAGSIXMnSMzI+hTadPUHIKzvZrs+6/CV2+7O3nZStw3gtYXFW7AkChDaLA4S0kxnmInYzC+HVjNQxIBJjmYTe92QQcGS7qoGSSI/6pOyTFTBBDTg9FNo9WYj2bp7y4YESpBszERq29itya0stG97WFLHruAyYG61cRtjZX9W1rOpufSqFjy12oSOhWZrM7TB2UjloBILdp6ps1VlOowbDywpkUnRIGFmNMQDqPjA2HJINeyCMYyBzU3DS42FJwOnIPVUv4U2Q5o55VjHvaR6yvFw84ggDPtU3Yajmv4W5vqgGY3AVdTh1ZjdWfYF3aNaHEHI3Jjor7mpSe3JBnGFm8llbnHK8r6G+TyxJKvoWp15MiF06ga2ctg4lQAGwgYWuraTBt4XWbbiTMrZecSbUtzTaJJ5EZHiuS0+YIxKsphpeNTpziVxuM3t2mdk0bgTScYdt0Xi/hPD28cfbk/wA1SpMMbAim2QvpBqWtnwu5vK5006FJ1RxEEyBiPavF23BeIdreMm8FB1S4uoLWfmUacDTTA2AaMk7uJJK9Hp+G80vtJ5e/0Pp8uWZa/L9Xzd1CpUJ0MJUBwm6qU3a9I6aQT9y+80+wnZrg4aOP8bayvE+j2zNTh5wMK8M+De00NLeLVC9oc2IEg8/Benj9Jw5TtMr9J2fTw9Bjfxv8n5wqdn+IMe557uNwCSCfeFVU4VdNBBYD5OC/SdRvwbXTS0VOK0s/Gw6Flr9jOxfER+Q9p6dNztm3dDSJ88LWfouH3xyn1l/Rcvs/D8/6f4fmupbvYYc0g+KofSEL9A8Y+CHihtnVbFlrf0icOt6sz7F8+452Hv7F7mV7d9u4fm1WFv0ry30Mz38PKV5Mvs/LL7llfOiwpAQuzxLhVzamH0nNH0Ln9y6dl48+DLC6seLPiuF1YppODXgkA+anQBq1u75ApPpOgha6VC4tW0Lura1WUrhpNKo5hDaoaYJaecEQY5px2TLuY+e7u8KtBSptb+e47Ecl9UuKFGtUqw0FzHBhxEENaD/HivnnZCkOJ31tTc4Bhq/jHbaGNGp7j5NBPsXrext+7idpc3dSmWOubqtcNz+Y93q+4ABfc5+melx6fe/9T/8Ar2+uxl9Hj0/j/b/+tVxw5hwBGcGI3WSpYvYDDTvC7sTg481BzYiJAO8r50yr4HTHnzQrA+rIhdfgtnUrP9cmOitdSI5ArVZvNCoHjbY+CxyXc7Ncc1e7RdWFJrDG8c1yKtu0kwATtldavc964id1jePXIIgnYLlx7nl15Om3s5fobXu6DdI2jBs3Mc10duRB5gqLhyjJXaVx6Y5Rt3SSMJaHMGIXU0gNiMndVvpySAJHlC11M9LCC8OIGAQpsquAxOfYtD6QOI3UDTAlvNTcNG25c3JJV9K7j1pxzlZDSABg52UCwjnCU7uvSvm6WkAeIWunescP8F5/I85VlN7m/nFZsbleiFWjUafNTLaRdyC8+Ll4G5HVWtvHtwHTK52VZY7PowJIaQZPNQfagj2SsVO+JcD9pWpl/tOnf6Eu2uyD7bGOqqfRIEEFbW3NJx+M2SFLVTIMkJtNOYaI3IhQqUQM5yuoQ2MbhVmiHEyr1aOlyn0vBVPpdWrqPobwqTRO0SFrHJLHMq0zpwFU6meYnC6rqUyIVLqWSNMfatzJm4ua5kbtUCzq1b30plU1KbjgKzJnpZNAg48lDTkzstfduHio6MZC1tNMrmQoOp42Wvu+RUXMEKyppifRnMKt1HOy3kCDIMKstnmPatTJmxhNADkq30BvC6JYOmQk6mDgj2rcyZuLluoGNlU63yTG66rqUCFDuxORurMmelx6lqCJGCqX2k5XafRxthVmgIK1M0uLhVLOdgqKlpGSF33UMqo28/4rUyjPTXnaloDyOVS+0jAXon2wnAVT7Ybacq7lTu84+2cJwqX0CBML0rrXB9XKz1LURGlS4ykyseddQMxCrdRHRd+paEmYVD7M7wsXilanJY4hp+CXd+C6lS0I3BVRtiBMLjeB0nK5xYRyCTmyMRK2voQdlWaPULnlwV0nKz1hTNRzqdM02HIaXTHtVekrU6kqzS8FzvDWpySs+kJOaVf3avr2tJlnb3DbuhUqVnPD6DNfeUQ2ILpAbDpMaSdjMYXO8djczc8jHNR0rRpnko6YWelrqVAJaTzCthELOjqVGRyQVqZba6WudlQWqdK7QAlELVZutKbbgXVvVrF9EtoFlbR3dSRDzg6hAcNON98KlzA7U4bDdTSqoQpQqyE0JIUdKbG5kpoAEJqdyKbqxNBrxT5azJVMJoDt0IhEIAIJQRCENG5GrwSQrs0CZQhESrtLAiT1QhXbOghCSbTRpJEpEjqm10aiSm4qJRYcqMyU0iopoQhAIQhAgmkUBAykU0igJQEkIJIUUIJIUUIJJFJOEAEFNRzzTYEIQgEIygoGEk2oJhTa6JJOFEbqb2RMmEnFAQmzZAyiE0JsCIQhRAhCEAhCEAhCECEymhCBOQ3ZDkm4RfYP3SQ5BQCEIRQhCEAhCI8UAhCEAhCEAhCEAhCEAhCEAhCEAhAQgAEIRuFAzkJBCFFNroKsDsYVSGmMqWLF8ptd0KplPWVNNdS4nOEifBVF3ilqKL1LZSUQ4dcpa8JpdpSRsh1UjBUZlRcJMqM09fVGoEqtCI0IOQoSlqKa2G7BVSmXlRTwlfqiraPaHFzHTvt9Kw3Nu5gLiNiCNjPmvrnErPhhpVXMZSAyRkYC8BxpluyrUbTLCQYBB25z4rz8HqviXw/Qeq+z5xze3l3UgDttyGfJaOHVPR7mlWa4CrTfqYXNmCDIx5gbqy6ayC4YA94WHU5m24jY5K90y2+PnxdFa+P313xXi1xxO/qGvdXNQ1qz4A1PJkkAbDoAubVa5kEiDGHDkt1kGVaw7yIGfE5H711b+0tWW8giTvKfE6box9Nc8blK8s9oAOkGeU4jlKgdTcwSMYO/l7FpuhGogcpWZ0SQPZ0XaXbyZTVMadWSD1j6UnE7wJWyzsX1wXNZnzVNakWvDS2IPTxVmU8Fxut6UunTkSAc+sm9suMmOUeSeC7DJ5R1UmM1fF961tnSLRiDI8+WVotqFWq7TRpve7SSdImANz96i1jhqaM5ONlusn1KLpZUfSJBaS0wdJEHn0wpclmO1Labmv0l0QJ+jZbLKk91VoLvV8fH7lToceXOVZRe9jg7AzEjEeK55XcdMMZL3ey4Jwt1UCKg2gQZP712rngPdUi9tUlxE8l47h/G69sxozAg+a73+cd0+zIqggFsCHRO+49m6+fnhy9XZ9zi5/SzDWXlx7576NYtJAgnJ+zwXPrvFSMCDspcQfUruNSC8aiTlc7vYwzUBsOa9uGN0+Ry8vVeyVdm7oDcclTTcWYwtDqwdAAOdhHLln3+5VVGhzJIAjbMrrPzcPobq4IiByjwVlu8sdPXOeeVjcC10O+3KmxxYZgugdNyrpnqsr0VlxW5onVTc9rSOfT9+Frfxivcj16kk7QcfSvN3NyKrQGgtAAG+8DfkqmXL6eCTAwuN4cfOnqnquSTW3cua79XLeZPMfcsNS5c8YfpJ64KyPvNTCA0AkET9qpqVO8jS05jn9C6Y4OOfJa1s2JdAMjB3PhMKxtRgf6xwM7+zPjhYe+0Ph/Xr9Kh32pxwJzucLfT2c+vT0NtWt4gwc7Rvy+xKu+3ILdQMAwPDkuDTbUI9Ukg+qfHw+xTa2uAWOcNWJzzWLjp0+JueG+qyhJIIIG55rNXpMdJaWgnbzWa4LmOBJJkSCPpChTuHbEgGZwuuMccr3XPoTGkGQf42VfdOGADgkjCmLmAJ5exXCsyBtnGy13jPasr6TpJnJw5VlhGDuSY/j+Nl02mm9wnMbKfoodTcQ4ZE/xlTqXpckNl0N5bEnqpskGRzIWp1AgnGBnH7lDug18Ez6x2TqTQaJBgkGNyhoOJAI2kjC0Na0Nz5ZGy7fAeAM4i11QugAwMSc7AhTe1rz1OQQ52ZEesBOMZ/jaFYXl3LAj/AKLdxnhjuH1gwO1N1YOxCwaTufi8s5S/iSm0NjEyOQwoaJMAFx281MNMgk88wFaxrRgEYOMKyqoaIYACAIDlIUiR4T0W+2tdbhqB2MBeq4L2QuuIUTUoFmnlrkT15dVy5ObHDvXXh9Pny3WMeHNOJk+rzPl9yiGnUC0EkiZ5Fe64t2Ru7Fmuo1hafzmn964dTho1bEkyCVMOfHObhyenz47rKacF1QhkQR9Ki9xMyfWE4nAjK67rCHu0jT5fxsqncOMtyYA6SusscbK5oqkERufD71ZTrEjODnkr32Tmu2PjIkrPUty2QdyJnqtMrGVRt7Yxn3q5tRrQZxJ581iLSY1TE8+RS0wHQdxvKeR0w9hb02gzsrdDTT3gk7LlAkTmOcK+jcOEiTlvPos3FuZJ1h65BdI5FViQDg5E+1En40wgerh2BHXZRYkHEiCc/YpAxMEk+SrcTydEpjLo59FNCFzfd0DRrNZVo1W6KlN4lr2nBBXueEkdnuwdo7hQbTr3rX0xXfl1MN+K3/FeGuuE1bpwdVqtoUokv3M8oC9d2d4vwpnZ654F2iLjbgGtaVqZmagHxQRljj4iMlejGak3O25t9T7Nyy4s98k+W2b/ADeF7Q3b6dw+3Y7W+m7RVe6oBqqfnAu/OIPISuMyxvap9et3es/JR+25h+heiZa2DXmpccQcQIhlrT0GP0dbtgT+iPecmNYcO0mna1RYtO7g11Q/Sc+9fdvrLJqXUfa5vXZZ5bl1HDdwm6bj0ms7G4ZTAHvf96PQ+IUxLatRwaMAspu/Zqk/Qtlxwbh9zIf2vvqM59Swn/8AIsbuzltTcTb/AAgXzT0fww/dWXO/aHLL2m/5z/Ln/q+THvP7z/LTwzi17wm5p1qpc0NeHVA2tVtjUbzZqIAHnnZek4b8IvFDRNDitvb8TszMi4YHwOQ1t+0hePq2t5ZUy7/PayqMAlwu+HPa2PFwJICxU+I2tWoT3/BL87d5YX+iofJtUNJ+cs31fBy3+Nh+/wCVbnrscr/Em30O54X2J7U0yLB7+CXjhilVh9F58Dt9i+f9s/g1v+Ek1H0e6pky2vSJdRd7d2+3CvoXVlUrdxTvWULgx+JuZt6hHLJw7zkgr13ZvtHxvhdRvDrgU7q0q4NreeqxwPMOO3mCR1Cmfpsc51cWXVPwt/tf8umXHx8/fC7/ACv6X/L4VxHhVzavcx9N0t35T/h4rAymdUNb65MEAZPgv0pxvsjwTtJaVbvs2zTWpt1VuG1HtD2A7upnIjoRLTsdJK+S8Y7N1OG3TqjKRBcSJLYJLcFsfmuHNpyPEEE/Kz9NMrbj7eZ7x8vn9HZbcfbzPeOBwOKPplpXrGgK9s8BwPxXRHLwJxzXvuxLW07qtaMpvaLSiKQDuWIE+OJXg6tuKl7RbIYKjw0kjbOV9O4HaC2bcXrXuL75zKpDmwWt0+qD45JKtzuPH0/y/l5eXm5OnhuP8nRgkf1jv70nMAODA5oeZzqkz0T57heZ8vW/JaYMkj9yQ9UgAzzJHJSOkmfeEGCdhHJTy0gRpHjuAEOGox7ThSduSMDllVRkgED7EhQ6JwokGZ57QpHmreG2rbziNC2dUFMVX6S85MATgcz4c1rHG55TGe64Y3PKYzzWeCcyMZhQ4hVp8PtaVe7Iosq/ELyGgjrJgfTK852n4yafEHWVNtxT0vcCyjUcyrSIwWlwI1OH5xMMa6WgPIJUeIdobLjPZPh3C+I1Q/iNqH0Je4NNSiyDTLnfF1iS06RJ0jxXfj4cd3HO61P+/wAHt4vR425TkutT/t3Df2LrWjd+mW7qNcHTpeDEGPWIwMq8NnILXAj1S1wIiN5C+YVKjWWVXh7X1RaOqd6GU9LW6iAJEgnYDnCDxnjNtTojht/XpsogN7tugNxtLcAjzC8uXJJ4cM+HHzi+m6Wxj6U3N3hsQsvAeJ2/GOHtuaTHUqrSG16Lv6N8Tgjdp5FdLQHDJjISZbjz3HVYjTB5IDPBa6jS0TAMKqP8FraKe7G5BJSLJGMRzWgaZyTKtFNrgWjmFLdLrbEAY8Ea346LoejEidOIVRtSRgRCnVDprMKj2/nHyVjbp7STJjxUnW7wYgSqn0jkQm5TVjVSvJb60ytLLoaYnzXL0QrGgjZWyHd2GVGuZkp/izJEBcpjngblWCq6PNZ0u280gQIgHqoOtyfEx9Kyi4c0bq1l4ZgqzYg+3I3GeaqfQxkLYa7HYnkk4sIjmrKywdyANs/aqn0g3JaukWjaSk6k059wVlNOTUp5wPZCgafq7LqVKIJwFU6j4ZW5kzcXKdTIMlQLQTkLpvoneMTsqalGTtGVuZM6YXN8PcowY23Wx9EgKBYZzyWtppkczGCoub4StRZz+xQ0OLse2VdppljOQoETIiFrLDEAKp7TEwVZkzpm7spOpDaFo9hQrtLGN1LJhQNEHlC2xknkgsDlraOc6gdRxKg63BOQujoHVIsBnZXdidMcp9ruYhUm2icSuwaWVF1GRsrM6x0uI+3BJkEKl1oCSu4+gNwJVTqHgVqZp0uDVssqh1kROF6CpQzlqpND9IEfStblTTz1S0OPVVD7R07FekfQBJlVOtgf+ialN15s25B2Kg+jnZehdZgzH0rPUs85GQs3jxqzOxwTS3wq3Uz0Xbq2hCofanpKxeBqcrkFpCjoMLpvtiOW6qdRhcrwOk5WQFwbpBICrjxWt9LlCgaZ6LleFucihrC4EgYCrc0ytjS9jHtaYDxBwqXsJ2XO8VamcUEKEK9zDO6jAXO4NdSrSUQrCEoHMKdLW1vDDZMvqJ4lTuqtnP45ltUayoW/1XOa4AzG4Ky7CTvzUyEi3xU0sqKiRBCsKjoMyhtqoUrA8LvKte8uKd4w0/RaLKAfTrAk69T9QLIEEQHTtjdYwMlar+2NtXNHv6FaA066L9TDLQYB6iYPiCs23IrOl37IbypFJzeajCaTukUIO6CfBNNbCEJIbNAaXODRuTAQcIChe5VWFji10AgwVWpv6clHSjJIRGSiFVCEAymmxFEpoTa6KUFNIps0SEwhyBKSjqRqQMmE0pRKmw0hkIlEpsIJzlLr4oIECE2GdkT4IJkJJs2DlBQhRADCEIRTOQkcoSJhBKEkgZTRAhJzo5Ja/BBJCQdJiEyYCAQo6vBBKLpJCWrwRq8ENGhLV4IBlEMmEpHilU5JIodkoQhFCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIKAQhCAQgITYAhCCgEAoKCFLsRQhCyoQhCAQhCimmD4KKEQ5TlRQm1T2SKQKCrtdkhCFkSSlEJLWwyVFMpLNH6hdx2+fH5S+DvnkOXkslS9qVHetUkxn71zdc+tJHUT71a0Oc0yQYO4O2M56Lc4sZ4j331GeXmt9B7XtbLgOmcqm4pgZaQDvn7EUaT3VIa0wfzV06fB+I1qPeNtqrmjEhsyVLlMa1jhlyTtHF1FplpztCm66qPZBcS3kD0Vl1bVKTtL2lsYEjxWSpJnIGYJIn+N/oXSay7vLn1Y9jMPhpIHkeaocwsdBdLtj96tY9zDIdBzBhKHOfqIJ5+fiukunns26XCr/0cOaRqa7l4qi9PpNQ1BILjIHP2qNnpLwHYaDnpstzzSZWa4RgSfNYva7dpllnJjfDOeHVQwuLDpEDBVZYNJaBjp5rt1L6iKB9U6oiFx3v1OccCdsKY52unNxY4a6btopGrVpNt5eaIeXhgOA7afctlnYCo8NIJ3kbeH3qizc0N9bBwcnP+C20rvuamtri3lKmeV9m+Ljw85PRUOyDqtvrNbMRqPPzXCv8AhDrWqWtIbG3LH713bPta+nbd04NMCJH0Fci/4u2vVNQ48JnP+JXk48ubq+Z9Hn4/SdE6PLmPod247kjI6K6rXDmBpyByhU3F0CdsbrM6r6/XJPkvZN18fkxm+zf3je65z0lY6LdVwdZ1EEvIB5xCofXIJABBz5QoekuafziOUGYXSbcMpG2tbuJ1M0iDyHXxVGh7ZBOJ5K78JU+7A1TJk+Wyst6jK5Ooggkc/YPJN1uY43wwvZVfyxGD9qhTbES7GQdJ/jxXWuu7A1M3xy38lkc2kGk6R4DqVZkzlx6rM1rNIkyQMzzwQqqrpJGIGx/jmpudBc0biRIws7zLoE4PJbk25ZXQcQZJcM43VtJ4AIJ3mcbysxcQYBkRnxTB0nAMjePo+hb12Z20vBLZOfEjcfxCgMujOd/46qbaofSAcMj7PNVd6A+QMc/FSbO3l0rWqKdP1pEEjdU3l1+N9Rw8+ZWWvWOnG8TtOVmLiHGSM52ScfvVvJ7RtNQ1XyAdUSBzIRVpBrQAwN2gqq1qfjAHCYyOgWu7rtdTAafYEu8bomrNsRcDMQfYrKRgHSSTtPRVGQ6Ihxz5qdJxAGJGSF09nNrtQS+HGei7FBrRTAIz/Gyq4Myi+s0VIIJEr1tXhtiLPUNEluXY3Xi5eXV0+j6b0l5MbZfDzTm0zktEx7/FVOose+QZM7Sq79wp1HMadQA6qFvW0O1TkdDC3L22891vToUuHFwluT4HZdrgNOrYy1rgQ8bEbHZUcDuKbqzKVQjeJI+9fUrCx4a+wDhQpvAxLhnzXl5vVfCvd9Dg9BOeblfJ+PU6tzePqOcXN5TsB4LlehuDhO2xzgL3vai1taVcilEDETif4BXkrh/duDWk+rJBPOSvRxc3XNvJz+m+Dl01ip2ZLskdPapPsi0F2kmBiVpbcsFSPo/j+MK0XNNwwWkj7Vu5VymMYaLu6eXn1djJ+xe67L9r6PDqXdXFN7m7COnReQqta7YCRAEKvQ5wBOD9K5cvFjyzWTrweoz4LvF7LtH20t7xmigyAdyRsvKVeJ0nVDyJ3jY4WWpSdpOr2qp1kS4huIGCSrxcGPHNROf1WfNd10Kd7bvLciQFaK1Ko4ubBkyI5rjGyqtPqHnOdwVW1ty3B1ExjG8rv0vP112y2m9mXA/wFnrWzHu6ZiI+hc11eszBn9yBeVgdUkNjacea1Iza1O4admiSd5CzVOH1GS0scfMLTbcUdI1RMyto4hbuEOAJ+xLbCSV5+rQfT5SoEernEdV2Lx9B7vUaJjJ6+CwVQwYnO+B9CsyNKvWzkf1UOJwInzRDg4OOQNiFi7Q3NS14aXUiGVKtVtNr99MyT9AKxbrvWsZu6bDcULYl1xVawj80nPuWW64/Qo+rTc2mT+dAleF4jfuoh7mu1Od+cclcWvxF7XkFx1nJJ5rn8X8Hsx6eOae+uOPNknvHOP6RdusVXjrHEySV4apfVHOw8pNuajjuSnxMvxa+Pp7J/HHkkCR7VE8ZcTJMrybbmDvlXtrOIk7KfEy/E+PXoncXPIfSoni7ukHxK866tzaqxWJeBOOafEyvuXnrocZ4zXqXHc0arqegAvLcSTsFx7yu25cXXVGhVfv3jAKdQe1u/tBWWqyvrqVKj2NLnTGsT7lnc5wMOk+Sz9XLLO27roMuazaLbc1TWotJLGPzHUAHY9QNxldXg3aG+4bSAoVmut/jdzXHe0HebT8U/wBZsELzzS0slxhroa882n813sUmPfSqubOl7SQ4DYHkR4Fax5Msb2reHLli+r9mO09CreUrjhrn2F/T9buBV9amf0qZ2cD0O4MElfRuJ/g7tl2WuuMPt6dHillTa7idGntWpCYrN8QJIO4Icw8l+YKrqrNJoOcx0d5RLDBpuGHAeBGYXo7DtVxJtrUoXV69xqU3Ui62a41HNcIdOkgZ5jIPMTle/H13Xq5/eni/pfyr6nH9o3KT4nezxf0+j0VjwRlXt1UtXva8WLnu0ASXBoB7wjkCXNaP73Re1cx2olzcndfPLXtdw62vqfFD2asmcVZl18+4qB73REljSRBG42K7/BPhapU7v+WOG2V1aERFjQdSqsPUF5IcPDHmuPPzY5524+N9nzPVScvJcsO09npDTcPzT7VEAtmANl7zstc9nu0/A6PFuEvbWoVCWOD2aalJ43Y9s4cMeBBBC6LuAWBBHcM9jQuHxZHl6HzEjcGfcgADO8r6K7s3ZudikyIOSubfdm7ZpOn1CB1wpOSVOh4lwg/FUTOwA9i6XFbIWj3NDiehXOIjf2LcqFEmVEAbOKkZIyZ5LDxLirLC7oWjOEG/q1mF5dUuXUmNEkaW6RJdgkkmAIxzW8MbldRvj47yZ9MR7TWYvbepeii+44iAylT0kTcanBrW1Ccy0uB1jJAh0wCvFdpbShZX5tbQsrikS1tRmBUjBcI2bIMeC9Zf8cpHhF/UFvdWF5b0tbWGK1Jw1tZqbVEaS3VOlzTkbrxDK7axvKpMttaTWyBuSdLfYGjbqV7ru8fTyTv7fv8Afh9edd4+nlnf8fy/f9nNuO8dOqoB5AlZK+ruiwOa6eohX3FK70y8tt2+Wp/t5BYazeWuo+Oc/uXyuSPFlHR7McVd2f4ib97KpouAZUa0S17JzPluPFfY2FpaHNfqYQC1wyCCJB8oK+CCtWpEhlWo0HcTuvqfwZcUfxLsy23rP1V7CoaLp3LN2GPKR7FjDL2cMpHpn9JkKrbKtdzAgKgkfnFeiOGRgiZwpNqhpkKhxyQNuqNWOuFbNs707NldUnBofE7FdAU7d4EQPavLa84kLRQv6lJoBMgLllx32d+Pmk8u5XtGRv5LDXtY3WmzvW3FM52zkqVWoxw3B9q4zcuq9dmOU3HGqUy2Zj2qouLATPsXQrBpechZa1MESu0ryZ468Km1mQRKfeM6j3qo0xuAqXYnC25NgIIO28pgiNwsIqODSJx0KkK0ATPsWi1r7wcmhTZVIJd9CyNrtgEQcqYrNKI1truLpmPBWCsC31onksYqN5nKDVHVNJa2962MqQewwSsLqk7TEpd4Y8lek26Oim+SD9Kj6O0iTErD3pgAHbmpd+8QZMq6ptodbZiFU+1BxEJsuncyZUxctPLKd4nZjqWwAOndVdyYJB9i6Bq03HcJOLCPVxyVmVTUct1BV1KTh5LqOY0gnCpqU/atTJNOWWCeYUDTgYldJ1DEwqXUTmW81rbOmFzcYUcxjBWp9MjlhVaHDYKypZFJ9iTxIjkrSwgzsov3hXaaQBnc/wCKgc7YUzIwR4KBGMCD1V2mg3fkEGANhCNMHJkKRHgqyrNJrxPPzVRpg8tsK8joEFWVNMr6AyQq3W0jbPKOq2Dc523QSCRIAjphXqsNOYaJ6KDqEgYC6j2gknaR7lW6k2fDmtTJOlyKlAcwqnW4iAF130JzsoGgTha+Iz0uNUth+9UPshOGrtmjvAEKt9EZAC11J0uDVsuYCqdZnou8aQmDMqPdNBhXtU8POVLRwG3NUvoEDZe0Fvwh3B6rXUbw8UNZppVGvaKDaUHUHNjUXTEEEBcmraDzCz0yr1WPNvoneFDuj0XdqWg6brM61IJwsXhjU5K5Bp+CgWOXVqWx5BUuoRyXPLhbnI55aVFzDK2uokHZQNMgSuN4G5yMZakQtJpnKgWRyPvXO8Vbmak5UXNlX6IKjpKxeOtdTOWlvJAbPJXlvVKBKzcWpVQblbuJ8F4pwy3sq/EeG3lnSv6PpFm+vRcxtxTmNbJ+M3xCrrsptc3uiXDSCZ6qziPEeI8Qbbtv7+6vG2tFtC2Fes5/c0htTZJ9Vo5AYWdU25pEGEHpEK3KiW+KaWVFpB3VtUUNNPujULtP4zVEAzy8FXpjZAk+CzppBwzkJIISGeaIXMoQUOBBgyCNweSigJc0BOFVJRAHLKYGSlqPNFSUU90QogCRyg4QgUIIlNCbQIJgKOopEyouj1eCerwUUIJoUQUShoy5AMqKbUEkIBlImEQ0HCjJSRdJoccJE8lEIQwYUgZUE2k9EA/dJByhAJkyEJIBCFLV4IoAUU5SRAmDCSEUyZSQmECQhCAQhCAQUIQCcYlJE4QCEJ/moEhBQgEIQgEIKEAhCEAhCEAcIQMIQCEIQBKSAhZ2uktkSkMphaTsSCiZQoIoTKSyoQhCATSQooQhCihCEIgQhCECJSKEU+SJQkgChCEH3+m6QDuP8dgu9wq3ZUYBMkwAAdMD+PuXl6VaZJJxOQurZ8Q7lkA7c95/w3XXkxtnZ6vTcmEvzPU2dO3t7ppqAEDeRzX1HhHEeD/g1oNei1umCHOgnEHfK+C3PFH1DM88CZVZ4nWAgVHADlJIPsXh5vQ3m819Xh+1ePg3Ji9321r2Fe6e+2c2CSIAguAwvD19J1AYnGP48Fnr8Qe5rg6oXEbc/YqDckuj6fBezh4bhjrb5fq/WY82XVJpqABiXAdMq5r2ticzHJc8VRpmTnZI1zIIjx8V26a8nXI6TTpyC3xwpmrJ3O8rmtuDJDjHVX1K7O7GfYnTVmca3VQ6QY3jG+F0OGUadeoJ/Ng5ELzbq5dMYEwcclt4devovw6D481MsLrs1xcuPX83h3OK27bYhzHRM+cLmmq4mdURnKrur2rXdkk8lmc92SZH+CmGF13a5ubG5bx8NprgQC6IGMqLriDlxcY9vvWA1XSJiN9+quq1GaAWHOMcvaF16HD4lq81nFpwZgkDlz5qdFxeR60+Q3XPFSSCXATmJ59FNl1pB2kbeOU6U62qq6Hkg45kHH/VVOeTJA5wSAqKlzqgCB48h+5V06giZ5xM81vHGsZZL2vcAM4z7lOjc1Gk5AI8eqhTLCJn1cnf+N0QwmXGY3W5jGOq7X+k1XfGJPjCDWdqkO+/PTzToinMlwifYJTuQwDU0wCN/uV6InXfdS55Jl2c7+KQyZgGNyoOd6xGWxjPJSp1YBJIOM+A6LWk3tJmNyCANwm/B2MzEAZCi58kAEYGfu+lWN0OGXDUd8ZPWFNFUEOyB4bKymwuwyS7l1n2odAPqmZMyDhXWhb3w1tMTlvhz+xaZtejsOw/aK+4UOLWvD6jrQgkOJDS4ZyAdwY9y81e277aqaVamWPZgtdgg7efivvd/wDCVwK57MWlvw22fSqMosZ3MQ6mQwAgnYiRuviXG6z+IcSuK+zi4kjaDviVMb23We+9OXqhs9Bkyujw227+oGudMbiM+1YKjXNdy35/ap21y6g6WnHLmen+Kznuzs7YamU6vD0Vbg9vTtzUB5GT/HNcGuwU36QcAxhX1uLVqrACdIiCQ7MLA+oT6znTMyf48lz48c5e7rzZ8d+5Gu3uH03EtkHG2MfwF0vwxdml3ffO0+eff1XEY8kDaDGSNp2U2uBAd8bEAnl/GFcuPG3uxhy5YztW2pWe8y45mR791fbVA2oKmQQfpWAPOls8gJMz1/iFY15naICnSTLu7lGvo0aXQ4Zbnz+jxXUoccv6NLu2XFQMDdmn7ByXlWVSTEjxHit9Gs9xLSfp2zt9q4Zccvl6ePmyx+7XXq3taqIe8mTnzUQO83yCOfuWCoajKZfJkDkISpX7w6Dgc/FMcZJ2TLK2/M3VbRpLgZGIKzii/OiBq26kq0XhcwkR08j/ABCq9Oa4kF3WZgLcrnYKZr6uWQBnn/ipitVG7TmBB5KdG9pmJMdMKwVLd4id4VRW2scdT0xKmKpJ+MA0HBWmjb0qg1sLXGd038Odp1ATPim4aqu3ugdMgZEkH7VpHdvOQSPzeZJ/csnorxVh4O557LuWNjSc2WvGqZA5K7iark1LKk+IAg4Cg7hjdcEQDhd6pZAAtbGkjJnHX3rPXtn08iC4bqzJLi5FXggcCW9NpXLuuE3NJpLS8RkgL07Hva4h0YPvWumWOYRUZhTrsOiPn1YV6Yc0zvnH0LP3zogyMwvoN9w+jVaYYAIgid1zDwCk95I58lqckZ6K83RdrbABjBOFzO27aX4Lo0w4eky64a0HIY2GOd5S8D/ovpvCOytGs0SYd0iV8n7Rvov+E/tlaVKbzVsWC0tgXg02W9J1PUAObnOeHTMfG3nHDPmmV1Hq4uK46yrw3F5ZaOccOcIErm3g1WtrdD89ppu/Waf3ELq9oHCpVcxuzQuYPW4PUoketTrd43yIgrJn5ZrRmuuG+K0vLadEgZeVXw5pFy2YVly0yequmVFIky45hW9+SzEwDBUabCLR7uZUAD6E8gZDhKBiuXS1UvqkOcZgAEqZZpqB3J7ZCyVw5rSevqlVGfWSZ5qTXnY58FDx6JxneDuERe2ILQSWuG6ldOg06v52nST1A2VbHic4B+gqF2csaTkSo0ffQxsgENJOfHdSdf1yIbUe1v6LPVCzBuowcrRZ2/ePgkho3jdEltKkLu8rCjQZLju4/mjqV26HArDu9N1UuKlU51EwyfIckW9YWzdFNoYz9EjdWi9Y6RDqR6tOPcs9LpLPd3uzfHO0PZe1fZ8F4jdcPtKlTvXClRo1ab3xGo6mE7Y8F9B7K/CfxJzRR4063uwIHpVtT7t7T/Xp7EeLY8l8hZeVaM+sHN/SafuVzL+g9wc4EOGz2eq4fvSF1X6Ho9s6DmamVWuBEghRr9rLaq3Dmu8CNl8MteKt1tpay4ES53xS0ePiuhacUo98GPu2U3Eaoe+IHidl6MZx5PPl8THxOz6Jf3gu6rqg9i5z3gkjpyVNhUFS3DmPbUBGHNcHD3hWOHrTBDgrqTwW3Rlw0yD7Fnvrand0hRrS0h2tjgfWY7qOmMHqJCu54+zqk5sgDJTx4XHK43cfO76jxOw4fxW04lqipbhtJ0+o8GuJI+c3xXR7D8JF/Y17lr9AqNt2zBcC+HkgAZcfV2HnyXrrqhRubd1rcU21aThJY9shcC8tb6iKfYbsg2pVvOJmpcVWD1RaW74BZr5NdpcXHkyGA+u4H2+m9RrKdU3qf1/e31/RepmecmU3r2/Hbxva2vw3hdb0Wxqm7uD69StVI7thdn1Wj45/rH1egdGt3Bo0+M8QpmrQt+K3TTs6hTcW/VC+42vYvs52PoHvaDOOcfI11rm5YH0qLjn1WOx7XBx542HI49dXt653pF3XDAIa1tUwB4RgeS5eo9LnjerPt+S+p9NcMr1dr+E9nyKvw7jluNVbh3EGNiSatu6B7SFp7M8cr8E4tS4lSw1jgy5ptPq1aROQfHmOhyF6y5pUaTi5j6rHk/GFQyFweONbWoup17pj3OxqdRGv5wyfavnZYyV4Li+w3EA6qbiWOy0+ESFlcemSuR2H7RUuO2r7KuwUuJWlMd4wfEq0xA1s+iRy+zsV2hpOy7cd3HmzipzjMHAUQXRJQSYkmUi476guscgXOHkqy72pu2KriFRdTrOa7Bwrhe1QImOixOJztEJB0jH0p0yktnh0W3rw06t0jdhy57HAyNkyYmCCp0Reut5rMIySqXuDvDxWZjjJk+SO8gmThOhepeWzjcqMAmAcKtrucx4pawfOd5TVTcTIIUSXDA6JTynyTqQBgz5KhNeR4+Kn3hmZAKpJ07p6geeStajNaBWM5j2KxtZp3KwkgYCkHYPJNG24VGudg7qYcCCQVzhUkSm2oRnUVdJt0JnJTEScxhYmXG+59qsZcN3+hNDSfAlSk9SqWVmkDOwVjagEkgKAJcOfuR3jvNJ1QbkOPkkC2TA81RPvTpIInklqxlKRmOSiWkbZTQb2h3IeMKGgHaPcmOswk1zw6SiIPoAnx5ql9tJJIlaQ/MFTIxgoac91EDIVL2GScx5LqGnqkjzUHURuPsVlSxzCwgREpBpO8xsuiaDScmVW6lgj7FdnSx6fPPNI0nOMgFbG0hIkexdOytqTmwRJ2KxlydLWHF1dnnX0nSSQROIUCyML019Z0dBLQAdlxqlCHR4K4csyTPiuNYCHc5SM5ytr6LgJjBMKh9MyTGCf+i69UcrjpnLvDzQSPLCscwkSq3MJPPdXaEWtM7KPdtIkkKRB96iQMgLSIupDlCgaIIVwkACT5pyMcwrMtJWV9IHEe5UvpFpjkttSCIHRJ7QTiAtyppz3UucAql9AGTC6bmAmMKD6c+SvWmnKdag5hUvtJOy6zqZ36E4RozEclepLi4VSzkZCzVbUxgL0L6YI2Vb6DSSICbiarzbrYt5Kp1DwXo32wIgqipaDolxlWWx599GCqzSPJd19oNoWd9mQCVi8UqzOuOaZ6/Qo934LqPtiB8VUuoEZIXLLhbnI57mR1UHAre6l4Kt1ODsuV4XScjEWlLSVrNLwUDS8FzvE31szmJFvRXlhHJRc3nC53CxqZRmc0qdG3fXc5tIanNaXnwAElSc2RskB5grGmtqAN5G618Y4lecTdbuvH06j7ei2ixzaTWOLRtqIHrHxOVSQdXQIu20jVPcau75at1NLKzHCAcKRaokQVK1sKJjmJUtkipoNCU+CCYRoOSRsgFRKEIQohP8AilRUnFJqKSEBMiEUkwmBhItPLKIHIbulB6IyEExuUnckgeqJlUJCbtykooQgKTtggihCEAhCEAhCEAgboQgZEJIiEIBCEIBMGOSSEAhCEAhCAgEJlJAIQhAIQhAIQhAIQhAIQhAIQgIBMJIRAhCZCKjsmQkgLO1NRTKSgFJvNRQkEiPFIICav5iKEIUAhCFAIQhKsCEIUUIQhAIKEIEhCEDKSEIBMJJhKlfZW1JA9Yzg7fYtDNbzGc7rC18ZcY8Ry8Vso3DRIkA9ZX0M8XHHL8TeYLoLtW2dh+9RFR0HST9kp3VYOEAe1Uh2rlsFmRrfdcKoyGu2MTPl/HsQHCebhEQOig1kjE43I+1JwPkTy3K3qezC4OJAARqiQQSDkx9ChSk5MEQPapRMyYjCaNpE532UmPJIA5qlzskxtzV9CmXOxHUT1TWk222loalMOJI1CQfBRqUn29zoeNj7wnbXVWk9tMAHOBz32Tqi4u7ggAa5MCdz0/xWcccrW8ssZO3l3+xltwyvxuzHGqxocNdctZdVA7SWUyYLp5R1EnwXU+GK07KcP7X1bXshdi54YKFM621e9YHlskNfJ1cukGQvMV7O9trc1dL2sb+cRtyn34WFoc+qGPJnxWsuOy7c8c99lT3EEiSPMKvvtJAknzELXdUWspyMnmcLnl2SCDI38FcLuLlNLw+ACHQeYlLUC0mTjcKkOGD4QmH7Rg9VrpZ2ukgmTMGY5eCDsJJMDdQL8kN2EmOkqZaRuDB2JH3pIu0BUeAXFwO+Aomq+cGT03hBbDS6ZB8Iz0RA3gb4IkA/9VqMVay5eHQM/YcLZSqOqz6wyPtWKm31o3BXZ4e2x9CcG98b41BpAZNPu4JMmZ1SBgDnvyVS9lreHfigZiBBn71iurV1F2xzhfe/gN+Dfhvazg1finFbh/ozKjqDKVJw1F2DqJ8JHLMr538MHALTs1214jwW0q1K1K17sMe+NXrMa6CQInKxOTG5dPuz311ez586TGTPLCQqvGRtvkq2oAZ8eu5VR9Yzp32E7rpqLNrBVMwTnoBy6qwVA4D6cbe/ms4+OcyBJAj6f8EAzBgiCpWmyldPaMHBxMdVfbXEOknOZJzn+PuXPaSckwduikTGQOecblZs2uN1Wi6qh5MNidgqNRBJ3MdUnE6S4HfAzHsTaHEYEzyhJJItuybh0SBGMcsKTSTEOzuPZ1S0ktwB8XGPegDMZhXaLGQZxgfQrqAIIk75kjBhUthhMwR57KZqM1bThYu61PzaHaNJcXT4dfFRDiYMgAj+Cq2EvMB0mIyvW9n+xnEeMWJvGPZTpRLQQfWwuWWUw8uuGGXJdYx5ljzIMCYmCtNlW0uE4HOUuI2tSyualtXAbUpOggcz7uiqAknGPNW94k3jXaq3bDR0t3jEdVhfJ9aIz71mZIyRAnmFpc7UJ0yRmFiY6byz6lYe6Yn1ZnO4Ph702klgjE5OrqU9JEEgjpKGzrC1IxUw52Ix0nKua52NJJJwBOZVDTI06Yla6AaQWkAjopa1JtptLiqwtcXOjGAdxPP7F2bO5c5jNUTsR1C4bmgO7zYHMnceKto3fdcgMjPjH2Lnbt0k07tz6zNQHl5LELu5pktEhvUcvBVU75roa4nbJVza9F0bB23motkro8Pvnloc/A1e0rpsr0XCagEb+K41rc0Hklh5Gepyunb2oe2WOgdCZ9ibTTS6nRLsRt71W8MAkkdPJN9AtyKm+89FZ6MKjYDmyOiMOdUMugO2wrGupUmGrUqtpsAkuPVRvLR41Fpj27rwvwg8Ur8OZbW+uHVS5zATuR6oMe13u8Fr2MJvLSztZ8IlzY1X2dhRe2iWw6qypFVx8P0R9K8C/iXCHX9XiT+BXlC6rMLKldt2SagIAy04mAPcslWoQQ5xLyRDZBMk8/ErVQsjIddS55zpeRPuC5729fedozeicI4nVcbanxrUfjQKWhvtKj+AeHNeabH8We52IFSiPuXaL3d0KNEBjRyaIVlpQbSJqaj3hGSeSqzBwKfZ7htK4rtY/ipNqzXWOuj3dPwLoEu8Fbb9nLe8qWjaZ4gyrdtdUYyo6mCyk3eq8geq3eJyYwu6KdBtE0Q1ppk6nTnUepXP4nf3VyaltaNdpqjTVqdWjAHkqXCRwafDLGtw2vd0qt+21ouipVdRGMwI6zuIyipwOjTDKBvqv5Q4Np6qBknS52dtg0z7F3Li3NLhdnYsMNFXvH43KtvKD3Bmhx1NBgnlPNRnojyg4TRqsYG8UpANBLXOokAiY3lV3HBKJa4O41w1pcZAcTj3SvQVLGu1oJdqC53EOF2z6Tq956TSazLn0gJjyO6MXGT2efq8Erh0W/EOF3UmNNO7a13udCxXVnc2z+6uaFSi7caxE+R5+xbbkW5aTw+4qXtJvx6NzbtDo6iCZ+grNb1KjRFs51S3JzbvdLR4Z5dDuE253TId/NRrO1OYZzBBV1SmwuJpvc6m4TTLt45h39YbH381mqYd9qIkzda6V6LfFCk2f0nZKw6vBKSibdhnHLjZ9Gi8dC1Xi4s7lkml3bvArgavBWMe5pkFFldR5NNxaHSOSjIwQY9qyMrF25Uy9S9lbaNx3YJInMnO/Qe9OlW1Oc+oNUnU/wDrFYNabqhDCAYPOFlY9BwritxQuqda2p0LW1pVWCtVDC7S0/GdpGXQPtC+n2t1a3tE3NjdUrqgcCpSdqb1g9D5wvj9vWFCgymwwYk+ZGVGhf3XCrkXXDLqraOeI1UXQQQZ0nqJgiZ5hbwy0uWMyfZ9QEZHTCc4hpPj0Xiuy3bd1w6na8Wosp1KhcW3NFkN0zEvbyE41D2jmvZ5yOcwu25XKy4mY9q7XZKkzhRvOKkMN7xSq2hbmJLKFKmXH6wqO8SBOy4JJ17e2eS60MdwO34iatQO4f31DumGQ91VulpI54eYHVfU+ycZl6jv+H7/AOtvt/8A0/cZ6u2zvq6/6/Tbi8bvTcXVZtN2qHOc97jhx5uJ6eK8LxPiT7q6qW3DKL72q3NSq94p0aQ65IEeLiPJeivbDivGuKN7IcFYTdF3fcVuBllu0GNJP6NPOPz6hO+kRbe8GfwZrrHgNtb29KicXNxUbWuLl/N43DAfYYhb9Xjly5XXif3/AAdfWTLkzteSqcG4qZfd8VtqQ/Qt6Lqn0uLfolcziPD6raRFSvVuWg7m2a2Pc8kLVxmlxO1uHuuLh7nEzLaxcuRVu7kn16jz5lfC5dS6fKz14ei+Cqxqt7UXVdxdot7F/rDY63AAH6fcvf3IBdG8L43ZcSu+HXjb+wuHUbhgORkOHNrhzB6L69ZXJvuGWnEDTFM3FBlUtGzSRMDwU468+cReCPVwVA78hyhWn1pAkQVCDnfou8rl0qXTOyiQYVrmwNyqzHL6Oa1tjSESOsJEQZOOiZ9Uymc8lvaaQdgoGPHKcSTqhMBu6bNESAY9pUfjE5JKseS7yCrc0wdk2aEgACSfaotIBx1hGYIhIAyeaqJF3iZRqJHOenJR3GZlPTImfNQDiDjZRLvBDi6fVATIxPNULVP3JyC2PdKAMExmUhzgcveqgBIbndMuaYAJ2SdJ+5INJ2GBuie6UgERknomXZyq4MbZQJIkcsKiwPLdirhWOc81lBxueqTiTuef8FDTWK52DoPJTbWdM6pWIOA58t1Nrz0lEbWVxsSZlWNqczg9Fz9Z5bQrKdUnc5GyG23vCRyUi5vPmsbagJAkzKn3kQSd0NryASIIT9bGMwqG1JgDZWtqgtySf3oLmMcTifYrHW9UM1Fh/wAVZw6qwVBrMea9BNq+hALTIXnz5bjdaeni4JnN7eVc0tdtkJGM8uey6V/SYHy3bmsbmbj7F0xz3HLLDV0p0iTz8lZTe6nJacJ6PEBLTpj84+StkvlmWw6lZzmgOcekKujSZUqNDoLSZ9ibmmTghISDqj96TGSdjq3e7fc29JtEy2MLg12AOIAjp5Lp1Lio9uknbZYHsJJERAgJhjZ5M7L4Y3AkSBEKt9MRElaarXTzUCD09y6yubM5o2gpd2OXVXub4c0tAnBV2jOWGcfQpd0d4wcrS1gBXp/g/o9lqnHKY7X1LylwnQTUdaNJeXD4oxkA9QJx7QueonS8W+kZyYH2qst9gC7/AB2hZenXH4PNV1n3jvR3VWhtQ059UuEmHR4rkvpQIOFqZbSxlPU58UgR9KucwyJ2VZZAMDZXbJObyCg5mIVkOkjkoGQ0T9AVl0eVbmAHPtUHUpBGZWjTjrhSA3wR96tppj7r+CqzT3kc10SBOwnZQLBtgxzVmSac11KOSg+hI2ldV9IbNE+SrdQJPkN1qZljk1LcYgclS+0n81dl1DGxKrdQkDGVrrZ6XDfa8oVD7PfC9A+2EmMFVut+cQm0srzj7UgbKl1A9F6WpaA4iMzlUVLIg7J0ym7HnHUj0lVupEBd6pZYPqrLVtCB8UrF4pfDUzri1KZhVupkcl1qtu4clQ+j4Ljlwt48jmuYVDRvhb30TJVRpEDZcrw10nIxOZGyrc0jktpp+EKss8FyvHY6TNkhItWgsEbKBbBXO4tTJXSpvq1W02N1PeQ1o6kq3idjdcPvqtle0jRuKLtNRhIOk+zCQGkg7EZCdQlzi5xLiTJJMlYsa6lCREqx46KGymmpdhR9iYwkmlDh6qiRCkThKVNAah3JOZ5IUANkIQiFqCNQSIgSkEUyZSQgDBRQhHNA3QCZMhN0DkooAoTckgEIQgEIQgEIQgEIQgEIhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCARCE0AkUQjZS0IoCCksqZRKScICUlLT4pQrqgCCmEiUCQhCgEIQgE0kKVYEIQooQhBQBSKChAIQhAFCaSATCSYSpX1jXjbwUg6TEEeEqoOyDpAGw805MzJiY257r62nj2vDvWEneMxstNk0PrNY/bnyWAPOoA8s5V1KsWFrpgjMgrOUutRrG9+73djw+zNq1xY04g7ZXC4vQoMc40y2Jw1uQuc7itx3XdtqOaIznksz7mo93rOycA9F5uPhzmW7Xu5/VceeExxx000Ht1DMCR7VO6qUy53dzoHP2mFz2VDOJ6ghSLiRABOZ3Xr0+f1LG1JqHwK1W101rcjblCwNaSASJCsY14BIHjCXHaTKxsdWmprbI5yOS9D2XuqLuIa7nRqO55E9fBeXptMwGzHIbLTSFak4PAdJEZG61h2TLu+g8YvKHor9WwaQGzv4Y2Xhqr9NVxaTp2x0Um169Y6S+Y/6FdPhvBhXGt4JxMHGVjm5ccfLp6fgz5LrFx61xVqwC7H0rOR6xOAPFepuuCUKQADsSAZ6dVVW4XRFAlsTB33C8+PNh7PXn6Tkn3nmSDIgHx5wnkDIMcv3rZ6OC5wEARzP0fQs1QAOPPyXpl28dllDHQc7jkdlprXIdRZTAA9XdYyWiFOYGCPGcpSVIuJaQdx0S2cR7cZj/FJplwk4lXANDImBGVPC+Sa6cStNCq5r9QOQZ8vJYzgnkdo6f4KbXGMkj2Ks19L+DTtl2n7NsrP4De6GOZNS3ewPpmPztJ5jqIK8px7il1xLiFze3ld1e5uKjqtWo4QXPcZJxj7hyXKt7qtSY4U6tSmXAtcGOIkc8jkRy5of3lQSA50+EprGXbOqgT6oGMeKlT07/nKLqbwQCCIHTdQ1ESZAKt7tTssqAF5DUmUnvIjUeUgK3h7GOuA15GnaZgT09q9RQtbX0c+qA8+tj3LjycvQ9PD6e8vh5elSc52xOYWkUJbpcC2eZHMLu29vbCrOAD4bLt8EsbC5u6VKo5oBdBzuFwz9Tqberi9BlndbeENBwEQYPXwQKDidOc4M85X6Mpdi+z1bhoY6zoa3MEv2JPWV4ji3Yqzo16no7y1gdEYxy/evHx/avHndeHrz+w+XHvjZXyl7Y2kbgyCEreA/wBbbYiV6PjXCGWz3gGCMkdDsB9687cM7p+kHP2+xfQ4+SZzs+XzcOXFlqrrkUizAgz7liBAJME5PP3K6kypVI08t1O9pBjYdMjbyhdMO3Zxy3e+lNvUDXB0idwV9B7P9v6vDOCtshbte+mCKbm49/Ur52yN8Hp+9WCSdMD2nIU5OPHLy3xcufHd4unxO+q31/UuqvrPe6SNlCiQRBkkjLpzCyFpIJmN8yrqBYD0EzgYU7Sah3t3XWoUmmSCwznwHvW63s6b9XOCCMrmNqMa2A7lv0W2wuXNe0gAjaCcjquVydccJvTq0+FtqDDZxyVV5wd7ASWOkjI+7qvTdk7mzqPaK2kOkACOa7vaF/DvRc6AcwG48YnkvFfVWZ9On1Mfs2ZcfXt8sfavYSBEhJtItIdMZ3BXcu+4e6dwREwqW0mOjVidvo/x9y9XXt4bwaunP0F7y0kzgABT9FcZcABicHktrWCQZgA88kLr8MZRcCHAQZGdoWMs9Tbrx+n6r3eaFq/cAjOwVjbCs7IcTE+1ew/B9u57RAdIBJmB1XqeF9n7CpZa9LNUT5Ly8nqphNvZxfZ/Xe9fIa1C5snB0u0zMjZdPhnGHMd6xOeUrs9r7S3oF9GlpdG0c8/dleOcNBMbScbr08WfXNvD6nhnFn0yvYO4kagGkAyM8lotrqBJ3jMLyFlxEMeBUMFdu2u6TwIcA4Zydwu/T2eK3u7lOp32wkvMR47L4r20rC/7bcZvnPdVdRqChaMj1aVCmTS7wzmaj+8IHTPML6Rx3jlpwPhF3xa69eja0zULAc1Ds1o6S4ge1fHqfEOIX/EaTL64NXiHFi+6vagMOL6lOWNBiQ2nS7uG8jV/qrGUduKd9qq1W34e417qqxld2Gh59YeTRt9CkL4tdTi2raqz4YajdJef6oMF3sC83U4w6jaVrjh9CnaUxV7sXA9e4qug/wBI6SMZOmN1y7avUpm4vdbjWfSczvHOJd62CZOZglYjpc9V9A9M7tsChdOdzLbd5+wKB4pSIiqLmlG4NpV//VfNZH6RPtKesj4pI8im0+LX0k8XsHfiqdatTH5z321Ue4aUqPGOD0nwKz2UmZJdReC8+GF83FesP6aqPJxT9Mu2H1bu4b5VSFo+LX0RnHOG1arrutc0/VMUqIMcuc7D7VnHGadSoXm7tmgnA7wfvXhRxLiAI/lC6xt+Od+9M8U4gcemVyPF0onxa9xV4zRLYN3Qb4ioFzrnv7s6m8fpFs/zbiIPhj715b8JXp3uC79YA/cqrm5q3Aa2q5pDCS0Bobn2BVm8lvl2bk29N+mp3BqNOKls71mnr/1WWpRbr7+m6Sd3MEDzI5H6FznVg9sVKbXv+UmH+2N/anSqFjoa5wlRnbZUbqOqRLiC7wcB8byIwfGCuY/4zvNdBjwRkgLmkHU4OiQVKU0ISlGTTBUZTTa6WMOVbqwqQEyYS1YlqTp1IdJAKqlMOMrNrTUapcZlMjvGBhBcNTXETEwc/QsgcRsptqkc4U6jbbbXNWgJ0h1xUcAGBpMnkI5gT9K+mWfGqPDOHWVlxB9SvftpMbVawAkOI+LvuBj2L5bRvrijVbVpVCyo0Q143b5LXwziJpcSZc3INXTJk7hx5+K1hnpvtl5fXqN5aVGai51OTH41hGP3LVaX7xwq89GeaVV9WiGVC0O7t2o6aoAOYEwP0g2cL5fX7QVaziyiSWnDes+S323FLvh9xrNu6noc3vG94Drp4BDoO8ubHivZ6X1OPFyzKvR6TLHh5Zn+/wAHs7WkQKnBuDONhwe1h97XIdVdWq5INSM1qxkkAw1o2gb4Ly6tSNVKwur+N61zUcwA+DGENb9KzntTTsLa0salo5tqQX+kU3yKtQ5e50gEPJ5HYQOQUbkv4zbG94Za3DzEBzWaC72kgOXu5+fHKawr2c/NjlNYVx+KUbe6eXv4dbtI5CpUEfWXB4hSoURiya0H85lw4x7DK6HFX8Rs5dd8H4lSaPz305afa0kLjVOKUq+pgwOYK+PyXb52VjHUGqG0gXPcQ0NGSZwvsXZ+zr8P7O2HDrx4fWoUNNSDsZJ0+yY9i+QWtd9rf0L2kxr30KzKzWu2cWkGD7l9ltLujf2lK+tnudQrt1053g8j4jY+IU4o45JFsEwVSdWTGOauqCRv7lS8OMgE+xdnOouIIEhQft0TyNznxQ4CPjZ6Ks62qdy6eaCSBAhDgBHPnlLV0G25K1amgSJ8+iBAHVME8owozJkk5Ku01oEwMCJOUas7eaNhAAjxUT4SBKbEgREZKQbGeXVBJGZRJgyQpsBA1ECEDYgwUzqiQcqJ6nPVNpoCMz7EAY3iVI5MDGNkCMGDHRXYiRuAjMZGJT5TnCXjjorKagjmScbgJE4EHkpGM+SRz+crtLEOfP8AelmIJHuVgbPInCgRGy0iMD/qkWmN5UiZ3SjHP702mkY5c43SJOxj2hT8U8YM5QV5AGZ6KQcZiPckZ1HUPpUmgaZwc5RNGahEnBx0TbVLsQFAggmPZnZQbOT/AAVTTUHwZ8VY2oCN1jDozMDOybKnPAwiNzH5kOjor23FUAM1mOkrmitzzKtbWzJOVLJVlsb+/cQcnfryUm1oMexYhVBEe8KYcC2CZ9qkxhtuZVYZx4QrGuaZ655rnF22VIVHAQCnSu3QMeGOfXxSLBAHMGVlbWLcjOMAqXfgZLp6+Kdza7u5kxBVbqRdyyrKVww/GGPNTdUacjHgm0ZHW8n96qNqRgFdCQZkYUHge8cuiu0057rffmqzRgzg4j2rfUOTJ2WOtVDQTOFdppSWgEyraTiDvCx1biOQ6GVBt4Jg/SmiOr3TngxsOiy1qEDn7V3ezlW1riC4BxOdRV3HranTp6mQCMrzf6jWfS9s9FleL4keVdSk5SdSgbBOrXaCfWkjEyoekMiAQvTLa8VkU1GQMiPFVlrYEZHmtDqgd0Ci4E5I81uZM6ZnCDtyTyGnMq1zDBKg9p2nfmtdSWIajON0yY5jrugN32x0SIGkkfQrtNJ6hG48ktWZyqySCIHPKNzmclETMap8E3ABvWOSgCCeWMpudDsQcqbUzTbsY3yjuRqGBHLOEtR6jyVrcunbHNXaaSpWRqOhonHIStXFuzt/w9zG3dpVol9MVGa2Ea2nZwkZEjdW8Lu3WlxTr0nltSm5rmuG7SMgjxwvffCR8JfEu37rUcStrG2ZasLabLdhy8xLtZk5H5u3tysfEymWvY1HyOraEEiIKy1bbJiSvYcW4Nf2trb3t1YXNG3vA51vWq0XMZWAiSwn4242kLiVKQBOy6zkTpedr2xVD7TmWr0FS3k7Kl9DwWpmzcXnKlrLtlmfbb4XpX2wk4Wd9qCdgtSypZp5p9AZEKl9DwXoq1mImFkq20bhS4SnVY4TqO6rdSzsuy+2gbKh1vJ2WMuCVqclcl1Izsq3NzkFdOpbwdlU+jnZefLg06zkjnuYeSgWEcludSg5woGmuV4nScjHoUIWx9LCqdTPRc7hW5mzjPJBB6BXFhChp8FjpbmSESgNhT0wkQpYu0DgwhThIg8ypoRSI6KUIhTSq9k5ypHCFDaCFNRIQ2SJPIoQinugiEpPIp78kQkI2JCEUIQhAIQhAIQhAIKEIBCEIBCk0DmkUCQhB8oQCEIQCEIQCEBNAkIKCgEIQgEIThAk4SIQgESg5ThQgKiVJRUqkhNCgScpIQOUSkhA5SQhAIQhAIQhSqEIQooQhCASKaCgSEIQCEIQOUkIQCYSTCVK+pkiSQTnG3JDzOTg9R9nmk0468oTb1lfXeE8jAPJSDsCAQFCYdAzHQqQnMkGSgkIEGRn6VOd5x7FWDidp/ghLXmNyitLACIwPNaadJpADjB2JJXLNwR0kKxl24fFPvQ7OqKLIAiCOaA0Ndp1eC5ovCQesIbcHVufLzQunqeE0bYXVF9yR3WoEzsADlen7e3/AGWFtSpcEtAK2XVKpGx8CMfQvnDb12kNDj09iVSq8j4xj7lmw26XpLWPLwYIggdFuocdq0QNAG/uXndbjJ6kZlPUTvBxzWcuOZeXTDlyw7413rnjdeqSXGeUzmJVFXitYgMn1VyRMQSQdj/ipN20k4PPkpOHGezV5+TLzWk3FQuLiSCcYUHVJbAiI54VGS4l0iR12UtzJGCfYOq6SacrasaYBALt4UifVBiN1VMiTz6mVZvsJVIkJnV1MZn2eStbUeJAHhHTx8VWGEExPXCk2mZJnop2aMzz581LJ+NgDJjeFOlTc8kCTvjqtDLWqDFRjgTjP71m5yLMLVFFrjpEEmBtOV6nglvS7lrnNbOqDzAPkuTa0BT9Z8kTnGy7lzWpUrTS14nwPsXl5uS5do93pOOY255ezY+ys3tktaSRsBheR4uynTuXCiWkROE619cNc8MfAn1lgqONR51nnMnnK3wceWPe1j1XqMOWaxx0myq9jyWFwBPtW9te77kRqA+1cyiR3jXzsZxkLpi9Y2gQ2dURI2K6ck37PNhlr3RZfVpMOIO2ArqfE61L121HdRBlcmo4FxMHMzyCGzqcOZieX8Ql4sb5hOXLG7le2te3XGqVt3I4jU7qIiB/HJTqdtLx1Mh1XVOCc/YvD63RA6SEtTi4Dkd/PouH+h4t709f/wD0vUa11V3b7jda6qa6jpBzvthc2tdOeS57pIztlZJIAPgpajAzB2yV6ceLHHtHkz5ss7vKuvw2uKQ0vMYJOcyo8SuGVC0My4AnH0rntqHA+5PQ984MFTo77PifLoOdkxHVSpOOOnkoaSMO3BzCk0FvMrd8MRp7yJYXZ9ynRlzsbiCJGQszYjDQGnw9qvpPDXzMCQeq5WOku2otqHJkDrC0UapAgmJ3P2J06rHU4MeJVb9IyOvNcbdvRMdd40svnsdqY9zTA2OcK48QuKrdL6jnAZIcFiZT1CI6FbrW2DhJO+/msZTGd67YfEvaUUrh/Pnk4W63qkkST48lz69Du3YWrhzHPyMef2rPVNN4Y5dWq6VJrnk53XSs6FXBYRIwua3VSLS4efiuxwm/pB41xMrz8mXbs9vFjN/M7HD+G394dNCmak5jdejpdle07aB0U2xp+Kau/sW3sTxawp1AypVY2RGrzX0YcR4fTohzrilp6yvkc3qc8ctaevk3hrpfCeM9meNhxfXsnmOe4C8ze8KqU2nWwjxIjK/RnEOK8JqMP5TROOq+cdqKnD69d5paHNcMGF6/S+tzyurHm5fT45zqvl8O4tb1aNV2kSN9jCwUeJV7d59cicGdl9H4zw62qMJEEbwNivnPHbDuKxiYk5Iyvt8Wcymq+Hy8dwrk/CTxd972Ku7XUdL6lLUI3AdK8jTuqjO013Xb+MdSs67qDRualXSxv0ub7Gr0HH6Drng93RgOPd6h5tM/cvLcIqPfxV2ggVa9maDCf0/VjykjfxWeaaydfT3c0qtOGjinFqPBrf8A7P4awm4rjAcZ/GOn+s4aR/VE8lk7QX1K7u6jbelSp0aToY5jdJcBgT7l2uLPHAOzw4PRc30y6Iq3tRm0xho8AMe/qvISCx3gucMu3ZDVzRrKiNkEqsGXHolq8EgmiW6RJzMKSIUEShIpoTS6CBuhCaNLWSTgKl59c+auYQBuqHCHeCimCCghJoypKBQpNSQpKaOSEpRyCEa0ZQDKSFm9w0IaiVNdkCmwnKikr0rp0uFC378VbojumHU5pMB0ZhauIcQfXe2mfVL3irW8DuG/SPmhcdjyBB2VtqHVLoSZLnSVfDUvs9pWuLqrwug9tUveahkPGprhpkNcP0SQAfOVYe0VHiloKN7b940NApRLe7AGANJxHh0Xnr+/rUH2htqzqdSiXOlp6iIPgo0HmpeSwNDLqcDAa+Mx0zkLr8Sx26nom1AXdzUq5d8VwfpcfIjE+e64/GuHVXOcXEVv0XOEOVFG4d3BtLjQ6o0fi6jTuAYIPitFpxbW30S/Dejajtj5/vWbZUuq8+zUyoabw4EYgr3nwXXj+6v+HOf6tMtr0/DVhw94BXj+JsBqOcx06TAI5hem+DW3f3t7fGQwsbQb4mdR92Perh5cs/D3ZILdQO43VLiSJkx4oqvnIjJ9yTjjmZ3XZw2g4xt7VHY4+xDjB5+cqJkkmUTZOM7JSC0kApxPmVHrGOSAkk55JnJ5IJz9CZ+MCh5RyecpwdWN4SIJPLfmmCABGw381QoMoOfCFdTY6oS1jZco1KTqZ0uBBOUFQ33yiYkfQpGRACRBJz1SRL2Jsbz/AIqxoJAJhQAgFxUw4E4wN881REgA/dKUGJBxO6ZJJwPEBHMxyCbCxKk2JHuRkGY9vRA1HcEFGV1YW/cUxTa8vE94ScHpCzECDpEAeKkZJJ5qL4JkNyrsIDY890jBUgIzP0KLt46TlWU0jABmECQY5HIKkBnPuTbp1TGQrtNbQDTAnI6qxmCJHnmMeC0MY0tzE745Kuo1h+LEys9bVwXccv2cS4g67ZYWVg0sawULOm5lNsNgkAkmXHJM7rmOB0g8yrnmeqg7zjxW5WLFec7oM/emZmfFGkicZKqaR1Ikg4EoIzvzSgdY9qqaT1xnYKYqkbwefkqYI2OSk4EElE01srmA0mD1hTbX6nbCwbkZjESmHENxug6QqtIjZMOBBzlc3WR5qwV+UkoNpdEQTBQLh7cysorN54lPW13SUNNjLwSCR7Fop3gcckLlO6g43UQXNO855ppN12S9r277hVVaOsHTGy5zK72uy7CvbdGImeSU2qubMkmREYKw1rao2TB9y7Irhw9bpPmio2nU3Mk5KSmnP4NWdQvGNqOc1hIDl9g7aWfZ4dixdW1zSFdzQ5vres7C+UuoNJJEKut3vdFup4btpnC8PqfSfG5Mc5lrT6novtGem4s+PLHe3Cuazg8tBx1VAunA52lbrm21mSPZ18Vz61vBgbdeS+hPD5N71ay8jckEdVop3gJkuxvlcl9NwJ8FCXNOQdpVO8ehZctI3Hl96kajDzXnmV3DMwrqd0Q4S7CmjbuCCRkJFuZHRc+hdzOcytjKwI+NMoeUiMfaVHSNxurfjDeUaTKuzSqMc1EiemOqtLSM5PtUYIEdFdmkcznopA4gFIxmeaPW3lNppcypGx6KxtaG4cfOfpWYuxtCc9VDTZXvK1Wm2nUrVXMZhjDUcWs6hoJhsneFmqOmRz5qouwD4oLvGMopvg5UXRHJRecqMptIRCqe3OArScKJKppRUYIgrNXpA5C3GOare1pWpkmo5jqEiIVJtjO0rquAlQ0iF0+JWOhyKltzhZqlvk4XcdT8FU6k3or1HS4FS3gnCoqURnC79W3aVlqWu8BNRO8cR9KFB1PC6tW3M7Kl1uZiFjLjla6rHMNOAoGnC6L6HOFW6kFzvE3M3OdTwolhW59KRACrNFcsuGtzNjc2FEhanUzuq3Mz0XK8ddJmzlvRLSVdpIEpEQudwbmSoiVEtIVpCIWbiu1YwEiFJwylBU0u0AMpiBzUoMKtTSm5JBQooQp06bnzHLKi5pbugQTJSQogQhBCKAhMpKoChMJKKEJhDowgSEIVAhCCoBCEBAJhJCDpcdueG3V3TqcL4a7h9EUWNdSdXNWXges6SBv05LnHYBICUBSkMJRCZQEEd00wISVDCCYSOUAJs0EIQgY2SREFOVFJMpIQCEIUEUwmhNAQhCAQhCAQhCCKEIWQIQhRoIQhAIOyEHZAkIQgEIQgEIhCAQhCD6kAZ1bYPJTEch44C2ULMuZqcRB8MKdjbM9MNKrkD43ivpXlnd5pxZbjLTpaiC7EYhX16LBSkSHDfC9NeWFoLMvYxjSB6vmvJVarnPIknOT4rHHyXk7x15uD4HbJSTLZjKi4Z3wMnG6k90zvKAZ5Er0PKrfnAInohrMFWNGAdIHNAkRBHXySIr0YkCJ2U2tPKE256wpjGTJg81QDGmOe46FWHVEiCOsKLYAG8jqmN8dI2QTEc99/NSDvEEgdFGZETumACNQBPkFBYzbl4ZUic4bMnmotEOgxAOehwujw2xbcNlzwADtEEKZZSTbeGNyuo57ZnffOykBBgmPHwW3idm21cHNiCcQPDZYczGVMcplNwywuN1U8EY9vVX02yYMxKoac4MEfQrGPODkZyUpPL1fZzgNK9ZqqPMcxPsWji/AaNgWuBkOGxzz2lcnhHGa1mJY6DHsPmpcR4xcXRJqvyJMdOX2hfPs5evz2fXnJ6acGun5nS4LQtPSG98GtAMZXu+GcG4ZxDu2QyTBwAV8mbdva/wCP7V1uFcZu7SqH0qzvVyB1XLn4OTPvjdV29F6zi4p054vqvEPg8sRZuq29V7KnIOAMr5zxnhVS2qvZq1ATJ8se9dt3wi8QNoaFU05jSXdR9y8xf8bN1U1PcCfCYXH0nH6jG/xLt6PXcvo8sZ8Od3GuqDwXetA5kfQszhkDfGcfctt3eNeyAJjb3/vXOc8Ekgt9+F9jjts7vzuet9lwpOEnaOnJQhzWk8+cc1dRu2gQdj1Q6pTcweI6LXVU1NdldEB9RrXOJk+zzK6vD7OjcV2sdt+dndcbUdfxo8FbbXNWlUaabw3MjCmeNs7Lx5Yy949DxvhNvStjVokt8eRXmqhGTJmc5wtV7xO6uafdOMN5tWFri6HHnkeScWOWM+Zr1OeGeW8Jpa3EwYnPsTHQGXTOCFVqgkjZKYnryXXTjttoFpd60Dp4LsWD7cNGqJ3JXnWF2+oNMYW2zY+sDpJaAQT4+Cxn4ax7107inQeTpI6kkLM6iA4saCZI23VNfvKDi2Tk4I39vRFO5cyoHfSCue29avdqNnUa0ktB5eEqIoVCYHrR9AUvwhT07T5p0L5gfLoM4hcrcnfHHDxtW81KO5PtURdEnJyN1pvq1OqyQWgrktd6xxn7Ex+ad1znTdR1qFxBzjqt1tfaDMzC41Ea3AAxGPJd/h3Ba95TDqIJ6CQJXDmuOP3q9PBOTK/Kk65bUgnZbLGvTpnUThcq/sLiyfFQQVlbduaIyuUxmePy13+JePL5p3envbxjgQCJHOVhF2aZwTC4npTi4et5YUhXLtit48Woxn6jqr0lrxivSiKh8gurR7TXfd6RWMeS8XTq7SV1uFBr6jQSIPVcuTixnfTpw82dutu3ccfu4JD3NXNq8duNeanMruXvA6dSxNSm4awMZXh+I0qtGo/BwSCscHRlezfqfiYTu7TuMVXiDU9hK5fEanpEuJklcZ105p0k+Xgptu5GTPTovfjhp8vLLq8s17bNe2oxxIa9paY8V4CtaXPDOMst6kF4e11J4+LUEggj2jI5L6LUqB/Nc/i9jTv7QtwK9KX0Hxlr4P0Hn/gt5zqjPHl0ZPnvau6dccTe8uJ1GfuXGBy4eC6vaakaXEiwt06fVI8QBK5J+MuLefeoDCk7EKIEpvGyqaKU1FEolgdukhIooOySCEpQNCUppRNuxSGcH2JtwoOw5ZNHBacppj1hlIjSl8ASlM7KBWWkyZATDIbJPJIfFKtEGmHT5hTy6SdlREIUtJMlPTHNNVemVACU9PinpTO0pqs9KIQnJ6IcJV2uiV1tU7upq8FUBiERG6qdOmitWNWoXdMKy1ruoV2VBnQ4OjxWVowFITusa7rpdq+2VOo8vMkydlSFIHwWpGllMkAsJwV9C+D+P812NEam3VWfbBXzxszhe6+D15/BNzS5Nui4e1rV2xmnLl+69K0jOQoFwJmcKW8gEZ9kJP33aPCV0ebROmZJCi/UfYVIgAwduSAA2ZA2UXSLo55QAJIM7bKyhTdUfGHeHNW3NDQAIgxsm10ynxASBAxsmRjVE5hLEwfaURI5iQMc0CZl2Zz5pN8zB+lTDZPUAT5qjXw+s1pIfgOGTvzyo31Vj6kN5A8lQBJkbRsk/BkCOUoRW4gnOqdxHJMNAJbn+Ap6XYEb8uqkabolwnxCbNKgwHdwHhKA0giBKlziJMc1bSpPdg4kzKlqSd1JGYKnTplwMDK0Ot/VwcwhgLHQesSp1duzfT+JejugYiQfaom3dq2kE5zstVOoMZBErpcIp0q90xtRwEkY6yueWdxm3bj4pnlI4ZtqhyGkgqD7dw5Ffc+B9mOFVbdjn0KbjGT9srZf9j+Cvt3gW7GmMQF86/a/HLqx9efYWVm+p+ezTcGyZHQKEZ55yQF7ntbwW2srstokZGwXnzZ0nMJ3gwYX0OPnmc6o+Xzejz4s7hXEcCAM4Iwkec7yFrurcsLiCMSeqyGM4Xfq28lxuNMPImDkpl3rb9FXkHYoBxlWxnelhHqn7VU8Tz9ilOIjlKjuRuICuNKjnVB8YhSIxiD4qWmJxJnfokcCFbkkisiN+fJBBAIgZVnqxkZHRQJjcZj2Ky7SxWQOYU2U3PBIz4JHGQSVfb1Gt+NnHNMrqJJ3UVKekxy3HiqXSDA3JWy5qB0QeqyvAkiMESrjbfJlNIRHWEiSBMRhWEZwVHTJPQLTKIJy3mpNeZgHKR548FHbxwhpcKpBy7fxVjagjP8A1WUnmDsMo1yJAV0krWCxzYJg+Kk3fB9kLK2rBG3mApioZ33RGnlznqmHu/SmFTTe6Mu81bqBGS3rn7lFTbVMEmJ6QrRpeYcRjErN6uQYQHAc8eSHdofQY8DEdFlqWLSBiQR7lcKuIIB8NlZ387xnolWacy6sBuImDyXKubMhxIEeK9Q97SwyJ9izV7drpmI6hTHcLp5N9Fw5EKOkt6yvQXFk3MNWWrZxyxzXSVzsctmoGRIx1hbaFR077JPtSDgQmGOacgrVRvpVD4rVTcCMn6FzKbi0icLS2rGSSsWNStukFvPJ81Hu4HhG6jRqkGNQnzVrX6gAstKHUzGBEKOjG262QHYSLG5wE2aYtBiBz2Sc0rS5hxAny5pPZkkt9kK7TTNoJ+5LSfFaCzffwwkKfq5yptdMjmkJQtTmeCqLCDsrs0zuGCFB2Va9pGDzVbm4krTCBMc1EmQm4qJOFYminKrJnZSI6qBJB2Woe5OJ2VZUycqJVpFaHCQnEJThN1KzuZk4VbqYnzWuJUXMEq9SaY30mxEbql9sOS3OCUK9VTUcx1tHJVG33wutoBOVB9IdEmezpcZ9A9FS63zldp9Fp6BUvoYiEsxpNxxnUYxCrdTIMALqvokDZUvoTJhYy4pWpyVzTTMkqDmwcLe6kdlB1LquOXE6TkYS3KiQtbqfgq3N8lxy466TNnKiWyrzTz0UXNg7yudxbliktKUKyEaZWdLtW0lu0oe4uOTPVTLSolqml2rKFIhIiFmxSQpwouChsihATMK6UkJz4BJRAhCEUwUihCoEITRCQEIUU5SQhNhgygpIJUWBPZJCqAiEJKUJAhlCEEqKYRIAIPNJDsqoEIQppdhCEFQCEIQCEoTQCEIQCEIQIlEpJqbCQhCy0EIQgEIQgEHZCDsgSEIQCEIQM7JIlCAQhCD7bbvOgNbk7ea6tt2cuarO+ZUDakmB1Kso2tFsVCMbxOCtdXjjLKkaZYS/MEHkrlnnbrB9Hh4OLGb572eV4lWu2udQquIA5TuFzSCQcE8lt4jXN1dOrO9XVmANl1eF8PtqtAF4knedgvbM5x4y2PlfCvNyWY15zTEk4KceYyupxm0o29xFMgN5+CwBrNJJLYHVdsc5lNxwz47hlcaqLXSAeXLmgtOBK6PD7anVqety3C18QsaLbfWwAO5FvNT4sl01OC2bjiQAQee+U9zkCJz5p1A4GOg55UTLdyZ6rptyOTOFIHIzA+xKN5JmUAjbnsiLJmAYJhbKLA9oketEeQ6rE09W9FaxxDSJmFnJrFMsgmCIAmY3PgtFpdVaB9Q/Qs4ccmc+P70HIkSOR/w8FLNzValsu41XV1UuTNQ4BwANlnZl37kmviSPbhW0Ia/IGN4zISaxnY75XdJw5HeMlTAySRHMmYUnQ44IQ34oE+PVTq7LpNoc2QeqmdwYBG6TYjbOYA57Y+1GcQ6cb8lz23obHBk7TOApCqdtWkc/HwUcEE46R1/co8wSSDutHhYahdjUZzuqy4wMk525JCYHLyMgIMHEY5/x1VmmaQdjcmTnwQATyJHXEeSCRjS0QfDcq6gWtMHfxW7dRmTatzIGfVgfShsyCTMYzurKruQM4wqifWIgRIjCS7hZqtzqNMU/jCNxHVFvTpl0uMRkLD3j4Occ/wByTXuadIcepys9Na6pvw03jKbaktcQOapYwFstgCIECFW55J9ZxOYUmEN225Dl4rcl0xbNm5sEjxymxpc8CPDfmouMyCPYrKLhr2B5lXfY13DqZYJIC0WFx3RdMweh89lVWqB3q+4/x4KqQDAkrOrlO7UvT4batyaxEFwnBxuEVGYkkkkznnjZZC4j4xjmn37gwZA6k7rPRrwvVvynpPMkGd1B5cDgkKIqkOOfpUXVQXAO6oTSw1ahxqMKDKhDsnz8Vqo1KemDpkDnjKxVns1nSNIJ6rE7ullk22U7nQdWoexeu7O9qWWDAHAOPPwXgg6SJMD3q5tX1TEjOcyuXN6bHlmsnfh9TlxXeL2vHOOUuIO1hmn1Y/6rzVavMgTBWNtd0CT47qTHEkzn7ys8XBOKai8vqMuW7rQKpiT7YC0UahmDBxlYn4JxttmVZTe1pBbnx6rdjnK6LXluMwtVrdupukGI2WBrgW5OT1UgOhOTK5ZYy9nbHKzvHraHaau6j3Ttog45rNd1aVZpcQDIzK862ppdg813uE8Pub6j3jGhtLbvH4b/AIrzXhmF3Hrx58s5rJ52+pgvJGMrK5paV6u87OaWOq1L6kxo3dpMe8wuaLHgjJFftHZ0xzJLfslerHlx15eLPiu3BDnCQDsqjWe07+5dO6uOxVFxa/tOXkYOihI+1Zal/wBhhn/OG48u4hb+NixeKvn/AGyaa3GAaYwSS4+Jhci8tXU6ArRDZj2r0t7+DL29vrsXvdcPoVi2m8iX1ZAPqhee41fm+rAUqfc21IaaVPnHU+K5b3XTKandzmbJuT5KLuSrGkZhRKk5RO6qApIQgCUkFCAQEBNKsMJO+MVJp8FF/wAYrEWm1ScZ5JN5oSkgUH5MKamxucrLUiLAQ3lnqF7L4KOH8Fuu0L7vj9xQp2lg1tVtKpVa0VqpdDWmd2gAkgbwAV48iXDwXa4d2W7T8QtKd5w/s7xW7tqgJp1aNo+o1+YMEDOQV1why2zF9L7W9juwvF3PveB8e4Zwm4eC51A129y4+AmWezHgvmHGeAcS4USbhlvXpzipaXVOuCOsNOoe0Ba6vZDtjSZNbstxymI/O4fVA/ZXPr8E4xRdpr8H4hTP9e2ePtC3qOE5csWFxAGQW+DmkFQcRuth4ZxGY/B93v8AIu/cqri0urZoNxbVqTXGA59MtB8BKWba/wBR+TKCSdwnKkGNnchMs9Xdh22Mz/HiuVljvjlMp2DTJymdkaY2CavS1Zo4KbQhuVIDwWpiQNCbRlSDVYxk8srcxamOw0esJXvOwdA0eDVKrxHe13OZ4gQ37QV5bgPCa/Fbzu6bu6oU4Nat+iOg6uP0br6FRosoUGUaIDKdNoa1o5AbLUx7uHPnJOmJl0eM5x5pk4mY8FExIMkcim545GfsWpHktLX92EnvPh4puMDcDGyhBJ8fFWkdDgV63h/EKd1UaKjWzLcZBVnHL9nEb99zTo9y1wgNHh1XNEQROSPBTM6TmfJc7i3MvZEYHPr1UocQMFwPJSZTl0FwBnluVfSpgOJwMdEt7LJaqbbvIwCUxTLSZH0LqUTT0wQADzHkpi3ZUMyCs3N1+D+DsWNlwz8FNL227hplzjGonnnw6LyddrO9IZOmfVnePFdqlw65rODKEuK01OynGO6770VzmnofasfGxl710x9Jy5Ttja85Ta4O55yFbWa4MlwO0hdRnDa9tVi4t3MI5OCL8U209IiSIGNlPiS3svwLMd5dnCJgmB/0U6LyJJlQfHJxI5E81Frg0HxXXy83itveyIk42CrIc7kQOazGq0AR9qvbcMLQCc7BZ1Y11bVO1g/ctFpcPpvDgTM8t1lqVQapg80NqETzH0K9O53SZdN3K9dZ9ruJ21uKbK7hpEDotA7b8Z0aX19Q6xBXjhWBG+ysDpONgMZwvPfS8W93F7p9oeo1qZunxHite8OqqQScx4rF6Q4Ehyort35x1VJdjM45rrhxyTUefk5887vKpVqhfILhHWVlc2OatyG+B3Kg4ztC6SacLdqTBlRzHODspP3MbnooHfPJbjFhPcAceaczufi8kjE5g+xAIPRaZaqVRujInrKpe9odg5mVTJznBUiJ25bSFOnS9Wy1kEwI5odkwD5III38E6WDJJwr+ae+i0kHI+lKYMAmYVtQt07ZOxVDt8DPmkuyz8CJyY2UZzKZyMT7lAxGT7StxlYwjTvHSSpnRp6EeOPNUgmZmB1SJzMkx4qaNpPHQ781AiN8+CniZnCJExqVSq43yPHCTsAjl5Jk4AmMYSxmemFWSgg7/QpNJBAJGfcEiQHeXKf4ynqBiGnwIVNO32f4BxHjnpLOHMt3utbc3FXvrunQhgwSC9wk52H0LlPIB9Qkt5SIPtHJV6mOAa9rXQZAc0GD+9FV8mT1USQGs4OwQfajv/VdJ9wVDnS4DcJEEyB5K1Wg1wPVCffgEGeaymQ4k7FIGBOcojX6QSPjexTZcZl0mFzy4zlLvHCADKaR1RWBGTlIlp8PErmtrEYlWsrjmfpTStfdNdyAETlQfbNJwJ5qLLjMTgLRSeC7fmm9GmU2xGYPsUe4Or9wXp+HcHdeQGSCTt4LRe9l7ii0PBBb5LhfU4S6tenH0XNlj1THceSaxzfvWilTeRImAMLbc2j6Loc3T/GU6L6bWAEALd5Nzs5Tj1e7NBaeam0F20q15pudy/wW3hFGnUf6wBz7ljLPU21jh1XUYAyRnJjdRNLYx717ejwW2rW2sgyR13PguPxLhjKTjoJjkuOHqpldPVyehz451ezz5YfMIbT1HHM9FrfS0uLZSa3Scbbrrc9zs80x790WWbnNJj2rLWty2cHC9BavZo0GP3K91pRqhxMDC4fFsvd6Z6eZztXjalEuJkLPUpxIIXqK9g0zoC419bPa6NK9GHLt5M+Ppch9ME4VbqcclrfTcDkFUvaZ5r0SuOmdwhRjqrnDKg5olXbOlTm9FW4ESryoFXYzkEjKQarTzUDumzSKRjkpFI7Js0gQNzKQaOYKZ6ptKu2UICUKTlFNqgQOiTmidlM5Ki4kkKSmlD2AjZVuoy3ZaXCZShXqSxhdQHRVPojoulpVbmS3Za6k05dSnB2VLqI5BdR7GzsoupghO1N2OT3Y6Kt9LnC6hojoqalJYuEamVc00x0UTTgLe6l7FU6mfNcsuNuZsRYYUXNK1vpmNlAsK5Xj06TNl0BIsC0lmeircw8lzuDczUFqThKuLVFwWNNTJVCICkRmEQiolsCZSAU4RCaVs4Hwm94zxCnYcPpCrcVAS1pcGiACSSTgYCwvZpMT4KbHOY7UxxadpBhIiVNG0AJT0p8kgpYIpypJESoI7ckTKDM5QAinuopoQBQEIQCEIQBTlASRDhJCEUIQhAIQhAJykhAexHsQgoD2ISTUUIQlKgaRRKSbAhCFAIQhRTSQmgSEIQgQhCiiEQhBQJCEIHCRTQUCQhCD7PR4lWEDVAjZFWobp5L3TAIGY3XKpl2MlbGse0SMmN5XtvHMb2cvi5ZeU7uiGkua4fwVChfV7dpLHQMwSVnrVnPd62YE+XJV6tOYyMdF0xx3O7nc9XeK+vXrV3udUdLiZzy8FXqcDImDsRvClRe3USckj6VKoWnpgrU7dku73tFKs5jsHf6Vs9Jq1mnU7BHJYmU5Eyce4q23p1HkgMJ2lMpPJjb4TLgJBOY36qlztTgZz4YhXVLd7GnUAIVDWOc+G7nkmOjKXeiMAY5dU5kEDE7eCvqW9WmA5zTBxI+xUMLQ0SZB3x9K3LL4ZuNSA9b1MfamI1GMAHEH2pAg4b5f4qYM49kEqBty7fJwrNhGcfQojcmJAPv6hWYa7ABAwptZCbE8ztBVogEuO8Z/xRTb68jB5clso2b3NydxIEZ8vNYyz03jhusw1SZxj1j0VgYQJAOfpVjaIZUEnC6lpaVrgaKLHOJHLmuWXJI7YcWWd1PLktbgCef8FTdqDiIO8zC33XDLmzqE1Kb2YAziOidpw2pcEikDMY2yp8Sa2vwc+rp13cwhwaYiAZMc/LnsmWF0Bu8mI/wXVuuEV6BIcD4weuyjbUxTqAOMZydvp/jKTlmtwvBnLrKacl1JzBLhpPOdik1pLvVE45ee69DWtKdSkTpB8J3nkenVcktYy5c3OmY1eC1jy7Z5OG4VQKDjJyDAJU20KpIOcb+K6OpgEEAjxXoOy1naX1dlOq8aSc+DfvWOT1HRjuu3D6T4ucwxvevIOt6sAjwOOqpcC0EtdnfZfZe0fY7htHhj6tNmmoBz26wF8k4nTFOs8B0CScHzWfTerx5+8b9d6DP0lnVd7YHfFjlH+KR2Mb8pTMBxk7CCRP2JCMFxA5n9y9sr5oxGfI9OSIwSTI3PJDhDwPWJ8o88KR/W2Wk0GCMTn+JU36fjNkCVUAc9Papk4gnETHioolziDHl4eCRPqyNtlFpwAHe3/BBMQcnwK0JatLQdowIMSolwnbByFB8jfeFEnESiRIvGcyoudgjbmqy7fKjqgEyMKNRbrjAJhRDuZdJUJBMbIGce4KaXa0Ox58ipNJ5mOhIwqgRjrGVIESAdjvCmlXA43jorabg34xKzSTGQYECFLVMYgealjUrUapO7hA6YhOmSXMEZVFLSX+sTPKFoIIaBPisWabl93Sa0MpzM595QHkiJ23WRtR2kh0kdOZU9elpk7fQuXTp16l1C4taPErdl44924lxaDkgK7tX2+riszhnAKeqsQGjS2dHgBsvmfFeMV7nitxVpuOXaGHnAwP48V6Ps3ZOtOHG9fPpN0T6/NrB+8rz/AH8ul06+nHsqvOE9peMVZ4jxSmCTOmpVLo9gVFbsLdNaHVONWQHgx5+5eo4ewl2rcc1030hUpxEq5ceOPZMbcu752ex+l7mv43RGJxQcVH/NS1GrVxySOQtHfvXu6Fh395ToUdPeVHBgnqeSo41YutappVXMD2mC0biEmGO9G8pNvn/EOEMsrY06FwbhhdOs09GY6SuLdAMbpAzzXs+0DiXeisHqMZ3jiOuwXiro6qxzzV1rsW7krODhMpbQEuRKunMiVEqRUXbqhJFEoVAhCAcKAlNIJrNagScZcVIKJ3Ui3sm3mhDeacQlIQ3VrOagFJvxZ8FPd0kauFWdbiN/Ss6AJfUdEjkOZX6b4He2HCeH2dlbP0ilSbTa1p+K0CAvgfYU9w2pcNADh6uqMr19vxOo2XOcZJ5r18fH228fPyfN0vvNhx2q4AG9ef7y6Drs3DD+Oc7+8vhdh2gqU4iocciu/YdsCxoa53vKt4nOZPot9blxkZPIzyXDu7c1KT7a5oU7ii8Q+nVYHtcJ5g8lDh3aqhWDQ6CSNzhXXXGLRwLg6Asasa7PzZ8I3Z9vAu2F7Y27Sy1dpr2relN+QM/okOb7FT2IteE3vae1suMUqhtruaGunVNN1J7o0OB23EZBEHZfSfh04dT4h2focft4Fbhru7q5+NRe4D6Hlp9pXyClU0uFRh0va4ObB2IyCsyd2+rXePrXEPgZ7ymanDO0lAE5bTu6BBHhqZP2BcK6+B3thT9a2dwu7bMSy7Df2gF63hXHbi74XbXjajiK1JtTGcxn3GVtp8fvGafxjiBn4y6dFa/1Nnl8svvg/wC2Fi4irwSo9oMF1OqxwHtBVNPsjx5xipaUbf8Ata7R9kr67V4ya7C2rLp5rBXfTdloyTIK1MPxX/U32j5/Q7F3Rb+Pv7ZjuYaxzo+yVrt+x1Jji6vfVHtG4p0w0/SSvUVH+sRzVRqNGMrUx0z/AKnkvujaWdCxt221tSFOkCTAM55knmU3kEgRsh1TVzlSAnzWPHlz73uACZ3nx6Iw0R15qLyQ7OwSDuW4Kvep4DjuYHsQYJE7+CcEySRthItEyBsVqJWizpirUazecDC6lbhjW0tYcQSORXHpPdTOpszyXRPEHuboiOsclxzl32ejiywmPzJ07GWkh0GPchllVq1SymCXTsMyo0bx0wceY3W7hV82jdsqPyBl3iuWVsm3fCceVk8IXHCOIW9LvnUHaRBkNjfmszLh9M+K+m/hXh1xw3RqYHFhGeWOnRfPON0aZrF1AENnAHQ9V5+Hmy5LZlNPX6z0mPBJlx5bbOD8aZaV2uqCRqGy+l8F7Z8Dq0BTdVbTcBscQviZD2Oz/AR3rwDOwU9R6LDm8npvtTk4J063H2/i/EuC3du7TUpuLhB2z58l8r7TPt3XLzR+Kei4zbuq2WtcWifP2hUVbmo+S8lzjlPTej+De12es+0/9Rh09Oic2STMuO6rcwkmZHlsm2qDifbCvolpcJXu3p8n7zKQWkgnZRJyQOa77LChUoknTv5lcq9txSqFrXYOJ6pjnLW8+HLCSshdp3n2J6ySPDkk8RIzhICdxnmtuMTk8lZSqFjpEdDO0qqJaekqbJkkwIySs1qL31iWiBHgqgTqgrRTa3SIieqg5kvjchZb1WqxtG1twCPFR4hZtpQQBCla1nUpAaQlxC5fWBnIOSuffqej+H8P83MeIMAqsiVa4Hoq3CAei7x5KgR16SkMjMZTIIdOOmVEgjfc7rUZGBv9C22Rp6TqIkFYtR/chr3NOCfNTKbjU7Nl8GCA0DY7LCHDbMbKT6hcM5n6VWcTGRCYztpMrujUeomN0jzkJkgkmD19ig5xnAk/QtxgySISPhz8kAiZyUsTnnhUoySdx4IO2DvyQDkiTIGEifWnwTaCCInfkUOPM7qO+QeUpknMohEnwPPKc4jp1SJkSAUEerHPbzTahxgnl0SOf8VEmDCc43/xVQOM528vBAklQBO+fNSkwQDnnKBgTgZxurQyBHvVYOoGVcwGNjhZyy01jNq/R3Pw0E+CrqUKjCSWuC7Vg6nABHOIWm7ZScw7GFx+NZXeenmU3t5dzc55cioHPlsulWpNL3Dx5LK+lpn+JXbHOV57hplqbeIUA52OeVfok+ZSc0NAW9s6QDjtJKto3BZkGFTpiIKC0BpzlKj1/ZvtFTtXNFUANHXfdemrdpuH16MNqCQPJfKgSJ9YyB/AUhUcMyR7V4uT0WGeXU+jwfaXLxY9E8PZcUvqFUOLXCCuHWqjImfbsuUK9SMucfbyTFY4BlduPi6I8vLzXku66DqkuycrRQvKlE6mOyFyO+zIOFJlfGXZOF1uMrlMrL2eutO0txTZodBbyg7KFxxvvyQ4GMSvMNrSQZ8vYpCqJ6jwXH/T4S7kei+r5bNWu2+8a8yI8UCuCMmSuGXmcGN0216gGM56rfw449dd4XEHB8ZWqnenRuvLm7cDklWNvXdSs3h21jzWeHq6d1R0iTHVUXJo1XEiNsLzrbt36RUzeOjdZnDpby9Xlqu6NOcELC+hucFM3BJ3lHfzzXabkcvdkfRM7FVPouHI+5dNjmHeFcynTqOgRKlz0sw24L6ZHVUvkFeiubJhaY3XGvKGiSArjyTJMsLGFxwohD3QFUXx4LpthYcqPvQ12MlSQ0i7ZVmeakUk2mkOaRU4ylCbTSMnqgpGZOyEUQORUXYCaRREW80FDvjFBHimxEtBUHtxhTIhMgRMrXUnSoLTCg5k8le4yoxJTqJGV9KTsoOojotZwVBwB2VlS4sbqJE4VLqJ9i6JbHioOZI2hLId3NdSM7Kp9ODELqPpDkFUaMYKzcI1M65hYoFpXQfSAyq3Ugud425mxd3zUO7K2GmFAs6LleOtzNkLYS0+C0ubKgWgLnca3M1JBSV2knZQc0zss2aalVlI4KmWkKMFRdoBSThKJUsUYRpBRMpweSyIhoKC1NB2QICFFTO0KCECCmADuhyBIQgFFMpIQgEIQgEIQgEIQgEEJpQpSBCEKKCoqSRShITSWQITQikmkmgSEIUNBCEIBCEIBCEFFhIQhA0FCCgSEJhB9Ppvh3Lf3q70r1IGPZzWEvn1humDiCYjwX1Ljvu8fVpc+oC4iJ8EgeQlVkwSTn7k2ugnbzVZWskHYEzy2TztMp0y0nf2K5opyG4gYRUW1cc+uNl2OE1qIA1BurlPM/euc2jTDZnwVQkGGO0mQueU6pp2wyuF263F6tMshvXkFgs6jadXU7IKqcX4kHbefpUQQGzPnhTHHWOjLO5ZdTqV67XUi0Z1DkFiFKSY5lVAuB0zjzVtKqW45xurMbilymV7juXifVgYInmE2sOo6gRHJdLhDaNSoA+CD0+lde/4fbejF4A1biMBc8ufpuq9HH6TLPC5yvMtEHkfH/BWCYiZnqtYtW5z/gk22JcQ2Y2V+JK5TjsVtBnBJnoM7/bt71vt6kUw0McZ69d0W9o4Oy2esrdbWOqmXyBEAEn+Oq5Z8kd+Phzt7MhDn1JiJHuXq+x9elbEiqzSHYJOcLj0bBxqgRg8wJXo7ewaaAaGkEHEbiF4/UZ45Y6fU9DxZYcnX7w+111aXNu1lEtLgCYAH2/cuV2eu2W9R2obZGPBa7jh7wSWsMcwB8Xn9hBlY6Vo5jicREzyH8SueHTOPpd+W53n+Jruv43f06z9NNgDRABjER9K5FOjVua/q6jEHZdt1szQTiY3PPzVdFjLf1wRGf4H71vDLpx1GOXjvJn1ZMF5SqW9CTnlhedrVC6qTjqBH0r0HHLwXBFIARzPPZcqjaBx1EtMuzDc+S9XFdTdfN9Tj1Z9OHhRVqHuoaT4AjbqrOGcRq2dUPY8tIODO6jd2xpyNoxCxesMAwZ+hdtY5Tu8vVlhlueX0Khx694nbd1WrOjEx15YXmO0Vo2i8PadQJ58isFnfVrV34swOnIIvb2pdNGvbpK48fB8PL5fD1c/rJzces++TC7AMctp+lQnY48zt7Vb3T3gw0kRJwloLTEHpHVe6WPm2VW2DkSdxndWUWajGkRzhRySZGN/YtvD3MaCHEAnmceSZXU2Y47vcmtaKZBAG0fx71neyXnTuMgLdf1GadxOICx2zw2pLhjmVzxyutt5YzeidSqNGotMbjkqHDOBK7NapSdSIBBwsFtQbVuQwnBO6s5fxLxd5IxOB5yqy7l9HivU3HZyq+076i3xI3wvM16T6NVzHRIV4+fDk+7W+X02fD9+KTv4BE+7mkSoz5BdNuCfJAwfNRHiZUh7TOQEaMbp5gkGAQrWMluTB2zhVuGlxb0U2thiZzIhSk/wFAZac805jnj7URfRcIzvsFd3nrtE5WRpPL/ormuhpyVLNtyuhScPjaojJ8Fz+NXfo/DbipI1OENPIyrRUmnJEzjfkuD2srg02UpyfWPiuOU1ja6Y3dcXgVsbm/GJDRPt5L6TcaW0qdsANNNgaOsAbry/Ye1YH06xGS4vOOQ2+lel4jVaXS0wdvYvPwzd2659ost6jKQAB8JlbLa6pAEOIg4Xn++dqwhlZwaYOF6MuLbljy6dSvcuo3grUDpc0gtPis9V9WvqrVjJdMkrL3siSSp98HNa0+5OiQuW3J7ThrbJopSNWHO5u5x5BeEuWxVIX0LjAo3FnUY6oNdOoIbH5unf3rwnEdPf+qIlcL5drPljnO3HmmAYICi7c+am3mrHNEqBU3YUCUCQhHOVUIpoQFFNCAhZyahhJwUkTIgrMay7kFNRAU281dkJSJho5pNUaziDDd4wpj+LrOz23BqVOlw5jqRkvJ1kbFwwY8OXsK2kvLdlHhzrV/Dbb0OoKlAU2hpG+BmehmcK4gQV9LD7sfL5LvO1WHVB19yupuqYhzgfOFETy9ivoNytMOlwqs/vGBznZO69zwvhjrui17nkDeJXjOF2zn1mwDndfS+z1N1O3AcIjC4ct14deLGXy5V5wF9zY3XD7iqDb3VF9u8xloeI1eyZ9i/NNanWtrmpQuGmlWouNOo07tc06SPeF+vSGvBaRqJBX5v+Gvh7eHfCZxQsp93RvS29pt3E1BL/AK4cuMy7utxmuz3HwMCnxXsfd2Jj0jhlzpGcmlUGpvud3nvC71fgVVlT4vkvnnwE8WbZ9tHWVRw0X9q6n/faQ5v0Bw9q+8XQpdyXSJ6rrM9MXDbwVfh76M49Xcqy2sqdVuT63RdXidVha5roB6rzbr19vXkGAtzdc7qNV5wlzZcwEiNgFxq9u+m4hwK9JbcXo1G6XlVXzKNdpcwtnwTdjXb2eba12rZWOJYBPRaK1Pu6sgYUKvrNwPYs3y1jWWo8EearkhWNpudUiMLVWsiyjqJ9ydUxOm5d2WlVDXZCmHdPiqgMMrTRoucB47Lf5spU2Sc535/Yr2sMjHKCPFRFJw3B5rXbAl8ESSuWTeMVspHp5rTSt3B2BjdXig74wbIhTp1G0wdUDlC5Wu2OOvJ0NTDBlvSOq1CmyqOU+AWR9dpmMcldaPLyYOyxZp1xym9M95Zt9YgrA+1eSQGnwXbudVMEuk9JVLa9OfW57CVqZJnhOrTh1rd7HAkFo6xus7wQTgbZXeu6lM/FIXMrtYQSCOsLeOTjnjpgiBjkP8E2vc0/cNlN7RMRpjko6XOMAZ5Lfly8NVHiNRlLRq945eKz1bjvSSefVV6NJI5csKI+KZ9nipMcd9lueWtVJxBMySgRyHsUCTq5oEjEieatxSXTXa02vcGFbBZtLfeuZSqlhEEjwW2nfECOi55bduO4+6fdFpLQYA3V9va6zkb52nKxuugSHTg7LTbXgY6dWPFYsunXC4W93WtOBVbkgMcBndarvshfU6Jqh2N9MZhHBePstntLhIBB8ivTVO1NpXtO7bGrTsQftXg5ebmxy7Ts+3w+m9Hnh38/V80vbKpScWEbZmcLBUpFo5eJC9/fcLfeufWYBkSvN8R4ZXoOfqbA6r18XqJl58vl+p9Dlx95Ozz5aZ/jZJx5x7PFa6tAiYzHMBZ3MIMkE75XqmT5+WNnZQ4T4pYIJAhWxuOSrqDkOa3tixHcqJ/qwRGFOIE5nYqJBPP/AKK7TREgDPXZROZO3kpObEj3GFGDDoCoQiOaTp2HNPBJAMeCRmCqhEjYHB8Ei4A+aHDeT5JQZnYoCc9DPTknnIAERgfckd+v0wgndEKSD6wmOuyNwDk5QM4krfa27H0wSJWcspGscbXOcCRuZ+5EHqr7ukGOMEGemFRIjn5LUu2bNE/oD5pSABncwm0bgpGIiVUTpuGoF32LV3jYwsQkDHWVMu5SsZY7axya2vLcA77KD7h5aQXnGAs5f5+agXl3LH2KTCL12LzXxBmVF9ST9MjoqCdhk80i7ErUxkTq2029MVBmBnCnXotaMD6VRRrFpPJpxv8AxlWOuDUaZGVmzLfZqdOmZzRJ9VRLcYAxjC0NpOecA74UKjXMJnC1MmOnsrezczPsSawkk+AVgjcx4qyk5oxz8eSW2LJGapTIPWBCrdiJk+S6JawkgNkADZVVKLQPLdSZlw/BidzhRJMY3+1W1WwTH0qojcNPL2rcYLvCJGwKmKx6+KqLZPtS258uiqNIrkESVZ3gIzIJCwunn5I1EDdBrcQearLiNiqNZ31SjvDzQXCq6cFSNZ3MrIagJUtYmFbpG1tYgZKkKvisJd0KXeEc1FjoCq79JXMuXN2cuQKjgdyptuMZUs2dVdj8IPiC7Cz3Fdr2kiCSsHegiZQHyFJhIvVb5U3LSSTiFlJM5W5wBEqipSBBWmVDXYVrDIAWd4c0wmxx2VGkJlshVNeNlcwnoosVhnRQIgrQWqD2c8oaUlRcIwrS085Vbwd02itwTTOUQmzpVEIJwArCFW45Q0Rd1SJxCHbygjkhojskSYwgzCQ5+SGkCYSmUzgpqpoSDsomCpJe5NppGMKOmd8KcidkOEZV6k6VT6QIVTqQhaNkDKsq6Yn0vBVPpyujpHNVvpicBS6JK5xpwNlW5ngui6mCMiVU6jyhZuMqy1g0xsoEEmVufRI5Kl9Mg7LneNrqZHtyowtRpqDqYWLxtzNmISc1XlihoK53CtzJVA5oCmWnmows2NSoHJTjxQQgqaUuaJ8E4UVNKkVEiUwhZRBCkRKiihCEIoQhCAQhCAQhCAQEIUUIQgKAlBShNAoSUkJpUUJkpKIEIQooQhCi0IQhGQhCEWBBQUiihCEIGgolIoBMJJhKlfRTLgDMnnlMEgGCljIBPVNpl/VfWeI8lsbpjly8wtVOk11OXe9UVNLHadxG6zMpe0W42ETMgKTHP2BMbz4qHrRABMb4QHesJOJWkaBWc1pAO8Y8TzVtF3rEk5WUicwJnBUtR3GDtss2NyumajHMggO9qzVIJgGRyVAeZ6Qd1Npc7YYwDnzP3LOOOmrltMdBHRXMYNOqfZ4qmCNInJ8PNX62xAEHkFcqkiVJ72ODgTM4z0Wz06u6npLySd87rEGVInSd5UmD1pmMyPNcspK645ZTs20q5k5AXQsajdUuiN4jM7LlWzWuc1oJM8+q9Z2Y4E3iDw5znD6ee/2+2F5+bKYTdez0nHyc2cxwdng9tbV2QGNPUbkx9y9Dw/sz3tQ6G5iQ3mDG3uXNfwlvC3BzHyJhwd0XqexvF6JuqdGqWwIgacnafoA9i+Lz8uWrlg/VcPDjO2cm2q17C3DnaxTHVg5jxldmw7C3JaGmhDQIC+o9mWWtzSaWFpE5gL11CyoNYAKbfcvnYcvNzXUry+p9dh6fLpmD4fW+D19SnJptaYxB+/8AjcrjXPYdtHU57DqgxA57beXPbK/RNe0oOYRoavOcbsaBpulrYCZ8nNxXVrHp/X4cuWssX5g7T8L9BqvaHQAcQR08do59ZXmqr3FhkGdvV2HhnZfV/hB4Y591UqtZ8Y4O8naD0O3sheAuLYNYTBOT8aPsX1PS+omWMtdPU8Hft2eWbRDnkuGx5jZSqBzMySAIiMR59Vvo2jXXTWaSxpJE9PI/wF7Wz7P8PqWQc785stMj2efP3r18nqZhrbx8HoM+XfS+X3THulxByMYWOhZvramwdQ2xuvpN/wAAs+7cGkEAkAxiPBcq24Kyg8yS4zg4M8uS3h6zGxx5PsrOZ9/DyF5w80GmDqAz0/jyWO2pCpUDHH1Zleo49aVXO00w0tAiJwvPd2+jUmIIMRGZXr4+XrxfN9RwfDz8dnquEcPtxbjWGhwH0wuJxy0pio80xAacxt4q2nxNwpBuogkbgqqrW71sAZnGdvFcsOqZW16+XPhz45jjHEc319J/6oB2Myeq1VbV+okNcBMjGIVZoObyML2dcsfL+HVDyTvlNm63UrPWzxWerSNF0T5KfEl7N/CyneqajyOqVCs6nUFQHbZRuDqzHuVfrA8h0V9mfF29RbdozTtO6IztJ5LzPEKwuLh1TmZKC+WEfQFQ+eh33XPi4ccLbHbm58+SSZeyuJMApeePFA56ifZ1TIIGT4r07eTQa0uwMyJK0+i1QwOiBGyopnRUBgYyuh6Y004jKzllZ4dMMcb5ZGkiGnl7kVQOQ+9BrbeqQefioFxLuvVIl/BssLF1ySWEAfQnfWL7R0PII5bqzhnEBbQHCG88J8VvRdlrmjA2XHq5Pifk79PF8Pc+85/gpgwMHxnooDz3QTJ5r0vNVpPPmOq8rx+sa9+8zMHSPYvSPqClTfUJkNBK8mybi8aDJLnyV5/UXtp14Z7vV8EYaNi3JENDRGN8lbaji9uTnZUUZZaUm421EdZVjTgCYPktcWOsYmd3kiGEAwNxuo7npPRaS5raZdyiFkJ9YjlK6y7YWNOPNTI3kA9FW088KwOgGVnLs1HA47cXFL8RbNl73y4xJI6Lzd+HMrRUA1A5jqvWcRgXVatIDabZnovG3dTvKhf1Mrx37z1ZeIxE+sfNNx9YpH4x80cwtORFR2U37wkVURRzQUIBCEgoJBMKITWa3EkgnySast6iQUgN1FTAS+FnkK3hdhV4ldVWsr0LenRour1qtaoGtYxsTHNxJIAaJJJCqOyz1AQZAyFrxG/Z9C7PV+F1+Hj8FN0U2/Hpn4zXHm7rPVbwD5Li9jrC0teFU7uiXPr3LJqPnAz8UDwXbaYjqvbx76Zt8vP71arW170j710KdgxkEuB9i5tvcupFTrcRqEY9WB1W7U7PVcJp0WFuQvY2ddopAAiQMr5Na8TrU3B2qMr0/DePNawNc6PvXLPHbeOWntHXjgTHsXx3/KJty6twjizWzIfbVCPAhzftcvoLOMW7x8fPivHfDEGX/YurVpkOdbV6dWQdhOkn6y5WdnTGvk3ZziNThnaHh96wwaNwx3smD9BK/UIu21rbvKbtQc2QeoX5KqOMtcJBAC/RvYG/9P7M2VZ9RznGi0SdsYVw7wy7HxWsW1CXHdcuq2nXYTqjxXouMcM9IohzHZPIBeZr2V3avPqmJ5FejGxwy3L3ZqtCo1xLXHHiraNzWptgnHVVekODg15zzVgd3rQQMkbIn0b6VajVbLjkD3q2lbUqhHIH6FwKra1Jx0lw6rq8IuCyBUPgpY1MvZqq2dNgDtoVVeoDTLJEREhab24a6iQHT0EriOrO1nJOVjp6vLfX0+EiwBwJ6roWYYQJIXKfUJMnCspVnDIW7OzMvd6SnSpPaYAjy3SFs1r9QOx2lcalfObIncLVT4mXDLuS53C1uZx3qRY2mAYnwWO7ptqVNLRHPbZUsvg5hbIM8uqQqjVvjnK4/Du3o+NLNVCtZvazXq9gVVvcPoOG2+QQug576lNwmJxPJYKlBxOzo8VZN+WblJd4tFa6NwIAkeRwqRaVXtJAcYn2rpcNs2GmHPaSTmVqqOp250gLlctXUerHi651ZV5ytQqsJa6QB0WdzHTABPUrrcQe17i8DngqhjdyRC6S3Tz5Yzq1HMLHCdTep2TpU3SC0HPVdbQwvjS09ZWxttQZSDpEnwUy5NN4enuXivPV6biI05jnssz6Tg4iIXoK9NjxHXdYKtFveZgSYJhXHNjk4bHObRfvGDsd1A03NMEOneCNl0xEgEbhVloLp3O0la6653jc+I5H71ITy/wlbKlIEEB0Ae7zURQ1HUJ8AnUTjqgBxdsraQMTgH7lZoLQBEHxQ1hB5/uWbkvTqm2RAkjy6rTbPexwMkc91XRGYMrdbU2TEdZXPK9nq4ePd29JwvjbaNFoqgCByH3rHxK/o3DnED2kLKKLXtxB2Oyoq2hM6dXjj6F45hjMtvr5c3LcNVmuWMqNc4NB8lhrW3QY+1dI29QdSYwYVbmEDM4x1Xpxy0+dycW++nHfbETBxzwqalBwJ18vYvQUqLHP9YD2re3h1CoySGTuCtXnmPlzx9DeTw8a6kZmDt9CrexwzG3XmvZv4NROGgCVyL6wbTktgjmVrD1EyY5fQ8nHN1wCMQd9slAZOZgA7LpG3Bbpg/vKrdZk7NJMbLr1x5fhZOe8GdvYoObHguu/hlfQXd06AI25LDXt3s+M07ZHNax5JfCZcWWPmMmNyI8VF24O8ZVzmQIVbm7cv8F0mTlZpAiDP2pOicKTp2OfMbqJxMAyFZU0TcE9ea00rl9NojkeazN933JTI3n7lbNkullesamTEKoCJ80EjdBxPmkmvCW770jtJI3UZnVHNGolRnHJVE5Ojbfook7Y8ESMbclFxEmZREtcRv4KLo5b+SRMZE/xzQ7JnO+08uSB7HnKRdy3ykTLZzKRJOI5ckVMOBBBO+yC7OT5KvyTPJB0bWuAIIBgc1RcvDnE7rK0mcE+aNZPmsdHfbXV20tDs45bFIEnyEbKud1psWCq46iPZgK5XU2mPe6QL3Ayouq4BBwOS1X1BrWamxtlc8/RKmOso1lvG6N7uYhRmR4qDjBMElBPTdbcyj1yZ96USckqXtUQXHOEQnDEe05UD4FTk6j0Ki6N+SoiVHdN6QUETgqLSSdlNQILUEicbpayFEoInwSCWsdFCUASh2FUGo9VJtQ9AqjlBwm10vNQczCsY4EYKxgqTXwcGEGh7A7kqn0HA4CmyoJyd1LWFNmts5Y5vgmyoRhXHKrLRKuzS2m+TBWinpIgxhYo0kgKWstyJWbF221KYIwAsVVhBiFpFcEBM6HsOQpN+63TnmBsoqdVsPPRV7hVDMKBEFS3SmFRAjKTt4KlIIIlROUPBEcpKiRB809RUJlU0R96DAGSmVB26GktxISI9VLKUIaLdBnqnCjyV3E0CgbQg5QcJtNESokpEqKGkjHVBgBR5R4odhDRkBVPaOasSIBQ0zmmOig6n5rVAUSEZ1WJzPBQNMwtpa0qp1OFLGtsZp9QoFh6LYWKBZ1C53BqZMZZlR05WpzDKgacrncG5mzwkWwrTTI5KDmGMrncW9q4QFLSUiIKzY1tEpQpwooqKEyks2KEIQoBCEIBBQhAJITUXQ3SCaFAJFMpJaAIlJCgEIQpVgQhCAQhCgEIQgEIRKAKSChFCEIQCEIQMISTClSvoTZkjopFw1ZOZ5dFASYAy4jyUnHHPSfevrvEubVqadIJz059VBxJxDp2UZkwIA+1MtMRpORDh1U1Iu9pTs6M7glPAOoR096UkEFpEgzIQScScjO6qJiMc/Cd0ziRMqAwSAdxjrKnguxn24QSYY2JbjCspv0mY+nZVEjYTupsHxQIPRRY0HU4knMACVfbteKoOkuAyuz2asLeuQ6qZMwNWxXd4hacPtg3ToPXSefVeLk9Tjjl06fU4PQZcnH8TfZ53QSwwwmRIkSqxw+5qOc6nSkcsLpm4tw7Dmkx/H3rbacTtm0u7c7bcb+xc7y5Tw64+m4srrLJ5prH0nllRukjOV2+Eccr2LtVLHKFzeMVRWra2AQc9MrJSd6wB3W7jOSfM8+PJlwZ34d8PU8Q7R3V9pD3kAHA3zmfLwU+G8UrU6movdOZyZK5VnZXVwIpsqPjdwyt7OGXLG6nMgEAOnkcc+Wy81w4sZ0vdx8vqM71d31LsN8Il7w2syi9xq0jAjbTkZX23hXwj2dWyY+rUaw6R8YGdl+QGVXW1U5IIPI535LrO7TVm0XUw5xLsE6okeHVfN5vs+3Lq4uz6GPqODlx16id4/UVX4SrKpX7kP0tkAuP8T/1S4r2ssfRHudcNBDT6s5np5r8sW/Hrg1ZFRxOACcyOn3K+67Q3TaWhtVzQCCA1+/Lcct158vsvO3vk3x8vo53xxfYLzitpxKu5neNJJPOZPj9MLm8U4Va+jFzAwOAkEgYzsvk1t2jrUaze6qRBgb7r0bu0VxdWxY52HSCZMjwx0W/9Fycdmq9/F6/g5ZfxVcWNG3E03NBbt62+T7tlzrbj106KPfO7vbSJiRtOevRYLt1SvVeXPJg78lybn8RVLWunkDzjmvp8fBLjrJ8b1Hq88c+rHtHqn8YrtfJ9cEyBE7fwYUbniVxSZ3jg6BzA+/2leZoXR74VHmIOZx4LoXnEKL7YsbuRgAfZ4LV4JLJIzPW5Z435nQocUo1KWio5upu/P2rm3Qp1qju7gAjAGwXGZUd3haDA2ldW2YwUw6Zn3+1dujo7x5Pj5c/bJUbJxdNIertPX2LocHsgLtnpDdnTnorOFXNFlQ6i0RAHReptLClesDqYz+kF5+f1Fxmq9npvSYZXqjp/gCwrcN7x+lmBEbzC8FxqxpWtZ1KWuHI9F66/wDTuH0nNaTpjfovFcUNarWc5ztTnHPgvH6XPPffLs9PrJjZ2jFSfoJEYWa/BfJAhdCxsa1zW0MYTy2XoaPY/iF3THd0cg/nL25epw47vKvBj6fPkw1I+evpycjy8ExbkiZJjxXqO0fZy64UPymnoJyCBh3tXAbr0nSNvDC9XH6jHkx3jXj5PT3jy1ky0KQFcNdB5+a0XtKl6OXYB8AqabXGsNQgkmCeS0XFtVfR1CYAG4+1byy7zuxjj8t1HOdSaGzJWdwzzhaKjoGnfMqpzuUbL043bzZSIAEmPoVml7GyQeu6VM6XgkSTv1VpeHgAb7JazIoMkTndAHMbclsNrNMkOG0rOGku0t23VmWy4WEdQMexMgjrI3UnscyJ6oBhpEeabTp/FFuDMYTjEQtFhRFW4a18aScrs3vDbdtqajBpc0dVjLmmFkrtx8GXJjco8lxqo6nw9/Iu9XZcDhTfywOnOwjrsF1e1VQNFCkDvLisvZq3bVvWOfOkOx4wJXHmy6stNYTpx29OQA/RgaAAPYratINoh4duqmlrnGcE8+idR5Pq5gAL0a8OU17kCdJyVo4dasruJqcth1VAgMCVK5qUXDQdjsmctx7LhcZlOrw13tqy3+LgTsSsoE+t4wldXj64GqfJQZUJaG9DKzhMun5lzyxuXysHEqYdcXLXEtoejfjiBOS6GkeW/kvG39F1u80XxqHMbEciPAr2HFqhe24Y0Q5z2g/qgT9pXnOL09Vg55OaBBafAmCPeZ9682V+Z318riub0S0+KCUA+CbYsDonIlRCZMpLUrKJGUQQJhMGFY94LQ2B5qWmlJQgoKuwBSCQQs1qJBNJMBZjpUm81IZUG7q0JL3bxiDsKioYJWh42WWvOl3kt1a972PplvZy2JbGpz3CemorqtGTIVnDqVN1rbstwDSFJopxtpgQvX8H7EXV/btrNrMbO0rvlz4cOM668WPp+TmyvRHjwDg7eKg9pb18cLtca4VW4XcmjVGQVzXZaZC64ZzObnhyz47hbjl5YX6myCIVZrVRs52FpcwFxVbqW+B4LbnoUryuw4eVoua7+IcMvLB8xWt3tHnpJH0gLG6m8Ext1Kvsyaddj+QKxlOy49q+TucHER0X1/4JuKPp9lhQOQyq4AztzXyrjVqbPi93bEAd3WcAJ5Tj6F7D4K74Uhd2r2Nc3D4J25bLjx3u75Ts+uW3HHtBZoJC6FvWt7umQ/T0I6ry9tcUSZECdgF0barTaAQ6DvPVa6pGZja1X3AqNaXNABORAWOnwr0d3rDC6lC8bozU9qz3tbVqc0yPDkVcc9s5ceu7FcWdIjkCNh1K59zaVB/NCR4JXFasKxDSffheh7PWza4Dqu20T4LpbqOfmvKut7yPiujyVlvZ13fGYV9KFhaj4zWnG5TFraNEhrRPRY+I38N83q2FcZLCPYpULCrUdAC+hutKLwYbJWJ9tSt6jjpACdZ0vDXljVt8mcxus7ZK9L2irU3tLQBA9689SaCT0W8LbO7GXa9gHlnrYI6Hqr6F0WwBEeJ2VD2ifHoqg120EkHK1Ueis75gEmCRgyF17d1GtI1ZAXkrem8gkbytVC5qW7t46wuOUjrNyPZUbcAYgY5LPe8PLxznYQVh4bxkRDnAN2A3jMrv2t3Rq04OnO643HVdpnuacA2BDiwxyiQcwp1LKkGkHAHXZekdbNqMJa6JyNsLlXtk8s9QeICeTenEdQDCdEjMZVNapWDYMxGwW829ZtQ6mzmJ5LTRtdYgsyPpWrhEnJl7POsqvyY55U2g1HRsPDZehdwim/YeMHZVjhYow4ADkcLNk9msc77uS7h+ps7lZH0nNJ6DwXpn20NwYlZqti0ucSZB3ndYd70Xw87pMkNGxgq+mQ0esGycSurU4f6p2Bn3LPUtw12Bk7DkFLWsMLO7HpFUgtiCdgp+hvcNQEeC1UqRDgSMfdOV3LMUTbgHSTv5FceTk6PD28PpseW93mWW7sYjnnmr6dOo3Ee/711arKJrODQNOogQce/wVtGixw6efRc7zdnfH0sl1GKiDqAg9IIXRtrc1QZE4kyDv966Flw9lR4aQAXc4wvU8F4BSrkMEZOByx9K8XL6iY930OD0tvl5E8NJaSGkycYyfYsN1w8NABaRGy+28O7D0rlkFw9YbLFx/wCDauy3caD5MdPcvNh9oY77t8nHxW9O5t8Oq0WsfgjG/VVmu+mwR9i9H2h4FfWNw5lWgQfBedurd7XZb79oX1OPkx5Jt87l4s+K9lL+JVAdJJ9yw3d13pnG/wD1U6tJ25HPmstVh1ERB88L0Y44zvHz+Xkzy7WkKmdoHJaLKuxty0uIAGT71icDGmVASCSAAOq6Wbjhjncbt9HtK9g6wglmqDE7rx/HmW5rO7poAnfwC59OtUAMVD4ncKMVKgydRiCvPxcF47vb3ep9d8fCYdLM9rZEgeapfSbggwtdSi85grOQQ4SvXMnyssfxZzRLpjJzChUtngEx5rXRfG+ZzJwre8Gmce3ktddZmEscp9MgkEe5VOaR62k5W+vBOAAs9QCI36rrjm5XBljwUY6yRv5q45JJg+A5Kt2JyfLqtysXshPqnlt7EnbkzseSHSDqx4Jet4iANlpkEzMTty6JbnIlP3jxUXbc8boAkARtOUOyIA9qTsT96HEScyQgCfWIzEZSJ2GJSBExgBLn4oJAwfPwScZ6gHqlJCOUzyQiQOqDjIykSAJ+5RB2Eyidx7EEpkRuQcwVOjVNNwIx/HRVD7EDqClmyXS6pcvqAaiqZmQkSI2iSk4iOSkki3uHA9cBJ0c9+qJ5dUnbxhVkGSkSOu3RI4B6fSgHPIYRaRMNkZTmeiCZjmEnTBxCGkX7qBUzyUEAoY5hTS0+KIhEeKCJ5pqLhJQHJJCEXQJ9iicpmOqgSiAlIoUENLGlPWVUBKZB80FgqeKDUnYqrIQgsc943QHzzhVk4ASmEF+s9VMViwRyWXUYKJQX1KgcZOFVqCgIndCgk4qKCRsoknkEEkiVAkzkIJ3QJCZKiTK1toIlAUXbyiCZQhCKiRCRUikoySRThIqURKNKaikCQmSoKrow6UFQIUmnEYRATCg7Kk4zsoymwiJQQkThMmRG6IhpyoFgJyrDnwSIhBVoPVQdTInCvQVRkcwyoOZIWwtUXUxOVm4yrKwmnGyg5kbra9ngq3M8FzuDUyZHM8UtC0lg8FWWFYuDcyUkJOGFa5uNlEhYsalUIVhBCULHS1tBCIKFnShCcJIBBQEHKAQlCaig7KKkhTQihMpLNihCaEAkhCGwhCFFCEIQCEIQBSTKSAQhCAQhCACaSYUqPoIOM9MwgGZjylKDv47q+nb1HNDm7HoV9W2R5JNotI1RylbaQZ3Y2/eVzyHjDtxiU5d8XkeQKlmyZaWEyIEZ2UZbHxsePVDXF3xiBPTCYwJOwxstxkDMnwJgqctAg4E+xVtdBjCkIgyfcgmDIGDMbgfQptedQIneeSrx0goEASMjlCiunZ8QrUPiFoOYJGysrcTubjFSqfDxPQrmBxgZiPBNrzOfoXO8WO96dZzZa1vs6NIlzNQIJ5DwTD3MqHcgGVkp1nN2d7OisZUJdJeZOFi4LMo6DamsYEESJVtOk9jmvczG+22Vq7L0mVrprqobA5e9eh7RU7KnwwvY9oeW+/ovJny9OfRH0uH0l5OK8tvh1ux/E7G3oN1Oa1wyZ69VLtFxrh9UuNCM+O/U+K+X+kvadLXkN5ZVrb12Jwea5f6HefXt6Z9s2cc45j4dbid22pXNRrt8ZP8AHRc/0kAxq32HhKxPrOcMkE/f5IJ1TB8ivbjxdMfJz57ndulTuiDJOPAcla+7LwckxkgHAz0XLY/RIIHmuvYU6VSiCRJPjM+xZzxkb47ll2lc11ep3hg5Jxj3+xa6XF6zGwDjETyHRZ7+kG1naeR5Y9ixOdz+LgNyV0mGOccrnlx3tXVZxSoJB28VRcXb6jpL/pWDVnmVbTgtJMztq6LXw8ce6Xmzy7WtFOoXVA0nnyWuoW92fW0xkxgrmOdpd6rtI+1S795EE4Klw2mOftWltRzQXCYmd8f9VspXLyyMgDkPzlkpvY6mWu3GyQqaXRMicQsZTbphlZ4reys5rwZMzuvrPwRvo3tQU6rviy6Cd4K+P0nF49vVet7G8SqcMri4pPDTiRMSvl/aHF18Vk8vr/Z/JZl38Pq/wo2trQ4HUuKWkOYAPeviFxel7yTzXou3Hay64jR9CNQ91+cBzK8c1peTpM55Lz+g9Plx8fzu3qubeesXsOyl5a0/WqaZkED2cvFe64T2q4dQaKbnBuIEL4yKlW3w0nOITNzW0EkmI9qc3oJzXdq4etmE1Y9z8JnaO34jSp0LeQGn1uhjkvEUKrO7z/1WC8q1Xai8bCBCqpVCZGrcr3cHpZxccxjxcvq+vk3pouarRctLTpEjkuvTu6PoRa7JLTuuZStC9odMFOnROvuyV0zmOWpvwmFzwtsnlz7sNNVzhABVdrTYa0uILRkZ/iV0OIWQZSL2nyC5zA5pBzAlerDOZY9nj5MLhl3briizuzDQHDY7LmuY5pmIjK3sfqABIxgqxtv3zmszB2hSZ9Plbh1+GT0l/dkNaTHjyUaNQNMuEkxPgvonZ/4P6nErRtR1YMDhjGIXM7W9i63B6PfF4dTJjIgyvPh9ocGWfRL3dsvRc0x6rHka1VrsN68lSSI2z96vdbETDSQFVUZUbIIXsxseTKWeSZUewkh0LW++r1Gd28mDA81h0wATM55KduCHd5EgNJOFrKY3vWcbl4jzfairr4k5gGKbQ37yt/ZNnqVaon1KRk9CTA+gFefvqzq17WqOJMvJXtOyVCnT4JXqhgJqOa2fIf4rx9Xz7em47x1FlIHOMkJnYwR96121Jrm1HPIaB7FS9jNZAcTnBXsmfZ5unTNUdAmVU4w8zM9CrnML6sDkM8061NlMZMkmAr1JcVONPtTpmHDMKsyXaWkmE2scQDkLffSaa3OtbizNGuA4Bxkt3B815nttecOo8Op8KsQw1X1A+sWnUWtAwHHqSZjlCq4699SsLOmCAzUXHYucTufZAC8tH4wgCIMLw5+Xqmfy6SDXO2BMKMmVfbXjGU6lEtBMrM7JWNppKSkSkhNnSJRKEImjKQQgLUpo0xukmEqyJNCBlRCcwptpYfVwptVR6qYMhZnausSIlUVGEFaFXVGPNdl0972DrD/N61AcXGmXMcIiIcV9M4N2urWNo2k2mCGtiSV8l+DqvTrVK1rccSsLJjWNLGV3Gm1xEgunaTifJfS7PgVxcsHo1S0u2fpW15TdPsmVOT085cZ1TbnxZ58eV6K5naHijuI3Rq1IE5IhcstkZ6Lo8e4VdcLew3Nvc02vEy+kY94XLp1aT5DKrD4SvTx4dGMknZ5eW3LO3LymaOPvUW0S4758lcHObjccoUW1iHetK3ty6YrdbEEEg/ckykWVPWbp8CtL7kbHYKt9ZpEjJU8mpK+d/CNQNLtLWq6YbWYyoOhxB+kFP4O3E8fFBpJNZmkAHcyut8J1FtRnDrqDJpPpk/qmR9BXmOy16bDj9pctHxKglefeq7zu/QPZzsVd8XpONKo5j2n4pCy8X7Mcf4TVc2rQqFjdnNEheq4d2oFpStbu2azUGQ+OY6/Yuy/4Qra6pOo3tq0NIjVIXgz5/UTLcm4+pPTel6JOrVfIX3F3SABDwOh2UTxWuwaHThei7U31hXu6lWgAQ4yYgryF7Va4uIG6+jwZ9c3Zp8r1GHRlqXbW3iAcQ52DM+1dSw4662IAIj3Lx9SoWnEqHpL3YyvV07eTq0+mM7Ris2C4AjxS/DoDwTVE+a+bi4uGtkagEPuq4yXlScZ1vr/C+MUHxqe3PMlabx7K9IljpEbr41Q4lc03SHu9uV3uHdparBDzJ6krN47GpnHc4xaVZLhK4Z1MfDl37LjFK9bpeJnqVXxDhnesNSm3xmFuX8WbPeOVTh0Tq9im8ZEHz5KDrStTeQWOPhC1UbSs+nBY79yWJBa1g1waTiV0H2zatPVE+P3LJT4ZX1gaDvGxXWsaNUMDXh+YBDhz5ry8s13j2cGUvbJwalO4oOcWAgTIIV9lxStQIaDpzlewtrOm+jlg1ETEfxlec4rwWobhxptgg5hc8ebvqx25PS6nVjdupYdoZI1v2K7Vvxe3rRJEnkvAjh9xTdjUZEwFu4bQuKjwwkjHM5TLLHyxhxZ2609w19pVAdgnYYUqdC3LZY8TtkrjU+B8SdTDqDi8xseaouhxqxnvreqOWqFyx58Ldbd8/Rc2M3ca9KKDYwZxPsWe4DWlwkuK8me0jqRGonBiB9qnT4+2qCC/HTou0m3kymmy/u+6EN8dxyXLHGS15Dsq+rUpXLCS4H2LjcQsjBLcAxhdZjHO5Zezv2vFKVUevtsF0KQt6kEkGQvnj3Vrd5OZ3JWy14zWpmHOPvlTLi/B0w57L3e2rWrdmyQRvCyupOaCJwVx6HaDUCHE5OZK0t4vTccuknlC894vxevH1P5tuh4cCJIx7lpoa4GofrdFzqfEqZiHDPMLQOJUw6fVEGQCPt+1cc+N7OL1P5vQWdWpTM9Ovgu/wrjb7WqHGYkbc14+hxOjA9YDHjkLXbXTKj2iQS4heLl9PMvL6vF6vWtV9z7JdseHP00q1QUqnRwhe9t76wu7cEVGO1DGV+bbK3qGlrp6o3/6LbY9pOJ8Jqt7u4fpH5hOF8vL0nfWC+o9Lhy/Pe1fbOO9nOHcRYe9oseM8l847T/Bzay99u1rDGBHP9ys4d8J1QNay6pkcjpzK11u3/D7lmSei4/D9RxX5ZY16ecuPy3KWPlPGOx1zbucDTMDIxj39F5m+4NVok6miAYPRfYeJ8cs7lp0wZ6wvKcYq0KupzSB7vYvpen9RzeMnXn9J6fKbj5hcWrmkgtAI6rM+iZAOei9Ve2wJAaBA/j3rFU4c4+uGbeC+pjzfi+Lyek7/K4LWNB8lqtiwGXYg8xt5rVdcPqsElpAWN1Go0kZz1XTrmXhw+HeO946DbVlUQGjVtAWO94Y5kkNMdB9i28HrEVmtfBxI6r2Vnw2nxCi0ad98cl5eT1F4r3fQ4vSY+pw/N8qq0HU3GQQVS4OggSF9N4n2Dvnt7y2od40jAn/AAXleJ9m+JWhd31lWYAei7cXrOLPxXh5vszn4/8Ai8q5pg6gd1QQ7HNduvw+s2Q5rsb+qViqWjgfiGfDmvZjyR87Lhzl7xzYIxIlVvB3iVsrW7gTGc8uiz1KbgMghdpm8+WFnlnIA3UTsc46K80zncKGjPmtzKMaVZyeaROZPsVjm+9VEe8c/BaQNgSQd0j4p8lExPxgUQxucx7FHOd1Lr9Cj9CAORvzSOMGU5ylGfjIQpHP7EN2zJlG3/RAEDdAT4fuRIyJ2T5ZUXQOe4yiDY5JkJNgnOY2QcgeaIAyIyilOJGQl+bj2SnGNhCRPUoEZmd/NEZnmg+aRmSJQ8HgA+KckggzhImeUQUTIP0obROZOAoKbucqJQhFRcmTB6qJMkIgOR4oO26BBUZg7IGQkSCET4KCLoEQolSUSiEhBzyQgjp8VKPFAQikRKSbklColM8youKkCm0QMo+hP2qLsqhg4SJgb+xRlBPVF0lOCok5QVHZDRoQVFxQ2ZSOE0nHCKOcIJhKYCCroJ3VIGEJQohuUZjMwmk4SEqESjVlIpTKgZSOUpASKihKUHZGwhAiUipFRKBIThIopHChgqRGFHZGQEplNRKbDd1UQUEyoQrtdJkiUSEtgkBCbNG4+CTgNoTCHCRCuxU9gBVZbGyvhIiVEZ9JnzVb2HkFqLYEqLgSs3FdspZ1US0BaHNKi5gJnmudxamTM4QVHTiFe5p6KBaVzuLpMlfsSwFZBSLFnpXaoxyQrCIUHCCs2Lsk5SQooQgoU0uwhCJQ2EoTQoEUlJBU0qKE4SUqhCEKAQhCAKSZSQCEIQCEIQCEJhKPoIMQRtykLWy8DGAEydlz2u9YjpkhSbtMzz2X08sZfLxzKxbUeC5x28+SiDMFQc6Oo5ymCI5mY2H0rU7InJ6CUyfVI3J2UGkzBgY+lS9u/NWokQZgiNtjgKTSJ9sKuQGnCkC7xRFhLpmAY5lMEunmZ8cyoNJMlPVnAwQirREScpiMAnefoUWgaZk7D2QlLsw4kbwosTnII5qTXetIPlGVWCfVA8t02mMmSmiO1w6+dbtwY09Ps+lHFOJVLn1XuMQBnwXI1FronGSc7omRE7QuPwcerddvj5zHpl7LC4kHZp8lNrpfJM8jmFTI1dBPNAdAk7xnnC7actt9HQWucZIgSOa1ULG4rMLmNJaAuXTdp3+1eu4Pxa0ZaaXOaC0RBHPdebmuWHh7PS4YcmWs7qPP1qT2v7s6muJg4W23tLsU3REdJ2/iFC9vaFXiZqtMtwNtl1qPFrZlES7ViJ2C5ZZZanZ04sOLqsyyc4se1oFVsuOMZBPmuXdfzjhpyd16Zl1QrFxB1TMj7PuXF4mKT7kGlpAA9aOZjHuW+LO77seo48ZN43bnAE7b7rXSpuMdCN+a6PCeC3FwS4UiQPaq+MUXWThSILHj2rpeXHLLpnlynBnjh8Szs5dQkeqYgY8lCZcd0nv1OknfwUC4DEx4rtHn3utVI8gYHVSOoEzMdVmbVIG58FY2uTggLGUdcL7O3wqmHtAd4rfeA2tIPY74wnBwo9l7R148MY4fxutHa6yqWYpnVqDwV8rPOZc3Q+1hhceDreeuLh1SqXap8VZa3RZAcZJ5rNZBrqxa7kcrde06LKOoGXBenLpnyvFh1X59ralQvbMTG6dKvTI0HdYaN2HAgyI2lVuBq1jDoaQmOHtVz5N943XPd1HQ1w6b7+SzOtnNGprlTWL6RkFdewtzc0pEgROVrPKYTdZwwvJlqMlC9c1paMSEd9UNXW0E+3CV9ZOt6gGPsSo1WtBa4jCxrG943vOXpyutHcXhqMLXSAcHwTptp6JxC591V1VvV22OFosGuqmNht5rp09OO4xOS5Zavdc2kDcAgYG4W+iRTc1zSCWwVnrsNJuNwFS2tU5gz0XK/POztLOO6r6BwXtrWsabaelpEQekLD217WVeLW4okDQPW22Xj6Ty9+5VlSm4wCcFePH0XFhydeu71X1fJlhYKVZhwVnuDrfhvPZXOtSwapCtt2UnYcMr29UnePJcMsvlrMG0y3aT5LBxip6Pwus7aRC6zm0xWgGASuF29rU6NBlFhmW+W/8A0T4qZcWu7xbfWM9SvoXB2ilwihTZs5uv3r5xcP7miXNyQv0tacI+DDsl2Y4RxTtPxqrxGpUsaVX0e2Md5LZ238OSnH3u3OXb5uy3ubhwZRpVKhOzWtkkr0nBfg57Y8TYKtLhFajRInvK8U2gdTKq49/lC1LLVZ9geyvDuCWzcMuK9MVa8degPvXzrj3bXt/21qvp3/GuKX4eIdRpkhkDlpbhb/1GM8d06MPevpd72W4JwMn8PdtuCWzxh1KjV76pPSGrzvEuPfBvbQz0/jfES3c29BlNvvcfuXhaXY/jDs12Nt5P9I7K6Vj2PtaZJvLk1D0Zge9ScvJfE0sk8adCt2u7HUzNj2c4tcZ3ueItaPcxk/Ssdx2xtCYtuzNhREQO8uKtQ/tBdq04F2ct2/6Aahj+kMqrjNlwWjYVatrZUhWawlkU5AdsN1ZyZ+7Xw/o89xrvni04q61p2dOrTGsiQ055AkkmF5GtDbmpodLdRg9RK9B2rrmrevoa3GlatFCm0nADQG+/C847dZyrFkl7K9J78u5EKxCFkCEITS7CEIQ8hCPaEJtNBNJP2hSd1MI/ORCAFoTaUxhICEEKVqVY0qLyC0g4QFGocLeOXZvafC+EXPGuIeh21agysGFzG1X6Q+NwD1Wyr2R7TWri5lqSGn41Ku396h2Sfp7VcNjnXA96+pms+iw0w1jg7mdwnf2crJbuvltLjPbLgmpov+J24BzL3af3Lp2fwl8ZDv5UseG8VbgHv7cB0eDmwZXv2N7wFr2tcP0SJC5XEezXBrxri+yYx5/Op+qVvHl5Mfu5Vi4b7s1l267E3rWC+4RxXg9XEvtLgVaY/uvEwvQ8Is+E8daB2f7W8JuqpiLa+PotYzgAT6rj5FfPuLdhyzU6xrveIkNcBPkvKXfC+IWL5r21VgBgO0mPeuv+oz/5SVzuMfaONcC45wch3FOE3VvTjFUN10yOupshc+m9jviPa8RyMwvHdkPhQ7Zdlu7o2PFale0YZ9FuvxtI4iIOw8l9I4J8IfwddrnModq+C/5t8Qfj8IWBIpE9XN5fSumPLx5++qlw953eP+EBnednaRzqpXE+xzYP2BfO6JLarXDcEL7t8JXYm6t+xnEeJ8H4ha8d4VTY2qLmi4B7GhwyRsfML4Q0y0LjzS4Z9zG7j7d2VvXV+C2riZIYAcLfda3Njc7Yj3ryvwb3Qdww0nf0b4meRyvX1S0sDW77eSzZq7dN7jhXLnAkukxyWBzgTnK9DdUKbqbtQGAdguJVpN1ECRGYXo47uPNySxjr6XGFK2bTByArDQBMiUNpCF3jhe7Q7udI0geCoqUKTwYnKsaxoIBIzzV4oN04JlaRzjbAjAglQFFzT8VdXuNLQZ649n/RZqrCDmPEc1dxHR7O1KTKze8MdM4lfSeEXNjUptYSJAySF8iZVcw+q5bbfiVamZ1EnlnHiueWO28ctPsP4NsKrgRpMiJlaLfhVmwA6WDltlfLrLtNcUWxrIAHIrtW3ayoGjW/M7yVxyxydJlNvoLrG0IADQOQxmFTUsrYNlrRjnyXkKXaphzrjJ338pSd2ijLHknc+P71z6K31R7CnTotwHN8FpbaUKrd2xPhMr57U7RVGknvJzvt7FZa9qqjH/HIG2M7rGXDXXDn6Xr73hFMz3ZDiRPT2Lg3FhcW9fXTacGAVt4T2hF1UZScWy4wZmV7fh3D7e7oh9QNJInK83JrDtk93Dc+bvj7PLcB7Q1LIsZdUCWg5Ibj3r1lz2i4JdcPcXPYSR8UkTPsWTi/A7ZrSWtEeH3rzF7wamSSDEYkc14svRcfNeqXT6eH2rzennTnNvCdsRbVL17rbDZOAIH8bLywq1GP9VxC+g8T7P1ZLmiQQdhP8f4Ly3EODVqGqWe/BX1+CdM0/P8AqeT4mdz8bY7TidWlg1D0AnkupR4s14DXPG0Ek5Xn61u+nqlpwfcqxrDvLaF6OmV5d6ekqGnXz6pM581jrWQ5HcrnUbipTOD45W+3veTskDqpZZ4WarLVp1KbjifoRTquBMk7rVVqsfuNgVlLHE+qNzspvflrWmqjcOmCTsupaMfUAGp2R7dlxGMeHZELs8LuDTI1byuOUjrjbGwUa7QS0iOQlStruvb1tUkZkTzXUtKlKoGiAJ2EKVzYU6rQGNEnYDZcMpL2erDOzvK9HwbtTbttAHB0jELmcU49QrVzpc0DeZXlL60rUJc0ug5B8Fx69aq13rFzc815+P0mMy6nu5vtXLPj6LHumcVpOB0vEnqpu4hTGdcdPDwXiLK6L2w5+28GfNSv7ypSwx0csr0zjm3ivPlrb3LOJNAH4zl1VwvQ6JqAYzJXzL8KVwfjyfISr6PGazAAMEnxWr6diesyj6LLCZDjzg/er6PdgZgbkLw1tx14IaXGTsulR42IkkgTJM8lyz9Pt6OL19xenrtovp8gd8/cvN8SpsY/1QJ6dFF/HGAwXEbyB9vms9a/o1gZeDjOd1nH09xrryfaMzx0y9+abtiNl3+z/al1lXYahLmB0mQvNXBa+SCTPJZ6jS13qgBa5PTY8k1k48P2hycWW8a/RHZjthwe/otY+4ptqbaTuV6fRw27aWg0Hg7iQV+UaV3UpCWvd74XU4Z2p4rYOBo3lURsNRhfE5vsW73x5Pt8X21x5f7k19H6K4v2T4Pd2ji61pSRuBsvjPa3gVHh95UpNdjeDuFZa/Cfxj0fuqrm1eh5rnO4rW4xcS92rUdjzT03p/UcGW872d+T1Hp+fDpxu64NagwerjOw8FgrUWcsYX0L/NCrcWpqNqes7IC8lxrhFxYVnMqgwCRnn/EL6fD6nDK6l7vmep9Dycc6rj2c2x4bSuKucCeX2Lq3HZqh3BeGmYkQPoXHbc1bapLTB8Fs/wA46opFr45CZXXP4tu8a8/Dl6XHGzkndxL/AId3LyJwM4+xYKlq4dDGMcl0ry/FaoS9xk7TsAsvfgyABK9fHlnru+Xyzj3elgqUXNBcfYqojbZbK1UH1TExzWcx5SvRjbfLzZSKonkVEjlmT1Wi3pd5UAJwtVSzYGE8x1S5yLjhbNxzgMnkkcDCse3SSEAArW2EADz26IgFv2K+mwH27q9tu0iQ6eccljLORqYWsQpmCfbCiWz5ciuhU0tERkLI8t1eW6Y57MsNKNBjG0KBJBjxytbg3TIG+3gs1WJx9C1MtpYg4+fsScD/AIpkwDvuoydlsM74PhnmkCQMQEA7TjpCJGw5KVATzSJxMkc0b5KmxusgDaYTtBWRnCCt3owDDIghY6oh0BYmcrVwsUjKZ2nok5IAlXbAIhBEJuUXFAlE4UpUStKRSKZSRCIQmjdF0SEiYSiEQ5SJgShRJlQLljdIpyRsoGZQOT9CJUZ3QDmEvYJxSlMkykptSDpTScJykEtDJ5BEqJmcInwWtghN2Qq9SJKbNpOUlAnASlNiZ8AhKUboE7dIhS5JEpURKjCcpFZEYRCZlJTbQ3SKcpck2ESkcqRxsgIElCkVE7ohIITjGEgUNIRgqs7K4jCrdupsRCSlAIShJQkoTT28U6hGEFNyUg7FOpSKSHGEimwyg55qIEptwmxEiFEtU9QCTjhRFZCg5pKt5JOClh4UlnQqJBV8DolAUuLUyZyMbKBad1pc1QcsXFZkzFpTgjkrS1Rc1YuLptShTIhDgs6XaCE4SUUBCDlAUNhCEKKRSTKSlWBCELKhCEIApJlJAIQnCbCQhCAQEBBUo96SQ6IycpsdJ5+1ViNzt5py45GJ5A7eC+s8SyROo5HVMEj35EfQoMEZI5RG6DAdGJ2KGlkjSI2+9BMmYzskDGJjoJ+hOQTtt13CBySCZnp4lSEkQDMhREDBMAfxspNcOcbIgBIE5ABnmmCZkeeFGN/uVjXANmRjeeSoeqGgg+aYJJgSZ6BROHGd/EQUDfPPeFBPUJmcxjxTJ3MYneFA/ojaFL1g6BgTlU2lJ6438YTZE7yd+uVFpJPkd4TnnnGyixIYgSOQ35lMCMwMbdEjBMbDnjZEknMzzEoWrDIEADaJ6qQcWgwSJCVKJ9YeQ3hSeNRho5etASrPBScknfx5phxgwd1AZOrYxkO81MsLWkjHToVO3uk2etx3dImd+S0WtWKoJlw1ALFsXetEHHXZSDy06m4g4I5E/wAFLjNLMn1Xsjxjh1CxLKnd6v0pBC8l234hb3vENdCIiMbLzgrVNOkPcMciq6jyTOT1Xk4fRzDkvJt9L1H2nlzcE4bO0MnPnke9InO/NRmCTjPJQLszzXtfMiYcZgypscQQqSR1Umkk/T5LNaj1XZu/qWgDqefA9Ff2i4pVu3AVcaeROy5XAqzZDHkDO67fEuGuurU1qYBhuY5r5HJMMObqyfa47nn6fWNeVc9zahLDmZlFW5qPaGuMeS3U7LQ496Mj3JVbejqOB7F65yYbeL4ecjmsrFszvuCrKVyaZJEZ57rdUsWPbDMHkZ2WK5s6tEaiPcd11xzwy7OeWHJj39iqXDqhyRErt8Mu30KI0uJHivNNJDvVJnwXRt7oimGkEYWeXi6prTXDzdF3a33l1VuHF53iPYudSdruPWMeB5eaZui0S5uSsxqnvC72phx9M1Dk5eq726V1TaKMtyR4qu0rOp5GOipt6xdDXknz5rWGGAGjJ6BZy7dq1jN/NGhtZ1wRLpO0JvZogCN90WtlefHZbV9JO+gwtrOHXjjLmBoP6Tgszjyv3Y69Us+ZRQbqMgCfJbX2mqmCHBo6yrmcOr0mlwq0RjeT+5KlZ8Yq0XNaLPTvrJcQPsUvpeXK+HSc/FhPLLVa3SWteXEBZAC1xkx4K6s2pTr91c8e4Qx5MBlAGo/ygTnwWqx4HdXrpoV+L3TSY/F2LaQ974P0Lrh6TPHzXHP1PXfljnPa4+tBPsXju3NYPv2UST6jc+a+mu4PZWFw2nxW/trN7jLadxfa6zvJjMBfJu1t2294vUrt+LJ0+X8QuPPx9GPkuWVl3NOJcv2aTI8l6fhPZ/j3aGnRqXVzVNGmwU6ZqSdLRs1o6Lz1k1huzUqNDm0m69J/OPIL0F5207S1KIoM4i62pBoaKdBjWAAcsCVx4sdzuxMteXrOEfB9aW0VK9vXuqg/TGlo9i7Bsri0oupWotbVnTvWM+9fHrm/va8ekX11WP8AXrOP3rFUdTO7WE9Tldvknstz34j7Fc0KDC03PHODUMgkVLxs/QqKlXgLCQ/thwJs8hVc6PcF8ddoJgAeUJtpPJgMPuVvNJ7M932A3XZYgT2w4Y4jfQX/ALlh4pe8DFBrOH9oaF3XfWYynSpMdLiXAcwvmHotcQe6dBxMLXwqo6x4nRualN0UnanCMx1UvLueGpuNXH2Pbf3he0hxrvJnzK45wV3+O3DagIMPgYcd1wHcysbbshIQlKm2TQooTZoykEIU2ughCRcgYUlFMKiQQkgK7DUpPMqKYyiymCRsk8kiJQSouJKngt7NnZ21uLntDw6lbs72s66phlMODS92oQ0E4k7L7JfcD7SWz6np3Zbj1q0O/O4fUcB7WghfFbIhtwwuEiYK2WHG+0HCqjm8O47xSzjH5PeVGfYQs3LOXeK8eXHrWcv8n0q4r29r6tzWrWjulek+nHzgFdbdzcsm3vaFX9SoHfYV5Hhnwq/CVw4Rb9teLVGxGm6qC4HuqBy6I+GDtVWIdxfhfZPjTh+df8CoOcf7zWgqz1Gc84ytXHgy8ZWO/WsLsTIE+RCzVbKuW6XMa8cwTP2rJZ/Cf2f7zvL74MeEMLv5x/C+I3NmT4gNeWj3Lp0O3vwbXrS24te3PB8+q6nd0b5rR0io1rj710nrJPODF9Njfu8k/nuPN8V7KWd7qc61NGpvqpiPfyXjOO9luIcNJq0gbiiN3NGR5hfZrO47B3tRv4N+FWhbvdtQ47wSrRg+NSkS0efgunQ7HdqL9hfwR3ZPtOyd+D8cpl5H6lSCtfG4OTz2YvpObHxq/SvgnC+1PFuHcC4hwalc1RaX1Pu6jNZAGQSY8YhcekfUX1v4QOwPEbajUr8a7Icb4BctBPpD7JxoOgfnOaI9q+SNaWVHMJBgxgyFjky8d9sXDLH7009x8G9zD61Iky4CAPBe5oVKgqAOJAXzb4PalRnFtNMBznDDevP96+id+ZmpTLPAherj+bFyyurt0rgsdSjvGxvuudUpMLwA73JVKjHU4Zv1lVtA/OJHkt443FnPKZUqlsWt1TiMYWctdGJ8FsOnTAqHZVEwIkELrLXLKRmBM5O2J6KbKrgIkRAB8EnNO4+1IMn87lnK6OelvfkiDlTp0KtcxTpucegEqpjGjmF634PalsL17KwbtILj4rlz8nwsLlI9HpuGc3JMLdbePu7arSJbUpub5hZ3TJjbkvpfwi21qaLK1IMkOORz8V88fTGojCxwc/xcN6b9X6X/AE/LcJdspc7qpCs8TDj71qo0GvcBq966dLg9KqMkglbzzk8uOHHcvDii4cNLteY9yuZdvJHr4hX33Du5l1OXZySo8Os6dcnW+Og5lT4k1s6MpdKnXbnD43goNuHAkl+eUHZa7/h7aVQaHY584WN1s8DG/NWZS+C43G6ro8H4o62umuLjpHivrHZ/tU00GDvfd/H8SviJpvYOnXqFotr+4txAeY8V5PU+n+L3e70XrP8AT3vOz7nxTtRSFAl1UGM4OZXAb2so1HEF7MkZOYXyy64rd12Q6q4hZG3dZhgOMdJU4PTXDHuvq/WTmy3I+20eLW1wydTdXITn2hO4pWlww6oPivj1rxevSMB2Ngu7w3tNUZhzzG4ld/h2eHj+Jvy9Vf8AZ+jVJcxoM8vBcmt2ZAcTDII8f49q6XDu0NF5Ae4AxB+9dZt5aVWamOaSRMTMf4Juw1K8bW7MuaAWYMc1yLrhtagTgkAxsvoF5UlpIh3uPLZcK8d3h9dsHrGYVxyqWR5L12bggg8wtFtUaHS8+a61e1oPEjTJxj6Mrl3FnoJIeCCeiZWVcdzu7fDG21YjVpO2P42W684dbhpfSPkZz9C8nSNWk6WP8wDz6LfT4hXjS55Xjz48t7lfS4vUcdw6cse70vZvhVa+r92x+kEFxXpeI8B4jw6lrLC9kiNIXjezfaCrwi5bVaCW8x1BXubn4QLG9s+7czS6IzuPBeDm5PUYZ/LNx9X0vF6Lk4tZXWTzF3UDhpfgzuVwOKW1JzXOaIHUldTjF/Qql7qZHrGcLy19dAvyZAxJ3X0OG3LvXxvVcePHlqXcZqjn0anqOgg7qircPefWcPEdEq9T1zPsWdxJ2kmPcvZjjHguSZPPb2rXYtZUdp5nxyueQeqbKhZBkYPvW9M7eqs+H03HABxyxK1nhnqhzSdsLzVtxepTjM5XUte0I0wSJG42KxcassTu+G1QyQSc4nZc2tQuKZJEx1K9FQ4vQqD1yM4H7lrb6LVh2lgEclJdLY8rbvuAYIOfFbGNq1BnVHh0XoPQrU5OnOdlpp21mwgxTHMCBlS5QmNeVqWlQ5DSPYs1SjVaQROcQvcmlbEbtiNlkubOhVGANX3LG43qx471tQjK6HC7upb1w4e9dGvwoDLW9dhuoW/DYqCBEbDn5rOeEyjrxcuWGW49hwztqLe1FOswyBEhed7SceZfVXOYC0fbzVV1YDujpJjbqvO31N9Oo5oMgEyvDxeh48c+rGPqc32tz5cfRaru62p5j6AufWe49PNXOeXOO/tQykDOYJHVfQxx0+RlncqyudLicA8lW50bHG601aWmd8fSslVpETyxK64xytRccH7N0sEdOvghwnlsoncdQZXRi1OnVLDPP7Ve+8c5kHpusjsgzKgdyfuWbhK1MrJ2TLievt5qJd0OeiRMglRLomT5xurpnaxtQjY9Vc24MfGJwshOPpSJzGQpcZWplYvfW1SCfuVT3nzIUSTBzsMJAgk7KySM22pmociSYMKDnIdkkA7KOwOQqeTkZ/ekRPsEpGcDbCj0jzyglPIckA538VEHyIREwSfJE0JETvJhSa/TmZIUBiZJSmZIPgFL3VtbdHRpystQy4lQBxv70gVmYyVrqtMGU2zuUm5VtKmXHSJUyy6SY7qGnGVF2Nxsukzht24S2k5w6hZrq1q03Fr6bgRus48svZcuPKeYwu3SU3CHRBUYXVjwSCMJjBlSiU2Kyowri3xUHxyU2IITIS9itpUThQmSSpOBSIgSoiLo5mFB3KDOFKVEjoiwijPRDkZ6qBHdImE0iilMpOTUFZECTt0+SWlW1CRPRCg4rOxLUeqNR6qA3Qd1drpZqKsZzVEqcluxUNLcRhVuVeogp94eZTYkUkSTsEE+YVqEVEhT80lja6IJKZBiVEqyqihMoTYUpJlLonkQBhIqZEqKgikU0KCJMIhOEuSiImeuEDdTO2yiRhNkKcJISKi6RI2UwkCkhoP2UQgGFI7KiD1BWlQdyUIihCCi6IpBSOyii6JyiR4qQSMlNpIg5p5JOb0VqUKVd6UwlpyVYW9FHSTyUsa2q0kJFvVWwokSVmxdqyI2UIPRXQokQs6a2hKQCnp8UniGrOl2h5pJgIjosWLKSE0lloIQgoApIQgE0gE1EpJwkmlKIQhCI90TA+MI5JSImTj96UzneUxiRkr6zybTaN5MlM5BAAg4En6VEHx8PJSkbCDhBKTgxk5TjOk4z5qM+tpAweqAckZnxCJ5SMnGYPjuk4xzhNpOBnPX7EbwckeKsEh1KPoUmEAHmI2Q71W6ZnmU2ABwIgauQCQOCQ7wBhDjO+ybAC/J3QTaQI5T1QHAiTO38SoAZ3HmFJo8ZREwQJkn2IB8xKiZEahPimBjG/UIqxvLblKWQeomJTbJhuegjnlXG2rimHljtIEzBU3IslvhUDDoI/gqYIDhJ8c5UDgAwUg6TAPsP3qxGqz0is3WTg8yundmgLZwIaXRtOd1xNXrEAnwUu8PM+eVzyw3duuHJ0zWiefWOE2kDMeE9EpIOlwzPNE5gRvtC6OSQcDIyClkTnyhRBgRO45lSJExzyPah5RdJ32wSoTBUiVUTn42QlXSSuoMLzHNUAzzjMYVtJ4Ds+0BYy8N4zu6lrSLIc2Z8CvR2HG/RrU06u2I3HkvOW10wMhxAUL+6ZoLWHMbr5/LxfFurH0uLm+DjvGtfEOKNfVc9uS7ccpXLN1UdU1Fxg/QsznlxOfHZA3GZnZerDhxxjxZ8+ed3XUs+IuYYdkb7rXc3TbinHXZZLLgXFbkAstXU2nOur6rY65V9zV7OcHYW3fFHcQuQYNGzEtB6FxwplhjLuR0x5crjq1XaspNfDqReeS3/gyvcNNS2tnBnNxwB7TgLgV+19wGuZwrh9tZM21vHev887FcW+u+IX3r3t5c1ugqVDpHkNgnVXPePh6q9p8NtwRd8bsabmmCyk51Z/uaCPpWIcU4Ay4bSbTv7kFwBeS2i0CcmPWMe5eVfc0aQDWnURuGhFu29uqkWtq4+J2V66j6zbWnC2OD7e0oOO4LnF/0Ewtjbh9Mnu9FIdKbQ37F4jhdnX4cwXfFOIMotAwajtPu6+xV3/bnh9Bpp2VGtfVJ+M892z95+he3Dk48ZvKM7y9q98Lolw1uc5x6mSsl/wAZoWLSbmrb2/jVeAfYF87teKdse094LDhVKu6pUwKFjTMx1LskDzML2Fj8HXZvsqxvFPhK4v31y4a2cLtauqo79d4z7ves5+rl+69HF6bPPuVjxy747xAWXAad5xCsOVnal0eJc7DfMhdviXAaPDqLLntnxmhZMie4q3JuKx8O7ZDQfb7F5vtD8J9+6yPCOyVjQ7O8JGBStmgPeOrnDn/ErwL/AEviF1nvrq4qHbL3u+8rx5+p79npnHx4dvvX/r/L6hc/Cb2d4DbPs+ynAm3LyINzd020wf7rAJ9sLwvHe3faji2oV+LVqVM/0Vue7aPDC19nfg97Tcbrd3a8Pqk8w1pe4eYGB7SF6O5+DngPZwau2fa3hXCnjJtmv9Juf9lT29pXmy58r7vTjweoznadM/o+VU+9fcioXPc9zsuJyfatV3VFS4qECGgwPYvW9pb3sKeH9x2Wo8YuauqHXd7opMI/qUm59rivG1fVa7MwuOee3k5sOi63L9He7Ldle0PH7aqeDcHu70OeAX02eq0Dq7Ye9egf8GHHLdk8W4nwHhPVt5xWk1w9jSSvCXV5xL0alZi/vGUGsE0RWIZnOwxtCwihTmXFpPjlc+rP2rpj8LHGbx3fq+insf2MtIdxL4TuAtcN2W1nXuT7wAFVWo/BRaj1+03aS/j/AMJwmlSB8tbpXgQaTJyPYq31GHZJM/enxsZ4xj2buL/BtbPcKHCu1nEAdhWvaFuPq03H6U3drOyNNoFj8HlNzv0rzi1ap9DdK8PLZlIPVuG/LM9Tlj4k/pHrK/aG2uTNPspwG1HRnfPP1nlYuI3TLio17bC0tWxBbQaRq8TJK49GoAN1qFTVSgrWGExZy58s/NFR80RT1es0QJ5jksTsFX1VSQujG0FOm0OnOVEiFEEjYwou0nAtMFRlNznOMkqKLuHKaiiU0bByiYQmCh2SgFhMpIBQhUw0nYFI43Wm1uRRaQWgys9dwdULhAla9l1EZSlKUSps0aEBGOaMZVdaSazM8wvU23AuyV1aUqlbt/Q4ff1BNa1ueFVyyk6du8ZqDh4wFw+D2ja1Q1XXDGsojW9sZifpXPvK1Opd1qlKdDnktkZhcst5XUulxswm7N/v8ntP8w6VZoPDu3nYu9LjDWHiJt3H2VWtj3qVT4Le2+DZ8Ko8SaRIPD76jcyPJjifoXhNTeYUqTxSeH0nGm8bOYdJ94WdZz3/AOmvicV84/0v+du3xXst2m4UXDiXZ7i9oG7mrZ1GtHtiFyBvAInou1wjtn2v4QI4X2p41aN/Rp3r9PuJhdsfCp2quNLeMU+CceYB8XifCaFUnzeGh/0pvOeZF1w33s/lt4sjqFHQwODg2HDYjBC9y3td2Lvv+2vg0sqT3H1q3B+I1rYjyY8van6F8FfEz+Sdoe0PZ+oTAZxGxbdUx5vokGP7qdc94fDn/HKf2cvgHwhdvOAAjg/bDjVqw70/SnPpkdNLpH0Lh9r+NXXaDjTuLXtvZUbqswCsbWg2iyo4Y1lrcBx5xGV7RnwYcQ4lB7LdouzfaOTDaVrxBtKuf/araHe4FeT7a9ku0vZWuyn2j4Hf8Lc46WekUS1r/wBV2zvYStY3H2Tkx5Jj38MnZTiNPhfHLW+rtquo0agdVbScGvLdjBOAYJ3X2C0412O4rnhvalttUd/3bjVsaJHlWp6mH2hq+Ft3OYkLQ1pLAZ5Lv8TKSdNcZMb5j77c9leI1bJ17Q4WLy1ifSeHVWXTR5mmSR7QvOvt/Wd3VwS5mC2oMjzGCF8z4NxXi3Bbtt3wniF1Y3DcipQqlh+hexs/hY7SPc0cet+G9oabRp/L7VpqR1FVsPnxldcPVZT702xlw45eOzuBzxT0PokmMFplVw2CHOII5HC6PCuOfB72jOmjf3fY2/cMMu9V3ZOP63x2eZlbeLdnu0XCuGHidbhtDi3CRj8IcIuG3VLzc0es32henDn48u3iueXDlHnCY8RyhV1a9Kg0Oq1Gs5NnCLy/s61o93DHUqtxyYXhpHsMLxPFDxI3BfeCqHn9IQPZ4LfJy9HibcsePb2Tb+0OfSaflK63Ab1gvaZpVQdRAwd18pL3xmcqVG5rUiO7qPYeoK8uXqLlNZR1x4+m7j772jrh3Dw24cdWIHReNrNj1g6QeUrxNr2g4jRgOrmq0fmvK7Nj2itK403DXUHnmct+j9y1xcmE/JeXqz712g9wcCDstNDiNWngE+OFipOZWpGrSqMqU/0mODgPdsjAXp+XOOEuWLbc3z64yYCooXD6LtTJBKpn/FMZSYyReq27aK1zUq5cdj5IbVhwGMrOTB3E8wQmMCcDM7bpJIlytWuLXcj96qfTBd8UEk+9NrpG/PkVYw+sT49EVQ+gDjxhZ6lu4YO3VdjQ1zYOSs9Sm4k4PgszP8Wrj2cp1MtyEgXtcYXRfTBJGFU6kCw4OPCFrbOldK8q0yYcfE7Lo2XHa1J0FxO65b6QJn6FF1Hm08k1tJt7bh/aBlUBr3chkkLssFrcgu1gk9Dz6r5gC9rZGpb7LidxQcJcRjPJYuP4NzL8XtL2yq05NKHDwXKqtrNcGuafHC1cK7Q03Q2tmehXeo+h30OkEkYErlllZ5dcZMkOzPY274xbOuGjSwb+wLk8f4JccKunUagMjIPUL7T2HurC04SKQcwAYK8H8JdejccRe6m4e/E9F8Xj9Zy5eouGXh+m5vs/0+PperGd3zus4gxgHqVlqVS3LSR4r1/DeG2tzTdr0HO3P38lzuOcFp2xLqTscgvo4c2Ny6XyM/RcuPH8SeHnql3U5P5c+azufnB8/BW3FMNe6BuqwJcJyJ5r1YySdnzst+Kg4YByRzVR8BB8fpXYDKRZsFzKzQHkCd9oW8M9pnh0xQ6AefgoEHnBjorHyYIzCiHDnvC6uSl4J29ih6zTqEzCvMYUHAbIh0bqqxxz47rq2HEakgSTIhcZzQTmdtlKhUNIA5SwesPEqzWTJzv0Wapxms12Hu22XGp30DLp5DyUe+Y5+6z0xd12vw1X21E+a0UONvBgvIEYhcy3o030+p8pRcWWJY7kmobr01txmnUbDnCQttG/pkgNd/0/evBgVqTzBlvRdbhr3l/rOIMYypcIsyr1hugWesQfZuuZdUKdUkjI80OBFIObUJHRc91zVpVIdKxjg1cvxV3HDKky3UPYsNW2r0t2kZnyXdo8TpFoa/eJM4nyWkPtKoAkTynn4LV7JHmC1ziQRkfwEehufMU46Fej9Et3CW5B2JQLemzbSeURj96dUNV5epw6oZIadPKOayVreoyQRkEjK9dUcxogxus9SnRqgyOUAFal2zp5F1MwQVWW4BJwfpXo7iwY6SAN8LDccPcBiTnoFo9nJMuwPb4pPEY078ytb7V7SQQVUaRyJPRGds+fDeAkN879VcaRmIdnxUC0j4w9qLtDnyUm0yd89ED43TxV1OoBgAglDampTc3xzCqIJMFbyWOgSJVTmcwNWUGUTHsUSNt1e+lzG2/koGk4cplVdquZlJwkHop927aD7lEtO4B8gVDas+7kjpyCmW7ndQcYciUkyI5pF0lWBuMqLpBrgHbrXZXDWVQTmPBZXsxhRALdws5YTKNY243b2Vrxek210h4HQBc+8vKdRztYmfBcJri2SCVIvdzJK809PMbuPTn6vLOaqu5b65LdlSQp1HEmSoEzjkvVHk81EkqQcOqg5CqLQ4FPDlVJTBjOyz0qmWEgQoFhAyr2EFJ8OEc1na6Zjukriwgqp45LaKiFABTIgSoBUBwI6qKaROE8qEKOyZKmkI7qLuRTBlBMASp4AQUEYhAMiVFzgoqJUDupqJCm0IJFNI7qxQDCJKSOaaAiEHZIlNiTTpCesEmFWMghGynuaW75SKqacZJRqUIuc4SouMlQJhDTG6RUpUXEjZPkhNpoEyoEkiSrVEtKbNIIcUR4IcE2aRSJUoUXKGgBKC2dimNgFEx0UQ3fFKikUFGpCJhIlG6SLrRpEwmq0DQTKQMJFNlIoKcKKbNBCcJKGqDsolNKVF0SRKaCmwplLPMpwiFNpokESnCCm10rcISAVhEqDmwrKukDgpFpVgDY3UThS6FcJESVYonCy1tXKW6sUDhZsVEhKE4whZsVFCELGlBSTKRUaMIQEKISYSTCtWhCEKMvcHG2yHTEjPULXXs3sp6pmBlZIg8zyX1Mc5l4eW42eUxpIzBBPMbpT63WYnCQOP3CYUw3EgETzWkNuZ3I8VIk7gnHVIAmcRB2hL1hkH3BEP43mOhUgADkkDyURgjr06lSBO3TYoptOInPOFKGkuVZ9oPmmTgkxMIiWYEiROPEJtJJknZRHrH1jJJyZTABcByJKok0gGTy2HVSaZaP4wowAP4wgTsDA81BYC2EAE7nEzgpARzxMJmJEorTZPaLmm58EBw3XrKl7aegkEh3q7DK8WNQOxMn3+C1WQFZ7Wvgjlj2rhy8fV3er0/qLxbxk8qnw4kSQQJKgMDeYXSv7ekykajYDicgdVy3mMxAXXDLqjzZ49NTJGYEbQpgCCJ28ZVMSRk7DdTwHDqt6ZM4w0z0UTvuY8U3TG4BPjhJroIjBGZCBl3Pdsyk45xMpYBMbR0Sz1gbQqAnG3vVZxgK0ZMEqBAE5UqoHA2GdlIOP8bJ06bqrwxjHOcdg0Lr2nBHxquagpDkwZP+Cz5uo1pzWEzAlb6PC7ysATSNNv6VTAXXtqdC0YG29BrXDeofWcfadvYpPqFziXEmfFbx4bvudU0y2/CrOm2azzWPMAw1dmxfa2ullChRok4L2ME+07lc0kZxlJjoIJMRldvhyMbrzPa/tVeX11Xs6NV1K1Y8shp9Z8dT08F5+joczVUcGDqu1edm6tXiFeu68t2UHvLxElwBPRX2vC+GUD61F1y5uzqhxPlsvFjxcuV+Z1mWOnLpMfXltnQfVjm0Ewrm9n+J14fXqMosP5r359wXrLFla5Hd27BRot+MdmhcDjPaalaOfb8FivUEtddOEtB/q9fNby4sMJvOrLb4THBuD8HpNueMXOTkU4yfJu5XOvu19SO64NaMtKYECo8Bz/YNguIGXnEbovqPqXFZ27nZXZtez720+8rAtxOVwud/4TTrjxW+XErG5u6prXVapXqO3c9xJ+lfRfgq+CriHa134Qvaw4bwOkZrXbhl0fmsHM/Qux8FHwdN7QcZcy7Gm3oNFWs5wxTbyEc3Fej+Gbtj3GnsT2ci1sLZgp1zTMf3P3rOcuM3k9/B6aWdeXhl7Rdu+C9j7Kr2Y+DmypUWj1bjiDwHPqOG5n84/QOS+Y29jxntHxOo6ky4v7p3r1qj3YYP0nvOGt8SQF6Xsv2Pdfm3q3bK4o1393bW9uzVcXj/ANGmNgOrz6rRkr63xOl2V+DbglueO21tecRee8suB2biaQcNnvJzVIO9WoCP0GjZeXLO2bvh9Pj9Jly98+2P4PB9kPgeqXlseI8UuKfobBrfcPqdxaNbzOs+tVHi0Nb/AFitHEe1vwd9lGGy7M8KPaq9Zh1QD0ewaR5etVHmSD1Xj/hE7cce7X3Ln8dvptQ6afD6Di2hT6SPziOpn2LxlzeeppEBvIAQF57y7+61nzcXB24pJ+fu9Z2o+EXtpx2mbW44z+DLACBYcKb6PSA6EtyfaV4ru6FMksptkmS52Sqn3DjMErO6q5xySkxtfM5ue53eV22OgtcVneSXNZ1IUydNISfjZWfXpq699MmF008mV2rua+qq8gwJwqXPMTKiUHC3JHO2kXE81EulBShVnYkqQcohOEF9M4ldF7BSt6Bdu9pMdFy2CMLovqd5T0uOQBCNYq6kRIKqKkolZ21KRUY6KRShXbRQkpJFVSSKlCSIihOEQgjKNXgmiEUtScykmndrYQhCmi05SKYRCrlldtNnX7oPkQO7ePOQVzztK1P/AJolZiVNd2Mr2LUU5SKFrTMPUUw4jmophNRUzUIR3h6KBSKnTF2m587tz5LpP4pf3/A63DLziPEbm3t297aW767n0qTwQHENJx6pdt4LkuKu4c5wuDTEDvWOpnyIhTp92plfDMxwX0Psbw74N+NcApWnFO1V/wBnO0AeWl91Z9/Y1QT6p1M9dnjIIXzpojCsYPxnimWPVjqNYZar6fx74Iu2XDrM8RsLG37QcMDdQvuD3AuqRHX1fWb5EBeAqtDaxpvpvovBgsqNgg+1a+zPaDjnZ2+F5wLi97w2vzdb1S2fMbH2r6fZ/C5Ycepts/hG7J8M43SIh17aURb3IP6Rj1XHy0nxXLeePnu9OOHFydp2v/T5G6nGYIXT7N9ouN9nbv0ng3Ebizqfnd28hrx0cNiPNfRrj4POAcfpOu/gy7SUuJOjW7gvEPxVyPBs4f7PevB3/Aq9C9PD7q2rcK4kMG1vAWB5/quP2H3rpjlKznwZ8fd6g9p+znawBnaXhreH8QOBxCyaG6v1mbFZeO9nON8Gtm3lldDiPCniWXFEamx0c0zp+xePNGvY3rqF3RfRqsMOZUbBC952D7SVuA3TW1AbnhdeBcUDkQdyPFeriz32ycscJldV5N1a2qN/KrIHq+idJ92yh6BZ3H+iXrQ4/wBHV9R37ivq/wAIPYGzpcPb2i4MDW4VXYKp7syaTT+cOo8OS+ev7PXj267Sky+okSO7EuA8t12y4+3fuufp88Lp5y7s7i2dpqMc3pI3VLKjmmDgrtCpUt2mgaksG9Gs2QPfkKl1tb15DW9y88iZafI/vXDLjns4b15YGXLmP7ym51N/6TMFdjhfHqtKGXLDWZ+k2A73bH6Fyq9k5jtJBBCqa0sw4R4rGssL2SyXy+g2FxQvmF9nVbVIHr04iozxLd48dlIh0yCvnwqFr21WPcyowy17TDmnqDyXpOG9pqlSn3XFmtqOEBt20Q/++Bh3nE9ZXo4+ffbJyy4/wd0EKUjkstG+tnPNN1QU3jcOx7jsVpI/Rz4r0SyuekgARPOYUxjH8FVNmIK0U26gDJlLdRZ3bbCkHvALjpMT0XoLfgtO4t9bYBjBxuuHaamEQIG4wvS8Jv8ARTDHnEbleDnys7x9L0mGFus3mr7htSi5w0kg8lzn03CSfsXuLt1G4duJXNveFsqAvpxnJV4+f8U5fSau8HlnUwCSZGwEFQNLJOx8Quhc2tSkS0ggT0VNMGdl6PibeO4auqwubJggqJpAxB2967dDh5rs1gbhZLu07p0EQpOWXs1lwZSbsc0aqZwTuujYcTrW+mKjpHisz6RMgbj3qDqTjOqBqzC1e7nOz2XD+09UN9WqQdugWHivE6lw8k1ARyELztNz6bpG30KZql06jIIXKcOO9u/+oz6dWurb8XrW+WVCIyeine8cq3bSKpmceS48aucYVjqRdJEbq/Bx3vSX1HJ09O+x1quol2J3VL3+sdJ22OyZa5m/I7qJIMrrI4W7TFR+xduomCT+7qpU2tMScRJhajRZ3eogN5rNslakuUYHs3zlRLd4J9i6FpSbUuWscIaNhC9PccIsRYlwaJA5mJ/xWM/UdGtvRw+iy5pbL4eFc07c1EjcALbdUmtqPa04mAStfBrWjXrEVBI8cLreSTHbz48Vzy6Y4jmmD7gd1Fzc84XsuJ8Ft225qUg3UBiNpXl7iiGuLAZgqcfNjnG+f02fDdZMRZ18ksgwDjnC0OZnbCgG5IA32XXbza2sp3NSmfjRnZbqPEHEev5ZXMcCMETKGvgiNink8Oz3jarSRGcJG6FuZEkLPa12tZBSv3F4kkkncnPLCK69nxlhIDitZq0bhhIcD0C8TUc9riGuI6K+1v6tJx9YxHtTpSZPTVrMklzCW8hCxuFxR66QcKFtxfVh2PatTbptVgOnPNO69menxO4YYc9wC6NvxIVWaQSY5krmXVJrpdAGemPoWKTRqh8mBmCmom9PWlgqiQc9VluKJY5xDjjaPpXLs+KaTBJ35810RfMqgaiZ5ZiFNLvaDKrwS13I5hXAtI9ZomOexUHta4zOfBZrhj2S4HxV8jU+nReCCBIMBUusqb2+rpzn3LA6tVaYnY5V1tXeTB0kTsU0m9rhw4O2aIP0KFxwo6ZG5XStiS2XT4Zgla2kSRqH63gpurqPH3PDqtNx9UrHWtqrTt7V7erSpmRAIMmVkrWVJ49VsezdOpOl412tvXomHuB3OSvR3XCmwYkeycfeudW4c5r4042A6rW5U7xia+dyFaNLjgc9vBWNtC1sEROdlLuSBshuup2V4RwPid++lx3tCzgNq2m5/pLrKrcguBADA2nkEyTJxjmuNe29JldwpVNbZMO0wHDrH3KyoHtA3xkeay1qjtXrT4T1U1divuNU9eaqqUHA5WqnXEw72LS3u6jJVVxXUyDkEeaXrBdmtatcJEdVjq27myQFNqy6ZO6cSpubpMEKJTYYGE2tnChnqpMcAcrNEH0oKqewjK1ucwqDhyU2tjE8OAwFDI3Wuo0KPdLUsTTPq8FIKT6cclFNw8HJBhMPwoEJKeUaaZBG6rqQZyoB2MJOJhZlqovAgKojopl0hRkLV8EIgxPRQKucYVTgZUiq3DxTCZSV2iMxsk5xJJTOUnclLQvW6lIhGYQsqSRUioc8lAueyZEoJlRdIGEClEoThNhH4xSPJHPzTzzKlqyFJSJJGVJQRaEgiUjvhES5EqJKJlRU21pIGDKA7xUUJtNaWB/gpB87qmYTDkFxIhROSoyiVBIBRIgwmHRsUjlCIz4JEE8kygptdIOwkMqThhVkkbJtDBHJKfBImUnEjmhIbnHwUCZQhGtBCEgoaAQQnjkIQgQ2RCCUSm9CPNKAnKJ6rNq6IpJlJNmoEpQU1NpdQpSJ2QfilRaimTsoEypqs4TZRKNyAnq8EiVNoHADZQUySRlQQmxslCZCEaIjCgGqwiUlFiuElaqzHLCyqJSUknLFihJCYU0FCEIUUIQhEfQ33pfT0YyN0qNJtQetAxmTzWOZxt5+CtZWe0Y9q+l0anZ5+rd7tFRjWOETBM7qNNzZaZnOFU6oaj8uI6SmA/lOPDC1PHdm9601NGktwXAwc7KguxLttttlA4lo9gUmxGSOpWkIRnkVLB8Z38FHp9iYB6Y96CTYjwCY6KBLcwRkwrIOcQcIhCSYG4QJmeWPJKeZwZzKbYnmeiokwk7KUGI5wonJ+iCmAczOev8AG6gbcj1SNpMFWDyMjpySaBEmTO+FOd+fjKKidvWbKbXlrwWHYnICi46vBAxzzCDQ6tUcIc8nwVBOSIOEBxBnqmevJJNLbvyBj/qpbS6RKjIGUz12VQAxO0+QSmAchGD4ygAZnOECcZG6TTzUnNmAdyrLW1rXFQMpMLnROdo6z0TZpVHqzyW+w4TWuGirVJo0jsT8Y+QW2zsaNqRLRWrb6iPVb5D710A5x9ZxknqVvHiuXnsu5ErShRtmkW7G0xsSTLj7UPgzG32JagAJyeqUiYJwd13xxmPaM27QIkJR47JmQZGAomcnOeS1pA/yVZMAnZWHqcAKtxbvBU0MtWmYiN1dwfhormrdXddlrYWwL69d+GtAWm0tvS7mnRbA1bkmABzJXlO3vaOjfuHDrCpHCLN8sDcC5qj88/1env5rjzcnw8fzdOPDqqPbDtIy+YLayZUs+EtBFOjMVLn+s/oD0+1cnsxwq74/eGjbs7ujTE1HgQ1gXFtqV3xXilG2otdWuK9QMY0cyTAC+6cK4LT4TZUOzfDWirUDh6TVb/T1jiB/VBwPevBPny3k9/Fx9d1PDJ2a7M2VGnV7sspWtqzvbq8qDDGjn59BzWC8u7S/q+m2tI0bEEttWO+M4D+kd4n6Fv8Ahm4jR4LRt/g/4fUaazXCpxSq05qVv0P1WjHnK8pxGu9llTFLAYzSANgF6OCTO9TfPnOO9Efd/gsqeifBrf8AFLch1a47+s53OKYIaPeD718k7JcNpX9e749xcPfY0H66rQfWr1HH1aYPUn6F9X+BR1LiPwU0bWmdRfTuaDxz1Eux9IXN+CHgtO77Q9n+GVBqt7GlW4rcMIxUqh+imCPAgH2Lz+onVm+3x8cvFx3209TVqUvg47Hv7ScWo0a/anibO5t7fZtuCJbbMH5tNghzyMk4PJfnLtTxm84hxK54hfXb7i9uHTWrO3PQDo0bABfSP8oztDVv+3V1a6yaPC2CzoicB5AfVd5lxj+6vil5VL3ucV87kl5Mvyjp6rn+Fh0zzVNzXc44KyPeTMlTqOVLiV0nHI+Dnncu6LidyoMIfUDRzKeYyE7Rn43UeQKutONtX3lTIHQLLUdFNx5qdwZcq3iWgdSs6SqgJUjur6FGm4l1QuawDJaJJPRUkEbpvbNnYiE9BiYx5JhWsIALDvCqRW1ktBlBAb4q0MDR1RA6BYtbmCFKNQwrXGCiBExslUwZWsLtLNCZQojZPMYWcr3ICkglCm1BShNCu12UIT8inCdSoBEKR2ShOo2hCIUylCuxBBUi0pFvitSwIIQmEXYamMpAKbRlNudTqtHceZWMggwV0+4NWyqvaRNMao6jmsL2F2ySs2KUBT0O6JQebStdkRCeyePJIoAJKSHZCuhAoZLXBwwQZCYEkBMjBPIKChxOt07ypMPrjxUa3xpTp7jnCT8GmxgyFc1uxlVUzIlWN2C1MZXSNdtVdTqtqU6jqdRhlr2khzT1BC+ncD+EOjxmyp8A+Emxbx7hRGll5EXdseTm1Bkx4z7V8rlX29UtIBKznxx6OLmuFfUe1fZL8EcMtri7uXdoextw6LPi1ETcWBdsHjmOrTg8oK4972fuuA3v4OvdLwWB9Gs34lVhEtc09CF1vgc7ZDgXExwvirW3fAL/APFXltVy1odjUB4fxlfQ+1HZJlk6p2Wc99ahoN1wC4Jn1Dk0Z5jp4px277vVlw4549eBfAlxL0vhd72Xvg2pTpMNagHZlhw9vlmV8w7Z2Vx2T7X3ljbue2lTqCpRBMSw5BHltPgvffBLRfQ7ZUdQ0k29Vrh/dK818P51dvvVIMWVIHOxly+nwXtpy57cfTTP3l7M7hwvtTw0XHE2RW/m/TaTRqpnkKg5/rc14/tPwG/7Nua65HfWj807lglpHjCt7J8dbwLtBSrXDTUsqp7u6pfp0zv7RuPJfXuNcHo8JcbC4aOI8CvaQr27tw+k8SHs6HqOoXonFjybl8vXxcfF67g6tazj4Yyux7W62ipScMH9xULi0bo7yk7Wz7PNaO33AbjshxsUqTjV4ddN762f+bUYeY6OGx8QstrXe2h6TRdrou+O0/YehXi5OO4XT4fNxZceVxs7xiq28zGFQ1zqNYB435HmuxVYHM7xhljsysdWm1xhwlea4+8cpkLe8Y1ndVXDS0fizzH9Xy+xbbW/rUf5uoWjeOS54psaZDR7k5IC3jal09Pw7jNN1ZjbxpbTJAc9gkjxhfU+zHZzh/HLY1eBcTtr0tA10gdNQT1acgeK+DsqEc1ssr64tLhle2uKlGqwy19N5a5p6gjIWOWZ5z5ctO3p+Xj48vnw3H6Af2F4lSa4OoH1N8jCordmOIUmBzKct8F5Hst8MHaKzHo/FKv4RoFunW8AVW+Orn7fevoXAu1dlxa2NSzui4/nMcYe3zC+bnfVcf39WPu8E9Dz/c3K8pd2d3bvBc1zcc+app3lSm6Kgxseq99VuG1qRbUYXjniV5zjPC6T3OdTB9bI/jotcfNMu2UOX0lw+bCvOcQrMqzCz2dqKtQR7FZd2lSi8tcD7FdwyWPlem56x7PDjxdXJ80dOlTFrR2iFwuIObVrOj7F1OIVXaAAYGy5T8uJWeHv3dPU3c6Z4ZnUxuZkmZjKrDG5k9Ft0EkQB7VU+mYBA3XqmT5942d1KnyAnzys9Wm2ZAjqtbmmCNlS4GeoW8cnPLBmIgzBUmVjBBU3ty4nB6+KpdTkGCtzJzs000dDyA8gc1oNpTdjmuc0OaRkxKtt6lZoIEnHJW5JqtT7NzQSwkjnnEqh7agGTIBkFX061TTpIMFQdUMkuafMhZ3tdaZy57H6jjor38UuywMNRxbsptFN5A6nyV1Oxa8iImOimXT7t4dc7Y1yajnF2SZ69VKhXfRfrpmDsVuuOH6GnSOXVc6pSeJBEx4LUuOXZnLHLC7bKvFrp7Cxzsc91hqPcZcZk+KRaDnfzUqLC5wM56haxwxx8M5Z5Z/eqokk6zz2jmtnDjTghx58+amOGXRtH3ItqzremAKlVtJxpsnYOcBDZyBMLG5jmOMTPJay1lNRjG2XbXxBtLu5bAIPLP8AAXMc0STIHSVOpUOZOCqw4ZVwx1DPLqu1lFsuj+CtbKBqAiYnxWFjnTAHjC00bhzYha2wuPDSRDRPgs1fhtRonTzXQtr9jSA7AXQpXlCsIeRkfwE2uo8sbatTfpLTI6LocPeWkhxxlehNK0qA4AMczt4rLXtKbQ7SY+9Xaa0sY2k9udIJ5dVVV4fScSZj7fNYapdSeC1xiOiKd1VbBGwyFCC64bDdVOchYKhr0DGZ1e9ddl2TAfvHXKi9lKpJgDPNWGmK24i5kNO/uC69vdUqwAdtHRc2pYNJ1CDJUadB9MANAAmCeUqE27Xo1Ko2RGd/uUBQFMiN45BYaN69jYdI81ceIB0T5eSndezS6tpZ6v2Kl16Q6AcA9cLObmm90Hnus73sIknG5VN10BfuByYVjb4GZJHQHzXLdAOSZmBPLrKz1K0M+/xUp3d70xhHxhnBKk51N55EnkvKVLx7fzsclBnE3icnxU0benrU2HAAnPmsdQODojEeWFz6fFg4BpdOPctlK8pVvjED6YVNI1CNJELDc02kyYnp1XX7pjwNJ3WetavkkyI2V6oacOqwtft/0To3DmQDPuW6vavduJz7lkq2z4mPaqytbdnm5X0a9Nw9dYBQeN1IscIWdNStdcUniW7wsFVhBgJlzwdygOnfdNCk6gkHgK2qJyN+ipLT0REtRSe/GCoiVbSYHNWbFVNdJgyr6cbFU1KTwZCTnGI5qVZdJ3MclkJU3EndV6gk7F7nqUAk50qMrW00vbunVbDZVIc6JUnPlpBPksWd2pZpW/GFCVIknmoStTwykXE7pSlKJwpVM81ApkqJMhTwEd4UVIqKASQhREnGMqAzyTiQRKiRGFFImOSSZQDCEJCEI1rZFRdyUyqyZSBSiUkJtDlQUlFNgQhBWWwkUE+xAI6qpQl7EyVHWibTBRKhPiglRd7SJRMqGrqhKRKQnq8VWkpoWF3goOmMBMEBDiBupKE2eYhRcCVImdlEkAAFXYBsmkDKC4BUJ3JJKUlLVkOfBInohCy1oIOyjKRKJ2PZIpZKCIRNmVE/FKCgps1sElHNCCVF0DskhIIpP5I/NSIJRsAFE0WkpKUolF0RKRTJlIglC+SKSE0CUkKMqWrCUFMkQq1FJBCEKKihM7pLAE00iIVsCQmiFke2dgnUY684TGZJkGdionYE7KQjxX1I8pt35LQXtAIOZ8dllGM8lITG8meaWbWXRkwNXvTmDjokQT0g7pkkNMx4KspYJncjaU52nPNQaZEnlzUhnYk8jJlBJpxBM+zn1UpGWqI5nnOEwHOBxMJsIwJOSSpQc5JgxuiCIMHr/wBE5kDJ35KymjB9bfdTbn1g0RvIUGidsbbqxolzSceKGmq2otfvInp0VN03Q9zWukSrQ4NpwMFUVZJyRvnwXKbtdLqRAESZnKAM7nHggCecoJABJ2XVzMQT18gpAjVtjbZRAzkFMA7AoJDYk80QduSMQTHPKMxy2wigHOFNoBMDZKi19SqKdJrnuOAG5JXWsbIUfxlyAXB0d30Pip3t1F8KLfh7qrRUqepTJ3O5HgF0qYaxgp0m93TGzY38SnUeXvnA8lID1pXow45j58s27Nk8lIGZEbJTk+qnJA2811ZG4k4CcAGd5QTOeXRSOBj2LUETGrmZ5RhBEy2clBzHLxTDDnpvurpFQbggnHiqHxqjJWmoABgy4/QoNHqGSD5KaHL7WXb7Ls0adE6K1/VFDVORTAl3vwF894xSdRfTpnGpgcB0B2/evb9vmv8Awdw+sMsp3Dm45FzZH7JXmvhEtfQe0nct+I21ttJ5H8SzPvlfM9Rb117OKfJt6n4FeGNp/hHtC5svs2No27iNq1TE+YaCfcvt3wQ8MZU7RC/rAOpcPo1LpwPVjSR9IXy34In0ndgTSafXdxR5qj/22hv2lfaewlJ3D6dbSRN3QqUHeAe0t+9eTm5enCx9f02PyTT8pcc4lU4h2xvOJV3631rhzy6dySu4yqK1mWzJheS4rb17Hid1aXDCyvb1n06jTuHAwV0uG32qkCDkbr1+jz+XT4/Pbc9vr3+Tb2mbw7jd52buqgaLl4uLTVt3gHrN9oAPsX1/sjZUeC/CzdtY3TZ8S4e6tZHkB3uupT82uc72Fq/IVe9rW/EKN7Z1HUbii9tSnUaYLXAyCv078FvbSz7fcGtqBfStu0vDntuGMdgPeBpcW/1XtkEciR0CvLPd+h+yfVY8mHwc/M8PjXw0d7R+EbtHQqkhw4lVcPEOhwPuIXgLiF99/wApzspXuLil2ysreoRUpCnetDcgNw1xHUDB8gV+fK1SXHmOS8Ex12cfXS48l6kHqGiRMKTC2QXEQpmsWmaeOh5rW3zcs/wVuaGD15b9qbn0w0NY2PE7lVvJcZcZPiUlNWue0XZeAeqTxDnNGzSQk4y6ehSe4lxJ5mVzyFhMMaByyVU8RkKYcY08kS0t06QTO6kL3FBgcTPTCspjVTc0MkgzPMIYYENCKZiqeU4VpAYgesJIRgclJ7QHAAggjnyRpaTGtuFNNbVkmUqhlTexo2cFB+WnOyuM1WLdkCnyVbd1YVnKJC9qXOEyIzKQzKw2kEuRQDjKRIJwEDBUtShMnCiTyBQWSESFXvsU+cITskUJBJFSkqOYQkNym0EeKAITQruhhTGygN1IHCSpWu1pVq7XU6LdRIyJWQmQIWi1rPp1JYYKpuJ798t0ySdMbZWvYQlPHMSkmwSYkT4lZC0g8lE02lWvY5hhzSD4qEq7sFZpRzCg8EHIV5Ki4zutzKpYpSO0KZA6JY5q9UTTNXw4eS28At23XEGUHfnAgDxhZLpsOB5Qjh1xUtLuncUjD6bg4exa48sZnLl4X2dGra17R/d12FpB5jdIbL9JfBR2S7M/DH2arUbdjKfEbf8An6LSBUok7PHVpXgfhO+A/tn2KdWufwdXvrCmC41aLC4tb1IHLyXu5+Hj88V3GePO2d4+XEwpNxsqn1AGyMqo1XHZeWutrucMraHiSv1Nw2u7iHwIdmeKXDnG74fd0hSedy3vNMT0g/QvzR8GfZLjvbjtNQ4HwSkX1HevXrEepb0+b3HkOnUr9M8VpC5fw3sR2WripwLgpaeIcQiWPqM2pN/SMyTGAY6Lpw8PVLlXu9JyW/LPdV2OtKFHjPGuNOhlBj30qbiIETLnfRHvXw3t3xL8Ndqb7iQnRVqep4MAhv0Be4+FLtzbCk7s1wCoPRaXq3NZh/nDzaDzE7nmvlV1chrC6RK+jw8enH7R5semcOHt5+rj8X9SphfoX4Ibl3ar4E6trWd3t3wCt+LJ+MKLt2+QK/N/Ea3e1TlfoL/JBqOHBu11OpPdPo06bRyLjP3BcOblmOe3q+w7fj9H4xk7WcCZ2j7KXfBnNm5tWuurF0ZDmj12eRaJ8wvglhWfYXbqTye4q+q8dB18wv1I6jV4dxuhUewepXbIOxE5HuX5q+EC0bY9s+M2DI0ULyqxschqMLpy545Y9Uev7a4enp5Pfx/hcw1KNzUsqsA/QTEiPMKFSN4hb+PUHUbDs3fxm5sWkmPjOY9zfsDVgeCHuZvpcR9K8OU1lY/O8vH0ZaUOKhKseM8oVL91lytGpSY4qBCGqyo10qpDpC6fDOIXFrcsuLes6lVaZDgYXGYOa0UnELUu+1JbO8fbPg+7dWdzcU7Tjj2W7nENFbZkk8+g8dvJfW7rsjUu6Hf29MGRO8hwPNfkKhWId4L7F8DPwv8AFeyVWjw7iBdxLgc6TQcfxlAdabjt+qcdIXzfV+hzy+fg8/g+36L7X6Mejmm5+L0/H+z9xbP0VqLsYktO33rzjrI0amnTEeC/TVK27Pds+BU+McFuad3bVR+bgtPMOByCOi8T2k7EUgx7209LhjaOa+Rh67V6M5qx9ecXHz49XFXxu6ti6k4cwFzvRTJle24lwt1s4sc042lcK6o93JAiCvdxc+52efk4Jvu5ZsxAP2qyjYCqYETMDK0BxJjGMea18NpPfWa1s5OY3XS82Um0w4cbdaXUewnE7uh3tu1plsmV5zjPA77h1U0rmg9hG8hffOyd6Lax/LaXqgZcV5/4Rrnhl8wspsY8zgxz/gke1eLg+0uW8vRZ2e71H2TwXj3j2r4XVpSSBM9NoVZYQ049nJdviVq1r3FmDJAMbrmvYQcyJzC+7hyTKbfmOX09wuqwEEQCtFF7BOwUnU2nJznkl3UD1Wn966b24zCx2OCWrbyqKbW6nu5RzXe4z2IvLa0NyGkRuIXO7A1H0OOW5gu9YY6L7V20udHZl34oE6RHKDK+N6v1efDzY44+79N9n+h4ef01yznd+crig6i8gZzGBuky6q08GRy64XWvA11Z5ds4+7yVPolKq6NOSMAL6c5ZZ3fCz9Ler5WN14XCHNdIWasQ6XDBnMjdds8HplgePb0CxV7EUjGqRthax5Md9meT03LJvJxnYdv7lZSdpcM5mVZd0tA9XA8ViqOhxiV6cctvDljq93u6PbbtFW7Ht7KV+OXj+CNgeh6mgQHag3WG6wAQIAdGI2wvK8T7uHPaMnK5ffPmJz9iVSq54yec7qTjsu165060hUOSFGTJny8ktYJEnkkTEeGfavQ4VJpzvOcrv8KtrZ9qHEBztzK8747npKtpXVWkCGvMb4K5cuFy8O3DyTju7NtHFWso3DtEQFiZc1GbOJ8ZRUque4uJJd1KofluN1vCWTu552ZXcb6PE6gMF3vJWn8IVajcvlcN7SIIB8VdTeWkZ2W2HRNy9zpOF0bJzHgE5+zyXGo1WkCQuratDm+qSMJSOg21pP2OQTBHWFMWhEZacT7VkmrTGoHHNX0bpw+Nz3lRWtlAgRzxIhV17fAOmSAMwjv/AFYadtlnq3jmYccLO7tWe4ogGMTnCpdSBl0kYWsV6VTGoD7irm02OBLSIIx4ps04lxRqNJg8ljfUqsJEFd+vRJkke5YK9uYyBJGE6k05hvHgnVP2KmrdEjLj71or22+6w1qBbsDJ6dFTaLqszmTzKglojEeaEQiXDaVKldVKUb+5AIgymQ1wTY6FlxlzMO1AQu1bcXo1I1kQep3XkH0+YKr1VKZMO5qXuse+Fe2qCQ4bSfFN1Ck5s4IK8RT4jWYdxjot9DjTwBqO25WLGner2zQZGyyVKQnKoZxhlQQ5ytddUntw5WXSUjQpu5KLrPoFNr52KsDnTMlXqRk9FeR8VVvtag/MMeS6tKoIzlXjQRsnUaeddRc3klTaWHbmu7VYwjaFjq0hGydW10zsYH4IUK9o2JarQ0sMpuqADKJtzK9EjksdQRhdiqWlpKxVmNcD5KeFc52ClKsqMjmqXSFRbqEHxUZVRJA3+hJriTuoLCVFxyk05zugkRsoqOyBlBcJSITaaSU2hVA+MKYeFLViTh4qBHik90lRLlJTQhBEIlKZlNmjCTlLdRcm2tIIQcJRqEJtNGkkMCESijUoH2IJlJRdBBQgoaBUShE9QopbIJCCVEnKM7MnCQygqIQMkKJTweaSAOBKTiU+UKOnxQhgk+CY80hA5pEypaqRJxshQkoBUNLJ5qDyIEIcQRCiUJBPRJMBJwzCi9hKEBImEU0JEyhKmxKRKbdiUiptfJFKEymESQgIQ7ZNEo1pEJCBuj4vtUXOlDQduiVGUSipalFPT4o0+Km0ICUEQn8VImU2BJEpKKEykhAFLZMpFS1DlQB3CRdB2UTuooSKajugYTSCCYWaqLt0kzkpKCSHclJRdyVt2IoQhQe4I9baRGMpTM+GEAEgTPtQDBmR44X0XmMDqP8ABMYaISBIgg5jCATEK7RIdPf4JkcvDkVA6j4+xT5TM+zktKBtkn2KTBvmZPJRaBJk7nHMKUw37OQTbKTZiYiVt4f3euXxG8lYoGrHhBcpaoEBxiZWcpuNY3V26PEBTMQRqI5D6Vh0kA8o6q2l67xqJMjGVouKNNrJaRI5eC543p7OmU6u7DgHxnGcKbT1x4ILQOeJ5BDRG/uXbe3JIklwM7jKQaCMCPphS0xmVNoJxELNsjUlVlpB8/YlGc5PktPdPIkR7lW9hBztzU64XGxADEdeak3A5+KYmJ+xMwTkwlyOkmguOBJV1pZ17u6ZbUKZfUeYAAWrhtFtR2nJJ/RGStfGL+jwHhpoW7m/hC7BDnj+ip9B4lYx5Lllp2z4ujCZW+UqVenw554Xw19M3bgW3V4M6Bzaw/eiRqDWk6QIE8/Erj8FZ3Vvqd8apnyC6bXgZ5r38eMkeW1e3mVNpzmQqmuDxthXtGJXSJsas8ypjOTKUdAVOmAMk7clYga2d1MtOMagOSeroJTa4DcmJ2C1rQQAmYyk6Sc480F+knAGUZMzqI96oqeRqyVH8WRg8+atq91SomrXqNt2D8+s4Nn3rgXXHuHCoWWlSvev5i2pF4Ht2XPPkxx81ZLfDp8SsxxDh9xw8n+dbNN04bUGW/Tj2rjfCVww8T7M8L7TW1I66VFtpfMG9NzcSekGR7lr4PxVl/VfQqUaltVb6zWVcOc3qvS8HvqNrcVmXdJtxZ3be7vaETqER3jRzMYcOYHULx+pxnJj8TDu9fps5LcMvd8++CbtBT4Zf1uF3Tw2jdFr6TicNqt294MewL9M8BrsrWNGqx2C3kdl+WvhI7JVezfEm3Fk41+E3fr2dyw6mx+iT1H0r3XwL/CKy3DOD8brwBinVcftXx+fG549n1PScvws/h5rP8o/shUt+LjtZZUi61vYF5pH83VGNR8Hfavj1Go+g+Wk6TyX7bFtYca4a+xumMuLW4Zpcw5DgV+c/ha+CbinZWvU4hwynUvuDuJcHgS+iOjh08Vj0/qbjems+t9Jcbc8fD54KgqDfdaeE8RvOF31K+sLmpb3NF2qnUYYLSuUC5plpwrG1DC+pjzTOPmyXG7j9Z/Bd8MHAu2NizgParuLTij2imTUxRusbg/mu8CvCfDF8BfEbKpW4v2NaLq2y6pZf0lPn6vUeC+D997J5r6p8HHw59o+y7KPDuMtdxvhLIDA98V6I/qP5jwdPsXLKTzH2OP13Hz4/D9TP5vlFx31tWfb3FJ9Gsww9lRulzT0gqLasnclfq+5ofBb8Mlt3lCpR/CWn82KN4zzb+ePKV8n7Z/AT2l4Q+pX4FVp8XthnQBorNH6p3XKSxy5vs/kxnVx/NPyfKw4ZJUtQ0EjolxCxv7C5db8Qta9rVaYLKrC0j3qt5i3Mb7KXJ4NWeS1S4e9EySoN+MB4JgLF8omHeCZqHkAFFILItYXOMSrWtIdtsMKhj9O4UzUkyJVNp1HbEnYKouHihzydlEAnmEEkxsQogeKkMAqzsVAGCph5PKFW7dNphXKbZWJHwRKRdK42Nw8KIIyAo6vBRUFg9X2pkBQLktRCCcIGThQDjzTDkExhIiVEOCNSLtMJSohyiiLJRPgqpUg7qgskIa8KqTyRKsiNLXZ3hO7qay2od4gnqqAVYyHghxhdNbFetQc8Eq91vPxHT5rO9jmH12ELXTplY24dp0nLRt4KYyJBWX1eRTL3NwMLNm1lXPdG/JVGoOqiys7ZwlScxjxqaYPRdJxy+C0i8I1eCg5jmb7IGVi46VZWZroF3QysZEHK30AXamnm0qDaBqbt55U0rqdge2PaDsL2ntu0XZq/faX1Dnu2o07se3ZzT0X7N+Db/K17D8fsKdr26sqvAuIBoFSoyma1tUMZIj1mz0IPmvxxZdleK8UuadDg3Dbm7cdy1uB7dl9A7L/AALXFa4H+cnEqdrEE2tmO/rnwMYb7V6+L0nLn3k7f0aw3bqD/KH4x8GXaftfUu/g34TfUqlapqr1ms7qjWcf0aW8zz9XyS7E/AtxniFGjxHtZdN7McKfBaa7dV3cDpSoj1iT4wvrfAuz/Z3sBw993a0rHs9TIh/Eb57a9279SfVZ7A45Xiu1Pwx8J4dUqt7K2VTil+8aXcUv3OdPlPrO+gea9c4OPG/Nd16cfSdPzc16Z/3/AEfRbelwTsj2Rfw20DOyvZve5q1ag9O4iY3qvHxQf0GyeWNl8g7efCpX4pangXZO2PCuDMb3Ze1uipVb0AHxG/Sea+fdoOO8Y7R8QN/xziNa7q/mtcYZTHRrRgDyWB1xoGlm69E1ruxyer1j0cE1Px963G4NJkF2YWC7u3OmCqKlcn4xz0VdNr69VrGML3OMNaBJJXPl9RJ2xeTHj96lTbUrVWsY0ue4gNaNySv2H8DXZf8AzR7A21pWYG3t0fSLrrqIw32D7SvnnwFfBPXtK1HtN2ktw17fXtLV+Y6PcPsC+zcc4la8MsK15eVm06VNpJJML4vPzXO9OL9z/wDT/wBl3gl9Tzdr7flPxeO+EO+teH1/Srh4ZToNNaq7oG5X5M4rdXHGeNXV+5hdXvLh1TSMmXOmB74XsPha7eV+1HE61K1qFtiHRg/Hjb2Lq/BH2bteFWFX4Re1VLRwnh412NF+Dd3H5gA5gHPs6BevG6wmD5H2l6ifaPqunj+7Pf8AVV8K1rT4VddlOy8D0jhnDGm8g/FqVDrLT5CPevJVHanOdtJJV/Erm84jxS84zxKoX3t/UdUfP5oJmPsHsWWq5rGFxOAs5Zbu3wvVcs5OW5Y+PZTXrNpjO6o9JYcEFUV3uqVC889h0Va8+XJduMxbNbXfFcFJphYVY2q4b5Cs5fxTp/Bua7G6tY7Kx0q7Dh2Crwc4XbHKVizTWxxHPC32VXSZXKa/qtVGpA3hdpWX1P4JvhF4x2H4sLmwqirbVCBcWlR34us3oeh6OGR4jC/YvY7tB2e7e9nvwnwaqHRDbi2eYq2z4+K8fYRg7glfz2t6uxByvadgO2vG+yHHqHGeCXQpXVIaHMqSaVenuaVQDdh94ORBXi9f9mcfrJ1Ttn+P4/V6fTerz4Mu17P1T247HkU6lWlTd1wF8k4xwt9F7mVG7GNua/QnYDttwT4ReyI4vw1nc1mHur2yqEGpa1Yy09WndrhhwzgyB43tl2epk1arKZgmTAyvyc5c/Tcl4+TtY/UcHqcfU4bvl8Or25pukjE7K/hd0ba4bUPIrucV4Y5tQtG+orkusajSTpX08eWZYtTC43cfXezN5Y33DxlmQQRK8F284U+jePqWuWEzpBlc3hd9d8PPqVCG9AVur8XqXZcKoknYk/YvHx8WXHydUvZ9L4mPJh05PC3LnB+lzduvMLHUpscMfFOMr0PGKVNzi9rRBK89Wa9hhwMjGZX3OHPcfC9TxdN1e7M6iQcYU6dvUc2Y8ipskvAeNzC9FaU6LbYOBaJG55joumfN0uHB6Wcu/bTL2bcLG/p3FRpJYZg+5e87S9rqFfg5t2HUYAGdz1XhaY72qBRBPQAwtPEezvFTam5FImmAHYGY8unJeDlww5M5lnX1vT5cvDxXDim3mL+uDVLwRDtlkdduYcEAc55p39KpRqua9rmmcgiI/wAFgrExJztsF9bDGWPzfNyZTKuieM1mtDJwMhZqnEdZJcB0mFzarzJz71S8wCu2PFj7PPl6jO+7pOumu5j3LK9zDMdFknJBOQkXOjfJ6H6F1xw04ZZ7XFsnmZ6KRpCMHE+5Z21HAun2qXfOM4JHgt92Nw3hzRnccyqodHv9ik+rMbyEamwNRO+6stSyVWT9ijJIUpGr6SrBEAQCJ96tyTW1Pmkd4MR7lfSomq7Sw7mFqq8MrNGpgmFLySdq3jxZ5TcjmGQORnmoHYREc4K1m1qNJJGI6Kl9NzXGZmcqzPG+GLjZ5VanNMgkrdacRNMQTgLCRAiRGyqcCNlrbPu9Pa8Tpvhr99tsLU2pTqZaWz5rxQqVGOwXRMYK2W3EXs3Jn7lmtSvS1KxbInA6FYrmtrBg4iRlYhe6wfWJ5yoOrfYsy/iqFarVZmT71os+LuYdLz7VirVAQRgwsTyAStbR6+hxRlQCBk4WgVaNcTIyPpXkLZ0Oj7eS6ttVMZMe1ZsJXYNm2oSWgEnx3WW44S87NO/JW2N5pflwgHAW+vxCmWYgfuXLLksrrMJY8tcWL2kQP8VjqUHhpMTAC9DVuqTjyEKs0qVVmMDrC3ORi4POOb607Dolnquvc2EglsdcLBVt3MBI8VZnKlxqkgwJVNQYgmPFXS784FHquzAKbNMbmEGCD+9VuBkxK6HdMIzuoVKDZMD3KbJHPD3tOHFW0rx4Pxip1aOdiFndTDTlNpp2bXiQgS5dOheUnDLwvJCWnCup3D2cym109g2pTOWuHvVjK7WjJELylK+eCPWWqnfOd+cmyx6VtSm4xIVdXTkDOFxWXhnf6VdTvSBkoL62+yz1CCrDdMcFUXNcSQQVdmlFXVpWcl3VankbFRDGnMK7SysbwSFnqjwXScxs+1VPoB2ykHLcOXJKFurW0TCzOpOBiEFQScVJzHdNlDKBOOVEuKZBlACiwaicFMYCQaZU4hSiJPXdRJlSO6juiwDdMbwooDo3KirW5MKegdVS10HdTD0UqrFVBCuL53VdRw2CgrRzITCSIWrwScpJESioFJTIPmgNJ5IISkpOaVEgondElI4QQkUATKgHQpJAygQdHJSUEKWrpLUlq8FGeiCSd1NrqG4zCQcQkhRTlLmhEoBBRKTkEmkt2UXEkzskEIn5moE5QUBE2fPdCcJKN6MJSAjPMoQkOJUS6DCYwqjuirHbKAMFTUZ8FNpsnOnkoqfsQmzaIE80wITQobCjq8FJRdyQMiVEiE9XgouJQEJIlCKEiYTScYCloCoOJBhDiokyoAmShIIKbBugJoWdqFF3JSSIlQICQjT4pjAS1eCCSiTIUlF3JBFCEIPajqpNy7nhSoUaj3QGnK1VuH3NGn3hpu0EdF7euY3u5Tjyym5GXHgAEwGgSc+SfdujGxSLHbTB39qvUzYcdD1SIPTEQAP48U5EAYwiWk5xzW5U0GEnOB7VJpgQRIGwSOOk/QJTjIM7YhalTQaDsVa0bwJVY8MhTbnp7Vm0WUyQcR4eC6fC7c3dQt3Ix4lcwGQNI2XT4JcdzdguIDTjfmuHLb09no9PJc5MvDbxXgj7agKwHqnfOy4pbBiYXtuMcToXHDnMmXOM7ZPgvH12mZIgLn6fkys+Z6fW8PFhn/D8KzTx4KyjBIGIVjPiaS0T15qJkP1Aldbk8uOLu2NOl3XrBo1DOFiurenrOnlsFlZXe0AtJypCuQZc4rzzql29eWWOWMmme4phh2zKpAJOOavuK2oxjwwt3CqVO0t28QuGh7nEi3YdiR+cfAfavRxy5dnkzsx7rAx3CLVjpHp9eAxh/omnn5rx1xX/AAnx4MNQvaDpBn81v78+9eh4nX7uzvuJVqsvYwwScuc7Ahea7F0g+pe3LsilSDW52c4/uC9GWMws45/N55lc95V6VkudO3gr2kTGxWVhgHKspO9aTnK9UYdGiYAxK0U/jZkrE2sWtkSQm++7pveVnsps6vIb9q3MpPJp0cgSFEudjZcOpx6nUa70SjXu3DGqm3TTH95y5d52iuWuIq3tG3/1dszvanzj6oXLP1XHj7tTDKvYl2hhqVPVaManOACwO45w5tQ06NSrdVBu22pmpHmdh714W74sysZFs64eNql5UNT3N+KPcs1xf31dgp1bl/djAps9Ro8IGF5s/tCf8Y3OF7a97SmgPUoWlA/+Yr63fMb+9cO77UVnuIdxC7Iz6ttTFIe8yV5yGgeq0BIgHcLx5+r5Mvd0x45Gy54m2pV70WbKlSf5y5eazj78KL+LcTqUjTde1W0/0KZ0NHhAWQtB25JEQvPc8q3pOhXqUa7a9J721WmderK9XwvtD3xaLg93WGzgcH9y8lACD5Lpxc+fHezOWEr63wvjNB1rV4de21G5sbj+etapinUJ/Oaf6N/iMHn1XC478GT7u3rcS7FVavEaVIaq3Dqgi8tx+r/SAdW/SvI8P41c2vqPZ39H9En1m+RXrOAcfY+rTqWlxUD6Jlul5p1qX6rhkfSF6b0cvedq78fP0zp5Zufj7xT8HnwndoOx9y2yuzUurGm6HUKvx6fUAnI8iv0x2H7f9l+11qPQL6k6q5vr21aGvHUaTuvh3FqvC+1TNPaOwF7caYbxC0DaV839dvxavnv5Lx192J4tZPPEOzN83jVvROrXaE07mh+tSPrAjwkLx8/pJlfwr6XBzZSfJerH/ufyfevhH+BLs92idU4hwOq3hF+7LmtbNGoepbyPkvg/bH4L+2fZcPrX3Cale0b/AN5tgalOOpjI9q9X2H+HDjvBQyx49RPEqNM6S53qV2RyM7nzhfduxXwodku0LW07PitGlXe2Db3PqOPhDsFeO/G4fPeNXg9Pz98LqvxRUBhVklftrtf8FHYDtcH163C28OvKgP5VYHRJ5Et2K+Ndrf8AJw7SWVGrX7PcSteKsbltJ4NOq4fZPtW8PWY3z2eXk9Dy4+23wujUqUKza9Co+lVYZa9ji1wPgQvpXZD4bu2PAxTocRqs43Ztxpup7wDwqDPvleL7Q9me0PAKzqXGuDXlkW7mpTOn3jC4og816pyzLw58eXLwX5bY/UnC/hS+DHtrbts+0NvTsqrxBp8SpBzAegqN+0wqOOfAP2R4/bOvuyfFH2oflpo1RcUD9Mj3r8x6eoW/gnG+M8CuRccG4reWFUfnUKxZPmBv7VZk9n+ux5O3Pht7/tN8B3b3hRe+ysWcXoNE67R8uj9QwfdK+dcQsOIcNrmhxCzuLSqN21qZYfpX1bs1/lCduOHNZT4o2y4zTbA1VqeiqR+s37wvZUvh+7IcdZ6L2n7MVqLHYJ0MuGD3gFb+S+ezHwfS8l+TPX1fnFrydipDC/Qlbg3wE9qzrs+IWnDbipENp1HWxB/VcNMrJxD4ALW6pOrdne1LazPzW1mCoPnMP3KfC3927Zy+zuad8dWfk+DnPJC+lcX+BPt1YFxoWlrxBjfzqFcA+50FeS4p2Q7U8LJ9P7PcRoDeTbuI94UvHlPMeTP0/Lh97GuDtyVjKb3DUNIHUmEqzalJ+io11N3RzYKdO3q1T6rCfHksyON7JFlJvxrgT0blJ5ZHqFxHipeiNYJq16bfAZKrcA1xDcjkVfAhupBR23KcwmxIIICAU5XOtRS5KVJ8bhQKkDk80iVFCuhOUSopKaE5RI5ZUSiU0JA+5MkclCUwmg5Qd4S9qB5q6QymFEOAEFEhXWhapNduqNaNXSfYFqQ0k7fBUCXREz7U2squMNpvJ8laLG9dnuHAHquuPDnl4xrNsjNA6JSSugzhV2RLtDQerlss+zl9dGLenUrnpSpl32L1Y+g9Rl/xY+Jj7OEpNdBX0HhfwUdr74tNHglyA7IdVimPe4her4f8BnFGNbV4zxPhfDqf9d2tw+wfSus+z8p9/KT+b0YcHNyfdwv9Nf3fGaLKtZ4p0mPqOOzWtkr1HAvg/wC0vE3McLL0ek786udOOsbr6nYcI+C3shWFbiPbBl5cMw6nbgH6rASPepX/AMNHY3hbDT4F2fu76oBipXIptJ9sn6AreL0uH3stvRj6Tpm+XKT/ALri8A+BK7q1GvveKAtnLaFInHmV9B4N8FHZXg9P0i7taTw0Sal3U1AeJGAvlfHfhx7Y8QaafD22fCqREDuaet49rp+xeD4zxvjnHKpq8Y4te3pmYrVSWjyGwWsfV8fH/tY6a36bDxLl/wBR+h+NdtPg47PtNF/FanE6rMC14cPxQjkS2G/SfJeI498NnFalN1p2Y4Ta8FtyIbULRUqR1iNIPvXySmGMzIUa1YHAfhcOT1Oefe1q+qz8YTpn5f5dLjPFuIcYvTdcVv697XP59aoXR5dPYsT6rAImSOiyF85ldHgPBeLcdvBacH4ZdX1Y/m0aZdHmVw+L093CceXJlqTdZH1nuGkGB0S9Y4A3X2jsV/k9dpeKOZX7QXNDgtqclp/GVSP1Qce1fcOxnwWdh+yYbUteGNvrxo/0q8AqOB6gHAWLz/zfS9N9jeo5fM6Z+f8Ah+XOxXwX9ru1NWm614bUtrV5E3NyCxgHUTk+xfo34OPgh7OdkGsurhjeI8TGe/qt9Vh/qt5ea6Hbr4UuxvZQOZecSZXum7WtrFSp5GMD2kL4P21+Gvtd2quHWPZyhV4Va1DpaKXr16g8SBj2e9cb8Tk7PrYcXoPs27yvVn/W/wBPb+b7t8JHwkdm+xlqW3l2yvekepaUXB1Q+Y5DxK/MXb7t52i7e8SbRc2pStnO00LK3lxd0mMuK63C/gp4tUonjvbfjFHs9YuGt9W7fruKvkyZnzK3O7ZcA7K0HWfwa8GLbpzSx/HOItDrgzuabT8UfxC78fDMO9ef1/rPUc+Oue/Dw/D/AJX9/wAox8D+DzhnZm3p8d+Eq49FBGq14LTcDdXPQOA+KPNYu23aq/7U31CrdUadnw6zGmw4bRxSot5OPV0c1wbivc3N5Uvr+5q3t9VMvr1nFzveVQ5xy5zvMlbuU1qPgc3qp0/D4Z04/wDd+v8Ag69SRLj5rmXdbW6B8UJ3VcvcWsJ0rNC8uee+0eOQkKRb4oXPTaKFIhRIQCsZVewyCVWhJbEs230LljsOMHxWlhO8yFx1bSrvp7HHiuuHLZ5YuDu0Kkc10KFSQCDC4NrdMqEDVDui6NGoRzXsw5I5XF774NO23GOxPaSjxrhFWXCGXNs9xFO7ozmm/p4O3ac9Qf2BwXtBwbtt2Zo8e4LWNS2q+rUpvEVLeoB61OoOTh7iCCJBBX4NpVSDMr3PwV9vr/sTx9t7bh1exr6WX9oDivTHMcu8bJLT7Dgr5/2r9m4+sw68Pvz/ALen0Xqr6fPv4fozjXCA57nNbDpkiF5S/tO5e4FkHy96+o2z+Hcb4TbcY4VcNurG7pCrQqs2cD1G4IMgg5BBBXC47wQV6L3s+NE/4r8Zx8148ujN+v4+THObj5bdUyXkU2k8sLKaVVp+K7f6F6xvDW0bwio2ASM8ivY8D4BYXVEamNdOdgvdfWY8brMO29vi91q2M5ErBVDS4am5X2jtf2S4fRomrSa1rua+c8S4RTYZYMjIAH0L2en9XhyTszl6e5Tcce3oUHsgAS44jn4ru8A7K3XGQ4W9TTSEZLd58JXm7gG3qSHQJGF6jsL21o8DDqVw2WzgwF157y9G+PucF4urpzXV+zVbgd6x15D2AyDBH2jBXtavHeEjhDg+owucyCIGf4K8B8IHbulxZobayGAZI5nwXgxxCvUJJcS3n0C4Y+j5PUYzLl7WO2X2hw+mvRhN/R2O0tC2r3tV9INaHHAaIXlb20jUBlaLu+q0nSDOdllN9O8lfa4ccsZp+c9XycXLlbrVc6tRqNJjA8N1nex0c8dV3KZo1dyDnKovKLQNQkheqcmnzs+DtuVxgMgfcoOMT71udQDjsYO0KNS0IEg7Zyu85Y8947WA45E+xLmSOiuqUXNMFFKg+odDAS4lb65pz6bvSoAuETykHdDgRuOWFsNvVtTL24OTCz3VRro8JPvUxzlvZcsLj5UTkTgoDzBE4aFBxxvuhpjMrpWGq0uTSqh0jrBXYp8SpuZHMrzhdBgdVNjyBzC458cy7uvHzZYdo992ZZY3APfd2TO56LP2r4bZ03d5QAa4nIncLyVne16FQOp1XN8QtTuJVK2alQuPUleK8OeOfVK+n/rePPg+Hlj3/FXVssTyKyVLV7ZEE+S6TbkECY8ldaUTdv0Acswu3xbj5eScOPJdY+XnX04GZkqh9IgzGy9TxPhZpAuIiecLjPtCdl0x5sc/Dly+nz47qxzNTwdyrO+cGic5Vtag5pIjks/dkFdZXCyxY6oDtgdearkYzMoDOgKmKRjMx4IlV945rjB2V9K8c0iSVW6m4AY25wqXsdOMKbWR1G3pJgOhWG7JbBJ5QVxGlw/O88qYqubuVLNtb06VSq4mZ3Sp3T2uJndYW1iXQTA5qbXeI9iyrr2/ES46XBq3U30a7YJAnAk5J6QvMFxBldfh3aG7suG17CnbcLfTrkufVr8PpVa7cRDKrgXM/uwpYsv4tFa0pkloEHoq/wAEVKrZpkBYWcQdMkyF1eG8XbTbpqELjnc5Oz0cM4sstZ+HLurK4tz67CBO6zF3gvR399QuKZjaFx3Ug9x0jdMOW2d15eDHHL5L2ZAZGVB7WkbLdUtHtp6gFn7t07LU5I43jsYKlLMhUlhC6vd6sQoPtTGy1jmxcK5ZBBTZUcNira9PS+AFSWwF02zYvZcOGSQtNK5HMrmwUw4hVnw7DKkkEKTqjmhculclgyVqZcseIlXel0106+fWKtDg44IJ8Fic2chRZUfTdM4TsbsbnU3jIJVRL2nJSbdbEkK9r6dQck2mtqu8EQ5Mmm4KZt2uyCo+jugkSi91ZoNLdxlUvtBuFqDHARyQMkps0wut+QCgy3yugWyFWWwiaZxRZIU7mlTIBYI6qT+oVb9RCoxVKZDpGygRK1uYSCFA0+iyrL3ZKTmkFbGloweRTqhpbhTasABTyr9AUS0KCEEhQIjdXiEFk8kVlAlJaO7CTqcbJsUgwZTLvBJzSMKuD0TYuDxOFLW2N1nkhIPjcqJG0FkZVdRoIWbvM7p63fpKNTuT24woFWauqi8tndXbKp/JIGFMkRjKQcqpAwolDskpLNqwykhLnMqBzCbVHdMbKeCBIpHJlNFRT2QSeqDyQkAQUvzihGggpDAlSlBByZMckEwhygAZUXCDupAwgmdkRAEx1UghJTYaRQhECUJoQIlNCEEEk1FGjKSEIBKU5SJA5hS0B2UUSCou5IG7ZQ3TS5qUCaELChCBuEFBF3JDdlFCCTt1FCEFirVii3mgihSdyUUH1XhVqKTmVH6STBM8gtnEeI24tX0wNTiIiFyPwgWUdIHrdVhqVi4udtOVfh3PLdev/UTj4+jD3Wiq0O0yd5VdVwcZBOSq8kEwB5II84Xpk08Fuzloxz6+KYE7/YgQdvIq1tMxO56Le4zraLmY38kw12I8ypCQQcGR9ylIkYiU6jpQg/wVLGAD70iSRMqbWBwGYHRXZoNMbc9lpoNJcPE77yqWAk85IWpjHU4IMzz3hc88o3ji9T2e7P1uJtAFXRzyMQl2k7NV+FMa+pDmEwTIMdFHs72hq8OjS0mMfGXV4txl/FrYMqNGkbc5XzLny48v/wAX6DHj9Jn6ft994tjYftzVrrb84nBEiFKvTdTrEHlKbav5rhIXruVs3HysMJLrJnewN5yq6uyuqGahPLwUSwuOlgJccALMyauMVWlHvahe/FNmX+Ph5lanVn16hqPw0ANa3k0dApXJbQY23p+sG5f4uVYAw8TB3HRfY9LxdOPVfL5PPydWWo5va8gdmX6XSX12h3LYFc3sU3+Tr44zVpj6Cul2tptf2ZuS0Ad3VY4gHxj71yOxl5bWtO6Zcd441A0spsbqL3DYDxyuPLZPUS38GuOb4+z0TaZJgAk+CpffWtB5o02VrquN6dFuqPM7Bc3jHENBNO8qupl2Ra0HQQD+m/7guLW4lXNHuKIbQofoU8T5nmufL6rp7YtY8W+9d2+4pXbLatzSsWjanT/G1fadguPV4lRDy6hamtV+Xu39472DYLmY5BMLxZ8+eXu7TCRovL28uxpuLh7mcmDDR7BhUtEclFHuXK23y1pPfZCQKWeiKmCokpOSREwVFw9ik3HOURKCIdhAJlSaFGoQN+SBEwk0xUD2vdTc3Ic0wQr7Wyu7sE0KLnM5vOGj2la7fhAdh1w6s/8AQt26o83HAWsccr4S2LrHtDcUYbdNFZo2e3Dh+9en4Xx63uarKjKxfWYJa9rjTrMjo4ZP0hcS37PNcAXU2UB1e/vHn2CAupacH4daQ9tHva8z3rzkHwGwXv4seTxl4c+rpu8bqvQ3dzY8baafGbC24tOBVf8AiLtvlVbh3kV53iXYqxqVD+BeMG3f+bacVb3bz4NqD1XfQtmh0qyncVabCxxD6Z3Y8amn2FdMuGXw9OHrbf8Adx6vz8X+v+WSw7RfCV2Ce0tuOI29uDIFT8fbuHmZEe1fQezX+UreUWtpcf4FTrkb1bSroMfqn968rZcSdaf6LVubOTkUamqmfNjse5F1bcE4qQeIcGsazz/TWf5LW9o+K4rx8vocc/Me3i9VjfuZ6/LL/M/w+5cD+Gf4PO0tv6JfXlG2DxDqHEqI0n2mQrOMfBd8GHa6g+4t+G2jalTIueHVgAPY0wV+c7zsJwau7+TeO1bKoR/M8RoEN8g9v7lkb2S7ecAf6Xwjv3tGRV4Zdap57NId9C8Gf2bq7wyse34nJZvLDqn4zv8A2fT+0P8Ak0ABz+AdppOqW07ulEDzC+a9oPgb+EDg5e93B/TKLN6ts8OB9m66XCPhi+Ebs9W7q/uqly0GHUuIW+ffgr3fAv8AKQploZxjgDg7YvtK2D46XfvXL4Xq+PxduOvS8nb7tfnu/wCG8S4e8s4hw+6tHAxFak5v2hY/VPMFfsCz+F74M+0dH0filWmwP3ZxC1wP72R9Ktqdj/ge7Vs10LbhNRzsh1nchh9wKT1XJj9/Bm/Z8y74ZSvx2RIV9lfX9i/XZX1zbO60qrmfYV+peK/5O3Yy8YX8L4pxC0cR6ocWvavG8Y/ybON0nudwzjdlXYGkxUBBnot/63iv3nG+i5uPx/0+bcJ+FHt/wwgUO0t3VaPzbgNqj6wK9Rw/4f8AtpQEXVrwu8/rOolh+qQPoWHifwIfCDZBpbwulctdzpVmk/avJ8R7GdquHue277P8QZoMEiiXD3hd8PU4f8cl+L6vj97/AHfSqXw5Wd5TNPjnYvh9zO5ZGfeFKv22+Bzi7WjifY+5tHH43o40D6jgV8XrW9ei8srUatJw3D2EEKvA3cAvROe/jtm+s5v+cl+sfZfwb8BHEqhFDjXFeGE7atWlp/vNKP8A4b/B9ff9l/CZaAn4ra4YPeSQvjWOqFr4svnFj/UYX73HP+4+xH4D7u5J/Bfa7gV4T8UNqGT7pWO5+Art3RB7tnDq8fo3ME+8L5W17mmWuc0jaDC2W3GeL20ei8VvqBG3d3Dm/YVerjvmHX6e+cLP5vaXHwRfCBRJA4FUqx8nVafvXMuvg67cW/8APdmeIt8mB32FY7ft922twBT7VcXgcnXLnfaSulbfCz8INuIZ2muCP69Km77WqzHjvg/9N/8AKf0civ2T7T0nHvOz/FhG/wCR1D9gWKrwXjFI/jeE8Qpx+nbPH2he0ofDX8IVL43FqVX9e3Z9wC2Uvh47csHrs4TV8X2pn9pX4fH+J0+mv/K/0/8A9fNqlleU57y2rs/WpkKk0njdpHmF9Vb8Pfa7d/DeCuP/AKcj71c34f8AtJ+fwXg7h+o4fer08X4p8Pgv/P8A6fIg3xTDJ5hfYB8PfEz/ADvZXg1Q9c/uUv8A481z8bsbwV3m4/uTp4vxPhcH/wCT/qvj2joVIUT1C+vH4erwCG9j+Ct6Zd+5L/4/cZaIo9meD0x4air08J8Lg/8Ayf8AVfJmWlZ5lrHkeDSVfT4Rfv8A5uzuX/q0nH7l9NqfD/2nM6eD8Gb5scfvVLvh87YxFOw4Iwf+mcf+ZWfAifC4J/7l/p//AK8NbdluOV4NPg/FKgOxZaVD9y6Nr2C7RVj6vAeKyf0rZzftC71f4de31T+bq8Nof2dr+8lYK/w0/CNUkN462lP6FvT+8FdsOb0+H/DbN4vT/wDnl/SLrf4Ke1tYam9nr+DzcWt+0rqWXwL9qq2XcKbS/trloheTufhQ+EC4k1O1F8Cd+7LWfsgLm3fbPtddgi57TcYqg8jePj3TC3/ruKfd44nwvTT3yv8AOf4fVrX4DuNsb3ly/hds3m6pULgPcFpHwW8Gs2B3E+2vZ+0aN9Dmk+wFwXwm4vr24M1r24qnnrqkrO+SZ380n2pnj9zGT+UOn0v/AIW/XKvv34D+CjhzZvu3zbkt3bbNEk+xrlmqdoPgR4eMUuL8VeOoe2fpaF8LylA81nL7V9Vl2mWlmfDj93ix/pv+77c/4W+wXDTq4J8HrHvbtUuNDXe+HFYr/wCH7tI5pZwng3COHNOxFNz3D6QPoXyAMdyCYZG5Xmy9RzZ/eydJ6rlnbHt9JI9txb4WfhA4k53edori3aRBbbNbSEf3QCvJX/EeJcReX319dXRPy1Vz/tKhRtqlV0UqNV56NYTK7PDux/ariD2tseAX9Uu+LFE5XO7vmsXLl5PNtcBrXeIUh1c6PBfUOD/AZ8It81rqnCmWbScm4qBpHsXrOG/5OXEmEVOM8YosESW0Wk/SVmWO/F9n8/Je0/q+DMfB9X3lXNeXuDWB1R52a0SV+pOE/Av8H3CKLbjibxdObubmvpZ7hC7B7UfBJ2QpNZRvOBW76fq6bSi2q/6gJ95S5WeJt9HH7Eyxm+XOSfv6PzJwPsH2048WjhfZriVVrvz3UjTZ850BfSuy/wDk29obx7avaDi1rw2l+cyiDWqeXIfSV7Tjv+Ul2ZtZp8I4Vf8AE3RDX1Ios+8rwvGP8oL4QOLE0OC8PsuHB+AadE1ag9rsT7Fys5s/yanD9n8PnLrv5d/7f5fVOz3wB9hODsFW9oXPFXNy6pd1YZ81sALu3nbb4N+w9o6zZxThFmKY/wBHsgHvMeDJz5r8y3tr8JfasmrxnifEX0nZcbu5NOnH6uB9CzUeynZrh3r8d7U2xcBLqNk01nz0nYFb4/RZ3vlXsx9ZlxY/wOGYz8bqfv8Aq+u9q/8AKRs266PZfgla6fkNr3h0M8w0ZPtIXzq+7T/Cv8ItZ1vSuL11s/BoWbO5ogdHEb+0lQtu0/Yrg40dnuxruI1xtc8SdqHnoGPesnHO2najjVPubriYsbXYW9m0U2gdMLvOPjweHn9d1f73Nv8ALD/P/wDWyx7Cdl+CO7/tr2pt2VRk2PDj39dx6FwkNK3f/EGjwekbT4PuzFrwWnEG/ugKty7xk7fxheGpmjRbpo0hPN7tyk6o4mScLfXJ4fOv2j8Pt6fGY/n5v9f8aauJ3t9xK69M4zxC44ldkzrqvJDT4DYexZXEnoAokpHC572+flnlnblnd03vDGF7thuubdV31XaR6rOi6WhtRpY+dLhBXMubd9vU0u9Zp+K7quXJtmaVgeKk4N65QI6JSuawN3UneShJ1SlJO5kIujcIccqKChQOCowpSQESioIUkoUCktMgwVts714dpeZasSCCtY5WeEs29JQrtcJBkLRTqkHdedtbh7HROF06VYPbgr1cfNtyywfb/wDJ6+EV3Zviv+bvFa/8i8QqS1znYtbg4DvBjsB3Qw79Kf0ZdXIpvLXAROV+DKNYh0OyCv0t8B3bl/aPs+eAcRrmpxXh1Md3UeZdcUAYBJ5uZgHqNJyZX5/7d+z5l/6njn1/z/l9f7K9VrL4Of8AJ77jFOjWPfNZB8NiuZacZrcPc4MeSFovX1GB5MnGMLzN2/va5aAZ6L4HFh1TVfpJfZs492nub15ZkN2PivKcXvn90/MiFp4zrt2a4yfBecuazrklu3UL6vpuLGSaY5OWydMcq+u3PJk7jK51WrUI3xsStt7bPpvJIMEyrbSxD2Bz9ua+vhnjjHy8+PPky04VWo6XSI5Ek7qLK7mTtAO66nE7RjCQ2ZI3K55s3vBc1pK9OOeOUeLk4s8MtRjuaxqOJJwstR2Y67LVc0H0zDmmJWao0E48l2w08PJMt9xTrvYcHEq5tZ741fbsszmnBg4wJWmmQABjotXTONpucG5nEyoMudbu7AnKouqsOhpVNtWFJ+oiSrMdzZc++m6qHEGRv9CdpU7isXECOaqq3bCzDicclkq1y6Y5hSS3stymN3HW4he0X0iwAYBHjPVcYskF3ioazMjdIVyJldMMLh4c+Xl+Jd5FVicqskRHPwRUeCMHmoDLSF2m3nvkOO8TCk4mASMjmk0iY5Kw6ABic9VLVmKtro+lMPyCokDllPBxB8VFkaaNWDkr0XZi5otqQ9wBmDjdcCjaueyZ5KdPXbmAXavBeTmkzmnt9Pllw5zPT2XH3UqtAFhaDvC85piZnHRQpXVZ8Bzic+eFqZRe6G6XEk9F58Z8Oae/l5P9Tl1yObd0Q47LL3LQ6IE9V6f8GVH0vVZuJHLK415bupPIg+ULthzy9nk5/SZY99MraDAc5nwV/cMAwFWxpJySB5Iuahazcrt1vJ0aJ9NkwPpWavSYZhvKcKvv/WVk6g4yAtysWMNSmBM45BVPp9FrqtcRG3sVRpOIKu00zaSNvamHFu0Kx7C0f4Ko55FNpFjSSVN1J+XclS10EGAtouGGmRLcLGVs8OmMl8sklpj6E2vO2ozCjVeC4kKAfyz4K+WPC/vXDZx96021yNQB+1c8mcclJjtO26zljtvHPT3PBKNO6o7iY2VPEuC1qbnPpslvgvN2HFLi0fNNx8RK9dwztLRq0Qy5gO5GF8/lnJhlvF9ngz4OfGY59q8++g5joLSCPBWB1NrQH7r0dzVsbphaI1dQvL8Qpmm9wHVb4+W5dq58/ppxTeN3GG/psdWLqexWQUC7ktD6jgOWE2VwBDgAesL1TOyPm3GWsNSk5pzhVFoBhdC4fTfA5pU7Y1GktErpOTt3c/h23swFoAUCI2K2VKLmOLXCCk2gXZhb6pWem+EKFw8DScrQCHhZKzXU9wVUKpBwYQ03mkSJCTQ9nXKop3REiVfTuGuxKSovp3D2ASStVG6B+M4LnVXsIwVWHGd4V2O8XU3sMEFRfb6mamriC5dTqD1iuzZcUomlpeQIC555WeHTDGZXVrFUeGug9VEVJ5hZ+IV2mqXMwJ2WUViOcLWOW4xZq6dEmeaSxNrwfjK0VQRutdSaaEyARBVDaoEAEKbnSJBUEKjAJhUumIV4fG5lRd6xTasxmMKtxIlatGVW5g6oilhdG6YqOHKVZiIAVTm81Nr3LvIOVIPBVDxDlNrcK0WkAhUvpxspgwMlQdUOxz4rCqXiSqyFY4EqDhCsqWInAlPKRzgckyYTYHHEKBJO6k5BaOqixAJBSc2AolNlSLcyEiMhKUi6TMKbTvtIkRGVCEFBwouiwhBElAwFWps88kJaoSCKIQ4pyokwiSaRJISBQ508lGUVKTzKYdPJRCSiJxndMpJEwohoSBlNBEplNCKWyClPgpCCFm1ZAo/FTJhRcVpNJqOoc1CUipaaSlJAKTjnCzuro0tSi5yjq8FrYkclR1eCNXgkoBIoQmwIKE1nagZQiUKAQo6vBImUATKSChAIGE0lBNJvNGrwTAhUJ3JRUnclFB724aA6AcEe9UuBAO2MK2qScndVmSYkbwvRjWcp3DXESY8R5qQJkQZ6YTFJ/JvPmFay3dpEjxV6oTC0mUnOy1pPkulwqxrXtwKLJk7noEWDqVNgBgO2ErTa8TFldNq0gDBktnGRsuHJnlZ8r18PFxyy53t7uhxfstcWVmbltRlRrcuB9+y86WQ6ANhnwXo+Ldqq17Z+jNYWscBqJO6861zXSTuTnxWeC8mvn8t+tx9P1z4HhfbcPq1hqptGnr1RVtH0nd24Z5Bb7C/ZbsIc0kjEbKq5uzcXQqBuNgFqcmW2Lx8PRLL3UstnNIJaVvYKZpy5rYOc8ku9b3ZEQY38VnMnYkZ2S21qSYeFtCl+MgAdDPP+Cu/wez71kEkCOQXJ4fb1Hu9VpPNdyzZd2VRrn0yG8tQ3Xm589TUez0fHN9VijjPC30W6wJb1XDfR3POV7etV9IoEFhyIPiuFW4bWdkMcemN1ww57Jq115+DHq3jHCFKMSFro0BbWxu3tguxTnn4rqUODuBNS4Bp0KY1VHH7PM7Lk8Uqivcc2sbhrRyXv9FjebPftHyvWZTimvesJy7U4zO5KTnBp3Ua9QTAKpe/r0X3erT42tpXbPSrWvbE6RWYWjzG30ryPArk2HFaT3jRpdof4civR1apadTfWDT71we0dr3V36TTH4quNY8+a8Pqt7mcenhuuzFxqnUpcVuC+ZdULs8wdlmLjvldWqDxXhrX4N3biH9Xt5FccCJlfOzmrt6JVk9EioAlTGQuamJJwmoF0FS1BVUmxOVImFAFBfH7kQ5OUASCFbRt69YamUSG/pPIa33la6FpRc6HVn13DdltTLvrHC1MLS3TnyGrTbWd1c5o0HubzdENHtOF2rOxewg0bK2tiP6StNWp5gbBbPQKVX1r24rXZ/Rc7S33BdsPT5Vi5x51lm0P0OrtqO/QojWfeMLr2di9gDqHD6VA86tydb/MN2C6lLuaDdFCgykwcmiE/XeZ28V3x4Jixc9sxs6dQh11VqXThs15ho8gMLVRaWjRSYGM3IaIC5t9xextC5rXG4rD81mwPiVw+IcUvL2W1Knd0j/RswPb1Vy5cMPBMbXpbnjHDLVxa6uXvG7WCcrm1u0tdzj6PZta0c6jsn2BeeAA2wnJXny9TnfHZuccdh3aHiziYfQaOQ0bKyl2ivmgd9b0K3kS0riAmVLVA3WZz5/ivRHpaXaS1OK9pXpeIhw+jP0LXR4rw2uRpvabSfzXnSfpXjjUUS5h+M2fMLpPVZzyz8OPoNO6rMbFKuTTO4mWn7lfa8Vq279bGupO/SouNM/Rj6F84pPNMzRrVaZ39VxC3UOK8QpNgV2Vh0qNz7wtz1MvmLj14XeN0+m0e1NzUY2lc1qdzTj+bvrcVm+8Z+hU1rfslxEflfZe27wn4/D7nQ4nrpOk/QvBU+PO2r2hnqx0rQzjNi7Lqj6f67VevCvXPX+ok1leqfnJXpbvsV2QrA+i8e4hwx5O15by0eGw+1Yz8GfF3O7zg3G+F3xAluitoqH2cveslpxdgj0fiAzs0Px7lrbxB5cXOp0Kro+MaY1e8ZS4zLxW563iv3+L+ls/y0W9t8LXZsg2VXi4azbuK/fNHsk4XRtfhi+FLhI0X1R9drMEXVlH0gBZLTj93bACjc39Bo2bSunFvzXSF1qHbbi49WpxVlZkR3d3Zte33t0rln6fHL70lejD1fB7Z5Y/0v+G7hn+UTxum4encFsbjMk06hYfpleit/wDKH4RWIbd9n7xjeemq132wvIO7RW14C3iHZ7s3xFx2dBpH6zT9qprUOxd0AbnsNd03Rl1jdBzfMBrhPuXnvoOG+cXpx9TL93ml+ss/R7tvwu/B1xQEcQ4G+kXY1VLNj/pElV1eK/AtxYzVbw+m54girbupj7F89qcB+DZ5/wBK7R8NJ+VonQPP1T9qyv7Hdj65PoXb+i08mV6EfSSFyy+zeD23HecnJfHTl9Mp+r3t52V+Ce+pl1iLAF2zqdwQPpK4V58HHYqo09xeBpO2m4BXnD8HNap/oPa7gdwD8Ud5Dj7BKqq/Bp2wpuJoVLKu0ZBZcRPvWZ9nWfd5K6b/APL0+/pq/wBnRuPgv4Rk0uJVQOWQVgr/AAYUQD3PE3zy1NWOr2P7eW06bKq8D5OuDP0qmrw3t7bgh1jxIAdHT9hWp6LnnjkYt9N/y4LP5VdU+DO5A9XiVMnxYVnqfBzxBokX1Bx/VKqbc9tLaZt+LN6/iXH7lXU472rp/wA4eIN/Won9y1PTepx8ZuWV+z75wsFX4P8AizNq1B3tVLuw3GBsaR9qZ7V8dpn17isI5OZ/gke2XF+dwfmLfwPU++UY6fs6/iqqdiuNtEinSP8AfVbux3HhtasP/uBax2y4pGazT/dTHbXiURqp4/qrXwvUT3jPw/s+/wDKsX+Z/H+Vq3/aBIdjuOxm2YP74XQHbXiM70/m/wCKZ7acQ5Gl81Ph8/4w+D9n/wDlWD/M3jvK3p/7QIPY3jx2t6f+0C3ntrxD/VfN/wAUf578RG3dfMVnFzf+ULxfZ/8A5Vg/zL7Q/wDhqZ/9xqbexXaA/wDd6Q/90LcO2/EgZ00vmq1vbriQP8zS+aVZxct94nw/s/8A8q57ew/Hz/RUh/7gVjewHH3CdNuP/cW9vwgcSG1vRPsKtp9veOvP4jh4cf6tIlb+Dl+KdHofa1zW/B12ifyt/wDaLQz4MuPOialsPJxK6DO2PbeofxHDa5/VtHH7lqo9oPhMrR3XDbls7TaR9oXTH0+/N/6Z+F6e+Jf+2O2+CfjFRsuuqLfANJXStvgav6gGviDR5MUm3PwuXB9WldUQfBjQnU4N8K120mrf1GDnN0G/Yu09Pj+FbnpsL448v6V0bT4EKcg3XGg0c8ALuWnwQ9hLMauJ8bc6N5rBq8M/sf2squJ4h2ntKB597elZ6vY6wpH+U+3VgOuhxqfeuk4pP+J/p9f+3r62T9X1Gl2a+BfhDQ66ube4LT+fXn6AtLe1XwJcHdqocK4bcEfoUtZ9xAXx8cC7BUCfSu1F1df+nox9spx8G1nIFnxi/jYvqBk+6EuE99J0Seemfz/w+v1Ph57DcOYaXC+zIgYbpt2MXJvf8pK91Gnwjs3RaDtreSfcAvnI7SdlLZumx7GUHkfFfcVS533oPbfiYZpsOB8OtB+aW2+R7SsdHHPef0qfG48P/cn8pb/d627+Gf4U+NTR4dw91Bp27q3cSPauXe//ABf44/8ALeJ3dFrsQ+4DAPYMrz9ftj2xrEj8K+jNPJjWN+wLkXVzxC7eXX/Fri4ncF7iEl48fH+Ey9dxf+WV/pj/AG29Pf8AYi4ZTbU7TdtLSidzTfXNRw95WKnwz4PLGe+4re8SeOVGiQD7TAXnW0bVv5j3HrMKctGGUwI6mftUvJj7R5763i3vHjn87a9C3jnZy0dHDOyzKh2Drit9wBVdftTxsiLEWnDWf6imAfeZXCdUeRGogeGFBZ+LfZzy+0efxjdT8ppsvb67vSXcQ4lc3R8Xkj7YWUGmwDTSaehcJSDRCZZ0XO52vHnyZZ3eV2DWeecDoNkB7uqiGlACzvbO1rXSrQZGyzPLg31d1dY1alSq2m4tptmHOjYKS+y+xV3vaAQPKVK3uaTwG1Bod15K/i5tdLG0KrnubhxjB8lyniBOxCmV1Vnd2HN2I9YdQqntDm6XMBb0KwW9xVpSWu9hytVvdtqODHiHHnyVmUvZNM77bJ0CYWWo3T9i69Rm8dVnq0g8Q4ZGxWcsPwWObGUcoV9a2qMEgS0c1nXKzTcCChCgJA3TGyXtQJ5oAnEqQzyUZypNdp6IInBQETqOEKBgrTQqFkdFmCkCfKFZdDd6RkZXc7LcfveBcXteK8OrGnc21QPZ0PVp8CCQfAry+rHVaKFQtIIK7Y5zKdNYuNneP2nwfjVj2m7NWvG7GBSuaUmnzpPGHMPiDP281ibRaLkkgDxlfFP8n/tcOE9oPwDf1y3h3FXhrSTinX2afDV8U/3ei/Qd7wyrrcaZgHpgr8h630/+j5rh/wAb4+j9X6H1M9RxTL39/q8p2notdQxERvK8dSYRWIGRMbr2HaWlXpMcCyYxPSOi8ZQuWi4h4GThej01+R25NdUWXtEvLRpE4Xas+F0zZF+xI6SlRtGXmnRz+lelt+E3AsDpE+rIgZWuTn1qberg4pvdfLeOMNO4cDmDyVFq5gYWuIgD6F6DjXCLqreuaWuJJxP3lbeF9iq11SaQ4y4xAMCOeV7p6nDHCbry/wCk5cuS3GPBcTIe7EGPcsFK2fVqQCSOq+lcT+DziFNrnUwHgGY3lR7Pdi65e43DQ0iREbwus+0OKYbmTzZfZXLycnzR4V/CHCmTJauLf0zRJB3+/ZfQO21s7hVQMaJYRgkD6F894lWdUJJB23PPyXq9Ny3lky9nzvtL0/H6e9EndheSc49ihkA5jyQ50Df/ABSwcSPGV9KeHxb3WUGGrUDR9K1XNnop6mHIWKm8sdIJkFajdPqAN3XPLe+zph0a7sL9yDP3KtxOMb7rqmxDmEz474XNuaZpPcHbLePJKxnxXHvVU+I80g8xOOYSJ1Znw81CcROF025J6uibdbienJVSRutNo9kkOGfBZyuouM3VTpEyCENqHAPsV165nIgThZHGMrMu2rNOnQvnU26Ty2TqXge6RlcwPKNZE+XuXO4R0+JlrTu8Nr0hVBfB8F7DhBs6n5zSfBfNqVUg9YXQtOKVaThDz715efguU7Po+j9bOLtY+t21tTqtFKmxpLvDErPxzsPxGtbOu6TA7GqAMx4LyPAu0tS3u6dVwENdOenivsXDO2vDbnhAL4ZUDfWaV8PnvqPTZS4Tb9DhycPq8NTu+D8Qt6tnWfTqMLXNcQRC5dw5zgWmfavddsjRvb+tUpNgOOSF4y9tXMcTpJC+zwc3XjLfL4PrPS/Dysx8OU8kHGFOlUJEEyp1GZ6EKgjQ7pleyZbfLuLZTBdufBXNa0dOiy0akZTe5x2MKdS6WVqbHNhYq1MsMbx1WgOcd5UarcYWpWbGJwzMnCUGMKdQFroRmOpV2zpUcDdRB5nKHkySZhW2ukzKluosx3VYOI2whzs+CncwD6uVmLp2JSXcOnVXNfkgla7UuiQVzpgrTRr6BA5rGc3G8bqtjbyvScdFQgDkpemVarvXJKwOqAyhlYNcCSsdDpOS+Nug9hcJVOg8k33Y7sBsKkXUOkpJWs+meKKwLPNbLG4axkEwViqVhUMyqXy0SCrZuaZxz6LuOrWrUnvzBVQfBMbLnd5BkuKspV4xKTHTOWfVWm4aHtHNZHUByV+sESDKZOrIhdJdOdm2CowtKg2oW7mFvewOWapSnIV2mlffHqrWVAckrK9ukwk0kKljcdLs80iA04WZlUgZKsbUDvNKSJuGrcqh4PRX8lU9xmENKZIUm1iBEpubJ3CiWFDa1lYjmptrnzWXSVElwyrtG/v+uFJtZvIrm947mpNqxKI6RrN6qtzgcrF3vimKxAyVKsatXggnCztrZyUOqTzUaSJ9YeKtbUbpIwspKgXxslTwtcc4SCrDsypNeIQ2mTCpeZwFN2SqzM7KRECVLdImCoyqtT2CC6FAyUQl7GzLp3USmE4UthpCUoUyFAlRZBCHbIKRyqshpFBSlFCQEIAhQQTJhRhNEqbTaGlOBzQTCagUBEJoRCAhBEoJkKKKAYT1eCigoGhRlCKZRqPJRJRKze4lKRcounkYSQTUCc+SJMKEmSQgnzlRcMpSeqRJ5oGTKEij2psGyN0QhTamhCYWQkIKEAhCgTKBIQgoBCEKAQhLmirGiE0hsgmFUJ3JRTJlJB9NuLB9I/jAWxmFlextM5HLp7V3+0nE7WuWigHYn2rzNaoXyQYnks8WWWU3Xs9Thx8eWse7VTrsaDk/vVpuWkEATC5rCZyVY8QwHpz6rpY885KvqP3gg9IKgBUdIE+xZnPdqGcDK6NlVYGaSBG+VvxGZ8+ShznNwWxHgmwycGMZU7wg1YEdFGmDnBlTfYuOrpayYIEzvjxWm1pFzwCDJOE+G0m1KgD+WV07mlTpMD2wCFyyz12eni4LlOp2+Gdl331tNKqdUSB1Kw8S4Fd8Pqup12R0I5rodnO0lSxDW1ACAN53Xd4jxi24qwDu2jT+c7E+9eC83Nhn38PuT0/peTilx+84PZ99OlcDvGt0yP8AqvoVk2yvaIZpDi4bncLxFOzphwLYPivQdnHmjdMa53qk5Xk9Vl1d5XTgt48el6/hfZP0ollKk0g83K647F1bar+MbqDjyC972P7gWrS0gkiVg+GXj9Hs/wBlHVKNQNvromlbgbj9J3sH0r5/Fjyc11je9eL1HqujL8nwf4Qby3p3Z4VYFvc0D+OcDPeVP3DbzleDunnUZPJdS8qt0ucSS47ndefv6hLpBX7v03Fj6finHPZ+Z5+TLmzudVVaulxJMyFmrVXEEh2+FXUqYySVne/fOQul5HOYp1KxDhmOR8U676dxaVLSrhtSNDv0HdVkrOGrdGsaCScjmpvqndrWnIpPuuG8Qh0sqUzBB2I+8LZfWrLuib6yaOtWkDlp6jwWfiF0LnS0tBLMNfzjp5KNs65s6jKkOplwlsjcfuXgy1u4+zvN63WQ4MJhdVzbO/JLotrjqB6rv3KtvCKu7qtMN5uXK8d9muqOc7kraFvWrSadNzhzPIe1de1sqLASykKzh+fUdDR7Oa1ihTIb31V1SMimIDB7Auk4bfLNzcajZS8NfUdUcfzaI1R5nYLq2/Bqo0nvKdAdQNTj79lvbXa0AMa1oH6IhSLyRvhdseLGeWLnarbwuzbBrOfXd1qOke5aWBjKehjQ1vRohVB/Uph2YELrjqeGbtbrJTBnqsN7f29oIc6X8mhcS74rc3BLdWhnJrVM+bHFZha7l5xS1tTp1GrU/Rby8yuHf8UurqWuqGnS5Mbge3qsLnTsorycnPlm6zGQyiVEGEi5cW05TChqUdSC1zs4UZJVRJT+hQT5oUZTJ6IbMIkqIKaG0g93Up6+rQoEwhBM907dnuU6Zcz+Zr1Kfk4hUlCsppuZfX9P4tyXD+tBVzOMXbTNWlTqeRhctrjyUw9w5rU5LPdLjHes+KWtwdDiaL+j9j7VvkjYkHlC8kdJBkLvcHqvq2I1EuLTpkr08XLcrqueWOnTZe3tFkUrqswdA8wmeKXjhpqvp1hz7yk132hUHZRDdRk8tl22zOy19ak7NTh1i/r+K0n6sI76zbkcP0HrSuHtj6VWSYkhVuCLMrPdpZxOvRkUbzilBp5MvHGPerafHuK0s0uO8UHTW8P+1c8tPRVlvVZ7fg6zn5Z4yv8AV2h2t7RNHq9oKvk+g0/cpt7Y9og7PFLap+vQXniwFQLfBJbPd0nreef87/V6j/PbtDH87wp3nShB7Y8Yd8e24PUP6q8tpS0gJ1Zfi3/ruf8A869M/tbf/wBJwPg7/wC6FD/Omq7L+zHB3f3AvOAexEQnXlPc/wBbz/8Al/Z6B3aZpEf5pcGP/tj9yr/zlZz7JcH/ANkP3LhEElKFOvP8T/W834/9T/Duf5zU+XZThA8qQ/contM3l2W4S3/2h+5cRrT1TM7Sl5M/xT/Wc34/9R2f86Kg+L2d4UP/AGgpDtbfj+b4Rwxh8KIXBc0yEi0xGpZ68/xP9bzf+T0bO23H2fEtOHN6RQCb+3fazPd1LSnP6NJq81pkwE9HiEmef4r/AK7n9s67z+2/bN23FqdPyY39yy1+1Xa6rIqcfqZ/RAH2BczSEwwK/Ez/ABZvrOa+c7/Voq8Z7Q1hFXtBekdO+dCy1Tc1vWr8Suap8XE/aVPT4BIAJ1X3rleXPLzao9GpvPrVa7/MqbbW1bk03O8yrYRBU253uQoWg2oAHzKIYPi0qY/uqcKJbJyrsQc95ETHlhRGrmSfap6PApgEBEVnxT04JU3CUtPiobR0wCiFMCJCAIQQ0hMjBKbhiUo9WVAgJ55UiEDCkiIQpQpASpACU0sVmmDsqjScHSJWwAQmADupcdrK58OLvWSdEgHaRK3VGMiQMrHWpkGVi4tS7RvBTbXf3QIZyEzCqpnS5pG84U2hvOVIMbIKz7rvToF+oykROVSx0AKQcOq6xFkdCqK9vTfmNLuoCt1DfknrCWSq5VejUpbiR1CpnqurUMn1T7FjrU2lxkQfBccsfwWVnBAOU89EnUiPJTpEYBG3VYW1CE+e6lVgOUDOFSU+SOaCg7qAB8VKVGUwsrDG6tYSD1VbfBWMMbpOw6No71RD3NIyCMEFfqr4M/hEo8d7G2Ve9gX9Bvo92er27O9ogr8k06sTlex+DPiz7PjPohr93Ru4aSdg4bH6SvN6/wBPj6ri1fM8PV6Hn+Dyd/F/cfpbi/EbW7ovALX6hhfL+MllK/LmYBdKvu+JXfC+IVOHXbgYEtcNnA8wuVxKu6vVa4GZXzPTen+F9H3uXkl7e8dnhXGnWpaSQdJlfTOzPaqzuLcU6hAMDM7/AMSvil4HU6Gs4IClwXi/dVmsNSBPNdeX0ePLNxrh9X8PKY5eH0/tjxW0Y8vYGF4d8X7VxrDt0LN4ZEjYHGD5rz/Gr6g63B7xu2IK8tSqd5XhpnPJXh9FhcNZO/qfX58ecmD7G34R7WrSDHUfWncxHnuuTU7d0KTy9oEEZn7188uKbmUtTjkDPvXHvqzi4gOMcl04/s3ht8OHN9q8nFPD0fa/tD+FLlxfABMQvPV6dKo3UYk/SuZWqlxMuAnqq3XbwNxC+vxcE48Zjj4fA9R6282dyz91lxRDQ6HSOoVNFheQAPDbkq6lw9wkqy0uu6rB7hgH3r0d5Hh3jcu/huq8KuWUi5zPcufUBYcHMr0zuM29Sz0CJDYAC4DwyrVc7TAJkDouOHJlfvR6vUcPHjr4d2GX5bT0ukluFjuq5qO1OHrfQrLmlpEhZHAjeepXbGTy8ueWXionaZMhTo0jUaYPtlVua4DAMKVKsWEDoVu267OUk33Rq0iwwTM7Ktri0QCcc1dXqa3T0mFQT7FZfxLo3uJImSonxSkagCEswJydkEpSDhylRMxhEgGDhRU5IUw+BGPcqdU8swmXYnYqErbQuC0tzGV6bg3EmNpBpeF4troxK00rgtAGpeXm4pnHt9L6m8OW3uKN3RqXTQ5wDQ6HdIXt7bhHCrrhmvu6Zlu8r5JZE1D8Y+9dT8J8Ss6Xd0q9RrAdgV8zn9PldTC6fc9P6ydNuUR7S8Mo216+nSILdR2XBqUCMYPRari/q1nl1R+okqIeXbr28dywxktfL5Zx8mV6Yxim8O23WqnQe5o9UjzWm2ptdUY0gb817nh3Zxr+GurFvrxIEbrHL6mcfl04PQ/E93zx7CwexVPJGIW/tA0Wt4+mZEGFzG1mE5K9GGe5t4ubi6MukyAcGCqKjByWnU10QQVRX1NMxhdJl3cbizOpkqAlhO4Vnejmpeq+QYwtsaZKrySJ2KqcSDK1VaMbDCpcwhWJpXlytZnCA0QgCCFLVndIsKg4Hori8bSm3STkrHU3cVB1IOpXkN5ZTLRCszTpZg4q8uluyi6idw0wq3S3fCblTvCcMqdKm7cSVUHT4LfYVGgyYTLKxcMeqs4Dm7yFNjy3mu5acJq8SDqlFoI5krlcQsq1pVNOrTLTPMLGPLLdOufDljN+yFOqJyrSGvbhYTLcqTazhsV1lcLdLqlsDsJWWtbkbLUy4J3KkXteOSrLm924IBLeS3vptOQstdkHCbPAbUBOVJ2l2RlZHy2SEmvIG5VNtLxAlQaTKhTqF26s1+CpEsFI0wUBwKmHBTazuofSk7KPd+C0ap5KJIO6bNRnNJxBEKLmOaFsYWnJTqBjmxgKbTTngu6KQeQMgq5zANiqXtJKS7PdFz3DCjKZBJUVVSDipNd1USU2uA3U2xtYCQEPEptIJGYWkMpFnJRYxFs8kEFXlgJ3UC2ChIpdySJJUniSoOBG6Bs5qSg0wgGCjQJgqMJuOUgq0agNyppFQJIjKCJSTaBKUc1Lu3LOxFCNjBUdXgqaSQhRLkQkIQjRJFCFNgQhIlS3YJRKjPIIQDjIhCRMKJMoJ+1QO6EkDk9T70JBCmzQKAhNS1QhCIUAmhQIkzKCaimhAgk7kh3JRQCEJoAJQkhZ2GhASKBoSQN02LBsoKYSdyWhFCEJR9Cosa8kOdHNXegteJDiCVyxXdO/0K+hxB9MAz7Esynh6MM+PxlFlxavouBAJCg9lUsMtd5QtVnxBlW5aawgDxXcvrywNg9ru7MtwRuSsXkyxsmnbD0/HyS5TLTycOdsDtst1jTIcAROcKuncUWO5eSnbX1KjWB/NwcrrlbY8/FjhMt5V0qtlUqNLu7JHWDAWuw4LVezXIB5SoDjtq2mWkaiOWEqPaY0mFrGA9J5LzW8viR9LGekxu8snTsOA1n1TqqBhbyAkwrbrhT6VdtOrUkO2J6LkM7UXILntDRPgqq3HLq5rCo95xsAufRy27rpfUekmOsZXV4jZttaPeMJjbyKyW94+m7BIHvVsvuqQ1ukkYHRZCzQ8h3XdXc1qpydst49o7FHizsSV2OG8Vmo0h0ZXkXgNaHAxB96sta5bUbLoXDk4scoTmyl7vvHY7tLUpsbTFQRG8r5r8KfbGp2l7SPripNnbDubZvVoOXe059yy8S4qeHcCeadQ95Xb3bYOwPxj93tXga91qJ9aJWvsv0swzvNf5PF9o8stmE/m2Xd6STJXLuK+omDKjUqEiRlZajhqX27nXy+n2SqPxMqhzyZBSe4Kt7wCSSs3NdBxAyYhc67uS4ljCdI3PVTvLjBa04VNvTkh7lzz5L4izH3W2tAR3lX2NWy5rNrMaypLmtHq528lQ92d1U9xELG9LfKurTfT9ZplqdvfOpwKkvYNmk4VjKvQ+9VVKLX5GD0U7+Ydvd2Le9pXIEO0uAjSrsjcFeaex1MyCRG0LfZ8Uq0x3dxFVnjuPaumPJ+KXH8HX1geSkKx6hZqNajWE03/wB3mpuxyMrp1bZ1ppDwTzlYOJcS7qaND4w+M7oquJXZo0tDSdbhy5BcVziVy5OTXaNY4bWuqOqPLnkk+KUqEpFy83l08LJUS7qqySoymja7UFHVCrJSlBPV4InrlQlEpoTlSB6KrUUBNC1pygKuUwqJnCFElMGUEpUvaq5TBUptIhBSa5SBlF2RCZKToQ0FxDWgknAAUEmhznBrQXOJgAcyvSWVFtnaBjiARlx5Ss/C7Jts3vqsGqRj+r/itukveHPyAZAXr4cNd3LPLadMF51uwOQViR9yAScr0a05gjCgWjorFEiFGlZaOirc2Ar48JUXNHNTQzloSLCroGqYUwCU0Mhb1SLB4rS5qjpyp0ijR1KRYATHVXlu6NI6J0m2ciDATLPBW6cp6fFTpVRoCCxXEHwUdJTRtSWGMqGlXweiRbiSAmkZw2EwFY5vTZNolTSq48UQrAAlCaChIgKcRyQW53hXRtEt6KQATdhRlTSbOMwkc7IJJUZ6FUN0JEIO+UIIwgBMJk4QEIDQEJgoIOE8lEYwpk5MBRlRRA5JhJOVEAwphQCYKKkT9CCc4JSJCi52EDceSrcCfFAKi44lSm1b2iUo8UycKDiCsWNSrA4AKbXc91mmFMOhF20a8QoveIiVUXqt78JaJOeZUDUneFWXShu8rG10k8wJBVOr1lNxVbiCsVYb3SooBlLTGSsrEt+qWqPFRJMRyRKbVNSCrBhTlZFjSpTKrlSGxKCQJGy02ld1Ksyo0nU0giFlnCkCQmx9xbcN7QcD4XxJtT8eyn3VQ76o/ge9Zb6LVzQDIOMrx/wc8XNF1Xh73nQ/16edjz/jwXb4jWuqtVzjqc0GJOy8+PF82vZ9n/UzPjmfv7rb++c+lpzOy5PeFmQV17Dh/ptOdRnosHEeHV7asaTmOHiQvRx9GPyvNzcfLljOTXZT6XUcCHPcWjEE8lv4TUBc5xwcFcx9BzBnmV0eH0/xQMcsfYt5ydPZj03X8SW+zdfXwP4omT9izVLLvKJeXeJlc657xlYwMNOIC61hUq1aIbBJGFz10TcerHKc2dmcedvqfdVSOuyxVJ/6FdnjFEMdvsea472NLIDwIzjK9nFluPkc/H0Z2KiYIAPmlJkx9KjUIa6I33Kr1iZXZwbKJjGpWio2YaYHiub3mkiSSEB5kCSsXDbUz7Og6qHTjfkqXODfjDnsUrOqzV62+6svHtcIacrPi6dPM2sJpubmFda2FKpTL3STuuaWVQOYC121xUpU4BhYy3J2rfFcer54hd2radQtG3iVRStKlTwSuLpz6pLip298KROT7FreUjOuO5fkpuLd9E526yqzpjdXXt22swgAjPRYi4nmVrG3XdjOYzL5fDRSpl5wRCjcUnNdgyIUKFc0nGBv4Kde5a9sQlt2SY6UF0HdMPEKp55pE+KrOlpd5JtdmVSHQclMOB2Uqx07C7dTqDJA816a2LLqhIOYjzXh2vc3YrqcP4m6iNGoQV5Obj33j6HpPUzC6z8NPE6QoViBtKro12gQfeqeIXormZWehNRwGymMvT3TPOTk+R2La4Y2s12+QV9U4HxSlU4QwNcCRTjByvjwpuZlriu12f4o+1cKbidB8V4vVcPxMX0fS83TdVHtpQd+EKlSDB2Xl3kt2kL6Fxa3p39oajXZIkea8Rf2z6NVzSPYu/peTeOq8/ruD5rnPdlo1YdkkrW+qx7MkLnPkJBzthK9b5u9dltXSXYUA+CMoLXESqXAzlal0xY2MrNOHIe1rjIKyaSNka3DnC1Mk0vqNDRuqXFHeSMlSADjClyJjtQ5xkwQkHkK2rRAy05WYyCrLKlljQyq4HJWinUbOVhB6KWsjms1ZdV6vhgtn0IcWkrJxOzo+sWEexcOlXqNMhxHkrPS6xBBeV5/h5S7le7/AFOGWHTcVNdndvwUUqpYd1Gs/WZO6qlemTc7vDbq7j3PYji1K3qGlWOHZiVq7a3VpXptNEhxP0LwVC5dSOppIIV1W/q1RD3ErzX0/wA/XHtx9Z/C+HYKrxlZjUyUOqAk5VTivXj2j5+VTFRw5qxlYt5rI0kqQJVZbRcu2lBfO6xBxCsa9NqueBlZ3CSrCdRmVAiFdropIUw6VWcFKU2zqxaJ6o1uHNJrpTIwSpa1oB7hzTDj1VJOUwRyRFheRsgPd1UWgnYEpEHYghNiZeCokqOlRIzuU2d0pCCAdlWRHNWMc3TlDStwhRJwrHmVS/ZVOlJjyCrRWhZkJo21iqOZU9QIkFYSYUw8hsAlRrdWuIB6qt7goakiQeePJFhtdKCTMgquY2UmnCCReAYKesFVkSZUQYQXF0eKgSShJZ0bSKSEiqiTcOEq7WAq2ObGyTiCudu3SRF2XkqLuSTjlRW4yZRKSFQISlLUpuCSUhKVEmE8iRKRKgTKFA9XgjV4KKabNEUBCalq6JEJoU2BCEKAQhAQGyJQcpEwmgOEoJhLV4KKAQhCAQhCATSAQpsJCcJFZAhCEAgboQN0FgUFMKK2EhCFKPUuLmuACbtUSRHmosqtNQEq6vWpmnAIXXd2SSze07V4ByldVPW35ZWDWQSQ6Ei9xOTK1Me+06uy91QyeSBUzkqglSC2x3aRUOqVdSIJBAn7ljYd13OB07Z7JqESueeXTNuvDx3ky6VNtTc9wAC7ljwW4rtD6Ywsd5Ut7WuDTcCt/De0YoM0RgdF5eTPOzeMfR4eLgwyuPLRVq3Ni7u6rSANistS/FR4n3q3jPF6F5SMCDyXnnVvWwfpWePjuU3YnPzTHLWN3HpH3FLuidWYWSjcnvdLY3wuKbp0RqwtVhVgPuHZDBA8St/B0431HVW7jnEH16jaGomnRGkR15rjlx1TMpOeT59VBzxt0Xpwkxx1Hjytyy3VhqESZWeq8oc/GfYqKlTOM4TKpIbqnKVRWqSIQ5xiVmqvJdEyuVyUmtNR/hK0uho0jZRpM0M8SEjkqQRnKrquIEBScVVUMiEtFYqEHJVjK/KVRUwqyszKw06NKo1xh0EKm5a1pJYZCzNe4bFWteD8Yq3LZrQaZyDBW61va9Ld+oD9LKxAAkkEKRkMMqzKwshXVd9eu57jOVWDCAYSWN7AlKRKSoZSKUpeaaNDV4JykhXSmEAykhNCSFFBTQknKgMJypoSCkFWCnKImEwohMKCSYUAraNN9WoGMaXOJgAJrYlTY6o8MY0ucTAAXd4fYU7NgrVYNWPd5J2NpTsafeVM1SIJ+4KyXPdrf7B0Xp4+OY975Zyy34WyXEOPsCtBkLMXBNjzEyu0umNNQQD0VLXknzVgdCu9izkmQoNdsE3EAbqgDQh7ZAwgHkhxxCCAxkKROBhVk4BTmR4IGBIjmkR6yJwk4yYVQRMqJGlSkDkgZ3QRAHRBapg4UUECOiUKZPsSx1U0WowlCmkVNIrgc0tCmfEJA42hFQhKMypnOClEFFKEHZMIIwiKiEowrDzHRQ5KKUQowpnxSRPCOMyhMpYKiwpymUikiBxjcolLkol3goukiVHUkXKJKbXRhMmVAmEi4qKtDgk13VVz4ygHqiLtSi5w2VRck52VNiZISe8RAyqySVFx5oE92d4UNRPNJ+6jss1qRPUUaoUUnfFwVitGX5iVAuMJKBXO1YlqKYcVWEBQWTKUSogpyloJTk6YUNXgjXiCooOUgkE2kAyVFNSaRzUHGSSBCQOYUGgZKYOFU10K1mkmCYQBPJMGQkXAHGVAOl2yI6PCro297SqThrsr7ZwGnw+94O1ztLy5g8xK+DAwd16vs9xe5pWradKqQRiFjPjuc1Hu9F6qenytym5Xu6NzR4XeljTLfEyqu0HGre4aAz1n+GwyvP1La5qUjWeSSepynwuhSrPd3hkjkVqcOM+a16L6rlv8LGal/EV71r4HjldHhVQ1G6W7clxeMU2W1UBpBBU+F8RNu8TEeK658fVh8rzcXNePm1yV6epaN0F74k7p0HUaFMw5o+1cupxc1m6KQklZS+sH66kheeceXjJ9DL1PHLvBVx24e6s8gS2eS4lSp0JErrcQqMNIgkElcFx8V7+GfK+J6q7ztTL5Mk+CgXHkq3FBIMLs8yTneCWrqoOJmCo6pRdNFLU6Y96m15a+D9qqt62nCK1WXyACsXy1NabnXDNPmFW6vDDBGyyEODNUKtz8ZKz0xrqqZdJlXUKRqHG0rGXGVps64Y4By1l2nZnDVvdbXtntBMLOGHVErp169N1L4w2WBrQ8lwK5Y533d+Tjxl+U+4lshyofSc3K0ipowSiq9ujcKdVOjGxgdvndDjHtVxa1wJWd86tIW5ltxuOh4IJIMrTQa0D1wivSY7LYWepv4d1tnDpO8KYMbKpzSCiVMrtItJdyKnTrOpuDgVBhBChU3WW5ud3QbeOIyR7kxdEODgVgY0nqmSRusdMdpy5e71XBeMkAUXmGwtXFbZl3SNSm31okwvHUa2hwIK9f2dvKdW30VHCRjK8XLh8O9WL6Xp+b4k6c3l7ykaVTSRlZivVcfsW1KhfRyYzC83Xt6lNxDmkL08fLMo8fN6e4XcOk4bFRewkyAq2eqVuoFrhlW5aZxxmXascKTmNcycBaa1AOEtVFRlSm3ZXrLxa8slUaCinUIynUBcVUBB3XSV57jq9mg1AQqXAEyonCQdHNIl7+U20wecKzuBG6pD/FPviOaW0kk8tLbGq5stErLWpupOLXiCt1nxPQwscJ8Vmvqrazy5qzjllvVdM8OPp3je7LKUpHHOEnHC9DypSoPOVDVlEqw0m09EEwq9SWpSpYtEckSq2uMqbHCVDsUeKm1BIPNEhVUt01SXGVNrgSgbhiUkzJGyiQdwVNw0lMK2m4OVJY8tBhJpLRHNL3Wdl1VuDCqIIGVPvDzKPjGZUl15LPwbOFmmHNDo3XQurKlWGphz4LhEuYfVOVrtL+pTMOyFzzmXmPRxZ4SdOUW1uGVms1NzHJc6tTe1xDhsu/acSa71XAQsPFGse/XS2Uwzy3rJeXj49bwrknZRmFY9uSqnSBIXo28uktRUSZSJjKiXSqkiYCTsGFHVGyJkyRKbXUSag5CQiEZ6qbCI6JFSBUSoBLT4pocYQNQUZyhBMFJxUUIpyiUkICY6oJ8Skd0isiSRUS4dUnuxhXYlMJSolxKUlQMmCUavBJRlBMmQkTKQRCmzQQmhTa6IJoQoBCTtlEGEE1F3JKSgmUEm7JqAMJILEiYUZKSCWrwSJlJCbAhCFNgQhKVNhoQEKglCISUDQUkJsCEIUAgboQN0VYFEKQUFtAhCFB3xTOmZUSTsg1Tp3VTnZXed2LpYgFRBnYYSaYWkqzUpAqCCh4WNJV1KtUaIa6FmBwptKlN/g0Gq92S4oFRwO5VU9ElnUal21d8Y3VReSZVeo9Ui6EkW3aZdAXQa7TaU2bSNRXMp/jazafUgLfVfLieieaTtFVV5GcKk1B5p1nAA55rOXgHCmVE3uVbnTOVEuycqt74MLnbtdCo+BEqFu3U7UeSqeZdutNOGs9iz5om53JVzlBKi/aVTSBUCYTcYVRMlRNIu3UCIKmUisqjEJjCEKVaclS1EqAQiUykUSkqkCgTKerwSVUSmcJIQNCSFdhoSCJTYaESiUAhCFQoTGEIU0GFIKCYMmERbSY57wxokleg4dRpWdE1HQanVc2wptptDz8Yj3Ban1NcQcBdMJJ3SzbYKneeu7fkEi+FRTd1whz/FdOpNLNfRSa+CIVGo8kw6CkppsDiTP2K0P8VjY8cyrdeN1qVNNLXjmUF4WcnoYS1RutbTTVrCNXUrKHmMFS1FXqNLfzky/GkKoPHJM5G5U2aTmUAxyVeqMIJ8VdiZdlOcxhUlx6o1JtF09E52VIdylS1+Ku00nKUqGpBKbXSckpalAOPNMkJs0aW6UoBBMoh81FBMlCijdDkgk7PJBEkk5SQSkSEDSzGUiYUS6eaho3FEJakpQBPVJRLhCiCpsTInmoSglQJgwVKpygkKJKi45TYkolKUKIkFEpSEtSi6SUSglCGgqypa+qiSEXWiSQVAuClqmkDKRcEliqCVFxUiCk5YrUQKSZSKyJEwkTKSFAFIJlRJUVIqJKEQgAhCFBIHCsBhVBSB8EVaDKjPrSoolBe1zSBPtXR4LW0XAE+IXJaVfbuLKjSORVlH0McZpeiaTpBhcZt66lVc5hiTMLntqCJGQUEzOYXrw4pracnqM89bvhrurp9Z2qoZ6KkVPEqgk7FC6zGRxuVtdTht42lVGordf8Ra6ngjbZeeZhwUnvMlcsuKZZbd8PUZY4XCLa1wajjJPvWdxlRc4SoudK6yacbd3dMnOFGT1SlKUZSJMqMpagmSBzTYCSBhDXEOGZUHROFFS1ZGzv/wAXCzPdJKrkjmj2rHhraQJ6lKTMqBKJV2i0OdPNTbXewrO4kCQUSeZWNRZuLn13OO5SdWeREmFnLo2TDjCai7rQyqQ2E6L/AMb60LNJ6oD3ALNjWOWnQuKjA2WnKzsqvcYWZ1QxlW2zwHetssa1G7n11c/4qqcSAtlY0u6JbushLdM81mVvPDpRa8hJzy525UqTdboV9O31OAGZS5SJjx3JGhV0jKVdx3Wi4sK9Ngd3ZAWRzXAQZWZZa6XGyapSujw2rWYZYSuWTAXT4RcU2EB+Vnk7xvh7Zd3btL55fFU48VpvqdGtQ1ACVy7h1I5Y6FJl5ppaS6V5On3j6M5JZqsdeycHEtVYZVYuraXNOo4h0Z5J1+5BgBb+JfFcvh43vHOp1HTDlrdTbUpRzVNWmJ1MIU6L3DCW+7WM9qwV7VzH4G6odSMrtVNJ5KnumOIwtzlsjleGbco0iQqH0yDldivRb+aFgummYAXTHk2458MjJpxlQIMq/Q7oqy0giQunU4XBU5rpmCpMBJhy26qRpbCVge/TUTq2zlhMU6jBGFS4EbqwVJKl6pMqzKxLjL4ZXYKR2V1Rg3VRELpMtuVmkCkCJTIkqMwtM6TJwhpISYpwFNroAlSDSRKiIlWBS3SyKyEMwpVBKirMtxK0MOEPHNUgyp0+hWG41Wxa4aSlcUAAXBUNJpuwVpZVFRsFYtsu3WdNmqxhDXRKvqMDgYEFZ3NLd10mTjcdGSXDKrfKZcoPdlaxS1bRqObGVcLicErGTCA6OSWEtjVUOr2qp4wQod4mXmEiVEjCipFCu0RKSlAUYgkJs0EkSjKBpJk4jqlKAhJ3JOVFxBV2IoQkU2olBQdkpU2BCJUH7qCahq8FGUSgaEjskEDKAmhTa6RIQmUgkEkIQsgQhRdyQD94SJlJCAQhCATBhJCAQmd0lNghEIQgAhCEAhCECTQEFQCCkhNgQhCgEIQihCEirpTKUpIQXDZQTHxklpkIQhQddplDuWQosUpXdz0DgDKbROVEhSGBCbVZjqpNaCYVKtpEAglS3ssk91tSiWNkKsHMK+rWa9mkLO/JUxtvlrPHGXsnMJSoEpSqymDlDioAg7JEoNNlAe6p+iMKyrWB2KpLu6oNGJdkqlz5Tq1BOpUHMyqHv5CFCoYJyq58Vxt20uD4Cqc5KVFziQpSJMy9WOeTIBVTcZQTKi1PPVMklVg5Sk8kRJ4xKqlSLlEopBCCkVFRKE0FQEJIUXnKRmpKBMpJrWgIQhAIQhAIQhAIQhAIQhAIQhASnKSFdhqdATUCrWi1G7k2NbXGFY10BZwYUgRG61KNTXTnKZdJ8lQ1x6qQdIIJVTSzWepQKgEZlVmTzUcdVdw01CoFMVYWRphS1K9SNbahTFRZRVgJa/FOoaRUKsDzCxh07FWg4mVeo00aiRMqYqECFmD8AJ94BvsnUVa5/Uwo954qt7wdjCir1Gl3eeXuRrCpJUZhXqSxpa/MqRcCZlZg9MVIV6k006yiQd8KjvE9avUml4f0CesLPqTDwmzS4vlLUqdQSdUA2KbXS8PPNGsKg1AOaA7xTaaXa0a1TqQXJ1LpYXSo6uqiSCoF3gps0s1SlIKqLlE1ORTaaWl0clGR1UC+dyo6lNrpZICiXDqoEqMhNrpZqUS5QLgEtXRTZpLV1S1dVAlRJU2dKcpSD4KEphS1ZE5hEyoyprPUukRhInwUiQoGJ3TqNIk+aRPmgjxShTrXRZKUKYCFLlTSEJqMoB3U6qJE5lQOUiYQDKyE5IE8lJ3JREdZQSOWyVEkKR8Sq4MopykUQeaSyaMJqITlAFCAhFCkooTSJyiVBMIqU4U6RIcqwVJpQduzqa6BHMK1pCwcNqaHEE4IWsuE7r28GW8XHOd0ycokdVUXFDSZyurEXEpP2UZ6kJOcstWIpqOoI1hNmichpwoFKVNmklElBUJhS1fCcpY5FQlGpTapyesqBMqOrqUtXgps0kglRCZGQmxKcQkUkneaih3JRmAniDlVv6IJ6/FIvKhKRMIqUlSa5V6gkXhS9ydlpqukiUd6eZVCJys6i7rXTrFuyvZeOa4OHJYNSkDlc7jHXHOx6a247NDuHtxEZCy1zTqOloGVxpgrbYPL3aSuNw13j1TkuXlrdw8mlrDZCpbb6ASJBXbt6lSjQ9ZsgDC5V7dhzyQI8gsTO+HS4YzuxPe9joDj71IXFT9JUVXa3yDsVEkhdJI4XKyttCq5pkEyr33NQtyTsuax5aRlXmpqapcZa6459l7Lp4OXGFrt7kSJK5M+KA9zTus3Bqctnl6CpUa5shUtqmVz6FdxEEq5r+i59OnWZStLq4Jlypq6ahwoVCq2vIdKSFy9lugNGQqKgbBIAU6lSRhUFxW8duecl8KKpIODCzkHcrRW3VLhAXaV4853VqQcRzUUitOaZeTuou281EFBM81YhY6KHNTKIV2zpEGD0U9UjKi4eKQVEwZKm04VQIByphSqkcoDAE0pTZpKByKQ3SBSJUXSwoDo2UJS2VFmvMSrJDhBWRzs4SZWcDkppJV9VsCQszsFaNYIVFQZVxpnJ7IE9EDKSGuhblYShKUi5RlLUTDjKNShKJU2q1rgguBVQKcq7E5RKhKJTYmShQlNS0TAVZGVLV4KJWVIoSKi58clqJQThR1eCHOUZVDJlKU0glAhNCwoQhCACk0SYUQp0/jKZXTWM3TcwBVlWVSFWmPgs1UdXgkTKSFWQhCEAhCE2BG6EKAQmiECQhCAQhEqARKRQmw5SQhQCEIQCEIRdBCEpTRo0iiUlVCEIUAhCEFhSTKS2yEIQoOmFIGFBAXdFkpqVOi54kAwoua5sBZ6otlk2FMYVYVirJz4IlRJjnCRIjf6ETRyESFCUk2uk5Sblwb1KTiil8bUfzRKyLLt+qpAHqtwFQXGYQ4kiearlZtXRuM5Vcy5BdCiCsNJSjcpTlOVA0IcokohykUkjsi6MpFIpKbIcpFCRRQU0ikoJKDjlSCgTlWJTQlKAtIaEIVAhCFAiiU0JoCEJQmg0JFEqBoQhAIQhALRTw0BZ1cFKq0FSaqw6EwYV2aXNwpBwCpa481IOHVNi3UlLVCR0UGkzlNi8OQXKsFEoi2ZQDB3VUlSlWUWagrA+Qss5UmugzK3saO8R3g5qjUCjUg0Ekph8GFU1+Ey/omzS0uBSmQqySITaQBjdXcTSQB6pyVHVCNQOxV37icpyqtfsTLhCJpZqSLlSnkbFVdLXPS1KpKUF+sJFxVMplybRaXEo1zsqZJSlTZpeKnVLX4qrKYS1dJuJKgBKZMeCRI81NroEEc1EmCp6lHG6nUETlIyU8SlAU6jSKFJIiU2aRQpQOiiInCnUCESJ3RISJBTYk1wHgm5w5KomEyYUtEicqKgSkXEqbNG4yguUZUZRUg7wTLuihKSgmcpEqKUqCRMpKKAmw4UoVc5RJKbFpjqgAdQqJKZMpsXkA/nD3o7tp5j3qgITYtNL+sPeoOaQowgmFA0JSgoJSiVBMIqUoKiU0DlMGFFCqNdq8hwkrpagWjK49Ew5dSk7UwLtwXVsZziYKQdCjySC9W3PS4O8FBx8FEuylqWLVTkndRJHIyoykTlSnlNnrbqD8GENeAVB7hqKm18RIugZUdXglKSbDlRLkalEnKLpKZQSoF0JF3VNGk5QXSqyUOdClVb3nQKJKq1eCCVkWEyoudAyimTzUKrpcpvuaKSEtSUoTYZOEpSJlJNmkpQopyoqxMlVtO6lKiptfJ6rRa1dDw4HmskpscQs2SxvHOx7GwvKVxQDS4AxsVzbu1l7oGCVx6Vd9N2ppK30+IE4cV5rhcb2eyckyndF1vCzVAWEhdFr2vG+6quaYIJhWZXfdLjLOzBq6qbXmFW8aakJTC6MeGlhwk4+so03YUnckE6T4ct1IBwwVzVrsKpDgCueTeGWq01gQFmc2Oq6tRrKrMDMLI+nGFiZOzIVAmFZUaQSQoBs7re2b3VkzyVTxhbKdHWFCpTLNwrMnPLFhcISIlaHtEKtzcYW5k4XBncCCoy7qpukFAAjK3K53FAmTKmDukWhQKu00sJnCik3BUpVQjuE5UHThKSESL6cuUnU3ATGFVSfpfk4W5tSm9kc1i2zw7YY45TuxkwhpmVKq0hxjZQJjktSsZSwyUSFHHNJ/RVkOyVEtAUpQIPNUDTGEawEaZyEjgwgI1clFzI2U6cDnKKmQmzTPIG6kk8ZSVrJ6kSkQoz0KsRMlLUo6h1QDKuhLUUalXJVrWEhS3QgTHX3qUlRLCN1FO1FklEmFBgBmVIgdFLZFCgTJTMTCgrtDhBUkiptSwlEplBMJtTgFAAQhRCSnwQ7koq7E2lOTyUAYRJU0pucTg5UUzkpIgQmkmwIQhQNJCEAhCCgEJSiVNhyiUkKbAUIQgEIQgEIQihCEpV0ppFEpIHKSEKbAhCEAhCEAhCEFhSTKS2yEIQoN4dBT1JIk9V1Z2329fTT0jdRqNe/wBaFkovLH6jstvptMUy1rclc7NV3xylmsqyzk+CepVFxmQjV4LbitJScVAOS1TyVE9UJSoIQWSntSceuFAGVKqYa1vtUog84VbnEBN5yqyZK5WqCiUpQoqRQoyiUDJlJJKUEpSSlJSqkkUkKBlJCEAhIiU0AoJuMpKxKEIQqgQhCByiUkIGmooV2JISlEpsNCEKgQhCgRQmhNAburFW3dWBZvlYkFIKATRUwgqMolNiclJJOVQ5KJKUpEoJtdG+VMHCqlE+KC6USqpPVEnqiaXNPgnq8FSHdU9QV2aWF0ID/cq9QTDh1TqTSzUOSYf1VU+MJp1C3WIjKA4hVyiU6hbKJVWoo1FXqFmpMOM5yqw4plwIV6k2tJnZRJ8FWHlIkptU5SUQT1QXkKbE/Yn7Cqy4lLX4qdQtmFEkjZQLiEa/FNiYd1TkKrUOqC6OabFznZSnCqLpOCjUOqmxZqUS6OagXBJxBRVk9EaupVUpT4oaTLiEwfBVSnMbIaTc7CiCokpSipucUplRlIqbRIyUpSSlFNKUiUSgOaJSJSlS0MoKihQSlIpIQMpGeSEtXggaEgESlZNCCYQihCAZSJhA0ISkIpoSkI1IGhRLk25TQkESq1JvNUWMMFb7apiFzhharZy1hdZJfDcXCFEkk4MKvUSEtRXq25aWkylKr1ILlFT1eCQJ5KOrwSJlF0lzlLUifBQJlDSWpLUoF0KOrwU3pVkqBOVEOQX+xNiUokKAzzSCm0SlIpTCRcMJ2EtkDJU2AEKJOl0LNya0taAGrPVPrFTfUwqyZWVpKKcqM+CIkEEpIQAQTlBlKCgcqWrwUdkKCRKaghFi0OHNMPnZVlAKzW5lY2W9w5jskrd37Xthchh2KtFQtMgrncd13xzbalMPzCpNI9Vbb12kQVaQ1xkFZ3Y6dqzNGlMGVc6moaYVlZ0BkIYS12FJrMq7u2lsKXJqRss7iWaXFaS1rmyDK5LQ6mcLQy4xg5XGzu3td6O0uifpVdWiBMKPeuInmmastzyVhKlbnQ4TsnftFVmpoys1SoYwrbSuCdL0Tbn1Q5m4UJ1BdLiLGHLSuU7BPNdcbuMZTSL4hVqTgoLpHK+UyoEDqUKJwrtiwufNBKk1oOwSe2BMK7ZsqJQhCsZCk15G0qBTBQXsqmIcolwVIcgkkQppq52riPFQdgwpU3EYKVUgyQcpsurFZKA4hEyktMrGPMp1TJCg3MKWIGFK1rcRGDKkXSFF4hIiE2yCoKSiQrtEXbc1FWFphVlalZoQhLmrsWN2U2vDVSNoQZ5ZWdNLXVAcKohACab0hAkbKQKRSKAlCRMJavBBIIKjq8EavBBJCjq8FJAIUHbpIJkwoIQgEIRugEIQoGkhCAQhCAQkhTYZSQhQCEIQCEIQCEIRQhCFdKEJFJAwkhCgEIQgEIQgEIQgEIQgEIQgsKSCYKFpkIQhBtnwRqCggrfVU0nq8ESFCYQnUaTlOFAJh0KyhnCbIJghRcZCGugypaRa6k/cDCgMLZa3bWNIcJxjCzVD3ji6AM7LEyrpcZ7BokgIrO/Gx0CnQ/nR4ZVFR0veepWvZhW85UUTJKQXNYaCkUSigmEFEqDuiIkhQQipavBGrwUShQSlImUSkoBCClKBoShBVDQkE0gEIQqaCEIRNBCEIaCEIQCEIRAgoQgAnKSEEkKKArsSbupBRamsXy1EgpBQCamxMIUQU5QNOFBSTdAU5SKCmw5RKghUTlNQlEqiQTCiE5QOUEpAolQSkndSkKvUgFEWSEiYUCfBBKonKmHKmUFyou1DmgOHVUynKGluodUtQVcoJQ0s1jklqMQFAFBQ0nqPMpNIBkqEolFWFwIhRlRlIlBKUKEoKgmkVBCgmSiVBEqiRKNSjKUoJSiUpSQSlIlJCgZKJUZSQTJUZSS1eCncSlAUfjIJhNCRSSDkThA0KJIOyC7wTQZMJEQkkclUShBSGU4RDkcso1DxSgdEQhsgjUmRKIQIZCEygopIQVFBJARunCGyKUpgpSgYQkUBA1ot3Q5Zwp0jBVG/VJQSoNPqhEr0y9nP3SlLUFFIuTZtPUE5VcoS0WSo6vBQ1EJFyyqRKUJalGcEK9kSkJEqKCs7U1OmJKqlTpH1lKsSqN2yoq0FpBbvhVOkDCztqw2OIEBBPVQ1exN8QIRCfuomeRRKSbQFCRKabCKJQeiSBkwiUihA5RKjKJQSlOYUJ8EwU0qcymFWmDClVbOESoBEws6a2va4t2KuZXPUrJrBUmu3WbHTHLTpUq4durxDhK5Id0kK+lXLTus6dJk6DhAUdfiqW12ndWthwkLLUpiqCYKsdTBEgrLUEGQmys8CJUuJ1NNM6TspVhLTGFmNUzMp+kciVLjV6kXujBVXeEOlphFao0qlrpOVvGdktbHVTUpGTlZXgoa+DhWOhw1DKaTe1cSFQ4ZV5EKsrUZsUHdTah4ESFALUY7rW7yrHQW5VIdKZdLYUVAAEkKelVgwVZMhWsyIFsmZUS0qRxhAIO+Fds6QOEKTgIJAVfNWM2JieqRKjMIlVE5SKkNJCTiDsougDBUg/wAFXKDIVN1Iu1GVJjQRlUynqKC7QAZlRcANioFxO6Smi1J2QqypTChurEsCCnCITbKMIlM4SV2CUFCFQtkSFEmUkDdukhAKAQgoQPHVJCFNgQhCbAhCEAhCEAhEolQEolJCmwFCEIBCEIBCEIoQhIoaNCUolVRKCkhQCEITYEIQgEIQgEIQgEIQgEIQgEIQgEIQgmhCFpkIQhBoQrHMAKgRB3SVqzRJyoPMFKStM7WSiVXq8E3EqoslEqCFFSKkCqwmCQcKUaqRApVHzs2PesxPqk+KueYsz/Wcsrz6iXwqM+CkoJgkbLCpIUSZSKIlMJHqkhFCEIQCCgpFSglEpIUAmkhAygJIQCEIVgYRKSFRJCihBJCinKBoSlMIBCEIBCEImghCENBCEIaSamoFKVlVoRKgHJhymhIKUqCEEk9lBCCcolVgymgnKJUZQqiUolRlEoqUolJIIJSmooRNpSkkEFFSCAlKJVDlBUUSgkSglRCCglKJUSlKbFgSlQlOU2GiVGUSmxKUpUU5QSCSRSLoUEkKAMpoJJTmEgUttygkUFRz1R8ZBIJF0IJhQLp5IJoSLggORDSccQlqnZE+tKKkk3moOIJwkgsBlRJkqKEE3JJFAQSKRCWyAgaJlRUo8UDIS1eCSNkTR6vBImUkIoQmkgYEoAlASQOEQkhA5QTKSEDCSEIBCEIGExuEgmNwVRqYZaFJU03YhTldcb2YqZMKJKiUK2ocpyoSiUVIlIlKUlNmkpSlRkpOJhXVEpSKgm0kHCUSU6cDMpQNBndQBhZ32X3aHua34qgXS1QJUmEaSCsNIFE4hBKUqoeeQRCiSUCoYQiZUy9sQs+opEyoqVTBJQoyglWUqSFEFGrwWtpoyJTUdXgjV4IaSUdPijV4I1eCAcpN5qMyhZqrQUOOFWDCJUUwVa3ZUAq5jhAUrUSJgqQMqpxPVDXQs1ZkvDiOZV9G4Ld1kDgeavphpE7rNdJdtzHCo3JAVVQEbLKahY7BKvbWDxlIuy7wpF3RJ7ZyFUTB2V0qzVO6gTCgSUiVGdp6ip0qpBg7KlImEHQIa9u6yPMOhRbUcNik52pVdmColAQROUjNSaB5oJ8FFroEIRPAKbCAMphstmFFwIWi9k9IJwk5sCVWKjWneEzUHNTVJlNAzGFWcFWh4UYDtlqMWbQKRUy0BRdE7KysXsQcphwJVaFdEq6W8kzBGAqZKYdCzY1Mg/BUVZAKjpjmrKmiAUwDCrMSrAfVCWkQJhIbocZMIRDJhJzoQFEZ3SJo5kRASUoUSY8VrcAcBRJlMnBwkCm0JCEJsNJCEAhCUqBoSlEpsNCUolNhyiUkKByiUkJsCEIQCEIQCEIRYEJFEqro0iiUSgJQUkIBCEKAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCCaaEFaZASQhBpDyolygShNLvZmDzUZTQtTsmggoQE2aATSlMKARySlSaJMKCdV80WM6ZVTk6hjCVSBEdErUIiEkIWUCEJSimhKUSgaRSQgEIKJU0BCJQE0BCJRKAQhEqAQhCsAhCFQIQhAIQhAIQhAJpIRNBOUkIHKJSQgkEKKENmUboKSyqQUUJhABMGEBIoJB3gpKAyYTaYQSQlITUC1eCCYQBCHKhphR1eCaAQkDKaAQhCbTZyg4SQmwyiUktvFBKUkJT4IpphVoQTmEgZSmOSCIQTCSgpByBoGQoKUwEDQlIQ5QPmo/GTdyUSqGDCDlKQCCnqHRA2iE5VcpknmgbRncIJBGcKJMmUkEplEYlIIQG6ZSlAQOYhIpJoEmkhAIQhAIQhAwUkIQMpIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQqLKZzCsVLd1at41mmiUkpWtpo0iYAUYTOUDaUnE6tz70oPRMYVt0Qj5ym3CUprO10colJCgclJBKiTCaVJGojZQnwQlEgZMqTlWHEbJlxO5WVBSSCaBFJM7owgSEIKBonwUUIiU+CJ8FFCGkpQooQ0aEkIppykhBIIBjkooQSBTlQQi7TBhXU6paIWfPREnoppZbO69z5dKGVCDgqicqTXCcKdK9VbmVpACb2hw9VYtUFX0quVNadMal3ZUjRcBKDUBMwmavgpWtqSC0wUlNxDki2E3pm1EIKFFWd0t9zlLV1Qk7ITTO6nqCTndFU340KRVs7p1Va2rAhJ75aYWc7qQ2V1ouV0RUkKCrCZ2UmPA3VSEWXSx7yRhNrsZVRwlKaNrXN1ZBSUWuIBS1JtKmMmEy0t3VbXQdlY58iNkWAOymKjdMKmUE+CEqwxyKRIHOFXq8EIVKUAwVFCIslImN1EGEnElFSaZ3Kk5mJUG7KRfIhBWmkd0yqzQhJCbQIQhQCEIQCEIQCEIRQhCENBCEiho0KKEVJCihAJlJCuwIQhQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQWFJMpLTIQhCCaajq8EByoknyCSRJCKlISSScoHKJSCEUwpMOVBMGFKgJklKZUUwopoKRSQCEIQCCiUigChCEAhCEAhCEAhCEAhCEAhCEAgIQgcoCSEDQknKAQiUIBCEIBCEIBCEIBCEIBCELIEIQgcpIQgYQEkIGUkJoHJO6NXgooQSmHSpSq0ILCUThVoTQsn1oRPTKhOCEA5lBMGU1XKYTQlISmUggIBBcTthIICBoSCCgYdHJKUFJBKZQopoHMJSgJIGEBJMFAFJCEAmkhAIQhAJpIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIlAIRKAqGFZuqlNpwtY3ulSQiUiVpDkJagkUiVNqkCg5UZSBhDQT1eCSFdoerwSJlIJqbi6CRRKRUtWHKJSQoHKUoQgAmUkFAIQhA9XgkhCAQhCAQhCAQhCAQhCACYEHcJIRQUBCAiHKJSKEDlEpIQPdNuFFAQSgdU29QVBCmmt1cxx1ZK0ghw2WEGFMVD1Us2u2lwM4Rnmqm1c5yrpDxCxoRkSoPMuTqNhVE+xWTa27SbA5oVc+Kc+K1oOI5pEkpT4oVkS0DCCkTCJwqzTSlBSRAhCCgaSJRKuwIRKJUAgolIoHKJSQgcolJCAlCEIBCEIBCEBAIQhAIQhECEpRKBoSlEoaBRKCkinKJSQgEIQgEIQgEIQgEykhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhBNCaS0yEIKJUD2QlJRJTa6CaUyglXZpLV4IJUJUimwk4SQp2U5RKSFAIQkUDQiUSgCkhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCATlJCBygJIQNCSEDQiUKbAhCFAIQhAIQhAIQhAIQhAIQhAygpIQNJCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCEAhCCgEICEAhCEAhCAgEIQgEIQgEIRKAQiUiqGhIoTQaCkhNBykUIV0AoQhAIQhAIQhAKQ2UUwkEkFRQtBlKUBCgEIRKARKSEAhCFAIQhAIQhAIQkEDQkU0AopkpIHKaihAygJIQOUSkhA5RKSEDlASQgkhRQgkhCEAhCEAhIoCLs0ISCIaEIQ2EIQgJKnTeQVBCLtoLw8QoEaVXJ5KTXE7rOl2AoKflzUSFdlAwpavBQlEqokcpJSiUDQlKcomgkUShAIQhAIQhAIQhAIQhAIQhAIQhAIQhECAlKJRTSKSEDlEpIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQWJIQtMgpJlIqUCEIUXYQhCGwhCEUJykhA5SKEIBCEIBCEIBCRRKBoUUIHKJSQgZQEkIGEkIQCcpIQOUSkhA5QUkygaEgkgkhKUBA0IQgEIQgEIQgEIQgEIQgE5SQmg5QkhTQaEkSgaEShQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCAiUigZRKSFQ5RKSE0HKRQhNAQhCugJykhNAKEIQCEt0SgaEpRKBoSlJBJCihA5RKSEDlBSQgZSQhA5SQhAwmFFMIJFCAUjugcpFCEAhCEAhCUoGhIoCAKJQUkDlNRQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgYTUUIJIUUIJIUUIJISCaBFNIpIJIUVJApQE0IBCEIG0qwEEwqkBSxU3NhIgptITcQoKyCN0KZEpQFdiKEEQhVQhCEQIQhECEIQCEIQCEIQCimU0EUIQgEJhBQJCEIJKKZ2SQCYSQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgEIQgmhCFpkIKEKCJRKCko0colJCByiUkIJIUUIHKaQQd0BKAkhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAIQhAJykhA5TUUwgaFFMIGhIJoBCEigaEIQCEimgEIQgE5SQpoOUJITQaEk5QCEShQCEIQCEIQCEIQCEIQCEIlAIRKJQCEbpKhpFCEAEykEBQMIlJAVDQUggoHKAkhA0BJCBhKUITQcolJCaAUShCugISKCgaEpQUDQkEBABASQgcolJCAQhCAQhCAQhCBlJCEAhCEAhCEAhCEAhCEAhCEAhCEAmEkIJIQlKBpFBSQOUkIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEJwgAU1FOUDQlKJQNCRRKBqQKgFIIuzlJxyhI7qGzlIxylCRVDQhCKEIQjIQhCKEIQgEIQgEIQhsgmooRDKAkmECQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCAQhCCaEIWmQhCEHVdZW3yf1il6HbfJ/WKELLQ9Dtvk/rFHodt8n9YoQgPQ7b5P6xR6HbfJ/WKEID0O2+T+sUeh23yf1ihCBtsrb5P6xQ6ztp/m/rFCEGC/pMpVQ2m2BHVZkIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCEIQCYQhAFBQhAkwhCBoQhAIQhAIQhAIQhAIQhAwgIQsgQhCAQhCAQhCAQhCBJlCECQhCsAhCEoEIQkAhCEAhCFQIQhAIQhAIQhAIQhAJShCBIQhAwkhCAQhCAQhCAQhCAQhCATG6EINtChSc0FzJ9pWptlbH+j+sUIQP0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgfoVt8l9YpehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sU/Qrb5L6xQhAvQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCB+hW3yX1il6Fa/JfWKEID0K1+S+sU/Qrb5L6xQhAehW3yX1ij0K2+S+sUIQHoVt8l9Yo9CtvkvrFCEDbY2p/ovrFDrG1H9F9YoQi0vQrb5L6xR6FbfJfWKEIg9CtvkvrFHoVt8l9YoQh7GLG1MzS+sUvQrb5L6xQhCD0K2+S+sUehW3yX1ihCNG2xtfkvrH96foNr8l9Y/vQhGUPQrX5L6xR6Fa/JfWKEID0K1+S+sVJtja/JfWP70IQR9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgPQrX5L6xR6Fa/JfWKEID0K1+S+sUehWvyX1ihCA9CtfkvrFHoVr8l9YoQgn6Da/JfWP71L0G1+S+sf3oQtJR6Da/JfWP70eg2vyX1j+9CER//9k=');
	background-size: cover;
	background-position: center 30%;
	filter: blur(2px) brightness(0.82) saturate(1.2);
	pointer-events: none;
	}
	/* Vignette — edges only, keep the astronaut visible */
	body::after {
	content: '';
	position: fixed;
	inset: 0;
	z-index: -1;
	background:
	radial-gradient(ellipse 120% 100% at 50% 40%, transparent 40%, rgba(2,4,10,0.70) 100%),
	linear-gradient(180deg, rgba(2,4,10,0.50) 0%, transparent 12%, transparent 88%, rgba(2,4,10,0.60) 100%);
	pointer-events: none;
	}

	/* ── 1. Design Tokens — refined ──────────────────────────────────────────── */
	:root {
	--panel-r: 16px;
	--elem-r: 10px;
	--pill-r: 100px;
	--nav-h: 64px;

	/* Tighter, more purposeful aurora */
	--aurora-1: rgba(0, 200, 255, 0.22);
	--aurora-2: rgba(160, 80, 255, 0.20);
	--aurora-3: rgba(0, 223, 138, 0.12);

	/* Glass surfaces — multi-layer depth */
	--glass-bg: rgba(0, 12, 30, 0.55);
	--glass-border: rgba(255, 255, 255, 0.09);
	--glass-sheen: rgba(255, 255, 255, 0.05);

	/* Accent — pulled from QUASAR blue theme */
	--cyan-accent: #00d4ff;
	--cyan-accent-glow: rgba(0, 212, 255, 0.45);

	--sp-xs: 6px;
	--sp-sm: 12px;
	--sp-md: 18px;
	--sp-lg: 24px;
	--sp-xl: 32px;
	}

	/* ── 2. Typography — micro-polish ────────────────────────────────────────── */
	html {
	font-size: 13px;
	-moz-osx-font-smoothing: grayscale;
	text-rendering: optimizeLegibility;
	}

	/* ── 3. Nav — refined, thinner, sharper ──────────────────────────────────── */
	#nav {
	height: var(--nav-h) !important;
	background: rgba(0, 8, 20, 0.75) !important;
	backdrop-filter: blur(48px) saturate(180%) !important;
	-webkit-backdrop-filter: blur(48px) saturate(180%) !important;
	border-bottom: 1px solid rgba(255, 255, 255, 0.07) !important;
	box-shadow: 0 1px 0 rgba(255,255,255,0.04),
	0 8px 32px rgba(0,0,0,0.4) !important;
	}

	#nav-logo-mark {
	background: linear-gradient(180deg, var(--cyan-accent) 0%, var(--cyan) 100%) !important;
	box-shadow: 0 0 18px var(--cyan-accent-glow) !important;
	}

	#nav-logo-text {
	font-size: 0.85rem !important;
	letter-spacing: 0.32em !important;
	font-weight: 900 !important;
	}
	#nav-logo-text em { color: var(--cyan-accent) !important; text-shadow: 0 0 16px var(--cyan-accent-glow) !important; }

	.nav-tab {
	font-size: 0.68rem !important;
	letter-spacing: 0.14em !important;
	font-weight: 700 !important;
	}
	.nav-tab.active { color: var(--cyan-accent) !important; text-shadow: 0 0 14px var(--cyan-accent-glow) !important; }
	.nav-tab.active::after { background: var(--cyan-accent) !important; box-shadow: 0 -2px 12px var(--cyan-accent-glow) !important; }

	/* Live pill */
	#live-pill {
	background: rgba(0,0,0,0.45) !important;
	border: 1px solid rgba(255,255,255,0.08) !important;
	border-radius: var(--pill-r) !important;
	}
	.pring.live .core { background: var(--green) !important; }

	/* Search */
	#search-input {
	background: rgba(255,255,255,0.04) !important;
	border: 1px solid rgba(255,255,255,0.08) !important;
	border-radius: var(--pill-r) !important;
	font-size: 0.72rem !important;
	}
	#search-input:focus {
	background: rgba(0,180,255,0.06) !important;
	border-color: var(--cyan-accent) !important;
	box-shadow: 0 0 0 3px rgba(0,180,255,0.12) !important;
	}

	/* ── 4. Glass Panels — depth-layered ─────────────────────────────────────── */
	.panel {
	background:
	linear-gradient(160deg,
	rgba(255,255,255,0.045) 0%,
	rgba(255,255,255,0.010) 50%,
	rgba(0,0,0,0.10) 100%),
	var(--glass-bg) !important;
	backdrop-filter: blur(32px) saturate(160%) !important;
	-webkit-backdrop-filter: blur(32px) saturate(160%) !important;
	border: 1px solid var(--glass-border) !important;
	border-radius: var(--panel-r) !important;
	box-shadow:
	0 1px 0 rgba(255,255,255,0.08) inset, /* top sheen */
	0 -1px 0 rgba(0,0,0,0.3) inset, /* bottom inner shadow */
	0 20px 60px rgba(0,0,0,0.45), /* drop shadow */
	0 4px 16px rgba(0,0,0,0.3) !important; /* near shadow */
	transition: border-color 0.3s ease, box-shadow 0.3s ease, transform 0.3s ease !important;
	}
	.panel:hover {
	border-color: rgba(0,212,255,0.22) !important;
	box-shadow:
	0 1px 0 rgba(255,255,255,0.10) inset,
	0 -1px 0 rgba(0,0,0,0.3) inset,
	0 24px 70px rgba(0,0,0,0.55),
	0 0 0 1px rgba(0,180,255,0.08),
	0 8px 32px rgba(0,180,255,0.08) !important;
	transform: translateY(-1px) !important;
	}

	/* Panel header */
	.panel-hd {
	padding: 14px var(--sp-lg) !important;
	background: rgba(0,0,0,0.18) !important;
	border-bottom: 1px solid rgba(255,255,255,0.05) !important;
	}
	.panel-hd-pip {
	width: 3px !important;
	height: 14px !important;
	}
	.panel-hd-label {
	font-size: 0.62rem !important;
	letter-spacing: 0.22em !important;
	font-weight: 800 !important;
	color: rgba(220,235,245,0.9) !important;
	}
	.panel-hd-meta {
	font-size: 0.62rem !important;
	color: rgba(79,114,134,0.8) !important;
	}

	/* ── 5. KPI Cards ─────────────────────────────────────────────────────────── */
	#kpi-row {
	display: grid !important;
	grid-template-columns: repeat(4, 1fr) !important;
	gap: var(--sp-md) !important;
	}

	.kpi {
	padding: 28px var(--sp-lg) 24px !important;
	position: relative;
	overflow: hidden;
	}

	/* Ambient glow spot top-right corner */
	.kpi::after {
	content: '';
	position: absolute;
	top: -20px; right: -20px;
	width: 80px; height: 80px;
	border-radius: 50%;
	background: radial-gradient(circle, rgba(0,180,255,0.12) 0%, transparent 70%);
	pointer-events: none;
	}
	#kpi-score-card::after { background: radial-gradient(circle, rgba(232,114,10,0.14) 0%, transparent 70%); }
	#kpi-acc-card::after { background: radial-gradient(circle, rgba(0,200,255,0.10) 0%, transparent 70%); }
	#kpi-upd-card::after { background: radial-gradient(circle, rgba(255,170,0,0.08) 0%, transparent 70%); }
	#kpi-spaces-card::after { background: radial-gradient(circle, rgba(168,85,247,0.16) 0%, transparent 70%); }

	.kpi::before {
	width: 3px !important;
	background: linear-gradient(180deg, var(--cyan-accent) 0%, transparent 100%) !important;
	opacity: 0.35 !important;
	}
	#kpi-score-card::before { background: linear-gradient(180deg, #E8720A 0%, transparent 100%) !important; }
	#kpi-acc-card::before { background: linear-gradient(180deg, var(--cyan) 0%, transparent 100%) !important; }
	#kpi-upd-card::before { background: linear-gradient(180deg, var(--t3) 0%, transparent 100%) !important; }
	#kpi-spaces-card::before { background: linear-gradient(180deg, #a855f7 0%, transparent 100%) !important; }
	.kpi:hover::before { opacity: 1 !important; }

	.kpi-k {
	font-size: 0.60rem !important;
	letter-spacing: 0.18em !important;
	font-weight: 700 !important;
	color: rgba(138,176,197,0.7) !important;
	margin-bottom: 14px !important;
	text-transform: uppercase !important;
	}
	.kpi-v {
	font-size: 2.6rem !important;
	font-weight: 800 !important;
	letter-spacing: -0.03em !important;
	line-height: 1 !important;
	}
	#kpi-spaces-card .kpi-v {
	color: #a855f7 !important;
	text-shadow: 0 0 24px rgba(168,85,247,0.5) !important;
	}
	.kpi-sub {
	margin-top: 12px !important;
	font-size: 0.65rem !important;
	color: rgba(79,114,134,0.75) !important;
	font-weight: 500 !important;
	letter-spacing: 0.03em !important;
	}

	/* ── 6. Table ─────────────────────────────────────────────────────────────── */
	thead tr { background: rgba(0,0,0,0.28) !important; }
	th {
	font-size: 0.60rem !important;
	letter-spacing: 0.16em !important;
	font-weight: 800 !important;
	padding: 14px var(--sp-lg) !important;
	color: rgba(79,114,134,0.85) !important;
	border-bottom: 1px solid rgba(255,255,255,0.05) !important;
	}
	th.sorted { color: var(--cyan-accent) !important; }

	tbody tr { border-bottom: 1px solid rgba(255,255,255,0.025) !important; }
	tbody tr:hover { background: rgba(0,180,255,0.04) !important; }
	tbody tr.sel {
	background: rgba(0,180,255,0.07) !important;
	border-left: 3px solid var(--cyan-accent) !important;
	box-shadow: inset 12px 0 20px -12px rgba(0,180,255,0.25) !important;
	}
	td {
	padding: 13px var(--sp-lg) !important;
	font-size: 0.78rem !important;
	}

	/* Signal badges */
	.sig {
	border-radius: var(--elem-r) !important;
	font-size: 0.60rem !important;
	padding: 5px 10px !important;
	font-weight: 800 !important;
	}

	/* ── 7. Feed Panel ────────────────────────────────────────────────────────── */
	#bottom-grid { grid-template-columns: 1fr !important; }
	#feed-panel {
	min-height: 200px;
	}
	#feed-body { max-height: 240px !important; }

	.feed-cols.hd {
	background: rgba(0,0,0,0.22) !important;
	font-size: 0.60rem !important;
	letter-spacing: 0.14em !important;
	}
	.feed-cols.row { padding: 11px var(--sp-lg) !important; }
	.f-asset { font-size: 0.78rem !important; }

	/* ── 8. Sidebar ───────────────────────────────────────────────────────────── */
	#sidebar-inner {
	background: rgba(0,8,20,0.75) !important;
	backdrop-filter: blur(40px) saturate(160%) !important;
	-webkit-backdrop-filter: blur(40px) saturate(160%) !important;
	border: 1px solid rgba(255,255,255,0.07) !important;
	border-radius: var(--panel-r) !important;
	box-shadow:
	0 1px 0 rgba(255,255,255,0.07) inset,
	0 20px 50px rgba(0,0,0,0.5) !important;
	}
	.sb-hd {
	font-size: 0.58rem !important;
	letter-spacing: 0.22em !important;
	color: rgba(0,180,255,0.75) !important;
	border-bottom: 1px solid rgba(0,180,255,0.12) !important;
	}
	.sb-k { font-size: 0.70rem !important; color: rgba(138,176,197,0.6) !important; }
	.sb-v { font-size: 0.72rem !important; }
	.sb-v.ok { color: #a855f7 !important; text-shadow: 0 0 8px rgba(168,85,247,0.45) !important; }
	.sb-v.err { color: var(--red) !important; }

	/* ── 9. Detail panel ──────────────────────────────────────────────────────── */
	#detail-panel { background: rgba(0,0,0,0.38) !important; }
	.dc-title { color: var(--cyan-accent) !important; font-size: 0.60rem !important; letter-spacing: 0.20em !important; }

	/* ── 10. Scrollbars — thin & styled ──────────────────────────────────────── */
	::-webkit-scrollbar { width: 4px; height: 4px; }
	::-webkit-scrollbar-track { background: transparent; }
	::-webkit-scrollbar-thumb { background: rgba(0,180,255,0.25); border-radius: 4px; }
	::-webkit-scrollbar-thumb:hover { background: rgba(0,180,255,0.45); }

	/* ── 11. Scanlines — subtler ──────────────────────────────────────────────── */
	#scanlines { opacity: 0.12 !important; }

	/* ── 12. Aurora blobs — toned down to complement, not compete ────────────── */
	.aurora-blob { filter: blur(140px) !important; }
	.aurora-blob.c1 { opacity: 0.5; }
	.aurora-blob.c2 { opacity: 0.45; }
	.aurora-blob.c3 { opacity: 0.3; }

	/* ── 13. Log badges ───────────────────────────────────────────────────────── */
	.cat-tag {
	background: rgba(0,180,255,0.10) !important;
	color: var(--cyan-accent) !important;
	border: 1px solid rgba(0,180,255,0.20) !important;
	font-size: 0.58rem !important;
	}
	.filter-btn.active, .filter-btn:hover {
	border-color: var(--cyan-accent) !important;
	background: rgba(0,180,255,0.10) !important;
	color: var(--cyan-accent) !important;
	box-shadow: 0 0 12px rgba(0,180,255,0.25) !important;
	}

	/* ── 14. Page entrance animation ─────────────────────────────────────────── */
	@keyframes rise {
	from { opacity: 0; transform: translateY(16px); filter: blur(4px); }
	to { opacity: 1; transform: none; filter: none; }
	}
	#main { animation: rise 0.6s cubic-bezier(0.16,1,0.3,1) both; }


	/* ═══════════════════════════════════════════════════════════════════════════
	✦ INTER TYPOGRAPHY SYSTEM — FULL OVERHAUL
	✦ Base: 15px \| Scale: Major Third (1.250)
	✦ Using Inter variable font optical sizing (opsz 14..32)
	═══════════════════════════════════════════════════════════════════════════ */

	/* Scale reference:
	10px = 0.667rem labels / badges
	11px = 0.733rem meta / timestamps
	12px = 0.800rem secondary labels
	13px = 0.867rem body small
	14px = 0.933rem body
	15px = 1.000rem base
	16px = 1.067rem body large
	18px = 1.200rem subheadings
	20px = 1.333rem headings
	*/

	body {
	font-family: 'Inter', system-ui, -apple-system, sans-serif !important;
	font-optical-sizing: auto;
	line-height: 1.55;
	letter-spacing: -0.01em;
	}

	/* ── NAV ──────────────────────────────────────────────────────────────────── */
	#nav-logo-text {
	font-size: 1.05rem !important; /* 15.75px */
	font-weight: 900 !important;
	letter-spacing: 0.30em !important;
	font-optical-sizing: auto;
	}

	.nav-tab {
	font-size: 0.767rem !important; /* 11.5px — crisp label */
	font-weight: 600 !important;
	letter-spacing: 0.13em !important;
	font-optical-sizing: auto;
	}

	#live-pill-label {
	font-size: 0.733rem !important; /* 11px */
	font-weight: 700 !important;
	letter-spacing: 0.12em !important;
	}

	#search-input {
	font-size: 0.833rem !important; /* 12.5px */
	font-family: 'Inter', sans-serif !important;
	font-weight: 400 !important;
	letter-spacing: 0.01em !important;
	}

	/* ── KPI CARDS ────────────────────────────────────────────────────────────── */
	.kpi-k {
	font-size: 0.667rem !important; /* 10px */
	font-weight: 700 !important;
	letter-spacing: 0.20em !important;
	font-optical-sizing: auto;
	text-transform: uppercase !important;
	}

	.kpi-v {
	font-size: 3.0rem !important; /* 45px — commanding */
	font-weight: 800 !important;
	letter-spacing: -0.04em !important; /* tight at large size */
	font-optical-sizing: auto;
	line-height: 1 !important;
	font-variant-numeric: tabular-nums !important;
	}

	.kpi-sub {
	font-size: 0.733rem !important; /* 11px */
	font-weight: 500 !important;
	letter-spacing: 0.02em !important;
	line-height: 1.4 !important;
	}

	/* ── PANEL HEADERS ────────────────────────────────────────────────────────── */
	.panel-hd-label {
	font-size: 0.700rem !important; /* 10.5px */
	font-weight: 800 !important;
	letter-spacing: 0.20em !important;
	text-transform: uppercase !important;
	font-optical-sizing: auto;
	}

	.panel-hd-meta {
	font-size: 0.700rem !important; /* 10.5px */
	font-weight: 400 !important;
	letter-spacing: 0.04em !important;
	}

	/* ── TABLE ────────────────────────────────────────────────────────────────── */
	th {
	font-size: 0.667rem !important; /* 10px */
	font-weight: 700 !important;
	letter-spacing: 0.16em !important;
	text-transform: uppercase !important;
	font-optical-sizing: auto;
	}

	td {
	font-size: 0.867rem !important; /* 13px — comfortable reading */
	font-weight: 500 !important;
	letter-spacing: 0.01em !important;
	line-height: 1.45 !important;
	}

	td.nc {
	font-size: 0.900rem !important; /* 13.5px */
	font-weight: 700 !important;
	letter-spacing: -0.01em !important;
	}

	td.num {
	font-variant-numeric: tabular-nums !important;
	font-feature-settings: "tnum" !important;
	font-size: 0.833rem !important;
	font-weight: 600 !important;
	}

	td.rc {
	font-size: 0.800rem !important;
	font-weight: 800 !important;
	letter-spacing: 0.06em !important;
	}

	/* ── SIGNAL BADGES ────────────────────────────────────────────────────────── */
	.sig {
	font-size: 0.667rem !important; /* 10px */
	font-weight: 800 !important;
	letter-spacing: 0.10em !important;
	font-optical-sizing: auto;
	}

	/* ── LIVE FEED ────────────────────────────────────────────────────────────── */
	.feed-cols.hd span {
	font-size: 0.667rem !important; /* 10px */
	font-weight: 700 !important;
	letter-spacing: 0.15em !important;
	}

	.f-asset {
	font-size: 0.867rem !important; /* 13px */
	font-weight: 800 !important;
	letter-spacing: -0.01em !important;
	}

	.f-ts {
	font-size: 0.700rem !important; /* 10.5px */
	font-weight: 400 !important;
	letter-spacing: 0.01em !important;
	}

	.f-dir, .f-out {
	font-size: 0.800rem !important;
	font-weight: 800 !important;
	letter-spacing: 0.04em !important;
	font-variant-numeric: tabular-nums !important;
	}

	/* ── SIDEBAR ──────────────────────────────────────────────────────────────── */
	.sb-hd {
	font-size: 0.633rem !important; /* 9.5px */
	font-weight: 800 !important;
	letter-spacing: 0.24em !important;
	text-transform: uppercase !important;
	}

	.sb-k {
	font-size: 0.800rem !important; /* 12px */
	font-weight: 500 !important;
	letter-spacing: 0.01em !important;
	}

	.sb-v {
	font-size: 0.833rem !important; /* 12.5px */
	font-weight: 700 !important;
	letter-spacing: -0.01em !important;
	font-variant-numeric: tabular-nums !important;
	}

	/* ── LOG TABLE ────────────────────────────────────────────────────────────── */
	#logs-table th {
	font-size: 0.667rem !important;
	font-weight: 700 !important;
	letter-spacing: 0.16em !important;
	}

	#logs-table td {
	font-size: 0.833rem !important; /* 12.5px */
	font-weight: 400 !important;
	line-height: 1.5 !important;
	}

	.log-time {
	font-size: 0.733rem !important; /* 11px */
	font-weight: 500 !important;
	font-variant-numeric: tabular-nums !important;
	letter-spacing: 0.01em !important;
	}

	.log-badge {
	font-size: 0.633rem !important; /* 9.5px */
	font-weight: 800 !important;
	letter-spacing: 0.10em !important;
	}

	.log-asset {
	font-size: 0.867rem !important; /* 13px */
	font-weight: 700 !important;
	}

	.log-message {
	font-size: 0.800rem !important; /* 12px */
	font-weight: 400 !important;
	line-height: 1.55 !important;
	}

	.cat-tag {
	font-size: 0.633rem !important;
	font-weight: 700 !important;
	letter-spacing: 0.06em !important;
	}

	/* ── FILTER BUTTONS ───────────────────────────────────────────────────────── */
	.filter-btn {
	font-size: 0.733rem !important; /* 11px */
	font-weight: 600 !important;
	letter-spacing: 0.08em !important;
	font-family: 'Inter', sans-serif !important;
	}

	/* ── DETAIL PANEL ─────────────────────────────────────────────────────────── */
	.dc-title {
	font-size: 0.667rem !important;
	font-weight: 800 !important;
	letter-spacing: 0.20em !important;
	}
	.dk {
	font-size: 0.800rem !important;
	font-weight: 500 !important;
	}
	.dv {
	font-size: 0.833rem !important;
	font-weight: 700 !important;
	font-variant-numeric: tabular-nums !important;
	}

	/* ── NO DATA STATE ────────────────────────────────────────────────────────── */
	.no-data, [colspan] {
	font-size: 0.867rem !important;
	font-weight: 500 !important;
	letter-spacing: 0.04em !important;
	color: var(--t3) !important;
	}

	/* ════════════════════════════════════════════════════════════════════════════
	TRADING PANEL STYLES
	════════════════════════════════════════════════════════════════════════════ */

	/* Trading signal table */
	#trade-signal-table th { font-size: 0.65rem !important; }
	#trade-signal-table td { font-size: 0.82rem !important; }

	/* Gate cards */
	.gate-card {
	display: flex; flex-direction: column; align-items: center; justify-content: center;
	padding: var(--sp-lg); border-radius: var(--elem-r);
	background: rgba(0,0,0,0.35);
	border: 1px solid rgba(255,255,255,0.07);
	text-align: center; gap: 10px;
	transition: all 0.3s ease;
	}
	.gate-card:hover { border-color: rgba(255,255,255,0.15); transform: translateY(-2px); }
	.gate-label {
	font-size: 0.65rem; font-weight: 800; letter-spacing: 0.18em;
	text-transform: uppercase; color: var(--t3);
	}
	.gate-name {
	font-size: 0.75rem; font-weight: 600; color: var(--t2);
	margin-top: 2px;
	}
	.gate-status {
	font-size: 1.5rem; font-weight: 900; letter-spacing: -0.02em;
	}
	.gate-status.pass { color: var(--green); text-shadow: 0 0 15px var(--green-glow); }
	.gate-status.fail { color: var(--red); text-shadow: 0 0 15px var(--red-glow); }
	.gate-status.idle { color: var(--t4); }
	.gate-desc {
	font-size: 0.65rem; color: var(--t3); font-weight: 500; line-height: 1.4;
	}

	/* Vote bar */
	.vote-row {
	display: flex; flex-direction: column; gap: 6px;
	}
	.vote-asset-label {
	display: flex; justify-content: space-between; align-items: center;
	}
	.vote-asset-name {
	font-size: 0.8rem; font-weight: 700; color: var(--t0);
	}
	.vote-signal-tag {
	font-size: 0.6rem; font-weight: 800; letter-spacing: 0.1em; padding: 3px 8px;
	border-radius: 4px;
	}
	.vote-bar-track {
	height: 8px; background: rgba(255,255,255,0.05); border-radius: 4px; overflow: hidden;
	display: flex;
	}
	.vote-bar-buy {
	background: linear-gradient(90deg, var(--green), rgba(0,223,138,0.6));
	transition: width 0.6s cubic-bezier(0.16,1,0.3,1);
	height: 100%;
	}
	.vote-bar-sell {
	background: linear-gradient(90deg, rgba(255,61,90,0.6), var(--red));
	transition: width 0.6s cubic-bezier(0.16,1,0.3,1);
	height: 100%;
	}
	.vote-counts {
	display: flex; justify-content: space-between;
	font-size: 0.65rem; font-weight: 600;
	}
	.vote-counts .v-buy { color: var(--green); }
	.vote-counts .v-sell { color: var(--red); }

	/* Positions table */
	.pos-gate-pass { color: var(--green); font-size: 0.7rem; font-weight: 700; }
	.pos-gate-warn { color: var(--amber); font-size: 0.7rem; font-weight: 700; }
	.pos-gate-fail { color: var(--red); font-size: 0.7rem; font-weight: 700; }

	/* Trade feed scrollbar */
	#trade-feed-body::-webkit-scrollbar { width: 4px; }
	#trade-feed-body::-webkit-scrollbar-thumb { background: rgba(255,255,255,0.1); border-radius: 4px; }

	/* ════════════════════════════════════════════════════════════════════════════
	ASSETS PANEL STYLES
	════════════════════════════════════════════════════════════════════════════ */

	/* Asset search focus */
	#asset-search:focus {
	border-color: var(--cyan) !important;
	background: rgba(0,200,255,0.05) !important;
	box-shadow: 0 0 15px rgba(0,200,255,0.2) !important;
	}

	/* Asset cards */
	.asset-card {
	background: var(--glass-bg);
	backdrop-filter: blur(24px) saturate(120%);
	-webkit-backdrop-filter: blur(24px) saturate(120%);
	border: 1px solid var(--glass-border);
	border-radius: var(--panel-r);
	padding: var(--sp-lg);
	cursor: pointer;
	transition: all 0.35s cubic-bezier(0.2, 0.8, 0.2, 1);
	position: relative; overflow: hidden;
	box-shadow: 0 10px 25px rgba(0,0,0,0.3);
	}
	.asset-card::before {
	content: ''; position: absolute; top: 0; left: 0; right: 0; height: 3px;
	transition: all 0.3s ease;
	}
	.asset-card.sig-buy::before { background: linear-gradient(90deg, var(--green), transparent); box-shadow: 0 0 15px var(--green-glow); }
	.asset-card.sig-sell::before { background: linear-gradient(90deg, var(--red), transparent); box-shadow: 0 0 15px var(--red-glow); }
	.asset-card.sig-hold::before { background: linear-gradient(90deg, var(--t4), transparent); }
	.asset-card:hover {
	border-color: var(--glass-edge);
	transform: translateY(-4px);
	box-shadow: 0 20px 40px rgba(0,0,0,0.5), inset 0 1px 15px rgba(0,200,255,0.05);
	}
	.asset-card.selected {
	border-color: var(--cyan);
	box-shadow: 0 0 0 1px var(--cyan), 0 20px 40px rgba(0,0,0,0.5);
	}

	.ac-header {
	display: flex; justify-content: space-between; align-items: flex-start;
	margin-bottom: var(--sp-md);
	}
	.ac-name {
	font-size: 1.1rem; font-weight: 800; color: var(--t0);
	letter-spacing: -0.01em; line-height: 1.2;
	}
	.ac-rank {
	font-size: 0.65rem; font-weight: 800; color: var(--t3);
	letter-spacing: 0.1em; margin-top: 3px;
	}

	.ac-score-block {
	margin-bottom: var(--sp-md);
	}
	.ac-score-label { font-size: 0.6rem; font-weight: 700; color: var(--t3); text-transform: uppercase; letter-spacing: 0.15em; }
	.ac-score-val { font-size: 2.2rem; font-weight: 800; line-height: 1; letter-spacing: -0.03em; margin-top: 4px; }

	.ac-metrics {
	display: grid; grid-template-columns: 1fr 1fr; gap: 8px;
	padding-top: var(--sp-md);
	border-top: 1px solid rgba(255,255,255,0.05);
	}
	.ac-metric { display: flex; flex-direction: column; gap: 3px; }
	.ac-metric-k { font-size: 0.58rem; font-weight: 700; color: var(--t3); text-transform: uppercase; letter-spacing: 0.12em; }
	.ac-metric-v { font-size: 0.85rem; font-weight: 700; color: var(--t1); font-variant-numeric: tabular-nums; }

	.ac-vote-bar {
	height: 4px; background: rgba(255,255,255,0.05); border-radius: 2px; overflow: hidden;
	display: flex; margin-top: var(--sp-sm);
	}
	.ac-vote-buy { background: var(--green); transition: width 0.5s ease; }
	.ac-vote-sell { background: var(--red); transition: width 0.5s ease; }

	.ac-footer {
	display: flex; justify-content: space-between; align-items: center;
	margin-top: var(--sp-sm);
	font-size: 0.65rem; color: var(--t3); font-weight: 500;
	}
	.ac-footer .ac-ts { color: var(--t3); }
	.ac-footer .ac-steps { color: var(--t2); font-weight: 600; }

	/* Heatmap */
	.hm-header-row {
	display: grid; align-items: center;
	font-size: 0.6rem; font-weight: 800; color: var(--t3);
	text-transform: uppercase; letter-spacing: 0.12em;
	padding: 6px 12px;
	border-bottom: 1px solid rgba(255,255,255,0.06);
	}
	.hm-row {
	display: grid; align-items: center;
	padding: 8px 12px; border-radius: 6px;
	transition: background 0.2s;
	}
	.hm-row:hover { background: rgba(255,255,255,0.03); }
	.hm-asset-name { font-size: 0.82rem; font-weight: 700; color: var(--t0); }
	.hm-cell {
	height: 28px; border-radius: 4px;
	display: flex; align-items: center; justify-content: center;
	font-size: 0.7rem; font-weight: 700;
	font-variant-numeric: tabular-nums;
	transition: all 0.4s ease;
	}

	/* Deep dive stat blocks */
	.dive-block { display: flex; flex-direction: column; gap: var(--sp-sm); }
	.dive-block-title {
	font-size: 0.65rem; font-weight: 800; letter-spacing: 0.18em;
	color: var(--cyan); text-transform: uppercase;
	padding-bottom: 10px; border-bottom: 1px dashed rgba(255,255,255,0.08);
	}
	.dive-row { display: flex; justify-content: space-between; padding: 7px 0; font-size: 0.78rem; border-bottom: 1px solid rgba(255,255,255,0.03); }
	.dive-k { color: var(--t2); font-weight: 500; }
	.dive-v { color: var(--t0); font-weight: 700; font-variant-numeric: tabular-nums; }
	.dive-v.g { color: var(--green); }
	.dive-v.r { color: var(--red); }
	.dive-v.c { color: var(--cyan); }
	.dive-v.a { color: var(--amber); }

	/* view buttons active state */
	.asset-view-btn.active {
	border-color: rgba(0,200,255,0.4) !important;
	background: rgba(0,200,255,0.1) !important;
	color: var(--cyan) !important;
	}

	/* ════════════════════════════════════════════════════════════════════════════
	TRAINING PANEL KPI CELLS
	════════════════════════════════════════════════════════════════════════════ */
	.training-kpi-cell {
	display: flex;
	flex-direction: column;
	align-items: center;
	justify-content: center;
	padding: 20px var(--sp-lg);
	gap: 6px;
	text-align: center;
	position: relative;
	transition: background 0.3s ease;
	}
	.training-kpi-cell:hover {
	background: rgba(255,255,255,0.02);
	}
	.training-kpi-label {
	font-size: 0.62rem;
	font-weight: 800;
	letter-spacing: 0.2em;
	text-transform: uppercase;
	color: var(--t3);
	}
	.training-kpi-value {
	font-size: 1.65rem;
	font-weight: 800;
	letter-spacing: -0.02em;
	line-height: 1;
	font-variant-numeric: tabular-nums;
	transition: all 0.4s ease;
	}
	.training-kpi-sub {
	font-size: 0.62rem;
	color: var(--t3);
	font-weight: 500;
	letter-spacing: 0.04em;
	min-height: 14px;
	}
	/* Terminal scrollbar styling */
	#training-log-terminal::-webkit-scrollbar { width: 4px; }
	#training-log-terminal::-webkit-scrollbar-thumb { background: rgba(0,212,255,0.2); border-radius: 4px; }
	#training-log-terminal::-webkit-scrollbar-track { background: transparent; }

	/* Log line colorings */
	.tlog-debug { color: var(--t0); }
	.tlog-info { color: var(--t0); }
	.tlog-signal { color: var(--t0); }
	.tlog-trade { color: var(--t0); }
	.tlog-error { color: var(--t0); }
	.tlog-warn { color: var(--t0); }
	.tlog-ts { color: var(--t2); margin-right: 6px; font-variant-numeric: tabular-nums; }
	.tlog-badge { font-weight: 700; margin-right: 4px; }

	</style>

	<script>
	/* ════════════════════════════════════════════════════════════════════════════
	TRADE ALERT AUDIO ENGINE
	─────────────────────────────────────────────────────────────────────────
	Architecture (50yr Sony DSP discipline):
	• Single AudioContext — creating multiple contexts is wasteful and browsers
	limit them. One context, many source nodes.
	• Decode-once pattern — WAV PCM decoded to AudioBuffer on first unlock.
	Subsequent plays clone a BufferSource node (zero decode overhead, <1ms).
	• Gain node at output — master volume, can be ramped for fade effects.
	• AudioContext unlocked on first user gesture anywhere on the page — this
	satisfies Chrome/Firefox autoplay policy without requiring a button click.
	• Fires on: (a) new messages_rx from /api/state polling, AND
	(b) new feed entries detected by last_updated timestamp diff.
	• Tab-agnostic — runs in the main JS execution context, not inside any
	tab-visibility guard.
	════════════════════════════════════════════════════════════════════════════ */
	(function() {
	// ── WAV data: 8-bit PCM mono 11025Hz (original file embedded verbatim) ──
	const WAV_B64 = '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';

	let _audioCtx = null;
	let _audioBuffer = null;
	let _gainNode = null;
	let _unlocked = false;

	// Convert base64 → ArrayBuffer
	function b64ToArrayBuffer(b64) {
	const bin = atob(b64);
	const buf = new ArrayBuffer(bin.length);
	const u8 = new Uint8Array(buf);
	for (let i = 0; i < bin.length; i++) u8[i] = bin.charCodeAt(i);
	return buf;
	}

	// Initialise context + decode buffer (called on first user gesture)
	function unlock() {
	if (_unlocked) return;
	_unlocked = true;

	try {
	_audioCtx = new (window.AudioContext \|\| window.webkitAudioContext)();

	// Master gain — 0.85 to leave headroom, avoids inter-sample clipping
	_gainNode = _audioCtx.createGain();
	_gainNode.gain.setValueAtTime(0.85, _audioCtx.currentTime);
	_gainNode.connect(_audioCtx.destination);

	// Decode PCM once, keep the AudioBuffer in memory
	const arrayBuf = b64ToArrayBuffer(WAV_B64);
	_audioCtx.decodeAudioData(arrayBuf,
	function(decoded) {
	_audioBuffer = decoded;
	console.log('[TradeAudio] Buffer decoded — duration:', decoded.duration.toFixed(3), 's, sr:', decoded.sampleRate, 'Hz');
	},
	function(err) {
	console.warn('[TradeAudio] Decode error:', err);
	}
	);
	} catch(e) {
	console.warn('[TradeAudio] AudioContext init failed:', e);
	}
	}

	// Play a single shot — <1ms overhead (buffer source nodes are lightweight)
	window.playTradeSound = function() {
	if (!_unlocked) { unlock(); return; } // first call unlocks silently
	if (!_audioBuffer \|\| !_audioCtx) return;

	// Resume context if suspended (browser tab backgrounding)
	const play = function() {
	const src = _audioCtx.createBufferSource();
	src.buffer = _audioBuffer;
	src.connect(_gainNode);
	src.start(0); // fire immediately, no scheduling delay
	};

	if (_audioCtx.state === 'suspended') {
	_audioCtx.resume().then(play);
	} else {
	play();
	}
	};

	// Unlock on ANY user gesture — click, keydown, touchstart
	['click','keydown','touchstart','mousedown'].forEach(function(evt) {
	document.addEventListener(evt, function onGesture() {
	unlock();
	document.removeEventListener(evt, onGesture);
	}, { once: true, passive: true });
	});

	// ── Trade detection ──────────────────────────────────────────────────────
	// Sound fires ONLY when a genuinely new trade_id appears in the Open
	// Positions panel (/api/trades → data.open[]). Detection runs inside
	// updateTerminal() which owns the canonical open-positions data.
	// _onTradeRefresh is kept as a no-op stub so call-sites don't break.

	window._onTradeRefresh = function(rankings, health) {
	// intentionally empty — sound is now driven by open-position diff only
	};

	console.log('[TradeAudio] Engine initialised — waiting for user gesture to unlock AudioContext');
	})();
	</script>

	</head>
	<body>

	<div id="bg-aurora">
	<div class="aurora-blob c1"></div>
	<div class="aurora-blob c2"></div>
	<div class="aurora-blob c3"></div>
	</div>
	<canvas id="bg-canvas"></canvas>
	<canvas id="three-canvas"></canvas>
	<div id="bg-overlay"></div>
	<div id="scanlines"></div>

	<div id="sidebar">
	<div id="sidebar-inner">
	<div class="sb-hd">System Status</div>
	<div class="sb-row"><span class="sb-k">Hub Node</span> <span id="sc-hub" class="sb-v err">Connecting…</span></div>
	<div class="sb-row"><span class="sb-k">Engine</span> <span id="sc-model" class="sb-v">—</span></div>
	<div class="sb-row"><span class="sb-k">Sync</span> <span id="sc-snap" class="sb-v">—</span></div>
	<div class="sb-row"><span class="sb-k">Clusters</span> <span id="sc-spaces" class="sb-v">0</span></div>
	<div class="sb-row" style="margin-top: 12px; padding-top: 12px; border-top: 1px solid rgba(255,255,255,0.05);">
	<span class="sb-k">Logs</span>
	<span id="sc-logs" class="sb-v">0</span>
	</div>
	</div>
	</div>

	<div id="shell">
	<nav id="nav">
	<div id="nav-logo">
	<div id="nav-logo-mark"></div>
	<div id="nav-logo-text">QUA<em>SAR</em></div>
	</div>
	<div id="nav-links">
	<button class="nav-tab active" onclick="switchTab(event,'rankings')">Rankings</button>
	<button class="nav-tab" onclick="switchTab(event,'assets')">Assets</button>
	<button class="nav-tab" onclick="switchTab(event,'trading')">Trading</button>
	<button class="nav-tab" onclick="switchTab(event,'logs')">Logs</button>
	<button class="nav-tab" onclick="switchTab(event,'telemetry')">Telemetry</button>
	<button class="nav-tab" onclick="switchTab(event,'terminal')" style="color:#E8720A">⬛ Terminal</button>
	</div>
	<div id="nav-right">
	<div class="search-wrap">
	<span class="search-icon">⌕</span>
	<input id="search-input" placeholder="Search parameters…" type="text" oninput="filterTable(this.value)" />
	</div>
	<div id="live-pill">
	<div class="pring live" id="nav-dot"><div class="core"></div></div>
	<span id="live-pill-label" id="nav-status">Live</span>
	</div>
	</div>
	</nav>

	<main id="main">

	<!-- RANKINGS TAB -->
	<div id="rankings-tab" class="tab-panel active">
	<div id="kpi-row">
	<div class="panel kpi" id="kpi-spaces-card">
	<div class="kpi-k">Active Clusters</div>
	<div class="kpi-v" id="kpi-spaces">—</div>
	<div class="kpi-sub" id="kpi-spaces-sub">of 9 registered</div>
	</div>
	<div class="panel kpi" id="kpi-score-card">
	<div class="kpi-k">Apex Score</div>
	<div class="kpi-v c-green" id="kpi-score">—</div>
	<div class="kpi-sub" id="kpi-score-asset">—</div>
	</div>
	<div class="panel kpi" id="kpi-acc-card">
	<div class="kpi-k">Mean AVN Accuracy</div>
	<div class="kpi-v c-cyan" id="kpi-acc">—</div>
	<div class="kpi-sub">across global network</div>
	</div>
	<div class="panel kpi" id="kpi-upd-card">
	<div class="kpi-k">Last Telemetry</div>
	<div class="kpi-v" id="kpi-upd">—</div>
	<div class="kpi-sub" id="kpi-msgs">0 packets received</div>
	</div>
	</div>

	<div class="panel" id="table-panel">
	<div class="panel-hd">
	<div class="panel-hd-left">
	<div class="panel-hd-pip"></div>
	<span class="panel-hd-label">Intelligence Matrix</span>
	</div>
	<span class="panel-hd-meta" id="rank-meta">0 assets — sorting algorithm active</span>
	</div>
	<table id="rankings-table">
	<thead>
	<tr>
	<th style="width:60px;text-align:center">RNK</th>
	<th onclick="sortBy('space_name')">Asset <span class="sa">▲</span></th>
	<th onclick="sortBy('score')" class="sorted">Score <span class="sa">▼</span></th>
	<th onclick="sortBy('signal_confidence')">Confidence <span class="sa">▲</span></th>
	<th onclick="sortBy('avn_accuracy')">AVN Acc <span class="sa">▲</span></th>
	<th>Vector</th>
	<th onclick="sortBy('training_steps')">Cycles <span class="sa">▲</span></th>
	<th onclick="sortBy('actor_loss')">Loss Rate <span class="sa">▲</span></th>
	<th>Status</th>
	</tr>
	</thead>
	<tbody id="rankings-body">
	<tr><td colspan="9" class="no-data">Awaiting data stream...</td></tr>
	</tbody>
	</table>
	<div id="detail-panel"></div>
	</div>

	<!-- TRAINING PANEL -->
	<div id="bottom-grid">
	<div class="panel" id="training-panel">
	<div class="panel-hd">
	<div class="panel-hd-left">
	<div class="panel-hd-pip" style="background:var(--cyan);box-shadow:0 0 10px var(--cyan-glow)"></div>
	<span class="panel-hd-label">Training Logs</span>
	</div>
	<div style="display:flex;align-items:center;gap:12px">
	<span class="panel-hd-meta" id="training-meta">awaiting training stream…</span>
	<div style="display:flex;align-items:center;gap:6px;padding:4px 10px;border-radius:var(--pill-r);border:1px solid rgba(0,212,255,0.2);background:rgba(0,212,255,0.06)">
	<div class="pring live" id="training-dot"><div class="core"></div></div>
	<span style="font-size:0.6rem;font-weight:800;letter-spacing:0.12em;color:var(--cyan)">LIVE</span>
	</div>
	</div>
	</div>

	<!-- Terminal log stream -->
	<div id="training-log-terminal" style="
	font-family:var(--font);
	font-size:0.82rem;
	line-height:1;
	color:var(--t0);
	background:rgba(0,0,0,0.42);
	border-bottom:1px solid rgba(255,255,255,0.05);
	padding:0;
	height:400px;
	overflow-y:auto;
	letter-spacing:0.01em;
	scrollbar-width:thin;
	scrollbar-color:rgba(255,255,255,0.15) transparent;
	">
	<div style="padding:20px 24px;color:var(--t3);font-style:italic;font-size:0.78rem">Awaiting training data stream…</div>
	</div>

	<!-- KPI strip: Loss · Learning Rate · Step · Assets -->
	<div style="display:grid;grid-template-columns:repeat(4,1fr);border-top:1px solid rgba(255,255,255,0.06)">

	<div class="training-kpi-cell" style="border-right:1px solid rgba(255,255,255,0.05);padding:36px 32px">
	<div class="training-kpi-label" style="font-size:0.65rem;letter-spacing:0.22em;margin-bottom:16px">Loss</div>
	<div class="training-kpi-value" id="trn-loss" style="font-size:3rem;color:var(--red);text-shadow:0 0 30px rgba(255,68,102,0.5)">—</div>
	<div class="training-kpi-sub" id="trn-loss-trend" style="margin-top:12px;font-size:0.75rem;min-height:18px"></div>
	</div>

	<div class="training-kpi-cell" style="border-right:1px solid rgba(255,255,255,0.05);padding:36px 32px">
	<div class="training-kpi-label" style="font-size:0.65rem;letter-spacing:0.22em;margin-bottom:16px">Learning Rate</div>
	<div class="training-kpi-value" id="trn-lr" style="font-size:3rem;color:var(--amber);text-shadow:0 0 30px rgba(255,170,0,0.45)">—</div>
	<div class="training-kpi-sub" id="trn-lr-sub" style="margin-top:12px;font-size:0.75rem">scheduler active</div>
	</div>

	<div class="training-kpi-cell" style="border-right:1px solid rgba(255,255,255,0.05);padding:36px 32px">
	<div class="training-kpi-label" style="font-size:0.65rem;letter-spacing:0.22em;margin-bottom:16px">Step</div>
	<div class="training-kpi-value" id="trn-step" style="font-size:3rem;color:var(--cyan);text-shadow:0 0 30px rgba(0,212,255,0.45)">—</div>
	<div class="training-kpi-sub" id="trn-step-sub" style="margin-top:12px;font-size:0.75rem">gradient updates</div>
	</div>

	<div class="training-kpi-cell" style="padding:36px 32px">
	<div class="training-kpi-label" style="font-size:0.65rem;letter-spacing:0.22em;margin-bottom:16px">Assets</div>
	<div class="training-kpi-value" id="trn-assets" style="font-size:3rem;color:var(--green);text-shadow:0 0 30px rgba(0,255,136,0.45)">—</div>
	<div class="training-kpi-sub" id="trn-assets-sub" style="margin-top:12px;font-size:0.75rem">in cluster</div>
	</div>

	</div>
	</div>
	</div>
	</div>

	<canvas id="score-chart" style="display:none"></canvas>
	<canvas id="loss-chart" style="display:none"></canvas>
	<canvas id="acc-chart" style="display:none"></canvas>
	<!-- LOGS TAB -->
	<div id="logs-tab" class="tab-panel">
	<div class="panel">
	<div class="panel-hd">
	<div class="panel-hd-left">
	<div class="panel-hd-pip" style="background:var(--amber);box-shadow:0 0 10px var(--amber-glow)"></div>
	<span class="panel-hd-label">Ranker Operations Log</span>
	</div>
	<span class="panel-hd-meta" id="logs-meta">loading…</span>
	</div>

	<div id="logs-filters">
	<button class="filter-btn active" onclick="filterLogs(event,'all')">All</button>
	<button class="filter-btn" onclick="filterLogs(event,'INFO')">Info</button>
	<button class="filter-btn" onclick="filterLogs(event,'DEBUG')">Debug</button>
	<button class="filter-btn" onclick="filterLogs(event,'WARNING')">Warning</button>
	<button class="filter-btn" onclick="filterLogs(event,'ERROR')">Error</button>
	<button class="filter-btn" onclick="filterLogs(event,'signal')">Signals</button>
	<button class="filter-btn" onclick="filterLogs(event,'trade')">Trades</button>
	<button class="filter-btn" onclick="filterLogs(event,'ranking')">Rankings</button>
	</div>

	<div style="overflow-x: auto;">
	<table id="logs-table">
	<thead>
	<tr>
	<th style="width:140px">Timestamp</th>
	<th style="width:90px">Level</th>
	<th style="width:100px">Category</th>
	<th style="width:80px">Asset</th>
	<th>Message</th>
	</tr>
	</thead>
	<tbody id="logs-body">
	<tr><td colspan="5" style="text-align:center;padding:40px;color:var(--t3)">Loading logs…</td></tr>
	</tbody>
	</table>
	</div>
	</div>

	<div class="panel">
	<div class="panel-hd">
	<div class="panel-hd-left">
	<div class="panel-hd-pip" style="background:var(--green)"></div>
	<span class="panel-hd-label">Log Statistics</span>
	</div>
	</div>
	<div id="logs-stats" style="display: grid; grid-template-columns: repeat(auto-fit, minmax(180px, 1fr)); gap: var(--sp-lg); padding: var(--sp-xl);">
	<!-- Stats populated by JS -->
	</div>
	</div>
	</div>

	<!-- ════════════════════════════════════════════════════════════════
	ASSETS TAB
	════════════════════════════════════════════════════════════════ -->
	<div id="assets-tab" class="tab-panel">

	<!-- ASSETS SEARCH + VIEW TOGGLE -->
	<div style="display:flex;align-items:center;justify-content:space-between;gap:var(--sp-md);flex-wrap:wrap;">
	<div style="display:flex;align-items:center;gap:var(--sp-sm)">
	<div style="position:relative">
	<span style="position:absolute;left:12px;top:50%;transform:translateY(-50%);color:var(--t3);font-size:14px;pointer-events:none">⌕</span>
	<input id="asset-search" placeholder="Filter assets…" type="text"
	style="background:rgba(0,0,0,0.4);border:1px solid var(--glass-border);border-radius:var(--pill-r);
	padding:9px 18px 9px 34px;color:var(--t1);font-family:var(--font);font-size:0.8rem;
	width:220px;outline:none;transition:all 0.3s ease;"
	oninput="filterAssets(this.value)" />
	</div>
	<span id="asset-count-label" style="font-size:0.7rem;color:var(--t3);font-weight:600;white-space:nowrap">— assets</span>
	</div>
	<div style="display:flex;gap:8px">
	<button class="asset-view-btn active" id="avb-cards" onclick="setAssetView('cards',this)" style="padding:7px 16px;border-radius:var(--pill-r);border:1px solid rgba(0,200,255,0.4);background:rgba(0,200,255,0.1);color:var(--cyan);font-size:0.7rem;font-weight:700;cursor:pointer;letter-spacing:0.1em">⊞ CARDS</button>
	<button class="asset-view-btn" id="avb-table" onclick="setAssetView('table',this)" style="padding:7px 16px;border-radius:var(--pill-r);border:1px solid rgba(255,255,255,0.1);background:rgba(0,0,0,0.4);color:var(--t2);font-size:0.7rem;font-weight:700;cursor:pointer;letter-spacing:0.1em">☰ TABLE</button>
	<button class="asset-view-btn" id="avb-heatmap" onclick="setAssetView('heatmap',this)" style="padding:7px 16px;border-radius:var(--pill-r);border:1px solid rgba(255,255,255,0.1);background:rgba(0,0,0,0.4);color:var(--t2);font-size:0.7rem;font-weight:700;cursor:pointer;letter-spacing:0.1em">⬛ HEATMAP</button>
	</div>
	</div>

	<!-- ASSET SUMMARY BAR -->
	<div style="display:grid;grid-template-columns:repeat(5,1fr);gap:var(--sp-md)">
	<div class="panel" style="padding:var(--sp-lg);text-align:center">
	<div style="font-size:0.65rem;font-weight:800;letter-spacing:0.15em;color:var(--t3);text-transform:uppercase;margin-bottom:8px">Total Assets</div>
	<div id="as-total" style="font-size:2rem;font-weight:800;color:var(--t0)">—</div>
	</div>
	<div class="panel" style="padding:var(--sp-lg);text-align:center">
	<div style="font-size:0.65rem;font-weight:800;letter-spacing:0.15em;color:var(--t3);text-transform:uppercase;margin-bottom:8px">Bullish</div>
	<div id="as-bull" style="font-size:2rem;font-weight:800;color:var(--green);text-shadow:0 0 15px var(--green-glow)">—</div>
	</div>
	<div class="panel" style="padding:var(--sp-lg);text-align:center">
	<div style="font-size:0.65rem;font-weight:800;letter-spacing:0.15em;color:var(--t3);text-transform:uppercase;margin-bottom:8px">Bearish</div>
	<div id="as-bear" style="font-size:2rem;font-weight:800;color:var(--red);text-shadow:0 0 15px var(--red-glow)">—</div>
	</div>
	<div class="panel" style="padding:var(--sp-lg);text-align:center">
	<div style="font-size:0.65rem;font-weight:800;letter-spacing:0.15em;color:var(--t3);text-transform:uppercase;margin-bottom:8px">Neutral</div>
	<div id="as-neut" style="font-size:2rem;font-weight:800;color:var(--t2)">—</div>
	</div>
	<div class="panel" style="padding:var(--sp-lg);text-align:center">
	<div style="font-size:0.65rem;font-weight:800;letter-spacing:0.15em;color:var(--t3);text-transform:uppercase;margin-bottom:8px">Avg AVN Acc</div>
	<div id="as-avgacc" style="font-size:2rem;font-weight:800;color:var(--cyan);text-shadow:0 0 15px var(--cyan-glow)">—</div>
	</div>
	</div>

	<!-- CARDS VIEW -->
	<div id="asset-cards-view">
	<div id="asset-card-grid" style="display:grid;grid-template-columns:repeat(auto-fill,minmax(320px,1fr));gap:var(--sp-lg)">
	<div style="grid-column:1/-1;text-align:center;padding:60px;color:var(--t3)">Awaiting asset data…</div>
	</div>
	</div>

	<!-- TABLE VIEW (hidden by default) -->
	<div id="asset-table-view" style="display:none">
	<div class="panel">
	<div class="panel-hd">
	<div class="panel-hd-left">
	<div class="panel-hd-pip"></div>
	<span class="panel-hd-label">Full Asset Comparison</span>
	</div>
	<span class="panel-hd-meta" id="asset-table-meta">—</span>
	</div>
	<div style="overflow-x:auto">
	<table id="asset-full-table" style="width:100%;border-collapse:collapse;white-space:nowrap">
	<thead>
	<tr>
	<th style="width:50px;text-align:center">RNK</th>
	<th>Asset</th>
	<th style="text-align:right">Signal</th>
	<th style="text-align:right">Confidence</th>
	<th style="text-align:right">AVN Acc</th>
	<th style="text-align:right">Score</th>
	<th style="text-align:right">Actor Loss</th>
	<th style="text-align:right">Critic Loss</th>
	<th style="text-align:right">AVN Loss</th>
	<th style="text-align:right">Train Steps</th>
	<th style="text-align:right">Buy Votes</th>
	<th style="text-align:right">Sell Votes</th>
	<th style="text-align:right">Updated</th>
	</tr>
	</thead>
	<tbody id="asset-full-body">
	<tr><td colspan="13" style="text-align:center;padding:40px;color:var(--t3)">Loading…</td></tr>
	</tbody>
	</table>
	</div>
	</div>
	</div>

	<!-- HEATMAP VIEW (hidden by default) -->
	<div id="asset-heatmap-view" style="display:none">
	<div class="panel">
	<div class="panel-hd">
	<div class="panel-hd-left">
	<div class="panel-hd-pip" style="background:var(--amber)"></div>
	<span class="panel-hd-label">Asset Performance Heatmap</span>
	</div>
	<span class="panel-hd-meta">Relative metric intensity across all assets</span>
	</div>
	<div id="asset-heatmap-grid" style="padding:var(--sp-xl);display:flex;flex-direction:column;gap:10px">
	<div style="text-align:center;padding:40px;color:var(--t3)">Loading heatmap…</div>
	</div>
	</div>
	</div>

	<!-- ASSET DEEP DIVE PANEL (appears on card click) -->
	<div id="asset-deep-dive" style="display:none">
	<div class="panel" style="border-color:var(--glass-edge)">
	<div class="panel-hd" style="background:rgba(0,200,255,0.05)">
	<div class="panel-hd-left">
	<div class="panel-hd-pip" style="background:var(--cyan)"></div>
	<span class="panel-hd-label" id="dive-title">Asset Deep Dive</span>
	</div>
	<button onclick="closeDeepDive()" style="background:rgba(255,255,255,0.08);border:1px solid rgba(255,255,255,0.15);border-radius:var(--elem-r);color:var(--t2);font-size:0.7rem;font-weight:700;padding:6px 14px;cursor:pointer;letter-spacing:0.08em">✕ CLOSE</button>
	</div>
	<div style="display:grid;grid-template-columns:1fr 1fr 1fr;gap:var(--sp-xl);padding:var(--sp-xl)" id="dive-stats">
	</div>
	<div style="display:grid;grid-template-columns:1fr 1fr;gap:var(--sp-lg);padding:0 var(--sp-xl) var(--sp-xl)">
	<div>
	<div style="font-size:0.65rem;font-weight:800;letter-spacing:0.18em;color:var(--t3);text-transform:uppercase;margin-bottom:var(--sp-sm)">Actor Loss History</div>
	<canvas id="dive-loss-chart" style="width:100%;height:120px"></canvas>
	</div>
	<div>
	<div style="font-size:0.65rem;font-weight:800;letter-spacing:0.18em;color:var(--t3);text-transform:uppercase;margin-bottom:var(--sp-sm)">AVN Accuracy History</div>
	<canvas id="dive-acc-chart" style="width:100%;height:120px"></canvas>
	</div>
	</div>
	</div>
	</div>

	</div>

	<div id="trading-tab" class="tab-panel">

	<!-- TRADING KPI ROW -->
	<div id="trade-kpi-row" style="display:grid;grid-template-columns:repeat(4,1fr);gap:var(--sp-lg);">
	<div class="panel kpi" style="--accent:var(--green)">
	<div class="kpi-k">Active Buy Signals</div>
	<div class="kpi-v c-green" id="t-kpi-buys">—</div>
	<div class="kpi-sub" id="t-kpi-buys-sub">across monitored assets</div>
	</div>
	<div class="panel kpi">
	<div class="kpi-k">Active Sell Signals</div>
	<div class="kpi-v" style="color:var(--red);text-shadow:0 0 20px rgba(255,61,90,0.3)" id="t-kpi-sells">—</div>
	<div class="kpi-sub" id="t-kpi-sells-sub">across monitored assets</div>
	</div>
	<div class="panel kpi">
	<div class="kpi-k">Top Conviction Asset</div>
	<div class="kpi-v c-cyan" id="t-kpi-top" style="font-size:1.6rem!important">—</div>
	<div class="kpi-sub" id="t-kpi-top-conf">confidence: —</div>
	</div>
	<div class="panel kpi">
	<div class="kpi-k">Bull / Bear Ratio</div>
	<div class="kpi-v" id="t-kpi-ratio">—</div>
	<div class="kpi-sub" id="t-kpi-ratio-sub">ensemble vote split</div>
	</div>
	</div>

	<!-- SIGNAL COMMAND CENTRE -->
	<div class="panel">
	<div class="panel-hd">
	<div class="panel-hd-left">
	<div class="panel-hd-pip" style="background:var(--green);box-shadow:0 0 10px var(--green-glow)"></div>
	<span class="panel-hd-label">Signal Command Centre</span>
	</div>
	<span class="panel-hd-meta" id="t-signal-meta">awaiting data…</span>
	</div>
	<table id="trade-signal-table" style="width:100%;border-collapse:collapse">
	<thead>
	<tr>
	<th style="width:50px;text-align:center">RNK</th>
	<th>Asset</th>
	<th>Direction</th>
	<th style="text-align:right">Confidence</th>
	<th style="text-align:right">Bull Votes</th>
	<th style="text-align:right">Bear Votes</th>
	<th style="text-align:right">Total Votes</th>
	<th style="text-align:right">Score</th>
	<th>Shreve Gate</th>
	<th style="text-align:right">Updated</th>
	</tr>
	</thead>
	<tbody id="trade-signal-body">
	<tr><td colspan="10" style="text-align:center;padding:40px;color:var(--t3)">Awaiting signal stream…</td></tr>
	</tbody>
	</table>
	</div>

	<!-- OPEN POSITIONS + LIVE FEED ROW -->
	<div style="display:grid;grid-template-columns:1.5fr 1fr;gap:var(--sp-lg)">

	<!-- OPEN POSITIONS -->
	<div class="panel">
	<div class="panel-hd">
	<div class="panel-hd-left">
	<div class="panel-hd-pip" style="background:var(--cyan);box-shadow:0 0 10px var(--cyan-glow)"></div>
	<span class="panel-hd-label">Open Positions Monitor</span>
	</div>
	<span class="panel-hd-meta" id="t-pos-meta">—</span>
	</div>
	<table style="width:100%;border-collapse:collapse">
	<thead>
	<tr>
	<th>Asset</th>
	<th>Side</th>
	<th style="text-align:right">Conf %</th>
	<th style="text-align:right">AVN Acc</th>
	<th style="text-align:right">Score</th>
	<th>Gate Status</th>
	</tr>
	</thead>
	<tbody id="trade-positions-body">
	<tr><td colspan="6" style="text-align:center;padding:30px;color:var(--t3)">No active positions</td></tr>
	</tbody>
	</table>
	</div>

	<!-- ENSEMBLE VOTE BREAKDOWN -->
	<div class="panel" style="display:flex;flex-direction:column">
	<div class="panel-hd">
	<div class="panel-hd-left">
	<div class="panel-hd-pip" style="background:var(--amber);box-shadow:0 0 10px var(--amber-glow)"></div>
	<span class="panel-hd-label">Ensemble Vote Breakdown</span>
	</div>
	</div>
	<div id="vote-breakdown" style="padding:var(--sp-lg);flex:1;display:flex;flex-direction:column;gap:12px;overflow-y:auto;max-height:340px">
	<div style="text-align:center;color:var(--t3);padding:40px 0">Awaiting ensemble data…</div>
	</div>
	</div>

	</div>

	<!-- EXECUTION GATES STATUS -->
	<div class="panel">
	<div class="panel-hd">
	<div class="panel-hd-left">
	<div class="panel-hd-pip" style="background:var(--amber);box-shadow:0 0 10px var(--amber-glow)"></div>
	<span class="panel-hd-label">Execution Gate Monitor</span>
	</div>
	<span class="panel-hd-meta">Shreve v6 — Gates A–E</span>
	</div>
	<div id="gate-monitor" style="display:grid;grid-template-columns:repeat(5,1fr);gap:var(--sp-md);padding:var(--sp-xl)">
	<!-- Gates rendered by JS -->
	</div>
	</div>

	<!-- LIVE OPERATION FEED (TRADING) -->
	<div class="panel">
	<div class="panel-hd">
	<div class="panel-hd-left">
	<div class="panel-hd-pip" style="background:var(--cyan);box-shadow:0 0 10px var(--cyan-glow)"></div>
	<span class="panel-hd-label">Live Operation Feed</span>
	</div>
	<span class="panel-hd-meta" id="t-feed-meta">streaming…</span>
	</div>
	<div class="feed-cols hd">
	<span>Asset / Timestamp</span>
	<span>Vector</span>
	<span style="text-align:right">Confidence</span>
	</div>
	<div id="trade-feed-body" style="max-height:260px;overflow-y:auto">
	<div class="feed-cols row"><div class="f-info"><span class="f-asset" style="color:var(--t4)">Standing by…</span></div></div>
	</div>
	</div>

	</div>

	<div id="telemetry-tab" class="tab-panel">
	<div class="panel">
	<div class="panel-hd">
	<div class="panel-hd-left">
	<div class="panel-hd-pip"></div>
	<span class="panel-hd-label">System Telemetry</span>
	</div>
	</div>
	<div style="padding: var(--sp-xl); color: var(--t3); text-align: center;">
	Telemetry panel — coming soon
	</div>
	</div>
	</div>

	<!-- ════════════════════════════════════════════════════════════════════
	MT5-STYLE TRADE TERMINAL
	Polls /api/trades every 2s — shows live open positions with
	running P&L, closed trades history, and equity curve.
	Data source: ranker log files parsed server-side.
	═════════════════════════════════════════════════════════════════════ -->
	<div id="terminal-tab" class="tab-panel">

	<!-- Equity summary strip -->
	<div id="terminal-kpi-row" style="display:grid;grid-template-columns:repeat(5,1fr);gap:var(--sp-lg);margin-bottom:var(--sp-lg)">
	<div class="panel kpi" style="border-color:rgba(232,114,10,0.25)">
	<div class="kpi-k">Equity</div>
	<div class="kpi-v" id="trm-equity" style="color:#E8720A;text-shadow:0 0 20px rgba(232,114,10,0.4)">—</div>
	<div class="kpi-sub">running balance</div>
	</div>
	<div class="panel kpi">
	<div class="kpi-k">Open P&L</div>
	<div class="kpi-v" id="trm-open-pnl">—</div>
	<div class="kpi-sub" id="trm-open-count">0 positions</div>
	</div>
	<div class="panel kpi">
	<div class="kpi-k">Realized P&L</div>
	<div class="kpi-v" id="trm-realized-pnl">—</div>
	<div class="kpi-sub" id="trm-closed-count">0 closed trades</div>
	</div>
	<div class="panel kpi">
	<div class="kpi-k">Win Rate</div>
	<div class="kpi-v c-cyan" id="trm-winrate">—</div>
	<div class="kpi-sub" id="trm-wl">W:0 / L:0</div>
	</div>
	<div class="panel kpi">
	<div class="kpi-k">Avg P&L / Trade</div>
	<div class="kpi-v" id="trm-avg-pnl">—</div>
	<div class="kpi-sub">per closed trade</div>
	</div>
	</div>

	<!-- Equity curve -->
	<div class="panel" style="margin-bottom:var(--sp-lg)">
	<div class="panel-hd">
	<div class="panel-hd-left">
	<div class="panel-hd-pip" style="background:#E8720A;box-shadow:0 0 10px rgba(232,114,10,0.5)"></div>
	<span class="panel-hd-label">Equity Curve</span>
	</div>
	<span class="panel-hd-meta" id="trm-curve-meta">—</span>
	</div>
	<div style="padding:var(--sp-lg);height:160px">
	<canvas id="trm-equity-chart"></canvas>
	</div>
	</div>

	<!-- Open Positions -->
	<div class="panel" style="margin-bottom:var(--sp-lg)">
	<div class="panel-hd">
	<div class="panel-hd-left">
	<div class="panel-hd-pip" style="background:var(--green);box-shadow:0 0 10px var(--green-glow)"></div>
	<span class="panel-hd-label">Open Positions</span>
	</div>
	<span class="panel-hd-meta" id="trm-open-meta">live · updates every 2s</span>
	</div>
	<div style="overflow-x:auto">
	<table id="trm-open-table" style="width:100%;border-collapse:collapse">
	<thead>
	<tr id="trm-open-head">
	<th style="padding:10px 16px;text-align:left;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">TRADE ID</th>
	<th style="padding:10px 16px;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">ASSET</th>
	<th style="padding:10px 16px;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">DIR</th>
	<th style="padding:10px 16px;text-align:right;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">ENTRY</th>
	<th style="padding:10px 16px;text-align:right;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">QTY</th>
	<th style="padding:10px 16px;text-align:right;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">OPEN P&L</th>
	<th style="padding:10px 16px;text-align:right;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">DURATION</th>
	<th style="padding:10px 16px;text-align:right;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">OPENED</th>
	</tr>
	</thead>
	<tbody id="trm-open-body">
	<tr><td colspan="8" style="padding:32px;text-align:center;color:var(--t4);font-size:0.75rem">No open positions</td></tr>
	</tbody>
	</table>
	</div>
	</div>

	<!-- Closed Trades History -->
	<div class="panel">
	<div class="panel-hd">
	<div class="panel-hd-left">
	<div class="panel-hd-pip" style="background:var(--t3)"></div>
	<span class="panel-hd-label">Trade History</span>
	</div>
	<span class="panel-hd-meta" id="trm-hist-meta">last 100 closed trades</span>
	</div>
	<div style="overflow-x:auto;max-height:420px;overflow-y:auto">
	<table id="trm-hist-table" style="width:100%;border-collapse:collapse">
	<thead style="position:sticky;top:0;background:rgba(0,8,20,0.95);backdrop-filter:blur(8px)">
	<tr>
	<th style="padding:10px 16px;text-align:left;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">TRADE ID</th>
	<th style="padding:10px 16px;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">ASSET</th>
	<th style="padding:10px 16px;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">DIR</th>
	<th style="padding:10px 16px;text-align:right;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">ENTRY</th>
	<th style="padding:10px 16px;text-align:right;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">EXIT</th>
	<th style="padding:10px 16px;text-align:right;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">QTY</th>
	<th style="padding:10px 16px;text-align:right;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">P&L</th>
	<th style="padding:10px 16px;text-align:right;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">DURATION</th>
	<th style="padding:10px 16px;text-align:right;font-size:0.6rem;font-weight:800;letter-spacing:0.16em;color:var(--t3);border-bottom:1px solid rgba(255,255,255,0.05)">CLOSED</th>
	</tr>
	</thead>
	<tbody id="trm-hist-body">
	<tr><td colspan="9" style="padding:32px;text-align:center;color:var(--t4);font-size:0.75rem">No trade history</td></tr>
	</tbody>
	</table>
	</div>
	</div>

	</div><!-- /terminal-tab -->

	</main>
	</div>

	<script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script>
	<script>

	/* ════════════════════════════════════════════════════════════════════════════
	LAYER 1A — ORIGINAL 2D PARTICLE CANVAS (restored exactly)
	Soft grid + floating cyan dots + proximity lines — the original ambient layer
	════════════════════════════════════════════════════════════════════════════ */
	(function () {
	const cv = document.getElementById('bg-canvas'); const cx = cv.getContext('2d');
	let W, H, pts = [];
	function resize() { W = cv.width = window.innerWidth; H = cv.height = window.innerHeight; }
	function init() {
	pts = []; const n = Math.floor(W * H / 18000);
	for (let i = 0; i < n; i++) {
	pts.push({ x: Math.random() * W, y: Math.random() * H, vx: (Math.random() - .5) * .2, vy: (Math.random() - .5) * .2, r: Math.random() * 1.5 + .5, a: Math.random() * .5 + .2, ph: Math.random() * Math.PI * 2 });
	}
	}
	function frame(t) {
	cx.clearRect(0, 0, W, H);
	cx.strokeStyle = 'rgba(255,255,255,0.02)'; cx.lineWidth = .5;
	for (let x = 0; x < W; x += 100) { cx.beginPath(); cx.moveTo(x,0); cx.lineTo(x,H); cx.stroke(); }
	for (let y = 0; y < H; y += 100) { cx.beginPath(); cx.moveTo(0,y); cx.lineTo(W,y); cx.stroke(); }
	for (const p of pts) {
	p.x += p.vx; p.y += p.vy;
	if (p.x < 0 \|\| p.x > W) p.vx = -1; if (p.y < 0 \|\| p.y > H) p.vy = -1;
	}
	const D = 150;
	for (let i = 0; i < pts.length; i++) {
	for (let j = i + 1; j < pts.length; j++) {
	const dx = pts[i].x - pts[j].x, dy = pts[i].y - pts[j].y;
	const d = Math.sqrt(dxdx + dydy);
	if (d < D) { cx.strokeStyle = `rgba(0,200,255,${(1 - d/D) * .15})`; cx.lineWidth = .5; cx.beginPath(); cx.moveTo(pts[i].x, pts[i].y); cx.lineTo(pts[j].x, pts[j].y); cx.stroke(); }
	}
	}
	for (const p of pts) {
	const pulse = Math.sin(t * .001 + p.ph) * .3 + .7;
	cx.beginPath(); cx.arc(p.x, p.y, p.r, 0, Math.PI2); cx.fillStyle = `rgba(0,200,255,${p.a pulse})`; cx.fill();
	}
	requestAnimationFrame(frame);
	}
	window.addEventListener('resize', () => { resize(); init(); });
	resize(); init(); requestAnimationFrame(frame);
	})();

	/* ════════════════════════════════════════════════════════════════════════════
	LAYER 1B — THREE.JS ASTROPHYSICS NEURAL NETWORK
	─────────────────────────────────────────────────────────────────────────
	Physics model (Harvard-grade N-body astrophysics):

	1. GRAVITATIONAL POTENTIAL — F = G·m₁·m₂/r² (softened: r²+ε)
	Each node has a real mass. Heavier nodes curve the field more.

	2. LENNARD-JONES POTENTIAL — V(r) = 4ε[(σ/r)¹² − (σ/r)⁶]
	Short-range repulsion (r¹²) + medium-range attraction (r⁶).
	Nodes settle at the potential well minimum: r = 2^(1/6)·σ
	Identical to how noble gas atoms self-organise — equilibrium
	separation emerges naturally, no hardcoded spring rest length.

	3. MAXWELL-BOLTZMANN initial velocities
	v drawn from MB distribution at "temperature" T.
	Fast nodes = hot, bright, large halos (stellar analogy).
	Cold nodes = slow, dim, tight.

	4. ANGULAR MOMENTUM SEED
	System initialized with net angular momentum L = Σ mᵢ(rᵢ×vᵢ).
	Creates emergent galactic-disc rotation — network slowly rotates
	like a spiral galaxy, no forced spin.

	5. TIDAL DISRUPTION / STELLAR WIND
	Mouse cursor acts as a massive perturber (m_perturber >> m_node).
	Nearby nodes experience tidal stretching along the radial axis —
	not just uniform repulsion. Realistic gravitational slingshot paths.

	6. ORBITAL RESONANCE dampening
	Velocity-dependent drag scaled by local density — denser regions
	damp faster (inter-particle collisions), sparse regions retain energy.

	Node colours: #00D4FF electric cyan (55%) — O/B-type hot blue stars
	#E8720A solar orange (30%) — G/K-type solar stars
	#7AB4FF deep blue (15%) — A-type white-blue stars
	════════════════════════════════════════════════════════════════════════════ */
	(function () {
	const canvas = document.getElementById('three-canvas');
	if (!canvas \|\| typeof THREE === 'undefined') return;

	const isMobile = window.innerWidth <= 768;

	const renderer = new THREE.WebGLRenderer({
	canvas, antialias: !isMobile, alpha: true,
	powerPreference: 'high-performance'
	});
	renderer.setSize(window.innerWidth, window.innerHeight);
	renderer.setPixelRatio(Math.min(window.devicePixelRatio, isMobile ? 1.5 : 2));
	renderer.setClearColor(0x000000, 0);

	const scene = new THREE.Scene();
	scene.fog = new THREE.FogExp2(0x02040a, 0.00022); // less fog — deep space

	const camera = new THREE.PerspectiveCamera(58, window.innerWidth / window.innerHeight, 1, 4000);
	camera.position.set(0, 60, 520);
	camera.lookAt(0, -10, 0);

	// ── Starfield — two populations (bright nearby + faint distant) ──────
	function makeStars(count, spread, size, opacity, col) {
	const geo = new THREE.BufferGeometry();
	const pos = new Float32Array(count * 3);
	for (let i = 0; i < count * 3; i += 3) {
	// Gaussian clustering — stars clump like real galaxies
	const r = spread * Math.sqrt(-2 * Math.log(Math.random() + 1e-9));
	const theta = Math.random() * Math.PI * 2;
	const phi = Math.random() * Math.PI;
	pos[i] = r * Math.sin(phi) * Math.cos(theta);
	pos[i+1] = r * Math.sin(phi) * Math.sin(theta) * 0.4; // disc flattening
	pos[i+2] = r * Math.cos(phi);
	}
	geo.setAttribute('position', new THREE.BufferAttribute(pos, 3));
	scene.add(new THREE.Points(geo, new THREE.PointsMaterial({
	color: col, size, transparent: true, opacity, sizeAttenuation: true
	})));
	}
	makeStars(isMobile ? 400 : 900, 1800, 1.1, 0.7, 0xd0e8ff); // bright nearby
	makeStars(isMobile ? 600 : 1400, 3200, 0.6, 0.3, 0x8ab0cc); // faint background

	// ── Node setup ───────────────────────────────────────────────────────
	const N = isMobile ? 60 : 100;

	// Physical constants (dimensionless but physically motivated)
	const G = 18.0; // gravitational constant
	const LJ_EPS = 55.0; // Lennard-Jones well depth (attraction strength)
	const LJ_SIGMA = 88.0; // LJ equilibrium separation scale
	const LJ_RCUT = LJ_SIGMA * 2.8; // cutoff radius — beyond this LJ ≈ 0
	const GRAV_RCUT = 380.0; // gravity cutoff — long-range only
	const SOFT_SQ = 180.0; // gravitational softening ε² (prevents singularity)
	const kT = 0.8; // thermal energy (Maxwell-Boltzmann temperature)
	const DAMPING = 0.9965; // velocity damping per frame (~viscous ISM)
	const MAX_V = 3.2;
	const BOUND_R = 480.0; // hard boundary
	const CONNECT_D = 145.0; // edge drawn if distance < this
	const MAX_CONN = 7;

	// Stellar spectral types mapped to colours
	// Type O/B — hot, blue, #00D4FF — massive, fast, bright
	// Type G/K — solar, orange #E8720A — medium mass, moderate speed
	// Type A — blue-white #7AB4FF — light, fast
	const STELLAR_TYPES = [
	{ r:0.000, g:0.831, b:1.000, massMin:0.8, massMax:2.2, Tfrac:1.4, frac:0.55 }, // O/B cyan
	{ r:0.910, g:0.447, b:0.039, massMin:0.5, massMax:1.3, Tfrac:0.8, frac:0.30 }, // G/K orange #E8720A
	{ r:0.478, g:0.706, b:1.000, massMin:0.4, massMax:0.9, Tfrac:1.1, frac:0.15 }, // A blue-white
	];

	// Maxwell-Boltzmann speed sample: \|v\| ~ sqrt(-2kT/m * ln(u))
	function mbSpeed(mass, temperature) {
	const u = Math.max(1e-10, Math.random());
	return Math.sqrt(-2.0 * temperature * kT / mass * Math.log(u));
	}

	// Assign stellar type by cumulative fraction
	function pickType() {
	const r = Math.random();
	let cum = 0;
	for (const t of STELLAR_TYPES) { cum += t.frac; if (r < cum) return t; }
	return STELLAR_TYPES[0];
	}

	const nodePositions = new Float32Array(N * 3);
	const nodeSizes = new Float32Array(N);
	const nodeColors = new Float32Array(N * 3);

	// nodes[] holds the mutable physics state
	const nodes = [];
	// Seed system angular momentum — galaxy-like disc rotation
	const SPIN_AXIS = new THREE.Vector3(0.15, 1.0, 0.08).normalize();
	const L_SEED = 0.22; // angular momentum per unit mass

	for (let i = 0; i < N; i++) {
	const i3 = i * 3;
	const type = pickType();

	// Position: uniform sphere with slight disc flattening (like a galaxy)
	const u = Math.random(), v = Math.random();
	const theta = 2 * Math.PI * u;
	const phi = Math.acos(2 * v - 1);
	const rMin = 140, rMax = BOUND_R * 0.88;
	const radius = rMin + Math.pow(Math.random(), 0.6) * (rMax - rMin);
	const x = radius * Math.sin(phi) * Math.cos(theta);
	const y = radius * Math.sin(phi) * Math.sin(theta) * 0.55; // disc compression
	const z = radius * Math.cos(phi);

	nodePositions[i3] = x;
	nodePositions[i3+1] = y;
	nodePositions[i3+2] = z;

	const mass = type.massMin + Math.random() * (type.massMax - type.massMin);
	nodeSizes[i] = (isMobile ? 2.2 : 3.2) * mass;

	// Color + small per-node spectral variation (stellar metallicity analogy)
	const jitter = 0.04;
	nodeColors[i3] = Math.min(1, type.r + (Math.random()-0.5)*jitter);
	nodeColors[i3+1] = Math.min(1, type.g + (Math.random()-0.5)*jitter);
	nodeColors[i3+2] = Math.min(1, type.b + (Math.random()-0.5)*jitter);

	// Maxwell-Boltzmann velocity + angular momentum seed
	const speed = mbSpeed(mass, type.Tfrac);
	// Thermal random direction
	const vTheta = Math.random() * Math.PI * 2;
	const vPhi = Math.acos(2 * Math.random() - 1);
	let vx = speed * Math.sin(vPhi) * Math.cos(vTheta);
	let vy = speed * Math.sin(vPhi) * Math.sin(vPhi);
	let vz = speed * Math.cos(vPhi);

	// Add angular momentum component: v_rot = L × r / \|r\|
	// This seeds net rotation around SPIN_AXIS
	const rVec = new THREE.Vector3(x, y, z);
	const rotV = new THREE.Vector3().crossVectors(SPIN_AXIS, rVec);
	const rotMag = rotV.length();
	if (rotMag > 1) {
	rotV.multiplyScalar(L_SEED / rotMag);
	vx += rotV.x; vy += rotV.y; vz += rotV.z;
	}

	nodes.push({ x, y, z, vx, vy, vz, mass, connections: [], energy: 0, density: 0 });
	}

	const nodeGeo = new THREE.BufferGeometry();
	nodeGeo.setAttribute('position', new THREE.BufferAttribute(nodePositions, 3));
	nodeGeo.setAttribute('size', new THREE.BufferAttribute(nodeSizes, 1));
	nodeGeo.setAttribute('color', new THREE.BufferAttribute(nodeColors, 3));

	// Shader — stellar glow: corona + photosphere + chromosphere rings
	const nodeMat = new THREE.ShaderMaterial({
	uniforms: {
	time: { value: 0 },
	pixelRatio:{ value: renderer.getPixelRatio() }
	},
	vertexShader: `
	attribute float size;
	attribute vec3 color;
	varying vec3 vColor;
	varying float vEnergy; /* encoded in size.w for now */
	uniform float time;
	uniform float pixelRatio;

	void main() {
	vColor = color;
	vec4 mvPos = modelViewMatrix * vec4(position, 1.0);

	/* Stellar pulsation — each node has unique phase from world pos */
	float phase = position.x * 0.0071 + position.y * 0.0053 + position.z * 0.0061;
	float pulsate = 1.0 + 0.16 * sin(time * 2.1 + phase)
	+ 0.06 * sin(time * 5.3 + phase * 2.0); /* harmonics */

	gl_PointSize = size * pulsate * pixelRatio * (310.0 / -mvPos.z);
	gl_Position = projectionMatrix * mvPos;
	}`,
	fragmentShader: `
	varying vec3 vColor;

	void main() {
	vec2 c = gl_PointCoord - 0.5;
	float d = length(c);
	if (d > 0.5) discard;

	/* Photosphere: solid bright disc */
	float photo = 1.0 - smoothstep(0.0, 0.09, d);
	/* Chromosphere: mid-range emission ring */
	float chrom = exp(-d * 6.5) * 1.1;
	/* Corona: wide diffuse halo — falls off as stellar corona */
	float corona = exp(-d * 2.6) * 0.7;
	/* Limb darkening: edges slightly dimmer than centre (physical) */
	float limb = 1.0 - 0.28 * smoothstep(0.0, 0.09, d);

	float a = clamp(photo * 1.8 * limb + chrom + corona, 0.0, 1.0);

	/* White-hot photosphere core → pure colour chromosphere → dimmer corona */
	vec3 hotWhite = vec3(1.0, 0.97, 0.93);
	vec3 col = mix(vColor, hotWhite, photo * limb * 0.72);
	col += vColor * chrom * 0.55;
	col += vColor * corona * 0.28;

	gl_FragColor = vec4(col, a);
	}`,
	transparent: true, depthWrite: false, blending: THREE.AdditiveBlending
	});

	scene.add(new THREE.Points(nodeGeo, nodeMat));

	// Connection lines — energy-scaled opacity
	const maxLines = N * MAX_CONN;
	const linePos = new Float32Array(maxLines * 6);
	const lineCol = new Float32Array(maxLines * 6);
	const lineGeo = new THREE.BufferGeometry();
	lineGeo.setAttribute('position', new THREE.BufferAttribute(linePos, 3));
	lineGeo.setAttribute('color', new THREE.BufferAttribute(lineCol, 3));
	const lineMat = new THREE.LineBasicMaterial({
	vertexColors: true, transparent: true, opacity: 0.65,
	blending: THREE.AdditiveBlending
	});
	scene.add(new THREE.LineSegments(lineGeo, lineMat));

	// ── Spatial hash for O(N) neighbor lookup ────────────────────────────
	function buildHash(cellSize) {
	const h = {};
	for (let i = 0; i < N; i++) {
	const n = nodes[i];
	const k = `${Math.floor(n.x/cellSize)},${Math.floor(n.y/cellSize)},${Math.floor(n.z/cellSize)}`;
	if (!h[k]) h[k] = [];
	h[k].push(i);
	}
	return h;
	}
	function getNeighbors(x, y, z, cs, hash) {
	const cx=Math.floor(x/cs), cy=Math.floor(y/cs), cz=Math.floor(z/cs);
	const out = [];
	for (let dx=-1;dx<=1;dx++) for(let dy=-1;dy<=1;dy++) for(let dz=-1;dz<=1;dz++) {
	const c = hash[`${cx+dx},${cy+dy},${cz+dz}`];
	if (c) for (const id of c) out.push(id);
	}
	return out;
	}

	// Mouse — perturber with tidal stretching
	const mouse = { x:0, y:0, z:0, active:false, mass: 800 };
	const raycaster = new THREE.Raycaster();
	const mouse2D = new THREE.Vector2();

	function onMove(e) {
	mouse2D.x = (e.clientX/innerWidth)*2-1;
	mouse2D.y = -((e.clientY/innerHeight)*2-1);
	raycaster.setFromCamera(mouse2D, camera);
	const plane = new THREE.Plane().setFromNormalAndCoplanarPoint(
	new THREE.Vector3(0,0,1), new THREE.Vector3(0,0,-80));
	const pt = new THREE.Vector3();
	if (raycaster.ray.intersectPlane(plane, pt)) {
	mouse.x=pt.x; mouse.y=pt.y; mouse.z=pt.z; mouse.active=true;
	}
	}
	document.addEventListener('mousemove', onMove);
	document.addEventListener('mouseleave', ()=>{ mouse.active=false; });
	document.addEventListener('touchmove', e=>{ if(e.touches[0]) onMove(e.touches[0]); },{passive:true});
	document.addEventListener('touchend', ()=>{ mouse.active=false; });

	// ── Physics step ─────────────────────────────────────────────────────
	function step(dt) {
	dt = Math.min(dt, 0.028); // sub-step cap for stability

	const csLJ = LJ_RCUT;
	const csGrav = GRAV_RCUT * 0.5;
	const hashLJ = buildHash(csLJ);
	const hashGrav = buildHash(csGrav);

	for (let i = 0; i < N; i++) nodes[i].connections = [];

	for (let i = 0; i < N; i++) {
	const ni = nodes[i];
	let fx=0, fy=0, fz=0;
	let localDensity = 0;

	// ── 1. LENNARD-JONES (short/medium range) ──────────────────
	const ljNeighbors = getNeighbors(ni.x, ni.y, ni.z, csLJ, hashLJ);
	for (const j of ljNeighbors) {
	if (j === i) continue;
	const nj = nodes[j];
	const dx=ni.x-nj.x, dy=ni.y-nj.y, dz=ni.z-nj.z;
	const r2 = dxdx + dydy + dz*dz;
	const r = Math.sqrt(r2);
	if (r < 1 \|\| r > LJ_RCUT) continue;

	// LJ force magnitude: F = 24ε/r * [2(σ/r)¹² − (σ/r)⁶]
	const sr = LJ_SIGMA / r;
	const sr6 = srsrsrsrsr*sr;
	const sr12= sr6 * sr6;
	const Flj = (24.0 * LJ_EPS / r2) * (2.0*sr12 - sr6);

	fx += (dx/r) * Flj / ni.mass;
	fy += (dy/r) * Flj / ni.mass;
	fz += (dz/r) * Flj / ni.mass;

	// Track local density (= # neighbours within LJ range)
	if (r < LJ_SIGMA * 1.8) localDensity++;

	// Connection edges form near LJ equilibrium
	if (r < CONNECT_D && ni.connections.length < MAX_CONN)
	if (!ni.connections.includes(j)) ni.connections.push(j);
	}

	// ── 2. NEWTONIAN GRAVITY (long range, all pairs via hash) ──
	const gravNeighbors = getNeighbors(ni.x, ni.y, ni.z, csGrav, hashGrav);
	for (const j of gravNeighbors) {
	if (j === i) continue;
	const nj = nodes[j];
	const dx=nj.x-ni.x, dy=nj.y-ni.y, dz=nj.z-ni.z;
	const r2soft = dxdx + dydy + dz*dz + SOFT_SQ;
	const r = Math.sqrt(r2soft);
	// F_grav = G * m_i * m_j / (r² + ε²) — softened
	const Fg = G * ni.mass * nj.mass / r2soft;
	fx += (dx/r) * Fg / ni.mass;
	fy += (dy/r) * Fg / ni.mass;
	fz += (dz/r) * Fg / ni.mass;
	}

	// ── 3. TIDAL MOUSE PERTURBATION ────────────────────────────
	if (mouse.active) {
	const mdx=mouse.x-ni.x, mdy=mouse.y-ni.y, mdz=mouse.z-ni.z;
	const mr2soft = mdxmdx + mdymdy + mdzmdz + SOFT_SQ 4;
	const mr = Math.sqrt(mr2soft);
	if (mr < 320) {
	// Gravitational attraction toward perturber
	const Fm = G * mouse.mass * ni.mass / mr2soft;
	fx += (mdx/mr) * Fm / ni.mass;
	fy += (mdy/mr) * Fm / ni.mass;
	fz += (mdz/mr) * Fm / ni.mass;

	// Tidal stretching — differential gravity across node extent
	// F_tidal ∝ -2(δr·r̂)r̂/r³ (quadrupole term)
	const tidalStr = -1.8 * G * mouse.mass / (mr2soft * mr);
	const rdotR = (mdxni.vx + mdyni.vy + mdz*ni.vz);
	fx += tidalStr * (mdx/mr) * rdotR * 0.12;
	fy += tidalStr * (mdy/mr) * rdotR * 0.12;
	fz += tidalStr * (mdz/mr) * rdotR * 0.12;
	}
	}

	// ── 4. BOUNDARY — soft spherical potential ─────────────────
	const dc = Math.sqrt(ni.xni.x + ni.yni.y + ni.z*ni.z);
	if (dc > BOUND_R && dc > 0.01) {
	// Quadratic restoring force — like a harmonic potential well
	const ov = dc - BOUND_R;
	const Fbnd = 0.012 * ov * ov / dc;
	fx -= ni.x * Fbnd; fy -= ni.y * Fbnd; fz -= ni.z * Fbnd;
	}

	// ── 5. DENSITY-DEPENDENT DRAG (orbital resonance damping) ──
	// Denser regions damp faster — mimics gas drag in star clusters
	const localDamping = Math.pow(DAMPING, 1.0 + localDensity * 0.08);
	ni.density = localDensity;

	// Integrate: velocity Verlet step
	ni.vx = (ni.vx + fx * dt) * localDamping;
	ni.vy = (ni.vy + fy * dt) * localDamping;
	ni.vz = (ni.vz + fz * dt) * localDamping;

	// Speed limit (relativistic analogy — no faster than c_sim)
	const spd = Math.sqrt(ni.vxni.vx + ni.vyni.vy + ni.vz*ni.vz);
	if (spd > MAX_V) { const sc=MAX_V/spd; ni.vx=sc; ni.vy=sc; ni.vz*=sc; }

	ni.energy = 0.5 * ni.mass * spd * spd; // kinetic energy (for glow scaling)
	}

	// Update positions
	const pos = nodeGeo.attributes.position.array;
	const sz = nodeGeo.attributes.size.array;
	for (let i = 0; i < N; i++) {
	const n = nodes[i], i3 = i*3;
	n.x += n.vx * dt * 60; // scale by 60 so dt=1/60 gives unit displacement
	n.y += n.vy * dt * 60;
	n.z += n.vz * dt * 60;
	pos[i3]=n.x; pos[i3+1]=n.y; pos[i3+2]=n.z;

	// Hot/fast nodes glow larger — kinetic temperature → apparent brightness
	const thermalBoost = 1.0 + Math.min(n.energy * 0.018, 0.7);
	sz[i] = (isMobile?2.2:3.2) * n.mass * thermalBoost + n.connections.length * 0.35;
	}
	nodeGeo.attributes.position.needsUpdate = true;
	nodeGeo.attributes.size.needsUpdate = true;
	}

	// ── Update connection lines ───────────────────────────────────────────
	function updateLines() {
	let li = 0;
	for (let i = 0; i < N; i++) {
	const ni = nodes[i];
	for (const j of ni.connections) {
	if (j > i) continue;
	const nj = nodes[j];
	const dx=nj.x-ni.x, dy=nj.y-ni.y, dz=nj.z-ni.z;
	const dist = Math.sqrt(dxdx+dydy+dz*dz);
	const idx = li*6;
	linePos[idx]=ni.x; linePos[idx+1]=ni.y; linePos[idx+2]=ni.z;
	linePos[idx+3]=nj.x; linePos[idx+4]=nj.y; linePos[idx+5]=nj.z;

	// Line brightness: inverse-square of distance (like EM radiation flux)
	const flux = Math.pow(1.0 - dist/CONNECT_D, 1.6);
	const nc = nodeColors;
	// Blend endpoint colors — connection "heats" near hot nodes
	const r = (nc[i3] +nc[j3]) 0.5 flux * 1.1;
	const g = (nc[i3+1]+nc[j3+1])0.5 flux * 1.1;
	const b = (nc[i3+2]+nc[j3+2])0.5 flux * 1.1;
	lineCol[idx]=r; lineCol[idx+1]=g; lineCol[idx+2]=b;
	lineCol[idx+3]=r; lineCol[idx+4]=g; lineCol[idx+5]=b;
	li++;
	}
	}
	for (let i=li*6; i<linePos.length; i++) { linePos[i]=0; lineCol[i]=0; }
	lineGeo.attributes.position.needsUpdate = true;
	lineGeo.attributes.color.needsUpdate = true;
	lineGeo.setDrawRange(0, li*2);
	}

	// ── Camera — precessing orbital viewpoint ────────────────────────────
	// Camera itself orbits slowly, like a satellite around the system.
	// Inclination precesses over a longer period — realistic observation geometry.
	let camT = 0;
	function driftCamera(dt) {
	camT += dt * 0.048;
	// Primary orbit (azimuthal)
	const az = camT * 0.52;
	// Inclination precession (much slower)
	const inc = 0.22 + 0.12 * Math.sin(camT * 0.11);
	const R = 520;
	camera.position.set(
	R * Math.cos(az) * Math.cos(inc),
	R * Math.sin(inc) + 60,
	R * Math.sin(az) * Math.cos(inc)
	);
	camera.lookAt(0, -10, 0);
	}

	// ── Render loop ───────────────────────────────────────────────────────
	let last = 0;
	function animate(t) {
	requestAnimationFrame(animate);
	const dt = Math.min((t - last) / 1000, 0.045);
	last = t;
	nodeMat.uniforms.time.value = t * 0.001;
	step(dt);
	updateLines();
	driftCamera(dt);
	renderer.render(scene, camera);
	}

	window.addEventListener('resize', () => {
	renderer.setSize(innerWidth, innerHeight);
	camera.aspect = innerWidth / innerHeight;
	camera.updateProjectionMatrix();
	});

	requestAnimationFrame(animate);
	})();

	/* ════════════════════════════════════════════════════════════════════════════
	CHARTS LOGIC
	════════════════════════════════════════════════════════════════════════════ */
	const GR = 'rgba(255,255,255,0.05)';
	const TK = { color:'#8ab0c5', font:{ family:"'Inter',sans-serif", size:11, weight:'500' } };
	const baseOpts = { responsive:true, maintainAspectRatio:false, animation:{ duration:500, easing: 'easeOutExpo' }, layout: { padding: 16 }, plugins:{ legend:{ display:false }, tooltip:{ backgroundColor:'rgba(0,0,0,0.8)', borderColor:'rgba(0,200,255,0.3)', borderWidth:1, titleColor:'#fff', bodyColor:'#d0e2ec', padding:12, cornerRadius:8 } }, scales:{ x:{ ticks:TK, grid:{ color:GR, drawBorder: false } }, y:{ ticks:TK, grid:{ color:GR, drawBorder: false } } } };

	const scoreChart = new Chart(document.getElementById('score-chart'),{ type:'bar', data:{ labels:[], datasets:[{ data:[], borderRadius:6 }] }, options:{ ...baseOpts } });
	const lossChart = new Chart(document.getElementById('loss-chart'),{ type:'line', data:{ labels:[], datasets:[{ data:[], borderColor:'#ff3d5a', backgroundColor:'rgba(255,61,90,0.15)', borderWidth:2, pointRadius:0, tension:.4, fill:true }] }, options:{ ...baseOpts } });
	const accChart = new Chart(document.getElementById('acc-chart'),{ type:'line', data:{ labels:[], datasets:[{ data:[], borderColor:'#00c8ff', backgroundColor:'rgba(0,200,255,0.15)', borderWidth:2, pointRadius:0, tension:.4, fill:true }] }, options:{ ...baseOpts } });

	/* ════════════════════════════════════════════════════════════════════════════
	TAB SWITCHING
	════════════════════════════════════════════════════════════════════════════ */
	function switchTab(evt, tab) {
	document.querySelectorAll('.tab-panel').forEach(p => p.classList.remove('active'));
	document.querySelectorAll('.nav-tab').forEach(t => t.classList.remove('active'));

	const tabEl = document.getElementById(tab + '-tab');
	if (tabEl) {
	tabEl.classList.add('active');
	}

	// Use the explicitly-passed event — never rely on deprecated window.event
	if (evt && evt.currentTarget) evt.currentTarget.classList.add('active');

	if (tab === 'logs') {
	loadRankerLogs();
	loadLogStats();
	} else if (tab === 'rankings') {
	updateCharts();
	} else if (tab === 'trading') {
	renderTradingTab();
	} else if (tab === 'assets') {
	renderAssetsTab();
	} else if (tab === 'terminal') {
	updateTerminal();
	}
	}

	/* ════════════════════════════════════════════════════════════════════════════
	DATA APPLICATION LOGIC
	════════════════════════════════════════════════════════════════════════════ */
	let _rankings=[], _hist={}, _health={}, _logs=[];
	let _sKey='score', _sDir=-1, _sel=null, _lastMsgs=0, _search=''; let _logFilter='all';
	const f4 = v => (v==null)?'—':Number(v).toFixed(4); const fPct = v => (v==null)?'—':(v*100).toFixed(1)+'%';
	const ago = ts => { if(!ts) return '—'; const s=Math.round(Date.now()/1000-ts); return s<60?s+'s ago':s<3600?Math.floor(s/60)+'m ago':Math.floor(s/3600)+'h ago'; };
	const stxt = r => r.signal_confidence>.7 ? '<span style="color:var(--green);font-weight:700;text-shadow:0 0 8px rgba(0,223,138,0.4)">Engaged</span>' : '<span style="color:var(--t3);font-weight:600">Standby</span>';

	function scoreBar(s) {
	const v=parseFloat(s)\|\|0; const p=Math.min(Math.abs(v)*100,100).toFixed(1);
	const c=v>.05?'#00df8a':v<-.05?'#ff3d5a':'#00c8ff';
	return `<div style="display:flex;align-items:center;gap:12px;min-width:120px">
	<div style="flex:1;height:4px;background:rgba(255,255,255,0.1);border-radius:2px;overflow:hidden;box-shadow:inset 0 1px 2px rgba(0,0,0,0.5)">
	<div style="height:100%;width:${p}%;background:${c};border-radius:2px;box-shadow:0 0 8px ${c}"></div>
	</div><span style="font-size:0.8rem;font-weight:700;min-width:60px;text-align:right">${f4(v)}</span></div>`;
	}

	function renderTable(){
	const sorted=[..._rankings].sort((a,b)=>{ const av=a[_sKey],bv=b[_sKey]; return typeof av==='string'?_sDirav.localeCompare(bv):_sDir(bv-av); });
	const rows=_search?sorted.filter(r=>r.space_name.toLowerCase().includes(_search)):sorted;
	document.getElementById('rank-meta').textContent=rows.length+' targets tracked';
	const tb=document.getElementById('rankings-body');
	if(!rows.length){ tb.innerHTML='<tr><td colspan="9" style="padding:40px;text-align:center;color:var(--t3)">No targets match</td></tr>'; return; }
	tb.innerHTML=rows.map((r,i)=>{
	const rk=i+1; const rcls=rk===1?'r1':''; const sel=_sel===r.space_name?'sel':'';
	return `<tr class="${sel} ${rcls}" onclick="onRow('${r.space_name}',this)">
	<td class="rc">${rk}</td><td class="nc">${r.space_name}</td><td>${scoreBar(r.score)}</td>
	<td class="num">${fPct(r.signal_confidence)}</td><td class="num">${fPct(r.avn_accuracy)}</td>
	<td><span class="sig ${r.dominant_signal}">${r.dominant_signal}</span></td>
	<td class="num">${(r.training_steps\|\|0).toLocaleString()}</td><td class="num">${f4(r.actor_loss)}</td>
	<td>${stxt(r)}</td></tr>`;
	}).join('');
	}

	function filterTable(v){ _search=v.toLowerCase().trim(); renderTable(); }
	function sortBy(k){ _sKey===k?_sDir*=-1:(_sKey=k,_sDir=-1); document.querySelectorAll('th.sorted').forEach(t=>t.classList.remove('sorted')); renderTable(); }

	function onRow(name,el){
	const dp=document.getElementById('detail-panel');
	if(_sel===name){ _sel=null; dp.classList.remove('open'); document.querySelectorAll('tbody tr.sel').forEach(t=>t.classList.remove('sel')); return; }
	_sel=name; document.querySelectorAll('tbody tr.sel').forEach(t=>t.classList.remove('sel')); el.classList.add('sel');
	const r=_rankings.find(x=>x.space_name===name); if(!r){dp.classList.remove('open');return;}
	dp.innerHTML=`
	<div><div class="dc-title">Deep Learning Matrix</div>
	<div class="dr"><span class="dk">Training Cycles</span><span class="dv c">${(r.training_steps\|\|0).toLocaleString()}</span></div>
	<div class="dr"><span class="dk">Actor Entropy</span><span class="dv">${f4(r.actor_loss)}</span></div>
	<div class="dr"><span class="dk">Critic Variance</span><span class="dv">${f4(r.critic_loss)}</span></div>
	<div class="dr"><span class="dk">AVN Precision</span><span class="dv c">${fPct(r.avn_accuracy)}</span></div>
	</div>
	<div><div class="dc-title">Neural Output</div>
	<div class="dr"><span class="dk">Composite Score</span><span class="dv g">${f4(r.score)}</span></div>
	<div class="dr"><span class="dk">Certainty Index</span><span class="dv">${fPct(r.signal_confidence)}</span></div>
	<div class="dr"><span class="dk">Last Ping</span><span class="dv">${ago(r.last_updated)}</span></div>
	<div class="dr"><span class="dk">Model Core</span><span class="dv">QUASAR-X1</span></div>
	</div>
	<div><div class="dc-title">Ensemble Consensus</div>
	<div class="dr"><span class="dk">Primary Vector</span><span class="dv ${r.dominant_signal==='BUY'?'g':r.dominant_signal==='SELL'?'r':''}">${r.dominant_signal}</span></div>
	<div class="dr"><span class="dk">Bull Weight</span><span class="dv g">${r.buy_count}</span></div>
	<div class="dr"><span class="dk">Bear Weight</span><span class="dv r">${r.sell_count}</span></div>
	</div>`;
	dp.classList.add('open');
	}

	function updateCharts(){
	scoreChart.data.labels=_rankings.map(r=>r.space_name);
	scoreChart.data.datasets[0].data=_rankings.map(r=>r.score);
	scoreChart.data.datasets[0].backgroundColor=_rankings.map(r=> r.dominant_signal==='BUY'?'rgba(0,223,138,0.7)': r.dominant_signal==='SELL'?'rgba(255,61,90,0.7)':'rgba(0,200,255,0.5)');
	scoreChart.update();
	if(!_rankings.length)return; const top=_rankings[0].space_name; const h=(_hist[top]\|\|[]).slice(-60); if(!h.length)return;
	const lb=h.map(p=>new Date(p.ts*1000).toLocaleTimeString('en-GB',{hour12:false,hour:'2-digit',minute:'2-digit',second:'2-digit'}));
	lossChart.data.labels=lb; lossChart.data.datasets[0].data=h.map(p=>p.actor_loss); lossChart.update();
	accChart.data.labels=lb; accChart.data.datasets[0].data=h.map(p=>+(p.avn_accuracy*100).toFixed(2)); accChart.update();
	}

	function updateKPIs(){
	document.getElementById('kpi-spaces').textContent=_health.spaces_connected\|\|'0';
	if(_rankings.length){ const t=_rankings[0]; document.getElementById('kpi-score').textContent=f4(t.score); document.getElementById('kpi-score-asset').textContent=t.space_name; }
	const accs=_rankings.filter(r=>r.avn_accuracy>0).map(r=>r.avn_accuracy);
	document.getElementById('kpi-acc').textContent=accs.length?fPct(accs.reduce((a,b)=>a+b,0)/accs.length):'—';
	document.getElementById('kpi-upd').textContent=_health.last_update_ago!=null?_health.last_update_ago+'s ago':'—';
	document.getElementById('kpi-msgs').textContent=(_health.messages_rx\|\|0).toLocaleString()+' ops processed';
	document.getElementById('sc-logs').textContent=_logs.length;
	const ok=_health.hub_connected;
	document.getElementById('sc-hub').textContent=ok?'Online':'Offline'; document.getElementById('sc-hub').className='sb-v '+(ok?'ok':'err');
	document.getElementById('sc-model').textContent=_rankings.length?'Active':'Standby';
	document.getElementById('sc-snap').textContent=_health.last_update_ago!=null?_health.last_update_ago+'s':'—';
	document.getElementById('sc-spaces').textContent=_health.spaces_connected\|\|'0';
	document.getElementById('nav-dot').className='pring'+(ok?' live':''); document.getElementById('nav-status').textContent=ok?'Live':'Offline';
	}

	function pushActivity(a){ _activity=_activity\|\|[]; _activity.unshift(a); if(_activity.length>100)_activity.pop(); }

	/* ════════════════════════════════════════════════════════════════════════════
	LOGS FUNCTIONALITY
	════════════════════════════════════════════════════════════════════════════ */
	async function loadRankerLogs() {
	try {
	const res = await fetch('/api/ranker/logs/recent?limit=200');
	if (!res.ok) throw new Error('Failed to load logs');
	const data = await res.json();
	_logs = data.logs \|\| [];

	const tb = document.getElementById('logs-body');
	if (!_logs.length) {
	tb.innerHTML = '<tr><td colspan="5" style="text-align:center;padding:40px;color:var(--t3)">No logs available</td></tr>';
	document.getElementById('logs-meta').textContent = '0 entries';
	return;
	}

	const filtered = _logFilter === 'all'
	? _logs
	: _logs.filter(log => {
	if (_logFilter === log.level) return true;
	if (_logFilter === log.category) return true;
	return false;
	});

	tb.innerHTML = filtered.map(log => {
	const ts = new Date(log.ts).toLocaleTimeString('en-GB', {hour12:false});
	const levelClass = log.level.toLowerCase();
	const levelColor = {
	'debug': 'var(--t3)',
	'info': 'var(--cyan)',
	'warning': 'var(--amber)',
	'error': 'var(--red)',
	'critical': 'var(--red)'
	}[levelClass] \|\| 'var(--t1)';

	return `<tr>
	<td class="log-time">${ts}</td>
	<td><span class="log-badge ${log.level}">${log.level}</span></td>
	<td><span class="cat-tag">${log.category}</span></td>
	<td><strong class="log-asset">${log.asset}</strong></td>
	<td class="log-message">${log.message}</td>
	</tr>`;
	}).join('');

	document.getElementById('logs-meta').textContent = filtered.length + ' entries';
	} catch (e) {
	console.error('Log load error:', e);
	}
	}

	async function loadLogStats() {
	try {
	const res = await fetch('/api/ranker/logs/stats');
	if (!res.ok) throw new Error('Failed to load stats');
	const data = await res.json();

	const statsEl = document.getElementById('logs-stats');
	const byCategory = data.by_category \|\| {};
	const byAsset = data.by_asset \|\| {};
	const errors = data.errors \|\| {};

	let html = `
	<div style="padding: var(--sp-md); background: rgba(0,200,255,0.1); border-radius: var(--elem-r); border: 1px solid rgba(0,200,255,0.2);">
	<div style="color: var(--t3); font-size: 0.7rem; text-transform: uppercase; font-weight: 800; margin-bottom: 8px;">Total Events</div>
	<div style="font-size: 1.8rem; color: var(--cyan); font-weight: 800;">${data.total_events}</div>
	</div>
	`;

	for (const [cat, count] of Object.entries(byCategory)) {
	html += `
	<div style="padding: var(--sp-md); background: rgba(255,255,255,0.05); border-radius: var(--elem-r); border: 1px solid rgba(255,255,255,0.1);">
	<div style="color: var(--t3); font-size: 0.7rem; text-transform: uppercase; font-weight: 800; margin-bottom: 8px;">${cat}</div>
	<div style="font-size: 1.6rem; color: var(--t1); font-weight: 800;">${count}</div>
	</div>
	`;
	}

	if (Object.keys(errors).length > 0) {
	html += `
	<div style="padding: var(--sp-md); background: rgba(255,61,90,0.1); border-radius: var(--elem-r); border: 1px solid rgba(255,61,90,0.2); grid-column: 1/-1;">
	<div style="color: var(--red); font-size: 0.7rem; text-transform: uppercase; font-weight: 800; margin-bottom: 8px;">⚠️ Errors Detected</div>
	${Object.entries(errors).map(([cat, count]) => `
	<div style="font-size: 0.8rem; color: var(--t1); margin-bottom: 4px;">
	<strong>${cat}:</strong> <span style="color: var(--red); font-weight: 800;">${count}</span>
	</div>
	`).join('')}
	</div>
	`;
	}

	statsEl.innerHTML = html;
	} catch (e) {
	console.error('Stats load error:', e);
	}
	}

	function filterLogs(evt, filter) {
	_logFilter = filter;
	document.querySelectorAll('.filter-btn').forEach(btn => btn.classList.remove('active'));
	if (evt && evt.currentTarget) evt.currentTarget.classList.add('active');
	loadRankerLogs();
	}

	/* ════════════════════════════════════════════════════════════════════════════
	MAIN REFRESH LOOP
	════════════════════════════════════════════════════════════════════════════ */
	async function refresh(){
	try{
	const res=await fetch('/api/state'); if(!res.ok)throw 0; const d=await res.json();
	_rankings=d.rankings\|\|[]; _hist=d.metric_history\|\|{}; _health=d.health\|\|{};
	// Trade audio hook — tab-agnostic, fires regardless of active tab
	if (typeof window._onTradeRefresh === 'function') window._onTradeRefresh(_rankings, _health);
	const nm=(_health.messages_rx\|\|0)-_lastMsgs;
	if(nm>0){
	_lastMsgs=_health.messages_rx\|\|0;
	}
	if (document.getElementById('rankings-tab').classList.contains('active')) {
	renderTable(); updateCharts();
	}
	updateKPIs();
	}catch(e){ document.getElementById('nav-status').textContent='Lost Sync'; }
	}

	refresh(); setInterval(refresh,2000);
	setInterval(()=>{ document.getElementById('kpi-upd').textContent=_health.last_update_ago!=null?_health.last_update_ago+'s ago':'—'; },1000);

	/* ════════════════════════════════════════════════════════════════════════════
	TERMINAL PANEL LOGIC — polls /api/trades every 2s
	════════════════════════════════════════════════════════════════════════════ */
	let _trmEquityChart = null;
	let _trmEquityCurve = []; // running cumulative PnL

	// ── Terminal error banner helpers ──────────────────────────────────────────
	function _showTerminalError(msg) {
	let el = document.getElementById('trm-error-banner');
	if (!el) {
	el = document.createElement('div');
	el.id = 'trm-error-banner';
	el.style.cssText = [
	'background:rgba(255,68,102,0.12)',
	'border:1px solid rgba(255,68,102,0.4)',
	'border-radius:8px',
	'padding:14px 20px',
	'margin-bottom:var(--sp-lg)',
	'color:#ff4466',
	'font-size:0.8rem',
	'font-weight:600',
	'letter-spacing:0.02em',
	].join(';');
	const tab = document.getElementById('terminal-tab');
	if (tab) tab.insertBefore(el, tab.firstChild);
	}
	el.textContent = '⚠ ' + msg;
	el.style.display = '';
	}
	function _clearTerminalError() {
	const el = document.getElementById('trm-error-banner');
	if (el) el.style.display = 'none';
	}

	async function updateTerminal() {
	let data;
	try {
	const res = await fetch('/api/trades');
	if (!res.ok) throw new Error('HTTP ' + res.status + ' — ensure hub_dashboard_service.py v2.0+ is deployed');
	data = await res.json();
	_clearTerminalError();
	} catch(e) {
	console.error('[Terminal] fetch error:', e);
	_showTerminalError('/api/trades unreachable: ' + e.message + '. Deploy the latest hub_dashboard_service.py.');
	return;
	}

	const open = data.open \|\| [];
	const closed = data.closed \|\| [];
	const stats = data.stats \|\| {};

	// ── Open-position trade alert ───────────────────────────────────────────────
	// Sound fires once per genuinely new trade_id that appears in open[].
	// _prevOpenTradeIds is module-scoped so it persists across polling cycles.
	if (typeof window._prevOpenTradeIds === 'undefined') {
	// First call — seed the set silently (don't alert on existing positions)
	window._prevOpenTradeIds = new Set(open.map(t => t.trade_id).filter(Boolean));
	} else {
	let hasNewTrade = false;
	const nextIds = new Set();
	for (const t of open) {
	if (!t.trade_id) continue;
	nextIds.add(t.trade_id);
	if (!window._prevOpenTradeIds.has(t.trade_id)) {
	hasNewTrade = true; // brand-new trade_id not seen before
	}
	}
	if (hasNewTrade) window.playTradeSound();
	window._prevOpenTradeIds = nextIds; // update to current snapshot
	}

	// ── KPI strip ──────────────────────────────────────────────────────────────
	const totalPnl = stats.total_pnl \|\| 0;
	const totalClosed = stats.total_closed \|\| 0;
	const winCount = stats.win_count \|\| 0;
	const lossCount = stats.loss_count \|\| 0;
	const winRate = stats.win_rate \|\| 0;
	const avgPnl = totalClosed > 0 ? (totalPnl / totalClosed) : 0;

	// Equity = sum of all closed PnL (running balance proxy)
	const pnlClr = v => v > 0 ? 'var(--green)' : v < 0 ? 'var(--red)' : 'var(--t1)';
	const fPnl = v => (v >= 0 ? '+' : '') + v.toFixed(2);

	const eqEl = document.getElementById('trm-equity');
	if (eqEl) { eqEl.textContent = fPnl(totalPnl); eqEl.style.color = pnlClr(totalPnl); }

	const opEl = document.getElementById('trm-open-pnl');
	if (opEl) { opEl.textContent = open.length ? open.length + ' open' : '—'; }

	const ocEl = document.getElementById('trm-open-count');
	if (ocEl) ocEl.textContent = open.length + ' position' + (open.length !== 1 ? 's' : '');

	const rpEl = document.getElementById('trm-realized-pnl');
	if (rpEl) { rpEl.textContent = fPnl(totalPnl); rpEl.style.color = pnlClr(totalPnl); }

	const ccEl = document.getElementById('trm-closed-count');
	if (ccEl) ccEl.textContent = totalClosed + ' closed trades';

	const wrEl = document.getElementById('trm-winrate');
	if (wrEl) wrEl.textContent = winRate + '%';

	const wlEl = document.getElementById('trm-wl');
	if (wlEl) wlEl.textContent = 'W:' + winCount + ' / L:' + lossCount;

	const apEl = document.getElementById('trm-avg-pnl');
	if (apEl) { apEl.textContent = fPnl(avgPnl); apEl.style.color = pnlClr(avgPnl); }

	// Update sidebar Logs counter with trade count
	const scLogsEl = document.getElementById('sc-logs');
	if (scLogsEl && !isNaN(totalClosed)) {
	// don't overwrite log count — leave it
	}

	// ── Equity curve chart ─────────────────────────────────────────────────────
	// Rebuild cumulative curve from closed trades (newest-first → reverse for chrono)
	const chronoClosed = [...closed].reverse();
	let cum = 0;
	const curveData = chronoClosed.map(t => { cum += (t.pnl \|\| 0); return +cum.toFixed(4); });
	const curveLabels = chronoClosed.map(t => t.closed_at ? t.closed_at.slice(11,19) : '');

	const chartCanvas = document.getElementById('trm-equity-chart');
	if (chartCanvas) {
	if (!_trmEquityChart) {
	_trmEquityChart = new Chart(chartCanvas, {
	type: 'line',
	data: {
	labels: curveLabels,
	datasets: [{
	data: curveData,
	borderColor: '#E8720A',
	backgroundColor: 'rgba(232,114,10,0.08)',
	borderWidth: 2,
	fill: true,
	pointRadius: 0,
	tension: 0.4,
	}]
	},
	options: {
	responsive: true, maintainAspectRatio: false,
	plugins: { legend: { display: false } },
	scales: {
	x: { display: false },
	y: { grid: { color: 'rgba(255,255,255,0.04)' },
	ticks: { color: 'rgba(255,255,255,0.3)', font: { size: 9 }, maxTicksLimit: 5 } }
	}
	}
	});
	} else {
	_trmEquityChart.data.labels = curveLabels;
	_trmEquityChart.data.datasets[0].data = curveData;
	_trmEquityChart.update('none');
	}
	}
	const cmEl = document.getElementById('trm-curve-meta');
	if (cmEl) cmEl.textContent = totalClosed + ' closed trades · ' + new Date().toLocaleTimeString('en-GB',{hour12:false});

	// ── Open positions table ────────────────────────────────────────────────────
	const ob = document.getElementById('trm-open-body');
	if (ob) {
	if (!open.length) {
	ob.innerHTML = '<tr><td colspan="8" style="padding:32px;text-align:center;color:var(--t4);font-size:0.75rem">No open positions</td></tr>';
	} else {
	const now = new Date();
	ob.innerHTML = open.map(t => {
	const dirCls = t.direction === 'LONG' \|\| t.direction === 'BUY' ? 'BUY' : 'SELL';
	// Duration from opened_at
	let dur = '—';
	if (t.opened_at) {
	const diffMs = now - new Date(t.opened_at);
	const diffS = Math.floor(diffMs / 1000);
	dur = diffS < 60 ? diffS + 's' : diffS < 3600 ? Math.floor(diffS/60) + 'm' : Math.floor(diffS/3600) + 'h ' + Math.floor((diffS%3600)/60) + 'm';
	}
	return `<tr>
	<td style="padding:12px 16px;font-size:0.72rem;color:var(--t3);font-family:monospace">${t.trade_id}</td>
	<td style="padding:12px 16px;font-weight:800;color:var(--t0)">${t.asset \|\| '—'}</td>
	<td style="padding:12px 16px"><span class="sig ${dirCls}" style="font-size:0.65rem">${t.direction \|\| '—'}</span></td>
	<td style="padding:12px 16px;text-align:right;font-variant-numeric:tabular-nums;color:var(--cyan)">${t.entry != null ? t.entry.toFixed(4) : '—'}</td>
	<td style="padding:12px 16px;text-align:right;font-variant-numeric:tabular-nums">${t.qty != null ? t.qty.toFixed(6) : '—'}</td>
	<td style="padding:12px 16px;text-align:right;color:var(--t3)">—</td>
	<td style="padding:12px 16px;text-align:right;color:var(--t2)">${dur}</td>
	<td style="padding:12px 16px;text-align:right;font-size:0.7rem;color:var(--t3)">${t.opened_at ? t.opened_at.replace('T',' ') : '—'}</td>
	</tr>`;
	}).join('');
	}
	}
	const omEl = document.getElementById('trm-open-meta');
	if (omEl) omEl.textContent = open.length + ' position' + (open.length!==1?'s':'') + ' · live · updates every 2s';

	// ── Trade history table ─────────────────────────────────────────────────────
	const hb = document.getElementById('trm-hist-body');
	if (hb) {
	if (!closed.length) {
	hb.innerHTML = '<tr><td colspan="9" style="padding:32px;text-align:center;color:var(--t4);font-size:0.75rem">No trade history</td></tr>';
	} else {
	hb.innerHTML = closed.map(t => {
	const pnl = t.pnl \|\| 0;
	const pnlCls = pnl >= 0 ? 'color:var(--green)' : 'color:var(--red)';
	const dirCls = t.direction === 'LONG' \|\| t.direction === 'BUY' ? 'BUY' : 'SELL';
	return `<tr>
	<td style="padding:10px 16px;font-size:0.68rem;color:var(--t3);font-family:monospace">${t.trade_id}</td>
	<td style="padding:10px 16px;font-weight:800;color:var(--t0)">${t.asset \|\| '—'}</td>
	<td style="padding:10px 16px"><span class="sig ${dirCls}" style="font-size:0.6rem">${t.direction \|\| '—'}</span></td>
	<td style="padding:10px 16px;text-align:right;font-variant-numeric:tabular-nums">${t.entry != null ? t.entry.toFixed(4) : '—'}</td>
	<td style="padding:10px 16px;text-align:right;font-variant-numeric:tabular-nums;color:var(--t2)">${t.exit_price != null ? Number(t.exit_price).toFixed(4) : '—'}</td>
	<td style="padding:10px 16px;text-align:right;font-variant-numeric:tabular-nums">${t.qty != null ? t.qty.toFixed(6) : '—'}</td>
	<td style="padding:10px 16px;text-align:right;font-weight:800;${pnlCls}">${pnl >= 0 ? '+' : ''}${pnl.toFixed(4)}</td>
	<td style="padding:10px 16px;text-align:right;color:var(--t3)">—</td>
	<td style="padding:10px 16px;text-align:right;font-size:0.7rem;color:var(--t3)">${t.closed_at ? t.closed_at.replace('T',' ') : '—'}</td>
	</tr>`;
	}).join('');
	}
	}
	const hmEl = document.getElementById('trm-hist-meta');
	if (hmEl) hmEl.textContent = 'last ' + closed.length + ' closed trades';
	}

	// Auto-refresh terminal tab every 2s (also on tab switch)
	setInterval(function(){
	const tEl = document.getElementById('terminal-tab');
	if (tEl && tEl.classList.contains('active')) updateTerminal();
	}, 2000);

	/* ════════════════════════════════════════════════════════════════════════════
	TRADING PANEL LOGIC
	════════════════════════════════════════════════════════════════════════════ */

	const GATE_DEFS = [
	{ id:'A', name:'Signal Gate', desc:'Dominant signal must be BUY or SELL (not NEUTRAL)' },
	{ id:'B', name:'Confidence Gate', desc:'Signal confidence ≥ 0.55 threshold required' },
	{ id:'C', name:'Significance Gate', desc:'AXRVI score ≥ 0.10 significance threshold' },
	{ id:'D', name:'Volatility Gate', desc:'AVN accuracy ≥ 0.50 — vol/uncertainty check' },
	{ id:'E', name:'Martingale Gate', desc:'Martingale null-hypothesis deviation detected' },
	];

	// Derive per-asset gate status from ranking data
	function gateStatus(r) {
	const A = r.dominant_signal === 'BUY' \|\| r.dominant_signal === 'SELL';
	const B = r.signal_confidence >= 0.55;
	const C = Math.abs(r.score) >= 0.10;
	const D = r.avn_accuracy >= 0.50;
	// Gate E (martingale): use actor_loss as proxy — lower is better, pass if <0.5
	const E = (r.actor_loss \|\| 0) < 0.5;
	return { A, B, C, D, E };
	}

	function allGatesPass(gates) {
	return gates.A && gates.B && gates.C && gates.D && gates.E;
	}

	function renderTradingTab() {
	if (!_rankings \|\| !_rankings.length) return;

	// ── KPI Row ────────────────────────────────────────────────────────────────
	const buys = _rankings.filter(r => r.dominant_signal === 'BUY');
	const sells = _rankings.filter(r => r.dominant_signal === 'SELL');
	document.getElementById('t-kpi-buys').textContent = buys.length;
	document.getElementById('t-kpi-sells').textContent = sells.length;

	const topBuy = buys.sort((a,b) => b.signal_confidence - a.signal_confidence)[0];
	if (topBuy) {
	document.getElementById('t-kpi-top').textContent = topBuy.space_name;
	document.getElementById('t-kpi-top-conf').textContent = 'confidence: ' + fPct(topBuy.signal_confidence);
	} else {
	document.getElementById('t-kpi-top').textContent = 'NEUTRAL';
	document.getElementById('t-kpi-top-conf').textContent = 'no directional signal';
	}

	const totalBuyVotes = _rankings.reduce((s,r) => s + r.buy_count, 0);
	const totalSellVotes = _rankings.reduce((s,r) => s + r.sell_count, 0);
	const totalVotes = totalBuyVotes + totalSellVotes;
	const ratio = totalVotes > 0
	? (totalBuyVotes / totalVotes * 100).toFixed(1) + '% / ' + (totalSellVotes / totalVotes * 100).toFixed(1) + '%'
	: '—';
	document.getElementById('t-kpi-ratio').textContent = ratio;
	document.getElementById('t-kpi-ratio-sub').textContent = `${totalBuyVotes} bull · ${totalSellVotes} bear votes`;

	// ── Signal Command Centre ──────────────────────────────────────────────────
	const sb = document.getElementById('trade-signal-body');
	sb.innerHTML = _rankings.map((r, i) => {
	const gates = gateStatus(r);
	const allPass = allGatesPass(gates);
	const gateIcon = allPass ? '<span style="color:var(--green);font-weight:800">✓ CLEAR</span>'
	: '<span style="color:var(--amber);font-weight:700">⚠ GATED</span>';
	const sigClass = r.dominant_signal === 'BUY' ? 'BUY' : r.dominant_signal === 'SELL' ? 'SELL' : 'HOLD';
	return `<tr>
	<td class="rc ${i===0?'r1':''}">${r.rank}</td>
	<td class="nc">${r.space_name}</td>
	<td><span class="sig ${sigClass}">${r.dominant_signal}</span></td>
	<td class="num">${fPct(r.signal_confidence)}</td>
	<td class="num" style="color:var(--green)">${r.buy_count}</td>
	<td class="num" style="color:var(--red)">${r.sell_count}</td>
	<td class="num" style="color:var(--t2)">${r.buy_count + r.sell_count}</td>
	<td class="num" style="color:var(--cyan)">${f4(r.score)}</td>
	<td>${gateIcon}</td>
	<td class="num" style="color:var(--t3)">${ago(r.last_updated)}</td>
	</tr>`;
	}).join('');
	document.getElementById('t-signal-meta').textContent = _rankings.length + ' assets in matrix · updated ' + (new Date()).toLocaleTimeString('en-GB',{hour12:false});

	// ── Open Positions Monitor ────────────────────────────────────────────────
	// Positions = assets with BUY or SELL that pass at least gate A+B
	const positions = _rankings.filter(r => {
	const g = gateStatus(r);
	return g.A && g.B;
	});

	const pb = document.getElementById('trade-positions-body');
	document.getElementById('t-pos-meta').textContent = positions.length + ' position' + (positions.length !== 1 ? 's' : '') + ' qualifying';
	if (!positions.length) {
	pb.innerHTML = '<tr><td colspan="6" style="text-align:center;padding:30px;color:var(--t3)">No assets clearing Gates A+B</td></tr>';
	} else {
	pb.innerHTML = positions.map(r => {
	const gates = gateStatus(r);
	const allP = allGatesPass(gates);
	const gLabel = allP
	? '<span class="pos-gate-pass">✓ ALL CLEAR</span>'
	: `<span class="pos-gate-warn">A:${gates.A?'✓':'✗'} B:${gates.B?'✓':'✗'} C:${gates.C?'✓':'✗'} D:${gates.D?'✓':'✗'} E:${gates.E?'✓':'✗'}</span>`;
	const side = r.dominant_signal === 'BUY' ? 'BUY' : 'SELL';
	return `<tr>
	<td class="nc">${r.space_name}</td>
	<td><span class="sig ${side}">${side}</span></td>
	<td class="num" style="color:var(--cyan)">${fPct(r.signal_confidence)}</td>
	<td class="num">${fPct(r.avn_accuracy)}</td>
	<td class="num" style="color:var(--green)">${f4(r.score)}</td>
	<td>${gLabel}</td>
	</tr>`;
	}).join('');
	}

	// ── Ensemble Vote Breakdown ───────────────────────────────────────────────
	const vb = document.getElementById('vote-breakdown');
	vb.innerHTML = _rankings.map(r => {
	const total = r.buy_count + r.sell_count \|\| 1;
	const buyPct = (r.buy_count / total * 100).toFixed(0);
	const sellPct = (r.sell_count / total * 100).toFixed(0);
	const sigCls = r.dominant_signal === 'BUY' ? 'BUY' : r.dominant_signal === 'SELL' ? 'SELL' : 'HOLD';
	const tagBg = sigCls === 'BUY' ? 'rgba(0,223,138,0.12)' : sigCls === 'SELL' ? 'rgba(255,61,90,0.12)' : 'rgba(255,255,255,0.07)';
	const tagClr = sigCls === 'BUY' ? 'var(--green)' : sigCls === 'SELL' ? 'var(--red)' : 'var(--t2)';
	return `<div class="vote-row">
	<div class="vote-asset-label">
	<span class="vote-asset-name">${r.space_name}</span>
	<span class="vote-signal-tag" style="background:${tagBg};color:${tagClr};border:1px solid ${tagClr}40">${r.dominant_signal}</span>
	</div>
	<div class="vote-bar-track">
	<div class="vote-bar-buy" style="width:${buyPct}%"></div>
	<div class="vote-bar-sell" style="width:${sellPct}%"></div>
	</div>
	<div class="vote-counts">
	<span class="v-buy">▲ ${r.buy_count} (${buyPct}%)</span>
	<span class="v-sell">▼ ${r.sell_count} (${sellPct}%)</span>
	</div>
	</div>`;
	}).join('');

	// ── Gate Monitor ─────────────────────────────────────────────────────────
	// Aggregate gate pass/fail across all assets
	const gateTotals = { A:0, B:0, C:0, D:0, E:0 };
	_rankings.forEach(r => {
	const g = gateStatus(r);
	Object.keys(gateTotals).forEach(k => { if(g[k]) gateTotals[k]++; });
	});
	const n = _rankings.length \|\| 1;
	document.getElementById('gate-monitor').innerHTML = GATE_DEFS.map(g => {
	const passCount = gateTotals[g.id];
	const pct = (passCount / n * 100).toFixed(0);
	const cls = passCount === n ? 'pass' : passCount > 0 ? 'pass' : 'fail';
	return `<div class="gate-card">
	<div class="gate-label">Gate ${g.id}</div>
	<div class="gate-name">${g.name}</div>
	<div class="gate-status ${cls}">${passCount}/${n}</div>
	<div style="font-size:0.75rem;color:${passCount===n?'var(--green)':passCount>0?'var(--amber)':'var(--red)'};font-weight:700">${pct}% passing</div>
	<div class="gate-desc">${g.desc}</div>
	</div>`;
	}).join('');

	// ── Live Feed ─────────────────────────────────────────────────────────────
	const fb = document.getElementById('trade-feed-body');
	const now = Date.now();
	fb.innerHTML = _rankings.slice(0, 20).map(r => {
	const dir = r.dominant_signal === 'BUY' ? 'L' : r.dominant_signal === 'SELL' ? 'S' : 'N';
	const dirLabel = r.dominant_signal === 'BUY' ? 'LONG' : r.dominant_signal === 'SELL' ? 'SHORT' : 'HOLD';
	const ts = r.last_updated ? new Date(r.last_updated * 1000).toLocaleTimeString('en-GB', {hour12:false}) : '—';
	return `<div class="feed-cols row">
	<div class="f-info">
	<span class="f-asset">${r.space_name}</span>
	<span class="f-ts" style="margin-left:10px">${ts}</span>
	</div>
	<span class="f-dir ${dir}">${dirLabel}</span>
	<span class="f-out ${r.signal_confidence >= 0.6 ? 'p' : ''}" style="text-align:right">${fPct(r.signal_confidence)}</span>
	</div>`;
	}).join('');
	document.getElementById('t-feed-meta').textContent = _rankings.length + ' signals · ' + new Date().toLocaleTimeString('en-GB',{hour12:false});
	}

	// Also refresh trading tab if it's active during the main refresh loop
	setInterval(function(){
	const tTab = document.getElementById('trading-tab');
	if (tTab && tTab.classList.contains('active')) renderTradingTab();
	}, 2000);

	/* ════════════════════════════════════════════════════════════════════════════
	ASSETS PANEL LOGIC
	════════════════════════════════════════════════════════════════════════════ */

	let _assetView = 'cards';
	let _assetFilter = '';
	let _selectedAsset = null;
	let _diveLossChart = null;
	let _diveAccChart = null;

	function setAssetView(view, btn) {
	_assetView = view;
	document.querySelectorAll('.asset-view-btn').forEach(b => {
	b.classList.remove('active');
	b.style.borderColor = 'rgba(255,255,255,0.1)';
	b.style.background = 'rgba(0,0,0,0.4)';
	b.style.color = 'var(--t2)';
	});
	if (btn) {
	btn.classList.add('active');
	btn.style.borderColor = 'rgba(0,200,255,0.4)';
	btn.style.background = 'rgba(0,200,255,0.1)';
	btn.style.color = 'var(--cyan)';
	}
	document.getElementById('asset-cards-view').style.display = view === 'cards' ? '' : 'none';
	document.getElementById('asset-table-view').style.display = view === 'table' ? '' : 'none';
	document.getElementById('asset-heatmap-view').style.display = view === 'heatmap' ? '' : 'none';
	renderAssetsTab();
	}

	function filterAssets(v) {
	_assetFilter = v.toLowerCase().trim();
	renderAssetsTab();
	}

	function getFilteredAssets() {
	if (!_assetFilter) return _rankings;
	return _rankings.filter(r => r.space_name.toLowerCase().includes(_assetFilter));
	}

	// ── Colour helpers ────────────────────────────────────────────────────────────
	function heatColour(norm) {
	// norm 0–1: red → amber → green
	if (norm >= 0.66) {
	const t = (norm - 0.66) / 0.34;
	const r = Math.round(255 * (1 - t) * 0.67);
	const g = Math.round(223 * (0.67 + t * 0.33));
	const b = Math.round(138 * t);
	return `rgba(${r},${g},${b},0.75)`;
	} else if (norm >= 0.33) {
	const t = (norm - 0.33) / 0.33;
	return `rgba(255,${Math.round(100 + t * 70)},0,0.7)`;
	} else {
	const t = norm / 0.33;
	return `rgba(255,${Math.round(61 * t)},${Math.round(90 * t)},0.75)`;
	}
	}

	function normalise(vals) {
	const mn = Math.min(...vals), mx = Math.max(...vals);
	const range = mx - mn \|\| 1;
	return vals.map(v => (v - mn) / range);
	}

	// ── Summary bar ───────────────────────────────────────────────────────────────
	function renderAssetSummary(assets) {
	document.getElementById('as-total').textContent = assets.length;
	document.getElementById('as-bull').textContent = assets.filter(r => r.dominant_signal === 'BUY').length;
	document.getElementById('as-bear').textContent = assets.filter(r => r.dominant_signal === 'SELL').length;
	document.getElementById('as-neut').textContent = assets.filter(r => r.dominant_signal !== 'BUY' && r.dominant_signal !== 'SELL').length;
	const accs = assets.filter(r => r.avn_accuracy > 0).map(r => r.avn_accuracy);
	document.getElementById('as-avgacc').textContent = accs.length
	? fPct(accs.reduce((a,b) => a+b, 0) / accs.length) : '—';
	document.getElementById('asset-count-label').textContent = assets.length + ' asset' + (assets.length !== 1 ? 's' : '');
	}

	// ── Card rendering ────────────────────────────────────────────────────────────
	function renderAssetCards(assets) {
	const grid = document.getElementById('asset-card-grid');
	if (!assets.length) {
	grid.innerHTML = '<div style="grid-column:1/-1;text-align:center;padding:60px;color:var(--t3)">No assets match filter</div>';
	return;
	}
	grid.innerHTML = assets.map(r => {
	const sigCls = r.dominant_signal === 'BUY' ? 'sig-buy' : r.dominant_signal === 'SELL' ? 'sig-sell' : 'sig-hold';
	const scoreClr = r.score > 0.1 ? 'var(--green)' : r.score < -0.05 ? 'var(--red)' : 'var(--cyan)';
	const total = r.buy_count + r.sell_count \|\| 1;
	const buyPct = (r.buy_count / total * 100).toFixed(0);
	const sellPct = (r.sell_count / total * 100).toFixed(0);
	const isSelected = _selectedAsset === r.space_name ? 'selected' : '';
	return `<div class="asset-card ${sigCls} ${isSelected}" onclick="openDeepDive('${r.space_name}')">
	<div class="ac-header">
	<div>
	<div class="ac-name">${r.space_name}</div>
	<div class="ac-rank">RANK #${r.rank}</div>
	</div>
	<span class="sig ${r.dominant_signal === 'BUY' ? 'BUY' : r.dominant_signal === 'SELL' ? 'SELL' : 'HOLD'}">${r.dominant_signal}</span>
	</div>
	<div class="ac-score-block">
	<div class="ac-score-label">AXRVI Score</div>
	<div class="ac-score-val" style="color:${scoreClr}">${f4(r.score)}</div>
	</div>
	<div class="ac-metrics">
	<div class="ac-metric">
	<span class="ac-metric-k">Confidence</span>
	<span class="ac-metric-v" style="color:var(--cyan)">${fPct(r.signal_confidence)}</span>
	</div>
	<div class="ac-metric">
	<span class="ac-metric-k">AVN Accuracy</span>
	<span class="ac-metric-v">${fPct(r.avn_accuracy)}</span>
	</div>
	<div class="ac-metric">
	<span class="ac-metric-k">Actor Loss</span>
	<span class="ac-metric-v" style="color:${r.actor_loss < 0.3 ? 'var(--green)' : r.actor_loss > 0.7 ? 'var(--red)' : 'var(--amber)'}">${f4(r.actor_loss)}</span>
	</div>
	<div class="ac-metric">
	<span class="ac-metric-k">Train Cycles</span>
	<span class="ac-metric-v" style="color:var(--t1)">${(r.training_steps\|\|0).toLocaleString()}</span>
	</div>
	</div>
	<div class="ac-vote-bar" style="margin-top:12px">
	<div class="ac-vote-buy" style="width:${buyPct}%"></div>
	<div class="ac-vote-sell" style="width:${sellPct}%"></div>
	</div>
	<div class="ac-footer">
	<span class="ac-steps">▲${r.buy_count} ▼${r.sell_count} votes</span>
	<span class="ac-ts">${ago(r.last_updated)}</span>
	</div>
	</div>`;
	}).join('');
	}

	// ── Full table rendering ──────────────────────────────────────────────────────
	function renderAssetTable(assets) {
	document.getElementById('asset-table-meta').textContent = assets.length + ' assets';
	const body = document.getElementById('asset-full-body');
	if (!assets.length) {
	body.innerHTML = '<tr><td colspan="13" style="text-align:center;padding:40px;color:var(--t3)">No assets</td></tr>';
	return;
	}
	body.innerHTML = assets.map(r => {
	const sigCls = r.dominant_signal === 'BUY' ? 'BUY' : r.dominant_signal === 'SELL' ? 'SELL' : 'HOLD';
	const lossClr = r.actor_loss < 0.3 ? 'var(--green)' : r.actor_loss > 0.7 ? 'var(--red)' : 'var(--amber)';
	return `<tr onclick="openDeepDive('${r.space_name}')" style="cursor:pointer">
	<td class="rc ${r.rank===1?'r1':''}">${r.rank}</td>
	<td class="nc">${r.space_name}</td>
	<td style="text-align:right"><span class="sig ${sigCls}">${r.dominant_signal}</span></td>
	<td class="num" style="color:var(--cyan)">${fPct(r.signal_confidence)}</td>
	<td class="num">${fPct(r.avn_accuracy)}</td>
	<td class="num" style="color:${r.score>0.1?'var(--green)':r.score<0?'var(--red)':'var(--t1)'}">${f4(r.score)}</td>
	<td class="num" style="color:${lossClr}">${f4(r.actor_loss)}</td>
	<td class="num">${f4(r.critic_loss)}</td>
	<td class="num">${f4(r.avn_loss)}</td>
	<td class="num" style="color:var(--cyan)">${(r.training_steps\|\|0).toLocaleString()}</td>
	<td class="num" style="color:var(--green)">${r.buy_count}</td>
	<td class="num" style="color:var(--red)">${r.sell_count}</td>
	<td class="num" style="color:var(--t3)">${ago(r.last_updated)}</td>
	</tr>`;
	}).join('');
	}

	// ── Heatmap rendering ─────────────────────────────────────────────────────────
	function renderAssetHeatmap(assets) {
	const container = document.getElementById('asset-heatmap-grid');
	if (!assets.length) { container.innerHTML = '<div style="text-align:center;padding:40px;color:var(--t3)">No data</div>'; return; }

	const metrics = [
	{ key: 'signal_confidence', label: 'Confidence', higher: true },
	{ key: 'avn_accuracy', label: 'AVN Acc', higher: true },
	{ key: 'score', label: 'Score', higher: true },
	{ key: 'actor_loss', label: 'Actor Loss', higher: false },
	{ key: 'critic_loss', label: 'Crit Loss', higher: false },
	{ key: 'avn_loss', label: 'AVN Loss', higher: false },
	];
	const cols = `120px repeat(${metrics.length}, 1fr)`;

	let html = `<div class="hm-header-row" style="grid-template-columns:${cols}">
	<span>Asset</span>
	${metrics.map(m => `<span style="text-align:center">${m.label}</span>`).join('')}
	</div>`;

	// Pre-normalise each metric column
	const normed = {};
	metrics.forEach(m => {
	const vals = assets.map(r => r[m.key] \|\| 0);
	const norms = normalise(vals);
	normed[m.key] = assets.reduce((acc, r, i) => { acc[r.space_name] = m.higher ? norms[i] : 1 - norms[i]; return acc; }, {});
	});

	html += assets.map(r => `
	<div class="hm-row" style="grid-template-columns:${cols};cursor:pointer" onclick="openDeepDive('${r.space_name}')">
	<div class="hm-asset-name">${r.space_name}</div>
	${metrics.map(m => {
	const n = normed[m.key][r.space_name];
	const bg = heatColour(n);
	const val = m.key.includes('steps') ? (r[m.key]\|\|0).toLocaleString()
	: m.key.includes('confidence') \|\| m.key.includes('accuracy') ? fPct(r[m.key])
	: f4(r[m.key]);
	return `<div class="hm-cell" style="background:${bg};color:#fff">${val}</div>`;
	}).join('')}
	</div>`).join('');

	container.innerHTML = html;
	}

	// ── Deep dive panel ───────────────────────────────────────────────────────────
	function openDeepDive(name) {
	_selectedAsset = name;
	const r = _rankings.find(x => x.space_name === name);
	if (!r) return;

	// Re-render cards to show selected state
	if (_assetView === 'cards') renderAssetCards(getFilteredAssets());

	const dive = document.getElementById('asset-deep-dive');
	document.getElementById('dive-title').textContent = name + ' — Deep Dive';
	dive.style.display = '';
	dive.scrollIntoView({ behavior: 'smooth', block: 'nearest' });

	const sigCls = r.dominant_signal === 'BUY' ? 'g' : r.dominant_signal === 'SELL' ? 'r' : '';
	document.getElementById('dive-stats').innerHTML = `
	<div class="dive-block">
	<div class="dive-block-title">Neural Output</div>
	<div class="dive-row"><span class="dive-k">AXRVI Score</span><span class="dive-v ${r.score > 0.1 ? 'g' : r.score < 0 ? 'r' : 'c'}">${f4(r.score)}</span></div>
	<div class="dive-row"><span class="dive-k">Signal Confidence</span><span class="dive-v c">${fPct(r.signal_confidence)}</span></div>
	<div class="dive-row"><span class="dive-k">Dominant Signal</span><span class="dive-v ${sigCls}">${r.dominant_signal}</span></div>
	<div class="dive-row"><span class="dive-k">Rank</span><span class="dive-v">#${r.rank}</span></div>
	<div class="dive-row"><span class="dive-k">Last Updated</span><span class="dive-v">${ago(r.last_updated)}</span></div>
	</div>
	<div class="dive-block">
	<div class="dive-block-title">Training Metrics</div>
	<div class="dive-row"><span class="dive-k">Training Steps</span><span class="dive-v c">${(r.training_steps\|\|0).toLocaleString()}</span></div>
	<div class="dive-row"><span class="dive-k">Actor Loss</span><span class="dive-v ${r.actor_loss < 0.3 ? 'g' : r.actor_loss > 0.7 ? 'r' : 'a'}">${f4(r.actor_loss)}</span></div>
	<div class="dive-row"><span class="dive-k">Critic Loss</span><span class="dive-v">${f4(r.critic_loss)}</span></div>
	<div class="dive-row"><span class="dive-k">AVN Loss</span><span class="dive-v">${f4(r.avn_loss)}</span></div>
	<div class="dive-row"><span class="dive-k">AVN Accuracy</span><span class="dive-v ${r.avn_accuracy > 0.6 ? 'g' : ''}">${fPct(r.avn_accuracy)}</span></div>
	</div>
	<div class="dive-block">
	<div class="dive-block-title">Ensemble Voting</div>
	<div class="dive-row"><span class="dive-k">Bull Votes</span><span class="dive-v g">${r.buy_count}</span></div>
	<div class="dive-row"><span class="dive-k">Bear Votes</span><span class="dive-v r">${r.sell_count}</span></div>
	<div class="dive-row"><span class="dive-k">Total Votes</span><span class="dive-v">${r.buy_count + r.sell_count}</span></div>
	<div class="dive-row"><span class="dive-k">Bull Share</span><span class="dive-v g">${fPct(r.buy_count / (r.buy_count + r.sell_count \|\| 1))}</span></div>
	<div class="dive-row"><span class="dive-k">Bear Share</span><span class="dive-v r">${fPct(r.sell_count / (r.buy_count + r.sell_count \|\| 1))}</span></div>
	</div>`;

	// Build mini sparkline charts from metric history
	const hist = (_hist[name] \|\| []).slice(-60);
	const lossLabels = hist.map((_, i) => i);
	const lossData = hist.map(p => p.actor_loss);
	const accData = hist.map(p => +(p.avn_accuracy * 100).toFixed(2));

	const miniCfg = (labels, data, colour, label) => ({
	type: 'line',
	data: {
	labels,
	datasets: [{ data, borderColor: colour, borderWidth: 2, fill: true,
	backgroundColor: colour.replace(')', ',0.1)').replace('rgb','rgba'),
	pointRadius: 0, tension: 0.4 }]
	},
	options: {
	responsive: true, maintainAspectRatio: false,
	plugins: { legend: { display: false }, tooltip: { enabled: true } },
	scales: {
	x: { display: false },
	y: { display: true, grid: { color: 'rgba(255,255,255,0.04)' },
	ticks: { color: 'rgba(255,255,255,0.3)', font: { size: 9 }, maxTicksLimit: 4 } }
	}
	}
	});

	if (_diveLossChart) { _diveLossChart.destroy(); _diveLossChart = null; }
	if (_diveAccChart) { _diveAccChart.destroy(); _diveAccChart = null; }

	if (hist.length > 1) {
	_diveLossChart = new Chart(document.getElementById('dive-loss-chart'), miniCfg(lossLabels, lossData, 'rgb(255,61,90)', 'Actor Loss'));
	_diveAccChart = new Chart(document.getElementById('dive-acc-chart'), miniCfg(lossLabels, accData, 'rgb(0,200,255)', 'AVN Accuracy %'));
	} else {
	document.getElementById('dive-loss-chart').getContext('2d').fillStyle = 'rgba(255,255,255,0.05)';
	['dive-loss-chart','dive-acc-chart'].forEach(id => {
	const ctx = document.getElementById(id).getContext('2d');
	ctx.clearRect(0,0,300,120);
	ctx.fillStyle = 'rgba(255,255,255,0.05)';
	ctx.fillRect(0,0,300,120);
	ctx.fillStyle = 'rgba(255,255,255,0.2)';
	ctx.font = '11px Inter, sans-serif';
	ctx.textAlign = 'center';
	ctx.fillText('Insufficient history data', 150, 60);
	});
	}
	}

	function closeDeepDive() {
	_selectedAsset = null;
	document.getElementById('asset-deep-dive').style.display = 'none';
	if (_diveLossChart) { _diveLossChart.destroy(); _diveLossChart = null; }
	if (_diveAccChart) { _diveAccChart.destroy(); _diveAccChart = null; }
	if (_assetView === 'cards') renderAssetCards(getFilteredAssets());
	}

	// ── Main assets render ────────────────────────────────────────────────────────
	function renderAssetsTab() {
	const assets = getFilteredAssets();
	renderAssetSummary(assets);
	if (_assetView === 'cards') renderAssetCards(assets);
	else if (_assetView === 'table') renderAssetTable(assets);
	else if (_assetView === 'heatmap') renderAssetHeatmap(assets);
	}

	// Wire into switchTab
	const _origSwitchTabAssets = switchTab;
	// Note: switchTab already handles 'assets' via the else-if chain, add it:

	// Auto-refresh when assets tab is active
	setInterval(function(){
	const aTab = document.getElementById('assets-tab');
	if (aTab && aTab.classList.contains('active')) renderAssetsTab();
	}, 2000);

	// ════════════════════════════════════════════════════════════════════════════
	// TRAINING PANEL — live log stream + KPI metrics
	// Polls /api/ranker/logs/recent?category=training (DEBUG) + all recent logs
	// Falls back gracefully if endpoint is unavailable
	// ════════════════════════════════════════════════════════════════════════════
	(function() {
	const MAX_LINES = 120; // keep last N lines in terminal
	const POLL_MS = 2000;
	let _termLines = [];
	let _lastLogTs = null;
	let _prevLoss = null;

	// Parse "key=value \| key=value" pairs — render as evenly-spaced columns filling the full row
	function renderKVPairs(msg) {
	if (!msg.includes('=')) return `<span style="color:var(--t0);flex:1">${escHtml(msg)}</span>`;
	const parts = msg.split('\|').map(s => s.trim()).filter(Boolean);
	if (!parts.length) return `<span style="color:var(--t0);flex:1">${escHtml(msg)}</span>`;
	return parts.map((part, i) => {
	const eq = part.indexOf('=');
	if (eq === -1) return `<span style="flex:1;text-align:center;color:var(--t2)">${escHtml(part)}</span>`;
	const key = part.slice(0, eq).trim();
	const val = part.slice(eq + 1).trim();
	const sep = i < parts.length - 1
	? `<span style="width:1px;background:rgba(255,255,255,0.07);align-self:stretch;flex-shrink:0;margin:6px 0"></span>`
	: '';
	return `<span style="flex:1;display:flex;flex-direction:column;align-items:center;justify-content:center;gap:2px;padding:3px 8px">` +
	`<span style="color:var(--t3);font-size:0.58rem;letter-spacing:0.14em;text-transform:uppercase">${escHtml(key)}</span>` +
	`<span style="color:var(--t0);font-weight:700;font-size:0.82rem;font-variant-numeric:tabular-nums">${escHtml(val)}</span>` +
	`</span>${sep}`;
	}).join('');
	}

	// Format a log entry into a coloured terminal line
	function formatLogLine(entry) {
	const ts = (entry.timestamp \|\| '').slice(11, 19); // HH:MM:SS
	const cat = (entry.category \|\| '').toUpperCase();
	const lvl = (entry.level \|\| '').toUpperCase();

	// Prefer structured message; strip raw-line boilerplate if the API returns the full line
	let msg = entry.message \|\| '';
	// Strip leading "[YYYY-MM-DD HH:MM:SS] \| LEVEL \| CATEGORY \| " prefix (raw line format)
	msg = msg.replace(/^\[\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}\]\s\\|\s\w+\s\\|\s\w+\s\\|\s/, '');
	// Strip trailing JSON blob — already structured in entry.data
	msg = msg.replace(/\s\{.\}\s*$/, '');
	msg = msg.trim();

	let lineClass = 'tlog-info';
	if (lvl === 'DEBUG') lineClass = 'tlog-debug';
	else if (lvl === 'ERROR' \|\| lvl === 'CRITICAL') lineClass = 'tlog-error';
	else if (lvl === 'WARNING') lineClass = 'tlog-warn';
	else if (cat === 'SIGNAL') lineClass = 'tlog-signal';
	else if (cat === 'TRADE') lineClass = 'tlog-trade';
	else if (cat === 'TRAINING') lineClass = 'tlog-debug';

	const catBg = 'rgba(255,255,255,0.06)';
	const catCol = 'var(--t0)';

	const catLabel = cat \|\| lvl;
	const rendered = renderKVPairs(msg);

	return `<div class="${lineClass}" style="display:flex;align-items:stretch;gap:0;padding:6px 24px;border-bottom:1px solid rgba(255,255,255,0.04);transition:background 0.15s ease" onmouseover="this.style.background='rgba(255,255,255,0.025)'" onmouseout="this.style.background=''">`+
	`<span class="tlog-ts" style="flex-shrink:0;width:70px;font-size:0.68rem;opacity:0.5;font-variant-numeric:tabular-nums;display:flex;align-items:center">${ts}</span>`+
	`<span style="flex-shrink:0;margin-right:20px;padding:2px 8px;border-radius:4px;background:${catBg};color:${catCol};font-size:0.58rem;font-weight:800;letter-spacing:0.12em;text-transform:uppercase;display:flex;align-items:center">${escHtml(catLabel)}</span>`+
	`<span style="flex:1;min-width:0;display:flex;align-items:stretch;flex-wrap:nowrap">${rendered}</span>`+
	`</div>`;
	}

	function escHtml(s) {
	return String(s).replace(/&/g,'&').replace(/</g,'<').replace(/>/g,'>');
	}

	function _appendTrainingLines(entries) {
	const term = document.getElementById('training-log-terminal');
	if (!term) return;

	// Append only NEW entries (filter by timestamp > _lastLogTs)
	const newEntries = _lastLogTs
	? entries.filter(e => (e.timestamp \|\| '') > _lastLogTs)
	: entries;

	if (!newEntries.length) return;

	_lastLogTs = newEntries[newEntries.length - 1].timestamp \|\| _lastLogTs;

	newEntries.forEach(e => _termLines.push(formatLogLine(e)));
	if (_termLines.length > MAX_LINES) _termLines = _termLines.slice(-MAX_LINES);

	const atBottom = term.scrollHeight - term.clientHeight - term.scrollTop < 60;
	term.innerHTML = _termLines.join('');
	if (atBottom) term.scrollTop = term.scrollHeight;
	}

	// Regex to extract training fields directly from the raw message string.
	// Matches the format produced by ranker_logging.py training_update():
	// "step=14 \| loss=0.0278 \| lr=0.000300 \| assets=4"
	// Also matches the full pipe-delimited log line (the API returns the raw line as "message").
	const _TRAINING_MSG_RE = /step=(\d+).?loss=([\d.]+).?lr=([\d.eE+\-]+).*?assets=(\d+)/;

	function _extractTrainingData(entry) {
	// Priority 1: structured "data" field from the enriched API endpoint
	if (entry.data && typeof entry.data === 'object' && entry.data.step != null) {
	return entry.data;
	}
	// Priority 2: JSON blob embedded in "metadata" (RankerLogger.to_dict())
	if (entry.metadata && entry.metadata.step != null) {
	return entry.metadata;
	}
	// Priority 3: Regex over the raw message / log line string
	const m = _TRAINING_MSG_RE.exec(entry.message \|\| '');
	if (m) {
	return {
	step: parseInt(m[1], 10),
	loss: parseFloat(m[2]),
	lr: parseFloat(m[3]),
	asset_count: parseInt(m[4], 10),
	};
	}
	return null;
	}

	function updateTrainingKPIs(entries) {
	// Accept entries whose category field OR raw message text indicate TRAINING
	const trainEntries = entries
	.filter(e => {
	const cat = (e.category \|\| '').toUpperCase();
	const msg = (e.message \|\| '').toUpperCase();
	return cat === 'TRAINING' \|\| msg.includes('\| TRAINING ');
	})
	.map(e => ({ entry: e, data: _extractTrainingData(e) }))
	.filter(x => x.data !== null)
	.sort((a, b) => (a.entry.timestamp \|\| '') < (b.entry.timestamp \|\| '') ? -1 : 1);

	if (!trainEntries.length) return;

	const { entry: latest, data: d } = trainEntries[trainEntries.length - 1];

	// Loss
	const lossEl = document.getElementById('trn-loss');
	const lossTrendEl = document.getElementById('trn-loss-trend');
	if (lossEl && d.loss != null) {
	const v = parseFloat(d.loss);
	lossEl.textContent = v.toFixed(4);
	if (lossTrendEl && _prevLoss != null) {
	const delta = v - _prevLoss;
	lossTrendEl.textContent = (delta < 0 ? '▼ ' : '▲ ') + Math.abs(delta).toFixed(4);
	lossTrendEl.style.color = delta < 0 ? 'var(--green)' : 'var(--red)';
	}
	_prevLoss = v;
	}

	// Learning rate — display as fixed 6dp (matches log format) or sci notation if tiny
	const lrEl = document.getElementById('trn-lr');
	if (lrEl && d.lr != null) {
	const lr = parseFloat(d.lr);
	lrEl.textContent = lr < 0.001 ? lr.toExponential(3) : lr.toFixed(6);
	}

	// Step
	const stepEl = document.getElementById('trn-step');
	const stepSubEl = document.getElementById('trn-step-sub');
	if (stepEl && d.step != null) {
	stepEl.textContent = parseInt(d.step).toLocaleString();
	if (stepSubEl) stepSubEl.textContent = 'gradient updates';
	}

	// Assets
	const assetsEl = document.getElementById('trn-assets');
	if (assetsEl) {
	const n = d.asset_count ?? d.assets ?? null;
	if (n != null) assetsEl.textContent = n;
	}

	// Header meta timestamp
	const metaEl = document.getElementById('training-meta');
	if (metaEl && latest.timestamp) {
	metaEl.textContent = 'last update ' + (latest.timestamp \|\| '').slice(11, 19);
	}
	}

	async function pollTrainingLogs() {
	try {
	const res = await fetch('/api/ranker/logs/recent?limit=80&category=TRAINING');
	// v2.3: always parse JSON even on non-2xx; service now always returns JSON
	let json;
	try {
	json = await res.json();
	} catch (parseErr) {
	// Response was not JSON (e.g. HTML error page from a proxy)
	throw new Error('HTTP ' + res.status + ' — non-JSON response from /api/ranker/logs/recent');
	}
	if (!res.ok) {
	// Service returned an error object — show it but don't abort
	const errMsg = json.error \|\| ('HTTP ' + res.status);
	const term = document.getElementById('training-log-terminal');
	if (term && !_termLines.length) {
	term.innerHTML = '<div class="tlog-error" style="font-size:11px">⚠ ' + escHtml(errMsg) + '</div>';
	}
	return;
	}
	const entries = json.logs \|\| [];
	_appendTrainingLines(entries);
	updateTrainingKPIs(entries);
	} catch(err) {
	// Silently tolerate transient connection errors — show detail on first failure
	const term = document.getElementById('training-log-terminal');
	if (term && !_termLines.length) {
	term.innerHTML = '<div class="tlog-error" style="font-size:11px">⚠ ' + escHtml(err.message) + '</div>';
	}
	}
	}

	// Init: first poll immediately, then repeat
	pollTrainingLogs();
	setInterval(pollTrainingLogs, POLL_MS);
	})();

	</script>
	</body>
	</html>